From 588cce7e7e7b280f6f93b401a46626db83ba0799 Mon Sep 17 00:00:00 2001 From: alxvov Date: Thu, 27 Jun 2019 09:30:10 +0000 Subject: [PATCH 001/192] add min_spin_oso (just a copy of min_spin) --- src/min_spin_oso.cpp | 333 +++++++++++++++++++++++++++++++++++++++++++ src/min_spin_oso.h | 59 ++++++++ 2 files changed, 392 insertions(+) create mode 100644 src/min_spin_oso.cpp create mode 100644 src/min_spin_oso.h diff --git a/src/min_spin_oso.cpp b/src/min_spin_oso.cpp new file mode 100644 index 0000000000..a97d7b40a1 --- /dev/null +++ b/src/min_spin_oso.cpp @@ -0,0 +1,333 @@ +/* ---------------------------------------------------------------------- + LAMMPS - Large-scale Atomic/Molecular Massively Parallel Simulator + http://lammps.sandia.gov, Sandia National Laboratories + Steve Plimpton, sjplimp@sandia.gov + + Copyright (2003) Sandia Corporation. Under the terms of Contract + DE-AC04-94AL85000 with Sandia Corporation, the U.S. Government retains + certain rights in this software. This software is distributed under + the GNU General Public License. + + See the README file in the top-level LAMMPS directory. +------------------------------------------------------------------------- */ + +/* ------------------------------------------------------------------------ + Contributing authors: Julien Tranchida (SNL) + + Please cite the related publication: +------------------------------------------------------------------------- */ + +#include +#include +#include +#include +#include "min_spin_oso.h" +#include "universe.h" +#include "atom.h" +#include "force.h" +#include "update.h" +#include "output.h" +#include "timer.h" +#include "error.h" +#include "modify.h" +#include "math_special.h" +#include "math_const.h" + +using namespace LAMMPS_NS; +using namespace MathConst; + +// EPS_ENERGY = minimum normalization for energy tolerance + +#define EPS_ENERGY 1.0e-8 + +#define DELAYSTEP 5 + +/* ---------------------------------------------------------------------- */ + +MinSpinOSO::MinSpinOSO(LAMMPS *lmp) : Min(lmp) {} + +/* ---------------------------------------------------------------------- */ + +void MinSpinOSO::init() +{ + alpha_damp = 1.0; + discrete_factor = 10.0; + + Min::init(); + + dts = dt = update->dt; + last_negative = update->ntimestep; +} + +/* ---------------------------------------------------------------------- */ + +void MinSpinOSO::setup_style() +{ + double **v = atom->v; + int nlocal = atom->nlocal; + + // check if the atom/spin style is defined + + if (!atom->sp_flag) + error->all(FLERR,"min/spin_oso requires atom/spin style"); + + for (int i = 0; i < nlocal; i++) + v[i][0] = v[i][1] = v[i][2] = 0.0; +} + +/* ---------------------------------------------------------------------- */ + +int MinSpinOSO::modify_param(int narg, char **arg) +{ + if (strcmp(arg[0],"alpha_damp") == 0) { + if (narg < 2) error->all(FLERR,"Illegal fix_modify command"); + alpha_damp = force->numeric(FLERR,arg[1]); + return 2; + } + if (strcmp(arg[0],"discrete_factor") == 0) { + if (narg < 2) error->all(FLERR,"Illegal fix_modify command"); + discrete_factor = force->numeric(FLERR,arg[1]); + return 2; + } + return 0; +} + +/* ---------------------------------------------------------------------- + set current vector lengths and pointers + called after atoms have migrated +------------------------------------------------------------------------- */ + +void MinSpinOSO::reset_vectors() +{ + // atomic dof + + // size sp is 4N vector + nvec = 4 * atom->nlocal; + if (nvec) spvec = atom->sp[0]; + + nvec = 3 * atom->nlocal; + if (nvec) fmvec = atom->fm[0]; + + if (nvec) xvec = atom->x[0]; + if (nvec) fvec = atom->f[0]; +} + +/* ---------------------------------------------------------------------- + minimization via damped spin dynamics +------------------------------------------------------------------------- */ + +int MinSpinOSO::iterate(int maxiter) +{ + bigint ntimestep; + double fmdotfm; + int flag, flagall; + + for (int iter = 0; iter < maxiter; iter++) { + + if (timer->check_timeout(niter)) + return TIMEOUT; + + ntimestep = ++update->ntimestep; + niter++; + + // optimize timestep accross processes / replicas + // need a force calculation for timestep optimization + + energy_force(0); + dts = evaluate_dt(); + + // apply damped precessional dynamics to the spins + + advance_spins(dts); + + eprevious = ecurrent; + ecurrent = energy_force(0); + neval++; + + //// energy tolerance criterion + //// only check after DELAYSTEP elapsed since velocties reset to 0 + //// sync across replicas if running multi-replica minimization + + if (update->etol > 0.0 && ntimestep-last_negative > DELAYSTEP) { + if (update->multireplica == 0) { + if (fabs(ecurrent-eprevious) < + update->etol * 0.5*(fabs(ecurrent) + fabs(eprevious) + EPS_ENERGY)) + return ETOL; + } else { + if (fabs(ecurrent-eprevious) < + update->etol * 0.5*(fabs(ecurrent) + fabs(eprevious) + EPS_ENERGY)) + flag = 0; + else flag = 1; + MPI_Allreduce(&flag,&flagall,1,MPI_INT,MPI_SUM,universe->uworld); + if (flagall == 0) return ETOL; + } + } + + // magnetic torque tolerance criterion + // sync across replicas if running multi-replica minimization + + if (update->ftol > 0.0) { + fmdotfm = fmnorm_sqr(); + if (update->multireplica == 0) { + if (fmdotfm < update->ftol*update->ftol) return FTOL; + } else { + if (fmdotfm < update->ftol*update->ftol) flag = 0; + else flag = 1; + MPI_Allreduce(&flag,&flagall,1,MPI_INT,MPI_SUM,universe->uworld); + if (flagall == 0) return FTOL; + } + } + + // output for thermo, dump, restart files + + if (output->next == ntimestep) { + timer->stamp(); + output->write(ntimestep); + timer->stamp(Timer::OUTPUT); + } + } + + return MAXITER; +} + +/* ---------------------------------------------------------------------- + evaluate max timestep +---------------------------------------------------------------------- */ + +double MinSpinOSO::evaluate_dt() +{ + double dtmax; + double fmsq; + double fmaxsqone,fmaxsqloc,fmaxsqall; + int nlocal = atom->nlocal; + double **fm = atom->fm; + + // finding max fm on this proc. + + fmsq = fmaxsqone = fmaxsqloc = fmaxsqall = 0.0; + for (int i = 0; i < nlocal; i++) { + fmsq = fm[i][0]*fm[i][0]+fm[i][1]*fm[i][1]+fm[i][2]*fm[i][2]; + fmaxsqone = MAX(fmaxsqone,fmsq); + } + + // finding max fm on this replica + + fmaxsqloc = fmaxsqone; + MPI_Allreduce(&fmaxsqone,&fmaxsqloc,1,MPI_DOUBLE,MPI_MAX,world); + + // finding max fm over all replicas, if necessary + // this communicator would be invalid for multiprocess replicas + + fmaxsqall = fmaxsqloc; + if (update->multireplica == 1) { + fmaxsqall = fmaxsqloc; + MPI_Allreduce(&fmaxsqloc,&fmaxsqall,1,MPI_DOUBLE,MPI_MAX,universe->uworld); + } + + if (fmaxsqall == 0.0) + error->all(FLERR,"Incorrect fmaxsqall calculation"); + + // define max timestep by dividing by the + // inverse of max frequency by discrete_factor + + dtmax = MY_2PI/(discrete_factor*sqrt(fmaxsqall)); + + return dtmax; +} + +/* ---------------------------------------------------------------------- + geometric damped advance of spins +---------------------------------------------------------------------- */ + +void MinSpinOSO::advance_spins(double dts) +{ + int nlocal = atom->nlocal; + double **sp = atom->sp; + double **fm = atom->fm; + double tdampx,tdampy,tdampz; + double msq, scale, fm2, energy, dts2; + double cp[3], g[3]; + + dts2 = dts*dts; + + // loop on all spins on proc. + + for (int i = 0; i < nlocal; i++) { + + // calc. damping torque + + tdampx = -alpha_damp*(fm[i][1]*sp[i][2] - fm[i][2]*sp[i][1]); + tdampy = -alpha_damp*(fm[i][2]*sp[i][0] - fm[i][0]*sp[i][2]); + tdampz = -alpha_damp*(fm[i][0]*sp[i][1] - fm[i][1]*sp[i][0]); + + // apply advance algorithm (geometric, norm preserving) + + fm2 = (tdampx*tdampx+tdampy*tdampy+tdampz*tdampz); + energy = (sp[i][0]*tdampx)+(sp[i][1]*tdampy)+(sp[i][2]*tdampz); + + cp[0] = tdampy*sp[i][2]-tdampz*sp[i][1]; + cp[1] = tdampz*sp[i][0]-tdampx*sp[i][2]; + cp[2] = tdampx*sp[i][1]-tdampy*sp[i][0]; + + g[0] = sp[i][0]+cp[0]*dts; + g[1] = sp[i][1]+cp[1]*dts; + g[2] = sp[i][2]+cp[2]*dts; + + g[0] += (tdampx*energy-0.5*sp[i][0]*fm2)*0.5*dts2; + g[1] += (tdampy*energy-0.5*sp[i][1]*fm2)*0.5*dts2; + g[2] += (tdampz*energy-0.5*sp[i][2]*fm2)*0.5*dts2; + + g[0] /= (1+0.25*fm2*dts2); + g[1] /= (1+0.25*fm2*dts2); + g[2] /= (1+0.25*fm2*dts2); + + sp[i][0] = g[0]; + sp[i][1] = g[1]; + sp[i][2] = g[2]; + + // renormalization (check if necessary) + + msq = g[0]*g[0] + g[1]*g[1] + g[2]*g[2]; + scale = 1.0/sqrt(msq); + sp[i][0] *= scale; + sp[i][1] *= scale; + sp[i][2] *= scale; + + // no comm. to atoms with same tag + // because no need for simplecticity + } +} + +/* ---------------------------------------------------------------------- + compute and return ||mag. torque||_2^2 +------------------------------------------------------------------------- */ + +double MinSpinOSO::fmnorm_sqr() +{ + int nlocal = atom->nlocal; + double tx,ty,tz; + double **sp = atom->sp; + double **fm = atom->fm; + + // calc. magnetic torques + + double local_norm2_sqr = 0.0; + for (int i = 0; i < nlocal; i++) { + tx = (fm[i][1]*sp[i][2] - fm[i][2]*sp[i][1]); + ty = (fm[i][2]*sp[i][0] - fm[i][0]*sp[i][2]); + tz = (fm[i][0]*sp[i][1] - fm[i][1]*sp[i][0]); + + local_norm2_sqr += tx*tx + ty*ty + tz*tz; + } + + // no extra atom calc. for spins + + if (nextra_atom) + error->all(FLERR,"extra atom option not available yet"); + + double norm2_sqr = 0.0; + MPI_Allreduce(&local_norm2_sqr,&norm2_sqr,1,MPI_DOUBLE,MPI_SUM,world); + + return norm2_sqr; +} + diff --git a/src/min_spin_oso.h b/src/min_spin_oso.h new file mode 100644 index 0000000000..81ad812e5c --- /dev/null +++ b/src/min_spin_oso.h @@ -0,0 +1,59 @@ +/* -*- c++ -*- ---------------------------------------------------------- + LAMMPS - Large-scale Atomic/Molecular Massively Parallel Simulator + http://lammps.sandia.gov, Sandia National Laboratories + Steve Plimpton, sjplimp@sandia.gov + + Copyright (2003) Sandia Corporation. Under the terms of Contract + DE-AC04-94AL85000 with Sandia Corporation, the U.S. Government retains + certain rights in this software. This software is distributed under + the GNU General Public License. + + See the README file in the top-level LAMMPS directory. +------------------------------------------------------------------------- */ + +#ifdef MINIMIZE_CLASS + +MinimizeStyle(spin_oso, MinSpinOSO) + +#else + +#ifndef LMP_MIN_SPIN_OSO_H +#define LMP_MIN_SPIN_OSO_H + +#include "min.h" + +namespace LAMMPS_NS { + +class MinSpinOSO : public Min { + public: + MinSpinOSO(class LAMMPS *); //? + ~MinSpinOSO() {} //? + void init(); + void setup_style(); + int modify_param(int, char **); + void reset_vectors(); + int iterate(int); + double evaluate_dt(); + void advance_spins(double); + double fmnorm_sqr(); + + private: + + // global and spin timesteps + + double dt; + double dts; + + double alpha_damp; // damping for spin minimization + double discrete_factor; // factor for spin timestep evaluation + + double *spvec; // variables for atomic dof, as 1d vector + double *fmvec; // variables for atomic dof, as 1d vector + + bigint last_negative; +}; + +} + +#endif +#endif From 1eb83136c4a86ad8d65e1d46284d8dc69a4a7858 Mon Sep 17 00:00:00 2001 From: alxvov Date: Thu, 27 Jun 2019 10:59:15 +0000 Subject: [PATCH 002/192] add gradient descent with rotation matrices with adaptive time step (as before) --- src/min_spin_oso.cpp | 149 ++++++++++++++++++++++++++++++------------- 1 file changed, 105 insertions(+), 44 deletions(-) diff --git a/src/min_spin_oso.cpp b/src/min_spin_oso.cpp index a97d7b40a1..c20096ae1c 100644 --- a/src/min_spin_oso.cpp +++ b/src/min_spin_oso.cpp @@ -42,6 +42,9 @@ using namespace MathConst; #define DELAYSTEP 5 +void vm3(const double *m, const double *v, double *out); +void rodrigues_rotation(const double *upp_tr, double *out); + /* ---------------------------------------------------------------------- */ MinSpinOSO::MinSpinOSO(LAMMPS *lmp) : Min(lmp) {} @@ -244,58 +247,33 @@ void MinSpinOSO::advance_spins(double dts) int nlocal = atom->nlocal; double **sp = atom->sp; double **fm = atom->fm; - double tdampx,tdampy,tdampz; - double msq, scale, fm2, energy, dts2; - double cp[3], g[3]; - - dts2 = dts*dts; + double tdampx, tdampy, tdampz; + double f[3]; // upper triag. part of skew-symm. matr. to be exponented + double rot_mat[9]; // exponential of a + double s_new[3]; // loop on all spins on proc. for (int i = 0; i < nlocal; i++) { - // calc. damping torque + // calc. damping torque + tdampx = -alpha_damp*(fm[i][1]*sp[i][2] - fm[i][2]*sp[i][1]); + tdampy = -alpha_damp*(fm[i][2]*sp[i][0] - fm[i][0]*sp[i][2]); + tdampz = -alpha_damp*(fm[i][0]*sp[i][1] - fm[i][1]*sp[i][0]); - tdampx = -alpha_damp*(fm[i][1]*sp[i][2] - fm[i][2]*sp[i][1]); - tdampy = -alpha_damp*(fm[i][2]*sp[i][0] - fm[i][0]*sp[i][2]); - tdampz = -alpha_damp*(fm[i][0]*sp[i][1] - fm[i][1]*sp[i][0]); + // calculate rotation matrix + f[0] = tdampz * dts; + f[1] = -tdampy * dts; + f[2] = tdampx * dts; + rodrigues_rotation(f, rot_mat); - // apply advance algorithm (geometric, norm preserving) - - fm2 = (tdampx*tdampx+tdampy*tdampy+tdampz*tdampz); - energy = (sp[i][0]*tdampx)+(sp[i][1]*tdampy)+(sp[i][2]*tdampz); - - cp[0] = tdampy*sp[i][2]-tdampz*sp[i][1]; - cp[1] = tdampz*sp[i][0]-tdampx*sp[i][2]; - cp[2] = tdampx*sp[i][1]-tdampy*sp[i][0]; - - g[0] = sp[i][0]+cp[0]*dts; - g[1] = sp[i][1]+cp[1]*dts; - g[2] = sp[i][2]+cp[2]*dts; - - g[0] += (tdampx*energy-0.5*sp[i][0]*fm2)*0.5*dts2; - g[1] += (tdampy*energy-0.5*sp[i][1]*fm2)*0.5*dts2; - g[2] += (tdampz*energy-0.5*sp[i][2]*fm2)*0.5*dts2; - - g[0] /= (1+0.25*fm2*dts2); - g[1] /= (1+0.25*fm2*dts2); - g[2] /= (1+0.25*fm2*dts2); - - sp[i][0] = g[0]; - sp[i][1] = g[1]; - sp[i][2] = g[2]; - - // renormalization (check if necessary) - - msq = g[0]*g[0] + g[1]*g[1] + g[2]*g[2]; - scale = 1.0/sqrt(msq); - sp[i][0] *= scale; - sp[i][1] *= scale; - sp[i][2] *= scale; - - // no comm. to atoms with same tag - // because no need for simplecticity + // rotate spins + vm3(rot_mat, sp[i], s_new); + sp[i][0] = s_new[0]; + sp[i][1] = s_new[1]; + sp[i][2] = s_new[2]; } + } /* ---------------------------------------------------------------------- @@ -331,3 +309,86 @@ double MinSpinOSO::fmnorm_sqr() return norm2_sqr; } + +void rodrigues_rotation(const double *upp_tr, double *out){ + + /*** + * calculate 3x3 matrix exponential using Rodrigues' formula + * (R. Murray, Z. Li, and S. Shankar Sastry, + * A Mathematical Introduction to + * Robotic Manipulation (1994), p. 28 and 30). + * + * upp_tr - vector x, y, z so that one calculate + * U = exp(A) with A= [[0, x, y], + * [-x, 0, z], + * [-y, -z, 0]] + ***/ + + + if (fabs(upp_tr[0]) < 1.0e-40 && + fabs(upp_tr[1]) < 1.0e-40 && + fabs(upp_tr[2]) < 1.0e-40){ + // if upp_tr is zero, return unity matrix + int k; + int m; + for(k = 0; k < 3; k++){ + for(m = 0; m < 3; m++){ + if (m == k) out[3 * k + m] = 1.0; + else out[3 * k + m] = 0.0; + } + } + return; + } + + double theta = sqrt(upp_tr[0] * upp_tr[0] + + upp_tr[1] * upp_tr[1] + + upp_tr[2] * upp_tr[2]); + + double A = cos(theta); + double B = sin(theta); + double D = 1 - A; + double x = upp_tr[0]/theta; + double y = upp_tr[1]/theta; + double z = upp_tr[2]/theta; + + // diagonal elements of U + out[0] = A + z * z * D; + out[4] = A + y * y * D; + out[8] = A + x * x * D; + + // off diagonal of U + double s1 = -y * z *D; + double s2 = x * z * D; + double s3 = -x * y * D; + + double a1 = x * B; + double a2 = y * B; + double a3 = z * B; + + out[1] = s1 + a1; + out[3] = s1 - a1; + out[2] = s2 + a2; + out[6] = s2 - a2; + out[5] = s3 + a3; + out[7] = s3 - a3; + +} + + +void vm3(const double *m, const double *v, double *out){ + /*** + * out = vector^T x m, + * m -- 3x3 matrix , v -- 3-d vector + ***/ + + int i; + int j; + + for(i = 0; i < 3; i++){ + out[i] *= 0.0; + for(j = 0; j < 3; j++){ + out[i] += *(m + 3 * j + i) * v[j]; + } + } + +} From f7ddf433ef03dc94fcf5e5e50a3d61018abe8e06 Mon Sep 17 00:00:00 2001 From: alxvov Date: Thu, 27 Jun 2019 13:14:27 +0000 Subject: [PATCH 003/192] modify comment --- src/min_spin_oso.cpp | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/min_spin_oso.cpp b/src/min_spin_oso.cpp index c20096ae1c..d26a7ffc39 100644 --- a/src/min_spin_oso.cpp +++ b/src/min_spin_oso.cpp @@ -239,7 +239,7 @@ double MinSpinOSO::evaluate_dt() } /* ---------------------------------------------------------------------- - geometric damped advance of spins + rotation of spins along the search direction ---------------------------------------------------------------------- */ void MinSpinOSO::advance_spins(double dts) From 589d0e2a6a53c760937b2b9b19c28f41c90db341 Mon Sep 17 00:00:00 2001 From: alxvov Date: Thu, 27 Jun 2019 16:26:24 +0000 Subject: [PATCH 004/192] add conjugate gradients with OSO --- .../min_spin_oso_cg.cpp} | 148 +++++++++++++----- src/SPIN/min_spin_oso_cg.h | 65 ++++++++ src/min_spin_oso.h | 59 ------- 3 files changed, 177 insertions(+), 95 deletions(-) rename src/{min_spin_oso.cpp => SPIN/min_spin_oso_cg.cpp} (72%) create mode 100644 src/SPIN/min_spin_oso_cg.h delete mode 100644 src/min_spin_oso.h diff --git a/src/min_spin_oso.cpp b/src/SPIN/min_spin_oso_cg.cpp similarity index 72% rename from src/min_spin_oso.cpp rename to src/SPIN/min_spin_oso_cg.cpp index d26a7ffc39..9f43442e27 100644 --- a/src/min_spin_oso.cpp +++ b/src/SPIN/min_spin_oso_cg.cpp @@ -21,7 +21,7 @@ #include #include #include -#include "min_spin_oso.h" +#include "min_spin_oso_cg.h" #include "universe.h" #include "atom.h" #include "force.h" @@ -47,24 +47,24 @@ void rodrigues_rotation(const double *upp_tr, double *out); /* ---------------------------------------------------------------------- */ -MinSpinOSO::MinSpinOSO(LAMMPS *lmp) : Min(lmp) {} +MinSpinOSO_CG::MinSpinOSO_CG(LAMMPS *lmp) : Min(lmp) {} /* ---------------------------------------------------------------------- */ -void MinSpinOSO::init() +void MinSpinOSO_CG::init() { - alpha_damp = 1.0; - discrete_factor = 10.0; + alpha_damp = 1.0; + discrete_factor = 10.0; - Min::init(); + Min::init(); - dts = dt = update->dt; - last_negative = update->ntimestep; + dts = dt = update->dt; + last_negative = update->ntimestep; } /* ---------------------------------------------------------------------- */ -void MinSpinOSO::setup_style() +void MinSpinOSO_CG::setup_style() { double **v = atom->v; int nlocal = atom->nlocal; @@ -72,7 +72,7 @@ void MinSpinOSO::setup_style() // check if the atom/spin style is defined if (!atom->sp_flag) - error->all(FLERR,"min/spin_oso requires atom/spin style"); + error->all(FLERR,"min/spin_oso_cg requires atom/spin style"); for (int i = 0; i < nlocal; i++) v[i][0] = v[i][1] = v[i][2] = 0.0; @@ -80,7 +80,7 @@ void MinSpinOSO::setup_style() /* ---------------------------------------------------------------------- */ -int MinSpinOSO::modify_param(int narg, char **arg) +int MinSpinOSO_CG::modify_param(int narg, char **arg) { if (strcmp(arg[0],"alpha_damp") == 0) { if (narg < 2) error->all(FLERR,"Illegal fix_modify command"); @@ -100,7 +100,7 @@ int MinSpinOSO::modify_param(int narg, char **arg) called after atoms have migrated ------------------------------------------------------------------------- */ -void MinSpinOSO::reset_vectors() +void MinSpinOSO_CG::reset_vectors() { // atomic dof @@ -119,13 +119,19 @@ void MinSpinOSO::reset_vectors() minimization via damped spin dynamics ------------------------------------------------------------------------- */ -int MinSpinOSO::iterate(int maxiter) +int MinSpinOSO_CG::iterate(int maxiter) { - bigint ntimestep; - double fmdotfm; - int flag, flagall; + bigint ntimestep; + double fmdotfm; + int flag, flagall; - for (int iter = 0; iter < maxiter; iter++) { + // not sure it is best place to allocate memory + int nlocal = atom->nlocal; + g = (double *) calloc(3*nlocal, sizeof(double)); + p = (double *) calloc(3*nlocal, sizeof(double)); + g_old = (double *) calloc(3*nlocal, sizeof(double)); + + for (int iter = 0; iter < maxiter; iter++) { if (timer->check_timeout(niter)) return TIMEOUT; @@ -139,9 +145,9 @@ int MinSpinOSO::iterate(int maxiter) energy_force(0); dts = evaluate_dt(); - // apply damped precessional dynamics to the spins - - advance_spins(dts); + calc_gradients(dts); + calc_search_direction(iter); + advance_spins(); eprevious = ecurrent; ecurrent = energy_force(0); @@ -190,6 +196,10 @@ int MinSpinOSO::iterate(int maxiter) } } + free(p); + free(g); + free(g_old); + return MAXITER; } @@ -197,7 +207,7 @@ int MinSpinOSO::iterate(int maxiter) evaluate max timestep ---------------------------------------------------------------------- */ -double MinSpinOSO::evaluate_dt() +double MinSpinOSO_CG::evaluate_dt() { double dtmax; double fmsq; @@ -238,35 +248,101 @@ double MinSpinOSO::evaluate_dt() return dtmax; } +/* ---------------------------------------------------------------------- + calculate gradients +---------------------------------------------------------------------- */ + +void MinSpinOSO_CG::calc_gradients(double dts) +{ + int nlocal = atom->nlocal; + double **sp = atom->sp; + double **fm = atom->fm; + double tdampx, tdampy, tdampz; + // loop on all spins on proc. + + for (int i = 0; i < nlocal; i++) { + + // calc. damping torque + tdampx = -alpha_damp*(fm[i][1]*sp[i][2] - fm[i][2]*sp[i][1]); + tdampy = -alpha_damp*(fm[i][2]*sp[i][0] - fm[i][0]*sp[i][2]); + tdampz = -alpha_damp*(fm[i][0]*sp[i][1] - fm[i][1]*sp[i][0]); + + // calculate rotation matrix + g[3 * i + 0] = -tdampz * dts; + g[3 * i + 1] = tdampy * dts; + g[3 * i + 2] = -tdampx * dts; + } +} + +void MinSpinOSO_CG::calc_search_direction(int iter) +{ + int nlocal = atom->nlocal; + double g2old = 0.0; + double g2 = 0.0; + double beta = 0.0; + + double g2_global= 0.0; + double g2old_global= 0.0; + + // for some reason on a second iteration g_old = 0 + // so we make to iterations as steepest descent + if (iter <= 2 || iter % 5 == 0){ + // steepest descent direction + for (int i = 0; i < nlocal; i++) { + for (int j = 0; j < 3; j++){ + p[3 * i + j] = -g[3 * i + j]; + g_old[3 * i + j] = g[3 * i + j]; + } + } + } else{ + // conjugate direction + for (int i = 0; i < nlocal; i++) { + for (int j = 0; j < 3; j++){ + g2old += g_old[3 * i + j] * g_old[3 * i + j]; + g2 += g[3 * i + j] * g[3 * i + j]; + + } + } + + // now we need to collect/broadcast beta on this replica + // different replica can have different beta for now. + // need to check what is beta for GNEB + MPI_Allreduce(&g2, &g2_global, 1, MPI_DOUBLE, MPI_SUM, world); + MPI_Allreduce(&g2old, &g2old_global, 1, MPI_DOUBLE, MPI_SUM, world); + + beta = g2_global / g2old_global; + + //calculate conjugate direction + for (int i = 0; i < nlocal; i++) { + for (int j = 0; j < 3; j++){ + p[3 * i + j] = beta * p[3 * i + j] - g[3 * i + j]; + g_old[3 * i + j] = g[3 * i + j]; + } + } + + } + +} + + /* ---------------------------------------------------------------------- rotation of spins along the search direction ---------------------------------------------------------------------- */ -void MinSpinOSO::advance_spins(double dts) +void MinSpinOSO_CG::advance_spins() { int nlocal = atom->nlocal; double **sp = atom->sp; double **fm = atom->fm; double tdampx, tdampy, tdampz; - double f[3]; // upper triag. part of skew-symm. matr. to be exponented + // double f[3]; // upper triag. part of skew-symm. matr. to be exponented double rot_mat[9]; // exponential of a double s_new[3]; // loop on all spins on proc. for (int i = 0; i < nlocal; i++) { - - // calc. damping torque - tdampx = -alpha_damp*(fm[i][1]*sp[i][2] - fm[i][2]*sp[i][1]); - tdampy = -alpha_damp*(fm[i][2]*sp[i][0] - fm[i][0]*sp[i][2]); - tdampz = -alpha_damp*(fm[i][0]*sp[i][1] - fm[i][1]*sp[i][0]); - - // calculate rotation matrix - f[0] = tdampz * dts; - f[1] = -tdampy * dts; - f[2] = tdampx * dts; - rodrigues_rotation(f, rot_mat); - + rodrigues_rotation(p + 3 * i, rot_mat); // rotate spins vm3(rot_mat, sp[i], s_new); sp[i][0] = s_new[0]; @@ -280,7 +356,7 @@ void MinSpinOSO::advance_spins(double dts) compute and return ||mag. torque||_2^2 ------------------------------------------------------------------------- */ -double MinSpinOSO::fmnorm_sqr() +double MinSpinOSO_CG::fmnorm_sqr() { int nlocal = atom->nlocal; double tx,ty,tz; diff --git a/src/SPIN/min_spin_oso_cg.h b/src/SPIN/min_spin_oso_cg.h new file mode 100644 index 0000000000..fa0b591c21 --- /dev/null +++ b/src/SPIN/min_spin_oso_cg.h @@ -0,0 +1,65 @@ +/* -*- c++ -*- ---------------------------------------------------------- + LAMMPS - Large-scale Atomic/Molecular Massively Parallel Simulator + http://lammps.sandia.gov, Sandia National Laboratories + Steve Plimpton, sjplimp@sandia.gov + + Copyright (2003) Sandia Corporation. Under the terms of Contract + DE-AC04-94AL85000 with Sandia Corporation, the U.S. Government retains + certain rights in this software. This software is distributed under + the GNU General Public License. + + See the README file in the top-level LAMMPS directory. +------------------------------------------------------------------------- */ + +#ifdef MINIMIZE_CLASS + +MinimizeStyle(spin_oso_cg, MinSpinOSO_CG) + +#else + +#ifndef LMP_MIN_SPIN_OSO_CG_H +#define LMP_MIN_SPIN_OSO_CG_H + +#include "min.h" + +namespace LAMMPS_NS { + +class MinSpinOSO_CG : public Min { + +public: + MinSpinOSO_CG(class LAMMPS *); //? + ~MinSpinOSO_CG() {} //? + void init(); + void setup_style(); + int modify_param(int, char **); + void reset_vectors(); + int iterate(int); + double evaluate_dt(); + void advance_spins(); + double fmnorm_sqr(); + void calc_gradients(double); + void calc_search_direction(int); + +private: + // global and spin timesteps + + double dt; + double dts; + + double alpha_damp; // damping for spin minimization + double discrete_factor; // factor for spin timestep evaluation + + double *spvec; // variables for atomic dof, as 1d vector + double *fmvec; // variables for atomic dof, as 1d vector + + double *g_old; // gradient vector + double *g; // gradient vector + double *p; // search direction vector + + bigint last_negative; +}; + +} + +#endif +#endif diff --git a/src/min_spin_oso.h b/src/min_spin_oso.h deleted file mode 100644 index 81ad812e5c..0000000000 --- a/src/min_spin_oso.h +++ /dev/null @@ -1,59 +0,0 @@ -/* -*- c++ -*- ---------------------------------------------------------- - LAMMPS - Large-scale Atomic/Molecular Massively Parallel Simulator - http://lammps.sandia.gov, Sandia National Laboratories - Steve Plimpton, sjplimp@sandia.gov - - Copyright (2003) Sandia Corporation. Under the terms of Contract - DE-AC04-94AL85000 with Sandia Corporation, the U.S. Government retains - certain rights in this software. This software is distributed under - the GNU General Public License. - - See the README file in the top-level LAMMPS directory. -------------------------------------------------------------------------- */ - -#ifdef MINIMIZE_CLASS - -MinimizeStyle(spin_oso, MinSpinOSO) - -#else - -#ifndef LMP_MIN_SPIN_OSO_H -#define LMP_MIN_SPIN_OSO_H - -#include "min.h" - -namespace LAMMPS_NS { - -class MinSpinOSO : public Min { - public: - MinSpinOSO(class LAMMPS *); //? - ~MinSpinOSO() {} //? - void init(); - void setup_style(); - int modify_param(int, char **); - void reset_vectors(); - int iterate(int); - double evaluate_dt(); - void advance_spins(double); - double fmnorm_sqr(); - - private: - - // global and spin timesteps - - double dt; - double dts; - - double alpha_damp; // damping for spin minimization - double discrete_factor; // factor for spin timestep evaluation - - double *spvec; // variables for atomic dof, as 1d vector - double *fmvec; // variables for atomic dof, as 1d vector - - bigint last_negative; -}; - -} - -#endif -#endif From 630ce7b96247b3d8bf23f54c83c04fef8da79c61 Mon Sep 17 00:00:00 2001 From: alxvov Date: Thu, 27 Jun 2019 16:31:24 +0000 Subject: [PATCH 005/192] add contributing authors --- src/SPIN/min_spin_oso_cg.cpp | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/SPIN/min_spin_oso_cg.cpp b/src/SPIN/min_spin_oso_cg.cpp index 9f43442e27..b36e5f280f 100644 --- a/src/SPIN/min_spin_oso_cg.cpp +++ b/src/SPIN/min_spin_oso_cg.cpp @@ -12,7 +12,7 @@ ------------------------------------------------------------------------- */ /* ------------------------------------------------------------------------ - Contributing authors: Julien Tranchida (SNL) + Contributing authors: Julien Tranchida (SNL), Aleksei Ivanov (UI) Please cite the related publication: ------------------------------------------------------------------------- */ From 2520eab46d844bda3e30111d1c8f06d94a009a82 Mon Sep 17 00:00:00 2001 From: alxvov Date: Thu, 27 Jun 2019 16:41:19 +0000 Subject: [PATCH 006/192] small typo --- src/SPIN/min_spin_oso_cg.cpp | 13 ++++++------- src/SPIN/min_spin_oso_cg.h | 4 ++-- 2 files changed, 8 insertions(+), 9 deletions(-) diff --git a/src/SPIN/min_spin_oso_cg.cpp b/src/SPIN/min_spin_oso_cg.cpp index b36e5f280f..9c084d9684 100644 --- a/src/SPIN/min_spin_oso_cg.cpp +++ b/src/SPIN/min_spin_oso_cg.cpp @@ -145,7 +145,7 @@ int MinSpinOSO_CG::iterate(int maxiter) energy_force(0); dts = evaluate_dt(); - calc_gradients(dts); + calc_gradient(dts); calc_search_direction(iter); advance_spins(); @@ -252,7 +252,7 @@ double MinSpinOSO_CG::evaluate_dt() calculate gradients ---------------------------------------------------------------------- */ -void MinSpinOSO_CG::calc_gradients(double dts) +void MinSpinOSO_CG::calc_gradient(double dts) { int nlocal = atom->nlocal; double **sp = atom->sp; @@ -267,7 +267,7 @@ void MinSpinOSO_CG::calc_gradients(double dts) tdampy = -alpha_damp*(fm[i][2]*sp[i][0] - fm[i][0]*sp[i][2]); tdampz = -alpha_damp*(fm[i][0]*sp[i][1] - fm[i][1]*sp[i][0]); - // calculate rotation matrix + // calculate gradients g[3 * i + 0] = -tdampz * dts; g[3 * i + 1] = tdampy * dts; g[3 * i + 2] = -tdampx * dts; @@ -285,7 +285,7 @@ void MinSpinOSO_CG::calc_search_direction(int iter) double g2old_global= 0.0; // for some reason on a second iteration g_old = 0 - // so we make to iterations as steepest descent + // so we make two iterations as steepest descent if (iter <= 2 || iter % 5 == 0){ // steepest descent direction for (int i = 0; i < nlocal; i++) { @@ -312,7 +312,7 @@ void MinSpinOSO_CG::calc_search_direction(int iter) beta = g2_global / g2old_global; - //calculate conjugate direction + // calculate conjugate direction for (int i = 0; i < nlocal; i++) { for (int j = 0; j < 3; j++){ p[3 * i + j] = beta * p[3 * i + j] - g[3 * i + j]; @@ -335,8 +335,7 @@ void MinSpinOSO_CG::advance_spins() double **sp = atom->sp; double **fm = atom->fm; double tdampx, tdampy, tdampz; - // double f[3]; // upper triag. part of skew-symm. matr. to be exponented - double rot_mat[9]; // exponential of a + double rot_mat[9]; // exponential of matrix made of search direction double s_new[3]; // loop on all spins on proc. diff --git a/src/SPIN/min_spin_oso_cg.h b/src/SPIN/min_spin_oso_cg.h index fa0b591c21..a2ecf53e55 100644 --- a/src/SPIN/min_spin_oso_cg.h +++ b/src/SPIN/min_spin_oso_cg.h @@ -37,7 +37,7 @@ public: double evaluate_dt(); void advance_spins(); double fmnorm_sqr(); - void calc_gradients(double); + void calc_gradient(double); void calc_search_direction(int); private: @@ -52,7 +52,7 @@ private: double *spvec; // variables for atomic dof, as 1d vector double *fmvec; // variables for atomic dof, as 1d vector - double *g_old; // gradient vector + double *g_old; // gradient vector at previous iteration double *g; // gradient vector double *p; // search direction vector From 3e8ab7cbb00f42745794afa5205ed4cafbea24f6 Mon Sep 17 00:00:00 2001 From: julient31 Date: Thu, 27 Jun 2019 15:15:57 -0600 Subject: [PATCH 007/192] Commit JT 062719 - cleaned code and setup LAMMPS format and indentation - added src/min_spin_oso_cg.h/cpp to .gitignore --- src/.gitignore | 2 + src/SPIN/min_spin_oso_cg.cpp | 340 ++++++++++++++++++----------------- src/SPIN/min_spin_oso_cg.h | 23 +-- 3 files changed, 193 insertions(+), 172 deletions(-) diff --git a/src/.gitignore b/src/.gitignore index c79c958e6d..0d802981f9 100644 --- a/src/.gitignore +++ b/src/.gitignore @@ -161,6 +161,8 @@ /fix_setforce_spin.h /min_spin.cpp /min_spin.h +/min_spin_oso_cg.cpp +/min_spin_oso_cg.h /neb_spin.cpp /neb_spin.h /pair_spin.cpp diff --git a/src/SPIN/min_spin_oso_cg.cpp b/src/SPIN/min_spin_oso_cg.cpp index 9c084d9684..c09d12dbc8 100644 --- a/src/SPIN/min_spin_oso_cg.cpp +++ b/src/SPIN/min_spin_oso_cg.cpp @@ -12,9 +12,13 @@ ------------------------------------------------------------------------- */ /* ------------------------------------------------------------------------ - Contributing authors: Julien Tranchida (SNL), Aleksei Ivanov (UI) + Contributing authors: Aleksei Ivanov (UI) + Julien Tranchida (SNL) Please cite the related publication: + Ivanov, A. V., Uzdin, V. M., & Jónsson, H. (2019). Fast and Robust + Algorithm for the Minimisation of the Energy of Spin Systems. arXiv + preprint arXiv:1904.02669. ------------------------------------------------------------------------- */ #include @@ -24,6 +28,7 @@ #include "min_spin_oso_cg.h" #include "universe.h" #include "atom.h" +#include "citeme.h" #include "force.h" #include "update.h" #include "output.h" @@ -36,30 +41,40 @@ using namespace LAMMPS_NS; using namespace MathConst; +static const char cite_minstyle_spin_oso_cg[] = + "min_style spin/oso_cg command:\n\n" + "@article{ivanov2019fast,\n" + "title={Fast and Robust Algorithm for the Minimisation of the Energy of " + "Spin Systems},\n" + "author={Ivanov, A. V and Uzdin, V. M. and J{\'o}nsson, H.},\n" + "journal={arXiv preprint arXiv:1904.02669},\n" + "year={2019}\n" + "}\n\n"; + // EPS_ENERGY = minimum normalization for energy tolerance #define EPS_ENERGY 1.0e-8 #define DELAYSTEP 5 -void vm3(const double *m, const double *v, double *out); -void rodrigues_rotation(const double *upp_tr, double *out); /* ---------------------------------------------------------------------- */ -MinSpinOSO_CG::MinSpinOSO_CG(LAMMPS *lmp) : Min(lmp) {} +MinSpinOSO_CG::MinSpinOSO_CG(LAMMPS *lmp) : Min(lmp) { + if (lmp->citeme) lmp->citeme->add(cite_minstyle_spin_oso_cg); +} /* ---------------------------------------------------------------------- */ void MinSpinOSO_CG::init() { - alpha_damp = 1.0; - discrete_factor = 10.0; + alpha_damp = 1.0; + discrete_factor = 10.0; - Min::init(); + Min::init(); - dts = dt = update->dt; - last_negative = update->ntimestep; + dts = dt = update->dt; + last_negative = update->ntimestep; } /* ---------------------------------------------------------------------- */ @@ -121,34 +136,34 @@ void MinSpinOSO_CG::reset_vectors() int MinSpinOSO_CG::iterate(int maxiter) { - bigint ntimestep; - double fmdotfm; - int flag, flagall; + bigint ntimestep; + double fmdotfm; + int flag, flagall; - // not sure it is best place to allocate memory - int nlocal = atom->nlocal; - g = (double *) calloc(3*nlocal, sizeof(double)); - p = (double *) calloc(3*nlocal, sizeof(double)); - g_old = (double *) calloc(3*nlocal, sizeof(double)); - - for (int iter = 0; iter < maxiter; iter++) { + // not sure it is best place to allocate memory + int nlocal = atom->nlocal; + g = (double *) calloc(3*nlocal, sizeof(double)); + p = (double *) calloc(3*nlocal, sizeof(double)); + g_old = (double *) calloc(3*nlocal, sizeof(double)); + for (int iter = 0; iter < maxiter; iter++) { + if (timer->check_timeout(niter)) return TIMEOUT; - + ntimestep = ++update->ntimestep; niter++; - + // optimize timestep accross processes / replicas // need a force calculation for timestep optimization - + energy_force(0); dts = evaluate_dt(); - + calc_gradient(dts); calc_search_direction(iter); advance_spins(); - + eprevious = ecurrent; ecurrent = energy_force(0); neval++; @@ -156,7 +171,7 @@ int MinSpinOSO_CG::iterate(int maxiter) //// energy tolerance criterion //// only check after DELAYSTEP elapsed since velocties reset to 0 //// sync across replicas if running multi-replica minimization - + if (update->etol > 0.0 && ntimestep-last_negative > DELAYSTEP) { if (update->multireplica == 0) { if (fabs(ecurrent-eprevious) < @@ -196,9 +211,9 @@ int MinSpinOSO_CG::iterate(int maxiter) } } - free(p); - free(g); - free(g_old); + free(p); + free(g); + free(g_old); return MAXITER; } @@ -254,76 +269,80 @@ double MinSpinOSO_CG::evaluate_dt() void MinSpinOSO_CG::calc_gradient(double dts) { - int nlocal = atom->nlocal; - double **sp = atom->sp; - double **fm = atom->fm; - double tdampx, tdampy, tdampz; - // loop on all spins on proc. + int nlocal = atom->nlocal; + double **sp = atom->sp; + double **fm = atom->fm; + double tdampx, tdampy, tdampz; + + // loop on all spins on proc. - for (int i = 0; i < nlocal; i++) { + for (int i = 0; i < nlocal; i++) { + + // calc. damping torque + + tdampx = -alpha_damp*(fm[i][1]*sp[i][2] - fm[i][2]*sp[i][1]); + tdampy = -alpha_damp*(fm[i][2]*sp[i][0] - fm[i][0]*sp[i][2]); + tdampz = -alpha_damp*(fm[i][0]*sp[i][1] - fm[i][1]*sp[i][0]); - // calc. damping torque - tdampx = -alpha_damp*(fm[i][1]*sp[i][2] - fm[i][2]*sp[i][1]); - tdampy = -alpha_damp*(fm[i][2]*sp[i][0] - fm[i][0]*sp[i][2]); - tdampz = -alpha_damp*(fm[i][0]*sp[i][1] - fm[i][1]*sp[i][0]); - - // calculate gradients - g[3 * i + 0] = -tdampz * dts; - g[3 * i + 1] = tdampy * dts; - g[3 * i + 2] = -tdampx * dts; - } + // calculate gradients + + g[3 * i + 0] = -tdampz * dts; + g[3 * i + 1] = tdampy * dts; + g[3 * i + 2] = -tdampx * dts; + } } +/* ---------------------------------------------------------------------- + search direction +---------------------------------------------------------------------- */ + void MinSpinOSO_CG::calc_search_direction(int iter) { - int nlocal = atom->nlocal; - double g2old = 0.0; - double g2 = 0.0; - double beta = 0.0; + int nlocal = atom->nlocal; + double g2old = 0.0; + double g2 = 0.0; + double beta = 0.0; - double g2_global= 0.0; - double g2old_global= 0.0; - - // for some reason on a second iteration g_old = 0 - // so we make two iterations as steepest descent - if (iter <= 2 || iter % 5 == 0){ - // steepest descent direction - for (int i = 0; i < nlocal; i++) { - for (int j = 0; j < 3; j++){ - p[3 * i + j] = -g[3 * i + j]; - g_old[3 * i + j] = g[3 * i + j]; - } - } - } else{ - // conjugate direction - for (int i = 0; i < nlocal; i++) { - for (int j = 0; j < 3; j++){ - g2old += g_old[3 * i + j] * g_old[3 * i + j]; - g2 += g[3 * i + j] * g[3 * i + j]; - - } - } - - // now we need to collect/broadcast beta on this replica - // different replica can have different beta for now. - // need to check what is beta for GNEB - MPI_Allreduce(&g2, &g2_global, 1, MPI_DOUBLE, MPI_SUM, world); - MPI_Allreduce(&g2old, &g2old_global, 1, MPI_DOUBLE, MPI_SUM, world); - - beta = g2_global / g2old_global; - - // calculate conjugate direction - for (int i = 0; i < nlocal; i++) { - for (int j = 0; j < 3; j++){ - p[3 * i + j] = beta * p[3 * i + j] - g[3 * i + j]; - g_old[3 * i + j] = g[3 * i + j]; - } - } + double g2_global= 0.0; + double g2old_global= 0.0; + // for some reason on a second iteration g_old = 0 + // so we make two iterations as steepest descent + + if (iter <= 2 || iter % 5 == 0){ // steepest descent direction + for (int i = 0; i < nlocal; i++) { + for (int j = 0; j < 3; j++){ + p[3 * i + j] = -g[3 * i + j]; + g_old[3 * i + j] = g[3 * i + j]; + } + } + } else { // conjugate direction + for (int i = 0; i < nlocal; i++) { + for (int j = 0; j < 3; j++){ + g2old += g_old[3 * i + j] * g_old[3 * i + j]; + g2 += g[3 * i + j] * g[3 * i + j]; + } } -} + // now we need to collect/broadcast beta on this replica + // different replica can have different beta for now. + // need to check what is beta for GNEB + + MPI_Allreduce(&g2, &g2_global, 1, MPI_DOUBLE, MPI_SUM, world); + MPI_Allreduce(&g2old, &g2old_global, 1, MPI_DOUBLE, MPI_SUM, world); + beta = g2_global / g2old_global; + + // calculate conjugate direction + + for (int i = 0; i < nlocal; i++) { + for (int j = 0; j < 3; j++){ + p[3 * i + j] = beta * p[3 * i + j] - g[3 * i + j]; + g_old[3 * i + j] = g[3 * i + j]; + } + } + } +} /* ---------------------------------------------------------------------- rotation of spins along the search direction @@ -341,14 +360,15 @@ void MinSpinOSO_CG::advance_spins() // loop on all spins on proc. for (int i = 0; i < nlocal; i++) { - rodrigues_rotation(p + 3 * i, rot_mat); - // rotate spins - vm3(rot_mat, sp[i], s_new); - sp[i][0] = s_new[0]; - sp[i][1] = s_new[1]; - sp[i][2] = s_new[2]; + rodrigues_rotation(p + 3 * i, rot_mat); + + // rotate spins + + vm3(rot_mat, sp[i], s_new); + sp[i][0] = s_new[0]; + sp[i][1] = s_new[1]; + sp[i][2] = s_new[2]; } - } /* ---------------------------------------------------------------------- @@ -384,86 +404,82 @@ double MinSpinOSO_CG::fmnorm_sqr() return norm2_sqr; } +/* ---------------------------------------------------------------------- + calculate 3x3 matrix exponential using Rodrigues' formula + (R. Murray, Z. Li, and S. Shankar Sastry, + A Mathematical Introduction to + Robotic Manipulation (1994), p. 28 and 30). + + upp_tr - vector x, y, z so that one calculate + U = exp(A) with A= [[0, x, y], + [-x, 0, z], + [-y, -z, 0]] +------------------------------------------------------------------------- */ -void rodrigues_rotation(const double *upp_tr, double *out){ +void MinSpinOSO_CG::rodrigues_rotation(const double *upp_tr, double *out) +{ - /*** - * calculate 3x3 matrix exponential using Rodrigues' formula - * (R. Murray, Z. Li, and S. Shankar Sastry, - * A Mathematical Introduction to - * Robotic Manipulation (1994), p. 28 and 30). - * - * upp_tr - vector x, y, z so that one calculate - * U = exp(A) with A= [[0, x, y], - * [-x, 0, z], - * [-y, -z, 0]] - ***/ - - - if (fabs(upp_tr[0]) < 1.0e-40 && - fabs(upp_tr[1]) < 1.0e-40 && - fabs(upp_tr[2]) < 1.0e-40){ - // if upp_tr is zero, return unity matrix - int k; - int m; - for(k = 0; k < 3; k++){ - for(m = 0; m < 3; m++){ - if (m == k) out[3 * k + m] = 1.0; - else out[3 * k + m] = 0.0; - } - } - return; + if (fabs(upp_tr[0]) < 1.0e-40 && + fabs(upp_tr[1]) < 1.0e-40 && + fabs(upp_tr[2]) < 1.0e-40){ + + // if upp_tr is zero, return unity matrix + for(int k = 0; k < 3; k++){ + for(int m = 0; m < 3; m++){ + if (m == k) out[3 * k + m] = 1.0; + else out[3 * k + m] = 0.0; + } } + return; + } - double theta = sqrt(upp_tr[0] * upp_tr[0] + - upp_tr[1] * upp_tr[1] + - upp_tr[2] * upp_tr[2]); + double theta = sqrt(upp_tr[0] * upp_tr[0] + + upp_tr[1] * upp_tr[1] + + upp_tr[2] * upp_tr[2]); - double A = cos(theta); - double B = sin(theta); - double D = 1 - A; - double x = upp_tr[0]/theta; - double y = upp_tr[1]/theta; - double z = upp_tr[2]/theta; + double A = cos(theta); + double B = sin(theta); + double D = 1 - A; + double x = upp_tr[0]/theta; + double y = upp_tr[1]/theta; + double z = upp_tr[2]/theta; - // diagonal elements of U - out[0] = A + z * z * D; - out[4] = A + y * y * D; - out[8] = A + x * x * D; + // diagonal elements of U + + out[0] = A + z * z * D; + out[4] = A + y * y * D; + out[8] = A + x * x * D; - // off diagonal of U - double s1 = -y * z *D; - double s2 = x * z * D; - double s3 = -x * y * D; + // off diagonal of U + + double s1 = -y * z *D; + double s2 = x * z * D; + double s3 = -x * y * D; - double a1 = x * B; - double a2 = y * B; - double a3 = z * B; + double a1 = x * B; + double a2 = y * B; + double a3 = z * B; - out[1] = s1 + a1; - out[3] = s1 - a1; - out[2] = s2 + a2; - out[6] = s2 - a2; - out[5] = s3 + a3; - out[7] = s3 - a3; + out[1] = s1 + a1; + out[3] = s1 - a1; + out[2] = s2 + a2; + out[6] = s2 - a2; + out[5] = s3 + a3; + out[7] = s3 - a3; } +/* ---------------------------------------------------------------------- + out = vector^T x m, + m -- 3x3 matrix , v -- 3-d vector +------------------------------------------------------------------------- */ -void vm3(const double *m, const double *v, double *out){ - /*** - * out = vector^T x m, - * m -- 3x3 matrix , v -- 3-d vector - ***/ - - int i; - int j; - - for(i = 0; i < 3; i++){ - out[i] *= 0.0; - for(j = 0; j < 3; j++){ - out[i] += *(m + 3 * j + i) * v[j]; - } +void MinSpinOSO_CG::vm3(const double *m, const double *v, double *out) +{ + for(int i = 0; i < 3; i++){ + out[i] *= 0.0; + for(int j = 0; j < 3; j++){ + out[i] += *(m + 3 * j + i) * v[j]; } - + } } diff --git a/src/SPIN/min_spin_oso_cg.h b/src/SPIN/min_spin_oso_cg.h index a2ecf53e55..8cff52431c 100644 --- a/src/SPIN/min_spin_oso_cg.h +++ b/src/SPIN/min_spin_oso_cg.h @@ -13,7 +13,7 @@ #ifdef MINIMIZE_CLASS -MinimizeStyle(spin_oso_cg, MinSpinOSO_CG) +MinimizeStyle(spin/oso_cg, MinSpinOSO_CG) #else @@ -27,8 +27,8 @@ namespace LAMMPS_NS { class MinSpinOSO_CG : public Min { public: - MinSpinOSO_CG(class LAMMPS *); //? - ~MinSpinOSO_CG() {} //? + MinSpinOSO_CG(class LAMMPS *); + ~MinSpinOSO_CG() {} void init(); void setup_style(); int modify_param(int, char **); @@ -46,15 +46,18 @@ private: double dt; double dts; - double alpha_damp; // damping for spin minimization - double discrete_factor; // factor for spin timestep evaluation + double alpha_damp; // damping for spin minimization + double discrete_factor; // factor for spin timestep evaluation - double *spvec; // variables for atomic dof, as 1d vector - double *fmvec; // variables for atomic dof, as 1d vector + double *spvec; // variables for atomic dof, as 1d vector + double *fmvec; // variables for atomic dof, as 1d vector - double *g_old; // gradient vector at previous iteration - double *g; // gradient vector - double *p; // search direction vector + double *g_old; // gradient vector at previous iteration + double *g; // gradient vector + double *p; // search direction vector + + void vm3(const double *m, const double *v, double *out); + void rodrigues_rotation(const double *upp_tr, double *out); bigint last_negative; }; From 5c8e81241aba49399ef221bc841ccdc249cc08c1 Mon Sep 17 00:00:00 2001 From: julient31 Date: Fri, 28 Jun 2019 10:49:21 -0600 Subject: [PATCH 008/192] Commit JT 062819 - modified memory allocation --- src/SPIN/fix_nve_spin.h | 2 +- src/SPIN/min_spin_oso_cg.cpp | 90 ++++++++++++++++++++++-------------- src/SPIN/min_spin_oso_cg.h | 11 +++-- 3 files changed, 63 insertions(+), 40 deletions(-) diff --git a/src/SPIN/fix_nve_spin.h b/src/SPIN/fix_nve_spin.h index 4800575c06..89cd617e0b 100644 --- a/src/SPIN/fix_nve_spin.h +++ b/src/SPIN/fix_nve_spin.h @@ -54,7 +54,7 @@ friend class PairSpin; double dtv, dtf, dts; // velocity, force, and spin timesteps - int nlocal_max; // max value of nlocal (for lists size) + int nlocal_max; // max value of nlocal (for size of lists) int pair_spin_flag; // magnetic pair flags int long_spin_flag; // magnetic long-range flag diff --git a/src/SPIN/min_spin_oso_cg.cpp b/src/SPIN/min_spin_oso_cg.cpp index c09d12dbc8..d6bca32a40 100644 --- a/src/SPIN/min_spin_oso_cg.cpp +++ b/src/SPIN/min_spin_oso_cg.cpp @@ -34,6 +34,7 @@ #include "output.h" #include "timer.h" #include "error.h" +#include "memory.h" #include "modify.h" #include "math_special.h" #include "math_const.h" @@ -60,8 +61,20 @@ static const char cite_minstyle_spin_oso_cg[] = /* ---------------------------------------------------------------------- */ -MinSpinOSO_CG::MinSpinOSO_CG(LAMMPS *lmp) : Min(lmp) { +MinSpinOSO_CG::MinSpinOSO_CG(LAMMPS *lmp) : + Min(lmp), g_old(NULL), g_cur(NULL), p_s(NULL) +{ if (lmp->citeme) lmp->citeme->add(cite_minstyle_spin_oso_cg); + nlocal_max = 0; +} + +/* ---------------------------------------------------------------------- */ + +MinSpinOSO_CG::~MinSpinOSO_CG() +{ + memory->destroy(g_old); + memory->destroy(g_cur); + memory->destroy(p_s); } /* ---------------------------------------------------------------------- */ @@ -75,6 +88,13 @@ void MinSpinOSO_CG::init() dts = dt = update->dt; last_negative = update->ntimestep; + + // allocate tables + + nlocal_max = atom->nlocal; + memory->grow(g_old,3*nlocal_max,"min/spin/oso/cg:g_old"); + memory->grow(g_cur,3*nlocal_max,"min/spin/oso/cg:g_cur"); + memory->grow(p_s,3*nlocal_max,"min/spin/oso/cg:p_s"); } /* ---------------------------------------------------------------------- */ @@ -134,17 +154,21 @@ void MinSpinOSO_CG::reset_vectors() minimization via damped spin dynamics ------------------------------------------------------------------------- */ +// g_old g_cur p_s + int MinSpinOSO_CG::iterate(int maxiter) { + int nlocal = atom->nlocal; bigint ntimestep; double fmdotfm; int flag, flagall; - // not sure it is best place to allocate memory - int nlocal = atom->nlocal; - g = (double *) calloc(3*nlocal, sizeof(double)); - p = (double *) calloc(3*nlocal, sizeof(double)); - g_old = (double *) calloc(3*nlocal, sizeof(double)); + if (nlocal_max < nlocal) { + nlocal_max = nlocal; + memory->grow(g_old,3*nlocal_max,"min/spin/oso/cg:g_old"); + memory->grow(g_cur,3*nlocal_max,"min/spin/oso/cg:g_cur"); + memory->grow(p_s,3*nlocal_max,"min/spin/oso/cg:p_s"); + } for (int iter = 0; iter < maxiter; iter++) { @@ -211,10 +235,6 @@ int MinSpinOSO_CG::iterate(int maxiter) } } - free(p); - free(g); - free(g_old); - return MAXITER; } @@ -286,9 +306,9 @@ void MinSpinOSO_CG::calc_gradient(double dts) // calculate gradients - g[3 * i + 0] = -tdampz * dts; - g[3 * i + 1] = tdampy * dts; - g[3 * i + 2] = -tdampx * dts; + g_cur[3 * i + 0] = -tdampz * dts; + g_cur[3 * i + 1] = tdampy * dts; + g_cur[3 * i + 2] = -tdampx * dts; } } @@ -312,15 +332,15 @@ void MinSpinOSO_CG::calc_search_direction(int iter) if (iter <= 2 || iter % 5 == 0){ // steepest descent direction for (int i = 0; i < nlocal; i++) { for (int j = 0; j < 3; j++){ - p[3 * i + j] = -g[3 * i + j]; - g_old[3 * i + j] = g[3 * i + j]; + p_s[3 * i + j] = -g_cur[3 * i + j]; + g_old[3 * i + j] = g_cur[3 * i + j]; } } } else { // conjugate direction for (int i = 0; i < nlocal; i++) { for (int j = 0; j < 3; j++){ g2old += g_old[3 * i + j] * g_old[3 * i + j]; - g2 += g[3 * i + j] * g[3 * i + j]; + g2 += g_cur[3 * i + j] * g_cur[3 * i + j]; } } @@ -337,8 +357,8 @@ void MinSpinOSO_CG::calc_search_direction(int iter) for (int i = 0; i < nlocal; i++) { for (int j = 0; j < 3; j++){ - p[3 * i + j] = beta * p[3 * i + j] - g[3 * i + j]; - g_old[3 * i + j] = g[3 * i + j]; + p_s[3 * i + j] = beta * p_s[3 * i + j] - g_cur[3 * i + j]; + g_old[3 * i + j] = g_cur[3 * i + j]; } } } @@ -360,7 +380,7 @@ void MinSpinOSO_CG::advance_spins() // loop on all spins on proc. for (int i = 0; i < nlocal; i++) { - rodrigues_rotation(p + 3 * i, rot_mat); + rodrigues_rotation(p_s + 3 * i, rot_mat); // rotate spins @@ -418,6 +438,8 @@ double MinSpinOSO_CG::fmnorm_sqr() void MinSpinOSO_CG::rodrigues_rotation(const double *upp_tr, double *out) { + double theta,A,B,D,x,y,z; + double s1,s2,s3,a1,a2,a3; if (fabs(upp_tr[0]) < 1.0e-40 && fabs(upp_tr[1]) < 1.0e-40 && @@ -433,16 +455,16 @@ void MinSpinOSO_CG::rodrigues_rotation(const double *upp_tr, double *out) return; } - double theta = sqrt(upp_tr[0] * upp_tr[0] + - upp_tr[1] * upp_tr[1] + - upp_tr[2] * upp_tr[2]); + theta = sqrt(upp_tr[0] * upp_tr[0] + + upp_tr[1] * upp_tr[1] + + upp_tr[2] * upp_tr[2]); - double A = cos(theta); - double B = sin(theta); - double D = 1 - A; - double x = upp_tr[0]/theta; - double y = upp_tr[1]/theta; - double z = upp_tr[2]/theta; + A = cos(theta); + B = sin(theta); + D = 1 - A; + x = upp_tr[0]/theta; + y = upp_tr[1]/theta; + z = upp_tr[2]/theta; // diagonal elements of U @@ -452,13 +474,13 @@ void MinSpinOSO_CG::rodrigues_rotation(const double *upp_tr, double *out) // off diagonal of U - double s1 = -y * z *D; - double s2 = x * z * D; - double s3 = -x * y * D; + s1 = -y * z *D; + s2 = x * z * D; + s3 = -x * y * D; - double a1 = x * B; - double a2 = y * B; - double a3 = z * B; + a1 = x * B; + a2 = y * B; + a3 = z * B; out[1] = s1 + a1; out[3] = s1 - a1; diff --git a/src/SPIN/min_spin_oso_cg.h b/src/SPIN/min_spin_oso_cg.h index 8cff52431c..a791754836 100644 --- a/src/SPIN/min_spin_oso_cg.h +++ b/src/SPIN/min_spin_oso_cg.h @@ -28,7 +28,7 @@ class MinSpinOSO_CG : public Min { public: MinSpinOSO_CG(class LAMMPS *); - ~MinSpinOSO_CG() {} + virtual ~MinSpinOSO_CG(); void init(); void setup_style(); int modify_param(int, char **); @@ -43,6 +43,7 @@ public: private: // global and spin timesteps + int nlocal_max; // max value of nlocal (for size of lists) double dt; double dts; @@ -53,11 +54,11 @@ private: double *fmvec; // variables for atomic dof, as 1d vector double *g_old; // gradient vector at previous iteration - double *g; // gradient vector - double *p; // search direction vector + double *g_cur; // current gradient vector + double *p_s; // search direction vector - void vm3(const double *m, const double *v, double *out); - void rodrigues_rotation(const double *upp_tr, double *out); + void vm3(const double *, const double *, double *); + void rodrigues_rotation(const double *, double *); bigint last_negative; }; From 61b12a09f2c3f81e520aa788721985f762d50ced Mon Sep 17 00:00:00 2001 From: alxvov Date: Mon, 1 Jul 2019 08:01:11 +0000 Subject: [PATCH 009/192] added lbfgs --- src/SPIN/min_spin_oso_lbfgs.cpp | 577 ++++++++++++++++++++++++++++++++ src/SPIN/min_spin_oso_lbfgs.h | 73 ++++ 2 files changed, 650 insertions(+) create mode 100644 src/SPIN/min_spin_oso_lbfgs.cpp create mode 100644 src/SPIN/min_spin_oso_lbfgs.h diff --git a/src/SPIN/min_spin_oso_lbfgs.cpp b/src/SPIN/min_spin_oso_lbfgs.cpp new file mode 100644 index 0000000000..f0a4fcbd87 --- /dev/null +++ b/src/SPIN/min_spin_oso_lbfgs.cpp @@ -0,0 +1,577 @@ +/* ---------------------------------------------------------------------- + LAMMPS - Large-scale Atomic/Molecular Massively Parallel Simulator + http://lammps.sandia.gov, Sandia National Laboratories + Steve Plimpton, sjplimp@sandia.gov + + Copyright (2003) Sandia Corporation. Under the terms of Contract + DE-AC04-94AL85000 with Sandia Corporation, the U.S. Government retains + certain rights in this software. This software is distributed under + the GNU General Public License. + + See the README file in the top-level LAMMPS directory. +------------------------------------------------------------------------- */ + +/* ------------------------------------------------------------------------ + Contributing authors: Aleksei Ivanov (UI) + Julien Tranchida (SNL) + + Please cite the related publication: + Ivanov, A. V., Uzdin, V. M., & Jónsson, H. (2019). Fast and Robust + Algorithm for the Minimisation of the Energy of Spin Systems. arXiv + preprint arXiv:1904.02669. +------------------------------------------------------------------------- */ + +#include +#include +#include +#include +#include "min_spin_oso_lbfgs.h" +#include "universe.h" +#include "atom.h" +#include "citeme.h" +#include "force.h" +#include "update.h" +#include "output.h" +#include "timer.h" +#include "error.h" +#include "modify.h" +#include "math_special.h" +#include "math_const.h" + +#include +using namespace std; + +using namespace LAMMPS_NS; +using namespace MathConst; + +static const char cite_minstyle_spin_oso_lbfgs[] = + "min_style spin/oso_lbfgs command:\n\n" + "@article{ivanov2019fast,\n" + "title={Fast and Robust Algorithm for the Minimisation of the Energy of " + "Spin Systems},\n" + "author={Ivanov, A. V and Uzdin, V. M. and J{\'o}nsson, H.},\n" + "journal={arXiv preprint arXiv:1904.02669},\n" + "year={2019}\n" + "}\n\n"; + +// EPS_ENERGY = minimum normalization for energy tolerance + +#define EPS_ENERGY 1.0e-8 + +#define DELAYSTEP 5 + + +/* ---------------------------------------------------------------------- */ + +MinSpinOSO_LBFGS::MinSpinOSO_LBFGS(LAMMPS *lmp) : Min(lmp) { + if (lmp->citeme) lmp->citeme->add(cite_minstyle_spin_oso_lbfgs); +} + +/* ---------------------------------------------------------------------- */ + +void MinSpinOSO_LBFGS::init() +{ + alpha_damp = 1.0; + discrete_factor = 10.0; + num_mem = 3; + + Min::init(); + + dts = dt = update->dt; + last_negative = update->ntimestep; +} + +/* ---------------------------------------------------------------------- */ + +void MinSpinOSO_LBFGS::setup_style() +{ + double **v = atom->v; + int nlocal = atom->nlocal; + + // check if the atom/spin style is defined + + if (!atom->sp_flag) + error->all(FLERR,"min/spin_oso_lbfgs requires atom/spin style"); + + for (int i = 0; i < nlocal; i++) + v[i][0] = v[i][1] = v[i][2] = 0.0; +} + +/* ---------------------------------------------------------------------- */ + +int MinSpinOSO_LBFGS::modify_param(int narg, char **arg) +{ + if (strcmp(arg[0],"alpha_damp") == 0) { + if (narg < 2) error->all(FLERR,"Illegal fix_modify command"); + alpha_damp = force->numeric(FLERR,arg[1]); + return 2; + } + if (strcmp(arg[0],"discrete_factor") == 0) { + if (narg < 2) error->all(FLERR,"Illegal fix_modify command"); + discrete_factor = force->numeric(FLERR,arg[1]); + return 2; + } + return 0; +} + +/* ---------------------------------------------------------------------- + set current vector lengths and pointers + called after atoms have migrated +------------------------------------------------------------------------- */ + +void MinSpinOSO_LBFGS::reset_vectors() +{ + // atomic dof + + // size sp is 4N vector + nvec = 4 * atom->nlocal; + if (nvec) spvec = atom->sp[0]; + + nvec = 3 * atom->nlocal; + if (nvec) fmvec = atom->fm[0]; + + if (nvec) xvec = atom->x[0]; + if (nvec) fvec = atom->f[0]; +} + +/* ---------------------------------------------------------------------- + minimization via damped spin dynamics +------------------------------------------------------------------------- */ + +int MinSpinOSO_LBFGS::iterate(int maxiter) +{ + bigint ntimestep; + double fmdotfm; + int flag, flagall; + + // not sure it is best place to allocate memory + int nlocal = atom->nlocal; + g = (double *) calloc(3*nlocal, sizeof(double)); + p = (double *) calloc(3*nlocal, sizeof(double)); + g_old = (double *) calloc(3*nlocal, sizeof(double)); + rho = (double *) calloc(num_mem, sizeof(double)); + ds = (double **) calloc(num_mem, sizeof(double *)); + dy = (double **) calloc(num_mem, sizeof(double *)); + for (int k = 0; k < num_mem; k++){ + ds[k] = (double *) calloc(3*nlocal, sizeof(double)); + dy[k] = (double *) calloc(3*nlocal, sizeof(double)); + } + + for (int iter = 0; iter < maxiter; iter++) { + + if (timer->check_timeout(niter)) + return TIMEOUT; + + ntimestep = ++update->ntimestep; + niter++; + + // optimize timestep accross processes / replicas + // need a force calculation for timestep optimization + + energy_force(0); + // dts = evaluate_dt(); + // dts = 1.0; + calc_gradient(1.0); + calc_search_direction(iter); + advance_spins(); + + eprevious = ecurrent; + ecurrent = energy_force(0); + neval++; + + //// energy tolerance criterion + //// only check after DELAYSTEP elapsed since velocties reset to 0 + //// sync across replicas if running multi-replica minimization + + if (update->etol > 0.0 && ntimestep-last_negative > DELAYSTEP) { + if (update->multireplica == 0) { + if (fabs(ecurrent-eprevious) < + update->etol * 0.5*(fabs(ecurrent) + fabs(eprevious) + EPS_ENERGY)) + return ETOL; + } else { + if (fabs(ecurrent-eprevious) < + update->etol * 0.5*(fabs(ecurrent) + fabs(eprevious) + EPS_ENERGY)) + flag = 0; + else flag = 1; + MPI_Allreduce(&flag,&flagall,1,MPI_INT,MPI_SUM,universe->uworld); + if (flagall == 0) return ETOL; + } + } + + // magnetic torque tolerance criterion + // sync across replicas if running multi-replica minimization + + if (update->ftol > 0.0) { + fmdotfm = fmnorm_sqr(); + if (update->multireplica == 0) { + if (fmdotfm < update->ftol*update->ftol) return FTOL; + } else { + if (fmdotfm < update->ftol*update->ftol) flag = 0; + else flag = 1; + MPI_Allreduce(&flag,&flagall,1,MPI_INT,MPI_SUM,universe->uworld); + if (flagall == 0) return FTOL; + } + } + + // output for thermo, dump, restart files + + if (output->next == ntimestep) { + timer->stamp(); + output->write(ntimestep); + timer->stamp(Timer::OUTPUT); + } + } + + free(p); + free(g); + free(g_old); + for (int k = 0; k < num_mem; k++){ + free(ds[k]); + free(dy[k]); + } + free(ds); + free(dy); + free(rho); + + return MAXITER; +} + +/* ---------------------------------------------------------------------- + evaluate max timestep +---------------------------------------------------------------------- */ + +double MinSpinOSO_LBFGS::evaluate_dt() +{ + double dtmax; + double fmsq; + double fmaxsqone,fmaxsqloc,fmaxsqall; + int nlocal = atom->nlocal; + double **fm = atom->fm; + + // finding max fm on this proc. + + fmsq = fmaxsqone = fmaxsqloc = fmaxsqall = 0.0; + for (int i = 0; i < nlocal; i++) { + fmsq = fm[i][0]*fm[i][0]+fm[i][1]*fm[i][1]+fm[i][2]*fm[i][2]; + fmaxsqone = MAX(fmaxsqone,fmsq); + } + + // finding max fm on this replica + + fmaxsqloc = fmaxsqone; + MPI_Allreduce(&fmaxsqone,&fmaxsqloc,1,MPI_DOUBLE,MPI_MAX,world); + + // finding max fm over all replicas, if necessary + // this communicator would be invalid for multiprocess replicas + + fmaxsqall = fmaxsqloc; + if (update->multireplica == 1) { + fmaxsqall = fmaxsqloc; + MPI_Allreduce(&fmaxsqloc,&fmaxsqall,1,MPI_DOUBLE,MPI_MAX,universe->uworld); + } + + if (fmaxsqall == 0.0) + error->all(FLERR,"Incorrect fmaxsqall calculation"); + + // define max timestep by dividing by the + // inverse of max frequency by discrete_factor + + dtmax = MY_2PI/(discrete_factor*sqrt(fmaxsqall)); + + return dtmax; +} + +/* ---------------------------------------------------------------------- + calculate gradients +---------------------------------------------------------------------- */ + +void MinSpinOSO_LBFGS::calc_gradient(double dts) +{ + int nlocal = atom->nlocal; + double **sp = atom->sp; + double **fm = atom->fm; + double tdampx, tdampy, tdampz; + + // loop on all spins on proc. + + for (int i = 0; i < nlocal; i++) { + + // calc. damping torque + + tdampx = -alpha_damp*(fm[i][1]*sp[i][2] - fm[i][2]*sp[i][1]); + tdampy = -alpha_damp*(fm[i][2]*sp[i][0] - fm[i][0]*sp[i][2]); + tdampz = -alpha_damp*(fm[i][0]*sp[i][1] - fm[i][1]*sp[i][0]); + + // calculate gradients + + g[3 * i + 0] = -tdampz * dts; + g[3 * i + 1] = tdampy * dts; + g[3 * i + 2] = -tdampx * dts; + } +} + +/* ---------------------------------------------------------------------- + search direction +---------------------------------------------------------------------- */ + +void MinSpinOSO_LBFGS::calc_search_direction(int iter) +{ + int nlocal = atom->nlocal; + + double dyds = 0.0; + double sq = 0.0; + double yy = 0.0; + double yr = 0.0; + double beta = 0.0; + + double dyds_global = 0.0; + double sq_global = 0.0; + double yy_global = 0.0; + double yr_global = 0.0; + double beta_global = 0.0; + + int m_index = iter % num_mem; // memory index + int c_ind = 0; + double *q; + double *alpha; + + q = (double *) calloc(3*nlocal, sizeof(double)); + alpha = (double *) calloc(num_mem, sizeof(double)); + + // for some reason on a second iteration g_old = 0 + // so we make two iterations as steepest descent + + if (iter == 0){ // steepest descent direction + for (int i = 0; i < 3 * nlocal; i++) { + p[i] = -g[i]; + g_old[i] = g[i]; + ds[m_index][i] = 0.0; + dy[m_index][i] = 0.0; + + } + } else { + dyds = 0.0; + for (int i = 0; i < 3 * nlocal; i++) { + ds[m_index][i] = p[i]; + dy[m_index][i] = g[i] - g_old[i]; + dyds += ds[m_index][i] * dy[m_index][i]; + } +// MPI_Allreduce(&dyds, &dyds_global, 1, MPI_DOUBLE, MPI_SUM, world); + if (fabs(dyds) > 1.0e-60) rho[m_index] = 1.0 / dyds; + else rho[m_index] = 1.0e60; + + // set the q vector + + for (int i = 0; i < 3 * nlocal; i++) { + q[i] = g[i]; + } + + // loop over last m indecies + for(int k = num_mem - 1; k > -1; k--) { + // this loop should run from the newest memory to the oldest one. + + c_ind = (k + m_index + 1) % num_mem; + + // dot product between dg and q + + sq = 0.0; + for (int i = 0; i < 3 * nlocal; i++) { + sq += ds[c_ind][i] * q[i]; + } + + // update alpha + + alpha[c_ind] = rho[c_ind] * sq; + + // update q + + for (int i = 0; i < 3 * nlocal; i++) { + q[i] -= alpha[c_ind] * dy[c_ind][i]; + } + } + + // dot product between dg with itself + yy = 0.0; + for (int i = 0; i < 3 * nlocal; i++) { + yy += dy[m_index][i] * dy[m_index][i]; + } + + // calculate now search direction + + if (fabs(yy) > 1.0e-60) { + for (int i = 0; i < 3 * nlocal; i++) { + p[i] = q[i] / (rho[m_index] * yy); + } + }else{ + for (int i = 0; i < 3 * nlocal; i++) { + p[i] = q[i] * 1.0e60; + } + } + + for (int k = 0; k < num_mem; k++){ + // this loop should run from the oldest memory to the newest one. + + if (iter < num_mem) c_ind = k; + else c_ind = (k + m_index + 1) % num_mem; + + // dot product between p and da + yr = 0.0; + for (int i = 0; i < 3 * nlocal; i++) { + yr += dy[c_ind][i] * p[i]; + } + + beta = rho[c_ind] * yr; + for (int i = 0; i < 3 * nlocal; i++) { + p[i] += ds[c_ind][i] * (alpha[c_ind] - beta); + } + } + for (int i = 0; i < 3 * nlocal; i++) { + p[i] = -1.0 * p[i]; + g_old[i] = g[i]; + } + } + + free(q); + free(alpha); + +} + +/* ---------------------------------------------------------------------- + rotation of spins along the search direction +---------------------------------------------------------------------- */ + +void MinSpinOSO_LBFGS::advance_spins() +{ + int nlocal = atom->nlocal; + double **sp = atom->sp; + double **fm = atom->fm; + double tdampx, tdampy, tdampz; + double rot_mat[9]; // exponential of matrix made of search direction + double s_new[3]; + + // loop on all spins on proc. + + for (int i = 0; i < nlocal; i++) { + rodrigues_rotation(p + 3 * i, rot_mat); + + // rotate spins + + vm3(rot_mat, sp[i], s_new); + sp[i][0] = s_new[0]; + sp[i][1] = s_new[1]; + sp[i][2] = s_new[2]; + } +} + +/* ---------------------------------------------------------------------- + compute and return ||mag. torque||_2^2 +------------------------------------------------------------------------- */ + +double MinSpinOSO_LBFGS::fmnorm_sqr() +{ + int nlocal = atom->nlocal; + double tx,ty,tz; + double **sp = atom->sp; + double **fm = atom->fm; + + // calc. magnetic torques + + double local_norm2_sqr = 0.0; + for (int i = 0; i < nlocal; i++) { + tx = (fm[i][1]*sp[i][2] - fm[i][2]*sp[i][1]); + ty = (fm[i][2]*sp[i][0] - fm[i][0]*sp[i][2]); + tz = (fm[i][0]*sp[i][1] - fm[i][1]*sp[i][0]); + + local_norm2_sqr += tx*tx + ty*ty + tz*tz; + } + + // no extra atom calc. for spins + + if (nextra_atom) + error->all(FLERR,"extra atom option not available yet"); + + double norm2_sqr = 0.0; + MPI_Allreduce(&local_norm2_sqr,&norm2_sqr,1,MPI_DOUBLE,MPI_SUM,world); + + return norm2_sqr; +} + +/* ---------------------------------------------------------------------- + calculate 3x3 matrix exponential using Rodrigues' formula + (R. Murray, Z. Li, and S. Shankar Sastry, + A Mathematical Introduction to + Robotic Manipulation (1994), p. 28 and 30). + + upp_tr - vector x, y, z so that one calculate + U = exp(A) with A= [[0, x, y], + [-x, 0, z], + [-y, -z, 0]] +------------------------------------------------------------------------- */ + +void MinSpinOSO_LBFGS::rodrigues_rotation(const double *upp_tr, double *out) +{ + + if (fabs(upp_tr[0]) < 1.0e-40 && + fabs(upp_tr[1]) < 1.0e-40 && + fabs(upp_tr[2]) < 1.0e-40){ + + // if upp_tr is zero, return unity matrix + for(int k = 0; k < 3; k++){ + for(int m = 0; m < 3; m++){ + if (m == k) out[3 * k + m] = 1.0; + else out[3 * k + m] = 0.0; + } + } + return; + } + + double theta = sqrt(upp_tr[0] * upp_tr[0] + + upp_tr[1] * upp_tr[1] + + upp_tr[2] * upp_tr[2]); + + double A = cos(theta); + double B = sin(theta); + double D = 1 - A; + double x = upp_tr[0]/theta; + double y = upp_tr[1]/theta; + double z = upp_tr[2]/theta; + + // diagonal elements of U + + out[0] = A + z * z * D; + out[4] = A + y * y * D; + out[8] = A + x * x * D; + + // off diagonal of U + + double s1 = -y * z *D; + double s2 = x * z * D; + double s3 = -x * y * D; + + double a1 = x * B; + double a2 = y * B; + double a3 = z * B; + + out[1] = s1 + a1; + out[3] = s1 - a1; + out[2] = s2 + a2; + out[6] = s2 - a2; + out[5] = s3 + a3; + out[7] = s3 - a3; + +} + +/* ---------------------------------------------------------------------- + out = vector^T x m, + m -- 3x3 matrix , v -- 3-d vector +------------------------------------------------------------------------- */ + +void MinSpinOSO_LBFGS::vm3(const double *m, const double *v, double *out) +{ + for(int i = 0; i < 3; i++){ + out[i] *= 0.0; + for(int j = 0; j < 3; j++){ + out[i] += *(m + 3 * j + i) * v[j]; + } + } +} diff --git a/src/SPIN/min_spin_oso_lbfgs.h b/src/SPIN/min_spin_oso_lbfgs.h new file mode 100644 index 0000000000..0a06824382 --- /dev/null +++ b/src/SPIN/min_spin_oso_lbfgs.h @@ -0,0 +1,73 @@ +/* -*- c++ -*- ---------------------------------------------------------- + LAMMPS - Large-scale Atomic/Molecular Massively Parallel Simulator + http://lammps.sandia.gov, Sandia National Laboratories + Steve Plimpton, sjplimp@sandia.gov + + Copyright (2003) Sandia Corporation. Under the terms of Contract + DE-AC04-94AL85000 with Sandia Corporation, the U.S. Government retains + certain rights in this software. This software is distributed under + the GNU General Public License. + + See the README file in the top-level LAMMPS directory. +------------------------------------------------------------------------- */ + +#ifdef MINIMIZE_CLASS + +MinimizeStyle(spin/oso_lbfgs, MinSpinOSO_LBFGS) + +#else + +#ifndef LMP_MIN_SPIN_OSO_LBFGS_H +#define LMP_MIN_SPIN_OSO_LBFGS_H + +#include "min.h" + +namespace LAMMPS_NS { + +class MinSpinOSO_LBFGS : public Min { + +public: + MinSpinOSO_LBFGS(class LAMMPS *); + ~MinSpinOSO_LBFGS() {} + void init(); + void setup_style(); + int modify_param(int, char **); + void reset_vectors(); + int iterate(int); + double evaluate_dt(); + void advance_spins(); + double fmnorm_sqr(); + void calc_gradient(double); + void calc_search_direction(int); + +private: + // global and spin timesteps + + double dt; + double dts; + + double alpha_damp; // damping for spin minimization + double discrete_factor; // factor for spin timestep evaluation + + double *spvec; // variables for atomic dof, as 1d vector + double *fmvec; // variables for atomic dof, as 1d vector + + double *g; // gradient vector + double *g_old; // gradient vector at previous step + double *p; // search direction vector + double **ds; // change in rotation matrix between two iterations, da + double **dy; // change in gradients between two iterations, dg + double *rho; // estimation of curvature + int num_mem; // number of stored steps + + + void vm3(const double *m, const double *v, double *out); + void rodrigues_rotation(const double *upp_tr, double *out); + + bigint last_negative; +}; + +} + +#endif +#endif From 89ecd5d9f9e3daa9fb62430a883e896c3c5235e1 Mon Sep 17 00:00:00 2001 From: alxvov Date: Mon, 1 Jul 2019 08:35:41 +0000 Subject: [PATCH 010/192] get rid off double loops in cg --- src/SPIN/min_spin_oso_cg.cpp | 30 +++++++++++------------------- 1 file changed, 11 insertions(+), 19 deletions(-) diff --git a/src/SPIN/min_spin_oso_cg.cpp b/src/SPIN/min_spin_oso_cg.cpp index d6bca32a40..0c628f7567 100644 --- a/src/SPIN/min_spin_oso_cg.cpp +++ b/src/SPIN/min_spin_oso_cg.cpp @@ -329,19 +329,15 @@ void MinSpinOSO_CG::calc_search_direction(int iter) // for some reason on a second iteration g_old = 0 // so we make two iterations as steepest descent - if (iter <= 2 || iter % 5 == 0){ // steepest descent direction - for (int i = 0; i < nlocal; i++) { - for (int j = 0; j < 3; j++){ - p_s[3 * i + j] = -g_cur[3 * i + j]; - g_old[3 * i + j] = g_cur[3 * i + j]; - } + if (iter == 0 || iter % 5 == 0){ // steepest descent direction + for (int i = 0; i < 3 * nlocal; i++) { + p_s[i] = -g_cur[i]; + g_old[i] = g_cur[i]; } } else { // conjugate direction - for (int i = 0; i < nlocal; i++) { - for (int j = 0; j < 3; j++){ - g2old += g_old[3 * i + j] * g_old[3 * i + j]; - g2 += g_cur[3 * i + j] * g_cur[3 * i + j]; - } + for (int i = 0; i < 3 * nlocal; i++) { + g2old += g_old[i] * g_old[i]; + g2 += g_cur[i] * g_cur[i]; } // now we need to collect/broadcast beta on this replica @@ -355,11 +351,9 @@ void MinSpinOSO_CG::calc_search_direction(int iter) // calculate conjugate direction - for (int i = 0; i < nlocal; i++) { - for (int j = 0; j < 3; j++){ - p_s[3 * i + j] = beta * p_s[3 * i + j] - g_cur[3 * i + j]; - g_old[3 * i + j] = g_cur[3 * i + j]; - } + for (int i = 0; i < 3 * nlocal; i++) { + p_s[i] = beta * p_s[i] - g_cur[i]; + g_old[i] = g_cur[i]; } } } @@ -385,9 +379,7 @@ void MinSpinOSO_CG::advance_spins() // rotate spins vm3(rot_mat, sp[i], s_new); - sp[i][0] = s_new[0]; - sp[i][1] = s_new[1]; - sp[i][2] = s_new[2]; + for (int j = 0; j < 3; j++) sp[i][j] = s_new[j]; } } From 0f2997533a258ca0869c57ca3c67b309b1d538d7 Mon Sep 17 00:00:00 2001 From: alxvov Date: Mon, 1 Jul 2019 08:36:44 +0000 Subject: [PATCH 011/192] get rid off double loops in cg --- src/SPIN/min_spin_oso_cg.cpp | 29 ++++++++++------------------- 1 file changed, 10 insertions(+), 19 deletions(-) diff --git a/src/SPIN/min_spin_oso_cg.cpp b/src/SPIN/min_spin_oso_cg.cpp index d6bca32a40..5ea5ad8b6d 100644 --- a/src/SPIN/min_spin_oso_cg.cpp +++ b/src/SPIN/min_spin_oso_cg.cpp @@ -326,22 +326,15 @@ void MinSpinOSO_CG::calc_search_direction(int iter) double g2_global= 0.0; double g2old_global= 0.0; - // for some reason on a second iteration g_old = 0 - // so we make two iterations as steepest descent - - if (iter <= 2 || iter % 5 == 0){ // steepest descent direction - for (int i = 0; i < nlocal; i++) { - for (int j = 0; j < 3; j++){ - p_s[3 * i + j] = -g_cur[3 * i + j]; - g_old[3 * i + j] = g_cur[3 * i + j]; - } + if (iter == 0 || iter % 5 == 0){ // steepest descent direction + for (int i = 0; i < 3 * nlocal; i++) { + p_s[i] = -g_cur[i]; + g_old[i] = g_cur[i]; } } else { // conjugate direction - for (int i = 0; i < nlocal; i++) { - for (int j = 0; j < 3; j++){ - g2old += g_old[3 * i + j] * g_old[3 * i + j]; - g2 += g_cur[3 * i + j] * g_cur[3 * i + j]; - } + for (int i = 0; i < 3 * nlocal; i++) { + g2old += g_old[i] * g_old[i]; + g2 += g_cur[i] * g_cur[i]; } // now we need to collect/broadcast beta on this replica @@ -355,11 +348,9 @@ void MinSpinOSO_CG::calc_search_direction(int iter) // calculate conjugate direction - for (int i = 0; i < nlocal; i++) { - for (int j = 0; j < 3; j++){ - p_s[3 * i + j] = beta * p_s[3 * i + j] - g_cur[3 * i + j]; - g_old[3 * i + j] = g_cur[3 * i + j]; - } + for (int i = 0; i < 3 * nlocal; i++) { + p_s[i] = beta * p_s[i] - g_cur[i]; + g_old[i] = g_cur[i]; } } } From 5f74f6ddfa9aac318a00c17e1afd59f5d3438f15 Mon Sep 17 00:00:00 2001 From: alxvov Date: Mon, 1 Jul 2019 08:38:44 +0000 Subject: [PATCH 012/192] delete irrelevant comment --- src/SPIN/min_spin_oso_cg.cpp | 3 --- 1 file changed, 3 deletions(-) diff --git a/src/SPIN/min_spin_oso_cg.cpp b/src/SPIN/min_spin_oso_cg.cpp index 0c628f7567..4449832f54 100644 --- a/src/SPIN/min_spin_oso_cg.cpp +++ b/src/SPIN/min_spin_oso_cg.cpp @@ -326,9 +326,6 @@ void MinSpinOSO_CG::calc_search_direction(int iter) double g2_global= 0.0; double g2old_global= 0.0; - // for some reason on a second iteration g_old = 0 - // so we make two iterations as steepest descent - if (iter == 0 || iter % 5 == 0){ // steepest descent direction for (int i = 0; i < 3 * nlocal; i++) { p_s[i] = -g_cur[i]; From 6a2a4d5cfb00c51de71e4f59288a73b739cb2da9 Mon Sep 17 00:00:00 2001 From: alxvov Date: Mon, 1 Jul 2019 08:58:31 +0000 Subject: [PATCH 013/192] parallelisation of lbfgs --- src/SPIN/min_spin_oso_lbfgs.cpp | 23 +++++++++++++---------- 1 file changed, 13 insertions(+), 10 deletions(-) diff --git a/src/SPIN/min_spin_oso_lbfgs.cpp b/src/SPIN/min_spin_oso_lbfgs.cpp index f0a4fcbd87..f21245899b 100644 --- a/src/SPIN/min_spin_oso_lbfgs.cpp +++ b/src/SPIN/min_spin_oso_lbfgs.cpp @@ -356,8 +356,8 @@ void MinSpinOSO_LBFGS::calc_search_direction(int iter) dy[m_index][i] = g[i] - g_old[i]; dyds += ds[m_index][i] * dy[m_index][i]; } -// MPI_Allreduce(&dyds, &dyds_global, 1, MPI_DOUBLE, MPI_SUM, world); - if (fabs(dyds) > 1.0e-60) rho[m_index] = 1.0 / dyds; + MPI_Allreduce(&dyds, &dyds_global, 1, MPI_DOUBLE, MPI_SUM, world); + if (fabs(dyds) > 1.0e-60) rho[m_index] = 1.0 / dyds_global; else rho[m_index] = 1.0e60; // set the q vector @@ -378,10 +378,11 @@ void MinSpinOSO_LBFGS::calc_search_direction(int iter) for (int i = 0; i < 3 * nlocal; i++) { sq += ds[c_ind][i] * q[i]; } + MPI_Allreduce(&sq, &sq_global, 1, MPI_DOUBLE, MPI_SUM, world); // update alpha - alpha[c_ind] = rho[c_ind] * sq; + alpha[c_ind] = rho[c_ind] * sq_global; // update q @@ -395,12 +396,13 @@ void MinSpinOSO_LBFGS::calc_search_direction(int iter) for (int i = 0; i < 3 * nlocal; i++) { yy += dy[m_index][i] * dy[m_index][i]; } + MPI_Allreduce(&yy, &yy_global, 1, MPI_DOUBLE, MPI_SUM, world); - // calculate now search direction + // calculate now search direction - if (fabs(yy) > 1.0e-60) { + if (fabs(yy_global) > 1.0e-60) { for (int i = 0; i < 3 * nlocal; i++) { - p[i] = q[i] / (rho[m_index] * yy); + p[i] = q[i] / (rho[m_index] * yy_global); } }else{ for (int i = 0; i < 3 * nlocal; i++) { @@ -419,8 +421,9 @@ void MinSpinOSO_LBFGS::calc_search_direction(int iter) for (int i = 0; i < 3 * nlocal; i++) { yr += dy[c_ind][i] * p[i]; } + MPI_Allreduce(&yr, &yr_global, 1, MPI_DOUBLE, MPI_SUM, world); - beta = rho[c_ind] * yr; + beta = rho[c_ind] * yr_global; for (int i = 0; i < 3 * nlocal; i++) { p[i] += ds[c_ind][i] * (alpha[c_ind] - beta); } @@ -514,7 +517,7 @@ void MinSpinOSO_LBFGS::rodrigues_rotation(const double *upp_tr, double *out) if (fabs(upp_tr[0]) < 1.0e-40 && fabs(upp_tr[1]) < 1.0e-40 && fabs(upp_tr[2]) < 1.0e-40){ - + // if upp_tr is zero, return unity matrix for(int k = 0; k < 3; k++){ for(int m = 0; m < 3; m++){ @@ -537,13 +540,13 @@ void MinSpinOSO_LBFGS::rodrigues_rotation(const double *upp_tr, double *out) double z = upp_tr[2]/theta; // diagonal elements of U - + out[0] = A + z * z * D; out[4] = A + y * y * D; out[8] = A + x * x * D; // off diagonal of U - + double s1 = -y * z *D; double s2 = x * z * D; double s3 = -x * y * D; From 0a0e85ac46b335e0df5242ee1b635a39adddc1a1 Mon Sep 17 00:00:00 2001 From: alxvov Date: Mon, 1 Jul 2019 09:03:17 +0000 Subject: [PATCH 014/192] rodr. rot. as in cg --- src/SPIN/min_spin_oso_lbfgs.cpp | 38 +++++++++++++++++---------------- 1 file changed, 20 insertions(+), 18 deletions(-) diff --git a/src/SPIN/min_spin_oso_lbfgs.cpp b/src/SPIN/min_spin_oso_lbfgs.cpp index f21245899b..d200e07f4a 100644 --- a/src/SPIN/min_spin_oso_lbfgs.cpp +++ b/src/SPIN/min_spin_oso_lbfgs.cpp @@ -513,6 +513,8 @@ double MinSpinOSO_LBFGS::fmnorm_sqr() void MinSpinOSO_LBFGS::rodrigues_rotation(const double *upp_tr, double *out) { + double theta,A,B,D,x,y,z; + double s1,s2,s3,a1,a2,a3; if (fabs(upp_tr[0]) < 1.0e-40 && fabs(upp_tr[1]) < 1.0e-40 && @@ -521,23 +523,23 @@ void MinSpinOSO_LBFGS::rodrigues_rotation(const double *upp_tr, double *out) // if upp_tr is zero, return unity matrix for(int k = 0; k < 3; k++){ for(int m = 0; m < 3; m++){ - if (m == k) out[3 * k + m] = 1.0; - else out[3 * k + m] = 0.0; - } + if (m == k) out[3 * k + m] = 1.0; + else out[3 * k + m] = 0.0; + } } return; } - double theta = sqrt(upp_tr[0] * upp_tr[0] + - upp_tr[1] * upp_tr[1] + - upp_tr[2] * upp_tr[2]); + theta = sqrt(upp_tr[0] * upp_tr[0] + + upp_tr[1] * upp_tr[1] + + upp_tr[2] * upp_tr[2]); - double A = cos(theta); - double B = sin(theta); - double D = 1 - A; - double x = upp_tr[0]/theta; - double y = upp_tr[1]/theta; - double z = upp_tr[2]/theta; + A = cos(theta); + B = sin(theta); + D = 1 - A; + x = upp_tr[0]/theta; + y = upp_tr[1]/theta; + z = upp_tr[2]/theta; // diagonal elements of U @@ -547,13 +549,13 @@ void MinSpinOSO_LBFGS::rodrigues_rotation(const double *upp_tr, double *out) // off diagonal of U - double s1 = -y * z *D; - double s2 = x * z * D; - double s3 = -x * y * D; + s1 = -y * z *D; + s2 = x * z * D; + s3 = -x * y * D; - double a1 = x * B; - double a2 = y * B; - double a3 = z * B; + a1 = x * B; + a2 = y * B; + a3 = z * B; out[1] = s1 + a1; out[3] = s1 - a1; From 1d64d78f240b3bc8a26872ba1cb78b5a83772b45 Mon Sep 17 00:00:00 2001 From: alxvov Date: Mon, 1 Jul 2019 09:40:14 +0000 Subject: [PATCH 015/192] handle memory in a right way --- src/SPIN/min_spin_oso_lbfgs.cpp | 93 ++++++++++++++++++--------------- 1 file changed, 52 insertions(+), 41 deletions(-) diff --git a/src/SPIN/min_spin_oso_lbfgs.cpp b/src/SPIN/min_spin_oso_lbfgs.cpp index d200e07f4a..1143786d73 100644 --- a/src/SPIN/min_spin_oso_lbfgs.cpp +++ b/src/SPIN/min_spin_oso_lbfgs.cpp @@ -34,13 +34,11 @@ #include "output.h" #include "timer.h" #include "error.h" +#include "memory.h" #include "modify.h" #include "math_special.h" #include "math_const.h" -#include -using namespace std; - using namespace LAMMPS_NS; using namespace MathConst; @@ -63,8 +61,23 @@ static const char cite_minstyle_spin_oso_lbfgs[] = /* ---------------------------------------------------------------------- */ -MinSpinOSO_LBFGS::MinSpinOSO_LBFGS(LAMMPS *lmp) : Min(lmp) { +MinSpinOSO_LBFGS::MinSpinOSO_LBFGS(LAMMPS *lmp) : + Min(lmp), g_old(NULL), g_cur(NULL), p_s(NULL), ds(NULL), dy(NULL), rho(NULL) +{ if (lmp->citeme) lmp->citeme->add(cite_minstyle_spin_oso_lbfgs); + nlocal_max = 0; +} + +/* ---------------------------------------------------------------------- */ + +MinSpinOSO_LBFGS::~MinSpinOSO_LBFGS() +{ + memory->destroy(g_old); + memory->destroy(g_cur); + memory->destroy(p_s); + memory->destroy(ds); + memory->destroy(dy); + memory->destroy(rho); } /* ---------------------------------------------------------------------- */ @@ -79,6 +92,17 @@ void MinSpinOSO_LBFGS::init() dts = dt = update->dt; last_negative = update->ntimestep; + + // allocate tables + + nlocal_max = atom->nlocal; + memory->grow(g_old,3*nlocal_max,"min/spin/oso/lbfgs:g_old"); + memory->grow(g_cur,3*nlocal_max,"min/spin/oso/lbfgs:g_cur"); + memory->grow(p_s,3*nlocal_max,"min/spin/oso/lbfgs:p_s"); + memory->grow(rho,num_mem,"min/spin/oso/lbfgs:rho"); + memory->grow(ds,num_mem,3*nlocal_max,"min/spin/oso/lbfgs:ds"); + memory->grow(dy,num_mem,3*nlocal_max,"min/spin/oso/lbfgs:dy"); + } /* ---------------------------------------------------------------------- */ @@ -140,21 +164,19 @@ void MinSpinOSO_LBFGS::reset_vectors() int MinSpinOSO_LBFGS::iterate(int maxiter) { + int nlocal = atom->nlocal; bigint ntimestep; double fmdotfm; int flag, flagall; - // not sure it is best place to allocate memory - int nlocal = atom->nlocal; - g = (double *) calloc(3*nlocal, sizeof(double)); - p = (double *) calloc(3*nlocal, sizeof(double)); - g_old = (double *) calloc(3*nlocal, sizeof(double)); - rho = (double *) calloc(num_mem, sizeof(double)); - ds = (double **) calloc(num_mem, sizeof(double *)); - dy = (double **) calloc(num_mem, sizeof(double *)); - for (int k = 0; k < num_mem; k++){ - ds[k] = (double *) calloc(3*nlocal, sizeof(double)); - dy[k] = (double *) calloc(3*nlocal, sizeof(double)); + if (nlocal_max < nlocal) { + nlocal_max = nlocal; + memory->grow(g_old,3*nlocal_max,"min/spin/oso/cg:g_old"); + memory->grow(g_cur,3*nlocal_max,"min/spin/oso/cg:g_cur"); + memory->grow(p_s,3*nlocal_max,"min/spin/oso/cg:p_s"); + memory->grow(rho,num_mem,"min/spin/oso/lbfgs:rho"); + memory->grow(ds,num_mem,3*nlocal_max,"min/spin/oso/lbfgs:ds"); + memory->grow(dy,num_mem,3*nlocal_max,"min/spin/oso/lbfgs:dy"); } for (int iter = 0; iter < maxiter; iter++) { @@ -222,17 +244,6 @@ int MinSpinOSO_LBFGS::iterate(int maxiter) } } - free(p); - free(g); - free(g_old); - for (int k = 0; k < num_mem; k++){ - free(ds[k]); - free(dy[k]); - } - free(ds); - free(dy); - free(rho); - return MAXITER; } @@ -304,9 +315,9 @@ void MinSpinOSO_LBFGS::calc_gradient(double dts) // calculate gradients - g[3 * i + 0] = -tdampz * dts; - g[3 * i + 1] = tdampy * dts; - g[3 * i + 2] = -tdampx * dts; + g_cur[3 * i + 0] = -tdampz * dts; + g_cur[3 * i + 1] = tdampy * dts; + g_cur[3 * i + 2] = -tdampx * dts; } } @@ -343,8 +354,8 @@ void MinSpinOSO_LBFGS::calc_search_direction(int iter) if (iter == 0){ // steepest descent direction for (int i = 0; i < 3 * nlocal; i++) { - p[i] = -g[i]; - g_old[i] = g[i]; + p_s[i] = -g_cur[i]; + g_old[i] = g_cur[i]; ds[m_index][i] = 0.0; dy[m_index][i] = 0.0; @@ -352,8 +363,8 @@ void MinSpinOSO_LBFGS::calc_search_direction(int iter) } else { dyds = 0.0; for (int i = 0; i < 3 * nlocal; i++) { - ds[m_index][i] = p[i]; - dy[m_index][i] = g[i] - g_old[i]; + ds[m_index][i] = p_s[i]; + dy[m_index][i] = g_cur[i] - g_old[i]; dyds += ds[m_index][i] * dy[m_index][i]; } MPI_Allreduce(&dyds, &dyds_global, 1, MPI_DOUBLE, MPI_SUM, world); @@ -363,7 +374,7 @@ void MinSpinOSO_LBFGS::calc_search_direction(int iter) // set the q vector for (int i = 0; i < 3 * nlocal; i++) { - q[i] = g[i]; + q[i] = g_cur[i]; } // loop over last m indecies @@ -402,11 +413,11 @@ void MinSpinOSO_LBFGS::calc_search_direction(int iter) if (fabs(yy_global) > 1.0e-60) { for (int i = 0; i < 3 * nlocal; i++) { - p[i] = q[i] / (rho[m_index] * yy_global); + p_s[i] = q[i] / (rho[m_index] * yy_global); } }else{ for (int i = 0; i < 3 * nlocal; i++) { - p[i] = q[i] * 1.0e60; + p_s[i] = q[i] * 1.0e60; } } @@ -419,18 +430,18 @@ void MinSpinOSO_LBFGS::calc_search_direction(int iter) // dot product between p and da yr = 0.0; for (int i = 0; i < 3 * nlocal; i++) { - yr += dy[c_ind][i] * p[i]; + yr += dy[c_ind][i] * p_s[i]; } MPI_Allreduce(&yr, &yr_global, 1, MPI_DOUBLE, MPI_SUM, world); beta = rho[c_ind] * yr_global; for (int i = 0; i < 3 * nlocal; i++) { - p[i] += ds[c_ind][i] * (alpha[c_ind] - beta); + p_s[i] += ds[c_ind][i] * (alpha[c_ind] - beta); } } for (int i = 0; i < 3 * nlocal; i++) { - p[i] = -1.0 * p[i]; - g_old[i] = g[i]; + p_s[i] = -1.0 * p_s[i]; + g_old[i] = g_cur[i]; } } @@ -455,7 +466,7 @@ void MinSpinOSO_LBFGS::advance_spins() // loop on all spins on proc. for (int i = 0; i < nlocal; i++) { - rodrigues_rotation(p + 3 * i, rot_mat); + rodrigues_rotation(p_s + 3 * i, rot_mat); // rotate spins From 56c34e42670b7b2c079d462e480f17afe4508cb1 Mon Sep 17 00:00:00 2001 From: alxvov Date: Mon, 1 Jul 2019 09:41:34 +0000 Subject: [PATCH 016/192] merge memory alloc for lbfgs --- src/SPIN/min_spin_oso_lbfgs.h | 7 ++++--- 1 file changed, 4 insertions(+), 3 deletions(-) diff --git a/src/SPIN/min_spin_oso_lbfgs.h b/src/SPIN/min_spin_oso_lbfgs.h index 0a06824382..3aa326142c 100644 --- a/src/SPIN/min_spin_oso_lbfgs.h +++ b/src/SPIN/min_spin_oso_lbfgs.h @@ -28,7 +28,7 @@ class MinSpinOSO_LBFGS : public Min { public: MinSpinOSO_LBFGS(class LAMMPS *); - ~MinSpinOSO_LBFGS() {} + virtual ~MinSpinOSO_LBFGS(); void init(); void setup_style(); int modify_param(int, char **); @@ -43,6 +43,7 @@ public: private: // global and spin timesteps + int nlocal_max; // max value of nlocal (for size of lists) double dt; double dts; @@ -52,9 +53,9 @@ private: double *spvec; // variables for atomic dof, as 1d vector double *fmvec; // variables for atomic dof, as 1d vector - double *g; // gradient vector + double *g_cur; // current gradient vector double *g_old; // gradient vector at previous step - double *p; // search direction vector + double *p_s; // search direction vector double **ds; // change in rotation matrix between two iterations, da double **dy; // change in gradients between two iterations, dg double *rho; // estimation of curvature From 924c610ebe69ae10656cd9ba70cc05f2723c900f Mon Sep 17 00:00:00 2001 From: alxvov Date: Mon, 1 Jul 2019 09:45:05 +0000 Subject: [PATCH 017/192] use for loop --- src/SPIN/min_spin_oso_lbfgs.cpp | 4 +--- 1 file changed, 1 insertion(+), 3 deletions(-) diff --git a/src/SPIN/min_spin_oso_lbfgs.cpp b/src/SPIN/min_spin_oso_lbfgs.cpp index 1143786d73..f3643168a4 100644 --- a/src/SPIN/min_spin_oso_lbfgs.cpp +++ b/src/SPIN/min_spin_oso_lbfgs.cpp @@ -471,9 +471,7 @@ void MinSpinOSO_LBFGS::advance_spins() // rotate spins vm3(rot_mat, sp[i], s_new); - sp[i][0] = s_new[0]; - sp[i][1] = s_new[1]; - sp[i][2] = s_new[2]; + for (int j = 0; j < 3; j++) sp[i][j] = s_new[j]; } } From 398f33d4072576e9237744f95709982c1e6c895a Mon Sep 17 00:00:00 2001 From: alxvov Date: Tue, 2 Jul 2019 16:36:06 +0000 Subject: [PATCH 018/192] added cubic line search --- src/SPIN/min_spin_oso_lbfgs_ls.cpp | 717 +++++++++++++++++++++++++++++ src/SPIN/min_spin_oso_lbfgs_ls.h | 84 ++++ 2 files changed, 801 insertions(+) create mode 100644 src/SPIN/min_spin_oso_lbfgs_ls.cpp create mode 100644 src/SPIN/min_spin_oso_lbfgs_ls.h diff --git a/src/SPIN/min_spin_oso_lbfgs_ls.cpp b/src/SPIN/min_spin_oso_lbfgs_ls.cpp new file mode 100644 index 0000000000..f054755129 --- /dev/null +++ b/src/SPIN/min_spin_oso_lbfgs_ls.cpp @@ -0,0 +1,717 @@ +/* ---------------------------------------------------------------------- + LAMMPS - Large-scale Atomic/Molecular Massively Parallel Simulator + http://lammps.sandia.gov, Sandia National Laboratories + Steve Plimpton, sjplimp@sandia.gov + + Copyright (2003) Sandia Corporation. Under the terms of Contract + DE-AC04-94AL85000 with Sandia Corporation, the U.S. Government retains + certain rights in this software. This software is distributed under + the GNU General Public License. + + See the README file in the top-level LAMMPS directory. +------------------------------------------------------------------------- */ + +/* ------------------------------------------------------------------------ + Contributing authors: Aleksei Ivanov (UI) + Julien Tranchida (SNL) + + Please cite the related publication: + Ivanov, A. V., Uzdin, V. M., & Jónsson, H. (2019). Fast and Robust + Algorithm for the Minimisation of the Energy of Spin Systems. arXiv + preprint arXiv:1904.02669. +------------------------------------------------------------------------- */ + +#include +#include +#include +#include +#include "min_spin_oso_lbfgs_ls.h" +#include "universe.h" +#include "atom.h" +#include "citeme.h" +#include "force.h" +#include "update.h" +#include "output.h" +#include "timer.h" +#include "error.h" +#include "memory.h" +#include "modify.h" +#include "math_special.h" +#include "math_const.h" +#include + + +using namespace LAMMPS_NS; +using namespace MathConst; + +static const char cite_minstyle_spin_oso_lbfgs_ls[] = + "min_style spin/oso_lbfgs_ls command:\n\n" + "@article{ivanov2019fast,\n" + "title={Fast and Robust Algorithm for the Minimisation of the Energy of " + "Spin Systems},\n" + "author={Ivanov, A. V and Uzdin, V. M. and J{\'o}nsson, H.},\n" + "journal={arXiv preprint arXiv:1904.02669},\n" + "year={2019}\n" + "}\n\n"; + +// EPS_ENERGY = minimum normalization for energy tolerance + +#define EPS_ENERGY 1.0e-8 + +#define DELAYSTEP 5 + + +/* ---------------------------------------------------------------------- */ + +MinSpinOSO_LBFGS_LS::MinSpinOSO_LBFGS_LS(LAMMPS *lmp) : + Min(lmp), g_old(NULL), g_cur(NULL), p_s(NULL), ds(NULL), dy(NULL), rho(NULL) +{ + if (lmp->citeme) lmp->citeme->add(cite_minstyle_spin_oso_lbfgs_ls); + nlocal_max = 0; +} + +/* ---------------------------------------------------------------------- */ + +MinSpinOSO_LBFGS_LS::~MinSpinOSO_LBFGS_LS() +{ + memory->destroy(g_old); + memory->destroy(g_cur); + memory->destroy(p_s); + memory->destroy(ds); + memory->destroy(dy); + memory->destroy(rho); + memory->destroy(sp_copy); +} + +/* ---------------------------------------------------------------------- */ + +void MinSpinOSO_LBFGS_LS::init() +{ + alpha_damp = 1.0; + discrete_factor = 10.0; + num_mem = 3; + der_e_cur = 0.0; + der_e_pr = 0.0; + use_line_search = 1; + + Min::init(); + + dts = dt = update->dt; + last_negative = update->ntimestep; + + // allocate tables + + nlocal_max = atom->nlocal; + memory->grow(g_old,3*nlocal_max,"min/spin/oso/lbfgs_ls:g_old"); + memory->grow(g_cur,3*nlocal_max,"min/spin/oso/lbfgs_ls:g_cur"); + memory->grow(p_s,3*nlocal_max,"min/spin/oso/lbfgs_ls:p_s"); + memory->grow(rho,num_mem,"min/spin/oso/lbfgs_ls:rho"); + memory->grow(ds,num_mem,3*nlocal_max,"min/spin/oso/lbfgs_ls:ds"); + memory->grow(dy,num_mem,3*nlocal_max,"min/spin/oso/lbfgs_ls:dy"); + memory->grow(sp_copy,nlocal_max,3,"min/spin/oso/lbfgs_ls:sp_copy"); + +} + +/* ---------------------------------------------------------------------- */ + +void MinSpinOSO_LBFGS_LS::setup_style() +{ + double **v = atom->v; + int nlocal = atom->nlocal; + + // check if the atom/spin style is defined + + if (!atom->sp_flag) + error->all(FLERR,"min/spin_oso_lbfgs_ls requires atom/spin style"); + + for (int i = 0; i < nlocal; i++) + v[i][0] = v[i][1] = v[i][2] = 0.0; +} + +/* ---------------------------------------------------------------------- */ + +int MinSpinOSO_LBFGS_LS::modify_param(int narg, char **arg) +{ + if (strcmp(arg[0],"alpha_damp") == 0) { + if (narg < 2) error->all(FLERR,"Illegal fix_modify command"); + alpha_damp = force->numeric(FLERR,arg[1]); + return 2; + } + if (strcmp(arg[0],"discrete_factor") == 0) { + if (narg < 2) error->all(FLERR,"Illegal fix_modify command"); + discrete_factor = force->numeric(FLERR,arg[1]); + return 2; + } + return 0; +} + +/* ---------------------------------------------------------------------- + set current vector lengths and pointers + called after atoms have migrated +------------------------------------------------------------------------- */ + +void MinSpinOSO_LBFGS_LS::reset_vectors() +{ + // atomic dof + + // size sp is 4N vector + nvec = 4 * atom->nlocal; + if (nvec) spvec = atom->sp[0]; + + nvec = 3 * atom->nlocal; + if (nvec) fmvec = atom->fm[0]; + + if (nvec) xvec = atom->x[0]; + if (nvec) fvec = atom->f[0]; +} + +/* ---------------------------------------------------------------------- + minimization via damped spin dynamics +------------------------------------------------------------------------- */ + +int MinSpinOSO_LBFGS_LS::iterate(int maxiter) +{ + int nlocal = atom->nlocal; + bigint ntimestep; + double fmdotfm; + int flag, flagall; + double **sp = atom->sp; + + if (nlocal_max < nlocal) { + nlocal_max = nlocal; + memory->grow(g_old,3*nlocal_max,"min/spin/oso/lbfgs_ls:g_old"); + memory->grow(g_cur,3*nlocal_max,"min/spin/oso/lbfgs_ls:g_cur"); + memory->grow(p_s,3*nlocal_max,"min/spin/oso/lbfgs_ls:p_s"); + memory->grow(rho,num_mem,"min/spin/oso/lbfgs_ls:rho"); + memory->grow(ds,num_mem,3*nlocal_max,"min/spin/oso/lbfgs_ls:ds"); + memory->grow(dy,num_mem,3*nlocal_max,"min/spin/oso/lbfgs_ls:dy"); + memory->grow(sp_copy,nlocal_max,3,"min/spin/oso/lbfgs_ls:sp_copy"); + } + + + for (int iter = 0; iter < maxiter; iter++) { + + if (timer->check_timeout(niter)) + return TIMEOUT; + + ntimestep = ++update->ntimestep; + niter++; + + // optimize timestep accross processes / replicas + // need a force calculation for timestep optimization + + if (iter == 0){ + ecurrent = energy_force(0); + calc_gradient(1.0); + neval++; + }else{ + } + calc_search_direction(iter); + + if (use_line_search) { + der_e_cur = 0.0; + for (int i = 0; i < 3 * nlocal; i++) { + der_e_cur += g_cur[i] * p_s[i]; + } + } + + if (use_line_search){ + // here we need to do line search + for (int i = 0; i < nlocal; i++) { + for (int j = 0; j < 3; j++) sp_copy[i][j] = sp[i][j]; + } + eprevious = ecurrent; + der_e_pr = der_e_cur; + + calc_and_make_step(0.0, 1.0, 0); + } + else{ + advance_spins(); + eprevious = ecurrent; + ecurrent = energy_force(0); + neval++; + } + + //// energy tolerance criterion + //// only check after DELAYSTEP elapsed since velocties reset to 0 + //// sync across replicas if running multi-replica minimization + + if (update->etol > 0.0 && ntimestep-last_negative > DELAYSTEP) { + if (update->multireplica == 0) { + if (fabs(ecurrent-eprevious) < + update->etol * 0.5*(fabs(ecurrent) + fabs(eprevious) + EPS_ENERGY)) + return ETOL; + } else { + if (fabs(ecurrent-eprevious) < + update->etol * 0.5*(fabs(ecurrent) + fabs(eprevious) + EPS_ENERGY)) + flag = 0; + else flag = 1; + MPI_Allreduce(&flag,&flagall,1,MPI_INT,MPI_SUM,universe->uworld); + if (flagall == 0) return ETOL; + } + } + + // magnetic torque tolerance criterion + // sync across replicas if running multi-replica minimization + + if (update->ftol > 0.0) { + fmdotfm = fmnorm_sqr(); + if (update->multireplica == 0) { + if (fmdotfm < update->ftol*update->ftol) return FTOL; + } else { + if (fmdotfm < update->ftol*update->ftol) flag = 0; + else flag = 1; + MPI_Allreduce(&flag,&flagall,1,MPI_INT,MPI_SUM,universe->uworld); + if (flagall == 0) return FTOL; + } + } + + // output for thermo, dump, restart files + + if (output->next == ntimestep) { + timer->stamp(); + output->write(ntimestep); + timer->stamp(Timer::OUTPUT); + } + } + + return MAXITER; +} + +/* ---------------------------------------------------------------------- + evaluate max timestep +---------------------------------------------------------------------- */ + +double MinSpinOSO_LBFGS_LS::evaluate_dt() +{ + double dtmax; + double fmsq; + double fmaxsqone,fmaxsqloc,fmaxsqall; + int nlocal = atom->nlocal; + double **fm = atom->fm; + + // finding max fm on this proc. + + fmsq = fmaxsqone = fmaxsqloc = fmaxsqall = 0.0; + for (int i = 0; i < nlocal; i++) { + fmsq = fm[i][0]*fm[i][0]+fm[i][1]*fm[i][1]+fm[i][2]*fm[i][2]; + fmaxsqone = MAX(fmaxsqone,fmsq); + } + + // finding max fm on this replica + + fmaxsqloc = fmaxsqone; + MPI_Allreduce(&fmaxsqone,&fmaxsqloc,1,MPI_DOUBLE,MPI_MAX,world); + + // finding max fm over all replicas, if necessary + // this communicator would be invalid for multiprocess replicas + + fmaxsqall = fmaxsqloc; + if (update->multireplica == 1) { + fmaxsqall = fmaxsqloc; + MPI_Allreduce(&fmaxsqloc,&fmaxsqall,1,MPI_DOUBLE,MPI_MAX,universe->uworld); + } + + if (fmaxsqall == 0.0) + error->all(FLERR,"Incorrect fmaxsqall calculation"); + + // define max timestep by dividing by the + // inverse of max frequency by discrete_factor + + dtmax = MY_2PI/(discrete_factor*sqrt(fmaxsqall)); + + return dtmax; +} + +/* ---------------------------------------------------------------------- + calculate gradients +---------------------------------------------------------------------- */ + +void MinSpinOSO_LBFGS_LS::calc_gradient(double dts) +{ + int nlocal = atom->nlocal; + double **sp = atom->sp; + double **fm = atom->fm; + double tdampx, tdampy, tdampz; + + // loop on all spins on proc. + + for (int i = 0; i < nlocal; i++) { + + // calc. damping torque + + tdampx = -alpha_damp*(fm[i][1]*sp[i][2] - fm[i][2]*sp[i][1]); + tdampy = -alpha_damp*(fm[i][2]*sp[i][0] - fm[i][0]*sp[i][2]); + tdampz = -alpha_damp*(fm[i][0]*sp[i][1] - fm[i][1]*sp[i][0]); + + // calculate gradients + + g_cur[3 * i + 0] = -tdampz * dts; + g_cur[3 * i + 1] = tdampy * dts; + g_cur[3 * i + 2] = -tdampx * dts; + } +} + +/* ---------------------------------------------------------------------- + search direction +---------------------------------------------------------------------- */ + +void MinSpinOSO_LBFGS_LS::calc_search_direction(int iter) +{ + int nlocal = atom->nlocal; + + double dyds = 0.0; + double sq = 0.0; + double yy = 0.0; + double yr = 0.0; + double beta = 0.0; + + double dyds_global = 0.0; + double sq_global = 0.0; + double yy_global = 0.0; + double yr_global = 0.0; + double beta_global = 0.0; + + int m_index = iter % num_mem; // memory index + int c_ind = 0; + double *q; + double *alpha; + + q = (double *) calloc(3*nlocal, sizeof(double)); + alpha = (double *) calloc(num_mem, sizeof(double)); + + // for some reason on a second iteration g_old = 0 + // so we make two iterations as steepest descent + + if (iter == 0){ // steepest descent direction + for (int i = 0; i < 3 * nlocal; i++) { + p_s[i] = -g_cur[i]; + g_old[i] = g_cur[i]; + ds[m_index][i] = 0.0; + dy[m_index][i] = 0.0; + + } + } else { + dyds = 0.0; + for (int i = 0; i < 3 * nlocal; i++) { + ds[m_index][i] = p_s[i]; + dy[m_index][i] = g_cur[i] - g_old[i]; + dyds += ds[m_index][i] * dy[m_index][i]; + } + MPI_Allreduce(&dyds, &dyds_global, 1, MPI_DOUBLE, MPI_SUM, world); + if (fabs(dyds) > 1.0e-60) rho[m_index] = 1.0 / dyds_global; + else rho[m_index] = 1.0e60; + + // set the q vector + + for (int i = 0; i < 3 * nlocal; i++) { + q[i] = g_cur[i]; + } + + // loop over last m indecies + for(int k = num_mem - 1; k > -1; k--) { + // this loop should run from the newest memory to the oldest one. + + c_ind = (k + m_index + 1) % num_mem; + + // dot product between dg and q + + sq = 0.0; + for (int i = 0; i < 3 * nlocal; i++) { + sq += ds[c_ind][i] * q[i]; + } + MPI_Allreduce(&sq, &sq_global, 1, MPI_DOUBLE, MPI_SUM, world); + + // update alpha + + alpha[c_ind] = rho[c_ind] * sq_global; + + // update q + + for (int i = 0; i < 3 * nlocal; i++) { + q[i] -= alpha[c_ind] * dy[c_ind][i]; + } + } + + // dot product between dg with itself + yy = 0.0; + for (int i = 0; i < 3 * nlocal; i++) { + yy += dy[m_index][i] * dy[m_index][i]; + } + MPI_Allreduce(&yy, &yy_global, 1, MPI_DOUBLE, MPI_SUM, world); + + // calculate now search direction + + if (fabs(yy_global) > 1.0e-60) { + for (int i = 0; i < 3 * nlocal; i++) { + p_s[i] = q[i] / (rho[m_index] * yy_global); + } + }else{ + for (int i = 0; i < 3 * nlocal; i++) { + p_s[i] = q[i] * 1.0e60; + } + } + + for (int k = 0; k < num_mem; k++){ + // this loop should run from the oldest memory to the newest one. + + if (iter < num_mem) c_ind = k; + else c_ind = (k + m_index + 1) % num_mem; + + // dot product between p and da + yr = 0.0; + for (int i = 0; i < 3 * nlocal; i++) { + yr += dy[c_ind][i] * p_s[i]; + } + MPI_Allreduce(&yr, &yr_global, 1, MPI_DOUBLE, MPI_SUM, world); + + beta = rho[c_ind] * yr_global; + for (int i = 0; i < 3 * nlocal; i++) { + p_s[i] += ds[c_ind][i] * (alpha[c_ind] - beta); + } + } + for (int i = 0; i < 3 * nlocal; i++) { + p_s[i] = -1.0 * p_s[i]; + g_old[i] = g_cur[i]; + } + } + + free(q); + free(alpha); + +} + +/* ---------------------------------------------------------------------- + rotation of spins along the search direction +---------------------------------------------------------------------- */ + +void MinSpinOSO_LBFGS_LS::advance_spins() +{ + int nlocal = atom->nlocal; + double **sp = atom->sp; + double **fm = atom->fm; + double tdampx, tdampy, tdampz; + double rot_mat[9]; // exponential of matrix made of search direction + double s_new[3]; + + // loop on all spins on proc. + + for (int i = 0; i < nlocal; i++) { + rodrigues_rotation(p_s + 3 * i, rot_mat); + + // rotate spins + + vm3(rot_mat, sp[i], s_new); + for (int j = 0; j < 3; j++) sp[i][j] = s_new[j]; + } +} + +/* ---------------------------------------------------------------------- + compute and return ||mag. torque||_2^2 +------------------------------------------------------------------------- */ + +double MinSpinOSO_LBFGS_LS::fmnorm_sqr() +{ + int nlocal = atom->nlocal; + double tx,ty,tz; + double **sp = atom->sp; + double **fm = atom->fm; + + // calc. magnetic torques + + double local_norm2_sqr = 0.0; + for (int i = 0; i < nlocal; i++) { + tx = (fm[i][1]*sp[i][2] - fm[i][2]*sp[i][1]); + ty = (fm[i][2]*sp[i][0] - fm[i][0]*sp[i][2]); + tz = (fm[i][0]*sp[i][1] - fm[i][1]*sp[i][0]); + + local_norm2_sqr += tx*tx + ty*ty + tz*tz; + } + + // no extra atom calc. for spins + + if (nextra_atom) + error->all(FLERR,"extra atom option not available yet"); + + double norm2_sqr = 0.0; + MPI_Allreduce(&local_norm2_sqr,&norm2_sqr,1,MPI_DOUBLE,MPI_SUM,world); + + return norm2_sqr; +} + +/* ---------------------------------------------------------------------- + calculate 3x3 matrix exponential using Rodrigues' formula + (R. Murray, Z. Li, and S. Shankar Sastry, + A Mathematical Introduction to + Robotic Manipulation (1994), p. 28 and 30). + + upp_tr - vector x, y, z so that one calculate + U = exp(A) with A= [[0, x, y], + [-x, 0, z], + [-y, -z, 0]] +------------------------------------------------------------------------- */ + +void MinSpinOSO_LBFGS_LS::rodrigues_rotation(const double *upp_tr, double *out) +{ + double theta,A,B,D,x,y,z; + double s1,s2,s3,a1,a2,a3; + + if (fabs(upp_tr[0]) < 1.0e-40 && + fabs(upp_tr[1]) < 1.0e-40 && + fabs(upp_tr[2]) < 1.0e-40){ + + // if upp_tr is zero, return unity matrix + for(int k = 0; k < 3; k++){ + for(int m = 0; m < 3; m++){ + if (m == k) out[3 * k + m] = 1.0; + else out[3 * k + m] = 0.0; + } + } + return; + } + + theta = sqrt(upp_tr[0] * upp_tr[0] + + upp_tr[1] * upp_tr[1] + + upp_tr[2] * upp_tr[2]); + + A = cos(theta); + B = sin(theta); + D = 1 - A; + x = upp_tr[0]/theta; + y = upp_tr[1]/theta; + z = upp_tr[2]/theta; + + // diagonal elements of U + + out[0] = A + z * z * D; + out[4] = A + y * y * D; + out[8] = A + x * x * D; + + // off diagonal of U + + s1 = -y * z *D; + s2 = x * z * D; + s3 = -x * y * D; + + a1 = x * B; + a2 = y * B; + a3 = z * B; + + out[1] = s1 + a1; + out[3] = s1 - a1; + out[2] = s2 + a2; + out[6] = s2 - a2; + out[5] = s3 + a3; + out[7] = s3 - a3; + +} + +/* ---------------------------------------------------------------------- + out = vector^T x m, + m -- 3x3 matrix , v -- 3-d vector +------------------------------------------------------------------------- */ + +void MinSpinOSO_LBFGS_LS::vm3(const double *m, const double *v, double *out) +{ + for(int i = 0; i < 3; i++){ + out[i] *= 0.0; + for(int j = 0; j < 3; j++){ + out[i] += *(m + 3 * j + i) * v[j]; + } + } +} + + +void MinSpinOSO_LBFGS_LS::make_step(double c, double *energy_and_der) +{ + double p_scaled[3]; + int nlocal = atom->nlocal; + double rot_mat[9]; // exponential of matrix made of search direction + double s_new[3]; + double **sp = atom->sp; + + for (int i = 0; i < nlocal; i++) { + + // scale the search direction + + for (int j = 0; j < 3; j++) p_scaled[j] = c * p_s[3 * i + j]; + + // calculate rotation matrix + + rodrigues_rotation(p_scaled, rot_mat); + + // rotate spins + + vm3(rot_mat, sp[i], s_new); + for (int j = 0; j < 3; j++) sp[i][j] = s_new[j]; + } + + ecurrent = energy_force(0); + calc_gradient(1.0); + neval++; + der_e_cur = 0.0; + for (int i = 0; i < 3 * nlocal; i++) { + der_e_cur += g_cur[i] * p_s[i]; + } + energy_and_der[0] = ecurrent; + energy_and_der[1] = der_e_cur; +} + + +int MinSpinOSO_LBFGS_LS::calc_and_make_step(double a, double b, int index) +{ + double e_and_d[2] = {0.0, 0.0}; + double alpha, c1, c2, c3; + double **sp = atom->sp; + int nlocal = atom->nlocal; + + make_step(b, e_and_d); + ecurrent = e_and_d[0]; + der_e_cur = e_and_d[1]; + index++; + + if (awc(der_e_pr, eprevious, e_and_d[1], e_and_d[0]) || index == 3){ + + for (int i = 0; i < 3 * nlocal; i++) { + p_s[i] = b * p_s[i]; + } + return 1; + } + else{ + double r, f0, f1, df0, df1; + r = b - a; + f0 = eprevious; + f1 = ecurrent; + df0 = der_e_pr; + df1 = der_e_cur; + + c1 = -2.0*(f1-f0)/(r*r*r)+(df1+df0)/(r*r); + c2 = 3.0*(f1-f0)/(r*r)-(df1+2.0*df0)/(r); + c3 = df0; + + alpha = (-c2 + sqrt(c2*c2 - 3.0*c1*c3))/(3.0*c1); + if (alpha < 0.0) alpha = r/2.0; + + for (int i = 0; i < nlocal; i++) { + for (int j = 0; j < 3; j++) sp[i][j] = sp_copy[i][j]; + } + calc_and_make_step(0.0, alpha, index); + } + + return 0; + +} + + +int MinSpinOSO_LBFGS_LS::awc(double der_phi_0, double phi_0, double der_phi_j, double phi_j){ + + double eps = 1.0e-6; + double delta = 0.1; + double sigma = 0.9; + + if ((phi_j <= phi_0 + eps * fabs(phi_0)) && + ((2.0*delta - 1.0) * der_phi_0 >= der_phi_j >= sigma * der_phi_0)) + return 1; + else + return 0; +} diff --git a/src/SPIN/min_spin_oso_lbfgs_ls.h b/src/SPIN/min_spin_oso_lbfgs_ls.h new file mode 100644 index 0000000000..3e0e608ecb --- /dev/null +++ b/src/SPIN/min_spin_oso_lbfgs_ls.h @@ -0,0 +1,84 @@ +/* -*- c++ -*- ---------------------------------------------------------- + LAMMPS - Large-scale Atomic/Molecular Massively Parallel Simulator + http://lammps.sandia.gov, Sandia National Laboratories + Steve Plimpton, sjplimp@sandia.gov + + Copyright (2003) Sandia Corporation. Under the terms of Contract + DE-AC04-94AL85000 with Sandia Corporation, the U.S. Government retains + certain rights in this software. This software is distributed under + the GNU General Public License. + + See the README file in the top-level LAMMPS directory. +------------------------------------------------------------------------- */ + +#ifdef MINIMIZE_CLASS + +MinimizeStyle(spin/oso_lbfgs_ls, MinSpinOSO_LBFGS_LS) + +#else + +#ifndef LMP_MIN_SPIN_OSO_LBFGS_LS_H +#define LMP_MIN_SPIN_OSO_LBFGS_LS_H + +#include "min.h" + +namespace LAMMPS_NS { + +class MinSpinOSO_LBFGS_LS : public Min { + +public: + MinSpinOSO_LBFGS_LS(class LAMMPS *); + virtual ~MinSpinOSO_LBFGS_LS(); + void init(); + void setup_style(); + int modify_param(int, char **); + void reset_vectors(); + int iterate(int); + double evaluate_dt(); + void advance_spins(); + double fmnorm_sqr(); + void calc_gradient(double); + void calc_search_direction(int); + +private: + // global and spin timesteps + + int nlocal_max; // max value of nlocal (for size of lists) + double dt; + double dts; + + double alpha_damp; // damping for spin minimization + double discrete_factor; // factor for spin timestep evaluation + + double *spvec; // variables for atomic dof, as 1d vector + double *fmvec; // variables for atomic dof, as 1d vector + + double *g_cur; // current gradient vector + double *g_old; // gradient vector at previous step + double *p_s; // search direction vector + double **ds; // change in rotation matrix between two iterations, da + double **dy; // change in gradients between two iterations, dg + double *rho; // estimation of curvature + double **sp_copy; // copy of the spins + + int num_mem; // number of stored steps + + double der_e_cur; // current derivative along search dir. + double der_e_pr; // previous derivative along search dir. + + int use_line_search; // use line search or not. + + + void vm3(const double *, const double *, double *); + void rodrigues_rotation(const double *, double *); + int calc_and_make_step(double, double, int); + int awc(double, double, double, double); + void make_step(double, double *); + + bigint last_negative; +}; + +} + +#endif +#endif From ee8d3ced31fb88bc0356fd55e52053106495ad0a Mon Sep 17 00:00:00 2001 From: alxvov Date: Tue, 2 Jul 2019 16:39:27 +0000 Subject: [PATCH 019/192] change cg to lbfgs in oso_lbfgs --- src/SPIN/min_spin_oso_lbfgs.cpp | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/src/SPIN/min_spin_oso_lbfgs.cpp b/src/SPIN/min_spin_oso_lbfgs.cpp index f3643168a4..2283a55e51 100644 --- a/src/SPIN/min_spin_oso_lbfgs.cpp +++ b/src/SPIN/min_spin_oso_lbfgs.cpp @@ -171,9 +171,9 @@ int MinSpinOSO_LBFGS::iterate(int maxiter) if (nlocal_max < nlocal) { nlocal_max = nlocal; - memory->grow(g_old,3*nlocal_max,"min/spin/oso/cg:g_old"); - memory->grow(g_cur,3*nlocal_max,"min/spin/oso/cg:g_cur"); - memory->grow(p_s,3*nlocal_max,"min/spin/oso/cg:p_s"); + memory->grow(g_old,3*nlocal_max,"min/spin/oso/lbfgs:g_old"); + memory->grow(g_cur,3*nlocal_max,"min/spin/oso/lbfgs:g_cur"); + memory->grow(p_s,3*nlocal_max,"min/spin/oso/lbfgs:p_s"); memory->grow(rho,num_mem,"min/spin/oso/lbfgs:rho"); memory->grow(ds,num_mem,3*nlocal_max,"min/spin/oso/lbfgs:ds"); memory->grow(dy,num_mem,3*nlocal_max,"min/spin/oso/lbfgs:dy"); From fd5bc857b24f3d62944c45f0d55542deba473aeb Mon Sep 17 00:00:00 2001 From: alxvov Date: Tue, 2 Jul 2019 17:03:15 +0000 Subject: [PATCH 020/192] calculate energy in the beginning only once --- src/SPIN/min_spin.cpp | 2 +- src/SPIN/min_spin_oso_cg.cpp | 4 ++-- src/SPIN/min_spin_oso_lbfgs.cpp | 2 +- 3 files changed, 4 insertions(+), 4 deletions(-) diff --git a/src/SPIN/min_spin.cpp b/src/SPIN/min_spin.cpp index 2bddc110e7..2277281e80 100644 --- a/src/SPIN/min_spin.cpp +++ b/src/SPIN/min_spin.cpp @@ -133,7 +133,7 @@ int MinSpin::iterate(int maxiter) // optimize timestep accross processes / replicas // need a force calculation for timestep optimization - energy_force(0); + if (iter == 0) energy_force(0); dts = evaluate_dt(); // apply damped precessional dynamics to the spins diff --git a/src/SPIN/min_spin_oso_cg.cpp b/src/SPIN/min_spin_oso_cg.cpp index 4449832f54..9ed2cb96ea 100644 --- a/src/SPIN/min_spin_oso_cg.cpp +++ b/src/SPIN/min_spin_oso_cg.cpp @@ -180,8 +180,8 @@ int MinSpinOSO_CG::iterate(int maxiter) // optimize timestep accross processes / replicas // need a force calculation for timestep optimization - - energy_force(0); + + if (iter == 0) energy_force(0); dts = evaluate_dt(); calc_gradient(dts); diff --git a/src/SPIN/min_spin_oso_lbfgs.cpp b/src/SPIN/min_spin_oso_lbfgs.cpp index 2283a55e51..b54c42ebfd 100644 --- a/src/SPIN/min_spin_oso_lbfgs.cpp +++ b/src/SPIN/min_spin_oso_lbfgs.cpp @@ -190,7 +190,7 @@ int MinSpinOSO_LBFGS::iterate(int maxiter) // optimize timestep accross processes / replicas // need a force calculation for timestep optimization - energy_force(0); + if (iter == 0) energy_force(0); // dts = evaluate_dt(); // dts = 1.0; calc_gradient(1.0); From 44ca54fa25cc90f772c352ee0bfa75bad687a16e Mon Sep 17 00:00:00 2001 From: alxvov Date: Tue, 2 Jul 2019 17:06:53 +0000 Subject: [PATCH 021/192] a bit more comments --- src/SPIN/min_spin_oso_cg.cpp | 7 +++++-- src/SPIN/min_spin_oso_lbfgs.cpp | 7 +++++-- 2 files changed, 10 insertions(+), 4 deletions(-) diff --git a/src/SPIN/min_spin_oso_cg.cpp b/src/SPIN/min_spin_oso_cg.cpp index 9ed2cb96ea..8d03ada45d 100644 --- a/src/SPIN/min_spin_oso_cg.cpp +++ b/src/SPIN/min_spin_oso_cg.cpp @@ -12,7 +12,7 @@ ------------------------------------------------------------------------- */ /* ------------------------------------------------------------------------ - Contributing authors: Aleksei Ivanov (UI) + Contributing authors: Aleksei Ivanov (University of Iceland) Julien Tranchida (SNL) Please cite the related publication: @@ -313,7 +313,10 @@ void MinSpinOSO_CG::calc_gradient(double dts) } /* ---------------------------------------------------------------------- - search direction + search direction: + The Fletcher-Reeves conj. grad. method + See Jorge Nocedal and Stephen J. Wright 'Numerical + Optimization' Second Edition, 2006 (p. 121) ---------------------------------------------------------------------- */ void MinSpinOSO_CG::calc_search_direction(int iter) diff --git a/src/SPIN/min_spin_oso_lbfgs.cpp b/src/SPIN/min_spin_oso_lbfgs.cpp index b54c42ebfd..81c36d5e32 100644 --- a/src/SPIN/min_spin_oso_lbfgs.cpp +++ b/src/SPIN/min_spin_oso_lbfgs.cpp @@ -12,7 +12,7 @@ ------------------------------------------------------------------------- */ /* ------------------------------------------------------------------------ - Contributing authors: Aleksei Ivanov (UI) + Contributing authors: Aleksei Ivanov (University of Iceland) Julien Tranchida (SNL) Please cite the related publication: @@ -322,7 +322,10 @@ void MinSpinOSO_LBFGS::calc_gradient(double dts) } /* ---------------------------------------------------------------------- - search direction + search direction: + Limited-memory BFGS. + See Jorge Nocedal and Stephen J. Wright 'Numerical + Optimization' Second Edition, 2006 (p. 177) ---------------------------------------------------------------------- */ void MinSpinOSO_LBFGS::calc_search_direction(int iter) From e3ed8d856209b3f7116f82b3077660ad4c2893ba Mon Sep 17 00:00:00 2001 From: alxvov Date: Tue, 2 Jul 2019 18:02:22 +0000 Subject: [PATCH 022/192] parallelisation of lbfgs, change indentation, more comments --- src/SPIN/min_spin_oso_lbfgs_ls.cpp | 140 ++++++++++++++++------------- 1 file changed, 79 insertions(+), 61 deletions(-) diff --git a/src/SPIN/min_spin_oso_lbfgs_ls.cpp b/src/SPIN/min_spin_oso_lbfgs_ls.cpp index f054755129..38a557266e 100644 --- a/src/SPIN/min_spin_oso_lbfgs_ls.cpp +++ b/src/SPIN/min_spin_oso_lbfgs_ls.cpp @@ -12,7 +12,7 @@ ------------------------------------------------------------------------- */ /* ------------------------------------------------------------------------ - Contributing authors: Aleksei Ivanov (UI) + Contributing authors: Aleksei Ivanov (University of Iceland) Julien Tranchida (SNL) Please cite the related publication: @@ -176,6 +176,7 @@ int MinSpinOSO_LBFGS_LS::iterate(int maxiter) double fmdotfm; int flag, flagall; double **sp = atom->sp; + double der_e_cur_global = 0.0; if (nlocal_max < nlocal) { nlocal_max = nlocal; @@ -213,6 +214,8 @@ int MinSpinOSO_LBFGS_LS::iterate(int maxiter) for (int i = 0; i < 3 * nlocal; i++) { der_e_cur += g_cur[i] * p_s[i]; } + MPI_Allreduce(&der_e_cur, &der_e_cur_global, 1, MPI_DOUBLE, MPI_SUM, world); + der_e_cur = der_e_cur_global; } if (use_line_search){ @@ -353,7 +356,10 @@ void MinSpinOSO_LBFGS_LS::calc_gradient(double dts) } /* ---------------------------------------------------------------------- - search direction + search direction: + Limited-memory BFGS. + See Jorge Nocedal and Stephen J. Wright 'Numerical + Optimization' Second Edition, 2006 (p. 177) ---------------------------------------------------------------------- */ void MinSpinOSO_LBFGS_LS::calc_search_direction(int iter) @@ -624,26 +630,26 @@ void MinSpinOSO_LBFGS_LS::vm3(const double *m, const double *v, double *out) void MinSpinOSO_LBFGS_LS::make_step(double c, double *energy_and_der) { - double p_scaled[3]; - int nlocal = atom->nlocal; - double rot_mat[9]; // exponential of matrix made of search direction - double s_new[3]; - double **sp = atom->sp; + double p_scaled[3]; + int nlocal = atom->nlocal; + double rot_mat[9]; // exponential of matrix made of search direction + double s_new[3]; + double **sp = atom->sp; + double der_e_cur_global = 0.0;; - for (int i = 0; i < nlocal; i++) { + for (int i = 0; i < nlocal; i++) { + // scale the search direction - // scale the search direction + for (int j = 0; j < 3; j++) p_scaled[j] = c * p_s[3 * i + j]; - for (int j = 0; j < 3; j++) p_scaled[j] = c * p_s[3 * i + j]; + // calculate rotation matrix - // calculate rotation matrix + rodrigues_rotation(p_scaled, rot_mat); - rodrigues_rotation(p_scaled, rot_mat); + // rotate spins - // rotate spins - - vm3(rot_mat, sp[i], s_new); - for (int j = 0; j < 3; j++) sp[i][j] = s_new[j]; + vm3(rot_mat, sp[i], s_new); + for (int j = 0; j < 3; j++) sp[i][j] = s_new[j]; } ecurrent = energy_force(0); @@ -653,65 +659,77 @@ void MinSpinOSO_LBFGS_LS::make_step(double c, double *energy_and_der) for (int i = 0; i < 3 * nlocal; i++) { der_e_cur += g_cur[i] * p_s[i]; } + MPI_Allreduce(&der_e_cur, &der_e_cur_global, 1, MPI_DOUBLE, MPI_SUM, world); + der_e_cur = der_e_cur_global; + energy_and_der[0] = ecurrent; energy_and_der[1] = der_e_cur; } +/* ---------------------------------------------------------------------- + Calculate step length which satisfies approximate Wolfe conditions + using the cubic interpolation +------------------------------------------------------------------------- */ int MinSpinOSO_LBFGS_LS::calc_and_make_step(double a, double b, int index) { - double e_and_d[2] = {0.0, 0.0}; - double alpha, c1, c2, c3; - double **sp = atom->sp; - int nlocal = atom->nlocal; + double e_and_d[2] = {0.0, 0.0}; + double alpha, c1, c2, c3; + double **sp = atom->sp; + int nlocal = atom->nlocal; - make_step(b, e_and_d); - ecurrent = e_and_d[0]; - der_e_cur = e_and_d[1]; - index++; + make_step(b, e_and_d); + ecurrent = e_and_d[0]; + der_e_cur = e_and_d[1]; + index++; - if (awc(der_e_pr, eprevious, e_and_d[1], e_and_d[0]) || index == 3){ + if (awc(der_e_pr, eprevious, e_and_d[1], e_and_d[0]) || index == 3){ + MPI_Bcast(&b,1,MPI_DOUBLE,0,world); - for (int i = 0; i < 3 * nlocal; i++) { - p_s[i] = b * p_s[i]; - } - return 1; + for (int i = 0; i < 3 * nlocal; i++) { + p_s[i] = b * p_s[i]; + } + return 1; + } + else{ + double r, f0, f1, df0, df1; + r = b - a; + f0 = eprevious; + f1 = ecurrent; + df0 = der_e_pr; + df1 = der_e_cur; + + c1 = -2.0*(f1-f0)/(r*r*r)+(df1+df0)/(r*r); + c2 = 3.0*(f1-f0)/(r*r)-(df1+2.0*df0)/(r); + c3 = df0; + + // f(x) = c1 x^3 + c2 x^2 + c3 x^1 + c4 + // has minimum at alpha below. We do not check boundaries. + + alpha = (-c2 + sqrt(c2*c2 - 3.0*c1*c3))/(3.0*c1); + if (alpha < 0.0) alpha = r/2.0; + + for (int i = 0; i < nlocal; i++) { + for (int j = 0; j < 3; j++) sp[i][j] = sp_copy[i][j]; } - else{ - double r, f0, f1, df0, df1; - r = b - a; - f0 = eprevious; - f1 = ecurrent; - df0 = der_e_pr; - df1 = der_e_cur; - - c1 = -2.0*(f1-f0)/(r*r*r)+(df1+df0)/(r*r); - c2 = 3.0*(f1-f0)/(r*r)-(df1+2.0*df0)/(r); - c3 = df0; - - alpha = (-c2 + sqrt(c2*c2 - 3.0*c1*c3))/(3.0*c1); - if (alpha < 0.0) alpha = r/2.0; - - for (int i = 0; i < nlocal; i++) { - for (int j = 0; j < 3; j++) sp[i][j] = sp_copy[i][j]; - } - calc_and_make_step(0.0, alpha, index); - } - - return 0; + calc_and_make_step(0.0, alpha, index); + } + return 0; } - - +/* ---------------------------------------------------------------------- + Approximate Wolfe conditions: + William W. Hager and Hongchao Zhang + SIAM J. optim., 16(1), 170-192. (23 pages) +------------------------------------------------------------------------- */ int MinSpinOSO_LBFGS_LS::awc(double der_phi_0, double phi_0, double der_phi_j, double phi_j){ - double eps = 1.0e-6; - double delta = 0.1; - double sigma = 0.9; + double eps = 1.0e-6; + double delta = 0.1; + double sigma = 0.9; - if ((phi_j <= phi_0 + eps * fabs(phi_0)) && - ((2.0*delta - 1.0) * der_phi_0 >= der_phi_j >= sigma * der_phi_0)) - return 1; - else - return 0; + if ((phi_j <= phi_0 + eps * fabs(phi_0)) && ((2.0*delta - 1.0) * der_phi_0 >= der_phi_j >= sigma * der_phi_0)) + return 1; + else + return 0; } From 66a50419734d343a246ab5ce5a91ea327c4f8ab8 Mon Sep 17 00:00:00 2001 From: julient31 Date: Tue, 2 Jul 2019 16:02:36 -0600 Subject: [PATCH 023/192] Commit1 JT 060219 - added all min/spin tests in src/SPIN/neb_spin.cpp - added lbfgs to .gitignore - commit before pull/merge --- src/.gitignore | 2 ++ src/SPIN/min_spin_oso_lbfgs.cpp | 14 +++++++------- src/SPIN/neb_spin.cpp | 5 +++-- 3 files changed, 12 insertions(+), 9 deletions(-) diff --git a/src/.gitignore b/src/.gitignore index 0d802981f9..f0ac3a1ff9 100644 --- a/src/.gitignore +++ b/src/.gitignore @@ -163,6 +163,8 @@ /min_spin.h /min_spin_oso_cg.cpp /min_spin_oso_cg.h +/min_spin_oso_lbfgs.cpp +/min_spin_oso_lbfgs.h /neb_spin.cpp /neb_spin.h /pair_spin.cpp diff --git a/src/SPIN/min_spin_oso_lbfgs.cpp b/src/SPIN/min_spin_oso_lbfgs.cpp index f3643168a4..23cb3718c8 100644 --- a/src/SPIN/min_spin_oso_lbfgs.cpp +++ b/src/SPIN/min_spin_oso_lbfgs.cpp @@ -361,12 +361,12 @@ void MinSpinOSO_LBFGS::calc_search_direction(int iter) } } else { - dyds = 0.0; - for (int i = 0; i < 3 * nlocal; i++) { - ds[m_index][i] = p_s[i]; - dy[m_index][i] = g_cur[i] - g_old[i]; - dyds += ds[m_index][i] * dy[m_index][i]; - } + dyds = 0.0; + for (int i = 0; i < 3 * nlocal; i++) { + ds[m_index][i] = p_s[i]; + dy[m_index][i] = g_cur[i] - g_old[i]; + dyds += ds[m_index][i] * dy[m_index][i]; + } MPI_Allreduce(&dyds, &dyds_global, 1, MPI_DOUBLE, MPI_SUM, world); if (fabs(dyds) > 1.0e-60) rho[m_index] = 1.0 / dyds_global; else rho[m_index] = 1.0e60; @@ -409,7 +409,7 @@ void MinSpinOSO_LBFGS::calc_search_direction(int iter) } MPI_Allreduce(&yy, &yy_global, 1, MPI_DOUBLE, MPI_SUM, world); - // calculate now search direction + // calculate now search direction if (fabs(yy_global) > 1.0e-60) { for (int i = 0; i < 3 * nlocal; i++) { diff --git a/src/SPIN/neb_spin.cpp b/src/SPIN/neb_spin.cpp index 126cfb09e3..9ab461cbe6 100644 --- a/src/SPIN/neb_spin.cpp +++ b/src/SPIN/neb_spin.cpp @@ -50,6 +50,7 @@ #include "memory.h" #include "error.h" #include "math_const.h" +#include "utils.h" using namespace LAMMPS_NS; using namespace MathConst; @@ -194,8 +195,8 @@ void NEBSpin::run() if (update->minimize->searchflag) error->all(FLERR,"NEBSpin requires damped dynamics minimizer"); - if (strcmp(update->minimize_style,"spin") != 0) - error->all(FLERR,"NEBSpin requires spin minimizer"); + if (!utils::strmatch(update->minimize_style,"^spin")) + error->all(FLERR,"NEBSpin requires a spin minimizer"); // setup regular NEBSpin minimization From 8452afb5120c03dfe941afa6a484b98b7e1c5347 Mon Sep 17 00:00:00 2001 From: alxvov Date: Wed, 3 Jul 2019 11:38:31 +0000 Subject: [PATCH 024/192] compare dyds_global instead --- src/SPIN/min_spin_oso_lbfgs.cpp | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/SPIN/min_spin_oso_lbfgs.cpp b/src/SPIN/min_spin_oso_lbfgs.cpp index 83d537030c..e8ac915d8b 100644 --- a/src/SPIN/min_spin_oso_lbfgs.cpp +++ b/src/SPIN/min_spin_oso_lbfgs.cpp @@ -371,7 +371,7 @@ void MinSpinOSO_LBFGS::calc_search_direction(int iter) dyds += ds[m_index][i] * dy[m_index][i]; } MPI_Allreduce(&dyds, &dyds_global, 1, MPI_DOUBLE, MPI_SUM, world); - if (fabs(dyds) > 1.0e-60) rho[m_index] = 1.0 / dyds_global; + if (fabs(dyds_global) > 1.0e-60) rho[m_index] = 1.0 / dyds_global; else rho[m_index] = 1.0e60; // set the q vector From eaa542b6e78c828756fd83ff82aba113ea36504a Mon Sep 17 00:00:00 2001 From: alxvov Date: Wed, 3 Jul 2019 11:59:54 +0000 Subject: [PATCH 025/192] scale initial gradients with adaptive time step in the beggining, try to use global parameters for lbfgs --- src/SPIN/min_spin_oso_lbfgs.cpp | 29 +++++++++++++++++++++++++---- 1 file changed, 25 insertions(+), 4 deletions(-) diff --git a/src/SPIN/min_spin_oso_lbfgs.cpp b/src/SPIN/min_spin_oso_lbfgs.cpp index e8ac915d8b..a598601532 100644 --- a/src/SPIN/min_spin_oso_lbfgs.cpp +++ b/src/SPIN/min_spin_oso_lbfgs.cpp @@ -190,10 +190,13 @@ int MinSpinOSO_LBFGS::iterate(int maxiter) // optimize timestep accross processes / replicas // need a force calculation for timestep optimization - if (iter == 0) energy_force(0); - // dts = evaluate_dt(); - // dts = 1.0; - calc_gradient(1.0); + if (iter == 0){ + energy_force(0); + dts = evaluate_dt(); + } + else dts = 1.0; + + calc_gradient(dts); calc_search_direction(iter); advance_spins(); @@ -371,6 +374,11 @@ void MinSpinOSO_LBFGS::calc_search_direction(int iter) dyds += ds[m_index][i] * dy[m_index][i]; } MPI_Allreduce(&dyds, &dyds_global, 1, MPI_DOUBLE, MPI_SUM, world); + if (update->multireplica == 1) { + dyds = dyds_global; + MPI_Allreduce(&dyds_global,&dyds,1,MPI_DOUBLE,MPI_SUM,universe->uworld); + } + if (fabs(dyds_global) > 1.0e-60) rho[m_index] = 1.0 / dyds_global; else rho[m_index] = 1.0e60; @@ -393,6 +401,10 @@ void MinSpinOSO_LBFGS::calc_search_direction(int iter) sq += ds[c_ind][i] * q[i]; } MPI_Allreduce(&sq, &sq_global, 1, MPI_DOUBLE, MPI_SUM, world); + if (update->multireplica == 1) { + sq = sq_global; + MPI_Allreduce(&sq_global,&sq,1,MPI_DOUBLE,MPI_SUM,universe->uworld); + } // update alpha @@ -411,6 +423,10 @@ void MinSpinOSO_LBFGS::calc_search_direction(int iter) yy += dy[m_index][i] * dy[m_index][i]; } MPI_Allreduce(&yy, &yy_global, 1, MPI_DOUBLE, MPI_SUM, world); + if (update->multireplica == 1) { + yy = yy_global; + MPI_Allreduce(&yy_global,&yy,1,MPI_DOUBLE,MPI_SUM,universe->uworld); + } // calculate now search direction @@ -435,7 +451,12 @@ void MinSpinOSO_LBFGS::calc_search_direction(int iter) for (int i = 0; i < 3 * nlocal; i++) { yr += dy[c_ind][i] * p_s[i]; } + MPI_Allreduce(&yr, &yr_global, 1, MPI_DOUBLE, MPI_SUM, world); + if (update->multireplica == 1) { + yr = yr_global; + MPI_Allreduce(&yr_global,&yr,1,MPI_DOUBLE,MPI_SUM,universe->uworld); + } beta = rho[c_ind] * yr_global; for (int i = 0; i < 3 * nlocal; i++) { From 48cc0293ffe7129370163ac8c0aa4c3e5c953e3d Mon Sep 17 00:00:00 2001 From: alxvov Date: Wed, 3 Jul 2019 12:01:21 +0000 Subject: [PATCH 026/192] if g2 zero then beta is also zero --- src/SPIN/min_spin_oso_cg.cpp | 15 +++++++++++---- 1 file changed, 11 insertions(+), 4 deletions(-) diff --git a/src/SPIN/min_spin_oso_cg.cpp b/src/SPIN/min_spin_oso_cg.cpp index 8d03ada45d..52bf48d228 100644 --- a/src/SPIN/min_spin_oso_cg.cpp +++ b/src/SPIN/min_spin_oso_cg.cpp @@ -326,9 +326,8 @@ void MinSpinOSO_CG::calc_search_direction(int iter) double g2 = 0.0; double beta = 0.0; - double g2_global= 0.0; - double g2old_global= 0.0; - + double g2_global = 0.0; + double g2old_global = 0.0; if (iter == 0 || iter % 5 == 0){ // steepest descent direction for (int i = 0; i < 3 * nlocal; i++) { p_s[i] = -g_cur[i]; @@ -347,8 +346,16 @@ void MinSpinOSO_CG::calc_search_direction(int iter) MPI_Allreduce(&g2, &g2_global, 1, MPI_DOUBLE, MPI_SUM, world); MPI_Allreduce(&g2old, &g2old_global, 1, MPI_DOUBLE, MPI_SUM, world); - beta = g2_global / g2old_global; + // we don't know yet if we need this. Needs to be tested with multiple replica. + // if (update->multireplica == 1) { + // g2 = g2_global; + // g2old = g2old_global; + // MPI_Allreduce(&g2,&g2_global,1,MPI_DOUBLE,MPI_SUM,universe->uworld); + // MPI_Allreduce(&g2old,&g2old_global,1,MPI_DOUBLE,MPI_SUM,universe->uworld); + // } + if (fabs(g2_global) < 1.0e-40) beta = 0.0; + else beta = g2_global / g2old_global; // calculate conjugate direction for (int i = 0; i < 3 * nlocal; i++) { From 87fd17a4d2ce411cfbcff15d1cdd2bc41550570d Mon Sep 17 00:00:00 2001 From: alxvov Date: Wed, 3 Jul 2019 14:54:02 +0000 Subject: [PATCH 027/192] global dot products --- src/SPIN/min_spin_oso_lbfgs_ls.cpp | 37 +++++++++++++++++++++++------- 1 file changed, 29 insertions(+), 8 deletions(-) diff --git a/src/SPIN/min_spin_oso_lbfgs_ls.cpp b/src/SPIN/min_spin_oso_lbfgs_ls.cpp index 38a557266e..2e124466ac 100644 --- a/src/SPIN/min_spin_oso_lbfgs_ls.cpp +++ b/src/SPIN/min_spin_oso_lbfgs_ls.cpp @@ -216,6 +216,9 @@ int MinSpinOSO_LBFGS_LS::iterate(int maxiter) } MPI_Allreduce(&der_e_cur, &der_e_cur_global, 1, MPI_DOUBLE, MPI_SUM, world); der_e_cur = der_e_cur_global; + if (update->multireplica == 1) { + MPI_Allreduce(&der_e_cur_global,&der_e_cur,1,MPI_DOUBLE,MPI_SUM,universe->uworld); + } } if (use_line_search){ @@ -388,7 +391,7 @@ void MinSpinOSO_LBFGS_LS::calc_search_direction(int iter) // for some reason on a second iteration g_old = 0 // so we make two iterations as steepest descent - + if (iter == 0){ // steepest descent direction for (int i = 0; i < 3 * nlocal; i++) { p_s[i] = -g_cur[i]; @@ -405,7 +408,12 @@ void MinSpinOSO_LBFGS_LS::calc_search_direction(int iter) dyds += ds[m_index][i] * dy[m_index][i]; } MPI_Allreduce(&dyds, &dyds_global, 1, MPI_DOUBLE, MPI_SUM, world); - if (fabs(dyds) > 1.0e-60) rho[m_index] = 1.0 / dyds_global; + if (update->multireplica == 1) { + dyds = dyds_global; + MPI_Allreduce(&dyds_global,&dyds,1,MPI_DOUBLE,MPI_SUM,universe->uworld); + } + + if (fabs(dyds_global) > 1.0e-60) rho[m_index] = 1.0 / dyds_global; else rho[m_index] = 1.0e60; // set the q vector @@ -427,7 +435,10 @@ void MinSpinOSO_LBFGS_LS::calc_search_direction(int iter) sq += ds[c_ind][i] * q[i]; } MPI_Allreduce(&sq, &sq_global, 1, MPI_DOUBLE, MPI_SUM, world); - + if (update->multireplica == 1) { + sq = sq_global; + MPI_Allreduce(&sq_global,&sq,1,MPI_DOUBLE,MPI_SUM,universe->uworld); + } // update alpha alpha[c_ind] = rho[c_ind] * sq_global; @@ -445,8 +456,12 @@ void MinSpinOSO_LBFGS_LS::calc_search_direction(int iter) yy += dy[m_index][i] * dy[m_index][i]; } MPI_Allreduce(&yy, &yy_global, 1, MPI_DOUBLE, MPI_SUM, world); + if (update->multireplica == 1) { + yy = yy_global; + MPI_Allreduce(&yy_global,&yy,1,MPI_DOUBLE,MPI_SUM,universe->uworld); + } - // calculate now search direction + // calculate now search direction if (fabs(yy_global) > 1.0e-60) { for (int i = 0; i < 3 * nlocal; i++) { @@ -470,6 +485,10 @@ void MinSpinOSO_LBFGS_LS::calc_search_direction(int iter) yr += dy[c_ind][i] * p_s[i]; } MPI_Allreduce(&yr, &yr_global, 1, MPI_DOUBLE, MPI_SUM, world); + if (update->multireplica == 1) { + yr = yr_global; + MPI_Allreduce(&yr_global,&yr,1,MPI_DOUBLE,MPI_SUM,universe->uworld); + } beta = rho[c_ind] * yr_global; for (int i = 0; i < 3 * nlocal; i++) { @@ -661,6 +680,9 @@ void MinSpinOSO_LBFGS_LS::make_step(double c, double *energy_and_der) } MPI_Allreduce(&der_e_cur, &der_e_cur_global, 1, MPI_DOUBLE, MPI_SUM, world); der_e_cur = der_e_cur_global; + if (update->multireplica == 1) { + MPI_Allreduce(&der_e_cur_global,&der_e_cur,1,MPI_DOUBLE,MPI_SUM,universe->uworld); + } energy_and_der[0] = ecurrent; energy_and_der[1] = der_e_cur; @@ -685,10 +707,9 @@ int MinSpinOSO_LBFGS_LS::calc_and_make_step(double a, double b, int index) if (awc(der_e_pr, eprevious, e_and_d[1], e_and_d[0]) || index == 3){ MPI_Bcast(&b,1,MPI_DOUBLE,0,world); - - for (int i = 0; i < 3 * nlocal; i++) { - p_s[i] = b * p_s[i]; - } + for (int i = 0; i < 3 * nlocal; i++) { + p_s[i] = b * p_s[i]; + } return 1; } else{ From 747245ee907151deb6cd691f9d53b43972f033d3 Mon Sep 17 00:00:00 2001 From: alxvov Date: Wed, 3 Jul 2019 15:06:53 +0000 Subject: [PATCH 028/192] sum beta over all replicas in cg. Good for GNEB --- src/SPIN/min_spin_oso_cg.cpp | 14 +++++++------- 1 file changed, 7 insertions(+), 7 deletions(-) diff --git a/src/SPIN/min_spin_oso_cg.cpp b/src/SPIN/min_spin_oso_cg.cpp index 52bf48d228..1b4e33ace3 100644 --- a/src/SPIN/min_spin_oso_cg.cpp +++ b/src/SPIN/min_spin_oso_cg.cpp @@ -346,13 +346,13 @@ void MinSpinOSO_CG::calc_search_direction(int iter) MPI_Allreduce(&g2, &g2_global, 1, MPI_DOUBLE, MPI_SUM, world); MPI_Allreduce(&g2old, &g2old_global, 1, MPI_DOUBLE, MPI_SUM, world); - // we don't know yet if we need this. Needs to be tested with multiple replica. - // if (update->multireplica == 1) { - // g2 = g2_global; - // g2old = g2old_global; - // MPI_Allreduce(&g2,&g2_global,1,MPI_DOUBLE,MPI_SUM,universe->uworld); - // MPI_Allreduce(&g2old,&g2old_global,1,MPI_DOUBLE,MPI_SUM,universe->uworld); - // } + // Sum over all replicas. Good for GNEB. + if (update->multireplica == 1) { + g2 = g2_global; + g2old = g2old_global; + MPI_Allreduce(&g2,&g2_global,1,MPI_DOUBLE,MPI_SUM,universe->uworld); + MPI_Allreduce(&g2old,&g2old_global,1,MPI_DOUBLE,MPI_SUM,universe->uworld); + } if (fabs(g2_global) < 1.0e-40) beta = 0.0; else beta = g2_global / g2old_global; From fb63c5a7085f3f5d6362f4cf3515bcd9666e469d Mon Sep 17 00:00:00 2001 From: julient31 Date: Wed, 3 Jul 2019 09:37:43 -0600 Subject: [PATCH 029/192] Commit1 JT 070319 - commit before pull --- src/SPIN/min_spin_oso_cg.cpp | 8 ++++---- src/SPIN/neb_spin.cpp | 2 ++ 2 files changed, 6 insertions(+), 4 deletions(-) diff --git a/src/SPIN/min_spin_oso_cg.cpp b/src/SPIN/min_spin_oso_cg.cpp index 52bf48d228..094ae376aa 100644 --- a/src/SPIN/min_spin_oso_cg.cpp +++ b/src/SPIN/min_spin_oso_cg.cpp @@ -154,8 +154,6 @@ void MinSpinOSO_CG::reset_vectors() minimization via damped spin dynamics ------------------------------------------------------------------------- */ -// g_old g_cur p_s - int MinSpinOSO_CG::iterate(int maxiter) { int nlocal = atom->nlocal; @@ -163,6 +161,8 @@ int MinSpinOSO_CG::iterate(int maxiter) double fmdotfm; int flag, flagall; + // grow tables if nlocal increased + if (nlocal_max < nlocal) { nlocal_max = nlocal; memory->grow(g_old,3*nlocal_max,"min/spin/oso/cg:g_old"); @@ -354,8 +354,8 @@ void MinSpinOSO_CG::calc_search_direction(int iter) // MPI_Allreduce(&g2old,&g2old_global,1,MPI_DOUBLE,MPI_SUM,universe->uworld); // } - if (fabs(g2_global) < 1.0e-40) beta = 0.0; - else beta = g2_global / g2old_global; + //if (fabs(g2_global) < 1.0e-40) beta = 0.0; + //else beta = g2_global / g2old_global; // calculate conjugate direction for (int i = 0; i < 3 * nlocal; i++) { diff --git a/src/SPIN/neb_spin.cpp b/src/SPIN/neb_spin.cpp index 9ab461cbe6..12d1d2a956 100644 --- a/src/SPIN/neb_spin.cpp +++ b/src/SPIN/neb_spin.cpp @@ -252,6 +252,8 @@ void NEBSpin::run() timer->init(); timer->barrier_start(); + // if(ireplica != 0 && ireplica != nreplica -1) + while (update->minimize->niter < n1steps) { update->minimize->run(nevery); print_status(); From 526e0da0a90bdd55458892a959b1bf1c60ce6204 Mon Sep 17 00:00:00 2001 From: alxvov Date: Wed, 3 Jul 2019 15:41:29 +0000 Subject: [PATCH 030/192] reduce correctly over the universe --- src/SPIN/min_spin_oso_lbfgs.cpp | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/src/SPIN/min_spin_oso_lbfgs.cpp b/src/SPIN/min_spin_oso_lbfgs.cpp index a598601532..5604f99752 100644 --- a/src/SPIN/min_spin_oso_lbfgs.cpp +++ b/src/SPIN/min_spin_oso_lbfgs.cpp @@ -376,7 +376,7 @@ void MinSpinOSO_LBFGS::calc_search_direction(int iter) MPI_Allreduce(&dyds, &dyds_global, 1, MPI_DOUBLE, MPI_SUM, world); if (update->multireplica == 1) { dyds = dyds_global; - MPI_Allreduce(&dyds_global,&dyds,1,MPI_DOUBLE,MPI_SUM,universe->uworld); + MPI_Allreduce(&dyds, &dyds_global, 1,MPI_DOUBLE,MPI_SUM,universe->uworld); } if (fabs(dyds_global) > 1.0e-60) rho[m_index] = 1.0 / dyds_global; @@ -403,7 +403,7 @@ void MinSpinOSO_LBFGS::calc_search_direction(int iter) MPI_Allreduce(&sq, &sq_global, 1, MPI_DOUBLE, MPI_SUM, world); if (update->multireplica == 1) { sq = sq_global; - MPI_Allreduce(&sq_global,&sq,1,MPI_DOUBLE,MPI_SUM,universe->uworld); + MPI_Allreduce(&sq,&sq_global,1,MPI_DOUBLE,MPI_SUM,universe->uworld); } // update alpha @@ -425,7 +425,7 @@ void MinSpinOSO_LBFGS::calc_search_direction(int iter) MPI_Allreduce(&yy, &yy_global, 1, MPI_DOUBLE, MPI_SUM, world); if (update->multireplica == 1) { yy = yy_global; - MPI_Allreduce(&yy_global,&yy,1,MPI_DOUBLE,MPI_SUM,universe->uworld); + MPI_Allreduce(&yy,&yy_global,1,MPI_DOUBLE,MPI_SUM,universe->uworld); } // calculate now search direction @@ -455,7 +455,7 @@ void MinSpinOSO_LBFGS::calc_search_direction(int iter) MPI_Allreduce(&yr, &yr_global, 1, MPI_DOUBLE, MPI_SUM, world); if (update->multireplica == 1) { yr = yr_global; - MPI_Allreduce(&yr_global,&yr,1,MPI_DOUBLE,MPI_SUM,universe->uworld); + MPI_Allreduce(&yr,&yr_global,1,MPI_DOUBLE,MPI_SUM,universe->uworld); } beta = rho[c_ind] * yr_global; From 99e58d889cdf3ba9794cd97b5315b891120b165b Mon Sep 17 00:00:00 2001 From: julient31 Date: Wed, 3 Jul 2019 10:48:11 -0600 Subject: [PATCH 031/192] Commit2 JT 070319 - fixing first and last images in oso_lbfgs.cpp --- src/SPIN/min_spin_oso_lbfgs.cpp | 20 +++++++++++++++++++- src/SPIN/min_spin_oso_lbfgs.h | 5 +++++ 2 files changed, 24 insertions(+), 1 deletion(-) diff --git a/src/SPIN/min_spin_oso_lbfgs.cpp b/src/SPIN/min_spin_oso_lbfgs.cpp index 5604f99752..a14bf7c4fd 100644 --- a/src/SPIN/min_spin_oso_lbfgs.cpp +++ b/src/SPIN/min_spin_oso_lbfgs.cpp @@ -39,6 +39,8 @@ #include "math_special.h" #include "math_const.h" +#include "universe.h" + using namespace LAMMPS_NS; using namespace MathConst; @@ -66,6 +68,13 @@ MinSpinOSO_LBFGS::MinSpinOSO_LBFGS(LAMMPS *lmp) : { if (lmp->citeme) lmp->citeme->add(cite_minstyle_spin_oso_lbfgs); nlocal_max = 0; + + // nreplica = number of partitions + // ireplica = which world I am in universe + + nreplica = universe->nworlds; + ireplica = universe->iworld; + } /* ---------------------------------------------------------------------- */ @@ -198,7 +207,16 @@ int MinSpinOSO_LBFGS::iterate(int maxiter) calc_gradient(dts); calc_search_direction(iter); - advance_spins(); + + // to be checked + // if gneb calc., nreplica > 0 + // then advance spins only if intermediate replica + // otherwise (simple minimization), advance spins + + if (nreplica > 0) { + if(ireplica != 0 && ireplica != nreplica-1) + advance_spins(); + } else advance_spins(); eprevious = ecurrent; ecurrent = energy_force(0); diff --git a/src/SPIN/min_spin_oso_lbfgs.h b/src/SPIN/min_spin_oso_lbfgs.h index 3aa326142c..3fc1d625dd 100644 --- a/src/SPIN/min_spin_oso_lbfgs.h +++ b/src/SPIN/min_spin_oso_lbfgs.h @@ -41,6 +41,11 @@ public: void calc_search_direction(int); private: + + + // test + int ireplica,nreplica; + // global and spin timesteps int nlocal_max; // max value of nlocal (for size of lists) From 3c3c7899b4fdceb378c206870ee4e93ff76711df Mon Sep 17 00:00:00 2001 From: alxvov Date: Wed, 3 Jul 2019 19:33:24 +0000 Subject: [PATCH 032/192] use local iteration counter, needed for neb --- src/SPIN/min_spin_oso_cg.cpp | 13 ++++++++----- src/SPIN/min_spin_oso_cg.h | 3 ++- 2 files changed, 10 insertions(+), 6 deletions(-) diff --git a/src/SPIN/min_spin_oso_cg.cpp b/src/SPIN/min_spin_oso_cg.cpp index 1b4e33ace3..8f2ba0623b 100644 --- a/src/SPIN/min_spin_oso_cg.cpp +++ b/src/SPIN/min_spin_oso_cg.cpp @@ -83,7 +83,7 @@ void MinSpinOSO_CG::init() { alpha_damp = 1.0; discrete_factor = 10.0; - + local_iter = 0; Min::init(); dts = dt = update->dt; @@ -164,6 +164,7 @@ int MinSpinOSO_CG::iterate(int maxiter) int flag, flagall; if (nlocal_max < nlocal) { + local_iter = 0; nlocal_max = nlocal; memory->grow(g_old,3*nlocal_max,"min/spin/oso/cg:g_old"); memory->grow(g_cur,3*nlocal_max,"min/spin/oso/cg:g_cur"); @@ -181,11 +182,11 @@ int MinSpinOSO_CG::iterate(int maxiter) // optimize timestep accross processes / replicas // need a force calculation for timestep optimization - if (iter == 0) energy_force(0); + if (local_iter == 0) energy_force(0); dts = evaluate_dt(); calc_gradient(dts); - calc_search_direction(iter); + calc_search_direction(); advance_spins(); eprevious = ecurrent; @@ -319,7 +320,7 @@ void MinSpinOSO_CG::calc_gradient(double dts) Optimization' Second Edition, 2006 (p. 121) ---------------------------------------------------------------------- */ -void MinSpinOSO_CG::calc_search_direction(int iter) +void MinSpinOSO_CG::calc_search_direction() { int nlocal = atom->nlocal; double g2old = 0.0; @@ -328,7 +329,7 @@ void MinSpinOSO_CG::calc_search_direction(int iter) double g2_global = 0.0; double g2old_global = 0.0; - if (iter == 0 || iter % 5 == 0){ // steepest descent direction + if (local_iter == 0 || local_iter % 5 == 0){ // steepest descent direction for (int i = 0; i < 3 * nlocal; i++) { p_s[i] = -g_cur[i]; g_old[i] = g_cur[i]; @@ -363,6 +364,8 @@ void MinSpinOSO_CG::calc_search_direction(int iter) g_old[i] = g_cur[i]; } } + + local_iter++; } /* ---------------------------------------------------------------------- diff --git a/src/SPIN/min_spin_oso_cg.h b/src/SPIN/min_spin_oso_cg.h index a791754836..3a3d24f078 100644 --- a/src/SPIN/min_spin_oso_cg.h +++ b/src/SPIN/min_spin_oso_cg.h @@ -38,7 +38,7 @@ public: void advance_spins(); double fmnorm_sqr(); void calc_gradient(double); - void calc_search_direction(int); + void calc_search_direction(); private: // global and spin timesteps @@ -56,6 +56,7 @@ private: double *g_old; // gradient vector at previous iteration double *g_cur; // current gradient vector double *p_s; // search direction vector + int local_iter; // number of times we call search_direction void vm3(const double *, const double *, double *); void rodrigues_rotation(const double *, double *); From 95cf85f1b932acc983ab826c90cdcc78e3991751 Mon Sep 17 00:00:00 2001 From: alxvov Date: Wed, 3 Jul 2019 21:12:04 +0000 Subject: [PATCH 033/192] bug: forget to calculate beta.. --- src/SPIN/min_spin_oso_cg.cpp | 5 ++--- 1 file changed, 2 insertions(+), 3 deletions(-) diff --git a/src/SPIN/min_spin_oso_cg.cpp b/src/SPIN/min_spin_oso_cg.cpp index 6ae2518986..d8535b19c4 100644 --- a/src/SPIN/min_spin_oso_cg.cpp +++ b/src/SPIN/min_spin_oso_cg.cpp @@ -355,10 +355,9 @@ void MinSpinOSO_CG::calc_search_direction() MPI_Allreduce(&g2old,&g2old_global,1,MPI_DOUBLE,MPI_SUM,universe->uworld); } - //if (fabs(g2_global) < 1.0e-40) beta = 0.0; - //else beta = g2_global / g2old_global; + if (fabs(g2_global) < 1.0e-60) beta = 0.0; + else beta = g2_global / g2old_global; // calculate conjugate direction - for (int i = 0; i < 3 * nlocal; i++) { p_s[i] = beta * p_s[i] - g_cur[i]; g_old[i] = g_cur[i]; From e85bdd17d3a2980f1987f2770c1958c8bbcd8015 Mon Sep 17 00:00:00 2001 From: alxvov Date: Thu, 4 Jul 2019 15:31:18 +0000 Subject: [PATCH 034/192] introduce cutoff step. make lbfgs stable --- src/SPIN/min_spin_oso_lbfgs.cpp | 107 +++++++++++++++++++++++++------- src/SPIN/min_spin_oso_lbfgs.h | 12 ++-- 2 files changed, 92 insertions(+), 27 deletions(-) diff --git a/src/SPIN/min_spin_oso_lbfgs.cpp b/src/SPIN/min_spin_oso_lbfgs.cpp index a14bf7c4fd..09948ac3e5 100644 --- a/src/SPIN/min_spin_oso_lbfgs.cpp +++ b/src/SPIN/min_spin_oso_lbfgs.cpp @@ -38,7 +38,6 @@ #include "modify.h" #include "math_special.h" #include "math_const.h" - #include "universe.h" using namespace LAMMPS_NS; @@ -96,6 +95,8 @@ void MinSpinOSO_LBFGS::init() alpha_damp = 1.0; discrete_factor = 10.0; num_mem = 3; + local_iter = 0; + maxepsrot = MY_2PI / (200.0); Min::init(); @@ -180,6 +181,7 @@ int MinSpinOSO_LBFGS::iterate(int maxiter) if (nlocal_max < nlocal) { nlocal_max = nlocal; + local_iter = 0; memory->grow(g_old,3*nlocal_max,"min/spin/oso/lbfgs:g_old"); memory->grow(g_cur,3*nlocal_max,"min/spin/oso/lbfgs:g_cur"); memory->grow(p_s,3*nlocal_max,"min/spin/oso/lbfgs:p_s"); @@ -198,26 +200,26 @@ int MinSpinOSO_LBFGS::iterate(int maxiter) // optimize timestep accross processes / replicas // need a force calculation for timestep optimization - - if (iter == 0){ - energy_force(0); - dts = evaluate_dt(); - } - else dts = 1.0; + if (local_iter == 0) energy_force(0); + // to be checked + // if gneb calc., nreplica > 1 + // then calculate gradients of intermediate replicas - calc_gradient(dts); + if (nreplica > 1) { + if(ireplica != 0 && ireplica != nreplica-1) + calc_gradient(1.0); + } else calc_gradient(1.0); calc_search_direction(iter); // to be checked - // if gneb calc., nreplica > 0 + // if gneb calc., nreplica > 1 // then advance spins only if intermediate replica // otherwise (simple minimization), advance spins - if (nreplica > 0) { + if (nreplica > 1) { if(ireplica != 0 && ireplica != nreplica-1) advance_spins(); } else advance_spins(); - eprevious = ecurrent; ecurrent = energy_force(0); neval++; @@ -307,7 +309,7 @@ double MinSpinOSO_LBFGS::evaluate_dt() // define max timestep by dividing by the // inverse of max frequency by discrete_factor - + // std::cout << fmaxsqall << "\n"; dtmax = MY_2PI/(discrete_factor*sqrt(fmaxsqall)); return dtmax; @@ -365,20 +367,31 @@ void MinSpinOSO_LBFGS::calc_search_direction(int iter) double yr_global = 0.0; double beta_global = 0.0; - int m_index = iter % num_mem; // memory index + int m_index = local_iter % num_mem; // memory index int c_ind = 0; double *q; double *alpha; + double factor; + double scaling; + + if (nreplica > 1) { + if (ireplica == 0 || ireplica == nreplica - 1) { + factor = 0.0; + } + else factor = 1.0; + }else{ + factor = 1.0; + } + q = (double *) calloc(3*nlocal, sizeof(double)); alpha = (double *) calloc(num_mem, sizeof(double)); - // for some reason on a second iteration g_old = 0 - // so we make two iterations as steepest descent - - if (iter == 0){ // steepest descent direction + if (local_iter == 0){ // steepest descent direction + + scaling = maximum_rotation(g_cur); for (int i = 0; i < 3 * nlocal; i++) { - p_s[i] = -g_cur[i]; + p_s[i] = - g_cur[i] * factor * scaling; g_old[i] = g_cur[i]; ds[m_index][i] = 0.0; dy[m_index][i] = 0.0; @@ -392,7 +405,9 @@ void MinSpinOSO_LBFGS::calc_search_direction(int iter) dyds += ds[m_index][i] * dy[m_index][i]; } MPI_Allreduce(&dyds, &dyds_global, 1, MPI_DOUBLE, MPI_SUM, world); + if (update->multireplica == 1) { + dyds_global *= factor; dyds = dyds_global; MPI_Allreduce(&dyds, &dyds_global, 1,MPI_DOUBLE,MPI_SUM,universe->uworld); } @@ -400,6 +415,17 @@ void MinSpinOSO_LBFGS::calc_search_direction(int iter) if (fabs(dyds_global) > 1.0e-60) rho[m_index] = 1.0 / dyds_global; else rho[m_index] = 1.0e60; + if (rho[m_index] < 0.0){ + local_iter = 0; + for (int k = 0; k < num_mem; k++){ + for (int i = 0; i < nlocal; i ++){ + ds[k][i] = 0.0; + dy[k][i] = 0.0; + } + } + return calc_search_direction(0); + } + // set the q vector for (int i = 0; i < 3 * nlocal; i++) { @@ -420,6 +446,7 @@ void MinSpinOSO_LBFGS::calc_search_direction(int iter) } MPI_Allreduce(&sq, &sq_global, 1, MPI_DOUBLE, MPI_SUM, world); if (update->multireplica == 1) { + sq_global *= factor; sq = sq_global; MPI_Allreduce(&sq,&sq_global,1,MPI_DOUBLE,MPI_SUM,universe->uworld); } @@ -442,19 +469,22 @@ void MinSpinOSO_LBFGS::calc_search_direction(int iter) } MPI_Allreduce(&yy, &yy_global, 1, MPI_DOUBLE, MPI_SUM, world); if (update->multireplica == 1) { + yy_global *= factor; yy = yy_global; MPI_Allreduce(&yy,&yy_global,1,MPI_DOUBLE,MPI_SUM,universe->uworld); } // calculate now search direction - if (fabs(yy_global) > 1.0e-60) { + double devis = rho[m_index] * yy_global; + + if (fabs(devis) > 1.0e-60) { for (int i = 0; i < 3 * nlocal; i++) { - p_s[i] = q[i] / (rho[m_index] * yy_global); + p_s[i] = factor * q[i] / devis; } }else{ for (int i = 0; i < 3 * nlocal; i++) { - p_s[i] = q[i] * 1.0e60; + p_s[i] = factor * q[i] * 1.0e60; } } @@ -472,6 +502,7 @@ void MinSpinOSO_LBFGS::calc_search_direction(int iter) MPI_Allreduce(&yr, &yr_global, 1, MPI_DOUBLE, MPI_SUM, world); if (update->multireplica == 1) { + yr_global *= factor; yr = yr_global; MPI_Allreduce(&yr,&yr_global,1,MPI_DOUBLE,MPI_SUM,universe->uworld); } @@ -481,12 +512,14 @@ void MinSpinOSO_LBFGS::calc_search_direction(int iter) p_s[i] += ds[c_ind][i] * (alpha[c_ind] - beta); } } + scaling = maximum_rotation(p_s); for (int i = 0; i < 3 * nlocal; i++) { - p_s[i] = -1.0 * p_s[i]; + p_s[i] = - factor * p_s[i] * scaling; g_old[i] = g_cur[i]; } } + local_iter++; free(q); free(alpha); @@ -631,3 +664,33 @@ void MinSpinOSO_LBFGS::vm3(const double *m, const double *v, double *out) } } } + +double MinSpinOSO_LBFGS::maximum_rotation(double *p) +{ + double norm, norm_global, scaling, alpha; + int nlocal = atom->nlocal; + int ntotal = 0; + + norm = 0.0; + for (int i = 0; i < 3 * nlocal; i++) norm += p[i] * p[i]; + + MPI_Allreduce(&norm,&norm_global,1,MPI_DOUBLE,MPI_SUM,world); + if (update->multireplica == 1) { + norm = norm_global; + MPI_Allreduce(&norm,&norm_global,1,MPI_DOUBLE,MPI_SUM,universe->uworld); + } + + MPI_Allreduce(&nlocal,&ntotal,1,MPI_INT,MPI_SUM,world); + if (update->multireplica == 1) { + nlocal = ntotal; + MPI_Allreduce(&nlocal,&ntotal,1,MPI_INT,MPI_SUM,universe->uworld); + } + + scaling = (maxepsrot * sqrt((double) ntotal / norm_global)); + + if (scaling < 1.0) alpha = scaling; + else alpha = 1.0; + + return alpha; +} + diff --git a/src/SPIN/min_spin_oso_lbfgs.h b/src/SPIN/min_spin_oso_lbfgs.h index 3fc1d625dd..dfc4ec06ff 100644 --- a/src/SPIN/min_spin_oso_lbfgs.h +++ b/src/SPIN/min_spin_oso_lbfgs.h @@ -38,8 +38,8 @@ public: void advance_spins(); double fmnorm_sqr(); void calc_gradient(double); - void calc_search_direction(int); - + void calc_search_direction(int); + double maximum_rotation(double *); private: @@ -64,11 +64,13 @@ private: double **ds; // change in rotation matrix between two iterations, da double **dy; // change in gradients between two iterations, dg double *rho; // estimation of curvature - int num_mem; // number of stored steps + int num_mem; // number of stored steps + int local_iter; // number of times we call search_direction + double maxepsrot; - void vm3(const double *m, const double *v, double *out); - void rodrigues_rotation(const double *upp_tr, double *out); + void vm3(const double *, const double *, double *); + void rodrigues_rotation(const double *, double *); bigint last_negative; }; From f3985c853edace460556d87ff22ed81de884cb25 Mon Sep 17 00:00:00 2001 From: alxvov Date: Thu, 4 Jul 2019 18:19:57 +0000 Subject: [PATCH 035/192] local iter instead of iter --- src/SPIN/min_spin_oso_lbfgs.cpp | 12 ++++++------ src/SPIN/min_spin_oso_lbfgs.h | 2 +- 2 files changed, 7 insertions(+), 7 deletions(-) diff --git a/src/SPIN/min_spin_oso_lbfgs.cpp b/src/SPIN/min_spin_oso_lbfgs.cpp index 09948ac3e5..9687f2f64d 100644 --- a/src/SPIN/min_spin_oso_lbfgs.cpp +++ b/src/SPIN/min_spin_oso_lbfgs.cpp @@ -96,7 +96,7 @@ void MinSpinOSO_LBFGS::init() discrete_factor = 10.0; num_mem = 3; local_iter = 0; - maxepsrot = MY_2PI / (200.0); + maxepsrot = MY_2PI / (100.0); Min::init(); @@ -209,7 +209,7 @@ int MinSpinOSO_LBFGS::iterate(int maxiter) if(ireplica != 0 && ireplica != nreplica-1) calc_gradient(1.0); } else calc_gradient(1.0); - calc_search_direction(iter); + calc_search_direction(); // to be checked // if gneb calc., nreplica > 1 @@ -351,7 +351,7 @@ void MinSpinOSO_LBFGS::calc_gradient(double dts) Optimization' Second Edition, 2006 (p. 177) ---------------------------------------------------------------------- */ -void MinSpinOSO_LBFGS::calc_search_direction(int iter) +void MinSpinOSO_LBFGS::calc_search_direction() { int nlocal = atom->nlocal; @@ -418,12 +418,12 @@ void MinSpinOSO_LBFGS::calc_search_direction(int iter) if (rho[m_index] < 0.0){ local_iter = 0; for (int k = 0; k < num_mem; k++){ - for (int i = 0; i < nlocal; i ++){ + for (int i = 0; i < nlocal; i ++){ ds[k][i] = 0.0; dy[k][i] = 0.0; } } - return calc_search_direction(0); + return calc_search_direction(); } // set the q vector @@ -491,7 +491,7 @@ void MinSpinOSO_LBFGS::calc_search_direction(int iter) for (int k = 0; k < num_mem; k++){ // this loop should run from the oldest memory to the newest one. - if (iter < num_mem) c_ind = k; + if (local_iter < num_mem) c_ind = k; else c_ind = (k + m_index + 1) % num_mem; // dot product between p and da diff --git a/src/SPIN/min_spin_oso_lbfgs.h b/src/SPIN/min_spin_oso_lbfgs.h index dfc4ec06ff..c0f8dc484d 100644 --- a/src/SPIN/min_spin_oso_lbfgs.h +++ b/src/SPIN/min_spin_oso_lbfgs.h @@ -38,7 +38,7 @@ public: void advance_spins(); double fmnorm_sqr(); void calc_gradient(double); - void calc_search_direction(int); + void calc_search_direction(); double maximum_rotation(double *); private: From 79f8e422f9f8ee044db5b9e5cb7cee6b637e3dff Mon Sep 17 00:00:00 2001 From: alxvov Date: Thu, 4 Jul 2019 18:21:07 +0000 Subject: [PATCH 036/192] indentation --- src/SPIN/min_spin_oso_lbfgs.cpp | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/SPIN/min_spin_oso_lbfgs.cpp b/src/SPIN/min_spin_oso_lbfgs.cpp index 9687f2f64d..fd83e7b460 100644 --- a/src/SPIN/min_spin_oso_lbfgs.cpp +++ b/src/SPIN/min_spin_oso_lbfgs.cpp @@ -418,7 +418,7 @@ void MinSpinOSO_LBFGS::calc_search_direction() if (rho[m_index] < 0.0){ local_iter = 0; for (int k = 0; k < num_mem; k++){ - for (int i = 0; i < nlocal; i ++){ + for (int i = 0; i < nlocal; i ++){ ds[k][i] = 0.0; dy[k][i] = 0.0; } From bb325a335ed3c8a8e612142aff2547461a3c35d3 Mon Sep 17 00:00:00 2001 From: julient31 Date: Wed, 10 Jul 2019 09:52:39 -0600 Subject: [PATCH 037/192] Commit1 JT 070919 - test energy/torque modif with etotal --- src/SPIN/pair_spin_dmi.cpp | 8 ++++---- src/SPIN/pair_spin_exchange.cpp | 8 ++++---- 2 files changed, 8 insertions(+), 8 deletions(-) diff --git a/src/SPIN/pair_spin_dmi.cpp b/src/SPIN/pair_spin_dmi.cpp index 41430d230f..817d933698 100644 --- a/src/SPIN/pair_spin_dmi.cpp +++ b/src/SPIN/pair_spin_dmi.cpp @@ -317,7 +317,7 @@ void PairSpinDmi::compute(int eflag, int vflag) if (eflag) { evdwl -= (spi[0]*fmi[0] + spi[1]*fmi[1] + spi[2]*fmi[2]); - evdwl *= hbar; + evdwl *= 0.5*hbar; } else evdwl = 0.0; if (evflag) ev_tally_xyz(i,j,nlocal,newton_pair, @@ -431,9 +431,9 @@ void PairSpinDmi::compute_dmi(int i, int j, double eij[3], double fmi[3], double dmiy = eij[2]*v_dmx[itype][jtype] - eij[0]*v_dmz[itype][jtype]; dmiz = eij[0]*v_dmy[itype][jtype] - eij[1]*v_dmx[itype][jtype]; - fmi[0] -= (dmiy*spj[2] - dmiz*spj[1]); - fmi[1] -= (dmiz*spj[0] - dmix*spj[2]); - fmi[2] -= (dmix*spj[1] - dmiy*spj[0]); + fmi[0] -= 2.0*(dmiy*spj[2] - dmiz*spj[1]); + fmi[1] -= 2.0*(dmiz*spj[0] - dmix*spj[2]); + fmi[2] -= 2.0*(dmix*spj[1] - dmiy*spj[0]); } /* ---------------------------------------------------------------------- diff --git a/src/SPIN/pair_spin_exchange.cpp b/src/SPIN/pair_spin_exchange.cpp index 93b6d9501e..721002acba 100644 --- a/src/SPIN/pair_spin_exchange.cpp +++ b/src/SPIN/pair_spin_exchange.cpp @@ -300,7 +300,7 @@ void PairSpinExchange::compute(int eflag, int vflag) if (eflag) { evdwl -= (spi[0]*fmi[0] + spi[1]*fmi[1] + spi[2]*fmi[2]); - evdwl *= hbar; + evdwl *= 0.5*hbar; } else evdwl = 0.0; if (evflag) ev_tally_xyz(i,j,nlocal,newton_pair, @@ -409,9 +409,9 @@ void PairSpinExchange::compute_exchange(int i, int j, double rsq, double fmi[3], Jex *= (1.0-J2[itype][jtype]*ra); Jex *= exp(-ra); - fmi[0] += Jex*spj[0]; - fmi[1] += Jex*spj[1]; - fmi[2] += Jex*spj[2]; + fmi[0] += 2.0*Jex*spj[0]; + fmi[1] += 2.0*Jex*spj[1]; + fmi[2] += 2.0*Jex*spj[2]; } /* ---------------------------------------------------------------------- From 2b2a9e775eed2d8991d776e3f50afd9f678f130c Mon Sep 17 00:00:00 2001 From: alxvov Date: Thu, 11 Jul 2019 08:24:28 +0000 Subject: [PATCH 038/192] fix memory, add sp_copy --- src/SPIN/min_spin_oso_lbfgs_ls.cpp | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/SPIN/min_spin_oso_lbfgs_ls.cpp b/src/SPIN/min_spin_oso_lbfgs_ls.cpp index 2e124466ac..0d9c2d7c51 100644 --- a/src/SPIN/min_spin_oso_lbfgs_ls.cpp +++ b/src/SPIN/min_spin_oso_lbfgs_ls.cpp @@ -64,7 +64,7 @@ static const char cite_minstyle_spin_oso_lbfgs_ls[] = /* ---------------------------------------------------------------------- */ MinSpinOSO_LBFGS_LS::MinSpinOSO_LBFGS_LS(LAMMPS *lmp) : - Min(lmp), g_old(NULL), g_cur(NULL), p_s(NULL), ds(NULL), dy(NULL), rho(NULL) + Min(lmp), g_old(NULL), g_cur(NULL), p_s(NULL), ds(NULL), dy(NULL), rho(NULL), sp_copy(NULL) { if (lmp->citeme) lmp->citeme->add(cite_minstyle_spin_oso_lbfgs_ls); nlocal_max = 0; From 6238ad321228ef4320dc0f006b30f6e150ed7890 Mon Sep 17 00:00:00 2001 From: alxvov Date: Thu, 11 Jul 2019 14:18:42 +0000 Subject: [PATCH 039/192] local iterator, broadcast more --- src/SPIN/min_spin_oso_lbfgs_ls.cpp | 100 ++++++++++++++++++++--------- src/SPIN/min_spin_oso_lbfgs_ls.h | 6 +- 2 files changed, 75 insertions(+), 31 deletions(-) diff --git a/src/SPIN/min_spin_oso_lbfgs_ls.cpp b/src/SPIN/min_spin_oso_lbfgs_ls.cpp index 0d9c2d7c51..e1a6ae99d5 100644 --- a/src/SPIN/min_spin_oso_lbfgs_ls.cpp +++ b/src/SPIN/min_spin_oso_lbfgs_ls.cpp @@ -38,6 +38,7 @@ #include "modify.h" #include "math_special.h" #include "math_const.h" +#include "universe.h" #include @@ -68,6 +69,13 @@ MinSpinOSO_LBFGS_LS::MinSpinOSO_LBFGS_LS(LAMMPS *lmp) : { if (lmp->citeme) lmp->citeme->add(cite_minstyle_spin_oso_lbfgs_ls); nlocal_max = 0; + + // nreplica = number of partitions + // ireplica = which world I am in universe + + nreplica = universe->nworlds; + ireplica = universe->iworld; + } /* ---------------------------------------------------------------------- */ @@ -90,6 +98,7 @@ void MinSpinOSO_LBFGS_LS::init() alpha_damp = 1.0; discrete_factor = 10.0; num_mem = 3; + local_iter = 0; der_e_cur = 0.0; der_e_pr = 0.0; use_line_search = 1; @@ -189,7 +198,6 @@ int MinSpinOSO_LBFGS_LS::iterate(int maxiter) memory->grow(sp_copy,nlocal_max,3,"min/spin/oso/lbfgs_ls:sp_copy"); } - for (int iter = 0; iter < maxiter; iter++) { if (timer->check_timeout(niter)) @@ -201,13 +209,12 @@ int MinSpinOSO_LBFGS_LS::iterate(int maxiter) // optimize timestep accross processes / replicas // need a force calculation for timestep optimization - if (iter == 0){ + if (local_iter == 0){ ecurrent = energy_force(0); calc_gradient(1.0); neval++; - }else{ } - calc_search_direction(iter); + calc_search_direction(); if (use_line_search) { der_e_cur = 0.0; @@ -365,7 +372,7 @@ void MinSpinOSO_LBFGS_LS::calc_gradient(double dts) Optimization' Second Edition, 2006 (p. 177) ---------------------------------------------------------------------- */ -void MinSpinOSO_LBFGS_LS::calc_search_direction(int iter) +void MinSpinOSO_LBFGS_LS::calc_search_direction() { int nlocal = atom->nlocal; @@ -381,41 +388,64 @@ void MinSpinOSO_LBFGS_LS::calc_search_direction(int iter) double yr_global = 0.0; double beta_global = 0.0; - int m_index = iter % num_mem; // memory index + int m_index = local_iter % num_mem; // memory index int c_ind = 0; double *q; double *alpha; + double factor; + + if (nreplica > 1) { + if (ireplica == 0 || ireplica == nreplica - 1) { + factor = 0.0; + } + else factor = 1.0; + }else{ + factor = 1.0; + } + q = (double *) calloc(3*nlocal, sizeof(double)); alpha = (double *) calloc(num_mem, sizeof(double)); - // for some reason on a second iteration g_old = 0 - // so we make two iterations as steepest descent - - if (iter == 0){ // steepest descent direction + if (local_iter == 0){ // steepest descent direction for (int i = 0; i < 3 * nlocal; i++) { p_s[i] = -g_cur[i]; g_old[i] = g_cur[i]; - ds[m_index][i] = 0.0; - dy[m_index][i] = 0.0; - + for (int k = 0; k < num_mem; k++){ + ds[k][i] = 0.0; + dy[k][i] = 0.0; + rho[k] = 0.0; + } } } else { - dyds = 0.0; - for (int i = 0; i < 3 * nlocal; i++) { - ds[m_index][i] = p_s[i]; - dy[m_index][i] = g_cur[i] - g_old[i]; - dyds += ds[m_index][i] * dy[m_index][i]; - } + dyds = 0.0; + for (int i = 0; i < 3 * nlocal; i++) { + ds[m_index][i] = p_s[i]; + dy[m_index][i] = g_cur[i] - g_old[i]; + dyds += ds[m_index][i] * dy[m_index][i]; + } MPI_Allreduce(&dyds, &dyds_global, 1, MPI_DOUBLE, MPI_SUM, world); + if (update->multireplica == 1) { + dyds_global *= factor; dyds = dyds_global; - MPI_Allreduce(&dyds_global,&dyds,1,MPI_DOUBLE,MPI_SUM,universe->uworld); + MPI_Allreduce(&dyds, &dyds_global, 1,MPI_DOUBLE,MPI_SUM,universe->uworld); } - if (fabs(dyds_global) > 1.0e-60) rho[m_index] = 1.0 / dyds_global; + if (fabs(dyds_global) > 1.0e-60) rho[m_index] = 1.0 / dyds_global; else rho[m_index] = 1.0e60; + if (rho[m_index] < 0.0){ + local_iter = 0; + for (int k = 0; k < num_mem; k++){ + for (int i = 0; i < nlocal; i ++){ + ds[k][i] = 0.0; + dy[k][i] = 0.0; + } + } + return calc_search_direction(); + } + // set the q vector for (int i = 0; i < 3 * nlocal; i++) { @@ -436,9 +466,11 @@ void MinSpinOSO_LBFGS_LS::calc_search_direction(int iter) } MPI_Allreduce(&sq, &sq_global, 1, MPI_DOUBLE, MPI_SUM, world); if (update->multireplica == 1) { + sq_global *= factor; sq = sq_global; - MPI_Allreduce(&sq_global,&sq,1,MPI_DOUBLE,MPI_SUM,universe->uworld); + MPI_Allreduce(&sq,&sq_global,1,MPI_DOUBLE,MPI_SUM,universe->uworld); } + // update alpha alpha[c_ind] = rho[c_ind] * sq_global; @@ -457,26 +489,29 @@ void MinSpinOSO_LBFGS_LS::calc_search_direction(int iter) } MPI_Allreduce(&yy, &yy_global, 1, MPI_DOUBLE, MPI_SUM, world); if (update->multireplica == 1) { + yy_global *= factor; yy = yy_global; - MPI_Allreduce(&yy_global,&yy,1,MPI_DOUBLE,MPI_SUM,universe->uworld); + MPI_Allreduce(&yy,&yy_global,1,MPI_DOUBLE,MPI_SUM,universe->uworld); } // calculate now search direction - if (fabs(yy_global) > 1.0e-60) { + double devis = rho[m_index] * yy_global; + + if (fabs(devis) > 1.0e-60) { for (int i = 0; i < 3 * nlocal; i++) { - p_s[i] = q[i] / (rho[m_index] * yy_global); + p_s[i] = factor * q[i] / devis; } }else{ for (int i = 0; i < 3 * nlocal; i++) { - p_s[i] = q[i] * 1.0e60; + p_s[i] = factor * q[i] * 1.0e60; } } for (int k = 0; k < num_mem; k++){ // this loop should run from the oldest memory to the newest one. - if (iter < num_mem) c_ind = k; + if (local_iter < num_mem) c_ind = k; else c_ind = (k + m_index + 1) % num_mem; // dot product between p and da @@ -484,10 +519,12 @@ void MinSpinOSO_LBFGS_LS::calc_search_direction(int iter) for (int i = 0; i < 3 * nlocal; i++) { yr += dy[c_ind][i] * p_s[i]; } + MPI_Allreduce(&yr, &yr_global, 1, MPI_DOUBLE, MPI_SUM, world); if (update->multireplica == 1) { + yr_global *= factor; yr = yr_global; - MPI_Allreduce(&yr_global,&yr,1,MPI_DOUBLE,MPI_SUM,universe->uworld); + MPI_Allreduce(&yr,&yr_global,1,MPI_DOUBLE,MPI_SUM,universe->uworld); } beta = rho[c_ind] * yr_global; @@ -496,11 +533,12 @@ void MinSpinOSO_LBFGS_LS::calc_search_direction(int iter) } } for (int i = 0; i < 3 * nlocal; i++) { - p_s[i] = -1.0 * p_s[i]; + p_s[i] = - factor * p_s[i]; g_old[i] = g_cur[i]; } } + local_iter++; free(q); free(alpha); @@ -705,7 +743,7 @@ int MinSpinOSO_LBFGS_LS::calc_and_make_step(double a, double b, int index) der_e_cur = e_and_d[1]; index++; - if (awc(der_e_pr, eprevious, e_and_d[1], e_and_d[0]) || index == 3){ + if (awc(der_e_pr, eprevious, e_and_d[1], e_and_d[0]) || index == 5){ MPI_Bcast(&b,1,MPI_DOUBLE,0,world); for (int i = 0; i < 3 * nlocal; i++) { p_s[i] = b * p_s[i]; @@ -728,6 +766,8 @@ int MinSpinOSO_LBFGS_LS::calc_and_make_step(double a, double b, int index) // has minimum at alpha below. We do not check boundaries. alpha = (-c2 + sqrt(c2*c2 - 3.0*c1*c3))/(3.0*c1); + MPI_Bcast(&alpha,1,MPI_DOUBLE,0,world); + if (alpha < 0.0) alpha = r/2.0; for (int i = 0; i < nlocal; i++) { diff --git a/src/SPIN/min_spin_oso_lbfgs_ls.h b/src/SPIN/min_spin_oso_lbfgs_ls.h index 3e0e608ecb..eeaf20adf4 100644 --- a/src/SPIN/min_spin_oso_lbfgs_ls.h +++ b/src/SPIN/min_spin_oso_lbfgs_ls.h @@ -38,9 +38,12 @@ public: void advance_spins(); double fmnorm_sqr(); void calc_gradient(double); - void calc_search_direction(int); + void calc_search_direction(); private: + // test + int ireplica,nreplica; + // global and spin timesteps int nlocal_max; // max value of nlocal (for size of lists) @@ -62,6 +65,7 @@ private: double **sp_copy; // copy of the spins int num_mem; // number of stored steps + int local_iter; double der_e_cur; // current derivative along search dir. double der_e_pr; // previous derivative along search dir. From 45516e329eaa69686823b26394541c077068f9f2 Mon Sep 17 00:00:00 2001 From: alxvov Date: Fri, 19 Jul 2019 09:30:02 +0000 Subject: [PATCH 040/192] delete unused variables and function --- src/SPIN/min_spin_oso_lbfgs_ls.cpp | 174 ++++++++++------------------- src/SPIN/min_spin_oso_lbfgs_ls.h | 15 +-- 2 files changed, 62 insertions(+), 127 deletions(-) diff --git a/src/SPIN/min_spin_oso_lbfgs_ls.cpp b/src/SPIN/min_spin_oso_lbfgs_ls.cpp index e1a6ae99d5..5896ba9a9f 100644 --- a/src/SPIN/min_spin_oso_lbfgs_ls.cpp +++ b/src/SPIN/min_spin_oso_lbfgs_ls.cpp @@ -75,6 +75,7 @@ MinSpinOSO_LBFGS_LS::MinSpinOSO_LBFGS_LS(LAMMPS *lmp) : nreplica = universe->nworlds; ireplica = universe->iworld; + use_line_search = 1; } @@ -88,24 +89,21 @@ MinSpinOSO_LBFGS_LS::~MinSpinOSO_LBFGS_LS() memory->destroy(ds); memory->destroy(dy); memory->destroy(rho); - memory->destroy(sp_copy); + if (use_line_search) + memory->destroy(sp_copy); } /* ---------------------------------------------------------------------- */ void MinSpinOSO_LBFGS_LS::init() { - alpha_damp = 1.0; - discrete_factor = 10.0; num_mem = 3; local_iter = 0; der_e_cur = 0.0; der_e_pr = 0.0; - use_line_search = 1; Min::init(); - dts = dt = update->dt; last_negative = update->ntimestep; // allocate tables @@ -117,7 +115,8 @@ void MinSpinOSO_LBFGS_LS::init() memory->grow(rho,num_mem,"min/spin/oso/lbfgs_ls:rho"); memory->grow(ds,num_mem,3*nlocal_max,"min/spin/oso/lbfgs_ls:ds"); memory->grow(dy,num_mem,3*nlocal_max,"min/spin/oso/lbfgs_ls:dy"); - memory->grow(sp_copy,nlocal_max,3,"min/spin/oso/lbfgs_ls:sp_copy"); + if (use_line_search) + memory->grow(sp_copy,nlocal_max,3,"min/spin/oso/lbfgs_ls:sp_copy"); } @@ -141,14 +140,10 @@ void MinSpinOSO_LBFGS_LS::setup_style() int MinSpinOSO_LBFGS_LS::modify_param(int narg, char **arg) { - if (strcmp(arg[0],"alpha_damp") == 0) { + + if (strcmp(arg[0],"line_search") == 0) { if (narg < 2) error->all(FLERR,"Illegal fix_modify command"); - alpha_damp = force->numeric(FLERR,arg[1]); - return 2; - } - if (strcmp(arg[0],"discrete_factor") == 0) { - if (narg < 2) error->all(FLERR,"Illegal fix_modify command"); - discrete_factor = force->numeric(FLERR,arg[1]); + use_line_search = force->numeric(FLERR,arg[1]); return 2; } return 0; @@ -185,7 +180,7 @@ int MinSpinOSO_LBFGS_LS::iterate(int maxiter) double fmdotfm; int flag, flagall; double **sp = atom->sp; - double der_e_cur_global = 0.0; + double der_e_cur_tmp = 0.0; if (nlocal_max < nlocal) { nlocal_max = nlocal; @@ -195,7 +190,8 @@ int MinSpinOSO_LBFGS_LS::iterate(int maxiter) memory->grow(rho,num_mem,"min/spin/oso/lbfgs_ls:rho"); memory->grow(ds,num_mem,3*nlocal_max,"min/spin/oso/lbfgs_ls:ds"); memory->grow(dy,num_mem,3*nlocal_max,"min/spin/oso/lbfgs_ls:dy"); - memory->grow(sp_copy,nlocal_max,3,"min/spin/oso/lbfgs_ls:sp_copy"); + if (use_line_search) + memory->grow(sp_copy,nlocal_max,3,"min/spin/oso/lbfgs_ls:sp_copy"); } for (int iter = 0; iter < maxiter; iter++) { @@ -211,34 +207,35 @@ int MinSpinOSO_LBFGS_LS::iterate(int maxiter) if (local_iter == 0){ ecurrent = energy_force(0); - calc_gradient(1.0); + calc_gradient(); neval++; } calc_search_direction(); if (use_line_search) { + + // here we need to do line search + der_e_cur = 0.0; for (int i = 0; i < 3 * nlocal; i++) { der_e_cur += g_cur[i] * p_s[i]; } - MPI_Allreduce(&der_e_cur, &der_e_cur_global, 1, MPI_DOUBLE, MPI_SUM, world); - der_e_cur = der_e_cur_global; + MPI_Allreduce(&der_e_cur,&der_e_cur_tmp,1,MPI_DOUBLE,MPI_SUM,world); + der_e_cur = der_e_cur_tmp; if (update->multireplica == 1) { - MPI_Allreduce(&der_e_cur_global,&der_e_cur,1,MPI_DOUBLE,MPI_SUM,universe->uworld); + MPI_Allreduce(&der_e_cur_tmp,&der_e_cur,1,MPI_DOUBLE,MPI_SUM,universe->uworld); } - } - - if (use_line_search){ - // here we need to do line search for (int i = 0; i < nlocal; i++) { for (int j = 0; j < 3; j++) sp_copy[i][j] = sp[i][j]; } eprevious = ecurrent; der_e_pr = der_e_cur; - calc_and_make_step(0.0, 1.0, 0); } else{ + + // here we don't do line search + advance_spins(); eprevious = ecurrent; ecurrent = energy_force(0); @@ -291,56 +288,11 @@ int MinSpinOSO_LBFGS_LS::iterate(int maxiter) return MAXITER; } -/* ---------------------------------------------------------------------- - evaluate max timestep ----------------------------------------------------------------------- */ - -double MinSpinOSO_LBFGS_LS::evaluate_dt() -{ - double dtmax; - double fmsq; - double fmaxsqone,fmaxsqloc,fmaxsqall; - int nlocal = atom->nlocal; - double **fm = atom->fm; - - // finding max fm on this proc. - - fmsq = fmaxsqone = fmaxsqloc = fmaxsqall = 0.0; - for (int i = 0; i < nlocal; i++) { - fmsq = fm[i][0]*fm[i][0]+fm[i][1]*fm[i][1]+fm[i][2]*fm[i][2]; - fmaxsqone = MAX(fmaxsqone,fmsq); - } - - // finding max fm on this replica - - fmaxsqloc = fmaxsqone; - MPI_Allreduce(&fmaxsqone,&fmaxsqloc,1,MPI_DOUBLE,MPI_MAX,world); - - // finding max fm over all replicas, if necessary - // this communicator would be invalid for multiprocess replicas - - fmaxsqall = fmaxsqloc; - if (update->multireplica == 1) { - fmaxsqall = fmaxsqloc; - MPI_Allreduce(&fmaxsqloc,&fmaxsqall,1,MPI_DOUBLE,MPI_MAX,universe->uworld); - } - - if (fmaxsqall == 0.0) - error->all(FLERR,"Incorrect fmaxsqall calculation"); - - // define max timestep by dividing by the - // inverse of max frequency by discrete_factor - - dtmax = MY_2PI/(discrete_factor*sqrt(fmaxsqall)); - - return dtmax; -} - /* ---------------------------------------------------------------------- calculate gradients ---------------------------------------------------------------------- */ -void MinSpinOSO_LBFGS_LS::calc_gradient(double dts) +void MinSpinOSO_LBFGS_LS::calc_gradient() { int nlocal = atom->nlocal; double **sp = atom->sp; @@ -351,17 +303,11 @@ void MinSpinOSO_LBFGS_LS::calc_gradient(double dts) for (int i = 0; i < nlocal; i++) { - // calc. damping torque - - tdampx = -alpha_damp*(fm[i][1]*sp[i][2] - fm[i][2]*sp[i][1]); - tdampy = -alpha_damp*(fm[i][2]*sp[i][0] - fm[i][0]*sp[i][2]); - tdampz = -alpha_damp*(fm[i][0]*sp[i][1] - fm[i][1]*sp[i][0]); - // calculate gradients - g_cur[3 * i + 0] = -tdampz * dts; - g_cur[3 * i + 1] = tdampy * dts; - g_cur[3 * i + 2] = -tdampx * dts; + g_cur[3 * i + 0] = (fm[i][0]*sp[i][1] - fm[i][1]*sp[i][0]); + g_cur[3 * i + 1] = -(fm[i][2]*sp[i][0] - fm[i][0]*sp[i][2]); + g_cur[3 * i + 2] = (fm[i][1]*sp[i][2] - fm[i][2]*sp[i][1]); } } @@ -438,7 +384,7 @@ void MinSpinOSO_LBFGS_LS::calc_search_direction() if (rho[m_index] < 0.0){ local_iter = 0; for (int k = 0; k < num_mem; k++){ - for (int i = 0; i < nlocal; i ++){ + for (int i = 0; i < nlocal; i ++){ ds[k][i] = 0.0; dy[k][i] = 0.0; } @@ -464,7 +410,7 @@ void MinSpinOSO_LBFGS_LS::calc_search_direction() for (int i = 0; i < 3 * nlocal; i++) { sq += ds[c_ind][i] * q[i]; } - MPI_Allreduce(&sq, &sq_global, 1, MPI_DOUBLE, MPI_SUM, world); + MPI_Allreduce(&sq,&sq_global,1,MPI_DOUBLE,MPI_SUM,world); if (update->multireplica == 1) { sq_global *= factor; sq = sq_global; @@ -487,7 +433,7 @@ void MinSpinOSO_LBFGS_LS::calc_search_direction() for (int i = 0; i < 3 * nlocal; i++) { yy += dy[m_index][i] * dy[m_index][i]; } - MPI_Allreduce(&yy, &yy_global, 1, MPI_DOUBLE, MPI_SUM, world); + MPI_Allreduce(&yy,&yy_global,1,MPI_DOUBLE,MPI_SUM,world); if (update->multireplica == 1) { yy_global *= factor; yy = yy_global; @@ -520,7 +466,7 @@ void MinSpinOSO_LBFGS_LS::calc_search_direction() yr += dy[c_ind][i] * p_s[i]; } - MPI_Allreduce(&yr, &yr_global, 1, MPI_DOUBLE, MPI_SUM, world); + MPI_Allreduce(&yr,&yr_global,1,MPI_DOUBLE,MPI_SUM,world); if (update->multireplica == 1) { yr_global *= factor; yr = yr_global; @@ -580,15 +526,11 @@ double MinSpinOSO_LBFGS_LS::fmnorm_sqr() double **sp = atom->sp; double **fm = atom->fm; - // calc. magnetic torques + // calc. magnetic torques norm double local_norm2_sqr = 0.0; - for (int i = 0; i < nlocal; i++) { - tx = (fm[i][1]*sp[i][2] - fm[i][2]*sp[i][1]); - ty = (fm[i][2]*sp[i][0] - fm[i][0]*sp[i][2]); - tz = (fm[i][0]*sp[i][1] - fm[i][1]*sp[i][0]); - - local_norm2_sqr += tx*tx + ty*ty + tz*tz; + for (int i = 0; i < 3 * nlocal; i++) { + local_norm2_sqr += g_cur[i]*g_cur[i]; } // no extra atom calc. for spins @@ -678,9 +620,8 @@ void MinSpinOSO_LBFGS_LS::vm3(const double *m, const double *v, double *out) { for(int i = 0; i < 3; i++){ out[i] *= 0.0; - for(int j = 0; j < 3; j++){ - out[i] += *(m + 3 * j + i) * v[j]; - } + for(int j = 0; j < 3; j++) + out[i] += *(m + 3 * j + i) * v[j]; } } @@ -692,9 +633,10 @@ void MinSpinOSO_LBFGS_LS::make_step(double c, double *energy_and_der) double rot_mat[9]; // exponential of matrix made of search direction double s_new[3]; double **sp = atom->sp; - double der_e_cur_global = 0.0;; + double der_e_cur_tmp = 0.0;; for (int i = 0; i < nlocal; i++) { + // scale the search direction for (int j = 0; j < 3; j++) p_scaled[j] = c * p_s[3 * i + j]; @@ -707,23 +649,23 @@ void MinSpinOSO_LBFGS_LS::make_step(double c, double *energy_and_der) vm3(rot_mat, sp[i], s_new); for (int j = 0; j < 3; j++) sp[i][j] = s_new[j]; - } + } - ecurrent = energy_force(0); - calc_gradient(1.0); - neval++; - der_e_cur = 0.0; - for (int i = 0; i < 3 * nlocal; i++) { - der_e_cur += g_cur[i] * p_s[i]; - } - MPI_Allreduce(&der_e_cur, &der_e_cur_global, 1, MPI_DOUBLE, MPI_SUM, world); - der_e_cur = der_e_cur_global; - if (update->multireplica == 1) { - MPI_Allreduce(&der_e_cur_global,&der_e_cur,1,MPI_DOUBLE,MPI_SUM,universe->uworld); - } + ecurrent = energy_force(0); + calc_gradient(); + neval++; + der_e_cur = 0.0; + for (int i = 0; i < 3 * nlocal; i++) { + der_e_cur += g_cur[i] * p_s[i]; + } + MPI_Allreduce(&der_e_cur,&der_e_cur_tmp, 1, MPI_DOUBLE, MPI_SUM, world); + der_e_cur = der_e_cur_tmp; + if (update->multireplica == 1) { + MPI_Allreduce(&der_e_cur_tmp,&der_e_cur,1,MPI_DOUBLE,MPI_SUM,universe->uworld); + } - energy_and_der[0] = ecurrent; - energy_and_der[1] = der_e_cur; + energy_and_der[0] = ecurrent; + energy_and_der[1] = der_e_cur; } /* ---------------------------------------------------------------------- @@ -733,17 +675,17 @@ void MinSpinOSO_LBFGS_LS::make_step(double c, double *energy_and_der) int MinSpinOSO_LBFGS_LS::calc_and_make_step(double a, double b, int index) { - double e_and_d[2] = {0.0, 0.0}; - double alpha, c1, c2, c3; + double e_and_d[2] = {0.0,0.0}; + double alpha,c1,c2,c3; double **sp = atom->sp; int nlocal = atom->nlocal; - make_step(b, e_and_d); + make_step(b,e_and_d); ecurrent = e_and_d[0]; der_e_cur = e_and_d[1]; index++; - if (awc(der_e_pr, eprevious, e_and_d[1], e_and_d[0]) || index == 5){ + if (awc(der_e_pr,eprevious,e_and_d[1],e_and_d[0]) || index == 5){ MPI_Bcast(&b,1,MPI_DOUBLE,0,world); for (int i = 0; i < 3 * nlocal; i++) { p_s[i] = b * p_s[i]; @@ -751,7 +693,7 @@ int MinSpinOSO_LBFGS_LS::calc_and_make_step(double a, double b, int index) return 1; } else{ - double r, f0, f1, df0, df1; + double r,f0,f1,df0,df1; r = b - a; f0 = eprevious; f1 = ecurrent; @@ -778,18 +720,20 @@ int MinSpinOSO_LBFGS_LS::calc_and_make_step(double a, double b, int index) return 0; } + /* ---------------------------------------------------------------------- Approximate Wolfe conditions: William W. Hager and Hongchao Zhang SIAM J. optim., 16(1), 170-192. (23 pages) ------------------------------------------------------------------------- */ + int MinSpinOSO_LBFGS_LS::awc(double der_phi_0, double phi_0, double der_phi_j, double phi_j){ double eps = 1.0e-6; double delta = 0.1; double sigma = 0.9; - if ((phi_j <= phi_0 + eps * fabs(phi_0)) && ((2.0*delta - 1.0) * der_phi_0 >= der_phi_j >= sigma * der_phi_0)) + if ((phi_j<=phi_0+eps*fabs(phi_0)) && ((2.0*delta-1.0) * der_phi_0>=der_phi_j>=sigma*der_phi_0)) return 1; else return 0; diff --git a/src/SPIN/min_spin_oso_lbfgs_ls.h b/src/SPIN/min_spin_oso_lbfgs_ls.h index eeaf20adf4..876e34f9c9 100644 --- a/src/SPIN/min_spin_oso_lbfgs_ls.h +++ b/src/SPIN/min_spin_oso_lbfgs_ls.h @@ -34,24 +34,15 @@ public: int modify_param(int, char **); void reset_vectors(); int iterate(int); - double evaluate_dt(); void advance_spins(); double fmnorm_sqr(); - void calc_gradient(double); + void calc_gradient(); void calc_search_direction(); private: - // test - int ireplica,nreplica; - - // global and spin timesteps + int ireplica,nreplica; // for neb int nlocal_max; // max value of nlocal (for size of lists) - double dt; - double dts; - - double alpha_damp; // damping for spin minimization - double discrete_factor; // factor for spin timestep evaluation double *spvec; // variables for atomic dof, as 1d vector double *fmvec; // variables for atomic dof, as 1d vector @@ -65,7 +56,7 @@ private: double **sp_copy; // copy of the spins int num_mem; // number of stored steps - int local_iter; + int local_iter; // for neb double der_e_cur; // current derivative along search dir. double der_e_pr; // previous derivative along search dir. From 7514eea9a7112a3962ff208178570125e4d9bb4c Mon Sep 17 00:00:00 2001 From: alxvov Date: Fri, 19 Jul 2019 11:47:24 +0000 Subject: [PATCH 041/192] no line search option too --- src/SPIN/min_spin_oso_lbfgs_ls.cpp | 115 ++++++++++++++++++++--------- src/SPIN/min_spin_oso_lbfgs_ls.h | 6 +- 2 files changed, 83 insertions(+), 38 deletions(-) diff --git a/src/SPIN/min_spin_oso_lbfgs_ls.cpp b/src/SPIN/min_spin_oso_lbfgs_ls.cpp index 5896ba9a9f..ddacd3e207 100644 --- a/src/SPIN/min_spin_oso_lbfgs_ls.cpp +++ b/src/SPIN/min_spin_oso_lbfgs_ls.cpp @@ -76,6 +76,7 @@ MinSpinOSO_LBFGS_LS::MinSpinOSO_LBFGS_LS(LAMMPS *lmp) : nreplica = universe->nworlds; ireplica = universe->iworld; use_line_search = 1; + maxepsrot = MY_2PI / (100.0); } @@ -146,6 +147,13 @@ int MinSpinOSO_LBFGS_LS::modify_param(int narg, char **arg) use_line_search = force->numeric(FLERR,arg[1]); return 2; } + if (strcmp(arg[0],"discrete_factor") == 0) { + if (narg < 2) error->all(FLERR,"Illegal fix_modify command"); + double discrete_factor; + discrete_factor = force->numeric(FLERR,arg[1]); + maxepsrot = MY_2PI / discrete_factor; + return 2; + } return 0; } @@ -184,6 +192,7 @@ int MinSpinOSO_LBFGS_LS::iterate(int maxiter) if (nlocal_max < nlocal) { nlocal_max = nlocal; + local_iter = 0; memory->grow(g_old,3*nlocal_max,"min/spin/oso/lbfgs_ls:g_old"); memory->grow(g_cur,3*nlocal_max,"min/spin/oso/lbfgs_ls:g_cur"); memory->grow(p_s,3*nlocal_max,"min/spin/oso/lbfgs_ls:p_s"); @@ -195,7 +204,7 @@ int MinSpinOSO_LBFGS_LS::iterate(int maxiter) } for (int iter = 0; iter < maxiter; iter++) { - + if (timer->check_timeout(niter)) return TIMEOUT; @@ -205,17 +214,13 @@ int MinSpinOSO_LBFGS_LS::iterate(int maxiter) // optimize timestep accross processes / replicas // need a force calculation for timestep optimization - if (local_iter == 0){ - ecurrent = energy_force(0); - calc_gradient(); - neval++; - } - calc_search_direction(); + if (local_iter == 0) + ecurrent = energy_force(0); if (use_line_search) { // here we need to do line search - + calc_search_direction(); der_e_cur = 0.0; for (int i = 0; i < 3 * nlocal; i++) { der_e_cur += g_cur[i] * p_s[i]; @@ -235,8 +240,22 @@ int MinSpinOSO_LBFGS_LS::iterate(int maxiter) else{ // here we don't do line search + // but use cutoff rotation angle + // if gneb calc., nreplica > 1 + // then calculate gradients and advance spins + // of intermediate replicas only + if (nreplica > 1) { + if(ireplica != 0 && ireplica != nreplica-1) + calc_gradient(); + calc_search_direction(); advance_spins(); + } else{ + calc_gradient(); + calc_search_direction(); + advance_spins(); + } + neval++; eprevious = ecurrent; ecurrent = energy_force(0); neval++; @@ -265,7 +284,7 @@ int MinSpinOSO_LBFGS_LS::iterate(int maxiter) // sync across replicas if running multi-replica minimization if (update->ftol > 0.0) { - fmdotfm = fmnorm_sqr(); + fmdotfm = fmnorm2(); if (update->multireplica == 0) { if (fmdotfm < update->ftol*update->ftol) return FTOL; } else { @@ -340,7 +359,9 @@ void MinSpinOSO_LBFGS_LS::calc_search_direction() double *alpha; double factor; + double scaling = 1.0; + // for multiple replica do not move end points if (nreplica > 1) { if (ireplica == 0 || ireplica == nreplica - 1) { factor = 0.0; @@ -354,9 +375,14 @@ void MinSpinOSO_LBFGS_LS::calc_search_direction() alpha = (double *) calloc(num_mem, sizeof(double)); if (local_iter == 0){ // steepest descent direction + + //if no line search then calculate maximum rotation + if (use_line_search == 0) + scaling = maximum_rotation(g_cur); + for (int i = 0; i < 3 * nlocal; i++) { - p_s[i] = -g_cur[i]; - g_old[i] = g_cur[i]; + p_s[i] = -g_cur[i] * factor * scaling;; + g_old[i] = g_cur[i] * factor; for (int k = 0; k < num_mem; k++){ ds[k][i] = 0.0; dy[k][i] = 0.0; @@ -478,9 +504,11 @@ void MinSpinOSO_LBFGS_LS::calc_search_direction() p_s[i] += ds[c_ind][i] * (alpha[c_ind] - beta); } } + if (use_line_search == 0) + scaling = maximum_rotation(p_s); for (int i = 0; i < 3 * nlocal; i++) { - p_s[i] = - factor * p_s[i]; - g_old[i] = g_cur[i]; + p_s[i] = - factor * p_s[i] * scaling; + g_old[i] = g_cur[i] * factor; } } @@ -516,32 +544,21 @@ void MinSpinOSO_LBFGS_LS::advance_spins() } /* ---------------------------------------------------------------------- - compute and return ||mag. torque||_2^2 + compute and return ||mag. torque||_2^2 / N ------------------------------------------------------------------------- */ -double MinSpinOSO_LBFGS_LS::fmnorm_sqr() -{ +double MinSpinOSO_LBFGS_LS::fmnorm2() { + double norm2, norm2_global; int nlocal = atom->nlocal; - double tx,ty,tz; - double **sp = atom->sp; - double **fm = atom->fm; + int ntotal = 0; - // calc. magnetic torques norm - - double local_norm2_sqr = 0.0; - for (int i = 0; i < 3 * nlocal; i++) { - local_norm2_sqr += g_cur[i]*g_cur[i]; - } - - // no extra atom calc. for spins - - if (nextra_atom) - error->all(FLERR,"extra atom option not available yet"); - - double norm2_sqr = 0.0; - MPI_Allreduce(&local_norm2_sqr,&norm2_sqr,1,MPI_DOUBLE,MPI_SUM,world); - - return norm2_sqr; + norm2 = 0.0; + for (int i = 0; i < 3 * nlocal; i++) norm2 += g_cur[i] * g_cur[i]; + MPI_Allreduce(&norm2, &norm2_global, 1, MPI_DOUBLE, MPI_SUM, world); + MPI_Allreduce(&nlocal, &ntotal, 1, MPI_INT, MPI_SUM, world); + double ans = norm2_global / (double) ntotal; + MPI_Bcast(&ans, 1, MPI_DOUBLE, 0, world); + return ans; } /* ---------------------------------------------------------------------- @@ -738,3 +755,31 @@ int MinSpinOSO_LBFGS_LS::awc(double der_phi_0, double phi_0, double der_phi_j, d else return 0; } + +double MinSpinOSO_LBFGS_LS::maximum_rotation(double *p) +{ + double norm2,norm2_global,scaling,alpha; + int nlocal = atom->nlocal; + int ntotal = 0; + + norm2 = 0.0; + for (int i = 0; i < 3 * nlocal; i++) norm2 += p[i] * p[i]; + + MPI_Allreduce(&norm2,&norm2_global,1,MPI_DOUBLE,MPI_SUM,world); + if (update->multireplica == 1) { + norm2 = norm2_global; + MPI_Allreduce(&norm2,&norm2_global,1,MPI_DOUBLE,MPI_SUM,universe->uworld); + } + MPI_Allreduce(&nlocal,&ntotal,1,MPI_INT,MPI_SUM,world); + if (update->multireplica == 1) { + nlocal = ntotal; + MPI_Allreduce(&nlocal,&ntotal,1,MPI_INT,MPI_SUM,universe->uworld); + } + + scaling = (maxepsrot * sqrt((double) ntotal / norm2_global)); + + if (scaling < 1.0) alpha = scaling; + else alpha = 1.0; + + return alpha; +} \ No newline at end of file diff --git a/src/SPIN/min_spin_oso_lbfgs_ls.h b/src/SPIN/min_spin_oso_lbfgs_ls.h index 876e34f9c9..a253808923 100644 --- a/src/SPIN/min_spin_oso_lbfgs_ls.h +++ b/src/SPIN/min_spin_oso_lbfgs_ls.h @@ -35,10 +35,10 @@ public: void reset_vectors(); int iterate(int); void advance_spins(); - double fmnorm_sqr(); + double fmnorm2(); void calc_gradient(); void calc_search_direction(); - + double maximum_rotation(double *); private: int ireplica,nreplica; // for neb @@ -62,7 +62,7 @@ private: double der_e_pr; // previous derivative along search dir. int use_line_search; // use line search or not. - + double maxepsrot; void vm3(const double *, const double *, double *); void rodrigues_rotation(const double *, double *); From ad713d39a41107601c7337ac281627057c2c451c Mon Sep 17 00:00:00 2001 From: alxvov Date: Fri, 19 Jul 2019 11:58:39 +0000 Subject: [PATCH 042/192] rename min_spin_oso_lbfgs_ls -> min_spin_oso_lbfgs --- src/SPIN/min_spin_oso_lbfgs.cpp | 365 +++++++++----- src/SPIN/min_spin_oso_lbfgs.h | 32 +- src/SPIN/min_spin_oso_lbfgs_ls.cpp | 785 ----------------------------- src/SPIN/min_spin_oso_lbfgs_ls.h | 79 --- 4 files changed, 241 insertions(+), 1020 deletions(-) delete mode 100644 src/SPIN/min_spin_oso_lbfgs_ls.cpp delete mode 100644 src/SPIN/min_spin_oso_lbfgs_ls.h diff --git a/src/SPIN/min_spin_oso_lbfgs.cpp b/src/SPIN/min_spin_oso_lbfgs.cpp index fd83e7b460..7f716da63d 100644 --- a/src/SPIN/min_spin_oso_lbfgs.cpp +++ b/src/SPIN/min_spin_oso_lbfgs.cpp @@ -63,16 +63,18 @@ static const char cite_minstyle_spin_oso_lbfgs[] = /* ---------------------------------------------------------------------- */ MinSpinOSO_LBFGS::MinSpinOSO_LBFGS(LAMMPS *lmp) : - Min(lmp), g_old(NULL), g_cur(NULL), p_s(NULL), ds(NULL), dy(NULL), rho(NULL) + Min(lmp), g_old(NULL), g_cur(NULL), p_s(NULL), ds(NULL), dy(NULL), rho(NULL), sp_copy(NULL) { if (lmp->citeme) lmp->citeme->add(cite_minstyle_spin_oso_lbfgs); nlocal_max = 0; - + // nreplica = number of partitions // ireplica = which world I am in universe nreplica = universe->nworlds; ireplica = universe->iworld; + use_line_search = 1; + maxepsrot = MY_2PI / (100.0); } @@ -86,21 +88,21 @@ MinSpinOSO_LBFGS::~MinSpinOSO_LBFGS() memory->destroy(ds); memory->destroy(dy); memory->destroy(rho); + if (use_line_search) + memory->destroy(sp_copy); } /* ---------------------------------------------------------------------- */ void MinSpinOSO_LBFGS::init() { - alpha_damp = 1.0; - discrete_factor = 10.0; num_mem = 3; local_iter = 0; - maxepsrot = MY_2PI / (100.0); + der_e_cur = 0.0; + der_e_pr = 0.0; Min::init(); - dts = dt = update->dt; last_negative = update->ntimestep; // allocate tables @@ -112,6 +114,8 @@ void MinSpinOSO_LBFGS::init() memory->grow(rho,num_mem,"min/spin/oso/lbfgs:rho"); memory->grow(ds,num_mem,3*nlocal_max,"min/spin/oso/lbfgs:ds"); memory->grow(dy,num_mem,3*nlocal_max,"min/spin/oso/lbfgs:dy"); + if (use_line_search) + memory->grow(sp_copy,nlocal_max,3,"min/spin/oso/lbfgs:sp_copy"); } @@ -135,14 +139,17 @@ void MinSpinOSO_LBFGS::setup_style() int MinSpinOSO_LBFGS::modify_param(int narg, char **arg) { - if (strcmp(arg[0],"alpha_damp") == 0) { + + if (strcmp(arg[0],"line_search") == 0) { if (narg < 2) error->all(FLERR,"Illegal fix_modify command"); - alpha_damp = force->numeric(FLERR,arg[1]); + use_line_search = force->numeric(FLERR,arg[1]); return 2; } if (strcmp(arg[0],"discrete_factor") == 0) { if (narg < 2) error->all(FLERR,"Illegal fix_modify command"); + double discrete_factor; discrete_factor = force->numeric(FLERR,arg[1]); + maxepsrot = MY_2PI / discrete_factor; return 2; } return 0; @@ -178,6 +185,8 @@ int MinSpinOSO_LBFGS::iterate(int maxiter) bigint ntimestep; double fmdotfm; int flag, flagall; + double **sp = atom->sp; + double der_e_cur_tmp = 0.0; if (nlocal_max < nlocal) { nlocal_max = nlocal; @@ -188,10 +197,12 @@ int MinSpinOSO_LBFGS::iterate(int maxiter) memory->grow(rho,num_mem,"min/spin/oso/lbfgs:rho"); memory->grow(ds,num_mem,3*nlocal_max,"min/spin/oso/lbfgs:ds"); memory->grow(dy,num_mem,3*nlocal_max,"min/spin/oso/lbfgs:dy"); + if (use_line_search) + memory->grow(sp_copy,nlocal_max,3,"min/spin/oso/lbfgs:sp_copy"); } for (int iter = 0; iter < maxiter; iter++) { - + if (timer->check_timeout(niter)) return TIMEOUT; @@ -200,29 +211,53 @@ int MinSpinOSO_LBFGS::iterate(int maxiter) // optimize timestep accross processes / replicas // need a force calculation for timestep optimization - if (local_iter == 0) energy_force(0); - // to be checked - // if gneb calc., nreplica > 1 - // then calculate gradients of intermediate replicas - if (nreplica > 1) { + if (local_iter == 0) + ecurrent = energy_force(0); + + if (use_line_search) { + + // here we need to do line search + calc_search_direction(); + der_e_cur = 0.0; + for (int i = 0; i < 3 * nlocal; i++) { + der_e_cur += g_cur[i] * p_s[i]; + } + MPI_Allreduce(&der_e_cur,&der_e_cur_tmp,1,MPI_DOUBLE,MPI_SUM,world); + der_e_cur = der_e_cur_tmp; + if (update->multireplica == 1) { + MPI_Allreduce(&der_e_cur_tmp,&der_e_cur,1,MPI_DOUBLE,MPI_SUM,universe->uworld); + } + for (int i = 0; i < nlocal; i++) { + for (int j = 0; j < 3; j++) sp_copy[i][j] = sp[i][j]; + } + eprevious = ecurrent; + der_e_pr = der_e_cur; + calc_and_make_step(0.0, 1.0, 0); + } + else{ + + // here we don't do line search + // but use cutoff rotation angle + // if gneb calc., nreplica > 1 + // then calculate gradients and advance spins + // of intermediate replicas only + + if (nreplica > 1) { if(ireplica != 0 && ireplica != nreplica-1) - calc_gradient(1.0); - } else calc_gradient(1.0); - calc_search_direction(); - - // to be checked - // if gneb calc., nreplica > 1 - // then advance spins only if intermediate replica - // otherwise (simple minimization), advance spins - - if (nreplica > 1) { - if(ireplica != 0 && ireplica != nreplica-1) - advance_spins(); - } else advance_spins(); - eprevious = ecurrent; - ecurrent = energy_force(0); - neval++; + calc_gradient(); + calc_search_direction(); + advance_spins(); + } else{ + calc_gradient(); + calc_search_direction(); + advance_spins(); + } + neval++; + eprevious = ecurrent; + ecurrent = energy_force(0); + neval++; + } //// energy tolerance criterion //// only check after DELAYSTEP elapsed since velocties reset to 0 @@ -247,7 +282,7 @@ int MinSpinOSO_LBFGS::iterate(int maxiter) // sync across replicas if running multi-replica minimization if (update->ftol > 0.0) { - fmdotfm = fmnorm_sqr(); + fmdotfm = fmnorm2(); if (update->multireplica == 0) { if (fmdotfm < update->ftol*update->ftol) return FTOL; } else { @@ -270,56 +305,11 @@ int MinSpinOSO_LBFGS::iterate(int maxiter) return MAXITER; } -/* ---------------------------------------------------------------------- - evaluate max timestep ----------------------------------------------------------------------- */ - -double MinSpinOSO_LBFGS::evaluate_dt() -{ - double dtmax; - double fmsq; - double fmaxsqone,fmaxsqloc,fmaxsqall; - int nlocal = atom->nlocal; - double **fm = atom->fm; - - // finding max fm on this proc. - - fmsq = fmaxsqone = fmaxsqloc = fmaxsqall = 0.0; - for (int i = 0; i < nlocal; i++) { - fmsq = fm[i][0]*fm[i][0]+fm[i][1]*fm[i][1]+fm[i][2]*fm[i][2]; - fmaxsqone = MAX(fmaxsqone,fmsq); - } - - // finding max fm on this replica - - fmaxsqloc = fmaxsqone; - MPI_Allreduce(&fmaxsqone,&fmaxsqloc,1,MPI_DOUBLE,MPI_MAX,world); - - // finding max fm over all replicas, if necessary - // this communicator would be invalid for multiprocess replicas - - fmaxsqall = fmaxsqloc; - if (update->multireplica == 1) { - fmaxsqall = fmaxsqloc; - MPI_Allreduce(&fmaxsqloc,&fmaxsqall,1,MPI_DOUBLE,MPI_MAX,universe->uworld); - } - - if (fmaxsqall == 0.0) - error->all(FLERR,"Incorrect fmaxsqall calculation"); - - // define max timestep by dividing by the - // inverse of max frequency by discrete_factor - // std::cout << fmaxsqall << "\n"; - dtmax = MY_2PI/(discrete_factor*sqrt(fmaxsqall)); - - return dtmax; -} - /* ---------------------------------------------------------------------- calculate gradients ---------------------------------------------------------------------- */ -void MinSpinOSO_LBFGS::calc_gradient(double dts) +void MinSpinOSO_LBFGS::calc_gradient() { int nlocal = atom->nlocal; double **sp = atom->sp; @@ -330,17 +320,11 @@ void MinSpinOSO_LBFGS::calc_gradient(double dts) for (int i = 0; i < nlocal; i++) { - // calc. damping torque - - tdampx = -alpha_damp*(fm[i][1]*sp[i][2] - fm[i][2]*sp[i][1]); - tdampy = -alpha_damp*(fm[i][2]*sp[i][0] - fm[i][0]*sp[i][2]); - tdampz = -alpha_damp*(fm[i][0]*sp[i][1] - fm[i][1]*sp[i][0]); - // calculate gradients - g_cur[3 * i + 0] = -tdampz * dts; - g_cur[3 * i + 1] = tdampy * dts; - g_cur[3 * i + 2] = -tdampx * dts; + g_cur[3 * i + 0] = (fm[i][0]*sp[i][1] - fm[i][1]*sp[i][0]); + g_cur[3 * i + 1] = -(fm[i][2]*sp[i][0] - fm[i][0]*sp[i][2]); + g_cur[3 * i + 2] = (fm[i][1]*sp[i][2] - fm[i][2]*sp[i][1]); } } @@ -373,8 +357,9 @@ void MinSpinOSO_LBFGS::calc_search_direction() double *alpha; double factor; - double scaling; + double scaling = 1.0; + // for multiple replica do not move end points if (nreplica > 1) { if (ireplica == 0 || ireplica == nreplica - 1) { factor = 0.0; @@ -388,14 +373,19 @@ void MinSpinOSO_LBFGS::calc_search_direction() alpha = (double *) calloc(num_mem, sizeof(double)); if (local_iter == 0){ // steepest descent direction - - scaling = maximum_rotation(g_cur); - for (int i = 0; i < 3 * nlocal; i++) { - p_s[i] = - g_cur[i] * factor * scaling; - g_old[i] = g_cur[i]; - ds[m_index][i] = 0.0; - dy[m_index][i] = 0.0; + //if no line search then calculate maximum rotation + if (use_line_search == 0) + scaling = maximum_rotation(g_cur); + + for (int i = 0; i < 3 * nlocal; i++) { + p_s[i] = -g_cur[i] * factor * scaling;; + g_old[i] = g_cur[i] * factor; + for (int k = 0; k < num_mem; k++){ + ds[k][i] = 0.0; + dy[k][i] = 0.0; + rho[k] = 0.0; + } } } else { dyds = 0.0; @@ -418,7 +408,7 @@ void MinSpinOSO_LBFGS::calc_search_direction() if (rho[m_index] < 0.0){ local_iter = 0; for (int k = 0; k < num_mem; k++){ - for (int i = 0; i < nlocal; i ++){ + for (int i = 0; i < nlocal; i ++){ ds[k][i] = 0.0; dy[k][i] = 0.0; } @@ -444,7 +434,7 @@ void MinSpinOSO_LBFGS::calc_search_direction() for (int i = 0; i < 3 * nlocal; i++) { sq += ds[c_ind][i] * q[i]; } - MPI_Allreduce(&sq, &sq_global, 1, MPI_DOUBLE, MPI_SUM, world); + MPI_Allreduce(&sq,&sq_global,1,MPI_DOUBLE,MPI_SUM,world); if (update->multireplica == 1) { sq_global *= factor; sq = sq_global; @@ -467,7 +457,7 @@ void MinSpinOSO_LBFGS::calc_search_direction() for (int i = 0; i < 3 * nlocal; i++) { yy += dy[m_index][i] * dy[m_index][i]; } - MPI_Allreduce(&yy, &yy_global, 1, MPI_DOUBLE, MPI_SUM, world); + MPI_Allreduce(&yy,&yy_global,1,MPI_DOUBLE,MPI_SUM,world); if (update->multireplica == 1) { yy_global *= factor; yy = yy_global; @@ -500,7 +490,7 @@ void MinSpinOSO_LBFGS::calc_search_direction() yr += dy[c_ind][i] * p_s[i]; } - MPI_Allreduce(&yr, &yr_global, 1, MPI_DOUBLE, MPI_SUM, world); + MPI_Allreduce(&yr,&yr_global,1,MPI_DOUBLE,MPI_SUM,world); if (update->multireplica == 1) { yr_global *= factor; yr = yr_global; @@ -512,10 +502,11 @@ void MinSpinOSO_LBFGS::calc_search_direction() p_s[i] += ds[c_ind][i] * (alpha[c_ind] - beta); } } - scaling = maximum_rotation(p_s); + if (use_line_search == 0) + scaling = maximum_rotation(p_s); for (int i = 0; i < 3 * nlocal; i++) { p_s[i] = - factor * p_s[i] * scaling; - g_old[i] = g_cur[i]; + g_old[i] = g_cur[i] * factor; } } @@ -551,36 +542,21 @@ void MinSpinOSO_LBFGS::advance_spins() } /* ---------------------------------------------------------------------- - compute and return ||mag. torque||_2^2 + compute and return ||mag. torque||_2^2 / N ------------------------------------------------------------------------- */ -double MinSpinOSO_LBFGS::fmnorm_sqr() -{ +double MinSpinOSO_LBFGS::fmnorm2() { + double norm2, norm2_global; int nlocal = atom->nlocal; - double tx,ty,tz; - double **sp = atom->sp; - double **fm = atom->fm; + int ntotal = 0; - // calc. magnetic torques - - double local_norm2_sqr = 0.0; - for (int i = 0; i < nlocal; i++) { - tx = (fm[i][1]*sp[i][2] - fm[i][2]*sp[i][1]); - ty = (fm[i][2]*sp[i][0] - fm[i][0]*sp[i][2]); - tz = (fm[i][0]*sp[i][1] - fm[i][1]*sp[i][0]); - - local_norm2_sqr += tx*tx + ty*ty + tz*tz; - } - - // no extra atom calc. for spins - - if (nextra_atom) - error->all(FLERR,"extra atom option not available yet"); - - double norm2_sqr = 0.0; - MPI_Allreduce(&local_norm2_sqr,&norm2_sqr,1,MPI_DOUBLE,MPI_SUM,world); - - return norm2_sqr; + norm2 = 0.0; + for (int i = 0; i < 3 * nlocal; i++) norm2 += g_cur[i] * g_cur[i]; + MPI_Allreduce(&norm2, &norm2_global, 1, MPI_DOUBLE, MPI_SUM, world); + MPI_Allreduce(&nlocal, &ntotal, 1, MPI_INT, MPI_SUM, world); + double ans = norm2_global / (double) ntotal; + MPI_Bcast(&ans, 1, MPI_DOUBLE, 0, world); + return ans; } /* ---------------------------------------------------------------------- @@ -659,38 +635,149 @@ void MinSpinOSO_LBFGS::vm3(const double *m, const double *v, double *out) { for(int i = 0; i < 3; i++){ out[i] *= 0.0; - for(int j = 0; j < 3; j++){ - out[i] += *(m + 3 * j + i) * v[j]; - } + for(int j = 0; j < 3; j++) + out[i] += *(m + 3 * j + i) * v[j]; } } + +void MinSpinOSO_LBFGS::make_step(double c, double *energy_and_der) +{ + double p_scaled[3]; + int nlocal = atom->nlocal; + double rot_mat[9]; // exponential of matrix made of search direction + double s_new[3]; + double **sp = atom->sp; + double der_e_cur_tmp = 0.0;; + + for (int i = 0; i < nlocal; i++) { + + // scale the search direction + + for (int j = 0; j < 3; j++) p_scaled[j] = c * p_s[3 * i + j]; + + // calculate rotation matrix + + rodrigues_rotation(p_scaled, rot_mat); + + // rotate spins + + vm3(rot_mat, sp[i], s_new); + for (int j = 0; j < 3; j++) sp[i][j] = s_new[j]; + } + + ecurrent = energy_force(0); + calc_gradient(); + neval++; + der_e_cur = 0.0; + for (int i = 0; i < 3 * nlocal; i++) { + der_e_cur += g_cur[i] * p_s[i]; + } + MPI_Allreduce(&der_e_cur,&der_e_cur_tmp, 1, MPI_DOUBLE, MPI_SUM, world); + der_e_cur = der_e_cur_tmp; + if (update->multireplica == 1) { + MPI_Allreduce(&der_e_cur_tmp,&der_e_cur,1,MPI_DOUBLE,MPI_SUM,universe->uworld); + } + + energy_and_der[0] = ecurrent; + energy_and_der[1] = der_e_cur; +} + +/* ---------------------------------------------------------------------- + Calculate step length which satisfies approximate Wolfe conditions + using the cubic interpolation +------------------------------------------------------------------------- */ + +int MinSpinOSO_LBFGS::calc_and_make_step(double a, double b, int index) +{ + double e_and_d[2] = {0.0,0.0}; + double alpha,c1,c2,c3; + double **sp = atom->sp; + int nlocal = atom->nlocal; + + make_step(b,e_and_d); + ecurrent = e_and_d[0]; + der_e_cur = e_and_d[1]; + index++; + + if (awc(der_e_pr,eprevious,e_and_d[1],e_and_d[0]) || index == 5){ + MPI_Bcast(&b,1,MPI_DOUBLE,0,world); + for (int i = 0; i < 3 * nlocal; i++) { + p_s[i] = b * p_s[i]; + } + return 1; + } + else{ + double r,f0,f1,df0,df1; + r = b - a; + f0 = eprevious; + f1 = ecurrent; + df0 = der_e_pr; + df1 = der_e_cur; + + c1 = -2.0*(f1-f0)/(r*r*r)+(df1+df0)/(r*r); + c2 = 3.0*(f1-f0)/(r*r)-(df1+2.0*df0)/(r); + c3 = df0; + + // f(x) = c1 x^3 + c2 x^2 + c3 x^1 + c4 + // has minimum at alpha below. We do not check boundaries. + + alpha = (-c2 + sqrt(c2*c2 - 3.0*c1*c3))/(3.0*c1); + MPI_Bcast(&alpha,1,MPI_DOUBLE,0,world); + + if (alpha < 0.0) alpha = r/2.0; + + for (int i = 0; i < nlocal; i++) { + for (int j = 0; j < 3; j++) sp[i][j] = sp_copy[i][j]; + } + calc_and_make_step(0.0, alpha, index); + } + + return 0; +} + +/* ---------------------------------------------------------------------- + Approximate Wolfe conditions: + William W. Hager and Hongchao Zhang + SIAM J. optim., 16(1), 170-192. (23 pages) +------------------------------------------------------------------------- */ + +int MinSpinOSO_LBFGS::awc(double der_phi_0, double phi_0, double der_phi_j, double phi_j){ + + double eps = 1.0e-6; + double delta = 0.1; + double sigma = 0.9; + + if ((phi_j<=phi_0+eps*fabs(phi_0)) && ((2.0*delta-1.0) * der_phi_0>=der_phi_j>=sigma*der_phi_0)) + return 1; + else + return 0; +} + double MinSpinOSO_LBFGS::maximum_rotation(double *p) { - double norm, norm_global, scaling, alpha; + double norm2,norm2_global,scaling,alpha; int nlocal = atom->nlocal; int ntotal = 0; - norm = 0.0; - for (int i = 0; i < 3 * nlocal; i++) norm += p[i] * p[i]; + norm2 = 0.0; + for (int i = 0; i < 3 * nlocal; i++) norm2 += p[i] * p[i]; - MPI_Allreduce(&norm,&norm_global,1,MPI_DOUBLE,MPI_SUM,world); + MPI_Allreduce(&norm2,&norm2_global,1,MPI_DOUBLE,MPI_SUM,world); if (update->multireplica == 1) { - norm = norm_global; - MPI_Allreduce(&norm,&norm_global,1,MPI_DOUBLE,MPI_SUM,universe->uworld); + norm2 = norm2_global; + MPI_Allreduce(&norm2,&norm2_global,1,MPI_DOUBLE,MPI_SUM,universe->uworld); } - MPI_Allreduce(&nlocal,&ntotal,1,MPI_INT,MPI_SUM,world); if (update->multireplica == 1) { nlocal = ntotal; MPI_Allreduce(&nlocal,&ntotal,1,MPI_INT,MPI_SUM,universe->uworld); } - scaling = (maxepsrot * sqrt((double) ntotal / norm_global)); + scaling = (maxepsrot * sqrt((double) ntotal / norm2_global)); if (scaling < 1.0) alpha = scaling; else alpha = 1.0; return alpha; -} - +} \ No newline at end of file diff --git a/src/SPIN/min_spin_oso_lbfgs.h b/src/SPIN/min_spin_oso_lbfgs.h index c0f8dc484d..91c900f244 100644 --- a/src/SPIN/min_spin_oso_lbfgs.h +++ b/src/SPIN/min_spin_oso_lbfgs.h @@ -24,7 +24,7 @@ MinimizeStyle(spin/oso_lbfgs, MinSpinOSO_LBFGS) namespace LAMMPS_NS { -class MinSpinOSO_LBFGS : public Min { +class MinSpinOSO_LBFGS: public Min { public: MinSpinOSO_LBFGS(class LAMMPS *); @@ -34,26 +34,15 @@ public: int modify_param(int, char **); void reset_vectors(); int iterate(int); - double evaluate_dt(); void advance_spins(); - double fmnorm_sqr(); - void calc_gradient(double); + double fmnorm2(); + void calc_gradient(); void calc_search_direction(); double maximum_rotation(double *); private: - - - // test - int ireplica,nreplica; - - // global and spin timesteps + int ireplica,nreplica; // for neb int nlocal_max; // max value of nlocal (for size of lists) - double dt; - double dts; - - double alpha_damp; // damping for spin minimization - double discrete_factor; // factor for spin timestep evaluation double *spvec; // variables for atomic dof, as 1d vector double *fmvec; // variables for atomic dof, as 1d vector @@ -64,13 +53,22 @@ private: double **ds; // change in rotation matrix between two iterations, da double **dy; // change in gradients between two iterations, dg double *rho; // estimation of curvature - int num_mem; // number of stored steps - int local_iter; // number of times we call search_direction + double **sp_copy; // copy of the spins + int num_mem; // number of stored steps + int local_iter; // for neb + + double der_e_cur; // current derivative along search dir. + double der_e_pr; // previous derivative along search dir. + + int use_line_search; // use line search or not. double maxepsrot; void vm3(const double *, const double *, double *); void rodrigues_rotation(const double *, double *); + int calc_and_make_step(double, double, int); + int awc(double, double, double, double); + void make_step(double, double *); bigint last_negative; }; diff --git a/src/SPIN/min_spin_oso_lbfgs_ls.cpp b/src/SPIN/min_spin_oso_lbfgs_ls.cpp deleted file mode 100644 index ddacd3e207..0000000000 --- a/src/SPIN/min_spin_oso_lbfgs_ls.cpp +++ /dev/null @@ -1,785 +0,0 @@ -/* ---------------------------------------------------------------------- - LAMMPS - Large-scale Atomic/Molecular Massively Parallel Simulator - http://lammps.sandia.gov, Sandia National Laboratories - Steve Plimpton, sjplimp@sandia.gov - - Copyright (2003) Sandia Corporation. Under the terms of Contract - DE-AC04-94AL85000 with Sandia Corporation, the U.S. Government retains - certain rights in this software. This software is distributed under - the GNU General Public License. - - See the README file in the top-level LAMMPS directory. -------------------------------------------------------------------------- */ - -/* ------------------------------------------------------------------------ - Contributing authors: Aleksei Ivanov (University of Iceland) - Julien Tranchida (SNL) - - Please cite the related publication: - Ivanov, A. V., Uzdin, V. M., & Jónsson, H. (2019). Fast and Robust - Algorithm for the Minimisation of the Energy of Spin Systems. arXiv - preprint arXiv:1904.02669. -------------------------------------------------------------------------- */ - -#include -#include -#include -#include -#include "min_spin_oso_lbfgs_ls.h" -#include "universe.h" -#include "atom.h" -#include "citeme.h" -#include "force.h" -#include "update.h" -#include "output.h" -#include "timer.h" -#include "error.h" -#include "memory.h" -#include "modify.h" -#include "math_special.h" -#include "math_const.h" -#include "universe.h" -#include - - -using namespace LAMMPS_NS; -using namespace MathConst; - -static const char cite_minstyle_spin_oso_lbfgs_ls[] = - "min_style spin/oso_lbfgs_ls command:\n\n" - "@article{ivanov2019fast,\n" - "title={Fast and Robust Algorithm for the Minimisation of the Energy of " - "Spin Systems},\n" - "author={Ivanov, A. V and Uzdin, V. M. and J{\'o}nsson, H.},\n" - "journal={arXiv preprint arXiv:1904.02669},\n" - "year={2019}\n" - "}\n\n"; - -// EPS_ENERGY = minimum normalization for energy tolerance - -#define EPS_ENERGY 1.0e-8 - -#define DELAYSTEP 5 - - -/* ---------------------------------------------------------------------- */ - -MinSpinOSO_LBFGS_LS::MinSpinOSO_LBFGS_LS(LAMMPS *lmp) : - Min(lmp), g_old(NULL), g_cur(NULL), p_s(NULL), ds(NULL), dy(NULL), rho(NULL), sp_copy(NULL) -{ - if (lmp->citeme) lmp->citeme->add(cite_minstyle_spin_oso_lbfgs_ls); - nlocal_max = 0; - - // nreplica = number of partitions - // ireplica = which world I am in universe - - nreplica = universe->nworlds; - ireplica = universe->iworld; - use_line_search = 1; - maxepsrot = MY_2PI / (100.0); - -} - -/* ---------------------------------------------------------------------- */ - -MinSpinOSO_LBFGS_LS::~MinSpinOSO_LBFGS_LS() -{ - memory->destroy(g_old); - memory->destroy(g_cur); - memory->destroy(p_s); - memory->destroy(ds); - memory->destroy(dy); - memory->destroy(rho); - if (use_line_search) - memory->destroy(sp_copy); -} - -/* ---------------------------------------------------------------------- */ - -void MinSpinOSO_LBFGS_LS::init() -{ - num_mem = 3; - local_iter = 0; - der_e_cur = 0.0; - der_e_pr = 0.0; - - Min::init(); - - last_negative = update->ntimestep; - - // allocate tables - - nlocal_max = atom->nlocal; - memory->grow(g_old,3*nlocal_max,"min/spin/oso/lbfgs_ls:g_old"); - memory->grow(g_cur,3*nlocal_max,"min/spin/oso/lbfgs_ls:g_cur"); - memory->grow(p_s,3*nlocal_max,"min/spin/oso/lbfgs_ls:p_s"); - memory->grow(rho,num_mem,"min/spin/oso/lbfgs_ls:rho"); - memory->grow(ds,num_mem,3*nlocal_max,"min/spin/oso/lbfgs_ls:ds"); - memory->grow(dy,num_mem,3*nlocal_max,"min/spin/oso/lbfgs_ls:dy"); - if (use_line_search) - memory->grow(sp_copy,nlocal_max,3,"min/spin/oso/lbfgs_ls:sp_copy"); - -} - -/* ---------------------------------------------------------------------- */ - -void MinSpinOSO_LBFGS_LS::setup_style() -{ - double **v = atom->v; - int nlocal = atom->nlocal; - - // check if the atom/spin style is defined - - if (!atom->sp_flag) - error->all(FLERR,"min/spin_oso_lbfgs_ls requires atom/spin style"); - - for (int i = 0; i < nlocal; i++) - v[i][0] = v[i][1] = v[i][2] = 0.0; -} - -/* ---------------------------------------------------------------------- */ - -int MinSpinOSO_LBFGS_LS::modify_param(int narg, char **arg) -{ - - if (strcmp(arg[0],"line_search") == 0) { - if (narg < 2) error->all(FLERR,"Illegal fix_modify command"); - use_line_search = force->numeric(FLERR,arg[1]); - return 2; - } - if (strcmp(arg[0],"discrete_factor") == 0) { - if (narg < 2) error->all(FLERR,"Illegal fix_modify command"); - double discrete_factor; - discrete_factor = force->numeric(FLERR,arg[1]); - maxepsrot = MY_2PI / discrete_factor; - return 2; - } - return 0; -} - -/* ---------------------------------------------------------------------- - set current vector lengths and pointers - called after atoms have migrated -------------------------------------------------------------------------- */ - -void MinSpinOSO_LBFGS_LS::reset_vectors() -{ - // atomic dof - - // size sp is 4N vector - nvec = 4 * atom->nlocal; - if (nvec) spvec = atom->sp[0]; - - nvec = 3 * atom->nlocal; - if (nvec) fmvec = atom->fm[0]; - - if (nvec) xvec = atom->x[0]; - if (nvec) fvec = atom->f[0]; -} - -/* ---------------------------------------------------------------------- - minimization via damped spin dynamics -------------------------------------------------------------------------- */ - -int MinSpinOSO_LBFGS_LS::iterate(int maxiter) -{ - int nlocal = atom->nlocal; - bigint ntimestep; - double fmdotfm; - int flag, flagall; - double **sp = atom->sp; - double der_e_cur_tmp = 0.0; - - if (nlocal_max < nlocal) { - nlocal_max = nlocal; - local_iter = 0; - memory->grow(g_old,3*nlocal_max,"min/spin/oso/lbfgs_ls:g_old"); - memory->grow(g_cur,3*nlocal_max,"min/spin/oso/lbfgs_ls:g_cur"); - memory->grow(p_s,3*nlocal_max,"min/spin/oso/lbfgs_ls:p_s"); - memory->grow(rho,num_mem,"min/spin/oso/lbfgs_ls:rho"); - memory->grow(ds,num_mem,3*nlocal_max,"min/spin/oso/lbfgs_ls:ds"); - memory->grow(dy,num_mem,3*nlocal_max,"min/spin/oso/lbfgs_ls:dy"); - if (use_line_search) - memory->grow(sp_copy,nlocal_max,3,"min/spin/oso/lbfgs_ls:sp_copy"); - } - - for (int iter = 0; iter < maxiter; iter++) { - - if (timer->check_timeout(niter)) - return TIMEOUT; - - ntimestep = ++update->ntimestep; - niter++; - - // optimize timestep accross processes / replicas - // need a force calculation for timestep optimization - - if (local_iter == 0) - ecurrent = energy_force(0); - - if (use_line_search) { - - // here we need to do line search - calc_search_direction(); - der_e_cur = 0.0; - for (int i = 0; i < 3 * nlocal; i++) { - der_e_cur += g_cur[i] * p_s[i]; - } - MPI_Allreduce(&der_e_cur,&der_e_cur_tmp,1,MPI_DOUBLE,MPI_SUM,world); - der_e_cur = der_e_cur_tmp; - if (update->multireplica == 1) { - MPI_Allreduce(&der_e_cur_tmp,&der_e_cur,1,MPI_DOUBLE,MPI_SUM,universe->uworld); - } - for (int i = 0; i < nlocal; i++) { - for (int j = 0; j < 3; j++) sp_copy[i][j] = sp[i][j]; - } - eprevious = ecurrent; - der_e_pr = der_e_cur; - calc_and_make_step(0.0, 1.0, 0); - } - else{ - - // here we don't do line search - // but use cutoff rotation angle - // if gneb calc., nreplica > 1 - // then calculate gradients and advance spins - // of intermediate replicas only - - if (nreplica > 1) { - if(ireplica != 0 && ireplica != nreplica-1) - calc_gradient(); - calc_search_direction(); - advance_spins(); - } else{ - calc_gradient(); - calc_search_direction(); - advance_spins(); - } - neval++; - eprevious = ecurrent; - ecurrent = energy_force(0); - neval++; - } - - //// energy tolerance criterion - //// only check after DELAYSTEP elapsed since velocties reset to 0 - //// sync across replicas if running multi-replica minimization - - if (update->etol > 0.0 && ntimestep-last_negative > DELAYSTEP) { - if (update->multireplica == 0) { - if (fabs(ecurrent-eprevious) < - update->etol * 0.5*(fabs(ecurrent) + fabs(eprevious) + EPS_ENERGY)) - return ETOL; - } else { - if (fabs(ecurrent-eprevious) < - update->etol * 0.5*(fabs(ecurrent) + fabs(eprevious) + EPS_ENERGY)) - flag = 0; - else flag = 1; - MPI_Allreduce(&flag,&flagall,1,MPI_INT,MPI_SUM,universe->uworld); - if (flagall == 0) return ETOL; - } - } - - // magnetic torque tolerance criterion - // sync across replicas if running multi-replica minimization - - if (update->ftol > 0.0) { - fmdotfm = fmnorm2(); - if (update->multireplica == 0) { - if (fmdotfm < update->ftol*update->ftol) return FTOL; - } else { - if (fmdotfm < update->ftol*update->ftol) flag = 0; - else flag = 1; - MPI_Allreduce(&flag,&flagall,1,MPI_INT,MPI_SUM,universe->uworld); - if (flagall == 0) return FTOL; - } - } - - // output for thermo, dump, restart files - - if (output->next == ntimestep) { - timer->stamp(); - output->write(ntimestep); - timer->stamp(Timer::OUTPUT); - } - } - - return MAXITER; -} - -/* ---------------------------------------------------------------------- - calculate gradients ----------------------------------------------------------------------- */ - -void MinSpinOSO_LBFGS_LS::calc_gradient() -{ - int nlocal = atom->nlocal; - double **sp = atom->sp; - double **fm = atom->fm; - double tdampx, tdampy, tdampz; - - // loop on all spins on proc. - - for (int i = 0; i < nlocal; i++) { - - // calculate gradients - - g_cur[3 * i + 0] = (fm[i][0]*sp[i][1] - fm[i][1]*sp[i][0]); - g_cur[3 * i + 1] = -(fm[i][2]*sp[i][0] - fm[i][0]*sp[i][2]); - g_cur[3 * i + 2] = (fm[i][1]*sp[i][2] - fm[i][2]*sp[i][1]); - } -} - -/* ---------------------------------------------------------------------- - search direction: - Limited-memory BFGS. - See Jorge Nocedal and Stephen J. Wright 'Numerical - Optimization' Second Edition, 2006 (p. 177) ----------------------------------------------------------------------- */ - -void MinSpinOSO_LBFGS_LS::calc_search_direction() -{ - int nlocal = atom->nlocal; - - double dyds = 0.0; - double sq = 0.0; - double yy = 0.0; - double yr = 0.0; - double beta = 0.0; - - double dyds_global = 0.0; - double sq_global = 0.0; - double yy_global = 0.0; - double yr_global = 0.0; - double beta_global = 0.0; - - int m_index = local_iter % num_mem; // memory index - int c_ind = 0; - double *q; - double *alpha; - - double factor; - double scaling = 1.0; - - // for multiple replica do not move end points - if (nreplica > 1) { - if (ireplica == 0 || ireplica == nreplica - 1) { - factor = 0.0; - } - else factor = 1.0; - }else{ - factor = 1.0; - } - - q = (double *) calloc(3*nlocal, sizeof(double)); - alpha = (double *) calloc(num_mem, sizeof(double)); - - if (local_iter == 0){ // steepest descent direction - - //if no line search then calculate maximum rotation - if (use_line_search == 0) - scaling = maximum_rotation(g_cur); - - for (int i = 0; i < 3 * nlocal; i++) { - p_s[i] = -g_cur[i] * factor * scaling;; - g_old[i] = g_cur[i] * factor; - for (int k = 0; k < num_mem; k++){ - ds[k][i] = 0.0; - dy[k][i] = 0.0; - rho[k] = 0.0; - } - } - } else { - dyds = 0.0; - for (int i = 0; i < 3 * nlocal; i++) { - ds[m_index][i] = p_s[i]; - dy[m_index][i] = g_cur[i] - g_old[i]; - dyds += ds[m_index][i] * dy[m_index][i]; - } - MPI_Allreduce(&dyds, &dyds_global, 1, MPI_DOUBLE, MPI_SUM, world); - - if (update->multireplica == 1) { - dyds_global *= factor; - dyds = dyds_global; - MPI_Allreduce(&dyds, &dyds_global, 1,MPI_DOUBLE,MPI_SUM,universe->uworld); - } - - if (fabs(dyds_global) > 1.0e-60) rho[m_index] = 1.0 / dyds_global; - else rho[m_index] = 1.0e60; - - if (rho[m_index] < 0.0){ - local_iter = 0; - for (int k = 0; k < num_mem; k++){ - for (int i = 0; i < nlocal; i ++){ - ds[k][i] = 0.0; - dy[k][i] = 0.0; - } - } - return calc_search_direction(); - } - - // set the q vector - - for (int i = 0; i < 3 * nlocal; i++) { - q[i] = g_cur[i]; - } - - // loop over last m indecies - for(int k = num_mem - 1; k > -1; k--) { - // this loop should run from the newest memory to the oldest one. - - c_ind = (k + m_index + 1) % num_mem; - - // dot product between dg and q - - sq = 0.0; - for (int i = 0; i < 3 * nlocal; i++) { - sq += ds[c_ind][i] * q[i]; - } - MPI_Allreduce(&sq,&sq_global,1,MPI_DOUBLE,MPI_SUM,world); - if (update->multireplica == 1) { - sq_global *= factor; - sq = sq_global; - MPI_Allreduce(&sq,&sq_global,1,MPI_DOUBLE,MPI_SUM,universe->uworld); - } - - // update alpha - - alpha[c_ind] = rho[c_ind] * sq_global; - - // update q - - for (int i = 0; i < 3 * nlocal; i++) { - q[i] -= alpha[c_ind] * dy[c_ind][i]; - } - } - - // dot product between dg with itself - yy = 0.0; - for (int i = 0; i < 3 * nlocal; i++) { - yy += dy[m_index][i] * dy[m_index][i]; - } - MPI_Allreduce(&yy,&yy_global,1,MPI_DOUBLE,MPI_SUM,world); - if (update->multireplica == 1) { - yy_global *= factor; - yy = yy_global; - MPI_Allreduce(&yy,&yy_global,1,MPI_DOUBLE,MPI_SUM,universe->uworld); - } - - // calculate now search direction - - double devis = rho[m_index] * yy_global; - - if (fabs(devis) > 1.0e-60) { - for (int i = 0; i < 3 * nlocal; i++) { - p_s[i] = factor * q[i] / devis; - } - }else{ - for (int i = 0; i < 3 * nlocal; i++) { - p_s[i] = factor * q[i] * 1.0e60; - } - } - - for (int k = 0; k < num_mem; k++){ - // this loop should run from the oldest memory to the newest one. - - if (local_iter < num_mem) c_ind = k; - else c_ind = (k + m_index + 1) % num_mem; - - // dot product between p and da - yr = 0.0; - for (int i = 0; i < 3 * nlocal; i++) { - yr += dy[c_ind][i] * p_s[i]; - } - - MPI_Allreduce(&yr,&yr_global,1,MPI_DOUBLE,MPI_SUM,world); - if (update->multireplica == 1) { - yr_global *= factor; - yr = yr_global; - MPI_Allreduce(&yr,&yr_global,1,MPI_DOUBLE,MPI_SUM,universe->uworld); - } - - beta = rho[c_ind] * yr_global; - for (int i = 0; i < 3 * nlocal; i++) { - p_s[i] += ds[c_ind][i] * (alpha[c_ind] - beta); - } - } - if (use_line_search == 0) - scaling = maximum_rotation(p_s); - for (int i = 0; i < 3 * nlocal; i++) { - p_s[i] = - factor * p_s[i] * scaling; - g_old[i] = g_cur[i] * factor; - } - } - - local_iter++; - free(q); - free(alpha); - -} - -/* ---------------------------------------------------------------------- - rotation of spins along the search direction ----------------------------------------------------------------------- */ - -void MinSpinOSO_LBFGS_LS::advance_spins() -{ - int nlocal = atom->nlocal; - double **sp = atom->sp; - double **fm = atom->fm; - double tdampx, tdampy, tdampz; - double rot_mat[9]; // exponential of matrix made of search direction - double s_new[3]; - - // loop on all spins on proc. - - for (int i = 0; i < nlocal; i++) { - rodrigues_rotation(p_s + 3 * i, rot_mat); - - // rotate spins - - vm3(rot_mat, sp[i], s_new); - for (int j = 0; j < 3; j++) sp[i][j] = s_new[j]; - } -} - -/* ---------------------------------------------------------------------- - compute and return ||mag. torque||_2^2 / N -------------------------------------------------------------------------- */ - -double MinSpinOSO_LBFGS_LS::fmnorm2() { - double norm2, norm2_global; - int nlocal = atom->nlocal; - int ntotal = 0; - - norm2 = 0.0; - for (int i = 0; i < 3 * nlocal; i++) norm2 += g_cur[i] * g_cur[i]; - MPI_Allreduce(&norm2, &norm2_global, 1, MPI_DOUBLE, MPI_SUM, world); - MPI_Allreduce(&nlocal, &ntotal, 1, MPI_INT, MPI_SUM, world); - double ans = norm2_global / (double) ntotal; - MPI_Bcast(&ans, 1, MPI_DOUBLE, 0, world); - return ans; -} - -/* ---------------------------------------------------------------------- - calculate 3x3 matrix exponential using Rodrigues' formula - (R. Murray, Z. Li, and S. Shankar Sastry, - A Mathematical Introduction to - Robotic Manipulation (1994), p. 28 and 30). - - upp_tr - vector x, y, z so that one calculate - U = exp(A) with A= [[0, x, y], - [-x, 0, z], - [-y, -z, 0]] -------------------------------------------------------------------------- */ - -void MinSpinOSO_LBFGS_LS::rodrigues_rotation(const double *upp_tr, double *out) -{ - double theta,A,B,D,x,y,z; - double s1,s2,s3,a1,a2,a3; - - if (fabs(upp_tr[0]) < 1.0e-40 && - fabs(upp_tr[1]) < 1.0e-40 && - fabs(upp_tr[2]) < 1.0e-40){ - - // if upp_tr is zero, return unity matrix - for(int k = 0; k < 3; k++){ - for(int m = 0; m < 3; m++){ - if (m == k) out[3 * k + m] = 1.0; - else out[3 * k + m] = 0.0; - } - } - return; - } - - theta = sqrt(upp_tr[0] * upp_tr[0] + - upp_tr[1] * upp_tr[1] + - upp_tr[2] * upp_tr[2]); - - A = cos(theta); - B = sin(theta); - D = 1 - A; - x = upp_tr[0]/theta; - y = upp_tr[1]/theta; - z = upp_tr[2]/theta; - - // diagonal elements of U - - out[0] = A + z * z * D; - out[4] = A + y * y * D; - out[8] = A + x * x * D; - - // off diagonal of U - - s1 = -y * z *D; - s2 = x * z * D; - s3 = -x * y * D; - - a1 = x * B; - a2 = y * B; - a3 = z * B; - - out[1] = s1 + a1; - out[3] = s1 - a1; - out[2] = s2 + a2; - out[6] = s2 - a2; - out[5] = s3 + a3; - out[7] = s3 - a3; - -} - -/* ---------------------------------------------------------------------- - out = vector^T x m, - m -- 3x3 matrix , v -- 3-d vector -------------------------------------------------------------------------- */ - -void MinSpinOSO_LBFGS_LS::vm3(const double *m, const double *v, double *out) -{ - for(int i = 0; i < 3; i++){ - out[i] *= 0.0; - for(int j = 0; j < 3; j++) - out[i] += *(m + 3 * j + i) * v[j]; - } -} - - -void MinSpinOSO_LBFGS_LS::make_step(double c, double *energy_and_der) -{ - double p_scaled[3]; - int nlocal = atom->nlocal; - double rot_mat[9]; // exponential of matrix made of search direction - double s_new[3]; - double **sp = atom->sp; - double der_e_cur_tmp = 0.0;; - - for (int i = 0; i < nlocal; i++) { - - // scale the search direction - - for (int j = 0; j < 3; j++) p_scaled[j] = c * p_s[3 * i + j]; - - // calculate rotation matrix - - rodrigues_rotation(p_scaled, rot_mat); - - // rotate spins - - vm3(rot_mat, sp[i], s_new); - for (int j = 0; j < 3; j++) sp[i][j] = s_new[j]; - } - - ecurrent = energy_force(0); - calc_gradient(); - neval++; - der_e_cur = 0.0; - for (int i = 0; i < 3 * nlocal; i++) { - der_e_cur += g_cur[i] * p_s[i]; - } - MPI_Allreduce(&der_e_cur,&der_e_cur_tmp, 1, MPI_DOUBLE, MPI_SUM, world); - der_e_cur = der_e_cur_tmp; - if (update->multireplica == 1) { - MPI_Allreduce(&der_e_cur_tmp,&der_e_cur,1,MPI_DOUBLE,MPI_SUM,universe->uworld); - } - - energy_and_der[0] = ecurrent; - energy_and_der[1] = der_e_cur; -} - -/* ---------------------------------------------------------------------- - Calculate step length which satisfies approximate Wolfe conditions - using the cubic interpolation -------------------------------------------------------------------------- */ - -int MinSpinOSO_LBFGS_LS::calc_and_make_step(double a, double b, int index) -{ - double e_and_d[2] = {0.0,0.0}; - double alpha,c1,c2,c3; - double **sp = atom->sp; - int nlocal = atom->nlocal; - - make_step(b,e_and_d); - ecurrent = e_and_d[0]; - der_e_cur = e_and_d[1]; - index++; - - if (awc(der_e_pr,eprevious,e_and_d[1],e_and_d[0]) || index == 5){ - MPI_Bcast(&b,1,MPI_DOUBLE,0,world); - for (int i = 0; i < 3 * nlocal; i++) { - p_s[i] = b * p_s[i]; - } - return 1; - } - else{ - double r,f0,f1,df0,df1; - r = b - a; - f0 = eprevious; - f1 = ecurrent; - df0 = der_e_pr; - df1 = der_e_cur; - - c1 = -2.0*(f1-f0)/(r*r*r)+(df1+df0)/(r*r); - c2 = 3.0*(f1-f0)/(r*r)-(df1+2.0*df0)/(r); - c3 = df0; - - // f(x) = c1 x^3 + c2 x^2 + c3 x^1 + c4 - // has minimum at alpha below. We do not check boundaries. - - alpha = (-c2 + sqrt(c2*c2 - 3.0*c1*c3))/(3.0*c1); - MPI_Bcast(&alpha,1,MPI_DOUBLE,0,world); - - if (alpha < 0.0) alpha = r/2.0; - - for (int i = 0; i < nlocal; i++) { - for (int j = 0; j < 3; j++) sp[i][j] = sp_copy[i][j]; - } - calc_and_make_step(0.0, alpha, index); - } - - return 0; -} - -/* ---------------------------------------------------------------------- - Approximate Wolfe conditions: - William W. Hager and Hongchao Zhang - SIAM J. optim., 16(1), 170-192. (23 pages) -------------------------------------------------------------------------- */ - -int MinSpinOSO_LBFGS_LS::awc(double der_phi_0, double phi_0, double der_phi_j, double phi_j){ - - double eps = 1.0e-6; - double delta = 0.1; - double sigma = 0.9; - - if ((phi_j<=phi_0+eps*fabs(phi_0)) && ((2.0*delta-1.0) * der_phi_0>=der_phi_j>=sigma*der_phi_0)) - return 1; - else - return 0; -} - -double MinSpinOSO_LBFGS_LS::maximum_rotation(double *p) -{ - double norm2,norm2_global,scaling,alpha; - int nlocal = atom->nlocal; - int ntotal = 0; - - norm2 = 0.0; - for (int i = 0; i < 3 * nlocal; i++) norm2 += p[i] * p[i]; - - MPI_Allreduce(&norm2,&norm2_global,1,MPI_DOUBLE,MPI_SUM,world); - if (update->multireplica == 1) { - norm2 = norm2_global; - MPI_Allreduce(&norm2,&norm2_global,1,MPI_DOUBLE,MPI_SUM,universe->uworld); - } - MPI_Allreduce(&nlocal,&ntotal,1,MPI_INT,MPI_SUM,world); - if (update->multireplica == 1) { - nlocal = ntotal; - MPI_Allreduce(&nlocal,&ntotal,1,MPI_INT,MPI_SUM,universe->uworld); - } - - scaling = (maxepsrot * sqrt((double) ntotal / norm2_global)); - - if (scaling < 1.0) alpha = scaling; - else alpha = 1.0; - - return alpha; -} \ No newline at end of file diff --git a/src/SPIN/min_spin_oso_lbfgs_ls.h b/src/SPIN/min_spin_oso_lbfgs_ls.h deleted file mode 100644 index a253808923..0000000000 --- a/src/SPIN/min_spin_oso_lbfgs_ls.h +++ /dev/null @@ -1,79 +0,0 @@ -/* -*- c++ -*- ---------------------------------------------------------- - LAMMPS - Large-scale Atomic/Molecular Massively Parallel Simulator - http://lammps.sandia.gov, Sandia National Laboratories - Steve Plimpton, sjplimp@sandia.gov - - Copyright (2003) Sandia Corporation. Under the terms of Contract - DE-AC04-94AL85000 with Sandia Corporation, the U.S. Government retains - certain rights in this software. This software is distributed under - the GNU General Public License. - - See the README file in the top-level LAMMPS directory. -------------------------------------------------------------------------- */ - -#ifdef MINIMIZE_CLASS - -MinimizeStyle(spin/oso_lbfgs_ls, MinSpinOSO_LBFGS_LS) - -#else - -#ifndef LMP_MIN_SPIN_OSO_LBFGS_LS_H -#define LMP_MIN_SPIN_OSO_LBFGS_LS_H - -#include "min.h" - -namespace LAMMPS_NS { - -class MinSpinOSO_LBFGS_LS : public Min { - -public: - MinSpinOSO_LBFGS_LS(class LAMMPS *); - virtual ~MinSpinOSO_LBFGS_LS(); - void init(); - void setup_style(); - int modify_param(int, char **); - void reset_vectors(); - int iterate(int); - void advance_spins(); - double fmnorm2(); - void calc_gradient(); - void calc_search_direction(); - double maximum_rotation(double *); -private: - int ireplica,nreplica; // for neb - - int nlocal_max; // max value of nlocal (for size of lists) - - double *spvec; // variables for atomic dof, as 1d vector - double *fmvec; // variables for atomic dof, as 1d vector - - double *g_cur; // current gradient vector - double *g_old; // gradient vector at previous step - double *p_s; // search direction vector - double **ds; // change in rotation matrix between two iterations, da - double **dy; // change in gradients between two iterations, dg - double *rho; // estimation of curvature - double **sp_copy; // copy of the spins - - int num_mem; // number of stored steps - int local_iter; // for neb - - double der_e_cur; // current derivative along search dir. - double der_e_pr; // previous derivative along search dir. - - int use_line_search; // use line search or not. - double maxepsrot; - - void vm3(const double *, const double *, double *); - void rodrigues_rotation(const double *, double *); - int calc_and_make_step(double, double, int); - int awc(double, double, double, double); - void make_step(double, double *); - - bigint last_negative; -}; - -} - -#endif -#endif From aa5263f729d6cfb996e7b0033c6737b1a6e5d8c9 Mon Sep 17 00:00:00 2001 From: alxvov Date: Fri, 19 Jul 2019 13:46:26 +0000 Subject: [PATCH 043/192] restructure a bit --- src/SPIN/min_spin_oso_lbfgs.h | 47 +++++++++++++++-------------------- 1 file changed, 20 insertions(+), 27 deletions(-) diff --git a/src/SPIN/min_spin_oso_lbfgs.h b/src/SPIN/min_spin_oso_lbfgs.h index 91c900f244..48d1b47837 100644 --- a/src/SPIN/min_spin_oso_lbfgs.h +++ b/src/SPIN/min_spin_oso_lbfgs.h @@ -25,8 +25,7 @@ MinimizeStyle(spin/oso_lbfgs, MinSpinOSO_LBFGS) namespace LAMMPS_NS { class MinSpinOSO_LBFGS: public Min { - -public: + public: MinSpinOSO_LBFGS(class LAMMPS *); virtual ~MinSpinOSO_LBFGS(); void init(); @@ -34,42 +33,36 @@ public: int modify_param(int, char **); void reset_vectors(); int iterate(int); + private: + int ireplica,nreplica; // for neb + double *spvec; // variables for atomic dof, as 1d vector + double *fmvec; // variables for atomic dof, as 1d vector + double *g_cur; // current gradient vector + double *g_old; // gradient vector at previous step + double *p_s; // search direction vector + double **sp_copy; // copy of the spins + int local_iter; // for neb + int nlocal_max; // max value of nlocal (for size of lists) + void advance_spins(); double fmnorm2(); void calc_gradient(); void calc_search_direction(); double maximum_rotation(double *); -private: - int ireplica,nreplica; // for neb - - int nlocal_max; // max value of nlocal (for size of lists) - - double *spvec; // variables for atomic dof, as 1d vector - double *fmvec; // variables for atomic dof, as 1d vector - - double *g_cur; // current gradient vector - double *g_old; // gradient vector at previous step - double *p_s; // search direction vector - double **ds; // change in rotation matrix between two iterations, da - double **dy; // change in gradients between two iterations, dg - double *rho; // estimation of curvature - double **sp_copy; // copy of the spins - - int num_mem; // number of stored steps - int local_iter; // for neb - - double der_e_cur; // current derivative along search dir. - double der_e_pr; // previous derivative along search dir. - - int use_line_search; // use line search or not. - double maxepsrot; - void vm3(const double *, const double *, double *); void rodrigues_rotation(const double *, double *); int calc_and_make_step(double, double, int); int awc(double, double, double, double); void make_step(double, double *); + double der_e_cur; // current derivative along search dir. + double der_e_pr; // previous derivative along search dir. + int use_line_search; // use line search or not. + double maxepsrot; + double **ds; // change in rotation matrix between two iterations, da + double **dy; // change in gradients between two iterations, dg + double *rho; // estimation of curvature + int num_mem; // number of stored steps bigint last_negative; }; From b31548df2e84ded3b50ebbbd53ae94b2cf912e35 Mon Sep 17 00:00:00 2001 From: alxvov Date: Fri, 19 Jul 2019 16:00:08 +0000 Subject: [PATCH 044/192] convergence criterion based on maximum toque at atom. Minor changes --- src/SPIN/min_spin_oso_lbfgs.cpp | 62 +++++++++++++++++++++------------ src/SPIN/min_spin_oso_lbfgs.h | 2 +- 2 files changed, 40 insertions(+), 24 deletions(-) diff --git a/src/SPIN/min_spin_oso_lbfgs.cpp b/src/SPIN/min_spin_oso_lbfgs.cpp index 7f716da63d..8d05ea63d8 100644 --- a/src/SPIN/min_spin_oso_lbfgs.cpp +++ b/src/SPIN/min_spin_oso_lbfgs.cpp @@ -212,25 +212,25 @@ int MinSpinOSO_LBFGS::iterate(int maxiter) // optimize timestep accross processes / replicas // need a force calculation for timestep optimization - if (local_iter == 0) - ecurrent = energy_force(0); - if (use_line_search) { // here we need to do line search + if (local_iter == 0) + calc_gradient(); + calc_search_direction(); der_e_cur = 0.0; - for (int i = 0; i < 3 * nlocal; i++) { + for (int i = 0; i < 3 * nlocal; i++) der_e_cur += g_cur[i] * p_s[i]; - } MPI_Allreduce(&der_e_cur,&der_e_cur_tmp,1,MPI_DOUBLE,MPI_SUM,world); der_e_cur = der_e_cur_tmp; if (update->multireplica == 1) { MPI_Allreduce(&der_e_cur_tmp,&der_e_cur,1,MPI_DOUBLE,MPI_SUM,universe->uworld); } - for (int i = 0; i < nlocal; i++) { - for (int j = 0; j < 3; j++) sp_copy[i][j] = sp[i][j]; - } + for (int i = 0; i < nlocal; i++) + for (int j = 0; j < 3; j++) + sp_copy[i][j] = sp[i][j]; + eprevious = ecurrent; der_e_pr = der_e_cur; calc_and_make_step(0.0, 1.0, 0); @@ -253,7 +253,6 @@ int MinSpinOSO_LBFGS::iterate(int maxiter) calc_search_direction(); advance_spins(); } - neval++; eprevious = ecurrent; ecurrent = energy_force(0); neval++; @@ -282,7 +281,7 @@ int MinSpinOSO_LBFGS::iterate(int maxiter) // sync across replicas if running multi-replica minimization if (update->ftol > 0.0) { - fmdotfm = fmnorm2(); + fmdotfm = max_torque(); if (update->multireplica == 0) { if (fmdotfm < update->ftol*update->ftol) return FTOL; } else { @@ -314,8 +313,7 @@ void MinSpinOSO_LBFGS::calc_gradient() int nlocal = atom->nlocal; double **sp = atom->sp; double **fm = atom->fm; - double tdampx, tdampy, tdampz; - + // loop on all spins on proc. for (int i = 0; i < nlocal; i++) { @@ -542,21 +540,39 @@ void MinSpinOSO_LBFGS::advance_spins() } /* ---------------------------------------------------------------------- - compute and return ||mag. torque||_2^2 / N + compute and return max_i||mag. torque_i||_2 ------------------------------------------------------------------------- */ -double MinSpinOSO_LBFGS::fmnorm2() { - double norm2, norm2_global; +double MinSpinOSO_LBFGS::max_torque() +{ + double fmsq,fmaxsqone,fmaxsqloc,fmaxsqall; int nlocal = atom->nlocal; - int ntotal = 0; - norm2 = 0.0; - for (int i = 0; i < 3 * nlocal; i++) norm2 += g_cur[i] * g_cur[i]; - MPI_Allreduce(&norm2, &norm2_global, 1, MPI_DOUBLE, MPI_SUM, world); - MPI_Allreduce(&nlocal, &ntotal, 1, MPI_INT, MPI_SUM, world); - double ans = norm2_global / (double) ntotal; - MPI_Bcast(&ans, 1, MPI_DOUBLE, 0, world); - return ans; + // finding max fm on this proc. + + fmsq = fmaxsqone = fmaxsqloc = fmaxsqall = 0.0; + for (int i = 0; i < nlocal; i++) { + fmsq = 0.0; + for (int j = 0; j < 3; j++) + fmsq += g_cur[3 * i + j] * g_cur[3 * i + j]; + fmaxsqone = MAX(fmaxsqone,fmsq); + } + + // finding max fm on this replica + + fmaxsqloc = fmaxsqone; + MPI_Allreduce(&fmaxsqone,&fmaxsqloc,1,MPI_DOUBLE,MPI_MAX,world); + + // finding max fm over all replicas, if necessary + // this communicator would be invalid for multiprocess replicas + + fmaxsqall = fmaxsqloc; + if (update->multireplica == 1) { + fmaxsqall = fmaxsqloc; + MPI_Allreduce(&fmaxsqloc,&fmaxsqall,1,MPI_DOUBLE,MPI_MAX,universe->uworld); + } + + return sqrt(fmaxsqall); } /* ---------------------------------------------------------------------- diff --git a/src/SPIN/min_spin_oso_lbfgs.h b/src/SPIN/min_spin_oso_lbfgs.h index 48d1b47837..d74898aa8c 100644 --- a/src/SPIN/min_spin_oso_lbfgs.h +++ b/src/SPIN/min_spin_oso_lbfgs.h @@ -45,7 +45,6 @@ class MinSpinOSO_LBFGS: public Min { int nlocal_max; // max value of nlocal (for size of lists) void advance_spins(); - double fmnorm2(); void calc_gradient(); void calc_search_direction(); double maximum_rotation(double *); @@ -54,6 +53,7 @@ class MinSpinOSO_LBFGS: public Min { int calc_and_make_step(double, double, int); int awc(double, double, double, double); void make_step(double, double *); + double max_torque(); double der_e_cur; // current derivative along search dir. double der_e_pr; // previous derivative along search dir. int use_line_search; // use line search or not. From 3b7bb668aecc3f32d32c1eb4061a112e07536e5b Mon Sep 17 00:00:00 2001 From: alxvov Date: Fri, 19 Jul 2019 16:41:51 +0000 Subject: [PATCH 045/192] conjugate gradients with line search --- src/SPIN/min_spin_oso_cg2.cpp | 665 ++++++++++++++++++++++++++++++++++ src/SPIN/min_spin_oso_cg2.h | 68 ++++ 2 files changed, 733 insertions(+) create mode 100644 src/SPIN/min_spin_oso_cg2.cpp create mode 100644 src/SPIN/min_spin_oso_cg2.h diff --git a/src/SPIN/min_spin_oso_cg2.cpp b/src/SPIN/min_spin_oso_cg2.cpp new file mode 100644 index 0000000000..23873e24f2 --- /dev/null +++ b/src/SPIN/min_spin_oso_cg2.cpp @@ -0,0 +1,665 @@ +/* ---------------------------------------------------------------------- + LAMMPS - Large-scale Atomic/Molecular Massively Parallel Simulator + http://lammps.sandia.gov, Sandia National Laboratories + Steve Plimpton, sjplimp@sandia.gov + + Copyright (2003) Sandia Corporation. Under the terms of Contract + DE-AC04-94AL85000 with Sandia Corporation, the U.S. Government retains + certain rights in this software. This software is distributed under + the GNU General Public License. + + See the README file in the top-level LAMMPS directory. +------------------------------------------------------------------------- */ + +/* ------------------------------------------------------------------------ + Contributing authors: Aleksei Ivanov (University of Iceland) + Julien Tranchida (SNL) + + Please cite the related publication: + Ivanov, A. V., Uzdin, V. M., & Jónsson, H. (2019). Fast and Robust + Algorithm for the Minimisation of the Energy of Spin Systems. arXiv + preprint arXiv:1904.02669. +------------------------------------------------------------------------- */ + +#include +#include +#include +#include +#include "min_spin_oso_cg2.h" +#include "universe.h" +#include "atom.h" +#include "citeme.h" +#include "force.h" +#include "update.h" +#include "output.h" +#include "timer.h" +#include "error.h" +#include "memory.h" +#include "modify.h" +#include "math_special.h" +#include "math_const.h" +#include "universe.h" +#include + +using namespace LAMMPS_NS; +using namespace MathConst; + +static const char cite_minstyle_spin_oso_cg2[] = + "min_style spin/oso_cg2 command:\n\n" + "@article{ivanov2019fast,\n" + "title={Fast and Robust Algorithm for the Minimisation of the Energy of " + "Spin Systems},\n" + "author={Ivanov, A. V and Uzdin, V. M. and J{\'o}nsson, H.},\n" + "journal={arXiv preprint arXiv:1904.02669},\n" + "year={2019}\n" + "}\n\n"; + +// EPS_ENERGY = minimum normalization for energy tolerance + +#define EPS_ENERGY 1.0e-8 + +#define DELAYSTEP 5 + + +/* ---------------------------------------------------------------------- */ + +MinSpinOSO_CG2::MinSpinOSO_CG2(LAMMPS *lmp) : + Min(lmp), g_old(NULL), g_cur(NULL), p_s(NULL) +{ + if (lmp->citeme) lmp->citeme->add(cite_minstyle_spin_oso_cg2); + nlocal_max = 0; + + // nreplica = number of partitions + // ireplica = which world I am in universe + + nreplica = universe->nworlds; + ireplica = universe->iworld; + use_line_search = 1; + maxepsrot = MY_2PI / (100.0); + +} + +/* ---------------------------------------------------------------------- */ + +MinSpinOSO_CG2::~MinSpinOSO_CG2() +{ + memory->destroy(g_old); + memory->destroy(g_cur); + memory->destroy(p_s); + if (use_line_search) + memory->destroy(sp_copy); +} + +/* ---------------------------------------------------------------------- */ + +void MinSpinOSO_CG2::init() +{ + local_iter = 0; + der_e_cur = 0.0; + der_e_pr = 0.0; + + Min::init(); + + last_negative = update->ntimestep; + + // allocate tables + + nlocal_max = atom->nlocal; + memory->grow(g_old,3*nlocal_max,"min/spin/oso/cg2:g_old"); + memory->grow(g_cur,3*nlocal_max,"min/spin/oso/cg2:g_cur"); + memory->grow(p_s,3*nlocal_max,"min/spin/oso/cg2:p_s"); + if (use_line_search) + memory->grow(sp_copy,nlocal_max,3,"min/spin/oso/cg2:sp_copy"); +} + +/* ---------------------------------------------------------------------- */ + +void MinSpinOSO_CG2::setup_style() +{ + double **v = atom->v; + int nlocal = atom->nlocal; + + // check if the atom/spin style is defined + + if (!atom->sp_flag) + error->all(FLERR,"min/spin_oso_cg2 requires atom/spin style"); + + for (int i = 0; i < nlocal; i++) + v[i][0] = v[i][1] = v[i][2] = 0.0; +} + +/* ---------------------------------------------------------------------- */ + +int MinSpinOSO_CG2::modify_param(int narg, char **arg) +{ + + if (strcmp(arg[0],"line_search") == 0) { + if (narg < 2) error->all(FLERR,"Illegal fix_modify command"); + use_line_search = force->numeric(FLERR,arg[1]); + return 2; + } + if (strcmp(arg[0],"discrete_factor") == 0) { + if (narg < 2) error->all(FLERR,"Illegal fix_modify command"); + double discrete_factor; + discrete_factor = force->numeric(FLERR,arg[1]); + maxepsrot = MY_2PI / discrete_factor; + return 2; + } + return 0; +} + +/* ---------------------------------------------------------------------- + set current vector lengths and pointers + called after atoms have migrated +------------------------------------------------------------------------- */ + +void MinSpinOSO_CG2::reset_vectors() +{ + // atomic dof + + // size sp is 4N vector + nvec = 4 * atom->nlocal; + if (nvec) spvec = atom->sp[0]; + + nvec = 3 * atom->nlocal; + if (nvec) fmvec = atom->fm[0]; + + if (nvec) xvec = atom->x[0]; + if (nvec) fvec = atom->f[0]; +} + +/* ---------------------------------------------------------------------- + minimization via damped spin dynamics +------------------------------------------------------------------------- */ + +int MinSpinOSO_CG2::iterate(int maxiter) +{ + int nlocal = atom->nlocal; + bigint ntimestep; + double fmdotfm; + int flag, flagall; + double **sp = atom->sp; + double der_e_cur_tmp = 0.0; + + if (nlocal_max < nlocal) { + nlocal_max = nlocal; + local_iter = 0; + nlocal_max = nlocal; + memory->grow(g_old,3*nlocal_max,"min/spin/oso/cg2:g_old"); + memory->grow(g_cur,3*nlocal_max,"min/spin/oso/cg2:g_cur"); + memory->grow(p_s,3*nlocal_max,"min/spin/oso/cg2:p_s"); + if (use_line_search) + memory->grow(sp_copy,nlocal_max,3,"min/spin/oso/cg2:sp_copy"); + } + + for (int iter = 0; iter < maxiter; iter++) { + + if (timer->check_timeout(niter)) + return TIMEOUT; + + ntimestep = ++update->ntimestep; + niter++; + + // optimize timestep accross processes / replicas + // need a force calculation for timestep optimization + + if (use_line_search) { + + // here we need to do line search + if (local_iter == 0) + calc_gradient(); + + calc_search_direction(); + der_e_cur = 0.0; + for (int i = 0; i < 3 * nlocal; i++) + der_e_cur += g_cur[i] * p_s[i]; + MPI_Allreduce(&der_e_cur,&der_e_cur_tmp,1,MPI_DOUBLE,MPI_SUM,world); + der_e_cur = der_e_cur_tmp; + if (update->multireplica == 1) { + MPI_Allreduce(&der_e_cur_tmp,&der_e_cur,1,MPI_DOUBLE,MPI_SUM,universe->uworld); + } + for (int i = 0; i < nlocal; i++) + for (int j = 0; j < 3; j++) + sp_copy[i][j] = sp[i][j]; + + eprevious = ecurrent; + der_e_pr = der_e_cur; + calc_and_make_step(0.0, 1.0, 0); + } + else{ + + // here we don't do line search + // but use cutoff rotation angle + // if gneb calc., nreplica > 1 + // then calculate gradients and advance spins + // of intermediate replicas only + + if (nreplica > 1) { + if(ireplica != 0 && ireplica != nreplica-1) + calc_gradient(); + calc_search_direction(); + advance_spins(); + } else{ + calc_gradient(); + calc_search_direction(); + advance_spins(); + } + eprevious = ecurrent; + ecurrent = energy_force(0); + neval++; + } + + //// energy tolerance criterion + //// only check after DELAYSTEP elapsed since velocties reset to 0 + //// sync across replicas if running multi-replica minimization + + if (update->etol > 0.0 && ntimestep-last_negative > DELAYSTEP) { + if (update->multireplica == 0) { + if (fabs(ecurrent-eprevious) < + update->etol * 0.5*(fabs(ecurrent) + fabs(eprevious) + EPS_ENERGY)) + return ETOL; + } else { + if (fabs(ecurrent-eprevious) < + update->etol * 0.5*(fabs(ecurrent) + fabs(eprevious) + EPS_ENERGY)) + flag = 0; + else flag = 1; + MPI_Allreduce(&flag,&flagall,1,MPI_INT,MPI_SUM,universe->uworld); + if (flagall == 0) return ETOL; + } + } + + // magnetic torque tolerance criterion + // sync across replicas if running multi-replica minimization + + if (update->ftol > 0.0) { + fmdotfm = max_torque(); + if (update->multireplica == 0) { + if (fmdotfm < update->ftol*update->ftol) return FTOL; + } else { + if (fmdotfm < update->ftol*update->ftol) flag = 0; + else flag = 1; + MPI_Allreduce(&flag,&flagall,1,MPI_INT,MPI_SUM,universe->uworld); + if (flagall == 0) return FTOL; + } + } + + // output for thermo, dump, restart files + + if (output->next == ntimestep) { + timer->stamp(); + output->write(ntimestep); + timer->stamp(Timer::OUTPUT); + } + } + + return MAXITER; +} + +/* ---------------------------------------------------------------------- + calculate gradients +---------------------------------------------------------------------- */ + +void MinSpinOSO_CG2::calc_gradient() +{ + int nlocal = atom->nlocal; + double **sp = atom->sp; + double **fm = atom->fm; + double hbar = force->hplanck/MY_2PI; + + // loop on all spins on proc. + + for (int i = 0; i < nlocal; i++) { + + // calculate gradients + + g_cur[3 * i + 0] = (fm[i][0]*sp[i][1] - fm[i][1]*sp[i][0]) * hbar; + g_cur[3 * i + 1] = -(fm[i][2]*sp[i][0] - fm[i][0]*sp[i][2]) * hbar; + g_cur[3 * i + 2] = (fm[i][1]*sp[i][2] - fm[i][2]*sp[i][1]) * hbar; + } +} + + +/* ---------------------------------------------------------------------- + search direction: + The Fletcher-Reeves conj. grad. method + See Jorge Nocedal and Stephen J. Wright 'Numerical + Optimization' Second Edition, 2006 (p. 121) +---------------------------------------------------------------------- */ + +void MinSpinOSO_CG2::calc_search_direction() +{ + int nlocal = atom->nlocal; + double g2old = 0.0; + double g2 = 0.0; + double beta = 0.0; + + double g2_global = 0.0; + double g2old_global = 0.0; + double scaling = 1.0; + + if (use_line_search == 0) + scaling = maximum_rotation(g_cur); + + if (local_iter == 0 || local_iter % 5 == 0){ // steepest descent direction + for (int i = 0; i < 3 * nlocal; i++) { + p_s[i] = -g_cur[i] * scaling; + g_old[i] = g_cur[i]; + } + } else { // conjugate direction + for (int i = 0; i < 3 * nlocal; i++) { + g2old += g_old[i] * g_old[i]; + g2 += g_cur[i] * g_cur[i]; + } + + // now we need to collect/broadcast beta on this replica + // different replica can have different beta for now. + // need to check what is beta for GNEB + + MPI_Allreduce(&g2, &g2_global, 1, MPI_DOUBLE, MPI_SUM, world); + MPI_Allreduce(&g2old, &g2old_global, 1, MPI_DOUBLE, MPI_SUM, world); + + // Sum over all replicas. Good for GNEB. + if (update->multireplica == 1) { + g2 = g2_global; + g2old = g2old_global; + MPI_Allreduce(&g2,&g2_global,1,MPI_DOUBLE,MPI_SUM,universe->uworld); + MPI_Allreduce(&g2old,&g2old_global,1,MPI_DOUBLE,MPI_SUM,universe->uworld); + } + + if (fabs(g2_global) < 1.0e-60) beta = 0.0; + else beta = g2_global / g2old_global; + // calculate conjugate direction + for (int i = 0; i < 3 * nlocal; i++) { + p_s[i] = (beta * p_s[i] - g_cur[i])*scaling; + g_old[i] = g_cur[i]; + } + } + + local_iter++; +} + +/* ---------------------------------------------------------------------- + rotation of spins along the search direction +---------------------------------------------------------------------- */ + +void MinSpinOSO_CG2::advance_spins() +{ + int nlocal = atom->nlocal; + double **sp = atom->sp; + double **fm = atom->fm; + double tdampx, tdampy, tdampz; + double rot_mat[9]; // exponential of matrix made of search direction + double s_new[3]; + + // loop on all spins on proc. + + for (int i = 0; i < nlocal; i++) { + rodrigues_rotation(p_s + 3 * i, rot_mat); + + // rotate spins + + vm3(rot_mat, sp[i], s_new); + for (int j = 0; j < 3; j++) sp[i][j] = s_new[j]; + } +} + +/* ---------------------------------------------------------------------- + compute and return max_i||mag. torque_i||_2 +------------------------------------------------------------------------- */ + +double MinSpinOSO_CG2::max_torque() +{ + double fmsq,fmaxsqone,fmaxsqloc,fmaxsqall; + int nlocal = atom->nlocal; + + // finding max fm on this proc. + + fmsq = fmaxsqone = fmaxsqloc = fmaxsqall = 0.0; + for (int i = 0; i < nlocal; i++) { + fmsq = 0.0; + for (int j = 0; j < 3; j++) + fmsq += g_cur[3 * i + j] * g_cur[3 * i + j]; + fmaxsqone = MAX(fmaxsqone,fmsq); + } + + // finding max fm on this replica + + fmaxsqloc = fmaxsqone; + MPI_Allreduce(&fmaxsqone,&fmaxsqloc,1,MPI_DOUBLE,MPI_MAX,world); + + // finding max fm over all replicas, if necessary + // this communicator would be invalid for multiprocess replicas + + fmaxsqall = fmaxsqloc; + if (update->multireplica == 1) { + fmaxsqall = fmaxsqloc; + MPI_Allreduce(&fmaxsqloc,&fmaxsqall,1,MPI_DOUBLE,MPI_MAX,universe->uworld); + } + + return sqrt(fmaxsqall); +} + +/* ---------------------------------------------------------------------- + calculate 3x3 matrix exponential using Rodrigues' formula + (R. Murray, Z. Li, and S. Shankar Sastry, + A Mathematical Introduction to + Robotic Manipulation (1994), p. 28 and 30). + + upp_tr - vector x, y, z so that one calculate + U = exp(A) with A= [[0, x, y], + [-x, 0, z], + [-y, -z, 0]] +------------------------------------------------------------------------- */ + +void MinSpinOSO_CG2::rodrigues_rotation(const double *upp_tr, double *out) +{ + double theta,A,B,D,x,y,z; + double s1,s2,s3,a1,a2,a3; + + if (fabs(upp_tr[0]) < 1.0e-40 && + fabs(upp_tr[1]) < 1.0e-40 && + fabs(upp_tr[2]) < 1.0e-40){ + + // if upp_tr is zero, return unity matrix + for(int k = 0; k < 3; k++){ + for(int m = 0; m < 3; m++){ + if (m == k) out[3 * k + m] = 1.0; + else out[3 * k + m] = 0.0; + } + } + return; + } + + theta = sqrt(upp_tr[0] * upp_tr[0] + + upp_tr[1] * upp_tr[1] + + upp_tr[2] * upp_tr[2]); + + A = cos(theta); + B = sin(theta); + D = 1 - A; + x = upp_tr[0]/theta; + y = upp_tr[1]/theta; + z = upp_tr[2]/theta; + + // diagonal elements of U + + out[0] = A + z * z * D; + out[4] = A + y * y * D; + out[8] = A + x * x * D; + + // off diagonal of U + + s1 = -y * z *D; + s2 = x * z * D; + s3 = -x * y * D; + + a1 = x * B; + a2 = y * B; + a3 = z * B; + + out[1] = s1 + a1; + out[3] = s1 - a1; + out[2] = s2 + a2; + out[6] = s2 - a2; + out[5] = s3 + a3; + out[7] = s3 - a3; + +} + +/* ---------------------------------------------------------------------- + out = vector^T x m, + m -- 3x3 matrix , v -- 3-d vector +------------------------------------------------------------------------- */ + +void MinSpinOSO_CG2::vm3(const double *m, const double *v, double *out) +{ + for(int i = 0; i < 3; i++){ + out[i] *= 0.0; + for(int j = 0; j < 3; j++) + out[i] += *(m + 3 * j + i) * v[j]; + } +} + + +void MinSpinOSO_CG2::make_step(double c, double *energy_and_der) +{ + double p_scaled[3]; + int nlocal = atom->nlocal; + double rot_mat[9]; // exponential of matrix made of search direction + double s_new[3]; + double **sp = atom->sp; + double der_e_cur_tmp = 0.0;; + + for (int i = 0; i < nlocal; i++) { + + // scale the search direction + + for (int j = 0; j < 3; j++) p_scaled[j] = c * p_s[3 * i + j]; + + // calculate rotation matrix + + rodrigues_rotation(p_scaled, rot_mat); + + // rotate spins + + vm3(rot_mat, sp[i], s_new); + for (int j = 0; j < 3; j++) sp[i][j] = s_new[j]; + } + + ecurrent = energy_force(0); + calc_gradient(); + neval++; + der_e_cur = 0.0; + for (int i = 0; i < 3 * nlocal; i++) { + der_e_cur += g_cur[i] * p_s[i]; + } + MPI_Allreduce(&der_e_cur,&der_e_cur_tmp,1,MPI_DOUBLE,MPI_SUM,world); + der_e_cur = der_e_cur_tmp; + if (update->multireplica == 1) { + MPI_Allreduce(&der_e_cur_tmp,&der_e_cur,1,MPI_DOUBLE,MPI_SUM,universe->uworld); + } + + energy_and_der[0] = ecurrent; + energy_and_der[1] = der_e_cur; +} + +/* ---------------------------------------------------------------------- + Calculate step length which satisfies approximate Wolfe conditions + using the cubic interpolation +------------------------------------------------------------------------- */ + +int MinSpinOSO_CG2::calc_and_make_step(double a, double b, int index) +{ + double e_and_d[2] = {0.0,0.0}; + double alpha,c1,c2,c3; + double **sp = atom->sp; + int nlocal = atom->nlocal; + + make_step(b,e_and_d); + ecurrent = e_and_d[0]; + der_e_cur = e_and_d[1]; + index++; + + if (awc(der_e_pr,eprevious,e_and_d[1],e_and_d[0]) || index == 10){ + MPI_Bcast(&b,1,MPI_DOUBLE,0,world); + for (int i = 0; i < 3 * nlocal; i++) { + p_s[i] = b * p_s[i]; + } + return 1; + } + else{ + double r,f0,f1,df0,df1; + r = b - a; + f0 = eprevious; + f1 = ecurrent; + df0 = der_e_pr; + df1 = der_e_cur; + + c1 = -2.0*(f1-f0)/(r*r*r)+(df1+df0)/(r*r); + c2 = 3.0*(f1-f0)/(r*r)-(df1+2.0*df0)/(r); + c3 = df0; + + // f(x) = c1 x^3 + c2 x^2 + c3 x^1 + c4 + // has minimum at alpha below. We do not check boundaries. + + alpha = (-c2 + sqrt(c2*c2 - 3.0*c1*c3))/(3.0*c1); + MPI_Bcast(&alpha,1,MPI_DOUBLE,0,world); + + if (alpha < 0.0) alpha = r/2.0; + + std::cout << alpha << "\n"; + + for (int i = 0; i < nlocal; i++) { + for (int j = 0; j < 3; j++) sp[i][j] = sp_copy[i][j]; + } + calc_and_make_step(0.0, alpha, index); + } + + return 0; +} + +/* ---------------------------------------------------------------------- + Approximate Wolfe conditions: + William W. Hager and Hongchao Zhang + SIAM J. optim., 16(1), 170-192. (23 pages) +------------------------------------------------------------------------- */ + +int MinSpinOSO_CG2::awc(double der_phi_0, double phi_0, double der_phi_j, double phi_j){ + + double eps = 1.0e-6; + double delta = 0.1; + double sigma = 0.9; + + if ((phi_j<=phi_0+eps*fabs(phi_0)) && ((2.0*delta-1.0) * der_phi_0>=der_phi_j>=sigma*der_phi_0)) + return 1; + else + return 0; +} + +double MinSpinOSO_CG2::maximum_rotation(double *p) +{ + double norm2,norm2_global,scaling,alpha; + int nlocal = atom->nlocal; + int ntotal = 0; + + norm2 = 0.0; + for (int i = 0; i < 3 * nlocal; i++) norm2 += p[i] * p[i]; + + MPI_Allreduce(&norm2,&norm2_global,1,MPI_DOUBLE,MPI_SUM,world); + if (update->multireplica == 1) { + norm2 = norm2_global; + MPI_Allreduce(&norm2,&norm2_global,1,MPI_DOUBLE,MPI_SUM,universe->uworld); + } + MPI_Allreduce(&nlocal,&ntotal,1,MPI_INT,MPI_SUM,world); + if (update->multireplica == 1) { + nlocal = ntotal; + MPI_Allreduce(&nlocal,&ntotal,1,MPI_INT,MPI_SUM,universe->uworld); + } + + scaling = (maxepsrot * sqrt((double) ntotal / norm2_global)); + + if (scaling < 1.0) alpha = scaling; + else alpha = 1.0; + + return alpha; +} \ No newline at end of file diff --git a/src/SPIN/min_spin_oso_cg2.h b/src/SPIN/min_spin_oso_cg2.h new file mode 100644 index 0000000000..c96e82ca8e --- /dev/null +++ b/src/SPIN/min_spin_oso_cg2.h @@ -0,0 +1,68 @@ +/* -*- c++ -*- ---------------------------------------------------------- + LAMMPS - Large-scale Atomic/Molecular Massively Parallel Simulator + http://lammps.sandia.gov, Sandia National Laboratories + Steve Plimpton, sjplimp@sandia.gov + + Copyright (2003) Sandia Corporation. Under the terms of Contract + DE-AC04-94AL85000 with Sandia Corporation, the U.S. Government retains + certain rights in this software. This software is distributed under + the GNU General Public License. + + See the README file in the top-level LAMMPS directory. +------------------------------------------------------------------------- */ + +#ifdef MINIMIZE_CLASS + +MinimizeStyle(spin/oso_cg2, MinSpinOSO_CG2) + +#else + +#ifndef LMP_MIN_SPIN_OSO_CG2_H +#define LMP_MIN_SPIN_OSO_CG2_H + +#include "min.h" + +namespace LAMMPS_NS { + +class MinSpinOSO_CG2: public Min { + public: + MinSpinOSO_CG2(class LAMMPS *); + virtual ~MinSpinOSO_CG2(); + void init(); + void setup_style(); + int modify_param(int, char **); + void reset_vectors(); + int iterate(int); + private: + int ireplica,nreplica; // for neb + double *spvec; // variables for atomic dof, as 1d vector + double *fmvec; // variables for atomic dof, as 1d vector + double *g_cur; // current gradient vector + double *g_old; // gradient vector at previous step + double *p_s; // search direction vector + double **sp_copy; // copy of the spins + int local_iter; // for neb + int nlocal_max; // max value of nlocal (for size of lists) + + void advance_spins(); + void calc_gradient(); + void calc_search_direction(); + double maximum_rotation(double *); + void vm3(const double *, const double *, double *); + void rodrigues_rotation(const double *, double *); + int calc_and_make_step(double, double, int); + int awc(double, double, double, double); + void make_step(double, double *); + double max_torque(); + double der_e_cur; // current derivative along search dir. + double der_e_pr; // previous derivative along search dir. + int use_line_search; // use line search or not. + double maxepsrot; + + bigint last_negative; +}; + +} + +#endif +#endif From a96e6f220a9dcf26221121a969ee690f06ae2212 Mon Sep 17 00:00:00 2001 From: casievers Date: Fri, 19 Jul 2019 13:36:57 -0700 Subject: [PATCH 046/192] updated fix_langevin and made example --- examples/gjf/argon.lmp | 886 ++++++++++++++++++++++++++++++++++ examples/gjf/ff-argon.lmp | 20 + examples/gjf/in.argon | 162 +++++++ examples/gjf/out.argon | 249 ++++++++++ examples/gjf/trajectory.0.dcd | Bin 0 -> 439092 bytes src/fix_langevin.cpp | 272 +++++++++-- src/fix_langevin.h | 7 +- 7 files changed, 1550 insertions(+), 46 deletions(-) create mode 100644 examples/gjf/argon.lmp create mode 100644 examples/gjf/ff-argon.lmp create mode 100644 examples/gjf/in.argon create mode 100644 examples/gjf/out.argon create mode 100644 examples/gjf/trajectory.0.dcd diff --git a/examples/gjf/argon.lmp b/examples/gjf/argon.lmp new file mode 100644 index 0000000000..00214b4c54 --- /dev/null +++ b/examples/gjf/argon.lmp @@ -0,0 +1,886 @@ +LAMMPS description + + 864 atoms + 0 bonds + 0 angles + 0 dihedrals + 0 impropers + + 1 atom types + 0 bond types + 0 angle types + 0 dihedral types + 0 improper types + + + 0.0000000 32.146000 xlo xhi + 0.0000000 32.146000 ylo yhi + 0.0000000 32.146000 zlo zhi + + Atoms + + 1 1 1 0.0000000 0.0000000 2.6790000 2.6790000 + 2 2 1 0.0000000 0.0000000 2.6790000 8.0360000 + 3 3 1 0.0000000 0.0000000 2.6790000 13.3940000 + 4 4 1 0.0000000 0.0000000 2.6790000 18.7520000 + 5 5 1 0.0000000 0.0000000 2.6790000 24.1090000 + 6 6 1 0.0000000 0.0000000 2.6790000 29.4670000 + 7 7 1 0.0000000 0.0000000 8.0360000 2.6790000 + 8 8 1 0.0000000 0.0000000 8.0360000 8.0360000 + 9 9 1 0.0000000 0.0000000 8.0360000 13.3940000 + 10 10 1 0.0000000 0.0000000 8.0360000 18.7520000 + 11 11 1 0.0000000 0.0000000 8.0360000 24.1090000 + 12 12 1 0.0000000 0.0000000 8.0360000 29.4670000 + 13 13 1 0.0000000 0.0000000 13.3940000 2.6790000 + 14 14 1 0.0000000 0.0000000 13.3940000 8.0360000 + 15 15 1 0.0000000 0.0000000 13.3940000 13.3940000 + 16 16 1 0.0000000 0.0000000 13.3940000 18.7520000 + 17 17 1 0.0000000 0.0000000 13.3940000 24.1090000 + 18 18 1 0.0000000 0.0000000 13.3940000 29.4670000 + 19 19 1 0.0000000 0.0000000 18.7520000 2.6790000 + 20 20 1 0.0000000 0.0000000 18.7520000 8.0360000 + 21 21 1 0.0000000 0.0000000 18.7520000 13.3940000 + 22 22 1 0.0000000 0.0000000 18.7520000 18.7520000 + 23 23 1 0.0000000 0.0000000 18.7520000 24.1090000 + 24 24 1 0.0000000 0.0000000 18.7520000 29.4670000 + 25 25 1 0.0000000 0.0000000 24.1090000 2.6790000 + 26 26 1 0.0000000 0.0000000 24.1090000 8.0360000 + 27 27 1 0.0000000 0.0000000 24.1090000 13.3940000 + 28 28 1 0.0000000 0.0000000 24.1090000 18.7520000 + 29 29 1 0.0000000 0.0000000 24.1090000 24.1090000 + 30 30 1 0.0000000 0.0000000 24.1090000 29.4670000 + 31 31 1 0.0000000 0.0000000 29.4670000 2.6790000 + 32 32 1 0.0000000 0.0000000 29.4670000 8.0360000 + 33 33 1 0.0000000 0.0000000 29.4670000 13.3940000 + 34 34 1 0.0000000 0.0000000 29.4670000 18.7520000 + 35 35 1 0.0000000 0.0000000 29.4670000 24.1090000 + 36 36 1 0.0000000 0.0000000 29.4670000 29.4670000 + 37 37 1 0.0000000 5.3580000 2.6790000 2.6790000 + 38 38 1 0.0000000 5.3580000 2.6790000 8.0360000 + 39 39 1 0.0000000 5.3580000 2.6790000 13.3940000 + 40 40 1 0.0000000 5.3580000 2.6790000 18.7520000 + 41 41 1 0.0000000 5.3580000 2.6790000 24.1090000 + 42 42 1 0.0000000 5.3580000 2.6790000 29.4670000 + 43 43 1 0.0000000 5.3580000 8.0360000 2.6790000 + 44 44 1 0.0000000 5.3580000 8.0360000 8.0360000 + 45 45 1 0.0000000 5.3580000 8.0360000 13.3940000 + 46 46 1 0.0000000 5.3580000 8.0360000 18.7520000 + 47 47 1 0.0000000 5.3580000 8.0360000 24.1090000 + 48 48 1 0.0000000 5.3580000 8.0360000 29.4670000 + 49 49 1 0.0000000 5.3580000 13.3940000 2.6790000 + 50 50 1 0.0000000 5.3580000 13.3940000 8.0360000 + 51 51 1 0.0000000 5.3580000 13.3940000 13.3940000 + 52 52 1 0.0000000 5.3580000 13.3940000 18.7520000 + 53 53 1 0.0000000 5.3580000 13.3940000 24.1090000 + 54 54 1 0.0000000 5.3580000 13.3940000 29.4670000 + 55 55 1 0.0000000 5.3580000 18.7520000 2.6790000 + 56 56 1 0.0000000 5.3580000 18.7520000 8.0360000 + 57 57 1 0.0000000 5.3580000 18.7520000 13.3940000 + 58 58 1 0.0000000 5.3580000 18.7520000 18.7520000 + 59 59 1 0.0000000 5.3580000 18.7520000 24.1090000 + 60 60 1 0.0000000 5.3580000 18.7520000 29.4670000 + 61 61 1 0.0000000 5.3580000 24.1090000 2.6790000 + 62 62 1 0.0000000 5.3580000 24.1090000 8.0360000 + 63 63 1 0.0000000 5.3580000 24.1090000 13.3940000 + 64 64 1 0.0000000 5.3580000 24.1090000 18.7520000 + 65 65 1 0.0000000 5.3580000 24.1090000 24.1090000 + 66 66 1 0.0000000 5.3580000 24.1090000 29.4670000 + 67 67 1 0.0000000 5.3580000 29.4670000 2.6790000 + 68 68 1 0.0000000 5.3580000 29.4670000 8.0360000 + 69 69 1 0.0000000 5.3580000 29.4670000 13.3940000 + 70 70 1 0.0000000 5.3580000 29.4670000 18.7520000 + 71 71 1 0.0000000 5.3580000 29.4670000 24.1090000 + 72 72 1 0.0000000 5.3580000 29.4670000 29.4670000 + 73 73 1 0.0000000 10.7150000 2.6790000 2.6790000 + 74 74 1 0.0000000 10.7150000 2.6790000 8.0360000 + 75 75 1 0.0000000 10.7150000 2.6790000 13.3940000 + 76 76 1 0.0000000 10.7150000 2.6790000 18.7520000 + 77 77 1 0.0000000 10.7150000 2.6790000 24.1090000 + 78 78 1 0.0000000 10.7150000 2.6790000 29.4670000 + 79 79 1 0.0000000 10.7150000 8.0360000 2.6790000 + 80 80 1 0.0000000 10.7150000 8.0360000 8.0360000 + 81 81 1 0.0000000 10.7150000 8.0360000 13.3940000 + 82 82 1 0.0000000 10.7150000 8.0360000 18.7520000 + 83 83 1 0.0000000 10.7150000 8.0360000 24.1090000 + 84 84 1 0.0000000 10.7150000 8.0360000 29.4670000 + 85 85 1 0.0000000 10.7150000 13.3940000 2.6790000 + 86 86 1 0.0000000 10.7150000 13.3940000 8.0360000 + 87 87 1 0.0000000 10.7150000 13.3940000 13.3940000 + 88 88 1 0.0000000 10.7150000 13.3940000 18.7520000 + 89 89 1 0.0000000 10.7150000 13.3940000 24.1090000 + 90 90 1 0.0000000 10.7150000 13.3940000 29.4670000 + 91 91 1 0.0000000 10.7150000 18.7520000 2.6790000 + 92 92 1 0.0000000 10.7150000 18.7520000 8.0360000 + 93 93 1 0.0000000 10.7150000 18.7520000 13.3940000 + 94 94 1 0.0000000 10.7150000 18.7520000 18.7520000 + 95 95 1 0.0000000 10.7150000 18.7520000 24.1090000 + 96 96 1 0.0000000 10.7150000 18.7520000 29.4670000 + 97 97 1 0.0000000 10.7150000 24.1090000 2.6790000 + 98 98 1 0.0000000 10.7150000 24.1090000 8.0360000 + 99 99 1 0.0000000 10.7150000 24.1090000 13.3940000 + 100 100 1 0.0000000 10.7150000 24.1090000 18.7520000 + 101 101 1 0.0000000 10.7150000 24.1090000 24.1090000 + 102 102 1 0.0000000 10.7150000 24.1090000 29.4670000 + 103 103 1 0.0000000 10.7150000 29.4670000 2.6790000 + 104 104 1 0.0000000 10.7150000 29.4670000 8.0360000 + 105 105 1 0.0000000 10.7150000 29.4670000 13.3940000 + 106 106 1 0.0000000 10.7150000 29.4670000 18.7520000 + 107 107 1 0.0000000 10.7150000 29.4670000 24.1090000 + 108 108 1 0.0000000 10.7150000 29.4670000 29.4670000 + 109 109 1 0.0000000 16.0730000 2.6790000 2.6790000 + 110 110 1 0.0000000 16.0730000 2.6790000 8.0360000 + 111 111 1 0.0000000 16.0730000 2.6790000 13.3940000 + 112 112 1 0.0000000 16.0730000 2.6790000 18.7520000 + 113 113 1 0.0000000 16.0730000 2.6790000 24.1090000 + 114 114 1 0.0000000 16.0730000 2.6790000 29.4670000 + 115 115 1 0.0000000 16.0730000 8.0360000 2.6790000 + 116 116 1 0.0000000 16.0730000 8.0360000 8.0360000 + 117 117 1 0.0000000 16.0730000 8.0360000 13.3940000 + 118 118 1 0.0000000 16.0730000 8.0360000 18.7520000 + 119 119 1 0.0000000 16.0730000 8.0360000 24.1090000 + 120 120 1 0.0000000 16.0730000 8.0360000 29.4670000 + 121 121 1 0.0000000 16.0730000 13.3940000 2.6790000 + 122 122 1 0.0000000 16.0730000 13.3940000 8.0360000 + 123 123 1 0.0000000 16.0730000 13.3940000 13.3940000 + 124 124 1 0.0000000 16.0730000 13.3940000 18.7520000 + 125 125 1 0.0000000 16.0730000 13.3940000 24.1090000 + 126 126 1 0.0000000 16.0730000 13.3940000 29.4670000 + 127 127 1 0.0000000 16.0730000 18.7520000 2.6790000 + 128 128 1 0.0000000 16.0730000 18.7520000 8.0360000 + 129 129 1 0.0000000 16.0730000 18.7520000 13.3940000 + 130 130 1 0.0000000 16.0730000 18.7520000 18.7520000 + 131 131 1 0.0000000 16.0730000 18.7520000 24.1090000 + 132 132 1 0.0000000 16.0730000 18.7520000 29.4670000 + 133 133 1 0.0000000 16.0730000 24.1090000 2.6790000 + 134 134 1 0.0000000 16.0730000 24.1090000 8.0360000 + 135 135 1 0.0000000 16.0730000 24.1090000 13.3940000 + 136 136 1 0.0000000 16.0730000 24.1090000 18.7520000 + 137 137 1 0.0000000 16.0730000 24.1090000 24.1090000 + 138 138 1 0.0000000 16.0730000 24.1090000 29.4670000 + 139 139 1 0.0000000 16.0730000 29.4670000 2.6790000 + 140 140 1 0.0000000 16.0730000 29.4670000 8.0360000 + 141 141 1 0.0000000 16.0730000 29.4670000 13.3940000 + 142 142 1 0.0000000 16.0730000 29.4670000 18.7520000 + 143 143 1 0.0000000 16.0730000 29.4670000 24.1090000 + 144 144 1 0.0000000 16.0730000 29.4670000 29.4670000 + 145 145 1 0.0000000 21.4310000 2.6790000 2.6790000 + 146 146 1 0.0000000 21.4310000 2.6790000 8.0360000 + 147 147 1 0.0000000 21.4310000 2.6790000 13.3940000 + 148 148 1 0.0000000 21.4310000 2.6790000 18.7520000 + 149 149 1 0.0000000 21.4310000 2.6790000 24.1090000 + 150 150 1 0.0000000 21.4310000 2.6790000 29.4670000 + 151 151 1 0.0000000 21.4310000 8.0360000 2.6790000 + 152 152 1 0.0000000 21.4310000 8.0360000 8.0360000 + 153 153 1 0.0000000 21.4310000 8.0360000 13.3940000 + 154 154 1 0.0000000 21.4310000 8.0360000 18.7520000 + 155 155 1 0.0000000 21.4310000 8.0360000 24.1090000 + 156 156 1 0.0000000 21.4310000 8.0360000 29.4670000 + 157 157 1 0.0000000 21.4310000 13.3940000 2.6790000 + 158 158 1 0.0000000 21.4310000 13.3940000 8.0360000 + 159 159 1 0.0000000 21.4310000 13.3940000 13.3940000 + 160 160 1 0.0000000 21.4310000 13.3940000 18.7520000 + 161 161 1 0.0000000 21.4310000 13.3940000 24.1090000 + 162 162 1 0.0000000 21.4310000 13.3940000 29.4670000 + 163 163 1 0.0000000 21.4310000 18.7520000 2.6790000 + 164 164 1 0.0000000 21.4310000 18.7520000 8.0360000 + 165 165 1 0.0000000 21.4310000 18.7520000 13.3940000 + 166 166 1 0.0000000 21.4310000 18.7520000 18.7520000 + 167 167 1 0.0000000 21.4310000 18.7520000 24.1090000 + 168 168 1 0.0000000 21.4310000 18.7520000 29.4670000 + 169 169 1 0.0000000 21.4310000 24.1090000 2.6790000 + 170 170 1 0.0000000 21.4310000 24.1090000 8.0360000 + 171 171 1 0.0000000 21.4310000 24.1090000 13.3940000 + 172 172 1 0.0000000 21.4310000 24.1090000 18.7520000 + 173 173 1 0.0000000 21.4310000 24.1090000 24.1090000 + 174 174 1 0.0000000 21.4310000 24.1090000 29.4670000 + 175 175 1 0.0000000 21.4310000 29.4670000 2.6790000 + 176 176 1 0.0000000 21.4310000 29.4670000 8.0360000 + 177 177 1 0.0000000 21.4310000 29.4670000 13.3940000 + 178 178 1 0.0000000 21.4310000 29.4670000 18.7520000 + 179 179 1 0.0000000 21.4310000 29.4670000 24.1090000 + 180 180 1 0.0000000 21.4310000 29.4670000 29.4670000 + 181 181 1 0.0000000 26.7880000 2.6790000 2.6790000 + 182 182 1 0.0000000 26.7880000 2.6790000 8.0360000 + 183 183 1 0.0000000 26.7880000 2.6790000 13.3940000 + 184 184 1 0.0000000 26.7880000 2.6790000 18.7520000 + 185 185 1 0.0000000 26.7880000 2.6790000 24.1090000 + 186 186 1 0.0000000 26.7880000 2.6790000 29.4670000 + 187 187 1 0.0000000 26.7880000 8.0360000 2.6790000 + 188 188 1 0.0000000 26.7880000 8.0360000 8.0360000 + 189 189 1 0.0000000 26.7880000 8.0360000 13.3940000 + 190 190 1 0.0000000 26.7880000 8.0360000 18.7520000 + 191 191 1 0.0000000 26.7880000 8.0360000 24.1090000 + 192 192 1 0.0000000 26.7880000 8.0360000 29.4670000 + 193 193 1 0.0000000 26.7880000 13.3940000 2.6790000 + 194 194 1 0.0000000 26.7880000 13.3940000 8.0360000 + 195 195 1 0.0000000 26.7880000 13.3940000 13.3940000 + 196 196 1 0.0000000 26.7880000 13.3940000 18.7520000 + 197 197 1 0.0000000 26.7880000 13.3940000 24.1090000 + 198 198 1 0.0000000 26.7880000 13.3940000 29.4670000 + 199 199 1 0.0000000 26.7880000 18.7520000 2.6790000 + 200 200 1 0.0000000 26.7880000 18.7520000 8.0360000 + 201 201 1 0.0000000 26.7880000 18.7520000 13.3940000 + 202 202 1 0.0000000 26.7880000 18.7520000 18.7520000 + 203 203 1 0.0000000 26.7880000 18.7520000 24.1090000 + 204 204 1 0.0000000 26.7880000 18.7520000 29.4670000 + 205 205 1 0.0000000 26.7880000 24.1090000 2.6790000 + 206 206 1 0.0000000 26.7880000 24.1090000 8.0360000 + 207 207 1 0.0000000 26.7880000 24.1090000 13.3940000 + 208 208 1 0.0000000 26.7880000 24.1090000 18.7520000 + 209 209 1 0.0000000 26.7880000 24.1090000 24.1090000 + 210 210 1 0.0000000 26.7880000 24.1090000 29.4670000 + 211 211 1 0.0000000 26.7880000 29.4670000 2.6790000 + 212 212 1 0.0000000 26.7880000 29.4670000 8.0360000 + 213 213 1 0.0000000 26.7880000 29.4670000 13.3940000 + 214 214 1 0.0000000 26.7880000 29.4670000 18.7520000 + 215 215 1 0.0000000 26.7880000 29.4670000 24.1090000 + 216 216 1 0.0000000 26.7880000 29.4670000 29.4670000 + 217 217 1 0.0000000 2.6790000 5.3580000 2.6790000 + 218 218 1 0.0000000 2.6790000 5.3580000 8.0360000 + 219 219 1 0.0000000 2.6790000 5.3580000 13.3940000 + 220 220 1 0.0000000 2.6790000 5.3580000 18.7520000 + 221 221 1 0.0000000 2.6790000 5.3580000 24.1090000 + 222 222 1 0.0000000 2.6790000 5.3580000 29.4670000 + 223 223 1 0.0000000 2.6790000 10.7150000 2.6790000 + 224 224 1 0.0000000 2.6790000 10.7150000 8.0360000 + 225 225 1 0.0000000 2.6790000 10.7150000 13.3940000 + 226 226 1 0.0000000 2.6790000 10.7150000 18.7520000 + 227 227 1 0.0000000 2.6790000 10.7150000 24.1090000 + 228 228 1 0.0000000 2.6790000 10.7150000 29.4670000 + 229 229 1 0.0000000 2.6790000 16.0730000 2.6790000 + 230 230 1 0.0000000 2.6790000 16.0730000 8.0360000 + 231 231 1 0.0000000 2.6790000 16.0730000 13.3940000 + 232 232 1 0.0000000 2.6790000 16.0730000 18.7520000 + 233 233 1 0.0000000 2.6790000 16.0730000 24.1090000 + 234 234 1 0.0000000 2.6790000 16.0730000 29.4670000 + 235 235 1 0.0000000 2.6790000 21.4310000 2.6790000 + 236 236 1 0.0000000 2.6790000 21.4310000 8.0360000 + 237 237 1 0.0000000 2.6790000 21.4310000 13.3940000 + 238 238 1 0.0000000 2.6790000 21.4310000 18.7520000 + 239 239 1 0.0000000 2.6790000 21.4310000 24.1090000 + 240 240 1 0.0000000 2.6790000 21.4310000 29.4670000 + 241 241 1 0.0000000 2.6790000 26.7880000 2.6790000 + 242 242 1 0.0000000 2.6790000 26.7880000 8.0360000 + 243 243 1 0.0000000 2.6790000 26.7880000 13.3940000 + 244 244 1 0.0000000 2.6790000 26.7880000 18.7520000 + 245 245 1 0.0000000 2.6790000 26.7880000 24.1090000 + 246 246 1 0.0000000 2.6790000 26.7880000 29.4670000 + 247 247 1 0.0000000 2.6790000 32.1460000 2.6790000 + 248 248 1 0.0000000 2.6790000 32.1460000 8.0360000 + 249 249 1 0.0000000 2.6790000 32.1460000 13.3940000 + 250 250 1 0.0000000 2.6790000 32.1460000 18.7520000 + 251 251 1 0.0000000 2.6790000 32.1460000 24.1090000 + 252 252 1 0.0000000 2.6790000 32.1460000 29.4670000 + 253 253 1 0.0000000 8.0360000 5.3580000 2.6790000 + 254 254 1 0.0000000 8.0360000 5.3580000 8.0360000 + 255 255 1 0.0000000 8.0360000 5.3580000 13.3940000 + 256 256 1 0.0000000 8.0360000 5.3580000 18.7520000 + 257 257 1 0.0000000 8.0360000 5.3580000 24.1090000 + 258 258 1 0.0000000 8.0360000 5.3580000 29.4670000 + 259 259 1 0.0000000 8.0360000 10.7150000 2.6790000 + 260 260 1 0.0000000 8.0360000 10.7150000 8.0360000 + 261 261 1 0.0000000 8.0360000 10.7150000 13.3940000 + 262 262 1 0.0000000 8.0360000 10.7150000 18.7520000 + 263 263 1 0.0000000 8.0360000 10.7150000 24.1090000 + 264 264 1 0.0000000 8.0360000 10.7150000 29.4670000 + 265 265 1 0.0000000 8.0360000 16.0730000 2.6790000 + 266 266 1 0.0000000 8.0360000 16.0730000 8.0360000 + 267 267 1 0.0000000 8.0360000 16.0730000 13.3940000 + 268 268 1 0.0000000 8.0360000 16.0730000 18.7520000 + 269 269 1 0.0000000 8.0360000 16.0730000 24.1090000 + 270 270 1 0.0000000 8.0360000 16.0730000 29.4670000 + 271 271 1 0.0000000 8.0360000 21.4310000 2.6790000 + 272 272 1 0.0000000 8.0360000 21.4310000 8.0360000 + 273 273 1 0.0000000 8.0360000 21.4310000 13.3940000 + 274 274 1 0.0000000 8.0360000 21.4310000 18.7520000 + 275 275 1 0.0000000 8.0360000 21.4310000 24.1090000 + 276 276 1 0.0000000 8.0360000 21.4310000 29.4670000 + 277 277 1 0.0000000 8.0360000 26.7880000 2.6790000 + 278 278 1 0.0000000 8.0360000 26.7880000 8.0360000 + 279 279 1 0.0000000 8.0360000 26.7880000 13.3940000 + 280 280 1 0.0000000 8.0360000 26.7880000 18.7520000 + 281 281 1 0.0000000 8.0360000 26.7880000 24.1090000 + 282 282 1 0.0000000 8.0360000 26.7880000 29.4670000 + 283 283 1 0.0000000 8.0360000 32.1460000 2.6790000 + 284 284 1 0.0000000 8.0360000 32.1460000 8.0360000 + 285 285 1 0.0000000 8.0360000 32.1460000 13.3940000 + 286 286 1 0.0000000 8.0360000 32.1460000 18.7520000 + 287 287 1 0.0000000 8.0360000 32.1460000 24.1090000 + 288 288 1 0.0000000 8.0360000 32.1460000 29.4670000 + 289 289 1 0.0000000 13.3940000 5.3580000 2.6790000 + 290 290 1 0.0000000 13.3940000 5.3580000 8.0360000 + 291 291 1 0.0000000 13.3940000 5.3580000 13.3940000 + 292 292 1 0.0000000 13.3940000 5.3580000 18.7520000 + 293 293 1 0.0000000 13.3940000 5.3580000 24.1090000 + 294 294 1 0.0000000 13.3940000 5.3580000 29.4670000 + 295 295 1 0.0000000 13.3940000 10.7150000 2.6790000 + 296 296 1 0.0000000 13.3940000 10.7150000 8.0360000 + 297 297 1 0.0000000 13.3940000 10.7150000 13.3940000 + 298 298 1 0.0000000 13.3940000 10.7150000 18.7520000 + 299 299 1 0.0000000 13.3940000 10.7150000 24.1090000 + 300 300 1 0.0000000 13.3940000 10.7150000 29.4670000 + 301 301 1 0.0000000 13.3940000 16.0730000 2.6790000 + 302 302 1 0.0000000 13.3940000 16.0730000 8.0360000 + 303 303 1 0.0000000 13.3940000 16.0730000 13.3940000 + 304 304 1 0.0000000 13.3940000 16.0730000 18.7520000 + 305 305 1 0.0000000 13.3940000 16.0730000 24.1090000 + 306 306 1 0.0000000 13.3940000 16.0730000 29.4670000 + 307 307 1 0.0000000 13.3940000 21.4310000 2.6790000 + 308 308 1 0.0000000 13.3940000 21.4310000 8.0360000 + 309 309 1 0.0000000 13.3940000 21.4310000 13.3940000 + 310 310 1 0.0000000 13.3940000 21.4310000 18.7520000 + 311 311 1 0.0000000 13.3940000 21.4310000 24.1090000 + 312 312 1 0.0000000 13.3940000 21.4310000 29.4670000 + 313 313 1 0.0000000 13.3940000 26.7880000 2.6790000 + 314 314 1 0.0000000 13.3940000 26.7880000 8.0360000 + 315 315 1 0.0000000 13.3940000 26.7880000 13.3940000 + 316 316 1 0.0000000 13.3940000 26.7880000 18.7520000 + 317 317 1 0.0000000 13.3940000 26.7880000 24.1090000 + 318 318 1 0.0000000 13.3940000 26.7880000 29.4670000 + 319 319 1 0.0000000 13.3940000 32.1460000 2.6790000 + 320 320 1 0.0000000 13.3940000 32.1460000 8.0360000 + 321 321 1 0.0000000 13.3940000 32.1460000 13.3940000 + 322 322 1 0.0000000 13.3940000 32.1460000 18.7520000 + 323 323 1 0.0000000 13.3940000 32.1460000 24.1090000 + 324 324 1 0.0000000 13.3940000 32.1460000 29.4670000 + 325 325 1 0.0000000 18.7520000 5.3580000 2.6790000 + 326 326 1 0.0000000 18.7520000 5.3580000 8.0360000 + 327 327 1 0.0000000 18.7520000 5.3580000 13.3940000 + 328 328 1 0.0000000 18.7520000 5.3580000 18.7520000 + 329 329 1 0.0000000 18.7520000 5.3580000 24.1090000 + 330 330 1 0.0000000 18.7520000 5.3580000 29.4670000 + 331 331 1 0.0000000 18.7520000 10.7150000 2.6790000 + 332 332 1 0.0000000 18.7520000 10.7150000 8.0360000 + 333 333 1 0.0000000 18.7520000 10.7150000 13.3940000 + 334 334 1 0.0000000 18.7520000 10.7150000 18.7520000 + 335 335 1 0.0000000 18.7520000 10.7150000 24.1090000 + 336 336 1 0.0000000 18.7520000 10.7150000 29.4670000 + 337 337 1 0.0000000 18.7520000 16.0730000 2.6790000 + 338 338 1 0.0000000 18.7520000 16.0730000 8.0360000 + 339 339 1 0.0000000 18.7520000 16.0730000 13.3940000 + 340 340 1 0.0000000 18.7520000 16.0730000 18.7520000 + 341 341 1 0.0000000 18.7520000 16.0730000 24.1090000 + 342 342 1 0.0000000 18.7520000 16.0730000 29.4670000 + 343 343 1 0.0000000 18.7520000 21.4310000 2.6790000 + 344 344 1 0.0000000 18.7520000 21.4310000 8.0360000 + 345 345 1 0.0000000 18.7520000 21.4310000 13.3940000 + 346 346 1 0.0000000 18.7520000 21.4310000 18.7520000 + 347 347 1 0.0000000 18.7520000 21.4310000 24.1090000 + 348 348 1 0.0000000 18.7520000 21.4310000 29.4670000 + 349 349 1 0.0000000 18.7520000 26.7880000 2.6790000 + 350 350 1 0.0000000 18.7520000 26.7880000 8.0360000 + 351 351 1 0.0000000 18.7520000 26.7880000 13.3940000 + 352 352 1 0.0000000 18.7520000 26.7880000 18.7520000 + 353 353 1 0.0000000 18.7520000 26.7880000 24.1090000 + 354 354 1 0.0000000 18.7520000 26.7880000 29.4670000 + 355 355 1 0.0000000 18.7520000 32.1460000 2.6790000 + 356 356 1 0.0000000 18.7520000 32.1460000 8.0360000 + 357 357 1 0.0000000 18.7520000 32.1460000 13.3940000 + 358 358 1 0.0000000 18.7520000 32.1460000 18.7520000 + 359 359 1 0.0000000 18.7520000 32.1460000 24.1090000 + 360 360 1 0.0000000 18.7520000 32.1460000 29.4670000 + 361 361 1 0.0000000 24.1090000 5.3580000 2.6790000 + 362 362 1 0.0000000 24.1090000 5.3580000 8.0360000 + 363 363 1 0.0000000 24.1090000 5.3580000 13.3940000 + 364 364 1 0.0000000 24.1090000 5.3580000 18.7520000 + 365 365 1 0.0000000 24.1090000 5.3580000 24.1090000 + 366 366 1 0.0000000 24.1090000 5.3580000 29.4670000 + 367 367 1 0.0000000 24.1090000 10.7150000 2.6790000 + 368 368 1 0.0000000 24.1090000 10.7150000 8.0360000 + 369 369 1 0.0000000 24.1090000 10.7150000 13.3940000 + 370 370 1 0.0000000 24.1090000 10.7150000 18.7520000 + 371 371 1 0.0000000 24.1090000 10.7150000 24.1090000 + 372 372 1 0.0000000 24.1090000 10.7150000 29.4670000 + 373 373 1 0.0000000 24.1090000 16.0730000 2.6790000 + 374 374 1 0.0000000 24.1090000 16.0730000 8.0360000 + 375 375 1 0.0000000 24.1090000 16.0730000 13.3940000 + 376 376 1 0.0000000 24.1090000 16.0730000 18.7520000 + 377 377 1 0.0000000 24.1090000 16.0730000 24.1090000 + 378 378 1 0.0000000 24.1090000 16.0730000 29.4670000 + 379 379 1 0.0000000 24.1090000 21.4310000 2.6790000 + 380 380 1 0.0000000 24.1090000 21.4310000 8.0360000 + 381 381 1 0.0000000 24.1090000 21.4310000 13.3940000 + 382 382 1 0.0000000 24.1090000 21.4310000 18.7520000 + 383 383 1 0.0000000 24.1090000 21.4310000 24.1090000 + 384 384 1 0.0000000 24.1090000 21.4310000 29.4670000 + 385 385 1 0.0000000 24.1090000 26.7880000 2.6790000 + 386 386 1 0.0000000 24.1090000 26.7880000 8.0360000 + 387 387 1 0.0000000 24.1090000 26.7880000 13.3940000 + 388 388 1 0.0000000 24.1090000 26.7880000 18.7520000 + 389 389 1 0.0000000 24.1090000 26.7880000 24.1090000 + 390 390 1 0.0000000 24.1090000 26.7880000 29.4670000 + 391 391 1 0.0000000 24.1090000 32.1460000 2.6790000 + 392 392 1 0.0000000 24.1090000 32.1460000 8.0360000 + 393 393 1 0.0000000 24.1090000 32.1460000 13.3940000 + 394 394 1 0.0000000 24.1090000 32.1460000 18.7520000 + 395 395 1 0.0000000 24.1090000 32.1460000 24.1090000 + 396 396 1 0.0000000 24.1090000 32.1460000 29.4670000 + 397 397 1 0.0000000 29.4670000 5.3580000 2.6790000 + 398 398 1 0.0000000 29.4670000 5.3580000 8.0360000 + 399 399 1 0.0000000 29.4670000 5.3580000 13.3940000 + 400 400 1 0.0000000 29.4670000 5.3580000 18.7520000 + 401 401 1 0.0000000 29.4670000 5.3580000 24.1090000 + 402 402 1 0.0000000 29.4670000 5.3580000 29.4670000 + 403 403 1 0.0000000 29.4670000 10.7150000 2.6790000 + 404 404 1 0.0000000 29.4670000 10.7150000 8.0360000 + 405 405 1 0.0000000 29.4670000 10.7150000 13.3940000 + 406 406 1 0.0000000 29.4670000 10.7150000 18.7520000 + 407 407 1 0.0000000 29.4670000 10.7150000 24.1090000 + 408 408 1 0.0000000 29.4670000 10.7150000 29.4670000 + 409 409 1 0.0000000 29.4670000 16.0730000 2.6790000 + 410 410 1 0.0000000 29.4670000 16.0730000 8.0360000 + 411 411 1 0.0000000 29.4670000 16.0730000 13.3940000 + 412 412 1 0.0000000 29.4670000 16.0730000 18.7520000 + 413 413 1 0.0000000 29.4670000 16.0730000 24.1090000 + 414 414 1 0.0000000 29.4670000 16.0730000 29.4670000 + 415 415 1 0.0000000 29.4670000 21.4310000 2.6790000 + 416 416 1 0.0000000 29.4670000 21.4310000 8.0360000 + 417 417 1 0.0000000 29.4670000 21.4310000 13.3940000 + 418 418 1 0.0000000 29.4670000 21.4310000 18.7520000 + 419 419 1 0.0000000 29.4670000 21.4310000 24.1090000 + 420 420 1 0.0000000 29.4670000 21.4310000 29.4670000 + 421 421 1 0.0000000 29.4670000 26.7880000 2.6790000 + 422 422 1 0.0000000 29.4670000 26.7880000 8.0360000 + 423 423 1 0.0000000 29.4670000 26.7880000 13.3940000 + 424 424 1 0.0000000 29.4670000 26.7880000 18.7520000 + 425 425 1 0.0000000 29.4670000 26.7880000 24.1090000 + 426 426 1 0.0000000 29.4670000 26.7880000 29.4670000 + 427 427 1 0.0000000 29.4670000 32.1460000 2.6790000 + 428 428 1 0.0000000 29.4670000 32.1460000 8.0360000 + 429 429 1 0.0000000 29.4670000 32.1460000 13.3940000 + 430 430 1 0.0000000 29.4670000 32.1460000 18.7520000 + 431 431 1 0.0000000 29.4670000 32.1460000 24.1090000 + 432 432 1 0.0000000 29.4670000 32.1460000 29.4670000 + 433 433 1 0.0000000 2.6790000 2.6790000 5.3580000 + 434 434 1 0.0000000 2.6790000 2.6790000 10.7150000 + 435 435 1 0.0000000 2.6790000 2.6790000 16.0730000 + 436 436 1 0.0000000 2.6790000 2.6790000 21.4310000 + 437 437 1 0.0000000 2.6790000 2.6790000 26.7880000 + 438 438 1 0.0000000 2.6790000 2.6790000 32.1460000 + 439 439 1 0.0000000 2.6790000 8.0360000 5.3580000 + 440 440 1 0.0000000 2.6790000 8.0360000 10.7150000 + 441 441 1 0.0000000 2.6790000 8.0360000 16.0730000 + 442 442 1 0.0000000 2.6790000 8.0360000 21.4310000 + 443 443 1 0.0000000 2.6790000 8.0360000 26.7880000 + 444 444 1 0.0000000 2.6790000 8.0360000 32.1460000 + 445 445 1 0.0000000 2.6790000 13.3940000 5.3580000 + 446 446 1 0.0000000 2.6790000 13.3940000 10.7150000 + 447 447 1 0.0000000 2.6790000 13.3940000 16.0730000 + 448 448 1 0.0000000 2.6790000 13.3940000 21.4310000 + 449 449 1 0.0000000 2.6790000 13.3940000 26.7880000 + 450 450 1 0.0000000 2.6790000 13.3940000 32.1460000 + 451 451 1 0.0000000 2.6790000 18.7520000 5.3580000 + 452 452 1 0.0000000 2.6790000 18.7520000 10.7150000 + 453 453 1 0.0000000 2.6790000 18.7520000 16.0730000 + 454 454 1 0.0000000 2.6790000 18.7520000 21.4310000 + 455 455 1 0.0000000 2.6790000 18.7520000 26.7880000 + 456 456 1 0.0000000 2.6790000 18.7520000 32.1460000 + 457 457 1 0.0000000 2.6790000 24.1090000 5.3580000 + 458 458 1 0.0000000 2.6790000 24.1090000 10.7150000 + 459 459 1 0.0000000 2.6790000 24.1090000 16.0730000 + 460 460 1 0.0000000 2.6790000 24.1090000 21.4310000 + 461 461 1 0.0000000 2.6790000 24.1090000 26.7880000 + 462 462 1 0.0000000 2.6790000 24.1090000 32.1460000 + 463 463 1 0.0000000 2.6790000 29.4670000 5.3580000 + 464 464 1 0.0000000 2.6790000 29.4670000 10.7150000 + 465 465 1 0.0000000 2.6790000 29.4670000 16.0730000 + 466 466 1 0.0000000 2.6790000 29.4670000 21.4310000 + 467 467 1 0.0000000 2.6790000 29.4670000 26.7880000 + 468 468 1 0.0000000 2.6790000 29.4670000 32.1460000 + 469 469 1 0.0000000 8.0360000 2.6790000 5.3580000 + 470 470 1 0.0000000 8.0360000 2.6790000 10.7150000 + 471 471 1 0.0000000 8.0360000 2.6790000 16.0730000 + 472 472 1 0.0000000 8.0360000 2.6790000 21.4310000 + 473 473 1 0.0000000 8.0360000 2.6790000 26.7880000 + 474 474 1 0.0000000 8.0360000 2.6790000 32.1460000 + 475 475 1 0.0000000 8.0360000 8.0360000 5.3580000 + 476 476 1 0.0000000 8.0360000 8.0360000 10.7150000 + 477 477 1 0.0000000 8.0360000 8.0360000 16.0730000 + 478 478 1 0.0000000 8.0360000 8.0360000 21.4310000 + 479 479 1 0.0000000 8.0360000 8.0360000 26.7880000 + 480 480 1 0.0000000 8.0360000 8.0360000 32.1460000 + 481 481 1 0.0000000 8.0360000 13.3940000 5.3580000 + 482 482 1 0.0000000 8.0360000 13.3940000 10.7150000 + 483 483 1 0.0000000 8.0360000 13.3940000 16.0730000 + 484 484 1 0.0000000 8.0360000 13.3940000 21.4310000 + 485 485 1 0.0000000 8.0360000 13.3940000 26.7880000 + 486 486 1 0.0000000 8.0360000 13.3940000 32.1460000 + 487 487 1 0.0000000 8.0360000 18.7520000 5.3580000 + 488 488 1 0.0000000 8.0360000 18.7520000 10.7150000 + 489 489 1 0.0000000 8.0360000 18.7520000 16.0730000 + 490 490 1 0.0000000 8.0360000 18.7520000 21.4310000 + 491 491 1 0.0000000 8.0360000 18.7520000 26.7880000 + 492 492 1 0.0000000 8.0360000 18.7520000 32.1460000 + 493 493 1 0.0000000 8.0360000 24.1090000 5.3580000 + 494 494 1 0.0000000 8.0360000 24.1090000 10.7150000 + 495 495 1 0.0000000 8.0360000 24.1090000 16.0730000 + 496 496 1 0.0000000 8.0360000 24.1090000 21.4310000 + 497 497 1 0.0000000 8.0360000 24.1090000 26.7880000 + 498 498 1 0.0000000 8.0360000 24.1090000 32.1460000 + 499 499 1 0.0000000 8.0360000 29.4670000 5.3580000 + 500 500 1 0.0000000 8.0360000 29.4670000 10.7150000 + 501 501 1 0.0000000 8.0360000 29.4670000 16.0730000 + 502 502 1 0.0000000 8.0360000 29.4670000 21.4310000 + 503 503 1 0.0000000 8.0360000 29.4670000 26.7880000 + 504 504 1 0.0000000 8.0360000 29.4670000 32.1460000 + 505 505 1 0.0000000 13.3940000 2.6790000 5.3580000 + 506 506 1 0.0000000 13.3940000 2.6790000 10.7150000 + 507 507 1 0.0000000 13.3940000 2.6790000 16.0730000 + 508 508 1 0.0000000 13.3940000 2.6790000 21.4310000 + 509 509 1 0.0000000 13.3940000 2.6790000 26.7880000 + 510 510 1 0.0000000 13.3940000 2.6790000 32.1460000 + 511 511 1 0.0000000 13.3940000 8.0360000 5.3580000 + 512 512 1 0.0000000 13.3940000 8.0360000 10.7150000 + 513 513 1 0.0000000 13.3940000 8.0360000 16.0730000 + 514 514 1 0.0000000 13.3940000 8.0360000 21.4310000 + 515 515 1 0.0000000 13.3940000 8.0360000 26.7880000 + 516 516 1 0.0000000 13.3940000 8.0360000 32.1460000 + 517 517 1 0.0000000 13.3940000 13.3940000 5.3580000 + 518 518 1 0.0000000 13.3940000 13.3940000 10.7150000 + 519 519 1 0.0000000 13.3940000 13.3940000 16.0730000 + 520 520 1 0.0000000 13.3940000 13.3940000 21.4310000 + 521 521 1 0.0000000 13.3940000 13.3940000 26.7880000 + 522 522 1 0.0000000 13.3940000 13.3940000 32.1460000 + 523 523 1 0.0000000 13.3940000 18.7520000 5.3580000 + 524 524 1 0.0000000 13.3940000 18.7520000 10.7150000 + 525 525 1 0.0000000 13.3940000 18.7520000 16.0730000 + 526 526 1 0.0000000 13.3940000 18.7520000 21.4310000 + 527 527 1 0.0000000 13.3940000 18.7520000 26.7880000 + 528 528 1 0.0000000 13.3940000 18.7520000 32.1460000 + 529 529 1 0.0000000 13.3940000 24.1090000 5.3580000 + 530 530 1 0.0000000 13.3940000 24.1090000 10.7150000 + 531 531 1 0.0000000 13.3940000 24.1090000 16.0730000 + 532 532 1 0.0000000 13.3940000 24.1090000 21.4310000 + 533 533 1 0.0000000 13.3940000 24.1090000 26.7880000 + 534 534 1 0.0000000 13.3940000 24.1090000 32.1460000 + 535 535 1 0.0000000 13.3940000 29.4670000 5.3580000 + 536 536 1 0.0000000 13.3940000 29.4670000 10.7150000 + 537 537 1 0.0000000 13.3940000 29.4670000 16.0730000 + 538 538 1 0.0000000 13.3940000 29.4670000 21.4310000 + 539 539 1 0.0000000 13.3940000 29.4670000 26.7880000 + 540 540 1 0.0000000 13.3940000 29.4670000 32.1460000 + 541 541 1 0.0000000 18.7520000 2.6790000 5.3580000 + 542 542 1 0.0000000 18.7520000 2.6790000 10.7150000 + 543 543 1 0.0000000 18.7520000 2.6790000 16.0730000 + 544 544 1 0.0000000 18.7520000 2.6790000 21.4310000 + 545 545 1 0.0000000 18.7520000 2.6790000 26.7880000 + 546 546 1 0.0000000 18.7520000 2.6790000 32.1460000 + 547 547 1 0.0000000 18.7520000 8.0360000 5.3580000 + 548 548 1 0.0000000 18.7520000 8.0360000 10.7150000 + 549 549 1 0.0000000 18.7520000 8.0360000 16.0730000 + 550 550 1 0.0000000 18.7520000 8.0360000 21.4310000 + 551 551 1 0.0000000 18.7520000 8.0360000 26.7880000 + 552 552 1 0.0000000 18.7520000 8.0360000 32.1460000 + 553 553 1 0.0000000 18.7520000 13.3940000 5.3580000 + 554 554 1 0.0000000 18.7520000 13.3940000 10.7150000 + 555 555 1 0.0000000 18.7520000 13.3940000 16.0730000 + 556 556 1 0.0000000 18.7520000 13.3940000 21.4310000 + 557 557 1 0.0000000 18.7520000 13.3940000 26.7880000 + 558 558 1 0.0000000 18.7520000 13.3940000 32.1460000 + 559 559 1 0.0000000 18.7520000 18.7520000 5.3580000 + 560 560 1 0.0000000 18.7520000 18.7520000 10.7150000 + 561 561 1 0.0000000 18.7520000 18.7520000 16.0730000 + 562 562 1 0.0000000 18.7520000 18.7520000 21.4310000 + 563 563 1 0.0000000 18.7520000 18.7520000 26.7880000 + 564 564 1 0.0000000 18.7520000 18.7520000 32.1460000 + 565 565 1 0.0000000 18.7520000 24.1090000 5.3580000 + 566 566 1 0.0000000 18.7520000 24.1090000 10.7150000 + 567 567 1 0.0000000 18.7520000 24.1090000 16.0730000 + 568 568 1 0.0000000 18.7520000 24.1090000 21.4310000 + 569 569 1 0.0000000 18.7520000 24.1090000 26.7880000 + 570 570 1 0.0000000 18.7520000 24.1090000 32.1460000 + 571 571 1 0.0000000 18.7520000 29.4670000 5.3580000 + 572 572 1 0.0000000 18.7520000 29.4670000 10.7150000 + 573 573 1 0.0000000 18.7520000 29.4670000 16.0730000 + 574 574 1 0.0000000 18.7520000 29.4670000 21.4310000 + 575 575 1 0.0000000 18.7520000 29.4670000 26.7880000 + 576 576 1 0.0000000 18.7520000 29.4670000 32.1460000 + 577 577 1 0.0000000 24.1090000 2.6790000 5.3580000 + 578 578 1 0.0000000 24.1090000 2.6790000 10.7150000 + 579 579 1 0.0000000 24.1090000 2.6790000 16.0730000 + 580 580 1 0.0000000 24.1090000 2.6790000 21.4310000 + 581 581 1 0.0000000 24.1090000 2.6790000 26.7880000 + 582 582 1 0.0000000 24.1090000 2.6790000 32.1460000 + 583 583 1 0.0000000 24.1090000 8.0360000 5.3580000 + 584 584 1 0.0000000 24.1090000 8.0360000 10.7150000 + 585 585 1 0.0000000 24.1090000 8.0360000 16.0730000 + 586 586 1 0.0000000 24.1090000 8.0360000 21.4310000 + 587 587 1 0.0000000 24.1090000 8.0360000 26.7880000 + 588 588 1 0.0000000 24.1090000 8.0360000 32.1460000 + 589 589 1 0.0000000 24.1090000 13.3940000 5.3580000 + 590 590 1 0.0000000 24.1090000 13.3940000 10.7150000 + 591 591 1 0.0000000 24.1090000 13.3940000 16.0730000 + 592 592 1 0.0000000 24.1090000 13.3940000 21.4310000 + 593 593 1 0.0000000 24.1090000 13.3940000 26.7880000 + 594 594 1 0.0000000 24.1090000 13.3940000 32.1460000 + 595 595 1 0.0000000 24.1090000 18.7520000 5.3580000 + 596 596 1 0.0000000 24.1090000 18.7520000 10.7150000 + 597 597 1 0.0000000 24.1090000 18.7520000 16.0730000 + 598 598 1 0.0000000 24.1090000 18.7520000 21.4310000 + 599 599 1 0.0000000 24.1090000 18.7520000 26.7880000 + 600 600 1 0.0000000 24.1090000 18.7520000 32.1460000 + 601 601 1 0.0000000 24.1090000 24.1090000 5.3580000 + 602 602 1 0.0000000 24.1090000 24.1090000 10.7150000 + 603 603 1 0.0000000 24.1090000 24.1090000 16.0730000 + 604 604 1 0.0000000 24.1090000 24.1090000 21.4310000 + 605 605 1 0.0000000 24.1090000 24.1090000 26.7880000 + 606 606 1 0.0000000 24.1090000 24.1090000 32.1460000 + 607 607 1 0.0000000 24.1090000 29.4670000 5.3580000 + 608 608 1 0.0000000 24.1090000 29.4670000 10.7150000 + 609 609 1 0.0000000 24.1090000 29.4670000 16.0730000 + 610 610 1 0.0000000 24.1090000 29.4670000 21.4310000 + 611 611 1 0.0000000 24.1090000 29.4670000 26.7880000 + 612 612 1 0.0000000 24.1090000 29.4670000 32.1460000 + 613 613 1 0.0000000 29.4670000 2.6790000 5.3580000 + 614 614 1 0.0000000 29.4670000 2.6790000 10.7150000 + 615 615 1 0.0000000 29.4670000 2.6790000 16.0730000 + 616 616 1 0.0000000 29.4670000 2.6790000 21.4310000 + 617 617 1 0.0000000 29.4670000 2.6790000 26.7880000 + 618 618 1 0.0000000 29.4670000 2.6790000 32.1460000 + 619 619 1 0.0000000 29.4670000 8.0360000 5.3580000 + 620 620 1 0.0000000 29.4670000 8.0360000 10.7150000 + 621 621 1 0.0000000 29.4670000 8.0360000 16.0730000 + 622 622 1 0.0000000 29.4670000 8.0360000 21.4310000 + 623 623 1 0.0000000 29.4670000 8.0360000 26.7880000 + 624 624 1 0.0000000 29.4670000 8.0360000 32.1460000 + 625 625 1 0.0000000 29.4670000 13.3940000 5.3580000 + 626 626 1 0.0000000 29.4670000 13.3940000 10.7150000 + 627 627 1 0.0000000 29.4670000 13.3940000 16.0730000 + 628 628 1 0.0000000 29.4670000 13.3940000 21.4310000 + 629 629 1 0.0000000 29.4670000 13.3940000 26.7880000 + 630 630 1 0.0000000 29.4670000 13.3940000 32.1460000 + 631 631 1 0.0000000 29.4670000 18.7520000 5.3580000 + 632 632 1 0.0000000 29.4670000 18.7520000 10.7150000 + 633 633 1 0.0000000 29.4670000 18.7520000 16.0730000 + 634 634 1 0.0000000 29.4670000 18.7520000 21.4310000 + 635 635 1 0.0000000 29.4670000 18.7520000 26.7880000 + 636 636 1 0.0000000 29.4670000 18.7520000 32.1460000 + 637 637 1 0.0000000 29.4670000 24.1090000 5.3580000 + 638 638 1 0.0000000 29.4670000 24.1090000 10.7150000 + 639 639 1 0.0000000 29.4670000 24.1090000 16.0730000 + 640 640 1 0.0000000 29.4670000 24.1090000 21.4310000 + 641 641 1 0.0000000 29.4670000 24.1090000 26.7880000 + 642 642 1 0.0000000 29.4670000 24.1090000 32.1460000 + 643 643 1 0.0000000 29.4670000 29.4670000 5.3580000 + 644 644 1 0.0000000 29.4670000 29.4670000 10.7150000 + 645 645 1 0.0000000 29.4670000 29.4670000 16.0730000 + 646 646 1 0.0000000 29.4670000 29.4670000 21.4310000 + 647 647 1 0.0000000 29.4670000 29.4670000 26.7880000 + 648 648 1 0.0000000 29.4670000 29.4670000 32.1460000 + 649 649 1 0.0000000 0.0000000 5.3580000 5.3580000 + 650 650 1 0.0000000 0.0000000 5.3580000 10.7150000 + 651 651 1 0.0000000 0.0000000 5.3580000 16.0730000 + 652 652 1 0.0000000 0.0000000 5.3580000 21.4310000 + 653 653 1 0.0000000 0.0000000 5.3580000 26.7880000 + 654 654 1 0.0000000 0.0000000 5.3580000 32.1460000 + 655 655 1 0.0000000 0.0000000 10.7150000 5.3580000 + 656 656 1 0.0000000 0.0000000 10.7150000 10.7150000 + 657 657 1 0.0000000 0.0000000 10.7150000 16.0730000 + 658 658 1 0.0000000 0.0000000 10.7150000 21.4310000 + 659 659 1 0.0000000 0.0000000 10.7150000 26.7880000 + 660 660 1 0.0000000 0.0000000 10.7150000 32.1460000 + 661 661 1 0.0000000 0.0000000 16.0730000 5.3580000 + 662 662 1 0.0000000 0.0000000 16.0730000 10.7150000 + 663 663 1 0.0000000 0.0000000 16.0730000 16.0730000 + 664 664 1 0.0000000 0.0000000 16.0730000 21.4310000 + 665 665 1 0.0000000 0.0000000 16.0730000 26.7880000 + 666 666 1 0.0000000 0.0000000 16.0730000 32.1460000 + 667 667 1 0.0000000 0.0000000 21.4310000 5.3580000 + 668 668 1 0.0000000 0.0000000 21.4310000 10.7150000 + 669 669 1 0.0000000 0.0000000 21.4310000 16.0730000 + 670 670 1 0.0000000 0.0000000 21.4310000 21.4310000 + 671 671 1 0.0000000 0.0000000 21.4310000 26.7880000 + 672 672 1 0.0000000 0.0000000 21.4310000 32.1460000 + 673 673 1 0.0000000 0.0000000 26.7880000 5.3580000 + 674 674 1 0.0000000 0.0000000 26.7880000 10.7150000 + 675 675 1 0.0000000 0.0000000 26.7880000 16.0730000 + 676 676 1 0.0000000 0.0000000 26.7880000 21.4310000 + 677 677 1 0.0000000 0.0000000 26.7880000 26.7880000 + 678 678 1 0.0000000 0.0000000 26.7880000 32.1460000 + 679 679 1 0.0000000 0.0000000 32.1460000 5.3580000 + 680 680 1 0.0000000 0.0000000 32.1460000 10.7150000 + 681 681 1 0.0000000 0.0000000 32.1460000 16.0730000 + 682 682 1 0.0000000 0.0000000 32.1460000 21.4310000 + 683 683 1 0.0000000 0.0000000 32.1460000 26.7880000 + 684 684 1 0.0000000 0.0000000 32.1460000 32.1460000 + 685 685 1 0.0000000 5.3580000 5.3580000 5.3580000 + 686 686 1 0.0000000 5.3580000 5.3580000 10.7150000 + 687 687 1 0.0000000 5.3580000 5.3580000 16.0730000 + 688 688 1 0.0000000 5.3580000 5.3580000 21.4310000 + 689 689 1 0.0000000 5.3580000 5.3580000 26.7880000 + 690 690 1 0.0000000 5.3580000 5.3580000 32.1460000 + 691 691 1 0.0000000 5.3580000 10.7150000 5.3580000 + 692 692 1 0.0000000 5.3580000 10.7150000 10.7150000 + 693 693 1 0.0000000 5.3580000 10.7150000 16.0730000 + 694 694 1 0.0000000 5.3580000 10.7150000 21.4310000 + 695 695 1 0.0000000 5.3580000 10.7150000 26.7880000 + 696 696 1 0.0000000 5.3580000 10.7150000 32.1460000 + 697 697 1 0.0000000 5.3580000 16.0730000 5.3580000 + 698 698 1 0.0000000 5.3580000 16.0730000 10.7150000 + 699 699 1 0.0000000 5.3580000 16.0730000 16.0730000 + 700 700 1 0.0000000 5.3580000 16.0730000 21.4310000 + 701 701 1 0.0000000 5.3580000 16.0730000 26.7880000 + 702 702 1 0.0000000 5.3580000 16.0730000 32.1460000 + 703 703 1 0.0000000 5.3580000 21.4310000 5.3580000 + 704 704 1 0.0000000 5.3580000 21.4310000 10.7150000 + 705 705 1 0.0000000 5.3580000 21.4310000 16.0730000 + 706 706 1 0.0000000 5.3580000 21.4310000 21.4310000 + 707 707 1 0.0000000 5.3580000 21.4310000 26.7880000 + 708 708 1 0.0000000 5.3580000 21.4310000 32.1460000 + 709 709 1 0.0000000 5.3580000 26.7880000 5.3580000 + 710 710 1 0.0000000 5.3580000 26.7880000 10.7150000 + 711 711 1 0.0000000 5.3580000 26.7880000 16.0730000 + 712 712 1 0.0000000 5.3580000 26.7880000 21.4310000 + 713 713 1 0.0000000 5.3580000 26.7880000 26.7880000 + 714 714 1 0.0000000 5.3580000 26.7880000 32.1460000 + 715 715 1 0.0000000 5.3580000 32.1460000 5.3580000 + 716 716 1 0.0000000 5.3580000 32.1460000 10.7150000 + 717 717 1 0.0000000 5.3580000 32.1460000 16.0730000 + 718 718 1 0.0000000 5.3580000 32.1460000 21.4310000 + 719 719 1 0.0000000 5.3580000 32.1460000 26.7880000 + 720 720 1 0.0000000 5.3580000 32.1460000 32.1460000 + 721 721 1 0.0000000 10.7150000 5.3580000 5.3580000 + 722 722 1 0.0000000 10.7150000 5.3580000 10.7150000 + 723 723 1 0.0000000 10.7150000 5.3580000 16.0730000 + 724 724 1 0.0000000 10.7150000 5.3580000 21.4310000 + 725 725 1 0.0000000 10.7150000 5.3580000 26.7880000 + 726 726 1 0.0000000 10.7150000 5.3580000 32.1460000 + 727 727 1 0.0000000 10.7150000 10.7150000 5.3580000 + 728 728 1 0.0000000 10.7150000 10.7150000 10.7150000 + 729 729 1 0.0000000 10.7150000 10.7150000 16.0730000 + 730 730 1 0.0000000 10.7150000 10.7150000 21.4310000 + 731 731 1 0.0000000 10.7150000 10.7150000 26.7880000 + 732 732 1 0.0000000 10.7150000 10.7150000 32.1460000 + 733 733 1 0.0000000 10.7150000 16.0730000 5.3580000 + 734 734 1 0.0000000 10.7150000 16.0730000 10.7150000 + 735 735 1 0.0000000 10.7150000 16.0730000 16.0730000 + 736 736 1 0.0000000 10.7150000 16.0730000 21.4310000 + 737 737 1 0.0000000 10.7150000 16.0730000 26.7880000 + 738 738 1 0.0000000 10.7150000 16.0730000 32.1460000 + 739 739 1 0.0000000 10.7150000 21.4310000 5.3580000 + 740 740 1 0.0000000 10.7150000 21.4310000 10.7150000 + 741 741 1 0.0000000 10.7150000 21.4310000 16.0730000 + 742 742 1 0.0000000 10.7150000 21.4310000 21.4310000 + 743 743 1 0.0000000 10.7150000 21.4310000 26.7880000 + 744 744 1 0.0000000 10.7150000 21.4310000 32.1460000 + 745 745 1 0.0000000 10.7150000 26.7880000 5.3580000 + 746 746 1 0.0000000 10.7150000 26.7880000 10.7150000 + 747 747 1 0.0000000 10.7150000 26.7880000 16.0730000 + 748 748 1 0.0000000 10.7150000 26.7880000 21.4310000 + 749 749 1 0.0000000 10.7150000 26.7880000 26.7880000 + 750 750 1 0.0000000 10.7150000 26.7880000 32.1460000 + 751 751 1 0.0000000 10.7150000 32.1460000 5.3580000 + 752 752 1 0.0000000 10.7150000 32.1460000 10.7150000 + 753 753 1 0.0000000 10.7150000 32.1460000 16.0730000 + 754 754 1 0.0000000 10.7150000 32.1460000 21.4310000 + 755 755 1 0.0000000 10.7150000 32.1460000 26.7880000 + 756 756 1 0.0000000 10.7150000 32.1460000 32.1460000 + 757 757 1 0.0000000 16.0730000 5.3580000 5.3580000 + 758 758 1 0.0000000 16.0730000 5.3580000 10.7150000 + 759 759 1 0.0000000 16.0730000 5.3580000 16.0730000 + 760 760 1 0.0000000 16.0730000 5.3580000 21.4310000 + 761 761 1 0.0000000 16.0730000 5.3580000 26.7880000 + 762 762 1 0.0000000 16.0730000 5.3580000 32.1460000 + 763 763 1 0.0000000 16.0730000 10.7150000 5.3580000 + 764 764 1 0.0000000 16.0730000 10.7150000 10.7150000 + 765 765 1 0.0000000 16.0730000 10.7150000 16.0730000 + 766 766 1 0.0000000 16.0730000 10.7150000 21.4310000 + 767 767 1 0.0000000 16.0730000 10.7150000 26.7880000 + 768 768 1 0.0000000 16.0730000 10.7150000 32.1460000 + 769 769 1 0.0000000 16.0730000 16.0730000 5.3580000 + 770 770 1 0.0000000 16.0730000 16.0730000 10.7150000 + 771 771 1 0.0000000 16.0730000 16.0730000 16.0730000 + 772 772 1 0.0000000 16.0730000 16.0730000 21.4310000 + 773 773 1 0.0000000 16.0730000 16.0730000 26.7880000 + 774 774 1 0.0000000 16.0730000 16.0730000 32.1460000 + 775 775 1 0.0000000 16.0730000 21.4310000 5.3580000 + 776 776 1 0.0000000 16.0730000 21.4310000 10.7150000 + 777 777 1 0.0000000 16.0730000 21.4310000 16.0730000 + 778 778 1 0.0000000 16.0730000 21.4310000 21.4310000 + 779 779 1 0.0000000 16.0730000 21.4310000 26.7880000 + 780 780 1 0.0000000 16.0730000 21.4310000 32.1460000 + 781 781 1 0.0000000 16.0730000 26.7880000 5.3580000 + 782 782 1 0.0000000 16.0730000 26.7880000 10.7150000 + 783 783 1 0.0000000 16.0730000 26.7880000 16.0730000 + 784 784 1 0.0000000 16.0730000 26.7880000 21.4310000 + 785 785 1 0.0000000 16.0730000 26.7880000 26.7880000 + 786 786 1 0.0000000 16.0730000 26.7880000 32.1460000 + 787 787 1 0.0000000 16.0730000 32.1460000 5.3580000 + 788 788 1 0.0000000 16.0730000 32.1460000 10.7150000 + 789 789 1 0.0000000 16.0730000 32.1460000 16.0730000 + 790 790 1 0.0000000 16.0730000 32.1460000 21.4310000 + 791 791 1 0.0000000 16.0730000 32.1460000 26.7880000 + 792 792 1 0.0000000 16.0730000 32.1460000 32.1460000 + 793 793 1 0.0000000 21.4310000 5.3580000 5.3580000 + 794 794 1 0.0000000 21.4310000 5.3580000 10.7150000 + 795 795 1 0.0000000 21.4310000 5.3580000 16.0730000 + 796 796 1 0.0000000 21.4310000 5.3580000 21.4310000 + 797 797 1 0.0000000 21.4310000 5.3580000 26.7880000 + 798 798 1 0.0000000 21.4310000 5.3580000 32.1460000 + 799 799 1 0.0000000 21.4310000 10.7150000 5.3580000 + 800 800 1 0.0000000 21.4310000 10.7150000 10.7150000 + 801 801 1 0.0000000 21.4310000 10.7150000 16.0730000 + 802 802 1 0.0000000 21.4310000 10.7150000 21.4310000 + 803 803 1 0.0000000 21.4310000 10.7150000 26.7880000 + 804 804 1 0.0000000 21.4310000 10.7150000 32.1460000 + 805 805 1 0.0000000 21.4310000 16.0730000 5.3580000 + 806 806 1 0.0000000 21.4310000 16.0730000 10.7150000 + 807 807 1 0.0000000 21.4310000 16.0730000 16.0730000 + 808 808 1 0.0000000 21.4310000 16.0730000 21.4310000 + 809 809 1 0.0000000 21.4310000 16.0730000 26.7880000 + 810 810 1 0.0000000 21.4310000 16.0730000 32.1460000 + 811 811 1 0.0000000 21.4310000 21.4310000 5.3580000 + 812 812 1 0.0000000 21.4310000 21.4310000 10.7150000 + 813 813 1 0.0000000 21.4310000 21.4310000 16.0730000 + 814 814 1 0.0000000 21.4310000 21.4310000 21.4310000 + 815 815 1 0.0000000 21.4310000 21.4310000 26.7880000 + 816 816 1 0.0000000 21.4310000 21.4310000 32.1460000 + 817 817 1 0.0000000 21.4310000 26.7880000 5.3580000 + 818 818 1 0.0000000 21.4310000 26.7880000 10.7150000 + 819 819 1 0.0000000 21.4310000 26.7880000 16.0730000 + 820 820 1 0.0000000 21.4310000 26.7880000 21.4310000 + 821 821 1 0.0000000 21.4310000 26.7880000 26.7880000 + 822 822 1 0.0000000 21.4310000 26.7880000 32.1460000 + 823 823 1 0.0000000 21.4310000 32.1460000 5.3580000 + 824 824 1 0.0000000 21.4310000 32.1460000 10.7150000 + 825 825 1 0.0000000 21.4310000 32.1460000 16.0730000 + 826 826 1 0.0000000 21.4310000 32.1460000 21.4310000 + 827 827 1 0.0000000 21.4310000 32.1460000 26.7880000 + 828 828 1 0.0000000 21.4310000 32.1460000 32.1460000 + 829 829 1 0.0000000 26.7880000 5.3580000 5.3580000 + 830 830 1 0.0000000 26.7880000 5.3580000 10.7150000 + 831 831 1 0.0000000 26.7880000 5.3580000 16.0730000 + 832 832 1 0.0000000 26.7880000 5.3580000 21.4310000 + 833 833 1 0.0000000 26.7880000 5.3580000 26.7880000 + 834 834 1 0.0000000 26.7880000 5.3580000 32.1460000 + 835 835 1 0.0000000 26.7880000 10.7150000 5.3580000 + 836 836 1 0.0000000 26.7880000 10.7150000 10.7150000 + 837 837 1 0.0000000 26.7880000 10.7150000 16.0730000 + 838 838 1 0.0000000 26.7880000 10.7150000 21.4310000 + 839 839 1 0.0000000 26.7880000 10.7150000 26.7880000 + 840 840 1 0.0000000 26.7880000 10.7150000 32.1460000 + 841 841 1 0.0000000 26.7880000 16.0730000 5.3580000 + 842 842 1 0.0000000 26.7880000 16.0730000 10.7150000 + 843 843 1 0.0000000 26.7880000 16.0730000 16.0730000 + 844 844 1 0.0000000 26.7880000 16.0730000 21.4310000 + 845 845 1 0.0000000 26.7880000 16.0730000 26.7880000 + 846 846 1 0.0000000 26.7880000 16.0730000 32.1460000 + 847 847 1 0.0000000 26.7880000 21.4310000 5.3580000 + 848 848 1 0.0000000 26.7880000 21.4310000 10.7150000 + 849 849 1 0.0000000 26.7880000 21.4310000 16.0730000 + 850 850 1 0.0000000 26.7880000 21.4310000 21.4310000 + 851 851 1 0.0000000 26.7880000 21.4310000 26.7880000 + 852 852 1 0.0000000 26.7880000 21.4310000 32.1460000 + 853 853 1 0.0000000 26.7880000 26.7880000 5.3580000 + 854 854 1 0.0000000 26.7880000 26.7880000 10.7150000 + 855 855 1 0.0000000 26.7880000 26.7880000 16.0730000 + 856 856 1 0.0000000 26.7880000 26.7880000 21.4310000 + 857 857 1 0.0000000 26.7880000 26.7880000 26.7880000 + 858 858 1 0.0000000 26.7880000 26.7880000 32.1460000 + 859 859 1 0.0000000 26.7880000 32.1460000 5.3580000 + 860 860 1 0.0000000 26.7880000 32.1460000 10.7150000 + 861 861 1 0.0000000 26.7880000 32.1460000 16.0730000 + 862 862 1 0.0000000 26.7880000 32.1460000 21.4310000 + 863 863 1 0.0000000 26.7880000 32.1460000 26.7880000 + 864 864 1 0.0000000 26.7880000 32.1460000 32.1460000 + diff --git a/examples/gjf/ff-argon.lmp b/examples/gjf/ff-argon.lmp new file mode 100644 index 0000000000..b6f7bc931a --- /dev/null +++ b/examples/gjf/ff-argon.lmp @@ -0,0 +1,20 @@ +############################# +#Atoms types - mass - charge# +############################# +#@ 1 atom types #!THIS LINE IS NECESSARY DON'T SPEND HOURS FINDING THAT OUT!# + +variable Ar equal 1 + +############# +#Atom Masses# +############# + +mass ${Ar} 39.903 + +########################### +#Pair Potentials - Tersoff# +########################### + +pair_style lj/cubic +pair_coeff * * 0.0102701 3.42 + diff --git a/examples/gjf/in.argon b/examples/gjf/in.argon new file mode 100644 index 0000000000..271882c665 --- /dev/null +++ b/examples/gjf/in.argon @@ -0,0 +1,162 @@ +###############################mm +# Atom style - charge/vdw/bonded# +################################# +atom_style full + +############################################## +#Units Metal : eV - ps - angstrom - bar# +# Real : kcal/mol - fs - angstrom - atm# +############################################## +units metal + +############ +#Run number# +############ +variable run_no equal 0 # is it a restart? +variable res_no equal ${run_no}-1 # restart file number + +####################################### +#Random Seeds and Domain Decomposition# +####################################### +variable iseed0 equal 2357 +variable iseed1 equal 26488 +variable iseed2 equal 10669 +processors * * * + +########### +#Data File# +########### +variable inpfile string argon.lmp +variable resfile string final_restart.${res_no} +variable ff_file string ff-argon.lmp + +########## +#Run Type# +########## +variable minimise equal 0 #Energy Minimization +variable md equal 1 #Plain MD + +############################### +#Molecular Dynamics Parameters# +############################### +variable run_no equal 0 # is it a restart? + +variable ens equal 9 # ensemble (0=nve, 1=nvt, 2=npt, 3=ber, 4=lang, 5=stoc, 6=vres, 7=stoch, 8=gjf) +variable ts equal 0.120 # simulation timestep (time units) +variable nequil equal 0 # number of equilibration steps +variable nsteps equal 200000 # number of MD steps +#variable nsteps equal 20 # number of MD steps + +variable temp_s equal 10 # starting temperature +variable temp_f equal 10 # final simulation temperature +variable trel equal 1 # thermostat relaxation time +variable tscale equal 1 # thermostat relaxation freq - vel rescaling only +variable deltat equal 1 # maximum temperature change - vel rescaling only + +variable npttype string iso # type of NPT (iso, aniso, tri, z...) +variable pres equal 1.01325 # pressure (NPT runs only) +variable prel equal 1.0 # barostat relaxation time + +neighbor 1 bin + +################### +#Output Parameters# +################### +variable ntraj equal 1000 # trajectory output frequency - all system +variable ntraj_s equal -100 # trajectory output frequency - solute only +variable nthermo equal 200 # thermodynamic data output frequency + +################################ +#Energy Minimization Parameters# +################################ +variable mtraj equal 1 # trajectory output frequency - all system +variable etol equal 1e-5 # % change in energy +variable ftol equal 1e-5 # max force threshold (force units) +variable maxiter equal 10000 # max # of iterations + +######################## +#3D Periodic Simulation# +######################## +boundary p p p + +############################# +#Reading the input structure# +############################# +if "${run_no} == 0" then "read_data ${inpfile}" else "read_restart ${resfile}" + +############# +#Force Field# +############# +include ${ff_file} + +###################### +#Thermodynamic Output# +###################### +variable str_basic string 'step time pe temp press' + +#MD ensemble (0=nve, 1=nvt, 2=npt, 3=ber, 4=lang, 5=stoc, 6=vres) +variable str_ens string ' ' +if "${ens} == 0" then "variable str_ens string 'etotal'" +if "${ens} == 2" then "variable str_ens string 'vol pxx pyy pzz cella cellb cellc cellakpha cellbeta cellgamma'" + +#Variable for a gulp friend output +if "${ens} >= 0" then "thermo_style custom time temp pe etotal press vol cpu" & + "thermo ${nthermo}" & + "thermo_modify flush yes" + +##################### +#Energy Minimization# +##################### +if "${minimise} <= 0 || ${run_no} > 0" then "jump SELF end_minimise" + print "Doing CG minimisation" + dump mdcd all dcd ${mtraj} min.dcd + dump_modify mdcd unwrap yes + min_style cg + min_modify line quadratic + minimize ${etol} ${ftol} ${maxiter} ${maxiter} + reset_timestep 0 + undump mdcd +label end_minimise + +################ +#Timestep in ps# +################ +timestep ${ts} + +############## +#Restart file# +############## +restart 100000 restart.1 restart.2 + +################### +#Trajectory output# +################### +#dump xyz all atom 1000 silicon.lammpstrj + +if "${ntraj} > 0" then & + "dump 1 all dcd ${ntraj} trajectory.${run_no}.dcd" & + "dump_modify 1 unwrap yes" + +fix mom all momentum 1 linear 1 1 1 + +############################################################### +#Ensembles (0=nve,1=nvt, 2=npt, 3=ber, 4=lang, 5=stoc, 6=vres)# +############################################################### +if "${md} > 0" then 'print "Setting up the ensembles"' & + 'if "${run_no} == 0" then "velocity all create ${temp_s} ${iseed0} mom yes dist gaussian"' & + 'if "${ens} == 0" then "fix nve all nve"' & + 'if "${ens} == 1" then "fix nvt all nvt temp ${temp_s} ${temp_f} ${trel} tchain 5"' & + 'if "${ens} == 2" then "fix npt all npt temp ${temp_s} ${temp_f} ${trel} ${npttype} ${pres} ${pres} ${prel} tchain 5 pchain 5 mtk yes"' & + 'if "${ens} == 3" then "fix nve all nve" "fix ber all temp/berendsen ${temp_s} ${temp_f} ${trel}"' & + 'if "${ens} == 4" then "fix nve all nve" "fix lang all langevin ${temp_s} ${temp_f} ${trel} ${iseed1} tally yes zero yes"' & + 'if "${ens} == 5" then "fix nve all nve" "fix stoch all temp/csvr ${temp_s} ${temp_f} ${trel} ${iseed1}"' & + 'if "${ens} == 6" then "fix nve all nve" "fix stoch all temp/csld ${temp_s} ${temp_f} ${trel} ${iseed1}"' & + 'if "${ens} == 7" then "fix nve all nve" "fix vres all temp/rescale ${tscale} ${temp_s} ${temp_f} ${tmin} ${tmax}"' & + 'if "${ens} == 8" then "fix nve all nve" "fix lang all langevin ${temp_s} ${temp_f} ${trel} ${iseed1} gjf yes"' & + 'if "${ens} == 9" then "fix nve all nve" "fix lang all langevin ${temp_s} ${temp_f} ${trel} ${iseed1} gjf yes halfstep yes"' + +if "${md} > 0" then "print 'Doing Molecular dynamics'" & + "run ${nsteps}" & + "write_restart final_restart.${run_no}" + + diff --git a/examples/gjf/out.argon b/examples/gjf/out.argon new file mode 100644 index 0000000000..8dda569157 --- /dev/null +++ b/examples/gjf/out.argon @@ -0,0 +1,249 @@ +LAMMPS (1 Feb 2019) +OMP_NUM_THREADS environment is not set. Defaulting to 1 thread. (src/comm.cpp:87) + using 1 OpenMP thread(s) per MPI task +Reading data file ... + orthogonal box = (0 0 0) to (32.146 32.146 32.146) + 1 by 2 by 2 MPI processor grid + reading atoms ... + 864 atoms +Finding 1-2 1-3 1-4 neighbors ... + special bond factors lj: 0 0 0 + special bond factors coul: 0 0 0 + 0 = max # of 1-2 neighbors + 0 = max # of 1-3 neighbors + 0 = max # of 1-4 neighbors + 1 = max # of special neighbors +Setting up the ensembles +WARNING: Careful, tally is untested (src/fix_langevin.cpp:145) +WARNING: Careful, tally is untested (src/fix_langevin.cpp:145) +WARNING: Careful, tally is untested (src/fix_langevin.cpp:145) +WARNING: Careful, tally is untested (src/fix_langevin.cpp:145) +Doing Molecular dynamics +Neighbor list info ... + update every 1 steps, delay 10 steps, check yes + max neighbors/atom: 2000, page size: 100000 + master list distance cutoff = 6.94072 + ghost atom cutoff = 6.94072 + binsize = 3.47036, bins = 10 10 10 + 1 neighbor lists, perpetual/occasional/extra = 1 0 0 + (1) pair lj/cubic, perpetual + attributes: half, newton on + pair build: half/bin/newton + stencil: half/bin/3d/newton + bin: standard +Setting up Verlet run ... + Unit style : metal + Current step : 0 + Time step : 0.12 +Per MPI rank memory allocation (min/avg/max) = 6.847 | 6.847 | 6.847 Mbytes +Time Temp PotEng TotEng Press Volume CPU + 0 10 -56.207655 -55.09214 33.340921 33218.561 0 + 24 10.156356 -55.092888 -53.959932 339.40964 33218.561 0.082175482 + 48 9.6121006 -55.07262 -54.000376 344.56765 33218.561 0.19529325 + 72 9.8187467 -55.16687 -54.071574 318.85979 33218.561 0.29643488 + 96 9.5421385 -55.151229 -54.086789 322.8842 33218.561 0.38801357 + 120 10.295035 -55.12919 -53.980763 332.00171 33218.561 0.47607262 + 144 10.331608 -55.09907 -53.946563 339.28896 33218.561 0.57389224 + 168 10.154698 -55.058246 -53.925475 349.03253 33218.561 0.65481471 + 192 9.858198 -55.127583 -54.027886 330.09298 33218.561 0.74437734 + 216 9.6658918 -55.10812 -54.029875 334.28383 33218.561 0.8278495 + 240 9.6801591 -55.102386 -54.02255 336.27242 33218.561 0.91167379 + 264 10.685658 -55.046238 -53.854237 355.0448 33218.561 1.0023789 + 288 10.387727 -55.08427 -53.925504 343.87247 33218.561 1.0960371 + 312 10.231132 -55.120428 -53.97913 333.22463 33218.561 1.2382998 + 336 10.20896 -55.075142 -53.936317 344.88438 33218.561 1.3420489 + 360 9.7876538 -55.165008 -54.07318 319.14962 33218.561 1.42782 + 384 9.9872551 -55.13881 -54.024717 327.82471 33218.561 1.5417666 + 408 9.5362734 -55.063733 -53.999947 346.50545 33218.561 1.6328366 + 432 10.262638 -55.126608 -53.981796 332.16342 33218.561 1.7242996 + 456 9.9228239 -55.122119 -54.015214 332.26261 33218.561 1.8124888 + 480 9.7026324 -55.17057 -54.088227 317.84818 33218.561 1.900233 + 504 10.028762 -55.082465 -53.963741 343.04257 33218.561 1.989605 + 528 9.8227851 -55.121222 -54.025476 332.42857 33218.561 2.0708802 + 552 10.208672 -55.100242 -53.961449 338.68109 33218.561 2.1527217 + 576 10.180849 -55.124065 -53.988376 331.29516 33218.561 2.238126 + 600 9.6467252 -55.119533 -54.043427 332.43109 33218.561 2.323443 + 624 10.041885 -55.173802 -54.053614 318.48579 33218.561 2.4046151 + 648 10.151597 -55.111725 -53.979299 334.66227 33218.561 2.4902161 + 672 9.7719111 -55.060111 -53.970039 348.55249 33218.561 2.5800372 + 696 10.476688 -55.088109 -53.919419 342.94922 33218.561 2.6731395 + 720 10.517805 -55.113604 -53.940327 335.47342 33218.561 2.760651 + 744 10.006466 -55.045085 -53.928848 353.53813 33218.561 2.8537894 + 768 10.201492 -55.081598 -53.943606 343.3206 33218.561 2.9404115 + 792 10.117738 -55.077806 -53.949157 345.31093 33218.561 3.030765 + 816 10.362288 -55.11635 -53.960421 333.9045 33218.561 3.1177356 + 840 10.204164 -55.097619 -53.959329 338.82717 33218.561 3.2091886 + 864 10.147722 -55.101372 -53.969378 338.19682 33218.561 3.3003742 + 888 9.9265037 -55.111394 -54.004077 334.08116 33218.561 3.395341 + 912 10.206403 -55.132181 -53.993642 328.89904 33218.561 3.4882881 + 936 10.28639 -55.093317 -53.945855 340.61244 33218.561 3.5764735 + 960 9.8028822 -55.078802 -53.985276 343.5904 33218.561 3.7056267 + 984 10.492755 -55.121321 -53.950839 334.62697 33218.561 3.8055611 + 1008 10.621569 -55.088588 -53.903736 343.33166 33218.561 3.9144807 + 1032 10.006729 -55.113459 -53.997193 334.43025 33218.561 4.0189888 + 1056 10.099853 -55.068035 -53.941381 347.42158 33218.561 4.1391664 + 1080 10.254232 -55.066685 -53.92281 347.15777 33218.561 4.2443953 + 1104 9.9495142 -55.13686 -54.026977 327.63107 33218.561 4.3368342 + 1128 10.377108 -55.08846 -53.930878 344.13083 33218.561 4.4287748 + 1152 10.036981 -55.114643 -53.995003 334.88053 33218.561 4.526868 + 1176 10.144779 -55.097125 -53.965459 339.698 33218.561 4.6614049 + 1200 10.075844 -55.14695 -54.022974 326.05911 33218.561 4.799835 + 1224 10.183695 -55.121716 -53.98571 332.75772 33218.561 4.8908897 + 1248 10.581369 -55.027954 -53.847587 359.06251 33218.561 4.9839788 + 1272 10.158269 -55.105173 -53.972003 337.52964 33218.561 5.0918646 + 1296 9.8776072 -55.064085 -53.962223 347.15648 33218.561 5.2291209 + 1320 10.38161 -55.118366 -53.960282 335.17767 33218.561 5.3570446 + 1344 9.9528146 -55.141937 -54.031685 326.27117 33218.561 5.4584705 + 1368 9.8024326 -55.117808 -54.024332 332.99835 33218.561 5.5557818 + 1392 10.35447 -55.110235 -53.955179 336.80412 33218.561 5.6467392 + 1416 10.199061 -55.105641 -53.96792 337.36785 33218.561 5.7476527 + 1440 9.6868779 -55.087316 -54.00673 340.9166 33218.561 5.8432207 + 1464 10.093238 -55.049436 -53.92352 352.27563 33218.561 5.9471521 + 1488 9.7578808 -55.123935 -54.035429 329.93926 33218.561 6.0495014 + 1512 10.099979 -55.205426 -54.078758 309.26166 33218.561 6.1612976 + 1536 10.172944 -55.087106 -53.952299 342.93395 33218.561 6.2506202 + 1560 10.51771 -55.107635 -53.934369 340.1967 33218.561 6.3379856 + 1584 10.044994 -55.101362 -53.980828 339.03163 33218.561 6.4362567 + 1608 9.624758 -55.146246 -54.07259 324.32486 33218.561 6.5385845 + 1632 9.9135215 -55.097278 -53.99141 338.69162 33218.561 6.6452786 + 1656 9.863681 -55.070523 -53.970214 345.84608 33218.561 6.7518212 + 1680 10.138513 -55.127065 -53.996099 330.40757 33218.561 6.8775188 + 1704 10.382237 -55.070572 -53.912417 347.074 33218.561 7.0126448 + 1728 10.72487 -55.081147 -53.884771 345.83623 33218.561 7.1384216 + 1752 9.829431 -55.131041 -54.034553 328.57652 33218.561 7.2616419 + 1776 9.9135662 -55.100556 -53.994682 336.52238 33218.561 7.4193201 + 1800 10.41873 -55.097116 -53.934891 340.24798 33218.561 7.5570544 + 1824 10.151782 -55.03231 -53.899864 357.3654 33218.561 7.6872905 + 1848 10.42307 -55.043808 -53.881099 355.71677 33218.561 7.7933885 + 1872 10.276862 -55.085016 -53.938616 344.46273 33218.561 7.8887472 + 1896 9.7681373 -55.146507 -54.056857 324.84323 33218.561 7.9977923 + 1920 9.6624824 -55.103214 -54.025349 336.06397 33218.561 8.090235 + 1944 10.153504 -55.049175 -53.916536 352.36339 33218.561 8.1923703 + 1968 10.191954 -55.098741 -53.961813 338.8667 33218.561 8.3320906 + 1992 9.92167 -55.117079 -54.010302 332.96497 33218.561 8.4774437 + 2016 9.5737281 -55.091141 -54.023178 339.41837 33218.561 8.6149527 + 2040 10.600908 -55.092717 -53.91017 342.71852 33218.561 8.7639523 + 2064 9.9214513 -55.099904 -53.993151 337.46799 33218.561 8.898087 + 2088 9.9256258 -55.082224 -53.975005 342.85042 33218.561 9.0130784 + 2112 10.345379 -55.112923 -53.95888 335.81471 33218.561 9.1422766 + 2136 9.8876649 -55.079254 -53.97627 343.05764 33218.561 9.2885707 + 2160 10.04492 -55.074876 -53.95435 344.82419 33218.561 9.3876103 + 2184 10.028705 -55.063961 -53.945244 347.70549 33218.561 9.500967 + 2208 10.412572 -55.136316 -53.974778 329.8188 33218.561 9.5900362 + 2232 10.404205 -55.09913 -53.938525 339.77542 33218.561 9.7048353 + 2256 9.5694135 -55.139021 -54.071538 326.37473 33218.561 9.8045958 + 2280 10.244745 -55.134529 -53.991713 329.19392 33218.561 9.8968908 + 2304 9.9129922 -55.116192 -54.010382 333.14326 33218.561 9.9818651 + 2328 10.167027 -55.08241 -53.948263 343.08135 33218.561 10.068683 + 2352 10.262045 -55.144327 -53.999581 327.40876 33218.561 10.155937 + 2376 10.520934 -55.073147 -53.899521 347.6998 33218.561 10.246316 + 2400 9.9628692 -55.122001 -54.010628 331.25369 33218.561 10.336833 + 2424 10.565531 -55.157113 -53.978512 325.14897 33218.561 10.452039 + 2448 10.03709 -55.096409 -53.976756 338.29607 33218.561 10.537936 + 2472 9.384311 -55.141821 -54.094987 324.23247 33218.561 10.628689 + 2496 9.8019362 -55.105685 -54.012264 335.97239 33218.561 10.717287 + 2520 10.31114 -55.078831 -53.928608 345.42395 33218.561 10.818756 + 2544 10.407237 -55.148382 -53.987439 325.94421 33218.561 10.910801 + 2568 10.257967 -55.041348 -53.897056 355.73261 33218.561 11.004221 + 2592 9.8425807 -55.139428 -54.041474 328.28096 33218.561 11.101295 + 2616 10.140697 -55.100238 -53.969028 338.76319 33218.561 11.192211 + 2640 9.7102818 -55.136288 -54.053091 326.7053 33218.561 11.280277 + 2664 10.120372 -55.128779 -53.999836 330.71707 33218.561 11.369001 + 2688 10.232537 -55.120614 -53.979159 333.35087 33218.561 11.464652 + 2712 10.032526 -55.094761 -53.975618 339.97984 33218.561 11.559387 + 2736 9.8791 -55.121998 -54.01997 332.32556 33218.561 11.649679 + 2760 9.891483 -55.120919 -54.017509 331.32614 33218.561 11.742604 + 2784 10.201053 -55.165525 -54.027582 320.39272 33218.561 11.85274 + 2808 10.238648 -55.096449 -53.954312 340.06316 33218.561 11.939782 + 2832 9.8692851 -55.068632 -53.967699 346.77535 33218.561 12.036655 + 2856 10.179976 -55.128413 -53.992822 331.5662 33218.561 12.123227 + 2880 9.7656315 -55.1468 -54.057429 324.02612 33218.561 12.213117 + 2904 9.7991628 -55.049191 -53.95608 352.45738 33218.561 12.326761 + 2928 10.581767 -55.093293 -53.912881 341.37292 33218.561 12.417633 + 2952 10.546144 -55.07452 -53.898081 347.02025 33218.561 12.52701 + 2976 9.8306008 -55.14762 -54.051002 323.45715 33218.561 12.633522 + 3000 10.033532 -55.076433 -53.957178 345.36812 33218.561 12.72627 + 3024 10.046266 -55.085775 -53.965099 342.47786 33218.561 12.816242 + 3048 10.176777 -55.133013 -53.997778 329.04144 33218.561 12.903175 + 3072 9.9778064 -55.143787 -54.030748 326.75284 33218.561 13.014329 + 3096 10.516223 -55.110144 -53.937043 336.802 33218.561 13.104673 + 3120 9.6561157 -55.138699 -54.061544 325.6652 33218.561 13.207371 + 3144 10.237043 -55.060968 -53.91901 349.44011 33218.561 13.303442 + 3168 9.9704264 -55.123073 -54.010857 332.19725 33218.561 13.391877 + 3192 10.493307 -55.144402 -53.973858 327.15485 33218.561 13.482857 + 3216 10.022171 -55.141782 -54.023794 326.08249 33218.561 13.574484 + 3240 9.6957248 -55.137865 -54.056292 326.04858 33218.561 13.671408 + 3264 9.9685299 -55.124301 -54.012297 331.9015 33218.561 13.760186 + 3288 10.413707 -55.153604 -53.99194 324.32939 33218.561 13.877604 + 3312 10.022953 -55.103422 -53.985346 337.52066 33218.561 13.977562 + 3336 10.044478 -55.110297 -53.98982 334.48379 33218.561 14.065563 + 3360 9.8593734 -55.130623 -54.030795 327.71748 33218.561 14.15952 + 3384 9.9269422 -55.107979 -54.000613 335.18173 33218.561 14.258064 + 3408 10.288049 -55.092276 -53.944629 340.71484 33218.561 14.36211 + 3432 9.9702156 -55.08732 -53.975128 341.72171 33218.561 14.452123 + 3456 10.246178 -55.091669 -53.948692 341.62844 33218.561 14.555775 + 3480 10.559292 -55.086917 -53.909012 343.70626 33218.561 14.645718 + 3504 10.652207 -55.050897 -53.862628 354.46979 33218.561 14.797422 + 3528 9.9835266 -55.0557 -53.942023 350.74747 33218.561 14.895716 + 3552 10.240934 -55.123217 -53.980825 332.26434 33218.561 15.023796 + 3576 10.406519 -55.093536 -53.932674 341.54029 33218.561 15.203252 + 3600 10.406733 -55.095168 -53.934282 341.22192 33218.561 15.303986 + 3624 9.9877484 -55.154231 -54.040083 323.55633 33218.561 15.398883 + 3648 10.391829 -55.110208 -53.950984 337.09219 33218.561 15.49042 + 3672 10.368995 -55.069591 -53.912914 346.82649 33218.561 15.582259 + 3696 10.362939 -55.109012 -53.953011 337.32216 33218.561 15.679316 + 3720 10.465254 -55.136214 -53.968799 331.22288 33218.561 15.773303 + 3744 9.8238226 -55.10114 -54.005278 338.12616 33218.561 15.86905 + 3768 10.205504 -55.101263 -53.962824 339.04196 33218.561 15.960072 + 3792 9.9589987 -55.118883 -54.007942 332.84318 33218.561 16.047055 + 3816 10.253382 -55.117513 -53.973732 334.42101 33218.561 16.148412 + 3840 10.262393 -55.069549 -53.924764 349.084 33218.561 16.235391 + 3864 9.7367167 -55.078288 -53.992142 342.48207 33218.561 16.329112 + 3888 10.171202 -55.134701 -54.000088 329.5847 33218.561 16.415353 + 3912 10.01925 -55.145139 -54.027477 326.65074 33218.561 16.526334 + 3936 10.053638 -55.038151 -53.916653 355.74893 33218.561 16.618524 + 3960 10.044055 -55.058382 -53.937953 349.01834 33218.561 16.712577 + 3984 10.382422 -55.099216 -53.941041 339.28099 33218.561 16.79941 + 4008 9.97927 -55.09284 -53.979637 339.07225 33218.561 16.904198 + 4032 9.6782319 -55.126143 -54.046522 329.0201 33218.561 16.991454 + 4056 9.6593809 -55.123677 -54.046159 329.89833 33218.561 17.097172 + 4080 10.442896 -55.141149 -53.976229 327.9899 33218.561 17.189364 + 4104 9.9571109 -55.08588 -53.975149 341.3746 33218.561 17.294147 + 4128 10.44943 -55.087946 -53.922296 343.09435 33218.561 17.387357 + 4152 10.040581 -55.171939 -54.051897 317.85348 33218.561 17.500905 + 4176 10.089442 -55.128713 -54.00322 330.29121 33218.561 17.588891 + 4200 10.316156 -55.123219 -53.972436 333.59382 33218.561 17.679254 + 4224 10.177245 -55.095671 -53.960384 339.34498 33218.561 17.770569 + 4248 9.7129183 -55.135335 -54.051844 328.25125 33218.561 17.857728 + 4272 10.231838 -55.099554 -53.958177 339.64015 33218.561 17.944226 + 4296 9.9737677 -55.117885 -54.005297 333.07248 33218.561 18.034105 + 4320 10.004955 -55.116155 -54.000088 333.52271 33218.561 18.129644 + 4344 9.5938901 -55.133824 -54.063612 327.84171 33218.561 18.215476 + 4368 9.8954562 -55.131603 -54.02775 329.0813 33218.561 18.306539 + 4392 10.439732 -55.100379 -53.935812 339.81679 33218.561 18.395651 + 4416 9.934513 -55.08449 -53.97628 341.74441 33218.561 18.484506 + 4440 10.025998 -55.136771 -54.018356 327.73718 33218.561 18.593946 + 4464 9.9304451 -55.101817 -53.994061 338.1801 33218.561 18.684011 + 4488 10.344371 -55.085856 -53.931926 342.91721 33218.561 18.782399 + 4512 10.033193 -55.091778 -53.972561 339.85728 33218.561 18.879666 + 4536 9.2361614 -55.169375 -54.139067 316.67597 33218.561 18.983667 + 4560 9.5786289 -55.179976 -54.111465 314.76415 33218.561 19.079009 + 4584 10.071651 -55.107218 -53.98371 336.10364 33218.561 19.163975 + 4608 9.9873098 -55.109348 -53.995249 336.03665 33218.561 19.25635 + 4632 10.143888 -55.119423 -53.987857 333.74978 33218.561 19.346658 + 4656 9.7506264 -55.114772 -54.027075 332.98271 33218.561 19.435425 + 4680 9.9616769 -55.096054 -53.984814 339.20499 33218.561 19.55562 + 4704 10.271313 -55.074522 -53.928742 345.87397 33218.561 19.642652 + 4728 9.9172336 -55.098805 -53.992523 338.06318 33218.561 19.734557 + 4752 9.9556222 -55.12128 -54.010716 332.66408 33218.561 19.83859 + 4776 10.197593 -55.095293 -53.957736 339.50067 33218.561 19.947471 + 4800 10.145085 -55.108467 -53.976768 336.05115 33218.561 20.044183 + 4824 10.205523 -55.147376 -54.008934 325.56559 33218.561 20.144393 + 4848 9.8900281 -55.121598 -54.01835 331.17401 33218.561 20.243197 + 4872 10.03655 -55.100936 -53.981343 337.6777 33218.561 20.336043 + 4896 9.8120635 -55.087507 -53.992957 341.42438 33218.561 20.425498 + 4920 10.615354 -55.093335 -53.909176 342.30776 33218.561 20.519318 + 4944 10.374366 -55.06455 -53.907274 351.10607 33218.561 20.612312 + 4968 10.677474 -55.147807 -53.956718 327.85703 33218.561 20.719371 + 4992 10.558882 -55.145253 -53.967393 327.427 33218.561 20.818726 + 5016 9.4097946 -55.150835 -54.101158 321.62641 33218.561 20.914472 diff --git a/examples/gjf/trajectory.0.dcd b/examples/gjf/trajectory.0.dcd new file mode 100644 index 0000000000000000000000000000000000000000..47927e9909cfcfc86ceb2568ba1660efed5834f2 GIT binary patch literal 439092 zcmeEubx>P-)a?m%rApmsu_RbsfbNyL3nZbgw72dqgu2rf66!*Wph-<^4HzCT{SnRe#fz`5b@<0pHsz1G?Z5d@)KufFZ2{QB$P>mq{S zx$A#^`5*ohne`=5@*nR0#~ao8RtR5v`Eue*J$20V>0uM=51&)NJ9_l!9nAOsEC2d- z=z+f7g6p@N8a8Zt*vR_+t?GB3F@BD`u^)dmY(-ooB;CH&xri%ET zuA4oq_?@ow=`!BWzt1%zO2F@Q-Rz;__4<9T8bx*Zovt>IO!%FyvFSGaPS@{rwtkJ} zcRE|Y#_~IztzTpLozB*;vHVVF>(^L*r?d5IEWZyj{Cgz76E^%cmfr~*{u;~ggbja< z<#)n{zsB-AVZ&cz`Bj7cy8bPX{aZfyx48aq@%7*0+`q+}KjZlucm0{4zwz*Y|NZly z^9uhKzyB?c{#!izx406a6%_y3^>2CX&v^cxuRrtiH;?h3?VVrue!uzo&pD1i`Rng` z`AwmAq{^8C3;fH?J0RM1%|8Q9Ua5aDK z|IJzbnTJ2~@aMez&A0!Vhd=Z1|1Tc?%}M{mz5bJf|KY0t-2XE_|L_O@=mr1q;(zY{ ztq=T}hd=Z1CrXpm(Y^Am!1@=C8=JhlmhR%a#ke$om+@u8W5&4T8^#Y` zoijr9a{~siOAZXaC=2*xhzXqXBRk#p$|e0-?qXx>Dl?56{Er64F4+~BwoYq&xMO{w z-?^fJx+UR(`$BvIr>{>Ae7df6z_=CF(^p>$HokaVGH}(bqv>1RPa2~ZA5ZTX*|<%& zw+Y6ge!Bvve|i-7zar8sq2G8`u^Xug3{n85=5-DollSAt##j;B>3>qcJ`&LpsnJ>fDZBm>Llp!UVy_6lL_&8jO zOD*M)?2;kOKLVMEz@2~yTzjR##UdJvpRB=kYmM&@~kE2TVQBvfvnJiz78t}b+cl!s};M{RtS@=2>)(@ z`Mw2Dy72oV`E`i}m#$mk+0KH`v#nU9v|_8t0!MQzKJ3ZH#urvZTP<)sW5v#4R$PB( zL9tH0)X*-cjVpZU&~Z;{V09(0=1s`?jwhA)+K_%u^`^v{Ze$$jP8~+esq;Z8#gF%< zBQCy_(a?*2UTaQaUd^fTTwf|$LQdU}HK6IwdRlm}Z{6D+V z?j16!e_Bpube_~_mIpQN=tdJ}xYGP8a+)#Pk8-mMsdGC4g{=#zl#_t0>xDF`xddwucTlxd2PM~+VEy?} z+`rrpYnS!I&^jSVa8g0nUX8o0RTwc*3F~t;BBrX)y@nD!SB2nuloB=Ph9ES~; zimy>YdQ^q4$3l@cQw>+O3Om;X<3)f9p@k}hPg0@xLN#8VP@;=G1T{;kvAKj2i&m>) z<>&7AP~kxN5EQMa!u*#iOzN-2fnz!}?HL2@LmfsO*J5rj9hxU;vFU&gmlZlRiq_#% z10Cj;(jl?54(9^3i1XFLRU3_%3R)cY(V_8kEo?P)XfacV_K{jVpQA;sfm$q|sfFLK z=QPn_$zd%@6>2f8l@3z=9iQ&$kbF~z{RKLd=o^EeTrG~4FvGFjgarposI}XSEsxDO z^3#L^uT3ztF`?X66TVh4A^cq?R8vi;KGTf1rOjx2)`VkS&4^l(iD&0BK_ktm`6v@b z@0c*Aml*~Z6NC!)2%)O$;_%cw|Gp+IFPP%7JNt4Ks_` z(QByooK_hoE*3{vq9x-$6u4|c-h>JaxpfNBS2qDg4;8GlI@xV z?t=u3kC31QpPNs$1(eS#q$xoH+-?fE(b+*MLLm)XQb?uS7Sh@1-|R09?ItWaV=MS!OR1U$7}H%1q_&wOZuA(ZO|`4xdkG z(e{BBg%$YcqqTUmUk9(TI?R}%#oj?$M4r~-r(O%y2_0fP#UQL=48D5n;9}I`VJbgY zn}y!dCXDN3hIXeJ>lT`Dkk8!K875pYW}?keGae^o;qnPSLoZDb4w+DIxCxWyn31*A zghp}vvzeJZPbTDEG$H%32@9v05MwgIZ?g&G`MjO3YR1*=CKP-#!DW&e&)S-?rg9d} z$;=!}%xF>Bj8wG=8#N}pt6;;vB{mdpx1o7k8>*DEq1*>EYz4n4mf8g9c}y$v@UIS6lJ zgTBy)obfg^`Iv(x={776%99&9|++B?19+AyQa`IfQd)pEw^ zD}MykKD8#`_4(QXVV(m5;&+ZUmP-f=+&k;@iT97+rN3+RDLt()<;2s0D+A-d8v{2M z>ze+odX$`KXH~Lm3ANN+whG@yZKpt7k+G`m$2J-nVs&5P;DxZgmdoDylt z?L=C1Gm&$iNJXyb>GkY1YHv)Y1G;1yo^GJ^u8EYSHBkBaNfdc1nfhJR(|UOlZ7wcS z&>cP9SeHzZIzmbBYBRsETwdCS|O6pnq=y|IGJ*T4HSG? zibFqSc-}{bB3r%SS4#^03ON?+_r@NH96!IxaBiFo@88H!r7Qalo67OIryR@r%iujm z3Xd6HxLrYppsF(1S9!s8ycA_i%3$>OM&qk8ge>wzpIb7_GDzWCSBk@sggRwA}Aeyhd!F0_~dy`M1#93*1!C_NlyL>zv`IFg_B@-Smb zlOEJvMCw`*9W)|JToSRGzdp*iFp-~On9jJ<*MNm<40yIpM5loU^y1&wzm^D9pam|= zEht&aigPovQ6t!jF}tl;UEhLXdACq!niYYSt;j#cSg@xB1DjY;ow20xwiRWZtVmsK z#hxe&&iY!hILv~h@fJ+DVSyk2zc>8e3qP$GcisXF%frYE^WwfcOH&se^&^^XhTSgR+Uke9` z!4ArD7LdZ;@GbAvDCMU{SQ{1IWQV}1w-VWBwWyk=#T1Jc5sWibjkVY|Fb1t_n9-zx z2}X?>@`6k(Ich@Hsb)0bIB*&^)Gn}LK^+_RF6S7K%V*zHN_ZzD*SY>QQ^)!7rZ>Hf zlv0hF1vFw#0X^IzU~E7k>5~N1>mWgtnd5u~HTI2DLH&*M%;gYt@KR&+869Gd=org$ z9M052J6ns`k~%D(WyaL`CS2WQf-J^_E8-4NoNlQWm%zrPz=+zQD@^DaH#;QAg`{B)JC05=J zL1o5~_8w}8ob&4SkKvr8L%E(h%x3JBR8@yl={ls|HsL*wq46LyigTQw*xif^pG+t{ z!HyanV@t2%I2mNaF2*&Ub8Kkz)Qvi~_oU4AGTNQwLt|$7(&|o4=mq27LG2}&A{S83 zPy}=@{<;oCfSR^f|>8mhKxBwN4J)pX4BE zr457L%4qfyciPykDQ#`slsZ3hBUu?A8g7+fd0k$w0Y#7zEWyC@PIx1A;u=r|d6y8p zAFsr)bTx)IQ(^D{HT*e$uRj}&p3gYvkJqAE865_3{x8>>=V!19yRMo*3KLAvP3Uhl z;REB--4An+=4XTAnhom295lPfzWik(-SRY$=4%Qa_fMk0N_uKh#z5{)9D8?oVLr#= z`PJp9+FFY0XQimnm%Z4>G`PMu97A$7_&QjFJ)<;m_7u@=j~-9Y=ppN>hxomMn&WJR+`D_Y8}comq9xZ#4rHbqcWlt~mXCkl$#k`jgI89{NeOcH&+sHfOr zDWpkGpz^y!GOLm({;m{0O}*gJObSS)xYtXD_=9phB>ubLGbs#+oPxV~Ms;L9zpgEv~y?w+6+-$PLJ_$ep` z$R&z1vjxTe6hX18auPMXmq^ZgQz&q3DoyKUpo=f`w7I+tBWKAmH(CZ8&sF?68Agp} zKEx{mpEER=+L-f1)d)oY2*=GG5pYY@BQ-$861@S_jd}z-889#?8PnHVF^OyMvXipm zQXw1F`ekEG2P-l~K`|&*P@LmAn*B{s7&-}x>URW1dELgqPo zda3k=?Vb!-52bK=zr!Mli-4JVmc^gL z;jvnSTAWwAAJt%POBh-R(d#yN=#J{`1fi1jNyQ2j~mQ_$ZYb_|AY?M-k{vLFEvy@tN zbEirHo-{F3N_DsfscvxmYP3d0u3xPCxaP65-sz`Aoi-uZd{~W2AC*Xdri9Kr6s1zM z8233ECpcF`*3)4!*U75SIvnEqvjSuE<;zUi!1-&x#0<9;X54#YL(%zm7zf)?cc%^2 zAKEY>g6qkZKJ;OQCymT$N@dn~)1;~%lyXB(Z9)oZ#=b(DKdg{!oGT9W6wq*<1VU34 zTs=cjuqFgyJf7wWYLp+X#@1mvv|Oact@~OuPt;*;dmZl9)nQaEGbYHhuxxrJsx!t9 z|6qo2g)#nZ8>aI(#&@wp%(ub+tqu7FHmq`Ur&0BNsmX&T^w+_rw4_i*&j&Rm=VB5Z zt}KB$$wA(nQ$JR5P>oGLX(PvCLwOZmomPUbD`D%UMhQtMrcKtN%v~KKIiC*C(qb0J z>zkEhkmb)jKtD6iyJlfndoxT$*zp3K$k<2tpK6CPx#P`;5GQs!GyGgTP%NQH_j z6=H{IQP!E~$c=OQel6a%)1iZJ40E9-Y;w=Sz1Jq}m-0HbG-JSh6Gn3_lmC_TC+GFc zoJ;48wPQh`9pN7v(qBRT^mw%|Y2Ub!S9^cjztfvaxp7|K>V$Dx2~Ho9pgz~q-I@uw z_gw|g`AQ`9<9T_k!m9ad%$&^iXOI>Zm{*y>S6i+J144AD)JKP}%%2=AYewH!nb>sC zgeqL~EjVIA7U!#4)wvGZU_;AV%v1O?{^9Q%>*Z8=tS?E<`_Y>VGCDp|PPx70l$apF zh&DwaOXAvI?SxBlMbLT^*V%a?cziGzUoWXpwyGKd^O(EZq(oj79e#2?eKw2d<$N@5 z9pJijlolt~WMUkTq4Taxp5kVv(gNpH>M%)9rL{8L8X`sCI^HO&mm-tvjY^-q5G^qFo)V4`jU#a05sv0x zHF&i?0uck4V@+dB%yIGg+ay>^8sHowq9$YCCUvbCFvNnC0t*uAGhY2@!CQl%n7Tqx zTrvrYv;KnO`X)g!ier*yTmrS*BvS0qM4InsAblSLedHSJ$8ISC;=FL`iWEN=b1l<@ zIqRu%eB)T$YP|-z91H!F8pw?rG&rHb>v5b%n}~?K#u$E}i2k`EauY=KZkCOk9#+h$ zlMR1!gLf<#E=UxwKL`prkE3avpy<9*P(0ruD4H!#qAiz`Y16h;a&MPH3pOND zkTchcDlb$Ik>mCmFMLRm!}XgCj$k=9; z&U`zMNf;Y}fIK}iq6|3nUc|v@JuD^>ZAiq8^;XPlm5nfWD`p}a3olu4ylpnRa*lX0 zSy22u!E2N*C@wq_6z_QrzdT5xr!5RLym>NR*)P%u_e8o;-#`lsvc4XEW~Me93O zsE1n6lrd0zCo7IK?s&98P{b_YaXb|iR~Y{k%j5mTxphXqNVd2X8t9Qs*+)eRu9iy6 zqeLn_P>MO*Wmv>mV|G7ptT--1g{eMJ9M|C3t%az~`&wBd9M1=9@HSF|9dD8l+k*GA zj~?fEZZbKyFYLp)_1i6k@Z5Avfvqcr;CW08>a{YV zq?-*m=0iQtNpNYq8Yi#oaPXT6Kl<2k(M3+FOPMb}7J{cjWOrS7FGbXk;;_-dMs8*EKS_9Oi@(ZfXR-(Ly|H#*Hy{)Qk0`!9yfiwLcg` zuWB(=W5Tq{oO_L~w7YU4xx8T>akUnSW6aF!b6uGurwLCSRFwI|qD6Js!|(4kI0ue! zKYBRd39UWVn0!HtO4m#{Q`U|IVFvOQ`x0K*pwi0^I zeTAcWe&*RR)n86yo;cx9t`bAmYf-v{2{kx=N9B0123SamZIo!wIr9#4dOarQARx?@ z7R3Ift`k&f8>&TzluW!}?yF4`DLu<`(1LMFjF9UvI@N^qQa1D`*@#ZH65#wqiNGT~ zZ;ee*)wkj4Vkt?SB?!H$f=gd5c3sIt+gEapvq1>Z^Wn6U%bbILcFcv#bp{P&Hh zjrfydoz-Z;CH(Z1~W&Astmq@Ogm>x9Y|~w=4@e$GLvXa;5y!4l<2ZV_j$FSDnpx z$uvUhCAo9;m_YaR6cuMnJSrbF#btdFeZ+Hg*N`o+<13m;}53kFrs%CUxEO*`6i=t2R{JVr=*IUM^i%sas zwQnb7BidY1f}TTEaChS0+dC88m)o$Sg*W9^74W#G3O#>BBP>1>uOj)J#`;mkC#*5> zd2iU0apmMp9C(|9$}1T+*K<&UZwS(OeLaIsI6TjW;!WMiBf>#4=A4LeU*%IKL@8}J z9@Bs-%N;a)w-S~b96uYG5LCyG_$M;@YpQ^YrPUac5RDHmCM5BG(*=1_r633CE~_w} z*U_vqA#F2r*1f!GMK1vzSU;%7^Ru~rCW4v!IPKv^LiYly;;X{;8Zmf(oN-)t){VM& zQQSxYJFIFvHEZF-T>OB>{C<@uZC)kdD?g_m^ZskwG1i*Tm~T@Ps<@H0$wg{BzQ+8E znYoQ+{P)iHAn}-k4%H6Dq`^8|FVA`#YfiT-x>IIT)?*@7=)mzI*~bLeNjALqkWp`c z2`U7uG5fL(o;OWsKaRQjK_2wpA>dj|HST}bVoQJ-b*I^J@n|E8$rtebg9;6%>9D%E z8J8;C;1uOW?k-N)^Enu2Pw7}|&P4P1HVm)oL&M%M2NwWzE(Pre#%Rz}|UNpG8 z6DEOqK>m9bWlh+;#D-bJlIVUvDXO&4U|~DPRm?eFm@X(JUlVD6TQBq-!1Zyk9tT{l zNZBVS!p`X_aIGimc8|dIED@8RS&+z>YTt<@YSPpjuTE$Xvx;lf##W5Y78DjSg(~&t zdYgIP2A&3tQ)eTqi=g;k$w0B`-Vg_AaCZ@NB(iJ-_Z1Z9$0gJE<6cR;14q6mDx1=+z!i$R3BozDdNpZWaWLWsV?IB(Jw# zxOXWWPgaXK!kF-)Mo`>+ucx~r^W=>*cr;CfUSfqjR!|I=rqcI4jE$M&F7Rhe$DHqY z{(GOcOQtW7!@%|U66SD(4;H-NEhwVzi=-C4kaj2>$38F)9b-kE5J90kqNias<>)w5 zgRDqBG&a`$8w-k4PRVrUvJ4c@n06NP$_*@7%v{E)+KE)^xfJ{V(!kn-@!BE_z*tpX zN>9-|Z?#)%P{WvnIgF3azY!G6w&9BU#pF#KR1q&M^M^96-@mYxR9m0}U&-sN-j_{P8Y zR98VEP7=vC#2e<1;V}0RF@1s+O|A-x6GaX5&cQhGp$6ABifF)i{E@$)7*RQ%Qe|>< zn;n6xLqxd5G7dEhilkA=^u|?&vk4mPZZ6_(t_4@O3JOmcsJ^olA*aJJll>{h7h0iv zA}F*iQfTHiITkL}z?d)MyVZi$%-cydX85y9G}C97p>k+WOfGIebpH-qGXbCo5JmkF~g?ft;SnaD_Cux>}EL?`&NE$b8^> z109fhV{t|}igOKCvJ2}Te+dfvz+`GxC`H3W4U$i=CbOS?FU=*2!Ab*7<61^}K!d_r zdc;3qZfG#i&j&qq@|9wfgx7Zh$ANOJo9uPq(c45iv{!})-8GoRf7gjhR&37{6y^IF z=oHsMpIJMSeiso?J{z~^alGnmpwqG5P@fD(!v?(WT#p_ZEK$IaLYov`%oi-gD!U$a zCt5KyNTOKuIGHv^d0|W**O$liD4$_L^mswh@)&c6UFE1aUjv0R^MB`Vq0bOO@hwVE zzVEzn>G?t=*A&rWo)yj?9jG}kiFPlQA^VaBk3B_H$+Mt11jVC^i8Qc<3|)t7@I$S~ zj9wO;Ud?s!W03}~^@6`O91%72khizsS|veIN@1XSC48_$9f36$li+aT`fRPBsPH<0 z6wf>naaDtLkJ-nRmW|#=ne!YFPf<5yc*JpLcx@3im~*>RPEd5-&-=5M3?IH|(4FhQ zp6M2BE5B5)#B&ov!$!pVXnHztwfeWX}>mdC^AT06&za*G7TD=~qVAM!@SKn*JL{-1x@ zio<;b#bQP6qqTWwIA@Dp@KPKbc%JFlCh)2%ZXw2*NU-dJlA3d4gq1buj)yNTn^FsyW z;i>!Ew5~QaaQ36>K|{+f2$-Lpi6qo9 zP-ou5jsT9c3uMquWbdL?j)N)Qu)dWds*MbJd~d>R&QpD**t}SVz$r4EIK**Z!5kCo zBXKvScx02I`g|E`ob@ag(1}v6~bR z&&wdaD1+&k9OwD_-dp7edJv9q-UD-XuqUxq1d_wp)99l?_Bi%6#%WO1s=YatXuo(_+IyLtQ)IAAU|hA z`3O|)7J-<${G7CfSkqO56MP11TnNW1_Dp8*{*SrHnh$Fh3;3KJKgu!lnFw`H_BX!J zBdnjEIb0DDr45jc(Btk5JsQUH{%5}Y8G9b@))2Ay6X*NmBANwo9{HLCmzS(tGsl0j zI&0P8dd#23-o-=_o5%8d`!j!Xm7iaef7fU|+-%HU7(_hTF2doiN9PNyF?kr^y5EAa z35?bF9JkoXJp3Eh1qNF&coOFej#*}BD^9?Q2ahc1r{dhT-h!3GvZ3eqFWJG`_DKtB z-?iZGCkqA}Ecja7ib9U18_X7r^R(c>1PksLvKGCOwP}tR1DtS>e%# zaS-!4XPMvWIm3$0vl>xkHFrAU;!jBhQhHn6ovIG;AZafjO3rISWk-5a`EhbeW*nW) ze#h1|Wt3K#Ie;Htw6>L;Dn>V^8v|wJpC_Y$u1zR-yp*L5{&~xalM@y#b<_Ke>oKfo>1d<8Lq`< zg<|F%CGI>9L19xBW+_#eX;5KB0rSbCMp8a2Jx6LpBa06TQ3wnv8zd@V1~VtQ?^d8X@NSs#N< zo0(79t%cO2MZ-xtjI5x;iCtQ(tgeN#zZNt>i!RLbPw%Y*`skp4AICn+d3u|O1@|Zh&&h@uT1@3%7muVO@JF~AyZB0I){0&VrD#*n~=}7R_-R&u1~W+E7ydl zmCX3OnmHSP8}>)r(6gEiy1q8{gykSEn>matcC;U8L)-o~Tpw#gs<#~{zvSReGp;MI zu@1k~2In9fiul-YIFM`5LpC_9HhA4)52MzGIj3@PvXKp6OERCfmbLoBcBIN}T*Krb zurLSNk8-f@9KZiW4#x`iHny|Fy3Lb57IUS71MJ;pA8@GwUUaaWj6TH3sn{uRQdIG! zI>)@IVMBj zRbQIF(1%`R%BUXmCqE~6({elWSoOSU|7Tx{8_nEadskZCPDbwA+1s#GPG58m>dySd z>z)$y-sFVCkpjwcy}OkCio-o5=zPvWBhNc%%oz4Ke3D?)6bZ(g1YG_sAdU64ydDDc zvI3?bl)%V*R@W!&F_sA^w#Nyh>Nseunf;E99hBxQLG!2rYF$Nw*@K;!1LpTUmLTD# zfMGui>DUwp-DoVpzL`A%%q_fI#-7E|N-VjiLX)>4=)-5FyIqOrBh(0Ouf`}Z6`nOy z!#-Apvw9WudsNuXe#YR%O4PllL~3$Bls%wAdK>0#OREr<6N2LfN{lP1MArQf6dT0n z=U6a^HJnR(l;}`IjXCZ3=L`Alo#wOoF$A5Lsc&U$jbUCgJrkw)`!`QaSazBHFJa7iCh$30 zZGs}hgrYUfILkV#W-ogzx|wj2pSNP72>}n7Gp)&fqVN232TV9JG7~qL*FEIIoN`4o zdQW1ljnDUf*0{Fla!_=R9bJy(pvD9nx-POIG|z@Uxi+-EYeV;aIhfzfj%mwtFl|5k zgAdv9I>UyIeD4~cxg9(BTwbzagxUsavK`K~+2_c7o>ppu#n*;nzIH6?WP{HG_Mi0R zGpDm*c2PST@VRZpuidZPU^FrhdY`$(mUisxvBsD-;iWNlk0j&Gmz!<&)N~JQv@tp` zZ;2+ba@kdZXOcWKT5PFkEZt&rz^%~Y#@w)*>Fu`d2=ot5H&zZv4(#78FL2bD2xEWW zJAv`a8i6B1o*JWS>`uQ@w~Mj+>7Ie9&9?<+M7jo6tk%cqbhfoocXW=i%&sMY&+c_P zacXx#o34%D8~cS8Zk-~W)YcuWTNWU$|%0L-P=6YdB4R0J> zBS+s!QnX|Ic$M`)|2LjUjF#e6QyHGUlVR&1DY{0=klUF3izB57@9c#(wb^GPN-_SW z4CCiAMr|v@nq-Or4a7w|tPXi4?!!^iX5`hl8HTXDQgBe`k=^k(& z%pMIoT+m=K%gm)SYOJF^2xdwXX6mGTFBc!*8jYC9SV84yDsR*CRB34Zi z5p!FQEmK8&J;5GDFaDfw_9J>T-aFjM00m>nr}y<(b5)P=Jz2{eZNPy_?0aPY&_X{E z?U{SHa3=|E-Wag2Bl9=!^r*5t3E|9{GzV;TGm3tjN2_JuJl-BhI!!%e>6)6;|{Z!#Iw(Kc$ToSJeFd39fH9 zSn+VR$P8|3(f9WaKI%S zjV@WSaI6(^Tnqm5xge{Sd(w_}a_Y6nkG>~KN%-PLFKhVFwfYiNyi-62ck`={1Px{t z#e_!!G|CX9aIF4tk$F*>8nKgE&ktctq-DR}BQ2^B`vzZY;cMeKcZK;;j!DLTW+b!z zaiKkX2-%Z1vmW<79OloDx@kvg3-=W)vZJf(TMS_RWny1fTI=Uc8_Rpspx2z&)KXgf zMou~1zSF54tdETPNw?XTFHI_-{6kKtVW` z!`;P)F7ezPpCl)1o;O`)%v(Rqm)t%Tke)sMGRBqeYYXY|O75fiAfR>!_7jAKV%S$D zj+RrRVGAX~t|@UbOot;cbr3?dSoedya`8HJe!^d~=i-+yZh(&&or{{ee}v~M+l&uS zIX;f&-U){d>v}UEz1fDOnXKQjZ*W0eHa(n^EpdS>Y5%j_K`33-YBCJ zPa4oPiJU?%2r!H(pzbdP%x3K0LsdwNc~7E+1xc09pcq!yet$suUMN1 z)uBl>9oBI!&b-an8^*dNO}NOKku&G4PLXCbUuH(DLuL$iZ^wUZrB zy0Xtc%7@$!%IVuSe>$;?eXy&&skPmmicI7_s?$ygU&j3yj9H=<^Y|t^=s}hey_>L> zIFNP539L!nRbh%s4gK+GJgcPxF(xQHqeF^b3x6Z`5N&1sB;SmVBTcwj-h|h;&4`(A zLO;sEraC$3!J6{0%pA1c%l?p1_JoW#(CPADBR0Q6x-MX@mZQg{>}6hzb=L5 z>`A7wvQ#p&KYsRRPxOkDq2mSi7OdlV-araJ^2VDN9JlvGV0;Y?pDzu2fi>8l#vJ&5 z?hlk0Q1P{h&Ri3FpD|!2^GV$bve7Mt{ny=@uUu)x)d^O}dN6kuD=2z)6BI+23JU+) z5=HM8f})9?_5INXqRdn}(;%7JbDn!RJC$%fnf4gHpdT;AxWn9g87IY&P#K(S$l;e6 zfzfj~M;z1O@@5V8E{VXH^~?`^6=Ap~q7Do=7sdQ)on+*2oxU!TJ>#hyD~EHxV1Fy# zdfmo~hPTn&!Ja|(>xC5viiNBzTp7dTVt#wZoCG@hYkoXas8eJ-ZQZM@(?sZ=>e0ZJ zb5W`R!|!v9ceY}>*@{YQt#Ie~U%xT0*9<|CJ&<{2=D-gXlPJpaTBY;4-Q1W$*GeUm zY^O+j&WfZ}BvXDHJ*9n4;vU_MCJ`G3hv#e%mf0rMv-Y51Idr+^UupM)!i5F@J5ji z;mFtX9%divLH0N;%wU~C7lHS+4d|*cp!5j#$von9;{1F2frudH=}U5+E4GJyDt$Ot z^4|Gc$XsVz)@-`)e&IcByvAOlg@U5-EkRLZvtzU)ol8tig5_i}FF8f~Ej{kXm=zkz!kD{y_|8478p5*eeo z_v$=*E}ybzBaQ3+lUnTI`l0R@_NK+@@Tf=@N)#}jk72*XB(Bd(vhQ4BMsy)-$VU+-jN37j|vZr;tgYZ-eR z`wG}}f%`d`2l>)ciLIs7*j7!6Qo%|DNOXAKh2!91EhhZ(#ZA^>_+A~RjbXoFu`EQk zGGkhQGj@D2BXAbyvQ>8Y9nHbP{W;ipg7c{VTe#|MsO08FwOaU4{7z3QXyQR5GyJH{ zZaIzGUPu)ybHA#O6Rw8~2+#@e<2o|cQ;F4#F%o*JF?cKUGdxEIhY~-Iu?Hhc3(E>E z=6&OujB{$!mt3FCV|}%$89h_E&RN2Igr6DZ7H~eDY(v!m&RdaOr_|%Tm10L+T^lq{ z{b}M@A8I&NPHQ%JQ;n-$q-xi^80T9%Sg-J%kxJ)KaN$Fuah zfVp|xTf+0zC0GTIiJZSUcloH8gSr|Dr|)XS^kS}OmlmV#TD-o+K75{^)}>+)9?SlP z;U-usm|^|IHKLapho3Vpi{L)AYrH;rHi(RYYBN4N!~BVDxcPHtmC-jrpHLD z9&}GkQ@g*S@#lIV|Q@f zu!wu+%SPbmBMsWJcKqY12n%z%%acSr9-WMhXSw%@^XG>S+34c1z|_@>rPUcPKjNIq zvG~Cw_Q+M2D31QpT{tc_f5|a%QzDgRjm>&6nJS!2qmXp|+=F-n6)7vlf?jgeZNeOW zJ1HV6%8{2Qg^}}n{ZRH*_KZN@!Emg9wh+b?u5(yh^a*A^_Z&SYT{j?qqX82yh}h|! z%|2c3YvTM>(uwD4DElkz*=WsqtJwn9yJoZYbWl*d<-Adzb-;IAM|Mm$(BSw)s@FP^ zKD|mNduKg0$mSYu1NQ{f<9@d4-dNU4hD4heK3CGf?#BK>Gy4q&u$ERBj*sPd&V1N2 zkjMJaDiNjjvflmF02O18+a;~&)RF6m%2upTWR29uz57zm@lOTCj+267I%}Y>PVriC zzE5i=Cmt?y{j@LwP9aCmK?ICtaGG?V;|Rk zA1-S!+!}$vXbogh5$Lj;`_7odPviP+MMDuE=NOQ!Y_*{5 zR_^KNxk1GVk%GB*VRLsGYhm6f zJyQl>55^mBWVpLrhN!XOSmdHX5bxvp>-e)6ShvjUslmH5to2Xjo(`U$!=Jd0OyO~{ z4$!zebMKr(!v`jRC`ddf)Rg1M4?M|>Z!Rbvp# zJW!<=R#ULFc^`IIo{vTgx;ThNnP2`(t&#fDk*WJ9($xe zWgwL~(KoML$*;VCipx=;KBe*5+za_dNHt8*N+<`%vw4 z0pi3^oSecv`3=o*-Dk(KvhL)PDWD(waY}n~F5a4nu)#Ul5hkUlMhBf*)EC?5N2AJm zj$LzeptX5WmCp`}e6ED^yJ$F4GvSh!gYv~>^pmxNj6O>EFV~`RYtENvYzPTzOlc|s zb=ZG&vXl-9?C(>&3D#w5%qGk8EH=!vNu?X+{NtwdThdt3pR8Kai_@QPRPH=TxV4tKl{agcH{aw)`t!r{z0A# z)QCHy#TBmWuB^zxy(BqZdGV93$FdKOYny!*6B;o0)-T7KdQLB(#kZ7bbu${X&v38x zt{l9W*pRx;WeumJ8e=!>u#fBcPbGPrBm602qrg4QTvsxm`ieD!Z3nnEoYH`Ly~(Gq zFO_(~IeG%ul26Lpu=sK#GWHcP^okOfhiOr>r3p*-Ft1)wMrEuHDi#~cHMtfeyK)|X zk%PYRo^;T;kb4P3u(zlVo12?3q@NAdp46ks#~DYp4nf`q{w#~Zj`Snpz;es;Jud57oVeb zn{x1Vl$5#-{Z35^g3+NF_qx2!#CFyS${PJ?ty}_$TL>mH|ND6q*T{Cxo4@>G2?B%# zO0053qtScz7nir=9ryZ0bt$A)KL=!hfEG$6KDx6;6Pt;NTx)M>A*WMK1aul7f{)eNH@7wu$?i4`jr62}asi3V zHH<96_Zbtu>0^U?XICnWaDv|tHTvnaC^E!^vrlvQGiJQ#Qau5_H9`<`Rg0AFnON~4 z2iMknQ{=}&iX5WE?Fl-ZY-&PbSw8QjJ*a9g)&+Vg(Xq7-)vf&ZhH&3H`!rh)WxnGY z_eYM^Vfzsi7H_a2rJN6Koy(d-Llu5LV?QSQY6p+7qhpMmy7Ffo6l<@NXgAmNbQy=A??GxGhCk2$Yk>nSIA?d45D491XGXz_@7hlq3=W*w7~>Y0FvUAQl_ zvTNPFwQruR2|e8cYULZ!BmcA@t*y8{N;eZ+1(dK8A; z$*^02ZG_!}&F*Aicd}W>MquCTyuXjnm5o(h;=Mi;Wd`#6)LK!9?@Oz}9?~;HfdU9cPoCQ?&!rGm^8r-2`EV|poT2V!xgFDW3atn6f$=UiB6~)|cbplES#x}0->&zkr|u8Yg#|@R2pw%s_>wYtXoT3}&`rjhaYp1Z%y8)Je4|p+?a^(b#>T`2#oUtKF>7 z-g73)zOnRNnWZC5Yu(!&7>Eo}#g~EKE4(v(R+i@YDy1Z%$(xapg#`FC; z+|i7&{Q3v0E3`M?@0Hm}8oVtZ4eK-$zWGw0p;l-&k28weR}EV}F`%y0>rt2CzKxiY z+AOC=_@Ec-NYCfY)@n@e=mM_ine^10R$;-EXebL2BbsAJT0QDO1B~+iCN()nqwui} zIfzB9A6eu7vo~J0UR9%rEgH)QnUK&s16$9#(4c6dB(SCrkJe*jwh@us7m1!OoX?Jz zhFw(H%lEz395al3&X!lG&pnnT<43D-h3nHjJP9*Lk_%|apLc*!e)Lx3_6}xF5U={T zDf1AB0d+r4ozp$$q)p^L+Q+Z|PbU86dY&@dB>#3)L0wyq3f#YWhskH~eNTOoAPXzf zQ$`JtC-pIJSK2Xy-rS!P5(PU{$QclYrZFZ|<30@zRcNcz-<{u3gZkcu88KuxxG?~SZzPZQD#@MMfA=5ttZ`<;9OG*~=ST!oN zjl#ffCZylVz)9j)FO!p{O=IS6G~oLlVZ!}~nXuQVetAoRG+scg>b@TLD<@%_yB$KE zW^3x8-R5baHS*ujoAKeh9fxmoJ#+n6u(3Bd7L7rDO*s71j#AW7hB?ggVW}FosE-Pz zpDC5+Si6=AZD_+}$@FHw)sj7Dq8a%<#QWAOw5unx_Zj7f$o0`E*Vzoq@Jw{!zAk&& zEE6hG=j%nx_o*4bcy6RLV;^-RMU;i8zuFpucAw4g_+W?sH-)zLextn1Bj?9HyZdnV zAgk%yHY>E&=kfAxvj!Ww>#?|-8C_;m&%2tvp^CXFF6zYib9G-sP1FSHj*2O?_vabK z`+}M{EpzBbCE@BtJG^-=we6iK6R&8Hqt|0Lf8OaYs88?3^L&s=`cZ>6!-tx!2jtes zMGc|;*S$%y48EYj!wGuGCvslrnC;e?p0<@n(M9le=Dl!*=R>hFnaF#=^}lkTZ0@f@ z#|7m1CYn(7nH>$5@cb;kS8fGp(6mVmCRR0b9r62e{nv{$OZ8J~)NB)jo!3nWV&54{ z%rx9-mLoUR=+RY=)Cl^s7u)gYlS132BXRd##AgRf8jyL@f1W#=i2=LJ}@n$9`tW?gOBsh?%JoHZ(V>D;I0j^iLaaaot}LoIkUc#j8MO@WqVImWpvDTm3VkuqE-)!&BymzG+8( z6bLTSqoAeT`8dlC;XeGFAakl3W&h?R$=I`3?DRFZVOGvtdJGyJ;JICzp3r&BZ!DH1 zlP@I8wC-jZyWJ?K0?iWUXO?qo$y+Q<5RWrS(t}^G9`{D4HfFj1-Y6aWo8;o*1R4ID zxjysEGB-6@UN=sb((TPMyh5VPPfnE5#AizMN|Y%&ql9PCtN2rcu}#(Z+pfY2-VN0n zsj<7W2JJrj;-!`T)1~yIHX$Z)P=jG}e9>H^#>|R-SaV5(I)NIzU#mvfIn>&(Q{z4V zp0-|t`!9U4gMaQpKAeCmRt0J3iPb<~LxcPBWqxWR4k50^K-06+ZJX@I=1|b%m zcA2=)9X%TS(nE2Tf3`CpCqmC0Ha+^CipESwG&U?`KEW70Mvv8FS#kPuePU2tsC)bo zg$dL3SkaKW$PUypwxLILtsar-(Rf6RyWu%<*0cC^J8^yU{}1OxBO^N+VFUGO+KU`U zMl>QD^6o9D$16TVG}q!c-sg)4n{k9(PwzAn-s!lnXPNPm=k!1yu5H#s+0=HoZ%STy zvKga>F^@6BjPZS#3oz8otVU)_oHe8B0De5b)|0YHm}fF!>~bUI0)3ZD=@02f9b^$R z4C9QL$b0Il-N-Y7y7r00!<;7SK9Ya~JkRIa(QUgOXTN43zcFjAX_+ux&BQ(8EV>$Y z3>0E5ywe}AU=9z@k}KTr7uIKx^UOrq51Cj@op8_2c9?ihwyl?mbG)}75;rPGtmbZ- z9d#m@b8*#l?2W$T0n(oN$by)Uxoc@-ee z`JOUrtXghG(Hr)K+N?svd3}AQ^gusZ;qVdVfjScK-b)^bYouXgjSO2HD4*$1Y$G1h z;-9*5VzF9kTkA=?OiyVYtHib%?1!Tic-+z@ElVh2eBqM40SfpiawP9Qv6j90Qsz>w z^lGbs@AZ7y_ECxCA}(U^3aq-JgwGf17Y+HME=w$TTE6T#qd=WVC5jUR|4~SEJf#=0DeLxu zW*t_rZ(d1$qd~QB;=d6X*iVOwo5G;lMNQVoP!u~Cj)!qNDA%%{KORa?pbn>qnG~22 zj$NB{c(_If%T@9L8R5)wVOHGRFg)uYhKKugIJ-O)S?_glvG=)4&a@wUg4BY{WKcz* z?SnX;_v}mftN%87``JTmxNX4C9n4lFelWj@0n1byun6oy%TYH)uD%v|j^#%U7&eoc zKV=O#IL!dfWdkl=HDF%rIMlCC4mLLyDdi2gLT}o(%FLZu5{HUr1KJTw&@y*sOSS?2 zH8Fkzk*4L(`%voNy{9#CTy zWW&34?A^y%@rKz9UT!v|CDZdt?&t3-=@|FUie-nacox8{#j50ft6A}PW;)6~p}z4V zySIZb_*j}@su(otuh72fZuYdl5`WhEQh{Y{ML6?Iic>ZhXKqbYHtnz0Vt zyyQR-dF>xr#Jj3Eux~5-%a=}^tn9?MYzOitIM}CWBZeR2=H|qo_sm;jPyb~TKaPL5 z4tAjK3J1<~bfPN%FE!bTXY4K0lui^K$A9~q*>e64OgZu%PpEA?)|0%ur{ax~gktY1~q zX4{17xa=}{sD5pElBDz(F?0X4wYI)x!{f(}j9VQAnW{?=KC=?kfgRB}%fCz|QhVL$cA zub)yc@tmGkPxkRn>J)Hhh!79%v8i$RKAKv^Nz6p~6o*1j;tS3DuF;lA$b5yy1zH_fA_Q&FVdMt*_=ALRmeQ_yjXlgMNBPtf{Ul=fS zumP_9)IE+jpjom3%R3PRsBM7Pj&uy&$_&NFR&37U9++lD!);bfDqzFG_1tq~=pRnw zei~uLf)7@#J#NLSYt&D0@4Xyh!zk`O$0aMCa*vvO+UQT<{_&*lIFcI22KxjqtJ#Jaag)E}xpCUG(o4ClB|F*{GTHjGtou;&umWbYR9KxOcceONBVm zi2HR2_vi`kt+C~qr`q3vwZv*WuXf@|Q)*9+I`H8bb4e!gYw-JKt#e|M&H<7naM;|^ z>K`qc);qY`>9q^nT8?e4A6$F!!P8G~CR(I$pH`{G-dZGjw`KR3BEh}imkHi!7}P2v z@80R#-L|)=-`sS%U|Y52srOLJmJ=FF@2F5qDYgXhHM$3ns1ns`*{H9r`h96 zSyFFo@YGfNEkjggEYn)tu@oFrDXnY#9?ST%H7#p;rw1Q(BwN~)8GqWfCP8{yljPOU zcxgaBf6XV8c%&I+8T~#1XU%eZZi1wE8pZi6LE_ueLpC-=w!co2*k(o? zO=1MGNpcpL<=J7Q^jeuLn-f#yk9U%6qj%;>Gn4djH_C5%HlHjpOS9D}^1ZK77Sv;g z6*DA8MjGW4{i`{?Ch@A|htV~OQ;hS4;-?Q@cl1R)_Aw>;X^X#8`48k`_A zMkKOETyMtT9n2`DWrpH&)@!UAO+}M1@hY=4MzD_^NN&|^!sOy+ayDkf^W)l&Wv%F9 zCiiaUd{v;1v@_Km~lcs+MICuRf-We8)e7J!*=YA&qSX@_ND7G zv5|f2z;W~@FU!Q_0-5B0=!a>>T$W5b=BCr*)-n?(_<64CcHF&5%xnp3%`kf6JhSlp zGO-%sHEmC`US!R9No&V2elK(3EchB(j~4#F^QMz*4Mq3RU)EF#lKt&{CE%2=`1jFB zW^6&+`9t0NJ7xvwa%InL1v<}Rj>pk3Y@wHag(Cuom<4f}dbBU+!|*$nHOUO>#k;b; zm>h>CJTo7VL+`c7iY6zl^j_F-vapp|T;$P85o4vk!BXJ^PHlEzfQh*FY6mv;cOvn= zhqMdzkzHPX;<3YD))iLC{Kh`=X{G|XpB3oCd#wQPoBXBBOFE@M+>tOeHbvmpL;6QX zl9O8;j-%tlaHS$^qtsYtz#4Gbo!Y$>aky88HBkxXAhMq5a@Y#PL!P64^so1|;^Z_Z zjxNeZ^FdDd`I0wU#7vXV)N1ch$)f~~+@zPst5;$*4cRG^UphMXz`3*_)$)TA9pfqkFU);J{$EH2Oc}IwveARiC~^Oc}4$9~h3DUSW96Y{YJR4d~aJ z8vn0+jtKf!F7ocnXPwCRYFcj_#$Beil3JB&W2yVx$Xwq5V)PB1n4aUnibyA75}22* zXV#U6O6Gj`lMOmwnc^ELo2?CH$1`Ti{GdMOsuBlEGjD4fdCnOMw0!M`*goOV4(f|8 zws0Ko9L|iAa9lEl!8MP1BJx95bLr{fUEQck9CQK9Nb|74y^jqymNL`(r4`wCY^cHe z^2MEO9Bt^ph&xV{=WCNQlG!wTwu|Efq(Y8b>aFpWBj?zg82n^_GEjo}9`$s0$<#GU zjOY3(wc8DcCn=e69)`lcI$#;sG3yB%^AUs`V(J>M-B9vpgEt`eeH^@9%xH{?Ls8zh zalALD6|>=1mK8D7gJcywL+p+|nYP*Z#k=b(*YVyj)Q4QA2GuiJO3@o0Fg;oRq3&zg zO|$HXNRgK8wbKv#VN6XwO!=rm+hAXGP9>*aDF!KHc?K$CaD1E|X*c!gQjL8y&zOUw z>DNnT4&q_4>-`nV09_5RbZp5kQ#h`K_ zp64Fq@%daOoq9ZfPOZuV6SJQ=qhJrQ*gP|C%w<+UmKiNlvyfxRM3wc_Ve`3Op1+50 zJdb|zdsn2^A#RvL+wl=`r4VAw)T_MmH_2jCioCyTltauU@ZFXwK01?BPUdWhTwiQ+ zYH+4@IzWBHSA{n1utK|$*m>JwN^RV_WSLw)S*kZr zk>p~j^5{&mcKw9nGAm$7G~U^W zhq#%s;*S}%d7oUqXo3$pfFJG6@XN5HSWG6mj?Y5c6y5PxZ98B;Hsk;yf*kvO)}+wWV(~&Wx>3sZA+OoTa20 z4nEJ1LgYhMXX1N&yV7CiXlznN6z{S`+WBfcpLt zLOp`nD^UJg=r0f0f2}@C-Pb8M9B-_^ig z%=}Bs#*XH!U)Pf-9nXB&7lGm^5-4j%)5m#4Ee9(G%FI+|=RRcqO>hBpXU|oZoZ#KZ z3bf4#!}3?uz;_@&9utN)55h2UHRn1s=l6cdISh;9kbfc$E8a2NeHZ`Sm9;)K20iy! zG4iYx@%wF<&VRd9i5Z9msDCfa-jvVr^{5kP8hk*Z%bcgNBtX)A17!DNmH3tOllV2w=K()0_QCej{#5o%@Wo$5&=Gm+~gADdn8#>w$*N@&T z_8_fSI$=ERB)8#&YdL+7Wi|4qpGF=#g2at85n}1*xHP4)Z2C`g%4gW*<%WLaU2=h1 z_~(1wQ1x;c!cK-WcPt#%65)8eow?9I*^e4HAA=Z9gGO;^#Tw{~&4AmL9rK;|Y$oNHIEdymQSqfsS;z((R(C&S9o-G&L&SxPAr_<1ttfZcfMbD9*0v<3#(t4xG)-#@^rA(78LX zpnQrnW~NF(_B+i!n&r^=REc{??H)5Aa?{DT_S9ffDmB%InZ?4KgsKzBqqNoIBz1$m zCdJ^GgIH~IYQ6t9A*@{zvbUHqjy3q!-{gdNf9UH|dp4im9itsrt#+(YtwaV z2k)9?^c0?bG2|0@Ps9vVY6UY;a?vperEFO&S$Jw?h)GfU?lDe_p&e8wi!y_fLC zb*`bnA8K^YWbRFI=DHYS;9ffh_p+HQ%zESa2YS~&vd=of{Gy*`oS8?jz#(SoPv zcqaTxWZ~o4Oln9nu`Jt;iV?)fjeMU*DztOIkjrbP)SjKE&^}-d;!!9h62s4{-oci9)WmTS;(mmZyV$DoKl1|MI?piMF6o}8nf zW1|^6Ba*Ph$hxBwy&b{KT5&RO^at}k<6e|%+5PY)?MnKkNq9kvl8YO~aezz6h>CV7adu@XuB=(F!ZjdTh1?j}M25ky zFl+37R;UWmBX0JS?N9UMz|c@gngM^$w_<2D>c!X#+TZ+<)?a#~mLnEZUJ*;$l#O!l zJ>)fW%1T@f!SnCTechXmnx!3R8|^L&O6ADX<6)>YFBZ$A({cP(HX^or%BC^-5;u>2 z<7UL0&sp(!3BOKVZ}B;oCu3&o@Qrxe)^AoEzfBDHiLWfCuIlOne*GD-ICPSkw)d%b zJLoBS8}gY$ABvFD^gSK7!gDMA>>oVkK<#`vQ$&YZr(>~hGjZe14isssmg3>LQjD1W z&8@MxGLe|rUe4@!QCDVM`YkP*ha>a@{lyCU>fh0aRM10ecFvV%<`Crb3H@wn^_Yc5*d*v_W2>O4Wr(tB(b*|>_2|^N)h6xUt^ig z&%P?3-?yHMzIkY*f1na6g+g(OXYo64dh{C+U!EHv>$D0SEJNIrSfRZXvGF3zd)`ma zTtL258xaa~QD)YENkO+NV#A1rmtgO-gEW6JUwXf^`y`e=E{}O;qt$+(3Z2J<3(b8oFSArPl18SVHnnuwa%Y(EH`9h5&OB? z5iXgTPW)73fcvv_EbYqYY{k5b0M;+OdsqKsz##UC=amlT+-PK7&L6q_JRHZy#G!&S z9jcRDS7YnQ)MtMrH-a+(co#M*cLsM0FfW=sQol~WrN)XdRPW36M*ZoQD%n`|xQ6)O zaEURD+Wb&@1E~9ZT#7xOvaZ}FFLdEC^B;B_@Q`==Top3~j(CaN5Cz`#)gieKvmH8G zQHr{)+9T^r-Cy}~erp(RM6x!RX~lt3e4fqpn4Ha*=GNZmH=H@jrRf9d^Yn+{A$(80?LokLo@8A#{8qw>r>5h-=JM5AP!~;&9h@}^d@5@sMl7?y|g!}7c z1sw)8;OoQM;0k-k@<%;oH}RHsX(6~BM~u2N_w_CMRQ7txf0@-a=j*WkW-LxDq7KfF z`Iz^;WLixH+!}>qaW4aQF63+nVg^e_F*o5{uADW|4>FOtu9J!R?r>n?bx$#F%9SzB z5KJTnzNaO1&}XSLec&St)#TH9QfKGGybE1AyvK0C9Qm z#>F~*QpPV|!aGx^Ol*AT9?sy}LvF-TTf$qoq*Xy3^u)yrY$vxf)Pcs-$-Z`1z`bq= z%J7`I&iZU)ayH7ItReT;=1I$DI&5xhz?dRdto+JZ83WZ)_hG&iTq9K@vyjq{vRJ%Q%*ttnb{;&c;1E*k1t0L|JqvOm76R6KSHqe zt^rX|%pKtRA9~PR{+Y@3Nv!Hm73!A)U_<-hOWE1f&5(QL3DcW0U~>J|BG59=D9@NV;NE9Zp(yLB?!7S#cwPl7+Fnjo^MtSB*?7AxR4GWuL zy+nPYRiVwR6fY^mRB#LD^8^!@c*Hy))*~TZlcZa=H&$+pLa#PvJRWPuJ?bTAO-YbV zZYu0)!o0kx%q}WNUpaf=Z%q?rQ6^_vj?&{q6#LUJ%o_4y{@ROulFeBJ{`BA{ji&D4 z5dXad^ULTRxn}f1+2_p5TWG@SqjoH&kJCl%N3@EXiivv6Xl_QKiOfTssnCw8W0dM` z>1FM%M{a}($7+%1XB~As)-3C(BYV-282LT=SEKEiO+DR$%|VPpI~tzu7pXdb@oBV zBx2>ms9%^*y-AyRS*K-PApSHtU*EVN<<>)Bnd^Td#C+d%= zUn|E9@cALE+x})QRjvtlJ7%Cby&4Z~%>24T4=VeBlts*nBA%UTP-qhmF|(_J3QbRP zPSYzBrsZWoz0-xE4UF=!pavbsM*|g;@a$P8svUJ<+^v1`CD#u(=IHT^_|Dc|)KKhm z;a(MLXPz?q+#Zd;*jv2M$-pW<7v{8%m*COVg;k>t^qL7%b~D$KI;P(p_lbFp2DNH( z-pF?9r_wW!Nd0VDtWkDcQDJ9_9^0rBw5=xYK1QJ}$eAJc%cwbPjl9BgW~HCCqY>Yi znOrA^k}8z07mdwLsK-pSBlNQie?pB?;*Jmg1VuqhU0Vxc^Q!GGxF1fG&9hV}V%KA6 zFX~dM1JRyzA!k>D?4iD|>Rvs5M4FKGE&~gwU;EI~C`tV|bMkg-iT-4|5;&_GVW3aD}##d7lJRr#A0tG)ztt zTF2V4-iPbJCPO!UF|VRLcup_zCX*JlA@Sby!2m2=c^FT<>giPRA% zX274dw`wQ#aZQ=G7Rz;#Lfs!Rp7IM_SitA;kMu#aEzC;GBd^km97iRE_SVlt8U0#? zSFh*dS!Z%BTbbp+_0zAKNnS?#Fo$w3<~KGWcoO|f^xDqm`nkrO4$t?|__~GM&Q|;X za$0Y1-7Cv-RY;X+Tp<_px(M+luID~&jZ$)v8v6^=d-t!2S-f^Uq2CC5;wAYBHB&st zzGibj#@lgvAp5=ciL#13+9c|!&lfXeNI%XJxI!#5D_)Af_90%y^WiD=l^v+pW?kQ# zz4F%P%uiHsee&mBMU1W5D}`2b(j>L^@!V*`eN9X^yrmtNJ1Dfpa#E#V8_q&2LhTga zufpBg1Alj66m@xB8~Gq&aTL~2Kiju4UxzrJlPk=uKRHw9bredSFmXm7^U=5-LWjqT zVt@u$?@+(2Gof6a4CvJKY*$K@!f$-IAE{&AXF}QIe0|uH#11q{lZEW#mq%l7xEXF! zIirR8?!MF`KYOggpmv-O^vHx+Ettp8btU}xZ(JugcSNJ!CKEd9Ie#{gxaF02xx1PA z?$*&Lbkl^-I-c`|724pQd*$j}uAlaL6nA5u9P!3QHK;eNpD2Hpdn1tjUSqDGIW4G1 z=Ig)WSAvu(!EC+CoV{aYo?~VP993O-);L~*R6bbRfj)LSc{)D7=j(jjpkC6#^SO8{ zJ#M~azQ_t+@%6uKf|dKRI@jC( ztDdn>=;`2$ibGDX%+0Wz{I{!Rb410E5r|9TT=SvcyHrP{_u zryA`z-0H{dVyzDq85vym*Lus8;6s+srv*=+y5W5~r`q4G>@TiZRNl4I99~7!&fS|A zJc{dVO3P%ae90_GiI?(w66NJplawhyZrYe62dbIn3+L=K>y;$t8%C+}Bt=}4O;Tj8 zS$eGU&1W=UYg`{+XOMsG0A|d$r5|oB)5N><=E?ZIk(;LEWLb!XXrR$RW3c2@qQZYLC$(QIpsCfAP(jXK@D;257doAk5#9mkzAU0eJhqaGqL3 zsF<^JhnzJ(_hd!Z73s|AO(oCm;mFB%MY65c* z?o-eF-H!4N>_~2x30Eldb*MjVLi|HP{J!iUW^80;V#H*g>j!yf@jhPGh+MY9j!m`i zVNSa&bO^CyPq$2LnnmpII?t1Z{IkQ3Vi*SJZJDU@R00pL1OL3d3Mx8 zmRsO2C5zXW=D$2-Zq2$fw6DKBJE)QYV>HrYgolj2Qb+u3?$R;VU*^_oBpts7%Gfzx z()68|T$|}BJ-QP+S15qCE~z-uCAt5SYh@;5i+wJcmE)3=Nz_cu{Uas%B9|a2b$(N1Yb7kaaa-^KE@M8B5v3e_T;7hLbDXl=}JOy47 zfA(Zg)i=r|SA*zn4OXJ^d4B)J3M4oEBX?WnNe=te3CvEMxmmD%if_L3uR5{^IBLU4RnDE#?(dx*8f zq|j$pIuw=0>yR&;UEv5pk1g~HPT}mPOdaOd2*d4H)IClM#oGJqmEW;%I?Oq_bLd$k zr=qSFhtu7ujam_l3x^CS4bDJ_X6|A>y_MI#W{KrGWabQiMY6v!(qq~r!iu5njV6s}CSy)IG4*uxTV};^ea|Jpxk8zcQvy2>YXMcP3c{avR zVdlaE2j;Y=UU7>9$3JCrUKZzFRiy4Qin$pd-lKqq9?f+Q;9NFwbtlZZ)L>a1u$`q| zaTd8}FXlyUaG*VBn|ul)M-@m-)nNy&hdc0_eX9@g{&`Iu=s(Yar&}GE&YXTr0gVK_ zt}p&$RPv{)kDSo^NZVYER6FY@Pa4z}Be@Y*DV3C}?=AiF0|hTMGN87%SeALnlotM? z9_uYt26L9BkFPA<;wg)kxJ%AtAGtSx8pqv@By@ncJe{YO-$!doV0lkz*~D9}3{uP7 zjs9Zu^OEY*>PvLETK4ZFR&Z5;i;WbV$B`$M9e?Com>cQ`a83vReZ(&2BW2{ttJVr^ zE1oY?xtH2@cgav{6sIyX5D>+yo8x&eJfAJfwq-I9eU=P;BOWj<;*+Ro@kY`rSg2 z`CA9io18fvti!mBP&_FbibKUC5YUDHJ~0GALv;x7(_!=q;#=>jp)AP#_KsL4ap0i7 z%z>;!tieM6@Gt|iB8Zz5-T+5`=922;aD)46|5@r9xervw$k(kS{&U=bx}&Hi*2cj) zkn=8@8t{XA^f9raL7faZaWxj*>lyIiTr3*YU>*nm@An#JtcGyzm^Z(Nj#|k91`I1i z9b*`^8B?hxZb_c&EA=dm4Cq4*O_ym_>UnI;-?k!@8B`yqrepOzD>}8}><*O`GjvuQ z4P+K0F_j5Lx$lNsvEv*0r^8lU3r@$`p*HI6IXBwIeeyURZ=PE5*SB<(e#d>A&bc`J z+>XDj=-!WW@+PID!HINCpGzFOCV90ZHVpk~#fez@re|?aZgQY9@zQ^*anJniKstXn z7>L&dIB|DdHk_%%{wxmM{X-q%nQWYNIPm4BgBY&^y57t(nk7 z*Xdv>U;Uw_(%e3la^q?S&stkKt;VNSr|XREE$ z(bQ67Q8~-~$EM)x3#+8vsB_V>(|9BJ^D5t9@8wrdEZhFrGWLp(rA_|}mg#>VY}KYh zx8N!h@3pEnqIFvH_BoaczauPBktHmx21HoK54y_8jGvYo!4q3vEjj(f$q!#GjS@}r zh5Sc!+e9h|bm zd-!609deBcYG{Y5k=ISdj6G&}J6SJMAJVZUJ#AiUoKULqHC=^GyXcSM{EH3j^}J0Q zoXb;V?GhivrTM_?AoUyW)O5@wesO|WQJjicCbJ-yQA=sjW96|J*r-+b%v!NVb3Gac zMZ@ig9{ze}Sbd2`hrnnQzpF?65Mmkg$W@hz!K|xMxKfxpnT>i>b8-%K2lKaGFC%KtxOM#=9cY%6ER ziN(x$cJ`Bvkq+eojF<;sZk8%oRY(wnUG9PVqZHVn($*9+0o-J^SxOoHlAZg zEvp?v3T2{hiA?Nf4VpSE6T66W;JF<=Ggv$FExzTX=9LR7X`@0 zm;TI^Du_}m6xbZ7z!qj`&wZ>w3^gLJT5&iJ_GF&jhje5%W=4_1hDc)lk$0JQObyy~pAUFflyf_GI&me! zL2RX=Ox)@(@5u{2{^=*%TKLJ_c0MxXOrE$!6hNItZuq$(U*07vP`Ma05)XzmCng-7 z{^+o2QW*Ll2*a4c%;ex%+&wrBA6N64A`KYc+yHM6p7q%_c=Nn9Eg&!Q-HL?yXK?Kj zXHai;!go98Lsg~Ln$KZ+PfjV#iKO}Dp?-Nw_1pe3ZvtmZO>H3gW7P7tBr~KsC{UQ0 zCtZ0DUS=k;UnS~Pp6JkM9`7^eZQbn|2ImLfQ}Qy(O z)+Oc-_M~3VXodTebcF7s9;D3~6#nZ2_D~mBpSsVwC8z~iMt#b12Le8MOHY@VY#-q- z_m=xf_7{zebp*)oCQ1xFPVYjL8&FLNY3v4tn;ZJ_^%*lc98Z>#*VquoS(IT&_N8v` zAT|9(;?V6AIikk~jN|WD?oxX%)Ks2lJ(ohhA=ZYz)DK=~Z5P&wdW(b10Nc-*;H{k) zaf5osNb)Izn@CUhK$$IZ#nDDKUy$i5q&yN%@)@ylKsOlq-Dk`I;}@USUuFN5%OhoPV%Tk5W^aYu7pkZp8oA zGkL$Xb~j5$>MmxKW=&5Rw>ldvx?3yR{L1@$Ns zhPRn`yD^;2bCM;y8g-w?sFx{lK&qVQ zT{zB{xr>}{)J%har)W^UJbj$J>x!px?&BPKafy>hjEcc8HSwygdRPycP`N)}lit*; z4DbteCDkQoG*`Alia(v^CYCP&P2){A*$Zu_NeA7YKvo{rk(hp)ZWIP#PD z@d;nteeZ{aRrHKLqJHN)^OAX&E;*&ggiA5hsU^WmT=K#|&J694gxi`V{QH64PVxgy z-|-m^Q&;~o6L*GC^GSV(atFURwXm7p>0n-=5`iwTe~I6kboo^ z=a($aJ{Tq8JawKa8eA$uy^JU4a;LI(2xH#Xcs;<{VAN7Q+RbA2=r=v~YnkEEDhYRv zGMjM%v1;Nh0UgY^UN8ysPf*)*kZXrJ)byKntZGH?=iix}O`_0F;F=kuQ)-pO*{AZg z>9Udfrbb@U{gW5D;l{FOn!of6R>?AQjKkdMpFCa=4Hvm2u(}eHiYe*iQzE?$^@AI9 z2#yNFttnx|sW|JtS{Oe6LvD8j=Os=yAaH9OJoA`!!+YZp&%tl=t?=c!_^s3#H1M!t z@I4#$4B;$Z=Kb}o&kV#6C$^iN@XXCdy;P0djn~MD!a>qJvXR`r)IhFLL%60lXIA!f z$;1!^-k%_@(at45ausOf3P)PB4sUrT7E0G)=ocNbsUd9sgr29p%!hv$3tMXgjvq2G zqaqIafmT!xw;|}J6$3g^``(To!5U|<{~ERCiyauZ#)%))ci;2>fMz_ScmMJiMUe*5 z(uvgdr(El3{p3zQxO>38GYy8~~TIk=FyRBM!2dRc+IJ=6*^>knPSG4edKeaUZs zHR$jp!+;f~+3(m5c+Q?ExlJ4~IrdS(Htg=ga~U?Y+Ga(Ci@eVQIJ4n0XWxZ!rt>5x zmTl(T%cV{{EKJ?`jRsOp=_^Yj8Zc)$K-}YkWa--gxk8^phPx62uJAQkszm)uO5|7- zs5v77|MKpt^N{|xEZ*@edDk<$YvPJH3|!58n;yhVyyM_sYXfe2Y{1$wHu&}7>2b_Y4hnO9Tkwt_tC78$ z0`U6fhVA`wWsOzIxwvkq?ctJJT_WIBoY~Zmbo9LG_+CcfR3*M%tbc;?nAem*O~)SQ z+KW}V?r{a~Vv8E-a7vJC@TI8eRj2M95U+g+R}#GYsNXJQl`{G@mP z0QoeqvD9UT<*9Vep8lqi8w*&A{o;G1;S7_LoRM(PCEL>#_}7y-({~+qRqTtSX1-sS zId7zq4v$a7q51~uhsf0@w%LGAe6Osl<4`V@IhxetHtuV~#7WHd8e)UJsf}1L^ZAQ@ zKqBvWtB(_F3exY{p7RKoCrQsZ>dpHckod8wqWzpGeOjkT&089bIix|q8_d?IPtD#Z zHBg8+HTU*CBeP33QHvi+ogB}j%#%D9EoQt>GT*!yXA$PnXMTx3^eW7VC7#*-KDB7a ziGOnMFUn%JuRH5xa?VK7&P1xjq5weF%Q$jc!B-JAm*-LH$#_8 zt@+#}ESf{@po@8X8fNB>Cr7+76U}*7RC424xP@5|M&=8z=lnHlEEk+6k9e2bv@B}V zID>n~O_MAc!Z}XNXp}=Ka)+5Roos5%U+M>Ejt1R2Q$JXhnEFTN5N1Z>RKaMJtQLbs zo-tTilR1q&^*Ftf**3432TweC`7QeG6OwS@uOw8?&BT_c%=a6S31bgx_c~{xgenv7 zcqaFvUN4Qlg+q;aF7iy=yIP^$m7FYHW+Zc#;C?yu(Ihu^BuSPzSyFAj_*jO0+CJ7D zi!`9O7Jb>< zD|dsLCw!keLF#T2UT5QbO)ojzfqK1Wq3Cj*o}@_PLY~=Z8tW~SYyFXH8$7MiiW@vMq)BsiOwGvRL7EpBRmgzbsGs zBN^92q1#J+pNAD|Ts$N8SLa-b9BDm7hZn5bPj;hDuz~}{!|KSV?=ItflD1o+ zzRPp8VSOt$7l`k3T<&8T#uCADC{W%t@%>FawzWb zj&E#8$56g6`V>V^dA0` zeWjJROR_pLuk8%`ZaaI)OAcfVV}8FjN4}Gj*f^0`rmq!t{=E7?Pgy+8C3RCnnc2wR zW?ni1r}OzU)G}dGzU<=rvb{C=2I|yO*<-~#@E1L~n@ykT|DaASlHYgZe?M<~m5j>F zlfm6WFq!#!x5xzyWIr~1ho^)wL!wAl2ux$CJFCw=j`#1K7HT=OGDrIE48^Wv1{j-J zG0u>U8w=`*W{pe6aa}EM9gCIysR#T?zw~;wd zd5t(5#=V|gsG2LoRu5SUglFSUa$Q-k z&6Q=*p*WC6j)nc;*&*3@YW0<}2I>ua^@gq^ed}B&_DFga`npT4qPg<&Z|YrtWu zeHO$*3w`#H+{{1ns4IW2=JaB4{k$c9`aZR`{Ho7+mn5QRm8(vr$e!TwTG{_l)A{?IF{Mdh{f%boD0P7+c2u0EFY6A z)3$`7wY%Yexvphq5(A#(Ek{1)$$~Lq*w3FgOlL*8ZtrpLL0!4PeY%Quq~{*yY!0(x ztdsiXNN)*#>5@-HIUm`VIgh8Us2b?NDekY0e4dIq%#D3b48W9*bspI`J&ZN<>U^n0 z-T)O?d$wc>Lv}W1p7jtV`3j9M^{rD`pYKaY(>I(8)UJ+9oRKSuA30wkpZdNtX*ff? zde8zdF;fqCS(qadPmJD+oYPctM$|Q5OI2WyS15*Tj)jqY)-qzy#s15on8H~OJwoxL zya5Bkt(fw6Hn|~hnK#NMkvSpopFj>EF&zc&WW(CcQ_Oq+NGs+qOpY-id?9mG#}MBx z;v?>VawUFdC?00<^6Y*~j5D@#v*XX-BJ=ElWSRZG6Zjo2At-48&i|BJHFMEdwiV}9`?cJ^~^XaYK7~C1OFte zWrOpl{7MVOJcR+Cb*zYZL7j4NU2*u6JAEF4E!C*YEr!iUlskC`J5{)LUb_RVU|N_8?L@2S5Ple zI&ASlSNCY@1E^~YWnMD%GRw#BlPP;tC`nBC^)vG1Ui4Sjqdv~DPoC9Rq1Qa(wXAto zf6TzjUJ7jidKrD0s~D6_ofqqmCnf0FzU{(@-NY?6s4?k$6h>4}LU=3Y&`~#6b7i9J z{N;nwv!hUdv=Nnta9%Kb!&;$cIX%W3joRqRvvLkWIqKSmu|C0Gaqd>3jyVd)Y$jZ< zO@AZxL^CsuvSyYKzPw^?+68(w-`Ej#IUfzuiQl(jPTYGvI;zd6+a&|%D%00ToZdi8 zB8;`bP4=!ysTn9xRG|$^Is#gZK zEps8pmMG);tMP9adNddR=drgVsJlXYr=n5xPubfSkHJztf7e$TXg)!q^`&kuU?j7t zD(dlJzlnDV^JSG&rE{nW+0m_Qw+ zE(XQI>CxXxk0JG>1!tN>(_D?Q9reg7L!HqS>iE)Jxb)sAGwP{PXmm8zyNF$N$Y54A zJvc3rMAcV~CxxT2lJ8^ta68^5x#01MKkt1X)OXPL8UAFS9O&+Yzzb1`szfa80dqnl7223w zK0o!jtD~dg_+vsZu7}yIMT=#|%ZD5vY@_bQtuJ%AhEey*{$@fS@Tu3r ziOS?$5bF4lAcGsI5tsP?k@nS5ZEoAQNvXTLAVrb@73wYRnyI@$fO<=N>h1=Fx+_w5 zBm#9O5U9Hms8F}lK;4VIdGBw$_r`etzB>k^=LSeZzWwdJ)?8CUaf>}v{ASjdvzc=p z7cafLyJIZpBzYT+2=b(#AbDOck+EW&=!O%EsjsbR!lla8ijC#<3OOKO$fHco3B|(Y z#H40%{f8;E4=%*Xt9vR;xl4ZB7J7nJBIdn7_jCB!_;Bi|L=ZkUUwX zkva(v_>eDLsS5Q)lWmxrLBGhj{W6^E*{5R|n)7vsFC-t3yx<$=SXp05jp_Cf zJue-LE*GL#>Otuk#TgWPpiX<}A5nyUg^>klt}@A*01x^*g`rt7os=)Miz%_Fyo;f4Ps5$GTVkx6&2cluNY)~ zt{PT7^-Y}rG%rYpofz5hs5qJ3Mumn)nRg#e-$@7Zb#4~IG(AS1Tp?!pA(Wm3MqItl z-0-sGrPhj-Pj^(<8L!7k^64h=zSFUf8;Kaf3=PJfPw{g8gt~6Bf@Q1{tl;9#+T62G(%JaE5t7)Ei%cCi8d6SaJw#(0@%r_b+cdgHk> zpM4$kqsjBF&gZZCh~9b~!mvz5e-cmTCX`lah2f(|MMBM7Phst=`zl@%8JaS zj6^3(?-LK&wSU~xGUU=BU!6W7sr-W9mY~RimWFk&`+lrZKY68YMAF{THp{{y|0ZR2 z?$mZ+>4la{chW5<%O7a}`+lb7Rmpef7Jo06{A%?|%hWf;+OIoO#Ztfh#-zc2KUm(T zeYGTJQ4gN+xlmN9yNBvC_Y%S!(jWd%{eG@imNcal1(t%r?>5 zFJ9(vBF}v&XWT6ea_4Kj^b6tr_KBXiX|a;aGcv3~jASmOuj3wrgwHU@h2us!aw=AK z4Pd5V1*44Js(~x_otE@ozQ0P1>NPa5s>v(u;|b$-dNG1oRg1}AoK6qj0&)|ZF)z@E zKD#`7gD>#Dvk^}Y^}r5#&i-^DC$T3rke|s}+(E8>kOpDA*Ivz`=MMdOKKCV$UZ+8E z-mk73=-*g^{Kg~9oPOeo(YrMG_a*C*iD3xYM2zaCo_;&@RxQnWGS4vYXg!oa>A_k{ z56`#s*m2h5dL=!1P+|B`QIE98p%``{47pBv{HPR;0w-o{kdHW}kshNr5Z_+FS@xVz z>X<{}QH)skV?D8ya9mkOjc8C9HZRko25X*g#ODv3U}m*T7&>@x?;yT%^ST)a!p(4d zVZ@dx^u$?WgnLC3f->n}y~u=RW+RrW%}8#@d_m$M9fQqCy~_;hIVQa6!;Jb?oMZ3e ztebVytyAPEcIWrFm!CXkLNb5eV;p&rZTWN2FdMa zJLGJJS8xVgezKO@OFwESa<13fP^ToZvAdifbH+62cLq*rZOG^S`I~!2-y@muq24yV zQwElBj^K1L6X%Jcg^&~JXkjhFb8;7Js@x|wL=WNInvXp%%lxGZ8HnD*z3VyokvmvZ z9LM0BBxk<&FUZQE`D)mF0C6l_Q0VDaCu25Pk71)zh zAf1_wd#*hF;(8Uxp03njO)8Z1NCozT$vRZ4+eBc7}*tHgjE z`O^MWp#-&~4y%O%*NZ6VZBiiL+9?sapIj~CyKWu|45`g|0X1K7#h5MkvOvP=Be!t4 z0xlgDSeVRNxFa9S^hdAdoTvJ-54_`t=;QwA97K(qRfnvjoN+42XWUG0w-|q%=|dkl z_BRQC{INw9z?>R?be}=aRDVCr*~koP3-h9O2H@&hdi4i0Yub%IK^4i%Ivm zB(f?;VZplyc+RGGTr&Ib<@|m2&)p;nKb^?m>JovVYEg)p!nr_s>gHfS%Ck4sxh`Fz^qRmX^)jp@*t~q%S3hEe_=3wYVJF*IyO^{75h%7!y?6uez8;Jew z$;P&HJNl_|FqgmAOr4Fy_u07cm)|>J$H<%6a8YQ888?y=i7J^tL@jfBc*&DdF5;nV zD$}nulzVr`<#lA%GqyM4xYkvAK2u2;^P{sb zxXSiYE^;ujsjOVtyB60=_9OY=R%bM`2(ZXENw{wz!%~H-#c%Rze7Krct0ttRnAk7x$$+cev^671% zY+R?rpjQPlQO6m}LIr%26fh1fkhj|un8^D{(JKJIj|bojHHyXW1fXP)4v8ZIunGQ{ z)WaVmeRU|Z${(di^06w+i{WF>#s@H;YQTRzr2_Wp;8fEe1AY8apSa1tXsC%45k5vc0wuKoh`NUm`p%m6(ZnQQUKE!et z^Pcf^j70mR?B82a%Q-I!x!%MQiQ76|CGVwuB(|O>wo;ECB=4Ca7DR5tFlJJmBj5L1 zB!c<%dltP=|D_jWF>-{5ko!0-5|~KbqFogJ)pHg(h@Kb;^ustyj$=pac!hlAIlMP} z@G;_S6UV0_ZFwqZ_SDZSQ&Hj*^CE~*g_Y)7C!ggYJx+=f8$7s>-Xd8ks8cQ#7fX`I zQDBAFJuA|WrDDl3em~g?3`s>XM=P@GlNZyQcwZmR@Q4?UqjtDFRgJeUrC>kr%@>^U z%_dIh#~Iek7vxTsOu>NVydP&Udn}F`R~z{Wej;`{!lOS?&Rms-{>m}&WQ`&V1ij+kUB*PK%0J9w>E58%8Baz$vq|Z)TJODe*F@NP^7R zL~S4Ivo<<{3k`BFMT z6v1Zc??G=ybDUgQl|W6QS&lle2G5U`lw)yHE1&wYal{bz#))6E1euyn-^L|IF(eq} z#G_c^!5;X1fwMASdTwX4_B%k#!jCzjuQ)TSqDDg(HOhFaVCVOoXAyU?s8D988eKkX zQ0uxH<)^ARYw#eqUWIol)VP$T7Z&k{rQV!L{_6?#W;N1RYjAIYhWvOH&M)NGIt_*| z_QVS(4f)GnC{@oB&8efw=f6eRPt3YY53eSAYW_lq(Xt*SmSml$M|0MSk(a^{Uzc8r zC8>3ZptmAtW-ZOk#&qC(@jP`e)Wa?2?`rt-M_ZB4Q#Kquy_g+f3q@;U7FUUfseA7odJO#(isZa-M6rKs!yY|hZzz604#V!_Cd}qc?#BZI?rtNl#G0>1 zJiWDJsdX)5hUJVArnZ->n=tab5iz&e*A6$L z*gkqTR$?zj+-dC{YU}=`pUYPxvNjp9ygB`*nv)+nlyk^56MDKB@w^E2q`Qqc#@C8g z5V!Fom*#l}ihpI6W(@N*I?&IXe8fT9nQM1A16NqvZ8*p}l0BbYn}KJgGBJ;jB@Sjy zxSM&hi!*U>mJJQtW?L9J; zO8zF^V585soqWg5w*SLt-0a*~jO&=qo8~SjS81dLxrDbk<8mpjM4dnd`h_SkG`CR7 zv;OjV!hGfUK=ip5fQ~f>p@w@9o@WN)^^QP#Ek-eOjeB1<{TYc@7v&87YjbkOf3k*{ zlL~X6RP_48nNLHW@sEi?tFlpPbq>;3@=WHLedjzq2z+x8V!-(5AZsJ#&Gp_?-*ftO=Ytzeja}=fy zi^AzGQLHVZi0yF?e@AZl0oE3$xi8jC!>7Ymq`9Y}OdWbhbKiUXhV!)6InWXxkFC!7 zU<|!vQ=7={d~eBcQAuU;2m5qU%dbh!@^Fw6qcZYjB+c)_1$3la0fH@XigMbex!chF%@q(gEM8Ok~dFo$PLy@ zZp5rFvhKJ{PB?3tiX(C`s0DMdi+{j^>OSK8Q6nF}X{0SPqQ(V#${CeLes@>k&3yVM zFIJ-G>LLh_D3BV{ieT!RKosrG45l9e7)Rf&J1qmLsU_d?F}GPAi|I3jW zVdB|$i}hS1aveNVvF>atM&$5JnMG`UI{Az5=-XS!4AB?ai1sEnpFv-TJB{RLq?`13 z>LtUkwve%op0fD8r#M|Jlol=M5lIe)jl7U~2@d$#NP#Eefmp2%z*yG4l{N-plR5x< z4+SEgHR;qR}>o(*xF;ompQx(kpuu`LCVG zCvqc4h1crUJDxRDG;-sim+T+wAvagK$>c98@%Y(ThO$R+%2#5=a|Jy0N(9@K7`Z@+ zedhw;dy*bkr-JZrgMs+HjC0pgIyB}CF?eefZgLGZ=@x}gzLBV#5QT}0Q_+eX&*o23 zQH`I?kiltqTa7jHnrz%F!+a|>J&ZX=IY*w;zJ2sTsbP}S^slSkJYKrHnWe}JgD8nB z)NHQ7OYXUqlF2vk>`6~?Z)huM;8Cc@r!aE9bII=xq`%dgaEvO#d;;!48@c}^wlHJk zUV6!%p#SR*;)Ud2Eb+?3(mBLsT4!Jy@A)@xnHfxuUeoWy@5wV5--~ksYM8qbFMaCD z*KZgv-Dby&+Se#W4;UppJ6^u`@Pvzn8phsU_@HfsSqGTy+){;RzTtQr9ge5d=}WXZ z47Q%kRcN4xGkf973rz5{(l?3yZ{9ENncPD|8*p#)WiLBC6E*nWTK6M2C5=5Vu`|m) zg|;Ozx^;D#14AtN^Ct2vi_mLur&)%O>lx&nAg3-fM`gZID!G$S5TM57isa&_d&2RB z26r4aP;k$mF+Utb?$MudgC5mdhocwqg~1cZIX`T~fy4A1{A0$)T4wzIX@cuaa=giL zSe9%eU{ds5;=S9vhXO=ftz%B1gVG2Uc;@I5yvx`zE&PX!*tDbe7p0?B_BNdKHC>l1Vc z$_qpTatOmz1IhUgfIf^l*!huoKA(QIwWCm)=hjYs9Un|T_=~9+$^E$wJz=*vq+v`m z_RSxdJAEM=<#qHPd`0aM_v&@5(OnGmM!f7Tt6dsN`R<;Qo9-gF?l+Pa``zVNav?PW zg>s&}y{*JsYSmKWN^qgPcMHVgvjOO_mp+j{1IRZB!1!-|2qu3qn`hX-B=$8AqwuXN z_vg`(_|lJ`N8eQJV6W2UBE6!7y+tQ#1#0AA$TRu@mB_&xZ4Npf&&J*y?$0;9#rGd? z=|JDXUF4shF=_-c9#UMVL^tls-oJ`qNi6Xn_LnJ}c%~KT;CxSqokN1Km^m5?%LQV^ zd1mPqaDV2$+&zLGSpB0ghv)s1_B`kRNuw4a6;D}fj6KY=b!{r1g;FC{B?nH$$Z2ew zgUs2?YPe1=!`2)u+TkWk70fJ&R*U=TmXi8jEnA`+OVfJPz}};`r?V0{(F*n}_MeYf_gthl;0^1bH<1`$k3Nn4s9|7^;r#h&DF4}t z3*-$hKE$=t-imp|7OL>P>P9`+RweTodA^srN1vWI?oyn7qvsxLuY)J49F7}vn4#R?4DD9xg*aClUDCwb-G~Xb=v&@|Gmd}^?(fX5QDtHa@Aq=2 zcy3*%pK!WDTScMNR^b01Xj5plKFqsHV}@J%1bLz2?0W-q)h@?M%~PK6{pbbL4-Jm5 zrLS-=HBPZ7+HR+}-^y?_Js6HL)55Xwsh%3GP_)sR(T_F!tSCp5w33mgHV-exT51D(GMG*eEmim}JfugE+NJ zkP2Fp40BAB>YTl-9m7^)g}onF;rOnK;V5@KPzIR!LstPx`~y z=kmRHDYQ4mET={qC03mv_iM7B{F@+q=v{JcswY;jQ)3%zjQ{xQbUo*V=XaThy<3mh zoB8_MaBNA}qtO68h6L-OElscEh2#??^56dSJa#2F|GW`8>J?s%rY65`1}5`bMO@`s z+9Lzy3KZHi{izM$Os(2)h4upYUZ_`C<(w$9=O&1aJp3B34$02*N9em^mbXhe)7Ywk z!yZr6W&U;5ZJak$_C!zmA3o0x$DT{{_3RXmHYs6vG?jCKWeFH&qeg8IeT6H~55FOM zDb0)5+Gx6mJXI2w3@u?_#p1qv)9#m-0l~!t>-BoDSJTLx|hq}DKNhTCE zN~uZ)sYUPOErsOfIvtg-56G!3O+IC|28E$qKV!JQ*OJdjzUP{~dh9tBjyj*{H~%qGfhmu5=vABy?rK?Htw3ayAAXl$Uh~ov zRJp*6nf2snaew-@$PX2_MbN7(1*eFImKx(MEx5POZb>cv03uV)yIBHXxNutVlN01`l~UT!D=| zLzeS>J{(AV%EgX1Yn-I*0rCVhh~XLNOE@qEUnbd6ceArJwB*b7mCRb%#Qx}3GL8~| z`eRVZ+A9U(bV7$p{`7@>k&MgF?1)WkC})}#%8-tJ*cVJZk9+;|p4rH{;wm0B@}2k$f@k;|EtoVB>b;V?4tx$JEk$PJwu{XRDVLfuY>5cl@+t zS`X$?5mPPmi~a*e$WsgEURg66_~9nIcI8UYYJW^1Ca)*IugMDHUi%%T)~Et;-RO^w zha!;MGX*EF65l%GD7g&^#Iw9VYVV9hpY6%04r0+c&N8nUan`QPWuDLHaZJU^q-=cV z9A)>_LMhXbe91HH&6-jd$mYqeB5n5nmeXASTPrhndlGrRSL|qhl-?b|3iKJl=h+g8Rijfdmd`U`XFX}_ zu0ZE%0qDTl$FpDbqYTVOlG0616Kj}e^@Fu8d-j$on3qJ{GT%wcJ^w37vzXDw%K_li(Pw|ko4e4unnfINJJl4CsFV53nuajE5evrp^Mh6Xfb|a@# z|H%8R{WZQW^Mbd`q^^|f(~}r-cVenp)f>vhx%6Fq=7+QVyYlia&i{I$9gNZ-bw z2(BM^VOEop`wsGvStpl?_K=FFa^-}L z-UhtB=a!M5ILD4Y+tl)UwE`^~_~YtrUSH0JN=Mk~tL`R!p5;nwXXc5M4`^A=nUgE| zq?;ScB=Qq`^weR~NaF9im=Au|j<)uOGN&E0rB?c*WK+(%dXpbIJR9}-J{K*_7w6Od zDC9n)Ab#-vAFkWs&QfGqzC12Uo-#iluOn9U@67eNTO&1Z{FO6#0r)YO{KslmG~)g+ zk~0_&)?0Hc1`!93fZb%p=o!p+-t8_1KLwU8VxE+qx>;x9U26Jux~Qe+pWpI?`^=`> zynpA?>tii-j_eJ(uP^_$-*2Dhr;k@n$Ys9Ha_7#K3 ztJU(p-WGtr?vZ%l!#aDmow^3{XVZSm^l%-@_KC!uF{~*=ImbHQP$m?ie}#^9a|vcl zJWWCMlkaijzLTVJKM$#@L+GRkD0u(=-9_Fm_p1ea^TgGK{<$l;Z*W~XwaUiB9o3}& z^gNl)^TMwTXNmsw9Z9z1rK_`;PvlGT2|x7Yb+1{8vj(Fb`-zKht*6FYtsc2kr~{vz zj@{(%RA#N_9z@?pdLjL~WW+`f8;W-#Kjnx~dR|c@@=z!qk1h8Rg8FT%-*zHjx(znj7tI(a~zn3EpPk&F6XDm;F6) z>#Ns|_`#n)w7U>psu|_^UKOg>qvmA2i8X-@{ofbjT5h}y>O%iJCG#P&jo4b7xrpqS z>qZ;p_YW1m(#P$786#G&q9(5@`EF&*vaYd)wH|$-4jQ0{r*|{|t}YMgldx3<-^t7u zE>A82aoWFC6xy0K<0ZJVJI)*mLz5BY6&AB$?~+39Pciagg&Hr&wWvbwLFXd$E1aRw z-YsvIn5QcI`)XXa>cx8Y$WK0Y*7j`(?CvorY= zHI3*}k=c-}O?33?ioB{qy(4;<8yRuJi+Qg-iPQMdSCLtuUA8k<+Qo!9rRmSe8gIa% zIMMXuyum#bwTKCo_{Qhisn8z1YLuK;9`qlfKV44~yj?P|cep}ppx0N>EDb&7=z&#_ z{0Z=V?jnzAkU>;;HTVoYdc8E_MQ0ljtI+0LjTgs24X(M+FDrz4%;`2%n6J=w@`#o3 zMm4?OsAo+vQP;`b3u0cf%^<%A(a(!BfZY8?=7=!&i0f_X<5+1sONDBwp~Nrg7kSsl z+&6`G-jX;u=B`H0Aw71tB>phZMjlup+N_I{p=(sQdM^wkZjo1VEFHIby`Jo+&tNYP zOfrR`Kur&Xem1;f-P?uv-Kj2WoZJ?Q6+3x-HDod}Ka?nHVo#Rr zP}H{?;Xj%A6}-N$Ud2g|95q5JQ1g7(fNM$V7}1aZm0|Hxa=Qv2t1_Qs81sTB+we|R z$V?rh1e9Y|*E#Zt`x`OQNPcKHg?4h(L3#g7gV;CpDC@>`m~VsQ;X;H~HA#`<9?;d& zGaH9<4;A?=e7w7o`Px|;9QqiFuFDK?IFOFfj|wrcb(|C|Rbd7_%hJ3#JK?&Geo%;% zvIe=gjq9YE9+PU3Z+OUt&ZBs}Hphs9pU;3PeQu8jS7QX zHTs3zRkwaVPYk5jfzi0Z8Zb-*SvqD>& zJmp@zFBbFu-B-?tgtqBWu2pDL+Q&)mN_SM@{BW8umpq0%cRo+j)L2~ zZ5D~s?y|NFoH_y7ODkN@X){?o&itZ>w_XXcRP;*Z*#dswZvZ`XTElO8P} zYzh57(=zvdmc?~a(WJ`bu3G{>lubVAYDx-qyl2_G(K-33_ZZ9WTJ@6(XWuwib;vi% z-i5W3o9$a^30N|@UHjoz&Mh45ncPP4ASu0xi?4B6>E!YAuO`*bOHFbg{l<5G>14~S z8aLWaDs{lpsq6iA8?}$xecKt)cEPmyN$u1JrQVr1v6qh%YncS;PCw78+l+FZzPz7S zbFZpNPaK}XYk!%=K&@fBVhK{Kkx_Q7iIduk<3*WA-^N)+ImSLYooC&fI|pP(<3tJI zSNnO1@^BZ=#Y6EjXG4O_jxo!nA;j$I^*G;&{KX-0vi)t0TpDbWeu42)zp+^~$J8h~ zg#L+r)mYJAjeoxJnsJ{VOz)hu7;+c`IB#yEf~krp7S~YYS|@rmJM+Bf+Sxr=gPQ@K z2(QD;D4t~wS!$e5BbR-p7hYFqhJ8m3vf8LICWABWVDcUtY2bL4`hK31Ku8|3E#whU;O<4a1v<lsbCP*l#OpXw}f6zl3ynR~O&MxSVE5YoDbBj!B6Pp)Ko zR0y2=vaVRIM|s{K$1^w&XFXw9Ms35IFk=7AyXt9%x}+JWw{d3i%79=eBkJ5Y0{7|1 zV=>}cX){v3(5K-N@rJcVYju^u z^L)sU_9Q;^%LWDa(o@+se9>~x_NQOLpbWU~vf)#4W)N}~@|ZQ(d18SBLb>OL^R-Xg zaE9mQ^gHPozs6m@-Kj55UmD5|@)SQf&@Y`{is3gJ$c=!8@;*f^I?hGCiQ{hjsh0kw zG&0WWCJwupqu{KPvjbg4rFWC&gWcuJS0@=z%U!1RZYnb}ykvWbhYZ}R5sPnqIr~e+ zTy>31e(NkgI#*dX&`qva^pJ?3ZZha!Z>d|!T{e2Ti>?E8_tV(7A5>uA_X5$9J5_zO z67!E1NHq0{f$UiW{>_t5{h8lqQ{W(d;6{I^-fDBcoFK>X=hs5&!I=BgT7g#NKknu8 zWy%A0>!w`%GZZFpC}ww{-M5)M51jKlYvh*j$F5^ko7t z@xDJQ(i`%LU59SZ{qePv|9>+UmdDZOKQ971`bUt`{4{K7i(tvKOnMb&?p=dhjHutf43?@$}N+loG`tvLUQ`4!DmFzb>P!M^lt zuv+2T^FLZ%D<1IYeJ1i}W)o8%$hpHqYG;YFzwE^4X5W33y{pp~D-NVs@wOg4=k}#w z@zM7%_-2y}%o+OGY|NQOjuiX7C8e|J18B#&-^`TWVn@?+w1EGMRUio~g<+8KI2z!GN`OtRx!7_L3=N`w5qXGEblGnD=F}>nF2Sz zEAaM>0**Tir0$%*61+@-wT+e7T1J6cp9*9Bg!JVJr)g#}`q zp@1`ajvC&NjyDRWdq|-qR^vRdJ#~8X3MKA3`Nqt9ubjpEuS&k`KFRy}R-Po-^Cdb$ ziP3G8^gSZ)WE}5T-vKb%IQ#kHk2+O|S;p!x{-Zy3b~&? zPwADhjeR}u=|1IyQ2H9Rw#@7BAMB5A)%-EBg$~a(QK++v_fiRBbec#c6LWn;PU7xq zk+{v7STO%BX(ApJAA#MR)%E!riH4UWVRR(tmzmO010qmkCUZo1zYQzOEH4}H6%~1l zYa&rSm-o^d`h}d0L`yGnA-7XcS}_W7p;6fOAOiESh8BZmnr7jhRV(5eRAq9q}R(zO9&cy<9Lk1CdZD2)( ztQ553{WX+0NP0NAj)I{S0SpT>H1L(07XXXhAuC?aXGT zfgQiPk~{3f3>p5+gErK@&(6jMVqi5}GIx*P58s%L9a(m?Yfc=hLJsyvlK)8l$qBn1 z*H=Ir!Dv9 zb+jBf*V{5`z{8}7iF!+efqN`qCbdsWgk?(ChL%MG2V1ghu4tF{B;2>iF^Be}H`YlW z(Wy_8IV?Hp_T5ds?+X|CuAd)dIsGP1njbaDi!%nP*wP@;l?`&-iJBqiTAW;DmVx!+ zWn^5ONNei5tZ}kDI8HkDh>_l3j8cW%k$rdR|2^Qa+_@hw#i*e&*vJJCer@8s&>Sxx zse6e$$t>%6hov<=t5y(4X>W>?=+~?%H^)l1k#RE1Y?f)WV@0Ph%0I>F5A|7%rhPe| z@>C(>g9pylW(G9pFoW6uoS}EO=`FpzEgI;rs*%B(FIc6);acoz{;JTYf(k3^YH**= zQSF)ng+j%lK^mEwP3%~ zk(#?)4=gRO$IL~cC`E0G-_kH*M|!*n(Bsb)au&ncJFq5vOV91ap<&E+rFKk74&#?F z1kR!N*SRo!ZonF^nH~$W*iSE@wvznENp_wqTqum(MHlA1gIOsU@N(e@B8cxb@l14c+y8`d~*4%pjE8 zDV2fxS=11&q^CA}-6cQi)%}!M-!$SZ-!rgciVdy{_}IV<_>^UDZcB$tKW26uWNyJG z`YS%pU_LHA9A8m)xygnxA2YCYE-{Y1%m=y2OzPz}-kan{*5~(zWFUJgGvUf-&^y`2 zx$*zyGakL{BQNT!#qEbXeM3Fu>@2l7_WtA2_akQq^! zbu|*>8q*^;)rwc#OD~p5LyvB(NxCzWvbzr*z!{tJ0U!w@l_awiPy#AUk74UWsK(8e_taTZPhG*yv z92|g8JkyMO=xuO@`+saCo)X6{)`;2@)_23tSgC2X;zw306x^d-e$yW%jx)tU*%+9e zjWU_pc=3_G(3v^NYr(qbHu;o2RgwbwR|YY=>kH>_7AG0RGkVfpp8F#e82OBTTLA^K zVxWTOFMW%52BOZLAT&)5!k#|N$mDgakrIg$)uYg93$NGaDEv6UET%dCGmom)HkCPy z)R+ur7B_3Of@-O#V$8AVoU*(U$w&!x?(arWXEuSonXrjUib^WH&VxuabLH)z$1(yE5xz0Qrj#>BmS+xbkv^Hi{UP z=CnfF`7!x$^sMyQYLM6TwkkrL#IV3D3(22ff1009H7|5~LEph@o>=SWiI#qPC|>JP zSY!ROK_tnfjWM0KA zPek~5VZkM4G7Z$=K!_fblgMKXrO%cv9Cya?Ji9?I|7e~!!~wrfH_;1#9E`8Lepkpp zeN8?)_v5Hm%rLD=E(rCD=SNZVK8rkutMt?)XE2D|hw_W53I7l8^FxB{f0ZcL^3C#W zMFO)J%`%KQ)9Fdfl;L$coJOyPdHm|5Mmyp(nbZhW+0XUUD;%5oxhzod+T}Cz`L_w` z^=33{VaBy1X6R0s@Gzfv;R9wy{3RE@+5>#!`uV;h10P0`LrBg=eNUzKgO%CN^_ALy zvPx~YNWMqM1bO@Os1%$c1{PwLmzz1iaWTr@Ku@d>@}LSRZ8uhdDNeCcJpEp=PrX4+D!vFPw{Cg7h@XB-ilr_)=rP%3XNp4dt+%+$pOKk z%z;xY(fg+obG7{M?$k{#(-E`L;gn|(ZciaU?i0Dx4+HRc4)5*Zc@ShA=;92A91b)vCT%^sS)^|^E_JwBL)r%1&?ixnGqcG~-pmyu3= z5OVOI=h^4d*+{78DvPIj$koyFLg@W*h7D0kKLSk3XY9rNCQ_H7}QKwyEc`a5MoY+ZgQ-E znT9!$dh6w5v&ekJ$uaXW&$erjL#q<0QeU3Lp;nk@q zjN$pUXhkIU?y#b~iQJDZsW|%6iovI?xcbS8P*-|7HK%vwPLH(b|c;}+LT zpTRlsn!~P+GsJNEA7;+r5cSfWA?nv}J$oJzDO|ByQ-qZ9Cis8AQkc!E5 z=rL@!VtbKP9NR{ZtcD*@dqp;?Y@zSyRn}#%$&r~szt0ATWu(J@GP3B0!d|BC63$7iy}eXizki{VN2CXJMXC3~T$#1;+_UfA-M3CE_Rdn z&c5_4Ayw_Z=S@JJc)fW4{D+(g7q34<5#z~q1baI z41EjflQ4@tCHudr!Fs&jO>dP=37AM+|LH3emc~*iu#eX(kZUHw27@1YohEV-NpdK4arQ&Qhyi zo@^uUsqr87O(4dzow!L?cX>KqiPPkNIj)Mtk+M_FpgZhQQdkblUxB5qc^gcS}I$#rh&DO-={OZl4v&{rFQYQ6bB z8!@Bfa|8OU1a;Dn_+gOPSwb){dw}>upf>TL?G*P3ijP0-gB~n^d*jH z9>&_A_;pEd;>QQL=OjAG$))*%lm2K|ClU!CQ_%S*aaT)2*+%?w%d-Jk{Wt<$E|Ir* z&5jq9-K6J)ztY4q0GDes7p1xtj zNH#hIHEEYdk~eYZE%n5w8hz7F4#32Z5x7#8dAN_W;Wo`#T9wO{ zem=~h-cHZul2#m^la1jwoTXrHf!wU^k79F}vrK$EQe#I0jk^q_-{q4h{uuc+0?*S@ zP-G$Vo!y*ee4RYm@210YK7Tjz8PjWI<4FhpUG(XDyibRp0nD0to{V#&=+pPpMKS{N z#gCfuo4+IQxses-PIjbhbCjds3grH8e~i5nfp>%XIk&N6#4=C0YgS^)cYj#&Bk=FW z6lC_Y9B+TZl$lKAbuQu>z>z>`Gb_0aD$lz^ks-OThT*7EO48PtlXI^10!_g8PYeC z8tm{F%quVICgoQu(2YKogQ{^}u{s4)-`erVNh3~irO0>VdS20#ewU9@kiojbaJ!CddsHYBI?>Z0jJW$m z^0JMrS?{>W^uR*V*6>Hww&V{wSh;7=SNw;gENa5s^V&Lcu_DnW*NS#VJLZ)luaI^9 z1b#lN!XuEVPr-~n)Db2%7R8=I89RwHglMkMt10+EUf$0MUNUNIp*+j*C$~HTfBzx> z^bdV0`n$=SdIgfaioDK4QE+-q9xijds{=@$+B%+)3IO=1S^8e@uQBfw?`1ueT;&n>qDQZqeuTtUuHbn0L>= zclH1~bSE2%qPqf1dgw5Kyh3##GtbuXe!O2#bUq5Wdg|c$obv-G&dE;MQN5;G?yV}2 zuqFXm@rd5>#uV0=%t6vSOFsR=r(ENH-b3|BrOLrbChk*H0(T>|&T(mRDc=w=mCc3O&6IoENgksm;%=_GdS78>+yq zTl9KaP4D_HDLAo+xKB4{aa)-y%Z&cGk;8hs3-_@QJH92x%gg&7&8Xd?YXj~rp+1pk>RrPDdDg)LPOM?PrjkFEM?P0> zAj35ps}ktyXhC^snE8VXArON9=P0?J$XG7LdIkusUd5DP5Z@OPla<^ zsA0WhK*b^%I6!{T+ac7PZgR%}XZk#@GNQ^{@{A@cw9CV&M?Iy&v*lrUoomFK$#~hqeBK^o$)o&bz*1rqL>ipaeGjsC-d-)dBLb49s+}9vtB=5`?g2=5Vq>&GGEr|8beWPq2tHvZ^H@;iB zPLk76E3^;>YH!qCyr|(P*1y__PPc6+R)U}NK$Fz0uf}>u;ykmB7}=g)?uQCd|2=c4 zJ2Q)FZWy}rb(4v2Z+u#aj#HR#zJR*UhG9^&HzKEv4dx!yt&)$aD$V=|K7V;1BUAEAflX#3z0;2mJew7}>Z{!#to+bS_4Yh>qM07p~98%x*oY!tpZnXLMoCZynb0 zKMK)gG}oIO^~{gL&}yj>f9&ZW`9>*)z<1a_sv)Rn&QZH+Q{ojVj& zLNR?2=L*H?nZ=s_H~C_Vl6YOX9^QW?kMaolVhZ~1xyQ)zcnzBMVJ-c|h=-$yd37LP zue?z@{-ef3^6bVwGoZx|a!!^O;`Z`5*%+us80RqeI~#FwD19wgv&ZNaBSWitAn!8y zXk5?JyvZXADa6H-anikk2QG9E#ZBT!^@ux;(kisgTOE*q!zwJ;5<<^p1OBWe|1^R= zkM!tRy;%kC3Sn65U_$W*HgqMQv{Ei}isRMD%v*#VW$5!*H{-v)iVNILvSbwbxoyaM z9d1Bi8FF8EKmJ-BBZECu*mpGq*MHG>FO9rQ;&x}M#z;Tb@H?GC@pOfWeGNVJ=P(Cc zZIIIR^_cb{4E4i|_&Ujkn_P$36eI7rUyYlmN2Np~Vqeo&v;i|o%F=5tkeLHXA-G8l z(OQ)ET~pq_;jyx9nmcMM^{CGK>py%<2Yx<%|22p&`N-2-Gk4a(h)lkp?MmKXH%(Hy zCHZ%G^o!JyuRV=DNm?P6{EC;`b^!qqpi0XbuiQzs_b7B|{aKD=7VZ)r=h0u~eUgId&5BH@! z?&tPB%$*;~znA>SQoHEad4&2rtr6-S?3-usb1QpL^kvj262uI*E7ZK7O~<8H|I>&4 z|L_?vt+-;jnKIQfc%8{|WLULitNp6wg#W~3-!rw7CzKDjDCv#!-KSY{)RC1*rjmV< z%M{z&Zgr}_L_t55~qh2*HYar{# zxv!3k=(qeaUiy3@){@3GNbg1S;zXIlIrgX@M#;{LmyPs39YDT(trN^TNHI#QW&gqO z4Kk7(--BMvp_*%u-kf#dApH_J>!`AsJXmO8GSRzn! z)L;!W*s0fyCGT;H3Qhkq&w8^4ZxTG|lgxdIXXNTEHO7&znB_t3#Tw3(SA^oyE8aGx~r;a30_Yw$oR}$*333V@$JJ0uxJMJHFe>kJ3Kq*c3-fOM-&iPE# z3Fqgk=rE)$eeR`nIKg>Df6hkq!tb-0zw+}vCsO|^9|Mnv(MYSr=L_$lt<*6dpVpxU zzyCi8^gfr=p;l>f8OJc65lBX?&dA;v_WD&|-nSmLmYW82n?ZKYegpRWHlXP_BT6Y! z&~i7qizf}3`G~zwBMtDsZ$yEI0S%jx={SWQ)y2pKh@vlQtGV**VC$hT|w_8?OBN z9#%YR%2@~3-M##N>e-xSSEuLs6aA3h?Gtftvc7I{J)$7 zjPjIt7qZh6yrc`WLUEjXzU^E`+E*i2e!Nl=;+fl9rjm;5eC6#xH+k}Jec2l9DJQgn za;QW@dHXgt-#O`3KTwDAeu?}GM8uG=7)aE z zEKdrI1roSKf%OgZ#I2S?x^~DHPtM=tYUfEYFNZv1-aopF6L!7Im*f@&Vn3{bhbq58dfo>_DC)v++}x@Xxjj$F2wA&~E3PoaCN>^7Bbw(lbsw_#uhQG-#;@m}yGrKKKTkPF*ha6^BeEl|G6Ty$U%=0$l`~`Z z=}dg{&qVCA40;bU5J2zb$jTXb_L&_evD9-qn{l7ITBSYwyJP5kJZpw|12cZ~Kh+*& zL)VAY`JUTwmgoFQEA2Q$w!zP9cC5H*LtHts7m9GEbIA^U4)rUw9Xh2Qqt4LJSUd-# z$C4rUjQO)(Ir#RNU(<?cE+u{+zEp5dMKr1L*sQoL7?e5<6A_i8us zt>q)%_5L#Bi@!{o9w_mRJS6xYy}};8()U$>#EobmBMy?upjAo!R3GW!>LI=}d?Y57 zx#UUiQoBfiO!oAZja7ZcLe^?*M|x1;A|K{@%B6i?a;!MB#q<_-slYz>Qwof#l`qz; zJh?S0k360{c|omFJ+MHY^v##pGk>J^JbwOEz8rh4Krwxu1h^N-)Y1j==xUyf>+g&q z-ef&>qKD*?f>~0Bm`^!mvr571jlM|gIjfc{FgG?|;^>KNUx_@%GRYQdFkI1+7pTDo6Z_3RXmBi7L+`y7z4p_8 zm`ML3d)gPz2}j#G8r0gXK}?GXJP4&0xGW4u$AshiIt^~E4#$kb&Od^ATV|QPsI&6S{zk)|vO?5osT+7*VwQFry$fadv8U`( zQ|YmgxWvQtPUHmGf5KXXjLA zOiky#lS{_qznM7B@7et?wV`~@s{T;pJw-O!olK~2u?N1k8R1UszgWfZ$6uSwHN$_G z4L9qP1$NCwz8v+fs?7cd*%7;g8S+x}FlssDx=($D8glS#8%ExwZ`fo*iIbdvWiao} z`=$C*cD;YGV{cFnoJ{09PPE~3v>jK-MR}6Xx#o82>by^jWY{qHBsIwoHdt!g(U^M6 z_x-$=`L%(<8SE3ysNO$+T4OCCF7@Ep{|D6wUD?mWZJhRw{Q zF)LN;`F>ecja-uz?78Bed{U!CncOBtV#(1M%=utypH$IUlVwO5qr47grY@Otx@(D2 zu1>Oi3m}WJOrjW=b-YCOw_mvg2`y!mdq|R>O_i8(*B9C;%!2k*BIZ4{0~OhdJIK<` z_d%U}&W0Yahmze3Pk6p*)Lx0nhm~+y#xry(bF^oenboLJ`Kk(?Dv+r(%nwhl`r^<= zC02A|mZl3kKDRR87pOv#54)(_G4pjtiGJ1Sot(tH~3A;Ov5#g9DCj@KdbP85pw;8~`U4l$lOyeP!k zRY)|_$${@QpL@LK6&+_0n^Njqwb`58gemeA8z`bP&9eKX< zkWw%Y9(_5#=oQ*^--1pHxySrq zLA5w~8)N8?9Av?+a#l<}VZo}m79>);nzYM;m0hgx&~e{M%^~Z#1snGMKR@Fza<@yZ z36Qlr{N!VyK$*3+k$fAi zvWmXJ!YE)#iLa`iaJ z-|&<7eGB&3f#MX{Sb~^a2;JFO-iHT> zn~O@C_ap;x5j`M{%vc%BpNHDKDbF{f)Owo$Mnw;yFV&Ib2(_xepzq$A)$p z=s$?uuM3&*pw|AgtC<{xOcWZ!jLJ4U4#t0gzGM!%3?%!@jqBAqA6bx7UtB->NKG)PEu@&~D-7Ju)DlJnSqG}#aO70e6AF$W#W zKFkU_Xn3aX|D9*w+4*=*NBW1 z>e(}_cs?W>HQtgZ`;|SJ8a}H+$-2s5kSJC_6&928zsj@9Q zRjf(L;;v7YzmX}@mHx%@lbElhrvJJP*R5yls~GK%+dJs@Y)>zvf_eJN)CcItSp1P1 z!6A0%oHMe|)rcw6>BVTtUgf|P%op|$WpQ@Uls{82pS>IC>uznu*hTcCggdDxlKs`2 zy~=88mi6XS&om~Z}B)RC4BH9eUC=X74*%}KVzFp76R9~0Gadzu;A`eX0G}E4Cd>zmip|bB?`4ab>qfoQ)R+! zqb#O=HKQnVzB$Zw#2ICGGe0=unV-EtpUgca28a6NV=wAf*-?1YDH`qm<(hwyj4SGk zE<>rQdZb`y33@%Pe2=U~{NB&kDv~*as@eD&OCP@73TOJ7@_&=L#r5)0HD1H}6l!12 zwqEhQ+G)1rVrxzy9lDGuYh)t1cK zPs|}k>hYv5dlTF<5i%+hp6BW7P9(3E-s+m%&$s7Vabj-{CRo_*{Lzj*>+SFv$@NU< zCz_58rS%4K5hDVmDf=WV-w%>u(ezYSD3B9F74RKImhLTzA%E>{+f^oRK!*v$5nz=DHeEOISg!FvyUfa|V}hn8|}+4`pB`e)6?x z%KiN3mF$^5%U`cE%2_S0(FkcHWn) z$Q1TZ*HBK8aqVL6vzSK&PBe`q?~Yw`^VuO4xyL&CUU)96F)bbux%8XH zbA6{)kyv2Hg1*dpEvJ8w=lm%HayXyh+TPucDkbP0;2GxNDSuhEzmb?M9`ZSd+{!gU zVj4^DPrL%>emdc*8$I|F6&O*{8P(`RwN}<(Tcid)!^2UwcqIPat;O}b)NuH^1U`vH z<5l#Abf;D`HxA`$==olm;Y8-p9=O{^-AQ)@VDiKVBp6d8mSjS|e+^?+<84)ye-c0gY3 zKqV&d+33HC8Tx+YMa-nXdz}t9j_6?KUfuSd>%|}=)cz?LzSD?7Cz%PN)*9c+2>VO& z2iIEBEQEbEMXcEQgnQ&^*?3N--r)=EQ;r}9@u)%_m_jb%5rw+NQ?8#EIs2@zPr4;1 z$(L(9e`Oe@{Apht-l{~ozRU^GN7%E13a_U4;Y%SMylgsl?dTA9oZiYD9dw8IoDOAI z&nou9o#jmOh7nz<`v$9+W#Y4W0iQv|>0|u&Dt&v;$w}w_dc}6~^|BRe=gsuw)5my< zGv3ksdGI1dMv%Gxl^l>h9m)QSPLXT$S!NChK%cVoFFy9ghu>VgnyWBzl`lGZGRxIf zhXcR(njFyKrAddRCDg%dr6Po0#_PE}YrNzQ!L{>4`c^}%$7`bryxdhJAJ7Iy8IM?7!NIk#V)j5o@!I{W4PkyL56%@2<> zO8C%c>31jq8`k?{vx9R3u2;{!Vz6jt6m~X^!4mF0s<(=Px)5jXZd|*leLJY1H{!YG zKORTVDCPmUhN@Rmvz}-{=~(tS`dE?Tt5AQ`E7UzWyL4TkP%q>D<7X0imU9f^5wu^P zk>4beEKl6XI_A&wG{+BqyU9to!VUp{KLoT?!8urkvi~rv@Gc6k=0!vIhU@!A9q)5` z3D?m}xyXoX)5!WMYNU6H8M7P%44fZM%VHPOTq}B0BVXxaWtSNL>*b^_NK>e{^x&+D zKbP!QsQYXoKZ!ZQEm!u*_|J**fY;6iW)Ej}OqOG_=wTi}~V0f0N>RERN~v(^<{_ z)}wB6x+XjC7li$f|E0wVa_(};NwmAkl|Zg1{^4lZlfL&s={Pyl1_eJJ!ToKI6=gId?{8Zsz*Qz?b>5`xi>^zEq}fXk{^K*7NC)n_|PfV?NUFa=v(d4?}*3 zSUi88fhu?2!#KcKJZn-%+(G@^v;lqVlRL(Jy645(a~1{qFv0>FJKRB!+O%Qaju-75Qa;p zSZaJcZ|<{^o#DdXbp;;XV~_TWI6O;ZKQ-86n@unO-8>1&3Bx-2zjQ8UoZw#FIm|~A zsi7X=^SpYESRAjJfd&0-SVX^7ZpI(^{-qc4O2y&>^|f9D$UPk6E^on5|w6CBTVzQed!T=XDc&zJA}VHaub#7?i}?7KoNHf^Ub zEX#)Pzq}~Si|9%ubu+0ZB)>71u%qcf2E)`qqIo)UOHUsi3PpN_BFCuT^l zo&n(O^~Qu;5smTG1=w#K6G>I@t? zZ^LqOC(D<~mjaJ)tfkLRj%J{tjoR#SSIMFd63Kn+(HF7!Iwk{|-}vw4+~8f~d>PB< zM#9oqc%I9^_BwWS^{69ty?C8$WS1E4Bkyq;Xi}N`p!2>GfB28Y_S7<)t4GcC8RXB} zvC>*sR#g8hXHvt^gV$~Q68!n8i>#aHA#0B~(VNCT>v4SF$I+*m#M#WMdh*Ud{vhw) z1DVXc9LwO@*3KMQU9l!R z6zWxJ)*#F+uP4=$MmFK^DVOXm; z1P{zWwNf_Z@ZUR}zVE)g9=e{|Kz3gS`gHh@=k6wR{uW5Nd0}w#j)U=31{x*vv zSC;~b{Lu^5ij#kO(~NIJ>e<$O8Rvcn^{fCw&KeU;v93)rqde<=A_aJ|^H+iN$^i3ad zkzRfUlA;d7>PNAdb07oHH!~NS;wh86A=*~ zL}|$V(bVOf?Uyj%DnFiZ+<`-G|K%R2H@oYw;T*Ydoh)eYPM+6+WGV5R`<2V|@r^TJ z7`4$m=N)LqT-`}>&35s8853&2Dqs54m{I&tZjWqytitBHI_3)K58~c(lBWZ+WA@02 z!OYvGMkB_FS^>4vsv{KYX)f&1*y@e*g}6VQmW!yV>D22M+%tYz())!-ka^Iz)PvMpYq2wpp2a})JR)rb-cU^zO9_l4l zY@f$HXnW2YzWR{s7fpN;^De3M2T;p67`IpaN~)l{&3RH~!L*JY_NzNtu;=3XWIYY?};OpO=`hs^2`m=s2@w+t{S@b4Fa;SfcqsXR76+C^?Uis(A2g*dRi|w-!X{-Qzc;_WMUqrnNPi6bnk%(p zr_y)wH&3yjIzLh3&eI21Ga71@0dJ~XFoZfn)ka2U!F@6E#XMZ_p{90~J~ir7Wtt?* z`KmscyC(|e1{h$f#`k?PyE9Jgk%#T60j-XP|J7t%UPxWPIJxosITye4MT-$pSl^cK z`wI(d^mE|&0QPTvWv7+rJS^w?zSGHqe+JR-c5{#H`bDA|mG7E$Fem!s^pRtk(R&O19S`27; zJPY%?E7X=6MsfM3L>~=%t>{y^H6#n)8!Oa{&L@fGy%PI*CbPDrU#uv7$MpZsPu?Rz zHGQz%MTc1GR;`!O7kN>kzWUQ3W4*{vTgncUk9=SLdp$=nYrAN-#8o5Lg7cO(2iebV z&qBFP}XY<&0M3zsm?-7G#mj znVGOhJeBM|`zH$dI}P~JfHRzS3U$mhdb(zi6*7qV>)vGl^ZBrr`K1@^i~l*E{K^~i zu#)=e)d+T?K%tHpWt66`d{LC=oie`c89$PRv|c6zAH!p7}h{^Ez+L`OgHC151`A$v}FQ@R-}w6U1^JEiAbAB?6idr>*&zk}F|V&`*gS%TD}ANe4!^Q-{+RkN968nip zU8{y*Q17&aDuvVgIBzpmS=K6T$IE7?4^QkI(qMqr)Um94df0`akZQ~Jnc`oqO=}eL z#uT+?cgVa0<ZPcC+SVQ&n`$eS(=*iE1WPbZvD+vTU)}kxmk3} z27c>J?-~?04fQMED$LqC-RF6c^zq$Zn)aUgVw(47uQ*jT%I0>7@`Rm7Jqo4BM}LEy zy`CsPwj0F3KEXpN3|)-{Zuy)P2_QJu&Q+ zF2C7V{V7=vv@%FmQ~tluD>=X@dm5yQsbrEQ3`vs2Hp%jgQE+l{hkh*J&bshf#hgtW?44x)T1!lu&ZLI^^SrV6t-ta&Fyt zDm$W$N)+wO{`Sf$oLxtjfH!lie4d}-v+sbPl3XZuqbsRFKl4TBPfF}o`{LYvB@89` zY(K5UW1i{9^Y17d${vrq%y!P=Oxjh4t`Rz<^IH4yD~b$oYDC|n(S*LlhwaJIxf_kT z-FW|AB8!JU#Us7B=I*4ww`nvoI?^Y;Lx-%_)U`L0F>Q^;_&YI3aPWHOvu|{R7)+Q< z?cKuX6g|FSBXoH5g!jOl82mk`L$Dj!kiOCIeZbBK-ZOqr=xOiBOf9eZliQgiO`tb= zz5#{3jF=H)K&jbAOf5!6LnksDnljT#c0|ty)MGN4$DL$kM;K?!Ey-}4$~pHeBPKD! zQM{HBu4XcaFVG{|jvmEjoK3%Ek3?PeYYc<~nLwFza0wroHAGGRz9^MeGMWY{9-#R-C`f`8u zD7=w9DaR}rwloV(66t4jq7SNzw+xNgV-f~(L-+d z`%2z#cQKr*CrhkK@jUE7t;tL5qo~DqttXkSJ*C1)ABp#@E0s_C%B{BaQdL(8X1L3V zRQj==`pBk-?9H{)w^&e5hGqLn)Gl}VSXL=JyLm~4a9o86sX|ugn86kT*zsxQ<>-BCS(OvWXG*ff!Mk#Fl`@MK~M9g$hAD_ z|4@OXSqiAu7f9>Q`I51m9>;u#N$i-Vkx^gc>{V{v-8x{@IfM@HO!4H}#X$EN^xF3hI> zU6WeLP%Yl1vA4QMIM&zEvbRjjjsXqE6(J{a7W1WQb_2C%|Hd3WUgVJrUrCSU)MHjZ zBxk5Ny^C?NSg|4w(>d?hRGqV5S3QQF(qmmmc1h3R?>RH?NncfLV?CB~?$GQTJ4Bkq zVaDwLyjkqs$Y6KXXzB|M^k}nz{YdNMV7||D*aR|h9>R%$mQW7!bP+a`tjAe=68}sm8;a3Sv0^^;5qc|H?Wx za6F8ij}~?`OtrJ;nC$nk2 z50FdL1Ebdj%EYHiNxWTCmX-67uH);;p_fK94K#!`pbFpn5wSw62l~K`C6Ck#&>(66gN-4oL`QQvl^ zuhB{m@<9bGYn%`;wtfiAz;d9zxJTgSq2 zX;L`wh-dg^)H_>~!MKjy(80VnYisdidj!TRG^kOX^F7{cTa{#Rz1INK!%^*#7DqPF zPt1EN^(1*K55n;;H9KV|etc6Tp5N8r{{NnBaY#5Bi@ec# z99Tvjc>#Y<9jPnt-<`YocXa1mYZQILQ}j4oo!-b-_8kJ)%eTZl2E!@O=Ba}R_VRoFP{`G~LR=Zg0rJ&c5_d$azoRjin zddi7kZ>5G;%Z~h}oYS?YKZ*Cy9=&#hzTp|R|M3sEZD$Q0T){u&d(RK2Tbx@J((L)ekWNE> znq0qTnkI z*|=-^oiCZDmkX<=p9pp{O&{$M@}x|Da9G8CY1`e>Os!rYF~t|ZmiG16YSXcOqtiBO zZkqnN**twl-OncNl+C8dDF;J3S7>h1RoyF%uO`a^za&YWoGPn!8RX#PBq_TtNlY#1 zQ{0~*#ix-~w32;jedrPCZCS*a2lX_Vj9Q)ST91gW&1U*9@OGD`221%FbcWhnm}yD}9b{mAJl_Gs7l2oZ)`YzJpo866{L|V1~t0hbA|5_+g9Y^EL|hV>+mk zxEEYWFXKZU8hOW{RCUfkgLRnQl=Ho@^g$LxVeCO>Tc+!f5v9ZGU1T*Dis2lXXYl4a zoaRi)dXe1jV)QN!kH)r}(U`Y03YG#L{ZY(cF4y5>4%uO^$>G0az^!2RM9*NB?_UG9 zIQaVrBMy!-;@B@E#+4vIk@wi~ zyi=!?BgxzkHgJeHSp>~XDlnY;!lbbZ$S^H@`h?@+33}c4Yf*C|y(%O4^KdV7;T3ti zd`_SBiN~{xtW$~vXirbx=J%UuQDsNrFe9RI2DF zOWp*@^kFL2+6Bt83kqCaKxSlJXWVE}2z9zSqa?2>oYvy8J`%luYY;&%hO$*8bgv?z zxspWy&?bGlDaB_2`_k|ktroklJ2M0Dk?Uw* z&Q#l&k#Ot`zWU~11^1e-Ds!K@CGt}T`QafW=zvmJDJwuWAZBJ}EA z&|&vu`c;xs5HgfZ+m`Gv;B)aXpPAn$q@d1J`Yq@InbSBMk={HH`|;=E*)*h~lRCbZ zliFFUP{+QcZ*MNO(x(o*TxFEzO_<-DwNLB=66D>+6lt(vpA2^Q$Bgg3C>Tr~f?km8 zZTv9yT>zHTYcZyx4l{pKS6su)@3KUIPtYu`O^>Mhf@=*=#Q$3rY1Vf&!&&iLa%+r7<6MkveQ=s z^gi^VE->K3Z6hMMCcNb{c`DhA8x1_8`(&eOC$h=5a8^;=Nj=S?P_NgsuaiE9u>+Z5 zR#8`fOF!&ldN8ah^3{Kz6n@P8Kpgu+W^k>p?}veZ{V<6?k2kgPoDF`sRVoInE5%@2 z{TN)X6T>`e3~o%1L3jFhZkvpl!}rYN3waE|WD#6W!RDIx(7n19vXUIK(e%#0wqW2Y zE1v9UA2&U)F4XpiQrC9xr%-#5ljg`smA~gxWLaveq*qRn1;?4!ZImphI;qf(np4dm zHOX^pz{Iy;%&36=f&*&KN{jHUKJoL9TDWX z(J$D5d;L?~v!}8r;h-KfGwI2n!M$;7a$#p@!btz%2DeO1{%oeNnLNgx}ph%q@9OVAG<82?Q>Q-0&_VN?;aepzm2FZ+#O8Iot z32o0R;MYol_He@Aw$AVm>=$=hh&MtO6=Ld*; zYgcKI87LuJ8cN-4FR9ltK%5Rc;mZVv#CtiT)kkMEpjWS&pEGJ+3`ayFnfq1^D$da0 zPbm8_m^EF+nS0B@ahUv@XEVM=gScKKj-_^ykco%C&3N4|6DP^8%w-mH%Xc%B3vy6U zEC-voRuu1NN5pNO<@4E(Sk*_4Uh|QG>x1Mbxt)Kls{kt%%Pd7l(VGmgDJ3*kZ^JTy%EiO7VnD`?S_u{o!oT-K5JeiH$`?y-D z?abFBwGp$d;ap3X>QSvJ*_9W`tU64e%5r8+$J3WTmwD2wHq;DaZjIjDgO_sf@}3<| zVPrzbr^>oVDdI+6#!hVVOva5KCOx(OrV)*)0W#9EvfBGvMsE~Pty>(=$oN^6> z>JjIchq;cn=If-OX0MEakD0yPeq2k-q+k)xKtoR$kxT!%d$kkN?J%1Z>e76jZm_$cYK2rOvM@#N`_o%ln7xieQ^ia# z!?buMUI(dQxXJ%jxHQ8BoyWfyki6ny8}Riz_Ynt!SD zXVcsGl=H3&T({I#*xa+Z?vj18$BN?IZ=7%Hqz)ZJZVRs?U#{zKxYn2L>!d#VIa#a+ z={>#4b(B9-s}4q4M|M(6oj;D=RwAOiKj*W4P{yd}Kc`1FTE|XevK0nJBhQVm%VHhQ z^F3^yV}v{R8{Ii`2wu&3Yd{J{^P0Zh&dRwjJ)WM~Sg&R$Wd9yy&2cm|LbQQQQ2RH*Hw^l#6D%_dVG$sKl;pj?C9h!RYw%ar)e5Iz05w- zml^o+o4O|R&a>EeT@Ug7hWcpFqb_>i#6!6CKiL+ zQ=g@ut2=pivt0`00{tveK6;EfpMltKZG6~C2vvS^%!oO`Ydfz0dj`8McZH>pRC z;rZY6WAf)LMLqXM8EQPQUFFo}T&eBEY;!idPq=PWiMQcl(Yo>`@voG=K;8Wj`()?v zSy#(`cZJzUmHbB@Um;I$QXFceXJAt`8=kImm$FR?V*$m_w(!Fh#)Wju(`u#b2% zwY6P5Z!&K%Z)g}E{bp}(@l324L}vd!Z@E;QJhjeYP+g40ITL+nVAiaOr)08Mx9H5C zuz2(Q)Py|5Z_HSnR*E$-SJH}vBWF-79>&stx7dc(PdKYNn=kLm(m%ML8fYgoO8VMx zt`+;cZvB-7^sx@##7Uzw)bF-hqy&D+b&w{WEP{rI*)K#5`M0m08bSshQ{TMa+FN$M$P@p{WK{6)ozN}=&6$CyF-0j0Coor;%wFbK zu~<~b4DIIk*fpS@d?(-V%#$z_s>Zcw6l-f zU)(no$X+e|bVXuOD1tflIrQ@;(eXx17GVB$e1(lhb;Me#V8o9v*Q|+S7(%5#Hi2`ErSSNRRKa2vwUg;Ue|p;(_8m zJXc=Fy0Uz_uoPe*;F_mg}H;`6XsP%KV3 zGO)_QUZ1w^vW?t^V)0?HD*NG+Yob=eags}HiyHpdoFw4%bT&n&xR3v9gfs1 zkiwkL9k0*Mvv>3l{vg+KjhEE+;GXN?Ww!OoM9h5XH&=WYRcVJ`7&n}eW0;%=vjjq zVEQ@($-O{1CwTBW@5BA=?_C*)3gs-Ss-N_vUvft|Em}nI-!;X|t_d4@>*~m~?+VU2 zH2BAj*P)H`fm77nJ9$Vgvf;;5+sL0lK5tX{$`jZ>w#8lS*O-k7WZ&F{Sd4qk><#bV zHOX#LznX$PNM2WsI9sg7=PGsl`E5L9qbgS}chw@jv>uDUvk$$r9lw_tWrY)cQum{9 zhv&;?n=RA}=%1RKBwUh=g52cVe_%1S-P~l%ZbRLYzOAO^ zj1s+&+DH-h8aFj!%>e45-yEoOB2iX)vpe#AG(v79qgw>ehw%<(fD`4z1r_cxk8%2K zGR8$&;6iO-gTo;AnI);_L$APM10pLh>rg_Ww(99)s-i+wRTL)AHo{xUK5ObDl?$iJ zS`YeVF&b2-V5r8&OX?5V@f>B;zhioUJN3ia-@3G$&neT6M~-XF=l zJoiJt`SsJM8l`1>AN=a9!~MqeC3WZAKAwBng?r@ZH1fg@%){lNP^eRSCCYK`Q><(0r8vUg zVQ2pQ%xuK=OOgxZ=(XePTv$u*0=45hJIFLoNS36H^o0!4VM{&cbt;lWM_=CBrz!HB zvx1r)QMk4u8E?O2!Dlo3J2vc*xB~jo>gzBk$%xRxWG}hVk69-{rZn?Lb?)iQj58vp zFZtXF4h&7&E&ly{aI#Sp>YicdWH?z&l@#iPA_n<;*@v?w`VH^${h~HqJDGjNFh~OP zyH}6QL%B9aJYP#6-)QT9oiN*Vs;Sw zXL%;jkOj7PJAEyUqVX}3Sz5l2pOgyqo}68xDyqaH?yrOS`hQtKZ^S1D)`#sCiSxmZ zkJQwb8{itlp5L;}X>vC6v$hgzzDMC+9<_Q6b@R96=xGvVO}HPNsaYI3#F;^3awmD6 z6ep{G+;k-ZUy;>aiZh1k7Cch$dgx=6o}h--jXcfjWE@c6@9?VteM_>Ji~h0#8)p~p zMhrh?A@@k3E=HeEZf_qPeM#RLIen#^$d~L(&4;s|TI2?%X6dkoGYjLCEbO3PZ<9S) zuJ=}9Ri|iFh&Lc`D*dYb`VI#AG{4a2+n>E0kGLltl7*N_4rG!$ndHpQl@HN)zJdO` zUs>2s|LM}mB*GBVeZze%63a%F;Cj8r1FoDRQC2K4N2 zfvPTjWcA2@bWvgSa-Mb0GaqHP;3+@8xln?5X;s+%G79axFei@!I{#}zSt0$$K_~j;dRw>5n1l-=!Z2W%9xqtB(g8N%nt*ub+VvuF=m`k?v{&#l{grw zLyKw#Wa_g}jJ`!(6lZ$%__|%=(gU;ikQKK+@%BQn1mDh94qY2`7%m;(}MxobW`m8M$TR3Iu?q0A|FqStJDxhRCVa2`fK=8ks`R9muFn*OUqDtWAlW$BsXd8-$n+lMbC zN&x-5$xY}18*0GB;QusVYMJAc&NU;W@pwLci$U~9@xCz5O_0(b z*#jOLg@)~nID5l_W+N2p!LGcIW_qKcL5HKO$zu(rAM2b0lMfkWYc6}wheadk4Y{|4 zt!P#Mf6rn6KYqp=mUX6ywKkaUeA$s!pkCE-SIdzGzy~ zrg!?TLW9%q1U@jO81A;b(`cosO5*_2$F&1Z-y}Bp%%jff(ZTgiWu^{KUtd2dWYCRq zCR4jEruwnGAIL@gGBQafJU=L(dl+OvcCsA)nkWyirpTs+336!TJ}Gcck~K})@x3lt zf*S0X)$}z#p1Vf^bIH;fW0aztOYdHmC`niM%CLyNQg%U-RKB}MUY+3gTaqMWrzA_* zd1?*RJYH5zl%Kl|VjXOda}AQjXU0CM#_Zy9FN1WCpaSo#AAMst$a@OXC}azTn3)&pD*&m@fk|wt@XuR&uA!@ zM&mm*p_WIZQAJCCxsU*E?%ya(8Bd-f*YvxiqHvL3SS>Xq zU9A`_YZQa=L&;Vc5zUSS<{iU1_tw+%C|qYak8WNq2LJNc%G2gi(`E0)U>&=obhy}& z8P+_qSeKDUynr+9$DHr1pf5a=p6E~P|7&HyMuib+oUg2%$LG)nBVKXdbDp#3JJhZm zTmu65@gAj8Q2qhu47p@Daz^xb2^rX25A~l7@R(*mXX-eMK<)(BhRwS;i}+x~l^I4X z9Zuh4X?6SL2#m~Yiu$e6UkbqV`JGWofN?8D-^dw-_|>swn9ev&NbQq*LwSm4I}kn1Qb z!hEe5*NI-ppINxZy~>?K%rQ5!;O!aS~zT3bC@_0yXvDI=B^*s+M`OaN-^mUg}HGRcexvtb9mvQS$Ul}sE zo}_jNU?-59l-$VvfXe|gj{OMJ)7-@rLC$>{cjl8C|uGW(Q6rVjfnf2dhcm`Y8ybgl%vD3GwX3cTE!FP~@SN~5Jt zxYwvait+QkBA7pAANAgH`7)xv6L$Y8peHj={1Wm-v&JDqiv5*)$MU5I&(rnn4jFcj zJrX53UtUuPqu7f(ZHN>5gz2v;>;$)Cxe_tL8I`*#@aCsOE^i9QYHBj?A8D~+l?J`n zhU3Q>`V76aX!ApZMu);MdVV+}cZK6KXVbF=hhq%SXzF4byxGDIK_B+hBLC)T5>B&%LFCphDj#kV}UW-HPz&OlIV?XpbYBK+w8-Fmv`6LeY>6eiKi}JvY?-cl)L+HkfHCwhI+Lf6O#jvPICMS4IZa_bPNXu^7@)^C ze$C_OWXvVRG4sOCrj2n}wOY@4I&*J@%}AT4$dlwDUs?Sm}2I&aKa zIx`ay;p_@oO&?YWGiBwO^*_g+ryTZgr1I;iM_ryyrVVwhfj#NZ>R=}4+YCEBSoN2Z zVc&$zxYC&jtz^b^&rBpNq3$#}6Q`-)JgvqVNzqJn>}bY;YBscWE40qYl zqZj!})JSfGk*B}Fh8|~aI9$?>#m9JVuSM2DU-E!AqKKy;sL9!gEZxrg8gQ9x&dDXIG!7%n( zhxth7I5!En*jP*sUzvZ`Uwj`1NQXu$DKtbWFVnoFprx18ozsx{1b0b$7$k>=QG0k$ zU0UVWWAB-}bR|P*(F~Q`Z|@@JsrBUGK_4k{xvmtM;wnz_>dD)C^`!mbda|*&mq;J_ z9KCsVc6f?1(noeI@f4%dM;cD@5Qk1B4{AE2REs=mb%@$fP^FKT?SySos{nE?f{72Ru&-4X-VvD;&} z!VGpNpkgaEGl1O;3@UaUrR*+dz)mE->wMnpy}p0I`vVt84h+NdJokO?z4i*~rpvwb zhh?lEl5_mAfc)N(oayao?~g6}1F-3U7Sk4KQM+v*4i3@c>pOpJi2n~8px5GdevaW> zYitk>G}0n#VgSbPX71OyAjA#{#IF@vbm70{RscSAXC~MSu61GoS>w2dUeOydBMiZt z$TMVLue|(Uz8rHj#zdeJ@f3%$Tn9@c{+Cl~oKIYE4?QiehT-Y{FeKHX-t;wjiQmHU zOh;~TyKu}L%v{W|5zvhxmbZraom|KLSCG3xET_%{dV~?XxzwJ%sCy$YsSJHr$)#*t zD+0wMIb$ORl(vjI>KPUs=UN!Eot&0Zskm1o6(OM(I6Y%_$Z&coM$kj-9`*Y9#BT0e zP;nsVtHd9dldrg^CMZbGPd*0M-5zpjJT6+$^$fMC?QHP5M8DD>e7>i0&bP$|-ziqy)=~?)!-hBCxgNOQ zIzF(XD3rb(oDD|RBo}Ep{YzblQ@*jG=}mrYr8i6wzjnq7zYgREb8S6P(65TT$5A%w zP}g(q>|_p055BG!*YgP*Iy|@GVhR3S>0BteRtwMC;PIx6*|NJwr_YH;I=S8{bKN<+pS9ST}#*GHoqgx zuf|U?Pc7FrDPl-(bJ3x4$tRlDN$x(Obn>w!wUaLwI3+JL9WoDibkRJmW!I!9lUMmD z4x!W8;oaL^t5ZF>akH8}@6%(=p?y}FI}h{i7}GC7(muyZhACcJwTcscKa(U6G05OS ziK3z=@LS_(xk-)QO!_(9I$)9w)eQ2hVXQdaG}1fOAc21wCGU$t3^{RfZ%4Gm)iFpY zJs$hV9+b)K%^E^xuek?B^Ezb<88V-bgV7+AE1tA1M@-p z)6m-`Ujyhbu<=gTt4aGn6F2jI@HOK%Q37rv*ex_FlZ|4xgFHD{4(P2 zJR{0ZWp86M!o^~O^DKVcpda^S>cf6A6W|^B9vLPe#)zlHPP({LmqyMek##~*6g!O)Q?AL;um)OdGkyY@r-yp5#n&|O>lFe{-rdrnLS4A{*{3# zYWCRdw`L7u{upb(T^-qbIZ%hPp7X%<)Txvr@6a@KlQ?YrU1(gik ze|U}$38v0rYYKjy;(oTD>%M$0B0rIXLHu_)*MIAOnHRO)U6wLyC?Z5HgT8x7@E{lI z6lpJ8IqTck$&OrE`f@K}PUp-LSny4O(PeoKybMB{z#!CXr^U-KE%{{34ffnlJwgO- z4x=}9GjbWTS>sF&$GNBUYI;sA{SS2$OXx$`Jq6#mhtB2xHpep;6|3bUNo-j1gtL@E z%oRIAew?d^So2-PEv$vy4EKyXb*?#1#m2haXW_vDZW19`Tl= z4qj5>iK{55Dy0!?kfb+u7*UIu_)l^y&ojGoN}(wG(UY+xXPAcq|L2pohu5fbPoCeb zNz1Olu==Ndgl^cf56T*?-(SkC~=_y4H$X=&ZEM(niS3eb(A9JS2XQynVTzqDo zmh+R|E36N1lmC&FrWQ||Qd}E)O3!qqDDBizubUl)k^^#MvmJK((NnWgv8)}d!2U=- zj9sFItpl}7*Xf1wJb-zSoZS=kC6LoiyHL9HE>>X zgxKLz<|@6(MDjL;rtqjjbC0tRlZA5^UwRLQ7h_~^qnsXhSW0e8kX^xv(xR_X5{Us{ z7)L+j|2P=&9vHGz4WAz>Og}=8_cjkA=#Ike57RhBC&iR9RDX$aX%XDJ=O3p8w7AMGn z8%BvsikF4&K6Ly|5!HYbQvOlt@Az(H__K^2?XD5j z7O7YL5Vx%CT^2^*&Ol}>Byo@4#QEmcaID`Nf&Jv5edO6S>JW8J<1EPZOo5rb z@~l^!iE46Da~;pqZ=B=)SG#v&9j|bcFEzd7Xd9lVEj=XjmW$lz<0wZ;70aN(3IwoU zJluzT#%I)GljFujuEJm8;)^9Bk+y=lie}Syj{qF zUy+It71>L0A6&G-La)6PEM^~bphO-*^T^kTrmwrR4KC~z{Je5ey&HA4KU+v*xVJnj zQpv0m_R^!2QcBlRU4V{D%s)b1ooa^3#8S^K#bn3#cH=9s8&@AhkVXgHwEBo zPihnPY)7zjIF_zpo+!`w`Q0L*CJqsJfIUwP`=jOb0IJChiB>%4|4^%Nl;>y`Gr`$| zRCmh7!!n!;A0gkpFExY3Zt|?Dmu&yrRs6{NoYt5=h|C)3`n8z4i4r&;Tr7G2eQlOM z9C`-vZ)dMLB8am_@(#*tajYN=qu;Ri+Z>KJsq7nn@GK=C!MHsY?G{}?M_!Xhw=9@= zfb;Pae2!Y@qE)S2Xrrjh3eDuocA9j~hkkh~G@qBzbJ)uyw`V6xJ^EJWKTeQ@-t_X_6eD4q z)!0#2jU;02p2K;zHuk{6vhJ8VmmKp6p`5Ale4newxaFbftO-TQ?09tENneqRMl|_q zz-u*i^2g~X&vT-SJ^AHBIlt$7dCxQc{2+cFsnFcwH9EpGBa-iDM^}Yr>2QUnkB32K zHcpgR)KUD?!64yXVkN%1QM^m2QS*=o`$IJ@g;Dz^?C0nM^PSv#Wf6O}DxoNHLDgP7sUp=h|*~(m(W51=r zLO+}#{=2`q1)Kk+-&q@#^q_CxmWRx5of{6_&=e@!+Tb|7sr=(yBt5^7uT&-s{ucHa z#4*E`G?bPj^X18QEjrc<$3>oT2+BbY^HtAwQ=qMvKMF5Vqq{MMIz9R`PHrj(cIQjV zZhw3U4ad;ZDcJtUirr!_6C;S(6aS8@_J8X3RR^tT?e8cqwF{+Yj34@Yhr?|J`wL=3 zE;;sM`A30uKK^(`o}iGI*SxhAE0;LQfVd*jt`5MM4LoCJr{MC@9D4jXh{|LKwVN;N ztT12!d3hD7tA(pf2r3Y_CjO{)in!ab3wXjhe8)6LX`#xO$~u2s{J0JGXIqf|h1k_0 zwUiGmkQ$f#5VR!>;V;Q=QrVFDjeNI@1v2@K9~8zgl-ZJkW4u0>u2G9XEx4ZghuDE( z7<-p|x0_aM$aR$IN6B~VOy1l-VHh@^xv?j6n8)5!irW@T{WL%HNejcpS{97EXT`fS zUefVLp=`1Q;4XP~?SCdSi;F&JHI(wFk^(_v>7Czzz6Gje%&KO?^Z*CR^7te6aqLeX zGsm`X3T!*Am~opt%9{CdGLU>LS7M2$lJRE%c}C^QKecC0PCj#@^AFRCZ8SGh)*07>kfTJAz^;>GM3_vq2wOpx;g9@*cq%#s>lLAfeChg-SJ0A0Sk{qB$F6Uo~R zO+gt2J@<1QW{xPsz}5rtrq0ne4e+C=U|-a5{_m(I4sixrF?|+x2DC zmI86!7(k9QpTme0G?-~cp4LsyZz+-i`~C2IAu}u z6F#4xaxi$EqjXGRcECk?WVdB6e2M(NSn6boU8UVn&a}uo8`LBmKIEO+X~p63Dk)Ws zzc(%bk$ag_+>AaI0n}b@Qp+7aZ*!*mVkh^3vU$n4nq@^jos)Q_{+3y3zQ{Wk1_#cE z{4SGs?Cm6PIg|LZ&liCfu50pnyFAN5P#u-5YfvQp>3ev;FboeDreHO%=e6Dra`1DJ zOlr?ertmP>meaS?9FoipA(pkCP2yFr+8L`keRcqOY>aq3???%0Tpju{KwZqR$X0P%2Noh~dfN}JFpW_O{WN4c))d9-G=t$eYdK|eWr2%265)`%fW&}SF9L! z!A(-Ae<{WK^|W0CR`I#gai7%sHD?}}g8pcJ*gY%E z^2F^jhERXw+e}^!{v|In1JI%;pR3LmJYH(WsM|*QKptOuUp@DK&dR4}pfziOT@HsN zk>`4ZiaL@^`l*qBWU0q9ko+d^no6t*(&5fY1G-PiK-?Yjk~SO?dkej_cLt*YvD)9~ zGvPl+q4~ZnN^W#xW+iiMm)&9>aYOQ--r(om}JH9j^ z3-7NNHNtJzC-D!R*~LFtT&p>P-wcZj+O>rnUI#Y1Wmf~_wLKUs6EB>Rw92V zjy$hpA@rs&Ag&MdtjUj?(mF;a2e{$FsSqd>tfh8mVA75v4DTE#gLW&?)tA?80c$>D zB_H^At-ELt|Hi8S`M%XYMqU_kf)Dc*nljYz%)G+9V2chrUm5`Nh7wr!eXK+;gkU#R zptgU^83R5{Brj=SF{YM}mHWqBQE^fT&i*oBR3QD!{=;F&IjQ_ciJMLIsD6=tXTcfx zR8))~H{ztjO!}Su2!=<0^2LfXuyz=0rvpa$o~|UnS%>kw{x>RT;rBnpa{4Don{i5H z#0F!^5+l~HW&KQkWd-U+_B?juEIF7Nea!9HM87BED<7Q=5`4fFxw;TsSWO=Q@(Tv&0bLdnL*V<_-9J|D7~EhQ8j59V6H5Kg03H?N zOp`cyK17LA+d`1@jd{&&Gti1WJCzIdF4^SR^y2&JORc3Bb+F{;J|G|H`Fv`n?gnG; zEFsMeXJP6wixB(NmuqX>@irsn{H-6LA<0J`M>R0 z*Pdn#+iC{+n+Gz`_6u{m1EZwO1to^n55Y3>=Bgjbz>Ryw$bL${$WKaCf2IH5^WTC# zi~(DV5iuuPRv%NM;I9675tTmt*V1vDA4A;|L|!$ZW(1$-a`bv2S)(P?o zml&mJwHtcw4@SEZMqE6ffioV=+$k3$8hX%qwx+k-A@Z!b-xjVcMt?Ou^6rwKs13$A z5Bh#`U)scdV@acU2|cGo@N*sZai5HxlnMLZ)SSJGmrFl5zxzi|Zw?by{>Z?H2gS(h z5hEG%nD6{y3El-#`@A3vYupu@SB;{$-rew}OE9Lok}uUR3%X0iX!s&d&JUpPVMWg8 z%Cm1=kb!^s^_$ey-S15=mF7Cm^Nc7lkoye#*7Eb?CA*_Lx(Bi!-^~8?B@9Iy|;%Q;4rjAw2&*YB3uJTG3mB7nVe)-3~CouRKTG0Lm-b{WN9Eo}`w@}j9N zb7Vddd##;37fwd1*uMm0Ux)!N!^w>bD@NO>SZVu>9JvE}lpRd`{1f?=-2eZZh5f(q z8AlyG*{R|9xQ@9mw)&*a+-)AY#kc*gykwudXR>^9mX-9WR;E(N`uUcmnbWFv+!kFk zSrO}uLYd!D5u7mFP{CH|yv-}z{D@wUi4Do; zCvL6UYmhKzKzq3wL}NC|raCc_#5r_HdNnF8$IG3;CZT7GgnA}Qh0HkS?Zir?W4sjj z()aQ?IjSq;Ww0_v()fJ3{)m&hwpjV1F^X$l@DqFd@M>3A)oa!^9es@#mTaP zhdJjl$@e<(Qr*cYFV4ryA&{$H+YK8lso?LchK)1nZ+Xm%5YCf%&J7(;55>lue~foS z<$EeDq&MT+5c(`CRZw%TJ$Z*3SGK4ybEFE__K~yL)*TL8__eqE*=24>oUFp~`YPP? zP+|U8H?(Z+&N-zTBRZ>bvomq&zACJ`s>DC%)tDtNXI^e9PgW9>K{p7HnW*iJ3!QqG#a zjp)ALhy&aoUxgTPi|hC75ze3Yo8TG348U0Ojn~r0q7}K1QPgxk<2wGyIrMN7{I2r* zJDO0pz6t+KU`}9bdcT(7dFf=tqA=!3ui}|%Pc5jCbCT7>-nSdE)gGciH&LWNuEXSqA%+k`)oA5 zm4%5n>D~CAKG>W+*W1SW>^aZIEA-aUF`uh+HqU`f9B)AX4TntJ9Y?-m{VW`zSHX;> z%&K}!oUJQsv3bm$f6Je(!mJj)P6h5$Ybww~IM_qlbaoa``jjl#!kbAc13el2U1ZNidj6BYHDH^QD6T7|SxdDfZBokhU{}do<0R82yGs2guJXL2 zQYsB8kp1KH<<3HKs-hJr+Qi)3ghKhzRe|N4eLlTN&XuPEmmL)-+kkw-@B(SS^pCVD zpysfQ0&)2YEUZ=_p0zlabXVZgUV7hwhxMFkI{XO01tb4GTg#fp zAFU$%(AnD$Z#@H0+szM4sM&hxOTN`R;@1ZH$hrHocVUhLd-heev>13^i;O$$NBS}= zSIz#l0(}=gYw>0=v89**jH>KUZFV5mc=+QbzxVh_Kg{-|r(skVlrZ+rw=_KLuV7wm}_(t9Y7ehnQWFg}qUjQt~!z9bxpe{l{& zt!r!I4R@%^SN9Ib5n>e`eCbUi8i1rrZdhDB)5u@=+#WMCvzm734;+zG$7E_0J zJQa0`kjXJI7^wk%G8rIiJt<%ydoTd?o71=Z3mh!~oT+4rgEWAC@jm$Ram7Wh?2 z#fHVnoTbq7@dY(#oJSnVO2GsE?xVGt+4PP63ZFT%F0|sYCwT_!Nq-K^Wlc$qXqi0J zNwrZg%o+Py8^+t)P@OZK?~(M2yF(AT4%Ca14={rK3FA|0|AvyI=wd@}eqZ5z`Z(s$ zt8sNM(l>BEzL;JT(d05{tyr8+4>`{4FW2YSb}_Gt|G)23&hkGHAKc<5am~~+d9}N| zCFWJKYco;Rc9#kM%z4=8EHlqJi}hz4S$kY9mzr^&wb5QoL!F5GxXZ+O&1La*2f26G zNdiZbL!9Cw-I6^d#6Ydqs-Jam*w4Dr1Di)N#l%T;wEP)O&;T{ zLbYrf>>{_Gs3knJxf~-0cog$PGTn+~1bK#P@)UzN+F|6)Vq$dE6`m}VM>~ltE~X|i zzF52l*r5sYJx+L#`$#Ti_?SO(rH&o$mgSuP5xI}Yi{;NRu2pg*-qDlsOrs+HtqSCB zDU`&?3hdfU%;>BFowM!mY=8pond6>FTyEOBVlj_UATiM&cTV|X(IkIl#B<$zBR;^j z;a5+KzzO8^9tgl=YL9DiP5AcnhkC6a_SFkO&{JPrObI~mj?BNAOATpc0R4ahP$@%; zUeN)l`N<#ks**4A(H}{-$RYNir-?u3H&*7~O!mjDk>nI}239`OA0v8jojQog@4``%xbW;e&P6{GSKJVe ziR41IzsYP5PyU{#%(fsddgK>zh7PUK(Qtj6*(W=T9v*}k<=V# zS}^Lk1*cA0@W8^1_GD(ey(j0lKfPHhlb^Vg++p%hHhf6IxrWqqt{~3UGzA-PTc8gi z$MG@O+-3_V5Wi@CGX-BcQ=3DLe_#N889S$<{aNa)dvcui?W_q(a-6?r=_(iiWuc6OP=ila#BY(^x2N!g5st}%Jd7fo1|7@JkjFo z>W4OON|1xE=$W|gu#8@2lCgQL<-1ewbw5EI#>Pn=`39B8M$4LR2D!GI`jqwtc}RWC z;cxNMqKQG$dld1$& z@|eEr&E1URH`|twVRUzgrhs2-qC)9nH69z3#8lm}Y>XPqB9+)OQH63<>G^b7 zg&VtA|F57nM$0@1)`w5Y=h#-BoW@bq-5#eW%N`Hr8IZRSsKaXJ25cwCWS4^aMe;kQ z@xR|_^jLRYhmgj4^uHgBP8XOVKu)8527Bi%^i!OzM+m=f3+uf#{NBI!lGmsW1swF~ zJV6I_0B2mbU_@*qw}7GI;rf>e^>>r!INpf;HI2ALEKlLg8nPm1 zZLA%Cw>LsJn>sdfR+5Q*C@W;)W-ZR&KwZnXOq`2hwx(}3UX$ZEH=g{K<jL$eeGIwcoM zw?V~nvb+Mly%accR*S=mK%@=T!ciHBTD(>}SnG|N9)Z%Ec_z$?_+JgSk9>^&ZajnP zrXqA#Dt>XVe_bsVr-<`^I%q-jZ}hC>K6sk-%gU=(^evqSFZvb8y`++}d{_Tf9eFK1dT1@>$ z50cyAc-gQVaBE;M%QJEU10~r`+k2Hjmdxs1pchy&FyKj5D7X8_zpC!X1@LtMQ8a=Hp4^4^9llgGh28esdpX zkKL6y)7eepVPpTfD2h3d{-*!s{=7Mz#W`yhUe~2R5&O-TEi>_ZDzgB_DKy@->@;bG z)VLFe&7Yvq98c#Ao#)G%>n4dU881g_8>LezlSD)%NCmSBE58yKdPDtUDK*w`kN>8*R1`|4rN8#1VMXFvS-J^dL^nJ|g_m;?P}ryOJ6 z{n0Fxuat!!_T1ANDKw*rqdS$g)6C{fzw#=Drud6O(|BUMn7+hIeVa*!li%-2eC2oB zqoS_pj%nNIyHKh*`z$qj>D8F>om$LnJ^KD3zu=P&F(r9@CXv6V)nn*c@<5IdKaDe? zXq5@;29Tq^llb~ka#DDG7Nk%=o}UTZ9OfZxra!KooyNB(uM08x4(ZgtGjlqTcz(<6 zhh<28a%G71e53Dj`Fr#yn|Vya$lY1Zv($rGPbHSC@E5U@o|oORF^4|Ft$9AR=UHS= z?*30b)_&9D=`x-ht~@Wu2Psq~;FgaG!#bJJ=mYr;R%T%LW-nimiQTWWP-Qc-p2)js zM$Scb-mgKY6q*;rP~&*d(mTb7$J%%q*uX>&R+IeMMt=Dqg!Kzb#2jQvl`aGqHk zZ|IA-(w+X4dR+D5tfN#Y5*(>vk09Q1i2Q#I^PGuUqm5tCdS*W;yXB=@6H8IM8Q~BJOd0qIqfr-x#{R!5# za}(-z=zoL$wX?Kn$v(dq=Z;BrBhawzcJy0BA6;uWXpbG$ha(I@FU_}Cu}HQXDYQR~Qg z`S_I)&^%|~Q;EG%TsUl#EHDxaNXuluVz59Rk%~N|U`>B!7caD-2G7*1{cu*(@Nk1c{Z0DX_1%B{EZ}f9mh~R_nchVFP!Orq*r7|))!@|;rN^U5T30I)>20? z(1JDW>25#dz4GDgI^2SdPpL~||5MgG7Zsv-ZalPM=YAW~chSGc+gXw!CJxe18>2o=_3*QX_u_^NVxT*cuax*8@W_ zn`hU~mZ8Y!xslW`6qQ0v=#$0Tcr!ihICuMZrU|PO`H@EbcM7r4;w-F7roV6mH9Uq) zEO?;MSPyak>uaY;;an%0GsYdW6q=AigR}`sko|@1!Dhru7pHhRev7lyInD8Xni^y4 zy5sE~cWkcVj$FPU9p_kA)`p^Ky-?;ogra&w^5LJ+^MmKtn`q*{tnK4IG2=Oby+W=L zA1{+%`H@*xpE-ALN`Ci7`qjRr&u~YDW^sS!UTsupN*<>_>{^B9{b0_ynC-l3xlvqV z$gsD{L*J4f6xaZO6?~% zfpev1bD0BBM~wuYU+X#FQne(9@iM)NI7c>ZqL%F#dr6)b?}o&aXHP$0-YfTA%uISo z{n+0;<4e#FvG;vEUd6d!KW2mLvT!ahi})1JhCI%t`JOuRxzX`nEx1L05eJhLEip*_ z21n$@TcgZ>mmoim)4Rv0!n!YN_;SutEmw_=JX4!K<2gS)6wj9H5xXW7ia0&$Gzvxi zGvwr_QX9}H9&2mH5XLM=a0nfOVUr@jyg7;q23o1n!(+9 zZbd0H0rZbNPCv{4+lOuM+E_mJ`6H%w2It`V(i_)2=`o&i2RcxyhM7;7;W9d7K{=YW^P=>XAzwariIM#}wl`isv zSa|ILT3oA3Zv3efjJ-`hS}8|4M}FCmTtB#!BVN2O1=G7&vDeZ}%6Fq*z-oWgSkB-3 zI2pq_Qu}?=Ri?iFDP0>AyY5B47|%od3dBV1n@IYFKk{L{KT6c0&ex8(?F1Xbt~$%R z%6$Li#xHKlv*S<-7W8Fb^R|)nI>@|WfBNoqW!>L{KFGv}yvWD#X8!5#e#~siB^F-N z!WrVGxR!hv9W-GXC==y!yaR8u%B8H~EYk=7zy32`v)$=f2eUh2ai)WS7)7bUo-QC)Av)Bs1stA#-WsQ_yFq73(S~ zrDXr#G9=v}p{MyA_DVtW8DfF0c%Av&x_E05dvzQ3RJ9=EfE5jgH4sO>{$5w+L{Fsu z^cv=sucZcK3Ui7E(cj`+0M^=v;n$uNbXKvxim?}6twO1$_eWTG7`Ah+5OT!|@0ZTf z;Y@+(ID_%{!+FPM`U&c+n0?npl9v3DMbG`PttD#%)=Fss8$vkt2tFF?>Kc zdQY_A>Nxs@c2&u^!cx zXIBer8=kM1oMdS5A6cGFUhoO>VZ+H6K0+Sxy1G)kOTL&^24Mf)FvR#;Q1U$UreC_s z?p5?RY|XsvN8$K5g*A=06*aaxib>Btwi)jWd+6>JSX&&=!O5FW5_h{$`WyU^et8=% zlw-YEgV%YtvwW%bhrS5DSotap>AzC2G?aN$L!BichBeP?=2MRf!}=A;xUI6{KIeF) ztp)P;H9s67rsG(XdDFs-t8I-%N593^6WA{|p|9%)GprHhlV&!Pbf-c&#`k%sCOtOz zcTE{+MM_Oa$?>NZ|l;nZ6#&As!*zmXr7z6ryo(dFT(xD{P#CFSj@k%4i~|FBFQ)ZRV;eh;5CvpfunAk4of0-})taspOR}p_j=Pd9N`G7iN{4Mxgb=cKVjye{|0<%9>Y$JbGlY*+m-Gd+U`Po-2 zeM`~XfwlkF#(Yl9IcUw{*z3apOfeW}Wvw;#+^3$mj73}^Wopun<{%$WPd8OSCJnnl=9s!TK4^`uaK z*Y`(-F5%dtOu?wSoCS<*BG#S-(wFnjLOv&3JX7&*a}H))s4x2aMe@%mE&ARKhpLMO zJFPibUp-cqhLG>pU5^+Yvuw&zZ%y9fla?mw74M3^L!2HZg(~9K z7xkDCYD66^{SY+@jh$<>+$OK^>kN1pNB^~>#h5)QR?dYIpBSSD(hUf+ke}5< zp?Q-YBhQFce#IrYo=9v9rEugER2$6JzX(CsmDsC3HxtkP(#oB?qM%MlECIp_39mvqIq5%Ydi*GLaIa&`hOYSipHVETE^t zg-i6U3m^xh8GDDj(Ng)F5=kd@*!tZ>4heHC8rkch0H7iPD$m3f;U%#Dp^v`l6->^FQaW&$k6tTRO3FODE zW5y?OFxBv4`ew(<%rz={XX~)vYQSIYCtfO;|LYPb#fM!v_h5!;Z~BM+PDimn^Mcz% zi_cE-@5qrUMXc|ynVIOVQfQjQ#K_dEZV0-fL*QWMhCWZnSl-8r4dO&QN)7)f%y;g{ zzn8e%@Poyebbxu~!&KNDt4HeqBNC3%_cNs!iOOh6;mqf34?gF^jF_-D17FzJ{6${p zg7M7Dj^Z4KzU&{*W@6hD@@?tGv3<5H=DL%QbB=zXnaox1RE#Sxd`I2fOB)XZ?JZ+LcXEXXeIVM2tl7nBQ|qAcA8Cp&rZ?eI@S%*`}MHvV?s;)nbc2GADqR!>Agx^Nz>t@miX5N?kA4L=zT9%1|Lvj z%;6CHv%v@tuHOT#$ZsvfbyPt#Z-u$c8#j3l~~m)bJ~mLCSxZJ&wfb&Bb;A0w|DsbD29 zTUTU20B1OE?G>6>-rq~zlz4PC1QU22jHj3@b4H=5Habp*9VQQv^RK@T7;&x==RIS{ zBW`69!*lYuRtMuwS0k=R(obz^F)^z+F|Jplc%csSi@ilOm}mTlx&KikcI zxB_Qkt(l=iesLf2aLb-n!o7hGn?D+0c*W=3iM^#)yo@}eM6>dI{;Lx+D?xpk#d614TT-RfUN7GMDiNs_bnm#uo zj67m@?w=D3)MYnu!(Zog^x!n0jY~F;9_Mq_I!-EushD}8!}JKg|F@aA^}HB^ro~8a zs}h~u^mtZ=yhZk(o&ognd|{Fh`ZEql=gd#RY@Q_<@FB04?V3Z7R-4?pgbix#!H2Nv@~1n@=u^NXks9m0WFQzIpcE3dtAUZkV5aE|u)q zq>1@P?{FFqGL*g$>+?Z2WE4Fipd4Gf=(;R`+ZCeYS@`*dHge0DqV|{o9|-9oqnY! z9vWrUwHOIl&U@J;R>p@K1)O2mq;JkY z=-->M!yu2Inxu7SgG?iT-;K{iwZ$gc{fzQ4){o7OY2fBRy`s)uB6| zq4lggMmw?gn8cr(9Ezi?6B4-xRjy23stY}J^62Tv+GjHN|2y?~25bt!!w`BMXvs@o z#%$}k{GKFosw4DxvY9x`zd9V?oV!hRYDn)8=lIJ6`|n0f_T}t?^XKwqO{g&0gmauN zk18^u%^oA}uQp=EN6t8Am@xLV36-Oa7+J=IWyI2I8;mG?ZA7zF?&)8R@V>&?bS>ih zZU4)VFd=|AyX`rD$0K6y+!yZdpyy*t`Yc-vnDUKTAe`ekZa2X^hg{002?*&$Uy2D? zu;kHa`yb*e#GHJ-@N5}O{^5D@3>BQAaBbcr9%LFyZ)(n#pCx9X`-cUXa<(Q3D-h(?Yduo9`?u-ZzuCPu0@qVl#Pm-AyiccalYJ zjxyzKQ;DA1OzJ#pCVkVJ%2;~J4cw)a#0qYbe853ErMpQ4xr)_Cc}ViyMpEYledy@f zKCuzAmFUwr`jLxFt*I8-&{95g_FFJhDHZ71U;P1pzpsijh60(wyuiXog>vUyp$u7C zD9(oq1QcLSPJvI< zUbU-Zhq2}W44F=^_TK^6`jh?$d;IAuq{VK>KwN$22a18QbPB!Q$iY(g^~dr%zSu;~ z+_##6aJflOcrWG$4C5@+jkwWaE$m~M8+}ZR9uET0u_b$+x4t+yo3H0X{ClYuuE_zY z8p14&7C~sJ;J=$Q=i#S6&l4>*O5lEXD2G8sC z0}3Xt{hRvRb@X~5URI$ZXT}=lQ&)+=+}-3nZVE>d`^Lx<#N>TAYyX>l@xWAMrdhCk zJ~g!isE;de!PFxbTv|Y^g#A$5Vqy`TV>Ae1wnA_!dNpC@263qc*Xco^qR$ZL8+Pq2 z=w2-q7oS+ryL>9<*yvI4ff~80#IHVB&~Oi5E1NTj4Dzh#A9w2}Ib5YvF@Ja}CT+Fg zb!&Rx7%kK++c3X}4M|IwxluM3AL57=jIp6!Q!7kesngA-*360j?;}0>Ij?v?tS+q` zb;HCUzH+YeVG^;3GW1}&YQ^W7tlnFy>H_Ixrjb*Lo)l+NiUe` za?Xm9Kbe(#(1!cH$YHFRixqqyNyPjwwsn$2J)C7OeWd)!Jv`B&g}f7IS$5b(PM3C; zzIn~$VUm;F)OyHZVi#Smx=1DOX41M0y-jo6WE1@x&o)=eIX`++^m3B9TyJl7GW#>m zN&akblLPnEa&MbbY(w2-<3N?TOi)S8V3jmK;zB)zr(`fU%zvt@crQ>%Qd~9X8hHyfDBH>BEbq_fRboZWBwSzV)m=0Mi1s*hH=3rq9G(hBI?wp_Vy0S_~EX zf9&IjgBIS~{4t#C?Pc`n;J#H zZ9RRi+LNcanmKhT%okh1JZa+2r%RCg*gXQ(Q;9uY41@U&v6{#9fNV zmIaoN^fA>iJFW_I8yfO+5q(ZpSx};t1*N!lQVZw<#r3qzkKEy8VrNCEs5hJ(W3G>Z zlZchJv!Ki0DR5YALH)g{C=q3Wdw*uue6wKN8@^6-D!d? zIoBjT9Os;8e#@j(lrvj#YBO=6w^rDkbMZQWv&cU-^6iOf4PlPwS#o{CIgdO-9*L6t zk=x8{iy`hk%8El-Jn$PDwI#VMWa(^qwfe3hTnE-&8PF1>Bi%NY^ox7%x* z6AH%qc)WbragSXS^Nh?-oq8q2`HZ;|Exn(|$il`k;@2r&X16g)9b=62YGaT}%$)9) z$T@$oL3*-(>Z^;BJ`G|dwca7|R7c6Fs|Kl1+9Y?{Qp*yZD7&$i z>$y{f7xW}qvPp&2iE2z&yJK=3`G(Zm?fsYiX=61Gu2kXc-^`7srlp&j^P2W*w2E}c zNcIzl`co@bxj9;XRw4V63ND=KSS>1SnWl!raL#oy$SWySvR7s%z(*x+^`y3@ggf@n zcE|2jD%AH^Bc(DmFr`EB@EzxLgUCnxOOMDhp~zL~;axWb+T$T;@rT-$F#4mg-#Iaq z{DyuZ zD)s0?o!>;(qyr8y&mxi-NCx{=_WBc9la`yJN2OBn7{)s9;Cmx%>Gb>GMhzr6Cc|0t zJwC>{+-=TQEk=yqKrI>Zt6#myW6U$4BmeDkjed@snT1h>wIA!eQ1UKzzoCY&hY42( z^5Z2l*zOxK^D@01`wl;(_<-_yP#d#h{{^(pkiqVG%hZyDGYlZotM zoWFgf2hG+D%wSD;#GZZGnoKy`i1U>ox3Os*UplU!`iR? zJaQHvXTqa;7TRy1r_EyeS+&c;(eK26`1$U9dZCfy)QdHsmytbj9%r%qzSy=u~8?jnqJ z?SR2<5avC0pU?X~f57_#AJpJ6m9!K{7;~5>tx=Fe9UNYZXEwee-;&i}M za?5*2z+#(3oMvAmg=fig1yU<1QD(dy^{zruAi*d(HxzcS=yN!OvC!uryu86$I%5>q zxL99xon`qBed zq??+^;Ter(MpQGoXZDh(6TGE4y_vEeE72w04l5OQ_-CI2mmJCN#VN4oWiZx$4McnH z^^<0V;Gdejwu8Y~uZ+cvpWKg2#vss#T28IWrwQXE#wn?dcs-%iXnf55_9k_%ZgQp~ zHXjb$-}cmchwsbY!AKqFw`9^<2Q`&p>!_;?FPU-JSDM_=%J)US;?Prxdi9j>twX)P z=?c8|Ag{NJ@upuW=9oe;`B?};9|q%wu|HnC3&C%54E>{HPSVE63*(Y;pip7cwj|73%AsCSN<(haDe^fDifBb&?9ah@_|mPXoF z^^&sZn@SGjfM%BzP){KbGDv~QTMCSr%d_3SB&shA!uHT0e6tHgRdPHTt3wgS>-lzr zj6-%T()+}q&-WN|O)+@4gZkg=EwJ>naMr+rBm62sCd6bjs;#FrZBuC>Wm-r!8a ztPu18=M#1ZA@42cid;gm{v?0*g=mbO!dU^H#g}-0?p=vSi!ckqQW#q@HnbZ-AJaM1 zKVVFHj{KtSCpp+&+nFMZ<4jT*c0m4kM-SogT1<`d#87f6`NPy0mEnnP z5gN``EyB|R&hCck(e9=mRaQmfq(P6G>#2jd)QAbsjrdqdJ=$HYX>OpG!GIhrS(63# z{W+K&mkrZR&iPf!!DF(NLwQYuKafcYQ|fM#$5>oVsq1>0T1|!VvVuIwIC2-24jmBh zEe7V5T8yp4bA{J(x~T^9mU!XGN>3EoQ|piS<;IOj=;yH)a$1jq0M-~jaAxtk2{reU zt88h)-(teDc}9f(q}JCp?s>`_?AgrxdTTbKUuR=*Tcz&u1hODx9(r|F{^yn1=o7WT zcs_rjCcxQt337RKvh1pzB15~R$o6-h*gS(8Qm@E4T-BiYA}zwpdSZjG9^v$qXx&2( z*9m&G9KHw{^XZSt>lmHF&n$y_h^MI2IN1o(8=fT*S$H>!dA%34n>KPUubzXcm9o+Q z0==ZjIehbD4~X@(J*+A2??*ib&Z$ovmn6G4a-LyYlC&R~B4vCNWPiLGsyG!CBQ@m9 zHF!Op_bHVgup{)CwS~MVYcvx!M_|Sw@`JM?K|&W>Ss(v!!Gr;Hvg#5ogkNTCY&6PiayiF$TWs>K6@w`kZFmscf3(*)uM;! z)?|5I$0V+uGORwBcS8;DES$k zsG5uwe2)IAU__XU5vwQWpi3t8$1Y~W$j`282G74q)VtbCZN}{i-5k9_H|w!NclJHK zc*5xa6xmn?P4g1_1|Bj>p^>Sj8q0taYALshXG3E<^sS&o?S(uyZjyg@Q&N{U7-ii< z(Bo1d?$`yR!Kz@?R)%m6kh*%KV=!$@45DhsV8#J@{pC<+cuWR7>yfAKZ^qY?^e{d} z?b`Ylgr20Ho>M+jr{`m=*$TB|KEjzxzFnf0q*fY9FX1k+={{2RsYaIlY$dieb|`mN ziCM=uClG9h;tqCjGBWRC4s^>D0%zt!E>o#x)IJzDFNUI8{aEzC2;Cm2vm=#5qT&GL)=2pbvS3i z9tGjnr5H536ph<=c&=CAoWd`1mdvG2f23a6AG{xBGw_jTeD!4N$-9tm{KJaQF8S2+ z&PQ458tprqk6yd;G3b`JB=2;Q119AlZ zogKD44#ted!Dv)S_Wkc*L#1u~(Ts<& z^ml%nj^N2=>f@NPowESTujk`5&oTdZWb$WP;mEu`(cVq8E!0xM%T>;CCbxO6x4i47 zm6OwKve28J1aXD(d!zz)mhg;kt-z_-!HD}DjLKvgOI`@Z?1Ug{jf5bVx#Eqn)aoC= zdC_z1^E$GI@{Bx17WFiXEYz5w{xb8m5WN{)3+Ovtp6AvA&Ph(>JO_0VO+I5!v@+U`-rQ%r?5u~T4kO{H&$@I!F(PNe8Mmpo;MMku3PmZy4 z4zASB#^F`jD4xN2pS#p6Cx=#_ymI67)I_{S4t_Pgv3QnUS$jaTQ<5e0szFu`CVSp4 zS={odB|r_4jos8Re$pazmj=PPS~&7NwOr9-rVH!R+@JUHdTNZLwjTFqAs^>+n`hV@ zBgT;({2os49WvI7o8+L!$t*lOl8w#W4>$ZGyBE(Go7dB&u2LsO3SGNB?0+02ua}_I z1yHxP-Av}1nhhwVMk8R z^>idEpP=4KiXL+Yns9To3G=s`5SB%KBaIO*r;YTqV~)VRFp4?ADb|l$)z5+TA9_B2 zRp^`&sB1&Ma$*Uk?lsShTzVOgA97G!n16b2;{4omYUj8ZrFFVdLYGp@;0g799JR3T z;E9nnyzuj(7W2DCVxD&-XOqY=I!2=9Yu5G`vF6^!gciI%E<8)WJz=ad-G~Eij2O;- zsoQkwXkN|6*oV|Zyq%3qXKKXrERE&04Ca^d3AKd}D|F`rl)AKS25A+LAPdSE{3W7MGLbmpPt|9!$*^!Bm>(MVCl?SxV-? zME`9oXD573=w8W)UAv8V`J6e>i!5k6Fb1+@q1&NMJUNz)qw5vAV(R1kX6$3CuhhNw zCmTz>nO74H5>9QRd&iQ*UYR0;{0yRbN8Yo$3b?^%cs`lW^=g<#b3WiM`zU|v@yBvr z!!l|e*XB7kM~@fnsh2&Hz1j#P)&`p}@HlmM#_%jQev~*N8@9q#45v)fCYkCyg)iEP{dLEYda+Wm4wF#~K(K(*8 z>Fvl+PtC)Ne;njvI(5yu(u;_-;pOCF8vSj>!dbPYO1WbBHjkbtE6LYHaJKbta({6i za;!7;dY6*>TOEysd(z=Hm9@`QCvjf#OHMrVM>1<%Ef%FCdtDwL`!^tyuE1C7ubm_p zIbsy+xC_Wb=lgOv9YF=zDDk{-;4TgodZyOMEAgqiREp)UD2Z_YI=X(Yoo|CWza0^zrXyy4L_xYQ-T zW^xvfAnF?q4x$b!=dk;yBQBc%u9YeY%d|L5meolSuBDEIM&!=(#++#K&;-DGtCv#?CZXLPfS1h`s0A!{`16$1SKb{Bu zc~=Qm^K)0Rui_sKuRqiABsLexGhF3R5;?LzsYlt9|6Ziy!yMKUFR8?SPk}sb6olyy zH(|-DbnKX!2S+!R94P!LPOAfO7u0J=Nk`7gJXEOXE+xtoN^ONd?o9pHH#{Ait+{yA z*HP?EMG_qvh(#6YQ+z26ZYQ`d`ZbU~-Kj%Y9DqMVqwt#itU;HDm(Y}e|8SW4xY8|_&hiT(xb~=Jnj>bAJ6^I-V81#UH=i zq}3V)qFZy0@oW@^J9F0LBzq*YoaA7AdZdk~Uvoh;{%mSS(P#eN6|U0EL4k%F$V+O- z@tvce^C`}o3xNIGO&EKH9P3|J;A(55A*M)u`fBU0ME6(N&z$?>*Pc3=b=so>c&-<4!xOJQQk1h?wR<}snm88z*l_+{rq;uvYkN(xvWx4!YeC7tik^9(} zU3{O~^d+C|A~S~;ilrub!y#N3hBSmI=r6RZfeiOjpegssYTct?Y|glsJ*J_idNO=c zv3x2Fz*6dUJ|`cl8XR_rA#*`15cWn3lt?r&+MqK@sq>!@!!9<^d!evOONC~K3p<^Xi%>%W;Z zbYp+3Lo)g3=Y^7A*bfiyQLpw|I@Wpd^DWy*R$ecZF)8GQ+tLr+)rO}@O#X|UnmuRvc`h{EmWg2x}UjUL=SEXX^VUQagF20kf-d?jwOZgI~yCnBCFBgT9j080%fj!se#T zt8@3uiT7^ULSI__8u}$X$fTc+LI?6k@$~tfl)n%){pnlXl75NIzh^&Ake@{!m=i`0 zsCyDtdC_0TU7^eQwqIhpXt48F1TI}8k2Z`m6>W6Aw}R;sm0pB zbLzoep*MtMIOe`dL}AxVIPl*)-X}?}w{^$4fC!WwZa~~RYELm9vp4ONT0K?BYY>hG z+mbjtmx(jv%j!n%mx()6X!VRxJI&UH;TTE_lzX}IuvaT3RU*Nwv zi}cBcCAxU|(&1mtbUk*pGGIeA{hsP7bZu{vr&FpC|2qO}_8Q^XlOCeOY&gwz*Mra1 z#hVN1^OXe0Blqy0+-u$M`^1GDaq|3dsJ0|wZZOwNM;q$-n#6jG{8Ap*dp30y-KpEi z^*HT#oSb7{>5V=DRd|2WYh^Dz0sNMTDVOPS+Fqec(NUMgNsSa&J^J%`vvbZwS_!Uq>X7vQ?hd=j;cyDz za~R1U3ik)E5&LDuad*sXMgI2zUnjrQjGSg2a$k#+RT%CYP7hTBd`?nV|B($p3aGa@ zO^y48aJ+j+pIDcBIK{lAXlk5v-Q|W)4I^-W8u{zpnW*yBhUYgDrH@U8auvv*+LExz zmIWN39w}a`=gn$U!0n#5WSvxF?q(YHq^U+T8s--5@dEWHB#F$Z+=X_c7n_l^DMJ#hC;7`CLapH`om{mpH7Rx435x4C0c zFFpP&M-KEvCc195;q!w1lAo#mPkX;-H=YX}vXR)-hJ;N<$+aWrPM;gYR0EcWa9tcP z#<;cd@;hIJmDIhpu}^1LBNHS0aQ`0`C(21G6t#skb7FQXlmRPMx?=?-zG1we6?< zb^SVTn2?%w*xGjRA*a-f*Q@%yN?7YxarG>}mPf)a{NEsoKw8sXH(D zwDtDCl8U(XsY~8oOg(kjcIs1hMZXDadZlK~n43D*u8!Zk35gQLI(nC2lN`!1ileVl z^kfxhFxQ>GJ5JP{OmhELl8hN{l#F_bvT+vuC3YoB)yfI-x@(dgi(tQ*zJr!$31VGm zl;&NN#djt3516|jm}8W?XAM$gC^b$eQg@gvqtYW$j$C8iKFcJ}Es1iwFj07hy1 zBfCx{>iT6_70*s_-2jcDBzhGNGQf{@_y%>2 zaQ=fji}v*4c#}z=yDSuHva!!82i_jph}l9WpEW6a)?9ksqBhU7EX?0bEk@SvCLYR0 zdq?U=uznVICJWalW}!=77J9H|m2f8;f1k_7jePn~kD-5HJI;Ep$U)7g+1M38ZO2Qj z`*FP&GgfOD${s|cY@|4`m$aJmyjMJ=bji9h{5$pIPN~J((_IE=J*4YUSBWa=F2{B? z68Agq@=ryT48H9y8Ry-k-sC1yGKF*MowO2h*IQaU_{i+7&T?`ky(FNL>bIyfH^x;u z%=3_PZ#*S>EqSc59-?&QjNW-?nOmM711Gf-a91TseVK34L*Pq}t8AU?EcJI3%l=ME zBn(mF?SAG*Rp_xmU)y=UN{p+iL{K)_s|Q8$_>%%(l$?q0ZHE)vl=!P8`?D*4%ZI88 z9PXsRg-bp#punDA3o}4u;|6t+v`^ z&j;3nqo`jupI(LEf6I2x%UxI4Ku_CZ`UWsJJ^Pkk zwfD(0szZ>>p7|gT&Y9+gpo4E9CiM!&`y~OeR3_KBH4q_d=~>;4d0(3le5u7c!CKZR z=7r#G$zaUv$UeKCY}L>pI9h|yv0E^zP~T`(2AMAMkKM14Ma*D6QHfeYUYw(!9fOd{ zF_?Zj8a2C6dw_NO%}Zht***pLy%{MujHPsIxo<8@^G?F_moM zLFP)|>47_rKhK|8Uy{9a3mL0!(bR3A4xI!4&OY|MnPjW(M5B#;EOxz%#`$gJwU*G6 zx1j}_zNX{SgLJg9;|#9R0(&P5Ua*dlxrsF|{#h}cS_6|U==I!;CpXfORgN|LRu;Uh zN)3QD)Bq@Hfj{$|*sEqNJWX9DzFz00nXE8*#r9@w7-UA%+vKs*$w{7~FT@ts`NcS;jsjp(i-^P6U15>}KBDIW0S*h{E{Fpr@ z-;!1|KE@f^`(&+tu`WL{AB(?Oagz18E&W)7xk^6kLOxoY$j9upWU1H_pRZvp-;Ycc zdmR&B(`PA`Gnc2VIGREI#}9d!oRNpmeBUd~c}v`7Z~wPe6!)Fv<84nln&B-uNn{=l zddPZepw0+uB#$~Ymdaf;5@x3r{j>)1sJXlB&2Sa%E44gPs-&OZMW&bWlETlfGH9_% zzEY>+Odqwh+~_T5$tpT<4m4#rH6D9;$eQz7sgbIZ;AI*a*UUrm`QK%iddSCDE|N!{ zVBX7y(sS}}$*-h9{a7-?eeHnmWPd9bNv1)8ZuWNMkvKEFp;(^xSE6kfB^I%-w(*Ao zhkn_ljgGpdR{BfNDwK2miljF6xL$I`^7>|*Jbqs+$4bQBFA_l3Xi5oGmc}uvsVl@a!vlbCe(Fe zP_qix#{4DalRllS)jf;i+Wj4c(fpqJ0a56EiCRRT}RBJ~|R(SM>hH6F9fsDIduQ#09vqy|>G?d+{B;JVe3^%%o>mlc{cXCGi)UpQoXxus zes)!#xvAyTeA~SmS3cDz$-!^S+G(k0-`q(ZWE|i2ceXY4sl%=|d)x=51syJR_Vw** zenao&`*olB$gh>6Lc1}WU$)+x=a5$7PH}3(M7MU^N;WuqYwx+XHJY6`TOq1c>W?uc z{0x6rPCHoodE04g8>hAWdqmqa&#tx&t2i^YRn#HB*JX~iIiT2{dU(CH?V)gk%&Tma z;A+VdKExy~FD6Pd=UJ{yFv#HN2GO-MN|z*qbTB7MOU|l}xR@mMPN&HC=p<3SpHps5~MtaVhWYH38AKB=4P{SziqD&H} zjh7cYP154BQS2o}5+@|co`Gt--k`;^^7P2sNZtQ6T3nq%4>;CR8oy*L$KFf>gBEqt z)I3Yn$epRh+j^YWi__58mU`U_)yR(0p!QfTN^PSy*G?_9^wjt;N{w-WYIK~W#!zyO zkH4wW{BJd;vqrFCq82^dYY^wG#dX$B4&2e=UIS`aFyDRkC+A2#$aG{=pSxQm8DGw` zjts|A1$mF~NccC`W5F?MX?aJWHTlIDFV63^rWW@_vMBwj%gFdo$KGCT<{2+4ayF(% z1ib!WjJThgS8Mf%n5BnXFZTaB>d8Duz~`zSEBU*Qwa{bkRO&Mx*JI>l_D(t97Vkrj z<0`#JImdhUXcFcX8Ij>^!v5h#%maIt(}*{nMH$*=X>V zGoLP5xcQv5xt;74j>>_SF=1tU>eh6m?nk>EykZZr_nK_XU(Na4Ls{7HEDPWGbBoOE zF~(&f_s?t;tmjPH9{O6(%)!2;I~FzkT)3YxK366^LyYs6{v+6!YEbSGK z`B_R zV(LVmqt@=9894FCOs@nBtZ&RHQ$+52j}`A0GUk|(kC6uMv(E1@Y?6=oUExg8OCS2q z`p8I!#?t$bCQ?|A8s(??dF@r8MgyMjkv0h-->7=TxtXc-=xjzG<)%Sc!SlDFG6(}5 zV*lemjy|RSpduExgkE8GG3d6J`U~V6dhW6S5!3-DKNHK(&-^wYyPM}@PTV`3983?< zr}@;hrcdT?A30ahM7HnqmE$F~;!&lAemyax=O=0iGfw=;>xx#J zF?t~5&s}5~H_?;(XC4A$tgz!b^OW&gYMCZ-+fO5@qna_lZY({bH8Q?(6KQqK4*NTl zK=YmoOf5k^B~QtHLWzqzL*aBM7zIaysAUj@BWHqOcOn!&EAm>7l3%RMIU~jmop#1x z;xOKy{)|=m88yCTMloaCNqx-FkqMd2-e=WL`Iy9bakPmX>L2u*=Jk~9azuP~8^!eA zBzbuWvU+2pbQxoif3|6HDTSMhn1 zYtN?E>lP#Gmtu~3%7DQ!+<%zAMug-b=`H8jSnn(2oP%oI7cTl|qXRuv4D91;$$jmA zP2VKe4i7w1=$!Q?DVUrhne?LYUU5La9Z8YTtTn!TsfBZh8nz~$DEUImJ`*((_Gn?c zPA%MYJ^b3~(QiI^bS1Tu@DW5BxW=t z(9F5SN36e&Am>>?y}w=5Y$BU-{#-UZ=2L&G!vAPjmj6O#a5PzvKa{$~yGpxyS&uEg5X$NH8IHP>osKvUb{G3{9FtDix z!zc1tI_ZhAw|OS=Je5}D|A+DUabZ2OVkD|nHo@(S0j@l=7Vxa=Jd*4w>yCSGv3}e# z8}gKXFRjT~vaY_fn6=jea-M!lT`%5~W$ZWHeyPx1jvyQIAVq@mIa6`VAPu|{ru z7S}V#(Iig<*7L;OI%GgfYyO+Hc*FUL^}dmqIgwhCWypfCRy(_WBsD$A6ZJNt+Bb5H z@9A@K(TI@yoF{EzK(AP`o};N5*_J$PXf~?G(bp=GXBvAC7jG+c3C9(>r@IuoL*!GM zA7kId!$)R5X(Fj*wbEt0yIl5D%dopz@##Qsh9D)9La7ZqU4gkt%!e-9q4uH>bovqu z%O3hnGdKB?7l?OX={MgZmYy5ToyU@aKg@i%S`4-~i$S%O7R+BkKF`mBxBV=b=$(O4 zjGgB`rEY&XHTAC2Q~7}v?F#bn_6`|lRTJsi$y2&5p?C4OhEiOynY4bamTGAV&JHT! z(%KHeDm&=EQY&^IzxsrrpluLzk-^Al9E@tELg)(-f?lIy@q9ZOIeiS~ZeyO_F9r_G zLvDF8R=4L_I@f~7x$KcvAm8|iJ_e&XdsN{aDl!&7NKR!sWAv}TxDP#UBGaa6#BHjN z_>O2QV;47-sdc<$9rMIv=k3sBA$iZw3QXp;%rq%cp+*S)>=c4B$ejPlnaDT``nSwLNAh|~iy7msX4E*!UTacKQ)qoZeD`Iy9A6Hg6f0z=&!ewxs$I2&s{C_=_cDU zE*&1f%y@i19~+Hi&6$f_TxLb|Cu&add@W&WEQN2I%8m+6_v#j`+)0n}rsP`MvSu=j{?5l)H}PQ}<;48TpL1Q^`FSOg|7?Nsa-61)b zt-)YlEry=(M0axL_XaUH8KcF>x{+|}7m3k}^wcDY#4I)Q3~KH9XiUgGY`|uoUDtaU z$;TSex`YYCCekl>Q4Yq>qDJkyY?Qph`1w^9URv0jB!AYQeC4Cf3S9-BUp0AclP^)1 z;2!J!w^Bq;&4QV)k|ld)q70r*KCdfl_;0n;vDd)<2=yyhd!kN2BtirADE*kT0lZf; z_tN8tXRGOy2~GN$P=e=asLF^*oX0xUh+51wb5Nok=hK^$!GFaW_HyLC9ka2C=lY61 zN?qj#yhrTUp5t{rJH)ef1^X9&9+&Q($uh5bvZOm6kiRP?%OV$Y_=i2A;yHTvff{X? zE4E&)hT?rB%#WBiH6#zPPLG?5sEbi85_|KEoCh#rO;Z!n9GEw$O|a)a4W8#q|H#4J z1fCmxIZMxLIcFwYKwt2O6BW8+pU5%tdPeeG-ORJTU;07Wnv)_O{^7M07^P{@A?a4> zptKsPMcz6sRxbAh`E%@~w#U6_>i^7)1o->)Tgbmh=@C*Kfol~a5vif3KI`+sGkx$g z*8680FiuIm#vfT2{)Rox<2)&R<4F^^gxs};K5E=pbZs!E+l zqZH}1DMi+@KhtJhvQ%<7C_eM4VcFOV9||;BK2eP)%h(rTPF#3Zi~71qZ2ihU#9;D_ z_w~s0ibSW9WI%6_W#m_@sYcwZM9qYs)O5-wV|hA@n(^7_(lZ;Sj%UHpCmYuD^iR63 z(0%bx>Q=icbsfk(jG4)M^yYtg#w%ayNSR%~sj>o$)MlpD9(NNbP;{O?~*#sA9F5jf~hn0!dm8{;tWTbev7

YmD()?v zsCQP+O=^#_Nv-g}|E|YrnHeW^R%+xs$&Z)C^2M-Zr&P% z_4ZN7vu7Suhx2ttm6+C1ACUerKd2w@DUbU&&sc38M_E0*Sh7lUE+Q@p_nUKHAJ19f zM~+giE;+%M%tL!}{`o>0JT~MZlfL1j-~X0HJl{i)lP_P-d4J|n`HkpHTlu%#b)?^u z%fJ3eX8NwMp8c|(jAlRNqcBe4zO8M@dfrYe@}!3B9c`0aEBxU(oxa|UIVZ^a*{|V_ za+&&-)#&3~h5dmFXVS3ud@iPCIZLNszr^uHKinr*mGe9eOEdGRSI|h_S1yoB+xa|n ziNUv=G^nEU=zr)aP6-9_!zB&a{KkF9nD&>t@fnH%Waz}jfd zB4=3>SRid8g0S}x`CQgePVx*M96N_2Z1ZV;(9l zQOQ}K0y$HWwfoYnYx||+&QtpEgw~c$zl){Y*+8h{3p98xS%X4djq zAMduBTH@WTXtuyv_PnF-6YsMtbp<+BV4eCO&cV-cmg7CBsgT_dGx>aeUSmd5bu0eL zX(;oX707(&fdAqt`=!)NP0Yig$_>Q((=Qn~ED%$<|Fr9yj9Q$*je%pTvF^_rs1Q>dS>OMe@87eWX6HA66zEFFIIJ zrH+fNx3@_cHBFZGpti_l_MevJaaPth)zu#_tkgicOT*vESO(r3A-zTaJv_ZNvLy{j%CjlzU_^tGQ) zzxclH62pDqoHhXC8Migyy1T)i(+cYF7A5}{Reyg>8cn^|_US0~Fb@aw>Pyj~U-Fjc z#nFB2_XY6!7x7&9?I;y^f0~27RCS`D;Qcvs=U@KXP3}ziDdkwVyO_U;v$pA|b|V*u zvZ_gjC%yCb2Elo66t3+eAI)51a1&2?Q^h9J&Hfn4{p93e>S@O3;k40F9vmr@yHNqS zNL|Y$k97F(dF%c@PNr4xzoF*SJXcTZua&ob?6q^2uOc~3->URFqW=dQ$$v~; zIdcTsdK>WZHFfch(qH)fe)*>JK-~%9=-k(UmCNp7eiMbR(~vm1Qd^C3`4OlwkN+;l zq1%TjblHq~M+d5Lxf5&ToOcP>k%ff@8#VO|QaMz| z9|Pmbzp4ASEE8>ObDqN?PPVjD;W4?t=>rUyRGsk}x!2IQ31VL2&g&#M>R`YN2iB?U zFh*LRAQ`^yWKF_wu|EBjSl=4ci8HZ%ljLke`utYr_1sKCBR(hX7*}mii)VTUiFNk;> z22;oIc};iR_YOy3EIGLEnaK2_w)VRO*+D+Bn7xf|JIGbd$-?pZHdLsZC}XR8a6Xbe z<}~VS4Wtjp2pc_ac8eRYC!7A%fAMpyx*&`3t&N^M@v=Rd9M;QlY~%ay*g)>DD|HFq zB}#3O`wNahGC!~N@tLd>D0J1!>=(QD?&!8rxbUtt*hnd^El zH5yJ+FY@U=@eLw3s#%C`Kd8T%Nqt6gWcso3QmZX>)ySh=c*W;oC3W3bvfdVHl=?s1 z@yFYR*!IzY3(kz)In&$yd7|WpyTPqqI8L5SLio>2`d8YJRf+W`YH-}09*)thsclp7 z``yS1_Kp{u8+p&x;mE3Nz={|?|GVg;O`XsguRP$KrALV|Nw^Z6g^XqjorhPvRJ+9) z;F_GVok@OnF1eX8)Pbd6ZVr91FMXpQtv&TsKXYGlA^*EDPG0( z-MJ*hC1>K>ZStq&tY?o>qduS8)~?jRXim+F*ETXq@zQRD8Wc%^V*?|qRLVlt6i-*^L^M)O)R$gt}o_aC~M%-*K!}$8aBr;y&4#UIBa_g1Db#fV}5W zdbu?V$H&9;dEY}_*Y*nC&p`6v%;o-2UvI*3?;> z&ZnYR@|l@YyZt8Wccli8m$QF8oYlJDi598GV@YR=N7qSRnOq@lS@{ZSOP)uhmfl#o z-MmBgX~E%*QxneUQa87|bGB*5tJICft5eN4;-s^I?DhRbd9lMFx!p{%WiHQ9^5iGz zg|s{@UTW(T<-l5loa4RvOjhyaKZ){MMLp%elcY1(+3JQ#GLk+I$7Y&jZv(#0vnTCD zqMSZQEgsG(j-z)+V!ly2p5bS6$|(Nf>~nLy9U%KVoqS`drSY=#6uH~J2Kl{`{?fi` zJpPM*9`uKf{acM{Rp`f1mVaKLX9R0E4Jv7|HJrYHKlnKx<{8TU;vCP?s?)S^DZ_eq zX%+T&QseA(a{j$Jd&ru68`f6hm(W+7v;CO^RQUOWULpOc=hL2=rvLW2tEf>rNke@m zYS_->xjB~FJ_%YxUyMLdNj-c9kT)bdKBxlgLS&WaeT~4TB5LEz)?>?KKFd!c;K}+? z!5jJx(wn-|4m~|_ijqn=PJ)IhK2N8AIs@ANKb&sxo{f%G6e!}nmndc4Vi znR5*AzQW$a1MbIj4LH=oh~>MTRG6xi1H&1Xj7khkBoCp1agmN zZ=h`m&$vff=&7Mspp|Um^=$N+$9h!lY|cor{-R<{i2ID=6MDV#9GicFy{OzwbYk7Z z&@>xiWY@p4Z+%0Th1mY|ldhkQ_`n=`xR77W%0ef;=QYN2-~J+VzlZz4bZYgme`GC_ zg&H%c#~hGNeNK0AadMWb%p1v z@U;}Vs_8cQP1dk~k7D`mset~iO&sitq)A1aINr8NqjpLhu0{`{k4jvfT`V0rA7omg zfUluQwptXZN?p3OWVCd%ZF1>ck#smyELEr4q~Aem5bUJhBQ+i49~R2(Z06S`ilxL1 z1xf@2;kt7W+;32igUc!eU(p4=ky49&_w&Y6>? z+C)tta)<{U>4DTL5Zgxvq0}CKyj>WK5!-?=f&63h?E#qQ5rlxGAcO@|KWIS!u6Cm~ zgnuyZ#dC)2GUv<2(igE$AWq#2M!k5>Dn5&ZGc=g;ftjpP!8k9DGPmo}RuIVtt91(%*N4?9bSYFawf7tQ3DE$H}(9?_Gi+j!WFUN_TGWj||O-OL!# z(E?e{x_O|5^9Ss|kmI^Gk=jVi?VbBrFyx^btAd%IZ!u#jxvl!=%xKq+HTMnt{mHBo zT`}W+Kt9%ZQ451?VfF=jSp_k-(y(68o|JtYr!PFZoOfOEG) z=wW-sifQ%PXP%Rfm4DEWt1fkYSVMWoo<`h|d>lK+?`8ja@HqDDCsN1p2=m2hdGO0( z-HrW*Q?uDC3L{I&Jl?J}dsf5wy?V|OH_%9rnp#OM^yci6i###7Nyfn@^2ndHw4SbH zGgtthIz=(2ydDElHTkeG%_R{~KmgtNflTx+*L==pvtGJ`Q^1--TC5C5I-d-^9i$TWY9xJn*D z6$Hn7tEgkD@P^X}0jtueiACQ$Em0%z3g#9)%JM$?*n z;~LJs^Yv@p$vpmw#-Nt$X&#Sej>fg-5QDVMTuUvZP;&`;jI8&Zs}+OHsA%+F5RF~; zspEKq>+vT2s})>Jf78DrJqj0nxn}?3`&;;4L#YY5G8%6d@oRkyUbE-tbT1v9UU6QO zeXa?I%&0kzHP`X1-&Upnmmi;fOFCw7-CZ7K#>j5`Z+?&V5q*eQJBk}?#=L*1hZ?{& zWae5)QAhBb3JuGZ^7v2W(;V}+T9ZR zX7J}%th3^08Tv@OkyW{u$KDoaRX6A3RGO9gdR9ChNbjJ-oSRL~!--tJ#&w|FX+?G) zu93H_-zco8^pM&ocex&oc`!%kK||iL&3nF{L)}x>=KJ2WVu6Y^`kC~7=Q>@-9@=;{ z*VT0XZmz)%d=KIGT`a-+;I55+e|TL=T~rv5`d6jhslQU1rJX%!NPV#GM`}djnYIl| z9P*o+`21{}@PO12y=$ip*xKCBwxYt>f@h0U$CS!Xb(&-H)A%Kwo!Iku>dxB7&jyxh zm-=ORg|m?_Yp1?hKGg4ajmxQ*8e3B>2NTZ>DqNH5e$zSi&5P92UoX{6J+$uR8HYy~ zQ=1)JmHJ4TnA&dk@>JJViSnRsyp-LRB=4rA$R$mZEObkj=m{oSeLYFGO-Yp5oMXAm z`6ZvtCh^^6kfIYQvTe0Ne*9pZ*WD;jbxAUONwU=D+)MDiB$>F~Bp?1TNo+fVOkq42 z{DAD@PtM8B+%Ny!FvyKgDKgI9C~Ho{N!f%r33D(?vexJEy{m)hdKBmYlat zi?2P@7%`p9VWUXuD6yX@k+}LNJ*L%UDjsq!>xdpxDpQZ-oSt009&aK!>(`guB6G%q zkKuUKhqI&nT0`ypG4u5Z+rk-{CX6@7k)6>pE@VyW>oz@lPG&8Lap#0ZoH_i9IvMut zE1inKknZ8A?99CMdj!Uh(xc=zJvK5{yE%n%UJz%+T9Z+nK`(~o2E5zHoPPs#{udkY zX^0W_teJh`|NAhBUK6)imnunZ?qVZidm2#gG1;LV?7uqGTlFDxpI=EhIn;nhlc-5n zjoge6c^NOpjBUvAv^QeJaU=H4rKb05GAyIWP;w45q^=30x^SlER3V6F7j7vJb)y`#Ocf}kuWe-^OJ{yZxk=Yrag}v@%8GRXZ?&MrDzwh&GYCp2(7PT}R zYpVS(&*+rZM2?s95<8`*$a^md+v_RUuer*+7u4%5vO`2KC9X7MPoL+5KPbo@pEG@W9oN_6O>z$Y&|4DF%7k(UbS*zZ}u7*91R7`p;P(QO%Z zzqc^X+epviwLA;RwLe`HgCuXpdNpFPmG@)`W2YxyEl6`BtIj>U*$48TudImI#KHAL*A%h!((C8TIB=J6dXAH=*YgH9$bN}RZRJ6ePx&<4y zSm3k7Lj4PBS_WG&Wp_R`$r&Skrx#@?*-sny>e*UqANWZ239Zbj=_U6bXr;*kl{9{? zKqIm{Hpdc}c1nRE6Y2YEQvj7i@a7pgkS~m{BZJ7h1z~9WAoi%JKNb`XpJCJ_9~^@x z^QZxKJ{o(;TU66q;C{x!Ib{nzE~iewo(#?hSz+Ik{Od_F@#F{}^6QFFx4U{%aqg#; zK{YhuKGs{thBOfeeG@sBqr`wMHc7g{I3}L+Q&3`slA3KTL!qf1f(=(g@bq>Fo^PVh zD*2Q(EqM(WqH%#|_~)~HuA5R<^I8nvwzNCufd(Is#u0b6>ndKjmHQopUd_zMDF*%wMm@G3VsIvzqJQ*C!iwD^bhU zm<4CDgH7GJAFO2!iwu~G+{1L0Qm1;Q(6u^2O`v^=(!DTQI@U;*FO!nxL)Qd(RyA3o zR%mf?odzd*(1$XH^TXfNxW$@+tpoS*R@B?#p4#nI1m3RFV|+dOJTs4;!@PI6)rg0; zjCd4hfW89#7T-{Bwnh$CU1J_fjiRK6IVhZ(gBGl@j#!}3Js=l%y{AG~{(wT)fDFWv z(?;3oo-7XnO!U4;lI|~!obNHpiCe5IueliUiTmvC2lPxxr+$M6_whC4EvHf+l8j73bPl}_$$7qKz4~89gxZj= zv`XFoA?>XHn%=|rKd?nTc1uZaAS!m=*Ywy)46(brj|yyd7YqYiscqPCPzJ;9B*h9rJ-n`=#*ZsV&Yobn}wp+{NA>VkGeojI3Zi-4dD#@FUOJ`?# zY0__bGquUTzEcCK=7(M*e395u1zc1jfyd~#^)`Z(tv$5Neo|>9$EIvk_@eq3*$)PSHAJd1&l0mLA+Q9QvpimED zUE^8fgR)3_P%PDtNay^6ayP&r;gKfk+n4^8&MK%mFHeFm+M9i#AU|kNE#@ZA%dj@g zSgrFPTeKK`pXd;?%!pMNn9oC&sN_f!sx@X$_Xp}3``LrJkp5rCv#{j`^BxXo;bsss zVE3?wF@*ib6Hv_ywmF*>Z;szo2(&)a?JS$UPYH1`Z(Lm>)U8Bwx<2~+R! zST2%h8cp4!b2bc*v)G%(xow3){i#r))|27+*w{|}Umo@;EA`kZesb&!*}*c6Wpk>Z zGqCH$cTUld&!2UZv`}J2?F-!3QDJ}B=a(nI5 ztw`s-u;;2KQm&w>-QwwxH5U?$0^)Oy+!A z?0Xi&1L$?k_4JT=R-Boe2ft-`P<>*qz?A0F?RaCUy3|ivw`nA6k{gM>4fl&niey~{ zd(H_Ydi8iDfDK1P9C57*ML@j61U4=9t1IKq?(s}=;be$tjs6Zm0-WIJpyvczqe4J zZf6B1Ut(Tga0r@r8i4YvIkz4gfN0KPWjJ@0;yF5-6ph9gqY;+JJ)V_(rHS{9g5H&1 zd98RXW!F$6$)bkRi1*4CzW!mx^DX+;f6BuX){Ad9^pm2h)YxYEv##4(^!uAg0<+7X zc2uC^Z+lF<%(?54O@`g02b~J?P1Lh8)-l5Ax_?YK%xC`YVfGI#Hlm7+zURRlZ!*cdKc|mf3K_z$SYdJ)MP>iCm*^=lGYVP=97k#Kt=JCe9a|`Y6=Noeffv$Mn*cBn?j*#hJb+ z{hB0*XANIWui=9+y?o%sIc&0uwLJC;oKTVToU6mN`Si1S!Trq{Ejkvl*Xtm2hB&9L zF&UXFVnV4YMi|*o8*jL0d*|kZ-+Q(6J|^o) zrZU-6hYsuM({Yw_8TUSCukuyNgwUZzJUdU`vyKS|i?h(>X*N=`>Hq$g=f^o4Bj_<4 z#2y6&y$5qYDb$a79Nk&-oIaEF(@ROB4l_yc6qD5NktFXu5@fVBQLHCaa4F%7Ps3C= zdC(i9S*u#W<7xc24q>c4KAxe)u?jkLIiSN$;asmaBAxTY;ua>;qAjyky-A^bI^o4(_3|#2fxdOfTx)8}t~)|5dQ#I`(q&kYESVJq zrwMulHl&WVf*e+|m)O%!t@vC3jL#zx`Z5isQ1;NqdCNQc7o@deC;XQvbZwf3xX2u& zvS)i-r$Tw$I0$hQBXQ?+8ro5({aB;EZA(nTf+BO z(Id{@g7|^tyzV+nRYShinIC|?)0nr*{Z>dr@_L;eW$O*j$=k`t>GTMvu6>w&y!%hM z$>C1L^2s3xXUXrh38haTkMqD*H>t{`f;!Kc&-*441tH{{YUjdbBY9GfVsY3IfC+yh zq3=b%vx(dj40e$rDfC~vK%Q$l^?AosdJd8MEAJ$chl^!S=>S}cibTw_G^jez2aUdR z@9x?p&@Kpd9z@d1o%znmIXHi+j@)})Am;o)OuiO{>LrPSjmh1V6CFW%_t14!=A%GIq*JS zS9*Uhl!H}*FuERfP-QBr&&!4WKm#dJxZM*%->FbaY!ATQ zz4UP#or(kGo67BQkr~r|%eY~I%nyyktvqtIE>^^sY$$iR`NN!L-k;QnfAcu6lk+;)lU!I!)|dJ*|9x;Y&IG2hN1MN|+C`$X3#1C`Ife*5 zQm3)jQ8fo{dQT}isZj0=WR1v`eVj*A(d|(V-mGsZH3$EZBJzy>J);rZCk@q?TCuOS ztJL88uQjD##&~jY+BC!mbG@XaU+2j}X*`|%{sW@$F)xdPkk}C z&`)p`bD4{IpL8S7>tw}(AQySXdcunmfq4Hl63+jm(l}%~=63SB}Df5%k62eOP~LU3p!eHAME_czNmJ(2KltW-fLzn{MiX zLb3D=#LWAVcuIaSX=yH^f?cKb>>_E)^V4)kBnB>`SHRv}9Qy7gLwXiSZRXlPnHt56 zUJG1va}ev_K;EkJ>h?%8@%kz9NkgugkSn3r2{X{;4N%j-!w zub*;qUm$y!cwIRD7$@bRR)&-8cwZn-j|L(lKN77uzSXHm9&@0RY+q0yD);`F!~5Bn zI2C%!2FW1Hy_(wKcH?Q=2jo|}BGT_{^Q9*+7Qg=ys9C-=0X!V^bX zB}H;!N-*?lJ@(w9zvKscd&IcP{MLmsa+wAp+~*d9f8fLiOY zPShqn=>NYYR#sX)5qc^d!?qj9<7ePc2^)GHPn0{2y)dSh7Dp=@(25#rW_hkJj>gLP zY2NH%(IQPl4I=p-zENjbdMsXguO}~dAsn^bm?yiHHTB;%eA<0LvZl}<&^-(VLkx(h zNlk#<+`MiH;xIu8*Nya4I+cjeg`PHa!z3yllwcNxrGK zH@V7ibe&2^auRN?1bxFH;gVB4!4E|Ox>P=&E$QKw`blbk8@~fIPUFEr$bDftj-Wxs|wj}oBhm5Gn{ZTQpDAWc_$LA_!jMm0}_zdieu z`1@{t7AM1=ctZ0}7|gkeNDU%~#WieS&p4^H#T)8~FwDQrwN(xJJ4M)#Vt+sa$*=TI z=jXeS53P^|T{{~hYRAgj=k)mUjKF}U?4{jKU$z2ri|W1NQAl>CT{vWFBK9B8z@{_2 zjyGc^_q`Vszr(TjFmshWGLYoN{-`AKn0haiIu-%Lzx0pu&A^mK=vjyyv$>#MzMt*=EDpReUa3lQAs`XI@((ibrRn(2qQGoc?89;5 z`I3HoO~cTbY)oO74D_8+40A@TY;WL+%-X!qH`2o^g`66B)v|8!vNDfr^0xE`Oh|-< z&z-|w8%F+&m-t9>ZRA+zyBd%>j``qydES1LcdO%#bT@v^3i>~+&t$JVeI!f9OPQtK z7{U8L@09_22eIZcnLOi2=8U}Z!pFy2G~n7<(#ePB*_fl4Am?6t)3-PbickZ#^FG;< zU5vl##>vmN%n=^L>*a4CYmk8k4fuSGjuW@N?4hG?MK$i1dK6{gW1K?0@egyT-+IEo zWCXso`X65P4fV5g%6MrO#{KDe@~wQXCppu{@P`fE=fujdsh)6h;n!WMgVoK%tcy0J zohHYs@xteh;TZXg=jU?8<$I9Xa(|-<(|!?edXn@H!;c+_c86z0mSU7`mDh zFy}peWBL0ACLWLlJyH!ovGOxy^vWW6Y!H_&lLRtZbRB!gF&NlFlSz!5sEh^Y=Xfex2j$WqU1rjwIs! z;tb3mXG4Qk`=so2Z%j#E1hbC3dEz~+-)cj7_FGRV=>^kt_Qg3F5PBs8vp9~q1;@!+ z^0_fSVW>2M{-Gt^g7&p9EHnFQ8k!GWsbG$|KA`>GuQ$z=HEqrA#~+(Fj#Z?l zSH7PT+~=OztA)PZICa~$v8+D_T}~2(Z@fI9*XA*Yc=`K>K^_h<%7i?6)skm_Lft=^ z++m&GCb7>kO7&_6={3S6>qaI@cIN}qw4p)1QE$#`pCp|)UVX@nmr_9ODg=w6|d#1E_rR! zJ}(4xP~yf!W>|!hIpnkTbD5Gg6mLwvtwO;DZ``TRoQ;Y6dosNQwyVhSDAD(V7Ybi7 zha;U?^fmchM|$IwFYDN!nbkg%`P7^v$bTxw03(Lj=OL5qJ|8 zj`QauFq-e*RUF0)l5q5CqlKPY#bs(bYaHqS;KZJYG%cFfCeN6|p3I6`Y?=@O)e`FQ z&9%%LjlkdT)LO3b*o|9d#HhRx5=w>08>Cw@;JJ$#z5 z4|J;$F4UIp45ok2ZTc|QXAa>idhb*>;wa}c3pJk+S6JKGNxo1=uf#f;7+ai)W3{s| zZwUQ%qRGEUWTL$y3lAP;V)_a4($qVq24pf1Gy``zE;grTcJ@yeMx4*Ywk=uMJBmI& ze9lHk(yO2;GpoyzmE<_K?*=`psq^=3nT513?8|7voNE4DJ=Z$b=VxP~ne}Ye!XNNe z_M(^Eoz+O{wDlC*W>0Z==OyLlHI!BKR(v=_C2`d~<$=4mI5zNJfDB23e?42OX7-EyYo;KM$fs9s-5?Dm@~2n zkUbo(p}$!mZU>QF{H#G@ELo@_!SLA|f`6!yn7xCcoE(V37lW{JIr&BZVBAR!#`|{~ zGT%XXdY=2g-}H*}<=3e>4H*y&$1&WK`wqasO2Ig-)u77kAl&F54C8Fp+tooR=*r$l zezxo9Kn$S%u;yzpT&J>Ub~?EyYT&&tvVZV8`KOuDFf5Kj&&7H?urc@cb`<7QYx(98 zjmQvY8nAzF!AE)m^dO&DL603H^ypS28vXn0aV<3(tLt+A%vwlv7CFXeQ8;j)-gJK4 zn^$EGULpeD;BjOT#~PSs!R=LDS@PbZljT zV|Uh4zNW!h!`uW{{<|r2C#G94JKchDr7dXtFb%)S2rR3bj=!nfkG-FUO<`%w^Ja}9 zkUZ6C3+5^;P@cEoLlgQ-tmpSgI;tt?y|dT?EKkF#GU>S4n*ZO7dDTT0d@h#`rz%zy zIa;Y*Fz0qAGie=j@un?37u&P$|1%dO`}5ze@^IlOGp-7Av94_%iU*R5s%k}_DfEe$ zMlZR8+=o-^3dx|(lWfIZ9s2{PGG}QRYvNt_*-fli!oA-%pFHe*$?qL%MJC^0KbyHJ zW32e|iFz16yFb~h_&8q)Y|UQ2jt%A487JxC!`$aeO=No~Z>enWEk`!Ao zwJo{C+VnkL)=0um`bzJ;Zt~%(Cws0{vZ=JUc=qy?e@`l<4msf8$Gl`}inn;>(U;NJ zM}l?k^4io$`k(TWH(%W(!LgCNa%d<{yWHg`nacA&J!Matr;OXlEXCh;X!zu}e5t6w z#977iJirbgKGE#j5XR9fD8Jm#hm`xrrRF5CCqF|k& zN4a)-s1xbQXwp+xV*mFsJw_g)r&dE|nRTT;@_^6Zh$z$ypvUQRX2AbVCNhn@1+}hI z_IeEDb5z_>j{$uCa_>YzrDV^%AL~f@Q8>|@d2w_3o<6KivQFCRPZVn}Y1mxKg2s*L zn@G*1QAZ2Bs6pY&?UZh(%+O^M}9pEN?c_7wI0s!F*nhr^%nI2IpX+33LUMr%R@5MmnAI&08#Y;CT)?{Nw_Ma_ zrkr18GQ@q!0wpmwBPEwTtK^FLeNSGpFO)U9QKPKf_w$+gNKUx971>5B8c^f)A7{l* zYYyD`49>kupH+U=u;saU+LD~ijtk~Ky8S6PdOc2=5KuF9^wgK;OS$D!t4@B@u5G(K z^Q{#+bN{r?Z!D%IN^`FbR!WywwLH22Dz4-bD~Zdqr!`NgBc_F;PWRKFVu=4TJroVmC1in+c2 zUUT?sm3igbShMSuz9~o8k22HFC}ZeHf1bT6ovN^|SI;OT*-uwgoG9aR;$_&BM7iy0 zloNC5k@2@drteOYmiyx6NP4`)@ckLguE@+Z$<{sxWixwRX1FIx$V>8yiShEvKT&eL z*-IHi??&cH7k6OK3wx4u^o1;IHb|YMIB~s@ApPj$UDPQ_hFv9}I9Q1jTpM1=@kXP@ zN^H5WqPG_Fr`xMAg?xdJ9W%~4d&8gX!`O5$^y;NV@=x|waZPzQ&>J4JnG?5*zKpE9 z{e8(3XA`{fG29zD551A5Q^LLxb%amcE0{ddE`c5zcI0mgRY*%xLRE<#{xiH$ae)uk zo$$q4XV!emYf+^){TAur|9q(y+WA`iOpU;#2-c@sN1$~Ed#miYetgd!I_~eC&uQ`Z zYYRwc;8I%bCD-FnAsl+HJB#dfm>Czr-&Y6y6)j48(3|lY^8nZf z^J8x~Vz~yLv5PgY&)i$HR(Y3u-Otnl7PesB^l2hC3^u}(Y~%E629)AnH0K`!YP?|P zG}n*i$OkoHUCMtAwX+S(k>*;jQ3E6D=?&=a$3MFoaq$rMqcGtg>H?NMXGgnD=;@;Z?%Oy_!V z2zyeJGcn24)MmO5Bd5rqfq4}@ z`8@+zyKBqrjZO69&nKh9I+`anyHl)pqDvN1`Tu#@TqEw!L`EF7v!z+6bSVq}p3Q>Y zqW|R?OPW=Z{?t)+{Od24pr+E%$5Y-;Z6qtnt$(2xud}@Zr`Fmb`lbR~`EQ?cAvk(2 z7%}v3+Bz}>#o_eUyUyI;wb4KVS?|ZJEo_QL^-^TNa>%H0{PD<4$DB%M(TC&F?fMox zX3s*m=T;Q3mLE7H5B`JbdtkM~Og3cGmqy~3+d|eIqqp~AAGt<8#MZHi)ELLC>vsx_ z+^@ic$IK1QwaLc?3S8xU683;z7$=y!!{howKkP-zHO%Uy*FwE5C~+(rt#;`V97-mw zEc2!(S}^_uGtB-?N2T8uOrMaBHT0Ky8JmY5$8*szn7kgxAN$Q@t~o|^%IhHSlYQm( zEqW<$Yb4z^vMv(tCp|uK{!38cS${jsa3W*5(;tpmU4{6X$E_F|C2NfWF>d zJWo@$Fw2@AgeS?x4@jqdJfr?@l*_B}2Bl}Q~ylFG85%->AMtI3Bc;*mIzBwA+QR$cvcovZ}$vu#> zT+KDx39|)BTC%1mt$6Ck4DLGglB#QkGuK-_>|0tm%}s*dsO0<|cc~ssma(vjxYSjk zOLnpBHYpJIojznmHgW7ghHzUjt|bQH$>m@ie-(_BI1L7KE&cc*Ye~iI+j+(L_bv0% z(&>B5Idlx?KeyUvp@_C%vx|kdb~^f#Q;EKshgx=dIPf|bUM^P5{@aSHjp@A=;wATY zH`~dr9={)OozJz!suf(P_adLt zGX&H1^p7mH1(Cn>$YHIo)JHwG6)+=iFg?@$wZO{tXv`qa!*eWXy~2VE3+X$~W3l5} zu}iHyw6e2eR68q~1+x8L4YKs7QSO{&U+cod;@T!r^kNk4FBLT!CHm3l?;Bt5G(MQ` z>Uohu_&3dyFjjHyz%*(ZX>&dANKdW}P8daM}pvX%qPs`oaFn!tD$6*V~$f zHfvbR|Hhnv7TI`5FR9EO>_?^NUv28hjmS3c<-dC=k4W3?Cgy}4kr~k@`E}1Es_zE* zPLJOjiAv1>L{25o2Zj=ViiQ!R+

53LT%t#X`a*-QHQ1DQDLv28vpkyBqqzd$d{+(TyWlolWJwWz&{OiHR2 zo)+@)kLme$$p{~wpFj_CpW!?|WGk0;BmZgS`Qbi1U`iG~PbSO#j=42tx?N`|)NTK= zQ?GeXkB9Z-JWnaq^<3=Kix4L%Cya8i-a+vmlPD(o9^~F3KjT7w$j|h)qP`Nj!k3(+ z5A}N`Ht*s*H%N<4WjKe;)1mVSEmo;`j>;LacbgHDzA)?IF?%jKzqHuJyolFX2+SaZ zF@?U2&g9r*=|6EH10Tr9^m#xZ#52rT>Y-3yWi4paCWU&&4dyM;7rONk`ahFHow+4R zGO|rl`nC#AGgVmghyKamsre{XxE<~bUwR?O=1?=9q{A=How0f?@=I_oJx71E4eY_J z%Q+3q2j{VEre1q5HJjdSWEwdyEp5ZxYo4F!v+1dMo%{vsJYP35%V)7d{h+5py&{cu z5ccgJdYmLxxE`wb@rXFhG|KS#Nz%@d=Y`j6+)!VPxU9tS(Z1NZTZMYdnbp~Zy$EDw zY#nqM)Iy7xC>@^cHsL`b=h9Q`GrdheGGA&m3Cz|gNqw4+|C_p#biOg594{_J-u&hGnu$tDWk}wZBRFn3HOxJ{H0RH#ukaoFa?IG$amY> zWTe_2A&2eI?WP88=5o)`hWi6^2zDj1{y&j>lsWWcToMh(=h0Znu`%|D9#6Q=-yBG< zKbr-|?b0zz$F(?ly=PA3^4Y61dm&l#9rQpPlZWOZd6-y~i(`ZRr8)WcZSOfIlaX69 z&{q;;Jfut=JM7Wg<4c8-I6qr~aH9g1TH3+4p9bHnhCo+egTh*z$EFOxp+GX{59kX! zfEmwE*=IF{eO6nU+wc!x$GA84NymX^=~(s5f=3o<6rYFa%Je<{$Z_xq zJ#ko%ezw#{dIh(Xq)shm`!sJU#Xh=s5zWNw)_;t-9fq|dLs-!c(-#*?rylm`!nwS9 zGW)-V4?y)0dNW=Qfn$>a*vuub3=kZO+7apZjp)IP`~^T{Fm+yZ<34M+U5a20cm=6zX=B4$Afq z2KmI^uj(*K$pc35-EERnV|;+eO8mahKMOdIUG}9XEBmob9B&?I;l;Yi!3$cf^w6QW zmX7`EMhvEQYv5cuslE}R)PaxOH6Wb~+Ta%K3E-TyYj748a@~AyCpF!xtl2!_G5jW5 zd7CUX$Hn7+v5v|9ghli@e!cCWJU?raylX~jRsW#ajrT=dLlr)4^+j8b(^opG5U8Y| z?)}9$_n00lb?7;GMvL~{n5A5idCw0y9;X{o-p5F0*+4%UBNDi;IDR$@>7U4aa&BM4 zIsV>I&S7`i<3w-TEtl!%vV>kZ~(V^v2@_KW0h`+%(Ka<{v)l8VkT3^l} zBhIX5UePR$(bSgz*}4(-S#|_TgL+LaveH^&&EsIlGKf zYE--oox{XoioWQ+pWec&wfNVGo}SSW ztiS8fW0($YH=9`ZFrw)v1E!2*eJYPy{CFdx=44~_V`g$I=?7Ai>}fnb1PocoCQrG) z8#%^~3iYp63iW-?VL@Db=(;D$=f&J}k2xq(a8Ul*OFyMcM)_WiEN)vBLYH&D>q8EI zJu|WT_@Kx~hmG9Jmf-bzQALOMlXdvgo*7i$CggIj*T~<5u{-D+`ON@js0m3LW|MDY zO|}l#WGCqHv^*1^`}3H}GMk+1opsOXtI58F4o4MgP5l4zj4#X{(y2CcQbL0;uM(fr zvuOx!X2t%xb)@gtA{lqIKYCw@LguS9`ZVRDdm|^w2q=^@1^v+3NsqUNRD7RBU%#F1 zvY$R>3z%=)$CrAOhGWlcE3S8Qm3QRbIwc3<26bb@KJGExm~l@oZv?YjA~y$N%+n~G z8N@v0Usim);V2ht6-fBz0QRZqk+qf_;sR=|^_-+><$SrYy&t?kZN{Wy>^HiegOXmIneK zl8d>PhH_lXtMZ*?iN6B%3jd5J~1%eL27)mXD&DAuNrKaVicNN3cBH4DKKYBi4 zp6o^PswZ+V(~kaAM-qi zF1KLAxm-kqk~`y`$md6Y%-hRcV;wceJGmG+*+rb0Gh6d-9#4H{%~(^(gs``Nyob#E zPCq;T+_i_PY0gQ*@;c0|E@~j>9ExOMBj!_iGq0w<1qXQ^9`tdOBYlfSM?P-o1lAOI zetJ%z9=NT6R9%)Yr+P4dX8`wA*=ewUnTzPwE;5_`j0c!UJhmhI4$E7Rsm*1*u%75b z3q)5p2y<$(r#yu@%Tsd@aokycJuVQ}s37#2$NENyg*kQXL1d=U$2Eo0pFQubIp3X3 zPDO>oIat!LzC3-9FC!ZS(4!;@ky$+d4m_Xt9mQpGft*$J$B<^^<5O}wsS7Y5}g9Udsk~{Wxk@#`+(_9^dOkUqI z?@}>)S}xqCG!XyG#bO`I^UyO2KY0I?Qj%BQQBPXz%9o#a1JQ) z$m5rItPMbobowwxk%v{#2eX8e1U@Q|FE@e^{ukFd=hG09Y{l5EUh?;?Uvj8xAZC3h zcSf#x+l^d==eWq8y9JWpf?9cF@`L*=^n2uWAvYKKpipYtm?W6)o2=9@=bd}!)m5l%x3yxir?Y&Y!0ZU-Dc2~7#01uajBm-M{&AA` zEo@SfTx82@QP|_22HTt*q;z$ZRObSj#{BUkubFAYUi}K=b5MVF14%qpB&&0Rkk0Y# z^V2j;WUVIPWqsN7^^bH=1)=gXa)qbU5ZQt{a&M)i(l0etOP`WKdR#e`hGEp4eL@<@ z?#hMo?>zRW^om9d^Td0P%O#J*+`41`<+*F{{<EEg|QU1cz9B4ZwFpngmr zQbQW{kH|$I@~1)Zza^n-Ft%OiIK%b0BGL+dwuhKQcs?ulN9Day_(R@s;~Xn|+wy*+ zMsurIAaYleBc99OD<=ohX)dy6(I2_DH4r5`aV%k+K&JA(D$Voht>*K-g8XcDeOc*H zEQeW_In{*q4D#9sBXV)IR|AP@QXuO+0#J>gAJ1{`#vv=d{p~8x%N0wR3LLk8)BiM+ zymo6VUcp_0$0=~$f&LP&qtI`08oF?tjLMFa>kmDU+n7D;V!#`&Q(i8i4_zhlM4P?v zHgFM6oH0UIhy57KY*h+o?> z;pM{h#F;o5OAc|kB^=#0(l@OfdB*29ytTy3fp_$0vXPHFMZdg(%oTlU!~N#5^4A?D zZdM9s{vCOo>C{el*-$v|fDEM%WA!78z-(d+t)GdYOdG<7#L8BXI}4$g67^m;@{E&8 zE7a^Nk}2!S_hr#vvKxJlu4kea=kYa~{qpjJCw-$La4XXQ|B;!nY@|<|bDY>+^v12n zVR(Oz++|t%^i|sI9+duXCuh*sk2J@)cHqjvoG9-5{w zhq`0Dj3tlLg73d$&+MO6`oxiU+sQnqyQ94^*C8C+2a$W|KyI-&*Mhcv@|wO^dve0j zw7db!cs{?j<{D!i`!T2sWH|A*~5O|P3cVhD zW3T+R(Hm>xxaQ&cxuvEr(`g$v)91^RdA>g_VQ9CXdBi*qr{n1>7r0MC4PMl(!{KV8 zpVZ?FJUwT_xAa)~aM%lf=7nQA*N+PhWoz9=TqeKQ?UghWH#7W<-%#TuXtxOH2%Wt0lvgD*b#>;$_7uxTNV8154 zr}}5&KtJjN)#Ajvv?u3>aD>!IL>jrOp5>T%@o2wf?BRJB%3NA%^M8%bfFh826aH~> zdY3m&c498=#Y8*=wfULMN%uC$`bXpzYtt*C3;D_u8Q40I>;8HNq{MtL_{1-SUj*}@ zxo7$5&wYwtoFupY?|zQJg~s&X{6P+Jm<=Ny#!I5X19xsmU}-*c#;<0g^jsUP1u1fH$rd2X74HciO+hQ~^p!ULU(BJgMhx!UI$ zSpLI?cI1C=Z}CLMaf@)Q7wZ>W={s3yL+6|XDRa^r?iClo(2ie!P5*>k8|tuL^?fCM z8^ms!*3To2TSM_f#Q| z{DL{-W%tQ0@;Ax-UfFSOW&lp&#PYV)&e;zke$) z%<3GD_zld>;@8cIUl7XXJ6zV44@p6teuD}=cZDc(r_;m(u z@%S%{PLPymp6GKrj9yFJ!v$wx=qMY4nD=c*e((u7)`2S%vFiwP+xhv8N5{)_@~VT5 zMquX=>Tv&Npw-o4_B6&zRz2n{FVe!+n)R728TjR@PqcE&3$35Y99BUf3arM%7#BnDy|)eKuCX#`7JI|` zL?HFH0Tu3Lz_T%V;f=AP9qfhaY8_@T;dsUSJj2BCs$jotbnvD>j}|q9$diVUPvRcV z&uhOtyz0*WNan7cNQC}d1}2bO9Cd|0EHAwkxt+S&!S;uJ=eL)R3(fCtelRnw!@T*#i*^-4j-GM&Jhshl`s?&&O}b`@ z1Uarul+yn6Vhl)lNzEKHDPMF+%>_f{A8cxHnpilTI)v>(UJbB>1_=95LFU!&?l zf|U3X&y0sSITMg5<=9()teBi+g(O+kDqe1WAQ$PIDB<}=iR0&HG(9Yf>FG0Tt3e{E zKNx!_Nxyjs(&C*#s&Fi7_DG3ELwt~C$DE_dDsUI-2eGNPt{MHhYBOmX*2bPs#+YQ zM`OR%E36IDgN8kvRt3ZqI&$ECbH-`}&Px zPp;005$6n0tY9B%H6!l2u`aEmXMmdlhsZd-AN@c1UU6s1N`B>M9X8EsVv(?f&nkvCjpbm6>GaRW1* zBFTf_XYN&(44hJ&GimJfy>o0_nD0ftS>JW)|474@-eVGw3JRLV+gik6aXAB+Ww< z7(IhABD-*S@kpN~l56`=&3y$88`zaJa|* zEx}M}_^QG@#HN9$`$YqffFNvM6#~Cc%)gD~p_dLl7g-ly_JDoCJ;_rguy2^PkcMaIk93gSV`w^> zEK9@rJFG*Pm<4f*pEZE&!87_O=~+)In}?~a(G1^6-QSb?TshX#9j$n@){2{~Db;9B zjjtYk8+EL=v!=XxWiGP)m_KdHLGgO-cd6;ErVh2bBQpv&SYdOdwnd%hELnk&s?5Um zv0@AN;||rV_#8l9OPPm?_4BYWoE{er^lU0gUx#D4XyD5l2=cIdv$w=`U~gN3N>-2o zejCQ;=eoBHobDvn(H^pSwU>NaO+Tk++}AE?EXO9hNsBS=GO%17Y3JZ6Q`49k-AE+| zCc29sH9Xe`4W+o0pG;ipB4q;|#lB@jDP7Z5q$~5KqgA5)%SUpUXC10l$+s{s`8Sza zla2gkZ4*D4mBr6t&))GM>HJfaIYm;DiKC`V9>>pw-ShR-Pjs`czGo!>l816|y zxXeDxY&Ch0pM3s4@;T85G5bk_j@y`bGn1KFjYHt!&*v~X7ku%q+?E^dudx$7^jgMnBi%-dgItU zo!&2e-nRdwPDgFBEuXjV(PRu~rDNg@3$|BE$9|V|vLqH9+R0p#@HBkOXTC$a1^$Wb zBd&ZF>sMRwdO#YIhgwkQEbE0@dY_Kxvq>EzjQ^*;o5mhk))iIk-ygz^yno3N9pJMR z$!BO4Sw}u+q2z>*yd_V3j-IL)EQonc&zXF($o1%#NK7C9-kWFNLO;L_DHr7Tx z%Fv6Hb--Y1UNJja-};e@**C24+Rltdj~r6%}1 z7b{QXBJNBse2$V|9B+loKUS>YO@4STS;jrgww}!Ac>sM%no^7OBG2;aKDLuc|HILk=PB~t|V!qINOZ!>*uI8Cn8m5*QaNS&Qr>gySlfJ#_=*D(KvMZT` zeDlnqt$kB1|2mo-YTYoOu4&(XcE!KVqo_{R zl9|!I^FmIPH|}3kqLzj=zEE-^1p;dNpq1KCEtt7B^l* z;BDUsGzldi`IG)CeDzf5aNfoo>XpnWX{p7tAIzFKtA#!HI7cVa3uXj!K9}>oCCCK* zOoVMR^Pb;vEyy~Po|?)&t^qI4GNOJH1Cp*8kg~~yDU0dLScQJx+*?*KQ1{{*Z~I#M zE1oexRo;XN+ymF<*W4zu7w`+$o2`xbc+r4>^+pUEM%|(g*M`(_-aD{YMoZ3-YtAx1 z3@FR`WCY(o%3#8^czQhsWaAgtY&~{zy>>4XtEOjS&;+j8&a>ZTHS3duGg03?3!{#( z2KJVo-9|DT+*_8eNY1f6dqY|Cy)h{hi@25?=fzCf5@du9vv-#J=Ue>$rGA-+b;w3X zuK#W|&%(pS%%!fHg;q-HP8Mp5Ls*k#ZFYTf7QlMsfBU!pUQg{jWKR(1m+AD>?x7<0 zt`h$Pp0d+Jfrk%SA2HgYx~2r0^dkdC{wveKvAT$Uh*28)8-!rQFAWOTX<$!HIQl8a z!K=}Doxy&KylBi?7mbS7=>yC0t((?D-)#%}e^190e`aRV(<*3RE?O+IB8=mQ%M;G+ z@yzXnpOo-wB2y!LCHJbIIBa58W&=MdwU50183jHzvqMSh!T+r#jm*HFdpii*4lx(A z30d|)4OXuX!NJ|ZFf5HGOGxJ7F#QL|(aY(tEojIwJ$11K_D$(G$g%Hp4{~UQWGs^{ z$oNd}0**V6{5kK(z~zy~_@Nrt?@%*r9hvUa!#_lt`dgamWCKHVVO=3n8e; zdCZ=#{y(A+MUJOkbTs=T$?m_QXVYN%ZLPH+cr1JP3I@FB?b(*Oro3L`Yx5YwqH&eX&ZnvD#ksNthsjyqq&HgHF3yz;)6ru$*Of~- zPkNE(;TkR9^8@N=xTfouhX{HzUOttF4tKp}LfPgLX!eoe_gY9z_K&o;c}d5br=SGQgOp;gh z>Rq`hNnXr0N{!(OQa;KDrQLk7_`V8b(tWV&tqRj~l=z^~!ihBjpHQ+O2|AR64vABA zm@&$TWw(szIM|4}9M`_JHDY87=HAa`A3OOE1O1!aZe`)s4EncL&%)IOE;G_g~k9&C_j9}}fGElHaFW>#jGBx(N6BweF@a9QIE+jSq9zp0>F>_fK5 z2U!{&rp?o0*`NsgY@|c~$;_e*;`p1*{WZtFN#p59OE$cW&43lX=;Oq3C;J9_e9vX0 z+JkJgo==W?8vSOq3iZFs6zVQb?bIXhku%_*J0J3E8lyxzn5d;BNuS9^G0!(j=^%r2 ztww$@i&+yk6?TqQq1j&gBetgp*Fw%M-t2AUIKSyCvm!V@jHgy#>KOUTXB@{r7|4bh zF}pg)-j3u9j*|Zlqo3_fj+c(vC`aDmE%Qxpj8UlH&||C0UWIyi5`71q?bME03Uzu7 zvLH`P^1a9?R)3QmrQcS|X9lV6sX}(R3JsmfI9&3ee+siCvX(qgRaYh9S0&C(Q>b5jH)7KqdPh?CIAWmAP&*41 zdG9RX+>yLK3+^Mb5ud404_aZTzR7EKlz*Q=|HxYj3Ux#FU#!_e{?%|$@}DG0nV3T| z_2xm*y;mY#--zC@^wsR#2%6?x6EyI_p%FS^sazq)__iHlGl)A?uer?ZkYL`%`KX@tBg_n6evGm$v{mXRL zL*hpHiE2UiEi^#JuTwTqh@4;C_aC;P3Pk zzr{7~6)Ud%Wbd4g8F|;)6UTkq0rG>V^XL;fUnz>V{!)Ffj})dTuzIf@3ai;eQA&Y? zm3Al|WRt7MLU5+@0Q7he1P?N4XIh3pTP+0rr}22+(#Po(xo++q`Zv{M<9hZ8Y~p(T z6!#2yoJUWjV_!0}g11_5lXK^Q#a0B;e{kgb57@=|HJW4eH+nIua=BOC)>snG_{sd4 ze$w-YN>Vs~Mh#NH|6P$Jne6ePwgNY1(?4=MvnL8Q`0)98^Z_fDuKj?@ zR?es6eWX^3uiP)~DaTDsr1Cp&i73I|K592by%jj}LV*USi=^p!dujxBxEMy3k#p(w zLe5>uAt*a_0F>DpjCG5~NRG!j1390s?vWJkMJ1x7PdbH*2{>CJEureO>1| z=lssz3g)b7AbLCq#4$hq{93#w9hmd>(WAvKJpya!p*q0YOKr|? z{I;NoIpKftJ}=yYrL1W@J;~gTXN}Nka#ZK7$l%#5#26=~h8~iSPZGqxyh#Qn9+bE2 z)jVFpoS-B%-fwupsj(*(1$n~aN1c{WI+QKPGr8Yl>UKn+Rx@hncHo*{WI|pgGqo() z1KdaLLDp-BE-+KunzhYStexJ?K;^vl1R3W`9PDrW3w z9K9HBgq3kDp&MDtBPI-Cyjs;f3q#vxVy9Oo6r7{4mq!l%5PN~1^sT#1{mQ9!8g&@= zX2y%L#spb&I9_zI2c=7_L8j>vrBs&$8O#2}lVd8pHmgy=o3Zo2P)jdm7#8saeL1UCi$)E@gZ_OrNILWKUc1 ze%_XehhH+Gr{4bi1(|4`OHEA!<2yOV;9!MjGx^*n)Qe0Yqx-x6|Hm`>T&^XvRu{@r zC+dH3KDPch)_Rs^qhIC5@_QV0$_Dr&upRa6o}^%uQw~nfb(8hC*Ba12XMQ$p+w03@@;Hr0 zQ?dMFBuacuMW@x|Xo~8}{E5Xft`E7J?opU9ITZtHQGc+ho0Q<=>(!z^N>CJ5c231^ zSP}8gS+3v8lczoW(PDZOf@0`joS%&@b85-@)zlo|-2b~yQE2@x1t*I*v%1SgW}GRO z-Q>S+4v(fc2mOA|Sdmbm6xRfDQvT$yg2|nc>zop6#g+tj@u~SoQtxpVYDXmg2~WZD znpSM+dWAd`SOK6 zwqMHW@w_JImk-e=x~_|~^Zz4_s0a6OWEArT3;u3OZR2@r8OoY1vsXCu)8mdy8rrd5 z-RhpR47vSB&ir9c=b*=o&=hq4n2l>{XKA`GU(`xJq&<$pkM^8-F8T;fbR!x4f;tWj zeNo2{g=_6upJ%S!xVBOb*DREME0{kY<@w@CDozwwG3q`!&3Q#K|Gh8%sU3x*nPlD> z2YTLYBBhdxWED9n(?#;Cc^1Ug%E8_Nj#9(3K&)p2v132`231oLqO?L0Qb#mxi=<}T z09ZOiK@O#$j63V_DUBqT{=Xv|`r+`0D45AZm17O@J=D^&pipYB^+$&R%(<#?o{n7M zC-$vYarXYgZ1TCAqtPjW+*S=K&DQ*Z7N z@57{w6h!s3BJ4&(sY>7EzB)fRI&X$k)(C?#kSc|==41Wl{u?jTU}r7<`$6|CXYFu_f-sa469|M?nYNBX!?h~=Yjb0 zBnoR8Q|q0z!fRbaNysP?bp-V;UXfe;l7c?T*;p1|PnK*ckkee(b#gaj@(S{6&B+(1 zxXH?ktj{}9U$RFO9N(s(bVxRyY<7|y`j-vo{r0X^6#TuYqsQyxKfqZ6>3ue6nlBPs zvfgn#1)igWr|-%Fh1q-pF$j=jZQ@w8GZKQF^Z|mZUnqP;xzXFQzYfMm8$! zXe`-nsA2HQA6ptnVc+T$6lG;&_}d0D=175*t?7>j{JC2;r;`28#^5iUN%1U_s}bag zS=YAfN)L`iD~@Nl%Z719Vo3Fc!vykl6D>fw986Akl^)ZJq;>=H)J@2ZHfK$`d^VoV zca-}vHksw_kKU8GzdcOBq@UUJ_oydBHj9R3qo;KRFt)FUSSopx$Djn^+IzNmcqpZ!X7qNd-M8(yVAO z)=5^(vB{?30F<~Ih22xQ?=9eZzvv>~zl!DW=YCic!F*s|3WmJS#>cvi<=Vr1X_xDd zDcm=D=BFUDi4~PMILT?pVyXGb4-0ovdt@;AKjst9-Tuiymwe{zu!>QrhJ$jiJ8kQF5{eB9XZ}6(xAxW~x8z-?VJg|!TUy;?Q z>$fQ#KT?XR-5D?I$t4}U7LFq$47j-?9mBrZpgKsMfYM5gR#I1qyj8Du8OT3ogPkc} zI=xmRe^VIBttBt>ki6b<8;Tyq$Vl>NEvZ*nvAU6ZM(J3+g8tEE;$^5kHKBUw@O^_3 zb=){hH`>N}W4sjB=lp+a80>@TmssSB{ZQaF|kmsrqEAP6Kmuwb}HH(bc z$?NvKB+mv5$Zt|_uJCC%e2Ws`RE8YWL;B46CrITD?uf2NJ-#Ti41+S@z})C4CzTf+1K&XIK~}s8inCacj~)s zc!0F6^qao5Pab|y!lxm9ll?jWeG`ag9f_t(J0S*>(*tD(@m-B0A2EL-!6S+JGhXirH=Yd_Ex2#z}j#WV| zC-QW06**_ZvzOESF!Wnu!1`$Z+%ELneH$kiFSw&PN{iDm)P?j(=b6KXGvNvHiuYR& z`j5~1%Y?r3$dk6G|17Wb_9727<^AUCXv7#D{lr@+G@j(7l%=SzSBgHNSLpjZBNNLf z*)aA(g4A{Lz_IPr%$jb1`=xYLT16k{c?aa(d@?jU!*T100Y`bAGglNNhdx{H={Nn@ z5X!k410tGGFYg6?gm+S>^0yj22a|(i{eRpN>eDfYsZ%>%u02y?!d@-fjApN46uDh1 z*F_?~&mPOc@8S3sXheSX4D@&BnfX<${G6`h8C!>o9Sm4Eh5DYnKlh)Gl{(bZTnj=bF(ns9 zf8OTPl}Ip`XC0+b|uCXOSm870*7J67HYL{e{v8 zd}aokF~4}$B9^(RJKo!cqhBNTWhSKKZ4=H>{f?Cbylz(}P%~|x0Xve?akeej9e-}} zZ592H$n7p>|A+kD=X@J_%}fwIea4@xr#Eb4Bl@38$L?;-5$MC#b0T|SYHDI+8Zc}c z^Fh`MHP>V1!Xyd&v!S?OtQ=oSJ<8HL@*?zB2$Q|$mG1w1CrObT99mO>YIH3$&pS@y0%GEHRY3> z<|vcrZd{NuteG}BxnZy5i=E4*s56@-D}tA$e0lOS`SG3&Nh9qBr(7I(A$h~hnaOuI z$4ZGs^c1`qD@ibC*rk2UO*Oi(M{S~a)Z{8;60It@KlH$w%Ur)?94#%CXcMhO zqX{bXXs)8pA8S8@`P^e_(-Sx%XvnN8>@8aW=Bn(QuKaq z!To!|agh4LW1sAIJlepZJIlXPgkdH@+mL@GmWTyf;A`B z;=Vev*3{I9;cl#fJvYL=qv3z%Ia-X!K>4v`8EcSLXI&#Ui{63zsGrDQ@((|9i4LsI zvu>xmn~p~>(-AU^yd(d9HJBcOx3duai#4JO>^+lbJi+sbS3GO_`P6V2!P?rR4BQ`+ z!CqQAy2NB)G@l#yj+#BqGEkNMkun>&&!us0Har7&lQK~Ej*IB;ImwSNu3|0YD#KU0 zN#21blF_J<^kiT5YK&SQ{PdQ&SJcvgjNBnP8WI5rm5`S;4FzBT}5+EB?*JvrQSUk8C6Fq?>;!lGkWA+iB-#4 z7YF&Z-9;+pJIm(CB3VO^TBBQ`oS`nk@Q`BJZzz;@T?(X6WBTT#70RAlHreY{B(}K< z6k3bqpGE9NC~Y!vK%unKu^+IZP}<}cigtnm_dh6bxV$|=J}I#6G3yHS*s!G1r-J%( zBO(?5ovAS84D-%kHmN*90sXf^3Gq^(^qT_doKPfNE(IWOus=pJKPf&>K5;y2!Ulgd z=^BWLqXCHP?~nIc0VrKJ2-UUzD0?LkZ6C7Vxh?>Q9+Q8h4t~h10Muc9X!XqieNq_81qD~$A7-w6MZ~WxTdCUM9 zILo$AP3^W2dX1bUd*~aDi-XA-DyStlPmf>6qTrB8Kk2biP%*D>yOTL2^R|ktjWjew z!}CKlCasP}ZT=~`7KP)7sU6pbeB!Za+-5#r4fL+c(PL~A=6a9xIJlRyf3KN$vuE>t zD4$cCen}tc$J?Dcb6+E|ZF(y1>?8Z6BU|`4X9Vk8uwt|YONORmeFY1()>83r9ri7L zrg9dBnoA=r_{u(pIW+|r@>4NA%Ys!g7JRS3{y6(BD?U+Uj(y+{tf6=QmJLYa*&Gai^&8%Jx_GVsKVBu>X{=gYx>IlTSrJ;KN92mY?acuy5B6q2w$o_hZ zU1XsW=;aY(rS36v#mK8&PSh4Xr*{ne7E7~~kdLS32s^lWji+%8s^r|*c zd#M_k$mu!Qv4LJ;Q?2OV&x$>)DQvl5#r%8pHrPcy$FVt>$J%~l{@mn|IXK!i2cgc? zbUf=O$A`H~-c+*#&P?;^Bbz7)2zM>5yU&pG5PjMTUA<~--pLdmaX z2mA8meA^dG^l6*etuL0h3I%6j6zH(Y4(@jq@LI1xzdzJ2YLh4WM$|Q}Xp^(;xW-!2 z6NAr9=4|c+YEbpz_h!^5AK8zdp9u=sA0vZ&%_bEdDA4nu0&DqCY^egk!qnB?K z`|<3T?TNyucGTM7bL;w%0nQ`GxQrU8>@)7QM8S*eZp5!>{MDA6%5&!YW%QVMjWv_y z>_K*9Pn2tGq#I{fE9h})Ai2imC^TIfg<2`pgd~TU*ns`E{4~s8U_oXF3)1GZCee=b z&2=rvi{jk-u2lMHTJU@bXOex%D(f zaUQljHC*_5e~nJVdnMV%0T${yat(h=)jrh8KIOmAPj2bFFOsI~SIAIoKU-#f$n@tg6n}pJ+vaFV_;+)`LA($RsOnb>M4! zwBpiKYB}<~e7%{`Az-s2<^!dOq2wl^_mUgBHBb3E&YbMjvs?0`1@6hG z7tBts!L^&myc=i$|o-+kZEL1)n?SAO_7xpVtEDK#d2 zOty?Kl`^V1=YygXP0$S+E~R2pZNu4Eoh)-j87 zhCv2s4bpXQf|#cpr2O4D>CIVJyN|Jwc+4OzwkZ*7@WAnr*8l`J-Duf!`MlF1J#_QfdOCOCeG!53$ z8%hVuSuIvZ=ul&m7RL&-_^sqwbNqj2K+e3((4j{Y9qO#qqTj#aXy29dGv1t6OxNK{ zNqSm$3d7LP;b`?M9Org%Mp(yuMMux+_S8y@CjY~FPT6woJ#98(?KJ~3qsZipFyYY` z)`ggJW_eP(it{PGa;P)LTGXQ)o-G57a9U+XZ!L37o-v;C8otus|tmia~qj&XRnF!yXfdOALAScuRFV9#q z%t^=yN*ejLlmXqEQP0j(e!ni35j<->NGpLq<`NkBnS1_=BAG!x@Aa?%OjyD5 z(ruL<8R#bI2Nm{NcRG7y4rIJx%VEhIQPFAC^tSu~=&Uz2Z6L1{syZJaUb~bt5myJ?10z zPP@zWhArjR-`=vblS+!c?Qyx49hPYAF_&kU;s*BEI^8B|C414py|Jx`$-mqR0bZFN7S?|c}R)!j8B`Vdt&<_YW*GZ#IAdu@UFz!M%DwS*VAFf z3LXBQ%=gkmhxskcs58oh3*qF>gP7ZICmY8cKZN_@kwxSSoHMa~DRs9hX2S6+wQYYZ zG|&CXf>0MRX{kcfhQ6j1?Cdmn9xtEU7-bh{OskYN%f{A+1dq*9zN3ngJJd1u@kCD( z*_{KP2so@lLBqw^U7*95<2u}MqBdfV4t{&cGfrWhz`)OF9(x+Bzu9`4&|hPQ*P%?* zKc9)IE$OSepKN-Uhd39Rg+b(XG*ftudMPwLsf{?a1K$hvwr=^GrQPpDxvn-#(9r}r z{qm4FbvMi77Mv%zq(4(9%IJ2A%Klt}HGv5R2 zr#Bj~ZZeK_-7VCy+(zAE)*BMXl4D$(iK^t^UF&Dz%4D*!aSDykOogTl-_OS{3eE9X zyhdbJ4quO#O(o6JkDlqh{~VI?pUsloJW<434dFRtdXXAAFVtAaI@5jn3w=JxIM4gI zVJkPPIN->41CAEyF^k3m2D`$Jj`$J8n?-R~5?x&Wo zPYE1ZYLELp6gV4YhueevF{TppkS65Oih^Kae!uvB05)IMqdsHTl(N)aueJpT67*k>k$K5nlqmM48S-9Q^P$F zLmkO3au0m|I2suh^>93|hf=M_vwr6hxFrp?%H%3NIakO$dHlRIbmH0Dt9~wA{!kCG zUM?1X&Or|M?1lH4Q}od0a2z?iXi7&5#Bo(v%SzL}h5 zr$7vh48Yh~L0Gvt5C=8~;K4G^m37tQY(8rRS^sf_di)!zM?rZ#J@3=7`Jx4nn2&hp zTTme)4L8=NVf#tyyB9N0p3FRfI*lt2@as7_xLd!mjJf0`&7++qWt^A13Gk7?wr=7& zM}bvaI2*^>PXS8c`xXWMx?U`^_tX30Z4frFW-=r&7^%yshq#IQ`^Tx>`$~@$)0oHc zT3IWT5t*?C)%U02VAy%gJ!pYvW3r6)=h4YK4Gzg<7@u2_?wpHTNx7)KB^RH%e}cKT ztAtJRmO7_hL|Li1bZg)()+SBm6!Y5>QS|nxXpe%Yye^q`@MWL)uh2j&-WZ7E^#jp) zQ2_V&AnLjW;VEP2w@Xpz*M~KiMO$!oksc54QCDb@1(*4GP5Me*U)D;F@3J5;kF^jB zwWz1$qF-hXY{PRAW@D`)oG~NGO@82Jv_$E^XtR)4Hg1z=d9KP>;U7tf!a&l=JBC()RER?i$&kKLc6ai%3T z{QFpNHix=WmQ>uTnMR*^`f@9B(PIGpRohYX=_I*?Nx5+CmxDpnuRHqNC`%F!%EE#} zGIWPo4qT>ZnV!Ab2<|}@J@MB|6>CQ-*e)ocu1n_q0nhhk=(Tf_e4I0NeY-^9`~Wkq z4>n_KGBwM2{yw5L!}}L?S^e2poSTJ;Q|L9rbM4X3)b~Be^?yvE*}(m83}ePCa$jr6 z$+cuGtHRvKu2h0NjW$Y753@u}rT0;5v)qdz``$^7);?+s{o4~yo~TiAi5Cv!Yhk^n zMOsfSG#wTr@(*K1ypGyyW<+_KG5HU@cj9?|KSPZap7WO<$RyYBzq-P2K5=fmNfw?Q zr9L|M!{VO`&7Zdl&134s7JO7_KJQj&A~WJ-c^dUAQ_Qkw*deLqa8x|28>My)vUy`Y z(SUXP!<-ce*v96Pa}zip z=cB{%wVV%NzdLzZ1j7E+p@B~XCbgl4z+!qXonvi&JZC6&n_%c5sS0^JuVG?j)@zxTUBlQT=9xyEbb!}$7bs8K39nq+<%lbk18*>|K_F1awD z-|U5A>JokbSB05tRq(Q^@nDlDs&1xs!zbz-Pv<%4I(4BL>)&kCQOCxJ^8wWIuVKQ{ znT%Z*sE4qZ*NA70g{;57Jxfma0dp_rciQ{R+1OL>Yfxxf{j?!)5B&pq=BPMd@jtpC z|IL+6_~0xrISX9oIP1eF>6_Dzypq2ax}yyxggS$Js4F*lV-zCPspuU|cK)2J)SK}~ zqN$&lQkGsln^UNhpN;bioaK9oKQfHmS=S>xzZRz8SEU@xndB;Yh9W8G%srwTYgNt2 z@BC$jrj?U)UtA#NlBws#*Xgz}6;8jcFe_Z7J-M)rBm8hu8-?{fENFAzit(xSrP1mF zxqZP8`iv+v)U&2khcm3yMY#F(kNDK}MZ<^DSRTMREnh2VQX0yOPzCBe8HDChktjbZ z6@l60aTby5vHX$0o6_gkL|wvtsd(?hdJ`H-vkrxVdem`uBfsOHiu*muF%6~P^rK?g z^uV7z^eBwEpUU`Tg-a^^qp$yxUNr}y+UrR4DV2&bD%PFqHk1Wz^F=Y&5BWyUC$nCy znwf*9Z{4MR#vf_j$`2b?L}3PNY*RK^5&4wbyb}tg+;o3r)gl+^&beULgmnwa_vQT& zH}0wGiS*b0Mt{|v*_e^wB(=%kt*P#Z6L;yiTgrl4z4DCe%r6e>59Isk6DaS)s%zS^r!_9l*ELuiQ@m>$k2lbZN1q2hmq|4(AFh z^E%I`e|KX?**G&_)=(dF|MN)TQ3~o;rvL2KCUS!QvyEp5V2Xmejf@HHb=i1xzM*7K zA@^4}2$AHxEX%0}x-FX;YV{<&AWzODkTYf9ATOD*gZ$?EgNu`qddjn~im@h37{88{A3Ni*P|qLzbi z8pc+ouEG1pvaVmD93MwNtn<{^u0?&leO8o?Y$#i)g|X+gFX~o}g3qK>6pyyz{&)7t z$P2G}HVBDZqHy3SdC!`B|NR=vOX}+_@$p6Pa#0w^dab1%XRfz8%jGdP>B5?IdM(z1 zO%^QfPCmD%ql|Pe7N-g1DBDCMkY}^GT)zP)8i`g{D3@yZVR>)Xo)=M%a!WSW-)SOK z+WnDzXMJJ(LjQN34JM7CF5XgiIhC6)GT)E6IBUiGEXXCldEk8`iMn1Ot#YYvI3x-W zf2MFAiXJ$b^<~nge7UliuYZ%A?_ugHeq$eFj)RQ*@<;Y3`JvAw@}!-4KM!Kvwpjyd zTv#ZV$w7DQPoCF_HRkErs5Hb?VmlSef^z;yIgZpQne zDY?ZLR`h%2B*mY8%jb5!^lae%5XbuRaQbC!Z!BeA{SnEHxv6EnWzTD?o?jHkxuj&?@3ACceJ_o5f%qBkXIA6pX zzu(DJBsf@MEaf7uvkGNJM_=@`(AVCQg2lYf%^o(A@i7H5c~t-gg8X<<3Tk(xPU4Hk zlDQ&ZOyq)-L!&UIANyPHvT@*ALm646NT!hQzQSI>`1TeIcD165wT3L??{#K4bt zd!d8{UGLEUoxj)6m(&lfKrgE1QJC}(KNs?+lUp^CYajBY5%)=*54l3di#?mzw~BI- z`x$xiy^=r5&F6KPk;+*v6X<^=%(onI|?BcWPpomiuDL$S6!Df9ijVT<83F zX}3p-cL>A9U;`Zd(lKF~4VACP%I-5tG^6ir5_!XPa|V)%Y^=A%iyt|%wz1TYb2Z|` zde$Tvql3uNw6=O+a9k)>vHseu1AS-6odumSNp%IalgpD&Ni$;oxpb)NDl~POn>V@T zflFiv;>H=U?P@xE@;2t!vC_S&inX0kOy6Wc+HdkTgB6;5Q=A;#;sy)r&M$7$gHfN3 zCK{fbsQ-1Z7UTcWP+Vl4`1ob&cCEAFYX5kdQqrA1tkh?kM_t7c8F)jEX}d>^ykF>s zG7jMgwIyIjL^?|F_xkbIe)%|xdVjfLP@bZXD*2|b=Zj(E+~%EQYV2$ij)#@$ACZuO zoM;>FmZiSiL^n9L4~6w#`f*3oKO)hFF64K-cer9TA73%Rh=b2E@MI3_0rX4ltz;cu z8A`7g12(ltM`2BcX6uz0`SZgaOKWNo)X#vryVA*y+u)ZMCq4U<4zsYWw^eNmxF2U=zkQkRXqo6#>$7C-QSn!M6o*77ws$;mp| zpzw~B2V`LCW|Bh@avYb^@qVcdiJmc%Hj`deueB&S$B3v{a(2IpG2?igD5$U3VVo9@ z76a$iGq9|sLgT(XMmAMd(!W*4&VR+Tu2){CXeR6FZ^5bPVdC4&!wV3WU7gUZ-aUI`ICCyiCs2 z(GBjrK1;a1&i18eDBov?2C>qTI%rin(-lm1rJxgix?L2Sj@J{Uu&oEeABJJ|Sk5OG zb6xl;Gw{ZEsc0Si1WGkY}jxoLAp>o z?Z?0{l(|d4?6dT1_El&mP~WiTM6M&X7R!DmAep?%r_c0BpBX1@FHsM)e;B&dp+EJC zbZT=dG}Y?GN$z?jdM?-EiiX@P@52YZ$rsO|5A|0M6qv{xKB50=opf@O#n{Hrr7iV2 zE)CQor=tG12veIqnhs*;zg?av++_mjqXv-V5gA@aQE zwOG8DZ>XDM2v?z2Vi;ykrRNy$t0Vlq()oEE?#|xd{7|f4MgQ7S+@HxO zj_p9-x6|~a|0f(bzZmfM1oFtRp=n;M96sre*wbNH$Ir#qfnHzXHdHwlE7SQt+m_Ix z3Ui=alc}?2wV~#e7`ac*+Ct9ypRoo^c%1>2qYcZb+k21q!(!G0;>oeD;5uz~oO-zT z;^f&M4{V^G=FkxK)p(yIaCY&<6zVPZal^U^;i%Nf0Q0|$7d;f3_G4mX&R)U`MLo7WSzZka{ z#z}fpC0@u$Gp@}=2m(wWaQm5w0{-gl* zy1!5M+i@fLYe%<~^$%0dPD^RjY3me+PNyWWQ`iAxhrah0C(qD2rj+%&m^{AC$xff& zs#6-hsnw}xxp~RT@4ZrbE1IMXTQ;&&2iK^MWu40>pK!f$PFmMZDV@3JT!RY-<(hwj zJYX%NP2~jf$chzTY8kvfW0u5?28kuld+>`<6z2>w<`I3Ss~M#F5~J+vVvrJ!2ANql zUY3+hkl#sWxt?v7!lwoq$614bEnN4U6&O99uhqvOFZrA$WN80fjFYL%^{lh^(YWsdGvMYuR_Mq{8Sa>>tliVQFvrGbGVJ z@HusZkI;j9vI@h=zV`}d{Hjhicn)IruqyZS4_b`P zCWCmM`~5E?=G0_eL2tz0Gfc4iM2+6X^s)cjfO{?I@1!(QXP>?8Ek-!*HzIBuV+Z5h zGVZknyN&4hg={d{#oW_I>KYmGo6l*R$(ht6CZuz{zGjRVK97&R%bHg|a*geb@F^f8 z`P+zLN$ht&HsVDs6SlX{#Ev-n{%vJH=@!3UMb6O3J#uFT$~~nfBRS?Ol8IiUGBDaB z16HoP!=KYJW@b8^hGxJqkLRt&=_ngX-k#I1QeyOq4TIDJ;N2}#hS$7Hh z9_UnqLyt~mra&!6GIV#4^CQ`%XCUZ-BisvPz{2b4GXN;$)YH@Bb z(@Az!E0%{Hi{&*L#-}BV#p{#;>am>D(^D6KU-zU(fNJv}N#9;54c2n5Y^ws=1@?%n zVw3sw#pSFvbAuvz<8H_MfczC_oRpCYGORXfKFKEfQN^-(0cZQ$D)6B{b^i^;a!pq( z_vYGUtCDk46YLOJ$0m(_{t*|20{tBVP>Q);wGRQf-i|X-ul?}4RsiPtvNk-~A4BNF zFs*GM9z62H`Q7xKULHuVr9j-%2Ev^0kEw40@bHj7b&=>DZ3;lI0f9KlT8Nya*K`ek z@=u)G9PN+AFX(rXNl$7^02;7Qp{`180Xu)zhUlA7m$R?W{o&(5kEhL17*vIfVn7u7 z%!o!DbC+-Ao=N;(f=t$khA5l1?ipJgh(VXYx{Mc-ISFmq?D~+Dftn*xK zL5|AwpZ202HQQ2uu0H$2qoQ%vpI#6HqS539Yf!1tSj^lpNxcPo`S>&4_4vWsMbRhn zUbCWc^Jx@ywOBV8!#*j2rw zsc65QJ?E#XILBV^05XiPnKvC~pI#BnUOiuQn5P7g1&QDci(Tpsc9CJWZi%0ZqDO=psyh7|1R}&Fm*S3NUk|p5ND-N zwH4=Qvrco2H51nRQZAEgEXAG*bGD=ttj}wyCs#Wc8_5aO;-7E1oCzI9O{f8^4W7+` z<}GvIDArYya?p&uppon^e1B%e@AWx27iPuHpj;fB%U=E~D*|g%)3LLU?7HJ1Tka`k zYNWHgUFjl)aUPOLUDPV0=-tp*EjmvhdD~hof5m%B%OjqWq-rANH#^IP9Vp*-#mmpC3@OSU2K!1oLL+;n;H>g z?2x*KOk}7{`cu<3K1TbDgy1nuzd6vyOq-srJW-Za@Un3Lc0J&1tfL>+UZh8L$pCs0`Jst(0JNNu#5(FwkxTy3D*#o7`l0PUfBYIt zUC12HmcHUWUzN3#73}qpVZ70bzCJF<8nPty6ItQ6pcFXIrGTJ%U$X`a;=#^MX6u{DUnagw8l0<6j@-1h)1H-AlTwy%O<8wyO;T0&DxKCQ-%kGb zYo(Oc$6Y#?e7!iSZJClOz1N&i(mYH*7doq6^7sCe&b`&_Noo~XCS_#6gQPwUOtQih zD;s_qWNrvOL!Yo`)YK$ZK2wu%cZ`5%$JPHBq)8^vZyyb!Y(Ouo-DdHk&QtE1SaIGI zBdgaMU3^UPli%MxEMA(h_mU7FBWqe4 zW%lk^>Kw;OrXgO=d^5>21!r5|DzUV`n*1H-y6B}a>AjMBD|NMlRLFm$M1TYR9*k-{ zcT?dv^+F1r)CgL{=kcsKcZU)OBY7??=2>qMHMx1-a~rF|WQ`il$}lgit48=1CH)*! z*yE#yay9)eIcN2UuNggobA>1Pycg`%o#f1#LXFHH;n=7lo2b>oM%M6DpceJkYq7fv z&x0Z17+Z0K0#V*|A?*PyP*9eT1Fw0Qhji;Qhr1dk6x-6GBr@@Hw-_X;Rw zKvA**mH*4n1I*~ev)b`X^u+KnVnb#A-Jbor_C_>kKk8mbBmU)M9bOp`(#nLcM@@J& zhrR+lE7sGSs4+wKVmS4z7SN;G!ALJZYRpt&zwxC3gLp1{Rmz0%3r%oT8PW1K|NmJd zw!S0B_>|9e;T)ke`?ii5$gWE-R!s(4gPxjaGEgf%6GJ$QdX!vAd7cwZ{W39$XTVLD zGcb>AM@RPP{=P#`k+Gc5ZInSDPxkD1hEy?6owFem{rLB_DfDjO- z?imRFnhwt$8R*Hg<El;T3^!imtdDuZEcmMH_M<4AlHBW)s5ABh5l;^jJB~YK|z*fTov1vZpIK~D2 z@F29l6NGWD!FaNb`|<)ku5h1zs?($U4DRXcs7Kw)f_kIRBlR*h88=h2mTcn{dITjc z%SCbl>*D|9lBvjnY9IHbr#YxS)kmbchjd(|mJaF7r0!fFc{)!ePd)7DnOr0b=iA|k z#U8cE`rA=^%Q`&>rI!R@)rKHM_Xwh&WDr8i1fx!{9&2N%VL6bVoktmWT5Lhy2I~LS zNkgSn>g4i_b7?wRxsR!6{*BCmj-GEmxoFhp6Tb4ge7sHlrWE!IE_sM*gNsngYwnf4-`q!1%}h_?Z%nu$O)~evsa(;q*m{3&N&? zXzXrJW+qUNDE{64v>r=#MPuI&3qCSFJRF;bYmPj>F@A)R_Z%>Y*MoXifs@HJR_2)~ zD;Kj`@cleg%CO$v^5~+g%pUD3wOrfDlex_#rOJ<&Dz8iqAP?~4TA8t8lb)PzoJWKYzo{J`AjH;7kFZf`h zcD6|#zdt1Bf)C5*f#lYIsqwmsCr)~K!ZuWe^)bxPi&RKl$QeK8%SWs_>{3La-BKN# z&PSjIbIcmC^k3R&!gO*NF+z`l0VW*VmX3!nGq5@&3r!vWSGTqDvrN>O%zpVIvJP1a z&DZ5*z+w~{<#B~(iN5;wQD36}S|`%^d{<*mNzM*T=CvZ*+4Wrn&LuKN z8Ob?N+bY(=8d_5`!g*b;jHI`!qZw;hhX`Yxp_(oOYinlVd{8E4pJr`!BRv_I>n|lM zcs)d+srQgIN%A{2`FYK{tkA^#h?fn2ndK$@odaB1cj{-7Z7GRTo}bf%PF{$7L@$nV zN(`*d&+n8P=SM`KEAN?ct~$K!tiyxbI^6!EgRG^N=RIl@?=s^XuhEMl6Q;2a{W6s? zWpySJ7Spej*J;MX420ig?XnN~3-UvkV_B=eq0n#uN;9e(=h3PEHF}jS1(c*qI3jG4UWK{YC0?`)}m<(9j=k#Q8-Z( zEr$LVHyKYuOjxv%*M?l9l6B3!W7rEAnT4+N=wo_-KD2E!(PR+yDpSEvc2hB4DJ(KMbJWhd}9s&4s zG7!I?2cpb2`URg3KtJw>*Lu;XV6+~CzcOcLPW)&vHL|WnBlH$$i`>)DQcF!%p2dv~ zEJ$s~v-1be_-xBX`WnWriaFSMJQowWU#}nJErXND>6K|F8Ld3U@YYSr7b@jzZ3QA8 zaKC9oEvZHdyj`up_k{{fOb9~K(Lf}I1mj0|5bl=>LJ8(W;CrbxgnIGJF}ky#7{DAN zgp75;zZN`Wu3Y;_8g?<4p0gwkd$;mTzdV;bTP_Bl$c1`TE-IeNWxbsGf0Nv0QC3Tt zGu2zJzVnjsDQX$VTF-_mbJLBs5ZsOAimJaZV-Y=PIy2qF5d?jUwN}@AqiDvynIF{=8y>9$kNPmZCb@JdZSJ|1jTK z#<~S-4C@Y1AG&-lM%nW-x|f4~x0uK8$;I?JRs^qgm;FKX;r_yT-bf#rUFayka@?iw zYCDYGQY@=FD==xI0$U1-rP2X<5_kt9oadg2egU{$CIF3M0uVYd5NS8`_{5kR{5TpV z8RyH)(LM%Zv4qDJHqq(=4u&%u^bqg+>ZO- z=k!dtG|0kzYaX-O6AveO!CCEvnXh#i z`i=AY+yl2}>X2}renlUtiFk(f=hj2@oSO^(H%^f z$*((=COc@&MBeC3tc_s3drB4@xnGCzx(sKGXv@7hoN>!#6WKlT19P(yWmA8X+#YU{ zC$o%Fb)`|pdz)oNq!+R-t1!ET8lU!iQj(odEa!1NW?xXwHl|A9b7|yq$io^LI(fs8?u$hIrFujc~2+4pHQ;zQ3}mo4~6FH zNrh%+u|iX72JfZ+L)u>kwbj30yl|+yJCq8ZQ0i1^uSMO9*WKL}33WFJ)JyRsK;4@V z>aIxL4XF!G&boj9dFITVx6eJp(DsH9_TFDx*XLTRI6=B~(#qVnd~S;AlN}!?3+Yqc zkk{rr&&Zo7Y8V=+kC)cZb3CNnm ztfxlolZ)p%_MPXntIV3-!wmK28Mt>j9cK#Z#owB>>P8ms-*z(-k#)NbTvzX{`oB8b zfAz2*ldYw!eSx^$_QK=(q43#2AHc&|NDH%*=_`uFw8aZg&xJ6LE*UXC%!41)SR%}Y z@}1|NHJ?M+fAgOV7|#!_W0hWU)Y4E686(9r-ynYx<@Eh-(e=uHu{v!XeO8FfA_4T51!W4py7Mw z$x?6Hw63W%|B)|svb->5s0RC@sB7QI#FlF|Vt24mZjrycL=Esy3V+`pnW$5dT5g|w zdG^f{J^4B@dy^4cn2EPjnn>Tbxq>QQ7%`E0c@^s2mB}Z5agx^E3+2@_PaN1Eig(ny zC;ucbW^O2NDin%oxHmf2?$-3ejB)JG?m>UdM&!%RS;{cx ziC1IK`N7*Ev?i{sRy%W`9Ay6 z5A=5?=5(@>hqM04hBPmDM22FSn!a*gS?Dy;j9sfjkEAl*+|SA zOGHh5`1F_%JlJf+=Wkgk8`(_Gr4&jCE5OsOLQ#ode|29bzUDQN_1}u+@JI4@jmSj~ zHsYHi3stPF<;G0rBinmp(v1*w+e!|rZ#F*UHY_pX9 zJQEi1`E+|7f~@XFxOL=NuCJr4=v^pV26*Awp%7fiscLEhjG-f*F9j*{p?JX z8q-WZO)Zkx(cb8JF$7gy$TbQte&ri1j_HyyzKlw?&LMK-Z^_OHUYfn!J+h%gg=b!BI^hWVFj-&0oZhNxe z6k;t)J@dt8wFge{`uDlPyyLc6I8&#-T#YOgi}7AqoX;AXDH&fcWuo&uTiM*IM7q@X zAd4D`AwQX8bR-iuw$ziPN`+E^{+lnT=l_|)`6TlTyq{Xim8J!v?n)ohlbn}=jW}^B z3-{02$^N-TGH9|FTn2KVsWBq1SvJyEHI(RH$C4%u;wK_IZ857zObnnUKU7~ zyF*dfB^3XVjHB;4AC4nGNZ-|U6TI;H6#X1e8?j51g^x~FQmK5Aq}>~efQO-2yn^{? z@tNpa!&<&(=Zp5IC*Cy;MZZM)i44wy{%})yKe9-kTa(Y78-gKL^a1BNYqz8=S&l3e_eEEum?N|(3!@{!Mf^y3hO^rL_7I`WUx8_DJ4%)3A34d=Zfm{p4R zCF2VmM>Umyh61Tef6RugkJL#eZ_d{#Z)YpGP$1(po|w-0b542AGYzwGyEJnvFWJMT z7Ww}X>IN>1neNcQ-Bx5qrP z2WD!uzh^O{uoM0D=+D)ZK3sEM1F+j)3lq<^W1{FwNI!upsSbGQ9Do5ST2u_7w-C&D zIwnfyULcp0pvJ`{EoxJf9nSsc)VEq$PiA85mLSw1FW_97`OCg$bkW4gmn)9we>e~a z<8^pWZMQ*nGZxc}YVaRBD1HXwpzwwdq9WBa=%Vu*x0<(f%mIz2MaW z^t;rRVBY5_@w!Fcsu6Rj7n2L)UN9ru47(*!%z$&i+Gzn8Q-eBHuT=QumSAAF2=Sfj zh(?9oE(rkePM!gC^$zJBzu1>}67&8i)`}}edpOc;e@F~U2&IZiT zX>=WpV$1t&aoRIgpoZ zq=jK*8hVzYSGiZTY}YuU!cFGhOC0ixa>7%$aS|q)foFFgxgFdP&=#Lr7>*=e@svLhT&enKEFFJpbF3-!poCGg!8CF`0w zA(B7$Y%F~<;~(Q@SI!TOnGZhK9#<0l@u3zuq(}6D{ab?i2~je%jsp%}3_!Yt4$V2f zrc@?py+2aU7ujQfy#ORs)X~SIKJ$3ytlQpu?QLHO%Fyl$3IC)jc2_<2y_j!?>GCxMA zBIY|kp%36Td(;~qfG30L`ElSeHoB2lW$*s5ro6wqR-)2vEe`Za#XP>x!M3sTDV}-I z>jUvuLvB5T-W-|arhVvxx!)1jIB(3l7?1Y#*vEI%jD7p!Br?tcLmLF3lQABhAE&~q zp&9*J#>!`M%@sJl4*ZD6{o1LxTa!89wId{gHO}(k0dPGXkM&@FnKk?ElreJUnj?Om z48%6G789p)o}|y?|GzwAwGjbs3b*@)jnC#Awv1Y5c+q)|vChj7!-^vv3{?6Jwwad= z6I--2?)+S2nB-XA7_y_cL0gd5Rb9q#@%zp)#{7-JZaxca+$wh4aBRfak_V(2kB z(eNp8k=u&B0}UOY-ZY$Oa;ED!?M;I&<*&i#(W8sYcI`5ZHB>Z=I;%FiYnB^!^&VxY zwm8O6p-!%0wI)H99f*}%(e!DYrWY!aGPRdh2J}8E^C#)$^1)cS!yJjq_RJ>;N|3fA z5@g9bt<3wVlZEWj?7+U!XmXBE=%-_uA1!;X$4i$LakAs6PUgOjm90DD#mQYO8%D-S zu_f2YNWIwT;-waO=Ie{;tr`(cEiH~2)LO}9FMj7oP6)22LWiF0dGAJl9M-5W(O+~- zIr=B=Qej{cy%TOb!8<^O+e1|7yiJ8g0qiSmtwLyJB^rjPQ0JhM8LcXueyZd-Ly4tz zRk%@}ee>Ow7<@;GU$4lAuXVuj0ZKfk*UxB$5`QW<;pJCHT%;ZyTh$p8S~@eUfL@Rd zsZVWHz{d4@)*xy_Yw@*Q+!mqcUqekEZHCEdO z;o6}(hOAsxdD|jdr!v7)OS@n;m_A z0@OHFBN$H}1fg<${`oaMd46#0rD>_%QWtll=2Dh(D*H!E-{l%Sn7JVydIaa_u=yV6 zhGG18qr=NX+%I%XK)Ksw6`RsmB9k?umpV+YrRUngTG18qx}Eg6)t|NNdh|^Ft;dZ2 z_6#Ac(+r~i2G(qj^0og^x8R=YsDWOOoZ~l`bod#Yh8}OoFS57T$hxszEAoXw%!?jK z{=GJt_IUPPIMbu2AQiQ<>C4E!U+P57tPJ}Nxc9g^fc+P}(&2KB`GN=O!)QTH@l+Zn z?@Na(HNMZk=+~T|hH%bj{>RBf?oLNR$22%@Ps6@F{26D{Q2z`4d?xYl+*5q&<|1Q; zImw-Uj#59Og^cQGBYnRpW&SCZJdJ57PiCm3-i4;ps>2D;*H&geX(B6^yGVS7BN+~Rd0E+B&W75{+t$q_ z^`nCvT1>yVsm<7PWg`Q=spQ?wrgD6h1vc%c4#FB@|8dkGEG$sXKxQ$RY~n%IJZ~uQ z^C|NNjwoQ=-GUyQ7FhVYNNkv!w}o{8kNxaX^(YaS&K7{J1zzndp-;3~9x0e3#T;o{ za+0gx7D)9Z_Byh!Kh0l(o8uM8WY652?j;gGwopEVx>HWE}VVVt^I<_V1F7BokTL%Ln6o`5^eMH;xAQVBJj;*$2I#e(wXvfu5*cLLI6f zImVv!h`h@lQoRQ5_sBqv<>#)pKJ8q&(|R3eKIQ7GNEE9&oP@#2DwPGNMuk*6-a-_;Dl|Wq8iDA!k*0nhAzM%(`Gb>Af}C$I3YvUpgDx`!nCG zd^RfWqUKH==Pg;o&14WiI5I1Mf7cqbu)ALt*6hi~iqotUtY+^pb@}2j=7YV;!q5?{ z@qEfctqEE1YncuEPuW-yNp^tWHzR`ifc*TkE$hD@`&AU!^NRjR z^pJY`T!Fa`3T$yv;LG}AaqOjlV|fca8AuM88POg7G3VwKGo|fIp#$^BF1%x%jjZDX z*52-aEtJ{UO2n#F5j~2FB=V~QK3~W=9w?M+Mzcf(vR87u0y72|%e^*c*~GCq{VDSx zw(#7)!w(bZGry7Jz_^WmjN}-t5;@lT_#q{ZxmZ_Nm-_01Ij(;2x#EM4<9%_ng)dwh zaa^Q%BmJ2VZjd#&OYLzEUt@lhH>#!jpfS-;UQLd(jk7sM$FkPO8lY`;4Rv;A!@INJmpbi6j<3FbOz4@Dj4Xb3^)=z` zH4}z4rWUr4KBfHgF>=GFAJW%@ykqWn6V}F`0@&(P)Eh!e7J3j@6AjZZz-G;F*IV#v{#;F}1Ku zg4+v2NWA?08Yi6x zCCDe2M0wz%msOfrS;=$amKw3Ly&=!F&*G%lGoC3Noara4LR2jkHXLH^WMwDncS`26 zllur%K~6Z4Z%`t=q6)evDqMF~!Y^C}Tb_&4sxjMPoio(s`Mq!1FJ^9mCKH_SIN1SD z8!;m-!x2wsC~`xibnotM!s+1$ga6%1}XD~u+)wtyqgb~w%>46Z07l~@rZmUM0 zA3?A#t%mv`{rea2%so|&Yk|QS$$ekWRlar*eZLjdV5lPvWERBEjX^l_fxV2|f?>fw zn=S>QOa-!zyL1?FMEAce)Wx^ik12X&zGoeb`@nk#$sWGdWBUX4GrH^XfV^W*p5^*) zB9GW5f#ZP;<2*e!rTt%SbVdF>Fi8*3JIs`(hB4TYxg)-M3~xs!B%l2>7j!W3wTc?* z@tu3lX&u;8W5wEE1wA_W=*Uaa4{}91dag~wo!x1ubcNX!_fp~1hTdiVX-IWv4a|`_ zd-dt((KHR~zS7UTCD}xN_AO6;kABqRCZyvj_kp+g=YiMwedHQlgVRxY75iKUr{VBy zdfKc?!>$GSAI&(RoaFo-VRZ^>llh}s3NL;j|R9+WEoR!57nO(Gz!97@n7B#`IPCCVi%-b?-1-%i~;0{;VLenrK1T=NH$*9&hYIhU0(x{|Y8P&&vKt&`}s zI?17<+($BZrw)5<{{AeIo=43xYzx=iA|Jfuy0t9A2S=CCOQbQqy*v1z#7o0GkTCib zg|YWK9F@0)A<>3^PDw$RE-BdXivC}d$TnUv;oD#CfqG`66Me0cs%5h#POgy*#+VCP zP&QY|f>>J#AKX;l%;z3{p|c#=Uu34NmF&p!?54J}Q z;~tTF&e`n4A!~WZA{;Z{gyC0w7)}mg26j_=cjvJ0CDnvAb5n4%Y6@J7Q_ykqCHggS zzvsu^5YF-Oo@5!h-?D9zgYDcuZMf$s-5gcY--YLeCM{*>nD#PlxKh4}0`cR$CUMW%&5PG+F?(5p==VDy8*}f_$Ab({zVynS1bLIXAldJa8+mS&*z z37$WPr(@bnh5O}^%ta#el~dlr{pl5j`}-g4d;XLlVG5lLy-z>k`bo0vG_xdp^inCs z8Na7FVbBux&X?u-aguChP0szd$S-yZ#;w_$yZNEpz;pf$@|D%~IK_ItOREGZ4LmQe zV%En$9rj;kKk$Qe*xXJ>JDyQp9`QU%?s|0>dg&D@+|S)7XK-ENo=KiC!Gb1_e4)w@N^#NeNI)Pk^JHo@*8R6RFECtdN0fDV!g@)A3?`IzCTKgAX<09b`V! ztQ78d3i-a4lP}0oxDVXJEX<#=GOtp+TnT00z|16Ba+jXTGgatc%(XRLg?g!E{$rIW z|5b&O}>?iDD;ui5;P5?@^)@ zly^oYTNTbUR$}60zNcGUleJ15pAd|D^VHNu_}six z&prW`>3ZzGmWS9B7|`{V}|E4awHOA~!gJ_pG79J$#YEJ&F0(ZONoQ?R7-r zwv<%A9t?n zbD7`SPmRHkwYWw7q`F!MH?GwS1NHQ4*CTWquZveYwml>hl19(AxBv0~>A0;{xI3I9 z-^u%Rl8lqJo*Mrc@{A{2$dQ+=C3L@1dN40IrJ{=*>Zg>?RV^^KKRs(3F`Ks(dnQ|( zBj>{*uYAy%K7Yf%__Cfej6JepD0MUp z;CaG5P=n-T4c2#HegoI9DO<@elG$_pn1UA@O{imU;=GiDqvP3^SLG|7a4xzslRbSr zD{p+*TsAO&F4l|~8CeCB+oI1#x zSQ9FQv;T2P3aSUD;P}22%;#GF`*t=ypUFlB*9|o})YCO{(2#5X{cKdt3D`$|HqDWy?+m2|z?UQS#wO9e8XEf$u@Al|EW?<^4h+5&}B zyz#a-`zMgaXAMk%j6)QJ#E%pFD!X>IqjDuan+Ng|M>(t7=A>i|8hp% z&CV#P;tZSPO1$Gapq?Ey=Nt54UBmwNd^K8d9_kyU#sdpAI9qIcwNsp$} z*;Bq>k8S1Xr_hYvu-xxXo0J9z?pJfmrs32)j`jWIse95Fk$;{#m}}WH)+6$hWY7b> zod2Ykt_^hJK1MIQSL@~H5i)PQclK1XLQ&J^w3aDfiJMa6L11PSb-hHv^}qaDMK}{r5Ne*S=S{-`6SJ zM{!>4M<3rJ^4=#D3U~Kci86xOUy-TwD^SOa#rg#KOaJ}-tTFc9!!;saiRG3~X#bJt zw5Rm7@1e%>ne-6psK(w<&WmBxvX#NGE|q}6TrG{pp_0ujM~-n1*RdH-S=S#(zOtN!d&>(6BJ7`ArPRqddNUeA^wMTT zoXp9l-k;zEFO@U$HO^djTu`r$3xbCS;rkag5U0kc5o#!JlGVG<9*XgLyd$gEyx_b=RUw4TbEXAcYa zs;85rRdcOWs}nEt=}~>IjZUm9>t%Y0GdTsGMd{DDyNn94AC*M7ozdl#8s2<{;u(SwdZdB-waUCr7*JWJWTxvbgV{~Tg+SlzNhU~gK_i^Q-B6~1p$C=&&BE#=ebd|6%36W7jjKWZ={g&f@aL-i#4eWC1SpVEaU)P%`5jlG+R z4VP+)wj#Ne8XlNAf_&c;BeTpiac@my$sbTC*-Jd((J2&1uNv_xIunOnEk!vdR}SA| z&T=%lAy(y|xM!iJG?KgYgKO8vgE|+pgT5uhZasO)j3%=C89Amue4Q5|ykABPe9C!# zNdt*^kt?mAc;N20K}~x8C@dCH=VPRSPycYov3r>k-y{pU7VeXY0WLA0(}pSA3Xk-A(KMBZ1lTK zoV08t8C&yYGT5_ypZwz!a&4W+CziI6iTXkr?&gVU)E8SGVt(;K`dwNz5l2P7Os~b9 zo6gMV-J6WM{?ys()fZFc5*g9c3jsqk+}|@__)jJtr#6j18rrhp-`T8 z_aK)=|Il&CxIUSDZWk-DD9M+RuHG;n2}Mv|GTy~x!mfWqu~rnx)5-LyzC_=^AaarE znONm$Ew0S@U2&GV&*~7YxNJm)Qkh5|*+ed8=gN`*4{V(miu)->G~spla;lN^|6rE7 z-8|9#dFup@iUha{uL z&P@EXuP;3+;Vfi)ImCR}S+ip{KC z2|LC8nsX@1@_E}eB$GUHBgy`oFZ=G%W5bu+Ss-~>Kl=LR@_xN2k#09VaBxp3vgjQV z_LVvHVa+9^VS(hY@PJ3bE<|mhk45cl3?T2h;X<*b9cJElNeJS}jdnSdiTH3U89b*% zoU3{uO&?0n1S8t!0zouFRre;j_7(^!}nB>kRha z2WKME&`dmn@}(F3D{V745Bx}mMQQFsG8@XG^2HLN^+dK;D00YO2OZ9WYr4IxI-V=` z!#uHiJh^WVa+ejUi%ei%a~TCTPT@G^yyR9V8BLe-JU*$hI1SGuvqWAvJ_L`xFhBZ4 z7XE3P$+yP^^2M9^-8|nw#!pX^jnL(=ehh)70Y=WMjIvz7~DmP4T) z^y&>o2PgU%_F%p_`O~^S`4YIo8(*n2S!t6oE}uTCYAbmeSSX8Fv*`7S`RrSa$mH`p z?s+{)(fyN!-}!u&p&#hXWGME0!Ag3{p9wCMti|+43841y!-&edObqa{lWlwRBzpsW zZ(Yb~-b}{N1H6y@>dP;3h?~g6hE3OC0JZ?vx61r4ppJw`X^2_qs6l*3CMFm|3)kE*-nR{i^&<8OYrk-luXk&;K7Oj zY_Qa#l0z!0EH}(l;9|M`6%h#WH%8Vdu z`YMtuOy2L0aii(+q)KJp0&}A6<7Ij)`tkJ)!uk>|-px$K{4r)YHjNUWUG}(KKy5!< zi?Qv~U@Xf_ijOg}`LPqGl8gLUiTkN_WFqJn`EFpW)STb|=g~p1tE)r$B63eZ_+0&n zl7TC^udWb?!VE3S@cuqIT!J1KBjxTh2ka}MALVd*QTabcIRAYMpNA|D2i$rbh)7!< z&Ke)1RSkNrCr62nyvyb2K>Qq}#gEy%UwZmT?ur%rN%V6J2*iOR9sH`$H{b*_PgX}u z*G`V`?a98V8(MVxLl3Gi#mG8HUTn4sZM*|aql;BZrtfF9v1)zk>rP_wa5g^3!>h>Owk`?>@2pRdFfe;qVC=$$a!jH2>!QYFy=7JUEtb+mZH zdEkl*`M8k7Vi#)JH>!{2u+^Rkm1pzFL6dpJK7zb1dj zUZ&7Su@X_ykzP#xs1mBhyc%ir<|{!A$DK`m2V7MJB4kTEbEF@`VF35%^`j+h1G!f| z52d#-U+dpvga**>uTzwiucgGM#Q`vr1zNTu74P&VaC{XbQ${KO$7P!u@V@isMn5P) zogL8o-_Cu?RI zhsgaMO+`{Ka(v6_2fES$Hx7^+C4c>VdMd7R{&~Q8?;<(hDdz$Z#P{>mgY!=p&Y$t| zGN!Zx5~$mLir_pf zBar)S+x&i}*A7;-;G&a`vDLe~8{alCAP`54WroAGmLgezw)tqVeRDfyTNGER6>(?A)+) zzH#BpOoP?>{e~y+UKv_#3pdQ@P~CX?RiR=0y_s%%FPt^3?z7v_u=ILElrq(@P+8YF z?ZQh#$4(F3%4!E0X1||kaCukXP+`8mnQY zv429{e?g-Bnwmi7F<#!LM9b);SSccZx@1v;G;fk1DZjNMvtlG=Mx0z$#7a`*M0rCl zIVgwU&ph~=PKi>jX@b16O%U~)7%6zhKGT%{(qnp_4zsJU*RwKvb=iO6 z(~G&)S~87%{hf=c`(M|iALnZ;TlTBY)-&&oo;>^+n_qH`c&o$pEqV;N&Uv*v{T33q z2JfW?|D8TKJ((+?%g@{=gvX`9ZE_k~PG>D+Ed3KVrD0KddN59=H$x_QMru~0BIu1U zJPmKigNMwZSL1SKdf3y$$A*2LbE)TVN=MzCH0DM9U%#h)Rr)mArsE%9|4K16LH_$6 zMLG_TCP%rEYi33Z=~B~48t%50$e&8-v)Wz;oN$maOPk2Ee$>|=+RMDx?D^8#O2S%8 z@xIzfuI+6uWo;cr$IR)juC~(6h2HB`o#fs@N4Zq2lBoU;GJ0q;i96F&A`dtV@>@$8 z>eG8WIg2lO$dPVNvgehvj7d<5-pW=At~Qgtds~p(c9e}gGcI1nyq;kS3<)wz9o81t z@_fIoQGqmBqQJKS3hbaq-11!|5uiMB*`jyDIOtX}pW0s&23vyD-!e#Ar<2>rUBQ4O7{c&ZU7RdP*W|mX7s?W4aHlH?v+#pB}|u)=m2Q!CcV? z2U#mr<$%LGp zCe(~FVb_Kf+*nFJt2S%o7pb3rW;e?RX70A3S3o8DC@eAIc@}%y_R$yePBPk`Nyfxg zWFWvy>r%;3dt{^Wa@K3C$r(0d?WO@4#Ch3xUybZyy=)A9nF*gYS@_0U@}Nfah)d4G zQtK?NTa%4jN2tS*2bhw^oRf<@+r?$U!bDHGB6>TnV>Uw!`yZcVBj;2$PTbAHwSTNL z3}@|y`bb?zY9z18QLZFkFpK@A#%zQcvv6s#i`dt1Ek*2WY&P6l23fm`S0872vByRt z;3Vb#Im)AZ&eH9wjcCpG66bC$x9hX#?X{hBo~DwFL@Q~$(?PC(v69h~9OUqUrji%S z9$|jI;AJCKzS@d&I|m7@$Sn8)PU7cjBQsY!%CZb+nYpWlOcq;dJJ6BY@2zFzNC!zx zRv@_#^Eemqxvy%LGh`X&tT&7E3>oh ziFCSemZFO6>n=m@5VFIjv+Uiar(=ZxdYm>e%c{c)xb?O`Qd^E)`kz+p%*=`udOL2j zK-i9A2~m`YKiT5QJ4LeM6mzVt=nHkq8^f%8Fw4~!`#zErZsdn3GQAZez1W{k7V#&2 zO8+sp!=D)uXS{G_o;RX4F*7vQ8+qk@v6k5&J2`Iht-N3{+!w~TJ}7uke~j;Bj|ckx zFIRK}d5A~Z^g8Y3iytR^(6WXvChCUavz9;Wi#Mv!AM3#sdPG|D`S)htM}7z@kX0BO zsv*;_LA%l#to}`J#qF&5Xqa0vUxQk#A!c(-)h2V2u#sB9P3A2WG0)v93@QA(iFzK~ z`SkMKxd{h8 zA!Dx7*RcsXWpc~CZZrS=F?~rFFmrkfGlkO0BfjNxzbFf;<5}=nn?)}I=CzTrS-}4{ z!7m%n&Ez+xQ5Pk*v7>1=mUST8vN01a$}y8=5c@T^F+@?hX0?hJ+xvrW=S>z9I_EzgMF_NdoH>KKQQEazPh;b*J!u&2a62- z@~65P!@Ugk^)Cz+R{Xq})ndLOD(8#A9R9)3;$X3%chx0^)qYit+dZlqFYk0PJgeBi z*x^APV~ti#jJk504Rt?FbF01bm7(*QRfecKC)`dQdvh`WO9f-VHEq|pj8|P;u9q@y zG$tBeUYvDdfw!O0GcVg<@Y8ka+1Ak*zbIZ>M$@ZgrCzk^IJxstCl~W{(zhg5u6~FY zTeo=md_Pf2*P>oBE?SdK`VkbP}>Q zUd*nsGWBqRe2&zK<*zsisH~OgmU@oO1gXHE`Q~YytS^-)EvD-v%!e$>GQCv0?S!&% zDzvZfgcUB_1Flj+^TP@AdpKeLK%Vn!IHS`p_AUKX!Pngp)BZSO;ZG+Vw@~6f`(k#R z=&N{?eS_p1Z8qOB`kI;p*X3+9R)qR+9;Xp&J4*9N^GSMN>6ex zA!H#RQeWD(hCNW%RG7?ur%m?*fU)dJc^Zh#P1X3jMvWiq$R9?NXB-s>yW}90@Lb<` zK@fKP1mPijrvm7wcz=HoPB#z6kQIRl@K)ocAA4l|>E*beIn!xsEPTQ}AZtl}w}arl zf&0)(^nsi}-$w2OYw`P=omQi9I{$ot*#u6(%*j@x?jL3XG}ggap~Jw%%uKth!=GJx zROzULu{1ptgV?Wfn_gaddYt6GuM+ohvE>rrKatr9(-Uy=IXzppvECX=*3n)Ei>f-r zvj+P651E|>^t$rau~$})rmKlSzEcz7^^chMC;+@q8Iv#2(OI-0Sgc{zTE&`yTsV0@D$5mA%eY z((!F~8Wf|_@nb?dOh1{!>7R!7Bj|&sWR_~Jboz#+;Ylm9D4}V%>(30@dg=5EOvi({ zjh6&AA}fu@N1|KcH9YrihB}W%`oW3YH%j>zpP;TYiuR2 zN6p;*LJFe(k^O2!|D;Rg4ZO0ELjEIjRSwRK%ptRujls^$yWi>{C!?L^`JDE$RI3u# zAUo;W(LpL*x4@KO3v`##_;K1S^~lGa%~D{%K5smpGz`TNzKD1^98vxJ;Jt4c0=I`D zU|<-ImJ7$`N?};ga5vuf48yuMmr#xK;;&}RS=^a|XJ!*FOiRHiYWMqv9!{Lc>N)4& z=BjKIS~3fg-pb)FEu>jRl{9x&iR`nHJZn3#9;d)zUklEq7WgvO0^b%{;PoyA#!vHu ze+@rm@)}*A;0yH_W_J4d!l_g^a{n@KnrlTG*ADL*^!Du)hO_hN`=w36&}SwL;oSZC zp9%Zla&N`?HIY8l)i@{5xX4^(UYk_1Gp&y(#X`kwaA_rF|F)4gpY3JvB<{nPmcqUz z7U)M`soL8V2s>U1o1_#ra4o#&<%eUVe9_0&7c06C$Ekv0=w}^<6I|=AZwW<%8Qc$k z=YF$WINoeZW-lvw!7I$`Oy-)B$^D)?*O(F67!kug()VnPw_r{tuh0A+S-9QPNpM*u z?t|OQ+}`bE-evluopzA3mAO|>D}|4z6*zi}jEcVn+P5f$JA?hOq^B>+9`wUqCm)RE z^(vlCzevk4m@kFFMXkZ#KI{WHz~`x37GD21*d`$Jxz@%U3uQkC3|5RjGljk@TzM9WT+l_ zdlInHI{|Sv^loaYNA(&R2pW@)vpfryzMX+%7XT zd9d%zD;6HKG$R)E62)m~mJdKLuERJhL^qLm?fogA#4 zBr|Iz%Fs4?>Cr7o%QtD` z_0NIVMY%VKp55d=gM)FmZ!mol^tdr50hxDnSf8Xv3kP~MX7l}Vy|K&XeM(BlhkhB@ zc_$tE3uzd!i5^nyGk;pm!abfG$TlZ>OZhQxb$Ohuphxu8GDifhnfKbCxg|a5dGXc} zvCd>+-BqZ>eZ-<5B?jg(+k-q)qvd3qCQ%cbNrvYdwVnVqnm*R!3ZI_?)M7sEO<=vB zpUWqp_v3Vwznz9hYtk`@Y)abT40=^iQ(2*KFVj)sZoaB;k6o{D|FlivK6{wL{p(#j zxsujZ-u8DEOO;C2am=@#Ku@c-oNv07!lii%IEAx^vYP_GI0rT1oU?4PFRX8KPFDF~ zZ?P{tcs|&9m2(X_v}2KB*q+S(qzv-!l{oe}7lv=(xpjOB{@qN$LhixWk!{?Nor4bj za}de7aLI%m?CQnL`}Oo^yxU4NQEkL}gi1DDXeDib*hq`|c2eyIdoP)z>`Xo4)Xx$b zQjgwxBP>vZeu%B#`yr6$o9NA)dmd0ELJjf3x7Y$=35YIlV zG(N!`V=^+*=yC;gc-i&J{&tPxB zK=v^`au$F8mQvg|g;9q6g+7=})3sg3+#X5SMHX3f;##9s}yM(PhuE}_M*WcKdx++#=1 zvY6gw`Rv28&!+ziy>mO{U{P@vy3C~K@kRdZmP#3yZ6l2zI!f^`2YHlaBj(lY>C3TT zCb$CmwTnc(nEt*s6gcbVgHWRrWf>uFg)(AL6V-?*OS8V zaUOdXmR>^7N7ON{reFcjT#4QId2I?>x@O}5ed(+4I?bHI_mz>2{*h$iM>|Qx!dCKR zZd*zF=pw%~%yDhhMn2Uf`!HSs*TWXbyjdu2nqrxnTP)2EdLtmt8;g(m;C*XfBsBlRsLQp;7Tk+_gr?J6~DgwyYDwI2K0(O)k*fi)%eopVpVs~`b64jJsBNQdRn z4Cv}`FWWF3b-0ENrib0!LS{M}6z*L%D%_P_I9F%TUvG7ySY1z&{A-Ca*)u`X$0SPH z?gVMp*cma0S|IWwna1kQm`4`=`zU7|ObtdZd+5D}uwTAYFb?L>cZO@)+DFXpxv9s5 zBg`!JOu$o(4lO+rQ12Q2b9d3xwSCY_6kva@1zdg|k^3e?;E9 z4zJCN6-i>Tk7v0KiPG;;yiA_27njE>tW>u^`*!rLOyhcSPzB32&bW7ny#ZaxQ(h)B zIGgjdhG(2n!T2{n0VmY-tIXG<^;`OX>|>2^a00Y9GvMh*u5ubVJu9wZTj|5TJRSQ> zS-78>q;S7S*7Kr~^P!8v{U&<_-X7x`Iv_!2oJo|o)sM>7)=6@uRFdr0w7^jAH`=ie zt$R&pOg`<5X;YnX!G?@^C_V9~1Y!L2Ahi3c#?IcWaQQp6@Qw5X`9zI;z8?P`>dom?^;cl^xd5H98JjA`n{4ommRo2X#c4c4R-=h-D zT8M^BV`Q%+DGJd_k9lNYuQ;QLyEERg#&FlN1zZ<6qr#tHRH>lGi=}F$R$PV8Jo~8^ zsgdWZ$C_N8t?KEK@k57f7d^^dps$CLEG7Mp!wu=k_?U{e)Ydb$^Xx=+FoxH|F_r8= zw8H&5uTf+adlx#=S1C^`%O)ps-x??919bAxK`#-%oZvfLg+{HE%!i~mbX6t1YCGcj z3HD8_{XeEreMgP4$9R@aq7QR4+0M`OE%8af%&$5OAD4hrWKmOZvVPc(e$YIRb-tDc zk80`kGRQ!bkiqA=KA(FHyRE!m?By8E=lZ`|*nb~ZeJrI~26><7-nd{Ff+_3+3v8c> z=}jzUO!Yz;7~z3z74@p>Hs*Ad9w4%EE-|jm7;o{mZPqFnn7G*+k|M7iYrbc~dDfDvv#veQP2NzmEE#zgndn%9+?+?gwA(Zk-5o>m^OX?|YGz@1t0uDC?w_RV zJyGgW2nO8?D)!LND3&htSUBj)_em{&OaXb-v5h6QMxiug-t?Ctp;*PU__JG? z`2CxCvSa^9nf0FNbutv{b4Ik{>tq`(<#6`@L)uyYMU{tdf52Wl0L37b2C)wV^WSEZxC!&XA?6pPCsa#h9%bmejD*)b?Y zmGfB4-EL?jy~tx0lYbl^z-L>p|K+xQ$?@}?`HxD1enoE~@MdJL>8-vOtaJCkm z-RAV@Ju{P}Li+5;b>1PDTH?ffbCW#SG`5gnb%m@O;fqeTkvQOzifugaR=nQBc9zR( ze$FRci@~5j>a;D_Ws|ZZt=W0;(YMd(Lj$TAGTK zk$IeZ<8`#AMC!NohN20*t0!2?-AF!^xyCE67l~;dZ=B%qpZ#2q^DB7XueB06S1h;O zeDIHD1a=hYQC6EC$!E>PwN|kh{_@7BIgv=|!TyXB`yFkY${Ky4n0*|9O!AC_caUR^ zVz$*AE2;cY$UTz}verbxlN@eoQZCNFZ!Vn!nLoaQIq4h8L6e(KBd44iZYM<-d4Avc z;7J>vmqI-nT+c(}pcYbiw@6(69)b2FcwH}GoqJaqo>&`8%@qSCkGc_ILnqIqf~m1 zz~e^|aI++rx*!)XXW2-8e5tfg^+nAc5ilqBU7+H5zu#Pj4JnnYj_gs;dmEdrN7ORr zYj<&!4UVPqrjs9P42gglKhKww^HBR{3+YIHS=rqew%m`-8kmZjW}N$P$a39`MqOIudl*(0>${VjJMuhXyW+de1}r)YXe^Z5SHrK0a5e*IxfF+W{M)|9=? zsq}9)O@)fTZ{y`w@*<>A0>As>6VFSFEczl(=c4#@3u!Z;SZca4PwQqR0(|v&T$#%( zf)-?ROJyB7_sPp6u_9NG^e0QtE8IIKbRow+(=_n0uuxu?Q_8yRS|tP)>tACsRQ9Pv*lC4%a3uc2Yi?-lyI z=F<~rN-yE}5JaCO2ULarwZqI6J(MUn%Iu(66M_qaROqycxycokQ2EnGO|DQ@grX0* zr{1H|$x<3IJt$F%=ueE@77XKa@=CQcFk_q%u7Ss7<7r1sn;nb=?BV-Za$fFLC1*U2 zai+l@ny;bg#M$KT!m9w!S=*yEiK`Ox=C|C80&eiglhOJl@muRSyD$Vp97<4XNZM0cc@ZD+jP z{KElf-h|K-slpiYM~**?81ng;RM|p)?Rp4vy_2wF0{2rkWSb7zI%*?SebhG)RDGmk^N1X0t=8Ff7r&wW+& z#xvJ@hY^?dF^~JcJyOqwz;!7508i85TS;GJK#Z)+vZwzi4A$fvt=DFtdqE|}9pmS! zwF4}xv-h!Ag@h@Y*m0r~Pv$2`8FRYbSBGNV8x<@|>IOQZj;4zHu4qrn(^R)zMB zS;HGap0P)qTzKV(r1A8nJ|QnQAph@Q2|IfVO8uSU)ij`Mx zPB>p94FB9vXwZ?8vjjaF(ffFh95CLuWrB4{OI~y;bp&+m`;p2mJihRbh7x_HFta(eQelyn5n* z`wf_99gu{un9$d-P0YuKKx9 zY&B6KQOmse6rRVTcv;KqD5rA>^4yt=^N80)ZzGP^j+Zv;c;841Mb)m%gXxfo@82si zm7HvgP03% zOOBGSzrp*!$T4x!q`m`|MTB8%eSS_>&>KfSbPb&^KRP&}l>GP}UUyr!Wgs)qh}dUb zkFGgjB;BNm z%P%i_v%z!I?vJ`>W~Ta?lmFDG{Ozf0y8o%JaakR`*I$3@77cOGcRL%S8$a=E&lz7$ z^p8z0>7FhcsXuIALuc4M-g9XCs+Svf+n_tUYNKb9^Hw@z$1r_O(~h1dmpgfsulrL! zc6?*qf!qJ;F4qXZw6oLs%NOX)Ng>aedrT!Q7bS`LnB$UjH&M=9P>Cn`#-|$+<=jGz z^#4Lnsds`5nVuvIKXcZwaguDEA1^yEBuT8FS~g5%zncAmPl`mT@;83X(MmJ*3Wgc^!>|D_xk`BlkuK4xX2{s8%XwZb26wxkt z|J)f(In#ONRw#5)p;+3Dvy!Y&`)p;sYHKKJ^I6}9vk~Wik#}W(dd5U0x}0I%dVd&x zc#^q($+~(iGP_rlu=~gyB-TxC_f+CavoPdU56Ag6^!3c;-#M$qJ!d6$&*63cXE^h0 z!%*SQ&+ayQcnqwOC9x*X+SG1aCGtF#SjWB5yV@GG`=Eg(dnvVT=&s0MFWQRUoG0Y( zn`p3{z2@aV$s7-7_R}>D8n6a&H%N+$F*HeyPu1w-xvR!e{+)@Z==7PX z#{2eGF`96nn)EE*3+P(fcK2^YW#VEnSNvyhq4yd zK81PEoYyFt%X-G)EL`8mJ=xG~__fbOI&1Vhsxc#jeP^>Tnds1sb)hGjSjw7E%y>F? zqOxFb#x;ZWtK(joSkQy>x&O^BD>Lz%b(;G}nGLm{f4@8X)04<>U&zF8YwmTdvM}Lg z79Nbu1UhCizs+8(`?r+@ahBL{H<@kYCVQ$nN$+NMGP8=al$zPd1kODEeZgKnY-lCj zXWB_M9~W^Cw33^@?8JV!gPgnNESriPl)^hT!y}W+h zMgr-q@n&t>pR?_+EZJ-IvynBm-NfCtwQPLMezduR*mSIv+EdEJzqe5itmm9!8+sK} zDp>oklp|M+@<)H8Onaq3@C>8$t5Yt=nk%3@Mo<69GFjNUTt2K)V12hTnK-smt~r~a zPhE0X4(yXosg$oV%)`A_A^yKB<&Vt@9R5aMjyHXEEltR?Gpl-jr9^kDklqoMa^;Z% zveE?ct9wnVo<`j*JR&+12 z$Lr7f(U7rG_{LiG@HNc1UBo(86#a59BVn~M8q==RyV#kIxj<%5vlr4bggxr_l;&XF&w^^WT^8Ym3%LqtW1K)EYp~KnDY&M;UNql>tij zlxuAjmT!8riYW@+%FiJPc_1*?^>Z23Q&la34p% zPAOT)v{YmsGoafKIssx+(fvE?9_gu=-H*@BW@)%PleyDB^%y~}OXru0kF4iu>!hLJ zUjy!%{?}LMGvZz{h#}+*?Ab4F#Qw+@G6=VriNL!1fVK1+^vuWR^LfZC&d0tf1-Q$) z)4J~Y@Z@Wsr7=7A95bFe<-u!k9_CsXVAYF!W}4-pK$!>YbM(r^=Am5^_N4dZNX0B_rGvD1MqgtIT}aHJ+^-|s z!8%=mC9j*}3b{XxdG0&PW!7Z{{VPU!Raq{3(-rU`2Rwdqh0KkslwBW`MsFz$eVIWy~>^!b2Xc>-{hNJDSh8pNZUmU zY>72Wyd&MK%$s)2QQ%2u_7L~_BJ!gjEK->fwurgy2LjN`o}YVizjetOzVP;k(aayk zCH|=M!51s`^Sau@8sJNRbgCM_enbEokvYEgmp?A{VK#hi=CZw`i;MMvBW3=q53sM4 zO!sMje|+UL`svH`VD0zEb9ZKd75d`PUqJ{<wPPjo7 zdW_*U$$nApE4sgU-94#FXX>OVWb(C-0-~^z|KIXm6e6y2W;~Jp(@o@#hesnq8I7I% zJIiX)?{tIL*hkKnvbNSL+kmr5vcJyE_~iApwiB6+5xjOP=w2B^H`Q5wt(O7cs;A-X z83W2E8-THCm_Cy}l-107<8`JV!fUk=ugz2B78|D`_*p6@pG<` zk*fh-ymng@@%67$(QCAUGYssh{m4h%SNV7_K94Lj{UsmxxhInty_P;xW};b>&zRSo znP_eDq4~@l>YJ<|Ud=-lUW57vtflk+nN8&EI{!{A@;P_PY_}ltLB0hT8kC2P3-YjP zTRxgrqsQ?}9$t^+b#ycz)_Q&|f!E+Z{=9$qx~t5cc3-SxJc<7Lwk*#%+iPF8od3c@ zce=LjVZ=S1`?_%b%IZ2@%iT8mULN&58(iwCAJF`&?$E3+x>kOhbTw6tJ%)c;r}J=` z?%|WYMVJ3-y@&U}Q@Vf+or%Gm*sl=zNTFgdsrm(6;wsL=1 zSeHKT?P|^tsn~Cemn+U1u_#cBJ?jtqdyq#os^oXJO2*w#$s%wzW_q&h&EnrrPLgcX zBq`s-IZbt%jN|vUaz(qw&RG4>1u@(QHmO5r1=$IZcZqxF zjDxpb5WziSQ13A8cUPiLeeUzDnJYPo`?tDbuwY-)ezX$N+_x?76ppNY;bd{>C26L_ zm~r%4^-yB*3py4jDly1`E{>*3)E*Ry7sA<>+05o(eW1sm{643YSoWt9uGwLTJ;HqI zc62pb)5GW(0$(-vl?}t;)HNKRxyL-di_e66)wq+O#)NRrp^)8}^o@**AH65nG}ymc zO-C&KFzk)l|59VmKn?Qz>Cv*_Ow0fc6!q!t{+BbZ%jxarY@^3vdb)j?ZPr;0ud`}Y zyQ#+MwQ4kZ&Hn5;HS71x(L2l8nNU7wr7_$34(llFw^hmEeA!ZF4Ll`3xtzImAhCHcwekb0?dq&%*auX3Lq;#p03$PwwL;Mlh$9Tw`n;=Tx{qywNZl zPf{{a@R~D{37K%__f)gj>Qj^19Mzdy(3ZXw`z$Q+qTgz7CN5v+JdBR}OFOzDyU_pW zPcE`L_mk8AAJ5o+qrIe`bd>qmT&4YUH+j*qv&{WsD?XtLZ2VOwBk5%zFW7+h zvyp?-&>_lzSn_DAcJbOT&cm+^GS3xcpXp5Uos|#gGAH)Mm@#ecDE^z;OK+o{EcoCi zH_n-08Xa4+>d?7eZUV(}u0>=+{)rC2mvleoBKTnf_gD35=362D7s5>FQH+I|I+o0;OoBf7vQn6M5;hGs(mu3HCU$}M`X zS_NX*s6b439Ec&V(O7wlp1-NlSkRq(%7bY9nol2?!hp*8Y52U>z~_!M#H_f&%ohVD zk^^6y!h3I4KCX}pDR!rWT0`bw5FLn<++{{}XNllmd(=-CX?vZl$}Cefse$?2hky-_s1`9W_L~s!s!ixaOoJ0rQ^xV*wPsZI;F^;wy4ehpD&ry zyQ%ow$o<|s0|M5j0i|T%6Z0@?Q2}~~=VKy|OX+jYe9S4p$K9^d+p)8l)b1kJZRub;@@QfBqGEiwoETJYayPAM>v(^YL$Ot~sp=;IN3F8}9L{ z#TKBSlcU@yv6r=KcX6uWC@YxV`S5dVxmvYC?#?j5ja~}eBX`;$M!|kBIi5#>_~T9> z_xyo4d(|Jq?*&5DIRMTEI-89=R~mkvdG0K@ANZLPg(&h(>p34V>Jn#sxPGQd8oX+y zA!!$ToCi5qqsm8ouL9QF=^P%Gk2$^?*)=UuwiapRSB+%m25P1EC$)_F(+L)3yhpEf zhQnTGT%PI%Gh1i;T*`dl6U>~BQKH7PaGbFT$3ay%Iw$iPGlp|>e`>KImu%W&Ey9yE zaHbDvAMXnX)Y<5MGYb=W?RPm%PtjcZnp!hggu`8{3ghfD-HdIN5RcV(HYOY& zj+4)8#reQlTKW+=4|tFF$ZRr&ZhXEymdW`Kx@ccyqV!27T*!pnT+3PejpXylUu+nu z@Y-5TXAT=6BC zp1*}kbi1L%0@e#k28HALrZD_GMFym;77e4-7(GqP=W{JO{$!mylsS~E=x;hfSENlg zG6wT`+%p^7SqrP0tngBhPg&lV$Evo8S7Z9EUYn)JqRU#j@1>Q9M_LK{%J+6%E9$YX zTx00ZoX2yO#dYx}^Dw5l;8Z>G^UvrYd(D0U*Qkqt+U%57pxGGYuw~ zk!k0e;Lr2ZfK27EZCQBOp6uz$EEH~JF6C&2S4u4tuVcf>snF3__dlMeMB$Z7o=ACI zExjI`kP)vrXM0s8ZpmuSCOX5*%mr0LoR~f5g4-uuF=>k%o|uK>;{0$-a%4v4StaKd z!qJWAFl{dVW2|FL)M;_^Bx@$y=`NV9LFomqA4ADA4#~pprCFG_m34=!L#J@WriH_cOwpH5O8hZOgCnfl{G9Y(rUqH3Dq2KZYjKM2r5}I( zU_&O-xVAYqc!F`CnMc7|@aTQ?DYRF3WxS^2ig~Nw$>+wowUsKToMm@ECrOER7d83D zj>FvKBA@$jIV$jJt0@w*6j0_@h@RKG>1n({ z$N1mQQdr?ATO!+teP(+(_sUJGF1M4BT0Uo;Rv^Q)QqoTu#ksZ#-bV6%nB<2xy8{r| zkB)k-9ecBaSl=Swt%!#Ckv-UG8-+a|qmbhqjRM}IOAe$lyUc*)T(@R(O%1_C)$)kOh5+u~B@^V21MYX!u!1BaH8- zpPtX?e2#Hgn1-lzY4B;3hQoYr*SF%@If`pKp9um67I4m($EbDz+PJvM!L=Qv@x(6j zkTs=wTiZ$1;7(%Nw+aUH-YioT=roe7-t9_e1~7+%nb#wF_`~UtKSurZhxP~ExdG(y z1EcXt$iLr-Mzohz{p(pYh zpUoC?jla(|>=jwl+xeIrLJwkcJ}&aSSs&paIz0!a+R4J!t}-{*S$49{uwh7BF>g~T zZf_MBzok;@%~hanCEZ%q3K(Vv;kkI9X2|(k9-oYL{%FAC^Ym3TT6Notb9z40 z^4WA=y*(Jo&&~)xuBEnDkij)x_VK-4=5cz@{E9H{fqHXRVJhn*;8xpqAc$LSMF z94%4eyC0n^$?gMZC$xw*_1$jwrk$ zPIKM3tnf-F2S0-SQ;T<6*+CD0C7l9ScN~{hj%qo^bv4k9{9?KjI((#KzJ)WA;D%*^ zbka9gqTx68vb1#gb_iz(57>(v zQr#8Oo37eMZU}wpg316_ES~Lxk#0&<`Kg4C4E#$`;sBp#>J1_PIaq@c^|i1ati>fq zEo|m%aMel+`@&2ljLJg)nVesD&c>BFS?D;2nTllJ`*2;K#`|&!|8)DQ@cI%(ZtwL8 z88lxbSLP?l!G0R)`-|-0g5y%-kqb`tbisri$1xTkap`{yan}=gsZRR6gq6cV{ z5?x;^(JV;G+$Sy6ff_Wur^WOY^j2nQn6<3IR5GW3&d)}cR~E8(zOn~rY+nyDUt+F0E2{b>OkF-@*4qmvGLWWXZjfB8AOVVo_Tyo4%=KHu=gc>@`>paK?<| z>|+GD;7ngS8<&M+*bF85MJnMvMhVkGo-58#jOR0y=`uc-jpt{kj~0_ZY7n$TgD-tJ z+x3a_8)LKJ-ktMax3iF=eCCXvuPe5$b7j4WtSEfrqg zWIszL{6C&Cu9~@AaxY{ytv8O5qtQArM|esOes*XfHe1W3)oF5n(Gh6-UXPtS^YFN= znOwV7CTD+>6SRrIvxcnWtjWc<6;0$*onMknkKyTo5ePhHfUPkHCDG00!8-cptbDNd z-$?8lPkyj%F1}Z@kOpSuQue?bQ@%#RxK58y`#g-TXek?qmoPKN2PNdQ-rA;O$E95S z`r1U6{VbGyEq(D%Xe2s%vsSw!2c31zWM+1uG-~6G{X-*hmmE_@MlO~)Tg!S4IkK1$ zI7=RC#Y8<+fw`D`wUyKvQ!bB|(BG#cxAl(PqC4}QlbK`Nyi^V^_eRTL&IN1qc%DX{ zu{vMhsZ>5rU`}gsB&I3#_;xJ^mzLF+EL(D*;ePOOVf}7!Dn^q}Y&FtSCh7`hS_X4( zH%FpMZF(D(xft2fTHwq~8F~rl#{I{Q>M)mF&)rrn<>|p9NpI(k=G`LkXhbSTUe3c{ zG?zJD%O%&8HA}}xY$GSNx+i^bUt3Dbl|q@a(HoT`BB8Fwkm|RJ#d4V++763AyQ6v>eUgjd zzgx=eH9Wsdy|Ia&yRrN}BmJ0@a?x6Dk1v;-VLmt*$h?`QshE|X%k07yl6SaRcD?t; zOCFzBXUJjw%EjfXEhTAAk<32hjXL8a=*H9|;6xq<3~D9cElT8RZ~EE>N8qvtIWLbq zyfS&&AncEoA)#diKqI;mY@OzJ4mc(^8c_hHVpgAeW;jX=xKI(*0{|24>3`qnL#U)dvYfgIm_a*+xf zdiQ?NXJ=g|)pyamH;kVv2m0pB^Dt*)BQfn=D#ZhRV8>eR97QU=ea%Hd3v-EO4)wQT zKFnT^gkdr{L~@angUw`!N1@d5_QnYEuulK#5z(CWO#5bX-J(=}_wd8>LlJm-R*$;9 zb8#`cjl7F5lA&rJyj&FtH*-DA2haZ?{i{<-A;U8qrE-buN{@ z^cybO9f|D8%%@Js#ryH*(maG-&Y3=_9YL>OV?BaisHMlR zD|vW>7P4+(sSM(EG&GkSXbS7V?{cy3TT|IRxKO5(4_!DS3ZpDiv5eR0&~r`Y=HwE2 z$n!O)7JEe>_&(R=V!01{46S&4+W3<9Ag@;~6`K$6_`5WfSu@JyO$T4xoW(rrL%eT{ z%0n&YMlJNH5X)#^JXsNmFLYMu+U6kac2n8Wgx9G#=OPv`vx}Tsa%m2x=eLkX@#QjU zg)f509lNzjMb~dR&~3Dms7-~kmUVZj6NxjK^c(ic<;=aMTx(Dw?U_G*o%gZcr*)ib z%EjJ&w(|9Jsl4mui|ax^CV63xlYIY&t>w+zLQ$ywV5k*|tLK?FT|1AnEmktrtw=ia ze3kP0{o0Fu(k8iNugsCLdXeXa9)0dG z$2`tLTHY>~HjS9=^ltw#SC`_e{yyy(qb>x1)+m>*5ohuS(1t=z5T{r5u2OY=c5+X!@IAFlmB zyq{0DmznQNr0dTS=#mmaZzzxF=N#;FNh;X?la3E@Mywm3BuzisV`=SB{K!Z`mOK57 zft5HSMKLa~DWwHN8|k0(#pB~f|}azvl(Q1)cV&GpDYGjf0RvX4pUoAeu| zGuN1Vii+yYOPov3n$0n}V{~Bt1@kC$@+9?BLZo6i-=4K3$*w!3Olu zmBfmd2R(h?!jQ<^-e>gR)weJrea2C#zR3ZzqC&9PUxndO8Ax15-c6Gr2ZlLda8d{+ z1(K(mlY#ulm6%r$FHZ+MU_bdd%RMTz9+81x2aT*-9h2%$>@jyAzrHXDA20CtB{y1Q z{!uaK`|%tZjEoN|T-0Y^)&TN-n_^`KIhBs~!CY%p*!4Iao;+XWjS}Sz^Q_Oik*{1r z&XMO=ai$WDa*oImCnvI%Ay~zH*b^1$sL{-byg%Y)W1JnfwF||Uiz;Y%9CndQD%=|{ zpZeRuXXPryk`ufhK+on=BgR+6ib-92^vGHThviA+`7&YF$O!8yv9iO~5skWqGIx<2 zCC~eg%awRtB~A*bIAL3Fdi``NELfC|_2f@W>6N=M#Q|ME2V;Is*8i-Q;e+HCR!3y-Dm&D?8w{U+lMr5#fy!Fs_?+UTXqp4UOGDr}M}?eZ z=4c$+gGM`@v{>R0Z2qa-GAB2)cPxmb7$0;!t`{3zLw^ulL~f z-qR~V%zd1&^L8ja>XG-Hnt_csj3~YnE9<`5BP=VJsx1{}@%vX9Ys9I^(e7WtT z1dkQ}G|~51u~ENwqLW^^Q19XGS*|`%Za2S7z$W=I_<@ zshXmjxpkJ_cKTXftF;p@*KG1z*WM<}qxJT$p1(J}(G7O2uD@j3TwfIRz;ol*1YJSh zIFE$Mmv#Bq?(0hbYM@`zVVrKubyI!#(;d2HtlMm&C(++5Sz^v6N&H`lGFFo$)?Kx7 z*)3VxhpOc>8O4|hDhZmWmN@1BJtvo_Kg3MH1Ie<5z3UUKGdoAAq&HoSk3y5hvs<#X z{>Yr_iyCP^FiG|*RWgGfNNp4TGlLGseOhUGCP{9Qlbp&vwT0htab)kh;U6k#w%7%m zIYXH?mptJY-k&S@-%jiwPj;dI+67OO=}z42gl3&x5y#gmf}GHM19PJJ|7QDt-UtO@<+yxyEaGl-4y1_tKykrmM+%9LluIY^2UH|33yC7-1Ggb~|or8ZO zzd54G6GvPa?Tkgm{22?B$f_HTD?RA_)rK)6J`5(DGcDT5+0KPwxHm5ho5`}bjt@gd z3VFuiVc2z1i8t&!w+!OkC+kUf9))1x>o6>D8wRySIGM{(*q*0@qOTIq*tfniISl7* zm2~{jDazNY>(JxKe!*nVP~2^z#AwbKL<-k&SJtSi)2qY#eGu15)5c^NS)+f~hjWsJ ztShLQ0TG~vcNVk%x@&R!DLucA8mw%@e)e!JPVm0tmPl@~4{IXBSR*N-ua*6WE!_9S zepVqOh1~i%?g=c_>`|!E<1+VQV>LMSo&4hxW=^-!pw)U6mX))g(~UV>?CTWG%E09Z z%#cpYgzqb^#q3us>z09;l8O93GBIl_x%~54_?W>y^+P(P56~OonuSqIvM`o47~?+n zrmJSbHaipV$R=9d;~c_i)@NADQlH`BiK4oAo@99^4 zve3^16

k(3eUSN@wI2>xvLzU?kG7;9mTIr zYq?f#Ex#T*$w1bd7p!)W?5_4=H`i6}ZnTwjD+l@2+fIgsImyk%E|PGY891vPWom6_ ziLr2!PN{Cv>ye$TUt%qJlkH^iTs!${XD?BG-6hYbjZApdTIOh(L;FgB^FGX(Hdi3! z2KhymQ5=?4$k%A*PCr#((gkvk&FO*jP~Z^1*6gn%`Da_H zv`kQ-`X2$PwVRAofgf(A1R#L?;-S`o_-j4;3JF07@9l>X*ZomtJKZ)t>5Y5thq++y zW0^my@|myKOlIP;@44fLKfDjnXAnXUV^g~0d;`$pOaRR0_+#^YKj>opG3=)==UDyd zu?xV!$^bkgU)8DDANx2H*u&Ew7PkY)Q?UOY6U~_$a!`l)9CeqTx7(aMbSF#oo6g2r z(YW<75>hL2!P-p4abZwwi&3O=VQ`E%7#INXFj2=Z7VqscPHvQN>2z5ieI zF`6*ns(}HnEtsvhlQWWTWT{T3!oDND3?0*O{v~VUX3WdoXTXfF?9G$Yn&Lt?!fyi} z_cmbAs8kHRlZrpa8(3#%jqOY-`n0Cwrg|!R_f5sZe*77Espz;km3w|>cNB2mEP#EH z>S=Ji#q4V5Ja{gkcX2#31lZ$mGMn7h`8?PSW>yn>ImhSbWBm^Pvl+9kN|=Gm{zVsC zG5}#kvQrkT=|!kX*Bqbs{j&0~lz->OOuoK6 z4+;EU_2=i|5r3ZQaX#wr%twtubSZ4L5xL6;t|9Us>79s~_(2>$|Hw`|K*mH#kc|RePC7Zt`bOH?iK`TF#UGP(F5%m{uk* zl$gLf-Y9FMjk5cy3A(x(WgdI@hWG3fRVDN5P%b`hM!9*sQp$(Z+sNLL?N$X&3{+sL ztpZ;cC=m37T;fn>eYIgLt*8IZT#9cdYY=b zF^|*U59O!)k+wSk6+c+RSnH1vZ(r71{jkR}0Eg=a;>lI!WmctM#fE;T*1l-(?}xr) z{P3iYKXl#wU_vh0PwR&U!~781pBZJWomj2*!@~A{n6@Q~_g?k}XORQuHKi!vtn%R~ zZ09vIc`SLvEM`i3@mhPzEQUX$@fUkzQ6r);V@?#ZO`|YD7X{aNW^iUpu}0Cm z4ttKHqM2L6evy_LI}M}Y#B0`Ih{C>^{5pB#F>RR_H-Og`|NYZ;`cipKj%DAgeo`t{ z_h3d)ce)u58PJUEp`|@%;NuNQ=|z_0oB>a!F-w|!A>%2(H~XC5 z@8%(b*X`@&%4^oqiaFFn>1;gTPCv2bV!dJALEYo39=cOUPU=jy z`{_rnX{X=WZ@1^!HeGdDmz(JtJ$k9TTd%+FpKF74mg?%gx}F;5x$x%H%RlQK*VXfN z*45m0Nq6_tj?1Zk9oMDYZ|(WVkq4gd!|PnCJ}N-Jpyg!VYUZ!f%>YR-v_kO zt?2(o_pH@1-Q%uW&vnkrb!m~`b@fX9^egf>ccMrZ&VF+;H2b6_YPIpwx$kA%) zaV}BT_^2hKmr8aHQ%n1oYPsc~EHn41B<-M9jOA+Ce>PbrY*I@DE43t%e?0WkmEL|g ztTND@IMf9WMrVv9^AR89f|Zk8@VW_epmQBjZ#Nm0pPWyt?S$dcE*Q(#y4+*$rjH9+ z9&w`c)EVx-oZ#M)JuVAp+-dHDT7Pq9MoEYFIVXI);|P5%@{UhA1GC))3w}70i*Q9Q zXSc>}q8Cc#ggP6YVeu^#MYqGy&?5|PbHnh7J*mx?$eH}5WR?gSj|Oz3EK$Opd$&W4 zln5dp^L#gX#dAu$>&5-z6*?H%+6#W~bmmu=@#pY0mfQI}x}UX?-Sn4n2Il=$x>i!?W@Ihq z*I_!mt?B4y|1JI+GZDD2d$);y7Bcs9ZWgARlO;*aLPhN?H2O0Wqwi&+@fmtzj2YNw zl8pot&cJYgcxMftj!41@}J>Vvas-C21eD*!jT&EJRacdDl$>yeFpw4}8hTO;&t!mILK3(q@dSy!x)dtNjWT_g0{?feETN zBL6_HQJc+q4f_D}>==l&#erx!!Jiq@fmrjNvlfVkSv7iVo%V3v~ZETv7M#G*$z@+ z;v^OmTqJG+9TR7`f8!by+s70`-)lR9?{^eat)uvO(h*4qSl}Bn zpK9hz_oOd!6#beOfr#i9h(Nw4&+BA(c#PV7B7;gEWvJO6)>@fsdMFCDmXO0JjKY)z z@;h_s{?gEk$bH@E_hfg%({MeHzQHdAXhJ6B)sH;1NGw2G9xMM#PO^EgqwF(;(*r*okMo138=Z*F1F(gR zOrzo`wBbJYU+ZY>qgV5yp7S@?*=J~xhMPOmFn^FhigS;3BogrAWY_Z-)e3&H21j=ZxapY7_RYE_rSe1`5m68np}@9RvNHl zPa59wYy0^5sUA%RRmru^jJe$0bN;)DzN>X=nNQy9K0Q)<+MSSlqmN7AbY}Fdbi{z^ zPBMsr4$rUW9N1xO!a*d@L z#I+%tc81S;1L^jkMz)|QvpUnr8EnahEi*~d$qrs36Bog`+EY6fUj6Tp2kU-Z%vPvn zS9{huIws2jzZ2p%VU+m3X{XiGyd!lJl9p`%We1 zMup=7S(K39bljSeO9|9q{&Di)?U{X`&cw+5%);qT&lc}r|G6U9l2IARfa@OA!TTZj?F~k*9PmsO8 z?@E6#>kIZuoaBAJZ^v+?yd*1Q8;-R}8qOVQab%MgwN}#MRFCYSg3RSh<`#_0=4-Q2 z$m7)MN*10Rr-P7eTsup;5RcO-Lc6v4<>eIK?Dhr$QGEt!=`+0@gs&Dw7D#%zi<1zA7cs(JH(W}2k ziv5zMR}yo=xo_yf*@%=UWHCCqpjrtXS8H8S)RJp|A2<9v!4=j%WGX#aH<>~&a_w-K zbymXRY&fcTYM{&FpCCGl`>T;}qD2>XEp#23t-6`#CpQyg1L^(xhyI4PSr{^g+0tZo zzH?SPZJ5H#_L~vH-1R0>wNcv&sb^c2(SFILrj}!7q%j!UuOD2t?fleoRr19ATmv} znK^qS6K8gj`5e#8a{9;4_ELEHI-7XCxTNsf??m2-@2B8FYw7aVMLg{~O5%+U(jv-P z?9RH0?NkMt&#I6X%}p?Dd=(T<zC0Fy?XfLNl+mAj19yaH^WRegFm*B4EKhRyE27chCfAA+(dZq;eC1yTB>ynLf#(;@G z)6n)l=k%-!puJD8Zy8;_e;05zgU`d`+~lL9vp7t2l$u_4%vN@giMO2P4Ee3*WcQ&su#ZpsKEW1AvdsKnYPYlAXM!YAMl5hMFh+Ew_1E$`C69v&2%=h)|RupFO zPorQ1)Z^1oxtf{N4r#E`8eqe(b*jU;z$0A4p6BDff!_5^1;}2@Jnkl(-<#qhS&1Fw zkDa#S5#%B|o3_#?P=Q3=qc1J3kX0`fDB{}DDnWr|#eT5#3BairoNwz90Q(SsY$y!i zTnV!YzeZzv5%0?vqv>{!MrV*WzhD42#kl_1KqpHYbbMx7nViNvwK59GD zWf`827_RfaKcudyQ=g)n{^S4o4yQAUoISsCstap6na~@|q z($mwB+LIaG4f(9JjvmBcoYVB6>+^LU#>D3%(%n@Y?8)ZFwv)@%U70`PE`7hah=S{A z=nMt?8=D}sohgQ~-eu8Pfh3(j;wA-RK4&OQ&iW(tSrE=1@W+_G-0zTQY*Z43y%YAJ z!Sra9HQR#=;|$2MO2ZJY>z#X~p({U2ZMn|RPRhg8-~!aH#d=7;d^9+bkINPGGaXgQ z;Y^jN`l-aUNwPGmsutr8y7s!W2HndUjV|$7!GsR?0WQeY(fzlAJpKyu5!G7DGCxOVX#bSRb?y-O5ctyj_q zOO`q?Sm9OUF|Yae3NPy`8oA@7l|d;dq~D0+lHzkhs*^c?_SOlt+?|<4PTxGeh;}({ zSRFu5{dgsmF`SjMQ=;`ku4R1gsO!LcbVn`XHquucph5i!8tmJsLHcqH;_op3<}m$w z(VPv~lLaP>U&&L+Z>nJ zCu&h$qZ@LJD`tIj;U162CzrgXtt58wRg|=TZ zGs`sy9>STZ4I12w&%}DJTUYqL3ZJm2Ixma$$80o>Pw>?9tN{5xPDMUc17ubeGJ)^=e53$8r=8LVzC8h)%fi5 z*ee?aVSHYy$imjytf?Q&#OnPDubLwiUYU(dyu!Q`UT4e|UTYUByoNa^NzJ+%Y0a6E z&h}dAk*pDic)C8}3X2`CcwNf{IvZC^h;>2EAy?cICE`Yfaqct>^ZSQmR=>z&c_h}eUK=z)`bL01BktxfB^{)){Yr!lg`i{?$cW@s|N6QMX z@d4y4IZyF_pTqv#)k>C}DUv^G_+WH)1bPh9V?q=;nnzZ09D$y;NR5 zC#U8biT=fUd<>-jvA=~Bg#DCj6}~W~FYLEI6$7s4;@V1UDS22VZhSw-yvXH!rJu_$ zA1y{(OZwUp3A*EraYyL6W8Es`S1wdb&87U!Pw7$Njls*9m%UYw*9y+L2ARpU?ZvXm zYy|#l9*I7KSleYS$j_0v$yZC|)*^4XHjTorJ9B!D@paZ~7d^iD;^ z&^&D3VJ;S{%Vg(eALPBDH*kL{V#8UR8q!GG`&LL@8z0o1$-4Pja%7X3Yuw&aPR}oq z1_Qj&fWOz?7JAGcNMGSS_9#{r%e8gP&rOQJ#?|DocpSo4w2-1*mC`iA2kkr4cUD)A z;@!E}J<3*eFH7X*zuu_%kn_*Kng8oWFJwS-Y5J@}-YsD6OtnbPSnClzHxG-NT1qE! zb2T%WYaC6^t0TRB4tbo9x003f%4FS0UwocRKJJ(vQ%^AmIn`Vq7L>@C3EuE2jldFD z=IUnWB4|}p`8l#gmL2p%Ok2)ef7Zj}O%9#HP38WON{Q$B{kDpE;x_dCz01XdxK>i1 z4*Eo$FZQ3OBe)i8^W>Noezg!6@_O5+`@m;IBwU~H_nk;Dz?T-H_~(Z_{pN$AX%SF1 z(c@n8T%6n6TxJ#(OX3J}tc4Mn=|z9vw_MyN|5!=R%MeRG^jRcAtLkAWWnOj^`%G!2 zV!MFey2g=+Fw-N9JYa#3h5T7mB&h?K7aYfYbJjK^ALsJeS;{^smawLNI9i+Q^)6;I zwP$Yf`bIM1Mxpe(=8FqAIqywAYfRT%==(L2&+W<8n$ZX6#=LKGWbuFJq3iO7VrO3> zM?d=F%eDwy{h~v&wagQ5M33ZbW^u*%pdWK`*EG=MYb-h0dUo=qaiO@H`e56H2z=tt z4X?s^vj|%m+oVX$#Se3y?nVGP(8pu*5PGS(40QM{W3G%q@h;{I*Ga{PCV4n8ys3o-3u)S@ zM7n$M^Z6)(b2#Le`;re0vyxZC3gzGdA5_^LNxwdQo%_k{4z`r~yGvytKUZ}}N8(Lk zDke_PMbQFViOVmM56p?a6&Zn$IjQg-$U3g7x$L0R;JJaHpH5L|!dmh1j2yh5%g=vl ziS!=oi>W-G!>j4Bu}&_ZY0Tt^RjCB6;rkgIflCHGa*y-t))wM+xLmdc_;9v3g1Ir| zDBtt`;9w2kc&3Q50!rKvdQSy|1yG2D^LhTqW%; z7_ftqnE~u(hOj#**IZk|U6YP;?f1OSIe)8E_xs}SWuu&qOka#~5Ku~eQm_o6E^3^&aTXhF``Wxj)Ss#_%echl4QJPfmr8}Xuk9&$UF z%eAp(@*>6yiRR>IXQwdNg`UKbEu`9o3UR%}{I)h4yx^K`g%vr$JMAUoL$O?b>w$wG zH8@@`6;3B}F|t}~=28?(o7tXl4-Uud)+reI7abUm&E;owvCI%JOgJBo-dl{=%(ErC z95V@-Stx^&ys+T!FuXWrM6Y&vsA}6r)@>=3(O*1q$UY1WLXC)dk&DUXE_3de%eLuW zbb|9ff0u%o?tJdvw3XjJ7R!`V9=LcboLOi_Jj%*Nhl&=Gm{=;q%{?%Z+@cMy{{ZiY z(B^F<(yL7Vtm}z&&f%D{+lZ3Axy-0(E1#ErmvN6gFeWn$_c^ZGt<6P5*Vb}jN{JlW zItu&$*#n87*Y*BqL{DuY^{4PTwerDOJ{O<5reKFhE*5-=5j*mOO)mz(W}6mnfF1TN6WoH8|1VJ#I#!EvnG+>q0g@L(_v|5VF%Y= zt1&E_dCDs?(V2ZLf7XkU>I3cZ+p7TB-_hbPn=G7~UWLtFj>*@vc37RV8mF#nk@<iXY#U2|qAUG|taThB zuUCI|w45Agi=t7hVK_!_oo^Og-KyZa^O$USXoq>_L1@rkhej8eqq?LL2#l7SA8p73 zkmH-6MPy+Hid`yk{zHs(K5L7k{^W6<#^Yg4`Y7MiA9tKN-J2b-=w<-x4)NGsoQbXc zys=)i7;n*!wj%)Az2uC@IiB^a#GyGy<)N(u`d0=*-%W>^%UBPl8(OoPp23dv)6ELR zByvxiLNYPsXBGaLA1xV0c33{1*-5clx;ZlOY#sfE;Zd?|qAfno4u(&CEn2rGr{+j* zj{NCw!M3c2kb~Pzk0Ck7fmg_xu8x*~TXq<38Gx8BT0A&Qe#$^Db#|<{=#+Tt5`^dl z^f126!1<_3jPZ&U9AZxHupo@{X2wPoc{g%Qixx#oO?oyH?*^kwo)-JJWnvP2bDsL6 zvW>aGQ|Zt;K|XOg8HldaDsgXRlq}cV;Y+(f)SRV71HPY+<0`RY&{6rwJl~$oL2hUr z4~wz%?tLbg_w1O|9-yRWl^#RBPJ_YZ@{aIza*s)Z-WJ>51fnV5pFj}`>s%~Rh0{Js1^KD7P2XmKI; zS6UW`vd;8c*2%<$R;%)l~>O5hL!cZP1B7?@_+aD(N6EGMbkv!U zBc96lQ}~?T=KViCM(*(a%)b)|%L*-7XWkFBs<3?-`Ntae80XI3svbIi{|xdD{JHMO z$>tvp$XywP#S?iy&t%R!@5A+)8b;X$zLtq^aFOf*7z{k zaP&Y2V}z={F{Yu$khkHGq49=ch8g#JxSc(gZ5Xw|%D61CJb8fawdCX09o*h^?c4il z;10vcWp51HqjL?b|Nhv3*Nz#HIM;F$F1~%5p z)Jna8S%vQ=>*PpDjM&eLllHe_#l2smJRjspcN+UllUYNzP@>d>EaPH2ba{mDv|eC38lXyK0R{894qDj^gQOoJK+9ix^f$^U-hX20!K3k#GN&a93`A=m54j% zKp(CWmc5kN-xm;uakg|JV%&A&Tvq-1Pt?J2H<=>n(fu0 z`DGoBB=USAi{qmu{XOgTn0Hl+_j7fuMJJ&9V`fO-*Fpc5=hSJ;vR+5;P6K`fl4~5V z#nRz=<|5MlJX43a)0k5o$FpnJ!TfERJH3Za#WZ?yo@e2BNEW7j$->Jcbh>WL!mC5s zxJNc|Pj(jjII~ecgJ(VSvk)7^b8K}sV%p~50_%A3lj;85orTK^X3{s$LP_%+_DE-8 z(Df{A`7H~7kK|Z?l=)DxJhNu~W|wys5;>lCo=NZHiEKC5riFYwZXsJ()9w?cl!g zWTTs%v|?YCO;a2BKG8~EwzZNPMJl;xZ6}L&*vR3Xw({(Tqcl2YDYehpOJZ*a8R<;7 zPoz?^gRSLyoQ-@P<}69CI>^=`72>Zk!L#f#i5_1j4i^>3xvOBN4QsONOi;Cx4!Bfu zhj%Na`8NgZyD6~nuL@Dqz4-gu3VBBN+!nJ+xv;xjX8S9!1150kP0q282^L>b;AjVO zS~XaocQ2FK+>e-#E0?~*d4{^LQu@xQl&)#zqUu#8C7zWMf0F0)K0dJRPrfk23)=c# z7?|RXIdkaxIpm8Cbm-qL;J)-M`|nTr;L8+dDkl5jsJS;TW->qb3|T6&Rz-WgQMS+< zH80b>_=vd#JDF3>f4{ihhb)8-^8fZi>l!>0xaN)fbG*@JEWM4tm_;4ToU0w)$Q$g1 zN#{J#lr{R~6b>FrND#4@Uzxa#sU+e&a}2&rIfUoJvKnL#fO$N?|q{8N^EFHzlXyuSuy`%0H7- zY1p%ceB(m;bB3nkg?kD%7jtjCFBM<-F=#q-6nm$lU@pCJ+@l`i>ja-o#q-U~o*tiy z4Ru-L-s6Eo~;R@^QX(>1aer^E2Peb;U&d zn8#kAeE3=AWA6Dpk)YCJi}F}>+$ z9FvdAeRM!NILYLpwz6WnQryfer1uCLsjOxvE3P<7?^6!+Jl&7F%-xnb7D`FcS<8;P-q5=ao{>z!VRy6d1R*N;JWh(qneHM4Ff&ty8&tZ$geZfbIx##gAK+$^q=mq%ix$r`tG7k)FDXD(-lrv!f51xA8`ghx9WtBj?*=auLbia5}?hwVp51 z$NS+t|E})k32Xk_zO~-;8u7LGOgxSc$Ldw#sNPfqn~UKXGm5-nOAXQ=Fhlw%&!Q^G z_XdO`{SQ79jhWFEz-RBX2G>{9J9d-#?#>#t`oOQNsljgQ_P)-WQ#HB*ZbIex`Y53+x=45dyE?!|j`pFb{ z%}&L%pfuDl(A}8An%RCbz~A^>c1nZgN`8;X6y&(2VsRaEkG5&3{*-^enu=dM*V>lN zj3L(2_8nq9urA#$yYtXT%M23U>l+Mtm_0S0H4UD>eaXiQV;)j+SPwmrkA-wLmLH|l ztWN=sexi@+FrS~VbfWT{cUy~m1n@b!w3%L0U$Pw!*;Cqv+|oaJ*m@x!%lO)QKC4!I zHc$Ux?)$_7T;9*`-5?KrXOer|@VoJbwrO&gGj|Mo53My^jPGb{1BG!ISU@`X86l6uKdMYo*9XE3b~ypEyd1Z1(Jp*K>_`Nr}k1 zj(A#6iQ6^~P#4?dG}m|Ct}0=sP$6On`&+g;;sV!pu5;{>HPaqBbsSOZ!ffgN|G5?& zkZ0upH##b=M=G%~+a5`A>}#Q`f4ivz23V1qoJW3fl@j3pTTs^ln^kT>kkv(4$jNV>q>t_5^zbq}E*KLnT72SZsi2=-hP zn);JZnG=lr+8}H{!p~I&GxH$?&7DI~$aQ3khe3$HM|ZbVFbWi8A~*4MdjHo;8;q~L z0&(CP-HsLPZR2YslfU^iI03HfbT~a-M<<*Xp}~4gb7#*>^#nAv(lc{Fk4IJs2^`Bf9fGa^q8E;ui@WqE$KKZWB+SLCJM=p3~;Aw@lY22?3#^avMetA z__;j`fApfm>}fUzbG>)(4*OJoWx}#8nMHHJbf^H;lkMj++ZVF>iXW2IIy@piK+1f=klqV^70#jyq>}rNP%DjpqVi z5ZkW+`3DN%IFyd7reEMuo%x;P9A$v(@6zd4M>(PDBy&33i^ICkGV>(+VA`2tJvk87 z(rWM=SSjv}nTfs37YdI1cVn4b9N-I|XkWa0<&B}s*_Xld{Am*+ux^J2V;v)*;<{;3 zRvH>{{OtCX=RlquKhLG&!W6DSoW8(+M?O|uEI@6}`7z(}F^){g&@?+)@J%V9>pIH( zx^}X8kdyd3c9L6j6>wcn&(;J5e(4qTW}D!ujR`v0`Jw+CU(~ARk5^lm)w#q6u4Luh zi#2GogpO=O1pM9Tw(7)dyAc7$X{o5WDveorX>i?`hHUZ}TgY4<=v9Dj_Y2TycL9E- zp! z1NH!X@kWRJez;0+<(((=8@u^nL?f;ZlOv$^j6f0R#w@ax{+zpf_b`jHZ#sfGkMtrt zQ-f=}|9HK@ngZ6c3h?@DK59?*Ew0zNt5Kz~OJRXBkK z4lLq$8~r8(y~0BAYF{XF-iDxaY6#kELf|#)KgTS`seL;5AEZkvDuMnI=G~C{ij-`$ z*vj$5F&mdwaEwUIK@GZ*zRgjn9d?k7Tf(z+9~1SqN`<-9mBuVJLpGZ@Jl3)}}6U+?&Jw z@L$|>=abvZB|})GgLh0e{Fdfm5pyyJTxG8EF!CT_JkKYe;_y(R?nUmQs+~ezm;7LT z@&(@Cbdo@q@&3L^a^_T`bf3$tie5>Q-qwlh7bVsoV2mR0?{9htKJ3=v?qNNik-xCJp+{Q_J-(%qw=8Gg!4&eHADE|1_Tq34zE65) zh?2Kxc0-{~-b}Xgu0riQQK4Q^%|u;SeM084ub^LiqRgk4F?MpIl$vQJZXsRAACzeP z(h&_gKjzO+p~W;M_OjOT>P9e9hq690C zSTdG#(Mml&xFuj_{{%E3i+cYqb79D$e2&gRKsb5$C(MjkNG9ZT7H(QIf4jYjI<}RG zdebC@+HMA~XBF$lc4T3@>10}$Byn_$muenlW;UFVX+4!FzUu^Sx)Ot&l+ZO-;m$%Q z6n$sCH75k)SjRccI?$LjO`8Nbd%UCw)X*&&5`8NFoLn>x$6vM$nQxUD>HM^^5jqvRjy zDrTn?_<2i#cYl~5irm4W=_at(m|`yX-WU4%u^voc`~qKSmiwanFkjqR6hS5{0`X_a zFZYN9xR-v~BLXhp$tq{Emneznthdq-M)pfJHkEu*KEAU*&T=_@h^NTyWpMr4f#c66 zC%HDLlN^e&lpO96-bOVSX4e zlf9CCy|DGOF9xt5YRK*gSa?NX#!Ud&)@eBU@&6k)0f$&poRWi_az~ z8(JmPH!E;{58tb7=3cMzVQ!ZnKHu>{=1D*7S8?x^!u`|62%LKqf$f(xIQ5o$9FEVy zVPqFMe{JN)&%aW!m2>Hpt?3v(kZwlq2YNadpcVTRz7EfaYk598u2#z8!Ol`TyR%H| z>m=`6bYWe|S^74tls5M&MPoysCi^Dd@*`t@m1KL<1%00T#$$f?hn(kKMvwL%1kI83$zzh19Iadri z$3CoA?5S#EFMEoWa_OFvRO9}A1bcl)?6Hv`&RrwcD)1($LeiI;pm>o9F1wO%bn?gQ zC%)M7yB|J|rT2J+FNW^(#b*uoby2*QBC@APBQT>auWupiIP1Ajo0W!bozu|wDCaS< z`E~8mU|yGdr;`QDs9+6a0oh9Km#)WTRV z$m7p6!Czfj|0-7CV@DGVol2gOuI%{^%nB*zUYPxRPO~|m?TNra?rY;7lYuQ~ZRmvt z1>GYsc5)g9eqin83VTiW(x=JyO3693q&waFl?6ziQh>panQ8Ha{Uxk{SJ@uNTyV*F#RuTthzYyh8nJq=|Y*_2V*fO1wBt(8;+YC*|VClQJ_! zFK2#tf*swAix#ntzmUCW(^;E8titd6LQwO42&VCxBKp!@dpZP>3i5+XIUWz7@7~+6QHf}L{n%;6Q>qi%19JzeX4?pRz{40Q-W6l$WobOXO*AHNS z+}O8z*~Pu*Lb8?{oKMKHLkW^(q|diEy$9@@XwYAYjCV>jHC3TjL*^p!{aCOp1hzJz z==OuYeD2$xfG)-eG?bm9I?p7iRw;&B5GdbT5<9-K^tYuL1M0TV`YP7=?N+@15(M$Lz_%UaoDT zuFiY<|L}~XyIY8@vPfdDcwu?1a6GI}_xB#=$n-ap$m50bJ3V46U$aKF!idV|xp89c6QO-Q#_Ib#5F_T)03&mlaC!&{yBYF;bA1CrDm1fdlXNk0b!rFBs z=EMHRoYO9O@Ne2drZ6YE3w>wDis)yIWlnA)`@Gk;mBTd(<)xK7UCHEqcBkOT**vsa z)lBBnFZSmkPo#7U!^$T{T;7p~PrEwExe2B6gRfIQo*W{1%yzSLq4>SEnA9wh(OXyx zw+_QK)}dBz&Sx*JjT|Z|mGsu0=#UYP=ls6STd+^|a9jCzWRbkS>kiA4VMw{1f~I%K z10FEv*;=XW3G||~I2_v?Qqf{&F3Ooh9aF24x$3ODE5f1fmV#Q|tm$U9mB&11_?+R1 z7hA&6m0ra-b8?+0Y-Hz%5-C6C0WCSlS<8&5bu<@~6>X%>#Ug3<$rD9U;duLvJenDE zLi(7?zy9POk9cBKGYv`$jkt1|ee@>QGB~S5w)dy6Ffa^L|46}$i_E7!)j>vwmC9*y zZ3$8I04^}%W-9rnVeRG1y;6xj;fYsWI9F{Xm-mL8-RHJa@~lKcZ+f5=`M9D9MzkE4 zi(SkSeppf_XaDlTd0uDwz*H25u#VlSos=1V$+F$-^G;-LFMqC*KXXyT#ZrciES2Zv zK$Y~?wV{WxF8hX!JuF2PUqnYdGo&^#FZhuW1Hb3OGq$x%EG-hxL)@S4B;QKTaZ=f5 zoJ+Bi%MX};O%7|ST{!C8Frdd+UJp6hG`k83c}ni`MHnvRlfxoMIl7~zZ0N?d!vrrF z$jOHA{jvV^85+A5^pus$pxIt{a4-zkt5RUi_tT}E_w(Hn>DI*qPF@3S!olmat$+|qObZ#eZZ+SmBk(=Z1{hN6TEO_2ga?)I;%_@_%tJ&Xime+5` z=U1DHpeOBQUrvb_mU$v#CEXPo^1o61{~v6ndv1wbY3zYSa&STQQ*b;Yk6tZ$1GVMS ztSh;>A7RKLC;R>ZJ%BAc$b_cl@}tCq4vjFhv^8P?*OAxR6Zm>SsqA(4z@=Dni`!Dr ztOdF0FYToBgJS8~g!$br;qbFGqM0xKl@rWF-?KHhJT zEWPRlO%3`qc9G}h_Z{%Cjo2iY%8OoJxW;kjVO!>m&(346i>35-E|Gh`=s)GSVT?DT zoLu36*H)6OB4@YR106?)V=BF$(TY5@7}Qn{q?gIkV;ryeTx^Im;5R-;E$rHg?PhtY{~fmzIe&$GvqE$TKDz@#j?L5Pc*s*`i3Y zR(WG1&(*$NHsIv0JUU6*$;hGPb6fM=gPdl(ixI}%^i-BxNQZ8fQf-?jc9I)iy@-Cv zm$_)!tfh=otg?j4Q=wdnoy%tcL}{T}i9CEt&G;O@~d)IDcJ)TPgOd9HILER3@scyGvQ*YP2^!tGvC?9+JvROdgg1GdKID=bOs>MdW-+p4 zqaB7!41^PToE~AUsro9^frDeD`(is--wQ?44w36=Rg?XMW%202 z+VZLmm1sl`v2d&d`|ShpJ~$o|Lo(5i{T7!G#>rF@J36aYqc#0;zrJO_X<8L-XC0I2 zW9%@{KLCzL z+F|G6Kx`#1Hu3jN))lJYyf0d&40k|WVIXR6(!psn`6>P$3;8-4l|3pN217MW3wu>2 z!tKbP#zsr4*37C}NnUlD79Q_1uu7^}4~><)W=fpe&m3f9Jaiv2&^VaAoAkIfBj5U! zez(-Oyq_Jjm|el2*EddL>)W9#f8NF);_*X64Pqw7B+H2Kvoq zzV_lMQ6ICz^TGgJA5X4!Vg?p#D$)K|jO=@Dix=uZ42a`>sLDdUnN?8tix^gy|a)-zut)c z$K~)Z8+;xfi21+b;iJt&M{=4Dbz@{zb2}`UOrK_YJYBEMzb>XOYs z(toBcWKs~m7`2!~&uOn(^gjkfOU^-ixYi1ULufp1X)~bMTZJh@VkLp&+miG^6muLK zS&h#-`QoSd{yP`6LCg0+Q0H@;?460S$_fm77$udR?2wqX8hv=3kE%E>@p;U$i;-5P zb{M*YnYlgb{XCh0LUN;R_H#TGdj#-(i}a#*V?qYa>qTi^rO?w)|XyLdSf3r+M!)1 zdT*C#vA23A1|6=#zkkI^mmTDJvjX5#iyjYpa-XlM!t>s7;(g2>^)@jdoc!Qgjx(EC zN6dN@ClkHxVP6@5iq7Q0&(q6xs)~*-a;!#M^d3sT=O}WZ(=u`I0N>A!u`+VMEt>Lr zCV%2{u|E^-8df18EJpl8>@boX4yFt%LX(CD?x)2*pvM`P@v?S_o@ zwT$DvUM8EFM;huMS?6YIJYi@w+tuy#q)x7d2koys3q5BDe(i5?JiOG9-?)a`_gAHc z$U5H)^INwxSZr%-T&G)WsOa&*2&`6bmY*lqdXcdArjLEx)oM1U%GPEaVcc( z_r2ROa&xOr9F|HjGZ zJI7_!isN!XwBlD7FZDxX#rN%TS!$(~6LWMjC@oe>EO`drf*zh26&`+Yz)03Xn$1z- zUmtpKk~`w^6te9_^a8McbI(NukAGCm$WM?y0>v4auevzh!{dFBK|C5Caob&$thk5Tj zPk!gdnw&ZtfAjppbV?QuCuMOQ%EFmVbPe$Qz`t4!>b1y1tK0myD_Pja^Nr?4_I2)N zE$vDszAVq?zh`4*0lf*V>nnIZ9de%hVjMZgx~!3qeKgGE*;PCC?T*Vr!B>8sXXb%E z^#5?~YPGt(7;ZaB`h6u9!aQli$I zAg5G;^+Bwycc_%7zndVAxwmaTSI8y5axz|(QX{xRCM>8DllUrWvbtP`gwqqht3njt z%VgjmRrK~(NQoQI-RCH9{Vg-BPn1cO8SB1d6=VS_#W1;2+B4_c&a+(pY+Wfbu!!g~AqT6DY|^ntaLA6(DT?Rd@)6Kne-u{!JTTYQi@+#5BxS7|@V zAB(nlqwg0VuGjq#(TCpoS);K*5y4Dn4JvSIPU4zjI4F+{2 z@A#0lpRpP=U8cd1U94A?(78xnu?Ej#K65|#4?o|%kSqb~`{$J!EOjNX<*Pw&@{bi~ zc?J=rfs1tnj@m___W=6lcJOt!vF<)Bf?1&&d~C^l-S!b!(2-nKhg9V5NJZaXJkQ>h ziq~CJF)l6@o$^yK;XXO2*D3h2iTz?^AD6kN;YkHEOnytlgjMtlS*9Q{lV=?fny zJ%#7U`M|3@Y_iLT^}Bp{4PsWbZ2{{3l@ArqCD!+4?Wq_21|#TK;yH?4Rz7|omxn3j zr{;Ad#~4ShaY8^Xz;Sy=DGozdRh~estRm@>sj+ z{o&t3GV(BDGqc1R(c{S1vEqL6a;Qp1PP3NjgRR7kz07l`*orr~!s9*3GHz4KzIS}4 zKHACc6=Wbb*ocf*$*IXIajfqo4_;VG8u^IdPrArOCmVS<*j7U3wUhacY^7FDM|o(c zlG7jTrE6PDsZSqN+Av#bIk%nc$Y?K5W-6u6C|mXeI!OIQE1B9^DW~aa?6s^y0^TUl zcRrtsDHUS!vPv!`C=lDl1XD(t;#%t}c{aXEY%W*Go;u~S)`nS~-z#L}=t>FW=a;Ri z2E)xNX=70-m#0>U-l{^{^;2N8wnCoj%4H<~Z|4bBGM1mu{81uJ>3MwnSb;E4G9{%Z z@ZrDzeXUZC^Yeddcn-9Xyzf;X_!)gM>W4R0^87I5Fmv5LF?Yk3XNVWbAM&|rtY*IZ z3LiYE@J5=m7gq3WsL4?ublBhyL#Q`<)tI}HNx$L-AG9g)LB?SE8(*^)(2Lok8;;`%;mpF&z+=A#Te!Dx2n~)-p}XpqhI=bMR}m2idc~}1K3fVtqZV-* zdLdbpJ4ycHGiw3b2n^3+^`GXIUwSbaXn z$NJ`B&%u2Bm70$?ANgEo=3(x_JX|s4GIxuaa3Ag%cADE5x_7%~*tj^+psser(A4^s zYlz7xH{JC{$t`kECAaf$V%%P|J$b=<-%3+3T<>^I2R}WbC?%aKVG`U$4j4!S~+<$R?g3e7hgx6$Z?$*cPU{pMulpY zO3Zv`kIA!Dm_t6MU_KcOXBEaRwMR&aJsu3=+A&m#TVYBZPgY`*nF_tr`LzeRHay_K zQ!5ANmn&gg!TeLc&cfYFm?!Y_%b8F1Mv1Zs4sg^fvCKk+Bxfh=`BRCn?RZAVui5g! z9<|;pG3S*MiF-rQpXhv z%6~KRtdwifo5zB2k>_7N*XZru#P9n(6uXT&Y~^}wL}&7a;X3@>^cA67Vxehpc^M z9J{c#P)~=tdvw@M_Hf%V9cJ%gX6Zoouej)NErva!m)X1WMhlDA39!=Zm{+fZU6>v> zuhQRGhk4Vv+_z=u@wbg0kKgLpyTf(hb7qy;>9M#=0v7SC>%=)7(#euE=$3_kt>|UU z&%(@kWDwo5kb08q!@+dYG@+}JfB*MlHYWDUf*skL{O|N+)g~L%Iva15%!vM!N#`tC zlSJl9A0eBg=Q(f>x)~>AF?I*a2B7uoj2M!M88!Se&;(mAJ$%rnKj9o6V} zrss-h=80FyjIZ@WlSw|fPp&cdj4$*v=(2mDL5tdCyW2&w7c~M?CvmLfm~={;ik=JU zwXm=;t{$_4&FHrx6W5q$`eXJMpm~o1981f`&w0$p z^x$0VZX+I1f2C5s#Z*b=#!9hSUnR*~6v+KbADFEP_HFRP_XU2iIZW?& z3qMpw`6BBCGnUE7*piDodo}`{awCv&GZJ;Caot6hU|S2i8M9MiHa;CoI7T-wP9-m1 zfYtwU+~xc7?q?qAZZ4oFr~p4Fbd=AH*>mKml8OQs(OIjc#`#Wix`1x0am<*0R3`Sv zO%c`B1Y--UWKdtSC`Xu~Oa|k!${(2LhmtWqu;84vKaA_hDa=wXqBEG>LySb=X1`Pn zu1)@fbA%P=pB|p+7}AHoJH8hYPsn?&&c_EW9apCdaB3ZUOYU@*4?msd>0)PbYt~UB z>d?D&xT6fYX^Qim6gYCJQiRu5AI#+Dy)^Z*F9z!U@zT-{8s@6jEcHd9qaPX^qJQjO z1ap@o&^{*;i_b)0YwZYZ_{I6Eklt_GRJhelL!BR~m={HVaj!49bcbs{MFC9a79ib; z@6GW7`h2>`RPHy{=Q&HGab0Ba*iI69qlc`!!?jSF0|<7XNUEud%gb}H(9 zOv3=LbU3OCa6h2{zunKrfGcD{crO)h%g6I@tpxw0m$GV!Vis~r!ke9xh;H$+>ZuA( z|5c&yLr2s*paQI&@#PouolEG}^9{u}?v;CbhoVIpeY46?Jl??beDeeh?3xIxa*k6T zdVHVA++dC${R6WxBq|#nreq_nCK(L!aqY=|wWNPAaK1vlnQVyX8HKtt9aFp8CCISg z1nJ?Vl^Tv(@oJbPvs#kb``ZzdBIvj3>WC?>DxCl12*&{`EO-_Qmu{g@#?kXv6^d4u zLg9Wo6s!9rpnOUKj=g0*0r$bC921{4;A}EE8&N#Z|CEpo|3Nu)#b;v`d6g4WnT@$X zp=E9WP`VHo|D>t2!L?*8OBHG@na2BC`WYim%Hlthm}Gh5wpR7(Rqz8*2w|caW)?jE9otp0wkkTa)Wn0M0R7=29Nx-*CJPS3{Z+-!WSlf!4t zM4e8Kh`9-B#T$jXCtXrW-A&X3Iws2TQu38_Q$L!TB!M$d$@Ad}vizbF#($jPTi+Qa zd~a-5F;A5Kua50QaXKOt9!<#hI1$d!Q|4q)xkN5W}vMRy)-(`rslk6^VmVw)q z^5<+DNj7(qvRkEc<7bsjbXU;xZi;d{6IhN>z`c(j{?z&4+G&5(X+v)<$Llj3hhFm; zzj#K2%-a#nE8{x;WCW%(iNFm@KI>!nj0dIT@3CYVyK!u^PeRRPmo^x#)kNp57N{CeVt zoG@Sf+tm+26aVux`l0Vw^4^#D{pUrXJNFuWIFHq~j>Lkz2o!Ef!<~RM=1j1!@MbDJ zho)f{-N(Pp$isqg_76p~N8lmZZd0;p?gi-c+)=g$sAS0Dtm+Ry;Go zT2p%V8!9mSyaGw@$)1lgVXqm-F;BTA_mDHXSILzZ3Y==i@p-%{2AP@QV_waA{kB;`Igi z^pe*SSb)i;%nP4cfTRyD;uG0X`hV}tYjP2@EzXkFx|4W+F+o1}&Gwf}aDRje>|U85 zb1u2Yi@vxx#E))OALujKOL5y5Z@Cr<3}EeMas--^8Jw+VUU`Q|6zpLJ^@((Bx|fR0 zWKSb_?_?ZFgL}txJetXQ;w7EFKiFs4J0BYt6`-P70W$w)e`2zYtY!xHqI{KnrPk&5z^QV8D4rp?*4vYO!Jf2zDha)g&X#`pY zl82qZJdc&^UEuzAm}5HnbIs$JkcJMA$-_paq4Wat%75}b*;T+ELiU!F6=3^~0yN5OSbIBS*(@ha^>ae^autR)Tm$EaAk|IQbzagr0UPfAS9hg1eJI(qt~uBp&o%I)984UajrqQ;m-fiP zE-Afk}^}tPJ)0n0FHY!0XU+d-8@+2{HjhFT@iE{oH^X}Jjk5jE9 zy&@{CUE+xMZB^Lo6Ux142)1k1;FD)4yf=hmR@YE0dacLP1MH&NfoB}=)V=LFWQ z+4o5hd94-OnpznV>VzrZIiD|7!u_fvs%k4SYY_Kdbwe>QAe85wp{P;7zAle7_`!KB zkK^&Ug9#XPQI8}tmVG%!kJ&`8@9)`|wun7XoX2i{;d*~hHZF7CICfm2#zCI{b6j3A zPoXYvWTKvHZlX4I)5-Um@p7Vp(V@#c z&(1-4tsLC+q)&4K&(6s+jyX+VB**D{oa4_GkwpzjVy`V3)VKuk=+1tQe-p*iBT;M{ zI-)}!9n7b=k9F*s*|3S|X-e0_~w)AR#(__vFdI(s@uTb&# z#C_MmCcL)L9P}y4#`5``*VmH$?4FIWZMbjZyp>6Qu`S;d)ho`Y*A!~kFADWhC%s6| zL@9caDC-gvB|AG&rr4j73FS&0wsmC2gcC+jb0Wj#1p9i9*xNW1gNKBoAd+h^w@~ao z7>YNXSHFHuK8^BV)IJm$SHT2?hk__Ili^5;jC=YQdT}JmctW0ko_KW-%pe~$xK1v*4z`f#ZOWK8?T(^x;W%8Fg6`xc*UUDPC0|RVfPKOD zF42!xYDAAf=E+8xOYd1FqU=DwnA2Cr7)Gn+Z!wjSs-BMc*U7_r>*GjnAvnFn1gD&~M!F9^fEz4X?-r|-w@fA)J&?RS94V~N-7{qmeQpbBPj2y8ju-ab z2}8wFdMXFx(obP7`%jSvWUg`Z9%0xq#ei!`^g<48Bj*~@Ygx^U=WpTI#rJvVe0uR} z(3?5BNLH46B9Z3;F>_hp8^xU8ITq5oCcTy`=_?$mL9Ha_dXuLc5N0Mt_e-Ql8*-gC z;W(X0|Jn`qBj@p4C!$2EC3~=^H4N>9dEW_nNbS{DW|)*o12yw-FNa|+>-CMl=c083 z3z@f?*$M2!@cP6&ZU^#H+qrMOO`l_WrCh&5e_vG?e21ivRby}S5i^kkr7|l6kJ-H3)>dv^4s6vW%OxJ_@#$2dyGCrKXO~O z&7{xupE933@0-`;;K*}r$j(I@V+(mbw^*!n>}iap*Rnwh;?2l2wrMLa=ZeLNu8MYi zUOw((?e%Id&T6fB=2a=1$V>jm1!sIU(gnlci=O$vU5jNs^V8jaqZ5MMq7-~W*}mqo zF}F;{KIeUVJ{;GM8reUX3)74?GR>)6svjmVHi6vkp%i?I;d7)h7cbsd&B8r#lsw?J zKI8${F{hjU%KeAwIVG<*b9ERBd7rCV<>E$7=6X*e-$xH%@&M)(ml(0zoX@+ok!D-V zq*FU@Its&Zva1ogv3a-I&-CS_V5P5j;D(#hS6XnLKJ*A$2x-!m?R73Zuzs zhULP#cS~7Pi@EL0Uw+8@ZTSxaPMGJR%a5k=y;qqu4D!I~1aicmjo3z?MPX7)`Fm=) zOrr1d)JFOfn;S8#VIGohn9H&EWm2P^2fS=FxWk{T)5lzdwdMWUw@f1AJn^fTo?HX# z^P}^zs<6GdA1IU$Px)N9XwcKdh+E#wufNz%+BPVZvss>Sc|u?3^c0*-BcIr*y;#gC zmOPCY>OKua(R^-H|TS%>NP`|?VG=kN4&uCS7$8ai5RJTU7}IQEUE zCwCS3;t(t8$sF@L9oV=96;rL&q zy>(Pu*&DVUsQc8YQ7@W6sSC7yZd&Sw*WKL>3zcc7-ePsZ3Q2&vCqUf|lDZq#c4}CG zeE0mm^}c_6|9-R9tSK~vGbiVqz4x=P=elJl_ZGgBFQ(TlVW=I79|ps=3%Mk6F1t3D z;rRGi*}K{nC+TI&p)c>_MSA@fl7F#{m#%U4_{bdI;+^Du$lpD1H>1+9I9Wu_CG$Wa za{Us~u{Z-ymz3d?DMkk8*de}C5M)Ur*7l)q%TR`-zA@5nu`M%a$a9f5EVIbOf>82G z%i<)gqCG6n1Yy{YL`M$+;BoO~h&LnIHX82HcI2wK4Ya4GSUr znEg*quJOw&X6u&1f=?IkqS4akL@(_30yPH!~COlgeQE zb-#qf+wrx5s2Z7we$z6c@G8TBRnZb+wnu2kK)Cub2lf*AubK+?$K=TJob0f2XfS*d z$O#(B6_O|VMZaFf3#5vd2(`zQH>)sgJ-vtI$o?)dGgmHJ zrjD`4w)6DXDH1U_I1_~j%@{QLuuPyAvW|5iJa|4ol2;nwU5eP~I7uC9k4FJP=*aUK z?3Ic8f6+I0Cq|qX+2eT^a)RaPdFn~-j66{dQ>;XHae$L=09sDbz>S>4w6{TLIm{zoS6J~HExAzB`; zu*JpfAe?6{e==*{M@(k4UVBJB8ggj*K@HjJ_3`e9% z8wbof9srBUe4m{e@HuDZ^DtJNn73QLbQQ+$(vZL6^?#528oAx!wde;-qqni42K}C9 z!tEV%jn5yJIhAZt`Yniki;2h}Kb!p0jK4mT>ntXRyEcS-dE{Q5=pZ1+y5L7N$7DOa ztU&)Jk8^JpxlV60UR{otUZ?0)tjEuV*TeE&?S#kkl&7%!0j)$;nhS%#X!W5x0;c{i&d zytN?*L*CP8hZzZO(P9~557(N3coUk4ts673I+ota({b{L{OKI>n+{i*i#m*X$0=qk z4Nj23o9u9VLJ)8!5$V;K^V^^dQ~2Cio#TMcVFB#zPsGpB8R+9$2Gv`BUgQ}kw^@a@ z;}Y>DjlRM+%qt%dE7R!pTf_ga0k!ELG|~gBs zI#${rbAT=Vq2~h-JT666%gL_ad zekR~pbOuKDGs7d`u#9Wrh}OK1KE)@{UHu4$x|=cM%wgHwn%7SZpEKRa&AHRdx!H^* zk7A{U!WJza1><)!=7F^)pUC&Ael1q!lY8}j8-Vy)NZy`+rlT_Ojk(*0 zuf#~zQafBY$MfmR`~6o2fWvhgZi*cRq(_cm!k5 z2Mu=f^Bq)$JfOr0X4+$W+h9cAN}%hJykQ;s9G&9i;#7M+7Xz`eNg|r|&%}_`sx=RTzsc-)_b3CrC;W; zU4Pl~dXMG_Lkx|tPSiJA_3Gm7k|_PI^f-N5q=VsQtkQ5f@4Y^ER~y6MxAQNqjyb4r zy{?BrQ8>y_$!)T0rq>Sr(0L(l?-!KQuR7I9Khuz}pV{2`VvUir^`rYIx>cF9PH$VU zwf;EkB8OWgG7mIKCQQ-Ez292N4M~vbjz^@;eb#g6Xgu~!E8~Z;AKk2#hX;?4P0`6G z9kT4^4oR|@jIIP}7qnhUnLIwSC?+C;$E@}qgWT}TEh|Twkc6#106f8-PcK0 zV;O7Z#aEdDQC*ED&D40Cug2IFA*}0$u=k0co>T0r>`pHL>qtg#?m_>}zWm2(IKN_V zD)*#QKB+N{H34H4H54D1J=l~^oiXGcr-agxqef0mHLC4q|LQF@R(g<+e5l4Vr%+fd zW36Qj-(#Q}jV5X_BvFgp`5H9Q|L5M}7;>9V#d>sBaGz)5GP+{N=s3S5=eSCX!fP62 z{iZLv0l)sC!7kQB*06q6(o%~tuH5fFNya&pd)U?JF*vD(;tuOv949-o-u0aO5ZNP` zV_la_B>xT6@%Q%DK&|8b_KEM?UW+XD(02H2glVY}wd>P8O`iP9Nh40%nxNXpI#dB2 zIjn6cV!2;EnjGUF^7!0e{?eR#*=yj}B3QU#{pP~btYVrk-B zDvS1;Wh;C8nzS$dUv}-YjU_UP`9JONDlpAcfsy>aTYv%%LG&{2uz)JnET2A>%E$K# ze7{CM($WG?EK6l@7T=c+xy;SXFk)@`XiYkF6c&i|RbX9n<^=_FZ{F1p-i!Ruw$vMy ztNY=_A|K=*WiGDK4?|CSqgJjDru{?j8=0%Om$>iooO_*IyS)0ytlKJn?D_P=>QWzU zYfjh07GFee_Q$_`pYd1y;MHd&8tDAcZHGVVlY3nF$Oq$k`eC%Y55~+G0jsXeaysLS z`074L-NZa6asWLlL}2r=2s~dDfqBCGfWino4Pw@9p9s8Uy`TkaQN`RBA2}xyKXb$J zBP$#uS4UvAdnB&%b#)u_@44@KJ(+w}qez$rkSpM8$B?ZuvbKF^757BwPa648Bv!jJ zuX-zea=*!KJzy4ZN4ghmBT(`$vx+9BVNF3QGOg2auRb$v3(`>AJ{{PS2D?sasNjPKk6+SY?2-n@_v``N z!9D47WFZ5{V0B~G!n0Hayi7yAKFrz8PD73MbUAKH1$L#;mz@Sv{anCsvg2C`tXDja; zhpp7~ZYFmYDrJVEg#;#$vzTuu@4C3iUC&msts}joRTQXN!hQQ0%nuu87T2K)Je#M$ z*ipPs>RZBGM}gI^%H*z1nG8uX%aSn)^xvewxe5xDRW-}Na%HmVCij$*707es`)vFp z#fDOu=0R?e_gwL5=2V|zwzP!>2IVQRbg5Zl+9;5tHjDm*1srQBkZ(~cH>#QC=O@-b z$R3)wPnYo94~Mt=VI=R9CqsPk;jAxCzGPi&sW+ODJ*nmG`#TZ5mIE_qVRUaIG zPY&cXxtSPW+;C!+dw*Z7jP*f-W_}nG#|-x_{s^c&0$&QrM1J(cQnep0{2=pK$sc|N zeo(gbqbJRmpSeHUwerRL>QQhda~QrS0y#?}aFEyexu+3mefqz9hWE(s2wWj2Tu%{+ zT8U&7?~ont%lyj>=1M?30_a%;yq?pH%P-3 z=Tz)ZNu$Fm4U<2R8{&QUAtMbnFQ$<<;-1=%R4gG2@__eT%ok?Hze+{(>Et9`n7ew9 zj#5=FbiAkLAIZfP?;PgN(Zv8n5;zt4K~Kb!9Gc{ODY5PiIO( z4$7tEpdGp5A8*^*;J~o%Z$El%3h5ea}Vupvpt^Cw^{s>*L>Ef3C_aH=VQF z#e)MI8q$ZnbDI%TC4z(kJ{Xy0Gfjsf+R7yBTUdJlB1Su2g@zK`Z@* zsJa(x|uGs z`5YOIwdFK&C6q2kzIJsJoh)dZD92AHN=;+344RW5wr7&$c4C~28l@2}Gp8?HrhC!j zh`4Z``HdM^-v=g$=2?QA8%dvqU6Q!ybmIJ0Cnfxyw>vtbM-_5~tifFNcHlZu2^mdx zk!$efmz8L5PuE461B@d$XRN1W|D+?1PIbcYt&Yg=VTV`M9r1ahBa$mC5qQ%P9y&*6 z=JD%1N4T*6WfotTbb>jSLse+O-kKj}O4tnM*PK6IZb%Bx^*x#~5 zi=pQ<7*LW3mj@b@+|^=cWi7LuHAow+MGohJU8ivG^}7ZYE@{zg8Z+2B>Yy#t;P6fj z^zK>&?Bo7ll9v4wbWELQHd}oy>IZ9Zsu^=NBl$CJO&GGlgbXjv-QF7EP-4VdfBF=c zaNW&)xJqOdOa7sA+m~F@4il>98*!^KSr^t(3@-G2%wc}?6eH3uw;8-@ewgP^KEOBZf-3#O%h7Ba2*4h%CZuw&uT}k(su@_^x zAI8Nni*hVoSEdM9?}&imJDs;4?3b7s3EQrbNKT+rb}_kYKC9lG=QGQV8ODL>m}^f? z?=*V|t}@$x5jnzVy#GJtV*Fr7I!c@*Ylp2YEq0K)+nAME%~_(`TA=kd3zV!P7iVjU zcM)_CJ}ZYw-O1|B^rgeyAJdkRnGf>EdB+jhG?l;KHWE$8(yiA%5>IWT@Sbz28#`h6e=1tasOhGs~86PqRzh~3=_m;WJ7U@{}B^N%Oa&U`$<@~mEIW6P- zryv(C#<|F-qhwEGoFp&1gJjxvl1V+CndxSU#(||W=QsVzF60`GW^wya4!KACFyfvM zc6s|DgY(t9x$MFDn$JU(A2)i_A15g4d0HD_q>^gc8$q|EFlMbnENC= zmXT!~E3eXXRmgnPOU&k+lOo|{+Ditrrr@fTPAih-zntJ92b>T_=4)^#W_CVOqOMAb zI-}Jvlfh`SR*mnKLQ#8SD6BPV42#fWMJ*lHFVN!hEFIR=)S*^o9q#1O`5HjJ;Dr%0 z$fK=4!hQX_%n(jdxPJ>*xa;X3>_aZ326?%ToXyfoH%&6@ z7b-k_>`2Fe5>uL}uzfS@1s}*h)aBa!lp2HL$(55)i8`Rhtz7#5)@bPpNR_hXEzk?i>y;* zfEDv7|4JY)tdaf=Q^auz$G(3ZvGO~|n0n-8PAf5@K!sZEoLCYm=Q{$^G%#>{Ngl0(<0LHx@pIEJ(PGyC@*fo+ zW4_XaiG|E!xI=d4AlLbed2YzdOjxRLzhG_Q-gT9QdzVcL_bbN}$aHJv(dZN@?Uf|| z9z7~klt(4jTZ!mMCF|qN@aX6acsC6dpSyU^7X1#-f|A1j#uH9S%sn{O59kW!WVze9h4lCHwB~o zEj40av-e;d86KXWBjk0?r_)=h*21$;i}k#YcJS*7tsmnkxuyVmwk&R#(2xAgq(kJK zZqm^fpl~lB57PBIxf${*Co5RESG=K=%d^`{xd5efDppF{3T@=XPX`&SvqVTMORlrc zGA>DhJuelw%jfjr^}gt>;Qc<2TsPMyZ+`kCl+Wkz3-s${b3L5PwRNK?JlY?D`@G)+ zL+G!&mX1X)(lBrb`;DyA5&t6{3*Y79_PIPPo|uOyt`VRAlZzwTJe;$1l&xVZSu@s2 zM)hkgo|8Ju3%#>ghyrIV%K=9%;5CFE#JL<>c}(Av{ZOGi-SsU;Ai1eOet%4GN zpTbdr>x{nkkvM*znF%$b=%=M~Z!Q_MLus&%Psd_DtF7Cl?*FSS;rYewsTyWY%R4wyMFZfH!Oz<97B3l zr7tqij~ps9r@4-LINcvlesMk3m$}zXqR=Fo>l#b0aS9`m$FVh`=_Tyu81ZglI?BqW z=i>bFJlr3Zi!M|0(EKv_!7{G%r`wCg zIY)VVuDuv$x=7<~9b`*=XX#vAD%1N|AXY{0GtLqlZd>AHEZ5K6k2hZML+xFDST}@T zL@oRA-uc0X^_r3|5!hWV5*1j>apt%>#gpqqj$Kx3(=oYYI@}%U`V38HLlt{Fo9AKJ zX!<<)xizATdGBKO3*5@XntBe>+t^;xySA4d&K+cauXbW8>nQhPEzqw^IeNa#Qgx0c zb{(_C%_0l*sKL*QYu{Nj{P5Dn54*?vVS6Ea1rA4|71ylmGFa5MsQS1|n#F<6u zcoUP3;~{C-Gc6s<+H$VJYwG19o)LJIW^V|Ba@#({+;vm(H?wWuTwMkk2TeN zvS?)SS0C5Gw+ZiiUoA4%nb=?W7#k*=;QEq#i6_{*Gv0)q298^GE!=mhEZpBPUtWsM zn6}u$-TA3jel1UuAsk1iStrTo@5wUtXOhf+r$Y7xCAObbB6m6cjEkJ$xK7DDpHMu# z5rP~YS^NO@&+~abp3lc)7q#dXNY63HjV>WN%$`l2`Wt)T?-=oUjtN()nXvH(>$$_p z5Ay3VtI1ZLQ@HmhtGAV2y~rKp^XWf+#{HMa4YZ=E#pBXw#jR(OESZ!dtG_$qZJ-io zE4Rh6I2GAmC#;yn@sxG&({0qKd`u0?Cu%5LgyQ@qHTJe8Q#q02Y3(G`nxn;rC@n%m znL!<7!org#6z?&i{V?{gCmNA>pMCD+^Gwz zZbzVx679&rKHQ{2aw8R%_^MESM+mN_ao=NXDBhIPUrAoq$}$x9-)XUrWBj^}TnqNo zVtO+j+!tvvD&jHsVwn$ql%JI&-NMJ%gZ6>7e;;})ds(>u;e4ZL68jeJDcpCgu=u}z z#`&uo%A{$3cZbnVss1PyXRJQD}gQ+}VdK4JCYD zf$Z(#1&`%nIN6_my=vqKCpD7o(SKynXm4~Z4I}%Rim3_Y96jpFwuVLGJ;)QHVm>dq zHdp&>WL2y$6}1I2euNk1k|$byo*dSPY+PcmcU;pyQt7rg=H3fKMN8(r*3QQ5Z}nx$ zi+nM3^F&4${@z~f2Tsez*^~xS$edYKh$me+JF#Lib6Ux1Zf#UYlw%7-G0qb)Kgdh+ z_#4j8#(;N?WZuC-u{gxs>d9f)&f}@@CJWP?>r3lP1yXQ&I9$tzb4^N4%|9F2#f`=9 zYrcGCUh}b!;pjWkz?5yqE*q9V_*6sL%e?P|)}EMOi}lF<%nk3EgH=ncq;7n%M7?E=m3-Ny zs8n(RIoQFR;w6!P#NR|uU*B;2wob*yjX6kP)kr?l8~D)L2SxqEuyY-Ke>ThkpVdlK zx>C8?kQr6vn|e1&MU^($P`+#|8xI!9UuV3KS3*9~U_jL0S(tOFfy^f-c)1sIlOvg< zy}$sQn_1ZV!%8BG@?~g8Z?xh0{I$b?){nDr&7+ZYK2{{T{@#f8A=mlAfXd_(N7ij4 zo#RVI*V_x%FYtKgvd_988`G@Xh~t$asn7i43YEiA%ZfbU66P<>pcijgiNpjCN9Xu( zEVM|azdjpvuGW&0cEvJ;dnzlK8=l^XzRR2}WGLE5rH8*{5zj+~Tj8v?7?6~mjd1RU z9uF^+q;PNi;}(WnuJkJM_)BIrm77`la(uTZtP>-K{wb+m=9|3`Fh2|teN$0H{&Zrw zx)QmvK$`UBeXXS5&?6OJmE>M8)|NfP^X2>iZ{+j}M{~0QI)4AjH2M~Y|B}J4J#p%D z7<@h(aNHvs|MqMkhsV(q>Pb#El-HXo6&dZakwvLkgkx^D=F*B9o1PbIHzMqZcc}?Y%;~yFG-V*`M!|<#w{hr6NVV+!Dreqe&&80rr z5*3c(r3OT_&VtLk`f~YEf!ML{vUX4I2^Q($!28bSNzCd=B_reLDpF_P2I5a*R zW1Ordv-}@9GtGzjN#R&pV8EN=Y#e@QBgP+PQuQ zNv@JS_`_8A?axM!6;@L7^=~nE^gUl3pZ6r-ukrNUEi1$P*3lBz)&WI5f>30g$ee-E+@<(@u z(;qkJu-x5khr0uUaB5m2j%qSk!zqK?%xL*F*A_O*gHW$l0=l(fKF(M2J5}Q44!wBo z5&{v~AOY{cXJGsIGPvA5B#+zLVV*h&iXqGeCKpz+kNLdxl$9~pI3b34!JhOpE@m(I zrZPO(wO=}ur^})T?L@6a){8UgQZl30@@Vnw$Nc3rL2xDyHGtgKKc`F4z$sqrHrZnK zmHi&xo!_{{S;WlAPmTbPmAh#tc_wy0&ILu#xBcVA@SI{C_xD-X)G&UVO) z3&Jt-P`yTyUvo6$?b=wmk!OpByw)nudoZVGP|B zJU=OXeVw2T+?!{H`JcnmhU@Co{j<;L8hgdE`B#Z;`jXT85VcW8@RPhp)Z`Aael!zsiwSX>UgM;sa7R!~tcF zfrwM`ym=bo>{^B;nge1>f8yk0!Dx3h5$`Oy_wl(5KbS*pqOY)ue;{tPVa?B!ff3{! z+j9-({SvQT(z4r&?PEA|gLfvMzV&vlCx2P@_^PYK4H zd5L&=H3LU@{S@7c7Vo;`J-IfW+?$@kn;95$y$l{Z;>6m<9yjToT*mX0xskji`McX^ zqh&as8^b0B(w?j#3bV)h8WGaQjJdnx zBxtN14)o@AHHO|&zYMHzYsS>{Xla^ahoF5SSUWTk>qcgxOF$VO-ij8{*`xUhX4sIY zsvnqvCw^tHR>nw`2LCVrZq4)H6+*x2cRq*5#z=#Q_E>u}5H-Ct$X-VuZdY=ttKwzX zO$SU|AB0yY60zxW1}@n%-)CW*++R*_%Yy(kcG95H(Mk{g3tOtKInsuJ20!w;$%BP$=T}UTJZ(jtKwwzkmL}U;lr< z|KHF2=LYdf7<}RJh7A4C28nu?fM@!u%^SF`UeZ7xdGxnFEp&MrZ*~QJncJy$_a5enB^142+U5ftpkgFG4e;#l# z$+3-FSu;Dg&8D!6A7-`FpV;}kN9yo1J#Ob;yEsQ>cd>`NjsEcFCHfmD*6Kf8@YO%P zfB9nVR~l*Fjqb!n8oACrWz`>zRAbgg--jZ`t>_KT&#I&`KyX6#n|5 zk)QsFVz6VsdM=$icN63(^PHLtraxyJ_b&P}Ln%im6{8cRULBom|E!atAGK1rOhYFM z*U}Ej@@89{Y-HYGyMgSXyv23CE!Lma8zDHTuM5N-Sq@zh?_2_CK|Q(-8-FZB$~9H?yZ|(BIhGk#1cj)E1#AdeXdsAjI08UZ)CAI&=U zoNjb0@@FHs|9!P$_o^|=TCo~)e$(-DCIkanlRw^q z8A@--LE5O%pf|IVxIfTvjRuL$wVY#f&mfZf&K+2zchkb3?DJpi=*?mMKJ+)Ur?}^w zpU6KS&|q~k^D~^ZDEP_zr{`Lv?&7`!T{?^3()s8|HnFZ2+f8H^`|9xiTO!6S=4&jq zn6q1h<=$F!jHBb=o(B2c*G`CM_62`F-eiRTaU<$=V!h{!5jDmeG1c=iirtO49B)J+ z>vcJ`+2_mWa?S=LwCuAzmcgD2*6d$QVf~{5dz6cf2x1*=2VZ}oG!svQjj%WH>xcCD zOy&M`O?ofFS>tywq3Lnf_?yzllf@d~HzTs!nK1vf34NC_0xSMD%iO^V)bCg<2W`vb zf!YFnR0>S)XO_(`6u9hffm@wf<{--{zxm~dtKw&x~(5pobW;Y{(jhchTg`l^g|BxB`e{J zZcCY|`-;3&7&E7jFrW5V6mHy)z%w1!`!10PxJRerzu_pyn)E{Mv$V*Gz>5g-R^+M1 zkss)Pii}m=DEO2ozqlY0lm3asqAkpouEqUW{@wi-5$L)(0&^QO-_VV2IX~uACq*Ee z`^B~fW(-#1*O3uez`9to8j2h9s1uErLhMq4UfrPE#}_ywwnC@`!pQ9%l@&^tbO%P!-A1% zSZ7W{gVAZo=u1v=3*Xm7zJMI$HnNUOwx%P1zi-4q*8Q7sKVnHbx(?38qyxFASwENg z>U74<$VCY2bQ_~`(RDAgr!#Z$;Rk(iabzRf=AzbD=1DckMN9VNE-21HR=+&#&ZAq1 z%;VTS^fCJ80x@|QSIX?$TDfREA`gR8n4xP&&ha~cS3EN(9P*H~joA%8%r)$g$MeqI z-SfF9&d!Bv7p2^Ebdc=lEoGG2Q9gS)%GtWD<@!rUY59*zdNgp5WG{Q^H_=|k|7$B# zD>#W?D`zFa95_v%uSS(~;B+=;iu_KBrZeqWg+ zy)Tn%+x+oQtRFtuli|%|E|-lzCLZ@CALWY*9zJ+;gr1bMe%R#8%=UG@$T~=0<0L;6 z@g8c%`=x4aAFMpZER;ijXwlgh5vhK>2mF`|;g2<7p663vRC1y>^{p>64|pH-^+6Y% zKl5bych#6Zy2l3}+WW)G&ktq1KevQMqO=Y3Bgq^F^e1P-n!yVl8RDw+SX3t4Q7IBF z^TJ`%i4LZB5%^g}?@n;>^G|4t+#W^vD~1@p~1&>yuh0%o!fhko(CdcA6=6@nkJtzX&2jQ5&pQ&K9R;m@U^TN7rw2c;sqe;TI#NX6lw^gd2bC##T-4fp6z(J&XD_ng@- z9i_)oVNPaGDetisM{{v3qFgW4anO+`Hp@ zC9mQ=7o3Y(3vzMkI{7Bva|x^RFuUi?i`80p(I2Wt48}EGU#C}?zVhrkh7Z%1UT9w| zJ@#f*GF+`TuE&*uUT$lKbTq846n(K{(UKl*QY#v2sM_d172k9_KBv?zvD#hz%2hk{ zTd&`|FsC58hi}gI9*^@P^n-Wr(|5SH|6*motcxx;OWdYTd*b%COsW6U@7jflE$bQ@ zc~moWm!WRWn{U=HZ=*Eas+uCYjq$R=I#E7lB+Ay=NpfROl9V?j%E_5pIrp93#q7S{Uzlzu!vn5$R_18%1NS!>Ws1tW)ZcYkI zkaQod)NQPhG1chk-mZ}YNeObtm-!FOrgoe_M$)8_c=pR|7^jiA2i%(?UlBT7g)(2I8%x4Ax^O3_mfQy99tcc`I`(R=afrR z9WgLdiGTl6qCqmf-Xm0a|CCv6-=f8?W&}U-^E^tmbo=%b>E}?klqQ=O(tXXir*Y6}f zQqJTZZiZm!cQsUgYWNJK3u6znr^D3f>q}1YF8}*26w`Wg&iI)eBVFD02Sedef%Czx zOoi57p6L#(1DZ!(>pFYa%eIJc|Bz0QO;TJ~bo<(5{ zLVCRC`n9$eO>{c!K1*MSk^cQ>iI`u=_1^^zCUDMp@wyhLJhe!_ZA3BmN9zO_aksY# z6W-CMm`w(edvSfw8u9uF-Q07H%p{<9n``}`d?O0#8gb8-Zbj~6Rv5)SRpzSQ-e$xb zGLU1Nk@q-igxQ6Ack_%`xP5p;kU(P#IIF}4G z;WWSgKYm8{*7PL3c9HsvouwIhhcVmROHcN|#ND!hnbg~XL{oq>UhZ}Fm>G8Q<#`(`b3nGv} zUd4YVdA(R>h2A9>H#Qvy$T{G7Iz3y=q$FQ3HkR{?{mfBrz#K^DFF2FVylMKaaI3W> zcC?cWR|m1QR7&+DO6kmVF|%GdbXaH!H%&Q=sHH$pIwSqg^LKN8XFu7W`{DjLm*b1Q zP5fZ}jBI=k^S2G*XvHz6wqqp5{fWd9KD!Inr^99(`#N5yq3(%GIP-$M0p~Tgc6sQO zl#4G7zu>$DeOLW*(YLcomRWX`bNco&(z>(!ZqQD;RPP{T_R`&S#uC>TlR3StfO}jy z1o1P>twTrT79Nk8{WcBB`_oT0vYRia4~c@q=_sVmqI;0@#)(Drf>$SVsZGWC8R@8z zNIyUV8H}#!h^$S_?oZ&^LW&M;jUMjzuwT-yvY)nM+exD5op=aA4B*0VMh*~WDR`rZ5ugDj;DJoMWJam z@`InrdKQp9-4KZb>GYu$@-zF9MmIn6UWcb6#qtt1JCm0WCvQrZR9?R?sGg9E-%Gz> z$8Z-}-?_cqOJ^pyvz^?o(?N`XJ2P9vl6eM}SU$;;S@LG-!hVmv{VieIIs)+r$%BBs zN}S)%cK_@?dlkSx!;7H}z7u59&nM-W`SeH0CKE*p?u(=oNlgQ7fOb z5+#!3RWEw3;wz{yV6qb~vo^5HN`;gqtPkWnVo4!6#&K%29M3)dL*(OTsu4IM6odGD zTuh5Hn; zjlnxvbBbj@u0BO(wMvrX*7P^MV=re?vaJ4*B6rE9?8{f7z?E#}da@xul(0-tp~tmQ z1XNqi-exsw^-?3-i5|kfJe~ns_=RZ^ypJB1&(eff$l=);F$T<}7yeuL|=$}j9-@Rl>8qUm6W^L4TN|wV5lO$o*QAy~c!oufH zz#1pa?L*FiUq}8@VR5n=?W=^MOQTTkgR;gkS&cM~YvVaa+z8fU>mLoyd}YQe8H@@? zS)fA%yEAUOz|KKfvSJ zJU|D#D>_W>qr=B(bfxVlPqdVLW8cT{wlksZ0~z@fk2&T)M&k0v$oubH)U$A(N*3hZ zS>~F?lOsG##__98{<(Hsnv>i4;jEK{{3O{KeUx4!6+Ro-2kWQAiO-ya3{oM;h3BVJ zD6Uo}2TKNapHYpC9K)-8QDXx?r-*g*Gv<;{xvF7ZihQhv4l8**dy5f|>zVMI+^64r zo~H>$_TMnSv`pdN;+MkxQxyyMtGg`RT~?D3ncyT%3!4eU)}_+;4iY@Mvjp(Zm&PdY z*=UJI6%^?3tW-uHDV4Dv7RY-t0w=Gs*KoN%x;OS`pAy}!<-v_IMvY) zK{I@Ct0H-7-zc==aqL`ArZJyAQ%mR|w2DG#ch2?uUBasfK6i$(@2O8ZOgrgnyv6nI zw;c37L3dFQ$JG_&<@D^~JEr8^l3wB7oh0>uQofJq$c#@H=}V@2{W1#->&!8Ax+PX^ zwtzmx0*74uaqJU&%A%Ob&9T1!NFLMX|HgdsajzobcR2#~C&Teq>quyH`3 zz1@j))uyDQ!tQjmT9JlXGuaPyJ{P{H^Du(z24}9_$Gy+PfjRAD`J>LVqI`RCWgV(! zlMYhphLe0Nv_Qnja`-TqPUvcUR=Zf@%u);7IOm7nb^Q>W?~8X&*b5rxi-{}zvFhJQ z^!-EMJ;(R&!z1BoABk#Nk>muJ!~HfD?{w)n6L$%RGwIiKWB#-Ue|J~*EZC5*teb}~ zTj-kqn1}DDT;zhUgM8ZHA`$28<=^{ubP=_c=-!s78exflmX?W*Ec~{oJXcqlLA}@) zJumZ|Oz^{e_Nnff$2II7e<(TMaA+Qd@|ICJaUlu^J~HcqYr};{(x4{;>z$pBa{PC| z>vVi&KKR9NdAMCE4>P;vL3JY!A2_BSXp)DcUtHzq)vnS;<08Z8%)ZvQGkYJM+lO;+ASu)$o5+j30U|RuFQKIuXC)gy@gGdg|rJfRlwyW6t9SR#h4+kZL;)|Xh zyNl%Y`26{LNrTGQIA+zqb2BuyBue zv~V94p>Y41NskSmg)=#pNqUM@+Mc)M`XaV6tSqRlj-M`c>h%e+g3`{2YUlj zxi)&G#Pss3ak5m6!)?hjZe_1P5_{vftMNDI{#I+~U2mhqRX5gm?X|4oks-Wd#FVin zJgfH@Kc~{|TjL46j&uz3S=gQXBposo?iN$Y;X7HluXVO?-|{O-#@y1#PWPi?`6*dW zFVadzL!De_esS{@XZ+?f@Zn-54qjGbt%ag9=*>z&2_^=fg9pTR!* zv0A(vuEp$R_SoyRII@g2=XNHv8E3+-2JA;75-rt;5>;T8v+>!$xZzre7t`$nky>*Dbn0BaU1D=Za_FMD53T z_TEVEmBPJcbNU7wS-8huRk+_G1K*^Zg}dfOqQu-wktKiVVV;*LzdP#0snsz_AL4|0 zwN=O)r^3WLTtn7%M$UC5a(<|hurw6y--lq5Qz&Z^YRnz|-+E7ndQ(}a=Q*l%TML)@ z{OpG7aK=d1bJSzh=X&UY?-P{DW1O$Waf8P(*3-hh&vH6F*{{%z=P7QE!aZy0F>&xu zk<;apWdPmF$L6y~@LRI@XjK^ZTZMN+x!xVCL~)W66gO0uo2F*}SSVcUgrdgnP>idl z#-tdIu>tH~`^hyQ+1xezxDP=`WA`8}`p1~?Ws(V-uCYJO?lEexcE5YbW4Qiz{nWN_ zKS{>&1dnGmujer4h5w&**uN>w<*!2pVn1g%>zVYRsZ(*g7P+nI)^e*6xg-~IRUgBk z%cQ4F$=+-4`qHn?PpK9@4DAPm zd?T4Twpa=p3`hFRaEu>mz|Ak&khM)EyB>Xu#q8y8!9KV(sVEF#9<&8>u|E}xCfyq~ zJekMZj`<_+v(fFol?-L>^Y40IsB<$6eFDh4k&E2%t(8Q5FOp-EhGXB>Fr?KZcbS)s zO@B9%6NW-5EE&{0ue66zF6;A*~qdvaS-QpsIs!+AhcQ4KDZkG3LDx9pyvAQ*r_dW8Z>yF{f5ZH;pV+J(pNk3-gCi0=QNZj9& zr)$T3huQ`#=I7FJWPKTOyF^Ztdwtm?9G|`#kn<%AwZ>UXOXeEe4Ddw?`OWb!4RGLj zuIy+pwcF>*+bB=;aSlUulK~msv$67IBk^Fq?a6YU=szS369=Xtyh;uQ#&6jX zOE2E)aEv9lHDFjauJ36fxKt=V?Yz*F*I{FRj+1yi>z7%}(>mn5%*-QZj`K@va%Y># zk#%S!!SsYy>gWSK_e#p`(_?o`7Ai2W*=}=@Pu^6fC@2c;stCHdBE4P{G4p|r>z zj(~nU(YSmnt{HRCrL2yOr_Z!isTU?6*@>G!=;d6`T;MM)rCDaaT=Aec^AWv`7Y*>g zn+^XhO{MTcf!z7m3l4GNa6V^XO*$KEbDPLpk9@h^$_KB1@;vI(zHVqLt+o}5U5qEH@i@;1rlNf><`kc6EKQsWrTtAW)MXuIN^@rM z(900psG&6ZQ!J68p0Hs3`1YbySj5w_nb%M{IhILsS08-i^*ri3pAQenOXf6|dyjsL zRdf1DJ;E_S=#Jo=%)!@Mg4X?!ZN0qU{grv>O7g|mvXR@xUV2y;$i1@R^jU}DuuUp% zYP0BbZY(XY7s=UnURbK-=e0?Xi7&ITfjPy&UH-_HRi0?_kk@mn0j1yuN(c02eT15sg^Wz zD3*X*p7=3<-hyogWX;Y(Zo4|tdRl>eF7igylW-g)|9jIt8`>|{GGNXhdA`dV19|^8 zqu26q3v!e_n~1mSk1U)%9K*B2V0>?Y_t9+ZbZsbw?+e5+dKl`A3WHTdDmwS0XLCg} znYyb`O7_#+=*|6t3e4$#n~h(c8cS-OBI&f4|6gTc7+O0O{#Ja>RI4YJ)`gPt$`_~J zhojyTa)RUmcXF?^#JflujPpX}Zea-JUfF2B98_|wFRyZoWCMBdasfNxFd-E+{>s7P zO7&z_UV-fQ9*%9~Pmid{P4}UHb6`F3qZe}bm|@t*>-Kdm-tXjRtDLPbb67Zk_s0v? z?{{KYq5;9_*%^99z!)1da=JW?0M34f)c6&rjzW^k!byW0_Aj z;zqU-OOFCM|IG^r$%79GVGdN=9Ncz}m5$_M+$>kYbR`jyu9=A6Xhw^_4@$*$wj3wv zFQdoseF5v6HOMFSjFIX49PnaW5Z2byVBR14-QJa9$If`k^RQ(WkQ%>|>1V7-Z`xyW zOo{YuwYJCjhe7D!L&wll@@4jB{Cs{;f^+N<8OyAny$J~B_ZJT#2iGlLzE0-x&luR^zMP6yhAxS!KkIqJV1}`UKa%cvir9Uw(M!LclA0-4P8}c>p z>19hZ<3jy-xzD`jYR>|>eoDkwzW>DUX1vLdmjm-{@&Ax^7G6>3Vf&uJT6gUh!6pYp z6kGJU$68w&ySqE6!R`VE1C|6sF>@LDw3qWw@_Tlo{ki4z~?M;EN=r^7TvqErVX-rJ0{2Dl!MTl zV`bVKdu&-vF3&)(nU-s~MhbOOw|!Fols!iKEkom9^d$DnLD+9{m;C##Bo8>c6M3i@ z9loB*M&8{rRM5mqt()ZalIXdsOg_Rc8wpm->28uBzkk_dxmO6LO{aftZ#MSUSE&2G zKPUy(_ITAf2=z0QpeAqVS6!hVKwshY(e^M8T!vHR>Ds+zAAeVR-y##`T$UX&9xub+ zV|0jFpN%(8WoXtpUebN+G3$OXd3YVF9VO5BnEuW7^ccQyU|lPWxet28yvc^um@+I$ z+AoJzIbjF6lJgt%n6f+@k;*bewoZ`igPc%ZyA1vEnX9{!{zqP)=Jn&G^xu}a!@Tcy z8<;D-IR|pI4DPk!Oz9L%_Fsp7OR|v^WkJmBJ(5<~0&i=DVEb#<0qk?Qr}~Y$ z^jGfc?|`sqa-d6eaM+py|I=mI`XoV~k+?i1g~4@5qvraCu&>Zu{lu&`8c4#j$oX=O}}9a=8Q&@ zGyNGWarO>~KgQ36_d}~2&Hp>UXX*Kf6{BY zV84{su*ces!I*tI2{St6U}ih!iPw&kzNPl?_6b4lx6Gs0-$l8RkL|N{=M3|BgcmvX~s`G4gt2PBRDDHV2pa`Sx*5kiKxhGiHr#`Kg25@*J#P$1}vE z2@<-_30KAkV_9>4AIE3o_Db@Yar7sSvBv`I5KIZwVcRb9cS#)gw#G>e`QN<$p*XgW z_gi23WXI6&nZf*S^004rg&?+wyrc&`mE`Y!(T|zG$euYr^laYJF$;_wcSae;rYA^g zO()!*K#rR}%AMKt&-z*Lcvyn8IOKqy{{$nl4*Afh*|?$M_px8RyxD7q;UPnF~+v=Pu?)PZ|@9+I;?KO*R_yI$S)qU#3LRBY7$WHA{J)JR%3}P=?$gd!l7~`Tb&T73c;U6N%-xa%B+cdp&Hf`N9&!jn$?%cXd z#xQ0lN;i2fs#7&R$W(B;MeRR4O_gV)CGUy! z)W+UVoAfO(J@cPGGrUjVKU1!Ut*1Qhnbvbby^NCMjnkJlYLhW3r9;L)4%IUj{%Fw6 zII%%S3)#?hSHCOijoBSf{O{_n*r8ToSQkF`l{0pCVzzWY7mVwv!kHwxcDk~*{lXd5J2}xY?t%fAnEx=H zeB=s8yoz>4hq25tEOy4p&0+X(nzsS%E->O4Q0qrvOj8bqcsTe>-YK1((DJ~bT6gEZ*7 zITU)<#*fTo4X2?7k9+eh{&E;Sw9KB^5sF(n4fI1a%sFHJL~YipYa5~IM*s0+J+85~ z9J7!4e(c*E&d2@wu?LsuRSowu7kU}_#kB^!U&RcKd3wy@xzU`PdQ5mj2H2VX059l( z{)_#(>`C1)lQoDz?2&E9dQG^V{Ffg4HX6~1^I)=x=k9d)yy5E~=6O$bvchWy^S!WU zvj1uxE|#Y&qaO31hv#C`G&A(9Rkw9ElgFb==QSC}?L6m5w(OMn@t z{-%R*Yc2{)bFsd&8I9iNB8UHds)!DUES?{o$icQu=1MDa;jg3Dhwh#1Xu60`neljH zE;ie+R{k$tKWACX;+nA$&-o8sY9;gTxJq(&l^odQCTV@i9eTUVOIKI1@8v8vqEu4p zva57>-bR$Qon=UpqclrzCij{;N+tG%H+|tQ*=ro6`m+|&a47Q|_?$k>kshyaB^?#6 zlEkb#yDrV-gV9dXA300A(QXnq-bG#qIf-wsi!8LXkc*32Nl5dSa{e~YU~4Mq-?K=w zNCiH_y#&f=Kn(U8DPw69YBA=M!gB&HDioX7+w$Tr*9{EB& zCIE5s{V^tRhpJPqFR)m;`x>#3jOQybq0_%aMYsGQ!-c8wNQT4qH$YhTR)CO*TYdzZf6a7 zJUvFuv(RHVxkc99qxaJ_;AVpTdh%4Gv*5>C#Vw6 z9N&_OH8;p7`t!f5)2p-4ghMTv^SG28SCR=&K4jw0H<>8&&&1~<`WV-;Hqtr^4>cyl z@^vqgeenC03F~hrOgdDEORbCGF{2RUbLiw*Uxf6Yto0`sVakC*6nPXP=QjV%x_|tp zLX25jg#GJ^@Ng`%5xAgR6Mc?5S)Yz8#P^eY&QE%zYSKwJ$xf8Rn@gR8Z6uHx(bK*;O58nn zxgXL>(p9ZwL{%3#Q>~>0@O!ZMLo3;HjIN-Q&1F05CW8k#iBo@Ok>#`zYezaEKDCl< z9~(=ZSe4{FQpudYtz-zZ;aAVJ<@e4(c4axs0l3PAJMPk=eKS!STS;DugY-M(C|9Q2 zlY_UDj#12RXO`j`I|VAQP~sSCRJRW+(9>IqRc;C_^(m8m-T3_)O&{uKdK?E?WboTE zxs|L$n+FO+t)ye>x)MpR6i9AZCMz5M7Arsc8^0@f#!1K0ae7eam5C#n<8>o`%UWyZ zrZp&&F$W|Jd$OK>V z#hX2>*|_>+&s$&ok?VsM<9w0Pi1jySxsR>jM^45Mmc_m}3qOtp{-|@&A78d>nI#kj zZKxKV&yd$8@4NMnDEvXrrB5d`gCyUZ{p9zm_+2cKheB&B^4=-dO?3M{V zv+3h_$uqMRtjk*QyLa7$>oIhb71QT9&jg2B?@?BPd2o^BRMr;YXc03l?vd*?7vd4W zI}%Coy$j7jr zd4v8eGQ}VI(67oftlF%ZZSW=+(}Nr`pS$Q{0sd%Gh(p^75i-3HA4%`kuTT2NX`MXXZj4F~Ze0G% zy{I4QKY!FuKT+4@`S#QPv~#)LGul*-Pv1PxJ-x>VH$MH+ntB;M zG*8lWWo2nIVs>^7ja}tgf1^3ASzza`4Hu-R%?a3>t{zlBGsGV170V~TF+Ez(aRt~)f2_(GW%V28s+rMWQm=g zBIUm8MeUa?hl1m!+p9#`O#r545TMeA2(4noS zi|IPoiaG34IYl>9P#A(;>F>5^P>JU~^@BAS$j8+WSkv>+;CzY(5xyF18_ilD|J(y( z7^ZpC?|p;$lze=%V;J;v=mb}3FeRLSW{C#a#x*DFU9(yD>c!rd^mn0%;kwb7WI)5= z20Flva37<`KfPHSByUriLMG9}02AGbed7(N%XQ=uHS3udm|<4Mh((jgov?oQZoQuF zSOXU4F`t?YQ7@j+=@%RD(8_=MJ8`oz_M0})pi!C`qK)l3)q`+%NJ#L>9(Fb6fPM7SVa~?*FlSRN28FoCmP#V zkR4||{VaKhU2@!76Ta}*Rrf3;#L$fx%Q5!PBFvpx zglUWE{flJ&)#pNlbA0R9+Ere5RY_D!dr?_bvhIZJnft};_OuuL{C zw1N+v$9w-CiqMbb>^BC$Ei?e-y!3k4hH)@FXMixd20EGNVghi1M?^h&vadae|BZ&1x;}t=;7012;); z>n0uQxJ#iZ(f*P}EFTqUmi}8}+!dI5murD^=7v`CL*Z4fXUXrhS;L-yL%t}C=5@&@ z-(VMwYc;ee?x@ACN96E3(D(H<3;nl{ci3!V-b5B!k}3T9qW}%Ja-7eggUrPDMg}8) zbrGs`bd$#RZRIa5*EJ>XQX#XAB(H5HFZi>2%~8PXDZQTKmDuB44pyQ-!>i0z?dFdr zpM0^kM<8o@WQmG>QBo}mmAS?p+mAWZoL}$y&=(o0MXfj!{JH+y*UE$r%gN#wWHBd_ z@25u*Z1ak+@J%6hkWX33dCO)mdrr!Ckg43aL>y@+3a{2OYEf&M)!aemS*$Sni4_hH zw1~@0CB{s&;vCF=s0qH9Rx1!oSNY@Us6f;?$lfBZ<7--xeWhn+<)7?*$kXE84J|&l zB5OJN97c_#ugy6NOJU;mrE_aH=TvuoJ{QTs+83egcdk?S7om}*05932sN86j4rlbz zps7*rc^Re62!rIl;g~#$+{Ivy-wrPLyMrqhZ*oO$C%O;!YG7VTR_~eyH*PTtVO%(J zZs@V%8Chzrk$E`G>YQwV`#1yax{!yfWk%8ix?hj5&yB9VmF4p=;{{p0L^6#j^fGD` z>h%klUEEZuzW1*|emqW=f5_EeT$ds#j}0>Syiw+>UGX<-`cI=&aIkU0^uexhGxI#* zY&c%;ryt2c7vfd&abDr@-WHDI)&{&i$~**Lx^GX=Jy@3<#%nSdwR0h@@({fwmuu`? zytrwGe-htgyh6Q^4B>I|db5@&)Tvv@V-(O+6p<|1t8`MxZ0Erhlck7#1HFf*h+{=p zsLAJtG*e+J*}-`RC!~>W{84#12F+z|aeXo%tHO}%%Ih;qgVr3ozgZjcme*zZSOcmp zW_IymBX-5HXE2%L;cPPwH0FMMEnTyuSU0eC7T;{28K9e@j)U z*O46@{ga;+^PUHh3>jW+LI%!Zj|cLDr_W6v}>LUaaOHx*qgnn z*3K|i)nLJ=FgW}syVEKh3pt1O{>J{$FU-ZPWWc$<$)WyZz@=M8^vE5KdQH7^a45FjgH7!&428CuwkUHnYLI^7HaA zqVYS6Cx^eCb0g=;0INJW%*@5$2h1?-qfi&}J&Yc&RD1PNs=qEG z+xWsklJ2=k*)tEh@PYfMbI!7NLMyqsNrBBvEwX5*57W8+bYpiLw@j_ANEZ1$9|qCWR%fWOBVi0RWgjxT6`X=g}l?EgyT`HP795T z3CB2JG;pmw#x1V4uz2XLX6x8e z4kq(i%=h&#-GkQ@SWV7+)KLXij{YSclgPgp(Gz*p2g&p=zpUhs=6iUy!S{ANBMP3} zBVFbBgKxMNy~;;pPHr^b-!|diMY4<|xz}jH-o*&=@8#*wy-wz1P$7DBDuUh4LUjIG zh#OVt^YwO;xB0E)LLZ(xy>OD4*>3Wl4$FU|c_wt8`^(DZFmSdK+8YYo%2S{R=ZHz( z{?Kauaqhb>>L8vAJUxy^g0J@Q-w|QRjR}Al?ZdnNF$8(T(?2WW4!tq4rV3UI#bEgPS;T;H zW6sDC`XaeE4LuNzFM2IrHPXUoC42RF&qU0~f&;J3kv>_7=UL7*NA4$wa6a$L^$xjw zciZ={_GiXLGp;)d^wM~cUb+rTmb|!R`9*hpHob_idA95^!3oO0nB&9m`H}UmxW=>N zmy0#XGlXLS$7i?E%;;4v$0^oWU+mGN{Cv(6K}PgDX22)1gkvJ<`#Wj=AEt577c=Hv zx6SQh6Br1F|?4W+uy? zb}qPAM}>A87qnl^^KM7-gPcFwP6(${T!T6nG}wMfgNYo2diLU3Gv|qedF1c8-fvJq zzxrGw3fj^!%=6gme&ngAu!o4_P6zgeFYA_v;#&&!xMYQTWqqaEhg|+hqe8ubu11@7 z$@0B{PPXZjW)a3v&?hapXG*!jp-d6<%B*}R4`v;A6Y7Wx-XeY6v(|z2;IvE z*pqcugXI&$nbBfI%Zqfov&KH&$%wtqMue6#qQNaCFqb**FM;5i;fFExmB9fOQzJwx})AeCCDN~aLcV>eaU{*)O{+%tyd zIb*q-6D~hyFWmVsCUVZ`Vnppk?u)pW z7`4TW)qTwPS<#FuOY?BJh-cXc73wQ=FSq-uP-l?E|G^%Cf5?08;J&!7q{^EEsWSDr zLF#`uicxKpL@PID1*;HRk8`^}dj+n#;M59dxPGFqz#N8sye>bggroI5UaJ5)`@7RG zFp{5FeKPs83~0mmc8q&Cs}M6n+2=LcHxHYV+0$=x4H+ z)H~>n9MG74>Y7L7-ySJ4gKp{<_YAVEhd~^UvX^9|3QM@pjph4VGR76j)5z$u_Aqx0 z9gS_nQEnYwqo=w5e8#=*O1d-;v0rTu``+&JTAkIS;spa1@n>g7(f`~f5BFcvt!c-- z+h?wU4znMC>z%50N;P=zRQbivj;!wg@{Biz)Rp4mVwu?A2WzH9Ag?=fPRS*yTpCN= zy+7o{8gCpw5s3nFI*J9%r7hn`@@oH(!v=4j{YT>bbu!#j^6`WDzb~`C%TYb^l7)JmWg%$;LF1 z{gaAi@IY^z7+WxhbVtOj)wfDwN@^MRV@;dwFqsg5H zvU6;)DDHcq6FJR7zR#VR%u)TPg|u}0DZ^X%AZ-Bm15ugqAdFG<$!_$QW-VHHk#&AbS1CCHXuh zcX_)+p3R}>@o@xd&CNtgy#n;EXCumz5}8}k8<9agdpwzeitF=%#x^pf_Ybk$@!?qt zy_}{D4CREKiF>Crbuy{gV%+Rb$ZxluAk!Z^ZaT!lPU!%*Ws1&TAVvki(xl$qQr2 z!`i;)&%N^wP50Q!qFKLWUa1deB}Jl`??31=dBZR}c}TzB^jkiNJIP#v!{lnoqbY`4 zOYG;b61UbHZKg#c_*f=xHY`A$qc-xHYY@j;zG#yi37@ibJgdy!>Ke8(bxf%YXa4fv zDH0Yz-?}%IOWEIL>R9GhFNws)D)d@bEI{=Q4J0+V z;KlI>e2UG$$f^bSGQn9MG8cFYbAE%gk#N1APLF>+(qSWGTNg{8j3H!0BN3v_K+~W3 zIDVk69J%&Qip<_*W&>5Z!7<_?jI9Q)}V&i=5GTR-TF z%wkTuE&`b$B8RO@2#7g%A7Bn16jd1DoEy!;1X+V!f6Z^-rmv>Wz2gVe`pB z-#d|y)1i$daNZ9Y_Ft|vum6~s4D{i+^z~?Cd3A>O=Yb)pus;%caT)k=;w`ogu$B2P zKV?I6Z#49afP1%0wEV=p_;(HIY5gVloqXs$jfC&AOf-sPX3+KqvcB&! zUw?Z_J{&f;l(_rFlK;{NgA*dLnH;MPYe*j_w-oI=j!TWn4;Dp`P2xHHD2|_2Hc~CN zL}q^D`;3U-oRxtW!}BqEwvE(nUM9oIGnQ3hU7~{t?b|XV%-2D_{>Lvr_lC(7iJUf> z*jlRq;R_l_kT?0$aPr7k$v^JT#4O%#-!|8hUX{Lz>W~j=b3AEOmVqx1^HIB+wWRPq z={bq>MOp-Q-(s$PdAbHBG?i*COC*NA(X>~QIIQB|_dETtXeo-sA9C@X4-~x52h7bt zr3~Jms+Q86j+k$Y$zA3~U@pf2W1j*z7bVCc=9$*W4u*OgeQJMYv)_lgx?Sisb8*De zJ;7+QREJw`wsh zEb!c#AcN_5J2aJkuA$^#_UE8hj6$vKx?g7bJ7C#1`Vi?29CtSd-Ye*Xi%F1Cp)GM} z^fEl@s>7?}IdEuJhFJ?^rF}TPW_BS+U(dX0U*?~VWPeKHehHZ6h)>x;STse4CE@f8 zRg>9JMgC`^mOAp!%5*bgQI8C7$P`9i(q@<6b#9#{m<`F-_rGzLXrF?phfJlN&1AN1tZL zAo%{FNBei#PzPFYa$}MVGuffSh!8YUk}I5_jgD?*nEd{LZ1%9n@S!1yNY=slF&jNx z6zcIO_e%xxiD$2p{pg~{Xn*DxIWbqdFhL%5cR+AN7)sxe<0Efqe9QN*PLM144rJ;> zu)&;!;R|!{p6_$i-gtTEX%G7}=5CX7T-`1Q`)e!Ifo_QsSY`+9giv~Sm{aVZgK^8s z&~`f68}4JqnL_buwjP7Wt z;Kc{z<3b1Y_X&bpOTS@M4g#8Tk5M~GY{og^@cB^8IzmrhbNT`Ed7b<2lPBvOu?@`a zO;19#V>~B$UxvD!m?!?3dDir4E*`?yX~X-3Je{E=PEL6`V%&}pblJ@J$(n+?J@4ld zdJ^B+WBct8I4N~dUC&091`74i6rBtlWsiQNgYoYt=5(iLw z@8t7c$rmrQps!bTCgS{ zLAEz?f|nu$Z$gsbv6Mc_Ze(dKa!-B;*`{XhCyCbWDq5qx)`#QN;K7m{wy@&gATjJj(%V1A0>g^xd=xj%CpkJKK zuIa?Q`4E&f(?NMK8!p!^n0G2x!d>ad^bSHd)^;Ax$;O0jWy~BqC@tW?wM{5CzhsVc zZ|2C;qk1~!fb_a;Pai-KYTae7eShBP{VlAM@jfAk+p$du{^H;3UAG+6_{Dti0Oq6* zc0kthAo#4%p|FfO>`5Fq?$9&4fd1BTp{U1kV--D;706fiTN5uUoE+%f2|=G8I(RMS zI1uw2clO4KO6!0j`e6KXhq>YBauCmPsm9CwlAFN4S1F#}@jp2X}Lvp_KW`0~43Ujdzjn|O-Uc%gY zMS|Qe;QdT~wgInyx&8F#`dIM0Z@esE_S~7vq4?gCq3nQa=Ur9S$a?s4@{`k?zCJk$C_q)(uOF(WiGJ;*jXt&w}vjN%W~Gs=DG zl-}7VFMWQmkS@88)fujFo@u*k%&C$z6#}wH>7vqZRDbkZ(pDSyOQsKE?+Eg=0y}BvV*~=iC z59*{*d-KgWSl~$u8B;Be*jvQ2>ohWs zD%P%@RIvAS!huOnIMtN(hj3yY2RVOrHUApRO zX9QMq!s6ZZFp`aIT$Sfhjhs>OxC)LBoY0y-|1;0<>l}54^%2%Mk~MhIJPcdn!*DlW zgI(uXL+}X0gko~=cf)XVDEIm98cg#DhlMrhkJIVj85D*|jy#XxIZ0M}IQo(?-t{yL z(X2@aH4jJcROU&448x8)>{I<$^FLYEC4)7%%GW4<5X$pL4gK62=8uwnoI`OGHdc0c2tcT6a#dxU4k|$&lL-eTCgzlUY1Cl@L@x{)74G;8aFiVf- zYkB6-l^NAHm^a;=e}0V~sd_y=@y~YA7|@cn=t?b^p~cq@;GgSNms!@|m}^m=85eww zR(F|EXhrAFEwlZ6qU>d2tn8=QNL7j?7g#WpX?w#_c}>=SCv%j*HnDw*~|B<4zkBnC2x5KeD^BrzM0NaCDKva z#yN;`K@*vG&q1EkQMWO~B11iuh)?C7MqMU;X%@+%GcMw|5`X?pf81sT5<)G^$7asq zlwUHkfDEG}S*kM@$r)#nY!BA3m$Iha&>~Y8{}#goB?1?-PRjbg`9BqKyQ9E7zGn9X zW)|2mQ}-Vw0xp$FBi5Ox4^|>=qD3C{v&amd*}s4HTZ$6=kd;T)u%AE9KO@6v znOoS?8(sSPA=t+kFYW1VVV$%6O<%a#(j$}ahp)d_51!%2d{+A7+6SPh2W!O<0SMva zn$ZC`U-dulqaUny_@f-py^E>^;PZX5Tf14~jtO9|? z4Kwz(MIzQG3NvP~Usc#w-!Tf6;&~SRlfC{M$w~dCh38EA%WUIy4Y%QF5=KkG}xzamW zL!QNagaORj;^U={qu|qB3x%(V8IsJtt!RQKG7I^;$VBI zOt`Ngi#3hUZNw}r9nYE4S>qT&Ch<5~DgJ)yITO|{Bct_$EWudQ|77X*SY*OVAD*MX zG9mm7GjVU25cxY3NApcU3VAHnC7Simg7OY|gI4G8lsr^ujY7oFFT`SX5yH;V30KN& z=y^q$6HBk#ghHGr2epIz;kcjzTzFA{0mBOE;wxfLC!aI25F=R6INzlZKO>n*{fy7? zC_-)v)}*EuLgPfPVoM>+jf=2|+`!@x=3`Z3jiKUu?p^u&WFO52vXBi6v1&eZ4evD- z_u0*)%GTym(a%om9+8YKf}^PH>b{^HkD9*;0;u zbde$9u2Rs%Nv<)gJ;T*OBKdn|vt4Bt=sSJHoc7}?iGR{ew(WJ1iBlcrK(4*CIjWL6 zYnT(i$X;fQag&DDPEsz@MLv#nla8!$+*FZU+*c;HzQ3i;kTMCnQYKY$e~WT*nGEZv zz_{2_iL#}8(VE%RpMFbEeyzaRpq-Pj+!v;GK^T^xMhn{>%Hm zoF7Wg1|XU>muW$K?1dj{#WM%<1|6qg>A867hY{y|a5&Wu{uh0*XN(_WulmE*#TN&< z`C=aHSNQ||(J$5)!-ITbe(H(O{2C_wYH7mek69ROVCM8-@2+itw7}9~0xrAo4rYZ(sp(x6@n7@10>oA-?kambkls zj%{+G`81xG$~kLH?vqsrxai29WGBq^a7NJ| zuF(GC9zEQdzB6WIat&v;a>mW=E>QTXVC?UNh*2t38cbHC^M5@ubT1Y=W1O1`oi37H z3{_zyof*}>sW5S~3XO)S5W=-(rL`)I=ejV%$r%9$op5&wp9fdW8>2$dzA(&Y9m!ESkF3Dix~Dvb|C*4tHG%=VR#b4T4RZZ zTp3xAQyP4(yBxi|$SRH`+qgI!9=pOYo&P`XWf-33YS4B$*M!x=@x?a`^BaUAZM_B~ z6Y2QoYn~||jxc{cV!zY3t)=T^Jw06}IvKhC3$mvNWgt1m^9J-xrSGgJdt!q1aQZ>! z(Nm9dMgx3V>+Cy+KJSBM8oBPP5u`_z0eaM-$0f$B!)?A+-$VljZ`Q*mG#M9a7?G$n zp!o@MA_ti{)L_*~>J$;GdHKJRQUGnR8P{zfjQ zcO#?Y%DUbLGaUWMHSICu*$QTuf_*iS%r@ova~Gepe~cN{HhDN%{C_-Sa6NZ9SJ+OD z?sb%{hg`)up|xxr>MmPW(z!cYiO1u}yT>W8b+#3zBr744hNAShFRmVCj|LgJayG)e(1e=qE+`kr~?(qR@`x`afk_M3Xn@7Mq2{XC{=N znT1tcn^-u0K9A?Pd9DC$^Na9h49BJph3GYfzDSOBPrEtGl$&HO%F#JK%SF_5SXP|p zEH!_Z%3t5fTioDWcZ=&(lM?f4vuCD^j_;#%Hof|<7selIGxI1N{88|?7T4C2YuAuV zX-Yn>ix!*CGY|4Gy}4v%hK$HU+-(!Kk&mm3EI8dR#MEI$SXHNxXS!VH6cpm~bY?zt zol*AERWg`+eZk-^vn#a~Yr8h08ES>kJ*;p(mwiFZ4*hsZfzqMmVqa$6t>Fcz(;CqhIWK zXh0T({|?~#TFLc!pH9*E!FBKZB=#KaVn0A$CZ@V(VKYC!biS7p-HLG8s|fdb@0_n# zga|vXAL*|<`-E=BQ^_)SwO%yilBH!>s*Lk>!RSI4#2!)M)<+i{+2M+yInJo$POt5U z5L^ilXQqh;sqZ+(#c1%?Y9lhM8}W*q!_B*Ttmc`N{;dIT$QHP@&O;3MfSwujHgU|T z(VYHQ*38F}El})GsGp2gsPCLmsQ1Mx)V15`WYM)lvZ1eDCern1=$0Zz_Gt!uR^eG= zSA2AKfytS<4uLMXu#5~wDfjU|=tv^-(EmEe*Q3l_xJ{mLqY;hP8ByyaJzM$oCS7Jm zLK(-%(Pm7a$Z@S1eX$O?h;2d!!@-Q?Va)uwLjH_w!BW;C_Ow>0oyqR0N7Fexn;DSX zlBGIXhjuFZB6+UjUZTR7udbM5-3n{S7W@epJ{hcS>#d98QD){l-JrMY4*h+e`PyiRUa38I?Nnw&aE?hsqlEJ3)=aH z<2T<^5SbJQGJ6N7)4x?a9OGk*aN%bae#C&683trFH#Q zcSaSS(FBz_<6bQN%bdgi%%7+v5O&9i6yI|cb7qob-!3^7Qbge~ZW;vOVLE)&p zT!SI}d@4*eB7T?=c_uvyLkv*e<~dD2Gfqw?mlDSJMFv0fxEakun6*l$=lfiRx_1CS zs|1Dm5qZn$%s729)?J)J+KS_J2dT5nLC%hMm;L_EQYYIA85RX}-0vi>BD>c>i2;8r z;dP6yT=>C;5%|&z(7BXjyYh{knam(53GgT$u4|EW(U-oivcpG`L+F2TE?Pb9p z1*$LQ{wj}qsPrA!y%;3}lD0S@LTf;dc-bq%E zZ7x;Rt>sd8W@lXSkfRlyvVS4~`**U}^JM`3 zJxmtA1N%4=wV3V8GlOngyzr-c`8>}G?s6YYHIV?vP;)Nm%^lvTm?Hnchpoc^xI?0Lv7oOQTOD{doePXQeVU|VAoG*Z_Py=7+k^18}1wefp!w=>4HZmt#@LQfRTWLNwe*^Q?mB z3f3LY;l&*jbIr+Ea?B2Op$B>@_b~b*R4XY&jSKA48qa-)m5W@v>?GeGvp;u>i!5N4 z!k0bva>-AD+=CX$oy%)dU5Pu76zI>nV?`roOI!TeTSA|fE&%WNd4=-aXWv~dzFcIE z=tSN_f$U}Trb}~nG-kD7Pv+7r6m;XBj@Rn6DvN#T=kR4~A^LMppJgn9rI5azeVpe9 z6=Cyp-aoxsi*1pcENbN{j$d0#Mzc1uCs2WIHRu<;!1J(A3ij_<;ow>&YFGurV^09` z&ifSCf+jOC&wX= z9-OacaD1L^#zLNJj@ZX~#Qj`U2v(@=H!9S2%y@qDf?hqPQmy0|Fs**FG_69%ajioV zxt)8mUF6|Q45Da5t~=WW4LA38eBiDLHBOqNF1cWqD>kUFJrHL zv>wri449?*kF7M|`A_EdROgr!$@5vB)n4VCQB;?i(f5Rf;rimLgU+jqzTnoLev4qMP8j0oloP9M>_>Q=*5?7xh;1PLv??EpAsTm&{Y1D`+H#GNMCS7`{hD3bClIaFOJNV4tamet z?v_C|y67alnUUE*Dj3eGurAdZcZWFR1K;0<$Ij@zn)Ph1fo?1c!+6dU{>#`OHz^$7 zv_=T`Uq867YFmqaWo?XD9L4uHAP-+&^SpeL8Rw^P4K%@w-(=v|a}Eu^tWdAuuLWe_ z@ALi%e@o``x>1I$N|sjpjMA{NUOF1-pGeosi&$n1e08RSN`>^Z-0MDb!4qbd|NDgV z=g@HWtMGFh%gpI!;TRhmjz_Eogg6_}!$ODuS3UZ$XN>D7|uTzT~5Yu{m?7f6IsSUU2Cd z38#om^jcT|Yq6D(v>)=GXJTGfk*Kyc1C6#8K%3S`UON4haY}DA4jz3{SKBx3q!V(3BgR+p`%#vJ<5*kAnN zQv?=gWnx=2eQJ*zNeHc(W3G7NSt^OE$P9!}E5PEiMsjVz52;5kW?xPOem%`Vh&dlS zeHzMBZLyrY<&7N)%ov))p7<8@2ClM}O5}qM9`Ql*a?F{v&BWMq?=ay~L%H3EdCKR8 zV8Mm$=w_b@ZMy>cBI?UK=JU>DZgLCfNYs7Bv*kt11)gssF`X@v$2?p=p8HLU%0O^p z0RnwnGLNl9?v3z1g$0s{ykdL5GFtC~QIaeY} zy8EK_@<{wFB_DT*dEYJ#}fu#*fbPNweNCsk2f}ukNbRxE&_)F1n+GoHUqxNot(k&+ZO@wbF5R8k9AQ^q)Go0 z>0L4ezTYCzfjrdGcl2OZYa!_KTMCwYV@bzIwC3maWkWvp9%&>`w|W-P{hyt&mf}IBa>O#2-uozo-^zr|Fn%t5TFCBQ z#jm@$dG(Ip*OG>A3t@(3yHCj*nKGjUpo{a-@lpEDETF;d7u2oZHL-O5B+!P*VPAKvgy+-VZV4%0qTEhAzO!) zNYyspIK=A~I3N?d#}x29%|@PVDV5926YtnK5<9cV^A4bo@?ljTi+u(rRU$t~zOwI*5((ql<`H?r)+aK^>oNbgUPC#U zS0YcDd%pi=1orcF6y#4Q@xC3|n5FZtgdtOwDj zd87_=aPHem^)Wvsfqu_tgCY@iAQJ=o6`<)t8~OTyx#Z;da&Iz^$SDI!-uY*f050k7LR^4&k4yn`ajR`iWa`hw3M5FdMb+!}?zl^j{`mf0w(WWnv- z^qOrTvv4v5d&m#o%E`g*z7{N6xlaQWfsGG}^G$pB&`%fIko?_)Z1`O+gGbd^ z3AA=X>by{VyT}}BazkdZ;O`pr8@_YIu1-OiQ24oH`CjUKRou7y81; z-&G)QIB0adbTv8R_Q6ne4<&awDjW85m~UI_fJ8+)p>B_0EJ&o6FoyYzH_Pys^?n(| z99YlWp{O!OhlF6B4ad-T_W7Ws(*IcN40Cn6=`nwP4zr4QoxdNHvs>*^@+cH_d+N|M zmAS6L798+Nl!?s6-qJ7_UX7Upz9t*flP!216DMOAIl$$wAmkm@AvZD`L1qgA&n8I! z$QI}p8ia$TN%%;P(qW$k+jQ|V^R6RGCWpW~jXYgw4%(9+95g;b=InC9!h{ga)9SF0 zzPU=|!mIN2YhK8iYG03KL4FOtj2||iDb=j2N1%qOvjPE`k83)sHH@m#k_C(>v#shI)JeZvlktaFXX(IDK)5YoP1W73`{2<+Pngo|ti`a+PtsTcTqD*GeYU5h^L$v+CuL*%Gbp~vvgr~n-B)FCS%1N->; z8+t^_1a~ED=?(OFq=kKP1}3JK!LmWDgpFr!@W1}pY^g&pJ@cA*e|9|^AunIkmp3N} z-}}?g_$M8k^rbMajh55jZD42-2)}hYboiT&SLF3doMPm1DRYf^AJ)64#l~0UdFzs2 zes@H=^k8yy@=Xbs-Tvq> zmR#gg^1r_1E~`h2`wjXEnUn5F9?-2beXJKsk$fORvMSkON7X<)TtF{j81KXR_4i<{B1Eut=FphwR#H2o4K6Pwtg(x4z%m(xPqiNBZk`I_0W za{h-B>(|n6_*;vWYtqRoaPM_GS}e9G5i*g^w-H(#-<5&&_Ixg`M#-sOHu!TQ5DR8$ zVfBkV^5imPrA5lX7q(bJZhAS#$?CD>C8v?I-V!O@S6BnP$u+l$gYhGC$)A3=H77an&V8p0-j#x7r^+7qI`# zG6PStOHrv?l>D7)4f9NY_|~N-?oI~!rj?>yS(IFyXNx2A12La0SD$g2*xa8v@_VAl z2-%`aXFuHKd~w2$oV9`Xl_^ThLT!=Q*dLv5X|ZMxpO-cY*G>H*<;WCUyjc~5_D6IW zbUp)PK9}O~r6aQ9kuBa|<@LYA@qb<>9`O7BfBlTrN5vZac6hlAe4To+WlrOim0PS_ zDp^%Dlud4DxTJn&*j_8t@J~^K!86S)W#9?5!6u=;VZaAna`_q6Qw~l)W=OiT*QNET zwB+F~!7hJ>3{2VFV}U{A8(`>o$C6_9R|fN#HHOur0=u1QT-#u?;iI8b{cSGGlc#hW znH-V4aI#rSIqTeHx0bzD-pdoj}Vh*la`(Mqd` z1gSGdD~5mLq;6DIS}^->j2))?+mR<>Cc-Ku_CL47hGuH0Ym-Ohb9rIC1CGv9!)Z0M0mUFYmCeW7H|aS-x81>wnwZzS>rfAU56l^onLFN$2zSZ&+~NXT%^O50eaj?)ZzY9p6$QZBR7f+ zvO$O2U)W>tnO}dW!#O8Ce(>zAWHNI=3i)@^nDbSQ%wuIeocS}GZPa0iFFia*=v}DA ztgq*MhQ}}i+ANb^EqZgl@oau3>lgN97R%^Re8f3%6&(?Ynb_x(g~#_ZG2eoI#(m6@ zCjabIF$;h5Goks*9t4iB^|R^nIhctq2|PFI&Y!iCtYag(6E0+8+44fbau-;6bqRd(XVx@WKPw$krxYccFoN~Ho@X>dm=H8u7!Vwp-_thW>2 zKx^rG%|@!Xv6UEi8yOJUN@~%0kXYSH2F`F2e|xpOCu_B-wT(PZw2?{fWFDop_y*Vs zPTI&@vXFgxIY`^=4l;IHTj_AnS|;vxka?A?q}SEPGP=A{npL)wu6@jKw}ei(m&HqE|x#dOXbuO)-;ZLp>9=A9C_%4jBK)02Rsp*;fb_l;h<4&E?~_lDgBFYL`^p0phqMIUBNbqo6+{;F9C_kF{| zU{Nj{&l`}bDj*9rkM&+}@=?#jkV~IUky|)Uke^Dw#9YOruPwq+cNgm=ufs6OijKO9%zEBU zZZX@4VPqTo1sdTvG!4@(Gw140Dh?ht!kwSTcQRrN&mJbfVqWe+BRn!wxvpZZg@2~K zNkvkADz;3cU$LW+Svy9gu?}405&6fSsd&oI7xH_0kiWV-mATX83VhZZG4ZMqUHG%d zaj&ErV#Kr^M%*YcLGd^j39Fb(dyS67`gs^M%!Eyq>2+G3i~cK3_~&dcuAVnxBLBPR z8~Q06O{kKRi{5K;v3PuF{Sxl~gr zaXJUF-`-lj)wY&Xu;4=48{NxvT24NM! ze%j_9*t&>5#_FDMzUs+*RQe!U6Kpca3v(NIAz0}}w~#02Dlfd6ABJt2VVD-qX9!_9 z)rI%{xiB0V9ELtK!{|x~$E!MF7|D93uXz~8@Oc`L!E@7bWOVwn)=55b%^5O_>HKpw zGox#UVb1}cyZt2dcsdMod-Iv(=ZC)YInLuV#P6NOpa0H<9!Cjdu1pxF^ds}b?;YMN z48Q(Og~bvh(to64g*`dLFnSvK95nDU;!>s&7n12+OrwjXl@Z0`jQF^lS#A%F_)-nbkaA7Eaa6z%?;a)+0_vY>1QE&l1FJQJg%Eijx}dG3>u$cIELHu^>P4XPaJT zor{w;Z{j6og;t{Cw32loK}w&qm!?ykjA^fx!mv2`Q9&oKV|7xUIcBPJTIv5=E7j<7 z{7rtbOFtEc3Hij`_NW~|_o9kkl570ssPMdmbtTp&tMygE>!Tf}m9xXIU#tzDCF97mo_k~Lp<$h{ zT`0MUnRc-JSA~FfDzq}QN7_*Kri5x>-kHut?!8LGG#CoHylZRFh3mhLJD3kTSp(Bz z4L18}u=aHj9U;L;W@{k8Lc(Fu-EqyfTXU{G%t{pR024THghrlX&)Xmi4(0taLw(Ia{ z20bHO|1~*44(JYDC^nTxLN$(w&Ww%a-I3F4xjv)Z5^#ctyC=rJCmP$ufwsE znTQ&gNk0@F+GHAA88dO~8GAwRX2O?y<1@*bs87!EJ9(0q-`Pu%Gx+q&E)j^G3y!-WVO?i;r9n-Q?Qh&TTT|zn1&?YU6 z{D_h3a?anI_;JdJfIH;3Sx0x{{5&R?V?rXwkEZmuhSJX(L;v5CwzBC@C%JE@mfVkO zIl1waFF?NW<(Ad~IY40yLcG-;s0Rdf=fm z-ASkOQ2wo>+)8zndea=`#TzR*VC^X5T06@38k|QPo1ynGb3AsTAG{JXJNfy=2i|C) z^TdLVzBpP$4~XME$-^WCI<_~% zt4K4PNi;_wuhHEKWKgqwFsqL@+LU;s(I6jGxkVT9dmnTsySQB&4$Ycy)Z+U#<1zig zd&2RabBsDR4F}H{@##q#E*Fyr$)uxk7Fot~CIlPk()9U{lOgwRBKN@S;~nTEC-*vv zswp|5%r+9dTq&LX%#dGThHY9iSnes6({oGZb+Q7Fv~(-4_rZIvn`e3WV84pJJcoR+ zy(kP5E^^*H%*@wMWGe%9V|kC=yq2kG>urSj^fVk`CuLzQ`(nnY!H@i4jcX=MviXdb zah$h!AN_2Xhf50_BsrnIoKI28DZRC{3u6z~YNhAp?O3`BO8Como zUi8N5U0&$;%L}%>z46h}7ppfj|9TeluJv3mlbQL=>vFNpZhSRxEx`Nd(IPTMyl-k& zNyFTxX=q9&q(MvaAM;FzcH;ZSHR9Qi%zz`~w5qjM;>f7ye2V8eU%WJbohUc_xYw_1 zkKT>daNE`vXUL@$)pvm65y#iaAk4o`H_?6#QaFaTAe+7V7=5<{QWr#N3z)0wk-?A$vmU!t8i75k+U+;LC8$Xw#5q9&N^mG z4^EUn%)GvOS1*<&dg(}>@VU7fsV3$t{#L`Cb^Hm|1Cdj~PYMjeZv+vjee>C=3c}5Kj z3p-q%9gIsOHMrI<7~`5~fRJE3?HP=%!u~^!>0L{7I60fy(>LPrp+y25yUy|qLkF$A zd`kb|7iMwW+XHhQFfWc7Im=WSZ?g(P9fPsQE*QUaH2>pi{8fRk@eRlQWz19V5|4EY z=^<<#kB#J2x|L-jm7L7RRK9QH=^`W7*nLSh{$Va=B(u2F`El;9!c}W$=9)f{yi6Q< zQ%Mx#Wxces(26Q0PM+`4$^*3;wVl|z(8C@UdO?MbIpKK;aGi?Uznk+qcb!i!84rZGPvF$)(KlfU4Z!aKUi`n6ZM zZo8mxy&0r%T|lnUjZB9BNS&lMq)R$VD-HU_%7<*NTp+(wy|O)alR53o*Y#qb8sp0B z;a05TH48$Q3*;#+gVD>#*TlJc*m?FVl<3j)dpy0XoQF-!$S~t|8Xu1Q5;iHAlgB=+i)G>!>BAa_4_eY?w_}zMrdJz*FP**NaErZupTaQM zCJduvxsP@aM+eSfOEespx3HIpYw%L;RaFDnclUsOK-nf_KF`J1PI;)DOxBy@&z=i; z2x!w;zRhSar^G>OzqXf7=jiL-)<(t-Fh{M}aK}%6AGi;9WNyL<<|*!@b7?jGxi#1i$lpJV<4`L1#R=OvHXcvI z@mD6i*qeu+?6oV)pktkVd@s%Na5BAvXts8d;6$}Fv9ysso^52%s4nvNz8QuU@Z6=d z8CJhkp!sWaJfzq6*EMg{4QAeS)CgQy;tP+8?Afg5i)Y{2=XEa}jg{f3{Vg23_}{Mw zaDKgFgtv|iet9yDZ7#w5Huov(>5P0xhkFKHh{5E$cjcktz&t$Y{uvKnw37v~ZKbMD z8>v3rNw&n;NyFI=@*~F#qxjKBYmOuCCE_|=fh+#zSQ^Xq#%;2vEq(E8yEnX3d{Aeb zFCH%nM|{OFJnkEgwY)}yj)r4#=iM0EpZ$@q)6k|-8uk^C&2P`SbSiV69ZXQ(GQrA7 zPoy0^gxq`VB4?>N(^h6rY%gD?sAZqEjWnvLmd!e~j6bS?AJ3vnBNf}Nev>Vpp(z3}M<_mubP751X@cqaFfobRjN49C%6Ba%JS(5W1~ zjGRk*^<~eeC;Jw@n=qB<3g2h2zmoGt@;DQ2)XGEc-OTR{S4xL_YDu1IBmcxXivLDy zS$mtWqn`rR+7`>m*St2NJnIS|r`yL9L#@0qsizmtk7a)V_q|@fy>Y`Y9G`oIW9o)5 zBqq?s>>G}2<#>Iz8L@)zSs%iK)#Du$b^5D<&lzW{`sKM8C_6c(; zESNLBBT*Kr;-zsMYfRVl;*zA3szG$aUts%v?cet>Idw-i0L)Q(5;adPkvGnvzqiP4#yD_&>PJ(q=)W$eeHziv2L zv^^OL*U8poz*zfwMgQOAUP;pKRia$t__LGa(6J^7GLHMGh&%R3kK~-u#R2|Z)R;_X zt&wNvLph%=U7^9l7OU{$G2M|5=xTgO=X+~r7W1{JPU*0}8C}N)J$g*xoEFZtH^=C9 zt1>ZRHaTjZ$5!BYophxPGi#Z-{v}J@gDkaz{JTRxGuK6r_4512F*!IrLH=2tAiFrH zPJWOeT@P~X%VOTqAo8A^*ISQPdwOcgU(VeWPE7@-MV6-@^fqtn5Kj+dLzgdr% ze9rA-^tfE8!{vMAJ=?LbeG4HS#;!BZk+<<+B+2<1u$fJe1t?EZIz#uLFDbpRtcWgZ)-PTx&$|n%vKV{z4YBUa~RZ z1f4b;%v@LIC|s{`E*rW;;abwo%yk{-^dHCdGNB4*u@ap$;JvdhS1-zH4%nEk#{I8! zE+17PaGe^i$5b%v2}1dp0K}AVFSkR3vK_%Ft+fh@S)8jL=`mqcJeK%yUVqAdvsQZ8 z7PBs`$i{{rS!n8>jXK`h$nKJbr)1x+^-#FhWr8th(6M?*fj(_r?P4AH=! zbJmTntQ!pGeZ+aI_z(L9#_18y9<}&goY(u&H>zUp^y(}O%g=%>=P&1JTm!`_TrZGg z^k(nGo`L_5XDoVbA?2?XihGG0o=y#A&MUoa4!LNhXHKhYvApWe^Sf2UR>)0da&|2o-{VUT_ z-BGSy7>CZ``QZ{N+2@AvHS`-sry}A|F7|wADh-%}ykzij=5B`I-dLWK z)nV?(+~(4~QK4*M{_MUVp{SBg4r?kopb0JH3H@UCo_Qj@To}YP6$`I0f9I^Nw5?qt zi61-=%QNpc3id!f&B4Tg#?q5Hzq#Mt@nd}`?yV>H_fIaWEpH^dW)zC^Sx-zO=UDum z9z$pL><+P#Jwl!_ZWx{N%(LFabL~&Lc&Kh6yUD?=ec+Cr+e2acz_R02<_@>0C&|N^ zRnyiJ{p$1F@JT8&nfdQ6YAW}){gI*qcf41GV%X9Y%xKQ@x(H7Ds z_>a_oG8}JxLa|Rz-&{C(LytysT3^U)ayNXL5sDz*Cr$Q~6Rh4$wucqS{Ok0`IfkHW zZVIXm$;G7U&BXG1p>&z#j<$v5?`9gH*hTN#h88j+k7@3wJz=aLO2;GfyF0Om*}jR) z*jXqkv)!W+@Z^jea)@+G&G9cw9u z@FF?2!yPaDLr{>Ag7d!2*FN4qU!`OGQal7jjhm{;Dku`obRCe)xOkv#8( zXx{&dT-MWCNQ=RLWnzLmKG!54w~z1FKip?8Z6u8w7Ko+79ZnzUhcHjY7xKSr_B9m; z+rRQ=zB}%{qIa);Dvs!K;M%;EG%qNS&J*3x@8K?3bWTN8r(C2AZZ3(YKavx0>Cqq#wBL&CEmrWR} zl>A|363BX$Q+aZBHI3NL=lXZBg`DeJD&NR0_P9#_X=na>o8{u>!UpmWJ&%j(df-fB z)`BiE4|;nJ?k=;I6D@zs`NM7~yA=Wtcjjx?&xLz&Gda)a!h4q|hI9$VqCu(1IQt1F zD_O`KQ;8g{Nk{e}@^rjU4%>09^0%3+C|4r8c>hX2-$(s68)m8(%hY#n_6DUzG?Jj#erl=Wfu2VZ~8YkCIre@oJGa-G{l z@GO&D_7V2g*JvT{?i9+rT5fbLhvL_vRQyA}yX0;wnNYJp8aDO7x|Z}^($n#FLN3f} zG?xi{e=W#gcR9gv=`;Dt=o~z~QCITY{S<99?>9vlj@L`Y)k*Z6@;ZmCE|7A6-EcQM z6h3?CfqnG}E1fMRmE&H+>Tb*&BL90X1%IC9F#o_>`V23YtdDNk&vDX$*KOzX9JKFb zDgUnjBg=+zJggatc?XzZPcFM?L}Rfz|3}6?cE{g2p?Ec({hYPwuc>NnTiIjlON;oG3pn`!s)SGnPZ{)U4MavU%K#vyq;q`sy?bgYp8>tji z93$oWaU1A7$kR0;Ulzdn^@K9!kVJ}iRcm~$%iP-!T0C4yA9NM^%QBOxH=^31Fhh2_=xa+5dtj}P77;~#T z(+4-g4vRNvu>XJ-PA4)@lbl*aNsK()Z-+|{{LrU5xkB=HT@IJwQRQfHZp^&t*Z@4} z!2bB^Qu0Q1dcWWR9ovH9I)Y(qQxkEu6b$U^qQ-7nO0cuagpOrUYO^ zJiU8Lu8muekJCrVpsM7mssw>X94sL>;5)Ju-SUr0V?8-aa(|b$@#lwTpsQ6GcH6|t zr7U_39r-$w$h&>dz_j8r9G*Z9Xqpns>Eo;4pS?T|JV!2NPVvhqX{A#_^Obzu6CI4R zGx5`oT+*OOX|q#_QA3z({6LHGkJ53MUQ53dk#gm}4Xix;k;VMqS0(8@*Dix;ZHz=% z+G70`Ke)Kkdw4t(c@@gI&xnw<%%QHAy%N*DYte2ExxZ>WSNNAanzIeY_V>rRtvYP0 zo{4z=dq0djC=cl$TyZrJjXLTu?PEILSLf>)A1M}rNYUAV@i?zGfMV6 zumNraK<>xldpW)@Gs!(|ij_31Kt4(X++Xp83=e(-W&pYSRA z_-qxf%g@9~g^M=0*_~dk-Q+QO|L8`Ot7;M@^Z9cUCk3JE4=u_nW+K+1434}$Q>!cC z=Me;7@@s=eWH5)K6yLHUq~a-h{pi=5xkig?^)m3yybMd8Mao25Iw4*L!r>3Sgyg^0 zhLRio94To-=+jIKz^IK{EI3F`)}Q=ruPAwT%m%d&25_CD#pLlBxZju0OO-fr@5Uak z$AK`Ci`@1*1G6Ga;oU4+I*<##*(DI3H?*i=&Fm(=&Ku;vek`|znz`*Q$?;7i*B0HW z45OMv2*qFMvBM9^=H&hw@qTDcZnRO9IMKV8Z03hvd@ih}X5iIig{!e@gp3-m#CK&N z*75o3?URWOyq-0`M99Jp^mxu@jV6Kl$h<$lsmsu9E&01!wy5kIfUa8RYp>0K|MfE5 zSsEqFQf)BePaq!f-`lm6{>pb{=wlxvyE@t75byuJ!{V^MN+y11l#=_1mBq|$A5n!l z$PKhG)+Tc^ikxXmlr-<6q|29Cuk*q+M@czn6=LQEp+^OtRkEHEL=N=9 zt7xe=L&?kt`u>LSdB4E?^dV(*AI8f2Li!@#1;M@#eTC+ks6_tPm~}+vGcP;hq(3Z` ztmm}K!0xJCzw4r;4xgiIo&6C$M~ACB(~*CkK312bGH|$xz10ECtI&Zj9+RBQ&^9|l zo{@hX@|K>^W;%F$BiBj)V5Ou8DQl}lT%qMp_ zJsqnTmtk#QtOOrcqF;O<`o_lLX$0R#Jw2ES{Qi9YoZkM}LVmVcwM=|^TZ)crV&$gM z27`A5qDw0sJZogaE}i~d=SVqp*ajy#9?qS}UdIf+PA^_JzoYWWgX7Fne=LjDqVptj zn)KUN`w=7ank(_GdjQN>!%HUj{d^gD+e`d8j!M)#;g1_paY*O$xMfr+4vdVDo2hm% zkP|;$M~m`h8Ns|@`T>Sa*+JvLgrQcx*0ExT59FaI%Zw>*NS(I zczL{DjS2QDW^>V#@L7dEj7kq4>BO52IA@;COME&+f_PDs*bC#wj~{ zc*LmDh4qXbAxc~wtH#;u{J!<9g|`hx8tWMQrUvp}4MG6x(phF2o+|`mJ?qL#9tNQ) z&+%(mFf%YggN(X?sI3pe;Fiq$Sf)YhG!5KrnGHprvHpCXb#Xmm`&)zJ0rdBD3Pf6c z=4;hsUHY^JA8V6YtU})o&!1*D(qP;mW`*n``#6Qab1u(+-Unfdj~)j(-_~oZN8uqI zb~RwuUj}oeyYt*7M~fAA*;8sFtJqhMF^%JhxbPTZfmPT0G|eFYC>WCLL=@o#|X47x{Id z9-*W47^Ka_E3&@LD`%n;>jR!HnaJ9ig`wUV@O0<-%ETgv-|dCw97fVGQf|sVX0w`{0R2ZeA!LXZ8KACzLr}bgX;f#b$bV$SZC)d1C2Fo->zt zA*;SOvXs8K$e*9z+6O}mJyE>L8y?p^ahl)T-~_oVdK(Xue=^_7n#G_nXjvz)>qA#u zd>DM4!=QAbXJ{S0iHCNh%FQs?WwSOPO80zl7@6N%h;T? z534dVRpb=M7KY&>&)Y984a2YpVQBd$41R0LJd&~6TA6uPbD0zQCluo*gyHiuo_~+0 z^RWl_N9R&8sHYJHi;W0+XT-G&Mp*A5lQ1fcwK>)=F4JAnnCIdbQ!)P+{fs=jar%}D zd^4iL6LJf$jj*|9#F*`@{raV%_DLhEgpg?*YsBwrM!b4sgza&<;^va!DoaKAW=2@K z@_gWn5z&Ek8nAZs;4WQs4bl+2+64b0CVcQPVdMcahZ{{$4>w^IS;Y-&Oh_7GLeZUE z%pnU^{w{ebPu90*<>GM-Iy2I9af)XbHLI9#P|g3x^Ll05Jk;EphkAc(`w zg1fU`Q&23W=4RL)#b@MtiS*I)xhg7_m6OV3Yr_(G;?1n~!DcwWhOWoPW+=_)9#_d) zVN@w|G!!W3&HOYzW4(AbGontJMD8z@+@@xjcc%4pXXJ~XpiOd zQiD9>$}mJ;r*~;aI70QIc)v0ft#7eb=M>H?4AwGBnblPx4EagnC}OQ_ZB#ghTn@wa z&pfBS5{8rHF19xd$If;1eg)Bi!P=*Fei*#Vk$oWl@Lw(I*GBqO=acKUr5o2-KoruqC{vW@llEOu8#DrlDOn6?vzGpsjdE59r@_UAFGGTlv&&Fnw1D;FY$V;Ac3^1Xs z56_k8unC|iwLPEDa9gs&=W@|&IDL*}9h(>C;*4b;5^I{^LQW>k(uAz?w+xZd&MsG) zr5fsM<{J7<6NB%Rk1h+oE-?%})w%oA^W$9FSU)$cO=)8oP%+3bzRD=Wf<20q$GfW~ zZ*@?lEV_8!;I#JT#o5gp8Z2+@>K?zjP4^8yBa?e)pEc~QY46fC+{tCdiyg@sN8^&c zzWW-MM{F_dn`+kMZJd+Kl};Cuk5(}zxBI@x#s1(ogZa;Nmm2PI;-b~bK)Ms{tjQ{V z(90&8OdKbS-ae=#@t`@d3&f);Hk##A3<u2Bm!;d7V%tADak?@bm=4cOCil673J;ofpxIIJIQUiMkYzMqMLftl!QPv$U& zXF44->2hFx8P9{dPS1pO7`@-e`1d~3+t0t-@(I1(i?ZOvn&iS{?iH}&E= zacm|I@oQ^rvXJ?K{cOLpup=iE4Wj-Z&shAzQ7&Gvm634{a+AKKezhEAZ**I6P?p2w zmnBl%m-9ugIjp0KMfchaF7Lh2jAL-icg&-7@-_S>rQVI8OC)wA6zT& zhRN0&%{-VDx*!Y+=Wv`So9?oo?BEdA_&?BrOYXw12K~1KFJT~GPkycuUFp?JUYdtq z9FKN2&V#pA9vaaf*)PLhUTEJ!pa{?kqlBs$0>M>`qX zw7ulerFm;dsnl{+;Po~-%Ck!3*~wDz$ne4tGhghai|p_oPxNl)je16Ja*N?e{tgOS1bsiGNnb6P3b=xcUsNCW88s{jNo7hRE{nqm3qLSGM4wA+ml0jUP9PUlNa$K48 z=9*_yWiy`HnBzKKRA##q{BtM{4^uqKA4PwyBa+osbKy{jgogNyr>t9 zg-z&YTpf(*-|H$1@ibk}oTzxzuq7YfjlF)S$rp^y!nktTJon9pfn!-S zjz?)^9_pN7Eq^i{hA+f+zn zujY(C4zMOmKZ^Xt89OyX$;GXhL)TW42Fm&DvE=yQM>r=K^zi2%{*qrjENkkqkbC<} zP06?lX^T;`J#r|a65!?p0(;p?z2RV5kce|UXsz{nZ~B=8f=@Y zL8MnO9$wYsR1W8Z{_$wAL63f%TYk`r(3EB*N2(+}w7DBWM`YI^26ktOUID-Cz(WaC$!4Y}Im-wkR^Xu`f!@-lU& zGIN#u;yu1c)#?Pp{sq~h+jJ$rXYFPaYaI1??r}CAe%08^xla#<1mJG||7Mk+c$|rf zcgW0_r(g3g=b{c~t_{bMOKGKWb(*4Z_0W+|(I{NY`6fyhGs2rp(8`-le6JeCOUt4p z39zS|aWmHsB|Mi}t479QHQL-(W7K%QKV(qbb3Px+dD`(t5H_}>f2&ZB7o3+z$Hn6f z=gG6R^{6$>}zj@>#3~@*LR!9gmhB4{#Umu zVZY?uO?EPFj=glA+eSJkwUsmT+R03wExf9vK&Rg381vU0eS4ZAwyPO_erC@T$Ky`i zPh6!Jv1)U=eV2H`(k&cWM>s!lOg1yny*`5bgGXWbm*er3!D)~|X&A(DxtpUAdtT7b zIx!C^+w;(jW8rghd)rgFR&Ha$_TC+2^y@aV=T>uhxWi6tBJAbTWP2(9UBPT)1%9k3 zl|x<1r27qiUfv8>`}x3das*P&dE+|I3NB}puXbdAz?V?O6^G-JuqWy~GaB?^ICg_v z!>lw^iXulHZ^WA$M%@0$J$6DGHgHY8xOyH|-lXTeCb_gOCS2hCN^BiP?o2}e1k7@jGOJVWPvzS)RPX6!*+!aQS+jcqv&c5uyu?@_v5 z7Ug0)_Yubqk*_@4MxHdVmu|kcQu?l?^j&Tzhq9d{g!8Dmrvf>?e`J$miG;T?gBACc zJ{{@h?@Om|yeF#j<3W-S>RtB1XwF+7gXm}Eyw!>C)3R60p@<;wsiYs0>x@QKFJX3F zBX+4Tp?ELdQ1!^?eK)~j56=V6ny}HF*XXecp@BA1%f?=!%Gt^H8%|P7=&l^fp2Fc~ zSa8Y=wS7ut)PPcHzeItl^LUoj$_wV)W7ZwxgL{#l*sz27+$yq!+z&c0-;MUw>4DA- zhkq1vGVH^#gX@i);5011%RV!!H1;X5pW>$xvGSSsBE4yxGj?cWv4#<6DbpRYhvusQah_QAkSV_Xw0;#z0*)-=pCPs3G*djOWxu**+jqs*PYa5dD6~$bKyd;2wm| zn*<+wbX~;0qJkidt{#lm!#VCWBL{YZZguty^^9TORNHv8JD_KMLPzc*9xaNQWpf}K ztBy0*<~=>NR_yOiVefXf!gbyyg=;lB{h_@R2Gev`^&YDBe4g8v*x_##)*an6h^V;= zjm$Neewuw-+{6+J193?i|TNUw$4jAPbGw zlaq@lYfk1|(?{WY;sf)+A~=tQ)BiU-LB1;Er6gV}-K)}{;G>g(?g^qGGq{4+=s_

n zGkHEeD+}FwWMRr}))K4Hhqx#UVxe%YJ&P{ig&dpLkSE}Ht-MKQ?@f}lwbF|@*Bra9 zu%Kg;6N-ayc4{!@R%2aYn1*}KU^w*&#*DLc zAT5bU);c8pW%=H!L(eQW7 z1DvgJ-MN7M9AoLNyqzc=R66N#nb}#~v)?9@zk99<@=}dk$5f~nsYH05JwofM@#GcP zJAtdvcY82$c<(2vnm}pmNE@XG0U|*{w)cJaIz_ z&$*tGhZ?+%XDUq_$crCE@@%0yzW)lPdz|M!>vEyF%G_$>FWI)&9YX_{Uy?xo;JF-l zS~L-lN_4E(_vHOc?<~)k0*-$~RYiSS`Jq6jSr3Qn#}K6TOGS~Iyv*KK(x-8WEIRH^ zCMFcF^aIY>k^|@2O~i}*QN`Jwh*7c!I3N|1M&{zLQ!|NqQY@Np?x?yU3}eX;9$1`% z?siRNO7#L!wPb#4PACSrkk|X~-}R!dTxPAnME_%&4SR~ar~D5O^|jDiJp28XGirW4 zf?mZf2CQwJgC6AR#`EY53uF71;&rT0jLhj?e3sW?Y6>nk%Ef9$ z3)U`5#DzTF_!lAQ*@L-5*?j%Xryeq(SQgji>+cncZ;w*(V`C2Hudon{_v9=8afh=v zJ(vab(EZLqs9QtX`jt80KRr<^oV=%`p!Mw>)ack$_E#yEZ2sQADxT%9O68vS6Etxx zrQ2U}i&N--Y{J*yirzh5x2GR1rKsW$xtZ^ddV~1$`M&s9WIyoBhVr&nf%vrc#JJ<3 znDr$UV_b9LJlaxjz9S(4nz*em44)>G^seVJ_nkA z8cJTLzf$ifbDZhlJW1YaOKL72*;~rWH>EOtfIDKE(VzGad!KveupUBxU$Z|lkgv0` zmbu=1zb4yr?%L8)HoW{RXO9g>$8Vt+wVn4BzwVoFA^KB=^2ON$H-)diMhYtNe)Ae* zDTi7VOHB)R%=HXGmr&*fd-C67)*YdE->n_shktP7P&dW|3H~cE_xn zp%@aJfV>)0#Zp&k(%$Hw6t_fA6wJa+K%vrwcsL z=0gZJKW3h9^&C`JSjpabMKW}l8$t>~@ZKkt^LP#vzLwHp+;7>imYEApm}$_7Yn=zV z*!Ivy*3$DhslXGBjUi~r=k9&^9OMVLmd{6ji`PLnY$y#yuoL-K2cGF(wvZC~6MyaJ zbCJZnqNfIU@5+Tmj-^!XS;+c?2NsMaha1Qo=Q#RO^IOQOM}H++;Q_nrA*h#QU}i}U zT3ED@Tir_KSF{J5bLnaIPQkp{IaoTnvD8f|lxBTB>GvjA`!fY$VL5PL-%`A#P@a-2 zT-BF3VTx4LJV~GF3M)~NUw$jYp~(!v*<&df_bCVdYg@>C@}d1}dtizUbE5y_D_7>i z^RA_gxbauYHRbaa6av3zDQMJz*V(&;Y)WK}gU`{nFaP;5Q*pCF4o(!-m$mJR1l=aQs@bGO2d3E|XT}`-_ZzXRJ7K$4=UuOxy$Q`MuF_c{MhWhfO_aB)R z;)y1yNLP}Hl+ObgDZ1TXY+)(u8{h&oEk9m37%cjMQmw2zTb)#+zqesSN+S`^I7fTghv+crf@dX5cDvjY(nqr*e4GfKnh z^?Mp2J9gW^da6HueWF{aDqTPi$lqBW5uXAZj!}V_xk!f}C3{o?Rml z-yGTF_&gok>EkP5e(r%`N{oK&kCh*_=-DA189T~wCL=~Vks~uq@rU`jI0Qv9=eMvF z#Y4&Ek$d{KGYEQT9V)cUz=(eI50VG;t8Is_T*rO*$-L<*^ayF`eftz90y$ zT=R}dNk_*9r5Mp8M&94I#gSHl*cHWG)J$@JZ_4QE)yey3N|?w=4Ve~)gv;ru$bZ*_ z7qQZJwGAA|8D;{IrGCGzMyyGRbGHaW*b_ezoT zEkca+omE-ok6LkB#Jx|)ejR;n1ESV+8kKZuuU;^}*tQhww?@c>7dD7o83;PU5i~jjWPAWzC-YD5kesjV{dH}m?ncGHI zWG#8dj}go|uth8Kwx-GC&gj!TVkpB;|0rp|`*XoPe;ggCLv&N-K$VtaR`VD+yuk+7 z_xqzLg3CXFhGumlWl0SsCff51D@=!>*O}A(xD?x*qh!6W5=BSp*E_65)%XmQ zye@@P|0s#zeKmFRz&#=-{FB<%MRT=j2k%I~pZ+=1LUP zOSpzV|4d#6e#Mod%0EZt!gV`DvYvB-yv@u|zVCmS8-65OlqdP`O$)?_b2?nAlz~Ur zOId3rhx^I~j>}o+IjTj6n;9r8DW!WVQlf*D80sE?={2-SanHcgUu8%n-*;N6#9VT_ zRaDI2`uq?T!{}k`6eaz)StE&l)z#DK<-C!Ok>%MhyE#Js1lwYi6&)G{T5Q@!p89DS zdRLB+1&(&8G4ubB_SSz53#G<5dCxi7^f6L+Ke&-7F;86~Rf6HnpZ_}Z z5cM`tU-ev^+*{#>sc)C#%PjKL1{01(Sn=|BtPrBcmJh+GF;#~?QM{g)t@v%nc`U{a zZg0sgHqm2B0PkZYeaU+!Nop-OJiopi(>oZ@X0QpDep;}gcD%f%E~?kn8 z;d0y=KPJdIdpC3$&;QF#hu}2oGsamlX>B4cu-%}kMgE%4d8fJLQY)|*KP*<(Xx;E` za|n)nPC=EW*|@sTiqGUm*9=!;@W$!BV%#SV8`*&}a{$fmp^qxC57(bjSe{S8(Pv;K04N1%C*5&-M;P&Ye-Rc-0 zo=x)dzIes>`mcPWN11g-eZQsWhumhp`U+!+Z=%FHB}>`2)YZ9jNbJtBpYW7HuthK5 zUM9=T**Y0BP$%OLB+0$wsS?JY*P!Rbj4~-=tV#{WLV8NEPTjMsPFjbiNJeeFxO^~3 z)>@rB*_SE@rt4*Vev()oCd>CZ2jwj53LPrD zBk3t?3!Fpue^TP)6Ez~rQ7eFq<9DqZ``6Gv8Y;9LMx93fZo*X7Aj+#?e?pD3TikKr zxe9~JdEh}aYCT4)(X&vET6_7rWDm@q%)jeRPr}h^B=>X2fCsFLzfxg7-}Ax?dRE8t z7z-Gy$WX3Phrc+nbuM)pUxs4;WDUB#=I=k#udurY6IU@d4`kklb8@X=1~j{=$Cea5`|PRpdyVTF z)|yvt&|{~L_2muJ0ANkJ_#^ci^?KH>b!bsY9Yz-eTE5XEi+Q6*jp$<$Wx%e1dZf28 zpu=v)fZsY8nYXCfm~3QSdKEg---55-#P=I;nw(=l15C&Dxap(E+p6?v+MSECoR5cg z&IV5$t)_8q?wt!O>nFi)v$5(kWB2}S6m6%Mpi>U&ouyQL3xuO-pM)sXe zn8V*<%_e(bLf1a@qJD2ex-DO`kTnO^iu}vuz+axn^=Kk^JLBr35=E zrMJRGwx=*RJj_YHH};SxUtMKlO;=H;c}RmV)O}o4BHyc9C3pe7-k$RF^b)E5-Xf>S zF8&)&pXfw-^~G7GQY#B}>TGf5w*pSvEHZYzRc^K`k$-9_kSPkpvPbRdmQwCNOXbFE zGLSVCctXv&i5;l>*i?ac)5td-P~d278@!}e+`bs*A`TTxC~KIt-t&DbD6nNw>UKb zD+7Y?&j9Wrz3EfkfqFd5Uvzp$T{!nZq&E)4=eyK;Eb@nIN7k~}1)-$G9~Za>YelAO zse&wITQZP?Sj&CshmBRZmzxxgp53*Ww3Ruiuk7_dOE27S++UZWMjSb)v1Au_e2<3x z3~~ehT5RR(C*RUyrG>qc>8wk04?Vm!wHxiVD9q4e{7W*8b}{S?qEBvJ>OKZ)IbSdz zz}(SUel)4c_u_FL#k1F}Ewz;Rx-;{%$mQPU{v9p;zDW&%Et&LJ$;9#6WUXx2(_f9; z)bmUv?a##34H-z?n293th!dErKfFB?wbH0B=a7ZjQ!=pWIrA?G8Thy<6N`|Am?l}U z9AW*XkbR4q40yO@;_=l?jC)LO@>)84;xaI6J@<~xv#)X?LphtCxdr5}W{|tmlFxcw zfN!O&)!fU6MX1a8#EfGzsFheu-MC=tE({&( zsh{O4aT{D^(snoT=Qt_zkF#VCZ!Ej)n@Z_G8D`r|PN_Lwb~%e~ zcT@4sah2ZGeoR+2l_$-ciS?&iA`iHU`fw9j7~EXSUviUP0ge*#i{53&$P(VNNQ8Z< zXm*hsj<(8;0;^o^bqnJi5q`Qspe6uME@t}7rfE3WjG??S$J2f6_ zkSXT4nZt3leS8e26w@yvA_iG&$w55VV$6At$A>Z4!S`?QG79VOYcb_hCejB}LvcYS z_KnEI?r`P@M`hp*$C0@WJ;5|&dL76ruFu546J!w+GWi~v$owM{FN?@B-eX_Kt&q#bH-+xTjjUE1#fuZ_bGo71k?nT^iRb{peIl`|fGJJPuN z$Z6y9>3+u1)~Uwwvo*%n^nJ{@s+UVklBD13BpLjXd6(y@lERwNoSyVMqZjla7M-}z z3)0>vRm!lZIT<^mEP!N%RI(_^eRN-*B-z(g@a8^wLAn~hhN&>T zhZ436$P##YV3(g7QHSZ@HPHiyQk1A)q{hHj?oh-kabUCxS8LMOp$2jJnnfyzN27W`suqrDIci)G>U8}*g&l+@m5Q-@q!r&YcjFJXnsLMUz za6hs!Ey8e{Ye9#iFl?B?bz)7{_=ai_RE4@^ed&L8APm35LScJV1LIw4K2{A!%EmBi zvhg*eG>GAvF+;REd1;rdV+O>QxRx-CDb+o+&!3fGdakLmHA zYs_pL15`5%h3mOn{{2eocC<@nUcdl(t;gQ&28{VL7cE%#%ZJ=?0NR*t*0;D@NC$4(m#|u_&Y{=@3 zU&?tdEEC^3=O|myBbf8aIgb0$t_7I&fc*+zsORDDCKac&6VGt9ge#pSc#cx;d9;(w zR_X}nvj3%~4MtwKLEcJRZ2Hp%wWbFEr2!bZkRF*@_M9Y=p}!h{FRfzGqLk~Lr&@SV zAb&oS^YKe99;_rA$6krf%d+r&Dz%D6(?575nYm%~PbLrd#zZ~DhyvJU+0{|dwtzW?mKfq2(4 z5aE908#@Kz6Jy6muB&>GXH4X|O=4W>8L7q7h)g`S<@|d;6RS998-{0Lm}?eJJt)AC zS_K$?H=ml-`FPFi^k`Z>4mh@wP4wSB749MTB3j9jrfntRw}*6_VS`kq0yg_f#R>(c zKC;E;400-DQJ%i%dUYXvGWj`btv|l|(|7tL**rUHdGDbvnU(izGyTEmZpYC>nYjH| zCh8P1R=mt)-Z={%)9F85A)lIioXfeUDrSF&W6O`w)cc6aL2YDg*Ov0dNi6|Qo6Fc; zt>yZ%Hd3Xr4L&_kAcy@&OMI*n-Om<^wmdJ!_BM^!H#CL44Qc!wOHWg-m8%zP*?Z1w z!)r9TTnt7I)WT&Ic|xuq6?uGKBD3g|K_BiM^8CDaja+zbHs>R74L!lR4m?X%ej{1S zm*zGyA+MzjrVjnA&=xY}aWgroQ&BJ5B26YKkTyVpB?GB5`r9Io3%G|ENLGd%$ow+? z2n_SX<=5mH#|Pp0`0WT!XAc6OnH?j!7WZfG13#YFUO)@-lrD~37f&S9NLEIv&O%ak zYP2;kfMq-x&lP0z9mrQYP%ko;EJ1jxoSsaNPHG|gh0)u2?lJa3Qk$`p2U@>SqBXg% zY)=mqy(5d!N&|b&pPx?Am#7x?iI#8=+-L>T#--9fnDz4l17?RCkb9GCb`Jwy^q`kK zKPvv4gL~XJ#$C+Df!FlNTuKgPm%{rCIfs4JN_u;UT7+8_-Y0i67jZsSZvUeb@3VS2 z_3WVR*>^~uT;qPfSdF?Z+z}X{hG%)Qd*7*xm`>)Ld;jZg*n5~4#{4w*^M&la4o`)u zssS+{=q>V#+;-hm_BfLRFU&!o0&>;obAYzF__QGVe|)fYJeQ&m3hxr?NS&Lg@NTkP z;qAq*2RWw5>0SmINS)#pJM~g4kY3NldPyp)hG~&IBFef$|I!`Ho~dDJ;!gi=4c2Fb zQPYc>zYD{0pmjKoz6{4c&eM)tsfXxK#&aX}BKxGG?>*`@j>zR&lf8e-*iYCu8^5-m`tz!sx$FR%V+90Vl#y!^MCp%p@sRV z)1&juSe<;ioGKx+4D$3S*%)4*smImm-i7f#RSgIFZcOV)E``@~LO>5h3i){FmJ6WdpQ~k1ei|4LQR8^BeSZsl=YijyyNUC>JuQl^^h2A{E~2LKWW6 z$(bBR*xGyQPp<)X-l~7~rfErzQtMN9_9e(ZI z(T>`g_w@96T`5VrA~3%b4jq z@Hijic^#ch8D25FH|k+V;=JRfm%-I zwv>5f_I$=s$2X39*lM(V;Pu<4CWF#)Gfe{qq<@tnps!pZScE3eFJT8%yEfv`Kf<1VB z1M$3+x?dv$kbln)^~U-mhS$TNd6aDjxwrEqXBowwwJS03Db7M-qb$TP&qBXWS$H`& z6T`n`A+s5C6HB=ls>i;7G&9Ct=RM=~XHp9JGhaonWdJyFI^;HTU${av`Vop z*EaUYB;Wskyv|HTfS}B>WYF za&O6iKFosGs4U#&wJ{!NO#POLwd`+;OQ0Wj1IG8s1yH=nM_+e7KeY=G>6(t|N8{=c57WagTCk!|$n{5Zw~=gGfMYplVFFvc#=aQ4BFM|(z{ zSgx_{d{epKpdR{8#*Mq=;ZIY~w|*|YOmombg}Kt3AkC?V&>$^E)OFQ3 z!hHMe2JY-*q9%aS9p~%O-+3qJLSCO+oC}+lq384i_UBIs$J_nvPw?P87(fmA`_x1v z8`rKE`==@}enrvi$3U%ivT>_B^IQgVp58$1LDs7~{A)!=#`td@3hyK`guj;@7F}6` zlDuDR+ARu@`LzeXq@GtTZ);YKIz$c^ZTbWbDe;;H*M}6z;G3 z-VMiyd_5)xGnUq)huU`o#6rJDmEAP08$$ z(Yw^$#=Guz#*OFf5xA<8<~33!im@Vks6iUkJtFJL5N=QKz?d=gms-bKrkgw3-Xxo! zLcQT24aUW5$Vh0=vJT@!9}O;6T7lnV*{{GD@n|piYVWCAFphh#1A0`8%0_7oJ~wHM z?_cRzUM?3U19I^05#z&gg}28fY8~_XBnI=mhA6xbBvPA^UW=^7NqnJBy00K>X-yKt z6c2oE<&LKbZfJ6sIy?XHyjHlw=}0)bt_Vd$oe;P)mfda5emxcaxswc-c-w%%^;6OB zu^yFQkg;e;F7|N_e(^p%9hig3tr)x3(NBqAHzmWkpj6@QK(6skW9mhc&2`~D{69Qn z=*ng?kU8-X=OLKQUiGEf8D!neNUiH6^IHFuFehK^TcX9qhMdp(nW>3wC*}Vtk&on1 z&XVtYH9P~cZOoYJYcJN*?Dry%_Gt@`3$`Ll1KKkp8WRsEkW)0dZiZDmYKNYp2u866VZ;ah{5cK z(a!XHeVvZ}qw`R%hO>C)TI8>@{^&cDI(H4pOOijb-fbu~SW9Se%pcmx+>hpH9x zO%iyziY8b-Vj9YVD5erbpw0S-}ZWaS-3%gwq4nCy^X%lm($_9 zClAU4_2txC>RNUVKzElYg#S#(?Y((8KeMrP$h62x`u5IT9gRCH(y_gP8K3SqmQzw9 zOGf*lM+*7M`5E|U1ohFTHIktGaJnDITgvCP>^9<7lt@_ApLkcZkbjQP4ZZnEJq z`O`PlPrOe4%RU2xEqtzKHNTJ-(`k@T(%is$1 zJ*Q^DWbb+svaeV!clE&rj-&gTtU+uxqkm!paXwxm4XIZ+w=d7XX9gM%CI9%czL+K! zOVJ!Z?CTzd%X>31HkH0IzntV);16ltoOzCHjz>PvqiUHE_pGj5D9e1vSwDKIMPp0l zbc9zlW5tZd(s*W(WRR<^QxFY#nSp-g%~;#IzLblgkI^$;pX4ZXo{@p)4f8NVI@am-&#NZP-|J|CY*w1_5a5K;DhdbEkD?*z{;5ftkOgTXpsTHlUvZ zbwxJ@=b_31J1K2$5l=I9E!R@N(j|l3B>llBG?XXpev6WNroFSGa4azct9gB{pQt0< zsi#?+b*G3(a+IFwh+N8^^b1YoN?x)2{h2zLypO9Erc;C3jPi9HGbUE3Ef?sQozyJ=2YYCd{UHPOIgW0(Y9OKAe#vw4uo>i4 z!-MEcUdN1+q4olLww34jE!Qg=zIW+UA8AHOe-}CIPCZciK2M2{#`!-okg=Vda-_S& znu}$6Q~IHwj)Fbsjrbnq1SgUYeepxiQzvvJdBEsu8EC@sa;|v;8Rhhw8bjn3Ymwt? zkbxUq=ika{CL@Zdqf#;mR8L2wA``x~&Dg;F!X*1&lI2fb-9ynh@GS#3znQU1 z^e*H4u;{L{L}vYz#*Vzsm9@BikUa83>WxyX=HjYi8OV9*ts`rCJ{h>>M6Hi4&7|`F zQaL+~zTvi7gimIUUrkS>9u3$>|67{H_;Kw(-ILr5G;7c6On-Un#X?!g>)E=37I!={ zF#2EKUp|K&vWlecRA0oAKkXBdjy%SleoyS>o7y7%!l^S`KN_z8@Hwwwre#5#+?q?h zHs4Uh)zaZBgCzDH=)dH>LC^03nJA%CoN@FAU%yv}ZaqwB*x7=(Hpw!4j*_*FP)ztp{%EQRn|@GV zY-)-qn1iq0J`9t|6KzXpOGL*WXz@ucN8AIGO7=?>MPVzwE@()CUZuU-NKscFo9V^+=NB4Q?2f6O7}D zDJYC){+WKn_PL4DQ>DVQsml@S$Ll#h8~fR_5gnBzZ+5D&n7+mb(}f*zv-V#-YWELqAWh<3hlok=vhME^NoTM&ZzifK!Sh(km7mb>FVC91G@q-?@ z8%^jqkZbOL$!#@u!=|cX7&e=0;(^)Bp;$5fX1v@^QQ^i^`b7Ka;ltzjHll9hz(iTM zpT5tIp@2b$kIdVeY(SGn)VJb#drHSdNo?qb`}AQqmC>U!YY5kVSs;yLrRyG7 zOs1aQeEz?+@6j)qJZ82gR)%#~;@uYdT{WVL;%_G<5 zMb2>|byT~%;dS$1Y195GAJ63qhTaDY&|r9A8bYYum)jfok-J zJraU}CUS6mo^`xm$qf%kF2}p=vHzd@d-vRgUqM#1X^|*SRp}SoHw@{csW18DA*?A@ zR8hrBr&J|coejhCw>o^{IBmJWidW7_GWQ=PhF=Py=C&T@3fZ`~+Cp8IWEtC!{Oo}c z^xsOo)Z_p8cT>l3eTwL3F(1X}E&mn$;(7duE>^@3N|vdqDtP`3!MW!;_NqU`sJY~+ zhf!aZI}u&^(k{b~?qHM@$${S4FIIA<%9Ww0?#sPf&uk3%%ZkStvGQD_gpTj~xCiH}&eSdSR(St>Oy6*m zD+s--2U=5!9(lo-PHuXup9x(iQm1k~YpO!M+MVRn z1~4ZZ$NLiYzvmgfpMNrL_j+aA(xid$;)X*;`~0QpTPklfrnK&4v>sjPHSqgnujqR3 z(`xmMGHyQD`+TPMTh{~kY}0rAT;b&q)-^q=dZgF*+SR(PF1(O7`|TR97JD9^-~Kwz z_+84UcZ?kEnRju@xzmorjMJ{&cy|(YP*IUfs}1wSDXtRB0F4CC6fM9ld0iTXIqN=Ye?9R|jpZZDic{7>x8Y=XMJMtT=F;S()pA+1v&!R%l zu1bW=Qo+2(1C`IH;q{2UgrbJ3whBke@wJE956Yg|er>6_7_G$ldCV_s)wo`u#+(fv z2(-=R4`iY-dXD&zmgNdv`^Lg*Hg6u8h+|fejhQ4z? zX~UX=nRV<{%%QO#_kMlWh8i&LB+-xXy#f8Y>JjKk-Q`bu6f^IiGs%FRzRW58mv{R{ zUoYk=R1OBbWZtR#F6v{b4anMJ!1#8|v8<+MBjZ|YSMrL3vayHxuQcYM{_}%gI6Iqt zoY~N}XDua*dKJvyjc1Le_&z-XnYXX@lOL=<(Z~yxTI66zUN&Z)&qbe3IdIxfZJv6p zS>MP;w-xjn;qQZ%WaF@bV_ZpJuPo-Z&Ss-s1ih?lXXDd1YC_h`##`q9H$<~)5XYtsdDZ7`5^#&;eH)Nm-4;2Jil zbe45c_V2BjVUbQZ*&ljSfx~5}%lP59oY_($lV>O(^!9T-z`SmdMXr)%Y_y1dYr_<{ z5kbF##jl&PO1Vh zb(OwE96{&3qCgo*tF z&?Ag`3VDH;Z6aIsiM|&*0??f7qeB~dGJYd#wIT@1+6Uludp`u-^TUp1{F?QY2x`;a zOz_9BO92?MpZakPVvyg4bzScB@A$KZ@rL=IWz=GvK|RH;)c5Jm9Qh-9@~zWi3BRA4 z$lN(|HRZNzQRxGDstheO{m4E}rMK-OE$oIf&rjXPkhAoPTEN=%T-MW%#=zNuT6D~B z&y9>huU*`OU7$`7Yb8AzX;GE0FP$92eJ1PL-_sFQl#T=MGw_2s@Pb{L_{Ca9UIH~4 zf--U4jowl-+2`*zKXQs~voNG- zCTf3X9xRieJ7=Otau)u&nu%F|@_78)Xy#~cGS5-Gl`NNuc?9M{@;m3l>AV?V&3U-p zj$XFW%(wGrp@YdLE~KwCbMb9Xu)gh@j{%?ZQTGa2EAH<`oT3-*X)=pP^YPQ0?3C$0 z?VJLbSpS*xFLmU~uohK5AHHpw$DhaF8O^9rjsAtVskd>3tQPmm<9D%Eb(1+DuY6n| zN8N(&Ja%_?@w!Tnvk;Yh+u$yVyOmOAT{8*2kEk|D{MRUBF)F^hA5p`OL$7iKnB6D1nVHL2?ZZY}aGUKdr_FIVzVgL4r z`X!Ro(klPyNewI{KU_(HFMY_U6qQQTP>Zx%sKCG|tN0u*mYm@wa%&8A8r#@1PS~IU zeYQfHvc}X-f$Tl(RlUSxHL}vD&?2wsEwja4!FisZF7&<0JY|)BbrjH8O2w9a+S^L} zFeNDv+8Cje(00&wLewI_T7&@R>&3-|fKtpj~4n{r%b4aL5vfp}rVx**3`(4+ut z`^GW2d?;qDBcHs&AHi1wF!&zpl&iIfjflqepcptg#^4*Dd(S@n`OYYe*&mI9`qV|e zrA1{GYls{>mF;3su}TbT-HL|(0lj-VXpvG7jhsR)R=3uoadI^5m}A~{UW*SGSzr6_ zSY&!?TxR}sx)vwHwMZ_Z=gfE305!}-e~LyC$L~4jdA8Qi#OfpTue-_q$&p!DT8$ct zCo^IBL|+r;+SbfU$1~O{>-8b`dz;Kne~vfuiu!@%fjIsg%2U_Wl`IVNMeQ@P(7>0q zJJvW)aXi%-N9LGg=K*uUJ!g_>;0 zT~*eFS2Qj_MUF2Ef4``XV_Ne{8@+Tp{!Y7NevxL=+C5#bXrI=v)c^ck^zyn9QODTt z(_dbZlVa0uoVHJ2)P9H2b?{?P)qsg!?$eUfew1`E#;+V;9Q`TWsO@^excAmHuX(L2 zrANE2H~usIUDt5kGUH`kZ=>O5<8+t#{~GfzWf-Hw4|-aL+NSUQbD!tf$UoB!&B~=m zS<9!#Xnq)%rO;oxfkFQLN?q+rsnVC4C1VZA@+mV>j%=d7;{H^zQnx#8aIz$_FXgbE zK@M!u$(h^KQi{<@@Kl3rUzRApo9U&Z=AcBpO_h^BlEf_~QO2>x(vlk9Cw&rRlA3Ey ztwC0eOp^5t=vzI(AVp^q;)#@{IJ+ z$WUY4Na}*jq_@~-H5PUAfV!;;Y3r0IeC3Xpz38E}L5=ylRB&CbWKWYjDqmFN(_-p) z-%?}aId_cVerv`d`jZ*eC>qY!zEPvbKK9lOVP9g78dbWJeN?kfr(=DNxgLN1?QHKb zsCtEAL8JyXx#rtkIUHMZHE=%~1}AF>`mui3X$o^x7eW!wwPNKbVVKCeUg;3>iMe4I zYz@Puq0|OpKj+8(8r;81-{=KlxaO?E(8y3sHHYE+UJdG;U>z_e4E6Y$rEX*+D~I9L z5e*U^k(X3*y_l&%swEW0PdaQ&V*lzH9S+Y(MeuC)yFAt7RTj1FcXN&BPHpZ9WKQPN z7xWd^hDY^Kmr`qSkO5DYkWW0PM{BMty(iLFI#!Ruy7W5>G2k56f0ITTQ06;((EcH- zQi=NC_6Dp7A|J{8!)n$fk0(%XihuLeWWeUf1`Ogl)YO7~a&@>?TWvzc$Jt14mW%Bb zb8w35y3O1Jf9KjT!HK#s&binal7sq+T;$Bp#<}opOk@tH-7b1>cF)G&G4v`O%bF`| zW^c*EyzE0Q$6@rE=CPKS@b~sP*vPeK)M5H`I+J~@LPm0BHf;G3S(&fr-<~12@_*`R zy+fVl^7U47HC-uNyw!5Jk5Z;JRZ9Cm$mi`X7RR-vGPAT){7JoFM=i*1!-^!C6oJeMmb@O%4$WpUr zaDnqi?pHI0Q4?{~X8PA}AfHx~y2-~~<;_r6c|O!h{u<{dJKi*tqtroe%~<1~r$FY( zQrUV~fzM-Y(A!%9GyB|Ua{U$AF$jGbS9bgkMAj(sd&$(<+C+Yl>ng%Dxb!bI8c%b5 z)0=Z_pDc9py1<_HEI635;1t01#|wHW_sT~L&S~jacrIKY_%9=aZFT4As-zP8cA^8_ zWSzTO#@^+6mT_@-pHjI~LxHX;1qL~hP3fgT;TCFa?G1p}f&gq^6Np}e>7`sL5R+b0 z8~8r;nz~TuiZMoCH3qY`l85IS3J0?oN3*bD@&yzR%ED$(&fAak(cdi}lE^*^@(xF5 zo1x{L>64_AVev}w{NXBpU2HCUR<#tr4E9z$vqTfxGhFSIGW!xWEZ?`3JE1Nz^lJ-QI@Vq4Py^ln zhXT7!(gQoPMAq0V*o#ij&MJZQ!eLxK9Eb~(0&!B~kNEP`N8?)b@@d9jUoDz0WAA~H z{Qp`lB7SGWK7d|&A>{l6GO^)&Cff1qUK{E8#_RFLKOcMPfgSgdOh_j6uFk2%?V4IX z%xEp4)mzAkDE5prRmp&08|?73!KM8Q>?u^h<(3WR`74m13xH;00PLIs;r=85?mzso zaToiMM#TW(F?e;1JwuG+h9g?OC-u$0(ub>*HNrC zWI;Z{_U1$Jglywwy~I%G4}Vg#_s>)btfrHJJ#-STW{&L+y?N)kqiZ{IV8`gyX;00h za^ZNnHw^Fo4#n!F8Z@}4!P|+{sO7xno@9U*_oMYK>{r&OLeD+y)dkeFYLbIieRFY$ zxT*?z_kuj$- z{{m|t1uEQQ%6~omQ2V2VF#K1IO;P_*C2W<=Tu~D(c@@M z>O@|k-)kK68vJ^8Yw|-M$jmeEkothW)BO6^J;oNE&txBRjByI@XXH?8wq;IntHS%T zf!d6@VJ2+ualy80U_~`|0t)8q(RGDr)3=pkN0XJwEd`s#b!IcpQ4{~ z68#1^7yiiP8rm}p1IlLM#{PW7P2#%t7kNF-iD#?Or}sN`uw2{9=dDVKxTuz6R@cj%do~21CFjH_Z|c}r3qXl4nYbVH zzxJYz?)wD>|U~8k*s-2 zX(nn^EI_xvc^>De!_4c{dK|qHF6Kiso%)A8JY+PP!HtZm~tZ&AxzZ>!jm^&CFl z2FtIONYHxjSGgBGScbf5sXuzU(gS-6YrxaV5jt_rF+Bz+xz^bKjXi0#wqr=27_{#Y z!`yf#+^+K@g8rg8?CYvTkB0*05|%MmBr-l!rY}Rk0yvb=n^Kz(=L4>sDci}^`f8c< z+*x|^o~^sjeqO5$){Q3fey&tbIN4x3S)ivg6j(Sf0GW#dal2&z)U5-s%AbDNO@dIa zQw;uKO!pZ>U4Hhnjlaa+H$FeB*mpLH=g~*Q+=(~isUi#W=Vak0a|{W8=A#DpOZ|KE zqb>JdyQoj?*<5=2HkB*yxZWU#@1=8<%A;Il17m24qgCE8rrwYGE#pSm!rY(z0{(n{ zI+FF&aXr?Yxhrz0%bkZ(LyP&GZCch|>GKg3jW#^D=vFcK_aWnGXX<40nv6=w1i0Sl z;?4LzgSBwRtA^#NNqw*Y)jqPfV}TjgE(V#~G+BO{ljPjo6#1>vNnv?K?!{>sJHyVS1b_;=i+@IKABmBq0hyIU3QhBTz1H9ewim|lgH+Q6+W9*70>%E8hX2#El39Qq7(opA2!&t4M zb{e&N&(p7uIo=*Tuf-mzNatMr;TY#YSDpv+w6Tu47!yj3bLLuak)8g;Iq*%O!rPJa z;%w^vMJa5&Te2_Bq@mWqQZn89Qe@?7>h51P$i=VB&rea)-&KtO&V#*_9ym5zjcZ4F z4ld#Jk)(dlGRCstFpM6lK`XCRY#UAApBkx{vz$7*8&lDVabrz$vhQT|ex9L@<$zqM z?_{H%F$Y8MDZKlnQLmN^V`>I98hM?*y0Gs5jr+~v^pdi$j(48iU^?&DPxdSr+;MD$ z2Tr!5j{ihA1nyU1>IoHoZ_r>wk1)i|<~h|2=bnMRXMbyOx&!@=V(Dwtidx5y3~(e* zSdG`G+{&vmWbdL8ZUEysrg`f8-y#HqW*x5+o-D1%}35!20 zi)QKMnSY9$4@r?b)Q=q4llsP6-SN%jjvN;iHm9kvZKgZ^zNo>TkL+z@481p)8V5r5 zls^l;&v-G5bu1g^;0IF2fO&rhXT~wEH|k8x##;7tct*3Q-%1^T4ea}OBRd#MAG*ct zqnM}g{+>x~l={?*^w5jLyHu%t@u1ASM4jwgdO80^Cw+IQaig<4?Cz>@u?%&fr*nUM z%LDVz^IQ%vW{o2c%h(mdz2*q+ZC}5lUN-lR14im`+p0&;AoiOKpk~5GEC1sQmR@aTuY>0rY}xjh^DrBI+;T= zj#F20^5)+%Vjg|5g&M`xGax(7Xb|fl3FL9Qk+WO1nDg1=479IpMu&!u(lWP5Y_9v^ zmYRH`A_I$(KHzJgdZI1-EiUBU`oxo;Iz*kj$$1#sklf;=B3b3)i->?|thO-M*4T_& zzKtZ?u0&o{^2Ot{D7>1N0qwOs?6YYsr#G_pu$2AP)5xPO%EZk8a!(O<((wCt+4Pq$ zHG`uO!Jd5EKh5-@X(&0Je#$oS!+UabjWp@l+tCcwb_ZFc{KfT>9~_yhw`8Sb*R4D} z>rhWT>2rOWI&P!aGdHQ^{nF;)@1O=!pV!UtiVxnOkH(3I)D0~D0K=gAk~ra)1lRY$ zt6(i|Fpu}|aQYf|vXg3~e@G>zAD;32oyfx;BWEl$n zsvY{EyDyuMg?C!d&{Q zQH^9|_Yyg@b_nkL8HElzGoen&gU5^}((6g7+-2Uk|CMOiNG2ww=i$xz`l2pxl^Lv~ z{Kq*~2+zO<9{=WYpy%sX41afVQ!l;k&S2X_U!uy+I#y4JGMfsZ6Wv z4^L|p7Trk4)?wr~-`0}^^KZHG!4L25P`{7kw@FPimL7K!FRoFt5BXv@`QlA()cfQ8 zofO(cEaAnn@zf9$^@_&g@$}I8od;WKD1VnJkx|q|y*)M>O*W?E*o{2aRUKpy`L%UV zsE^r*S{bG3$R0)i`qTDe7)(F(5!7{!V_!cx)6tXp{HUE|b8L~cm`q;pZZy51=r2#6 z@zw77vStK%$v1u&!|^rPEdvFYdB4Uqlxo!R{O7I@8dfG}dNBhw_S`e?c9d;1=o`M& z2iaAagJ+I=d?Dwz6nn|o_d_~N^o7&eD2(dG9032{KXV(%a^-K?N8V)4)-7K z`yX_xFU8st*)qi!>z8U_-#rr^pYx#CG?Ji(#o}S-kEhFcKI_Txk?*$Y(|~&Jh0-Q) zFy>TZZA>z7Ix`Q=$~BSc^M7)T`QmivX!`DEU{@tG=KgFbc~zc`O5yrjR4Pq!hbN#WJzTANCcaal?aNXI-g{!RP-0^;NPK zkvndxMZu+XxbQsJsF>?&QY;JMiwUi$qfm={WkuGUERCd^k@=JRKJXz&*?R?_|Al6} zwrwhpzL&__*F&JAZsV%S^pCE zHf%+Uj@v*hP9BSw0CIe@JVKGv zSBJoMCj2>)y($~Xou#SpmV3f;O8O%Hdj>1PsxVOw;_dO*IZrWMM% z^id5_;!G-a{i^C7BoCqh6Nj|Q2OZv|?%SQdXRy4nmDD@jE@jjD&&Cxm( zZzq@3)Pg^m&zMdAZr;aWL^mN%dN&(20-5V*L%qvkF8CH12K9A%54AL*w=H>}V|zsB ztb+T&V3cd2L;gVeG7EXAGx1{c%M}5;$)Aqb0$VHsvfiF zQ%A1{b^4k@lf}b9i4U`a(eWVpufF6pxJKRAm0lcE z-Pqer?(BdLN9D}F3LYWpqK9>IJ*Rt`rA@$C6iL(C(Ih>=xxWu|fpM56y zU9`X{JxK~otOL>GblyW9PINZm3c0O8r;@}jPl@(Q4X)MIBYpuauwo=@cF3h7@=o_ED<`jx-X!E;bHqS$jYrCXw$awFf$ap6Ob)j5*6nK@SW z^^l{qy5d$ha&tjCbY1fhopQ;yPEC*j=jaRX90vPePQ?u|bHcFs1NA_Q=vzIKIm3@} z@?;hLj*~+%pPXaX=ZEy|qOM=Pcsa6AjgIm3%U(r2M2r ztybjbvMgv`6fcLU$J%oOeXDuh4C750@t!}Qo+y>3sBnwE$y>gX^L=eXEcFCkFT}~| zWO9^qm!k`FdsX>7*W`ZUkJse&e!8Is^+Q9dvfpbxePBGT)bEIsw3TjnwK@dT9CEY-I;HZ zdz0g+_Fif0ufmtrp)mWB3w~w7c#w*BrBK?+-gO^cAcbBkM(6r zDE!*8_Ep6M*Dx!4sS@M`{oI<=4@Jk8df0w8!GYJ|^QdIG_R$sdJh?xjPU1Mu|NS_A zPbb95%F5JpoECzse^bwtM0VkN)p(Em&76 zSqc}b@U3V$+B+EFbd2%hHGSS)lI1G7@7f$+q0B=hd1RyRzW+VX7(C)lT56cZSpL8R z&rAEAyQV!)G>&QKpSJYILr;&dM?Keni|E?gUhn0$x{TL9F^$vfS6yLL-};*Nhihuu zgTqQ=`>d(P37=M`y*fF~%jWJa&yPnxbq2 zWWU$ot=Eld^&*XXWv)03Ujx7F0im3anf`t-2Wm}wAI zo=zgwsd8?IL3X?9WJ<$>Qmz60{`%}_d`;QgOZh$Do+c@Ascn_t}Aoo`3C8*nqTLoNbKnp*-MR|4CfU2L@$OV zH+f9{?TxGMn8f*R{sDI!q26nydh`n1L*1NR?yM`jM!!^syE%y zyPO9a-C-=|I^$onI~mXqp!l^S!AFXQP2qXikXMSMNM0%6l3q@*w z)@_&v>(n>|{~u{*9n|K#wd(}x?gmuw1gU#z*G=6iUUzp_Ak^KEx?@RzQrAGJyCQWr z0@O=^0y+2I-+Xgs&cA2RbSfLd`%7MVp0%!Z-4WF^_!mr;opl6%*1cB-hGPC9I-SYw z|LMaz{Td#Jl?LaJ>5+7X^9hUSQsncaiJKnwfn*u&;xTO>>q0AZ*cQwF@}_u1JFs3g zC?1uz=}^y~{b_zrw}$M!tkH8OMUPXfba;G0i|AcC%wtXc$vs~0tMt%aWX+;8``kME z8F`Oy&6-^OemV@fL!S7l4sVa@P^B_^;_*5hwr9<~BpsHV4UH;hHX!R7iL8xnxXjwz z6J`p2Wi}w|8`*v7%W)#-_%Izq26BFr_rEqfm}kQOudifcS4+-4uuX*FZ8g8ej1hz%b*vCbrZfuferInW|Ds#$66qJ61pB_AA38=_3O?O z@|c-@cFkn@Sw~51?I5rFxXK=Dy66qfBzc{S?3ztKkHJYOD3Uk)`}yIna&k8JqFtQD z@iAwBraQ}qNsdy-zp-{y4(EMhC9_?Z^9K z)`$QM9Khbf0QNlA`ynRF2R$_O$K3YA(}O-(H-s*iVqffk7YNljf6TV_qpO48f5IE) z1Dp?K-T%>K&Jo`5$GOey`R@vVbw6MHU~OiORRBiRpcf*=A2a6qp^@GP`E_jx6j*flsiI> z>M1!Z*9dH_8o^$3Bo4CPFfxYTIb8%&l34E_6oF=(RSauM?vcNo?}nrD5B{uKTa@&Wmy{^ zMZU2Qod{!@f3=Pdf>+Et(9_$#EEq!<#0EMTH@iv40V+B9!&$tpw~+&CcUdvXU8)YY6Q>C(*;3I#E(~#(iu5oJ zd21(~R+Ax~(M+6bs-)a+H|fP(i3a@ImXF9Nk~!&AMTuwgi)9ZP#`S6oH0;2PwQuxX zv{J&>g}ejVlm(7TjHYjKwzF9dyYRZGY!+uaD7M!ukz-$rMf;On#%Tq%@*35TQlM0h z5>0v(%g5?`?d!~tEU!eDuOPx-x>4}Gv|f-iR5 z@WJ8M^q#z>|B(#hd9sHImXUax7>-dXgn zftz?AQePd?Qg_H%pLtPxbOWFxhdaNXL z*U5lvtvvpdAhXzGx}T_(-={be!|$6-xA*wc3G(}Byj-)>O2}6-kJS?7<2EvrR}2M?^D0-Az2yS8LF5m> z?8^RhbpKM}elInSmvDxSzw#cc*)Mg)wJV&R;?KM^gxDg4Z)^M^mu>QAZ@k=nt}9i|6+aNmIm27G-w#gnZy8ktPX@AZvp)zW$4%9KIlzb z&aw37oJzq zJ!142md*LSJgx=LaqUMp$*A+35B^X8?2--I#~YG;~T#=s-7O@*kkkO zYu`Gh$KW4Y6m4Xd-gxFFbYeCM>kftdo(CiJNF?8bM|7z*&cJ@oyEI##0sC{zV&Gcv zp_-0H5ANHV(k;UE;OkH6>}`|fV9)T{an8H4-@9l<23nKLnMKA!*)0=SxHj}O{*P~L zNDga7F|4<64eClyc_ zINclJD%Wo|m40Jd%B(5PW%48iG9Pih^_)47FS#z;roiAs3iv$=QAI3Ec2&tILaa`GW#>_<=S(1snp+DE|qnYIppNGuH%}K&$kEN$vSLj zUgiuX>Mrud*%f|x)7}pXvKKe`Y}j3gF74!Sv^*Y(m?S!=hekr*FcN{anDac(hzjM5 zIQNhBdh!KviM;22G9qXx{m#5sRqn_2LQfNp+{(d%EjgHUhyLSewS?_!CXS`rN!8S5 zGV_{R=6fmeGgE;yDW6pZ^nNwh`{9(yADuQwAm|C} z_@5#XIfu`h&h-3}3-PROM3v1(lw`}%1s>BT3wRk6XqRo4?>!ZmUfmxL_t8JD z;LJ|4FAiSuLuzj_Gxj_1YiuMg@VWME3^|@=WG#E~eJV8x@QZDUs%4_E2-!CodDRm*42S9F`D!1CP+ zuB}RBat*U=)G1N_fl_U(RMDVJL?|;+xaYNIue>6excYh=t-^h4AMRs$Z@OuhiBqioPF&Bra3lH| z$r~u&ai8f-9xg-SX~ml4NPF^nhxz9$h3DUxSlRzVD{Xhg$;T>m2~X8YeihD74pSqj zuPfw@8~${6MO0@shL)&NrXO>Ax`pE8;t=e9u7R^t2v!^+WBFQ#^$oe-UaUjzIQnNN zk$rfmM`snYfuA#Dx(pqNkLjK5#(ivT1|E-6cqZ*oc-CVNLUlpmY44@<sz)l@AtA3=zhx_w8YctXH7CDUW%nJRW z@LWLG--Omm&jDt#gA)~=w-s91+crsB>`RnepXu8QijgUu;^k5xYtLzFj1Ojp=@(br z;d9lW@6TFa4HA}-OBtkrg9~dIe2@N)4@KkIe9p{d4tH}hdkOKV*p#dc8J^9NY52)! zfeqi66Hz>lR?IX_WQ~CDNj$kq+it8O+bccKB#_nnt?+DAStpm`6Q!=RUe3}3_Gg1m z9_`jiu$n$JTUQ)?szMV>7YupiioX+>zj2s8D+djBC25c`A{2xAg+gl=j20pEZB^i0 ze;n%_ZaR2`>QS+FJX-!HYmvj*Zq^xm&d?FOlXZ;h88FZ0xx)Hihh7TLCY$MMtVOpc zKfgQ74V^tPLFiYLU+3b5E&@rPnIuKNYFyc?#*^kee@2kcJ*Gx{ea=;MrynwkYlFS? zF6T4fV|XZ^C84N4MTc6$^r%`s9$8n&6(#GKAsmkr_H+~1BfI05iECfdk=`l;W8Kqv z|519b_)OpE9W$msA%S*U;pw|k;kh@)R+cJVrDhuEH`}QsWJEKudC*iw>q;b=^@Z&N zEs)<ON-jKZCYcG% z#ev@A2Y;O9&qh0m=W#fcvczfDIXY~%K-M57{J$vRrSON<9X}l6{%8b`=f*vMxOJpo zp8J%yd}gJ@Mxp}u_;!yY;Klo6f|Zdx5%=F**H7oOb$K7|33&fG%4fvv_2dO+kfScg zS)rlyBPNjbW@bR?!7Zd~VLN&H!%coY<~=&bRdS4+>-4l_evk!oQn_byR3LjyiRi2Y zFm19wRvq<6JbSV2N7D7zCII!g7s?2v!?HK`H!mYl`7q}p8%N^ReeUOn(&1Z)&f3!S z3fo`8#xkjNJ>>wWv!UdA-o$79GOHZS4o4DR;B6Xcy<>&f3K4j9(f65;l`F?#3@JGd`k^JwBL}MS$kFiz~ zmJ!LmI-mFbQV{J(2mS0+9O63TRe+KAEixSMc`W4KkKHk0-^wx5sZeb0*yTogj-t=JWh{ z?tS>2IO0uTBed;rK1|Mrqjs4#2GR4 zZwd+%c<%6d-=r<)JqNHa&GRQPg`QEK&y&6A)x4z>Uz1LnI_c$;N-x8#5+zC>FXuX{ zP@cZ_XLHo(mQB8UIeQ0Z)HqR#KHs|D8{xfq z%SRo&xTc=jFauQ;anF%!(?P7Cu2y(9B)?dj&y7DJ&*etI+;9sl2)9wYC6L9DBmyTHCkV?IZ_b8Wsl6Vu0%i`&C{ zAz8G~!xf%m_-y?|KhV3Z1Q|wmeqL&#G#L>uhYHyT7?~(tpSWR4mOFlKbcOXFSIn7D z$M94a=r=N}XoCj1%23{~Ll9>l3cFDH=UGplvp|Q=tZBy|(P5(K(RU&1)I6TmtPNl7 z!}q8ZeZDCf=s%yC*ksGAsFa>tc9XHBFY>CD(zE_4GN7y2uee2quup=x-DWm;CH76L zCrN+y3Y>Lrn5lHbfCRb{>|J0y?SiLf4GJSPIBB85+WLHte$sO>QN#N<=ekDfu|I_@ z;|V=Zc8h056J3P9oVkj~Kqwi{r*$&m$Mwfvt~rjrpwolLVeGH;Y{&cb@#%EvJXLr; zoX4Dk%s9FBAYL5kYB0{!i{-UM>A%_)o9DWq9(m7)N>{X6#g zzVsb)e&cOCT#+i5?jmv;;ALq-Cu=gK94u2tgvgzzkyYtxo{9m52<_RlF$o(tBpK;#( zaTrdXOh#=t6IKtXFK+1ta*}&2|NL;?Us5postGc#iOinEoRk}bQ1?A^K$vGbzbSJs zYT0nMiS_ZG^bDS+r_3z{>zbI5;8{lwcP^9At zBN|Iz&qA4W+6QCwtc|rGFTF7fi>Fvi;jo_@YJZY>SR0*@5*e8U>@^?DM0ut>h` z@WzngtoJ=j!He4DhBjGAN!fe})-ca^b~yAttZo0!LLKstBaOesnmIC)Duv^0=@fMA zkcIwD8b~!V=8H7m=rJV>woO^DV|{vD4I8<%;IGKaLFn3zu7FBLDE+f=sHm=#ZShxD z_4S5+J3WSjQkVrzUQE|OtnL4b|Jy;B+c*q(!S_FwJYaGYXdAk!)bUB#7R(+ zo)@+Zq-XF@3LYnsYrEf2vOg5b;r8Bm7e-Ev|K5H#^Qj$e^omjgINc+$o+-wWhRwrJ9e-(`G&{o-NIUyoGp}#2feYD`QQ)u%+A=v z^Fi4_jEz{!Zp%!c(_v_xk%B9~==Z!~E4?{mu$^^?PvK#BpOy@_?k1$UGH;!;{Mnbi zaeP)7qL(qBx10%4rmjS%Gb%^ z=f16hsmrkW4-@pEi(Ck3VAOvsziNS^%4lPRm{vn$U&3OP6nevXdM8_4Bp`OeZ5_?+T?(Gat-r8;(=4^nEWep~vrrGTWy}My?}AIW3GHtQ0Id zX+n#!wZ)elYtbljh2xo-@FWEbJDX55sGd|h!W`jxzOXnDhC4hT*4@qma_h?KN=4Fi zurFTmd~RBhf&iZ9s(Q7h^VGjmVH$I~N066HV7@TdtD*gCNx;N>Io5$W;MU{^)%3JZ z%fd8wJ5inaBiWpHtUNv(Z`rF!2d``A2BKO2SE9)^yUwS#^m7VYzBXZONj(`tUbtl^ zA95vODCYU2>TiN`^?IU+E0A`he6Xx>I5M46P`-2)JRdZY!T0m!-WzY|5}1(`%zUqc zEL`c*K%RXokxCQ1@mEQ&=;{>I=h{e5uCr(0Ux{Nr`&s{RST!Wy9hikP;r4QS?O&-$ zZ}%o%M_pOVxiCKqV`ke({+B%QWlnd_D!z_W3KIGCHDA_~kd_5f|B^RO_X$Iv3(4%8 zXQ7w6v5fclC%qex16>)8`s71P^L>8P&Q^wa7fRV4zIaiFyz`i3bem|x_J(x2a6j=X z&Kv(&`|sdOZ)xu=%skgbEcAu)GRX(YKg03-Z8D;VlUsaOUk(~dWCVFY&FXLj@H`1` zn2j~Z8_VY!3REBmts*yit_JzjYhUo|4|&^cW@BCTL0-mo6TO_KVtM=4 z8wdC~zUBR@%YNoZziA*%$sJFxM?Ud(7}iE4W86pPp_jIj8R~zs&CUmX74$GprdMQw z3BFtENEZF48RTA9z6i(f`Sd0nBp*7Xp3Jr|ix=<12RD=B9+iSY08VV z#!S5yJN0QuBGU8(dcm)D`?hcvXAWk#jK{ZjL(BN{m`Lywa>tjtTt@Ot!}B^{CV5h_G( z3dRPV7K#P*pj9lv{RIc42lQH-A8Xi6~BV+OrxvrGi6jQeSEc*H*bW_rz9sG_9*2IfjP zVMZl6oh<%bw^rQSRyr)|rB0~)Ybl18VNIh-I_p&AgUDO;b5vpKUe;wsYO(tddBd9} z2rND<&zaBLg1H{Gb}|=&Tw(L(W~gyUg!#^Wmo7sizR&Rw)3AnoQ*U#u#Me<_9rL@b z8fa1LHFI50nej`-{M1bInfqAu=hfxx~ow?!ka!%UR)c!JZ{Jy#PJYlw#T8cc^bU0(L=YJ zpVtj%cx@qfHiN#)_GySa&GYJEoVeasAuy1>xrWT@WQ|-~&5YqIweo?i%ZSWi&Tnb4 zp$d6YORk+;AC^ip)cCtTh`HBV+_&YdDPOS=zFGKkq^s$aghdX(_TAL2Z^7l?yVdlS=Vjj0H9j~gI;afFI_B38=ep)Ok zlZFyc&WqEV*}c6A?KTJF%4G71ypGZq@cIosBBpvO)ZV%bJJPkR)jmd}V%Hi zN4yRpuS(AGRv&sTb9f&c7c2U8Ds17uU+Kfw&wY#;{QB>WqvdE-CusgGL;DqRsNI-c z>Hsr5Umg-O{hM~=E_K_;vrkWl?+RK6r`&<1md>v5P!%!;j!b=xz$9ZE`C5KtoOjbq>_So=Zm0{wQ=LYMu z!wp*#U6Ma5@(r<-)P{pTRXzT6wDj1SQr^S%-zvje)dNG{%BGHgUt1(MUv{(8wM@(8 zsiy~c#93XsILu8iDMbnL!G<&NxAaooS|=+)nXmC$Cl&U@OXcM{dAK4@PUPz8p-PZy zUOL&VkCt_!mD6Uu)My?nt3Jd_kLK~xZ4>v)H}taZZmcZ0q?6B~dTDnkR+=y)BfpGR zCY+9!v6J-DDv<0pVx|M8TK~-ND zcr>6Mp-_)%WrVU3f7nAYF+SYrwh(=e|~tD3o7zHJ7a7^5(0N&R%&=57r!( zGuw~7<~Z)_OGAUP`K)4qXYJ6NeV(0qlpVx6&=F<2 zawZn@@2gqsdu@@)nJn^(>}&V;WZmX;1}+6K+u{K4=j>0PIL5!v;_Pf_IzES|V`$5! zl0Vl~MsI5_OPB#C|LjCjM=hi8sl@0yRRPueltHc-DN-kNefZYn5-d!xFehOUQQYA>Sno^s=x_1C9GetCjY}M{-qQc zzo|%C^*2k&_kZ%KLb0@}rhp~)NtZ$t2>N6eMVTV8IHJV7HA~^3D$% zdicTmYXHI=>5h5zpB{Yx4yOe`9q12ty+2yJ`(f}AUtC@4507sF=#=b_@t^!r;O~d1 z{{ArC@YxpY-@Wz)ZG{X|A+|G+!ldN-0zL%-gHY-x*Gq{&p0^(`>M0o{4xUb4+I;x79-NvwnC zu|}VKi>#D^_3(PB2)8%l))*t2&R{Ms8LXz4=#N`NW??LS4KGvC*`D0MT=G+kQ&CBk zipu=|wt?Ozn^dS*(%m?Yj<{1P7^$N(?k}^m8mA(kuVL_Kmi2bB2gg#-wmEx7J~{Nf z(W#i4je-1og>qRCi)_4_X+peHHg;6WM!9UxymmCfr)M_acFD#GPtL4;WhUWMGFRJK zZ;H*vy6>E49hHNj^O$kDDH|@ev$381@SWrZ&aTTr(h}xLKgq_W&2(?vpciRxHafB= zvxjxEMxEGm$jHXeN-CLLsFt1297XG(l5zWOnQQ1I!wvM7?qtoz-9dWYv6rKZ++^`u z2kCj!Nv0ig6xr-7TMOLeXhvf?7+oZ;u8R!m;3{)6U8Ve97pd0FQRa%DS5->P?ph)r>M9WZRe|0a z7C6dly#6ThY6jg}qC~K_0vmG`s7-(AjK<`C1I!Y;rdT|Km1yy$M6|V(*nUch zl&j<%&1RYHRU!e+OXU9je{y+63A2Lesu)lrX9g6@xT<87jS3_kE0Sgd6;QubVr*+> zg3{SoX@x%;&GW-$dQVO9%(=Y99J5M(m|7zMJ8Jl$M|ozLvDTH@+#kwT^lelnV==@Z z_DKOqeNSeQ*IgXHZ($!_*v9z5{X_tKK62*psxJlv`YWgt@_-`t@9AEe&#}(7BsE>rxSaQVtvyE*e z9>#>D)uRaf=}b1bJ~_uB^fFD2L8z2Mgj`}g9agm?k?qHPcdH%fJtQ0kGug#q z{Jy*}Jg>?b*|}tjKhVcDJ(9Cm%xGK3*XHjD#o@3BVJ7v_aJ1QD#2fbgCXS)s^a1;& zb9mkKBq!0B*O-B{e9aaejmWU3TT79O#z*=8&*61gGnMN*BO2!M8cQ@{;lWhQxoboR)(q#(GvW(> ze`g|7#Qs`Q&1|H$%E5#Lp68*g0|qmfeMC0qlNs4Ghu4yAHnxo7{BLg)GRYy1c}EVh zCEbe`v+%l74!jqTcS$nAYg9HG@_W5*kn2b%+xVQUaf=)*`jU+s{CfcTn7;pVkj<|P z$)OLjZZ_tvWZlS@{m%%HR8SG0&(r_}G+BR({YJcFOPz?^@M0Sh#ga{(a)KVUsa2VieZvPyp)=%mElFP@{?=9`oVg+H%l+u_cH%EjQ)wwak9}*Cv(rm$ zv8s^BIox9s<{2k*Iq%ZuE!T{nVx-Z(I7xBTi(`!hN&d+7BD1ebmT1K@H%9z!>R7u? zlsO~mW#lZ)ovZAPS!!kde62ifuaof(39{W%Cvek=vM#eOYjQofRt?|wE|~Ixy}TqB z1Z{Fb6K6Mc^r!EFJ+zA+WI|H8CLFIqZ>|Ab&7ni(sEW*u3##qr+HZpzI~us+K>&S9 zpV?m;@64=P6^1#h&@xOsIhznXJ%4V__~6bb6ktwTjYYY zVe}@FSxBf9g0e{(G=3j~g*Q0g(m;c}ln`uF)7kP=gBAR`Z{>1Pe-Lmzlku0OeUEav)h)jT@E?a9|{BfH|40aaiIYLYdq^eY{U3(^q8 zwc2v72YYr+M*-J@?;O*S(>?>nUYtv5nt{g4$tdklr#p=GuihEx_J-MIBRLbpzVGN- z{GFb!zfN?xkW)PBnu!CYGcj}``H!cp1v5v-df^vRnn~voe?~y@wF^b5NwuvoRLX>O-AmiFD6*{Le)6{2{!_eKZbtc3%+Q< z=g-+2^z$}jCZ@{{wx0q|M>P8&odML3rM? za{ry3Y;Mp}G+aknY_^sCMG9v0l*nf~z^vPuW$s`F?$=dfQ#JBK(e$;=;GD&k0Q}h& zfJwXj(RFqNHn=l$`W%^=nUQeKjD(jL^QPCP!orK|)BCBou`m_evuKq5%J~9+GW>gU zkn54d*|!|lhIlSF&B2GcNfOXAUaVFnl9SQPp?i8sUKlSsuBp*_mpc|#XC~$c71BGn zq5=2&k>ly3)rX?+FZaHI8r&YM0p@6M>LvM$Ejk<=$a|ME9yiXA#o#^3_ES1$f9Gsl z5%-;DX3ccSL^AIS`$zMDis`RWwH&O!=GbglkB5r5R!#-Z> zRMg2rgBmLbF(WgB9w#2#2tFtB_q*aX^F6$yLa^*BS&)~Zxbc8|dN_SfE4k0!uEQ87 zW;*ZUJ&${5LrdlrY+$~?R{COjkGgD`i91Od%zq}E&D=-aPiaC}89^8Bm2{l0 zn2GTYN>3|yrRSlkNrT=CGv z8PT_{(64pFbw^iJT;z(JJhCbE$?NesR*TQB7onk;P-i*Db>l4LbUl*8br{)`PG7Ph zAHDSSosm&rLWhI{@9}-f%Y^ct-Zc})$%3pr#XQqkg=fk*g=ddU@~0;Ht*XUK{AHck zjv=SAHBsiRh?n}z$Xr><70u`;ux~;?^I~Rj+*f1kWHknC*PvzDP^^xjHY|Ykg*JNRC=~hlEvrzSkP!ksU7MdrzWcu&xi8O?nNUBh#C&=q@$xe6ya$HzT*@ojp1 zE7Fa)hkNa)2pmi2-gN<)G|m}~j@U6gEuG;>1v|tD- zZ45wEJ04Sj4<0V$J+OfL^p%mU=|-@=Mi=~8@^USVcw3u(z1w`Q?oP$XAx3QdoPw*) zIe6VG2P3=WpuvM2G<3{`GuQLm46b5q?Ji?Ry2*sf&7^FSyV!hfCYze_nI2y( z?TQj3S8-oAPl?YJ{7|7<0Ls4bL-nu#v|Hte1JC{N*e-(mD$Y&TC*#Sw!J__=7^sNE zVguPu?%zA@;|vz}^Z3WTgqpk_*ZZgV9No>ma%avpW&7k}A@|suSGY*qip|8z+gVEa zI*FmMsXUBxl8s&YUQ{y6_znvEVA$`f4d%cXnVm>b_4Twa|%4FVmq#`?xb7IfAml~alf@?-ZS~G*eCI=Ham-W0w zHl{Dg#gR5S*g@trHpoHjtz0GWv09$}a+Mg?z`C8~IpaVcwVd;q^q%*vuj113suwY|0DvZUqs*<_j-dhMkKH2XS6C6Z~ic& zlMZH_OvUxXWM6ZchnUa#u)4W;Xvul8pV{;$xk+9{cR8NpBvbR9rIoIkOz-R>%g0)v z+CR>7@cF*dS4lUf5^r-$q-HU_PcQvZi_g_W1!r;LkF)Fjklvr4R|IED?7046{io}& z9SB|)iTh5S}>3OD|2kMG&IbtngAJaf?a4L!`9;hbJMQQ94( zt2SRRgMH)4Pmy7s!@TJ%7i0yvq3k$UXt#2{K0=KO-^ep2Xi%>U=hL6@xxu-j($je# znxNsVln$3WlVAM9b#)D{$=k&LcYW?MDif|Z)9FXb!1u3YzmAecd(S*$a@`;5DLh}+ zR(h_TtnfTXpYBoejBke@lRs|~CFRml`Qgqw`i}&;K)zDK)fjct4gY4Uv3Qj$c3QY% z{b(mNvcLqjI z;Y`r%4BXG9-J^^P$m$KCBeqLr@`L2{j&|W}z$Be$dXd?C5+@GlV&!xh z&Ma)B`*1YxgGoFV*5}9Cs!`nD6^5a~xMQQiyZOv6_Sc{dpQmsAf-#S*d#3~Req7R{ zm5(0Tig@%^=$U($jzAt$6RzW{*UH3_A|BgqW-BkD+nCR<*$3&Yg9_E9WIVV7_ab+3iPFFc9P04$1@QRm>i*#~h8)rMnd*-cj!F4|u{JrNw4nc+Y z`{>p*xc=9@e<*-i)1KTDmSxUUP$-`D2t~;qJuXgQ|J6dL9ZN9>D5q-yJ_mdyw^F5yP6L-nR&fUd6PMKHOgdd$Q=sKMk&x*3Bt=v<3lg$<#Y#I?t}o%DN7 z*5fhf147nv-NDc8(sw;JEX}}x(iw2sL-)WU=5g~gE15}mKKafTDezs!dP`(O zIq)e@f}i*x>L}-Azoej50~56Ct?8F7mLtFEU%L{Hb^Yn*>YWA4GPZJndBiKqu{Pa~ zIkw~(olem!H=>c;QT~&y+c;;`oqof^o&8$Q`?G`td<{+=})0aw(YOLH==C zLuoVmpL|>4gFgqDFYLhMbjw0qww+Y5`6op~eDHi@7?u>KAY`WrNx$vn{iq^&*4Y<- zdUM{n1O0A`nIC<%k<1Rv7t4;!Y31?M48&4DPrHVnJ?`N~n|R@ZTqsr2rJo$^DK zMf@DAle=W?y3~tWvd_6#$~^PI9`*oYELnFH{=1Eh_!|Do-FiN7?G=usI;r@2$OMO# z^`!I7V(Hh@2lnO2XU$5+yJug}O>ZscumWm;e9*ZOy=*6vVOP$CP3-$j?fF-N$&;?W z6ONxeuX1;okoCz~cDntOpziE}%nQetYnDANYAkz~{B%;1Asy8Mt7M6k^cFa%8 zvKMbR1MY z^MN{&^R>#xi^3*Sz2QH}@8g5NtWlr4mW%*$ou39bl*nFr(#hT%{?+NexJ90k9Ad0@ zJ+a?k$O?fEB6xo&Q^N?4FIgxv!b*b5B*>ZEeog4TFc8O|74gG|6RlUF!G62qD^?c zsgbx(%9pl(2I244aO^DR>(}J@@W5Ka))YxDz1vTFhQl^C1xU}r!JGCH!k)u~k*wo4 z;Q1Dwf~u^AthK8zn^lD}>YNXPVwrQ{L@(zw6GvyPWbC0LDfA%MxtsR^XCsDrGtVo# zfh=bJ_-BPL%;fJHH>0o9ota+m8p`6udD8rk7j~5nL)G{cOl?4?#YXmLJb0h%<%6qp zcs_?GKtH3W zwUjIG#uu?$=Ghn!hyLe*}9gW<4JOe{O|gBGzC*KvoP7&mbrTW#OaDJwv-J= za69I_k2m4PR$HkQSS;!)%ozDa|K{mrJl$);aE-NWdRinWCVDeJl|B{TXXfa#u-y3& z8Ea>Jm>h)OtF*WhoQ5s7^!xvb6_*o^*d0agiG0wF8;{YwANixQhegZz`i;vqIBlgR z*OP{`P0UdJJ1Bos9DxZTjOW$C?Qj|{H#Ea;?-2=YQ3 z<^>1t3&D72-G6(BP&kN7%GPLm(>RAV>urr&MRVqTXtoL@!1;iJPcZlV*s z6&kcBdoaQ;4Nf*@+*uVZDW9Ftl=9oA|z|ne!3IT8%SjgTI=Qq&XsAl2q8ee;Kr^ zwWwRjyze&5vkr`vo6nswkNM6XGqsp~iMixW6rNN6MoVie=AoAaqsuTY-u+8MbajQN zGxN9ZxbpL=5)9WqI=DCB@dVO$X^NIti=*9aO zrAC!D^gNPh^q#>Sd5sy(?tRw$Br$UT$cXER9JUQiAI_$DZ z!_;&hCwaghT^+EKykXPPIyB0sM|HB9p2cX%>*0v+0pt+L^Y)*ghB~v%uv{J`7u;3Y zKQ0($ZqnPhm9Hb5eVrIhhKv2Gjv?4z7>CVP%)z?O>(us;6jWAW!hm2X`Tl&m`xuVo zf}6aLmN^+tnDvyIBF{OqU4zU{mKk>qQL^|7J)sAKu_Tbb#VO=i1I*CxWiE3cXH4aF z-FG=>^c>P*m{Eexn+{5ehCR1n=BI~f@q+*U!HYA~$|IuTEc-bg=S#j11H$-z=9+OJ z{je0pI^t492;T5KEHf(&vr3!MVCWIC{Y-x%_l^EbwP=4a9kr*@8@nS$TojI&_jW1X z(JyIYkI0kre`(}cCp~e3#nmAEs!pfJbiNKf_4W^9#C0F%4*f8ziv&QI&CxWWAo`<8^)Y&V~i~4c~yTGb91|B z@n$f+wD;*(T^=hRwm2j9{4z|@&=YD*M`@n770D-#uvDWUY#A=|{<&%zulL3Z&%TI} z#f_X{J0%!9|7yu?q@gwW?v0DI@~(k17V>zk)3k6{#_N>Nk(A9bVp`~gR}X^d;i9kh zPC7EFJ3j) z8C#YtLofF4%ma8mR{o!TSTlt}5wqt?e9wROaN5P)lK1Cc zGjv{h-=pU7)rOMKjSOdZ95Jj`zq>d#{dA|GZ5<4I6rVaAI#$ilZBbLhyg}Tf9BaGl}P_2UMss&5V6OCK0I zEG(bgyj>TAdF)Yxp+WM+?wd||n5J*_SXcSC!S{H@qs{CY zkB=AYa`93H9ra9HwjK`%|41^of-zD|9kY6(@^_>E&*vcvBzG#O_ER}Yt!k>iSDdI>N*$9;=RnNfg4iy(wo?gbA%IIP=1w~Go0*4$B=tu zZ~0nldU--zFq^z;U0Zkb?W;zhP6cyAHJX}L%&TS3ySJM4e)cQsy2AOA3${RoE_5>N zDt5v5KWaGrR>6{c`OfcD2A8`%F&48iN15DbdYpi?M&%$MoZ znWDq(08!rQ`Cr}({Q2iRcO7#~^%xPxETdCeG+)HE0{hp|*L4V*z~1y)Ju?Hy zJKv-ypbG!oo=#*wr^EW_Q6p7{>U^!4zd7d+M<*|zLygMmurY#p)W7)}HQ6U;4|{P7 z9cH}IVRj=O=AL40=R`W<$Sz(VoDLy}7{*%98xy(3({wem$K=DB)bk(dnDLoD20mv` z#bwa3myQ6|%Pxd)_LdB!eR=kxYG&X(S;x(+6KVK-o%|&Y@%uB-Yb-M?Ea<;z%ieVl z&h0i}?SDA?)@w81&ga!3_Q3<&rsJ(+23i;#_@8nVzury~Y40L8Pd1i`O0_s!I?Bw7cG9B-b9XZArKPn>4ll761-Zq{^>$+Y z*-1{ncaZ|-DMh|yrnCncteK7Fh^?J$YtU3u);Y+WCr)z8&0Sh8aF}3DzmU5++ zStgfPVwY=)3_hTM_3C1o`&5Akp$f#*Q=m;ukqj!QfHUj1F1JeLO-t^$QWWsL!Cc$} zN-R?riE(PN#E_vXiBcjinQQq`%+4i4)uoOSks5Mboy`)whkm)iWU)T59=)$bI^|fP z%}FJm{P`zQYt3RPE|kCC%-C(`2dnmeu({!f=oD{ktn7z^SANVuVCGY_A2Vjzt9M`> zf4eX4exy60p+DXP(*YDtkDSRH&j0+eV^RR(%dsEvmfnCbzIfNfAA@szu!YRloqXm< z5AZ{+IsOQDp)+WdAL6b3&|VRM)v12?Kct=YTa;@Twr8-ry9mhv!9cePx-RT((O`?Z z?b_UsF*AVO#9(((b{7nGQ8M54zVGoJ-yiV(;Gx@%ILG<7`h2M$L`JY0fh4W*xjESt^N%#_jYd1fPpSTTR8V-pi`f9l%{j&Di{-uxTkakbYpFMF|!{R@YhGl zHm-`o(rCII$!=Y_OI~sUIW7L(%?FU%;{QMLnmj^3`WGXaWqX~uP0KQ|y;c^QJ~m(w z`zVuUWYOB^=*T}`ISc2#3^>l7Fn8E^Vr78Yu}pl@XTs%uCQ3>&abh5OtebT2e`J53 ztdnjzbG7`)8dhV!q@xkT)*5k;J&KhZicmbah~6l=7j<+lRxzU6R3k3!V2>b)oD_d= zR!2H3YS01YV}yZ!ZamM&3Z6YRujr6_K;Ei_kv#`yJI*e|zAJ@@9Y&^M4!sV|*~>SO zm9#8E|9VE$sW4*b1#8L3P)T-qN0~g|R*LpHNYP{V(hoVvszY>4y|nx0G>von^pGJ1HIDEK9%H%lu(h(p<&f%6HzU8`_Kcb_bd5 zsuH_;tmX0hbR9ysYGXUGDpSdla9gQlY%hNu=`3H9UF5z|fw2R~A97}UcMI|ram;kT zr9kh4CK)%#B%``kh|01;9`YWmGQ}jD`Y9lJ72>~*eVV59Pt0In>mRZZbQVph^IOi% zS7Jte)|Yyg%2j4p9;;!7^|eegZ&bNh2apk-qJ-5!1&RilVVRu*6V6n~!Rckv_>@W7 zdomY`_r-A?-CZku5$@=Vh_1}SV&CxURAxDL^F@bE%yzuM-dP)ej9cf26=ebFH;&$o z1%7zhAOPzQ`{Vi^e?0l>i%JXpaqGP|rtM&E^(0^P7(;*KS05}Z@x_I5AAH#yfQ!tH zdvwwdYBlfO!@fvs=!+>D_L+J!d)kj~)HBhTZLdL~TCDjrEzs)+w5dv6Aj5Vmf$D)wKd-LpDI#tJI;cu@@^lL}Y zQ!nzsi^(z`priC3x=ne{I5ptC*B}drCm3+sE|Z=e1D=g#)=gp-y|T<;&oE#cYeGla ztGl;`zvo2OV=CF0ZoKD=2E01V`Pu=Q2%19o7{7Ki>sCEqWMcLX11^51pRq+2RJjJM z2{a(hHw*igF_R+Ni0$uqKYcMG$g2podEKv@Z^Vp!22Wb;Ua+Bmdb1<>>7KfM>4P)RqzAT3NuXL-Ctun4|KbKy8>tF6ui|4sD zv)Y?JDbOZ;+s&)#H!rQ|+3Itq`}YE^=&vNn(mF{pa7&WVl_l?(H+_#jr`*tF>6xyR z8RqnG5pI;l3AzNgNd(c2g=7e>TOBALY3`ssOp=43>&$zZomD?`tMZp2PDje{j zAH7u*9r3cW3R!bi=sdt4J&X>l%{ky1dyLaKzt=;p!uvoKIvlXa&BJzl#yY^7=bI&k z_E@#k9$u#%(3yKf?^`PPS+d8}(h;toIY+}Y%G`wxxcN~9AMPb@mN=r$Wad({|6|e9 z9!H+AhINelMb;Je%}^tQ^^t#?g+ozDCh<);>Q7fAeTf?He{yff{h?f_WT~}@QVAv(m6aQm9RHi#Mzj}oTEwBqxbb(9Ogc4*rr^1 zD%i7akdN(N%!01PJs$US{U+1f=#-D#^SLi++1}(slegp27a};|%kr)nBcoaDcsZ16;n7 zv7V3xd+raSI0F$egFZWJ@_J@P7|C_~aHS7uHM|ftv+ZTB%1M&1JIS8&R>$N1bI^Vj=h!$Uv(cH>-0b7oJcYEU+j?6_Wo zCI>W#yTs@Ca1EAyFhJj)j*zc>UY^K8JMLx1)L^aI!-$79$#G}W)jWf2^-elF{-s~9 zGFirW<~h@&9DRTsV=sH@=hjhbL?{tnL6(1;5`GFZymkI9KPD)!MN0Vh2Af6DbCFTaebg4*3Jz;Vh4X%?$SUe zGIM%Axs(_5Ta_{cjcaOi&dn57&%!n`_=CxWc}$??!j}w#d#b zyFpGqoDAb;7rE1?lh~O$N=b}^d|qQI)(yKkBrhU@4j z0}{BWT>adLA+w6`sn-W|oNYvWRw0&5Vx9I6t=Kox%Bb>GIY%C?&@ojWzo5@9+!6PA zws-KPmx!GB@qG@s(>wx?ZbzU;f*Mh!JS+F*b8;Ykgd6EdIzgt^?oub(VY2v&*$!9 z`YZkNaQ{AQeDpSrj#YScD>uPitMF)6M%I#kEvMlJB_l{D=9?1aJz0=OT+jOsbVS{? zoCmdWf^%<2465aXR_2aSjg5fqOFD))U_{rJp1p0xiC&QZS%Ddil zU6qhQeM$e|1#<1DStn?fhnE5Q$R0taaV^;$`kMYUC_LWqeOgS`p{P{hF)}Y%(zhIv z!WIW*9_JvA(%U={0o6GM`5@QohNn*5K4t-{aj*zr6}@0yQ#O<99TQ+R~VR(SLw zPh`XQMg5kpjdt`91f@uud@?i4CGi_iH+5#JSgq4a`eyD&4zRxD$Nj@7vLN^E@$0S= zYOdoP?B)pc%Z7M`6lVCHoLau*n2#olmGK0S!Nd4}vp2CS(O8#xbWnWB=Z zwe01G$ypAJ?j%Rz97N^ZMdl4s;88UNRy?YZsyusTve$Wm9+irV{>bVPh-AwEe0myy ziA(+PM<$(rz3FAFM2~NU21=esKI_TJ?I9mA$$*wavv7-N=Ol82h8N7i*8GRpBM-OC zh)TzpAxAFFelqv*VSH^{Tx39qN`ev{#G$vHh#v-3^2Ics(?0O^= zAIyTkodIR8TsH=>J}`#o^T|aRJ(#cKg%LZi(anC;2=lT|(qnKJ2|sTuB|-ems;H#> z8(Z1(j@ilmmCRf-VL<)6`*!oAPW_t7vXGuYuTy7!l6;WTR~sv2ZHwONSe zUZe9a{)jHZ*ZD;#Ty2Ca&s_nVI!eFk&ddYqC?hBLkU<@7CD2+W-JO-V;Y{x`vpTnM z&ahyd8SZlCBz*>F11FEb%ARCm#|7f-5zgff2*AJd==c1f!Szbp@Tdo~1x!4PR*S~b za?S^Ey|TE?y3L3zcn-_LZMrOvq_Xz0sR+;8aVE`&c^6#YgZ%k3&p8dw=;gP+PTacc zWY7=2+_g%PCjU6%_EHC^|8PX7b1Lj!uEIyI8?Kktcv532!q2GbC1m~%pVx>`!#!IE zw}r{5dng%lNRLT7`3#!FS#j=#1Jrq#b0!zb%kwa16TRY_$>x*$>PUXM>j2*GYOY<2 z{>SE5HtD3-GaV=8b@C!XFI8%?p6;cW8OJye@F(+yxPHx_rNX@}4ro=O!Y9`V&d{nM zqarY#YuMw-;p7L@2)fHG9`56p^R>82G8S&cM<1E((t+;aoGw?|q;ncF?6H*+$o~)yyN(W<`<=E=ZCMyHn&*kP7-8Dpasm ze_caLt=JzDS_Z{c1dU8$e zoQuAr$eCB+GjSMM%LS|%KVls?j_WA7%KLm@-W_AVmh7P8MTN(W0jUybmnz2w>!riq zB(bf~$w|kfq8O*bD+fmmuHp!T-VVVV9WeD1^OsgKXZk_}A}-Psz|U$=ANJuh)Y!UG zkLGtc-_LW-nIUu`a{n=XtsYx>e%Kw6hv&QVk;XMXKZvzwKb|SF>4xO{@$sC(!;D;h z*A)tn+GHC;>3bOWAVo&>Wq!d-o%~p-lO2Xs$yn`(GqW6V@fCU4ZYs>UtHSqw9k3@d zg3lMO?X@CsD~VhquO~Iv*OpvMmj`kU>y(VC<8|mXifjC7_Wdex9eu*tiEjCLnU#nA zQ}Zz3GdcK!TrbGLE22;kpWq zxhI=^M}?T?DwHo(!KIQ4_C67K{F6?Gugs?USB?2w)rdI6_h&QrJvrnC^0|(#)gk`3 z9-Y`9Q}L`-YeydQ=<{%O2{XBMdFXwKndM|X9nL5`ws|N$4t?W{$ylymRsJ8(m}T8c zS};fGZarUI8Ar}&K6$hqg;;vbLXzhGkm+xI5#W z66-6a@_xQI29q0FQ!f({Im{7W)Kc^XrQ$=MS3dbN-8FjX+S8Lb-$J%dDVMtIy%3ug zg@#`;@No@msApQsm|JBsafBBfS?79OmAN0g3UH@!OR3Hr=ZWMiOZa_)gEE-WSjhFo zQa%L)*xvlL&OVmY;te!vrvSQ(swKm3@Hli5^q`;|zQ8$Osj zBN7Tj2C7#SAls*@T%t#8buVw2H=rLdArr63*G%qEPjZ-VYZL2@WuxeMBv+Mlv=IGP zw~@r=3cNLVq3~%W!rx~wud@K}uC|gp8%pI+H*XwBq=znub!zuQ6dr3PB?n5R9=(uD z9a&GW&stnS0S4$IQ`gc7wc|p#Vd*yXR(ta@v9N*bdL1pHEkw&Crc!ieTS2*<$p{eA9tq!1^rveQ>$`0JCN($ z4*CjN1Dx}z0Aq66$d$66GW<_31Rab-_NGh>dBR-XKN^aE^)m4u?uWsZn9bx)P7~xn z!`n!=s=wr)Jo?}kM8V0EoZV`^{(a5m#iUC<~Itk zB(;TX>R2p|&B>8nBd_-@6YsXLuHLP+sQfBqUzsmPwqf4QI@bMXk|WD$C13dZ*Ix02 zF*p)$w$Z;ilb*P$Ev0lG=j9VUaW#G`?(AU>`1k_+IN3r5HR9_Th55`Vz)vJd~7AX=M+oxAKsX27Kw_*L5zn3%Xf7=ye*0i?L;Y+djeelBJRh(Cx#(mnS_i)NLmmWjP z%6Z1^FDOGKt7i>^%Qr`K&BSp@cUMB;)F?dPb3Fj%6xF%*M)rwp>j2ssLd7P zN-kU3klyHp8F-XbfKfNvNzSBF(bJoGZAlbX6=%TyN&(E9v=nWl64^)I`9SL^*2Xii z+?oF_=T_24!RJ5?A9$^e!i10HQWH2|xum(IWR~zON#7{@VgEXFb|j4a^1#-zc~6;y zv2XA*Fbcgo^M2=Z(si(yX!eoQX{n3i0TXx$It6 zCfbJNh&M#iyP1if9}976a9g>1uUO(9d1FfMRxCY}ftj1h?b6R!_^?dY)aLci>sgRN?a{^c1t_qS#Y>oq?Q?0<=<^%fRNpot!TYjR$HuVS9*7|z6V0&AHgm~Try<#IP01T_o8wwjzh*_eY6awt1L$4L4t zTO2z|{~GxqtBM>1rdMEW|9F{0er@d3a10}N){K4h!{inZM<+<|T5CLf8UpOqBBpjO z?!=Hwnh`HH4d~-LNpD>ibEqqG&hI3>jW+RecROn%uS2kTEWLrB$&t-5;rp8y*&btq z8I42nrl$_Q>oDgxiT=1&39|034GLR_!nUCf5f%4PzZw0Kf0D-}r*oLEKeD41QR}mD zqbIq=AMvuRGxLsvLNU3C7BfP~<0R1McrjK!kbj&~D-^*XpLL$I?vv>stQjX~$Z5Q~ z9EyW{Kg$~A;#yx5jE4_M-wF2U6BmL(F7Xs`YRlJ^0n}LmV@q~5Ah56R%csmAs04#FmslQGY-;6n% zjTz+fu0D;I+!uE6=XHBDREti%Ifqr1KDeC;(t&aW*b;X7~BjI2n4> z7TME6;7ktXp-b+6{f1vW;w3G>7Du*+F$-IZTg!9!Of+HXxL66NcXHYJ5LDlxMMf*; zHPhc0G4+5f*=LKcrzISd{2Z4Zh?RtLJ9ymU{eD`DNtrpQF`7QmA8~StzQ3=$P7YqsGOvR7 zos$W_4a|d{Y7KeKTx*6d3#iw5sEdv$eHFc7oPV~yEXfyR~vgc z_UHY=zqiYr9Q;v9;h`BBFMIdf;`tQLf*<1hwmS!VzMC-9Cqc%OpS4X0L(G~am|y1S z=nC04cuGe0+jd?u$xxAJ4 zLh$g74rhku;9U;=o)&R3X{0^kl9*Rco^*&)4hFhbpx&YV(tHbfTcIcME3cC`*_gK1 z#0FO;@hclO$&=>Jq;L0?Ju*Lsp~RKG%cI#i>2AV) zz7K2X+M|kj7}k_%agUs7SB(i%_8gG5E9`J^Whm&UxsH;Pg3;SWN^lU2QC3*^H)0T$Ov7tq;=o}3By8>>F z;v`?}p`H?kx%~aSy15wGvEsk|u>T*P(c<};^l5|B-Qo`)bThuTOWPTv>NRBC#`KRp z%`^1Xj=QhA*~BfP`JQx}YJ1bGh3!xGS#&);NHyW8{h)>Ftf?rNK{V918E zsR^sn7hK)sz9zC|uVq=SGA#A)+&;Fvopx4l>%J#wP0#a{|4Os0wl1x5-jTB@ar*Rw z8~okJt{9nqH)-3M{wvbclU)z@G_BT3N;>PsXA@-(^9SB6N)(S%DKdR#io~_o$>{1y zVzE#sBex~Wy1Ge{Gllb*8m&0aN|J6{lVsT7B(eE?Kt^XJ%GvJ8ay%eKPXE$M7iKwi zeUu;zb|uM!I?3FFCrj5hT3N?B`LUFEW`8p`V@-o+|85aX@uj_C!`Y;8BhWSGe9Sqfg*> z0<%Dl+2ip|&W83P)2LSAMQ6_Pv!1bUDA{3y0}_5aA|qafltC)=D{w%@IA)Poc0iwS z2TbYci0btnVex=}N7D%O)Za6*`sPWgYFbqtI zfd6Rv8z-otyP(F5kMuMqhNB1neCJR#n!P8l$bHWo_9eQ!Qe*P1aC{F^W6Bj~m2kb8 zJ(wATtJK)T`uB9!=G_-Ee_{vw7Oejq_*0GNtS784WbY!9`O)b*Jj)>$eO-rTnL4cV zq_cwecW2f;URTf`JX(hk{v5eqkH$vUt4^?n??{g$>or~Yb*nime6<5T1wP3*&K}6+ z1N=JwWYlE6q|-Bg-;R3xn@iUNzxSlcdd|M-P`zg|itdqXd`%C}LmkTJ@wGgq51M^| zCwAWFz$_)cG*Q4JPXQMwaqXQ+w9kKw;YF#aJkZ( z2_?QQH_6~yl{lxVgnu?`^VO87^n?zWbR}-?WdGo6g&b?3M1z^EN$;kQpt=%Gd(n~b zf&K7-{_tggcSKkqaNG}#elnx*5&6YNzSz0V4~J8kso0UTj*tCN;Nu5Z71_o0zKBtf zZ*-?$#*Dc~nLe*q&JTB``>1CB&2Atqn-vQ{K!i+q{nfn25npL_imA^I!fkhfCil#^8YWQ z$G}{J%VeokTQxYTivBNikoSn3B>&EC6PP`?A)0$7GLHe#m~euOm74CEG4#1@ARooL ziDDRes^$iyHQ+oyd&(XDbC#cHK)f$&X$8#TtDS{=^danKy?nth16BrP!TT+JKZ~;P zl#JHvSy||Dg!S~1S(sp*g*+!mS>A z1W}x0Ja5DjM>+`T@zJ*^!jtAk*xWKA@<}1io~GOJR3UnHGh#Wv$Bjtl?iLvlLw@ma zMj^KEF=7M1$G+QSw%DhUkwzr4hrcDpUe=y=5;O7+s}4F!%P1$Y*kmh1^v?3R3VFj0 zR-(UeBO7GNbKDU;M z1@>Z>>L|_WXxwbkLH>AZBS}M4@~W4OM6~K4%9b6Z(V_P8YmQ1T9(IyLN##y#LYzu}%N@E-1Hu$2y;>m--4*CF zfzF~+be~3;WXS_^8kyy?V?R9*n@zH{A!mZy(Xli{fgMpwSezs0QoUSyd67fjOcxaI zuOAx~=#@rpIoJ%{Ci!7HbGWvU>z&t+Ua0T@bX!4=qOw2s_3%gW>HyfkWtN!I4^>&C zG^W$Tae_SJEMH{(K^Mn9Us#_Cz=#!oNIm0+w?F-0-Iw2^x*vYFW}eoXKn!O-^*_9) zrsevfRu_Nf+4&)(W&qw*XWl!1&-m4!E**dL<@b*0%KNL3jKZxbtPN$)(u{0kPYuGp zN7G%Wfx~WQqn1RWnJF4x?eb=f<4AxbfEIj zt$j&mCqjcIuJo$j;XTKn7n6O+$cx6g_tDs;AUD}SgLCd0l(f`f;CE(x1ZlAQ8r@eF z%oqtYVAaF_WKkHHw?HQ;xnI}&beZ+ef^s5RUmf#R!ZPVd;r-=jU_Lb&;DrX%xypJU zzxF-vL7xYlL7rv6xw!wiO+7URys1gAX|Mq!i`if7&i`kY#hMCp;e>V6_T(?v>zgn& z3p1bbp5%QUXf!gj(TFjAMX+@$Lf5WESjy}D&Gkauo<>%r8?%haXDn-P#LM@EXl}`S zi5$|a3G_J5=DqltGpwvz{e7Uh1dwa0+^7gK{QD=D@cy!AFEp=FdU~O*=ZvlE(!Fl4NdKiubc+l-mF^a0 zm#)}dE92;aSLx*u$?3<9zthV$Lr+JsyeAvBSlob66HC6y`q&)7Od1tzo-=1uvsUG zkF-*wp;q=rrpoS4NfP!?l6ap?mSq)M=09-`t-4k=WoqT)Z~D3llErPiR@}Gg#Zi+W zVPqc%{iBx_+frl==VYEKb<$u7(OiYrrd#RU^WC?=z+GD{{d+hjW zj{qMPO8%f%+m3dYZz>egAvMz35v$**u;wKF-4E;#y_aXS>g>;qvS&}h0R>_7I?iyw zkP#}FLjRL_%Gtb$PAD~U-*{4mmL(3D)5sCmrqlKPT7}$n2c&Fw#KeEu6*<9q%qR9( zTjYS=TO7$|sW8|>jV8w;aNV4HGjfIxKZL{n5PLwo)d-GOVM}Ll?Lh7xexk_iioOgZfK{J^jf%^7qE5$>~(+@cfA$2ihj1=TRM$tY=t;>F}cpvqQOW zJa&=U(^d3%%C9?fiW$}|nLmA%-tR;`>Llt=*_!=Y{{7eZwMzE6#@Oo-xs`iAr(EWw z@Z8V6;I!wtsQo$@Gn&)2UBsCd_Hogi^Du*Q!3P>HIWQ;nS}yXwat@{e`*r8&R!rbb z?4Rt{jm*W!K6!Mdkx@LxzS%$YR}IKT)3%%~Wl!(?C^{Ms<)M`#5B1(N$2ubygEGlM z@(e!wIvs9P{vXd+Mi$QJcnA6P7x#fTo#jlblbjl6BL%)@SW|^8h`ADHdnu4nti(Dy zC9{9HUwP~g&pbc)f1w*8oIb)+fiTObTe>(JE5qs4tF;Zwi}>rEWEvYY8~9Kbsw8J2 zzmow2%*ljw$U?U21L_ScLRyRw$2^MgGWY{r_b_|0uS)I)+DiAA^b^NA%ds0ya&CZ= zyl8KR@iWNJx32_?MP}$UjdLtlD&$wy0JPKlfem-m&i04n;XrJmlOx%hzUnXBPbs5e z@67!W+49cZH%;1RK!3|DeBmC&a(fn9+#}2QE)yR&(fjN}W{*rrtwiQKzbrysvIZ-Q zRPs>QLC()|lmW%I;_;a-e-h{f4$vT6u?=4$_^ck!XZ;Uy>wG5f<@5bm6rI;w zIX^*We9?p=Sl=*WA!jjiFVRbFYbURIJB!P|9c9B3l{8tek_WkTH+%B$fAd?u%~qoO zCMDvRD{*gKg$(LL4;h`6oelnYZQ+l{+?TehABc(kY}!oRhQ2GANBNj}NQ>!0yb+Cy zTu-XUW+CLR0pk-m!$M}}papph@-mmY7h%E|KD+sx&doQ%u743$P39gY+*$fvaFFAj zne#k_udA=4jOMjcbGu1Sk!c*fS&7$2&0x=KsRv)jn`Qo3;ulD_IOh@4{BX`b5Q~GN zk;u<0$RZk!adaK;j)r=+22&n#jpABXZ+I4t-pRzB6a%I<%7W{9ax$06rg(FmNiuTg zjk(;#TvJ-P@Z94fVIRpAC2-$VrK2R7yU3|zC0xifzJB_fXL<$vHkrZqk^<*mkv%=+ zha3sS^lSw!F{4%BKM#@lBK>%FXK3WetgnFiFl-wfcyNtj!vjoIB}8Ec+>CoR+=sEr=l zM|p^T!t-PGeB9;vvX0k%+~PA~$oj`+6>BZx;P8w$D z#&T&Es4`9=+78Q4Uag#NFatJsG)u zTiMGeZ{Wl%$o6Kb@^7CMS+!4}$@Bh9vU#jId-5FJ<}lx@ ze>n^IK93GM@(s+pUeDJNepBJ0pqrp6U)LUfUQ@>Dq`zm1SOn_D+&e{1&eKY7|uM*E=y6DujACF|J3HfF!TU@nv#s^6ZG`!>#_Zl4qKb* zAzTyIWpK_hlkKryUF~JSq_{(U|ouP5ex1^lph?> z^$1y%NfB_ih``@n)G+rVFGEITQ9nJ7-`8VL3i&1l*X75|P*>_Pi|@yMer7)x(aU&^ zF5y2pS6w$Bns;9M`IBss~nan792>?|jT zk~iO|MC=a*)MX~g@mC^xsRE8$n5S^e4|!Uixu=qko6DSpXZ{%0n~dHv4e~2#@T;x{ zb?0%m&zcFMDPC>BhGVA8`_Z1LjKz2S0~X0 zSxYZJ2N}?$lPvY=B#k$!Sjjab@fgqIA2R9kqO0Aa2tC@; z&qyB4$CB%ou?VY&7NNI)2eF9jEGgGJh+RYG0#xcCetbTDBP)2N1z!hiA_XZ5oGN6U z#ZrN(JgfQmaDD$b0P8!`Wmzi#Q@Gyy@!a!ZEYC!&AG~(=Ip8vU~DtSgZSL`Is zGM!{uRR?;YoaFDHPI9=LO0q6h$jH_TOnj_B)0gBJ+bYm+iAlcZV++K?Sghukr`_l*G3h2&0;EOFaGzeC1!)2az4}8_&c~cDxvw7Cd;yEyl z{Ng~?aJU!R-Gnul>Ri(@IETjdE1BoNX?$%PcaqHwF2ejl2gPY(vRu_ANt1^M<#mlz z@nt?yPj3fw*-nog=iXxy?BTyig&x<)rFpPlcwLQuYcl8l4cCe3YR<)}5!*W%Q)VUO zW_vxVUeu$_U_EyH!`Yz~`S|^J9@dS^$L$4qSnwqeiDr2)dr7XF&zzX63XkW`^a{UF zc$~eh@R+RU^LaC8#CSfs8?Tp@ti{i7d{B1t`LidOe)_IX2#zC9UDpXOhdN@P4IRGy z>4>}>j-@Nr`0<|4X6Fb@c*S}5_w@PX>oCBRvjJyx2r%g2v7gVKF7zLs%EKqtavKKb zL34e=_;iQsnnLC#=v0*GZ_yx(( z*pl(Sk&DH#TqjC%(XSdgc+Nq2*3LtJx+-n>TJHAa^SOo6L;sWP-ZO+#@`9@kg#+1y=^FBh1DG=Oejo@1tLC*K*Ik0Hlcqdu93O1ty0l+WV>t+}43 zDm?0wV@xaJtO7qj?J=!XFu!2y{RDCNMo&XTs_a^l-JMr4#`ECBTJZ##KheOI$#zad{X$nXcobJm1w}=HUHY&W`3GX{OTS*f#o8BI&H6+tZG(X%RoO|2tQ9 z-m{fFv?h16*9W@q}H#oLrwniV`wI>2a}8OHW$UtUvj<^bBY&7p~E9`YFY1* zw2wU9;9_}xeK;14kHVt*oU0-iliItD^k%;89_A)rPKd;VXBjxWuMkm%ZKTdblVlHP zPIN^iToeX4&nU#8ZPs$nuS9$(Ey$q8e~G_%N!numU1q=RQfmf0!Bn(R&hE; zmc*Mn%7qve%v{~#U-F#)t}y<)EE?0l#;^b3+fpj}m&vJ? z%#E!b2{V5Ei?~8mYSC8uH7S$SZoXLfFbbC%Wddo1nC)OC%bAbd!GYeojZugiO)nmK zw-0^WNnrb*l4s?O-33ulmoRrp$GPEl=FsH2NS>EH~ks?Y1n-$KS+E0(W4 zeG%|63PXiiOlJ#l;{$z;_bQ|yfnGWCQ=48hr<;6M#}jQOGyfu|^q2 zj;~r9v7Gu#T!Ot&p^rq`sSH$W#+hk)6;E>CGsna{<)8Ez#?q^}p#YyAScxBf6pN$1 z*`H*N!Vm-I-7bW4WgGcoS1MzJd{8qc3fm56Ah|AU_9{!}4Y8hG?2XzNqA<8aCJe0m z_qb#yRVSCok5F&?%ll{=d0r2HdP^s@5!aA1aVB4Om3ht2^cko%s{m1}TgyX>V%bLy z*Pr#@wM#QG!iCNQk2a#PDwRj)ePA^|5*PZCALR9~-qlpJXN#q3Fmdo~q zJ{V7jh0nVTEb7Voh&<*~t1{V?47llqe*AY0;(gbU_v6+9?WEz-U!pngg?oYA368#gc62i@6fTT6`v& z@cqe)w2(jlDi$9*Z=Aod6}`@7Ku^whXE6IHr}#YS?Sq7VQLq`Cfo0BrA58iR!60M&!_Mc+G&mmW7ycv6Yn7E)%O2eBNH7w~;*Z zEOOKBUenjv^QQzyd7|IKNQA7&K%0~TlniVyr&|A(lV;?^`8<5hGs5UPMy$MSA=FA>L@YAPUbyGca^4-_J%?(j&E4mbCI@?nx9~j=cVBl8+wWPX0Jm zEMOWrr*DaN8S>Oqif$L6BK9?#LBHPqf`i%J{$ESK?k9QOj-ROxwQGlsGV`Tar z8(e-Lg24J(yzarw8FEYucEvEy$PRNxgu<-_-9MFb;j+Vo^q5#dku9^QLy^6o9=Fcy zZAY81{z{_UVjgH$yHGq|L_gP=90WyIpzp7Jbh_IjjI-}~oydRrX5+gn^P{u&%Z{41 zc+;HzzOh;?ADM%%Jxwq)jFB7#lpvZ8hPXxTV75>D^eV9A^)YFZ9G&Xz?U2 z8?I|jSZo(7eUfa^u4yRh*^rBwk&RBjD^TV8ez||#7K{Gi>m08|#E2Z2tW4K^p25P|Ja~pRT!oQYq8lxPvUVClv@%df1Cp>`1&s;Yhkiy zKJRQ3ec|M@W|DVvWBvP>7L}aoI;x@Y__d9^+jQo%k}Gt1!hGa&Ik5S}oYr?SvgmKt z^Ir$!b6+hs?aD!ybtZJLaX`xY*&=gJC>&>M(VXvFoEhg_{-z($oIbuZ@?0ymm>y=;w`8`~^Fl=R#+-XDUd{M^f|`T15- zc+4fwc<&TN zF{D$Xq&>95@qTJFHRpA8AP4pICS05nD`|xw_>z7I5h{J9^5nDOq8s+_Sp43 z6wQ6L&~GQ-x4MEXK#a8BYLAlNOW>r?VRSdv>Z>wG_)ff39qYiHw{Z6Vv?yE1S)Vs1 z=z1TJ$!~1Yk-XlYWm+`kbw1|431{xdOYs>Sj3cjCi|_xA*lcuYqwuKwGeNGGS)tOx zFnk)W`!8?%XHyeCMaPS})E4W>sXa?$F7tpKyxGe8>u{Wm>0pa()?s*dPm6uz1alr% zVB?$vvh$=JM%D~P#Fr#=_?iPvV|p9=B*;x(Z}sQXXZMrYqEEA-nOT7omhn>kfHgd7 zgre_iE&fQz#>`|B1`dpuZ#UXwem-;67w9mxe=c_1rMI+woE+_GhmYiZ&7H|D=Fq1} z|J~Q;^c!Z_qAIhv*`D5+~93cQ{4{&9KD?a)JTmK;7w2O#in6t*~FFc-mouZz%4^lB+$Ci%py8 zOPw4q#?$250{D6TN<#U*Y?%F`=dn|QbT+fa(25YaR@cIH)c<^uS>I#i{!BY~`-Pwr zpEIu(vG-C_;Sqd2MwTX7qjXXzs`9#8`&SOu7gs>HD^@C9vqjyxAsAJIvv3Axug+wy z_tFG;>T8WTe4bcV=j-pyY}BW`Urxoy=QKNHFju;BIdi>vogb{F@YwIo8R?bQ%&rN= zxOe2KopUgDe+3#^BuLO&8vf!DjJ888`OO!B zIxMWlK9f0p_1ak3pKk*X^I)u=OFlF>2dRAitUAFw^mH4nTojHVOLCEebMU^M!oxC( z&zUpKa9bZnCR&S$d_6mQIw&u!4i1*TQ#74zofym6ZQj$v2RvNq+rbzWqiUUE^NK7ZcXv!fE@Mdgw#;dJe6*p(<#vUKu`?|JA0 zt@OXftU%`M9Nfz~dkd{p<+J5bZ+Zj{B+CWXbzSf3WZFN;;@V3q({JizZj%&w(wQ}c z>&bG{Hc7fhCrUqaW;#vaoa>4N`4q2{R9@Gc$WC5en<&#VQe~u9swg?`DvCI{SRox0s62VA04xh@lM`^jWYq43tD)doEr z>*_fNp~H>JdemqAtb5~RT%SR|&U!i6J<8x>cGow?JF^gZn$${%#Up-#kW6z-x z|LiUDi+l!e4Ax;6``M>i^J>mIPI#^!D%Rf2*XdBNrXKx2>F_N_hv6FLU+^__)#~uX zH4mws^N{;1AJme=F+o#F&7EXSeLiu9P&)EiSy}WNMvTmH*$#jJgo7~ zML26zHw?L`@gWztZ1NG^IG@?}tmm`m-PFVx3_~8?vSu@VYaV;C%$Qc?V(7_S{MeI+ z0`|WrHOWWcZg~hR$weCLOB*LL`)!$vczSh^CWQ_%Xp6O!SGSXPSDZyR&{^IewwH`v zE)sjtN{+p@5!>sWm;Y!Z!;%~X8Ifd08je$d|-SD?TM8`h2^%rMMKi8Rh3S(LGcJE%g6 z)yzHgrQaY*fn)r$dkrReTv{##MJCaBv1c)}LIyjVq__$*t0$IAj~E5dzDiu=-%+_# zfoVOI=seXVw^Mwfb@D;~;mp|>Qs+QS-bI#i5wkb;2IBcT zI*ls)FuJ8bG~4`9y4(l*Hqj9=(;t=I_+w0@AJ(wfJ&*kXGxl}Mu190xDh;|^j7Iw> ztdHL%r?`PRxl_q8zGbdaWHg4Ec- zANFaGH?!gJmpK0z zNQN=IPZrFt8t@|BfW}3veO1cD?Y0J3tTAx!O-GVvCJq#4(cwiOq=~!(zfVGCdL9i1 zD8{mvO%}5GNcNAd*h8OX#5~sg>rNz#=*QkZnDKXfF8LuMif`D z-?Y|D|~?sx@IgyBQrKi5;Z-4F{Q3&0a<(rLDL% z`z>F(nW6O9GOSSc-vL>jEGiSeL`#uGlwNPN4nG$xBDrDGm1yT}BQqo3&8+%PM zW4Iao9V+By7X|k3Rp9V$vJfZ8JG!$cNJb)=_nl|90u5HNmy)W$uSq6R%`205Ka)Hf zYm#q0$wWHR?RdL_xsK&B_+6RYX6AZ9JwJ@h_r=5iL)u%nMcKV!+XHrY5Q>P@5O#x} z2X^1Y0JhlOEopZFV`8Ah%m8*X45+u=l-&h`o#ed7{d=}|dp^MPhZ~46jMvOs*IMh` z&;3}dLN|IEU)J|Wlj`IWhp8~JfS*L}d~M>-937-aR6k}_&m!+opZU{UqOqoPG&%*UG4Bq0bH|V~ z9u|$lDP(+#nDxQmSG9^7-7UzFsOV;N;>Q6Q^qyVB_V>)H@=so+Wb(72csg z@qRk))nPU(YjVpX)6k(~I=08Bqc!VuBbKLQU=5x_#q(^e9rMC$GZ2};+>HffkdKiq zCf|7b7kLzpso?o^TD4Ed!p`K1_`MINlb_i{W|B48+8n2US7cyCB)zK-@-c|-{rdKw zVBWp}W4(-6evi59W=5zt^L#a;0OQ<@@a|rK9#sl3fa5Irni2Xqj-51qoKt`@%L3H$ z;2(~yJ-J2%?aRmD+jO#=W*ze#&j`EdD}KGt2%ZBu z(777GT>0*|yV$tBx=@h)yzA@=yY!LMPU*Y#i}nmnov3de;-h~&=}_te+hkAI4l2)@ zVGB~LG>h^mdix@^-KkU$&!$y9R{grHuit!{=ak`mmS2Q(PVW!d2Tm zr#@ibvq!SnE!WAYZCVMsnk0)7H8MXoDzWa03o4Q`{J5K$&)?`*v~$5?_GzBJ zt;BDg3j*fTzs&mzYyxPZgXCC`zxMnokALphHtGO;5HBE>4YqgmAj}~b<4YRq(G?Hzsr%Zx*E%vs! z>(Ga5L&bjbkRCc*iqavay$)Awbo9{j9Et0|YUa6kJ}et^N9JH?a1PR^WuZjP-rHh& zvRJPidz<^Qw)C1!$iW)_Y{Y1o1-g?xsZH1?!*ykkLaz6Q(bGsSX8T3D(CYGhFp}#= zaznpz$vKA5cf&fYjVcFT54h*!f*bf4PD z*!nKgLAjjT)SPw5*#?YruS7O*$DydM5gk$9_?OXwC@-IiFPJ z91{QCi0ZS9XrgW>JyyENd>0p~RohJ#opzPQjp#>=;aYFMImVI)DSy}u;hqYN)sRP9 z>5q1H{`jT{q*FNnUA_G=+`}JF$e(>nqEC-=b;c-iD(jgU6|aWp-gKxqe`aT#T3g`_o;@f7rr>}D^=5;#VkJ*!n zE#=fQSLqhwBx@@&FMMDdNqJvNCp7zh7SY)>)eO^{nDgx34C6H_U~nKKF6oOr?T3a{ z{1KAui)UeK#PRpL^4b(Bcc8`w`mXLqq1|`#f_y%`r)5Cr&2`r;KEEHl2bmSXZX#Wp zbLh`aB!fDZb2YEg&EZZm^+h{Lhj!1v4^AnFVWx-Q~;V{SF1n zP%6ov*^kiHAOB{maI1bG2BrHWF@t~Sn$+@ZG)DH|y|)GX2>AEUyU7&&HDK^H0}}Y& zSvfER^WS8k?^}M}`V)>UDnK}`?^Kpbd zk99_+$QjnohpLk09eW!8lrf8;whO**C3BJQijiMk@u@F+3j4U=M@~3yB{1_PCLG3v z5oq{4oLnmV0N1m2&bcRr^U7I%zSWL<*uhDt#C_k&Q5^IAb8%`Wb17$V&e)xUf8)qI zkSDm=jgH2z3a@YELhA8rk>v5C@6#=O>zK4@sFRM}lI7)Pogjd{kK`}5dXkIls>H)x zWG~9oMXYC@eC6=6eD!qT%oWoNim`$m}JnpG&59BpdIg-o%q~F@&1%XCjT3~ z!Q>t?dGB&B3&m$%pJ@-tTMQ)A-ZKfIw{@sv(BbiLDfq#D0kR-U-d`^c;=S(!J;WdBw&MLLv504yN_sBd z(Ql>AK||hmCi2=ebmcv0RW{;+6<#l%E4=)(6kd7P$fxkEeKC2$qJdhOS20Q4#~hVq zlaGkiDV_X0oG9z7lO?L+3j0gU?Bw}Vw};FS<@M=2fG%bCaM+#Ty?JsN9tALa77>VU zLU(3EEdqH)v(hyQmaB9qc*OkIOSxDufqeeD94t!W{Y{^Pm+!ODXtKg<+#vEzWJ1>4 zntA#4W$rY2%Wd@LejaQuTi3UhNn_mPhSEizJW|SYy65+;Hpe~oU_IvjVtgM3ylR%p ztT@g!LH>we7>HpO{%EwE{MTfEICkMW|6Vi#Ox#uN-p>JlS){y|TlM z)?)X>Rh%u|IjOioys<5RjXrqu{QUTFX- z-}A%D@&4%e$`4KEvNwxo2V=ErW@qg{`**y*b3R--f%75fzz450F#8Fek%Q@9&Q6EL zsRA6W#d)yBf4u?BNZ?+&_#E?$qn*W`{NlnX?y}>nv$VBiPi)Ul@(5-as4A67;R>8? zXp)k}W~lO-ds)9g?BJQo===Vd8WVu33;p2Nk@IwUHOj2j__CCHuSJ}f`|ZG|Z&9%K zvWFQ{8}m%xZapUpXEL;=9*4XF}s|5POg9IRpVKZzY4h> z)i_#*+~5c98HdyJ8OM7o_nS{k3{Z|_7B^orhr{fh;CiFp_cY|+Ex>Un@|D~hy;#b7 zDbF%4j$}W_J{R#YqZ4{*Ysq`tT&_2El}A1<5-`&Yu9eH-!4q@5sH?!$Dhj+gSth*) z@a#$F4|}^nwCbUPVU3FU&jGOZj%MF2`|o(2QrR2Of%mV;*n#jX+#~8UFd;SroxC&f zF(m`NUNdu&uhqqMbRDaiThW&Hu2sf=L-FBkg!8!^I?q0FuBV@M&B5_nxtK9j;nmqv z;WgJ+;bqDB(7gw1=AkNMv#D_a$WHt7_P33;cDIDorBCvBlug~Rh{GJ#NS(7sJYL~=*09%Du*#?D|{xxgz z-xOZMxkoOJ(@1lpR&MgzY+kLEbIUYRvYR!DJuX=N-37TXxzC*ELYE+2mVCc7;e8@u zM;Jc1MPP&>9JRkPgV3Jm_SJOQ-z*77lXX~AJqfdRai7*C2eCXKzx0dzLVcD$Dzq7!;CYlM71KPLk_yB(j)ScO*xKmY%EMvuwOWEXiW z4S71Rn~~@}!hq_N^I>LeBKwwc#We4v*+Bv#^zI1!YoUyD!fZqVV%`8V2g}Q0u<6;Czt`X;1Et+|9z9Y3TXw zBl^v-kV|j=NXaN~RDH=DVe)rQEAmkNfsIrjQ!F;Kym{}BLM%C^0ewEA`6oWlgd$l@ zzU=CRD3rEi{%qfTEL+q>HZLud#(CZt{W=N<$EV@Y;g9&YcN0k*TOy+;`vG5~cz(vL zk;8fHW44ry)eEHtIiLzUdg68(xE9RE^%!fh*8CN>LO+;gk{`UsoZNGHI6JU~_;xFj z?ujZm|A@l%)6Dh0%G{94*FM4j~b*n>8&_EAnGaDH;wn$varGESxg%2kT zxc-!$z8=ogQiB)@56Aq5M6OO3`pTwg_@|5E0;jL1h|clrva7fI+?Uo5P{{Ni&4 zyt86n_S)u>FtbR~zxkqc1G&puysvfVy|m0io{_`dK@PED0Qs+q2Chfh@0?~W4|oQx z^7lcqo_SF3(s&K%yL?brM&2tDpL#wh-5iO;9M%r#10A8NFYkK%m6bfN?Ny#U?5T8I zYoCYJ5e+4CCG)u3_@U1$=58NPLvuqOOh21T-4!LWqNfim?nS{f#sG=T$0+*m4)5pd zYwv^d7LnMUuE*--`B;C_PC9y)$fMGKaN;n%kRTs7^&>s|wo+>X{iOch%ycGi`z;O0 zw)q%QkKWSm#nLF*2cw#mJ;yxD z=UJMC)b%ct!lmR)yVGfLihN}b^UXOf+P(iPrz`s6C;2t&Yy-J?W>^F@5@+usc~{>L zo(}YeKTE^tMR}0PO=Sb?an&7t@ppVQLWLZ3MXrq}Hxy&TQt3fn(wX_l-}t&49rM{c z&{ziP3Pt7ai$JbZKD=O#whuYta7)3IBDrvcIZS8Bv62s+Ta$i3dIqnJ`Ym}sy^-EF z8eZg-Q^|2Jf80cN-TF&L#T!-)qEMxOItnJ`W4^DAG*06D$@lZLJyGy)Yry&6VzAnv=autuoLBu#hQxyIoU)lNIM_663l$BA15_OutH#Z7)`OIyvmXCu+ zT8MkQB59P#|1amOn|;ZFUd%`B06RHV@SAfY-w)#=abdgx1#9#0rkACd_LRwuFW$J6 z7KxZ(1MfBTC$?)L(`y&W=7XHi2S;I4fdLku^H4OVv7FdZBs0tVAjgWYS8oHF?jq+t z+lF&n)ECH(^B0L-Oml1D%SYn9x>(Wuuu}YB1q-(E*7b#&c%+)IR-A z#DKP0nC@Z1ME`g?haC~~Efl{jG#Hbag-zxPud5g0q&Aw7(&|Cbx8^x0j4Q*itB2)TReB5?hXO0f50Vd! zIaY?6iw?-|drpYA4a27%8vG`YwuC%ah1G||u+tHj>V;y<2@QVm-1^{7@=6us=~3nX zYh);HNAUGMMqg7oh1bYmv2wkfBiarK#rUTh`i016IVrqs*2c-Iy3BSO913?nPksMv zI*r(OTP|J}+-Dy51p4Ew$!VU=f?s{^0s6+Rd2F_=W?Q-TacjxO^g*nu#$l0Z7u$%m* zntW(m=9oLUJ7etj5NH=C!m5<-p8|eAbCaieI3kSP=(@ieoLi8^GiHTX*D0}b`jR6K z_yyC=pg~9Sq$NQn6Z8+D*D~RN3~o)QSZWwz$%`eEQ@cE$ zx#5H8I2&n?Y06+MDo4NM)-3e!p;yijCqB%?nmL&~+VVuSh{?qL-h7^l1o;-`jFzi; zwiKF(nOm~3W|Rqy+8&bE-yP7ma2a+D(%}5$Y>dh_;ZM(4d34Vn*XdjQ<;i@~{^Z~q zD!j4}kW+h2zAru)#n%&2I-B|FCKDV69+p)x_E>)+6pbp7m*M!WpJGDGLmIiv|F1SP z7$??iu;d~+TyGOBYH20yIdj;D2BYW~$JfU!Slutfr6&i)aL^H1_kuCaQ;V&MnOI3) z&+O?T>GsVLrad8OI7EvYO|$U#dnvwqCrAf!iwj*s@Qv4bTTm9_N7KhQE>>=nKegBp zf~DUR@gO-1ip3_xlh^B4n|ZO_L&@zV;#cD=7>s2YZ5=PwD?4N8xG=J=TIBDizwciY z4*%LOW&FJby+YxaszvX)%#ojFf>rWCxn7HIkLjV9mO!rXStffsO*m*BCy6tdM_e-m zU&(dW^&q2D)x`V@t(;D9!qNVrsGUK+lJnTCg(h50jg_nR%s5LAMaMx}OmX7-nY>VvU-RMKS6^g)H8a&*a1%L9+A0x?J_i) z&nyGZOAaSYXgVWK#&|j6o@WSD++Pfu#X3?V^JG@XNif0b9JrWtZ|N~ z<>8_F+mFpWl2^L$)|9O|E{@<7D^>tI4cxGi}dk$_=&SPZUE04nL9jPAYt8`oK zT27zvs-5TZz+GM43bm<2lB#-cHM~vzJ9U9RA)t}xd|3|Np7N_DR?txBD1SZPZ&CIo^7ccu~>m+goSx;sTeTrsX;_gxTFow14IZ0wu zGf6Cl$IG$DTImx*=OXhIs--1KC^N%5)r*s_RkYH&k%s4m8rfKxJ+76tvM^99Gh#K; zGDsuGPbA5f1g&g1mMAXE;^j^St=P6pl8j7^Y@W{E_D{~tO>sdJa*OrZkAKyR{rBr# zkj}mLmnEzvkD*J!$_?coDe-i&8|-XS;C$0+f2Gg-u5%#psML=?xakJ1GW zt(o0)TnRfD@`{t4k>skRv(pt;^^|0Nlu&SNeyqzq{R=XUN;ecJmFOm}FiQ_djSKYW z{2PYqDdDKf+Vj^XVfZ^J9AjpO!{JFdtnP(jYQqRDUmK2Us&FKC3x`Kw7@q771Ddi& z{|$Wsox&mW!qER79Xrc-uKgqoy>F9Ubfw?megqyK=b1`KDECpURZA%1U-At6Rv0`R z@f>_*IQ|~v&)KoYvxx3t)~9Ro3_P+5dr5Q2AdaSQN5eHu4>}mnYO$#=GoJc0n~P`X z^(}Zt#Pvx3Hmq@6X5INGzsI0uEnSD|adi0{WHw+HYY@wM&bE{8g89sd+NQ-3GaY=& zSl3>|IycYcezN{ONR@=wQCe7w4(s_d4g+*(xHkvO`sZNI{%knCqI=OU2NPLuK7K0) zT?)zY^L%Uu|LsL~Hp<DWXL38%(jy%Ua>OAHT+VFg5IcwgVoaId8 z7IKC@m%BUMB=(?-#N|55!AMt$Z_`nFpK2iuVp_?-vvkV6Xeo^%Tg!yu_OfoOgR~gt zB6Ci+m5c0E?`-Zacjq>jRyJ-j=#ah4o@y_Bf3au$gsZ$OD#Tfyoqih8>ZOGJO>9E`-VBx3zagw3EeST1>D(tUvnW{DWlC0>7YPsC2I}$S&JQ` zK*)5H9DPO)&}wE27MtOG0|m1mOJ(phlbF*3ciLWo#9yUiWdG?_{@a9qm{09Zw|zqe z%1<;&6R^ksAzeZWGyIG+$Aozb#N^Wv)1yS9hMHvc7UmT$qC;*^sVEnyuEnX{V;Q?3T=C;kUg7uLzRc3 zIK>bDcJ)VX7rGvKu086P9|k6JZ|~1~_HsXX-ws6T7k?ax2e3^u0xMkNlhG(<@k?=Q)0D z?&TD3xZiz2zv3h^QX|y#_ebM-fAR#{Xhd16(P@|(!o5p&1-cif(P3YXE`zCb-1Biq zyQ^`Fwd_Isvwn^m<}1lH)~7c}rN-`@D8xNXN4X%@{dr!}D}-*vII;-O$X)#;mspid z0RMgCi*)RKZonYcd`8*uTzpgpwujUGb|D=XSmU^vl@8;PbTkSjJMh|o$+I$$&+q$| z!QS0W12eH%2YzWll@Bw{>)V$xlcFZ)0hJG1u+*_V`NVOJ#g2^ zUfrSB=N7$k4UMRGg}H!}3gE`aue#BQ39ad8s$M{@*oZJCAD>R5mD`Ls8bo*8XZn(+ zGSh1Sb13J#%d!p*a`Kvkv>DMtEbSd-SZ#N?VCEowPV)V~#!ZIbcb9}%XZiY;u7wNq z7cFv?F3J|tu(_RFZQ4e9Pj!<8{hZ|l$CP1~oxFaol&W2vr9(|;ahPi_A7?0Kev$L=}SLUQw3cb3Jf1pA{Ip) z6Dv(Jb8o3kcPoeO26GH#9qoQU1=cK~YimKNtfY&v*FAC&niBcYg*ojH6xbG3Dsy_% zx7dU($9U#@)+m$J)k`HhvW)%F^r~{4MUrFOYDGTsrUDC2mP-9@3M}qzhT50SFzI5M zR3+~_F;|7%WK5nPQNiQ03Qa38OPZW-UHD4XL??*<(v`&HQgNQIr10+GYQ?uT&! zzBp_2M*_!W(18HdT;hvCgH+5C-GQI0I8F@odc0x2dJ8prsoBSwL1$^tXdH85?&cWg z%k|+HSf^(8E3-HG^&r;q?rvgkSFjq(`||4?Hzzui8SbsdOfUM!mXJSgy926L>i^aH zY}V2<#X4mF+G>2_`E%qDj=33X%nzn-^$>j~f#g~^2CF2Ji7=33Nio21Ivr!%vmd!@ z1}3>>pud)^@ZNNUm8Rol_Y5@mrHdtuW05tw4F3$&H>Vr5)PR?J$W&Y*<5)2R>Mi78 zhNfeXDFatob4`!o82yxn!?QDxXG@<8$LOLW^2DrRt!}63=~%< zM>vx??O*ay`8hqOkBxYCm#lB55zWm$A=sAgQvOl@B`-{Ohu0V8v%WE6D%rz~cVvFa zGX`20U|N6?(I;73Eihu#KzdPGJ1oz!7qr%hv48S$ZMPBUjr6hgp#OvCTz^vNg&b)_ zV;_1SryEgloD6aT*_6RgJk))!>CHw?*N?mI=9zf6xqh_SmefftKXp!<)HC&NVI}?T zRv$gRsy_2@+g!`@Lv9;=pTt3)i~i=O-b?J_@gh0hb6%rWo|&o^`q1sc`U?ZDd!+5@ zkk)JAVb2i7L(lp@CV4jf)+lYV$7OxrXRr1Br=+I_S8tdWS6R`mSz8zVz*Za2+n(8? zKjPOQZPRRhs)Zp@mgI8pzV4{ZpG`&)%$SbQ$di*?yS3Cvvz0nwAD`q}GY|5HPO3hp zr(?55#?RA;{S0!50~2N4jU=(uYUTE=MA`j5QFh!k$+$487>MxWlZ;Pf9#{ro@Qx%*wj2 zL}TuUD^796f|{;SDqIoT(FF++E_mjrL>TLAJJ-1IUO_ki6D6}3*b~EEmtzf`F<=Mt z;fQ$8z35?bB1ln3`+Qa^aY>iH}(!3HNxuHGHuSl|G5Z#KQRe2* zsYkYv_0y!6>~UE}ZgDf$f?LVEaQ!&*64#F8fqMC5;M z!i>r#n@KnKu5A2XLI-#ezt6~Zr%w*^q3H?vK-V{WYSb0zz~Q=bku%qhSN|{1cz>Of zT**;N#{#9?%yf|c1+8V_eizB_W`?IX&9Qlvf_V#Ei#eJ>ZBSqb=ibb_Dp=kLz||bC zp%$|*V~q+K$LROF#yK!5ntAbDPjKDxAv79Wd9VMqH62-;lfpPxZSKS@NT+nPa^hUW zb9C3?biBs#p4`QV49*wB>1>KyEhWI)MLz#>laKpaN!>PNF3ylgdqv(p#|$Tn znYY-8a7cKdQd71f8dGO;9BfKWl(YU6yID0B3o}R`%XeEV?ZREvC zdL#4A@TH3xmdr89nQ81Ja5aOwy*WIu(mlxQV@F=bdQc#qr3B*Mk3ekgxC2(_=m7SK zM&52ZlYT{Gur3;j-^mrkq+==P;nk~{i}{TAf!XPp;bp|kLv%$)v&Z6M0cLQ0v%!`w zTU`tJe#A{C%xWchciT#hg3A5*9fxuFV$rFc&`}F9B!_;%&s%9^I|$Q!ht`$XpyOz)QL{-OrPCILp7&Mg3`ji*)bmE~g7yi?Y;FieJ0Rr^f6p>QoNBcbK84 zg&Drzq5t`V8S2u5SZRw2B{%)aSqCCvgFnuX48)O%bV#sn=NuW0hUa0#M5D;5d|Y0Dfwy=c(G;Na#P+f|z9n$o|6eE@-jK1@>Odqx_~snc5j6#?omu zDI8Bc$)g2?zI)_gxo`a^2#ll zf72|7KTD?Ipu(&7BYLeylWWXYcvalSe9W;&q{WUTDdzpG`x>3hNlX!|={k8hm06um zuBcYq4Gwi%qQ-3{j`_O4+AIRjY2hg4JZm;E93{`g5Wx90@0Jc7(>Qnb)?%@a`)8h& zPvbtkm~)eFL^hnKlG__YU*y?rIzVzUg$&~cvMCeu6kcz}Fk3m73?ay)bx4t|r*-1i zBS}`?(Mh>FN92nq8IcfI)c;LJWtS_4v~|VLI9Ci!cfsWY5r_{8M=f5X6nzIqb({u6iDd){SWG(6TJ8(kbRdo}4 z@yTLz9gZ+FkfS;M&2Awk(T@1U^J2WRJmf_G&fv-=#E}J z+}Mx8JZ|zIhR)2T91+1B8=i**M&NdNzD~TS1oucnxSl+{O%nD`;A@t}*XS$f=9FBt zypW4Nr?PQ#UN-8|4cUi$!#r}0+YJh@>*OCcpC$Wgqm|#+j!Tkjl5D4+xx=Icd9glO zyqhtnoNP+mS~uKY=!So`@eJpS3oLk^(w_YSDZIyyNQ}UZjBxfoGxLIHA!l#WiMWSc zWw|88{9+F^&v(Cm&jt?j%%NN^Qh1JVlJ}td-E%N{Ed7<_QsPc2yy9aOUaAt-7Q&bl zR-XK6ShAcLMn`lHoeaLBm38+uvLCK!`G}6ub#555$`z}x9njb&9ibvUd($d)e5(k@u?# zW?tiY9$(m+Oi?X`*Y+!XFKt$M1=MpD#Yk6aUX#6Ht6ZgT)s}K^OABd#&m&^Y@JI+Sz89T~a31)BN$mgFTS90ufr5nGlct@oOi~ z5IU>L`m^7Vd-aOn$)i9My*_lctDNiI zR%(1EG>C7w$ST&h68S93HPWzN2Da-WCFWTsUB!n+1wGS80I{`H5s zYamRARd}#58gF~4F_<6U^Sv|wU*?0KBIEdmy`WARDEh?y%On{KFcpHks_E*WPxCRI)RsI0N}x-}PL23&JeNsG zCqI-9Kd*E+?%`Pt*Jb8>50^h+L?rKDyJ{C;(|x{|>lI+aORbc?&`5V{jVz{re)fc; z@`l+(*87xj+u{n(a2HHTChJWOY;ZXxrgJ{D;`)C%KRPXn!0!|E4{}ai!*kLIZ=Tma zX74%AUB6lCa5qqgUfZ(BB;}yN=WHB5l7qF?=rO;OgU-_wUZwviyn+VuKDM5|+PR#I z__fnt62-DMxwxh}X`??b1ISv|o=6V?_be4TAKoyzBE*OD^uOH0Oms%UlL+Q9vKHzV zffM~X7jdufnERCW?mF}}@Hz0laoR5lv0SIuJfwq{F&n+x1eVr_!0HVVxIk9!W3~=K6PfdKi|5K~*jM$FuEsdt zPraD$lbMa9O7^zb$-zd>i@iBt_bpU-b>cn3K9k(}d$Mv}&AcpmU%j|8MSM$GyEv?q zfVW2^dt{1Svq_d_on7Enq(np>-OJxyvFVu`9CKaa?L?nIU^s?Mia@=%2y7o8fd&t` z7n_y@6YECW?|d$k=>o{qqRCM*mWy)mbZ#!j)?mN=Ccb8sa?tu}Haa~}ctzdf^&xBC zoqY=_oTs;}Qh2pEqLWI+8gZ+WBClWRm^q#zQMZ40XMkMU~bhfXJl;;h0;9&m-!w(U>%MN31O&voo>z1IxJSv6Un}~ zxV7{OyYlY^S_GBPg|RdXN4fqPk&^?%dHSk(PG7?J?%v1rj4Y!^liA?r4|z`=_kVfD zoZrplR^7i+bEOY%FQV@+m_4i=I0m~}%kJ<(X<6SFiGk!_5}6Zvf_cG%8_39Ee`R2- zFP&)Q_-3(>wG(rPM_S8p^-pR0=^s?gi^TBMH0*4Zk4csmGIDdVw9fTLxFhpYZ_?8j zNN?9(3kmZ3CDHf1@%Eo6G$XHfYh)hcE;p77^pvf;Ngv|fDArlh@OwCOevdVkt^vjJ zgL{er!y<9&mI0pD^yRg%67|GClDWzo<*Gy?x;DAXO8K}E(nvCxi>+4qz<&jK9GxDo z`Tg+^$UQOV^wbe=G^77+gtq~^$Y;e?Zz|=Q7E8CU{~)z;6x5cy*B$zZb{;l#F#eJG z?t`HyABCza<^{DTSEy(#R`i-3ddcS>&iv>#hT3L4$9iBb{zZReBsrspGota$j`Mm``pbG*$gVfvB)g6;e)Dmv^GvQE z`Jh`bti){d9~n;H-`|;$2zjqZx9fRWxyecbpZ}DpO?}X&Be^88jrNP?b63?F@+6m52NQ3$brfC{O3m_eXAP%R&Q!I_9C_rbcqEYOzcV`Ukn(N2Mxw zALjjJ{Qf4AdjGF1PV&KlKjhbVe;%2`$KTXg;9Mf<SMa`Tw0tes(8)j$;eu z`ILX~d3Gf9Mg0Hj^I%zIC7&A5*GBK2YsDyBYsS3k`pnx6qaX0nZ}Bhj1zJU+yj>c? z!}IZ}26Km_isfV{Urgy1i6K1=n3lsl?nVuz_6>4gV}0?MuWvRvzCB~}@Hf7$3|v?w zWhyVV<~8p;(e{4PC_gM{*h-rsZK?XDjh|^jjXy@I~FLkvQ@v z4eH+cxO}3a3{5PQYfF4EGk|_fGoG9N{D}H@tz_ldVrfr4@!JM+fBtE>A^G?+yp|Yt z{FT5F%-tT&9P<{;C8tkNd7+uyoc>qVSMY_!Xy%FEC(pYjA6GlrNPIPNltDg7;&r|< z&48AD$Wd;zlk%&J<@}d_5IiIbbA!|2q|U>nZ4D&qL5Wlv?+ukU3LTmoSeMDe*d|RS z$f8*EZoZh$@!Kqj84=_h^L#C(hD(u%i!c6d5{cKP^eVp1qvN-}^t|y)QqB#=d}S1x zuT8_({^SZH8%p!5^at?yS0J}&|1k~Amgk`?)J{&*XK-tSAG$q>g#T|n=4kU!(8faY zDlvzBhYzx5M8bnS;Fo#%@HRG;(f|CGm8E>Yb%;V8zFzwEeExGS#AP+d#U*d7{7BxJ zXUapSO;@ZW-M>iAR#8FA^YYI_ z_&9vM9D|$7<>F!)L2qfKO%(ntqi3)rA0^fnGMN11@9o|=dwe_8ybd)+v!8Gzxk7TX z#tJ^DG=TZ_k!h&kh<-_WAsh4guW0Fu)#O+=H=xh7=p)w6w3AuA|Hzp4%#Y^d|E|hB zkt2Cnyv;%uX-Z|=2wx0Y6p1kfk z0W-ak#c}cIS{gpw%*QZSYx#EUkIcT|4NLPVoV>#MZCM^JOll$l&V>@Q(Hk+LQP@ZB z_<`{wTqZXbed2HNnc#yD=g2QB(y(uAK7tb2Cq*8-a;XnG(%TDz9+SyY_Bv-HW%K^X zUHUgKa{hU3oyPModTHNUi_-K*GB%TkZOn`)8v`Dy@|kPgP@b>)EslI0$MAhv+|+=d zmds&~u#z#X8^!eV#gC~`n9uLO-6apR`m@&i{+IOo=8Z+uSyOZ;XPxsAIynbuGAWUCDgsm^gWu=ZN*& zLU7xP&g94}tRPo7h&?yI3hmJaVd#ELi~UWqFtohFYeJPc_6#^;|9|<{ZxZ3>%AS?0 zWtg`wR_e}TzH0C?7#zqq6=jkoD??@5y|Qkv1AaaUL7jh@yIPio6K$AzF_hfd0cY4H zEW^lr4Z7I#|5c7$q-VUGAlK>NITX?KnoYe-zu_ViE;czVbLu(Z(C9E!<$m`;a2EOv zHeuP~gJM&i{94x#^w9DQg&dz#Hxv6ZY0rDz;;O@kSFf=g1!obbzKP1d)IEIIlCYsxO~^ zK&*VH&(1S93|(t!;dC+^%O{yI>)~OsD|CVb*F75Hnsj3}-J~XDU5J&t^_|f_ektyn zCnE44@}6VpS-Vbe!!HN?qPNZ?Tm!cgS-AeO44*q3lB_f*oV~)Y?@Pp)Hd!d{Z^AA2 zL*lWE-br$x@8@Yym9LjW4}SgMLo(gyfIe=)Fb~jR!7ZLc)HEUDCcnSX8Sjn+qmr`* zq4k(A^t231hsDdpSO<)37mTZMTHNE~Z);>?AJ$>1HQxylw}P>W=Lyc2m{VNagjYH7 z;`zY=d98wR;I;;{$j$k#AP-o4K+;z`(0d(%G>rz94e7Z%RR-IDco~-G0Dp2@#vh3o zUyIK_yA0j?9FSSoP6&D)0*i_oEH0OY7gx&Ar_n)4ziE#fzI>m5X72WlOgw2=h6Yy; zNN67i3?(<(i|@Aw7R+IHRd~I3J|y*iIw2+{1ntQKdYxx3^P4hksvaxd?CAlt3qjKn zS{xAi@-CTR;_IlPk8cFI)Sw0$^!|~FnoY?6c0C~V-~=1nFgmdKzBOfH5&5+tulWBZ zKfAXu6#pDbgfscm!~-S_>2gpKsyJg&awx7;(2_04MD>{_%-eWSO7A#eX15S%wrR+& zko!w7Lx_<%&Nm#e(K!U&ZMA5|_f_qq9AD%;jakk(%ir5-EWNAz`o-xcY-aB8c=Era zINm*z6ET9krS<~|peL3ckv68_qw`?_HK z=Jl*tm3i^xNfYlMl*D`o6dw&m41aHredMOe! zVVO*iXZWNL6g^FZ9XZXScjRGP?w3Q~9nomnGTa}acgg`zU&lQUm4F_!bsY@fptd6l{L+sI3D+?_NhpWChs4-X!YwH+OC;l?ryBu}~u z^rfyc;l{{A0`izK;mn=q{N{0u*KMo`wwwp9Fh|=oF$8_BxM#e{@lsrdcXtm<`7aJg zOA5xqnau5NPQIS6%m1sNG2n_%s`k$@{jV)%`WJWd^{f7NNZXdUHPt3;yJyE6D?MY* zkJNX%ZyrRQQ?AStWzt4ow4zv66?FM_tnN3 zRvVOPI-Fj`d(OD2QsQis6S^;ULE>d+tiI&}aixQ2k&?a$7c60|`OGmFoFDHBKb|?w zy6A!iYn^eh8C^X)lsGQzi=4nS1WRWevv9%DfzF(7nIYKG6&rL)l*GE=^KCj`E71Kz z{#e^1j6K2h>s0?gXG489GdpMiIYgclwe22((yi<}y~rB1lD@^!JV&1uh7m0zurfEC zS)n{v;@NhM2Vqz`fDT61N#4E>L(>)P#k33OeLoa0`EmCcW?lRU{a>#AAAYVXA*X9g z-%l@Q4~B*#+?>7$J-v&E&k^zFFuob1nkj#1VVSo2Ba znfV0XoBcQ+SGmu%&|4ic=4z3%NsF<~bvWvvMcFi-^G{?QdN%Vcc$QRSGV=$I(76-A z$Ni>7PyZy8EYQ*Iz_Sb6BKgiC;>T&ENOCgph;${7yFa*4fNh%mI86N&IiA8_{Rc%?L?WMp!pA^jQQoz|qft*MD*<~gfO~$HqEM0Sh z&CuAk9A+OT%SHFfy-8(Kj=$ppf9_RlGZZA4WKLX(WNj`JnMs!;*~HD4RdCqHoF`iq z2DVVaHOP*;XH#mM63lgeddRsvwg6+djN9A`NP5Bhtcx`Sj%Kh zcOd_C_DAkqo{21rg83FQRT?r={?U*R^z2Whv*sc>s7v%C_|h+QRSi`T`NRZ%|5iGO zp0oaYhpvLx(U{2nPOCT3s9BqRZmd6SPN7q7N;IO2Sr<7T4f_;kReLks31T52IUdIrFa;7?=adUc*>2i0#QiJ~5#24+ADPOUDCKI`S@LFuRv$ z>ATW#$%3`&&l$LUjV#tTvXaUSSZ}A_;XLc-v8?MKNoTJz^ZfRwW6Xwpe0)sSi3~&| z)*~)>8j*j2%;A2z`p+0qJIIKx&FEJ;$7~6nr=%{)M?q)uSNDx%28?*c+SAC<^eVo~ zhvjRsk^C6X8q3GU1vqT^2_++q$UJJq*N_67QXBCzhOVgX%%5CGk6Z)RrmGg<@+Bi~ zA0lT^m7HXflN=oEEYq!=q*l0{+$(dC5sSzyj&PBlUF;<(hF*n(HlnZRBIA0xi3{0B zpX!b>&x_e#x7=lX2X}eX)lsVMwUtt9=0&@Fgw=9*q>zKKIvsB)=(%s-$Cez-M z2QD?qd)7U!c2J=nUb{)cS3X z(s~N$oyZukQQ*5?flCo|q;f3AeJqw)TgX7}HN&F?{QAFS96Kp6aY2bpsZu5_9TkXJ zMu(!OA3~4&p%KSd&T@YYTtwgLGk~!4^SK6|^xJ!k_$5p6eOO~J; zGtRd971SJS z&)=yq?wg8kMHM!(wzFb<0HR{m^mIhynkzHglgMoxAy?uXO&=v|KD)@4e2YeBj+Jd3 z7hiADlUkLWBLA&j2zyl>nC)IejcWgL95&!Mx*rYoPqM?eqj33K6xMx@!sIsm-s?PP z>dSHTiM76JSdnAr&oBC*;#eOWK$mG)I%2n_GmHDb^HTb&o~6^J zO+JU*$0mEa9+M4lvE`WL<1VU@f$;(9uH zWLfm5%roN94%S918PPq7=aTCRFeKlIrsN!_XXfKXPcpt0nN2p9-0#tR94jDC%&|55 zml6NoG2(s)j>(Qj9G^|DIGP#o>H?_$XIk!MmNbZ@*n)O znrE#39IpmG=0T3X*s;b7pQ~3%8(SHv4+=i$d-u%LFPmK_?c=Pl-jAMn?AHg(=@s9P#|O^(GjLH;dFkj%q+$^FwP zbH1^+v;L68bvDTApakiEP%me{>Sd^nQC_bzO4QZ^V)>|-pV4{=Wk0A-Mb5}n)=Sjo z1M-VGS-q4=vN=tO?OR=7ysE^9ROTGiQ{mBg@`^Fc&6=vh@)gc_FRtkLi1%`?N`y?H z2kfDWb08|{8mO@iN({(X;aNBC1<6KsJ?VmK@h%wj+=VVfH3mm=zd47TqeY2D1C@CB z&J~Y`tI4D*;TfXB%MBI0i?cE1V3uR+XL^$bIcbk4qS2a$gI(KbbcgPPaF|e=mnwV4mDtwj?iEg|jjVTIl$=TYj9o;r{PTK4(_q z*^A?S-I+h=rm|-y^k3`|nvMK-kbAjnK(`{!shIV+pTJod-j_#^QykNj`D%Fv)N025 z-8Am)jJrqrSXYzN)oRrnlNjkv8cq7J#n7d@E;JH&|W6Wnh;qnGi9 z5sObUzq&VBN3w()*!%PDYsRm}tR2mv!z_S%H8b~x-kd}EV#b!w%!W3YG4dU2IkT9f zzLrs>z%H^ z9x?ZUL4&gX$4k1}XCcLx-kCzy@3zrFL%;rizj{n|lTn5?^4DRdM25ANs~ua(KgCL^ zFt8A=9lx^! z5qgc;q1J)u=^BVb%XBE$gPy;IQ5b0zjg^XMRJf)?nBoE&3?o}GEgj`D(#Z~{BXv+Z z^iK*9{k8xPO39~iZ*kY04>dXNLBri7baHE16{M7)RZg-qUM&X(sN~eXQfb(Vd(?ld zvFpAy292Rt>K`j8&jn$zX)vyZ491+jbXfA2YA2bMjZtu{%=ct|6fE4^)oU4z{x8YU zlLr}6GaaY62ih8Kf?Fh+_J*A6IF}Fm7j%Ge1|y5t=IS*H;4_du!r`r?a~C&ptm`UU zSGvk|i@T&JsN{JHXBkdfWB}Ls*Ig}g!chU^cm=kO=6h0Ig9K~tUEA^XM3Q%yqd|BD za{b)*y=_UC@J$_ObGRn%Cf~^Q!Oi0WZabu-^&=BTpENNWoG#%f`RF~j0Qfy^QXtmb=!j^4A!(q+jFSp?aw-X-YSGJ9<7JaeqIrOzf5P zDs#<#e1Lm`7-miP48X#4vPF?PgdEo~k2DH*8%CkkMe-oa`TDM7rwuHm~9__}tG zi><_cawGCPBTSgmEgd8IUYWT!9;!DXCWLH%33I#d=A+N+JXF}jp69Fr+{{Rn1Eq;F znT*5cZ3Zd&dPLNVjM8^BvyhDJnTL|u+p9!VUQ9KpE@OE3H z@ZLr@<06ff_r->EDCv`=+L%PSIWJL8lASl)KPW~rEBC6?jWk=0e9k%6)T&Y1K@C0Y z0Jq4ctlU8-V?23>y5ZR3!+ZD`@*vax&&*#3a%qEWBx3t*Bc9Nm)S)Yx>DVlEsFRIu zH#pPREE|{Kv!}1J^1ej=%zU1V!7zn)!aRkyYrewU!GW`*@rT6R>yX%Yp~nEk@*@IX47?!3*$$9nYsHO|Jkwe-}wXXD^PdcU41yz}X?WC!_>x0?^~Hqahfk<*#cwn-Gp?-NO*uk*tgZ>m_{8u2xUPnd5wqSR1)EhmN#;%mSLttkum~$oycY z=OG)F-e=;rOmonHR3t!RF@%k>lP@=EP2lZxCVphPWm_ms-vW>&cU zq=b2D^!#nI!q_dG?<~}yN?m3&EDgf)8Dt1glHYqb7{vuTSa=Qm+%$?a3_A2sM8T#v z-M*P*DVxxFYe)7 z1ATv;p3@ttF2JX7H)(c{{5yG;(SN(hn3l{oaCeoR8jEb*NalS3vrNa9%9`y8c=}r; zbV>jo{|dmWZGkY+Wm)4z0Intk;^BuVyloW)JksGe@4IU7{W?*P_huhW=zQ9Q`uvRc zaGx=}UpkJgONXLb0ZhCnseP7=WgPEWYUSfyf3B&G+llocr5u0kB-husk;<>#r5=5j z$2KeA_<{ANZ&s*lqN|#-dQS}&$>V#`Fk3^GtG(<2c?cMsf|k{g&&)1ZG>1h3{~bbrbfmgU9Bh=gE9T^PXowNAru>dP9}A z^3u~y#yNUO@|L!8X1SBRT<9nvKP?i${m!~!);NB?9GWVu@usUa+TYTk`Gg?+J0%eA zCpFm2TGgzh8XVrjd(L6>LGRbWzGoEb2hs=4HQs8v3CnqZ*_L$a>oVL3~e{Gin;{6)rl-U}5r zjZ&lM02NwUxiRxR97kixmp5i^aG4e@D*ne1@|sO{*>SEBH@b3u+$IsDUh=%3XT;D` zbd%4d>#sZKbn?xpSw0K1+AzmvBG-xcblH*rntoK_ZCS7I-o1t1+NFsyfcIZN4jQGU zjb1KKX6`hv%=21sK7jqEuTz<==b^+y*2mv*O26^^xc?<$0ri8X?!9+&L)G-_4DcXER5z}{jDww9s6g)Z(}xWE#&aYqurmW@K%vM z-(A(p`(JYBduGsAyNdkc3T8KLOO#!A66IC@L}{4F*FYaYT322N&nV$^hS}G=Mi1Xa zF3udz<3x*5S-fBJX1|@D;X8GV@F_81@e=y}9E{koAQ2B=aNdgjJ(U!*7`yQ|-f%t`8$$%loZgVeljm?>SV9jjm+hIrr6l968hxMjXG* z8u_9`1TM)&RDL#W`eq^IDw#cgR(1uP->1uW=u5g8L+OKVLhtcoUayn6&W}%&|1$LE zJN?Hn9unW0NwUR5FCW*s;L1TI4s=%I9Pc65^;Kdl_d%Cd@n`#L5nCJvtH0<;s2Gmn z1GIP;ZA6l9BIfTkVC`1khefciZ)QC|k9pTu$iJ@6!W1j^%9Lh=`(?o;k1TAo!g~p4 zChW4A)5y;TaAe4QER_g`zIbBkMhuceGBRG<+sd+AA-rVta+Y>+K2OCU)VtE78XnS2R}lk-2BzwFJNR)r3|52eBBGIPKm z+0ai?ESnnnqVu%C)eW*oZHCDrV zdnDAXI}ZI$Pvt%*nNg)sy!tRFdSWCjY7;(x%)#V7_VSv%gR zX(yL#f5{_0|Ndr?Sp1YfSCxx>-5QAU2{}Xu=5a6KziUb=c08s>?_Ya)T)RY4FZ!S~ zmA-N@%)#a+@Z%%U6DS-rjZ!Q=Qmx<#S#ZcIkl)rGN1UO_WDSC`$$ja*<4Jo z*-+-4E0Spye6ehEBtksX(2_jkGKZ!zZ|hHqXAaPP<^tQMry*e(dC44Gxp9o=#TP%M z&Sn3kRvJ?I_+|?mi@73?+h|{W^WxqrCKVnxbFpDabLrqkj+pOrmlYAPI+}{PzjINm zFS*Xmzog_7=j5kG;>G1u)Nsnf^x943#pFU6MgFwpKqUP5KJQzQ$LlryedT`0&Gr0T zsz>6uGi$bUSkvTQOF6h$!ruDhY(De5`S@Q4d3;uGEH&eQOV(IFv^Fy@yG}AroAF}X>A8uNhm++Ih*yqU+zjKiK!{{6BOinW@65~>tlini_w&R+}ZE}v~>B0Q* zJ_6fT(i_2_>(r>pV63jvWRe`3ia7D0(FCl7D<^D^Eg7C6e{>uVE1|^Z3klVZK$D z#!{MDEX$wyyM*1nGYVu<7Z+HUT$wHhtws~y}myV z?T*0EEr}}63x71=an*Z!D$d37b9Z-;ln+0p?NUDfY`*@5Y4oD!VwW_PE`5rn#TND! z>as^hUVFk`=0PX$-)sF#ig-W&E12iw)-<>`&*NNTeR<(mD2I5y`0#js&(Hn#2mV}J zTZvg!B)8aq=u)0P_m5PRz05(Kke6RA+NxOGc-)@ib#H+kuZJhd54LJ5jqJ!F(zk1~KLRr{$zz_$h0D0>Fdj?Bfehs|W?ni45@)fZ8r5lHo;uQnnN zvA-J25BD3k-OYzD}f#=r$2GU#eQ~YcD z;o4I2*AwV1*_?~hpX|i(=1-aH;g9MMBQRk$=c+=;vuh8?NqP?#8kz6e&ww7}$mTZZ zzGTimsmodUaTP+bkoS07N;C0fH+i?Zu~Ib31y7m;dN8a;GbegfCO&7EA@l^F zXRb5i6k+(-jXA151pjcsgy+GmmDBkYnhB5X16U~tzu>2FK4=8L-5c01SGq0-?!9)%75>b&aCnE8x;(fUIx_RUb%UB z@?2wM!kjXFOw$^YwxR+=?-y-BspIKOh%2n0eE4 znR&(It$^OcYE>*yk=wdo=*L2##d&7egw#OMGgUR1%^*9zzr&di1 z=Gg2PUp|k=z%cCO=R41fd*$aA#5|7?|G&w3#Rucsk_4>0Y{s+z3p(tHmFaHI_;*kU zF7bJ`#%H2zEIpDn<7NE6u4t?aLBJ0^Uhw0`G?56opd6@y%dUF z^oRQKbF8EAR#uJY94)!sBzpIn8<^2;#;x`i^mdPz*T-Fv+J(Nw7J6JEx4ZXK8E`&U z>e2J)Tss6a4klnX^Q`Ss%JB6ouS=U;G4=&LssRREI7#1PJoAW|y*ufl6MR#H=|W3D zS1+D-!DUz!y-%*VJ7FGw?(?ejtDeY2b0-U8-D0KjpGquP5C#u>1Ltot;dqC+*s(EE zJIDn??gV4ZU_E@-WMZ}}Ki})I(y56HKDmUV$qe?NT4eJ6vkWa??w3u>AAf#21Xs(E zJL2`Kp1s2RNU2^X9d|}&MJQIx)??hn3~UH3L(!~Qsn*67+v$EAcSVoV(HY3U#(!7H zemTbL?fV@ec<9G`_8%EIb)yVftM|!8xMC#p$6Jrp!!DY&;zPVH4dr!mC3$UnOY2rP zpvi|!tmNw%&GXB$+6jy3g`@=@BW7k|1?R(NCd5i&XBTw18G_$DA6vCEV-Y{EW;q9B zz)p|C@od~EH6p{s+jOGzh)n)$OcEpT2GBMa6!;*^d#-Hr5U zdnA*6vog+x9FXH4E@(C-6w&RN+ukP=z3W&|P)#pS$2&tanY^=?9+49{<2TPj|9hMy z)#Ld>-uchYdemyp8UjDxz*GCBksZWlsZb}Gt^L#h` z%j@l;|Nnl*cZMn{o10jte0jGv#k%RT z_fig8_42BFJ1FJeoXcI@L$;@EdDq^vC^J6gervtw;^%$6+IQ%eQs@3)uNM^>ru_V) zlb6#N-(=6X1{w4&QA(M`^o-2ynN|jQI?E{b?UUrrn*?zxV1GH;AfHN^2Uzux4_mIsMEP*Q#(XalQ({-91t7kU*E%RK_;dK}s zriA0>N#+Bx-q2)gIKp|jTXhb!s*N5 ztmR}a))&(Q%zBc`$S^D&5r)a5v{=wD47FKHiJl&cwXCIhj?iLHKP_Ihp=;-K7<#qV zV)T)4{O&DTZi2=vf88O+J{hd4YOz8&(diPi>VbA){ z=SJw966t;;%gA-M5&vAuI43%ab+9I69dFVBQPGH4KlV$0WaAa<8DFxQ9msk{1^%kl zpT3dYWMN{Y84oVfAv-J!$65Pm_R|cnT-Nl*lTGB~ zi(<`KzTAw7EwiARLw^r@*0Ke#5iha$=+v_UHbV!!Ju^d5RT2Ot3;@ zw-P!1MgiSfiyW{ml}hwMdL5;Uagzd{uCTA$!U|hcm_xn6B15VwkWn=VHt#h!`Ba0Q z8V#Pe34(Xz5Y!m z-YEz{Z#3|3Our&CrGnGg$6XnPkPT6|k`RRkI=U3Uv9DrBZ=xz1yAH6oQOMk>iL9G< z(V^P~9lC@@p<)E{6&;uz_>S2Q<8+w3kvVyNna8w@xz+3u?`WsPQWv@#mymrdBG<+G z|JP7yY2V@ype;<^_9>t>n=Hb$@tp}ZpjoHJAFkv!#0t4HdFazmG|6xLx zcIh}-kcM&W7ZkN;PySgNnmr*?)iWL5@5p8yp<`$wxvCE)=3bfbVZ8~_wJsoSD0|~m zO&D{M^NZut@Ga4V2j+B~KV?F(oe94ius`zBgcu85a}Lb+x|N3er`fmposUV^*h4C% zFOI$R!%dh6eVzC72lM~uf;j#?4`Y(pYrjffk##F$C;AlstI7Mbe_>$XqA&e%&U7)V z^3ivCKK3jkuXw!xb!*dUF*G03+55S@njVR9WGY6}B^Qy8Ug`o&>YI<#{N8`AruOW~ zto)+@<&NiJ!futQ_BzSG^j^gLc9u<9DhW3@OY}NdIpE_aB?&HasbM=Y7CFgnty&PvZv%Y2@uJi$Z(tH*8u3}zScA13o|5a!6 zYvwI1X20s^Oa<1oS0H%46_$6U-;{o$Q@u+iH`pTk-dIE%Q!0wn7OBL?_%tn*@3*b6 zvX>Q>9xss{SIQ*%yaGdcKK8B349U?7Jc;M?6)A9j1KlG-t#GoZ0(F*IHvupo8B9Jh5VJ37pjzjT*|E%^?nmFm z;2@NY*WgAt{ii`1_?rSSWJw_A-`3!EQUDBx0+{O;fPF*#5zsggaa)<&wo8MR`^YZZ z@%hLpZ?z4??`Y3FysQ|Fmb&(GVeGle|WVP>T$)JkTiOhp|w9A%b;o;|e+ z%yPe|gZ`=x?b}2l<9;Me^`cSaqeJ*#WPYH7$2=WO3(3>Oq~r8h6GBF?M>*Yu{2A%! z`S%6P{lwYo?diDPAsuB8O^7(dj4&q?de%t)A7lJr09{^P({b@TYu<-AKl;Ulra5GO zU!Zmv$5bBwJIERG{74<2|G&Ou(q-m(?8!$1{#wa%?)1QXY^g)mMwm5yDi6ySGBdh> zv!}?16>H(g19@((qPy!B*+&yIOC0Gx&Ckbu2l9lrziIQm(u%_FOY+o99Wx2Ct~yHmUj_ z`%_LdOiIb^_d2=Ck1Jm2dNt+TS%*~b<$tD3`>aUW&}dn*-I`@xFNPgVQFklnHFwn- zFUy>yls!xQy)wI7d#-q>PX4xHYI37fjk@mFBze~H{p__r|BhG5Kvl}V-)B9yG~RV~ zXVC^Pd+WbF>rOSwc!fb~=Ou_^wo!I1NR;vPZIwHjDF5_Ll6{;{sqC2`mOBR7RTM9M zJPq<}p;5kYe$m&KKCaJ3xx*aI1yd6xIsSmuJwTUt$zd@xFv|NodWm^%l+z&zGWBVq z+~~`B79_~Iq9n1LGsyCviSp+$gX}q%AQQ(O6xZZLdCPs?k>~8!_2qu8xe}G8st^{a zMlFjH2QRo{{XjLWGn5D&LDuj#nZzf|&#I(?pD$-#4l7YacIEH&bar1#coQ{NH>dC9EPqZr74p?8>};*VnKHV(zq#VjbUx=l zoO3y*Mc*;>)(@gXt6ey%wFrl%Rv5|$(qVOz`$O&*1MbjaHCPM7)iC^g8OrSVFsQh1 z)K1f4#9d~c{RlzD8DZGLz2ErtT4ZaqnD8+SEMLISS>%6${Ba?XVkP*B08_C)l z5%%7IH~vO!`itzzNxJ^6j94|D+~Wcxrg9&-l7Hu=ZxTu`(jT?ifU*2KVx0j#JGq}+ zOGf22IZ2CwjI;s9SG*SuGU5dHr+Y>uV$g0QezE>`w@ViLyWE>C$wD*7Y^+PoLZQjb z*UEiiWpartSyv$Ia_tTGfRo7_mY8wqMHWP|5cn7W>}V$LwB~HgM>7sj%tHJge!mr2 zp-k>Ie{=3-a2A@^F=IV{#@M1PG*yykJVf_nlPq|w&c?=}%&OxavYA5`qF599e|g5) zg(`8=w2%)&oMa{$xxbGq<;OF%j9X=qijGzYx?+X#hEmzsfvjFj1y1}7pf^N=KD`1_ zi5!Lu4MhIufd6G;E}tI7S$ED+T&GvMZxnQMqo6&=IR$UJD{iD=OSTDh=Ckic9xP!% z0Svr`?7p3cVY|4V^LkOWfHMjY=-Bdd6zlO$lKg|c{L^mIca58z;C{|nS|-U8$m{L4 z!jR<(l(SXf__F}qIzlGCEB9Zs2V?bYx_n3YBYmt6yX!_{u8JP(>d~<69EE-S_1|@O zYM=?f9+=QXPcL-ebaebD9ao}0pj(FmJeosBt|PC5L&zAsE5P;5ZZe6^@^#FlTu|gJ z>DFyzxLs@cx$w8VtxzhxZwnjUYTAVe>t zmv;#{`DRhbc}E6gvJRj6(ZkJs)``&f#@c~MSbF)GfQIS!u`2c7PHp64T+pVcp3!xMTIAhjPE_`@z@o7qBo_jeKB{*E#~&|R*jDrM-4QaRtB zUbF^Q_~#n;11}XYv%Y^YIRL#62EcAe5PlEf`}1%xvTp^Ty>%3vx6_3@NQd&?+{at}CWeHu0|G~vL2bkyS7Hi@jtH2SS-d-HginUBV`$i{=SEM$2e%ypB~%i4)k z+txD8(^2jz$j)?gmDeR!*d3w3*ah^C>J;$c@w9?pPo{@`4(E(Ee$}8(@4+Z(O`ql^ z&Q$O->KD!RpZjWOuI1}z>rk^=6gto1esz}#x>o7f%Ht@i(1bUyIYYqL5`Hlc@-Yuz zrjV=DGDE5;56xE7IQN?3Ji;{RP{5{B&f72rJWf(Rt<@NPEXS@GM#C_KIJ6R2=$-LK#_|PZ$6MOCrj|}2IgLqQMpuu8IaeRUoa&bz9SUg z_0B20dyP?e-@2jj_8?zy{}OYL@(;=Oaz=X5jWWwVQL1X_vfONx;?}NcJ5h;Q^jBWu zeCWDfD*6SvDaW-jD!@}&D zE&QAwu?`YPH*rsLpIp1%vMyNa$oGUy(crdOe)N;#9| z#vBU|Dfrb^W_p&%urt5qv)UqedHtC=og6&ZjX?+fG2(ato}SVmCxdH6C|$=vye^t` zI6q&9*tO~@oWn9}^2jR$Ne@t4S!>?|1+5ZuZiVHcDHJR%LuZLT2o3Lh9I$j)0<^GZP zEM^m`nM}xBKqjssImSX}aJv_vbW;H;Jj%z${B|-iw50@EwGnl1&IjypmB#noq+$l= zCcaoB;U4EzYtTLT&?29PDexdO2pO6{OiBvGx5Y!?N*=XqX#n}}NSy!0dPVIhI5mvs zJa829Ogc0#HNkra-DBI+@N9+&SB98SnXj?oXL9eq@)%*rdyVE&InHu7 zrG?lZa^^m$jr5J8r_n|wEjwDIC+Ga;wzfj|RAzpdtl+kQv$dW)^(oE?aQ&K|lLp0N6K1VQM>f~@N+D-Ye? zlCSxZPwzxN0>e0$S(S5S9bDwcS=I$SRdne%N!=GtV))Tg4pn8A3Gc^G6|+wE-69QQ z%4Coyvlbo%;ZZjY?#>LvFfCtGrUnBiXmIWadCF^CPX|Py+$kNLnn$4v?@d4QKJa5j z6J8xjL-7*2vwb;JIyxQgxYww1AP;fncuZHw$JZRrmhC6oI6huFbxoA`enzQN!p!?* zy_Ci#N=|jo&~H;gUq=nkAu7aGAOki|iSKS&{861VO&MBr*g@vJGz{b4hv47qWR=fy zCTIrdhHSVOSJ3;%{qyzqX4s!M zZzAjc%^(Yo7^Qz@gY^H0HT3&QGO{R9<}FcT-aI7+4O7E3MG4ahI^(x-PHP{G|-s+WM zhDVCRJNK}{+jG9c`(c#A`_WEvX)AnVy9Ij1$ih@?<-P1!q6}@8C>^#P zmg@8|{J~zt;-g0Ca7=~26Y0=huY`Mq3O2vh7*pngjZ5er7{vJr+hs6tE&cFPi?MlO zoW0`fxM)ON+e9QcOoUG-W<6JB-qA+huXto(l$qSXE7q+G>5k`n^^NR(c!I*40x9q5 zQ}{kzBYV1lj$w^aRyZA$9Rm$Ac4@p^a56}PeVm`zpvI0KDwNA%rhvN}4r^4f=4UvX zeStO!VVvb+4`F#Y=bXY(E}K68mGmFJWM1O$L>%V5)x#pX_jx}zz919B=9>{a!;H?a zSwm0G!UBF?jk(8IOAeyt8in_1@~|zE6y9Fk2emv)7QZ6r6S(hCpU_L~y$ND9oH<&j z*+*HgLI&@Lmj}|RSzCo~PytqCVHapofoppgn{Z6o9}Xuwy0f=4uY4_M*;*RW@0Jnq zxdz-GO~!Gx8TC76;U+&fk13p4<8ht-gR^H|oDJy7wd(|5S7m;7Yw0?U{Qr2ye38G${K^ce2QMb`CZ z@_y3~amn<9pC29e1Ig$6 zHI;~nV%a^+2W_X3yX4PZPkyS_*!nV9e#xztJ{aRb&WOCyiB-99{?NX(9G%^p>zc&`ch7$R_!x!@-Be6W0v-+dx4Gd`@zxscd2Dbe7 z8Y7YYAqBUtf=1jb+o)Qfc|89~Nlnog{yn=feErAB|-~N})9A=7*DZkr+aMV(HI3 z{1sVWl)rz8h98QcrzI5+ zdEUKjSX;VQ{~^aNl2hY(dZrT3yCJ!VV19I!(L5e_9A@T4!lPd*UXRGd!MsNDeE%=$ z(uCKIk_gO6<@Eu%uwK?g2Czq$FwCDBrabSyr=o{TE;45~7n817!gE+t;rSRnG7U?g zkmt>@6VKve*)uo*6Bf}MSUC;Hp5W>%rR=HthbTl9L7ieMfOreV!xZaK~$uJOaXph&d+n2K?F z){^@-mtQS-zN`yCi)YMt9+`rwOLH-zc{9lwP%L*gGJpB+NGO9+;ocz+VJ&z(2N%jF z7eDOk9*MC@sm#zLCpe;!oUij+QWw+58WI7ACcNGrCvRxyEXN1_lJ2}OxOX@bnfCN| z@c3D4w38YBMKY6~N6n%LY*-+(_Q$xbkr*|L$NA1&&O6nWZ=(w3 zODlhLd$SeI2c)5259XdPbCC6~eoECCA9#^BJa#q}(Y(&bHEhoOy6+O}4dN;2WTstnC{#L9>a7lfP&#+t#boBnOa zgePU_dgOqN-O&=`tC9t1MQ&w2ePO@L(D_B2yddXtnmM7LR{=^1V^{DqH1F0v=@T2ho*}cFC zPy9on7-hg}TYA10mBFpfUa3vq=Nx@ub<&xOeJO+WZVN75ijz(J{*~>)=;UGG{()XI z@->Us#LM{(%%$xfhNouc+a_kh%ApMFr^U(FDo&i~3`OZVJpvzR&|j+XzDs_p?ksXu z?L!gY(|`?pyzfBraZ~q8{nO6KvI#}p>japlnQ<|l`M-MRQ!jOa+KKz$7YWQ1$Uujw z^cd2U_}1itZm0PC-t^f$ra!4SIiq>;(xSix%O3^fOpzWQlj()LWx>&7`^4{qGu~}s zw!#KI^UE?(y@J9!VqTmq^K!%l`ULw-B)@hu6FamPfc)v8GfwDVBN$sw>Tx zdi}=JgGql}@+k`roAyiHe$LpGO>Q*RfK$UV=-4mAmTIx0pXQ2V14D86sh&BK88|zJ zye&D$mGfNS(~WsjB?;)CVut$&3%u6GNxN3gi1!SEIhWo>9{(-LyY=qBU-I5MVm9-R zU$FPkWfA=c9q74J>Sb;&y^1<|=+2W*+?|2W#ieL)ley}<$gxTY+T7IR%=-+?>S)2w zeX;U#q7%k3S9$??&+8jFvwFO}7(&vz~NyHgkGWz~Ksluii7ivi55B0t#7-vS@U{nE0hGmfQ)q9S`L z?qbH>X=S)n6e|&JoH61E{fu|@7+RQtro+e^4&nL8dn+gMiS5{H*;y_VlgaaLRN# zL@RnTFUH5nz!+y#oD>2Zz7G|@XX17ly__R<%Vp-C`ArN(&x+(R-)7*CrOc5(v`?av zoKb#u2%H^QW8?eTqGuT%PD+plIv4C^j`??9$13xDi9Bk7P1yli8|sSRmSD~sGnY9y z6B*|$7;d*;YCAdO;NDPFU7$zErVQ4{$QM70lj@ExsMwR7CeJ(P8JRdo&e|;`PHe`y z;@>@?ND@7|?&0-qD7n|q2c*juSM=Qxj5$*cNN^;-yxxNDo%YK}cX}rWhG61#J;IJ= zaBkm%<|X^2i0A3ur6IUa-Y}pouiI)1o@&TxE_Eia5e&_9@|)YtIFMC_S$FqI#0^JG zzZi_sysj2bp;z=Eujhe#rA>|_W(*C%+EIF3<@@}!53eUj_RE7aE_mk?f+-*3IooB% z@d@-!wvCYohh4F97eC*n^gsU0z$JwR<;%y(Y0i#MA%{MpuO8YKnRI(tFrI!jkai|NTz6PTwuiJs-;wR4G`95u*_*fj_To!^w%k`)+%uIJ_ z8UE}MD~`O*&!(?)qm2PSczh0GZSlW;SZjqsad79Q=11y?@VEc_@BjY#|Nj1ef9Joy zTj$Gt&qv8(h5N}#Q#?G~S6BA5yEQU-!M%s)eWJ#t z4%N;`xn&GUQTMo#5*&O!*|~61$_l^9sfDk`rD%UAr98WFu4_5F$I0c^H1$07HYFwh zWB23_V{fF~O)l|jly=AS^hh_aO<&x-zK*(((&ypzGjPLvq-Eu@N3hE<7|0=+>T!a1v%e^6fBI3$bj86~(}y!>&1J@B?`C7ks6ty;=Koz#V*P$*RI|?1(!zW6obIPZ8=p}8vJZv*LoInG@{TUy_}exN#~QOIe&tg1#y;T( zabal78DPit%z2*9xlxxy)=rIBev5sTCPvKI&0bHw0RxwEwsax6#s~v!RxwLZXMj^% zGK*JgU#$_iHl-w9kS+*oPR-uOrRynV8Mq7ked{W~fmMTcUhkGpi4jMHcJO7hBoitBs7b zC}r#)9)d+}nD0?0v*}CRy3>m6ofTTJuQ;Hc6?T@lf^%xAjA3svO3$7HSYNMcjW0$E zIq=`o{Z*;NyII4bjRGM7)-Zllp#2vG=Qu6$h5d@#@nj$M7Mb+4R2&|#Uuh|o&txTM z`H-93!RO9VV8TQN4D5f`cA`&bY&rNhXMUp2ADw#yaW6qHTu~r`nX6R!l?K-n=v!p% z{Pi1p`k!cUne~T1KLo&sd{y1q^eD1cY`=hEBiBNl+Q0puEOHF$q35EFfaum?dHkV_ZcZa(MyKsc5Jz-?3@J)Ihu(xc#E7lozv zv6evH|;4e;HYq5Xql#czwSc4BGTgczLub^jf0rRFO(hp&M0o!|<=qP0lAel#vhFP{H ztlhKcGm|y@>3zsGPNqkPkH6ziUW?Ds}@`tR4G8f^gM)L$VY`B_E+-rF{pk4)YA*_ z;Z`1&-emUWI(j9J(E&N80FkrFK2D}@rw4oHITx9uhC+W?6L;HqK63@){*BWQ}(Z@yH{&trVkLI$}MlGLLwUPNFlv4gr zSBXzn%BY@BoXvI??HDK79_}Jd+BwMAMQ(DT#9o?oc9lo$(-oySiEoIb#LjS#4p&-> z-PiV#aJr4`dhRAWR=LZN55=(#7bg!KF_D=zd6pe;Nnj z_{9L`K9L>f_l`CSfTxOnM)eT*uG4V7QUfh}G9DW=Xl5OVHdY#}ZW4$wD*`cK3BRt& z^N#$(oI3Pku+J8uWG^z8wIc@&BqR_`#s=a|`2d_N7la23194(B|GvKlSE|q_Hb8?U zo0 znEOnJGd=nBUDn#jC5i|6$dCL!&&4>Nv!|LyVM!sqCEa=Mu=lv+OB7;Q$IB$gvNeQ% zH;L!vEczcy`SWmHERRnj??L_et;8J1=2y%msI^h<|F_jIUd^1Ne>v3BKjbgx2Y zk<9OR_6t*cr(+(^hr7GzYGhAyacDYbkblg&pN2he)A78X2?6Fbw97YP*PApL1DIzz zpFYP(IyhR=En~|bXlF9WuQ*rfV8Y=L`XD!^W6W4O(!LhpFLJx3^5K6D(%Uncp=o5V z?Hn1$7j%;HoC*4xhvy@iCC5L@38#-{0Qr`qdH8pI9+EuB0P`G-s!jjNJu<=Uu~yih z&l&D~%&SlLBU#106$;RgU$=GnfRF=ZhhFDnCv&Q6eJa4^HF=2Q_nu`j&!lr@uMs7q zz4YTEy&i2^>2+PVE=6^0PfD2Qg%rnSF)5R3W~Cgp)+N7PH#xjOFe7OczOQzkA0q}$HvQkdba<4k|@S7 zdP-K2O^izr7uPr$ra3GJhbD-wU6PDr?ZtsEn^_e%jIxBD#y4;EQm=)Pwdh3IQ9VI?`XtK73WsF0-6450Gf6&dWp9i>du4m0 z=vNpdrqOXJ;U2S3JtbPqArmv5dDF2fY|Kz&RCO0jt)pV@sw;NdxuMZn6+)Y-$%ZO% z%2tgRCLLl$=pw#U3?`T{%Z{-4)e# zt8jO<3L|T%@p%BV%JeGSo=8`CunKjnGV|Jpy`a6^zugXl`wQ;VioE5`Yg zgGLDN=_8q-MZwLGNqKH3wr$J~rS;pVAsLgfV=IdG%FW2CGAG&1@((iqijKp@xSnfE4ye5W`g7zBmvJ4)bKL{1XB^yC2V$T{-Z@K}#`D7U%G8b+P*Od(n zxc{D9B==zdeGRthC@uObWydxL@jj%I{9t?O-M~)9t*(-VT!&5U!ma@UIocETqdZ~T-xC2pJz!=t0nK?;KGq7u7_L>`y(L=16Z#&R zXv^`(>J1q=t_SX%Vo!QoW_Ehg#d@XyVSMi!m2m!T-d%deDdovqdWUaymyhh1`TMR? zW=S&7kM!={{V+9wLtMTwm>EJ^X8s2f8>^hraX@mkDxVD{ljO)O*o`~0ZB6grB z`f%=gaLo(jd2Mo*us@|~1T-3YdR^)Idq<8iAQP*(-ucffHJfvS%Vs^?MrC5<`XX!@ zQHb^ma-PZ}JXp!T3mbYP>-CaBm%GTo$(?0nLu)zmKq+VEDrNo&lN_DT_3uMElsPZ| zL3iY9U!x4$Jpuc+GB-5X6ZejK!pFpH?h1E$1H*CgGIP}yhSTjIhRIRkC~n2;!+SKf zZzk$A$;7kROw3%Ii8NobGY`0yT1`G>E9VJaA>7|HN0i^YTVf}nL#(CjM<-dlxtmPB z-9rwwvnB^(lEs6oBdOR7CeA3+%*|l&+$e8uc%YY_b3GZ$M;0DvobAaPpcj5WLhl#n z$O1AUuQ!Atnd{JVrR>>hk%=2z7Y<#MiS|3WMl{bv8F`*R2XIa~QGg$_il8{mIb?Ma ze7dpDukFVER0ruZStU1W^EtYpl9cu;3BFb(a-UA~6=8Um&3v)1%u6Td)Mh-_v`(31 zKgh*?F2shpg$QiV4AIH-TD>lW`SAiQe3u~ZsfjXw0=>H&!;5bwN&ECT86D_=OLPE@ zUa!K7cS@vGC{gc&13C@}z~mi)$R5S9EGH2Di^*ef?;IVY#npf5V=Q7H-&_qoa(o-J zkvRfU2H3R9#qVS2dYwY=e`}5#+FbPKS^4oM3U!8-nY`o-nq(`~vR0v<^GgzQN|L0f zxkgrmC5s=uz)P%>B=?FVUM^Q5aIq4NhC85Xej$s^=CUrMpkCy#<>zI{UMfPlhLhawt zOnrWeLOtd_om)2)>ib`kC47KZz+Ql96B6X3w^sHflke~Eh#ogMf8{w~$!)p_SE%6Y zt3n%&?RB4%FYw|xAI923SP-1Z5N?g-_&XyB-4^gOSu?lcz6SN*(6{vqGnBvOV9hQ1 z8Ln`A^fTaCqa3W_pRJ}p>VYHKi+&3Ao^o;+hZO1-YZ64wzJtrH$%4?~w3EI_^V4xM zt_l5vEgexWUx|i=N@&QR`cGHkY9{lyQv&Jp2|&Uto{=mddqGC!YNsTG-_+vYM@i6c zOo9jR-Am3B$&!nynjE+W8W1zYfV_DIZ2L0@Z^;in?XOTz9;i^aB8xFNi7rAqr6$)o zC8s)TrPh9pNVHa3F%#q;*JQb5uEHCI5(~bNBiyURRPQd($0%WUH;}tb)?RK0BH$UF zWXAd^AAXY1Yy z^`@N)wQmaRw&xV;_3N1-IzLh7Ha#UN&61>WqE-U>$B27@M(n4l;2Fz)hduV#USN-T ze2%Wnutz)2|2|pF==?hn+r|fAKiJd28qQ44wW&Vr7wE#e%5+|%i|i3yLRa!~&S@*j z-A^`P1ZyXM@;MsnWI)_wg}OVL5Yun;R*qGuGnXsW)^xU=e$ZLE2C8JSuB$A&++D^E zR!UrLNBMljBnmK ztHZJAd78Zxy-~^E7dZ~ScaZ)8U0K_+mwRH8gx<_`er$%=Nw&7_e;G$^X5s1=%_j=D-7v$hI@Njp$o=%% z3D`jX-GSU^!8doDSnr7|4LqQs;W&2xY(kr6JtLy*uFL3Qa9@la?uSak4u(h}^Qx%~-dnlf0*r)X+ zRT`xx$m3V^>PbAWO@hR8uW;d>62ps`-gWm%+nB9O3;Xo}MYvrO(4%gpb z=_g_R^>uFp#&E2jZas8f7!~pg6`TE&CJy6ILBX) zO_1dmQe^(ec-gr-Nm_5#irEV?1>=;M+nBv?85+;!!+-;tO#(Oka*;0#>ZCTU)VSuGI`{?z|Q|1`m@=y*lS{3Sv zt?11qlfRDhMh;m^>vd#M|4EW{os;EeH4XXqBw1GX4+-0!C=E0Y7`B+_8@Bd%)RTKk zGL5|(Fb{wnW8Mw!0du(q()%OQA`sql*w3+BgExBveLp#{fKkvu89iu_hzZGikS#M*w0a?XQFs> z&z@YOmHwR^Fgcf=hfzw@e`OC%7iJiQsxbOT04^j1BDr%AmTwQj`z<`1XvBSMH7zbL z*P^Bw^P2eFT>Hv>W3mP#V+;u3XZo97YT;*ky`KK#RXKE(Db$Jl3|m|j>VenDesV2l z#Yc1yFh8DeY!^;cok*$}3tI6~p?zNCy|5BMdXaXYd(K|Ms{>1(TI7Qy= z*2VAg*_{3|=TPjN#rn@h@{C@V;-oE;>L2Mri=fBNoF3Lk`6!!WAr0vHy4l1X?T3e= z7X52;m~X3eX)O8V5U=RmVA6-;%n%)HbLbsw-c(%X{*YJ9an>ye#aI5GKPTm*@>@qK z@F^mOWRyA`F#k= zn~_^Qz&vYbE4g#ER9-)EgH1^YB3oqOMpNbm&#)4;S(!Zi#5~_sA<(LHh})TmgZ0{w z(=C;YeO&o>55=w3{QPb5v1vj_$)(rq20fA&28AMo{LW0Pd|VjVMzlFUWl!mNY@ZQ| zKi26mmfzpIy_M{#&D_L{{WF*`n~$4;?WO0WN=aMJ+*scbyxfz42SW?kci3KP-~B1$quenp zAQajytG|x`QluiYx z_D@TBv!zV#UUNex_tuqnbeJ2P2bZty#4n~)UM(WOc_b9>>oZUiTL8n`Hj=rhR1Pyo z_zZbK$8sHNt)X*wcMJKZG>WDB1ZFRWV*fgFdDRQhq*rsf)3QqX)5{i5zBT$jxzX|D zJ-@e-4%^CQTO)VmKc?rg7kQ<}c^G%Cl~f)tku<#vR+3xP|J0$$bzaXAE#zxdg+w3Y z_2K>9-IKY%Va!M>q&M)FD!E$U4Qbm$(cl?5xVCxB=V>879xHeb#(wi|p)gZt;6hnG z!h+h0KkLeiCb_{jC=^Qzb+|-NVsa-7c@bJF)A-!FaBVi1&xs$setU;n$evlH67|Lv z3x8v-^xv#`{*ecJuXb{O2%k4z=Zk$p(cDjmUZa_lJE6IF`d3PmnJ&otH57GvGgtSo zeDoyOIX(HO^me0va2oT?2V`I`dBa`{n$a^;BHQM><3MZfOCRYF@HQWdhFQvc@@1cr z-Ep!uuTQEDYmNEnIG*31_f3WkoPZDSLZJMl9`0%D!IZpowv+aEH&o$5(Qf zpRA;k{GiuS=0X2Xj&*eg@^~HElILAfy-HdIx#CZr6%9{kem(2DCFp6jEFvYO|CFK56!z<*xmn(bw z$V(~v^fKc5U^ zD_L-;Qqmi`Lwg_uU!Uo4rF%X`S+tRx4S&e_!){2~Ob&5eIu`8U@44DReDg~sw9pN| ztqI1{Z{#{T9(KIfM&8dV6RTEkyjP)k#_KaCyZ}d-PyNfy3VCpp`R}Vj;a!9K6LQwG zw=@=+`%|9noq*(Y=A?6++&48J6Tdc<5b~JK`qA6lj``6CbZCBw-q+<2gy@h1we3y}pT+xSIw)(LSi=WdI+PJj@fBGpsFS@~b96gnsrw+7Y zj?=0*(bG?Nn|uoBt$Q~r8?{1>%qobKSBGs;*OMN=iwP+2OP^o_y?ftI%ChxzX*0KU z!TJRBbSk6CzSZNk;482Q%91}_Krqt-ogF&nZmZGjP&PsB)@NzA=Hy@7q6{Qar)%Dt_^ z+T$m zvKBL@PTA8-@6Qa*L}WB$e)oAJ5{5^URk26hC1!QzkvIIFg^f`r6wE&%zc;qUYkxnq zp?`Dm*lY~(HPMM2D|3F>ApV>$x-8P*9M`i?xo)&{j+OLjHn3U8vjhH~#tZrVmquhv zBRliS8tuu+ZnoB-n?*Jzg_)o)h$X*l&)zM1+{PwC9`NtA&V*gHnOEDw78`E)qUKxr z^_V04Jlx1W_7h^A&ihCnP|JMV4M&*=-Q9%m^u!&e$Fp;cANp@6hedwF+fJblJ)a<6 z;kMXr>5Eh3w(d4z4s|yZq;a&=)Y@U}6@RQrqc?L;7NXu5@nzOAiQ7a^Ty^S;tD=1r(bd+dwDN%7tzcJuL;McK~r+RgZH+%bn%DP5;`cB(f=^igmujIem0la;W+)3JvFG%XVH~oV#Y+Yy!Exk!@54u zmeFf@F$?pXnvmNqQc|+XSVj9_O>839{n>bU+K6H4vC@Fa)wjMN=z1OJ!gsShNe>j(0uf0z(|EI|tD*kjlfU*z%c z`)BPO{5#f!&<@dZj^E#Zf#W23-fk!8)#Y>8NEs&!_*`w;&F}L%4Dt9c&zgMe&Uo3~ z#)e)Te|#O6fbHG+d9IppGBsM>IN37a#1CW0^O~me{S7wZ{^2NTV`jr_4qv=ln}9<# zaxf`}UeP{rqF!u^zgzlZ9?$3c)*wghVZ^DdXmKQmK4*tNoUbH6YskW)eI_W6B*>w6 zT_0%;`=bZ@V@d$?vLgW%x;P{APpNPkhPPCSqn_ zHj3XHu_h=+4viwWUW4O&3g;J&Z(CCT|NV^fe{3DN*U~CIa8prQNX!_g)CHl=>BI8U zGoCba-qWKhJ#NGKbj3u4Zlm{{^oz|-rCn^kGCj6MaN71iU#D9-P1QZC`OW!9N<@0j z=vB_6A8b!g+-{wI?(GgI|E7(dtM5s3-k4~WzOb~hbHl^!(yiz1PT!Ms$EkPht+YW? zR-_mD9!RToe$=4y+E(eB&8yQ*Rnh62<|Iisez_MX%Z3LDa>`sQ(f`JabHjL9;=*TV zCiA3w#misr$>N!wC~ar4W-&EZtY5{+t;wvb&}VyiTat`4Pm~z;jxHILEUj7hJ^V;3 zE!w1r`ec%Xm&Qu%^BOVtp?}~}igZ20Il?Jfj?l}P$KKcc(Mj^;gI0EJ)X0!Dd(`5& zvWj)$&sGj_Tx*Z%kL=NLs{@{Grz^lmg%4j@&u+%LaXd2z-5v1ip*>*ffOokn^ir#! zIH_b7HGiI7fyO;m_&HpODJu3v-e+HJq&*hsc#a)J?s1L^s~f3sfc5#@mG&^>*@1!o zO(!0pL|Kaxm z*x8il**pXJRG)o~O@gpy66@Hk^?O;f{(nCZgP#Q;BR&8I6KmTGSp%CEgdxuZutY;9 z(uU^)|M;Vc1j6dGKay?+U=n}-71k0C_n>d!8}lc~3_nz9Fe!~==1483AJ<~|Ff9&r zWNt?X*6W`!k6Nci!l)z^E}{qEr3U`f=-~0-dA73#<0~{+#53tg2Ra;j(%+M=g<=MM z*!;cScwXI@XEgOvHHg}##lyzzC+5#?8lnLX(%Be9SH=K3f>-iFsNwE2MdIT+8H+Rwk~rB3I&JI8?Q`8kMV-7jtw>ukkv+DGITC z=GV8EIZ7LuMdN+WC6!p@E9H+<4sxrTqm=zr$|&Eiq8Qv&j1G=sJEezw$?YnqqwOX9 zjICVn)msj>u$QG5nXB8Oy`*%v5vxN=IX2c-e6OgOziuxf?dfkkY=)+{E2VBbGdK@4 ziG5I|9I`OU!lMeLvQF&!O2KuN0#j}1q+eAbdlpn1ABQOfM?O$>+$QPH@=?qfZ{3LF|#J1{209e zA3X5uH}X^8=$YHdI)4*S*04Qs@-GjJ9>5-XGFF8TJ=ovF9P0fO(Cu#zSd(p3O`@mn zEzbyM@a*>T1oXP^fyh+;8J)ba=CTK3i#_nUS{Tm140v7z4(OPndN}fxw z)?GeM4<|AJs$F`_Q1Cp*s7FCfy5B4_;d3+-H8<;_cW0eEUys9{dYZ3=!n|gHbm5KiP3}*PUE~d;t=>$3#SL)#q$9`Hba$UXk7@R@x#2MyAP1fW7YCY0T z%;Y`F%<4^gtlP@-nbC##I;0RD=7p%bT8Q2{@=teouHB>%ezObk-oTs%o>eIKk(D@4 zo+`V5{RV|dj4yyW&v<@V@q8tj4mh4;+;u60B7_;2WEe8Hk=0^PY{N{Rb2MO0zkvCL zEei22x)3k76yomW*AqOq?qe$pGVR5GPJ5|t<0$ikI!mhyw$fQ_ z<>OXsW?pm@(-d2|+m$X}AF?W=QjA7adkg-Earl_j@PVZ&1p@SB`Sj z&`s*S?kcX#b?_~$jB>@?C@Yp5B`&BM8hlkCd7=X2=yzCFsldfd{@fP@ zdS0)R1y8D>wqKRpyQ;urf0G2|Gq19`N%F>#AxTsq#-9J1`7?_iC}78Pl_RW41^+Ng zi+qz{0yEw0s=@cW0=?cUkl48z4nOC6Gn?mg*@iIEKi&t>51Eg^dl`M2ie36^MxNUps270|8~6^f4)9_@I98Au zJ~%53lYZyB!}rQm%>Ht+l2=wT7siX{Nc_s_Mn~#d=7sQmHfzSd^vE#yC(+r+Gt#>J za}`#4c=3JOxre@&s7$5;y}4wET^;G^C}b^XND=2?GKdN~xds-( z@+8ko=M`Zk-z%@m0(?15#&;9_jw|WMn#$bGxrOL-oDN58x)+xfVm{y1@iBCv@Ew}B zoea|gx@~F}p@e67mI?GZ7V`buRD>O+1u%Xo;JT#{-|k*_o|bW9VBO&6=@uR8JHHun zByC_F!@y~c&ZgH-YOA}kC&Ot(<&pHt`EI(XBMRpX|L}DEb?5Z>8iSqoZg1q=t;Q!O zyFT8RzFpYoJbPtWTD$Ci>FdAkciQ}_{F2uYf9KYk>gfYJ9Zox%G%9`D=OMq*VOs9`y%hOmf+|`O< zxmJ`#@nTMI;~!5GWNPa;$@q{UpRQ=6-h7P&ZcP#U+wl?_c}hA}Xl0)&LGJuZ-%@_E zlov3Un!Ph``y|Pmg^4nL(kV&oLD%C&t!xX^%9bq&($$6T?!)8I6JTp#DP5(_L$YL>``sBBWCwf@f?(H@N`Gy zUsED^x&!)hU3sFw5&r&kh_|MTX}3T0y~r=-kuhu&gmwGrA9=})XtFqwYq^fQ#@-dy zLSB0DpDxV53}7a7EL~E+(A6}NEaYm|Nw~+D7{T+a!Ss`5(B;&EXKZ5v@k$+p20sH3 zcZJ>;{_N`kK}g`*v-NWJyIc;y7p_T9dj()@IrGWP=mFU1Q*yrbwgfXA#h>Fu-V>vm;Yz0P6=UG;L>ENo%bJ3YvtaRbm5G_{h zC(~HWUX~rq)vL`MJDzblMY7+`itD{o^fYp<_heBH(rfbE($|1a^$hss9na?avqyNm z0opuf@m(d zfXnC~K&J5xbB#V{Ad+Lzu}*q4I8=y=TFmL3S%~S&3sKXO^LWD|EX%Qz_AQn2u)n<= zZrELJj$XoRBBNy|>)UpfgkpPH^Q61ny5cCNFZSYc$Bb^@>WF_qZ{-=2jH;`ELyS>I zWqBd~E`3rzJ>WFJ3#I2gVKjK6zkfJ;%EM97Cmi+2HvU*kkMCkKbBF249YIcJeI}Ov zP39r+GSubt^rjVI4zG>#u0k}NRES*xMRb;a!WHMPQvbfa?7Q7v+?V#0_j#R}wc1r~ znbSF_GsEOo3j8FCdh;yvmFJKR`Rs`V_6amN?1=~?Gudi+B4v%||EwqNC(=t?7KUw) z>Hj)MkEKmG{^VL~ds-&04x$@)K_*OOL_V>P_H$+der*WxS9aFY3$L&uxpw0Pmm9WQ(=;XLk1 zk7Ylys1rO9Jv$6_GU=_H5QZ6Ck7gBx<4d=7IL32?iL{ROd(o36~LmGqbwZMLzb;j%IBdyrCWQI94c^>plCCEI&X%BE33q& zhee1CaaiFUgLfk!}=NjXMjTbaM*%QHgbbV78mLn9cG+~IC8itnlxfa+> z|M6%&ZXBi)jnB~F1DP;O)nkV_9hzLD_Bu;0mupKK&X?KkituByMsD~g%Rez>2cxud zwMr{RZ8VaT$Ns`oDkRrdA*Glsn4c2;*Q&68FkQ9Z$;5>PVdH`TWVH-Lg9m}=dWXGq z9B&rQ(V+JS4K{bz!d=K2jLpT~rUs1OnFEVw20Ru6{$SSg;Qh>2G$_=I9L&@jo~5g1 zk}bH){`iZ@ViTP#O~^C;Rlw}deTg!5kVc{xtMKv^^QNb&pdP0}&N=ezI(t+MCF?Md zJ?%RKvGx%A6ggghnoaIuJe{;@T2ww~AK`2*R<9;+N#-E?qyZDi$VK)sVD)ALT@tyN zP@Ic-%uoL5&A#_Ug}Q^cnfd^|Tb|6!w5^#eNzCbVd7+`_kB-K*%(k$Mmkq3WDF5>f zdO2ckA$u&JaGtBdyyp_KohkG&HV#6@D7vI}1R`%~AY6arp8T5@rCA);pR;eVDL>m` zEjraP!0JX0mT^qA=)$~%6S+Jmp*N`;U6BVA>QW7Jo<}gZlZ?v6(PnDr2T8K!c#1gC z1GeifKMUPo+nrLSTYdJIrZU5VETf!bmgzrTQ17@BBAvDHeqGx4H4#$44O8i`ES$VGb5?%i=fljZgZYp+CDi3&r>fNuQ| zh!LEFZ8#SnUlE8uKL(com=O&fR`xpaV zA)HI@(2bv9)FrlCD}@Ur9xfN*-Y&->y#AqN|Zo)CEQIKDXW<%zL6UFP0Jcn zA9|dt+2imlB?kSfL{2Le`p*c$x2J)a9~ubH1_7w;69|=65Dc!&)=;tEfKJan%gLqK zlCNCPet@?I*w!+j*Ec#V`FUEPE*=90JneY85Jq|P|LOR#L z_um)5n|sSnYYNd+$YR1=3e^M5%SaAr!I*s!m;6;zZ!hRIy>q3$zEE2c9g<3-DO9E z-qORri~JR-z=SIbx&X*DZdc&I0)DQm3iP$|f_^AJ2j{L|!kJ&3=??#|^yzcoq&fhVTb zqLVR%{iS&xnAC6*qBwV*`N{mxap5p8q4WL#uhn(t8*)xJ>z0X+LF6m>&mZU6yReqr z`QReFp2of@&SAHovuBDuR9kJyq6T-BX=7C4b=E;f`1F(-t8HXVGe`E7SBD3x;csSx zA6Q|AR*TGV@Od@V;~sS1HV;%+dm`tm2mZZCmT-nARt^qFx3Szex`$z+MK~s&V_zJ3 z)CqMnv27?_zB}}oevb8#0zI}Bb8l9`9?5fs_|$`Sg^WVjb)bKFD*cSryGaX=E)u45 z6zO0mbFV7pX-)PU|6!8Sbw;sfy{pwe_VdOX#lS2Dmt0Sn|HdA{treY`#+!?C&sGs|n~@#4517i+Ok?tmUieKWCwpRLBbLiEVwzV2Wl z0QR)yvVUP5uUYpLX>OG$JsxXic#uY>o{N`X_oawW8SBWLC*+a}Z(led;krFt4oXD! z3qnMTAS_goq2@b3c5x8Cer26FgEdypTb8f2_)PDMYYcnJxi0oGvOi~C4)mMJr1i^% zc~%b27BT0UoZj^qh1&3t%<_E`_mXC6S7s`2*qKOvIzjquO%lI#$)ao>FLPKoAGnog ztx6TP=5o*SL50Eh9Z^1BiRnQB+=BL+B`Ub#rWB_(?|4T7=~)U$STj{Pl3 zMm*69GqA+%Sd#QVn8;i*tz6&hfRNYh3#j1UYAmnQXFIfAt;C&QgRuJmJ&^%q81InT z1LyfHj@6D@6#mqr!vrmQ$I|Kkl>3rxNoc;!z+S8zSo5E8uUIoK%f({ypWiCTo7083 z;G04nd`O|zJW;4KACW2ioFpDONz!HZDM@XYET^NAq_TdpqzrSw-JvS1w@@LE=L$c| z>C)}tz#K9<2jjSZ;vQ{udLT*z1Mwm}2)4g#@!U;|9sEk2lLWiANm%qvgRu(kUFMLd zTw_4kW4hpbaZY8Q{kVk+bus-xy{nt4eYwtX{Hai)aIw8 z`MVVP(998%2n6G5t*aic$iwziJ&-tqn`~AlmkQiWq8GXyKrxa>svO-<9m|ovA3UvbK z_?u@E#r#T=MAJv{&@5Sc=f=vx1xeDOM^{Yb^BZi=41?=R`2Ix~gtrQF`UIivSgv`h zabL@G2+N`X4CX#m-+-A+g&G`vNG|`a1~a%mn^Zt9wnh%>{KNd~Xl6_Y(7${>2k-V7 z@E7OuK=uZ#B8O^|&;QLizUm$S`G5M#7Cmn*_7&waVuTw`HVDNDwGIa&3g{?qCD)ez zkf(tzm~P2hFnO-Y|B@@LYc78=hp1W<^MxPKi+4N&Jx7o?iEbo0&de8X=8CbAA!J`O zaC;v6v(?RIZQJiMYqC2ED?_nlw+_~!1yCMpB^}j2rA0&XJAVYjvXLHBg2^RqvXqxe z6%s#^yxW;z6fM=^tu7z?+gQrR=H;UL;DT~Z2u>NvLv7DTMvFG`g88r?tlhD5YzT6X zq$BG&y<->2VKF<&a=Hq!Q3(09z zB4NzoJuoce||B!o)w{Zl*pXu0r{A@ubo)d{V9Q?-B3qIo@>Z| zc_aB~f7(KpEGw0+aV~Uev5$BP^II3^BmFtKysKpr)R7*{k>n!l>oD#*J$H!>rN@zP zGStTv_lI-un5V-$a#(F=TgkVRrF1>g)7LD7``rv2<8>aHMGh#aLi&}v0)3b-Jd=LC zsQ|nM@z(ieTo|4zkeUeTxFjENLeT&VQFVyl&6UL!g?Q0q@uOSZ&`*Iu9-r zgP!+yZWxvXWx#wHIacrXqT5j^*QU_-Ff0U$_UzvxzxF8JLUu)zNbxZ~hi^l0X@5GN zEg_$k+C+-7OJuph1?`JMaFw-7wH@!TzP&h1E|;e*-SA^}DBh97ayZKSmEM9GVL#=8 zxMGe)DB>!0C>>USX!;h-pH)ixTJ%-FBe(040ayP1?|)fJ{nmUh_<7uHLa{iPT%J=t z4)wE;9hK#xadE|XK8H?&=-KQ+FXXOvQnvPo_%a84RCU&CU+It?mXEY|%_M~U;Q56v z5Z=e9yuZ&j@OiLmD?WcPHz3socdCN1^q~%p6?x1MpvRLr@2Y(Mp4lNlFu6;I0z6&Y zLh5uV72O9n%#0?Nx`!1X3xFTZ% z{eyfCTb$0v)B7D{pl6wc@V)a42*J%T9o;G9XX`hYYOl&<8M)56iHT!)fc`LJkW zA>a4?l;cZW*%uswu1Y?K76nL2wGe~%cTs$!kCohavspUyO=E6*{T5Q$ieAwHE*QZ3 zHK1Dt8u2;#`pimBxK&6QbFuX!L-5ujgSo&3xX4`fho0Z%Qw=wGKMg@oa^-0?3-Gpc zGx=n!l;~|PxXE!TEmnsNa+JSaYfBGysf7IMib8UW4?B=6pH83b*iJI`LaF#H8;6rK zLNSz_=E)j719)~qru*Ar@2d@H=a`7ef%NE2GU4FESb0=rjn-#;;Ow4={+`Th&LU5@ zHd5{_vO%99AFd@5(6b#KJ>>rU_eDuI`KBw|0}&dZh;a$oP`oi>L&OPb{mmY$-;m2= zO?HfT7B21~514yGjt{iO8s?b}dY6Dfi?b1Nk(}L}IH~EuTwQW`_y3AV6LM!~4w|r| zUbLjA*kPQjAN#`-Vc8)Y!Do#~nHVW5yduZLtrsdnBS(em1ipjr7YzNl!}~^e|(d^5uB^z9$>Qt{GAB zYmBT2vBu0dKDb|*fZxwQ#5?kaj-~O^ z9C@xWEy*R#GGcgmtUQjl#l|{*So1Ie`+AcznruXmFDGT_7v^8jA=h&-0aq?$VIV)x zP48oJ|FjK8P4ht+xzSNKbKpTfD`z|NyZ4bdyvbbMA@pYYXW`Hh6FR%c$mh@2^c4DI zbO?J4BeM|9>pbvYv@F=h`+Lt1e|od#{UjTg_Lx|kkCA(scDQ?B12RGq@xYC|LVFYL zS;a^n7hCk1v;ptVCh(jm3tPLN_-pTqQ%)kCCM#9Riah>M? zD|{2sdVLl;yfWhBwP@)|o^<Ybw8KeRLbunWRGvFnC!*$tEGRyZ zd&-KHLvNWAO>U&eUkUiUnf&QE6VmEOi4F6VBZiVMo1K7vR%bEm*8~r8ZSKtJzOdE@ zwO1#gY%;x&{BzGFMN0v>zp_()XwokcK7RC1)ns3=f&5^o4bM(|@R*!b5qY#b+nB#R zGD=E%vX^ra^K*-t4a&dQkLyNQ^d+Zx$QC;m`XN3#f%~K!JRV@g_c~FM;bI5x&i+`$ z>lwI+Tw9J2-c#eGjDPOC{0(@0Gy#EmS?m#IZuR;Y+4jN)2J&AIxqmv?HwTJcMs$)` z8A@*SSdkBVM-otDeGX=?Gor)2C>fSwgJXkykvKIG?!J7^la1KZ>$ps!7xLaLKinM2 z=Qfet-$WC(I7N!jB0Dth=8qC`m&xS&tfI+#21LrY-)%6kg+D(1O5dn18|$B$aEhML zPxL}Q*hSysjRagP&qCwlCcKywCGY9WdvMAZ6IJAJBgujCd2<>RCy&nAqEYY$JpUts zPM0iP{l$c3+DNIk+ZKDmeKF0FT%dVMW zlB1lH>WkD93Cxt`bIa$g7yIqPnRo2;m3hs)?{n^v=lyQN(LbZ*G(Cgvdwkj3oQOT- z?0&R0K|4KG_8M%+j_~^LOhCJJ~esvegDX&-uX1kbwLHe6I4C zul+butnS(%uFxMotrF3b?{9;P^j#X`Wbj+wuUKE`cpYk!v!2nCwZ;e0;>PjZa{LAq z%}>Pkt64bw$%wS%XsK&qi~5QFP~Ru#+lKkS_UN_Hhpy~+j!juGe{94vn^^hT(iUc~{or#V5g)r}all(FLERR,"Illegal fix langevin command"); iarg += 2; + } else if (strcmp(arg[iarg],"halfstep") == 0) { + if (iarg+2 > narg) error->all(FLERR,"Illegal fix langevin command"); + if (gjfflag == 0) error->all(FLERR,"GJF must be set"); + if (tallyflag == 0) error->warning(FLERR,"Careful, tally is untested"); + if (strcmp(arg[iarg+1],"no") == 0) hsflag = 0; + else if (strcmp(arg[iarg+1],"yes") == 0) hsflag = 1; + else error->all(FLERR,"Illegal fix langevin command"); + iarg += 2; } else error->all(FLERR,"Illegal fix langevin command"); } @@ -155,6 +164,8 @@ FixLangevin::FixLangevin(LAMMPS *lmp, int narg, char **arg) : flangevin = NULL; flangevin_allocated = 0; franprev = NULL; + wildcard = NULL; + lv = NULL; tforce = NULL; maxatom1 = maxatom2 = 0; @@ -163,6 +174,12 @@ FixLangevin::FixLangevin(LAMMPS *lmp, int narg, char **arg) : // no need to set peratom_flag, b/c data is for internal use only if (gjfflag) { + int mem = 6*atom->nmax*sizeof(double); + if (hsflag) mem += 3*atom->nmax*sizeof(double); + + comm->maxexchange_fix = MAX(comm->maxexchange_fix, 0); + comm->maxexchange_fix += MAX(1000, mem); + nvalues = 3; grow_arrays(atom->nmax); atom->add_callback(0); @@ -174,6 +191,14 @@ FixLangevin::FixLangevin(LAMMPS *lmp, int narg, char **arg) : franprev[i][0] = 0.0; franprev[i][1] = 0.0; franprev[i][2] = 0.0; + wildcard[i][0] = 0.0; + wildcard[i][1] = 0.0; + wildcard[i][2] = 0.0; + if (hsflag) { + lv[i][0] = 0.0; + lv[i][1] = 0.0; + lv[i][2] = 0.0; + } } } @@ -196,6 +221,8 @@ FixLangevin::~FixLangevin() if (gjfflag) { memory->destroy(franprev); + memory->destroy(wildcard); + if (hsflag) memory->destroy(lv); atom->delete_callback(id,0); } } @@ -205,6 +232,8 @@ FixLangevin::~FixLangevin() int FixLangevin::setmask() { int mask = 0; + //if (gjfflag) mask |= INITIAL_INTEGRATE; + if (gjfflag) mask |= POST_INTEGRATE; mask |= POST_FORCE; mask |= POST_FORCE_RESPA; mask |= END_OF_STEP; @@ -260,13 +289,11 @@ void FixLangevin::init() error->one(FLERR,"Fix langevin angmom requires extended particles"); } - // set force prefactors - if (!atom->rmass) { for (int i = 1; i <= atom->ntypes; i++) { gfactor1[i] = -atom->mass[i] / t_period / force->ftm2v; gfactor2[i] = sqrt(atom->mass[i]) * - sqrt(24.0*force->boltz/t_period/update->dt/force->mvv2e) / + sqrt(2.0*force->boltz/t_period/update->dt/force->mvv2e) / force->ftm2v; gfactor1[i] *= 1.0/ratio[i]; gfactor2[i] *= 1.0/sqrt(ratio[i]); @@ -279,7 +306,7 @@ void FixLangevin::init() if (strstr(update->integrate_style,"respa")) nlevels_respa = ((Respa *) update->integrate)->nlevels; - if (gjfflag) gjffac = 1.0/(1.0+update->dt/2.0/t_period); + if (gjfflag) gjffac = 1.0/sqrt(1.0+update->dt/2.0/t_period); } @@ -294,6 +321,94 @@ void FixLangevin::setup(int vflag) post_force_respa(vflag,nlevels_respa-1,0); ((Respa *) update->integrate)->copy_f_flevel(nlevels_respa-1); } + if (gjfflag && hsflag) { + + double dt = update->dt; + + // update v of atoms in group + + double **v = atom->v; + double *rmass = atom->rmass; + int *type = atom->type; + int nlocal = atom->nlocal; + if (igroup == atom->firstgroup) nlocal = atom->nfirst; + + double boltz = force->boltz; + double mvv2e = force->mvv2e; + double ftm2v = force->ftm2v; + + double gamma2; + + for (int i = 0; i < nlocal; i++) { + if (rmass) { + gamma2 = sqrt(rmass[i]) * sqrt(2.0*boltz/t_period/dt/mvv2e) / ftm2v; + gamma2 *= 1.0/sqrt(ratio[type[i]]) * tsqrt; + } else { + gamma2 = gfactor2[type[i]] * tsqrt; + } + + franprev[i][0] = gamma2*random->gaussian(); + franprev[i][1] = gamma2*random->gaussian(); + franprev[i][2] = gamma2*random->gaussian(); + wildcard[i][0] = v[i][0]; + wildcard[i][1] = v[i][1]; + wildcard[i][2] = v[i][2]; + } + } +} + +/* ---------------------------------------------------------------------- + allow for both per-type and per-atom mass +------------------------------------------------------------------------- */ + +void FixLangevin::post_integrate() +{ + double dtfm; + double dt = update->dt; + double dtf = 0.5 * dt * force->ftm2v; + + // update v of atoms in group + + double **x = atom->x; + double **v = atom->v; + double **f = atom->f; + double *rmass = atom->rmass; + double *mass = atom->mass; + int *type = atom->type; + int *mask = atom->mask; + int nlocal = atom->nlocal; + if (igroup == atom->firstgroup) nlocal = atom->nfirst; + + if (rmass) { + for (int i = 0; i < nlocal; i++) + if (mask[i] & groupbit) { + dtfm = dtf / rmass[i]; + x[i][0] += -dt * v[i][0]; + x[i][1] += -dt * v[i][1]; + x[i][2] += -dt * v[i][2]; + v[i][0] = gjffac * (wildcard[i][0] + dtfm * franprev[i][0] + dtfm * f[i][0]); + v[i][1] = gjffac * (wildcard[i][1] + dtfm * franprev[i][1] + dtfm * f[i][1]); + v[i][2] = gjffac * (wildcard[i][2] + dtfm * franprev[i][2] + dtfm * f[i][2]); + x[i][0] += gjffac * dt * v[i][0]; + x[i][1] += gjffac * dt * v[i][1]; + x[i][2] += gjffac * dt * v[i][2]; + } + + } else { + for (int i = 0; i < nlocal; i++) + if (mask[i] & groupbit) { + dtfm = dtf / mass[type[i]]; + x[i][0] += -dt * v[i][0]; + x[i][1] += -dt * v[i][1]; + x[i][2] += -dt * v[i][2]; + v[i][0] = gjffac * (wildcard[i][0] + dtfm * franprev[i][0] + dtfm * f[i][0]); + v[i][1] = gjffac * (wildcard[i][1] + dtfm * franprev[i][1] + dtfm * f[i][1]); + v[i][2] = gjffac * (wildcard[i][2] + dtfm * franprev[i][2] + dtfm * f[i][2]); + x[i][0] += gjffac * dt * v[i][0]; + x[i][1] += gjffac * dt * v[i][1]; + x[i][2] += gjffac * dt * v[i][2]; + } + } } /* ---------------------------------------------------------------------- */ @@ -490,9 +605,8 @@ void FixLangevin::post_force_untemplated // sum random force over all atoms in group // subtract sum/count from each atom in group - double fdrag[3],fran[3],fsum[3],fsumall[3]; + double fdrag[3],fran[3],fsum[3],fsumall[3], rantemp[3]; bigint count; - double fswap; double boltz = force->boltz; double dt = update->dt; @@ -526,7 +640,7 @@ void FixLangevin::post_force_untemplated if (Tp_TSTYLEATOM) tsqrt = sqrt(tforce[i]); if (Tp_RMASS) { gamma1 = -rmass[i] / t_period / ftm2v; - gamma2 = sqrt(rmass[i]) * sqrt(24.0*boltz/t_period/dt/mvv2e) / ftm2v; + gamma2 = sqrt(rmass[i]) * sqrt(2.0*boltz/t_period/dt/mvv2e) / ftm2v; gamma1 *= 1.0/ratio[type[i]]; gamma2 *= 1.0/sqrt(ratio[type[i]]) * tsqrt; } else { @@ -534,9 +648,9 @@ void FixLangevin::post_force_untemplated gamma2 = gfactor2[type[i]] * tsqrt; } - fran[0] = gamma2*(random->uniform()-0.5); - fran[1] = gamma2*(random->uniform()-0.5); - fran[2] = gamma2*(random->uniform()-0.5); + fran[0] = gamma2*random->gaussian(); + fran[1] = gamma2*random->gaussian(); + fran[2] = gamma2*random->gaussian(); if (Tp_BIAS) { temperature->remove_bias(i,v[i]); @@ -554,25 +668,20 @@ void FixLangevin::post_force_untemplated } if (Tp_GJF) { - fswap = 0.5*(fran[0]+franprev[i][0]); - franprev[i][0] = fran[0]; - fran[0] = fswap; - fswap = 0.5*(fran[1]+franprev[i][1]); - franprev[i][1] = fran[1]; - fran[1] = fswap; - fswap = 0.5*(fran[2]+franprev[i][2]); - franprev[i][2] = fran[2]; - fran[2] = fswap; + wildcard[i][0] = f[i][0]; + wildcard[i][1] = f[i][1]; + wildcard[i][2] = f[i][2]; - fdrag[0] *= gjffac; - fdrag[1] *= gjffac; - fdrag[2] *= gjffac; - fran[0] *= gjffac; - fran[1] *= gjffac; - fran[2] *= gjffac; - f[i][0] *= gjffac; - f[i][1] *= gjffac; - f[i][2] *= gjffac; + rantemp[0] = fran[0]; + rantemp[1] = fran[1]; + rantemp[2] = fran[2]; + fran[0] = franprev[i][0]; + fran[1] = franprev[i][1]; + fran[2] = franprev[i][2]; + + fdrag[0] *= -2*t_period*(2*gjffac-1/gjffac-1)/dt; + fdrag[1] *= -2*t_period*(2*gjffac-1/gjffac-1)/dt; + fdrag[2] *= -2*t_period*(2*gjffac-1/gjffac-1)/dt; } f[i][0] += fdrag[0] + fran[0]; @@ -580,6 +689,11 @@ void FixLangevin::post_force_untemplated f[i][2] += fdrag[2] + fran[2]; if (Tp_TALLY) { + if (Tp_GJF){ + fdrag[0] = gamma1*gjffac*v[i][0]; + fdrag[1] = gamma1*gjffac*v[i][1]; + fdrag[2] = gamma1*gjffac*v[i][2]; + } flangevin[i][0] = fdrag[0] + fran[0]; flangevin[i][1] = fdrag[1] + fran[1]; flangevin[i][2] = fdrag[2] + fran[2]; @@ -590,6 +704,19 @@ void FixLangevin::post_force_untemplated fsum[1] += fran[1]; fsum[2] += fran[2]; } + + if (Tp_GJF) + { + franprev[i][0] = rantemp[0]; + franprev[i][1] = rantemp[1]; + franprev[i][2] = rantemp[2]; + + if (hsflag){ + lv[i][0] = v[i][0]; + lv[i][1] = v[i][1]; + lv[i][2] = v[i][2]; + } + } } } @@ -649,9 +776,9 @@ void FixLangevin::compute_target() input->variable->compute_atom(tvar,igroup,tforce,1,0); for (int i = 0; i < nlocal; i++) if (mask[i] & groupbit) - if (tforce[i] < 0.0) - error->one(FLERR, - "Fix langevin variable returned negative temperature"); + if (tforce[i] < 0.0) + error->one(FLERR, + "Fix langevin variable returned negative temperature"); } modify->addstep_compute(update->ntimestep + 1); } @@ -764,20 +891,41 @@ void FixLangevin::angmom_thermostat() void FixLangevin::end_of_step() { - if (!tallyflag) return; + if (!tallyflag && !gjfflag) return; double **v = atom->v; + double **f = atom->f; int *mask = atom->mask; int nlocal = atom->nlocal; energy_onestep = 0.0; - for (int i = 0; i < nlocal; i++) - if (mask[i] & groupbit) - energy_onestep += flangevin[i][0]*v[i][0] + flangevin[i][1]*v[i][1] + - flangevin[i][2]*v[i][2]; - - energy += energy_onestep*update->dt; + if (mask[i] & groupbit) { + if (gjfflag){ + f[i][0] = wildcard[i][0]; + f[i][1] = wildcard[i][1]; + f[i][2] = wildcard[i][2]; + wildcard[i][0] = v[i][0]; + wildcard[i][1] = v[i][1]; + wildcard[i][2] = v[i][2]; + if (hsflag){ + v[i][0] = lv[i][0]; + v[i][1] = lv[i][1]; + v[i][2] = lv[i][2]; + } + } + if (tallyflag && hsflag){ + energy_onestep += gjffac*(flangevin[i][0] * lv[i][0] + + flangevin[i][1] * lv[i][1] + flangevin[i][2] * lv[i][2]); + } + else if (tallyflag){ + energy_onestep += flangevin[i][0] * v[i][0] + flangevin[i][1] * v[i][1] + + flangevin[i][2] * v[i][2]; + } + } + if (tallyflag) { + energy += energy_onestep * update->dt; + } } /* ---------------------------------------------------------------------- */ @@ -877,7 +1025,8 @@ void *FixLangevin::extract(const char *str, int &dim) double FixLangevin::memory_usage() { double bytes = 0.0; - if (gjfflag) bytes += atom->nmax*3 * sizeof(double); + if (gjfflag) bytes += atom->nmax*3*2 * sizeof(double); + if (gjfflag) if (hsflag) bytes += atom->nmax*3 * sizeof(double); if (tallyflag) bytes += atom->nmax*3 * sizeof(double); if (tforce) bytes += atom->nmax * sizeof(double); return bytes; @@ -890,6 +1039,8 @@ double FixLangevin::memory_usage() void FixLangevin::grow_arrays(int nmax) { memory->grow(franprev,nmax,3,"fix_langevin:franprev"); + memory->grow(wildcard,nmax,3,"fix_langevin:wildcard"); + if (hsflag) memory->grow(lv,nmax,3,"fix_langevin:lv"); } /* ---------------------------------------------------------------------- @@ -898,8 +1049,17 @@ void FixLangevin::grow_arrays(int nmax) void FixLangevin::copy_arrays(int i, int j, int /*delflag*/) { - for (int m = 0; m < nvalues; m++) - franprev[j][m] = franprev[i][m]; + franprev[j][0] = franprev[i][0]; + franprev[j][1] = franprev[i][1]; + franprev[j][2] = franprev[i][2]; + wildcard[j][0] = wildcard[i][0]; + wildcard[j][1] = wildcard[i][1]; + wildcard[j][2] = wildcard[i][2]; + if (hsflag) { + lv[j][0] = lv[i][0]; + lv[j][1] = lv[i][1]; + lv[j][2] = lv[i][2]; + } } /* ---------------------------------------------------------------------- @@ -908,8 +1068,19 @@ void FixLangevin::copy_arrays(int i, int j, int /*delflag*/) int FixLangevin::pack_exchange(int i, double *buf) { - for (int m = 0; m < nvalues; m++) buf[m] = franprev[i][m]; - return nvalues; + int n = 0; + buf[n++] = franprev[i][0]; + buf[n++] = franprev[i][1]; + buf[n++] = franprev[i][2]; + buf[n++] = wildcard[i][0]; + buf[n++] = wildcard[i][1]; + buf[n++] = wildcard[i][2]; + if (hsflag){ + buf[n++] = lv[i][0]; + buf[n++] = lv[i][1]; + buf[n++] = lv[i][2]; + } + return n; } /* ---------------------------------------------------------------------- @@ -918,6 +1089,17 @@ int FixLangevin::pack_exchange(int i, double *buf) int FixLangevin::unpack_exchange(int nlocal, double *buf) { - for (int m = 0; m < nvalues; m++) franprev[nlocal][m] = buf[m]; - return nvalues; + int n = 0; + franprev[nlocal][0] = buf[n++]; + franprev[nlocal][1] = buf[n++]; + franprev[nlocal][2] = buf[n++]; + wildcard[nlocal][0] = buf[n++]; + wildcard[nlocal][1] = buf[n++]; + wildcard[nlocal][2] = buf[n++]; + if (hsflag){ + lv[nlocal][0] = buf[n++]; + lv[nlocal][1] = buf[n++]; + lv[nlocal][2] = buf[n++]; + } + return n; } diff --git a/src/fix_langevin.h b/src/fix_langevin.h index 2883ac9ea2..70fb254f4e 100644 --- a/src/fix_langevin.h +++ b/src/fix_langevin.h @@ -31,6 +31,8 @@ class FixLangevin : public Fix { int setmask(); void init(); void setup(int); + //virtual void initial_integrate(int); + virtual void post_integrate(); virtual void post_force(int); void post_force_respa(int, int, int); virtual void end_of_step(); @@ -46,7 +48,7 @@ class FixLangevin : public Fix { int unpack_exchange(int, double *); protected: - int gjfflag,oflag,tallyflag,zeroflag,tbiasflag; + int gjfflag,oflag,tallyflag,zeroflag,tbiasflag,hsflag; int flangevin_allocated; double ascale; double t_start,t_stop,t_period,t_target; @@ -63,6 +65,9 @@ class FixLangevin : public Fix { double **flangevin; double *tforce; double **franprev; + double **lv; //lucas velocity or half-step velocity + double **wildcard; + int nvalues; char *id_temp; From eb447db7c55efc18cd3e6c398fbf31e5f7f56d1b Mon Sep 17 00:00:00 2001 From: casievers Date: Fri, 19 Jul 2019 13:51:36 -0700 Subject: [PATCH 047/192] added lammps python example --- examples/python/gjf_python/argon.lmp | 886 +++++++++++++++++++++ examples/python/gjf_python/ff-argon.lmp | 20 + examples/python/gjf_python/gjf.py | 180 +++++ examples/python/gjf_python/lammps_tools.py | 78 ++ 4 files changed, 1164 insertions(+) create mode 100644 examples/python/gjf_python/argon.lmp create mode 100644 examples/python/gjf_python/ff-argon.lmp create mode 100644 examples/python/gjf_python/gjf.py create mode 100644 examples/python/gjf_python/lammps_tools.py diff --git a/examples/python/gjf_python/argon.lmp b/examples/python/gjf_python/argon.lmp new file mode 100644 index 0000000000..00214b4c54 --- /dev/null +++ b/examples/python/gjf_python/argon.lmp @@ -0,0 +1,886 @@ +LAMMPS description + + 864 atoms + 0 bonds + 0 angles + 0 dihedrals + 0 impropers + + 1 atom types + 0 bond types + 0 angle types + 0 dihedral types + 0 improper types + + + 0.0000000 32.146000 xlo xhi + 0.0000000 32.146000 ylo yhi + 0.0000000 32.146000 zlo zhi + + Atoms + + 1 1 1 0.0000000 0.0000000 2.6790000 2.6790000 + 2 2 1 0.0000000 0.0000000 2.6790000 8.0360000 + 3 3 1 0.0000000 0.0000000 2.6790000 13.3940000 + 4 4 1 0.0000000 0.0000000 2.6790000 18.7520000 + 5 5 1 0.0000000 0.0000000 2.6790000 24.1090000 + 6 6 1 0.0000000 0.0000000 2.6790000 29.4670000 + 7 7 1 0.0000000 0.0000000 8.0360000 2.6790000 + 8 8 1 0.0000000 0.0000000 8.0360000 8.0360000 + 9 9 1 0.0000000 0.0000000 8.0360000 13.3940000 + 10 10 1 0.0000000 0.0000000 8.0360000 18.7520000 + 11 11 1 0.0000000 0.0000000 8.0360000 24.1090000 + 12 12 1 0.0000000 0.0000000 8.0360000 29.4670000 + 13 13 1 0.0000000 0.0000000 13.3940000 2.6790000 + 14 14 1 0.0000000 0.0000000 13.3940000 8.0360000 + 15 15 1 0.0000000 0.0000000 13.3940000 13.3940000 + 16 16 1 0.0000000 0.0000000 13.3940000 18.7520000 + 17 17 1 0.0000000 0.0000000 13.3940000 24.1090000 + 18 18 1 0.0000000 0.0000000 13.3940000 29.4670000 + 19 19 1 0.0000000 0.0000000 18.7520000 2.6790000 + 20 20 1 0.0000000 0.0000000 18.7520000 8.0360000 + 21 21 1 0.0000000 0.0000000 18.7520000 13.3940000 + 22 22 1 0.0000000 0.0000000 18.7520000 18.7520000 + 23 23 1 0.0000000 0.0000000 18.7520000 24.1090000 + 24 24 1 0.0000000 0.0000000 18.7520000 29.4670000 + 25 25 1 0.0000000 0.0000000 24.1090000 2.6790000 + 26 26 1 0.0000000 0.0000000 24.1090000 8.0360000 + 27 27 1 0.0000000 0.0000000 24.1090000 13.3940000 + 28 28 1 0.0000000 0.0000000 24.1090000 18.7520000 + 29 29 1 0.0000000 0.0000000 24.1090000 24.1090000 + 30 30 1 0.0000000 0.0000000 24.1090000 29.4670000 + 31 31 1 0.0000000 0.0000000 29.4670000 2.6790000 + 32 32 1 0.0000000 0.0000000 29.4670000 8.0360000 + 33 33 1 0.0000000 0.0000000 29.4670000 13.3940000 + 34 34 1 0.0000000 0.0000000 29.4670000 18.7520000 + 35 35 1 0.0000000 0.0000000 29.4670000 24.1090000 + 36 36 1 0.0000000 0.0000000 29.4670000 29.4670000 + 37 37 1 0.0000000 5.3580000 2.6790000 2.6790000 + 38 38 1 0.0000000 5.3580000 2.6790000 8.0360000 + 39 39 1 0.0000000 5.3580000 2.6790000 13.3940000 + 40 40 1 0.0000000 5.3580000 2.6790000 18.7520000 + 41 41 1 0.0000000 5.3580000 2.6790000 24.1090000 + 42 42 1 0.0000000 5.3580000 2.6790000 29.4670000 + 43 43 1 0.0000000 5.3580000 8.0360000 2.6790000 + 44 44 1 0.0000000 5.3580000 8.0360000 8.0360000 + 45 45 1 0.0000000 5.3580000 8.0360000 13.3940000 + 46 46 1 0.0000000 5.3580000 8.0360000 18.7520000 + 47 47 1 0.0000000 5.3580000 8.0360000 24.1090000 + 48 48 1 0.0000000 5.3580000 8.0360000 29.4670000 + 49 49 1 0.0000000 5.3580000 13.3940000 2.6790000 + 50 50 1 0.0000000 5.3580000 13.3940000 8.0360000 + 51 51 1 0.0000000 5.3580000 13.3940000 13.3940000 + 52 52 1 0.0000000 5.3580000 13.3940000 18.7520000 + 53 53 1 0.0000000 5.3580000 13.3940000 24.1090000 + 54 54 1 0.0000000 5.3580000 13.3940000 29.4670000 + 55 55 1 0.0000000 5.3580000 18.7520000 2.6790000 + 56 56 1 0.0000000 5.3580000 18.7520000 8.0360000 + 57 57 1 0.0000000 5.3580000 18.7520000 13.3940000 + 58 58 1 0.0000000 5.3580000 18.7520000 18.7520000 + 59 59 1 0.0000000 5.3580000 18.7520000 24.1090000 + 60 60 1 0.0000000 5.3580000 18.7520000 29.4670000 + 61 61 1 0.0000000 5.3580000 24.1090000 2.6790000 + 62 62 1 0.0000000 5.3580000 24.1090000 8.0360000 + 63 63 1 0.0000000 5.3580000 24.1090000 13.3940000 + 64 64 1 0.0000000 5.3580000 24.1090000 18.7520000 + 65 65 1 0.0000000 5.3580000 24.1090000 24.1090000 + 66 66 1 0.0000000 5.3580000 24.1090000 29.4670000 + 67 67 1 0.0000000 5.3580000 29.4670000 2.6790000 + 68 68 1 0.0000000 5.3580000 29.4670000 8.0360000 + 69 69 1 0.0000000 5.3580000 29.4670000 13.3940000 + 70 70 1 0.0000000 5.3580000 29.4670000 18.7520000 + 71 71 1 0.0000000 5.3580000 29.4670000 24.1090000 + 72 72 1 0.0000000 5.3580000 29.4670000 29.4670000 + 73 73 1 0.0000000 10.7150000 2.6790000 2.6790000 + 74 74 1 0.0000000 10.7150000 2.6790000 8.0360000 + 75 75 1 0.0000000 10.7150000 2.6790000 13.3940000 + 76 76 1 0.0000000 10.7150000 2.6790000 18.7520000 + 77 77 1 0.0000000 10.7150000 2.6790000 24.1090000 + 78 78 1 0.0000000 10.7150000 2.6790000 29.4670000 + 79 79 1 0.0000000 10.7150000 8.0360000 2.6790000 + 80 80 1 0.0000000 10.7150000 8.0360000 8.0360000 + 81 81 1 0.0000000 10.7150000 8.0360000 13.3940000 + 82 82 1 0.0000000 10.7150000 8.0360000 18.7520000 + 83 83 1 0.0000000 10.7150000 8.0360000 24.1090000 + 84 84 1 0.0000000 10.7150000 8.0360000 29.4670000 + 85 85 1 0.0000000 10.7150000 13.3940000 2.6790000 + 86 86 1 0.0000000 10.7150000 13.3940000 8.0360000 + 87 87 1 0.0000000 10.7150000 13.3940000 13.3940000 + 88 88 1 0.0000000 10.7150000 13.3940000 18.7520000 + 89 89 1 0.0000000 10.7150000 13.3940000 24.1090000 + 90 90 1 0.0000000 10.7150000 13.3940000 29.4670000 + 91 91 1 0.0000000 10.7150000 18.7520000 2.6790000 + 92 92 1 0.0000000 10.7150000 18.7520000 8.0360000 + 93 93 1 0.0000000 10.7150000 18.7520000 13.3940000 + 94 94 1 0.0000000 10.7150000 18.7520000 18.7520000 + 95 95 1 0.0000000 10.7150000 18.7520000 24.1090000 + 96 96 1 0.0000000 10.7150000 18.7520000 29.4670000 + 97 97 1 0.0000000 10.7150000 24.1090000 2.6790000 + 98 98 1 0.0000000 10.7150000 24.1090000 8.0360000 + 99 99 1 0.0000000 10.7150000 24.1090000 13.3940000 + 100 100 1 0.0000000 10.7150000 24.1090000 18.7520000 + 101 101 1 0.0000000 10.7150000 24.1090000 24.1090000 + 102 102 1 0.0000000 10.7150000 24.1090000 29.4670000 + 103 103 1 0.0000000 10.7150000 29.4670000 2.6790000 + 104 104 1 0.0000000 10.7150000 29.4670000 8.0360000 + 105 105 1 0.0000000 10.7150000 29.4670000 13.3940000 + 106 106 1 0.0000000 10.7150000 29.4670000 18.7520000 + 107 107 1 0.0000000 10.7150000 29.4670000 24.1090000 + 108 108 1 0.0000000 10.7150000 29.4670000 29.4670000 + 109 109 1 0.0000000 16.0730000 2.6790000 2.6790000 + 110 110 1 0.0000000 16.0730000 2.6790000 8.0360000 + 111 111 1 0.0000000 16.0730000 2.6790000 13.3940000 + 112 112 1 0.0000000 16.0730000 2.6790000 18.7520000 + 113 113 1 0.0000000 16.0730000 2.6790000 24.1090000 + 114 114 1 0.0000000 16.0730000 2.6790000 29.4670000 + 115 115 1 0.0000000 16.0730000 8.0360000 2.6790000 + 116 116 1 0.0000000 16.0730000 8.0360000 8.0360000 + 117 117 1 0.0000000 16.0730000 8.0360000 13.3940000 + 118 118 1 0.0000000 16.0730000 8.0360000 18.7520000 + 119 119 1 0.0000000 16.0730000 8.0360000 24.1090000 + 120 120 1 0.0000000 16.0730000 8.0360000 29.4670000 + 121 121 1 0.0000000 16.0730000 13.3940000 2.6790000 + 122 122 1 0.0000000 16.0730000 13.3940000 8.0360000 + 123 123 1 0.0000000 16.0730000 13.3940000 13.3940000 + 124 124 1 0.0000000 16.0730000 13.3940000 18.7520000 + 125 125 1 0.0000000 16.0730000 13.3940000 24.1090000 + 126 126 1 0.0000000 16.0730000 13.3940000 29.4670000 + 127 127 1 0.0000000 16.0730000 18.7520000 2.6790000 + 128 128 1 0.0000000 16.0730000 18.7520000 8.0360000 + 129 129 1 0.0000000 16.0730000 18.7520000 13.3940000 + 130 130 1 0.0000000 16.0730000 18.7520000 18.7520000 + 131 131 1 0.0000000 16.0730000 18.7520000 24.1090000 + 132 132 1 0.0000000 16.0730000 18.7520000 29.4670000 + 133 133 1 0.0000000 16.0730000 24.1090000 2.6790000 + 134 134 1 0.0000000 16.0730000 24.1090000 8.0360000 + 135 135 1 0.0000000 16.0730000 24.1090000 13.3940000 + 136 136 1 0.0000000 16.0730000 24.1090000 18.7520000 + 137 137 1 0.0000000 16.0730000 24.1090000 24.1090000 + 138 138 1 0.0000000 16.0730000 24.1090000 29.4670000 + 139 139 1 0.0000000 16.0730000 29.4670000 2.6790000 + 140 140 1 0.0000000 16.0730000 29.4670000 8.0360000 + 141 141 1 0.0000000 16.0730000 29.4670000 13.3940000 + 142 142 1 0.0000000 16.0730000 29.4670000 18.7520000 + 143 143 1 0.0000000 16.0730000 29.4670000 24.1090000 + 144 144 1 0.0000000 16.0730000 29.4670000 29.4670000 + 145 145 1 0.0000000 21.4310000 2.6790000 2.6790000 + 146 146 1 0.0000000 21.4310000 2.6790000 8.0360000 + 147 147 1 0.0000000 21.4310000 2.6790000 13.3940000 + 148 148 1 0.0000000 21.4310000 2.6790000 18.7520000 + 149 149 1 0.0000000 21.4310000 2.6790000 24.1090000 + 150 150 1 0.0000000 21.4310000 2.6790000 29.4670000 + 151 151 1 0.0000000 21.4310000 8.0360000 2.6790000 + 152 152 1 0.0000000 21.4310000 8.0360000 8.0360000 + 153 153 1 0.0000000 21.4310000 8.0360000 13.3940000 + 154 154 1 0.0000000 21.4310000 8.0360000 18.7520000 + 155 155 1 0.0000000 21.4310000 8.0360000 24.1090000 + 156 156 1 0.0000000 21.4310000 8.0360000 29.4670000 + 157 157 1 0.0000000 21.4310000 13.3940000 2.6790000 + 158 158 1 0.0000000 21.4310000 13.3940000 8.0360000 + 159 159 1 0.0000000 21.4310000 13.3940000 13.3940000 + 160 160 1 0.0000000 21.4310000 13.3940000 18.7520000 + 161 161 1 0.0000000 21.4310000 13.3940000 24.1090000 + 162 162 1 0.0000000 21.4310000 13.3940000 29.4670000 + 163 163 1 0.0000000 21.4310000 18.7520000 2.6790000 + 164 164 1 0.0000000 21.4310000 18.7520000 8.0360000 + 165 165 1 0.0000000 21.4310000 18.7520000 13.3940000 + 166 166 1 0.0000000 21.4310000 18.7520000 18.7520000 + 167 167 1 0.0000000 21.4310000 18.7520000 24.1090000 + 168 168 1 0.0000000 21.4310000 18.7520000 29.4670000 + 169 169 1 0.0000000 21.4310000 24.1090000 2.6790000 + 170 170 1 0.0000000 21.4310000 24.1090000 8.0360000 + 171 171 1 0.0000000 21.4310000 24.1090000 13.3940000 + 172 172 1 0.0000000 21.4310000 24.1090000 18.7520000 + 173 173 1 0.0000000 21.4310000 24.1090000 24.1090000 + 174 174 1 0.0000000 21.4310000 24.1090000 29.4670000 + 175 175 1 0.0000000 21.4310000 29.4670000 2.6790000 + 176 176 1 0.0000000 21.4310000 29.4670000 8.0360000 + 177 177 1 0.0000000 21.4310000 29.4670000 13.3940000 + 178 178 1 0.0000000 21.4310000 29.4670000 18.7520000 + 179 179 1 0.0000000 21.4310000 29.4670000 24.1090000 + 180 180 1 0.0000000 21.4310000 29.4670000 29.4670000 + 181 181 1 0.0000000 26.7880000 2.6790000 2.6790000 + 182 182 1 0.0000000 26.7880000 2.6790000 8.0360000 + 183 183 1 0.0000000 26.7880000 2.6790000 13.3940000 + 184 184 1 0.0000000 26.7880000 2.6790000 18.7520000 + 185 185 1 0.0000000 26.7880000 2.6790000 24.1090000 + 186 186 1 0.0000000 26.7880000 2.6790000 29.4670000 + 187 187 1 0.0000000 26.7880000 8.0360000 2.6790000 + 188 188 1 0.0000000 26.7880000 8.0360000 8.0360000 + 189 189 1 0.0000000 26.7880000 8.0360000 13.3940000 + 190 190 1 0.0000000 26.7880000 8.0360000 18.7520000 + 191 191 1 0.0000000 26.7880000 8.0360000 24.1090000 + 192 192 1 0.0000000 26.7880000 8.0360000 29.4670000 + 193 193 1 0.0000000 26.7880000 13.3940000 2.6790000 + 194 194 1 0.0000000 26.7880000 13.3940000 8.0360000 + 195 195 1 0.0000000 26.7880000 13.3940000 13.3940000 + 196 196 1 0.0000000 26.7880000 13.3940000 18.7520000 + 197 197 1 0.0000000 26.7880000 13.3940000 24.1090000 + 198 198 1 0.0000000 26.7880000 13.3940000 29.4670000 + 199 199 1 0.0000000 26.7880000 18.7520000 2.6790000 + 200 200 1 0.0000000 26.7880000 18.7520000 8.0360000 + 201 201 1 0.0000000 26.7880000 18.7520000 13.3940000 + 202 202 1 0.0000000 26.7880000 18.7520000 18.7520000 + 203 203 1 0.0000000 26.7880000 18.7520000 24.1090000 + 204 204 1 0.0000000 26.7880000 18.7520000 29.4670000 + 205 205 1 0.0000000 26.7880000 24.1090000 2.6790000 + 206 206 1 0.0000000 26.7880000 24.1090000 8.0360000 + 207 207 1 0.0000000 26.7880000 24.1090000 13.3940000 + 208 208 1 0.0000000 26.7880000 24.1090000 18.7520000 + 209 209 1 0.0000000 26.7880000 24.1090000 24.1090000 + 210 210 1 0.0000000 26.7880000 24.1090000 29.4670000 + 211 211 1 0.0000000 26.7880000 29.4670000 2.6790000 + 212 212 1 0.0000000 26.7880000 29.4670000 8.0360000 + 213 213 1 0.0000000 26.7880000 29.4670000 13.3940000 + 214 214 1 0.0000000 26.7880000 29.4670000 18.7520000 + 215 215 1 0.0000000 26.7880000 29.4670000 24.1090000 + 216 216 1 0.0000000 26.7880000 29.4670000 29.4670000 + 217 217 1 0.0000000 2.6790000 5.3580000 2.6790000 + 218 218 1 0.0000000 2.6790000 5.3580000 8.0360000 + 219 219 1 0.0000000 2.6790000 5.3580000 13.3940000 + 220 220 1 0.0000000 2.6790000 5.3580000 18.7520000 + 221 221 1 0.0000000 2.6790000 5.3580000 24.1090000 + 222 222 1 0.0000000 2.6790000 5.3580000 29.4670000 + 223 223 1 0.0000000 2.6790000 10.7150000 2.6790000 + 224 224 1 0.0000000 2.6790000 10.7150000 8.0360000 + 225 225 1 0.0000000 2.6790000 10.7150000 13.3940000 + 226 226 1 0.0000000 2.6790000 10.7150000 18.7520000 + 227 227 1 0.0000000 2.6790000 10.7150000 24.1090000 + 228 228 1 0.0000000 2.6790000 10.7150000 29.4670000 + 229 229 1 0.0000000 2.6790000 16.0730000 2.6790000 + 230 230 1 0.0000000 2.6790000 16.0730000 8.0360000 + 231 231 1 0.0000000 2.6790000 16.0730000 13.3940000 + 232 232 1 0.0000000 2.6790000 16.0730000 18.7520000 + 233 233 1 0.0000000 2.6790000 16.0730000 24.1090000 + 234 234 1 0.0000000 2.6790000 16.0730000 29.4670000 + 235 235 1 0.0000000 2.6790000 21.4310000 2.6790000 + 236 236 1 0.0000000 2.6790000 21.4310000 8.0360000 + 237 237 1 0.0000000 2.6790000 21.4310000 13.3940000 + 238 238 1 0.0000000 2.6790000 21.4310000 18.7520000 + 239 239 1 0.0000000 2.6790000 21.4310000 24.1090000 + 240 240 1 0.0000000 2.6790000 21.4310000 29.4670000 + 241 241 1 0.0000000 2.6790000 26.7880000 2.6790000 + 242 242 1 0.0000000 2.6790000 26.7880000 8.0360000 + 243 243 1 0.0000000 2.6790000 26.7880000 13.3940000 + 244 244 1 0.0000000 2.6790000 26.7880000 18.7520000 + 245 245 1 0.0000000 2.6790000 26.7880000 24.1090000 + 246 246 1 0.0000000 2.6790000 26.7880000 29.4670000 + 247 247 1 0.0000000 2.6790000 32.1460000 2.6790000 + 248 248 1 0.0000000 2.6790000 32.1460000 8.0360000 + 249 249 1 0.0000000 2.6790000 32.1460000 13.3940000 + 250 250 1 0.0000000 2.6790000 32.1460000 18.7520000 + 251 251 1 0.0000000 2.6790000 32.1460000 24.1090000 + 252 252 1 0.0000000 2.6790000 32.1460000 29.4670000 + 253 253 1 0.0000000 8.0360000 5.3580000 2.6790000 + 254 254 1 0.0000000 8.0360000 5.3580000 8.0360000 + 255 255 1 0.0000000 8.0360000 5.3580000 13.3940000 + 256 256 1 0.0000000 8.0360000 5.3580000 18.7520000 + 257 257 1 0.0000000 8.0360000 5.3580000 24.1090000 + 258 258 1 0.0000000 8.0360000 5.3580000 29.4670000 + 259 259 1 0.0000000 8.0360000 10.7150000 2.6790000 + 260 260 1 0.0000000 8.0360000 10.7150000 8.0360000 + 261 261 1 0.0000000 8.0360000 10.7150000 13.3940000 + 262 262 1 0.0000000 8.0360000 10.7150000 18.7520000 + 263 263 1 0.0000000 8.0360000 10.7150000 24.1090000 + 264 264 1 0.0000000 8.0360000 10.7150000 29.4670000 + 265 265 1 0.0000000 8.0360000 16.0730000 2.6790000 + 266 266 1 0.0000000 8.0360000 16.0730000 8.0360000 + 267 267 1 0.0000000 8.0360000 16.0730000 13.3940000 + 268 268 1 0.0000000 8.0360000 16.0730000 18.7520000 + 269 269 1 0.0000000 8.0360000 16.0730000 24.1090000 + 270 270 1 0.0000000 8.0360000 16.0730000 29.4670000 + 271 271 1 0.0000000 8.0360000 21.4310000 2.6790000 + 272 272 1 0.0000000 8.0360000 21.4310000 8.0360000 + 273 273 1 0.0000000 8.0360000 21.4310000 13.3940000 + 274 274 1 0.0000000 8.0360000 21.4310000 18.7520000 + 275 275 1 0.0000000 8.0360000 21.4310000 24.1090000 + 276 276 1 0.0000000 8.0360000 21.4310000 29.4670000 + 277 277 1 0.0000000 8.0360000 26.7880000 2.6790000 + 278 278 1 0.0000000 8.0360000 26.7880000 8.0360000 + 279 279 1 0.0000000 8.0360000 26.7880000 13.3940000 + 280 280 1 0.0000000 8.0360000 26.7880000 18.7520000 + 281 281 1 0.0000000 8.0360000 26.7880000 24.1090000 + 282 282 1 0.0000000 8.0360000 26.7880000 29.4670000 + 283 283 1 0.0000000 8.0360000 32.1460000 2.6790000 + 284 284 1 0.0000000 8.0360000 32.1460000 8.0360000 + 285 285 1 0.0000000 8.0360000 32.1460000 13.3940000 + 286 286 1 0.0000000 8.0360000 32.1460000 18.7520000 + 287 287 1 0.0000000 8.0360000 32.1460000 24.1090000 + 288 288 1 0.0000000 8.0360000 32.1460000 29.4670000 + 289 289 1 0.0000000 13.3940000 5.3580000 2.6790000 + 290 290 1 0.0000000 13.3940000 5.3580000 8.0360000 + 291 291 1 0.0000000 13.3940000 5.3580000 13.3940000 + 292 292 1 0.0000000 13.3940000 5.3580000 18.7520000 + 293 293 1 0.0000000 13.3940000 5.3580000 24.1090000 + 294 294 1 0.0000000 13.3940000 5.3580000 29.4670000 + 295 295 1 0.0000000 13.3940000 10.7150000 2.6790000 + 296 296 1 0.0000000 13.3940000 10.7150000 8.0360000 + 297 297 1 0.0000000 13.3940000 10.7150000 13.3940000 + 298 298 1 0.0000000 13.3940000 10.7150000 18.7520000 + 299 299 1 0.0000000 13.3940000 10.7150000 24.1090000 + 300 300 1 0.0000000 13.3940000 10.7150000 29.4670000 + 301 301 1 0.0000000 13.3940000 16.0730000 2.6790000 + 302 302 1 0.0000000 13.3940000 16.0730000 8.0360000 + 303 303 1 0.0000000 13.3940000 16.0730000 13.3940000 + 304 304 1 0.0000000 13.3940000 16.0730000 18.7520000 + 305 305 1 0.0000000 13.3940000 16.0730000 24.1090000 + 306 306 1 0.0000000 13.3940000 16.0730000 29.4670000 + 307 307 1 0.0000000 13.3940000 21.4310000 2.6790000 + 308 308 1 0.0000000 13.3940000 21.4310000 8.0360000 + 309 309 1 0.0000000 13.3940000 21.4310000 13.3940000 + 310 310 1 0.0000000 13.3940000 21.4310000 18.7520000 + 311 311 1 0.0000000 13.3940000 21.4310000 24.1090000 + 312 312 1 0.0000000 13.3940000 21.4310000 29.4670000 + 313 313 1 0.0000000 13.3940000 26.7880000 2.6790000 + 314 314 1 0.0000000 13.3940000 26.7880000 8.0360000 + 315 315 1 0.0000000 13.3940000 26.7880000 13.3940000 + 316 316 1 0.0000000 13.3940000 26.7880000 18.7520000 + 317 317 1 0.0000000 13.3940000 26.7880000 24.1090000 + 318 318 1 0.0000000 13.3940000 26.7880000 29.4670000 + 319 319 1 0.0000000 13.3940000 32.1460000 2.6790000 + 320 320 1 0.0000000 13.3940000 32.1460000 8.0360000 + 321 321 1 0.0000000 13.3940000 32.1460000 13.3940000 + 322 322 1 0.0000000 13.3940000 32.1460000 18.7520000 + 323 323 1 0.0000000 13.3940000 32.1460000 24.1090000 + 324 324 1 0.0000000 13.3940000 32.1460000 29.4670000 + 325 325 1 0.0000000 18.7520000 5.3580000 2.6790000 + 326 326 1 0.0000000 18.7520000 5.3580000 8.0360000 + 327 327 1 0.0000000 18.7520000 5.3580000 13.3940000 + 328 328 1 0.0000000 18.7520000 5.3580000 18.7520000 + 329 329 1 0.0000000 18.7520000 5.3580000 24.1090000 + 330 330 1 0.0000000 18.7520000 5.3580000 29.4670000 + 331 331 1 0.0000000 18.7520000 10.7150000 2.6790000 + 332 332 1 0.0000000 18.7520000 10.7150000 8.0360000 + 333 333 1 0.0000000 18.7520000 10.7150000 13.3940000 + 334 334 1 0.0000000 18.7520000 10.7150000 18.7520000 + 335 335 1 0.0000000 18.7520000 10.7150000 24.1090000 + 336 336 1 0.0000000 18.7520000 10.7150000 29.4670000 + 337 337 1 0.0000000 18.7520000 16.0730000 2.6790000 + 338 338 1 0.0000000 18.7520000 16.0730000 8.0360000 + 339 339 1 0.0000000 18.7520000 16.0730000 13.3940000 + 340 340 1 0.0000000 18.7520000 16.0730000 18.7520000 + 341 341 1 0.0000000 18.7520000 16.0730000 24.1090000 + 342 342 1 0.0000000 18.7520000 16.0730000 29.4670000 + 343 343 1 0.0000000 18.7520000 21.4310000 2.6790000 + 344 344 1 0.0000000 18.7520000 21.4310000 8.0360000 + 345 345 1 0.0000000 18.7520000 21.4310000 13.3940000 + 346 346 1 0.0000000 18.7520000 21.4310000 18.7520000 + 347 347 1 0.0000000 18.7520000 21.4310000 24.1090000 + 348 348 1 0.0000000 18.7520000 21.4310000 29.4670000 + 349 349 1 0.0000000 18.7520000 26.7880000 2.6790000 + 350 350 1 0.0000000 18.7520000 26.7880000 8.0360000 + 351 351 1 0.0000000 18.7520000 26.7880000 13.3940000 + 352 352 1 0.0000000 18.7520000 26.7880000 18.7520000 + 353 353 1 0.0000000 18.7520000 26.7880000 24.1090000 + 354 354 1 0.0000000 18.7520000 26.7880000 29.4670000 + 355 355 1 0.0000000 18.7520000 32.1460000 2.6790000 + 356 356 1 0.0000000 18.7520000 32.1460000 8.0360000 + 357 357 1 0.0000000 18.7520000 32.1460000 13.3940000 + 358 358 1 0.0000000 18.7520000 32.1460000 18.7520000 + 359 359 1 0.0000000 18.7520000 32.1460000 24.1090000 + 360 360 1 0.0000000 18.7520000 32.1460000 29.4670000 + 361 361 1 0.0000000 24.1090000 5.3580000 2.6790000 + 362 362 1 0.0000000 24.1090000 5.3580000 8.0360000 + 363 363 1 0.0000000 24.1090000 5.3580000 13.3940000 + 364 364 1 0.0000000 24.1090000 5.3580000 18.7520000 + 365 365 1 0.0000000 24.1090000 5.3580000 24.1090000 + 366 366 1 0.0000000 24.1090000 5.3580000 29.4670000 + 367 367 1 0.0000000 24.1090000 10.7150000 2.6790000 + 368 368 1 0.0000000 24.1090000 10.7150000 8.0360000 + 369 369 1 0.0000000 24.1090000 10.7150000 13.3940000 + 370 370 1 0.0000000 24.1090000 10.7150000 18.7520000 + 371 371 1 0.0000000 24.1090000 10.7150000 24.1090000 + 372 372 1 0.0000000 24.1090000 10.7150000 29.4670000 + 373 373 1 0.0000000 24.1090000 16.0730000 2.6790000 + 374 374 1 0.0000000 24.1090000 16.0730000 8.0360000 + 375 375 1 0.0000000 24.1090000 16.0730000 13.3940000 + 376 376 1 0.0000000 24.1090000 16.0730000 18.7520000 + 377 377 1 0.0000000 24.1090000 16.0730000 24.1090000 + 378 378 1 0.0000000 24.1090000 16.0730000 29.4670000 + 379 379 1 0.0000000 24.1090000 21.4310000 2.6790000 + 380 380 1 0.0000000 24.1090000 21.4310000 8.0360000 + 381 381 1 0.0000000 24.1090000 21.4310000 13.3940000 + 382 382 1 0.0000000 24.1090000 21.4310000 18.7520000 + 383 383 1 0.0000000 24.1090000 21.4310000 24.1090000 + 384 384 1 0.0000000 24.1090000 21.4310000 29.4670000 + 385 385 1 0.0000000 24.1090000 26.7880000 2.6790000 + 386 386 1 0.0000000 24.1090000 26.7880000 8.0360000 + 387 387 1 0.0000000 24.1090000 26.7880000 13.3940000 + 388 388 1 0.0000000 24.1090000 26.7880000 18.7520000 + 389 389 1 0.0000000 24.1090000 26.7880000 24.1090000 + 390 390 1 0.0000000 24.1090000 26.7880000 29.4670000 + 391 391 1 0.0000000 24.1090000 32.1460000 2.6790000 + 392 392 1 0.0000000 24.1090000 32.1460000 8.0360000 + 393 393 1 0.0000000 24.1090000 32.1460000 13.3940000 + 394 394 1 0.0000000 24.1090000 32.1460000 18.7520000 + 395 395 1 0.0000000 24.1090000 32.1460000 24.1090000 + 396 396 1 0.0000000 24.1090000 32.1460000 29.4670000 + 397 397 1 0.0000000 29.4670000 5.3580000 2.6790000 + 398 398 1 0.0000000 29.4670000 5.3580000 8.0360000 + 399 399 1 0.0000000 29.4670000 5.3580000 13.3940000 + 400 400 1 0.0000000 29.4670000 5.3580000 18.7520000 + 401 401 1 0.0000000 29.4670000 5.3580000 24.1090000 + 402 402 1 0.0000000 29.4670000 5.3580000 29.4670000 + 403 403 1 0.0000000 29.4670000 10.7150000 2.6790000 + 404 404 1 0.0000000 29.4670000 10.7150000 8.0360000 + 405 405 1 0.0000000 29.4670000 10.7150000 13.3940000 + 406 406 1 0.0000000 29.4670000 10.7150000 18.7520000 + 407 407 1 0.0000000 29.4670000 10.7150000 24.1090000 + 408 408 1 0.0000000 29.4670000 10.7150000 29.4670000 + 409 409 1 0.0000000 29.4670000 16.0730000 2.6790000 + 410 410 1 0.0000000 29.4670000 16.0730000 8.0360000 + 411 411 1 0.0000000 29.4670000 16.0730000 13.3940000 + 412 412 1 0.0000000 29.4670000 16.0730000 18.7520000 + 413 413 1 0.0000000 29.4670000 16.0730000 24.1090000 + 414 414 1 0.0000000 29.4670000 16.0730000 29.4670000 + 415 415 1 0.0000000 29.4670000 21.4310000 2.6790000 + 416 416 1 0.0000000 29.4670000 21.4310000 8.0360000 + 417 417 1 0.0000000 29.4670000 21.4310000 13.3940000 + 418 418 1 0.0000000 29.4670000 21.4310000 18.7520000 + 419 419 1 0.0000000 29.4670000 21.4310000 24.1090000 + 420 420 1 0.0000000 29.4670000 21.4310000 29.4670000 + 421 421 1 0.0000000 29.4670000 26.7880000 2.6790000 + 422 422 1 0.0000000 29.4670000 26.7880000 8.0360000 + 423 423 1 0.0000000 29.4670000 26.7880000 13.3940000 + 424 424 1 0.0000000 29.4670000 26.7880000 18.7520000 + 425 425 1 0.0000000 29.4670000 26.7880000 24.1090000 + 426 426 1 0.0000000 29.4670000 26.7880000 29.4670000 + 427 427 1 0.0000000 29.4670000 32.1460000 2.6790000 + 428 428 1 0.0000000 29.4670000 32.1460000 8.0360000 + 429 429 1 0.0000000 29.4670000 32.1460000 13.3940000 + 430 430 1 0.0000000 29.4670000 32.1460000 18.7520000 + 431 431 1 0.0000000 29.4670000 32.1460000 24.1090000 + 432 432 1 0.0000000 29.4670000 32.1460000 29.4670000 + 433 433 1 0.0000000 2.6790000 2.6790000 5.3580000 + 434 434 1 0.0000000 2.6790000 2.6790000 10.7150000 + 435 435 1 0.0000000 2.6790000 2.6790000 16.0730000 + 436 436 1 0.0000000 2.6790000 2.6790000 21.4310000 + 437 437 1 0.0000000 2.6790000 2.6790000 26.7880000 + 438 438 1 0.0000000 2.6790000 2.6790000 32.1460000 + 439 439 1 0.0000000 2.6790000 8.0360000 5.3580000 + 440 440 1 0.0000000 2.6790000 8.0360000 10.7150000 + 441 441 1 0.0000000 2.6790000 8.0360000 16.0730000 + 442 442 1 0.0000000 2.6790000 8.0360000 21.4310000 + 443 443 1 0.0000000 2.6790000 8.0360000 26.7880000 + 444 444 1 0.0000000 2.6790000 8.0360000 32.1460000 + 445 445 1 0.0000000 2.6790000 13.3940000 5.3580000 + 446 446 1 0.0000000 2.6790000 13.3940000 10.7150000 + 447 447 1 0.0000000 2.6790000 13.3940000 16.0730000 + 448 448 1 0.0000000 2.6790000 13.3940000 21.4310000 + 449 449 1 0.0000000 2.6790000 13.3940000 26.7880000 + 450 450 1 0.0000000 2.6790000 13.3940000 32.1460000 + 451 451 1 0.0000000 2.6790000 18.7520000 5.3580000 + 452 452 1 0.0000000 2.6790000 18.7520000 10.7150000 + 453 453 1 0.0000000 2.6790000 18.7520000 16.0730000 + 454 454 1 0.0000000 2.6790000 18.7520000 21.4310000 + 455 455 1 0.0000000 2.6790000 18.7520000 26.7880000 + 456 456 1 0.0000000 2.6790000 18.7520000 32.1460000 + 457 457 1 0.0000000 2.6790000 24.1090000 5.3580000 + 458 458 1 0.0000000 2.6790000 24.1090000 10.7150000 + 459 459 1 0.0000000 2.6790000 24.1090000 16.0730000 + 460 460 1 0.0000000 2.6790000 24.1090000 21.4310000 + 461 461 1 0.0000000 2.6790000 24.1090000 26.7880000 + 462 462 1 0.0000000 2.6790000 24.1090000 32.1460000 + 463 463 1 0.0000000 2.6790000 29.4670000 5.3580000 + 464 464 1 0.0000000 2.6790000 29.4670000 10.7150000 + 465 465 1 0.0000000 2.6790000 29.4670000 16.0730000 + 466 466 1 0.0000000 2.6790000 29.4670000 21.4310000 + 467 467 1 0.0000000 2.6790000 29.4670000 26.7880000 + 468 468 1 0.0000000 2.6790000 29.4670000 32.1460000 + 469 469 1 0.0000000 8.0360000 2.6790000 5.3580000 + 470 470 1 0.0000000 8.0360000 2.6790000 10.7150000 + 471 471 1 0.0000000 8.0360000 2.6790000 16.0730000 + 472 472 1 0.0000000 8.0360000 2.6790000 21.4310000 + 473 473 1 0.0000000 8.0360000 2.6790000 26.7880000 + 474 474 1 0.0000000 8.0360000 2.6790000 32.1460000 + 475 475 1 0.0000000 8.0360000 8.0360000 5.3580000 + 476 476 1 0.0000000 8.0360000 8.0360000 10.7150000 + 477 477 1 0.0000000 8.0360000 8.0360000 16.0730000 + 478 478 1 0.0000000 8.0360000 8.0360000 21.4310000 + 479 479 1 0.0000000 8.0360000 8.0360000 26.7880000 + 480 480 1 0.0000000 8.0360000 8.0360000 32.1460000 + 481 481 1 0.0000000 8.0360000 13.3940000 5.3580000 + 482 482 1 0.0000000 8.0360000 13.3940000 10.7150000 + 483 483 1 0.0000000 8.0360000 13.3940000 16.0730000 + 484 484 1 0.0000000 8.0360000 13.3940000 21.4310000 + 485 485 1 0.0000000 8.0360000 13.3940000 26.7880000 + 486 486 1 0.0000000 8.0360000 13.3940000 32.1460000 + 487 487 1 0.0000000 8.0360000 18.7520000 5.3580000 + 488 488 1 0.0000000 8.0360000 18.7520000 10.7150000 + 489 489 1 0.0000000 8.0360000 18.7520000 16.0730000 + 490 490 1 0.0000000 8.0360000 18.7520000 21.4310000 + 491 491 1 0.0000000 8.0360000 18.7520000 26.7880000 + 492 492 1 0.0000000 8.0360000 18.7520000 32.1460000 + 493 493 1 0.0000000 8.0360000 24.1090000 5.3580000 + 494 494 1 0.0000000 8.0360000 24.1090000 10.7150000 + 495 495 1 0.0000000 8.0360000 24.1090000 16.0730000 + 496 496 1 0.0000000 8.0360000 24.1090000 21.4310000 + 497 497 1 0.0000000 8.0360000 24.1090000 26.7880000 + 498 498 1 0.0000000 8.0360000 24.1090000 32.1460000 + 499 499 1 0.0000000 8.0360000 29.4670000 5.3580000 + 500 500 1 0.0000000 8.0360000 29.4670000 10.7150000 + 501 501 1 0.0000000 8.0360000 29.4670000 16.0730000 + 502 502 1 0.0000000 8.0360000 29.4670000 21.4310000 + 503 503 1 0.0000000 8.0360000 29.4670000 26.7880000 + 504 504 1 0.0000000 8.0360000 29.4670000 32.1460000 + 505 505 1 0.0000000 13.3940000 2.6790000 5.3580000 + 506 506 1 0.0000000 13.3940000 2.6790000 10.7150000 + 507 507 1 0.0000000 13.3940000 2.6790000 16.0730000 + 508 508 1 0.0000000 13.3940000 2.6790000 21.4310000 + 509 509 1 0.0000000 13.3940000 2.6790000 26.7880000 + 510 510 1 0.0000000 13.3940000 2.6790000 32.1460000 + 511 511 1 0.0000000 13.3940000 8.0360000 5.3580000 + 512 512 1 0.0000000 13.3940000 8.0360000 10.7150000 + 513 513 1 0.0000000 13.3940000 8.0360000 16.0730000 + 514 514 1 0.0000000 13.3940000 8.0360000 21.4310000 + 515 515 1 0.0000000 13.3940000 8.0360000 26.7880000 + 516 516 1 0.0000000 13.3940000 8.0360000 32.1460000 + 517 517 1 0.0000000 13.3940000 13.3940000 5.3580000 + 518 518 1 0.0000000 13.3940000 13.3940000 10.7150000 + 519 519 1 0.0000000 13.3940000 13.3940000 16.0730000 + 520 520 1 0.0000000 13.3940000 13.3940000 21.4310000 + 521 521 1 0.0000000 13.3940000 13.3940000 26.7880000 + 522 522 1 0.0000000 13.3940000 13.3940000 32.1460000 + 523 523 1 0.0000000 13.3940000 18.7520000 5.3580000 + 524 524 1 0.0000000 13.3940000 18.7520000 10.7150000 + 525 525 1 0.0000000 13.3940000 18.7520000 16.0730000 + 526 526 1 0.0000000 13.3940000 18.7520000 21.4310000 + 527 527 1 0.0000000 13.3940000 18.7520000 26.7880000 + 528 528 1 0.0000000 13.3940000 18.7520000 32.1460000 + 529 529 1 0.0000000 13.3940000 24.1090000 5.3580000 + 530 530 1 0.0000000 13.3940000 24.1090000 10.7150000 + 531 531 1 0.0000000 13.3940000 24.1090000 16.0730000 + 532 532 1 0.0000000 13.3940000 24.1090000 21.4310000 + 533 533 1 0.0000000 13.3940000 24.1090000 26.7880000 + 534 534 1 0.0000000 13.3940000 24.1090000 32.1460000 + 535 535 1 0.0000000 13.3940000 29.4670000 5.3580000 + 536 536 1 0.0000000 13.3940000 29.4670000 10.7150000 + 537 537 1 0.0000000 13.3940000 29.4670000 16.0730000 + 538 538 1 0.0000000 13.3940000 29.4670000 21.4310000 + 539 539 1 0.0000000 13.3940000 29.4670000 26.7880000 + 540 540 1 0.0000000 13.3940000 29.4670000 32.1460000 + 541 541 1 0.0000000 18.7520000 2.6790000 5.3580000 + 542 542 1 0.0000000 18.7520000 2.6790000 10.7150000 + 543 543 1 0.0000000 18.7520000 2.6790000 16.0730000 + 544 544 1 0.0000000 18.7520000 2.6790000 21.4310000 + 545 545 1 0.0000000 18.7520000 2.6790000 26.7880000 + 546 546 1 0.0000000 18.7520000 2.6790000 32.1460000 + 547 547 1 0.0000000 18.7520000 8.0360000 5.3580000 + 548 548 1 0.0000000 18.7520000 8.0360000 10.7150000 + 549 549 1 0.0000000 18.7520000 8.0360000 16.0730000 + 550 550 1 0.0000000 18.7520000 8.0360000 21.4310000 + 551 551 1 0.0000000 18.7520000 8.0360000 26.7880000 + 552 552 1 0.0000000 18.7520000 8.0360000 32.1460000 + 553 553 1 0.0000000 18.7520000 13.3940000 5.3580000 + 554 554 1 0.0000000 18.7520000 13.3940000 10.7150000 + 555 555 1 0.0000000 18.7520000 13.3940000 16.0730000 + 556 556 1 0.0000000 18.7520000 13.3940000 21.4310000 + 557 557 1 0.0000000 18.7520000 13.3940000 26.7880000 + 558 558 1 0.0000000 18.7520000 13.3940000 32.1460000 + 559 559 1 0.0000000 18.7520000 18.7520000 5.3580000 + 560 560 1 0.0000000 18.7520000 18.7520000 10.7150000 + 561 561 1 0.0000000 18.7520000 18.7520000 16.0730000 + 562 562 1 0.0000000 18.7520000 18.7520000 21.4310000 + 563 563 1 0.0000000 18.7520000 18.7520000 26.7880000 + 564 564 1 0.0000000 18.7520000 18.7520000 32.1460000 + 565 565 1 0.0000000 18.7520000 24.1090000 5.3580000 + 566 566 1 0.0000000 18.7520000 24.1090000 10.7150000 + 567 567 1 0.0000000 18.7520000 24.1090000 16.0730000 + 568 568 1 0.0000000 18.7520000 24.1090000 21.4310000 + 569 569 1 0.0000000 18.7520000 24.1090000 26.7880000 + 570 570 1 0.0000000 18.7520000 24.1090000 32.1460000 + 571 571 1 0.0000000 18.7520000 29.4670000 5.3580000 + 572 572 1 0.0000000 18.7520000 29.4670000 10.7150000 + 573 573 1 0.0000000 18.7520000 29.4670000 16.0730000 + 574 574 1 0.0000000 18.7520000 29.4670000 21.4310000 + 575 575 1 0.0000000 18.7520000 29.4670000 26.7880000 + 576 576 1 0.0000000 18.7520000 29.4670000 32.1460000 + 577 577 1 0.0000000 24.1090000 2.6790000 5.3580000 + 578 578 1 0.0000000 24.1090000 2.6790000 10.7150000 + 579 579 1 0.0000000 24.1090000 2.6790000 16.0730000 + 580 580 1 0.0000000 24.1090000 2.6790000 21.4310000 + 581 581 1 0.0000000 24.1090000 2.6790000 26.7880000 + 582 582 1 0.0000000 24.1090000 2.6790000 32.1460000 + 583 583 1 0.0000000 24.1090000 8.0360000 5.3580000 + 584 584 1 0.0000000 24.1090000 8.0360000 10.7150000 + 585 585 1 0.0000000 24.1090000 8.0360000 16.0730000 + 586 586 1 0.0000000 24.1090000 8.0360000 21.4310000 + 587 587 1 0.0000000 24.1090000 8.0360000 26.7880000 + 588 588 1 0.0000000 24.1090000 8.0360000 32.1460000 + 589 589 1 0.0000000 24.1090000 13.3940000 5.3580000 + 590 590 1 0.0000000 24.1090000 13.3940000 10.7150000 + 591 591 1 0.0000000 24.1090000 13.3940000 16.0730000 + 592 592 1 0.0000000 24.1090000 13.3940000 21.4310000 + 593 593 1 0.0000000 24.1090000 13.3940000 26.7880000 + 594 594 1 0.0000000 24.1090000 13.3940000 32.1460000 + 595 595 1 0.0000000 24.1090000 18.7520000 5.3580000 + 596 596 1 0.0000000 24.1090000 18.7520000 10.7150000 + 597 597 1 0.0000000 24.1090000 18.7520000 16.0730000 + 598 598 1 0.0000000 24.1090000 18.7520000 21.4310000 + 599 599 1 0.0000000 24.1090000 18.7520000 26.7880000 + 600 600 1 0.0000000 24.1090000 18.7520000 32.1460000 + 601 601 1 0.0000000 24.1090000 24.1090000 5.3580000 + 602 602 1 0.0000000 24.1090000 24.1090000 10.7150000 + 603 603 1 0.0000000 24.1090000 24.1090000 16.0730000 + 604 604 1 0.0000000 24.1090000 24.1090000 21.4310000 + 605 605 1 0.0000000 24.1090000 24.1090000 26.7880000 + 606 606 1 0.0000000 24.1090000 24.1090000 32.1460000 + 607 607 1 0.0000000 24.1090000 29.4670000 5.3580000 + 608 608 1 0.0000000 24.1090000 29.4670000 10.7150000 + 609 609 1 0.0000000 24.1090000 29.4670000 16.0730000 + 610 610 1 0.0000000 24.1090000 29.4670000 21.4310000 + 611 611 1 0.0000000 24.1090000 29.4670000 26.7880000 + 612 612 1 0.0000000 24.1090000 29.4670000 32.1460000 + 613 613 1 0.0000000 29.4670000 2.6790000 5.3580000 + 614 614 1 0.0000000 29.4670000 2.6790000 10.7150000 + 615 615 1 0.0000000 29.4670000 2.6790000 16.0730000 + 616 616 1 0.0000000 29.4670000 2.6790000 21.4310000 + 617 617 1 0.0000000 29.4670000 2.6790000 26.7880000 + 618 618 1 0.0000000 29.4670000 2.6790000 32.1460000 + 619 619 1 0.0000000 29.4670000 8.0360000 5.3580000 + 620 620 1 0.0000000 29.4670000 8.0360000 10.7150000 + 621 621 1 0.0000000 29.4670000 8.0360000 16.0730000 + 622 622 1 0.0000000 29.4670000 8.0360000 21.4310000 + 623 623 1 0.0000000 29.4670000 8.0360000 26.7880000 + 624 624 1 0.0000000 29.4670000 8.0360000 32.1460000 + 625 625 1 0.0000000 29.4670000 13.3940000 5.3580000 + 626 626 1 0.0000000 29.4670000 13.3940000 10.7150000 + 627 627 1 0.0000000 29.4670000 13.3940000 16.0730000 + 628 628 1 0.0000000 29.4670000 13.3940000 21.4310000 + 629 629 1 0.0000000 29.4670000 13.3940000 26.7880000 + 630 630 1 0.0000000 29.4670000 13.3940000 32.1460000 + 631 631 1 0.0000000 29.4670000 18.7520000 5.3580000 + 632 632 1 0.0000000 29.4670000 18.7520000 10.7150000 + 633 633 1 0.0000000 29.4670000 18.7520000 16.0730000 + 634 634 1 0.0000000 29.4670000 18.7520000 21.4310000 + 635 635 1 0.0000000 29.4670000 18.7520000 26.7880000 + 636 636 1 0.0000000 29.4670000 18.7520000 32.1460000 + 637 637 1 0.0000000 29.4670000 24.1090000 5.3580000 + 638 638 1 0.0000000 29.4670000 24.1090000 10.7150000 + 639 639 1 0.0000000 29.4670000 24.1090000 16.0730000 + 640 640 1 0.0000000 29.4670000 24.1090000 21.4310000 + 641 641 1 0.0000000 29.4670000 24.1090000 26.7880000 + 642 642 1 0.0000000 29.4670000 24.1090000 32.1460000 + 643 643 1 0.0000000 29.4670000 29.4670000 5.3580000 + 644 644 1 0.0000000 29.4670000 29.4670000 10.7150000 + 645 645 1 0.0000000 29.4670000 29.4670000 16.0730000 + 646 646 1 0.0000000 29.4670000 29.4670000 21.4310000 + 647 647 1 0.0000000 29.4670000 29.4670000 26.7880000 + 648 648 1 0.0000000 29.4670000 29.4670000 32.1460000 + 649 649 1 0.0000000 0.0000000 5.3580000 5.3580000 + 650 650 1 0.0000000 0.0000000 5.3580000 10.7150000 + 651 651 1 0.0000000 0.0000000 5.3580000 16.0730000 + 652 652 1 0.0000000 0.0000000 5.3580000 21.4310000 + 653 653 1 0.0000000 0.0000000 5.3580000 26.7880000 + 654 654 1 0.0000000 0.0000000 5.3580000 32.1460000 + 655 655 1 0.0000000 0.0000000 10.7150000 5.3580000 + 656 656 1 0.0000000 0.0000000 10.7150000 10.7150000 + 657 657 1 0.0000000 0.0000000 10.7150000 16.0730000 + 658 658 1 0.0000000 0.0000000 10.7150000 21.4310000 + 659 659 1 0.0000000 0.0000000 10.7150000 26.7880000 + 660 660 1 0.0000000 0.0000000 10.7150000 32.1460000 + 661 661 1 0.0000000 0.0000000 16.0730000 5.3580000 + 662 662 1 0.0000000 0.0000000 16.0730000 10.7150000 + 663 663 1 0.0000000 0.0000000 16.0730000 16.0730000 + 664 664 1 0.0000000 0.0000000 16.0730000 21.4310000 + 665 665 1 0.0000000 0.0000000 16.0730000 26.7880000 + 666 666 1 0.0000000 0.0000000 16.0730000 32.1460000 + 667 667 1 0.0000000 0.0000000 21.4310000 5.3580000 + 668 668 1 0.0000000 0.0000000 21.4310000 10.7150000 + 669 669 1 0.0000000 0.0000000 21.4310000 16.0730000 + 670 670 1 0.0000000 0.0000000 21.4310000 21.4310000 + 671 671 1 0.0000000 0.0000000 21.4310000 26.7880000 + 672 672 1 0.0000000 0.0000000 21.4310000 32.1460000 + 673 673 1 0.0000000 0.0000000 26.7880000 5.3580000 + 674 674 1 0.0000000 0.0000000 26.7880000 10.7150000 + 675 675 1 0.0000000 0.0000000 26.7880000 16.0730000 + 676 676 1 0.0000000 0.0000000 26.7880000 21.4310000 + 677 677 1 0.0000000 0.0000000 26.7880000 26.7880000 + 678 678 1 0.0000000 0.0000000 26.7880000 32.1460000 + 679 679 1 0.0000000 0.0000000 32.1460000 5.3580000 + 680 680 1 0.0000000 0.0000000 32.1460000 10.7150000 + 681 681 1 0.0000000 0.0000000 32.1460000 16.0730000 + 682 682 1 0.0000000 0.0000000 32.1460000 21.4310000 + 683 683 1 0.0000000 0.0000000 32.1460000 26.7880000 + 684 684 1 0.0000000 0.0000000 32.1460000 32.1460000 + 685 685 1 0.0000000 5.3580000 5.3580000 5.3580000 + 686 686 1 0.0000000 5.3580000 5.3580000 10.7150000 + 687 687 1 0.0000000 5.3580000 5.3580000 16.0730000 + 688 688 1 0.0000000 5.3580000 5.3580000 21.4310000 + 689 689 1 0.0000000 5.3580000 5.3580000 26.7880000 + 690 690 1 0.0000000 5.3580000 5.3580000 32.1460000 + 691 691 1 0.0000000 5.3580000 10.7150000 5.3580000 + 692 692 1 0.0000000 5.3580000 10.7150000 10.7150000 + 693 693 1 0.0000000 5.3580000 10.7150000 16.0730000 + 694 694 1 0.0000000 5.3580000 10.7150000 21.4310000 + 695 695 1 0.0000000 5.3580000 10.7150000 26.7880000 + 696 696 1 0.0000000 5.3580000 10.7150000 32.1460000 + 697 697 1 0.0000000 5.3580000 16.0730000 5.3580000 + 698 698 1 0.0000000 5.3580000 16.0730000 10.7150000 + 699 699 1 0.0000000 5.3580000 16.0730000 16.0730000 + 700 700 1 0.0000000 5.3580000 16.0730000 21.4310000 + 701 701 1 0.0000000 5.3580000 16.0730000 26.7880000 + 702 702 1 0.0000000 5.3580000 16.0730000 32.1460000 + 703 703 1 0.0000000 5.3580000 21.4310000 5.3580000 + 704 704 1 0.0000000 5.3580000 21.4310000 10.7150000 + 705 705 1 0.0000000 5.3580000 21.4310000 16.0730000 + 706 706 1 0.0000000 5.3580000 21.4310000 21.4310000 + 707 707 1 0.0000000 5.3580000 21.4310000 26.7880000 + 708 708 1 0.0000000 5.3580000 21.4310000 32.1460000 + 709 709 1 0.0000000 5.3580000 26.7880000 5.3580000 + 710 710 1 0.0000000 5.3580000 26.7880000 10.7150000 + 711 711 1 0.0000000 5.3580000 26.7880000 16.0730000 + 712 712 1 0.0000000 5.3580000 26.7880000 21.4310000 + 713 713 1 0.0000000 5.3580000 26.7880000 26.7880000 + 714 714 1 0.0000000 5.3580000 26.7880000 32.1460000 + 715 715 1 0.0000000 5.3580000 32.1460000 5.3580000 + 716 716 1 0.0000000 5.3580000 32.1460000 10.7150000 + 717 717 1 0.0000000 5.3580000 32.1460000 16.0730000 + 718 718 1 0.0000000 5.3580000 32.1460000 21.4310000 + 719 719 1 0.0000000 5.3580000 32.1460000 26.7880000 + 720 720 1 0.0000000 5.3580000 32.1460000 32.1460000 + 721 721 1 0.0000000 10.7150000 5.3580000 5.3580000 + 722 722 1 0.0000000 10.7150000 5.3580000 10.7150000 + 723 723 1 0.0000000 10.7150000 5.3580000 16.0730000 + 724 724 1 0.0000000 10.7150000 5.3580000 21.4310000 + 725 725 1 0.0000000 10.7150000 5.3580000 26.7880000 + 726 726 1 0.0000000 10.7150000 5.3580000 32.1460000 + 727 727 1 0.0000000 10.7150000 10.7150000 5.3580000 + 728 728 1 0.0000000 10.7150000 10.7150000 10.7150000 + 729 729 1 0.0000000 10.7150000 10.7150000 16.0730000 + 730 730 1 0.0000000 10.7150000 10.7150000 21.4310000 + 731 731 1 0.0000000 10.7150000 10.7150000 26.7880000 + 732 732 1 0.0000000 10.7150000 10.7150000 32.1460000 + 733 733 1 0.0000000 10.7150000 16.0730000 5.3580000 + 734 734 1 0.0000000 10.7150000 16.0730000 10.7150000 + 735 735 1 0.0000000 10.7150000 16.0730000 16.0730000 + 736 736 1 0.0000000 10.7150000 16.0730000 21.4310000 + 737 737 1 0.0000000 10.7150000 16.0730000 26.7880000 + 738 738 1 0.0000000 10.7150000 16.0730000 32.1460000 + 739 739 1 0.0000000 10.7150000 21.4310000 5.3580000 + 740 740 1 0.0000000 10.7150000 21.4310000 10.7150000 + 741 741 1 0.0000000 10.7150000 21.4310000 16.0730000 + 742 742 1 0.0000000 10.7150000 21.4310000 21.4310000 + 743 743 1 0.0000000 10.7150000 21.4310000 26.7880000 + 744 744 1 0.0000000 10.7150000 21.4310000 32.1460000 + 745 745 1 0.0000000 10.7150000 26.7880000 5.3580000 + 746 746 1 0.0000000 10.7150000 26.7880000 10.7150000 + 747 747 1 0.0000000 10.7150000 26.7880000 16.0730000 + 748 748 1 0.0000000 10.7150000 26.7880000 21.4310000 + 749 749 1 0.0000000 10.7150000 26.7880000 26.7880000 + 750 750 1 0.0000000 10.7150000 26.7880000 32.1460000 + 751 751 1 0.0000000 10.7150000 32.1460000 5.3580000 + 752 752 1 0.0000000 10.7150000 32.1460000 10.7150000 + 753 753 1 0.0000000 10.7150000 32.1460000 16.0730000 + 754 754 1 0.0000000 10.7150000 32.1460000 21.4310000 + 755 755 1 0.0000000 10.7150000 32.1460000 26.7880000 + 756 756 1 0.0000000 10.7150000 32.1460000 32.1460000 + 757 757 1 0.0000000 16.0730000 5.3580000 5.3580000 + 758 758 1 0.0000000 16.0730000 5.3580000 10.7150000 + 759 759 1 0.0000000 16.0730000 5.3580000 16.0730000 + 760 760 1 0.0000000 16.0730000 5.3580000 21.4310000 + 761 761 1 0.0000000 16.0730000 5.3580000 26.7880000 + 762 762 1 0.0000000 16.0730000 5.3580000 32.1460000 + 763 763 1 0.0000000 16.0730000 10.7150000 5.3580000 + 764 764 1 0.0000000 16.0730000 10.7150000 10.7150000 + 765 765 1 0.0000000 16.0730000 10.7150000 16.0730000 + 766 766 1 0.0000000 16.0730000 10.7150000 21.4310000 + 767 767 1 0.0000000 16.0730000 10.7150000 26.7880000 + 768 768 1 0.0000000 16.0730000 10.7150000 32.1460000 + 769 769 1 0.0000000 16.0730000 16.0730000 5.3580000 + 770 770 1 0.0000000 16.0730000 16.0730000 10.7150000 + 771 771 1 0.0000000 16.0730000 16.0730000 16.0730000 + 772 772 1 0.0000000 16.0730000 16.0730000 21.4310000 + 773 773 1 0.0000000 16.0730000 16.0730000 26.7880000 + 774 774 1 0.0000000 16.0730000 16.0730000 32.1460000 + 775 775 1 0.0000000 16.0730000 21.4310000 5.3580000 + 776 776 1 0.0000000 16.0730000 21.4310000 10.7150000 + 777 777 1 0.0000000 16.0730000 21.4310000 16.0730000 + 778 778 1 0.0000000 16.0730000 21.4310000 21.4310000 + 779 779 1 0.0000000 16.0730000 21.4310000 26.7880000 + 780 780 1 0.0000000 16.0730000 21.4310000 32.1460000 + 781 781 1 0.0000000 16.0730000 26.7880000 5.3580000 + 782 782 1 0.0000000 16.0730000 26.7880000 10.7150000 + 783 783 1 0.0000000 16.0730000 26.7880000 16.0730000 + 784 784 1 0.0000000 16.0730000 26.7880000 21.4310000 + 785 785 1 0.0000000 16.0730000 26.7880000 26.7880000 + 786 786 1 0.0000000 16.0730000 26.7880000 32.1460000 + 787 787 1 0.0000000 16.0730000 32.1460000 5.3580000 + 788 788 1 0.0000000 16.0730000 32.1460000 10.7150000 + 789 789 1 0.0000000 16.0730000 32.1460000 16.0730000 + 790 790 1 0.0000000 16.0730000 32.1460000 21.4310000 + 791 791 1 0.0000000 16.0730000 32.1460000 26.7880000 + 792 792 1 0.0000000 16.0730000 32.1460000 32.1460000 + 793 793 1 0.0000000 21.4310000 5.3580000 5.3580000 + 794 794 1 0.0000000 21.4310000 5.3580000 10.7150000 + 795 795 1 0.0000000 21.4310000 5.3580000 16.0730000 + 796 796 1 0.0000000 21.4310000 5.3580000 21.4310000 + 797 797 1 0.0000000 21.4310000 5.3580000 26.7880000 + 798 798 1 0.0000000 21.4310000 5.3580000 32.1460000 + 799 799 1 0.0000000 21.4310000 10.7150000 5.3580000 + 800 800 1 0.0000000 21.4310000 10.7150000 10.7150000 + 801 801 1 0.0000000 21.4310000 10.7150000 16.0730000 + 802 802 1 0.0000000 21.4310000 10.7150000 21.4310000 + 803 803 1 0.0000000 21.4310000 10.7150000 26.7880000 + 804 804 1 0.0000000 21.4310000 10.7150000 32.1460000 + 805 805 1 0.0000000 21.4310000 16.0730000 5.3580000 + 806 806 1 0.0000000 21.4310000 16.0730000 10.7150000 + 807 807 1 0.0000000 21.4310000 16.0730000 16.0730000 + 808 808 1 0.0000000 21.4310000 16.0730000 21.4310000 + 809 809 1 0.0000000 21.4310000 16.0730000 26.7880000 + 810 810 1 0.0000000 21.4310000 16.0730000 32.1460000 + 811 811 1 0.0000000 21.4310000 21.4310000 5.3580000 + 812 812 1 0.0000000 21.4310000 21.4310000 10.7150000 + 813 813 1 0.0000000 21.4310000 21.4310000 16.0730000 + 814 814 1 0.0000000 21.4310000 21.4310000 21.4310000 + 815 815 1 0.0000000 21.4310000 21.4310000 26.7880000 + 816 816 1 0.0000000 21.4310000 21.4310000 32.1460000 + 817 817 1 0.0000000 21.4310000 26.7880000 5.3580000 + 818 818 1 0.0000000 21.4310000 26.7880000 10.7150000 + 819 819 1 0.0000000 21.4310000 26.7880000 16.0730000 + 820 820 1 0.0000000 21.4310000 26.7880000 21.4310000 + 821 821 1 0.0000000 21.4310000 26.7880000 26.7880000 + 822 822 1 0.0000000 21.4310000 26.7880000 32.1460000 + 823 823 1 0.0000000 21.4310000 32.1460000 5.3580000 + 824 824 1 0.0000000 21.4310000 32.1460000 10.7150000 + 825 825 1 0.0000000 21.4310000 32.1460000 16.0730000 + 826 826 1 0.0000000 21.4310000 32.1460000 21.4310000 + 827 827 1 0.0000000 21.4310000 32.1460000 26.7880000 + 828 828 1 0.0000000 21.4310000 32.1460000 32.1460000 + 829 829 1 0.0000000 26.7880000 5.3580000 5.3580000 + 830 830 1 0.0000000 26.7880000 5.3580000 10.7150000 + 831 831 1 0.0000000 26.7880000 5.3580000 16.0730000 + 832 832 1 0.0000000 26.7880000 5.3580000 21.4310000 + 833 833 1 0.0000000 26.7880000 5.3580000 26.7880000 + 834 834 1 0.0000000 26.7880000 5.3580000 32.1460000 + 835 835 1 0.0000000 26.7880000 10.7150000 5.3580000 + 836 836 1 0.0000000 26.7880000 10.7150000 10.7150000 + 837 837 1 0.0000000 26.7880000 10.7150000 16.0730000 + 838 838 1 0.0000000 26.7880000 10.7150000 21.4310000 + 839 839 1 0.0000000 26.7880000 10.7150000 26.7880000 + 840 840 1 0.0000000 26.7880000 10.7150000 32.1460000 + 841 841 1 0.0000000 26.7880000 16.0730000 5.3580000 + 842 842 1 0.0000000 26.7880000 16.0730000 10.7150000 + 843 843 1 0.0000000 26.7880000 16.0730000 16.0730000 + 844 844 1 0.0000000 26.7880000 16.0730000 21.4310000 + 845 845 1 0.0000000 26.7880000 16.0730000 26.7880000 + 846 846 1 0.0000000 26.7880000 16.0730000 32.1460000 + 847 847 1 0.0000000 26.7880000 21.4310000 5.3580000 + 848 848 1 0.0000000 26.7880000 21.4310000 10.7150000 + 849 849 1 0.0000000 26.7880000 21.4310000 16.0730000 + 850 850 1 0.0000000 26.7880000 21.4310000 21.4310000 + 851 851 1 0.0000000 26.7880000 21.4310000 26.7880000 + 852 852 1 0.0000000 26.7880000 21.4310000 32.1460000 + 853 853 1 0.0000000 26.7880000 26.7880000 5.3580000 + 854 854 1 0.0000000 26.7880000 26.7880000 10.7150000 + 855 855 1 0.0000000 26.7880000 26.7880000 16.0730000 + 856 856 1 0.0000000 26.7880000 26.7880000 21.4310000 + 857 857 1 0.0000000 26.7880000 26.7880000 26.7880000 + 858 858 1 0.0000000 26.7880000 26.7880000 32.1460000 + 859 859 1 0.0000000 26.7880000 32.1460000 5.3580000 + 860 860 1 0.0000000 26.7880000 32.1460000 10.7150000 + 861 861 1 0.0000000 26.7880000 32.1460000 16.0730000 + 862 862 1 0.0000000 26.7880000 32.1460000 21.4310000 + 863 863 1 0.0000000 26.7880000 32.1460000 26.7880000 + 864 864 1 0.0000000 26.7880000 32.1460000 32.1460000 + diff --git a/examples/python/gjf_python/ff-argon.lmp b/examples/python/gjf_python/ff-argon.lmp new file mode 100644 index 0000000000..b6f7bc931a --- /dev/null +++ b/examples/python/gjf_python/ff-argon.lmp @@ -0,0 +1,20 @@ +############################# +#Atoms types - mass - charge# +############################# +#@ 1 atom types #!THIS LINE IS NECESSARY DON'T SPEND HOURS FINDING THAT OUT!# + +variable Ar equal 1 + +############# +#Atom Masses# +############# + +mass ${Ar} 39.903 + +########################### +#Pair Potentials - Tersoff# +########################### + +pair_style lj/cubic +pair_coeff * * 0.0102701 3.42 + diff --git a/examples/python/gjf_python/gjf.py b/examples/python/gjf_python/gjf.py new file mode 100644 index 0000000000..37fc28bb79 --- /dev/null +++ b/examples/python/gjf_python/gjf.py @@ -0,0 +1,180 @@ +"""Made by Charlie Sievers Ph.D. Candidate, UC Davis, Donadio Lab 2019""" + +from mpi4py import MPI +from lammps import lammps +import lammps_tools as lt +import numpy as np + +comm = MPI.COMM_WORLD +rank = comm.Get_rank() + +""" LAMMPS VARIABLES """ + +# new file or restart +run_no = 0 + +# data files +infile = "argon.lmp" +restart_file = "final_restart.{}".format(run_no) +ff_file = "ff-argon.lmp" +outfile = "output.dat" + +# write final_restart +write_final_restart = False + +# random numbers +seed0 = 2357 +seed1 = 26588 +seed2 = 10669 + +# MD Parameters +# number of steps +nsteps = 50000 +# timestep +# dt = 0.001 +# starting simulation temp +temp_start = 10 +# final simulation temp +temp_final = 10 +# relaxation time +trel = 1 +# trajectory frequency +ntraj = 0 + +# Ensemble 0 = GJF u, 1 = GJF v, 2 = Nose-Hoover, 3 = Langevin, 4 = BDP (Currently all NVT) +ensemble = 0 + +# Output Parameters +nthermo = 200 +nout = int(nsteps / nthermo) # Important + +# output to screen and log file? +lammps_output = False +# Lammps Thermo +thermo = False + +python_output = True + +# Write output to file? +write_output = False + +if write_output is True: + data = open("{}".format(outfile), "w") + +if python_output is True: + if rank == 0: + print("dt, temp, ke, fke, pe, fpe") + +for j in range(20): + + # timestep + dt = 0.005*(j+1) + + if lammps_output is True: + lmp = lammps() + else: + lmp = lammps(cmdargs=["-screen", "none", "-log", "none"]) + + lmp.command("atom_style full") + lmp.command("units metal") + lmp.command("processors * * *") + lmp.command("neighbor 1 bin") + lmp.command("boundary p p p") + + if run_no is 0: + lmp.command("read_data {}".format(infile)) + else: + lmp.command("read_restart final_restart".format(run_no-1)) + + if thermo is True: + lmp.command("thermo_style custom time temp pe ke press vol cpu") + lmp.command("thermo {}".format(nthermo)) + lmp.command("thermo_modify flush yes") + + lmp.file("{}".format(ff_file)) + lmp.command("timestep {}".format(dt)) + + # get_per_atom_compute example with dim of two and within a group + # lmp.command("region rand block 5 20 5 20 5 20") + # lmp.command("group rand region rand") + # lmp.command("compute x rand property/atom x y") + # test = get_per_atom_compute(comm, lmp, "x", 2, group="rand") + + lmp.command("compute ke all ke/atom") + + lmp.command("compute pe all pe") + + if ntraj != 0: + lmp.command("dump 1 all dcd {} trajectory.dcd".format(ntraj)) + lmp.command("dump_modify 1 unwrap yes") + + if run_no == 0: + lmp.command("velocity all create {} {} mom yes dist gaussian".format(temp_start, seed0)) + lmp.command("fix nve all nve") + + if ensemble == 0: + # gjf u + lmp.command("fix lang all langevin {} {} {} {} gjf yes halfstep yes".format( + temp_start, temp_final, trel, seed1)) + elif ensemble == 1: + # gjf v + lmp.command("fix lang all langevin {} {} {} {} gjf yes".format( + temp_start, temp_final, trel, seed1)) + elif ensemble == 2: + # NH + lmp.command("fix nvt all nvt temp {} {} {}".format( + temp_start, temp_final, trel)) + elif ensemble == 3: + # lang + lmp.command("fix lang all langevin {} {} {} {} tally yes zero yes".format( + temp_start, temp_final, trel, seed1)) + elif ensemble == 4: + # BDP + lmp.command("fix stoch all temp/csvr {} {} {} {}".format( + temp_start, temp_final, trel, seed1)) + + natoms = lmp.extract_global("natoms", 0) + nlocal = lmp.extract_global("nlocal", 0) + ke_sum = lt.get_per_atom_compute(comm, lmp, "ke") + ke_2 = ke_sum**2 + pe_sum = 0 + pe_2 = 0 + temp_sum = 0 + + for i in range(nout): + nlocal = lmp.extract_global("nlocal", 0) + lmp.command("run {} pre no post no".format(nthermo)) + temp = lmp.extract_compute("thermo_temp", 0, 0) + ke = lt.get_per_atom_compute(comm, lmp, "ke") + pe = lmp.extract_compute("pe", 0, 0) + ke_sum += ke + ke_2 += ke**2 + pe_sum += pe + pe_2 += pe**2 + temp_sum += temp + + if python_output is True: + if rank == 0: + print("Time: {:.6f}, Temp: {:.6f}, KE: {:.6f}, PE: {:.6f}".format( + i*nthermo*dt, temp, ke.sum(), pe)) + + if write_final_restart is True: + lmp.command("write_restart {}".format(restart_file)) + + if rank == 0: + ke = ke_sum.sum() / (nout + 1) + fke = (np.sqrt((ke_2 - ke_sum ** 2 / (nout + 1)) / (nout + 1))).sum() + pe = pe_sum / nout + fpe = np.sqrt((pe_2 - pe_sum ** 2 / nout) / nout) + temp = temp_sum / nout + + if python_output is True: + print(dt, temp, ke, fke, pe, fpe) + + if write_output is True: + data.write("{:.6f} {:.6f} {:.6f} {:.6f} {:.6f} {:.6f}\n".format( + dt, temp, ke, fke, pe, fpe)) + data.flush() + +if write_output is True: + data.close() diff --git a/examples/python/gjf_python/lammps_tools.py b/examples/python/gjf_python/lammps_tools.py new file mode 100644 index 0000000000..f9f25eaa28 --- /dev/null +++ b/examples/python/gjf_python/lammps_tools.py @@ -0,0 +1,78 @@ +"""Made by Charlie Sievers Ph.D. Candidate, UC Davis, Donadio Lab 2019""" + +from mpi4py import MPI +import numpy as np +import ctypes as ctypes + +""" USEFULL LAMMPS FUNCTION """ + + +def get_nlocal(lmp): + + nlocal = lmp.extract_global("nlocal", 0) + + return nlocal + + +def get_aid(lmp, group=None): + + if group is None: + c_aid = lmp.extract_atom("id", 0) + ptr = ctypes.cast(c_aid, ctypes.POINTER(ctypes.c_int32 * get_nlocal(lmp))) + aid = np.frombuffer(ptr.contents, dtype=np.int32) + else: + try: + c_aid = lmp.extract_variable("aid", group, 1) + ptr = ctypes.cast(c_aid, ctypes.POINTER(ctypes.c_double * get_nlocal(lmp))) + aid = np.frombuffer(ptr.contents, dtype=np.double) + except ValueError: + lmp.command("variable aid atom id") + aid = get_aid(lmp, group) + + return aid + + +def get_per_atom_compute(comm, lmp, name, dim=1, dtype="double", group=None): + laid = get_aid(lmp, group) + nlocal = get_nlocal(lmp) + ngroup = comm.allgather(laid) + type = dim + if dim > 1: + type = 2 + for array in ngroup: + try: + aid = np.concatenate((aid, array)) + except UnboundLocalError: + aid = array + if dtype == "double": + mem_type = ctypes.c_double + elif dtype == "integer": + mem_type = ctypes.c_int + elif dtype == "bigint": + mem_type = ctypes.c_int32 + else: + print("{} not implemented".format(dtype)) + return + + tmp = lmp.extract_compute(name, 1, type) + if type == 1: + ptr = ctypes.cast(tmp, ctypes.POINTER(mem_type * nlocal)) + else: + ptr = ctypes.cast(tmp[0], ctypes.POINTER(mem_type * nlocal * dim)) + lcompute = comm.allgather(np.frombuffer(ptr.contents).reshape((-1, dim))) + for array in lcompute: + try: + compute = np.concatenate((compute, array)) + except UnboundLocalError: + compute = array + + aid = np.expand_dims(aid, axis=1) + + compute = np.concatenate((aid, compute), axis=-1) + compute = compute[compute[..., 0] != 0] + compute = compute[compute[..., 0].argsort()][..., 1:] + + if dim == 1: + compute = np.squeeze(compute, axis=-1) + + return compute \ No newline at end of file From e517a16bdae1b1b3b1064b39f9a663d5900faff6 Mon Sep 17 00:00:00 2001 From: casievers Date: Fri, 19 Jul 2019 17:21:01 -0700 Subject: [PATCH 048/192] updated gjf in fix_langevin --- src/fix_langevin.cpp | 39 +++++++++++---------------------------- src/fix_langevin.h | 2 +- 2 files changed, 12 insertions(+), 29 deletions(-) diff --git a/src/fix_langevin.cpp b/src/fix_langevin.cpp index 5058d5c650..840861ef91 100644 --- a/src/fix_langevin.cpp +++ b/src/fix_langevin.cpp @@ -174,11 +174,11 @@ FixLangevin::FixLangevin(LAMMPS *lmp, int narg, char **arg) : // no need to set peratom_flag, b/c data is for internal use only if (gjfflag) { - int mem = 6*atom->nmax*sizeof(double); - if (hsflag) mem += 3*atom->nmax*sizeof(double); - - comm->maxexchange_fix = MAX(comm->maxexchange_fix, 0); - comm->maxexchange_fix += MAX(1000, mem); + //int mem = 6*atom->nmax*sizeof(double); + //if (hsflag) mem += 3*atom->nmax*sizeof(double); +// + //comm->maxexchange_fix = MAX(comm->maxexchange_fix, 0); + //comm->maxexchange_fix += MAX(1000, mem); nvalues = 3; grow_arrays(atom->nmax); @@ -232,7 +232,6 @@ FixLangevin::~FixLangevin() int FixLangevin::setmask() { int mask = 0; - //if (gjfflag) mask |= INITIAL_INTEGRATE; if (gjfflag) mask |= POST_INTEGRATE; mask |= POST_FORCE; mask |= POST_FORCE_RESPA; @@ -321,35 +320,19 @@ void FixLangevin::setup(int vflag) post_force_respa(vflag,nlevels_respa-1,0); ((Respa *) update->integrate)->copy_f_flevel(nlevels_respa-1); } - if (gjfflag && hsflag) { + if (gjfflag) { - double dt = update->dt; // update v of atoms in group - - double **v = atom->v; - double *rmass = atom->rmass; - int *type = atom->type; + double ** v = atom->v; + double **f = atom->f; int nlocal = atom->nlocal; if (igroup == atom->firstgroup) nlocal = atom->nfirst; - double boltz = force->boltz; - double mvv2e = force->mvv2e; - double ftm2v = force->ftm2v; - - double gamma2; - for (int i = 0; i < nlocal; i++) { - if (rmass) { - gamma2 = sqrt(rmass[i]) * sqrt(2.0*boltz/t_period/dt/mvv2e) / ftm2v; - gamma2 *= 1.0/sqrt(ratio[type[i]]) * tsqrt; - } else { - gamma2 = gfactor2[type[i]] * tsqrt; - } - - franprev[i][0] = gamma2*random->gaussian(); - franprev[i][1] = gamma2*random->gaussian(); - franprev[i][2] = gamma2*random->gaussian(); + f[i][0] = wildcard[i][0]; + f[i][1] = wildcard[i][1]; + f[i][2] = wildcard[i][2]; wildcard[i][0] = v[i][0]; wildcard[i][1] = v[i][1]; wildcard[i][2] = v[i][2]; diff --git a/src/fix_langevin.h b/src/fix_langevin.h index 70fb254f4e..91ed210e54 100644 --- a/src/fix_langevin.h +++ b/src/fix_langevin.h @@ -65,7 +65,7 @@ class FixLangevin : public Fix { double **flangevin; double *tforce; double **franprev; - double **lv; //lucas velocity or half-step velocity + double **lv; //2GJ velocity or half-step velocity double **wildcard; int nvalues; From 473e64c6b6d2c2ac86db5672075febd12af4385c Mon Sep 17 00:00:00 2001 From: alxvov Date: Mon, 22 Jul 2019 13:49:41 +0000 Subject: [PATCH 049/192] actual gradient of energy, not scaled by hbar. convergence criterion is in eV --- src/SPIN/min_spin_oso_lbfgs.cpp | 10 ++++------ 1 file changed, 4 insertions(+), 6 deletions(-) diff --git a/src/SPIN/min_spin_oso_lbfgs.cpp b/src/SPIN/min_spin_oso_lbfgs.cpp index 8d05ea63d8..d7e7302e4f 100644 --- a/src/SPIN/min_spin_oso_lbfgs.cpp +++ b/src/SPIN/min_spin_oso_lbfgs.cpp @@ -313,16 +313,14 @@ void MinSpinOSO_LBFGS::calc_gradient() int nlocal = atom->nlocal; double **sp = atom->sp; double **fm = atom->fm; + double hbar = force->hplanck/MY_2PI; // loop on all spins on proc. for (int i = 0; i < nlocal; i++) { - - // calculate gradients - - g_cur[3 * i + 0] = (fm[i][0]*sp[i][1] - fm[i][1]*sp[i][0]); - g_cur[3 * i + 1] = -(fm[i][2]*sp[i][0] - fm[i][0]*sp[i][2]); - g_cur[3 * i + 2] = (fm[i][1]*sp[i][2] - fm[i][2]*sp[i][1]); + g_cur[3 * i + 0] = (fm[i][0]*sp[i][1] - fm[i][1]*sp[i][0]) * hbar; + g_cur[3 * i + 1] = -(fm[i][2]*sp[i][0] - fm[i][0]*sp[i][2]) * hbar; + g_cur[3 * i + 2] = (fm[i][1]*sp[i][2] - fm[i][2]*sp[i][1]) * hbar; } } From e4001b01791e9ac1caa54d0c5962886f566afa18 Mon Sep 17 00:00:00 2001 From: alxvov Date: Mon, 22 Jul 2019 14:38:02 +0000 Subject: [PATCH 050/192] change convergence criterion --- src/SPIN/min_spin_oso_cg.cpp | 49 +++++++++++++++++++----------------- src/SPIN/min_spin_oso_cg.h | 10 ++++---- 2 files changed, 31 insertions(+), 28 deletions(-) diff --git a/src/SPIN/min_spin_oso_cg.cpp b/src/SPIN/min_spin_oso_cg.cpp index d8535b19c4..fe52ddebe1 100644 --- a/src/SPIN/min_spin_oso_cg.cpp +++ b/src/SPIN/min_spin_oso_cg.cpp @@ -66,6 +66,8 @@ MinSpinOSO_CG::MinSpinOSO_CG(LAMMPS *lmp) : { if (lmp->citeme) lmp->citeme->add(cite_minstyle_spin_oso_cg); nlocal_max = 0; + alpha_damp = 1.0; + discrete_factor = 10.0; } /* ---------------------------------------------------------------------- */ @@ -81,11 +83,9 @@ MinSpinOSO_CG::~MinSpinOSO_CG() void MinSpinOSO_CG::init() { - alpha_damp = 1.0; - discrete_factor = 10.0; + local_iter = 0; Min::init(); - dts = dt = update->dt; last_negative = update->ntimestep; @@ -216,7 +216,7 @@ int MinSpinOSO_CG::iterate(int maxiter) // sync across replicas if running multi-replica minimization if (update->ftol > 0.0) { - fmdotfm = fmnorm_sqr(); + fmdotfm = max_torque(); if (update->multireplica == 0) { if (fmdotfm < update->ftol*update->ftol) return FTOL; } else { @@ -393,38 +393,41 @@ void MinSpinOSO_CG::advance_spins() } /* ---------------------------------------------------------------------- - compute and return ||mag. torque||_2^2 + compute and return max_i||mag. torque_i||_2 ------------------------------------------------------------------------- */ -double MinSpinOSO_CG::fmnorm_sqr() +double MinSpinOSO_CG::max_torque() { + double fmsq,fmaxsqone,fmaxsqloc,fmaxsqall; int nlocal = atom->nlocal; - double tx,ty,tz; - double **sp = atom->sp; - double **fm = atom->fm; + double hbar = force->hplanck/MY_2PI; - // calc. magnetic torques + // finding max fm on this proc. - double local_norm2_sqr = 0.0; + fmsq = fmaxsqone = fmaxsqloc = fmaxsqall = 0.0; for (int i = 0; i < nlocal; i++) { - tx = (fm[i][1]*sp[i][2] - fm[i][2]*sp[i][1]); - ty = (fm[i][2]*sp[i][0] - fm[i][0]*sp[i][2]); - tz = (fm[i][0]*sp[i][1] - fm[i][1]*sp[i][0]); - - local_norm2_sqr += tx*tx + ty*ty + tz*tz; + fmsq = 0.0; + for (int j = 0; j < 3; j++) + fmsq += g_cur[3 * i + j] * g_cur[3 * i + j]; + fmaxsqone = MAX(fmaxsqone,fmsq); } - // no extra atom calc. for spins + // finding max fm on this replica - if (nextra_atom) - error->all(FLERR,"extra atom option not available yet"); + fmaxsqloc = fmaxsqone; + MPI_Allreduce(&fmaxsqone,&fmaxsqloc,1,MPI_DOUBLE,MPI_MAX,world); - double norm2_sqr = 0.0; - MPI_Allreduce(&local_norm2_sqr,&norm2_sqr,1,MPI_DOUBLE,MPI_SUM,world); + // finding max fm over all replicas, if necessary + // this communicator would be invalid for multiprocess replicas - return norm2_sqr; + fmaxsqall = fmaxsqloc; + if (update->multireplica == 1) { + fmaxsqall = fmaxsqloc; + MPI_Allreduce(&fmaxsqloc,&fmaxsqall,1,MPI_DOUBLE,MPI_MAX,universe->uworld); + } + + return sqrt(fmaxsqall) * hbar; } - /* ---------------------------------------------------------------------- calculate 3x3 matrix exponential using Rodrigues' formula (R. Murray, Z. Li, and S. Shankar Sastry, diff --git a/src/SPIN/min_spin_oso_cg.h b/src/SPIN/min_spin_oso_cg.h index 3a3d24f078..81bbd2c294 100644 --- a/src/SPIN/min_spin_oso_cg.h +++ b/src/SPIN/min_spin_oso_cg.h @@ -25,8 +25,7 @@ MinimizeStyle(spin/oso_cg, MinSpinOSO_CG) namespace LAMMPS_NS { class MinSpinOSO_CG : public Min { - -public: + public: MinSpinOSO_CG(class LAMMPS *); virtual ~MinSpinOSO_CG(); void init(); @@ -34,18 +33,19 @@ public: int modify_param(int, char **); void reset_vectors(); int iterate(int); + + private: double evaluate_dt(); void advance_spins(); - double fmnorm_sqr(); + double max_torque(); void calc_gradient(double); void calc_search_direction(); -private: // global and spin timesteps - int nlocal_max; // max value of nlocal (for size of lists) double dt; double dts; + int nlocal_max; // max value of nlocal (for size of lists) double alpha_damp; // damping for spin minimization double discrete_factor; // factor for spin timestep evaluation From fabe611c110b1366088369b9e8c5eb56f50aaf04 Mon Sep 17 00:00:00 2001 From: alxvov Date: Mon, 22 Jul 2019 17:26:47 +0000 Subject: [PATCH 051/192] use line search or adaptive time step --- src/SPIN/min_spin_oso_cg.cpp | 3 +- src/SPIN/min_spin_oso_cg2.cpp | 98 ++++++++++++++++++++--------------- src/SPIN/min_spin_oso_cg2.h | 4 ++ 3 files changed, 62 insertions(+), 43 deletions(-) diff --git a/src/SPIN/min_spin_oso_cg.cpp b/src/SPIN/min_spin_oso_cg.cpp index fe52ddebe1..8eb358f86a 100644 --- a/src/SPIN/min_spin_oso_cg.cpp +++ b/src/SPIN/min_spin_oso_cg.cpp @@ -151,7 +151,7 @@ void MinSpinOSO_CG::reset_vectors() } /* ---------------------------------------------------------------------- - minimization via damped spin dynamics + minimization via orthogonal spin optimisation ------------------------------------------------------------------------- */ int MinSpinOSO_CG::iterate(int maxiter) @@ -428,6 +428,7 @@ double MinSpinOSO_CG::max_torque() return sqrt(fmaxsqall) * hbar; } + /* ---------------------------------------------------------------------- calculate 3x3 matrix exponential using Rodrigues' formula (R. Murray, Z. Li, and S. Shankar Sastry, diff --git a/src/SPIN/min_spin_oso_cg2.cpp b/src/SPIN/min_spin_oso_cg2.cpp index 23873e24f2..52b98eead7 100644 --- a/src/SPIN/min_spin_oso_cg2.cpp +++ b/src/SPIN/min_spin_oso_cg2.cpp @@ -75,7 +75,7 @@ MinSpinOSO_CG2::MinSpinOSO_CG2(LAMMPS *lmp) : nreplica = universe->nworlds; ireplica = universe->iworld; use_line_search = 1; - maxepsrot = MY_2PI / (100.0); + discrete_factor = 10.0; } @@ -100,6 +100,7 @@ void MinSpinOSO_CG2::init() Min::init(); + dts = dt = update->dt; last_negative = update->ntimestep; // allocate tables @@ -140,9 +141,7 @@ int MinSpinOSO_CG2::modify_param(int narg, char **arg) } if (strcmp(arg[0],"discrete_factor") == 0) { if (narg < 2) error->all(FLERR,"Illegal fix_modify command"); - double discrete_factor; discrete_factor = force->numeric(FLERR,arg[1]); - maxepsrot = MY_2PI / discrete_factor; return 2; } return 0; @@ -169,7 +168,7 @@ void MinSpinOSO_CG2::reset_vectors() } /* ---------------------------------------------------------------------- - minimization via damped spin dynamics + minimization via orthogonal spin optimisation ------------------------------------------------------------------------- */ int MinSpinOSO_CG2::iterate(int maxiter) @@ -305,20 +304,21 @@ void MinSpinOSO_CG2::calc_gradient() double **sp = atom->sp; double **fm = atom->fm; double hbar = force->hplanck/MY_2PI; + double factor; + + if (use_line_search) + factor = hbar; + else factor = evaluate_dt(); // loop on all spins on proc. for (int i = 0; i < nlocal; i++) { - - // calculate gradients - - g_cur[3 * i + 0] = (fm[i][0]*sp[i][1] - fm[i][1]*sp[i][0]) * hbar; - g_cur[3 * i + 1] = -(fm[i][2]*sp[i][0] - fm[i][0]*sp[i][2]) * hbar; - g_cur[3 * i + 2] = (fm[i][1]*sp[i][2] - fm[i][2]*sp[i][1]) * hbar; + g_cur[3 * i + 0] = (fm[i][0]*sp[i][1] - fm[i][1]*sp[i][0]) * factor; + g_cur[3 * i + 1] = -(fm[i][2]*sp[i][0] - fm[i][0]*sp[i][2]) * factor; + g_cur[3 * i + 2] = (fm[i][1]*sp[i][2] - fm[i][2]*sp[i][1]) * factor; } } - /* ---------------------------------------------------------------------- search direction: The Fletcher-Reeves conj. grad. method @@ -335,14 +335,10 @@ void MinSpinOSO_CG2::calc_search_direction() double g2_global = 0.0; double g2old_global = 0.0; - double scaling = 1.0; - - if (use_line_search == 0) - scaling = maximum_rotation(g_cur); if (local_iter == 0 || local_iter % 5 == 0){ // steepest descent direction for (int i = 0; i < 3 * nlocal; i++) { - p_s[i] = -g_cur[i] * scaling; + p_s[i] = -g_cur[i]; g_old[i] = g_cur[i]; } } else { // conjugate direction @@ -352,11 +348,10 @@ void MinSpinOSO_CG2::calc_search_direction() } // now we need to collect/broadcast beta on this replica - // different replica can have different beta for now. // need to check what is beta for GNEB - MPI_Allreduce(&g2, &g2_global, 1, MPI_DOUBLE, MPI_SUM, world); - MPI_Allreduce(&g2old, &g2old_global, 1, MPI_DOUBLE, MPI_SUM, world); + MPI_Allreduce(&g2,&g2_global,1,MPI_DOUBLE,MPI_SUM,world); + MPI_Allreduce(&g2old,&g2old_global,1,MPI_DOUBLE,MPI_SUM,world); // Sum over all replicas. Good for GNEB. if (update->multireplica == 1) { @@ -365,12 +360,11 @@ void MinSpinOSO_CG2::calc_search_direction() MPI_Allreduce(&g2,&g2_global,1,MPI_DOUBLE,MPI_SUM,universe->uworld); MPI_Allreduce(&g2old,&g2old_global,1,MPI_DOUBLE,MPI_SUM,universe->uworld); } - if (fabs(g2_global) < 1.0e-60) beta = 0.0; else beta = g2_global / g2old_global; // calculate conjugate direction for (int i = 0; i < 3 * nlocal; i++) { - p_s[i] = (beta * p_s[i] - g_cur[i])*scaling; + p_s[i] = (beta * p_s[i] - g_cur[i]); g_old[i] = g_cur[i]; } } @@ -411,6 +405,11 @@ double MinSpinOSO_CG2::max_torque() { double fmsq,fmaxsqone,fmaxsqloc,fmaxsqall; int nlocal = atom->nlocal; + double factor; + double hbar = force->hplanck/MY_2PI; + + if (use_line_search) factor = 1.0; + else factor = hbar; // finding max fm on this proc. @@ -436,7 +435,7 @@ double MinSpinOSO_CG2::max_torque() MPI_Allreduce(&fmaxsqloc,&fmaxsqall,1,MPI_DOUBLE,MPI_MAX,universe->uworld); } - return sqrt(fmaxsqall); + return sqrt(fmaxsqall) * factor; } /* ---------------------------------------------------------------------- @@ -607,8 +606,6 @@ int MinSpinOSO_CG2::calc_and_make_step(double a, double b, int index) if (alpha < 0.0) alpha = r/2.0; - std::cout << alpha << "\n"; - for (int i = 0; i < nlocal; i++) { for (int j = 0; j < 3; j++) sp[i][j] = sp_copy[i][j]; } @@ -636,30 +633,47 @@ int MinSpinOSO_CG2::awc(double der_phi_0, double phi_0, double der_phi_j, double return 0; } -double MinSpinOSO_CG2::maximum_rotation(double *p) +/* ---------------------------------------------------------------------- + evaluate max timestep +---------------------------------------------------------------------- */ + +double MinSpinOSO_CG2::evaluate_dt() { - double norm2,norm2_global,scaling,alpha; + double dtmax; + double fmsq; + double fmaxsqone,fmaxsqloc,fmaxsqall; int nlocal = atom->nlocal; - int ntotal = 0; + double **fm = atom->fm; - norm2 = 0.0; - for (int i = 0; i < 3 * nlocal; i++) norm2 += p[i] * p[i]; + // finding max fm on this proc. - MPI_Allreduce(&norm2,&norm2_global,1,MPI_DOUBLE,MPI_SUM,world); - if (update->multireplica == 1) { - norm2 = norm2_global; - MPI_Allreduce(&norm2,&norm2_global,1,MPI_DOUBLE,MPI_SUM,universe->uworld); - } - MPI_Allreduce(&nlocal,&ntotal,1,MPI_INT,MPI_SUM,world); - if (update->multireplica == 1) { - nlocal = ntotal; - MPI_Allreduce(&nlocal,&ntotal,1,MPI_INT,MPI_SUM,universe->uworld); + fmsq = fmaxsqone = fmaxsqloc = fmaxsqall = 0.0; + for (int i = 0; i < nlocal; i++) { + fmsq = fm[i][0]*fm[i][0]+fm[i][1]*fm[i][1]+fm[i][2]*fm[i][2]; + fmaxsqone = MAX(fmaxsqone,fmsq); } - scaling = (maxepsrot * sqrt((double) ntotal / norm2_global)); + // finding max fm on this replica - if (scaling < 1.0) alpha = scaling; - else alpha = 1.0; + fmaxsqloc = fmaxsqone; + MPI_Allreduce(&fmaxsqone,&fmaxsqloc,1,MPI_DOUBLE,MPI_MAX,world); - return alpha; + // finding max fm over all replicas, if necessary + // this communicator would be invalid for multiprocess replicas + + fmaxsqall = fmaxsqloc; + if (update->multireplica == 1) { + fmaxsqall = fmaxsqloc; + MPI_Allreduce(&fmaxsqloc,&fmaxsqall,1,MPI_DOUBLE,MPI_MAX,universe->uworld); + } + + if (fmaxsqall == 0.0) + error->all(FLERR,"Incorrect fmaxsqall calculation"); + + // define max timestep by dividing by the + // inverse of max frequency by discrete_factor + + dtmax = MY_2PI/(discrete_factor*sqrt(fmaxsqall)); + + return dtmax; } \ No newline at end of file diff --git a/src/SPIN/min_spin_oso_cg2.h b/src/SPIN/min_spin_oso_cg2.h index c96e82ca8e..83605f98ed 100644 --- a/src/SPIN/min_spin_oso_cg2.h +++ b/src/SPIN/min_spin_oso_cg2.h @@ -34,6 +34,8 @@ class MinSpinOSO_CG2: public Min { void reset_vectors(); int iterate(int); private: + double dt; // global timestep + double dts; // spin timestep int ireplica,nreplica; // for neb double *spvec; // variables for atomic dof, as 1d vector double *fmvec; // variables for atomic dof, as 1d vector @@ -43,7 +45,9 @@ class MinSpinOSO_CG2: public Min { double **sp_copy; // copy of the spins int local_iter; // for neb int nlocal_max; // max value of nlocal (for size of lists) + double discrete_factor; // factor for spin timestep evaluation + double evaluate_dt(); void advance_spins(); void calc_gradient(); void calc_search_direction(); From 31d2b23f9c8de272051beac63261278bcd6bf411 Mon Sep 17 00:00:00 2001 From: alxvov Date: Mon, 22 Jul 2019 17:53:02 +0000 Subject: [PATCH 052/192] rename cg2 -> cg --- src/SPIN/min_spin_oso_cg.cpp | 660 ++++++++++++++++++++------------- src/SPIN/min_spin_oso_cg.h | 43 +-- src/SPIN/min_spin_oso_cg2.cpp | 679 ---------------------------------- src/SPIN/min_spin_oso_cg2.h | 72 ---- 4 files changed, 435 insertions(+), 1019 deletions(-) delete mode 100644 src/SPIN/min_spin_oso_cg2.cpp delete mode 100644 src/SPIN/min_spin_oso_cg2.h diff --git a/src/SPIN/min_spin_oso_cg.cpp b/src/SPIN/min_spin_oso_cg.cpp index 8eb358f86a..c9f3a59f87 100644 --- a/src/SPIN/min_spin_oso_cg.cpp +++ b/src/SPIN/min_spin_oso_cg.cpp @@ -38,6 +38,7 @@ #include "modify.h" #include "math_special.h" #include "math_const.h" +#include "universe.h" using namespace LAMMPS_NS; using namespace MathConst; @@ -61,12 +62,18 @@ static const char cite_minstyle_spin_oso_cg[] = /* ---------------------------------------------------------------------- */ -MinSpinOSO_CG::MinSpinOSO_CG(LAMMPS *lmp) : +MinSpinOSO_CG::MinSpinOSO_CG(LAMMPS *lmp) : Min(lmp), g_old(NULL), g_cur(NULL), p_s(NULL) { if (lmp->citeme) lmp->citeme->add(cite_minstyle_spin_oso_cg); nlocal_max = 0; - alpha_damp = 1.0; + + // nreplica = number of partitions + // ireplica = which world I am in universe + + nreplica = universe->nworlds; + ireplica = universe->iworld; + use_line_search = 1; discrete_factor = 10.0; } @@ -77,24 +84,31 @@ MinSpinOSO_CG::~MinSpinOSO_CG() memory->destroy(g_old); memory->destroy(g_cur); memory->destroy(p_s); + if (use_line_search) + memory->destroy(sp_copy); } /* ---------------------------------------------------------------------- */ void MinSpinOSO_CG::init() { - local_iter = 0; + der_e_cur = 0.0; + der_e_pr = 0.0; + Min::init(); + dts = dt = update->dt; last_negative = update->ntimestep; - + // allocate tables nlocal_max = atom->nlocal; memory->grow(g_old,3*nlocal_max,"min/spin/oso/cg:g_old"); memory->grow(g_cur,3*nlocal_max,"min/spin/oso/cg:g_cur"); memory->grow(p_s,3*nlocal_max,"min/spin/oso/cg:p_s"); + if (use_line_search) + memory->grow(sp_copy,nlocal_max,3,"min/spin/oso/cg:sp_copy"); } /* ---------------------------------------------------------------------- */ @@ -117,9 +131,9 @@ void MinSpinOSO_CG::setup_style() int MinSpinOSO_CG::modify_param(int narg, char **arg) { - if (strcmp(arg[0],"alpha_damp") == 0) { + if (strcmp(arg[0],"line_search") == 0) { if (narg < 2) error->all(FLERR,"Illegal fix_modify command"); - alpha_damp = force->numeric(FLERR,arg[1]); + use_line_search = force->numeric(FLERR,arg[1]); return 2; } if (strcmp(arg[0],"discrete_factor") == 0) { @@ -160,19 +174,22 @@ int MinSpinOSO_CG::iterate(int maxiter) bigint ntimestep; double fmdotfm; int flag, flagall; - - // grow tables if nlocal increased + double **sp = atom->sp; + double der_e_cur_tmp = 0.0; if (nlocal_max < nlocal) { + nlocal_max = nlocal; local_iter = 0; nlocal_max = nlocal; memory->grow(g_old,3*nlocal_max,"min/spin/oso/cg:g_old"); memory->grow(g_cur,3*nlocal_max,"min/spin/oso/cg:g_cur"); memory->grow(p_s,3*nlocal_max,"min/spin/oso/cg:p_s"); + if (use_line_search) + memory->grow(sp_copy,nlocal_max,3,"min/spin/oso/cg:sp_copy"); } for (int iter = 0; iter < maxiter; iter++) { - + if (timer->check_timeout(niter)) return TIMEOUT; @@ -182,16 +199,51 @@ int MinSpinOSO_CG::iterate(int maxiter) // optimize timestep accross processes / replicas // need a force calculation for timestep optimization - if (local_iter == 0) energy_force(0); - dts = evaluate_dt(); - - calc_gradient(dts); - calc_search_direction(); - advance_spins(); - - eprevious = ecurrent; - ecurrent = energy_force(0); - neval++; + if (use_line_search) { + + // here we need to do line search + if (local_iter == 0) + calc_gradient(); + + calc_search_direction(); + der_e_cur = 0.0; + for (int i = 0; i < 3 * nlocal; i++) + der_e_cur += g_cur[i] * p_s[i]; + MPI_Allreduce(&der_e_cur,&der_e_cur_tmp,1,MPI_DOUBLE,MPI_SUM,world); + der_e_cur = der_e_cur_tmp; + if (update->multireplica == 1) { + MPI_Allreduce(&der_e_cur_tmp,&der_e_cur,1,MPI_DOUBLE,MPI_SUM,universe->uworld); + } + for (int i = 0; i < nlocal; i++) + for (int j = 0; j < 3; j++) + sp_copy[i][j] = sp[i][j]; + + eprevious = ecurrent; + der_e_pr = der_e_cur; + calc_and_make_step(0.0, 1.0, 0); + } + else{ + + // here we don't do line search + // but use cutoff rotation angle + // if gneb calc., nreplica > 1 + // then calculate gradients and advance spins + // of intermediate replicas only + + if (nreplica > 1) { + if(ireplica != 0 && ireplica != nreplica-1) + calc_gradient(); + calc_search_direction(); + advance_spins(); + } else{ + calc_gradient(); + calc_search_direction(); + advance_spins(); + } + eprevious = ecurrent; + ecurrent = energy_force(0); + neval++; + } //// energy tolerance criterion //// only check after DELAYSTEP elapsed since velocties reset to 0 @@ -239,6 +291,347 @@ int MinSpinOSO_CG::iterate(int maxiter) return MAXITER; } +/* ---------------------------------------------------------------------- + calculate gradients +---------------------------------------------------------------------- */ + +void MinSpinOSO_CG::calc_gradient() +{ + int nlocal = atom->nlocal; + double **sp = atom->sp; + double **fm = atom->fm; + double hbar = force->hplanck/MY_2PI; + double factor; + + if (use_line_search) + factor = hbar; + else factor = evaluate_dt(); + + // loop on all spins on proc. + + for (int i = 0; i < nlocal; i++) { + g_cur[3 * i + 0] = (fm[i][0]*sp[i][1] - fm[i][1]*sp[i][0]) * factor; + g_cur[3 * i + 1] = -(fm[i][2]*sp[i][0] - fm[i][0]*sp[i][2]) * factor; + g_cur[3 * i + 2] = (fm[i][1]*sp[i][2] - fm[i][2]*sp[i][1]) * factor; + } +} + +/* ---------------------------------------------------------------------- + search direction: + The Fletcher-Reeves conj. grad. method + See Jorge Nocedal and Stephen J. Wright 'Numerical + Optimization' Second Edition, 2006 (p. 121) +---------------------------------------------------------------------- */ + +void MinSpinOSO_CG::calc_search_direction() +{ + int nlocal = atom->nlocal; + double g2old = 0.0; + double g2 = 0.0; + double beta = 0.0; + + double g2_global = 0.0; + double g2old_global = 0.0; + + if (local_iter == 0 || local_iter % 5 == 0){ // steepest descent direction + for (int i = 0; i < 3 * nlocal; i++) { + p_s[i] = -g_cur[i]; + g_old[i] = g_cur[i]; + } + } else { // conjugate direction + for (int i = 0; i < 3 * nlocal; i++) { + g2old += g_old[i] * g_old[i]; + g2 += g_cur[i] * g_cur[i]; + } + + // now we need to collect/broadcast beta on this replica + // need to check what is beta for GNEB + + MPI_Allreduce(&g2,&g2_global,1,MPI_DOUBLE,MPI_SUM,world); + MPI_Allreduce(&g2old,&g2old_global,1,MPI_DOUBLE,MPI_SUM,world); + + // Sum over all replicas. Good for GNEB. + if (update->multireplica == 1) { + g2 = g2_global; + g2old = g2old_global; + MPI_Allreduce(&g2,&g2_global,1,MPI_DOUBLE,MPI_SUM,universe->uworld); + MPI_Allreduce(&g2old,&g2old_global,1,MPI_DOUBLE,MPI_SUM,universe->uworld); + } + if (fabs(g2_global) < 1.0e-60) beta = 0.0; + else beta = g2_global / g2old_global; + // calculate conjugate direction + for (int i = 0; i < 3 * nlocal; i++) { + p_s[i] = (beta * p_s[i] - g_cur[i]); + g_old[i] = g_cur[i]; + } + } + + local_iter++; +} + +/* ---------------------------------------------------------------------- + rotation of spins along the search direction +---------------------------------------------------------------------- */ + +void MinSpinOSO_CG::advance_spins() +{ + int nlocal = atom->nlocal; + double **sp = atom->sp; + double **fm = atom->fm; + double tdampx, tdampy, tdampz; + double rot_mat[9]; // exponential of matrix made of search direction + double s_new[3]; + + // loop on all spins on proc. + + for (int i = 0; i < nlocal; i++) { + rodrigues_rotation(p_s + 3 * i, rot_mat); + + // rotate spins + + vm3(rot_mat, sp[i], s_new); + for (int j = 0; j < 3; j++) sp[i][j] = s_new[j]; + } +} + +/* ---------------------------------------------------------------------- + compute and return max_i||mag. torque_i||_2 +------------------------------------------------------------------------- */ + +double MinSpinOSO_CG::max_torque() +{ + double fmsq,fmaxsqone,fmaxsqloc,fmaxsqall; + int nlocal = atom->nlocal; + double factor; + double hbar = force->hplanck/MY_2PI; + + if (use_line_search) factor = 1.0; + else factor = hbar; + + // finding max fm on this proc. + + fmsq = fmaxsqone = fmaxsqloc = fmaxsqall = 0.0; + for (int i = 0; i < nlocal; i++) { + fmsq = 0.0; + for (int j = 0; j < 3; j++) + fmsq += g_cur[3 * i + j] * g_cur[3 * i + j]; + fmaxsqone = MAX(fmaxsqone,fmsq); + } + + // finding max fm on this replica + + fmaxsqloc = fmaxsqone; + MPI_Allreduce(&fmaxsqone,&fmaxsqloc,1,MPI_DOUBLE,MPI_MAX,world); + + // finding max fm over all replicas, if necessary + // this communicator would be invalid for multiprocess replicas + + fmaxsqall = fmaxsqloc; + if (update->multireplica == 1) { + fmaxsqall = fmaxsqloc; + MPI_Allreduce(&fmaxsqloc,&fmaxsqall,1,MPI_DOUBLE,MPI_MAX,universe->uworld); + } + + return sqrt(fmaxsqall) * factor; +} + +/* ---------------------------------------------------------------------- + calculate 3x3 matrix exponential using Rodrigues' formula + (R. Murray, Z. Li, and S. Shankar Sastry, + A Mathematical Introduction to + Robotic Manipulation (1994), p. 28 and 30). + + upp_tr - vector x, y, z so that one calculate + U = exp(A) with A= [[0, x, y], + [-x, 0, z], + [-y, -z, 0]] +------------------------------------------------------------------------- */ + +void MinSpinOSO_CG::rodrigues_rotation(const double *upp_tr, double *out) +{ + double theta,A,B,D,x,y,z; + double s1,s2,s3,a1,a2,a3; + + if (fabs(upp_tr[0]) < 1.0e-40 && + fabs(upp_tr[1]) < 1.0e-40 && + fabs(upp_tr[2]) < 1.0e-40){ + + // if upp_tr is zero, return unity matrix + for(int k = 0; k < 3; k++){ + for(int m = 0; m < 3; m++){ + if (m == k) + out[3 * k + m] = 1.0; + else + out[3 * k + m] = 0.0; + } + } + return; + } + + theta = sqrt(upp_tr[0] * upp_tr[0] + + upp_tr[1] * upp_tr[1] + + upp_tr[2] * upp_tr[2]); + + A = cos(theta); + B = sin(theta); + D = 1 - A; + x = upp_tr[0]/theta; + y = upp_tr[1]/theta; + z = upp_tr[2]/theta; + + // diagonal elements of U + + out[0] = A + z * z * D; + out[4] = A + y * y * D; + out[8] = A + x * x * D; + + // off diagonal of U + + s1 = -y * z *D; + s2 = x * z * D; + s3 = -x * y * D; + + a1 = x * B; + a2 = y * B; + a3 = z * B; + + out[1] = s1 + a1; + out[3] = s1 - a1; + out[2] = s2 + a2; + out[6] = s2 - a2; + out[5] = s3 + a3; + out[7] = s3 - a3; + +} + +/* ---------------------------------------------------------------------- + out = vector^T x m, + m -- 3x3 matrix , v -- 3-d vector +------------------------------------------------------------------------- */ + +void MinSpinOSO_CG::vm3(const double *m, const double *v, double *out) +{ + for(int i = 0; i < 3; i++){ + out[i] *= 0.0; + for(int j = 0; j < 3; j++) + out[i] += *(m + 3 * j + i) * v[j]; + } +} + + +void MinSpinOSO_CG::make_step(double c, double *energy_and_der) +{ + double p_scaled[3]; + int nlocal = atom->nlocal; + double rot_mat[9]; // exponential of matrix made of search direction + double s_new[3]; + double **sp = atom->sp; + double der_e_cur_tmp = 0.0;; + + for (int i = 0; i < nlocal; i++) { + + // scale the search direction + + for (int j = 0; j < 3; j++) p_scaled[j] = c * p_s[3 * i + j]; + + // calculate rotation matrix + + rodrigues_rotation(p_scaled, rot_mat); + + // rotate spins + + vm3(rot_mat, sp[i], s_new); + for (int j = 0; j < 3; j++) sp[i][j] = s_new[j]; + } + + ecurrent = energy_force(0); + calc_gradient(); + neval++; + der_e_cur = 0.0; + for (int i = 0; i < 3 * nlocal; i++) { + der_e_cur += g_cur[i] * p_s[i]; + } + MPI_Allreduce(&der_e_cur,&der_e_cur_tmp,1,MPI_DOUBLE,MPI_SUM,world); + der_e_cur = der_e_cur_tmp; + if (update->multireplica == 1) { + MPI_Allreduce(&der_e_cur_tmp,&der_e_cur,1,MPI_DOUBLE,MPI_SUM,universe->uworld); + } + + energy_and_der[0] = ecurrent; + energy_and_der[1] = der_e_cur; +} + +/* ---------------------------------------------------------------------- + Calculate step length which satisfies approximate Wolfe conditions + using the cubic interpolation +------------------------------------------------------------------------- */ + +int MinSpinOSO_CG::calc_and_make_step(double a, double b, int index) +{ + double e_and_d[2] = {0.0,0.0}; + double alpha,c1,c2,c3; + double **sp = atom->sp; + int nlocal = atom->nlocal; + + make_step(b,e_and_d); + ecurrent = e_and_d[0]; + der_e_cur = e_and_d[1]; + index++; + + if (awc(der_e_pr,eprevious,e_and_d[1],e_and_d[0]) || index == 10){ + MPI_Bcast(&b,1,MPI_DOUBLE,0,world); + for (int i = 0; i < 3 * nlocal; i++) { + p_s[i] = b * p_s[i]; + } + return 1; + } + else{ + double r,f0,f1,df0,df1; + r = b - a; + f0 = eprevious; + f1 = ecurrent; + df0 = der_e_pr; + df1 = der_e_cur; + + c1 = -2.0*(f1-f0)/(r*r*r)+(df1+df0)/(r*r); + c2 = 3.0*(f1-f0)/(r*r)-(df1+2.0*df0)/(r); + c3 = df0; + + // f(x) = c1 x^3 + c2 x^2 + c3 x^1 + c4 + // has minimum at alpha below. We do not check boundaries. + + alpha = (-c2 + sqrt(c2*c2 - 3.0*c1*c3))/(3.0*c1); + MPI_Bcast(&alpha,1,MPI_DOUBLE,0,world); + + if (alpha < 0.0) alpha = r/2.0; + + for (int i = 0; i < nlocal; i++) { + for (int j = 0; j < 3; j++) sp[i][j] = sp_copy[i][j]; + } + calc_and_make_step(0.0, alpha, index); + } + + return 0; +} + +/* ---------------------------------------------------------------------- + Approximate Wolfe conditions: + William W. Hager and Hongchao Zhang + SIAM J. optim., 16(1), 170-192. (23 pages) +------------------------------------------------------------------------- */ + +int MinSpinOSO_CG::awc(double der_phi_0, double phi_0, double der_phi_j, double phi_j){ + + double eps = 1.0e-6; + double delta = 0.1; + double sigma = 0.9; + + if ((phi_j<=phi_0+eps*fabs(phi_0)) && ((2.0*delta-1.0) * der_phi_0>=der_phi_j>=sigma*der_phi_0)) + return 1; + else + return 0; +} + /* ---------------------------------------------------------------------- evaluate max timestep ---------------------------------------------------------------------- */ @@ -282,231 +675,4 @@ double MinSpinOSO_CG::evaluate_dt() dtmax = MY_2PI/(discrete_factor*sqrt(fmaxsqall)); return dtmax; -} - -/* ---------------------------------------------------------------------- - calculate gradients ----------------------------------------------------------------------- */ - -void MinSpinOSO_CG::calc_gradient(double dts) -{ - int nlocal = atom->nlocal; - double **sp = atom->sp; - double **fm = atom->fm; - double tdampx, tdampy, tdampz; - - // loop on all spins on proc. - - for (int i = 0; i < nlocal; i++) { - - // calc. damping torque - - tdampx = -alpha_damp*(fm[i][1]*sp[i][2] - fm[i][2]*sp[i][1]); - tdampy = -alpha_damp*(fm[i][2]*sp[i][0] - fm[i][0]*sp[i][2]); - tdampz = -alpha_damp*(fm[i][0]*sp[i][1] - fm[i][1]*sp[i][0]); - - // calculate gradients - - g_cur[3 * i + 0] = -tdampz * dts; - g_cur[3 * i + 1] = tdampy * dts; - g_cur[3 * i + 2] = -tdampx * dts; - } -} - -/* ---------------------------------------------------------------------- - search direction: - The Fletcher-Reeves conj. grad. method - See Jorge Nocedal and Stephen J. Wright 'Numerical - Optimization' Second Edition, 2006 (p. 121) ----------------------------------------------------------------------- */ - -void MinSpinOSO_CG::calc_search_direction() -{ - int nlocal = atom->nlocal; - double g2old = 0.0; - double g2 = 0.0; - double beta = 0.0; - - double g2_global = 0.0; - double g2old_global = 0.0; - if (local_iter == 0 || local_iter % 5 == 0){ // steepest descent direction - for (int i = 0; i < 3 * nlocal; i++) { - p_s[i] = -g_cur[i]; - g_old[i] = g_cur[i]; - } - } else { // conjugate direction - for (int i = 0; i < 3 * nlocal; i++) { - g2old += g_old[i] * g_old[i]; - g2 += g_cur[i] * g_cur[i]; - } - - // now we need to collect/broadcast beta on this replica - // different replica can have different beta for now. - // need to check what is beta for GNEB - - MPI_Allreduce(&g2, &g2_global, 1, MPI_DOUBLE, MPI_SUM, world); - MPI_Allreduce(&g2old, &g2old_global, 1, MPI_DOUBLE, MPI_SUM, world); - - // Sum over all replicas. Good for GNEB. - if (update->multireplica == 1) { - g2 = g2_global; - g2old = g2old_global; - MPI_Allreduce(&g2,&g2_global,1,MPI_DOUBLE,MPI_SUM,universe->uworld); - MPI_Allreduce(&g2old,&g2old_global,1,MPI_DOUBLE,MPI_SUM,universe->uworld); - } - - if (fabs(g2_global) < 1.0e-60) beta = 0.0; - else beta = g2_global / g2old_global; - // calculate conjugate direction - for (int i = 0; i < 3 * nlocal; i++) { - p_s[i] = beta * p_s[i] - g_cur[i]; - g_old[i] = g_cur[i]; - } - } - - local_iter++; -} - -/* ---------------------------------------------------------------------- - rotation of spins along the search direction ----------------------------------------------------------------------- */ - -void MinSpinOSO_CG::advance_spins() -{ - int nlocal = atom->nlocal; - double **sp = atom->sp; - double **fm = atom->fm; - double tdampx, tdampy, tdampz; - double rot_mat[9]; // exponential of matrix made of search direction - double s_new[3]; - - // loop on all spins on proc. - - for (int i = 0; i < nlocal; i++) { - rodrigues_rotation(p_s + 3 * i, rot_mat); - - // rotate spins - - vm3(rot_mat, sp[i], s_new); - for (int j = 0; j < 3; j++) sp[i][j] = s_new[j]; - } -} - -/* ---------------------------------------------------------------------- - compute and return max_i||mag. torque_i||_2 -------------------------------------------------------------------------- */ - -double MinSpinOSO_CG::max_torque() -{ - double fmsq,fmaxsqone,fmaxsqloc,fmaxsqall; - int nlocal = atom->nlocal; - double hbar = force->hplanck/MY_2PI; - - // finding max fm on this proc. - - fmsq = fmaxsqone = fmaxsqloc = fmaxsqall = 0.0; - for (int i = 0; i < nlocal; i++) { - fmsq = 0.0; - for (int j = 0; j < 3; j++) - fmsq += g_cur[3 * i + j] * g_cur[3 * i + j]; - fmaxsqone = MAX(fmaxsqone,fmsq); - } - - // finding max fm on this replica - - fmaxsqloc = fmaxsqone; - MPI_Allreduce(&fmaxsqone,&fmaxsqloc,1,MPI_DOUBLE,MPI_MAX,world); - - // finding max fm over all replicas, if necessary - // this communicator would be invalid for multiprocess replicas - - fmaxsqall = fmaxsqloc; - if (update->multireplica == 1) { - fmaxsqall = fmaxsqloc; - MPI_Allreduce(&fmaxsqloc,&fmaxsqall,1,MPI_DOUBLE,MPI_MAX,universe->uworld); - } - - return sqrt(fmaxsqall) * hbar; -} - -/* ---------------------------------------------------------------------- - calculate 3x3 matrix exponential using Rodrigues' formula - (R. Murray, Z. Li, and S. Shankar Sastry, - A Mathematical Introduction to - Robotic Manipulation (1994), p. 28 and 30). - - upp_tr - vector x, y, z so that one calculate - U = exp(A) with A= [[0, x, y], - [-x, 0, z], - [-y, -z, 0]] -------------------------------------------------------------------------- */ - -void MinSpinOSO_CG::rodrigues_rotation(const double *upp_tr, double *out) -{ - double theta,A,B,D,x,y,z; - double s1,s2,s3,a1,a2,a3; - - if (fabs(upp_tr[0]) < 1.0e-40 && - fabs(upp_tr[1]) < 1.0e-40 && - fabs(upp_tr[2]) < 1.0e-40){ - - // if upp_tr is zero, return unity matrix - for(int k = 0; k < 3; k++){ - for(int m = 0; m < 3; m++){ - if (m == k) out[3 * k + m] = 1.0; - else out[3 * k + m] = 0.0; - } - } - return; - } - - theta = sqrt(upp_tr[0] * upp_tr[0] + - upp_tr[1] * upp_tr[1] + - upp_tr[2] * upp_tr[2]); - - A = cos(theta); - B = sin(theta); - D = 1 - A; - x = upp_tr[0]/theta; - y = upp_tr[1]/theta; - z = upp_tr[2]/theta; - - // diagonal elements of U - - out[0] = A + z * z * D; - out[4] = A + y * y * D; - out[8] = A + x * x * D; - - // off diagonal of U - - s1 = -y * z *D; - s2 = x * z * D; - s3 = -x * y * D; - - a1 = x * B; - a2 = y * B; - a3 = z * B; - - out[1] = s1 + a1; - out[3] = s1 - a1; - out[2] = s2 + a2; - out[6] = s2 - a2; - out[5] = s3 + a3; - out[7] = s3 - a3; - -} - -/* ---------------------------------------------------------------------- - out = vector^T x m, - m -- 3x3 matrix , v -- 3-d vector -------------------------------------------------------------------------- */ - -void MinSpinOSO_CG::vm3(const double *m, const double *v, double *out) -{ - for(int i = 0; i < 3; i++){ - out[i] *= 0.0; - for(int j = 0; j < 3; j++){ - out[i] += *(m + 3 * j + i) * v[j]; - } - } -} +} \ No newline at end of file diff --git a/src/SPIN/min_spin_oso_cg.h b/src/SPIN/min_spin_oso_cg.h index 81bbd2c294..e50d1a69db 100644 --- a/src/SPIN/min_spin_oso_cg.h +++ b/src/SPIN/min_spin_oso_cg.h @@ -24,7 +24,7 @@ MinimizeStyle(spin/oso_cg, MinSpinOSO_CG) namespace LAMMPS_NS { -class MinSpinOSO_CG : public Min { +class MinSpinOSO_CG: public Min { public: MinSpinOSO_CG(class LAMMPS *); virtual ~MinSpinOSO_CG(); @@ -33,33 +33,34 @@ class MinSpinOSO_CG : public Min { int modify_param(int, char **); void reset_vectors(); int iterate(int); - private: - double evaluate_dt(); - void advance_spins(); - double max_torque(); - void calc_gradient(double); - void calc_search_direction(); - - // global and spin timesteps - - double dt; - double dts; - int nlocal_max; // max value of nlocal (for size of lists) - - double alpha_damp; // damping for spin minimization - double discrete_factor; // factor for spin timestep evaluation - + double dt; // global timestep + double dts; // spin timestep + int ireplica,nreplica; // for neb double *spvec; // variables for atomic dof, as 1d vector double *fmvec; // variables for atomic dof, as 1d vector - - double *g_old; // gradient vector at previous iteration - double *g_cur; // current gradient vector + double *g_cur; // current gradient vector + double *g_old; // gradient vector at previous step double *p_s; // search direction vector - int local_iter; // number of times we call search_direction + double **sp_copy; // copy of the spins + int local_iter; // for neb + int nlocal_max; // max value of nlocal (for size of lists) + double discrete_factor; // factor for spin timestep evaluation + double evaluate_dt(); + void advance_spins(); + void calc_gradient(); + void calc_search_direction(); + double maximum_rotation(double *); void vm3(const double *, const double *, double *); void rodrigues_rotation(const double *, double *); + int calc_and_make_step(double, double, int); + int awc(double, double, double, double); + void make_step(double, double *); + double max_torque(); + double der_e_cur; // current derivative along search dir. + double der_e_pr; // previous derivative along search dir. + int use_line_search; // use line search or not. bigint last_negative; }; diff --git a/src/SPIN/min_spin_oso_cg2.cpp b/src/SPIN/min_spin_oso_cg2.cpp deleted file mode 100644 index 52b98eead7..0000000000 --- a/src/SPIN/min_spin_oso_cg2.cpp +++ /dev/null @@ -1,679 +0,0 @@ -/* ---------------------------------------------------------------------- - LAMMPS - Large-scale Atomic/Molecular Massively Parallel Simulator - http://lammps.sandia.gov, Sandia National Laboratories - Steve Plimpton, sjplimp@sandia.gov - - Copyright (2003) Sandia Corporation. Under the terms of Contract - DE-AC04-94AL85000 with Sandia Corporation, the U.S. Government retains - certain rights in this software. This software is distributed under - the GNU General Public License. - - See the README file in the top-level LAMMPS directory. -------------------------------------------------------------------------- */ - -/* ------------------------------------------------------------------------ - Contributing authors: Aleksei Ivanov (University of Iceland) - Julien Tranchida (SNL) - - Please cite the related publication: - Ivanov, A. V., Uzdin, V. M., & Jónsson, H. (2019). Fast and Robust - Algorithm for the Minimisation of the Energy of Spin Systems. arXiv - preprint arXiv:1904.02669. -------------------------------------------------------------------------- */ - -#include -#include -#include -#include -#include "min_spin_oso_cg2.h" -#include "universe.h" -#include "atom.h" -#include "citeme.h" -#include "force.h" -#include "update.h" -#include "output.h" -#include "timer.h" -#include "error.h" -#include "memory.h" -#include "modify.h" -#include "math_special.h" -#include "math_const.h" -#include "universe.h" -#include - -using namespace LAMMPS_NS; -using namespace MathConst; - -static const char cite_minstyle_spin_oso_cg2[] = - "min_style spin/oso_cg2 command:\n\n" - "@article{ivanov2019fast,\n" - "title={Fast and Robust Algorithm for the Minimisation of the Energy of " - "Spin Systems},\n" - "author={Ivanov, A. V and Uzdin, V. M. and J{\'o}nsson, H.},\n" - "journal={arXiv preprint arXiv:1904.02669},\n" - "year={2019}\n" - "}\n\n"; - -// EPS_ENERGY = minimum normalization for energy tolerance - -#define EPS_ENERGY 1.0e-8 - -#define DELAYSTEP 5 - - -/* ---------------------------------------------------------------------- */ - -MinSpinOSO_CG2::MinSpinOSO_CG2(LAMMPS *lmp) : - Min(lmp), g_old(NULL), g_cur(NULL), p_s(NULL) -{ - if (lmp->citeme) lmp->citeme->add(cite_minstyle_spin_oso_cg2); - nlocal_max = 0; - - // nreplica = number of partitions - // ireplica = which world I am in universe - - nreplica = universe->nworlds; - ireplica = universe->iworld; - use_line_search = 1; - discrete_factor = 10.0; - -} - -/* ---------------------------------------------------------------------- */ - -MinSpinOSO_CG2::~MinSpinOSO_CG2() -{ - memory->destroy(g_old); - memory->destroy(g_cur); - memory->destroy(p_s); - if (use_line_search) - memory->destroy(sp_copy); -} - -/* ---------------------------------------------------------------------- */ - -void MinSpinOSO_CG2::init() -{ - local_iter = 0; - der_e_cur = 0.0; - der_e_pr = 0.0; - - Min::init(); - - dts = dt = update->dt; - last_negative = update->ntimestep; - - // allocate tables - - nlocal_max = atom->nlocal; - memory->grow(g_old,3*nlocal_max,"min/spin/oso/cg2:g_old"); - memory->grow(g_cur,3*nlocal_max,"min/spin/oso/cg2:g_cur"); - memory->grow(p_s,3*nlocal_max,"min/spin/oso/cg2:p_s"); - if (use_line_search) - memory->grow(sp_copy,nlocal_max,3,"min/spin/oso/cg2:sp_copy"); -} - -/* ---------------------------------------------------------------------- */ - -void MinSpinOSO_CG2::setup_style() -{ - double **v = atom->v; - int nlocal = atom->nlocal; - - // check if the atom/spin style is defined - - if (!atom->sp_flag) - error->all(FLERR,"min/spin_oso_cg2 requires atom/spin style"); - - for (int i = 0; i < nlocal; i++) - v[i][0] = v[i][1] = v[i][2] = 0.0; -} - -/* ---------------------------------------------------------------------- */ - -int MinSpinOSO_CG2::modify_param(int narg, char **arg) -{ - - if (strcmp(arg[0],"line_search") == 0) { - if (narg < 2) error->all(FLERR,"Illegal fix_modify command"); - use_line_search = force->numeric(FLERR,arg[1]); - return 2; - } - if (strcmp(arg[0],"discrete_factor") == 0) { - if (narg < 2) error->all(FLERR,"Illegal fix_modify command"); - discrete_factor = force->numeric(FLERR,arg[1]); - return 2; - } - return 0; -} - -/* ---------------------------------------------------------------------- - set current vector lengths and pointers - called after atoms have migrated -------------------------------------------------------------------------- */ - -void MinSpinOSO_CG2::reset_vectors() -{ - // atomic dof - - // size sp is 4N vector - nvec = 4 * atom->nlocal; - if (nvec) spvec = atom->sp[0]; - - nvec = 3 * atom->nlocal; - if (nvec) fmvec = atom->fm[0]; - - if (nvec) xvec = atom->x[0]; - if (nvec) fvec = atom->f[0]; -} - -/* ---------------------------------------------------------------------- - minimization via orthogonal spin optimisation -------------------------------------------------------------------------- */ - -int MinSpinOSO_CG2::iterate(int maxiter) -{ - int nlocal = atom->nlocal; - bigint ntimestep; - double fmdotfm; - int flag, flagall; - double **sp = atom->sp; - double der_e_cur_tmp = 0.0; - - if (nlocal_max < nlocal) { - nlocal_max = nlocal; - local_iter = 0; - nlocal_max = nlocal; - memory->grow(g_old,3*nlocal_max,"min/spin/oso/cg2:g_old"); - memory->grow(g_cur,3*nlocal_max,"min/spin/oso/cg2:g_cur"); - memory->grow(p_s,3*nlocal_max,"min/spin/oso/cg2:p_s"); - if (use_line_search) - memory->grow(sp_copy,nlocal_max,3,"min/spin/oso/cg2:sp_copy"); - } - - for (int iter = 0; iter < maxiter; iter++) { - - if (timer->check_timeout(niter)) - return TIMEOUT; - - ntimestep = ++update->ntimestep; - niter++; - - // optimize timestep accross processes / replicas - // need a force calculation for timestep optimization - - if (use_line_search) { - - // here we need to do line search - if (local_iter == 0) - calc_gradient(); - - calc_search_direction(); - der_e_cur = 0.0; - for (int i = 0; i < 3 * nlocal; i++) - der_e_cur += g_cur[i] * p_s[i]; - MPI_Allreduce(&der_e_cur,&der_e_cur_tmp,1,MPI_DOUBLE,MPI_SUM,world); - der_e_cur = der_e_cur_tmp; - if (update->multireplica == 1) { - MPI_Allreduce(&der_e_cur_tmp,&der_e_cur,1,MPI_DOUBLE,MPI_SUM,universe->uworld); - } - for (int i = 0; i < nlocal; i++) - for (int j = 0; j < 3; j++) - sp_copy[i][j] = sp[i][j]; - - eprevious = ecurrent; - der_e_pr = der_e_cur; - calc_and_make_step(0.0, 1.0, 0); - } - else{ - - // here we don't do line search - // but use cutoff rotation angle - // if gneb calc., nreplica > 1 - // then calculate gradients and advance spins - // of intermediate replicas only - - if (nreplica > 1) { - if(ireplica != 0 && ireplica != nreplica-1) - calc_gradient(); - calc_search_direction(); - advance_spins(); - } else{ - calc_gradient(); - calc_search_direction(); - advance_spins(); - } - eprevious = ecurrent; - ecurrent = energy_force(0); - neval++; - } - - //// energy tolerance criterion - //// only check after DELAYSTEP elapsed since velocties reset to 0 - //// sync across replicas if running multi-replica minimization - - if (update->etol > 0.0 && ntimestep-last_negative > DELAYSTEP) { - if (update->multireplica == 0) { - if (fabs(ecurrent-eprevious) < - update->etol * 0.5*(fabs(ecurrent) + fabs(eprevious) + EPS_ENERGY)) - return ETOL; - } else { - if (fabs(ecurrent-eprevious) < - update->etol * 0.5*(fabs(ecurrent) + fabs(eprevious) + EPS_ENERGY)) - flag = 0; - else flag = 1; - MPI_Allreduce(&flag,&flagall,1,MPI_INT,MPI_SUM,universe->uworld); - if (flagall == 0) return ETOL; - } - } - - // magnetic torque tolerance criterion - // sync across replicas if running multi-replica minimization - - if (update->ftol > 0.0) { - fmdotfm = max_torque(); - if (update->multireplica == 0) { - if (fmdotfm < update->ftol*update->ftol) return FTOL; - } else { - if (fmdotfm < update->ftol*update->ftol) flag = 0; - else flag = 1; - MPI_Allreduce(&flag,&flagall,1,MPI_INT,MPI_SUM,universe->uworld); - if (flagall == 0) return FTOL; - } - } - - // output for thermo, dump, restart files - - if (output->next == ntimestep) { - timer->stamp(); - output->write(ntimestep); - timer->stamp(Timer::OUTPUT); - } - } - - return MAXITER; -} - -/* ---------------------------------------------------------------------- - calculate gradients ----------------------------------------------------------------------- */ - -void MinSpinOSO_CG2::calc_gradient() -{ - int nlocal = atom->nlocal; - double **sp = atom->sp; - double **fm = atom->fm; - double hbar = force->hplanck/MY_2PI; - double factor; - - if (use_line_search) - factor = hbar; - else factor = evaluate_dt(); - - // loop on all spins on proc. - - for (int i = 0; i < nlocal; i++) { - g_cur[3 * i + 0] = (fm[i][0]*sp[i][1] - fm[i][1]*sp[i][0]) * factor; - g_cur[3 * i + 1] = -(fm[i][2]*sp[i][0] - fm[i][0]*sp[i][2]) * factor; - g_cur[3 * i + 2] = (fm[i][1]*sp[i][2] - fm[i][2]*sp[i][1]) * factor; - } -} - -/* ---------------------------------------------------------------------- - search direction: - The Fletcher-Reeves conj. grad. method - See Jorge Nocedal and Stephen J. Wright 'Numerical - Optimization' Second Edition, 2006 (p. 121) ----------------------------------------------------------------------- */ - -void MinSpinOSO_CG2::calc_search_direction() -{ - int nlocal = atom->nlocal; - double g2old = 0.0; - double g2 = 0.0; - double beta = 0.0; - - double g2_global = 0.0; - double g2old_global = 0.0; - - if (local_iter == 0 || local_iter % 5 == 0){ // steepest descent direction - for (int i = 0; i < 3 * nlocal; i++) { - p_s[i] = -g_cur[i]; - g_old[i] = g_cur[i]; - } - } else { // conjugate direction - for (int i = 0; i < 3 * nlocal; i++) { - g2old += g_old[i] * g_old[i]; - g2 += g_cur[i] * g_cur[i]; - } - - // now we need to collect/broadcast beta on this replica - // need to check what is beta for GNEB - - MPI_Allreduce(&g2,&g2_global,1,MPI_DOUBLE,MPI_SUM,world); - MPI_Allreduce(&g2old,&g2old_global,1,MPI_DOUBLE,MPI_SUM,world); - - // Sum over all replicas. Good for GNEB. - if (update->multireplica == 1) { - g2 = g2_global; - g2old = g2old_global; - MPI_Allreduce(&g2,&g2_global,1,MPI_DOUBLE,MPI_SUM,universe->uworld); - MPI_Allreduce(&g2old,&g2old_global,1,MPI_DOUBLE,MPI_SUM,universe->uworld); - } - if (fabs(g2_global) < 1.0e-60) beta = 0.0; - else beta = g2_global / g2old_global; - // calculate conjugate direction - for (int i = 0; i < 3 * nlocal; i++) { - p_s[i] = (beta * p_s[i] - g_cur[i]); - g_old[i] = g_cur[i]; - } - } - - local_iter++; -} - -/* ---------------------------------------------------------------------- - rotation of spins along the search direction ----------------------------------------------------------------------- */ - -void MinSpinOSO_CG2::advance_spins() -{ - int nlocal = atom->nlocal; - double **sp = atom->sp; - double **fm = atom->fm; - double tdampx, tdampy, tdampz; - double rot_mat[9]; // exponential of matrix made of search direction - double s_new[3]; - - // loop on all spins on proc. - - for (int i = 0; i < nlocal; i++) { - rodrigues_rotation(p_s + 3 * i, rot_mat); - - // rotate spins - - vm3(rot_mat, sp[i], s_new); - for (int j = 0; j < 3; j++) sp[i][j] = s_new[j]; - } -} - -/* ---------------------------------------------------------------------- - compute and return max_i||mag. torque_i||_2 -------------------------------------------------------------------------- */ - -double MinSpinOSO_CG2::max_torque() -{ - double fmsq,fmaxsqone,fmaxsqloc,fmaxsqall; - int nlocal = atom->nlocal; - double factor; - double hbar = force->hplanck/MY_2PI; - - if (use_line_search) factor = 1.0; - else factor = hbar; - - // finding max fm on this proc. - - fmsq = fmaxsqone = fmaxsqloc = fmaxsqall = 0.0; - for (int i = 0; i < nlocal; i++) { - fmsq = 0.0; - for (int j = 0; j < 3; j++) - fmsq += g_cur[3 * i + j] * g_cur[3 * i + j]; - fmaxsqone = MAX(fmaxsqone,fmsq); - } - - // finding max fm on this replica - - fmaxsqloc = fmaxsqone; - MPI_Allreduce(&fmaxsqone,&fmaxsqloc,1,MPI_DOUBLE,MPI_MAX,world); - - // finding max fm over all replicas, if necessary - // this communicator would be invalid for multiprocess replicas - - fmaxsqall = fmaxsqloc; - if (update->multireplica == 1) { - fmaxsqall = fmaxsqloc; - MPI_Allreduce(&fmaxsqloc,&fmaxsqall,1,MPI_DOUBLE,MPI_MAX,universe->uworld); - } - - return sqrt(fmaxsqall) * factor; -} - -/* ---------------------------------------------------------------------- - calculate 3x3 matrix exponential using Rodrigues' formula - (R. Murray, Z. Li, and S. Shankar Sastry, - A Mathematical Introduction to - Robotic Manipulation (1994), p. 28 and 30). - - upp_tr - vector x, y, z so that one calculate - U = exp(A) with A= [[0, x, y], - [-x, 0, z], - [-y, -z, 0]] -------------------------------------------------------------------------- */ - -void MinSpinOSO_CG2::rodrigues_rotation(const double *upp_tr, double *out) -{ - double theta,A,B,D,x,y,z; - double s1,s2,s3,a1,a2,a3; - - if (fabs(upp_tr[0]) < 1.0e-40 && - fabs(upp_tr[1]) < 1.0e-40 && - fabs(upp_tr[2]) < 1.0e-40){ - - // if upp_tr is zero, return unity matrix - for(int k = 0; k < 3; k++){ - for(int m = 0; m < 3; m++){ - if (m == k) out[3 * k + m] = 1.0; - else out[3 * k + m] = 0.0; - } - } - return; - } - - theta = sqrt(upp_tr[0] * upp_tr[0] + - upp_tr[1] * upp_tr[1] + - upp_tr[2] * upp_tr[2]); - - A = cos(theta); - B = sin(theta); - D = 1 - A; - x = upp_tr[0]/theta; - y = upp_tr[1]/theta; - z = upp_tr[2]/theta; - - // diagonal elements of U - - out[0] = A + z * z * D; - out[4] = A + y * y * D; - out[8] = A + x * x * D; - - // off diagonal of U - - s1 = -y * z *D; - s2 = x * z * D; - s3 = -x * y * D; - - a1 = x * B; - a2 = y * B; - a3 = z * B; - - out[1] = s1 + a1; - out[3] = s1 - a1; - out[2] = s2 + a2; - out[6] = s2 - a2; - out[5] = s3 + a3; - out[7] = s3 - a3; - -} - -/* ---------------------------------------------------------------------- - out = vector^T x m, - m -- 3x3 matrix , v -- 3-d vector -------------------------------------------------------------------------- */ - -void MinSpinOSO_CG2::vm3(const double *m, const double *v, double *out) -{ - for(int i = 0; i < 3; i++){ - out[i] *= 0.0; - for(int j = 0; j < 3; j++) - out[i] += *(m + 3 * j + i) * v[j]; - } -} - - -void MinSpinOSO_CG2::make_step(double c, double *energy_and_der) -{ - double p_scaled[3]; - int nlocal = atom->nlocal; - double rot_mat[9]; // exponential of matrix made of search direction - double s_new[3]; - double **sp = atom->sp; - double der_e_cur_tmp = 0.0;; - - for (int i = 0; i < nlocal; i++) { - - // scale the search direction - - for (int j = 0; j < 3; j++) p_scaled[j] = c * p_s[3 * i + j]; - - // calculate rotation matrix - - rodrigues_rotation(p_scaled, rot_mat); - - // rotate spins - - vm3(rot_mat, sp[i], s_new); - for (int j = 0; j < 3; j++) sp[i][j] = s_new[j]; - } - - ecurrent = energy_force(0); - calc_gradient(); - neval++; - der_e_cur = 0.0; - for (int i = 0; i < 3 * nlocal; i++) { - der_e_cur += g_cur[i] * p_s[i]; - } - MPI_Allreduce(&der_e_cur,&der_e_cur_tmp,1,MPI_DOUBLE,MPI_SUM,world); - der_e_cur = der_e_cur_tmp; - if (update->multireplica == 1) { - MPI_Allreduce(&der_e_cur_tmp,&der_e_cur,1,MPI_DOUBLE,MPI_SUM,universe->uworld); - } - - energy_and_der[0] = ecurrent; - energy_and_der[1] = der_e_cur; -} - -/* ---------------------------------------------------------------------- - Calculate step length which satisfies approximate Wolfe conditions - using the cubic interpolation -------------------------------------------------------------------------- */ - -int MinSpinOSO_CG2::calc_and_make_step(double a, double b, int index) -{ - double e_and_d[2] = {0.0,0.0}; - double alpha,c1,c2,c3; - double **sp = atom->sp; - int nlocal = atom->nlocal; - - make_step(b,e_and_d); - ecurrent = e_and_d[0]; - der_e_cur = e_and_d[1]; - index++; - - if (awc(der_e_pr,eprevious,e_and_d[1],e_and_d[0]) || index == 10){ - MPI_Bcast(&b,1,MPI_DOUBLE,0,world); - for (int i = 0; i < 3 * nlocal; i++) { - p_s[i] = b * p_s[i]; - } - return 1; - } - else{ - double r,f0,f1,df0,df1; - r = b - a; - f0 = eprevious; - f1 = ecurrent; - df0 = der_e_pr; - df1 = der_e_cur; - - c1 = -2.0*(f1-f0)/(r*r*r)+(df1+df0)/(r*r); - c2 = 3.0*(f1-f0)/(r*r)-(df1+2.0*df0)/(r); - c3 = df0; - - // f(x) = c1 x^3 + c2 x^2 + c3 x^1 + c4 - // has minimum at alpha below. We do not check boundaries. - - alpha = (-c2 + sqrt(c2*c2 - 3.0*c1*c3))/(3.0*c1); - MPI_Bcast(&alpha,1,MPI_DOUBLE,0,world); - - if (alpha < 0.0) alpha = r/2.0; - - for (int i = 0; i < nlocal; i++) { - for (int j = 0; j < 3; j++) sp[i][j] = sp_copy[i][j]; - } - calc_and_make_step(0.0, alpha, index); - } - - return 0; -} - -/* ---------------------------------------------------------------------- - Approximate Wolfe conditions: - William W. Hager and Hongchao Zhang - SIAM J. optim., 16(1), 170-192. (23 pages) -------------------------------------------------------------------------- */ - -int MinSpinOSO_CG2::awc(double der_phi_0, double phi_0, double der_phi_j, double phi_j){ - - double eps = 1.0e-6; - double delta = 0.1; - double sigma = 0.9; - - if ((phi_j<=phi_0+eps*fabs(phi_0)) && ((2.0*delta-1.0) * der_phi_0>=der_phi_j>=sigma*der_phi_0)) - return 1; - else - return 0; -} - -/* ---------------------------------------------------------------------- - evaluate max timestep ----------------------------------------------------------------------- */ - -double MinSpinOSO_CG2::evaluate_dt() -{ - double dtmax; - double fmsq; - double fmaxsqone,fmaxsqloc,fmaxsqall; - int nlocal = atom->nlocal; - double **fm = atom->fm; - - // finding max fm on this proc. - - fmsq = fmaxsqone = fmaxsqloc = fmaxsqall = 0.0; - for (int i = 0; i < nlocal; i++) { - fmsq = fm[i][0]*fm[i][0]+fm[i][1]*fm[i][1]+fm[i][2]*fm[i][2]; - fmaxsqone = MAX(fmaxsqone,fmsq); - } - - // finding max fm on this replica - - fmaxsqloc = fmaxsqone; - MPI_Allreduce(&fmaxsqone,&fmaxsqloc,1,MPI_DOUBLE,MPI_MAX,world); - - // finding max fm over all replicas, if necessary - // this communicator would be invalid for multiprocess replicas - - fmaxsqall = fmaxsqloc; - if (update->multireplica == 1) { - fmaxsqall = fmaxsqloc; - MPI_Allreduce(&fmaxsqloc,&fmaxsqall,1,MPI_DOUBLE,MPI_MAX,universe->uworld); - } - - if (fmaxsqall == 0.0) - error->all(FLERR,"Incorrect fmaxsqall calculation"); - - // define max timestep by dividing by the - // inverse of max frequency by discrete_factor - - dtmax = MY_2PI/(discrete_factor*sqrt(fmaxsqall)); - - return dtmax; -} \ No newline at end of file diff --git a/src/SPIN/min_spin_oso_cg2.h b/src/SPIN/min_spin_oso_cg2.h deleted file mode 100644 index 83605f98ed..0000000000 --- a/src/SPIN/min_spin_oso_cg2.h +++ /dev/null @@ -1,72 +0,0 @@ -/* -*- c++ -*- ---------------------------------------------------------- - LAMMPS - Large-scale Atomic/Molecular Massively Parallel Simulator - http://lammps.sandia.gov, Sandia National Laboratories - Steve Plimpton, sjplimp@sandia.gov - - Copyright (2003) Sandia Corporation. Under the terms of Contract - DE-AC04-94AL85000 with Sandia Corporation, the U.S. Government retains - certain rights in this software. This software is distributed under - the GNU General Public License. - - See the README file in the top-level LAMMPS directory. -------------------------------------------------------------------------- */ - -#ifdef MINIMIZE_CLASS - -MinimizeStyle(spin/oso_cg2, MinSpinOSO_CG2) - -#else - -#ifndef LMP_MIN_SPIN_OSO_CG2_H -#define LMP_MIN_SPIN_OSO_CG2_H - -#include "min.h" - -namespace LAMMPS_NS { - -class MinSpinOSO_CG2: public Min { - public: - MinSpinOSO_CG2(class LAMMPS *); - virtual ~MinSpinOSO_CG2(); - void init(); - void setup_style(); - int modify_param(int, char **); - void reset_vectors(); - int iterate(int); - private: - double dt; // global timestep - double dts; // spin timestep - int ireplica,nreplica; // for neb - double *spvec; // variables for atomic dof, as 1d vector - double *fmvec; // variables for atomic dof, as 1d vector - double *g_cur; // current gradient vector - double *g_old; // gradient vector at previous step - double *p_s; // search direction vector - double **sp_copy; // copy of the spins - int local_iter; // for neb - int nlocal_max; // max value of nlocal (for size of lists) - double discrete_factor; // factor for spin timestep evaluation - - double evaluate_dt(); - void advance_spins(); - void calc_gradient(); - void calc_search_direction(); - double maximum_rotation(double *); - void vm3(const double *, const double *, double *); - void rodrigues_rotation(const double *, double *); - int calc_and_make_step(double, double, int); - int awc(double, double, double, double); - void make_step(double, double *); - double max_torque(); - double der_e_cur; // current derivative along search dir. - double der_e_pr; // previous derivative along search dir. - int use_line_search; // use line search or not. - double maxepsrot; - - bigint last_negative; -}; - -} - -#endif -#endif From 07f2f5e5266983d3fcec42c5e50ac19ce82903f4 Mon Sep 17 00:00:00 2001 From: alxvov Date: Mon, 22 Jul 2019 18:15:32 +0000 Subject: [PATCH 053/192] no line search for multireplica --- src/SPIN/min_spin_oso_cg.cpp | 10 +++++++++- src/SPIN/min_spin_oso_lbfgs.cpp | 12 ++++++++++-- 2 files changed, 19 insertions(+), 3 deletions(-) diff --git a/src/SPIN/min_spin_oso_cg.cpp b/src/SPIN/min_spin_oso_cg.cpp index c9f3a59f87..21927d0d31 100644 --- a/src/SPIN/min_spin_oso_cg.cpp +++ b/src/SPIN/min_spin_oso_cg.cpp @@ -73,7 +73,11 @@ MinSpinOSO_CG::MinSpinOSO_CG(LAMMPS *lmp) : nreplica = universe->nworlds; ireplica = universe->iworld; - use_line_search = 1; + if (nreplica > 1) + use_line_search = 0; // no line search for NEB + else + use_line_search = 1; + discrete_factor = 10.0; } @@ -134,6 +138,10 @@ int MinSpinOSO_CG::modify_param(int narg, char **arg) if (strcmp(arg[0],"line_search") == 0) { if (narg < 2) error->all(FLERR,"Illegal fix_modify command"); use_line_search = force->numeric(FLERR,arg[1]); + + if (nreplica > 1 && use_line_search) + error->all(FLERR,"Illegal fix_modify command, cannot use NEB and line search together"); + return 2; } if (strcmp(arg[0],"discrete_factor") == 0) { diff --git a/src/SPIN/min_spin_oso_lbfgs.cpp b/src/SPIN/min_spin_oso_lbfgs.cpp index d7e7302e4f..eba62f296f 100644 --- a/src/SPIN/min_spin_oso_lbfgs.cpp +++ b/src/SPIN/min_spin_oso_lbfgs.cpp @@ -73,7 +73,11 @@ MinSpinOSO_LBFGS::MinSpinOSO_LBFGS(LAMMPS *lmp) : nreplica = universe->nworlds; ireplica = universe->iworld; - use_line_search = 1; + if (nreplica > 1) + use_line_search = 0; // no line search for NEB + else + use_line_search = 1; + maxepsrot = MY_2PI / (100.0); } @@ -143,13 +147,17 @@ int MinSpinOSO_LBFGS::modify_param(int narg, char **arg) if (strcmp(arg[0],"line_search") == 0) { if (narg < 2) error->all(FLERR,"Illegal fix_modify command"); use_line_search = force->numeric(FLERR,arg[1]); + + if (nreplica > 1 && use_line_search) + error->all(FLERR,"Illegal fix_modify command, cannot use NEB and line search together"); + return 2; } if (strcmp(arg[0],"discrete_factor") == 0) { if (narg < 2) error->all(FLERR,"Illegal fix_modify command"); double discrete_factor; discrete_factor = force->numeric(FLERR,arg[1]); - maxepsrot = MY_2PI / discrete_factor; + maxepsrot = MY_2PI / (10 * discrete_factor); return 2; } return 0; From 89bfe4acf23eb09e6c9ab04302fb1faef89106de Mon Sep 17 00:00:00 2001 From: alxvov Date: Mon, 22 Jul 2019 18:29:24 +0000 Subject: [PATCH 054/192] change convergence criteria in min_spin --- src/SPIN/min_spin.cpp | 42 +++++++++++++++++++++++++++++++++++++++++- src/SPIN/min_spin.h | 1 + 2 files changed, 42 insertions(+), 1 deletion(-) diff --git a/src/SPIN/min_spin.cpp b/src/SPIN/min_spin.cpp index 2277281e80..9849ba9946 100644 --- a/src/SPIN/min_spin.cpp +++ b/src/SPIN/min_spin.cpp @@ -167,7 +167,7 @@ int MinSpin::iterate(int maxiter) // sync across replicas if running multi-replica minimization if (update->ftol > 0.0) { - fmdotfm = fmnorm_sqr(); + fmdotfm = max_torque(); if (update->multireplica == 0) { if (fmdotfm < update->ftol*update->ftol) return FTOL; } else { @@ -331,3 +331,43 @@ double MinSpin::fmnorm_sqr() return norm2_sqr; } +/* ---------------------------------------------------------------------- + compute and return max_i||mag. torque_i||_2 +------------------------------------------------------------------------- */ + +double MinSpin::max_torque() +{ + double fmsq,fmaxsqone,fmaxsqloc,fmaxsqall; + int nlocal = atom->nlocal; + double hbar = force->hplanck/MY_2PI; + double tx,ty,tz; + double **sp = atom->sp; + double **fm = atom->fm; + + fmsq = fmaxsqone = fmaxsqloc = fmaxsqall = 0.0; + for (int i = 0; i < nlocal; i++) { + tx = fm[i][1] * sp[i][2] - fm[i][2] * sp[i][1]; + ty = fm[i][2] * sp[i][0] - fm[i][0] * sp[i][2]; + tz = fm[i][0] * sp[i][1] - fm[i][1] * sp[i][0]; + fmsq = tx * tx + ty * ty + tz * tz; + fmaxsqone = MAX(fmaxsqone,fmsq); + } + + // finding max fm on this replica + + fmaxsqloc = fmaxsqone; + MPI_Allreduce(&fmaxsqone,&fmaxsqloc,1,MPI_DOUBLE,MPI_MAX,world); + + // finding max fm over all replicas, if necessary + // this communicator would be invalid for multiprocess replicas + + fmaxsqall = fmaxsqloc; + if (update->multireplica == 1) { + fmaxsqall = fmaxsqloc; + MPI_Allreduce(&fmaxsqloc,&fmaxsqall,1,MPI_DOUBLE,MPI_MAX,universe->uworld); + } + + // multiply it by hbar so that units are in eV + + return sqrt(fmaxsqall) * hbar; +} diff --git a/src/SPIN/min_spin.h b/src/SPIN/min_spin.h index fbc624a9cc..d6d49203d5 100644 --- a/src/SPIN/min_spin.h +++ b/src/SPIN/min_spin.h @@ -36,6 +36,7 @@ class MinSpin : public Min { double evaluate_dt(); void advance_spins(double); double fmnorm_sqr(); + double max_torque(); private: From a9a2c7a496b38e4f30f6aa8389e6f7a58e13267c Mon Sep 17 00:00:00 2001 From: alxvov Date: Mon, 22 Jul 2019 18:31:14 +0000 Subject: [PATCH 055/192] no line search as default option for CG --- src/SPIN/min_spin_oso_cg.cpp | 5 +---- 1 file changed, 1 insertion(+), 4 deletions(-) diff --git a/src/SPIN/min_spin_oso_cg.cpp b/src/SPIN/min_spin_oso_cg.cpp index 21927d0d31..843f1e48f1 100644 --- a/src/SPIN/min_spin_oso_cg.cpp +++ b/src/SPIN/min_spin_oso_cg.cpp @@ -73,10 +73,7 @@ MinSpinOSO_CG::MinSpinOSO_CG(LAMMPS *lmp) : nreplica = universe->nworlds; ireplica = universe->iworld; - if (nreplica > 1) - use_line_search = 0; // no line search for NEB - else - use_line_search = 1; + use_line_search = 0; // no line search as default option for CG discrete_factor = 10.0; } From 1f4039048936835fb84a1e7a0f21d920b28a14ab Mon Sep 17 00:00:00 2001 From: casievers Date: Mon, 22 Jul 2019 13:48:02 -0700 Subject: [PATCH 056/192] recent change to gjf tally (not working) --- examples/gjf/out.argon | 249 ---------------------------------- examples/gjf/trajectory.0.dcd | Bin 439092 -> 0 bytes src/fix_langevin.cpp | 7 +- 3 files changed, 6 insertions(+), 250 deletions(-) delete mode 100644 examples/gjf/out.argon delete mode 100644 examples/gjf/trajectory.0.dcd diff --git a/examples/gjf/out.argon b/examples/gjf/out.argon deleted file mode 100644 index 8dda569157..0000000000 --- a/examples/gjf/out.argon +++ /dev/null @@ -1,249 +0,0 @@ -LAMMPS (1 Feb 2019) -OMP_NUM_THREADS environment is not set. Defaulting to 1 thread. (src/comm.cpp:87) - using 1 OpenMP thread(s) per MPI task -Reading data file ... - orthogonal box = (0 0 0) to (32.146 32.146 32.146) - 1 by 2 by 2 MPI processor grid - reading atoms ... - 864 atoms -Finding 1-2 1-3 1-4 neighbors ... - special bond factors lj: 0 0 0 - special bond factors coul: 0 0 0 - 0 = max # of 1-2 neighbors - 0 = max # of 1-3 neighbors - 0 = max # of 1-4 neighbors - 1 = max # of special neighbors -Setting up the ensembles -WARNING: Careful, tally is untested (src/fix_langevin.cpp:145) -WARNING: Careful, tally is untested (src/fix_langevin.cpp:145) -WARNING: Careful, tally is untested (src/fix_langevin.cpp:145) -WARNING: Careful, tally is untested (src/fix_langevin.cpp:145) -Doing Molecular dynamics -Neighbor list info ... - update every 1 steps, delay 10 steps, check yes - max neighbors/atom: 2000, page size: 100000 - master list distance cutoff = 6.94072 - ghost atom cutoff = 6.94072 - binsize = 3.47036, bins = 10 10 10 - 1 neighbor lists, perpetual/occasional/extra = 1 0 0 - (1) pair lj/cubic, perpetual - attributes: half, newton on - pair build: half/bin/newton - stencil: half/bin/3d/newton - bin: standard -Setting up Verlet run ... - Unit style : metal - Current step : 0 - Time step : 0.12 -Per MPI rank memory allocation (min/avg/max) = 6.847 | 6.847 | 6.847 Mbytes -Time Temp PotEng TotEng Press Volume CPU - 0 10 -56.207655 -55.09214 33.340921 33218.561 0 - 24 10.156356 -55.092888 -53.959932 339.40964 33218.561 0.082175482 - 48 9.6121006 -55.07262 -54.000376 344.56765 33218.561 0.19529325 - 72 9.8187467 -55.16687 -54.071574 318.85979 33218.561 0.29643488 - 96 9.5421385 -55.151229 -54.086789 322.8842 33218.561 0.38801357 - 120 10.295035 -55.12919 -53.980763 332.00171 33218.561 0.47607262 - 144 10.331608 -55.09907 -53.946563 339.28896 33218.561 0.57389224 - 168 10.154698 -55.058246 -53.925475 349.03253 33218.561 0.65481471 - 192 9.858198 -55.127583 -54.027886 330.09298 33218.561 0.74437734 - 216 9.6658918 -55.10812 -54.029875 334.28383 33218.561 0.8278495 - 240 9.6801591 -55.102386 -54.02255 336.27242 33218.561 0.91167379 - 264 10.685658 -55.046238 -53.854237 355.0448 33218.561 1.0023789 - 288 10.387727 -55.08427 -53.925504 343.87247 33218.561 1.0960371 - 312 10.231132 -55.120428 -53.97913 333.22463 33218.561 1.2382998 - 336 10.20896 -55.075142 -53.936317 344.88438 33218.561 1.3420489 - 360 9.7876538 -55.165008 -54.07318 319.14962 33218.561 1.42782 - 384 9.9872551 -55.13881 -54.024717 327.82471 33218.561 1.5417666 - 408 9.5362734 -55.063733 -53.999947 346.50545 33218.561 1.6328366 - 432 10.262638 -55.126608 -53.981796 332.16342 33218.561 1.7242996 - 456 9.9228239 -55.122119 -54.015214 332.26261 33218.561 1.8124888 - 480 9.7026324 -55.17057 -54.088227 317.84818 33218.561 1.900233 - 504 10.028762 -55.082465 -53.963741 343.04257 33218.561 1.989605 - 528 9.8227851 -55.121222 -54.025476 332.42857 33218.561 2.0708802 - 552 10.208672 -55.100242 -53.961449 338.68109 33218.561 2.1527217 - 576 10.180849 -55.124065 -53.988376 331.29516 33218.561 2.238126 - 600 9.6467252 -55.119533 -54.043427 332.43109 33218.561 2.323443 - 624 10.041885 -55.173802 -54.053614 318.48579 33218.561 2.4046151 - 648 10.151597 -55.111725 -53.979299 334.66227 33218.561 2.4902161 - 672 9.7719111 -55.060111 -53.970039 348.55249 33218.561 2.5800372 - 696 10.476688 -55.088109 -53.919419 342.94922 33218.561 2.6731395 - 720 10.517805 -55.113604 -53.940327 335.47342 33218.561 2.760651 - 744 10.006466 -55.045085 -53.928848 353.53813 33218.561 2.8537894 - 768 10.201492 -55.081598 -53.943606 343.3206 33218.561 2.9404115 - 792 10.117738 -55.077806 -53.949157 345.31093 33218.561 3.030765 - 816 10.362288 -55.11635 -53.960421 333.9045 33218.561 3.1177356 - 840 10.204164 -55.097619 -53.959329 338.82717 33218.561 3.2091886 - 864 10.147722 -55.101372 -53.969378 338.19682 33218.561 3.3003742 - 888 9.9265037 -55.111394 -54.004077 334.08116 33218.561 3.395341 - 912 10.206403 -55.132181 -53.993642 328.89904 33218.561 3.4882881 - 936 10.28639 -55.093317 -53.945855 340.61244 33218.561 3.5764735 - 960 9.8028822 -55.078802 -53.985276 343.5904 33218.561 3.7056267 - 984 10.492755 -55.121321 -53.950839 334.62697 33218.561 3.8055611 - 1008 10.621569 -55.088588 -53.903736 343.33166 33218.561 3.9144807 - 1032 10.006729 -55.113459 -53.997193 334.43025 33218.561 4.0189888 - 1056 10.099853 -55.068035 -53.941381 347.42158 33218.561 4.1391664 - 1080 10.254232 -55.066685 -53.92281 347.15777 33218.561 4.2443953 - 1104 9.9495142 -55.13686 -54.026977 327.63107 33218.561 4.3368342 - 1128 10.377108 -55.08846 -53.930878 344.13083 33218.561 4.4287748 - 1152 10.036981 -55.114643 -53.995003 334.88053 33218.561 4.526868 - 1176 10.144779 -55.097125 -53.965459 339.698 33218.561 4.6614049 - 1200 10.075844 -55.14695 -54.022974 326.05911 33218.561 4.799835 - 1224 10.183695 -55.121716 -53.98571 332.75772 33218.561 4.8908897 - 1248 10.581369 -55.027954 -53.847587 359.06251 33218.561 4.9839788 - 1272 10.158269 -55.105173 -53.972003 337.52964 33218.561 5.0918646 - 1296 9.8776072 -55.064085 -53.962223 347.15648 33218.561 5.2291209 - 1320 10.38161 -55.118366 -53.960282 335.17767 33218.561 5.3570446 - 1344 9.9528146 -55.141937 -54.031685 326.27117 33218.561 5.4584705 - 1368 9.8024326 -55.117808 -54.024332 332.99835 33218.561 5.5557818 - 1392 10.35447 -55.110235 -53.955179 336.80412 33218.561 5.6467392 - 1416 10.199061 -55.105641 -53.96792 337.36785 33218.561 5.7476527 - 1440 9.6868779 -55.087316 -54.00673 340.9166 33218.561 5.8432207 - 1464 10.093238 -55.049436 -53.92352 352.27563 33218.561 5.9471521 - 1488 9.7578808 -55.123935 -54.035429 329.93926 33218.561 6.0495014 - 1512 10.099979 -55.205426 -54.078758 309.26166 33218.561 6.1612976 - 1536 10.172944 -55.087106 -53.952299 342.93395 33218.561 6.2506202 - 1560 10.51771 -55.107635 -53.934369 340.1967 33218.561 6.3379856 - 1584 10.044994 -55.101362 -53.980828 339.03163 33218.561 6.4362567 - 1608 9.624758 -55.146246 -54.07259 324.32486 33218.561 6.5385845 - 1632 9.9135215 -55.097278 -53.99141 338.69162 33218.561 6.6452786 - 1656 9.863681 -55.070523 -53.970214 345.84608 33218.561 6.7518212 - 1680 10.138513 -55.127065 -53.996099 330.40757 33218.561 6.8775188 - 1704 10.382237 -55.070572 -53.912417 347.074 33218.561 7.0126448 - 1728 10.72487 -55.081147 -53.884771 345.83623 33218.561 7.1384216 - 1752 9.829431 -55.131041 -54.034553 328.57652 33218.561 7.2616419 - 1776 9.9135662 -55.100556 -53.994682 336.52238 33218.561 7.4193201 - 1800 10.41873 -55.097116 -53.934891 340.24798 33218.561 7.5570544 - 1824 10.151782 -55.03231 -53.899864 357.3654 33218.561 7.6872905 - 1848 10.42307 -55.043808 -53.881099 355.71677 33218.561 7.7933885 - 1872 10.276862 -55.085016 -53.938616 344.46273 33218.561 7.8887472 - 1896 9.7681373 -55.146507 -54.056857 324.84323 33218.561 7.9977923 - 1920 9.6624824 -55.103214 -54.025349 336.06397 33218.561 8.090235 - 1944 10.153504 -55.049175 -53.916536 352.36339 33218.561 8.1923703 - 1968 10.191954 -55.098741 -53.961813 338.8667 33218.561 8.3320906 - 1992 9.92167 -55.117079 -54.010302 332.96497 33218.561 8.4774437 - 2016 9.5737281 -55.091141 -54.023178 339.41837 33218.561 8.6149527 - 2040 10.600908 -55.092717 -53.91017 342.71852 33218.561 8.7639523 - 2064 9.9214513 -55.099904 -53.993151 337.46799 33218.561 8.898087 - 2088 9.9256258 -55.082224 -53.975005 342.85042 33218.561 9.0130784 - 2112 10.345379 -55.112923 -53.95888 335.81471 33218.561 9.1422766 - 2136 9.8876649 -55.079254 -53.97627 343.05764 33218.561 9.2885707 - 2160 10.04492 -55.074876 -53.95435 344.82419 33218.561 9.3876103 - 2184 10.028705 -55.063961 -53.945244 347.70549 33218.561 9.500967 - 2208 10.412572 -55.136316 -53.974778 329.8188 33218.561 9.5900362 - 2232 10.404205 -55.09913 -53.938525 339.77542 33218.561 9.7048353 - 2256 9.5694135 -55.139021 -54.071538 326.37473 33218.561 9.8045958 - 2280 10.244745 -55.134529 -53.991713 329.19392 33218.561 9.8968908 - 2304 9.9129922 -55.116192 -54.010382 333.14326 33218.561 9.9818651 - 2328 10.167027 -55.08241 -53.948263 343.08135 33218.561 10.068683 - 2352 10.262045 -55.144327 -53.999581 327.40876 33218.561 10.155937 - 2376 10.520934 -55.073147 -53.899521 347.6998 33218.561 10.246316 - 2400 9.9628692 -55.122001 -54.010628 331.25369 33218.561 10.336833 - 2424 10.565531 -55.157113 -53.978512 325.14897 33218.561 10.452039 - 2448 10.03709 -55.096409 -53.976756 338.29607 33218.561 10.537936 - 2472 9.384311 -55.141821 -54.094987 324.23247 33218.561 10.628689 - 2496 9.8019362 -55.105685 -54.012264 335.97239 33218.561 10.717287 - 2520 10.31114 -55.078831 -53.928608 345.42395 33218.561 10.818756 - 2544 10.407237 -55.148382 -53.987439 325.94421 33218.561 10.910801 - 2568 10.257967 -55.041348 -53.897056 355.73261 33218.561 11.004221 - 2592 9.8425807 -55.139428 -54.041474 328.28096 33218.561 11.101295 - 2616 10.140697 -55.100238 -53.969028 338.76319 33218.561 11.192211 - 2640 9.7102818 -55.136288 -54.053091 326.7053 33218.561 11.280277 - 2664 10.120372 -55.128779 -53.999836 330.71707 33218.561 11.369001 - 2688 10.232537 -55.120614 -53.979159 333.35087 33218.561 11.464652 - 2712 10.032526 -55.094761 -53.975618 339.97984 33218.561 11.559387 - 2736 9.8791 -55.121998 -54.01997 332.32556 33218.561 11.649679 - 2760 9.891483 -55.120919 -54.017509 331.32614 33218.561 11.742604 - 2784 10.201053 -55.165525 -54.027582 320.39272 33218.561 11.85274 - 2808 10.238648 -55.096449 -53.954312 340.06316 33218.561 11.939782 - 2832 9.8692851 -55.068632 -53.967699 346.77535 33218.561 12.036655 - 2856 10.179976 -55.128413 -53.992822 331.5662 33218.561 12.123227 - 2880 9.7656315 -55.1468 -54.057429 324.02612 33218.561 12.213117 - 2904 9.7991628 -55.049191 -53.95608 352.45738 33218.561 12.326761 - 2928 10.581767 -55.093293 -53.912881 341.37292 33218.561 12.417633 - 2952 10.546144 -55.07452 -53.898081 347.02025 33218.561 12.52701 - 2976 9.8306008 -55.14762 -54.051002 323.45715 33218.561 12.633522 - 3000 10.033532 -55.076433 -53.957178 345.36812 33218.561 12.72627 - 3024 10.046266 -55.085775 -53.965099 342.47786 33218.561 12.816242 - 3048 10.176777 -55.133013 -53.997778 329.04144 33218.561 12.903175 - 3072 9.9778064 -55.143787 -54.030748 326.75284 33218.561 13.014329 - 3096 10.516223 -55.110144 -53.937043 336.802 33218.561 13.104673 - 3120 9.6561157 -55.138699 -54.061544 325.6652 33218.561 13.207371 - 3144 10.237043 -55.060968 -53.91901 349.44011 33218.561 13.303442 - 3168 9.9704264 -55.123073 -54.010857 332.19725 33218.561 13.391877 - 3192 10.493307 -55.144402 -53.973858 327.15485 33218.561 13.482857 - 3216 10.022171 -55.141782 -54.023794 326.08249 33218.561 13.574484 - 3240 9.6957248 -55.137865 -54.056292 326.04858 33218.561 13.671408 - 3264 9.9685299 -55.124301 -54.012297 331.9015 33218.561 13.760186 - 3288 10.413707 -55.153604 -53.99194 324.32939 33218.561 13.877604 - 3312 10.022953 -55.103422 -53.985346 337.52066 33218.561 13.977562 - 3336 10.044478 -55.110297 -53.98982 334.48379 33218.561 14.065563 - 3360 9.8593734 -55.130623 -54.030795 327.71748 33218.561 14.15952 - 3384 9.9269422 -55.107979 -54.000613 335.18173 33218.561 14.258064 - 3408 10.288049 -55.092276 -53.944629 340.71484 33218.561 14.36211 - 3432 9.9702156 -55.08732 -53.975128 341.72171 33218.561 14.452123 - 3456 10.246178 -55.091669 -53.948692 341.62844 33218.561 14.555775 - 3480 10.559292 -55.086917 -53.909012 343.70626 33218.561 14.645718 - 3504 10.652207 -55.050897 -53.862628 354.46979 33218.561 14.797422 - 3528 9.9835266 -55.0557 -53.942023 350.74747 33218.561 14.895716 - 3552 10.240934 -55.123217 -53.980825 332.26434 33218.561 15.023796 - 3576 10.406519 -55.093536 -53.932674 341.54029 33218.561 15.203252 - 3600 10.406733 -55.095168 -53.934282 341.22192 33218.561 15.303986 - 3624 9.9877484 -55.154231 -54.040083 323.55633 33218.561 15.398883 - 3648 10.391829 -55.110208 -53.950984 337.09219 33218.561 15.49042 - 3672 10.368995 -55.069591 -53.912914 346.82649 33218.561 15.582259 - 3696 10.362939 -55.109012 -53.953011 337.32216 33218.561 15.679316 - 3720 10.465254 -55.136214 -53.968799 331.22288 33218.561 15.773303 - 3744 9.8238226 -55.10114 -54.005278 338.12616 33218.561 15.86905 - 3768 10.205504 -55.101263 -53.962824 339.04196 33218.561 15.960072 - 3792 9.9589987 -55.118883 -54.007942 332.84318 33218.561 16.047055 - 3816 10.253382 -55.117513 -53.973732 334.42101 33218.561 16.148412 - 3840 10.262393 -55.069549 -53.924764 349.084 33218.561 16.235391 - 3864 9.7367167 -55.078288 -53.992142 342.48207 33218.561 16.329112 - 3888 10.171202 -55.134701 -54.000088 329.5847 33218.561 16.415353 - 3912 10.01925 -55.145139 -54.027477 326.65074 33218.561 16.526334 - 3936 10.053638 -55.038151 -53.916653 355.74893 33218.561 16.618524 - 3960 10.044055 -55.058382 -53.937953 349.01834 33218.561 16.712577 - 3984 10.382422 -55.099216 -53.941041 339.28099 33218.561 16.79941 - 4008 9.97927 -55.09284 -53.979637 339.07225 33218.561 16.904198 - 4032 9.6782319 -55.126143 -54.046522 329.0201 33218.561 16.991454 - 4056 9.6593809 -55.123677 -54.046159 329.89833 33218.561 17.097172 - 4080 10.442896 -55.141149 -53.976229 327.9899 33218.561 17.189364 - 4104 9.9571109 -55.08588 -53.975149 341.3746 33218.561 17.294147 - 4128 10.44943 -55.087946 -53.922296 343.09435 33218.561 17.387357 - 4152 10.040581 -55.171939 -54.051897 317.85348 33218.561 17.500905 - 4176 10.089442 -55.128713 -54.00322 330.29121 33218.561 17.588891 - 4200 10.316156 -55.123219 -53.972436 333.59382 33218.561 17.679254 - 4224 10.177245 -55.095671 -53.960384 339.34498 33218.561 17.770569 - 4248 9.7129183 -55.135335 -54.051844 328.25125 33218.561 17.857728 - 4272 10.231838 -55.099554 -53.958177 339.64015 33218.561 17.944226 - 4296 9.9737677 -55.117885 -54.005297 333.07248 33218.561 18.034105 - 4320 10.004955 -55.116155 -54.000088 333.52271 33218.561 18.129644 - 4344 9.5938901 -55.133824 -54.063612 327.84171 33218.561 18.215476 - 4368 9.8954562 -55.131603 -54.02775 329.0813 33218.561 18.306539 - 4392 10.439732 -55.100379 -53.935812 339.81679 33218.561 18.395651 - 4416 9.934513 -55.08449 -53.97628 341.74441 33218.561 18.484506 - 4440 10.025998 -55.136771 -54.018356 327.73718 33218.561 18.593946 - 4464 9.9304451 -55.101817 -53.994061 338.1801 33218.561 18.684011 - 4488 10.344371 -55.085856 -53.931926 342.91721 33218.561 18.782399 - 4512 10.033193 -55.091778 -53.972561 339.85728 33218.561 18.879666 - 4536 9.2361614 -55.169375 -54.139067 316.67597 33218.561 18.983667 - 4560 9.5786289 -55.179976 -54.111465 314.76415 33218.561 19.079009 - 4584 10.071651 -55.107218 -53.98371 336.10364 33218.561 19.163975 - 4608 9.9873098 -55.109348 -53.995249 336.03665 33218.561 19.25635 - 4632 10.143888 -55.119423 -53.987857 333.74978 33218.561 19.346658 - 4656 9.7506264 -55.114772 -54.027075 332.98271 33218.561 19.435425 - 4680 9.9616769 -55.096054 -53.984814 339.20499 33218.561 19.55562 - 4704 10.271313 -55.074522 -53.928742 345.87397 33218.561 19.642652 - 4728 9.9172336 -55.098805 -53.992523 338.06318 33218.561 19.734557 - 4752 9.9556222 -55.12128 -54.010716 332.66408 33218.561 19.83859 - 4776 10.197593 -55.095293 -53.957736 339.50067 33218.561 19.947471 - 4800 10.145085 -55.108467 -53.976768 336.05115 33218.561 20.044183 - 4824 10.205523 -55.147376 -54.008934 325.56559 33218.561 20.144393 - 4848 9.8900281 -55.121598 -54.01835 331.17401 33218.561 20.243197 - 4872 10.03655 -55.100936 -53.981343 337.6777 33218.561 20.336043 - 4896 9.8120635 -55.087507 -53.992957 341.42438 33218.561 20.425498 - 4920 10.615354 -55.093335 -53.909176 342.30776 33218.561 20.519318 - 4944 10.374366 -55.06455 -53.907274 351.10607 33218.561 20.612312 - 4968 10.677474 -55.147807 -53.956718 327.85703 33218.561 20.719371 - 4992 10.558882 -55.145253 -53.967393 327.427 33218.561 20.818726 - 5016 9.4097946 -55.150835 -54.101158 321.62641 33218.561 20.914472 diff --git a/examples/gjf/trajectory.0.dcd b/examples/gjf/trajectory.0.dcd deleted file mode 100644 index 47927e9909cfcfc86ceb2568ba1660efed5834f2..0000000000000000000000000000000000000000 GIT binary patch literal 0 HcmV?d00001 literal 439092 zcmeEubx>P-)a?m%rApmsu_RbsfbNyL3nZbgw72dqgu2rf66!*Wph-<^4HzCT{SnRe#fz`5b@<0pHsz1G?Z5d@)KufFZ2{QB$P>mq{S zx$A#^`5*ohne`=5@*nR0#~ao8RtR5v`Eue*J$20V>0uM=51&)NJ9_l!9nAOsEC2d- z=z+f7g6p@N8a8Zt*vR_+t?GB3F@BD`u^)dmY(-ooB;CH&xri%ET zuA4oq_?@ow=`!BWzt1%zO2F@Q-Rz;__4<9T8bx*Zovt>IO!%FyvFSGaPS@{rwtkJ} zcRE|Y#_~IztzTpLozB*;vHVVF>(^L*r?d5IEWZyj{Cgz76E^%cmfr~*{u;~ggbja< z<#)n{zsB-AVZ&cz`Bj7cy8bPX{aZfyx48aq@%7*0+`q+}KjZlucm0{4zwz*Y|NZly z^9uhKzyB?c{#!izx406a6%_y3^>2CX&v^cxuRrtiH;?h3?VVrue!uzo&pD1i`Rng` z`AwmAq{^8C3;fH?J0RM1%|8Q9Ua5aDK z|IJzbnTJ2~@aMez&A0!Vhd=Z1|1Tc?%}M{mz5bJf|KY0t-2XE_|L_O@=mr1q;(zY{ ztq=T}hd=Z1CrXpm(Y^Am!1@=C8=JhlmhR%a#ke$om+@u8W5&4T8^#Y` zoijr9a{~siOAZXaC=2*xhzXqXBRk#p$|e0-?qXx>Dl?56{Er64F4+~BwoYq&xMO{w z-?^fJx+UR(`$BvIr>{>Ae7df6z_=CF(^p>$HokaVGH}(bqv>1RPa2~ZA5ZTX*|<%& zw+Y6ge!Bvve|i-7zar8sq2G8`u^Xug3{n85=5-DollSAt##j;B>3>qcJ`&LpsnJ>fDZBm>Llp!UVy_6lL_&8jO zOD*M)?2;kOKLVMEz@2~yTzjR##UdJvpRB=kYmM&@~kE2TVQBvfvnJiz78t}b+cl!s};M{RtS@=2>)(@ z`Mw2Dy72oV`E`i}m#$mk+0KH`v#nU9v|_8t0!MQzKJ3ZH#urvZTP<)sW5v#4R$PB( zL9tH0)X*-cjVpZU&~Z;{V09(0=1s`?jwhA)+K_%u^`^v{Ze$$jP8~+esq;Z8#gF%< zBQCy_(a?*2UTaQaUd^fTTwf|$LQdU}HK6IwdRlm}Z{6D+V z?j16!e_Bpube_~_mIpQN=tdJ}xYGP8a+)#Pk8-mMsdGC4g{=#zl#_t0>xDF`xddwucTlxd2PM~+VEy?} z+`rrpYnS!I&^jSVa8g0nUX8o0RTwc*3F~t;BBrX)y@nD!SB2nuloB=Ph9ES~; zimy>YdQ^q4$3l@cQw>+O3Om;X<3)f9p@k}hPg0@xLN#8VP@;=G1T{;kvAKj2i&m>) z<>&7AP~kxN5EQMa!u*#iOzN-2fnz!}?HL2@LmfsO*J5rj9hxU;vFU&gmlZlRiq_#% z10Cj;(jl?54(9^3i1XFLRU3_%3R)cY(V_8kEo?P)XfacV_K{jVpQA;sfm$q|sfFLK z=QPn_$zd%@6>2f8l@3z=9iQ&$kbF~z{RKLd=o^EeTrG~4FvGFjgarposI}XSEsxDO z^3#L^uT3ztF`?X66TVh4A^cq?R8vi;KGTf1rOjx2)`VkS&4^l(iD&0BK_ktm`6v@b z@0c*Aml*~Z6NC!)2%)O$;_%cw|Gp+IFPP%7JNt4Ks_` z(QByooK_hoE*3{vq9x-$6u4|c-h>JaxpfNBS2qDg4;8GlI@xV z?t=u3kC31QpPNs$1(eS#q$xoH+-?fE(b+*MLLm)XQb?uS7Sh@1-|R09?ItWaV=MS!OR1U$7}H%1q_&wOZuA(ZO|`4xdkG z(e{BBg%$YcqqTUmUk9(TI?R}%#oj?$M4r~-r(O%y2_0fP#UQL=48D5n;9}I`VJbgY zn}y!dCXDN3hIXeJ>lT`Dkk8!K875pYW}?keGae^o;qnPSLoZDb4w+DIxCxWyn31*A zghp}vvzeJZPbTDEG$H%32@9v05MwgIZ?g&G`MjO3YR1*=CKP-#!DW&e&)S-?rg9d} z$;=!}%xF>Bj8wG=8#N}pt6;;vB{mdpx1o7k8>*DEq1*>EYz4n4mf8g9c}y$v@UIS6lJ zgTBy)obfg^`Iv(x={776%99&9|++B?19+AyQa`IfQd)pEw^ zD}MykKD8#`_4(QXVV(m5;&+ZUmP-f=+&k;@iT97+rN3+RDLt()<;2s0D+A-d8v{2M z>ze+odX$`KXH~Lm3ANN+whG@yZKpt7k+G`m$2J-nVs&5P;DxZgmdoDylt z?L=C1Gm&$iNJXyb>GkY1YHv)Y1G;1yo^GJ^u8EYSHBkBaNfdc1nfhJR(|UOlZ7wcS z&>cP9SeHzZIzmbBYBRsETwdCS|O6pnq=y|IGJ*T4HSG? zibFqSc-}{bB3r%SS4#^03ON?+_r@NH96!IxaBiFo@88H!r7Qalo67OIryR@r%iujm z3Xd6HxLrYppsF(1S9!s8ycA_i%3$>OM&qk8ge>wzpIb7_GDzWCSBk@sggRwA}Aeyhd!F0_~dy`M1#93*1!C_NlyL>zv`IFg_B@-Smb zlOEJvMCw`*9W)|JToSRGzdp*iFp-~On9jJ<*MNm<40yIpM5loU^y1&wzm^D9pam|= zEht&aigPovQ6t!jF}tl;UEhLXdACq!niYYSt;j#cSg@xB1DjY;ow20xwiRWZtVmsK z#hxe&&iY!hILv~h@fJ+DVSyk2zc>8e3qP$GcisXF%frYE^WwfcOH&se^&^^XhTSgR+Uke9` z!4ArD7LdZ;@GbAvDCMU{SQ{1IWQV}1w-VWBwWyk=#T1Jc5sWibjkVY|Fb1t_n9-zx z2}X?>@`6k(Ich@Hsb)0bIB*&^)Gn}LK^+_RF6S7K%V*zHN_ZzD*SY>QQ^)!7rZ>Hf zlv0hF1vFw#0X^IzU~E7k>5~N1>mWgtnd5u~HTI2DLH&*M%;gYt@KR&+869Gd=org$ z9M052J6ns`k~%D(WyaL`CS2WQf-J^_E8-4NoNlQWm%zrPz=+zQD@^DaH#;QAg`{B)JC05=J zL1o5~_8w}8ob&4SkKvr8L%E(h%x3JBR8@yl={ls|HsL*wq46LyigTQw*xif^pG+t{ z!HyanV@t2%I2mNaF2*&Ub8Kkz)Qvi~_oU4AGTNQwLt|$7(&|o4=mq27LG2}&A{S83 zPy}=@{<;oCfSR^f|>8mhKxBwN4J)pX4BE zr457L%4qfyciPykDQ#`slsZ3hBUu?A8g7+fd0k$w0Y#7zEWyC@PIx1A;u=r|d6y8p zAFsr)bTx)IQ(^D{HT*e$uRj}&p3gYvkJqAE865_3{x8>>=V!19yRMo*3KLAvP3Uhl z;REB--4An+=4XTAnhom295lPfzWik(-SRY$=4%Qa_fMk0N_uKh#z5{)9D8?oVLr#= z`PJp9+FFY0XQimnm%Z4>G`PMu97A$7_&QjFJ)<;m_7u@=j~-9Y=ppN>hxomMn&WJR+`D_Y8}comq9xZ#4rHbqcWlt~mXCkl$#k`jgI89{NeOcH&+sHfOr zDWpkGpz^y!GOLm({;m{0O}*gJObSS)xYtXD_=9phB>ubLGbs#+oPxV~Ms;L9zpgEv~y?w+6+-$PLJ_$ep` z$R&z1vjxTe6hX18auPMXmq^ZgQz&q3DoyKUpo=f`w7I+tBWKAmH(CZ8&sF?68Agp} zKEx{mpEER=+L-f1)d)oY2*=GG5pYY@BQ-$861@S_jd}z-889#?8PnHVF^OyMvXipm zQXw1F`ekEG2P-l~K`|&*P@LmAn*B{s7&-}x>URW1dELgqPo zda3k=?Vb!-52bK=zr!Mli-4JVmc^gL z;jvnSTAWwAAJt%POBh-R(d#yN=#J{`1fi1jNyQ2j~mQ_$ZYb_|AY?M-k{vLFEvy@tN zbEirHo-{F3N_DsfscvxmYP3d0u3xPCxaP65-sz`Aoi-uZd{~W2AC*Xdri9Kr6s1zM z8233ECpcF`*3)4!*U75SIvnEqvjSuE<;zUi!1-&x#0<9;X54#YL(%zm7zf)?cc%^2 zAKEY>g6qkZKJ;OQCymT$N@dn~)1;~%lyXB(Z9)oZ#=b(DKdg{!oGT9W6wq*<1VU34 zTs=cjuqFgyJf7wWYLp+X#@1mvv|Oact@~OuPt;*;dmZl9)nQaEGbYHhuxxrJsx!t9 z|6qo2g)#nZ8>aI(#&@wp%(ub+tqu7FHmq`Ur&0BNsmX&T^w+_rw4_i*&j&Rm=VB5Z zt}KB$$wA(nQ$JR5P>oGLX(PvCLwOZmomPUbD`D%UMhQtMrcKtN%v~KKIiC*C(qb0J z>zkEhkmb)jKtD6iyJlfndoxT$*zp3K$k<2tpK6CPx#P`;5GQs!GyGgTP%NQH_j z6=H{IQP!E~$c=OQel6a%)1iZJ40E9-Y;w=Sz1Jq}m-0HbG-JSh6Gn3_lmC_TC+GFc zoJ;48wPQh`9pN7v(qBRT^mw%|Y2Ub!S9^cjztfvaxp7|K>V$Dx2~Ho9pgz~q-I@uw z_gw|g`AQ`9<9T_k!m9ad%$&^iXOI>Zm{*y>S6i+J144AD)JKP}%%2=AYewH!nb>sC zgeqL~EjVIA7U!#4)wvGZU_;AV%v1O?{^9Q%>*Z8=tS?E<`_Y>VGCDp|PPx70l$apF zh&DwaOXAvI?SxBlMbLT^*V%a?cziGzUoWXpwyGKd^O(EZq(oj79e#2?eKw2d<$N@5 z9pJijlolt~WMUkTq4Taxp5kVv(gNpH>M%)9rL{8L8X`sCI^HO&mm-tvjY^-q5G^qFo)V4`jU#a05sv0x zHF&i?0uck4V@+dB%yIGg+ay>^8sHowq9$YCCUvbCFvNnC0t*uAGhY2@!CQl%n7Tqx zTrvrYv;KnO`X)g!ier*yTmrS*BvS0qM4InsAblSLedHSJ$8ISC;=FL`iWEN=b1l<@ zIqRu%eB)T$YP|-z91H!F8pw?rG&rHb>v5b%n}~?K#u$E}i2k`EauY=KZkCOk9#+h$ zlMR1!gLf<#E=UxwKL`prkE3avpy<9*P(0ruD4H!#qAiz`Y16h;a&MPH3pOND zkTchcDlb$Ik>mCmFMLRm!}XgCj$k=9; z&U`zMNf;Y}fIK}iq6|3nUc|v@JuD^>ZAiq8^;XPlm5nfWD`p}a3olu4ylpnRa*lX0 zSy22u!E2N*C@wq_6z_QrzdT5xr!5RLym>NR*)P%u_e8o;-#`lsvc4XEW~Me93O zsE1n6lrd0zCo7IK?s&98P{b_YaXb|iR~Y{k%j5mTxphXqNVd2X8t9Qs*+)eRu9iy6 zqeLn_P>MO*Wmv>mV|G7ptT--1g{eMJ9M|C3t%az~`&wBd9M1=9@HSF|9dD8l+k*GA zj~?fEZZbKyFYLp)_1i6k@Z5Avfvqcr;CW08>a{YV zq?-*m=0iQtNpNYq8Yi#oaPXT6Kl<2k(M3+FOPMb}7J{cjWOrS7FGbXk;;_-dMs8*EKS_9Oi@(ZfXR-(Ly|H#*Hy{)Qk0`!9yfiwLcg` zuWB(=W5Tq{oO_L~w7YU4xx8T>akUnSW6aF!b6uGurwLCSRFwI|qD6Js!|(4kI0ue! zKYBRd39UWVn0!HtO4m#{Q`U|IVFvOQ`x0K*pwi0^I zeTAcWe&*RR)n86yo;cx9t`bAmYf-v{2{kx=N9B0123SamZIo!wIr9#4dOarQARx?@ z7R3Ift`k&f8>&TzluW!}?yF4`DLu<`(1LMFjF9UvI@N^qQa1D`*@#ZH65#wqiNGT~ zZ;ee*)wkj4Vkt?SB?!H$f=gd5c3sIt+gEapvq1>Z^Wn6U%bbILcFcv#bp{P&Hh zjrfydoz-Z;CH(Z1~W&Astmq@Ogm>x9Y|~w=4@e$GLvXa;5y!4l<2ZV_j$FSDnpx z$uvUhCAo9;m_YaR6cuMnJSrbF#btdFeZ+Hg*N`o+<13m;}53kFrs%CUxEO*`6i=t2R{JVr=*IUM^i%sas zwQnb7BidY1f}TTEaChS0+dC88m)o$Sg*W9^74W#G3O#>BBP>1>uOj)J#`;mkC#*5> zd2iU0apmMp9C(|9$}1T+*K<&UZwS(OeLaIsI6TjW;!WMiBf>#4=A4LeU*%IKL@8}J z9@Bs-%N;a)w-S~b96uYG5LCyG_$M;@YpQ^YrPUac5RDHmCM5BG(*=1_r633CE~_w} z*U_vqA#F2r*1f!GMK1vzSU;%7^Ru~rCW4v!IPKv^LiYly;;X{;8Zmf(oN-)t){VM& zQQSxYJFIFvHEZF-T>OB>{C<@uZC)kdD?g_m^ZskwG1i*Tm~T@Ps<@H0$wg{BzQ+8E znYoQ+{P)iHAn}-k4%H6Dq`^8|FVA`#YfiT-x>IIT)?*@7=)mzI*~bLeNjALqkWp`c z2`U7uG5fL(o;OWsKaRQjK_2wpA>dj|HST}bVoQJ-b*I^J@n|E8$rtebg9;6%>9D%E z8J8;C;1uOW?k-N)^Enu2Pw7}|&P4P1HVm)oL&M%M2NwWzE(Pre#%Rz}|UNpG8 z6DEOqK>m9bWlh+;#D-bJlIVUvDXO&4U|~DPRm?eFm@X(JUlVD6TQBq-!1Zyk9tT{l zNZBVS!p`X_aIGimc8|dIED@8RS&+z>YTt<@YSPpjuTE$Xvx;lf##W5Y78DjSg(~&t zdYgIP2A&3tQ)eTqi=g;k$w0B`-Vg_AaCZ@NB(iJ-_Z1Z9$0gJE<6cR;14q6mDx1=+z!i$R3BozDdNpZWaWLWsV?IB(Jw# zxOXWWPgaXK!kF-)Mo`>+ucx~r^W=>*cr;CfUSfqjR!|I=rqcI4jE$M&F7Rhe$DHqY z{(GOcOQtW7!@%|U66SD(4;H-NEhwVzi=-C4kaj2>$38F)9b-kE5J90kqNias<>)w5 zgRDqBG&a`$8w-k4PRVrUvJ4c@n06NP$_*@7%v{E)+KE)^xfJ{V(!kn-@!BE_z*tpX zN>9-|Z?#)%P{WvnIgF3azY!G6w&9BU#pF#KR1q&M^M^96-@mYxR9m0}U&-sN-j_{P8Y zR98VEP7=vC#2e<1;V}0RF@1s+O|A-x6GaX5&cQhGp$6ABifF)i{E@$)7*RQ%Qe|>< zn;n6xLqxd5G7dEhilkA=^u|?&vk4mPZZ6_(t_4@O3JOmcsJ^olA*aJJll>{h7h0iv zA}F*iQfTHiITkL}z?d)MyVZi$%-cydX85y9G}C97p>k+WOfGIebpH-qGXbCo5JmkF~g?ft;SnaD_Cux>}EL?`&NE$b8^> z109fhV{t|}igOKCvJ2}Te+dfvz+`GxC`H3W4U$i=CbOS?FU=*2!Ab*7<61^}K!d_r zdc;3qZfG#i&j&qq@|9wfgx7Zh$ANOJo9uPq(c45iv{!})-8GoRf7gjhR&37{6y^IF z=oHsMpIJMSeiso?J{z~^alGnmpwqG5P@fD(!v?(WT#p_ZEK$IaLYov`%oi-gD!U$a zCt5KyNTOKuIGHv^d0|W**O$liD4$_L^mswh@)&c6UFE1aUjv0R^MB`Vq0bOO@hwVE zzVEzn>G?t=*A&rWo)yj?9jG}kiFPlQA^VaBk3B_H$+Mt11jVC^i8Qc<3|)t7@I$S~ zj9wO;Ud?s!W03}~^@6`O91%72khizsS|veIN@1XSC48_$9f36$li+aT`fRPBsPH<0 z6wf>naaDtLkJ-nRmW|#=ne!YFPf<5yc*JpLcx@3im~*>RPEd5-&-=5M3?IH|(4FhQ zp6M2BE5B5)#B&ov!$!pVXnHztwfeWX}>mdC^AT06&za*G7TD=~qVAM!@SKn*JL{-1x@ zio<;b#bQP6qqTWwIA@Dp@KPKbc%JFlCh)2%ZXw2*NU-dJlA3d4gq1buj)yNTn^FsyW z;i>!Ew5~QaaQ36>K|{+f2$-Lpi6qo9 zP-ou5jsT9c3uMquWbdL?j)N)Qu)dWds*MbJd~d>R&QpD**t}SVz$r4EIK**Z!5kCo zBXKvScx02I`g|E`ob@ag(1}v6~bR z&&wdaD1+&k9OwD_-dp7edJv9q-UD-XuqUxq1d_wp)99l?_Bi%6#%WO1s=YatXuo(_+IyLtQ)IAAU|hA z`3O|)7J-<${G7CfSkqO56MP11TnNW1_Dp8*{*SrHnh$Fh3;3KJKgu!lnFw`H_BX!J zBdnjEIb0DDr45jc(Btk5JsQUH{%5}Y8G9b@))2Ay6X*NmBANwo9{HLCmzS(tGsl0j zI&0P8dd#23-o-=_o5%8d`!j!Xm7iaef7fU|+-%HU7(_hTF2doiN9PNyF?kr^y5EAa z35?bF9JkoXJp3Eh1qNF&coOFej#*}BD^9?Q2ahc1r{dhT-h!3GvZ3eqFWJG`_DKtB z-?iZGCkqA}Ecja7ib9U18_X7r^R(c>1PksLvKGCOwP}tR1DtS>e%# zaS-!4XPMvWIm3$0vl>xkHFrAU;!jBhQhHn6ovIG;AZafjO3rISWk-5a`EhbeW*nW) ze#h1|Wt3K#Ie;Htw6>L;Dn>V^8v|wJpC_Y$u1zR-yp*L5{&~xalM@y#b<_Ke>oKfo>1d<8Lq`< zg<|F%CGI>9L19xBW+_#eX;5KB0rSbCMp8a2Jx6LpBa06TQ3wnv8zd@V1~VtQ?^d8X@NSs#N< zo0(79t%cO2MZ-xtjI5x;iCtQ(tgeN#zZNt>i!RLbPw%Y*`skp4AICn+d3u|O1@|Zh&&h@uT1@3%7muVO@JF~AyZB0I){0&VrD#*n~=}7R_-R&u1~W+E7ydl zmCX3OnmHSP8}>)r(6gEiy1q8{gykSEn>matcC;U8L)-o~Tpw#gs<#~{zvSReGp;MI zu@1k~2In9fiul-YIFM`5LpC_9HhA4)52MzGIj3@PvXKp6OERCfmbLoBcBIN}T*Krb zurLSNk8-f@9KZiW4#x`iHny|Fy3Lb57IUS71MJ;pA8@GwUUaaWj6TH3sn{uRQdIG! zI>)@IVMBj zRbQIF(1%`R%BUXmCqE~6({elWSoOSU|7Tx{8_nEadskZCPDbwA+1s#GPG58m>dySd z>z)$y-sFVCkpjwcy}OkCio-o5=zPvWBhNc%%oz4Ke3D?)6bZ(g1YG_sAdU64ydDDc zvI3?bl)%V*R@W!&F_sA^w#Nyh>Nseunf;E99hBxQLG!2rYF$Nw*@K;!1LpTUmLTD# zfMGui>DUwp-DoVpzL`A%%q_fI#-7E|N-VjiLX)>4=)-5FyIqOrBh(0Ouf`}Z6`nOy z!#-Apvw9WudsNuXe#YR%O4PllL~3$Bls%wAdK>0#OREr<6N2LfN{lP1MArQf6dT0n z=U6a^HJnR(l;}`IjXCZ3=L`Alo#wOoF$A5Lsc&U$jbUCgJrkw)`!`QaSazBHFJa7iCh$30 zZGs}hgrYUfILkV#W-ogzx|wj2pSNP72>}n7Gp)&fqVN232TV9JG7~qL*FEIIoN`4o zdQW1ljnDUf*0{Fla!_=R9bJy(pvD9nx-POIG|z@Uxi+-EYeV;aIhfzfj%mwtFl|5k zgAdv9I>UyIeD4~cxg9(BTwbzagxUsavK`K~+2_c7o>ppu#n*;nzIH6?WP{HG_Mi0R zGpDm*c2PST@VRZpuidZPU^FrhdY`$(mUisxvBsD-;iWNlk0j&Gmz!<&)N~JQv@tp` zZ;2+ba@kdZXOcWKT5PFkEZt&rz^%~Y#@w)*>Fu`d2=ot5H&zZv4(#78FL2bD2xEWW zJAv`a8i6B1o*JWS>`uQ@w~Mj+>7Ie9&9?<+M7jo6tk%cqbhfoocXW=i%&sMY&+c_P zacXx#o34%D8~cS8Zk-~W)YcuWTNWU$|%0L-P=6YdB4R0J> zBS+s!QnX|Ic$M`)|2LjUjF#e6QyHGUlVR&1DY{0=klUF3izB57@9c#(wb^GPN-_SW z4CCiAMr|v@nq-Or4a7w|tPXi4?!!^iX5`hl8HTXDQgBe`k=^k(& z%pMIoT+m=K%gm)SYOJF^2xdwXX6mGTFBc!*8jYC9SV84yDsR*CRB34Zi z5p!FQEmK8&J;5GDFaDfw_9J>T-aFjM00m>nr}y<(b5)P=Jz2{eZNPy_?0aPY&_X{E z?U{SHa3=|E-Wag2Bl9=!^r*5t3E|9{GzV;TGm3tjN2_JuJl-BhI!!%e>6)6;|{Z!#Iw(Kc$ToSJeFd39fH9 zSn+VR$P8|3(f9WaKI%S zjV@WSaI6(^Tnqm5xge{Sd(w_}a_Y6nkG>~KN%-PLFKhVFwfYiNyi-62ck`={1Px{t z#e_!!G|CX9aIF4tk$F*>8nKgE&ktctq-DR}BQ2^B`vzZY;cMeKcZK;;j!DLTW+b!z zaiKkX2-%Z1vmW<79OloDx@kvg3-=W)vZJf(TMS_RWny1fTI=Uc8_Rpspx2z&)KXgf zMou~1zSF54tdETPNw?XTFHI_-{6kKtVW` z!`;P)F7ezPpCl)1o;O`)%v(Rqm)t%Tke)sMGRBqeYYXY|O75fiAfR>!_7jAKV%S$D zj+RrRVGAX~t|@UbOot;cbr3?dSoedya`8HJe!^d~=i-+yZh(&&or{{ee}v~M+l&uS zIX;f&-U){d>v}UEz1fDOnXKQjZ*W0eHa(n^EpdS>Y5%j_K`33-YBCJ zPa4oPiJU?%2r!H(pzbdP%x3K0LsdwNc~7E+1xc09pcq!yet$suUMN1 z)uBl>9oBI!&b-an8^*dNO}NOKku&G4PLXCbUuH(DLuL$iZ^wUZrB zy0Xtc%7@$!%IVuSe>$;?eXy&&skPmmicI7_s?$ygU&j3yj9H=<^Y|t^=s}hey_>L> zIFNP539L!nRbh%s4gK+GJgcPxF(xQHqeF^b3x6Z`5N&1sB;SmVBTcwj-h|h;&4`(A zLO;sEraC$3!J6{0%pA1c%l?p1_JoW#(CPADBR0Q6x-MX@mZQg{>}6hzb=L5 z>`A7wvQ#p&KYsRRPxOkDq2mSi7OdlV-araJ^2VDN9JlvGV0;Y?pDzu2fi>8l#vJ&5 z?hlk0Q1P{h&Ri3FpD|!2^GV$bve7Mt{ny=@uUu)x)d^O}dN6kuD=2z)6BI+23JU+) z5=HM8f})9?_5INXqRdn}(;%7JbDn!RJC$%fnf4gHpdT;AxWn9g87IY&P#K(S$l;e6 zfzfj~M;z1O@@5V8E{VXH^~?`^6=Ap~q7Do=7sdQ)on+*2oxU!TJ>#hyD~EHxV1Fy# zdfmo~hPTn&!Ja|(>xC5viiNBzTp7dTVt#wZoCG@hYkoXas8eJ-ZQZM@(?sZ=>e0ZJ zb5W`R!|!v9ceY}>*@{YQt#Ie~U%xT0*9<|CJ&<{2=D-gXlPJpaTBY;4-Q1W$*GeUm zY^O+j&WfZ}BvXDHJ*9n4;vU_MCJ`G3hv#e%mf0rMv-Y51Idr+^UupM)!i5F@J5ji z;mFtX9%divLH0N;%wU~C7lHS+4d|*cp!5j#$von9;{1F2frudH=}U5+E4GJyDt$Ot z^4|Gc$XsVz)@-`)e&IcByvAOlg@U5-EkRLZvtzU)ol8tig5_i}FF8f~Ej{kXm=zkz!kD{y_|8478p5*eeo z_v$=*E}ybzBaQ3+lUnTI`l0R@_NK+@@Tf=@N)#}jk72*XB(Bd(vhQ4BMsy)-$VU+-jN37j|vZr;tgYZ-eR z`wG}}f%`d`2l>)ciLIs7*j7!6Qo%|DNOXAKh2!91EhhZ(#ZA^>_+A~RjbXoFu`EQk zGGkhQGj@D2BXAbyvQ>8Y9nHbP{W;ipg7c{VTe#|MsO08FwOaU4{7z3QXyQR5GyJH{ zZaIzGUPu)ybHA#O6Rw8~2+#@e<2o|cQ;F4#F%o*JF?cKUGdxEIhY~-Iu?Hhc3(E>E z=6&OujB{$!mt3FCV|}%$89h_E&RN2Igr6DZ7H~eDY(v!m&RdaOr_|%Tm10L+T^lq{ z{b}M@A8I&NPHQ%JQ;n-$q-xi^80T9%Sg-J%kxJ)KaN$Fuah zfVp|xTf+0zC0GTIiJZSUcloH8gSr|Dr|)XS^kS}OmlmV#TD-o+K75{^)}>+)9?SlP z;U-usm|^|IHKLapho3Vpi{L)AYrH;rHi(RYYBN4N!~BVDxcPHtmC-jrpHLD z9&}GkQ@g*S@#lIV|Q@f zu!wu+%SPbmBMsWJcKqY12n%z%%acSr9-WMhXSw%@^XG>S+34c1z|_@>rPUcPKjNIq zvG~Cw_Q+M2D31QpT{tc_f5|a%QzDgRjm>&6nJS!2qmXp|+=F-n6)7vlf?jgeZNeOW zJ1HV6%8{2Qg^}}n{ZRH*_KZN@!Emg9wh+b?u5(yh^a*A^_Z&SYT{j?qqX82yh}h|! z%|2c3YvTM>(uwD4DElkz*=WsqtJwn9yJoZYbWl*d<-Adzb-;IAM|Mm$(BSw)s@FP^ zKD|mNduKg0$mSYu1NQ{f<9@d4-dNU4hD4heK3CGf?#BK>Gy4q&u$ERBj*sPd&V1N2 zkjMJaDiNjjvflmF02O18+a;~&)RF6m%2upTWR29uz57zm@lOTCj+267I%}Y>PVriC zzE5i=Cmt?y{j@LwP9aCmK?ICtaGG?V;|Rk zA1-S!+!}$vXbogh5$Lj;`_7odPviP+MMDuE=NOQ!Y_*{5 zR_^KNxk1GVk%GB*VRLsGYhm6f zJyQl>55^mBWVpLrhN!XOSmdHX5bxvp>-e)6ShvjUslmH5to2Xjo(`U$!=Jd0OyO~{ z4$!zebMKr(!v`jRC`ddf)Rg1M4?M|>Z!Rbvp# zJW!<=R#ULFc^`IIo{vTgx;ThNnP2`(t&#fDk*WJ9($xe zWgwL~(KoML$*;VCipx=;KBe*5+za_dNHt8*N+<`%vw4 z0pi3^oSecv`3=o*-Dk(KvhL)PDWD(waY}n~F5a4nu)#Ul5hkUlMhBf*)EC?5N2AJm zj$LzeptX5WmCp`}e6ED^yJ$F4GvSh!gYv~>^pmxNj6O>EFV~`RYtENvYzPTzOlc|s zb=ZG&vXl-9?C(>&3D#w5%qGk8EH=!vNu?X+{NtwdThdt3pR8Kai_@QPRPH=TxV4tKl{agcH{aw)`t!r{z0A# z)QCHy#TBmWuB^zxy(BqZdGV93$FdKOYny!*6B;o0)-T7KdQLB(#kZ7bbu${X&v38x zt{l9W*pRx;WeumJ8e=!>u#fBcPbGPrBm602qrg4QTvsxm`ieD!Z3nnEoYH`Ly~(Gq zFO_(~IeG%ul26Lpu=sK#GWHcP^okOfhiOr>r3p*-Ft1)wMrEuHDi#~cHMtfeyK)|X zk%PYRo^;T;kb4P3u(zlVo12?3q@NAdp46ks#~DYp4nf`q{w#~Zj`Snpz;es;Jud57oVeb zn{x1Vl$5#-{Z35^g3+NF_qx2!#CFyS${PJ?ty}_$TL>mH|ND6q*T{Cxo4@>G2?B%# zO0053qtScz7nir=9ryZ0bt$A)KL=!hfEG$6KDx6;6Pt;NTx)M>A*WMK1aul7f{)eNH@7wu$?i4`jr62}asi3V zHH<96_Zbtu>0^U?XICnWaDv|tHTvnaC^E!^vrlvQGiJQ#Qau5_H9`<`Rg0AFnON~4 z2iMknQ{=}&iX5WE?Fl-ZY-&PbSw8QjJ*a9g)&+Vg(Xq7-)vf&ZhH&3H`!rh)WxnGY z_eYM^Vfzsi7H_a2rJN6Koy(d-Llu5LV?QSQY6p+7qhpMmy7Ffo6l<@NXgAmNbQy=A??GxGhCk2$Yk>nSIA?d45D491XGXz_@7hlq3=W*w7~>Y0FvUAQl_ zvTNPFwQruR2|e8cYULZ!BmcA@t*y8{N;eZ+1(dK8A; z$*^02ZG_!}&F*Aicd}W>MquCTyuXjnm5o(h;=Mi;Wd`#6)LK!9?@Oz}9?~;HfdU9cPoCQ?&!rGm^8r-2`EV|poT2V!xgFDW3atn6f$=UiB6~)|cbplES#x}0->&zkr|u8Yg#|@R2pw%s_>wYtXoT3}&`rjhaYp1Z%y8)Je4|p+?a^(b#>T`2#oUtKF>7 z-g73)zOnRNnWZC5Yu(!&7>Eo}#g~EKE4(v(R+i@YDy1Z%$(xapg#`FC; z+|i7&{Q3v0E3`M?@0Hm}8oVtZ4eK-$zWGw0p;l-&k28weR}EV}F`%y0>rt2CzKxiY z+AOC=_@Ec-NYCfY)@n@e=mM_ine^10R$;-EXebL2BbsAJT0QDO1B~+iCN()nqwui} zIfzB9A6eu7vo~J0UR9%rEgH)QnUK&s16$9#(4c6dB(SCrkJe*jwh@us7m1!OoX?Jz zhFw(H%lEz395al3&X!lG&pnnT<43D-h3nHjJP9*Lk_%|apLc*!e)Lx3_6}xF5U={T zDf1AB0d+r4ozp$$q)p^L+Q+Z|PbU86dY&@dB>#3)L0wyq3f#YWhskH~eNTOoAPXzf zQ$`JtC-pIJSK2Xy-rS!P5(PU{$QclYrZFZ|<30@zRcNcz-<{u3gZkcu88KuxxG?~SZzPZQD#@MMfA=5ttZ`<;9OG*~=ST!oN zjl#ffCZylVz)9j)FO!p{O=IS6G~oLlVZ!}~nXuQVetAoRG+scg>b@TLD<@%_yB$KE zW^3x8-R5baHS*ujoAKeh9fxmoJ#+n6u(3Bd7L7rDO*s71j#AW7hB?ggVW}FosE-Pz zpDC5+Si6=AZD_+}$@FHw)sj7Dq8a%<#QWAOw5unx_Zj7f$o0`E*Vzoq@Jw{!zAk&& zEE6hG=j%nx_o*4bcy6RLV;^-RMU;i8zuFpucAw4g_+W?sH-)zLextn1Bj?9HyZdnV zAgk%yHY>E&=kfAxvj!Ww>#?|-8C_;m&%2tvp^CXFF6zYib9G-sP1FSHj*2O?_vabK z`+}M{EpzBbCE@BtJG^-=we6iK6R&8Hqt|0Lf8OaYs88?3^L&s=`cZ>6!-tx!2jtes zMGc|;*S$%y48EYj!wGuGCvslrnC;e?p0<@n(M9le=Dl!*=R>hFnaF#=^}lkTZ0@f@ z#|7m1CYn(7nH>$5@cb;kS8fGp(6mVmCRR0b9r62e{nv{$OZ8J~)NB)jo!3nWV&54{ z%rx9-mLoUR=+RY=)Cl^s7u)gYlS132BXRd##AgRf8jyL@f1W#=i2=LJ}@n$9`tW?gOBsh?%JoHZ(V>D;I0j^iLaaaot}LoIkUc#j8MO@WqVImWpvDTm3VkuqE-)!&BymzG+8( z6bLTSqoAeT`8dlC;XeGFAakl3W&h?R$=I`3?DRFZVOGvtdJGyJ;JICzp3r&BZ!DH1 zlP@I8wC-jZyWJ?K0?iWUXO?qo$y+Q<5RWrS(t}^G9`{D4HfFj1-Y6aWo8;o*1R4ID zxjysEGB-6@UN=sb((TPMyh5VPPfnE5#AizMN|Y%&ql9PCtN2rcu}#(Z+pfY2-VN0n zsj<7W2JJrj;-!`T)1~yIHX$Z)P=jG}e9>H^#>|R-SaV5(I)NIzU#mvfIn>&(Q{z4V zp0-|t`!9U4gMaQpKAeCmRt0J3iPb<~LxcPBWqxWR4k50^K-06+ZJX@I=1|b%m zcA2=)9X%TS(nE2Tf3`CpCqmC0Ha+^CipESwG&U?`KEW70Mvv8FS#kPuePU2tsC)bo zg$dL3SkaKW$PUypwxLILtsar-(Rf6RyWu%<*0cC^J8^yU{}1OxBO^N+VFUGO+KU`U zMl>QD^6o9D$16TVG}q!c-sg)4n{k9(PwzAn-s!lnXPNPm=k!1yu5H#s+0=HoZ%STy zvKga>F^@6BjPZS#3oz8otVU)_oHe8B0De5b)|0YHm}fF!>~bUI0)3ZD=@02f9b^$R z4C9QL$b0Il-N-Y7y7r00!<;7SK9Ya~JkRIa(QUgOXTN43zcFjAX_+ux&BQ(8EV>$Y z3>0E5ywe}AU=9z@k}KTr7uIKx^UOrq51Cj@op8_2c9?ihwyl?mbG)}75;rPGtmbZ- z9d#m@b8*#l?2W$T0n(oN$by)Uxoc@-ee z`JOUrtXghG(Hr)K+N?svd3}AQ^gusZ;qVdVfjScK-b)^bYouXgjSO2HD4*$1Y$G1h z;-9*5VzF9kTkA=?OiyVYtHib%?1!Tic-+z@ElVh2eBqM40SfpiawP9Qv6j90Qsz>w z^lGbs@AZ7y_ECxCA}(U^3aq-JgwGf17Y+HME=w$TTE6T#qd=WVC5jUR|4~SEJf#=0DeLxu zW*t_rZ(d1$qd~QB;=d6X*iVOwo5G;lMNQVoP!u~Cj)!qNDA%%{KORa?pbn>qnG~22 zj$NB{c(_If%T@9L8R5)wVOHGRFg)uYhKKugIJ-O)S?_glvG=)4&a@wUg4BY{WKcz* z?SnX;_v}mftN%87``JTmxNX4C9n4lFelWj@0n1byun6oy%TYH)uD%v|j^#%U7&eoc zKV=O#IL!dfWdkl=HDF%rIMlCC4mLLyDdi2gLT}o(%FLZu5{HUr1KJTw&@y*sOSS?2 zH8Fkzk*4L(`%voNy{9#CTy zWW&34?A^y%@rKz9UT!v|CDZdt?&t3-=@|FUie-nacox8{#j50ft6A}PW;)6~p}z4V zySIZb_*j}@su(otuh72fZuYdl5`WhEQh{Y{ML6?Iic>ZhXKqbYHtnz0Vt zyyQR-dF>xr#Jj3Eux~5-%a=}^tn9?MYzOitIM}CWBZeR2=H|qo_sm;jPyb~TKaPL5 z4tAjK3J1<~bfPN%FE!bTXY4K0lui^K$A9~q*>e64OgZu%PpEA?)|0%ur{ax~gktY1~q zX4{17xa=}{sD5pElBDz(F?0X4wYI)x!{f(}j9VQAnW{?=KC=?kfgRB}%fCz|QhVL$cA zub)yc@tmGkPxkRn>J)Hhh!79%v8i$RKAKv^Nz6p~6o*1j;tS3DuF;lA$b5yy1zH_fA_Q&FVdMt*_=ALRmeQ_yjXlgMNBPtf{Ul=fS zumP_9)IE+jpjom3%R3PRsBM7Pj&uy&$_&NFR&37U9++lD!);bfDqzFG_1tq~=pRnw zei~uLf)7@#J#NLSYt&D0@4Xyh!zk`O$0aMCa*vvO+UQT<{_&*lIFcI22KxjqtJ#Jaag)E}xpCUG(o4ClB|F*{GTHjGtou;&umWbYR9KxOcceONBVm zi2HR2_vi`kt+C~qr`q3vwZv*WuXf@|Q)*9+I`H8bb4e!gYw-JKt#e|M&H<7naM;|^ z>K`qc);qY`>9q^nT8?e4A6$F!!P8G~CR(I$pH`{G-dZGjw`KR3BEh}imkHi!7}P2v z@80R#-L|)=-`sS%U|Y52srOLJmJ=FF@2F5qDYgXhHM$3ns1ns`*{H9r`h96 zSyFFo@YGfNEkjggEYn)tu@oFrDXnY#9?ST%H7#p;rw1Q(BwN~)8GqWfCP8{yljPOU zcxgaBf6XV8c%&I+8T~#1XU%eZZi1wE8pZi6LE_ueLpC-=w!co2*k(o? zO=1MGNpcpL<=J7Q^jeuLn-f#yk9U%6qj%;>Gn4djH_C5%HlHjpOS9D}^1ZK77Sv;g z6*DA8MjGW4{i`{?Ch@A|htV~OQ;hS4;-?Q@cl1R)_Aw>;X^X#8`48k`_A zMkKOETyMtT9n2`DWrpH&)@!UAO+}M1@hY=4MzD_^NN&|^!sOy+ayDkf^W)l&Wv%F9 zCiiaUd{v;1v@_Km~lcs+MICuRf-We8)e7J!*=YA&qSX@_ND7G zv5|f2z;W~@FU!Q_0-5B0=!a>>T$W5b=BCr*)-n?(_<64CcHF&5%xnp3%`kf6JhSlp zGO-%sHEmC`US!R9No&V2elK(3EchB(j~4#F^QMz*4Mq3RU)EF#lKt&{CE%2=`1jFB zW^6&+`9t0NJ7xvwa%InL1v<}Rj>pk3Y@wHag(Cuom<4f}dbBU+!|*$nHOUO>#k;b; zm>h>CJTo7VL+`c7iY6zl^j_F-vapp|T;$P85o4vk!BXJ^PHlEzfQh*FY6mv;cOvn= zhqMdzkzHPX;<3YD))iLC{Kh`=X{G|XpB3oCd#wQPoBXBBOFE@M+>tOeHbvmpL;6QX zl9O8;j-%tlaHS$^qtsYtz#4Gbo!Y$>aky88HBkxXAhMq5a@Y#PL!P64^so1|;^Z_Z zjxNeZ^FdDd`I0wU#7vXV)N1ch$)f~~+@zPst5;$*4cRG^UphMXz`3*_)$)TA9pfqkFU);J{$EH2Oc}IwveARiC~^Oc}4$9~h3DUSW96Y{YJR4d~aJ z8vn0+jtKf!F7ocnXPwCRYFcj_#$Beil3JB&W2yVx$Xwq5V)PB1n4aUnibyA75}22* zXV#U6O6Gj`lMOmwnc^ELo2?CH$1`Ti{GdMOsuBlEGjD4fdCnOMw0!M`*goOV4(f|8 zws0Ko9L|iAa9lEl!8MP1BJx95bLr{fUEQck9CQK9Nb|74y^jqymNL`(r4`wCY^cHe z^2MEO9Bt^ph&xV{=WCNQlG!wTwu|Efq(Y8b>aFpWBj?zg82n^_GEjo}9`$s0$<#GU zjOY3(wc8DcCn=e69)`lcI$#;sG3yB%^AUs`V(J>M-B9vpgEt`eeH^@9%xH{?Ls8zh zalALD6|>=1mK8D7gJcywL+p+|nYP*Z#k=b(*YVyj)Q4QA2GuiJO3@o0Fg;oRq3&zg zO|$HXNRgK8wbKv#VN6XwO!=rm+hAXGP9>*aDF!KHc?K$CaD1E|X*c!gQjL8y&zOUw z>DNnT4&q_4>-`nV09_5RbZp5kQ#h`K_ zp64Fq@%daOoq9ZfPOZuV6SJQ=qhJrQ*gP|C%w<+UmKiNlvyfxRM3wc_Ve`3Op1+50 zJdb|zdsn2^A#RvL+wl=`r4VAw)T_MmH_2jCioCyTltauU@ZFXwK01?BPUdWhTwiQ+ zYH+4@IzWBHSA{n1utK|$*m>JwN^RV_WSLw)S*kZr zk>p~j^5{&mcKw9nGAm$7G~U^W zhq#%s;*S}%d7oUqXo3$pfFJG6@XN5HSWG6mj?Y5c6y5PxZ98B;Hsk;yf*kvO)}+wWV(~&Wx>3sZA+OoTa20 z4nEJ1LgYhMXX1N&yV7CiXlznN6z{S`+WBfcpLt zLOp`nD^UJg=r0f0f2}@C-Pb8M9B-_^ig z%=}Bs#*XH!U)Pf-9nXB&7lGm^5-4j%)5m#4Ee9(G%FI+|=RRcqO>hBpXU|oZoZ#KZ z3bf4#!}3?uz;_@&9utN)55h2UHRn1s=l6cdISh;9kbfc$E8a2NeHZ`Sm9;)K20iy! zG4iYx@%wF<&VRd9i5Z9msDCfa-jvVr^{5kP8hk*Z%bcgNBtX)A17!DNmH3tOllV2w=K()0_QCej{#5o%@Wo$5&=Gm+~gADdn8#>w$*N@&T z_8_fSI$=ERB)8#&YdL+7Wi|4qpGF=#g2at85n}1*xHP4)Z2C`g%4gW*<%WLaU2=h1 z_~(1wQ1x;c!cK-WcPt#%65)8eow?9I*^e4HAA=Z9gGO;^#Tw{~&4AmL9rK;|Y$oNHIEdymQSqfsS;z((R(C&S9o-G&L&SxPAr_<1ttfZcfMbD9*0v<3#(t4xG)-#@^rA(78LX zpnQrnW~NF(_B+i!n&r^=REc{??H)5Aa?{DT_S9ffDmB%InZ?4KgsKzBqqNoIBz1$m zCdJ^GgIH~IYQ6t9A*@{zvbUHqjy3q!-{gdNf9UH|dp4im9itsrt#+(YtwaV z2k)9?^c0?bG2|0@Ps9vVY6UY;a?vperEFO&S$Jw?h)GfU?lDe_p&e8wi!y_fLC zb*`bnA8K^YWbRFI=DHYS;9ffh_p+HQ%zESa2YS~&vd=of{Gy*`oS8?jz#(SoPv zcqaTxWZ~o4Oln9nu`Jt;iV?)fjeMU*DztOIkjrbP)SjKE&^}-d;!!9h62s4{-oci9)WmTS;(mmZyV$DoKl1|MI?piMF6o}8nf zW1|^6Ba*Ph$hxBwy&b{KT5&RO^at}k<6e|%+5PY)?MnKkNq9kvl8YO~aezz6h>CV7adu@XuB=(F!ZjdTh1?j}M25ky zFl+37R;UWmBX0JS?N9UMz|c@gngM^$w_<2D>c!X#+TZ+<)?a#~mLnEZUJ*;$l#O!l zJ>)fW%1T@f!SnCTechXmnx!3R8|^L&O6ADX<6)>YFBZ$A({cP(HX^or%BC^-5;u>2 z<7UL0&sp(!3BOKVZ}B;oCu3&o@Qrxe)^AoEzfBDHiLWfCuIlOne*GD-ICPSkw)d%b zJLoBS8}gY$ABvFD^gSK7!gDMA>>oVkK<#`vQ$&YZr(>~hGjZe14isssmg3>LQjD1W z&8@MxGLe|rUe4@!QCDVM`YkP*ha>a@{lyCU>fh0aRM10ecFvV%<`Crb3H@wn^_Yc5*d*v_W2>O4Wr(tB(b*|>_2|^N)h6xUt^ig z&%P?3-?yHMzIkY*f1na6g+g(OXYo64dh{C+U!EHv>$D0SEJNIrSfRZXvGF3zd)`ma zTtL258xaa~QD)YENkO+NV#A1rmtgO-gEW6JUwXf^`y`e=E{}O;qt$+(3Z2J<3(b8oFSArPl18SVHnnuwa%Y(EH`9h5&OB? z5iXgTPW)73fcvv_EbYqYY{k5b0M;+OdsqKsz##UC=amlT+-PK7&L6q_JRHZy#G!&S z9jcRDS7YnQ)MtMrH-a+(co#M*cLsM0FfW=sQol~WrN)XdRPW36M*ZoQD%n`|xQ6)O zaEURD+Wb&@1E~9ZT#7xOvaZ}FFLdEC^B;B_@Q`==Top3~j(CaN5Cz`#)gieKvmH8G zQHr{)+9T^r-Cy}~erp(RM6x!RX~lt3e4fqpn4Ha*=GNZmH=H@jrRf9d^Yn+{A$(80?LokLo@8A#{8qw>r>5h-=JM5AP!~;&9h@}^d@5@sMl7?y|g!}7c z1sw)8;OoQM;0k-k@<%;oH}RHsX(6~BM~u2N_w_CMRQ7txf0@-a=j*WkW-LxDq7KfF z`Iz^;WLixH+!}>qaW4aQF63+nVg^e_F*o5{uADW|4>FOtu9J!R?r>n?bx$#F%9SzB z5KJTnzNaO1&}XSLec&St)#TH9QfKGGybE1AyvK0C9Qm z#>F~*QpPV|!aGx^Ol*AT9?sy}LvF-TTf$qoq*Xy3^u)yrY$vxf)Pcs-$-Z`1z`bq= z%J7`I&iZU)ayH7ItReT;=1I$DI&5xhz?dRdto+JZ83WZ)_hG&iTq9K@vyjq{vRJ%Q%*ttnb{;&c;1E*k1t0L|JqvOm76R6KSHqe zt^rX|%pKtRA9~PR{+Y@3Nv!Hm73!A)U_<-hOWE1f&5(QL3DcW0U~>J|BG59=D9@NV;NE9Zp(yLB?!7S#cwPl7+Fnjo^MtSB*?7AxR4GWuL zy+nPYRiVwR6fY^mRB#LD^8^!@c*Hy))*~TZlcZa=H&$+pLa#PvJRWPuJ?bTAO-YbV zZYu0)!o0kx%q}WNUpaf=Z%q?rQ6^_vj?&{q6#LUJ%o_4y{@ROulFeBJ{`BA{ji&D4 z5dXad^ULTRxn}f1+2_p5TWG@SqjoH&kJCl%N3@EXiivv6Xl_QKiOfTssnCw8W0dM` z>1FM%M{a}($7+%1XB~As)-3C(BYV-282LT=SEKEiO+DR$%|VPpI~tzu7pXdb@oBV zBx2>ms9%^*y-AyRS*K-PApSHtU*EVN<<>)Bnd^Td#C+d%= zUn|E9@cALE+x})QRjvtlJ7%Cby&4Z~%>24T4=VeBlts*nBA%UTP-qhmF|(_J3QbRP zPSYzBrsZWoz0-xE4UF=!pavbsM*|g;@a$P8svUJ<+^v1`CD#u(=IHT^_|Dc|)KKhm z;a(MLXPz?q+#Zd;*jv2M$-pW<7v{8%m*COVg;k>t^qL7%b~D$KI;P(p_lbFp2DNH( z-pF?9r_wW!Nd0VDtWkDcQDJ9_9^0rBw5=xYK1QJ}$eAJc%cwbPjl9BgW~HCCqY>Yi znOrA^k}8z07mdwLsK-pSBlNQie?pB?;*Jmg1VuqhU0Vxc^Q!GGxF1fG&9hV}V%KA6 zFX~dM1JRyzA!k>D?4iD|>Rvs5M4FKGE&~gwU;EI~C`tV|bMkg-iT-4|5;&_GVW3aD}##d7lJRr#A0tG)ztt zTF2V4-iPbJCPO!UF|VRLcup_zCX*JlA@Sby!2m2=c^FT<>giPRA% zX274dw`wQ#aZQ=G7Rz;#Lfs!Rp7IM_SitA;kMu#aEzC;GBd^km97iRE_SVlt8U0#? zSFh*dS!Z%BTbbp+_0zAKNnS?#Fo$w3<~KGWcoO|f^xDqm`nkrO4$t?|__~GM&Q|;X za$0Y1-7Cv-RY;X+Tp<_px(M+luID~&jZ$)v8v6^=d-t!2S-f^Uq2CC5;wAYBHB&st zzGibj#@lgvAp5=ciL#13+9c|!&lfXeNI%XJxI!#5D_)Af_90%y^WiD=l^v+pW?kQ# zz4F%P%uiHsee&mBMU1W5D}`2b(j>L^@!V*`eN9X^yrmtNJ1Dfpa#E#V8_q&2LhTga zufpBg1Alj66m@xB8~Gq&aTL~2Kiju4UxzrJlPk=uKRHw9bredSFmXm7^U=5-LWjqT zVt@u$?@+(2Gof6a4CvJKY*$K@!f$-IAE{&AXF}QIe0|uH#11q{lZEW#mq%l7xEXF! zIirR8?!MF`KYOggpmv-O^vHx+Ettp8btU}xZ(JugcSNJ!CKEd9Ie#{gxaF02xx1PA z?$*&Lbkl^-I-c`|724pQd*$j}uAlaL6nA5u9P!3QHK;eNpD2Hpdn1tjUSqDGIW4G1 z=Ig)WSAvu(!EC+CoV{aYo?~VP993O-);L~*R6bbRfj)LSc{)D7=j(jjpkC6#^SO8{ zJ#M~azQ_t+@%6uKf|dKRI@jC( ztDdn>=;`2$ibGDX%+0Wz{I{!Rb410E5r|9TT=SvcyHrP{_u zryA`z-0H{dVyzDq85vym*Lus8;6s+srv*=+y5W5~r`q4G>@TiZRNl4I99~7!&fS|A zJc{dVO3P%ae90_GiI?(w66NJplawhyZrYe62dbIn3+L=K>y;$t8%C+}Bt=}4O;Tj8 zS$eGU&1W=UYg`{+XOMsG0A|d$r5|oB)5N><=E?ZIk(;LEWLb!XXrR$RW3c2@qQZYLC$(QIpsCfAP(jXK@D;257doAk5#9mkzAU0eJhqaGqL3 zsF<^JhnzJ(_hd!Z73s|AO(oCm;mFB%MY65c* z?o-eF-H!4N>_~2x30Eldb*MjVLi|HP{J!iUW^80;V#H*g>j!yf@jhPGh+MY9j!m`i zVNSa&bO^CyPq$2LnnmpII?t1Z{IkQ3Vi*SJZJDU@R00pL1OL3d3Mx8 zmRsO2C5zXW=D$2-Zq2$fw6DKBJE)QYV>HrYgolj2Qb+u3?$R;VU*^_oBpts7%Gfzx z()68|T$|}BJ-QP+S15qCE~z-uCAt5SYh@;5i+wJcmE)3=Nz_cu{Uas%B9|a2b$(N1Yb7kaaa-^KE@M8B5v3e_T;7hLbDXl=}JOy47 zfA(Zg)i=r|SA*zn4OXJ^d4B)J3M4oEBX?WnNe=te3CvEMxmmD%if_L3uR5{^IBLU4RnDE#?(dx*8f zq|j$pIuw=0>yR&;UEv5pk1g~HPT}mPOdaOd2*d4H)IClM#oGJqmEW;%I?Oq_bLd$k zr=qSFhtu7ujam_l3x^CS4bDJ_X6|A>y_MI#W{KrGWabQiMY6v!(qq~r!iu5njV6s}CSy)IG4*uxTV};^ea|Jpxk8zcQvy2>YXMcP3c{avR zVdlaE2j;Y=UU7>9$3JCrUKZzFRiy4Qin$pd-lKqq9?f+Q;9NFwbtlZZ)L>a1u$`q| zaTd8}FXlyUaG*VBn|ul)M-@m-)nNy&hdc0_eX9@g{&`Iu=s(Yar&}GE&YXTr0gVK_ zt}p&$RPv{)kDSo^NZVYER6FY@Pa4z}Be@Y*DV3C}?=AiF0|hTMGN87%SeALnlotM? z9_uYt26L9BkFPA<;wg)kxJ%AtAGtSx8pqv@By@ncJe{YO-$!doV0lkz*~D9}3{uP7 zjs9Zu^OEY*>PvLETK4ZFR&Z5;i;WbV$B`$M9e?Com>cQ`a83vReZ(&2BW2{ttJVr^ zE1oY?xtH2@cgav{6sIyX5D>+yo8x&eJfAJfwq-I9eU=P;BOWj<;*+Ro@kY`rSg2 z`CA9io18fvti!mBP&_FbibKUC5YUDHJ~0GALv;x7(_!=q;#=>jp)AP#_KsL4ap0i7 z%z>;!tieM6@Gt|iB8Zz5-T+5`=922;aD)46|5@r9xervw$k(kS{&U=bx}&Hi*2cj) zkn=8@8t{XA^f9raL7faZaWxj*>lyIiTr3*YU>*nm@An#JtcGyzm^Z(Nj#|k91`I1i z9b*`^8B?hxZb_c&EA=dm4Cq4*O_ym_>UnI;-?k!@8B`yqrepOzD>}8}><*O`GjvuQ z4P+K0F_j5Lx$lNsvEv*0r^8lU3r@$`p*HI6IXBwIeeyURZ=PE5*SB<(e#d>A&bc`J z+>XDj=-!WW@+PID!HINCpGzFOCV90ZHVpk~#fez@re|?aZgQY9@zQ^*anJniKstXn z7>L&dIB|DdHk_%%{wxmM{X-q%nQWYNIPm4BgBY&^y57t(nk7 z*Xdv>U;Uw_(%e3la^q?S&stkKt;VNSr|XREE$ z(bQ67Q8~-~$EM)x3#+8vsB_V>(|9BJ^D5t9@8wrdEZhFrGWLp(rA_|}mg#>VY}KYh zx8N!h@3pEnqIFvH_BoaczauPBktHmx21HoK54y_8jGvYo!4q3vEjj(f$q!#GjS@}r zh5Sc!+e9h|bm zd-!609deBcYG{Y5k=ISdj6G&}J6SJMAJVZUJ#AiUoKULqHC=^GyXcSM{EH3j^}J0Q zoXb;V?GhivrTM_?AoUyW)O5@wesO|WQJjicCbJ-yQA=sjW96|J*r-+b%v!NVb3Gac zMZ@ig9{ze}Sbd2`hrnnQzpF?65Mmkg$W@hz!K|xMxKfxpnT>i>b8-%K2lKaGFC%KtxOM#=9cY%6ER ziN(x$cJ`Bvkq+eojF<;sZk8%oRY(wnUG9PVqZHVn($*9+0o-J^SxOoHlAZg zEvp?v3T2{hiA?Nf4VpSE6T66W;JF<=Ggv$FExzTX=9LR7X`@0 zm;TI^Du_}m6xbZ7z!qj`&wZ>w3^gLJT5&iJ_GF&jhje5%W=4_1hDc)lk$0JQObyy~pAUFflyf_GI&me! zL2RX=Ox)@(@5u{2{^=*%TKLJ_c0MxXOrE$!6hNItZuq$(U*07vP`Ma05)XzmCng-7 z{^+o2QW*Ll2*a4c%;ex%+&wrBA6N64A`KYc+yHM6p7q%_c=Nn9Eg&!Q-HL?yXK?Kj zXHai;!go98Lsg~Ln$KZ+PfjV#iKO}Dp?-Nw_1pe3ZvtmZO>H3gW7P7tBr~KsC{UQ0 zCtZ0DUS=k;UnS~Pp6JkM9`7^eZQbn|2ImLfQ}Qy(O z)+Oc-_M~3VXodTebcF7s9;D3~6#nZ2_D~mBpSsVwC8z~iMt#b12Le8MOHY@VY#-q- z_m=xf_7{zebp*)oCQ1xFPVYjL8&FLNY3v4tn;ZJ_^%*lc98Z>#*VquoS(IT&_N8v` zAT|9(;?V6AIikk~jN|WD?oxX%)Ks2lJ(ohhA=ZYz)DK=~Z5P&wdW(b10Nc-*;H{k) zaf5osNb)Izn@CUhK$$IZ#nDDKUy$i5q&yN%@)@ylKsOlq-Dk`I;}@USUuFN5%OhoPV%Tk5W^aYu7pkZp8oA zGkL$Xb~j5$>MmxKW=&5Rw>ldvx?3yR{L1@$Ns zhPRn`yD^;2bCM;y8g-w?sFx{lK&qVQ zT{zB{xr>}{)J%har)W^UJbj$J>x!px?&BPKafy>hjEcc8HSwygdRPycP`N)}lit*; z4DbteCDkQoG*`Alia(v^CYCP&P2){A*$Zu_NeA7YKvo{rk(hp)ZWIP#PD z@d;nteeZ{aRrHKLqJHN)^OAX&E;*&ggiA5hsU^WmT=K#|&J694gxi`V{QH64PVxgy z-|-m^Q&;~o6L*GC^GSV(atFURwXm7p>0n-=5`iwTe~I6kboo^ z=a($aJ{Tq8JawKa8eA$uy^JU4a;LI(2xH#Xcs;<{VAN7Q+RbA2=r=v~YnkEEDhYRv zGMjM%v1;Nh0UgY^UN8ysPf*)*kZXrJ)byKntZGH?=iix}O`_0F;F=kuQ)-pO*{AZg z>9Udfrbb@U{gW5D;l{FOn!of6R>?AQjKkdMpFCa=4Hvm2u(}eHiYe*iQzE?$^@AI9 z2#yNFttnx|sW|JtS{Oe6LvD8j=Os=yAaH9OJoA`!!+YZp&%tl=t?=c!_^s3#H1M!t z@I4#$4B;$Z=Kb}o&kV#6C$^iN@XXCdy;P0djn~MD!a>qJvXR`r)IhFLL%60lXIA!f z$;1!^-k%_@(at45ausOf3P)PB4sUrT7E0G)=ocNbsUd9sgr29p%!hv$3tMXgjvq2G zqaqIafmT!xw;|}J6$3g^``(To!5U|<{~ERCiyauZ#)%))ci;2>fMz_ScmMJiMUe*5 z(uvgdr(El3{p3zQxO>38GYy8~~TIk=FyRBM!2dRc+IJ=6*^>knPSG4edKeaUZs zHR$jp!+;f~+3(m5c+Q?ExlJ4~IrdS(Htg=ga~U?Y+Ga(Ci@eVQIJ4n0XWxZ!rt>5x zmTl(T%cV{{EKJ?`jRsOp=_^Yj8Zc)$K-}YkWa--gxk8^phPx62uJAQkszm)uO5|7- zs5v77|MKpt^N{|xEZ*@edDk<$YvPJH3|!58n;yhVyyM_sYXfe2Y{1$wHu&}7>2b_Y4hnO9Tkwt_tC78$ z0`U6fhVA`wWsOzIxwvkq?ctJJT_WIBoY~Zmbo9LG_+CcfR3*M%tbc;?nAem*O~)SQ z+KW}V?r{a~Vv8E-a7vJC@TI8eRj2M95U+g+R}#GYsNXJQl`{G@mP z0QoeqvD9UT<*9Vep8lqi8w*&A{o;G1;S7_LoRM(PCEL>#_}7y-({~+qRqTtSX1-sS zId7zq4v$a7q51~uhsf0@w%LGAe6Osl<4`V@IhxetHtuV~#7WHd8e)UJsf}1L^ZAQ@ zKqBvWtB(_F3exY{p7RKoCrQsZ>dpHckod8wqWzpGeOjkT&089bIix|q8_d?IPtD#Z zHBg8+HTU*CBeP33QHvi+ogB}j%#%D9EoQt>GT*!yXA$PnXMTx3^eW7VC7#*-KDB7a ziGOnMFUn%JuRH5xa?VK7&P1xjq5weF%Q$jc!B-JAm*-LH$#_8 zt@+#}ESf{@po@8X8fNB>Cr7+76U}*7RC424xP@5|M&=8z=lnHlEEk+6k9e2bv@B}V zID>n~O_MAc!Z}XNXp}=Ka)+5Roos5%U+M>Ejt1R2Q$JXhnEFTN5N1Z>RKaMJtQLbs zo-tTilR1q&^*Ftf**3432TweC`7QeG6OwS@uOw8?&BT_c%=a6S31bgx_c~{xgenv7 zcqaFvUN4Qlg+q;aF7iy=yIP^$m7FYHW+Zc#;C?yu(Ihu^BuSPzSyFAj_*jO0+CJ7D zi!`9O7Jb>< zD|dsLCw!keLF#T2UT5QbO)ojzfqK1Wq3Cj*o}@_PLY~=Z8tW~SYyFXH8$7MiiW@vMq)BsiOwGvRL7EpBRmgzbsGs zBN^92q1#J+pNAD|Ts$N8SLa-b9BDm7hZn5bPj;hDuz~}{!|KSV?=ItflD1o+ zzRPp8VSOt$7l`k3T<&8T#uCADC{W%t@%>FawzWb zj&E#8$56g6`V>V^dA0` zeWjJROR_pLuk8%`ZaaI)OAcfVV}8FjN4}Gj*f^0`rmq!t{=E7?Pgy+8C3RCnnc2wR zW?ni1r}OzU)G}dGzU<=rvb{C=2I|yO*<-~#@E1L~n@ykT|DaASlHYgZe?M<~m5j>F zlfm6WFq!#!x5xzyWIr~1ho^)wL!wAl2ux$CJFCw=j`#1K7HT=OGDrIE48^Wv1{j-J zG0u>U8w=`*W{pe6aa}EM9gCIysR#T?zw~;wd zd5t(5#=V|gsG2LoRu5SUglFSUa$Q-k z&6Q=*p*WC6j)nc;*&*3@YW0<}2I>ua^@gq^ed}B&_DFga`npT4qPg<&Z|YrtWu zeHO$*3w`#H+{{1ns4IW2=JaB4{k$c9`aZR`{Ho7+mn5QRm8(vr$e!TwTG{_l)A{?IF{Mdh{f%boD0P7+c2u0EFY6A z)3$`7wY%Yexvphq5(A#(Ek{1)$$~Lq*w3FgOlL*8ZtrpLL0!4PeY%Quq~{*yY!0(x ztdsiXNN)*#>5@-HIUm`VIgh8Us2b?NDekY0e4dIq%#D3b48W9*bspI`J&ZN<>U^n0 z-T)O?d$wc>Lv}W1p7jtV`3j9M^{rD`pYKaY(>I(8)UJ+9oRKSuA30wkpZdNtX*ff? zde8zdF;fqCS(qadPmJD+oYPctM$|Q5OI2WyS15*Tj)jqY)-qzy#s15on8H~OJwoxL zya5Bkt(fw6Hn|~hnK#NMkvSpopFj>EF&zc&WW(CcQ_Oq+NGs+qOpY-id?9mG#}MBx z;v?>VawUFdC?00<^6Y*~j5D@#v*XX-BJ=ElWSRZG6Zjo2At-48&i|BJHFMEdwiV}9`?cJ^~^XaYK7~C1OFte zWrOpl{7MVOJcR+Cb*zYZL7j4NU2*u6JAEF4E!C*YEr!iUlskC`J5{)LUb_RVU|N_8?L@2S5Ple zI&ASlSNCY@1E^~YWnMD%GRw#BlPP;tC`nBC^)vG1Ui4Sjqdv~DPoC9Rq1Qa(wXAto zf6TzjUJ7jidKrD0s~D6_ofqqmCnf0FzU{(@-NY?6s4?k$6h>4}LU=3Y&`~#6b7i9J z{N;nwv!hUdv=Nnta9%Kb!&;$cIX%W3joRqRvvLkWIqKSmu|C0Gaqd>3jyVd)Y$jZ< zO@AZxL^CsuvSyYKzPw^?+68(w-`Ej#IUfzuiQl(jPTYGvI;zd6+a&|%D%00ToZdi8 zB8;`bP4=!ysTn9xRG|$^Is#gZK zEps8pmMG);tMP9adNddR=drgVsJlXYr=n5xPubfSkHJztf7e$TXg)!q^`&kuU?j7t zD(dlJzlnDV^JSG&rE{nW+0m_Qw+ zE(XQI>CxXxk0JG>1!tN>(_D?Q9reg7L!HqS>iE)Jxb)sAGwP{PXmm8zyNF$N$Y54A zJvc3rMAcV~CxxT2lJ8^ta68^5x#01MKkt1X)OXPL8UAFS9O&+Yzzb1`szfa80dqnl7223w zK0o!jtD~dg_+vsZu7}yIMT=#|%ZD5vY@_bQtuJ%AhEey*{$@fS@Tu3r ziOS?$5bF4lAcGsI5tsP?k@nS5ZEoAQNvXTLAVrb@73wYRnyI@$fO<=N>h1=Fx+_w5 zBm#9O5U9Hms8F}lK;4VIdGBw$_r`etzB>k^=LSeZzWwdJ)?8CUaf>}v{ASjdvzc=p z7cafLyJIZpBzYT+2=b(#AbDOck+EW&=!O%EsjsbR!lla8ijC#<3OOKO$fHco3B|(Y z#H40%{f8;E4=%*Xt9vR;xl4ZB7J7nJBIdn7_jCB!_;Bi|L=ZkUUwX zkva(v_>eDLsS5Q)lWmxrLBGhj{W6^E*{5R|n)7vsFC-t3yx<$=SXp05jp_Cf zJue-LE*GL#>Otuk#TgWPpiX<}A5nyUg^>klt}@A*01x^*g`rt7os=)Miz%_Fyo;f4Ps5$GTVkx6&2cluNY)~ zt{PT7^-Y}rG%rYpofz5hs5qJ3Mumn)nRg#e-$@7Zb#4~IG(AS1Tp?!pA(Wm3MqItl z-0-sGrPhj-Pj^(<8L!7k^64h=zSFUf8;Kaf3=PJfPw{g8gt~6Bf@Q1{tl;9#+T62G(%JaE5t7)Ei%cCi8d6SaJw#(0@%r_b+cdgHk> zpM4$kqsjBF&gZZCh~9b~!mvz5e-cmTCX`lah2f(|MMBM7Phst=`zl@%8JaS zj6^3(?-LK&wSU~xGUU=BU!6W7sr-W9mY~RimWFk&`+lrZKY68YMAF{THp{{y|0ZR2 z?$mZ+>4la{chW5<%O7a}`+lb7Rmpef7Jo06{A%?|%hWf;+OIoO#Ztfh#-zc2KUm(T zeYGTJQ4gN+xlmN9yNBvC_Y%S!(jWd%{eG@imNcal1(t%r?>5 zFJ9(vBF}v&XWT6ea_4Kj^b6tr_KBXiX|a;aGcv3~jASmOuj3wrgwHU@h2us!aw=AK z4Pd5V1*44Js(~x_otE@ozQ0P1>NPa5s>v(u;|b$-dNG1oRg1}AoK6qj0&)|ZF)z@E zKD#`7gD>#Dvk^}Y^}r5#&i-^DC$T3rke|s}+(E8>kOpDA*Ivz`=MMdOKKCV$UZ+8E z-mk73=-*g^{Kg~9oPOeo(YrMG_a*C*iD3xYM2zaCo_;&@RxQnWGS4vYXg!oa>A_k{ z56`#s*m2h5dL=!1P+|B`QIE98p%``{47pBv{HPR;0w-o{kdHW}kshNr5Z_+FS@xVz z>X<{}QH)skV?D8ya9mkOjc8C9HZRko25X*g#ODv3U}m*T7&>@x?;yT%^ST)a!p(4d zVZ@dx^u$?WgnLC3f->n}y~u=RW+RrW%}8#@d_m$M9fQqCy~_;hIVQa6!;Jb?oMZ3e ztebVytyAPEcIWrFm!CXkLNb5eV;p&rZTWN2FdMa zJLGJJS8xVgezKO@OFwESa<13fP^ToZvAdifbH+62cLq*rZOG^S`I~!2-y@muq24yV zQwElBj^K1L6X%Jcg^&~JXkjhFb8;7Js@x|wL=WNInvXp%%lxGZ8HnD*z3VyokvmvZ z9LM0BBxk<&FUZQE`D)mF0C6l_Q0VDaCu25Pk71)zh zAf1_wd#*hF;(8Uxp03njO)8Z1NCozT$vRZ4+eBc7}*tHgjE z`O^MWp#-&~4y%O%*NZ6VZBiiL+9?sapIj~CyKWu|45`g|0X1K7#h5MkvOvP=Be!t4 z0xlgDSeVRNxFa9S^hdAdoTvJ-54_`t=;QwA97K(qRfnvjoN+42XWUG0w-|q%=|dkl z_BRQC{INw9z?>R?be}=aRDVCr*~koP3-h9O2H@&hdi4i0Yub%IK^4i%Ivm zB(f?;VZplyc+RGGTr&Ib<@|m2&)p;nKb^?m>JovVYEg)p!nr_s>gHfS%Ck4sxh`Fz^qRmX^)jp@*t~q%S3hEe_=3wYVJF*IyO^{75h%7!y?6uez8;Jew z$;P&HJNl_|FqgmAOr4Fy_u07cm)|>J$H<%6a8YQ888?y=i7J^tL@jfBc*&DdF5;nV zD$}nulzVr`<#lA%GqyM4xYkvAK2u2;^P{sb zxXSiYE^;ujsjOVtyB60=_9OY=R%bM`2(ZXENw{wz!%~H-#c%Rze7Krct0ttRnAk7x$$+cev^671% zY+R?rpjQPlQO6m}LIr%26fh1fkhj|un8^D{(JKJIj|bojHHyXW1fXP)4v8ZIunGQ{ z)WaVmeRU|Z${(di^06w+i{WF>#s@H;YQTRzr2_Wp;8fEe1AY8apSa1tXsC%45k5vc0wuKoh`NUm`p%m6(ZnQQUKE!et z^Pcf^j70mR?B82a%Q-I!x!%MQiQ76|CGVwuB(|O>wo;ECB=4Ca7DR5tFlJJmBj5L1 zB!c<%dltP=|D_jWF>-{5ko!0-5|~KbqFogJ)pHg(h@Kb;^ustyj$=pac!hlAIlMP} z@G;_S6UV0_ZFwqZ_SDZSQ&Hj*^CE~*g_Y)7C!ggYJx+=f8$7s>-Xd8ks8cQ#7fX`I zQDBAFJuA|WrDDl3em~g?3`s>XM=P@GlNZyQcwZmR@Q4?UqjtDFRgJeUrC>kr%@>^U z%_dIh#~Iek7vxTsOu>NVydP&Udn}F`R~z{Wej;`{!lOS?&Rms-{>m}&WQ`&V1ij+kUB*PK%0J9w>E58%8Baz$vq|Z)TJODe*F@NP^7R zL~S4Ivo<<{3k`BFMT z6v1Zc??G=ybDUgQl|W6QS&lle2G5U`lw)yHE1&wYal{bz#))6E1euyn-^L|IF(eq} z#G_c^!5;X1fwMASdTwX4_B%k#!jCzjuQ)TSqDDg(HOhFaVCVOoXAyU?s8D988eKkX zQ0uxH<)^ARYw#eqUWIol)VP$T7Z&k{rQV!L{_6?#W;N1RYjAIYhWvOH&M)NGIt_*| z_QVS(4f)GnC{@oB&8efw=f6eRPt3YY53eSAYW_lq(Xt*SmSml$M|0MSk(a^{Uzc8r zC8>3ZptmAtW-ZOk#&qC(@jP`e)Wa?2?`rt-M_ZB4Q#Kquy_g+f3q@;U7FUUfseA7odJO#(isZa-M6rKs!yY|hZzz604#V!_Cd}qc?#BZI?rtNl#G0>1 zJiWDJsdX)5hUJVArnZ->n=tab5iz&e*A6$L z*gkqTR$?zj+-dC{YU}=`pUYPxvNjp9ygB`*nv)+nlyk^56MDKB@w^E2q`Qqc#@C8g z5V!Fom*#l}ihpI6W(@N*I?&IXe8fT9nQM1A16NqvZ8*p}l0BbYn}KJgGBJ;jB@Sjy zxSM&hi!*U>mJJQtW?L9J; zO8zF^V585soqWg5w*SLt-0a*~jO&=qo8~SjS81dLxrDbk<8mpjM4dnd`h_SkG`CR7 zv;OjV!hGfUK=ip5fQ~f>p@w@9o@WN)^^QP#Ek-eOjeB1<{TYc@7v&87YjbkOf3k*{ zlL~X6RP_48nNLHW@sEi?tFlpPbq>;3@=WHLedjzq2z+x8V!-(5AZsJ#&Gp_?-*ftO=Ytzeja}=fy zi^AzGQLHVZi0yF?e@AZl0oE3$xi8jC!>7Ymq`9Y}OdWbhbKiUXhV!)6InWXxkFC!7 zU<|!vQ=7={d~eBcQAuU;2m5qU%dbh!@^Fw6qcZYjB+c)_1$3la0fH@XigMbex!chF%@q(gEM8Ok~dFo$PLy@ zZp5rFvhKJ{PB?3tiX(C`s0DMdi+{j^>OSK8Q6nF}X{0SPqQ(V#${CeLes@>k&3yVM zFIJ-G>LLh_D3BV{ieT!RKosrG45l9e7)Rf&J1qmLsU_d?F}GPAi|I3jW zVdB|$i}hS1aveNVvF>atM&$5JnMG`UI{Az5=-XS!4AB?ai1sEnpFv-TJB{RLq?`13 z>LtUkwve%op0fD8r#M|Jlol=M5lIe)jl7U~2@d$#NP#Eefmp2%z*yG4l{N-plR5x< z4+SEgHR;qR}>o(*xF;ompQx(kpuu`LCVG zCvqc4h1crUJDxRDG;-sim+T+wAvagK$>c98@%Y(ThO$R+%2#5=a|Jy0N(9@K7`Z@+ zedhw;dy*bkr-JZrgMs+HjC0pgIyB}CF?eefZgLGZ=@x}gzLBV#5QT}0Q_+eX&*o23 zQH`I?kiltqTa7jHnrz%F!+a|>J&ZX=IY*w;zJ2sTsbP}S^slSkJYKrHnWe}JgD8nB z)NHQ7OYXUqlF2vk>`6~?Z)huM;8Cc@r!aE9bII=xq`%dgaEvO#d;;!48@c}^wlHJk zUV6!%p#SR*;)Ud2Eb+?3(mBLsT4!Jy@A)@xnHfxuUeoWy@5wV5--~ksYM8qbFMaCD z*KZgv-Dby&+Se#W4;UppJ6^u`@Pvzn8phsU_@HfsSqGTy+){;RzTtQr9ge5d=}WXZ z47Q%kRcN4xGkf973rz5{(l?3yZ{9ENncPD|8*p#)WiLBC6E*nWTK6M2C5=5Vu`|m) zg|;Ozx^;D#14AtN^Ct2vi_mLur&)%O>lx&nAg3-fM`gZID!G$S5TM57isa&_d&2RB z26r4aP;k$mF+Utb?$MudgC5mdhocwqg~1cZIX`T~fy4A1{A0$)T4wzIX@cuaa=giL zSe9%eU{ds5;=S9vhXO=ftz%B1gVG2Uc;@I5yvx`zE&PX!*tDbe7p0?B_BNdKHC>l1Vc z$_qpTatOmz1IhUgfIf^l*!huoKA(QIwWCm)=hjYs9Un|T_=~9+$^E$wJz=*vq+v`m z_RSxdJAEM=<#qHPd`0aM_v&@5(OnGmM!f7Tt6dsN`R<;Qo9-gF?l+Pa``zVNav?PW zg>s&}y{*JsYSmKWN^qgPcMHVgvjOO_mp+j{1IRZB!1!-|2qu3qn`hX-B=$8AqwuXN z_vg`(_|lJ`N8eQJV6W2UBE6!7y+tQ#1#0AA$TRu@mB_&xZ4Npf&&J*y?$0;9#rGd? z=|JDXUF4shF=_-c9#UMVL^tls-oJ`qNi6Xn_LnJ}c%~KT;CxSqokN1Km^m5?%LQV^ zd1mPqaDV2$+&zLGSpB0ghv)s1_B`kRNuw4a6;D}fj6KY=b!{r1g;FC{B?nH$$Z2ew zgUs2?YPe1=!`2)u+TkWk70fJ&R*U=TmXi8jEnA`+OVfJPz}};`r?V0{(F*n}_MeYf_gthl;0^1bH<1`$k3Nn4s9|7^;r#h&DF4}t z3*-$hKE$=t-imp|7OL>P>P9`+RweTodA^srN1vWI?oyn7qvsxLuY)J49F7}vn4#R?4DD9xg*aClUDCwb-G~Xb=v&@|Gmd}^?(fX5QDtHa@Aq=2 zcy3*%pK!WDTScMNR^b01Xj5plKFqsHV}@J%1bLz2?0W-q)h@?M%~PK6{pbbL4-Jm5 zrLS-=HBPZ7+HR+}-^y?_Js6HL)55Xwsh%3GP_)sR(T_F!tSCp5w33mgHV-exT51D(GMG*eEmim}JfugE+NJ zkP2Fp40BAB>YTl-9m7^)g}onF;rOnK;V5@KPzIR!LstPx`~y z=kmRHDYQ4mET={qC03mv_iM7B{F@+q=v{JcswY;jQ)3%zjQ{xQbUo*V=XaThy<3mh zoB8_MaBNA}qtO68h6L-OElscEh2#??^56dSJa#2F|GW`8>J?s%rY65`1}5`bMO@`s z+9Lzy3KZHi{izM$Os(2)h4upYUZ_`C<(w$9=O&1aJp3B34$02*N9em^mbXhe)7Ywk z!yZr6W&U;5ZJak$_C!zmA3o0x$DT{{_3RXmHYs6vG?jCKWeFH&qeg8IeT6H~55FOM zDb0)5+Gx6mJXI2w3@u?_#p1qv)9#m-0l~!t>-BoDSJTLx|hq}DKNhTCE zN~uZ)sYUPOErsOfIvtg-56G!3O+IC|28E$qKV!JQ*OJdjzUP{~dh9tBjyj*{H~%qGfhmu5=vABy?rK?Htw3ayAAXl$Uh~ov zRJp*6nf2snaew-@$PX2_MbN7(1*eFImKx(MEx5POZb>cv03uV)yIBHXxNutVlN01`l~UT!D=| zLzeS>J{(AV%EgX1Yn-I*0rCVhh~XLNOE@qEUnbd6ceArJwB*b7mCRb%#Qx}3GL8~| z`eRVZ+A9U(bV7$p{`7@>k&MgF?1)WkC})}#%8-tJ*cVJZk9+;|p4rH{;wm0B@}2k$f@k;|EtoVB>b;V?4tx$JEk$PJwu{XRDVLfuY>5cl@+t zS`X$?5mPPmi~a*e$WsgEURg66_~9nIcI8UYYJW^1Ca)*IugMDHUi%%T)~Et;-RO^w zha!;MGX*EF65l%GD7g&^#Iw9VYVV9hpY6%04r0+c&N8nUan`QPWuDLHaZJU^q-=cV z9A)>_LMhXbe91HH&6-jd$mYqeB5n5nmeXASTPrhndlGrRSL|qhl-?b|3iKJl=h+g8Rijfdmd`U`XFX}_ zu0ZE%0qDTl$FpDbqYTVOlG0616Kj}e^@Fu8d-j$on3qJ{GT%wcJ^w37vzXDw%K_li(Pw|ko4e4unnfINJJl4CsFV53nuajE5evrp^Mh6Xfb|a@# z|H%8R{WZQW^Mbd`q^^|f(~}r-cVenp)f>vhx%6Fq=7+QVyYlia&i{I$9gNZ-bw z2(BM^VOEop`wsGvStpl?_K=FFa^-}L z-UhtB=a!M5ILD4Y+tl)UwE`^~_~YtrUSH0JN=Mk~tL`R!p5;nwXXc5M4`^A=nUgE| zq?;ScB=Qq`^weR~NaF9im=Au|j<)uOGN&E0rB?c*WK+(%dXpbIJR9}-J{K*_7w6Od zDC9n)Ab#-vAFkWs&QfGqzC12Uo-#iluOn9U@67eNTO&1Z{FO6#0r)YO{KslmG~)g+ zk~0_&)?0Hc1`!93fZb%p=o!p+-t8_1KLwU8VxE+qx>;x9U26Jux~Qe+pWpI?`^=`> zynpA?>tii-j_eJ(uP^_$-*2Dhr;k@n$Ys9Ha_7#K3 ztJU(p-WGtr?vZ%l!#aDmow^3{XVZSm^l%-@_KC!uF{~*=ImbHQP$m?ie}#^9a|vcl zJWWCMlkaijzLTVJKM$#@L+GRkD0u(=-9_Fm_p1ea^TgGK{<$l;Z*W~XwaUiB9o3}& z^gNl)^TMwTXNmsw9Z9z1rK_`;PvlGT2|x7Yb+1{8vj(Fb`-zKht*6FYtsc2kr~{vz zj@{(%RA#N_9z@?pdLjL~WW+`f8;W-#Kjnx~dR|c@@=z!qk1h8Rg8FT%-*zHjx(znj7tI(a~zn3EpPk&F6XDm;F6) z>#Ns|_`#n)w7U>psu|_^UKOg>qvmA2i8X-@{ofbjT5h}y>O%iJCG#P&jo4b7xrpqS z>qZ;p_YW1m(#P$786#G&q9(5@`EF&*vaYd)wH|$-4jQ0{r*|{|t}YMgldx3<-^t7u zE>A82aoWFC6xy0K<0ZJVJI)*mLz5BY6&AB$?~+39Pciagg&Hr&wWvbwLFXd$E1aRw z-YsvIn5QcI`)XXa>cx8Y$WK0Y*7j`(?CvorY= zHI3*}k=c-}O?33?ioB{qy(4;<8yRuJi+Qg-iPQMdSCLtuUA8k<+Qo!9rRmSe8gIa% zIMMXuyum#bwTKCo_{Qhisn8z1YLuK;9`qlfKV44~yj?P|cep}ppx0N>EDb&7=z&#_ z{0Z=V?jnzAkU>;;HTVoYdc8E_MQ0ljtI+0LjTgs24X(M+FDrz4%;`2%n6J=w@`#o3 zMm4?OsAo+vQP;`b3u0cf%^<%A(a(!BfZY8?=7=!&i0f_X<5+1sONDBwp~Nrg7kSsl z+&6`G-jX;u=B`H0Aw71tB>phZMjlup+N_I{p=(sQdM^wkZjo1VEFHIby`Jo+&tNYP zOfrR`Kur&Xem1;f-P?uv-Kj2WoZJ?Q6+3x-HDod}Ka?nHVo#Rr zP}H{?;Xj%A6}-N$Ud2g|95q5JQ1g7(fNM$V7}1aZm0|Hxa=Qv2t1_Qs81sTB+we|R z$V?rh1e9Y|*E#Zt`x`OQNPcKHg?4h(L3#g7gV;CpDC@>`m~VsQ;X;H~HA#`<9?;d& zGaH9<4;A?=e7w7o`Px|;9QqiFuFDK?IFOFfj|wrcb(|C|Rbd7_%hJ3#JK?&Geo%;% zvIe=gjq9YE9+PU3Z+OUt&ZBs}Hphs9pU;3PeQu8jS7QX zHTs3zRkwaVPYk5jfzi0Z8Zb-*SvqD>& zJmp@zFBbFu-B-?tgtqBWu2pDL+Q&)mN_SM@{BW8umpq0%cRo+j)L2~ zZ5D~s?y|NFoH_y7ODkN@X){?o&itZ>w_XXcRP;*Z*#dswZvZ`XTElO8P} zYzh57(=zvdmc?~a(WJ`bu3G{>lubVAYDx-qyl2_G(K-33_ZZ9WTJ@6(XWuwib;vi% z-i5W3o9$a^30N|@UHjoz&Mh45ncPP4ASu0xi?4B6>E!YAuO`*bOHFbg{l<5G>14~S z8aLWaDs{lpsq6iA8?}$xecKt)cEPmyN$u1JrQVr1v6qh%YncS;PCw78+l+FZzPz7S zbFZpNPaK}XYk!%=K&@fBVhK{Kkx_Q7iIduk<3*WA-^N)+ImSLYooC&fI|pP(<3tJI zSNnO1@^BZ=#Y6EjXG4O_jxo!nA;j$I^*G;&{KX-0vi)t0TpDbWeu42)zp+^~$J8h~ zg#L+r)mYJAjeoxJnsJ{VOz)hu7;+c`IB#yEf~krp7S~YYS|@rmJM+Bf+Sxr=gPQ@K z2(QD;D4t~wS!$e5BbR-p7hYFqhJ8m3vf8LICWABWVDcUtY2bL4`hK31Ku8|3E#whU;O<4a1v<lsbCP*l#OpXw}f6zl3ynR~O&MxSVE5YoDbBj!B6Pp)Ko zR0y2=vaVRIM|s{K$1^w&XFXw9Ms35IFk=7AyXt9%x}+JWw{d3i%79=eBkJ5Y0{7|1 zV=>}cX){v3(5K-N@rJcVYju^u z^L)sU_9Q;^%LWDa(o@+se9>~x_NQOLpbWU~vf)#4W)N}~@|ZQ(d18SBLb>OL^R-Xg zaE9mQ^gHPozs6m@-Kj55UmD5|@)SQf&@Y`{is3gJ$c=!8@;*f^I?hGCiQ{hjsh0kw zG&0WWCJwupqu{KPvjbg4rFWC&gWcuJS0@=z%U!1RZYnb}ykvWbhYZ}R5sPnqIr~e+ zTy>31e(NkgI#*dX&`qva^pJ?3ZZha!Z>d|!T{e2Ti>?E8_tV(7A5>uA_X5$9J5_zO z67!E1NHq0{f$UiW{>_t5{h8lqQ{W(d;6{I^-fDBcoFK>X=hs5&!I=BgT7g#NKknu8 zWy%A0>!w`%GZZFpC}ww{-M5)M51jKlYvh*j$F5^ko7t z@xDJQ(i`%LU59SZ{qePv|9>+UmdDZOKQ971`bUt`{4{K7i(tvKOnMb&?p=dhjHutf43?@$}N+loG`tvLUQ`4!DmFzb>P!M^lt zuv+2T^FLZ%D<1IYeJ1i}W)o8%$hpHqYG;YFzwE^4X5W33y{pp~D-NVs@wOg4=k}#w z@zM7%_-2y}%o+OGY|NQOjuiX7C8e|J18B#&-^`TWVn@?+w1EGMRUio~g<+8KI2z!GN`OtRx!7_L3=N`w5qXGEblGnD=F}>nF2Sz zEAaM>0**Tir0$%*61+@-wT+e7T1J6cp9*9Bg!JVJr)g#}`q zp@1`ajvC&NjyDRWdq|-qR^vRdJ#~8X3MKA3`Nqt9ubjpEuS&k`KFRy}R-Po-^Cdb$ ziP3G8^gSZ)WE}5T-vKb%IQ#kHk2+O|S;p!x{-Zy3b~&? zPwADhjeR}u=|1IyQ2H9Rw#@7BAMB5A)%-EBg$~a(QK++v_fiRBbec#c6LWn;PU7xq zk+{v7STO%BX(ApJAA#MR)%E!riH4UWVRR(tmzmO010qmkCUZo1zYQzOEH4}H6%~1l zYa&rSm-o^d`h}d0L`yGnA-7XcS}_W7p;6fOAOiESh8BZmnr7jhRV(5eRAq9q}R(zO9&cy<9Lk1CdZD2)( ztQ553{WX+0NP0NAj)I{S0SpT>H1L(07XXXhAuC?aXGT zfgQiPk~{3f3>p5+gErK@&(6jMVqi5}GIx*P58s%L9a(m?Yfc=hLJsyvlK)8l$qBn1 z*H=Ir!Dv9 zb+jBf*V{5`z{8}7iF!+efqN`qCbdsWgk?(ChL%MG2V1ghu4tF{B;2>iF^Be}H`YlW z(Wy_8IV?Hp_T5ds?+X|CuAd)dIsGP1njbaDi!%nP*wP@;l?`&-iJBqiTAW;DmVx!+ zWn^5ONNei5tZ}kDI8HkDh>_l3j8cW%k$rdR|2^Qa+_@hw#i*e&*vJJCer@8s&>Sxx zse6e$$t>%6hov<=t5y(4X>W>?=+~?%H^)l1k#RE1Y?f)WV@0Ph%0I>F5A|7%rhPe| z@>C(>g9pylW(G9pFoW6uoS}EO=`FpzEgI;rs*%B(FIc6);acoz{;JTYf(k3^YH**= zQSF)ng+j%lK^mEwP3%~ zk(#?)4=gRO$IL~cC`E0G-_kH*M|!*n(Bsb)au&ncJFq5vOV91ap<&E+rFKk74&#?F z1kR!N*SRo!ZonF^nH~$W*iSE@wvznENp_wqTqum(MHlA1gIOsU@N(e@B8cxb@l14c+y8`d~*4%pjE8 zDV2fxS=11&q^CA}-6cQi)%}!M-!$SZ-!rgciVdy{_}IV<_>^UDZcB$tKW26uWNyJG z`YS%pU_LHA9A8m)xygnxA2YCYE-{Y1%m=y2OzPz}-kan{*5~(zWFUJgGvUf-&^y`2 zx$*zyGakL{BQNT!#qEbXeM3Fu>@2l7_WtA2_akQq^! zbu|*>8q*^;)rwc#OD~p5LyvB(NxCzWvbzr*z!{tJ0U!w@l_awiPy#AUk74UWsK(8e_taTZPhG*yv z92|g8JkyMO=xuO@`+saCo)X6{)`;2@)_23tSgC2X;zw306x^d-e$yW%jx)tU*%+9e zjWU_pc=3_G(3v^NYr(qbHu;o2RgwbwR|YY=>kH>_7AG0RGkVfpp8F#e82OBTTLA^K zVxWTOFMW%52BOZLAT&)5!k#|N$mDgakrIg$)uYg93$NGaDEv6UET%dCGmom)HkCPy z)R+ur7B_3Of@-O#V$8AVoU*(U$w&!x?(arWXEuSonXrjUib^WH&VxuabLH)z$1(yE5xz0Qrj#>BmS+xbkv^Hi{UP z=CnfF`7!x$^sMyQYLM6TwkkrL#IV3D3(22ff1009H7|5~LEph@o>=SWiI#qPC|>JP zSY!ROK_tnfjWM0KA zPek~5VZkM4G7Z$=K!_fblgMKXrO%cv9Cya?Ji9?I|7e~!!~wrfH_;1#9E`8Lepkpp zeN8?)_v5Hm%rLD=E(rCD=SNZVK8rkutMt?)XE2D|hw_W53I7l8^FxB{f0ZcL^3C#W zMFO)J%`%KQ)9Fdfl;L$coJOyPdHm|5Mmyp(nbZhW+0XUUD;%5oxhzod+T}Cz`L_w` z^=33{VaBy1X6R0s@Gzfv;R9wy{3RE@+5>#!`uV;h10P0`LrBg=eNUzKgO%CN^_ALy zvPx~YNWMqM1bO@Os1%$c1{PwLmzz1iaWTr@Ku@d>@}LSRZ8uhdDNeCcJpEp=PrX4+D!vFPw{Cg7h@XB-ilr_)=rP%3XNp4dt+%+$pOKk z%z;xY(fg+obG7{M?$k{#(-E`L;gn|(ZciaU?i0Dx4+HRc4)5*Zc@ShA=;92A91b)vCT%^sS)^|^E_JwBL)r%1&?ixnGqcG~-pmyu3= z5OVOI=h^4d*+{78DvPIj$koyFLg@W*h7D0kKLSk3XY9rNCQ_H7}QKwyEc`a5MoY+ZgQ-E znT9!$dh6w5v&ekJ$uaXW&$erjL#q<0QeU3Lp;nk@q zjN$pUXhkIU?y#b~iQJDZsW|%6iovI?xcbS8P*-|7HK%vwPLH(b|c;}+LT zpTRlsn!~P+GsJNEA7;+r5cSfWA?nv}J$oJzDO|ByQ-qZ9Cis8AQkc!E5 z=rL@!VtbKP9NR{ZtcD*@dqp;?Y@zSyRn}#%$&r~szt0ATWu(J@GP3B0!d|BC63$7iy}eXizki{VN2CXJMXC3~T$#1;+_UfA-M3CE_Rdn z&c5_4Ayw_Z=S@JJc)fW4{D+(g7q34<5#z~q1baI z41EjflQ4@tCHudr!Fs&jO>dP=37AM+|LH3emc~*iu#eX(kZUHw27@1YohEV-NpdK4arQ&Qhyi zo@^uUsqr87O(4dzow!L?cX>KqiPPkNIj)Mtk+M_FpgZhQQdkblUxB5qc^gcS}I$#rh&DO-={OZl4v&{rFQYQ6bB z8!@Bfa|8OU1a;Dn_+gOPSwb){dw}>upf>TL?G*P3ijP0-gB~n^d*jH z9>&_A_;pEd;>QQL=OjAG$))*%lm2K|ClU!CQ_%S*aaT)2*+%?w%d-Jk{Wt<$E|Ir* z&5jq9-K6J)ztY4q0GDes7p1xtj zNH#hIHEEYdk~eYZE%n5w8hz7F4#32Z5x7#8dAN_W;Wo`#T9wO{ zem=~h-cHZul2#m^la1jwoTXrHf!wU^k79F}vrK$EQe#I0jk^q_-{q4h{uuc+0?*S@ zP-G$Vo!y*ee4RYm@210YK7Tjz8PjWI<4FhpUG(XDyibRp0nD0to{V#&=+pPpMKS{N z#gCfuo4+IQxses-PIjbhbCjds3grH8e~i5nfp>%XIk&N6#4=C0YgS^)cYj#&Bk=FW z6lC_Y9B+TZl$lKAbuQu>z>z>`Gb_0aD$lz^ks-OThT*7EO48PtlXI^10!_g8PYeC z8tm{F%quVICgoQu(2YKogQ{^}u{s4)-`erVNh3~irO0>VdS20#ewU9@kiojbaJ!CddsHYBI?>Z0jJW$m z^0JMrS?{>W^uR*V*6>Hww&V{wSh;7=SNw;gENa5s^V&Lcu_DnW*NS#VJLZ)luaI^9 z1b#lN!XuEVPr-~n)Db2%7R8=I89RwHglMkMt10+EUf$0MUNUNIp*+j*C$~HTfBzx> z^bdV0`n$=SdIgfaioDK4QE+-q9xijds{=@$+B%+)3IO=1S^8e@uQBfw?`1ueT;&n>qDQZqeuTtUuHbn0L>= zclH1~bSE2%qPqf1dgw5Kyh3##GtbuXe!O2#bUq5Wdg|c$obv-G&dE;MQN5;G?yV}2 zuqFXm@rd5>#uV0=%t6vSOFsR=r(ENH-b3|BrOLrbChk*H0(T>|&T(mRDc=w=mCc3O&6IoENgksm;%=_GdS78>+yq zTl9KaP4D_HDLAo+xKB4{aa)-y%Z&cGk;8hs3-_@QJH92x%gg&7&8Xd?YXj~rp+1pk>RrPDdDg)LPOM?PrjkFEM?P0> zAj35ps}ktyXhC^snE8VXArON9=P0?J$XG7LdIkusUd5DP5Z@OPla<^ zsA0WhK*b^%I6!{T+ac7PZgR%}XZk#@GNQ^{@{A@cw9CV&M?Iy&v*lrUoomFK$#~hqeBK^o$)o&bz*1rqL>ipaeGjsC-d-)dBLb49s+}9vtB=5`?g2=5Vq>&GGEr|8beWPq2tHvZ^H@;iB zPLk76E3^;>YH!qCyr|(P*1y__PPc6+R)U}NK$Fz0uf}>u;ykmB7}=g)?uQCd|2=c4 zJ2Q)FZWy}rb(4v2Z+u#aj#HR#zJR*UhG9^&HzKEv4dx!yt&)$aD$V=|K7V;1BUAEAflX#3z0;2mJew7}>Z{!#to+bS_4Yh>qM07p~98%x*oY!tpZnXLMoCZynb0 zKMK)gG}oIO^~{gL&}yj>f9&ZW`9>*)z<1a_sv)Rn&QZH+Q{ojVj& zLNR?2=L*H?nZ=s_H~C_Vl6YOX9^QW?kMaolVhZ~1xyQ)zcnzBMVJ-c|h=-$yd37LP zue?z@{-ef3^6bVwGoZx|a!!^O;`Z`5*%+us80RqeI~#FwD19wgv&ZNaBSWitAn!8y zXk5?JyvZXADa6H-anikk2QG9E#ZBT!^@ux;(kisgTOE*q!zwJ;5<<^p1OBWe|1^R= zkM!tRy;%kC3Sn65U_$W*HgqMQv{Ei}isRMD%v*#VW$5!*H{-v)iVNILvSbwbxoyaM z9d1Bi8FF8EKmJ-BBZECu*mpGq*MHG>FO9rQ;&x}M#z;Tb@H?GC@pOfWeGNVJ=P(Cc zZIIIR^_cb{4E4i|_&Ujkn_P$36eI7rUyYlmN2Np~Vqeo&v;i|o%F=5tkeLHXA-G8l z(OQ)ET~pq_;jyx9nmcMM^{CGK>py%<2Yx<%|22p&`N-2-Gk4a(h)lkp?MmKXH%(Hy zCHZ%G^o!JyuRV=DNm?P6{EC;`b^!qqpi0XbuiQzs_b7B|{aKD=7VZ)r=h0u~eUgId&5BH@! z?&tPB%$*;~znA>SQoHEad4&2rtr6-S?3-usb1QpL^kvj262uI*E7ZK7O~<8H|I>&4 z|L_?vt+-;jnKIQfc%8{|WLULitNp6wg#W~3-!rw7CzKDjDCv#!-KSY{)RC1*rjmV< z%M{z&Zgr}_L_t55~qh2*HYar{# zxv!3k=(qeaUiy3@){@3GNbg1S;zXIlIrgX@M#;{LmyPs39YDT(trN^TNHI#QW&gqO z4Kk7(--BMvp_*%u-kf#dApH_J>!`AsJXmO8GSRzn! z)L;!W*s0fyCGT;H3Qhkq&w8^4ZxTG|lgxdIXXNTEHO7&znB_t3#Tw3(SA^oyE8aGx~r;a30_Yw$oR}$*333V@$JJ0uxJMJHFe>kJ3Kq*c3-fOM-&iPE# z3Fqgk=rE)$eeR`nIKg>Df6hkq!tb-0zw+}vCsO|^9|Mnv(MYSr=L_$lt<*6dpVpxU zzyCi8^gfr=p;l>f8OJc65lBX?&dA;v_WD&|-nSmLmYW82n?ZKYegpRWHlXP_BT6Y! z&~i7qizf}3`G~zwBMtDsZ$yEI0S%jx={SWQ)y2pKh@vlQtGV**VC$hT|w_8?OBN z9#%YR%2@~3-M##N>e-xSSEuLs6aA3h?Gtftvc7I{J)$7 zjPjIt7qZh6yrc`WLUEjXzU^E`+E*i2e!Nl=;+fl9rjm;5eC6#xH+k}Jec2l9DJQgn za;QW@dHXgt-#O`3KTwDAeu?}GM8uG=7)aE z zEKdrI1roSKf%OgZ#I2S?x^~DHPtM=tYUfEYFNZv1-aopF6L!7Im*f@&Vn3{bhbq58dfo>_DC)v++}x@Xxjj$F2wA&~E3PoaCN>^7Bbw(lbsw_#uhQG-#;@m}yGrKKKTkPF*ha6^BeEl|G6Ty$U%=0$l`~`Z z=}dg{&qVCA40;bU5J2zb$jTXb_L&_evD9-qn{l7ITBSYwyJP5kJZpw|12cZ~Kh+*& zL)VAY`JUTwmgoFQEA2Q$w!zP9cC5H*LtHts7m9GEbIA^U4)rUw9Xh2Qqt4LJSUd-# z$C4rUjQO)(Ir#RNU(<?cE+u{+zEp5dMKr1L*sQoL7?e5<6A_i8us zt>q)%_5L#Bi@!{o9w_mRJS6xYy}};8()U$>#EobmBMy?upjAo!R3GW!>LI=}d?Y57 zx#UUiQoBfiO!oAZja7ZcLe^?*M|x1;A|K{@%B6i?a;!MB#q<_-slYz>Qwof#l`qz; zJh?S0k360{c|omFJ+MHY^v##pGk>J^JbwOEz8rh4Krwxu1h^N-)Y1j==xUyf>+g&q z-ef&>qKD*?f>~0Bm`^!mvr571jlM|gIjfc{FgG?|;^>KNUx_@%GRYQdFkI1+7pTDo6Z_3RXmBi7L+`y7z4p_8 zm`ML3d)gPz2}j#G8r0gXK}?GXJP4&0xGW4u$AshiIt^~E4#$kb&Od^ATV|QPsI&6S{zk)|vO?5osT+7*VwQFry$fadv8U`( zQ|YmgxWvQtPUHmGf5KXXjLA zOiky#lS{_qznM7B@7et?wV`~@s{T;pJw-O!olK~2u?N1k8R1UszgWfZ$6uSwHN$_G z4L9qP1$NCwz8v+fs?7cd*%7;g8S+x}FlssDx=($D8glS#8%ExwZ`fo*iIbdvWiao} z`=$C*cD;YGV{cFnoJ{09PPE~3v>jK-MR}6Xx#o82>by^jWY{qHBsIwoHdt!g(U^M6 z_x-$=`L%(<8SE3ysNO$+T4OCCF7@Ep{|D6wUD?mWZJhRw{Q zF)LN;`F>ecja-uz?78Bed{U!CncOBtV#(1M%=utypH$IUlVwO5qr47grY@Otx@(D2 zu1>Oi3m}WJOrjW=b-YCOw_mvg2`y!mdq|R>O_i8(*B9C;%!2k*BIZ4{0~OhdJIK<` z_d%U}&W0Yahmze3Pk6p*)Lx0nhm~+y#xry(bF^oenboLJ`Kk(?Dv+r(%nwhl`r^<= zC02A|mZl3kKDRR87pOv#54)(_G4pjtiGJ1Sot(tH~3A;Ov5#g9DCj@KdbP85pw;8~`U4l$lOyeP!k zRY)|_$${@QpL@LK6&+_0n^Njqwb`58gemeA8z`bP&9eKX< zkWw%Y9(_5#=oQ*^--1pHxySrq zLA5w~8)N8?9Av?+a#l<}VZo}m79>);nzYM;m0hgx&~e{M%^~Z#1snGMKR@Fza<@yZ z36Qlr{N!VyK$*3+k$fAi zvWmXJ!YE)#iLa`iaJ z-|&<7eGB&3f#MX{Sb~^a2;JFO-iHT> zn~O@C_ap;x5j`M{%vc%BpNHDKDbF{f)Owo$Mnw;yFV&Ib2(_xepzq$A)$p z=s$?uuM3&*pw|AgtC<{xOcWZ!jLJ4U4#t0gzGM!%3?%!@jqBAqA6bx7UtB->NKG)PEu@&~D-7Ju)DlJnSqG}#aO70e6AF$W#W zKFkU_Xn3aX|D9*w+4*=*NBW1 z>e(}_cs?W>HQtgZ`;|SJ8a}H+$-2s5kSJC_6&928zsj@9Q zRjf(L;;v7YzmX}@mHx%@lbElhrvJJP*R5yls~GK%+dJs@Y)>zvf_eJN)CcItSp1P1 z!6A0%oHMe|)rcw6>BVTtUgf|P%op|$WpQ@Uls{82pS>IC>uznu*hTcCggdDxlKs`2 zy~=88mi6XS&om~Z}B)RC4BH9eUC=X74*%}KVzFp76R9~0Gadzu;A`eX0G}E4Cd>zmip|bB?`4ab>qfoQ)R+! zqb#O=HKQnVzB$Zw#2ICGGe0=unV-EtpUgca28a6NV=wAf*-?1YDH`qm<(hwyj4SGk zE<>rQdZb`y33@%Pe2=U~{NB&kDv~*as@eD&OCP@73TOJ7@_&=L#r5)0HD1H}6l!12 zwqEhQ+G)1rVrxzy9lDGuYh)t1cK zPs|}k>hYv5dlTF<5i%+hp6BW7P9(3E-s+m%&$s7Vabj-{CRo_*{Lzj*>+SFv$@NU< zCz_58rS%4K5hDVmDf=WV-w%>u(ezYSD3B9F74RKImhLTzA%E>{+f^oRK!*v$5nz=DHeEOISg!FvyUfa|V}hn8|}+4`pB`e)6?x z%KiN3mF$^5%U`cE%2_S0(FkcHWn) z$Q1TZ*HBK8aqVL6vzSK&PBe`q?~Yw`^VuO4xyL&CUU)96F)bbux%8XH zbA6{)kyv2Hg1*dpEvJ8w=lm%HayXyh+TPucDkbP0;2GxNDSuhEzmb?M9`ZSd+{!gU zVj4^DPrL%>emdc*8$I|F6&O*{8P(`RwN}<(Tcid)!^2UwcqIPat;O}b)NuH^1U`vH z<5l#Abf;D`HxA`$==olm;Y8-p9=O{^-AQ)@VDiKVBp6d8mSjS|e+^?+<84)ye-c0gY3 zKqV&d+33HC8Tx+YMa-nXdz}t9j_6?KUfuSd>%|}=)cz?LzSD?7Cz%PN)*9c+2>VO& z2iIEBEQEbEMXcEQgnQ&^*?3N--r)=EQ;r}9@u)%_m_jb%5rw+NQ?8#EIs2@zPr4;1 z$(L(9e`Oe@{Apht-l{~ozRU^GN7%E13a_U4;Y%SMylgsl?dTA9oZiYD9dw8IoDOAI z&nou9o#jmOh7nz<`v$9+W#Y4W0iQv|>0|u&Dt&v;$w}w_dc}6~^|BRe=gsuw)5my< zGv3ksdGI1dMv%Gxl^l>h9m)QSPLXT$S!NChK%cVoFFy9ghu>VgnyWBzl`lGZGRxIf zhXcR(njFyKrAddRCDg%dr6Po0#_PE}YrNzQ!L{>4`c^}%$7`bryxdhJAJ7Iy8IM?7!NIk#V)j5o@!I{W4PkyL56%@2<> zO8C%c>31jq8`k?{vx9R3u2;{!Vz6jt6m~X^!4mF0s<(=Px)5jXZd|*leLJY1H{!YG zKORTVDCPmUhN@Rmvz}-{=~(tS`dE?Tt5AQ`E7UzWyL4TkP%q>D<7X0imU9f^5wu^P zk>4beEKl6XI_A&wG{+BqyU9to!VUp{KLoT?!8urkvi~rv@Gc6k=0!vIhU@!A9q)5` z3D?m}xyXoX)5!WMYNU6H8M7P%44fZM%VHPOTq}B0BVXxaWtSNL>*b^_NK>e{^x&+D zKbP!QsQYXoKZ!ZQEm!u*_|J**fY;6iW)Ej}OqOG_=wTi}~V0f0N>RERN~v(^<{_ z)}wB6x+XjC7li$f|E0wVa_(};NwmAkl|Zg1{^4lZlfL&s={Pyl1_eJJ!ToKI6=gId?{8Zsz*Qz?b>5`xi>^zEq}fXk{^K*7NC)n_|PfV?NUFa=v(d4?}*3 zSUi88fhu?2!#KcKJZn-%+(G@^v;lqVlRL(Jy645(a~1{qFv0>FJKRB!+O%Qaju-75Qa;p zSZaJcZ|<{^o#DdXbp;;XV~_TWI6O;ZKQ-86n@unO-8>1&3Bx-2zjQ8UoZw#FIm|~A zsi7X=^SpYESRAjJfd&0-SVX^7ZpI(^{-qc4O2y&>^|f9D$UPk6E^on5|w6CBTVzQed!T=XDc&zJA}VHaub#7?i}?7KoNHf^Ub zEX#)Pzq}~Si|9%ubu+0ZB)>71u%qcf2E)`qqIo)UOHUsi3PpN_BFCuT^l zo&n(O^~Qu;5smTG1=w#K6G>I@t? zZ^LqOC(D<~mjaJ)tfkLRj%J{tjoR#SSIMFd63Kn+(HF7!Iwk{|-}vw4+~8f~d>PB< zM#9oqc%I9^_BwWS^{69ty?C8$WS1E4Bkyq;Xi}N`p!2>GfB28Y_S7<)t4GcC8RXB} zvC>*sR#g8hXHvt^gV$~Q68!n8i>#aHA#0B~(VNCT>v4SF$I+*m#M#WMdh*Ud{vhw) z1DVXc9LwO@*3KMQU9l!R z6zWxJ)*#F+uP4=$MmFK^DVOXm; z1P{zWwNf_Z@ZUR}zVE)g9=e{|Kz3gS`gHh@=k6wR{uW5Nd0}w#j)U=31{x*vv zSC;~b{Lu^5ij#kO(~NIJ>e<$O8Rvcn^{fCw&KeU;v93)rqde<=A_aJ|^H+iN$^i3ad zkzRfUlA;d7>PNAdb07oHH!~NS;wh86A=*~ zL}|$V(bVOf?Uyj%DnFiZ+<`-G|K%R2H@oYw;T*Ydoh)eYPM+6+WGV5R`<2V|@r^TJ z7`4$m=N)LqT-`}>&35s8853&2Dqs54m{I&tZjWqytitBHI_3)K58~c(lBWZ+WA@02 z!OYvGMkB_FS^>4vsv{KYX)f&1*y@e*g}6VQmW!yV>D22M+%tYz())!-ka^Iz)PvMpYq2wpp2a})JR)rb-cU^zO9_l4l zY@f$HXnW2YzWR{s7fpN;^De3M2T;p67`IpaN~)l{&3RH~!L*JY_NzNtu;=3XWIYY?};OpO=`hs^2`m=s2@w+t{S@b4Fa;SfcqsXR76+C^?Uis(A2g*dRi|w-!X{-Qzc;_WMUqrnNPi6bnk%(p zr_y)wH&3yjIzLh3&eI21Ga71@0dJ~XFoZfn)ka2U!F@6E#XMZ_p{90~J~ir7Wtt?* z`KmscyC(|e1{h$f#`k?PyE9Jgk%#T60j-XP|J7t%UPxWPIJxosITye4MT-$pSl^cK z`wI(d^mE|&0QPTvWv7+rJS^w?zSGHqe+JR-c5{#H`bDA|mG7E$Fem!s^pRtk(R&O19S`27; zJPY%?E7X=6MsfM3L>~=%t>{y^H6#n)8!Oa{&L@fGy%PI*CbPDrU#uv7$MpZsPu?Rz zHGQz%MTc1GR;`!O7kN>kzWUQ3W4*{vTgncUk9=SLdp$=nYrAN-#8o5Lg7cO(2iebV z&qBFP}XY<&0M3zsm?-7G#mj znVGOhJeBM|`zH$dI}P~JfHRzS3U$mhdb(zi6*7qV>)vGl^ZBrr`K1@^i~l*E{K^~i zu#)=e)d+T?K%tHpWt66`d{LC=oie`c89$PRv|c6zAH!p7}h{^Ez+L`OgHC151`A$v}FQ@R-}w6U1^JEiAbAB?6idr>*&zk}F|V&`*gS%TD}ANe4!^Q-{+RkN968nip zU8{y*Q17&aDuvVgIBzpmS=K6T$IE7?4^QkI(qMqr)Um94df0`akZQ~Jnc`oqO=}eL z#uT+?cgVa0<ZPcC+SVQ&n`$eS(=*iE1WPbZvD+vTU)}kxmk3} z27c>J?-~?04fQMED$LqC-RF6c^zq$Zn)aUgVw(47uQ*jT%I0>7@`Rm7Jqo4BM}LEy zy`CsPwj0F3KEXpN3|)-{Zuy)P2_QJu&Q+ zF2C7V{V7=vv@%FmQ~tluD>=X@dm5yQsbrEQ3`vs2Hp%jgQE+l{hkh*J&bshf#hgtW?44x)T1!lu&ZLI^^SrV6t-ta&Fyt zDm$W$N)+wO{`Sf$oLxtjfH!lie4d}-v+sbPl3XZuqbsRFKl4TBPfF}o`{LYvB@89` zY(K5UW1i{9^Y17d${vrq%y!P=Oxjh4t`Rz<^IH4yD~b$oYDC|n(S*LlhwaJIxf_kT z-FW|AB8!JU#Us7B=I*4ww`nvoI?^Y;Lx-%_)U`L0F>Q^;_&YI3aPWHOvu|{R7)+Q< z?cKuX6g|FSBXoH5g!jOl82mk`L$Dj!kiOCIeZbBK-ZOqr=xOiBOf9eZliQgiO`tb= zz5#{3jF=H)K&jbAOf5!6LnksDnljT#c0|ty)MGN4$DL$kM;K?!Ey-}4$~pHeBPKD! zQM{HBu4XcaFVG{|jvmEjoK3%Ek3?PeYYc<~nLwFza0wroHAGGRz9^MeGMWY{9-#R-C`f`8u zD7=w9DaR}rwloV(66t4jq7SNzw+xNgV-f~(L-+d z`%2z#cQKr*CrhkK@jUE7t;tL5qo~DqttXkSJ*C1)ABp#@E0s_C%B{BaQdL(8X1L3V zRQj==`pBk-?9H{)w^&e5hGqLn)Gl}VSXL=JyLm~4a9o86sX|ugn86kT*zsxQ<>-BCS(OvWXG*ff!Mk#Fl`@MK~M9g$hAD_ z|4@OXSqiAu7f9>Q`I51m9>;u#N$i-Vkx^gc>{V{v-8x{@IfM@HO!4H}#X$EN^xF3hI> zU6WeLP%Yl1vA4QMIM&zEvbRjjjsXqE6(J{a7W1WQb_2C%|Hd3WUgVJrUrCSU)MHjZ zBxk5Ny^C?NSg|4w(>d?hRGqV5S3QQF(qmmmc1h3R?>RH?NncfLV?CB~?$GQTJ4Bkq zVaDwLyjkqs$Y6KXXzB|M^k}nz{YdNMV7||D*aR|h9>R%$mQW7!bP+a`tjAe=68}sm8;a3Sv0^^;5qc|H?Wx za6F8ij}~?`OtrJ;nC$nk2 z50FdL1Ebdj%EYHiNxWTCmX-67uH);;p_fK94K#!`pbFpn5wSw62l~K`C6Ck#&>(66gN-4oL`QQvl^ zuhB{m@<9bGYn%`;wtfiAz;d9zxJTgSq2 zX;L`wh-dg^)H_>~!MKjy(80VnYisdidj!TRG^kOX^F7{cTa{#Rz1INK!%^*#7DqPF zPt1EN^(1*K55n;;H9KV|etc6Tp5N8r{{NnBaY#5Bi@ec# z99Tvjc>#Y<9jPnt-<`YocXa1mYZQILQ}j4oo!-b-_8kJ)%eTZl2E!@O=Ba}R_VRoFP{`G~LR=Zg0rJ&c5_d$azoRjin zddi7kZ>5G;%Z~h}oYS?YKZ*Cy9=&#hzTp|R|M3sEZD$Q0T){u&d(RK2Tbx@J((L)ekWNE> znq0qTnkI z*|=-^oiCZDmkX<=p9pp{O&{$M@}x|Da9G8CY1`e>Os!rYF~t|ZmiG16YSXcOqtiBO zZkqnN**twl-OncNl+C8dDF;J3S7>h1RoyF%uO`a^za&YWoGPn!8RX#PBq_TtNlY#1 zQ{0~*#ix-~w32;jedrPCZCS*a2lX_Vj9Q)ST91gW&1U*9@OGD`221%FbcWhnm}yD}9b{mAJl_Gs7l2oZ)`YzJpo866{L|V1~t0hbA|5_+g9Y^EL|hV>+mk zxEEYWFXKZU8hOW{RCUfkgLRnQl=Ho@^g$LxVeCO>Tc+!f5v9ZGU1T*Dis2lXXYl4a zoaRi)dXe1jV)QN!kH)r}(U`Y03YG#L{ZY(cF4y5>4%uO^$>G0az^!2RM9*NB?_UG9 zIQaVrBMy!-;@B@E#+4vIk@wi~ zyi=!?BgxzkHgJeHSp>~XDlnY;!lbbZ$S^H@`h?@+33}c4Yf*C|y(%O4^KdV7;T3ti zd`_SBiN~{xtW$~vXirbx=J%UuQDsNrFe9RI2DF zOWp*@^kFL2+6Bt83kqCaKxSlJXWVE}2z9zSqa?2>oYvy8J`%luYY;&%hO$*8bgv?z zxspWy&?bGlDaB_2`_k|ktroklJ2M0Dk?Uw* z&Q#l&k#Ot`zWU~11^1e-Ds!K@CGt}T`QafW=zvmJDJwuWAZBJ}EA z&|&vu`c;xs5HgfZ+m`Gv;B)aXpPAn$q@d1J`Yq@InbSBMk={HH`|;=E*)*h~lRCbZ zliFFUP{+QcZ*MNO(x(o*TxFEzO_<-DwNLB=66D>+6lt(vpA2^Q$Bgg3C>Tr~f?km8 zZTv9yT>zHTYcZyx4l{pKS6su)@3KUIPtYu`O^>Mhf@=*=#Q$3rY1Vf&!&&iLa%+r7<6MkveQ=s z^gi^VE->K3Z6hMMCcNb{c`DhA8x1_8`(&eOC$h=5a8^;=Nj=S?P_NgsuaiE9u>+Z5 zR#8`fOF!&ldN8ah^3{Kz6n@P8Kpgu+W^k>p?}veZ{V<6?k2kgPoDF`sRVoInE5%@2 z{TN)X6T>`e3~o%1L3jFhZkvpl!}rYN3waE|WD#6W!RDIx(7n19vXUIK(e%#0wqW2Y zE1v9UA2&U)F4XpiQrC9xr%-#5ljg`smA~gxWLaveq*qRn1;?4!ZImphI;qf(np4dm zHOX^pz{Iy;%&36=f&*&KN{jHUKJoL9TDWX z(J$D5d;L?~v!}8r;h-KfGwI2n!M$;7a$#p@!btz%2DeO1{%oeNnLNgx}ph%q@9OVAG<82?Q>Q-0&_VN?;aepzm2FZ+#O8Iot z32o0R;MYol_He@Aw$AVm>=$=hh&MtO6=Ld*; zYgcKI87LuJ8cN-4FR9ltK%5Rc;mZVv#CtiT)kkMEpjWS&pEGJ+3`ayFnfq1^D$da0 zPbm8_m^EF+nS0B@ahUv@XEVM=gScKKj-_^ykco%C&3N4|6DP^8%w-mH%Xc%B3vy6U zEC-voRuu1NN5pNO<@4E(Sk*_4Uh|QG>x1Mbxt)Kls{kt%%Pd7l(VGmgDJ3*kZ^JTy%EiO7VnD`?S_u{o!oT-K5JeiH$`?y-D z?abFBwGp$d;ap3X>QSvJ*_9W`tU64e%5r8+$J3WTmwD2wHq;DaZjIjDgO_sf@}3<| zVPrzbr^>oVDdI+6#!hVVOva5KCOx(OrV)*)0W#9EvfBGvMsE~Pty>(=$oN^6> z>JjIchq;cn=If-OX0MEakD0yPeq2k-q+k)xKtoR$kxT!%d$kkN?J%1Z>e76jZm_$cYK2rOvM@#N`_o%ln7xieQ^ia# z!?buMUI(dQxXJ%jxHQ8BoyWfyki6ny8}Riz_Ynt!SD zXVcsGl=H3&T({I#*xa+Z?vj18$BN?IZ=7%Hqz)ZJZVRs?U#{zKxYn2L>!d#VIa#a+ z={>#4b(B9-s}4q4M|M(6oj;D=RwAOiKj*W4P{yd}Kc`1FTE|XevK0nJBhQVm%VHhQ z^F3^yV}v{R8{Ii`2wu&3Yd{J{^P0Zh&dRwjJ)WM~Sg&R$Wd9yy&2cm|LbQQQQ2RH*Hw^l#6D%_dVG$sKl;pj?C9h!RYw%ar)e5Iz05w- zml^o+o4O|R&a>EeT@Ug7hWcpFqb_>i#6!6CKiL+ zQ=g@ut2=pivt0`00{tveK6;EfpMltKZG6~C2vvS^%!oO`Ydfz0dj`8McZH>pRC z;rZY6WAf)LMLqXM8EQPQUFFo}T&eBEY;!idPq=PWiMQcl(Yo>`@voG=K;8Wj`()?v zSy#(`cZJzUmHbB@Um;I$QXFceXJAt`8=kImm$FR?V*$m_w(!Fh#)Wju(`u#b2% zwY6P5Z!&K%Z)g}E{bp}(@l324L}vd!Z@E;QJhjeYP+g40ITL+nVAiaOr)08Mx9H5C zuz2(Q)Py|5Z_HSnR*E$-SJH}vBWF-79>&stx7dc(PdKYNn=kLm(m%ML8fYgoO8VMx zt`+;cZvB-7^sx@##7Uzw)bF-hqy&D+b&w{WEP{rI*)K#5`M0m08bSshQ{TMa+FN$M$P@p{WK{6)ozN}=&6$CyF-0j0Coor;%wFbK zu~<~b4DIIk*fpS@d?(-V%#$z_s>Zcw6l-f zU)(no$X+e|bVXuOD1tflIrQ@;(eXx17GVB$e1(lhb;Me#V8o9v*Q|+S7(%5#Hi2`ErSSNRRKa2vwUg;Ue|p;(_8m zJXc=Fy0Uz_uoPe*;F_mg}H;`6XsP%KV3 zGO)_QUZ1w^vW?t^V)0?HD*NG+Yob=eags}HiyHpdoFw4%bT&n&xR3v9gfs1 zkiwkL9k0*Mvv>3l{vg+KjhEE+;GXN?Ww!OoM9h5XH&=WYRcVJ`7&n}eW0;%=vjjq zVEQ@($-O{1CwTBW@5BA=?_C*)3gs-Ss-N_vUvft|Em}nI-!;X|t_d4@>*~m~?+VU2 zH2BAj*P)H`fm77nJ9$Vgvf;;5+sL0lK5tX{$`jZ>w#8lS*O-k7WZ&F{Sd4qk><#bV zHOX#LznX$PNM2WsI9sg7=PGsl`E5L9qbgS}chw@jv>uDUvk$$r9lw_tWrY)cQum{9 zhv&;?n=RA}=%1RKBwUh=g52cVe_%1S-P~l%ZbRLYzOAO^ zj1s+&+DH-h8aFj!%>e45-yEoOB2iX)vpe#AG(v79qgw>ehw%<(fD`4z1r_cxk8%2K zGR8$&;6iO-gTo;AnI);_L$APM10pLh>rg_Ww(99)s-i+wRTL)AHo{xUK5ObDl?$iJ zS`YeVF&b2-V5r8&OX?5V@f>B;zhioUJN3ia-@3G$&neT6M~-XF=l zJoiJt`SsJM8l`1>AN=a9!~MqeC3WZAKAwBng?r@ZH1fg@%){lNP^eRSCCYK`Q><(0r8vUg zVQ2pQ%xuK=OOgxZ=(XePTv$u*0=45hJIFLoNS36H^o0!4VM{&cbt;lWM_=CBrz!HB zvx1r)QMk4u8E?O2!Dlo3J2vc*xB~jo>gzBk$%xRxWG}hVk69-{rZn?Lb?)iQj58vp zFZtXF4h&7&E&ly{aI#Sp>YicdWH?z&l@#iPA_n<;*@v?w`VH^${h~HqJDGjNFh~OP zyH}6QL%B9aJYP#6-)QT9oiN*Vs;Sw zXL%;jkOj7PJAEyUqVX}3Sz5l2pOgyqo}68xDyqaH?yrOS`hQtKZ^S1D)`#sCiSxmZ zkJQwb8{itlp5L;}X>vC6v$hgzzDMC+9<_Q6b@R96=xGvVO}HPNsaYI3#F;^3awmD6 z6ep{G+;k-ZUy;>aiZh1k7Cch$dgx=6o}h--jXcfjWE@c6@9?VteM_>Ji~h0#8)p~p zMhrh?A@@k3E=HeEZf_qPeM#RLIen#^$d~L(&4;s|TI2?%X6dkoGYjLCEbO3PZ<9S) zuJ=}9Ri|iFh&Lc`D*dYb`VI#AG{4a2+n>E0kGLltl7*N_4rG!$ndHpQl@HN)zJdO` zUs>2s|LM}mB*GBVeZze%63a%F;Cj8r1FoDRQC2K4N2 zfvPTjWcA2@bWvgSa-Mb0GaqHP;3+@8xln?5X;s+%G79axFei@!I{#}zSt0$$K_~j;dRw>5n1l-=!Z2W%9xqtB(g8N%nt*ub+VvuF=m`k?v{&#l{grw zLyKw#Wa_g}jJ`!(6lZ$%__|%=(gU;ikQKK+@%BQn1mDh94qY2`7%m;(}MxobW`m8M$TR3Iu?q0A|FqStJDxhRCVa2`fK=8ks`R9muFn*OUqDtWAlW$BsXd8-$n+lMbC zN&x-5$xY}18*0GB;QusVYMJAc&NU;W@pwLci$U~9@xCz5O_0(b z*#jOLg@)~nID5l_W+N2p!LGcIW_qKcL5HKO$zu(rAM2b0lMfkWYc6}wheadk4Y{|4 zt!P#Mf6rn6KYqp=mUX6ywKkaUeA$s!pkCE-SIdzGzy~ zrg!?TLW9%q1U@jO81A;b(`cosO5*_2$F&1Z-y}Bp%%jff(ZTgiWu^{KUtd2dWYCRq zCR4jEruwnGAIL@gGBQafJU=L(dl+OvcCsA)nkWyirpTs+336!TJ}Gcck~K})@x3lt zf*S0X)$}z#p1Vf^bIH;fW0aztOYdHmC`niM%CLyNQg%U-RKB}MUY+3gTaqMWrzA_* zd1?*RJYH5zl%Kl|VjXOda}AQjXU0CM#_Zy9FN1WCpaSo#AAMst$a@OXC}azTn3)&pD*&m@fk|wt@XuR&uA!@ zM&mm*p_WIZQAJCCxsU*E?%ya(8Bd-f*YvxiqHvL3SS>Xq zU9A`_YZQa=L&;Vc5zUSS<{iU1_tw+%C|qYak8WNq2LJNc%G2gi(`E0)U>&=obhy}& z8P+_qSeKDUynr+9$DHr1pf5a=p6E~P|7&HyMuib+oUg2%$LG)nBVKXdbDp#3JJhZm zTmu65@gAj8Q2qhu47p@Daz^xb2^rX25A~l7@R(*mXX-eMK<)(BhRwS;i}+x~l^I4X z9Zuh4X?6SL2#m~Yiu$e6UkbqV`JGWofN?8D-^dw-_|>swn9ev&NbQq*LwSm4I}kn1Qb z!hEe5*NI-ppINxZy~>?K%rQ5!;O!aS~zT3bC@_0yXvDI=B^*s+M`OaN-^mUg}HGRcexvtb9mvQS$Ul}sE zo}_jNU?-59l-$VvfXe|gj{OMJ)7-@rLC$>{cjl8C|uGW(Q6rVjfnf2dhcm`Y8ybgl%vD3GwX3cTE!FP~@SN~5Jt zxYwvait+QkBA7pAANAgH`7)xv6L$Y8peHj={1Wm-v&JDqiv5*)$MU5I&(rnn4jFcj zJrX53UtUuPqu7f(ZHN>5gz2v;>;$)Cxe_tL8I`*#@aCsOE^i9QYHBj?A8D~+l?J`n zhU3Q>`V76aX!ApZMu);MdVV+}cZK6KXVbF=hhq%SXzF4byxGDIK_B+hBLC)T5>B&%LFCphDj#kV}UW-HPz&OlIV?XpbYBK+w8-Fmv`6LeY>6eiKi}JvY?-cl)L+HkfHCwhI+Lf6O#jvPICMS4IZa_bPNXu^7@)^C ze$C_OWXvVRG4sOCrj2n}wOY@4I&*J@%}AT4$dlwDUs?Sm}2I&aKa zIx`ay;p_@oO&?YWGiBwO^*_g+ryTZgr1I;iM_ryyrVVwhfj#NZ>R=}4+YCEBSoN2Z zVc&$zxYC&jtz^b^&rBpNq3$#}6Q`-)JgvqVNzqJn>}bY;YBscWE40qYl zqZj!})JSfGk*B}Fh8|~aI9$?>#m9JVuSM2DU-E!AqKKy;sL9!gEZxrg8gQ9x&dDXIG!7%n( zhxth7I5!En*jP*sUzvZ`Uwj`1NQXu$DKtbWFVnoFprx18ozsx{1b0b$7$k>=QG0k$ zU0UVWWAB-}bR|P*(F~Q`Z|@@JsrBUGK_4k{xvmtM;wnz_>dD)C^`!mbda|*&mq;J_ z9KCsVc6f?1(noeI@f4%dM;cD@5Qk1B4{AE2REs=mb%@$fP^FKT?SySos{nE?f{72Ru&-4X-VvD;&} z!VGpNpkgaEGl1O;3@UaUrR*+dz)mE->wMnpy}p0I`vVt84h+NdJokO?z4i*~rpvwb zhh?lEl5_mAfc)N(oayao?~g6}1F-3U7Sk4KQM+v*4i3@c>pOpJi2n~8px5GdevaW> zYitk>G}0n#VgSbPX71OyAjA#{#IF@vbm70{RscSAXC~MSu61GoS>w2dUeOydBMiZt z$TMVLue|(Uz8rHj#zdeJ@f3%$Tn9@c{+Cl~oKIYE4?QiehT-Y{FeKHX-t;wjiQmHU zOh;~TyKu}L%v{W|5zvhxmbZraom|KLSCG3xET_%{dV~?XxzwJ%sCy$YsSJHr$)#*t zD+0wMIb$ORl(vjI>KPUs=UN!Eot&0Zskm1o6(OM(I6Y%_$Z&coM$kj-9`*Y9#BT0e zP;nsVtHd9dldrg^CMZbGPd*0M-5zpjJT6+$^$fMC?QHP5M8DD>e7>i0&bP$|-ziqy)=~?)!-hBCxgNOQ zIzF(XD3rb(oDD|RBo}Ep{YzblQ@*jG=}mrYr8i6wzjnq7zYgREb8S6P(65TT$5A%w zP}g(q>|_p055BG!*YgP*Iy|@GVhR3S>0BteRtwMC;PIx6*|NJwr_YH;I=S8{bKN<+pS9ST}#*GHoqgx zuf|U?Pc7FrDPl-(bJ3x4$tRlDN$x(Obn>w!wUaLwI3+JL9WoDibkRJmW!I!9lUMmD z4x!W8;oaL^t5ZF>akH8}@6%(=p?y}FI}h{i7}GC7(muyZhACcJwTcscKa(U6G05OS ziK3z=@LS_(xk-)QO!_(9I$)9w)eQ2hVXQdaG}1fOAc21wCGU$t3^{RfZ%4Gm)iFpY zJs$hV9+b)K%^E^xuek?B^Ezb<88V-bgV7+AE1tA1M@-p z)6m-`Ujyhbu<=gTt4aGn6F2jI@HOK%Q37rv*ex_FlZ|4xgFHD{4(P2 zJR{0ZWp86M!o^~O^DKVcpda^S>cf6A6W|^B9vLPe#)zlHPP({LmqyMek##~*6g!O)Q?AL;um)OdGkyY@r-yp5#n&|O>lFe{-rdrnLS4A{*{3# zYWCRdw`L7u{upb(T^-qbIZ%hPp7X%<)Txvr@6a@KlQ?YrU1(gik ze|U}$38v0rYYKjy;(oTD>%M$0B0rIXLHu_)*MIAOnHRO)U6wLyC?Z5HgT8x7@E{lI z6lpJ8IqTck$&OrE`f@K}PUp-LSny4O(PeoKybMB{z#!CXr^U-KE%{{34ffnlJwgO- z4x=}9GjbWTS>sF&$GNBUYI;sA{SS2$OXx$`Jq6#mhtB2xHpep;6|3bUNo-j1gtL@E z%oRIAew?d^So2-PEv$vy4EKyXb*?#1#m2haXW_vDZW19`Tl= z4qj5>iK{55Dy0!?kfb+u7*UIu_)l^y&ojGoN}(wG(UY+xXPAcq|L2pohu5fbPoCeb zNz1Olu==Ndgl^cf56T*?-(SkC~=_y4H$X=&ZEM(niS3eb(A9JS2XQynVTzqDo zmh+R|E36N1lmC&FrWQ||Qd}E)O3!qqDDBizubUl)k^^#MvmJK((NnWgv8)}d!2U=- zj9sFItpl}7*Xf1wJb-zSoZS=kC6LoiyHL9HE>>X zgxKLz<|@6(MDjL;rtqjjbC0tRlZA5^UwRLQ7h_~^qnsXhSW0e8kX^xv(xR_X5{Us{ z7)L+j|2P=&9vHGz4WAz>Og}=8_cjkA=#Ike57RhBC&iR9RDX$aX%XDJ=O3p8w7AMGn z8%BvsikF4&K6Ly|5!HYbQvOlt@Az(H__K^2?XD5j z7O7YL5Vx%CT^2^*&Ol}>Byo@4#QEmcaID`Nf&Jv5edO6S>JW8J<1EPZOo5rb z@~l^!iE46Da~;pqZ=B=)SG#v&9j|bcFEzd7Xd9lVEj=XjmW$lz<0wZ;70aN(3IwoU zJluzT#%I)GljFujuEJm8;)^9Bk+y=lie}Syj{qF zUy+It71>L0A6&G-La)6PEM^~bphO-*^T^kTrmwrR4KC~z{Je5ey&HA4KU+v*xVJnj zQpv0m_R^!2QcBlRU4V{D%s)b1ooa^3#8S^K#bn3#cH=9s8&@AhkVXgHwEBo zPihnPY)7zjIF_zpo+!`w`Q0L*CJqsJfIUwP`=jOb0IJChiB>%4|4^%Nl;>y`Gr`$| zRCmh7!!n!;A0gkpFExY3Zt|?Dmu&yrRs6{NoYt5=h|C)3`n8z4i4r&;Tr7G2eQlOM z9C`-vZ)dMLB8am_@(#*tajYN=qu;Ri+Z>KJsq7nn@GK=C!MHsY?G{}?M_!Xhw=9@= zfb;Pae2!Y@qE)S2Xrrjh3eDuocA9j~hkkh~G@qBzbJ)uyw`V6xJ^EJWKTeQ@-t_X_6eD4q z)!0#2jU;02p2K;zHuk{6vhJ8VmmKp6p`5Ale4newxaFbftO-TQ?09tENneqRMl|_q zz-u*i^2g~X&vT-SJ^AHBIlt$7dCxQc{2+cFsnFcwH9EpGBa-iDM^}Yr>2QUnkB32K zHcpgR)KUD?!64yXVkN%1QM^m2QS*=o`$IJ@g;Dz^?C0nM^PSv#Wf6O}DxoNHLDgP7sUp=h|*~(m(W51=r zLO+}#{=2`q1)Kk+-&q@#^q_CxmWRx5of{6_&=e@!+Tb|7sr=(yBt5^7uT&-s{ucHa z#4*E`G?bPj^X18QEjrc<$3>oT2+BbY^HtAwQ=qMvKMF5Vqq{MMIz9R`PHrj(cIQjV zZhw3U4ad;ZDcJtUirr!_6C;S(6aS8@_J8X3RR^tT?e8cqwF{+Yj34@Yhr?|J`wL=3 zE;;sM`A30uKK^(`o}iGI*SxhAE0;LQfVd*jt`5MM4LoCJr{MC@9D4jXh{|LKwVN;N ztT12!d3hD7tA(pf2r3Y_CjO{)in!ab3wXjhe8)6LX`#xO$~u2s{J0JGXIqf|h1k_0 zwUiGmkQ$f#5VR!>;V;Q=QrVFDjeNI@1v2@K9~8zgl-ZJkW4u0>u2G9XEx4ZghuDE( z7<-p|x0_aM$aR$IN6B~VOy1l-VHh@^xv?j6n8)5!irW@T{WL%HNejcpS{97EXT`fS zUefVLp=`1Q;4XP~?SCdSi;F&JHI(wFk^(_v>7Czzz6Gje%&KO?^Z*CR^7te6aqLeX zGsm`X3T!*Am~opt%9{CdGLU>LS7M2$lJRE%c}C^QKecC0PCj#@^AFRCZ8SGh)*07>kfTJAz^;>GM3_vq2wOpx;g9@*cq%#s>lLAfeChg-SJ0A0Sk{qB$F6Uo~R zO+gt2J@<1QW{xPsz}5rtrq0ne4e+C=U|-a5{_m(I4sixrF?|+x2DC zmI86!7(k9QpTme0G?-~cp4LsyZz+-i`~C2IAu}u z6F#4xaxi$EqjXGRcECk?WVdB6e2M(NSn6boU8UVn&a}uo8`LBmKIEO+X~p63Dk)Ws zzc(%bk$ag_+>AaI0n}b@Qp+7aZ*!*mVkh^3vU$n4nq@^jos)Q_{+3y3zQ{Wk1_#cE z{4SGs?Cm6PIg|LZ&liCfu50pnyFAN5P#u-5YfvQp>3ev;FboeDreHO%=e6Dra`1DJ zOlr?ertmP>meaS?9FoipA(pkCP2yFr+8L`keRcqOY>aq3???%0Tpju{KwZqR$X0P%2Noh~dfN}JFpW_O{WN4c))d9-G=t$eYdK|eWr2%265)`%fW&}SF9L! z!A(-Ae<{WK^|W0CR`I#gai7%sHD?}}g8pcJ*gY%E z^2F^jhERXw+e}^!{v|In1JI%;pR3LmJYH(WsM|*QKptOuUp@DK&dR4}pfziOT@HsN zk>`4ZiaL@^`l*qBWU0q9ko+d^no6t*(&5fY1G-PiK-?Yjk~SO?dkej_cLt*YvD)9~ zGvPl+q4~ZnN^W#xW+iiMm)&9>aYOQ--r(om}JH9j^ z3-7NNHNtJzC-D!R*~LFtT&p>P-wcZj+O>rnUI#Y1Wmf~_wLKUs6EB>Rw92V zjy$hpA@rs&Ag&MdtjUj?(mF;a2e{$FsSqd>tfh8mVA75v4DTE#gLW&?)tA?80c$>D zB_H^At-ELt|Hi8S`M%XYMqU_kf)Dc*nljYz%)G+9V2chrUm5`Nh7wr!eXK+;gkU#R zptgU^83R5{Brj=SF{YM}mHWqBQE^fT&i*oBR3QD!{=;F&IjQ_ciJMLIsD6=tXTcfx zR8))~H{ztjO!}Su2!=<0^2LfXuyz=0rvpa$o~|UnS%>kw{x>RT;rBnpa{4Don{i5H z#0F!^5+l~HW&KQkWd-U+_B?juEIF7Nea!9HM87BED<7Q=5`4fFxw;TsSWO=Q@(Tv&0bLdnL*V<_-9J|D7~EhQ8j59V6H5Kg03H?N zOp`cyK17LA+d`1@jd{&&Gti1WJCzIdF4^SR^y2&JORc3Bb+F{;J|G|H`Fv`n?gnG; zEFsMeXJP6wixB(NmuqX>@irsn{H-6LA<0J`M>R0 z*Pdn#+iC{+n+Gz`_6u{m1EZwO1to^n55Y3>=Bgjbz>Ryw$bL${$WKaCf2IH5^WTC# zi~(DV5iuuPRv%NM;I9675tTmt*V1vDA4A;|L|!$ZW(1$-a`bv2S)(P?o zml&mJwHtcw4@SEZMqE6ffioV=+$k3$8hX%qwx+k-A@Z!b-xjVcMt?Ou^6rwKs13$A z5Bh#`U)scdV@acU2|cGo@N*sZai5HxlnMLZ)SSJGmrFl5zxzi|Zw?by{>Z?H2gS(h z5hEG%nD6{y3El-#`@A3vYupu@SB;{$-rew}OE9Lok}uUR3%X0iX!s&d&JUpPVMWg8 z%Cm1=kb!^s^_$ey-S15=mF7Cm^Nc7lkoye#*7Eb?CA*_Lx(Bi!-^~8?B@9Iy|;%Q;4rjAw2&*YB3uJTG3mB7nVe)-3~CouRKTG0Lm-b{WN9Eo}`w@}j9N zb7Vddd##;37fwd1*uMm0Ux)!N!^w>bD@NO>SZVu>9JvE}lpRd`{1f?=-2eZZh5f(q z8AlyG*{R|9xQ@9mw)&*a+-)AY#kc*gykwudXR>^9mX-9WR;E(N`uUcmnbWFv+!kFk zSrO}uLYd!D5u7mFP{CH|yv-}z{D@wUi4Do; zCvL6UYmhKzKzq3wL}NC|raCc_#5r_HdNnF8$IG3;CZT7GgnA}Qh0HkS?Zir?W4sjj z()aQ?IjSq;Ww0_v()fJ3{)m&hwpjV1F^X$l@DqFd@M>3A)oa!^9es@#mTaP zhdJjl$@e<(Qr*cYFV4ryA&{$H+YK8lso?LchK)1nZ+Xm%5YCf%&J7(;55>lue~foS z<$EeDq&MT+5c(`CRZw%TJ$Z*3SGK4ybEFE__K~yL)*TL8__eqE*=24>oUFp~`YPP? zP+|U8H?(Z+&N-zTBRZ>bvomq&zACJ`s>DC%)tDtNXI^e9PgW9>K{p7HnW*iJ3!QqG#a zjp)ALhy&aoUxgTPi|hC75ze3Yo8TG348U0Ojn~r0q7}K1QPgxk<2wGyIrMN7{I2r* zJDO0pz6t+KU`}9bdcT(7dFf=tqA=!3ui}|%Pc5jCbCT7>-nSdE)gGciH&LWNuEXSqA%+k`)oA5 zm4%5n>D~CAKG>W+*W1SW>^aZIEA-aUF`uh+HqU`f9B)AX4TntJ9Y?-m{VW`zSHX;> z%&K}!oUJQsv3bm$f6Je(!mJj)P6h5$Ybww~IM_qlbaoa``jjl#!kbAc13el2U1ZNidj6BYHDH^QD6T7|SxdDfZBokhU{}do<0R82yGs2guJXL2 zQYsB8kp1KH<<3HKs-hJr+Qi)3ghKhzRe|N4eLlTN&XuPEmmL)-+kkw-@B(SS^pCVD zpysfQ0&)2YEUZ=_p0zlabXVZgUV7hwhxMFkI{XO01tb4GTg#fp zAFU$%(AnD$Z#@H0+szM4sM&hxOTN`R;@1ZH$hrHocVUhLd-heev>13^i;O$$NBS}= zSIz#l0(}=gYw>0=v89**jH>KUZFV5mc=+QbzxVh_Kg{-|r(skVlrZ+rw=_KLuV7wm}_(t9Y7ehnQWFg}qUjQt~!z9bxpe{l{& zt!r!I4R@%^SN9Ib5n>e`eCbUi8i1rrZdhDB)5u@=+#WMCvzm734;+zG$7E_0J zJQa0`kjXJI7^wk%G8rIiJt<%ydoTd?o71=Z3mh!~oT+4rgEWAC@jm$Ram7Wh?2 z#fHVnoTbq7@dY(#oJSnVO2GsE?xVGt+4PP63ZFT%F0|sYCwT_!Nq-K^Wlc$qXqi0J zNwrZg%o+Py8^+t)P@OZK?~(M2yF(AT4%Ca14={rK3FA|0|AvyI=wd@}eqZ5z`Z(s$ zt8sNM(l>BEzL;JT(d05{tyr8+4>`{4FW2YSb}_Gt|G)23&hkGHAKc<5am~~+d9}N| zCFWJKYco;Rc9#kM%z4=8EHlqJi}hz4S$kY9mzr^&wb5QoL!F5GxXZ+O&1La*2f26G zNdiZbL!9Cw-I6^d#6Ydqs-Jam*w4Dr1Di)N#l%T;wEP)O&;T{ zLbYrf>>{_Gs3knJxf~-0cog$PGTn+~1bK#P@)UzN+F|6)Vq$dE6`m}VM>~ltE~X|i zzF52l*r5sYJx+L#`$#Ti_?SO(rH&o$mgSuP5xI}Yi{;NRu2pg*-qDlsOrs+HtqSCB zDU`&?3hdfU%;>BFowM!mY=8pond6>FTyEOBVlj_UATiM&cTV|X(IkIl#B<$zBR;^j z;a5+KzzO8^9tgl=YL9DiP5AcnhkC6a_SFkO&{JPrObI~mj?BNAOATpc0R4ahP$@%; zUeN)l`N<#ks**4A(H}{-$RYNir-?u3H&*7~O!mjDk>nI}239`OA0v8jojQog@4``%xbW;e&P6{GSKJVe ziR41IzsYP5PyU{#%(fsddgK>zh7PUK(Qtj6*(W=T9v*}k<=V# zS}^Lk1*cA0@W8^1_GD(ey(j0lKfPHhlb^Vg++p%hHhf6IxrWqqt{~3UGzA-PTc8gi z$MG@O+-3_V5Wi@CGX-BcQ=3DLe_#N889S$<{aNa)dvcui?W_q(a-6?r=_(iiWuc6OP=ila#BY(^x2N!g5st}%Jd7fo1|7@JkjFo z>W4OON|1xE=$W|gu#8@2lCgQL<-1ewbw5EI#>Pn=`39B8M$4LR2D!GI`jqwtc}RWC z;cxNMqKQG$dld1$& z@|eEr&E1URH`|twVRUzgrhs2-qC)9nH69z3#8lm}Y>XPqB9+)OQH63<>G^b7 zg&VtA|F57nM$0@1)`w5Y=h#-BoW@bq-5#eW%N`Hr8IZRSsKaXJ25cwCWS4^aMe;kQ z@xR|_^jLRYhmgj4^uHgBP8XOVKu)8527Bi%^i!OzM+m=f3+uf#{NBI!lGmsW1swF~ zJV6I_0B2mbU_@*qw}7GI;rf>e^>>r!INpf;HI2ALEKlLg8nPm1 zZLA%Cw>LsJn>sdfR+5Q*C@W;)W-ZR&KwZnXOq`2hwx(}3UX$ZEH=g{K<jL$eeGIwcoM zw?V~nvb+Mly%accR*S=mK%@=T!ciHBTD(>}SnG|N9)Z%Ec_z$?_+JgSk9>^&ZajnP zrXqA#Dt>XVe_bsVr-<`^I%q-jZ}hC>K6sk-%gU=(^evqSFZvb8y`++}d{_Tf9eFK1dT1@>$ z50cyAc-gQVaBE;M%QJEU10~r`+k2Hjmdxs1pchy&FyKj5D7X8_zpC!X1@LtMQ8a=Hp4^4^9llgGh28esdpX zkKL6y)7eepVPpTfD2h3d{-*!s{=7Mz#W`yhUe~2R5&O-TEi>_ZDzgB_DKy@->@;bG z)VLFe&7Yvq98c#Ao#)G%>n4dU881g_8>LezlSD)%NCmSBE58yKdPDtUDK*w`kN>8*R1`|4rN8#1VMXFvS-J^dL^nJ|g_m;?P}ryOJ6 z{n0Fxuat!!_T1ANDKw*rqdS$g)6C{fzw#=Drud6O(|BUMn7+hIeVa*!li%-2eC2oB zqoS_pj%nNIyHKh*`z$qj>D8F>om$LnJ^KD3zu=P&F(r9@CXv6V)nn*c@<5IdKaDe? zXq5@;29Tq^llb~ka#DDG7Nk%=o}UTZ9OfZxra!KooyNB(uM08x4(ZgtGjlqTcz(<6 zhh<28a%G71e53Dj`Fr#yn|Vya$lY1Zv($rGPbHSC@E5U@o|oORF^4|Ft$9AR=UHS= z?*30b)_&9D=`x-ht~@Wu2Psq~;FgaG!#bJJ=mYr;R%T%LW-nimiQTWWP-Qc-p2)js zM$Scb-mgKY6q*;rP~&*d(mTb7$J%%q*uX>&R+IeMMt=Dqg!Kzb#2jQvl`aGqHk zZ|IA-(w+X4dR+D5tfN#Y5*(>vk09Q1i2Q#I^PGuUqm5tCdS*W;yXB=@6H8IM8Q~BJOd0qIqfr-x#{R!5# za}(-z=zoL$wX?Kn$v(dq=Z;BrBhawzcJy0BA6;uWXpbG$ha(I@FU_}Cu}HQXDYQR~Qg z`S_I)&^%|~Q;EG%TsUl#EHDxaNXuluVz59Rk%~N|U`>B!7caD-2G7*1{cu*(@Nk1c{Z0DX_1%B{EZ}f9mh~R_nchVFP!Orq*r7|))!@|;rN^U5T30I)>20? z(1JDW>25#dz4GDgI^2SdPpL~||5MgG7Zsv-ZalPM=YAW~chSGc+gXw!CJxe18>2o=_3*QX_u_^NVxT*cuax*8@W_ zn`hU~mZ8Y!xslW`6qQ0v=#$0Tcr!ihICuMZrU|PO`H@EbcM7r4;w-F7roV6mH9Uq) zEO?;MSPyak>uaY;;an%0GsYdW6q=AigR}`sko|@1!Dhru7pHhRev7lyInD8Xni^y4 zy5sE~cWkcVj$FPU9p_kA)`p^Ky-?;ogra&w^5LJ+^MmKtn`q*{tnK4IG2=Oby+W=L zA1{+%`H@*xpE-ALN`Ci7`qjRr&u~YDW^sS!UTsupN*<>_>{^B9{b0_ynC-l3xlvqV z$gsD{L*J4f6xaZO6?~% zfpev1bD0BBM~wuYU+X#FQne(9@iM)NI7c>ZqL%F#dr6)b?}o&aXHP$0-YfTA%uISo z{n+0;<4e#FvG;vEUd6d!KW2mLvT!ahi})1JhCI%t`JOuRxzX`nEx1L05eJhLEip*_ z21n$@TcgZ>mmoim)4Rv0!n!YN_;SutEmw_=JX4!K<2gS)6wj9H5xXW7ia0&$Gzvxi zGvwr_QX9}H9&2mH5XLM=a0nfOVUr@jyg7;q23o1n!(+9 zZbd0H0rZbNPCv{4+lOuM+E_mJ`6H%w2It`V(i_)2=`o&i2RcxyhM7;7;W9d7K{=YW^P=>XAzwariIM#}wl`isv zSa|ILT3oA3Zv3efjJ-`hS}8|4M}FCmTtB#!BVN2O1=G7&vDeZ}%6Fq*z-oWgSkB-3 zI2pq_Qu}?=Ri?iFDP0>AyY5B47|%od3dBV1n@IYFKk{L{KT6c0&ex8(?F1Xbt~$%R z%6$Li#xHKlv*S<-7W8Fb^R|)nI>@|WfBNoqW!>L{KFGv}yvWD#X8!5#e#~siB^F-N z!WrVGxR!hv9W-GXC==y!yaR8u%B8H~EYk=7zy32`v)$=f2eUh2ai)WS7)7bUo-QC)Av)Bs1stA#-WsQ_yFq73(S~ zrDXr#G9=v}p{MyA_DVtW8DfF0c%Av&x_E05dvzQ3RJ9=EfE5jgH4sO>{$5w+L{Fsu z^cv=sucZcK3Ui7E(cj`+0M^=v;n$uNbXKvxim?}6twO1$_eWTG7`Ah+5OT!|@0ZTf z;Y@+(ID_%{!+FPM`U&c+n0?npl9v3DMbG`PttD#%)=Fss8$vkt2tFF?>Kc zdQY_A>Nxs@c2&u^!cx zXIBer8=kM1oMdS5A6cGFUhoO>VZ+H6K0+Sxy1G)kOTL&^24Mf)FvR#;Q1U$UreC_s z?p5?RY|XsvN8$K5g*A=06*aaxib>Btwi)jWd+6>JSX&&=!O5FW5_h{$`WyU^et8=% zlw-YEgV%YtvwW%bhrS5DSotap>AzC2G?aN$L!BichBeP?=2MRf!}=A;xUI6{KIeF) ztp)P;H9s67rsG(XdDFs-t8I-%N593^6WA{|p|9%)GprHhlV&!Pbf-c&#`k%sCOtOz zcTE{+MM_Oa$?>NZ|l;nZ6#&As!*zmXr7z6ryo(dFT(xD{P#CFSj@k%4i~|FBFQ)ZRV;eh;5CvpfunAk4of0-})taspOR}p_j=Pd9N`G7iN{4Mxgb=cKVjye{|0<%9>Y$JbGlY*+m-Gd+U`Po-2 zeM`~XfwlkF#(Yl9IcUw{*z3apOfeW}Wvw;#+^3$mj73}^Wopun<{%$WPd8OSCJnnl=9s!TK4^`uaK z*Y`(-F5%dtOu?wSoCS<*BG#S-(wFnjLOv&3JX7&*a}H))s4x2aMe@%mE&ARKhpLMO zJFPibUp-cqhLG>pU5^+Yvuw&zZ%y9fla?mw74M3^L!2HZg(~9K z7xkDCYD66^{SY+@jh$<>+$OK^>kN1pNB^~>#h5)QR?dYIpBSSD(hUf+ke}5< zp?Q-YBhQFce#IrYo=9v9rEugER2$6JzX(CsmDsC3HxtkP(#oB?qM%MlECIp_39mvqIq5%Ydi*GLaIa&`hOYSipHVETE^t zg-i6U3m^xh8GDDj(Ng)F5=kd@*!tZ>4heHC8rkch0H7iPD$m3f;U%#Dp^v`l6->^FQaW&$k6tTRO3FODE zW5y?OFxBv4`ew(<%rz={XX~)vYQSIYCtfO;|LYPb#fM!v_h5!;Z~BM+PDimn^Mcz% zi_cE-@5qrUMXc|ynVIOVQfQjQ#K_dEZV0-fL*QWMhCWZnSl-8r4dO&QN)7)f%y;g{ zzn8e%@Poyebbxu~!&KNDt4HeqBNC3%_cNs!iOOh6;mqf34?gF^jF_-D17FzJ{6${p zg7M7Dj^Z4KzU&{*W@6hD@@?tGv3<5H=DL%QbB=zXnaox1RE#Sxd`I2fOB)XZ?JZ+LcXEXXeIVM2tl7nBQ|qAcA8Cp&rZ?eI@S%*`}MHvV?s;)nbc2GADqR!>Agx^Nz>t@miX5N?kA4L=zT9%1|Lvj z%;6CHv%v@tuHOT#$ZsvfbyPt#Z-u$c8#j3l~~m)bJ~mLCSxZJ&wfb&Bb;A0w|DsbD29 zTUTU20B1OE?G>6>-rq~zlz4PC1QU22jHj3@b4H=5Habp*9VQQv^RK@T7;&x==RIS{ zBW`69!*lYuRtMuwS0k=R(obz^F)^z+F|Jplc%csSi@ilOm}mTlx&KikcI zxB_Qkt(l=iesLf2aLb-n!o7hGn?D+0c*W=3iM^#)yo@}eM6>dI{;Lx+D?xpk#d614TT-RfUN7GMDiNs_bnm#uo zj67m@?w=D3)MYnu!(Zog^x!n0jY~F;9_Mq_I!-EushD}8!}JKg|F@aA^}HB^ro~8a zs}h~u^mtZ=yhZk(o&ognd|{Fh`ZEql=gd#RY@Q_<@FB04?V3Z7R-4?pgbix#!H2Nv@~1n@=u^NXks9m0WFQzIpcE3dtAUZkV5aE|u)q zq>1@P?{FFqGL*g$>+?Z2WE4Fipd4Gf=(;R`+ZCeYS@`*dHge0DqV|{o9|-9oqnY! z9vWrUwHOIl&U@J;R>p@K1)O2mq;JkY z=-->M!yu2Inxu7SgG?iT-;K{iwZ$gc{fzQ4){o7OY2fBRy`s)uB6| zq4lggMmw?gn8cr(9Ezi?6B4-xRjy23stY}J^62Tv+GjHN|2y?~25bt!!w`BMXvs@o z#%$}k{GKFosw4DxvY9x`zd9V?oV!hRYDn)8=lIJ6`|n0f_T}t?^XKwqO{g&0gmauN zk18^u%^oA}uQp=EN6t8Am@xLV36-Oa7+J=IWyI2I8;mG?ZA7zF?&)8R@V>&?bS>ih zZU4)VFd=|AyX`rD$0K6y+!yZdpyy*t`Yc-vnDUKTAe`ekZa2X^hg{002?*&$Uy2D? zu;kHa`yb*e#GHJ-@N5}O{^5D@3>BQAaBbcr9%LFyZ)(n#pCx9X`-cUXa<(Q3D-h(?Yduo9`?u-ZzuCPu0@qVl#Pm-AyiccalYJ zjxyzKQ;DA1OzJ#pCVkVJ%2;~J4cw)a#0qYbe853ErMpQ4xr)_Cc}ViyMpEYledy@f zKCuzAmFUwr`jLxFt*I8-&{95g_FFJhDHZ71U;P1pzpsijh60(wyuiXog>vUyp$u7C zD9(oq1QcLSPJvI< zUbU-Zhq2}W44F=^_TK^6`jh?$d;IAuq{VK>KwN$22a18QbPB!Q$iY(g^~dr%zSu;~ z+_##6aJflOcrWG$4C5@+jkwWaE$m~M8+}ZR9uET0u_b$+x4t+yo3H0X{ClYuuE_zY z8p14&7C~sJ;J=$Q=i#S6&l4>*O5lEXD2G8sC z0}3Xt{hRvRb@X~5URI$ZXT}=lQ&)+=+}-3nZVE>d`^Lx<#N>TAYyX>l@xWAMrdhCk zJ~g!isE;de!PFxbTv|Y^g#A$5Vqy`TV>Ae1wnA_!dNpC@263qc*Xco^qR$ZL8+Pq2 z=w2-q7oS+ryL>9<*yvI4ff~80#IHVB&~Oi5E1NTj4Dzh#A9w2}Ib5YvF@Ja}CT+Fg zb!&Rx7%kK++c3X}4M|IwxluM3AL57=jIp6!Q!7kesngA-*360j?;}0>Ij?v?tS+q` zb;HCUzH+YeVG^;3GW1}&YQ^W7tlnFy>H_Ixrjb*Lo)l+NiUe` za?Xm9Kbe(#(1!cH$YHFRixqqyNyPjwwsn$2J)C7OeWd)!Jv`B&g}f7IS$5b(PM3C; zzIn~$VUm;F)OyHZVi#Smx=1DOX41M0y-jo6WE1@x&o)=eIX`++^m3B9TyJl7GW#>m zN&akblLPnEa&MbbY(w2-<3N?TOi)S8V3jmK;zB)zr(`fU%zvt@crQ>%Qd~9X8hHyfDBH>BEbq_fRboZWBwSzV)m=0Mi1s*hH=3rq9G(hBI?wp_Vy0S_~EX zf9&IjgBIS~{4t#C?Pc`n;J#H zZ9RRi+LNcanmKhT%okh1JZa+2r%RCg*gXQ(Q;9uY41@U&v6{#9fNV zmIaoN^fA>iJFW_I8yfO+5q(ZpSx};t1*N!lQVZw<#r3qzkKEy8VrNCEs5hJ(W3G>Z zlZchJv!Ki0DR5YALH)g{C=q3Wdw*uue6wKN8@^6-D!d? zIoBjT9Os;8e#@j(lrvj#YBO=6w^rDkbMZQWv&cU-^6iOf4PlPwS#o{CIgdO-9*L6t zk=x8{iy`hk%8El-Jn$PDwI#VMWa(^qwfe3hTnE-&8PF1>Bi%NY^ox7%x* z6AH%qc)WbragSXS^Nh?-oq8q2`HZ;|Exn(|$il`k;@2r&X16g)9b=62YGaT}%$)9) z$T@$oL3*-(>Z^;BJ`G|dwca7|R7c6Fs|Kl1+9Y?{Qp*yZD7&$i z>$y{f7xW}qvPp&2iE2z&yJK=3`G(Zm?fsYiX=61Gu2kXc-^`7srlp&j^P2W*w2E}c zNcIzl`co@bxj9;XRw4V63ND=KSS>1SnWl!raL#oy$SWySvR7s%z(*x+^`y3@ggf@n zcE|2jD%AH^Bc(DmFr`EB@EzxLgUCnxOOMDhp~zL~;axWb+T$T;@rT-$F#4mg-#Iaq z{DyuZ zD)s0?o!>;(qyr8y&mxi-NCx{=_WBc9la`yJN2OBn7{)s9;Cmx%>Gb>GMhzr6Cc|0t zJwC>{+-=TQEk=yqKrI>Zt6#myW6U$4BmeDkjed@snT1h>wIA!eQ1UKzzoCY&hY42( z^5Z2l*zOxK^D@01`wl;(_<-_yP#d#h{{^(pkiqVG%hZyDGYlZotM zoWFgf2hG+D%wSD;#GZZGnoKy`i1U>ox3Os*UplU!`iR? zJaQHvXTqa;7TRy1r_EyeS+&c;(eK26`1$U9dZCfy)QdHsmytbj9%r%qzSy=u~8?jnqJ z?SR2<5avC0pU?X~f57_#AJpJ6m9!K{7;~5>tx=Fe9UNYZXEwee-;&i}M za?5*2z+#(3oMvAmg=fig1yU<1QD(dy^{zruAi*d(HxzcS=yN!OvC!uryu86$I%5>q zxL99xon`qBed zq??+^;Ter(MpQGoXZDh(6TGE4y_vEeE72w04l5OQ_-CI2mmJCN#VN4oWiZx$4McnH z^^<0V;Gdejwu8Y~uZ+cvpWKg2#vss#T28IWrwQXE#wn?dcs-%iXnf55_9k_%ZgQp~ zHXjb$-}cmchwsbY!AKqFw`9^<2Q`&p>!_;?FPU-JSDM_=%J)US;?Prxdi9j>twX)P z=?c8|Ag{NJ@upuW=9oe;`B?};9|q%wu|HnC3&C%54E>{HPSVE63*(Y;pip7cwj|73%AsCSN<(haDe^fDifBb&?9ah@_|mPXoF z^^&sZn@SGjfM%BzP){KbGDv~QTMCSr%d_3SB&shA!uHT0e6tHgRdPHTt3wgS>-lzr zj6-%T()+}q&-WN|O)+@4gZkg=EwJ>naMr+rBm62sCd6bjs;#FrZBuC>Wm-r!8a ztPu18=M#1ZA@42cid;gm{v?0*g=mbO!dU^H#g}-0?p=vSi!ckqQW#q@HnbZ-AJaM1 zKVVFHj{KtSCpp+&+nFMZ<4jT*c0m4kM-SogT1<`d#87f6`NPy0mEnnP z5gN``EyB|R&hCck(e9=mRaQmfq(P6G>#2jd)QAbsjrdqdJ=$HYX>OpG!GIhrS(63# z{W+K&mkrZR&iPf!!DF(NLwQYuKafcYQ|fM#$5>oVsq1>0T1|!VvVuIwIC2-24jmBh zEe7V5T8yp4bA{J(x~T^9mU!XGN>3EoQ|piS<;IOj=;yH)a$1jq0M-~jaAxtk2{reU zt88h)-(teDc}9f(q}JCp?s>`_?AgrxdTTbKUuR=*Tcz&u1hODx9(r|F{^yn1=o7WT zcs_rjCcxQt337RKvh1pzB15~R$o6-h*gS(8Qm@E4T-BiYA}zwpdSZjG9^v$qXx&2( z*9m&G9KHw{^XZSt>lmHF&n$y_h^MI2IN1o(8=fT*S$H>!dA%34n>KPUubzXcm9o+Q z0==ZjIehbD4~X@(J*+A2??*ib&Z$ovmn6G4a-LyYlC&R~B4vCNWPiLGsyG!CBQ@m9 zHF!Op_bHVgup{)CwS~MVYcvx!M_|Sw@`JM?K|&W>Ss(v!!Gr;Hvg#5ogkNTCY&6PiayiF$TWs>K6@w`kZFmscf3(*)uM;! z)?|5I$0V+uGORwBcS8;DES$k zsG5uwe2)IAU__XU5vwQWpi3t8$1Y~W$j`282G74q)VtbCZN}{i-5k9_H|w!NclJHK zc*5xa6xmn?P4g1_1|Bj>p^>Sj8q0taYALshXG3E<^sS&o?S(uyZjyg@Q&N{U7-ii< z(Bo1d?$`yR!Kz@?R)%m6kh*%KV=!$@45DhsV8#J@{pC<+cuWR7>yfAKZ^qY?^e{d} z?b`Ylgr20Ho>M+jr{`m=*$TB|KEjzxzFnf0q*fY9FX1k+={{2RsYaIlY$dieb|`mN ziCM=uClG9h;tqCjGBWRC4s^>D0%zt!E>o#x)IJzDFNUI8{aEzC2;Cm2vm=#5qT&GL)=2pbvS3i z9tGjnr5H536ph<=c&=CAoWd`1mdvG2f23a6AG{xBGw_jTeD!4N$-9tm{KJaQF8S2+ z&PQ458tprqk6yd;G3b`JB=2;Q119AlZ zogKD44#ted!Dv)S_Wkc*L#1u~(Ts<& z^ml%nj^N2=>f@NPowESTujk`5&oTdZWb$WP;mEu`(cVq8E!0xM%T>;CCbxO6x4i47 zm6OwKve28J1aXD(d!zz)mhg;kt-z_-!HD}DjLKvgOI`@Z?1Ug{jf5bVx#Eqn)aoC= zdC_z1^E$GI@{Bx17WFiXEYz5w{xb8m5WN{)3+Ovtp6AvA&Ph(>JO_0VO+I5!v@+U`-rQ%r?5u~T4kO{H&$@I!F(PNe8Mmpo;MMku3PmZy4 z4zASB#^F`jD4xN2pS#p6Cx=#_ymI67)I_{S4t_Pgv3QnUS$jaTQ<5e0szFu`CVSp4 zS={odB|r_4jos8Re$pazmj=PPS~&7NwOr9-rVH!R+@JUHdTNZLwjTFqAs^>+n`hV@ zBgT;({2os49WvI7o8+L!$t*lOl8w#W4>$ZGyBE(Go7dB&u2LsO3SGNB?0+02ua}_I z1yHxP-Av}1nhhwVMk8R z^>idEpP=4KiXL+Yns9To3G=s`5SB%KBaIO*r;YTqV~)VRFp4?ADb|l$)z5+TA9_B2 zRp^`&sB1&Ma$*Uk?lsShTzVOgA97G!n16b2;{4omYUj8ZrFFVdLYGp@;0g799JR3T z;E9nnyzuj(7W2DCVxD&-XOqY=I!2=9Yu5G`vF6^!gciI%E<8)WJz=ad-G~Eij2O;- zsoQkwXkN|6*oV|Zyq%3qXKKXrERE&04Ca^d3AKd}D|F`rl)AKS25A+LAPdSE{3W7MGLbmpPt|9!$*^!Bm>(MVCl?SxV-? zME`9oXD573=w8W)UAv8V`J6e>i!5k6Fb1+@q1&NMJUNz)qw5vAV(R1kX6$3CuhhNw zCmTz>nO74H5>9QRd&iQ*UYR0;{0yRbN8Yo$3b?^%cs`lW^=g<#b3WiM`zU|v@yBvr z!!l|e*XB7kM~@fnsh2&Hz1j#P)&`p}@HlmM#_%jQev~*N8@9q#45v)fCYkCyg)iEP{dLEYda+Wm4wF#~K(K(*8 z>Fvl+PtC)Ne;njvI(5yu(u;_-;pOCF8vSj>!dbPYO1WbBHjkbtE6LYHaJKbta({6i za;!7;dY6*>TOEysd(z=Hm9@`QCvjf#OHMrVM>1<%Ef%FCdtDwL`!^tyuE1C7ubm_p zIbsy+xC_Wb=lgOv9YF=zDDk{-;4TgodZyOMEAgqiREp)UD2Z_YI=X(Yoo|CWza0^zrXyy4L_xYQ-T zW^xvfAnF?q4x$b!=dk;yBQBc%u9YeY%d|L5meolSuBDEIM&!=(#++#K&;-DGtCv#?CZXLPfS1h`s0A!{`16$1SKb{Bu zc~=Qm^K)0Rui_sKuRqiABsLexGhF3R5;?LzsYlt9|6Ziy!yMKUFR8?SPk}sb6olyy zH(|-DbnKX!2S+!R94P!LPOAfO7u0J=Nk`7gJXEOXE+xtoN^ONd?o9pHH#{Ait+{yA z*HP?EMG_qvh(#6YQ+z26ZYQ`d`ZbU~-Kj%Y9DqMVqwt#itU;HDm(Y}e|8SW4xY8|_&hiT(xb~=Jnj>bAJ6^I-V81#UH=i zq}3V)qFZy0@oW@^J9F0LBzq*YoaA7AdZdk~Uvoh;{%mSS(P#eN6|U0EL4k%F$V+O- z@tvce^C`}o3xNIGO&EKH9P3|J;A(55A*M)u`fBU0ME6(N&z$?>*Pc3=b=so>c&-<4!xOJQQk1h?wR<}snm88z*l_+{rq;uvYkN(xvWx4!YeC7tik^9(} zU3{O~^d+C|A~S~;ilrub!y#N3hBSmI=r6RZfeiOjpegssYTct?Y|glsJ*J_idNO=c zv3x2Fz*6dUJ|`cl8XR_rA#*`15cWn3lt?r&+MqK@sq>!@!!9<^d!evOONC~K3p<^Xi%>%W;Z zbYp+3Lo)g3=Y^7A*bfiyQLpw|I@Wpd^DWy*R$ecZF)8GQ+tLr+)rO}@O#X|UnmuRvc`h{EmWg2x}UjUL=SEXX^VUQagF20kf-d?jwOZgI~yCnBCFBgT9j080%fj!se#T zt8@3uiT7^ULSI__8u}$X$fTc+LI?6k@$~tfl)n%){pnlXl75NIzh^&Ake@{!m=i`0 zsCyDtdC_0TU7^eQwqIhpXt48F1TI}8k2Z`m6>W6Aw}R;sm0pB zbLzoep*MtMIOe`dL}AxVIPl*)-X}?}w{^$4fC!WwZa~~RYELm9vp4ONT0K?BYY>hG z+mbjtmx(jv%j!n%mx()6X!VRxJI&UH;TTE_lzX}IuvaT3RU*Nwv zi}cBcCAxU|(&1mtbUk*pGGIeA{hsP7bZu{vr&FpC|2qO}_8Q^XlOCeOY&gwz*Mra1 z#hVN1^OXe0Blqy0+-u$M`^1GDaq|3dsJ0|wZZOwNM;q$-n#6jG{8Ap*dp30y-KpEi z^*HT#oSb7{>5V=DRd|2WYh^Dz0sNMTDVOPS+Fqec(NUMgNsSa&J^J%`vvbZwS_!Uq>X7vQ?hd=j;cyDz za~R1U3ik)E5&LDuad*sXMgI2zUnjrQjGSg2a$k#+RT%CYP7hTBd`?nV|B($p3aGa@ zO^y48aJ+j+pIDcBIK{lAXlk5v-Q|W)4I^-W8u{zpnW*yBhUYgDrH@U8auvv*+LExz zmIWN39w}a`=gn$U!0n#5WSvxF?q(YHq^U+T8s--5@dEWHB#F$Z+=X_c7n_l^DMJ#hC;7`CLapH`om{mpH7Rx435x4C0c zFFpP&M-KEvCc195;q!w1lAo#mPkX;-H=YX}vXR)-hJ;N<$+aWrPM;gYR0EcWa9tcP z#<;cd@;hIJmDIhpu}^1LBNHS0aQ`0`C(21G6t#skb7FQXlmRPMx?=?-zG1we6?< zb^SVTn2?%w*xGjRA*a-f*Q@%yN?7YxarG>}mPf)a{NEsoKw8sXH(D zwDtDCl8U(XsY~8oOg(kjcIs1hMZXDadZlK~n43D*u8!Zk35gQLI(nC2lN`!1ileVl z^kfxhFxQ>GJ5JP{OmhELl8hN{l#F_bvT+vuC3YoB)yfI-x@(dgi(tQ*zJr!$31VGm zl;&NN#djt3516|jm}8W?XAM$gC^b$eQg@gvqtYW$j$C8iKFcJ}Es1iwFj07hy1 zBfCx{>iT6_70*s_-2jcDBzhGNGQf{@_y%>2 zaQ=fji}v*4c#}z=yDSuHva!!82i_jph}l9WpEW6a)?9ksqBhU7EX?0bEk@SvCLYR0 zdq?U=uznVICJWalW}!=77J9H|m2f8;f1k_7jePn~kD-5HJI;Ep$U)7g+1M38ZO2Qj z`*FP&GgfOD${s|cY@|4`m$aJmyjMJ=bji9h{5$pIPN~J((_IE=J*4YUSBWa=F2{B? z68Agq@=ryT48H9y8Ry-k-sC1yGKF*MowO2h*IQaU_{i+7&T?`ky(FNL>bIyfH^x;u z%=3_PZ#*S>EqSc59-?&QjNW-?nOmM711Gf-a91TseVK34L*Pq}t8AU?EcJI3%l=ME zBn(mF?SAG*Rp_xmU)y=UN{p+iL{K)_s|Q8$_>%%(l$?q0ZHE)vl=!P8`?D*4%ZI88 z9PXsRg-bp#punDA3o}4u;|6t+v`^ z&j;3nqo`jupI(LEf6I2x%UxI4Ku_CZ`UWsJJ^Pkk zwfD(0szZ>>p7|gT&Y9+gpo4E9CiM!&`y~OeR3_KBH4q_d=~>;4d0(3le5u7c!CKZR z=7r#G$zaUv$UeKCY}L>pI9h|yv0E^zP~T`(2AMAMkKM14Ma*D6QHfeYUYw(!9fOd{ zF_?Zj8a2C6dw_NO%}Zht***pLy%{MujHPsIxo<8@^G?F_moM zLFP)|>47_rKhK|8Uy{9a3mL0!(bR3A4xI!4&OY|MnPjW(M5B#;EOxz%#`$gJwU*G6 zx1j}_zNX{SgLJg9;|#9R0(&P5Ua*dlxrsF|{#h}cS_6|U==I!;CpXfORgN|LRu;Uh zN)3QD)Bq@Hfj{$|*sEqNJWX9DzFz00nXE8*#r9@w7-UA%+vKs*$w{7~FT@ts`NcS;jsjp(i-^P6U15>}KBDIW0S*h{E{Fpr@ z-;!1|KE@f^`(&+tu`WL{AB(?Oagz18E&W)7xk^6kLOxoY$j9upWU1H_pRZvp-;Ycc zdmR&B(`PA`Gnc2VIGREI#}9d!oRNpmeBUd~c}v`7Z~wPe6!)Fv<84nln&B-uNn{=l zddPZepw0+uB#$~Ymdaf;5@x3r{j>)1sJXlB&2Sa%E44gPs-&OZMW&bWlETlfGH9_% zzEY>+Odqwh+~_T5$tpT<4m4#rH6D9;$eQz7sgbIZ;AI*a*UUrm`QK%iddSCDE|N!{ zVBX7y(sS}}$*-h9{a7-?eeHnmWPd9bNv1)8ZuWNMkvKEFp;(^xSE6kfB^I%-w(*Ao zhkn_ljgGpdR{BfNDwK2miljF6xL$I`^7>|*Jbqs+$4bQBFA_l3Xi5oGmc}uvsVl@a!vlbCe(Fe zP_qix#{4DalRllS)jf;i+Wj4c(fpqJ0a56EiCRRT}RBJ~|R(SM>hH6F9fsDIduQ#09vqy|>G?d+{B;JVe3^%%o>mlc{cXCGi)UpQoXxus zes)!#xvAyTeA~SmS3cDz$-!^S+G(k0-`q(ZWE|i2ceXY4sl%=|d)x=51syJR_Vw** zenao&`*olB$gh>6Lc1}WU$)+x=a5$7PH}3(M7MU^N;WuqYwx+XHJY6`TOq1c>W?uc z{0x6rPCHoodE04g8>hAWdqmqa&#tx&t2i^YRn#HB*JX~iIiT2{dU(CH?V)gk%&Tma z;A+VdKExy~FD6Pd=UJ{yFv#HN2GO-MN|z*qbTB7MOU|l}xR@mMPN&HC=p<3SpHps5~MtaVhWYH38AKB=4P{SziqD&H} zjh7cYP154BQS2o}5+@|co`Gt--k`;^^7P2sNZtQ6T3nq%4>;CR8oy*L$KFf>gBEqt z)I3Yn$epRh+j^YWi__58mU`U_)yR(0p!QfTN^PSy*G?_9^wjt;N{w-WYIK~W#!zyO zkH4wW{BJd;vqrFCq82^dYY^wG#dX$B4&2e=UIS`aFyDRkC+A2#$aG{=pSxQm8DGw` zjts|A1$mF~NccC`W5F?MX?aJWHTlIDFV63^rWW@_vMBwj%gFdo$KGCT<{2+4ayF(% z1ib!WjJThgS8Mf%n5BnXFZTaB>d8Duz~`zSEBU*Qwa{bkRO&Mx*JI>l_D(t97Vkrj z<0`#JImdhUXcFcX8Ij>^!v5h#%maIt(}*{nMH$*=X>V zGoLP5xcQv5xt;74j>>_SF=1tU>eh6m?nk>EykZZr_nK_XU(Na4Ls{7HEDPWGbBoOE zF~(&f_s?t;tmjPH9{O6(%)!2;I~FzkT)3YxK366^LyYs6{v+6!YEbSGK z`B_R zV(LVmqt@=9894FCOs@nBtZ&RHQ$+52j}`A0GUk|(kC6uMv(E1@Y?6=oUExg8OCS2q z`p8I!#?t$bCQ?|A8s(??dF@r8MgyMjkv0h-->7=TxtXc-=xjzG<)%Sc!SlDFG6(}5 zV*lemjy|RSpduExgkE8GG3d6J`U~V6dhW6S5!3-DKNHK(&-^wYyPM}@PTV`3983?< zr}@;hrcdT?A30ahM7HnqmE$F~;!&lAemyax=O=0iGfw=;>xx#J zF?t~5&s}5~H_?;(XC4A$tgz!b^OW&gYMCZ-+fO5@qna_lZY({bH8Q?(6KQqK4*NTl zK=YmoOf5k^B~QtHLWzqzL*aBM7zIaysAUj@BWHqOcOn!&EAm>7l3%RMIU~jmop#1x z;xOKy{)|=m88yCTMloaCNqx-FkqMd2-e=WL`Iy9bakPmX>L2u*=Jk~9azuP~8^!eA zBzbuWvU+2pbQxoif3|6HDTSMhn1 zYtN?E>lP#Gmtu~3%7DQ!+<%zAMug-b=`H8jSnn(2oP%oI7cTl|qXRuv4D91;$$jmA zP2VKe4i7w1=$!Q?DVUrhne?LYUU5La9Z8YTtTn!TsfBZh8nz~$DEUImJ`*((_Gn?c zPA%MYJ^b3~(QiI^bS1Tu@DW5BxW=t z(9F5SN36e&Am>>?y}w=5Y$BU-{#-UZ=2L&G!vAPjmj6O#a5PzvKa{$~yGpxyS&uEg5X$NH8IHP>osKvUb{G3{9FtDix z!zc1tI_ZhAw|OS=Je5}D|A+DUabZ2OVkD|nHo@(S0j@l=7Vxa=Jd*4w>yCSGv3}e# z8}gKXFRjT~vaY_fn6=jea-M!lT`%5~W$ZWHeyPx1jvyQIAVq@mIa6`VAPu|{ru z7S}V#(Iig<*7L;OI%GgfYyO+Hc*FUL^}dmqIgwhCWypfCRy(_WBsD$A6ZJNt+Bb5H z@9A@K(TI@yoF{EzK(AP`o};N5*_J$PXf~?G(bp=GXBvAC7jG+c3C9(>r@IuoL*!GM zA7kId!$)R5X(Fj*wbEt0yIl5D%dopz@##Qsh9D)9La7ZqU4gkt%!e-9q4uH>bovqu z%O3hnGdKB?7l?OX={MgZmYy5ToyU@aKg@i%S`4-~i$S%O7R+BkKF`mBxBV=b=$(O4 zjGgB`rEY&XHTAC2Q~7}v?F#bn_6`|lRTJsi$y2&5p?C4OhEiOynY4bamTGAV&JHT! z(%KHeDm&=EQY&^IzxsrrpluLzk-^Al9E@tELg)(-f?lIy@q9ZOIeiS~ZeyO_F9r_G zLvDF8R=4L_I@f~7x$KcvAm8|iJ_e&XdsN{aDl!&7NKR!sWAv}TxDP#UBGaa6#BHjN z_>O2QV;47-sdc<$9rMIv=k3sBA$iZw3QXp;%rq%cp+*S)>=c4B$ejPlnaDT``nSwLNAh|~iy7msX4E*!UTacKQ)qoZeD`Iy9A6Hg6f0z=&!ewxs$I2&s{C_=_cDU zE*&1f%y@i19~+Hi&6$f_TxLb|Cu&add@W&WEQN2I%8m+6_v#j`+)0n}rsP`MvSu=j{?5l)H}PQ}<;48TpL1Q^`FSOg|7?Nsa-61)b zt-)YlEry=(M0axL_XaUH8KcF>x{+|}7m3k}^wcDY#4I)Q3~KH9XiUgGY`|uoUDtaU z$;TSex`YYCCekl>Q4Yq>qDJkyY?Qph`1w^9URv0jB!AYQeC4Cf3S9-BUp0AclP^)1 z;2!J!w^Bq;&4QV)k|ld)q70r*KCdfl_;0n;vDd)<2=yyhd!kN2BtirADE*kT0lZf; z_tN8tXRGOy2~GN$P=e=asLF^*oX0xUh+51wb5Nok=hK^$!GFaW_HyLC9ka2C=lY61 zN?qj#yhrTUp5t{rJH)ef1^X9&9+&Q($uh5bvZOm6kiRP?%OV$Y_=i2A;yHTvff{X? zE4E&)hT?rB%#WBiH6#zPPLG?5sEbi85_|KEoCh#rO;Z!n9GEw$O|a)a4W8#q|H#4J z1fCmxIZMxLIcFwYKwt2O6BW8+pU5%tdPeeG-ORJTU;07Wnv)_O{^7M07^P{@A?a4> zptKsPMcz6sRxbAh`E%@~w#U6_>i^7)1o->)Tgbmh=@C*Kfol~a5vif3KI`+sGkx$g z*8680FiuIm#vfT2{)Rox<2)&R<4F^^gxs};K5E=pbZs!E+l zqZH}1DMi+@KhtJhvQ%<7C_eM4VcFOV9||;BK2eP)%h(rTPF#3Zi~71qZ2ihU#9;D_ z_w~s0ibSW9WI%6_W#m_@sYcwZM9qYs)O5-wV|hA@n(^7_(lZ;Sj%UHpCmYuD^iR63 z(0%bx>Q=icbsfk(jG4)M^yYtg#w%ayNSR%~sj>o$)MlpD9(NNbP;{O?~*#sA9F5jf~hn0!dm8{;tWTbev7

YmD()?v zsCQP+O=^#_Nv-g}|E|YrnHeW^R%+xs$&Z)C^2M-Zr&P% z_4ZN7vu7Suhx2ttm6+C1ACUerKd2w@DUbU&&sc38M_E0*Sh7lUE+Q@p_nUKHAJ19f zM~+giE;+%M%tL!}{`o>0JT~MZlfL1j-~X0HJl{i)lP_P-d4J|n`HkpHTlu%#b)?^u z%fJ3eX8NwMp8c|(jAlRNqcBe4zO8M@dfrYe@}!3B9c`0aEBxU(oxa|UIVZ^a*{|V_ za+&&-)#&3~h5dmFXVS3ud@iPCIZLNszr^uHKinr*mGe9eOEdGRSI|h_S1yoB+xa|n ziNUv=G^nEU=zr)aP6-9_!zB&a{KkF9nD&>t@fnH%Waz}jfd zB4=3>SRid8g0S}x`CQgePVx*M96N_2Z1ZV;(9l zQOQ}K0y$HWwfoYnYx||+&QtpEgw~c$zl){Y*+8h{3p98xS%X4djq zAMduBTH@WTXtuyv_PnF-6YsMtbp<+BV4eCO&cV-cmg7CBsgT_dGx>aeUSmd5bu0eL zX(;oX707(&fdAqt`=!)NP0Yig$_>Q((=Qn~ED%$<|Fr9yj9Q$*je%pTvF^_rs1Q>dS>OMe@87eWX6HA66zEFFIIJ zrH+fNx3@_cHBFZGpti_l_MevJaaPth)zu#_tkgicOT*vESO(r3A-zTaJv_ZNvLy{j%CjlzU_^tGQ) zzxclH62pDqoHhXC8Migyy1T)i(+cYF7A5}{Reyg>8cn^|_US0~Fb@aw>Pyj~U-Fjc z#nFB2_XY6!7x7&9?I;y^f0~27RCS`D;Qcvs=U@KXP3}ziDdkwVyO_U;v$pA|b|V*u zvZ_gjC%yCb2Elo66t3+eAI)51a1&2?Q^h9J&Hfn4{p93e>S@O3;k40F9vmr@yHNqS zNL|Y$k97F(dF%c@PNr4xzoF*SJXcTZua&ob?6q^2uOc~3->URFqW=dQ$$v~; zIdcTsdK>WZHFfch(qH)fe)*>JK-~%9=-k(UmCNp7eiMbR(~vm1Qd^C3`4OlwkN+;l zq1%TjblHq~M+d5Lxf5&ToOcP>k%ff@8#VO|QaMz| z9|Pmbzp4ASEE8>ObDqN?PPVjD;W4?t=>rUyRGsk}x!2IQ31VL2&g&#M>R`YN2iB?U zFh*LRAQ`^yWKF_wu|EBjSl=4ci8HZ%ljLke`utYr_1sKCBR(hX7*}mii)VTUiFNk;> z22;oIc};iR_YOy3EIGLEnaK2_w)VRO*+D+Bn7xf|JIGbd$-?pZHdLsZC}XR8a6Xbe z<}~VS4Wtjp2pc_ac8eRYC!7A%fAMpyx*&`3t&N^M@v=Rd9M;QlY~%ay*g)>DD|HFq zB}#3O`wNahGC!~N@tLd>D0J1!>=(QD?&!8rxbUtt*hnd^El zH5yJ+FY@U=@eLw3s#%C`Kd8T%Nqt6gWcso3QmZX>)ySh=c*W;oC3W3bvfdVHl=?s1 z@yFYR*!IzY3(kz)In&$yd7|WpyTPqqI8L5SLio>2`d8YJRf+W`YH-}09*)thsclp7 z``yS1_Kp{u8+p&x;mE3Nz={|?|GVg;O`XsguRP$KrALV|Nw^Z6g^XqjorhPvRJ+9) z;F_GVok@OnF1eX8)Pbd6ZVr91FMXpQtv&TsKXYGlA^*EDPG0( z-MJ*hC1>K>ZStq&tY?o>qduS8)~?jRXim+F*ETXq@zQRD8Wc%^V*?|qRLVlt6i-*^L^M)O)R$gt}o_aC~M%-*K!}$8aBr;y&4#UIBa_g1Db#fV}5W zdbu?V$H&9;dEY}_*Y*nC&p`6v%;o-2UvI*3?;> z&ZnYR@|l@YyZt8Wccli8m$QF8oYlJDi598GV@YR=N7qSRnOq@lS@{ZSOP)uhmfl#o z-MmBgX~E%*QxneUQa87|bGB*5tJICft5eN4;-s^I?DhRbd9lMFx!p{%WiHQ9^5iGz zg|s{@UTW(T<-l5loa4RvOjhyaKZ){MMLp%elcY1(+3JQ#GLk+I$7Y&jZv(#0vnTCD zqMSZQEgsG(j-z)+V!ly2p5bS6$|(Nf>~nLy9U%KVoqS`drSY=#6uH~J2Kl{`{?fi` zJpPM*9`uKf{acM{Rp`f1mVaKLX9R0E4Jv7|HJrYHKlnKx<{8TU;vCP?s?)S^DZ_eq zX%+T&QseA(a{j$Jd&ru68`f6hm(W+7v;CO^RQUOWULpOc=hL2=rvLW2tEf>rNke@m zYS_->xjB~FJ_%YxUyMLdNj-c9kT)bdKBxlgLS&WaeT~4TB5LEz)?>?KKFd!c;K}+? z!5jJx(wn-|4m~|_ijqn=PJ)IhK2N8AIs@ANKb&sxo{f%G6e!}nmndc4Vi znR5*AzQW$a1MbIj4LH=oh~>MTRG6xi1H&1Xj7khkBoCp1agmN zZ=h`m&$vff=&7Mspp|Um^=$N+$9h!lY|cor{-R<{i2ID=6MDV#9GicFy{OzwbYk7Z z&@>xiWY@p4Z+%0Th1mY|ldhkQ_`n=`xR77W%0ef;=QYN2-~J+VzlZz4bZYgme`GC_ zg&H%c#~hGNeNK0AadMWb%p1v z@U;}Vs_8cQP1dk~k7D`mset~iO&sitq)A1aINr8NqjpLhu0{`{k4jvfT`V0rA7omg zfUluQwptXZN?p3OWVCd%ZF1>ck#smyELEr4q~Aem5bUJhBQ+i49~R2(Z06S`ilxL1 z1xf@2;kt7W+;32igUc!eU(p4=ky49&_w&Y6>? z+C)tta)<{U>4DTL5Zgxvq0}CKyj>WK5!-?=f&63h?E#qQ5rlxGAcO@|KWIS!u6Cm~ zgnuyZ#dC)2GUv<2(igE$AWq#2M!k5>Dn5&ZGc=g;ftjpP!8k9DGPmo}RuIVtt91(%*N4?9bSYFawf7tQ3DE$H}(9?_Gi+j!WFUN_TGWj||O-OL!# z(E?e{x_O|5^9Ss|kmI^Gk=jVi?VbBrFyx^btAd%IZ!u#jxvl!=%xKq+HTMnt{mHBo zT`}W+Kt9%ZQ451?VfF=jSp_k-(y(68o|JtYr!PFZoOfOEG) z=wW-sifQ%PXP%Rfm4DEWt1fkYSVMWoo<`h|d>lK+?`8ja@HqDDCsN1p2=m2hdGO0( z-HrW*Q?uDC3L{I&Jl?J}dsf5wy?V|OH_%9rnp#OM^yci6i###7Nyfn@^2ndHw4SbH zGgtthIz=(2ydDElHTkeG%_R{~KmgtNflTx+*L==pvtGJ`Q^1--TC5C5I-d-^9i$TWY9xJn*D z6$Hn7tEgkD@P^X}0jtueiACQ$Em0%z3g#9)%JM$?*n z;~LJs^Yv@p$vpmw#-Nt$X&#Sej>fg-5QDVMTuUvZP;&`;jI8&Zs}+OHsA%+F5RF~; zspEKq>+vT2s})>Jf78DrJqj0nxn}?3`&;;4L#YY5G8%6d@oRkyUbE-tbT1v9UU6QO zeXa?I%&0kzHP`X1-&Upnmmi;fOFCw7-CZ7K#>j5`Z+?&V5q*eQJBk}?#=L*1hZ?{& zWae5)QAhBb3JuGZ^7v2W(;V}+T9ZR zX7J}%th3^08Tv@OkyW{u$KDoaRX6A3RGO9gdR9ChNbjJ-oSRL~!--tJ#&w|FX+?G) zu93H_-zco8^pM&ocex&oc`!%kK||iL&3nF{L)}x>=KJ2WVu6Y^`kC~7=Q>@-9@=;{ z*VT0XZmz)%d=KIGT`a-+;I55+e|TL=T~rv5`d6jhslQU1rJX%!NPV#GM`}djnYIl| z9P*o+`21{}@PO12y=$ip*xKCBwxYt>f@h0U$CS!Xb(&-H)A%Kwo!Iku>dxB7&jyxh zm-=ORg|m?_Yp1?hKGg4ajmxQ*8e3B>2NTZ>DqNH5e$zSi&5P92UoX{6J+$uR8HYy~ zQ=1)JmHJ4TnA&dk@>JJViSnRsyp-LRB=4rA$R$mZEObkj=m{oSeLYFGO-Yp5oMXAm z`6ZvtCh^^6kfIYQvTe0Ne*9pZ*WD;jbxAUONwU=D+)MDiB$>F~Bp?1TNo+fVOkq42 z{DAD@PtM8B+%Ny!FvyKgDKgI9C~Ho{N!f%r33D(?vexJEy{m)hdKBmYlat zi?2P@7%`p9VWUXuD6yX@k+}LNJ*L%UDjsq!>xdpxDpQZ-oSt009&aK!>(`guB6G%q zkKuUKhqI&nT0`ypG4u5Z+rk-{CX6@7k)6>pE@VyW>oz@lPG&8Lap#0ZoH_i9IvMut zE1inKknZ8A?99CMdj!Uh(xc=zJvK5{yE%n%UJz%+T9Z+nK`(~o2E5zHoPPs#{udkY zX^0W_teJh`|NAhBUK6)imnunZ?qVZidm2#gG1;LV?7uqGTlFDxpI=EhIn;nhlc-5n zjoge6c^NOpjBUvAv^QeJaU=H4rKb05GAyIWP;w45q^=30x^SlER3V6F7j7vJb)y`#Ocf}kuWe-^OJ{yZxk=Yrag}v@%8GRXZ?&MrDzwh&GYCp2(7PT}R zYpVS(&*+rZM2?s95<8`*$a^md+v_RUuer*+7u4%5vO`2KC9X7MPoL+5KPbo@pEG@W9oN_6O>z$Y&|4DF%7k(UbS*zZ}u7*91R7`p;P(QO%Z zzqc^X+epviwLA;RwLe`HgCuXpdNpFPmG@)`W2YxyEl6`BtIj>U*$48TudImI#KHAL*A%h!((C8TIB=J6dXAH=*YgH9$bN}RZRJ6ePx&<4y zSm3k7Lj4PBS_WG&Wp_R`$r&Skrx#@?*-sny>e*UqANWZ239Zbj=_U6bXr;*kl{9{? zKqIm{Hpdc}c1nRE6Y2YEQvj7i@a7pgkS~m{BZJ7h1z~9WAoi%JKNb`XpJCJ_9~^@x z^QZxKJ{o(;TU66q;C{x!Ib{nzE~iewo(#?hSz+Ik{Od_F@#F{}^6QFFx4U{%aqg#; zK{YhuKGs{thBOfeeG@sBqr`wMHc7g{I3}L+Q&3`slA3KTL!qf1f(=(g@bq>Fo^PVh zD*2Q(EqM(WqH%#|_~)~HuA5R<^I8nvwzNCufd(Is#u0b6>ndKjmHQopUd_zMDF*%wMm@G3VsIvzqJQ*C!iwD^bhU zm<4CDgH7GJAFO2!iwu~G+{1L0Qm1;Q(6u^2O`v^=(!DTQI@U;*FO!nxL)Qd(RyA3o zR%mf?odzd*(1$XH^TXfNxW$@+tpoS*R@B?#p4#nI1m3RFV|+dOJTs4;!@PI6)rg0; zjCd4hfW89#7T-{Bwnh$CU1J_fjiRK6IVhZ(gBGl@j#!}3Js=l%y{AG~{(wT)fDFWv z(?;3oo-7XnO!U4;lI|~!obNHpiCe5IueliUiTmvC2lPxxr+$M6_whC4EvHf+l8j73bPl}_$$7qKz4~89gxZj= zv`XFoA?>XHn%=|rKd?nTc1uZaAS!m=*Ywy)46(brj|yyd7YqYiscqPCPzJ;9B*h9rJ-n`=#*ZsV&Yobn}wp+{NA>VkGeojI3Zi-4dD#@FUOJ`?# zY0__bGquUTzEcCK=7(M*e395u1zc1jfyd~#^)`Z(tv$5Neo|>9$EIvk_@eq3*$)PSHAJd1&l0mLA+Q9QvpimED zUE^8fgR)3_P%PDtNay^6ayP&r;gKfk+n4^8&MK%mFHeFm+M9i#AU|kNE#@ZA%dj@g zSgrFPTeKK`pXd;?%!pMNn9oC&sN_f!sx@X$_Xp}3``LrJkp5rCv#{j`^BxXo;bsss zVE3?wF@*ib6Hv_ywmF*>Z;szo2(&)a?JS$UPYH1`Z(Lm>)U8Bwx<2~+R! zST2%h8cp4!b2bc*v)G%(xow3){i#r))|27+*w{|}Umo@;EA`kZesb&!*}*c6Wpk>Z zGqCH$cTUld&!2UZv`}J2?F-!3QDJ}B=a(nI5 ztw`s-u;;2KQm&w>-QwwxH5U?$0^)Oy+!A z?0Xi&1L$?k_4JT=R-Boe2ft-`P<>*qz?A0F?RaCUy3|ivw`nA6k{gM>4fl&niey~{ zd(H_Ydi8iDfDK1P9C57*ML@j61U4=9t1IKq?(s}=;be$tjs6Zm0-WIJpyvczqe4J zZf6B1Ut(Tga0r@r8i4YvIkz4gfN0KPWjJ@0;yF5-6ph9gqY;+JJ)V_(rHS{9g5H&1 zd98RXW!F$6$)bkRi1*4CzW!mx^DX+;f6BuX){Ad9^pm2h)YxYEv##4(^!uAg0<+7X zc2uC^Z+lF<%(?54O@`g02b~J?P1Lh8)-l5Ax_?YK%xC`YVfGI#Hlm7+zURRlZ!*cdKc|mf3K_z$SYdJ)MP>iCm*^=lGYVP=97k#Kt=JCe9a|`Y6=Noeffv$Mn*cBn?j*#hJb+ z{hB0*XANIWui=9+y?o%sIc&0uwLJC;oKTVToU6mN`Si1S!Trq{Ejkvl*Xtm2hB&9L zF&UXFVnV4YMi|*o8*jL0d*|kZ-+Q(6J|^o) zrZU-6hYsuM({Yw_8TUSCukuyNgwUZzJUdU`vyKS|i?h(>X*N=`>Hq$g=f^o4Bj_<4 z#2y6&y$5qYDb$a79Nk&-oIaEF(@ROB4l_yc6qD5NktFXu5@fVBQLHCaa4F%7Ps3C= zdC(i9S*u#W<7xc24q>c4KAxe)u?jkLIiSN$;asmaBAxTY;ua>;qAjyky-A^bI^o4(_3|#2fxdOfTx)8}t~)|5dQ#I`(q&kYESVJq zrwMulHl&WVf*e+|m)O%!t@vC3jL#zx`Z5isQ1;NqdCNQc7o@deC;XQvbZwf3xX2u& zvS)i-r$Tw$I0$hQBXQ?+8ro5({aB;EZA(nTf+BO z(Id{@g7|^tyzV+nRYShinIC|?)0nr*{Z>dr@_L;eW$O*j$=k`t>GTMvu6>w&y!%hM z$>C1L^2s3xXUXrh38haTkMqD*H>t{`f;!Kc&-*441tH{{YUjdbBY9GfVsY3IfC+yh zq3=b%vx(dj40e$rDfC~vK%Q$l^?AosdJd8MEAJ$chl^!S=>S}cibTw_G^jez2aUdR z@9x?p&@Kpd9z@d1o%znmIXHi+j@)})Am;o)OuiO{>LrPSjmh1V6CFW%_t14!=A%GIq*JS zS9*Uhl!H}*FuERfP-QBr&&!4WKm#dJxZM*%->FbaY!ATQ zz4UP#or(kGo67BQkr~r|%eY~I%nyyktvqtIE>^^sY$$iR`NN!L-k;QnfAcu6lk+;)lU!I!)|dJ*|9x;Y&IG2hN1MN|+C`$X3#1C`Ife*5 zQm3)jQ8fo{dQT}isZj0=WR1v`eVj*A(d|(V-mGsZH3$EZBJzy>J);rZCk@q?TCuOS ztJL88uQjD##&~jY+BC!mbG@XaU+2j}X*`|%{sW@$F)xdPkk}C z&`)p`bD4{IpL8S7>tw}(AQySXdcunmfq4Hl63+jm(l}%~=63SB}Df5%k62eOP~LU3p!eHAME_czNmJ(2KltW-fLzn{MiX zLb3D=#LWAVcuIaSX=yH^f?cKb>>_E)^V4)kBnB>`SHRv}9Qy7gLwXiSZRXlPnHt56 zUJG1va}ev_K;EkJ>h?%8@%kz9NkgugkSn3r2{X{;4N%j-!w zub*;qUm$y!cwIRD7$@bRR)&-8cwZn-j|L(lKN77uzSXHm9&@0RY+q0yD);`F!~5Bn zI2C%!2FW1Hy_(wKcH?Q=2jo|}BGT_{^Q9*+7Qg=ys9C-=0X!V^bX zB}H;!N-*?lJ@(w9zvKscd&IcP{MLmsa+wAp+~*d9f8fLiOY zPShqn=>NYYR#sX)5qc^d!?qj9<7ePc2^)GHPn0{2y)dSh7Dp=@(25#rW_hkJj>gLP zY2NH%(IQPl4I=p-zENjbdMsXguO}~dAsn^bm?yiHHTB;%eA<0LvZl}<&^-(VLkx(h zNlk#<+`MiH;xIu8*Nya4I+cjeg`PHa!z3yllwcNxrGK zH@V7ibe&2^auRN?1bxFH;gVB4!4E|Ox>P=&E$QKw`blbk8@~fIPUFEr$bDftj-Wxs|wj}oBhm5Gn{ZTQpDAWc_$LA_!jMm0}_zdieu z`1@{t7AM1=ctZ0}7|gkeNDU%~#WieS&p4^H#T)8~FwDQrwN(xJJ4M)#Vt+sa$*=TI z=jXeS53P^|T{{~hYRAgj=k)mUjKF}U?4{jKU$z2ri|W1NQAl>CT{vWFBK9B8z@{_2 zjyGc^_q`Vszr(TjFmshWGLYoN{-`AKn0haiIu-%Lzx0pu&A^mK=vjyyv$>#MzMt*=EDpReUa3lQAs`XI@((ibrRn(2qQGoc?89;5 z`I3HoO~cTbY)oO74D_8+40A@TY;WL+%-X!qH`2o^g`66B)v|8!vNDfr^0xE`Oh|-< z&z-|w8%F+&m-t9>ZRA+zyBd%>j``qydES1LcdO%#bT@v^3i>~+&t$JVeI!f9OPQtK z7{U8L@09_22eIZcnLOi2=8U}Z!pFy2G~n7<(#ePB*_fl4Am?6t)3-PbickZ#^FG;< zU5vl##>vmN%n=^L>*a4CYmk8k4fuSGjuW@N?4hG?MK$i1dK6{gW1K?0@egyT-+IEo zWCXso`X65P4fV5g%6MrO#{KDe@~wQXCppu{@P`fE=fujdsh)6h;n!WMgVoK%tcy0J zohHYs@xteh;TZXg=jU?8<$I9Xa(|-<(|!?edXn@H!;c+_c86z0mSU7`mDh zFy}peWBL0ACLWLlJyH!ovGOxy^vWW6Y!H_&lLRtZbRB!gF&NlFlSz!5sEh^Y=Xfex2j$WqU1rjwIs! z;tb3mXG4Qk`=so2Z%j#E1hbC3dEz~+-)cj7_FGRV=>^kt_Qg3F5PBs8vp9~q1;@!+ z^0_fSVW>2M{-Gt^g7&p9EHnFQ8k!GWsbG$|KA`>GuQ$z=HEqrA#~+(Fj#Z?l zSH7PT+~=OztA)PZICa~$v8+D_T}~2(Z@fI9*XA*Yc=`K>K^_h<%7i?6)skm_Lft=^ z++m&GCb7>kO7&_6={3S6>qaI@cIN}qw4p)1QE$#`pCp|)UVX@nmr_9ODg=w6|d#1E_rR! zJ}(4xP~yf!W>|!hIpnkTbD5Gg6mLwvtwO;DZ``TRoQ;Y6dosNQwyVhSDAD(V7Ybi7 zha;U?^fmchM|$IwFYDN!nbkg%`P7^v$bTxw03(Lj=OL5qJ|8 zj`QauFq-e*RUF0)l5q5CqlKPY#bs(bYaHqS;KZJYG%cFfCeN6|p3I6`Y?=@O)e`FQ z&9%%LjlkdT)LO3b*o|9d#HhRx5=w>08>Cw@;JJ$#z5 z4|J;$F4UIp45ok2ZTc|QXAa>idhb*>;wa}c3pJk+S6JKGNxo1=uf#f;7+ai)W3{s| zZwUQ%qRGEUWTL$y3lAP;V)_a4($qVq24pf1Gy``zE;grTcJ@yeMx4*Ywk=uMJBmI& ze9lHk(yO2;GpoyzmE<_K?*=`psq^=3nT513?8|7voNE4DJ=Z$b=VxP~ne}Ye!XNNe z_M(^Eoz+O{wDlC*W>0Z==OyLlHI!BKR(v=_C2`d~<$=4mI5zNJfDB23e?42OX7-EyYo;KM$fs9s-5?Dm@~2n zkUbo(p}$!mZU>QF{H#G@ELo@_!SLA|f`6!yn7xCcoE(V37lW{JIr&BZVBAR!#`|{~ zGT%XXdY=2g-}H*}<=3e>4H*y&$1&WK`wqasO2Ig-)u77kAl&F54C8Fp+tooR=*r$l zezxo9Kn$S%u;yzpT&J>Ub~?EyYT&&tvVZV8`KOuDFf5Kj&&7H?urc@cb`<7QYx(98 zjmQvY8nAzF!AE)m^dO&DL603H^ypS28vXn0aV<3(tLt+A%vwlv7CFXeQ8;j)-gJK4 zn^$EGULpeD;BjOT#~PSs!R=LDS@PbZljT zV|Uh4zNW!h!`uW{{<|r2C#G94JKchDr7dXtFb%)S2rR3bj=!nfkG-FUO<`%w^Ja}9 zkUZ6C3+5^;P@cEoLlgQ-tmpSgI;tt?y|dT?EKkF#GU>S4n*ZO7dDTT0d@h#`rz%zy zIa;Y*Fz0qAGie=j@un?37u&P$|1%dO`}5ze@^IlOGp-7Av94_%iU*R5s%k}_DfEe$ zMlZR8+=o-^3dx|(lWfIZ9s2{PGG}QRYvNt_*-fli!oA-%pFHe*$?qL%MJC^0KbyHJ zW32e|iFz16yFb~h_&8q)Y|UQ2jt%A487JxC!`$aeO=No~Z>enWEk`!Ao zwJo{C+VnkL)=0um`bzJ;Zt~%(Cws0{vZ=JUc=qy?e@`l<4msf8$Gl`}inn;>(U;NJ zM}l?k^4io$`k(TWH(%W(!LgCNa%d<{yWHg`nacA&J!Matr;OXlEXCh;X!zu}e5t6w z#977iJirbgKGE#j5XR9fD8Jm#hm`xrrRF5CCqF|k& zN4a)-s1xbQXwp+xV*mFsJw_g)r&dE|nRTT;@_^6Zh$z$ypvUQRX2AbVCNhn@1+}hI z_IeEDb5z_>j{$uCa_>YzrDV^%AL~f@Q8>|@d2w_3o<6KivQFCRPZVn}Y1mxKg2s*L zn@G*1QAZ2Bs6pY&?UZh(%+O^M}9pEN?c_7wI0s!F*nhr^%nI2IpX+33LUMr%R@5MmnAI&08#Y;CT)?{Nw_Ma_ zrkr18GQ@q!0wpmwBPEwTtK^FLeNSGpFO)U9QKPKf_w$+gNKUx971>5B8c^f)A7{l* zYYyD`49>kupH+U=u;saU+LD~ijtk~Ky8S6PdOc2=5KuF9^wgK;OS$D!t4@B@u5G(K z^Q{#+bN{r?Z!D%IN^`FbR!WywwLH22Dz4-bD~Zdqr!`NgBc_F;PWRKFVu=4TJroVmC1in+c2 zUUT?sm3igbShMSuz9~o8k22HFC}ZeHf1bT6ovN^|SI;OT*-uwgoG9aR;$_&BM7iy0 zloNC5k@2@drteOYmiyx6NP4`)@ckLguE@+Z$<{sxWixwRX1FIx$V>8yiShEvKT&eL z*-IHi??&cH7k6OK3wx4u^o1;IHb|YMIB~s@ApPj$UDPQ_hFv9}I9Q1jTpM1=@kXP@ zN^H5WqPG_Fr`xMAg?xdJ9W%~4d&8gX!`O5$^y;NV@=x|waZPzQ&>J4JnG?5*zKpE9 z{e8(3XA`{fG29zD551A5Q^LLxb%amcE0{ddE`c5zcI0mgRY*%xLRE<#{xiH$ae)uk zo$$q4XV!emYf+^){TAur|9q(y+WA`iOpU;#2-c@sN1$~Ed#miYetgd!I_~eC&uQ`Z zYYRwc;8I%bCD-FnAsl+HJB#dfm>Czr-&Y6y6)j48(3|lY^8nZf z^J8x~Vz~yLv5PgY&)i$HR(Y3u-Otnl7PesB^l2hC3^u}(Y~%E629)AnH0K`!YP?|P zG}n*i$OkoHUCMtAwX+S(k>*;jQ3E6D=?&=a$3MFoaq$rMqcGtg>H?NMXGgnD=;@;Z?%Oy_!V z2zyeJGcn24)MmO5Bd5rqfq4}@ z`8@+zyKBqrjZO69&nKh9I+`anyHl)pqDvN1`Tu#@TqEw!L`EF7v!z+6bSVq}p3Q>Y zqW|R?OPW=Z{?t)+{Od24pr+E%$5Y-;Z6qtnt$(2xud}@Zr`Fmb`lbR~`EQ?cAvk(2 z7%}v3+Bz}>#o_eUyUyI;wb4KVS?|ZJEo_QL^-^TNa>%H0{PD<4$DB%M(TC&F?fMox zX3s*m=T;Q3mLE7H5B`JbdtkM~Og3cGmqy~3+d|eIqqp~AAGt<8#MZHi)ELLC>vsx_ z+^@ic$IK1QwaLc?3S8xU683;z7$=y!!{howKkP-zHO%Uy*FwE5C~+(rt#;`V97-mw zEc2!(S}^_uGtB-?N2T8uOrMaBHT0Ky8JmY5$8*szn7kgxAN$Q@t~o|^%IhHSlYQm( zEqW<$Yb4z^vMv(tCp|uK{!38cS${jsa3W*5(;tpmU4{6X$E_F|C2NfWF>d zJWo@$Fw2@AgeS?x4@jqdJfr?@l*_B}2Bl}Q~ylFG85%->AMtI3Bc;*mIzBwA+QR$cvcovZ}$vu#> zT+KDx39|)BTC%1mt$6Ck4DLGglB#QkGuK-_>|0tm%}s*dsO0<|cc~ssma(vjxYSjk zOLnpBHYpJIojznmHgW7ghHzUjt|bQH$>m@ie-(_BI1L7KE&cc*Ye~iI+j+(L_bv0% z(&>B5Idlx?KeyUvp@_C%vx|kdb~^f#Q;EKshgx=dIPf|bUM^P5{@aSHjp@A=;wATY zH`~dr9={)OozJz!suf(P_adLt zGX&H1^p7mH1(Cn>$YHIo)JHwG6)+=iFg?@$wZO{tXv`qa!*eWXy~2VE3+X$~W3l5} zu}iHyw6e2eR68q~1+x8L4YKs7QSO{&U+cod;@T!r^kNk4FBLT!CHm3l?;Bt5G(MQ` z>Uohu_&3dyFjjHyz%*(ZX>&dANKdW}P8daM}pvX%qPs`oaFn!tD$6*V~$f zHfvbR|Hhnv7TI`5FR9EO>_?^NUv28hjmS3c<-dC=k4W3?Cgy}4kr~k@`E}1Es_zE* zPLJOjiAv1>L{25o2Zj=ViiQ!R+

53LT%t#X`a*-QHQ1DQDLv28vpkyBqqzd$d{+(TyWlolWJwWz&{OiHR2 zo)+@)kLme$$p{~wpFj_CpW!?|WGk0;BmZgS`Qbi1U`iG~PbSO#j=42tx?N`|)NTK= zQ?GeXkB9Z-JWnaq^<3=Kix4L%Cya8i-a+vmlPD(o9^~F3KjT7w$j|h)qP`Nj!k3(+ z5A}N`Ht*s*H%N<4WjKe;)1mVSEmo;`j>;LacbgHDzA)?IF?%jKzqHuJyolFX2+SaZ zF@?U2&g9r*=|6EH10Tr9^m#xZ#52rT>Y-3yWi4paCWU&&4dyM;7rONk`ahFHow+4R zGO|rl`nC#AGgVmghyKamsre{XxE<~bUwR?O=1?=9q{A=How0f?@=I_oJx71E4eY_J z%Q+3q2j{VEre1q5HJjdSWEwdyEp5ZxYo4F!v+1dMo%{vsJYP35%V)7d{h+5py&{cu z5ccgJdYmLxxE`wb@rXFhG|KS#Nz%@d=Y`j6+)!VPxU9tS(Z1NZTZMYdnbp~Zy$EDw zY#nqM)Iy7xC>@^cHsL`b=h9Q`GrdheGGA&m3Cz|gNqw4+|C_p#biOg594{_J-u&hGnu$tDWk}wZBRFn3HOxJ{H0RH#ukaoFa?IG$amY> zWTe_2A&2eI?WP88=5o)`hWi6^2zDj1{y&j>lsWWcToMh(=h0Znu`%|D9#6Q=-yBG< zKbr-|?b0zz$F(?ly=PA3^4Y61dm&l#9rQpPlZWOZd6-y~i(`ZRr8)WcZSOfIlaX69 z&{q;;Jfut=JM7Wg<4c8-I6qr~aH9g1TH3+4p9bHnhCo+egTh*z$EFOxp+GX{59kX! zfEmwE*=IF{eO6nU+wc!x$GA84NymX^=~(s5f=3o<6rYFa%Je<{$Z_xq zJ#ko%ezw#{dIh(Xq)shm`!sJU#Xh=s5zWNw)_;t-9fq|dLs-!c(-#*?rylm`!nwS9 zGW)-V4?y)0dNW=Qfn$>a*vuub3=kZO+7apZjp)IP`~^T{Fm+yZ<34M+U5a20cm=6zX=B4$Afq z2KmI^uj(*K$pc35-EERnV|;+eO8mahKMOdIUG}9XEBmob9B&?I;l;Yi!3$cf^w6QW zmX7`EMhvEQYv5cuslE}R)PaxOH6Wb~+Ta%K3E-TyYj748a@~AyCpF!xtl2!_G5jW5 zd7CUX$Hn7+v5v|9ghli@e!cCWJU?raylX~jRsW#ajrT=dLlr)4^+j8b(^opG5U8Y| z?)}9$_n00lb?7;GMvL~{n5A5idCw0y9;X{o-p5F0*+4%UBNDi;IDR$@>7U4aa&BM4 zIsV>I&S7`i<3w-TEtl!%vV>kZ~(V^v2@_KW0h`+%(Ka<{v)l8VkT3^l} zBhIX5UePR$(bSgz*}4(-S#|_TgL+LaveH^&&EsIlGKf zYE--oox{XoioWQ+pWec&wfNVGo}SSW ztiS8fW0($YH=9`ZFrw)v1E!2*eJYPy{CFdx=44~_V`g$I=?7Ai>}fnb1PocoCQrG) z8#%^~3iYp63iW-?VL@Db=(;D$=f&J}k2xq(a8Ul*OFyMcM)_WiEN)vBLYH&D>q8EI zJu|WT_@Kx~hmG9Jmf-bzQALOMlXdvgo*7i$CggIj*T~<5u{-D+`ON@js0m3LW|MDY zO|}l#WGCqHv^*1^`}3H}GMk+1opsOXtI58F4o4MgP5l4zj4#X{(y2CcQbL0;uM(fr zvuOx!X2t%xb)@gtA{lqIKYCw@LguS9`ZVRDdm|^w2q=^@1^v+3NsqUNRD7RBU%#F1 zvY$R>3z%=)$CrAOhGWlcE3S8Qm3QRbIwc3<26bb@KJGExm~l@oZv?YjA~y$N%+n~G z8N@v0Usim);V2ht6-fBz0QRZqk+qf_;sR=|^_-+><$SrYy&t?kZN{Wy>^HiegOXmIneK zl8d>PhH_lXtMZ*?iN6B%3jd5J~1%eL27)mXD&DAuNrKaVicNN3cBH4DKKYBi4 zp6o^PswZ+V(~kaAM-qi zF1KLAxm-kqk~`y`$md6Y%-hRcV;wceJGmG+*+rb0Gh6d-9#4H{%~(^(gs``Nyob#E zPCq;T+_i_PY0gQ*@;c0|E@~j>9ExOMBj!_iGq0w<1qXQ^9`tdOBYlfSM?P-o1lAOI zetJ%z9=NT6R9%)Yr+P4dX8`wA*=ewUnTzPwE;5_`j0c!UJhmhI4$E7Rsm*1*u%75b z3q)5p2y<$(r#yu@%Tsd@aokycJuVQ}s37#2$NENyg*kQXL1d=U$2Eo0pFQubIp3X3 zPDO>oIat!LzC3-9FC!ZS(4!;@ky$+d4m_Xt9mQpGft*$J$B<^^<5O}wsS7Y5}g9Udsk~{Wxk@#`+(_9^dOkUqI z?@}>)S}xqCG!XyG#bO`I^UyO2KY0I?Qj%BQQBPXz%9o#a1JQ) z$m5rItPMbobowwxk%v{#2eX8e1U@Q|FE@e^{ukFd=hG09Y{l5EUh?;?Uvj8xAZC3h zcSf#x+l^d==eWq8y9JWpf?9cF@`L*=^n2uWAvYKKpipYtm?W6)o2=9@=bd}!)m5l%x3yxir?Y&Y!0ZU-Dc2~7#01uajBm-M{&AA` zEo@SfTx82@QP|_22HTt*q;z$ZRObSj#{BUkubFAYUi}K=b5MVF14%qpB&&0Rkk0Y# z^V2j;WUVIPWqsN7^^bH=1)=gXa)qbU5ZQt{a&M)i(l0etOP`WKdR#e`hGEp4eL@<@ z?#hMo?>zRW^om9d^Td0P%O#J*+`41`<+*F{{<EEg|QU1cz9B4ZwFpngmr zQbQW{kH|$I@~1)Zza^n-Ft%OiIK%b0BGL+dwuhKQcs?ulN9Day_(R@s;~Xn|+wy*+ zMsurIAaYleBc99OD<=ohX)dy6(I2_DH4r5`aV%k+K&JA(D$Voht>*K-g8XcDeOc*H zEQeW_In{*q4D#9sBXV)IR|AP@QXuO+0#J>gAJ1{`#vv=d{p~8x%N0wR3LLk8)BiM+ zymo6VUcp_0$0=~$f&LP&qtI`08oF?tjLMFa>kmDU+n7D;V!#`&Q(i8i4_zhlM4P?v zHgFM6oH0UIhy57KY*h+o?> z;pM{h#F;o5OAc|kB^=#0(l@OfdB*29ytTy3fp_$0vXPHFMZdg(%oTlU!~N#5^4A?D zZdM9s{vCOo>C{el*-$v|fDEM%WA!78z-(d+t)GdYOdG<7#L8BXI}4$g67^m;@{E&8 zE7a^Nk}2!S_hr#vvKxJlu4kea=kYa~{qpjJCw-$La4XXQ|B;!nY@|<|bDY>+^v12n zVR(Oz++|t%^i|sI9+duXCuh*sk2J@)cHqjvoG9-5{w zhq`0Dj3tlLg73d$&+MO6`oxiU+sQnqyQ94^*C8C+2a$W|KyI-&*Mhcv@|wO^dve0j zw7db!cs{?j<{D!i`!T2sWH|A*~5O|P3cVhD zW3T+R(Hm>xxaQ&cxuvEr(`g$v)91^RdA>g_VQ9CXdBi*qr{n1>7r0MC4PMl(!{KV8 zpVZ?FJUwT_xAa)~aM%lf=7nQA*N+PhWoz9=TqeKQ?UghWH#7W<-%#TuXtxOH2%Wt0lvgD*b#>;$_7uxTNV8154 zr}}5&KtJjN)#Ajvv?u3>aD>!IL>jrOp5>T%@o2wf?BRJB%3NA%^M8%bfFh826aH~> zdY3m&c498=#Y8*=wfULMN%uC$`bXpzYtt*C3;D_u8Q40I>;8HNq{MtL_{1-SUj*}@ zxo7$5&wYwtoFupY?|zQJg~s&X{6P+Jm<=Ny#!I5X19xsmU}-*c#;<0g^jsUP1u1fH$rd2X74HciO+hQ~^p!ULU(BJgMhx!UI$ zSpLI?cI1C=Z}CLMaf@)Q7wZ>W={s3yL+6|XDRa^r?iClo(2ie!P5*>k8|tuL^?fCM z8^ms!*3To2TSM_f#Q| z{DL{-W%tQ0@;Ax-UfFSOW&lp&#PYV)&e;zke$) z%<3GD_zld>;@8cIUl7XXJ6zV44@p6teuD}=cZDc(r_;m(u z@%S%{PLPymp6GKrj9yFJ!v$wx=qMY4nD=c*e((u7)`2S%vFiwP+xhv8N5{)_@~VT5 zMquX=>Tv&Npw-o4_B6&zRz2n{FVe!+n)R728TjR@PqcE&3$35Y99BUf3arM%7#BnDy|)eKuCX#`7JI|` zL?HFH0Tu3Lz_T%V;f=AP9qfhaY8_@T;dsUSJj2BCs$jotbnvD>j}|q9$diVUPvRcV z&uhOtyz0*WNan7cNQC}d1}2bO9Cd|0EHAwkxt+S&!S;uJ=eL)R3(fCtelRnw!@T*#i*^-4j-GM&Jhshl`s?&&O}b`@ z1Uarul+yn6Vhl)lNzEKHDPMF+%>_f{A8cxHnpilTI)v>(UJbB>1_=95LFU!&?l zf|U3X&y0sSITMg5<=9()teBi+g(O+kDqe1WAQ$PIDB<}=iR0&HG(9Yf>FG0Tt3e{E zKNx!_Nxyjs(&C*#s&Fi7_DG3ELwt~C$DE_dDsUI-2eGNPt{MHhYBOmX*2bPs#+YQ zM`OR%E36IDgN8kvRt3ZqI&$ECbH-`}&Px zPp;005$6n0tY9B%H6!l2u`aEmXMmdlhsZd-AN@c1UU6s1N`B>M9X8EsVv(?f&nkvCjpbm6>GaRW1* zBFTf_XYN&(44hJ&GimJfy>o0_nD0ftS>JW)|474@-eVGw3JRLV+gik6aXAB+Ww< z7(IhABD-*S@kpN~l56`=&3y$88`zaJa|* zEx}M}_^QG@#HN9$`$YqffFNvM6#~Cc%)gD~p_dLl7g-ly_JDoCJ;_rguy2^PkcMaIk93gSV`w^> zEK9@rJFG*Pm<4f*pEZE&!87_O=~+)In}?~a(G1^6-QSb?TshX#9j$n@){2{~Db;9B zjjtYk8+EL=v!=XxWiGP)m_KdHLGgO-cd6;ErVh2bBQpv&SYdOdwnd%hELnk&s?5Um zv0@AN;||rV_#8l9OPPm?_4BYWoE{er^lU0gUx#D4XyD5l2=cIdv$w=`U~gN3N>-2o zejCQ;=eoBHobDvn(H^pSwU>NaO+Tk++}AE?EXO9hNsBS=GO%17Y3JZ6Q`49k-AE+| zCc29sH9Xe`4W+o0pG;ipB4q;|#lB@jDP7Z5q$~5KqgA5)%SUpUXC10l$+s{s`8Sza zla2gkZ4*D4mBr6t&))GM>HJfaIYm;DiKC`V9>>pw-ShR-Pjs`czGo!>l816|y zxXeDxY&Ch0pM3s4@;T85G5bk_j@y`bGn1KFjYHt!&*v~X7ku%q+?E^dudx$7^jgMnBi%-dgItU zo!&2e-nRdwPDgFBEuXjV(PRu~rDNg@3$|BE$9|V|vLqH9+R0p#@HBkOXTC$a1^$Wb zBd&ZF>sMRwdO#YIhgwkQEbE0@dY_Kxvq>EzjQ^*;o5mhk))iIk-ygz^yno3N9pJMR z$!BO4Sw}u+q2z>*yd_V3j-IL)EQonc&zXF($o1%#NK7C9-kWFNLO;L_DHr7Tx z%Fv6Hb--Y1UNJja-};e@**C24+Rltdj~r6%}1 z7b{QXBJNBse2$V|9B+loKUS>YO@4STS;jrgww}!Ac>sM%no^7OBG2;aKDLuc|HILk=PB~t|V!qINOZ!>*uI8Cn8m5*QaNS&Qr>gySlfJ#_=*D(KvMZT` zeDlnqt$kB1|2mo-YTYoOu4&(XcE!KVqo_{R zl9|!I^FmIPH|}3kqLzj=zEE-^1p;dNpq1KCEtt7B^l* z;BDUsGzldi`IG)CeDzf5aNfoo>XpnWX{p7tAIzFKtA#!HI7cVa3uXj!K9}>oCCCK* zOoVMR^Pb;vEyy~Po|?)&t^qI4GNOJH1Cp*8kg~~yDU0dLScQJx+*?*KQ1{{*Z~I#M zE1oexRo;XN+ymF<*W4zu7w`+$o2`xbc+r4>^+pUEM%|(g*M`(_-aD{YMoZ3-YtAx1 z3@FR`WCY(o%3#8^czQhsWaAgtY&~{zy>>4XtEOjS&;+j8&a>ZTHS3duGg03?3!{#( z2KJVo-9|DT+*_8eNY1f6dqY|Cy)h{hi@25?=fzCf5@du9vv-#J=Ue>$rGA-+b;w3X zuK#W|&%(pS%%!fHg;q-HP8Mp5Ls*k#ZFYTf7QlMsfBU!pUQg{jWKR(1m+AD>?x7<0 zt`h$Pp0d+Jfrk%SA2HgYx~2r0^dkdC{wveKvAT$Uh*28)8-!rQFAWOTX<$!HIQl8a z!K=}Doxy&KylBi?7mbS7=>yC0t((?D-)#%}e^190e`aRV(<*3RE?O+IB8=mQ%M;G+ z@yzXnpOo-wB2y!LCHJbIIBa58W&=MdwU50183jHzvqMSh!T+r#jm*HFdpii*4lx(A z30d|)4OXuX!NJ|ZFf5HGOGxJ7F#QL|(aY(tEojIwJ$11K_D$(G$g%Hp4{~UQWGs^{ z$oNd}0**V6{5kK(z~zy~_@Nrt?@%*r9hvUa!#_lt`dgamWCKHVVO=3n8e; zdCZ=#{y(A+MUJOkbTs=T$?m_QXVYN%ZLPH+cr1JP3I@FB?b(*Oro3L`Yx5YwqH&eX&ZnvD#ksNthsjyqq&HgHF3yz;)6ru$*Of~- zPkNE(;TkR9^8@N=xTfouhX{HzUOttF4tKp}LfPgLX!eoe_gY9z_K&o;c}d5br=SGQgOp;gh z>Rq`hNnXr0N{!(OQa;KDrQLk7_`V8b(tWV&tqRj~l=z^~!ihBjpHQ+O2|AR64vABA zm@&$TWw(szIM|4}9M`_JHDY87=HAa`A3OOE1O1!aZe`)s4EncL&%)IOE;G_g~k9&C_j9}}fGElHaFW>#jGBx(N6BweF@a9QIE+jSq9zp0>F>_fK5 z2U!{&rp?o0*`NsgY@|c~$;_e*;`p1*{WZtFN#p59OE$cW&43lX=;Oq3C;J9_e9vX0 z+JkJgo==W?8vSOq3iZFs6zVQb?bIXhku%_*J0J3E8lyxzn5d;BNuS9^G0!(j=^%r2 ztww$@i&+yk6?TqQq1j&gBetgp*Fw%M-t2AUIKSyCvm!V@jHgy#>KOUTXB@{r7|4bh zF}pg)-j3u9j*|Zlqo3_fj+c(vC`aDmE%Qxpj8UlH&||C0UWIyi5`71q?bME03Uzu7 zvLH`P^1a9?R)3QmrQcS|X9lV6sX}(R3JsmfI9&3ee+siCvX(qgRaYh9S0&C(Q>b5jH)7KqdPh?CIAWmAP&*41 zdG9RX+>yLK3+^Mb5ud404_aZTzR7EKlz*Q=|HxYj3Ux#FU#!_e{?%|$@}DG0nV3T| z_2xm*y;mY#--zC@^wsR#2%6?x6EyI_p%FS^sazq)__iHlGl)A?uer?ZkYL`%`KX@tBg_n6evGm$v{mXRL zL*hpHiE2UiEi^#JuTwTqh@4;C_aC;P3Pk zzr{7~6)Ud%Wbd4g8F|;)6UTkq0rG>V^XL;fUnz>V{!)Ffj})dTuzIf@3ai;eQA&Y? zm3Al|WRt7MLU5+@0Q7he1P?N4XIh3pTP+0rr}22+(#Po(xo++q`Zv{M<9hZ8Y~p(T z6!#2yoJUWjV_!0}g11_5lXK^Q#a0B;e{kgb57@=|HJW4eH+nIua=BOC)>snG_{sd4 ze$w-YN>Vs~Mh#NH|6P$Jne6ePwgNY1(?4=MvnL8Q`0)98^Z_fDuKj?@ zR?es6eWX^3uiP)~DaTDsr1Cp&i73I|K592by%jj}LV*USi=^p!dujxBxEMy3k#p(w zLe5>uAt*a_0F>DpjCG5~NRG!j1390s?vWJkMJ1x7PdbH*2{>CJEureO>1| z=lssz3g)b7AbLCq#4$hq{93#w9hmd>(WAvKJpya!p*q0YOKr|? z{I;NoIpKftJ}=yYrL1W@J;~gTXN}Nka#ZK7$l%#5#26=~h8~iSPZGqxyh#Qn9+bE2 z)jVFpoS-B%-fwupsj(*(1$n~aN1c{WI+QKPGr8Yl>UKn+Rx@hncHo*{WI|pgGqo() z1KdaLLDp-BE-+KunzhYStexJ?K;^vl1R3W`9PDrW3w z9K9HBgq3kDp&MDtBPI-Cyjs;f3q#vxVy9Oo6r7{4mq!l%5PN~1^sT#1{mQ9!8g&@= zX2y%L#spb&I9_zI2c=7_L8j>vrBs&$8O#2}lVd8pHmgy=o3Zo2P)jdm7#8saeL1UCi$)E@gZ_OrNILWKUc1 ze%_XehhH+Gr{4bi1(|4`OHEA!<2yOV;9!MjGx^*n)Qe0Yqx-x6|Hm`>T&^XvRu{@r zC+dH3KDPch)_Rs^qhIC5@_QV0$_Dr&upRa6o}^%uQw~nfb(8hC*Ba12XMQ$p+w03@@;Hr0 zQ?dMFBuacuMW@x|Xo~8}{E5Xft`E7J?opU9ITZtHQGc+ho0Q<=>(!z^N>CJ5c231^ zSP}8gS+3v8lczoW(PDZOf@0`joS%&@b85-@)zlo|-2b~yQE2@x1t*I*v%1SgW}GRO z-Q>S+4v(fc2mOA|Sdmbm6xRfDQvT$yg2|nc>zop6#g+tj@u~SoQtxpVYDXmg2~WZD znpSM+dWAd`SOK6 zwqMHW@w_JImk-e=x~_|~^Zz4_s0a6OWEArT3;u3OZR2@r8OoY1vsXCu)8mdy8rrd5 z-RhpR47vSB&ir9c=b*=o&=hq4n2l>{XKA`GU(`xJq&<$pkM^8-F8T;fbR!x4f;tWj zeNo2{g=_6upJ%S!xVBOb*DREME0{kY<@w@CDozwwG3q`!&3Q#K|Gh8%sU3x*nPlD> z2YTLYBBhdxWED9n(?#;Cc^1Ug%E8_Nj#9(3K&)p2v132`231oLqO?L0Qb#mxi=<}T z09ZOiK@O#$j63V_DUBqT{=Xv|`r+`0D45AZm17O@J=D^&pipYB^+$&R%(<#?o{n7M zC-$vYarXYgZ1TCAqtPjW+*S=K&DQ*Z7N z@57{w6h!s3BJ4&(sY>7EzB)fRI&X$k)(C?#kSc|==41Wl{u?jTU}r7<`$6|CXYFu_f-sa469|M?nYNBX!?h~=Yjb0 zBnoR8Q|q0z!fRbaNysP?bp-V;UXfe;l7c?T*;p1|PnK*ckkee(b#gaj@(S{6&B+(1 zxXH?ktj{}9U$RFO9N(s(bVxRyY<7|y`j-vo{r0X^6#TuYqsQyxKfqZ6>3ue6nlBPs zvfgn#1)igWr|-%Fh1q-pF$j=jZQ@w8GZKQF^Z|mZUnqP;xzXFQzYfMm8$! zXe`-nsA2HQA6ptnVc+T$6lG;&_}d0D=175*t?7>j{JC2;r;`28#^5iUN%1U_s}bag zS=YAfN)L`iD~@Nl%Z719Vo3Fc!vykl6D>fw986Akl^)ZJq;>=H)J@2ZHfK$`d^VoV zca-}vHksw_kKU8GzdcOBq@UUJ_oydBHj9R3qo;KRFt)FUSSopx$Djn^+IzNmcqpZ!X7qNd-M8(yVAO z)=5^(vB{?30F<~Ih22xQ?=9eZzvv>~zl!DW=YCic!F*s|3WmJS#>cvi<=Vr1X_xDd zDcm=D=BFUDi4~PMILT?pVyXGb4-0ovdt@;AKjst9-Tuiymwe{zu!>QrhJ$jiJ8kQF5{eB9XZ}6(xAxW~x8z-?VJg|!TUy;?Q z>$fQ#KT?XR-5D?I$t4}U7LFq$47j-?9mBrZpgKsMfYM5gR#I1qyj8Du8OT3ogPkc} zI=xmRe^VIBttBt>ki6b<8;Tyq$Vl>NEvZ*nvAU6ZM(J3+g8tEE;$^5kHKBUw@O^_3 zb=){hH`>N}W4sjB=lp+a80>@TmssSB{ZQaF|kmsrqEAP6Kmuwb}HH(bc z$?NvKB+mv5$Zt|_uJCC%e2Ws`RE8YWL;B46CrITD?uf2NJ-#Ti41+S@z})C4CzTf+1K&XIK~}s8inCacj~)s zc!0F6^qao5Pab|y!lxm9ll?jWeG`ag9f_t(J0S*>(*tD(@m-B0A2EL-!6S+JGhXirH=Yd_Ex2#z}j#WV| zC-QW06**_ZvzOESF!Wnu!1`$Z+%ELneH$kiFSw&PN{iDm)P?j(=b6KXGvNvHiuYR& z`j5~1%Y?r3$dk6G|17Wb_9727<^AUCXv7#D{lr@+G@j(7l%=SzSBgHNSLpjZBNNLf z*)aA(g4A{Lz_IPr%$jb1`=xYLT16k{c?aa(d@?jU!*T100Y`bAGglNNhdx{H={Nn@ z5X!k410tGGFYg6?gm+S>^0yj22a|(i{eRpN>eDfYsZ%>%u02y?!d@-fjApN46uDh1 z*F_?~&mPOc@8S3sXheSX4D@&BnfX<${G6`h8C!>o9Sm4Eh5DYnKlh)Gl{(bZTnj=bF(ns9 zf8OTPl}Ip`XC0+b|uCXOSm870*7J67HYL{e{v8 zd}aokF~4}$B9^(RJKo!cqhBNTWhSKKZ4=H>{f?Cbylz(}P%~|x0Xve?akeej9e-}} zZ592H$n7p>|A+kD=X@J_%}fwIea4@xr#Eb4Bl@38$L?;-5$MC#b0T|SYHDI+8Zc}c z^Fh`MHP>V1!Xyd&v!S?OtQ=oSJ<8HL@*?zB2$Q|$mG1w1CrObT99mO>YIH3$&pS@y0%GEHRY3> z<|vcrZd{NuteG}BxnZy5i=E4*s56@-D}tA$e0lOS`SG3&Nh9qBr(7I(A$h~hnaOuI z$4ZGs^c1`qD@ibC*rk2UO*Oi(M{S~a)Z{8;60It@KlH$w%Ur)?94#%CXcMhO zqX{bXXs)8pA8S8@`P^e_(-Sx%XvnN8>@8aW=Bn(QuKaq z!To!|agh4LW1sAIJlepZJIlXPgkdH@+mL@GmWTyf;A`B z;=Vev*3{I9;cl#fJvYL=qv3z%Ia-X!K>4v`8EcSLXI&#Ui{63zsGrDQ@((|9i4LsI zvu>xmn~p~>(-AU^yd(d9HJBcOx3duai#4JO>^+lbJi+sbS3GO_`P6V2!P?rR4BQ`+ z!CqQAy2NB)G@l#yj+#BqGEkNMkun>&&!us0Har7&lQK~Ej*IB;ImwSNu3|0YD#KU0 zN#21blF_J<^kiT5YK&SQ{PdQ&SJcvgjNBnP8WI5rm5`S;4FzBT}5+EB?*JvrQSUk8C6Fq?>;!lGkWA+iB-#4 z7YF&Z-9;+pJIm(CB3VO^TBBQ`oS`nk@Q`BJZzz;@T?(X6WBTT#70RAlHreY{B(}K< z6k3bqpGE9NC~Y!vK%unKu^+IZP}<}cigtnm_dh6bxV$|=J}I#6G3yHS*s!G1r-J%( zBO(?5ovAS84D-%kHmN*90sXf^3Gq^(^qT_doKPfNE(IWOus=pJKPf&>K5;y2!Ulgd z=^BWLqXCHP?~nIc0VrKJ2-UUzD0?LkZ6C7Vxh?>Q9+Q8h4t~h10Muc9X!XqieNq_81qD~$A7-w6MZ~WxTdCUM9 zILo$AP3^W2dX1bUd*~aDi-XA-DyStlPmf>6qTrB8Kk2biP%*D>yOTL2^R|ktjWjew z!}CKlCasP}ZT=~`7KP)7sU6pbeB!Za+-5#r4fL+c(PL~A=6a9xIJlRyf3KN$vuE>t zD4$cCen}tc$J?Dcb6+E|ZF(y1>?8Z6BU|`4X9Vk8uwt|YONORmeFY1()>83r9ri7L zrg9dBnoA=r_{u(pIW+|r@>4NA%Ys!g7JRS3{y6(BD?U+Uj(y+{tf6=QmJLYa*&Gai^&8%Jx_GVsKVBu>X{=gYx>IlTSrJ;KN92mY?acuy5B6q2w$o_hZ zU1XsW=;aY(rS36v#mK8&PSh4Xr*{ne7E7~~kdLS32s^lWji+%8s^r|*c zd#M_k$mu!Qv4LJ;Q?2OV&x$>)DQvl5#r%8pHrPcy$FVt>$J%~l{@mn|IXK!i2cgc? zbUf=O$A`H~-c+*#&P?;^Bbz7)2zM>5yU&pG5PjMTUA<~--pLdmaX z2mA8meA^dG^l6*etuL0h3I%6j6zH(Y4(@jq@LI1xzdzJ2YLh4WM$|Q}Xp^(;xW-!2 z6NAr9=4|c+YEbpz_h!^5AK8zdp9u=sA0vZ&%_bEdDA4nu0&DqCY^egk!qnB?K z`|<3T?TNyucGTM7bL;w%0nQ`GxQrU8>@)7QM8S*eZp5!>{MDA6%5&!YW%QVMjWv_y z>_K*9Pn2tGq#I{fE9h})Ai2imC^TIfg<2`pgd~TU*ns`E{4~s8U_oXF3)1GZCee=b z&2=rvi{jk-u2lMHTJU@bXOex%D(f zaUQljHC*_5e~nJVdnMV%0T${yat(h=)jrh8KIOmAPj2bFFOsI~SIAIoKU-#f$n@tg6n}pJ+vaFV_;+)`LA($RsOnb>M4! zwBpiKYB}<~e7%{`Az-s2<^!dOq2wl^_mUgBHBb3E&YbMjvs?0`1@6hG z7tBts!L^&myc=i$|o-+kZEL1)n?SAO_7xpVtEDK#d2 zOty?Kl`^V1=YygXP0$S+E~R2pZNu4Eoh)-j87 zhCv2s4bpXQf|#cpr2O4D>CIVJyN|Jwc+4OzwkZ*7@WAnr*8l`J-Duf!`MlF1J#_QfdOCOCeG!53$ z8%hVuSuIvZ=ul&m7RL&-_^sqwbNqj2K+e3((4j{Y9qO#qqTj#aXy29dGv1t6OxNK{ zNqSm$3d7LP;b`?M9Org%Mp(yuMMux+_S8y@CjY~FPT6woJ#98(?KJ~3qsZipFyYY` z)`ggJW_eP(it{PGa;P)LTGXQ)o-G57a9U+XZ!L37o-v;C8otus|tmia~qj&XRnF!yXfdOALAScuRFV9#q z%t^=yN*ejLlmXqEQP0j(e!ni35j<->NGpLq<`NkBnS1_=BAG!x@Aa?%OjyD5 z(ruL<8R#bI2Nm{NcRG7y4rIJx%VEhIQPFAC^tSu~=&Uz2Z6L1{syZJaUb~bt5myJ?10z zPP@zWhArjR-`=vblS+!c?Qyx49hPYAF_&kU;s*BEI^8B|C414py|Jx`$-mqR0bZFN7S?|c}R)!j8B`Vdt&<_YW*GZ#IAdu@UFz!M%DwS*VAFf z3LXBQ%=gkmhxskcs58oh3*qF>gP7ZICmY8cKZN_@kwxSSoHMa~DRs9hX2S6+wQYYZ zG|&CXf>0MRX{kcfhQ6j1?Cdmn9xtEU7-bh{OskYN%f{A+1dq*9zN3ngJJd1u@kCD( z*_{KP2so@lLBqw^U7*95<2u}MqBdfV4t{&cGfrWhz`)OF9(x+Bzu9`4&|hPQ*P%?* zKc9)IE$OSepKN-Uhd39Rg+b(XG*ftudMPwLsf{?a1K$hvwr=^GrQPpDxvn-#(9r}r z{qm4FbvMi77Mv%zq(4(9%IJ2A%Klt}HGv5R2 zr#Bj~ZZeK_-7VCy+(zAE)*BMXl4D$(iK^t^UF&Dz%4D*!aSDykOogTl-_OS{3eE9X zyhdbJ4quO#O(o6JkDlqh{~VI?pUsloJW<434dFRtdXXAAFVtAaI@5jn3w=JxIM4gI zVJkPPIN->41CAEyF^k3m2D`$Jj`$J8n?-R~5?x&Wo zPYE1ZYLELp6gV4YhueevF{TppkS65Oih^Kae!uvB05)IMqdsHTl(N)aueJpT67*k>k$K5nlqmM48S-9Q^P$F zLmkO3au0m|I2suh^>93|hf=M_vwr6hxFrp?%H%3NIakO$dHlRIbmH0Dt9~wA{!kCG zUM?1X&Or|M?1lH4Q}od0a2z?iXi7&5#Bo(v%SzL}h5 zr$7vh48Yh~L0Gvt5C=8~;K4G^m37tQY(8rRS^sf_di)!zM?rZ#J@3=7`Jx4nn2&hp zTTme)4L8=NVf#tyyB9N0p3FRfI*lt2@as7_xLd!mjJf0`&7++qWt^A13Gk7?wr=7& zM}bvaI2*^>PXS8c`xXWMx?U`^_tX30Z4frFW-=r&7^%yshq#IQ`^Tx>`$~@$)0oHc zT3IWT5t*?C)%U02VAy%gJ!pYvW3r6)=h4YK4Gzg<7@u2_?wpHTNx7)KB^RH%e}cKT ztAtJRmO7_hL|Li1bZg)()+SBm6!Y5>QS|nxXpe%Yye^q`@MWL)uh2j&-WZ7E^#jp) zQ2_V&AnLjW;VEP2w@Xpz*M~KiMO$!oksc54QCDb@1(*4GP5Me*U)D;F@3J5;kF^jB zwWz1$qF-hXY{PRAW@D`)oG~NGO@82Jv_$E^XtR)4Hg1z=d9KP>;U7tf!a&l=JBC()RER?i$&kKLc6ai%3T z{QFpNHix=WmQ>uTnMR*^`f@9B(PIGpRohYX=_I*?Nx5+CmxDpnuRHqNC`%F!%EE#} zGIWPo4qT>ZnV!Ab2<|}@J@MB|6>CQ-*e)ocu1n_q0nhhk=(Tf_e4I0NeY-^9`~Wkq z4>n_KGBwM2{yw5L!}}L?S^e2poSTJ;Q|L9rbM4X3)b~Be^?yvE*}(m83}ePCa$jr6 z$+cuGtHRvKu2h0NjW$Y753@u}rT0;5v)qdz``$^7);?+s{o4~yo~TiAi5Cv!Yhk^n zMOsfSG#wTr@(*K1ypGyyW<+_KG5HU@cj9?|KSPZap7WO<$RyYBzq-P2K5=fmNfw?Q zr9L|M!{VO`&7Zdl&134s7JO7_KJQj&A~WJ-c^dUAQ_Qkw*deLqa8x|28>My)vUy`Y z(SUXP!<-ce*v96Pa}zip z=cB{%wVV%NzdLzZ1j7E+p@B~XCbgl4z+!qXonvi&JZC6&n_%c5sS0^JuVG?j)@zxTUBlQT=9xyEbb!}$7bs8K39nq+<%lbk18*>|K_F1awD z-|U5A>JokbSB05tRq(Q^@nDlDs&1xs!zbz-Pv<%4I(4BL>)&kCQOCxJ^8wWIuVKQ{ znT%Z*sE4qZ*NA70g{;57Jxfma0dp_rciQ{R+1OL>Yfxxf{j?!)5B&pq=BPMd@jtpC z|IL+6_~0xrISX9oIP1eF>6_Dzypq2ax}yyxggS$Js4F*lV-zCPspuU|cK)2J)SK}~ zqN$&lQkGsln^UNhpN;bioaK9oKQfHmS=S>xzZRz8SEU@xndB;Yh9W8G%srwTYgNt2 z@BC$jrj?U)UtA#NlBws#*Xgz}6;8jcFe_Z7J-M)rBm8hu8-?{fENFAzit(xSrP1mF zxqZP8`iv+v)U&2khcm3yMY#F(kNDK}MZ<^DSRTMREnh2VQX0yOPzCBe8HDChktjbZ z6@l60aTby5vHX$0o6_gkL|wvtsd(?hdJ`H-vkrxVdem`uBfsOHiu*muF%6~P^rK?g z^uV7z^eBwEpUU`Tg-a^^qp$yxUNr}y+UrR4DV2&bD%PFqHk1Wz^F=Y&5BWyUC$nCy znwf*9Z{4MR#vf_j$`2b?L}3PNY*RK^5&4wbyb}tg+;o3r)gl+^&beULgmnwa_vQT& zH}0wGiS*b0Mt{|v*_e^wB(=%kt*P#Z6L;yiTgrl4z4DCe%r6e>59Isk6DaS)s%zS^r!_9l*ELuiQ@m>$k2lbZN1q2hmq|4(AFh z^E%I`e|KX?**G&_)=(dF|MN)TQ3~o;rvL2KCUS!QvyEp5V2Xmejf@HHb=i1xzM*7K zA@^4}2$AHxEX%0}x-FX;YV{<&AWzODkTYf9ATOD*gZ$?EgNu`qddjn~im@h37{88{A3Ni*P|qLzbi z8pc+ouEG1pvaVmD93MwNtn<{^u0?&leO8o?Y$#i)g|X+gFX~o}g3qK>6pyyz{&)7t z$P2G}HVBDZqHy3SdC!`B|NR=vOX}+_@$p6Pa#0w^dab1%XRfz8%jGdP>B5?IdM(z1 zO%^QfPCmD%ql|Pe7N-g1DBDCMkY}^GT)zP)8i`g{D3@yZVR>)Xo)=M%a!WSW-)SOK z+WnDzXMJJ(LjQN34JM7CF5XgiIhC6)GT)E6IBUiGEXXCldEk8`iMn1Ot#YYvI3x-W zf2MFAiXJ$b^<~nge7UliuYZ%A?_ugHeq$eFj)RQ*@<;Y3`JvAw@}!-4KM!Kvwpjyd zTv#ZV$w7DQPoCF_HRkErs5Hb?VmlSef^z;yIgZpQne zDY?ZLR`h%2B*mY8%jb5!^lae%5XbuRaQbC!Z!BeA{SnEHxv6EnWzTD?o?jHkxuj&?@3ACceJ_o5f%qBkXIA6pX zzu(DJBsf@MEaf7uvkGNJM_=@`(AVCQg2lYf%^o(A@i7H5c~t-gg8X<<3Tk(xPU4Hk zlDQ&ZOyq)-L!&UIANyPHvT@*ALm646NT!hQzQSI>`1TeIcD165wT3L??{#K4bt zd!d8{UGLEUoxj)6m(&lfKrgE1QJC}(KNs?+lUp^CYajBY5%)=*54l3di#?mzw~BI- z`x$xiy^=r5&F6KPk;+*v6X<^=%(onI|?BcWPpomiuDL$S6!Df9ijVT<83F zX}3p-cL>A9U;`Zd(lKF~4VACP%I-5tG^6ir5_!XPa|V)%Y^=A%iyt|%wz1TYb2Z|` zde$Tvql3uNw6=O+a9k)>vHseu1AS-6odumSNp%IalgpD&Ni$;oxpb)NDl~POn>V@T zflFiv;>H=U?P@xE@;2t!vC_S&inX0kOy6Wc+HdkTgB6;5Q=A;#;sy)r&M$7$gHfN3 zCK{fbsQ-1Z7UTcWP+Vl4`1ob&cCEAFYX5kdQqrA1tkh?kM_t7c8F)jEX}d>^ykF>s zG7jMgwIyIjL^?|F_xkbIe)%|xdVjfLP@bZXD*2|b=Zj(E+~%EQYV2$ij)#@$ACZuO zoM;>FmZiSiL^n9L4~6w#`f*3oKO)hFF64K-cer9TA73%Rh=b2E@MI3_0rX4ltz;cu z8A`7g12(ltM`2BcX6uz0`SZgaOKWNo)X#vryVA*y+u)ZMCq4U<4zsYWw^eNmxF2U=zkQkRXqo6#>$7C-QSn!M6o*77ws$;mp| zpzw~B2V`LCW|Bh@avYb^@qVcdiJmc%Hj`deueB&S$B3v{a(2IpG2?igD5$U3VVo9@ z76a$iGq9|sLgT(XMmAMd(!W*4&VR+Tu2){CXeR6FZ^5bPVdC4&!wV3WU7gUZ-aUI`ICCyiCs2 z(GBjrK1;a1&i18eDBov?2C>qTI%rin(-lm1rJxgix?L2Sj@J{Uu&oEeABJJ|Sk5OG zb6xl;Gw{ZEsc0Si1WGkY}jxoLAp>o z?Z?0{l(|d4?6dT1_El&mP~WiTM6M&X7R!DmAep?%r_c0BpBX1@FHsM)e;B&dp+EJC zbZT=dG}Y?GN$z?jdM?-EiiX@P@52YZ$rsO|5A|0M6qv{xKB50=opf@O#n{Hrr7iV2 zE)CQor=tG12veIqnhs*;zg?av++_mjqXv-V5gA@aQE zwOG8DZ>XDM2v?z2Vi;ykrRNy$t0Vlq()oEE?#|xd{7|f4MgQ7S+@HxO zj_p9-x6|~a|0f(bzZmfM1oFtRp=n;M96sre*wbNH$Ir#qfnHzXHdHwlE7SQt+m_Ix z3Ui=alc}?2wV~#e7`ac*+Ct9ypRoo^c%1>2qYcZb+k21q!(!G0;>oeD;5uz~oO-zT z;^f&M4{V^G=FkxK)p(yIaCY&<6zVPZal^U^;i%Nf0Q0|$7d;f3_G4mX&R)U`MLo7WSzZka{ z#z}fpC0@u$Gp@}=2m(wWaQm5w0{-gl* zy1!5M+i@fLYe%<~^$%0dPD^RjY3me+PNyWWQ`iAxhrah0C(qD2rj+%&m^{AC$xff& zs#6-hsnw}xxp~RT@4ZrbE1IMXTQ;&&2iK^MWu40>pK!f$PFmMZDV@3JT!RY-<(hwj zJYX%NP2~jf$chzTY8kvfW0u5?28kuld+>`<6z2>w<`I3Ss~M#F5~J+vVvrJ!2ANql zUY3+hkl#sWxt?v7!lwoq$614bEnN4U6&O99uhqvOFZrA$WN80fjFYL%^{lh^(YWsdGvMYuR_Mq{8Sa>>tliVQFvrGbGVJ z@HusZkI;j9vI@h=zV`}d{Hjhicn)IruqyZS4_b`P zCWCmM`~5E?=G0_eL2tz0Gfc4iM2+6X^s)cjfO{?I@1!(QXP>?8Ek-!*HzIBuV+Z5h zGVZknyN&4hg={d{#oW_I>KYmGo6l*R$(ht6CZuz{zGjRVK97&R%bHg|a*geb@F^f8 z`P+zLN$ht&HsVDs6SlX{#Ev-n{%vJH=@!3UMb6O3J#uFT$~~nfBRS?Ol8IiUGBDaB z16HoP!=KYJW@b8^hGxJqkLRt&=_ngX-k#I1QeyOq4TIDJ;N2}#hS$7Hh z9_UnqLyt~mra&!6GIV#4^CQ`%XCUZ-BisvPz{2b4GXN;$)YH@Bb z(@Az!E0%{Hi{&*L#-}BV#p{#;>am>D(^D6KU-zU(fNJv}N#9;54c2n5Y^ws=1@?%n zVw3sw#pSFvbAuvz<8H_MfczC_oRpCYGORXfKFKEfQN^-(0cZQ$D)6B{b^i^;a!pq( z_vYGUtCDk46YLOJ$0m(_{t*|20{tBVP>Q);wGRQf-i|X-ul?}4RsiPtvNk-~A4BNF zFs*GM9z62H`Q7xKULHuVr9j-%2Ev^0kEw40@bHj7b&=>DZ3;lI0f9KlT8Nya*K`ek z@=u)G9PN+AFX(rXNl$7^02;7Qp{`180Xu)zhUlA7m$R?W{o&(5kEhL17*vIfVn7u7 z%!o!DbC+-Ao=N;(f=t$khA5l1?ipJgh(VXYx{Mc-ISFmq?D~+Dftn*xK zL5|AwpZ202HQQ2uu0H$2qoQ%vpI#6HqS539Yf!1tSj^lpNxcPo`S>&4_4vWsMbRhn zUbCWc^Jx@ywOBV8!#*j2rw zsc65QJ?E#XILBV^05XiPnKvC~pI#BnUOiuQn5P7g1&QDci(Tpsc9CJWZi%0ZqDO=psyh7|1R}&Fm*S3NUk|p5ND-N zwH4=Qvrco2H51nRQZAEgEXAG*bGD=ttj}wyCs#Wc8_5aO;-7E1oCzI9O{f8^4W7+` z<}GvIDArYya?p&uppon^e1B%e@AWx27iPuHpj;fB%U=E~D*|g%)3LLU?7HJ1Tka`k zYNWHgUFjl)aUPOLUDPV0=-tp*EjmvhdD~hof5m%B%OjqWq-rANH#^IP9Vp*-#mmpC3@OSU2K!1oLL+;n;H>g z?2x*KOk}7{`cu<3K1TbDgy1nuzd6vyOq-srJW-Za@Un3Lc0J&1tfL>+UZh8L$pCs0`Jst(0JNNu#5(FwkxTy3D*#o7`l0PUfBYIt zUC12HmcHUWUzN3#73}qpVZ70bzCJF<8nPty6ItQ6pcFXIrGTJ%U$X`a;=#^MX6u{DUnagw8l0<6j@-1h)1H-AlTwy%O<8wyO;T0&DxKCQ-%kGb zYo(Oc$6Y#?e7!iSZJClOz1N&i(mYH*7doq6^7sCe&b`&_Noo~XCS_#6gQPwUOtQih zD;s_qWNrvOL!Yo`)YK$ZK2wu%cZ`5%$JPHBq)8^vZyyb!Y(Ouo-DdHk&QtE1SaIGI zBdgaMU3^UPli%MxEMA(h_mU7FBWqe4 zW%lk^>Kw;OrXgO=d^5>21!r5|DzUV`n*1H-y6B}a>AjMBD|NMlRLFm$M1TYR9*k-{ zcT?dv^+F1r)CgL{=kcsKcZU)OBY7??=2>qMHMx1-a~rF|WQ`il$}lgit48=1CH)*! z*yE#yay9)eIcN2UuNggobA>1Pycg`%o#f1#LXFHH;n=7lo2b>oM%M6DpceJkYq7fv z&x0Z17+Z0K0#V*|A?*PyP*9eT1Fw0Qhji;Qhr1dk6x-6GBr@@Hw-_X;Rw zKvA**mH*4n1I*~ev)b`X^u+KnVnb#A-Jbor_C_>kKk8mbBmU)M9bOp`(#nLcM@@J& zhrR+lE7sGSs4+wKVmS4z7SN;G!ALJZYRpt&zwxC3gLp1{Rmz0%3r%oT8PW1K|NmJd zw!S0B_>|9e;T)ke`?ii5$gWE-R!s(4gPxjaGEgf%6GJ$QdX!vAd7cwZ{W39$XTVLD zGcb>AM@RPP{=P#`k+Gc5ZInSDPxkD1hEy?6owFem{rLB_DfDjO- z?imRFnhwt$8R*Hg<El;T3^!imtdDuZEcmMH_M<4AlHBW)s5ABh5l;^jJB~YK|z*fTov1vZpIK~D2 z@F29l6NGWD!FaNb`|<)ku5h1zs?($U4DRXcs7Kw)f_kIRBlR*h88=h2mTcn{dITjc z%SCbl>*D|9lBvjnY9IHbr#YxS)kmbchjd(|mJaF7r0!fFc{)!ePd)7DnOr0b=iA|k z#U8cE`rA=^%Q`&>rI!R@)rKHM_Xwh&WDr8i1fx!{9&2N%VL6bVoktmWT5Lhy2I~LS zNkgSn>g4i_b7?wRxsR!6{*BCmj-GEmxoFhp6Tb4ge7sHlrWE!IE_sM*gNsngYwnf4-`q!1%}h_?Z%nu$O)~evsa(;q*m{3&N&? zXzXrJW+qUNDE{64v>r=#MPuI&3qCSFJRF;bYmPj>F@A)R_Z%>Y*MoXifs@HJR_2)~ zD;Kj`@cleg%CO$v^5~+g%pUD3wOrfDlex_#rOJ<&Dz8iqAP?~4TA8t8lb)PzoJWKYzo{J`AjH;7kFZf`h zcD6|#zdt1Bf)C5*f#lYIsqwmsCr)~K!ZuWe^)bxPi&RKl$QeK8%SWs_>{3La-BKN# z&PSjIbIcmC^k3R&!gO*NF+z`l0VW*VmX3!nGq5@&3r!vWSGTqDvrN>O%zpVIvJP1a z&DZ5*z+w~{<#B~(iN5;wQD36}S|`%^d{<*mNzM*T=CvZ*+4Wrn&LuKN z8Ob?N+bY(=8d_5`!g*b;jHI`!qZw;hhX`Yxp_(oOYinlVd{8E4pJr`!BRv_I>n|lM zcs)d+srQgIN%A{2`FYK{tkA^#h?fn2ndK$@odaB1cj{-7Z7GRTo}bf%PF{$7L@$nV zN(`*d&+n8P=SM`KEAN?ct~$K!tiyxbI^6!EgRG^N=RIl@?=s^XuhEMl6Q;2a{W6s? zWpySJ7Spej*J;MX420ig?XnN~3-UvkV_B=eq0n#uN;9e(=h3PEHF}jS1(c*qI3jG4UWK{YC0?`)}m<(9j=k#Q8-Z( zEr$LVHyKYuOjxv%*M?l9l6B3!W7rEAnT4+N=wo_-KD2E!(PR+yDpSEvc2hB4DJ(KMbJWhd}9s&4s zG7!I?2cpb2`URg3KtJw>*Lu;XV6+~CzcOcLPW)&vHL|WnBlH$$i`>)DQcF!%p2dv~ zEJ$s~v-1be_-xBX`WnWriaFSMJQowWU#}nJErXND>6K|F8Ld3U@YYSr7b@jzZ3QA8 zaKC9oEvZHdyj`up_k{{fOb9~K(Lf}I1mj0|5bl=>LJ8(W;CrbxgnIGJF}ky#7{DAN zgp75;zZN`Wu3Y;_8g?<4p0gwkd$;mTzdV;bTP_Bl$c1`TE-IeNWxbsGf0Nv0QC3Tt zGu2zJzVnjsDQX$VTF-_mbJLBs5ZsOAimJaZV-Y=PIy2qF5d?jUwN}@AqiDvynIF{=8y>9$kNPmZCb@JdZSJ|1jTK z#<~S-4C@Y1AG&-lM%nW-x|f4~x0uK8$;I?JRs^qgm;FKX;r_yT-bf#rUFayka@?iw zYCDYGQY@=FD==xI0$U1-rP2X<5_kt9oadg2egU{$CIF3M0uVYd5NS8`_{5kR{5TpV z8RyH)(LM%Zv4qDJHqq(=4u&%u^bqg+>ZO- z=k!dtG|0kzYaX-O6AveO!CCEvnXh#i z`i=AY+yl2}>X2}renlUtiFk(f=hj2@oSO^(H%^f z$*((=COc@&MBeC3tc_s3drB4@xnGCzx(sKGXv@7hoN>!#6WKlT19P(yWmA8X+#YU{ zC$o%Fb)`|pdz)oNq!+R-t1!ET8lU!iQj(odEa!1NW?xXwHl|A9b7|yq$io^LI(fs8?u$hIrFujc~2+4pHQ;zQ3}mo4~6FH zNrh%+u|iX72JfZ+L)u>kwbj30yl|+yJCq8ZQ0i1^uSMO9*WKL}33WFJ)JyRsK;4@V z>aIxL4XF!G&boj9dFITVx6eJp(DsH9_TFDx*XLTRI6=B~(#qVnd~S;AlN}!?3+Yqc zkk{rr&&Zo7Y8V=+kC)cZb3CNnm ztfxlolZ)p%_MPXntIV3-!wmK28Mt>j9cK#Z#owB>>P8ms-*z(-k#)NbTvzX{`oB8b zfAz2*ldYw!eSx^$_QK=(q43#2AHc&|NDH%*=_`uFw8aZg&xJ6LE*UXC%!41)SR%}Y z@}1|NHJ?M+fAgOV7|#!_W0hWU)Y4E686(9r-ynYx<@Eh-(e=uHu{v!XeO8FfA_4T51!W4py7Mw z$x?6Hw63W%|B)|svb->5s0RC@sB7QI#FlF|Vt24mZjrycL=Esy3V+`pnW$5dT5g|w zdG^f{J^4B@dy^4cn2EPjnn>Tbxq>QQ7%`E0c@^s2mB}Z5agx^E3+2@_PaN1Eig(ny zC;ucbW^O2NDin%oxHmf2?$-3ejB)JG?m>UdM&!%RS;{cx ziC1IK`N7*Ev?i{sRy%W`9Ay6 z5A=5?=5(@>hqM04hBPmDM22FSn!a*gS?Dy;j9sfjkEAl*+|SA zOGHh5`1F_%JlJf+=Wkgk8`(_Gr4&jCE5OsOLQ#ode|29bzUDQN_1}u+@JI4@jmSj~ zHsYHi3stPF<;G0rBinmp(v1*w+e!|rZ#F*UHY_pX9 zJQEi1`E+|7f~@XFxOL=NuCJr4=v^pV26*Awp%7fiscLEhjG-f*F9j*{p?JX z8q-WZO)Zkx(cb8JF$7gy$TbQte&ri1j_HyyzKlw?&LMK-Z^_OHUYfn!J+h%gg=b!BI^hWVFj-&0oZhNxe z6k;t)J@dt8wFge{`uDlPyyLc6I8&#-T#YOgi}7AqoX;AXDH&fcWuo&uTiM*IM7q@X zAd4D`AwQX8bR-iuw$ziPN`+E^{+lnT=l_|)`6TlTyq{Xim8J!v?n)ohlbn}=jW}^B z3-{02$^N-TGH9|FTn2KVsWBq1SvJyEHI(RH$C4%u;wK_IZ857zObnnUKU7~ zyF*dfB^3XVjHB;4AC4nGNZ-|U6TI;H6#X1e8?j51g^x~FQmK5Aq}>~efQO-2yn^{? z@tNpa!&<&(=Zp5IC*Cy;MZZM)i44wy{%})yKe9-kTa(Y78-gKL^a1BNYqz8=S&l3e_eEEum?N|(3!@{!Mf^y3hO^rL_7I`WUx8_DJ4%)3A34d=Zfm{p4R zCF2VmM>Umyh61Tef6RugkJL#eZ_d{#Z)YpGP$1(po|w-0b542AGYzwGyEJnvFWJMT z7Ww}X>IN>1neNcQ-Bx5qrP z2WD!uzh^O{uoM0D=+D)ZK3sEM1F+j)3lq<^W1{FwNI!upsSbGQ9Do5ST2u_7w-C&D zIwnfyULcp0pvJ`{EoxJf9nSsc)VEq$PiA85mLSw1FW_97`OCg$bkW4gmn)9we>e~a z<8^pWZMQ*nGZxc}YVaRBD1HXwpzwwdq9WBa=%Vu*x0<(f%mIz2MaW z^t;rRVBY5_@w!Fcsu6Rj7n2L)UN9ru47(*!%z$&i+Gzn8Q-eBHuT=QumSAAF2=Sfj zh(?9oE(rkePM!gC^$zJBzu1>}67&8i)`}}edpOc;e@F~U2&IZiT zX>=WpV$1t&aoRIgpoZ zq=jK*8hVzYSGiZTY}YuU!cFGhOC0ixa>7%$aS|q)foFFgxgFdP&=#Lr7>*=e@svLhT&enKEFFJpbF3-!poCGg!8CF`0w zA(B7$Y%F~<;~(Q@SI!TOnGZhK9#<0l@u3zuq(}6D{ab?i2~je%jsp%}3_!Yt4$V2f zrc@?py+2aU7ujQfy#ORs)X~SIKJ$3ytlQpu?QLHO%Fyl$3IC)jc2_<2y_j!?>GCxMA zBIY|kp%36Td(;~qfG30L`ElSeHoB2lW$*s5ro6wqR-)2vEe`Za#XP>x!M3sTDV}-I z>jUvuLvB5T-W-|arhVvxx!)1jIB(3l7?1Y#*vEI%jD7p!Br?tcLmLF3lQABhAE&~q zp&9*J#>!`M%@sJl4*ZD6{o1LxTa!89wId{gHO}(k0dPGXkM&@FnKk?ElreJUnj?Om z48%6G789p)o}|y?|GzwAwGjbs3b*@)jnC#Awv1Y5c+q)|vChj7!-^vv3{?6Jwwad= z6I--2?)+S2nB-XA7_y_cL0gd5Rb9q#@%zp)#{7-JZaxca+$wh4aBRfak_V(2kB z(eNp8k=u&B0}UOY-ZY$Oa;ED!?M;I&<*&i#(W8sYcI`5ZHB>Z=I;%FiYnB^!^&VxY zwm8O6p-!%0wI)H99f*}%(e!DYrWY!aGPRdh2J}8E^C#)$^1)cS!yJjq_RJ>;N|3fA z5@g9bt<3wVlZEWj?7+U!XmXBE=%-_uA1!;X$4i$LakAs6PUgOjm90DD#mQYO8%D-S zu_f2YNWIwT;-waO=Ie{;tr`(cEiH~2)LO}9FMj7oP6)22LWiF0dGAJl9M-5W(O+~- zIr=B=Qej{cy%TOb!8<^O+e1|7yiJ8g0qiSmtwLyJB^rjPQ0JhM8LcXueyZd-Ly4tz zRk%@}ee>Ow7<@;GU$4lAuXVuj0ZKfk*UxB$5`QW<;pJCHT%;ZyTh$p8S~@eUfL@Rd zsZVWHz{d4@)*xy_Yw@*Q+!mqcUqekEZHCEdO z;o6}(hOAsxdD|jdr!v7)OS@n;m_A z0@OHFBN$H}1fg<${`oaMd46#0rD>_%QWtll=2Dh(D*H!E-{l%Sn7JVydIaa_u=yV6 zhGG18qr=NX+%I%XK)Ksw6`RsmB9k?umpV+YrRUngTG18qx}Eg6)t|NNdh|^Ft;dZ2 z_6#Ac(+r~i2G(qj^0og^x8R=YsDWOOoZ~l`bod#Yh8}OoFS57T$hxszEAoXw%!?jK z{=GJt_IUPPIMbu2AQiQ<>C4E!U+P57tPJ}Nxc9g^fc+P}(&2KB`GN=O!)QTH@l+Zn z?@Na(HNMZk=+~T|hH%bj{>RBf?oLNR$22%@Ps6@F{26D{Q2z`4d?xYl+*5q&<|1Q; zImw-Uj#59Og^cQGBYnRpW&SCZJdJ57PiCm3-i4;ps>2D;*H&geX(B6^yGVS7BN+~Rd0E+B&W75{+t$q_ z^`nCvT1>yVsm<7PWg`Q=spQ?wrgD6h1vc%c4#FB@|8dkGEG$sXKxQ$RY~n%IJZ~uQ z^C|NNjwoQ=-GUyQ7FhVYNNkv!w}o{8kNxaX^(YaS&K7{J1zzndp-;3~9x0e3#T;o{ za+0gx7D)9Z_Byh!Kh0l(o8uM8WY652?j;gGwopEVx>HWE}VVVt^I<_V1F7BokTL%Ln6o`5^eMH;xAQVBJj;*$2I#e(wXvfu5*cLLI6f zImVv!h`h@lQoRQ5_sBqv<>#)pKJ8q&(|R3eKIQ7GNEE9&oP@#2DwPGNMuk*6-a-_;Dl|Wq8iDA!k*0nhAzM%(`Gb>Af}C$I3YvUpgDx`!nCG zd^RfWqUKH==Pg;o&14WiI5I1Mf7cqbu)ALt*6hi~iqotUtY+^pb@}2j=7YV;!q5?{ z@qEfctqEE1YncuEPuW-yNp^tWHzR`ifc*TkE$hD@`&AU!^NRjR z^pJY`T!Fa`3T$yv;LG}AaqOjlV|fca8AuM88POg7G3VwKGo|fIp#$^BF1%x%jjZDX z*52-aEtJ{UO2n#F5j~2FB=V~QK3~W=9w?M+Mzcf(vR87u0y72|%e^*c*~GCq{VDSx zw(#7)!w(bZGry7Jz_^WmjN}-t5;@lT_#q{ZxmZ_Nm-_01Ij(;2x#EM4<9%_ng)dwh zaa^Q%BmJ2VZjd#&OYLzEUt@lhH>#!jpfS-;UQLd(jk7sM$FkPO8lY`;4Rv;A!@INJmpbi6j<3FbOz4@Dj4Xb3^)=z` zH4}z4rWUr4KBfHgF>=GFAJW%@ykqWn6V}F`0@&(P)Eh!e7J3j@6AjZZz-G;F*IV#v{#;F}1Ku zg4+v2NWA?08Yi6x zCCDe2M0wz%msOfrS;=$amKw3Ly&=!F&*G%lGoC3Noara4LR2jkHXLH^WMwDncS`26 zllur%K~6Z4Z%`t=q6)evDqMF~!Y^C}Tb_&4sxjMPoio(s`Mq!1FJ^9mCKH_SIN1SD z8!;m-!x2wsC~`xibnotM!s+1$ga6%1}XD~u+)wtyqgb~w%>46Z07l~@rZmUM0 zA3?A#t%mv`{rea2%so|&Yk|QS$$ekWRlar*eZLjdV5lPvWERBEjX^l_fxV2|f?>fw zn=S>QOa-!zyL1?FMEAce)Wx^ik12X&zGoeb`@nk#$sWGdWBUX4GrH^XfV^W*p5^*) zB9GW5f#ZP;<2*e!rTt%SbVdF>Fi8*3JIs`(hB4TYxg)-M3~xs!B%l2>7j!W3wTc?* z@tu3lX&u;8W5wEE1wA_W=*Uaa4{}91dag~wo!x1ubcNX!_fp~1hTdiVX-IWv4a|`_ zd-dt((KHR~zS7UTCD}xN_AO6;kABqRCZyvj_kp+g=YiMwedHQlgVRxY75iKUr{VBy zdfKc?!>$GSAI&(RoaFo-VRZ^>llh}s3NL;j|R9+WEoR!57nO(Gz!97@n7B#`IPCCVi%-b?-1-%i~;0{;VLenrK1T=NH$*9&hYIhU0(x{|Y8P&&vKt&`}s zI?17<+($BZrw)5<{{AeIo=43xYzx=iA|Jfuy0t9A2S=CCOQbQqy*v1z#7o0GkTCib zg|YWK9F@0)A<>3^PDw$RE-BdXivC}d$TnUv;oD#CfqG`66Me0cs%5h#POgy*#+VCP zP&QY|f>>J#AKX;l%;z3{p|c#=Uu34NmF&p!?54J}Q z;~tTF&e`n4A!~WZA{;Z{gyC0w7)}mg26j_=cjvJ0CDnvAb5n4%Y6@J7Q_ykqCHggS zzvsu^5YF-Oo@5!h-?D9zgYDcuZMf$s-5gcY--YLeCM{*>nD#PlxKh4}0`cR$CUMW%&5PG+F?(5p==VDy8*}f_$Ab({zVynS1bLIXAldJa8+mS&*z z37$WPr(@bnh5O}^%ta#el~dlr{pl5j`}-g4d;XLlVG5lLy-z>k`bo0vG_xdp^inCs z8Na7FVbBux&X?u-aguChP0szd$S-yZ#;w_$yZNEpz;pf$@|D%~IK_ItOREGZ4LmQe zV%En$9rj;kKk$Qe*xXJ>JDyQp9`QU%?s|0>dg&D@+|S)7XK-ENo=KiC!Gb1_e4)w@N^#NeNI)Pk^JHo@*8R6RFECtdN0fDV!g@)A3?`IzCTKgAX<09b`V! ztQ78d3i-a4lP}0oxDVXJEX<#=GOtp+TnT00z|16Ba+jXTGgatc%(XRLg?g!E{$rIW z|5b&O}>?iDD;ui5;P5?@^)@ zly^oYTNTbUR$}60zNcGUleJ15pAd|D^VHNu_}six z&prW`>3ZzGmWS9B7|`{V}|E4awHOA~!gJ_pG79J$#YEJ&F0(ZONoQ?R7-r zwv<%A9t?n zbD7`SPmRHkwYWw7q`F!MH?GwS1NHQ4*CTWquZveYwml>hl19(AxBv0~>A0;{xI3I9 z-^u%Rl8lqJo*Mrc@{A{2$dQ+=C3L@1dN40IrJ{=*>Zg>?RV^^KKRs(3F`Ks(dnQ|( zBj>{*uYAy%K7Yf%__Cfej6JepD0MUp z;CaG5P=n-T4c2#HegoI9DO<@elG$_pn1UA@O{imU;=GiDqvP3^SLG|7a4xzslRbSr zD{p+*TsAO&F4l|~8CeCB+oI1#x zSQ9FQv;T2P3aSUD;P}22%;#GF`*t=ypUFlB*9|o})YCO{(2#5X{cKdt3D`$|HqDWy?+m2|z?UQS#wO9e8XEf$u@Al|EW?<^4h+5&}B zyz#a-`zMgaXAMk%j6)QJ#E%pFD!X>IqjDuan+Ng|M>(t7=A>i|8hp% z&CV#P;tZSPO1$Gapq?Ey=Nt54UBmwNd^K8d9_kyU#sdpAI9qIcwNsp$} z*;Bq>k8S1Xr_hYvu-xxXo0J9z?pJfmrs32)j`jWIse95Fk$;{#m}}WH)+6$hWY7b> zod2Ykt_^hJK1MIQSL@~H5i)PQclK1XLQ&J^w3aDfiJMa6L11PSb-hHv^}qaDMK}{r5Ne*S=S{-`6SJ zM{!>4M<3rJ^4=#D3U~Kci86xOUy-TwD^SOa#rg#KOaJ}-tTFc9!!;saiRG3~X#bJt zw5Rm7@1e%>ne-6psK(w<&WmBxvX#NGE|q}6TrG{pp_0ujM~-n1*RdH-S=S#(zOtN!d&>(6BJ7`ArPRqddNUeA^wMTT zoXp9l-k;zEFO@U$HO^djTu`r$3xbCS;rkag5U0kc5o#!JlGVG<9*XgLyd$gEyx_b=RUw4TbEXAcYa zs;85rRdcOWs}nEt=}~>IjZUm9>t%Y0GdTsGMd{DDyNn94AC*M7ozdl#8s2<{;u(SwdZdB-waUCr7*JWJWTxvbgV{~Tg+SlzNhU~gK_i^Q-B6~1p$C=&&BE#=ebd|6%36W7jjKWZ={g&f@aL-i#4eWC1SpVEaU)P%`5jlG+R z4VP+)wj#Ne8XlNAf_&c;BeTpiac@my$sbTC*-Jd((J2&1uNv_xIunOnEk!vdR}SA| z&T=%lAy(y|xM!iJG?KgYgKO8vgE|+pgT5uhZasO)j3%=C89Amue4Q5|ykABPe9C!# zNdt*^kt?mAc;N20K}~x8C@dCH=VPRSPycYov3r>k-y{pU7VeXY0WLA0(}pSA3Xk-A(KMBZ1lTK zoV08t8C&yYGT5_ypZwz!a&4W+CziI6iTXkr?&gVU)E8SGVt(;K`dwNz5l2P7Os~b9 zo6gMV-J6WM{?ys()fZFc5*g9c3jsqk+}|@__)jJtr#6j18rrhp-`T8 z_aK)=|Il&CxIUSDZWk-DD9M+RuHG;n2}Mv|GTy~x!mfWqu~rnx)5-LyzC_=^AaarE znONm$Ew0S@U2&GV&*~7YxNJm)Qkh5|*+ed8=gN`*4{V(miu)->G~spla;lN^|6rE7 z-8|9#dFup@iUha{uL z&P@EXuP;3+;Vfi)ImCR}S+ip{KC z2|LC8nsX@1@_E}eB$GUHBgy`oFZ=G%W5bu+Ss-~>Kl=LR@_xN2k#09VaBxp3vgjQV z_LVvHVa+9^VS(hY@PJ3bE<|mhk45cl3?T2h;X<*b9cJElNeJS}jdnSdiTH3U89b*% zoU3{uO&?0n1S8t!0zouFRre;j_7(^!}nB>kRha z2WKME&`dmn@}(F3D{V745Bx}mMQQFsG8@XG^2HLN^+dK;D00YO2OZ9WYr4IxI-V=` z!#uHiJh^WVa+ejUi%ei%a~TCTPT@G^yyR9V8BLe-JU*$hI1SGuvqWAvJ_L`xFhBZ4 z7XE3P$+yP^^2M9^-8|nw#!pX^jnL(=ehh)70Y=WMjIvz7~DmP4T) z^y&>o2PgU%_F%p_`O~^S`4YIo8(*n2S!t6oE}uTCYAbmeSSX8Fv*`7S`RrSa$mH`p z?s+{)(fyN!-}!u&p&#hXWGME0!Ag3{p9wCMti|+43841y!-&edObqa{lWlwRBzpsW zZ(Yb~-b}{N1H6y@>dP;3h?~g6hE3OC0JZ?vx61r4ppJw`X^2_qs6l*3CMFm|3)kE*-nR{i^&<8OYrk-luXk&;K7Oj zY_Qa#l0z!0EH}(l;9|M`6%h#WH%8Vdu z`YMtuOy2L0aii(+q)KJp0&}A6<7Ij)`tkJ)!uk>|-px$K{4r)YHjNUWUG}(KKy5!< zi?Qv~U@Xf_ijOg}`LPqGl8gLUiTkN_WFqJn`EFpW)STb|=g~p1tE)r$B63eZ_+0&n zl7TC^udWb?!VE3S@cuqIT!J1KBjxTh2ka}MALVd*QTabcIRAYMpNA|D2i$rbh)7!< z&Ke)1RSkNrCr62nyvyb2K>Qq}#gEy%UwZmT?ur%rN%V6J2*iOR9sH`$H{b*_PgX}u z*G`V`?a98V8(MVxLl3Gi#mG8HUTn4sZM*|aql;BZrtfF9v1)zk>rP_wa5g^3!>h>Owk`?>@2pRdFfe;qVC=$$a!jH2>!QYFy=7JUEtb+mZH zdEkl*`M8k7Vi#)JH>!{2u+^Rkm1pzFL6dpJK7zb1dj zUZ&7Su@X_ykzP#xs1mBhyc%ir<|{!A$DK`m2V7MJB4kTEbEF@`VF35%^`j+h1G!f| z52d#-U+dpvga**>uTzwiucgGM#Q`vr1zNTu74P&VaC{XbQ${KO$7P!u@V@isMn5P) zogL8o-_Cu?RI zhsgaMO+`{Ka(v6_2fES$Hx7^+C4c>VdMd7R{&~Q8?;<(hDdz$Z#P{>mgY!=p&Y$t| zGN!Zx5~$mLir_pf zBar)S+x&i}*A7;-;G&a`vDLe~8{alCAP`54WroAGmLgezw)tqVeRDfyTNGER6>(?A)+) zzH#BpOoP?>{e~y+UKv_#3pdQ@P~CX?RiR=0y_s%%FPt^3?z7v_u=ILElrq(@P+8YF z?ZQh#$4(F3%4!E0X1||kaCukXP+`8mnQY zv429{e?g-Bnwmi7F<#!LM9b);SSccZx@1v;G;fk1DZjNMvtlG=Mx0z$#7a`*M0rCl zIVgwU&ph~=PKi>jX@b16O%U~)7%6zhKGT%{(qnp_4zsJU*RwKvb=iO6 z(~G&)S~87%{hf=c`(M|iALnZ;TlTBY)-&&oo;>^+n_qH`c&o$pEqV;N&Uv*v{T33q z2JfW?|D8TKJ((+?%g@{=gvX`9ZE_k~PG>D+Ed3KVrD0KddN59=H$x_QMru~0BIu1U zJPmKigNMwZSL1SKdf3y$$A*2LbE)TVN=MzCH0DM9U%#h)Rr)mArsE%9|4K16LH_$6 zMLG_TCP%rEYi33Z=~B~48t%50$e&8-v)Wz;oN$maOPk2Ee$>|=+RMDx?D^8#O2S%8 z@xIzfuI+6uWo;cr$IR)juC~(6h2HB`o#fs@N4Zq2lBoU;GJ0q;i96F&A`dtV@>@$8 z>eG8WIg2lO$dPVNvgehvj7d<5-pW=At~Qgtds~p(c9e}gGcI1nyq;kS3<)wz9o81t z@_fIoQGqmBqQJKS3hbaq-11!|5uiMB*`jyDIOtX}pW0s&23vyD-!e#Ar<2>rUBQ4O7{c&ZU7RdP*W|mX7s?W4aHlH?v+#pB}|u)=m2Q!CcV? z2U#mr<$%LGp zCe(~FVb_Kf+*nFJt2S%o7pb3rW;e?RX70A3S3o8DC@eAIc@}%y_R$yePBPk`Nyfxg zWFWvy>r%;3dt{^Wa@K3C$r(0d?WO@4#Ch3xUybZyy=)A9nF*gYS@_0U@}Nfah)d4G zQtK?NTa%4jN2tS*2bhw^oRf<@+r?$U!bDHGB6>TnV>Uw!`yZcVBj;2$PTbAHwSTNL z3}@|y`bb?zY9z18QLZFkFpK@A#%zQcvv6s#i`dt1Ek*2WY&P6l23fm`S0872vByRt z;3Vb#Im)AZ&eH9wjcCpG66bC$x9hX#?X{hBo~DwFL@Q~$(?PC(v69h~9OUqUrji%S z9$|jI;AJCKzS@d&I|m7@$Sn8)PU7cjBQsY!%CZb+nYpWlOcq;dJJ6BY@2zFzNC!zx zRv@_#^Eemqxvy%LGh`X&tT&7E3>oh ziFCSemZFO6>n=m@5VFIjv+Uiar(=ZxdYm>e%c{c)xb?O`Qd^E)`kz+p%*=`udOL2j zK-i9A2~m`YKiT5QJ4LeM6mzVt=nHkq8^f%8Fw4~!`#zErZsdn3GQAZez1W{k7V#&2 zO8+sp!=D)uXS{G_o;RX4F*7vQ8+qk@v6k5&J2`Iht-N3{+!w~TJ}7uke~j;Bj|ckx zFIRK}d5A~Z^g8Y3iytR^(6WXvChCUavz9;Wi#Mv!AM3#sdPG|D`S)htM}7z@kX0BO zsv*;_LA%l#to}`J#qF&5Xqa0vUxQk#A!c(-)h2V2u#sB9P3A2WG0)v93@QA(iFzK~ z`SkMKxd{h8 zA!Dx7*RcsXWpc~CZZrS=F?~rFFmrkfGlkO0BfjNxzbFf;<5}=nn?)}I=CzTrS-}4{ z!7m%n&Ez+xQ5Pk*v7>1=mUST8vN01a$}y8=5c@T^F+@?hX0?hJ+xvrW=S>z9I_EzgMF_NdoH>KKQQEazPh;b*J!u&2a62- z@~65P!@Ugk^)Cz+R{Xq})ndLOD(8#A9R9)3;$X3%chx0^)qYit+dZlqFYk0PJgeBi z*x^APV~ti#jJk504Rt?FbF01bm7(*QRfecKC)`dQdvh`WO9f-VHEq|pj8|P;u9q@y zG$tBeUYvDdfw!O0GcVg<@Y8ka+1Ak*zbIZ>M$@ZgrCzk^IJxstCl~W{(zhg5u6~FY zTeo=md_Pf2*P>oBE?SdK`VkbP}>Q zUd*nsGWBqRe2&zK<*zsisH~OgmU@oO1gXHE`Q~YytS^-)EvD-v%!e$>GQCv0?S!&% zDzvZfgcUB_1Flj+^TP@AdpKeLK%Vn!IHS`p_AUKX!Pngp)BZSO;ZG+Vw@~6f`(k#R z=&N{?eS_p1Z8qOB`kI;p*X3+9R)qR+9;Xp&J4*9N^GSMN>6ex zA!H#RQeWD(hCNW%RG7?ur%m?*fU)dJc^Zh#P1X3jMvWiq$R9?NXB-s>yW}90@Lb<` zK@fKP1mPijrvm7wcz=HoPB#z6kQIRl@K)ocAA4l|>E*beIn!xsEPTQ}AZtl}w}arl zf&0)(^nsi}-$w2OYw`P=omQi9I{$ot*#u6(%*j@x?jL3XG}ggap~Jw%%uKth!=GJx zROzULu{1ptgV?Wfn_gaddYt6GuM+ohvE>rrKatr9(-Uy=IXzppvECX=*3n)Ei>f-r zvj+P651E|>^t$rau~$})rmKlSzEcz7^^chMC;+@q8Iv#2(OI-0Sgc{zTE&`yTsV0@D$5mA%eY z((!F~8Wf|_@nb?dOh1{!>7R!7Bj|&sWR_~Jboz#+;Ylm9D4}V%>(30@dg=5EOvi({ zjh6&AA}fu@N1|KcH9YrihB}W%`oW3YH%j>zpP;TYiuR2 zN6p;*LJFe(k^O2!|D;Rg4ZO0ELjEIjRSwRK%ptRujls^$yWi>{C!?L^`JDE$RI3u# zAUo;W(LpL*x4@KO3v`##_;K1S^~lGa%~D{%K5smpGz`TNzKD1^98vxJ;Jt4c0=I`D zU|<-ImJ7$`N?};ga5vuf48yuMmr#xK;;&}RS=^a|XJ!*FOiRHiYWMqv9!{Lc>N)4& z=BjKIS~3fg-pb)FEu>jRl{9x&iR`nHJZn3#9;d)zUklEq7WgvO0^b%{;PoyA#!vHu ze+@rm@)}*A;0yH_W_J4d!l_g^a{n@KnrlTG*ADL*^!Du)hO_hN`=w36&}SwL;oSZC zp9%Zla&N`?HIY8l)i@{5xX4^(UYk_1Gp&y(#X`kwaA_rF|F)4gpY3JvB<{nPmcqUz z7U)M`soL8V2s>U1o1_#ra4o#&<%eUVe9_0&7c06C$Ekv0=w}^<6I|=AZwW<%8Qc$k z=YF$WINoeZW-lvw!7I$`Oy-)B$^D)?*O(F67!kug()VnPw_r{tuh0A+S-9QPNpM*u z?t|OQ+}`bE-evluopzA3mAO|>D}|4z6*zi}jEcVn+P5f$JA?hOq^B>+9`wUqCm)RE z^(vlCzevk4m@kFFMXkZ#KI{WHz~`x37GD21*d`$Jxz@%U3uQkC3|5RjGljk@TzM9WT+l_ zdlInHI{|Sv^loaYNA(&R2pW@)vpfryzMX+%7XT zd9d%zD;6HKG$R)E62)m~mJdKLuERJhL^qLm?fogA#4 zBr|Iz%Fs4?>Cr7o%QtD` z_0NIVMY%VKp55d=gM)FmZ!mol^tdr50hxDnSf8Xv3kP~MX7l}Vy|K&XeM(BlhkhB@ zc_$tE3uzd!i5^nyGk;pm!abfG$TlZ>OZhQxb$Ohuphxu8GDifhnfKbCxg|a5dGXc} zvCd>+-BqZ>eZ-<5B?jg(+k-q)qvd3qCQ%cbNrvYdwVnVqnm*R!3ZI_?)M7sEO<=vB zpUWqp_v3Vwznz9hYtk`@Y)abT40=^iQ(2*KFVj)sZoaB;k6o{D|FlivK6{wL{p(#j zxsujZ-u8DEOO;C2am=@#Ku@c-oNv07!lii%IEAx^vYP_GI0rT1oU?4PFRX8KPFDF~ zZ?P{tcs|&9m2(X_v}2KB*q+S(qzv-!l{oe}7lv=(xpjOB{@qN$LhixWk!{?Nor4bj za}de7aLI%m?CQnL`}Oo^yxU4NQEkL}gi1DDXeDib*hq`|c2eyIdoP)z>`Xo4)Xx$b zQjgwxBP>vZeu%B#`yr6$o9NA)dmd0ELJjf3x7Y$=35YIlV zG(N!`V=^+*=yC;gc-i&J{&tPxB zK=v^`au$F8mQvg|g;9q6g+7=})3sg3+#X5SMHX3f;##9s}yM(PhuE}_M*WcKdx++#=1 zvY6gw`Rv28&!+ziy>mO{U{P@vy3C~K@kRdZmP#3yZ6l2zI!f^`2YHlaBj(lY>C3TT zCb$CmwTnc(nEt*s6gcbVgHWRrWf>uFg)(AL6V-?*OS8V zaUOdXmR>^7N7ON{reFcjT#4QId2I?>x@O}5ed(+4I?bHI_mz>2{*h$iM>|Qx!dCKR zZd*zF=pw%~%yDhhMn2Uf`!HSs*TWXbyjdu2nqrxnTP)2EdLtmt8;g(m;C*XfBsBlRsLQp;7Tk+_gr?J6~DgwyYDwI2K0(O)k*fi)%eopVpVs~`b64jJsBNQdRn z4Cv}`FWWF3b-0ENrib0!LS{M}6z*L%D%_P_I9F%TUvG7ySY1z&{A-Ca*)u`X$0SPH z?gVMp*cma0S|IWwna1kQm`4`=`zU7|ObtdZd+5D}uwTAYFb?L>cZO@)+DFXpxv9s5 zBg`!JOu$o(4lO+rQ12Q2b9d3xwSCY_6kva@1zdg|k^3e?;E9 z4zJCN6-i>Tk7v0KiPG;;yiA_27njE>tW>u^`*!rLOyhcSPzB32&bW7ny#ZaxQ(h)B zIGgjdhG(2n!T2{n0VmY-tIXG<^;`OX>|>2^a00Y9GvMh*u5ubVJu9wZTj|5TJRSQ> zS-78>q;S7S*7Kr~^P!8v{U&<_-X7x`Iv_!2oJo|o)sM>7)=6@uRFdr0w7^jAH`=ie zt$R&pOg`<5X;YnX!G?@^C_V9~1Y!L2Ahi3c#?IcWaQQp6@Qw5X`9zI;z8?P`>dom?^;cl^xd5H98JjA`n{4ommRo2X#c4c4R-=h-D zT8M^BV`Q%+DGJd_k9lNYuQ;QLyEERg#&FlN1zZ<6qr#tHRH>lGi=}F$R$PV8Jo~8^ zsgdWZ$C_N8t?KEK@k57f7d^^dps$CLEG7Mp!wu=k_?U{e)Ydb$^Xx=+FoxH|F_r8= zw8H&5uTf+adlx#=S1C^`%O)ps-x??919bAxK`#-%oZvfLg+{HE%!i~mbX6t1YCGcj z3HD8_{XeEreMgP4$9R@aq7QR4+0M`OE%8af%&$5OAD4hrWKmOZvVPc(e$YIRb-tDc zk80`kGRQ!bkiqA=KA(FHyRE!m?By8E=lZ`|*nb~ZeJrI~26><7-nd{Ff+_3+3v8c> z=}jzUO!Yz;7~z3z74@p>Hs*Ad9w4%EE-|jm7;o{mZPqFnn7G*+k|M7iYrbc~dDfDvv#veQP2NzmEE#zgndn%9+?+?gwA(Zk-5o>m^OX?|YGz@1t0uDC?w_RV zJyGgW2nO8?D)!LND3&htSUBj)_em{&OaXb-v5h6QMxiug-t?Ctp;*PU__JG? z`2CxCvSa^9nf0FNbutv{b4Ik{>tq`(<#6`@L)uyYMU{tdf52Wl0L37b2C)wV^WSEZxC!&XA?6pPCsa#h9%bmejD*)b?Y zmGfB4-EL?jy~tx0lYbl^z-L>p|K+xQ$?@}?`HxD1enoE~@MdJL>8-vOtaJCkm z-RAV@Ju{P}Li+5;b>1PDTH?ffbCW#SG`5gnb%m@O;fqeTkvQOzifugaR=nQBc9zR( ze$FRci@~5j>a;D_Ws|ZZt=W0;(YMd(Lj$TAGTK zk$IeZ<8`#AMC!NohN20*t0!2?-AF!^xyCE67l~;dZ=B%qpZ#2q^DB7XueB06S1h;O zeDIHD1a=hYQC6EC$!E>PwN|kh{_@7BIgv=|!TyXB`yFkY${Ky4n0*|9O!AC_caUR^ zVz$*AE2;cY$UTz}verbxlN@eoQZCNFZ!Vn!nLoaQIq4h8L6e(KBd44iZYM<-d4Avc z;7J>vmqI-nT+c(}pcYbiw@6(69)b2FcwH}GoqJaqo>&`8%@qSCkGc_ILnqIqf~m1 zz~e^|aI++rx*!)XXW2-8e5tfg^+nAc5ilqBU7+H5zu#Pj4JnnYj_gs;dmEdrN7ORr zYj<&!4UVPqrjs9P42gglKhKww^HBR{3+YIHS=rqew%m`-8kmZjW}N$P$a39`MqOIudl*(0>${VjJMuhXyW+de1}r)YXe^Z5SHrK0a5e*IxfF+W{M)|9=? zsq}9)O@)fTZ{y`w@*<>A0>As>6VFSFEczl(=c4#@3u!Z;SZca4PwQqR0(|v&T$#%( zf)-?ROJyB7_sPp6u_9NG^e0QtE8IIKbRow+(=_n0uuxu?Q_8yRS|tP)>tACsRQ9Pv*lC4%a3uc2Yi?-lyI z=F<~rN-yE}5JaCO2ULarwZqI6J(MUn%Iu(66M_qaROqycxycokQ2EnGO|DQ@grX0* zr{1H|$x<3IJt$F%=ueE@77XKa@=CQcFk_q%u7Ss7<7r1sn;nb=?BV-Za$fFLC1*U2 zai+l@ny;bg#M$KT!m9w!S=*yEiK`Ox=C|C80&eiglhOJl@muRSyD$Vp97<4XNZM0cc@ZD+jP z{KElf-h|K-slpiYM~**?81ng;RM|p)?Rp4vy_2wF0{2rkWSb7zI%*?SebhG)RDGmk^N1X0t=8Ff7r&wW+& z#xvJ@hY^?dF^~JcJyOqwz;!7508i85TS;GJK#Z)+vZwzi4A$fvt=DFtdqE|}9pmS! zwF4}xv-h!Ag@h@Y*m0r~Pv$2`8FRYbSBGNV8x<@|>IOQZj;4zHu4qrn(^R)zMB zS;HGap0P)qTzKV(r1A8nJ|QnQAph@Q2|IfVO8uSU)ij`Mx zPB>p94FB9vXwZ?8vjjaF(ffFh95CLuWrB4{OI~y;bp&+m`;p2mJihRbh7x_HFta(eQelyn5n* z`wf_99gu{un9$d-P0YuKKx9 zY&B6KQOmse6rRVTcv;KqD5rA>^4yt=^N80)ZzGP^j+Zv;c;841Mb)m%gXxfo@82si zm7HvgP03% zOOBGSzrp*!$T4x!q`m`|MTB8%eSS_>&>KfSbPb&^KRP&}l>GP}UUyr!Wgs)qh}dUb zkFGgjB;BNm z%P%i_v%z!I?vJ`>W~Ta?lmFDG{Ozf0y8o%JaakR`*I$3@77cOGcRL%S8$a=E&lz7$ z^p8z0>7FhcsXuIALuc4M-g9XCs+Svf+n_tUYNKb9^Hw@z$1r_O(~h1dmpgfsulrL! zc6?*qf!qJ;F4qXZw6oLs%NOX)Ng>aedrT!Q7bS`LnB$UjH&M=9P>Cn`#-|$+<=jGz z^#4Lnsds`5nVuvIKXcZwaguDEA1^yEBuT8FS~g5%zncAmPl`mT@;83X(MmJ*3Wgc^!>|D_xk`BlkuK4xX2{s8%XwZb26wxkt z|J)f(In#ONRw#5)p;+3Dvy!Y&`)p;sYHKKJ^I6}9vk~Wik#}W(dd5U0x}0I%dVd&x zc#^q($+~(iGP_rlu=~gyB-TxC_f+CavoPdU56Ag6^!3c;-#M$qJ!d6$&*63cXE^h0 z!%*SQ&+ayQcnqwOC9x*X+SG1aCGtF#SjWB5yV@GG`=Eg(dnvVT=&s0MFWQRUoG0Y( zn`p3{z2@aV$s7-7_R}>D8n6a&H%N+$F*HeyPu1w-xvR!e{+)@Z==7PX z#{2eGF`96nn)EE*3+P(fcK2^YW#VEnSNvyhq4yd zK81PEoYyFt%X-G)EL`8mJ=xG~__fbOI&1Vhsxc#jeP^>Tnds1sb)hGjSjw7E%y>F? zqOxFb#x;ZWtK(joSkQy>x&O^BD>Lz%b(;G}nGLm{f4@8X)04<>U&zF8YwmTdvM}Lg z79Nbu1UhCizs+8(`?r+@ahBL{H<@kYCVQ$nN$+NMGP8=al$zPd1kODEeZgKnY-lCj zXWB_M9~W^Cw33^@?8JV!gPgnNESriPl)^hT!y}W+h zMgr-q@n&t>pR?_+EZJ-IvynBm-NfCtwQPLMezduR*mSIv+EdEJzqe5itmm9!8+sK} zDp>oklp|M+@<)H8Onaq3@C>8$t5Yt=nk%3@Mo<69GFjNUTt2K)V12hTnK-smt~r~a zPhE0X4(yXosg$oV%)`A_A^yKB<&Vt@9R5aMjyHXEEltR?Gpl-jr9^kDklqoMa^;Z% zveE?ct9wnVo<`j*JR&+12 z$Lr7f(U7rG_{LiG@HNc1UBo(86#a59BVn~M8q==RyV#kIxj<%5vlr4bggxr_l;&XF&w^^WT^8Ym3%LqtW1K)EYp~KnDY&M;UNql>tij zlxuAjmT!8riYW@+%FiJPc_1*?^>Z23Q&la34p% zPAOT)v{YmsGoafKIssx+(fvE?9_gu=-H*@BW@)%PleyDB^%y~}OXru0kF4iu>!hLJ zUjy!%{?}LMGvZz{h#}+*?Ab4F#Qw+@G6=VriNL!1fVK1+^vuWR^LfZC&d0tf1-Q$) z)4J~Y@Z@Wsr7=7A95bFe<-u!k9_CsXVAYF!W}4-pK$!>YbM(r^=Am5^_N4dZNX0B_rGvD1MqgtIT}aHJ+^-|s z!8%=mC9j*}3b{XxdG0&PW!7Z{{VPU!Raq{3(-rU`2Rwdqh0KkslwBW`MsFz$eVIWy~>^!b2Xc>-{hNJDSh8pNZUmU zY>72Wyd&MK%$s)2QQ%2u_7L~_BJ!gjEK->fwurgy2LjN`o}YVizjetOzVP;k(aayk zCH|=M!51s`^Sau@8sJNRbgCM_enbEokvYEgmp?A{VK#hi=CZw`i;MMvBW3=q53sM4 zO!sMje|+UL`svH`VD0zEb9ZKd75d`PUqJ{<wPPjo7 zdW_*U$$nApE4sgU-94#FXX>OVWb(C-0-~^z|KIXm6e6y2W;~Jp(@o@#hesnq8I7I% zJIiX)?{tIL*hkKnvbNSL+kmr5vcJyE_~iApwiB6+5xjOP=w2B^H`Q5wt(O7cs;A-X z83W2E8-THCm_Cy}l-107<8`JV!fUk=ugz2B78|D`_*p6@pG<` zk*fh-ymng@@%67$(QCAUGYssh{m4h%SNV7_K94Lj{UsmxxhInty_P;xW};b>&zRSo znP_eDq4~@l>YJ<|Ud=-lUW57vtflk+nN8&EI{!{A@;P_PY_}ltLB0hT8kC2P3-YjP zTRxgrqsQ?}9$t^+b#ycz)_Q&|f!E+Z{=9$qx~t5cc3-SxJc<7Lwk*#%+iPF8od3c@ zce=LjVZ=S1`?_%b%IZ2@%iT8mULN&58(iwCAJF`&?$E3+x>kOhbTw6tJ%)c;r}J=` z?%|WYMVJ3-y@&U}Q@Vf+or%Gm*sl=zNTFgdsrm(6;wsL=1 zSeHKT?P|^tsn~Cemn+U1u_#cBJ?jtqdyq#os^oXJO2*w#$s%wzW_q&h&EnrrPLgcX zBq`s-IZbt%jN|vUaz(qw&RG4>1u@(QHmO5r1=$IZcZqxF zjDxpb5WziSQ13A8cUPiLeeUzDnJYPo`?tDbuwY-)ezX$N+_x?76ppNY;bd{>C26L_ zm~r%4^-yB*3py4jDly1`E{>*3)E*Ry7sA<>+05o(eW1sm{643YSoWt9uGwLTJ;HqI zc62pb)5GW(0$(-vl?}t;)HNKRxyL-di_e66)wq+O#)NRrp^)8}^o@**AH65nG}ymc zO-C&KFzk)l|59VmKn?Qz>Cv*_Ow0fc6!q!t{+BbZ%jxarY@^3vdb)j?ZPr;0ud`}Y zyQ#+MwQ4kZ&Hn5;HS71x(L2l8nNU7wr7_$34(llFw^hmEeA!ZF4Ll`3xtzImAhCHcwekb0?dq&%*auX3Lq;#p03$PwwL;Mlh$9Tw`n;=Tx{qywNZl zPf{{a@R~D{37K%__f)gj>Qj^19Mzdy(3ZXw`z$Q+qTgz7CN5v+JdBR}OFOzDyU_pW zPcE`L_mk8AAJ5o+qrIe`bd>qmT&4YUH+j*qv&{WsD?XtLZ2VOwBk5%zFW7+h zvyp?-&>_lzSn_DAcJbOT&cm+^GS3xcpXp5Uos|#gGAH)Mm@#ecDE^z;OK+o{EcoCi zH_n-08Xa4+>d?7eZUV(}u0>=+{)rC2mvleoBKTnf_gD35=362D7s5>FQH+I|I+o0;OoBf7vQn6M5;hGs(mu3HCU$}M`X zS_NX*s6b439Ec&V(O7wlp1-NlSkRq(%7bY9nol2?!hp*8Y52U>z~_!M#H_f&%ohVD zk^^6y!h3I4KCX}pDR!rWT0`bw5FLn<++{{}XNllmd(=-CX?vZl$}Cefse$?2hky-_s1`9W_L~s!s!ixaOoJ0rQ^xV*wPsZI;F^;wy4ehpD&ry zyQ%ow$o<|s0|M5j0i|T%6Z0@?Q2}~~=VKy|OX+jYe9S4p$K9^d+p)8l)b1kJZRub;@@QfBqGEiwoETJYayPAM>v(^YL$Ot~sp=;IN3F8}9L{ z#TKBSlcU@yv6r=KcX6uWC@YxV`S5dVxmvYC?#?j5ja~}eBX`;$M!|kBIi5#>_~T9> z_xyo4d(|Jq?*&5DIRMTEI-89=R~mkvdG0K@ANZLPg(&h(>p34V>Jn#sxPGQd8oX+y zA!!$ToCi5qqsm8ouL9QF=^P%Gk2$^?*)=UuwiapRSB+%m25P1EC$)_F(+L)3yhpEf zhQnTGT%PI%Gh1i;T*`dl6U>~BQKH7PaGbFT$3ay%Iw$iPGlp|>e`>KImu%W&Ey9yE zaHbDvAMXnX)Y<5MGYb=W?RPm%PtjcZnp!hggu`8{3ghfD-HdIN5RcV(HYOY& zj+4)8#reQlTKW+=4|tFF$ZRr&ZhXEymdW`Kx@ccyqV!27T*!pnT+3PejpXylUu+nu z@Y-5TXAT=6BC zp1*}kbi1L%0@e#k28HALrZD_GMFym;77e4-7(GqP=W{JO{$!mylsS~E=x;hfSENlg zG6wT`+%p^7SqrP0tngBhPg&lV$Evo8S7Z9EUYn)JqRU#j@1>Q9M_LK{%J+6%E9$YX zTx00ZoX2yO#dYx}^Dw5l;8Z>G^UvrYd(D0U*Qkqt+U%57pxGGYuw~ zk!k0e;Lr2ZfK27EZCQBOp6uz$EEH~JF6C&2S4u4tuVcf>snF3__dlMeMB$Z7o=ACI zExjI`kP)vrXM0s8ZpmuSCOX5*%mr0LoR~f5g4-uuF=>k%o|uK>;{0$-a%4v4StaKd z!qJWAFl{dVW2|FL)M;_^Bx@$y=`NV9LFomqA4ADA4#~pprCFG_m34=!L#J@WriH_cOwpH5O8hZOgCnfl{G9Y(rUqH3Dq2KZYjKM2r5}I( zU_&O-xVAYqc!F`CnMc7|@aTQ?DYRF3WxS^2ig~Nw$>+wowUsKToMm@ECrOER7d83D zj>FvKBA@$jIV$jJt0@w*6j0_@h@RKG>1n({ z$N1mQQdr?ATO!+teP(+(_sUJGF1M4BT0Uo;Rv^Q)QqoTu#ksZ#-bV6%nB<2xy8{r| zkB)k-9ecBaSl=Swt%!#Ckv-UG8-+a|qmbhqjRM}IOAe$lyUc*)T(@R(O%1_C)$)kOh5+u~B@^V21MYX!u!1BaH8- zpPtX?e2#Hgn1-lzY4B;3hQoYr*SF%@If`pKp9um67I4m($EbDz+PJvM!L=Qv@x(6j zkTs=wTiZ$1;7(%Nw+aUH-YioT=roe7-t9_e1~7+%nb#wF_`~UtKSurZhxP~ExdG(y z1EcXt$iLr-Mzohz{p(pYh zpUoC?jla(|>=jwl+xeIrLJwkcJ}&aSSs&paIz0!a+R4J!t}-{*S$49{uwh7BF>g~T zZf_MBzok;@%~hanCEZ%q3K(Vv;kkI9X2|(k9-oYL{%FAC^Ym3TT6Notb9z40 z^4WA=y*(Jo&&~)xuBEnDkij)x_VK-4=5cz@{E9H{fqHXRVJhn*;8xpqAc$LSMF z94%4eyC0n^$?gMZC$xw*_1$jwrk$ zPIKM3tnf-F2S0-SQ;T<6*+CD0C7l9ScN~{hj%qo^bv4k9{9?KjI((#KzJ)WA;D%*^ zbka9gqTx68vb1#gb_iz(57>(v zQr#8Oo37eMZU}wpg316_ES~Lxk#0&<`Kg4C4E#$`;sBp#>J1_PIaq@c^|i1ati>fq zEo|m%aMel+`@&2ljLJg)nVesD&c>BFS?D;2nTllJ`*2;K#`|&!|8)DQ@cI%(ZtwL8 z88lxbSLP?l!G0R)`-|-0g5y%-kqb`tbisri$1xTkap`{yan}=gsZRR6gq6cV{ z5?x;^(JV;G+$Sy6ff_Wur^WOY^j2nQn6<3IR5GW3&d)}cR~E8(zOn~rY+nyDUt+F0E2{b>OkF-@*4qmvGLWWXZjfB8AOVVo_Tyo4%=KHu=gc>@`>paK?<| z>|+GD;7ngS8<&M+*bF85MJnMvMhVkGo-58#jOR0y=`uc-jpt{kj~0_ZY7n$TgD-tJ z+x3a_8)LKJ-ktMax3iF=eCCXvuPe5$b7j4WtSEfrqg zWIszL{6C&Cu9~@AaxY{ytv8O5qtQArM|esOes*XfHe1W3)oF5n(Gh6-UXPtS^YFN= znOwV7CTD+>6SRrIvxcnWtjWc<6;0$*onMknkKyTo5ePhHfUPkHCDG00!8-cptbDNd z-$?8lPkyj%F1}Z@kOpSuQue?bQ@%#RxK58y`#g-TXek?qmoPKN2PNdQ-rA;O$E95S z`r1U6{VbGyEq(D%Xe2s%vsSw!2c31zWM+1uG-~6G{X-*hmmE_@MlO~)Tg!S4IkK1$ zI7=RC#Y8<+fw`D`wUyKvQ!bB|(BG#cxAl(PqC4}QlbK`Nyi^V^_eRTL&IN1qc%DX{ zu{vMhsZ>5rU`}gsB&I3#_;xJ^mzLF+EL(D*;ePOOVf}7!Dn^q}Y&FtSCh7`hS_X4( zH%FpMZF(D(xft2fTHwq~8F~rl#{I{Q>M)mF&)rrn<>|p9NpI(k=G`LkXhbSTUe3c{ zG?zJD%O%&8HA}}xY$GSNx+i^bUt3Dbl|q@a(HoT`BB8Fwkm|RJ#d4V++763AyQ6v>eUgjd zzgx=eH9Wsdy|Ia&yRrN}BmJ0@a?x6Dk1v;-VLmt*$h?`QshE|X%k07yl6SaRcD?t; zOCFzBXUJjw%EjfXEhTAAk<32hjXL8a=*H9|;6xq<3~D9cElT8RZ~EE>N8qvtIWLbq zyfS&&AncEoA)#diKqI;mY@OzJ4mc(^8c_hHVpgAeW;jX=xKI(*0{|24>3`qnL#U)dvYfgIm_a*+xf zdiQ?NXJ=g|)pyamH;kVv2m0pB^Dt*)BQfn=D#ZhRV8>eR97QU=ea%Hd3v-EO4)wQT zKFnT^gkdr{L~@angUw`!N1@d5_QnYEuulK#5z(CWO#5bX-J(=}_wd8>LlJm-R*$;9 zb8#`cjl7F5lA&rJyj&FtH*-DA2haZ?{i{<-A;U8qrE-buN{@ z^cybO9f|D8%%@Js#ryH*(maG-&Y3=_9YL>OV?BaisHMlR zD|vW>7P4+(sSM(EG&GkSXbS7V?{cy3TT|IRxKO5(4_!DS3ZpDiv5eR0&~r`Y=HwE2 z$n!O)7JEe>_&(R=V!01{46S&4+W3<9Ag@;~6`K$6_`5WfSu@JyO$T4xoW(rrL%eT{ z%0n&YMlJNH5X)#^JXsNmFLYMu+U6kac2n8Wgx9G#=OPv`vx}Tsa%m2x=eLkX@#QjU zg)f509lNzjMb~dR&~3Dms7-~kmUVZj6NxjK^c(ic<;=aMTx(Dw?U_G*o%gZcr*)ib z%EjJ&w(|9Jsl4mui|ax^CV63xlYIY&t>w+zLQ$ywV5k*|tLK?FT|1AnEmktrtw=ia ze3kP0{o0Fu(k8iNugsCLdXeXa9)0dG z$2`tLTHY>~HjS9=^ltw#SC`_e{yyy(qb>x1)+m>*5ohuS(1t=z5T{r5u2OY=c5+X!@IAFlmB zyq{0DmznQNr0dTS=#mmaZzzxF=N#;FNh;X?la3E@Mywm3BuzisV`=SB{K!Z`mOK57 zft5HSMKLa~DWwHN8|k0(#pB~f|}azvl(Q1)cV&GpDYGjf0RvX4pUoAeu| zGuN1Vii+yYOPov3n$0n}V{~Bt1@kC$@+9?BLZo6i-=4K3$*w!3Olu zmBfmd2R(h?!jQ<^-e>gR)weJrea2C#zR3ZzqC&9PUxndO8Ax15-c6Gr2ZlLda8d{+ z1(K(mlY#ulm6%r$FHZ+MU_bdd%RMTz9+81x2aT*-9h2%$>@jyAzrHXDA20CtB{y1Q z{!uaK`|%tZjEoN|T-0Y^)&TN-n_^`KIhBs~!CY%p*!4Iao;+XWjS}Sz^Q_Oik*{1r z&XMO=ai$WDa*oImCnvI%Ay~zH*b^1$sL{-byg%Y)W1JnfwF||Uiz;Y%9CndQD%=|{ zpZeRuXXPryk`ufhK+on=BgR+6ib-92^vGHThviA+`7&YF$O!8yv9iO~5skWqGIx<2 zCC~eg%awRtB~A*bIAL3Fdi``NELfC|_2f@W>6N=M#Q|ME2V;Is*8i-Q;e+HCR!3y-Dm&D?8w{U+lMr5#fy!Fs_?+UTXqp4UOGDr}M}?eZ z=4c$+gGM`@v{>R0Z2qa-GAB2)cPxmb7$0;!t`{3zLw^ulL~f z-qR~V%zd1&^L8ja>XG-Hnt_csj3~YnE9<`5BP=VJsx1{}@%vX9Ys9I^(e7WtT z1dkQ}G|~51u~ENwqLW^^Q19XGS*|`%Za2S7z$W=I_<@ zshXmjxpkJ_cKTXftF;p@*KG1z*WM<}qxJT$p1(J}(G7O2uD@j3TwfIRz;ol*1YJSh zIFE$Mmv#Bq?(0hbYM@`zVVrKubyI!#(;d2HtlMm&C(++5Sz^v6N&H`lGFFo$)?Kx7 z*)3VxhpOc>8O4|hDhZmWmN@1BJtvo_Kg3MH1Ie<5z3UUKGdoAAq&HoSk3y5hvs<#X z{>Yr_iyCP^FiG|*RWgGfNNp4TGlLGseOhUGCP{9Qlbp&vwT0htab)kh;U6k#w%7%m zIYXH?mptJY-k&S@-%jiwPj;dI+67OO=}z42gl3&x5y#gmf}GHM19PJJ|7QDt-UtO@<+yxyEaGl-4y1_tKykrmM+%9LluIY^2UH|33yC7-1Ggb~|or8ZO zzd54G6GvPa?Tkgm{22?B$f_HTD?RA_)rK)6J`5(DGcDT5+0KPwxHm5ho5`}bjt@gd z3VFuiVc2z1i8t&!w+!OkC+kUf9))1x>o6>D8wRySIGM{(*q*0@qOTIq*tfniISl7* zm2~{jDazNY>(JxKe!*nVP~2^z#AwbKL<-k&SJtSi)2qY#eGu15)5c^NS)+f~hjWsJ ztShLQ0TG~vcNVk%x@&R!DLucA8mw%@e)e!JPVm0tmPl@~4{IXBSR*N-ua*6WE!_9S zepVqOh1~i%?g=c_>`|!E<1+VQV>LMSo&4hxW=^-!pw)U6mX))g(~UV>?CTWG%E09Z z%#cpYgzqb^#q3us>z09;l8O93GBIl_x%~54_?W>y^+P(P56~OonuSqIvM`o47~?+n zrmJSbHaipV$R=9d;~c_i)@NADQlH`BiK4oAo@99^4 zve3^16

k(3eUSN@wI2>xvLzU?kG7;9mTIr zYq?f#Ex#T*$w1bd7p!)W?5_4=H`i6}ZnTwjD+l@2+fIgsImyk%E|PGY891vPWom6_ ziLr2!PN{Cv>ye$TUt%qJlkH^iTs!${XD?BG-6hYbjZApdTIOh(L;FgB^FGX(Hdi3! z2KhymQ5=?4$k%A*PCr#((gkvk&FO*jP~Z^1*6gn%`Da_H zv`kQ-`X2$PwVRAofgf(A1R#L?;-S`o_-j4;3JF07@9l>X*ZomtJKZ)t>5Y5thq++y zW0^my@|myKOlIP;@44fLKfDjnXAnXUV^g~0d;`$pOaRR0_+#^YKj>opG3=)==UDyd zu?xV!$^bkgU)8DDANx2H*u&Ew7PkY)Q?UOY6U~_$a!`l)9CeqTx7(aMbSF#oo6g2r z(YW<75>hL2!P-p4abZwwi&3O=VQ`E%7#INXFj2=Z7VqscPHvQN>2z5ieI zF`6*ns(}HnEtsvhlQWWTWT{T3!oDND3?0*O{v~VUX3WdoXTXfF?9G$Yn&Lt?!fyi} z_cmbAs8kHRlZrpa8(3#%jqOY-`n0Cwrg|!R_f5sZe*77Espz;km3w|>cNB2mEP#EH z>S=Ji#q4V5Ja{gkcX2#31lZ$mGMn7h`8?PSW>yn>ImhSbWBm^Pvl+9kN|=Gm{zVsC zG5}#kvQrkT=|!kX*Bqbs{j&0~lz->OOuoK6 z4+;EU_2=i|5r3ZQaX#wr%twtubSZ4L5xL6;t|9Us>79s~_(2>$|Hw`|K*mH#kc|RePC7Zt`bOH?iK`TF#UGP(F5%m{uk* zl$gLf-Y9FMjk5cy3A(x(WgdI@hWG3fRVDN5P%b`hM!9*sQp$(Z+sNLL?N$X&3{+sL ztpZ;cC=m37T;fn>eYIgLt*8IZT#9cdYY=b zF^|*U59O!)k+wSk6+c+RSnH1vZ(r71{jkR}0Eg=a;>lI!WmctM#fE;T*1l-(?}xr) z{P3iYKXl#wU_vh0PwR&U!~781pBZJWomj2*!@~A{n6@Q~_g?k}XORQuHKi!vtn%R~ zZ09vIc`SLvEM`i3@mhPzEQUX$@fUkzQ6r);V@?#ZO`|YD7X{aNW^iUpu}0Cm z4ttKHqM2L6evy_LI}M}Y#B0`Ih{C>^{5pB#F>RR_H-Og`|NYZ;`cipKj%DAgeo`t{ z_h3d)ce)u58PJUEp`|@%;NuNQ=|z_0oB>a!F-w|!A>%2(H~XC5 z@8%(b*X`@&%4^oqiaFFn>1;gTPCv2bV!dJALEYo39=cOUPU=jy z`{_rnX{X=WZ@1^!HeGdDmz(JtJ$k9TTd%+FpKF74mg?%gx}F;5x$x%H%RlQK*VXfN z*45m0Nq6_tj?1Zk9oMDYZ|(WVkq4gd!|PnCJ}N-Jpyg!VYUZ!f%>YR-v_kO zt?2(o_pH@1-Q%uW&vnkrb!m~`b@fX9^egf>ccMrZ&VF+;H2b6_YPIpwx$kA%) zaV}BT_^2hKmr8aHQ%n1oYPsc~EHn41B<-M9jOA+Ce>PbrY*I@DE43t%e?0WkmEL|g ztTND@IMf9WMrVv9^AR89f|Zk8@VW_epmQBjZ#Nm0pPWyt?S$dcE*Q(#y4+*$rjH9+ z9&w`c)EVx-oZ#M)JuVAp+-dHDT7Pq9MoEYFIVXI);|P5%@{UhA1GC))3w}70i*Q9Q zXSc>}q8Cc#ggP6YVeu^#MYqGy&?5|PbHnh7J*mx?$eH}5WR?gSj|Oz3EK$Opd$&W4 zln5dp^L#gX#dAu$>&5-z6*?H%+6#W~bmmu=@#pY0mfQI}x}UX?-Sn4n2Il=$x>i!?W@Ihq z*I_!mt?B4y|1JI+GZDD2d$);y7Bcs9ZWgARlO;*aLPhN?H2O0Wqwi&+@fmtzj2YNw zl8pot&cJYgcxMftj!41@}J>Vvas-C21eD*!jT&EJRacdDl$>yeFpw4}8hTO;&t!mILK3(q@dSy!x)dtNjWT_g0{?feETN zBL6_HQJc+q4f_D}>==l&#erx!!Jiq@fmrjNvlfVkSv7iVo%V3v~ZETv7M#G*$z@+ z;v^OmTqJG+9TR7`f8!by+s70`-)lR9?{^eat)uvO(h*4qSl}Bn zpK9hz_oOd!6#beOfr#i9h(Nw4&+BA(c#PV7B7;gEWvJO6)>@fsdMFCDmXO0JjKY)z z@;h_s{?gEk$bH@E_hfg%({MeHzQHdAXhJ6B)sH;1NGw2G9xMM#PO^EgqwF(;(*r*okMo138=Z*F1F(gR zOrzo`wBbJYU+ZY>qgV5yp7S@?*=J~xhMPOmFn^FhigS;3BogrAWY_Z-)e3&H21j=ZxapY7_RYE_rSe1`5m68np}@9RvNHl zPa59wYy0^5sUA%RRmru^jJe$0bN;)DzN>X=nNQy9K0Q)<+MSSlqmN7AbY}Fdbi{z^ zPBMsr4$rUW9N1xO!a*d@L z#I+%tc81S;1L^jkMz)|QvpUnr8EnahEi*~d$qrs36Bog`+EY6fUj6Tp2kU-Z%vPvn zS9{huIws2jzZ2p%VU+m3X{XiGyd!lJl9p`%We1 zMup=7S(K39bljSeO9|9q{&Di)?U{X`&cw+5%);qT&lc}r|G6U9l2IARfa@OA!TTZj?F~k*9PmsO8 z?@E6#>kIZuoaBAJZ^v+?yd*1Q8;-R}8qOVQab%MgwN}#MRFCYSg3RSh<`#_0=4-Q2 z$m7)MN*10Rr-P7eTsup;5RcO-Lc6v4<>eIK?Dhr$QGEt!=`+0@gs&Dw7D#%zi<1zA7cs(JH(W}2k ziv5zMR}yo=xo_yf*@%=UWHCCqpjrtXS8H8S)RJp|A2<9v!4=j%WGX#aH<>~&a_w-K zbymXRY&fcTYM{&FpCCGl`>T;}qD2>XEp#23t-6`#CpQyg1L^(xhyI4PSr{^g+0tZo zzH?SPZJ5H#_L~vH-1R0>wNcv&sb^c2(SFILrj}!7q%j!UuOD2t?fleoRr19ATmv} znK^qS6K8gj`5e#8a{9;4_ELEHI-7XCxTNsf??m2-@2B8FYw7aVMLg{~O5%+U(jv-P z?9RH0?NkMt&#I6X%}p?Dd=(T<zC0Fy?XfLNl+mAj19yaH^WRegFm*B4EKhRyE27chCfAA+(dZq;eC1yTB>ynLf#(;@G z)6n)l=k%-!puJD8Zy8;_e;05zgU`d`+~lL9vp7t2l$u_4%vN@giMO2P4Ee3*WcQ&su#ZpsKEW1AvdsKnYPYlAXM!YAMl5hMFh+Ew_1E$`C69v&2%=h)|RupFO zPorQ1)Z^1oxtf{N4r#E`8eqe(b*jU;z$0A4p6BDff!_5^1;}2@Jnkl(-<#qhS&1Fw zkDa#S5#%B|o3_#?P=Q3=qc1J3kX0`fDB{}DDnWr|#eT5#3BairoNwz90Q(SsY$y!i zTnV!YzeZzv5%0?vqv>{!MrV*WzhD42#kl_1KqpHYbbMx7nViNvwK59GD zWf`827_RfaKcudyQ=g)n{^S4o4yQAUoISsCstap6na~@|q z($mwB+LIaG4f(9JjvmBcoYVB6>+^LU#>D3%(%n@Y?8)ZFwv)@%U70`PE`7hah=S{A z=nMt?8=D}sohgQ~-eu8Pfh3(j;wA-RK4&OQ&iW(tSrE=1@W+_G-0zTQY*Z43y%YAJ z!Sra9HQR#=;|$2MO2ZJY>z#X~p({U2ZMn|RPRhg8-~!aH#d=7;d^9+bkINPGGaXgQ z;Y^jN`l-aUNwPGmsutr8y7s!W2HndUjV|$7!GsR?0WQeY(fzlAJpKyu5!G7DGCxOVX#bSRb?y-O5ctyj_q zOO`q?Sm9OUF|Yae3NPy`8oA@7l|d;dq~D0+lHzkhs*^c?_SOlt+?|<4PTxGeh;}({ zSRFu5{dgsmF`SjMQ=;`ku4R1gsO!LcbVn`XHquucph5i!8tmJsLHcqH;_op3<}m$w z(VPv~lLaP>U&&L+Z>nJ zCu&h$qZ@LJD`tIj;U162CzrgXtt58wRg|=TZ zGs`sy9>STZ4I12w&%}DJTUYqL3ZJm2Ixma$$80o>Pw>?9tN{5xPDMUc17ubeGJ)^=e53$8r=8LVzC8h)%fi5 z*ee?aVSHYy$imjytf?Q&#OnPDubLwiUYU(dyu!Q`UT4e|UTYUByoNa^NzJ+%Y0a6E z&h}dAk*pDic)C8}3X2`CcwNf{IvZC^h;>2EAy?cICE`Yfaqct>^ZSQmR=>z&c_h}eUK=z)`bL01BktxfB^{)){Yr!lg`i{?$cW@s|N6QMX z@d4y4IZyF_pTqv#)k>C}DUv^G_+WH)1bPh9V?q=;nnzZ09D$y;NR5 zC#U8biT=fUd<>-jvA=~Bg#DCj6}~W~FYLEI6$7s4;@V1UDS22VZhSw-yvXH!rJu_$ zA1y{(OZwUp3A*EraYyL6W8Es`S1wdb&87U!Pw7$Njls*9m%UYw*9y+L2ARpU?ZvXm zYy|#l9*I7KSleYS$j_0v$yZC|)*^4XHjTorJ9B!D@paZ~7d^iD;^ z&^&D3VJ;S{%Vg(eALPBDH*kL{V#8UR8q!GG`&LL@8z0o1$-4Pja%7X3Yuw&aPR}oq z1_Qj&fWOz?7JAGcNMGSS_9#{r%e8gP&rOQJ#?|DocpSo4w2-1*mC`iA2kkr4cUD)A z;@!E}J<3*eFH7X*zuu_%kn_*Kng8oWFJwS-Y5J@}-YsD6OtnbPSnClzHxG-NT1qE! zb2T%WYaC6^t0TRB4tbo9x003f%4FS0UwocRKJJ(vQ%^AmIn`Vq7L>@C3EuE2jldFD z=IUnWB4|}p`8l#gmL2p%Ok2)ef7Zj}O%9#HP38WON{Q$B{kDpE;x_dCz01XdxK>i1 z4*Eo$FZQ3OBe)i8^W>Noezg!6@_O5+`@m;IBwU~H_nk;Dz?T-H_~(Z_{pN$AX%SF1 z(c@n8T%6n6TxJ#(OX3J}tc4Mn=|z9vw_MyN|5!=R%MeRG^jRcAtLkAWWnOj^`%G!2 zV!MFey2g=+Fw-N9JYa#3h5T7mB&h?K7aYfYbJjK^ALsJeS;{^smawLNI9i+Q^)6;I zwP$Yf`bIM1Mxpe(=8FqAIqywAYfRT%==(L2&+W<8n$ZX6#=LKGWbuFJq3iO7VrO3> zM?d=F%eDwy{h~v&wagQ5M33ZbW^u*%pdWK`*EG=MYb-h0dUo=qaiO@H`e56H2z=tt z4X?s^vj|%m+oVX$#Se3y?nVGP(8pu*5PGS(40QM{W3G%q@h;{I*Ga{PCV4n8ys3o-3u)S@ zM7n$M^Z6)(b2#Le`;re0vyxZC3gzGdA5_^LNxwdQo%_k{4z`r~yGvytKUZ}}N8(Lk zDke_PMbQFViOVmM56p?a6&Zn$IjQg-$U3g7x$L0R;JJaHpH5L|!dmh1j2yh5%g=vl ziS!=oi>W-G!>j4Bu}&_ZY0Tt^RjCB6;rkgIflCHGa*y-t))wM+xLmdc_;9v3g1Ir| zDBtt`;9w2kc&3Q50!rKvdQSy|1yG2D^LhTqW%; z7_ftqnE~u(hOj#**IZk|U6YP;?f1OSIe)8E_xs}SWuu&qOka#~5Ku~eQm_o6E^3^&aTXhF``Wxj)Ss#_%echl4QJPfmr8}Xuk9&$UF z%eAp(@*>6yiRR>IXQwdNg`UKbEu`9o3UR%}{I)h4yx^K`g%vr$JMAUoL$O?b>w$wG zH8@@`6;3B}F|t}~=28?(o7tXl4-Uud)+reI7abUm&E;owvCI%JOgJBo-dl{=%(ErC z95V@-Stx^&ys+T!FuXWrM6Y&vsA}6r)@>=3(O*1q$UY1WLXC)dk&DUXE_3de%eLuW zbb|9ff0u%o?tJdvw3XjJ7R!`V9=LcboLOi_Jj%*Nhl&=Gm{=;q%{?%Z+@cMy{{ZiY z(B^F<(yL7Vtm}z&&f%D{+lZ3Axy-0(E1#ErmvN6gFeWn$_c^ZGt<6P5*Vb}jN{JlW zItu&$*#n87*Y*BqL{DuY^{4PTwerDOJ{O<5reKFhE*5-=5j*mOO)mz(W}6mnfF1TN6WoH8|1VJ#I#!EvnG+>q0g@L(_v|5VF%Y= zt1&E_dCDs?(V2ZLf7XkU>I3cZ+p7TB-_hbPn=G7~UWLtFj>*@vc37RV8mF#nk@<iXY#U2|qAUG|taThB zuUCI|w45Agi=t7hVK_!_oo^Og-KyZa^O$USXoq>_L1@rkhej8eqq?LL2#l7SA8p73 zkmH-6MPy+Hid`yk{zHs(K5L7k{^W6<#^Yg4`Y7MiA9tKN-J2b-=w<-x4)NGsoQbXc zys=)i7;n*!wj%)Az2uC@IiB^a#GyGy<)N(u`d0=*-%W>^%UBPl8(OoPp23dv)6ELR zByvxiLNYPsXBGaLA1xV0c33{1*-5clx;ZlOY#sfE;Zd?|qAfno4u(&CEn2rGr{+j* zj{NCw!M3c2kb~Pzk0Ck7fmg_xu8x*~TXq<38Gx8BT0A&Qe#$^Db#|<{=#+Tt5`^dl z^f126!1<_3jPZ&U9AZxHupo@{X2wPoc{g%Qixx#oO?oyH?*^kwo)-JJWnvP2bDsL6 zvW>aGQ|Zt;K|XOg8HldaDsgXRlq}cV;Y+(f)SRV71HPY+<0`RY&{6rwJl~$oL2hUr z4~wz%?tLbg_w1O|9-yRWl^#RBPJ_YZ@{aIza*s)Z-WJ>51fnV5pFj}`>s%~Rh0{Js1^KD7P2XmKI; zS6UW`vd;8c*2%<$R;%)l~>O5hL!cZP1B7?@_+aD(N6EGMbkv!U zBc96lQ}~?T=KViCM(*(a%)b)|%L*-7XWkFBs<3?-`Ntae80XI3svbIi{|xdD{JHMO z$>tvp$XywP#S?iy&t%R!@5A+)8b;X$zLtq^aFOf*7z{k zaP&Y2V}z={F{Yu$khkHGq49=ch8g#JxSc(gZ5Xw|%D61CJb8fawdCX09o*h^?c4il z;10vcWp51HqjL?b|Nhv3*Nz#HIM;F$F1~%5p z)Jna8S%vQ=>*PpDjM&eLllHe_#l2smJRjspcN+UllUYNzP@>d>EaPH2ba{mDv|eC38lXyK0R{894qDj^gQOoJK+9ix^f$^U-hX20!K3k#GN&a93`A=m54j% zKp(CWmc5kN-xm;uakg|JV%&A&Tvq-1Pt?J2H<=>n(fu0 z`DGoBB=USAi{qmu{XOgTn0Hl+_j7fuMJJ&9V`fO-*Fpc5=hSJ;vR+5;P6K`fl4~5V z#nRz=<|5MlJX43a)0k5o$FpnJ!TfERJH3Za#WZ?yo@e2BNEW7j$->Jcbh>WL!mC5s zxJNc|Pj(jjII~ecgJ(VSvk)7^b8K}sV%p~50_%A3lj;85orTK^X3{s$LP_%+_DE-8 z(Df{A`7H~7kK|Z?l=)DxJhNu~W|wys5;>lCo=NZHiEKC5riFYwZXsJ()9w?cl!g zWTTs%v|?YCO;a2BKG8~EwzZNPMJl;xZ6}L&*vR3Xw({(Tqcl2YDYehpOJZ*a8R<;7 zPoz?^gRSLyoQ-@P<}69CI>^=`72>Zk!L#f#i5_1j4i^>3xvOBN4QsONOi;Cx4!Bfu zhj%Na`8NgZyD6~nuL@Dqz4-gu3VBBN+!nJ+xv;xjX8S9!1150kP0q282^L>b;AjVO zS~XaocQ2FK+>e-#E0?~*d4{^LQu@xQl&)#zqUu#8C7zWMf0F0)K0dJRPrfk23)=c# z7?|RXIdkaxIpm8Cbm-qL;J)-M`|nTr;L8+dDkl5jsJS;TW->qb3|T6&Rz-WgQMS+< zH80b>_=vd#JDF3>f4{ihhb)8-^8fZi>l!>0xaN)fbG*@JEWM4tm_;4ToU0w)$Q$g1 zN#{J#lr{R~6b>FrND#4@Uzxa#sU+e&a}2&rIfUoJvKnL#fO$N?|q{8N^EFHzlXyuSuy`%0H7- zY1p%ceB(m;bB3nkg?kD%7jtjCFBM<-F=#q-6nm$lU@pCJ+@l`i>ja-o#q-U~o*tiy z4Ru-L-s6Eo~;R@^QX(>1aer^E2Peb;U&d zn8#kAeE3=AWA6Dpk)YCJi}F}>+$ z9FvdAeRM!NILYLpwz6WnQryfer1uCLsjOxvE3P<7?^6!+Jl&7F%-xnb7D`FcS<8;P-q5=ao{>z!VRy6d1R*N;JWh(qneHM4Ff&ty8&tZ$geZfbIx##gAK+$^q=mq%ix$r`tG7k)FDXD(-lrv!f51xA8`ghx9WtBj?*=auLbia5}?hwVp51 z$NS+t|E})k32Xk_zO~-;8u7LGOgxSc$Ldw#sNPfqn~UKXGm5-nOAXQ=Fhlw%&!Q^G z_XdO`{SQ79jhWFEz-RBX2G>{9J9d-#?#>#t`oOQNsljgQ_P)-WQ#HB*ZbIex`Y53+x=45dyE?!|j`pFb{ z%}&L%pfuDl(A}8An%RCbz~A^>c1nZgN`8;X6y&(2VsRaEkG5&3{*-^enu=dM*V>lN zj3L(2_8nq9urA#$yYtXT%M23U>l+Mtm_0S0H4UD>eaXiQV;)j+SPwmrkA-wLmLH|l ztWN=sexi@+FrS~VbfWT{cUy~m1n@b!w3%L0U$Pw!*;Cqv+|oaJ*m@x!%lO)QKC4!I zHc$Ux?)$_7T;9*`-5?KrXOer|@VoJbwrO&gGj|Mo53My^jPGb{1BG!ISU@`X86l6uKdMYo*9XE3b~ypEyd1Z1(Jp*K>_`Nr}k1 zj(A#6iQ6^~P#4?dG}m|Ct}0=sP$6On`&+g;;sV!pu5;{>HPaqBbsSOZ!ffgN|G5?& zkZ0upH##b=M=G%~+a5`A>}#Q`f4ivz23V1qoJW3fl@j3pTTs^ln^kT>kkv(4$jNV>q>t_5^zbq}E*KLnT72SZsi2=-hP zn);JZnG=lr+8}H{!p~I&GxH$?&7DI~$aQ3khe3$HM|ZbVFbWi8A~*4MdjHo;8;q~L z0&(CP-HsLPZR2YslfU^iI03HfbT~a-M<<*Xp}~4gb7#*>^#nAv(lc{Fk4IJs2^`Bf9fGa^q8E;ui@WqE$KKZWB+SLCJM=p3~;Aw@lY22?3#^avMetA z__;j`fApfm>}fUzbG>)(4*OJoWx}#8nMHHJbf^H;lkMj++ZVF>iXW2IIy@piK+1f=klqV^70#jyq>}rNP%DjpqVi z5ZkW+`3DN%IFyd7reEMuo%x;P9A$v(@6zd4M>(PDBy&33i^ICkGV>(+VA`2tJvk87 z(rWM=SSjv}nTfs37YdI1cVn4b9N-I|XkWa0<&B}s*_Xld{Am*+ux^J2V;v)*;<{;3 zRvH>{{OtCX=RlquKhLG&!W6DSoW8(+M?O|uEI@6}`7z(}F^){g&@?+)@J%V9>pIH( zx^}X8kdyd3c9L6j6>wcn&(;J5e(4qTW}D!ujR`v0`Jw+CU(~ARk5^lm)w#q6u4Luh zi#2GogpO=O1pM9Tw(7)dyAc7$X{o5WDveorX>i?`hHUZ}TgY4<=v9Dj_Y2TycL9E- zp! z1NH!X@kWRJez;0+<(((=8@u^nL?f;ZlOv$^j6f0R#w@ax{+zpf_b`jHZ#sfGkMtrt zQ-f=}|9HK@ngZ6c3h?@DK59?*Ew0zNt5Kz~OJRXBkK z4lLq$8~r8(y~0BAYF{XF-iDxaY6#kELf|#)KgTS`seL;5AEZkvDuMnI=G~C{ij-`$ z*vj$5F&mdwaEwUIK@GZ*zRgjn9d?k7Tf(z+9~1SqN`<-9mBuVJLpGZ@Jl3)}}6U+?&Jw z@L$|>=abvZB|})GgLh0e{Fdfm5pyyJTxG8EF!CT_JkKYe;_y(R?nUmQs+~ezm;7LT z@&(@Cbdo@q@&3L^a^_T`bf3$tie5>Q-qwlh7bVsoV2mR0?{9htKJ3=v?qNNik-xCJp+{Q_J-(%qw=8Gg!4&eHADE|1_Tq34zE65) zh?2Kxc0-{~-b}Xgu0riQQK4Q^%|u;SeM084ub^LiqRgk4F?MpIl$vQJZXsRAACzeP z(h&_gKjzO+p~W;M_OjOT>P9e9hq690C zSTdG#(Mml&xFuj_{{%E3i+cYqb79D$e2&gRKsb5$C(MjkNG9ZT7H(QIf4jYjI<}RG zdebC@+HMA~XBF$lc4T3@>10}$Byn_$muenlW;UFVX+4!FzUu^Sx)Ot&l+ZO-;m$%Q z6n$sCH75k)SjRccI?$LjO`8Nbd%UCw)X*&&5`8NFoLn>x$6vM$nQxUD>HM^^5jqvRjy zDrTn?_<2i#cYl~5irm4W=_at(m|`yX-WU4%u^voc`~qKSmiwanFkjqR6hS5{0`X_a zFZYN9xR-v~BLXhp$tq{Emneznthdq-M)pfJHkEu*KEAU*&T=_@h^NTyWpMr4f#c66 zC%HDLlN^e&lpO96-bOVSX4e zlf9CCy|DGOF9xt5YRK*gSa?NX#!Ud&)@eBU@&6k)0f$&poRWi_az~ z8(JmPH!E;{58tb7=3cMzVQ!ZnKHu>{=1D*7S8?x^!u`|62%LKqf$f(xIQ5o$9FEVy zVPqFMe{JN)&%aW!m2>Hpt?3v(kZwlq2YNadpcVTRz7EfaYk598u2#z8!Ol`TyR%H| z>m=`6bYWe|S^74tls5M&MPoysCi^Dd@*`t@m1KL<1%00T#$$f?hn(kKMvwL%1kI83$zzh19Iadri z$3CoA?5S#EFMEoWa_OFvRO9}A1bcl)?6Hv`&RrwcD)1($LeiI;pm>o9F1wO%bn?gQ zC%)M7yB|J|rT2J+FNW^(#b*uoby2*QBC@APBQT>auWupiIP1Ajo0W!bozu|wDCaS< z`E~8mU|yGdr;`QDs9+6a0oh9Km#)WTRV z$m7p6!Czfj|0-7CV@DGVol2gOuI%{^%nB*zUYPxRPO~|m?TNra?rY;7lYuQ~ZRmvt z1>GYsc5)g9eqin83VTiW(x=JyO3693q&waFl?6ziQh>panQ8Ha{Uxk{SJ@uNTyV*F#RuTthzYyh8nJq=|Y*_2V*fO1wBt(8;+YC*|VClQJ_! zFK2#tf*swAix#ntzmUCW(^;E8titd6LQwO42&VCxBKp!@dpZP>3i5+XIUWz7@7~+6QHf}L{n%;6Q>qi%19JzeX4?pRz{40Q-W6l$WobOXO*AHNS z+}O8z*~Pu*Lb8?{oKMKHLkW^(q|diEy$9@@XwYAYjCV>jHC3TjL*^p!{aCOp1hzJz z==OuYeD2$xfG)-eG?bm9I?p7iRw;&B5GdbT5<9-K^tYuL1M0TV`YP7=?N+@15(M$Lz_%UaoDT zuFiY<|L}~XyIY8@vPfdDcwu?1a6GI}_xB#=$n-ap$m50bJ3V46U$aKF!idV|xp89c6QO-Q#_Ib#5F_T)03&mlaC!&{yBYF;bA1CrDm1fdlXNk0b!rFBs z=EMHRoYO9O@Ne2drZ6YE3w>wDis)yIWlnA)`@Gk;mBTd(<)xK7UCHEqcBkOT**vsa z)lBBnFZSmkPo#7U!^$T{T;7p~PrEwExe2B6gRfIQo*W{1%yzSLq4>SEnA9wh(OXyx zw+_QK)}dBz&Sx*JjT|Z|mGsu0=#UYP=ls6STd+^|a9jCzWRbkS>kiA4VMw{1f~I%K z10FEv*;=XW3G||~I2_v?Qqf{&F3Ooh9aF24x$3ODE5f1fmV#Q|tm$U9mB&11_?+R1 z7hA&6m0ra-b8?+0Y-Hz%5-C6C0WCSlS<8&5bu<@~6>X%>#Ug3<$rD9U;duLvJenDE zLi(7?zy9POk9cBKGYv`$jkt1|ee@>QGB~S5w)dy6Ffa^L|46}$i_E7!)j>vwmC9*y zZ3$8I04^}%W-9rnVeRG1y;6xj;fYsWI9F{Xm-mL8-RHJa@~lKcZ+f5=`M9D9MzkE4 zi(SkSeppf_XaDlTd0uDwz*H25u#VlSos=1V$+F$-^G;-LFMqC*KXXyT#ZrciES2Zv zK$Y~?wV{WxF8hX!JuF2PUqnYdGo&^#FZhuW1Hb3OGq$x%EG-hxL)@S4B;QKTaZ=f5 zoJ+Bi%MX};O%7|ST{!C8Frdd+UJp6hG`k83c}ni`MHnvRlfxoMIl7~zZ0N?d!vrrF z$jOHA{jvV^85+A5^pus$pxIt{a4-zkt5RUi_tT}E_w(Hn>DI*qPF@3S!olmat$+|qObZ#eZZ+SmBk(=Z1{hN6TEO_2ga?)I;%_@_%tJ&Xime+5` z=U1DHpeOBQUrvb_mU$v#CEXPo^1o61{~v6ndv1wbY3zYSa&STQQ*b;Yk6tZ$1GVMS ztSh;>A7RKLC;R>ZJ%BAc$b_cl@}tCq4vjFhv^8P?*OAxR6Zm>SsqA(4z@=Dni`!Dr ztOdF0FYToBgJS8~g!$br;qbFGqM0xKl@rWF-?KHhJT zEWPRlO%3`qc9G}h_Z{%Cjo2iY%8OoJxW;kjVO!>m&(346i>35-E|Gh`=s)GSVT?DT zoLu36*H)6OB4@YR106?)V=BF$(TY5@7}Qn{q?gIkV;ryeTx^Im;5R-;E$rHg?PhtY{~fmzIe&$GvqE$TKDz@#j?L5Pc*s*`i3Y zR(WG1&(*$NHsIv0JUU6*$;hGPb6fM=gPdl(ixI}%^i-BxNQZ8fQf-?jc9I)iy@-Cv zm$_)!tfh=otg?j4Q=wdnoy%tcL}{T}i9CEt&G;O@~d)IDcJ)TPgOd9HILER3@scyGvQ*YP2^!tGvC?9+JvROdgg1GdKID=bOs>MdW-+p4 zqaB7!41^PToE~AUsro9^frDeD`(is--wQ?44w36=Rg?XMW%202 z+VZLmm1sl`v2d&d`|ShpJ~$o|Lo(5i{T7!G#>rF@J36aYqc#0;zrJO_X<8L-XC0I2 zW9%@{KLCzL z+F|G6Kx`#1Hu3jN))lJYyf0d&40k|WVIXR6(!psn`6>P$3;8-4l|3pN217MW3wu>2 z!tKbP#zsr4*37C}NnUlD79Q_1uu7^}4~><)W=fpe&m3f9Jaiv2&^VaAoAkIfBj5U! zez(-Oyq_Jjm|el2*EddL>)W9#f8NF);_*X64Pqw7B+H2Kvoq zzV_lMQ6ICz^TGgJA5X4!Vg?p#D$)K|jO=@Dix=uZ42a`>sLDdUnN?8tix^gy|a)-zut)c z$K~)Z8+;xfi21+b;iJt&M{=4Dbz@{zb2}`UOrK_YJYBEMzb>XOYs z(toBcWKs~m7`2!~&uOn(^gjkfOU^-ixYi1ULufp1X)~bMTZJh@VkLp&+miG^6muLK zS&h#-`QoSd{yP`6LCg0+Q0H@;?460S$_fm77$udR?2wqX8hv=3kE%E>@p;U$i;-5P zb{M*YnYlgb{XCh0LUN;R_H#TGdj#-(i}a#*V?qYa>qTi^rO?w)|XyLdSf3r+M!)1 zdT*C#vA23A1|6=#zkkI^mmTDJvjX5#iyjYpa-XlM!t>s7;(g2>^)@jdoc!Qgjx(EC zN6dN@ClkHxVP6@5iq7Q0&(q6xs)~*-a;!#M^d3sT=O}WZ(=u`I0N>A!u`+VMEt>Lr zCV%2{u|E^-8df18EJpl8>@boX4yFt%LX(CD?x)2*pvM`P@v?S_o@ zwT$DvUM8EFM;huMS?6YIJYi@w+tuy#q)x7d2koys3q5BDe(i5?JiOG9-?)a`_gAHc z$U5H)^INwxSZr%-T&G)WsOa&*2&`6bmY*lqdXcdArjLEx)oM1U%GPEaVcc( z_r2ROa&xOr9F|HjGZ zJI7_!isN!XwBlD7FZDxX#rN%TS!$(~6LWMjC@oe>EO`drf*zh26&`+Yz)03Xn$1z- zUmtpKk~`w^6te9_^a8McbI(NukAGCm$WM?y0>v4auevzh!{dFBK|C5Caob&$thk5Tj zPk!gdnw&ZtfAjppbV?QuCuMOQ%EFmVbPe$Qz`t4!>b1y1tK0myD_Pja^Nr?4_I2)N zE$vDszAVq?zh`4*0lf*V>nnIZ9de%hVjMZgx~!3qeKgGE*;PCC?T*Vr!B>8sXXb%E z^#5?~YPGt(7;ZaB`h6u9!aQli$I zAg5G;^+Bwycc_%7zndVAxwmaTSI8y5axz|(QX{xRCM>8DllUrWvbtP`gwqqht3njt z%VgjmRrK~(NQoQI-RCH9{Vg-BPn1cO8SB1d6=VS_#W1;2+B4_c&a+(pY+Wfbu!!g~AqT6DY|^ntaLA6(DT?Rd@)6Kne-u{!JTTYQi@+#5BxS7|@V zAB(nlqwg0VuGjq#(TCpoS);K*5y4Dn4JvSIPU4zjI4F+{2 z@A#0lpRpP=U8cd1U94A?(78xnu?Ej#K65|#4?o|%kSqb~`{$J!EOjNX<*Pw&@{bi~ zc?J=rfs1tnj@m___W=6lcJOt!vF<)Bf?1&&d~C^l-S!b!(2-nKhg9V5NJZaXJkQ>h ziq~CJF)l6@o$^yK;XXO2*D3h2iTz?^AD6kN;YkHEOnytlgjMtlS*9Q{lV=?fny zJ%#7U`M|3@Y_iLT^}Bp{4PsWbZ2{{3l@ArqCD!+4?Wq_21|#TK;yH?4Rz7|omxn3j zr{;Ad#~4ShaY8^Xz;Sy=DGozdRh~estRm@>sj+ z{o&t3GV(BDGqc1R(c{S1vEqL6a;Qp1PP3NjgRR7kz07l`*orr~!s9*3GHz4KzIS}4 zKHACc6=Wbb*ocf*$*IXIajfqo4_;VG8u^IdPrArOCmVS<*j7U3wUhacY^7FDM|o(c zlG7jTrE6PDsZSqN+Av#bIk%nc$Y?K5W-6u6C|mXeI!OIQE1B9^DW~aa?6s^y0^TUl zcRrtsDHUS!vPv!`C=lDl1XD(t;#%t}c{aXEY%W*Go;u~S)`nS~-z#L}=t>FW=a;Ri z2E)xNX=70-m#0>U-l{^{^;2N8wnCoj%4H<~Z|4bBGM1mu{81uJ>3MwnSb;E4G9{%Z z@ZrDzeXUZC^Yeddcn-9Xyzf;X_!)gM>W4R0^87I5Fmv5LF?Yk3XNVWbAM&|rtY*IZ z3LiYE@J5=m7gq3WsL4?ublBhyL#Q`<)tI}HNx$L-AG9g)LB?SE8(*^)(2Lok8;;`%;mpF&z+=A#Te!Dx2n~)-p}XpqhI=bMR}m2idc~}1K3fVtqZV-* zdLdbpJ4ycHGiw3b2n^3+^`GXIUwSbaXn z$NJ`B&%u2Bm70$?ANgEo=3(x_JX|s4GIxuaa3Ag%cADE5x_7%~*tj^+psser(A4^s zYlz7xH{JC{$t`kECAaf$V%%P|J$b=<-%3+3T<>^I2R}WbC?%aKVG`U$4j4!S~+<$R?g3e7hgx6$Z?$*cPU{pMulpY zO3Zv`kIA!Dm_t6MU_KcOXBEaRwMR&aJsu3=+A&m#TVYBZPgY`*nF_tr`LzeRHay_K zQ!5ANmn&gg!TeLc&cfYFm?!Y_%b8F1Mv1Zs4sg^fvCKk+Bxfh=`BRCn?RZAVui5g! z9<|;pG3S*MiF-rQpXhv z%6~KRtdwifo5zB2k>_7N*XZru#P9n(6uXT&Y~^}wL}&7a;X3@>^cA67Vxehpc^M z9J{c#P)~=tdvw@M_Hf%V9cJ%gX6Zoouej)NErva!m)X1WMhlDA39!=Zm{+fZU6>v> zuhQRGhk4Vv+_z=u@wbg0kKgLpyTf(hb7qy;>9M#=0v7SC>%=)7(#euE=$3_kt>|UU z&%(@kWDwo5kb08q!@+dYG@+}JfB*MlHYWDUf*skL{O|N+)g~L%Iva15%!vM!N#`tC zlSJl9A0eBg=Q(f>x)~>AF?I*a2B7uoj2M!M88!Se&;(mAJ$%rnKj9o6V} zrss-h=80FyjIZ@WlSw|fPp&cdj4$*v=(2mDL5tdCyW2&w7c~M?CvmLfm~={;ik=JU zwXm=;t{$_4&FHrx6W5q$`eXJMpm~o1981f`&w0$p z^x$0VZX+I1f2C5s#Z*b=#!9hSUnR*~6v+KbADFEP_HFRP_XU2iIZW?& z3qMpw`6BBCGnUE7*piDodo}`{awCv&GZJ;Caot6hU|S2i8M9MiHa;CoI7T-wP9-m1 zfYtwU+~xc7?q?qAZZ4oFr~p4Fbd=AH*>mKml8OQs(OIjc#`#Wix`1x0am<*0R3`Sv zO%c`B1Y--UWKdtSC`Xu~Oa|k!${(2LhmtWqu;84vKaA_hDa=wXqBEG>LySb=X1`Pn zu1)@fbA%P=pB|p+7}AHoJH8hYPsn?&&c_EW9apCdaB3ZUOYU@*4?msd>0)PbYt~UB z>d?D&xT6fYX^Qim6gYCJQiRu5AI#+Dy)^Z*F9z!U@zT-{8s@6jEcHd9qaPX^qJQjO z1ap@o&^{*;i_b)0YwZYZ_{I6Eklt_GRJhelL!BR~m={HVaj!49bcbs{MFC9a79ib; z@6GW7`h2>`RPHy{=Q&HGab0Ba*iI69qlc`!!?jSF0|<7XNUEud%gb}H(9 zOv3=LbU3OCa6h2{zunKrfGcD{crO)h%g6I@tpxw0m$GV!Vis~r!ke9xh;H$+>ZuA( z|5c&yLr2s*paQI&@#PouolEG}^9{u}?v;CbhoVIpeY46?Jl??beDeeh?3xIxa*k6T zdVHVA++dC${R6WxBq|#nreq_nCK(L!aqY=|wWNPAaK1vlnQVyX8HKtt9aFp8CCISg z1nJ?Vl^Tv(@oJbPvs#kb``ZzdBIvj3>WC?>DxCl12*&{`EO-_Qmu{g@#?kXv6^d4u zLg9Wo6s!9rpnOUKj=g0*0r$bC921{4;A}EE8&N#Z|CEpo|3Nu)#b;v`d6g4WnT@$X zp=E9WP`VHo|D>t2!L?*8OBHG@na2BC`WYim%Hlthm}Gh5wpR7(Rqz8*2w|caW)?jE9otp0wkkTa)Wn0M0R7=29Nx-*CJPS3{Z+-!WSlf!4t zM4e8Kh`9-B#T$jXCtXrW-A&X3Iws2TQu38_Q$L!TB!M$d$@Ad}vizbF#($jPTi+Qa zd~a-5F;A5Kua50QaXKOt9!<#hI1$d!Q|4q)xkN5W}vMRy)-(`rslk6^VmVw)q z^5<+DNj7(qvRkEc<7bsjbXU;xZi;d{6IhN>z`c(j{?z&4+G&5(X+v)<$Llj3hhFm; zzj#K2%-a#nE8{x;WCW%(iNFm@KI>!nj0dIT@3CYVyK!u^PeRRPmo^x#)kNp57N{CeVt zoG@Sf+tm+26aVux`l0Vw^4^#D{pUrXJNFuWIFHq~j>Lkz2o!Ef!<~RM=1j1!@MbDJ zho)f{-N(Pp$isqg_76p~N8lmZZd0;p?gi-c+)=g$sAS0Dtm+Ry;Go zT2p%V8!9mSyaGw@$)1lgVXqm-F;BTA_mDHXSILzZ3Y==i@p-%{2AP@QV_waA{kB;`Igi z^pe*SSb)i;%nP4cfTRyD;uG0X`hV}tYjP2@EzXkFx|4W+F+o1}&Gwf}aDRje>|U85 zb1u2Yi@vxx#E))OALujKOL5y5Z@Cr<3}EeMas--^8Jw+VUU`Q|6zpLJ^@((Bx|fR0 zWKSb_?_?ZFgL}txJetXQ;w7EFKiFs4J0BYt6`-P70W$w)e`2zYtY!xHqI{KnrPk&5z^QV8D4rp?*4vYO!Jf2zDha)g&X#`pY zl82qZJdc&^UEuzAm}5HnbIs$JkcJMA$-_paq4Wat%75}b*;T+ELiU!F6=3^~0yN5OSbIBS*(@ha^>ae^autR)Tm$EaAk|IQbzagr0UPfAS9hg1eJI(qt~uBp&o%I)984UajrqQ;m-fiP zE-Afk}^}tPJ)0n0FHY!0XU+d-8@+2{HjhFT@iE{oH^X}Jjk5jE9 zy&@{CUE+xMZB^Lo6Ux142)1k1;FD)4yf=hmR@YE0dacLP1MH&NfoB}=)V=LFWQ z+4o5hd94-OnpznV>VzrZIiD|7!u_fvs%k4SYY_Kdbwe>QAe85wp{P;7zAle7_`!KB zkK^&Ug9#XPQI8}tmVG%!kJ&`8@9)`|wun7XoX2i{;d*~hHZF7CICfm2#zCI{b6j3A zPoXYvWTKvHZlX4I)5-Um@p7Vp(V@#c z&(1-4tsLC+q)&4K&(6s+jyX+VB**D{oa4_GkwpzjVy`V3)VKuk=+1tQe-p*iBT;M{ zI-)}!9n7b=k9F*s*|3S|X-e0_~w)AR#(__vFdI(s@uTb&# z#C_MmCcL)L9P}y4#`5``*VmH$?4FIWZMbjZyp>6Qu`S;d)ho`Y*A!~kFADWhC%s6| zL@9caDC-gvB|AG&rr4j73FS&0wsmC2gcC+jb0Wj#1p9i9*xNW1gNKBoAd+h^w@~ao z7>YNXSHFHuK8^BV)IJm$SHT2?hk__Ili^5;jC=YQdT}JmctW0ko_KW-%pe~$xK1v*4z`f#ZOWK8?T(^x;W%8Fg6`xc*UUDPC0|RVfPKOD zF42!xYDAAf=E+8xOYd1FqU=DwnA2Cr7)Gn+Z!wjSs-BMc*U7_r>*GjnAvnFn1gD&~M!F9^fEz4X?-r|-w@fA)J&?RS94V~N-7{qmeQpbBPj2y8ju-ab z2}8wFdMXFx(obP7`%jSvWUg`Z9%0xq#ei!`^g<48Bj*~@Ygx^U=WpTI#rJvVe0uR} z(3?5BNLH46B9Z3;F>_hp8^xU8ITq5oCcTy`=_?$mL9Ha_dXuLc5N0Mt_e-Ql8*-gC z;W(X0|Jn`qBj@p4C!$2EC3~=^H4N>9dEW_nNbS{DW|)*o12yw-FNa|+>-CMl=c083 z3z@f?*$M2!@cP6&ZU^#H+qrMOO`l_WrCh&5e_vG?e21ivRby}S5i^kkr7|l6kJ-H3)>dv^4s6vW%OxJ_@#$2dyGCrKXO~O z&7{xupE933@0-`;;K*}r$j(I@V+(mbw^*!n>}iap*Rnwh;?2l2wrMLa=ZeLNu8MYi zUOw((?e%Id&T6fB=2a=1$V>jm1!sIU(gnlci=O$vU5jNs^V8jaqZ5MMq7-~W*}mqo zF}F;{KIeUVJ{;GM8reUX3)74?GR>)6svjmVHi6vkp%i?I;d7)h7cbsd&B8r#lsw?J zKI8${F{hjU%KeAwIVG<*b9ERBd7rCV<>E$7=6X*e-$xH%@&M)(ml(0zoX@+ok!D-V zq*FU@Its&Zva1ogv3a-I&-CS_V5P5j;D(#hS6XnLKJ*A$2x-!m?R73Zuzs zhULP#cS~7Pi@EL0Uw+8@ZTSxaPMGJR%a5k=y;qqu4D!I~1aicmjo3z?MPX7)`Fm=) zOrr1d)JFOfn;S8#VIGohn9H&EWm2P^2fS=FxWk{T)5lzdwdMWUw@f1AJn^fTo?HX# z^P}^zs<6GdA1IU$Px)N9XwcKdh+E#wufNz%+BPVZvss>Sc|u?3^c0*-BcIr*y;#gC zmOPCY>OKua(R^-H|TS%>NP`|?VG=kN4&uCS7$8ai5RJTU7}IQEUE zCwCS3;t(t8$sF@L9oV=96;rL&q zy>(Pu*&DVUsQc8YQ7@W6sSC7yZd&Sw*WKL>3zcc7-ePsZ3Q2&vCqUf|lDZq#c4}CG zeE0mm^}c_6|9-R9tSK~vGbiVqz4x=P=elJl_ZGgBFQ(TlVW=I79|ps=3%Mk6F1t3D z;rRGi*}K{nC+TI&p)c>_MSA@fl7F#{m#%U4_{bdI;+^Du$lpD1H>1+9I9Wu_CG$Wa za{Us~u{Z-ymz3d?DMkk8*de}C5M)Ur*7l)q%TR`-zA@5nu`M%a$a9f5EVIbOf>82G z%i<)gqCG6n1Yy{YL`M$+;BoO~h&LnIHX82HcI2wK4Ya4GSUr znEg*quJOw&X6u&1f=?IkqS4akL@(_30yPH!~COlgeQE zb-#qf+wrx5s2Z7we$z6c@G8TBRnZb+wnu2kK)Cub2lf*AubK+?$K=TJob0f2XfS*d z$O#(B6_O|VMZaFf3#5vd2(`zQH>)sgJ-vtI$o?)dGgmHJ zrjD`4w)6DXDH1U_I1_~j%@{QLuuPyAvW|5iJa|4ol2;nwU5eP~I7uC9k4FJP=*aUK z?3Ic8f6+I0Cq|qX+2eT^a)RaPdFn~-j66{dQ>;XHae$L=09sDbz>S>4w6{TLIm{zoS6J~HExAzB`; zu*JpfAe?6{e==*{M@(k4UVBJB8ggj*K@HjJ_3`e9% z8wbof9srBUe4m{e@HuDZ^DtJNn73QLbQQ+$(vZL6^?#528oAx!wde;-qqni42K}C9 z!tEV%jn5yJIhAZt`Yniki;2h}Kb!p0jK4mT>ntXRyEcS-dE{Q5=pZ1+y5L7N$7DOa ztU&)Jk8^JpxlV60UR{otUZ?0)tjEuV*TeE&?S#kkl&7%!0j)$;nhS%#X!W5x0;c{i&d zytN?*L*CP8hZzZO(P9~557(N3coUk4ts673I+ota({b{L{OKI>n+{i*i#m*X$0=qk z4Nj23o9u9VLJ)8!5$V;K^V^^dQ~2Cio#TMcVFB#zPsGpB8R+9$2Gv`BUgQ}kw^@a@ z;}Y>DjlRM+%qt%dE7R!pTf_ga0k!ELG|~gBs zI#${rbAT=Vq2~h-JT666%gL_ad zekR~pbOuKDGs7d`u#9Wrh}OK1KE)@{UHu4$x|=cM%wgHwn%7SZpEKRa&AHRdx!H^* zk7A{U!WJza1><)!=7F^)pUC&Ael1q!lY8}j8-Vy)NZy`+rlT_Ojk(*0 zuf#~zQafBY$MfmR`~6o2fWvhgZi*cRq(_cm!k5 z2Mu=f^Bq)$JfOr0X4+$W+h9cAN}%hJykQ;s9G&9i;#7M+7Xz`eNg|r|&%}_`sx=RTzsc-)_b3CrC;W; zU4Pl~dXMG_Lkx|tPSiJA_3Gm7k|_PI^f-N5q=VsQtkQ5f@4Y^ER~y6MxAQNqjyb4r zy{?BrQ8>y_$!)T0rq>Sr(0L(l?-!KQuR7I9Khuz}pV{2`VvUir^`rYIx>cF9PH$VU zwf;EkB8OWgG7mIKCQQ-Ez292N4M~vbjz^@;eb#g6Xgu~!E8~Z;AKk2#hX;?4P0`6G z9kT4^4oR|@jIIP}7qnhUnLIwSC?+C;$E@}qgWT}TEh|Twkc6#106f8-PcK0 zV;O7Z#aEdDQC*ED&D40Cug2IFA*}0$u=k0co>T0r>`pHL>qtg#?m_>}zWm2(IKN_V zD)*#QKB+N{H34H4H54D1J=l~^oiXGcr-agxqef0mHLC4q|LQF@R(g<+e5l4Vr%+fd zW36Qj-(#Q}jV5X_BvFgp`5H9Q|L5M}7;>9V#d>sBaGz)5GP+{N=s3S5=eSCX!fP62 z{iZLv0l)sC!7kQB*06q6(o%~tuH5fFNya&pd)U?JF*vD(;tuOv949-o-u0aO5ZNP` zV_la_B>xT6@%Q%DK&|8b_KEM?UW+XD(02H2glVY}wd>P8O`iP9Nh40%nxNXpI#dB2 zIjn6cV!2;EnjGUF^7!0e{?eR#*=yj}B3QU#{pP~btYVrk-B zDvS1;Wh;C8nzS$dUv}-YjU_UP`9JONDlpAcfsy>aTYv%%LG&{2uz)JnET2A>%E$K# ze7{CM($WG?EK6l@7T=c+xy;SXFk)@`XiYkF6c&i|RbX9n<^=_FZ{F1p-i!Ruw$vMy ztNY=_A|K=*WiGDK4?|CSqgJjDru{?j8=0%Om$>iooO_*IyS)0ytlKJn?D_P=>QWzU zYfjh07GFee_Q$_`pYd1y;MHd&8tDAcZHGVVlY3nF$Oq$k`eC%Y55~+G0jsXeaysLS z`074L-NZa6asWLlL}2r=2s~dDfqBCGfWino4Pw@9p9s8Uy`TkaQN`RBA2}xyKXb$J zBP$#uS4UvAdnB&%b#)u_@44@KJ(+w}qez$rkSpM8$B?ZuvbKF^757BwPa648Bv!jJ zuX-zea=*!KJzy4ZN4ghmBT(`$vx+9BVNF3QGOg2auRb$v3(`>AJ{{PS2D?sasNjPKk6+SY?2-n@_v``N z!9D47WFZ5{V0B~G!n0Hayi7yAKFrz8PD73MbUAKH1$L#;mz@Sv{anCsvg2C`tXDja; zhpp7~ZYFmYDrJVEg#;#$vzTuu@4C3iUC&msts}joRTQXN!hQQ0%nuu87T2K)Je#M$ z*ipPs>RZBGM}gI^%H*z1nG8uX%aSn)^xvewxe5xDRW-}Na%HmVCij$*707es`)vFp z#fDOu=0R?e_gwL5=2V|zwzP!>2IVQRbg5Zl+9;5tHjDm*1srQBkZ(~cH>#QC=O@-b z$R3)wPnYo94~Mt=VI=R9CqsPk;jAxCzGPi&sW+ODJ*nmG`#TZ5mIE_qVRUaIG zPY&cXxtSPW+;C!+dw*Z7jP*f-W_}nG#|-x_{s^c&0$&QrM1J(cQnep0{2=pK$sc|N zeo(gbqbJRmpSeHUwerRL>QQhda~QrS0y#?}aFEyexu+3mefqz9hWE(s2wWj2Tu%{+ zT8U&7?~ont%lyj>=1M?30_a%;yq?pH%P-3 z=Tz)ZNu$Fm4U<2R8{&QUAtMbnFQ$<<;-1=%R4gG2@__eT%ok?Hze+{(>Et9`n7ew9 zj#5=FbiAkLAIZfP?;PgN(Zv8n5;zt4K~Kb!9Gc{ODY5PiIO( z4$7tEpdGp5A8*^*;J~o%Z$El%3h5ea}Vupvpt^Cw^{s>*L>Ef3C_aH=VQF z#e)MI8q$ZnbDI%TC4z(kJ{Xy0Gfjsf+R7yBTUdJlB1Su2g@zK`Z@* zsJa(x|uGs z`5YOIwdFK&C6q2kzIJsJoh)dZD92AHN=;+344RW5wr7&$c4C~28l@2}Gp8?HrhC!j zh`4Z``HdM^-v=g$=2?QA8%dvqU6Q!ybmIJ0Cnfxyw>vtbM-_5~tifFNcHlZu2^mdx zk!$efmz8L5PuE461B@d$XRN1W|D+?1PIbcYt&Yg=VTV`M9r1ahBa$mC5qQ%P9y&*6 z=JD%1N4T*6WfotTbb>jSLse+O-kKj}O4tnM*PK6IZb%Bx^*x#~5 zi=pQ<7*LW3mj@b@+|^=cWi7LuHAow+MGohJU8ivG^}7ZYE@{zg8Z+2B>Yy#t;P6fj z^zK>&?Bo7ll9v4wbWELQHd}oy>IZ9Zsu^=NBl$CJO&GGlgbXjv-QF7EP-4VdfBF=c zaNW&)xJqOdOa7sA+m~F@4il>98*!^KSr^t(3@-G2%wc}?6eH3uw;8-@ewgP^KEOBZf-3#O%h7Ba2*4h%CZuw&uT}k(su@_^x zAI8Nni*hVoSEdM9?}&imJDs;4?3b7s3EQrbNKT+rb}_kYKC9lG=QGQV8ODL>m}^f? z?=*V|t}@$x5jnzVy#GJtV*Fr7I!c@*Ylp2YEq0K)+nAME%~_(`TA=kd3zV!P7iVjU zcM)_CJ}ZYw-O1|B^rgeyAJdkRnGf>EdB+jhG?l;KHWE$8(yiA%5>IWT@Sbz28#`h6e=1tasOhGs~86PqRzh~3=_m;WJ7U@{}B^N%Oa&U`$<@~mEIW6P- zryv(C#<|F-qhwEGoFp&1gJjxvl1V+CndxSU#(||W=QsVzF60`GW^wya4!KACFyfvM zc6s|DgY(t9x$MFDn$JU(A2)i_A15g4d0HD_q>^gc8$q|EFlMbnENC= zmXT!~E3eXXRmgnPOU&k+lOo|{+Ditrrr@fTPAih-zntJ92b>T_=4)^#W_CVOqOMAb zI-}Jvlfh`SR*mnKLQ#8SD6BPV42#fWMJ*lHFVN!hEFIR=)S*^o9q#1O`5HjJ;Dr%0 z$fK=4!hQX_%n(jdxPJ>*xa;X3>_aZ326?%ToXyfoH%&6@ z7b-k_>`2Fe5>uL}uzfS@1s}*h)aBa!lp2HL$(55)i8`Rhtz7#5)@bPpNR_hXEzk?i>y;* zfEDv7|4JY)tdaf=Q^auz$G(3ZvGO~|n0n-8PAf5@K!sZEoLCYm=Q{$^G%#>{Ngl0(<0LHx@pIEJ(PGyC@*fo+ zW4_XaiG|E!xI=d4AlLbed2YzdOjxRLzhG_Q-gT9QdzVcL_bbN}$aHJv(dZN@?Uf|| z9z7~klt(4jTZ!mMCF|qN@aX6acsC6dpSyU^7X1#-f|A1j#uH9S%sn{O59kW!WVze9h4lCHwB~o zEj40av-e;d86KXWBjk0?r_)=h*21$;i}k#YcJS*7tsmnkxuyVmwk&R#(2xAgq(kJK zZqm^fpl~lB57PBIxf${*Co5RESG=K=%d^`{xd5efDppF{3T@=XPX`&SvqVTMORlrc zGA>DhJuelw%jfjr^}gt>;Qc<2TsPMyZ+`kCl+Wkz3-s${b3L5PwRNK?JlY?D`@G)+ zL+G!&mX1X)(lBrb`;DyA5&t6{3*Y79_PIPPo|uOyt`VRAlZzwTJe;$1l&xVZSu@s2 zM)hkgo|8Ju3%#>ghyrIV%K=9%;5CFE#JL<>c}(Av{ZOGi-SsU;Ai1eOet%4GN zpTbdr>x{nkkvM*znF%$b=%=M~Z!Q_MLus&%Psd_DtF7Cl?*FSS;rYewsTyWY%R4wyMFZfH!Oz<97B3l zr7tqij~ps9r@4-LINcvlesMk3m$}zXqR=Fo>l#b0aS9`m$FVh`=_Tyu81ZglI?BqW z=i>bFJlr3Zi!M|0(EKv_!7{G%r`wCg zIY)VVuDuv$x=7<~9b`*=XX#vAD%1N|AXY{0GtLqlZd>AHEZ5K6k2hZML+xFDST}@T zL@oRA-uc0X^_r3|5!hWV5*1j>apt%>#gpqqj$Kx3(=oYYI@}%U`V38HLlt{Fo9AKJ zX!<<)xizATdGBKO3*5@XntBe>+t^;xySA4d&K+cauXbW8>nQhPEzqw^IeNa#Qgx0c zb{(_C%_0l*sKL*QYu{Nj{P5Dn54*?vVS6Ea1rA4|71ylmGFa5MsQS1|n#F<6u zcoUP3;~{C-Gc6s<+H$VJYwG19o)LJIW^V|Ba@#({+;vm(H?wWuTwMkk2TeN zvS?)SS0C5Gw+ZiiUoA4%nb=?W7#k*=;QEq#i6_{*Gv0)q298^GE!=mhEZpBPUtWsM zn6}u$-TA3jel1UuAsk1iStrTo@5wUtXOhf+r$Y7xCAObbB6m6cjEkJ$xK7DDpHMu# z5rP~YS^NO@&+~abp3lc)7q#dXNY63HjV>WN%$`l2`Wt)T?-=oUjtN()nXvH(>$$_p z5Ay3VtI1ZLQ@HmhtGAV2y~rKp^XWf+#{HMa4YZ=E#pBXw#jR(OESZ!dtG_$qZJ-io zE4Rh6I2GAmC#;yn@sxG&({0qKd`u0?Cu%5LgyQ@qHTJe8Q#q02Y3(G`nxn;rC@n%m znL!<7!org#6z?&i{V?{gCmNA>pMCD+^Gwz zZbzVx679&rKHQ{2aw8R%_^MESM+mN_ao=NXDBhIPUrAoq$}$x9-)XUrWBj^}TnqNo zVtO+j+!tvvD&jHsVwn$ql%JI&-NMJ%gZ6>7e;;})ds(>u;e4ZL68jeJDcpCgu=u}z z#`&uo%A{$3cZbnVss1PyXRJQD}gQ+}VdK4JCYD zf$Z(#1&`%nIN6_my=vqKCpD7o(SKynXm4~Z4I}%Rim3_Y96jpFwuVLGJ;)QHVm>dq zHdp&>WL2y$6}1I2euNk1k|$byo*dSPY+PcmcU;pyQt7rg=H3fKMN8(r*3QQ5Z}nx$ zi+nM3^F&4${@z~f2Tsez*^~xS$edYKh$me+JF#Lib6Ux1Zf#UYlw%7-G0qb)Kgdh+ z_#4j8#(;N?WZuC-u{gxs>d9f)&f}@@CJWP?>r3lP1yXQ&I9$tzb4^N4%|9F2#f`=9 zYrcGCUh}b!;pjWkz?5yqE*q9V_*6sL%e?P|)}EMOi}lF<%nk3EgH=ncq;7n%M7?E=m3-Ny zs8n(RIoQFR;w6!P#NR|uU*B;2wob*yjX6kP)kr?l8~D)L2SxqEuyY-Ke>ThkpVdlK zx>C8?kQr6vn|e1&MU^($P`+#|8xI!9UuV3KS3*9~U_jL0S(tOFfy^f-c)1sIlOvg< zy}$sQn_1ZV!%8BG@?~g8Z?xh0{I$b?){nDr&7+ZYK2{{T{@#f8A=mlAfXd_(N7ij4 zo#RVI*V_x%FYtKgvd_988`G@Xh~t$asn7i43YEiA%ZfbU66P<>pcijgiNpjCN9Xu( zEVM|azdjpvuGW&0cEvJ;dnzlK8=l^XzRR2}WGLE5rH8*{5zj+~Tj8v?7?6~mjd1RU z9uF^+q;PNi;}(WnuJkJM_)BIrm77`la(uTZtP>-K{wb+m=9|3`Fh2|teN$0H{&Zrw zx)QmvK$`UBeXXS5&?6OJmE>M8)|NfP^X2>iZ{+j}M{~0QI)4AjH2M~Y|B}J4J#p%D z7<@h(aNHvs|MqMkhsV(q>Pb#El-HXo6&dZakwvLkgkx^D=F*B9o1PbIHzMqZcc}?Y%;~yFG-V*`M!|<#w{hr6NVV+!Dreqe&&80rr z5*3c(r3OT_&VtLk`f~YEf!ML{vUX4I2^Q($!28bSNzCd=B_reLDpF_P2I5a*R zW1Ordv-}@9GtGzjN#R&pV8EN=Y#e@QBgP+PQuQ zNv@JS_`_8A?axM!6;@L7^=~nE^gUl3pZ6r-ukrNUEi1$P*3lBz)&WI5f>30g$ee-E+@<(@u z(;qkJu-x5khr0uUaB5m2j%qSk!zqK?%xL*F*A_O*gHW$l0=l(fKF(M2J5}Q44!wBo z5&{v~AOY{cXJGsIGPvA5B#+zLVV*h&iXqGeCKpz+kNLdxl$9~pI3b34!JhOpE@m(I zrZPO(wO=}ur^})T?L@6a){8UgQZl30@@Vnw$Nc3rL2xDyHGtgKKc`F4z$sqrHrZnK zmHi&xo!_{{S;WlAPmTbPmAh#tc_wy0&ILu#xBcVA@SI{C_xD-X)G&UVO) z3&Jt-P`yTyUvo6$?b=wmk!OpByw)nudoZVGP|B zJU=OXeVw2T+?!{H`JcnmhU@Co{j<;L8hgdE`B#Z;`jXT85VcW8@RPhp)Z`Aael!zsiwSX>UgM;sa7R!~tcF zfrwM`ym=bo>{^B;nge1>f8yk0!Dx3h5$`Oy_wl(5KbS*pqOY)ue;{tPVa?B!ff3{! z+j9-({SvQT(z4r&?PEA|gLfvMzV&vlCx2P@_^PYK4H zd5L&=H3LU@{S@7c7Vo;`J-IfW+?$@kn;95$y$l{Z;>6m<9yjToT*mX0xskji`McX^ zqh&as8^b0B(w?j#3bV)h8WGaQjJdnx zBxtN14)o@AHHO|&zYMHzYsS>{Xla^ahoF5SSUWTk>qcgxOF$VO-ij8{*`xUhX4sIY zsvnqvCw^tHR>nw`2LCVrZq4)H6+*x2cRq*5#z=#Q_E>u}5H-Ct$X-VuZdY=ttKwzX zO$SU|AB0yY60zxW1}@n%-)CW*++R*_%Yy(kcG95H(Mk{g3tOtKInsuJ20!w;$%BP$=T}UTJZ(jtKwwzkmL}U;lr< z|KHF2=LYdf7<}RJh7A4C28nu?fM@!u%^SF`UeZ7xdGxnFEp&MrZ*~QJncJy$_a5enB^142+U5ftpkgFG4e;#l# z$+3-FSu;Dg&8D!6A7-`FpV;}kN9yo1J#Ob;yEsQ>cd>`NjsEcFCHfmD*6Kf8@YO%P zfB9nVR~l*Fjqb!n8oACrWz`>zRAbgg--jZ`t>_KT&#I&`KyX6#n|5 zk)QsFVz6VsdM=$icN63(^PHLtraxyJ_b&P}Ln%im6{8cRULBom|E!atAGK1rOhYFM z*U}Ej@@89{Y-HYGyMgSXyv23CE!Lma8zDHTuM5N-Sq@zh?_2_CK|Q(-8-FZB$~9H?yZ|(BIhGk#1cj)E1#AdeXdsAjI08UZ)CAI&=U zoNjb0@@FHs|9!P$_o^|=TCo~)e$(-DCIkanlRw^q z8A@--LE5O%pf|IVxIfTvjRuL$wVY#f&mfZf&K+2zchkb3?DJpi=*?mMKJ+)Ur?}^w zpU6KS&|q~k^D~^ZDEP_zr{`Lv?&7`!T{?^3()s8|HnFZ2+f8H^`|9xiTO!6S=4&jq zn6q1h<=$F!jHBb=o(B2c*G`CM_62`F-eiRTaU<$=V!h{!5jDmeG1c=iirtO49B)J+ z>vcJ`+2_mWa?S=LwCuAzmcgD2*6d$QVf~{5dz6cf2x1*=2VZ}oG!svQjj%WH>xcCD zOy&M`O?ofFS>tywq3Lnf_?yzllf@d~HzTs!nK1vf34NC_0xSMD%iO^V)bCg<2W`vb zf!YFnR0>S)XO_(`6u9hffm@wf<{--{zxm~dtKw&x~(5pobW;Y{(jhchTg`l^g|BxB`e{J zZcCY|`-;3&7&E7jFrW5V6mHy)z%w1!`!10PxJRerzu_pyn)E{Mv$V*Gz>5g-R^+M1 zkss)Pii}m=DEO2ozqlY0lm3asqAkpouEqUW{@wi-5$L)(0&^QO-_VV2IX~uACq*Ee z`^B~fW(-#1*O3uez`9to8j2h9s1uErLhMq4UfrPE#}_ywwnC@`!pQ9%l@&^tbO%P!-A1% zSZ7W{gVAZo=u1v=3*Xm7zJMI$HnNUOwx%P1zi-4q*8Q7sKVnHbx(?38qyxFASwENg z>U74<$VCY2bQ_~`(RDAgr!#Z$;Rk(iabzRf=AzbD=1DckMN9VNE-21HR=+&#&ZAq1 z%;VTS^fCJ80x@|QSIX?$TDfREA`gR8n4xP&&ha~cS3EN(9P*H~joA%8%r)$g$MeqI z-SfF9&d!Bv7p2^Ebdc=lEoGG2Q9gS)%GtWD<@!rUY59*zdNgp5WG{Q^H_=|k|7$B# zD>#W?D`zFa95_v%uSS(~;B+=;iu_KBrZeqWg+ zy)Tn%+x+oQtRFtuli|%|E|-lzCLZ@CALWY*9zJ+;gr1bMe%R#8%=UG@$T~=0<0L;6 z@g8c%`=x4aAFMpZER;ijXwlgh5vhK>2mF`|;g2<7p663vRC1y>^{p>64|pH-^+6Y% zKl5bych#6Zy2l3}+WW)G&ktq1KevQMqO=Y3Bgq^F^e1P-n!yVl8RDw+SX3t4Q7IBF z^TJ`%i4LZB5%^g}?@n;>^G|4t+#W^vD~1@p~1&>yuh0%o!fhko(CdcA6=6@nkJtzX&2jQ5&pQ&K9R;m@U^TN7rw2c;sqe;TI#NX6lw^gd2bC##T-4fp6z(J&XD_ng@- z9i_)oVNPaGDetisM{{v3qFgW4anO+`Hp@ zC9mQ=7o3Y(3vzMkI{7Bva|x^RFuUi?i`80p(I2Wt48}EGU#C}?zVhrkh7Z%1UT9w| zJ@#f*GF+`TuE&*uUT$lKbTq846n(K{(UKl*QY#v2sM_d172k9_KBv?zvD#hz%2hk{ zTd&`|FsC58hi}gI9*^@P^n-Wr(|5SH|6*motcxx;OWdYTd*b%COsW6U@7jflE$bQ@ zc~moWm!WRWn{U=HZ=*Eas+uCYjq$R=I#E7lB+Ay=NpfROl9V?j%E_5pIrp93#q7S{Uzlzu!vn5$R_18%1NS!>Ws1tW)ZcYkI zkaQod)NQPhG1chk-mZ}YNeObtm-!FOrgoe_M$)8_c=pR|7^jiA2i%(?UlBT7g)(2I8%x4Ax^O3_mfQy99tcc`I`(R=afrR z9WgLdiGTl6qCqmf-Xm0a|CCv6-=f8?W&}U-^E^tmbo=%b>E}?klqQ=O(tXXir*Y6}f zQqJTZZiZm!cQsUgYWNJK3u6znr^D3f>q}1YF8}*26w`Wg&iI)eBVFD02Sedef%Czx zOoi57p6L#(1DZ!(>pFYa%eIJc|Bz0QO;TJ~bo<(5{ zLVCRC`n9$eO>{c!K1*MSk^cQ>iI`u=_1^^zCUDMp@wyhLJhe!_ZA3BmN9zO_aksY# z6W-CMm`w(edvSfw8u9uF-Q07H%p{<9n``}`d?O0#8gb8-Zbj~6Rv5)SRpzSQ-e$xb zGLU1Nk@q-igxQ6Ack_%`xP5p;kU(P#IIF}4G z;WWSgKYm8{*7PL3c9HsvouwIhhcVmROHcN|#ND!hnbg~XL{oq>UhZ}Fm>G8Q<#`(`b3nGv} zUd4YVdA(R>h2A9>H#Qvy$T{G7Iz3y=q$FQ3HkR{?{mfBrz#K^DFF2FVylMKaaI3W> zcC?cWR|m1QR7&+DO6kmVF|%GdbXaH!H%&Q=sHH$pIwSqg^LKN8XFu7W`{DjLm*b1Q zP5fZ}jBI=k^S2G*XvHz6wqqp5{fWd9KD!Inr^99(`#N5yq3(%GIP-$M0p~Tgc6sQO zl#4G7zu>$DeOLW*(YLcomRWX`bNco&(z>(!ZqQD;RPP{T_R`&S#uC>TlR3StfO}jy z1o1P>twTrT79Nk8{WcBB`_oT0vYRia4~c@q=_sVmqI;0@#)(Drf>$SVsZGWC8R@8z zNIyUV8H}#!h^$S_?oZ&^LW&M;jUMjzuwT-yvY)nM+exD5op=aA4B*0VMh*~WDR`rZ5ugDj;DJoMWJam z@`InrdKQp9-4KZb>GYu$@-zF9MmIn6UWcb6#qtt1JCm0WCvQrZR9?R?sGg9E-%Gz> z$8Z-}-?_cqOJ^pyvz^?o(?N`XJ2P9vl6eM}SU$;;S@LG-!hVmv{VieIIs)+r$%BBs zN}S)%cK_@?dlkSx!;7H}z7u59&nM-W`SeH0CKE*p?u(=oNlgQ7fOb z5+#!3RWEw3;wz{yV6qb~vo^5HN`;gqtPkWnVo4!6#&K%29M3)dL*(OTsu4IM6odGD zTuh5Hn; zjlnxvbBbj@u0BO(wMvrX*7P^MV=re?vaJ4*B6rE9?8{f7z?E#}da@xul(0-tp~tmQ z1XNqi-exsw^-?3-i5|kfJe~ns_=RZ^ypJB1&(eff$l=);F$T<}7yeuL|=$}j9-@Rl>8qUm6W^L4TN|wV5lO$o*QAy~c!oufH zz#1pa?L*FiUq}8@VR5n=?W=^MOQTTkgR;gkS&cM~YvVaa+z8fU>mLoyd}YQe8H@@? zS)fA%yEAUOz|KKfvSJ zJU|D#D>_W>qr=B(bfxVlPqdVLW8cT{wlksZ0~z@fk2&T)M&k0v$oubH)U$A(N*3hZ zS>~F?lOsG##__98{<(Hsnv>i4;jEK{{3O{KeUx4!6+Ro-2kWQAiO-ya3{oM;h3BVJ zD6Uo}2TKNapHYpC9K)-8QDXx?r-*g*Gv<;{xvF7ZihQhv4l8**dy5f|>zVMI+^64r zo~H>$_TMnSv`pdN;+MkxQxyyMtGg`RT~?D3ncyT%3!4eU)}_+;4iY@Mvjp(Zm&PdY z*=UJI6%^?3tW-uHDV4Dv7RY-t0w=Gs*KoN%x;OS`pAy}!<-v_IMvY) zK{I@Ct0H-7-zc==aqL`ArZJyAQ%mR|w2DG#ch2?uUBasfK6i$(@2O8ZOgrgnyv6nI zw;c37L3dFQ$JG_&<@D^~JEr8^l3wB7oh0>uQofJq$c#@H=}V@2{W1#->&!8Ax+PX^ zwtzmx0*74uaqJU&%A%Ob&9T1!NFLMX|HgdsajzobcR2#~C&Teq>quyH`3 zz1@j))uyDQ!tQjmT9JlXGuaPyJ{P{H^Du(z24}9_$Gy+PfjRAD`J>LVqI`RCWgV(! zlMYhphLe0Nv_Qnja`-TqPUvcUR=Zf@%u);7IOm7nb^Q>W?~8X&*b5rxi-{}zvFhJQ z^!-EMJ;(R&!z1BoABk#Nk>muJ!~HfD?{w)n6L$%RGwIiKWB#-Ue|J~*EZC5*teb}~ zTj-kqn1}DDT;zhUgM8ZHA`$28<=^{ubP=_c=-!s78exflmX?W*Ec~{oJXcqlLA}@) zJumZ|Oz^{e_Nnff$2II7e<(TMaA+Qd@|ICJaUlu^J~HcqYr};{(x4{;>z$pBa{PC| z>vVi&KKR9NdAMCE4>P;vL3JY!A2_BSXp)DcUtHzq)vnS;<08Z8%)ZvQGkYJM+lO;+ASu)$o5+j30U|RuFQKIuXC)gy@gGdg|rJfRlwyW6t9SR#h4+kZL;)|Xh zyNl%Y`26{LNrTGQIA+zqb2BuyBue zv~V94p>Y41NskSmg)=#pNqUM@+Mc)M`XaV6tSqRlj-M`c>h%e+g3`{2YUlj zxi)&G#Pss3ak5m6!)?hjZe_1P5_{vftMNDI{#I+~U2mhqRX5gm?X|4oks-Wd#FVin zJgfH@Kc~{|TjL46j&uz3S=gQXBposo?iN$Y;X7HluXVO?-|{O-#@y1#PWPi?`6*dW zFVadzL!De_esS{@XZ+?f@Zn-54qjGbt%ag9=*>z&2_^=fg9pTR!* zv0A(vuEp$R_SoyRII@g2=XNHv8E3+-2JA;75-rt;5>;T8v+>!$xZzre7t`$nky>*Dbn0BaU1D=Za_FMD53T z_TEVEmBPJcbNU7wS-8huRk+_G1K*^Zg}dfOqQu-wktKiVVV;*LzdP#0snsz_AL4|0 zwN=O)r^3WLTtn7%M$UC5a(<|hurw6y--lq5Qz&Z^YRnz|-+E7ndQ(}a=Q*l%TML)@ z{OpG7aK=d1bJSzh=X&UY?-P{DW1O$Waf8P(*3-hh&vH6F*{{%z=P7QE!aZy0F>&xu zk<;apWdPmF$L6y~@LRI@XjK^ZTZMN+x!xVCL~)W66gO0uo2F*}SSVcUgrdgnP>idl z#-tdIu>tH~`^hyQ+1xezxDP=`WA`8}`p1~?Ws(V-uCYJO?lEexcE5YbW4Qiz{nWN_ zKS{>&1dnGmujer4h5w&**uN>w<*!2pVn1g%>zVYRsZ(*g7P+nI)^e*6xg-~IRUgBk z%cQ4F$=+-4`qHn?PpK9@4DAPm zd?T4Twpa=p3`hFRaEu>mz|Ak&khM)EyB>Xu#q8y8!9KV(sVEF#9<&8>u|E}xCfyq~ zJekMZj`<_+v(fFol?-L>^Y40IsB<$6eFDh4k&E2%t(8Q5FOp-EhGXB>Fr?KZcbS)s zO@B9%6NW-5EE&{0ue66zF6;A*~qdvaS-QpsIs!+AhcQ4KDZkG3LDx9pyvAQ*r_dW8Z>yF{f5ZH;pV+J(pNk3-gCi0=QNZj9& zr)$T3huQ`#=I7FJWPKTOyF^Ztdwtm?9G|`#kn<%AwZ>UXOXeEe4Ddw?`OWb!4RGLj zuIy+pwcF>*+bB=;aSlUulK~msv$67IBk^Fq?a6YU=szS369=Xtyh;uQ#&6jX zOE2E)aEv9lHDFjauJ36fxKt=V?Yz*F*I{FRj+1yi>z7%}(>mn5%*-QZj`K@va%Y># zk#%S!!SsYy>gWSK_e#p`(_?o`7Ai2W*=}=@Pu^6fC@2c;stCHdBE4P{G4p|r>z zj(~nU(YSmnt{HRCrL2yOr_Z!isTU?6*@>G!=;d6`T;MM)rCDaaT=Aec^AWv`7Y*>g zn+^XhO{MTcf!z7m3l4GNa6V^XO*$KEbDPLpk9@h^$_KB1@;vI(zHVqLt+o}5U5qEH@i@;1rlNf><`kc6EKQsWrTtAW)MXuIN^@rM z(900psG&6ZQ!J68p0Hs3`1YbySj5w_nb%M{IhILsS08-i^*ri3pAQenOXf6|dyjsL zRdf1DJ;E_S=#Jo=%)!@Mg4X?!ZN0qU{grv>O7g|mvXR@xUV2y;$i1@R^jU}DuuUp% zYP0BbZY(XY7s=UnURbK-=e0?Xi7&ITfjPy&UH-_HRi0?_kk@mn0j1yuN(c02eT15sg^Wz zD3*X*p7=3<-hyogWX;Y(Zo4|tdRl>eF7igylW-g)|9jIt8`>|{GGNXhdA`dV19|^8 zqu26q3v!e_n~1mSk1U)%9K*B2V0>?Y_t9+ZbZsbw?+e5+dKl`A3WHTdDmwS0XLCg} znYyb`O7_#+=*|6t3e4$#n~h(c8cS-OBI&f4|6gTc7+O0O{#Ja>RI4YJ)`gPt$`_~J zhojyTa)RUmcXF?^#JflujPpX}Zea-JUfF2B98_|wFRyZoWCMBdasfNxFd-E+{>s7P zO7&z_UV-fQ9*%9~Pmid{P4}UHb6`F3qZe}bm|@t*>-Kdm-tXjRtDLPbb67Zk_s0v? z?{{KYq5;9_*%^99z!)1da=JW?0M34f)c6&rjzW^k!byW0_Aj z;zqU-OOFCM|IG^r$%79GVGdN=9Ncz}m5$_M+$>kYbR`jyu9=A6Xhw^_4@$*$wj3wv zFQdoseF5v6HOMFSjFIX49PnaW5Z2byVBR14-QJa9$If`k^RQ(WkQ%>|>1V7-Z`xyW zOo{YuwYJCjhe7D!L&wll@@4jB{Cs{;f^+N<8OyAny$J~B_ZJT#2iGlLzE0-x&luR^zMP6yhAxS!KkIqJV1}`UKa%cvir9Uw(M!LclA0-4P8}c>p z>19hZ<3jy-xzD`jYR>|>eoDkwzW>DUX1vLdmjm-{@&Ax^7G6>3Vf&uJT6gUh!6pYp z6kGJU$68w&ySqE6!R`VE1C|6sF>@LDw3qWw@_Tlo{ki4z~?M;EN=r^7TvqErVX-rJ0{2Dl!MTl zV`bVKdu&-vF3&)(nU-s~MhbOOw|!Fols!iKEkom9^d$DnLD+9{m;C##Bo8>c6M3i@ z9loB*M&8{rRM5mqt()ZalIXdsOg_Rc8wpm->28uBzkk_dxmO6LO{aftZ#MSUSE&2G zKPUy(_ITAf2=z0QpeAqVS6!hVKwshY(e^M8T!vHR>Ds+zAAeVR-y##`T$UX&9xub+ zV|0jFpN%(8WoXtpUebN+G3$OXd3YVF9VO5BnEuW7^ccQyU|lPWxet28yvc^um@+I$ z+AoJzIbjF6lJgt%n6f+@k;*bewoZ`igPc%ZyA1vEnX9{!{zqP)=Jn&G^xu}a!@Tcy z8<;D-IR|pI4DPk!Oz9L%_Fsp7OR|v^WkJmBJ(5<~0&i=DVEb#<0qk?Qr}~Y$ z^jGfc?|`sqa-d6eaM+py|I=mI`XoV~k+?i1g~4@5qvraCu&>Zu{lu&`8c4#j$oX=O}}9a=8Q&@ zGyNGWarO>~KgQ36_d}~2&Hp>UXX*Kf6{BY zV84{su*ces!I*tI2{St6U}ih!iPw&kzNPl?_6b4lx6Gs0-$l8RkL|N{=M3|BgcmvX~s`G4gt2PBRDDHV2pa`Sx*5kiKxhGiHr#`Kg25@*J#P$1}vE z2@<-_30KAkV_9>4AIE3o_Db@Yar7sSvBv`I5KIZwVcRb9cS#)gw#G>e`QN<$p*XgW z_gi23WXI6&nZf*S^004rg&?+wyrc&`mE`Y!(T|zG$euYr^laYJF$;_wcSae;rYA^g zO()!*K#rR}%AMKt&-z*Lcvyn8IOKqy{{$nl4*Afh*|?$M_px8RyxD7q;UPnF~+v=Pu?)PZ|@9+I;?KO*R_yI$S)qU#3LRBY7$WHA{J)JR%3}P=?$gd!l7~`Tb&T73c;U6N%-xa%B+cdp&Hf`N9&!jn$?%cXd z#xQ0lN;i2fs#7&R$W(B;MeRR4O_gV)CGUy! z)W+UVoAfO(J@cPGGrUjVKU1!Ut*1Qhnbvbby^NCMjnkJlYLhW3r9;L)4%IUj{%Fw6 zII%%S3)#?hSHCOijoBSf{O{_n*r8ToSQkF`l{0pCVzzWY7mVwv!kHwxcDk~*{lXd5J2}xY?t%fAnEx=H zeB=s8yoz>4hq25tEOy4p&0+X(nzsS%E->O4Q0qrvOj8bqcsTe>-YK1((DJ~bT6gEZ*7 zITU)<#*fTo4X2?7k9+eh{&E;Sw9KB^5sF(n4fI1a%sFHJL~YipYa5~IM*s0+J+85~ z9J7!4e(c*E&d2@wu?LsuRSowu7kU}_#kB^!U&RcKd3wy@xzU`PdQ5mj2H2VX059l( z{)_#(>`C1)lQoDz?2&E9dQG^V{Ffg4HX6~1^I)=x=k9d)yy5E~=6O$bvchWy^S!WU zvj1uxE|#Y&qaO31hv#C`G&A(9Rkw9ElgFb==QSC}?L6m5w(OMn@t z{-%R*Yc2{)bFsd&8I9iNB8UHds)!DUES?{o$icQu=1MDa;jg3Dhwh#1Xu60`neljH zE;ie+R{k$tKWACX;+nA$&-o8sY9;gTxJq(&l^odQCTV@i9eTUVOIKI1@8v8vqEu4p zva57>-bR$Qon=UpqclrzCij{;N+tG%H+|tQ*=ro6`m+|&a47Q|_?$k>kshyaB^?#6 zlEkb#yDrV-gV9dXA300A(QXnq-bG#qIf-wsi!8LXkc*32Nl5dSa{e~YU~4Mq-?K=w zNCiH_y#&f=Kn(U8DPw69YBA=M!gB&HDioX7+w$Tr*9{EB& zCIE5s{V^tRhpJPqFR)m;`x>#3jOQybq0_%aMYsGQ!-c8wNQT4qH$YhTR)CO*TYdzZf6a7 zJUvFuv(RHVxkc99qxaJ_;AVpTdh%4Gv*5>C#Vw6 z9N&_OH8;p7`t!f5)2p-4ghMTv^SG28SCR=&K4jw0H<>8&&&1~<`WV-;Hqtr^4>cyl z@^vqgeenC03F~hrOgdDEORbCGF{2RUbLiw*Uxf6Yto0`sVakC*6nPXP=QjV%x_|tp zLX25jg#GJ^@Ng`%5xAgR6Mc?5S)Yz8#P^eY&QE%zYSKwJ$xf8Rn@gR8Z6uHx(bK*;O58nn zxgXL>(p9ZwL{%3#Q>~>0@O!ZMLo3;HjIN-Q&1F05CW8k#iBo@Ok>#`zYezaEKDCl< z9~(=ZSe4{FQpudYtz-zZ;aAVJ<@e4(c4axs0l3PAJMPk=eKS!STS;DugY-M(C|9Q2 zlY_UDj#12RXO`j`I|VAQP~sSCRJRW+(9>IqRc;C_^(m8m-T3_)O&{uKdK?E?WboTE zxs|L$n+FO+t)ye>x)MpR6i9AZCMz5M7Arsc8^0@f#!1K0ae7eam5C#n<8>o`%UWyZ zrZp&&F$W|Jd$OK>V z#hX2>*|_>+&s$&ok?VsM<9w0Pi1jySxsR>jM^45Mmc_m}3qOtp{-|@&A78d>nI#kj zZKxKV&yd$8@4NMnDEvXrrB5d`gCyUZ{p9zm_+2cKheB&B^4=-dO?3M{V zv+3h_$uqMRtjk*QyLa7$>oIhb71QT9&jg2B?@?BPd2o^BRMr;YXc03l?vd*?7vd4W zI}%Coy$j7jr zd4v8eGQ}VI(67oftlF%ZZSW=+(}Nr`pS$Q{0sd%Gh(p^75i-3HA4%`kuTT2NX`MXXZj4F~Ze0G% zy{I4QKY!FuKT+4@`S#QPv~#)LGul*-Pv1PxJ-x>VH$MH+ntB;M zG*8lWWo2nIVs>^7ja}tgf1^3ASzza`4Hu-R%?a3>t{zlBGsGV170V~TF+Ez(aRt~)f2_(GW%V28s+rMWQm=g zBIUm8MeUa?hl1m!+p9#`O#r545TMeA2(4noS zi|IPoiaG34IYl>9P#A(;>F>5^P>JU~^@BAS$j8+WSkv>+;CzY(5xyF18_ilD|J(y( z7^ZpC?|p;$lze=%V;J;v=mb}3FeRLSW{C#a#x*DFU9(yD>c!rd^mn0%;kwb7WI)5= z20Flva37<`KfPHSByUriLMG9}02AGbed7(N%XQ=uHS3udm|<4Mh((jgov?oQZoQuF zSOXU4F`t?YQ7@j+=@%RD(8_=MJ8`oz_M0})pi!C`qK)l3)q`+%NJ#L>9(Fb6fPM7SVa~?*FlSRN28FoCmP#V zkR4||{VaKhU2@!76Ta}*Rrf3;#L$fx%Q5!PBFvpx zglUWE{flJ&)#pNlbA0R9+Ere5RY_D!dr?_bvhIZJnft};_OuuL{C zw1N+v$9w-CiqMbb>^BC$Ei?e-y!3k4hH)@FXMixd20EGNVghi1M?^h&vadae|BZ&1x;}t=;7012;); z>n0uQxJ#iZ(f*P}EFTqUmi}8}+!dI5murD^=7v`CL*Z4fXUXrhS;L-yL%t}C=5@&@ z-(VMwYc;ee?x@ACN96E3(D(H<3;nl{ci3!V-b5B!k}3T9qW}%Ja-7eggUrPDMg}8) zbrGs`bd$#RZRIa5*EJ>XQX#XAB(H5HFZi>2%~8PXDZQTKmDuB44pyQ-!>i0z?dFdr zpM0^kM<8o@WQmG>QBo}mmAS?p+mAWZoL}$y&=(o0MXfj!{JH+y*UE$r%gN#wWHBd_ z@25u*Z1ak+@J%6hkWX33dCO)mdrr!Ckg43aL>y@+3a{2OYEf&M)!aemS*$Sni4_hH zw1~@0CB{s&;vCF=s0qH9Rx1!oSNY@Us6f;?$lfBZ<7--xeWhn+<)7?*$kXE84J|&l zB5OJN97c_#ugy6NOJU;mrE_aH=TvuoJ{QTs+83egcdk?S7om}*05932sN86j4rlbz zps7*rc^Re62!rIl;g~#$+{Ivy-wrPLyMrqhZ*oO$C%O;!YG7VTR_~eyH*PTtVO%(J zZs@V%8Chzrk$E`G>YQwV`#1yax{!yfWk%8ix?hj5&yB9VmF4p=;{{p0L^6#j^fGD` z>h%klUEEZuzW1*|emqW=f5_EeT$ds#j}0>Syiw+>UGX<-`cI=&aIkU0^uexhGxI#* zY&c%;ryt2c7vfd&abDr@-WHDI)&{&i$~**Lx^GX=Jy@3<#%nSdwR0h@@({fwmuu`? zytrwGe-htgyh6Q^4B>I|db5@&)Tvv@V-(O+6p<|1t8`MxZ0Erhlck7#1HFf*h+{=p zsLAJtG*e+J*}-`RC!~>W{84#12F+z|aeXo%tHO}%%Ih;qgVr3ozgZjcme*zZSOcmp zW_IymBX-5HXE2%L;cPPwH0FMMEnTyuSU0eC7T;{28K9e@j)U z*O46@{ga;+^PUHh3>jW+LI%!Zj|cLDr_W6v}>LUaaOHx*qgnn z*3K|i)nLJ=FgW}syVEKh3pt1O{>J{$FU-ZPWWc$<$)WyZz@=M8^vE5KdQH7^a45FjgH7!&428CuwkUHnYLI^7HaA zqVYS6Cx^eCb0g=;0INJW%*@5$2h1?-qfi&}J&Yc&RD1PNs=qEG z+xWsklJ2=k*)tEh@PYfMbI!7NLMyqsNrBBvEwX5*57W8+bYpiLw@j_ANEZ1$9|qCWR%fWOBVi0RWgjxT6`X=g}l?EgyT`HP795T z3CB2JG;pmw#x1V4uz2XLX6x8e z4kq(i%=h&#-GkQ@SWV7+)KLXij{YSclgPgp(Gz*p2g&p=zpUhs=6iUy!S{ANBMP3} zBVFbBgKxMNy~;;pPHr^b-!|diMY4<|xz}jH-o*&=@8#*wy-wz1P$7DBDuUh4LUjIG zh#OVt^YwO;xB0E)LLZ(xy>OD4*>3Wl4$FU|c_wt8`^(DZFmSdK+8YYo%2S{R=ZHz( z{?Kauaqhb>>L8vAJUxy^g0J@Q-w|QRjR}Al?ZdnNF$8(T(?2WW4!tq4rV3UI#bEgPS;T;H zW6sDC`XaeE4LuNzFM2IrHPXUoC42RF&qU0~f&;J3kv>_7=UL7*NA4$wa6a$L^$xjw zciZ={_GiXLGp;)d^wM~cUb+rTmb|!R`9*hpHob_idA95^!3oO0nB&9m`H}UmxW=>N zmy0#XGlXLS$7i?E%;;4v$0^oWU+mGN{Cv(6K}PgDX22)1gkvJ<`#Wj=AEt577c=Hv zx6SQh6Br1F|?4W+uy? zb}qPAM}>A87qnl^^KM7-gPcFwP6(${T!T6nG}wMfgNYo2diLU3Gv|qedF1c8-fvJq zzxrGw3fj^!%=6gme&ngAu!o4_P6zgeFYA_v;#&&!xMYQTWqqaEhg|+hqe8ubu11@7 z$@0B{PPXZjW)a3v&?hapXG*!jp-d6<%B*}R4`v;A6Y7Wx-XeY6v(|z2;IvE z*pqcugXI&$nbBfI%Zqfov&KH&$%wtqMue6#qQNaCFqb**FM;5i;fFExmB9fOQzJwx})AeCCDN~aLcV>eaU{*)O{+%tyd zIb*q-6D~hyFWmVsCUVZ`Vnppk?u)pW z7`4TW)qTwPS<#FuOY?BJh-cXc73wQ=FSq-uP-l?E|G^%Cf5?08;J&!7q{^EEsWSDr zLF#`uicxKpL@PID1*;HRk8`^}dj+n#;M59dxPGFqz#N8sye>bggroI5UaJ5)`@7RG zFp{5FeKPs83~0mmc8q&Cs}M6n+2=LcHxHYV+0$=x4H+ z)H~>n9MG74>Y7L7-ySJ4gKp{<_YAVEhd~^UvX^9|3QM@pjph4VGR76j)5z$u_Aqx0 z9gS_nQEnYwqo=w5e8#=*O1d-;v0rTu``+&JTAkIS;spa1@n>g7(f`~f5BFcvt!c-- z+h?wU4znMC>z%50N;P=zRQbivj;!wg@{Biz)Rp4mVwu?A2WzH9Ag?=fPRS*yTpCN= zy+7o{8gCpw5s3nFI*J9%r7hn`@@oH(!v=4j{YT>bbu!#j^6`WDzb~`C%TYb^l7)JmWg%$;LF1 z{gaAi@IY^z7+WxhbVtOj)wfDwN@^MRV@;dwFqsg5H zvU6;)DDHcq6FJR7zR#VR%u)TPg|u}0DZ^X%AZ-Bm15ugqAdFG<$!_$QW-VHHk#&AbS1CCHXuh zcX_)+p3R}>@o@xd&CNtgy#n;EXCumz5}8}k8<9agdpwzeitF=%#x^pf_Ybk$@!?qt zy_}{D4CREKiF>Crbuy{gV%+Rb$ZxluAk!Z^ZaT!lPU!%*Ws1&TAVvki(xl$qQr2 z!`i;)&%N^wP50Q!qFKLWUa1deB}Jl`??31=dBZR}c}TzB^jkiNJIP#v!{lnoqbY`4 zOYG;b61UbHZKg#c_*f=xHY`A$qc-xHYY@j;zG#yi37@ibJgdy!>Ke8(bxf%YXa4fv zDH0Yz-?}%IOWEIL>R9GhFNws)D)d@bEI{=Q4J0+V z;KlI>e2UG$$f^bSGQn9MG8cFYbAE%gk#N1APLF>+(qSWGTNg{8j3H!0BN3v_K+~W3 zIDVk69J%&Qip<_*W&>5Z!7<_?jI9Q)}V&i=5GTR-TF z%wkTuE&`b$B8RO@2#7g%A7Bn16jd1DoEy!;1X+V!f6Z^-rmv>Wz2gVe`pB z-#d|y)1i$daNZ9Y_Ft|vum6~s4D{i+^z~?Cd3A>O=Yb)pus;%caT)k=;w`ogu$B2P zKV?I6Z#49afP1%0wEV=p_;(HIY5gVloqXs$jfC&AOf-sPX3+KqvcB&! zUw?Z_J{&f;l(_rFlK;{NgA*dLnH;MPYe*j_w-oI=j!TWn4;Dp`P2xHHD2|_2Hc~CN zL}q^D`;3U-oRxtW!}BqEwvE(nUM9oIGnQ3hU7~{t?b|XV%-2D_{>Lvr_lC(7iJUf> z*jlRq;R_l_kT?0$aPr7k$v^JT#4O%#-!|8hUX{Lz>W~j=b3AEOmVqx1^HIB+wWRPq z={bq>MOp-Q-(s$PdAbHBG?i*COC*NA(X>~QIIQB|_dETtXeo-sA9C@X4-~x52h7bt zr3~Jms+Q86j+k$Y$zA3~U@pf2W1j*z7bVCc=9$*W4u*OgeQJMYv)_lgx?Sisb8*De zJ;7+QREJw`wsh zEb!c#AcN_5J2aJkuA$^#_UE8hj6$vKx?g7bJ7C#1`Vi?29CtSd-Ye*Xi%F1Cp)GM} z^fEl@s>7?}IdEuJhFJ?^rF}TPW_BS+U(dX0U*?~VWPeKHehHZ6h)>x;STse4CE@f8 zRg>9JMgC`^mOAp!%5*bgQI8C7$P`9i(q@<6b#9#{m<`F-_rGzLXrF?phfJlN&1AN1tZL zAo%{FNBei#PzPFYa$}MVGuffSh!8YUk}I5_jgD?*nEd{LZ1%9n@S!1yNY=slF&jNx z6zcIO_e%xxiD$2p{pg~{Xn*DxIWbqdFhL%5cR+AN7)sxe<0Efqe9QN*PLM144rJ;> zu)&;!;R|!{p6_$i-gtTEX%G7}=5CX7T-`1Q`)e!Ifo_QsSY`+9giv~Sm{aVZgK^8s z&~`f68}4JqnL_buwjP7Wt z;Kc{z<3b1Y_X&bpOTS@M4g#8Tk5M~GY{og^@cB^8IzmrhbNT`Ed7b<2lPBvOu?@`a zO;19#V>~B$UxvD!m?!?3dDir4E*`?yX~X-3Je{E=PEL6`V%&}pblJ@J$(n+?J@4ld zdJ^B+WBct8I4N~dUC&091`74i6rBtlWsiQNgYoYt=5(iLw z@8t7c$rmrQps!bTCgS{ zLAEz?f|nu$Z$gsbv6Mc_Ze(dKa!-B;*`{XhCyCbWDq5qx)`#QN;K7m{wy@&gATjJj(%V1A0>g^xd=xj%CpkJKK zuIa?Q`4E&f(?NMK8!p!^n0G2x!d>ad^bSHd)^;Ax$;O0jWy~BqC@tW?wM{5CzhsVc zZ|2C;qk1~!fb_a;Pai-KYTae7eShBP{VlAM@jfAk+p$du{^H;3UAG+6_{Dti0Oq6* zc0kthAo#4%p|FfO>`5Fq?$9&4fd1BTp{U1kV--D;706fiTN5uUoE+%f2|=G8I(RMS zI1uw2clO4KO6!0j`e6KXhq>YBauCmPsm9CwlAFN4S1F#}@jp2X}Lvp_KW`0~43Ujdzjn|O-Uc%gY zMS|Qe;QdT~wgInyx&8F#`dIM0Z@esE_S~7vq4?gCq3nQa=Ur9S$a?s4@{`k?zCJk$C_q)(uOF(WiGJ;*jXt&w}vjN%W~Gs=DG zl-}7VFMWQmkS@88)fujFo@u*k%&C$z6#}wH>7vqZRDbkZ(pDSyOQsKE?+Eg=0y}BvV*~=iC z59*{*d-KgWSl~$u8B;Be*jvQ2>ohWs zD%P%@RIvAS!huOnIMtN(hj3yY2RVOrHUApRO zX9QMq!s6ZZFp`aIT$Sfhjhs>OxC)LBoY0y-|1;0<>l}54^%2%Mk~MhIJPcdn!*DlW zgI(uXL+}X0gko~=cf)XVDEIm98cg#DhlMrhkJIVj85D*|jy#XxIZ0M}IQo(?-t{yL z(X2@aH4jJcROU&448x8)>{I<$^FLYEC4)7%%GW4<5X$pL4gK62=8uwnoI`OGHdc0c2tcT6a#dxU4k|$&lL-eTCgzlUY1Cl@L@x{)74G;8aFiVf- zYkB6-l^NAHm^a;=e}0V~sd_y=@y~YA7|@cn=t?b^p~cq@;GgSNms!@|m}^m=85eww zR(F|EXhrAFEwlZ6qU>d2tn8=QNL7j?7g#WpX?w#_c}>=SCv%j*HnDw*~|B<4zkBnC2x5KeD^BrzM0NaCDKva z#yN;`K@*vG&q1EkQMWO~B11iuh)?C7MqMU;X%@+%GcMw|5`X?pf81sT5<)G^$7asq zlwUHkfDEG}S*kM@$r)#nY!BA3m$Iha&>~Y8{}#goB?1?-PRjbg`9BqKyQ9E7zGn9X zW)|2mQ}-Vw0xp$FBi5Ox4^|>=qD3C{v&amd*}s4HTZ$6=kd;T)u%AE9KO@6v znOoS?8(sSPA=t+kFYW1VVV$%6O<%a#(j$}ahp)d_51!%2d{+A7+6SPh2W!O<0SMva zn$ZC`U-dulqaUny_@f-py^E>^;PZX5Tf14~jtO9|? z4Kwz(MIzQG3NvP~Usc#w-!Tf6;&~SRlfC{M$w~dCh38EA%WUIy4Y%QF5=KkG}xzamW zL!QNagaORj;^U={qu|qB3x%(V8IsJtt!RQKG7I^;$VBI zOt`Ngi#3hUZNw}r9nYE4S>qT&Ch<5~DgJ)yITO|{Bct_$EWudQ|77X*SY*OVAD*MX zG9mm7GjVU25cxY3NApcU3VAHnC7Simg7OY|gI4G8lsr^ujY7oFFT`SX5yH;V30KN& z=y^q$6HBk#ghHGr2epIz;kcjzTzFA{0mBOE;wxfLC!aI25F=R6INzlZKO>n*{fy7? zC_-)v)}*EuLgPfPVoM>+jf=2|+`!@x=3`Z3jiKUu?p^u&WFO52vXBi6v1&eZ4evD- z_u0*)%GTym(a%om9+8YKf}^PH>b{^HkD9*;0;u zbde$9u2Rs%Nv<)gJ;T*OBKdn|vt4Bt=sSJHoc7}?iGR{ew(WJ1iBlcrK(4*CIjWL6 zYnT(i$X;fQag&DDPEsz@MLv#nla8!$+*FZU+*c;HzQ3i;kTMCnQYKY$e~WT*nGEZv zz_{2_iL#}8(VE%RpMFbEeyzaRpq-Pj+!v;GK^T^xMhn{>%Hm zoF7Wg1|XU>muW$K?1dj{#WM%<1|6qg>A867hY{y|a5&Wu{uh0*XN(_WulmE*#TN&< z`C=aHSNQ||(J$5)!-ITbe(H(O{2C_wYH7mek69ROVCM8-@2+itw7}9~0xrAo4rYZ(sp(x6@n7@10>oA-?kambkls zj%{+G`81xG$~kLH?vqsrxai29WGBq^a7NJ| zuF(GC9zEQdzB6WIat&v;a>mW=E>QTXVC?UNh*2t38cbHC^M5@ubT1Y=W1O1`oi37H z3{_zyof*}>sW5S~3XO)S5W=-(rL`)I=ejV%$r%9$op5&wp9fdW8>2$dzA(&Y9m!ESkF3Dix~Dvb|C*4tHG%=VR#b4T4RZZ zTp3xAQyP4(yBxi|$SRH`+qgI!9=pOYo&P`XWf-33YS4B$*M!x=@x?a`^BaUAZM_B~ z6Y2QoYn~||jxc{cV!zY3t)=T^Jw06}IvKhC3$mvNWgt1m^9J-xrSGgJdt!q1aQZ>! z(Nm9dMgx3V>+Cy+KJSBM8oBPP5u`_z0eaM-$0f$B!)?A+-$VljZ`Q*mG#M9a7?G$n zp!o@MA_ti{)L_*~>J$;GdHKJRQUGnR8P{zfjQ zcO#?Y%DUbLGaUWMHSICu*$QTuf_*iS%r@ova~Gepe~cN{HhDN%{C_-Sa6NZ9SJ+OD z?sb%{hg`)up|xxr>MmPW(z!cYiO1u}yT>W8b+#3zBr744hNAShFRmVCj|LgJayG)e(1e=qE+`kr~?(qR@`x`afk_M3Xn@7Mq2{XC{=N znT1tcn^-u0K9A?Pd9DC$^Na9h49BJph3GYfzDSOBPrEtGl$&HO%F#JK%SF_5SXP|p zEH!_Z%3t5fTioDWcZ=&(lM?f4vuCD^j_;#%Hof|<7selIGxI1N{88|?7T4C2YuAuV zX-Yn>ix!*CGY|4Gy}4v%hK$HU+-(!Kk&mm3EI8dR#MEI$SXHNxXS!VH6cpm~bY?zt zol*AERWg`+eZk-^vn#a~Yr8h08ES>kJ*;p(mwiFZ4*hsZfzqMmVqa$6t>Fcz(;CqhIWK zXh0T({|?~#TFLc!pH9*E!FBKZB=#KaVn0A$CZ@V(VKYC!biS7p-HLG8s|fdb@0_n# zga|vXAL*|<`-E=BQ^_)SwO%yilBH!>s*Lk>!RSI4#2!)M)<+i{+2M+yInJo$POt5U z5L^ilXQqh;sqZ+(#c1%?Y9lhM8}W*q!_B*Ttmc`N{;dIT$QHP@&O;3MfSwujHgU|T z(VYHQ*38F}El})GsGp2gsPCLmsQ1Mx)V15`WYM)lvZ1eDCern1=$0Zz_Gt!uR^eG= zSA2AKfytS<4uLMXu#5~wDfjU|=tv^-(EmEe*Q3l_xJ{mLqY;hP8ByyaJzM$oCS7Jm zLK(-%(Pm7a$Z@S1eX$O?h;2d!!@-Q?Va)uwLjH_w!BW;C_Ow>0oyqR0N7Fexn;DSX zlBGIXhjuFZB6+UjUZTR7udbM5-3n{S7W@epJ{hcS>#d98QD){l-JrMY4*h+e`PyiRUa38I?Nnw&aE?hsqlEJ3)=aH z<2T<^5SbJQGJ6N7)4x?a9OGk*aN%bae#C&683trFH#Q zcSaSS(FBz_<6bQN%bdgi%%7+v5O&9i6yI|cb7qob-!3^7Qbge~ZW;vOVLE)&p zT!SI}d@4*eB7T?=c_uvyLkv*e<~dD2Gfqw?mlDSJMFv0fxEakun6*l$=lfiRx_1CS zs|1Dm5qZn$%s729)?J)J+KS_J2dT5nLC%hMm;L_EQYYIA85RX}-0vi>BD>c>i2;8r z;dP6yT=>C;5%|&z(7BXjyYh{knam(53GgT$u4|EW(U-oivcpG`L+F2TE?Pb9p z1*$LQ{wj}qsPrA!y%;3}lD0S@LTf;dc-bq%E zZ7x;Rt>sd8W@lXSkfRlyvVS4~`**U}^JM`3 zJxmtA1N%4=wV3V8GlOngyzr-c`8>}G?s6YYHIV?vP;)Nm%^lvTm?Hnchpoc^xI?0Lv7oOQTOD{doePXQeVU|VAoG*Z_Py=7+k^18}1wefp!w=>4HZmt#@LQfRTWLNwe*^Q?mB z3f3LY;l&*jbIr+Ea?B2Op$B>@_b~b*R4XY&jSKA48qa-)m5W@v>?GeGvp;u>i!5N4 z!k0bva>-AD+=CX$oy%)dU5Pu76zI>nV?`roOI!TeTSA|fE&%WNd4=-aXWv~dzFcIE z=tSN_f$U}Trb}~nG-kD7Pv+7r6m;XBj@Rn6DvN#T=kR4~A^LMppJgn9rI5azeVpe9 z6=Cyp-aoxsi*1pcENbN{j$d0#Mzc1uCs2WIHRu<;!1J(A3ij_<;ow>&YFGurV^09` z&ifSCf+jOC&wX= z9-OacaD1L^#zLNJj@ZX~#Qj`U2v(@=H!9S2%y@qDf?hqPQmy0|Fs**FG_69%ajioV zxt)8mUF6|Q45Da5t~=WW4LA38eBiDLHBOqNF1cWqD>kUFJrHL zv>wri449?*kF7M|`A_EdROgr!$@5vB)n4VCQB;?i(f5Rf;rimLgU+jqzTnoLev4qMP8j0oloP9M>_>Q=*5?7xh;1PLv??EpAsTm&{Y1D`+H#GNMCS7`{hD3bClIaFOJNV4tamet z?v_C|y67alnUUE*Dj3eGurAdZcZWFR1K;0<$Ij@zn)Ph1fo?1c!+6dU{>#`OHz^$7 zv_=T`Uq867YFmqaWo?XD9L4uHAP-+&^SpeL8Rw^P4K%@w-(=v|a}Eu^tWdAuuLWe_ z@ALi%e@o``x>1I$N|sjpjMA{NUOF1-pGeosi&$n1e08RSN`>^Z-0MDb!4qbd|NDgV z=g@HWtMGFh%gpI!;TRhmjz_Eogg6_}!$ODuS3UZ$XN>D7|uTzT~5Yu{m?7f6IsSUU2Cd z38#om^jcT|Yq6D(v>)=GXJTGfk*Kyc1C6#8K%3S`UON4haY}DA4jz3{SKBx3q!V(3BgR+p`%#vJ<5*kAnN zQv?=gWnx=2eQJ*zNeHc(W3G7NSt^OE$P9!}E5PEiMsjVz52;5kW?xPOem%`Vh&dlS zeHzMBZLyrY<&7N)%ov))p7<8@2ClM}O5}qM9`Ql*a?F{v&BWMq?=ay~L%H3EdCKR8 zV8Mm$=w_b@ZMy>cBI?UK=JU>DZgLCfNYs7Bv*kt11)gssF`X@v$2?p=p8HLU%0O^p z0RnwnGLNl9?v3z1g$0s{ykdL5GFtC~QIaeY} zy8EK_@<{wFB_DT*dEYJ#}fu#*fbPNweNCsk2f}ukNbRxE&_)F1n+GoHUqxNot(k&+ZO@wbF5R8k9AQ^q)Go0 z>0L4ezTYCzfjrdGcl2OZYa!_KTMCwYV@bzIwC3maWkWvp9%&>`w|W-P{hyt&mf}IBa>O#2-uozo-^zr|Fn%t5TFCBQ z#jm@$dG(Ip*OG>A3t@(3yHCj*nKGjUpo{a-@lpEDETF;d7u2oZHL-O5B+!P*VPAKvgy+-VZV4%0qTEhAzO!) zNYyspIK=A~I3N?d#}x29%|@PVDV5926YtnK5<9cV^A4bo@?ljTi+u(rRU$t~zOwI*5((ql<`H?r)+aK^>oNbgUPC#U zS0YcDd%pi=1orcF6y#4Q@xC3|n5FZtgdtOwDj zd87_=aPHem^)Wvsfqu_tgCY@iAQJ=o6`<)t8~OTyx#Z;da&Iz^$SDI!-uY*f050k7LR^4&k4yn`ajR`iWa`hw3M5FdMb+!}?zl^j{`mf0w(WWnv- z^qOrTvv4v5d&m#o%E`g*z7{N6xlaQWfsGG}^G$pB&`%fIko?_)Z1`O+gGbd^ z3AA=X>by{VyT}}BazkdZ;O`pr8@_YIu1-OiQ24oH`CjUKRou7y81; z-&G)QIB0adbTv8R_Q6ne4<&awDjW85m~UI_fJ8+)p>B_0EJ&o6FoyYzH_Pys^?n(| z99YlWp{O!OhlF6B4ad-T_W7Ws(*IcN40Cn6=`nwP4zr4QoxdNHvs>*^@+cH_d+N|M zmAS6L798+Nl!?s6-qJ7_UX7Upz9t*flP!216DMOAIl$$wAmkm@AvZD`L1qgA&n8I! z$QI}p8ia$TN%%;P(qW$k+jQ|V^R6RGCWpW~jXYgw4%(9+95g;b=InC9!h{ga)9SF0 zzPU=|!mIN2YhK8iYG03KL4FOtj2||iDb=j2N1%qOvjPE`k83)sHH@m#k_C(>v#shI)JeZvlktaFXX(IDK)5YoP1W73`{2<+Pngo|ti`a+PtsTcTqD*GeYU5h^L$v+CuL*%Gbp~vvgr~n-B)FCS%1N->; z8+t^_1a~ED=?(OFq=kKP1}3JK!LmWDgpFr!@W1}pY^g&pJ@cA*e|9|^AunIkmp3N} z-}}?g_$M8k^rbMajh55jZD42-2)}hYboiT&SLF3doMPm1DRYf^AJ)64#l~0UdFzs2 zes@H=^k8yy@=Xbs-Tvq> zmR#gg^1r_1E~`h2`wjXEnUn5F9?-2beXJKsk$fORvMSkON7X<)TtF{j81KXR_4i<{B1Eut=FphwR#H2o4K6Pwtg(x4z%m(xPqiNBZk`I_0W za{h-B>(|n6_*;vWYtqRoaPM_GS}e9G5i*g^w-H(#-<5&&_Ixg`M#-sOHu!TQ5DR8$ zVfBkV^5imPrA5lX7q(bJZhAS#$?CD>C8v?I-V!O@S6BnP$u+l$gYhGC$)A3=H77an&V8p0-j#x7r^+7qI`# zG6PStOHrv?l>D7)4f9NY_|~N-?oI~!rj?>yS(IFyXNx2A12La0SD$g2*xa8v@_VAl z2-%`aXFuHKd~w2$oV9`Xl_^ThLT!=Q*dLv5X|ZMxpO-cY*G>H*<;WCUyjc~5_D6IW zbUp)PK9}O~r6aQ9kuBa|<@LYA@qb<>9`O7BfBlTrN5vZac6hlAe4To+WlrOim0PS_ zDp^%Dlud4DxTJn&*j_8t@J~^K!86S)W#9?5!6u=;VZaAna`_q6Qw~l)W=OiT*QNET zwB+F~!7hJ>3{2VFV}U{A8(`>o$C6_9R|fN#HHOur0=u1QT-#u?;iI8b{cSGGlc#hW znH-V4aI#rSIqTeHx0bzD-pdoj}Vh*la`(Mqd` z1gSGdD~5mLq;6DIS}^->j2))?+mR<>Cc-Ku_CL47hGuH0Ym-Ohb9rIC1CGv9!)Z0M0mUFYmCeW7H|aS-x81>wnwZzS>rfAU56l^onLFN$2zSZ&+~NXT%^O50eaj?)ZzY9p6$QZBR7f+ zvO$O2U)W>tnO}dW!#O8Ce(>zAWHNI=3i)@^nDbSQ%wuIeocS}GZPa0iFFia*=v}DA ztgq*MhQ}}i+ANb^EqZgl@oau3>lgN97R%^Re8f3%6&(?Ynb_x(g~#_ZG2eoI#(m6@ zCjabIF$;h5Goks*9t4iB^|R^nIhctq2|PFI&Y!iCtYag(6E0+8+44fbau-;6bqRd(XVx@WKPw$krxYccFoN~Ho@X>dm=H8u7!Vwp-_thW>2 zKx^rG%|@!Xv6UEi8yOJUN@~%0kXYSH2F`F2e|xpOCu_B-wT(PZw2?{fWFDop_y*Vs zPTI&@vXFgxIY`^=4l;IHTj_AnS|;vxka?A?q}SEPGP=A{npL)wu6@jKw}ei(m&HqE|x#dOXbuO)-;ZLp>9=A9C_%4jBK)02Rsp*;fb_l;h<4&E?~_lDgBFYL`^p0phqMIUBNbqo6+{;F9C_kF{| zU{Nj{&l`}bDj*9rkM&+}@=?#jkV~IUky|)Uke^Dw#9YOruPwq+cNgm=ufs6OijKO9%zEBU zZZX@4VPqTo1sdTvG!4@(Gw140Dh?ht!kwSTcQRrN&mJbfVqWe+BRn!wxvpZZg@2~K zNkvkADz;3cU$LW+Svy9gu?}405&6fSsd&oI7xH_0kiWV-mATX83VhZZG4ZMqUHG%d zaj&ErV#Kr^M%*YcLGd^j39Fb(dyS67`gs^M%!Eyq>2+G3i~cK3_~&dcuAVnxBLBPR z8~Q06O{kKRi{5K;v3PuF{Sxl~gr zaXJUF-`-lj)wY&Xu;4=48{NxvT24NM! ze%j_9*t&>5#_FDMzUs+*RQe!U6Kpca3v(NIAz0}}w~#02Dlfd6ABJt2VVD-qX9!_9 z)rI%{xiB0V9ELtK!{|x~$E!MF7|D93uXz~8@Oc`L!E@7bWOVwn)=55b%^5O_>HKpw zGox#UVb1}cyZt2dcsdMod-Iv(=ZC)YInLuV#P6NOpa0H<9!Cjdu1pxF^ds}b?;YMN z48Q(Og~bvh(to64g*`dLFnSvK95nDU;!>s&7n12+OrwjXl@Z0`jQF^lS#A%F_)-nbkaA7Eaa6z%?;a)+0_vY>1QE&l1FJQJg%Eijx}dG3>u$cIELHu^>P4XPaJT zor{w;Z{j6og;t{Cw32loK}w&qm!?ykjA^fx!mv2`Q9&oKV|7xUIcBPJTIv5=E7j<7 z{7rtbOFtEc3Hij`_NW~|_o9kkl570ssPMdmbtTp&tMygE>!Tf}m9xXIU#tzDCF97mo_k~Lp<$h{ zT`0MUnRc-JSA~FfDzq}QN7_*Kri5x>-kHut?!8LGG#CoHylZRFh3mhLJD3kTSp(Bz z4L18}u=aHj9U;L;W@{k8Lc(Fu-EqyfTXU{G%t{pR024THghrlX&)Xmi4(0taLw(Ia{ z20bHO|1~*44(JYDC^nTxLN$(w&Ww%a-I3F4xjv)Z5^#ctyC=rJCmP$ufwsE znTQ&gNk0@F+GHAA88dO~8GAwRX2O?y<1@*bs87!EJ9(0q-`Pu%Gx+q&E)j^G3y!-WVO?i;r9n-Q?Qh&TTT|zn1&?YU6 z{D_h3a?anI_;JdJfIH;3Sx0x{{5&R?V?rXwkEZmuhSJX(L;v5CwzBC@C%JE@mfVkO zIl1waFF?NW<(Ad~IY40yLcG-;s0Rdf=fm z-ASkOQ2wo>+)8zndea=`#TzR*VC^X5T06@38k|QPo1ynGb3AsTAG{JXJNfy=2i|C) z^TdLVzBpP$4~XME$-^WCI<_~% zt4K4PNi;_wuhHEKWKgqwFsqL@+LU;s(I6jGxkVT9dmnTsySQB&4$Ycy)Z+U#<1zig zd&2RabBsDR4F}H{@##q#E*Fyr$)uxk7Fot~CIlPk()9U{lOgwRBKN@S;~nTEC-*vv zswp|5%r+9dTq&LX%#dGThHY9iSnes6({oGZb+Q7Fv~(-4_rZIvn`e3WV84pJJcoR+ zy(kP5E^^*H%*@wMWGe%9V|kC=yq2kG>urSj^fVk`CuLzQ`(nnY!H@i4jcX=MviXdb zah$h!AN_2Xhf50_BsrnIoKI28DZRC{3u6z~YNhAp?O3`BO8Como zUi8N5U0&$;%L}%>z46h}7ppfj|9TeluJv3mlbQL=>vFNpZhSRxEx`Nd(IPTMyl-k& zNyFTxX=q9&q(MvaAM;FzcH;ZSHR9Qi%zz`~w5qjM;>f7ye2V8eU%WJbohUc_xYw_1 zkKT>daNE`vXUL@$)pvm65y#iaAk4o`H_?6#QaFaTAe+7V7=5<{QWr#N3z)0wk-?A$vmU!t8i75k+U+;LC8$Xw#5q9&N^mG z4^EUn%)GvOS1*<&dg(}>@VU7fsV3$t{#L`Cb^Hm|1Cdj~PYMjeZv+vjee>C=3c}5Kj z3p-q%9gIsOHMrI<7~`5~fRJE3?HP=%!u~^!>0L{7I60fy(>LPrp+y25yUy|qLkF$A zd`kb|7iMwW+XHhQFfWc7Im=WSZ?g(P9fPsQE*QUaH2>pi{8fRk@eRlQWz19V5|4EY z=^<<#kB#J2x|L-jm7L7RRK9QH=^`W7*nLSh{$Va=B(u2F`El;9!c}W$=9)f{yi6Q< zQ%Mx#Wxces(26Q0PM+`4$^*3;wVl|z(8C@UdO?MbIpKK;aGi?Uznk+qcb!i!84rZGPvF$)(KlfU4Z!aKUi`n6ZM zZo8mxy&0r%T|lnUjZB9BNS&lMq)R$VD-HU_%7<*NTp+(wy|O)alR53o*Y#qb8sp0B z;a05TH48$Q3*;#+gVD>#*TlJc*m?FVl<3j)dpy0XoQF-!$S~t|8Xu1Q5;iHAlgB=+i)G>!>BAa_4_eY?w_}zMrdJz*FP**NaErZupTaQM zCJduvxsP@aM+eSfOEespx3HIpYw%L;RaFDnclUsOK-nf_KF`J1PI;)DOxBy@&z=i; z2x!w;zRhSar^G>OzqXf7=jiL-)<(t-Fh{M}aK}%6AGi;9WNyL<<|*!@b7?jGxi#1i$lpJV<4`L1#R=OvHXcvI z@mD6i*qeu+?6oV)pktkVd@s%Na5BAvXts8d;6$}Fv9ysso^52%s4nvNz8QuU@Z6=d z8CJhkp!sWaJfzq6*EMg{4QAeS)CgQy;tP+8?Afg5i)Y{2=XEa}jg{f3{Vg23_}{Mw zaDKgFgtv|iet9yDZ7#w5Huov(>5P0xhkFKHh{5E$cjcktz&t$Y{uvKnw37v~ZKbMD z8>v3rNw&n;NyFI=@*~F#qxjKBYmOuCCE_|=fh+#zSQ^Xq#%;2vEq(E8yEnX3d{Aeb zFCH%nM|{OFJnkEgwY)}yj)r4#=iM0EpZ$@q)6k|-8uk^C&2P`SbSiV69ZXQ(GQrA7 zPoy0^gxq`VB4?>N(^h6rY%gD?sAZqEjWnvLmd!e~j6bS?AJ3vnBNf}Nev>Vpp(z3}M<_mubP751X@cqaFfobRjN49C%6Ba%JS(5W1~ zjGRk*^<~eeC;Jw@n=qB<3g2h2zmoGt@;DQ2)XGEc-OTR{S4xL_YDu1IBmcxXivLDy zS$mtWqn`rR+7`>m*St2NJnIS|r`yL9L#@0qsizmtk7a)V_q|@fy>Y`Y9G`oIW9o)5 zBqq?s>>G}2<#>Iz8L@)zSs%iK)#Du$b^5D<&lzW{`sKM8C_6c(; zESNLBBT*Kr;-zsMYfRVl;*zA3szG$aUts%v?cet>Idw-i0L)Q(5;adPkvGnvzqiP4#yD_&>PJ(q=)W$eeHziv2L zv^^OL*U8poz*zfwMgQOAUP;pKRia$t__LGa(6J^7GLHMGh&%R3kK~-u#R2|Z)R;_X zt&wNvLph%=U7^9l7OU{$G2M|5=xTgO=X+~r7W1{JPU*0}8C}N)J$g*xoEFZtH^=C9 zt1>ZRHaTjZ$5!BYophxPGi#Z-{v}J@gDkaz{JTRxGuK6r_4512F*!IrLH=2tAiFrH zPJWOeT@P~X%VOTqAo8A^*ISQPdwOcgU(VeWPE7@-MV6-@^fqtn5Kj+dLzgdr% ze9rA-^tfE8!{vMAJ=?LbeG4HS#;!BZk+<<+B+2<1u$fJe1t?EZIz#uLFDbpRtcWgZ)-PTx&$|n%vKV{z4YBUa~RZ z1f4b;%v@LIC|s{`E*rW;;abwo%yk{-^dHCdGNB4*u@ap$;JvdhS1-zH4%nEk#{I8! zE+17PaGe^i$5b%v2}1dp0K}AVFSkR3vK_%Ft+fh@S)8jL=`mqcJeK%yUVqAdvsQZ8 z7PBs`$i{{rS!n8>jXK`h$nKJbr)1x+^-#FhWr8th(6M?*fj(_r?P4AH=! zbJmTntQ!pGeZ+aI_z(L9#_18y9<}&goY(u&H>zUp^y(}O%g=%>=P&1JTm!`_TrZGg z^k(nGo`L_5XDoVbA?2?XihGG0o=y#A&MUoa4!LNhXHKhYvApWe^Sf2UR>)0da&|2o-{VUT_ z-BGSy7>CZ``QZ{N+2@AvHS`-sry}A|F7|wADh-%}ykzij=5B`I-dLWK z)nV?(+~(4~QK4*M{_MUVp{SBg4r?kopb0JH3H@UCo_Qj@To}YP6$`I0f9I^Nw5?qt zi61-=%QNpc3id!f&B4Tg#?q5Hzq#Mt@nd}`?yV>H_fIaWEpH^dW)zC^Sx-zO=UDum z9z$pL><+P#Jwl!_ZWx{N%(LFabL~&Lc&Kh6yUD?=ec+Cr+e2acz_R02<_@>0C&|N^ zRnyiJ{p$1F@JT8&nfdQ6YAW}){gI*qcf41GV%X9Y%xKQ@x(H7Ds z_>a_oG8}JxLa|Rz-&{C(LytysT3^U)ayNXL5sDz*Cr$Q~6Rh4$wucqS{Ok0`IfkHW zZVIXm$;G7U&BXG1p>&z#j<$v5?`9gH*hTN#h88j+k7@3wJz=aLO2;GfyF0Om*}jR) z*jXqkv)!W+@Z^jea)@+G&G9cw9u z@FF?2!yPaDLr{>Ag7d!2*FN4qU!`OGQal7jjhm{;Dku`obRCe)xOkv#8( zXx{&dT-MWCNQ=RLWnzLmKG!54w~z1FKip?8Z6u8w7Ko+79ZnzUhcHjY7xKSr_B9m; z+rRQ=zB}%{qIa);Dvs!K;M%;EG%qNS&J*3x@8K?3bWTN8r(C2AZZ3(YKavx0>Cqq#wBL&CEmrWR} zl>A|363BX$Q+aZBHI3NL=lXZBg`DeJD&NR0_P9#_X=na>o8{u>!UpmWJ&%j(df-fB z)`BiE4|;nJ?k=;I6D@zs`NM7~yA=Wtcjjx?&xLz&Gda)a!h4q|hI9$VqCu(1IQt1F zD_O`KQ;8g{Nk{e}@^rjU4%>09^0%3+C|4r8c>hX2-$(s68)m8(%hY#n_6DUzG?Jj#erl=Wfu2VZ~8YkCIre@oJGa-G{l z@GO&D_7V2g*JvT{?i9+rT5fbLhvL_vRQyA}yX0;wnNYJp8aDO7x|Z}^($n#FLN3f} zG?xi{e=W#gcR9gv=`;Dt=o~z~QCITY{S<99?>9vlj@L`Y)k*Z6@;ZmCE|7A6-EcQM z6h3?CfqnG}E1fMRmE&H+>Tb*&BL90X1%IC9F#o_>`V23YtdDNk&vDX$*KOzX9JKFb zDgUnjBg=+zJggatc?XzZPcFM?L}Rfz|3}6?cE{g2p?Ec({hYPwuc>NnTiIjlON;oG3pn`!s)SGnPZ{)U4MavU%K#vyq;q`sy?bgYp8>tji z93$oWaU1A7$kR0;Ulzdn^@K9!kVJ}iRcm~$%iP-!T0C4yA9NM^%QBOxH=^31Fhh2_=xa+5dtj}P77;~#T z(+4-g4vRNvu>XJ-PA4)@lbl*aNsK()Z-+|{{LrU5xkB=HT@IJwQRQfHZp^&t*Z@4} z!2bB^Qu0Q1dcWWR9ovH9I)Y(qQxkEu6b$U^qQ-7nO0cuagpOrUYO^ zJiU8Lu8muekJCrVpsM7mssw>X94sL>;5)Ju-SUr0V?8-aa(|b$@#lwTpsQ6GcH6|t zr7U_39r-$w$h&>dz_j8r9G*Z9Xqpns>Eo;4pS?T|JV!2NPVvhqX{A#_^Obzu6CI4R zGx5`oT+*OOX|q#_QA3z({6LHGkJ53MUQ53dk#gm}4Xix;k;VMqS0(8@*Dix;ZHz=% z+G70`Ke)Kkdw4t(c@@gI&xnw<%%QHAy%N*DYte2ExxZ>WSNNAanzIeY_V>rRtvYP0 zo{4z=dq0djC=cl$TyZrJjXLTu?PEILSLf>)A1M}rNYUAV@i?zGfMV6 zumNraK<>xldpW)@Gs!(|ij_31Kt4(X++Xp83=e(-W&pYSRA z_-qxf%g@9~g^M=0*_~dk-Q+QO|L8`Ot7;M@^Z9cUCk3JE4=u_nW+K+1434}$Q>!cC z=Me;7@@s=eWH5)K6yLHUq~a-h{pi=5xkig?^)m3yybMd8Mao25Iw4*L!r>3Sgyg^0 zhLRio94To-=+jIKz^IK{EI3F`)}Q=ruPAwT%m%d&25_CD#pLlBxZju0OO-fr@5Uak z$AK`Ci`@1*1G6Ga;oU4+I*<##*(DI3H?*i=&Fm(=&Ku;vek`|znz`*Q$?;7i*B0HW z45OMv2*qFMvBM9^=H&hw@qTDcZnRO9IMKV8Z03hvd@ih}X5iIig{!e@gp3-m#CK&N z*75o3?URWOyq-0`M99Jp^mxu@jV6Kl$h<$lsmsu9E&01!wy5kIfUa8RYp>0K|MfE5 zSsEqFQf)BePaq!f-`lm6{>pb{=wlxvyE@t75byuJ!{V^MN+y11l#=_1mBq|$A5n!l z$PKhG)+Tc^ikxXmlr-<6q|29Cuk*q+M@czn6=LQEp+^OtRkEHEL=N=9 zt7xe=L&?kt`u>LSdB4E?^dV(*AI8f2Li!@#1;M@#eTC+ks6_tPm~}+vGcP;hq(3Z` ztmm}K!0xJCzw4r;4xgiIo&6C$M~ACB(~*CkK312bGH|$xz10ECtI&Zj9+RBQ&^9|l zo{@hX@|K>^W;%F$BiBj)V5Ou8DQl}lT%qMp_ zJsqnTmtk#QtOOrcqF;O<`o_lLX$0R#Jw2ES{Qi9YoZkM}LVmVcwM=|^TZ)crV&$gM z27`A5qDw0sJZogaE}i~d=SVqp*ajy#9?qS}UdIf+PA^_JzoYWWgX7Fne=LjDqVptj zn)KUN`w=7ank(_GdjQN>!%HUj{d^gD+e`d8j!M)#;g1_paY*O$xMfr+4vdVDo2hm% zkP|;$M~m`h8Ns|@`T>Sa*+JvLgrQcx*0ExT59FaI%Zw>*NS(I zczL{DjS2QDW^>V#@L7dEj7kq4>BO52IA@;COME&+f_PDs*bC#wj~{ zc*LmDh4qXbAxc~wtH#;u{J!<9g|`hx8tWMQrUvp}4MG6x(phF2o+|`mJ?qL#9tNQ) z&+%(mFf%YggN(X?sI3pe;Fiq$Sf)YhG!5KrnGHprvHpCXb#Xmm`&)zJ0rdBD3Pf6c z=4;hsUHY^JA8V6YtU})o&!1*D(qP;mW`*n``#6Qab1u(+-Unfdj~)j(-_~oZN8uqI zb~RwuUj}oeyYt*7M~fAA*;8sFtJqhMF^%JhxbPTZfmPT0G|eFYC>WCLL=@o#|X47x{Id z9-*W47^Ka_E3&@LD`%n;>jR!HnaJ9ig`wUV@O0<-%ETgv-|dCw97fVGQf|sVX0w`{0R2ZeA!LXZ8KACzLr}bgX;f#b$bV$SZC)d1C2Fo->zt zA*;SOvXs8K$e*9z+6O}mJyE>L8y?p^ahl)T-~_oVdK(Xue=^_7n#G_nXjvz)>qA#u zd>DM4!=QAbXJ{S0iHCNh%FQs?WwSOPO80zl7@6N%h;T? z534dVRpb=M7KY&>&)Y984a2YpVQBd$41R0LJd&~6TA6uPbD0zQCluo*gyHiuo_~+0 z^RWl_N9R&8sHYJHi;W0+XT-G&Mp*A5lQ1fcwK>)=F4JAnnCIdbQ!)P+{fs=jar%}D zd^4iL6LJf$jj*|9#F*`@{raV%_DLhEgpg?*YsBwrM!b4sgza&<;^va!DoaKAW=2@K z@_gWn5z&Ek8nAZs;4WQs4bl+2+64b0CVcQPVdMcahZ{{$4>w^IS;Y-&Oh_7GLeZUE z%pnU^{w{ebPu90*<>GM-Iy2I9af)XbHLI9#P|g3x^Ll05Jk;EphkAc(`w zg1fU`Q&23W=4RL)#b@MtiS*I)xhg7_m6OV3Yr_(G;?1n~!DcwWhOWoPW+=_)9#_d) zVN@w|G!!W3&HOYzW4(AbGontJMD8z@+@@xjcc%4pXXJ~XpiOd zQiD9>$}mJ;r*~;aI70QIc)v0ft#7eb=M>H?4AwGBnblPx4EagnC}OQ_ZB#ghTn@wa z&pfBS5{8rHF19xd$If;1eg)Bi!P=*Fei*#Vk$oWl@Lw(I*GBqO=acKUr5o2-KoruqC{vW@llEOu8#DrlDOn6?vzGpsjdE59r@_UAFGGTlv&&Fnw1D;FY$V;Ac3^1Xs z56_k8unC|iwLPEDa9gs&=W@|&IDL*}9h(>C;*4b;5^I{^LQW>k(uAz?w+xZd&MsG) zr5fsM<{J7<6NB%Rk1h+oE-?%})w%oA^W$9FSU)$cO=)8oP%+3bzRD=Wf<20q$GfW~ zZ*@?lEV_8!;I#JT#o5gp8Z2+@>K?zjP4^8yBa?e)pEc~QY46fC+{tCdiyg@sN8^&c zzWW-MM{F_dn`+kMZJd+Kl};Cuk5(}zxBI@x#s1(ogZa;Nmm2PI;-b~bK)Ms{tjQ{V z(90&8OdKbS-ae=#@t`@d3&f);Hk##A3<u2Bm!;d7V%tADak?@bm=4cOCil673J;ofpxIIJIQUiMkYzMqMLftl!QPv$U& zXF44->2hFx8P9{dPS1pO7`@-e`1d~3+t0t-@(I1(i?ZOvn&iS{?iH}&E= zacm|I@oQ^rvXJ?K{cOLpup=iE4Wj-Z&shAzQ7&Gvm634{a+AKKezhEAZ**I6P?p2w zmnBl%m-9ugIjp0KMfchaF7Lh2jAL-icg&-7@-_S>rQVI8OC)wA6zT& zhRN0&%{-VDx*!Y+=Wv`So9?oo?BEdA_&?BrOYXw12K~1KFJT~GPkycuUFp?JUYdtq z9FKN2&V#pA9vaaf*)PLhUTEJ!pa{?kqlBs$0>M>`qX zw7ulerFm;dsnl{+;Po~-%Ck!3*~wDz$ne4tGhghai|p_oPxNl)je16Ja*N?e{tgOS1bsiGNnb6P3b=xcUsNCW88s{jNo7hRE{nqm3qLSGM4wA+ml0jUP9PUlNa$K48 z=9*_yWiy`HnBzKKRA##q{BtM{4^uqKA4PwyBa+osbKy{jgogNyr>t9 zg-z&YTpf(*-|H$1@ibk}oTzxzuq7YfjlF)S$rp^y!nktTJon9pfn!-S zjz?)^9_pN7Eq^i{hA+f+zn zujY(C4zMOmKZ^Xt89OyX$;GXhL)TW42Fm&DvE=yQM>r=K^zi2%{*qrjENkkqkbC<} zP06?lX^T;`J#r|a65!?p0(;p?z2RV5kce|UXsz{nZ~B=8f=@Y zL8MnO9$wYsR1W8Z{_$wAL63f%TYk`r(3EB*N2(+}w7DBWM`YI^26ktOUID-Cz(WaC$!4Y}Im-wkR^Xu`f!@-lU& zGIN#u;yu1c)#?Pp{sq~h+jJ$rXYFPaYaI1??r}CAe%08^xla#<1mJG||7Mk+c$|rf zcgW0_r(g3g=b{c~t_{bMOKGKWb(*4Z_0W+|(I{NY`6fyhGs2rp(8`-le6JeCOUt4p z39zS|aWmHsB|Mi}t479QHQL-(W7K%QKV(qbb3Px+dD`(t5H_}>f2&ZB7o3+z$Hn6f z=gG6R^{6$>}zj@>#3~@*LR!9gmhB4{#Umu zVZY?uO?EPFj=glA+eSJkwUsmT+R03wExf9vK&Rg381vU0eS4ZAwyPO_erC@T$Ky`i zPh6!Jv1)U=eV2H`(k&cWM>s!lOg1yny*`5bgGXWbm*er3!D)~|X&A(DxtpUAdtT7b zIx!C^+w;(jW8rghd)rgFR&Ha$_TC+2^y@aV=T>uhxWi6tBJAbTWP2(9UBPT)1%9k3 zl|x<1r27qiUfv8>`}x3das*P&dE+|I3NB}puXbdAz?V?O6^G-JuqWy~GaB?^ICg_v z!>lw^iXulHZ^WA$M%@0$J$6DGHgHY8xOyH|-lXTeCb_gOCS2hCN^BiP?o2}e1k7@jGOJVWPvzS)RPX6!*+!aQS+jcqv&c5uyu?@_v5 z7Ug0)_Yubqk*_@4MxHdVmu|kcQu?l?^j&Tzhq9d{g!8Dmrvf>?e`J$miG;T?gBACc zJ{{@h?@Om|yeF#j<3W-S>RtB1XwF+7gXm}Eyw!>C)3R60p@<;wsiYs0>x@QKFJX3F zBX+4Tp?ELdQ1!^?eK)~j56=V6ny}HF*XXecp@BA1%f?=!%Gt^H8%|P7=&l^fp2Fc~ zSa8Y=wS7ut)PPcHzeItl^LUoj$_wV)W7ZwxgL{#l*sz27+$yq!+z&c0-;MUw>4DA- zhkq1vGVH^#gX@i);5011%RV!!H1;X5pW>$xvGSSsBE4yxGj?cWv4#<6DbpRYhvusQah_QAkSV_Xw0;#z0*)-=pCPs3G*djOWxu**+jqs*PYa5dD6~$bKyd;2wm| zn*<+wbX~;0qJkidt{#lm!#VCWBL{YZZguty^^9TORNHv8JD_KMLPzc*9xaNQWpf}K ztBy0*<~=>NR_yOiVefXf!gbyyg=;lB{h_@R2Gev`^&YDBe4g8v*x_##)*an6h^V;= zjm$Neewuw-+{6+J193?i|TNUw$4jAPbGw zlaq@lYfk1|(?{WY;sf)+A~=tQ)BiU-LB1;Er6gV}-K)}{;G>g(?g^qGGq{4+=s_

n zGkHEeD+}FwWMRr}))K4Hhqx#UVxe%YJ&P{ig&dpLkSE}Ht-MKQ?@f}lwbF|@*Bra9 zu%Kg;6N-ayc4{!@R%2aYn1*}KU^w*&#*DLc zAT5bU);c8pW%=H!L(eQW7 z1DvgJ-MN7M9AoLNyqzc=R66N#nb}#~v)?9@zk99<@=}dk$5f~nsYH05JwofM@#GcP zJAtdvcY82$c<(2vnm}pmNE@XG0U|*{w)cJaIz_ z&$*tGhZ?+%XDUq_$crCE@@%0yzW)lPdz|M!>vEyF%G_$>FWI)&9YX_{Uy?xo;JF-l zS~L-lN_4E(_vHOc?<~)k0*-$~RYiSS`Jq6jSr3Qn#}K6TOGS~Iyv*KK(x-8WEIRH^ zCMFcF^aIY>k^|@2O~i}*QN`Jwh*7c!I3N|1M&{zLQ!|NqQY@Np?x?yU3}eX;9$1`% z?siRNO7#L!wPb#4PACSrkk|X~-}R!dTxPAnME_%&4SR~ar~D5O^|jDiJp28XGirW4 zf?mZf2CQwJgC6AR#`EY53uF71;&rT0jLhj?e3sW?Y6>nk%Ef9$ z3)U`5#DzTF_!lAQ*@L-5*?j%Xryeq(SQgji>+cncZ;w*(V`C2Hudon{_v9=8afh=v zJ(vab(EZLqs9QtX`jt80KRr<^oV=%`p!Mw>)ack$_E#yEZ2sQADxT%9O68vS6Etxx zrQ2U}i&N--Y{J*yirzh5x2GR1rKsW$xtZ^ddV~1$`M&s9WIyoBhVr&nf%vrc#JJ<3 znDr$UV_b9LJlaxjz9S(4nz*em44)>G^seVJ_nkA z8cJTLzf$ifbDZhlJW1YaOKL72*;~rWH>EOtfIDKE(VzGad!KveupUBxU$Z|lkgv0` zmbu=1zb4yr?%L8)HoW{RXO9g>$8Vt+wVn4BzwVoFA^KB=^2ON$H-)diMhYtNe)Ae* zDTi7VOHB)R%=HXGmr&*fd-C67)*YdE->n_shktP7P&dW|3H~cE_xn zp%@aJfV>)0#Zp&k(%$Hw6t_fA6wJa+K%vrwcsL z=0gZJKW3h9^&C`JSjpabMKW}l8$t>~@ZKkt^LP#vzLwHp+;7>imYEApm}$_7Yn=zV z*!Ivy*3$DhslXGBjUi~r=k9&^9OMVLmd{6ji`PLnY$y#yuoL-K2cGF(wvZC~6MyaJ zbCJZnqNfIU@5+Tmj-^!XS;+c?2NsMaha1Qo=Q#RO^IOQOM}H++;Q_nrA*h#QU}i}U zT3ED@Tir_KSF{J5bLnaIPQkp{IaoTnvD8f|lxBTB>GvjA`!fY$VL5PL-%`A#P@a-2 zT-BF3VTx4LJV~GF3M)~NUw$jYp~(!v*<&df_bCVdYg@>C@}d1}dtizUbE5y_D_7>i z^RA_gxbauYHRbaa6av3zDQMJz*V(&;Y)WK}gU`{nFaP;5Q*pCF4o(!-m$mJR1l=aQs@bGO2d3E|XT}`-_ZzXRJ7K$4=UuOxy$Q`MuF_c{MhWhfO_aB)R z;)y1yNLP}Hl+ObgDZ1TXY+)(u8{h&oEk9m37%cjMQmw2zTb)#+zqesSN+S`^I7fTghv+crf@dX5cDvjY(nqr*e4GfKnh z^?Mp2J9gW^da6HueWF{aDqTPi$lqBW5uXAZj!}V_xk!f}C3{o?Rml z-yGTF_&gok>EkP5e(r%`N{oK&kCh*_=-DA189T~wCL=~Vks~uq@rU`jI0Qv9=eMvF z#Y4&Ek$d{KGYEQT9V)cUz=(eI50VG;t8Is_T*rO*$-L<*^ayF`eftz90y$ zT=R}dNk_*9r5Mp8M&94I#gSHl*cHWG)J$@JZ_4QE)yey3N|?w=4Ve~)gv;ru$bZ*_ z7qQZJwGAA|8D;{IrGCGzMyyGRbGHaW*b_ezoT zEkca+omE-ok6LkB#Jx|)ejR;n1ESV+8kKZuuU;^}*tQhww?@c>7dD7o83;PU5i~jjWPAWzC-YD5kesjV{dH}m?ncGHI zWG#8dj}go|uth8Kwx-GC&gj!TVkpB;|0rp|`*XoPe;ggCLv&N-K$VtaR`VD+yuk+7 z_xqzLg3CXFhGumlWl0SsCff51D@=!>*O}A(xD?x*qh!6W5=BSp*E_65)%XmQ zye@@P|0s#zeKmFRz&#=-{FB<%MRT=j2k%I~pZ+=1LUP zOSpzV|4d#6e#Mod%0EZt!gV`DvYvB-yv@u|zVCmS8-65OlqdP`O$)?_b2?nAlz~Ur zOId3rhx^I~j>}o+IjTj6n;9r8DW!WVQlf*D80sE?={2-SanHcgUu8%n-*;N6#9VT_ zRaDI2`uq?T!{}k`6eaz)StE&l)z#DK<-C!Ok>%MhyE#Js1lwYi6&)G{T5Q@!p89DS zdRLB+1&(&8G4ubB_SSz53#G<5dCxi7^f6L+Ke&-7F;86~Rf6HnpZ_}Z z5cM`tU-ev^+*{#>sc)C#%PjKL1{01(Sn=|BtPrBcmJh+GF;#~?QM{g)t@v%nc`U{a zZg0sgHqm2B0PkZYeaU+!Nop-OJiopi(>oZ@X0QpDep;}gcD%f%E~?kn8 z;d0y=KPJdIdpC3$&;QF#hu}2oGsamlX>B4cu-%}kMgE%4d8fJLQY)|*KP*<(Xx;E` za|n)nPC=EW*|@sTiqGUm*9=!;@W$!BV%#SV8`*&}a{$fmp^qxC57(bjSe{S8(Pv;K04N1%C*5&-M;P&Ye-Rc-0 zo=x)dzIes>`mcPWN11g-eZQsWhumhp`U+!+Z=%FHB}>`2)YZ9jNbJtBpYW7HuthK5 zUM9=T**Y0BP$%OLB+0$wsS?JY*P!Rbj4~-=tV#{WLV8NEPTjMsPFjbiNJeeFxO^~3 z)>@rB*_SE@rt4*Vev()oCd>CZ2jwj53LPrD zBk3t?3!Fpue^TP)6Ez~rQ7eFq<9DqZ``6Gv8Y;9LMx93fZo*X7Aj+#?e?pD3TikKr zxe9~JdEh}aYCT4)(X&vET6_7rWDm@q%)jeRPr}h^B=>X2fCsFLzfxg7-}Ax?dRE8t z7z-Gy$WX3Phrc+nbuM)pUxs4;WDUB#=I=k#udurY6IU@d4`kklb8@X=1~j{=$Cea5`|PRpdyVTF z)|yvt&|{~L_2muJ0ANkJ_#^ci^?KH>b!bsY9Yz-eTE5XEi+Q6*jp$<$Wx%e1dZf28 zpu=v)fZsY8nYXCfm~3QSdKEg---55-#P=I;nw(=l15C&Dxap(E+p6?v+MSECoR5cg z&IV5$t)_8q?wt!O>nFi)v$5(kWB2}S6m6%Mpi>U&ouyQL3xuO-pM)sXe zn8V*<%_e(bLf1a@qJD2ex-DO`kTnO^iu}vuz+axn^=Kk^JLBr35=E zrMJRGwx=*RJj_YHH};SxUtMKlO;=H;c}RmV)O}o4BHyc9C3pe7-k$RF^b)E5-Xf>S zF8&)&pXfw-^~G7GQY#B}>TGf5w*pSvEHZYzRc^K`k$-9_kSPkpvPbRdmQwCNOXbFE zGLSVCctXv&i5;l>*i?ac)5td-P~d278@!}e+`bs*A`TTxC~KIt-t&DbD6nNw>UKb zD+7Y?&j9Wrz3EfkfqFd5Uvzp$T{!nZq&E)4=eyK;Eb@nIN7k~}1)-$G9~Za>YelAO zse&wITQZP?Sj&CshmBRZmzxxgp53*Ww3Ruiuk7_dOE27S++UZWMjSb)v1Au_e2<3x z3~~ehT5RR(C*RUyrG>qc>8wk04?Vm!wHxiVD9q4e{7W*8b}{S?qEBvJ>OKZ)IbSdz zz}(SUel)4c_u_FL#k1F}Ewz;Rx-;{%$mQPU{v9p;zDW&%Et&LJ$;9#6WUXx2(_f9; z)bmUv?a##34H-z?n293th!dErKfFB?wbH0B=a7ZjQ!=pWIrA?G8Thy<6N`|Am?l}U z9AW*XkbR4q40yO@;_=l?jC)LO@>)84;xaI6J@<~xv#)X?LphtCxdr5}W{|tmlFxcw zfN!O&)!fU6MX1a8#EfGzsFheu-MC=tE({&( zsh{O4aT{D^(snoT=Qt_zkF#VCZ!Ej)n@Z_G8D`r|PN_Lwb~%e~ zcT@4sah2ZGeoR+2l_$-ciS?&iA`iHU`fw9j7~EXSUviUP0ge*#i{53&$P(VNNQ8Z< zXm*hsj<(8;0;^o^bqnJi5q`Qspe6uME@t}7rfE3WjG??S$J2f6_ zkSXT4nZt3leS8e26w@yvA_iG&$w55VV$6At$A>Z4!S`?QG79VOYcb_hCejB}LvcYS z_KnEI?r`P@M`hp*$C0@WJ;5|&dL76ruFu546J!w+GWi~v$owM{FN?@B-eX_Kt&q#bH-+xTjjUE1#fuZ_bGo71k?nT^iRb{peIl`|fGJJPuN z$Z6y9>3+u1)~Uwwvo*%n^nJ{@s+UVklBD13BpLjXd6(y@lERwNoSyVMqZjla7M-}z z3)0>vRm!lZIT<^mEP!N%RI(_^eRN-*B-z(g@a8^wLAn~hhN&>T zhZ436$P##YV3(g7QHSZ@HPHiyQk1A)q{hHj?oh-kabUCxS8LMOp$2jJnnfyzN27W`suqrDIci)G>U8}*g&l+@m5Q-@q!r&YcjFJXnsLMUz za6hs!Ey8e{Ye9#iFl?B?bz)7{_=ai_RE4@^ed&L8APm35LScJV1LIw4K2{A!%EmBi zvhg*eG>GAvF+;REd1;rdV+O>QxRx-CDb+o+&!3fGdakLmHA zYs_pL15`5%h3mOn{{2eocC<@nUcdl(t;gQ&28{VL7cE%#%ZJ=?0NR*t*0;D@NC$4(m#|u_&Y{=@3 zU&?tdEEC^3=O|myBbf8aIgb0$t_7I&fc*+zsORDDCKac&6VGt9ge#pSc#cx;d9;(w zR_X}nvj3%~4MtwKLEcJRZ2Hp%wWbFEr2!bZkRF*@_M9Y=p}!h{FRfzGqLk~Lr&@SV zAb&oS^YKe99;_rA$6krf%d+r&Dz%D6(?575nYm%~PbLrd#zZ~DhyvJU+0{|dwtzW?mKfq2(4 z5aE908#@Kz6Jy6muB&>GXH4X|O=4W>8L7q7h)g`S<@|d;6RS998-{0Lm}?eJJt)AC zS_K$?H=ml-`FPFi^k`Z>4mh@wP4wSB749MTB3j9jrfntRw}*6_VS`kq0yg_f#R>(c zKC;E;400-DQJ%i%dUYXvGWj`btv|l|(|7tL**rUHdGDbvnU(izGyTEmZpYC>nYjH| zCh8P1R=mt)-Z={%)9F85A)lIioXfeUDrSF&W6O`w)cc6aL2YDg*Ov0dNi6|Qo6Fc; zt>yZ%Hd3Xr4L&_kAcy@&OMI*n-Om<^wmdJ!_BM^!H#CL44Qc!wOHWg-m8%zP*?Z1w z!)r9TTnt7I)WT&Ic|xuq6?uGKBD3g|K_BiM^8CDaja+zbHs>R74L!lR4m?X%ej{1S zm*zGyA+MzjrVjnA&=xY}aWgroQ&BJ5B26YKkTyVpB?GB5`r9Io3%G|ENLGd%$ow+? z2n_SX<=5mH#|Pp0`0WT!XAc6OnH?j!7WZfG13#YFUO)@-lrD~37f&S9NLEIv&O%ak zYP2;kfMq-x&lP0z9mrQYP%ko;EJ1jxoSsaNPHG|gh0)u2?lJa3Qk$`p2U@>SqBXg% zY)=mqy(5d!N&|b&pPx?Am#7x?iI#8=+-L>T#--9fnDz4l17?RCkb9GCb`Jwy^q`kK zKPvv4gL~XJ#$C+Df!FlNTuKgPm%{rCIfs4JN_u;UT7+8_-Y0i67jZsSZvUeb@3VS2 z_3WVR*>^~uT;qPfSdF?Z+z}X{hG%)Qd*7*xm`>)Ld;jZg*n5~4#{4w*^M&la4o`)u zssS+{=q>V#+;-hm_BfLRFU&!o0&>;obAYzF__QGVe|)fYJeQ&m3hxr?NS&Lg@NTkP z;qAq*2RWw5>0SmINS)#pJM~g4kY3NldPyp)hG~&IBFef$|I!`Ho~dDJ;!gi=4c2Fb zQPYc>zYD{0pmjKoz6{4c&eM)tsfXxK#&aX}BKxGG?>*`@j>zR&lf8e-*iYCu8^5-m`tz!sx$FR%V+90Vl#y!^MCp%p@sRV z)1&juSe<;ioGKx+4D$3S*%)4*smImm-i7f#RSgIFZcOV)E``@~LO>5h3i){FmJ6WdpQ~k1ei|4LQR8^BeSZsl=YijyyNUC>JuQl^^h2A{E~2LKWW6 z$(bBR*xGyQPp<)X-l~7~rfErzQtMN9_9e(ZI z(T>`g_w@96T`5VrA~3%b4jq z@Hijic^#ch8D25FH|k+V;=JRfm%-I zwv>5f_I$=s$2X39*lM(V;Pu<4CWF#)Gfe{qq<@tnps!pZScE3eFJT8%yEfv`Kf<1VB z1M$3+x?dv$kbln)^~U-mhS$TNd6aDjxwrEqXBowwwJS03Db7M-qb$TP&qBXWS$H`& z6T`n`A+s5C6HB=ls>i;7G&9Ct=RM=~XHp9JGhaonWdJyFI^;HTU${av`Vop z*EaUYB;Wskyv|HTfS}B>WYF za&O6iKFosGs4U#&wJ{!NO#POLwd`+;OQ0Wj1IG8s1yH=nM_+e7KeY=G>6(t|N8{=c57WagTCk!|$n{5Zw~=gGfMYplVFFvc#=aQ4BFM|(z{ zSgx_{d{epKpdR{8#*Mq=;ZIY~w|*|YOmombg}Kt3AkC?V&>$^E)OFQ3 z!hHMe2JY-*q9%aS9p~%O-+3qJLSCO+oC}+lq384i_UBIs$J_nvPw?P87(fmA`_x1v z8`rKE`==@}enrvi$3U%ivT>_B^IQgVp58$1LDs7~{A)!=#`td@3hyK`guj;@7F}6` zlDuDR+ARu@`LzeXq@GtTZ);YKIz$c^ZTbWbDe;;H*M}6z;G3 z-VMiyd_5)xGnUq)huU`o#6rJDmEAP08$$ z(Yw^$#=Guz#*OFf5xA<8<~33!im@Vks6iUkJtFJL5N=QKz?d=gms-bKrkgw3-Xxo! zLcQT24aUW5$Vh0=vJT@!9}O;6T7lnV*{{GD@n|piYVWCAFphh#1A0`8%0_7oJ~wHM z?_cRzUM?3U19I^05#z&gg}28fY8~_XBnI=mhA6xbBvPA^UW=^7NqnJBy00K>X-yKt z6c2oE<&LKbZfJ6sIy?XHyjHlw=}0)bt_Vd$oe;P)mfda5emxcaxswc-c-w%%^;6OB zu^yFQkg;e;F7|N_e(^p%9hig3tr)x3(NBqAHzmWkpj6@QK(6skW9mhc&2`~D{69Qn z=*ng?kU8-X=OLKQUiGEf8D!neNUiH6^IHFuFehK^TcX9qhMdp(nW>3wC*}Vtk&on1 z&XVtYH9P~cZOoYJYcJN*?Dry%_Gt@`3$`Ll1KKkp8WRsEkW)0dZiZDmYKNYp2u866VZ;ah{5cK z(a!XHeVvZ}qw`R%hO>C)TI8>@{^&cDI(H4pOOijb-fbu~SW9Se%pcmx+>hpH9x zO%iyziY8b-Vj9YVD5erbpw0S-}ZWaS-3%gwq4nCy^X%lm($_9 zClAU4_2txC>RNUVKzElYg#S#(?Y((8KeMrP$h62x`u5IT9gRCH(y_gP8K3SqmQzw9 zOGf*lM+*7M`5E|U1ohFTHIktGaJnDITgvCP>^9<7lt@_ApLkcZkbjQP4ZZnEJq z`O`PlPrOe4%RU2xEqtzKHNTJ-(`k@T(%is$1 zJ*Q^DWbb+svaeV!clE&rj-&gTtU+uxqkm!paXwxm4XIZ+w=d7XX9gM%CI9%czL+K! zOVJ!Z?CTzd%X>31HkH0IzntV);16ltoOzCHjz>PvqiUHE_pGj5D9e1vSwDKIMPp0l zbc9zlW5tZd(s*W(WRR<^QxFY#nSp-g%~;#IzLblgkI^$;pX4ZXo{@p)4f8NVI@am-&#NZP-|J|CY*w1_5a5K;DhdbEkD?*z{;5ftkOgTXpsTHlUvZ zbwxJ@=b_31J1K2$5l=I9E!R@N(j|l3B>llBG?XXpev6WNroFSGa4azct9gB{pQt0< zsi#?+b*G3(a+IFwh+N8^^b1YoN?x)2{h2zLypO9Erc;C3jPi9HGbUE3Ef?sQozyJ=2YYCd{UHPOIgW0(Y9OKAe#vw4uo>i4 z!-MEcUdN1+q4olLww34jE!Qg=zIW+UA8AHOe-}CIPCZciK2M2{#`!-okg=Vda-_S& znu}$6Q~IHwj)Fbsjrbnq1SgUYeepxiQzvvJdBEsu8EC@sa;|v;8Rhhw8bjn3Ymwt? zkbxUq=ika{CL@Zdqf#;mR8L2wA``x~&Dg;F!X*1&lI2fb-9ynh@GS#3znQU1 z^e*H4u;{L{L}vYz#*Vzsm9@BikUa83>WxyX=HjYi8OV9*ts`rCJ{h>>M6Hi4&7|`F zQaL+~zTvi7gimIUUrkS>9u3$>|67{H_;Kw(-ILr5G;7c6On-Un#X?!g>)E=37I!={ zF#2EKUp|K&vWlecRA0oAKkXBdjy%SleoyS>o7y7%!l^S`KN_z8@Hwwwre#5#+?q?h zHs4Uh)zaZBgCzDH=)dH>LC^03nJA%CoN@FAU%yv}ZaqwB*x7=(Hpw!4j*_*FP)ztp{%EQRn|@GV zY-)-qn1iq0J`9t|6KzXpOGL*WXz@ucN8AIGO7=?>MPVzwE@()CUZuU-NKscFo9V^+=NB4Q?2f6O7}D zDJYC){+WKn_PL4DQ>DVQsml@S$Ll#h8~fR_5gnBzZ+5D&n7+mb(}f*zv-V#-YWELqAWh<3hlok=vhME^NoTM&ZzifK!Sh(km7mb>FVC91G@q-?@ z8%^jqkZbOL$!#@u!=|cX7&e=0;(^)Bp;$5fX1v@^QQ^i^`b7Ka;ltzjHll9hz(iTM zpT5tIp@2b$kIdVeY(SGn)VJb#drHSdNo?qb`}AQqmC>U!YY5kVSs;yLrRyG7 zOs1aQeEz?+@6j)qJZ82gR)%#~;@uYdT{WVL;%_G<5 zMb2>|byT~%;dS$1Y195GAJ63qhTaDY&|r9A8bYYum)jfok-J zJraU}CUS6mo^`xm$qf%kF2}p=vHzd@d-vRgUqM#1X^|*SRp}SoHw@{csW18DA*?A@ zR8hrBr&J|coejhCw>o^{IBmJWidW7_GWQ=PhF=Py=C&T@3fZ`~+Cp8IWEtC!{Oo}c z^xsOo)Z_p8cT>l3eTwL3F(1X}E&mn$;(7duE>^@3N|vdqDtP`3!MW!;_NqU`sJY~+ zhf!aZI}u&^(k{b~?qHM@$${S4FIIA<%9Ww0?#sPf&uk3%%ZkStvGQD_gpTj~xCiH}&eSdSR(St>Oy6*m zD+s--2U=5!9(lo-PHuXup9x(iQm1k~YpO!M+MVRn z1~4ZZ$NLiYzvmgfpMNrL_j+aA(xid$;)X*;`~0QpTPklfrnK&4v>sjPHSqgnujqR3 z(`xmMGHyQD`+TPMTh{~kY}0rAT;b&q)-^q=dZgF*+SR(PF1(O7`|TR97JD9^-~Kwz z_+84UcZ?kEnRju@xzmorjMJ{&cy|(YP*IUfs}1wSDXtRB0F4CC6fM9ld0iTXIqN=Ye?9R|jpZZDic{7>x8Y=XMJMtT=F;S()pA+1v&!R%l zu1bW=Qo+2(1C`IH;q{2UgrbJ3whBke@wJE956Yg|er>6_7_G$ldCV_s)wo`u#+(fv z2(-=R4`iY-dXD&zmgNdv`^Lg*Hg6u8h+|fejhQ4z? zX~UX=nRV<{%%QO#_kMlWh8i&LB+-xXy#f8Y>JjKk-Q`bu6f^IiGs%FRzRW58mv{R{ zUoYk=R1OBbWZtR#F6v{b4anMJ!1#8|v8<+MBjZ|YSMrL3vayHxuQcYM{_}%gI6Iqt zoY~N}XDua*dKJvyjc1Le_&z-XnYXX@lOL=<(Z~yxTI66zUN&Z)&qbe3IdIxfZJv6p zS>MP;w-xjn;qQZ%WaF@bV_ZpJuPo-Z&Ss-s1ih?lXXDd1YC_h`##`q9H$<~)5XYtsdDZ7`5^#&;eH)Nm-4;2Jil zbe45c_V2BjVUbQZ*&ljSfx~5}%lP59oY_($lV>O(^!9T-z`SmdMXr)%Y_y1dYr_<{ z5kbF##jl&PO1Vh zb(OwE96{&3qCgo*tF z&?Ag`3VDH;Z6aIsiM|&*0??f7qeB~dGJYd#wIT@1+6Uludp`u-^TUp1{F?QY2x`;a zOz_9BO92?MpZakPVvyg4bzScB@A$KZ@rL=IWz=GvK|RH;)c5Jm9Qh-9@~zWi3BRA4 z$lN(|HRZNzQRxGDstheO{m4E}rMK-OE$oIf&rjXPkhAoPTEN=%T-MW%#=zNuT6D~B z&y9>huU*`OU7$`7Yb8AzX;GE0FP$92eJ1PL-_sFQl#T=MGw_2s@Pb{L_{Ca9UIH~4 zf--U4jowl-+2`*zKXQs~voNG- zCTf3X9xRieJ7=Otau)u&nu%F|@_78)Xy#~cGS5-Gl`NNuc?9M{@;m3l>AV?V&3U-p zj$XFW%(wGrp@YdLE~KwCbMb9Xu)gh@j{%?ZQTGa2EAH<`oT3-*X)=pP^YPQ0?3C$0 z?VJLbSpS*xFLmU~uohK5AHHpw$DhaF8O^9rjsAtVskd>3tQPmm<9D%Eb(1+DuY6n| zN8N(&Ja%_?@w!Tnvk;Yh+u$yVyOmOAT{8*2kEk|D{MRUBF)F^hA5p`OL$7iKnB6D1nVHL2?ZZY}aGUKdr_FIVzVgL4r z`X!Ro(klPyNewI{KU_(HFMY_U6qQQTP>Zx%sKCG|tN0u*mYm@wa%&8A8r#@1PS~IU zeYQfHvc}X-f$Tl(RlUSxHL}vD&?2wsEwja4!FisZF7&<0JY|)BbrjH8O2w9a+S^L} zFeNDv+8Cje(00&wLewI_T7&@R>&3-|fKtpj~4n{r%b4aL5vfp}rVx**3`(4+ut z`^GW2d?;qDBcHs&AHi1wF!&zpl&iIfjflqepcptg#^4*Dd(S@n`OYYe*&mI9`qV|e zrA1{GYls{>mF;3su}TbT-HL|(0lj-VXpvG7jhsR)R=3uoadI^5m}A~{UW*SGSzr6_ zSY&!?TxR}sx)vwHwMZ_Z=gfE305!}-e~LyC$L~4jdA8Qi#OfpTue-_q$&p!DT8$ct zCo^IBL|+r;+SbfU$1~O{>-8b`dz;Kne~vfuiu!@%fjIsg%2U_Wl`IVNMeQ@P(7>0q zJJvW)aXi%-N9LGg=K*uUJ!g_>;0 zT~*eFS2Qj_MUF2Ef4``XV_Ne{8@+Tp{!Y7NevxL=+C5#bXrI=v)c^ck^zyn9QODTt z(_dbZlVa0uoVHJ2)P9H2b?{?P)qsg!?$eUfew1`E#;+V;9Q`TWsO@^excAmHuX(L2 zrANE2H~usIUDt5kGUH`kZ=>O5<8+t#{~GfzWf-Hw4|-aL+NSUQbD!tf$UoB!&B~=m zS<9!#Xnq)%rO;oxfkFQLN?q+rsnVC4C1VZA@+mV>j%=d7;{H^zQnx#8aIz$_FXgbE zK@M!u$(h^KQi{<@@Kl3rUzRApo9U&Z=AcBpO_h^BlEf_~QO2>x(vlk9Cw&rRlA3Ey ztwC0eOp^5t=vzI(AVp^q;)#@{IJ+ z$WUY4Na}*jq_@~-H5PUAfV!;;Y3r0IeC3Xpz38E}L5=ylRB&CbWKWYjDqmFN(_-p) z-%?}aId_cVerv`d`jZ*eC>qY!zEPvbKK9lOVP9g78dbWJeN?kfr(=DNxgLN1?QHKb zsCtEAL8JyXx#rtkIUHMZHE=%~1}AF>`mui3X$o^x7eW!wwPNKbVVKCeUg;3>iMe4I zYz@Puq0|OpKj+8(8r;81-{=KlxaO?E(8y3sHHYE+UJdG;U>z_e4E6Y$rEX*+D~I9L z5e*U^k(X3*y_l&%swEW0PdaQ&V*lzH9S+Y(MeuC)yFAt7RTj1FcXN&BPHpZ9WKQPN z7xWd^hDY^Kmr`qSkO5DYkWW0PM{BMty(iLFI#!Ruy7W5>G2k56f0ITTQ06;((EcH- zQi=NC_6Dp7A|J{8!)n$fk0(%XihuLeWWeUf1`Ogl)YO7~a&@>?TWvzc$Jt14mW%Bb zb8w35y3O1Jf9KjT!HK#s&binal7sq+T;$Bp#<}opOk@tH-7b1>cF)G&G4v`O%bF`| zW^c*EyzE0Q$6@rE=CPKS@b~sP*vPeK)M5H`I+J~@LPm0BHf;G3S(&fr-<~12@_*`R zy+fVl^7U47HC-uNyw!5Jk5Z;JRZ9Cm$mi`X7RR-vGPAT){7JoFM=i*1!-^!C6oJeMmb@O%4$WpUr zaDnqi?pHI0Q4?{~X8PA}AfHx~y2-~~<;_r6c|O!h{u<{dJKi*tqtroe%~<1~r$FY( zQrUV~fzM-Y(A!%9GyB|Ua{U$AF$jGbS9bgkMAj(sd&$(<+C+Yl>ng%Dxb!bI8c%b5 z)0=Z_pDc9py1<_HEI635;1t01#|wHW_sT~L&S~jacrIKY_%9=aZFT4As-zP8cA^8_ zWSzTO#@^+6mT_@-pHjI~LxHX;1qL~hP3fgT;TCFa?G1p}f&gq^6Np}e>7`sL5R+b0 z8~8r;nz~TuiZMoCH3qY`l85IS3J0?oN3*bD@&yzR%ED$(&fAak(cdi}lE^*^@(xF5 zo1x{L>64_AVev}w{NXBpU2HCUR<#tr4E9z$vqTfxGhFSIGW!xWEZ?`3JE1Nz^lJ-QI@Vq4Py^ln zhXT7!(gQoPMAq0V*o#ij&MJZQ!eLxK9Eb~(0&!B~kNEP`N8?)b@@d9jUoDz0WAA~H z{Qp`lB7SGWK7d|&A>{l6GO^)&Cff1qUK{E8#_RFLKOcMPfgSgdOh_j6uFk2%?V4IX z%xEp4)mzAkDE5prRmp&08|?73!KM8Q>?u^h<(3WR`74m13xH;00PLIs;r=85?mzso zaToiMM#TW(F?e;1JwuG+h9g?OC-u$0(ub>*HNrC zWI;Z{_U1$Jglywwy~I%G4}Vg#_s>)btfrHJJ#-STW{&L+y?N)kqiZ{IV8`gyX;00h za^ZNnHw^Fo4#n!F8Z@}4!P|+{sO7xno@9U*_oMYK>{r&OLeD+y)dkeFYLbIieRFY$ zxT*?z_kuj$- z{{m|t1uEQQ%6~omQ2V2VF#K1IO;P_*C2W<=Tu~D(c@@M z>O@|k-)kK68vJ^8Yw|-M$jmeEkothW)BO6^J;oNE&txBRjByI@XXH?8wq;IntHS%T zf!d6@VJ2+ualy80U_~`|0t)8q(RGDr)3=pkN0XJwEd`s#b!IcpQ4{~ z68#1^7yiiP8rm}p1IlLM#{PW7P2#%t7kNF-iD#?Or}sN`uw2{9=dDVKxTuz6R@cj%do~21CFjH_Z|c}r3qXl4nYbVH zzxJYz?)wD>|U~8k*s-2 zX(nn^EI_xvc^>De!_4c{dK|qHF6Kiso%)A8JY+PP!HtZm~tZ&AxzZ>!jm^&CFl z2FtIONYHxjSGgBGScbf5sXuzU(gS-6YrxaV5jt_rF+Bz+xz^bKjXi0#wqr=27_{#Y z!`yf#+^+K@g8rg8?CYvTkB0*05|%MmBr-l!rY}Rk0yvb=n^Kz(=L4>sDci}^`f8c< z+*x|^o~^sjeqO5$){Q3fey&tbIN4x3S)ivg6j(Sf0GW#dal2&z)U5-s%AbDNO@dIa zQw;uKO!pZ>U4Hhnjlaa+H$FeB*mpLH=g~*Q+=(~isUi#W=Vak0a|{W8=A#DpOZ|KE zqb>JdyQoj?*<5=2HkB*yxZWU#@1=8<%A;Il17m24qgCE8rrwYGE#pSm!rY(z0{(n{ zI+FF&aXr?Yxhrz0%bkZ(LyP&GZCch|>GKg3jW#^D=vFcK_aWnGXX<40nv6=w1i0Sl z;?4LzgSBwRtA^#NNqw*Y)jqPfV}TjgE(V#~G+BO{ljPjo6#1>vNnv?K?!{>sJHyVS1b_;=i+@IKABmBq0hyIU3QhBTz1H9ewim|lgH+Q6+W9*70>%E8hX2#El39Qq7(opA2!&t4M zb{e&N&(p7uIo=*Tuf-mzNatMr;TY#YSDpv+w6Tu47!yj3bLLuak)8g;Iq*%O!rPJa z;%w^vMJa5&Te2_Bq@mWqQZn89Qe@?7>h51P$i=VB&rea)-&KtO&V#*_9ym5zjcZ4F z4ld#Jk)(dlGRCstFpM6lK`XCRY#UAApBkx{vz$7*8&lDVabrz$vhQT|ex9L@<$zqM z?_{H%F$Y8MDZKlnQLmN^V`>I98hM?*y0Gs5jr+~v^pdi$j(48iU^?&DPxdSr+;MD$ z2Tr!5j{ihA1nyU1>IoHoZ_r>wk1)i|<~h|2=bnMRXMbyOx&!@=V(Dwtidx5y3~(e* zSdG`G+{&vmWbdL8ZUEysrg`f8-y#HqW*x5+o-D1%}35!20 zi)QKMnSY9$4@r?b)Q=q4llsP6-SN%jjvN;iHm9kvZKgZ^zNo>TkL+z@481p)8V5r5 zls^l;&v-G5bu1g^;0IF2fO&rhXT~wEH|k8x##;7tct*3Q-%1^T4ea}OBRd#MAG*ct zqnM}g{+>x~l={?*^w5jLyHu%t@u1ASM4jwgdO80^Cw+IQaig<4?Cz>@u?%&fr*nUM z%LDVz^IQ%vW{o2c%h(mdz2*q+ZC}5lUN-lR14im`+p0&;AoiOKpk~5GEC1sQmR@aTuY>0rY}xjh^DrBI+;T= zj#F20^5)+%Vjg|5g&M`xGax(7Xb|fl3FL9Qk+WO1nDg1=479IpMu&!u(lWP5Y_9v^ zmYRH`A_I$(KHzJgdZI1-EiUBU`oxo;Iz*kj$$1#sklf;=B3b3)i->?|thO-M*4T_& zzKtZ?u0&o{^2Ot{D7>1N0qwOs?6YYsr#G_pu$2AP)5xPO%EZk8a!(O<((wCt+4Pq$ zHG`uO!Jd5EKh5-@X(&0Je#$oS!+UabjWp@l+tCcwb_ZFc{KfT>9~_yhw`8Sb*R4D} z>rhWT>2rOWI&P!aGdHQ^{nF;)@1O=!pV!UtiVxnOkH(3I)D0~D0K=gAk~ra)1lRY$ zt6(i|Fpu}|aQYf|vXg3~e@G>zAD;32oyfx;BWEl$n zsvY{EyDyuMg?C!d&{Q zQH^9|_Yyg@b_nkL8HElzGoen&gU5^}((6g7+-2Uk|CMOiNG2ww=i$xz`l2pxl^Lv~ z{Kq*~2+zO<9{=WYpy%sX41afVQ!l;k&S2X_U!uy+I#y4JGMfsZ6Wv z4^L|p7Trk4)?wr~-`0}^^KZHG!4L25P`{7kw@FPimL7K!FRoFt5BXv@`QlA()cfQ8 zofO(cEaAnn@zf9$^@_&g@$}I8od;WKD1VnJkx|q|y*)M>O*W?E*o{2aRUKpy`L%UV zsE^r*S{bG3$R0)i`qTDe7)(F(5!7{!V_!cx)6tXp{HUE|b8L~cm`q;pZZy51=r2#6 z@zw77vStK%$v1u&!|^rPEdvFYdB4Uqlxo!R{O7I@8dfG}dNBhw_S`e?c9d;1=o`M& z2iaAagJ+I=d?Dwz6nn|o_d_~N^o7&eD2(dG9032{KXV(%a^-K?N8V)4)-7K z`yX_xFU8st*)qi!>z8U_-#rr^pYx#CG?Ji(#o}S-kEhFcKI_Txk?*$Y(|~&Jh0-Q) zFy>TZZA>z7Ix`Q=$~BSc^M7)T`QmivX!`DEU{@tG=KgFbc~zc`O5yrjR4Pq!hbN#WJzTANCcaal?aNXI-g{!RP-0^;NPK zkvndxMZu+XxbQsJsF>?&QY;JMiwUi$qfm={WkuGUERCd^k@=JRKJXz&*?R?_|Al6} zwrwhpzL&__*F&JAZsV%S^pCE zHf%+Uj@v*hP9BSw0CIe@JVKGv zSBJoMCj2>)y($~Xou#SpmV3f;O8O%Hdj>1PsxVOw;_dO*IZrWMM% z^id5_;!G-a{i^C7BoCqh6Nj|Q2OZv|?%SQdXRy4nmDD@jE@jjD&&Cxm( zZzq@3)Pg^m&zMdAZr;aWL^mN%dN&(20-5V*L%qvkF8CH12K9A%54AL*w=H>}V|zsB ztb+T&V3cd2L;gVeG7EXAGx1{c%M}5;$)Aqb0$VHsvfiF zQ%A1{b^4k@lf}b9i4U`a(eWVpufF6pxJKRAm0lcE z-Pqer?(BdLN9D}F3LYWpqK9>IJ*Rt`rA@$C6iL(C(Ih>=xxWu|fpM56y zU9`X{JxK~otOL>GblyW9PINZm3c0O8r;@}jPl@(Q4X)MIBYpuauwo=@cF3h7@=o_ED<`jx-X!E;bHqS$jYrCXw$awFf$ap6Ob)j5*6nK@SW z^^l{qy5d$ha&tjCbY1fhopQ;yPEC*j=jaRX90vPePQ?u|bHcFs1NA_Q=vzIKIm3@} z@?;hLj*~+%pPXaX=ZEy|qOM=Pcsa6AjgIm3%U(r2M2r ztybjbvMgv`6fcLU$J%oOeXDuh4C750@t!}Qo+y>3sBnwE$y>gX^L=eXEcFCkFT}~| zWO9^qm!k`FdsX>7*W`ZUkJse&e!8Is^+Q9dvfpbxePBGT)bEIsw3TjnwK@dT9CEY-I;HZ zdz0g+_Fif0ufmtrp)mWB3w~w7c#w*BrBK?+-gO^cAcbBkM(6r zDE!*8_Ep6M*Dx!4sS@M`{oI<=4@Jk8df0w8!GYJ|^QdIG_R$sdJh?xjPU1Mu|NS_A zPbb95%F5JpoECzse^bwtM0VkN)p(Em&76 zSqc}b@U3V$+B+EFbd2%hHGSS)lI1G7@7f$+q0B=hd1RyRzW+VX7(C)lT56cZSpL8R z&rAEAyQV!)G>&QKpSJYILr;&dM?Keni|E?gUhn0$x{TL9F^$vfS6yLL-};*Nhihuu zgTqQ=`>d(P37=M`y*fF~%jWJa&yPnxbq2 zWWU$ot=Eld^&*XXWv)03Ujx7F0im3anf`t-2Wm}wAI zo=zgwsd8?IL3X?9WJ<$>Qmz60{`%}_d`;QgOZh$Do+c@Ascn_t}Aoo`3C8*nqTLoNbKnp*-MR|4CfU2L@$OV zH+f9{?TxGMn8f*R{sDI!q26nydh`n1L*1NR?yM`jM!!^syE%y zyPO9a-C-=|I^$onI~mXqp!l^S!AFXQP2qXikXMSMNM0%6l3q@*w z)@_&v>(n>|{~u{*9n|K#wd(}x?gmuw1gU#z*G=6iUUzp_Ak^KEx?@RzQrAGJyCQWr z0@O=^0y+2I-+Xgs&cA2RbSfLd`%7MVp0%!Z-4WF^_!mr;opl6%*1cB-hGPC9I-SYw z|LMaz{Td#Jl?LaJ>5+7X^9hUSQsncaiJKnwfn*u&;xTO>>q0AZ*cQwF@}_u1JFs3g zC?1uz=}^y~{b_zrw}$M!tkH8OMUPXfba;G0i|AcC%wtXc$vs~0tMt%aWX+;8``kME z8F`Oy&6-^OemV@fL!S7l4sVa@P^B_^;_*5hwr9<~BpsHV4UH;hHX!R7iL8xnxXjwz z6J`p2Wi}w|8`*v7%W)#-_%Izq26BFr_rEqfm}kQOudifcS4+-4uuX*FZ8g8ej1hz%b*vCbrZfuferInW|Ds#$66qJ61pB_AA38=_3O?O z@|c-@cFkn@Sw~51?I5rFxXK=Dy66qfBzc{S?3ztKkHJYOD3Uk)`}yIna&k8JqFtQD z@iAwBraQ}qNsdy-zp-{y4(EMhC9_?Z^9K z)`$QM9Khbf0QNlA`ynRF2R$_O$K3YA(}O-(H-s*iVqffk7YNljf6TV_qpO48f5IE) z1Dp?K-T%>K&Jo`5$GOey`R@vVbw6MHU~OiORRBiRpcf*=A2a6qp^@GP`E_jx6j*flsiI> z>M1!Z*9dH_8o^$3Bo4CPFfxYTIb8%&l34E_6oF=(RSauM?vcNo?}nrD5B{uKTa@&Wmy{^ zMZU2Qod{!@f3=Pdf>+Et(9_$#EEq!<#0EMTH@iv40V+B9!&$tpw~+&CcUdvXU8)YY6Q>C(*;3I#E(~#(iu5oJ zd21(~R+Ax~(M+6bs-)a+H|fP(i3a@ImXF9Nk~!&AMTuwgi)9ZP#`S6oH0;2PwQuxX zv{J&>g}ejVlm(7TjHYjKwzF9dyYRZGY!+uaD7M!ukz-$rMf;On#%Tq%@*35TQlM0h z5>0v(%g5?`?d!~tEU!eDuOPx-x>4}Gv|f-iR5 z@WJ8M^q#z>|B(#hd9sHImXUax7>-dXgn zftz?AQePd?Qg_H%pLtPxbOWFxhdaNXL z*U5lvtvvpdAhXzGx}T_(-={be!|$6-xA*wc3G(}Byj-)>O2}6-kJS?7<2EvrR}2M?^D0-Az2yS8LF5m> z?8^RhbpKM}elInSmvDxSzw#cc*)Mg)wJV&R;?KM^gxDg4Z)^M^mu>QAZ@k=nt}9i|6+aNmIm27G-w#gnZy8ktPX@AZvp)zW$4%9KIlzb z&aw37oJzq zJ!142md*LSJgx=LaqUMp$*A+35B^X8?2--I#~YG;~T#=s-7O@*kkkO zYu`Gh$KW4Y6m4Xd-gxFFbYeCM>kftdo(CiJNF?8bM|7z*&cJ@oyEI##0sC{zV&Gcv zp_-0H5ANHV(k;UE;OkH6>}`|fV9)T{an8H4-@9l<23nKLnMKA!*)0=SxHj}O{*P~L zNDga7F|4<64eClyc_ zINclJD%Wo|m40Jd%B(5PW%48iG9Pih^_)47FS#z;roiAs3iv$=QAI3Ec2&tILaa`GW#>_<=S(1snp+DE|qnYIppNGuH%}K&$kEN$vSLj zUgiuX>Mrud*%f|x)7}pXvKKe`Y}j3gF74!Sv^*Y(m?S!=hekr*FcN{anDac(hzjM5 zIQNhBdh!KviM;22G9qXx{m#5sRqn_2LQfNp+{(d%EjgHUhyLSewS?_!CXS`rN!8S5 zGV_{R=6fmeGgE;yDW6pZ^nNwh`{9(yADuQwAm|C} z_@5#XIfu`h&h-3}3-PROM3v1(lw`}%1s>BT3wRk6XqRo4?>!ZmUfmxL_t8JD z;LJ|4FAiSuLuzj_Gxj_1YiuMg@VWME3^|@=WG#E~eJV8x@QZDUs%4_E2-!CodDRm*42S9F`D!1CP+ zuB}RBat*U=)G1N_fl_U(RMDVJL?|;+xaYNIue>6excYh=t-^h4AMRs$Z@OuhiBqioPF&Bra3lH| z$r~u&ai8f-9xg-SX~ml4NPF^nhxz9$h3DUxSlRzVD{Xhg$;T>m2~X8YeihD74pSqj zuPfw@8~${6MO0@shL)&NrXO>Ax`pE8;t=e9u7R^t2v!^+WBFQ#^$oe-UaUjzIQnNN zk$rfmM`snYfuA#Dx(pqNkLjK5#(ivT1|E-6cqZ*oc-CVNLUlpmY44@<sz)l@AtA3=zhx_w8YctXH7CDUW%nJRW z@LWLG--Omm&jDt#gA)~=w-s91+crsB>`RnepXu8QijgUu;^k5xYtLzFj1Ojp=@(br z;d9lW@6TFa4HA}-OBtkrg9~dIe2@N)4@KkIe9p{d4tH}hdkOKV*p#dc8J^9NY52)! zfeqi66Hz>lR?IX_WQ~CDNj$kq+it8O+bccKB#_nnt?+DAStpm`6Q!=RUe3}3_Gg1m z9_`jiu$n$JTUQ)?szMV>7YupiioX+>zj2s8D+djBC25c`A{2xAg+gl=j20pEZB^i0 ze;n%_ZaR2`>QS+FJX-!HYmvj*Zq^xm&d?FOlXZ;h88FZ0xx)Hihh7TLCY$MMtVOpc zKfgQ74V^tPLFiYLU+3b5E&@rPnIuKNYFyc?#*^kee@2kcJ*Gx{ea=;MrynwkYlFS? zF6T4fV|XZ^C84N4MTc6$^r%`s9$8n&6(#GKAsmkr_H+~1BfI05iECfdk=`l;W8Kqv z|519b_)OpE9W$msA%S*U;pw|k;kh@)R+cJVrDhuEH`}QsWJEKudC*iw>q;b=^@Z&N zEs)<ON-jKZCYcG% z#ev@A2Y;O9&qh0m=W#fcvczfDIXY~%K-M57{J$vRrSON<9X}l6{%8b`=f*vMxOJpo zp8J%yd}gJ@Mxp}u_;!yY;Klo6f|Zdx5%=F**H7oOb$K7|33&fG%4fvv_2dO+kfScg zS)rlyBPNjbW@bR?!7Zd~VLN&H!%coY<~=&bRdS4+>-4l_evk!oQn_byR3LjyiRi2Y zFm19wRvq<6JbSV2N7D7zCII!g7s?2v!?HK`H!mYl`7q}p8%N^ReeUOn(&1Z)&f3!S z3fo`8#xkjNJ>>wWv!UdA-o$79GOHZS4o4DR;B6Xcy<>&f3K4j9(f65;l`F?#3@JGd`k^JwBL}MS$kFiz~ zmJ!LmI-mFbQV{J(2mS0+9O63TRe+KAEixSMc`W4KkKHk0-^wx5sZeb0*yTogj-t=JWh{ z?tS>2IO0uTBed;rK1|Mrqjs4#2GR4 zZwd+%c<%6d-=r<)JqNHa&GRQPg`QEK&y&6A)x4z>Uz1LnI_c$;N-x8#5+zC>FXuX{ zP@cZ_XLHo(mQB8UIeQ0Z)HqR#KHs|D8{xfq z%SRo&xTc=jFauQ;anF%!(?P7Cu2y(9B)?dj&y7DJ&*etI+;9sl2)9wYC6L9DBmyTHCkV?IZ_b8Wsl6Vu0%i`&C{ zAz8G~!xf%m_-y?|KhV3Z1Q|wmeqL&#G#L>uhYHyT7?~(tpSWR4mOFlKbcOXFSIn7D z$M94a=r=N}XoCj1%23{~Ll9>l3cFDH=UGplvp|Q=tZBy|(P5(K(RU&1)I6TmtPNl7 z!}q8ZeZDCf=s%yC*ksGAsFa>tc9XHBFY>CD(zE_4GN7y2uee2quup=x-DWm;CH76L zCrN+y3Y>Lrn5lHbfCRb{>|J0y?SiLf4GJSPIBB85+WLHte$sO>QN#N<=ekDfu|I_@ z;|V=Zc8h056J3P9oVkj~Kqwi{r*$&m$Mwfvt~rjrpwolLVeGH;Y{&cb@#%EvJXLr; zoX4Dk%s9FBAYL5kYB0{!i{-UM>A%_)o9DWq9(m7)N>{X6#g zzVsb)e&cOCT#+i5?jmv;;ALq-Cu=gK94u2tgvgzzkyYtxo{9m52<_RlF$o(tBpK;#( zaTrdXOh#=t6IKtXFK+1ta*}&2|NL;?Us5postGc#iOinEoRk}bQ1?A^K$vGbzbSJs zYT0nMiS_ZG^bDS+r_3z{>zbI5;8{lwcP^9At zBN|Iz&qA4W+6QCwtc|rGFTF7fi>Fvi;jo_@YJZY>SR0*@5*e8U>@^?DM0ut>h` z@WzngtoJ=j!He4DhBjGAN!fe})-ca^b~yAttZo0!LLKstBaOesnmIC)Duv^0=@fMA zkcIwD8b~!V=8H7m=rJV>woO^DV|{vD4I8<%;IGKaLFn3zu7FBLDE+f=sHm=#ZShxD z_4S5+J3WSjQkVrzUQE|OtnL4b|Jy;B+c*q(!S_FwJYaGYXdAk!)bUB#7R(+ zo)@+Zq-XF@3LYnsYrEf2vOg5b;r8Bm7e-Ev|K5H#^Qj$e^omjgINc+$o+-wWhRwrJ9e-(`G&{o-NIUyoGp}#2feYD`QQ)u%+A=v z^Fi4_jEz{!Zp%!c(_v_xk%B9~==Z!~E4?{mu$^^?PvK#BpOy@_?k1$UGH;!;{Mnbi zaeP)7qL(qBx10%4rmjS%Gb%^ z=f16hsmrkW4-@pEi(Ck3VAOvsziNS^%4lPRm{vn$U&3OP6nevXdM8_4Bp`OeZ5_?+T?(Gat-r8;(=4^nEWep~vrrGTWy}My?}AIW3GHtQ0Id zX+n#!wZ)elYtbljh2xo-@FWEbJDX55sGd|h!W`jxzOXnDhC4hT*4@qma_h?KN=4Fi zurFTmd~RBhf&iZ9s(Q7h^VGjmVH$I~N066HV7@TdtD*gCNx;N>Io5$W;MU{^)%3JZ z%fd8wJ5inaBiWpHtUNv(Z`rF!2d``A2BKO2SE9)^yUwS#^m7VYzBXZONj(`tUbtl^ zA95vODCYU2>TiN`^?IU+E0A`he6Xx>I5M46P`-2)JRdZY!T0m!-WzY|5}1(`%zUqc zEL`c*K%RXokxCQ1@mEQ&=;{>I=h{e5uCr(0Ux{Nr`&s{RST!Wy9hikP;r4QS?O&-$ zZ}%o%M_pOVxiCKqV`ke({+B%QWlnd_D!z_W3KIGCHDA_~kd_5f|B^RO_X$Iv3(4%8 zXQ7w6v5fclC%qex16>)8`s71P^L>8P&Q^wa7fRV4zIaiFyz`i3bem|x_J(x2a6j=X z&Kv(&`|sdOZ)xu=%skgbEcAu)GRX(YKg03-Z8D;VlUsaOUk(~dWCVFY&FXLj@H`1` zn2j~Z8_VY!3REBmts*yit_JzjYhUo|4|&^cW@BCTL0-mo6TO_KVtM=4 z8wdC~zUBR@%YNoZziA*%$sJFxM?Ud(7}iE4W86pPp_jIj8R~zs&CUmX74$GprdMQw z3BFtENEZF48RTA9z6i(f`Sd0nBp*7Xp3Jr|ix=<12RD=B9+iSY08VV z#!S5yJN0QuBGU8(dcm)D`?hcvXAWk#jK{ZjL(BN{m`Lywa>tjtTt@Ot!}B^{CV5h_G( z3dRPV7K#P*pj9lv{RIc42lQH-A8Xi6~BV+OrxvrGi6jQeSEc*H*bW_rz9sG_9*2IfjP zVMZl6oh<%bw^rQSRyr)|rB0~)Ybl18VNIh-I_p&AgUDO;b5vpKUe;wsYO(tddBd9} z2rND<&zaBLg1H{Gb}|=&Tw(L(W~gyUg!#^Wmo7sizR&Rw)3AnoQ*U#u#Me<_9rL@b z8fa1LHFI50nej`-{M1bInfqAu=hfxx~ow?!ka!%UR)c!JZ{Jy#PJYlw#T8cc^bU0(L=YJ zpVtj%cx@qfHiN#)_GySa&GYJEoVeasAuy1>xrWT@WQ|-~&5YqIweo?i%ZSWi&Tnb4 zp$d6YORk+;AC^ip)cCtTh`HBV+_&YdDPOS=zFGKkq^s$aghdX(_TAL2Z^7l?yVdlS=Vjj0H9j~gI;afFI_B38=ep)Ok zlZFyc&WqEV*}c6A?KTJF%4G71ypGZq@cIosBBpvO)ZV%bJJPkR)jmd}V%Hi zN4yRpuS(AGRv&sTb9f&c7c2U8Ds17uU+Kfw&wY#;{QB>WqvdE-CusgGL;DqRsNI-c z>Hsr5Umg-O{hM~=E_K_;vrkWl?+RK6r`&<1md>v5P!%!;j!b=xz$9ZE`C5KtoOjbq>_So=Zm0{wQ=LYMu z!wp*#U6Ma5@(r<-)P{pTRXzT6wDj1SQr^S%-zvje)dNG{%BGHgUt1(MUv{(8wM@(8 zsiy~c#93XsILu8iDMbnL!G<&NxAaooS|=+)nXmC$Cl&U@OXcM{dAK4@PUPz8p-PZy zUOL&VkCt_!mD6Uu)My?nt3Jd_kLK~xZ4>v)H}taZZmcZ0q?6B~dTDnkR+=y)BfpGR zCY+9!v6J-DDv<0pVx|M8TK~-ND zcr>6Mp-_)%WrVU3f7nAYF+SYrwh(=e|~tD3o7zHJ7a7^5(0N&R%&=57r!( zGuw~7<~Z)_OGAUP`K)4qXYJ6NeV(0qlpVx6&=F<2 zawZn@@2gqsdu@@)nJn^(>}&V;WZmX;1}+6K+u{K4=j>0PIL5!v;_Pf_IzES|V`$5! zl0Vl~MsI5_OPB#C|LjCjM=hi8sl@0yRRPueltHc-DN-kNefZYn5-d!xFehOUQQYA>Sno^s=x_1C9GetCjY}M{-qQc zzo|%C^*2k&_kZ%KLb0@}rhp~)NtZ$t2>N6eMVTV8IHJV7HA~^3D$% zdicTmYXHI=>5h5zpB{Yx4yOe`9q12ty+2yJ`(f}AUtC@4507sF=#=b_@t^!r;O~d1 z{{ArC@YxpY-@Wz)ZG{X|A+|G+!ldN-0zL%-gHY-x*Gq{&p0^(`>M0o{4xUb4+I;x79-NvwnC zu|}VKi>#D^_3(PB2)8%l))*t2&R{Ms8LXz4=#N`NW??LS4KGvC*`D0MT=G+kQ&CBk zipu=|wt?Ozn^dS*(%m?Yj<{1P7^$N(?k}^m8mA(kuVL_Kmi2bB2gg#-wmEx7J~{Nf z(W#i4je-1og>qRCi)_4_X+peHHg;6WM!9UxymmCfr)M_acFD#GPtL4;WhUWMGFRJK zZ;H*vy6>E49hHNj^O$kDDH|@ev$381@SWrZ&aTTr(h}xLKgq_W&2(?vpciRxHafB= zvxjxEMxEGm$jHXeN-CLLsFt1297XG(l5zWOnQQ1I!wvM7?qtoz-9dWYv6rKZ++^`u z2kCj!Nv0ig6xr-7TMOLeXhvf?7+oZ;u8R!m;3{)6U8Ve97pd0FQRa%DS5->P?ph)r>M9WZRe|0a z7C6dly#6ThY6jg}qC~K_0vmG`s7-(AjK<`C1I!Y;rdT|Km1yy$M6|V(*nUch zl&j<%&1RYHRU!e+OXU9je{y+63A2Lesu)lrX9g6@xT<87jS3_kE0Sgd6;QubVr*+> zg3{SoX@x%;&GW-$dQVO9%(=Y99J5M(m|7zMJ8Jl$M|ozLvDTH@+#kwT^lelnV==@Z z_DKOqeNSeQ*IgXHZ($!_*v9z5{X_tKK62*psxJlv`YWgt@_-`t@9AEe&#}(7BsE>rxSaQVtvyE*e z9>#>D)uRaf=}b1bJ~_uB^fFD2L8z2Mgj`}g9agm?k?qHPcdH%fJtQ0kGug#q z{Jy*}Jg>?b*|}tjKhVcDJ(9Cm%xGK3*XHjD#o@3BVJ7v_aJ1QD#2fbgCXS)s^a1;& zb9mkKBq!0B*O-B{e9aaejmWU3TT79O#z*=8&*61gGnMN*BO2!M8cQ@{;lWhQxoboR)(q#(GvW(> ze`g|7#Qs`Q&1|H$%E5#Lp68*g0|qmfeMC0qlNs4Ghu4yAHnxo7{BLg)GRYy1c}EVh zCEbe`v+%l74!jqTcS$nAYg9HG@_W5*kn2b%+xVQUaf=)*`jU+s{CfcTn7;pVkj<|P z$)OLjZZ_tvWZlS@{m%%HR8SG0&(r_}G+BR({YJcFOPz?^@M0Sh#ga{(a)KVUsa2VieZvPyp)=%mElFP@{?=9`oVg+H%l+u_cH%EjQ)wwak9}*Cv(rm$ zv8s^BIox9s<{2k*Iq%ZuE!T{nVx-Z(I7xBTi(`!hN&d+7BD1ebmT1K@H%9z!>R7u? zlsO~mW#lZ)ovZAPS!!kde62ifuaof(39{W%Cvek=vM#eOYjQofRt?|wE|~Ixy}TqB z1Z{Fb6K6Mc^r!EFJ+zA+WI|H8CLFIqZ>|Ab&7ni(sEW*u3##qr+HZpzI~us+K>&S9 zpV?m;@64=P6^1#h&@xOsIhznXJ%4V__~6bb6ktwTjYYY zVe}@FSxBf9g0e{(G=3j~g*Q0g(m;c}ln`uF)7kP=gBAR`Z{>1Pe-Lmzlku0OeUEav)h)jT@E?a9|{BfH|40aaiIYLYdq^eY{U3(^q8 zwc2v72YYr+M*-J@?;O*S(>?>nUYtv5nt{g4$tdklr#p=GuihEx_J-MIBRLbpzVGN- z{GFb!zfN?xkW)PBnu!CYGcj}``H!cp1v5v-df^vRnn~voe?~y@wF^b5NwuvoRLX>O-AmiFD6*{Le)6{2{!_eKZbtc3%+Q< z=g-+2^z$}jCZ@{{wx0q|M>P8&odML3rM? za{ry3Y;Mp}G+aknY_^sCMG9v0l*nf~z^vPuW$s`F?$=dfQ#JBK(e$;=;GD&k0Q}h& zfJwXj(RFqNHn=l$`W%^=nUQeKjD(jL^QPCP!orK|)BCBou`m_evuKq5%J~9+GW>gU zkn54d*|!|lhIlSF&B2GcNfOXAUaVFnl9SQPp?i8sUKlSsuBp*_mpc|#XC~$c71BGn zq5=2&k>ly3)rX?+FZaHI8r&YM0p@6M>LvM$Ejk<=$a|ME9yiXA#o#^3_ES1$f9Gsl z5%-;DX3ccSL^AIS`$zMDis`RWwH&O!=GbglkB5r5R!#-Z> zRMg2rgBmLbF(WgB9w#2#2tFtB_q*aX^F6$yLa^*BS&)~Zxbc8|dN_SfE4k0!uEQ87 zW;*ZUJ&${5LrdlrY+$~?R{COjkGgD`i91Od%zq}E&D=-aPiaC}89^8Bm2{l0 zn2GTYN>3|yrRSlkNrT=CGv z8PT_{(64pFbw^iJT;z(JJhCbE$?NesR*TQB7onk;P-i*Db>l4LbUl*8br{)`PG7Ph zAHDSSosm&rLWhI{@9}-f%Y^ct-Zc})$%3pr#XQqkg=fk*g=ddU@~0;Ht*XUK{AHck zjv=SAHBsiRh?n}z$Xr><70u`;ux~;?^I~Rj+*f1kWHknC*PvzDP^^xjHY|Ykg*JNRC=~hlEvrzSkP!ksU7MdrzWcu&xi8O?nNUBh#C&=q@$xe6ya$HzT*@ojp1 zE7Fa)hkNa)2pmi2-gN<)G|m}~j@U6gEuG;>1v|tD- zZ45wEJ04Sj4<0V$J+OfL^p%mU=|-@=Mi=~8@^USVcw3u(z1w`Q?oP$XAx3QdoPw*) zIe6VG2P3=WpuvM2G<3{`GuQLm46b5q?Ji?Ry2*sf&7^FSyV!hfCYze_nI2y( z?TQj3S8-oAPl?YJ{7|7<0Ls4bL-nu#v|Hte1JC{N*e-(mD$Y&TC*#Sw!J__=7^sNE zVguPu?%zA@;|vz}^Z3WTgqpk_*ZZgV9No>ma%avpW&7k}A@|suSGY*qip|8z+gVEa zI*FmMsXUBxl8s&YUQ{y6_znvEVA$`f4d%cXnVm>b_4Twa|%4FVmq#`?xb7IfAml~alf@?-ZS~G*eCI=Ham-W0w zHl{Dg#gR5S*g@trHpoHjtz0GWv09$}a+Mg?z`C8~IpaVcwVd;q^q%*vuj113suwY|0DvZUqs*<_j-dhMkKH2XS6C6Z~ic& zlMZH_OvUxXWM6ZchnUa#u)4W;Xvul8pV{;$xk+9{cR8NpBvbR9rIoIkOz-R>%g0)v z+CR>7@cF*dS4lUf5^r-$q-HU_PcQvZi_g_W1!r;LkF)Fjklvr4R|IED?7046{io}& z9SB|)iTh5S}>3OD|2kMG&IbtngAJaf?a4L!`9;hbJMQQ94( zt2SRRgMH)4Pmy7s!@TJ%7i0yvq3k$UXt#2{K0=KO-^ep2Xi%>U=hL6@xxu-j($je# znxNsVln$3WlVAM9b#)D{$=k&LcYW?MDif|Z)9FXb!1u3YzmAecd(S*$a@`;5DLh}+ zR(h_TtnfTXpYBoejBke@lRs|~CFRml`Qgqw`i}&;K)zDK)fjct4gY4Uv3Qj$c3QY% z{b(mNvcLqjI z;Y`r%4BXG9-J^^P$m$KCBeqLr@`L2{j&|W}z$Be$dXd?C5+@GlV&!xh z&Ma)B`*1YxgGoFV*5}9Cs!`nD6^5a~xMQQiyZOv6_Sc{dpQmsAf-#S*d#3~Req7R{ zm5(0Tig@%^=$U($jzAt$6RzW{*UH3_A|BgqW-BkD+nCR<*$3&Yg9_E9WIVV7_ab+3iPFFc9P04$1@QRm>i*#~h8)rMnd*-cj!F4|u{JrNw4nc+Y z`{>p*xc=9@e<*-i)1KTDmSxUUP$-`D2t~;qJuXgQ|J6dL9ZN9>D5q-yJ_mdyw^F5yP6L-nR&fUd6PMKHOgdd$Q=sKMk&x*3Bt=v<3lg$<#Y#I?t}o%DN7 z*5fhf147nv-NDc8(sw;JEX}}x(iw2sL-)WU=5g~gE15}mKKafTDezs!dP`(O zIq)e@f}i*x>L}-Azoej50~56Ct?8F7mLtFEU%L{Hb^Yn*>YWA4GPZJndBiKqu{Pa~ zIkw~(olem!H=>c;QT~&y+c;;`oqof^o&8$Q`?G`td<{+=})0aw(YOLH==C zLuoVmpL|>4gFgqDFYLhMbjw0qww+Y5`6op~eDHi@7?u>KAY`WrNx$vn{iq^&*4Y<- zdUM{n1O0A`nIC<%k<1Rv7t4;!Y31?M48&4DPrHVnJ?`N~n|R@ZTqsr2rJo$^DK zMf@DAle=W?y3~tWvd_6#$~^PI9`*oYELnFH{=1Eh_!|Do-FiN7?G=usI;r@2$OMO# z^`!I7V(Hh@2lnO2XU$5+yJug}O>ZscumWm;e9*ZOy=*6vVOP$CP3-$j?fF-N$&;?W z6ONxeuX1;okoCz~cDntOpziE}%nQetYnDANYAkz~{B%;1Asy8Mt7M6k^cFa%8 zvKMbR1MY z^MN{&^R>#xi^3*Sz2QH}@8g5NtWlr4mW%*$ou39bl*nFr(#hT%{?+NexJ90k9Ad0@ zJ+a?k$O?fEB6xo&Q^N?4FIgxv!b*b5B*>ZEeog4TFc8O|74gG|6RlUF!G62qD^?c zsgbx(%9pl(2I244aO^DR>(}J@@W5Ka))YxDz1vTFhQl^C1xU}r!JGCH!k)u~k*wo4 z;Q1Dwf~u^AthK8zn^lD}>YNXPVwrQ{L@(zw6GvyPWbC0LDfA%MxtsR^XCsDrGtVo# zfh=bJ_-BPL%;fJHH>0o9ota+m8p`6udD8rk7j~5nL)G{cOl?4?#YXmLJb0h%<%6qp zcs_?GKtH3W zwUjIG#uu?$=Ghn!hyLe*}9gW<4JOe{O|gBGzC*KvoP7&mbrTW#OaDJwv-J= za69I_k2m4PR$HkQSS;!)%ozDa|K{mrJl$);aE-NWdRinWCVDeJl|B{TXXfa#u-y3& z8Ea>Jm>h)OtF*WhoQ5s7^!xvb6_*o^*d0agiG0wF8;{YwANixQhegZz`i;vqIBlgR z*OP{`P0UdJJ1Bos9DxZTjOW$C?Qj|{H#Ea;?-2=YQ3 z<^>1t3&D72-G6(BP&kN7%GPLm(>RAV>urr&MRVqTXtoL@!1;iJPcZlV*s z6&kcBdoaQ;4Nf*@+*uVZDW9Ftl=9oA|z|ne!3IT8%SjgTI=Qq&XsAl2q8ee;Kr^ zwWwRjyze&5vkr`vo6nswkNM6XGqsp~iMixW6rNN6MoVie=AoAaqsuTY-u+8MbajQN zGxN9ZxbpL=5)9WqI=DCB@dVO$X^NIti=*9aO zrAC!D^gNPh^q#>Sd5sy(?tRw$Br$UT$cXER9JUQiAI_$DZ z!_;&hCwaghT^+EKykXPPIyB0sM|HB9p2cX%>*0v+0pt+L^Y)*ghB~v%uv{J`7u;3Y zKQ0($ZqnPhm9Hb5eVrIhhKv2Gjv?4z7>CVP%)z?O>(us;6jWAW!hm2X`Tl&m`xuVo zf}6aLmN^+tnDvyIBF{OqU4zU{mKk>qQL^|7J)sAKu_Tbb#VO=i1I*CxWiE3cXH4aF z-FG=>^c>P*m{Eexn+{5ehCR1n=BI~f@q+*U!HYA~$|IuTEc-bg=S#j11H$-z=9+OJ z{je0pI^t492;T5KEHf(&vr3!MVCWIC{Y-x%_l^EbwP=4a9kr*@8@nS$TojI&_jW1X z(JyIYkI0kre`(}cCp~e3#nmAEs!pfJbiNKf_4W^9#C0F%4*f8ziv&QI&CxWWAo`<8^)Y&V~i~4c~yTGb91|B z@n$f+wD;*(T^=hRwm2j9{4z|@&=YD*M`@n770D-#uvDWUY#A=|{<&%zulL3Z&%TI} z#f_X{J0%!9|7yu?q@gwW?v0DI@~(k17V>zk)3k6{#_N>Nk(A9bVp`~gR}X^d;i9kh zPC7EFJ3j) z8C#YtLofF4%ma8mR{o!TSTlt}5wqt?e9wROaN5P)lK1Cc zGjv{h-=pU7)rOMKjSOdZ95Jj`zq>d#{dA|GZ5<4I6rVaAI#$ilZBbLhyg}Tf9BaGl}P_2UMss&5V6OCK0I zEG(bgyj>TAdF)Yxp+WM+?wd||n5J*_SXcSC!S{H@qs{CY zkB=AYa`93H9ra9HwjK`%|41^of-zD|9kY6(@^_>E&*vcvBzG#O_ER}Yt!k>iSDdI>N*$9;=RnNfg4iy(wo?gbA%IIP=1w~Go0*4$B=tu zZ~0nldU--zFq^z;U0Zkb?W;zhP6cyAHJX}L%&TS3ySJM4e)cQsy2AOA3${RoE_5>N zDt5v5KWaGrR>6{c`OfcD2A8`%F&48iN15DbdYpi?M&%$MoZ znWDq(08!rQ`Cr}({Q2iRcO7#~^%xPxETdCeG+)HE0{hp|*L4V*z~1y)Ju?Hy zJKv-ypbG!oo=#*wr^EW_Q6p7{>U^!4zd7d+M<*|zLygMmurY#p)W7)}HQ6U;4|{P7 z9cH}IVRj=O=AL40=R`W<$Sz(VoDLy}7{*%98xy(3({wem$K=DB)bk(dnDLoD20mv` z#bwa3myQ6|%Pxd)_LdB!eR=kxYG&X(S;x(+6KVK-o%|&Y@%uB-Yb-M?Ea<;z%ieVl z&h0i}?SDA?)@w81&ga!3_Q3<&rsJ(+23i;#_@8nVzury~Y40L8Pd1i`O0_s!I?Bw7cG9B-b9XZArKPn>4ll761-Zq{^>$+Y z*-1{ncaZ|-DMh|yrnCncteK7Fh^?J$YtU3u);Y+WCr)z8&0Sh8aF}3DzmU5++ zStgfPVwY=)3_hTM_3C1o`&5Akp$f#*Q=m;ukqj!QfHUj1F1JeLO-t^$QWWsL!Cc$} zN-R?riE(PN#E_vXiBcjinQQq`%+4i4)uoOSks5Mboy`)whkm)iWU)T59=)$bI^|fP z%}FJm{P`zQYt3RPE|kCC%-C(`2dnmeu({!f=oD{ktn7z^SANVuVCGY_A2Vjzt9M`> zf4eX4exy60p+DXP(*YDtkDSRH&j0+eV^RR(%dsEvmfnCbzIfNfAA@szu!YRloqXm< z5AZ{+IsOQDp)+WdAL6b3&|VRM)v12?Kct=YTa;@Twr8-ry9mhv!9cePx-RT((O`?Z z?b_UsF*AVO#9(((b{7nGQ8M54zVGoJ-yiV(;Gx@%ILG<7`h2M$L`JY0fh4W*xjESt^N%#_jYd1fPpSTTR8V-pi`f9l%{j&Di{-uxTkakbYpFMF|!{R@YhGl zHm-`o(rCII$!=Y_OI~sUIW7L(%?FU%;{QMLnmj^3`WGXaWqX~uP0KQ|y;c^QJ~m(w z`zVuUWYOB^=*T}`ISc2#3^>l7Fn8E^Vr78Yu}pl@XTs%uCQ3>&abh5OtebT2e`J53 ztdnjzbG7`)8dhV!q@xkT)*5k;J&KhZicmbah~6l=7j<+lRxzU6R3k3!V2>b)oD_d= zR!2H3YS01YV}yZ!ZamM&3Z6YRujr6_K;Ei_kv#`yJI*e|zAJ@@9Y&^M4!sV|*~>SO zm9#8E|9VE$sW4*b1#8L3P)T-qN0~g|R*LpHNYP{V(hoVvszY>4y|nx0G>von^pGJ1HIDEK9%H%lu(h(p<&f%6HzU8`_Kcb_bd5 zsuH_;tmX0hbR9ysYGXUGDpSdla9gQlY%hNu=`3H9UF5z|fw2R~A97}UcMI|ram;kT zr9kh4CK)%#B%``kh|01;9`YWmGQ}jD`Y9lJ72>~*eVV59Pt0In>mRZZbQVph^IOi% zS7Jte)|Yyg%2j4p9;;!7^|eegZ&bNh2apk-qJ-5!1&RilVVRu*6V6n~!Rckv_>@W7 zdomY`_r-A?-CZku5$@=Vh_1}SV&CxURAxDL^F@bE%yzuM-dP)ej9cf26=ebFH;&$o z1%7zhAOPzQ`{Vi^e?0l>i%JXpaqGP|rtM&E^(0^P7(;*KS05}Z@x_I5AAH#yfQ!tH zdvwwdYBlfO!@fvs=!+>D_L+J!d)kj~)HBhTZLdL~TCDjrEzs)+w5dv6Aj5Vmf$D)wKd-LpDI#tJI;cu@@^lL}Y zQ!nzsi^(z`priC3x=ne{I5ptC*B}drCm3+sE|Z=e1D=g#)=gp-y|T<;&oE#cYeGla ztGl;`zvo2OV=CF0ZoKD=2E01V`Pu=Q2%19o7{7Ki>sCEqWMcLX11^51pRq+2RJjJM z2{a(hHw*igF_R+Ni0$uqKYcMG$g2podEKv@Z^Vp!22Wb;Ua+Bmdb1<>>7KfM>4P)RqzAT3NuXL-Ctun4|KbKy8>tF6ui|4sD zv)Y?JDbOZ;+s&)#H!rQ|+3Itq`}YE^=&vNn(mF{pa7&WVl_l?(H+_#jr`*tF>6xyR z8RqnG5pI;l3AzNgNd(c2g=7e>TOBALY3`ssOp=43>&$zZomD?`tMZp2PDje{j zAH7u*9r3cW3R!bi=sdt4J&X>l%{ky1dyLaKzt=;p!uvoKIvlXa&BJzl#yY^7=bI&k z_E@#k9$u#%(3yKf?^`PPS+d8}(h;toIY+}Y%G`wxxcN~9AMPb@mN=r$Wad({|6|e9 z9!H+AhINelMb;Je%}^tQ^^t#?g+ozDCh<);>Q7fAeTf?He{yff{h?f_WT~}@QVAv(m6aQm9RHi#Mzj}oTEwBqxbb(9Ogc4*rr^1 zD%i7akdN(N%!01PJs$US{U+1f=#-D#^SLi++1}(slegp27a};|%kr)nBcoaDcsZ16;n7 zv7V3xd+raSI0F$egFZWJ@_J@P7|C_~aHS7uHM|ftv+ZTB%1M&1JIS8&R>$N1bI^Vj=h!$Uv(cH>-0b7oJcYEU+j?6_Wo zCI>W#yTs@Ca1EAyFhJj)j*zc>UY^K8JMLx1)L^aI!-$79$#G}W)jWf2^-elF{-s~9 zGFirW<~h@&9DRTsV=sH@=hjhbL?{tnL6(1;5`GFZymkI9KPD)!MN0Vh2Af6DbCFTaebg4*3Jz;Vh4X%?$SUe zGIM%Axs(_5Ta_{cjcaOi&dn57&%!n`_=CxWc}$??!j}w#d#b zyFpGqoDAb;7rE1?lh~O$N=b}^d|qQI)(yKkBrhU@4j z0}{BWT>adLA+w6`sn-W|oNYvWRw0&5Vx9I6t=Kox%Bb>GIY%C?&@ojWzo5@9+!6PA zws-KPmx!GB@qG@s(>wx?ZbzU;f*Mh!JS+F*b8;Ykgd6EdIzgt^?oub(VY2v&*$!9 z`YZkNaQ{AQeDpSrj#YScD>uPitMF)6M%I#kEvMlJB_l{D=9?1aJz0=OT+jOsbVS{? zoCmdWf^%<2465aXR_2aSjg5fqOFD))U_{rJp1p0xiC&QZS%Ddil zU6qhQeM$e|1#<1DStn?fhnE5Q$R0taaV^;$`kMYUC_LWqeOgS`p{P{hF)}Y%(zhIv z!WIW*9_JvA(%U={0o6GM`5@QohNn*5K4t-{aj*zr6}@0yQ#O<99TQ+R~VR(SLw zPh`XQMg5kpjdt`91f@uud@?i4CGi_iH+5#JSgq4a`eyD&4zRxD$Nj@7vLN^E@$0S= zYOdoP?B)pc%Z7M`6lVCHoLau*n2#olmGK0S!Nd4}vp2CS(O8#xbWnWB=Z zwe01G$ypAJ?j%Rz97N^ZMdl4s;88UNRy?YZsyusTve$Wm9+irV{>bVPh-AwEe0myy ziA(+PM<$(rz3FAFM2~NU21=esKI_TJ?I9mA$$*wavv7-N=Ol82h8N7i*8GRpBM-OC zh)TzpAxAFFelqv*VSH^{Tx39qN`ev{#G$vHh#v-3^2Ics(?0O^= zAIyTkodIR8TsH=>J}`#o^T|aRJ(#cKg%LZi(anC;2=lT|(qnKJ2|sTuB|-ems;H#> z8(Z1(j@ilmmCRf-VL<)6`*!oAPW_t7vXGuYuTy7!l6;WTR~sv2ZHwONSe zUZe9a{)jHZ*ZD;#Ty2Ca&s_nVI!eFk&ddYqC?hBLkU<@7CD2+W-JO-V;Y{x`vpTnM z&ahyd8SZlCBz*>F11FEb%ARCm#|7f-5zgff2*AJd==c1f!Szbp@Tdo~1x!4PR*S~b za?S^Ey|TE?y3L3zcn-_LZMrOvq_Xz0sR+;8aVE`&c^6#YgZ%k3&p8dw=;gP+PTacc zWY7=2+_g%PCjU6%_EHC^|8PX7b1Lj!uEIyI8?Kktcv532!q2GbC1m~%pVx>`!#!IE zw}r{5dng%lNRLT7`3#!FS#j=#1Jrq#b0!zb%kwa16TRY_$>x*$>PUXM>j2*GYOY<2 z{>SE5HtD3-GaV=8b@C!XFI8%?p6;cW8OJye@F(+yxPHx_rNX@}4ro=O!Y9`V&d{nM zqarY#YuMw-;p7L@2)fHG9`56p^R>82G8S&cM<1E((t+;aoGw?|q;ncF?6H*+$o~)yyN(W<`<=E=ZCMyHn&*kP7-8Dpasm ze_caLt=JzDS_Z{c1dU8$e zoQuAr$eCB+GjSMM%LS|%KVls?j_WA7%KLm@-W_AVmh7P8MTN(W0jUybmnz2w>!riq zB(bf~$w|kfq8O*bD+fmmuHp!T-VVVV9WeD1^OsgKXZk_}A}-Psz|U$=ANJuh)Y!UG zkLGtc-_LW-nIUu`a{n=XtsYx>e%Kw6hv&QVk;XMXKZvzwKb|SF>4xO{@$sC(!;D;h z*A)tn+GHC;>3bOWAVo&>Wq!d-o%~p-lO2Xs$yn`(GqW6V@fCU4ZYs>UtHSqw9k3@d zg3lMO?X@CsD~VhquO~Iv*OpvMmj`kU>y(VC<8|mXifjC7_Wdex9eu*tiEjCLnU#nA zQ}Zz3GdcK!TrbGLE22;kpWq zxhI=^M}?T?DwHo(!KIQ4_C67K{F6?Gugs?USB?2w)rdI6_h&QrJvrnC^0|(#)gk`3 z9-Y`9Q}L`-YeydQ=<{%O2{XBMdFXwKndM|X9nL5`ws|N$4t?W{$ylymRsJ8(m}T8c zS};fGZarUI8Ar}&K6$hqg;;vbLXzhGkm+xI5#W z66-6a@_xQI29q0FQ!f({Im{7W)Kc^XrQ$=MS3dbN-8FjX+S8Lb-$J%dDVMtIy%3ug zg@#`;@No@msApQsm|JBsafBBfS?79OmAN0g3UH@!OR3Hr=ZWMiOZa_)gEE-WSjhFo zQa%L)*xvlL&OVmY;te!vrvSQ(swKm3@Hli5^q`;|zQ8$Osj zBN7Tj2C7#SAls*@T%t#8buVw2H=rLdArr63*G%qEPjZ-VYZL2@WuxeMBv+Mlv=IGP zw~@r=3cNLVq3~%W!rx~wud@K}uC|gp8%pI+H*XwBq=znub!zuQ6dr3PB?n5R9=(uD z9a&GW&stnS0S4$IQ`gc7wc|p#Vd*yXR(ta@v9N*bdL1pHEkw&Crc!ieTS2*<$p{eA9tq!1^rveQ>$`0JCN($ z4*CjN1Dx}z0Aq66$d$66GW<_31Rab-_NGh>dBR-XKN^aE^)m4u?uWsZn9bx)P7~xn z!`n!=s=wr)Jo?}kM8V0EoZV`^{(a5m#iUC<~Itk zB(;TX>R2p|&B>8nBd_-@6YsXLuHLP+sQfBqUzsmPwqf4QI@bMXk|WD$C13dZ*Ix02 zF*p)$w$Z;ilb*P$Ev0lG=j9VUaW#G`?(AU>`1k_+IN3r5HR9_Th55`Vz)vJd~7AX=M+oxAKsX27Kw_*L5zn3%Xf7=ye*0i?L;Y+djeelBJRh(Cx#(mnS_i)NLmmWjP z%6Z1^FDOGKt7i>^%Qr`K&BSp@cUMB;)F?dPb3Fj%6xF%*M)rwp>j2ssLd7P zN-kU3klyHp8F-XbfKfNvNzSBF(bJoGZAlbX6=%TyN&(E9v=nWl64^)I`9SL^*2Xii z+?oF_=T_24!RJ5?A9$^e!i10HQWH2|xum(IWR~zON#7{@VgEXFb|j4a^1#-zc~6;y zv2XA*Fbcgo^M2=Z(si(yX!eoQX{n3i0TXx$It6 zCfbJNh&M#iyP1if9}976a9g>1uUO(9d1FfMRxCY}ftj1h?b6R!_^?dY)aLci>sgRN?a{^c1t_qS#Y>oq?Q?0<=<^%fRNpot!TYjR$HuVS9*7|z6V0&AHgm~Try<#IP01T_o8wwjzh*_eY6awt1L$4L4t zTO2z|{~GxqtBM>1rdMEW|9F{0er@d3a10}N){K4h!{inZM<+<|T5CLf8UpOqBBpjO z?!=Hwnh`HH4d~-LNpD>ibEqqG&hI3>jW+RecROn%uS2kTEWLrB$&t-5;rp8y*&btq z8I42nrl$_Q>oDgxiT=1&39|034GLR_!nUCf5f%4PzZw0Kf0D-}r*oLEKeD41QR}mD zqbIq=AMvuRGxLsvLNU3C7BfP~<0R1McrjK!kbj&~D-^*XpLL$I?vv>stQjX~$Z5Q~ z9EyW{Kg$~A;#yx5jE4_M-wF2U6BmL(F7Xs`YRlJ^0n}LmV@q~5Ah56R%csmAs04#FmslQGY-;6n% zjTz+fu0D;I+!uE6=XHBDREti%Ifqr1KDeC;(t&aW*b;X7~BjI2n4> z7TME6;7ktXp-b+6{f1vW;w3G>7Du*+F$-IZTg!9!Of+HXxL66NcXHYJ5LDlxMMf*; zHPhc0G4+5f*=LKcrzISd{2Z4Zh?RtLJ9ymU{eD`DNtrpQF`7QmA8~StzQ3=$P7YqsGOvR7 zos$W_4a|d{Y7KeKTx*6d3#iw5sEdv$eHFc7oPV~yEXfyR~vgc z_UHY=zqiYr9Q;v9;h`BBFMIdf;`tQLf*<1hwmS!VzMC-9Cqc%OpS4X0L(G~am|y1S z=nC04cuGe0+jd?u$xxAJ4 zLh$g74rhku;9U;=o)&R3X{0^kl9*Rco^*&)4hFhbpx&YV(tHbfTcIcME3cC`*_gK1 z#0FO;@hclO$&=>Jq;L0?Ju*Lsp~RKG%cI#i>2AV) zz7K2X+M|kj7}k_%agUs7SB(i%_8gG5E9`J^Whm&UxsH;Pg3;SWN^lU2QC3*^H)0T$Ov7tq;=o}3By8>>F z;v`?}p`H?kx%~aSy15wGvEsk|u>T*P(c<};^l5|B-Qo`)bThuTOWPTv>NRBC#`KRp z%`^1Xj=QhA*~BfP`JQx}YJ1bGh3!xGS#&);NHyW8{h)>Ftf?rNK{V918E zsR^sn7hK)sz9zC|uVq=SGA#A)+&;Fvopx4l>%J#wP0#a{|4Os0wl1x5-jTB@ar*Rw z8~okJt{9nqH)-3M{wvbclU)z@G_BT3N;>PsXA@-(^9SB6N)(S%DKdR#io~_o$>{1y zVzE#sBex~Wy1Ge{Gllb*8m&0aN|J6{lVsT7B(eE?Kt^XJ%GvJ8ay%eKPXE$M7iKwi zeUu;zb|uM!I?3FFCrj5hT3N?B`LUFEW`8p`V@-o+|85aX@uj_C!`Y;8BhWSGe9Sqfg*> z0<%Dl+2ip|&W83P)2LSAMQ6_Pv!1bUDA{3y0}_5aA|qafltC)=D{w%@IA)Poc0iwS z2TbYci0btnVex=}N7D%O)Za6*`sPWgYFbqtI zfd6Rv8z-otyP(F5kMuMqhNB1neCJR#n!P8l$bHWo_9eQ!Qe*P1aC{F^W6Bj~m2kb8 zJ(wATtJK)T`uB9!=G_-Ee_{vw7Oejq_*0GNtS784WbY!9`O)b*Jj)>$eO-rTnL4cV zq_cwecW2f;URTf`JX(hk{v5eqkH$vUt4^?n??{g$>or~Yb*nime6<5T1wP3*&K}6+ z1N=JwWYlE6q|-Bg-;R3xn@iUNzxSlcdd|M-P`zg|itdqXd`%C}LmkTJ@wGgq51M^| zCwAWFz$_)cG*Q4JPXQMwaqXQ+w9kKw;YF#aJkZ( z2_?QQH_6~yl{lxVgnu?`^VO87^n?zWbR}-?WdGo6g&b?3M1z^EN$;kQpt=%Gd(n~b zf&K7-{_tggcSKkqaNG}#elnx*5&6YNzSz0V4~J8kso0UTj*tCN;Nu5Z71_o0zKBtf zZ*-?$#*Dc~nLe*q&JTB``>1CB&2Atqn-vQ{K!i+q{nfn25npL_imA^I!fkhfCil#^8YWQ z$G}{J%VeokTQxYTivBNikoSn3B>&EC6PP`?A)0$7GLHe#m~euOm74CEG4#1@ARooL ziDDRes^$iyHQ+oyd&(XDbC#cHK)f$&X$8#TtDS{=^danKy?nth16BrP!TT+JKZ~;P zl#JHvSy||Dg!S~1S(sp*g*+!mS>A z1W}x0Ja5DjM>+`T@zJ*^!jtAk*xWKA@<}1io~GOJR3UnHGh#Wv$Bjtl?iLvlLw@ma zMj^KEF=7M1$G+QSw%DhUkwzr4hrcDpUe=y=5;O7+s}4F!%P1$Y*kmh1^v?3R3VFj0 zR-(UeBO7GNbKDU;M z1@>Z>>L|_WXxwbkLH>AZBS}M4@~W4OM6~K4%9b6Z(V_P8YmQ1T9(IyLN##y#LYzu}%N@E-1Hu$2y;>m--4*CF zfzF~+be~3;WXS_^8kyy?V?R9*n@zH{A!mZy(Xli{fgMpwSezs0QoUSyd67fjOcxaI zuOAx~=#@rpIoJ%{Ci!7HbGWvU>z&t+Ua0T@bX!4=qOw2s_3%gW>HyfkWtN!I4^>&C zG^W$Tae_SJEMH{(K^Mn9Us#_Cz=#!oNIm0+w?F-0-Iw2^x*vYFW}eoXKn!O-^*_9) zrsevfRu_Nf+4&)(W&qw*XWl!1&-m4!E**dL<@b*0%KNL3jKZxbtPN$)(u{0kPYuGp zN7G%Wfx~WQqn1RWnJF4x?eb=f<4AxbfEIj zt$j&mCqjcIuJo$j;XTKn7n6O+$cx6g_tDs;AUD}SgLCd0l(f`f;CE(x1ZlAQ8r@eF z%oqtYVAaF_WKkHHw?HQ;xnI}&beZ+ef^s5RUmf#R!ZPVd;r-=jU_Lb&;DrX%xypJU zzxF-vL7xYlL7rv6xw!wiO+7URys1gAX|Mq!i`if7&i`kY#hMCp;e>V6_T(?v>zgn& z3p1bbp5%QUXf!gj(TFjAMX+@$Lf5WESjy}D&Gkauo<>%r8?%haXDn-P#LM@EXl}`S zi5$|a3G_J5=DqltGpwvz{e7Uh1dwa0+^7gK{QD=D@cy!AFEp=FdU~O*=ZvlE(!Fl4NdKiubc+l-mF^a0 zm#)}dE92;aSLx*u$?3<9zthV$Lr+JsyeAvBSlob66HC6y`q&)7Od1tzo-=1uvsUG zkF-*wp;q=rrpoS4NfP!?l6ap?mSq)M=09-`t-4k=WoqT)Z~D3llErPiR@}Gg#Zi+W zVPqc%{iBx_+frl==VYEKb<$u7(OiYrrd#RU^WC?=z+GD{{d+hjW zj{qMPO8%f%+m3dYZz>egAvMz35v$**u;wKF-4E;#y_aXS>g>;qvS&}h0R>_7I?iyw zkP#}FLjRL_%Gtb$PAD~U-*{4mmL(3D)5sCmrqlKPT7}$n2c&Fw#KeEu6*<9q%qR9( zTjYS=TO7$|sW8|>jV8w;aNV4HGjfIxKZL{n5PLwo)d-GOVM}Ll?Lh7xexk_iioOgZfK{J^jf%^7qE5$>~(+@cfA$2ihj1=TRM$tY=t;>F}cpvqQOW zJa&=U(^d3%%C9?fiW$}|nLmA%-tR;`>Llt=*_!=Y{{7eZwMzE6#@Oo-xs`iAr(EWw z@Z8V6;I!wtsQo$@Gn&)2UBsCd_Hogi^Du*Q!3P>HIWQ;nS}yXwat@{e`*r8&R!rbb z?4Rt{jm*W!K6!Mdkx@LxzS%$YR}IKT)3%%~Wl!(?C^{Ms<)M`#5B1(N$2ubygEGlM z@(e!wIvs9P{vXd+Mi$QJcnA6P7x#fTo#jlblbjl6BL%)@SW|^8h`ADHdnu4nti(Dy zC9{9HUwP~g&pbc)f1w*8oIb)+fiTObTe>(JE5qs4tF;Zwi}>rEWEvYY8~9Kbsw8J2 zzmow2%*ljw$U?U21L_ScLRyRw$2^MgGWY{r_b_|0uS)I)+DiAA^b^NA%ds0ya&CZ= zyl8KR@iWNJx32_?MP}$UjdLtlD&$wy0JPKlfem-m&i04n;XrJmlOx%hzUnXBPbs5e z@67!W+49cZH%;1RK!3|DeBmC&a(fn9+#}2QE)yR&(fjN}W{*rrtwiQKzbrysvIZ-Q zRPs>QLC()|lmW%I;_;a-e-h{f4$vT6u?=4$_^ck!XZ;Uy>wG5f<@5bm6rI;w zIX^*We9?p=Sl=*WA!jjiFVRbFYbURIJB!P|9c9B3l{8tek_WkTH+%B$fAd?u%~qoO zCMDvRD{*gKg$(LL4;h`6oelnYZQ+l{+?TehABc(kY}!oRhQ2GANBNj}NQ>!0yb+Cy zTu-XUW+CLR0pk-m!$M}}papph@-mmY7h%E|KD+sx&doQ%u743$P39gY+*$fvaFFAj zne#k_udA=4jOMjcbGu1Sk!c*fS&7$2&0x=KsRv)jn`Qo3;ulD_IOh@4{BX`b5Q~GN zk;u<0$RZk!adaK;j)r=+22&n#jpABXZ+I4t-pRzB6a%I<%7W{9ax$06rg(FmNiuTg zjk(;#TvJ-P@Z94fVIRpAC2-$VrK2R7yU3|zC0xifzJB_fXL<$vHkrZqk^<*mkv%=+ zha3sS^lSw!F{4%BKM#@lBK>%FXK3WetgnFiFl-wfcyNtj!vjoIB}8Ec+>CoR+=sEr=l zM|p^T!t-PGeB9;vvX0k%+~PA~$oj`+6>BZx;P8w$D z#&T&Es4`9=+78Q4Uag#NFatJsG)u zTiMGeZ{Wl%$o6Kb@^7CMS+!4}$@Bh9vU#jId-5FJ<}lx@ ze>n^IK93GM@(s+pUeDJNepBJ0pqrp6U)LUfUQ@>Dq`zm1SOn_D+&e{1&eKY7|uM*E=y6DujACF|J3HfF!TU@nv#s^6ZG`!>#_Zl4qKb* zAzTyIWpK_hlkKryUF~JSq_{(U|ouP5ex1^lph?> z^$1y%NfB_ih``@n)G+rVFGEITQ9nJ7-`8VL3i&1l*X75|P*>_Pi|@yMer7)x(aU&^ zF5y2pS6w$Bns;9M`IBss~nan792>?|jT zk~iO|MC=a*)MX~g@mC^xsRE8$n5S^e4|!Uixu=qko6DSpXZ{%0n~dHv4e~2#@T;x{ zb?0%m&zcFMDPC>BhGVA8`_Z1LjKz2S0~X0 zSxYZJ2N}?$lPvY=B#k$!Sjjab@fgqIA2R9kqO0Aa2tC@; z&qyB4$CB%ou?VY&7NNI)2eF9jEGgGJh+RYG0#xcCetbTDBP)2N1z!hiA_XZ5oGN6U z#ZrN(JgfQmaDD$b0P8!`Wmzi#Q@Gyy@!a!ZEYC!&AG~(=Ip8vU~DtSgZSL`Is zGM!{uRR?;YoaFDHPI9=LO0q6h$jH_TOnj_B)0gBJ+bYm+iAlcZV++K?Sghukr`_l*G3h2&0;EOFaGzeC1!)2az4}8_&c~cDxvw7Cd;yEyl z{Ng~?aJU!R-Gnul>Ri(@IETjdE1BoNX?$%PcaqHwF2ejl2gPY(vRu_ANt1^M<#mlz z@nt?yPj3fw*-nog=iXxy?BTyig&x<)rFpPlcwLQuYcl8l4cCe3YR<)}5!*W%Q)VUO zW_vxVUeu$_U_EyH!`Yz~`S|^J9@dS^$L$4qSnwqeiDr2)dr7XF&zzX63XkW`^a{UF zc$~eh@R+RU^LaC8#CSfs8?Tp@ti{i7d{B1t`LidOe)_IX2#zC9UDpXOhdN@P4IRGy z>4>}>j-@Nr`0<|4X6Fb@c*S}5_w@PX>oCBRvjJyx2r%g2v7gVKF7zLs%EKqtavKKb zL34e=_;iQsnnLC#=v0*GZ_yx(( z*pl(Sk&DH#TqjC%(XSdgc+Nq2*3LtJx+-n>TJHAa^SOo6L;sWP-ZO+#@`9@kg#+1y=^FBh1DG=Oejo@1tLC*K*Ik0Hlcqdu93O1ty0l+WV>t+}43 zDm?0wV@xaJtO7qj?J=!XFu!2y{RDCNMo&XTs_a^l-JMr4#`ECBTJZ##KheOI$#zad{X$nXcobJm1w}=HUHY&W`3GX{OTS*f#o8BI&H6+tZG(X%RoO|2tQ9 z-m{fFv?h16*9W@q}H#oLrwniV`wI>2a}8OHW$UtUvj<^bBY&7p~E9`YFY1* zw2wU9;9_}xeK;14kHVt*oU0-iliItD^k%;89_A)rPKd;VXBjxWuMkm%ZKTdblVlHP zPIN^iToeX4&nU#8ZPs$nuS9$(Ey$q8e~G_%N!numU1q=RQfmf0!Bn(R&hE; zmc*Mn%7qve%v{~#U-F#)t}y<)EE?0l#;^b3+fpj}m&vJ? z%#E!b2{V5Ei?~8mYSC8uH7S$SZoXLfFbbC%Wddo1nC)OC%bAbd!GYeojZugiO)nmK zw-0^WNnrb*l4s?O-33ulmoRrp$GPEl=FsH2NS>EH~ks?Y1n-$KS+E0(W4 zeG%|63PXiiOlJ#l;{$z;_bQ|yfnGWCQ=48hr<;6M#}jQOGyfu|^q2 zj;~r9v7Gu#T!Ot&p^rq`sSH$W#+hk)6;E>CGsna{<)8Ez#?q^}p#YyAScxBf6pN$1 z*`H*N!Vm-I-7bW4WgGcoS1MzJd{8qc3fm56Ah|AU_9{!}4Y8hG?2XzNqA<8aCJe0m z_qb#yRVSCok5F&?%ll{=d0r2HdP^s@5!aA1aVB4Om3ht2^cko%s{m1}TgyX>V%bLy z*Pr#@wM#QG!iCNQk2a#PDwRj)ePA^|5*PZCALR9~-qlpJXN#q3Fmdo~q zJ{V7jh0nVTEb7Voh&<*~t1{V?47llqe*AY0;(gbU_v6+9?WEz-U!pngg?oYA368#gc62i@6fTT6`v& z@cqe)w2(jlDi$9*Z=Aod6}`@7Ku^whXE6IHr}#YS?Sq7VQLq`Cfo0BrA58iR!60M&!_Mc+G&mmW7ycv6Yn7E)%O2eBNH7w~;*Z zEOOKBUenjv^QQzyd7|IKNQA7&K%0~TlniVyr&|A(lV;?^`8<5hGs5UPMy$MSA=FA>L@YAPUbyGca^4-_J%?(j&E4mbCI@?nx9~j=cVBl8+wWPX0Jm zEMOWrr*DaN8S>Oqif$L6BK9?#LBHPqf`i%J{$ESK?k9QOj-ROxwQGlsGV`Tar z8(e-Lg24J(yzarw8FEYucEvEy$PRNxgu<-_-9MFb;j+Vo^q5#dku9^QLy^6o9=Fcy zZAY81{z{_UVjgH$yHGq|L_gP=90WyIpzp7Jbh_IjjI-}~oydRrX5+gn^P{u&%Z{41 zc+;HzzOh;?ADM%%Jxwq)jFB7#lpvZ8hPXxTV75>D^eV9A^)YFZ9G&Xz?U2 z8?I|jSZo(7eUfa^u4yRh*^rBwk&RBjD^TV8ez||#7K{Gi>m08|#E2Z2tW4K^p25P|Ja~pRT!oQYq8lxPvUVClv@%df1Cp>`1&s;Yhkiy zKJRQ3ec|M@W|DVvWBvP>7L}aoI;x@Y__d9^+jQo%k}Gt1!hGa&Ik5S}oYr?SvgmKt z^Ir$!b6+hs?aD!ybtZJLaX`xY*&=gJC>&>M(VXvFoEhg_{-z($oIbuZ@?0ymm>y=;w`8`~^Fl=R#+-XDUd{M^f|`T15- zc+4fwc<&TN zF{D$Xq&>95@qTJFHRpA8AP4pICS05nD`|xw_>z7I5h{J9^5nDOq8s+_Sp43 z6wQ6L&~GQ-x4MEXK#a8BYLAlNOW>r?VRSdv>Z>wG_)ff39qYiHw{Z6Vv?yE1S)Vs1 z=z1TJ$!~1Yk-XlYWm+`kbw1|431{xdOYs>Sj3cjCi|_xA*lcuYqwuKwGeNGGS)tOx zFnk)W`!8?%XHyeCMaPS})E4W>sXa?$F7tpKyxGe8>u{Wm>0pa()?s*dPm6uz1alr% zVB?$vvh$=JM%D~P#Fr#=_?iPvV|p9=B*;x(Z}sQXXZMrYqEEA-nOT7omhn>kfHgd7 zgre_iE&fQz#>`|B1`dpuZ#UXwem-;67w9mxe=c_1rMI+woE+_GhmYiZ&7H|D=Fq1} z|J~Q;^c!Z_qAIhv*`D5+~93cQ{4{&9KD?a)JTmK;7w2O#in6t*~FFc-mouZz%4^lB+$Ci%py8 zOPw4q#?$250{D6TN<#U*Y?%F`=dn|QbT+fa(25YaR@cIH)c<^uS>I#i{!BY~`-Pwr zpEIu(vG-C_;Sqd2MwTX7qjXXzs`9#8`&SOu7gs>HD^@C9vqjyxAsAJIvv3Axug+wy z_tFG;>T8WTe4bcV=j-pyY}BW`Urxoy=QKNHFju;BIdi>vogb{F@YwIo8R?bQ%&rN= zxOe2KopUgDe+3#^BuLO&8vf!DjJ888`OO!B zIxMWlK9f0p_1ak3pKk*X^I)u=OFlF>2dRAitUAFw^mH4nTojHVOLCEebMU^M!oxC( z&zUpKa9bZnCR&S$d_6mQIw&u!4i1*TQ#74zofym6ZQj$v2RvNq+rbzWqiUUE^NK7ZcXv!fE@Mdgw#;dJe6*p(<#vUKu`?|JA0 zt@OXftU%`M9Nfz~dkd{p<+J5bZ+Zj{B+CWXbzSf3WZFN;;@V3q({JizZj%&w(wQ}c z>&bG{Hc7fhCrUqaW;#vaoa>4N`4q2{R9@Gc$WC5en<&#VQe~u9swg?`DvCI{SRox0s62VA04xh@lM`^jWYq43tD)doEr z>*_fNp~H>JdemqAtb5~RT%SR|&U!i6J<8x>cGow?JF^gZn$${%#Up-#kW6z-x z|LiUDi+l!e4Ax;6``M>i^J>mIPI#^!D%Rf2*XdBNrXKx2>F_N_hv6FLU+^__)#~uX zH4mws^N{;1AJme=F+o#F&7EXSeLiu9P&)EiSy}WNMvTmH*$#jJgo7~ zML26zHw?L`@gWztZ1NG^IG@?}tmm`m-PFVx3_~8?vSu@VYaV;C%$Qc?V(7_S{MeI+ z0`|WrHOWWcZg~hR$weCLOB*LL`)!$vczSh^CWQ_%Xp6O!SGSXPSDZyR&{^IewwH`v zE)sjtN{+p@5!>sWm;Y!Z!;%~X8Ifd08je$d|-SD?TM8`h2^%rMMKi8Rh3S(LGcJE%g6 z)yzHgrQaY*fn)r$dkrReTv{##MJCaBv1c)}LIyjVq__$*t0$IAj~E5dzDiu=-%+_# zfoVOI=seXVw^Mwfb@D;~;mp|>Qs+QS-bI#i5wkb;2IBcT zI*ls)FuJ8bG~4`9y4(l*Hqj9=(;t=I_+w0@AJ(wfJ&*kXGxl}Mu190xDh;|^j7Iw> ztdHL%r?`PRxl_q8zGbdaWHg4Ec- zANFaGH?!gJmpK0z zNQN=IPZrFt8t@|BfW}3veO1cD?Y0J3tTAx!O-GVvCJq#4(cwiOq=~!(zfVGCdL9i1 zD8{mvO%}5GNcNAd*h8OX#5~sg>rNz#=*QkZnDKXfF8LuMif`D z-?Y|D|~?sx@IgyBQrKi5;Z-4F{Q3&0a<(rLDL% z`z>F(nW6O9GOSSc-vL>jEGiSeL`#uGlwNPN4nG$xBDrDGm1yT}BQqo3&8+%PM zW4Iao9V+By7X|k3Rp9V$vJfZ8JG!$cNJb)=_nl|90u5HNmy)W$uSq6R%`205Ka)Hf zYm#q0$wWHR?RdL_xsK&B_+6RYX6AZ9JwJ@h_r=5iL)u%nMcKV!+XHrY5Q>P@5O#x} z2X^1Y0JhlOEopZFV`8Ah%m8*X45+u=l-&h`o#ed7{d=}|dp^MPhZ~46jMvOs*IMh` z&;3}dLN|IEU)J|Wlj`IWhp8~JfS*L}d~M>-937-aR6k}_&m!+opZU{UqOqoPG&%*UG4Bq0bH|V~ z9u|$lDP(+#nDxQmSG9^7-7UzFsOV;N;>Q6Q^qyVB_V>)H@=so+Wb(72csg z@qRk))nPU(YjVpX)6k(~I=08Bqc!VuBbKLQU=5x_#q(^e9rMC$GZ2};+>HffkdKiq zCf|7b7kLzpso?o^TD4Ed!p`K1_`MINlb_i{W|B48+8n2US7cyCB)zK-@-c|-{rdKw zVBWp}W4(-6evi59W=5zt^L#a;0OQ<@@a|rK9#sl3fa5Irni2Xqj-51qoKt`@%L3H$ z;2(~yJ-J2%?aRmD+jO#=W*ze#&j`EdD}KGt2%ZBu z(777GT>0*|yV$tBx=@h)yzA@=yY!LMPU*Y#i}nmnov3de;-h~&=}_te+hkAI4l2)@ zVGB~LG>h^mdix@^-KkU$&!$y9R{grHuit!{=ak`mmS2Q(PVW!d2Tm zr#@ibvq!SnE!WAYZCVMsnk0)7H8MXoDzWa03o4Q`{J5K$&)?`*v~$5?_GzBJ zt;BDg3j*fTzs&mzYyxPZgXCC`zxMnokALphHtGO;5HBE>4YqgmAj}~b<4YRq(G?Hzsr%Zx*E%vs! z>(Ga5L&bjbkRCc*iqavay$)Awbo9{j9Et0|YUa6kJ}et^N9JH?a1PR^WuZjP-rHh& zvRJPidz<^Qw)C1!$iW)_Y{Y1o1-g?xsZH1?!*ykkLaz6Q(bGsSX8T3D(CYGhFp}#= zaznpz$vKA5cf&fYjVcFT54h*!f*bf4PD z*!nKgLAjjT)SPw5*#?YruS7O*$DydM5gk$9_?OXwC@-IiFPJ z91{QCi0ZS9XrgW>JyyENd>0p~RohJ#opzPQjp#>=;aYFMImVI)DSy}u;hqYN)sRP9 z>5q1H{`jT{q*FNnUA_G=+`}JF$e(>nqEC-=b;c-iD(jgU6|aWp-gKxqe`aT#T3g`_o;@f7rr>}D^=5;#VkJ*!n zE#=fQSLqhwBx@@&FMMDdNqJvNCp7zh7SY)>)eO^{nDgx34C6H_U~nKKF6oOr?T3a{ z{1KAui)UeK#PRpL^4b(Bcc8`w`mXLqq1|`#f_y%`r)5Cr&2`r;KEEHl2bmSXZX#Wp zbLh`aB!fDZb2YEg&EZZm^+h{Lhj!1v4^AnFVWx-Q~;V{SF1n zP%6ov*^kiHAOB{maI1bG2BrHWF@t~Sn$+@ZG)DH|y|)GX2>AEUyU7&&HDK^H0}}Y& zSvfER^WS8k?^}M}`V)>UDnK}`?^Kpbd zk99_+$QjnohpLk09eW!8lrf8;whO**C3BJQijiMk@u@F+3j4U=M@~3yB{1_PCLG3v z5oq{4oLnmV0N1m2&bcRr^U7I%zSWL<*uhDt#C_k&Q5^IAb8%`Wb17$V&e)xUf8)qI zkSDm=jgH2z3a@YELhA8rk>v5C@6#=O>zK4@sFRM}lI7)Pogjd{kK`}5dXkIls>H)x zWG~9oMXYC@eC6=6eD!qT%oWoNim`$m}JnpG&59BpdIg-o%q~F@&1%XCjT3~ z!Q>t?dGB&B3&m$%pJ@-tTMQ)A-ZKfIw{@sv(BbiLDfq#D0kR-U-d`^c;=S(!J;WdBw&MLLv504yN_sBd z(Ql>AK||hmCi2=ebmcv0RW{;+6<#l%E4=)(6kd7P$fxkEeKC2$qJdhOS20Q4#~hVq zlaGkiDV_X0oG9z7lO?L+3j0gU?Bw}Vw};FS<@M=2fG%bCaM+#Ty?JsN9tALa77>VU zLU(3EEdqH)v(hyQmaB9qc*OkIOSxDufqeeD94t!W{Y{^Pm+!ODXtKg<+#vEzWJ1>4 zntA#4W$rY2%Wd@LejaQuTi3UhNn_mPhSEizJW|SYy65+;Hpe~oU_IvjVtgM3ylR%p ztT@g!LH>we7>HpO{%EwE{MTfEICkMW|6Vi#Ox#uN-p>JlS){y|TlM z)?)X>Rh%u|IjOioys<5RjXrqu{QUTFX- z-}A%D@&4%e$`4KEvNwxo2V=ErW@qg{`**y*b3R--f%75fzz450F#8Fek%Q@9&Q6EL zsRA6W#d)yBf4u?BNZ?+&_#E?$qn*W`{NlnX?y}>nv$VBiPi)Ul@(5-as4A67;R>8? zXp)k}W~lO-ds)9g?BJQo===Vd8WVu33;p2Nk@IwUHOj2j__CCHuSJ}f`|ZG|Z&9%K zvWFQ{8}m%xZapUpXEL;=9*4XF}s|5POg9IRpVKZzY4h> z)i_#*+~5c98HdyJ8OM7o_nS{k3{Z|_7B^orhr{fh;CiFp_cY|+Ex>Un@|D~hy;#b7 zDbF%4j$}W_J{R#YqZ4{*Ysq`tT&_2El}A1<5-`&Yu9eH-!4q@5sH?!$Dhj+gSth*) z@a#$F4|}^nwCbUPVU3FU&jGOZj%MF2`|o(2QrR2Of%mV;*n#jX+#~8UFd;SroxC&f zF(m`NUNdu&uhqqMbRDaiThW&Hu2sf=L-FBkg!8!^I?q0FuBV@M&B5_nxtK9j;nmqv z;WgJ+;bqDB(7gw1=AkNMv#D_a$WHt7_P33;cDIDorBCvBlug~Rh{GJ#NS(7sJYL~=*09%Du*#?D|{xxgz z-xOZMxkoOJ(@1lpR&MgzY+kLEbIUYRvYR!DJuX=N-37TXxzC*ELYE+2mVCc7;e8@u zM;Jc1MPP&>9JRkPgV3Jm_SJOQ-z*77lXX~AJqfdRai7*C2eCXKzx0dzLVcD$Dzq7!;CYlM71KPLk_yB(j)ScO*xKmY%EMvuwOWEXiW z4S71Rn~~@}!hq_N^I>LeBKwwc#We4v*+Bv#^zI1!YoUyD!fZqVV%`8V2g}Q0u<6;Czt`X;1Et+|9z9Y3TXw zBl^v-kV|j=NXaN~RDH=DVe)rQEAmkNfsIrjQ!F;Kym{}BLM%C^0ewEA`6oWlgd$l@ zzU=CRD3rEi{%qfTEL+q>HZLud#(CZt{W=N<$EV@Y;g9&YcN0k*TOy+;`vG5~cz(vL zk;8fHW44ry)eEHtIiLzUdg68(xE9RE^%!fh*8CN>LO+;gk{`UsoZNGHI6JU~_;xFj z?ujZm|A@l%)6Dh0%G{94*FM4j~b*n>8&_EAnGaDH;wn$varGESxg%2kT zxc-!$z8=ogQiB)@56Aq5M6OO3`pTwg_@|5E0;jL1h|clrva7fI+?Uo5P{{Ni&4 zyt86n_S)u>FtbR~zxkqc1G&puysvfVy|m0io{_`dK@PED0Qs+q2Chfh@0?~W4|oQx z^7lcqo_SF3(s&K%yL?brM&2tDpL#wh-5iO;9M%r#10A8NFYkK%m6bfN?Ny#U?5T8I zYoCYJ5e+4CCG)u3_@U1$=58NPLvuqOOh21T-4!LWqNfim?nS{f#sG=T$0+*m4)5pd zYwv^d7LnMUuE*--`B;C_PC9y)$fMGKaN;n%kRTs7^&>s|wo+>X{iOch%ycGi`z;O0 zw)q%QkKWSm#nLF*2cw#mJ;yxD z=UJMC)b%ct!lmR)yVGfLihN}b^UXOf+P(iPrz`s6C;2t&Yy-J?W>^F@5@+usc~{>L zo(}YeKTE^tMR}0PO=Sb?an&7t@ppVQLWLZ3MXrq}Hxy&TQt3fn(wX_l-}t&49rM{c z&{ziP3Pt7ai$JbZKD=O#whuYta7)3IBDrvcIZS8Bv62s+Ta$i3dIqnJ`Ym}sy^-EF z8eZg-Q^|2Jf80cN-TF&L#T!-)qEMxOItnJ`W4^DAG*06D$@lZLJyGy)Yry&6VzAnv=autuoLBu#hQxyIoU)lNIM_663l$BA15_OutH#Z7)`OIyvmXCu+ zT8MkQB59P#|1amOn|;ZFUd%`B06RHV@SAfY-w)#=abdgx1#9#0rkACd_LRwuFW$J6 z7KxZ(1MfBTC$?)L(`y&W=7XHi2S;I4fdLku^H4OVv7FdZBs0tVAjgWYS8oHF?jq+t z+lF&n)ECH(^B0L-Oml1D%SYn9x>(Wuuu}YB1q-(E*7b#&c%+)IR-A z#DKP0nC@Z1ME`g?haC~~Efl{jG#Hbag-zxPud5g0q&Aw7(&|Cbx8^x0j4Q*itB2)TReB5?hXO0f50Vd! zIaY?6iw?-|drpYA4a27%8vG`YwuC%ah1G||u+tHj>V;y<2@QVm-1^{7@=6us=~3nX zYh);HNAUGMMqg7oh1bYmv2wkfBiarK#rUTh`i016IVrqs*2c-Iy3BSO913?nPksMv zI*r(OTP|J}+-Dy51p4Ew$!VU=f?s{^0s6+Rd2F_=W?Q-TacjxO^g*nu#$l0Z7u$%m* zntW(m=9oLUJ7etj5NH=C!m5<-p8|eAbCaieI3kSP=(@ieoLi8^GiHTX*D0}b`jR6K z_yyC=pg~9Sq$NQn6Z8+D*D~RN3~o)QSZWwz$%`eEQ@cE$ zx#5H8I2&n?Y06+MDo4NM)-3e!p;yijCqB%?nmL&~+VVuSh{?qL-h7^l1o;-`jFzi; zwiKF(nOm~3W|Rqy+8&bE-yP7ma2a+D(%}5$Y>dh_;ZM(4d34Vn*XdjQ<;i@~{^Z~q zD!j4}kW+h2zAru)#n%&2I-B|FCKDV69+p)x_E>)+6pbp7m*M!WpJGDGLmIiv|F1SP z7$??iu;d~+TyGOBYH20yIdj;D2BYW~$JfU!Slutfr6&i)aL^H1_kuCaQ;V&MnOI3) z&+O?T>GsVLrad8OI7EvYO|$U#dnvwqCrAf!iwj*s@Qv4bTTm9_N7KhQE>>=nKegBp zf~DUR@gO-1ip3_xlh^B4n|ZO_L&@zV;#cD=7>s2YZ5=PwD?4N8xG=J=TIBDizwciY z4*%LOW&FJby+YxaszvX)%#ojFf>rWCxn7HIkLjV9mO!rXStffsO*m*BCy6tdM_e-m zU&(dW^&q2D)x`V@t(;D9!qNVrsGUK+lJnTCg(h50jg_nR%s5LAMaMx}OmX7-nY>VvU-RMKS6^g)H8a&*a1%L9+A0x?J_i) z&nyGZOAaSYXgVWK#&|j6o@WSD++Pfu#X3?V^JG@XNif0b9JrWtZ|N~ z<>8_F+mFpWl2^L$)|9O|E{@<7D^>tI4cxGi}dk$_=&SPZUE04nL9jPAYt8`oK zT27zvs-5TZz+GM43bm<2lB#-cHM~vzJ9U9RA)t}xd|3|Np7N_DR?txBD1SZPZ&CIo^7ccu~>m+goSx;sTeTrsX;_gxTFow14IZ0wu zGf6Cl$IG$DTImx*=OXhIs--1KC^N%5)r*s_RkYH&k%s4m8rfKxJ+76tvM^99Gh#K; zGDsuGPbA5f1g&g1mMAXE;^j^St=P6pl8j7^Y@W{E_D{~tO>sdJa*OrZkAKyR{rBr# zkj}mLmnEzvkD*J!$_?coDe-i&8|-XS;C$0+f2Gg-u5%#psML=?xakJ1GW zt(o0)TnRfD@`{t4k>skRv(pt;^^|0Nlu&SNeyqzq{R=XUN;ecJmFOm}FiQ_djSKYW z{2PYqDdDKf+Vj^XVfZ^J9AjpO!{JFdtnP(jYQqRDUmK2Us&FKC3x`Kw7@q771Ddi& z{|$Wsox&mW!qER79Xrc-uKgqoy>F9Ubfw?megqyK=b1`KDECpURZA%1U-At6Rv0`R z@f>_*IQ|~v&)KoYvxx3t)~9Ro3_P+5dr5Q2AdaSQN5eHu4>}mnYO$#=GoJc0n~P`X z^(}Zt#Pvx3Hmq@6X5INGzsI0uEnSD|adi0{WHw+HYY@wM&bE{8g89sd+NQ-3GaY=& zSl3>|IycYcezN{ONR@=wQCe7w4(s_d4g+*(xHkvO`sZNI{%knCqI=OU2NPLuK7K0) zT?)zY^L%Uu|LsL~Hp<DWXL38%(jy%Ua>OAHT+VFg5IcwgVoaId8 z7IKC@m%BUMB=(?-#N|55!AMt$Z_`nFpK2iuVp_?-vvkV6Xeo^%Tg!yu_OfoOgR~gt zB6Ci+m5c0E?`-Zacjq>jRyJ-j=#ah4o@y_Bf3au$gsZ$OD#Tfyoqih8>ZOGJO>9E`-VBx3zagw3EeST1>D(tUvnW{DWlC0>7YPsC2I}$S&JQ` zK*)5H9DPO)&}wE27MtOG0|m1mOJ(phlbF*3ciLWo#9yUiWdG?_{@a9qm{09Zw|zqe z%1<;&6R^ksAzeZWGyIG+$Aozb#N^Wv)1yS9hMHvc7UmT$qC;*^sVEnyuEnX{V;Q?3T=C;kUg7uLzRc3 zIK>bDcJ)VX7rGvKu086P9|k6JZ|~1~_HsXX-ws6T7k?ax2e3^u0xMkNlhG(<@k?=Q)0D z?&TD3xZiz2zv3h^QX|y#_ebM-fAR#{Xhd16(P@|(!o5p&1-cif(P3YXE`zCb-1Biq zyQ^`Fwd_Isvwn^m<}1lH)~7c}rN-`@D8xNXN4X%@{dr!}D}-*vII;-O$X)#;mspid z0RMgCi*)RKZonYcd`8*uTzpgpwujUGb|D=XSmU^vl@8;PbTkSjJMh|o$+I$$&+q$| z!QS0W12eH%2YzWll@Bw{>)V$xlcFZ)0hJG1u+*_V`NVOJ#g2^ zUfrSB=N7$k4UMRGg}H!}3gE`aue#BQ39ad8s$M{@*oZJCAD>R5mD`Ls8bo*8XZn(+ zGSh1Sb13J#%d!p*a`Kvkv>DMtEbSd-SZ#N?VCEowPV)V~#!ZIbcb9}%XZiY;u7wNq z7cFv?F3J|tu(_RFZQ4e9Pj!<8{hZ|l$CP1~oxFaol&W2vr9(|;ahPi_A7?0Kev$L=}SLUQw3cb3Jf1pA{Ip) z6Dv(Jb8o3kcPoeO26GH#9qoQU1=cK~YimKNtfY&v*FAC&niBcYg*ojH6xbG3Dsy_% zx7dU($9U#@)+m$J)k`HhvW)%F^r~{4MUrFOYDGTsrUDC2mP-9@3M}qzhT50SFzI5M zR3+~_F;|7%WK5nPQNiQ03Qa38OPZW-UHD4XL??*<(v`&HQgNQIr10+GYQ?uT&! zzBp_2M*_!W(18HdT;hvCgH+5C-GQI0I8F@odc0x2dJ8prsoBSwL1$^tXdH85?&cWg z%k|+HSf^(8E3-HG^&r;q?rvgkSFjq(`||4?Hzzui8SbsdOfUM!mXJSgy926L>i^aH zY}V2<#X4mF+G>2_`E%qDj=33X%nzn-^$>j~f#g~^2CF2Ji7=33Nio21Ivr!%vmd!@ z1}3>>pud)^@ZNNUm8Rol_Y5@mrHdtuW05tw4F3$&H>Vr5)PR?J$W&Y*<5)2R>Mi78 zhNfeXDFatob4`!o82yxn!?QDxXG@<8$LOLW^2DrRt!}63=~%< zM>vx??O*ay`8hqOkBxYCm#lB55zWm$A=sAgQvOl@B`-{Ohu0V8v%WE6D%rz~cVvFa zGX`20U|N6?(I;73Eihu#KzdPGJ1oz!7qr%hv48S$ZMPBUjr6hgp#OvCTz^vNg&b)_ zV;_1SryEgloD6aT*_6RgJk))!>CHw?*N?mI=9zf6xqh_SmefftKXp!<)HC&NVI}?T zRv$gRsy_2@+g!`@Lv9;=pTt3)i~i=O-b?J_@gh0hb6%rWo|&o^`q1sc`U?ZDd!+5@ zkk)JAVb2i7L(lp@CV4jf)+lYV$7OxrXRr1Br=+I_S8tdWS6R`mSz8zVz*Za2+n(8? zKjPOQZPRRhs)Zp@mgI8pzV4{ZpG`&)%$SbQ$di*?yS3Cvvz0nwAD`q}GY|5HPO3hp zr(?55#?RA;{S0!50~2N4jU=(uYUTE=MA`j5QFh!k$+$487>MxWlZ;Pf9#{ro@Qx%*wj2 zL}TuUD^796f|{;SDqIoT(FF++E_mjrL>TLAJJ-1IUO_ki6D6}3*b~EEmtzf`F<=Mt z;fQ$8z35?bB1ln3`+Qa^aY>iH}(!3HNxuHGHuSl|G5Z#KQRe2* zsYkYv_0y!6>~UE}ZgDf$f?LVEaQ!&*64#F8fqMC5;M z!i>r#n@KnKu5A2XLI-#ezt6~Zr%w*^q3H?vK-V{WYSb0zz~Q=bku%qhSN|{1cz>Of zT**;N#{#9?%yf|c1+8V_eizB_W`?IX&9Qlvf_V#Ei#eJ>ZBSqb=ibb_Dp=kLz||bC zp%$|*V~q+K$LROF#yK!5ntAbDPjKDxAv79Wd9VMqH62-;lfpPxZSKS@NT+nPa^hUW zb9C3?biBs#p4`QV49*wB>1>KyEhWI)MLz#>laKpaN!>PNF3ylgdqv(p#|$Tn znYY-8a7cKdQd71f8dGO;9BfKWl(YU6yID0B3o}R`%XeEV?ZREvC zdL#4A@TH3xmdr89nQ81Ja5aOwy*WIu(mlxQV@F=bdQc#qr3B*Mk3ekgxC2(_=m7SK zM&52ZlYT{Gur3;j-^mrkq+==P;nk~{i}{TAf!XPp;bp|kLv%$)v&Z6M0cLQ0v%!`w zTU`tJe#A{C%xWchciT#hg3A5*9fxuFV$rFc&`}F9B!_;%&s%9^I|$Q!ht`$XpyOz)QL{-OrPCILp7&Mg3`ji*)bmE~g7yi?Y;FieJ0Rr^f6p>QoNBcbK84 zg&Drzq5t`V8S2u5SZRw2B{%)aSqCCvgFnuX48)O%bV#sn=NuW0hUa0#M5D;5d|Y0Dfwy=c(G;Na#P+f|z9n$o|6eE@-jK1@>Odqx_~snc5j6#?omu zDI8Bc$)g2?zI)_gxo`a^2#ll zf72|7KTD?Ipu(&7BYLeylWWXYcvalSe9W;&q{WUTDdzpG`x>3hNlX!|={k8hm06um zuBcYq4Gwi%qQ-3{j`_O4+AIRjY2hg4JZm;E93{`g5Wx90@0Jc7(>Qnb)?%@a`)8h& zPvbtkm~)eFL^hnKlG__YU*y?rIzVzUg$&~cvMCeu6kcz}Fk3m73?ay)bx4t|r*-1i zBS}`?(Mh>FN92nq8IcfI)c;LJWtS_4v~|VLI9Ci!cfsWY5r_{8M=f5X6nzIqb({u6iDd){SWG(6TJ8(kbRdo}4 z@yTLz9gZ+FkfS;M&2Awk(T@1U^J2WRJmf_G&fv-=#E}J z+}Mx8JZ|zIhR)2T91+1B8=i**M&NdNzD~TS1oucnxSl+{O%nD`;A@t}*XS$f=9FBt zypW4Nr?PQ#UN-8|4cUi$!#r}0+YJh@>*OCcpC$Wgqm|#+j!Tkjl5D4+xx=Icd9glO zyqhtnoNP+mS~uKY=!So`@eJpS3oLk^(w_YSDZIyyNQ}UZjBxfoGxLIHA!l#WiMWSc zWw|88{9+F^&v(Cm&jt?j%%NN^Qh1JVlJ}td-E%N{Ed7<_QsPc2yy9aOUaAt-7Q&bl zR-XK6ShAcLMn`lHoeaLBm38+uvLCK!`G}6ub#555$`z}x9njb&9ibvUd($d)e5(k@u?# zW?tiY9$(m+Oi?X`*Y+!XFKt$M1=MpD#Yk6aUX#6Ht6ZgT)s}K^OABd#&m&^Y@JI+Sz89T~a31)BN$mgFTS90ufr5nGlct@oOi~ z5IU>L`m^7Vd-aOn$)i9My*_lctDNiI zR%(1EG>C7w$ST&h68S93HPWzN2Da-WCFWTsUB!n+1wGS80I{`H5s zYamRARd}#58gF~4F_<6U^Sv|wU*?0KBIEdmy`WARDEh?y%On{KFcpHks_E*WPxCRI)RsI0N}x-}PL23&JeNsG zCqI-9Kd*E+?%`Pt*Jb8>50^h+L?rKDyJ{C;(|x{|>lI+aORbc?&`5V{jVz{re)fc; z@`l+(*87xj+u{n(a2HHTChJWOY;ZXxrgJ{D;`)C%KRPXn!0!|E4{}ai!*kLIZ=Tma zX74%AUB6lCa5qqgUfZ(BB;}yN=WHB5l7qF?=rO;OgU-_wUZwviyn+VuKDM5|+PR#I z__fnt62-DMxwxh}X`??b1ISv|o=6V?_be4TAKoyzBE*OD^uOH0Oms%UlL+Q9vKHzV zffM~X7jdufnERCW?mF}}@Hz0laoR5lv0SIuJfwq{F&n+x1eVr_!0HVVxIk9!W3~=K6PfdKi|5K~*jM$FuEsdt zPraD$lbMa9O7^zb$-zd>i@iBt_bpU-b>cn3K9k(}d$Mv}&AcpmU%j|8MSM$GyEv?q zfVW2^dt{1Svq_d_on7Enq(np>-OJxyvFVu`9CKaa?L?nIU^s?Mia@=%2y7o8fd&t` z7n_y@6YECW?|d$k=>o{qqRCM*mWy)mbZ#!j)?mN=Ccb8sa?tu}Haa~}ctzdf^&xBC zoqY=_oTs;}Qh2pEqLWI+8gZ+WBClWRm^q#zQMZ40XMkMU~bhfXJl;;h0;9&m-!w(U>%MN31O&voo>z1IxJSv6Un}~ zxV7{OyYlY^S_GBPg|RdXN4fqPk&^?%dHSk(PG7?J?%v1rj4Y!^liA?r4|z`=_kVfD zoZrplR^7i+bEOY%FQV@+m_4i=I0m~}%kJ<(X<6SFiGk!_5}6Zvf_cG%8_39Ee`R2- zFP&)Q_-3(>wG(rPM_S8p^-pR0=^s?gi^TBMH0*4Zk4csmGIDdVw9fTLxFhpYZ_?8j zNN?9(3kmZ3CDHf1@%Eo6G$XHfYh)hcE;p77^pvf;Ngv|fDArlh@OwCOevdVkt^vjJ zgL{er!y<9&mI0pD^yRg%67|GClDWzo<*Gy?x;DAXO8K}E(nvCxi>+4qz<&jK9GxDo z`Tg+^$UQOV^wbe=G^77+gtq~^$Y;e?Zz|=Q7E8CU{~)z;6x5cy*B$zZb{;l#F#eJG z?t`HyABCza<^{DTSEy(#R`i-3ddcS>&iv>#hT3L4$9iBb{zZReBsrspGota$j`Mm``pbG*$gVfvB)g6;e)Dmv^GvQE z`Jh`bti){d9~n;H-`|;$2zjqZx9fRWxyecbpZ}DpO?}X&Be^88jrNP?b63?F@+6m52NQ3$brfC{O3m_eXAP%R&Q!I_9C_rbcqEYOzcV`Ukn(N2Mxw zALjjJ{Qf4AdjGF1PV&KlKjhbVe;%2`$KTXg;9Mf<SMa`Tw0tes(8)j$;eu z`ILX~d3Gf9Mg0Hj^I%zIC7&A5*GBK2YsDyBYsS3k`pnx6qaX0nZ}Bhj1zJU+yj>c? z!}IZ}26Km_isfV{Urgy1i6K1=n3lsl?nVuz_6>4gV}0?MuWvRvzCB~}@Hf7$3|v?w zWhyVV<~8p;(e{4PC_gM{*h-rsZK?XDjh|^jjXy@I~FLkvQ@v z4eH+cxO}3a3{5PQYfF4EGk|_fGoG9N{D}H@tz_ldVrfr4@!JM+fBtE>A^G?+yp|Yt z{FT5F%-tT&9P<{;C8tkNd7+uyoc>qVSMY_!Xy%FEC(pYjA6GlrNPIPNltDg7;&r|< z&48AD$Wd;zlk%&J<@}d_5IiIbbA!|2q|U>nZ4D&qL5Wlv?+ukU3LTmoSeMDe*d|RS z$f8*EZoZh$@!Kqj84=_h^L#C(hD(u%i!c6d5{cKP^eVp1qvN-}^t|y)QqB#=d}S1x zuT8_({^SZH8%p!5^at?yS0J}&|1k~Amgk`?)J{&*XK-tSAG$q>g#T|n=4kU!(8faY zDlvzBhYzx5M8bnS;Fo#%@HRG;(f|CGm8E>Yb%;V8zFzwEeExGS#AP+d#U*d7{7BxJ zXUapSO;@ZW-M>iAR#8FA^YYI_ z_&9vM9D|$7<>F!)L2qfKO%(ntqi3)rA0^fnGMN11@9o|=dwe_8ybd)+v!8Gzxk7TX z#tJ^DG=TZ_k!h&kh<-_WAsh4guW0Fu)#O+=H=xh7=p)w6w3AuA|Hzp4%#Y^d|E|hB zkt2Cnyv;%uX-Z|=2wx0Y6p1kfk z0W-ak#c}cIS{gpw%*QZSYx#EUkIcT|4NLPVoV>#MZCM^JOll$l&V>@Q(Hk+LQP@ZB z_<`{wTqZXbed2HNnc#yD=g2QB(y(uAK7tb2Cq*8-a;XnG(%TDz9+SyY_Bv-HW%K^X zUHUgKa{hU3oyPModTHNUi_-K*GB%TkZOn`)8v`Dy@|kPgP@b>)EslI0$MAhv+|+=d zmds&~u#z#X8^!eV#gC~`n9uLO-6apR`m@&i{+IOo=8Z+uSyOZ;XPxsAIynbuGAWUCDgsm^gWu=ZN*& zLU7xP&g94}tRPo7h&?yI3hmJaVd#ELi~UWqFtohFYeJPc_6#^;|9|<{ZxZ3>%AS?0 zWtg`wR_e}TzH0C?7#zqq6=jkoD??@5y|Qkv1AaaUL7jh@yIPio6K$AzF_hfd0cY4H zEW^lr4Z7I#|5c7$q-VUGAlK>NITX?KnoYe-zu_ViE;czVbLu(Z(C9E!<$m`;a2EOv zHeuP~gJM&i{94x#^w9DQg&dz#Hxv6ZY0rDz;;O@kSFf=g1!obbzKP1d)IEIIlCYsxO~^ zK&*VH&(1S93|(t!;dC+^%O{yI>)~OsD|CVb*F75Hnsj3}-J~XDU5J&t^_|f_ektyn zCnE44@}6VpS-Vbe!!HN?qPNZ?Tm!cgS-AeO44*q3lB_f*oV~)Y?@Pp)Hd!d{Z^AA2 zL*lWE-br$x@8@Yym9LjW4}SgMLo(gyfIe=)Fb~jR!7ZLc)HEUDCcnSX8Sjn+qmr`* zq4k(A^t231hsDdpSO<)37mTZMTHNE~Z);>?AJ$>1HQxylw}P>W=Lyc2m{VNagjYH7 z;`zY=d98wR;I;;{$j$k#AP-o4K+;z`(0d(%G>rz94e7Z%RR-IDco~-G0Dp2@#vh3o zUyIK_yA0j?9FSSoP6&D)0*i_oEH0OY7gx&Ar_n)4ziE#fzI>m5X72WlOgw2=h6Yy; zNN67i3?(<(i|@Aw7R+IHRd~I3J|y*iIw2+{1ntQKdYxx3^P4hksvaxd?CAlt3qjKn zS{xAi@-CTR;_IlPk8cFI)Sw0$^!|~FnoY?6c0C~V-~=1nFgmdKzBOfH5&5+tulWBZ zKfAXu6#pDbgfscm!~-S_>2gpKsyJg&awx7;(2_04MD>{_%-eWSO7A#eX15S%wrR+& zko!w7Lx_<%&Nm#e(K!U&ZMA5|_f_qq9AD%;jakk(%ir5-EWNAz`o-xcY-aB8c=Era zINm*z6ET9krS<~|peL3ckv68_qw`?_HK z=Jl*tm3i^xNfYlMl*D`o6dw&m41aHredMOe! zVVO*iXZWNL6g^FZ9XZXScjRGP?w3Q~9nomnGTa}acgg`zU&lQUm4F_!bsY@fptd6l{L+sI3D+?_NhpWChs4-X!YwH+OC;l?ryBu}~u z^rfyc;l{{A0`izK;mn=q{N{0u*KMo`wwwp9Fh|=oF$8_BxM#e{@lsrdcXtm<`7aJg zOA5xqnau5NPQIS6%m1sNG2n_%s`k$@{jV)%`WJWd^{f7NNZXdUHPt3;yJyE6D?MY* zkJNX%ZyrRQQ?AStWzt4ow4zv66?FM_tnN3 zRvVOPI-Fj`d(OD2QsQis6S^;ULE>d+tiI&}aixQ2k&?a$7c60|`OGmFoFDHBKb|?w zy6A!iYn^eh8C^X)lsGQzi=4nS1WRWevv9%DfzF(7nIYKG6&rL)l*GE=^KCj`E71Kz z{#e^1j6K2h>s0?gXG489GdpMiIYgclwe22((yi<}y~rB1lD@^!JV&1uh7m0zurfEC zS)n{v;@NhM2Vqz`fDT61N#4E>L(>)P#k33OeLoa0`EmCcW?lRU{a>#AAAYVXA*X9g z-%l@Q4~B*#+?>7$J-v&E&k^zFFuob1nkj#1VVSo2Ba znfV0XoBcQ+SGmu%&|4ic=4z3%NsF<~bvWvvMcFi-^G{?QdN%Vcc$QRSGV=$I(76-A z$Ni>7PyZy8EYQ*Iz_Sb6BKgiC;>T&ENOCgph;${7yFa*4fNh%mI86N&IiA8_{Rc%?L?WMp!pA^jQQoz|qft*MD*<~gfO~$HqEM0Sh z&CuAk9A+OT%SHFfy-8(Kj=$ppf9_RlGZZA4WKLX(WNj`JnMs!;*~HD4RdCqHoF`iq z2DVVaHOP*;XH#mM63lgeddRsvwg6+djN9A`NP5Bhtcx`Sj%Kh zcOd_C_DAkqo{21rg83FQRT?r={?U*R^z2Whv*sc>s7v%C_|h+QRSi`T`NRZ%|5iGO zp0oaYhpvLx(U{2nPOCT3s9BqRZmd6SPN7q7N;IO2Sr<7T4f_;kReLks31T52IUdIrFa;7?=adUc*>2i0#QiJ~5#24+ADPOUDCKI`S@LFuRv$ z>ATW#$%3`&&l$LUjV#tTvXaUSSZ}A_;XLc-v8?MKNoTJz^ZfRwW6Xwpe0)sSi3~&| z)*~)>8j*j2%;A2z`p+0qJIIKx&FEJ;$7~6nr=%{)M?q)uSNDx%28?*c+SAC<^eVo~ zhvjRsk^C6X8q3GU1vqT^2_++q$UJJq*N_67QXBCzhOVgX%%5CGk6Z)RrmGg<@+Bi~ zA0lT^m7HXflN=oEEYq!=q*l0{+$(dC5sSzyj&PBlUF;<(hF*n(HlnZRBIA0xi3{0B zpX!b>&x_e#x7=lX2X}eX)lsVMwUtt9=0&@Fgw=9*q>zKKIvsB)=(%s-$Cez-M z2QD?qd)7U!c2J=nUb{)cS3X z(s~N$oyZukQQ*5?flCo|q;f3AeJqw)TgX7}HN&F?{QAFS96Kp6aY2bpsZu5_9TkXJ zMu(!OA3~4&p%KSd&T@YYTtwgLGk~!4^SK6|^xJ!k_$5p6eOO~J; zGtRd971SJS z&)=yq?wg8kMHM!(wzFb<0HR{m^mIhynkzHglgMoxAy?uXO&=v|KD)@4e2YeBj+Jd3 z7hiADlUkLWBLA&j2zyl>nC)IejcWgL95&!Mx*rYoPqM?eqj33K6xMx@!sIsm-s?PP z>dSHTiM76JSdnAr&oBC*;#eOWK$mG)I%2n_GmHDb^HTb&o~6^J zO+JU*$0mEa9+M4lvE`WL<1VU@f$;(9uH zWLfm5%roN94%S918PPq7=aTCRFeKlIrsN!_XXfKXPcpt0nN2p9-0#tR94jDC%&|55 zml6NoG2(s)j>(Qj9G^|DIGP#o>H?_$XIk!MmNbZ@*n)O znrE#39IpmG=0T3X*s;b7pQ~3%8(SHv4+=i$d-u%LFPmK_?c=Pl-jAMn?AHg(=@s9P#|O^(GjLH;dFkj%q+$^FwP zbH1^+v;L68bvDTApakiEP%me{>Sd^nQC_bzO4QZ^V)>|-pV4{=Wk0A-Mb5}n)=Sjo z1M-VGS-q4=vN=tO?OR=7ysE^9ROTGiQ{mBg@`^Fc&6=vh@)gc_FRtkLi1%`?N`y?H z2kfDWb08|{8mO@iN({(X;aNBC1<6KsJ?VmK@h%wj+=VVfH3mm=zd47TqeY2D1C@CB z&J~Y`tI4D*;TfXB%MBI0i?cE1V3uR+XL^$bIcbk4qS2a$gI(KbbcgPPaF|e=mnwV4mDtwj?iEg|jjVTIl$=TYj9o;r{PTK4(_q z*^A?S-I+h=rm|-y^k3`|nvMK-kbAjnK(`{!shIV+pTJod-j_#^QykNj`D%Fv)N025 z-8Am)jJrqrSXYzN)oRrnlNjkv8cq7J#n7d@E;JH&|W6Wnh;qnGi9 z5sObUzq&VBN3w()*!%PDYsRm}tR2mv!z_S%H8b~x-kd}EV#b!w%!W3YG4dU2IkT9f zzLrs>z%H^ z9x?ZUL4&gX$4k1}XCcLx-kCzy@3zrFL%;rizj{n|lTn5?^4DRdM25ANs~ua(KgCL^ zFt8A=9lx^! z5qgc;q1J)u=^BVb%XBE$gPy;IQ5b0zjg^XMRJf)?nBoE&3?o}GEgj`D(#Z~{BXv+Z z^iK*9{k8xPO39~iZ*kY04>dXNLBri7baHE16{M7)RZg-qUM&X(sN~eXQfb(Vd(?ld zvFpAy292Rt>K`j8&jn$zX)vyZ491+jbXfA2YA2bMjZtu{%=ct|6fE4^)oU4z{x8YU zlLr}6GaaY62ih8Kf?Fh+_J*A6IF}Fm7j%Ge1|y5t=IS*H;4_du!r`r?a~C&ptm`UU zSGvk|i@T&JsN{JHXBkdfWB}Ls*Ig}g!chU^cm=kO=6h0Ig9K~tUEA^XM3Q%yqd|BD za{b)*y=_UC@J$_ObGRn%Cf~^Q!Oi0WZabu-^&=BTpENNWoG#%f`RF~j0Qfy^QXtmb=!j^4A!(q+jFSp?aw-X-YSGJ9<7JaeqIrOzf5P zDs#<#e1Lm`7-miP48X#4vPF?PgdEo~k2DH*8%CkkMe-oa`TDM7rwuHm~9__}tG zi><_cawGCPBTSgmEgd8IUYWT!9;!DXCWLH%33I#d=A+N+JXF}jp69Fr+{{Rn1Eq;F znT*5cZ3Zd&dPLNVjM8^BvyhDJnTL|u+p9!VUQ9KpE@OE3H z@ZLr@<06ff_r->EDCv`=+L%PSIWJL8lASl)KPW~rEBC6?jWk=0e9k%6)T&Y1K@C0Y z0Jq4ctlU8-V?23>y5ZR3!+ZD`@*vax&&*#3a%qEWBx3t*Bc9Nm)S)Yx>DVlEsFRIu zH#pPREE|{Kv!}1J^1ej=%zU1V!7zn)!aRkyYrewU!GW`*@rT6R>yX%Yp~nEk@*@IX47?!3*$$9nYsHO|Jkwe-}wXXD^PdcU41yz}X?WC!_>x0?^~Hqahfk<*#cwn-Gp?-NO*uk*tgZ>m_{8u2xUPnd5wqSR1)EhmN#;%mSLttkum~$oycY z=OG)F-e=;rOmonHR3t!RF@%k>lP@=EP2lZxCVphPWm_ms-vW>&cU zq=b2D^!#nI!q_dG?<~}yN?m3&EDgf)8Dt1glHYqb7{vuTSa=Qm+%$?a3_A2sM8T#v z-M*P*DVxxFYe)7 z1ATv;p3@ttF2JX7H)(c{{5yG;(SN(hn3l{oaCeoR8jEb*NalS3vrNa9%9`y8c=}r; zbV>jo{|dmWZGkY+Wm)4z0Intk;^BuVyloW)JksGe@4IU7{W?*P_huhW=zQ9Q`uvRc zaGx=}UpkJgONXLb0ZhCnseP7=WgPEWYUSfyf3B&G+llocr5u0kB-husk;<>#r5=5j z$2KeA_<{ANZ&s*lqN|#-dQS}&$>V#`Fk3^GtG(<2c?cMsf|k{g&&)1ZG>1h3{~bbrbfmgU9Bh=gE9T^PXowNAru>dP9}A z^3u~y#yNUO@|L!8X1SBRT<9nvKP?i${m!~!);NB?9GWVu@usUa+TYTk`Gg?+J0%eA zCpFm2TGgzh8XVrjd(L6>LGRbWzGoEb2hs=4HQs8v3CnqZ*_L$a>oVL3~e{Gin;{6)rl-U}5r zjZ&lM02NwUxiRxR97kixmp5i^aG4e@D*ne1@|sO{*>SEBH@b3u+$IsDUh=%3XT;D` zbd%4d>#sZKbn?xpSw0K1+AzmvBG-xcblH*rntoK_ZCS7I-o1t1+NFsyfcIZN4jQGU zjb1KKX6`hv%=21sK7jqEuTz<==b^+y*2mv*O26^^xc?<$0ri8X?!9+&L)G-_4DcXER5z}{jDww9s6g)Z(}xWE#&aYqurmW@K%vM z-(A(p`(JYBduGsAyNdkc3T8KLOO#!A66IC@L}{4F*FYaYT322N&nV$^hS}G=Mi1Xa zF3udz<3x*5S-fBJX1|@D;X8GV@F_81@e=y}9E{koAQ2B=aNdgjJ(U!*7`yQ|-f%t`8$$%loZgVeljm?>SV9jjm+hIrr6l968hxMjXG* z8u_9`1TM)&RDL#W`eq^IDw#cgR(1uP->1uW=u5g8L+OKVLhtcoUayn6&W}%&|1$LE zJN?Hn9unW0NwUR5FCW*s;L1TI4s=%I9Pc65^;Kdl_d%Cd@n`#L5nCJvtH0<;s2Gmn z1GIP;ZA6l9BIfTkVC`1khefciZ)QC|k9pTu$iJ@6!W1j^%9Lh=`(?o;k1TAo!g~p4 zChW4A)5y;TaAe4QER_g`zIbBkMhuceGBRG<+sd+AA-rVta+Y>+K2OCU)VtE78XnS2R}lk-2BzwFJNR)r3|52eBBGIPKm z+0ai?ESnnnqVu%C)eW*oZHCDrV zdnDAXI}ZI$Pvt%*nNg)sy!tRFdSWCjY7;(x%)#V7_VSv%gR zX(yL#f5{_0|Ndr?Sp1YfSCxx>-5QAU2{}Xu=5a6KziUb=c08s>?_Ya)T)RY4FZ!S~ zmA-N@%)#a+@Z%%U6DS-rjZ!Q=Qmx<#S#ZcIkl)rGN1UO_WDSC`$$ja*<4Jo z*-+-4E0Spye6ehEBtksX(2_jkGKZ!zZ|hHqXAaPP<^tQMry*e(dC44Gxp9o=#TP%M z&Sn3kRvJ?I_+|?mi@73?+h|{W^WxqrCKVnxbFpDabLrqkj+pOrmlYAPI+}{PzjINm zFS*Xmzog_7=j5kG;>G1u)Nsnf^x943#pFU6MgFwpKqUP5KJQzQ$LlryedT`0&Gr0T zsz>6uGi$bUSkvTQOF6h$!ruDhY(De5`S@Q4d3;uGEH&eQOV(IFv^Fy@yG}AroAF}X>A8uNhm++Ih*yqU+zjKiK!{{6BOinW@65~>tlini_w&R+}ZE}v~>B0Q* zJ_6fT(i_2_>(r>pV63jvWRe`3ia7D0(FCl7D<^D^Eg7C6e{>uVE1|^Z3klVZK$D z#!{MDEX$wyyM*1nGYVu<7Z+HUT$wHhtws~y}myV z?T*0EEr}}63x71=an*Z!D$d37b9Z-;ln+0p?NUDfY`*@5Y4oD!VwW_PE`5rn#TND! z>as^hUVFk`=0PX$-)sF#ig-W&E12iw)-<>`&*NNTeR<(mD2I5y`0#js&(Hn#2mV}J zTZvg!B)8aq=u)0P_m5PRz05(Kke6RA+NxOGc-)@ib#H+kuZJhd54LJ5jqJ!F(zk1~KLRr{$zz_$h0D0>Fdj?Bfehs|W?ni45@)fZ8r5lHo;uQnnN zvA-J25BD3k-OYzD}f#=r$2GU#eQ~YcD z;o4I2*AwV1*_?~hpX|i(=1-aH;g9MMBQRk$=c+=;vuh8?NqP?#8kz6e&ww7}$mTZZ zzGTimsmodUaTP+bkoS07N;C0fH+i?Zu~Ib31y7m;dN8a;GbegfCO&7EA@l^F zXRb5i6k+(-jXA151pjcsgy+GmmDBkYnhB5X16U~tzu>2FK4=8L-5c01SGq0-?!9)%75>b&aCnE8x;(fUIx_RUb%UB z@?2wM!kjXFOw$^YwxR+=?-y-BspIKOh%2n0eE4 znR&(It$^OcYE>*yk=wdo=*L2##d&7egw#OMGgUR1%^*9zzr&di1 z=Gg2PUp|k=z%cCO=R41fd*$aA#5|7?|G&w3#Rucsk_4>0Y{s+z3p(tHmFaHI_;*kU zF7bJ`#%H2zEIpDn<7NE6u4t?aLBJ0^Uhw0`G?56opd6@y%dUF z^oRQKbF8EAR#uJY94)!sBzpIn8<^2;#;x`i^mdPz*T-Fv+J(Nw7J6JEx4ZXK8E`&U z>e2J)Tss6a4klnX^Q`Ss%JB6ouS=U;G4=&LssRREI7#1PJoAW|y*ufl6MR#H=|W3D zS1+D-!DUz!y-%*VJ7FGw?(?ejtDeY2b0-U8-D0KjpGquP5C#u>1Ltot;dqC+*s(EE zJIDn??gV4ZU_E@-WMZ}}Ki})I(y56HKDmUV$qe?NT4eJ6vkWa??w3u>AAf#21Xs(E zJL2`Kp1s2RNU2^X9d|}&MJQIx)??hn3~UH3L(!~Qsn*67+v$EAcSVoV(HY3U#(!7H zemTbL?fV@ec<9G`_8%EIb)yVftM|!8xMC#p$6Jrp!!DY&;zPVH4dr!mC3$UnOY2rP zpvi|!tmNw%&GXB$+6jy3g`@=@BW7k|1?R(NCd5i&XBTw18G_$DA6vCEV-Y{EW;q9B zz)p|C@od~EH6p{s+jOGzh)n)$OcEpT2GBMa6!;*^d#-Hr5U zdnA*6vog+x9FXH4E@(C-6w&RN+ukP=z3W&|P)#pS$2&tanY^=?9+49{<2TPj|9hMy z)#Ld>-uchYdemyp8UjDxz*GCBksZWlsZb}Gt^L#h` z%j@l;|Nnl*cZMn{o10jte0jGv#k%RT z_fig8_42BFJ1FJeoXcI@L$;@EdDq^vC^J6gervtw;^%$6+IQ%eQs@3)uNM^>ru_V) zlb6#N-(=6X1{w4&QA(M`^o-2ynN|jQI?E{b?UUrrn*?zxV1GH;AfHN^2Uzux4_mIsMEP*Q#(XalQ({-91t7kU*E%RK_;dK}s zriA0>N#+Bx-q2)gIKp|jTXhb!s*N5 ztmR}a))&(Q%zBc`$S^D&5r)a5v{=wD47FKHiJl&cwXCIhj?iLHKP_Ihp=;-K7<#qV zV)T)4{O&DTZi2=vf88O+J{hd4YOz8&(diPi>VbA){ z=SJw966t;;%gA-M5&vAuI43%ab+9I69dFVBQPGH4KlV$0WaAa<8DFxQ9msk{1^%kl zpT3dYWMN{Y84oVfAv-J!$65Pm_R|cnT-Nl*lTGB~ zi(<`KzTAw7EwiARLw^r@*0Ke#5iha$=+v_UHbV!!Ju^d5RT2Ot3;@ zw-P!1MgiSfiyW{ml}hwMdL5;Uagzd{uCTA$!U|hcm_xn6B15VwkWn=VHt#h!`Ba0Q z8V#Pe34(Xz5Y!m z-YEz{Z#3|3Our&CrGnGg$6XnPkPT6|k`RRkI=U3Uv9DrBZ=xz1yAH6oQOMk>iL9G< z(V^P~9lC@@p<)E{6&;uz_>S2Q<8+w3kvVyNna8w@xz+3u?`WsPQWv@#mymrdBG<+G z|JP7yY2V@ype;<^_9>t>n=Hb$@tp}ZpjoHJAFkv!#0t4HdFazmG|6xLx zcIh}-kcM&W7ZkN;PySgNnmr*?)iWL5@5p8yp<`$wxvCE)=3bfbVZ8~_wJsoSD0|~m zO&D{M^NZut@Ga4V2j+B~KV?F(oe94ius`zBgcu85a}Lb+x|N3er`fmposUV^*h4C% zFOI$R!%dh6eVzC72lM~uf;j#?4`Y(pYrjffk##F$C;AlstI7Mbe_>$XqA&e%&U7)V z^3ivCKK3jkuXw!xb!*dUF*G03+55S@njVR9WGY6}B^Qy8Ug`o&>YI<#{N8`AruOW~ zto)+@<&NiJ!futQ_BzSG^j^gLc9u<9DhW3@OY}NdIpE_aB?&HasbM=Y7CFgnty&PvZv%Y2@uJi$Z(tH*8u3}zScA13o|5a!6 zYvwI1X20s^Oa<1oS0H%46_$6U-;{o$Q@u+iH`pTk-dIE%Q!0wn7OBL?_%tn*@3*b6 zvX>Q>9xss{SIQ*%yaGdcKK8B349U?7Jc;M?6)A9j1KlG-t#GoZ0(F*IHvupo8B9Jh5VJ37pjzjT*|E%^?nmFm z;2@NY*WgAt{ii`1_?rSSWJw_A-`3!EQUDBx0+{O;fPF*#5zsggaa)<&wo8MR`^YZZ z@%hLpZ?z4??`Y3FysQ|Fmb&(GVeGle|WVP>T$)JkTiOhp|w9A%b;o;|e+ z%yPe|gZ`=x?b}2l<9;Me^`cSaqeJ*#WPYH7$2=WO3(3>Oq~r8h6GBF?M>*Yu{2A%! z`S%6P{lwYo?diDPAsuB8O^7(dj4&q?de%t)A7lJr09{^P({b@TYu<-AKl;Ulra5GO zU!Zmv$5bBwJIERG{74<2|G&Ou(q-m(?8!$1{#wa%?)1QXY^g)mMwm5yDi6ySGBdh> zv!}?16>H(g19@((qPy!B*+&yIOC0Gx&Ckbu2l9lrziIQm(u%_FOY+o99Wx2Ct~yHmUj_ z`%_LdOiIb^_d2=Ck1Jm2dNt+TS%*~b<$tD3`>aUW&}dn*-I`@xFNPgVQFklnHFwn- zFUy>yls!xQy)wI7d#-q>PX4xHYI37fjk@mFBze~H{p__r|BhG5Kvl}V-)B9yG~RV~ zXVC^Pd+WbF>rOSwc!fb~=Ou_^wo!I1NR;vPZIwHjDF5_Ll6{;{sqC2`mOBR7RTM9M zJPq<}p;5kYe$m&KKCaJ3xx*aI1yd6xIsSmuJwTUt$zd@xFv|NodWm^%l+z&zGWBVq z+~~`B79_~Iq9n1LGsyCviSp+$gX}q%AQQ(O6xZZLdCPs?k>~8!_2qu8xe}G8st^{a zMlFjH2QRo{{XjLWGn5D&LDuj#nZzf|&#I(?pD$-#4l7YacIEH&bar1#coQ{NH>dC9EPqZr74p?8>};*VnKHV(zq#VjbUx=l zoO3y*Mc*;>)(@gXt6ey%wFrl%Rv5|$(qVOz`$O&*1MbjaHCPM7)iC^g8OrSVFsQh1 z)K1f4#9d~c{RlzD8DZGLz2ErtT4ZaqnD8+SEMLISS>%6${Ba?XVkP*B08_C)l z5%%7IH~vO!`itzzNxJ^6j94|D+~Wcxrg9&-l7Hu=ZxTu`(jT?ifU*2KVx0j#JGq}+ zOGf22IZ2CwjI;s9SG*SuGU5dHr+Y>uV$g0QezE>`w@ViLyWE>C$wD*7Y^+PoLZQjb z*UEiiWpartSyv$Ia_tTGfRo7_mY8wqMHWP|5cn7W>}V$LwB~HgM>7sj%tHJge!mr2 zp-k>Ie{=3-a2A@^F=IV{#@M1PG*yykJVf_nlPq|w&c?=}%&OxavYA5`qF599e|g5) zg(`8=w2%)&oMa{$xxbGq<;OF%j9X=qijGzYx?+X#hEmzsfvjFj1y1}7pf^N=KD`1_ zi5!Lu4MhIufd6G;E}tI7S$ED+T&GvMZxnQMqo6&=IR$UJD{iD=OSTDh=Ckic9xP!% z0Svr`?7p3cVY|4V^LkOWfHMjY=-Bdd6zlO$lKg|c{L^mIca58z;C{|nS|-U8$m{L4 z!jR<(l(SXf__F}qIzlGCEB9Zs2V?bYx_n3YBYmt6yX!_{u8JP(>d~<69EE-S_1|@O zYM=?f9+=QXPcL-ebaebD9ao}0pj(FmJeosBt|PC5L&zAsE5P;5ZZe6^@^#FlTu|gJ z>DFyzxLs@cx$w8VtxzhxZwnjUYTAVe>t zmv;#{`DRhbc}E6gvJRj6(ZkJs)``&f#@c~MSbF)GfQIS!u`2c7PHp64T+pVcp3!xMTIAhjPE_`@z@o7qBo_jeKB{*E#~&|R*jDrM-4QaRtB zUbF^Q_~#n;11}XYv%Y^YIRL#62EcAe5PlEf`}1%xvTp^Ty>%3vx6_3@NQd&?+{at}CWeHu0|G~vL2bkyS7Hi@jtH2SS-d-HginUBV`$i{=SEM$2e%ypB~%i4)k z+txD8(^2jz$j)?gmDeR!*d3w3*ah^C>J;$c@w9?pPo{@`4(E(Ee$}8(@4+Z(O`ql^ z&Q$O->KD!RpZjWOuI1}z>rk^=6gto1esz}#x>o7f%Ht@i(1bUyIYYqL5`Hlc@-Yuz zrjV=DGDE5;56xE7IQN?3Ji;{RP{5{B&f72rJWf(Rt<@NPEXS@GM#C_KIJ6R2=$-LK#_|PZ$6MOCrj|}2IgLqQMpuu8IaeRUoa&bz9SUg z_0B20dyP?e-@2jj_8?zy{}OYL@(;=Oaz=X5jWWwVQL1X_vfONx;?}NcJ5h;Q^jBWu zeCWDfD*6SvDaW-jD!@}&D zE&QAwu?`YPH*rsLpIp1%vMyNa$oGUy(crdOe)N;#9| z#vBU|Dfrb^W_p&%urt5qv)UqedHtC=og6&ZjX?+fG2(ato}SVmCxdH6C|$=vye^t` zI6q&9*tO~@oWn9}^2jR$Ne@t4S!>?|1+5ZuZiVHcDHJR%LuZLT2o3Lh9I$j)0<^GZP zEM^m`nM}xBKqjssImSX}aJv_vbW;H;Jj%z${B|-iw50@EwGnl1&IjypmB#noq+$l= zCcaoB;U4EzYtTLT&?29PDexdO2pO6{OiBvGx5Y!?N*=XqX#n}}NSy!0dPVIhI5mvs zJa829Ogc0#HNkra-DBI+@N9+&SB98SnXj?oXL9eq@)%*rdyVE&InHu7 zrG?lZa^^m$jr5J8r_n|wEjwDIC+Ga;wzfj|RAzpdtl+kQv$dW)^(oE?aQ&K|lLp0N6K1VQM>f~@N+D-Ye? zlCSxZPwzxN0>e0$S(S5S9bDwcS=I$SRdne%N!=GtV))Tg4pn8A3Gc^G6|+wE-69QQ z%4Coyvlbo%;ZZjY?#>LvFfCtGrUnBiXmIWadCF^CPX|Py+$kNLnn$4v?@d4QKJa5j z6J8xjL-7*2vwb;JIyxQgxYww1AP;fncuZHw$JZRrmhC6oI6huFbxoA`enzQN!p!?* zy_Ci#N=|jo&~H;gUq=nkAu7aGAOki|iSKS&{861VO&MBr*g@vJGz{b4hv47qWR=fy zCTIrdhHSVOSJ3;%{qyzqX4s!M zZzAjc%^(Yo7^Qz@gY^H0HT3&QGO{R9<}FcT-aI7+4O7E3MG4ahI^(x-PHP{G|-s+WM zhDVCRJNK}{+jG9c`(c#A`_WEvX)AnVy9Ij1$ih@?<-P1!q6}@8C>^#P zmg@8|{J~zt;-g0Ca7=~26Y0=huY`Mq3O2vh7*pngjZ5er7{vJr+hs6tE&cFPi?MlO zoW0`fxM)ON+e9QcOoUG-W<6JB-qA+huXto(l$qSXE7q+G>5k`n^^NR(c!I*40x9q5 zQ}{kzBYV1lj$w^aRyZA$9Rm$Ac4@p^a56}PeVm`zpvI0KDwNA%rhvN}4r^4f=4UvX zeStO!VVvb+4`F#Y=bXY(E}K68mGmFJWM1O$L>%V5)x#pX_jx}zz919B=9>{a!;H?a zSwm0G!UBF?jk(8IOAeyt8in_1@~|zE6y9Fk2emv)7QZ6r6S(hCpU_L~y$ND9oH<&j z*+*HgLI&@Lmj}|RSzCo~PytqCVHapofoppgn{Z6o9}Xuwy0f=4uY4_M*;*RW@0Jnq zxdz-GO~!Gx8TC76;U+&fk13p4<8ht-gR^H|oDJy7wd(|5S7m;7Yw0?U{Qr2ye38G${K^ce2QMb`CZ z@_y3~amn<9pC29e1Ig$6 zHI;~nV%a^+2W_X3yX4PZPkyS_*!nV9e#xztJ{aRb&WOCyiB-99{?NX(9G%^p>zc&`ch7$R_!x!@-Be6W0v-+dx4Gd`@zxscd2Dbe7 z8Y7YYAqBUtf=1jb+o)Qfc|89~Nlnog{yn=feErAB|-~N})9A=7*DZkr+aMV(HI3 z{1sVWl)rz8h98QcrzI5+ zdEUKjSX;VQ{~^aNl2hY(dZrT3yCJ!VV19I!(L5e_9A@T4!lPd*UXRGd!MsNDeE%=$ z(uCKIk_gO6<@Eu%uwK?g2Czq$FwCDBrabSyr=o{TE;45~7n817!gE+t;rSRnG7U?g zkmt>@6VKve*)uo*6Bf}MSUC;Hp5W>%rR=HthbTl9L7ieMfOreV!xZaK~$uJOaXph&d+n2K?F z){^@-mtQS-zN`yCi)YMt9+`rwOLH-zc{9lwP%L*gGJpB+NGO9+;ocz+VJ&z(2N%jF z7eDOk9*MC@sm#zLCpe;!oUij+QWw+58WI7ACcNGrCvRxyEXN1_lJ2}OxOX@bnfCN| z@c3D4w38YBMKY6~N6n%LY*-+(_Q$xbkr*|L$NA1&&O6nWZ=(w3 zODlhLd$SeI2c)5259XdPbCC6~eoECCA9#^BJa#q}(Y(&bHEhoOy6+O}4dN;2WTstnC{#L9>a7lfP&#+t#boBnOa zgePU_dgOqN-O&=`tC9t1MQ&w2ePO@L(D_B2yddXtnmM7LR{=^1V^{DqH1F0v=@T2ho*}cFC zPy9on7-hg}TYA10mBFpfUa3vq=Nx@ub<&xOeJO+WZVN75ijz(J{*~>)=;UGG{()XI z@->Us#LM{(%%$xfhNouc+a_kh%ApMFr^U(FDo&i~3`OZVJpvzR&|j+XzDs_p?ksXu z?L!gY(|`?pyzfBraZ~q8{nO6KvI#}p>japlnQ<|l`M-MRQ!jOa+KKz$7YWQ1$Uujw z^cd2U_}1itZm0PC-t^f$ra!4SIiq>;(xSix%O3^fOpzWQlj()LWx>&7`^4{qGu~}s zw!#KI^UE?(y@J9!VqTmq^K!%l`ULw-B)@hu6FamPfc)v8GfwDVBN$sw>Tx zdi}=JgGql}@+k`roAyiHe$LpGO>Q*RfK$UV=-4mAmTIx0pXQ2V14D86sh&BK88|zJ zye&D$mGfNS(~WsjB?;)CVut$&3%u6GNxN3gi1!SEIhWo>9{(-LyY=qBU-I5MVm9-R zU$FPkWfA=c9q74J>Sb;&y^1<|=+2W*+?|2W#ieL)ley}<$gxTY+T7IR%=-+?>S)2w zeX;U#q7%k3S9$??&+8jFvwFO}7(&vz~NyHgkGWz~Ksluii7ivi55B0t#7-vS@U{nE0hGmfQ)q9S`L z?qbH>X=S)n6e|&JoH61E{fu|@7+RQtro+e^4&nL8dn+gMiS5{H*;y_VlgaaLRN# zL@RnTFUH5nz!+y#oD>2Zz7G|@XX17ly__R<%Vp-C`ArN(&x+(R-)7*CrOc5(v`?av zoKb#u2%H^QW8?eTqGuT%PD+plIv4C^j`??9$13xDi9Bk7P1yli8|sSRmSD~sGnY9y z6B*|$7;d*;YCAdO;NDPFU7$zErVQ4{$QM70lj@ExsMwR7CeJ(P8JRdo&e|;`PHe`y z;@>@?ND@7|?&0-qD7n|q2c*juSM=Qxj5$*cNN^;-yxxNDo%YK}cX}rWhG61#J;IJ= zaBkm%<|X^2i0A3ur6IUa-Y}pouiI)1o@&TxE_Eia5e&_9@|)YtIFMC_S$FqI#0^JG zzZi_sysj2bp;z=Eujhe#rA>|_W(*C%+EIF3<@@}!53eUj_RE7aE_mk?f+-*3IooB% z@d@-!wvCYohh4F97eC*n^gsU0z$JwR<;%y(Y0i#MA%{MpuO8YKnRI(tFrI!jkai|NTz6PTwuiJs-;wR4G`95u*_*fj_To!^w%k`)+%uIJ_ z8UE}MD~`O*&!(?)qm2PSczh0GZSlW;SZjqsad79Q=11y?@VEc_@BjY#|Nj1ef9Joy zTj$Gt&qv8(h5N}#Q#?G~S6BA5yEQU-!M%s)eWJ#t z4%N;`xn&GUQTMo#5*&O!*|~61$_l^9sfDk`rD%UAr98WFu4_5F$I0c^H1$07HYFwh zWB23_V{fF~O)l|jly=AS^hh_aO<&x-zK*(((&ypzGjPLvq-Eu@N3hE<7|0=+>T!a1v%e^6fBI3$bj86~(}y!>&1J@B?`C7ks6ty;=Koz#V*P$*RI|?1(!zW6obIPZ8=p}8vJZv*LoInG@{TUy_}exN#~QOIe&tg1#y;T( zabal78DPit%z2*9xlxxy)=rIBev5sTCPvKI&0bHw0RxwEwsax6#s~v!RxwLZXMj^% zGK*JgU#$_iHl-w9kS+*oPR-uOrRynV8Mq7ked{W~fmMTcUhkGpi4jMHcJO7hBoitBs7b zC}r#)9)d+}nD0?0v*}CRy3>m6ofTTJuQ;Hc6?T@lf^%xAjA3svO3$7HSYNMcjW0$E zIq=`o{Z*;NyII4bjRGM7)-Zllp#2vG=Qu6$h5d@#@nj$M7Mb+4R2&|#Uuh|o&txTM z`H-93!RO9VV8TQN4D5f`cA`&bY&rNhXMUp2ADw#yaW6qHTu~r`nX6R!l?K-n=v!p% z{Pi1p`k!cUne~T1KLo&sd{y1q^eD1cY`=hEBiBNl+Q0puEOHF$q35EFfaum?dHkV_ZcZa(MyKsc5Jz-?3@J)Ihu(xc#E7lozv zv6evH|;4e;HYq5Xql#czwSc4BGTgczLub^jf0rRFO(hp&M0o!|<=qP0lAel#vhFP{H ztlhKcGm|y@>3zsGPNqkPkH6ziUW?Ds}@`tR4G8f^gM)L$VY`B_E+-rF{pk4)YA*_ z;Z`1&-emUWI(j9J(E&N80FkrFK2D}@rw4oHITx9uhC+W?6L;HqK63@){*BWQ}(Z@yH{&trVkLI$}MlGLLwUPNFlv4gr zSBXzn%BY@BoXvI??HDK79_}Jd+BwMAMQ(DT#9o?oc9lo$(-oySiEoIb#LjS#4p&-> z-PiV#aJr4`dhRAWR=LZN55=(#7bg!KF_D=zd6pe;Nnj z_{9L`K9L>f_l`CSfTxOnM)eT*uG4V7QUfh}G9DW=Xl5OVHdY#}ZW4$wD*`cK3BRt& z^N#$(oI3Pku+J8uWG^z8wIc@&BqR_`#s=a|`2d_N7la23194(B|GvKlSE|q_Hb8?U zo0 znEOnJGd=nBUDn#jC5i|6$dCL!&&4>Nv!|LyVM!sqCEa=Mu=lv+OB7;Q$IB$gvNeQ% zH;L!vEczcy`SWmHERRnj??L_et;8J1=2y%msI^h<|F_jIUd^1Ne>v3BKjbgx2Y zk<9OR_6t*cr(+(^hr7GzYGhAyacDYbkblg&pN2he)A78X2?6Fbw97YP*PApL1DIzz zpFYP(IyhR=En~|bXlF9WuQ*rfV8Y=L`XD!^W6W4O(!LhpFLJx3^5K6D(%Uncp=o5V z?Hn1$7j%;HoC*4xhvy@iCC5L@38#-{0Qr`qdH8pI9+EuB0P`G-s!jjNJu<=Uu~yih z&l&D~%&SlLBU#106$;RgU$=GnfRF=ZhhFDnCv&Q6eJa4^HF=2Q_nu`j&!lr@uMs7q zz4YTEy&i2^>2+PVE=6^0PfD2Qg%rnSF)5R3W~Cgp)+N7PH#xjOFe7OczOQzkA0q}$HvQkdba<4k|@S7 zdP-K2O^izr7uPr$ra3GJhbD-wU6PDr?ZtsEn^_e%jIxBD#y4;EQm=)Pwdh3IQ9VI?`XtK73WsF0-6450Gf6&dWp9i>du4m0 z=vNpdrqOXJ;U2S3JtbPqArmv5dDF2fY|Kz&RCO0jt)pV@sw;NdxuMZn6+)Y-$%ZO% z%2tgRCLLl$=pw#U3?`T{%Z{-4)e# zt8jO<3L|T%@p%BV%JeGSo=8`CunKjnGV|Jpy`a6^zugXl`wQ;VioE5`Yg zgGLDN=_8q-MZwLGNqKH3wr$J~rS;pVAsLgfV=IdG%FW2CGAG&1@((iqijKp@xSnfE4ye5W`g7zBmvJ4)bKL{1XB^yC2V$T{-Z@K}#`D7U%G8b+P*Od(n zxc{D9B==zdeGRthC@uObWydxL@jj%I{9t?O-M~)9t*(-VT!&5U!ma@UIocETqdZ~T-xC2pJz!=t0nK?;KGq7u7_L>`y(L=16Z#&R zXv^`(>J1q=t_SX%Vo!QoW_Ehg#d@XyVSMi!m2m!T-d%deDdovqdWUaymyhh1`TMR? zW=S&7kM!={{V+9wLtMTwm>EJ^X8s2f8>^hraX@mkDxVD{ljO)O*o`~0ZB6grB z`f%=gaLo(jd2Mo*us@|~1T-3YdR^)Idq<8iAQP*(-ucffHJfvS%Vs^?MrC5<`XX!@ zQHb^ma-PZ}JXp!T3mbYP>-CaBm%GTo$(?0nLu)zmKq+VEDrNo&lN_DT_3uMElsPZ| zL3iY9U!x4$Jpuc+GB-5X6ZejK!pFpH?h1E$1H*CgGIP}yhSTjIhRIRkC~n2;!+SKf zZzk$A$;7kROw3%Ii8NobGY`0yT1`G>E9VJaA>7|HN0i^YTVf}nL#(CjM<-dlxtmPB z-9rwwvnB^(lEs6oBdOR7CeA3+%*|l&+$e8uc%YY_b3GZ$M;0DvobAaPpcj5WLhl#n z$O1AUuQ!Atnd{JVrR>>hk%=2z7Y<#MiS|3WMl{bv8F`*R2XIa~QGg$_il8{mIb?Ma ze7dpDukFVER0ruZStU1W^EtYpl9cu;3BFb(a-UA~6=8Um&3v)1%u6Td)Mh-_v`(31 zKgh*?F2shpg$QiV4AIH-TD>lW`SAiQe3u~ZsfjXw0=>H&!;5bwN&ECT86D_=OLPE@ zUa!K7cS@vGC{gc&13C@}z~mi)$R5S9EGH2Di^*ef?;IVY#npf5V=Q7H-&_qoa(o-J zkvRfU2H3R9#qVS2dYwY=e`}5#+FbPKS^4oM3U!8-nY`o-nq(`~vR0v<^GgzQN|L0f zxkgrmC5s=uz)P%>B=?FVUM^Q5aIq4NhC85Xej$s^=CUrMpkCy#<>zI{UMfPlhLhawt zOnrWeLOtd_om)2)>ib`kC47KZz+Ql96B6X3w^sHflke~Eh#ogMf8{w~$!)p_SE%6Y zt3n%&?RB4%FYw|xAI923SP-1Z5N?g-_&XyB-4^gOSu?lcz6SN*(6{vqGnBvOV9hQ1 z8Ln`A^fTaCqa3W_pRJ}p>VYHKi+&3Ao^o;+hZO1-YZ64wzJtrH$%4?~w3EI_^V4xM zt_l5vEgexWUx|i=N@&QR`cGHkY9{lyQv&Jp2|&Uto{=mddqGC!YNsTG-_+vYM@i6c zOo9jR-Am3B$&!nynjE+W8W1zYfV_DIZ2L0@Z^;in?XOTz9;i^aB8xFNi7rAqr6$)o zC8s)TrPh9pNVHa3F%#q;*JQb5uEHCI5(~bNBiyURRPQd($0%WUH;}tb)?RK0BH$UF zWXAd^AAXY1Yy z^`@N)wQmaRw&xV;_3N1-IzLh7Ha#UN&61>WqE-U>$B27@M(n4l;2Fz)hduV#USN-T ze2%Wnutz)2|2|pF==?hn+r|fAKiJd28qQ44wW&Vr7wE#e%5+|%i|i3yLRa!~&S@*j z-A^`P1ZyXM@;MsnWI)_wg}OVL5Yun;R*qGuGnXsW)^xU=e$ZLE2C8JSuB$A&++D^E zR!UrLNBMljBnmK ztHZJAd78Zxy-~^E7dZ~ScaZ)8U0K_+mwRH8gx<_`er$%=Nw&7_e;G$^X5s1=%_j=D-7v$hI@Njp$o=%% z3D`jX-GSU^!8doDSnr7|4LqQs;W&2xY(kr6JtLy*uFL3Qa9@la?uSak4u(h}^Qx%~-dnlf0*r)X+ zRT`xx$m3V^>PbAWO@hR8uW;d>62ps`-gWm%+nB9O3;Xo}MYvrO(4%gpb z=_g_R^>uFp#&E2jZas8f7!~pg6`TE&CJy6ILBX) zO_1dmQe^(ec-gr-Nm_5#irEV?1>=;M+nBv?85+;!!+-;tO#(Oka*;0#>ZCTU)VSuGI`{?z|Q|1`m@=y*lS{3Sv zt?11qlfRDhMh;m^>vd#M|4EW{os;EeH4XXqBw1GX4+-0!C=E0Y7`B+_8@Bd%)RTKk zGL5|(Fb{wnW8Mw!0du(q()%OQA`sql*w3+BgExBveLp#{fKkvu89iu_hzZGikS#M*w0a?XQFs> z&z@YOmHwR^Fgcf=hfzw@e`OC%7iJiQsxbOT04^j1BDr%AmTwQj`z<`1XvBSMH7zbL z*P^Bw^P2eFT>Hv>W3mP#V+;u3XZo97YT;*ky`KK#RXKE(Db$Jl3|m|j>VenDesV2l z#Yc1yFh8DeY!^;cok*$}3tI6~p?zNCy|5BMdXaXYd(K|Ms{>1(TI7Qy= z*2VAg*_{3|=TPjN#rn@h@{C@V;-oE;>L2Mri=fBNoF3Lk`6!!WAr0vHy4l1X?T3e= z7X52;m~X3eX)O8V5U=RmVA6-;%n%)HbLbsw-c(%X{*YJ9an>ye#aI5GKPTm*@>@qK z@F^mOWRyA`F#k= zn~_^Qz&vYbE4g#ER9-)EgH1^YB3oqOMpNbm&#)4;S(!Zi#5~_sA<(LHh})TmgZ0{w z(=C;YeO&o>55=w3{QPb5v1vj_$)(rq20fA&28AMo{LW0Pd|VjVMzlFUWl!mNY@ZQ| zKi26mmfzpIy_M{#&D_L{{WF*`n~$4;?WO0WN=aMJ+*scbyxfz42SW?kci3KP-~B1$quenp zAQajytG|x`QluiYx z_D@TBv!zV#UUNex_tuqnbeJ2P2bZty#4n~)UM(WOc_b9>>oZUiTL8n`Hj=rhR1Pyo z_zZbK$8sHNt)X*wcMJKZG>WDB1ZFRWV*fgFdDRQhq*rsf)3QqX)5{i5zBT$jxzX|D zJ-@e-4%^CQTO)VmKc?rg7kQ<}c^G%Cl~f)tku<#vR+3xP|J0$$bzaXAE#zxdg+w3Y z_2K>9-IKY%Va!M>q&M)FD!E$U4Qbm$(cl?5xVCxB=V>879xHeb#(wi|p)gZt;6hnG z!h+h0KkLeiCb_{jC=^Qzb+|-NVsa-7c@bJF)A-!FaBVi1&xs$setU;n$evlH67|Lv z3x8v-^xv#`{*ecJuXb{O2%k4z=Zk$p(cDjmUZa_lJE6IF`d3PmnJ&otH57GvGgtSo zeDoyOIX(HO^me0va2oT?2V`I`dBa`{n$a^;BHQM><3MZfOCRYF@HQWdhFQvc@@1cr z-Ep!uuTQEDYmNEnIG*31_f3WkoPZDSLZJMl9`0%D!IZpowv+aEH&o$5(Qf zpRA;k{GiuS=0X2Xj&*eg@^~HElILAfy-HdIx#CZr6%9{kem(2DCFp6jEFvYO|CFK56!z<*xmn(bw z$V(~v^fKc5U^ zD_L-;Qqmi`Lwg_uU!Uo4rF%X`S+tRx4S&e_!){2~Ob&5eIu`8U@44DReDg~sw9pN| ztqI1{Z{#{T9(KIfM&8dV6RTEkyjP)k#_KaCyZ}d-PyNfy3VCpp`R}Vj;a!9K6LQwG zw=@=+`%|9noq*(Y=A?6++&48J6Tdc<5b~JK`qA6lj``6CbZCBw-q+<2gy@h1we3y}pT+xSIw)(LSi=WdI+PJj@fBGpsFS@~b96gnsrw+7Y zj?=0*(bG?Nn|uoBt$Q~r8?{1>%qobKSBGs;*OMN=iwP+2OP^o_y?ftI%ChxzX*0KU z!TJRBbSk6CzSZNk;482Q%91}_Krqt-ogF&nZmZGjP&PsB)@NzA=Hy@7q6{Qar)%Dt_^ z+T$m zvKBL@PTA8-@6Qa*L}WB$e)oAJ5{5^URk26hC1!QzkvIIFg^f`r6wE&%zc;qUYkxnq zp?`Dm*lY~(HPMM2D|3F>ApV>$x-8P*9M`i?xo)&{j+OLjHn3U8vjhH~#tZrVmquhv zBRliS8tuu+ZnoB-n?*Jzg_)o)h$X*l&)zM1+{PwC9`NtA&V*gHnOEDw78`E)qUKxr z^_V04Jlx1W_7h^A&ihCnP|JMV4M&*=-Q9%m^u!&e$Fp;cANp@6hedwF+fJblJ)a<6 z;kMXr>5Eh3w(d4z4s|yZq;a&=)Y@U}6@RQrqc?L;7NXu5@nzOAiQ7a^Ty^S;tD=1r(bd+dwDN%7tzcJuL;McK~r+RgZH+%bn%DP5;`cB(f=^igmujIem0la;W+)3JvFG%XVH~oV#Y+Yy!Exk!@54u zmeFf@F$?pXnvmNqQc|+XSVj9_O>839{n>bU+K6H4vC@Fa)wjMN=z1OJ!gsShNe>j(0uf0z(|EI|tD*kjlfU*z%c z`)BPO{5#f!&<@dZj^E#Zf#W23-fk!8)#Y>8NEs&!_*`w;&F}L%4Dt9c&zgMe&Uo3~ z#)e)Te|#O6fbHG+d9IppGBsM>IN37a#1CW0^O~me{S7wZ{^2NTV`jr_4qv=ln}9<# zaxf`}UeP{rqF!u^zgzlZ9?$3c)*wghVZ^DdXmKQmK4*tNoUbH6YskW)eI_W6B*>w6 zT_0%;`=bZ@V@d$?vLgW%x;P{APpNPkhPPCSqn_ zHj3XHu_h=+4viwWUW4O&3g;J&Z(CCT|NV^fe{3DN*U~CIa8prQNX!_g)CHl=>BI8U zGoCba-qWKhJ#NGKbj3u4Zlm{{^oz|-rCn^kGCj6MaN71iU#D9-P1QZC`OW!9N<@0j z=vB_6A8b!g+-{wI?(GgI|E7(dtM5s3-k4~WzOb~hbHl^!(yiz1PT!Ms$EkPht+YW? zR-_mD9!RToe$=4y+E(eB&8yQ*Rnh62<|Iisez_MX%Z3LDa>`sQ(f`JabHjL9;=*TV zCiA3w#misr$>N!wC~ar4W-&EZtY5{+t;wvb&}VyiTat`4Pm~z;jxHILEUj7hJ^V;3 zE!w1r`ec%Xm&Qu%^BOVtp?}~}igZ20Il?Jfj?l}P$KKcc(Mj^;gI0EJ)X0!Dd(`5& zvWj)$&sGj_Tx*Z%kL=NLs{@{Grz^lmg%4j@&u+%LaXd2z-5v1ip*>*ffOokn^ir#! zIH_b7HGiI7fyO;m_&HpODJu3v-e+HJq&*hsc#a)J?s1L^s~f3sfc5#@mG&^>*@1!o zO(!0pL|Kaxm z*x8il**pXJRG)o~O@gpy66@Hk^?O;f{(nCZgP#Q;BR&8I6KmTGSp%CEgdxuZutY;9 z(uU^)|M;Vc1j6dGKay?+U=n}-71k0C_n>d!8}lc~3_nz9Fe!~==1483AJ<~|Ff9&r zWNt?X*6W`!k6Nci!l)z^E}{qEr3U`f=-~0-dA73#<0~{+#53tg2Ra;j(%+M=g<=MM z*!;cScwXI@XEgOvHHg}##lyzzC+5#?8lnLX(%Be9SH=K3f>-iFsNwE2MdIT+8H+Rwk~rB3I&JI8?Q`8kMV-7jtw>ukkv+DGITC z=GV8EIZ7LuMdN+WC6!p@E9H+<4sxrTqm=zr$|&Eiq8Qv&j1G=sJEezw$?YnqqwOX9 zjICVn)msj>u$QG5nXB8Oy`*%v5vxN=IX2c-e6OgOziuxf?dfkkY=)+{E2VBbGdK@4 ziG5I|9I`OU!lMeLvQF&!O2KuN0#j}1q+eAbdlpn1ABQOfM?O$>+$QPH@=?qfZ{3LF|#J1{209e zA3X5uH}X^8=$YHdI)4*S*04Qs@-GjJ9>5-XGFF8TJ=ovF9P0fO(Cu#zSd(p3O`@mn zEzbyM@a*>T1oXP^fyh+;8J)ba=CTK3i#_nUS{Tm140v7z4(OPndN}fxw z)?GeM4<|AJs$F`_Q1Cp*s7FCfy5B4_;d3+-H8<;_cW0eEUys9{dYZ3=!n|gHbm5KiP3}*PUE~d;t=>$3#SL)#q$9`Hba$UXk7@R@x#2MyAP1fW7YCY0T z%;Y`F%<4^gtlP@-nbC##I;0RD=7p%bT8Q2{@=teouHB>%ezObk-oTs%o>eIKk(D@4 zo+`V5{RV|dj4yyW&v<@V@q8tj4mh4;+;u60B7_;2WEe8Hk=0^PY{N{Rb2MO0zkvCL zEei22x)3k76yomW*AqOq?qe$pGVR5GPJ5|t<0$ikI!mhyw$fQ_ z<>OXsW?pm@(-d2|+m$X}AF?W=QjA7adkg-Earl_j@PVZ&1p@SB`Sj z&`s*S?kcX#b?_~$jB>@?C@Yp5B`&BM8hlkCd7=X2=yzCFsldfd{@fP@ zdS0)R1y8D>wqKRpyQ;urf0G2|Gq19`N%F>#AxTsq#-9J1`7?_iC}78Pl_RW41^+Ng zi+qz{0yEw0s=@cW0=?cUkl48z4nOC6Gn?mg*@iIEKi&t>51Eg^dl`M2ie36^MxNUps270|8~6^f4)9_@I98Au zJ~%53lYZyB!}rQm%>Ht+l2=wT7siX{Nc_s_Mn~#d=7sQmHfzSd^vE#yC(+r+Gt#>J za}`#4c=3JOxre@&s7$5;y}4wET^;G^C}b^XND=2?GKdN~xds-( z@+8ko=M`Zk-z%@m0(?15#&;9_jw|WMn#$bGxrOL-oDN58x)+xfVm{y1@iBCv@Ew}B zoea|gx@~F}p@e67mI?GZ7V`buRD>O+1u%Xo;JT#{-|k*_o|bW9VBO&6=@uR8JHHun zByC_F!@y~c&ZgH-YOA}kC&Ot(<&pHt`EI(XBMRpX|L}DEb?5Z>8iSqoZg1q=t;Q!O zyFT8RzFpYoJbPtWTD$Ci>FdAkciQ}_{F2uYf9KYk>gfYJ9Zox%G%9`D=OMq*VOs9`y%hOmf+|`O< zxmJ`#@nTMI;~!5GWNPa;$@q{UpRQ=6-h7P&ZcP#U+wl?_c}hA}Xl0)&LGJuZ-%@_E zlov3Un!Ph``y|Pmg^4nL(kV&oLD%C&t!xX^%9bq&($$6T?!)8I6JTp#DP5(_L$YL>``sBBWCwf@f?(H@N`Gy zUsED^x&!)hU3sFw5&r&kh_|MTX}3T0y~r=-kuhu&gmwGrA9=})XtFqwYq^fQ#@-dy zLSB0DpDxV53}7a7EL~E+(A6}NEaYm|Nw~+D7{T+a!Ss`5(B;&EXKZ5v@k$+p20sH3 zcZJ>;{_N`kK}g`*v-NWJyIc;y7p_T9dj()@IrGWP=mFU1Q*yrbwgfXA#h>Fu-V>vm;Yz0P6=UG;L>ENo%bJ3YvtaRbm5G_{h zC(~HWUX~rq)vL`MJDzblMY7+`itD{o^fYp<_heBH(rfbE($|1a^$hss9na?avqyNm z0opuf@m(d zfXnC~K&J5xbB#V{Ad+Lzu}*q4I8=y=TFmL3S%~S&3sKXO^LWD|EX%Qz_AQn2u)n<= zZrELJj$XoRBBNy|>)UpfgkpPH^Q61ny5cCNFZSYc$Bb^@>WF_qZ{-=2jH;`ELyS>I zWqBd~E`3rzJ>WFJ3#I2gVKjK6zkfJ;%EM97Cmi+2HvU*kkMCkKbBF249YIcJeI}Ov zP39r+GSubt^rjVI4zG>#u0k}NRES*xMRb;a!WHMPQvbfa?7Q7v+?V#0_j#R}wc1r~ znbSF_GsEOo3j8FCdh;yvmFJKR`Rs`V_6amN?1=~?Gudi+B4v%||EwqNC(=t?7KUw) z>Hj)MkEKmG{^VL~ds-&04x$@)K_*OOL_V>P_H$+der*WxS9aFY3$L&uxpw0Pmm9WQ(=;XLk1 zk7Ylys1rO9Jv$6_GU=_H5QZ6Ck7gBx<4d=7IL32?iL{ROd(o36~LmGqbwZMLzb;j%IBdyrCWQI94c^>plCCEI&X%BE33q& zhee1CaaiFUgLfk!}=NjXMjTbaM*%QHgbbV78mLn9cG+~IC8itnlxfa+> z|M6%&ZXBi)jnB~F1DP;O)nkV_9hzLD_Bu;0mupKK&X?KkituByMsD~g%Rez>2cxud zwMr{RZ8VaT$Ns`oDkRrdA*Glsn4c2;*Q&68FkQ9Z$;5>PVdH`TWVH-Lg9m}=dWXGq z9B&rQ(V+JS4K{bz!d=K2jLpT~rUs1OnFEVw20Ru6{$SSg;Qh>2G$_=I9L&@jo~5g1 zk}bH){`iZ@ViTP#O~^C;Rlw}deTg!5kVc{xtMKv^^QNb&pdP0}&N=ezI(t+MCF?Md zJ?%RKvGx%A6ggghnoaIuJe{;@T2ww~AK`2*R<9;+N#-E?qyZDi$VK)sVD)ALT@tyN zP@Ic-%uoL5&A#_Ug}Q^cnfd^|Tb|6!w5^#eNzCbVd7+`_kB-K*%(k$Mmkq3WDF5>f zdO2ckA$u&JaGtBdyyp_KohkG&HV#6@D7vI}1R`%~AY6arp8T5@rCA);pR;eVDL>m` zEjraP!0JX0mT^qA=)$~%6S+Jmp*N`;U6BVA>QW7Jo<}gZlZ?v6(PnDr2T8K!c#1gC z1GeifKMUPo+nrLSTYdJIrZU5VETf!bmgzrTQ17@BBAvDHeqGx4H4#$44O8i`ES$VGb5?%i=fljZgZYp+CDi3&r>fNuQ| zh!LEFZ8#SnUlE8uKL(com=O&fR`xpaV zA)HI@(2bv9)FrlCD}@Ur9xfN*-Y&->y#AqN|Zo)CEQIKDXW<%zL6UFP0Jcn zA9|dt+2imlB?kSfL{2Le`p*c$x2J)a9~ubH1_7w;69|=65Dc!&)=;tEfKJan%gLqK zlCNCPet@?I*w!+j*Ec#V`FUEPE*=90JneY85Jq|P|LOR#L z_um)5n|sSnYYNd+$YR1=3e^M5%SaAr!I*s!m;6;zZ!hRIy>q3$zEE2c9g<3-DO9E z-qORri~JR-z=SIbx&X*DZdc&I0)DQm3iP$|f_^AJ2j{L|!kJ&3=??#|^yzcoq&fhVTb zqLVR%{iS&xnAC6*qBwV*`N{mxap5p8q4WL#uhn(t8*)xJ>z0X+LF6m>&mZU6yReqr z`QReFp2of@&SAHovuBDuR9kJyq6T-BX=7C4b=E;f`1F(-t8HXVGe`E7SBD3x;csSx zA6Q|AR*TGV@Od@V;~sS1HV;%+dm`tm2mZZCmT-nARt^qFx3Szex`$z+MK~s&V_zJ3 z)CqMnv27?_zB}}oevb8#0zI}Bb8l9`9?5fs_|$`Sg^WVjb)bKFD*cSryGaX=E)u45 z6zO0mbFV7pX-)PU|6!8Sbw;sfy{pwe_VdOX#lS2Dmt0Sn|HdA{treY`#+!?C&sGs|n~@#4517i+Ok?tmUieKWCwpRLBbLiEVwzV2Wl z0QR)yvVUP5uUYpLX>OG$JsxXic#uY>o{N`X_oawW8SBWLC*+a}Z(led;krFt4oXD! z3qnMTAS_goq2@b3c5x8Cer26FgEdypTb8f2_)PDMYYcnJxi0oGvOi~C4)mMJr1i^% zc~%b27BT0UoZj^qh1&3t%<_E`_mXC6S7s`2*qKOvIzjquO%lI#$)ao>FLPKoAGnog ztx6TP=5o*SL50Eh9Z^1BiRnQB+=BL+B`Ub#rWB_(?|4T7=~)U$STj{Pl3 zMm*69GqA+%Sd#QVn8;i*tz6&hfRNYh3#j1UYAmnQXFIfAt;C&QgRuJmJ&^%q81InT z1LyfHj@6D@6#mqr!vrmQ$I|Kkl>3rxNoc;!z+S8zSo5E8uUIoK%f({ypWiCTo7083 z;G04nd`O|zJW;4KACW2ioFpDONz!HZDM@XYET^NAq_TdpqzrSw-JvS1w@@LE=L$c| z>C)}tz#K9<2jjSZ;vQ{udLT*z1Mwm}2)4g#@!U;|9sEk2lLWiANm%qvgRu(kUFMLd zTw_4kW4hpbaZY8Q{kVk+bus-xy{nt4eYwtX{Hai)aIw8 z`MVVP(998%2n6G5t*aic$iwziJ&-tqn`~AlmkQiWq8GXyKrxa>svO-<9m|ovA3UvbK z_?u@E#r#T=MAJv{&@5Sc=f=vx1xeDOM^{Yb^BZi=41?=R`2Ix~gtrQF`UIivSgv`h zabL@G2+N`X4CX#m-+-A+g&G`vNG|`a1~a%mn^Zt9wnh%>{KNd~Xl6_Y(7${>2k-V7 z@E7OuK=uZ#B8O^|&;QLizUm$S`G5M#7Cmn*_7&waVuTw`HVDNDwGIa&3g{?qCD)ez zkf(tzm~P2hFnO-Y|B@@LYc78=hp1W<^MxPKi+4N&Jx7o?iEbo0&de8X=8CbAA!J`O zaC;v6v(?RIZQJiMYqC2ED?_nlw+_~!1yCMpB^}j2rA0&XJAVYjvXLHBg2^RqvXqxe z6%s#^yxW;z6fM=^tu7z?+gQrR=H;UL;DT~Z2u>NvLv7DTMvFG`g88r?tlhD5YzT6X zq$BG&y<->2VKF<&a=Hq!Q3(09z zB4NzoJuoce||B!o)w{Zl*pXu0r{A@ubo)d{V9Q?-B3qIo@>Z| zc_aB~f7(KpEGw0+aV~Uev5$BP^II3^BmFtKysKpr)R7*{k>n!l>oD#*J$H!>rN@zP zGStTv_lI-un5V-$a#(F=TgkVRrF1>g)7LD7``rv2<8>aHMGh#aLi&}v0)3b-Jd=LC zsQ|nM@z(ieTo|4zkeUeTxFjENLeT&VQFVyl&6UL!g?Q0q@uOSZ&`*Iu9-r zgP!+yZWxvXWx#wHIacrXqT5j^*QU_-Ff0U$_UzvxzxF8JLUu)zNbxZ~hi^l0X@5GN zEg_$k+C+-7OJuph1?`JMaFw-7wH@!TzP&h1E|;e*-SA^}DBh97ayZKSmEM9GVL#=8 zxMGe)DB>!0C>>USX!;h-pH)ixTJ%-FBe(040ayP1?|)fJ{nmUh_<7uHLa{iPT%J=t z4)wE;9hK#xadE|XK8H?&=-KQ+FXXOvQnvPo_%a84RCU&CU+It?mXEY|%_M~U;Q56v z5Z=e9yuZ&j@OiLmD?WcPHz3socdCN1^q~%p6?x1MpvRLr@2Y(Mp4lNlFu6;I0z6&Y zLh5uV72O9n%#0?Nx`!1X3xFTZ% z{eyfCTb$0v)B7D{pl6wc@V)a42*J%T9o;G9XX`hYYOl&<8M)56iHT!)fc`LJkW zA>a4?l;cZW*%uswu1Y?K76nL2wGe~%cTs$!kCohavspUyO=E6*{T5Q$ieAwHE*QZ3 zHK1Dt8u2;#`pimBxK&6QbFuX!L-5ujgSo&3xX4`fho0Z%Qw=wGKMg@oa^-0?3-Gpc zGx=n!l;~|PxXE!TEmnsNa+JSaYfBGysf7IMib8UW4?B=6pH83b*iJI`LaF#H8;6rK zLNSz_=E)j719)~qru*Ar@2d@H=a`7ef%NE2GU4FESb0=rjn-#;;Ow4={+`Th&LU5@ zHd5{_vO%99AFd@5(6b#KJ>>rU_eDuI`KBw|0}&dZh;a$oP`oi>L&OPb{mmY$-;m2= zO?HfT7B21~514yGjt{iO8s?b}dY6Dfi?b1Nk(}L}IH~EuTwQW`_y3AV6LM!~4w|r| zUbLjA*kPQjAN#`-Vc8)Y!Do#~nHVW5yduZLtrsdnBS(em1ipjr7YzNl!}~^e|(d^5uB^z9$>Qt{GAB zYmBT2vBu0dKDb|*fZxwQ#5?kaj-~O^ z9C@xWEy*R#GGcgmtUQjl#l|{*So1Ie`+AcznruXmFDGT_7v^8jA=h&-0aq?$VIV)x zP48oJ|FjK8P4ht+xzSNKbKpTfD`z|NyZ4bdyvbbMA@pYYXW`Hh6FR%c$mh@2^c4DI zbO?J4BeM|9>pbvYv@F=h`+Lt1e|od#{UjTg_Lx|kkCA(scDQ?B12RGq@xYC|LVFYL zS;a^n7hCk1v;ptVCh(jm3tPLN_-pTqQ%)kCCM#9Riah>M? zD|{2sdVLl;yfWhBwP@)|o^<Ybw8KeRLbunWRGvFnC!*$tEGRyZ zd&-KHLvNWAO>U&eUkUiUnf&QE6VmEOi4F6VBZiVMo1K7vR%bEm*8~r8ZSKtJzOdE@ zwO1#gY%;x&{BzGFMN0v>zp_()XwokcK7RC1)ns3=f&5^o4bM(|@R*!b5qY#b+nB#R zGD=E%vX^ra^K*-t4a&dQkLyNQ^d+Zx$QC;m`XN3#f%~K!JRV@g_c~FM;bI5x&i+`$ z>lwI+Tw9J2-c#eGjDPOC{0(@0Gy#EmS?m#IZuR;Y+4jN)2J&AIxqmv?HwTJcMs$)` z8A@*SSdkBVM-otDeGX=?Gor)2C>fSwgJXkykvKIG?!J7^la1KZ>$ps!7xLaLKinM2 z=Qfet-$WC(I7N!jB0Dth=8qC`m&xS&tfI+#21LrY-)%6kg+D(1O5dn18|$B$aEhML zPxL}Q*hSysjRagP&qCwlCcKywCGY9WdvMAZ6IJAJBgujCd2<>RCy&nAqEYY$JpUts zPM0iP{l$c3+DNIk+ZKDmeKF0FT%dVMW zlB1lH>WkD93Cxt`bIa$g7yIqPnRo2;m3hs)?{n^v=lyQN(LbZ*G(Cgvdwkj3oQOT- z?0&R0K|4KG_8M%+j_~^LOhCJJ~esvegDX&-uX1kbwLHe6I4C zul+butnS(%uFxMotrF3b?{9;P^j#X`Wbj+wuUKE`cpYk!v!2nCwZ;e0;>PjZa{LAq z%}>Pkt64bw$%wS%XsK&qi~5QFP~Ru#+lKkS_UN_Hhpy~+j!juGe{94vn^^hT(iUc~{or#V5g)r}ntimestep != update->beginstep){ fdrag[0] = gamma1*gjffac*v[i][0]; fdrag[1] = gamma1*gjffac*v[i][1]; fdrag[2] = gamma1*gjffac*v[i][2]; } + else if (Tp_GJF && update->ntimestep == update->beginstep){ + fdrag[0] = 0.0; + fdrag[1] = 0.0; + fdrag[2] = 0.0; + } flangevin[i][0] = fdrag[0] + fran[0]; flangevin[i][1] = fdrag[1] + fran[1]; flangevin[i][2] = fdrag[2] + fran[2]; From f0679cff6d87b0133f05833309af9c5d44468a0f Mon Sep 17 00:00:00 2001 From: julient31 Date: Tue, 23 Jul 2019 09:27:15 -0600 Subject: [PATCH 057/192] Commit JT 072319 - added 2 oso examples in examples/SPIN/spinmin - added doc for oso_cg and oso_lbfgs --- doc/src/lammps.book | 1 + doc/src/min_modify.txt | 22 +++++++-- doc/src/min_spin.txt | 36 +++++++++++++-- doc/src/min_style.txt | 19 +++++++- doc/src/minimize.txt | 3 +- doc/src/neb_spin.txt | 6 ++- doc/src/pair_spin_dipole.txt | 5 +- examples/SPIN/spinmin/in.spinmin_cg.bfo | 54 ++++++++++++++++++++++ examples/SPIN/spinmin/in.spinmin_lbfgs.bfo | 54 ++++++++++++++++++++++ src/SPIN/min_spin.cpp | 4 +- src/SPIN/min_spin_oso_cg.cpp | 12 ++--- src/SPIN/min_spin_oso_lbfgs.cpp | 16 +++---- 12 files changed, 200 insertions(+), 32 deletions(-) create mode 100644 examples/SPIN/spinmin/in.spinmin_cg.bfo create mode 100644 examples/SPIN/spinmin/in.spinmin_lbfgs.bfo diff --git a/doc/src/lammps.book b/doc/src/lammps.book index 2738c9b051..8abe9cffa1 100644 --- a/doc/src/lammps.book +++ b/doc/src/lammps.book @@ -647,6 +647,7 @@ pair_sph_lj.html pair_sph_rhosum.html pair_sph_taitwater.html pair_sph_taitwater_morris.html +pair_spin_dipole.html pair_spin_dmi.html pair_spin_exchange.html pair_spin_magelec.html diff --git a/doc/src/min_modify.txt b/doc/src/min_modify.txt index d342e8bf01..da7b593d16 100644 --- a/doc/src/min_modify.txt +++ b/doc/src/min_modify.txt @@ -13,11 +13,11 @@ min_modify command :h3 min_modify keyword values ... :pre one or more keyword/value pairs may be listed :ulb,l -keyword = {dmax} or {line} or {alpha_damp} or {discrete_factor} +keyword = {dmax} or {line} or {alpha_damp} or {discrete_factor} or {spin_cubic} or {spin_none} {dmax} value = max max = maximum distance for line search to move (distance units) - {line} value = {backtrack} or {quadratic} or {forcezero} - backtrack,quadratic,forcezero = style of linesearch to use + {line} value = {backtrack} or {quadratic} or {forcezero} or {spin_cubic} or {spin_none} + backtrack,quadratic,forcezero,spin_cubic,spin_none = style of linesearch to use {alpha_damp} value = damping damping = fictitious Gilbert damping for spin minimization (adim) {discrete_factor} value = factor @@ -80,7 +80,21 @@ See "min_spin"_min_spin.html for more information about those quantities. Default values are {alpha_damp} = 1.0 and {discrete_factor} = 10.0. -[Restrictions:] none +The choice of a line search algorithm for the {spin_oso_cg} and +{spin_oso_lbfgs} can be specified via the {line} keyword. +The {spin_cubic} and {spin_none} only make sense when those two +when one of those two minimization styles is declared. + +The {spin_cubic} keyword activates the line search procedure when +the {spin_oso_cg} algorithm is used. + +The {spin_none} keyword deactivates the line search procedure when +the {spin_oso_lbfgs} algorithm is used. + +[Restrictions:] The line search procedure of styles +{spin_oso_cg} and {spin_oso_lbfgs} cannot be used for magnetic +NEB calculations. See "neb/spin"_neb_spin.html for more +explanation. [Related commands:] diff --git a/doc/src/min_spin.txt b/doc/src/min_spin.txt index 890e324aca..6883a4197c 100644 --- a/doc/src/min_spin.txt +++ b/doc/src/min_spin.txt @@ -6,14 +6,19 @@ :line min_style spin command :h3 +min_style spin_oso_cg command :h3 +min_style spin_oso_lbfgs command :h3 [Syntax:] -min_style spin :pre +min_style spin +min_style spin_oso_cg +min_style spin_oso_lbfgs :pre [Examples:] -min_style spin :pre +min_style spin_oso_lbfgs +min_modify discrete_factor 10.0 line_search 0 :pre [Description:] @@ -46,9 +51,29 @@ definition of this timestep. {discrete_factor} can be defined with the "min_modify"_min_modify.html command. -NOTE: The {spin} style replaces the force tolerance by a torque +Style {spin_oso_cg} defines an orthogonal spin optimization +(OSO) combined to a conjugate gradient (CG) algorithm. +The "min_modify"_min_modify.html command can be used to +couple the {spin_oso_cg} to a line search procedure, and to modify the +discretization factor {discrete_factor}. + +Style {spin_oso_lbfgs} defines an orthogonal spin optimization +(OSO) combined to a limited-memory Broyden-Fletcher-Goldfarb-Shanno +(LBFGS) algorithm. +By default, style {spin_oso_lbfgs} uses a line search procedure. +The "min_modify"_min_modify.html command can be used to +deactivate the line search procedure. + +For more information about styles {spin_oso_cg} and {spin_oso_lbfgs}, +see their implementation reported in "(Ivanov)"_#Ivanov1. + +NOTE: All the {spin} styles replace the force tolerance by a torque tolerance. See "minimize"_minimize.html for more explanation. +NOTE: The {spin_oso_cg} and {spin_oso_lbfgs} styles can be used +for magnetic NEB calculations only if the line search procedure +is deactivated. See "neb/spin"_neb_spin.html for more explanation. + [Restrictions:] This minimization procedure is only applied to spin degrees of @@ -63,3 +88,8 @@ freedom for a frozen lattice configuration. The option defaults are {alpha_damp} = 1.0 and {discrete_factor} = 10.0. + +:line + +:link(Ivanov1) +[(Ivanov)] Ivanov, Uzdin, Jonsson. arXiv preprint arXiv:1904.02669, (2019). diff --git a/doc/src/min_style.txt b/doc/src/min_style.txt index c46c1492b4..081ec17889 100644 --- a/doc/src/min_style.txt +++ b/doc/src/min_style.txt @@ -11,7 +11,8 @@ min_style command :h3 min_style style :pre -style = {cg} or {hftn} or {sd} or {quickmin} or {fire} or {spin} :ul +style = {cg} or {hftn} or {sd} or {quickmin} or {fire} or {spin} +or {spin_oso_cg} or {spin_oso_lbfgs} :ul [Examples:] @@ -64,11 +65,25 @@ a minimization. Style {spin} is a damped spin dynamics with an adaptive timestep. -See the "min/spin"_min_spin.html doc page for more information. + +Style {spin_oso_cg} uses an orthogonal spin optimization (OSO) +combined to a conjugate gradient (CG) approach to minimize spin +configurations. + +Style {spin_oso_lbfgs} uses an orthogonal spin optimization (OSO) +combined to a limited-memory Broyden-Fletcher-Goldfarb-Shanno +(LBFGS) approach to minimize spin configurations. + +See the "min/spin"_min_spin.html doc page for more information +about the {spin}, {spin_oso_cg} and {spin_oso_lbfgs} styles. Either the {quickmin} and {fire} styles are useful in the context of nudged elastic band (NEB) calculations via the "neb"_neb.html command. +Either the {spin}, {spin_oso_cg} and {spin_oso_lbfgs} styles are useful +in the context of magnetic geodesic nudged elastic band (GNEB) calculations +via the "neb/spin"_neb_spin.html command. + NOTE: The damped dynamic minimizers use whatever timestep you have defined via the "timestep"_timestep.html command. Often they will converge more quickly if you use a timestep about 10x larger than you diff --git a/doc/src/minimize.txt b/doc/src/minimize.txt index ecf1ad0fcf..1dc28acdef 100644 --- a/doc/src/minimize.txt +++ b/doc/src/minimize.txt @@ -103,7 +103,8 @@ the line search fails because the step distance backtracks to 0.0 the number of outer iterations or timesteps exceeds {maxiter} the number of total force evaluations exceeds {maxeval} :ul -NOTE: the "minimization style"_min_style.html {spin} replaces +NOTE: the "minimization style"_min_style.html {spin}, +{spin_oso_cg}, and {spin_oso_lbfgs} replace the force tolerance {ftol} by a torque tolerance. The minimization procedure stops if the 2-norm (length) of the global torque vector (defined as the cross product between the diff --git a/doc/src/neb_spin.txt b/doc/src/neb_spin.txt index 7dbd924cd2..46478b1219 100644 --- a/doc/src/neb_spin.txt +++ b/doc/src/neb_spin.txt @@ -172,7 +172,8 @@ command is issued. A NEB calculation proceeds in two stages, each of which is a minimization procedure, performed via damped dynamics. To enable this, you must first define a damped spin dynamics -"min_style"_min_style.html, using the {spin} style (see +"min_style"_min_style.html, using either the {spin}, +{spin_oso_cg}, or {spin_oso_lbfgs} style (see "min_spin"_min_spin.html for more information). The other styles cannot be used, since they relax the lattice degrees of freedom instead of the spins. @@ -358,6 +359,9 @@ This command can only be used if LAMMPS was built with the SPIN package. See the "Build package"_Build_package.html doc page for more info. +The line search procedures of the {spin_oso_cg} and {spin_oso_lbfgs} +minimization styles cannot be used in a GNEB calculation. + :line [Related commands:] diff --git a/doc/src/pair_spin_dipole.txt b/doc/src/pair_spin_dipole.txt index 0d6471e07f..735c71139a 100644 --- a/doc/src/pair_spin_dipole.txt +++ b/doc/src/pair_spin_dipole.txt @@ -25,9 +25,8 @@ pair_coeff * * 10.0 pair_coeff 2 3 8.0 :pre pair_style spin/dipole/long 9.0 -pair_coeff * * 1.0 1.0 -pair_coeff 2 3 1.0 1.0 2.5 4.0 scale 0.5 -pair_coeff 2 3 1.0 1.0 2.5 4.0 :pre +pair_coeff * * 10.0 +pair_coeff 2 3 6.0 :pre [Description:] diff --git a/examples/SPIN/spinmin/in.spinmin_cg.bfo b/examples/SPIN/spinmin/in.spinmin_cg.bfo new file mode 100644 index 0000000000..cd6ec485ad --- /dev/null +++ b/examples/SPIN/spinmin/in.spinmin_cg.bfo @@ -0,0 +1,54 @@ +# bfo in a 3d periodic box + +units metal +dimension 3 +boundary p p f +atom_style spin + +# necessary for the serial algorithm (sametag) +atom_modify map array + +lattice sc 3.96 +region box block 0.0 34.0 0.0 34.0 0.0 1.0 +create_box 1 box +create_atoms 1 box + +# setting mass, mag. moments, and interactions for bcc iron + +mass 1 1.0 +set group all spin/random 11 2.50 + +pair_style hybrid/overlay spin/exchange 6.0 spin/magelec 4.5 spin/dmi 4.5 +pair_coeff * * spin/exchange exchange 6.0 -0.01575 0.0 1.965 +# pair_coeff * * spin/magelec magelec 4.5 0.000109 1.0 1.0 1.0 +pair_coeff * * spin/magelec magelec 4.5 0.00109 1.0 1.0 1.0 +pair_coeff * * spin/dmi dmi 4.5 0.00005 1.0 1.0 1.0 + +neighbor 0.1 bin +neigh_modify every 10 check yes delay 20 + +fix 1 all precession/spin anisotropy 0.0000033 0.0 0.0 1.0 +fix_modify 1 energy yes + +timestep 0.0001 + +compute out_mag all spin +compute out_pe all pe +compute out_ke all ke +compute out_temp all temp + +variable magz equal c_out_mag[3] +variable magnorm equal c_out_mag[4] +variable emag equal c_out_mag[5] +variable tmag equal c_out_mag[6] + +thermo 50 +thermo_style custom step time v_magnorm v_emag v_tmag temp etotal +thermo_modify format float %20.15g + +compute outsp all property/atom spx spy spz sp fmx fmy fmz +dump 1 all custom 50 dump.lammpstrj type x y z c_outsp[1] c_outsp[2] c_outsp[3] c_outsp[4] c_outsp[5] c_outsp[6] c_outsp[7] + +min_style spin/oso_cg +min_modify discrete_factor 10.0 line_search 0 +minimize 1.0e-10 1.0e-10 10000 1000 diff --git a/examples/SPIN/spinmin/in.spinmin_lbfgs.bfo b/examples/SPIN/spinmin/in.spinmin_lbfgs.bfo new file mode 100644 index 0000000000..5db44522e1 --- /dev/null +++ b/examples/SPIN/spinmin/in.spinmin_lbfgs.bfo @@ -0,0 +1,54 @@ +# bfo in a 3d periodic box + +units metal +dimension 3 +boundary p p f +atom_style spin + +# necessary for the serial algorithm (sametag) +atom_modify map array + +lattice sc 3.96 +region box block 0.0 34.0 0.0 34.0 0.0 1.0 +create_box 1 box +create_atoms 1 box + +# setting mass, mag. moments, and interactions for bcc iron + +mass 1 1.0 +set group all spin/random 11 2.50 + +pair_style hybrid/overlay spin/exchange 6.0 spin/magelec 4.5 spin/dmi 4.5 +pair_coeff * * spin/exchange exchange 6.0 -0.01575 0.0 1.965 +#pair_coeff * * spin/magelec magelec 4.5 0.000109 1.0 1.0 1.0 +pair_coeff * * spin/magelec magelec 4.5 0.00109 1.0 1.0 1.0 +pair_coeff * * spin/dmi dmi 4.5 0.00005 1.0 1.0 1.0 + +neighbor 0.1 bin +neigh_modify every 10 check yes delay 20 + +fix 1 all precession/spin anisotropy 0.0000033 0.0 0.0 1.0 +fix_modify 1 energy yes + +timestep 0.0001 + +compute out_mag all spin +compute out_pe all pe +compute out_ke all ke +compute out_temp all temp + +variable magz equal c_out_mag[3] +variable magnorm equal c_out_mag[4] +variable emag equal c_out_mag[5] +variable tmag equal c_out_mag[6] + +thermo 50 +thermo_style custom step time v_magnorm v_emag v_tmag temp etotal +thermo_modify format float %20.15g + +compute outsp all property/atom spx spy spz sp fmx fmy fmz +dump 1 all custom 50 dump.lammpstrj type x y z c_outsp[1] c_outsp[2] c_outsp[3] c_outsp[4] c_outsp[5] c_outsp[6] c_outsp[7] + +min_style spin/oso_lbfgs +min_modify discrete_factor 10.0 line_search 1 +minimize 1.0e-15 1.0e-10 10000 1000 diff --git a/src/SPIN/min_spin.cpp b/src/SPIN/min_spin.cpp index 9849ba9946..f56c9f0d96 100644 --- a/src/SPIN/min_spin.cpp +++ b/src/SPIN/min_spin.cpp @@ -80,12 +80,12 @@ void MinSpin::setup_style() int MinSpin::modify_param(int narg, char **arg) { if (strcmp(arg[0],"alpha_damp") == 0) { - if (narg < 2) error->all(FLERR,"Illegal fix_modify command"); + if (narg < 2) error->all(FLERR,"Illegal min_modify command"); alpha_damp = force->numeric(FLERR,arg[1]); return 2; } if (strcmp(arg[0],"discrete_factor") == 0) { - if (narg < 2) error->all(FLERR,"Illegal fix_modify command"); + if (narg < 2) error->all(FLERR,"Illegal min_modify command"); discrete_factor = force->numeric(FLERR,arg[1]); return 2; } diff --git a/src/SPIN/min_spin_oso_cg.cpp b/src/SPIN/min_spin_oso_cg.cpp index 843f1e48f1..e43c51e3af 100644 --- a/src/SPIN/min_spin_oso_cg.cpp +++ b/src/SPIN/min_spin_oso_cg.cpp @@ -133,12 +133,10 @@ void MinSpinOSO_CG::setup_style() int MinSpinOSO_CG::modify_param(int narg, char **arg) { if (strcmp(arg[0],"line_search") == 0) { - if (narg < 2) error->all(FLERR,"Illegal fix_modify command"); + if (narg < 2) error->all(FLERR,"Illegal min_modify command"); use_line_search = force->numeric(FLERR,arg[1]); - if (nreplica > 1 && use_line_search) error->all(FLERR,"Illegal fix_modify command, cannot use NEB and line search together"); - return 2; } if (strcmp(arg[0],"discrete_factor") == 0) { @@ -250,9 +248,9 @@ int MinSpinOSO_CG::iterate(int maxiter) neval++; } - //// energy tolerance criterion - //// only check after DELAYSTEP elapsed since velocties reset to 0 - //// sync across replicas if running multi-replica minimization + // energy tolerance criterion + // only check after DELAYSTEP elapsed since velocties reset to 0 + // sync across replicas if running multi-replica minimization if (update->etol > 0.0 && ntimestep-last_negative > DELAYSTEP) { if (update->multireplica == 0) { @@ -680,4 +678,4 @@ double MinSpinOSO_CG::evaluate_dt() dtmax = MY_2PI/(discrete_factor*sqrt(fmaxsqall)); return dtmax; -} \ No newline at end of file +} diff --git a/src/SPIN/min_spin_oso_lbfgs.cpp b/src/SPIN/min_spin_oso_lbfgs.cpp index eba62f296f..0bd128367f 100644 --- a/src/SPIN/min_spin_oso_lbfgs.cpp +++ b/src/SPIN/min_spin_oso_lbfgs.cpp @@ -145,16 +145,14 @@ int MinSpinOSO_LBFGS::modify_param(int narg, char **arg) { if (strcmp(arg[0],"line_search") == 0) { - if (narg < 2) error->all(FLERR,"Illegal fix_modify command"); + if (narg < 2) error->all(FLERR,"Illegal min_modify command"); use_line_search = force->numeric(FLERR,arg[1]); - if (nreplica > 1 && use_line_search) - error->all(FLERR,"Illegal fix_modify command, cannot use NEB and line search together"); - + error->all(FLERR,"Illegal min_modify command, cannot use NEB and line search together"); return 2; } if (strcmp(arg[0],"discrete_factor") == 0) { - if (narg < 2) error->all(FLERR,"Illegal fix_modify command"); + if (narg < 2) error->all(FLERR,"Illegal min_modify command"); double discrete_factor; discrete_factor = force->numeric(FLERR,arg[1]); maxepsrot = MY_2PI / (10 * discrete_factor); @@ -266,9 +264,9 @@ int MinSpinOSO_LBFGS::iterate(int maxiter) neval++; } - //// energy tolerance criterion - //// only check after DELAYSTEP elapsed since velocties reset to 0 - //// sync across replicas if running multi-replica minimization + // energy tolerance criterion + // only check after DELAYSTEP elapsed since velocties reset to 0 + // sync across replicas if running multi-replica minimization if (update->etol > 0.0 && ntimestep-last_negative > DELAYSTEP) { if (update->multireplica == 0) { @@ -802,4 +800,4 @@ double MinSpinOSO_LBFGS::maximum_rotation(double *p) else alpha = 1.0; return alpha; -} \ No newline at end of file +} From f1c3b9d0bf3fd4f27711e81eb11dbb70d79da5fb Mon Sep 17 00:00:00 2001 From: julient31 Date: Tue, 23 Jul 2019 11:24:52 -0600 Subject: [PATCH 058/192] Commit2 JT 072319 - corrected some mistakes in doc files - modified oso examples to match new line options --- doc/src/min_modify.txt | 10 +++++----- doc/src/min_spin.txt | 5 +++-- doc/src/neb_spin.txt | 4 ++-- examples/SPIN/spinmin/in.spinmin_cg.bfo | 2 +- examples/SPIN/spinmin/in.spinmin_lbfgs.bfo | 2 +- src/SPIN/neb_spin.cpp | 2 +- 6 files changed, 13 insertions(+), 12 deletions(-) diff --git a/doc/src/min_modify.txt b/doc/src/min_modify.txt index da7b593d16..c59e2b474b 100644 --- a/doc/src/min_modify.txt +++ b/doc/src/min_modify.txt @@ -13,7 +13,7 @@ min_modify command :h3 min_modify keyword values ... :pre one or more keyword/value pairs may be listed :ulb,l -keyword = {dmax} or {line} or {alpha_damp} or {discrete_factor} or {spin_cubic} or {spin_none} +keyword = {dmax} or {line} or {alpha_damp} or {discrete_factor} {dmax} value = max max = maximum distance for line search to move (distance units) {line} value = {backtrack} or {quadratic} or {forcezero} or {spin_cubic} or {spin_none} @@ -81,9 +81,9 @@ quantities. Default values are {alpha_damp} = 1.0 and {discrete_factor} = 10.0. The choice of a line search algorithm for the {spin_oso_cg} and -{spin_oso_lbfgs} can be specified via the {line} keyword. -The {spin_cubic} and {spin_none} only make sense when those two -when one of those two minimization styles is declared. +{spin_oso_lbfgs} styles can be specified via the {line} keyword. +The {spin_cubic} and {spin_none} only make sense when one of those +two minimization styles is declared. The {spin_cubic} keyword activates the line search procedure when the {spin_oso_cg} algorithm is used. @@ -93,7 +93,7 @@ the {spin_oso_lbfgs} algorithm is used. [Restrictions:] The line search procedure of styles {spin_oso_cg} and {spin_oso_lbfgs} cannot be used for magnetic -NEB calculations. See "neb/spin"_neb_spin.html for more +GNEB calculations. See "neb/spin"_neb_spin.html for more explanation. [Related commands:] diff --git a/doc/src/min_spin.txt b/doc/src/min_spin.txt index 6883a4197c..2a85427c56 100644 --- a/doc/src/min_spin.txt +++ b/doc/src/min_spin.txt @@ -18,7 +18,7 @@ min_style spin_oso_lbfgs :pre [Examples:] min_style spin_oso_lbfgs -min_modify discrete_factor 10.0 line_search 0 :pre +min_modify discrete_factor 10.0 line spin_none :pre [Description:] @@ -62,7 +62,8 @@ Style {spin_oso_lbfgs} defines an orthogonal spin optimization (LBFGS) algorithm. By default, style {spin_oso_lbfgs} uses a line search procedure. The "min_modify"_min_modify.html command can be used to -deactivate the line search procedure. +deactivate the line search procedure, and to modify the +discretization factor {discrete_factor}. For more information about styles {spin_oso_cg} and {spin_oso_lbfgs}, see their implementation reported in "(Ivanov)"_#Ivanov1. diff --git a/doc/src/neb_spin.txt b/doc/src/neb_spin.txt index 46478b1219..27e835276e 100644 --- a/doc/src/neb_spin.txt +++ b/doc/src/neb_spin.txt @@ -60,8 +60,8 @@ processors per replica. See the "Howto replica"_Howto_replica.html doc page for further discussion. NOTE: As explained below, a GNEB calculation performs a damped dynamics -minimization across all the replicas. The "spin"_min_spin.html -style minimizer has to be defined in your input script. +minimization across all the replicas. One of the "spin"_min_spin.html +style minimizers has to be defined in your input script. When a GNEB calculation is performed, it is assumed that each replica is running the same system, though LAMMPS does not check for this. diff --git a/examples/SPIN/spinmin/in.spinmin_cg.bfo b/examples/SPIN/spinmin/in.spinmin_cg.bfo index cd6ec485ad..901b04e5fd 100644 --- a/examples/SPIN/spinmin/in.spinmin_cg.bfo +++ b/examples/SPIN/spinmin/in.spinmin_cg.bfo @@ -50,5 +50,5 @@ compute outsp all property/atom spx spy spz sp fmx fmy fmz dump 1 all custom 50 dump.lammpstrj type x y z c_outsp[1] c_outsp[2] c_outsp[3] c_outsp[4] c_outsp[5] c_outsp[6] c_outsp[7] min_style spin/oso_cg -min_modify discrete_factor 10.0 line_search 0 +min_modify discrete_factor 10.0 line spin_cubic minimize 1.0e-10 1.0e-10 10000 1000 diff --git a/examples/SPIN/spinmin/in.spinmin_lbfgs.bfo b/examples/SPIN/spinmin/in.spinmin_lbfgs.bfo index 5db44522e1..4edd1a053e 100644 --- a/examples/SPIN/spinmin/in.spinmin_lbfgs.bfo +++ b/examples/SPIN/spinmin/in.spinmin_lbfgs.bfo @@ -50,5 +50,5 @@ compute outsp all property/atom spx spy spz sp fmx fmy fmz dump 1 all custom 50 dump.lammpstrj type x y z c_outsp[1] c_outsp[2] c_outsp[3] c_outsp[4] c_outsp[5] c_outsp[6] c_outsp[7] min_style spin/oso_lbfgs -min_modify discrete_factor 10.0 line_search 1 +min_modify discrete_factor 10.0 line spin_none minimize 1.0e-15 1.0e-10 10000 1000 diff --git a/src/SPIN/neb_spin.cpp b/src/SPIN/neb_spin.cpp index 12d1d2a956..4fa1f4467b 100644 --- a/src/SPIN/neb_spin.cpp +++ b/src/SPIN/neb_spin.cpp @@ -650,7 +650,7 @@ int NEBSpin::initial_rotation(double *spi, double *sploc, double fraction) kcrossy = kz*spix - kx*spiz; kcrossz = kx*spiy - ky*spix; - kdots = kx*spix + ky*spiz + kz*spiz; + kdots = kx*spix + ky*spiy + kz*spiz; omega = acos(sidotsf); omega *= fraction; From 15d791d0e3ff82b05fd5012daea2e6a9e41643a4 Mon Sep 17 00:00:00 2001 From: casievers Date: Tue, 23 Jul 2019 18:41:31 -0700 Subject: [PATCH 059/192] debugging gjf tally --- src/fix_langevin.cpp | 26 +++++++++++++------------- 1 file changed, 13 insertions(+), 13 deletions(-) diff --git a/src/fix_langevin.cpp b/src/fix_langevin.cpp index 7d5c382488..82366be4dd 100644 --- a/src/fix_langevin.cpp +++ b/src/fix_langevin.cpp @@ -673,9 +673,12 @@ void FixLangevin::post_force_untemplated if (Tp_TALLY) { if (Tp_GJF && update->ntimestep != update->beginstep){ - fdrag[0] = gamma1*gjffac*v[i][0]; - fdrag[1] = gamma1*gjffac*v[i][1]; - fdrag[2] = gamma1*gjffac*v[i][2]; + fdrag[0] = gamma1*gjffac*gjffac*v[i][0]; + fdrag[1] = gamma1*gjffac*gjffac*v[i][1]; + fdrag[2] = gamma1*gjffac*gjffac*v[i][2]; + fran[0] *= gjffac; + fran[1] *= gjffac; + fran[2] *= gjffac; } else if (Tp_GJF && update->ntimestep == update->beginstep){ fdrag[0] = 0.0; @@ -902,14 +905,8 @@ void FixLangevin::end_of_step() v[i][2] = lv[i][2]; } } - if (tallyflag && hsflag){ - energy_onestep += gjffac*(flangevin[i][0] * lv[i][0] + - flangevin[i][1] * lv[i][1] + flangevin[i][2] * lv[i][2]); - } - else if (tallyflag){ - energy_onestep += flangevin[i][0] * v[i][0] + flangevin[i][1] * v[i][1] + - flangevin[i][2] * v[i][2]; - } + energy_onestep += flangevin[i][0] * v[i][0] + flangevin[i][1] * v[i][1] + + flangevin[i][2] * v[i][2]; } if (tallyflag) { energy += energy_onestep * update->dt; @@ -985,8 +982,11 @@ double FixLangevin::compute_scalar() } // convert midstep energy back to previous fullstep energy - - double energy_me = energy - 0.5*energy_onestep*update->dt; + double energy_me; + if (gjfflag) + energy_me = energy - energy_onestep*update->dt; + else + energy_me = energy - 0.5*energy_onestep*update->dt; double energy_all; MPI_Allreduce(&energy_me,&energy_all,1,MPI_DOUBLE,MPI_SUM,world); From 25653e67f8a041890f1ff6ff933a0fe2f84250b6 Mon Sep 17 00:00:00 2001 From: casievers Date: Wed, 24 Jul 2019 16:05:25 -0700 Subject: [PATCH 060/192] Tally works and example readmes addes --- examples/gjf/README.md | 13 +++++++++++++ examples/python/gjf_python/README.md | 18 ++++++++++++++++++ src/fix_langevin.cpp | 5 ----- 3 files changed, 31 insertions(+), 5 deletions(-) create mode 100644 examples/gjf/README.md create mode 100644 examples/python/gjf_python/README.md diff --git a/examples/gjf/README.md b/examples/gjf/README.md new file mode 100644 index 0000000000..e285ab8510 --- /dev/null +++ b/examples/gjf/README.md @@ -0,0 +1,13 @@ +# LAMMPS GJF-2GJ THERMOSTAT EXAMPLE W/ PYTHON + +## GJF-2GJ THERMOSTAT + +This directory contains the ingredients to run an NVT simulation using the GJF-2GJ thermostat. + +Example: +``` +NP=4 #number of processors +mpirun -np $NP lmp_mpi -in.argon -out.argon +``` + +## Required LAMMPS packages: MOLECULE package diff --git a/examples/python/gjf_python/README.md b/examples/python/gjf_python/README.md new file mode 100644 index 0000000000..707289f02d --- /dev/null +++ b/examples/python/gjf_python/README.md @@ -0,0 +1,18 @@ +# LAMMPS GJF-2GJ THERMOSTAT EXAMPLE W/ PYTHON + +## GJF-2GJ THERMOSTAT + +This directory contains a python script to run NVT simulations using the GJF-2GJ thermostat. +The script will vary the timestep and write thermodynamic output to screen. +This script has True/False options to change how you would like to dump/write your output. + +Example: +``` +NP=4 #number of processors +mpirun -np $NP python gjf.py +``` + +## Required LAMMPS packages: MOLECULE package +## LAMMPS COMPILE MODE: SHLIB +## LAMMPS OPTIONAL INSTALL: make install-python +## Required Python packages: mpi4py diff --git a/src/fix_langevin.cpp b/src/fix_langevin.cpp index 82366be4dd..4fcf7c6a1d 100644 --- a/src/fix_langevin.cpp +++ b/src/fix_langevin.cpp @@ -174,11 +174,6 @@ FixLangevin::FixLangevin(LAMMPS *lmp, int narg, char **arg) : // no need to set peratom_flag, b/c data is for internal use only if (gjfflag) { - //int mem = 6*atom->nmax*sizeof(double); - //if (hsflag) mem += 3*atom->nmax*sizeof(double); -// - //comm->maxexchange_fix = MAX(comm->maxexchange_fix, 0); - //comm->maxexchange_fix += MAX(1000, mem); nvalues = 3; grow_arrays(atom->nmax); From f9ed12be4f0ff547661a6dffe420b67c76655379 Mon Sep 17 00:00:00 2001 From: alxvov Date: Wed, 24 Jul 2019 23:21:07 +0000 Subject: [PATCH 061/192] modify line for spin_cubic, spin_none. edit docs a bit. --- doc/src/min_modify.txt | 12 ++-- doc/src/min_spin.txt | 17 ++++-- doc/src/minimize.txt | 8 +-- doc/src/neb_spin.txt | 6 +- examples/SPIN/spinmin/in.spinmin_cg.bfo | 8 +-- examples/SPIN/spinmin/in.spinmin_lbfgs.bfo | 6 +- src/MAKE/Makefile.serial | 2 +- src/SPIN/min_spin_oso_cg.cpp | 64 +++++++++++----------- src/SPIN/min_spin_oso_cg.h | 4 +- src/SPIN/min_spin_oso_lbfgs.cpp | 48 +++++++--------- src/SPIN/min_spin_oso_lbfgs.h | 2 +- 11 files changed, 89 insertions(+), 88 deletions(-) diff --git a/doc/src/min_modify.txt b/doc/src/min_modify.txt index c59e2b474b..9c4d7c8fcb 100644 --- a/doc/src/min_modify.txt +++ b/doc/src/min_modify.txt @@ -84,12 +84,12 @@ The choice of a line search algorithm for the {spin_oso_cg} and {spin_oso_lbfgs} styles can be specified via the {line} keyword. The {spin_cubic} and {spin_none} only make sense when one of those two minimization styles is declared. - -The {spin_cubic} keyword activates the line search procedure when -the {spin_oso_cg} algorithm is used. - -The {spin_none} keyword deactivates the line search procedure when -the {spin_oso_lbfgs} algorithm is used. +The {spin_cubic} performs the line search based on a cubic interpolation +of the energy along the search direction. The {spin_none} keyword +deactivates the line search procedure. +The {spin_none} is a default value for {line} keyword apart from the case when +single-replica calculations are performed with {spin_oso_lbfgs} that +uses {spin_cubic} line search. [Restrictions:] The line search procedure of styles {spin_oso_cg} and {spin_oso_lbfgs} cannot be used for magnetic diff --git a/doc/src/min_spin.txt b/doc/src/min_spin.txt index 2a85427c56..77dc008b3e 100644 --- a/doc/src/min_spin.txt +++ b/doc/src/min_spin.txt @@ -18,7 +18,7 @@ min_style spin_oso_lbfgs :pre [Examples:] min_style spin_oso_lbfgs -min_modify discrete_factor 10.0 line spin_none :pre +min_modify line spin_none discrete_factor 10.0 :pre [Description:] @@ -55,12 +55,21 @@ Style {spin_oso_cg} defines an orthogonal spin optimization (OSO) combined to a conjugate gradient (CG) algorithm. The "min_modify"_min_modify.html command can be used to couple the {spin_oso_cg} to a line search procedure, and to modify the -discretization factor {discrete_factor}. +discretization factor {discrete_factor}. +By defualt, the style {spin_oso_cg} does not employ line search procedure and +and uses the adaptive time-step technique in the same way as style {spin}. Style {spin_oso_lbfgs} defines an orthogonal spin optimization (OSO) combined to a limited-memory Broyden-Fletcher-Goldfarb-Shanno -(LBFGS) algorithm. -By default, style {spin_oso_lbfgs} uses a line search procedure. +(L-BFGS) algorithm. +By default, style {spin_oso_lbfgs} uses a line search procedure +based on cubic interpolation for +a single-replica calculation, and it does not use line search procedure +for a multireplica calculation (such as in case of GNEB calculation). +If the line search procedure is not used then the discrete factor defines +the maximum root mean squared rotation angle of spins by equation {pi/(5*Kappa)}. +The default value for Kappa is 10. + The "min_modify"_min_modify.html command can be used to deactivate the line search procedure, and to modify the discretization factor {discrete_factor}. diff --git a/doc/src/minimize.txt b/doc/src/minimize.txt index 1dc28acdef..1de925d6c8 100644 --- a/doc/src/minimize.txt +++ b/doc/src/minimize.txt @@ -106,10 +106,10 @@ the number of total force evaluations exceeds {maxeval} :ul NOTE: the "minimization style"_min_style.html {spin}, {spin_oso_cg}, and {spin_oso_lbfgs} replace the force tolerance {ftol} by a torque tolerance. -The minimization procedure stops if the 2-norm (length) of the -global torque vector (defined as the cross product between the -spins and their precession vectors omega) is less than {ftol}, -or if any of the other criteria are met. +The minimization procedure stops if the 2-norm (length) of the torque vector on atom +(defined as the cross product between the +atomic spin and its precession vectors omega) is less than {ftol}, +or if any of the other criteria are met. Torque have the same units as the energy. NOTE: You can also use the "fix halt"_fix_halt.html command to specify a general criterion for exiting a minimization, that is a calculation diff --git a/doc/src/neb_spin.txt b/doc/src/neb_spin.txt index 27e835276e..2fdfda8c66 100644 --- a/doc/src/neb_spin.txt +++ b/doc/src/neb_spin.txt @@ -59,7 +59,7 @@ performance speed-up you would see with one or more physical processors per replica. See the "Howto replica"_Howto_replica.html doc page for further discussion. -NOTE: As explained below, a GNEB calculation performs a damped dynamics +NOTE: As explained below, a GNEB calculation performs a minimization across all the replicas. One of the "spin"_min_spin.html style minimizers has to be defined in your input script. @@ -170,8 +170,8 @@ command is issued. :line A NEB calculation proceeds in two stages, each of which is a -minimization procedure, performed via damped dynamics. To enable -this, you must first define a damped spin dynamics +minimization procedure. To enable +this, you must first define a "min_style"_min_style.html, using either the {spin}, {spin_oso_cg}, or {spin_oso_lbfgs} style (see "min_spin"_min_spin.html for more information). diff --git a/examples/SPIN/spinmin/in.spinmin_cg.bfo b/examples/SPIN/spinmin/in.spinmin_cg.bfo index 901b04e5fd..776079edb8 100644 --- a/examples/SPIN/spinmin/in.spinmin_cg.bfo +++ b/examples/SPIN/spinmin/in.spinmin_cg.bfo @@ -42,13 +42,13 @@ variable magnorm equal c_out_mag[4] variable emag equal c_out_mag[5] variable tmag equal c_out_mag[6] -thermo 50 +thermo 100 thermo_style custom step time v_magnorm v_emag v_tmag temp etotal thermo_modify format float %20.15g compute outsp all property/atom spx spy spz sp fmx fmy fmz dump 1 all custom 50 dump.lammpstrj type x y z c_outsp[1] c_outsp[2] c_outsp[3] c_outsp[4] c_outsp[5] c_outsp[6] c_outsp[7] -min_style spin/oso_cg -min_modify discrete_factor 10.0 line spin_cubic -minimize 1.0e-10 1.0e-10 10000 1000 +min_style spin_oso_cg +# min_modify line spin_none discrete_factor 10.0 +minimize 1.0e-10 1.0e-7 1000 1000 diff --git a/examples/SPIN/spinmin/in.spinmin_lbfgs.bfo b/examples/SPIN/spinmin/in.spinmin_lbfgs.bfo index 4edd1a053e..ca600f1c2b 100644 --- a/examples/SPIN/spinmin/in.spinmin_lbfgs.bfo +++ b/examples/SPIN/spinmin/in.spinmin_lbfgs.bfo @@ -49,6 +49,6 @@ thermo_modify format float %20.15g compute outsp all property/atom spx spy spz sp fmx fmy fmz dump 1 all custom 50 dump.lammpstrj type x y z c_outsp[1] c_outsp[2] c_outsp[3] c_outsp[4] c_outsp[5] c_outsp[6] c_outsp[7] -min_style spin/oso_lbfgs -min_modify discrete_factor 10.0 line spin_none -minimize 1.0e-15 1.0e-10 10000 1000 +min_style spin_oso_lbfgs +min_modify line spin_cubic discrete_factor 10.0 +minimize 1.0e-15 1.0e-7 10000 1000 diff --git a/src/MAKE/Makefile.serial b/src/MAKE/Makefile.serial index 5954d97761..8628d2bb73 100644 --- a/src/MAKE/Makefile.serial +++ b/src/MAKE/Makefile.serial @@ -7,7 +7,7 @@ SHELL = /bin/sh # specify flags and libraries needed for your compiler CC = g++ -CCFLAGS = -g -O3 +CCFLAGS = -g -O3 -Wall SHFLAGS = -fPIC DEPFLAGS = -M diff --git a/src/SPIN/min_spin_oso_cg.cpp b/src/SPIN/min_spin_oso_cg.cpp index e43c51e3af..2bdc00d8ed 100644 --- a/src/SPIN/min_spin_oso_cg.cpp +++ b/src/SPIN/min_spin_oso_cg.cpp @@ -63,7 +63,7 @@ static const char cite_minstyle_spin_oso_cg[] = /* ---------------------------------------------------------------------- */ MinSpinOSO_CG::MinSpinOSO_CG(LAMMPS *lmp) : - Min(lmp), g_old(NULL), g_cur(NULL), p_s(NULL) + Min(lmp), g_old(NULL), g_cur(NULL), p_s(NULL), sp_copy(NULL) { if (lmp->citeme) lmp->citeme->add(cite_minstyle_spin_oso_cg); nlocal_max = 0; @@ -99,6 +99,13 @@ void MinSpinOSO_CG::init() Min::init(); + if (linestyle == 3 && nreplica == 1){ + use_line_search = 1; + } + else{ + use_line_search = 0; + } + dts = dt = update->dt; last_negative = update->ntimestep; @@ -132,13 +139,6 @@ void MinSpinOSO_CG::setup_style() int MinSpinOSO_CG::modify_param(int narg, char **arg) { - if (strcmp(arg[0],"line_search") == 0) { - if (narg < 2) error->all(FLERR,"Illegal min_modify command"); - use_line_search = force->numeric(FLERR,arg[1]); - if (nreplica > 1 && use_line_search) - error->all(FLERR,"Illegal fix_modify command, cannot use NEB and line search together"); - return 2; - } if (strcmp(arg[0],"discrete_factor") == 0) { if (narg < 2) error->all(FLERR,"Illegal fix_modify command"); discrete_factor = force->numeric(FLERR,arg[1]); @@ -181,7 +181,6 @@ int MinSpinOSO_CG::iterate(int maxiter) double der_e_cur_tmp = 0.0; if (nlocal_max < nlocal) { - nlocal_max = nlocal; local_iter = 0; nlocal_max = nlocal; memory->grow(g_old,3*nlocal_max,"min/spin/oso/cg:g_old"); @@ -205,8 +204,9 @@ int MinSpinOSO_CG::iterate(int maxiter) if (use_line_search) { // here we need to do line search - if (local_iter == 0) + if (local_iter == 0){ calc_gradient(); + } calc_search_direction(); der_e_cur = 0.0; @@ -219,7 +219,7 @@ int MinSpinOSO_CG::iterate(int maxiter) } for (int i = 0; i < nlocal; i++) for (int j = 0; j < 3; j++) - sp_copy[i][j] = sp[i][j]; + sp_copy[i][j] = sp[i][j]; eprevious = ecurrent; der_e_pr = der_e_cur; @@ -228,24 +228,15 @@ int MinSpinOSO_CG::iterate(int maxiter) else{ // here we don't do line search - // but use cutoff rotation angle // if gneb calc., nreplica > 1 // then calculate gradients and advance spins // of intermediate replicas only - - if (nreplica > 1) { - if(ireplica != 0 && ireplica != nreplica-1) calc_gradient(); calc_search_direction(); advance_spins(); - } else{ - calc_gradient(); - calc_search_direction(); - advance_spins(); - } + neval++; eprevious = ecurrent; ecurrent = energy_force(0); - neval++; } // energy tolerance criterion @@ -336,10 +327,18 @@ void MinSpinOSO_CG::calc_search_direction() double g2_global = 0.0; double g2old_global = 0.0; + double factor = 1.0; + + // for multiple replica do not move end points + if (nreplica > 1) + if (ireplica == 0 || ireplica == nreplica - 1) + factor = 0.0; + + if (local_iter == 0 || local_iter % 5 == 0){ // steepest descent direction for (int i = 0; i < 3 * nlocal; i++) { - p_s[i] = -g_cur[i]; - g_old[i] = g_cur[i]; + p_s[i] = -g_cur[i] * factor; + g_old[i] = g_cur[i] * factor; } } else { // conjugate direction for (int i = 0; i < 3 * nlocal; i++) { @@ -354,9 +353,9 @@ void MinSpinOSO_CG::calc_search_direction() MPI_Allreduce(&g2old,&g2old_global,1,MPI_DOUBLE,MPI_SUM,world); // Sum over all replicas. Good for GNEB. - if (update->multireplica == 1) { - g2 = g2_global; - g2old = g2old_global; + if (nreplica > 1) { + g2 = g2_global * factor; + g2old = g2old_global * factor; MPI_Allreduce(&g2,&g2_global,1,MPI_DOUBLE,MPI_SUM,universe->uworld); MPI_Allreduce(&g2old,&g2old_global,1,MPI_DOUBLE,MPI_SUM,universe->uworld); } @@ -364,8 +363,8 @@ void MinSpinOSO_CG::calc_search_direction() else beta = g2_global / g2old_global; // calculate conjugate direction for (int i = 0; i < 3 * nlocal; i++) { - p_s[i] = (beta * p_s[i] - g_cur[i]); - g_old[i] = g_cur[i]; + p_s[i] = (beta * p_s[i] - g_cur[i]) * factor; + g_old[i] = g_cur[i] * factor; } } @@ -380,8 +379,6 @@ void MinSpinOSO_CG::advance_spins() { int nlocal = atom->nlocal; double **sp = atom->sp; - double **fm = atom->fm; - double tdampx, tdampy, tdampz; double rot_mat[9]; // exponential of matrix made of search direction double s_new[3]; @@ -477,7 +474,7 @@ void MinSpinOSO_CG::rodrigues_rotation(const double *upp_tr, double *out) A = cos(theta); B = sin(theta); - D = 1 - A; + D = 1.0 - A; x = upp_tr[0]/theta; y = upp_tr[1]/theta; z = upp_tr[2]/theta; @@ -529,7 +526,7 @@ void MinSpinOSO_CG::make_step(double c, double *energy_and_der) double rot_mat[9]; // exponential of matrix made of search direction double s_new[3]; double **sp = atom->sp; - double der_e_cur_tmp = 0.0;; + double der_e_cur_tmp = 0.0; for (int i = 0; i < nlocal; i++) { @@ -629,7 +626,8 @@ int MinSpinOSO_CG::awc(double der_phi_0, double phi_0, double der_phi_j, double double delta = 0.1; double sigma = 0.9; - if ((phi_j<=phi_0+eps*fabs(phi_0)) && ((2.0*delta-1.0) * der_phi_0>=der_phi_j>=sigma*der_phi_0)) + if ((phi_j<=phi_0+eps*fabs(phi_0)) && + ((2.0*delta-1.0) * der_phi_0>=der_phi_j>=sigma*der_phi_0)) return 1; else return 0; diff --git a/src/SPIN/min_spin_oso_cg.h b/src/SPIN/min_spin_oso_cg.h index e50d1a69db..41253f440f 100644 --- a/src/SPIN/min_spin_oso_cg.h +++ b/src/SPIN/min_spin_oso_cg.h @@ -13,7 +13,7 @@ #ifdef MINIMIZE_CLASS -MinimizeStyle(spin/oso_cg, MinSpinOSO_CG) +MinimizeStyle(spin_oso_cg, MinSpinOSO_CG) #else @@ -39,8 +39,8 @@ class MinSpinOSO_CG: public Min { int ireplica,nreplica; // for neb double *spvec; // variables for atomic dof, as 1d vector double *fmvec; // variables for atomic dof, as 1d vector - double *g_cur; // current gradient vector double *g_old; // gradient vector at previous step + double *g_cur; // current gradient vector double *p_s; // search direction vector double **sp_copy; // copy of the spins int local_iter; // for neb diff --git a/src/SPIN/min_spin_oso_lbfgs.cpp b/src/SPIN/min_spin_oso_lbfgs.cpp index 0bd128367f..6aaeb7ca23 100644 --- a/src/SPIN/min_spin_oso_lbfgs.cpp +++ b/src/SPIN/min_spin_oso_lbfgs.cpp @@ -107,6 +107,13 @@ void MinSpinOSO_LBFGS::init() Min::init(); + if (linestyle != 4 && nreplica == 1){ + use_line_search = 1; + } + else{ + use_line_search = 0; + } + last_negative = update->ntimestep; // allocate tables @@ -143,14 +150,6 @@ void MinSpinOSO_LBFGS::setup_style() int MinSpinOSO_LBFGS::modify_param(int narg, char **arg) { - - if (strcmp(arg[0],"line_search") == 0) { - if (narg < 2) error->all(FLERR,"Illegal min_modify command"); - use_line_search = force->numeric(FLERR,arg[1]); - if (nreplica > 1 && use_line_search) - error->all(FLERR,"Illegal min_modify command, cannot use NEB and line search together"); - return 2; - } if (strcmp(arg[0],"discrete_factor") == 0) { if (narg < 2) error->all(FLERR,"Illegal min_modify command"); double discrete_factor; @@ -221,8 +220,11 @@ int MinSpinOSO_LBFGS::iterate(int maxiter) if (use_line_search) { // here we need to do line search - if (local_iter == 0) + if (local_iter == 0){ + eprevious = ecurrent; + ecurrent = energy_force(0); calc_gradient(); + } calc_search_direction(); der_e_cur = 0.0; @@ -248,19 +250,11 @@ int MinSpinOSO_LBFGS::iterate(int maxiter) // if gneb calc., nreplica > 1 // then calculate gradients and advance spins // of intermediate replicas only - - if (nreplica > 1) { - if(ireplica != 0 && ireplica != nreplica-1) - calc_gradient(); - calc_search_direction(); - advance_spins(); - } else{ - calc_gradient(); - calc_search_direction(); - advance_spins(); - } eprevious = ecurrent; ecurrent = energy_force(0); + calc_gradient(); + calc_search_direction(); + advance_spins(); neval++; } @@ -398,7 +392,7 @@ void MinSpinOSO_LBFGS::calc_search_direction() } MPI_Allreduce(&dyds, &dyds_global, 1, MPI_DOUBLE, MPI_SUM, world); - if (update->multireplica == 1) { + if (nreplica > 1) { dyds_global *= factor; dyds = dyds_global; MPI_Allreduce(&dyds, &dyds_global, 1,MPI_DOUBLE,MPI_SUM,universe->uworld); @@ -437,7 +431,7 @@ void MinSpinOSO_LBFGS::calc_search_direction() sq += ds[c_ind][i] * q[i]; } MPI_Allreduce(&sq,&sq_global,1,MPI_DOUBLE,MPI_SUM,world); - if (update->multireplica == 1) { + if (nreplica > 1) { sq_global *= factor; sq = sq_global; MPI_Allreduce(&sq,&sq_global,1,MPI_DOUBLE,MPI_SUM,universe->uworld); @@ -460,7 +454,7 @@ void MinSpinOSO_LBFGS::calc_search_direction() yy += dy[m_index][i] * dy[m_index][i]; } MPI_Allreduce(&yy,&yy_global,1,MPI_DOUBLE,MPI_SUM,world); - if (update->multireplica == 1) { + if (nreplica > 1) { yy_global *= factor; yy = yy_global; MPI_Allreduce(&yy,&yy_global,1,MPI_DOUBLE,MPI_SUM,universe->uworld); @@ -493,7 +487,7 @@ void MinSpinOSO_LBFGS::calc_search_direction() } MPI_Allreduce(&yr,&yr_global,1,MPI_DOUBLE,MPI_SUM,world); - if (update->multireplica == 1) { + if (nreplica > 1) { yr_global *= factor; yr = yr_global; MPI_Allreduce(&yr,&yr_global,1,MPI_DOUBLE,MPI_SUM,universe->uworld); @@ -668,7 +662,7 @@ void MinSpinOSO_LBFGS::make_step(double c, double *energy_and_der) double rot_mat[9]; // exponential of matrix made of search direction double s_new[3]; double **sp = atom->sp; - double der_e_cur_tmp = 0.0;; + double der_e_cur_tmp = 0.0; for (int i = 0; i < nlocal; i++) { @@ -784,12 +778,12 @@ double MinSpinOSO_LBFGS::maximum_rotation(double *p) for (int i = 0; i < 3 * nlocal; i++) norm2 += p[i] * p[i]; MPI_Allreduce(&norm2,&norm2_global,1,MPI_DOUBLE,MPI_SUM,world); - if (update->multireplica == 1) { + if (nreplica > 1) { norm2 = norm2_global; MPI_Allreduce(&norm2,&norm2_global,1,MPI_DOUBLE,MPI_SUM,universe->uworld); } MPI_Allreduce(&nlocal,&ntotal,1,MPI_INT,MPI_SUM,world); - if (update->multireplica == 1) { + if (nreplica > 1) { nlocal = ntotal; MPI_Allreduce(&nlocal,&ntotal,1,MPI_INT,MPI_SUM,universe->uworld); } diff --git a/src/SPIN/min_spin_oso_lbfgs.h b/src/SPIN/min_spin_oso_lbfgs.h index d74898aa8c..3071bacc35 100644 --- a/src/SPIN/min_spin_oso_lbfgs.h +++ b/src/SPIN/min_spin_oso_lbfgs.h @@ -13,7 +13,7 @@ #ifdef MINIMIZE_CLASS -MinimizeStyle(spin/oso_lbfgs, MinSpinOSO_LBFGS) +MinimizeStyle(spin_oso_lbfgs, MinSpinOSO_LBFGS) #else From 13f4fe186be64b10ed387f716dcf6cfb91a904c7 Mon Sep 17 00:00:00 2001 From: casievers Date: Wed, 24 Jul 2019 16:30:02 -0700 Subject: [PATCH 062/192] Updated examples/gjf/README.md --- examples/gjf/README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/examples/gjf/README.md b/examples/gjf/README.md index e285ab8510..79ef4cd2e1 100644 --- a/examples/gjf/README.md +++ b/examples/gjf/README.md @@ -1,4 +1,4 @@ -# LAMMPS GJF-2GJ THERMOSTAT EXAMPLE W/ PYTHON +# LAMMPS GJF-2GJ THERMOSTAT EXAMPLE ## GJF-2GJ THERMOSTAT From 14d38596050af99f9b3bbeef49bf229b18031b41 Mon Sep 17 00:00:00 2001 From: casievers Date: Wed, 24 Jul 2019 20:08:00 -0700 Subject: [PATCH 063/192] Added GJF-2GJ authors --- src/fix_langevin.cpp | 2 ++ 1 file changed, 2 insertions(+) diff --git a/src/fix_langevin.cpp b/src/fix_langevin.cpp index bfd170262e..ea0929a236 100644 --- a/src/fix_langevin.cpp +++ b/src/fix_langevin.cpp @@ -14,6 +14,8 @@ /* ---------------------------------------------------------------------- Contributing authors: Carolyn Phillips (U Mich), reservoir energy tally Aidan Thompson (SNL) GJF formulation + Charles Sievers (UC Davis) GJF-2GJ Implementation + Niels Gronbech-Jensen (UC Davis) GJF-2GJ Formulation ------------------------------------------------------------------------- */ #include From cc96ea1ded97f45f394bc9abec28b5e649a3368b Mon Sep 17 00:00:00 2001 From: casievers Date: Thu, 25 Jul 2019 15:23:01 -0700 Subject: [PATCH 064/192] added respa compatability, and simplified examples --- .gitignore | 3 + examples/gjf/README.md | 2 +- examples/gjf/in.argon | 162 -------------------------------------- examples/gjf/in.gjf.vfull | 23 ++++++ examples/gjf/in.gjf.vhalf | 23 ++++++ 5 files changed, 50 insertions(+), 163 deletions(-) delete mode 100644 examples/gjf/in.argon create mode 100644 examples/gjf/in.gjf.vfull create mode 100644 examples/gjf/in.gjf.vhalf diff --git a/.gitignore b/.gitignore index f9dda49da6..3e4ebcda98 100644 --- a/.gitignore +++ b/.gitignore @@ -43,3 +43,6 @@ Thumbs.db /Makefile /cmake_install.cmake /lmp + +#python example +/example/python/gjf_python diff --git a/examples/gjf/README.md b/examples/gjf/README.md index 79ef4cd2e1..e6886cb2dd 100644 --- a/examples/gjf/README.md +++ b/examples/gjf/README.md @@ -7,7 +7,7 @@ This directory contains the ingredients to run an NVT simulation using the GJF-2 Example: ``` NP=4 #number of processors -mpirun -np $NP lmp_mpi -in.argon -out.argon +mpirun -np $NP lmp_mpi -in.gjf.vhalf ``` ## Required LAMMPS packages: MOLECULE package diff --git a/examples/gjf/in.argon b/examples/gjf/in.argon deleted file mode 100644 index 271882c665..0000000000 --- a/examples/gjf/in.argon +++ /dev/null @@ -1,162 +0,0 @@ -###############################mm -# Atom style - charge/vdw/bonded# -################################# -atom_style full - -############################################## -#Units Metal : eV - ps - angstrom - bar# -# Real : kcal/mol - fs - angstrom - atm# -############################################## -units metal - -############ -#Run number# -############ -variable run_no equal 0 # is it a restart? -variable res_no equal ${run_no}-1 # restart file number - -####################################### -#Random Seeds and Domain Decomposition# -####################################### -variable iseed0 equal 2357 -variable iseed1 equal 26488 -variable iseed2 equal 10669 -processors * * * - -########### -#Data File# -########### -variable inpfile string argon.lmp -variable resfile string final_restart.${res_no} -variable ff_file string ff-argon.lmp - -########## -#Run Type# -########## -variable minimise equal 0 #Energy Minimization -variable md equal 1 #Plain MD - -############################### -#Molecular Dynamics Parameters# -############################### -variable run_no equal 0 # is it a restart? - -variable ens equal 9 # ensemble (0=nve, 1=nvt, 2=npt, 3=ber, 4=lang, 5=stoc, 6=vres, 7=stoch, 8=gjf) -variable ts equal 0.120 # simulation timestep (time units) -variable nequil equal 0 # number of equilibration steps -variable nsteps equal 200000 # number of MD steps -#variable nsteps equal 20 # number of MD steps - -variable temp_s equal 10 # starting temperature -variable temp_f equal 10 # final simulation temperature -variable trel equal 1 # thermostat relaxation time -variable tscale equal 1 # thermostat relaxation freq - vel rescaling only -variable deltat equal 1 # maximum temperature change - vel rescaling only - -variable npttype string iso # type of NPT (iso, aniso, tri, z...) -variable pres equal 1.01325 # pressure (NPT runs only) -variable prel equal 1.0 # barostat relaxation time - -neighbor 1 bin - -################### -#Output Parameters# -################### -variable ntraj equal 1000 # trajectory output frequency - all system -variable ntraj_s equal -100 # trajectory output frequency - solute only -variable nthermo equal 200 # thermodynamic data output frequency - -################################ -#Energy Minimization Parameters# -################################ -variable mtraj equal 1 # trajectory output frequency - all system -variable etol equal 1e-5 # % change in energy -variable ftol equal 1e-5 # max force threshold (force units) -variable maxiter equal 10000 # max # of iterations - -######################## -#3D Periodic Simulation# -######################## -boundary p p p - -############################# -#Reading the input structure# -############################# -if "${run_no} == 0" then "read_data ${inpfile}" else "read_restart ${resfile}" - -############# -#Force Field# -############# -include ${ff_file} - -###################### -#Thermodynamic Output# -###################### -variable str_basic string 'step time pe temp press' - -#MD ensemble (0=nve, 1=nvt, 2=npt, 3=ber, 4=lang, 5=stoc, 6=vres) -variable str_ens string ' ' -if "${ens} == 0" then "variable str_ens string 'etotal'" -if "${ens} == 2" then "variable str_ens string 'vol pxx pyy pzz cella cellb cellc cellakpha cellbeta cellgamma'" - -#Variable for a gulp friend output -if "${ens} >= 0" then "thermo_style custom time temp pe etotal press vol cpu" & - "thermo ${nthermo}" & - "thermo_modify flush yes" - -##################### -#Energy Minimization# -##################### -if "${minimise} <= 0 || ${run_no} > 0" then "jump SELF end_minimise" - print "Doing CG minimisation" - dump mdcd all dcd ${mtraj} min.dcd - dump_modify mdcd unwrap yes - min_style cg - min_modify line quadratic - minimize ${etol} ${ftol} ${maxiter} ${maxiter} - reset_timestep 0 - undump mdcd -label end_minimise - -################ -#Timestep in ps# -################ -timestep ${ts} - -############## -#Restart file# -############## -restart 100000 restart.1 restart.2 - -################### -#Trajectory output# -################### -#dump xyz all atom 1000 silicon.lammpstrj - -if "${ntraj} > 0" then & - "dump 1 all dcd ${ntraj} trajectory.${run_no}.dcd" & - "dump_modify 1 unwrap yes" - -fix mom all momentum 1 linear 1 1 1 - -############################################################### -#Ensembles (0=nve,1=nvt, 2=npt, 3=ber, 4=lang, 5=stoc, 6=vres)# -############################################################### -if "${md} > 0" then 'print "Setting up the ensembles"' & - 'if "${run_no} == 0" then "velocity all create ${temp_s} ${iseed0} mom yes dist gaussian"' & - 'if "${ens} == 0" then "fix nve all nve"' & - 'if "${ens} == 1" then "fix nvt all nvt temp ${temp_s} ${temp_f} ${trel} tchain 5"' & - 'if "${ens} == 2" then "fix npt all npt temp ${temp_s} ${temp_f} ${trel} ${npttype} ${pres} ${pres} ${prel} tchain 5 pchain 5 mtk yes"' & - 'if "${ens} == 3" then "fix nve all nve" "fix ber all temp/berendsen ${temp_s} ${temp_f} ${trel}"' & - 'if "${ens} == 4" then "fix nve all nve" "fix lang all langevin ${temp_s} ${temp_f} ${trel} ${iseed1} tally yes zero yes"' & - 'if "${ens} == 5" then "fix nve all nve" "fix stoch all temp/csvr ${temp_s} ${temp_f} ${trel} ${iseed1}"' & - 'if "${ens} == 6" then "fix nve all nve" "fix stoch all temp/csld ${temp_s} ${temp_f} ${trel} ${iseed1}"' & - 'if "${ens} == 7" then "fix nve all nve" "fix vres all temp/rescale ${tscale} ${temp_s} ${temp_f} ${tmin} ${tmax}"' & - 'if "${ens} == 8" then "fix nve all nve" "fix lang all langevin ${temp_s} ${temp_f} ${trel} ${iseed1} gjf yes"' & - 'if "${ens} == 9" then "fix nve all nve" "fix lang all langevin ${temp_s} ${temp_f} ${trel} ${iseed1} gjf yes halfstep yes"' - -if "${md} > 0" then "print 'Doing Molecular dynamics'" & - "run ${nsteps}" & - "write_restart final_restart.${run_no}" - - diff --git a/examples/gjf/in.gjf.vfull b/examples/gjf/in.gjf.vfull new file mode 100644 index 0000000000..19420e22ca --- /dev/null +++ b/examples/gjf/in.gjf.vfull @@ -0,0 +1,23 @@ +# GJF-2GJ thermostat + +units metal +atom_style full + +boundary p p p +read_data argon.lmp + +include ff-argon.lmp + +velocity all create 10 2357 mom yes dist gaussian + +neighbor 1 bin + +timestep 0.1 + +fix nve all nve +fix lang all langevin 10 10 1 26488 gjf vfull + +thermo 200 +run 50000 + + diff --git a/examples/gjf/in.gjf.vhalf b/examples/gjf/in.gjf.vhalf new file mode 100644 index 0000000000..74e2089595 --- /dev/null +++ b/examples/gjf/in.gjf.vhalf @@ -0,0 +1,23 @@ +# GJF-2GJ thermostat + +units metal +atom_style full + +boundary p p p +read_data argon.lmp + +include ff-argon.lmp + +velocity all create 10 2357 mom yes dist gaussian + +neighbor 1 bin + +timestep 0.1 + +fix nve all nve +fix lang all langevin 10 10 1 26488 gjf vhalf + +thermo 200 +run 50000 + + From 883f6d1e8d6eb18e7ab520a1a7845ec41f31607a Mon Sep 17 00:00:00 2001 From: julient31 Date: Fri, 26 Jul 2019 09:06:43 -0600 Subject: [PATCH 065/192] Commit1 JT 072619 - corrected warnings in cg and lbfgs - removed unused variables in spin/dipole pair styles --- src/SPIN/min_spin_oso_cg.cpp | 6 ++++-- src/SPIN/min_spin_oso_lbfgs.cpp | 12 ++++++------ src/SPIN/min_spin_oso_lbfgs.h | 20 ++++++++++---------- src/SPIN/pair_spin_dipole_cut.cpp | 2 +- src/SPIN/pair_spin_dipole_long.cpp | 5 +---- 5 files changed, 22 insertions(+), 23 deletions(-) diff --git a/src/SPIN/min_spin_oso_cg.cpp b/src/SPIN/min_spin_oso_cg.cpp index 2bdc00d8ed..1c91fa1500 100644 --- a/src/SPIN/min_spin_oso_cg.cpp +++ b/src/SPIN/min_spin_oso_cg.cpp @@ -512,7 +512,8 @@ void MinSpinOSO_CG::rodrigues_rotation(const double *upp_tr, double *out) void MinSpinOSO_CG::vm3(const double *m, const double *v, double *out) { for(int i = 0; i < 3; i++){ - out[i] *= 0.0; + //out[i] *= 0.0; + out[i] = 0.0; for(int j = 0; j < 3; j++) out[i] += *(m + 3 * j + i) * v[j]; } @@ -627,7 +628,8 @@ int MinSpinOSO_CG::awc(double der_phi_0, double phi_0, double der_phi_j, double double sigma = 0.9; if ((phi_j<=phi_0+eps*fabs(phi_0)) && - ((2.0*delta-1.0) * der_phi_0>=der_phi_j>=sigma*der_phi_0)) + ((2.0*delta-1.0) * der_phi_0>=der_phi_j) && + (der_phi_j>=sigma*der_phi_0)) return 1; else return 0; diff --git a/src/SPIN/min_spin_oso_lbfgs.cpp b/src/SPIN/min_spin_oso_lbfgs.cpp index 6aaeb7ca23..b9315d706e 100644 --- a/src/SPIN/min_spin_oso_lbfgs.cpp +++ b/src/SPIN/min_spin_oso_lbfgs.cpp @@ -63,7 +63,7 @@ static const char cite_minstyle_spin_oso_lbfgs[] = /* ---------------------------------------------------------------------- */ MinSpinOSO_LBFGS::MinSpinOSO_LBFGS(LAMMPS *lmp) : - Min(lmp), g_old(NULL), g_cur(NULL), p_s(NULL), ds(NULL), dy(NULL), rho(NULL), sp_copy(NULL) + Min(lmp), g_old(NULL), g_cur(NULL), p_s(NULL), rho(NULL), ds(NULL), dy(NULL), sp_copy(NULL) { if (lmp->citeme) lmp->citeme->add(cite_minstyle_spin_oso_lbfgs); nlocal_max = 0; @@ -345,7 +345,6 @@ void MinSpinOSO_LBFGS::calc_search_direction() double sq_global = 0.0; double yy_global = 0.0; double yr_global = 0.0; - double beta_global = 0.0; int m_index = local_iter % num_mem; // memory index int c_ind = 0; @@ -520,8 +519,6 @@ void MinSpinOSO_LBFGS::advance_spins() { int nlocal = atom->nlocal; double **sp = atom->sp; - double **fm = atom->fm; - double tdampx, tdampy, tdampz; double rot_mat[9]; // exponential of matrix made of search direction double s_new[3]; @@ -648,7 +645,8 @@ void MinSpinOSO_LBFGS::rodrigues_rotation(const double *upp_tr, double *out) void MinSpinOSO_LBFGS::vm3(const double *m, const double *v, double *out) { for(int i = 0; i < 3; i++){ - out[i] *= 0.0; + //out[i] *= 0.0; + out[i] = 0.0; for(int j = 0; j < 3; j++) out[i] += *(m + 3 * j + i) * v[j]; } @@ -762,7 +760,9 @@ int MinSpinOSO_LBFGS::awc(double der_phi_0, double phi_0, double der_phi_j, doub double delta = 0.1; double sigma = 0.9; - if ((phi_j<=phi_0+eps*fabs(phi_0)) && ((2.0*delta-1.0) * der_phi_0>=der_phi_j>=sigma*der_phi_0)) + if ((phi_j<=phi_0+eps*fabs(phi_0)) && + ((2.0*delta-1.0) * der_phi_0>=der_phi_j) && + (der_phi_j>=sigma*der_phi_0)) return 1; else return 0; diff --git a/src/SPIN/min_spin_oso_lbfgs.h b/src/SPIN/min_spin_oso_lbfgs.h index 3071bacc35..204f6bf058 100644 --- a/src/SPIN/min_spin_oso_lbfgs.h +++ b/src/SPIN/min_spin_oso_lbfgs.h @@ -34,14 +34,13 @@ class MinSpinOSO_LBFGS: public Min { void reset_vectors(); int iterate(int); private: - int ireplica,nreplica; // for neb + int ireplica,nreplica; // for neb double *spvec; // variables for atomic dof, as 1d vector double *fmvec; // variables for atomic dof, as 1d vector - double *g_cur; // current gradient vector - double *g_old; // gradient vector at previous step + double *g_old; // gradient vector at previous step + double *g_cur; // current gradient vector double *p_s; // search direction vector - double **sp_copy; // copy of the spins - int local_iter; // for neb + int local_iter; // for neb int nlocal_max; // max value of nlocal (for size of lists) void advance_spins(); @@ -54,14 +53,15 @@ class MinSpinOSO_LBFGS: public Min { int awc(double, double, double, double); void make_step(double, double *); double max_torque(); - double der_e_cur; // current derivative along search dir. - double der_e_pr; // previous derivative along search dir. - int use_line_search; // use line search or not. + double der_e_cur; // current derivative along search dir. + double der_e_pr; // previous derivative along search dir. + int use_line_search; // use line search or not. double maxepsrot; - double **ds; // change in rotation matrix between two iterations, da - double **dy; // change in gradients between two iterations, dg double *rho; // estimation of curvature + double **ds; // change in rotation matrix between two iterations, da + double **dy; // change in gradients between two iterations, dg + double **sp_copy; // copy of the spins int num_mem; // number of stored steps bigint last_negative; }; diff --git a/src/SPIN/pair_spin_dipole_cut.cpp b/src/SPIN/pair_spin_dipole_cut.cpp index 4ff198488a..e6b9a59ad9 100644 --- a/src/SPIN/pair_spin_dipole_cut.cpp +++ b/src/SPIN/pair_spin_dipole_cut.cpp @@ -323,7 +323,7 @@ void PairSpinDipoleCut::compute(int eflag, int vflag) void PairSpinDipoleCut::compute_single_pair(int ii, double fmi[3]) { int j,jnum,itype,jtype,ntypes; - int *ilist,*jlist,*numneigh,**firstneigh; + int *jlist,*numneigh,**firstneigh; double rsq,rinv,r2inv,r3inv,local_cut2; double xi[3],rij[3],eij[3],spi[4],spj[4]; diff --git a/src/SPIN/pair_spin_dipole_long.cpp b/src/SPIN/pair_spin_dipole_long.cpp index e3575a6a07..febc6f924c 100644 --- a/src/SPIN/pair_spin_dipole_long.cpp +++ b/src/SPIN/pair_spin_dipole_long.cpp @@ -355,10 +355,9 @@ void PairSpinDipoleLong::compute(int eflag, int vflag) void PairSpinDipoleLong::compute_single_pair(int ii, double fmi[3]) { - //int i,j,jj,jnum,itype,jtype; int j,jj,jnum,itype,jtype,ntypes; int k,locflag; - int *ilist,*jlist,*numneigh,**firstneigh; + int *jlist,*numneigh,**firstneigh; double r,rinv,r2inv,rsq,grij,expm2,t,erfc; double local_cut2,pre1,pre2,pre3; double bij[4],xi[3],rij[3],eij[3],spi[4],spj[4]; @@ -368,7 +367,6 @@ void PairSpinDipoleLong::compute_single_pair(int ii, double fmi[3]) double **sp = atom->sp; double **fm_long = atom->fm_long; - ilist = list->ilist; numneigh = list->numneigh; firstneigh = list->firstneigh; @@ -406,7 +404,6 @@ void PairSpinDipoleLong::compute_single_pair(int ii, double fmi[3]) // computation of the exchange interaction // loop over neighbors of atom i - //i = ilist[ii]; xi[0] = x[ii][0]; xi[1] = x[ii][1]; xi[2] = x[ii][2]; From 7e5c293a233b7f8e5b7095559452b92fb4c7eddd Mon Sep 17 00:00:00 2001 From: alxvov Date: Fri, 26 Jul 2019 16:30:38 +0000 Subject: [PATCH 066/192] delete comment. Add line option --- src/SPIN/min_spin_oso_cg.cpp | 1 - src/SPIN/min_spin_oso_lbfgs.cpp | 3 +-- src/min.cpp | 2 ++ 3 files changed, 3 insertions(+), 3 deletions(-) diff --git a/src/SPIN/min_spin_oso_cg.cpp b/src/SPIN/min_spin_oso_cg.cpp index 1c91fa1500..f95bffb947 100644 --- a/src/SPIN/min_spin_oso_cg.cpp +++ b/src/SPIN/min_spin_oso_cg.cpp @@ -512,7 +512,6 @@ void MinSpinOSO_CG::rodrigues_rotation(const double *upp_tr, double *out) void MinSpinOSO_CG::vm3(const double *m, const double *v, double *out) { for(int i = 0; i < 3; i++){ - //out[i] *= 0.0; out[i] = 0.0; for(int j = 0; j < 3; j++) out[i] += *(m + 3 * j + i) * v[j]; diff --git a/src/SPIN/min_spin_oso_lbfgs.cpp b/src/SPIN/min_spin_oso_lbfgs.cpp index b9315d706e..ce459586bf 100644 --- a/src/SPIN/min_spin_oso_lbfgs.cpp +++ b/src/SPIN/min_spin_oso_lbfgs.cpp @@ -645,7 +645,6 @@ void MinSpinOSO_LBFGS::rodrigues_rotation(const double *upp_tr, double *out) void MinSpinOSO_LBFGS::vm3(const double *m, const double *v, double *out) { for(int i = 0; i < 3; i++){ - //out[i] *= 0.0; out[i] = 0.0; for(int j = 0; j < 3; j++) out[i] += *(m + 3 * j + i) * v[j]; @@ -760,7 +759,7 @@ int MinSpinOSO_LBFGS::awc(double der_phi_0, double phi_0, double der_phi_j, doub double delta = 0.1; double sigma = 0.9; - if ((phi_j<=phi_0+eps*fabs(phi_0)) && + if ((phi_j<=phi_0+eps*fabs(phi_0)) && ((2.0*delta-1.0) * der_phi_0>=der_phi_j) && (der_phi_j>=sigma*der_phi_0)) return 1; diff --git a/src/min.cpp b/src/min.cpp index 2a42a444a0..a903fa98d8 100644 --- a/src/min.cpp +++ b/src/min.cpp @@ -653,6 +653,8 @@ void Min::modify_params(int narg, char **arg) if (strcmp(arg[iarg+1],"backtrack") == 0) linestyle = 0; else if (strcmp(arg[iarg+1],"quadratic") == 0) linestyle = 1; else if (strcmp(arg[iarg+1],"forcezero") == 0) linestyle = 2; + else if (strcmp(arg[iarg+1],"spin_cubic") == 0) linestyle = 3; + else if (strcmp(arg[iarg+1],"spin_none") == 0) linestyle = 4; else error->all(FLERR,"Illegal min_modify command"); iarg += 2; } else { From c5b7a36eebe3f8a886c902d53d71486920ecea2d Mon Sep 17 00:00:00 2001 From: julient31 Date: Fri, 26 Jul 2019 17:33:49 -0600 Subject: [PATCH 067/192] Commit JT 072619 - added a min_style option for norm type (euclidean or Max) - adapted and tested spin minimizers - adapted (net tested) regular minimizers --- src/SPIN/min_spin.cpp | 90 +++++-------------------------- src/SPIN/min_spin.h | 2 - src/SPIN/min_spin_oso_cg.cpp | 94 +++++++++++++-------------------- src/SPIN/min_spin_oso_cg.h | 72 ++++++++++++------------- src/SPIN/min_spin_oso_lbfgs.cpp | 61 ++++++++------------- src/SPIN/min_spin_oso_lbfgs.h | 74 +++++++++++++------------- src/min.cpp | 74 ++++++++++++++++++++++++++ src/min.h | 14 +++-- src/min_cg.cpp | 12 ++++- src/min_fire.cpp | 12 ++++- src/min_hftn.cpp | 4 ++ src/min_quickmin.cpp | 12 ++++- src/min_sd.cpp | 3 +- 13 files changed, 266 insertions(+), 258 deletions(-) diff --git a/src/SPIN/min_spin.cpp b/src/SPIN/min_spin.cpp index f56c9f0d96..d229927c29 100644 --- a/src/SPIN/min_spin.cpp +++ b/src/SPIN/min_spin.cpp @@ -119,7 +119,7 @@ void MinSpin::reset_vectors() int MinSpin::iterate(int maxiter) { bigint ntimestep; - double fmdotfm; + double fmdotfm,fmsq,fmsqall; int flag,flagall; for (int iter = 0; iter < maxiter; iter++) { @@ -166,8 +166,20 @@ int MinSpin::iterate(int maxiter) // magnetic torque tolerance criterion // sync across replicas if running multi-replica minimization + fmdotfm = fmsq = fmsqall = 0.0; if (update->ftol > 0.0) { - fmdotfm = max_torque(); + if (normstyle == 1) { // max torque norm + fmsq = max_torque(); + fmsqall = fmsq; + if (update->multireplica == 0) + MPI_Allreduce(&fmsq,&fmsqall,1,MPI_INT,MPI_MAX,universe->uworld); + } else { // Euclidean torque norm + fmsq = total_torque(); + fmsqall = fmsq; + if (update->multireplica == 0) + MPI_Allreduce(&fmsq,&fmsqall,1,MPI_INT,MPI_SUM,universe->uworld); + } + fmdotfm = fmsqall*fmsqall; if (update->multireplica == 0) { if (fmdotfm < update->ftol*update->ftol) return FTOL; } else { @@ -297,77 +309,3 @@ void MinSpin::advance_spins(double dts) // because no need for simplecticity } } - -/* ---------------------------------------------------------------------- - compute and return ||mag. torque||_2^2 -------------------------------------------------------------------------- */ - -double MinSpin::fmnorm_sqr() -{ - int nlocal = atom->nlocal; - double tx,ty,tz; - double **sp = atom->sp; - double **fm = atom->fm; - - // calc. magnetic torques - - double local_norm2_sqr = 0.0; - for (int i = 0; i < nlocal; i++) { - tx = (fm[i][1]*sp[i][2] - fm[i][2]*sp[i][1]); - ty = (fm[i][2]*sp[i][0] - fm[i][0]*sp[i][2]); - tz = (fm[i][0]*sp[i][1] - fm[i][1]*sp[i][0]); - - local_norm2_sqr += tx*tx + ty*ty + tz*tz; - } - - // no extra atom calc. for spins - - if (nextra_atom) - error->all(FLERR,"extra atom option not available yet"); - - double norm2_sqr = 0.0; - MPI_Allreduce(&local_norm2_sqr,&norm2_sqr,1,MPI_DOUBLE,MPI_SUM,world); - - return norm2_sqr; -} - -/* ---------------------------------------------------------------------- - compute and return max_i||mag. torque_i||_2 -------------------------------------------------------------------------- */ - -double MinSpin::max_torque() -{ - double fmsq,fmaxsqone,fmaxsqloc,fmaxsqall; - int nlocal = atom->nlocal; - double hbar = force->hplanck/MY_2PI; - double tx,ty,tz; - double **sp = atom->sp; - double **fm = atom->fm; - - fmsq = fmaxsqone = fmaxsqloc = fmaxsqall = 0.0; - for (int i = 0; i < nlocal; i++) { - tx = fm[i][1] * sp[i][2] - fm[i][2] * sp[i][1]; - ty = fm[i][2] * sp[i][0] - fm[i][0] * sp[i][2]; - tz = fm[i][0] * sp[i][1] - fm[i][1] * sp[i][0]; - fmsq = tx * tx + ty * ty + tz * tz; - fmaxsqone = MAX(fmaxsqone,fmsq); - } - - // finding max fm on this replica - - fmaxsqloc = fmaxsqone; - MPI_Allreduce(&fmaxsqone,&fmaxsqloc,1,MPI_DOUBLE,MPI_MAX,world); - - // finding max fm over all replicas, if necessary - // this communicator would be invalid for multiprocess replicas - - fmaxsqall = fmaxsqloc; - if (update->multireplica == 1) { - fmaxsqall = fmaxsqloc; - MPI_Allreduce(&fmaxsqloc,&fmaxsqall,1,MPI_DOUBLE,MPI_MAX,universe->uworld); - } - - // multiply it by hbar so that units are in eV - - return sqrt(fmaxsqall) * hbar; -} diff --git a/src/SPIN/min_spin.h b/src/SPIN/min_spin.h index d6d49203d5..f2df81e58c 100644 --- a/src/SPIN/min_spin.h +++ b/src/SPIN/min_spin.h @@ -35,8 +35,6 @@ class MinSpin : public Min { int iterate(int); double evaluate_dt(); void advance_spins(double); - double fmnorm_sqr(); - double max_torque(); private: diff --git a/src/SPIN/min_spin_oso_cg.cpp b/src/SPIN/min_spin_oso_cg.cpp index 1c91fa1500..16a95c5c02 100644 --- a/src/SPIN/min_spin_oso_cg.cpp +++ b/src/SPIN/min_spin_oso_cg.cpp @@ -29,6 +29,7 @@ #include "universe.h" #include "atom.h" #include "citeme.h" +#include "comm.h" #include "force.h" #include "update.h" #include "output.h" @@ -99,6 +100,13 @@ void MinSpinOSO_CG::init() Min::init(); + // warning if line_search combined to gneb + + if ((nreplica >= 1) && (linestyle != 4) && (comm->me == 0)) + error->warning(FLERR,"Line search incompatible gneb"); + + // set back use_line_search to 0 if more than one replica + if (linestyle == 3 && nreplica == 1){ use_line_search = 1; } @@ -175,7 +183,7 @@ int MinSpinOSO_CG::iterate(int maxiter) { int nlocal = atom->nlocal; bigint ntimestep; - double fmdotfm; + double fmdotfm,fmsq,fmsqall; int flag, flagall; double **sp = atom->sp; double der_e_cur_tmp = 0.0; @@ -261,8 +269,20 @@ int MinSpinOSO_CG::iterate(int maxiter) // magnetic torque tolerance criterion // sync across replicas if running multi-replica minimization + fmdotfm = fmsq = fmsqall = 0.0; if (update->ftol > 0.0) { - fmdotfm = max_torque(); + if (normstyle == 1) { // max torque norm + fmsq = max_torque(); + fmsqall = fmsq; + if (update->multireplica == 0) + MPI_Allreduce(&fmsq,&fmsqall,1,MPI_INT,MPI_MAX,universe->uworld); + } else { // Euclidean torque norm + fmsq = total_torque(); + fmsqall = fmsq; + if (update->multireplica == 0) + MPI_Allreduce(&fmsq,&fmsqall,1,MPI_INT,MPI_SUM,universe->uworld); + } + fmdotfm = fmsqall*fmsqall; if (update->multireplica == 0) { if (fmdotfm < update->ftol*update->ftol) return FTOL; } else { @@ -353,6 +373,7 @@ void MinSpinOSO_CG::calc_search_direction() MPI_Allreduce(&g2old,&g2old_global,1,MPI_DOUBLE,MPI_SUM,world); // Sum over all replicas. Good for GNEB. + if (nreplica > 1) { g2 = g2_global * factor; g2old = g2old_global * factor; @@ -361,7 +382,9 @@ void MinSpinOSO_CG::calc_search_direction() } if (fabs(g2_global) < 1.0e-60) beta = 0.0; else beta = g2_global / g2old_global; + // calculate conjugate direction + for (int i = 0; i < 3 * nlocal; i++) { p_s[i] = (beta * p_s[i] - g_cur[i]) * factor; g_old[i] = g_cur[i] * factor; @@ -379,7 +402,7 @@ void MinSpinOSO_CG::advance_spins() { int nlocal = atom->nlocal; double **sp = atom->sp; - double rot_mat[9]; // exponential of matrix made of search direction + double rot_mat[9]; // exponential of matrix made of search direction double s_new[3]; // loop on all spins on proc. @@ -394,47 +417,6 @@ void MinSpinOSO_CG::advance_spins() } } -/* ---------------------------------------------------------------------- - compute and return max_i||mag. torque_i||_2 -------------------------------------------------------------------------- */ - -double MinSpinOSO_CG::max_torque() -{ - double fmsq,fmaxsqone,fmaxsqloc,fmaxsqall; - int nlocal = atom->nlocal; - double factor; - double hbar = force->hplanck/MY_2PI; - - if (use_line_search) factor = 1.0; - else factor = hbar; - - // finding max fm on this proc. - - fmsq = fmaxsqone = fmaxsqloc = fmaxsqall = 0.0; - for (int i = 0; i < nlocal; i++) { - fmsq = 0.0; - for (int j = 0; j < 3; j++) - fmsq += g_cur[3 * i + j] * g_cur[3 * i + j]; - fmaxsqone = MAX(fmaxsqone,fmsq); - } - - // finding max fm on this replica - - fmaxsqloc = fmaxsqone; - MPI_Allreduce(&fmaxsqone,&fmaxsqloc,1,MPI_DOUBLE,MPI_MAX,world); - - // finding max fm over all replicas, if necessary - // this communicator would be invalid for multiprocess replicas - - fmaxsqall = fmaxsqloc; - if (update->multireplica == 1) { - fmaxsqall = fmaxsqloc; - MPI_Allreduce(&fmaxsqloc,&fmaxsqall,1,MPI_DOUBLE,MPI_MAX,universe->uworld); - } - - return sqrt(fmaxsqall) * factor; -} - /* ---------------------------------------------------------------------- calculate 3x3 matrix exponential using Rodrigues' formula (R. Murray, Z. Li, and S. Shankar Sastry, @@ -456,15 +438,14 @@ void MinSpinOSO_CG::rodrigues_rotation(const double *upp_tr, double *out) fabs(upp_tr[1]) < 1.0e-40 && fabs(upp_tr[2]) < 1.0e-40){ - // if upp_tr is zero, return unity matrix - for(int k = 0; k < 3; k++){ - for(int m = 0; m < 3; m++){ - if (m == k) - out[3 * k + m] = 1.0; - else - out[3 * k + m] = 0.0; + // if upp_tr is zero, return unity matrix + + for(int k = 0; k < 3; k++){ + for(int m = 0; m < 3; m++){ + if (m == k) out[3 * k + m] = 1.0; + else out[3 * k + m] = 0.0; + } } - } return; } @@ -512,13 +493,14 @@ void MinSpinOSO_CG::rodrigues_rotation(const double *upp_tr, double *out) void MinSpinOSO_CG::vm3(const double *m, const double *v, double *out) { for(int i = 0; i < 3; i++){ - //out[i] *= 0.0; out[i] = 0.0; - for(int j = 0; j < 3; j++) - out[i] += *(m + 3 * j + i) * v[j]; + for(int j = 0; j < 3; j++) out[i] += *(m + 3 * j + i) * v[j]; } } +/* ---------------------------------------------------------------------- + advance spins +------------------------------------------------------------------------- */ void MinSpinOSO_CG::make_step(double c, double *energy_and_der) { @@ -586,7 +568,7 @@ int MinSpinOSO_CG::calc_and_make_step(double a, double b, int index) } return 1; } - else{ + else { double r,f0,f1,df0,df1; r = b - a; f0 = eprevious; diff --git a/src/SPIN/min_spin_oso_cg.h b/src/SPIN/min_spin_oso_cg.h index 41253f440f..30d9adf066 100644 --- a/src/SPIN/min_spin_oso_cg.h +++ b/src/SPIN/min_spin_oso_cg.h @@ -25,44 +25,44 @@ MinimizeStyle(spin_oso_cg, MinSpinOSO_CG) namespace LAMMPS_NS { class MinSpinOSO_CG: public Min { - public: - MinSpinOSO_CG(class LAMMPS *); - virtual ~MinSpinOSO_CG(); - void init(); - void setup_style(); - int modify_param(int, char **); - void reset_vectors(); - int iterate(int); - private: - double dt; // global timestep - double dts; // spin timestep - int ireplica,nreplica; // for neb - double *spvec; // variables for atomic dof, as 1d vector - double *fmvec; // variables for atomic dof, as 1d vector - double *g_old; // gradient vector at previous step - double *g_cur; // current gradient vector - double *p_s; // search direction vector - double **sp_copy; // copy of the spins - int local_iter; // for neb - int nlocal_max; // max value of nlocal (for size of lists) - double discrete_factor; // factor for spin timestep evaluation + public: + MinSpinOSO_CG(class LAMMPS *); + virtual ~MinSpinOSO_CG(); + void init(); + void setup_style(); + void reset_vectors(); + int modify_param(int, char **); + int iterate(int); - double evaluate_dt(); - void advance_spins(); - void calc_gradient(); - void calc_search_direction(); - double maximum_rotation(double *); - void vm3(const double *, const double *, double *); - void rodrigues_rotation(const double *, double *); - int calc_and_make_step(double, double, int); - int awc(double, double, double, double); - void make_step(double, double *); - double max_torque(); - double der_e_cur; // current derivative along search dir. - double der_e_pr; // previous derivative along search dir. - int use_line_search; // use line search or not. + private: + int local_iter; // for neb + int nlocal_max; // max value of nlocal (for size of lists) + int use_line_search; // use line search or not. + int ireplica,nreplica; // for neb + double dt; // global timestep + double dts; // spin timestep + double discrete_factor; // factor for spin timestep evaluation + double der_e_cur; // current derivative along search dir. + double der_e_pr; // previous derivative along search dir. + double *spvec; // variables for atomic dof, as 1d vector + double *fmvec; // variables for atomic dof, as 1d vector + double *g_old; // gradient vector at previous step + double *g_cur; // current gradient vector + double *p_s; // search direction vector + double **sp_copy; // copy of the spins - bigint last_negative; + void advance_spins(); + void calc_gradient(); + void calc_search_direction(); + void vm3(const double *, const double *, double *); + void rodrigues_rotation(const double *, double *); + void make_step(double, double *); + int calc_and_make_step(double, double, int); + int awc(double, double, double, double); + double evaluate_dt(); + double maximum_rotation(double *); + + bigint last_negative; }; } diff --git a/src/SPIN/min_spin_oso_lbfgs.cpp b/src/SPIN/min_spin_oso_lbfgs.cpp index b9315d706e..2913ef4101 100644 --- a/src/SPIN/min_spin_oso_lbfgs.cpp +++ b/src/SPIN/min_spin_oso_lbfgs.cpp @@ -26,9 +26,9 @@ #include #include #include "min_spin_oso_lbfgs.h" -#include "universe.h" #include "atom.h" #include "citeme.h" +#include "comm.h" #include "force.h" #include "update.h" #include "output.h" @@ -107,6 +107,13 @@ void MinSpinOSO_LBFGS::init() Min::init(); + // warning if line_search combined to gneb + + if ((nreplica >= 1) && (linestyle != 4) && (comm->me == 0)) + error->warning(FLERR,"Line search incompatible gneb"); + + // set back use_line_search to 0 if more than one replica + if (linestyle != 4 && nreplica == 1){ use_line_search = 1; } @@ -188,7 +195,7 @@ int MinSpinOSO_LBFGS::iterate(int maxiter) { int nlocal = atom->nlocal; bigint ntimestep; - double fmdotfm; + double fmdotfm,fmsq,fmsqall; int flag, flagall; double **sp = atom->sp; double der_e_cur_tmp = 0.0; @@ -280,8 +287,20 @@ int MinSpinOSO_LBFGS::iterate(int maxiter) // magnetic torque tolerance criterion // sync across replicas if running multi-replica minimization + fmdotfm = fmsq = fmsqall = 0.0; if (update->ftol > 0.0) { - fmdotfm = max_torque(); + if (normstyle == 1) { // max torque norm + fmsq = max_torque(); + fmsqall = fmsq; + if (update->multireplica == 0) + MPI_Allreduce(&fmsq,&fmsqall,1,MPI_INT,MPI_MAX,universe->uworld); + } else { // Euclidean torque norm + fmsq = total_torque(); + fmsqall = fmsq; + if (update->multireplica == 0) + MPI_Allreduce(&fmsq,&fmsqall,1,MPI_INT,MPI_SUM,universe->uworld); + } + fmdotfm = fmsqall*fmsqall; if (update->multireplica == 0) { if (fmdotfm < update->ftol*update->ftol) return FTOL; } else { @@ -534,42 +553,6 @@ void MinSpinOSO_LBFGS::advance_spins() } } -/* ---------------------------------------------------------------------- - compute and return max_i||mag. torque_i||_2 -------------------------------------------------------------------------- */ - -double MinSpinOSO_LBFGS::max_torque() -{ - double fmsq,fmaxsqone,fmaxsqloc,fmaxsqall; - int nlocal = atom->nlocal; - - // finding max fm on this proc. - - fmsq = fmaxsqone = fmaxsqloc = fmaxsqall = 0.0; - for (int i = 0; i < nlocal; i++) { - fmsq = 0.0; - for (int j = 0; j < 3; j++) - fmsq += g_cur[3 * i + j] * g_cur[3 * i + j]; - fmaxsqone = MAX(fmaxsqone,fmsq); - } - - // finding max fm on this replica - - fmaxsqloc = fmaxsqone; - MPI_Allreduce(&fmaxsqone,&fmaxsqloc,1,MPI_DOUBLE,MPI_MAX,world); - - // finding max fm over all replicas, if necessary - // this communicator would be invalid for multiprocess replicas - - fmaxsqall = fmaxsqloc; - if (update->multireplica == 1) { - fmaxsqall = fmaxsqloc; - MPI_Allreduce(&fmaxsqloc,&fmaxsqall,1,MPI_DOUBLE,MPI_MAX,universe->uworld); - } - - return sqrt(fmaxsqall); -} - /* ---------------------------------------------------------------------- calculate 3x3 matrix exponential using Rodrigues' formula (R. Murray, Z. Li, and S. Shankar Sastry, diff --git a/src/SPIN/min_spin_oso_lbfgs.h b/src/SPIN/min_spin_oso_lbfgs.h index 204f6bf058..9bd36afa8b 100644 --- a/src/SPIN/min_spin_oso_lbfgs.h +++ b/src/SPIN/min_spin_oso_lbfgs.h @@ -25,45 +25,45 @@ MinimizeStyle(spin_oso_lbfgs, MinSpinOSO_LBFGS) namespace LAMMPS_NS { class MinSpinOSO_LBFGS: public Min { - public: - MinSpinOSO_LBFGS(class LAMMPS *); - virtual ~MinSpinOSO_LBFGS(); - void init(); - void setup_style(); - int modify_param(int, char **); - void reset_vectors(); - int iterate(int); - private: - int ireplica,nreplica; // for neb - double *spvec; // variables for atomic dof, as 1d vector - double *fmvec; // variables for atomic dof, as 1d vector - double *g_old; // gradient vector at previous step - double *g_cur; // current gradient vector - double *p_s; // search direction vector - int local_iter; // for neb - int nlocal_max; // max value of nlocal (for size of lists) + public: + MinSpinOSO_LBFGS(class LAMMPS *); + virtual ~MinSpinOSO_LBFGS(); + void init(); + void setup_style(); + int modify_param(int, char **); + void reset_vectors(); + int iterate(int); - void advance_spins(); - void calc_gradient(); - void calc_search_direction(); - double maximum_rotation(double *); - void vm3(const double *, const double *, double *); - void rodrigues_rotation(const double *, double *); - int calc_and_make_step(double, double, int); - int awc(double, double, double, double); - void make_step(double, double *); - double max_torque(); - double der_e_cur; // current derivative along search dir. - double der_e_pr; // previous derivative along search dir. - int use_line_search; // use line search or not. - double maxepsrot; + private: + int local_iter; // for neb + int use_line_search; // use line search or not. + int nlocal_max; // max value of nlocal (for size of lists) + int ireplica,nreplica; // for neb + double der_e_cur; // current derivative along search dir. + double der_e_pr; // previous derivative along search dir. + double maxepsrot; + double *spvec; // variables for atomic dof, as 1d vector + double *fmvec; // variables for atomic dof, as 1d vector + double *g_old; // gradient vector at previous step + double *g_cur; // current gradient vector + double *p_s; // search direction vector - double *rho; // estimation of curvature - double **ds; // change in rotation matrix between two iterations, da - double **dy; // change in gradients between two iterations, dg - double **sp_copy; // copy of the spins - int num_mem; // number of stored steps - bigint last_negative; + void advance_spins(); + void calc_gradient(); + void calc_search_direction(); + void vm3(const double *, const double *, double *); + void rodrigues_rotation(const double *, double *); + void make_step(double, double *); + int calc_and_make_step(double, double, int); + int awc(double, double, double, double); + double maximum_rotation(double *); + + double *rho; // estimation of curvature + double **ds; // change in rotation matrix between two iterations, da + double **dy; // change in gradients between two iterations, dg + double **sp_copy; // copy of the spins + int num_mem; // number of stored steps + bigint last_negative; }; } diff --git a/src/min.cpp b/src/min.cpp index 2a42a444a0..e476b1abc8 100644 --- a/src/min.cpp +++ b/src/min.cpp @@ -42,10 +42,12 @@ #include "output.h" #include "thermo.h" #include "timer.h" +#include "math_const.h" #include "memory.h" #include "error.h" using namespace LAMMPS_NS; +using namespace MathConst; /* ---------------------------------------------------------------------- */ @@ -54,6 +56,7 @@ Min::Min(LAMMPS *lmp) : Pointers(lmp) dmax = 0.1; searchflag = 0; linestyle = 1; + normstyle = 0; elist_global = elist_atom = NULL; vlist_global = vlist_atom = NULL; @@ -653,6 +656,14 @@ void Min::modify_params(int narg, char **arg) if (strcmp(arg[iarg+1],"backtrack") == 0) linestyle = 0; else if (strcmp(arg[iarg+1],"quadratic") == 0) linestyle = 1; else if (strcmp(arg[iarg+1],"forcezero") == 0) linestyle = 2; + else if (strcmp(arg[iarg+1],"spin_cubic") == 0) linestyle = 3; + else if (strcmp(arg[iarg+1],"spin_none") == 0) linestyle = 4; + else error->all(FLERR,"Illegal min_modify command"); + iarg += 2; + } else if (strcmp(arg[iarg],"norm") == 0) { + if (iarg+2 > narg) error->all(FLERR,"Illegal min_modify command"); + if (strcmp(arg[iarg+1],"euclidean") == 0) normstyle = 0; + else if (strcmp(arg[iarg+1],"max") == 0) normstyle = 1; else error->all(FLERR,"Illegal min_modify command"); iarg += 2; } else { @@ -816,6 +827,69 @@ double Min::fnorm_inf() return norm_inf; } +/* ---------------------------------------------------------------------- + compute and return sum_i||mag. torque_i||_2 (in eV) +------------------------------------------------------------------------- */ + +double Min::total_torque() +{ + double fmsq,ftotsqone,ftotsqall; + int nlocal = atom->nlocal; + double hbar = force->hplanck/MY_2PI; + double tx,ty,tz; + double **sp = atom->sp; + double **fm = atom->fm; + + fmsq = ftotsqone = ftotsqall = 0.0; + for (int i = 0; i < nlocal; i++) { + tx = fm[i][1] * sp[i][2] - fm[i][2] * sp[i][1]; + ty = fm[i][2] * sp[i][0] - fm[i][0] * sp[i][2]; + tz = fm[i][0] * sp[i][1] - fm[i][1] * sp[i][0]; + fmsq = tx * tx + ty * ty + tz * tz; + ftotsqone += fmsq; + } + + // summing all fmsqtot on this replica + + MPI_Allreduce(&ftotsqone,&ftotsqall,1,MPI_DOUBLE,MPI_SUM,world); + + // multiply it by hbar so that units are in eV + + return sqrt(ftotsqall) * hbar; +} + +/* ---------------------------------------------------------------------- + compute and return max_i ||mag. torque_i|| (in eV) +------------------------------------------------------------------------- */ + +double Min::max_torque() +{ + double fmsq,fmaxsqone,fmaxsqall; + int nlocal = atom->nlocal; + double hbar = force->hplanck/MY_2PI; + double tx,ty,tz; + double **sp = atom->sp; + double **fm = atom->fm; + + fmsq = fmaxsqone = fmaxsqall = 0.0; + for (int i = 0; i < nlocal; i++) { + tx = fm[i][1] * sp[i][2] - fm[i][2] * sp[i][1]; + ty = fm[i][2] * sp[i][0] - fm[i][0] * sp[i][2]; + tz = fm[i][0] * sp[i][1] - fm[i][1] * sp[i][0]; + fmsq = tx * tx + ty * ty + tz * tz; + fmaxsqone = MAX(fmaxsqone,fmsq); + } + + // finding max fm on this replica + + fmaxsqall = fmaxsqone; + MPI_Allreduce(&fmaxsqone,&fmaxsqall,1,MPI_DOUBLE,MPI_MAX,world); + + // multiply it by hbar so that units are in eV + + return sqrt(fmaxsqall) * hbar; +} + /* ---------------------------------------------------------------------- possible stop conditions ------------------------------------------------------------------------- */ diff --git a/src/min.h b/src/min.h index a63254231c..e18d0dd677 100644 --- a/src/min.h +++ b/src/min.h @@ -42,6 +42,10 @@ class Min : protected Pointers { double fnorm_sqr(); double fnorm_inf(); + // methods for spin minimizers + double max_torque(); + double total_torque(); + virtual void init_style() {} virtual void setup_style() = 0; virtual void reset_vectors() = 0; @@ -56,8 +60,11 @@ class Min : protected Pointers { int virial_style; // compute virial explicitly or implicitly int external_force_clear; // clear forces locally or externally - double dmax; // max dist to move any atom in one step - int linestyle; // 0 = backtrack, 1 = quadratic, 2 = forcezero + double dmax; // max dist to move any atom in one step + int linestyle; // 0 = backtrack, 1 = quadratic, 2 = forcezero + // 3 = spin_cubic, 4 = spin_none + + int normstyle; // 0 = Euclidean norm, 1 = inf. norm int nelist_global,nelist_atom; // # of PE,virial computes to check int nvlist_global,nvlist_atom; @@ -102,9 +109,6 @@ class Min : protected Pointers { double energy_force(int); void force_clear(); - double compute_force_norm_sqr(); - double compute_force_norm_inf(); - void ev_setup(); void ev_set(bigint); diff --git a/src/min_cg.cpp b/src/min_cg.cpp index 20e8cc30dd..9801e57f4d 100644 --- a/src/min_cg.cpp +++ b/src/min_cg.cpp @@ -37,7 +37,7 @@ MinCG::MinCG(LAMMPS *lmp) : MinLineSearch(lmp) {} int MinCG::iterate(int maxiter) { int i,m,n,fail,ntimestep; - double beta,gg,dot[2],dotall[2]; + double beta,gg,dot[2],dotall[2],fmax,fmaxall; double *fatom,*gatom,*hatom; // nlimit = max # of CG iterations before restarting @@ -87,10 +87,12 @@ int MinCG::iterate(int maxiter) // force tolerance criterion + fmax = fmaxall = 0.0; dot[0] = dot[1] = 0.0; for (i = 0; i < nvec; i++) { dot[0] += fvec[i]*fvec[i]; dot[1] += fvec[i]*g[i]; + fmax = MAX(fmax,fvec[i]*fvec[i]); } if (nextra_atom) for (m = 0; m < nextra_atom; m++) { @@ -100,16 +102,22 @@ int MinCG::iterate(int maxiter) for (i = 0; i < n; i++) { dot[0] += fatom[i]*fatom[i]; dot[1] += fatom[i]*gatom[i]; + fmax = MAX(fmax,fatom[i]*fatom[i]); } } MPI_Allreduce(dot,dotall,2,MPI_DOUBLE,MPI_SUM,world); + MPI_Allreduce(&fmax,&fmaxall,2,MPI_DOUBLE,MPI_MAX,world); if (nextra_global) for (i = 0; i < nextra_global; i++) { dotall[0] += fextra[i]*fextra[i]; dotall[1] += fextra[i]*gextra[i]; } - if (dotall[0] < update->ftol*update->ftol) return FTOL; + if (normstyle == 1) { // max force norm + if (fmax < update->ftol*update->ftol) return FTOL; + } else { // Euclidean force norm + if (dotall[0] < update->ftol*update->ftol) return FTOL; + } // update new search direction h from new f = -Grad(x) and old g // this is Polak-Ribieri formulation diff --git a/src/min_fire.cpp b/src/min_fire.cpp index a50071d562..a0a3bce8ba 100644 --- a/src/min_fire.cpp +++ b/src/min_fire.cpp @@ -80,7 +80,7 @@ void MinFire::reset_vectors() int MinFire::iterate(int maxiter) { bigint ntimestep; - double vmax,vdotf,vdotfall,vdotv,vdotvall,fdotf,fdotfall; + double vmax,vdotf,vdotfall,vdotv,vdotvall,fdotf,fdotfloc,fdotfall; double scale1,scale2; double dtvone,dtv,dtf,dtfm; int flag,flagall; @@ -250,7 +250,15 @@ int MinFire::iterate(int maxiter) // sync across replicas if running multi-replica minimization if (update->ftol > 0.0) { - fdotf = fnorm_sqr(); + if (normstyle == 1) { // max force norm + fdotf = fnorm_inf(); + fdotfloc = fdotf; + MPI_Allreduce(&fdotfloc,&fdotf,1,MPI_INT,MPI_MAX,universe->uworld); + } else { // Euclidean force norm + fdotf = fnorm_sqr(); + fdotfloc = fdotf; + MPI_Allreduce(&fdotfloc,&fdotf,1,MPI_INT,MPI_SUM,universe->uworld); + } if (update->multireplica == 0) { if (fdotf < update->ftol*update->ftol) return FTOL; } else { diff --git a/src/min_hftn.cpp b/src/min_hftn.cpp index 0c834fbeb4..9f8695f151 100644 --- a/src/min_hftn.cpp +++ b/src/min_hftn.cpp @@ -20,6 +20,7 @@ #include #include #include "atom.h" +#include "error.h" #include "fix_minimize.h" #include "min_hftn.h" #include "modify.h" @@ -111,6 +112,9 @@ void MinHFTN::init() { Min::init(); + if (normstyle == 1) + error->all(FLERR,"Incorrect min_modify option"); + for (int i = 1; i < NUM_HFTN_ATOM_BASED_VECTORS; i++) { if (_daExtraGlobal[i] != NULL) delete [] _daExtraGlobal[i]; diff --git a/src/min_quickmin.cpp b/src/min_quickmin.cpp index 8b48816355..d6507cfcde 100644 --- a/src/min_quickmin.cpp +++ b/src/min_quickmin.cpp @@ -76,7 +76,7 @@ void MinQuickMin::reset_vectors() int MinQuickMin::iterate(int maxiter) { bigint ntimestep; - double vmax,vdotf,vdotfall,fdotf,fdotfall,scale; + double vmax,vdotf,vdotfall,fdotf,fdotfloc,fdotfall,scale; double dtvone,dtv,dtf,dtfm; int flag,flagall; @@ -216,7 +216,15 @@ int MinQuickMin::iterate(int maxiter) // sync across replicas if running multi-replica minimization if (update->ftol > 0.0) { - fdotf = fnorm_sqr(); + if (normstyle == 1) { // max force norm + fdotf = fnorm_inf(); + fdotfloc = fdotf; + MPI_Allreduce(&fdotfloc,&fdotf,1,MPI_INT,MPI_MAX,universe->uworld); + } else { // Euclidean force norm + fdotf = fnorm_sqr(); + fdotfloc = fdotf; + MPI_Allreduce(&fdotfloc,&fdotf,1,MPI_INT,MPI_SUM,universe->uworld); + } if (update->multireplica == 0) { if (fdotf < update->ftol*update->ftol) return FTOL; } else { diff --git a/src/min_sd.cpp b/src/min_sd.cpp index 5d44437ca0..60386df82c 100644 --- a/src/min_sd.cpp +++ b/src/min_sd.cpp @@ -79,7 +79,8 @@ int MinSD::iterate(int maxiter) // force tolerance criterion - fdotf = fnorm_sqr(); + if (normstyle == 1) fdotf = fnorm_inf(); // max force norm + else fdotf = fnorm_sqr(); // Euclidean force norm if (fdotf < update->ftol*update->ftol) return FTOL; // set new search direction h to f = -Grad(x) From 1364329432bef1809811b4e188e02520091ed825 Mon Sep 17 00:00:00 2001 From: julient31 Date: Fri, 26 Jul 2019 17:54:04 -0600 Subject: [PATCH 068/192] Commit JT 072619 - draft doc of norm option (doc/src/min_modify.txt) --- doc/src/min_modify.txt | 10 ++++++++++ 1 file changed, 10 insertions(+) diff --git a/doc/src/min_modify.txt b/doc/src/min_modify.txt index 9c4d7c8fcb..ecd4795a8f 100644 --- a/doc/src/min_modify.txt +++ b/doc/src/min_modify.txt @@ -18,6 +18,8 @@ keyword = {dmax} or {line} or {alpha_damp} or {discrete_factor} max = maximum distance for line search to move (distance units) {line} value = {backtrack} or {quadratic} or {forcezero} or {spin_cubic} or {spin_none} backtrack,quadratic,forcezero,spin_cubic,spin_none = style of linesearch to use + {norm} value = {euclidean} or {max} + euclidean,max = style of norm to use {alpha_damp} value = damping damping = fictitious Gilbert damping for spin minimization (adim) {discrete_factor} value = factor @@ -69,6 +71,14 @@ difference of two large values (energy before and energy after) and that difference may be smaller than machine epsilon even if atoms could move in the gradient direction to reduce forces further. +The choice of a norm can be modified for the min styles {fire}, +{quickmin}, {sd}, {spin}, {spin_oso_cg} and {spin_oso_lbfgs} +using the {norm} keyword. +The default {euclidean} norm computes the 2-norm (length) of the +global force vector. The {max} norm computes the maximum value +of the 2-norms of all forces in the system. + + Keywords {alpha_damp} and {discrete_factor} only make sense when a "min_spin"_min_spin.html command is declared. Keyword {alpha_damp} defines an analog of a magnetic Gilbert From 9609c75073130b19856c3bc0e64068e72254e507 Mon Sep 17 00:00:00 2001 From: alxvov Date: Tue, 30 Jul 2019 11:16:40 +0000 Subject: [PATCH 069/192] Use descent condition, and no line search as a default option for all oso --- examples/SPIN/spinmin/in.spinmin_cg.bfo | 2 +- examples/SPIN/spinmin/in.spinmin_lbfgs.bfo | 4 ++-- src/SPIN/min_spin_oso_cg.cpp | 14 ++++---------- src/SPIN/min_spin_oso_cg.h | 2 +- src/SPIN/min_spin_oso_lbfgs.cpp | 21 ++++++--------------- src/SPIN/min_spin_oso_lbfgs.h | 2 +- 6 files changed, 15 insertions(+), 30 deletions(-) diff --git a/examples/SPIN/spinmin/in.spinmin_cg.bfo b/examples/SPIN/spinmin/in.spinmin_cg.bfo index 776079edb8..8c288763c4 100644 --- a/examples/SPIN/spinmin/in.spinmin_cg.bfo +++ b/examples/SPIN/spinmin/in.spinmin_cg.bfo @@ -51,4 +51,4 @@ dump 1 all custom 50 dump.lammpstrj type x y z c_outsp[1] c_outsp[2] c_outsp[3 min_style spin_oso_cg # min_modify line spin_none discrete_factor 10.0 -minimize 1.0e-10 1.0e-7 1000 1000 +minimize 1.0e-10 1.0e-10 10000 10000 diff --git a/examples/SPIN/spinmin/in.spinmin_lbfgs.bfo b/examples/SPIN/spinmin/in.spinmin_lbfgs.bfo index ca600f1c2b..6a9104cc9c 100644 --- a/examples/SPIN/spinmin/in.spinmin_lbfgs.bfo +++ b/examples/SPIN/spinmin/in.spinmin_lbfgs.bfo @@ -50,5 +50,5 @@ compute outsp all property/atom spx spy spz sp fmx fmy fmz dump 1 all custom 50 dump.lammpstrj type x y z c_outsp[1] c_outsp[2] c_outsp[3] c_outsp[4] c_outsp[5] c_outsp[6] c_outsp[7] min_style spin_oso_lbfgs -min_modify line spin_cubic discrete_factor 10.0 -minimize 1.0e-15 1.0e-7 10000 1000 +# min_modify line spin_cubic discrete_factor 10.0 +minimize 1.0e-15 1.0e-10 10000 1000 diff --git a/src/SPIN/min_spin_oso_cg.cpp b/src/SPIN/min_spin_oso_cg.cpp index 16a95c5c02..f1f2f72436 100644 --- a/src/SPIN/min_spin_oso_cg.cpp +++ b/src/SPIN/min_spin_oso_cg.cpp @@ -561,7 +561,7 @@ int MinSpinOSO_CG::calc_and_make_step(double a, double b, int index) der_e_cur = e_and_d[1]; index++; - if (awc(der_e_pr,eprevious,e_and_d[1],e_and_d[0]) || index == 10){ + if (adescent(eprevious,e_and_d[0]) || index == 5){ MPI_Bcast(&b,1,MPI_DOUBLE,0,world); for (int i = 0; i < 3 * nlocal; i++) { p_s[i] = b * p_s[i]; @@ -598,20 +598,14 @@ int MinSpinOSO_CG::calc_and_make_step(double a, double b, int index) } /* ---------------------------------------------------------------------- - Approximate Wolfe conditions: - William W. Hager and Hongchao Zhang - SIAM J. optim., 16(1), 170-192. (23 pages) + Approximate descent ------------------------------------------------------------------------- */ -int MinSpinOSO_CG::awc(double der_phi_0, double phi_0, double der_phi_j, double phi_j){ +int MinSpinOSO_CG::adescent(double phi_0, double phi_j){ double eps = 1.0e-6; - double delta = 0.1; - double sigma = 0.9; - if ((phi_j<=phi_0+eps*fabs(phi_0)) && - ((2.0*delta-1.0) * der_phi_0>=der_phi_j) && - (der_phi_j>=sigma*der_phi_0)) + if (phi_j<=phi_0+eps*fabs(phi_0)) return 1; else return 0; diff --git a/src/SPIN/min_spin_oso_cg.h b/src/SPIN/min_spin_oso_cg.h index 30d9adf066..d6dc7c03d0 100644 --- a/src/SPIN/min_spin_oso_cg.h +++ b/src/SPIN/min_spin_oso_cg.h @@ -58,7 +58,7 @@ class MinSpinOSO_CG: public Min { void rodrigues_rotation(const double *, double *); void make_step(double, double *); int calc_and_make_step(double, double, int); - int awc(double, double, double, double); + int adescent(double, double); double evaluate_dt(); double maximum_rotation(double *); diff --git a/src/SPIN/min_spin_oso_lbfgs.cpp b/src/SPIN/min_spin_oso_lbfgs.cpp index f850879d1a..8623a8bb29 100644 --- a/src/SPIN/min_spin_oso_lbfgs.cpp +++ b/src/SPIN/min_spin_oso_lbfgs.cpp @@ -73,10 +73,7 @@ MinSpinOSO_LBFGS::MinSpinOSO_LBFGS(LAMMPS *lmp) : nreplica = universe->nworlds; ireplica = universe->iworld; - if (nreplica > 1) - use_line_search = 0; // no line search for NEB - else - use_line_search = 1; + use_line_search = 0; // no line search as default option for LBFGS maxepsrot = MY_2PI / (100.0); @@ -114,7 +111,7 @@ void MinSpinOSO_LBFGS::init() // set back use_line_search to 0 if more than one replica - if (linestyle != 4 && nreplica == 1){ + if (linestyle == 3 && nreplica == 1){ use_line_search = 1; } else{ @@ -694,7 +691,7 @@ int MinSpinOSO_LBFGS::calc_and_make_step(double a, double b, int index) der_e_cur = e_and_d[1]; index++; - if (awc(der_e_pr,eprevious,e_and_d[1],e_and_d[0]) || index == 5){ + if (adescent(eprevious,e_and_d[0]) || index == 5){ MPI_Bcast(&b,1,MPI_DOUBLE,0,world); for (int i = 0; i < 3 * nlocal; i++) { p_s[i] = b * p_s[i]; @@ -731,20 +728,14 @@ int MinSpinOSO_LBFGS::calc_and_make_step(double a, double b, int index) } /* ---------------------------------------------------------------------- - Approximate Wolfe conditions: - William W. Hager and Hongchao Zhang - SIAM J. optim., 16(1), 170-192. (23 pages) + Approximate descent ------------------------------------------------------------------------- */ -int MinSpinOSO_LBFGS::awc(double der_phi_0, double phi_0, double der_phi_j, double phi_j){ +int MinSpinOSO_LBFGS::adescent(double phi_0, double phi_j){ double eps = 1.0e-6; - double delta = 0.1; - double sigma = 0.9; - if ((phi_j<=phi_0+eps*fabs(phi_0)) && - ((2.0*delta-1.0) * der_phi_0>=der_phi_j) && - (der_phi_j>=sigma*der_phi_0)) + if (phi_j<=phi_0+eps*fabs(phi_0)) return 1; else return 0; diff --git a/src/SPIN/min_spin_oso_lbfgs.h b/src/SPIN/min_spin_oso_lbfgs.h index 9bd36afa8b..68fa10921e 100644 --- a/src/SPIN/min_spin_oso_lbfgs.h +++ b/src/SPIN/min_spin_oso_lbfgs.h @@ -55,7 +55,7 @@ class MinSpinOSO_LBFGS: public Min { void rodrigues_rotation(const double *, double *); void make_step(double, double *); int calc_and_make_step(double, double, int); - int awc(double, double, double, double); + int adescent(double, double); double maximum_rotation(double *); double *rho; // estimation of curvature From aa3c44ad4af471e3c4cc65734f3abe43179d3b27 Mon Sep 17 00:00:00 2001 From: alxvov Date: Tue, 30 Jul 2019 12:02:10 +0000 Subject: [PATCH 070/192] modify documentation a bit --- doc/src/min_modify.txt | 6 +++--- doc/src/min_spin.txt | 11 +++++------ 2 files changed, 8 insertions(+), 9 deletions(-) diff --git a/doc/src/min_modify.txt b/doc/src/min_modify.txt index ecd4795a8f..35a02c47c3 100644 --- a/doc/src/min_modify.txt +++ b/doc/src/min_modify.txt @@ -97,9 +97,9 @@ two minimization styles is declared. The {spin_cubic} performs the line search based on a cubic interpolation of the energy along the search direction. The {spin_none} keyword deactivates the line search procedure. -The {spin_none} is a default value for {line} keyword apart from the case when -single-replica calculations are performed with {spin_oso_lbfgs} that -uses {spin_cubic} line search. +The {spin_none} is a default value for {line} keyword for both {spin_oso_lbfgs} +and {spin_oso_cg}. Convergence of {spin_oso_lbfgs} can be more robust if +{spin_cubic} line search is used. [Restrictions:] The line search procedure of styles {spin_oso_cg} and {spin_oso_lbfgs} cannot be used for magnetic diff --git a/doc/src/min_spin.txt b/doc/src/min_spin.txt index 77dc008b3e..20c4cde1d7 100644 --- a/doc/src/min_spin.txt +++ b/doc/src/min_spin.txt @@ -18,7 +18,7 @@ min_style spin_oso_lbfgs :pre [Examples:] min_style spin_oso_lbfgs -min_modify line spin_none discrete_factor 10.0 :pre +min_modify line spin_cubic discrete_factor 10.0 :pre [Description:] @@ -62,16 +62,15 @@ and uses the adaptive time-step technique in the same way as style {spin}. Style {spin_oso_lbfgs} defines an orthogonal spin optimization (OSO) combined to a limited-memory Broyden-Fletcher-Goldfarb-Shanno (L-BFGS) algorithm. -By default, style {spin_oso_lbfgs} uses a line search procedure -based on cubic interpolation for -a single-replica calculation, and it does not use line search procedure -for a multireplica calculation (such as in case of GNEB calculation). +By default, style {spin_oso_lbfgs} does not employ line search procedure. If the line search procedure is not used then the discrete factor defines the maximum root mean squared rotation angle of spins by equation {pi/(5*Kappa)}. The default value for Kappa is 10. +The {spin_cubic} line search can improve +the convergence of the {spin_oso_lbfgs} algorithm. The "min_modify"_min_modify.html command can be used to -deactivate the line search procedure, and to modify the +activate the line search procedure, and to modify the discretization factor {discrete_factor}. For more information about styles {spin_oso_cg} and {spin_oso_lbfgs}, From 74fa4f741571be0bb060462691d76651d10394e8 Mon Sep 17 00:00:00 2001 From: julient31 Date: Tue, 30 Jul 2019 08:58:12 -0600 Subject: [PATCH 071/192] Commit JT 073019 - modified doc doc/src/min_modify.txt - tested lattice minimizers with norm styles --- doc/src/min_modify.txt | 19 +++++++++++-------- doc/src/min_spin.txt | 10 +++++----- doc/src/min_style.txt | 3 +-- 3 files changed, 17 insertions(+), 15 deletions(-) diff --git a/doc/src/min_modify.txt b/doc/src/min_modify.txt index 35a02c47c3..2056655d40 100644 --- a/doc/src/min_modify.txt +++ b/doc/src/min_modify.txt @@ -13,7 +13,7 @@ min_modify command :h3 min_modify keyword values ... :pre one or more keyword/value pairs may be listed :ulb,l -keyword = {dmax} or {line} or {alpha_damp} or {discrete_factor} +keyword = {dmax} or {line} or {norm} or {alpha_damp} or {discrete_factor} {dmax} value = max max = maximum distance for line search to move (distance units) {line} value = {backtrack} or {quadratic} or {forcezero} or {spin_cubic} or {spin_none} @@ -71,13 +71,12 @@ difference of two large values (energy before and energy after) and that difference may be smaller than machine epsilon even if atoms could move in the gradient direction to reduce forces further. -The choice of a norm can be modified for the min styles {fire}, -{quickmin}, {sd}, {spin}, {spin_oso_cg} and {spin_oso_lbfgs} -using the {norm} keyword. +The choice of a norm can be modified for the min styles {cg}, {sd}, +{quickmin}, {fire}, {spin}, {spin_oso_cg} and {spin_oso_lbfgs} using +the {norm} keyword. The default {euclidean} norm computes the 2-norm (length) of the global force vector. The {max} norm computes the maximum value -of the 2-norms of all forces in the system. - +of the 2-norms across all forces in the system. Keywords {alpha_damp} and {discrete_factor} only make sense when a "min_spin"_min_spin.html command is declared. @@ -88,7 +87,6 @@ Keyword {discrete_factor} defines a discretization factor for the adaptive timestep used in the {spin} minimization. See "min_spin"_min_spin.html for more information about those quantities. -Default values are {alpha_damp} = 1.0 and {discrete_factor} = 10.0. The choice of a line search algorithm for the {spin_oso_cg} and {spin_oso_lbfgs} styles can be specified via the {line} keyword. @@ -112,4 +110,9 @@ explanation. [Default:] -The option defaults are dmax = 0.1 and line = quadratic. +The option defaults are dmax = 0.1, line = quadratic and norm = +euclidean. + +For the {spin}, {spin_oso_cg} and {spin_oso_lbfgs} styles, the +option defaults are alpha_damp = 1.0, discrete_factor = 10.0, +line = spin_none, and norm = euclidean. diff --git a/doc/src/min_spin.txt b/doc/src/min_spin.txt index 20c4cde1d7..575db2dc74 100644 --- a/doc/src/min_spin.txt +++ b/doc/src/min_spin.txt @@ -56,7 +56,7 @@ Style {spin_oso_cg} defines an orthogonal spin optimization The "min_modify"_min_modify.html command can be used to couple the {spin_oso_cg} to a line search procedure, and to modify the discretization factor {discrete_factor}. -By defualt, the style {spin_oso_cg} does not employ line search procedure and +By default, style {spin_oso_cg} does not employ the line search procedure and uses the adaptive time-step technique in the same way as style {spin}. Style {spin_oso_lbfgs} defines an orthogonal spin optimization @@ -66,8 +66,8 @@ By default, style {spin_oso_lbfgs} does not employ line search procedure. If the line search procedure is not used then the discrete factor defines the maximum root mean squared rotation angle of spins by equation {pi/(5*Kappa)}. The default value for Kappa is 10. -The {spin_cubic} line search can improve -the convergence of the {spin_oso_lbfgs} algorithm. +The {spin_cubic} line search can improve the convergence of the +{spin_oso_lbfgs} algorithm. The "min_modify"_min_modify.html command can be used to activate the line search procedure, and to modify the @@ -95,8 +95,8 @@ freedom for a frozen lattice configuration. [Default:] -The option defaults are {alpha_damp} = 1.0 and {discrete_factor} = -10.0. +The option defaults are {alpha_damp} = 1.0, {discrete_factor} = +10.0, {line} = spin_none and {norm} = euclidean. :line diff --git a/doc/src/min_style.txt b/doc/src/min_style.txt index 081ec17889..7c40fd4947 100644 --- a/doc/src/min_style.txt +++ b/doc/src/min_style.txt @@ -11,8 +11,7 @@ min_style command :h3 min_style style :pre -style = {cg} or {hftn} or {sd} or {quickmin} or {fire} or {spin} -or {spin_oso_cg} or {spin_oso_lbfgs} :ul +style = {cg} or {hftn} or {sd} or {quickmin} or {fire} or {spin} or {spin_oso_cg} or {spin_oso_lbfgs} :ul [Examples:] From f4e3186abf95e0b0d6efd165c84a693ca295f448 Mon Sep 17 00:00:00 2001 From: julient31 Date: Tue, 30 Jul 2019 13:10:27 -0600 Subject: [PATCH 072/192] Commit JT 073019 - modified the false_positive file to correct errors - improved the doc page of fix nve/spin --- doc/src/fix_nve_spin.txt | 15 +++++++++++---- doc/src/min_modify.txt | 3 +-- doc/utils/sphinx-config/false_positives.txt | 5 +++++ 3 files changed, 17 insertions(+), 6 deletions(-) diff --git a/doc/src/fix_nve_spin.txt b/doc/src/fix_nve_spin.txt index 7b382bb6ad..30df484e54 100644 --- a/doc/src/fix_nve_spin.txt +++ b/doc/src/fix_nve_spin.txt @@ -27,10 +27,16 @@ fix 1 all nve/spin lattice no :pre Perform a symplectic integration for the spin or spin-lattice system. -The {lattice} keyword defines if the spins are integrated on a lattice -of fixed atoms (lattice = no), or if atoms are moving (lattice = yes). +The {lattice} keyword defines whether the spins are integrated on a +fixed or moving lattice. -By default (lattice = yes), a spin-lattice integration is performed. +If {lattice}=yes, the equations of motion of the atoms are integrated, +and a combined spin and lattice calculation is performed. +This is the default option. + +If {lattice}=no, the equations of motion of the atoms are not +integrated. The lattice degrees of freedom are frozen, and a +spin dynamics only calculation is performed. The {nve/spin} fix applies a Suzuki-Trotter decomposition to the equations of motion of the spin lattice system, following the scheme: @@ -63,7 +69,8 @@ instead of "array" is also valid. "atom_style spin"_atom_style.html, "fix nve"_fix_nve.html -[Default:] none +[Default:] By default (lattice = yes), a spin-lattice integration is +performed. :line diff --git a/doc/src/min_modify.txt b/doc/src/min_modify.txt index 2056655d40..857c3551aa 100644 --- a/doc/src/min_modify.txt +++ b/doc/src/min_modify.txt @@ -110,8 +110,7 @@ explanation. [Default:] -The option defaults are dmax = 0.1, line = quadratic and norm = -euclidean. +The option defaults are dmax = 0.1, line = quadratic and norm = euclidean. For the {spin}, {spin_oso_cg} and {spin_oso_lbfgs} styles, the option defaults are alpha_damp = 1.0, discrete_factor = 10.0, diff --git a/doc/utils/sphinx-config/false_positives.txt b/doc/utils/sphinx-config/false_positives.txt index 1dea229393..417738998e 100644 --- a/doc/utils/sphinx-config/false_positives.txt +++ b/doc/utils/sphinx-config/false_positives.txt @@ -273,6 +273,7 @@ Broadwell Broglie brownian brownw +Broyden Bryantsev Btarget btype @@ -981,6 +982,7 @@ gmask Gmask gneb GNEB +Goldfarb googlemail Gordan GPa @@ -1395,6 +1397,7 @@ Laupretre lavenderblush lawngreen lB +lbfgs lbl LBtype lcbop @@ -2030,6 +2033,7 @@ Orsi ortho orthonormal orthorhombic +oso ot Otype Ouldridge @@ -2493,6 +2497,7 @@ setvel sfftw Sg Shan +Shanno shapex shapey shapez From 55a7200246e5f3253d3f964e086a2cee8ba24048 Mon Sep 17 00:00:00 2001 From: charlie sievers Date: Wed, 7 Aug 2019 12:13:49 -0700 Subject: [PATCH 073/192] updates to src/fix_langevin.cpp --- src/fix_langevin.cpp | 5 ++++- 1 file changed, 4 insertions(+), 1 deletion(-) diff --git a/src/fix_langevin.cpp b/src/fix_langevin.cpp index 723f4be2e4..ea0929a236 100644 --- a/src/fix_langevin.cpp +++ b/src/fix_langevin.cpp @@ -18,10 +18,11 @@ Niels Gronbech-Jensen (UC Davis) GJF-2GJ Formulation ------------------------------------------------------------------------- */ -#include "fix_langevin.h" #include #include #include +#include +#include "fix_langevin.h" #include "math_extra.h" #include "atom.h" #include "atom_vec_ellipsoid.h" @@ -29,6 +30,8 @@ #include "update.h" #include "modify.h" #include "compute.h" +#include "domain.h" +#include "region.h" #include "respa.h" #include "comm.h" #include "input.h" From ef3f382f61f436540fe6fc980f6fd40b876c793a Mon Sep 17 00:00:00 2001 From: charlie sievers Date: Wed, 7 Aug 2019 17:27:35 -0700 Subject: [PATCH 074/192] fixed tbias --- examples/python/gjf_python/README.md | 18 - examples/python/gjf_python/argon.lmp | 886 --------------------- examples/python/gjf_python/ff-argon.lmp | 20 - examples/python/gjf_python/gjf.py | 180 ----- examples/python/gjf_python/lammps_tools.py | 78 -- src/fix_langevin.cpp | 142 +++- src/fix_langevin.h | 1 + 7 files changed, 117 insertions(+), 1208 deletions(-) delete mode 100644 examples/python/gjf_python/README.md delete mode 100644 examples/python/gjf_python/argon.lmp delete mode 100644 examples/python/gjf_python/ff-argon.lmp delete mode 100644 examples/python/gjf_python/gjf.py delete mode 100644 examples/python/gjf_python/lammps_tools.py diff --git a/examples/python/gjf_python/README.md b/examples/python/gjf_python/README.md deleted file mode 100644 index 707289f02d..0000000000 --- a/examples/python/gjf_python/README.md +++ /dev/null @@ -1,18 +0,0 @@ -# LAMMPS GJF-2GJ THERMOSTAT EXAMPLE W/ PYTHON - -## GJF-2GJ THERMOSTAT - -This directory contains a python script to run NVT simulations using the GJF-2GJ thermostat. -The script will vary the timestep and write thermodynamic output to screen. -This script has True/False options to change how you would like to dump/write your output. - -Example: -``` -NP=4 #number of processors -mpirun -np $NP python gjf.py -``` - -## Required LAMMPS packages: MOLECULE package -## LAMMPS COMPILE MODE: SHLIB -## LAMMPS OPTIONAL INSTALL: make install-python -## Required Python packages: mpi4py diff --git a/examples/python/gjf_python/argon.lmp b/examples/python/gjf_python/argon.lmp deleted file mode 100644 index 00214b4c54..0000000000 --- a/examples/python/gjf_python/argon.lmp +++ /dev/null @@ -1,886 +0,0 @@ -LAMMPS description - - 864 atoms - 0 bonds - 0 angles - 0 dihedrals - 0 impropers - - 1 atom types - 0 bond types - 0 angle types - 0 dihedral types - 0 improper types - - - 0.0000000 32.146000 xlo xhi - 0.0000000 32.146000 ylo yhi - 0.0000000 32.146000 zlo zhi - - Atoms - - 1 1 1 0.0000000 0.0000000 2.6790000 2.6790000 - 2 2 1 0.0000000 0.0000000 2.6790000 8.0360000 - 3 3 1 0.0000000 0.0000000 2.6790000 13.3940000 - 4 4 1 0.0000000 0.0000000 2.6790000 18.7520000 - 5 5 1 0.0000000 0.0000000 2.6790000 24.1090000 - 6 6 1 0.0000000 0.0000000 2.6790000 29.4670000 - 7 7 1 0.0000000 0.0000000 8.0360000 2.6790000 - 8 8 1 0.0000000 0.0000000 8.0360000 8.0360000 - 9 9 1 0.0000000 0.0000000 8.0360000 13.3940000 - 10 10 1 0.0000000 0.0000000 8.0360000 18.7520000 - 11 11 1 0.0000000 0.0000000 8.0360000 24.1090000 - 12 12 1 0.0000000 0.0000000 8.0360000 29.4670000 - 13 13 1 0.0000000 0.0000000 13.3940000 2.6790000 - 14 14 1 0.0000000 0.0000000 13.3940000 8.0360000 - 15 15 1 0.0000000 0.0000000 13.3940000 13.3940000 - 16 16 1 0.0000000 0.0000000 13.3940000 18.7520000 - 17 17 1 0.0000000 0.0000000 13.3940000 24.1090000 - 18 18 1 0.0000000 0.0000000 13.3940000 29.4670000 - 19 19 1 0.0000000 0.0000000 18.7520000 2.6790000 - 20 20 1 0.0000000 0.0000000 18.7520000 8.0360000 - 21 21 1 0.0000000 0.0000000 18.7520000 13.3940000 - 22 22 1 0.0000000 0.0000000 18.7520000 18.7520000 - 23 23 1 0.0000000 0.0000000 18.7520000 24.1090000 - 24 24 1 0.0000000 0.0000000 18.7520000 29.4670000 - 25 25 1 0.0000000 0.0000000 24.1090000 2.6790000 - 26 26 1 0.0000000 0.0000000 24.1090000 8.0360000 - 27 27 1 0.0000000 0.0000000 24.1090000 13.3940000 - 28 28 1 0.0000000 0.0000000 24.1090000 18.7520000 - 29 29 1 0.0000000 0.0000000 24.1090000 24.1090000 - 30 30 1 0.0000000 0.0000000 24.1090000 29.4670000 - 31 31 1 0.0000000 0.0000000 29.4670000 2.6790000 - 32 32 1 0.0000000 0.0000000 29.4670000 8.0360000 - 33 33 1 0.0000000 0.0000000 29.4670000 13.3940000 - 34 34 1 0.0000000 0.0000000 29.4670000 18.7520000 - 35 35 1 0.0000000 0.0000000 29.4670000 24.1090000 - 36 36 1 0.0000000 0.0000000 29.4670000 29.4670000 - 37 37 1 0.0000000 5.3580000 2.6790000 2.6790000 - 38 38 1 0.0000000 5.3580000 2.6790000 8.0360000 - 39 39 1 0.0000000 5.3580000 2.6790000 13.3940000 - 40 40 1 0.0000000 5.3580000 2.6790000 18.7520000 - 41 41 1 0.0000000 5.3580000 2.6790000 24.1090000 - 42 42 1 0.0000000 5.3580000 2.6790000 29.4670000 - 43 43 1 0.0000000 5.3580000 8.0360000 2.6790000 - 44 44 1 0.0000000 5.3580000 8.0360000 8.0360000 - 45 45 1 0.0000000 5.3580000 8.0360000 13.3940000 - 46 46 1 0.0000000 5.3580000 8.0360000 18.7520000 - 47 47 1 0.0000000 5.3580000 8.0360000 24.1090000 - 48 48 1 0.0000000 5.3580000 8.0360000 29.4670000 - 49 49 1 0.0000000 5.3580000 13.3940000 2.6790000 - 50 50 1 0.0000000 5.3580000 13.3940000 8.0360000 - 51 51 1 0.0000000 5.3580000 13.3940000 13.3940000 - 52 52 1 0.0000000 5.3580000 13.3940000 18.7520000 - 53 53 1 0.0000000 5.3580000 13.3940000 24.1090000 - 54 54 1 0.0000000 5.3580000 13.3940000 29.4670000 - 55 55 1 0.0000000 5.3580000 18.7520000 2.6790000 - 56 56 1 0.0000000 5.3580000 18.7520000 8.0360000 - 57 57 1 0.0000000 5.3580000 18.7520000 13.3940000 - 58 58 1 0.0000000 5.3580000 18.7520000 18.7520000 - 59 59 1 0.0000000 5.3580000 18.7520000 24.1090000 - 60 60 1 0.0000000 5.3580000 18.7520000 29.4670000 - 61 61 1 0.0000000 5.3580000 24.1090000 2.6790000 - 62 62 1 0.0000000 5.3580000 24.1090000 8.0360000 - 63 63 1 0.0000000 5.3580000 24.1090000 13.3940000 - 64 64 1 0.0000000 5.3580000 24.1090000 18.7520000 - 65 65 1 0.0000000 5.3580000 24.1090000 24.1090000 - 66 66 1 0.0000000 5.3580000 24.1090000 29.4670000 - 67 67 1 0.0000000 5.3580000 29.4670000 2.6790000 - 68 68 1 0.0000000 5.3580000 29.4670000 8.0360000 - 69 69 1 0.0000000 5.3580000 29.4670000 13.3940000 - 70 70 1 0.0000000 5.3580000 29.4670000 18.7520000 - 71 71 1 0.0000000 5.3580000 29.4670000 24.1090000 - 72 72 1 0.0000000 5.3580000 29.4670000 29.4670000 - 73 73 1 0.0000000 10.7150000 2.6790000 2.6790000 - 74 74 1 0.0000000 10.7150000 2.6790000 8.0360000 - 75 75 1 0.0000000 10.7150000 2.6790000 13.3940000 - 76 76 1 0.0000000 10.7150000 2.6790000 18.7520000 - 77 77 1 0.0000000 10.7150000 2.6790000 24.1090000 - 78 78 1 0.0000000 10.7150000 2.6790000 29.4670000 - 79 79 1 0.0000000 10.7150000 8.0360000 2.6790000 - 80 80 1 0.0000000 10.7150000 8.0360000 8.0360000 - 81 81 1 0.0000000 10.7150000 8.0360000 13.3940000 - 82 82 1 0.0000000 10.7150000 8.0360000 18.7520000 - 83 83 1 0.0000000 10.7150000 8.0360000 24.1090000 - 84 84 1 0.0000000 10.7150000 8.0360000 29.4670000 - 85 85 1 0.0000000 10.7150000 13.3940000 2.6790000 - 86 86 1 0.0000000 10.7150000 13.3940000 8.0360000 - 87 87 1 0.0000000 10.7150000 13.3940000 13.3940000 - 88 88 1 0.0000000 10.7150000 13.3940000 18.7520000 - 89 89 1 0.0000000 10.7150000 13.3940000 24.1090000 - 90 90 1 0.0000000 10.7150000 13.3940000 29.4670000 - 91 91 1 0.0000000 10.7150000 18.7520000 2.6790000 - 92 92 1 0.0000000 10.7150000 18.7520000 8.0360000 - 93 93 1 0.0000000 10.7150000 18.7520000 13.3940000 - 94 94 1 0.0000000 10.7150000 18.7520000 18.7520000 - 95 95 1 0.0000000 10.7150000 18.7520000 24.1090000 - 96 96 1 0.0000000 10.7150000 18.7520000 29.4670000 - 97 97 1 0.0000000 10.7150000 24.1090000 2.6790000 - 98 98 1 0.0000000 10.7150000 24.1090000 8.0360000 - 99 99 1 0.0000000 10.7150000 24.1090000 13.3940000 - 100 100 1 0.0000000 10.7150000 24.1090000 18.7520000 - 101 101 1 0.0000000 10.7150000 24.1090000 24.1090000 - 102 102 1 0.0000000 10.7150000 24.1090000 29.4670000 - 103 103 1 0.0000000 10.7150000 29.4670000 2.6790000 - 104 104 1 0.0000000 10.7150000 29.4670000 8.0360000 - 105 105 1 0.0000000 10.7150000 29.4670000 13.3940000 - 106 106 1 0.0000000 10.7150000 29.4670000 18.7520000 - 107 107 1 0.0000000 10.7150000 29.4670000 24.1090000 - 108 108 1 0.0000000 10.7150000 29.4670000 29.4670000 - 109 109 1 0.0000000 16.0730000 2.6790000 2.6790000 - 110 110 1 0.0000000 16.0730000 2.6790000 8.0360000 - 111 111 1 0.0000000 16.0730000 2.6790000 13.3940000 - 112 112 1 0.0000000 16.0730000 2.6790000 18.7520000 - 113 113 1 0.0000000 16.0730000 2.6790000 24.1090000 - 114 114 1 0.0000000 16.0730000 2.6790000 29.4670000 - 115 115 1 0.0000000 16.0730000 8.0360000 2.6790000 - 116 116 1 0.0000000 16.0730000 8.0360000 8.0360000 - 117 117 1 0.0000000 16.0730000 8.0360000 13.3940000 - 118 118 1 0.0000000 16.0730000 8.0360000 18.7520000 - 119 119 1 0.0000000 16.0730000 8.0360000 24.1090000 - 120 120 1 0.0000000 16.0730000 8.0360000 29.4670000 - 121 121 1 0.0000000 16.0730000 13.3940000 2.6790000 - 122 122 1 0.0000000 16.0730000 13.3940000 8.0360000 - 123 123 1 0.0000000 16.0730000 13.3940000 13.3940000 - 124 124 1 0.0000000 16.0730000 13.3940000 18.7520000 - 125 125 1 0.0000000 16.0730000 13.3940000 24.1090000 - 126 126 1 0.0000000 16.0730000 13.3940000 29.4670000 - 127 127 1 0.0000000 16.0730000 18.7520000 2.6790000 - 128 128 1 0.0000000 16.0730000 18.7520000 8.0360000 - 129 129 1 0.0000000 16.0730000 18.7520000 13.3940000 - 130 130 1 0.0000000 16.0730000 18.7520000 18.7520000 - 131 131 1 0.0000000 16.0730000 18.7520000 24.1090000 - 132 132 1 0.0000000 16.0730000 18.7520000 29.4670000 - 133 133 1 0.0000000 16.0730000 24.1090000 2.6790000 - 134 134 1 0.0000000 16.0730000 24.1090000 8.0360000 - 135 135 1 0.0000000 16.0730000 24.1090000 13.3940000 - 136 136 1 0.0000000 16.0730000 24.1090000 18.7520000 - 137 137 1 0.0000000 16.0730000 24.1090000 24.1090000 - 138 138 1 0.0000000 16.0730000 24.1090000 29.4670000 - 139 139 1 0.0000000 16.0730000 29.4670000 2.6790000 - 140 140 1 0.0000000 16.0730000 29.4670000 8.0360000 - 141 141 1 0.0000000 16.0730000 29.4670000 13.3940000 - 142 142 1 0.0000000 16.0730000 29.4670000 18.7520000 - 143 143 1 0.0000000 16.0730000 29.4670000 24.1090000 - 144 144 1 0.0000000 16.0730000 29.4670000 29.4670000 - 145 145 1 0.0000000 21.4310000 2.6790000 2.6790000 - 146 146 1 0.0000000 21.4310000 2.6790000 8.0360000 - 147 147 1 0.0000000 21.4310000 2.6790000 13.3940000 - 148 148 1 0.0000000 21.4310000 2.6790000 18.7520000 - 149 149 1 0.0000000 21.4310000 2.6790000 24.1090000 - 150 150 1 0.0000000 21.4310000 2.6790000 29.4670000 - 151 151 1 0.0000000 21.4310000 8.0360000 2.6790000 - 152 152 1 0.0000000 21.4310000 8.0360000 8.0360000 - 153 153 1 0.0000000 21.4310000 8.0360000 13.3940000 - 154 154 1 0.0000000 21.4310000 8.0360000 18.7520000 - 155 155 1 0.0000000 21.4310000 8.0360000 24.1090000 - 156 156 1 0.0000000 21.4310000 8.0360000 29.4670000 - 157 157 1 0.0000000 21.4310000 13.3940000 2.6790000 - 158 158 1 0.0000000 21.4310000 13.3940000 8.0360000 - 159 159 1 0.0000000 21.4310000 13.3940000 13.3940000 - 160 160 1 0.0000000 21.4310000 13.3940000 18.7520000 - 161 161 1 0.0000000 21.4310000 13.3940000 24.1090000 - 162 162 1 0.0000000 21.4310000 13.3940000 29.4670000 - 163 163 1 0.0000000 21.4310000 18.7520000 2.6790000 - 164 164 1 0.0000000 21.4310000 18.7520000 8.0360000 - 165 165 1 0.0000000 21.4310000 18.7520000 13.3940000 - 166 166 1 0.0000000 21.4310000 18.7520000 18.7520000 - 167 167 1 0.0000000 21.4310000 18.7520000 24.1090000 - 168 168 1 0.0000000 21.4310000 18.7520000 29.4670000 - 169 169 1 0.0000000 21.4310000 24.1090000 2.6790000 - 170 170 1 0.0000000 21.4310000 24.1090000 8.0360000 - 171 171 1 0.0000000 21.4310000 24.1090000 13.3940000 - 172 172 1 0.0000000 21.4310000 24.1090000 18.7520000 - 173 173 1 0.0000000 21.4310000 24.1090000 24.1090000 - 174 174 1 0.0000000 21.4310000 24.1090000 29.4670000 - 175 175 1 0.0000000 21.4310000 29.4670000 2.6790000 - 176 176 1 0.0000000 21.4310000 29.4670000 8.0360000 - 177 177 1 0.0000000 21.4310000 29.4670000 13.3940000 - 178 178 1 0.0000000 21.4310000 29.4670000 18.7520000 - 179 179 1 0.0000000 21.4310000 29.4670000 24.1090000 - 180 180 1 0.0000000 21.4310000 29.4670000 29.4670000 - 181 181 1 0.0000000 26.7880000 2.6790000 2.6790000 - 182 182 1 0.0000000 26.7880000 2.6790000 8.0360000 - 183 183 1 0.0000000 26.7880000 2.6790000 13.3940000 - 184 184 1 0.0000000 26.7880000 2.6790000 18.7520000 - 185 185 1 0.0000000 26.7880000 2.6790000 24.1090000 - 186 186 1 0.0000000 26.7880000 2.6790000 29.4670000 - 187 187 1 0.0000000 26.7880000 8.0360000 2.6790000 - 188 188 1 0.0000000 26.7880000 8.0360000 8.0360000 - 189 189 1 0.0000000 26.7880000 8.0360000 13.3940000 - 190 190 1 0.0000000 26.7880000 8.0360000 18.7520000 - 191 191 1 0.0000000 26.7880000 8.0360000 24.1090000 - 192 192 1 0.0000000 26.7880000 8.0360000 29.4670000 - 193 193 1 0.0000000 26.7880000 13.3940000 2.6790000 - 194 194 1 0.0000000 26.7880000 13.3940000 8.0360000 - 195 195 1 0.0000000 26.7880000 13.3940000 13.3940000 - 196 196 1 0.0000000 26.7880000 13.3940000 18.7520000 - 197 197 1 0.0000000 26.7880000 13.3940000 24.1090000 - 198 198 1 0.0000000 26.7880000 13.3940000 29.4670000 - 199 199 1 0.0000000 26.7880000 18.7520000 2.6790000 - 200 200 1 0.0000000 26.7880000 18.7520000 8.0360000 - 201 201 1 0.0000000 26.7880000 18.7520000 13.3940000 - 202 202 1 0.0000000 26.7880000 18.7520000 18.7520000 - 203 203 1 0.0000000 26.7880000 18.7520000 24.1090000 - 204 204 1 0.0000000 26.7880000 18.7520000 29.4670000 - 205 205 1 0.0000000 26.7880000 24.1090000 2.6790000 - 206 206 1 0.0000000 26.7880000 24.1090000 8.0360000 - 207 207 1 0.0000000 26.7880000 24.1090000 13.3940000 - 208 208 1 0.0000000 26.7880000 24.1090000 18.7520000 - 209 209 1 0.0000000 26.7880000 24.1090000 24.1090000 - 210 210 1 0.0000000 26.7880000 24.1090000 29.4670000 - 211 211 1 0.0000000 26.7880000 29.4670000 2.6790000 - 212 212 1 0.0000000 26.7880000 29.4670000 8.0360000 - 213 213 1 0.0000000 26.7880000 29.4670000 13.3940000 - 214 214 1 0.0000000 26.7880000 29.4670000 18.7520000 - 215 215 1 0.0000000 26.7880000 29.4670000 24.1090000 - 216 216 1 0.0000000 26.7880000 29.4670000 29.4670000 - 217 217 1 0.0000000 2.6790000 5.3580000 2.6790000 - 218 218 1 0.0000000 2.6790000 5.3580000 8.0360000 - 219 219 1 0.0000000 2.6790000 5.3580000 13.3940000 - 220 220 1 0.0000000 2.6790000 5.3580000 18.7520000 - 221 221 1 0.0000000 2.6790000 5.3580000 24.1090000 - 222 222 1 0.0000000 2.6790000 5.3580000 29.4670000 - 223 223 1 0.0000000 2.6790000 10.7150000 2.6790000 - 224 224 1 0.0000000 2.6790000 10.7150000 8.0360000 - 225 225 1 0.0000000 2.6790000 10.7150000 13.3940000 - 226 226 1 0.0000000 2.6790000 10.7150000 18.7520000 - 227 227 1 0.0000000 2.6790000 10.7150000 24.1090000 - 228 228 1 0.0000000 2.6790000 10.7150000 29.4670000 - 229 229 1 0.0000000 2.6790000 16.0730000 2.6790000 - 230 230 1 0.0000000 2.6790000 16.0730000 8.0360000 - 231 231 1 0.0000000 2.6790000 16.0730000 13.3940000 - 232 232 1 0.0000000 2.6790000 16.0730000 18.7520000 - 233 233 1 0.0000000 2.6790000 16.0730000 24.1090000 - 234 234 1 0.0000000 2.6790000 16.0730000 29.4670000 - 235 235 1 0.0000000 2.6790000 21.4310000 2.6790000 - 236 236 1 0.0000000 2.6790000 21.4310000 8.0360000 - 237 237 1 0.0000000 2.6790000 21.4310000 13.3940000 - 238 238 1 0.0000000 2.6790000 21.4310000 18.7520000 - 239 239 1 0.0000000 2.6790000 21.4310000 24.1090000 - 240 240 1 0.0000000 2.6790000 21.4310000 29.4670000 - 241 241 1 0.0000000 2.6790000 26.7880000 2.6790000 - 242 242 1 0.0000000 2.6790000 26.7880000 8.0360000 - 243 243 1 0.0000000 2.6790000 26.7880000 13.3940000 - 244 244 1 0.0000000 2.6790000 26.7880000 18.7520000 - 245 245 1 0.0000000 2.6790000 26.7880000 24.1090000 - 246 246 1 0.0000000 2.6790000 26.7880000 29.4670000 - 247 247 1 0.0000000 2.6790000 32.1460000 2.6790000 - 248 248 1 0.0000000 2.6790000 32.1460000 8.0360000 - 249 249 1 0.0000000 2.6790000 32.1460000 13.3940000 - 250 250 1 0.0000000 2.6790000 32.1460000 18.7520000 - 251 251 1 0.0000000 2.6790000 32.1460000 24.1090000 - 252 252 1 0.0000000 2.6790000 32.1460000 29.4670000 - 253 253 1 0.0000000 8.0360000 5.3580000 2.6790000 - 254 254 1 0.0000000 8.0360000 5.3580000 8.0360000 - 255 255 1 0.0000000 8.0360000 5.3580000 13.3940000 - 256 256 1 0.0000000 8.0360000 5.3580000 18.7520000 - 257 257 1 0.0000000 8.0360000 5.3580000 24.1090000 - 258 258 1 0.0000000 8.0360000 5.3580000 29.4670000 - 259 259 1 0.0000000 8.0360000 10.7150000 2.6790000 - 260 260 1 0.0000000 8.0360000 10.7150000 8.0360000 - 261 261 1 0.0000000 8.0360000 10.7150000 13.3940000 - 262 262 1 0.0000000 8.0360000 10.7150000 18.7520000 - 263 263 1 0.0000000 8.0360000 10.7150000 24.1090000 - 264 264 1 0.0000000 8.0360000 10.7150000 29.4670000 - 265 265 1 0.0000000 8.0360000 16.0730000 2.6790000 - 266 266 1 0.0000000 8.0360000 16.0730000 8.0360000 - 267 267 1 0.0000000 8.0360000 16.0730000 13.3940000 - 268 268 1 0.0000000 8.0360000 16.0730000 18.7520000 - 269 269 1 0.0000000 8.0360000 16.0730000 24.1090000 - 270 270 1 0.0000000 8.0360000 16.0730000 29.4670000 - 271 271 1 0.0000000 8.0360000 21.4310000 2.6790000 - 272 272 1 0.0000000 8.0360000 21.4310000 8.0360000 - 273 273 1 0.0000000 8.0360000 21.4310000 13.3940000 - 274 274 1 0.0000000 8.0360000 21.4310000 18.7520000 - 275 275 1 0.0000000 8.0360000 21.4310000 24.1090000 - 276 276 1 0.0000000 8.0360000 21.4310000 29.4670000 - 277 277 1 0.0000000 8.0360000 26.7880000 2.6790000 - 278 278 1 0.0000000 8.0360000 26.7880000 8.0360000 - 279 279 1 0.0000000 8.0360000 26.7880000 13.3940000 - 280 280 1 0.0000000 8.0360000 26.7880000 18.7520000 - 281 281 1 0.0000000 8.0360000 26.7880000 24.1090000 - 282 282 1 0.0000000 8.0360000 26.7880000 29.4670000 - 283 283 1 0.0000000 8.0360000 32.1460000 2.6790000 - 284 284 1 0.0000000 8.0360000 32.1460000 8.0360000 - 285 285 1 0.0000000 8.0360000 32.1460000 13.3940000 - 286 286 1 0.0000000 8.0360000 32.1460000 18.7520000 - 287 287 1 0.0000000 8.0360000 32.1460000 24.1090000 - 288 288 1 0.0000000 8.0360000 32.1460000 29.4670000 - 289 289 1 0.0000000 13.3940000 5.3580000 2.6790000 - 290 290 1 0.0000000 13.3940000 5.3580000 8.0360000 - 291 291 1 0.0000000 13.3940000 5.3580000 13.3940000 - 292 292 1 0.0000000 13.3940000 5.3580000 18.7520000 - 293 293 1 0.0000000 13.3940000 5.3580000 24.1090000 - 294 294 1 0.0000000 13.3940000 5.3580000 29.4670000 - 295 295 1 0.0000000 13.3940000 10.7150000 2.6790000 - 296 296 1 0.0000000 13.3940000 10.7150000 8.0360000 - 297 297 1 0.0000000 13.3940000 10.7150000 13.3940000 - 298 298 1 0.0000000 13.3940000 10.7150000 18.7520000 - 299 299 1 0.0000000 13.3940000 10.7150000 24.1090000 - 300 300 1 0.0000000 13.3940000 10.7150000 29.4670000 - 301 301 1 0.0000000 13.3940000 16.0730000 2.6790000 - 302 302 1 0.0000000 13.3940000 16.0730000 8.0360000 - 303 303 1 0.0000000 13.3940000 16.0730000 13.3940000 - 304 304 1 0.0000000 13.3940000 16.0730000 18.7520000 - 305 305 1 0.0000000 13.3940000 16.0730000 24.1090000 - 306 306 1 0.0000000 13.3940000 16.0730000 29.4670000 - 307 307 1 0.0000000 13.3940000 21.4310000 2.6790000 - 308 308 1 0.0000000 13.3940000 21.4310000 8.0360000 - 309 309 1 0.0000000 13.3940000 21.4310000 13.3940000 - 310 310 1 0.0000000 13.3940000 21.4310000 18.7520000 - 311 311 1 0.0000000 13.3940000 21.4310000 24.1090000 - 312 312 1 0.0000000 13.3940000 21.4310000 29.4670000 - 313 313 1 0.0000000 13.3940000 26.7880000 2.6790000 - 314 314 1 0.0000000 13.3940000 26.7880000 8.0360000 - 315 315 1 0.0000000 13.3940000 26.7880000 13.3940000 - 316 316 1 0.0000000 13.3940000 26.7880000 18.7520000 - 317 317 1 0.0000000 13.3940000 26.7880000 24.1090000 - 318 318 1 0.0000000 13.3940000 26.7880000 29.4670000 - 319 319 1 0.0000000 13.3940000 32.1460000 2.6790000 - 320 320 1 0.0000000 13.3940000 32.1460000 8.0360000 - 321 321 1 0.0000000 13.3940000 32.1460000 13.3940000 - 322 322 1 0.0000000 13.3940000 32.1460000 18.7520000 - 323 323 1 0.0000000 13.3940000 32.1460000 24.1090000 - 324 324 1 0.0000000 13.3940000 32.1460000 29.4670000 - 325 325 1 0.0000000 18.7520000 5.3580000 2.6790000 - 326 326 1 0.0000000 18.7520000 5.3580000 8.0360000 - 327 327 1 0.0000000 18.7520000 5.3580000 13.3940000 - 328 328 1 0.0000000 18.7520000 5.3580000 18.7520000 - 329 329 1 0.0000000 18.7520000 5.3580000 24.1090000 - 330 330 1 0.0000000 18.7520000 5.3580000 29.4670000 - 331 331 1 0.0000000 18.7520000 10.7150000 2.6790000 - 332 332 1 0.0000000 18.7520000 10.7150000 8.0360000 - 333 333 1 0.0000000 18.7520000 10.7150000 13.3940000 - 334 334 1 0.0000000 18.7520000 10.7150000 18.7520000 - 335 335 1 0.0000000 18.7520000 10.7150000 24.1090000 - 336 336 1 0.0000000 18.7520000 10.7150000 29.4670000 - 337 337 1 0.0000000 18.7520000 16.0730000 2.6790000 - 338 338 1 0.0000000 18.7520000 16.0730000 8.0360000 - 339 339 1 0.0000000 18.7520000 16.0730000 13.3940000 - 340 340 1 0.0000000 18.7520000 16.0730000 18.7520000 - 341 341 1 0.0000000 18.7520000 16.0730000 24.1090000 - 342 342 1 0.0000000 18.7520000 16.0730000 29.4670000 - 343 343 1 0.0000000 18.7520000 21.4310000 2.6790000 - 344 344 1 0.0000000 18.7520000 21.4310000 8.0360000 - 345 345 1 0.0000000 18.7520000 21.4310000 13.3940000 - 346 346 1 0.0000000 18.7520000 21.4310000 18.7520000 - 347 347 1 0.0000000 18.7520000 21.4310000 24.1090000 - 348 348 1 0.0000000 18.7520000 21.4310000 29.4670000 - 349 349 1 0.0000000 18.7520000 26.7880000 2.6790000 - 350 350 1 0.0000000 18.7520000 26.7880000 8.0360000 - 351 351 1 0.0000000 18.7520000 26.7880000 13.3940000 - 352 352 1 0.0000000 18.7520000 26.7880000 18.7520000 - 353 353 1 0.0000000 18.7520000 26.7880000 24.1090000 - 354 354 1 0.0000000 18.7520000 26.7880000 29.4670000 - 355 355 1 0.0000000 18.7520000 32.1460000 2.6790000 - 356 356 1 0.0000000 18.7520000 32.1460000 8.0360000 - 357 357 1 0.0000000 18.7520000 32.1460000 13.3940000 - 358 358 1 0.0000000 18.7520000 32.1460000 18.7520000 - 359 359 1 0.0000000 18.7520000 32.1460000 24.1090000 - 360 360 1 0.0000000 18.7520000 32.1460000 29.4670000 - 361 361 1 0.0000000 24.1090000 5.3580000 2.6790000 - 362 362 1 0.0000000 24.1090000 5.3580000 8.0360000 - 363 363 1 0.0000000 24.1090000 5.3580000 13.3940000 - 364 364 1 0.0000000 24.1090000 5.3580000 18.7520000 - 365 365 1 0.0000000 24.1090000 5.3580000 24.1090000 - 366 366 1 0.0000000 24.1090000 5.3580000 29.4670000 - 367 367 1 0.0000000 24.1090000 10.7150000 2.6790000 - 368 368 1 0.0000000 24.1090000 10.7150000 8.0360000 - 369 369 1 0.0000000 24.1090000 10.7150000 13.3940000 - 370 370 1 0.0000000 24.1090000 10.7150000 18.7520000 - 371 371 1 0.0000000 24.1090000 10.7150000 24.1090000 - 372 372 1 0.0000000 24.1090000 10.7150000 29.4670000 - 373 373 1 0.0000000 24.1090000 16.0730000 2.6790000 - 374 374 1 0.0000000 24.1090000 16.0730000 8.0360000 - 375 375 1 0.0000000 24.1090000 16.0730000 13.3940000 - 376 376 1 0.0000000 24.1090000 16.0730000 18.7520000 - 377 377 1 0.0000000 24.1090000 16.0730000 24.1090000 - 378 378 1 0.0000000 24.1090000 16.0730000 29.4670000 - 379 379 1 0.0000000 24.1090000 21.4310000 2.6790000 - 380 380 1 0.0000000 24.1090000 21.4310000 8.0360000 - 381 381 1 0.0000000 24.1090000 21.4310000 13.3940000 - 382 382 1 0.0000000 24.1090000 21.4310000 18.7520000 - 383 383 1 0.0000000 24.1090000 21.4310000 24.1090000 - 384 384 1 0.0000000 24.1090000 21.4310000 29.4670000 - 385 385 1 0.0000000 24.1090000 26.7880000 2.6790000 - 386 386 1 0.0000000 24.1090000 26.7880000 8.0360000 - 387 387 1 0.0000000 24.1090000 26.7880000 13.3940000 - 388 388 1 0.0000000 24.1090000 26.7880000 18.7520000 - 389 389 1 0.0000000 24.1090000 26.7880000 24.1090000 - 390 390 1 0.0000000 24.1090000 26.7880000 29.4670000 - 391 391 1 0.0000000 24.1090000 32.1460000 2.6790000 - 392 392 1 0.0000000 24.1090000 32.1460000 8.0360000 - 393 393 1 0.0000000 24.1090000 32.1460000 13.3940000 - 394 394 1 0.0000000 24.1090000 32.1460000 18.7520000 - 395 395 1 0.0000000 24.1090000 32.1460000 24.1090000 - 396 396 1 0.0000000 24.1090000 32.1460000 29.4670000 - 397 397 1 0.0000000 29.4670000 5.3580000 2.6790000 - 398 398 1 0.0000000 29.4670000 5.3580000 8.0360000 - 399 399 1 0.0000000 29.4670000 5.3580000 13.3940000 - 400 400 1 0.0000000 29.4670000 5.3580000 18.7520000 - 401 401 1 0.0000000 29.4670000 5.3580000 24.1090000 - 402 402 1 0.0000000 29.4670000 5.3580000 29.4670000 - 403 403 1 0.0000000 29.4670000 10.7150000 2.6790000 - 404 404 1 0.0000000 29.4670000 10.7150000 8.0360000 - 405 405 1 0.0000000 29.4670000 10.7150000 13.3940000 - 406 406 1 0.0000000 29.4670000 10.7150000 18.7520000 - 407 407 1 0.0000000 29.4670000 10.7150000 24.1090000 - 408 408 1 0.0000000 29.4670000 10.7150000 29.4670000 - 409 409 1 0.0000000 29.4670000 16.0730000 2.6790000 - 410 410 1 0.0000000 29.4670000 16.0730000 8.0360000 - 411 411 1 0.0000000 29.4670000 16.0730000 13.3940000 - 412 412 1 0.0000000 29.4670000 16.0730000 18.7520000 - 413 413 1 0.0000000 29.4670000 16.0730000 24.1090000 - 414 414 1 0.0000000 29.4670000 16.0730000 29.4670000 - 415 415 1 0.0000000 29.4670000 21.4310000 2.6790000 - 416 416 1 0.0000000 29.4670000 21.4310000 8.0360000 - 417 417 1 0.0000000 29.4670000 21.4310000 13.3940000 - 418 418 1 0.0000000 29.4670000 21.4310000 18.7520000 - 419 419 1 0.0000000 29.4670000 21.4310000 24.1090000 - 420 420 1 0.0000000 29.4670000 21.4310000 29.4670000 - 421 421 1 0.0000000 29.4670000 26.7880000 2.6790000 - 422 422 1 0.0000000 29.4670000 26.7880000 8.0360000 - 423 423 1 0.0000000 29.4670000 26.7880000 13.3940000 - 424 424 1 0.0000000 29.4670000 26.7880000 18.7520000 - 425 425 1 0.0000000 29.4670000 26.7880000 24.1090000 - 426 426 1 0.0000000 29.4670000 26.7880000 29.4670000 - 427 427 1 0.0000000 29.4670000 32.1460000 2.6790000 - 428 428 1 0.0000000 29.4670000 32.1460000 8.0360000 - 429 429 1 0.0000000 29.4670000 32.1460000 13.3940000 - 430 430 1 0.0000000 29.4670000 32.1460000 18.7520000 - 431 431 1 0.0000000 29.4670000 32.1460000 24.1090000 - 432 432 1 0.0000000 29.4670000 32.1460000 29.4670000 - 433 433 1 0.0000000 2.6790000 2.6790000 5.3580000 - 434 434 1 0.0000000 2.6790000 2.6790000 10.7150000 - 435 435 1 0.0000000 2.6790000 2.6790000 16.0730000 - 436 436 1 0.0000000 2.6790000 2.6790000 21.4310000 - 437 437 1 0.0000000 2.6790000 2.6790000 26.7880000 - 438 438 1 0.0000000 2.6790000 2.6790000 32.1460000 - 439 439 1 0.0000000 2.6790000 8.0360000 5.3580000 - 440 440 1 0.0000000 2.6790000 8.0360000 10.7150000 - 441 441 1 0.0000000 2.6790000 8.0360000 16.0730000 - 442 442 1 0.0000000 2.6790000 8.0360000 21.4310000 - 443 443 1 0.0000000 2.6790000 8.0360000 26.7880000 - 444 444 1 0.0000000 2.6790000 8.0360000 32.1460000 - 445 445 1 0.0000000 2.6790000 13.3940000 5.3580000 - 446 446 1 0.0000000 2.6790000 13.3940000 10.7150000 - 447 447 1 0.0000000 2.6790000 13.3940000 16.0730000 - 448 448 1 0.0000000 2.6790000 13.3940000 21.4310000 - 449 449 1 0.0000000 2.6790000 13.3940000 26.7880000 - 450 450 1 0.0000000 2.6790000 13.3940000 32.1460000 - 451 451 1 0.0000000 2.6790000 18.7520000 5.3580000 - 452 452 1 0.0000000 2.6790000 18.7520000 10.7150000 - 453 453 1 0.0000000 2.6790000 18.7520000 16.0730000 - 454 454 1 0.0000000 2.6790000 18.7520000 21.4310000 - 455 455 1 0.0000000 2.6790000 18.7520000 26.7880000 - 456 456 1 0.0000000 2.6790000 18.7520000 32.1460000 - 457 457 1 0.0000000 2.6790000 24.1090000 5.3580000 - 458 458 1 0.0000000 2.6790000 24.1090000 10.7150000 - 459 459 1 0.0000000 2.6790000 24.1090000 16.0730000 - 460 460 1 0.0000000 2.6790000 24.1090000 21.4310000 - 461 461 1 0.0000000 2.6790000 24.1090000 26.7880000 - 462 462 1 0.0000000 2.6790000 24.1090000 32.1460000 - 463 463 1 0.0000000 2.6790000 29.4670000 5.3580000 - 464 464 1 0.0000000 2.6790000 29.4670000 10.7150000 - 465 465 1 0.0000000 2.6790000 29.4670000 16.0730000 - 466 466 1 0.0000000 2.6790000 29.4670000 21.4310000 - 467 467 1 0.0000000 2.6790000 29.4670000 26.7880000 - 468 468 1 0.0000000 2.6790000 29.4670000 32.1460000 - 469 469 1 0.0000000 8.0360000 2.6790000 5.3580000 - 470 470 1 0.0000000 8.0360000 2.6790000 10.7150000 - 471 471 1 0.0000000 8.0360000 2.6790000 16.0730000 - 472 472 1 0.0000000 8.0360000 2.6790000 21.4310000 - 473 473 1 0.0000000 8.0360000 2.6790000 26.7880000 - 474 474 1 0.0000000 8.0360000 2.6790000 32.1460000 - 475 475 1 0.0000000 8.0360000 8.0360000 5.3580000 - 476 476 1 0.0000000 8.0360000 8.0360000 10.7150000 - 477 477 1 0.0000000 8.0360000 8.0360000 16.0730000 - 478 478 1 0.0000000 8.0360000 8.0360000 21.4310000 - 479 479 1 0.0000000 8.0360000 8.0360000 26.7880000 - 480 480 1 0.0000000 8.0360000 8.0360000 32.1460000 - 481 481 1 0.0000000 8.0360000 13.3940000 5.3580000 - 482 482 1 0.0000000 8.0360000 13.3940000 10.7150000 - 483 483 1 0.0000000 8.0360000 13.3940000 16.0730000 - 484 484 1 0.0000000 8.0360000 13.3940000 21.4310000 - 485 485 1 0.0000000 8.0360000 13.3940000 26.7880000 - 486 486 1 0.0000000 8.0360000 13.3940000 32.1460000 - 487 487 1 0.0000000 8.0360000 18.7520000 5.3580000 - 488 488 1 0.0000000 8.0360000 18.7520000 10.7150000 - 489 489 1 0.0000000 8.0360000 18.7520000 16.0730000 - 490 490 1 0.0000000 8.0360000 18.7520000 21.4310000 - 491 491 1 0.0000000 8.0360000 18.7520000 26.7880000 - 492 492 1 0.0000000 8.0360000 18.7520000 32.1460000 - 493 493 1 0.0000000 8.0360000 24.1090000 5.3580000 - 494 494 1 0.0000000 8.0360000 24.1090000 10.7150000 - 495 495 1 0.0000000 8.0360000 24.1090000 16.0730000 - 496 496 1 0.0000000 8.0360000 24.1090000 21.4310000 - 497 497 1 0.0000000 8.0360000 24.1090000 26.7880000 - 498 498 1 0.0000000 8.0360000 24.1090000 32.1460000 - 499 499 1 0.0000000 8.0360000 29.4670000 5.3580000 - 500 500 1 0.0000000 8.0360000 29.4670000 10.7150000 - 501 501 1 0.0000000 8.0360000 29.4670000 16.0730000 - 502 502 1 0.0000000 8.0360000 29.4670000 21.4310000 - 503 503 1 0.0000000 8.0360000 29.4670000 26.7880000 - 504 504 1 0.0000000 8.0360000 29.4670000 32.1460000 - 505 505 1 0.0000000 13.3940000 2.6790000 5.3580000 - 506 506 1 0.0000000 13.3940000 2.6790000 10.7150000 - 507 507 1 0.0000000 13.3940000 2.6790000 16.0730000 - 508 508 1 0.0000000 13.3940000 2.6790000 21.4310000 - 509 509 1 0.0000000 13.3940000 2.6790000 26.7880000 - 510 510 1 0.0000000 13.3940000 2.6790000 32.1460000 - 511 511 1 0.0000000 13.3940000 8.0360000 5.3580000 - 512 512 1 0.0000000 13.3940000 8.0360000 10.7150000 - 513 513 1 0.0000000 13.3940000 8.0360000 16.0730000 - 514 514 1 0.0000000 13.3940000 8.0360000 21.4310000 - 515 515 1 0.0000000 13.3940000 8.0360000 26.7880000 - 516 516 1 0.0000000 13.3940000 8.0360000 32.1460000 - 517 517 1 0.0000000 13.3940000 13.3940000 5.3580000 - 518 518 1 0.0000000 13.3940000 13.3940000 10.7150000 - 519 519 1 0.0000000 13.3940000 13.3940000 16.0730000 - 520 520 1 0.0000000 13.3940000 13.3940000 21.4310000 - 521 521 1 0.0000000 13.3940000 13.3940000 26.7880000 - 522 522 1 0.0000000 13.3940000 13.3940000 32.1460000 - 523 523 1 0.0000000 13.3940000 18.7520000 5.3580000 - 524 524 1 0.0000000 13.3940000 18.7520000 10.7150000 - 525 525 1 0.0000000 13.3940000 18.7520000 16.0730000 - 526 526 1 0.0000000 13.3940000 18.7520000 21.4310000 - 527 527 1 0.0000000 13.3940000 18.7520000 26.7880000 - 528 528 1 0.0000000 13.3940000 18.7520000 32.1460000 - 529 529 1 0.0000000 13.3940000 24.1090000 5.3580000 - 530 530 1 0.0000000 13.3940000 24.1090000 10.7150000 - 531 531 1 0.0000000 13.3940000 24.1090000 16.0730000 - 532 532 1 0.0000000 13.3940000 24.1090000 21.4310000 - 533 533 1 0.0000000 13.3940000 24.1090000 26.7880000 - 534 534 1 0.0000000 13.3940000 24.1090000 32.1460000 - 535 535 1 0.0000000 13.3940000 29.4670000 5.3580000 - 536 536 1 0.0000000 13.3940000 29.4670000 10.7150000 - 537 537 1 0.0000000 13.3940000 29.4670000 16.0730000 - 538 538 1 0.0000000 13.3940000 29.4670000 21.4310000 - 539 539 1 0.0000000 13.3940000 29.4670000 26.7880000 - 540 540 1 0.0000000 13.3940000 29.4670000 32.1460000 - 541 541 1 0.0000000 18.7520000 2.6790000 5.3580000 - 542 542 1 0.0000000 18.7520000 2.6790000 10.7150000 - 543 543 1 0.0000000 18.7520000 2.6790000 16.0730000 - 544 544 1 0.0000000 18.7520000 2.6790000 21.4310000 - 545 545 1 0.0000000 18.7520000 2.6790000 26.7880000 - 546 546 1 0.0000000 18.7520000 2.6790000 32.1460000 - 547 547 1 0.0000000 18.7520000 8.0360000 5.3580000 - 548 548 1 0.0000000 18.7520000 8.0360000 10.7150000 - 549 549 1 0.0000000 18.7520000 8.0360000 16.0730000 - 550 550 1 0.0000000 18.7520000 8.0360000 21.4310000 - 551 551 1 0.0000000 18.7520000 8.0360000 26.7880000 - 552 552 1 0.0000000 18.7520000 8.0360000 32.1460000 - 553 553 1 0.0000000 18.7520000 13.3940000 5.3580000 - 554 554 1 0.0000000 18.7520000 13.3940000 10.7150000 - 555 555 1 0.0000000 18.7520000 13.3940000 16.0730000 - 556 556 1 0.0000000 18.7520000 13.3940000 21.4310000 - 557 557 1 0.0000000 18.7520000 13.3940000 26.7880000 - 558 558 1 0.0000000 18.7520000 13.3940000 32.1460000 - 559 559 1 0.0000000 18.7520000 18.7520000 5.3580000 - 560 560 1 0.0000000 18.7520000 18.7520000 10.7150000 - 561 561 1 0.0000000 18.7520000 18.7520000 16.0730000 - 562 562 1 0.0000000 18.7520000 18.7520000 21.4310000 - 563 563 1 0.0000000 18.7520000 18.7520000 26.7880000 - 564 564 1 0.0000000 18.7520000 18.7520000 32.1460000 - 565 565 1 0.0000000 18.7520000 24.1090000 5.3580000 - 566 566 1 0.0000000 18.7520000 24.1090000 10.7150000 - 567 567 1 0.0000000 18.7520000 24.1090000 16.0730000 - 568 568 1 0.0000000 18.7520000 24.1090000 21.4310000 - 569 569 1 0.0000000 18.7520000 24.1090000 26.7880000 - 570 570 1 0.0000000 18.7520000 24.1090000 32.1460000 - 571 571 1 0.0000000 18.7520000 29.4670000 5.3580000 - 572 572 1 0.0000000 18.7520000 29.4670000 10.7150000 - 573 573 1 0.0000000 18.7520000 29.4670000 16.0730000 - 574 574 1 0.0000000 18.7520000 29.4670000 21.4310000 - 575 575 1 0.0000000 18.7520000 29.4670000 26.7880000 - 576 576 1 0.0000000 18.7520000 29.4670000 32.1460000 - 577 577 1 0.0000000 24.1090000 2.6790000 5.3580000 - 578 578 1 0.0000000 24.1090000 2.6790000 10.7150000 - 579 579 1 0.0000000 24.1090000 2.6790000 16.0730000 - 580 580 1 0.0000000 24.1090000 2.6790000 21.4310000 - 581 581 1 0.0000000 24.1090000 2.6790000 26.7880000 - 582 582 1 0.0000000 24.1090000 2.6790000 32.1460000 - 583 583 1 0.0000000 24.1090000 8.0360000 5.3580000 - 584 584 1 0.0000000 24.1090000 8.0360000 10.7150000 - 585 585 1 0.0000000 24.1090000 8.0360000 16.0730000 - 586 586 1 0.0000000 24.1090000 8.0360000 21.4310000 - 587 587 1 0.0000000 24.1090000 8.0360000 26.7880000 - 588 588 1 0.0000000 24.1090000 8.0360000 32.1460000 - 589 589 1 0.0000000 24.1090000 13.3940000 5.3580000 - 590 590 1 0.0000000 24.1090000 13.3940000 10.7150000 - 591 591 1 0.0000000 24.1090000 13.3940000 16.0730000 - 592 592 1 0.0000000 24.1090000 13.3940000 21.4310000 - 593 593 1 0.0000000 24.1090000 13.3940000 26.7880000 - 594 594 1 0.0000000 24.1090000 13.3940000 32.1460000 - 595 595 1 0.0000000 24.1090000 18.7520000 5.3580000 - 596 596 1 0.0000000 24.1090000 18.7520000 10.7150000 - 597 597 1 0.0000000 24.1090000 18.7520000 16.0730000 - 598 598 1 0.0000000 24.1090000 18.7520000 21.4310000 - 599 599 1 0.0000000 24.1090000 18.7520000 26.7880000 - 600 600 1 0.0000000 24.1090000 18.7520000 32.1460000 - 601 601 1 0.0000000 24.1090000 24.1090000 5.3580000 - 602 602 1 0.0000000 24.1090000 24.1090000 10.7150000 - 603 603 1 0.0000000 24.1090000 24.1090000 16.0730000 - 604 604 1 0.0000000 24.1090000 24.1090000 21.4310000 - 605 605 1 0.0000000 24.1090000 24.1090000 26.7880000 - 606 606 1 0.0000000 24.1090000 24.1090000 32.1460000 - 607 607 1 0.0000000 24.1090000 29.4670000 5.3580000 - 608 608 1 0.0000000 24.1090000 29.4670000 10.7150000 - 609 609 1 0.0000000 24.1090000 29.4670000 16.0730000 - 610 610 1 0.0000000 24.1090000 29.4670000 21.4310000 - 611 611 1 0.0000000 24.1090000 29.4670000 26.7880000 - 612 612 1 0.0000000 24.1090000 29.4670000 32.1460000 - 613 613 1 0.0000000 29.4670000 2.6790000 5.3580000 - 614 614 1 0.0000000 29.4670000 2.6790000 10.7150000 - 615 615 1 0.0000000 29.4670000 2.6790000 16.0730000 - 616 616 1 0.0000000 29.4670000 2.6790000 21.4310000 - 617 617 1 0.0000000 29.4670000 2.6790000 26.7880000 - 618 618 1 0.0000000 29.4670000 2.6790000 32.1460000 - 619 619 1 0.0000000 29.4670000 8.0360000 5.3580000 - 620 620 1 0.0000000 29.4670000 8.0360000 10.7150000 - 621 621 1 0.0000000 29.4670000 8.0360000 16.0730000 - 622 622 1 0.0000000 29.4670000 8.0360000 21.4310000 - 623 623 1 0.0000000 29.4670000 8.0360000 26.7880000 - 624 624 1 0.0000000 29.4670000 8.0360000 32.1460000 - 625 625 1 0.0000000 29.4670000 13.3940000 5.3580000 - 626 626 1 0.0000000 29.4670000 13.3940000 10.7150000 - 627 627 1 0.0000000 29.4670000 13.3940000 16.0730000 - 628 628 1 0.0000000 29.4670000 13.3940000 21.4310000 - 629 629 1 0.0000000 29.4670000 13.3940000 26.7880000 - 630 630 1 0.0000000 29.4670000 13.3940000 32.1460000 - 631 631 1 0.0000000 29.4670000 18.7520000 5.3580000 - 632 632 1 0.0000000 29.4670000 18.7520000 10.7150000 - 633 633 1 0.0000000 29.4670000 18.7520000 16.0730000 - 634 634 1 0.0000000 29.4670000 18.7520000 21.4310000 - 635 635 1 0.0000000 29.4670000 18.7520000 26.7880000 - 636 636 1 0.0000000 29.4670000 18.7520000 32.1460000 - 637 637 1 0.0000000 29.4670000 24.1090000 5.3580000 - 638 638 1 0.0000000 29.4670000 24.1090000 10.7150000 - 639 639 1 0.0000000 29.4670000 24.1090000 16.0730000 - 640 640 1 0.0000000 29.4670000 24.1090000 21.4310000 - 641 641 1 0.0000000 29.4670000 24.1090000 26.7880000 - 642 642 1 0.0000000 29.4670000 24.1090000 32.1460000 - 643 643 1 0.0000000 29.4670000 29.4670000 5.3580000 - 644 644 1 0.0000000 29.4670000 29.4670000 10.7150000 - 645 645 1 0.0000000 29.4670000 29.4670000 16.0730000 - 646 646 1 0.0000000 29.4670000 29.4670000 21.4310000 - 647 647 1 0.0000000 29.4670000 29.4670000 26.7880000 - 648 648 1 0.0000000 29.4670000 29.4670000 32.1460000 - 649 649 1 0.0000000 0.0000000 5.3580000 5.3580000 - 650 650 1 0.0000000 0.0000000 5.3580000 10.7150000 - 651 651 1 0.0000000 0.0000000 5.3580000 16.0730000 - 652 652 1 0.0000000 0.0000000 5.3580000 21.4310000 - 653 653 1 0.0000000 0.0000000 5.3580000 26.7880000 - 654 654 1 0.0000000 0.0000000 5.3580000 32.1460000 - 655 655 1 0.0000000 0.0000000 10.7150000 5.3580000 - 656 656 1 0.0000000 0.0000000 10.7150000 10.7150000 - 657 657 1 0.0000000 0.0000000 10.7150000 16.0730000 - 658 658 1 0.0000000 0.0000000 10.7150000 21.4310000 - 659 659 1 0.0000000 0.0000000 10.7150000 26.7880000 - 660 660 1 0.0000000 0.0000000 10.7150000 32.1460000 - 661 661 1 0.0000000 0.0000000 16.0730000 5.3580000 - 662 662 1 0.0000000 0.0000000 16.0730000 10.7150000 - 663 663 1 0.0000000 0.0000000 16.0730000 16.0730000 - 664 664 1 0.0000000 0.0000000 16.0730000 21.4310000 - 665 665 1 0.0000000 0.0000000 16.0730000 26.7880000 - 666 666 1 0.0000000 0.0000000 16.0730000 32.1460000 - 667 667 1 0.0000000 0.0000000 21.4310000 5.3580000 - 668 668 1 0.0000000 0.0000000 21.4310000 10.7150000 - 669 669 1 0.0000000 0.0000000 21.4310000 16.0730000 - 670 670 1 0.0000000 0.0000000 21.4310000 21.4310000 - 671 671 1 0.0000000 0.0000000 21.4310000 26.7880000 - 672 672 1 0.0000000 0.0000000 21.4310000 32.1460000 - 673 673 1 0.0000000 0.0000000 26.7880000 5.3580000 - 674 674 1 0.0000000 0.0000000 26.7880000 10.7150000 - 675 675 1 0.0000000 0.0000000 26.7880000 16.0730000 - 676 676 1 0.0000000 0.0000000 26.7880000 21.4310000 - 677 677 1 0.0000000 0.0000000 26.7880000 26.7880000 - 678 678 1 0.0000000 0.0000000 26.7880000 32.1460000 - 679 679 1 0.0000000 0.0000000 32.1460000 5.3580000 - 680 680 1 0.0000000 0.0000000 32.1460000 10.7150000 - 681 681 1 0.0000000 0.0000000 32.1460000 16.0730000 - 682 682 1 0.0000000 0.0000000 32.1460000 21.4310000 - 683 683 1 0.0000000 0.0000000 32.1460000 26.7880000 - 684 684 1 0.0000000 0.0000000 32.1460000 32.1460000 - 685 685 1 0.0000000 5.3580000 5.3580000 5.3580000 - 686 686 1 0.0000000 5.3580000 5.3580000 10.7150000 - 687 687 1 0.0000000 5.3580000 5.3580000 16.0730000 - 688 688 1 0.0000000 5.3580000 5.3580000 21.4310000 - 689 689 1 0.0000000 5.3580000 5.3580000 26.7880000 - 690 690 1 0.0000000 5.3580000 5.3580000 32.1460000 - 691 691 1 0.0000000 5.3580000 10.7150000 5.3580000 - 692 692 1 0.0000000 5.3580000 10.7150000 10.7150000 - 693 693 1 0.0000000 5.3580000 10.7150000 16.0730000 - 694 694 1 0.0000000 5.3580000 10.7150000 21.4310000 - 695 695 1 0.0000000 5.3580000 10.7150000 26.7880000 - 696 696 1 0.0000000 5.3580000 10.7150000 32.1460000 - 697 697 1 0.0000000 5.3580000 16.0730000 5.3580000 - 698 698 1 0.0000000 5.3580000 16.0730000 10.7150000 - 699 699 1 0.0000000 5.3580000 16.0730000 16.0730000 - 700 700 1 0.0000000 5.3580000 16.0730000 21.4310000 - 701 701 1 0.0000000 5.3580000 16.0730000 26.7880000 - 702 702 1 0.0000000 5.3580000 16.0730000 32.1460000 - 703 703 1 0.0000000 5.3580000 21.4310000 5.3580000 - 704 704 1 0.0000000 5.3580000 21.4310000 10.7150000 - 705 705 1 0.0000000 5.3580000 21.4310000 16.0730000 - 706 706 1 0.0000000 5.3580000 21.4310000 21.4310000 - 707 707 1 0.0000000 5.3580000 21.4310000 26.7880000 - 708 708 1 0.0000000 5.3580000 21.4310000 32.1460000 - 709 709 1 0.0000000 5.3580000 26.7880000 5.3580000 - 710 710 1 0.0000000 5.3580000 26.7880000 10.7150000 - 711 711 1 0.0000000 5.3580000 26.7880000 16.0730000 - 712 712 1 0.0000000 5.3580000 26.7880000 21.4310000 - 713 713 1 0.0000000 5.3580000 26.7880000 26.7880000 - 714 714 1 0.0000000 5.3580000 26.7880000 32.1460000 - 715 715 1 0.0000000 5.3580000 32.1460000 5.3580000 - 716 716 1 0.0000000 5.3580000 32.1460000 10.7150000 - 717 717 1 0.0000000 5.3580000 32.1460000 16.0730000 - 718 718 1 0.0000000 5.3580000 32.1460000 21.4310000 - 719 719 1 0.0000000 5.3580000 32.1460000 26.7880000 - 720 720 1 0.0000000 5.3580000 32.1460000 32.1460000 - 721 721 1 0.0000000 10.7150000 5.3580000 5.3580000 - 722 722 1 0.0000000 10.7150000 5.3580000 10.7150000 - 723 723 1 0.0000000 10.7150000 5.3580000 16.0730000 - 724 724 1 0.0000000 10.7150000 5.3580000 21.4310000 - 725 725 1 0.0000000 10.7150000 5.3580000 26.7880000 - 726 726 1 0.0000000 10.7150000 5.3580000 32.1460000 - 727 727 1 0.0000000 10.7150000 10.7150000 5.3580000 - 728 728 1 0.0000000 10.7150000 10.7150000 10.7150000 - 729 729 1 0.0000000 10.7150000 10.7150000 16.0730000 - 730 730 1 0.0000000 10.7150000 10.7150000 21.4310000 - 731 731 1 0.0000000 10.7150000 10.7150000 26.7880000 - 732 732 1 0.0000000 10.7150000 10.7150000 32.1460000 - 733 733 1 0.0000000 10.7150000 16.0730000 5.3580000 - 734 734 1 0.0000000 10.7150000 16.0730000 10.7150000 - 735 735 1 0.0000000 10.7150000 16.0730000 16.0730000 - 736 736 1 0.0000000 10.7150000 16.0730000 21.4310000 - 737 737 1 0.0000000 10.7150000 16.0730000 26.7880000 - 738 738 1 0.0000000 10.7150000 16.0730000 32.1460000 - 739 739 1 0.0000000 10.7150000 21.4310000 5.3580000 - 740 740 1 0.0000000 10.7150000 21.4310000 10.7150000 - 741 741 1 0.0000000 10.7150000 21.4310000 16.0730000 - 742 742 1 0.0000000 10.7150000 21.4310000 21.4310000 - 743 743 1 0.0000000 10.7150000 21.4310000 26.7880000 - 744 744 1 0.0000000 10.7150000 21.4310000 32.1460000 - 745 745 1 0.0000000 10.7150000 26.7880000 5.3580000 - 746 746 1 0.0000000 10.7150000 26.7880000 10.7150000 - 747 747 1 0.0000000 10.7150000 26.7880000 16.0730000 - 748 748 1 0.0000000 10.7150000 26.7880000 21.4310000 - 749 749 1 0.0000000 10.7150000 26.7880000 26.7880000 - 750 750 1 0.0000000 10.7150000 26.7880000 32.1460000 - 751 751 1 0.0000000 10.7150000 32.1460000 5.3580000 - 752 752 1 0.0000000 10.7150000 32.1460000 10.7150000 - 753 753 1 0.0000000 10.7150000 32.1460000 16.0730000 - 754 754 1 0.0000000 10.7150000 32.1460000 21.4310000 - 755 755 1 0.0000000 10.7150000 32.1460000 26.7880000 - 756 756 1 0.0000000 10.7150000 32.1460000 32.1460000 - 757 757 1 0.0000000 16.0730000 5.3580000 5.3580000 - 758 758 1 0.0000000 16.0730000 5.3580000 10.7150000 - 759 759 1 0.0000000 16.0730000 5.3580000 16.0730000 - 760 760 1 0.0000000 16.0730000 5.3580000 21.4310000 - 761 761 1 0.0000000 16.0730000 5.3580000 26.7880000 - 762 762 1 0.0000000 16.0730000 5.3580000 32.1460000 - 763 763 1 0.0000000 16.0730000 10.7150000 5.3580000 - 764 764 1 0.0000000 16.0730000 10.7150000 10.7150000 - 765 765 1 0.0000000 16.0730000 10.7150000 16.0730000 - 766 766 1 0.0000000 16.0730000 10.7150000 21.4310000 - 767 767 1 0.0000000 16.0730000 10.7150000 26.7880000 - 768 768 1 0.0000000 16.0730000 10.7150000 32.1460000 - 769 769 1 0.0000000 16.0730000 16.0730000 5.3580000 - 770 770 1 0.0000000 16.0730000 16.0730000 10.7150000 - 771 771 1 0.0000000 16.0730000 16.0730000 16.0730000 - 772 772 1 0.0000000 16.0730000 16.0730000 21.4310000 - 773 773 1 0.0000000 16.0730000 16.0730000 26.7880000 - 774 774 1 0.0000000 16.0730000 16.0730000 32.1460000 - 775 775 1 0.0000000 16.0730000 21.4310000 5.3580000 - 776 776 1 0.0000000 16.0730000 21.4310000 10.7150000 - 777 777 1 0.0000000 16.0730000 21.4310000 16.0730000 - 778 778 1 0.0000000 16.0730000 21.4310000 21.4310000 - 779 779 1 0.0000000 16.0730000 21.4310000 26.7880000 - 780 780 1 0.0000000 16.0730000 21.4310000 32.1460000 - 781 781 1 0.0000000 16.0730000 26.7880000 5.3580000 - 782 782 1 0.0000000 16.0730000 26.7880000 10.7150000 - 783 783 1 0.0000000 16.0730000 26.7880000 16.0730000 - 784 784 1 0.0000000 16.0730000 26.7880000 21.4310000 - 785 785 1 0.0000000 16.0730000 26.7880000 26.7880000 - 786 786 1 0.0000000 16.0730000 26.7880000 32.1460000 - 787 787 1 0.0000000 16.0730000 32.1460000 5.3580000 - 788 788 1 0.0000000 16.0730000 32.1460000 10.7150000 - 789 789 1 0.0000000 16.0730000 32.1460000 16.0730000 - 790 790 1 0.0000000 16.0730000 32.1460000 21.4310000 - 791 791 1 0.0000000 16.0730000 32.1460000 26.7880000 - 792 792 1 0.0000000 16.0730000 32.1460000 32.1460000 - 793 793 1 0.0000000 21.4310000 5.3580000 5.3580000 - 794 794 1 0.0000000 21.4310000 5.3580000 10.7150000 - 795 795 1 0.0000000 21.4310000 5.3580000 16.0730000 - 796 796 1 0.0000000 21.4310000 5.3580000 21.4310000 - 797 797 1 0.0000000 21.4310000 5.3580000 26.7880000 - 798 798 1 0.0000000 21.4310000 5.3580000 32.1460000 - 799 799 1 0.0000000 21.4310000 10.7150000 5.3580000 - 800 800 1 0.0000000 21.4310000 10.7150000 10.7150000 - 801 801 1 0.0000000 21.4310000 10.7150000 16.0730000 - 802 802 1 0.0000000 21.4310000 10.7150000 21.4310000 - 803 803 1 0.0000000 21.4310000 10.7150000 26.7880000 - 804 804 1 0.0000000 21.4310000 10.7150000 32.1460000 - 805 805 1 0.0000000 21.4310000 16.0730000 5.3580000 - 806 806 1 0.0000000 21.4310000 16.0730000 10.7150000 - 807 807 1 0.0000000 21.4310000 16.0730000 16.0730000 - 808 808 1 0.0000000 21.4310000 16.0730000 21.4310000 - 809 809 1 0.0000000 21.4310000 16.0730000 26.7880000 - 810 810 1 0.0000000 21.4310000 16.0730000 32.1460000 - 811 811 1 0.0000000 21.4310000 21.4310000 5.3580000 - 812 812 1 0.0000000 21.4310000 21.4310000 10.7150000 - 813 813 1 0.0000000 21.4310000 21.4310000 16.0730000 - 814 814 1 0.0000000 21.4310000 21.4310000 21.4310000 - 815 815 1 0.0000000 21.4310000 21.4310000 26.7880000 - 816 816 1 0.0000000 21.4310000 21.4310000 32.1460000 - 817 817 1 0.0000000 21.4310000 26.7880000 5.3580000 - 818 818 1 0.0000000 21.4310000 26.7880000 10.7150000 - 819 819 1 0.0000000 21.4310000 26.7880000 16.0730000 - 820 820 1 0.0000000 21.4310000 26.7880000 21.4310000 - 821 821 1 0.0000000 21.4310000 26.7880000 26.7880000 - 822 822 1 0.0000000 21.4310000 26.7880000 32.1460000 - 823 823 1 0.0000000 21.4310000 32.1460000 5.3580000 - 824 824 1 0.0000000 21.4310000 32.1460000 10.7150000 - 825 825 1 0.0000000 21.4310000 32.1460000 16.0730000 - 826 826 1 0.0000000 21.4310000 32.1460000 21.4310000 - 827 827 1 0.0000000 21.4310000 32.1460000 26.7880000 - 828 828 1 0.0000000 21.4310000 32.1460000 32.1460000 - 829 829 1 0.0000000 26.7880000 5.3580000 5.3580000 - 830 830 1 0.0000000 26.7880000 5.3580000 10.7150000 - 831 831 1 0.0000000 26.7880000 5.3580000 16.0730000 - 832 832 1 0.0000000 26.7880000 5.3580000 21.4310000 - 833 833 1 0.0000000 26.7880000 5.3580000 26.7880000 - 834 834 1 0.0000000 26.7880000 5.3580000 32.1460000 - 835 835 1 0.0000000 26.7880000 10.7150000 5.3580000 - 836 836 1 0.0000000 26.7880000 10.7150000 10.7150000 - 837 837 1 0.0000000 26.7880000 10.7150000 16.0730000 - 838 838 1 0.0000000 26.7880000 10.7150000 21.4310000 - 839 839 1 0.0000000 26.7880000 10.7150000 26.7880000 - 840 840 1 0.0000000 26.7880000 10.7150000 32.1460000 - 841 841 1 0.0000000 26.7880000 16.0730000 5.3580000 - 842 842 1 0.0000000 26.7880000 16.0730000 10.7150000 - 843 843 1 0.0000000 26.7880000 16.0730000 16.0730000 - 844 844 1 0.0000000 26.7880000 16.0730000 21.4310000 - 845 845 1 0.0000000 26.7880000 16.0730000 26.7880000 - 846 846 1 0.0000000 26.7880000 16.0730000 32.1460000 - 847 847 1 0.0000000 26.7880000 21.4310000 5.3580000 - 848 848 1 0.0000000 26.7880000 21.4310000 10.7150000 - 849 849 1 0.0000000 26.7880000 21.4310000 16.0730000 - 850 850 1 0.0000000 26.7880000 21.4310000 21.4310000 - 851 851 1 0.0000000 26.7880000 21.4310000 26.7880000 - 852 852 1 0.0000000 26.7880000 21.4310000 32.1460000 - 853 853 1 0.0000000 26.7880000 26.7880000 5.3580000 - 854 854 1 0.0000000 26.7880000 26.7880000 10.7150000 - 855 855 1 0.0000000 26.7880000 26.7880000 16.0730000 - 856 856 1 0.0000000 26.7880000 26.7880000 21.4310000 - 857 857 1 0.0000000 26.7880000 26.7880000 26.7880000 - 858 858 1 0.0000000 26.7880000 26.7880000 32.1460000 - 859 859 1 0.0000000 26.7880000 32.1460000 5.3580000 - 860 860 1 0.0000000 26.7880000 32.1460000 10.7150000 - 861 861 1 0.0000000 26.7880000 32.1460000 16.0730000 - 862 862 1 0.0000000 26.7880000 32.1460000 21.4310000 - 863 863 1 0.0000000 26.7880000 32.1460000 26.7880000 - 864 864 1 0.0000000 26.7880000 32.1460000 32.1460000 - diff --git a/examples/python/gjf_python/ff-argon.lmp b/examples/python/gjf_python/ff-argon.lmp deleted file mode 100644 index b6f7bc931a..0000000000 --- a/examples/python/gjf_python/ff-argon.lmp +++ /dev/null @@ -1,20 +0,0 @@ -############################# -#Atoms types - mass - charge# -############################# -#@ 1 atom types #!THIS LINE IS NECESSARY DON'T SPEND HOURS FINDING THAT OUT!# - -variable Ar equal 1 - -############# -#Atom Masses# -############# - -mass ${Ar} 39.903 - -########################### -#Pair Potentials - Tersoff# -########################### - -pair_style lj/cubic -pair_coeff * * 0.0102701 3.42 - diff --git a/examples/python/gjf_python/gjf.py b/examples/python/gjf_python/gjf.py deleted file mode 100644 index 37fc28bb79..0000000000 --- a/examples/python/gjf_python/gjf.py +++ /dev/null @@ -1,180 +0,0 @@ -"""Made by Charlie Sievers Ph.D. Candidate, UC Davis, Donadio Lab 2019""" - -from mpi4py import MPI -from lammps import lammps -import lammps_tools as lt -import numpy as np - -comm = MPI.COMM_WORLD -rank = comm.Get_rank() - -""" LAMMPS VARIABLES """ - -# new file or restart -run_no = 0 - -# data files -infile = "argon.lmp" -restart_file = "final_restart.{}".format(run_no) -ff_file = "ff-argon.lmp" -outfile = "output.dat" - -# write final_restart -write_final_restart = False - -# random numbers -seed0 = 2357 -seed1 = 26588 -seed2 = 10669 - -# MD Parameters -# number of steps -nsteps = 50000 -# timestep -# dt = 0.001 -# starting simulation temp -temp_start = 10 -# final simulation temp -temp_final = 10 -# relaxation time -trel = 1 -# trajectory frequency -ntraj = 0 - -# Ensemble 0 = GJF u, 1 = GJF v, 2 = Nose-Hoover, 3 = Langevin, 4 = BDP (Currently all NVT) -ensemble = 0 - -# Output Parameters -nthermo = 200 -nout = int(nsteps / nthermo) # Important - -# output to screen and log file? -lammps_output = False -# Lammps Thermo -thermo = False - -python_output = True - -# Write output to file? -write_output = False - -if write_output is True: - data = open("{}".format(outfile), "w") - -if python_output is True: - if rank == 0: - print("dt, temp, ke, fke, pe, fpe") - -for j in range(20): - - # timestep - dt = 0.005*(j+1) - - if lammps_output is True: - lmp = lammps() - else: - lmp = lammps(cmdargs=["-screen", "none", "-log", "none"]) - - lmp.command("atom_style full") - lmp.command("units metal") - lmp.command("processors * * *") - lmp.command("neighbor 1 bin") - lmp.command("boundary p p p") - - if run_no is 0: - lmp.command("read_data {}".format(infile)) - else: - lmp.command("read_restart final_restart".format(run_no-1)) - - if thermo is True: - lmp.command("thermo_style custom time temp pe ke press vol cpu") - lmp.command("thermo {}".format(nthermo)) - lmp.command("thermo_modify flush yes") - - lmp.file("{}".format(ff_file)) - lmp.command("timestep {}".format(dt)) - - # get_per_atom_compute example with dim of two and within a group - # lmp.command("region rand block 5 20 5 20 5 20") - # lmp.command("group rand region rand") - # lmp.command("compute x rand property/atom x y") - # test = get_per_atom_compute(comm, lmp, "x", 2, group="rand") - - lmp.command("compute ke all ke/atom") - - lmp.command("compute pe all pe") - - if ntraj != 0: - lmp.command("dump 1 all dcd {} trajectory.dcd".format(ntraj)) - lmp.command("dump_modify 1 unwrap yes") - - if run_no == 0: - lmp.command("velocity all create {} {} mom yes dist gaussian".format(temp_start, seed0)) - lmp.command("fix nve all nve") - - if ensemble == 0: - # gjf u - lmp.command("fix lang all langevin {} {} {} {} gjf yes halfstep yes".format( - temp_start, temp_final, trel, seed1)) - elif ensemble == 1: - # gjf v - lmp.command("fix lang all langevin {} {} {} {} gjf yes".format( - temp_start, temp_final, trel, seed1)) - elif ensemble == 2: - # NH - lmp.command("fix nvt all nvt temp {} {} {}".format( - temp_start, temp_final, trel)) - elif ensemble == 3: - # lang - lmp.command("fix lang all langevin {} {} {} {} tally yes zero yes".format( - temp_start, temp_final, trel, seed1)) - elif ensemble == 4: - # BDP - lmp.command("fix stoch all temp/csvr {} {} {} {}".format( - temp_start, temp_final, trel, seed1)) - - natoms = lmp.extract_global("natoms", 0) - nlocal = lmp.extract_global("nlocal", 0) - ke_sum = lt.get_per_atom_compute(comm, lmp, "ke") - ke_2 = ke_sum**2 - pe_sum = 0 - pe_2 = 0 - temp_sum = 0 - - for i in range(nout): - nlocal = lmp.extract_global("nlocal", 0) - lmp.command("run {} pre no post no".format(nthermo)) - temp = lmp.extract_compute("thermo_temp", 0, 0) - ke = lt.get_per_atom_compute(comm, lmp, "ke") - pe = lmp.extract_compute("pe", 0, 0) - ke_sum += ke - ke_2 += ke**2 - pe_sum += pe - pe_2 += pe**2 - temp_sum += temp - - if python_output is True: - if rank == 0: - print("Time: {:.6f}, Temp: {:.6f}, KE: {:.6f}, PE: {:.6f}".format( - i*nthermo*dt, temp, ke.sum(), pe)) - - if write_final_restart is True: - lmp.command("write_restart {}".format(restart_file)) - - if rank == 0: - ke = ke_sum.sum() / (nout + 1) - fke = (np.sqrt((ke_2 - ke_sum ** 2 / (nout + 1)) / (nout + 1))).sum() - pe = pe_sum / nout - fpe = np.sqrt((pe_2 - pe_sum ** 2 / nout) / nout) - temp = temp_sum / nout - - if python_output is True: - print(dt, temp, ke, fke, pe, fpe) - - if write_output is True: - data.write("{:.6f} {:.6f} {:.6f} {:.6f} {:.6f} {:.6f}\n".format( - dt, temp, ke, fke, pe, fpe)) - data.flush() - -if write_output is True: - data.close() diff --git a/examples/python/gjf_python/lammps_tools.py b/examples/python/gjf_python/lammps_tools.py deleted file mode 100644 index f9f25eaa28..0000000000 --- a/examples/python/gjf_python/lammps_tools.py +++ /dev/null @@ -1,78 +0,0 @@ -"""Made by Charlie Sievers Ph.D. Candidate, UC Davis, Donadio Lab 2019""" - -from mpi4py import MPI -import numpy as np -import ctypes as ctypes - -""" USEFULL LAMMPS FUNCTION """ - - -def get_nlocal(lmp): - - nlocal = lmp.extract_global("nlocal", 0) - - return nlocal - - -def get_aid(lmp, group=None): - - if group is None: - c_aid = lmp.extract_atom("id", 0) - ptr = ctypes.cast(c_aid, ctypes.POINTER(ctypes.c_int32 * get_nlocal(lmp))) - aid = np.frombuffer(ptr.contents, dtype=np.int32) - else: - try: - c_aid = lmp.extract_variable("aid", group, 1) - ptr = ctypes.cast(c_aid, ctypes.POINTER(ctypes.c_double * get_nlocal(lmp))) - aid = np.frombuffer(ptr.contents, dtype=np.double) - except ValueError: - lmp.command("variable aid atom id") - aid = get_aid(lmp, group) - - return aid - - -def get_per_atom_compute(comm, lmp, name, dim=1, dtype="double", group=None): - laid = get_aid(lmp, group) - nlocal = get_nlocal(lmp) - ngroup = comm.allgather(laid) - type = dim - if dim > 1: - type = 2 - for array in ngroup: - try: - aid = np.concatenate((aid, array)) - except UnboundLocalError: - aid = array - if dtype == "double": - mem_type = ctypes.c_double - elif dtype == "integer": - mem_type = ctypes.c_int - elif dtype == "bigint": - mem_type = ctypes.c_int32 - else: - print("{} not implemented".format(dtype)) - return - - tmp = lmp.extract_compute(name, 1, type) - if type == 1: - ptr = ctypes.cast(tmp, ctypes.POINTER(mem_type * nlocal)) - else: - ptr = ctypes.cast(tmp[0], ctypes.POINTER(mem_type * nlocal * dim)) - lcompute = comm.allgather(np.frombuffer(ptr.contents).reshape((-1, dim))) - for array in lcompute: - try: - compute = np.concatenate((compute, array)) - except UnboundLocalError: - compute = array - - aid = np.expand_dims(aid, axis=1) - - compute = np.concatenate((aid, compute), axis=-1) - compute = compute[compute[..., 0] != 0] - compute = compute[compute[..., 0].argsort()][..., 1:] - - if dim == 1: - compute = np.squeeze(compute, axis=-1) - - return compute \ No newline at end of file diff --git a/src/fix_langevin.cpp b/src/fix_langevin.cpp index ea0929a236..36671ba6a4 100644 --- a/src/fix_langevin.cpp +++ b/src/fix_langevin.cpp @@ -18,11 +18,10 @@ Niels Gronbech-Jensen (UC Davis) GJF-2GJ Formulation ------------------------------------------------------------------------- */ +#include "fix_langevin.h" #include #include #include -#include -#include "fix_langevin.h" #include "math_extra.h" #include "atom.h" #include "atom_vec_ellipsoid.h" @@ -30,8 +29,6 @@ #include "update.h" #include "modify.h" #include "compute.h" -#include "domain.h" -#include "region.h" #include "respa.h" #include "comm.h" #include "input.h" @@ -55,7 +52,8 @@ enum{CONSTANT,EQUAL,ATOM}; FixLangevin::FixLangevin(LAMMPS *lmp, int narg, char **arg) : Fix(lmp, narg, arg), gjfflag(0), gfactor1(NULL), gfactor2(NULL), ratio(NULL), tstr(NULL), - flangevin(NULL), tforce(NULL), franprev(NULL), id_temp(NULL), random(NULL) + flangevin(NULL), tforce(NULL), franprev(NULL), id_temp(NULL), random(NULL), + lv(NULL), wildcard(NULL), bias(NULL) { if (narg < 7) error->all(FLERR,"Illegal fix langevin command"); @@ -112,7 +110,10 @@ FixLangevin::FixLangevin(LAMMPS *lmp, int narg, char **arg) : } else if (strcmp(arg[iarg],"gjf") == 0) { if (iarg+2 > narg) error->all(FLERR,"Illegal fix langevin command"); if (strcmp(arg[iarg+1],"no") == 0) gjfflag = 0; - else if (strcmp(arg[iarg+1],"yes") == 0) gjfflag = 1; + else if (strcmp(arg[iarg+1],"yes") == 0) + error->all(FLERR,"GJF yes keyword is deprecated.\nPlease use vhalf or vfull."); + else if (strcmp(arg[iarg+1],"vfull") == 0) {gjfflag = 1; hsflag = 0;} + else if (strcmp(arg[iarg+1],"vhalf") == 0) {gjfflag = 1; hsflag = 1;} else error->all(FLERR,"Illegal fix langevin command"); iarg += 2; } else if (strcmp(arg[iarg],"omega") == 0) { @@ -141,14 +142,6 @@ FixLangevin::FixLangevin(LAMMPS *lmp, int narg, char **arg) : else if (strcmp(arg[iarg+1],"yes") == 0) zeroflag = 1; else error->all(FLERR,"Illegal fix langevin command"); iarg += 2; - } else if (strcmp(arg[iarg],"halfstep") == 0) { - if (iarg+2 > narg) error->all(FLERR,"Illegal fix langevin command"); - if (gjfflag == 0) error->all(FLERR,"GJF must be set"); - if (tallyflag == 0) error->warning(FLERR,"Careful, tally is untested"); - if (strcmp(arg[iarg+1],"no") == 0) hsflag = 0; - else if (strcmp(arg[iarg+1],"yes") == 0) hsflag = 1; - else error->all(FLERR,"Illegal fix langevin command"); - iarg += 2; } else error->all(FLERR,"Illegal fix langevin command"); } @@ -168,6 +161,7 @@ FixLangevin::FixLangevin(LAMMPS *lmp, int narg, char **arg) : franprev = NULL; wildcard = NULL; lv = NULL; + bias = NULL; tforce = NULL; maxatom1 = maxatom2 = 0; @@ -218,6 +212,7 @@ FixLangevin::~FixLangevin() memory->destroy(franprev); memory->destroy(wildcard); if (hsflag) memory->destroy(lv); + if (temperature && temperature->tempbias) memory->destroy(bias); atom->delete_callback(id,0); } } @@ -300,6 +295,9 @@ void FixLangevin::init() if (strstr(update->integrate_style,"respa")) nlevels_respa = ((Respa *) update->integrate)->nlevels; + if (strstr(update->integrate_style,"respa")) + error->one(FLERR,"Fix langevin gjf not implemented with respa capabilities"); + if (gjfflag) gjffac = 1.0/sqrt(1.0+update->dt/2.0/t_period); } @@ -331,6 +329,11 @@ void FixLangevin::setup(int vflag) wildcard[i][0] = v[i][0]; wildcard[i][1] = v[i][1]; wildcard[i][2] = v[i][2]; + if (tbiasflag == BIAS) { + bias[i][0] = 0.0; + bias[i][1] = 0.0; + bias[i][2] = 0.0; + } } } } @@ -357,34 +360,95 @@ void FixLangevin::post_integrate() int nlocal = atom->nlocal; if (igroup == atom->firstgroup) nlocal = atom->nfirst; + if (tbiasflag == BIAS) { + double b[3] = {0.0, 0.0, 0.0}; + for (int i = 0; i < nlocal; i++) { + bias[i][0] = v[i][0]; + bias[i][1] = v[i][1]; + bias[i][2] = v[i][2]; + v[i][0] = wildcard[i][0]; + v[i][1] = wildcard[i][1]; + v[i][2] = wildcard[i][2]; + } + temperature->compute_scalar(); + for (int i = 0; i < nlocal; i++) { + temperature->remove_bias(i, v[i]); + wildcard[i][0] = v[i][0]; + wildcard[i][1] = v[i][1]; + wildcard[i][2] = v[i][2]; + if (wildcard[i][0] == 0.0) franprev[i][0] = 0.0; + if (wildcard[i][1] == 0.0) franprev[i][1] = 0.0; + if (wildcard[i][2] == 0.0) franprev[i][2] = 0.0; + temperature->restore_bias(i, v[i]); + b[0] = v[i][0] - wildcard[i][0]; + b[1] = v[i][1] - wildcard[i][1]; + b[2] = v[i][2] - wildcard[i][2]; + v[i][0] = bias[i][0]; + v[i][1] = bias[i][1]; + v[i][2] = bias[i][2]; + bias[i][0] = b[0]; + bias[i][1] = b[1]; + bias[i][2] = b[2]; + } + } if (rmass) { for (int i = 0; i < nlocal; i++) if (mask[i] & groupbit) { dtfm = dtf / rmass[i]; - x[i][0] += -dt * v[i][0]; - x[i][1] += -dt * v[i][1]; - x[i][2] += -dt * v[i][2]; + x[i][0] -= dt * v[i][0]; + x[i][1] -= dt * v[i][1]; + x[i][2] -= dt * v[i][2]; v[i][0] = gjffac * (wildcard[i][0] + dtfm * franprev[i][0] + dtfm * f[i][0]); v[i][1] = gjffac * (wildcard[i][1] + dtfm * franprev[i][1] + dtfm * f[i][1]); v[i][2] = gjffac * (wildcard[i][2] + dtfm * franprev[i][2] + dtfm * f[i][2]); + if (tbiasflag == BIAS) + for (int j = 0; j < 3; j++) { + if (wildcard[i][j] == 0) { + v[i][j] /= gjffac; + } + v[i][j] += bias[i][j]; + if (wildcard[i][j] == 0){ + v[i][j] /= gjffac; + } + } x[i][0] += gjffac * dt * v[i][0]; x[i][1] += gjffac * dt * v[i][1]; x[i][2] += gjffac * dt * v[i][2]; + if (tbiasflag == BIAS) + for (int j = 0; j < 3; j++) { + if (wildcard[i][j] == 0) + v[i][j] *= gjffac; + } } } else { for (int i = 0; i < nlocal; i++) if (mask[i] & groupbit) { dtfm = dtf / mass[type[i]]; - x[i][0] += -dt * v[i][0]; - x[i][1] += -dt * v[i][1]; - x[i][2] += -dt * v[i][2]; + x[i][0] -= dt * v[i][0]; + x[i][1] -= dt * v[i][1]; + x[i][2] -= dt * v[i][2]; v[i][0] = gjffac * (wildcard[i][0] + dtfm * franprev[i][0] + dtfm * f[i][0]); v[i][1] = gjffac * (wildcard[i][1] + dtfm * franprev[i][1] + dtfm * f[i][1]); v[i][2] = gjffac * (wildcard[i][2] + dtfm * franprev[i][2] + dtfm * f[i][2]); + if (tbiasflag == BIAS) + for (int j = 0; j < 3; j++) { + if (wildcard[i][j] == 0) { + v[i][j] /= gjffac; + } + v[i][j] += bias[i][j]; + if (wildcard[i][j] == 0){ + v[i][j] /= gjffac; + } + } x[i][0] += gjffac * dt * v[i][0]; x[i][1] += gjffac * dt * v[i][1]; x[i][2] += gjffac * dt * v[i][2]; + if (tbiasflag == BIAS) + for (int j = 0; j < 3; j++) { + if (wildcard[i][j] == 0) + v[i][j] *= gjffac; + } } } } @@ -657,9 +721,17 @@ void FixLangevin::post_force_templated() if (Tp_TALLY) { if (Tp_GJF && update->ntimestep != update->beginstep){ - fdrag[0] = gamma1*gjffac*gjffac*v[i][0]; - fdrag[1] = gamma1*gjffac*gjffac*v[i][1]; - fdrag[2] = gamma1*gjffac*gjffac*v[i][2]; + if (Tp_BIAS) { + temperature->remove_bias(i,v[i]); + fdrag[0] = gamma1*gjffac*gjffac*v[i][0]; + fdrag[1] = gamma1*gjffac*gjffac*v[i][1]; + fdrag[2] = gamma1*gjffac*gjffac*v[i][2]; + temperature->restore_bias(i,v[i]); + } else { + fdrag[0] = gamma1*gjffac*gjffac*v[i][0]; + fdrag[1] = gamma1*gjffac*gjffac*v[i][1]; + fdrag[2] = gamma1*gjffac*gjffac*v[i][2]; + } fran[0] *= gjffac; fran[1] *= gjffac; fran[2] *= gjffac; @@ -894,8 +966,9 @@ void FixLangevin::end_of_step() v[i][2] = lv[i][2]; } } - energy_onestep += flangevin[i][0] * v[i][0] + flangevin[i][1] * v[i][1] + - flangevin[i][2] * v[i][2]; + if (tallyflag) + energy_onestep += flangevin[i][0] * v[i][0] + flangevin[i][1] * v[i][1] + + flangevin[i][2] * v[i][2]; } if (tallyflag) { energy += energy_onestep * update->dt; @@ -953,7 +1026,7 @@ int FixLangevin::modify_param(int narg, char **arg) double FixLangevin::compute_scalar() { - if (!tallyflag || !flangevin_allocated) return 0.0; + if (!tallyflag && !flangevin_allocated) return 0.0; // capture the very first energy transfer to thermal reservoir @@ -1004,6 +1077,7 @@ double FixLangevin::memory_usage() double bytes = 0.0; if (gjfflag) bytes += atom->nmax*3*2 * sizeof(double); if (gjfflag) if (hsflag) bytes += atom->nmax*3 * sizeof(double); + if (gjfflag && tbiasflag == BIAS) bytes += atom->nmax*3 * sizeof(double); if (tallyflag) bytes += atom->nmax*3 * sizeof(double); if (tforce) bytes += atom->nmax * sizeof(double); return bytes; @@ -1018,6 +1092,7 @@ void FixLangevin::grow_arrays(int nmax) memory->grow(franprev,nmax,3,"fix_langevin:franprev"); memory->grow(wildcard,nmax,3,"fix_langevin:wildcard"); if (hsflag) memory->grow(lv,nmax,3,"fix_langevin:lv"); + if (tbiasflag == BIAS) memory->grow(bias,nmax,3,"fix_langevin:bias"); } /* ---------------------------------------------------------------------- @@ -1037,6 +1112,11 @@ void FixLangevin::copy_arrays(int i, int j, int /*delflag*/) lv[j][1] = lv[i][1]; lv[j][2] = lv[i][2]; } + if (tbiasflag == BIAS){ + bias[j][0] = bias[i][0]; + bias[j][1] = bias[i][1]; + bias[j][2] = bias[i][2]; + } } /* ---------------------------------------------------------------------- @@ -1057,6 +1137,11 @@ int FixLangevin::pack_exchange(int i, double *buf) buf[n++] = lv[i][1]; buf[n++] = lv[i][2]; } + if (tbiasflag == BIAS){ + buf[n++] = bias[i][0]; + buf[n++] = bias[i][1]; + buf[n++] = bias[i][2]; + } return n; } @@ -1078,5 +1163,10 @@ int FixLangevin::unpack_exchange(int nlocal, double *buf) lv[nlocal][1] = buf[n++]; lv[nlocal][2] = buf[n++]; } + if (tbiasflag == BIAS){ + bias[nlocal][0] = buf[n++]; + bias[nlocal][1] = buf[n++]; + bias[nlocal][2] = buf[n++]; + } return n; } diff --git a/src/fix_langevin.h b/src/fix_langevin.h index 888734de04..1f9954153f 100644 --- a/src/fix_langevin.h +++ b/src/fix_langevin.h @@ -67,6 +67,7 @@ class FixLangevin : public Fix { double **franprev; double **lv; //2GJ velocity or half-step velocity double **wildcard; + double **bias; int nvalues; From 39050265c279ac662e5921ebb1afaa9ab26faeea Mon Sep 17 00:00:00 2001 From: charlie sievers Date: Sun, 11 Aug 2019 20:23:57 -0700 Subject: [PATCH 075/192] Added gjf zero flag functionality and tbias functionality --- src/fix_langevin.cpp | 160 ++++++++++++++++++++++++++----------------- src/fix_langevin.h | 1 + 2 files changed, 99 insertions(+), 62 deletions(-) diff --git a/src/fix_langevin.cpp b/src/fix_langevin.cpp index 36671ba6a4..3dedce1b18 100644 --- a/src/fix_langevin.cpp +++ b/src/fix_langevin.cpp @@ -239,6 +239,8 @@ void FixLangevin::init() if (ascale && !atom->ellipsoid_flag) error->all(FLERR,"Fix langevin angmom requires atom style ellipsoid"); + if (gjfflag && zeroflag && tallyflag) + error->warning(FLERR,"Fix langevin gjf zero and tally were all set"); // check variable if (tstr) { @@ -315,24 +317,29 @@ void FixLangevin::setup(int vflag) } if (gjfflag) { - // update v of atoms in group double ** v = atom->v; double **f = atom->f; int nlocal = atom->nlocal; if (igroup == atom->firstgroup) nlocal = atom->nfirst; + double b[3] = {0.0,0.0,0.0}; for (int i = 0; i < nlocal; i++) { f[i][0] = wildcard[i][0]; f[i][1] = wildcard[i][1]; f[i][2] = wildcard[i][2]; + b[0] = v[i][0]; + b[1] = v[i][1]; + b[2] = v[i][2]; + if (tbiasflag == BIAS) temperature->remove_bias(i,v[i]); wildcard[i][0] = v[i][0]; wildcard[i][1] = v[i][1]; wildcard[i][2] = v[i][2]; if (tbiasflag == BIAS) { - bias[i][0] = 0.0; - bias[i][1] = 0.0; - bias[i][2] = 0.0; + temperature->restore_bias(i,v[i]); + bias[i][0] = b[0] - wildcard[i][0]; + bias[i][1] = b[1] - wildcard[i][1]; + bias[i][2] = b[2] - wildcard[i][2]; } } } @@ -360,37 +367,17 @@ void FixLangevin::post_integrate() int nlocal = atom->nlocal; if (igroup == atom->firstgroup) nlocal = atom->nfirst; - if (tbiasflag == BIAS) { - double b[3] = {0.0, 0.0, 0.0}; - for (int i = 0; i < nlocal; i++) { - bias[i][0] = v[i][0]; - bias[i][1] = v[i][1]; - bias[i][2] = v[i][2]; - v[i][0] = wildcard[i][0]; - v[i][1] = wildcard[i][1]; - v[i][2] = wildcard[i][2]; - } - temperature->compute_scalar(); - for (int i = 0; i < nlocal; i++) { - temperature->remove_bias(i, v[i]); - wildcard[i][0] = v[i][0]; - wildcard[i][1] = v[i][1]; - wildcard[i][2] = v[i][2]; - if (wildcard[i][0] == 0.0) franprev[i][0] = 0.0; - if (wildcard[i][1] == 0.0) franprev[i][1] = 0.0; - if (wildcard[i][2] == 0.0) franprev[i][2] = 0.0; - temperature->restore_bias(i, v[i]); - b[0] = v[i][0] - wildcard[i][0]; - b[1] = v[i][1] - wildcard[i][1]; - b[2] = v[i][2] - wildcard[i][2]; - v[i][0] = bias[i][0]; - v[i][1] = bias[i][1]; - v[i][2] = bias[i][2]; - bias[i][0] = b[0]; - bias[i][1] = b[1]; - bias[i][2] = b[2]; - } + // zero option + double vsum[3],vsumall[3]; + bigint count; + + if (zeroflag) { + vsum[0] = vsum[1] = vsum[2] = 0.0; + count = group->count(igroup); + if (count == 0) + error->all(FLERR,"Cannot zero Langevin force of 0 atoms"); } + if (rmass) { for (int i = 0; i < nlocal; i++) if (mask[i] & groupbit) { @@ -404,11 +391,7 @@ void FixLangevin::post_integrate() if (tbiasflag == BIAS) for (int j = 0; j < 3; j++) { if (wildcard[i][j] == 0) { - v[i][j] /= gjffac; - } - v[i][j] += bias[i][j]; - if (wildcard[i][j] == 0){ - v[i][j] /= gjffac; + v[i][j] /= gjffac * gjffac; } } x[i][0] += gjffac * dt * v[i][0]; @@ -418,6 +401,8 @@ void FixLangevin::post_integrate() for (int j = 0; j < 3; j++) { if (wildcard[i][j] == 0) v[i][j] *= gjffac; + v[i][j] += bias[i][j]; + x[i][j] += dt * bias[i][j]; } } @@ -434,11 +419,7 @@ void FixLangevin::post_integrate() if (tbiasflag == BIAS) for (int j = 0; j < 3; j++) { if (wildcard[i][j] == 0) { - v[i][j] /= gjffac; - } - v[i][j] += bias[i][j]; - if (wildcard[i][j] == 0){ - v[i][j] /= gjffac; + v[i][j] /= gjffac*gjffac; } } x[i][0] += gjffac * dt * v[i][0]; @@ -446,11 +427,32 @@ void FixLangevin::post_integrate() x[i][2] += gjffac * dt * v[i][2]; if (tbiasflag == BIAS) for (int j = 0; j < 3; j++) { - if (wildcard[i][j] == 0) - v[i][j] *= gjffac; + if (wildcard[i][j] == 0) + v[i][j] *= gjffac; + v[i][j] += bias[i][j]; + x[i][j] += dt * bias[i][j]; } + if (zeroflag){ + vsum[0] += gjffac * dtfm * franprev[i][0]; + vsum[1] += gjffac * dtfm * franprev[i][1]; + vsum[2] += gjffac * dtfm * franprev[i][2]; + } } } + + if (zeroflag) { + MPI_Allreduce(vsum,vsumall,3,MPI_DOUBLE,MPI_SUM,world); + vsumall[0] /= count; + vsumall[1] /= count; + vsumall[2] /= count; + for (int i = 0; i < nlocal; i++) { + if (mask[i] & groupbit) { + v[i][0] -= vsumall[0]; + v[i][1] -= vsumall[1]; + v[i][2] -= vsumall[2]; + } + } + } } /* ---------------------------------------------------------------------- */ @@ -664,26 +666,34 @@ void FixLangevin::post_force_templated() flangevin_allocated = 1; } - if (Tp_BIAS) temperature->compute_scalar(); + if (Tp_BIAS && !gjfflag) temperature->compute_scalar(); + else if (Tp_BIAS && update->ntimestep == update->beginstep && gjfflag) temperature->compute_scalar(); for (int i = 0; i < nlocal; i++) { if (mask[i] & groupbit) { if (Tp_TSTYLEATOM) tsqrt = sqrt(tforce[i]); if (Tp_RMASS) { gamma1 = -rmass[i] / t_period / ftm2v; - gamma2 = sqrt(rmass[i]) * sqrt(2.0*boltz/t_period/dt/mvv2e) / ftm2v; - gamma1 *= 1.0/ratio[type[i]]; - gamma2 *= 1.0/sqrt(ratio[type[i]]) * tsqrt; + gamma2 = sqrt(rmass[i]) * sqrt(2.0 * boltz / t_period / dt / mvv2e) / ftm2v; + gamma1 *= 1.0 / ratio[type[i]]; + gamma2 *= 1.0 / sqrt(ratio[type[i]]) * tsqrt; } else { gamma1 = gfactor1[type[i]]; gamma2 = gfactor2[type[i]] * tsqrt; } - fran[0] = gamma2*random->gaussian(); - fran[1] = gamma2*random->gaussian(); - fran[2] = gamma2*random->gaussian(); + if (!gjfflag) { + fran[0] = gamma2 * random->uniform(); + fran[1] = gamma2 * random->uniform(); + fran[2] = gamma2 * random->uniform(); + } else { + fran[0] = gamma2 * random->gaussian(); + fran[1] = gamma2 * random->gaussian(); + fran[2] = gamma2 * random->gaussian(); + } if (Tp_BIAS) { + double b[3] = {0.0,0.0,0.0}; temperature->remove_bias(i,v[i]); fdrag[0] = gamma1*v[i][0]; fdrag[1] = gamma1*v[i][1]; @@ -693,9 +703,9 @@ void FixLangevin::post_force_templated() if (v[i][2] == 0.0) fran[2] = 0.0; temperature->restore_bias(i,v[i]); } else { - fdrag[0] = gamma1*v[i][0]; - fdrag[1] = gamma1*v[i][1]; - fdrag[2] = gamma1*v[i][2]; + fdrag[0] = gamma1*v[i][0];// - gjffac*(dtf / mass[type[i]])*gamma1*franprev[i][0]; + fdrag[1] = gamma1*v[i][1];// - gjffac*(dtf / mass[type[i]])*gamma1*franprev[i][1]; + fdrag[2] = gamma1*v[i][2];// - gjffac*(dtf / mass[type[i]])*gamma1*franprev[i][2]; } if (Tp_GJF) { @@ -706,13 +716,14 @@ void FixLangevin::post_force_templated() rantemp[0] = fran[0]; rantemp[1] = fran[1]; rantemp[2] = fran[2]; + fran[0] = franprev[i][0]; fran[1] = franprev[i][1]; fran[2] = franprev[i][2]; - fdrag[0] *= -2*t_period*(2*gjffac-1/gjffac-1)/dt; - fdrag[1] *= -2*t_period*(2*gjffac-1/gjffac-1)/dt; - fdrag[2] *= -2*t_period*(2*gjffac-1/gjffac-1)/dt; + fdrag[0] *= -2*t_period*((2*gjffac)-(1.0/gjffac)-1.0)/dt; + fdrag[1] *= -2*t_period*((2*gjffac)-(1.0/gjffac)-1.0)/dt; + fdrag[2] *= -2*t_period*((2*gjffac)-(1.0/gjffac)-1.0)/dt; } f[i][0] += fdrag[0] + fran[0]; @@ -747,9 +758,16 @@ void FixLangevin::post_force_templated() } if (Tp_ZERO) { - fsum[0] += fran[0]; - fsum[1] += fran[1]; - fsum[2] += fran[2]; + if (!gjfflag){ + fsum[0] += fran[0]; + fsum[1] += fran[1]; + fsum[2] += fran[2]; + } + else { + fsum[0] += franprev[i][0]; + fsum[1] += franprev[i][1]; + fsum[2] += franprev[i][2]; + } } if (Tp_GJF) @@ -762,6 +780,11 @@ void FixLangevin::post_force_templated() lv[i][0] = v[i][0]; lv[i][1] = v[i][1]; lv[i][2] = v[i][2]; + if (tbiasflag == BIAS) { + lv[i][0] += bias[i][0]; + lv[i][1] += bias[i][1]; + lv[i][2] += bias[i][2]; + } } } } @@ -949,17 +972,30 @@ void FixLangevin::end_of_step() double **f = atom->f; int *mask = atom->mask; int nlocal = atom->nlocal; + double b[3] = {0.0,0.0,0.0}; + + if (gjfflag && tbiasflag == BIAS) temperature->compute_scalar(); energy_onestep = 0.0; for (int i = 0; i < nlocal; i++) if (mask[i] & groupbit) { if (gjfflag){ + b[0] = v[i][0]; + b[1] = v[i][1]; + b[2] = v[i][2]; f[i][0] = wildcard[i][0]; f[i][1] = wildcard[i][1]; f[i][2] = wildcard[i][2]; + if (tbiasflag == BIAS) temperature->remove_bias(i,v[i]); wildcard[i][0] = v[i][0]; wildcard[i][1] = v[i][1]; wildcard[i][2] = v[i][2]; + if (tbiasflag == BIAS) { + bias[i][0] = b[0] - v[i][0]; + bias[i][1] = b[1] - v[i][1]; + bias[i][2] = b[2] - v[i][2]; + temperature->restore_bias(i, v[i]); + } if (hsflag){ v[i][0] = lv[i][0]; v[i][1] = lv[i][1]; diff --git a/src/fix_langevin.h b/src/fix_langevin.h index 1f9954153f..9cd1ecb66a 100644 --- a/src/fix_langevin.h +++ b/src/fix_langevin.h @@ -68,6 +68,7 @@ class FixLangevin : public Fix { double **lv; //2GJ velocity or half-step velocity double **wildcard; double **bias; + double cm[3]; int nvalues; From 8078ac38493eb08d56f9c377c905ce7725ca6f00 Mon Sep 17 00:00:00 2001 From: charlie sievers Date: Mon, 12 Aug 2019 15:32:13 -0700 Subject: [PATCH 076/192] cleaned up src files --- src/fix_langevin.cpp | 36 ++++++++++++++++++++++-------------- src/fix_langevin.h | 3 +-- 2 files changed, 23 insertions(+), 16 deletions(-) diff --git a/src/fix_langevin.cpp b/src/fix_langevin.cpp index 3dedce1b18..c2e56881b7 100644 --- a/src/fix_langevin.cpp +++ b/src/fix_langevin.cpp @@ -240,7 +240,8 @@ void FixLangevin::init() error->all(FLERR,"Fix langevin angmom requires atom style ellipsoid"); if (gjfflag && zeroflag && tallyflag) - error->warning(FLERR,"Fix langevin gjf zero and tally were all set"); + error->warning(FLERR, + "Fix langevin: gjf, zero, and tally were all set correct energy tallying is not guaranteed"); // check variable if (tstr) { @@ -283,9 +284,14 @@ void FixLangevin::init() if (!atom->rmass) { for (int i = 1; i <= atom->ntypes; i++) { gfactor1[i] = -atom->mass[i] / t_period / force->ftm2v; - gfactor2[i] = sqrt(atom->mass[i]) * - sqrt(2.0*force->boltz/t_period/update->dt/force->mvv2e) / - force->ftm2v; + if (gjfflag) + gfactor2[i] = sqrt(atom->mass[i]) * + sqrt(2.0*force->boltz/t_period/update->dt/force->mvv2e) / + force->ftm2v; + else + gfactor2[i] = sqrt(atom->mass[i]) * + sqrt(24.0*force->boltz/t_period/update->dt/force->mvv2e) / + force->ftm2v; gfactor1[i] *= 1.0/ratio[i]; gfactor2[i] *= 1.0/sqrt(ratio[i]); } @@ -674,7 +680,10 @@ void FixLangevin::post_force_templated() if (Tp_TSTYLEATOM) tsqrt = sqrt(tforce[i]); if (Tp_RMASS) { gamma1 = -rmass[i] / t_period / ftm2v; - gamma2 = sqrt(rmass[i]) * sqrt(2.0 * boltz / t_period / dt / mvv2e) / ftm2v; + if (gjfflag) + gamma2 = sqrt(rmass[i]) * sqrt(2.0 * boltz / t_period / dt / mvv2e) / ftm2v; + else + gamma2 = sqrt(rmass[i]) * sqrt(24.0 * boltz / t_period / dt / mvv2e) / ftm2v; gamma1 *= 1.0 / ratio[type[i]]; gamma2 *= 1.0 / sqrt(ratio[type[i]]) * tsqrt; } else { @@ -682,18 +691,17 @@ void FixLangevin::post_force_templated() gamma2 = gfactor2[type[i]] * tsqrt; } - if (!gjfflag) { - fran[0] = gamma2 * random->uniform(); - fran[1] = gamma2 * random->uniform(); - fran[2] = gamma2 * random->uniform(); - } else { + if (gjfflag) { fran[0] = gamma2 * random->gaussian(); fran[1] = gamma2 * random->gaussian(); fran[2] = gamma2 * random->gaussian(); + } else { + fran[0] = gamma2 * random->uniform(); + fran[1] = gamma2 * random->uniform(); + fran[2] = gamma2 * random->uniform(); } if (Tp_BIAS) { - double b[3] = {0.0,0.0,0.0}; temperature->remove_bias(i,v[i]); fdrag[0] = gamma1*v[i][0]; fdrag[1] = gamma1*v[i][1]; @@ -703,9 +711,9 @@ void FixLangevin::post_force_templated() if (v[i][2] == 0.0) fran[2] = 0.0; temperature->restore_bias(i,v[i]); } else { - fdrag[0] = gamma1*v[i][0];// - gjffac*(dtf / mass[type[i]])*gamma1*franprev[i][0]; - fdrag[1] = gamma1*v[i][1];// - gjffac*(dtf / mass[type[i]])*gamma1*franprev[i][1]; - fdrag[2] = gamma1*v[i][2];// - gjffac*(dtf / mass[type[i]])*gamma1*franprev[i][2]; + fdrag[0] = gamma1*v[i][0]; + fdrag[1] = gamma1*v[i][1]; + fdrag[2] = gamma1*v[i][2]; } if (Tp_GJF) { diff --git a/src/fix_langevin.h b/src/fix_langevin.h index 9cd1ecb66a..939b161c35 100644 --- a/src/fix_langevin.h +++ b/src/fix_langevin.h @@ -67,8 +67,7 @@ class FixLangevin : public Fix { double **franprev; double **lv; //2GJ velocity or half-step velocity double **wildcard; - double **bias; - double cm[3]; + double **bias; //Bias velocity int nvalues; From f2068ece84baf0cf3b5fa0f28cba819b905ea814 Mon Sep 17 00:00:00 2001 From: charlie sievers Date: Tue, 13 Aug 2019 16:06:17 -0700 Subject: [PATCH 077/192] restored regular langevin functionality --- src/fix_langevin.cpp | 12 ++++++------ 1 file changed, 6 insertions(+), 6 deletions(-) diff --git a/src/fix_langevin.cpp b/src/fix_langevin.cpp index c2e56881b7..d323453cdb 100644 --- a/src/fix_langevin.cpp +++ b/src/fix_langevin.cpp @@ -680,7 +680,7 @@ void FixLangevin::post_force_templated() if (Tp_TSTYLEATOM) tsqrt = sqrt(tforce[i]); if (Tp_RMASS) { gamma1 = -rmass[i] / t_period / ftm2v; - if (gjfflag) + if (Tp_GJF) gamma2 = sqrt(rmass[i]) * sqrt(2.0 * boltz / t_period / dt / mvv2e) / ftm2v; else gamma2 = sqrt(rmass[i]) * sqrt(24.0 * boltz / t_period / dt / mvv2e) / ftm2v; @@ -691,14 +691,14 @@ void FixLangevin::post_force_templated() gamma2 = gfactor2[type[i]] * tsqrt; } - if (gjfflag) { + if (Tp_GJF) { fran[0] = gamma2 * random->gaussian(); fran[1] = gamma2 * random->gaussian(); fran[2] = gamma2 * random->gaussian(); } else { - fran[0] = gamma2 * random->uniform(); - fran[1] = gamma2 * random->uniform(); - fran[2] = gamma2 * random->uniform(); + fran[0] = gamma2 * (random->uniform()-0.5); + fran[1] = gamma2 * (random->uniform()-0.5); + fran[2] = gamma2 * (random->uniform()-0.5); } if (Tp_BIAS) { @@ -766,7 +766,7 @@ void FixLangevin::post_force_templated() } if (Tp_ZERO) { - if (!gjfflag){ + if (!Tp_GJF){ fsum[0] += fran[0]; fsum[1] += fran[1]; fsum[2] += fran[2]; From c71e869a33cdec0c855763a0ce60928cf1149975 Mon Sep 17 00:00:00 2001 From: alxvov Date: Wed, 21 Aug 2019 14:02:34 +0000 Subject: [PATCH 078/192] define params in creator as init is called after modify --- src/SPIN/min_spin.cpp | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/src/SPIN/min_spin.cpp b/src/SPIN/min_spin.cpp index c8e0020ef8..947e281b42 100644 --- a/src/SPIN/min_spin.cpp +++ b/src/SPIN/min_spin.cpp @@ -41,15 +41,15 @@ using namespace MathConst; /* ---------------------------------------------------------------------- */ -MinSpin::MinSpin(LAMMPS *lmp) : Min(lmp) {} +MinSpin::MinSpin(LAMMPS *lmp) : Min(lmp) { + alpha_damp = 1.0; + discrete_factor = 10.0; +} /* ---------------------------------------------------------------------- */ void MinSpin::init() { - alpha_damp = 1.0; - discrete_factor = 10.0; - Min::init(); dts = dt = update->dt; From 52a51ea470dbd9f844db003af0153e3dad33c493 Mon Sep 17 00:00:00 2001 From: charlie sievers Date: Wed, 21 Aug 2019 19:14:08 -0700 Subject: [PATCH 079/192] Simplified GJF formalism --- src/fix_langevin.cpp | 762 ++++++++++++++++++------------------------- src/fix_langevin.h | 135 +++----- 2 files changed, 371 insertions(+), 526 deletions(-) diff --git a/src/fix_langevin.cpp b/src/fix_langevin.cpp index d323453cdb..b8144fc5f3 100644 --- a/src/fix_langevin.cpp +++ b/src/fix_langevin.cpp @@ -2,20 +2,16 @@ LAMMPS - Large-scale Atomic/Molecular Massively Parallel Simulator http://lammps.sandia.gov, Sandia National Laboratories Steve Plimpton, sjplimp@sandia.gov - Copyright (2003) Sandia Corporation. Under the terms of Contract DE-AC04-94AL85000 with Sandia Corporation, the U.S. Government retains certain rights in this software. This software is distributed under the GNU General Public License. - See the README file in the top-level LAMMPS directory. ------------------------------------------------------------------------- */ /* ---------------------------------------------------------------------- Contributing authors: Carolyn Phillips (U Mich), reservoir energy tally Aidan Thompson (SNL) GJF formulation - Charles Sievers (UC Davis) GJF-2GJ Implementation - Niels Gronbech-Jensen (UC Davis) GJF-2GJ Formulation ------------------------------------------------------------------------- */ #include "fix_langevin.h" @@ -50,10 +46,9 @@ enum{CONSTANT,EQUAL,ATOM}; /* ---------------------------------------------------------------------- */ FixLangevin::FixLangevin(LAMMPS *lmp, int narg, char **arg) : - Fix(lmp, narg, arg), - gjfflag(0), gfactor1(NULL), gfactor2(NULL), ratio(NULL), tstr(NULL), - flangevin(NULL), tforce(NULL), franprev(NULL), id_temp(NULL), random(NULL), - lv(NULL), wildcard(NULL), bias(NULL) + Fix(lmp, narg, arg), + gjfflag(0), gfactor1(NULL), gfactor2(NULL), ratio(NULL), tstr(NULL), + flangevin(NULL), tforce(NULL), franprev(NULL), id_temp(NULL), random(NULL), lv(NULL) { if (narg < 7) error->all(FLERR,"Illegal fix langevin command"); @@ -98,7 +93,6 @@ FixLangevin::FixLangevin(LAMMPS *lmp, int narg, char **arg) : oflag = 0; tallyflag = 0; zeroflag = 0; - hsflag = 0; int iarg = 7; while (iarg < narg) { @@ -110,10 +104,7 @@ FixLangevin::FixLangevin(LAMMPS *lmp, int narg, char **arg) : } else if (strcmp(arg[iarg],"gjf") == 0) { if (iarg+2 > narg) error->all(FLERR,"Illegal fix langevin command"); if (strcmp(arg[iarg+1],"no") == 0) gjfflag = 0; - else if (strcmp(arg[iarg+1],"yes") == 0) - error->all(FLERR,"GJF yes keyword is deprecated.\nPlease use vhalf or vfull."); - else if (strcmp(arg[iarg+1],"vfull") == 0) {gjfflag = 1; hsflag = 0;} - else if (strcmp(arg[iarg+1],"vhalf") == 0) {gjfflag = 1; hsflag = 1;} + else if (strcmp(arg[iarg+1],"yes") == 0) gjfflag = 1; else error->all(FLERR,"Illegal fix langevin command"); iarg += 2; } else if (strcmp(arg[iarg],"omega") == 0) { @@ -159,9 +150,7 @@ FixLangevin::FixLangevin(LAMMPS *lmp, int narg, char **arg) : flangevin = NULL; flangevin_allocated = 0; franprev = NULL; - wildcard = NULL; lv = NULL; - bias = NULL; tforce = NULL; maxatom1 = maxatom2 = 0; @@ -170,26 +159,19 @@ FixLangevin::FixLangevin(LAMMPS *lmp, int narg, char **arg) : // no need to set peratom_flag, b/c data is for internal use only if (gjfflag) { - - nvalues = 3; grow_arrays(atom->nmax); atom->add_callback(0); - // initialize franprev to zero + // initialize franprev to zero int nlocal = atom->nlocal; for (int i = 0; i < nlocal; i++) { franprev[i][0] = 0.0; franprev[i][1] = 0.0; franprev[i][2] = 0.0; - wildcard[i][0] = 0.0; - wildcard[i][1] = 0.0; - wildcard[i][2] = 0.0; - if (hsflag) { - lv[i][0] = 0.0; - lv[i][1] = 0.0; - lv[i][2] = 0.0; - } + lv[i][0] = 0.0; + lv[i][1] = 0.0; + lv[i][2] = 0.0; } } @@ -210,9 +192,7 @@ FixLangevin::~FixLangevin() if (gjfflag) { memory->destroy(franprev); - memory->destroy(wildcard); - if (hsflag) memory->destroy(lv); - if (temperature && temperature->tempbias) memory->destroy(bias); + memory->destroy(lv); atom->delete_callback(id,0); } } @@ -222,7 +202,8 @@ FixLangevin::~FixLangevin() int FixLangevin::setmask() { int mask = 0; - if (gjfflag) mask |= POST_INTEGRATE; + if (gjfflag) mask |= INITIAL_INTEGRATE; + if (gjfflag) mask |= INITIAL_INTEGRATE_RESPA; mask |= POST_FORCE; mask |= POST_FORCE_RESPA; mask |= END_OF_STEP; @@ -234,14 +215,26 @@ int FixLangevin::setmask() void FixLangevin::init() { + if (gjfflag){ + if (t_period*2 == update->dt) + error->all(FLERR,"Fix langevin gjf cannot have t_period equal to dt/2 at the start"); + + // warn if any integrate fix comes after this one + int before = 1; + int flag = 0; + for (int i = 0; i < modify->nfix; i++) { + if (strcmp(id,modify->fix[i]->id) == 0) before = 0; + else if ((modify->fmask[i] && strcmp(modify->fix[i]->style,"nve")==0) && before) flag = 1; + } + if (flag && comm->me == 0) + error->all(FLERR,"Fix langevin gjf should come before fix nve"); + } + if (oflag && !atom->sphere_flag) error->all(FLERR,"Fix langevin omega requires atom style sphere"); if (ascale && !atom->ellipsoid_flag) error->all(FLERR,"Fix langevin angmom requires atom style ellipsoid"); - if (gjfflag && zeroflag && tallyflag) - error->warning(FLERR, - "Fix langevin: gjf, zero, and tally were all set correct energy tallying is not guaranteed"); // check variable if (tstr) { @@ -281,17 +274,19 @@ void FixLangevin::init() error->one(FLERR,"Fix langevin angmom requires extended particles"); } + // set force prefactors + if (!atom->rmass) { for (int i = 1; i <= atom->ntypes; i++) { gfactor1[i] = -atom->mass[i] / t_period / force->ftm2v; - if (gjfflag) + if (!gjfflag) gfactor2[i] = sqrt(atom->mass[i]) * - sqrt(2.0*force->boltz/t_period/update->dt/force->mvv2e) / - force->ftm2v; + sqrt(24.0*force->boltz/t_period/update->dt/force->mvv2e) / + force->ftm2v; else gfactor2[i] = sqrt(atom->mass[i]) * - sqrt(24.0*force->boltz/t_period/update->dt/force->mvv2e) / - force->ftm2v; + sqrt(2.0*force->boltz/t_period/update->dt/force->mvv2e) / + force->ftm2v; gfactor1[i] *= 1.0/ratio[i]; gfactor2[i] *= 1.0/sqrt(ratio[i]); } @@ -303,17 +298,57 @@ void FixLangevin::init() if (strstr(update->integrate_style,"respa")) nlevels_respa = ((Respa *) update->integrate)->nlevels; - if (strstr(update->integrate_style,"respa")) - error->one(FLERR,"Fix langevin gjf not implemented with respa capabilities"); - - if (gjfflag) gjffac = 1.0/sqrt(1.0+update->dt/2.0/t_period); - + if (gjfflag) gjfa = (1.0-update->dt/2.0/t_period)/(1.0+update->dt/2.0/t_period); + if (gjfflag) gjfsib = sqrt(1.0+update->dt/2.0/t_period); } /* ---------------------------------------------------------------------- */ void FixLangevin::setup(int vflag) { + if (gjfflag){ + double dtfm; + double dt = update->dt; + double **v = atom->v; + double **f = atom->f; + int *mask = atom->mask; + int nlocal = atom->nlocal; + double *rmass = atom->rmass; + double *mass = atom->mass; + int *type = atom->type; + if (rmass) { + for (int i = 0; i < nlocal; i++) + if (mask[i] & groupbit) { + dtfm = 0.5 * dt / rmass[i]; + v[i][0] -= dtfm * f[i][0]; + v[i][1] -= dtfm * f[i][1]; + v[i][2] -= dtfm * f[i][2]; + if (tbiasflag) + temperature->remove_bias(i,v[i]); + v[i][0] /= gjfa*gjfsib*gjfsib; + v[i][1] /= gjfa*gjfsib*gjfsib; + v[i][2] /= gjfa*gjfsib*gjfsib; + if (tbiasflag) + temperature->restore_bias(i,v[i]); + } + + } else { + for (int i = 0; i < nlocal; i++) + if (mask[i] & groupbit) { + dtfm = 0.5 * dt / mass[type[i]]; + v[i][0] -= dtfm * f[i][0]; + v[i][1] -= dtfm * f[i][1]; + v[i][2] -= dtfm * f[i][2]; + if (tbiasflag) + temperature->remove_bias(i,v[i]); + v[i][0] /= gjfa*gjfsib*gjfsib; + v[i][1] /= gjfa*gjfsib*gjfsib; + v[i][2] /= gjfa*gjfsib*gjfsib; + if (tbiasflag) + temperature->restore_bias(i,v[i]); + } + } + } if (strstr(update->integrate_style,"verlet")) post_force(vflag); else { @@ -321,144 +356,67 @@ void FixLangevin::setup(int vflag) post_force_respa(vflag,nlevels_respa-1,0); ((Respa *) update->integrate)->copy_f_flevel(nlevels_respa-1); } - if (gjfflag) { - - // update v of atoms in group - double ** v = atom->v; + if (gjfflag){ + double dtfm; + double dt = update->dt; double **f = atom->f; + double **v = atom->v; + int *mask = atom->mask; int nlocal = atom->nlocal; - if (igroup == atom->firstgroup) nlocal = atom->nfirst; - double b[3] = {0.0,0.0,0.0}; - - for (int i = 0; i < nlocal; i++) { - f[i][0] = wildcard[i][0]; - f[i][1] = wildcard[i][1]; - f[i][2] = wildcard[i][2]; - b[0] = v[i][0]; - b[1] = v[i][1]; - b[2] = v[i][2]; - if (tbiasflag == BIAS) temperature->remove_bias(i,v[i]); - wildcard[i][0] = v[i][0]; - wildcard[i][1] = v[i][1]; - wildcard[i][2] = v[i][2]; - if (tbiasflag == BIAS) { - temperature->restore_bias(i,v[i]); - bias[i][0] = b[0] - wildcard[i][0]; - bias[i][1] = b[1] - wildcard[i][1]; - bias[i][2] = b[2] - wildcard[i][2]; - } + double *rmass = atom->rmass; + double *mass = atom->mass; + int *type = atom->type; + if (rmass) { + for (int i = 0; i < nlocal; i++) + if (mask[i] & groupbit) { + dtfm = 0.5 * dt / rmass[i]; + v[i][0] += dtfm * f[i][0]; + v[i][1] += dtfm * f[i][1]; + v[i][2] += dtfm * f[i][2]; + lv[i][0] = f[i][0]; + lv[i][1] = f[i][1]; + lv[i][2] = f[i][2]; + } +// + } else { + for (int i = 0; i < nlocal; i++) + if (mask[i] & groupbit) { + dtfm = 0.5 * dt / mass[type[i]]; + v[i][0] += dtfm * f[i][0]; + v[i][1] += dtfm * f[i][1]; + v[i][2] += dtfm * f[i][2]; + lv[i][0] = v[i][0]; + lv[i][1] = v[i][1]; + lv[i][2] = v[i][2]; + } } } } -/* ---------------------------------------------------------------------- - allow for both per-type and per-atom mass -------------------------------------------------------------------------- */ +/* ---------------------------------------------------------------------- */ -void FixLangevin::post_integrate() +void FixLangevin::initial_integrate_respa(int vflag, int ilevel, int /* iloop */){ + if (ilevel == respa_level-1) initial_integrate(vflag); +} + +/* ---------------------------------------------------------------------- */ + +void FixLangevin::initial_integrate(int /* vflag */) { - double dtfm; - double dt = update->dt; - double dtf = 0.5 * dt * force->ftm2v; - - // update v of atoms in group - - double **x = atom->x; double **v = atom->v; double **f = atom->f; - double *rmass = atom->rmass; - double *mass = atom->mass; - int *type = atom->type; int *mask = atom->mask; int nlocal = atom->nlocal; - if (igroup == atom->firstgroup) nlocal = atom->nfirst; - // zero option - double vsum[3],vsumall[3]; - bigint count; - - if (zeroflag) { - vsum[0] = vsum[1] = vsum[2] = 0.0; - count = group->count(igroup); - if (count == 0) - error->all(FLERR,"Cannot zero Langevin force of 0 atoms"); - } - - if (rmass) { - for (int i = 0; i < nlocal; i++) - if (mask[i] & groupbit) { - dtfm = dtf / rmass[i]; - x[i][0] -= dt * v[i][0]; - x[i][1] -= dt * v[i][1]; - x[i][2] -= dt * v[i][2]; - v[i][0] = gjffac * (wildcard[i][0] + dtfm * franprev[i][0] + dtfm * f[i][0]); - v[i][1] = gjffac * (wildcard[i][1] + dtfm * franprev[i][1] + dtfm * f[i][1]); - v[i][2] = gjffac * (wildcard[i][2] + dtfm * franprev[i][2] + dtfm * f[i][2]); - if (tbiasflag == BIAS) - for (int j = 0; j < 3; j++) { - if (wildcard[i][j] == 0) { - v[i][j] /= gjffac * gjffac; - } - } - x[i][0] += gjffac * dt * v[i][0]; - x[i][1] += gjffac * dt * v[i][1]; - x[i][2] += gjffac * dt * v[i][2]; - if (tbiasflag == BIAS) - for (int j = 0; j < 3; j++) { - if (wildcard[i][j] == 0) - v[i][j] *= gjffac; - v[i][j] += bias[i][j]; - x[i][j] += dt * bias[i][j]; - } - } - - } else { - for (int i = 0; i < nlocal; i++) - if (mask[i] & groupbit) { - dtfm = dtf / mass[type[i]]; - x[i][0] -= dt * v[i][0]; - x[i][1] -= dt * v[i][1]; - x[i][2] -= dt * v[i][2]; - v[i][0] = gjffac * (wildcard[i][0] + dtfm * franprev[i][0] + dtfm * f[i][0]); - v[i][1] = gjffac * (wildcard[i][1] + dtfm * franprev[i][1] + dtfm * f[i][1]); - v[i][2] = gjffac * (wildcard[i][2] + dtfm * franprev[i][2] + dtfm * f[i][2]); - if (tbiasflag == BIAS) - for (int j = 0; j < 3; j++) { - if (wildcard[i][j] == 0) { - v[i][j] /= gjffac*gjffac; - } - } - x[i][0] += gjffac * dt * v[i][0]; - x[i][1] += gjffac * dt * v[i][1]; - x[i][2] += gjffac * dt * v[i][2]; - if (tbiasflag == BIAS) - for (int j = 0; j < 3; j++) { - if (wildcard[i][j] == 0) - v[i][j] *= gjffac; - v[i][j] += bias[i][j]; - x[i][j] += dt * bias[i][j]; - } - if (zeroflag){ - vsum[0] += gjffac * dtfm * franprev[i][0]; - vsum[1] += gjffac * dtfm * franprev[i][1]; - vsum[2] += gjffac * dtfm * franprev[i][2]; - } - } - } - - if (zeroflag) { - MPI_Allreduce(vsum,vsumall,3,MPI_DOUBLE,MPI_SUM,world); - vsumall[0] /= count; - vsumall[1] /= count; - vsumall[2] /= count; - for (int i = 0; i < nlocal; i++) { - if (mask[i] & groupbit) { - v[i][0] -= vsumall[0]; - v[i][1] -= vsumall[1]; - v[i][2] -= vsumall[2]; - } + for (int i = 0; i < nlocal; i++) + if (mask[i] & groupbit){ + f[i][0] /= gjfa; + f[i][1] /= gjfa; + f[i][2] /= gjfa; + v[i][0] = lv[i][0]; + v[i][1] = lv[i][1]; + v[i][2] = lv[i][2]; } - } } /* ---------------------------------------------------------------------- */ @@ -479,124 +437,124 @@ void FixLangevin::post_force(int /*vflag*/) if (zeroflag) post_force_templated<1,1,1,1,1,1>(); else post_force_templated<1,1,1,1,1,0>(); else - if (zeroflag) post_force_templated<1,1,1,1,0,1>(); - else post_force_templated<1,1,1,1,0,0>(); + if (zeroflag) post_force_templated<1,1,1,1,0,1>(); + else post_force_templated<1,1,1,1,0,0>(); else - if (rmass) - if (zeroflag) post_force_templated<1,1,1,0,1,1>(); - else post_force_templated<1,1,1,0,1,0>(); - else - if (zeroflag) post_force_templated<1,1,1,0,0,1>(); - else post_force_templated<1,1,1,0,0,0>(); + if (rmass) + if (zeroflag) post_force_templated<1,1,1,0,1,1>(); + else post_force_templated<1,1,1,0,1,0>(); + else + if (zeroflag) post_force_templated<1,1,1,0,0,1>(); + else post_force_templated<1,1,1,0,0,0>(); else - if (tbiasflag == BIAS) - if (rmass) - if (zeroflag) post_force_templated<1,1,0,1,1,1>(); - else post_force_templated<1,1,0,1,1,0>(); - else - if (zeroflag) post_force_templated<1,1,0,1,0,1>(); - else post_force_templated<1,1,0,1,0,0>(); + if (tbiasflag == BIAS) + if (rmass) + if (zeroflag) post_force_templated<1,1,0,1,1,1>(); + else post_force_templated<1,1,0,1,1,0>(); else - if (rmass) - if (zeroflag) post_force_templated<1,1,0,0,1,1>(); - else post_force_templated<1,1,0,0,1,0>(); - else - if (zeroflag) post_force_templated<1,1,0,0,0,1>(); - else post_force_templated<1,1,0,0,0,0>(); + if (zeroflag) post_force_templated<1,1,0,1,0,1>(); + else post_force_templated<1,1,0,1,0,0>(); + else + if (rmass) + if (zeroflag) post_force_templated<1,1,0,0,1,1>(); + else post_force_templated<1,1,0,0,1,0>(); + else + if (zeroflag) post_force_templated<1,1,0,0,0,1>(); + else post_force_templated<1,1,0,0,0,0>(); else - if (tallyflag) - if (tbiasflag == BIAS) - if (rmass) - if (zeroflag) post_force_templated<1,0,1,1,1,1>(); - else post_force_templated<1,0,1,1,1,0>(); - else - if (zeroflag) post_force_templated<1,0,1,1,0,1>(); - else post_force_templated<1,0,1,1,0,0>(); + if (tallyflag) + if (tbiasflag == BIAS) + if (rmass) + if (zeroflag) post_force_templated<1,0,1,1,1,1>(); + else post_force_templated<1,0,1,1,1,0>(); else - if (rmass) - if (zeroflag) post_force_templated<1,0,1,0,1,1>(); - else post_force_templated<1,0,1,0,1,0>(); - else - if (zeroflag) post_force_templated<1,0,1,0,0,1>(); - else post_force_templated<1,0,1,0,0,0>(); + if (zeroflag) post_force_templated<1,0,1,1,0,1>(); + else post_force_templated<1,0,1,1,0,0>(); else - if (tbiasflag == BIAS) - if (rmass) - if (zeroflag) post_force_templated<1,0,0,1,1,1>(); - else post_force_templated<1,0,0,1,1,0>(); - else - if (zeroflag) post_force_templated<1,0,0,1,0,1>(); - else post_force_templated<1,0,0,1,0,0>(); - else - if (rmass) - if (zeroflag) post_force_templated<1,0,0,0,1,1>(); - else post_force_templated<1,0,0,0,1,0>(); - else - if (zeroflag) post_force_templated<1,0,0,0,0,1>(); - else post_force_templated<1,0,0,0,0,0>(); + if (rmass) + if (zeroflag) post_force_templated<1,0,1,0,1,1>(); + else post_force_templated<1,0,1,0,1,0>(); + else + if (zeroflag) post_force_templated<1,0,1,0,0,1>(); + else post_force_templated<1,0,1,0,0,0>(); + else + if (tbiasflag == BIAS) + if (rmass) + if (zeroflag) post_force_templated<1,0,0,1,1,1>(); + else post_force_templated<1,0,0,1,1,0>(); + else + if (zeroflag) post_force_templated<1,0,0,1,0,1>(); + else post_force_templated<1,0,0,1,0,0>(); + else + if (rmass) + if (zeroflag) post_force_templated<1,0,0,0,1,1>(); + else post_force_templated<1,0,0,0,1,0>(); + else + if (zeroflag) post_force_templated<1,0,0,0,0,1>(); + else post_force_templated<1,0,0,0,0,0>(); else - if (gjfflag) - if (tallyflag) - if (tbiasflag == BIAS) - if (rmass) - if (zeroflag) post_force_templated<0,1,1,1,1,1>(); - else post_force_templated<0,1,1,1,1,0>(); - else - if (zeroflag) post_force_templated<0,1,1,1,0,1>(); - else post_force_templated<0,1,1,1,0,0>(); + if (gjfflag) + if (tallyflag) + if (tbiasflag == BIAS) + if (rmass) + if (zeroflag) post_force_templated<0,1,1,1,1,1>(); + else post_force_templated<0,1,1,1,1,0>(); else - if (rmass) - if (zeroflag) post_force_templated<0,1,1,0,1,1>(); - else post_force_templated<0,1,1,0,1,0>(); - else - if (zeroflag) post_force_templated<0,1,1,0,0,1>(); - else post_force_templated<0,1,1,0,0,0>(); + if (zeroflag) post_force_templated<0,1,1,1,0,1>(); + else post_force_templated<0,1,1,1,0,0>(); else - if (tbiasflag == BIAS) - if (rmass) - if (zeroflag) post_force_templated<0,1,0,1,1,1>(); - else post_force_templated<0,1,0,1,1,0>(); - else - if (zeroflag) post_force_templated<0,1,0,1,0,1>(); - else post_force_templated<0,1,0,1,0,0>(); - else - if (rmass) - if (zeroflag) post_force_templated<0,1,0,0,1,1>(); - else post_force_templated<0,1,0,0,1,0>(); - else - if (zeroflag) post_force_templated<0,1,0,0,0,1>(); - else post_force_templated<0,1,0,0,0,0>(); + if (rmass) + if (zeroflag) post_force_templated<0,1,1,0,1,1>(); + else post_force_templated<0,1,1,0,1,0>(); + else + if (zeroflag) post_force_templated<0,1,1,0,0,1>(); + else post_force_templated<0,1,1,0,0,0>(); else - if (tallyflag) - if (tbiasflag == BIAS) - if (rmass) - if (zeroflag) post_force_templated<0,0,1,1,1,1>(); - else post_force_templated<0,0,1,1,1,0>(); - else - if (zeroflag) post_force_templated<0,0,1,1,0,1>(); - else post_force_templated<0,0,1,1,0,0>(); - else - if (rmass) - if (zeroflag) post_force_templated<0,0,1,0,1,1>(); - else post_force_templated<0,0,1,0,1,0>(); - else - if (zeroflag) post_force_templated<0,0,1,0,0,1>(); - else post_force_templated<0,0,1,0,0,0>(); + if (tbiasflag == BIAS) + if (rmass) + if (zeroflag) post_force_templated<0,1,0,1,1,1>(); + else post_force_templated<0,1,0,1,1,0>(); else - if (tbiasflag == BIAS) - if (rmass) - if (zeroflag) post_force_templated<0,0,0,1,1,1>(); - else post_force_templated<0,0,0,1,1,0>(); - else - if (zeroflag) post_force_templated<0,0,0,1,0,1>(); - else post_force_templated<0,0,0,1,0,0>(); - else - if (rmass) - if (zeroflag) post_force_templated<0,0,0,0,1,1>(); - else post_force_templated<0,0,0,0,1,0>(); - else - if (zeroflag) post_force_templated<0,0,0,0,0,1>(); - else post_force_templated<0,0,0,0,0,0>(); + if (zeroflag) post_force_templated<0,1,0,1,0,1>(); + else post_force_templated<0,1,0,1,0,0>(); + else + if (rmass) + if (zeroflag) post_force_templated<0,1,0,0,1,1>(); + else post_force_templated<0,1,0,0,1,0>(); + else + if (zeroflag) post_force_templated<0,1,0,0,0,1>(); + else post_force_templated<0,1,0,0,0,0>(); + else + if (tallyflag) + if (tbiasflag == BIAS) + if (rmass) + if (zeroflag) post_force_templated<0,0,1,1,1,1>(); + else post_force_templated<0,0,1,1,1,0>(); + else + if (zeroflag) post_force_templated<0,0,1,1,0,1>(); + else post_force_templated<0,0,1,1,0,0>(); + else + if (rmass) + if (zeroflag) post_force_templated<0,0,1,0,1,1>(); + else post_force_templated<0,0,1,0,1,0>(); + else + if (zeroflag) post_force_templated<0,0,1,0,0,1>(); + else post_force_templated<0,0,1,0,0,0>(); + else + if (tbiasflag == BIAS) + if (rmass) + if (zeroflag) post_force_templated<0,0,0,1,1,1>(); + else post_force_templated<0,0,0,1,1,0>(); + else + if (zeroflag) post_force_templated<0,0,0,1,0,1>(); + else post_force_templated<0,0,0,1,0,0>(); + else + if (rmass) + if (zeroflag) post_force_templated<0,0,0,0,1,1>(); + else post_force_templated<0,0,0,0,1,0>(); + else + if (zeroflag) post_force_templated<0,0,0,0,0,1>(); + else post_force_templated<0,0,0,0,0,0>(); } /* ---------------------------------------------------------------------- */ @@ -611,7 +569,7 @@ void FixLangevin::post_force_respa(int vflag, int ilevel, int /*iloop*/) ------------------------------------------------------------------------- */ template < int Tp_TSTYLEATOM, int Tp_GJF, int Tp_TALLY, - int Tp_BIAS, int Tp_RMASS, int Tp_ZERO > + int Tp_BIAS, int Tp_RMASS, int Tp_ZERO > void FixLangevin::post_force_templated() { double gamma1,gamma2; @@ -644,8 +602,9 @@ void FixLangevin::post_force_templated() // sum random force over all atoms in group // subtract sum/count from each atom in group - double fdrag[3],fran[3],fsum[3],fsumall[3], rantemp[3]; + double fdrag[3],fran[3],fsum[3],fsumall[3]; bigint count; + double fswap; double boltz = force->boltz; double dt = update->dt; @@ -672,33 +631,33 @@ void FixLangevin::post_force_templated() flangevin_allocated = 1; } - if (Tp_BIAS && !gjfflag) temperature->compute_scalar(); - else if (Tp_BIAS && update->ntimestep == update->beginstep && gjfflag) temperature->compute_scalar(); + if (Tp_BIAS) temperature->compute_scalar(); for (int i = 0; i < nlocal; i++) { if (mask[i] & groupbit) { if (Tp_TSTYLEATOM) tsqrt = sqrt(tforce[i]); if (Tp_RMASS) { gamma1 = -rmass[i] / t_period / ftm2v; - if (Tp_GJF) - gamma2 = sqrt(rmass[i]) * sqrt(2.0 * boltz / t_period / dt / mvv2e) / ftm2v; + if (!Tp_GJF) + gamma2 = sqrt(rmass[i]) * sqrt(24.0*boltz/t_period/dt/mvv2e) / ftm2v; else - gamma2 = sqrt(rmass[i]) * sqrt(24.0 * boltz / t_period / dt / mvv2e) / ftm2v; - gamma1 *= 1.0 / ratio[type[i]]; - gamma2 *= 1.0 / sqrt(ratio[type[i]]) * tsqrt; + gamma2 = sqrt(rmass[i]) * sqrt(2.0*boltz/t_period/dt/mvv2e) / ftm2v; + gamma1 *= 1.0/ratio[type[i]]; + gamma2 *= 1.0/sqrt(ratio[type[i]]) * tsqrt; } else { gamma1 = gfactor1[type[i]]; gamma2 = gfactor2[type[i]] * tsqrt; } - if (Tp_GJF) { - fran[0] = gamma2 * random->gaussian(); - fran[1] = gamma2 * random->gaussian(); - fran[2] = gamma2 * random->gaussian(); - } else { - fran[0] = gamma2 * (random->uniform()-0.5); - fran[1] = gamma2 * (random->uniform()-0.5); - fran[2] = gamma2 * (random->uniform()-0.5); + if (!Tp_GJF){ + fran[0] = gamma2*(random->uniform()-0.5); + fran[1] = gamma2*(random->uniform()-0.5); + fran[2] = gamma2*(random->uniform()-0.5); + } + else{ + fran[0] = gamma2*random->gaussian(); + fran[1] = gamma2*random->gaussian(); + fran[2] = gamma2*random->gaussian(); } if (Tp_BIAS) { @@ -717,21 +676,35 @@ void FixLangevin::post_force_templated() } if (Tp_GJF) { - wildcard[i][0] = f[i][0]; - wildcard[i][1] = f[i][1]; - wildcard[i][2] = f[i][2]; + if (Tp_BIAS) + temperature->remove_bias(i,v[i]); + lv[i][0] = gjfsib*v[i][0]; + lv[i][1] = gjfsib*v[i][1]; + lv[i][2] = gjfsib*v[i][2]; + if (Tp_BIAS) + temperature->restore_bias(i,v[i]); + if (Tp_BIAS) + temperature->restore_bias(i,lv[i]); - rantemp[0] = fran[0]; - rantemp[1] = fran[1]; - rantemp[2] = fran[2]; + fswap = 0.5*(fran[0]+franprev[i][0]); + franprev[i][0] = fran[0]; + fran[0] = fswap; + fswap = 0.5*(fran[1]+franprev[i][1]); + franprev[i][1] = fran[1]; + fran[1] = fswap; + fswap = 0.5*(fran[2]+franprev[i][2]); + franprev[i][2] = fran[2]; + fran[2] = fswap; - fran[0] = franprev[i][0]; - fran[1] = franprev[i][1]; - fran[2] = franprev[i][2]; - - fdrag[0] *= -2*t_period*((2*gjffac)-(1.0/gjffac)-1.0)/dt; - fdrag[1] *= -2*t_period*((2*gjffac)-(1.0/gjffac)-1.0)/dt; - fdrag[2] *= -2*t_period*((2*gjffac)-(1.0/gjffac)-1.0)/dt; + fdrag[0] *= gjfa; + fdrag[1] *= gjfa; + fdrag[2] *= gjfa; + fran[0] *= gjfa; + fran[1] *= gjfa; + fran[2] *= gjfa; + f[i][0] *= gjfa; + f[i][1] *= gjfa; + f[i][2] *= gjfa; } f[i][0] += fdrag[0] + fran[0]; @@ -739,61 +712,15 @@ void FixLangevin::post_force_templated() f[i][2] += fdrag[2] + fran[2]; if (Tp_TALLY) { - if (Tp_GJF && update->ntimestep != update->beginstep){ - if (Tp_BIAS) { - temperature->remove_bias(i,v[i]); - fdrag[0] = gamma1*gjffac*gjffac*v[i][0]; - fdrag[1] = gamma1*gjffac*gjffac*v[i][1]; - fdrag[2] = gamma1*gjffac*gjffac*v[i][2]; - temperature->restore_bias(i,v[i]); - } else { - fdrag[0] = gamma1*gjffac*gjffac*v[i][0]; - fdrag[1] = gamma1*gjffac*gjffac*v[i][1]; - fdrag[2] = gamma1*gjffac*gjffac*v[i][2]; - } - fran[0] *= gjffac; - fran[1] *= gjffac; - fran[2] *= gjffac; - } - else if (Tp_GJF && update->ntimestep == update->beginstep){ - fdrag[0] = 0.0; - fdrag[1] = 0.0; - fdrag[2] = 0.0; - } flangevin[i][0] = fdrag[0] + fran[0]; flangevin[i][1] = fdrag[1] + fran[1]; flangevin[i][2] = fdrag[2] + fran[2]; } if (Tp_ZERO) { - if (!Tp_GJF){ - fsum[0] += fran[0]; - fsum[1] += fran[1]; - fsum[2] += fran[2]; - } - else { - fsum[0] += franprev[i][0]; - fsum[1] += franprev[i][1]; - fsum[2] += franprev[i][2]; - } - } - - if (Tp_GJF) - { - franprev[i][0] = rantemp[0]; - franprev[i][1] = rantemp[1]; - franprev[i][2] = rantemp[2]; - - if (hsflag){ - lv[i][0] = v[i][0]; - lv[i][1] = v[i][1]; - lv[i][2] = v[i][2]; - if (tbiasflag == BIAS) { - lv[i][0] += bias[i][0]; - lv[i][1] += bias[i][1]; - lv[i][2] += bias[i][2]; - } - } + fsum[0] += fran[0]; + fsum[1] += fran[1]; + fsum[2] += fran[2]; } } } @@ -977,46 +904,34 @@ void FixLangevin::end_of_step() if (!tallyflag && !gjfflag) return; double **v = atom->v; - double **f = atom->f; int *mask = atom->mask; int nlocal = atom->nlocal; - double b[3] = {0.0,0.0,0.0}; - - if (gjfflag && tbiasflag == BIAS) temperature->compute_scalar(); energy_onestep = 0.0; - for (int i = 0; i < nlocal; i++) - if (mask[i] & groupbit) { - if (gjfflag){ - b[0] = v[i][0]; - b[1] = v[i][1]; - b[2] = v[i][2]; - f[i][0] = wildcard[i][0]; - f[i][1] = wildcard[i][1]; - f[i][2] = wildcard[i][2]; - if (tbiasflag == BIAS) temperature->remove_bias(i,v[i]); - wildcard[i][0] = v[i][0]; - wildcard[i][1] = v[i][1]; - wildcard[i][2] = v[i][2]; - if (tbiasflag == BIAS) { - bias[i][0] = b[0] - v[i][0]; - bias[i][1] = b[1] - v[i][1]; - bias[i][2] = b[2] - v[i][2]; - temperature->restore_bias(i, v[i]); - } - if (hsflag){ - v[i][0] = lv[i][0]; - v[i][1] = lv[i][1]; - v[i][2] = lv[i][2]; - } + + if (gjfflag){ + double tmp[3]; + for (int i = 0; i < nlocal; i++) + if (mask[i] & groupbit){ + tmp[0] = v[i][0]; + tmp[1] = v[i][1]; + tmp[2] = v[i][2]; + v[i][0] = lv[i][0]; + v[i][1] = lv[i][1]; + v[i][2] = lv[i][2]; + lv[i][0] = tmp[0]; + lv[i][1] = tmp[1]; + lv[i][2] = tmp[2]; } - if (tallyflag) - energy_onestep += flangevin[i][0] * v[i][0] + flangevin[i][1] * v[i][1] + - flangevin[i][2] * v[i][2]; - } - if (tallyflag) { - energy += energy_onestep * update->dt; } + + if (tallyflag) + for (int i = 0; i < nlocal; i++) + if (mask[i] & groupbit) + energy_onestep += flangevin[i][0]*v[i][0] + flangevin[i][1]*v[i][1] + + flangevin[i][2]*v[i][2]; + + energy += energy_onestep*update->dt; } /* ---------------------------------------------------------------------- */ @@ -1033,8 +948,8 @@ void FixLangevin::reset_dt() if (atom->mass) { for (int i = 1; i <= atom->ntypes; i++) { gfactor2[i] = sqrt(atom->mass[i]) * - sqrt(24.0*force->boltz/t_period/update->dt/force->mvv2e) / - force->ftm2v; + sqrt(24.0*force->boltz/t_period/update->dt/force->mvv2e) / + force->ftm2v; gfactor2[i] *= 1.0/sqrt(ratio[i]); } } @@ -1070,7 +985,7 @@ int FixLangevin::modify_param(int narg, char **arg) double FixLangevin::compute_scalar() { - if (!tallyflag && !flangevin_allocated) return 0.0; + if (!tallyflag || !flangevin_allocated) return 0.0; // capture the very first energy transfer to thermal reservoir @@ -1083,16 +998,13 @@ double FixLangevin::compute_scalar() for (int i = 0; i < nlocal; i++) if (mask[i] & groupbit) energy_onestep += flangevin[i][0]*v[i][0] + flangevin[i][1]*v[i][1] + - flangevin[i][2]*v[i][2]; + flangevin[i][2]*v[i][2]; energy = 0.5*energy_onestep*update->dt; } // convert midstep energy back to previous fullstep energy - double energy_me; - if (gjfflag) - energy_me = energy - energy_onestep*update->dt; - else - energy_me = energy - 0.5*energy_onestep*update->dt; + + double energy_me = energy - 0.5*energy_onestep*update->dt; double energy_all; MPI_Allreduce(&energy_me,&energy_all,1,MPI_DOUBLE,MPI_SUM,world); @@ -1119,9 +1031,7 @@ void *FixLangevin::extract(const char *str, int &dim) double FixLangevin::memory_usage() { double bytes = 0.0; - if (gjfflag) bytes += atom->nmax*3*2 * sizeof(double); - if (gjfflag) if (hsflag) bytes += atom->nmax*3 * sizeof(double); - if (gjfflag && tbiasflag == BIAS) bytes += atom->nmax*3 * sizeof(double); + if (gjfflag) bytes += atom->nmax*6 * sizeof(double); if (tallyflag) bytes += atom->nmax*3 * sizeof(double); if (tforce) bytes += atom->nmax * sizeof(double); return bytes; @@ -1134,9 +1044,7 @@ double FixLangevin::memory_usage() void FixLangevin::grow_arrays(int nmax) { memory->grow(franprev,nmax,3,"fix_langevin:franprev"); - memory->grow(wildcard,nmax,3,"fix_langevin:wildcard"); - if (hsflag) memory->grow(lv,nmax,3,"fix_langevin:lv"); - if (tbiasflag == BIAS) memory->grow(bias,nmax,3,"fix_langevin:bias"); + memory->grow(lv,nmax,3,"fix_langevin:lv"); } /* ---------------------------------------------------------------------- @@ -1148,19 +1056,9 @@ void FixLangevin::copy_arrays(int i, int j, int /*delflag*/) franprev[j][0] = franprev[i][0]; franprev[j][1] = franprev[i][1]; franprev[j][2] = franprev[i][2]; - wildcard[j][0] = wildcard[i][0]; - wildcard[j][1] = wildcard[i][1]; - wildcard[j][2] = wildcard[i][2]; - if (hsflag) { - lv[j][0] = lv[i][0]; - lv[j][1] = lv[i][1]; - lv[j][2] = lv[i][2]; - } - if (tbiasflag == BIAS){ - bias[j][0] = bias[i][0]; - bias[j][1] = bias[i][1]; - bias[j][2] = bias[i][2]; - } + lv[j][0] = lv[i][0]; + lv[j][1] = lv[i][1]; + lv[j][2] = lv[i][2]; } /* ---------------------------------------------------------------------- @@ -1173,19 +1071,9 @@ int FixLangevin::pack_exchange(int i, double *buf) buf[n++] = franprev[i][0]; buf[n++] = franprev[i][1]; buf[n++] = franprev[i][2]; - buf[n++] = wildcard[i][0]; - buf[n++] = wildcard[i][1]; - buf[n++] = wildcard[i][2]; - if (hsflag){ - buf[n++] = lv[i][0]; - buf[n++] = lv[i][1]; - buf[n++] = lv[i][2]; - } - if (tbiasflag == BIAS){ - buf[n++] = bias[i][0]; - buf[n++] = bias[i][1]; - buf[n++] = bias[i][2]; - } + buf[n++] = lv[i][0]; + buf[n++] = lv[i][1]; + buf[n++] = lv[i][2]; return n; } @@ -1199,18 +1087,8 @@ int FixLangevin::unpack_exchange(int nlocal, double *buf) franprev[nlocal][0] = buf[n++]; franprev[nlocal][1] = buf[n++]; franprev[nlocal][2] = buf[n++]; - wildcard[nlocal][0] = buf[n++]; - wildcard[nlocal][1] = buf[n++]; - wildcard[nlocal][2] = buf[n++]; - if (hsflag){ - lv[nlocal][0] = buf[n++]; - lv[nlocal][1] = buf[n++]; - lv[nlocal][2] = buf[n++]; - } - if (tbiasflag == BIAS){ - bias[nlocal][0] = buf[n++]; - bias[nlocal][1] = buf[n++]; - bias[nlocal][2] = buf[n++]; - } + lv[nlocal][0] = buf[n++]; + lv[nlocal][1] = buf[n++]; + lv[nlocal][2] = buf[n++]; return n; -} +} \ No newline at end of file diff --git a/src/fix_langevin.h b/src/fix_langevin.h index 939b161c35..8b8c1cd6c8 100644 --- a/src/fix_langevin.h +++ b/src/fix_langevin.h @@ -2,12 +2,10 @@ LAMMPS - Large-scale Atomic/Molecular Massively Parallel Simulator http://lammps.sandia.gov, Sandia National Laboratories Steve Plimpton, sjplimp@sandia.gov - Copyright (2003) Sandia Corporation. Under the terms of Contract DE-AC04-94AL85000 with Sandia Corporation, the U.S. Government retains certain rights in this software. This software is distributed under the GNU General Public License. - See the README file in the top-level LAMMPS directory. ------------------------------------------------------------------------- */ @@ -24,68 +22,64 @@ FixStyle(langevin,FixLangevin) namespace LAMMPS_NS { -class FixLangevin : public Fix { - public: - FixLangevin(class LAMMPS *, int, char **); - virtual ~FixLangevin(); - int setmask(); - void init(); - void setup(int); - //virtual void initial_integrate(int); - virtual void post_integrate(); - virtual void post_force(int); - void post_force_respa(int, int, int); - virtual void end_of_step(); - void reset_target(double); - void reset_dt(); - int modify_param(int, char **); - virtual double compute_scalar(); - double memory_usage(); - virtual void *extract(const char *, int &); - void grow_arrays(int); - void copy_arrays(int, int, int); - int pack_exchange(int, double *); - int unpack_exchange(int, double *); + class FixLangevin : public Fix { + public: + FixLangevin(class LAMMPS *, int, char **); + virtual ~FixLangevin(); + int setmask(); + void init(); + void setup(int); + void initial_integrate_respa(int, int, int); + virtual void initial_integrate(int); + virtual void post_force(int); + void post_force_respa(int, int, int); + virtual void end_of_step(); + void reset_target(double); + void reset_dt(); + int modify_param(int, char **); + virtual double compute_scalar(); + double memory_usage(); + virtual void *extract(const char *, int &); + void grow_arrays(int); + void copy_arrays(int, int, int); + int pack_exchange(int, double *); + int unpack_exchange(int, double *); - protected: - int gjfflag,oflag,tallyflag,zeroflag,tbiasflag,hsflag; - int flangevin_allocated; - double ascale; - double t_start,t_stop,t_period,t_target; - double *gfactor1,*gfactor2,*ratio; - double energy,energy_onestep; - double tsqrt; - int tstyle,tvar; - double gjffac; - char *tstr; + protected: + int gjfflag,oflag,tallyflag,zeroflag,tbiasflag; + int flangevin_allocated; + double ascale; + double t_start,t_stop,t_period,t_target; + double *gfactor1,*gfactor2,*ratio; + double energy,energy_onestep; + double tsqrt; + int tstyle,tvar; + double gjfa, gjfsib; //gjf a and gjf sqrt inverse b + char *tstr; - class AtomVecEllipsoid *avec; + class AtomVecEllipsoid *avec; - int maxatom1,maxatom2; - double **flangevin; - double *tforce; - double **franprev; - double **lv; //2GJ velocity or half-step velocity - double **wildcard; - double **bias; //Bias velocity + int maxatom1,maxatom2; + double **flangevin; + double *tforce; + double **franprev; + double **lv; //half step velocity - int nvalues; + char *id_temp; + class Compute *temperature; - char *id_temp; - class Compute *temperature; + int nlevels_respa; + class RanMars *random; + int seed; - int nlevels_respa; - class RanMars *random; - int seed; + template < int Tp_TSTYLEATOM, int Tp_GJF, int Tp_TALLY, + int Tp_BIAS, int Tp_RMASS, int Tp_ZERO > + void post_force_templated(); - template < int Tp_TSTYLEATOM, int Tp_GJF, int Tp_TALLY, - int Tp_BIAS, int Tp_RMASS, int Tp_ZERO > - void post_force_templated(); - - void omega_thermostat(); - void angmom_thermostat(); - void compute_target(); -}; + void omega_thermostat(); + void angmom_thermostat(); + void compute_target(); + }; } @@ -93,62 +87,35 @@ class FixLangevin : public Fix { #endif /* ERROR/WARNING messages: - E: Illegal ... command - Self-explanatory. Check the input script syntax and compare to the documentation for the command. You can use -echo screen as a command-line option when running LAMMPS to see the offending line. - E: Fix langevin period must be > 0.0 - The time window for temperature relaxation must be > 0 - E: Fix langevin omega requires atom style sphere - Self-explanatory. - E: Fix langevin angmom requires atom style ellipsoid - Self-explanatory. - E: Variable name for fix langevin does not exist - Self-explanatory. - E: Variable for fix langevin is invalid style - It must be an equal-style variable. - E: Fix langevin omega requires extended particles - One of the particles has radius 0.0. - E: Fix langevin angmom requires extended particles - This fix option cannot be used with point particles. - E: Cannot zero Langevin force of 0 atoms - The group has zero atoms, so you cannot request its force be zeroed. - E: Fix langevin variable returned negative temperature - Self-explanatory. - E: Could not find fix_modify temperature ID - The compute ID for computing temperature does not exist. - E: Fix_modify temperature ID does not compute temperature - The compute ID assigned to the fix must compute temperature. - W: Group for fix_modify temp != fix group - The fix_modify command is specifying a temperature computation that computes a temperature on a different group of atoms than the fix itself operates on. This is probably not what you want to do. - */ From 801c1656533e65234d97ef2d996c57afce76a80e Mon Sep 17 00:00:00 2001 From: charlie sievers Date: Wed, 21 Aug 2019 20:11:43 -0700 Subject: [PATCH 080/192] Added onsite GJF formalism --- src/fix_langevin.cpp | 49 +++++++++++++++++++++++++++++++++++--------- 1 file changed, 39 insertions(+), 10 deletions(-) diff --git a/src/fix_langevin.cpp b/src/fix_langevin.cpp index b8144fc5f3..6971b145ec 100644 --- a/src/fix_langevin.cpp +++ b/src/fix_langevin.cpp @@ -90,6 +90,7 @@ FixLangevin::FixLangevin(LAMMPS *lmp, int narg, char **arg) : for (int i = 1; i <= atom->ntypes; i++) ratio[i] = 1.0; ascale = 0.0; gjfflag = 0; + fsflag = 0; oflag = 0; tallyflag = 0; zeroflag = 0; @@ -103,8 +104,11 @@ FixLangevin::FixLangevin(LAMMPS *lmp, int narg, char **arg) : iarg += 2; } else if (strcmp(arg[iarg],"gjf") == 0) { if (iarg+2 > narg) error->all(FLERR,"Illegal fix langevin command"); - if (strcmp(arg[iarg+1],"no") == 0) gjfflag = 0; - else if (strcmp(arg[iarg+1],"yes") == 0) gjfflag = 1; + if (strcmp(arg[iarg+1],"no") == 0) {gjfflag = 0; fsflag = 0;} + else if (strcmp(arg[iarg+1],"yes") == 0) + error->all(FLERR,"Fix langevin gjf yes is outdated, please use vhalf or vfull"); + else if (strcmp(arg[iarg+1],"vhalf") == 0) {gjfflag = 1; fsflag = 0;} + else if (strcmp(arg[iarg+1],"vfull") == 0) {gjfflag = 1; fsflag = 1;} else error->all(FLERR,"Illegal fix langevin command"); iarg += 2; } else if (strcmp(arg[iarg],"omega") == 0) { @@ -431,7 +435,7 @@ void FixLangevin::post_force(int /*vflag*/) if (tstyle == ATOM) if (gjfflag) - if (tallyflag) + if (tallyflag || fsflag) if (tbiasflag == BIAS) if (rmass) if (zeroflag) post_force_templated<1,1,1,1,1,1>(); @@ -462,7 +466,7 @@ void FixLangevin::post_force(int /*vflag*/) if (zeroflag) post_force_templated<1,1,0,0,0,1>(); else post_force_templated<1,1,0,0,0,0>(); else - if (tallyflag) + if (tallyflag || fsflag) if (tbiasflag == BIAS) if (rmass) if (zeroflag) post_force_templated<1,0,1,1,1,1>(); @@ -494,7 +498,7 @@ void FixLangevin::post_force(int /*vflag*/) else post_force_templated<1,0,0,0,0,0>(); else if (gjfflag) - if (tallyflag) + if (tallyflag || fsflag) if (tbiasflag == BIAS) if (rmass) if (zeroflag) post_force_templated<0,1,1,1,1,1>(); @@ -525,7 +529,7 @@ void FixLangevin::post_force(int /*vflag*/) if (zeroflag) post_force_templated<0,1,0,0,0,1>(); else post_force_templated<0,1,0,0,0,0>(); else - if (tallyflag) + if (tallyflag || fsflag) if (tbiasflag == BIAS) if (rmass) if (zeroflag) post_force_templated<0,0,1,1,1,1>(); @@ -906,6 +910,13 @@ void FixLangevin::end_of_step() double **v = atom->v; int *mask = atom->mask; int nlocal = atom->nlocal; + double ftm2v = force->ftm2v; + double gamma1; double dtfm; + double dt = update->dt; + double *mass = atom->mass; + double *rmass = atom->rmass; + double **f = atom->f; + int *type = atom->type; energy_onestep = 0.0; @@ -916,9 +927,27 @@ void FixLangevin::end_of_step() tmp[0] = v[i][0]; tmp[1] = v[i][1]; tmp[2] = v[i][2]; - v[i][0] = lv[i][0]; - v[i][1] = lv[i][1]; - v[i][2] = lv[i][2]; + if (!fsflag){ + v[i][0] = lv[i][0]; + v[i][1] = lv[i][1]; + v[i][2] = lv[i][2]; + } + else{ + if (atom->rmass) { + dtfm = 0.5 * dt / rmass[i]; + gamma1 = -rmass[i] / t_period / ftm2v; + gamma1 *= 1.0/ratio[type[i]]; + } else { + dtfm = 0.5 * dt / mass[type[i]]; + gamma1 = gfactor1[type[i]]; + } + v[i][0] = flangevin[i][0] - franprev[i][0] + gjfa * (gjfsib/2 + gamma1/gjfsib) * lv[i][0] + + gjfsib*gjfsib*(dtfm * f[i][0] + v[i][0])/2; + v[i][1] = flangevin[i][1] - franprev[i][1] + gjfa * (gjfsib/2 + gamma1/gjfsib) * lv[i][1] + + gjfsib*gjfsib*(dtfm * f[i][1] + v[i][1])/2; + v[i][2] = flangevin[i][2] - franprev[i][2] + gjfa * (gjfsib/2 + gamma1/gjfsib) * lv[i][2] + + gjfsib*gjfsib*(dtfm * f[i][2] + v[i][2])/2; + } lv[i][0] = tmp[0]; lv[i][1] = tmp[1]; lv[i][2] = tmp[2]; @@ -1032,7 +1061,7 @@ double FixLangevin::memory_usage() { double bytes = 0.0; if (gjfflag) bytes += atom->nmax*6 * sizeof(double); - if (tallyflag) bytes += atom->nmax*3 * sizeof(double); + if (tallyflag || fsflag) bytes += atom->nmax*3 * sizeof(double); if (tforce) bytes += atom->nmax * sizeof(double); return bytes; } From ceeb7da5911c47c7b7eda617a172954bc04a1134 Mon Sep 17 00:00:00 2001 From: charlie sievers Date: Wed, 21 Aug 2019 20:47:17 -0700 Subject: [PATCH 081/192] Added onsite GJF formalism --- src/fix_langevin.h | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/fix_langevin.h b/src/fix_langevin.h index 8b8c1cd6c8..5abfa53288 100644 --- a/src/fix_langevin.h +++ b/src/fix_langevin.h @@ -46,7 +46,7 @@ namespace LAMMPS_NS { int unpack_exchange(int, double *); protected: - int gjfflag,oflag,tallyflag,zeroflag,tbiasflag; + int gjfflag,fsflag,oflag,tallyflag,zeroflag,tbiasflag; int flangevin_allocated; double ascale; double t_start,t_stop,t_period,t_target; From 8ec4e3fc9164fb21a2ceadf5211b3abe7987690f Mon Sep 17 00:00:00 2001 From: julient31 Date: Thu, 22 Aug 2019 10:48:58 -0600 Subject: [PATCH 082/192] Commit JT 082219 - modified min spin names (removed oso from spin/cg and spin/lbfgs) - modified associated option name (from spin_oso_cg to spin/cg, same for lbfgs) - modified .gitignore, doc pages, and examples accordingly --- doc/src/min_modify.txt | 14 ++-- doc/src/min_spin.txt | 26 +++---- doc/src/min_style.txt | 10 +-- doc/src/minimize.txt | 2 +- doc/src/neb_spin.txt | 4 +- examples/SPIN/spinmin/in.spinmin_cg.bfo | 2 +- examples/SPIN/spinmin/in.spinmin_lbfgs.bfo | 2 +- src/.gitignore | 8 +-- .../{min_spin_oso_cg.cpp => min_spin_cg.cpp} | 58 +++++++-------- src/SPIN/{min_spin_oso_cg.h => min_spin_cg.h} | 12 ++-- ..._spin_oso_lbfgs.cpp => min_spin_lbfgs.cpp} | 70 +++++++++---------- ...{min_spin_oso_lbfgs.h => min_spin_lbfgs.h} | 12 ++-- 12 files changed, 110 insertions(+), 110 deletions(-) rename src/SPIN/{min_spin_oso_cg.cpp => min_spin_cg.cpp} (91%) rename src/SPIN/{min_spin_oso_cg.h => min_spin_cg.h} (90%) rename src/SPIN/{min_spin_oso_lbfgs.cpp => min_spin_lbfgs.cpp} (90%) rename src/SPIN/{min_spin_oso_lbfgs.h => min_spin_lbfgs.h} (90%) diff --git a/doc/src/min_modify.txt b/doc/src/min_modify.txt index 857c3551aa..22ee232467 100644 --- a/doc/src/min_modify.txt +++ b/doc/src/min_modify.txt @@ -72,7 +72,7 @@ that difference may be smaller than machine epsilon even if atoms could move in the gradient direction to reduce forces further. The choice of a norm can be modified for the min styles {cg}, {sd}, -{quickmin}, {fire}, {spin}, {spin_oso_cg} and {spin_oso_lbfgs} using +{quickmin}, {fire}, {spin}, {spin/cg} and {spin/lbfgs} using the {norm} keyword. The default {euclidean} norm computes the 2-norm (length) of the global force vector. The {max} norm computes the maximum value @@ -88,19 +88,19 @@ adaptive timestep used in the {spin} minimization. See "min_spin"_min_spin.html for more information about those quantities. -The choice of a line search algorithm for the {spin_oso_cg} and -{spin_oso_lbfgs} styles can be specified via the {line} keyword. +The choice of a line search algorithm for the {spin/cg} and +{spin/lbfgs} styles can be specified via the {line} keyword. The {spin_cubic} and {spin_none} only make sense when one of those two minimization styles is declared. The {spin_cubic} performs the line search based on a cubic interpolation of the energy along the search direction. The {spin_none} keyword deactivates the line search procedure. -The {spin_none} is a default value for {line} keyword for both {spin_oso_lbfgs} -and {spin_oso_cg}. Convergence of {spin_oso_lbfgs} can be more robust if +The {spin_none} is a default value for {line} keyword for both {spin/lbfgs} +and {spin/cg}. Convergence of {spin/lbfgs} can be more robust if {spin_cubic} line search is used. [Restrictions:] The line search procedure of styles -{spin_oso_cg} and {spin_oso_lbfgs} cannot be used for magnetic +{spin/cg} and {spin/lbfgs} cannot be used for magnetic GNEB calculations. See "neb/spin"_neb_spin.html for more explanation. @@ -112,6 +112,6 @@ explanation. The option defaults are dmax = 0.1, line = quadratic and norm = euclidean. -For the {spin}, {spin_oso_cg} and {spin_oso_lbfgs} styles, the +For the {spin}, {spin/cg} and {spin/lbfgs} styles, the option defaults are alpha_damp = 1.0, discrete_factor = 10.0, line = spin_none, and norm = euclidean. diff --git a/doc/src/min_spin.txt b/doc/src/min_spin.txt index 575db2dc74..ba034cfbb9 100644 --- a/doc/src/min_spin.txt +++ b/doc/src/min_spin.txt @@ -6,18 +6,18 @@ :line min_style spin command :h3 -min_style spin_oso_cg command :h3 -min_style spin_oso_lbfgs command :h3 +min_style spin/cg command :h3 +min_style spin/lbfgs command :h3 [Syntax:] min_style spin -min_style spin_oso_cg -min_style spin_oso_lbfgs :pre +min_style spin/cg +min_style spin/lbfgs :pre [Examples:] -min_style spin_oso_lbfgs +min_style spin/lbfgs min_modify line spin_cubic discrete_factor 10.0 :pre [Description:] @@ -51,35 +51,35 @@ definition of this timestep. {discrete_factor} can be defined with the "min_modify"_min_modify.html command. -Style {spin_oso_cg} defines an orthogonal spin optimization +Style {spin/cg} defines an orthogonal spin optimization (OSO) combined to a conjugate gradient (CG) algorithm. The "min_modify"_min_modify.html command can be used to -couple the {spin_oso_cg} to a line search procedure, and to modify the +couple the {spin/cg} to a line search procedure, and to modify the discretization factor {discrete_factor}. -By default, style {spin_oso_cg} does not employ the line search procedure +By default, style {spin/cg} does not employ the line search procedure and uses the adaptive time-step technique in the same way as style {spin}. -Style {spin_oso_lbfgs} defines an orthogonal spin optimization +Style {spin/lbfgs} defines an orthogonal spin optimization (OSO) combined to a limited-memory Broyden-Fletcher-Goldfarb-Shanno (L-BFGS) algorithm. -By default, style {spin_oso_lbfgs} does not employ line search procedure. +By default, style {spin/lbfgs} does not employ line search procedure. If the line search procedure is not used then the discrete factor defines the maximum root mean squared rotation angle of spins by equation {pi/(5*Kappa)}. The default value for Kappa is 10. The {spin_cubic} line search can improve the convergence of the -{spin_oso_lbfgs} algorithm. +{spin/lbfgs} algorithm. The "min_modify"_min_modify.html command can be used to activate the line search procedure, and to modify the discretization factor {discrete_factor}. -For more information about styles {spin_oso_cg} and {spin_oso_lbfgs}, +For more information about styles {spin/cg} and {spin/lbfgs}, see their implementation reported in "(Ivanov)"_#Ivanov1. NOTE: All the {spin} styles replace the force tolerance by a torque tolerance. See "minimize"_minimize.html for more explanation. -NOTE: The {spin_oso_cg} and {spin_oso_lbfgs} styles can be used +NOTE: The {spin/cg} and {spin/lbfgs} styles can be used for magnetic NEB calculations only if the line search procedure is deactivated. See "neb/spin"_neb_spin.html for more explanation. diff --git a/doc/src/min_style.txt b/doc/src/min_style.txt index 7c40fd4947..9613da7b13 100644 --- a/doc/src/min_style.txt +++ b/doc/src/min_style.txt @@ -11,7 +11,7 @@ min_style command :h3 min_style style :pre -style = {cg} or {hftn} or {sd} or {quickmin} or {fire} or {spin} or {spin_oso_cg} or {spin_oso_lbfgs} :ul +style = {cg} or {hftn} or {sd} or {quickmin} or {fire} or {spin} or {spin/cg} or {spin/lbfgs} :ul [Examples:] @@ -65,21 +65,21 @@ a minimization. Style {spin} is a damped spin dynamics with an adaptive timestep. -Style {spin_oso_cg} uses an orthogonal spin optimization (OSO) +Style {spin/cg} uses an orthogonal spin optimization (OSO) combined to a conjugate gradient (CG) approach to minimize spin configurations. -Style {spin_oso_lbfgs} uses an orthogonal spin optimization (OSO) +Style {spin/lbfgs} uses an orthogonal spin optimization (OSO) combined to a limited-memory Broyden-Fletcher-Goldfarb-Shanno (LBFGS) approach to minimize spin configurations. See the "min/spin"_min_spin.html doc page for more information -about the {spin}, {spin_oso_cg} and {spin_oso_lbfgs} styles. +about the {spin}, {spin/cg} and {spin/lbfgs} styles. Either the {quickmin} and {fire} styles are useful in the context of nudged elastic band (NEB) calculations via the "neb"_neb.html command. -Either the {spin}, {spin_oso_cg} and {spin_oso_lbfgs} styles are useful +Either the {spin}, {spin/cg} and {spin/lbfgs} styles are useful in the context of magnetic geodesic nudged elastic band (GNEB) calculations via the "neb/spin"_neb_spin.html command. diff --git a/doc/src/minimize.txt b/doc/src/minimize.txt index 1de925d6c8..bfdc02bedf 100644 --- a/doc/src/minimize.txt +++ b/doc/src/minimize.txt @@ -104,7 +104,7 @@ the number of outer iterations or timesteps exceeds {maxiter} the number of total force evaluations exceeds {maxeval} :ul NOTE: the "minimization style"_min_style.html {spin}, -{spin_oso_cg}, and {spin_oso_lbfgs} replace +{spin/cg}, and {spin/lbfgs} replace the force tolerance {ftol} by a torque tolerance. The minimization procedure stops if the 2-norm (length) of the torque vector on atom (defined as the cross product between the diff --git a/doc/src/neb_spin.txt b/doc/src/neb_spin.txt index 2fdfda8c66..b64df39219 100644 --- a/doc/src/neb_spin.txt +++ b/doc/src/neb_spin.txt @@ -173,7 +173,7 @@ A NEB calculation proceeds in two stages, each of which is a minimization procedure. To enable this, you must first define a "min_style"_min_style.html, using either the {spin}, -{spin_oso_cg}, or {spin_oso_lbfgs} style (see +{spin/cg}, or {spin/lbfgs} style (see "min_spin"_min_spin.html for more information). The other styles cannot be used, since they relax the lattice degrees of freedom instead of the spins. @@ -359,7 +359,7 @@ This command can only be used if LAMMPS was built with the SPIN package. See the "Build package"_Build_package.html doc page for more info. -The line search procedures of the {spin_oso_cg} and {spin_oso_lbfgs} +The line search procedures of the {spin/cg} and {spin/lbfgs} minimization styles cannot be used in a GNEB calculation. :line diff --git a/examples/SPIN/spinmin/in.spinmin_cg.bfo b/examples/SPIN/spinmin/in.spinmin_cg.bfo index 8c288763c4..9d57399a56 100644 --- a/examples/SPIN/spinmin/in.spinmin_cg.bfo +++ b/examples/SPIN/spinmin/in.spinmin_cg.bfo @@ -49,6 +49,6 @@ thermo_modify format float %20.15g compute outsp all property/atom spx spy spz sp fmx fmy fmz dump 1 all custom 50 dump.lammpstrj type x y z c_outsp[1] c_outsp[2] c_outsp[3] c_outsp[4] c_outsp[5] c_outsp[6] c_outsp[7] -min_style spin_oso_cg +min_style spin/cg # min_modify line spin_none discrete_factor 10.0 minimize 1.0e-10 1.0e-10 10000 10000 diff --git a/examples/SPIN/spinmin/in.spinmin_lbfgs.bfo b/examples/SPIN/spinmin/in.spinmin_lbfgs.bfo index 6a9104cc9c..a73b863b11 100644 --- a/examples/SPIN/spinmin/in.spinmin_lbfgs.bfo +++ b/examples/SPIN/spinmin/in.spinmin_lbfgs.bfo @@ -49,6 +49,6 @@ thermo_modify format float %20.15g compute outsp all property/atom spx spy spz sp fmx fmy fmz dump 1 all custom 50 dump.lammpstrj type x y z c_outsp[1] c_outsp[2] c_outsp[3] c_outsp[4] c_outsp[5] c_outsp[6] c_outsp[7] -min_style spin_oso_lbfgs +min_style spin/lbfgs # min_modify line spin_cubic discrete_factor 10.0 minimize 1.0e-15 1.0e-10 10000 1000 diff --git a/src/.gitignore b/src/.gitignore index 595276853c..5848874d94 100644 --- a/src/.gitignore +++ b/src/.gitignore @@ -161,10 +161,10 @@ /fix_setforce_spin.h /min_spin.cpp /min_spin.h -/min_spin_oso_cg.cpp -/min_spin_oso_cg.h -/min_spin_oso_lbfgs.cpp -/min_spin_oso_lbfgs.h +/min_spin_cg.cpp +/min_spin_cg.h +/min_spin_lbfgs.cpp +/min_spin_lbfgs.h /neb_spin.cpp /neb_spin.h /pair_spin.cpp diff --git a/src/SPIN/min_spin_oso_cg.cpp b/src/SPIN/min_spin_cg.cpp similarity index 91% rename from src/SPIN/min_spin_oso_cg.cpp rename to src/SPIN/min_spin_cg.cpp index f1f2f72436..322915c0f3 100644 --- a/src/SPIN/min_spin_oso_cg.cpp +++ b/src/SPIN/min_spin_cg.cpp @@ -25,7 +25,7 @@ #include #include #include -#include "min_spin_oso_cg.h" +#include "min_spin_cg.h" #include "universe.h" #include "atom.h" #include "citeme.h" @@ -44,8 +44,8 @@ using namespace LAMMPS_NS; using namespace MathConst; -static const char cite_minstyle_spin_oso_cg[] = - "min_style spin/oso_cg command:\n\n" +static const char cite_minstyle_spin_cg[] = + "min_style spin/cg command:\n\n" "@article{ivanov2019fast,\n" "title={Fast and Robust Algorithm for the Minimisation of the Energy of " "Spin Systems},\n" @@ -63,10 +63,10 @@ static const char cite_minstyle_spin_oso_cg[] = /* ---------------------------------------------------------------------- */ -MinSpinOSO_CG::MinSpinOSO_CG(LAMMPS *lmp) : +MinSpinCG::MinSpinCG(LAMMPS *lmp) : Min(lmp), g_old(NULL), g_cur(NULL), p_s(NULL), sp_copy(NULL) { - if (lmp->citeme) lmp->citeme->add(cite_minstyle_spin_oso_cg); + if (lmp->citeme) lmp->citeme->add(cite_minstyle_spin_cg); nlocal_max = 0; // nreplica = number of partitions @@ -81,7 +81,7 @@ MinSpinOSO_CG::MinSpinOSO_CG(LAMMPS *lmp) : /* ---------------------------------------------------------------------- */ -MinSpinOSO_CG::~MinSpinOSO_CG() +MinSpinCG::~MinSpinCG() { memory->destroy(g_old); memory->destroy(g_cur); @@ -92,7 +92,7 @@ MinSpinOSO_CG::~MinSpinOSO_CG() /* ---------------------------------------------------------------------- */ -void MinSpinOSO_CG::init() +void MinSpinCG::init() { local_iter = 0; der_e_cur = 0.0; @@ -120,16 +120,16 @@ void MinSpinOSO_CG::init() // allocate tables nlocal_max = atom->nlocal; - memory->grow(g_old,3*nlocal_max,"min/spin/oso/cg:g_old"); - memory->grow(g_cur,3*nlocal_max,"min/spin/oso/cg:g_cur"); - memory->grow(p_s,3*nlocal_max,"min/spin/oso/cg:p_s"); + memory->grow(g_old,3*nlocal_max,"min/spin/cg:g_old"); + memory->grow(g_cur,3*nlocal_max,"min/spin/cg:g_cur"); + memory->grow(p_s,3*nlocal_max,"min/spin/cg:p_s"); if (use_line_search) - memory->grow(sp_copy,nlocal_max,3,"min/spin/oso/cg:sp_copy"); + memory->grow(sp_copy,nlocal_max,3,"min/spin/cg:sp_copy"); } /* ---------------------------------------------------------------------- */ -void MinSpinOSO_CG::setup_style() +void MinSpinCG::setup_style() { double **v = atom->v; int nlocal = atom->nlocal; @@ -137,7 +137,7 @@ void MinSpinOSO_CG::setup_style() // check if the atom/spin style is defined if (!atom->sp_flag) - error->all(FLERR,"min/spin_oso_cg requires atom/spin style"); + error->all(FLERR,"min spin/cg requires atom/spin style"); for (int i = 0; i < nlocal; i++) v[i][0] = v[i][1] = v[i][2] = 0.0; @@ -145,7 +145,7 @@ void MinSpinOSO_CG::setup_style() /* ---------------------------------------------------------------------- */ -int MinSpinOSO_CG::modify_param(int narg, char **arg) +int MinSpinCG::modify_param(int narg, char **arg) { if (strcmp(arg[0],"discrete_factor") == 0) { if (narg < 2) error->all(FLERR,"Illegal fix_modify command"); @@ -160,7 +160,7 @@ int MinSpinOSO_CG::modify_param(int narg, char **arg) called after atoms have migrated ------------------------------------------------------------------------- */ -void MinSpinOSO_CG::reset_vectors() +void MinSpinCG::reset_vectors() { // atomic dof @@ -179,7 +179,7 @@ void MinSpinOSO_CG::reset_vectors() minimization via orthogonal spin optimisation ------------------------------------------------------------------------- */ -int MinSpinOSO_CG::iterate(int maxiter) +int MinSpinCG::iterate(int maxiter) { int nlocal = atom->nlocal; bigint ntimestep; @@ -191,11 +191,11 @@ int MinSpinOSO_CG::iterate(int maxiter) if (nlocal_max < nlocal) { local_iter = 0; nlocal_max = nlocal; - memory->grow(g_old,3*nlocal_max,"min/spin/oso/cg:g_old"); - memory->grow(g_cur,3*nlocal_max,"min/spin/oso/cg:g_cur"); - memory->grow(p_s,3*nlocal_max,"min/spin/oso/cg:p_s"); + memory->grow(g_old,3*nlocal_max,"min/spin/cg:g_old"); + memory->grow(g_cur,3*nlocal_max,"min/spin/cg:g_cur"); + memory->grow(p_s,3*nlocal_max,"min/spin/cg:p_s"); if (use_line_search) - memory->grow(sp_copy,nlocal_max,3,"min/spin/oso/cg:sp_copy"); + memory->grow(sp_copy,nlocal_max,3,"min/spin/cg:sp_copy"); } for (int iter = 0; iter < maxiter; iter++) { @@ -309,7 +309,7 @@ int MinSpinOSO_CG::iterate(int maxiter) calculate gradients ---------------------------------------------------------------------- */ -void MinSpinOSO_CG::calc_gradient() +void MinSpinCG::calc_gradient() { int nlocal = atom->nlocal; double **sp = atom->sp; @@ -337,7 +337,7 @@ void MinSpinOSO_CG::calc_gradient() Optimization' Second Edition, 2006 (p. 121) ---------------------------------------------------------------------- */ -void MinSpinOSO_CG::calc_search_direction() +void MinSpinCG::calc_search_direction() { int nlocal = atom->nlocal; double g2old = 0.0; @@ -398,7 +398,7 @@ void MinSpinOSO_CG::calc_search_direction() rotation of spins along the search direction ---------------------------------------------------------------------- */ -void MinSpinOSO_CG::advance_spins() +void MinSpinCG::advance_spins() { int nlocal = atom->nlocal; double **sp = atom->sp; @@ -429,7 +429,7 @@ void MinSpinOSO_CG::advance_spins() [-y, -z, 0]] ------------------------------------------------------------------------- */ -void MinSpinOSO_CG::rodrigues_rotation(const double *upp_tr, double *out) +void MinSpinCG::rodrigues_rotation(const double *upp_tr, double *out) { double theta,A,B,D,x,y,z; double s1,s2,s3,a1,a2,a3; @@ -490,7 +490,7 @@ void MinSpinOSO_CG::rodrigues_rotation(const double *upp_tr, double *out) m -- 3x3 matrix , v -- 3-d vector ------------------------------------------------------------------------- */ -void MinSpinOSO_CG::vm3(const double *m, const double *v, double *out) +void MinSpinCG::vm3(const double *m, const double *v, double *out) { for(int i = 0; i < 3; i++){ out[i] = 0.0; @@ -502,7 +502,7 @@ void MinSpinOSO_CG::vm3(const double *m, const double *v, double *out) advance spins ------------------------------------------------------------------------- */ -void MinSpinOSO_CG::make_step(double c, double *energy_and_der) +void MinSpinCG::make_step(double c, double *energy_and_der) { double p_scaled[3]; int nlocal = atom->nlocal; @@ -549,7 +549,7 @@ void MinSpinOSO_CG::make_step(double c, double *energy_and_der) using the cubic interpolation ------------------------------------------------------------------------- */ -int MinSpinOSO_CG::calc_and_make_step(double a, double b, int index) +int MinSpinCG::calc_and_make_step(double a, double b, int index) { double e_and_d[2] = {0.0,0.0}; double alpha,c1,c2,c3; @@ -601,7 +601,7 @@ int MinSpinOSO_CG::calc_and_make_step(double a, double b, int index) Approximate descent ------------------------------------------------------------------------- */ -int MinSpinOSO_CG::adescent(double phi_0, double phi_j){ +int MinSpinCG::adescent(double phi_0, double phi_j){ double eps = 1.0e-6; @@ -615,7 +615,7 @@ int MinSpinOSO_CG::adescent(double phi_0, double phi_j){ evaluate max timestep ---------------------------------------------------------------------- */ -double MinSpinOSO_CG::evaluate_dt() +double MinSpinCG::evaluate_dt() { double dtmax; double fmsq; diff --git a/src/SPIN/min_spin_oso_cg.h b/src/SPIN/min_spin_cg.h similarity index 90% rename from src/SPIN/min_spin_oso_cg.h rename to src/SPIN/min_spin_cg.h index d6dc7c03d0..0eed7a61e6 100644 --- a/src/SPIN/min_spin_oso_cg.h +++ b/src/SPIN/min_spin_cg.h @@ -13,21 +13,21 @@ #ifdef MINIMIZE_CLASS -MinimizeStyle(spin_oso_cg, MinSpinOSO_CG) +MinimizeStyle(spin/cg, MinSpinCG) #else -#ifndef LMP_MIN_SPIN_OSO_CG_H -#define LMP_MIN_SPIN_OSO_CG_H +#ifndef LMP_MIN_SPIN_CG_H +#define LMP_MIN_SPIN_CG_H #include "min.h" namespace LAMMPS_NS { -class MinSpinOSO_CG: public Min { +class MinSpinCG: public Min { public: - MinSpinOSO_CG(class LAMMPS *); - virtual ~MinSpinOSO_CG(); + MinSpinCG(class LAMMPS *); + virtual ~MinSpinCG(); void init(); void setup_style(); void reset_vectors(); diff --git a/src/SPIN/min_spin_oso_lbfgs.cpp b/src/SPIN/min_spin_lbfgs.cpp similarity index 90% rename from src/SPIN/min_spin_oso_lbfgs.cpp rename to src/SPIN/min_spin_lbfgs.cpp index 8623a8bb29..891dec5c93 100644 --- a/src/SPIN/min_spin_oso_lbfgs.cpp +++ b/src/SPIN/min_spin_lbfgs.cpp @@ -25,7 +25,7 @@ #include #include #include -#include "min_spin_oso_lbfgs.h" +#include "min_spin_lbfgs.h" #include "atom.h" #include "citeme.h" #include "comm.h" @@ -43,8 +43,8 @@ using namespace LAMMPS_NS; using namespace MathConst; -static const char cite_minstyle_spin_oso_lbfgs[] = - "min_style spin/oso_lbfgs command:\n\n" +static const char cite_minstyle_spin_lbfgs[] = + "min_style spin/lbfgs command:\n\n" "@article{ivanov2019fast,\n" "title={Fast and Robust Algorithm for the Minimisation of the Energy of " "Spin Systems},\n" @@ -62,10 +62,10 @@ static const char cite_minstyle_spin_oso_lbfgs[] = /* ---------------------------------------------------------------------- */ -MinSpinOSO_LBFGS::MinSpinOSO_LBFGS(LAMMPS *lmp) : +MinSpinLBFGS::MinSpinLBFGS(LAMMPS *lmp) : Min(lmp), g_old(NULL), g_cur(NULL), p_s(NULL), rho(NULL), ds(NULL), dy(NULL), sp_copy(NULL) { - if (lmp->citeme) lmp->citeme->add(cite_minstyle_spin_oso_lbfgs); + if (lmp->citeme) lmp->citeme->add(cite_minstyle_spin_lbfgs); nlocal_max = 0; // nreplica = number of partitions @@ -81,7 +81,7 @@ MinSpinOSO_LBFGS::MinSpinOSO_LBFGS(LAMMPS *lmp) : /* ---------------------------------------------------------------------- */ -MinSpinOSO_LBFGS::~MinSpinOSO_LBFGS() +MinSpinLBFGS::~MinSpinLBFGS() { memory->destroy(g_old); memory->destroy(g_cur); @@ -95,7 +95,7 @@ MinSpinOSO_LBFGS::~MinSpinOSO_LBFGS() /* ---------------------------------------------------------------------- */ -void MinSpinOSO_LBFGS::init() +void MinSpinLBFGS::init() { num_mem = 3; local_iter = 0; @@ -123,20 +123,20 @@ void MinSpinOSO_LBFGS::init() // allocate tables nlocal_max = atom->nlocal; - memory->grow(g_old,3*nlocal_max,"min/spin/oso/lbfgs:g_old"); - memory->grow(g_cur,3*nlocal_max,"min/spin/oso/lbfgs:g_cur"); - memory->grow(p_s,3*nlocal_max,"min/spin/oso/lbfgs:p_s"); - memory->grow(rho,num_mem,"min/spin/oso/lbfgs:rho"); - memory->grow(ds,num_mem,3*nlocal_max,"min/spin/oso/lbfgs:ds"); - memory->grow(dy,num_mem,3*nlocal_max,"min/spin/oso/lbfgs:dy"); + memory->grow(g_old,3*nlocal_max,"min/spin/lbfgs:g_old"); + memory->grow(g_cur,3*nlocal_max,"min/spin/lbfgs:g_cur"); + memory->grow(p_s,3*nlocal_max,"min/spin/lbfgs:p_s"); + memory->grow(rho,num_mem,"min/spin/lbfgs:rho"); + memory->grow(ds,num_mem,3*nlocal_max,"min/spin/lbfgs:ds"); + memory->grow(dy,num_mem,3*nlocal_max,"min/spin/lbfgs:dy"); if (use_line_search) - memory->grow(sp_copy,nlocal_max,3,"min/spin/oso/lbfgs:sp_copy"); + memory->grow(sp_copy,nlocal_max,3,"min/spin/lbfgs:sp_copy"); } /* ---------------------------------------------------------------------- */ -void MinSpinOSO_LBFGS::setup_style() +void MinSpinLBFGS::setup_style() { double **v = atom->v; int nlocal = atom->nlocal; @@ -144,7 +144,7 @@ void MinSpinOSO_LBFGS::setup_style() // check if the atom/spin style is defined if (!atom->sp_flag) - error->all(FLERR,"min/spin_oso_lbfgs requires atom/spin style"); + error->all(FLERR,"min spin/lbfgs requires atom/spin style"); for (int i = 0; i < nlocal; i++) v[i][0] = v[i][1] = v[i][2] = 0.0; @@ -152,7 +152,7 @@ void MinSpinOSO_LBFGS::setup_style() /* ---------------------------------------------------------------------- */ -int MinSpinOSO_LBFGS::modify_param(int narg, char **arg) +int MinSpinLBFGS::modify_param(int narg, char **arg) { if (strcmp(arg[0],"discrete_factor") == 0) { if (narg < 2) error->all(FLERR,"Illegal min_modify command"); @@ -169,7 +169,7 @@ int MinSpinOSO_LBFGS::modify_param(int narg, char **arg) called after atoms have migrated ------------------------------------------------------------------------- */ -void MinSpinOSO_LBFGS::reset_vectors() +void MinSpinLBFGS::reset_vectors() { // atomic dof @@ -188,7 +188,7 @@ void MinSpinOSO_LBFGS::reset_vectors() minimization via damped spin dynamics ------------------------------------------------------------------------- */ -int MinSpinOSO_LBFGS::iterate(int maxiter) +int MinSpinLBFGS::iterate(int maxiter) { int nlocal = atom->nlocal; bigint ntimestep; @@ -200,14 +200,14 @@ int MinSpinOSO_LBFGS::iterate(int maxiter) if (nlocal_max < nlocal) { nlocal_max = nlocal; local_iter = 0; - memory->grow(g_old,3*nlocal_max,"min/spin/oso/lbfgs:g_old"); - memory->grow(g_cur,3*nlocal_max,"min/spin/oso/lbfgs:g_cur"); - memory->grow(p_s,3*nlocal_max,"min/spin/oso/lbfgs:p_s"); - memory->grow(rho,num_mem,"min/spin/oso/lbfgs:rho"); - memory->grow(ds,num_mem,3*nlocal_max,"min/spin/oso/lbfgs:ds"); - memory->grow(dy,num_mem,3*nlocal_max,"min/spin/oso/lbfgs:dy"); + memory->grow(g_old,3*nlocal_max,"min/spin/lbfgs:g_old"); + memory->grow(g_cur,3*nlocal_max,"min/spin/lbfgs:g_cur"); + memory->grow(p_s,3*nlocal_max,"min/spin/lbfgs:p_s"); + memory->grow(rho,num_mem,"min/spin/lbfgs:rho"); + memory->grow(ds,num_mem,3*nlocal_max,"min/spin/lbfgs:ds"); + memory->grow(dy,num_mem,3*nlocal_max,"min/spin/lbfgs:dy"); if (use_line_search) - memory->grow(sp_copy,nlocal_max,3,"min/spin/oso/lbfgs:sp_copy"); + memory->grow(sp_copy,nlocal_max,3,"min/spin/lbfgs:sp_copy"); } for (int iter = 0; iter < maxiter; iter++) { @@ -324,7 +324,7 @@ int MinSpinOSO_LBFGS::iterate(int maxiter) calculate gradients ---------------------------------------------------------------------- */ -void MinSpinOSO_LBFGS::calc_gradient() +void MinSpinLBFGS::calc_gradient() { int nlocal = atom->nlocal; double **sp = atom->sp; @@ -347,7 +347,7 @@ void MinSpinOSO_LBFGS::calc_gradient() Optimization' Second Edition, 2006 (p. 177) ---------------------------------------------------------------------- */ -void MinSpinOSO_LBFGS::calc_search_direction() +void MinSpinLBFGS::calc_search_direction() { int nlocal = atom->nlocal; @@ -531,7 +531,7 @@ void MinSpinOSO_LBFGS::calc_search_direction() rotation of spins along the search direction ---------------------------------------------------------------------- */ -void MinSpinOSO_LBFGS::advance_spins() +void MinSpinLBFGS::advance_spins() { int nlocal = atom->nlocal; double **sp = atom->sp; @@ -562,7 +562,7 @@ void MinSpinOSO_LBFGS::advance_spins() [-y, -z, 0]] ------------------------------------------------------------------------- */ -void MinSpinOSO_LBFGS::rodrigues_rotation(const double *upp_tr, double *out) +void MinSpinLBFGS::rodrigues_rotation(const double *upp_tr, double *out) { double theta,A,B,D,x,y,z; double s1,s2,s3,a1,a2,a3; @@ -622,7 +622,7 @@ void MinSpinOSO_LBFGS::rodrigues_rotation(const double *upp_tr, double *out) m -- 3x3 matrix , v -- 3-d vector ------------------------------------------------------------------------- */ -void MinSpinOSO_LBFGS::vm3(const double *m, const double *v, double *out) +void MinSpinLBFGS::vm3(const double *m, const double *v, double *out) { for(int i = 0; i < 3; i++){ out[i] = 0.0; @@ -632,7 +632,7 @@ void MinSpinOSO_LBFGS::vm3(const double *m, const double *v, double *out) } -void MinSpinOSO_LBFGS::make_step(double c, double *energy_and_der) +void MinSpinLBFGS::make_step(double c, double *energy_and_der) { double p_scaled[3]; int nlocal = atom->nlocal; @@ -679,7 +679,7 @@ void MinSpinOSO_LBFGS::make_step(double c, double *energy_and_der) using the cubic interpolation ------------------------------------------------------------------------- */ -int MinSpinOSO_LBFGS::calc_and_make_step(double a, double b, int index) +int MinSpinLBFGS::calc_and_make_step(double a, double b, int index) { double e_and_d[2] = {0.0,0.0}; double alpha,c1,c2,c3; @@ -731,7 +731,7 @@ int MinSpinOSO_LBFGS::calc_and_make_step(double a, double b, int index) Approximate descent ------------------------------------------------------------------------- */ -int MinSpinOSO_LBFGS::adescent(double phi_0, double phi_j){ +int MinSpinLBFGS::adescent(double phi_0, double phi_j){ double eps = 1.0e-6; @@ -741,7 +741,7 @@ int MinSpinOSO_LBFGS::adescent(double phi_0, double phi_j){ return 0; } -double MinSpinOSO_LBFGS::maximum_rotation(double *p) +double MinSpinLBFGS::maximum_rotation(double *p) { double norm2,norm2_global,scaling,alpha; int nlocal = atom->nlocal; diff --git a/src/SPIN/min_spin_oso_lbfgs.h b/src/SPIN/min_spin_lbfgs.h similarity index 90% rename from src/SPIN/min_spin_oso_lbfgs.h rename to src/SPIN/min_spin_lbfgs.h index 68fa10921e..cead605b32 100644 --- a/src/SPIN/min_spin_oso_lbfgs.h +++ b/src/SPIN/min_spin_lbfgs.h @@ -13,21 +13,21 @@ #ifdef MINIMIZE_CLASS -MinimizeStyle(spin_oso_lbfgs, MinSpinOSO_LBFGS) +MinimizeStyle(spin/lbfgs, MinSpinLBFGS) #else -#ifndef LMP_MIN_SPIN_OSO_LBFGS_H -#define LMP_MIN_SPIN_OSO_LBFGS_H +#ifndef LMP_MIN_SPIN_LBFGS_H +#define LMP_MIN_SPIN_LBFGS_H #include "min.h" namespace LAMMPS_NS { -class MinSpinOSO_LBFGS: public Min { +class MinSpinLBFGS: public Min { public: - MinSpinOSO_LBFGS(class LAMMPS *); - virtual ~MinSpinOSO_LBFGS(); + MinSpinLBFGS(class LAMMPS *); + virtual ~MinSpinLBFGS(); void init(); void setup_style(); int modify_param(int, char **); From 3736fc27584a226b8b972792db2360297f085347 Mon Sep 17 00:00:00 2001 From: charlie sievers Date: Thu, 22 Aug 2019 19:08:01 -0700 Subject: [PATCH 083/192] fix gjf on site velocity --- src/fix_langevin.cpp | 30 +++++++++++++++++++++--------- 1 file changed, 21 insertions(+), 9 deletions(-) diff --git a/src/fix_langevin.cpp b/src/fix_langevin.cpp index 6971b145ec..c14541dee4 100644 --- a/src/fix_langevin.cpp +++ b/src/fix_langevin.cpp @@ -716,9 +716,21 @@ void FixLangevin::post_force_templated() f[i][2] += fdrag[2] + fran[2]; if (Tp_TALLY) { + if (Tp_GJF && update->ntimestep != update->beginstep){ + fdrag[0] = gamma1*lv[i][0]/gjfsib/gjfsib; + fdrag[1] = gamma1*lv[i][1]/gjfsib/gjfsib; + fdrag[2] = gamma1*lv[i][2]/gjfsib/gjfsib; + fswap = (2*fran[0] - franprev[i][0])/gjfsib; + fran[0] = fswap; + fswap = (2*fran[1] - franprev[i][1])/gjfsib; + fran[1] = fswap; + fswap = (2*fran[2] - franprev[i][2])/gjfsib; + fran[2] = fswap; + } flangevin[i][0] = fdrag[0] + fran[0]; flangevin[i][1] = fdrag[1] + fran[1]; flangevin[i][2] = fdrag[2] + fran[2]; + } if (Tp_ZERO) { @@ -935,18 +947,18 @@ void FixLangevin::end_of_step() else{ if (atom->rmass) { dtfm = 0.5 * dt / rmass[i]; - gamma1 = -rmass[i] / t_period / ftm2v; - gamma1 *= 1.0/ratio[type[i]]; } else { dtfm = 0.5 * dt / mass[type[i]]; - gamma1 = gfactor1[type[i]]; } - v[i][0] = flangevin[i][0] - franprev[i][0] + gjfa * (gjfsib/2 + gamma1/gjfsib) * lv[i][0] - + gjfsib*gjfsib*(dtfm * f[i][0] + v[i][0])/2; - v[i][1] = flangevin[i][1] - franprev[i][1] + gjfa * (gjfsib/2 + gamma1/gjfsib) * lv[i][1] - + gjfsib*gjfsib*(dtfm * f[i][1] + v[i][1])/2; - v[i][2] = flangevin[i][2] - franprev[i][2] + gjfa * (gjfsib/2 + gamma1/gjfsib) * lv[i][2] - + gjfsib*gjfsib*(dtfm * f[i][2] + v[i][2])/2; + v[i][0] = 0.5 * gjfsib*gjfsib*(v[i][0] + dtfm * f[i][0] / gjfa) + + dtfm * 0.5 * (gjfsib * flangevin[i][0] - franprev[i][0]) + + (gjfsib * gjfa * 0.5 + dt * 0.25 / t_period / gjfsib) * lv[i][0]; + v[i][1] = 0.5 * gjfsib*gjfsib*(v[i][1] + dtfm * f[i][1] / gjfa) + + dtfm * 0.5 * (gjfsib * flangevin[i][1] - franprev[i][1]) + + (gjfsib * gjfa * 0.5 + dt * 0.25 / t_period / gjfsib) * lv[i][1]; + v[i][2] = 0.5 * gjfsib*gjfsib*(v[i][2] + dtfm * f[i][2] / gjfa) + + dtfm * 0.5 * (gjfsib * flangevin[i][2] - franprev[i][2]) + + (gjfsib * gjfa * 0.5 + dt * 0.25 / t_period / gjfsib) * lv[i][2]; } lv[i][0] = tmp[0]; lv[i][1] = tmp[1]; From ed02c25cfc6ced2c8a2b50341c3875d0e9eaa969 Mon Sep 17 00:00:00 2001 From: jrgissing Date: Thu, 22 Aug 2019 22:36:48 -0600 Subject: [PATCH 084/192] bond/react: bug in 'max_rxn' option fix one-line bug in 'max_rxn' option of bond/react --- src/USER-MISC/fix_bond_react.cpp | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/USER-MISC/fix_bond_react.cpp b/src/USER-MISC/fix_bond_react.cpp index 05dc54c57e..852362018f 100644 --- a/src/USER-MISC/fix_bond_react.cpp +++ b/src/USER-MISC/fix_bond_react.cpp @@ -1209,7 +1209,7 @@ void FixBondReact::superimpose_algorithm() rxn_by_proc[j] = -1; // corresponds to ghostly int itemp = 0; for (int j = 0; j < nprocs; j++) - for (int k = 0; k < local_rxn_count[j]; k++) + for (int k = 0; k < local_rxncounts[j]; k++) rxn_by_proc[itemp++] = j; std::random_shuffle(&rxn_by_proc[0],&rxn_by_proc[delta_rxn]); for (int j = 0; j < nprocs; j++) From 8b7c0e13b3596cae14b5e5ef657a8ca46c6db424 Mon Sep 17 00:00:00 2001 From: charlie sievers Date: Fri, 23 Aug 2019 18:34:43 -0700 Subject: [PATCH 085/192] updated onsite velocity --- src/fix_langevin.cpp | 35 +++++++++++++++++++++-------------- 1 file changed, 21 insertions(+), 14 deletions(-) diff --git a/src/fix_langevin.cpp b/src/fix_langevin.cpp index c14541dee4..7734989e35 100644 --- a/src/fix_langevin.cpp +++ b/src/fix_langevin.cpp @@ -716,15 +716,15 @@ void FixLangevin::post_force_templated() f[i][2] += fdrag[2] + fran[2]; if (Tp_TALLY) { - if (Tp_GJF && update->ntimestep != update->beginstep){ + if (Tp_GJF){ fdrag[0] = gamma1*lv[i][0]/gjfsib/gjfsib; fdrag[1] = gamma1*lv[i][1]/gjfsib/gjfsib; fdrag[2] = gamma1*lv[i][2]/gjfsib/gjfsib; - fswap = (2*fran[0] - franprev[i][0])/gjfsib; + fswap = (2*fran[0]/gjfa - franprev[i][0])/gjfsib; fran[0] = fswap; - fswap = (2*fran[1] - franprev[i][1])/gjfsib; + fswap = (2*fran[1]/gjfa - franprev[i][1])/gjfsib; fran[1] = fswap; - fswap = (2*fran[2] - franprev[i][2])/gjfsib; + fswap = (2*fran[2]/gjfa - franprev[i][2])/gjfsib; fran[2] = fswap; } flangevin[i][0] = fdrag[0] + fran[0]; @@ -922,8 +922,7 @@ void FixLangevin::end_of_step() double **v = atom->v; int *mask = atom->mask; int nlocal = atom->nlocal; - double ftm2v = force->ftm2v; - double gamma1; double dtfm; + double dtfm; double dt = update->dt; double *mass = atom->mass; double *rmass = atom->rmass; @@ -932,6 +931,20 @@ void FixLangevin::end_of_step() energy_onestep = 0.0; + if (tallyflag){ + if (gjfflag){ + for (int i = 0; i < nlocal; i++) + if (mask[i] & groupbit) + energy_onestep += flangevin[i][0]*lv[i][0] + flangevin[i][1]*lv[i][1] + + flangevin[i][2]*lv[i][2]; + } + else + for (int i = 0; i < nlocal; i++) + if (mask[i] & groupbit) + energy_onestep += flangevin[i][0]*v[i][0] + flangevin[i][1]*v[i][1] + + flangevin[i][2]*v[i][2]; +} + if (gjfflag){ double tmp[3]; for (int i = 0; i < nlocal; i++) @@ -946,9 +959,9 @@ void FixLangevin::end_of_step() } else{ if (atom->rmass) { - dtfm = 0.5 * dt / rmass[i]; + dtfm = force->ftm2v * 0.5 * dt / rmass[i]; } else { - dtfm = 0.5 * dt / mass[type[i]]; + dtfm = force->ftm2v * 0.5 * dt / mass[type[i]]; } v[i][0] = 0.5 * gjfsib*gjfsib*(v[i][0] + dtfm * f[i][0] / gjfa) + dtfm * 0.5 * (gjfsib * flangevin[i][0] - franprev[i][0]) + @@ -966,12 +979,6 @@ void FixLangevin::end_of_step() } } - if (tallyflag) - for (int i = 0; i < nlocal; i++) - if (mask[i] & groupbit) - energy_onestep += flangevin[i][0]*v[i][0] + flangevin[i][1]*v[i][1] + - flangevin[i][2]*v[i][2]; - energy += energy_onestep*update->dt; } From f1563ed9885ecd1ad9e5b914a320969a7ea44504 Mon Sep 17 00:00:00 2001 From: julient31 Date: Tue, 27 Aug 2019 17:44:04 -0600 Subject: [PATCH 086/192] Commit JT 082719 - correcting min_modify.txt --- doc/src/min_modify.txt | 7 ++++--- 1 file changed, 4 insertions(+), 3 deletions(-) diff --git a/doc/src/min_modify.txt b/doc/src/min_modify.txt index 22ee232467..06c1f7514f 100644 --- a/doc/src/min_modify.txt +++ b/doc/src/min_modify.txt @@ -99,9 +99,10 @@ The {spin_none} is a default value for {line} keyword for both {spin/lbfgs} and {spin/cg}. Convergence of {spin/lbfgs} can be more robust if {spin_cubic} line search is used. -[Restrictions:] The line search procedure of styles -{spin/cg} and {spin/lbfgs} cannot be used for magnetic -GNEB calculations. See "neb/spin"_neb_spin.html for more +[Restrictions:] + +The line search procedure of styles {spin/cg} and {spin/lbfgs} cannot be +used for magnetic GNEB calculations. See "neb/spin"_neb_spin.html for more explanation. [Related commands:] From c981dd7cf4999ff9e1f01ed76c8c0375e8f93545 Mon Sep 17 00:00:00 2001 From: jrgissing Date: Sat, 31 Aug 2019 22:51:06 -0600 Subject: [PATCH 087/192] another one-liner: incorrect string assigment does not affect any current features --- src/USER-MISC/fix_bond_react.cpp | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/USER-MISC/fix_bond_react.cpp b/src/USER-MISC/fix_bond_react.cpp index 852362018f..9c4d819f5d 100644 --- a/src/USER-MISC/fix_bond_react.cpp +++ b/src/USER-MISC/fix_bond_react.cpp @@ -207,7 +207,7 @@ FixBondReact::FixBondReact(LAMMPS *lmp, int narg, char **arg) : iarg++; - rxn_name[rxn] = arg[iarg++]; + strcpy(rxn_name[rxn],arg[iarg++]); int igroup = group->find(arg[iarg++]); if (igroup == -1) error->all(FLERR,"Could not find fix group ID"); From 86c21264b951b64713125f77767f1d74c19b87de Mon Sep 17 00:00:00 2001 From: jrgissing Date: Sun, 1 Sep 2019 23:09:01 -0600 Subject: [PATCH 088/192] correct string assignment, take 2 --- src/USER-MISC/fix_bond_react.cpp | 4 +++- 1 file changed, 3 insertions(+), 1 deletion(-) diff --git a/src/USER-MISC/fix_bond_react.cpp b/src/USER-MISC/fix_bond_react.cpp index 9c4d819f5d..b38a3468c2 100644 --- a/src/USER-MISC/fix_bond_react.cpp +++ b/src/USER-MISC/fix_bond_react.cpp @@ -207,7 +207,9 @@ FixBondReact::FixBondReact(LAMMPS *lmp, int narg, char **arg) : iarg++; - strcpy(rxn_name[rxn],arg[iarg++]); + int n = strlen(arg[iarg]) + 1; + if (n > MAXLINE) error->all(FLERR,"Reaction name (react-ID) is too long (limit: 256 characters)"); + strncpy(rxn_name[rxn],arg[iarg++],n); int igroup = group->find(arg[iarg++]); if (igroup == -1) error->all(FLERR,"Could not find fix group ID"); From 50af20d194ee86de6f873ab48493d81c72d79389 Mon Sep 17 00:00:00 2001 From: jrgissing Date: Sun, 1 Sep 2019 23:31:31 -0600 Subject: [PATCH 089/192] bond/react: remember reaction counts allow restart files to restore cumutative reaction counts --- doc/src/fix_bond_react.txt | 9 ++++--- src/USER-MISC/fix_bond_react.cpp | 42 ++++++++++++++++++++++++++++++++ src/USER-MISC/fix_bond_react.h | 9 +++++++ 3 files changed, 56 insertions(+), 4 deletions(-) diff --git a/doc/src/fix_bond_react.txt b/doc/src/fix_bond_react.txt index 3f428e2103..5aff35787d 100644 --- a/doc/src/fix_bond_react.txt +++ b/doc/src/fix_bond_react.txt @@ -392,10 +392,11 @@ local command. [Restart, fix_modify, output, run start/stop, minimize info:] -No information about this fix is written to "binary restart -files"_restart.html, aside from internally-created per-atom -properties. None of the "fix_modify"_fix_modify.html options are -relevant to this fix. +Cumulative reaction counts for each reaction are written to "binary +restart files"_restart.html. These values are associated with the +reaction name (react-ID). Additionally, internally-created per-atom +properties are stored to allow for smooth restarts. None of the +"fix_modify"_fix_modify.html options are relevant to this fix. This fix computes one statistic for each {react} argument that it stores in a global vector, of length 'number of react arguments', that diff --git a/src/USER-MISC/fix_bond_react.cpp b/src/USER-MISC/fix_bond_react.cpp index b38a3468c2..07f009360a 100644 --- a/src/USER-MISC/fix_bond_react.cpp +++ b/src/USER-MISC/fix_bond_react.cpp @@ -87,6 +87,7 @@ FixBondReact::FixBondReact(LAMMPS *lmp, int narg, char **arg) : MPI_Comm_size(world,&nprocs); newton_bond = force->newton_bond; + restart_global = 1; attempted_rxn = 0; force_reneighbor = 1; next_reneighbor = -1; @@ -388,6 +389,10 @@ FixBondReact::FixBondReact(LAMMPS *lmp, int narg, char **arg) : id_fix3 = NULL; statted_id = NULL; custom_exclude_flag = 0; + + // used to store restart info + set = new Set[nreacts]; + memset(set,0,nreacts*sizeof(Set)); } /* ---------------------------------------------------------------------- */ @@ -471,6 +476,7 @@ FixBondReact::~FixBondReact() delete [] statted_id; delete [] guess_branch; delete [] pioneer_count; + delete [] set; if (group) { char **newarg; @@ -3100,6 +3106,42 @@ void FixBondReact::unpack_reverse_comm(int n, int *list, double *buf) } } +/* ---------------------------------------------------------------------- + write Set data to restart file +------------------------------------------------------------------------- */ + +void FixBondReact::write_restart(FILE *fp) +{ + set[0].nreacts = nreacts; + for (int i = 0; i < nreacts; i++) { + set[i].reaction_count_total = reaction_count_total[i]; + int n = strlen(rxn_name[i]) + 1; + strncpy(set[i].rxn_name,rxn_name[i],n); + } + + if (me == 0) { + int size = nreacts*sizeof(Set); + fwrite(&size,sizeof(int),1,fp); + fwrite(set,sizeof(Set),nreacts,fp); + } +} + +/* ---------------------------------------------------------------------- + use selected state info from restart file to restart the Fix +------------------------------------------------------------------------- */ + +void FixBondReact::restart(char *buf) +{ + Set *set_restart = (Set *) buf; + for (int i = 0; i < set_restart[0].nreacts; i++) { + for (int j = 0; j < nreacts; j++) { + if (strcmp(set_restart[i].rxn_name,rxn_name[j]) == 0) { + reaction_count_total[j] = set_restart[i].reaction_count_total; + } + } + } +} + /* ---------------------------------------------------------------------- memory usage of local atom-based arrays ------------------------------------------------------------------------- */ diff --git a/src/USER-MISC/fix_bond_react.h b/src/USER-MISC/fix_bond_react.h index 1ac8d624a9..2be20cf8ec 100644 --- a/src/USER-MISC/fix_bond_react.h +++ b/src/USER-MISC/fix_bond_react.h @@ -170,6 +170,15 @@ class FixBondReact : public Fix { void unlimit_bond(); void limit_bond(int); void dedup_mega_gloves(int); //dedup global mega_glove + virtual void write_restart(FILE *); + virtual void restart(char *buf); + + struct Set { + int nreacts; + char rxn_name[256]; + int reaction_count_total; + }; + Set *set; // DEBUG From 21699b89e0ac20f1c6380c99b59456ad4a3e0f70 Mon Sep 17 00:00:00 2001 From: "tanmoy.7989" Date: Wed, 4 Sep 2019 15:26:10 -0700 Subject: [PATCH 090/192] python tool to reorder replica traj --- doc/src/Tools.txt | 18 +- tools/replica/README.md | 86 + tools/replica/example/data.peptide | 6531 ++++++++++++++++++++++++++++ tools/replica/example/in.peptide | 50 + tools/replica/example/parse_ene.py | 30 + tools/replica/example/run.sh | 10 + tools/replica/example/temps.txt | 1 + tools/replica/reorder_remd_traj.py | 571 +++ 8 files changed, 7296 insertions(+), 1 deletion(-) create mode 100644 tools/replica/README.md create mode 100644 tools/replica/example/data.peptide create mode 100644 tools/replica/example/in.peptide create mode 100644 tools/replica/example/parse_ene.py create mode 100755 tools/replica/example/run.sh create mode 100644 tools/replica/example/temps.txt create mode 100644 tools/replica/reorder_remd_traj.py diff --git a/doc/src/Tools.txt b/doc/src/Tools.txt index eb7b6d81b8..fcbafdaf7e 100644 --- a/doc/src/Tools.txt +++ b/doc/src/Tools.txt @@ -78,7 +78,8 @@ Post-processing tools :h3 "reax"_#reax_tool, "smd"_#smd, "spin"_#spin, -"xmgrace"_#xmgrace :tb(c=6,ea=c,a=l) +"xmgrace"_#xmgrace, +"replica"_#replica :tb(c=6,ea=c,a=l) Miscellaneous tools :h3 @@ -549,3 +550,18 @@ simulation. See the README file for details. These files were provided by Vikas Varshney (vv0210 at gmail.com) + +:line + +replica tool :h4,link(replica) + +The tools/replica directory contains the reorder_remd_traj python script which +can be used to reorder the replica trajectories (resulting from the use of the +temper command) according to temperature. This will produce discontinuous +trajectories with all frames at the same temperature in each trajectory. +Additional options can be used to calculate the canonical configurational +log-weight for each frame at each temperature using the pymbar package. See +the README.md file for further details. Try out the peptide example provided. + +This tool was written by Tanmoy Sanyal, +while at the Shell lab at UC Santa Barbara. (tanmoy dot 7989 at gmail.com) diff --git a/tools/replica/README.md b/tools/replica/README.md new file mode 100644 index 0000000000..9205d962b2 --- /dev/null +++ b/tools/replica/README.md @@ -0,0 +1,86 @@ +## reorder_remd_traj + +LAMMPS Replica Exchange Molecular Dynamics (REMD) trajectories (implemented using the temper command) are arranged by replica, i.e., each trajectory is a continuous replica that records all the ups and downs in temperature. However, often the requirement is that trajectories be continuous in temperature. This requires the LAMMPS REMD trajectories to be re-ordered, which LAMMPS does not do automatically. (see the discussion [here](https://lammps.sandia.gov/threads/msg60440.html)). The reorderLAMMPSREMD tool does exactly this in parallel (using MPI) + +(Protein folding trajectories in [Sanyal, Mittal and Shell, JPC, 2019, 151(4), 044111](https://aip.scitation.org/doi/abs/10.1063/1.5108761) were ordered in temperature space using this tool) + +#### Author + +Tanmoy Sanyal, Shell lab, UC Santa Barbara + +(currently at UC San Francisco) + +email: tanmoy dot 7989 at gmail.com + +#### Features + +- reorder LAMMPS REMD trajectories by temperature keeping only desired frames. + Note: this only handles LAMMPS format trajectories (i.e., lammpstrj format) + Trajectories can be gzipped or bz2-compressed. The trajectories are assumed to + be named as \\.%d.lammpstrj[.gz or .bz2] + +- (optionally) calculate configurational weights for each frame at each + temperature if potential energies are supplied (only implemented for the canonical (NVT) ensemble) + +#### Dependencies + +[`mpi4py`](https://mpi4py.readthedocs.io/en/stable/) +[`pymbar`](https://pymbar.readthedocs.io/en/master/) (for getting configurational weights) +[`tqdm`](https://github.com/tqdm/tqdm) (for printing pretty progress bars) +[`StringIO`](https://docs.python.org/2/library/stringio.html) (or [`io`](https://docs.python.org/3/library/io.html) if in Python 3.x) + +#### Example + +###### REMD Simulation specs +Suppose you ran a REMD simulation for the peptide example using the CHARMM forcefield (see lammps/examples/peptide) in Lammps with the following settings: + +- number of replicas = 16 +- temperatures used (in K): 200 209 219 230 241 252 264 276 289 303 317 332 348 365 382 400 (i.e., exponentially distributed in the range 270-400 K) +- timestep = 2 fs +- total number of timesteps simulated using temper = 2000 (i.e. 4 ps) +- swap frequency = temperatures swapped after every this many steps = `ns` = 10 (i.e. 20 fs) +- write frequency = trajectory frame written to disk after this many steps (using the dump command) = `nw` = 20 (i.e. 40 fs) + +###### LAMMPS output +So, when the dust settles, + +- You'll have 16 replica trajectories. For this tool to work, each replica traj must be named: `..lammpstrj[.gz or .bz2]`, where, + - `prefix` = some common prefix for all your trajectories and (say it is called "peptide")` + - `n` = replica number (0-15 in this case). Note: trajectories **must be in default LAMMPS format **(so stuff like dcd won't work) + +- You will also have a master LAMMPS log file (`logfn`) that contains the swap history of all the replicas + (for more details see [here](https://lammps.sandia.gov/doc/temper.html). Assume that this is called `log.peptide` + +- Further you must have a txt file that numpy can read which stores all the temperature values (say this is called `temps.txt`) + +###### Your desired output +- The total number of timesteps you want consider as production (i.e. after equilbration) = 1000 (i.e. last 2 ps) + +- Reordered trajectories at temperatures 200 K, 276 K, 400 K + +- Configurational log-weight calculation (using [`pymbar`](https://github.com/choderalab/pymbar)). Here, this is limited to the canonical (NVT) ensemble **and without biasing restraints** in your simulation. To do this you'd need to have a file (say called `ene.dat`) that stores a 2D (K X N) array of total potential energies, where, + + - K = total number of replicas = 16, and N = total number of frames in each replica trajectory (= 1000 / 20 = 50 in this case) + + - `ene[k,n]` = energy from n-th frame of k-th replica. + +###### Using the tool (description of the workflow) +Assume you have 16 processors at your disposal. When you run the following: + +```bash +mpirun -np 16 python reorder_remd_traj.py peptide -logfn log.peptide -tfn temps.txt -ns 10 -nw 20 -np 1000 -ot 200 276 400 -logw -e ene.peptide -od ./output +``` + +1. First the temperature swap history file (`log.peptide` in this case) is read. This is done on one processor since it is usually fast. +2. Then the (compressed or otherwise) LAMMPS replica trajectories are read in parallel. So if you have less processors than replicas at this stage, it'll be slower. +3. Then using the frame ordering generated in (1), trajectory frames read in (2) are re-ordered and written to disk in parallel. Each processor writes one trajectory. So, If you request reordered trajectories for less temperatures (3 in this case) than the total number of temperatures (16), then 16-3 = 13 processors will be retired. +4. If you have further requested configurational log-weight calculation, then they will be done on a single processor since pymbar is pretty fast. +5. Finally you will have 3 LAMMPS trajectories of the form ``peptide..lammpstrj.gz`` each with 1000 / 20 = 50 frames, where `` = 200, 276, 400. If you request reordering at a temperature like say 280 K which is not present in the supplied temp schedule (as written in `temps.txt`), the closest temperature (276 K) will be chosen. + +For more details, use the help menu generated by the tool by using: +python reorder_remd_traj.py -h + +###### Caveats +- This tool crawls through the replica trajectories and creates index files that are hidden. These are called .byteind_`'.gz files. You may delete these if you want, but subsequent replica reads will be slow in that case. + +- When writing trajectories to disk, the trajectories are first written to a buffer in memory, and then finally dumped all-at-once to the disk. While this makes the tool very fast, it can cause out-of-memory errors for very large trajectories. A useful feature might be to write to the buffer in batches and emptying to disk when some (predefined) max-buffer-size is exceeded. diff --git a/tools/replica/example/data.peptide b/tools/replica/example/data.peptide new file mode 100644 index 0000000000..f9dfb6e485 --- /dev/null +++ b/tools/replica/example/data.peptide @@ -0,0 +1,6531 @@ +LAMMPS Description + + 2004 atoms + 1365 bonds + 786 angles + 207 dihedrals + 12 impropers + + 14 atom types + 18 bond types + 31 angle types + 21 dihedral types + 2 improper types + + 36.840194 64.211560 xlo xhi + 41.013691 68.385058 ylo yhi + 29.768095 57.139462 zlo zhi + +Masses + + 1 12.0110 + 2 12.0110 + 3 15.9990 + 4 1.0080 + 5 14.0070 + 6 12.0110 + 7 12.0110 + 8 12.0110 + 9 15.9990 + 10 1.0080 + 11 1.0080 + 12 32.0660 + 13 16.0000 + 14 1.0100 + +Pair Coeffs + + 1 0.110000 3.563595 0.110000 3.563595 + 2 0.080000 3.670503 0.010000 3.385415 + 3 0.120000 3.029056 0.120000 2.494516 + 4 0.022000 2.351973 0.022000 2.351973 + 5 0.200000 3.296325 0.200000 2.761786 + 6 0.020000 4.053589 0.010000 3.385415 + 7 0.055000 3.875410 0.010000 3.385415 + 8 0.070000 3.550053 0.070000 3.550053 + 9 0.152100 3.153782 0.152100 3.153782 + 10 0.046000 0.400014 0.046000 0.400014 + 11 0.030000 2.420037 0.030000 2.420037 + 12 0.450000 3.563595 0.450000 3.563595 + 13 0.152100 3.150570 0.152100 3.150570 + 14 0.046000 0.400014 0.046000 0.400014 + +Bond Coeffs + + 1 249.999999 1.490000 + 2 620.000001 1.230000 + 3 370.000000 1.345000 + 4 322.000001 1.111000 + 5 319.999999 1.430000 + 6 440.000000 0.997000 + 7 222.500001 1.538000 + 8 330.000001 1.080000 + 9 230.000000 1.490000 + 10 309.000001 1.111000 + 11 305.000000 1.375000 + 12 340.000001 1.080000 + 13 334.300000 1.411000 + 14 545.000001 0.960000 + 15 222.500001 1.530000 + 16 198.000000 1.818000 + 17 239.999999 1.816000 + 18 450.000000 0.957200 + +Angle Coeffs + + 1 33.000000 109.500000 30.000000 2.163000 + 2 50.000000 120.000000 0.000000 0.000000 + 3 34.000000 123.000000 0.000000 0.000000 + 4 80.000000 121.000000 0.000000 0.000000 + 5 80.000000 116.500000 0.000000 0.000000 + 6 80.000000 122.500000 0.000000 0.000000 + 7 35.500000 108.400000 5.400000 1.802000 + 8 50.000000 107.000000 0.000000 0.000000 + 9 70.000000 113.500000 0.000000 0.000000 + 10 48.000000 108.000000 0.000000 0.000000 + 11 35.000000 117.000000 0.000000 0.000000 + 12 51.800000 107.500000 0.000000 0.000000 + 13 33.430000 110.100000 22.530000 2.179000 + 14 52.000000 108.000000 0.000000 0.000000 + 15 50.000000 109.500000 0.000000 0.000000 + 16 35.000000 111.000000 0.000000 0.000000 + 17 45.800000 122.300000 0.000000 0.000000 + 18 49.300000 107.500000 0.000000 0.000000 + 19 40.000000 120.000000 35.000000 2.416200 + 20 30.000000 120.000000 22.000000 2.152500 + 21 45.200000 120.000000 0.000000 0.000000 + 22 65.000000 108.000000 0.000000 0.000000 + 23 35.500000 109.000000 5.400000 1.802000 + 24 36.000000 115.000000 0.000000 0.000000 + 25 58.350000 113.500000 11.160000 2.561000 + 26 58.000000 114.500000 0.000000 0.000000 + 27 26.500000 110.100000 22.530000 2.179000 + 28 34.000000 95.000000 0.000000 0.000000 + 29 46.100000 111.300000 0.000000 0.000000 + 30 51.500000 109.500000 0.000000 0.000000 + 31 55.000000 104.520000 0.000000 0.000000 + +Dihedral Coeffs + + 1 0.200000 1 180 1.000000 + 2 1.800000 1 0 1.000000 + 3 0.000000 1 0 1.000000 + 4 1.600000 1 0 0.500000 + 5 2.500000 2 180 0.500000 + 6 2.500000 2 180 1.000000 + 7 0.600000 1 0 1.000000 + 8 0.200000 3 0 1.000000 + 9 0.230000 2 180 1.000000 + 10 0.040000 3 0 1.000000 + 11 1.400000 1 0 1.000000 + 12 3.100000 2 180 1.000000 + 13 4.200000 2 180 1.000000 + 14 3.100000 2 180 0.500000 + 15 0.990000 2 180 1.000000 + 16 2.400000 2 180 1.000000 + 17 0.195000 3 0 1.000000 + 18 0.240000 1 180 0.500000 + 19 0.370000 3 0 0.500000 + 20 0.280000 3 0 1.000000 + 21 0.010000 3 0 1.000000 + +Improper Coeffs + + 1 120.000000 0.000000 + 2 20.000000 0.000000 + +Atoms + + 1 1 1 0.510 43.99993 58.52678 36.78550 0 0 0 + 2 1 2 -0.270 45.10395 58.23499 35.86693 0 0 0 + 3 1 3 -0.510 43.81519 59.54928 37.43995 0 0 0 + 4 1 4 0.090 45.71714 57.34797 36.13434 0 0 0 + 5 1 4 0.090 45.72261 59.13657 35.67007 0 0 0 + 6 1 4 0.090 44.66624 58.09539 34.85538 0 0 0 + 7 1 5 -0.470 43.28193 57.47427 36.91953 0 0 0 + 8 1 6 0.070 42.07157 57.45486 37.62418 0 0 0 + 9 1 1 0.510 42.19985 57.57789 39.12163 0 0 0 + 10 1 3 -0.510 41.88641 58.62251 39.70398 0 0 0 + 11 1 7 -0.180 41.25052 56.15304 37.41811 0 0 0 + 12 1 8 0.000 40.88511 55.94638 35.97460 0 0 0 + 13 1 8 -0.115 41.48305 54.96372 35.11223 0 0 0 + 14 1 8 -0.115 39.74003 56.60996 35.46443 0 0 0 + 15 1 8 -0.115 41.02111 54.75715 33.80764 0 0 0 + 16 1 8 -0.115 39.26180 56.39194 34.12024 0 0 0 + 17 1 8 0.110 39.92330 55.46092 33.27135 0 0 0 + 18 1 9 -0.540 39.48164 55.22919 31.91865 0 0 0 + 19 1 10 0.310 43.60633 56.61693 36.52744 0 0 0 + 20 1 4 0.090 41.49619 58.31145 37.30543 0 0 0 + 21 1 4 0.090 41.88498 55.29476 37.72657 0 0 0 + 22 1 4 0.090 40.30899 56.19690 38.00627 0 0 0 + 23 1 11 0.115 42.31528 54.36176 35.44606 0 0 0 + 24 1 11 0.115 39.26330 57.31216 36.13230 0 0 0 + 25 1 11 0.115 41.62695 54.10606 33.19490 0 0 0 + 26 1 11 0.115 38.42147 56.98236 33.78612 0 0 0 + 27 1 10 0.430 38.78233 55.86217 31.74004 0 0 0 + 28 1 5 -0.470 42.79933 56.56370 39.79000 0 0 0 + 29 1 7 -0.020 42.96709 56.75379 41.28116 0 0 0 + 30 1 1 0.510 43.83019 55.68988 41.92255 0 0 0 + 31 1 3 -0.510 44.98521 55.93104 42.21713 0 0 0 + 32 1 10 0.310 43.13466 55.75696 39.30966 0 0 0 + 33 1 4 0.090 42.04692 56.86721 41.83507 0 0 0 + 34 1 4 0.090 43.52938 57.66324 41.43329 0 0 0 + 35 1 5 -0.470 43.26792 54.43342 42.07043 0 0 0 + 36 1 7 -0.020 43.92411 53.28930 42.63327 0 0 0 + 37 1 1 0.510 43.51012 53.02289 44.10510 0 0 0 + 38 1 3 -0.510 42.35086 53.07863 44.50806 0 0 0 + 39 1 10 0.310 42.28859 54.34993 41.90323 0 0 0 + 40 1 4 0.090 44.98464 53.47473 42.54797 0 0 0 + 41 1 4 0.090 43.49715 52.54787 41.97419 0 0 0 + 42 1 5 -0.470 44.51925 52.64535 44.88133 0 0 0 + 43 1 6 0.070 44.47588 52.35054 46.24397 0 0 0 + 44 1 1 0.510 45.40218 53.34579 46.94730 0 0 0 + 45 1 3 -0.510 45.23520 54.55893 46.92038 0 0 0 + 46 1 7 -0.180 44.77960 50.82831 46.50232 0 0 0 + 47 1 8 0.000 43.72184 49.84551 45.98093 0 0 0 + 48 1 8 -0.115 44.14810 49.00477 44.97195 0 0 0 + 49 1 8 -0.115 42.43499 49.66652 46.53541 0 0 0 + 50 1 8 -0.115 43.26154 48.00434 44.46769 0 0 0 + 51 1 8 -0.115 41.54732 48.79670 45.95416 0 0 0 + 52 1 8 -0.115 41.98220 47.90746 44.95574 0 0 0 + 53 1 10 0.310 45.39510 52.50937 44.42482 0 0 0 + 54 1 4 0.090 43.51312 52.58974 46.67092 0 0 0 + 55 1 4 0.090 44.89709 50.54313 47.56965 0 0 0 + 56 1 4 0.090 45.72096 50.49337 46.01654 0 0 0 + 57 1 11 0.115 45.13573 49.07933 44.54134 0 0 0 + 58 1 11 0.115 42.07869 50.34816 47.29358 0 0 0 + 59 1 11 0.115 43.47793 47.29281 43.68456 0 0 0 + 60 1 11 0.115 40.52625 48.76134 46.30425 0 0 0 + 61 1 11 0.115 41.35446 47.13287 44.54059 0 0 0 + 62 1 5 -0.470 46.41448 52.86278 47.68291 0 0 0 + 63 1 6 0.070 47.25136 53.68184 48.51163 0 0 0 + 64 1 1 0.510 48.33905 54.40097 47.73886 0 0 0 + 65 1 3 -0.510 49.27132 53.85220 47.16549 0 0 0 + 66 1 7 -0.180 47.88329 52.75681 49.60227 0 0 0 + 67 1 7 -0.140 48.82515 53.51102 50.61578 0 0 0 + 68 1 12 -0.090 48.12492 55.00373 51.43039 0 0 0 + 69 1 2 -0.220 47.70783 54.12980 53.04072 0 0 0 + 70 1 10 0.310 46.67199 51.90088 47.73231 0 0 0 + 71 1 4 0.090 46.64593 54.43552 48.99310 0 0 0 + 72 1 4 0.090 48.41361 51.90817 49.11968 0 0 0 + 73 1 4 0.090 47.08748 52.35196 50.26341 0 0 0 + 74 1 4 0.090 49.16067 52.81305 51.41238 0 0 0 + 75 1 4 0.090 49.73705 53.67062 50.00155 0 0 0 + 76 1 4 0.090 47.18593 54.84215 53.71488 0 0 0 + 77 1 4 0.090 48.69939 53.91624 53.49408 0 0 0 + 78 1 4 0.090 47.19749 53.18294 52.76264 0 0 0 + 79 1 5 -0.470 48.34472 55.71775 47.80498 0 0 0 + 80 1 2 -0.110 49.37792 56.51754 47.29492 0 0 0 + 81 1 10 0.310 47.51777 56.11617 48.19410 0 0 0 + 82 1 4 0.090 50.41495 56.13038 47.38980 0 0 0 + 83 1 4 0.090 49.23515 57.51193 47.76940 0 0 0 + 84 1 4 0.090 49.28612 56.52094 46.18773 0 0 0 + 85 2 13 -0.834 52.28049 45.72878 41.48140 -1 0 1 + 86 2 14 0.417 51.97210 46.07066 40.64218 -1 0 1 + 87 2 14 0.417 52.43689 44.79855 41.31868 -1 0 1 + 88 3 13 -0.834 43.84472 45.66062 47.17660 -2 -1 -1 + 89 3 14 0.417 43.42120 44.88337 46.81226 -2 -1 -1 + 90 3 14 0.417 44.31099 46.04907 46.43636 -2 -1 -1 + 91 4 13 -0.834 51.27805 50.25403 54.67397 0 0 -1 + 92 4 14 0.417 50.81295 50.23728 53.83753 0 0 -1 + 93 4 14 0.417 52.00273 49.63953 54.55795 0 0 -1 + 94 5 13 -0.834 44.71976 53.72011 56.43834 -1 0 -1 + 95 5 14 0.417 44.56050 53.84218 55.50241 -1 0 -1 + 96 5 14 0.417 44.91937 52.78829 56.52828 -1 0 -1 + 97 6 13 -0.834 37.07074 62.07204 53.35752 -1 -1 -1 + 98 6 14 0.417 64.17057 61.77089 52.49043 -2 -1 -1 + 99 6 14 0.417 37.90147 62.52273 53.20573 -1 -1 -1 + 100 7 13 -0.834 38.31817 66.10834 49.17406 0 -1 0 + 101 7 14 0.417 37.39300 65.93985 48.99534 0 -1 0 + 102 7 14 0.417 38.36506 66.20528 50.12520 0 -1 0 + 103 8 13 -0.834 60.90915 45.97690 35.53863 -1 -1 1 + 104 8 14 0.417 61.19898 46.87819 35.39745 -1 -1 1 + 105 8 14 0.417 59.98680 45.97855 35.28269 -1 -1 1 + 106 9 13 -0.834 54.33913 64.47210 51.00391 -1 -2 0 + 107 9 14 0.417 54.43191 63.71377 50.42724 -1 -2 0 + 108 9 14 0.417 55.16289 64.94980 50.90662 -1 -2 0 + 109 10 13 -0.834 44.58017 54.03749 53.84708 1 0 -1 + 110 10 14 0.417 43.87040 54.43768 53.34476 1 0 -1 + 111 10 14 0.417 45.02999 53.47261 53.21873 1 0 -1 + 112 11 13 -0.834 45.48693 52.12363 34.38241 0 -1 1 + 113 11 14 0.417 45.46898 52.67450 33.59981 0 -1 1 + 114 11 14 0.417 44.61476 52.22113 34.76457 0 -1 1 + 115 12 13 -0.834 60.15770 61.68799 54.74753 1 0 -2 + 116 12 14 0.417 59.23977 61.46439 54.59378 1 0 -2 + 117 12 14 0.417 60.43785 61.08922 55.43980 1 0 -2 + 118 13 13 -0.834 60.74732 66.72156 42.80906 1 -2 0 + 119 13 14 0.417 60.34713 66.21969 42.09898 1 -2 0 + 120 13 14 0.417 60.92444 66.07344 43.49082 1 -2 0 + 121 14 13 -0.834 60.82245 64.17281 50.54212 0 0 0 + 122 14 14 0.417 61.43571 64.88448 50.35863 0 0 0 + 123 14 14 0.417 60.87804 64.04633 51.48930 0 0 0 + 124 15 13 -0.834 36.92704 63.01353 56.05215 0 -1 0 + 125 15 14 0.417 37.10744 62.17054 56.46815 0 -1 0 + 126 15 14 0.417 64.06237 62.79109 55.15157 -1 -1 0 + 127 16 13 -0.834 48.35559 58.70568 56.14001 1 0 0 + 128 16 14 0.417 48.11655 59.48087 55.63191 1 0 0 + 129 16 14 0.417 47.93212 58.83502 56.98865 1 0 0 + 130 17 13 -0.834 58.14651 57.18542 51.08241 0 -1 -1 + 131 17 14 0.417 57.88523 56.72609 51.88052 0 -1 -1 + 132 17 14 0.417 57.35121 57.63116 50.79076 0 -1 -1 + 133 18 13 -0.834 58.09837 59.68005 36.16995 -1 0 0 + 134 18 14 0.417 58.25901 58.76822 36.41283 -1 0 0 + 135 18 14 0.417 58.56239 60.19049 36.83355 -1 0 0 + 136 19 13 -0.834 52.29019 60.51169 50.55611 0 -2 1 + 137 19 14 0.417 52.61972 60.01708 51.30645 0 -2 1 + 138 19 14 0.417 52.55621 59.99722 49.79401 0 -2 1 + 139 20 13 -0.834 41.36642 50.33705 42.98530 0 -1 -1 + 140 20 14 0.417 41.27846 50.09969 43.90844 0 -1 -1 + 141 20 14 0.417 40.99321 51.21659 42.92708 0 -1 -1 + 142 21 13 -0.834 53.76920 67.02645 32.18667 -1 0 1 + 143 21 14 0.417 53.59447 67.18509 31.25901 -1 0 1 + 144 21 14 0.417 54.65308 67.36647 32.32596 -1 0 1 + 145 22 13 -0.834 57.83691 45.33663 46.94671 0 0 -2 + 146 22 14 0.417 57.36287 45.59552 46.15647 0 0 -2 + 147 22 14 0.417 58.62995 44.91017 46.62197 0 0 -2 + 148 23 13 -0.834 60.34518 45.83000 45.57964 -1 0 0 + 149 23 14 0.417 60.61871 44.93757 45.79176 -1 0 0 + 150 23 14 0.417 61.09971 46.21212 45.13141 -1 0 0 + 151 24 13 -0.834 55.97902 46.85046 56.80163 0 1 1 + 152 24 14 0.417 56.57528 46.69952 30.16370 0 1 2 + 153 24 14 0.417 55.81156 47.79276 56.81850 0 1 1 + 154 25 13 -0.834 57.54668 45.52135 31.46139 -1 0 1 + 155 25 14 0.417 58.36291 46.00311 31.32743 -1 0 1 + 156 25 14 0.417 57.54151 45.31312 32.39566 -1 0 1 + 157 26 13 -0.834 58.03029 52.86783 46.33564 -1 -1 0 + 158 26 14 0.417 58.13662 52.56730 47.23820 -1 -1 0 + 159 26 14 0.417 58.81317 52.55269 45.88396 -1 -1 0 + 160 27 13 -0.834 62.89253 60.86549 46.75131 -2 -1 0 + 161 27 14 0.417 63.83924 60.74010 46.81653 -2 -1 0 + 162 27 14 0.417 62.51896 60.12788 47.23361 -2 -1 0 + 163 28 13 -0.834 43.29171 48.58106 31.82206 -1 0 2 + 164 28 14 0.417 43.07532 49.46362 32.12290 -1 0 2 + 165 28 14 0.417 43.82286 48.21072 32.52701 -1 0 2 + 166 29 13 -0.834 64.19867 44.17673 45.81391 -1 1 -1 + 167 29 14 0.417 63.72986 44.44010 45.02202 -1 1 -1 + 168 29 14 0.417 37.02069 43.24876 45.68087 0 1 -1 + 169 30 13 -0.834 50.42749 42.01163 53.60484 0 2 0 + 170 30 14 0.417 51.03177 41.90084 52.87081 0 2 0 + 171 30 14 0.417 50.77279 42.76181 54.08882 0 2 0 + 172 31 13 -0.834 38.63739 61.71113 49.95150 1 0 0 + 173 31 14 0.417 38.55432 62.15607 49.10808 1 0 0 + 174 31 14 0.417 37.81718 61.22751 50.04950 1 0 0 + 175 32 13 -0.834 61.47262 53.02922 33.08309 -1 -1 0 + 176 32 14 0.417 61.21894 52.67931 33.93717 -1 -1 0 + 177 32 14 0.417 61.89351 53.86564 33.28182 -1 -1 0 + 178 33 13 -0.834 54.44545 60.06011 48.63522 -1 0 1 + 179 33 14 0.417 54.80032 60.94424 48.72810 -1 0 1 + 180 33 14 0.417 54.09041 60.03614 47.74662 -1 0 1 + 181 34 13 -0.834 56.34364 60.90201 52.60838 -1 -1 0 + 182 34 14 0.417 56.48857 60.19161 53.23333 -1 -1 0 + 183 34 14 0.417 56.17362 61.67024 53.15351 -1 -1 0 + 184 35 13 -0.834 56.05881 51.84328 55.76103 -1 0 0 + 185 35 14 0.417 55.59060 51.75146 54.93121 -1 0 0 + 186 35 14 0.417 55.46974 52.35732 56.31335 -1 0 0 + 187 36 13 -0.834 39.00621 42.74743 30.97845 0 0 1 + 188 36 14 0.417 39.67620 42.11390 30.72152 0 0 1 + 189 36 14 0.417 39.43456 43.29673 31.63499 0 0 1 + 190 37 13 -0.834 46.77585 55.39774 30.24026 0 1 0 + 191 37 14 0.417 46.10274 54.90237 29.77360 0 1 0 + 192 37 14 0.417 46.39626 56.26890 30.35527 0 1 0 + 193 38 13 -0.834 45.10722 57.60431 31.54688 -1 0 0 + 194 38 14 0.417 44.80783 58.50032 31.70105 -1 0 0 + 195 38 14 0.417 44.44237 57.22463 30.97238 -1 0 0 + 196 39 13 -0.834 43.94230 46.99244 34.45668 -2 1 1 + 197 39 14 0.417 44.62010 46.49140 34.00306 -2 1 1 + 198 39 14 0.417 44.38150 47.79794 34.72964 -2 1 1 + 199 40 13 -0.834 51.39443 50.96507 34.69072 -1 1 0 + 200 40 14 0.417 51.18729 50.42829 35.45570 -1 1 0 + 201 40 14 0.417 51.33198 51.86665 35.00616 -1 1 0 + 202 41 13 -0.834 58.96398 48.19727 42.98856 -2 1 0 + 203 41 14 0.417 58.42587 48.90112 42.62618 -2 1 0 + 204 41 14 0.417 58.82383 48.25054 43.93397 -2 1 0 + 205 42 13 -0.834 62.89335 41.94260 37.40820 0 0 0 + 206 42 14 0.417 62.48690 41.07818 37.46980 0 0 0 + 207 42 14 0.417 63.01802 42.08284 36.46957 0 0 0 + 208 43 13 -0.834 54.19388 47.88689 36.24110 -1 0 1 + 209 43 14 0.417 54.32054 48.63090 35.65235 -1 0 1 + 210 43 14 0.417 53.24370 47.78935 36.30358 -1 0 1 + 211 44 13 -0.834 39.19734 57.40342 41.28495 0 0 -2 + 212 44 14 0.417 39.05428 57.72940 40.39641 0 0 -2 + 213 44 14 0.417 39.30846 56.45861 41.17895 0 0 -2 + 214 45 13 -0.834 52.85483 61.73749 54.63897 0 0 0 + 215 45 14 0.417 53.34938 62.52765 54.42147 0 0 0 + 216 45 14 0.417 53.01046 61.14656 53.90221 0 0 0 + 217 46 13 -0.834 47.09467 62.01384 35.02302 1 0 1 + 218 46 14 0.417 47.54527 61.47644 35.67448 1 0 1 + 219 46 14 0.417 47.10116 62.89626 35.39385 1 0 1 + 220 47 13 -0.834 46.80497 49.60334 37.05700 0 0 1 + 221 47 14 0.417 46.70216 49.79770 36.12540 0 0 1 + 222 47 14 0.417 45.91311 49.45393 37.37084 0 0 1 + 223 48 13 -0.834 63.21969 59.12311 54.43455 -1 -1 -1 + 224 48 14 0.417 63.94585 59.72833 54.28405 -1 -1 -1 + 225 48 14 0.417 63.63016 58.34481 54.81141 -1 -1 -1 + 226 49 13 -0.834 59.88416 59.64215 44.04914 -2 1 0 + 227 49 14 0.417 59.74255 59.14412 44.85422 -2 1 0 + 228 49 14 0.417 59.02635 60.01323 43.84248 -2 1 0 + 229 50 13 -0.834 40.50825 42.85328 50.81112 -1 1 0 + 230 50 14 0.417 40.34650 43.39801 51.58141 -1 1 0 + 231 50 14 0.417 39.63964 42.69867 50.43985 -1 1 0 + 232 51 13 -0.834 63.77522 64.97067 44.83010 -2 0 0 + 233 51 14 0.417 37.00507 65.56132 45.28388 -1 0 0 + 234 51 14 0.417 64.14243 64.88383 43.95041 -2 0 0 + 235 52 13 -0.834 62.47161 67.86189 47.38235 -1 0 -1 + 236 52 14 0.417 61.58819 67.64608 47.08360 -1 0 -1 + 237 52 14 0.417 62.79136 67.05596 47.78790 -1 0 -1 + 238 53 13 -0.834 43.90800 54.16107 50.35199 0 0 0 + 239 53 14 0.417 43.96769 53.24711 50.07388 0 0 0 + 240 53 14 0.417 43.72593 54.64554 49.54677 0 0 0 + 241 54 13 -0.834 63.46829 44.63390 34.73615 -1 1 1 + 242 54 14 0.417 62.63731 45.04623 34.97217 -1 1 1 + 243 54 14 0.417 64.11050 45.03645 35.32075 -1 1 1 + 244 55 13 -0.834 37.30679 58.22047 51.04345 0 0 0 + 245 55 14 0.417 38.18596 58.37862 50.69950 0 0 0 + 246 55 14 0.417 36.85723 59.06017 50.94824 0 0 0 + 247 56 13 -0.834 58.72649 42.45768 31.23820 -1 1 -1 + 248 56 14 0.417 59.43634 42.77561 30.68028 -1 1 -1 + 249 56 14 0.417 58.76581 41.50474 31.15690 -1 1 -1 + 250 57 13 -0.834 52.47101 42.85691 41.60986 0 1 -1 + 251 57 14 0.417 51.62289 42.91562 41.16997 0 1 -1 + 252 57 14 0.417 52.53109 41.94497 41.89448 0 1 -1 + 253 58 13 -0.834 60.63476 59.78356 56.53663 -2 -1 -1 + 254 58 14 0.417 60.87428 58.86269 56.43247 -2 -1 -1 + 255 58 14 0.417 59.72615 59.76269 56.83705 -2 -1 -1 + 256 59 13 -0.834 52.78127 57.47386 30.66786 -1 -1 0 + 257 59 14 0.417 52.55495 58.26092 30.17228 -1 -1 0 + 258 59 14 0.417 53.05203 56.84104 30.00267 -1 -1 0 + 259 60 13 -0.834 46.04848 57.65321 54.89998 0 3 -1 + 260 60 14 0.417 46.96883 57.71336 55.15607 0 3 -1 + 261 60 14 0.417 46.02768 57.98076 54.00081 0 3 -1 + 262 61 13 -0.834 60.39356 51.43705 35.66109 -1 1 -1 + 263 61 14 0.417 60.57739 52.08235 36.34376 -1 1 -1 + 264 61 14 0.417 59.59475 50.99860 35.95414 -1 1 -1 + 265 62 13 -0.834 50.32338 62.46972 35.65752 -1 0 2 + 266 62 14 0.417 51.24156 62.23287 35.52678 -1 0 2 + 267 62 14 0.417 49.89601 61.64851 35.90085 -1 0 2 + 268 63 13 -0.834 38.23983 45.11908 50.02773 0 1 0 + 269 63 14 0.417 38.61336 45.27494 50.89515 0 1 0 + 270 63 14 0.417 38.91224 45.42406 49.41856 0 1 0 + 271 64 13 -0.834 58.93720 57.36605 46.08362 -3 0 0 + 272 64 14 0.417 58.65753 56.63297 46.63190 -3 0 0 + 273 64 14 0.417 58.29914 58.05674 46.26268 -3 0 0 + 274 65 13 -0.834 47.99806 43.44789 47.43046 -1 0 0 + 275 65 14 0.417 48.39580 43.78289 46.62684 -1 0 0 + 276 65 14 0.417 47.85848 44.22523 47.97128 -1 0 0 + 277 66 13 -0.834 51.26744 52.05593 47.09995 -1 0 0 + 278 66 14 0.417 51.36736 52.09873 46.14894 -1 0 0 + 279 66 14 0.417 50.33779 52.22629 47.25149 -1 0 0 + 280 67 13 -0.834 39.06132 52.11517 46.39010 0 0 -1 + 281 67 14 0.417 38.53402 51.36282 46.65876 0 0 -1 + 282 67 14 0.417 39.47133 52.42190 47.19884 0 0 -1 + 283 68 13 -0.834 60.17907 58.95174 50.22759 -1 1 0 + 284 68 14 0.417 60.34080 59.56538 50.94420 -1 1 0 + 285 68 14 0.417 59.41497 58.44908 50.50992 -1 1 0 + 286 69 13 -0.834 40.47698 59.65154 34.92537 0 -1 1 + 287 69 14 0.417 40.89044 60.49055 35.12877 0 -1 1 + 288 69 14 0.417 41.17964 59.12336 34.54648 0 -1 1 + 289 70 13 -0.834 60.12998 66.51474 47.03971 -1 0 -1 + 290 70 14 0.417 59.26620 66.39701 47.43506 -1 0 -1 + 291 70 14 0.417 60.21358 65.78625 46.42443 -1 0 -1 + 292 71 13 -0.834 49.25986 47.27506 43.03372 -1 0 1 + 293 71 14 0.417 49.11810 48.15331 42.68041 -1 0 1 + 294 71 14 0.417 49.86162 47.40550 43.76662 -1 0 1 + 295 72 13 -0.834 41.48105 63.65699 31.84433 0 0 1 + 296 72 14 0.417 41.11022 64.48589 32.14713 0 0 1 + 297 72 14 0.417 40.89461 63.37379 31.14281 0 0 1 + 298 73 13 -0.834 47.82875 47.97039 54.56720 0 2 0 + 299 73 14 0.417 46.99167 47.50633 54.55352 0 2 0 + 300 73 14 0.417 47.60488 48.87558 54.35102 0 2 0 + 301 74 13 -0.834 62.36735 58.64445 48.35778 -2 1 0 + 302 74 14 0.417 62.88767 57.90867 48.68045 -2 1 0 + 303 74 14 0.417 61.65918 58.73544 48.99531 -2 1 0 + 304 75 13 -0.834 52.09508 65.08907 32.87560 0 0 0 + 305 75 14 0.417 52.67402 65.75058 32.49683 0 0 0 + 306 75 14 0.417 52.41855 64.97003 33.76859 0 0 0 + 307 76 13 -0.834 39.06932 41.62988 40.69498 1 1 0 + 308 76 14 0.417 39.51114 41.04433 40.08003 1 1 0 + 309 76 14 0.417 38.93584 42.43936 40.20186 1 1 0 + 310 77 13 -0.834 37.68325 49.50718 46.00750 0 2 0 + 311 77 14 0.417 64.11601 49.67107 45.91568 -1 2 0 + 312 77 14 0.417 37.90845 48.96991 45.24796 0 2 0 + 313 78 13 -0.834 53.00757 59.49351 52.98404 -2 1 -1 + 314 78 14 0.417 52.16721 59.28329 53.39127 -2 1 -1 + 315 78 14 0.417 53.61000 58.83023 53.32076 -2 1 -1 + 316 79 13 -0.834 51.89369 64.75001 56.68467 1 0 0 + 317 79 14 0.417 51.88079 65.63682 56.32462 1 0 0 + 318 79 14 0.417 52.40589 64.82531 30.11841 1 0 1 + 319 80 13 -0.834 48.43261 63.10155 32.63566 0 0 1 + 320 80 14 0.417 47.68021 63.01753 32.04993 0 0 1 + 321 80 14 0.417 48.13916 62.71424 33.46035 0 0 1 + 322 81 13 -0.834 62.41171 68.18251 30.67168 0 -1 2 + 323 81 14 0.417 61.79235 41.16145 30.03143 0 0 2 + 324 81 14 0.417 63.18314 67.94790 30.15584 0 -1 2 + 325 82 13 -0.834 42.57575 41.32197 37.66791 0 0 1 + 326 82 14 0.417 42.98116 41.36016 36.80164 0 0 1 + 327 82 14 0.417 42.32522 42.22654 37.85569 0 0 1 + 328 83 13 -0.834 50.17315 67.44398 36.91606 0 -2 0 + 329 83 14 0.417 50.08765 67.03449 37.77701 0 -2 0 + 330 83 14 0.417 50.35347 66.71621 36.32101 0 -2 0 + 331 84 13 -0.834 39.70163 60.45247 40.03790 0 -2 -1 + 332 84 14 0.417 38.85282 60.01540 40.10676 0 -2 -1 + 333 84 14 0.417 40.20579 60.11563 40.77858 0 -2 -1 + 334 85 13 -0.834 51.74323 42.80814 51.33239 0 0 -1 + 335 85 14 0.417 52.44810 43.22892 51.82466 0 0 -1 + 336 85 14 0.417 51.80961 43.17998 50.45286 0 0 -1 + 337 86 13 -0.834 51.34695 47.68316 36.38089 0 0 1 + 338 86 14 0.417 50.77701 46.92707 36.52138 0 0 1 + 339 86 14 0.417 51.27109 47.87031 35.44523 0 0 1 + 340 87 13 -0.834 62.66950 50.66085 43.15883 -2 0 0 + 341 87 14 0.417 63.57796 50.36318 43.11051 -2 0 0 + 342 87 14 0.417 62.24654 50.26548 42.39659 -2 0 0 + 343 88 13 -0.834 46.37996 60.13914 31.06428 -2 -1 1 + 344 88 14 0.417 46.89125 59.89673 31.83632 -2 -1 1 + 345 88 14 0.417 45.51811 60.37092 31.41028 -2 -1 1 + 346 89 13 -0.834 50.23251 41.17559 46.18435 0 1 2 + 347 89 14 0.417 49.40509 68.16142 45.89628 0 0 2 + 348 89 14 0.417 50.55747 67.94506 46.85395 0 0 2 + 349 90 13 -0.834 56.10446 66.70018 42.60390 0 -2 1 + 350 90 14 0.417 56.27454 67.42915 42.00732 0 -2 1 + 351 90 14 0.417 56.27819 67.05729 43.47483 0 -2 1 + 352 91 13 -0.834 55.53824 48.43866 51.97225 -1 0 1 + 353 91 14 0.417 56.26440 48.96682 52.30388 -1 0 1 + 354 91 14 0.417 55.26306 48.88494 51.17140 -1 0 1 + 355 92 13 -0.834 37.88016 52.62502 33.55552 0 -1 0 + 356 92 14 0.417 37.58757 51.72397 33.41859 0 -1 0 + 357 92 14 0.417 38.51960 52.77804 32.85986 0 -1 0 + 358 93 13 -0.834 50.40592 66.14455 39.40035 -1 -2 -1 + 359 93 14 0.417 49.74974 66.37168 40.05920 -1 -2 -1 + 360 93 14 0.417 50.22642 65.22843 39.18876 -1 -2 -1 + 361 94 13 -0.834 59.56315 43.63477 50.02876 -1 0 0 + 362 94 14 0.417 60.08533 44.36640 50.35782 -1 0 0 + 363 94 14 0.417 60.10101 42.86112 50.19730 -1 0 0 + 364 95 13 -0.834 57.16125 61.75981 55.17964 0 0 -1 + 365 95 14 0.417 56.45534 61.68609 55.82189 0 0 -1 + 366 95 14 0.417 57.38335 62.69087 55.17297 0 0 -1 + 367 96 13 -0.834 54.81274 43.48714 43.13392 -1 2 1 + 368 96 14 0.417 53.88771 43.40698 42.90124 -1 2 1 + 369 96 14 0.417 54.97915 42.74512 43.71525 -1 2 1 + 370 97 13 -0.834 41.23040 49.49766 49.75568 0 -2 0 + 371 97 14 0.417 40.54278 49.43865 49.09241 0 -2 0 + 372 97 14 0.417 41.81904 48.76959 49.55653 0 -2 0 + 373 98 13 -0.834 54.20957 45.39084 54.97428 -1 0 0 + 374 98 14 0.417 54.66721 46.06623 55.47493 -1 0 0 + 375 98 14 0.417 53.74016 44.87996 55.63374 -1 0 0 + 376 99 13 -0.834 61.27515 64.38553 39.98716 -1 0 1 + 377 99 14 0.417 61.56153 64.23410 40.88787 -1 0 1 + 378 99 14 0.417 60.44736 63.91029 39.91542 -1 0 1 + 379 100 13 -0.834 55.67284 58.14856 42.21767 -1 1 2 + 380 100 14 0.417 55.46369 57.24253 42.44485 -1 1 2 + 381 100 14 0.417 56.62771 58.19397 42.26677 -1 1 2 + 382 101 13 -0.834 43.66528 51.07118 53.71174 0 0 0 + 383 101 14 0.417 42.87715 50.89079 53.19934 0 0 0 + 384 101 14 0.417 43.37793 51.68815 54.38481 0 0 0 + 385 102 13 -0.834 39.90899 44.53973 36.42818 0 2 0 + 386 102 14 0.417 39.84006 43.65427 36.07118 0 2 0 + 387 102 14 0.417 40.52179 44.98683 35.84438 0 2 0 + 388 103 13 -0.834 51.24695 66.96031 48.71611 -1 -1 1 + 389 103 14 0.417 50.88275 67.26607 49.54684 -1 -1 1 + 390 103 14 0.417 52.19366 66.95318 48.85726 -1 -1 1 + 391 104 13 -0.834 55.15911 56.17347 57.08906 -1 0 0 + 392 104 14 0.417 55.86241 55.65189 56.70232 -1 0 0 + 393 104 14 0.417 54.93977 55.71619 30.52949 -1 0 1 + 394 105 13 -0.834 37.33282 54.30424 56.96734 0 0 0 + 395 105 14 0.417 64.15558 54.97773 29.99806 -1 0 1 + 396 105 14 0.417 64.13467 53.88397 56.32293 -1 0 0 + 397 106 13 -0.834 53.07827 51.20543 32.31512 -1 0 1 + 398 106 14 0.417 52.39494 50.78813 31.79057 -1 0 1 + 399 106 14 0.417 52.65819 51.38698 33.15584 -1 0 1 + 400 107 13 -0.834 43.06086 51.65229 35.75926 1 1 1 + 401 107 14 0.417 42.70958 52.01746 36.57135 1 1 1 + 402 107 14 0.417 43.42908 50.80682 36.01586 1 1 1 + 403 108 13 -0.834 53.92253 56.24460 34.48089 0 0 1 + 404 108 14 0.417 53.22007 56.39276 35.11401 0 0 1 + 405 108 14 0.417 54.59075 55.76600 34.97147 0 0 1 + 406 109 13 -0.834 61.71524 66.84153 38.60005 -1 -1 0 + 407 109 14 0.417 61.25397 66.04877 38.87388 -1 -1 0 + 408 109 14 0.417 62.23260 67.09437 39.36467 -1 -1 0 + 409 110 13 -0.834 43.52824 62.78695 41.49939 0 -1 -1 + 410 110 14 0.417 43.61050 61.97218 41.00379 0 -1 -1 + 411 110 14 0.417 43.53140 63.47437 40.83330 0 -1 -1 + 412 111 13 -0.834 51.13822 55.54090 53.50461 0 1 -2 + 413 111 14 0.417 50.69587 56.38179 53.62064 0 1 -2 + 414 111 14 0.417 51.43262 55.54828 52.59383 0 1 -2 + 415 112 13 -0.834 46.94709 50.11761 31.92599 0 0 0 + 416 112 14 0.417 47.19652 51.02564 31.75423 0 0 0 + 417 112 14 0.417 46.57462 49.81059 31.09941 0 0 0 + 418 113 13 -0.834 47.96666 45.13049 44.46108 -1 2 -1 + 419 113 14 0.417 47.01871 45.24108 44.53489 -1 2 -1 + 420 113 14 0.417 48.26343 45.91034 43.99202 -1 2 -1 + 421 114 13 -0.834 44.43868 43.44849 32.90814 -1 -1 1 + 422 114 14 0.417 43.86055 43.24165 33.64245 -1 -1 1 + 423 114 14 0.417 45.31670 43.24154 33.22828 -1 -1 1 + 424 115 13 -0.834 61.07172 47.80130 53.14504 -1 1 -1 + 425 115 14 0.417 61.34864 48.71600 53.19864 -1 1 -1 + 426 115 14 0.417 60.72118 47.60538 54.01394 -1 1 -1 + 427 116 13 -0.834 51.38727 44.10864 54.92855 -1 0 -1 + 428 116 14 0.417 50.77962 44.80360 55.18160 -1 0 -1 + 429 116 14 0.417 52.05111 44.10744 55.61815 -1 0 -1 + 430 117 13 -0.834 41.05585 60.12319 49.44785 1 -1 0 + 431 117 14 0.417 41.72702 60.76812 49.67116 1 -1 0 + 432 117 14 0.417 40.24373 60.62784 49.40265 1 -1 0 + 433 118 13 -0.834 50.88548 68.33364 33.37284 -1 0 -1 + 434 118 14 0.417 50.48275 67.46671 33.32310 -1 0 -1 + 435 118 14 0.417 51.82702 68.16119 33.37343 -1 0 -1 + 436 119 13 -0.834 38.79644 59.29061 55.22446 1 1 -1 + 437 119 14 0.417 38.82887 59.83550 56.01077 1 1 -1 + 438 119 14 0.417 39.26097 59.79985 54.56028 1 1 -1 + 439 120 13 -0.834 56.31813 41.68729 51.11871 -2 0 -1 + 440 120 14 0.417 55.45155 41.35580 51.35412 -2 0 -1 + 441 120 14 0.417 56.14879 42.34135 50.44062 -2 0 -1 + 442 121 13 -0.834 45.53697 59.28154 47.22033 -1 0 -1 + 443 121 14 0.417 45.45062 59.55577 46.30733 -1 0 -1 + 444 121 14 0.417 46.00774 59.99977 47.64313 -1 0 -1 + 445 122 13 -0.834 60.47636 43.28130 46.20944 -1 0 -1 + 446 122 14 0.417 60.97762 42.59184 45.77396 -1 0 -1 + 447 122 14 0.417 59.72992 42.82584 46.59884 -1 0 -1 + 448 123 13 -0.834 58.49080 48.18289 45.77215 0 0 -1 + 449 123 14 0.417 58.74342 47.25991 45.74879 0 0 -1 + 450 123 14 0.417 58.17926 48.32386 46.66621 0 0 -1 + 451 124 13 -0.834 50.93473 56.12663 41.58575 -1 0 0 + 452 124 14 0.417 50.36171 56.05214 42.34885 -1 0 0 + 453 124 14 0.417 50.40135 56.57242 40.92771 -1 0 0 + 454 125 13 -0.834 60.55008 41.95542 56.22749 -1 0 -1 + 455 125 14 0.417 59.65163 41.78987 55.94175 -1 0 -1 + 456 125 14 0.417 61.09463 41.59967 55.52524 -1 0 -1 + 457 126 13 -0.834 58.58373 51.69338 48.78985 -1 1 0 + 458 126 14 0.417 58.38773 52.01803 49.66874 -1 1 0 + 459 126 14 0.417 58.66973 50.74614 48.89756 -1 1 0 + 460 127 13 -0.834 37.82769 45.69808 30.85100 0 1 3 + 461 127 14 0.417 38.37007 45.10637 31.37248 0 1 3 + 462 127 14 0.417 37.14646 45.99401 31.45481 0 1 3 + 463 128 13 -0.834 50.96455 60.06361 33.68049 0 0 0 + 464 128 14 0.417 51.72055 60.15430 34.26055 0 0 0 + 465 128 14 0.417 51.05673 60.77997 33.05234 0 0 0 + 466 129 13 -0.834 46.43413 68.11245 51.48833 -1 0 -1 + 467 129 14 0.417 46.82151 41.36005 50.86943 -1 1 -1 + 468 129 14 0.417 47.09847 67.43153 51.59433 -1 0 -1 + 469 130 13 -0.834 61.79997 47.41648 57.05141 -1 -1 0 + 470 130 14 0.417 62.68713 47.23872 56.73898 -1 -1 0 + 471 130 14 0.417 61.48917 46.57417 30.01195 -1 -1 1 + 472 131 13 -0.834 45.30689 46.58119 54.43763 0 1 -1 + 473 131 14 0.417 45.67282 45.73922 54.70859 0 1 -1 + 474 131 14 0.417 44.46622 46.35973 54.03705 0 1 -1 + 475 132 13 -0.834 62.60829 48.56385 49.02640 -1 1 0 + 476 132 14 0.417 62.44761 48.65968 48.08766 -1 1 0 + 477 132 14 0.417 62.98242 47.68753 49.11762 -1 1 0 + 478 133 13 -0.834 63.49107 56.77075 38.74961 -1 0 2 + 479 133 14 0.417 63.12281 56.39554 39.54952 -1 0 2 + 480 133 14 0.417 62.84612 57.42058 38.47033 -1 0 2 + 481 134 13 -0.834 50.74846 48.34849 33.46075 0 0 1 + 482 134 14 0.417 50.75342 49.30521 33.43086 0 0 1 + 483 134 14 0.417 50.91203 48.07929 32.55686 0 0 1 + 484 135 13 -0.834 44.40923 67.37148 56.42156 0 0 0 + 485 135 14 0.417 43.93400 67.78902 29.76856 0 0 1 + 486 135 14 0.417 44.94884 66.70468 56.84633 0 0 0 + 487 136 13 -0.834 44.25343 64.95349 43.22104 0 0 0 + 488 136 14 0.417 44.13229 64.08173 42.84472 0 0 0 + 489 136 14 0.417 44.01188 65.55470 42.51643 0 0 0 + 490 137 13 -0.834 46.68300 67.52863 32.69859 -1 -1 0 + 491 137 14 0.417 46.68369 68.22637 33.35389 -1 -1 0 + 492 137 14 0.417 47.60248 67.43099 32.45106 -1 -1 0 + 493 138 13 -0.834 57.25376 61.01737 33.86507 -2 1 1 + 494 138 14 0.417 57.40827 60.52366 34.67043 -2 1 1 + 495 138 14 0.417 57.35792 60.37307 33.16488 -2 1 1 + 496 139 13 -0.834 57.39946 54.16835 56.70699 0 -1 -1 + 497 139 14 0.417 57.31939 53.23092 56.53080 0 -1 -1 + 498 139 14 0.417 57.32300 54.24112 30.28699 0 -1 0 + 499 140 13 -0.834 52.36697 48.69246 41.49227 -1 1 0 + 500 140 14 0.417 51.78735 47.93629 41.40021 -1 1 0 + 501 140 14 0.417 53.21603 48.31702 41.72547 -1 1 0 + 502 141 13 -0.834 54.69200 49.57915 45.55048 0 0 -1 + 503 141 14 0.417 54.95958 48.66911 45.42211 0 0 -1 + 504 141 14 0.417 55.28513 50.08439 44.99446 0 0 -1 + 505 142 13 -0.834 37.26724 53.17896 42.50469 1 -1 -1 + 506 142 14 0.417 63.93194 53.34801 43.12782 0 -1 -1 + 507 142 14 0.417 36.94831 52.45044 41.97199 1 -1 -1 + 508 143 13 -0.834 42.56283 66.92379 33.49577 -1 0 1 + 509 143 14 0.417 41.71356 66.58931 33.20750 -1 0 1 + 510 143 14 0.417 43.03645 66.14842 33.79697 -1 0 1 + 511 144 13 -0.834 61.43331 45.62855 38.97695 0 1 1 + 512 144 14 0.417 61.20190 45.98514 39.83458 0 1 1 + 513 144 14 0.417 62.31351 45.96414 38.80708 0 1 1 + 514 145 13 -0.834 49.37935 56.26031 56.72879 1 1 0 + 515 145 14 0.417 49.03977 57.11146 56.45221 1 1 0 + 516 145 14 0.417 48.60052 55.75658 56.96530 1 1 0 + 517 146 13 -0.834 63.13959 56.23999 49.92079 -1 0 -1 + 518 146 14 0.417 63.72474 55.58123 50.29478 -1 0 -1 + 519 146 14 0.417 63.40966 57.06154 50.33112 -1 0 -1 + 520 147 13 -0.834 58.55937 66.56287 54.17345 -1 0 0 + 521 147 14 0.417 59.28260 66.81524 53.59945 -1 0 0 + 522 147 14 0.417 58.28559 67.38088 54.58834 -1 0 0 + 523 148 13 -0.834 55.49901 62.14366 46.01274 -1 0 -1 + 524 148 14 0.417 55.08057 61.57956 45.36238 -1 0 -1 + 525 148 14 0.417 55.53371 63.00495 45.59652 -1 0 -1 + 526 149 13 -0.834 48.09589 47.38106 38.97384 0 1 0 + 527 149 14 0.417 47.94178 48.02346 38.28116 0 1 0 + 528 149 14 0.417 47.26125 47.32494 39.43910 0 1 0 + 529 150 13 -0.834 40.27661 53.03711 48.83757 0 0 0 + 530 150 14 0.417 40.32476 53.91333 49.21992 0 0 0 + 531 150 14 0.417 41.18363 52.81848 48.62365 0 0 0 + 532 151 13 -0.834 36.85277 41.68065 44.81488 1 2 0 + 533 151 14 0.417 36.95709 68.34807 45.45504 1 1 0 + 534 151 14 0.417 37.14062 41.29651 43.98673 1 2 0 + 535 152 13 -0.834 37.74881 65.81650 33.58759 -1 0 1 + 536 152 14 0.417 37.69052 65.99217 34.52673 -1 0 1 + 537 152 14 0.417 37.02193 65.21970 33.40951 -1 0 1 + 538 153 13 -0.834 63.01838 46.13766 43.99274 -2 0 0 + 539 153 14 0.417 62.72780 46.33504 43.10232 -2 0 0 + 540 153 14 0.417 63.75125 46.73459 44.14387 -2 0 0 + 541 154 13 -0.834 43.83288 53.92104 38.64974 0 2 1 + 542 154 14 0.417 44.46072 53.30394 39.02556 0 2 1 + 543 154 14 0.417 44.17373 54.10726 37.77488 0 2 1 + 544 155 13 -0.834 54.48021 41.30441 45.39416 1 1 -2 + 545 155 14 0.417 54.42996 67.86451 44.88861 1 0 -2 + 546 155 14 0.417 54.84291 41.03852 46.23914 1 1 -2 + 547 156 13 -0.834 51.26407 63.10699 50.73012 0 0 -2 + 548 156 14 0.417 51.64016 62.23294 50.83411 0 0 -2 + 549 156 14 0.417 51.56733 63.39797 49.87011 0 0 -2 + 550 157 13 -0.834 54.61161 63.67709 53.56970 0 1 1 + 551 157 14 0.417 55.55339 63.81655 53.47054 0 1 1 + 552 157 14 0.417 54.24805 63.87070 52.70565 0 1 1 + 553 158 13 -0.834 46.57444 42.69363 30.13287 -1 0 1 + 554 158 14 0.417 45.93025 42.28051 30.70783 -1 0 1 + 555 158 14 0.417 47.27305 42.04459 30.04973 -1 0 1 + 556 159 13 -0.834 37.92811 50.36816 42.31352 1 1 0 + 557 159 14 0.417 38.62401 50.90050 42.69899 1 1 0 + 558 159 14 0.417 38.11553 50.37135 41.37484 1 1 0 + 559 160 13 -0.834 40.53318 48.69302 33.52502 -1 0 0 + 560 160 14 0.417 40.10720 48.55075 32.67972 -1 0 0 + 561 160 14 0.417 41.22323 49.33057 33.34173 -1 0 0 + 562 161 13 -0.834 58.20095 45.48345 42.83426 1 0 -1 + 563 161 14 0.417 58.76156 46.25356 42.92849 1 0 -1 + 564 161 14 0.417 58.80813 44.74348 42.83158 1 0 -1 + 565 162 13 -0.834 59.85909 67.06752 31.43173 -1 1 0 + 566 162 14 0.417 59.95062 66.12180 31.54782 -1 1 0 + 567 162 14 0.417 60.75672 67.38534 31.33437 -1 1 0 + 568 163 13 -0.834 48.48808 51.17807 55.92072 -2 0 0 + 569 163 14 0.417 49.24951 51.62602 55.55219 -2 0 0 + 570 163 14 0.417 48.81105 50.30745 56.15303 -2 0 0 + 571 164 13 -0.834 47.51169 45.69616 48.99410 0 0 -1 + 572 164 14 0.417 48.36822 46.03425 48.73281 0 0 -1 + 573 164 14 0.417 47.56201 45.62598 49.94740 0 0 -1 + 574 165 13 -0.834 51.10678 64.23082 47.99167 0 -2 -1 + 575 165 14 0.417 51.33188 65.16116 47.98611 0 -2 -1 + 576 165 14 0.417 50.15837 64.21415 48.12002 0 -2 -1 + 577 166 13 -0.834 42.97263 56.29674 30.18230 0 0 0 + 578 166 14 0.417 42.45756 55.50818 30.01170 0 0 0 + 579 166 14 0.417 42.79675 56.86516 56.80386 0 0 -1 + 580 167 13 -0.834 44.45917 53.64338 31.85015 -1 0 0 + 581 167 14 0.417 44.64093 54.17218 31.07325 -1 0 0 + 582 167 14 0.417 43.66299 53.15965 31.63030 -1 0 0 + 583 168 13 -0.834 52.20677 49.92062 48.65330 1 0 0 + 584 168 14 0.417 52.24176 50.63538 49.28902 1 0 0 + 585 168 14 0.417 52.01918 50.35058 47.81890 1 0 0 + 586 169 13 -0.834 45.94013 51.43638 56.49888 0 0 0 + 587 169 14 0.417 46.89200 51.34153 56.53372 0 0 0 + 588 169 14 0.417 45.60504 50.66051 56.94833 0 0 0 + 589 170 13 -0.834 45.61845 41.38709 48.05698 1 0 0 + 590 170 14 0.417 46.42604 41.83441 47.80406 1 0 0 + 591 170 14 0.417 45.31743 41.85685 48.83477 1 0 0 + 592 171 13 -0.834 47.68232 42.84819 52.92728 0 1 0 + 593 171 14 0.417 47.61830 42.41414 52.07654 0 1 0 + 594 171 14 0.417 48.39202 42.39011 53.37758 0 1 0 + 595 172 13 -0.834 37.01774 65.84057 36.39542 1 -1 0 + 596 172 14 0.417 36.84918 65.13561 37.02061 1 -1 0 + 597 172 14 0.417 63.52368 66.19949 36.19938 0 -1 0 + 598 173 13 -0.834 51.52891 58.65207 39.31760 -1 -3 -1 + 599 173 14 0.417 51.57384 59.35596 39.96472 -1 -3 -1 + 600 173 14 0.417 51.00435 59.01522 38.60403 -1 -3 -1 + 601 174 13 -0.834 49.06578 54.25781 44.33488 0 -1 -1 + 602 174 14 0.417 48.81980 55.18018 44.26437 0 -1 -1 + 603 174 14 0.417 49.41695 54.17018 45.22104 0 -1 -1 + 604 175 13 -0.834 47.03819 42.38557 34.31948 -1 -1 0 + 605 175 14 0.417 47.39035 41.82883 35.01393 -1 -1 0 + 606 175 14 0.417 47.47024 43.23019 34.44673 -1 -1 0 + 607 176 13 -0.834 41.64025 43.65472 38.33192 0 1 0 + 608 176 14 0.417 41.17224 44.02383 37.58295 0 1 0 + 609 176 14 0.417 41.46027 44.26142 39.05008 0 1 0 + 610 177 13 -0.834 61.41261 58.14241 37.49312 -2 0 0 + 611 177 14 0.417 61.24368 59.06676 37.67551 -2 0 0 + 612 177 14 0.417 60.57871 57.80631 37.16465 -2 0 0 + 613 178 13 -0.834 48.58355 55.60536 32.34542 0 -2 -2 + 614 178 14 0.417 48.05292 55.64371 31.54969 0 -2 -2 + 615 178 14 0.417 49.00004 56.46561 32.39784 0 -2 -2 + 616 179 13 -0.834 51.18618 52.33768 44.26866 0 -1 0 + 617 179 14 0.417 50.47419 52.97535 44.21659 0 -1 0 + 618 179 14 0.417 51.18053 51.90159 43.41657 0 -1 0 + 619 180 13 -0.834 63.77008 46.64985 53.45124 -2 0 -1 + 620 180 14 0.417 37.25943 46.94040 53.14955 -1 0 -1 + 621 180 14 0.417 63.15834 47.28506 53.07904 -2 0 -1 + 622 181 13 -0.834 37.28071 56.79400 31.30862 1 1 0 + 623 181 14 0.417 37.34297 57.68998 31.63963 1 1 0 + 624 181 14 0.417 36.99543 56.89301 30.40030 1 1 0 + 625 182 13 -0.834 38.98742 57.66608 44.07685 1 0 1 + 626 182 14 0.417 39.04152 57.61214 43.12270 1 0 1 + 627 182 14 0.417 39.46043 56.89430 44.38805 1 0 1 + 628 183 13 -0.834 64.13749 51.25767 48.28997 0 -1 0 + 629 183 14 0.417 64.05120 52.19840 48.13566 0 -1 0 + 630 183 14 0.417 63.26932 50.90255 48.09918 0 -1 0 + 631 184 13 -0.834 41.02949 42.14202 43.02064 0 0 -1 + 632 184 14 0.417 40.60130 42.82178 43.54104 0 0 -1 + 633 184 14 0.417 40.43829 41.99723 42.28189 0 0 -1 + 634 185 13 -0.834 49.87332 48.21836 52.83028 0 1 0 + 635 185 14 0.417 49.13733 48.15035 53.43849 0 1 0 + 636 185 14 0.417 50.32176 47.37567 52.90100 0 1 0 + 637 186 13 -0.834 56.06860 48.51217 38.12813 -1 1 0 + 638 186 14 0.417 56.55702 47.73454 38.39826 -1 1 0 + 639 186 14 0.417 55.52690 48.21357 37.39762 -1 1 0 + 640 187 13 -0.834 54.22718 59.47740 40.22374 -1 0 1 + 641 187 14 0.417 53.93839 59.03820 39.42377 -1 0 1 + 642 187 14 0.417 54.74005 58.81629 40.68868 -1 0 1 + 643 188 13 -0.834 60.09461 46.88146 32.04739 -1 0 -1 + 644 188 14 0.417 60.91535 46.43611 31.83683 -1 0 -1 + 645 188 14 0.417 60.13630 47.02716 32.99253 -1 0 -1 + 646 189 13 -0.834 45.18646 44.57845 41.54076 0 0 0 + 647 189 14 0.417 44.28239 44.89208 41.51774 0 0 0 + 648 189 14 0.417 45.34481 44.23786 40.66033 0 0 0 + 649 190 13 -0.834 42.47099 45.68692 31.56356 1 0 1 + 650 190 14 0.417 43.26152 45.18821 31.76995 1 0 1 + 651 190 14 0.417 42.78187 46.58070 31.41951 1 0 1 + 652 191 13 -0.834 41.23413 47.67043 41.85221 0 1 0 + 653 191 14 0.417 41.04508 48.58329 42.06946 0 1 0 + 654 191 14 0.417 40.84394 47.54379 40.98737 0 1 0 + 655 192 13 -0.834 48.84750 60.39708 36.57115 0 0 0 + 656 192 14 0.417 48.57626 59.48478 36.46920 0 0 0 + 657 192 14 0.417 48.59448 60.62409 37.46597 0 0 0 + 658 193 13 -0.834 56.78263 43.55464 49.12966 -1 0 -1 + 659 193 14 0.417 56.56851 44.25428 48.51250 -1 0 -1 + 660 193 14 0.417 57.66563 43.76469 49.43365 -1 0 -1 + 661 194 13 -0.834 59.52236 53.66894 43.24587 -1 2 0 + 662 194 14 0.417 59.44365 54.61174 43.10041 -1 2 0 + 663 194 14 0.417 59.73284 53.58637 44.17598 -1 2 0 + 664 195 13 -0.834 63.61393 61.54696 40.57053 -1 -1 1 + 665 195 14 0.417 36.90989 60.94398 40.24291 0 -1 1 + 666 195 14 0.417 63.74510 61.55794 41.51864 -1 -1 1 + 667 196 13 -0.834 54.91742 43.16160 33.69639 0 0 -1 + 668 196 14 0.417 55.84062 43.16106 33.94925 0 0 -1 + 669 196 14 0.417 54.73416 44.07060 33.45898 0 0 -1 + 670 197 13 -0.834 41.09699 64.92982 48.38401 0 -1 -1 + 671 197 14 0.417 40.19042 64.83711 48.67687 0 -1 -1 + 672 197 14 0.417 41.27055 64.13206 47.88433 0 -1 -1 + 673 198 13 -0.834 49.09688 60.43369 49.80048 0 0 -1 + 674 198 14 0.417 49.75346 61.03633 50.14971 0 0 -1 + 675 198 14 0.417 49.51718 59.57440 49.83534 0 0 -1 + 676 199 13 -0.834 45.06873 45.25146 44.50830 0 1 0 + 677 199 14 0.417 45.08807 45.11881 43.56053 0 1 0 + 678 199 14 0.417 44.41198 44.63084 44.82413 0 1 0 + 679 200 13 -0.834 37.63886 45.88962 36.45768 0 0 2 + 680 200 14 0.417 38.32892 45.23766 36.58017 0 0 2 + 681 200 14 0.417 37.24627 45.98938 37.32495 0 0 2 + 682 201 13 -0.834 45.25770 47.01692 51.04211 -1 0 -2 + 683 201 14 0.417 45.49830 47.82868 50.59555 -1 0 -2 + 684 201 14 0.417 46.08295 46.68269 51.39354 -1 0 -2 + 685 202 13 -0.834 63.44567 60.77839 50.98507 -2 0 0 + 686 202 14 0.417 62.95029 60.46072 51.74001 -2 0 0 + 687 202 14 0.417 62.77774 61.08133 50.36998 -2 0 0 + 688 203 13 -0.834 48.00038 59.99003 33.31045 0 1 1 + 689 203 14 0.417 48.92391 59.89924 33.54518 0 1 1 + 690 203 14 0.417 47.68314 60.70831 33.85788 0 1 1 + 691 204 13 -0.834 51.29617 53.45952 36.10138 -1 -1 1 + 692 204 14 0.417 50.79623 53.20605 36.87731 -1 -1 1 + 693 204 14 0.417 51.41983 54.40421 36.19363 -1 -1 1 + 694 205 13 -0.834 48.55343 45.13540 34.47517 0 0 0 + 695 205 14 0.417 48.10547 45.97105 34.34382 0 0 0 + 696 205 14 0.417 49.13373 45.28879 35.22081 0 0 0 + 697 206 13 -0.834 48.34844 61.02741 54.77908 1 -1 -1 + 698 206 14 0.417 47.77364 61.75290 55.02301 1 -1 -1 + 699 206 14 0.417 49.14675 61.17253 55.28690 1 -1 -1 + 700 207 13 -0.834 38.97661 48.73541 31.27301 2 -1 0 + 701 207 14 0.417 38.86774 47.99634 30.67453 2 -1 0 + 702 207 14 0.417 38.60214 49.48112 30.80404 2 -1 0 + 703 208 13 -0.834 56.37687 61.69299 40.12439 0 -1 -1 + 704 208 14 0.417 56.35009 61.71409 39.16778 0 -1 -1 + 705 208 14 0.417 55.62486 61.15580 40.37371 0 -1 -1 + 706 209 13 -0.834 47.86700 41.38854 36.76722 -1 0 0 + 707 209 14 0.417 48.79854 41.26117 36.94678 -1 0 0 + 708 209 14 0.417 47.57553 42.00602 37.43804 -1 0 0 + 709 210 13 -0.834 43.22089 60.92576 39.48904 -1 -1 0 + 710 210 14 0.417 42.70029 60.20976 39.85311 -1 -1 0 + 711 210 14 0.417 43.25319 60.74538 38.54954 -1 -1 0 + 712 211 13 -0.834 56.26248 49.03317 34.29585 -1 0 0 + 713 211 14 0.417 56.69244 49.86416 34.09381 -1 0 0 + 714 211 14 0.417 55.61194 48.92467 33.60212 -1 0 0 + 715 212 13 -0.834 47.52063 49.37901 51.21673 1 0 0 + 716 212 14 0.417 48.35964 48.95385 51.03909 1 0 0 + 717 212 14 0.417 47.47856 49.43746 52.17122 1 0 0 + 718 213 13 -0.834 62.35532 56.31018 41.33556 0 0 0 + 719 213 14 0.417 62.07506 57.22150 41.42032 0 0 0 + 720 213 14 0.417 62.92184 56.16192 42.09274 0 0 0 + 721 214 13 -0.834 61.09797 64.53756 45.11003 -1 0 1 + 722 214 14 0.417 61.11801 63.59600 44.93887 -1 0 1 + 723 214 14 0.417 61.95676 64.85132 44.82670 -1 0 1 + 724 215 13 -0.834 51.22661 62.08872 31.93454 0 0 0 + 725 215 14 0.417 51.98994 62.65586 32.04369 0 0 0 + 726 215 14 0.417 50.47877 62.65171 32.13456 0 0 0 + 727 216 13 -0.834 40.65443 48.64853 54.43476 0 0 -1 + 728 216 14 0.417 40.25608 47.97845 54.99023 0 0 -1 + 729 216 14 0.417 41.58025 48.64240 54.67776 0 0 -1 + 730 217 13 -0.834 39.34873 63.07587 52.07209 1 1 -1 + 731 217 14 0.417 39.17266 63.98076 51.81438 1 1 -1 + 732 217 14 0.417 39.29792 62.57948 51.25523 1 1 -1 + 733 218 13 -0.834 45.66307 65.90840 47.75613 -1 0 0 + 734 218 14 0.417 44.99427 65.52542 48.32381 -1 0 0 + 735 218 14 0.417 45.75913 66.80721 48.07102 -1 0 0 + 736 219 13 -0.834 45.83158 51.91442 38.93974 0 0 0 + 737 219 14 0.417 46.07939 51.87422 39.86344 0 0 0 + 738 219 14 0.417 45.49928 51.03877 38.74210 0 0 0 + 739 220 13 -0.834 58.03934 67.88594 44.36036 -1 1 -1 + 740 220 14 0.417 58.69084 68.22520 43.74661 -1 1 -1 + 741 220 14 0.417 58.24719 68.31309 45.19138 -1 1 -1 + 742 221 13 -0.834 57.23319 66.95459 30.42832 0 0 0 + 743 221 14 0.417 56.95316 66.93560 31.34345 0 0 0 + 744 221 14 0.417 58.18154 66.82998 30.46491 0 0 0 + 745 222 13 -0.834 60.87005 44.72970 53.74755 -1 0 -1 + 746 222 14 0.417 60.02694 44.42275 53.41412 -1 0 -1 + 747 222 14 0.417 61.31963 45.07903 52.97808 -1 0 -1 + 748 223 13 -0.834 50.61352 50.44308 31.66369 0 -1 0 + 749 223 14 0.417 50.38691 49.95555 30.87173 0 -1 0 + 750 223 14 0.417 50.16704 51.28387 31.56391 0 -1 0 + 751 224 13 -0.834 42.70363 42.07925 34.73823 0 1 0 + 752 224 14 0.417 42.74630 41.15512 34.49249 0 1 0 + 753 224 14 0.417 41.77538 42.23983 34.90796 0 1 0 + 754 225 13 -0.834 50.34157 43.80796 44.49841 -1 1 0 + 755 225 14 0.417 49.44649 44.14718 44.50119 -1 1 0 + 756 225 14 0.417 50.24323 42.86994 44.66171 -1 1 0 + 757 226 13 -0.834 62.39528 64.92163 33.72829 -3 -1 1 + 758 226 14 0.417 61.94679 64.42233 34.41078 -3 -1 1 + 759 226 14 0.417 61.94061 64.68505 32.91986 -3 -1 1 + 760 227 13 -0.834 46.62188 47.13429 41.79430 0 1 1 + 761 227 14 0.417 46.21721 46.28415 41.62178 0 1 1 + 762 227 14 0.417 47.40198 46.92861 42.30946 0 1 1 + 763 228 13 -0.834 41.35469 54.31275 56.45453 0 0 -1 + 764 228 14 0.417 41.79769 53.47653 56.31055 0 0 -1 + 765 228 14 0.417 40.57273 54.26794 55.90425 0 0 -1 + 766 229 13 -0.834 48.43878 42.20000 49.94999 0 0 0 + 767 229 14 0.417 49.34431 42.29756 50.24447 0 0 0 + 768 229 14 0.417 48.41583 42.63350 49.09688 0 0 0 + 769 230 13 -0.834 37.29829 50.04209 33.34795 0 1 0 + 770 230 14 0.417 36.96213 49.51969 34.07619 0 1 0 + 771 230 14 0.417 37.98470 49.49933 32.96002 0 1 0 + 772 231 13 -0.834 58.91995 56.17895 33.02333 -1 0 0 + 773 231 14 0.417 59.83980 56.43785 32.96791 -1 0 0 + 774 231 14 0.417 58.89269 55.54120 33.73661 -1 0 0 + 775 232 13 -0.834 39.86900 65.81481 43.81866 0 0 -1 + 776 232 14 0.417 40.31483 64.99515 43.60502 0 0 -1 + 777 232 14 0.417 40.41298 66.21397 44.49762 0 0 -1 + 778 233 13 -0.834 62.71324 65.93556 51.55400 -1 0 0 + 779 233 14 0.417 62.38032 66.39597 52.32436 -1 0 0 + 780 233 14 0.417 63.52336 65.52245 51.85285 -1 0 0 + 781 234 13 -0.834 59.23324 49.58642 31.35843 0 0 0 + 782 234 14 0.417 59.28102 48.68976 31.69001 0 0 0 + 783 234 14 0.417 59.95115 50.04304 31.79700 0 0 0 + 784 235 13 -0.834 41.02310 67.21389 51.60243 0 0 0 + 785 235 14 0.417 41.77450 67.79064 51.74021 0 0 0 + 786 235 14 0.417 40.36922 67.76899 51.17753 0 0 0 + 787 236 13 -0.834 41.38918 62.43794 34.42449 0 0 1 + 788 236 14 0.417 41.26665 63.14612 33.79227 0 0 1 + 789 236 14 0.417 42.30454 62.51275 34.69423 0 0 1 + 790 237 13 -0.834 52.28796 56.01034 50.59905 0 -1 -1 + 791 237 14 0.417 53.14113 56.07317 51.02851 0 -1 -1 + 792 237 14 0.417 52.14509 55.07070 50.48548 0 -1 -1 + 793 238 13 -0.834 53.25204 66.52198 39.76351 0 -1 0 + 794 238 14 0.417 52.30774 66.44732 39.62571 0 -1 0 + 795 238 14 0.417 53.47725 67.38617 39.41895 0 -1 0 + 796 239 13 -0.834 59.77604 60.82055 48.12264 -1 -1 -1 + 797 239 14 0.417 59.80699 60.05926 48.70205 -1 -1 -1 + 798 239 14 0.417 58.96049 60.71611 47.63253 -1 -1 -1 + 799 240 13 -0.834 48.99693 51.07559 36.89084 0 -1 1 + 800 240 14 0.417 48.22315 50.55308 37.10175 0 -1 1 + 801 240 14 0.417 48.88824 51.30348 35.96753 0 -1 1 + 802 241 13 -0.834 50.67863 62.63916 55.60559 1 0 -2 + 803 241 14 0.417 51.43406 62.16856 55.25331 1 0 -2 + 804 241 14 0.417 51.05760 63.36945 56.09477 1 0 -2 + 805 242 13 -0.834 41.05301 64.77947 55.72335 1 -1 -1 + 806 242 14 0.417 41.95836 64.58666 55.96711 1 -1 -1 + 807 242 14 0.417 41.07998 65.67647 55.39035 1 -1 -1 + 808 243 13 -0.834 59.16096 63.30207 34.55147 0 -1 2 + 809 243 14 0.417 58.62636 62.51316 34.64131 0 -1 2 + 810 243 14 0.417 59.80830 63.23451 35.25333 0 -1 2 + 811 244 13 -0.834 59.86542 53.52546 55.50419 0 -1 -1 + 812 244 14 0.417 60.26921 53.79963 56.32761 0 -1 -1 + 813 244 14 0.417 58.96256 53.83773 55.56399 0 -1 -1 + 814 245 13 -0.834 56.48528 44.99075 44.65443 1 0 0 + 815 245 14 0.417 55.84854 44.49932 44.13551 1 0 0 + 816 245 14 0.417 57.18258 45.20803 44.03571 1 0 0 + 817 246 13 -0.834 37.25407 54.85866 36.86076 0 -1 -1 + 818 246 14 0.417 37.37951 55.31820 36.03050 0 -1 -1 + 819 246 14 0.417 36.91899 55.52805 37.45731 0 -1 -1 + 820 247 13 -0.834 54.42875 47.21339 48.23883 -1 -1 -1 + 821 247 14 0.417 54.60966 48.13349 48.43097 -1 -1 -1 + 822 247 14 0.417 54.44092 47.16092 47.28312 -1 -1 -1 + 823 248 13 -0.834 42.61226 41.78391 40.84493 1 0 1 + 824 248 14 0.417 41.98531 41.90233 41.55849 1 0 1 + 825 248 14 0.417 42.35866 42.43623 40.19194 1 0 1 + 826 249 13 -0.834 37.83522 41.95649 50.31377 0 0 -2 + 827 249 14 0.417 37.42231 42.81133 50.19124 0 0 -2 + 828 249 14 0.417 37.46684 41.41031 49.61934 0 0 -2 + 829 250 13 -0.834 44.80898 44.15062 49.20688 0 -1 0 + 830 250 14 0.417 44.80289 44.55594 48.33975 0 -1 0 + 831 250 14 0.417 45.29722 44.76463 49.75537 0 -1 0 + 832 251 13 -0.834 37.44321 44.03405 38.75076 1 0 1 + 833 251 14 0.417 37.12277 44.06014 39.65235 1 0 1 + 834 251 14 0.417 64.13547 43.56266 38.26824 0 0 1 + 835 252 13 -0.834 38.82113 46.15070 46.12915 1 0 0 + 836 252 14 0.417 38.96657 46.44867 47.02709 1 0 0 + 837 252 14 0.417 38.09796 45.52731 46.19733 1 0 0 + 838 253 13 -0.834 43.08482 60.65520 45.34135 -1 0 1 + 839 253 14 0.417 42.82882 59.73347 45.30784 -1 0 1 + 840 253 14 0.417 44.00885 60.65685 45.09147 -1 0 1 + 841 254 13 -0.834 45.72190 46.51173 32.51384 1 0 0 + 842 254 14 0.417 46.00925 45.78294 31.96381 1 0 0 + 843 254 14 0.417 46.53186 46.95248 32.77064 1 0 0 + 844 255 13 -0.834 63.64359 44.33728 41.24417 -1 0 0 + 845 255 14 0.417 63.60411 43.61794 41.87443 -1 0 0 + 846 255 14 0.417 62.76926 44.36407 40.85550 -1 0 0 + 847 256 13 -0.834 48.53353 66.27879 51.60437 0 0 -1 + 848 256 14 0.417 49.21611 66.24938 50.93396 0 0 -1 + 849 256 14 0.417 48.67507 65.48862 52.12577 0 0 -1 + 850 257 13 -0.834 54.11962 54.32751 39.83526 -1 1 1 + 851 257 14 0.417 53.37975 54.47391 39.24585 -1 1 1 + 852 257 14 0.417 53.95747 53.46346 40.21391 -1 1 1 + 853 258 13 -0.834 53.72785 66.08707 44.78384 -1 -1 0 + 854 258 14 0.417 54.65423 65.85662 44.85413 -1 -1 0 + 855 258 14 0.417 53.26300 65.26936 44.96130 -1 -1 0 + 856 259 13 -0.834 39.06287 51.40870 53.96063 0 0 -1 + 857 259 14 0.417 39.12854 51.34243 53.00796 0 0 -1 + 858 259 14 0.417 38.38057 52.06341 54.10916 0 0 -1 + 859 260 13 -0.834 58.77064 49.77012 37.45292 0 0 0 + 860 260 14 0.417 59.49652 49.20688 37.72142 0 0 0 + 861 260 14 0.417 57.98575 49.25379 37.63621 0 0 0 + 862 261 13 -0.834 37.94204 48.36591 35.22049 -1 0 0 + 863 261 14 0.417 37.94000 47.48368 35.59187 -1 0 0 + 864 261 14 0.417 38.86901 48.59216 35.14453 -1 0 0 + 865 262 13 -0.834 47.05754 54.06564 40.63628 0 -2 1 + 866 262 14 0.417 47.01965 53.22193 41.08679 0 -2 1 + 867 262 14 0.417 46.68660 54.68838 41.26145 0 -2 1 + 868 263 13 -0.834 46.01283 65.88108 53.59469 0 0 0 + 869 263 14 0.417 45.30729 66.50296 53.77277 0 0 0 + 870 263 14 0.417 46.76378 66.42902 53.36650 0 0 0 + 871 264 13 -0.834 45.32546 67.91008 39.11365 -1 -1 0 + 872 264 14 0.417 44.38981 67.96233 38.91853 -1 -1 0 + 873 264 14 0.417 45.70517 67.47097 38.35257 -1 -1 0 + 874 265 13 -0.834 55.39761 51.53823 53.16553 -1 1 -1 + 875 265 14 0.417 54.64975 52.10179 53.36389 -1 1 -1 + 876 265 14 0.417 55.78119 51.91789 52.37499 -1 1 -1 + 877 266 13 -0.834 57.06415 51.22923 32.75117 -1 -1 0 + 878 266 14 0.417 56.79908 52.11139 32.49079 -1 -1 0 + 879 266 14 0.417 57.98399 51.16910 32.49322 -1 -1 0 + 880 267 13 -0.834 50.05222 47.30342 45.67457 0 0 -2 + 881 267 14 0.417 49.85957 46.82324 46.47990 0 0 -2 + 882 267 14 0.417 50.60617 46.70964 45.16781 0 0 -2 + 883 268 13 -0.834 50.46819 45.47822 52.51129 0 1 -1 + 884 268 14 0.417 50.78823 45.07196 53.31677 0 1 -1 + 885 268 14 0.417 51.03886 45.13243 51.82499 0 1 -1 + 886 269 13 -0.834 47.44130 61.30175 47.80124 0 0 0 + 887 269 14 0.417 48.02715 60.89314 48.43850 0 0 0 + 888 269 14 0.417 47.98636 61.43626 47.02595 0 0 0 + 889 270 13 -0.834 41.31630 52.47434 39.71677 1 0 0 + 890 270 14 0.417 41.07609 52.94514 40.51485 1 0 0 + 891 270 14 0.417 42.05418 52.96849 39.35955 1 0 0 + 892 271 13 -0.834 55.90762 58.63213 50.47814 0 1 0 + 893 271 14 0.417 55.80273 59.37784 51.06903 0 1 0 + 894 271 14 0.417 55.41449 58.87554 49.69468 0 1 0 + 895 272 13 -0.834 42.23424 55.62725 53.35280 0 1 -1 + 896 272 14 0.417 41.62946 55.10926 53.88399 0 1 -1 + 897 272 14 0.417 41.75761 56.43615 53.16647 0 1 -1 + 898 273 13 -0.834 62.31754 63.97065 42.48774 0 0 1 + 899 273 14 0.417 63.27023 64.05391 42.44669 0 0 1 + 900 273 14 0.417 62.16851 63.13573 42.93152 0 0 1 + 901 274 13 -0.834 60.93154 49.79182 56.13812 0 -1 0 + 902 274 14 0.417 61.38991 48.97402 56.33134 0 -1 0 + 903 274 14 0.417 60.29808 49.88575 56.84955 0 -1 0 + 904 275 13 -0.834 50.39572 45.11274 36.60756 0 1 -1 + 905 275 14 0.417 50.88541 44.33834 36.33051 0 1 -1 + 906 275 14 0.417 50.38352 45.05976 37.56322 0 1 -1 + 907 276 13 -0.834 46.57204 43.12189 39.29488 -1 2 -1 + 908 276 14 0.417 46.48449 42.17951 39.43813 -1 2 -1 + 909 276 14 0.417 47.49357 43.30747 39.47547 -1 2 -1 + 910 277 13 -0.834 54.39979 41.37518 38.62483 0 0 1 + 911 277 14 0.417 54.27469 42.27221 38.31511 0 0 1 + 912 277 14 0.417 54.57135 68.24024 37.83080 0 -1 1 + 913 278 13 -0.834 60.57638 52.40343 41.12327 -1 1 -1 + 914 278 14 0.417 60.40196 53.27982 40.78010 -1 1 -1 + 915 278 14 0.417 60.37657 52.46726 42.05721 -1 1 -1 + 916 279 13 -0.834 61.77806 59.06524 41.98029 0 0 0 + 917 279 14 0.417 62.58317 59.36537 42.40214 0 0 0 + 918 279 14 0.417 61.10430 59.16112 42.65342 0 0 0 + 919 280 13 -0.834 43.46789 48.64833 54.88223 0 1 -2 + 920 280 14 0.417 43.60676 49.48200 54.43286 0 1 -2 + 921 280 14 0.417 43.74339 47.98554 54.24895 0 1 -2 + 922 281 13 -0.834 51.98628 58.37454 48.60562 -1 0 0 + 923 281 14 0.417 51.81372 57.54909 49.05852 -1 0 0 + 924 281 14 0.417 52.67545 58.16319 47.97583 -1 0 0 + 925 282 13 -0.834 55.00551 65.64176 56.63926 0 -1 -1 + 926 282 14 0.417 55.59134 66.11131 29.86167 0 -1 0 + 927 282 14 0.417 54.80211 66.27584 55.95165 0 -1 -1 + 928 283 13 -0.834 55.02996 52.59142 50.59986 -1 1 0 + 929 283 14 0.417 54.13615 52.66743 50.26585 -1 1 0 + 930 283 14 0.417 55.48513 53.35419 50.24316 -1 1 0 + 931 284 13 -0.834 37.39245 67.88600 56.81733 0 -1 -1 + 932 284 14 0.417 38.13326 41.09044 56.62787 0 0 -1 + 933 284 14 0.417 37.74351 67.00148 56.71419 0 -1 -1 + 934 285 13 -0.834 42.83234 60.22766 53.36959 0 0 0 + 935 285 14 0.417 43.51497 59.86233 52.80672 0 0 0 + 936 285 14 0.417 43.27782 60.90528 53.87815 0 0 0 + 937 286 13 -0.834 59.24806 43.81265 38.44265 1 0 0 + 938 286 14 0.417 59.12140 43.55748 39.35647 1 0 0 + 939 286 14 0.417 60.07673 44.29174 38.43991 1 0 0 + 940 287 13 -0.834 61.29263 60.52642 52.74164 -1 1 -1 + 941 287 14 0.417 61.73918 60.02180 53.42149 -1 1 -1 + 942 287 14 0.417 60.93759 61.28711 53.20156 -1 1 -1 + 943 288 13 -0.834 63.43980 43.30119 30.90384 -1 1 0 + 944 288 14 0.417 63.34979 42.36405 30.73085 -1 1 0 + 945 288 14 0.417 64.20504 43.56693 30.39393 -1 1 0 + 946 289 13 -0.834 57.11924 59.06522 54.48909 -1 0 0 + 947 289 14 0.417 57.40605 59.83488 54.98062 -1 0 0 + 948 289 14 0.417 57.59698 58.33614 54.88463 -1 0 0 + 949 290 13 -0.834 51.89759 59.82680 44.82923 1 1 -1 + 950 290 14 0.417 51.33588 59.94068 44.06258 1 1 -1 + 951 290 14 0.417 51.32846 60.01914 45.57443 1 1 -1 + 952 291 13 -0.834 57.64696 65.49112 47.86068 -1 0 0 + 953 291 14 0.417 57.31105 65.98457 48.60895 -1 0 0 + 954 291 14 0.417 57.73765 64.59519 48.18521 -1 0 0 + 955 292 13 -0.834 50.35232 57.73892 32.55459 0 1 0 + 956 292 14 0.417 51.07441 57.69034 31.92813 0 1 0 + 957 292 14 0.417 50.48339 58.57180 33.00777 0 1 0 + 958 293 13 -0.834 46.20166 60.82812 38.38269 0 1 1 + 959 293 14 0.417 46.12191 61.76977 38.53504 0 1 1 + 960 293 14 0.417 45.30555 60.53505 38.21735 0 1 1 + 961 294 13 -0.834 41.42660 51.46433 55.94150 1 0 -1 + 962 294 14 0.417 40.58025 51.71240 55.56944 1 0 -1 + 963 294 14 0.417 41.63094 50.62307 55.53311 1 0 -1 + 964 295 13 -0.834 56.72642 53.95840 32.00323 0 -1 0 + 965 295 14 0.417 57.12177 54.49254 32.69216 0 -1 0 + 966 295 14 0.417 55.80349 54.21231 32.00259 0 -1 0 + 967 296 13 -0.834 43.25852 41.40642 31.27656 0 1 0 + 968 296 14 0.417 43.58058 42.21308 31.67880 0 1 0 + 969 296 14 0.417 43.16985 68.16459 32.00619 0 0 0 + 970 297 13 -0.834 54.50477 52.62435 30.30235 -2 1 0 + 971 297 14 0.417 54.04985 52.22243 31.04245 -2 1 0 + 972 297 14 0.417 54.36900 53.56465 30.41915 -2 1 0 + 973 298 13 -0.834 38.11258 59.33341 36.21749 1 0 0 + 974 298 14 0.417 38.95754 58.91929 36.04205 1 0 0 + 975 298 14 0.417 38.14750 60.16192 35.73940 1 0 0 + 976 299 13 -0.834 39.65020 64.70254 40.48616 -1 0 1 + 977 299 14 0.417 39.87581 65.58596 40.19474 -1 0 1 + 978 299 14 0.417 39.66086 64.17611 39.68676 -1 0 1 + 979 300 13 -0.834 63.26661 53.84973 48.10281 -1 1 1 + 980 300 14 0.417 63.38261 54.75210 48.40032 -1 1 1 + 981 300 14 0.417 62.32830 53.68505 48.19603 -1 1 1 + 982 301 13 -0.834 43.65966 61.04202 50.03088 0 0 0 + 983 301 14 0.417 44.11377 60.35973 50.52538 0 0 0 + 984 301 14 0.417 44.30508 61.74317 49.94108 0 0 0 + 985 302 13 -0.834 61.75204 50.20037 32.39414 0 0 0 + 986 302 14 0.417 62.04749 51.09027 32.58663 0 0 0 + 987 302 14 0.417 62.55370 49.67736 32.38826 0 0 0 + 988 303 13 -0.834 53.79071 58.98335 36.25336 -1 -2 -1 + 989 303 14 0.417 53.17711 58.26833 36.42220 -1 -2 -1 + 990 303 14 0.417 54.65389 58.60140 36.41235 -1 -2 -1 + 991 304 13 -0.834 50.47963 50.13918 42.58243 1 -1 -2 + 992 304 14 0.417 51.28111 49.63880 42.42915 1 -1 -2 + 993 304 14 0.417 50.33279 50.61369 41.76419 1 -1 -2 + 994 305 13 -0.834 50.28770 49.02182 56.79391 1 -1 -2 + 995 305 14 0.417 50.66164 48.14920 56.91622 1 -1 -2 + 996 305 14 0.417 50.60501 49.30063 55.93493 1 -1 -2 + 997 306 13 -0.834 41.36930 46.36343 34.87469 1 1 0 + 998 306 14 0.417 42.25704 46.59841 34.60463 1 1 0 + 999 306 14 0.417 40.85961 47.16333 34.74582 1 1 0 + 1000 307 13 -0.834 61.15349 47.47016 41.71779 0 1 0 + 1001 307 14 0.417 61.50139 48.29469 41.37818 0 1 0 + 1002 307 14 0.417 60.28203 47.69385 42.04454 0 1 0 + 1003 308 13 -0.834 58.35337 46.83622 34.81712 0 0 1 + 1004 308 14 0.417 57.63221 46.22391 34.67141 0 0 1 + 1005 308 14 0.417 57.97297 47.69883 34.65146 0 0 1 + 1006 309 13 -0.834 38.79812 57.92803 48.26323 1 -2 -1 + 1007 309 14 0.417 38.67444 56.98130 48.33141 1 -2 -1 + 1008 309 14 0.417 39.70990 58.06987 48.51776 1 -2 -1 + 1009 310 13 -0.834 42.15963 57.96891 45.03230 1 0 0 + 1010 310 14 0.417 42.11698 57.98663 45.98839 1 0 0 + 1011 310 14 0.417 41.83611 57.10021 44.79371 1 0 0 + 1012 311 13 -0.834 55.17551 54.72671 36.49400 0 -1 0 + 1013 311 14 0.417 55.26386 53.77738 36.57890 0 -1 0 + 1014 311 14 0.417 55.36463 55.06457 37.36939 0 -1 0 + 1015 312 13 -0.834 58.64573 63.28550 41.10609 -1 -2 -1 + 1016 312 14 0.417 58.98147 62.66636 41.75429 -1 -2 -1 + 1017 312 14 0.417 57.90273 62.83419 40.70545 -1 -2 -1 + 1018 313 13 -0.834 49.96498 59.98797 42.54359 0 -1 0 + 1019 313 14 0.417 50.57886 60.48612 42.00390 0 -1 0 + 1020 313 14 0.417 49.10600 60.17526 42.16501 0 -1 0 + 1021 314 13 -0.834 57.54750 44.35075 52.12722 -1 -1 -1 + 1022 314 14 0.417 57.86221 43.84739 51.37633 -1 -1 -1 + 1023 314 14 0.417 56.76423 44.79718 51.80558 -1 -1 -1 + 1024 315 13 -0.834 58.07892 59.46258 41.31930 1 -1 0 + 1025 315 14 0.417 58.27344 60.10968 41.99729 1 -1 0 + 1026 315 14 0.417 57.80524 59.98199 40.56328 1 -1 0 + 1027 316 13 -0.834 42.21869 44.49848 55.65511 2 1 0 + 1028 316 14 0.417 42.77458 44.78017 56.38166 2 1 0 + 1029 316 14 0.417 42.83052 44.15513 55.00395 2 1 0 + 1030 317 13 -0.834 56.38334 63.45614 43.52622 -1 -1 0 + 1031 317 14 0.417 55.66283 63.62998 42.92052 -1 -1 0 + 1032 317 14 0.417 56.48976 64.27319 44.01338 -1 -1 0 + 1033 318 13 -0.834 43.21354 46.04700 52.52965 1 1 0 + 1034 318 14 0.417 43.24360 45.09879 52.40226 1 1 0 + 1035 318 14 0.417 43.99839 46.37328 52.08943 1 1 0 + 1036 319 13 -0.834 55.96174 45.94863 35.39660 -1 0 1 + 1037 319 14 0.417 55.64687 46.44680 36.15088 -1 0 1 + 1038 319 14 0.417 55.28305 46.06527 34.73174 -1 0 1 + 1039 320 13 -0.834 47.36406 54.82690 34.84439 -1 -1 2 + 1040 320 14 0.417 47.90093 54.86776 34.05295 -1 -1 2 + 1041 320 14 0.417 47.23152 53.89118 34.99640 -1 -1 2 + 1042 321 13 -0.834 49.62685 50.00229 45.27362 1 0 -2 + 1043 321 14 0.417 49.70876 49.05477 45.38192 1 0 -2 + 1044 321 14 0.417 49.82566 50.15634 44.35005 1 0 -2 + 1045 322 13 -0.834 49.58249 46.02940 55.43310 -1 0 -2 + 1046 322 14 0.417 49.10378 46.80060 55.12924 -1 0 -2 + 1047 322 14 0.417 49.31802 45.92761 56.34739 -1 0 -2 + 1048 323 13 -0.834 51.72150 51.53491 51.55558 0 -1 -1 + 1049 323 14 0.417 51.50292 52.17946 50.88251 0 -1 -1 + 1050 323 14 0.417 52.14568 52.04382 52.24646 0 -1 -1 + 1051 324 13 -0.834 37.98107 56.66338 52.98024 0 1 0 + 1052 324 14 0.417 37.64467 57.53823 52.78607 0 1 0 + 1053 324 14 0.417 38.15999 56.27913 52.12200 0 1 0 + 1054 325 13 -0.834 59.20226 51.55233 53.16877 -1 1 0 + 1055 325 14 0.417 59.68851 51.88535 53.92302 -1 1 0 + 1056 325 14 0.417 58.63621 50.87031 53.53025 -1 1 0 + 1057 326 13 -0.834 45.75783 63.62117 39.24032 1 1 -1 + 1058 326 14 0.417 46.25179 64.38626 39.53508 1 1 -1 + 1059 326 14 0.417 44.85376 63.80686 39.49409 1 1 -1 + 1060 327 13 -0.834 58.00953 52.38584 37.67148 -1 1 1 + 1061 327 14 0.417 58.24242 51.47235 37.50553 -1 1 1 + 1062 327 14 0.417 57.26453 52.33853 38.27062 -1 1 1 + 1063 328 13 -0.834 50.62838 66.20855 42.36072 0 0 -1 + 1064 328 14 0.417 51.45434 66.68250 42.45770 0 0 -1 + 1065 328 14 0.417 49.99531 66.87945 42.10506 0 0 -1 + 1066 329 13 -0.834 53.69444 52.39171 45.41982 1 0 0 + 1067 329 14 0.417 53.84961 51.45739 45.55855 1 0 0 + 1068 329 14 0.417 52.75879 52.45359 45.22750 1 0 0 + 1069 330 13 -0.834 38.34038 60.92162 30.12773 2 0 0 + 1070 330 14 0.417 39.08908 61.47644 29.90887 2 0 0 + 1071 330 14 0.417 38.64185 60.39196 30.86585 2 0 0 + 1072 331 13 -0.834 48.03336 64.84935 43.13262 -1 0 -2 + 1073 331 14 0.417 48.90813 65.00919 43.48682 -1 0 -2 + 1074 331 14 0.417 47.46214 65.43367 43.63114 -1 0 -2 + 1075 332 13 -0.834 39.68760 66.88962 36.60665 2 0 0 + 1076 332 14 0.417 38.74743 66.72116 36.66944 2 0 0 + 1077 332 14 0.417 40.05009 66.08888 36.22764 2 0 0 + 1078 333 13 -0.834 51.94118 65.49897 51.83197 0 -1 -2 + 1079 333 14 0.417 52.71282 65.06165 51.47204 0 -1 -2 + 1080 333 14 0.417 51.22446 64.88225 51.68297 0 -1 -2 + 1081 334 13 -0.834 43.33066 57.53264 55.09930 -1 0 -2 + 1082 334 14 0.417 43.05496 56.76932 54.59178 -1 0 -2 + 1083 334 14 0.417 44.28179 57.55937 54.99503 -1 0 -2 + 1084 335 13 -0.834 47.70128 45.69178 52.17773 -1 3 -1 + 1085 335 14 0.417 47.54566 44.86273 52.63016 -1 3 -1 + 1086 335 14 0.417 48.58530 45.94693 52.44163 -1 3 -1 + 1087 336 13 -0.834 58.71603 41.81571 40.73899 -1 0 0 + 1088 336 14 0.417 57.77048 41.84330 40.88539 -1 0 0 + 1089 336 14 0.417 58.81275 41.43332 39.86682 -1 0 0 + 1090 337 13 -0.834 57.56034 60.98533 43.60766 0 -1 0 + 1091 337 14 0.417 56.67639 60.61816 43.59917 0 -1 0 + 1092 337 14 0.417 57.42830 61.92611 43.72486 0 -1 0 + 1093 338 13 -0.834 44.68088 65.08579 34.27880 -1 0 2 + 1094 338 14 0.417 45.54678 65.09564 34.68668 -1 0 2 + 1095 338 14 0.417 44.45037 64.15818 34.22739 -1 0 2 + 1096 339 13 -0.834 54.98236 48.04093 42.26075 0 0 0 + 1097 339 14 0.417 55.16505 47.86552 43.18384 0 0 0 + 1098 339 14 0.417 55.70493 48.59999 41.97513 0 0 0 + 1099 340 13 -0.834 60.57099 56.88773 56.53671 0 0 1 + 1100 340 14 0.417 60.67151 56.21616 29.83998 0 0 2 + 1101 340 14 0.417 61.34465 56.78824 55.98192 0 0 1 + 1102 341 13 -0.834 48.05045 49.69974 47.93542 -1 0 0 + 1103 341 14 0.417 48.70922 49.23613 48.45249 -1 0 0 + 1104 341 14 0.417 48.26410 49.48583 47.02721 -1 0 0 + 1105 342 13 -0.834 40.63207 55.77589 49.21695 1 0 -1 + 1106 342 14 0.417 40.84917 56.26844 50.00847 1 0 -1 + 1107 342 14 0.417 41.40772 55.85904 48.66226 1 0 -1 + 1108 343 13 -0.834 61.66015 42.71355 39.91223 0 0 0 + 1109 343 14 0.417 61.87748 41.86774 40.30419 0 0 0 + 1110 343 14 0.417 61.98864 42.65380 39.01514 0 0 0 + 1111 344 13 -0.834 38.52157 65.12766 57.04010 0 -1 -1 + 1112 344 14 0.417 38.04157 64.32142 56.85084 0 -1 -1 + 1113 344 14 0.417 39.36310 65.01535 56.59799 0 -1 -1 + 1114 345 13 -0.834 54.26556 44.72348 38.61852 -1 0 0 + 1115 345 14 0.417 54.65781 45.53245 38.94708 -1 0 0 + 1116 345 14 0.417 54.97105 44.29396 38.13473 -1 0 0 + 1117 346 13 -0.834 55.38993 55.61246 43.96322 -1 0 1 + 1118 346 14 0.417 54.74535 54.99107 43.62461 -1 0 1 + 1119 346 14 0.417 55.11835 55.77119 44.86726 -1 0 1 + 1120 347 13 -0.834 56.42023 55.00369 50.06211 -1 -1 0 + 1121 347 14 0.417 55.77599 55.59187 50.45611 -1 -1 0 + 1122 347 14 0.417 56.93756 54.68448 50.80151 -1 -1 0 + 1123 348 13 -0.834 45.79495 66.88952 36.56670 1 1 -1 + 1124 348 14 0.417 45.28578 66.71904 35.77429 1 1 -1 + 1125 348 14 0.417 46.57709 67.34552 36.25591 1 1 -1 + 1126 349 13 -0.834 62.75278 45.54084 32.23733 0 0 0 + 1127 349 14 0.417 62.61586 44.79986 31.64705 0 0 0 + 1128 349 14 0.417 62.96974 45.14017 33.07913 0 0 0 + 1129 350 13 -0.834 57.50625 65.62986 39.74454 0 0 0 + 1130 350 14 0.417 57.73342 64.85584 40.25983 0 0 0 + 1131 350 14 0.417 57.07082 66.21286 40.36642 0 0 0 + 1132 351 13 -0.834 55.96293 62.10636 50.17062 0 1 -1 + 1133 351 14 0.417 56.24333 61.70901 50.99507 0 1 -1 + 1134 351 14 0.417 56.67888 62.69531 49.93234 0 1 -1 + 1135 352 13 -0.834 37.45010 41.11856 53.00894 0 0 0 + 1136 352 14 0.417 37.99062 41.49514 53.70339 0 0 0 + 1137 352 14 0.417 37.83337 41.45341 52.19826 0 0 0 + 1138 353 13 -0.834 40.59344 47.85232 38.52244 1 0 1 + 1139 353 14 0.417 41.31256 47.71502 37.90580 1 0 1 + 1140 353 14 0.417 40.21612 48.69426 38.26747 1 0 1 + 1141 354 13 -0.834 60.77214 62.31711 30.33695 0 2 -1 + 1142 354 14 0.417 59.83662 62.43212 30.17023 0 2 -1 + 1143 354 14 0.417 60.97856 61.45964 29.96496 0 2 -1 + 1144 355 13 -0.834 47.83829 64.26042 48.43592 0 1 -1 + 1145 355 14 0.417 47.12209 64.85952 48.22523 0 1 -1 + 1146 355 14 0.417 47.44823 63.38856 48.37295 0 1 -1 + 1147 356 13 -0.834 38.69679 45.31108 42.13672 1 1 0 + 1148 356 14 0.417 39.20464 45.52138 41.35308 1 1 0 + 1149 356 14 0.417 37.90440 44.89009 41.80335 1 1 0 + 1150 357 13 -0.834 38.90832 47.67164 52.69089 0 1 0 + 1151 357 14 0.417 39.51269 48.14149 53.26554 0 1 0 + 1152 357 14 0.417 38.42834 48.36117 52.23218 0 1 0 + 1153 358 13 -0.834 45.13879 48.98199 29.96256 0 2 1 + 1154 358 14 0.417 44.63649 48.48457 30.60794 0 2 1 + 1155 358 14 0.417 44.70163 48.80464 56.50106 0 2 0 + 1156 359 13 -0.834 54.78460 57.58368 54.24956 1 1 -1 + 1157 359 14 0.417 54.71436 57.34891 55.17486 1 1 -1 + 1158 359 14 0.417 55.60599 58.07122 54.18735 1 1 -1 + 1159 360 13 -0.834 40.77006 67.09387 46.34204 0 0 1 + 1160 360 14 0.417 40.91087 66.51539 47.09156 0 0 1 + 1161 360 14 0.417 41.47386 67.73986 46.40192 0 0 1 + 1162 361 13 -0.834 53.75960 49.21723 54.03526 1 0 -1 + 1163 361 14 0.417 54.17778 50.07537 53.96484 1 0 -1 + 1164 361 14 0.417 54.18187 48.68822 53.35846 1 0 -1 + 1165 362 13 -0.834 46.41755 62.84035 30.52059 0 0 1 + 1166 362 14 0.417 46.37357 61.90548 30.72136 0 0 1 + 1167 362 14 0.417 46.76359 62.87829 57.00030 0 0 0 + 1168 363 13 -0.834 51.27491 42.28113 30.83818 0 -1 0 + 1169 363 14 0.417 51.18814 42.11416 31.77671 0 -1 0 + 1170 363 14 0.417 50.41560 42.60836 30.57220 0 -1 0 + 1171 364 13 -0.834 52.36258 42.54738 46.83477 0 -1 -1 + 1172 364 14 0.417 51.62853 42.02025 46.51928 0 -1 -1 + 1173 364 14 0.417 53.11771 42.22680 46.34158 0 -1 -1 + 1174 365 13 -0.834 40.11442 46.69570 48.71466 3 -2 1 + 1175 365 14 0.417 39.89820 47.61495 48.55824 3 -2 1 + 1176 365 14 0.417 40.87520 46.72352 49.29493 3 -2 1 + 1177 366 13 -0.834 56.56957 65.78976 45.32589 0 -2 -1 + 1178 366 14 0.417 56.86196 65.56407 46.20896 0 -2 -1 + 1179 366 14 0.417 57.34222 66.16870 44.90678 0 -2 -1 + 1180 367 13 -0.834 38.37373 47.63723 43.98242 2 0 0 + 1181 367 14 0.417 38.78516 47.21384 44.73589 2 0 0 + 1182 367 14 0.417 38.73588 47.18051 43.22315 2 0 0 + 1183 368 13 -0.834 45.69445 49.36872 40.50736 -1 0 -2 + 1184 368 14 0.417 44.73771 49.39892 40.51002 -1 0 -2 + 1185 368 14 0.417 45.90701 48.47357 40.77155 -1 0 -2 + 1186 369 13 -0.834 53.93830 54.76570 31.99728 0 -1 0 + 1187 369 14 0.417 53.94849 55.50033 32.61083 0 -1 0 + 1188 369 14 0.417 53.13070 54.29402 32.20107 0 -1 0 + 1189 370 13 -0.834 58.79125 64.07093 37.97498 -1 -1 -2 + 1190 370 14 0.417 58.48296 64.72380 38.60343 -1 -1 -2 + 1191 370 14 0.417 58.20942 64.16977 37.22136 -1 -1 -2 + 1192 371 13 -0.834 51.76123 61.42281 40.82794 0 -1 0 + 1193 371 14 0.417 52.69114 61.24136 40.69160 0 -1 0 + 1194 371 14 0.417 51.74755 62.21395 41.36660 0 -1 0 + 1195 372 13 -0.834 44.28377 63.70509 53.71234 -1 -2 -1 + 1196 372 14 0.417 44.98211 64.35001 53.59994 -1 -2 -1 + 1197 372 14 0.417 43.75271 63.78587 52.92008 -1 -2 -1 + 1198 373 13 -0.834 61.50835 48.76378 34.91047 0 0 -1 + 1199 373 14 0.417 61.23254 49.09753 34.05678 0 0 -1 + 1200 373 14 0.417 61.51672 49.53447 35.47812 0 0 -1 + 1201 374 13 -0.834 61.51337 41.63477 44.26291 -1 -1 0 + 1202 374 14 0.417 62.42662 41.58544 44.54543 -1 -1 0 + 1203 374 14 0.417 61.34749 68.16405 43.83907 -1 -2 0 + 1204 375 13 -0.834 57.73267 43.39213 33.64792 0 -1 0 + 1205 375 14 0.417 58.46456 43.28438 34.25535 0 -1 0 + 1206 375 14 0.417 58.09278 43.15396 32.79362 0 -1 0 + 1207 376 13 -0.834 63.51473 49.31549 51.59705 -1 1 -1 + 1208 376 14 0.417 63.13045 49.03534 50.76631 -1 1 -1 + 1209 376 14 0.417 62.84038 49.86142 52.00137 -1 1 -1 + 1210 377 13 -0.834 58.21462 44.79010 54.73553 -1 -1 -1 + 1211 377 14 0.417 58.08068 43.94884 55.17209 -1 -1 -1 + 1212 377 14 0.417 57.81645 44.67856 53.87224 -1 -1 -1 + 1213 378 13 -0.834 57.08090 55.14561 52.86183 0 -2 1 + 1214 378 14 0.417 57.05215 55.46811 53.76261 0 -2 1 + 1215 378 14 0.417 57.69965 54.41575 52.88786 0 -2 1 + 1216 379 13 -0.834 60.83502 54.45436 45.82182 1 0 -1 + 1217 379 14 0.417 61.05342 55.38616 45.83857 1 0 -1 + 1218 379 14 0.417 60.79443 54.20077 46.74392 1 0 -1 + 1219 380 13 -0.834 60.86442 48.23162 37.95658 0 0 2 + 1220 380 14 0.417 61.77710 48.43881 37.75572 0 0 2 + 1221 380 14 0.417 60.87611 47.30540 38.19788 0 0 2 + 1222 381 13 -0.834 43.21478 43.26953 44.97859 2 1 -1 + 1223 381 14 0.417 42.50778 42.78849 44.54850 2 1 -1 + 1224 381 14 0.417 43.42173 42.74895 45.75474 2 1 -1 + 1225 382 13 -0.834 39.01904 49.57571 48.28198 1 -1 -1 + 1226 382 14 0.417 38.68877 49.32064 47.42052 1 -1 -1 + 1227 382 14 0.417 38.42357 50.26661 48.57234 1 -1 -1 + 1228 383 13 -0.834 47.20253 45.34580 30.26781 0 0 1 + 1229 383 14 0.417 47.05738 44.40526 30.16508 0 0 1 + 1230 383 14 0.417 46.80592 45.73631 56.86044 0 0 0 + 1231 384 13 -0.834 44.57742 55.88746 33.53830 0 -1 0 + 1232 384 14 0.417 45.13093 56.49768 33.05096 0 -1 0 + 1233 384 14 0.417 44.41092 55.17196 32.92464 0 -1 0 + 1234 385 13 -0.834 42.17091 64.36626 51.74369 1 0 0 + 1235 385 14 0.417 41.78583 65.24128 51.69570 1 0 0 + 1236 385 14 0.417 41.41926 63.77568 51.79343 1 0 0 + 1237 386 13 -0.834 43.82615 43.47821 52.97551 0 0 0 + 1238 386 14 0.417 43.64099 42.56407 52.76025 0 0 0 + 1239 386 14 0.417 44.58924 43.43914 53.55207 0 0 0 + 1240 387 13 -0.834 63.58286 63.91035 38.47173 0 -1 -1 + 1241 387 14 0.417 64.14591 63.71296 39.22023 0 -1 -1 + 1242 387 14 0.417 62.70901 64.01191 38.84896 0 -1 -1 + 1243 388 13 -0.834 57.85225 42.19019 46.82252 1 1 -2 + 1244 388 14 0.417 57.61712 42.29475 47.74450 1 1 -2 + 1245 388 14 0.417 57.29406 42.81537 46.36013 1 1 -2 + 1246 389 13 -0.834 57.90802 64.30101 52.26362 1 0 1 + 1247 389 14 0.417 58.43907 64.81717 52.87010 1 0 1 + 1248 389 14 0.417 58.54387 63.78888 51.76396 1 0 1 + 1249 390 13 -0.834 53.18379 66.68791 54.05156 1 -2 0 + 1250 390 14 0.417 52.23394 66.79510 54.00115 1 -2 0 + 1251 390 14 0.417 53.33447 65.77140 53.82015 1 -2 0 + 1252 391 13 -0.834 56.95394 68.26036 36.42711 -1 1 1 + 1253 391 14 0.417 56.91362 41.83232 36.58445 -1 2 1 + 1254 391 14 0.417 57.79173 67.98998 36.80292 -1 1 1 + 1255 392 13 -0.834 64.19252 44.20158 54.88143 0 0 0 + 1256 392 14 0.417 64.09322 45.07899 54.51194 0 0 0 + 1257 392 14 0.417 63.39239 43.74201 54.62684 0 0 0 + 1258 393 13 -0.834 63.10536 65.42626 48.53464 0 0 0 + 1259 393 14 0.417 62.79665 64.63036 48.10166 0 0 0 + 1260 393 14 0.417 62.77768 65.35429 49.43112 0 0 0 + 1261 394 13 -0.834 49.28836 66.20367 32.27628 1 -1 0 + 1262 394 14 0.417 49.46858 65.88738 33.16155 1 -1 0 + 1263 394 14 0.417 49.29197 65.41476 31.73420 1 -1 0 + 1264 395 13 -0.834 46.11216 66.09570 44.77896 0 -1 0 + 1265 395 14 0.417 45.90309 66.07762 45.71287 0 -1 0 + 1266 395 14 0.417 45.36137 65.67813 44.35683 0 -1 0 + 1267 396 13 -0.834 41.43943 50.30026 52.32584 1 0 0 + 1268 396 14 0.417 41.39866 49.93140 51.44351 1 0 0 + 1269 396 14 0.417 40.92759 49.69528 52.86275 1 0 0 + 1270 397 13 -0.834 54.69177 57.80859 32.50623 0 -1 -1 + 1271 397 14 0.417 53.99890 57.66594 31.86139 0 -1 -1 + 1272 397 14 0.417 54.37599 57.37325 33.29806 0 -1 -1 + 1273 398 13 -0.834 43.56781 46.79065 37.17838 0 1 0 + 1274 398 14 0.417 43.18325 46.24795 36.49004 0 1 0 + 1275 398 14 0.417 44.03819 46.17194 37.73711 0 1 0 + 1276 399 13 -0.834 55.33436 45.90772 50.69068 -1 0 0 + 1277 399 14 0.417 55.55455 46.77982 51.01809 -1 0 0 + 1278 399 14 0.417 55.09425 46.04877 49.77488 -1 0 0 + 1279 400 13 -0.834 56.15383 51.87018 43.92178 -1 0 1 + 1280 400 14 0.417 55.25073 52.12373 44.11256 -1 0 1 + 1281 400 14 0.417 56.65027 52.68628 43.98319 -1 0 1 + 1282 401 13 -0.834 62.38946 50.01240 45.94802 0 1 -2 + 1283 401 14 0.417 62.43815 50.07607 44.99418 0 1 -2 + 1284 401 14 0.417 61.47369 50.19932 46.15457 0 1 -2 + 1285 402 13 -0.834 53.60920 58.35575 46.37412 0 0 1 + 1286 402 14 0.417 53.25556 59.03071 45.79481 0 0 1 + 1287 402 14 0.417 53.24753 57.53627 46.03666 0 0 1 + 1288 403 13 -0.834 43.13375 42.07203 50.04429 1 0 0 + 1289 403 14 0.417 43.76099 42.76922 49.85267 1 0 0 + 1290 403 14 0.417 42.35437 42.53016 50.35879 1 0 0 + 1291 404 13 -0.834 47.41498 59.41146 52.77687 -1 -1 0 + 1292 404 14 0.417 47.81303 59.83868 53.53534 -1 -1 0 + 1293 404 14 0.417 48.01011 59.60512 52.05261 -1 -1 0 + 1294 405 13 -0.834 63.75607 47.28104 38.80571 0 2 -1 + 1295 405 14 0.417 63.78573 48.20840 38.57042 0 2 -1 + 1296 405 14 0.417 37.08655 47.17376 39.44769 1 2 -1 + 1297 406 13 -0.834 46.67594 56.20863 44.42866 1 1 0 + 1298 406 14 0.417 45.82140 56.15280 44.00100 1 1 0 + 1299 406 14 0.417 46.48292 56.12468 45.36243 1 1 0 + 1300 407 13 -0.834 62.54251 68.21194 54.20445 0 -1 1 + 1301 407 14 0.417 63.31640 41.15490 53.73696 0 0 1 + 1302 407 14 0.417 62.78865 67.34176 54.51819 0 -1 1 + 1303 408 13 -0.834 60.27010 54.96049 39.87633 0 0 0 + 1304 408 14 0.417 59.62959 55.67175 39.88547 0 0 0 + 1305 408 14 0.417 61.04761 55.33233 40.29281 0 0 0 + 1306 409 13 -0.834 40.02595 44.30132 44.29580 0 -2 0 + 1307 409 14 0.417 39.70595 44.75009 45.07839 0 -2 0 + 1308 409 14 0.417 39.56836 44.72725 43.57092 0 -2 0 + 1309 410 13 -0.834 54.20011 41.08252 35.61017 0 1 0 + 1310 410 14 0.417 55.10396 68.23613 35.83794 0 0 0 + 1311 410 14 0.417 54.27044 41.57221 34.79072 0 1 0 + 1312 411 13 -0.834 60.64478 45.93023 50.84376 1 1 -1 + 1313 411 14 0.417 60.80088 46.54647 51.55941 1 1 -1 + 1314 411 14 0.417 61.20574 46.24077 50.13303 1 1 -1 + 1315 412 13 -0.834 44.55137 44.47403 38.16771 1 0 -1 + 1316 412 14 0.417 45.28189 43.86333 38.26597 1 0 -1 + 1317 412 14 0.417 43.77025 43.93754 38.30281 1 0 -1 + 1318 413 13 -0.834 58.08933 62.76987 30.45191 1 -1 0 + 1319 413 14 0.417 57.64138 63.31997 29.80927 1 -1 0 + 1320 413 14 0.417 57.43674 62.11708 30.70545 1 -1 0 + 1321 414 13 -0.834 55.65273 56.71117 38.74877 1 0 1 + 1322 414 14 0.417 56.53260 56.59636 39.10779 1 0 1 + 1323 414 14 0.417 55.14964 55.98047 39.10825 1 0 1 + 1324 415 13 -0.834 55.50009 51.16952 38.77962 0 0 0 + 1325 415 14 0.417 54.95350 51.23711 37.99672 0 0 0 + 1326 415 14 0.417 55.53220 50.23190 38.96963 0 0 0 + 1327 416 13 -0.834 47.64702 52.79911 31.71446 0 -1 0 + 1328 416 14 0.417 48.52504 53.09556 31.47481 0 -1 0 + 1329 416 14 0.417 47.06032 53.44853 31.32681 0 -1 0 + 1330 417 13 -0.834 49.26727 42.35880 39.18566 1 1 -2 + 1331 417 14 0.417 50.02784 42.93912 39.15429 1 1 -2 + 1332 417 14 0.417 49.46495 41.74196 39.89040 1 1 -2 + 1333 418 13 -0.834 47.22542 64.65021 35.82232 1 -1 0 + 1334 418 14 0.417 46.76114 65.20346 36.45050 1 -1 0 + 1335 418 14 0.417 47.98585 65.16966 35.56120 1 -1 0 + 1336 419 13 -0.834 58.53686 56.85468 40.78587 1 1 0 + 1337 419 14 0.417 58.45283 56.63469 41.71365 1 1 0 + 1338 419 14 0.417 58.36285 57.79507 40.74550 1 1 0 + 1339 420 13 -0.834 50.09436 46.17981 48.16619 -1 -1 -2 + 1340 420 14 0.417 50.67249 45.42897 48.30138 -1 -1 -2 + 1341 420 14 0.417 50.49629 46.88624 48.67183 -1 -1 -2 + 1342 421 13 -0.834 42.30297 57.95379 33.48633 0 -1 1 + 1343 421 14 0.417 41.56921 57.39445 33.23136 0 -1 1 + 1344 421 14 0.417 43.00718 57.34235 33.70193 0 -1 1 + 1345 422 13 -0.834 45.76518 43.79811 54.82490 0 -1 0 + 1346 422 14 0.417 46.45133 43.55343 54.20397 0 -1 0 + 1347 422 14 0.417 45.87205 43.18693 55.55379 0 -1 0 + 1348 423 13 -0.834 59.33326 61.34125 37.96927 -1 -1 1 + 1349 423 14 0.417 59.29007 62.29004 38.08827 -1 -1 1 + 1350 423 14 0.417 59.90006 61.03609 38.67769 -1 -1 1 + 1351 424 13 -0.834 40.95662 63.48104 42.72192 1 -1 0 + 1352 424 14 0.417 40.33618 63.69074 42.02383 1 -1 0 + 1353 424 14 0.417 41.73946 63.17568 42.26346 1 -1 0 + 1354 425 13 -0.834 38.13662 59.25720 46.08402 1 -1 -1 + 1355 425 14 0.417 38.31499 59.03616 46.99811 1 -1 -1 + 1356 425 14 0.417 38.55502 58.55783 45.58196 1 -1 -1 + 1357 426 13 -0.834 48.88681 66.85051 54.82298 1 -2 0 + 1358 426 14 0.417 49.16879 67.45078 54.13275 1 -2 0 + 1359 426 14 0.417 49.42353 66.06836 54.69484 1 -2 0 + 1360 427 13 -0.834 45.88049 57.05477 48.46508 0 0 -1 + 1361 427 14 0.417 45.73709 57.90911 48.05793 0 0 -1 + 1362 427 14 0.417 45.83791 57.22701 49.40569 0 0 -1 + 1363 428 13 -0.834 39.37333 50.31613 37.93447 0 1 0 + 1364 428 14 0.417 39.11456 50.97624 37.29140 0 1 0 + 1365 428 14 0.417 38.97424 50.60960 38.75352 0 1 0 + 1366 429 13 -0.834 37.89753 62.82745 47.39297 0 -1 0 + 1367 429 14 0.417 38.39122 62.78202 46.57414 0 -1 0 + 1368 429 14 0.417 37.01605 63.08963 47.12747 0 -1 0 + 1369 430 13 -0.834 43.16514 41.31420 47.01379 0 1 0 + 1370 430 14 0.417 42.71409 41.22965 47.85382 0 1 0 + 1371 430 14 0.417 44.05112 68.36565 47.18386 0 0 0 + 1372 431 13 -0.834 47.03179 42.44477 42.46475 1 0 0 + 1373 431 14 0.417 46.12350 42.65285 42.24573 1 0 0 + 1374 431 14 0.417 47.53228 43.19970 42.15516 1 0 0 + 1375 432 13 -0.834 55.35894 54.15040 46.85340 0 -1 0 + 1376 432 14 0.417 54.76544 53.43667 46.61975 0 -1 0 + 1377 432 14 0.417 56.17133 53.71318 47.10853 0 -1 0 + 1378 433 13 -0.834 47.00663 55.28313 38.22800 -1 -2 1 + 1379 433 14 0.417 46.53490 56.00706 38.63987 -1 -2 1 + 1380 433 14 0.417 47.07459 54.61953 38.91449 -1 -2 1 + 1381 434 13 -0.834 57.16336 58.62297 32.33349 -1 0 2 + 1382 434 14 0.417 57.63330 57.80350 32.48798 -1 0 2 + 1383 434 14 0.417 56.24209 58.36680 32.29014 -1 0 2 + 1384 435 13 -0.834 37.23245 47.62479 56.34765 0 1 -1 + 1385 435 14 0.417 37.24274 47.21497 55.48268 0 1 -1 + 1386 435 14 0.417 37.36000 46.89905 56.95860 0 1 -1 + 1387 436 13 -0.834 48.77030 41.06015 29.86683 2 1 0 + 1388 436 14 0.417 48.81141 67.97117 56.39997 2 0 -1 + 1389 436 14 0.417 49.05230 67.78232 30.51123 2 0 0 + 1390 437 13 -0.834 49.10149 56.15638 36.66346 0 0 1 + 1391 437 14 0.417 48.50786 55.61659 36.14146 0 0 1 + 1392 437 14 0.417 48.61812 56.33305 37.47053 0 0 1 + 1393 438 13 -0.834 58.15731 59.39698 29.96092 0 -1 1 + 1394 438 14 0.417 58.20240 59.10993 30.87296 0 -1 1 + 1395 438 14 0.417 57.30076 59.81721 29.88367 0 -1 1 + 1396 439 13 -0.834 59.37068 41.03089 37.87324 1 0 0 + 1397 439 14 0.417 59.56889 41.95335 37.71194 1 0 0 + 1398 439 14 0.417 60.22643 67.97433 37.90167 1 -1 0 + 1399 440 13 -0.834 38.32241 55.03397 50.58952 1 0 0 + 1400 440 14 0.417 38.22793 54.19584 50.13692 1 0 0 + 1401 440 14 0.417 39.21785 55.31153 50.39614 1 0 0 + 1402 441 13 -0.834 36.94673 59.01778 33.00159 1 -1 2 + 1403 441 14 0.417 36.95260 59.97305 32.94091 1 -1 2 + 1404 441 14 0.417 63.71798 58.82680 33.72245 0 -1 2 + 1405 442 13 -0.834 62.50746 54.84239 54.03343 0 -1 0 + 1406 442 14 0.417 61.69710 54.35984 54.19681 0 -1 0 + 1407 442 14 0.417 63.09119 54.20097 53.62833 0 -1 0 + 1408 443 13 -0.834 40.59690 62.80012 38.69405 1 -1 1 + 1409 443 14 0.417 41.53881 62.90970 38.82458 1 -1 1 + 1410 443 14 0.417 40.36980 62.03187 39.21794 1 -1 1 + 1411 444 13 -0.834 37.67477 67.71471 42.59127 0 -1 -1 + 1412 444 14 0.417 38.12213 68.13627 41.85751 0 -1 -1 + 1413 444 14 0.417 38.28279 67.03643 42.88534 0 -1 -1 + 1414 445 13 -0.834 42.73681 50.65782 33.30839 1 1 0 + 1415 445 14 0.417 42.84587 51.15085 34.12157 1 1 0 + 1416 445 14 0.417 42.32631 51.27747 32.70527 1 1 0 + 1417 446 13 -0.834 37.13349 57.05842 55.81927 0 0 0 + 1418 446 14 0.417 37.95375 57.53453 55.68979 0 0 0 + 1419 446 14 0.417 36.99014 56.59807 54.99236 0 0 0 + 1420 447 13 -0.834 61.08039 63.50929 36.52096 -1 0 0 + 1421 447 14 0.417 60.44389 63.87414 37.13579 -1 0 0 + 1422 447 14 0.417 61.70642 63.04107 37.07331 -1 0 0 + 1423 448 13 -0.834 57.12289 46.04019 38.75954 0 0 0 + 1424 448 14 0.417 56.81351 45.55997 39.52760 0 0 0 + 1425 448 14 0.417 57.99543 45.68504 38.58988 0 0 0 + 1426 449 13 -0.834 45.45003 49.45347 49.54397 0 0 -1 + 1427 449 14 0.417 45.96611 49.34591 48.74502 0 0 -1 + 1428 449 14 0.417 46.09930 49.60861 50.22999 0 0 -1 + 1429 450 13 -0.834 37.77009 64.51990 42.66941 1 0 0 + 1430 450 14 0.417 38.49339 64.80040 43.23011 1 0 0 + 1431 450 14 0.417 38.14071 64.50928 41.78694 1 0 0 + 1432 451 13 -0.834 45.78323 57.65378 39.37062 1 0 0 + 1433 451 14 0.417 46.03758 58.03295 40.21190 1 0 0 + 1434 451 14 0.417 44.96217 58.09258 39.14803 1 0 0 + 1435 452 13 -0.834 56.96672 60.41636 47.59314 0 -1 1 + 1436 452 14 0.417 56.18373 60.11455 48.05365 0 -1 1 + 1437 452 14 0.417 56.65889 61.13663 47.04297 0 -1 1 + 1438 453 13 -0.834 52.44356 65.82746 35.82081 -1 -1 0 + 1439 453 14 0.417 53.10567 65.14225 35.91211 -1 -1 0 + 1440 453 14 0.417 52.93741 66.64611 35.86748 -1 -1 0 + 1441 454 13 -0.834 50.70912 51.42252 40.30021 0 0 -1 + 1442 454 14 0.417 50.97387 50.70177 39.72866 0 0 -1 + 1443 454 14 0.417 50.17774 51.98938 39.74116 0 0 -1 + 1444 455 13 -0.834 39.22290 45.94023 39.69239 2 1 -1 + 1445 455 14 0.417 39.63836 46.66722 39.22859 2 1 -1 + 1446 455 14 0.417 38.97218 45.32685 39.00164 2 1 -1 + 1447 456 13 -0.834 43.73041 61.86387 55.46954 2 0 0 + 1448 456 14 0.417 43.61274 62.32163 56.30192 2 0 0 + 1449 456 14 0.417 43.90401 62.55964 54.83549 2 0 0 + 1450 457 13 -0.834 61.51877 56.42039 33.84869 0 0 1 + 1451 457 14 0.417 62.17805 55.74211 33.70200 0 0 1 + 1452 457 14 0.417 62.00943 57.15723 34.21276 0 0 1 + 1453 458 13 -0.834 51.72050 63.63199 42.34406 1 0 1 + 1454 458 14 0.417 51.24482 64.43296 42.56407 1 0 1 + 1455 458 14 0.417 52.62118 63.92057 42.19669 1 0 1 + 1456 459 13 -0.834 54.73666 56.51839 51.73687 0 0 -1 + 1457 459 14 0.417 54.77503 56.56844 52.69200 0 0 -1 + 1458 459 14 0.417 54.91702 57.41111 51.44234 0 0 -1 + 1459 460 13 -0.834 50.97984 54.35591 33.27919 0 1 0 + 1460 460 14 0.417 50.47200 55.12727 33.02747 0 1 0 + 1461 460 14 0.417 50.36917 53.82187 33.78725 0 1 0 + 1462 461 13 -0.834 44.82656 54.45280 36.09973 1 0 2 + 1463 461 14 0.417 45.75766 54.23599 36.14740 1 0 2 + 1464 461 14 0.417 44.76968 55.11700 35.41283 1 0 2 + 1465 462 13 -0.834 58.05791 56.64716 55.29041 1 1 0 + 1466 462 14 0.417 58.98499 56.81997 55.45441 1 1 0 + 1467 462 14 0.417 57.82639 55.96338 55.91897 1 1 0 + 1468 463 13 -0.834 55.95112 61.02029 30.79757 1 0 1 + 1469 463 14 0.417 55.28483 61.63344 30.48711 1 0 1 + 1470 463 14 0.417 55.45357 60.27206 31.12748 1 0 1 + 1471 464 13 -0.834 54.80996 46.88659 45.41700 -1 0 0 + 1472 464 14 0.417 55.42348 46.16300 45.28950 -1 0 0 + 1473 464 14 0.417 54.08129 46.68997 44.82826 -1 0 0 + 1474 465 13 -0.834 60.19361 64.43268 31.92053 0 -1 2 + 1475 465 14 0.417 60.05792 63.85315 32.67017 0 -1 2 + 1476 465 14 0.417 60.47170 63.84993 31.21392 0 -1 2 + 1477 466 13 -0.834 45.55496 65.56032 30.88251 0 -1 1 + 1478 466 14 0.417 45.97644 64.70102 30.89691 0 -1 1 + 1479 466 14 0.417 45.82502 65.97384 31.70248 0 -1 1 + 1480 467 13 -0.834 52.92714 44.06759 29.88429 0 1 0 + 1481 467 14 0.417 52.39641 43.38446 30.29405 0 1 0 + 1482 467 14 0.417 53.79372 43.96686 30.27818 0 1 0 + 1483 468 13 -0.834 40.71534 55.31247 44.93070 1 0 0 + 1484 468 14 0.417 39.81994 55.07165 45.16841 1 0 0 + 1485 468 14 0.417 41.16802 54.47609 44.82218 1 0 0 + 1486 469 13 -0.834 64.04777 59.80626 42.91634 0 -1 -1 + 1487 469 14 0.417 37.09051 60.51146 43.41377 1 -1 -1 + 1488 469 14 0.417 37.01609 59.00291 43.31068 1 -1 -1 + 1489 470 13 -0.834 57.05030 49.72625 41.88829 -1 1 1 + 1490 470 14 0.417 56.75150 50.53290 42.30818 -1 1 1 + 1491 470 14 0.417 57.52176 50.02159 41.10935 -1 1 1 + 1492 471 13 -0.834 62.59447 67.67898 41.14714 -2 -2 1 + 1493 471 14 0.417 63.45155 67.57764 41.56112 -2 -2 1 + 1494 471 14 0.417 61.96974 67.40478 41.81854 -2 -2 1 + 1495 472 13 -0.834 62.98029 58.34420 35.34278 0 0 1 + 1496 472 14 0.417 62.45371 58.26151 36.13783 0 0 1 + 1497 472 14 0.417 63.83636 58.64077 35.65169 0 0 1 + 1498 473 13 -0.834 63.44584 56.74146 44.14484 0 1 -2 + 1499 473 14 0.417 64.13590 56.53036 44.77371 0 1 -2 + 1500 473 14 0.417 62.70665 57.02149 44.68470 0 1 -2 + 1501 474 13 -0.834 44.05905 56.56929 51.60681 1 0 -1 + 1502 474 14 0.417 43.57850 56.15764 52.32504 1 0 -1 + 1503 474 14 0.417 43.90344 55.99747 50.85512 1 0 -1 + 1504 475 13 -0.834 37.49588 59.31379 39.05252 0 0 0 + 1505 475 14 0.417 37.07904 58.45297 39.09112 0 0 0 + 1506 475 14 0.417 37.58867 59.49374 38.11696 0 0 0 + 1507 476 13 -0.834 54.75747 41.52122 56.48609 -1 1 0 + 1508 476 14 0.417 54.79987 42.39714 56.86981 -1 1 0 + 1509 476 14 0.417 54.80582 41.67034 55.54179 -1 1 0 + 1510 477 13 -0.834 42.91665 58.39379 47.91495 1 0 0 + 1511 477 14 0.417 43.70923 58.91951 47.80683 1 0 0 + 1512 477 14 0.417 42.28811 58.98861 48.32409 1 0 0 + 1513 478 13 -0.834 60.63731 64.78822 56.03697 -2 1 -1 + 1514 478 14 0.417 60.86485 63.91302 56.35082 -2 1 -1 + 1515 478 14 0.417 60.50973 65.30321 56.83369 -2 1 -1 + 1516 479 13 -0.834 52.85180 54.69512 43.09842 0 0 1 + 1517 479 14 0.417 52.31485 55.13373 42.43846 0 0 1 + 1518 479 14 0.417 53.08000 53.85428 42.70200 0 0 1 + 1519 480 13 -0.834 51.49497 54.97356 38.95012 -2 1 -1 + 1520 480 14 0.417 50.77717 54.34090 38.97811 -2 1 -1 + 1521 480 14 0.417 51.51597 55.35169 39.82923 -2 1 -1 + 1522 481 13 -0.834 40.46924 62.02458 56.36341 1 0 -1 + 1523 481 14 0.417 40.45814 61.65439 55.48076 1 0 -1 + 1524 481 14 0.417 40.81799 62.90856 56.24853 1 0 -1 + 1525 482 13 -0.834 52.26692 56.29032 45.24820 0 2 1 + 1526 482 14 0.417 51.65227 56.79794 44.71834 0 2 1 + 1527 482 14 0.417 52.43092 55.49973 44.73408 0 2 1 + 1528 483 13 -0.834 53.46372 44.63556 52.39623 -1 1 1 + 1529 483 14 0.417 53.51664 45.03502 53.26448 -1 1 1 + 1530 483 14 0.417 54.08491 45.13343 51.86474 -1 1 1 + 1531 484 13 -0.834 42.90202 49.87822 40.32919 0 2 1 + 1532 484 14 0.417 42.40392 49.63281 41.10889 0 2 1 + 1533 484 14 0.417 42.31302 50.45172 39.83885 0 2 1 + 1534 485 13 -0.834 43.07357 64.57931 39.44006 2 1 1 + 1535 485 14 0.417 42.79300 64.80186 38.55237 2 1 1 + 1536 485 14 0.417 43.26869 65.42268 39.84860 2 1 1 + 1537 486 13 -0.834 38.86691 42.35197 55.12826 1 1 -1 + 1538 486 14 0.417 38.06621 42.87541 55.16185 1 1 -1 + 1539 486 14 0.417 39.52681 42.89488 55.55954 1 1 -1 + 1540 487 13 -0.834 59.15412 47.19863 55.46904 0 -1 0 + 1541 487 14 0.417 59.83963 46.99833 56.10636 0 -1 0 + 1542 487 14 0.417 58.74433 46.35364 55.28381 0 -1 0 + 1543 488 13 -0.834 52.12071 45.94110 44.23903 1 1 0 + 1544 488 14 0.417 51.89927 45.05144 44.51416 1 1 0 + 1545 488 14 0.417 52.26697 45.87115 43.29566 1 1 0 + 1546 489 13 -0.834 41.73140 52.23741 31.27732 0 0 1 + 1547 489 14 0.417 40.84403 52.55314 31.44796 0 0 1 + 1548 489 14 0.417 41.81503 52.26011 30.32405 0 0 1 + 1549 490 13 -0.834 38.46034 66.01701 52.27886 1 0 -1 + 1550 490 14 0.417 39.39276 66.02392 52.49517 1 0 -1 + 1551 490 14 0.417 38.11246 66.80769 52.69121 1 0 -1 + 1552 491 13 -0.834 42.13838 67.12262 54.88509 0 0 -3 + 1553 491 14 0.417 42.22460 67.38235 53.96784 0 0 -3 + 1554 491 14 0.417 42.96673 67.38388 55.28736 0 0 -3 + 1555 492 13 -0.834 37.89607 66.86351 46.16867 -1 -1 -1 + 1556 492 14 0.417 38.03129 66.98073 47.10899 -1 -1 -1 + 1557 492 14 0.417 38.75367 66.60168 45.83369 -1 -1 -1 + 1558 493 13 -0.834 40.37538 58.21424 30.88318 0 -1 0 + 1559 493 14 0.417 41.23010 58.63566 30.79307 0 -1 0 + 1560 493 14 0.417 40.45502 57.40101 30.38463 0 -1 0 + 1561 494 13 -0.834 54.56531 48.85249 32.17940 1 -2 2 + 1562 494 14 0.417 54.90082 48.98086 31.29216 1 -2 2 + 1563 494 14 0.417 54.03604 49.63141 32.35086 1 -2 2 + 1564 495 13 -0.834 63.56488 49.70113 37.88594 0 -1 1 + 1565 495 14 0.417 63.93261 49.40780 37.05228 0 -1 1 + 1566 495 14 0.417 63.98151 50.54765 38.04739 0 -1 1 + 1567 496 13 -0.834 39.26126 54.76920 54.71493 2 -1 2 + 1568 496 14 0.417 38.75402 55.21237 54.03483 2 -1 2 + 1569 496 14 0.417 38.67139 54.73109 55.46781 2 -1 2 + 1570 497 13 -0.834 42.78607 47.20625 49.30057 2 -1 0 + 1571 497 14 0.417 42.93670 46.34815 48.90404 2 -1 0 + 1572 497 14 0.417 43.53800 47.33917 49.87780 2 -1 0 + 1573 498 13 -0.834 59.99490 55.30114 50.55687 0 1 -1 + 1574 498 14 0.417 60.84158 55.66821 50.81111 0 1 -1 + 1575 498 14 0.417 59.38335 56.03363 50.63237 0 1 -1 + 1576 499 13 -0.834 57.95276 49.30660 54.37087 1 -1 -1 + 1577 499 14 0.417 57.34184 49.29544 55.10769 1 -1 -1 + 1578 499 14 0.417 58.55272 48.58151 54.54557 1 -1 -1 + 1579 500 13 -0.834 43.43041 64.04345 57.10111 1 -1 -1 + 1580 500 14 0.417 43.03742 64.07155 30.60210 1 -1 0 + 1581 500 14 0.417 44.26016 64.51104 29.82515 1 -1 0 + 1582 501 13 -0.834 40.71066 57.82778 50.85579 1 -1 -1 + 1583 501 14 0.417 41.04411 57.83612 51.75299 1 -1 -1 + 1584 501 14 0.417 40.96886 58.67633 50.49590 1 -1 -1 + 1585 502 13 -0.834 61.21331 60.53661 39.63578 1 -1 0 + 1586 502 14 0.417 61.87151 61.23113 39.61011 1 -1 0 + 1587 502 14 0.417 61.32085 60.13583 40.49837 1 -1 0 + 1588 503 13 -0.834 43.54081 65.33296 49.47114 1 -1 -1 + 1589 503 14 0.417 42.67637 65.41138 49.06762 1 -1 -1 + 1590 503 14 0.417 43.36562 64.99829 50.35065 1 -1 -1 + 1591 504 13 -0.834 50.27329 53.06087 30.87109 -1 0 1 + 1592 504 14 0.417 50.38769 53.42204 29.99204 -1 0 1 + 1593 504 14 0.417 50.86354 53.57620 31.42092 -1 0 1 + 1594 505 13 -0.834 40.29157 66.01889 32.67757 0 -1 0 + 1595 505 14 0.417 40.18198 66.27998 31.76320 0 -1 0 + 1596 505 14 0.417 39.39873 65.90460 33.00317 0 -1 0 + 1597 506 13 -0.834 48.15372 67.97019 44.25255 1 -1 1 + 1598 506 14 0.417 47.34263 67.52534 44.49854 1 -1 1 + 1599 506 14 0.417 47.87159 41.31478 43.68328 1 0 1 + 1600 507 13 -0.834 53.38019 63.98437 38.13827 0 0 -1 + 1601 507 14 0.417 54.19463 63.69976 37.72362 0 0 -1 + 1602 507 14 0.417 53.59582 64.82739 38.53711 0 0 -1 + 1603 508 13 -0.834 40.87597 58.12305 53.50808 0 0 0 + 1604 508 14 0.417 40.17916 58.26636 54.14852 0 0 0 + 1605 508 14 0.417 41.66044 58.48234 53.92256 0 0 0 + 1606 509 13 -0.834 38.19887 52.28056 36.30714 2 0 -1 + 1607 509 14 0.417 38.20463 53.19038 36.60452 2 0 -1 + 1608 509 14 0.417 38.09924 52.33929 35.35695 2 0 -1 + 1609 510 13 -0.834 49.63883 57.32410 43.72359 0 -1 0 + 1610 510 14 0.417 49.72446 58.17232 43.28833 0 -1 0 + 1611 510 14 0.417 48.76183 57.33851 44.10688 0 -1 0 + 1612 511 13 -0.834 42.58791 59.61362 29.86455 1 0 0 + 1613 511 14 0.417 43.07246 58.91969 56.78877 1 0 -1 + 1614 511 14 0.417 42.69535 60.38141 56.67447 1 0 -1 + 1615 512 13 -0.834 50.76111 60.95449 46.98165 -1 0 -1 + 1616 512 14 0.417 50.90477 61.15450 47.90663 -1 0 -1 + 1617 512 14 0.417 50.20825 61.66875 46.66473 -1 0 -1 + 1618 513 13 -0.834 43.18406 55.61939 48.08539 1 0 0 + 1619 513 14 0.417 43.11229 56.55752 47.90932 1 0 0 + 1620 513 14 0.417 44.01330 55.36231 47.68228 1 0 0 + 1621 514 13 -0.834 54.67377 64.76817 41.62522 1 0 1 + 1622 514 14 0.417 54.39407 65.19031 40.81294 1 0 1 + 1623 514 14 0.417 55.29742 65.38243 42.01250 1 0 1 + 1624 515 13 -0.834 53.87383 68.12810 51.72031 0 -1 0 + 1625 515 14 0.417 53.06918 41.24938 51.55887 0 0 0 + 1626 515 14 0.417 53.74278 67.72971 52.58074 0 -1 0 + 1627 516 13 -0.834 38.24785 41.26767 33.50598 2 0 0 + 1628 516 14 0.417 38.16490 67.75301 33.15337 2 -1 0 + 1629 516 14 0.417 37.95757 41.83753 32.79377 2 0 0 + 1630 517 13 -0.834 47.35008 61.96125 42.94580 2 -2 0 + 1631 517 14 0.417 47.46077 62.90828 43.03015 2 -2 0 + 1632 517 14 0.417 47.09087 61.83022 42.03373 2 -2 0 + 1633 518 13 -0.834 40.55210 54.00820 41.89137 1 -1 1 + 1634 518 14 0.417 39.80099 54.24986 41.34946 1 -1 1 + 1635 518 14 0.417 40.19429 53.40377 42.54166 1 -1 1 + 1636 519 13 -0.834 57.17705 64.40362 55.44286 1 -1 -1 + 1637 519 14 0.417 56.34510 64.78670 55.72097 1 -1 -1 + 1638 519 14 0.417 57.64987 65.12814 55.03330 1 -1 -1 + 1639 520 13 -0.834 41.86955 59.84132 42.65268 0 -1 1 + 1640 520 14 0.417 41.72011 59.11980 43.26367 0 -1 1 + 1641 520 14 0.417 42.24995 60.53605 43.19017 0 -1 1 + 1642 521 13 -0.834 61.62566 57.26645 46.18447 0 -1 -1 + 1643 521 14 0.417 60.68119 57.41642 46.22577 0 -1 -1 + 1644 521 14 0.417 61.98987 57.84356 46.85569 0 -1 -1 + 1645 522 13 -0.834 46.82701 65.68647 41.03579 0 0 0 + 1646 522 14 0.417 46.01385 65.85266 41.51264 0 0 0 + 1647 522 14 0.417 47.44009 65.38297 41.70531 0 0 0 + 1648 523 13 -0.834 54.12960 45.94549 32.81485 0 0 1 + 1649 523 14 0.417 53.25962 45.65636 32.53955 0 0 1 + 1650 523 14 0.417 54.18942 46.85072 32.50950 0 0 1 + 1651 524 13 -0.834 43.71268 59.97805 32.34985 1 1 0 + 1652 524 14 0.417 43.46300 59.27568 32.95033 1 1 0 + 1653 524 14 0.417 42.94131 60.10757 31.79808 1 1 0 + 1654 525 13 -0.834 50.10604 48.47250 49.62054 1 0 -2 + 1655 525 14 0.417 50.96037 48.77303 49.31064 1 0 -2 + 1656 525 14 0.417 50.19320 48.44287 50.57331 1 0 -2 + 1657 526 13 -0.834 54.68660 60.38920 43.62499 0 0 0 + 1658 526 14 0.417 54.62862 59.85089 42.83561 0 0 0 + 1659 526 14 0.417 53.78667 60.44045 43.94712 0 0 0 + 1660 527 13 -0.834 56.35115 44.75736 40.87552 0 -1 -1 + 1661 527 14 0.417 56.99705 44.99197 41.54186 0 -1 -1 + 1662 527 14 0.417 55.55387 44.56808 41.37024 0 -1 -1 + 1663 528 13 -0.834 48.77009 62.36934 40.44473 0 -1 0 + 1664 528 14 0.417 49.30266 62.60520 41.20432 0 -1 0 + 1665 528 14 0.417 49.04689 62.97756 39.75939 0 -1 0 + 1666 529 13 -0.834 45.88757 58.55209 41.94547 0 1 0 + 1667 529 14 0.417 46.76719 58.27665 42.20365 0 1 0 + 1668 529 14 0.417 45.35604 57.75963 42.02128 0 1 0 + 1669 530 13 -0.834 39.44116 52.22097 43.65725 1 0 2 + 1670 530 14 0.417 39.30570 52.06689 44.59221 1 0 2 + 1671 530 14 0.417 38.61744 52.60378 43.35530 1 0 2 + 1672 531 13 -0.834 43.95976 66.73852 41.23250 1 0 1 + 1673 531 14 0.417 44.64454 67.13772 40.69588 1 0 1 + 1674 531 14 0.417 43.40678 67.47232 41.50081 1 0 1 + 1675 532 13 -0.834 62.99634 65.50241 54.70446 0 -1 -1 + 1676 532 14 0.417 63.58398 64.98613 55.25617 0 -1 -1 + 1677 532 14 0.417 62.12519 65.14960 54.88585 0 -1 -1 + 1678 533 13 -0.834 62.92898 53.27582 44.77167 0 0 0 + 1679 533 14 0.417 62.08998 53.60880 45.09018 0 0 0 + 1680 533 14 0.417 62.85751 52.32504 44.85618 0 0 0 + 1681 534 13 -0.834 63.31201 43.08081 48.29805 -1 0 -1 + 1682 534 14 0.417 63.01276 42.23705 47.95930 -1 0 -1 + 1683 534 14 0.417 63.67142 43.53221 47.53431 -1 0 -1 + 1684 535 13 -0.834 47.11867 63.34781 55.06249 0 0 -1 + 1685 535 14 0.417 47.19267 64.30022 55.00160 0 0 -1 + 1686 535 14 0.417 46.22495 63.15783 54.77716 0 0 -1 + 1687 536 13 -0.834 60.37216 67.91341 52.27568 -1 0 0 + 1688 536 14 0.417 61.05051 68.14950 52.90839 -1 0 0 + 1689 536 14 0.417 60.81546 67.93922 51.42771 -1 0 0 + 1690 537 13 -0.834 60.04315 43.26291 35.25445 -1 1 1 + 1691 537 14 0.417 60.42501 44.05815 35.62593 -1 1 1 + 1692 537 14 0.417 60.79709 42.72574 35.01102 -1 1 1 + 1693 538 13 -0.834 53.03851 55.52589 47.75769 0 0 -1 + 1694 538 14 0.417 53.93635 55.46537 47.43136 0 0 -1 + 1695 538 14 0.417 52.51527 55.73342 46.98347 0 0 -1 + 1696 539 13 -0.834 37.91895 50.43697 56.37325 0 0 0 + 1697 539 14 0.417 37.51622 49.56884 56.35299 0 0 0 + 1698 539 14 0.417 38.37591 50.50915 55.53527 0 0 0 + 1699 540 13 -0.834 50.50006 63.56852 38.27177 1 1 0 + 1700 540 14 0.417 50.22462 63.18436 37.43944 1 1 0 + 1701 540 14 0.417 51.44083 63.71275 38.16986 1 1 0 + 1702 541 13 -0.834 49.44600 43.95446 42.01861 0 0 1 + 1703 541 14 0.417 49.59639 44.80378 41.60354 0 0 1 + 1704 541 14 0.417 49.73882 44.07372 42.92211 0 0 1 + 1705 542 13 -0.834 50.98365 47.23031 39.51901 1 0 1 + 1706 542 14 0.417 51.18743 48.09631 39.16579 1 0 1 + 1707 542 14 0.417 50.03928 47.13635 39.39410 1 0 1 + 1708 543 13 -0.834 45.54625 60.20130 44.30493 0 0 2 + 1709 543 14 0.417 46.27140 60.62480 43.84553 0 0 2 + 1710 543 14 0.417 45.09838 59.69256 43.62904 0 0 2 + 1711 544 13 -0.834 60.48207 53.69772 48.42686 0 0 1 + 1712 544 14 0.417 60.03677 54.31581 49.00644 0 0 1 + 1713 544 14 0.417 59.89364 52.94407 48.38216 0 0 1 + 1714 545 13 -0.834 63.04952 45.83903 48.97963 -1 1 1 + 1715 545 14 0.417 63.88202 45.63831 49.40729 -1 1 1 + 1716 545 14 0.417 62.76408 45.00498 48.60667 -1 1 1 + 1717 546 13 -0.834 40.62890 44.95273 52.60003 2 -1 -2 + 1718 546 14 0.417 41.29110 45.55853 52.26721 2 -1 -2 + 1719 546 14 0.417 40.33885 45.34348 53.42431 2 -1 -2 + 1720 547 13 -0.834 39.91743 46.12102 55.72693 -1 1 -1 + 1721 547 14 0.417 40.70381 45.68274 56.05216 -1 1 -1 + 1722 547 14 0.417 39.19323 45.65943 56.14967 -1 1 -1 + 1723 548 13 -0.834 42.06829 45.07566 41.79962 0 0 -1 + 1724 548 14 0.417 41.61985 45.91039 41.93531 0 0 -1 + 1725 548 14 0.417 41.86481 44.56390 42.58253 0 0 -1 + 1726 549 13 -0.834 44.17588 49.40877 37.86902 1 1 0 + 1727 549 14 0.417 43.85185 49.35470 38.76808 1 1 0 + 1728 549 14 0.417 43.95346 48.56183 37.48242 1 1 0 + 1729 550 13 -0.834 52.64793 63.92130 45.68237 0 1 0 + 1730 550 14 0.417 52.63502 62.96908 45.58561 0 1 0 + 1731 550 14 0.417 52.43571 64.07178 46.60356 0 1 0 + 1732 551 13 -0.834 51.57615 43.64864 38.83377 1 1 0 + 1733 551 14 0.417 51.74260 43.03820 38.11551 1 1 0 + 1734 551 14 0.417 52.20192 44.35945 38.69449 1 1 0 + 1735 552 13 -0.834 62.02099 63.12241 47.73587 0 1 0 + 1736 552 14 0.417 61.17806 62.75352 47.99973 0 1 0 + 1737 552 14 0.417 62.48263 62.39363 47.32116 0 1 0 + 1738 553 13 -0.834 38.41497 51.40373 50.93034 1 1 0 + 1739 553 14 0.417 37.60807 51.12879 50.49494 1 1 0 + 1740 553 14 0.417 38.99796 51.65996 50.21571 1 1 0 + 1741 554 13 -0.834 51.96339 44.25313 49.02477 0 0 0 + 1742 554 14 0.417 52.81680 44.60151 49.28274 0 0 0 + 1743 554 14 0.417 52.16570 43.57682 48.37831 0 0 0 + 1744 555 13 -0.834 43.58422 51.42052 49.88959 0 1 -1 + 1745 555 14 0.417 42.74054 51.00549 50.06897 0 1 -1 + 1746 555 14 0.417 44.20160 50.69175 49.82657 0 1 -1 + 1747 556 13 -0.834 52.39836 53.43568 49.29165 1 0 -1 + 1748 556 14 0.417 51.88756 52.90169 48.68323 1 0 -1 + 1749 556 14 0.417 52.64451 54.20889 48.78391 1 0 -1 + 1750 557 13 -0.834 57.76885 46.61656 49.32842 0 1 0 + 1751 557 14 0.417 57.83718 46.26991 48.43879 0 1 0 + 1752 557 14 0.417 58.65246 46.53329 49.68694 0 1 0 + 1753 558 13 -0.834 59.20868 56.75211 36.79427 0 1 -1 + 1754 558 14 0.417 59.74268 56.20033 36.22276 0 1 -1 + 1755 558 14 0.417 58.75094 56.13459 37.36470 0 1 -1 + 1756 559 13 -0.834 51.74055 42.45875 36.24184 0 1 1 + 1757 559 14 0.417 51.04879 41.79745 36.22260 0 1 1 + 1758 559 14 0.417 52.52794 41.99055 35.96429 0 1 1 + 1759 560 13 -0.834 56.37631 67.32150 33.05439 -1 0 1 + 1760 560 14 0.417 56.52797 66.39716 33.25152 -1 0 1 + 1761 560 14 0.417 56.88845 67.79399 33.71068 -1 0 1 + 1762 561 13 -0.834 54.61713 62.99597 56.69158 0 1 -1 + 1763 561 14 0.417 54.59393 63.94258 56.83172 0 1 -1 + 1764 561 14 0.417 54.12883 62.86158 55.87934 0 1 -1 + 1765 562 13 -0.834 59.12420 67.78462 34.49420 0 -1 1 + 1766 562 14 0.417 59.61921 67.94665 33.69111 0 -1 1 + 1767 562 14 0.417 59.22686 41.21594 35.00547 0 0 1 + 1768 563 13 -0.834 63.35827 53.14027 38.43168 -1 0 0 + 1769 563 14 0.417 62.48186 53.05933 38.05538 -1 0 0 + 1770 563 14 0.417 63.87715 53.55740 37.74392 -1 0 0 + 1771 564 13 -0.834 50.05518 64.80335 44.94078 1 0 -2 + 1772 564 14 0.417 50.16173 65.71408 44.66608 1 0 -2 + 1773 564 14 0.417 50.94818 64.48993 45.08424 1 0 -2 + 1774 565 13 -0.834 61.91076 61.67486 44.00650 0 -3 0 + 1775 565 14 0.417 61.40514 60.86646 44.09077 0 -3 0 + 1776 565 14 0.417 62.58390 61.60857 44.68380 0 -3 0 + 1777 566 13 -0.834 61.53884 41.33016 50.02212 -1 0 -1 + 1778 566 14 0.417 61.75835 68.35836 49.15591 -1 -1 -1 + 1779 566 14 0.417 62.19075 42.01255 50.18215 -1 0 -1 + 1780 567 13 -0.834 54.81641 49.94673 49.66324 0 -1 -1 + 1781 567 14 0.417 54.81533 50.72359 50.22249 0 -1 -1 + 1782 567 14 0.417 53.94410 49.93341 49.26932 0 -1 -1 + 1783 568 13 -0.834 60.68933 64.00249 53.56679 -1 -1 -1 + 1784 568 14 0.417 60.72666 63.10922 53.90872 -1 -1 -1 + 1785 568 14 0.417 60.37485 64.52808 54.30238 -1 -1 -1 + 1786 569 13 -0.834 55.51605 42.60469 53.96890 0 -1 0 + 1787 569 14 0.417 55.82084 42.66633 53.06360 0 -1 0 + 1788 569 14 0.417 54.99565 43.39708 54.10137 0 -1 0 + 1789 570 13 -0.834 43.79008 68.23755 52.31171 2 -1 1 + 1790 570 14 0.417 43.47705 41.06627 51.42954 2 0 1 + 1791 570 14 0.417 44.72624 68.07073 52.20206 2 -1 1 + 1792 571 13 -0.834 40.19615 44.94623 32.57234 0 0 1 + 1793 571 14 0.417 40.90940 45.49825 32.25173 0 0 1 + 1794 571 14 0.417 40.42796 44.75889 33.48196 0 0 1 + 1795 572 13 -0.834 51.93921 56.60019 36.60262 -1 0 1 + 1796 572 14 0.417 51.78399 56.35099 37.51368 -1 0 1 + 1797 572 14 0.417 51.06469 56.74242 36.24039 -1 0 1 + 1798 573 13 -0.834 61.66916 50.48338 53.29865 -1 0 -2 + 1799 573 14 0.417 61.63036 50.41309 54.25248 -1 0 -2 + 1800 573 14 0.417 60.77283 50.69388 53.03687 -1 0 -2 + 1801 574 13 -0.834 51.74160 54.87485 56.16871 0 -1 0 + 1802 574 14 0.417 50.91429 55.26706 56.44795 0 -1 0 + 1803 574 14 0.417 51.91124 55.25931 55.30869 0 -1 0 + 1804 575 13 -0.834 40.85698 68.18248 30.13155 1 -1 0 + 1805 575 14 0.417 41.30492 67.87357 56.71541 1 -1 -1 + 1806 575 14 0.417 41.55175 41.19073 30.66952 1 0 0 + 1807 576 13 -0.834 50.89809 58.89690 54.50288 -1 0 0 + 1808 576 14 0.417 50.06229 58.64352 54.89466 -1 0 0 + 1809 576 14 0.417 51.37024 59.33797 55.20914 -1 0 0 + 1810 577 13 -0.834 58.37524 67.95427 49.91095 0 1 0 + 1811 577 14 0.417 57.83519 41.29391 50.25604 0 2 0 + 1812 577 14 0.417 59.26942 68.19076 50.15744 0 1 0 + 1813 578 13 -0.834 51.40785 46.48357 30.68744 1 0 1 + 1814 578 14 0.417 52.21871 45.99275 30.55389 1 0 1 + 1815 578 14 0.417 50.76683 45.82189 30.94725 1 0 1 + 1816 579 13 -0.834 57.04032 43.52295 36.91237 0 0 0 + 1817 579 14 0.417 56.97310 44.35969 36.45239 0 0 0 + 1818 579 14 0.417 57.91622 43.53095 37.29833 0 0 0 + 1819 580 13 -0.834 48.05479 47.92450 33.11226 0 0 1 + 1820 580 14 0.417 47.68291 48.79527 32.97186 0 0 1 + 1821 580 14 0.417 48.92592 48.09081 33.47242 0 0 1 + 1822 581 13 -0.834 52.31083 59.89064 56.95945 1 -2 -1 + 1823 581 14 0.417 51.77727 60.32576 30.25310 1 -2 0 + 1824 581 14 0.417 52.84806 60.59010 56.58744 1 -2 -1 + 1825 582 13 -0.834 49.28190 53.14534 38.62511 0 0 1 + 1826 582 14 0.417 48.56647 53.70668 38.92395 0 0 1 + 1827 582 14 0.417 48.86634 52.52585 38.02526 0 0 1 + 1828 583 13 -0.834 48.15214 51.90611 34.43290 2 0 0 + 1829 583 14 0.417 48.57405 51.97443 33.57642 2 0 0 + 1830 583 14 0.417 47.22654 51.76503 34.23389 2 0 0 + 1831 584 13 -0.834 61.27546 54.09168 30.34511 0 1 1 + 1832 584 14 0.417 61.26898 53.84689 31.27046 0 1 1 + 1833 584 14 0.417 62.02427 53.62196 29.97785 0 1 1 + 1834 585 13 -0.834 47.15916 50.47662 53.78471 0 -1 0 + 1835 585 14 0.417 47.32648 50.93912 54.60588 0 -1 0 + 1836 585 14 0.417 46.29671 50.78520 53.50690 0 -1 0 + 1837 586 13 -0.834 58.58091 63.09753 49.23949 0 -1 1 + 1838 586 14 0.417 59.43607 63.50227 49.38484 0 -1 1 + 1839 586 14 0.417 58.76326 62.34843 48.67219 0 -1 1 + 1840 587 13 -0.834 55.82082 49.65937 30.11648 0 1 1 + 1841 587 14 0.417 56.52757 49.92139 30.70647 0 1 1 + 1842 587 14 0.417 55.68213 50.42183 56.92602 0 1 0 + 1843 588 13 -0.834 63.79581 52.53565 53.17702 0 -2 1 + 1844 588 14 0.417 36.89869 52.41207 52.35479 1 -2 1 + 1845 588 14 0.417 63.12882 51.84908 53.17487 0 -2 1 + 1846 589 13 -0.834 58.30874 56.36537 43.52715 0 0 3 + 1847 589 14 0.417 58.58025 56.80205 44.33452 0 0 3 + 1848 589 14 0.417 57.40732 56.09029 43.69457 0 0 3 + 1849 590 13 -0.834 38.42652 61.06904 33.48425 0 -2 -1 + 1850 590 14 0.417 39.08604 61.75763 33.56856 0 -2 -1 + 1851 590 14 0.417 38.90648 60.25628 33.64334 0 -2 -1 + 1852 591 13 -0.834 46.61439 51.58566 41.81121 1 -1 0 + 1853 591 14 0.417 46.97646 51.37067 42.67082 1 -1 0 + 1854 591 14 0.417 46.41089 50.73724 41.41750 1 -1 0 + 1855 592 13 -0.834 60.01555 43.31814 42.71405 1 0 1 + 1856 592 14 0.417 60.52150 42.79903 43.33920 1 0 1 + 1857 592 14 0.417 59.90024 42.74003 41.95989 1 0 1 + 1858 593 13 -0.834 44.88246 59.34852 51.75271 1 0 -1 + 1859 593 14 0.417 45.75263 59.37400 52.15069 1 0 -1 + 1860 593 14 0.417 44.67274 58.41644 51.69374 1 0 -1 + 1861 594 13 -0.834 58.22051 53.10280 51.15729 0 -1 0 + 1862 594 14 0.417 58.53381 52.60654 51.91346 0 -1 0 + 1863 594 14 0.417 58.92607 53.72100 50.96688 0 -1 0 + 1864 595 13 -0.834 52.85332 67.67658 42.66705 0 -1 0 + 1865 595 14 0.417 53.29462 67.40699 41.86157 0 -1 0 + 1866 595 14 0.417 53.28090 67.16860 43.35652 0 -1 0 + 1867 596 13 -0.834 60.42773 53.38162 37.56585 0 0 1 + 1868 596 14 0.417 60.55482 53.97513 38.30601 0 0 1 + 1869 596 14 0.417 59.53313 53.05721 37.66924 0 0 1 + 1870 597 13 -0.834 56.52028 65.87791 50.38146 0 0 1 + 1871 597 14 0.417 56.94337 66.73645 50.39389 0 0 1 + 1872 597 14 0.417 57.02985 65.35034 50.99649 0 0 1 + 1873 598 13 -0.834 54.80064 62.49993 33.68680 1 0 1 + 1874 598 14 0.417 55.58425 61.96146 33.79744 1 0 1 + 1875 598 14 0.417 55.10591 63.27334 33.21259 1 0 1 + 1876 599 13 -0.834 44.11783 61.90196 34.52932 1 1 -1 + 1877 599 14 0.417 44.98641 61.86349 34.92975 1 1 -1 + 1878 599 14 0.417 44.21923 61.44892 33.69223 1 1 -1 + 1879 600 13 -0.834 47.64060 51.80694 44.33090 -1 -1 0 + 1880 600 14 0.417 48.33775 51.24158 44.66345 -1 -1 0 + 1881 600 14 0.417 47.96940 52.69619 44.46262 -1 -1 0 + 1882 601 13 -0.834 56.93644 64.17109 32.73010 0 -2 0 + 1883 601 14 0.417 57.35484 63.79547 31.95543 0 -2 0 + 1884 601 14 0.417 57.46604 63.85913 33.46389 0 -2 0 + 1885 602 13 -0.834 40.19928 60.95715 53.68963 1 0 -1 + 1886 602 14 0.417 41.08822 60.76154 53.39341 1 0 -1 + 1887 602 14 0.417 39.80336 61.43545 52.96114 1 0 -1 + 1888 603 13 -0.834 56.02366 41.52320 41.07986 0 1 0 + 1889 603 14 0.417 55.42766 41.48842 40.33165 0 1 0 + 1890 603 14 0.417 55.93467 42.41489 41.41631 0 1 0 + 1891 604 13 -0.834 52.35261 67.43639 29.83633 -1 0 0 + 1892 604 14 0.417 53.08703 67.77971 56.69878 -1 0 -1 + 1893 604 14 0.417 51.97673 68.20568 30.26426 -1 0 0 + 1894 605 13 -0.834 51.14102 49.90060 37.90539 1 0 1 + 1895 605 14 0.417 51.41236 49.08269 37.48865 1 0 1 + 1896 605 14 0.417 50.32915 50.13989 37.45830 1 0 1 + 1897 606 13 -0.834 48.40753 57.18555 40.43062 0 0 0 + 1898 606 14 0.417 47.74030 57.19949 39.74445 0 0 0 + 1899 606 14 0.417 48.68357 58.09814 40.51553 0 0 0 + 1900 607 13 -0.834 38.43185 54.52830 40.23522 1 -2 1 + 1901 607 14 0.417 37.76601 54.24704 40.86274 1 -2 1 + 1902 607 14 0.417 37.95756 54.62565 39.40951 1 -2 1 + 1903 608 13 -0.834 52.97765 52.38562 41.57118 0 0 0 + 1904 608 14 0.417 52.16773 52.00413 41.23247 0 0 0 + 1905 608 14 0.417 53.62059 51.67937 41.50742 0 0 0 + 1906 609 13 -0.834 52.82978 61.35779 35.40768 0 1 -2 + 1907 609 14 0.417 53.63682 61.71145 35.03372 0 1 -2 + 1908 609 14 0.417 53.10766 60.57217 35.87865 0 1 -2 + 1909 610 13 -0.834 55.37636 43.79165 30.66790 0 0 0 + 1910 610 14 0.417 55.82860 43.25432 31.31827 0 0 0 + 1911 610 14 0.417 55.97415 44.52040 30.50110 0 0 0 + 1912 611 13 -0.834 37.90570 54.55715 45.50029 1 -2 -1 + 1913 611 14 0.417 37.12871 54.09851 45.18066 1 -2 -1 + 1914 611 14 0.417 38.24821 53.99402 46.19441 1 -2 -1 + 1915 612 13 -0.834 60.01324 50.96528 45.16358 1 1 0 + 1916 612 14 0.417 59.85669 51.13906 44.23539 1 1 0 + 1917 612 14 0.417 59.48415 50.19096 45.35532 1 1 0 + 1918 613 13 -0.834 38.84394 52.32942 30.93040 2 1 0 + 1919 613 14 0.417 38.51878 51.61086 30.38802 2 1 0 + 1920 613 14 0.417 38.41000 53.10831 30.58218 2 1 0 + 1921 614 13 -0.834 38.99542 61.66171 44.80992 1 0 2 + 1922 614 14 0.417 38.78488 60.74588 44.99207 1 0 2 + 1923 614 14 0.417 39.68427 61.62223 44.14648 1 0 2 + 1924 615 13 -0.834 57.70791 41.72720 55.47643 0 1 -2 + 1925 615 14 0.417 57.25844 41.36846 56.24163 0 1 -2 + 1926 615 14 0.417 57.00496 41.93588 54.86116 0 1 -2 + 1927 616 13 -0.834 58.08999 54.20225 35.53764 0 -1 0 + 1928 616 14 0.417 58.28608 53.46338 36.11372 0 -1 0 + 1929 616 14 0.417 57.15628 54.11553 35.34551 0 -1 0 + 1930 617 13 -0.834 53.05217 52.71850 54.07873 0 0 -1 + 1931 617 14 0.417 52.72353 53.45661 54.59199 0 0 -1 + 1932 617 14 0.417 52.69237 51.94509 54.51306 0 0 -1 + 1933 618 13 -0.834 49.92059 65.13477 35.13462 0 1 1 + 1934 618 14 0.417 50.86780 65.25694 35.19866 0 1 1 + 1935 618 14 0.417 49.79534 64.18846 35.20565 0 1 1 + 1936 619 13 -0.834 41.32410 62.50943 46.98364 1 -1 0 + 1937 619 14 0.417 40.63048 62.20572 46.39807 1 -1 0 + 1938 619 14 0.417 41.96090 61.79482 46.99226 1 -1 0 + 1939 620 13 -0.834 53.94559 67.39201 49.11860 0 0 0 + 1940 620 14 0.417 54.46912 66.60137 48.98810 0 0 0 + 1941 620 14 0.417 54.03461 67.58755 50.05138 0 0 0 + 1942 621 13 -0.834 62.73724 52.28919 56.37358 -2 0 0 + 1943 621 14 0.417 61.94239 51.76764 56.26203 -2 0 0 + 1944 621 14 0.417 63.44036 51.64333 56.44233 -2 0 0 + 1945 622 13 -0.834 40.38118 67.16060 39.18721 2 1 1 + 1946 622 14 0.417 41.33280 67.21360 39.09858 2 1 1 + 1947 622 14 0.417 40.05780 67.12713 38.28691 2 1 1 + 1948 623 13 -0.834 62.86517 42.00727 34.57539 -1 0 -1 + 1949 623 14 0.417 63.37239 42.81882 34.59420 -1 0 -1 + 1950 623 14 0.417 63.40838 41.39624 34.07760 -1 0 -1 + 1951 624 13 -0.834 45.52270 49.32960 34.34348 1 -1 1 + 1952 624 14 0.417 45.92383 49.19413 33.48500 1 -1 1 + 1953 624 14 0.417 45.24004 50.24407 34.33468 1 -1 1 + 1954 625 13 -0.834 61.03811 44.77668 56.49913 1 1 0 + 1955 625 14 0.417 60.72892 43.87199 56.45248 1 1 0 + 1956 625 14 0.417 60.93423 45.11202 55.60864 1 1 0 + 1957 626 13 -0.834 37.82896 51.65548 39.75440 0 1 1 + 1958 626 14 0.417 37.05574 52.05171 39.35268 0 1 1 + 1959 626 14 0.417 38.46628 52.36806 39.80236 0 1 1 + 1960 627 13 -0.834 57.87448 65.36125 35.56679 -1 -1 0 + 1961 627 14 0.417 58.45940 64.84211 35.01489 -1 -1 0 + 1962 627 14 0.417 58.01580 66.26448 35.28319 -1 -1 0 + 1963 628 13 -0.834 41.02352 64.37669 36.41484 0 0 1 + 1964 628 14 0.417 40.85775 63.95254 37.25679 0 0 1 + 1965 628 14 0.417 41.32667 63.66948 35.84545 0 0 1 + 1966 629 13 -0.834 48.62923 67.86173 41.06030 1 0 1 + 1967 629 14 0.417 48.15680 41.13844 41.58283 1 1 1 + 1968 629 14 0.417 47.94185 67.35115 40.63246 1 0 1 + 1969 630 13 -0.834 57.99331 55.69311 47.88478 1 2 0 + 1970 630 14 0.417 57.70999 55.65425 48.79826 1 2 0 + 1971 630 14 0.417 57.37284 55.13407 47.41709 1 2 0 + 1972 631 13 -0.834 48.67013 62.47689 45.75332 -1 -1 0 + 1973 631 14 0.417 49.00300 63.35392 45.56291 -1 -1 0 + 1974 631 14 0.417 48.17776 62.23177 44.96992 -1 -1 0 + 1975 632 13 -0.834 63.70160 54.96100 33.30497 -1 0 0 + 1976 632 14 0.417 64.21034 55.41699 32.63452 -1 0 0 + 1977 632 14 0.417 36.84822 54.18301 33.51151 0 0 0 + 1978 633 13 -0.834 61.71933 50.02843 40.52579 1 0 -1 + 1979 633 14 0.417 61.89605 49.89083 39.59516 1 0 -1 + 1980 633 14 0.417 61.20325 50.83404 40.55551 1 0 -1 + 1981 634 13 -0.834 49.51254 64.46386 53.41539 0 -1 -1 + 1982 634 14 0.417 48.93704 63.81647 53.00803 0 -1 -1 + 1983 634 14 0.417 49.96102 63.98252 54.11066 0 -1 -1 + 1984 635 13 -0.834 49.54405 44.64373 31.53722 1 2 1 + 1985 635 14 0.417 49.17415 44.45447 32.39954 1 2 1 + 1986 635 14 0.417 48.78808 44.87386 30.99705 1 2 1 + 1987 636 13 -0.834 55.54392 65.92737 37.61921 0 -1 -1 + 1988 636 14 0.417 56.11408 65.75233 38.36791 0 -1 -1 + 1989 636 14 0.417 56.12096 66.32174 36.96519 0 -1 -1 + 1990 637 13 -0.834 55.12269 51.83986 35.86341 1 0 1 + 1991 637 14 0.417 55.56426 51.26412 35.23910 1 0 1 + 1992 637 14 0.417 54.23658 51.93728 35.51477 1 0 1 + 1993 638 13 -0.834 55.63681 62.23759 37.50835 1 -1 0 + 1994 638 14 0.417 55.30920 61.35525 37.33403 1 -1 0 + 1995 638 14 0.417 56.23965 62.41667 36.78672 1 -1 0 + 1996 639 13 -0.834 39.91450 42.04260 35.59226 0 0 0 + 1997 639 14 0.417 39.72903 41.27571 36.13422 0 0 0 + 1998 639 14 0.417 39.23583 42.02933 34.91737 0 0 0 + 1999 640 13 -0.834 48.26433 59.84813 40.16126 0 1 0 + 2000 640 14 0.417 48.74870 60.67004 40.23938 0 1 0 + 2001 640 14 0.417 47.50743 60.06639 39.61748 0 1 0 + 2002 641 13 -0.834 57.35097 49.28414 48.37687 1 1 1 + 2003 641 14 0.417 57.35715 48.51028 48.94022 1 1 1 + 2004 641 14 0.417 56.55074 49.75049 48.61854 1 1 1 + +Velocities + + 1 -0.000671 -0.002823 0.003832 + 2 -0.001597 0.002405 -0.003777 + 3 0.005494 0.003807 -0.002300 + 4 -0.000077 0.004524 -0.000287 + 5 0.003116 -0.007135 -0.034325 + 6 -0.006676 0.004889 -0.001939 + 7 0.003499 -0.004774 0.000159 + 8 -0.003460 0.000694 0.000994 + 9 -0.000065 -0.001353 -0.002848 + 10 -0.001260 -0.002649 0.000699 + 11 -0.002820 -0.002457 -0.005671 + 12 0.005156 -0.005914 0.000984 + 13 -0.002342 -0.001592 0.004306 + 14 0.004397 -0.000231 0.003308 + 15 -0.003258 -0.000006 0.001838 + 16 -0.001637 -0.004429 0.003154 + 17 0.007073 -0.000472 -0.003331 + 18 -0.003380 -0.001390 0.005013 + 19 -0.011019 -0.005332 -0.010451 + 20 -0.005433 0.000844 0.004938 + 21 0.002988 0.000244 -0.009941 + 22 -0.003695 0.006546 -0.007678 + 23 0.009473 0.023276 0.019457 + 24 -0.010016 -0.024193 0.018017 + 25 0.004015 0.008726 -0.000397 + 26 -0.001741 -0.001861 0.007862 + 27 -0.009771 -0.011577 -0.005703 + 28 0.003573 0.006265 -0.005932 + 29 0.004789 0.001987 -0.004620 + 30 0.008858 -0.001064 -0.001455 + 31 -0.001403 0.000613 0.002330 + 32 -0.005808 -0.001620 0.000816 + 33 -0.004160 0.001188 -0.019638 + 34 -0.006899 0.006285 0.013256 + 35 0.000717 -0.000432 -0.006883 + 36 0.002110 0.002628 -0.004683 + 37 0.000765 -0.007298 0.000289 + 38 -0.000128 -0.002893 0.004065 + 39 -0.000411 -0.021741 0.010968 + 40 0.002858 0.000302 0.000042 + 41 0.014233 -0.004599 -0.004060 + 42 -0.001473 -0.003572 -0.006228 + 43 0.009129 -0.002755 0.001456 + 44 0.003931 0.000151 0.003472 + 45 0.001621 0.005391 -0.006087 + 46 -0.004269 -0.001973 0.002735 + 47 -0.006898 -0.001187 -0.003394 + 48 -0.008556 -0.000163 -0.001387 + 49 -0.000633 -0.001754 0.011460 + 50 0.004854 -0.002902 -0.005057 + 51 0.000678 0.003272 0.006218 + 52 0.006502 0.006365 -0.000215 + 53 0.005708 0.012368 0.002955 + 54 0.008627 -0.007839 0.003177 + 55 0.004394 0.000132 0.002346 + 56 -0.004641 0.009426 -0.005548 + 57 -0.004801 -0.024766 0.002851 + 58 -0.002703 0.001589 0.007521 + 59 0.023718 -0.006559 0.003743 + 60 -0.010013 -0.042894 -0.029745 + 61 0.016140 -0.000721 -0.001747 + 62 -0.004871 0.002439 0.001990 + 63 0.009632 0.007144 0.001203 + 64 -0.001150 0.001648 -0.003018 + 65 0.006658 -0.002268 0.006874 + 66 -0.002617 0.003321 0.002230 + 67 -0.000803 0.002802 0.003258 + 68 -0.000984 -0.001579 -0.001813 + 69 0.001316 0.000607 0.003431 + 70 -0.010901 0.000580 -0.004134 + 71 0.005370 -0.003909 0.013130 + 72 -0.012282 0.007114 -0.015100 + 73 0.004641 -0.007554 0.004302 + 74 0.017455 0.013344 0.004896 + 75 0.006200 0.026885 0.020665 + 76 -0.010372 0.000470 -0.005601 + 77 -0.003368 -0.004484 0.010962 + 78 0.012416 -0.004728 0.000719 + 79 -0.005789 0.005198 -0.007541 + 80 0.005480 -0.004049 0.003455 + 81 -0.004935 0.005839 -0.006405 + 82 0.001157 -0.011200 0.018491 + 83 -0.029013 -0.016935 0.021131 + 84 -0.020335 0.020972 0.006071 + 85 0.003304 0.007374 -0.005056 + 86 0.029227 0.010776 -0.013183 + 87 0.001651 0.006570 -0.002085 + 88 0.001533 -0.009172 0.007562 + 89 0.018153 -0.022223 0.015786 + 90 -0.010012 -0.004911 0.002561 + 91 0.000435 0.003941 -0.005468 + 92 0.003301 0.001183 -0.006999 + 93 0.006788 0.011331 -0.004427 + 94 0.001392 0.005663 -0.002907 + 95 -0.001849 -0.002229 -0.003422 + 96 -0.000820 0.005872 0.004561 + 97 -0.003264 0.002461 -0.009257 + 98 0.000160 0.016954 -0.015355 + 99 -0.006597 0.011858 0.000426 + 100 0.001816 -0.005854 -0.001317 + 101 -0.001936 -0.006103 0.018111 + 102 0.024621 -0.022735 -0.000704 + 103 -0.001102 0.008384 -0.003086 + 104 0.012559 0.004375 -0.000361 + 105 0.008377 0.014814 -0.037755 + 106 -0.002851 -0.000200 -0.000722 + 107 0.010701 0.006888 -0.007831 + 108 -0.008490 0.011514 0.009399 + 109 -0.001181 0.001853 0.002176 + 110 -0.018912 -0.023868 0.006706 + 111 -0.000415 -0.001525 0.005751 + 112 -0.001172 0.001329 -0.001270 + 113 -0.006700 -0.006243 -0.006459 + 114 0.000018 0.001429 0.001376 + 115 0.001269 0.002521 0.005249 + 116 -0.002179 0.015666 0.006861 + 117 -0.007158 0.000981 0.007353 + 118 0.001047 0.000840 -0.004404 + 119 0.000974 -0.012527 0.005053 + 120 0.026729 0.008884 -0.003350 + 121 0.001181 -0.004040 -0.002037 + 122 0.006556 -0.007438 0.002656 + 123 0.005056 -0.015002 -0.003727 + 124 -0.002704 -0.003683 -0.001021 + 125 0.025048 0.007258 0.008873 + 126 0.019645 -0.020824 -0.002539 + 127 0.000061 0.001072 0.002612 + 128 0.005132 0.013203 0.018763 + 129 0.033473 0.004804 0.018651 + 130 -0.003459 -0.000309 -0.001348 + 131 -0.008088 0.023660 0.011047 + 132 0.010962 0.031994 0.008711 + 133 0.000181 -0.002894 -0.001677 + 134 0.024049 -0.000711 -0.009405 + 135 0.018702 0.003422 -0.019522 + 136 -0.000836 -0.003270 -0.005700 + 137 0.012246 0.016524 0.001525 + 138 0.006270 -0.011288 0.002224 + 139 -0.005169 0.005097 -0.000688 + 140 -0.006982 0.003044 -0.001383 + 141 0.012227 0.012767 0.004047 + 142 -0.001169 0.006070 -0.007989 + 143 0.005451 0.002569 -0.009841 + 144 0.001825 -0.002822 -0.005341 + 145 0.000911 0.004242 -0.002026 + 146 0.012072 -0.001187 -0.010498 + 147 0.007366 0.005541 0.012099 + 148 0.009820 0.000588 0.001087 + 149 0.013758 0.005140 0.015262 + 150 0.015580 0.003311 0.013079 + 151 0.002031 0.000411 0.003403 + 152 -0.001996 0.003750 0.007387 + 153 0.000790 0.000281 -0.000919 + 154 -0.004168 0.001886 -0.004993 + 155 -0.011049 0.015294 0.001052 + 156 -0.012308 0.010348 -0.003128 + 157 -0.001609 -0.004040 -0.002294 + 158 -0.005715 -0.015529 -0.005700 + 159 0.014489 0.026653 0.004024 + 160 0.004070 0.000866 0.003373 + 161 0.004691 0.005062 0.002569 + 162 0.007082 -0.019961 -0.026174 + 163 0.005501 0.000902 -0.001325 + 164 0.007503 0.001448 -0.001472 + 165 0.013628 0.003649 -0.005952 + 166 -0.000639 0.003162 -0.007271 + 167 0.007342 -0.011001 -0.016849 + 168 -0.018400 -0.004772 0.020839 + 169 0.000214 -0.000386 0.002706 + 170 -0.005862 0.010449 -0.003793 + 171 -0.013612 0.011870 -0.006417 + 172 -0.005485 0.006465 0.005343 + 173 0.001788 0.008428 0.005641 + 174 -0.018354 0.029579 0.010717 + 175 0.002627 -0.000754 0.000071 + 176 -0.018080 0.018546 0.001794 + 177 0.006754 -0.000962 -0.007786 + 178 0.002343 0.002166 0.004945 + 179 -0.001724 0.003155 0.010761 + 180 0.010728 0.003441 0.001544 + 181 -0.000849 -0.002856 0.001461 + 182 0.009366 -0.003672 -0.001935 + 183 0.016615 -0.001746 0.005238 + 184 -0.002730 -0.000316 -0.004583 + 185 -0.014755 -0.011310 0.003338 + 186 0.005862 0.008235 -0.003200 + 187 -0.003189 -0.006285 0.009536 + 188 -0.005114 -0.007060 0.006450 + 189 -0.000516 -0.008757 0.009854 + 190 -0.000859 0.005266 0.001864 + 191 0.003108 -0.007021 0.009190 + 192 -0.015949 -0.002050 0.007021 + 193 -0.007008 0.002608 -0.004583 + 194 -0.020431 -0.004004 0.008047 + 195 -0.000364 0.001236 -0.011425 + 196 0.002420 0.006931 0.002031 + 197 0.007178 0.006129 0.009924 + 198 -0.005981 0.016623 -0.013067 + 199 0.003142 -0.001394 -0.001846 + 200 0.011374 -0.002895 -0.000674 + 201 0.032698 -0.002552 0.007288 + 202 -0.005709 0.000071 0.005037 + 203 -0.013193 -0.012592 -0.008102 + 204 -0.008194 0.014723 0.003840 + 205 -0.003270 -0.006146 0.004301 + 206 0.004399 -0.010132 -0.001197 + 207 -0.030308 0.012803 0.003540 + 208 0.002110 0.002374 0.006075 + 209 -0.000845 -0.004182 -0.002795 + 210 0.002582 -0.004671 0.002224 + 211 -0.003768 0.002130 0.001339 + 212 0.022509 0.017397 0.002782 + 213 0.020609 0.006682 -0.014082 + 214 0.003956 0.004282 -0.005023 + 215 0.007499 0.004128 0.002237 + 216 0.034882 -0.005096 0.008948 + 217 -0.002552 -0.000287 -0.001907 + 218 0.025445 0.005560 -0.016526 + 219 0.002741 0.000814 -0.004654 + 220 0.002162 -0.001203 0.000936 + 221 0.004071 0.004725 0.001938 + 222 0.002393 -0.013063 -0.003950 + 223 -0.001609 -0.003218 -0.004310 + 224 -0.012550 0.009033 -0.007868 + 225 0.014344 0.000886 -0.013005 + 226 0.005863 0.010335 -0.003424 + 227 0.011104 -0.005602 -0.012415 + 228 0.001222 0.002408 0.001546 + 229 -0.002038 0.001858 0.002991 + 230 -0.017517 -0.020932 0.016099 + 231 0.005257 0.011588 -0.018236 + 232 -0.002660 -0.006193 0.003186 + 233 -0.021995 0.012375 0.004372 + 234 -0.013906 0.028004 -0.004997 + 235 0.002339 -0.001255 -0.003548 + 236 0.001689 0.005243 -0.006337 + 237 0.000498 -0.007782 -0.015260 + 238 0.001142 0.002234 0.003408 + 239 0.007521 0.004622 -0.003272 + 240 -0.001154 0.006952 0.006739 + 241 -0.000938 -0.004609 0.002499 + 242 0.004903 0.001117 0.013021 + 243 0.008126 -0.013873 -0.001075 + 244 -0.004097 0.002491 -0.002459 + 245 0.002093 -0.002989 0.010881 + 246 0.008552 0.010436 0.008330 + 247 -0.000211 0.002295 0.001935 + 248 0.004346 0.003486 0.008405 + 249 -0.006182 0.002873 -0.007955 + 250 0.002466 0.001439 -0.002302 + 251 -0.003246 0.007233 0.009469 + 252 -0.002606 0.002646 0.002563 + 253 0.000833 -0.001794 -0.003483 + 254 -0.001066 -0.001277 -0.012569 + 255 -0.003354 -0.002604 -0.016130 + 256 0.007379 0.006324 -0.003535 + 257 0.025411 0.006788 -0.010928 + 258 0.011648 0.000201 0.004051 + 259 -0.000385 -0.000823 -0.000593 + 260 -0.001070 -0.019569 0.006235 + 261 0.011350 0.009136 0.002805 + 262 -0.001688 0.002178 0.004704 + 263 -0.011748 0.007674 0.002198 + 264 -0.005358 0.003728 -0.002879 + 265 -0.004209 0.000686 -0.004990 + 266 0.000586 0.011928 0.008080 + 267 0.004512 -0.002493 -0.000297 + 268 -0.000130 0.007801 -0.005732 + 269 -0.006259 -0.000991 -0.001515 + 270 0.015560 -0.011483 0.001826 + 271 -0.003544 0.003178 0.000326 + 272 0.006639 0.005731 0.008812 + 273 -0.009361 -0.001371 -0.002830 + 274 -0.000226 0.001739 0.001787 + 275 -0.001846 -0.005637 -0.002071 + 276 0.009461 0.005629 -0.001253 + 277 0.003294 -0.005377 -0.000680 + 278 0.027740 0.013288 0.002669 + 279 0.003403 0.012169 -0.019874 + 280 -0.001383 0.000386 -0.006636 + 281 -0.005910 0.003429 -0.006992 + 282 0.002649 -0.004178 -0.006969 + 283 0.004768 -0.001680 0.000104 + 284 -0.012916 0.017467 -0.012201 + 285 0.010278 -0.007970 0.003734 + 286 0.000005 0.000300 0.006224 + 287 0.003150 -0.001535 0.007443 + 288 -0.000547 -0.003737 0.010794 + 289 0.003054 0.005656 0.000426 + 290 0.006673 0.002252 0.007300 + 291 0.004185 0.001696 0.005292 + 292 -0.001277 -0.005156 -0.001765 + 293 0.005969 -0.004326 -0.002540 + 294 -0.026915 -0.005145 0.019233 + 295 -0.003352 -0.000356 -0.001610 + 296 -0.023375 -0.003718 -0.017075 + 297 0.006387 -0.025086 0.000315 + 298 -0.005064 0.001395 0.004436 + 299 -0.004111 0.000853 -0.032909 + 300 0.000933 0.005949 0.017391 + 301 0.000607 0.002490 -0.002786 + 302 0.002638 0.008857 0.008537 + 303 0.001294 0.011357 -0.003275 + 304 -0.001798 -0.003127 -0.000795 + 305 -0.003320 0.000996 0.004122 + 306 -0.008728 -0.000634 0.002033 + 307 -0.003535 -0.002662 -0.002777 + 308 -0.005954 -0.002781 -0.004403 + 309 -0.002147 -0.001477 -0.001223 + 310 -0.002595 -0.001397 0.002359 + 311 -0.003605 -0.000224 0.015269 + 312 -0.014002 -0.002828 0.000027 + 313 0.001583 -0.005357 0.002380 + 314 -0.002955 -0.014106 -0.011581 + 315 0.000151 -0.006411 0.002865 + 316 0.004278 -0.004088 0.000114 + 317 -0.019291 0.001584 0.015204 + 318 -0.013439 -0.000674 0.010987 + 319 0.000024 0.000995 0.005326 + 320 -0.009041 0.020464 0.014139 + 321 0.004208 -0.003482 0.004723 + 322 0.001489 -0.003292 0.000500 + 323 0.000364 0.006211 0.006844 + 324 0.007467 0.021162 -0.001636 + 325 0.009527 -0.000863 -0.005483 + 326 -0.009936 0.006496 -0.014136 + 327 -0.007595 -0.006469 -0.002090 + 328 -0.002856 -0.010388 -0.000678 + 329 -0.026693 -0.007624 -0.001572 + 330 0.029582 -0.010319 0.009090 + 331 -0.009062 0.000913 0.000368 + 332 -0.019327 0.020501 -0.000560 + 333 -0.018764 -0.008632 0.002570 + 334 0.004502 0.001200 -0.008087 + 335 0.008714 -0.005091 -0.008624 + 336 0.004610 0.003623 -0.007048 + 337 0.002461 -0.000759 0.003913 + 338 0.021591 -0.013925 0.009416 + 339 -0.017190 0.002325 0.006138 + 340 0.003361 0.004027 0.006986 + 341 0.006850 0.012752 0.018496 + 342 0.019589 0.009932 -0.004987 + 343 0.000463 0.005037 -0.000723 + 344 0.008333 0.006382 -0.005532 + 345 0.004288 0.006565 0.007800 + 346 -0.001505 -0.001295 0.001190 + 347 -0.015747 0.011253 0.025149 + 348 0.014871 -0.012646 -0.016815 + 349 -0.000186 0.002115 -0.002539 + 350 0.001936 0.000958 -0.003366 + 351 -0.014299 0.007078 -0.001653 + 352 -0.000876 -0.001637 -0.002032 + 353 -0.001168 0.005556 -0.012749 + 354 -0.003162 -0.016318 -0.009468 + 355 -0.000674 -0.001888 -0.003265 + 356 0.017652 -0.009515 0.007889 + 357 0.015313 -0.006079 0.010454 + 358 -0.000964 -0.004354 0.000067 + 359 0.004137 -0.002540 0.004500 + 360 -0.011376 -0.000921 -0.006123 + 361 0.002023 0.003210 -0.000511 + 362 0.012560 -0.011698 0.016109 + 363 -0.013295 -0.009379 -0.009014 + 364 0.003315 0.003249 0.007620 + 365 -0.010739 0.000915 -0.008118 + 366 -0.015293 0.007564 -0.004343 + 367 0.000192 0.002269 -0.000485 + 368 0.002520 -0.012494 -0.004632 + 369 0.010222 0.003093 -0.002247 + 370 0.003953 0.000628 0.004147 + 371 0.001165 -0.005271 0.007550 + 372 -0.013412 -0.019696 0.026961 + 373 0.001883 0.002252 -0.003560 + 374 0.005482 -0.004609 0.002380 + 375 -0.008048 0.004473 -0.008866 + 376 -0.002663 0.001073 0.001951 + 377 0.010178 0.018964 0.000820 + 378 0.007583 -0.018984 0.016464 + 379 0.001136 0.007646 0.002719 + 380 0.006251 0.008125 0.009187 + 381 0.001284 0.011634 -0.004097 + 382 -0.000767 0.000265 -0.000818 + 383 -0.000089 0.001579 -0.002300 + 384 -0.004565 -0.011251 0.008186 + 385 0.004778 -0.000871 0.002405 + 386 0.006618 -0.002801 0.006849 + 387 0.029884 -0.012377 0.019662 + 388 -0.002799 -0.005785 0.000693 + 389 -0.006988 0.014716 -0.008738 + 390 -0.003130 0.004832 0.002982 + 391 0.000036 -0.002467 0.000498 + 392 -0.001382 -0.006847 0.003863 + 393 -0.003623 0.001391 0.001664 + 394 0.004431 0.000182 0.002043 + 395 0.007177 -0.001675 0.008884 + 396 0.000324 0.003728 0.003379 + 397 0.004107 -0.000618 0.000098 + 398 0.019272 -0.008832 -0.013192 + 399 -0.025041 0.027976 -0.020594 + 400 0.002982 -0.002889 -0.005826 + 401 0.010564 -0.003899 -0.002078 + 402 0.005218 -0.003308 -0.010357 + 403 0.002304 -0.003833 -0.008812 + 404 -0.013421 -0.017603 -0.023172 + 405 -0.003134 -0.000582 0.001712 + 406 -0.003398 -0.002176 0.001635 + 407 -0.015813 0.008046 0.010515 + 408 0.003940 -0.004144 -0.002666 + 409 0.008428 -0.002203 -0.004077 + 410 -0.004859 0.004207 -0.016803 + 411 -0.022714 0.005614 0.004119 + 412 -0.000677 -0.000486 0.001019 + 413 0.004137 0.001524 0.004810 + 414 -0.011495 -0.003293 -0.002498 + 415 -0.004277 -0.004620 -0.002973 + 416 0.005727 -0.002611 0.021922 + 417 0.009759 0.016284 -0.017136 + 418 0.001140 -0.003169 0.001021 + 419 0.002072 0.019101 -0.019824 + 420 0.029356 -0.011686 0.004675 + 421 0.001175 0.002540 0.001846 + 422 0.009479 -0.017538 0.002696 + 423 0.008327 0.028039 -0.001246 + 424 0.002971 -0.004730 0.000069 + 425 0.010168 -0.005904 -0.016535 + 426 0.009223 0.011295 0.006248 + 427 -0.003323 0.000861 0.005020 + 428 -0.005244 0.001685 -0.001864 + 429 0.000994 0.014826 0.000976 + 430 -0.002795 0.003958 -0.004848 + 431 0.010698 -0.011688 -0.000537 + 432 0.008158 0.021591 -0.003259 + 433 0.000363 0.002223 0.004053 + 434 -0.002225 0.004315 -0.010042 + 435 -0.000151 -0.000572 0.000675 + 436 0.006996 -0.000559 0.003307 + 437 -0.011410 -0.004708 0.006782 + 438 -0.015909 0.022113 0.004877 + 439 -0.002401 -0.002279 0.002655 + 440 -0.002478 0.000164 0.005849 + 441 -0.003545 0.002314 0.007358 + 442 0.002189 0.006935 -0.001251 + 443 -0.007190 0.031224 0.006804 + 444 0.004661 -0.003296 0.013412 + 445 0.003709 0.001514 -0.003921 + 446 0.015678 0.007604 0.000133 + 447 -0.004648 -0.004474 -0.027064 + 448 0.001807 -0.004146 0.004203 + 449 0.029598 0.003434 0.012408 + 450 -0.004603 -0.006201 0.002287 + 451 -0.003031 -0.004136 -0.006564 + 452 0.009003 0.019264 0.004529 + 453 -0.000188 0.010449 0.001077 + 454 0.003891 0.002752 0.005629 + 455 0.001092 0.012776 0.008682 + 456 -0.002762 0.015371 -0.005857 + 457 0.002697 -0.003406 -0.002865 + 458 0.007823 -0.013511 0.002023 + 459 -0.030492 -0.008107 -0.020624 + 460 0.000483 0.001162 0.002651 + 461 0.002571 -0.007508 -0.009384 + 462 -0.010774 -0.027329 0.003619 + 463 0.005791 0.000086 0.004298 + 464 0.008820 0.016257 -0.002226 + 465 0.000317 -0.014932 -0.013621 + 466 0.003540 0.001551 -0.001349 + 467 0.008241 0.020014 0.019807 + 468 -0.004258 -0.010227 -0.029599 + 469 0.007640 0.001287 -0.003128 + 470 0.004600 -0.001555 -0.010230 + 471 0.007870 0.002461 0.000094 + 472 0.001001 0.005160 -0.001529 + 473 0.006073 0.015127 0.022819 + 474 0.006356 -0.012345 -0.003131 + 475 -0.005549 -0.000151 0.001312 + 476 -0.015747 0.009610 0.004075 + 477 0.009345 0.004620 -0.013632 + 478 -0.005694 -0.004777 0.002781 + 479 -0.015785 0.018249 0.008919 + 480 0.007264 0.001342 -0.012954 + 481 -0.002601 -0.003124 -0.001775 + 482 -0.010924 -0.002942 0.001676 + 483 0.020644 0.001519 0.001050 + 484 -0.003829 -0.001681 0.001973 + 485 -0.009248 -0.008096 0.002166 + 486 -0.004627 -0.003317 0.000426 + 487 0.004750 0.008629 -0.001691 + 488 -0.009177 0.001481 0.019567 + 489 -0.000748 -0.004703 -0.011184 + 490 -0.000930 -0.004032 -0.001796 + 491 -0.007051 -0.001375 -0.004647 + 492 -0.000505 0.005436 -0.004029 + 493 -0.000767 -0.000313 -0.004426 + 494 0.007019 0.022441 0.008035 + 495 0.002030 -0.018016 0.012244 + 496 -0.000430 -0.004092 0.001186 + 497 0.012447 -0.008156 0.016405 + 498 -0.008008 0.011043 -0.000527 + 499 0.001752 0.001451 -0.008850 + 500 -0.001696 0.002950 -0.000035 + 501 0.006054 -0.001180 -0.028952 + 502 0.001434 -0.008124 -0.001958 + 503 0.001762 -0.007034 -0.009244 + 504 -0.008796 -0.004759 -0.009928 + 505 0.000249 0.001170 0.006380 + 506 -0.005081 0.014461 -0.003259 + 507 -0.002522 0.001324 0.007841 + 508 0.003441 0.001538 0.006742 + 509 0.007735 -0.006583 0.003492 + 510 0.009681 0.006088 0.008608 + 511 -0.006695 -0.001970 0.000807 + 512 0.004268 0.004052 0.001263 + 513 -0.004129 -0.012886 -0.007489 + 514 -0.002878 0.001158 0.006535 + 515 -0.007680 -0.001896 0.002953 + 516 -0.000917 -0.006257 -0.002762 + 517 -0.001401 -0.003523 -0.005778 + 518 -0.001854 0.007834 0.015061 + 519 -0.010095 0.007049 -0.021128 + 520 -0.000766 -0.000153 0.007009 + 521 0.009064 -0.003223 0.017921 + 522 0.000864 -0.000043 0.007876 + 523 -0.001025 0.001319 -0.006573 + 524 -0.006395 0.000755 -0.002686 + 525 -0.032670 0.007943 0.004175 + 526 0.002953 0.006520 0.004065 + 527 0.009139 -0.008077 -0.010889 + 528 -0.002820 0.012454 -0.005504 + 529 -0.008727 0.003418 0.002451 + 530 -0.007112 -0.005703 0.023446 + 531 -0.011285 0.014165 -0.019563 + 532 -0.002562 0.003192 -0.002295 + 533 -0.003618 0.007211 0.002298 + 534 0.010325 0.001834 0.002853 + 535 0.002563 0.000345 -0.002878 + 536 0.002396 0.022293 -0.006961 + 537 0.001693 -0.002677 0.010576 + 538 -0.001561 0.000734 0.001793 + 539 -0.008542 0.015338 0.007321 + 540 -0.015880 0.015140 0.014642 + 541 0.001092 0.000090 0.000997 + 542 -0.004522 -0.004004 0.003687 + 543 0.003258 -0.006156 0.000500 + 544 -0.001608 0.002026 0.003790 + 545 -0.010430 -0.004583 0.015482 + 546 0.002628 0.011416 0.004923 + 547 -0.002068 0.005845 0.001850 + 548 0.001194 0.007931 0.007672 + 549 -0.020261 -0.007195 -0.008896 + 550 0.005399 0.001999 0.000211 + 551 0.004420 0.012603 0.006214 + 552 0.007790 0.005534 0.000006 + 553 -0.004249 0.001186 -0.000260 + 554 0.006385 -0.014925 0.000020 + 555 0.009902 0.016988 -0.004080 + 556 0.006637 -0.003469 0.000450 + 557 -0.002010 0.011423 -0.004361 + 558 -0.009074 0.013716 -0.002539 + 559 0.003243 -0.003710 -0.002565 + 560 -0.000480 -0.009433 0.000267 + 561 0.002981 -0.005587 -0.010088 + 562 0.002665 0.008169 0.002667 + 563 -0.001817 0.009035 0.022525 + 564 0.005689 0.010678 0.000603 + 565 0.003217 0.002617 0.001072 + 566 0.025108 0.001061 -0.027288 + 567 -0.003091 0.028727 0.028529 + 568 0.003991 -0.002246 0.002528 + 569 0.011195 -0.007917 0.010511 + 570 -0.006686 -0.007088 -0.000640 + 571 0.005302 0.003751 0.001484 + 572 0.001250 0.007658 -0.006666 + 573 0.018145 -0.005375 0.000139 + 574 -0.003857 0.003583 0.000238 + 575 0.006752 0.001063 0.004538 + 576 -0.006479 0.014326 -0.017669 + 577 0.001793 0.003661 0.002509 + 578 0.010186 -0.003147 0.008687 + 579 -0.001160 -0.005645 -0.003812 + 580 -0.002296 0.006997 0.000837 + 581 -0.031138 0.017223 0.000984 + 582 0.002587 -0.007480 0.015277 + 583 0.000288 -0.000668 0.001548 + 584 0.016041 -0.004051 0.004629 + 585 -0.025116 0.003224 0.009356 + 586 -0.000853 0.003188 0.004014 + 587 -0.001700 -0.004491 0.006716 + 588 -0.008947 -0.009004 -0.023328 + 589 0.005432 -0.003893 -0.001000 + 590 -0.019524 0.021049 -0.035976 + 591 0.009404 0.004475 -0.004525 + 592 -0.006508 -0.002709 0.000481 + 593 0.010852 -0.015643 0.005754 + 594 0.006526 0.026156 0.009018 + 595 -0.004611 -0.001841 0.002205 + 596 -0.013411 -0.011893 -0.011510 + 597 -0.002150 -0.000804 -0.006730 + 598 -0.002593 -0.000356 0.003104 + 599 0.009483 0.002951 -0.001362 + 600 -0.015523 -0.003843 0.010828 + 601 -0.001229 0.003953 0.000471 + 602 -0.017788 0.002114 0.033354 + 603 0.015187 -0.017947 -0.007994 + 604 -0.001335 -0.000196 0.007281 + 605 0.015188 0.007448 0.005030 + 606 -0.001538 0.002386 -0.009662 + 607 -0.001172 0.004261 0.002894 + 608 -0.002229 0.015661 0.009134 + 609 0.017428 0.004976 0.006974 + 610 -0.001490 0.003604 0.004586 + 611 -0.017720 0.006222 -0.023144 + 612 0.010016 -0.015847 -0.004678 + 613 -0.002648 0.000934 0.000698 + 614 -0.011832 0.016782 0.007626 + 615 -0.005427 0.001385 0.015386 + 616 0.003669 -0.001949 0.003946 + 617 0.005164 0.000243 0.009975 + 618 -0.000161 0.003111 0.001353 + 619 0.002976 -0.004733 0.001868 + 620 -0.002832 -0.014197 -0.023534 + 621 -0.003347 -0.011551 0.000693 + 622 0.004912 0.001701 -0.000793 + 623 0.013809 0.007164 -0.016905 + 624 0.024958 -0.010962 -0.008428 + 625 0.007422 -0.002948 -0.001308 + 626 -0.016590 -0.032000 -0.001025 + 627 0.011367 0.004098 0.010259 + 628 -0.002045 -0.000742 0.000577 + 629 -0.030845 0.001448 0.030396 + 630 0.001781 -0.017639 0.014980 + 631 0.002233 -0.004427 -0.002429 + 632 0.018586 -0.001402 0.006993 + 633 -0.012356 0.003736 0.007796 + 634 -0.004338 0.007766 0.000310 + 635 0.001990 0.000209 0.007107 + 636 -0.006343 0.005190 -0.018263 + 637 -0.005455 0.000492 -0.002847 + 638 0.000522 0.006495 0.003755 + 639 -0.001841 -0.009429 -0.001507 + 640 -0.002314 -0.002516 -0.005613 + 641 0.018652 0.002237 -0.015930 + 642 -0.002326 -0.000776 -0.003132 + 643 -0.005512 -0.000623 -0.000619 + 644 -0.001015 0.005882 0.003225 + 645 0.000586 0.023218 -0.004529 + 646 -0.001138 0.000800 0.002687 + 647 0.003627 0.013371 -0.016172 + 648 0.018968 0.017228 -0.000038 + 649 -0.002086 -0.000112 -0.007393 + 650 0.016103 0.035588 0.008775 + 651 -0.038516 0.012158 -0.009536 + 652 0.002958 0.004862 -0.007554 + 653 0.024333 0.013052 -0.023133 + 654 0.002379 -0.000049 -0.006601 + 655 0.003804 -0.003076 -0.001112 + 656 -0.004763 0.002283 -0.025897 + 657 -0.036538 -0.010672 -0.010599 + 658 -0.000713 0.003957 0.002151 + 659 -0.016531 0.001472 0.004862 + 660 -0.009287 0.028134 0.010480 + 661 0.004192 -0.003835 0.000568 + 662 0.011523 0.002433 0.036479 + 663 -0.009197 -0.041577 0.000393 + 664 0.000280 -0.002373 -0.004460 + 665 0.002206 -0.003211 0.000957 + 666 0.006211 0.013469 -0.005353 + 667 -0.000522 0.001664 -0.004748 + 668 0.004459 -0.024042 -0.023029 + 669 0.011377 0.013403 0.030836 + 670 0.003382 -0.002813 0.000451 + 671 0.000766 0.000074 -0.006820 + 672 0.013252 -0.015598 0.024274 + 673 -0.003243 0.006406 -0.002570 + 674 0.019962 -0.008888 -0.019769 + 675 -0.027628 -0.005508 -0.000297 + 676 -0.007770 -0.003882 0.002155 + 677 -0.001777 0.012358 0.000036 + 678 -0.024978 0.005564 -0.015024 + 679 0.000188 0.001017 0.004117 + 680 -0.006440 -0.003105 0.019733 + 681 -0.016780 0.005575 -0.004078 + 682 0.000151 0.001697 -0.001387 + 683 -0.002925 0.000955 -0.004378 + 684 0.000826 0.008069 0.003052 + 685 -0.003543 -0.000321 -0.000587 + 686 -0.012205 0.000432 -0.005990 + 687 0.004010 0.009678 -0.003793 + 688 0.001940 -0.000340 0.003900 + 689 0.005837 0.014815 -0.005621 + 690 -0.008710 -0.017653 0.020395 + 691 -0.001931 -0.003975 -0.002577 + 692 -0.003368 -0.014386 -0.006878 + 693 -0.013782 -0.002984 0.003522 + 694 0.004968 -0.000283 -0.003322 + 695 0.019160 0.006665 -0.007077 + 696 0.022604 -0.000847 -0.016983 + 697 0.002571 0.000550 -0.007379 + 698 -0.001443 -0.002487 -0.007727 + 699 -0.011487 -0.013883 0.019460 + 700 0.001096 -0.004750 0.003965 + 701 -0.016603 -0.010473 0.014272 + 702 0.023559 -0.001392 -0.008500 + 703 -0.002022 -0.005262 -0.004485 + 704 0.002332 -0.014942 -0.004917 + 705 -0.009402 0.006267 -0.002020 + 706 -0.000288 0.003264 -0.003564 + 707 0.004565 0.033122 -0.006655 + 708 -0.018922 -0.009521 0.000208 + 709 -0.003485 0.003285 -0.000556 + 710 0.004587 -0.002798 -0.000984 + 711 -0.006054 0.007231 -0.001425 + 712 0.004718 0.000201 -0.003948 + 713 -0.014114 0.009800 -0.004955 + 714 -0.008099 -0.004168 0.008689 + 715 0.000410 -0.000654 0.009605 + 716 0.008711 0.018707 0.002740 + 717 0.003459 -0.008185 0.010239 + 718 0.003479 0.000757 0.004467 + 719 0.000433 -0.000495 0.007710 + 720 0.012945 0.003286 -0.002052 + 721 -0.010010 -0.003567 0.006956 + 722 0.005307 -0.001615 -0.002198 + 723 -0.012515 0.011984 0.016669 + 724 0.001378 -0.002186 -0.001614 + 725 0.012587 -0.019891 0.012237 + 726 0.012601 0.007024 0.014776 + 727 -0.002983 -0.001722 -0.004228 + 728 0.015268 -0.011359 -0.002815 + 729 -0.003967 0.028638 0.000653 + 730 -0.000313 -0.000495 0.001546 + 731 -0.030938 -0.009463 -0.008649 + 732 -0.033474 -0.019299 0.015331 + 733 0.000845 -0.003919 -0.003202 + 734 -0.027178 0.011071 -0.026350 + 735 -0.007741 0.001470 -0.016184 + 736 -0.001239 0.001989 -0.002789 + 737 0.011285 0.001382 -0.006222 + 738 0.022813 -0.006205 -0.006536 + 739 0.003987 -0.004190 -0.005010 + 740 -0.007915 0.002670 -0.013878 + 741 0.004194 0.006086 -0.010350 + 742 0.006539 -0.005074 0.002196 + 743 0.015306 0.008181 0.005081 + 744 0.007865 0.003022 -0.004716 + 745 -0.001784 -0.010062 0.004309 + 746 -0.002378 -0.011275 0.006933 + 747 -0.008336 -0.001053 0.004620 + 748 -0.002979 0.004768 -0.002497 + 749 -0.000959 0.004004 -0.002600 + 750 -0.019512 -0.002978 0.005044 + 751 -0.004903 -0.000550 0.000659 + 752 -0.005086 0.005639 -0.022167 + 753 -0.008131 0.001631 -0.018889 + 754 -0.001761 -0.001628 0.000503 + 755 -0.003957 -0.007199 -0.006609 + 756 0.003155 -0.001306 0.005143 + 757 0.000937 0.008247 -0.008723 + 758 0.028994 0.004889 0.007225 + 759 -0.000469 -0.025903 0.001925 + 760 -0.001834 -0.000370 -0.001605 + 761 0.007234 -0.001225 -0.019036 + 762 -0.003442 -0.001966 0.000209 + 763 0.000445 0.007510 0.001158 + 764 -0.008348 0.004439 -0.007776 + 765 -0.012793 0.011539 0.019680 + 766 0.000065 -0.000962 -0.004032 + 767 -0.002013 -0.005477 0.003901 + 768 0.003529 0.021570 0.007224 + 769 -0.002661 0.002604 -0.003268 + 770 0.005668 -0.003962 -0.004196 + 771 -0.003633 0.008263 -0.012842 + 772 0.001811 0.001915 0.002764 + 773 0.007995 -0.017893 0.012738 + 774 -0.018466 -0.002519 -0.001997 + 775 -0.002231 0.000080 0.000338 + 776 -0.020092 -0.012422 0.010443 + 777 0.017610 0.006562 -0.019411 + 778 -0.001733 0.005494 0.004582 + 779 0.013495 0.017522 0.004058 + 780 0.014733 0.026971 -0.010419 + 781 0.001950 0.000577 -0.000870 + 782 -0.025830 0.001269 0.005271 + 783 0.007534 -0.015453 0.006553 + 784 0.004959 0.000931 -0.005022 + 785 -0.008754 0.005835 0.049441 + 786 0.010447 0.012462 0.001546 + 787 -0.001107 0.002522 0.000433 + 788 0.009871 0.011686 0.008446 + 789 -0.006988 0.002247 0.021211 + 790 0.004245 0.001822 -0.000253 + 791 0.000153 -0.002603 0.008675 + 792 0.006252 0.003177 -0.013109 + 793 -0.002534 0.003863 0.000617 + 794 -0.000057 0.004391 -0.016346 + 795 0.005974 -0.000584 -0.004834 + 796 0.001827 -0.002339 -0.002010 + 797 -0.023150 0.007693 0.012507 + 798 0.012203 0.000464 -0.020004 + 799 -0.000293 -0.001883 -0.002470 + 800 -0.004248 0.006084 0.002613 + 801 -0.013517 0.015693 0.003574 + 802 -0.009450 0.005229 -0.003400 + 803 -0.015058 -0.007700 0.001796 + 804 -0.000196 -0.003546 0.002537 + 805 0.008758 -0.003257 0.005431 + 806 0.012998 -0.011952 -0.017276 + 807 0.008558 -0.002765 0.006723 + 808 -0.001470 -0.000539 0.002965 + 809 0.024028 -0.019423 -0.012788 + 810 0.003892 0.003966 -0.001573 + 811 0.000254 0.001510 0.000089 + 812 0.024395 0.007424 -0.013783 + 813 0.006830 0.017138 0.017010 + 814 -0.001535 -0.003749 -0.001708 + 815 0.013748 -0.018314 -0.006646 + 816 0.003900 0.002047 0.006451 + 817 0.006585 0.003832 -0.000629 + 818 0.021540 0.003252 0.001280 + 819 0.007897 0.007247 -0.003727 + 820 -0.002115 -0.002434 -0.005025 + 821 -0.016735 0.003360 -0.019137 + 822 0.003237 -0.017804 -0.004111 + 823 -0.003907 0.002878 -0.003988 + 824 -0.005419 -0.002010 -0.004476 + 825 -0.006449 0.003104 -0.002766 + 826 -0.013638 -0.002258 -0.002448 + 827 -0.007838 0.000023 -0.005866 + 828 -0.006633 0.001312 -0.008943 + 829 0.001696 0.003761 -0.002125 + 830 -0.001113 -0.010288 -0.008692 + 831 0.010380 0.008838 -0.015548 + 832 -0.003164 0.004544 -0.002070 + 833 -0.001495 -0.013094 -0.000890 + 834 0.011945 -0.015741 -0.003378 + 835 -0.008802 -0.001939 -0.005442 + 836 -0.002949 -0.007279 -0.004665 + 837 0.008414 -0.021459 -0.000948 + 838 0.001330 0.000622 0.000916 + 839 -0.001965 0.001331 0.006138 + 840 0.003081 -0.004825 0.007272 + 841 0.001557 -0.005770 -0.001563 + 842 0.014285 0.020628 -0.029634 + 843 -0.006815 0.003616 0.008747 + 844 0.001116 -0.003881 -0.003556 + 845 0.008316 -0.005783 -0.005256 + 846 -0.011615 0.015346 0.026431 + 847 0.004309 0.003546 -0.004311 + 848 0.007868 -0.013572 0.000073 + 849 -0.011699 0.005875 0.003604 + 850 0.000505 -0.004069 -0.002113 + 851 0.001211 -0.005770 -0.003436 + 852 -0.004651 0.001028 0.007154 + 853 -0.003913 -0.006795 -0.004733 + 854 -0.004339 -0.014527 -0.023555 + 855 -0.006756 -0.006056 -0.008714 + 856 0.007493 0.001588 -0.006408 + 857 0.020526 0.022065 -0.006921 + 858 0.010862 0.004031 -0.001655 + 859 0.003459 -0.001125 -0.001494 + 860 -0.000710 0.004855 0.022662 + 861 -0.000022 0.009082 0.012428 + 862 -0.000591 0.002648 0.002517 + 863 0.017910 0.003993 0.005847 + 864 -0.004999 0.014284 -0.016199 + 865 -0.001700 -0.002300 0.001206 + 866 -0.016994 -0.008747 -0.012103 + 867 -0.008118 -0.008616 0.003715 + 868 -0.002056 -0.003732 -0.006667 + 869 -0.002586 -0.005666 -0.002032 + 870 -0.002179 -0.001361 -0.001378 + 871 0.001952 0.000747 -0.004175 + 872 -0.000006 -0.004573 0.003592 + 873 -0.004377 -0.012174 0.000091 + 874 -0.006945 -0.004708 0.004295 + 875 -0.011724 -0.010397 0.002368 + 876 0.006805 0.012734 0.019238 + 877 0.004959 0.005871 -0.001277 + 878 -0.012228 -0.000867 -0.006672 + 879 0.014516 0.032640 0.025985 + 880 0.000767 -0.000179 0.004816 + 881 0.006242 0.002132 0.007465 + 882 0.006812 0.003103 0.007707 + 883 0.005120 -0.003059 -0.001062 + 884 -0.008255 -0.016076 -0.002362 + 885 -0.001789 -0.014152 -0.001194 + 886 -0.009000 0.001340 0.001690 + 887 -0.020559 -0.017599 0.000329 + 888 -0.003544 -0.006539 0.004087 + 889 -0.000933 0.000538 -0.001999 + 890 0.032797 0.013397 0.000525 + 891 -0.012354 -0.008526 -0.038077 + 892 0.002953 -0.002317 -0.004454 + 893 -0.029479 -0.014864 0.005868 + 894 0.019223 0.000709 -0.013773 + 895 0.002346 -0.003694 -0.004486 + 896 -0.005275 -0.001221 -0.010755 + 897 0.010883 0.001918 -0.002099 + 898 -0.000263 -0.000830 0.005518 + 899 0.000399 -0.005578 0.011643 + 900 -0.007207 -0.006080 -0.006632 + 901 -0.000868 0.002637 -0.000416 + 902 -0.003601 0.001456 0.001019 + 903 0.003465 0.009000 0.002627 + 904 -0.005492 0.001153 0.005034 + 905 0.008501 0.009963 0.005133 + 906 0.002740 0.005510 0.005387 + 907 0.001230 0.003701 -0.010904 + 908 0.005640 0.000943 -0.026378 + 909 -0.001655 0.006661 0.001080 + 910 0.000417 -0.004485 0.000899 + 911 0.004051 -0.003590 0.002016 + 912 0.010109 -0.002124 0.001500 + 913 0.002439 0.006335 0.003103 + 914 -0.006325 0.005901 0.006397 + 915 0.008058 0.002545 0.004591 + 916 -0.001774 -0.003954 -0.005522 + 917 -0.001697 -0.002110 -0.006988 + 918 0.000641 -0.012660 -0.001878 + 919 0.000840 0.002158 -0.002127 + 920 -0.006972 -0.005865 -0.019536 + 921 -0.009078 -0.009093 0.005319 + 922 -0.002466 0.001612 -0.002348 + 923 -0.007997 0.000173 -0.007016 + 924 -0.005167 0.000122 -0.004809 + 925 0.000182 0.007626 -0.005820 + 926 -0.000187 0.006758 -0.004766 + 927 -0.005146 0.010941 -0.001145 + 928 -0.001035 0.003329 -0.000156 + 929 -0.002925 0.005286 0.005381 + 930 -0.007353 0.014383 0.015446 + 931 0.001566 0.003779 -0.001844 + 932 0.014111 -0.006162 0.016836 + 933 -0.008051 -0.000942 0.006114 + 934 0.000472 0.000581 0.003898 + 935 0.010438 -0.015336 0.026259 + 936 -0.009803 0.018803 -0.011113 + 937 -0.002622 0.001845 -0.004649 + 938 0.000192 0.006195 -0.003034 + 939 -0.004379 0.004856 -0.008876 + 940 0.005312 -0.005320 -0.000644 + 941 0.004197 0.002434 0.005873 + 942 0.001054 -0.002144 -0.009156 + 943 0.001818 0.002764 0.000410 + 944 0.002489 0.005354 -0.014128 + 945 0.003819 0.010472 0.007403 + 946 0.005262 -0.000699 0.001191 + 947 -0.002052 -0.008290 0.017377 + 948 -0.012921 -0.009037 0.007720 + 949 0.002875 -0.000206 -0.005514 + 950 0.004620 -0.003924 -0.007344 + 951 0.004396 0.015332 -0.008395 + 952 -0.001773 -0.005567 0.004807 + 953 0.014650 -0.004337 0.011316 + 954 0.007355 -0.004603 0.004796 + 955 0.001050 0.002663 -0.000049 + 956 -0.000422 0.019759 -0.003121 + 957 -0.011736 0.001700 0.005445 + 958 0.002314 -0.007359 0.001422 + 959 0.000226 -0.009157 0.011161 + 960 0.002971 -0.007641 -0.001658 + 961 0.002025 0.003310 0.000085 + 962 0.003783 0.005544 -0.002440 + 963 -0.003390 -0.001680 0.007759 + 964 -0.000259 -0.001517 -0.001671 + 965 -0.009891 -0.000275 0.002930 + 966 -0.004798 -0.018121 0.000493 + 967 0.002742 0.002196 0.002639 + 968 -0.032110 0.008681 0.017593 + 969 -0.005767 -0.003804 -0.003447 + 970 -0.001025 -0.001901 0.007377 + 971 -0.025416 -0.005633 -0.009650 + 972 -0.002448 -0.002342 0.009184 + 973 0.000510 -0.004313 0.003297 + 974 -0.004244 -0.006185 -0.015114 + 975 0.002817 0.008222 0.025232 + 976 -0.005979 0.000432 0.003264 + 977 0.000348 0.000126 0.007237 + 978 -0.031461 0.008376 -0.002490 + 979 -0.003066 -0.005264 0.001528 + 980 0.000500 -0.005194 -0.000082 + 981 -0.006145 0.003915 -0.013465 + 982 -0.002081 -0.001596 0.001268 + 983 0.004918 -0.004802 -0.009499 + 984 -0.008729 0.005751 0.010881 + 985 0.002456 -0.001947 -0.001558 + 986 -0.006566 -0.000024 0.003315 + 987 0.007532 0.005898 -0.002575 + 988 -0.004247 -0.003264 -0.000409 + 989 0.002165 -0.007499 0.004990 + 990 -0.000419 0.003692 -0.004472 + 991 -0.001571 -0.000159 -0.000431 + 992 0.005413 0.009517 0.004397 + 993 -0.002643 -0.002292 -0.001478 + 994 -0.003884 0.005066 -0.000457 + 995 0.006816 0.009263 -0.003376 + 996 -0.007273 0.011919 0.000514 + 997 0.000030 0.001409 0.005477 + 998 0.005334 -0.020033 0.004464 + 999 0.016228 0.009598 -0.007106 + 1000 -0.002283 -0.004481 0.001317 + 1001 -0.002631 -0.006631 -0.004233 + 1002 0.004184 0.000805 0.014756 + 1003 0.000408 -0.003693 0.003308 + 1004 0.004530 -0.006410 -0.006453 + 1005 -0.004928 -0.003846 0.015168 + 1006 0.003101 -0.001511 0.005308 + 1007 0.014081 -0.002443 0.012313 + 1008 0.002846 0.010440 -0.000376 + 1009 0.003569 -0.002175 -0.006662 + 1010 -0.008368 -0.011644 -0.006989 + 1011 0.019824 -0.004949 -0.018661 + 1012 0.003202 -0.011850 0.003160 + 1013 0.014918 -0.009378 0.018579 + 1014 -0.002594 0.004575 -0.001959 + 1015 -0.002298 0.000413 -0.003910 + 1016 0.012837 -0.003799 -0.015681 + 1017 -0.005955 -0.000660 0.004171 + 1018 0.001582 0.000975 0.000146 + 1019 0.006776 -0.014144 -0.007821 + 1020 0.004234 -0.001693 -0.007198 + 1021 -0.001802 -0.002656 0.003257 + 1022 0.028537 0.012512 0.005966 + 1023 -0.000026 -0.011732 -0.013572 + 1024 0.006685 0.008417 -0.002619 + 1025 -0.018380 0.006240 0.006444 + 1026 0.014195 0.009753 -0.004447 + 1027 -0.000769 -0.006799 -0.003510 + 1028 -0.003532 0.013774 -0.009337 + 1029 0.005263 0.018084 -0.010946 + 1030 0.004102 0.004262 -0.002426 + 1031 -0.003256 -0.005354 0.003498 + 1032 -0.021894 -0.003478 0.016467 + 1033 0.001456 -0.004355 -0.002070 + 1034 -0.005859 -0.004113 -0.005871 + 1035 -0.005758 -0.006886 -0.016585 + 1036 0.001562 0.006459 -0.000209 + 1037 0.001331 0.004667 0.000892 + 1038 0.012898 0.027063 -0.008125 + 1039 0.002117 0.007131 0.002457 + 1040 0.026605 0.010046 0.019045 + 1041 -0.017364 0.007077 -0.014953 + 1042 -0.000452 0.009291 0.004625 + 1043 -0.011059 0.009571 0.015357 + 1044 0.027928 -0.000208 0.009437 + 1045 0.003475 -0.004274 -0.000546 + 1046 0.012160 -0.001385 -0.006922 + 1047 -0.016274 -0.008100 -0.006675 + 1048 -0.003853 -0.003278 -0.001388 + 1049 0.014697 -0.003341 -0.007454 + 1050 0.011346 -0.009086 -0.006461 + 1051 -0.001161 -0.003940 -0.002833 + 1052 0.011182 0.001281 -0.000803 + 1053 -0.001345 -0.002375 -0.003580 + 1054 0.004028 0.002256 0.000990 + 1055 0.013302 0.008212 -0.007566 + 1056 0.029179 -0.014499 0.008878 + 1057 0.000706 0.001652 0.001826 + 1058 0.000498 -0.007266 0.024956 + 1059 0.001324 -0.008155 0.011295 + 1060 0.000971 -0.006253 -0.004688 + 1061 -0.004746 -0.005680 -0.016047 + 1062 -0.000356 -0.009050 -0.006561 + 1063 -0.000866 0.005460 0.000045 + 1064 -0.006882 0.011747 0.020163 + 1065 -0.000733 0.001409 -0.010900 + 1066 -0.003804 0.003558 0.001444 + 1067 0.004513 0.002071 -0.017536 + 1068 -0.000869 -0.002704 -0.014336 + 1069 -0.003015 0.003241 -0.002075 + 1070 0.003734 -0.005456 -0.000879 + 1071 -0.006686 -0.008010 -0.008654 + 1072 -0.000541 -0.003669 -0.004373 + 1073 0.003151 -0.002513 -0.013951 + 1074 0.003979 -0.005557 0.002931 + 1075 -0.005175 -0.004387 0.000228 + 1076 -0.005613 -0.012392 -0.029351 + 1077 0.009704 0.009953 -0.015680 + 1078 -0.000915 0.003660 -0.003078 + 1079 0.002529 0.001465 0.006987 + 1080 0.000880 0.001866 -0.004217 + 1081 0.000835 -0.000410 0.000029 + 1082 0.003324 -0.009356 0.012151 + 1083 -0.000797 0.009753 -0.012613 + 1084 0.004557 -0.006851 0.000257 + 1085 0.014378 -0.010986 -0.004036 + 1086 0.001889 0.001865 0.000904 + 1087 0.003881 0.000306 -0.000266 + 1088 0.006043 -0.030376 0.018797 + 1089 -0.001012 -0.002296 0.000324 + 1090 0.007042 0.008682 0.007323 + 1091 0.010016 0.002442 -0.028255 + 1092 -0.004827 0.009414 -0.012200 + 1093 0.002178 0.003272 0.000190 + 1094 0.003486 0.001815 -0.002585 + 1095 0.006020 0.002953 -0.010998 + 1096 0.002573 -0.000704 0.002051 + 1097 -0.010233 0.004335 0.005568 + 1098 0.003397 0.002649 0.010631 + 1099 -0.000367 -0.008657 0.004003 + 1100 0.006810 -0.008282 0.003316 + 1101 -0.008301 -0.011638 -0.006525 + 1102 -0.001900 -0.008810 0.001531 + 1103 0.003628 0.008111 0.009571 + 1104 0.017147 0.000173 0.003988 + 1105 0.006161 0.005444 0.001389 + 1106 -0.033784 0.028714 -0.002486 + 1107 0.022179 0.015181 0.025221 + 1108 0.002935 0.001125 -0.009560 + 1109 0.013392 0.009490 0.002655 + 1110 0.015380 -0.002935 -0.004728 + 1111 0.002760 -0.001052 0.002516 + 1112 -0.006737 0.002302 0.012384 + 1113 -0.004649 -0.009652 -0.009326 + 1114 -0.003333 0.004385 -0.006004 + 1115 -0.014175 0.007089 0.000199 + 1116 0.009875 0.004925 0.012791 + 1117 -0.004828 0.000366 0.001718 + 1118 0.009618 -0.007069 -0.012330 + 1119 -0.021489 -0.009155 -0.001603 + 1120 -0.001360 0.002089 -0.003585 + 1121 0.003530 -0.001847 0.010254 + 1122 0.016468 0.005240 -0.014692 + 1123 0.001989 -0.000949 0.003286 + 1124 0.022107 -0.012110 -0.007316 + 1125 0.012518 -0.010337 0.015891 + 1126 0.000850 -0.001413 -0.001737 + 1127 -0.014943 0.000360 -0.000490 + 1128 -0.027983 -0.005206 0.004037 + 1129 0.011232 0.000349 -0.006679 + 1130 -0.005484 -0.003095 -0.004430 + 1131 -0.005050 -0.002005 -0.015837 + 1132 -0.000470 0.001924 0.001131 + 1133 -0.016506 0.005240 0.008171 + 1134 0.011977 -0.012388 0.003671 + 1135 -0.000818 0.001081 0.001571 + 1136 0.009956 -0.006601 -0.002667 + 1137 -0.013344 0.009962 -0.000602 + 1138 -0.004379 0.004681 0.005655 + 1139 -0.022717 0.009805 -0.016911 + 1140 -0.017223 0.002867 0.018671 + 1141 -0.000339 -0.000149 -0.001276 + 1142 0.002292 0.016872 -0.004987 + 1143 -0.012964 -0.000693 -0.007140 + 1144 -0.002149 0.004008 -0.001355 + 1145 0.012575 0.018012 -0.011467 + 1146 -0.018572 0.011663 -0.005755 + 1147 0.000951 -0.000232 0.005705 + 1148 0.001030 -0.002411 0.005162 + 1149 -0.004871 0.010528 0.006213 + 1150 -0.003431 0.005236 0.003321 + 1151 -0.006083 0.008172 0.003730 + 1152 0.021201 0.002738 -0.026021 + 1153 -0.000559 -0.001274 0.002074 + 1154 -0.000342 -0.008595 -0.003314 + 1155 -0.004563 0.013150 0.001114 + 1156 0.002547 -0.003346 0.000793 + 1157 -0.004000 0.002915 0.001908 + 1158 0.008526 -0.013385 0.001263 + 1159 0.003331 -0.001629 -0.001592 + 1160 0.012216 0.004263 0.001290 + 1161 -0.024729 0.027722 0.012828 + 1162 -0.004556 0.005331 -0.000790 + 1163 -0.001260 0.004809 0.012624 + 1164 0.009151 0.007740 0.005908 + 1165 0.006739 -0.002486 0.000962 + 1166 0.002801 -0.001010 0.007063 + 1167 0.006266 -0.009780 0.000447 + 1168 -0.001756 -0.006121 -0.000399 + 1169 0.002128 0.011752 0.003187 + 1170 -0.000744 -0.004455 -0.001624 + 1171 -0.003120 -0.007987 0.008768 + 1172 -0.001279 -0.014309 0.014916 + 1173 -0.003496 -0.005392 0.006518 + 1174 -0.005252 -0.000094 0.002610 + 1175 -0.004319 0.000327 0.003799 + 1176 0.014469 -0.001407 -0.023557 + 1177 -0.001733 0.011173 0.001097 + 1178 0.019607 0.000729 -0.008577 + 1179 -0.013430 0.021297 -0.011104 + 1180 0.005550 -0.002953 -0.004489 + 1181 -0.021164 -0.004283 0.009224 + 1182 0.020762 -0.011806 0.008058 + 1183 -0.003934 -0.006346 0.000789 + 1184 -0.004154 -0.012917 -0.000804 + 1185 0.001834 -0.003234 0.006486 + 1186 -0.003359 -0.000166 0.000482 + 1187 -0.010938 -0.009570 0.011838 + 1188 -0.006339 -0.002743 -0.017319 + 1189 -0.002008 -0.000238 -0.002842 + 1190 0.009730 0.002797 -0.000255 + 1191 0.004802 0.018470 -0.005529 + 1192 0.002978 0.003254 0.000406 + 1193 0.001762 -0.016118 0.017481 + 1194 0.009625 0.005549 -0.002833 + 1195 -0.005277 -0.000015 -0.004247 + 1196 0.008535 -0.018189 -0.023760 + 1197 -0.020839 0.008581 0.007193 + 1198 0.001976 -0.001531 0.001386 + 1199 -0.012488 -0.005613 0.004418 + 1200 0.012387 0.001324 -0.002579 + 1201 0.004612 0.001574 0.002430 + 1202 0.004011 0.024078 0.008286 + 1203 0.028635 -0.001749 -0.000378 + 1204 -0.001292 -0.004163 0.001688 + 1205 0.018917 -0.005327 -0.022863 + 1206 -0.021498 0.026796 -0.015481 + 1207 -0.004360 -0.003023 -0.007483 + 1208 0.015222 -0.007834 -0.014901 + 1209 -0.015487 -0.004003 -0.024684 + 1210 0.000162 -0.000232 -0.002511 + 1211 0.005663 0.001759 0.003041 + 1212 -0.026577 0.001752 0.009499 + 1213 -0.002118 -0.004800 0.002106 + 1214 0.012772 0.013880 -0.004149 + 1215 0.008831 0.004495 0.004278 + 1216 -0.001002 0.000396 0.000450 + 1217 0.001493 -0.000300 0.006615 + 1218 0.022789 -0.011336 -0.001626 + 1219 -0.002165 0.002305 -0.004399 + 1220 -0.001727 0.010653 0.006150 + 1221 0.001799 -0.000399 -0.015101 + 1222 -0.002535 -0.001664 0.000167 + 1223 -0.007939 0.009699 -0.003581 + 1224 -0.009214 -0.009452 -0.003331 + 1225 -0.002745 0.003249 0.011490 + 1226 0.010727 -0.015563 0.011870 + 1227 -0.003771 0.013856 -0.015486 + 1228 -0.000932 0.001513 0.000721 + 1229 -0.002528 0.000192 0.015301 + 1230 -0.027023 -0.007231 0.009659 + 1231 -0.005525 0.001099 -0.001369 + 1232 -0.002318 -0.008510 -0.009719 + 1233 -0.005945 -0.008347 0.009845 + 1234 -0.000817 -0.006097 -0.001394 + 1235 0.026844 0.005400 -0.013998 + 1236 -0.019837 0.017329 -0.010038 + 1237 -0.002691 -0.005371 -0.000786 + 1238 -0.007304 -0.006372 0.007409 + 1239 -0.014066 -0.005252 0.014237 + 1240 -0.000660 -0.004157 -0.007445 + 1241 -0.015343 -0.015681 0.000525 + 1242 -0.004856 0.008296 -0.020506 + 1243 -0.000451 -0.006253 0.005274 + 1244 -0.016626 -0.024128 0.003146 + 1245 0.003430 -0.001516 0.006995 + 1246 0.002369 0.000761 -0.000692 + 1247 -0.011034 0.017913 -0.003576 + 1248 0.014886 0.005052 0.010870 + 1249 0.000976 0.003044 0.004043 + 1250 0.002084 0.009119 -0.003484 + 1251 -0.004682 -0.003095 0.024419 + 1252 -0.001872 0.005519 -0.003878 + 1253 0.014045 0.004474 0.006660 + 1254 -0.006683 -0.012923 -0.006357 + 1255 -0.007125 -0.002296 0.002894 + 1256 -0.009126 -0.000293 0.008175 + 1257 -0.005668 -0.002902 -0.000640 + 1258 -0.009805 0.000500 -0.001546 + 1259 -0.007254 -0.007274 0.010849 + 1260 0.005786 0.004719 0.004479 + 1261 0.000767 -0.007091 -0.002809 + 1262 -0.010861 -0.024470 -0.006678 + 1263 0.010352 0.003874 -0.018616 + 1264 -0.001332 -0.000776 -0.001533 + 1265 0.005055 -0.002761 -0.000154 + 1266 0.001293 -0.010766 0.003695 + 1267 0.004101 0.005423 0.004161 + 1268 -0.006495 -0.001645 0.007645 + 1269 0.024277 0.000761 0.018148 + 1270 0.000384 -0.004677 0.001777 + 1271 -0.000305 -0.022286 0.006378 + 1272 0.014900 -0.009298 0.005029 + 1273 -0.002201 -0.002422 -0.001266 + 1274 0.002419 0.000621 -0.006170 + 1275 0.002242 -0.003567 -0.006329 + 1276 0.001155 0.006214 -0.002164 + 1277 -0.025679 0.011598 0.001775 + 1278 -0.016652 0.005061 0.002255 + 1279 -0.000163 0.000193 -0.001041 + 1280 -0.002822 -0.004131 -0.007696 + 1281 -0.007029 0.005316 -0.012422 + 1282 -0.001259 -0.001443 0.001295 + 1283 -0.000992 -0.027820 -0.000474 + 1284 -0.012190 -0.043729 -0.008054 + 1285 -0.001840 -0.001572 0.001104 + 1286 0.008311 0.001263 -0.001841 + 1287 0.001277 0.000429 -0.007113 + 1288 -0.005029 -0.002280 -0.002761 + 1289 -0.024723 0.012515 -0.012864 + 1290 -0.013845 -0.020399 0.001674 + 1291 -0.000161 0.002303 0.004199 + 1292 -0.010956 -0.010528 0.017163 + 1293 0.023554 -0.006815 0.021159 + 1294 0.000772 -0.000829 0.004462 + 1295 0.024106 -0.007189 -0.017980 + 1296 -0.011795 0.000225 0.018351 + 1297 -0.002503 0.000288 -0.000931 + 1298 -0.001901 -0.006775 -0.001166 + 1299 -0.002626 0.004209 -0.000596 + 1300 -0.003248 -0.009856 0.001496 + 1301 -0.008616 0.000206 -0.000660 + 1302 0.012991 -0.001944 0.010735 + 1303 0.000183 0.003767 -0.002207 + 1304 0.002875 0.006021 0.006091 + 1305 -0.003343 -0.008883 0.015455 + 1306 -0.003761 0.009400 -0.007147 + 1307 -0.002601 -0.012510 0.005900 + 1308 -0.013464 0.021935 0.006364 + 1309 0.007717 -0.006568 -0.004280 + 1310 0.004551 -0.013432 0.001741 + 1311 0.016676 -0.009730 -0.005415 + 1312 -0.003518 -0.000115 0.000120 + 1313 -0.018566 -0.004441 0.007076 + 1314 0.011422 0.004168 0.013848 + 1315 -0.002232 0.003004 -0.005210 + 1316 -0.004985 -0.000655 -0.007286 + 1317 -0.004756 0.005461 -0.010032 + 1318 0.003296 -0.000345 0.003797 + 1319 0.000013 0.003387 0.009258 + 1320 -0.001175 0.009021 0.016554 + 1321 0.004610 0.000563 0.001890 + 1322 0.001511 0.004957 0.010795 + 1323 -0.000517 0.009529 0.012695 + 1324 0.003561 -0.002127 -0.002139 + 1325 -0.016355 -0.004573 0.011414 + 1326 0.002437 -0.000969 0.003958 + 1327 -0.003191 0.002772 0.003706 + 1328 0.002188 0.004078 0.024902 + 1329 0.005804 0.008997 0.000514 + 1330 0.000169 -0.001823 0.006601 + 1331 -0.012837 0.016738 0.032499 + 1332 -0.003787 -0.003993 0.005792 + 1333 -0.006500 -0.001952 -0.005568 + 1334 0.004632 0.002607 -0.001417 + 1335 0.007826 -0.018417 0.003893 + 1336 0.001400 0.000629 -0.002329 + 1337 -0.026090 -0.010827 -0.007428 + 1338 0.014757 0.003359 0.005866 + 1339 0.005344 0.002452 0.000637 + 1340 0.002304 0.001516 0.008371 + 1341 0.003116 0.003502 0.000920 + 1342 0.000219 0.006872 -0.006361 + 1343 0.004872 0.004948 -0.015461 + 1344 0.002293 0.008990 -0.007103 + 1345 -0.000248 -0.001405 -0.000404 + 1346 0.016050 0.005473 0.014883 + 1347 0.000661 0.010958 0.009762 + 1348 0.002507 0.004854 0.004016 + 1349 -0.000026 0.005865 -0.004933 + 1350 -0.003541 0.012071 0.011984 + 1351 -0.000388 -0.001662 -0.002624 + 1352 -0.008781 0.002236 0.005933 + 1353 -0.002303 0.010321 -0.013971 + 1354 0.000266 0.005381 0.006218 + 1355 -0.030793 -0.017551 0.006520 + 1356 -0.001710 0.006198 0.003481 + 1357 -0.000575 0.000387 0.003498 + 1358 0.011844 0.006387 0.013823 + 1359 -0.004149 -0.001630 0.001064 + 1360 0.002966 -0.001211 -0.000529 + 1361 0.011026 0.001160 0.001568 + 1362 0.015143 -0.001234 0.000065 + 1363 0.000976 0.001952 -0.002769 + 1364 0.013527 0.011152 0.001594 + 1365 -0.000179 -0.000211 -0.002554 + 1366 -0.005351 -0.004969 -0.002979 + 1367 -0.006889 0.021662 -0.005435 + 1368 -0.002462 0.016113 0.008657 + 1369 -0.000975 0.000751 -0.000755 + 1370 -0.003243 0.006738 -0.001393 + 1371 -0.002267 -0.000779 0.003167 + 1372 0.001566 -0.003190 -0.000583 + 1373 -0.002018 -0.005136 0.012563 + 1374 -0.006828 0.007134 0.011132 + 1375 0.005244 -0.004715 -0.003319 + 1376 -0.010064 -0.001392 0.024842 + 1377 -0.003331 -0.012180 0.011450 + 1378 0.005044 -0.003538 0.000197 + 1379 0.014932 -0.005316 0.014871 + 1380 0.002959 -0.015155 -0.010790 + 1381 0.004288 0.003508 0.003045 + 1382 0.010516 0.006731 0.001181 + 1383 0.003157 0.002004 0.039661 + 1384 -0.003464 -0.000341 -0.002519 + 1385 0.000767 -0.010574 0.002375 + 1386 0.012132 0.009405 0.005728 + 1387 -0.002537 0.005096 -0.000141 + 1388 0.008455 -0.000335 0.003398 + 1389 0.000567 0.012932 0.006368 + 1390 0.007440 -0.002304 0.001444 + 1391 0.003946 0.007849 -0.005030 + 1392 0.012038 -0.016280 0.007159 + 1393 -0.001061 -0.002610 -0.000083 + 1394 0.010905 -0.006613 -0.001941 + 1395 -0.013885 -0.027620 0.005494 + 1396 0.013746 0.003525 0.007163 + 1397 0.003586 0.002644 -0.010792 + 1398 0.018544 0.013850 0.017322 + 1399 0.004571 0.000027 -0.001760 + 1400 0.012220 0.001858 -0.006751 + 1401 0.009850 -0.002003 0.019339 + 1402 -0.001383 0.002281 -0.007042 + 1403 -0.003363 0.001654 -0.017801 + 1404 0.011330 0.009635 0.005470 + 1405 0.000650 -0.001098 -0.005942 + 1406 0.005198 -0.008028 -0.003832 + 1407 0.017668 -0.005738 0.026099 + 1408 -0.001891 0.001162 0.003476 + 1409 -0.003537 0.018838 0.000972 + 1410 0.007980 0.016250 0.030292 + 1411 -0.001348 0.000197 0.004181 + 1412 -0.002255 -0.008393 -0.001355 + 1413 -0.008567 -0.008184 -0.000151 + 1414 -0.001145 0.001777 -0.004250 + 1415 -0.002565 -0.000609 -0.002622 + 1416 0.017182 0.009342 -0.008899 + 1417 -0.000336 -0.000833 -0.006619 + 1418 0.006594 -0.014023 -0.011705 + 1419 -0.010047 -0.002912 -0.003804 + 1420 0.005759 0.000406 0.005233 + 1421 -0.013174 -0.018780 -0.002966 + 1422 -0.003551 -0.005212 0.011087 + 1423 -0.001811 -0.005836 -0.002120 + 1424 -0.008296 0.022099 0.012646 + 1425 0.010130 0.006059 0.033707 + 1426 0.001039 -0.001025 -0.000459 + 1427 0.004468 0.000527 0.001539 + 1428 -0.001728 -0.005304 0.003140 + 1429 -0.000141 -0.003112 0.003400 + 1430 0.007530 -0.026022 0.005020 + 1431 -0.011982 0.032142 -0.001998 + 1432 -0.001642 0.003923 -0.003350 + 1433 0.016086 -0.002664 -0.005695 + 1434 -0.010354 0.000136 0.021071 + 1435 0.001502 -0.001507 0.005856 + 1436 -0.003359 -0.017617 -0.013060 + 1437 -0.001621 -0.013764 -0.008355 + 1438 -0.006074 0.001165 0.001910 + 1439 -0.004946 0.003618 0.011324 + 1440 -0.007761 0.002697 -0.006763 + 1441 -0.009332 0.000898 0.000750 + 1442 -0.017083 -0.010335 0.011191 + 1443 0.020780 0.013466 -0.015083 + 1444 -0.008140 -0.008032 -0.000180 + 1445 -0.001836 -0.008988 0.003973 + 1446 -0.008280 -0.004548 -0.003224 + 1447 0.000996 -0.002062 -0.001184 + 1448 -0.001863 -0.012096 0.003957 + 1449 -0.027050 0.007989 0.002157 + 1450 -0.001321 -0.000325 0.001355 + 1451 -0.006885 -0.000536 -0.022446 + 1452 0.008792 -0.007975 0.003329 + 1453 -0.003682 -0.004782 -0.002567 + 1454 -0.001180 -0.009011 0.018662 + 1455 -0.000958 -0.004899 0.013723 + 1456 0.000545 0.011919 -0.001753 + 1457 0.023799 0.010298 -0.002649 + 1458 0.014717 0.007757 -0.005400 + 1459 -0.004576 -0.007691 0.001365 + 1460 -0.006577 -0.016846 -0.022862 + 1461 -0.005206 0.003687 0.012428 + 1462 0.001923 -0.004758 -0.001993 + 1463 0.006600 0.017503 0.006935 + 1464 -0.006747 -0.003482 -0.000067 + 1465 0.000613 0.004580 0.004038 + 1466 -0.001945 0.022605 -0.000652 + 1467 0.017624 -0.001392 0.003829 + 1468 -0.003065 -0.003003 -0.000747 + 1469 -0.012664 -0.016566 -0.007030 + 1470 0.008660 -0.008358 0.004763 + 1471 -0.004008 0.000421 -0.006040 + 1472 0.003555 0.008566 -0.015842 + 1473 -0.001032 0.001700 -0.010204 + 1474 -0.000556 0.000599 0.003074 + 1475 0.001542 0.002939 0.005269 + 1476 -0.005281 -0.001944 0.003338 + 1477 -0.000195 -0.000293 -0.001004 + 1478 -0.009991 -0.005354 -0.013386 + 1479 -0.000476 -0.017594 0.007900 + 1480 0.000550 -0.000431 0.001422 + 1481 0.018094 -0.005183 0.016234 + 1482 0.010706 0.011668 -0.017772 + 1483 0.001291 0.006499 0.000951 + 1484 0.009985 -0.016962 0.009714 + 1485 0.020849 0.018365 -0.008351 + 1486 0.006940 0.004692 -0.002409 + 1487 0.022308 0.010182 -0.022897 + 1488 0.000269 0.008847 0.011834 + 1489 0.002051 0.007334 -0.000125 + 1490 -0.023048 0.013759 -0.030276 + 1491 0.023523 -0.005817 0.007754 + 1492 -0.001269 0.002979 0.001311 + 1493 -0.005596 0.006174 0.011007 + 1494 -0.009061 0.022719 0.002133 + 1495 -0.001128 0.004307 -0.002381 + 1496 -0.004340 0.013891 -0.003505 + 1497 0.001822 -0.005505 -0.001135 + 1498 -0.000910 0.001437 0.000165 + 1499 0.004510 -0.000360 -0.006425 + 1500 0.003993 0.000498 0.007321 + 1501 -0.002868 -0.000316 -0.000509 + 1502 0.000620 0.011286 0.008461 + 1503 -0.013079 -0.008157 0.007561 + 1504 -0.003002 0.003413 0.004968 + 1505 0.015262 -0.005133 0.012052 + 1506 -0.003968 -0.003643 0.003514 + 1507 0.005087 -0.001882 -0.000518 + 1508 0.000932 -0.002238 0.000800 + 1509 -0.008149 0.000695 -0.000827 + 1510 -0.001261 -0.003375 0.000333 + 1511 -0.001224 -0.004135 -0.003080 + 1512 0.009246 -0.010372 0.026354 + 1513 0.000697 -0.003200 0.001222 + 1514 -0.002319 0.003800 0.022860 + 1515 -0.018205 0.011600 -0.011416 + 1516 -0.001731 -0.001076 0.002612 + 1517 -0.004661 -0.010783 -0.001505 + 1518 0.016208 0.002810 0.004482 + 1519 0.003508 -0.001750 0.002537 + 1520 0.024576 -0.026041 -0.004083 + 1521 -0.019140 0.000844 0.001909 + 1522 -0.000341 0.001152 0.001967 + 1523 -0.020076 0.003364 0.001315 + 1524 -0.000942 0.000692 -0.003283 + 1525 -0.006519 -0.000419 0.000991 + 1526 -0.004033 0.006531 0.004791 + 1527 0.005626 0.012187 -0.014266 + 1528 0.001113 -0.004253 0.011930 + 1529 -0.010144 0.003567 0.009059 + 1530 -0.003464 0.001115 0.011591 + 1531 0.000006 0.000074 0.005751 + 1532 0.003604 0.008464 0.010627 + 1533 -0.004351 -0.009621 -0.000453 + 1534 -0.000196 -0.001160 0.002795 + 1535 -0.006855 0.001414 0.005552 + 1536 -0.000894 -0.002102 0.005053 + 1537 -0.002040 -0.005887 -0.003590 + 1538 -0.006852 -0.011947 -0.023080 + 1539 -0.016070 0.000160 0.010390 + 1540 0.004712 0.002848 -0.002998 + 1541 -0.004259 0.007840 0.008142 + 1542 -0.004861 0.004263 0.011728 + 1543 0.006968 -0.004871 0.004119 + 1544 -0.016558 -0.002046 -0.006090 + 1545 -0.006229 0.004475 0.001436 + 1546 -0.002341 -0.004733 -0.003946 + 1547 0.003563 0.004733 0.009615 + 1548 -0.013018 0.004747 -0.004733 + 1549 0.001703 -0.000331 0.003605 + 1550 0.005459 -0.002653 -0.012447 + 1551 0.013689 0.008625 -0.003301 + 1552 0.003195 0.001205 -0.000779 + 1553 -0.003336 -0.011439 -0.004979 + 1554 0.001015 0.018568 -0.007361 + 1555 -0.001647 -0.003759 0.001214 + 1556 0.015583 -0.016961 0.000384 + 1557 -0.011138 -0.013161 -0.015913 + 1558 0.005848 -0.002193 -0.007682 + 1559 0.009577 -0.005765 0.010025 + 1560 0.006984 0.005858 -0.020668 + 1561 -0.005040 0.001396 0.001932 + 1562 0.007071 0.009231 0.007700 + 1563 0.001743 0.005137 0.005850 + 1564 0.001857 0.002145 -0.004455 + 1565 -0.007462 0.014047 -0.012730 + 1566 0.013730 -0.006385 0.009586 + 1567 -0.002000 0.003453 -0.001882 + 1568 -0.009622 -0.007424 -0.003371 + 1569 -0.006993 -0.018224 -0.006858 + 1570 0.001461 0.001281 -0.002568 + 1571 0.018901 0.002357 0.001811 + 1572 -0.001592 0.019333 -0.002732 + 1573 -0.001308 -0.005730 -0.002519 + 1574 -0.014074 0.007287 0.021518 + 1575 -0.017324 -0.018775 -0.005647 + 1576 0.002340 -0.001593 0.004994 + 1577 -0.000516 0.003608 0.002676 + 1578 -0.014840 -0.017283 -0.001508 + 1579 -0.001557 -0.002471 -0.002555 + 1580 0.016654 -0.033672 0.006595 + 1581 0.013351 -0.030070 0.003443 + 1582 0.003752 0.001449 0.001862 + 1583 -0.011257 -0.002704 0.007355 + 1584 0.002139 0.006577 0.012771 + 1585 0.002251 0.002492 -0.002180 + 1586 0.010691 -0.005615 -0.001517 + 1587 -0.018738 0.016070 0.006914 + 1588 -0.001600 0.000180 0.001378 + 1589 0.004891 -0.007732 -0.013906 + 1590 -0.015149 0.011285 0.002913 + 1591 0.003944 -0.001162 -0.002407 + 1592 -0.013220 -0.006427 -0.006873 + 1593 -0.008388 0.022805 -0.011588 + 1594 0.000621 -0.004836 0.005509 + 1595 0.006148 -0.013451 0.002326 + 1596 -0.001161 -0.012639 -0.002024 + 1597 -0.005042 0.000613 0.003072 + 1598 -0.002560 -0.009516 -0.007164 + 1599 -0.007736 0.003315 0.007824 + 1600 -0.002409 -0.002549 -0.003082 + 1601 -0.002839 0.004415 -0.008830 + 1602 -0.006633 -0.001003 -0.004060 + 1603 -0.004810 -0.007495 -0.004047 + 1604 0.005200 -0.017270 0.009101 + 1605 0.000670 -0.009280 -0.012848 + 1606 -0.003830 0.001924 -0.002728 + 1607 -0.035525 0.007821 -0.020602 + 1608 0.016575 -0.019547 -0.006176 + 1609 0.003828 0.000099 -0.002605 + 1610 0.017387 0.007652 0.014875 + 1611 0.012190 0.014852 0.016071 + 1612 -0.003436 0.002187 -0.001035 + 1613 -0.005586 -0.003901 0.006033 + 1614 -0.005884 -0.005331 -0.011796 + 1615 -0.001799 -0.005019 0.004011 + 1616 0.002094 -0.028579 0.008471 + 1617 0.023334 0.020189 0.016696 + 1618 -0.000653 -0.003079 -0.001689 + 1619 -0.005925 -0.004542 -0.007489 + 1620 0.003980 0.000361 0.005598 + 1621 -0.000999 0.004025 -0.003724 + 1622 0.000058 0.024442 0.006515 + 1623 0.011473 -0.013431 0.004073 + 1624 0.002923 -0.003314 0.001931 + 1625 0.003377 -0.006029 -0.008704 + 1626 0.002413 0.015094 0.010447 + 1627 0.003654 -0.000619 -0.001261 + 1628 -0.004232 -0.000930 0.001384 + 1629 0.019160 0.000313 -0.006734 + 1630 0.003534 0.002394 -0.000501 + 1631 -0.008068 0.002953 0.008451 + 1632 0.014612 0.006975 -0.004278 + 1633 0.001620 0.003004 0.003226 + 1634 -0.007605 -0.007788 0.011245 + 1635 0.020296 -0.014907 -0.003043 + 1636 -0.002678 -0.006261 0.001869 + 1637 -0.007968 -0.013586 -0.003793 + 1638 -0.015202 -0.007224 -0.014352 + 1639 -0.005816 -0.003019 0.006480 + 1640 -0.001607 -0.004084 0.006246 + 1641 0.008520 -0.008049 0.002824 + 1642 -0.000658 -0.004008 -0.000300 + 1643 -0.000444 0.000650 -0.012168 + 1644 -0.006399 -0.006883 0.005254 + 1645 -0.001317 0.006093 0.001522 + 1646 -0.010770 -0.004270 -0.010989 + 1647 -0.005520 0.020979 0.012203 + 1648 -0.004763 0.001957 0.003649 + 1649 -0.010531 0.001095 0.022741 + 1650 0.001695 -0.009764 -0.029750 + 1651 0.000561 0.003660 0.004562 + 1652 0.004814 -0.011887 -0.011791 + 1653 0.015151 -0.017660 -0.020515 + 1654 -0.003720 -0.008154 0.002101 + 1655 -0.006836 0.005342 0.006830 + 1656 -0.008891 -0.005752 0.002656 + 1657 -0.004211 -0.006534 0.001470 + 1658 0.024344 -0.009232 0.001415 + 1659 -0.010793 -0.032076 -0.013330 + 1660 -0.000393 0.010082 -0.000260 + 1661 -0.003386 0.024037 -0.002341 + 1662 0.005231 -0.007154 0.002310 + 1663 0.004778 0.000685 -0.001247 + 1664 0.006845 -0.000146 -0.002439 + 1665 0.002831 0.001509 -0.001312 + 1666 -0.004575 0.002015 0.002231 + 1667 -0.008714 0.004773 0.019310 + 1668 -0.009036 0.006437 0.017025 + 1669 -0.001102 -0.003004 0.003294 + 1670 0.004690 0.016121 0.007181 + 1671 -0.000881 -0.003815 0.001639 + 1672 -0.000053 -0.001708 0.002633 + 1673 -0.004620 0.003536 0.000715 + 1674 -0.002636 -0.005429 0.007498 + 1675 0.002307 0.001406 0.002665 + 1676 -0.005270 -0.001969 0.007587 + 1677 0.001417 -0.009022 -0.021912 + 1678 0.000203 0.002930 -0.002177 + 1679 0.003819 0.012652 -0.002939 + 1680 -0.001040 0.005171 0.022221 + 1681 -0.001765 0.004140 -0.001020 + 1682 0.015888 -0.002384 -0.000464 + 1683 -0.019573 0.014814 -0.003047 + 1684 -0.002840 -0.000626 0.000097 + 1685 0.019011 -0.004434 -0.031132 + 1686 -0.011722 0.011711 0.019623 + 1687 -0.000720 0.008278 0.001232 + 1688 -0.000014 -0.005707 0.005722 + 1689 0.006445 -0.004607 0.004541 + 1690 -0.008451 -0.005406 -0.003097 + 1691 -0.025859 -0.004092 0.011942 + 1692 0.003198 0.017013 -0.015979 + 1693 0.001237 0.005482 0.001012 + 1694 -0.003233 0.012773 -0.012817 + 1695 -0.013658 -0.008102 0.007350 + 1696 0.004867 0.002547 -0.001769 + 1697 0.019074 -0.004173 0.005165 + 1698 0.008487 0.001064 0.000080 + 1699 0.002766 -0.001251 -0.001561 + 1700 -0.019200 0.027169 -0.007481 + 1701 0.006036 -0.028485 -0.009388 + 1702 -0.005460 0.002563 0.001784 + 1703 -0.017462 0.006398 0.005231 + 1704 -0.014453 0.005484 0.004388 + 1705 0.002956 -0.001348 0.006512 + 1706 0.009654 0.004653 0.025184 + 1707 0.006226 -0.001478 -0.018062 + 1708 0.003757 -0.000921 -0.000401 + 1709 0.004307 -0.009700 -0.007768 + 1710 0.003780 -0.012914 0.008582 + 1711 0.004846 -0.002032 -0.000808 + 1712 -0.000823 -0.002500 -0.004619 + 1713 0.014769 -0.010350 0.008970 + 1714 -0.001580 -0.000837 0.000021 + 1715 -0.002003 -0.002972 -0.000158 + 1716 -0.004469 -0.000404 0.001257 + 1717 -0.001782 0.001231 -0.003624 + 1718 -0.009550 0.008477 -0.006010 + 1719 -0.003240 -0.001801 -0.002707 + 1720 -0.003131 -0.002749 -0.002782 + 1721 -0.003319 -0.008008 -0.009572 + 1722 -0.003280 -0.008289 -0.009069 + 1723 -0.006776 0.001807 0.000809 + 1724 0.000630 0.005359 0.003033 + 1725 0.016012 0.013546 0.014364 + 1726 -0.005383 0.003683 -0.001052 + 1727 -0.000343 -0.021814 -0.000655 + 1728 0.015975 0.004809 -0.015863 + 1729 -0.002843 0.002136 0.000031 + 1730 0.008511 0.002265 -0.002748 + 1731 -0.026285 -0.002274 -0.004757 + 1732 0.005294 -0.003565 0.004694 + 1733 -0.002668 0.001103 -0.001112 + 1734 -0.009429 0.006969 -0.008965 + 1735 -0.001634 0.000110 0.001819 + 1736 -0.004942 0.001203 -0.007254 + 1737 -0.002655 0.002573 -0.003610 + 1738 -0.004831 0.005860 0.001407 + 1739 -0.014232 0.009476 0.016389 + 1740 -0.017895 0.005674 -0.009379 + 1741 0.003013 -0.002508 -0.001228 + 1742 0.000746 0.006449 -0.005992 + 1743 0.006650 -0.002762 0.000152 + 1744 0.002550 -0.008457 0.001324 + 1745 -0.001868 -0.010233 -0.023525 + 1746 0.003968 -0.007880 0.008439 + 1747 -0.000591 0.004322 -0.003592 + 1748 -0.014424 0.009132 0.003708 + 1749 0.012052 -0.004950 -0.011581 + 1750 0.001849 0.003842 -0.009164 + 1751 0.009453 -0.005684 -0.004817 + 1752 0.001564 0.018776 -0.004831 + 1753 0.000794 0.000968 -0.001710 + 1754 -0.003816 -0.004723 -0.000498 + 1755 -0.011972 0.005633 -0.006975 + 1756 -0.004635 0.005064 -0.004764 + 1757 -0.010722 0.012077 -0.027297 + 1758 -0.003376 0.000707 0.006078 + 1759 0.001092 0.005159 -0.000557 + 1760 0.014326 0.002844 -0.021424 + 1761 0.019579 -0.002405 -0.009532 + 1762 -0.000565 0.006632 0.002294 + 1763 -0.025047 0.006219 0.001583 + 1764 -0.004637 -0.007484 0.007079 + 1765 0.002563 -0.001616 -0.003316 + 1766 -0.001239 0.014897 -0.002355 + 1767 -0.001256 -0.009226 0.009450 + 1768 0.001056 0.005329 -0.003831 + 1769 -0.012555 0.037676 0.021233 + 1770 -0.005969 -0.003116 -0.014248 + 1771 0.000691 0.001302 0.002405 + 1772 -0.015733 0.001224 -0.004288 + 1773 0.006783 0.015986 -0.003342 + 1774 0.002355 0.002897 -0.002965 + 1775 -0.000435 0.005789 0.007980 + 1776 0.014211 0.000855 -0.014841 + 1777 -0.004596 -0.002169 0.000774 + 1778 0.002630 -0.027237 0.012553 + 1779 -0.000727 -0.003394 -0.009924 + 1780 0.001821 -0.001310 0.000540 + 1781 0.005476 -0.002057 0.001588 + 1782 0.008060 0.013457 -0.013767 + 1783 0.003078 -0.007047 0.009501 + 1784 -0.004392 -0.004982 0.015684 + 1785 -0.021173 -0.003917 -0.003013 + 1786 0.001492 -0.007162 -0.003460 + 1787 0.020179 0.025050 0.005018 + 1788 -0.018378 -0.021938 0.007656 + 1789 -0.000363 0.004076 -0.003991 + 1790 0.012179 0.023942 -0.003853 + 1791 0.002207 0.011773 0.006443 + 1792 0.001993 0.000538 0.002365 + 1793 0.008602 -0.013779 -0.007218 + 1794 0.007374 0.001122 0.001108 + 1795 0.003207 -0.011319 -0.004081 + 1796 0.010332 -0.007827 -0.001929 + 1797 0.001869 0.022609 0.012256 + 1798 0.001101 0.003835 0.002357 + 1799 -0.003624 0.011759 0.002745 + 1800 0.001557 -0.002337 -0.004179 + 1801 0.003327 -0.001910 -0.005250 + 1802 0.011996 0.003017 0.013309 + 1803 -0.013682 -0.002775 -0.008939 + 1804 -0.002064 -0.000934 0.000427 + 1805 -0.012146 0.024406 -0.015171 + 1806 0.005030 -0.019570 0.004311 + 1807 0.003003 0.004365 0.002257 + 1808 0.000823 0.000086 -0.005161 + 1809 -0.003001 0.001206 0.008241 + 1810 0.005602 -0.001423 0.002945 + 1811 0.000330 0.001483 -0.011075 + 1812 0.003652 0.009252 -0.000166 + 1813 0.004531 -0.000860 -0.000170 + 1814 0.018728 0.013621 0.031510 + 1815 0.011579 -0.009257 -0.004100 + 1816 0.002862 0.000330 -0.002342 + 1817 -0.003456 -0.001426 -0.004566 + 1818 -0.006589 0.018593 0.018322 + 1819 -0.001663 0.002113 0.003120 + 1820 0.002523 0.005185 0.010725 + 1821 -0.006456 -0.005159 0.018366 + 1822 -0.000677 -0.000638 0.005530 + 1823 0.006499 0.011396 0.003392 + 1824 0.000945 -0.008826 -0.007441 + 1825 -0.002582 0.001006 0.000170 + 1826 -0.000739 0.010378 -0.012944 + 1827 -0.004082 -0.009693 0.012271 + 1828 -0.002259 -0.002179 0.001812 + 1829 0.004365 0.028602 0.007523 + 1830 -0.001047 0.006781 -0.010318 + 1831 0.003053 0.002227 0.004523 + 1832 -0.004297 -0.007295 0.001900 + 1833 0.002925 0.002066 0.004473 + 1834 0.003171 0.000025 0.002189 + 1835 0.001188 0.002838 0.001014 + 1836 0.006142 0.003073 -0.003689 + 1837 0.009818 0.005253 0.006222 + 1838 0.013907 -0.003607 0.006764 + 1839 -0.000327 0.015573 -0.010930 + 1840 -0.003110 -0.005538 0.000400 + 1841 0.006244 -0.021206 -0.003853 + 1842 -0.010299 0.008474 0.021147 + 1843 -0.001053 -0.000598 0.004581 + 1844 -0.013621 0.002557 -0.003175 + 1845 -0.002495 0.000789 0.011106 + 1846 -0.000137 -0.004006 -0.000014 + 1847 -0.017819 -0.013981 0.011316 + 1848 -0.005844 -0.000863 -0.025248 + 1849 -0.002799 0.002996 -0.002499 + 1850 -0.012455 0.012490 -0.004469 + 1851 0.010514 0.009490 -0.009495 + 1852 -0.000560 -0.004144 -0.000656 + 1853 -0.007255 0.002559 0.003817 + 1854 0.004602 -0.007276 0.003469 + 1855 0.000128 0.001144 -0.008402 + 1856 0.008157 0.001721 -0.014464 + 1857 -0.004034 0.002739 -0.008982 + 1858 0.002856 0.004731 -0.003812 + 1859 0.008481 -0.004184 -0.015612 + 1860 -0.004966 0.006658 -0.006541 + 1861 0.005415 -0.007185 0.002622 + 1862 -0.000791 0.004294 0.012806 + 1863 0.006266 -0.008943 0.000048 + 1864 -0.004891 -0.000259 0.002435 + 1865 0.000775 -0.012600 0.009738 + 1866 -0.000239 0.020688 0.014963 + 1867 0.007752 0.006605 0.003522 + 1868 0.005559 0.005449 0.004823 + 1869 0.001382 0.020031 -0.009484 + 1870 0.000269 -0.000837 -0.001948 + 1871 -0.015324 0.006379 0.032972 + 1872 -0.010895 -0.006739 0.002233 + 1873 0.002406 -0.005817 -0.007929 + 1874 0.011974 0.013774 0.020789 + 1875 -0.005616 -0.012309 -0.023698 + 1876 -0.002712 -0.000118 0.000894 + 1877 -0.000559 -0.018665 -0.005699 + 1878 -0.022904 -0.016730 0.007620 + 1879 -0.006235 -0.000119 -0.005440 + 1880 -0.008616 0.001720 0.002602 + 1881 -0.019263 0.001295 0.018377 + 1882 -0.002493 0.002824 -0.002915 + 1883 0.007384 0.000692 0.003462 + 1884 -0.019228 -0.005451 0.005676 + 1885 0.002956 0.004628 -0.002177 + 1886 0.005617 0.021792 -0.005623 + 1887 -0.010771 -0.007154 -0.002600 + 1888 -0.006932 -0.006388 0.001795 + 1889 -0.026638 0.002211 0.017012 + 1890 -0.006429 -0.013703 0.021233 + 1891 0.004179 0.001508 -0.002942 + 1892 -0.015358 0.009799 -0.025507 + 1893 -0.009827 0.001263 -0.015038 + 1894 0.002515 0.004808 -0.006083 + 1895 -0.001395 -0.005178 0.010798 + 1896 0.005498 0.001296 -0.013456 + 1897 -0.006679 0.000004 0.000833 + 1898 -0.006339 0.003210 0.000555 + 1899 -0.007815 -0.000155 0.006317 + 1900 -0.003334 -0.000730 -0.000139 + 1901 -0.003197 -0.021225 -0.009098 + 1902 0.003310 -0.008203 -0.004863 + 1903 -0.007379 0.001152 -0.003847 + 1904 -0.008175 0.003836 -0.004939 + 1905 -0.007216 0.002039 -0.012076 + 1906 -0.002751 -0.006050 -0.001404 + 1907 -0.005827 0.008129 0.005351 + 1908 0.010377 0.010628 0.018761 + 1909 -0.002571 -0.007065 0.006215 + 1910 -0.004848 -0.014622 0.001577 + 1911 -0.004351 -0.002361 0.020679 + 1912 0.006139 0.001291 0.002464 + 1913 0.004939 0.003608 0.002097 + 1914 0.004274 0.000152 0.002451 + 1915 0.002989 0.000832 -0.000352 + 1916 -0.014159 -0.000914 0.002187 + 1917 0.012237 -0.003167 0.009134 + 1918 -0.004575 -0.001662 0.000082 + 1919 -0.007883 -0.002056 0.002571 + 1920 -0.003336 -0.001305 -0.000658 + 1921 0.004366 0.000439 0.001158 + 1922 -0.000155 0.003368 0.010592 + 1923 -0.014972 -0.009424 -0.018312 + 1924 -0.000613 -0.002374 0.000797 + 1925 0.007460 -0.016336 -0.000977 + 1926 -0.006787 0.004573 0.010255 + 1927 -0.002452 -0.000122 0.000124 + 1928 -0.015584 -0.009431 -0.007285 + 1929 -0.000101 0.008080 -0.015191 + 1930 0.002197 0.002310 -0.001612 + 1931 0.016237 -0.005090 0.018070 + 1932 0.001709 -0.003220 -0.011865 + 1933 -0.001150 0.000898 0.004173 + 1934 0.000323 -0.000312 -0.014495 + 1935 0.000516 -0.000491 -0.011422 + 1936 -0.005815 -0.002965 0.000187 + 1937 0.008195 0.018425 -0.027236 + 1938 -0.010921 -0.007575 -0.002217 + 1939 -0.004740 0.002745 0.006330 + 1940 0.002035 0.006523 0.010880 + 1941 -0.012191 0.004818 0.006605 + 1942 -0.003197 -0.004418 -0.003375 + 1943 0.003590 -0.017196 0.008070 + 1944 0.004548 0.006106 0.016045 + 1945 0.005444 0.002200 0.004561 + 1946 0.004448 0.009092 -0.001577 + 1947 -0.000522 0.006033 0.006559 + 1948 0.005450 0.001267 0.002269 + 1949 0.027952 -0.012604 0.001935 + 1950 -0.004826 -0.018174 0.014813 + 1951 0.005498 -0.000626 0.001156 + 1952 0.001428 -0.010472 0.000805 + 1953 -0.010198 -0.005573 -0.014564 + 1954 0.001605 -0.006572 0.005587 + 1955 -0.002403 -0.004981 0.000460 + 1956 0.010287 -0.003414 0.005774 + 1957 -0.005679 0.003540 -0.003175 + 1958 -0.005054 0.005203 -0.002733 + 1959 -0.006462 0.003843 0.002657 + 1960 -0.006606 -0.002499 -0.001538 + 1961 0.027567 -0.002565 0.034908 + 1962 0.001905 -0.003739 -0.001134 + 1963 -0.000871 0.002779 0.006534 + 1964 -0.013473 -0.002631 0.001200 + 1965 -0.008136 0.003625 0.001725 + 1966 0.002375 -0.002767 -0.000214 + 1967 0.015603 0.001192 0.006785 + 1968 -0.008229 0.002751 0.010337 + 1969 -0.002111 -0.006139 0.006236 + 1970 0.025783 -0.003684 0.015052 + 1971 -0.008026 -0.018580 0.028847 + 1972 -0.001966 -0.005103 0.002533 + 1973 0.025504 -0.012928 0.014439 + 1974 0.015919 0.008653 -0.013047 + 1975 -0.002145 -0.003853 -0.002353 + 1976 0.020573 0.023626 0.033600 + 1977 0.002418 -0.000127 0.000258 + 1978 -0.000168 -0.002747 0.002505 + 1979 0.011847 0.007945 0.003222 + 1980 0.002222 -0.001343 0.005437 + 1981 -0.004734 0.003071 -0.000955 + 1982 0.003752 -0.001882 -0.005052 + 1983 -0.008195 0.007844 0.004577 + 1984 0.007575 0.002209 -0.000466 + 1985 -0.005510 0.009650 -0.004399 + 1986 0.018263 0.019292 -0.008157 + 1987 -0.005098 -0.001581 -0.000328 + 1988 -0.004522 -0.021884 -0.005509 + 1989 -0.001598 -0.001668 0.002704 + 1990 -0.000494 0.002205 0.012458 + 1991 0.003153 0.001522 0.015672 + 1992 -0.000092 -0.002603 0.010098 + 1993 0.001919 -0.007389 0.001539 + 1994 -0.002690 -0.003376 -0.009963 + 1995 -0.005006 0.002932 -0.001670 + 1996 -0.003089 -0.005736 0.003689 + 1997 0.010713 -0.027613 -0.023000 + 1998 -0.006878 0.009457 0.006998 + 1999 -0.001817 0.000266 -0.004238 + 2000 -0.010974 0.005190 0.000117 + 2001 -0.008937 -0.003277 0.004337 + 2002 -0.000987 -0.001334 -0.004265 + 2003 -0.022280 -0.011677 -0.018343 + 2004 -0.010076 -0.005729 -0.026032 + +Bonds + + 1 3 1 7 + 2 2 1 3 + 3 1 1 2 + 4 4 2 5 + 5 4 2 6 + 6 4 2 4 + 7 6 7 19 + 8 5 7 8 + 9 1 8 9 + 10 7 8 11 + 11 8 8 20 + 12 3 9 28 + 13 2 9 10 + 14 10 11 21 + 15 9 11 12 + 16 10 11 22 + 17 11 12 14 + 18 11 12 13 + 19 12 13 23 + 20 11 13 15 + 21 12 14 24 + 22 11 14 16 + 23 11 15 17 + 24 12 15 25 + 25 11 16 17 + 26 12 16 26 + 27 13 17 18 + 28 14 18 27 + 29 5 28 29 + 30 6 28 32 + 31 1 29 30 + 32 8 29 33 + 33 8 29 34 + 34 3 30 35 + 35 2 30 31 + 36 5 35 36 + 37 6 35 39 + 38 1 36 37 + 39 8 36 40 + 40 8 36 41 + 41 2 37 38 + 42 3 37 42 + 43 6 42 53 + 44 5 42 43 + 45 1 43 44 + 46 7 43 46 + 47 8 43 54 + 48 3 44 62 + 49 2 44 45 + 50 10 46 56 + 51 10 46 55 + 52 9 46 47 + 53 11 47 48 + 54 11 47 49 + 55 11 48 50 + 56 12 48 57 + 57 11 49 51 + 58 12 49 58 + 59 11 50 52 + 60 12 50 59 + 61 11 51 52 + 62 12 51 60 + 63 12 52 61 + 64 6 62 70 + 65 5 62 63 + 66 7 63 66 + 67 1 63 64 + 68 8 63 71 + 69 2 64 65 + 70 3 64 79 + 71 15 66 67 + 72 10 66 73 + 73 10 66 72 + 74 10 67 75 + 75 10 67 74 + 76 16 67 68 + 77 17 68 69 + 78 4 69 76 + 79 4 69 78 + 80 4 69 77 + 81 5 79 80 + 82 6 79 81 + 83 4 80 84 + 84 4 80 83 + 85 4 80 82 + 86 18 85 86 + 87 18 85 87 + 88 18 88 90 + 89 18 88 89 + 90 18 91 93 + 91 18 91 92 + 92 18 94 96 + 93 18 94 95 + 94 18 97 98 + 95 18 97 99 + 96 18 100 101 + 97 18 100 102 + 98 18 103 104 + 99 18 103 105 + 100 18 106 107 + 101 18 106 108 + 102 18 109 111 + 103 18 109 110 + 104 18 112 114 + 105 18 112 113 + 106 18 115 116 + 107 18 115 117 + 108 18 118 120 + 109 18 118 119 + 110 18 121 123 + 111 18 121 122 + 112 18 124 126 + 113 18 124 125 + 114 18 127 128 + 115 18 127 129 + 116 18 130 132 + 117 18 130 131 + 118 18 133 134 + 119 18 133 135 + 120 18 136 137 + 121 18 136 138 + 122 18 139 140 + 123 18 139 141 + 124 18 142 144 + 125 18 142 143 + 126 18 145 147 + 127 18 145 146 + 128 18 148 150 + 129 18 148 149 + 130 18 151 152 + 131 18 151 153 + 132 18 154 156 + 133 18 154 155 + 134 18 157 159 + 135 18 157 158 + 136 18 160 162 + 137 18 160 161 + 138 18 163 164 + 139 18 163 165 + 140 18 166 168 + 141 18 166 167 + 142 18 169 171 + 143 18 169 170 + 144 18 172 174 + 145 18 172 173 + 146 18 175 177 + 147 18 175 176 + 148 18 178 180 + 149 18 178 179 + 150 18 181 182 + 151 18 181 183 + 152 18 184 186 + 153 18 184 185 + 154 18 187 188 + 155 18 187 189 + 156 18 190 191 + 157 18 190 192 + 158 18 193 194 + 159 18 193 195 + 160 18 196 197 + 161 18 196 198 + 162 18 199 201 + 163 18 199 200 + 164 18 202 204 + 165 18 202 203 + 166 18 205 206 + 167 18 205 207 + 168 18 208 210 + 169 18 208 209 + 170 18 211 212 + 171 18 211 213 + 172 18 214 215 + 173 18 214 216 + 174 18 217 219 + 175 18 217 218 + 176 18 220 222 + 177 18 220 221 + 178 18 223 224 + 179 18 223 225 + 180 18 226 228 + 181 18 226 227 + 182 18 229 231 + 183 18 229 230 + 184 18 232 233 + 185 18 232 234 + 186 18 235 236 + 187 18 235 237 + 188 18 238 240 + 189 18 238 239 + 190 18 241 242 + 191 18 241 243 + 192 18 244 246 + 193 18 244 245 + 194 18 247 248 + 195 18 247 249 + 196 18 250 251 + 197 18 250 252 + 198 18 253 254 + 199 18 253 255 + 200 18 256 257 + 201 18 256 258 + 202 18 259 261 + 203 18 259 260 + 204 18 262 264 + 205 18 262 263 + 206 18 265 266 + 207 18 265 267 + 208 18 268 269 + 209 18 268 270 + 210 18 271 272 + 211 18 271 273 + 212 18 274 275 + 213 18 274 276 + 214 18 277 279 + 215 18 277 278 + 216 18 280 282 + 217 18 280 281 + 218 18 283 284 + 219 18 283 285 + 220 18 286 287 + 221 18 286 288 + 222 18 289 290 + 223 18 289 291 + 224 18 292 294 + 225 18 292 293 + 226 18 295 296 + 227 18 295 297 + 228 18 298 299 + 229 18 298 300 + 230 18 301 303 + 231 18 301 302 + 232 18 304 305 + 233 18 304 306 + 234 18 307 309 + 235 18 307 308 + 236 18 310 311 + 237 18 310 312 + 238 18 313 314 + 239 18 313 315 + 240 18 316 317 + 241 18 316 318 + 242 18 319 321 + 243 18 319 320 + 244 18 322 323 + 245 18 322 324 + 246 18 325 327 + 247 18 325 326 + 248 18 328 329 + 249 18 328 330 + 250 18 331 332 + 251 18 331 333 + 252 18 334 335 + 253 18 334 336 + 254 18 337 339 + 255 18 337 338 + 256 18 340 341 + 257 18 340 342 + 258 18 343 344 + 259 18 343 345 + 260 18 346 347 + 261 18 346 348 + 262 18 349 350 + 263 18 349 351 + 264 18 352 353 + 265 18 352 354 + 266 18 355 356 + 267 18 355 357 + 268 18 358 359 + 269 18 358 360 + 270 18 361 362 + 271 18 361 363 + 272 18 364 365 + 273 18 364 366 + 274 18 367 369 + 275 18 367 368 + 276 18 370 372 + 277 18 370 371 + 278 18 373 374 + 279 18 373 375 + 280 18 376 378 + 281 18 376 377 + 282 18 379 381 + 283 18 379 380 + 284 18 382 383 + 285 18 382 384 + 286 18 385 386 + 287 18 385 387 + 288 18 388 390 + 289 18 388 389 + 290 18 391 393 + 291 18 391 392 + 292 18 394 395 + 293 18 394 396 + 294 18 397 399 + 295 18 397 398 + 296 18 400 402 + 297 18 400 401 + 298 18 403 405 + 299 18 403 404 + 300 18 406 407 + 301 18 406 408 + 302 18 409 411 + 303 18 409 410 + 304 18 412 413 + 305 18 412 414 + 306 18 415 417 + 307 18 415 416 + 308 18 418 420 + 309 18 418 419 + 310 18 421 422 + 311 18 421 423 + 312 18 424 425 + 313 18 424 426 + 314 18 427 428 + 315 18 427 429 + 316 18 430 432 + 317 18 430 431 + 318 18 433 435 + 319 18 433 434 + 320 18 436 437 + 321 18 436 438 + 322 18 439 440 + 323 18 439 441 + 324 18 442 443 + 325 18 442 444 + 326 18 445 447 + 327 18 445 446 + 328 18 448 449 + 329 18 448 450 + 330 18 451 453 + 331 18 451 452 + 332 18 454 456 + 333 18 454 455 + 334 18 457 458 + 335 18 457 459 + 336 18 460 462 + 337 18 460 461 + 338 18 463 465 + 339 18 463 464 + 340 18 466 467 + 341 18 466 468 + 342 18 469 470 + 343 18 469 471 + 344 18 472 473 + 345 18 472 474 + 346 18 475 476 + 347 18 475 477 + 348 18 478 479 + 349 18 478 480 + 350 18 481 482 + 351 18 481 483 + 352 18 484 485 + 353 18 484 486 + 354 18 487 489 + 355 18 487 488 + 356 18 490 492 + 357 18 490 491 + 358 18 493 495 + 359 18 493 494 + 360 18 496 497 + 361 18 496 498 + 362 18 499 501 + 363 18 499 500 + 364 18 502 503 + 365 18 502 504 + 366 18 505 507 + 367 18 505 506 + 368 18 508 509 + 369 18 508 510 + 370 18 511 513 + 371 18 511 512 + 372 18 514 516 + 373 18 514 515 + 374 18 517 518 + 375 18 517 519 + 376 18 520 521 + 377 18 520 522 + 378 18 523 525 + 379 18 523 524 + 380 18 526 528 + 381 18 526 527 + 382 18 529 530 + 383 18 529 531 + 384 18 532 533 + 385 18 532 534 + 386 18 535 536 + 387 18 535 537 + 388 18 538 540 + 389 18 538 539 + 390 18 541 542 + 391 18 541 543 + 392 18 544 546 + 393 18 544 545 + 394 18 547 549 + 395 18 547 548 + 396 18 550 551 + 397 18 550 552 + 398 18 553 555 + 399 18 553 554 + 400 18 556 557 + 401 18 556 558 + 402 18 559 561 + 403 18 559 560 + 404 18 562 563 + 405 18 562 564 + 406 18 565 567 + 407 18 565 566 + 408 18 568 570 + 409 18 568 569 + 410 18 571 573 + 411 18 571 572 + 412 18 574 575 + 413 18 574 576 + 414 18 577 579 + 415 18 577 578 + 416 18 580 581 + 417 18 580 582 + 418 18 583 585 + 419 18 583 584 + 420 18 586 588 + 421 18 586 587 + 422 18 589 590 + 423 18 589 591 + 424 18 592 594 + 425 18 592 593 + 426 18 595 597 + 427 18 595 596 + 428 18 598 600 + 429 18 598 599 + 430 18 601 602 + 431 18 601 603 + 432 18 604 606 + 433 18 604 605 + 434 18 607 609 + 435 18 607 608 + 436 18 610 611 + 437 18 610 612 + 438 18 613 615 + 439 18 613 614 + 440 18 616 618 + 441 18 616 617 + 442 18 619 620 + 443 18 619 621 + 444 18 622 623 + 445 18 622 624 + 446 18 625 627 + 447 18 625 626 + 448 18 628 629 + 449 18 628 630 + 450 18 631 632 + 451 18 631 633 + 452 18 634 635 + 453 18 634 636 + 454 18 637 639 + 455 18 637 638 + 456 18 640 642 + 457 18 640 641 + 458 18 643 644 + 459 18 643 645 + 460 18 646 647 + 461 18 646 648 + 462 18 649 650 + 463 18 649 651 + 464 18 652 653 + 465 18 652 654 + 466 18 655 657 + 467 18 655 656 + 468 18 658 660 + 469 18 658 659 + 470 18 661 663 + 471 18 661 662 + 472 18 664 665 + 473 18 664 666 + 474 18 667 669 + 475 18 667 668 + 476 18 670 672 + 477 18 670 671 + 478 18 673 674 + 479 18 673 675 + 480 18 676 677 + 481 18 676 678 + 482 18 679 681 + 483 18 679 680 + 484 18 682 684 + 485 18 682 683 + 486 18 685 686 + 487 18 685 687 + 488 18 688 690 + 489 18 688 689 + 490 18 691 693 + 491 18 691 692 + 492 18 694 695 + 493 18 694 696 + 494 18 697 698 + 495 18 697 699 + 496 18 700 701 + 497 18 700 702 + 498 18 703 704 + 499 18 703 705 + 500 18 706 707 + 501 18 706 708 + 502 18 709 710 + 503 18 709 711 + 504 18 712 714 + 505 18 712 713 + 506 18 715 716 + 507 18 715 717 + 508 18 718 719 + 509 18 718 720 + 510 18 721 722 + 511 18 721 723 + 512 18 724 726 + 513 18 724 725 + 514 18 727 728 + 515 18 727 729 + 516 18 730 731 + 517 18 730 732 + 518 18 733 735 + 519 18 733 734 + 520 18 736 737 + 521 18 736 738 + 522 18 739 741 + 523 18 739 740 + 524 18 742 743 + 525 18 742 744 + 526 18 745 746 + 527 18 745 747 + 528 18 748 750 + 529 18 748 749 + 530 18 751 753 + 531 18 751 752 + 532 18 754 756 + 533 18 754 755 + 534 18 757 758 + 535 18 757 759 + 536 18 760 762 + 537 18 760 761 + 538 18 763 764 + 539 18 763 765 + 540 18 766 767 + 541 18 766 768 + 542 18 769 770 + 543 18 769 771 + 544 18 772 774 + 545 18 772 773 + 546 18 775 777 + 547 18 775 776 + 548 18 778 780 + 549 18 778 779 + 550 18 781 783 + 551 18 781 782 + 552 18 784 786 + 553 18 784 785 + 554 18 787 789 + 555 18 787 788 + 556 18 790 791 + 557 18 790 792 + 558 18 793 795 + 559 18 793 794 + 560 18 796 797 + 561 18 796 798 + 562 18 799 801 + 563 18 799 800 + 564 18 802 803 + 565 18 802 804 + 566 18 805 806 + 567 18 805 807 + 568 18 808 809 + 569 18 808 810 + 570 18 811 813 + 571 18 811 812 + 572 18 814 815 + 573 18 814 816 + 574 18 817 818 + 575 18 817 819 + 576 18 820 821 + 577 18 820 822 + 578 18 823 824 + 579 18 823 825 + 580 18 826 828 + 581 18 826 827 + 582 18 829 830 + 583 18 829 831 + 584 18 832 834 + 585 18 832 833 + 586 18 835 837 + 587 18 835 836 + 588 18 838 839 + 589 18 838 840 + 590 18 841 842 + 591 18 841 843 + 592 18 844 845 + 593 18 844 846 + 594 18 847 848 + 595 18 847 849 + 596 18 850 852 + 597 18 850 851 + 598 18 853 854 + 599 18 853 855 + 600 18 856 858 + 601 18 856 857 + 602 18 859 861 + 603 18 859 860 + 604 18 862 863 + 605 18 862 864 + 606 18 865 866 + 607 18 865 867 + 608 18 868 869 + 609 18 868 870 + 610 18 871 873 + 611 18 871 872 + 612 18 874 875 + 613 18 874 876 + 614 18 877 878 + 615 18 877 879 + 616 18 880 882 + 617 18 880 881 + 618 18 883 884 + 619 18 883 885 + 620 18 886 887 + 621 18 886 888 + 622 18 889 891 + 623 18 889 890 + 624 18 892 894 + 625 18 892 893 + 626 18 895 896 + 627 18 895 897 + 628 18 898 899 + 629 18 898 900 + 630 18 901 903 + 631 18 901 902 + 632 18 904 905 + 633 18 904 906 + 634 18 907 908 + 635 18 907 909 + 636 18 910 911 + 637 18 910 912 + 638 18 913 915 + 639 18 913 914 + 640 18 916 917 + 641 18 916 918 + 642 18 919 920 + 643 18 919 921 + 644 18 922 924 + 645 18 922 923 + 646 18 925 927 + 647 18 925 926 + 648 18 928 930 + 649 18 928 929 + 650 18 931 932 + 651 18 931 933 + 652 18 934 935 + 653 18 934 936 + 654 18 937 939 + 655 18 937 938 + 656 18 940 942 + 657 18 940 941 + 658 18 943 945 + 659 18 943 944 + 660 18 946 948 + 661 18 946 947 + 662 18 949 950 + 663 18 949 951 + 664 18 952 953 + 665 18 952 954 + 666 18 955 956 + 667 18 955 957 + 668 18 958 960 + 669 18 958 959 + 670 18 961 963 + 671 18 961 962 + 672 18 964 965 + 673 18 964 966 + 674 18 967 969 + 675 18 967 968 + 676 18 970 972 + 677 18 970 971 + 678 18 973 975 + 679 18 973 974 + 680 18 976 978 + 681 18 976 977 + 682 18 979 981 + 683 18 979 980 + 684 18 982 983 + 685 18 982 984 + 686 18 985 987 + 687 18 985 986 + 688 18 988 989 + 689 18 988 990 + 690 18 991 993 + 691 18 991 992 + 692 18 994 996 + 693 18 994 995 + 694 18 997 998 + 695 18 997 999 + 696 18 1000 1001 + 697 18 1000 1002 + 698 18 1003 1005 + 699 18 1003 1004 + 700 18 1006 1007 + 701 18 1006 1008 + 702 18 1009 1011 + 703 18 1009 1010 + 704 18 1012 1013 + 705 18 1012 1014 + 706 18 1015 1017 + 707 18 1015 1016 + 708 18 1018 1020 + 709 18 1018 1019 + 710 18 1021 1023 + 711 18 1021 1022 + 712 18 1024 1025 + 713 18 1024 1026 + 714 18 1027 1028 + 715 18 1027 1029 + 716 18 1030 1032 + 717 18 1030 1031 + 718 18 1033 1034 + 719 18 1033 1035 + 720 18 1036 1037 + 721 18 1036 1038 + 722 18 1039 1041 + 723 18 1039 1040 + 724 18 1042 1043 + 725 18 1042 1044 + 726 18 1045 1046 + 727 18 1045 1047 + 728 18 1048 1050 + 729 18 1048 1049 + 730 18 1051 1053 + 731 18 1051 1052 + 732 18 1054 1056 + 733 18 1054 1055 + 734 18 1057 1058 + 735 18 1057 1059 + 736 18 1060 1062 + 737 18 1060 1061 + 738 18 1063 1064 + 739 18 1063 1065 + 740 18 1066 1068 + 741 18 1066 1067 + 742 18 1069 1071 + 743 18 1069 1070 + 744 18 1072 1074 + 745 18 1072 1073 + 746 18 1075 1077 + 747 18 1075 1076 + 748 18 1078 1079 + 749 18 1078 1080 + 750 18 1081 1082 + 751 18 1081 1083 + 752 18 1084 1085 + 753 18 1084 1086 + 754 18 1087 1089 + 755 18 1087 1088 + 756 18 1090 1092 + 757 18 1090 1091 + 758 18 1093 1095 + 759 18 1093 1094 + 760 18 1096 1097 + 761 18 1096 1098 + 762 18 1099 1100 + 763 18 1099 1101 + 764 18 1102 1103 + 765 18 1102 1104 + 766 18 1105 1107 + 767 18 1105 1106 + 768 18 1108 1110 + 769 18 1108 1109 + 770 18 1111 1112 + 771 18 1111 1113 + 772 18 1114 1116 + 773 18 1114 1115 + 774 18 1117 1119 + 775 18 1117 1118 + 776 18 1120 1121 + 777 18 1120 1122 + 778 18 1123 1124 + 779 18 1123 1125 + 780 18 1126 1128 + 781 18 1126 1127 + 782 18 1129 1130 + 783 18 1129 1131 + 784 18 1132 1133 + 785 18 1132 1134 + 786 18 1135 1137 + 787 18 1135 1136 + 788 18 1138 1140 + 789 18 1138 1139 + 790 18 1141 1142 + 791 18 1141 1143 + 792 18 1144 1146 + 793 18 1144 1145 + 794 18 1147 1149 + 795 18 1147 1148 + 796 18 1150 1152 + 797 18 1150 1151 + 798 18 1153 1155 + 799 18 1153 1154 + 800 18 1156 1158 + 801 18 1156 1157 + 802 18 1159 1160 + 803 18 1159 1161 + 804 18 1162 1164 + 805 18 1162 1163 + 806 18 1165 1166 + 807 18 1165 1167 + 808 18 1168 1170 + 809 18 1168 1169 + 810 18 1171 1172 + 811 18 1171 1173 + 812 18 1174 1175 + 813 18 1174 1176 + 814 18 1177 1179 + 815 18 1177 1178 + 816 18 1180 1182 + 817 18 1180 1181 + 818 18 1183 1185 + 819 18 1183 1184 + 820 18 1186 1187 + 821 18 1186 1188 + 822 18 1189 1190 + 823 18 1189 1191 + 824 18 1192 1194 + 825 18 1192 1193 + 826 18 1195 1196 + 827 18 1195 1197 + 828 18 1198 1199 + 829 18 1198 1200 + 830 18 1201 1202 + 831 18 1201 1203 + 832 18 1204 1205 + 833 18 1204 1206 + 834 18 1207 1209 + 835 18 1207 1208 + 836 18 1210 1212 + 837 18 1210 1211 + 838 18 1213 1214 + 839 18 1213 1215 + 840 18 1216 1218 + 841 18 1216 1217 + 842 18 1219 1221 + 843 18 1219 1220 + 844 18 1222 1224 + 845 18 1222 1223 + 846 18 1225 1226 + 847 18 1225 1227 + 848 18 1228 1229 + 849 18 1228 1230 + 850 18 1231 1232 + 851 18 1231 1233 + 852 18 1234 1236 + 853 18 1234 1235 + 854 18 1237 1239 + 855 18 1237 1238 + 856 18 1240 1242 + 857 18 1240 1241 + 858 18 1243 1244 + 859 18 1243 1245 + 860 18 1246 1248 + 861 18 1246 1247 + 862 18 1249 1250 + 863 18 1249 1251 + 864 18 1252 1254 + 865 18 1252 1253 + 866 18 1255 1256 + 867 18 1255 1257 + 868 18 1258 1259 + 869 18 1258 1260 + 870 18 1261 1263 + 871 18 1261 1262 + 872 18 1264 1265 + 873 18 1264 1266 + 874 18 1267 1268 + 875 18 1267 1269 + 876 18 1270 1271 + 877 18 1270 1272 + 878 18 1273 1274 + 879 18 1273 1275 + 880 18 1276 1277 + 881 18 1276 1278 + 882 18 1279 1280 + 883 18 1279 1281 + 884 18 1282 1283 + 885 18 1282 1284 + 886 18 1285 1286 + 887 18 1285 1287 + 888 18 1288 1289 + 889 18 1288 1290 + 890 18 1291 1293 + 891 18 1291 1292 + 892 18 1294 1295 + 893 18 1294 1296 + 894 18 1297 1299 + 895 18 1297 1298 + 896 18 1300 1302 + 897 18 1300 1301 + 898 18 1303 1304 + 899 18 1303 1305 + 900 18 1306 1308 + 901 18 1306 1307 + 902 18 1309 1311 + 903 18 1309 1310 + 904 18 1312 1314 + 905 18 1312 1313 + 906 18 1315 1317 + 907 18 1315 1316 + 908 18 1318 1320 + 909 18 1318 1319 + 910 18 1321 1323 + 911 18 1321 1322 + 912 18 1324 1325 + 913 18 1324 1326 + 914 18 1327 1329 + 915 18 1327 1328 + 916 18 1330 1332 + 917 18 1330 1331 + 918 18 1333 1334 + 919 18 1333 1335 + 920 18 1336 1337 + 921 18 1336 1338 + 922 18 1339 1340 + 923 18 1339 1341 + 924 18 1342 1344 + 925 18 1342 1343 + 926 18 1345 1347 + 927 18 1345 1346 + 928 18 1348 1350 + 929 18 1348 1349 + 930 18 1351 1352 + 931 18 1351 1353 + 932 18 1354 1355 + 933 18 1354 1356 + 934 18 1357 1358 + 935 18 1357 1359 + 936 18 1360 1362 + 937 18 1360 1361 + 938 18 1363 1365 + 939 18 1363 1364 + 940 18 1366 1368 + 941 18 1366 1367 + 942 18 1369 1370 + 943 18 1369 1371 + 944 18 1372 1373 + 945 18 1372 1374 + 946 18 1375 1377 + 947 18 1375 1376 + 948 18 1378 1379 + 949 18 1378 1380 + 950 18 1381 1382 + 951 18 1381 1383 + 952 18 1384 1385 + 953 18 1384 1386 + 954 18 1387 1388 + 955 18 1387 1389 + 956 18 1390 1392 + 957 18 1390 1391 + 958 18 1393 1395 + 959 18 1393 1394 + 960 18 1396 1397 + 961 18 1396 1398 + 962 18 1399 1401 + 963 18 1399 1400 + 964 18 1402 1403 + 965 18 1402 1404 + 966 18 1405 1406 + 967 18 1405 1407 + 968 18 1408 1409 + 969 18 1408 1410 + 970 18 1411 1412 + 971 18 1411 1413 + 972 18 1414 1416 + 973 18 1414 1415 + 974 18 1417 1419 + 975 18 1417 1418 + 976 18 1420 1422 + 977 18 1420 1421 + 978 18 1423 1425 + 979 18 1423 1424 + 980 18 1426 1428 + 981 18 1426 1427 + 982 18 1429 1430 + 983 18 1429 1431 + 984 18 1432 1434 + 985 18 1432 1433 + 986 18 1435 1436 + 987 18 1435 1437 + 988 18 1438 1439 + 989 18 1438 1440 + 990 18 1441 1442 + 991 18 1441 1443 + 992 18 1444 1445 + 993 18 1444 1446 + 994 18 1447 1448 + 995 18 1447 1449 + 996 18 1450 1451 + 997 18 1450 1452 + 998 18 1453 1455 + 999 18 1453 1454 + 1000 18 1456 1457 + 1001 18 1456 1458 + 1002 18 1459 1461 + 1003 18 1459 1460 + 1004 18 1462 1463 + 1005 18 1462 1464 + 1006 18 1465 1466 + 1007 18 1465 1467 + 1008 18 1468 1470 + 1009 18 1468 1469 + 1010 18 1471 1472 + 1011 18 1471 1473 + 1012 18 1474 1476 + 1013 18 1474 1475 + 1014 18 1477 1478 + 1015 18 1477 1479 + 1016 18 1480 1482 + 1017 18 1480 1481 + 1018 18 1483 1485 + 1019 18 1483 1484 + 1020 18 1486 1488 + 1021 18 1486 1487 + 1022 18 1489 1491 + 1023 18 1489 1490 + 1024 18 1492 1493 + 1025 18 1492 1494 + 1026 18 1495 1496 + 1027 18 1495 1497 + 1028 18 1498 1499 + 1029 18 1498 1500 + 1030 18 1501 1502 + 1031 18 1501 1503 + 1032 18 1504 1505 + 1033 18 1504 1506 + 1034 18 1507 1509 + 1035 18 1507 1508 + 1036 18 1510 1512 + 1037 18 1510 1511 + 1038 18 1513 1515 + 1039 18 1513 1514 + 1040 18 1516 1518 + 1041 18 1516 1517 + 1042 18 1519 1520 + 1043 18 1519 1521 + 1044 18 1522 1524 + 1045 18 1522 1523 + 1046 18 1525 1526 + 1047 18 1525 1527 + 1048 18 1528 1529 + 1049 18 1528 1530 + 1050 18 1531 1533 + 1051 18 1531 1532 + 1052 18 1534 1536 + 1053 18 1534 1535 + 1054 18 1537 1539 + 1055 18 1537 1538 + 1056 18 1540 1541 + 1057 18 1540 1542 + 1058 18 1543 1545 + 1059 18 1543 1544 + 1060 18 1546 1547 + 1061 18 1546 1548 + 1062 18 1549 1551 + 1063 18 1549 1550 + 1064 18 1552 1553 + 1065 18 1552 1554 + 1066 18 1555 1557 + 1067 18 1555 1556 + 1068 18 1558 1559 + 1069 18 1558 1560 + 1070 18 1561 1562 + 1071 18 1561 1563 + 1072 18 1564 1565 + 1073 18 1564 1566 + 1074 18 1567 1569 + 1075 18 1567 1568 + 1076 18 1570 1571 + 1077 18 1570 1572 + 1078 18 1573 1575 + 1079 18 1573 1574 + 1080 18 1576 1578 + 1081 18 1576 1577 + 1082 18 1579 1581 + 1083 18 1579 1580 + 1084 18 1582 1584 + 1085 18 1582 1583 + 1086 18 1585 1586 + 1087 18 1585 1587 + 1088 18 1588 1590 + 1089 18 1588 1589 + 1090 18 1591 1592 + 1091 18 1591 1593 + 1092 18 1594 1596 + 1093 18 1594 1595 + 1094 18 1597 1598 + 1095 18 1597 1599 + 1096 18 1600 1602 + 1097 18 1600 1601 + 1098 18 1603 1605 + 1099 18 1603 1604 + 1100 18 1606 1608 + 1101 18 1606 1607 + 1102 18 1609 1610 + 1103 18 1609 1611 + 1104 18 1612 1614 + 1105 18 1612 1613 + 1106 18 1615 1617 + 1107 18 1615 1616 + 1108 18 1618 1620 + 1109 18 1618 1619 + 1110 18 1621 1623 + 1111 18 1621 1622 + 1112 18 1624 1625 + 1113 18 1624 1626 + 1114 18 1627 1629 + 1115 18 1627 1628 + 1116 18 1630 1631 + 1117 18 1630 1632 + 1118 18 1633 1635 + 1119 18 1633 1634 + 1120 18 1636 1637 + 1121 18 1636 1638 + 1122 18 1639 1641 + 1123 18 1639 1640 + 1124 18 1642 1643 + 1125 18 1642 1644 + 1126 18 1645 1646 + 1127 18 1645 1647 + 1128 18 1648 1650 + 1129 18 1648 1649 + 1130 18 1651 1653 + 1131 18 1651 1652 + 1132 18 1654 1656 + 1133 18 1654 1655 + 1134 18 1657 1658 + 1135 18 1657 1659 + 1136 18 1660 1661 + 1137 18 1660 1662 + 1138 18 1663 1664 + 1139 18 1663 1665 + 1140 18 1666 1668 + 1141 18 1666 1667 + 1142 18 1669 1670 + 1143 18 1669 1671 + 1144 18 1672 1674 + 1145 18 1672 1673 + 1146 18 1675 1676 + 1147 18 1675 1677 + 1148 18 1678 1680 + 1149 18 1678 1679 + 1150 18 1681 1683 + 1151 18 1681 1682 + 1152 18 1684 1685 + 1153 18 1684 1686 + 1154 18 1687 1688 + 1155 18 1687 1689 + 1156 18 1690 1691 + 1157 18 1690 1692 + 1158 18 1693 1695 + 1159 18 1693 1694 + 1160 18 1696 1697 + 1161 18 1696 1698 + 1162 18 1699 1701 + 1163 18 1699 1700 + 1164 18 1702 1703 + 1165 18 1702 1704 + 1166 18 1705 1707 + 1167 18 1705 1706 + 1168 18 1708 1709 + 1169 18 1708 1710 + 1170 18 1711 1712 + 1171 18 1711 1713 + 1172 18 1714 1716 + 1173 18 1714 1715 + 1174 18 1717 1718 + 1175 18 1717 1719 + 1176 18 1720 1721 + 1177 18 1720 1722 + 1178 18 1723 1724 + 1179 18 1723 1725 + 1180 18 1726 1727 + 1181 18 1726 1728 + 1182 18 1729 1730 + 1183 18 1729 1731 + 1184 18 1732 1734 + 1185 18 1732 1733 + 1186 18 1735 1737 + 1187 18 1735 1736 + 1188 18 1738 1740 + 1189 18 1738 1739 + 1190 18 1741 1743 + 1191 18 1741 1742 + 1192 18 1744 1745 + 1193 18 1744 1746 + 1194 18 1747 1749 + 1195 18 1747 1748 + 1196 18 1750 1751 + 1197 18 1750 1752 + 1198 18 1753 1755 + 1199 18 1753 1754 + 1200 18 1756 1758 + 1201 18 1756 1757 + 1202 18 1759 1760 + 1203 18 1759 1761 + 1204 18 1762 1764 + 1205 18 1762 1763 + 1206 18 1765 1767 + 1207 18 1765 1766 + 1208 18 1768 1769 + 1209 18 1768 1770 + 1210 18 1771 1773 + 1211 18 1771 1772 + 1212 18 1774 1776 + 1213 18 1774 1775 + 1214 18 1777 1779 + 1215 18 1777 1778 + 1216 18 1780 1781 + 1217 18 1780 1782 + 1218 18 1783 1784 + 1219 18 1783 1785 + 1220 18 1786 1787 + 1221 18 1786 1788 + 1222 18 1789 1790 + 1223 18 1789 1791 + 1224 18 1792 1793 + 1225 18 1792 1794 + 1226 18 1795 1796 + 1227 18 1795 1797 + 1228 18 1798 1799 + 1229 18 1798 1800 + 1230 18 1801 1803 + 1231 18 1801 1802 + 1232 18 1804 1806 + 1233 18 1804 1805 + 1234 18 1807 1809 + 1235 18 1807 1808 + 1236 18 1810 1812 + 1237 18 1810 1811 + 1238 18 1813 1815 + 1239 18 1813 1814 + 1240 18 1816 1818 + 1241 18 1816 1817 + 1242 18 1819 1821 + 1243 18 1819 1820 + 1244 18 1822 1823 + 1245 18 1822 1824 + 1246 18 1825 1827 + 1247 18 1825 1826 + 1248 18 1828 1830 + 1249 18 1828 1829 + 1250 18 1831 1832 + 1251 18 1831 1833 + 1252 18 1834 1835 + 1253 18 1834 1836 + 1254 18 1837 1838 + 1255 18 1837 1839 + 1256 18 1840 1842 + 1257 18 1840 1841 + 1258 18 1843 1845 + 1259 18 1843 1844 + 1260 18 1846 1848 + 1261 18 1846 1847 + 1262 18 1849 1851 + 1263 18 1849 1850 + 1264 18 1852 1854 + 1265 18 1852 1853 + 1266 18 1855 1856 + 1267 18 1855 1857 + 1268 18 1858 1859 + 1269 18 1858 1860 + 1270 18 1861 1862 + 1271 18 1861 1863 + 1272 18 1864 1866 + 1273 18 1864 1865 + 1274 18 1867 1869 + 1275 18 1867 1868 + 1276 18 1870 1871 + 1277 18 1870 1872 + 1278 18 1873 1874 + 1279 18 1873 1875 + 1280 18 1876 1877 + 1281 18 1876 1878 + 1282 18 1879 1881 + 1283 18 1879 1880 + 1284 18 1882 1883 + 1285 18 1882 1884 + 1286 18 1885 1886 + 1287 18 1885 1887 + 1288 18 1888 1890 + 1289 18 1888 1889 + 1290 18 1891 1892 + 1291 18 1891 1893 + 1292 18 1894 1896 + 1293 18 1894 1895 + 1294 18 1897 1898 + 1295 18 1897 1899 + 1296 18 1900 1902 + 1297 18 1900 1901 + 1298 18 1903 1905 + 1299 18 1903 1904 + 1300 18 1906 1908 + 1301 18 1906 1907 + 1302 18 1909 1911 + 1303 18 1909 1910 + 1304 18 1912 1913 + 1305 18 1912 1914 + 1306 18 1915 1916 + 1307 18 1915 1917 + 1308 18 1918 1920 + 1309 18 1918 1919 + 1310 18 1921 1923 + 1311 18 1921 1922 + 1312 18 1924 1926 + 1313 18 1924 1925 + 1314 18 1927 1929 + 1315 18 1927 1928 + 1316 18 1930 1932 + 1317 18 1930 1931 + 1318 18 1933 1935 + 1319 18 1933 1934 + 1320 18 1936 1937 + 1321 18 1936 1938 + 1322 18 1939 1940 + 1323 18 1939 1941 + 1324 18 1942 1944 + 1325 18 1942 1943 + 1326 18 1945 1947 + 1327 18 1945 1946 + 1328 18 1948 1950 + 1329 18 1948 1949 + 1330 18 1951 1953 + 1331 18 1951 1952 + 1332 18 1954 1955 + 1333 18 1954 1956 + 1334 18 1957 1959 + 1335 18 1957 1958 + 1336 18 1960 1961 + 1337 18 1960 1962 + 1338 18 1963 1965 + 1339 18 1963 1964 + 1340 18 1966 1967 + 1341 18 1966 1968 + 1342 18 1969 1970 + 1343 18 1969 1971 + 1344 18 1972 1974 + 1345 18 1972 1973 + 1346 18 1975 1977 + 1347 18 1975 1976 + 1348 18 1978 1979 + 1349 18 1978 1980 + 1350 18 1981 1982 + 1351 18 1981 1983 + 1352 18 1984 1986 + 1353 18 1984 1985 + 1354 18 1987 1988 + 1355 18 1987 1989 + 1356 18 1990 1992 + 1357 18 1990 1991 + 1358 18 1993 1995 + 1359 18 1993 1994 + 1360 18 1996 1998 + 1361 18 1996 1997 + 1362 18 1999 2000 + 1363 18 1999 2001 + 1364 18 2002 2004 + 1365 18 2002 2003 + +Angles + + 1 5 2 1 7 + 2 4 2 1 3 + 3 6 3 1 7 + 4 7 4 2 5 + 5 7 5 2 6 + 6 1 1 2 5 + 7 1 1 2 6 + 8 1 1 2 4 + 9 7 4 2 6 + 10 2 1 7 8 + 11 3 1 7 19 + 12 11 8 7 19 + 13 9 7 8 11 + 14 8 7 8 9 + 15 16 11 8 20 + 16 15 9 8 20 + 17 14 9 8 11 + 18 10 7 8 20 + 19 5 8 9 28 + 20 4 8 9 10 + 21 6 10 9 28 + 22 18 12 11 22 + 23 23 21 11 22 + 24 12 8 11 12 + 25 13 8 11 21 + 26 18 12 11 21 + 27 13 8 11 22 + 28 19 13 12 14 + 29 17 11 12 14 + 30 17 11 12 13 + 31 20 15 13 23 + 32 20 12 13 23 + 33 19 12 13 15 + 34 20 12 14 24 + 35 20 16 14 24 + 36 19 12 14 16 + 37 20 13 15 25 + 38 20 17 15 25 + 39 19 13 15 17 + 40 20 14 16 26 + 41 19 14 16 17 + 42 20 17 16 26 + 43 21 15 17 18 + 44 19 15 17 16 + 45 21 16 17 18 + 46 22 17 18 27 + 47 2 9 28 29 + 48 3 9 28 32 + 49 11 29 28 32 + 50 15 30 29 34 + 51 10 28 29 33 + 52 10 28 29 34 + 53 15 30 29 33 + 54 24 33 29 34 + 55 8 28 29 30 + 56 6 31 30 35 + 57 5 29 30 35 + 58 4 29 30 31 + 59 2 30 35 36 + 60 3 30 35 39 + 61 11 36 35 39 + 62 8 35 36 37 + 63 10 35 36 41 + 64 10 35 36 40 + 65 24 40 36 41 + 66 15 37 36 40 + 67 15 37 36 41 + 68 6 38 37 42 + 69 5 36 37 42 + 70 4 36 37 38 + 71 11 43 42 53 + 72 2 37 42 43 + 73 3 37 42 53 + 74 10 42 43 54 + 75 16 46 43 54 + 76 14 44 43 46 + 77 9 42 43 46 + 78 8 42 43 44 + 79 15 44 43 54 + 80 5 43 44 62 + 81 6 45 44 62 + 82 4 43 44 45 + 83 13 43 46 55 + 84 13 43 46 56 + 85 12 43 46 47 + 86 23 55 46 56 + 87 18 47 46 56 + 88 18 47 46 55 + 89 17 46 47 49 + 90 17 46 47 48 + 91 19 48 47 49 + 92 20 50 48 57 + 93 19 47 48 50 + 94 20 47 48 57 + 95 20 51 49 58 + 96 19 47 49 51 + 97 20 47 49 58 + 98 20 48 50 59 + 99 19 48 50 52 + 100 20 52 50 59 + 101 20 52 51 60 + 102 20 49 51 60 + 103 19 49 51 52 + 104 20 50 52 61 + 105 19 50 52 51 + 106 20 51 52 61 + 107 2 44 62 63 + 108 3 44 62 70 + 109 11 63 62 70 + 110 16 66 63 71 + 111 15 64 63 71 + 112 14 64 63 66 + 113 10 62 63 71 + 114 9 62 63 66 + 115 8 62 63 64 + 116 4 63 64 65 + 117 6 65 64 79 + 118 5 63 64 79 + 119 23 72 66 73 + 120 27 67 66 73 + 121 27 67 66 72 + 122 25 63 66 67 + 123 13 63 66 73 + 124 13 63 66 72 + 125 29 68 67 75 + 126 23 74 67 75 + 127 29 68 67 74 + 128 26 66 67 68 + 129 27 66 67 74 + 130 27 66 67 75 + 131 28 67 68 69 + 132 29 68 69 76 + 133 29 68 69 77 + 134 29 68 69 78 + 135 7 76 69 78 + 136 7 76 69 77 + 137 7 77 69 78 + 138 3 64 79 81 + 139 2 64 79 80 + 140 11 80 79 81 + 141 7 83 80 84 + 142 30 79 80 84 + 143 7 82 80 83 + 144 30 79 80 83 + 145 30 79 80 82 + 146 7 82 80 84 + 147 31 86 85 87 + 148 31 89 88 90 + 149 31 92 91 93 + 150 31 95 94 96 + 151 31 98 97 99 + 152 31 101 100 102 + 153 31 104 103 105 + 154 31 107 106 108 + 155 31 110 109 111 + 156 31 113 112 114 + 157 31 116 115 117 + 158 31 119 118 120 + 159 31 122 121 123 + 160 31 125 124 126 + 161 31 128 127 129 + 162 31 131 130 132 + 163 31 134 133 135 + 164 31 137 136 138 + 165 31 140 139 141 + 166 31 143 142 144 + 167 31 146 145 147 + 168 31 149 148 150 + 169 31 152 151 153 + 170 31 155 154 156 + 171 31 158 157 159 + 172 31 161 160 162 + 173 31 164 163 165 + 174 31 167 166 168 + 175 31 170 169 171 + 176 31 173 172 174 + 177 31 176 175 177 + 178 31 179 178 180 + 179 31 182 181 183 + 180 31 185 184 186 + 181 31 188 187 189 + 182 31 191 190 192 + 183 31 194 193 195 + 184 31 197 196 198 + 185 31 200 199 201 + 186 31 203 202 204 + 187 31 206 205 207 + 188 31 209 208 210 + 189 31 212 211 213 + 190 31 215 214 216 + 191 31 218 217 219 + 192 31 221 220 222 + 193 31 224 223 225 + 194 31 227 226 228 + 195 31 230 229 231 + 196 31 233 232 234 + 197 31 236 235 237 + 198 31 239 238 240 + 199 31 242 241 243 + 200 31 245 244 246 + 201 31 248 247 249 + 202 31 251 250 252 + 203 31 254 253 255 + 204 31 257 256 258 + 205 31 260 259 261 + 206 31 263 262 264 + 207 31 266 265 267 + 208 31 269 268 270 + 209 31 272 271 273 + 210 31 275 274 276 + 211 31 278 277 279 + 212 31 281 280 282 + 213 31 284 283 285 + 214 31 287 286 288 + 215 31 290 289 291 + 216 31 293 292 294 + 217 31 296 295 297 + 218 31 299 298 300 + 219 31 302 301 303 + 220 31 305 304 306 + 221 31 308 307 309 + 222 31 311 310 312 + 223 31 314 313 315 + 224 31 317 316 318 + 225 31 320 319 321 + 226 31 323 322 324 + 227 31 326 325 327 + 228 31 329 328 330 + 229 31 332 331 333 + 230 31 335 334 336 + 231 31 338 337 339 + 232 31 341 340 342 + 233 31 344 343 345 + 234 31 347 346 348 + 235 31 350 349 351 + 236 31 353 352 354 + 237 31 356 355 357 + 238 31 359 358 360 + 239 31 362 361 363 + 240 31 365 364 366 + 241 31 368 367 369 + 242 31 371 370 372 + 243 31 374 373 375 + 244 31 377 376 378 + 245 31 380 379 381 + 246 31 383 382 384 + 247 31 386 385 387 + 248 31 389 388 390 + 249 31 392 391 393 + 250 31 395 394 396 + 251 31 398 397 399 + 252 31 401 400 402 + 253 31 404 403 405 + 254 31 407 406 408 + 255 31 410 409 411 + 256 31 413 412 414 + 257 31 416 415 417 + 258 31 419 418 420 + 259 31 422 421 423 + 260 31 425 424 426 + 261 31 428 427 429 + 262 31 431 430 432 + 263 31 434 433 435 + 264 31 437 436 438 + 265 31 440 439 441 + 266 31 443 442 444 + 267 31 446 445 447 + 268 31 449 448 450 + 269 31 452 451 453 + 270 31 455 454 456 + 271 31 458 457 459 + 272 31 461 460 462 + 273 31 464 463 465 + 274 31 467 466 468 + 275 31 470 469 471 + 276 31 473 472 474 + 277 31 476 475 477 + 278 31 479 478 480 + 279 31 482 481 483 + 280 31 485 484 486 + 281 31 488 487 489 + 282 31 491 490 492 + 283 31 494 493 495 + 284 31 497 496 498 + 285 31 500 499 501 + 286 31 503 502 504 + 287 31 506 505 507 + 288 31 509 508 510 + 289 31 512 511 513 + 290 31 515 514 516 + 291 31 518 517 519 + 292 31 521 520 522 + 293 31 524 523 525 + 294 31 527 526 528 + 295 31 530 529 531 + 296 31 533 532 534 + 297 31 536 535 537 + 298 31 539 538 540 + 299 31 542 541 543 + 300 31 545 544 546 + 301 31 548 547 549 + 302 31 551 550 552 + 303 31 554 553 555 + 304 31 557 556 558 + 305 31 560 559 561 + 306 31 563 562 564 + 307 31 566 565 567 + 308 31 569 568 570 + 309 31 572 571 573 + 310 31 575 574 576 + 311 31 578 577 579 + 312 31 581 580 582 + 313 31 584 583 585 + 314 31 587 586 588 + 315 31 590 589 591 + 316 31 593 592 594 + 317 31 596 595 597 + 318 31 599 598 600 + 319 31 602 601 603 + 320 31 605 604 606 + 321 31 608 607 609 + 322 31 611 610 612 + 323 31 614 613 615 + 324 31 617 616 618 + 325 31 620 619 621 + 326 31 623 622 624 + 327 31 626 625 627 + 328 31 629 628 630 + 329 31 632 631 633 + 330 31 635 634 636 + 331 31 638 637 639 + 332 31 641 640 642 + 333 31 644 643 645 + 334 31 647 646 648 + 335 31 650 649 651 + 336 31 653 652 654 + 337 31 656 655 657 + 338 31 659 658 660 + 339 31 662 661 663 + 340 31 665 664 666 + 341 31 668 667 669 + 342 31 671 670 672 + 343 31 674 673 675 + 344 31 677 676 678 + 345 31 680 679 681 + 346 31 683 682 684 + 347 31 686 685 687 + 348 31 689 688 690 + 349 31 692 691 693 + 350 31 695 694 696 + 351 31 698 697 699 + 352 31 701 700 702 + 353 31 704 703 705 + 354 31 707 706 708 + 355 31 710 709 711 + 356 31 713 712 714 + 357 31 716 715 717 + 358 31 719 718 720 + 359 31 722 721 723 + 360 31 725 724 726 + 361 31 728 727 729 + 362 31 731 730 732 + 363 31 734 733 735 + 364 31 737 736 738 + 365 31 740 739 741 + 366 31 743 742 744 + 367 31 746 745 747 + 368 31 749 748 750 + 369 31 752 751 753 + 370 31 755 754 756 + 371 31 758 757 759 + 372 31 761 760 762 + 373 31 764 763 765 + 374 31 767 766 768 + 375 31 770 769 771 + 376 31 773 772 774 + 377 31 776 775 777 + 378 31 779 778 780 + 379 31 782 781 783 + 380 31 785 784 786 + 381 31 788 787 789 + 382 31 791 790 792 + 383 31 794 793 795 + 384 31 797 796 798 + 385 31 800 799 801 + 386 31 803 802 804 + 387 31 806 805 807 + 388 31 809 808 810 + 389 31 812 811 813 + 390 31 815 814 816 + 391 31 818 817 819 + 392 31 821 820 822 + 393 31 824 823 825 + 394 31 827 826 828 + 395 31 830 829 831 + 396 31 833 832 834 + 397 31 836 835 837 + 398 31 839 838 840 + 399 31 842 841 843 + 400 31 845 844 846 + 401 31 848 847 849 + 402 31 851 850 852 + 403 31 854 853 855 + 404 31 857 856 858 + 405 31 860 859 861 + 406 31 863 862 864 + 407 31 866 865 867 + 408 31 869 868 870 + 409 31 872 871 873 + 410 31 875 874 876 + 411 31 878 877 879 + 412 31 881 880 882 + 413 31 884 883 885 + 414 31 887 886 888 + 415 31 890 889 891 + 416 31 893 892 894 + 417 31 896 895 897 + 418 31 899 898 900 + 419 31 902 901 903 + 420 31 905 904 906 + 421 31 908 907 909 + 422 31 911 910 912 + 423 31 914 913 915 + 424 31 917 916 918 + 425 31 920 919 921 + 426 31 923 922 924 + 427 31 926 925 927 + 428 31 929 928 930 + 429 31 932 931 933 + 430 31 935 934 936 + 431 31 938 937 939 + 432 31 941 940 942 + 433 31 944 943 945 + 434 31 947 946 948 + 435 31 950 949 951 + 436 31 953 952 954 + 437 31 956 955 957 + 438 31 959 958 960 + 439 31 962 961 963 + 440 31 965 964 966 + 441 31 968 967 969 + 442 31 971 970 972 + 443 31 974 973 975 + 444 31 977 976 978 + 445 31 980 979 981 + 446 31 983 982 984 + 447 31 986 985 987 + 448 31 989 988 990 + 449 31 992 991 993 + 450 31 995 994 996 + 451 31 998 997 999 + 452 31 1001 1000 1002 + 453 31 1004 1003 1005 + 454 31 1007 1006 1008 + 455 31 1010 1009 1011 + 456 31 1013 1012 1014 + 457 31 1016 1015 1017 + 458 31 1019 1018 1020 + 459 31 1022 1021 1023 + 460 31 1025 1024 1026 + 461 31 1028 1027 1029 + 462 31 1031 1030 1032 + 463 31 1034 1033 1035 + 464 31 1037 1036 1038 + 465 31 1040 1039 1041 + 466 31 1043 1042 1044 + 467 31 1046 1045 1047 + 468 31 1049 1048 1050 + 469 31 1052 1051 1053 + 470 31 1055 1054 1056 + 471 31 1058 1057 1059 + 472 31 1061 1060 1062 + 473 31 1064 1063 1065 + 474 31 1067 1066 1068 + 475 31 1070 1069 1071 + 476 31 1073 1072 1074 + 477 31 1076 1075 1077 + 478 31 1079 1078 1080 + 479 31 1082 1081 1083 + 480 31 1085 1084 1086 + 481 31 1088 1087 1089 + 482 31 1091 1090 1092 + 483 31 1094 1093 1095 + 484 31 1097 1096 1098 + 485 31 1100 1099 1101 + 486 31 1103 1102 1104 + 487 31 1106 1105 1107 + 488 31 1109 1108 1110 + 489 31 1112 1111 1113 + 490 31 1115 1114 1116 + 491 31 1118 1117 1119 + 492 31 1121 1120 1122 + 493 31 1124 1123 1125 + 494 31 1127 1126 1128 + 495 31 1130 1129 1131 + 496 31 1133 1132 1134 + 497 31 1136 1135 1137 + 498 31 1139 1138 1140 + 499 31 1142 1141 1143 + 500 31 1145 1144 1146 + 501 31 1148 1147 1149 + 502 31 1151 1150 1152 + 503 31 1154 1153 1155 + 504 31 1157 1156 1158 + 505 31 1160 1159 1161 + 506 31 1163 1162 1164 + 507 31 1166 1165 1167 + 508 31 1169 1168 1170 + 509 31 1172 1171 1173 + 510 31 1175 1174 1176 + 511 31 1178 1177 1179 + 512 31 1181 1180 1182 + 513 31 1184 1183 1185 + 514 31 1187 1186 1188 + 515 31 1190 1189 1191 + 516 31 1193 1192 1194 + 517 31 1196 1195 1197 + 518 31 1199 1198 1200 + 519 31 1202 1201 1203 + 520 31 1205 1204 1206 + 521 31 1208 1207 1209 + 522 31 1211 1210 1212 + 523 31 1214 1213 1215 + 524 31 1217 1216 1218 + 525 31 1220 1219 1221 + 526 31 1223 1222 1224 + 527 31 1226 1225 1227 + 528 31 1229 1228 1230 + 529 31 1232 1231 1233 + 530 31 1235 1234 1236 + 531 31 1238 1237 1239 + 532 31 1241 1240 1242 + 533 31 1244 1243 1245 + 534 31 1247 1246 1248 + 535 31 1250 1249 1251 + 536 31 1253 1252 1254 + 537 31 1256 1255 1257 + 538 31 1259 1258 1260 + 539 31 1262 1261 1263 + 540 31 1265 1264 1266 + 541 31 1268 1267 1269 + 542 31 1271 1270 1272 + 543 31 1274 1273 1275 + 544 31 1277 1276 1278 + 545 31 1280 1279 1281 + 546 31 1283 1282 1284 + 547 31 1286 1285 1287 + 548 31 1289 1288 1290 + 549 31 1292 1291 1293 + 550 31 1295 1294 1296 + 551 31 1298 1297 1299 + 552 31 1301 1300 1302 + 553 31 1304 1303 1305 + 554 31 1307 1306 1308 + 555 31 1310 1309 1311 + 556 31 1313 1312 1314 + 557 31 1316 1315 1317 + 558 31 1319 1318 1320 + 559 31 1322 1321 1323 + 560 31 1325 1324 1326 + 561 31 1328 1327 1329 + 562 31 1331 1330 1332 + 563 31 1334 1333 1335 + 564 31 1337 1336 1338 + 565 31 1340 1339 1341 + 566 31 1343 1342 1344 + 567 31 1346 1345 1347 + 568 31 1349 1348 1350 + 569 31 1352 1351 1353 + 570 31 1355 1354 1356 + 571 31 1358 1357 1359 + 572 31 1361 1360 1362 + 573 31 1364 1363 1365 + 574 31 1367 1366 1368 + 575 31 1370 1369 1371 + 576 31 1373 1372 1374 + 577 31 1376 1375 1377 + 578 31 1379 1378 1380 + 579 31 1382 1381 1383 + 580 31 1385 1384 1386 + 581 31 1388 1387 1389 + 582 31 1391 1390 1392 + 583 31 1394 1393 1395 + 584 31 1397 1396 1398 + 585 31 1400 1399 1401 + 586 31 1403 1402 1404 + 587 31 1406 1405 1407 + 588 31 1409 1408 1410 + 589 31 1412 1411 1413 + 590 31 1415 1414 1416 + 591 31 1418 1417 1419 + 592 31 1421 1420 1422 + 593 31 1424 1423 1425 + 594 31 1427 1426 1428 + 595 31 1430 1429 1431 + 596 31 1433 1432 1434 + 597 31 1436 1435 1437 + 598 31 1439 1438 1440 + 599 31 1442 1441 1443 + 600 31 1445 1444 1446 + 601 31 1448 1447 1449 + 602 31 1451 1450 1452 + 603 31 1454 1453 1455 + 604 31 1457 1456 1458 + 605 31 1460 1459 1461 + 606 31 1463 1462 1464 + 607 31 1466 1465 1467 + 608 31 1469 1468 1470 + 609 31 1472 1471 1473 + 610 31 1475 1474 1476 + 611 31 1478 1477 1479 + 612 31 1481 1480 1482 + 613 31 1484 1483 1485 + 614 31 1487 1486 1488 + 615 31 1490 1489 1491 + 616 31 1493 1492 1494 + 617 31 1496 1495 1497 + 618 31 1499 1498 1500 + 619 31 1502 1501 1503 + 620 31 1505 1504 1506 + 621 31 1508 1507 1509 + 622 31 1511 1510 1512 + 623 31 1514 1513 1515 + 624 31 1517 1516 1518 + 625 31 1520 1519 1521 + 626 31 1523 1522 1524 + 627 31 1526 1525 1527 + 628 31 1529 1528 1530 + 629 31 1532 1531 1533 + 630 31 1535 1534 1536 + 631 31 1538 1537 1539 + 632 31 1541 1540 1542 + 633 31 1544 1543 1545 + 634 31 1547 1546 1548 + 635 31 1550 1549 1551 + 636 31 1553 1552 1554 + 637 31 1556 1555 1557 + 638 31 1559 1558 1560 + 639 31 1562 1561 1563 + 640 31 1565 1564 1566 + 641 31 1568 1567 1569 + 642 31 1571 1570 1572 + 643 31 1574 1573 1575 + 644 31 1577 1576 1578 + 645 31 1580 1579 1581 + 646 31 1583 1582 1584 + 647 31 1586 1585 1587 + 648 31 1589 1588 1590 + 649 31 1592 1591 1593 + 650 31 1595 1594 1596 + 651 31 1598 1597 1599 + 652 31 1601 1600 1602 + 653 31 1604 1603 1605 + 654 31 1607 1606 1608 + 655 31 1610 1609 1611 + 656 31 1613 1612 1614 + 657 31 1616 1615 1617 + 658 31 1619 1618 1620 + 659 31 1622 1621 1623 + 660 31 1625 1624 1626 + 661 31 1628 1627 1629 + 662 31 1631 1630 1632 + 663 31 1634 1633 1635 + 664 31 1637 1636 1638 + 665 31 1640 1639 1641 + 666 31 1643 1642 1644 + 667 31 1646 1645 1647 + 668 31 1649 1648 1650 + 669 31 1652 1651 1653 + 670 31 1655 1654 1656 + 671 31 1658 1657 1659 + 672 31 1661 1660 1662 + 673 31 1664 1663 1665 + 674 31 1667 1666 1668 + 675 31 1670 1669 1671 + 676 31 1673 1672 1674 + 677 31 1676 1675 1677 + 678 31 1679 1678 1680 + 679 31 1682 1681 1683 + 680 31 1685 1684 1686 + 681 31 1688 1687 1689 + 682 31 1691 1690 1692 + 683 31 1694 1693 1695 + 684 31 1697 1696 1698 + 685 31 1700 1699 1701 + 686 31 1703 1702 1704 + 687 31 1706 1705 1707 + 688 31 1709 1708 1710 + 689 31 1712 1711 1713 + 690 31 1715 1714 1716 + 691 31 1718 1717 1719 + 692 31 1721 1720 1722 + 693 31 1724 1723 1725 + 694 31 1727 1726 1728 + 695 31 1730 1729 1731 + 696 31 1733 1732 1734 + 697 31 1736 1735 1737 + 698 31 1739 1738 1740 + 699 31 1742 1741 1743 + 700 31 1745 1744 1746 + 701 31 1748 1747 1749 + 702 31 1751 1750 1752 + 703 31 1754 1753 1755 + 704 31 1757 1756 1758 + 705 31 1760 1759 1761 + 706 31 1763 1762 1764 + 707 31 1766 1765 1767 + 708 31 1769 1768 1770 + 709 31 1772 1771 1773 + 710 31 1775 1774 1776 + 711 31 1778 1777 1779 + 712 31 1781 1780 1782 + 713 31 1784 1783 1785 + 714 31 1787 1786 1788 + 715 31 1790 1789 1791 + 716 31 1793 1792 1794 + 717 31 1796 1795 1797 + 718 31 1799 1798 1800 + 719 31 1802 1801 1803 + 720 31 1805 1804 1806 + 721 31 1808 1807 1809 + 722 31 1811 1810 1812 + 723 31 1814 1813 1815 + 724 31 1817 1816 1818 + 725 31 1820 1819 1821 + 726 31 1823 1822 1824 + 727 31 1826 1825 1827 + 728 31 1829 1828 1830 + 729 31 1832 1831 1833 + 730 31 1835 1834 1836 + 731 31 1838 1837 1839 + 732 31 1841 1840 1842 + 733 31 1844 1843 1845 + 734 31 1847 1846 1848 + 735 31 1850 1849 1851 + 736 31 1853 1852 1854 + 737 31 1856 1855 1857 + 738 31 1859 1858 1860 + 739 31 1862 1861 1863 + 740 31 1865 1864 1866 + 741 31 1868 1867 1869 + 742 31 1871 1870 1872 + 743 31 1874 1873 1875 + 744 31 1877 1876 1878 + 745 31 1880 1879 1881 + 746 31 1883 1882 1884 + 747 31 1886 1885 1887 + 748 31 1889 1888 1890 + 749 31 1892 1891 1893 + 750 31 1895 1894 1896 + 751 31 1898 1897 1899 + 752 31 1901 1900 1902 + 753 31 1904 1903 1905 + 754 31 1907 1906 1908 + 755 31 1910 1909 1911 + 756 31 1913 1912 1914 + 757 31 1916 1915 1917 + 758 31 1919 1918 1920 + 759 31 1922 1921 1923 + 760 31 1925 1924 1926 + 761 31 1928 1927 1929 + 762 31 1931 1930 1932 + 763 31 1934 1933 1935 + 764 31 1937 1936 1938 + 765 31 1940 1939 1941 + 766 31 1943 1942 1944 + 767 31 1946 1945 1947 + 768 31 1949 1948 1950 + 769 31 1952 1951 1953 + 770 31 1955 1954 1956 + 771 31 1958 1957 1959 + 772 31 1961 1960 1962 + 773 31 1964 1963 1965 + 774 31 1967 1966 1968 + 775 31 1970 1969 1971 + 776 31 1973 1972 1974 + 777 31 1976 1975 1977 + 778 31 1979 1978 1980 + 779 31 1982 1981 1983 + 780 31 1985 1984 1986 + 781 31 1988 1987 1989 + 782 31 1991 1990 1992 + 783 31 1994 1993 1995 + 784 31 1997 1996 1998 + 785 31 2000 1999 2001 + 786 31 2003 2002 2004 + +Dihedrals + + 1 6 3 1 7 8 + 2 6 2 1 7 19 + 3 4 2 1 7 8 + 4 5 2 1 7 8 + 5 6 3 1 7 19 + 6 3 3 1 2 4 + 7 3 3 1 2 6 + 8 3 3 1 2 5 + 9 3 5 2 1 7 + 10 3 4 2 1 7 + 11 3 6 2 1 7 + 12 3 19 7 8 20 + 13 1 1 7 8 9 + 14 3 1 7 8 20 + 15 2 1 7 8 11 + 16 8 9 8 11 22 + 17 3 7 8 9 10 + 18 7 7 8 9 28 + 19 8 7 8 11 21 + 20 8 7 8 11 12 + 21 3 9 8 7 19 + 22 3 11 8 9 28 + 23 8 7 8 11 22 + 24 3 11 8 7 19 + 25 10 9 8 11 12 + 26 3 20 8 9 28 + 27 8 9 8 11 21 + 28 8 20 8 11 22 + 29 8 20 8 11 21 + 30 4 8 9 28 29 + 31 5 8 9 28 29 + 32 6 10 9 28 29 + 33 11 10 9 8 11 + 34 6 10 9 28 32 + 35 3 10 9 8 20 + 36 6 8 9 28 32 + 37 9 8 11 12 13 + 38 8 12 11 8 20 + 39 9 8 11 12 14 + 40 14 14 12 13 15 + 41 13 13 12 14 24 + 42 3 13 12 11 22 + 43 14 13 12 14 16 + 44 3 14 12 11 22 + 45 3 13 12 11 21 + 46 13 11 12 14 24 + 47 12 11 12 14 16 + 48 3 14 12 11 21 + 49 13 11 12 13 23 + 50 13 14 12 13 23 + 51 12 11 12 13 15 + 52 16 23 13 15 25 + 53 13 12 13 15 25 + 54 14 12 13 15 17 + 55 14 12 14 16 17 + 56 13 12 14 16 26 + 57 16 24 14 16 26 + 58 12 13 15 17 18 + 59 13 17 15 13 23 + 60 14 13 15 17 16 + 61 12 14 16 17 18 + 62 13 17 16 14 24 + 63 14 14 16 17 15 + 64 15 16 17 18 27 + 65 13 15 17 16 26 + 66 13 18 17 15 25 + 67 15 15 17 18 27 + 68 13 16 17 15 25 + 69 13 18 17 16 26 + 70 1 9 28 29 30 + 71 3 32 28 29 33 + 72 3 9 28 29 33 + 73 3 9 28 29 34 + 74 3 32 28 29 34 + 75 3 33 29 30 35 + 76 3 30 29 28 32 + 77 3 34 29 30 35 + 78 7 28 29 30 35 + 79 3 28 29 30 31 + 80 6 29 30 35 39 + 81 4 29 30 35 36 + 82 5 29 30 35 36 + 83 3 31 30 29 34 + 84 3 31 30 29 33 + 85 6 31 30 35 39 + 86 6 31 30 35 36 + 87 1 30 35 36 37 + 88 3 39 35 36 41 + 89 3 30 35 36 40 + 90 3 30 35 36 41 + 91 3 39 35 36 40 + 92 3 40 36 37 42 + 93 3 41 36 37 42 + 94 7 35 36 37 42 + 95 3 35 36 37 38 + 96 3 37 36 35 39 + 97 6 38 37 42 53 + 98 3 38 37 36 40 + 99 6 38 37 42 43 + 100 4 36 37 42 43 + 101 6 36 37 42 53 + 102 5 36 37 42 43 + 103 3 38 37 36 41 + 104 3 37 42 43 54 + 105 1 37 42 43 44 + 106 3 53 42 43 54 + 107 2 37 42 43 46 + 108 10 44 43 46 47 + 109 3 44 43 42 53 + 110 8 42 43 46 56 + 111 8 42 43 46 55 + 112 8 42 43 46 47 + 113 3 46 43 42 53 + 114 8 44 43 46 55 + 115 8 54 43 46 56 + 116 7 42 43 44 62 + 117 3 42 43 44 45 + 118 3 46 43 44 62 + 119 3 54 43 44 62 + 120 8 54 43 46 55 + 121 8 44 43 46 56 + 122 5 43 44 62 63 + 123 6 45 44 62 70 + 124 6 43 44 62 70 + 125 4 43 44 62 63 + 126 11 45 44 43 46 + 127 3 45 44 43 54 + 128 6 45 44 62 63 + 129 9 43 46 47 48 + 130 8 47 46 43 54 + 131 9 43 46 47 49 + 132 3 49 47 46 55 + 133 13 46 47 48 57 + 134 14 49 47 48 50 + 135 3 49 47 46 56 + 136 12 46 47 48 50 + 137 12 46 47 49 51 + 138 14 48 47 49 51 + 139 13 46 47 49 58 + 140 3 48 47 46 55 + 141 3 48 47 46 56 + 142 13 48 47 49 58 + 143 13 49 47 48 57 + 144 14 47 48 50 52 + 145 16 57 48 50 59 + 146 13 47 48 50 59 + 147 16 58 49 51 60 + 148 13 47 49 51 60 + 149 14 47 49 51 52 + 150 13 48 50 52 61 + 151 14 48 50 52 51 + 152 16 59 50 52 61 + 153 13 52 50 48 57 + 154 14 49 51 52 50 + 155 13 49 51 52 61 + 156 13 52 51 49 58 + 157 16 60 51 52 61 + 158 13 51 52 50 59 + 159 13 50 52 51 60 + 160 3 70 62 63 71 + 161 2 44 62 63 66 + 162 1 44 62 63 64 + 163 3 44 62 63 71 + 164 8 62 63 66 72 + 165 8 62 63 66 67 + 166 3 71 63 64 79 + 167 3 62 63 64 65 + 168 3 64 63 62 70 + 169 8 62 63 66 73 + 170 7 62 63 64 79 + 171 8 64 63 66 67 + 172 3 66 63 64 79 + 173 8 64 63 66 72 + 174 3 66 63 62 70 + 175 8 71 63 66 73 + 176 8 64 63 66 73 + 177 8 71 63 66 72 + 178 6 63 64 79 81 + 179 6 65 64 79 80 + 180 3 65 64 63 71 + 181 4 63 64 79 80 + 182 6 65 64 79 81 + 183 5 63 64 79 80 + 184 11 65 64 63 66 + 185 8 67 66 63 71 + 186 17 63 66 67 74 + 187 17 72 66 67 75 + 188 17 63 66 67 75 + 189 17 63 66 67 68 + 190 17 73 66 67 74 + 191 17 73 66 67 75 + 192 17 72 66 67 74 + 193 19 66 67 68 69 + 194 21 68 67 66 72 + 195 18 66 67 68 69 + 196 21 68 67 66 73 + 197 20 69 68 67 74 + 198 20 69 68 67 75 + 199 20 67 68 69 77 + 200 20 67 68 69 76 + 201 20 67 68 69 78 + 202 3 81 79 80 83 + 203 3 81 79 80 84 + 204 3 64 79 80 84 + 205 3 81 79 80 82 + 206 3 64 79 80 83 + 207 3 64 79 80 82 + +Impropers + + 1 2 7 1 8 19 + 2 1 1 2 7 3 + 3 1 9 8 28 10 + 4 2 28 9 29 32 + 5 1 30 29 35 31 + 6 2 35 30 36 39 + 7 1 37 36 42 38 + 8 2 42 37 43 53 + 9 1 44 43 62 45 + 10 2 62 44 63 70 + 11 1 64 63 79 65 + 12 2 79 64 80 81 diff --git a/tools/replica/example/in.peptide b/tools/replica/example/in.peptide new file mode 100644 index 0000000000..5d321e34c3 --- /dev/null +++ b/tools/replica/example/in.peptide @@ -0,0 +1,50 @@ +# Solvated 5-mer peptide + +#---------------------------------- +# Taken as is from examples/peptide + +units real +atom_style full +boundary p p p + +pair_style lj/charmm/coul/long 8.0 10.0 10.0 +bond_style harmonic +angle_style charmm +dihedral_style charmm +improper_style harmonic +kspace_style pppm 0.0001 + +read_data data.peptide + +neighbor 2.0 bin +neigh_modify delay 5 + +timestep 2.0 +#---------------------------------- + + +# temperature schedule for REMD +variable idx world 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 +variable t world 200.0 209.0 219.0 230.0 241.0 252.0 264.0 276.0 289.0 303.0 317.0 332.0 348.0 365.0 382.0 400.0 + +# thermostat +fix thermostat all langevin $t $t 1000 772530 + +# log-file output before minimization +thermo_style custom step temp ke pe +thermo 20 + +# minimization +minimize 1e-4 0.0 1000 1000 + +# change logfile output after minimization +thermo_style custom step temp pe +thermo 20 + +# trajectory style +dump myDump all atom 20 peptide.${idx}.lammpstrj.gz +dump_modify myDump sort id scale no + +# run REMD (for realistic results run for 100000000 steps with 10000 frequency) +reset_timestep 0 +temper 2000 10 $t thermostat 3847 5382 diff --git a/tools/replica/example/parse_ene.py b/tools/replica/example/parse_ene.py new file mode 100644 index 0000000000..56b9328a6a --- /dev/null +++ b/tools/replica/example/parse_ene.py @@ -0,0 +1,30 @@ +#!/usr/bin/env python + +import os, sys, numpy as np + +tempfn = os.path.abspath(sys.argv[1]) +logfnprefix = os.path.abspath(sys.argv[2]) + +temps = np.loadtxt(tempfn) +ntemps = len(temps) +u_kn = [] +start_token = 'Step Temp PotEng' +end_token = 'Loop time' + +for i in range(ntemps): + logfn = '%s.%d' % (logfnprefix, i) + with open(logfn, 'r') as of: + lines = of.readlines() + + # extract relevant lines from logfile + start = [lines.index(line) for line in lines if line.startswith(start_token)][0] + lines = lines[(start+1) : ] + stop = [lines.index(line) for line in lines if line.startswith(end_token)][0] + lines = lines[:stop] + + # store the potential energies + pe = [float(line.strip().split()[-1]) for line in lines] + u_kn.append(pe) + +u_kn = np.array(u_kn) +np.savetxt('ene.peptide', u_kn, fmt = '%5.5f') diff --git a/tools/replica/example/run.sh b/tools/replica/example/run.sh new file mode 100755 index 0000000000..419dc6625f --- /dev/null +++ b/tools/replica/example/run.sh @@ -0,0 +1,10 @@ +#!/bin/bash + +## run REMD using LAMMPS +#mpirun -np 16 ~/mysoftware/lammps/src/lmp_mpi -partition 16x1 -in in.peptide -log log.peptide + +## collect all energies from different replica logs +#python parse_ene.py temps.txt log.peptide + +## run the reordering tool to get reordered trajectories @ 200 K, 276 K, 400 K +mpirun -np 16 python ../reorder_remd_traj.py peptide -logfn log.peptide -tfn temps.txt -ns 10 -nw 20 -np 1000 -ot 200 276 400 -logw -e ene.peptide -od ./output diff --git a/tools/replica/example/temps.txt b/tools/replica/example/temps.txt new file mode 100644 index 0000000000..5931ff06c8 --- /dev/null +++ b/tools/replica/example/temps.txt @@ -0,0 +1 @@ +200.0 209.0 219.0 230.0 241.0 252.0 264.0 276.0 289.0 303.0 317.0 332.0 348.0 365.0 382.0 400.0 diff --git a/tools/replica/reorder_remd_traj.py b/tools/replica/reorder_remd_traj.py new file mode 100644 index 0000000000..6d40b69ec4 --- /dev/null +++ b/tools/replica/reorder_remd_traj.py @@ -0,0 +1,571 @@ +#!/usr/bin/env python + +""" +LAMMPS Replica Exchange Molecular Dynamics (REMD) trajectories are arranged by +replica, i.e., each trajectory is a continuous replica that records all the +ups and downs in temperature. However, often the requirement is trajectories +that are continuous in temperature, which is achieved by this tool. + +Author: +Tanmoy Sanyal, Shell lab, Chemical Engineering, UC Santa Barbara +Email: tanmoy dot 7989 at gmail dot com + +Usage +----- +To get detailed information about the arguments, flags, etc use: +python reorder_remd_traj.py -h or +python reorder_remd_traj.py --help + +Features of this script +----------------------- +a) reorder LAMMPS REMD trajectories by temperature keeping only desired frames. +Note: this only handles LAMMPS format trajectories (i.e. .lammpstrj format) +Trajectories can be gzipped or bz2-compressed. The trajectories are assumed to +be named as .%d.lammpstrj[.gz or .bz2] + +b) (optionally) calculate configurational weights for each frame at each +temperature if potential energies are supplied. But this if for the canonical +(NVT) ensemble only. + +Dependencies +------------ +mpi4py +pymbar (for getting configurational weights) +tqdm (for printing pretty progress bars) +StringIO (or io if in Python 3.x) + +""" + + + +import os, sys, numpy as np, argparse, time, pickle +from scipy.special import logsumexp +from mpi4py import MPI + +from tqdm import tqdm, trange +import gzip +try: + # python-2 + from StringIO import StringIO as IOBuffer +except ImportError: + # python-3 + from io import BytesIO as IOBuffer + + + +#### INITIALISE MPI #### +# (note that all output on screen will be printed only on the ROOT proc) +ROOT = 0 +comm = MPI.COMM_WORLD +me = comm.rank # my proc id +nproc = comm.size + + +#### HELPER FUNCTIONS #### +def _get_nearest_temp(temps, query_temp): + """ + Helper function to get the nearest temp in a list + from a given query_temp + + :param temps: list of temps. + + :param query_temp: query temp + + Returns: + idx: index of nearest temp in the list + + out_temp: nearest temp from the list + """ + + if isinstance(temps, list): temps = np.array(temps) + idx = np.argmin(abs(temps - query_temp)) + out_temp = temps[idx] + return out_temp + + +def readwrite(trajfn, mode = "rb"): + """ + Helper function for input/output LAMMPS traj files. + Trajectories may be plain text, .gz or .bz2 compressed. + + :param trajfn: name of LAMMPS traj + + :param mode: "r" ("w") and "rb" ("wb") depending on read or write + + Returns: file pointer + """ + + if trajfn.endswith(".gz"): + return gzip.GzipFile(trajfn, mode) + elif trajfn.endswith(".bz2"): + return bz2.BZ2File(trajfn, mode) + else: + return file(trajfn, mode) + + +def get_replica_frames(logfn, temps, nswap, writefreq): + """ + Get a list of frames from each replica that is + at a particular temp. Do this for all temps. + + :param logfn: master LAMMPS log file that contains the temp + swap history of all replicas + + :param temps: list of all temps used in the REMD simulation. + + :param nswap: swap frequency of the REMD simulation + + :param writefreq: traj dump frequency in LAMMPS + + Returns: master_frametuple_dict: + dict containing a tuple (replica #, frame #) for each temp. + """ + + n_rep = len(temps) + swap_history = np.loadtxt(logfn, skiprows = 3) + master_frametuple_dict = dict( (n, []) for n in range(n_rep) ) + + # walk through the replicas + print("Getting frames from all replicas at temperature:") + for n in range(n_rep): + print("%3.2f K" % temps[n]) + rep_inds = [np.where(x[1:] == n)[0][0] for x in swap_history] + + # case-1: when frames are dumped faster than temp. swaps + if writefreq <= nswap: + for ii, i in enumerate(rep_inds[:-1]): + start = int(ii * nswap / writefreq) + stop = int( (ii+1) * nswap / writefreq) + [master_frametuple_dict[n].append( (i,x) ) \ + for x in range(start, stop)] + + # case-2: when temps. are swapped faster than dumping frames + else: + nskip = int(writefreq / nswap) + [master_frametuple_dict[n].append( (i,ii) ) \ + for ii, i in enumerate(rep_inds[0::nskip])] + + return master_frametuple_dict + + +def get_byte_index(rep_inds, byteindfns, intrajfns): + """ + Get byte indices from (un-ordered) trajectories. + + :param rep_inds: indices of replicas to process on this proc + + :param byteindsfns: list of filenames that will contain the byte indices + + :param intrajfns: list of (unordered) input traj filenames + """ + for n in rep_inds: + # check if the byte indices for this traj has aleady been computed + if os.path.isfile(byteindfns[n]): continue + + # extract bytes + fobj = readwrite(intrajfns[n]) + byteinds = [ [0,0] ] + + # place file pointer at first line + nframe = 0 + first_line = fobj.readline() + cur_pos = fobj.tell() + + # status printed only for replica read on root proc + # this assumes that each proc takes roughly the same time + if me == ROOT: + pb = tqdm(desc = "Reading replicas", leave = True, + position = ROOT + 2*me, + unit = "B/replica", unit_scale = True, + unit_divisor = 1024) + + # start crawling through the bytes + while True: + next_line = fobj.readline() + if len(next_line) == 0: break + # this will only work with lammpstrj traj format. + # this condition essentially checks periodic recurrences + # of the token TIMESTEP. Each time it is found, + # we have crawled through a frame (snapshot) + if next_line == first_line: + nframe += 1 + byteinds.append( [nframe, cur_pos] ) + if me == ROOT: pb.update() + cur_pos = fobj.tell() + if me == ROOT: pb.update(0) + if me == ROOT: pb.close() + + # take care of the EOF + cur_pos = fobj.tell() + byteinds.append( [nframe+1, cur_pos] ) # dummy index for the EOF + + # write to file + np.savetxt(byteindfns[n], np.array(byteinds), fmt = "%d") + + # close the trajfile object + fobj.close() + + return + + +def write_reordered_traj(temp_inds, byte_inds, outtemps, temps, + frametuple_dict, nprod, writefreq, + outtrajfns, infobjs): + """ + Reorders trajectories by temp. and writes them to disk + + :param temp_inds: list index of temps (in the list of all temps) for which + reordered trajs will be produced on this proc. + + :param byte_inds: dict containing the (previously stored) byte indices + for each replica file (key = replica number) + + :param outtemps: list of all temps for which to produce reordered trajs. + + :param temps: list of all temps used in the REMD simulation. + + :param outtrajfns: list of filenames for output (ordered) trajs. + + :param frametuple_dict: dict containing a tuple (replica #, frame #) + for each temp. + + :param nprod: number of production timesteps. + Last (nprod / writefreq) frames + from the end will be written to disk. + + :param writefreq: traj dump frequency in LAMMPS + + :param infobjs: list of file pointers to input (unordered) trajs. + """ + + nframes = int(nprod / writefreq) + + for n in temp_inds: + # open string-buffer and file + buf = IOBuffer() + of = readwrite(outtrajfns[n], mode = "wb") + + # get frames + abs_temp_ind = np.argmin( abs(temps - outtemps[n]) ) + frametuple = frametuple_dict[abs_temp_ind][-nframes:] + + # write frames to buffer + if me == ROOT: + pb = tqdm(frametuple, + desc = ("Buffering trajectories for writing"), + leave = True, position = ROOT + 2*me, + unit = 'frame/replica', unit_scale = True) + + iterable = pb + else: + iterable = frametuple + + for i, (rep, frame) in enumerate(iterable): + infobj = infobjs[rep] + start_ptr = int(byte_inds[rep][frame,1]) + stop_ptr = int(byte_inds[rep][frame+1,1]) + byte_len = stop_ptr - start_ptr + infobj.seek(start_ptr) + buf.write(infobj.read(byte_len)) + if me == ROOT: pb.close() + + # write buffer to disk + if me == ROOT: print("Writing buffer to file") + of.write(buf.getvalue()) + of.close() + buf.close() + + for i in infobjs: i.close() + + return + + +def get_canonical_logw(enefn, frametuple_dict, temps, nprod, writefreq, + kB = 0.001987): + """ + Gets configurational log-weights (logw) for each frame and at each temp. + from the REMD simulation. ONLY WRITTEN FOR THE CANONICAL (NVT) ensemble. + + This weights can be used to calculate the + ensemble averaged value of any simulation observable X at a given temp. T : + (T) = \sum_{k=1, ntemps} \sum_{n=1, nframes} w[idx][k,n] X[k,n] + where nframes is the number of frames to use from each *reordered* traj + + :param enefn: ascii file (readable by numpy.loadtxt) containing an array + u[r,n] of *total* potential energy for the n-th frame for + the r-th replica. + + :param frametuple_dict: dict containing a tuple (replica #, frame #) + for each temp. + + :param temps: array of temps. used in the REMD simulation + + :param nprod: number of production timesteps. Last (nprod / writefreq) + frames from the end will be written to disk. + + :param writefreq: traj dump frequency in LAMMPS + + :param kB : Boltzmann constant to set the energy scale. + Default is in kcal/mol + + Returns: logw: dict, logw[l][k,n] gives the log weights from the + n-th frame of the k-th temp. *ordered* trajectory + to reweight to the l-th temp. + + """ + + try: + import pymbar + except ImportError: + print(""" + Configurational log-weight calculation requires pymbar. + Here are some options to install it: + conda install -c omnia pymbar + pip install pymbar + + To install the dev. version directly from github, use: + pip install pip install git+https://github.com/choderalab/pymbar.git + """) + + u_rn = np.loadtxt(enefn) + ntemps = u_rn.shape[0] # number of temps. + nframes = int(nprod / writefreq) # number of frames at each temp. + + # reorder the temps + u_kn = np.zeros([ntemps, nframes], float) + for k in range(ntemps): + frame_tuple = frametuple_dict[k][-nframes:] + for i, (rep, frame) in enumerate(frame_tuple): + u_kn[k, i] = u_rn[rep, frame] + + # prep input for pymbar + #1) array of frames at each temp. + nframes_k = nframes * np.ones(ntemps, np.uint8) + + #2) inverse temps. for chosen energy scale + beta_k = 1.0 / (kB * temps) + + #3) get reduced energies (*ONLY FOR THE CANONICAL ENSEMBLE*) + u_kln = np.zeros([ntemps, ntemps, nframes], float) + for k in range(ntemps): + for l in range(ntemps): + u_kln[ k, l, 0:nframes_k[k] ] = beta_k[l] * u_kn[k, 0:nframes_k[k]] + + # run pymbar and extract the free energies + print("\nRunning pymbar...") + mbar = pymbar.mbar.MBAR(u_kln, nframes_k, verbose = True) + f_k = mbar.f_k + + # calculate the log-weights + print("\nExtracting log-weights...") + log_nframes = np.log(nframes) + logw = dict( (k, np.zeros([ntemps, nframes], float)) for k in range(ntemps) ) + for l in range(ntemps): + # get log-weights to reweight to this temp. + for k in range(ntemps): + for n in range(nframes): + num = -beta_k[k] * u_kn[k,n] + denom = f_k - beta_k[k] * u_kn[k,n] + logw[l][k,n] = num - logsumexp(denom) - log_nframes + return logw + + + +#### MAIN WORKFLOW #### +if __name__ == "__main__": + # accept user inputs + parser = argparse.ArgumentParser(description = __doc__, + formatter_class = argparse.RawDescriptionHelpFormatter) + + parser.add_argument("prefix", + help = "Prefix of REMD LAMMPS trajectories.\ + Supply full path. Trajectories assumed to be named as \ + .%%d.lammpstrj. \ + Can be in compressed (.gz or .bz2) format. \ + This is a required argument") + + parser.add_argument("-logfn", "--logfn", default = "log.lammps", + help = "LAMMPS log file that contains swap history \ + of temperatures among replicas. \ + Default = 'lammps.log'") + + parser.add_argument("-tfn", "--tempfn", default = "temps.txt", + help = "ascii file (readable by numpy.loadtxt) with \ + the temperatures used in the REMD simulation.") + + parser.add_argument("-ns", "--nswap", type = int, + help = "Swap frequency used in LAMMPS temper command") + + parser.add_argument("-nw", "--nwrite", type = int, default = 1, + help = "Trajectory writing frequency used \ + in LAMMPS dump command") + + parser.add_argument("-np", "--nprod", type = int, default = 0, + help = "Number of timesteps to save in the reordered\ + trajectories.\ + This should be in units of the LAMMPS timestep") + + parser.add_argument("-logw", "--logw", action = 'store_true', + help = "Supplying this flag \ + calculates *canonical* (NVT ensemble) log weights") + + parser.add_argument("-e", "--enefn", + help = "File that has n_replica x n_frames array\ + of total potential energies") + + parser.add_argument("-kB", "--boltzmann_const", + type = float, default = 0.001987, + help = "Boltzmann constant in appropriate units. \ + Default is kcal/mol") + + parser.add_argument("-ot", "--out_temps", nargs = '+', type = np.float64, + help = "Reorder trajectories at these temperatures.\n \ + Default is all temperatures used in the simulation") + + parser.add_argument("-od", "--outdir", default = ".", + help = "All output will be saved to this directory") + + # parse inputs + args = parser.parse_args() + traj_prefix = os.path.abspath(args.prefix) + logfn = os.path.abspath(args.logfn) + tempfn = os.path.abspath(args.tempfn) + + nswap = args.nswap + writefreq = args.nwrite + nprod = args.nprod + + enefn = args.enefn + if not enefn is None: enefn = os.path.abspath(enefn) + get_logw = args.logw + kB = args.boltzmann_const + + out_temps = args.out_temps + outdir = os.path.abspath(args.outdir) + if not os.path.isdir(outdir): + if me == ROOT: os.mkdir(outdir) + + # check that all input files are present (only on the ROOT proc) + if me == ROOT: + if not os.path.isfile(tempfn): + raise IOError("Temperature file %s not found." % tempfn) + elif not os.path.isfile(logfn): + raise IOError("LAMMPS log file %s not found." % logfn) + elif get_logw and not os.path.isfile(enefn): + raise IOError("Canonical log-weight calculation requested but\ + energy file %s not found" % enefn) + + # get (unordered) trajectories + temps = np.loadtxt(tempfn) + ntemps = len(temps) + intrajfns = ["%s.%d.lammpstrj" % (traj_prefix, k) for k in range(ntemps)] + # check if the trajs. (or their zipped versions are present) + for i in range(ntemps): + this_intrajfn = intrajfns[i] + x = this_intrajfn + ".gz" + if os.path.isfile(this_intrajfn): continue + elif os.path.isfile(this_intrajfn + ".gz"): + intrajfns[i] = this_intrajfn + ".gz" + elif os.path.isfile(this_intrajfn + ".bz2"): + intrajfns[i] = this_intrajfn + ".bz2" + else: + if me == ROOT: + raise IOError("Trajectory for replica # %d missing" % i) + + # set output filenames + outprefix = os.path.join(outdir, traj_prefix.split('/')[-1]) + outtrajfns = ["%s.%3.2f.lammpstrj.gz" % \ + (outprefix, _get_nearest_temp(temps, t)) \ + for t in out_temps] + byteindfns = [os.path.join(outdir, ".byteind_%d.gz" % k) \ + for k in range(ntemps)] + frametuplefn = outprefix + '.frametuple.pickle' + if get_logw: + logwfn = outprefix + ".logw.pickle" + + + # get a list of all frames at a particular temp visited by each replica + # this is fast so run only on ROOT proc. + master_frametuple_dict = {} + if me == ROOT: + master_frametuple_dict = get_replica_frames(logfn = logfn, + temps = temps, + nswap = nswap, + writefreq = writefreq) + # save to a pickle from the ROOT proc + with open(frametuplefn, 'wb') as of: + pickle.dump(master_frametuple_dict, of) + + # broadcast to all procs + master_frametuple_dict = comm.bcast(master_frametuple_dict, root = ROOT) + + # define a chunk of replicas to process on each proc + CHUNKSIZE_1 = int(ntemps/nproc) + if me < nproc - 1: + my_rep_inds = range( (me*CHUNKSIZE_1), (me+1)*CHUNKSIZE_1 ) + else: + my_rep_inds = range( (me*CHUNKSIZE_1), ntemps ) + + # get byte indices from replica (un-ordered) trajs. in parallel + get_byte_index(rep_inds = my_rep_inds, + byteindfns = byteindfns, + intrajfns = intrajfns) + + # block until all procs have finished + comm.barrier() + + # open all replica files for reading + infobjs = [readwrite(i) for i in intrajfns] + + # open all byteindex files + byte_inds = dict( (i, np.loadtxt(fn)) for i, fn in enumerate(byteindfns) ) + + # define a chunk of output trajs. to process for each proc. + # # of reordered trajs. to write may be less than the total # of replicas + # which is usually equal to the requested nproc. If that is indeed the case, + # retire excess procs + n_out_temps = len(out_temps) + CHUNKSIZE_2 = int(n_out_temps / nproc) + if CHUNKSIZE_2 == 0: + nproc_active = n_out_temps + CHUNKSIZE_2 = 1 + if me == ROOT: + print("\nReleasing %d excess procs" % (nproc - nproc_active)) + else: + nproc_active = nproc + if me < nproc_active-1: + my_temp_inds = range( (me*CHUNKSIZE_2), (me+1)*CHUNKSIZE_1 ) + else: + my_temp_inds = range( (me*CHUNKSIZE_2), n_out_temps) + + # retire the excess procs + # dont' forget to close any open file objects + if me >= nproc_active: + for fobj in infobjs: fobj.close() + exit() + + # write reordered trajectories to disk from active procs in parallel + write_reordered_traj(temp_inds = my_temp_inds, + byte_inds = byte_inds, + outtemps = out_temps, temps = temps, + frametuple_dict = master_frametuple_dict, + nprod = nprod, writefreq = writefreq, + outtrajfns = outtrajfns, + infobjs = infobjs) + + # calculate canonical log-weights if requested + # usually this is very fast so retire all but the ROOT proc + if not get_logw: exit() + if not me == ROOT: exit() + + logw = get_canonical_logw(enefn = enefn, temps = temps, + frametuple_dict = master_frametuple_dict, + nprod = nprod, writefreq = writefreq, + kB = kB) + + + # save the logweights to a pickle + with open(logwfn, 'wb') as of: + pickle.dump(logw, of) + + From 96c21bec982e2cfcff03aba3a24c99fac9c1dd8a Mon Sep 17 00:00:00 2001 From: "tanmoy.7989" Date: Wed, 4 Sep 2019 23:16:19 -0700 Subject: [PATCH 091/192] added new valid words to doc/utils/sphinx-config/false_positives.txt --- doc/src/Tools.txt | 4 ++-- doc/utils/sphinx-config/false_positives.txt | 5 +++++ 2 files changed, 7 insertions(+), 2 deletions(-) diff --git a/doc/src/Tools.txt b/doc/src/Tools.txt index fcbafdaf7e..6c41524d20 100644 --- a/doc/src/Tools.txt +++ b/doc/src/Tools.txt @@ -563,5 +563,5 @@ Additional options can be used to calculate the canonical configurational log-weight for each frame at each temperature using the pymbar package. See the README.md file for further details. Try out the peptide example provided. -This tool was written by Tanmoy Sanyal, -while at the Shell lab at UC Santa Barbara. (tanmoy dot 7989 at gmail.com) +This tool was written by Tanmoy Sanyal, while at the Shell lab +at UC Santa Barbara. (tanmoy dot 7989 at gmail.com) diff --git a/doc/utils/sphinx-config/false_positives.txt b/doc/utils/sphinx-config/false_positives.txt index 6d5112b4c7..e635c71ab8 100644 --- a/doc/utils/sphinx-config/false_positives.txt +++ b/doc/utils/sphinx-config/false_positives.txt @@ -2239,6 +2239,7 @@ Py pydir pylammps PyLammps +pymbar pymodule pymol pypar @@ -2325,6 +2326,7 @@ reinit relink relTol remappings +remd Ren Rendon reneighbor @@ -2456,6 +2458,7 @@ Sandia sandybrown Sanitizer sanitizers +Sanyal sc scafacos SCAFACOS @@ -2689,6 +2692,8 @@ Tajkhorshid Tamaskovics Tanaka tanh +tanmoy +Tanmoy Tartakovsky taskset taubi From cffe43c96ce23bf119a2cf1e8f8b4cbb768c8d49 Mon Sep 17 00:00:00 2001 From: Axel Kohlmeyer Date: Thu, 5 Sep 2019 12:11:32 -0400 Subject: [PATCH 092/192] bugfix for copying svector data with hybrid pair styles --- src/pair_hybrid.cpp | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/src/pair_hybrid.cpp b/src/pair_hybrid.cpp index 762b9fe8fc..6402cf7fdc 100644 --- a/src/pair_hybrid.cpp +++ b/src/pair_hybrid.cpp @@ -776,8 +776,8 @@ double PairHybrid::single(int i, int j, int itype, int jtype, // copy substyle extra values into hybrid's svector if (single_extra && styles[map[itype][jtype][m]]->single_extra) - for (m = 0; m < single_extra; m++) - svector[m] = styles[map[itype][jtype][m]]->svector[m]; + for (int n = 0; n < single_extra; n++) + svector[n] = styles[map[itype][jtype][m]]->svector[n]; } } From 41d9dbff33011f5fb4d268a6a76468ec6e10de20 Mon Sep 17 00:00:00 2001 From: Axel Kohlmeyer Date: Thu, 5 Sep 2019 14:08:26 -0400 Subject: [PATCH 093/192] append all svector entries instead of copying over each other --- src/pair_hybrid.cpp | 13 +++++++------ 1 file changed, 7 insertions(+), 6 deletions(-) diff --git a/src/pair_hybrid.cpp b/src/pair_hybrid.cpp index 6402cf7fdc..31f017df12 100644 --- a/src/pair_hybrid.cpp +++ b/src/pair_hybrid.cpp @@ -363,12 +363,12 @@ void PairHybrid::flags() if (styles[m]->compute_flag) compute_flag = 1; } - // single_extra = min of all sub-style single_extra + // single_extra = sum of all sub-style single_extra // allocate svector - single_extra = styles[0]->single_extra; - for (m = 1; m < nstyles; m++) - single_extra = MIN(single_extra,styles[m]->single_extra); + single_extra = 0; + for (m = 0; m < nstyles; m++) + single_extra += styles[m]->single_extra; if (single_extra) { delete [] svector; @@ -758,6 +758,7 @@ double PairHybrid::single(int i, int j, int itype, int jtype, double fone; fforce = 0.0; double esum = 0.0; + int n = 0; for (int m = 0; m < nmap[itype][jtype]; m++) { if (rsq < styles[map[itype][jtype][m]]->cutsq[itype][jtype]) { @@ -776,8 +777,8 @@ double PairHybrid::single(int i, int j, int itype, int jtype, // copy substyle extra values into hybrid's svector if (single_extra && styles[map[itype][jtype][m]]->single_extra) - for (int n = 0; n < single_extra; n++) - svector[n] = styles[map[itype][jtype][m]]->svector[n]; + for (int l = 0; l < styles[map[itype][jtype][m]]->single_extra; l++) + svector[n++] = styles[map[itype][jtype][m]]->svector[l]; } } From 24f1981e31f9041955a4269c983b6389cf212137 Mon Sep 17 00:00:00 2001 From: Axel Kohlmeyer Date: Thu, 5 Sep 2019 14:10:02 -0400 Subject: [PATCH 094/192] use link instead of copy of data file for replica tool example --- tools/replica/example/data.peptide | 6532 +--------------------------- 1 file changed, 1 insertion(+), 6531 deletions(-) mode change 100644 => 120000 tools/replica/example/data.peptide diff --git a/tools/replica/example/data.peptide b/tools/replica/example/data.peptide deleted file mode 100644 index f9dfb6e485..0000000000 --- a/tools/replica/example/data.peptide +++ /dev/null @@ -1,6531 +0,0 @@ -LAMMPS Description - - 2004 atoms - 1365 bonds - 786 angles - 207 dihedrals - 12 impropers - - 14 atom types - 18 bond types - 31 angle types - 21 dihedral types - 2 improper types - - 36.840194 64.211560 xlo xhi - 41.013691 68.385058 ylo yhi - 29.768095 57.139462 zlo zhi - -Masses - - 1 12.0110 - 2 12.0110 - 3 15.9990 - 4 1.0080 - 5 14.0070 - 6 12.0110 - 7 12.0110 - 8 12.0110 - 9 15.9990 - 10 1.0080 - 11 1.0080 - 12 32.0660 - 13 16.0000 - 14 1.0100 - -Pair Coeffs - - 1 0.110000 3.563595 0.110000 3.563595 - 2 0.080000 3.670503 0.010000 3.385415 - 3 0.120000 3.029056 0.120000 2.494516 - 4 0.022000 2.351973 0.022000 2.351973 - 5 0.200000 3.296325 0.200000 2.761786 - 6 0.020000 4.053589 0.010000 3.385415 - 7 0.055000 3.875410 0.010000 3.385415 - 8 0.070000 3.550053 0.070000 3.550053 - 9 0.152100 3.153782 0.152100 3.153782 - 10 0.046000 0.400014 0.046000 0.400014 - 11 0.030000 2.420037 0.030000 2.420037 - 12 0.450000 3.563595 0.450000 3.563595 - 13 0.152100 3.150570 0.152100 3.150570 - 14 0.046000 0.400014 0.046000 0.400014 - -Bond Coeffs - - 1 249.999999 1.490000 - 2 620.000001 1.230000 - 3 370.000000 1.345000 - 4 322.000001 1.111000 - 5 319.999999 1.430000 - 6 440.000000 0.997000 - 7 222.500001 1.538000 - 8 330.000001 1.080000 - 9 230.000000 1.490000 - 10 309.000001 1.111000 - 11 305.000000 1.375000 - 12 340.000001 1.080000 - 13 334.300000 1.411000 - 14 545.000001 0.960000 - 15 222.500001 1.530000 - 16 198.000000 1.818000 - 17 239.999999 1.816000 - 18 450.000000 0.957200 - -Angle Coeffs - - 1 33.000000 109.500000 30.000000 2.163000 - 2 50.000000 120.000000 0.000000 0.000000 - 3 34.000000 123.000000 0.000000 0.000000 - 4 80.000000 121.000000 0.000000 0.000000 - 5 80.000000 116.500000 0.000000 0.000000 - 6 80.000000 122.500000 0.000000 0.000000 - 7 35.500000 108.400000 5.400000 1.802000 - 8 50.000000 107.000000 0.000000 0.000000 - 9 70.000000 113.500000 0.000000 0.000000 - 10 48.000000 108.000000 0.000000 0.000000 - 11 35.000000 117.000000 0.000000 0.000000 - 12 51.800000 107.500000 0.000000 0.000000 - 13 33.430000 110.100000 22.530000 2.179000 - 14 52.000000 108.000000 0.000000 0.000000 - 15 50.000000 109.500000 0.000000 0.000000 - 16 35.000000 111.000000 0.000000 0.000000 - 17 45.800000 122.300000 0.000000 0.000000 - 18 49.300000 107.500000 0.000000 0.000000 - 19 40.000000 120.000000 35.000000 2.416200 - 20 30.000000 120.000000 22.000000 2.152500 - 21 45.200000 120.000000 0.000000 0.000000 - 22 65.000000 108.000000 0.000000 0.000000 - 23 35.500000 109.000000 5.400000 1.802000 - 24 36.000000 115.000000 0.000000 0.000000 - 25 58.350000 113.500000 11.160000 2.561000 - 26 58.000000 114.500000 0.000000 0.000000 - 27 26.500000 110.100000 22.530000 2.179000 - 28 34.000000 95.000000 0.000000 0.000000 - 29 46.100000 111.300000 0.000000 0.000000 - 30 51.500000 109.500000 0.000000 0.000000 - 31 55.000000 104.520000 0.000000 0.000000 - -Dihedral Coeffs - - 1 0.200000 1 180 1.000000 - 2 1.800000 1 0 1.000000 - 3 0.000000 1 0 1.000000 - 4 1.600000 1 0 0.500000 - 5 2.500000 2 180 0.500000 - 6 2.500000 2 180 1.000000 - 7 0.600000 1 0 1.000000 - 8 0.200000 3 0 1.000000 - 9 0.230000 2 180 1.000000 - 10 0.040000 3 0 1.000000 - 11 1.400000 1 0 1.000000 - 12 3.100000 2 180 1.000000 - 13 4.200000 2 180 1.000000 - 14 3.100000 2 180 0.500000 - 15 0.990000 2 180 1.000000 - 16 2.400000 2 180 1.000000 - 17 0.195000 3 0 1.000000 - 18 0.240000 1 180 0.500000 - 19 0.370000 3 0 0.500000 - 20 0.280000 3 0 1.000000 - 21 0.010000 3 0 1.000000 - -Improper Coeffs - - 1 120.000000 0.000000 - 2 20.000000 0.000000 - -Atoms - - 1 1 1 0.510 43.99993 58.52678 36.78550 0 0 0 - 2 1 2 -0.270 45.10395 58.23499 35.86693 0 0 0 - 3 1 3 -0.510 43.81519 59.54928 37.43995 0 0 0 - 4 1 4 0.090 45.71714 57.34797 36.13434 0 0 0 - 5 1 4 0.090 45.72261 59.13657 35.67007 0 0 0 - 6 1 4 0.090 44.66624 58.09539 34.85538 0 0 0 - 7 1 5 -0.470 43.28193 57.47427 36.91953 0 0 0 - 8 1 6 0.070 42.07157 57.45486 37.62418 0 0 0 - 9 1 1 0.510 42.19985 57.57789 39.12163 0 0 0 - 10 1 3 -0.510 41.88641 58.62251 39.70398 0 0 0 - 11 1 7 -0.180 41.25052 56.15304 37.41811 0 0 0 - 12 1 8 0.000 40.88511 55.94638 35.97460 0 0 0 - 13 1 8 -0.115 41.48305 54.96372 35.11223 0 0 0 - 14 1 8 -0.115 39.74003 56.60996 35.46443 0 0 0 - 15 1 8 -0.115 41.02111 54.75715 33.80764 0 0 0 - 16 1 8 -0.115 39.26180 56.39194 34.12024 0 0 0 - 17 1 8 0.110 39.92330 55.46092 33.27135 0 0 0 - 18 1 9 -0.540 39.48164 55.22919 31.91865 0 0 0 - 19 1 10 0.310 43.60633 56.61693 36.52744 0 0 0 - 20 1 4 0.090 41.49619 58.31145 37.30543 0 0 0 - 21 1 4 0.090 41.88498 55.29476 37.72657 0 0 0 - 22 1 4 0.090 40.30899 56.19690 38.00627 0 0 0 - 23 1 11 0.115 42.31528 54.36176 35.44606 0 0 0 - 24 1 11 0.115 39.26330 57.31216 36.13230 0 0 0 - 25 1 11 0.115 41.62695 54.10606 33.19490 0 0 0 - 26 1 11 0.115 38.42147 56.98236 33.78612 0 0 0 - 27 1 10 0.430 38.78233 55.86217 31.74004 0 0 0 - 28 1 5 -0.470 42.79933 56.56370 39.79000 0 0 0 - 29 1 7 -0.020 42.96709 56.75379 41.28116 0 0 0 - 30 1 1 0.510 43.83019 55.68988 41.92255 0 0 0 - 31 1 3 -0.510 44.98521 55.93104 42.21713 0 0 0 - 32 1 10 0.310 43.13466 55.75696 39.30966 0 0 0 - 33 1 4 0.090 42.04692 56.86721 41.83507 0 0 0 - 34 1 4 0.090 43.52938 57.66324 41.43329 0 0 0 - 35 1 5 -0.470 43.26792 54.43342 42.07043 0 0 0 - 36 1 7 -0.020 43.92411 53.28930 42.63327 0 0 0 - 37 1 1 0.510 43.51012 53.02289 44.10510 0 0 0 - 38 1 3 -0.510 42.35086 53.07863 44.50806 0 0 0 - 39 1 10 0.310 42.28859 54.34993 41.90323 0 0 0 - 40 1 4 0.090 44.98464 53.47473 42.54797 0 0 0 - 41 1 4 0.090 43.49715 52.54787 41.97419 0 0 0 - 42 1 5 -0.470 44.51925 52.64535 44.88133 0 0 0 - 43 1 6 0.070 44.47588 52.35054 46.24397 0 0 0 - 44 1 1 0.510 45.40218 53.34579 46.94730 0 0 0 - 45 1 3 -0.510 45.23520 54.55893 46.92038 0 0 0 - 46 1 7 -0.180 44.77960 50.82831 46.50232 0 0 0 - 47 1 8 0.000 43.72184 49.84551 45.98093 0 0 0 - 48 1 8 -0.115 44.14810 49.00477 44.97195 0 0 0 - 49 1 8 -0.115 42.43499 49.66652 46.53541 0 0 0 - 50 1 8 -0.115 43.26154 48.00434 44.46769 0 0 0 - 51 1 8 -0.115 41.54732 48.79670 45.95416 0 0 0 - 52 1 8 -0.115 41.98220 47.90746 44.95574 0 0 0 - 53 1 10 0.310 45.39510 52.50937 44.42482 0 0 0 - 54 1 4 0.090 43.51312 52.58974 46.67092 0 0 0 - 55 1 4 0.090 44.89709 50.54313 47.56965 0 0 0 - 56 1 4 0.090 45.72096 50.49337 46.01654 0 0 0 - 57 1 11 0.115 45.13573 49.07933 44.54134 0 0 0 - 58 1 11 0.115 42.07869 50.34816 47.29358 0 0 0 - 59 1 11 0.115 43.47793 47.29281 43.68456 0 0 0 - 60 1 11 0.115 40.52625 48.76134 46.30425 0 0 0 - 61 1 11 0.115 41.35446 47.13287 44.54059 0 0 0 - 62 1 5 -0.470 46.41448 52.86278 47.68291 0 0 0 - 63 1 6 0.070 47.25136 53.68184 48.51163 0 0 0 - 64 1 1 0.510 48.33905 54.40097 47.73886 0 0 0 - 65 1 3 -0.510 49.27132 53.85220 47.16549 0 0 0 - 66 1 7 -0.180 47.88329 52.75681 49.60227 0 0 0 - 67 1 7 -0.140 48.82515 53.51102 50.61578 0 0 0 - 68 1 12 -0.090 48.12492 55.00373 51.43039 0 0 0 - 69 1 2 -0.220 47.70783 54.12980 53.04072 0 0 0 - 70 1 10 0.310 46.67199 51.90088 47.73231 0 0 0 - 71 1 4 0.090 46.64593 54.43552 48.99310 0 0 0 - 72 1 4 0.090 48.41361 51.90817 49.11968 0 0 0 - 73 1 4 0.090 47.08748 52.35196 50.26341 0 0 0 - 74 1 4 0.090 49.16067 52.81305 51.41238 0 0 0 - 75 1 4 0.090 49.73705 53.67062 50.00155 0 0 0 - 76 1 4 0.090 47.18593 54.84215 53.71488 0 0 0 - 77 1 4 0.090 48.69939 53.91624 53.49408 0 0 0 - 78 1 4 0.090 47.19749 53.18294 52.76264 0 0 0 - 79 1 5 -0.470 48.34472 55.71775 47.80498 0 0 0 - 80 1 2 -0.110 49.37792 56.51754 47.29492 0 0 0 - 81 1 10 0.310 47.51777 56.11617 48.19410 0 0 0 - 82 1 4 0.090 50.41495 56.13038 47.38980 0 0 0 - 83 1 4 0.090 49.23515 57.51193 47.76940 0 0 0 - 84 1 4 0.090 49.28612 56.52094 46.18773 0 0 0 - 85 2 13 -0.834 52.28049 45.72878 41.48140 -1 0 1 - 86 2 14 0.417 51.97210 46.07066 40.64218 -1 0 1 - 87 2 14 0.417 52.43689 44.79855 41.31868 -1 0 1 - 88 3 13 -0.834 43.84472 45.66062 47.17660 -2 -1 -1 - 89 3 14 0.417 43.42120 44.88337 46.81226 -2 -1 -1 - 90 3 14 0.417 44.31099 46.04907 46.43636 -2 -1 -1 - 91 4 13 -0.834 51.27805 50.25403 54.67397 0 0 -1 - 92 4 14 0.417 50.81295 50.23728 53.83753 0 0 -1 - 93 4 14 0.417 52.00273 49.63953 54.55795 0 0 -1 - 94 5 13 -0.834 44.71976 53.72011 56.43834 -1 0 -1 - 95 5 14 0.417 44.56050 53.84218 55.50241 -1 0 -1 - 96 5 14 0.417 44.91937 52.78829 56.52828 -1 0 -1 - 97 6 13 -0.834 37.07074 62.07204 53.35752 -1 -1 -1 - 98 6 14 0.417 64.17057 61.77089 52.49043 -2 -1 -1 - 99 6 14 0.417 37.90147 62.52273 53.20573 -1 -1 -1 - 100 7 13 -0.834 38.31817 66.10834 49.17406 0 -1 0 - 101 7 14 0.417 37.39300 65.93985 48.99534 0 -1 0 - 102 7 14 0.417 38.36506 66.20528 50.12520 0 -1 0 - 103 8 13 -0.834 60.90915 45.97690 35.53863 -1 -1 1 - 104 8 14 0.417 61.19898 46.87819 35.39745 -1 -1 1 - 105 8 14 0.417 59.98680 45.97855 35.28269 -1 -1 1 - 106 9 13 -0.834 54.33913 64.47210 51.00391 -1 -2 0 - 107 9 14 0.417 54.43191 63.71377 50.42724 -1 -2 0 - 108 9 14 0.417 55.16289 64.94980 50.90662 -1 -2 0 - 109 10 13 -0.834 44.58017 54.03749 53.84708 1 0 -1 - 110 10 14 0.417 43.87040 54.43768 53.34476 1 0 -1 - 111 10 14 0.417 45.02999 53.47261 53.21873 1 0 -1 - 112 11 13 -0.834 45.48693 52.12363 34.38241 0 -1 1 - 113 11 14 0.417 45.46898 52.67450 33.59981 0 -1 1 - 114 11 14 0.417 44.61476 52.22113 34.76457 0 -1 1 - 115 12 13 -0.834 60.15770 61.68799 54.74753 1 0 -2 - 116 12 14 0.417 59.23977 61.46439 54.59378 1 0 -2 - 117 12 14 0.417 60.43785 61.08922 55.43980 1 0 -2 - 118 13 13 -0.834 60.74732 66.72156 42.80906 1 -2 0 - 119 13 14 0.417 60.34713 66.21969 42.09898 1 -2 0 - 120 13 14 0.417 60.92444 66.07344 43.49082 1 -2 0 - 121 14 13 -0.834 60.82245 64.17281 50.54212 0 0 0 - 122 14 14 0.417 61.43571 64.88448 50.35863 0 0 0 - 123 14 14 0.417 60.87804 64.04633 51.48930 0 0 0 - 124 15 13 -0.834 36.92704 63.01353 56.05215 0 -1 0 - 125 15 14 0.417 37.10744 62.17054 56.46815 0 -1 0 - 126 15 14 0.417 64.06237 62.79109 55.15157 -1 -1 0 - 127 16 13 -0.834 48.35559 58.70568 56.14001 1 0 0 - 128 16 14 0.417 48.11655 59.48087 55.63191 1 0 0 - 129 16 14 0.417 47.93212 58.83502 56.98865 1 0 0 - 130 17 13 -0.834 58.14651 57.18542 51.08241 0 -1 -1 - 131 17 14 0.417 57.88523 56.72609 51.88052 0 -1 -1 - 132 17 14 0.417 57.35121 57.63116 50.79076 0 -1 -1 - 133 18 13 -0.834 58.09837 59.68005 36.16995 -1 0 0 - 134 18 14 0.417 58.25901 58.76822 36.41283 -1 0 0 - 135 18 14 0.417 58.56239 60.19049 36.83355 -1 0 0 - 136 19 13 -0.834 52.29019 60.51169 50.55611 0 -2 1 - 137 19 14 0.417 52.61972 60.01708 51.30645 0 -2 1 - 138 19 14 0.417 52.55621 59.99722 49.79401 0 -2 1 - 139 20 13 -0.834 41.36642 50.33705 42.98530 0 -1 -1 - 140 20 14 0.417 41.27846 50.09969 43.90844 0 -1 -1 - 141 20 14 0.417 40.99321 51.21659 42.92708 0 -1 -1 - 142 21 13 -0.834 53.76920 67.02645 32.18667 -1 0 1 - 143 21 14 0.417 53.59447 67.18509 31.25901 -1 0 1 - 144 21 14 0.417 54.65308 67.36647 32.32596 -1 0 1 - 145 22 13 -0.834 57.83691 45.33663 46.94671 0 0 -2 - 146 22 14 0.417 57.36287 45.59552 46.15647 0 0 -2 - 147 22 14 0.417 58.62995 44.91017 46.62197 0 0 -2 - 148 23 13 -0.834 60.34518 45.83000 45.57964 -1 0 0 - 149 23 14 0.417 60.61871 44.93757 45.79176 -1 0 0 - 150 23 14 0.417 61.09971 46.21212 45.13141 -1 0 0 - 151 24 13 -0.834 55.97902 46.85046 56.80163 0 1 1 - 152 24 14 0.417 56.57528 46.69952 30.16370 0 1 2 - 153 24 14 0.417 55.81156 47.79276 56.81850 0 1 1 - 154 25 13 -0.834 57.54668 45.52135 31.46139 -1 0 1 - 155 25 14 0.417 58.36291 46.00311 31.32743 -1 0 1 - 156 25 14 0.417 57.54151 45.31312 32.39566 -1 0 1 - 157 26 13 -0.834 58.03029 52.86783 46.33564 -1 -1 0 - 158 26 14 0.417 58.13662 52.56730 47.23820 -1 -1 0 - 159 26 14 0.417 58.81317 52.55269 45.88396 -1 -1 0 - 160 27 13 -0.834 62.89253 60.86549 46.75131 -2 -1 0 - 161 27 14 0.417 63.83924 60.74010 46.81653 -2 -1 0 - 162 27 14 0.417 62.51896 60.12788 47.23361 -2 -1 0 - 163 28 13 -0.834 43.29171 48.58106 31.82206 -1 0 2 - 164 28 14 0.417 43.07532 49.46362 32.12290 -1 0 2 - 165 28 14 0.417 43.82286 48.21072 32.52701 -1 0 2 - 166 29 13 -0.834 64.19867 44.17673 45.81391 -1 1 -1 - 167 29 14 0.417 63.72986 44.44010 45.02202 -1 1 -1 - 168 29 14 0.417 37.02069 43.24876 45.68087 0 1 -1 - 169 30 13 -0.834 50.42749 42.01163 53.60484 0 2 0 - 170 30 14 0.417 51.03177 41.90084 52.87081 0 2 0 - 171 30 14 0.417 50.77279 42.76181 54.08882 0 2 0 - 172 31 13 -0.834 38.63739 61.71113 49.95150 1 0 0 - 173 31 14 0.417 38.55432 62.15607 49.10808 1 0 0 - 174 31 14 0.417 37.81718 61.22751 50.04950 1 0 0 - 175 32 13 -0.834 61.47262 53.02922 33.08309 -1 -1 0 - 176 32 14 0.417 61.21894 52.67931 33.93717 -1 -1 0 - 177 32 14 0.417 61.89351 53.86564 33.28182 -1 -1 0 - 178 33 13 -0.834 54.44545 60.06011 48.63522 -1 0 1 - 179 33 14 0.417 54.80032 60.94424 48.72810 -1 0 1 - 180 33 14 0.417 54.09041 60.03614 47.74662 -1 0 1 - 181 34 13 -0.834 56.34364 60.90201 52.60838 -1 -1 0 - 182 34 14 0.417 56.48857 60.19161 53.23333 -1 -1 0 - 183 34 14 0.417 56.17362 61.67024 53.15351 -1 -1 0 - 184 35 13 -0.834 56.05881 51.84328 55.76103 -1 0 0 - 185 35 14 0.417 55.59060 51.75146 54.93121 -1 0 0 - 186 35 14 0.417 55.46974 52.35732 56.31335 -1 0 0 - 187 36 13 -0.834 39.00621 42.74743 30.97845 0 0 1 - 188 36 14 0.417 39.67620 42.11390 30.72152 0 0 1 - 189 36 14 0.417 39.43456 43.29673 31.63499 0 0 1 - 190 37 13 -0.834 46.77585 55.39774 30.24026 0 1 0 - 191 37 14 0.417 46.10274 54.90237 29.77360 0 1 0 - 192 37 14 0.417 46.39626 56.26890 30.35527 0 1 0 - 193 38 13 -0.834 45.10722 57.60431 31.54688 -1 0 0 - 194 38 14 0.417 44.80783 58.50032 31.70105 -1 0 0 - 195 38 14 0.417 44.44237 57.22463 30.97238 -1 0 0 - 196 39 13 -0.834 43.94230 46.99244 34.45668 -2 1 1 - 197 39 14 0.417 44.62010 46.49140 34.00306 -2 1 1 - 198 39 14 0.417 44.38150 47.79794 34.72964 -2 1 1 - 199 40 13 -0.834 51.39443 50.96507 34.69072 -1 1 0 - 200 40 14 0.417 51.18729 50.42829 35.45570 -1 1 0 - 201 40 14 0.417 51.33198 51.86665 35.00616 -1 1 0 - 202 41 13 -0.834 58.96398 48.19727 42.98856 -2 1 0 - 203 41 14 0.417 58.42587 48.90112 42.62618 -2 1 0 - 204 41 14 0.417 58.82383 48.25054 43.93397 -2 1 0 - 205 42 13 -0.834 62.89335 41.94260 37.40820 0 0 0 - 206 42 14 0.417 62.48690 41.07818 37.46980 0 0 0 - 207 42 14 0.417 63.01802 42.08284 36.46957 0 0 0 - 208 43 13 -0.834 54.19388 47.88689 36.24110 -1 0 1 - 209 43 14 0.417 54.32054 48.63090 35.65235 -1 0 1 - 210 43 14 0.417 53.24370 47.78935 36.30358 -1 0 1 - 211 44 13 -0.834 39.19734 57.40342 41.28495 0 0 -2 - 212 44 14 0.417 39.05428 57.72940 40.39641 0 0 -2 - 213 44 14 0.417 39.30846 56.45861 41.17895 0 0 -2 - 214 45 13 -0.834 52.85483 61.73749 54.63897 0 0 0 - 215 45 14 0.417 53.34938 62.52765 54.42147 0 0 0 - 216 45 14 0.417 53.01046 61.14656 53.90221 0 0 0 - 217 46 13 -0.834 47.09467 62.01384 35.02302 1 0 1 - 218 46 14 0.417 47.54527 61.47644 35.67448 1 0 1 - 219 46 14 0.417 47.10116 62.89626 35.39385 1 0 1 - 220 47 13 -0.834 46.80497 49.60334 37.05700 0 0 1 - 221 47 14 0.417 46.70216 49.79770 36.12540 0 0 1 - 222 47 14 0.417 45.91311 49.45393 37.37084 0 0 1 - 223 48 13 -0.834 63.21969 59.12311 54.43455 -1 -1 -1 - 224 48 14 0.417 63.94585 59.72833 54.28405 -1 -1 -1 - 225 48 14 0.417 63.63016 58.34481 54.81141 -1 -1 -1 - 226 49 13 -0.834 59.88416 59.64215 44.04914 -2 1 0 - 227 49 14 0.417 59.74255 59.14412 44.85422 -2 1 0 - 228 49 14 0.417 59.02635 60.01323 43.84248 -2 1 0 - 229 50 13 -0.834 40.50825 42.85328 50.81112 -1 1 0 - 230 50 14 0.417 40.34650 43.39801 51.58141 -1 1 0 - 231 50 14 0.417 39.63964 42.69867 50.43985 -1 1 0 - 232 51 13 -0.834 63.77522 64.97067 44.83010 -2 0 0 - 233 51 14 0.417 37.00507 65.56132 45.28388 -1 0 0 - 234 51 14 0.417 64.14243 64.88383 43.95041 -2 0 0 - 235 52 13 -0.834 62.47161 67.86189 47.38235 -1 0 -1 - 236 52 14 0.417 61.58819 67.64608 47.08360 -1 0 -1 - 237 52 14 0.417 62.79136 67.05596 47.78790 -1 0 -1 - 238 53 13 -0.834 43.90800 54.16107 50.35199 0 0 0 - 239 53 14 0.417 43.96769 53.24711 50.07388 0 0 0 - 240 53 14 0.417 43.72593 54.64554 49.54677 0 0 0 - 241 54 13 -0.834 63.46829 44.63390 34.73615 -1 1 1 - 242 54 14 0.417 62.63731 45.04623 34.97217 -1 1 1 - 243 54 14 0.417 64.11050 45.03645 35.32075 -1 1 1 - 244 55 13 -0.834 37.30679 58.22047 51.04345 0 0 0 - 245 55 14 0.417 38.18596 58.37862 50.69950 0 0 0 - 246 55 14 0.417 36.85723 59.06017 50.94824 0 0 0 - 247 56 13 -0.834 58.72649 42.45768 31.23820 -1 1 -1 - 248 56 14 0.417 59.43634 42.77561 30.68028 -1 1 -1 - 249 56 14 0.417 58.76581 41.50474 31.15690 -1 1 -1 - 250 57 13 -0.834 52.47101 42.85691 41.60986 0 1 -1 - 251 57 14 0.417 51.62289 42.91562 41.16997 0 1 -1 - 252 57 14 0.417 52.53109 41.94497 41.89448 0 1 -1 - 253 58 13 -0.834 60.63476 59.78356 56.53663 -2 -1 -1 - 254 58 14 0.417 60.87428 58.86269 56.43247 -2 -1 -1 - 255 58 14 0.417 59.72615 59.76269 56.83705 -2 -1 -1 - 256 59 13 -0.834 52.78127 57.47386 30.66786 -1 -1 0 - 257 59 14 0.417 52.55495 58.26092 30.17228 -1 -1 0 - 258 59 14 0.417 53.05203 56.84104 30.00267 -1 -1 0 - 259 60 13 -0.834 46.04848 57.65321 54.89998 0 3 -1 - 260 60 14 0.417 46.96883 57.71336 55.15607 0 3 -1 - 261 60 14 0.417 46.02768 57.98076 54.00081 0 3 -1 - 262 61 13 -0.834 60.39356 51.43705 35.66109 -1 1 -1 - 263 61 14 0.417 60.57739 52.08235 36.34376 -1 1 -1 - 264 61 14 0.417 59.59475 50.99860 35.95414 -1 1 -1 - 265 62 13 -0.834 50.32338 62.46972 35.65752 -1 0 2 - 266 62 14 0.417 51.24156 62.23287 35.52678 -1 0 2 - 267 62 14 0.417 49.89601 61.64851 35.90085 -1 0 2 - 268 63 13 -0.834 38.23983 45.11908 50.02773 0 1 0 - 269 63 14 0.417 38.61336 45.27494 50.89515 0 1 0 - 270 63 14 0.417 38.91224 45.42406 49.41856 0 1 0 - 271 64 13 -0.834 58.93720 57.36605 46.08362 -3 0 0 - 272 64 14 0.417 58.65753 56.63297 46.63190 -3 0 0 - 273 64 14 0.417 58.29914 58.05674 46.26268 -3 0 0 - 274 65 13 -0.834 47.99806 43.44789 47.43046 -1 0 0 - 275 65 14 0.417 48.39580 43.78289 46.62684 -1 0 0 - 276 65 14 0.417 47.85848 44.22523 47.97128 -1 0 0 - 277 66 13 -0.834 51.26744 52.05593 47.09995 -1 0 0 - 278 66 14 0.417 51.36736 52.09873 46.14894 -1 0 0 - 279 66 14 0.417 50.33779 52.22629 47.25149 -1 0 0 - 280 67 13 -0.834 39.06132 52.11517 46.39010 0 0 -1 - 281 67 14 0.417 38.53402 51.36282 46.65876 0 0 -1 - 282 67 14 0.417 39.47133 52.42190 47.19884 0 0 -1 - 283 68 13 -0.834 60.17907 58.95174 50.22759 -1 1 0 - 284 68 14 0.417 60.34080 59.56538 50.94420 -1 1 0 - 285 68 14 0.417 59.41497 58.44908 50.50992 -1 1 0 - 286 69 13 -0.834 40.47698 59.65154 34.92537 0 -1 1 - 287 69 14 0.417 40.89044 60.49055 35.12877 0 -1 1 - 288 69 14 0.417 41.17964 59.12336 34.54648 0 -1 1 - 289 70 13 -0.834 60.12998 66.51474 47.03971 -1 0 -1 - 290 70 14 0.417 59.26620 66.39701 47.43506 -1 0 -1 - 291 70 14 0.417 60.21358 65.78625 46.42443 -1 0 -1 - 292 71 13 -0.834 49.25986 47.27506 43.03372 -1 0 1 - 293 71 14 0.417 49.11810 48.15331 42.68041 -1 0 1 - 294 71 14 0.417 49.86162 47.40550 43.76662 -1 0 1 - 295 72 13 -0.834 41.48105 63.65699 31.84433 0 0 1 - 296 72 14 0.417 41.11022 64.48589 32.14713 0 0 1 - 297 72 14 0.417 40.89461 63.37379 31.14281 0 0 1 - 298 73 13 -0.834 47.82875 47.97039 54.56720 0 2 0 - 299 73 14 0.417 46.99167 47.50633 54.55352 0 2 0 - 300 73 14 0.417 47.60488 48.87558 54.35102 0 2 0 - 301 74 13 -0.834 62.36735 58.64445 48.35778 -2 1 0 - 302 74 14 0.417 62.88767 57.90867 48.68045 -2 1 0 - 303 74 14 0.417 61.65918 58.73544 48.99531 -2 1 0 - 304 75 13 -0.834 52.09508 65.08907 32.87560 0 0 0 - 305 75 14 0.417 52.67402 65.75058 32.49683 0 0 0 - 306 75 14 0.417 52.41855 64.97003 33.76859 0 0 0 - 307 76 13 -0.834 39.06932 41.62988 40.69498 1 1 0 - 308 76 14 0.417 39.51114 41.04433 40.08003 1 1 0 - 309 76 14 0.417 38.93584 42.43936 40.20186 1 1 0 - 310 77 13 -0.834 37.68325 49.50718 46.00750 0 2 0 - 311 77 14 0.417 64.11601 49.67107 45.91568 -1 2 0 - 312 77 14 0.417 37.90845 48.96991 45.24796 0 2 0 - 313 78 13 -0.834 53.00757 59.49351 52.98404 -2 1 -1 - 314 78 14 0.417 52.16721 59.28329 53.39127 -2 1 -1 - 315 78 14 0.417 53.61000 58.83023 53.32076 -2 1 -1 - 316 79 13 -0.834 51.89369 64.75001 56.68467 1 0 0 - 317 79 14 0.417 51.88079 65.63682 56.32462 1 0 0 - 318 79 14 0.417 52.40589 64.82531 30.11841 1 0 1 - 319 80 13 -0.834 48.43261 63.10155 32.63566 0 0 1 - 320 80 14 0.417 47.68021 63.01753 32.04993 0 0 1 - 321 80 14 0.417 48.13916 62.71424 33.46035 0 0 1 - 322 81 13 -0.834 62.41171 68.18251 30.67168 0 -1 2 - 323 81 14 0.417 61.79235 41.16145 30.03143 0 0 2 - 324 81 14 0.417 63.18314 67.94790 30.15584 0 -1 2 - 325 82 13 -0.834 42.57575 41.32197 37.66791 0 0 1 - 326 82 14 0.417 42.98116 41.36016 36.80164 0 0 1 - 327 82 14 0.417 42.32522 42.22654 37.85569 0 0 1 - 328 83 13 -0.834 50.17315 67.44398 36.91606 0 -2 0 - 329 83 14 0.417 50.08765 67.03449 37.77701 0 -2 0 - 330 83 14 0.417 50.35347 66.71621 36.32101 0 -2 0 - 331 84 13 -0.834 39.70163 60.45247 40.03790 0 -2 -1 - 332 84 14 0.417 38.85282 60.01540 40.10676 0 -2 -1 - 333 84 14 0.417 40.20579 60.11563 40.77858 0 -2 -1 - 334 85 13 -0.834 51.74323 42.80814 51.33239 0 0 -1 - 335 85 14 0.417 52.44810 43.22892 51.82466 0 0 -1 - 336 85 14 0.417 51.80961 43.17998 50.45286 0 0 -1 - 337 86 13 -0.834 51.34695 47.68316 36.38089 0 0 1 - 338 86 14 0.417 50.77701 46.92707 36.52138 0 0 1 - 339 86 14 0.417 51.27109 47.87031 35.44523 0 0 1 - 340 87 13 -0.834 62.66950 50.66085 43.15883 -2 0 0 - 341 87 14 0.417 63.57796 50.36318 43.11051 -2 0 0 - 342 87 14 0.417 62.24654 50.26548 42.39659 -2 0 0 - 343 88 13 -0.834 46.37996 60.13914 31.06428 -2 -1 1 - 344 88 14 0.417 46.89125 59.89673 31.83632 -2 -1 1 - 345 88 14 0.417 45.51811 60.37092 31.41028 -2 -1 1 - 346 89 13 -0.834 50.23251 41.17559 46.18435 0 1 2 - 347 89 14 0.417 49.40509 68.16142 45.89628 0 0 2 - 348 89 14 0.417 50.55747 67.94506 46.85395 0 0 2 - 349 90 13 -0.834 56.10446 66.70018 42.60390 0 -2 1 - 350 90 14 0.417 56.27454 67.42915 42.00732 0 -2 1 - 351 90 14 0.417 56.27819 67.05729 43.47483 0 -2 1 - 352 91 13 -0.834 55.53824 48.43866 51.97225 -1 0 1 - 353 91 14 0.417 56.26440 48.96682 52.30388 -1 0 1 - 354 91 14 0.417 55.26306 48.88494 51.17140 -1 0 1 - 355 92 13 -0.834 37.88016 52.62502 33.55552 0 -1 0 - 356 92 14 0.417 37.58757 51.72397 33.41859 0 -1 0 - 357 92 14 0.417 38.51960 52.77804 32.85986 0 -1 0 - 358 93 13 -0.834 50.40592 66.14455 39.40035 -1 -2 -1 - 359 93 14 0.417 49.74974 66.37168 40.05920 -1 -2 -1 - 360 93 14 0.417 50.22642 65.22843 39.18876 -1 -2 -1 - 361 94 13 -0.834 59.56315 43.63477 50.02876 -1 0 0 - 362 94 14 0.417 60.08533 44.36640 50.35782 -1 0 0 - 363 94 14 0.417 60.10101 42.86112 50.19730 -1 0 0 - 364 95 13 -0.834 57.16125 61.75981 55.17964 0 0 -1 - 365 95 14 0.417 56.45534 61.68609 55.82189 0 0 -1 - 366 95 14 0.417 57.38335 62.69087 55.17297 0 0 -1 - 367 96 13 -0.834 54.81274 43.48714 43.13392 -1 2 1 - 368 96 14 0.417 53.88771 43.40698 42.90124 -1 2 1 - 369 96 14 0.417 54.97915 42.74512 43.71525 -1 2 1 - 370 97 13 -0.834 41.23040 49.49766 49.75568 0 -2 0 - 371 97 14 0.417 40.54278 49.43865 49.09241 0 -2 0 - 372 97 14 0.417 41.81904 48.76959 49.55653 0 -2 0 - 373 98 13 -0.834 54.20957 45.39084 54.97428 -1 0 0 - 374 98 14 0.417 54.66721 46.06623 55.47493 -1 0 0 - 375 98 14 0.417 53.74016 44.87996 55.63374 -1 0 0 - 376 99 13 -0.834 61.27515 64.38553 39.98716 -1 0 1 - 377 99 14 0.417 61.56153 64.23410 40.88787 -1 0 1 - 378 99 14 0.417 60.44736 63.91029 39.91542 -1 0 1 - 379 100 13 -0.834 55.67284 58.14856 42.21767 -1 1 2 - 380 100 14 0.417 55.46369 57.24253 42.44485 -1 1 2 - 381 100 14 0.417 56.62771 58.19397 42.26677 -1 1 2 - 382 101 13 -0.834 43.66528 51.07118 53.71174 0 0 0 - 383 101 14 0.417 42.87715 50.89079 53.19934 0 0 0 - 384 101 14 0.417 43.37793 51.68815 54.38481 0 0 0 - 385 102 13 -0.834 39.90899 44.53973 36.42818 0 2 0 - 386 102 14 0.417 39.84006 43.65427 36.07118 0 2 0 - 387 102 14 0.417 40.52179 44.98683 35.84438 0 2 0 - 388 103 13 -0.834 51.24695 66.96031 48.71611 -1 -1 1 - 389 103 14 0.417 50.88275 67.26607 49.54684 -1 -1 1 - 390 103 14 0.417 52.19366 66.95318 48.85726 -1 -1 1 - 391 104 13 -0.834 55.15911 56.17347 57.08906 -1 0 0 - 392 104 14 0.417 55.86241 55.65189 56.70232 -1 0 0 - 393 104 14 0.417 54.93977 55.71619 30.52949 -1 0 1 - 394 105 13 -0.834 37.33282 54.30424 56.96734 0 0 0 - 395 105 14 0.417 64.15558 54.97773 29.99806 -1 0 1 - 396 105 14 0.417 64.13467 53.88397 56.32293 -1 0 0 - 397 106 13 -0.834 53.07827 51.20543 32.31512 -1 0 1 - 398 106 14 0.417 52.39494 50.78813 31.79057 -1 0 1 - 399 106 14 0.417 52.65819 51.38698 33.15584 -1 0 1 - 400 107 13 -0.834 43.06086 51.65229 35.75926 1 1 1 - 401 107 14 0.417 42.70958 52.01746 36.57135 1 1 1 - 402 107 14 0.417 43.42908 50.80682 36.01586 1 1 1 - 403 108 13 -0.834 53.92253 56.24460 34.48089 0 0 1 - 404 108 14 0.417 53.22007 56.39276 35.11401 0 0 1 - 405 108 14 0.417 54.59075 55.76600 34.97147 0 0 1 - 406 109 13 -0.834 61.71524 66.84153 38.60005 -1 -1 0 - 407 109 14 0.417 61.25397 66.04877 38.87388 -1 -1 0 - 408 109 14 0.417 62.23260 67.09437 39.36467 -1 -1 0 - 409 110 13 -0.834 43.52824 62.78695 41.49939 0 -1 -1 - 410 110 14 0.417 43.61050 61.97218 41.00379 0 -1 -1 - 411 110 14 0.417 43.53140 63.47437 40.83330 0 -1 -1 - 412 111 13 -0.834 51.13822 55.54090 53.50461 0 1 -2 - 413 111 14 0.417 50.69587 56.38179 53.62064 0 1 -2 - 414 111 14 0.417 51.43262 55.54828 52.59383 0 1 -2 - 415 112 13 -0.834 46.94709 50.11761 31.92599 0 0 0 - 416 112 14 0.417 47.19652 51.02564 31.75423 0 0 0 - 417 112 14 0.417 46.57462 49.81059 31.09941 0 0 0 - 418 113 13 -0.834 47.96666 45.13049 44.46108 -1 2 -1 - 419 113 14 0.417 47.01871 45.24108 44.53489 -1 2 -1 - 420 113 14 0.417 48.26343 45.91034 43.99202 -1 2 -1 - 421 114 13 -0.834 44.43868 43.44849 32.90814 -1 -1 1 - 422 114 14 0.417 43.86055 43.24165 33.64245 -1 -1 1 - 423 114 14 0.417 45.31670 43.24154 33.22828 -1 -1 1 - 424 115 13 -0.834 61.07172 47.80130 53.14504 -1 1 -1 - 425 115 14 0.417 61.34864 48.71600 53.19864 -1 1 -1 - 426 115 14 0.417 60.72118 47.60538 54.01394 -1 1 -1 - 427 116 13 -0.834 51.38727 44.10864 54.92855 -1 0 -1 - 428 116 14 0.417 50.77962 44.80360 55.18160 -1 0 -1 - 429 116 14 0.417 52.05111 44.10744 55.61815 -1 0 -1 - 430 117 13 -0.834 41.05585 60.12319 49.44785 1 -1 0 - 431 117 14 0.417 41.72702 60.76812 49.67116 1 -1 0 - 432 117 14 0.417 40.24373 60.62784 49.40265 1 -1 0 - 433 118 13 -0.834 50.88548 68.33364 33.37284 -1 0 -1 - 434 118 14 0.417 50.48275 67.46671 33.32310 -1 0 -1 - 435 118 14 0.417 51.82702 68.16119 33.37343 -1 0 -1 - 436 119 13 -0.834 38.79644 59.29061 55.22446 1 1 -1 - 437 119 14 0.417 38.82887 59.83550 56.01077 1 1 -1 - 438 119 14 0.417 39.26097 59.79985 54.56028 1 1 -1 - 439 120 13 -0.834 56.31813 41.68729 51.11871 -2 0 -1 - 440 120 14 0.417 55.45155 41.35580 51.35412 -2 0 -1 - 441 120 14 0.417 56.14879 42.34135 50.44062 -2 0 -1 - 442 121 13 -0.834 45.53697 59.28154 47.22033 -1 0 -1 - 443 121 14 0.417 45.45062 59.55577 46.30733 -1 0 -1 - 444 121 14 0.417 46.00774 59.99977 47.64313 -1 0 -1 - 445 122 13 -0.834 60.47636 43.28130 46.20944 -1 0 -1 - 446 122 14 0.417 60.97762 42.59184 45.77396 -1 0 -1 - 447 122 14 0.417 59.72992 42.82584 46.59884 -1 0 -1 - 448 123 13 -0.834 58.49080 48.18289 45.77215 0 0 -1 - 449 123 14 0.417 58.74342 47.25991 45.74879 0 0 -1 - 450 123 14 0.417 58.17926 48.32386 46.66621 0 0 -1 - 451 124 13 -0.834 50.93473 56.12663 41.58575 -1 0 0 - 452 124 14 0.417 50.36171 56.05214 42.34885 -1 0 0 - 453 124 14 0.417 50.40135 56.57242 40.92771 -1 0 0 - 454 125 13 -0.834 60.55008 41.95542 56.22749 -1 0 -1 - 455 125 14 0.417 59.65163 41.78987 55.94175 -1 0 -1 - 456 125 14 0.417 61.09463 41.59967 55.52524 -1 0 -1 - 457 126 13 -0.834 58.58373 51.69338 48.78985 -1 1 0 - 458 126 14 0.417 58.38773 52.01803 49.66874 -1 1 0 - 459 126 14 0.417 58.66973 50.74614 48.89756 -1 1 0 - 460 127 13 -0.834 37.82769 45.69808 30.85100 0 1 3 - 461 127 14 0.417 38.37007 45.10637 31.37248 0 1 3 - 462 127 14 0.417 37.14646 45.99401 31.45481 0 1 3 - 463 128 13 -0.834 50.96455 60.06361 33.68049 0 0 0 - 464 128 14 0.417 51.72055 60.15430 34.26055 0 0 0 - 465 128 14 0.417 51.05673 60.77997 33.05234 0 0 0 - 466 129 13 -0.834 46.43413 68.11245 51.48833 -1 0 -1 - 467 129 14 0.417 46.82151 41.36005 50.86943 -1 1 -1 - 468 129 14 0.417 47.09847 67.43153 51.59433 -1 0 -1 - 469 130 13 -0.834 61.79997 47.41648 57.05141 -1 -1 0 - 470 130 14 0.417 62.68713 47.23872 56.73898 -1 -1 0 - 471 130 14 0.417 61.48917 46.57417 30.01195 -1 -1 1 - 472 131 13 -0.834 45.30689 46.58119 54.43763 0 1 -1 - 473 131 14 0.417 45.67282 45.73922 54.70859 0 1 -1 - 474 131 14 0.417 44.46622 46.35973 54.03705 0 1 -1 - 475 132 13 -0.834 62.60829 48.56385 49.02640 -1 1 0 - 476 132 14 0.417 62.44761 48.65968 48.08766 -1 1 0 - 477 132 14 0.417 62.98242 47.68753 49.11762 -1 1 0 - 478 133 13 -0.834 63.49107 56.77075 38.74961 -1 0 2 - 479 133 14 0.417 63.12281 56.39554 39.54952 -1 0 2 - 480 133 14 0.417 62.84612 57.42058 38.47033 -1 0 2 - 481 134 13 -0.834 50.74846 48.34849 33.46075 0 0 1 - 482 134 14 0.417 50.75342 49.30521 33.43086 0 0 1 - 483 134 14 0.417 50.91203 48.07929 32.55686 0 0 1 - 484 135 13 -0.834 44.40923 67.37148 56.42156 0 0 0 - 485 135 14 0.417 43.93400 67.78902 29.76856 0 0 1 - 486 135 14 0.417 44.94884 66.70468 56.84633 0 0 0 - 487 136 13 -0.834 44.25343 64.95349 43.22104 0 0 0 - 488 136 14 0.417 44.13229 64.08173 42.84472 0 0 0 - 489 136 14 0.417 44.01188 65.55470 42.51643 0 0 0 - 490 137 13 -0.834 46.68300 67.52863 32.69859 -1 -1 0 - 491 137 14 0.417 46.68369 68.22637 33.35389 -1 -1 0 - 492 137 14 0.417 47.60248 67.43099 32.45106 -1 -1 0 - 493 138 13 -0.834 57.25376 61.01737 33.86507 -2 1 1 - 494 138 14 0.417 57.40827 60.52366 34.67043 -2 1 1 - 495 138 14 0.417 57.35792 60.37307 33.16488 -2 1 1 - 496 139 13 -0.834 57.39946 54.16835 56.70699 0 -1 -1 - 497 139 14 0.417 57.31939 53.23092 56.53080 0 -1 -1 - 498 139 14 0.417 57.32300 54.24112 30.28699 0 -1 0 - 499 140 13 -0.834 52.36697 48.69246 41.49227 -1 1 0 - 500 140 14 0.417 51.78735 47.93629 41.40021 -1 1 0 - 501 140 14 0.417 53.21603 48.31702 41.72547 -1 1 0 - 502 141 13 -0.834 54.69200 49.57915 45.55048 0 0 -1 - 503 141 14 0.417 54.95958 48.66911 45.42211 0 0 -1 - 504 141 14 0.417 55.28513 50.08439 44.99446 0 0 -1 - 505 142 13 -0.834 37.26724 53.17896 42.50469 1 -1 -1 - 506 142 14 0.417 63.93194 53.34801 43.12782 0 -1 -1 - 507 142 14 0.417 36.94831 52.45044 41.97199 1 -1 -1 - 508 143 13 -0.834 42.56283 66.92379 33.49577 -1 0 1 - 509 143 14 0.417 41.71356 66.58931 33.20750 -1 0 1 - 510 143 14 0.417 43.03645 66.14842 33.79697 -1 0 1 - 511 144 13 -0.834 61.43331 45.62855 38.97695 0 1 1 - 512 144 14 0.417 61.20190 45.98514 39.83458 0 1 1 - 513 144 14 0.417 62.31351 45.96414 38.80708 0 1 1 - 514 145 13 -0.834 49.37935 56.26031 56.72879 1 1 0 - 515 145 14 0.417 49.03977 57.11146 56.45221 1 1 0 - 516 145 14 0.417 48.60052 55.75658 56.96530 1 1 0 - 517 146 13 -0.834 63.13959 56.23999 49.92079 -1 0 -1 - 518 146 14 0.417 63.72474 55.58123 50.29478 -1 0 -1 - 519 146 14 0.417 63.40966 57.06154 50.33112 -1 0 -1 - 520 147 13 -0.834 58.55937 66.56287 54.17345 -1 0 0 - 521 147 14 0.417 59.28260 66.81524 53.59945 -1 0 0 - 522 147 14 0.417 58.28559 67.38088 54.58834 -1 0 0 - 523 148 13 -0.834 55.49901 62.14366 46.01274 -1 0 -1 - 524 148 14 0.417 55.08057 61.57956 45.36238 -1 0 -1 - 525 148 14 0.417 55.53371 63.00495 45.59652 -1 0 -1 - 526 149 13 -0.834 48.09589 47.38106 38.97384 0 1 0 - 527 149 14 0.417 47.94178 48.02346 38.28116 0 1 0 - 528 149 14 0.417 47.26125 47.32494 39.43910 0 1 0 - 529 150 13 -0.834 40.27661 53.03711 48.83757 0 0 0 - 530 150 14 0.417 40.32476 53.91333 49.21992 0 0 0 - 531 150 14 0.417 41.18363 52.81848 48.62365 0 0 0 - 532 151 13 -0.834 36.85277 41.68065 44.81488 1 2 0 - 533 151 14 0.417 36.95709 68.34807 45.45504 1 1 0 - 534 151 14 0.417 37.14062 41.29651 43.98673 1 2 0 - 535 152 13 -0.834 37.74881 65.81650 33.58759 -1 0 1 - 536 152 14 0.417 37.69052 65.99217 34.52673 -1 0 1 - 537 152 14 0.417 37.02193 65.21970 33.40951 -1 0 1 - 538 153 13 -0.834 63.01838 46.13766 43.99274 -2 0 0 - 539 153 14 0.417 62.72780 46.33504 43.10232 -2 0 0 - 540 153 14 0.417 63.75125 46.73459 44.14387 -2 0 0 - 541 154 13 -0.834 43.83288 53.92104 38.64974 0 2 1 - 542 154 14 0.417 44.46072 53.30394 39.02556 0 2 1 - 543 154 14 0.417 44.17373 54.10726 37.77488 0 2 1 - 544 155 13 -0.834 54.48021 41.30441 45.39416 1 1 -2 - 545 155 14 0.417 54.42996 67.86451 44.88861 1 0 -2 - 546 155 14 0.417 54.84291 41.03852 46.23914 1 1 -2 - 547 156 13 -0.834 51.26407 63.10699 50.73012 0 0 -2 - 548 156 14 0.417 51.64016 62.23294 50.83411 0 0 -2 - 549 156 14 0.417 51.56733 63.39797 49.87011 0 0 -2 - 550 157 13 -0.834 54.61161 63.67709 53.56970 0 1 1 - 551 157 14 0.417 55.55339 63.81655 53.47054 0 1 1 - 552 157 14 0.417 54.24805 63.87070 52.70565 0 1 1 - 553 158 13 -0.834 46.57444 42.69363 30.13287 -1 0 1 - 554 158 14 0.417 45.93025 42.28051 30.70783 -1 0 1 - 555 158 14 0.417 47.27305 42.04459 30.04973 -1 0 1 - 556 159 13 -0.834 37.92811 50.36816 42.31352 1 1 0 - 557 159 14 0.417 38.62401 50.90050 42.69899 1 1 0 - 558 159 14 0.417 38.11553 50.37135 41.37484 1 1 0 - 559 160 13 -0.834 40.53318 48.69302 33.52502 -1 0 0 - 560 160 14 0.417 40.10720 48.55075 32.67972 -1 0 0 - 561 160 14 0.417 41.22323 49.33057 33.34173 -1 0 0 - 562 161 13 -0.834 58.20095 45.48345 42.83426 1 0 -1 - 563 161 14 0.417 58.76156 46.25356 42.92849 1 0 -1 - 564 161 14 0.417 58.80813 44.74348 42.83158 1 0 -1 - 565 162 13 -0.834 59.85909 67.06752 31.43173 -1 1 0 - 566 162 14 0.417 59.95062 66.12180 31.54782 -1 1 0 - 567 162 14 0.417 60.75672 67.38534 31.33437 -1 1 0 - 568 163 13 -0.834 48.48808 51.17807 55.92072 -2 0 0 - 569 163 14 0.417 49.24951 51.62602 55.55219 -2 0 0 - 570 163 14 0.417 48.81105 50.30745 56.15303 -2 0 0 - 571 164 13 -0.834 47.51169 45.69616 48.99410 0 0 -1 - 572 164 14 0.417 48.36822 46.03425 48.73281 0 0 -1 - 573 164 14 0.417 47.56201 45.62598 49.94740 0 0 -1 - 574 165 13 -0.834 51.10678 64.23082 47.99167 0 -2 -1 - 575 165 14 0.417 51.33188 65.16116 47.98611 0 -2 -1 - 576 165 14 0.417 50.15837 64.21415 48.12002 0 -2 -1 - 577 166 13 -0.834 42.97263 56.29674 30.18230 0 0 0 - 578 166 14 0.417 42.45756 55.50818 30.01170 0 0 0 - 579 166 14 0.417 42.79675 56.86516 56.80386 0 0 -1 - 580 167 13 -0.834 44.45917 53.64338 31.85015 -1 0 0 - 581 167 14 0.417 44.64093 54.17218 31.07325 -1 0 0 - 582 167 14 0.417 43.66299 53.15965 31.63030 -1 0 0 - 583 168 13 -0.834 52.20677 49.92062 48.65330 1 0 0 - 584 168 14 0.417 52.24176 50.63538 49.28902 1 0 0 - 585 168 14 0.417 52.01918 50.35058 47.81890 1 0 0 - 586 169 13 -0.834 45.94013 51.43638 56.49888 0 0 0 - 587 169 14 0.417 46.89200 51.34153 56.53372 0 0 0 - 588 169 14 0.417 45.60504 50.66051 56.94833 0 0 0 - 589 170 13 -0.834 45.61845 41.38709 48.05698 1 0 0 - 590 170 14 0.417 46.42604 41.83441 47.80406 1 0 0 - 591 170 14 0.417 45.31743 41.85685 48.83477 1 0 0 - 592 171 13 -0.834 47.68232 42.84819 52.92728 0 1 0 - 593 171 14 0.417 47.61830 42.41414 52.07654 0 1 0 - 594 171 14 0.417 48.39202 42.39011 53.37758 0 1 0 - 595 172 13 -0.834 37.01774 65.84057 36.39542 1 -1 0 - 596 172 14 0.417 36.84918 65.13561 37.02061 1 -1 0 - 597 172 14 0.417 63.52368 66.19949 36.19938 0 -1 0 - 598 173 13 -0.834 51.52891 58.65207 39.31760 -1 -3 -1 - 599 173 14 0.417 51.57384 59.35596 39.96472 -1 -3 -1 - 600 173 14 0.417 51.00435 59.01522 38.60403 -1 -3 -1 - 601 174 13 -0.834 49.06578 54.25781 44.33488 0 -1 -1 - 602 174 14 0.417 48.81980 55.18018 44.26437 0 -1 -1 - 603 174 14 0.417 49.41695 54.17018 45.22104 0 -1 -1 - 604 175 13 -0.834 47.03819 42.38557 34.31948 -1 -1 0 - 605 175 14 0.417 47.39035 41.82883 35.01393 -1 -1 0 - 606 175 14 0.417 47.47024 43.23019 34.44673 -1 -1 0 - 607 176 13 -0.834 41.64025 43.65472 38.33192 0 1 0 - 608 176 14 0.417 41.17224 44.02383 37.58295 0 1 0 - 609 176 14 0.417 41.46027 44.26142 39.05008 0 1 0 - 610 177 13 -0.834 61.41261 58.14241 37.49312 -2 0 0 - 611 177 14 0.417 61.24368 59.06676 37.67551 -2 0 0 - 612 177 14 0.417 60.57871 57.80631 37.16465 -2 0 0 - 613 178 13 -0.834 48.58355 55.60536 32.34542 0 -2 -2 - 614 178 14 0.417 48.05292 55.64371 31.54969 0 -2 -2 - 615 178 14 0.417 49.00004 56.46561 32.39784 0 -2 -2 - 616 179 13 -0.834 51.18618 52.33768 44.26866 0 -1 0 - 617 179 14 0.417 50.47419 52.97535 44.21659 0 -1 0 - 618 179 14 0.417 51.18053 51.90159 43.41657 0 -1 0 - 619 180 13 -0.834 63.77008 46.64985 53.45124 -2 0 -1 - 620 180 14 0.417 37.25943 46.94040 53.14955 -1 0 -1 - 621 180 14 0.417 63.15834 47.28506 53.07904 -2 0 -1 - 622 181 13 -0.834 37.28071 56.79400 31.30862 1 1 0 - 623 181 14 0.417 37.34297 57.68998 31.63963 1 1 0 - 624 181 14 0.417 36.99543 56.89301 30.40030 1 1 0 - 625 182 13 -0.834 38.98742 57.66608 44.07685 1 0 1 - 626 182 14 0.417 39.04152 57.61214 43.12270 1 0 1 - 627 182 14 0.417 39.46043 56.89430 44.38805 1 0 1 - 628 183 13 -0.834 64.13749 51.25767 48.28997 0 -1 0 - 629 183 14 0.417 64.05120 52.19840 48.13566 0 -1 0 - 630 183 14 0.417 63.26932 50.90255 48.09918 0 -1 0 - 631 184 13 -0.834 41.02949 42.14202 43.02064 0 0 -1 - 632 184 14 0.417 40.60130 42.82178 43.54104 0 0 -1 - 633 184 14 0.417 40.43829 41.99723 42.28189 0 0 -1 - 634 185 13 -0.834 49.87332 48.21836 52.83028 0 1 0 - 635 185 14 0.417 49.13733 48.15035 53.43849 0 1 0 - 636 185 14 0.417 50.32176 47.37567 52.90100 0 1 0 - 637 186 13 -0.834 56.06860 48.51217 38.12813 -1 1 0 - 638 186 14 0.417 56.55702 47.73454 38.39826 -1 1 0 - 639 186 14 0.417 55.52690 48.21357 37.39762 -1 1 0 - 640 187 13 -0.834 54.22718 59.47740 40.22374 -1 0 1 - 641 187 14 0.417 53.93839 59.03820 39.42377 -1 0 1 - 642 187 14 0.417 54.74005 58.81629 40.68868 -1 0 1 - 643 188 13 -0.834 60.09461 46.88146 32.04739 -1 0 -1 - 644 188 14 0.417 60.91535 46.43611 31.83683 -1 0 -1 - 645 188 14 0.417 60.13630 47.02716 32.99253 -1 0 -1 - 646 189 13 -0.834 45.18646 44.57845 41.54076 0 0 0 - 647 189 14 0.417 44.28239 44.89208 41.51774 0 0 0 - 648 189 14 0.417 45.34481 44.23786 40.66033 0 0 0 - 649 190 13 -0.834 42.47099 45.68692 31.56356 1 0 1 - 650 190 14 0.417 43.26152 45.18821 31.76995 1 0 1 - 651 190 14 0.417 42.78187 46.58070 31.41951 1 0 1 - 652 191 13 -0.834 41.23413 47.67043 41.85221 0 1 0 - 653 191 14 0.417 41.04508 48.58329 42.06946 0 1 0 - 654 191 14 0.417 40.84394 47.54379 40.98737 0 1 0 - 655 192 13 -0.834 48.84750 60.39708 36.57115 0 0 0 - 656 192 14 0.417 48.57626 59.48478 36.46920 0 0 0 - 657 192 14 0.417 48.59448 60.62409 37.46597 0 0 0 - 658 193 13 -0.834 56.78263 43.55464 49.12966 -1 0 -1 - 659 193 14 0.417 56.56851 44.25428 48.51250 -1 0 -1 - 660 193 14 0.417 57.66563 43.76469 49.43365 -1 0 -1 - 661 194 13 -0.834 59.52236 53.66894 43.24587 -1 2 0 - 662 194 14 0.417 59.44365 54.61174 43.10041 -1 2 0 - 663 194 14 0.417 59.73284 53.58637 44.17598 -1 2 0 - 664 195 13 -0.834 63.61393 61.54696 40.57053 -1 -1 1 - 665 195 14 0.417 36.90989 60.94398 40.24291 0 -1 1 - 666 195 14 0.417 63.74510 61.55794 41.51864 -1 -1 1 - 667 196 13 -0.834 54.91742 43.16160 33.69639 0 0 -1 - 668 196 14 0.417 55.84062 43.16106 33.94925 0 0 -1 - 669 196 14 0.417 54.73416 44.07060 33.45898 0 0 -1 - 670 197 13 -0.834 41.09699 64.92982 48.38401 0 -1 -1 - 671 197 14 0.417 40.19042 64.83711 48.67687 0 -1 -1 - 672 197 14 0.417 41.27055 64.13206 47.88433 0 -1 -1 - 673 198 13 -0.834 49.09688 60.43369 49.80048 0 0 -1 - 674 198 14 0.417 49.75346 61.03633 50.14971 0 0 -1 - 675 198 14 0.417 49.51718 59.57440 49.83534 0 0 -1 - 676 199 13 -0.834 45.06873 45.25146 44.50830 0 1 0 - 677 199 14 0.417 45.08807 45.11881 43.56053 0 1 0 - 678 199 14 0.417 44.41198 44.63084 44.82413 0 1 0 - 679 200 13 -0.834 37.63886 45.88962 36.45768 0 0 2 - 680 200 14 0.417 38.32892 45.23766 36.58017 0 0 2 - 681 200 14 0.417 37.24627 45.98938 37.32495 0 0 2 - 682 201 13 -0.834 45.25770 47.01692 51.04211 -1 0 -2 - 683 201 14 0.417 45.49830 47.82868 50.59555 -1 0 -2 - 684 201 14 0.417 46.08295 46.68269 51.39354 -1 0 -2 - 685 202 13 -0.834 63.44567 60.77839 50.98507 -2 0 0 - 686 202 14 0.417 62.95029 60.46072 51.74001 -2 0 0 - 687 202 14 0.417 62.77774 61.08133 50.36998 -2 0 0 - 688 203 13 -0.834 48.00038 59.99003 33.31045 0 1 1 - 689 203 14 0.417 48.92391 59.89924 33.54518 0 1 1 - 690 203 14 0.417 47.68314 60.70831 33.85788 0 1 1 - 691 204 13 -0.834 51.29617 53.45952 36.10138 -1 -1 1 - 692 204 14 0.417 50.79623 53.20605 36.87731 -1 -1 1 - 693 204 14 0.417 51.41983 54.40421 36.19363 -1 -1 1 - 694 205 13 -0.834 48.55343 45.13540 34.47517 0 0 0 - 695 205 14 0.417 48.10547 45.97105 34.34382 0 0 0 - 696 205 14 0.417 49.13373 45.28879 35.22081 0 0 0 - 697 206 13 -0.834 48.34844 61.02741 54.77908 1 -1 -1 - 698 206 14 0.417 47.77364 61.75290 55.02301 1 -1 -1 - 699 206 14 0.417 49.14675 61.17253 55.28690 1 -1 -1 - 700 207 13 -0.834 38.97661 48.73541 31.27301 2 -1 0 - 701 207 14 0.417 38.86774 47.99634 30.67453 2 -1 0 - 702 207 14 0.417 38.60214 49.48112 30.80404 2 -1 0 - 703 208 13 -0.834 56.37687 61.69299 40.12439 0 -1 -1 - 704 208 14 0.417 56.35009 61.71409 39.16778 0 -1 -1 - 705 208 14 0.417 55.62486 61.15580 40.37371 0 -1 -1 - 706 209 13 -0.834 47.86700 41.38854 36.76722 -1 0 0 - 707 209 14 0.417 48.79854 41.26117 36.94678 -1 0 0 - 708 209 14 0.417 47.57553 42.00602 37.43804 -1 0 0 - 709 210 13 -0.834 43.22089 60.92576 39.48904 -1 -1 0 - 710 210 14 0.417 42.70029 60.20976 39.85311 -1 -1 0 - 711 210 14 0.417 43.25319 60.74538 38.54954 -1 -1 0 - 712 211 13 -0.834 56.26248 49.03317 34.29585 -1 0 0 - 713 211 14 0.417 56.69244 49.86416 34.09381 -1 0 0 - 714 211 14 0.417 55.61194 48.92467 33.60212 -1 0 0 - 715 212 13 -0.834 47.52063 49.37901 51.21673 1 0 0 - 716 212 14 0.417 48.35964 48.95385 51.03909 1 0 0 - 717 212 14 0.417 47.47856 49.43746 52.17122 1 0 0 - 718 213 13 -0.834 62.35532 56.31018 41.33556 0 0 0 - 719 213 14 0.417 62.07506 57.22150 41.42032 0 0 0 - 720 213 14 0.417 62.92184 56.16192 42.09274 0 0 0 - 721 214 13 -0.834 61.09797 64.53756 45.11003 -1 0 1 - 722 214 14 0.417 61.11801 63.59600 44.93887 -1 0 1 - 723 214 14 0.417 61.95676 64.85132 44.82670 -1 0 1 - 724 215 13 -0.834 51.22661 62.08872 31.93454 0 0 0 - 725 215 14 0.417 51.98994 62.65586 32.04369 0 0 0 - 726 215 14 0.417 50.47877 62.65171 32.13456 0 0 0 - 727 216 13 -0.834 40.65443 48.64853 54.43476 0 0 -1 - 728 216 14 0.417 40.25608 47.97845 54.99023 0 0 -1 - 729 216 14 0.417 41.58025 48.64240 54.67776 0 0 -1 - 730 217 13 -0.834 39.34873 63.07587 52.07209 1 1 -1 - 731 217 14 0.417 39.17266 63.98076 51.81438 1 1 -1 - 732 217 14 0.417 39.29792 62.57948 51.25523 1 1 -1 - 733 218 13 -0.834 45.66307 65.90840 47.75613 -1 0 0 - 734 218 14 0.417 44.99427 65.52542 48.32381 -1 0 0 - 735 218 14 0.417 45.75913 66.80721 48.07102 -1 0 0 - 736 219 13 -0.834 45.83158 51.91442 38.93974 0 0 0 - 737 219 14 0.417 46.07939 51.87422 39.86344 0 0 0 - 738 219 14 0.417 45.49928 51.03877 38.74210 0 0 0 - 739 220 13 -0.834 58.03934 67.88594 44.36036 -1 1 -1 - 740 220 14 0.417 58.69084 68.22520 43.74661 -1 1 -1 - 741 220 14 0.417 58.24719 68.31309 45.19138 -1 1 -1 - 742 221 13 -0.834 57.23319 66.95459 30.42832 0 0 0 - 743 221 14 0.417 56.95316 66.93560 31.34345 0 0 0 - 744 221 14 0.417 58.18154 66.82998 30.46491 0 0 0 - 745 222 13 -0.834 60.87005 44.72970 53.74755 -1 0 -1 - 746 222 14 0.417 60.02694 44.42275 53.41412 -1 0 -1 - 747 222 14 0.417 61.31963 45.07903 52.97808 -1 0 -1 - 748 223 13 -0.834 50.61352 50.44308 31.66369 0 -1 0 - 749 223 14 0.417 50.38691 49.95555 30.87173 0 -1 0 - 750 223 14 0.417 50.16704 51.28387 31.56391 0 -1 0 - 751 224 13 -0.834 42.70363 42.07925 34.73823 0 1 0 - 752 224 14 0.417 42.74630 41.15512 34.49249 0 1 0 - 753 224 14 0.417 41.77538 42.23983 34.90796 0 1 0 - 754 225 13 -0.834 50.34157 43.80796 44.49841 -1 1 0 - 755 225 14 0.417 49.44649 44.14718 44.50119 -1 1 0 - 756 225 14 0.417 50.24323 42.86994 44.66171 -1 1 0 - 757 226 13 -0.834 62.39528 64.92163 33.72829 -3 -1 1 - 758 226 14 0.417 61.94679 64.42233 34.41078 -3 -1 1 - 759 226 14 0.417 61.94061 64.68505 32.91986 -3 -1 1 - 760 227 13 -0.834 46.62188 47.13429 41.79430 0 1 1 - 761 227 14 0.417 46.21721 46.28415 41.62178 0 1 1 - 762 227 14 0.417 47.40198 46.92861 42.30946 0 1 1 - 763 228 13 -0.834 41.35469 54.31275 56.45453 0 0 -1 - 764 228 14 0.417 41.79769 53.47653 56.31055 0 0 -1 - 765 228 14 0.417 40.57273 54.26794 55.90425 0 0 -1 - 766 229 13 -0.834 48.43878 42.20000 49.94999 0 0 0 - 767 229 14 0.417 49.34431 42.29756 50.24447 0 0 0 - 768 229 14 0.417 48.41583 42.63350 49.09688 0 0 0 - 769 230 13 -0.834 37.29829 50.04209 33.34795 0 1 0 - 770 230 14 0.417 36.96213 49.51969 34.07619 0 1 0 - 771 230 14 0.417 37.98470 49.49933 32.96002 0 1 0 - 772 231 13 -0.834 58.91995 56.17895 33.02333 -1 0 0 - 773 231 14 0.417 59.83980 56.43785 32.96791 -1 0 0 - 774 231 14 0.417 58.89269 55.54120 33.73661 -1 0 0 - 775 232 13 -0.834 39.86900 65.81481 43.81866 0 0 -1 - 776 232 14 0.417 40.31483 64.99515 43.60502 0 0 -1 - 777 232 14 0.417 40.41298 66.21397 44.49762 0 0 -1 - 778 233 13 -0.834 62.71324 65.93556 51.55400 -1 0 0 - 779 233 14 0.417 62.38032 66.39597 52.32436 -1 0 0 - 780 233 14 0.417 63.52336 65.52245 51.85285 -1 0 0 - 781 234 13 -0.834 59.23324 49.58642 31.35843 0 0 0 - 782 234 14 0.417 59.28102 48.68976 31.69001 0 0 0 - 783 234 14 0.417 59.95115 50.04304 31.79700 0 0 0 - 784 235 13 -0.834 41.02310 67.21389 51.60243 0 0 0 - 785 235 14 0.417 41.77450 67.79064 51.74021 0 0 0 - 786 235 14 0.417 40.36922 67.76899 51.17753 0 0 0 - 787 236 13 -0.834 41.38918 62.43794 34.42449 0 0 1 - 788 236 14 0.417 41.26665 63.14612 33.79227 0 0 1 - 789 236 14 0.417 42.30454 62.51275 34.69423 0 0 1 - 790 237 13 -0.834 52.28796 56.01034 50.59905 0 -1 -1 - 791 237 14 0.417 53.14113 56.07317 51.02851 0 -1 -1 - 792 237 14 0.417 52.14509 55.07070 50.48548 0 -1 -1 - 793 238 13 -0.834 53.25204 66.52198 39.76351 0 -1 0 - 794 238 14 0.417 52.30774 66.44732 39.62571 0 -1 0 - 795 238 14 0.417 53.47725 67.38617 39.41895 0 -1 0 - 796 239 13 -0.834 59.77604 60.82055 48.12264 -1 -1 -1 - 797 239 14 0.417 59.80699 60.05926 48.70205 -1 -1 -1 - 798 239 14 0.417 58.96049 60.71611 47.63253 -1 -1 -1 - 799 240 13 -0.834 48.99693 51.07559 36.89084 0 -1 1 - 800 240 14 0.417 48.22315 50.55308 37.10175 0 -1 1 - 801 240 14 0.417 48.88824 51.30348 35.96753 0 -1 1 - 802 241 13 -0.834 50.67863 62.63916 55.60559 1 0 -2 - 803 241 14 0.417 51.43406 62.16856 55.25331 1 0 -2 - 804 241 14 0.417 51.05760 63.36945 56.09477 1 0 -2 - 805 242 13 -0.834 41.05301 64.77947 55.72335 1 -1 -1 - 806 242 14 0.417 41.95836 64.58666 55.96711 1 -1 -1 - 807 242 14 0.417 41.07998 65.67647 55.39035 1 -1 -1 - 808 243 13 -0.834 59.16096 63.30207 34.55147 0 -1 2 - 809 243 14 0.417 58.62636 62.51316 34.64131 0 -1 2 - 810 243 14 0.417 59.80830 63.23451 35.25333 0 -1 2 - 811 244 13 -0.834 59.86542 53.52546 55.50419 0 -1 -1 - 812 244 14 0.417 60.26921 53.79963 56.32761 0 -1 -1 - 813 244 14 0.417 58.96256 53.83773 55.56399 0 -1 -1 - 814 245 13 -0.834 56.48528 44.99075 44.65443 1 0 0 - 815 245 14 0.417 55.84854 44.49932 44.13551 1 0 0 - 816 245 14 0.417 57.18258 45.20803 44.03571 1 0 0 - 817 246 13 -0.834 37.25407 54.85866 36.86076 0 -1 -1 - 818 246 14 0.417 37.37951 55.31820 36.03050 0 -1 -1 - 819 246 14 0.417 36.91899 55.52805 37.45731 0 -1 -1 - 820 247 13 -0.834 54.42875 47.21339 48.23883 -1 -1 -1 - 821 247 14 0.417 54.60966 48.13349 48.43097 -1 -1 -1 - 822 247 14 0.417 54.44092 47.16092 47.28312 -1 -1 -1 - 823 248 13 -0.834 42.61226 41.78391 40.84493 1 0 1 - 824 248 14 0.417 41.98531 41.90233 41.55849 1 0 1 - 825 248 14 0.417 42.35866 42.43623 40.19194 1 0 1 - 826 249 13 -0.834 37.83522 41.95649 50.31377 0 0 -2 - 827 249 14 0.417 37.42231 42.81133 50.19124 0 0 -2 - 828 249 14 0.417 37.46684 41.41031 49.61934 0 0 -2 - 829 250 13 -0.834 44.80898 44.15062 49.20688 0 -1 0 - 830 250 14 0.417 44.80289 44.55594 48.33975 0 -1 0 - 831 250 14 0.417 45.29722 44.76463 49.75537 0 -1 0 - 832 251 13 -0.834 37.44321 44.03405 38.75076 1 0 1 - 833 251 14 0.417 37.12277 44.06014 39.65235 1 0 1 - 834 251 14 0.417 64.13547 43.56266 38.26824 0 0 1 - 835 252 13 -0.834 38.82113 46.15070 46.12915 1 0 0 - 836 252 14 0.417 38.96657 46.44867 47.02709 1 0 0 - 837 252 14 0.417 38.09796 45.52731 46.19733 1 0 0 - 838 253 13 -0.834 43.08482 60.65520 45.34135 -1 0 1 - 839 253 14 0.417 42.82882 59.73347 45.30784 -1 0 1 - 840 253 14 0.417 44.00885 60.65685 45.09147 -1 0 1 - 841 254 13 -0.834 45.72190 46.51173 32.51384 1 0 0 - 842 254 14 0.417 46.00925 45.78294 31.96381 1 0 0 - 843 254 14 0.417 46.53186 46.95248 32.77064 1 0 0 - 844 255 13 -0.834 63.64359 44.33728 41.24417 -1 0 0 - 845 255 14 0.417 63.60411 43.61794 41.87443 -1 0 0 - 846 255 14 0.417 62.76926 44.36407 40.85550 -1 0 0 - 847 256 13 -0.834 48.53353 66.27879 51.60437 0 0 -1 - 848 256 14 0.417 49.21611 66.24938 50.93396 0 0 -1 - 849 256 14 0.417 48.67507 65.48862 52.12577 0 0 -1 - 850 257 13 -0.834 54.11962 54.32751 39.83526 -1 1 1 - 851 257 14 0.417 53.37975 54.47391 39.24585 -1 1 1 - 852 257 14 0.417 53.95747 53.46346 40.21391 -1 1 1 - 853 258 13 -0.834 53.72785 66.08707 44.78384 -1 -1 0 - 854 258 14 0.417 54.65423 65.85662 44.85413 -1 -1 0 - 855 258 14 0.417 53.26300 65.26936 44.96130 -1 -1 0 - 856 259 13 -0.834 39.06287 51.40870 53.96063 0 0 -1 - 857 259 14 0.417 39.12854 51.34243 53.00796 0 0 -1 - 858 259 14 0.417 38.38057 52.06341 54.10916 0 0 -1 - 859 260 13 -0.834 58.77064 49.77012 37.45292 0 0 0 - 860 260 14 0.417 59.49652 49.20688 37.72142 0 0 0 - 861 260 14 0.417 57.98575 49.25379 37.63621 0 0 0 - 862 261 13 -0.834 37.94204 48.36591 35.22049 -1 0 0 - 863 261 14 0.417 37.94000 47.48368 35.59187 -1 0 0 - 864 261 14 0.417 38.86901 48.59216 35.14453 -1 0 0 - 865 262 13 -0.834 47.05754 54.06564 40.63628 0 -2 1 - 866 262 14 0.417 47.01965 53.22193 41.08679 0 -2 1 - 867 262 14 0.417 46.68660 54.68838 41.26145 0 -2 1 - 868 263 13 -0.834 46.01283 65.88108 53.59469 0 0 0 - 869 263 14 0.417 45.30729 66.50296 53.77277 0 0 0 - 870 263 14 0.417 46.76378 66.42902 53.36650 0 0 0 - 871 264 13 -0.834 45.32546 67.91008 39.11365 -1 -1 0 - 872 264 14 0.417 44.38981 67.96233 38.91853 -1 -1 0 - 873 264 14 0.417 45.70517 67.47097 38.35257 -1 -1 0 - 874 265 13 -0.834 55.39761 51.53823 53.16553 -1 1 -1 - 875 265 14 0.417 54.64975 52.10179 53.36389 -1 1 -1 - 876 265 14 0.417 55.78119 51.91789 52.37499 -1 1 -1 - 877 266 13 -0.834 57.06415 51.22923 32.75117 -1 -1 0 - 878 266 14 0.417 56.79908 52.11139 32.49079 -1 -1 0 - 879 266 14 0.417 57.98399 51.16910 32.49322 -1 -1 0 - 880 267 13 -0.834 50.05222 47.30342 45.67457 0 0 -2 - 881 267 14 0.417 49.85957 46.82324 46.47990 0 0 -2 - 882 267 14 0.417 50.60617 46.70964 45.16781 0 0 -2 - 883 268 13 -0.834 50.46819 45.47822 52.51129 0 1 -1 - 884 268 14 0.417 50.78823 45.07196 53.31677 0 1 -1 - 885 268 14 0.417 51.03886 45.13243 51.82499 0 1 -1 - 886 269 13 -0.834 47.44130 61.30175 47.80124 0 0 0 - 887 269 14 0.417 48.02715 60.89314 48.43850 0 0 0 - 888 269 14 0.417 47.98636 61.43626 47.02595 0 0 0 - 889 270 13 -0.834 41.31630 52.47434 39.71677 1 0 0 - 890 270 14 0.417 41.07609 52.94514 40.51485 1 0 0 - 891 270 14 0.417 42.05418 52.96849 39.35955 1 0 0 - 892 271 13 -0.834 55.90762 58.63213 50.47814 0 1 0 - 893 271 14 0.417 55.80273 59.37784 51.06903 0 1 0 - 894 271 14 0.417 55.41449 58.87554 49.69468 0 1 0 - 895 272 13 -0.834 42.23424 55.62725 53.35280 0 1 -1 - 896 272 14 0.417 41.62946 55.10926 53.88399 0 1 -1 - 897 272 14 0.417 41.75761 56.43615 53.16647 0 1 -1 - 898 273 13 -0.834 62.31754 63.97065 42.48774 0 0 1 - 899 273 14 0.417 63.27023 64.05391 42.44669 0 0 1 - 900 273 14 0.417 62.16851 63.13573 42.93152 0 0 1 - 901 274 13 -0.834 60.93154 49.79182 56.13812 0 -1 0 - 902 274 14 0.417 61.38991 48.97402 56.33134 0 -1 0 - 903 274 14 0.417 60.29808 49.88575 56.84955 0 -1 0 - 904 275 13 -0.834 50.39572 45.11274 36.60756 0 1 -1 - 905 275 14 0.417 50.88541 44.33834 36.33051 0 1 -1 - 906 275 14 0.417 50.38352 45.05976 37.56322 0 1 -1 - 907 276 13 -0.834 46.57204 43.12189 39.29488 -1 2 -1 - 908 276 14 0.417 46.48449 42.17951 39.43813 -1 2 -1 - 909 276 14 0.417 47.49357 43.30747 39.47547 -1 2 -1 - 910 277 13 -0.834 54.39979 41.37518 38.62483 0 0 1 - 911 277 14 0.417 54.27469 42.27221 38.31511 0 0 1 - 912 277 14 0.417 54.57135 68.24024 37.83080 0 -1 1 - 913 278 13 -0.834 60.57638 52.40343 41.12327 -1 1 -1 - 914 278 14 0.417 60.40196 53.27982 40.78010 -1 1 -1 - 915 278 14 0.417 60.37657 52.46726 42.05721 -1 1 -1 - 916 279 13 -0.834 61.77806 59.06524 41.98029 0 0 0 - 917 279 14 0.417 62.58317 59.36537 42.40214 0 0 0 - 918 279 14 0.417 61.10430 59.16112 42.65342 0 0 0 - 919 280 13 -0.834 43.46789 48.64833 54.88223 0 1 -2 - 920 280 14 0.417 43.60676 49.48200 54.43286 0 1 -2 - 921 280 14 0.417 43.74339 47.98554 54.24895 0 1 -2 - 922 281 13 -0.834 51.98628 58.37454 48.60562 -1 0 0 - 923 281 14 0.417 51.81372 57.54909 49.05852 -1 0 0 - 924 281 14 0.417 52.67545 58.16319 47.97583 -1 0 0 - 925 282 13 -0.834 55.00551 65.64176 56.63926 0 -1 -1 - 926 282 14 0.417 55.59134 66.11131 29.86167 0 -1 0 - 927 282 14 0.417 54.80211 66.27584 55.95165 0 -1 -1 - 928 283 13 -0.834 55.02996 52.59142 50.59986 -1 1 0 - 929 283 14 0.417 54.13615 52.66743 50.26585 -1 1 0 - 930 283 14 0.417 55.48513 53.35419 50.24316 -1 1 0 - 931 284 13 -0.834 37.39245 67.88600 56.81733 0 -1 -1 - 932 284 14 0.417 38.13326 41.09044 56.62787 0 0 -1 - 933 284 14 0.417 37.74351 67.00148 56.71419 0 -1 -1 - 934 285 13 -0.834 42.83234 60.22766 53.36959 0 0 0 - 935 285 14 0.417 43.51497 59.86233 52.80672 0 0 0 - 936 285 14 0.417 43.27782 60.90528 53.87815 0 0 0 - 937 286 13 -0.834 59.24806 43.81265 38.44265 1 0 0 - 938 286 14 0.417 59.12140 43.55748 39.35647 1 0 0 - 939 286 14 0.417 60.07673 44.29174 38.43991 1 0 0 - 940 287 13 -0.834 61.29263 60.52642 52.74164 -1 1 -1 - 941 287 14 0.417 61.73918 60.02180 53.42149 -1 1 -1 - 942 287 14 0.417 60.93759 61.28711 53.20156 -1 1 -1 - 943 288 13 -0.834 63.43980 43.30119 30.90384 -1 1 0 - 944 288 14 0.417 63.34979 42.36405 30.73085 -1 1 0 - 945 288 14 0.417 64.20504 43.56693 30.39393 -1 1 0 - 946 289 13 -0.834 57.11924 59.06522 54.48909 -1 0 0 - 947 289 14 0.417 57.40605 59.83488 54.98062 -1 0 0 - 948 289 14 0.417 57.59698 58.33614 54.88463 -1 0 0 - 949 290 13 -0.834 51.89759 59.82680 44.82923 1 1 -1 - 950 290 14 0.417 51.33588 59.94068 44.06258 1 1 -1 - 951 290 14 0.417 51.32846 60.01914 45.57443 1 1 -1 - 952 291 13 -0.834 57.64696 65.49112 47.86068 -1 0 0 - 953 291 14 0.417 57.31105 65.98457 48.60895 -1 0 0 - 954 291 14 0.417 57.73765 64.59519 48.18521 -1 0 0 - 955 292 13 -0.834 50.35232 57.73892 32.55459 0 1 0 - 956 292 14 0.417 51.07441 57.69034 31.92813 0 1 0 - 957 292 14 0.417 50.48339 58.57180 33.00777 0 1 0 - 958 293 13 -0.834 46.20166 60.82812 38.38269 0 1 1 - 959 293 14 0.417 46.12191 61.76977 38.53504 0 1 1 - 960 293 14 0.417 45.30555 60.53505 38.21735 0 1 1 - 961 294 13 -0.834 41.42660 51.46433 55.94150 1 0 -1 - 962 294 14 0.417 40.58025 51.71240 55.56944 1 0 -1 - 963 294 14 0.417 41.63094 50.62307 55.53311 1 0 -1 - 964 295 13 -0.834 56.72642 53.95840 32.00323 0 -1 0 - 965 295 14 0.417 57.12177 54.49254 32.69216 0 -1 0 - 966 295 14 0.417 55.80349 54.21231 32.00259 0 -1 0 - 967 296 13 -0.834 43.25852 41.40642 31.27656 0 1 0 - 968 296 14 0.417 43.58058 42.21308 31.67880 0 1 0 - 969 296 14 0.417 43.16985 68.16459 32.00619 0 0 0 - 970 297 13 -0.834 54.50477 52.62435 30.30235 -2 1 0 - 971 297 14 0.417 54.04985 52.22243 31.04245 -2 1 0 - 972 297 14 0.417 54.36900 53.56465 30.41915 -2 1 0 - 973 298 13 -0.834 38.11258 59.33341 36.21749 1 0 0 - 974 298 14 0.417 38.95754 58.91929 36.04205 1 0 0 - 975 298 14 0.417 38.14750 60.16192 35.73940 1 0 0 - 976 299 13 -0.834 39.65020 64.70254 40.48616 -1 0 1 - 977 299 14 0.417 39.87581 65.58596 40.19474 -1 0 1 - 978 299 14 0.417 39.66086 64.17611 39.68676 -1 0 1 - 979 300 13 -0.834 63.26661 53.84973 48.10281 -1 1 1 - 980 300 14 0.417 63.38261 54.75210 48.40032 -1 1 1 - 981 300 14 0.417 62.32830 53.68505 48.19603 -1 1 1 - 982 301 13 -0.834 43.65966 61.04202 50.03088 0 0 0 - 983 301 14 0.417 44.11377 60.35973 50.52538 0 0 0 - 984 301 14 0.417 44.30508 61.74317 49.94108 0 0 0 - 985 302 13 -0.834 61.75204 50.20037 32.39414 0 0 0 - 986 302 14 0.417 62.04749 51.09027 32.58663 0 0 0 - 987 302 14 0.417 62.55370 49.67736 32.38826 0 0 0 - 988 303 13 -0.834 53.79071 58.98335 36.25336 -1 -2 -1 - 989 303 14 0.417 53.17711 58.26833 36.42220 -1 -2 -1 - 990 303 14 0.417 54.65389 58.60140 36.41235 -1 -2 -1 - 991 304 13 -0.834 50.47963 50.13918 42.58243 1 -1 -2 - 992 304 14 0.417 51.28111 49.63880 42.42915 1 -1 -2 - 993 304 14 0.417 50.33279 50.61369 41.76419 1 -1 -2 - 994 305 13 -0.834 50.28770 49.02182 56.79391 1 -1 -2 - 995 305 14 0.417 50.66164 48.14920 56.91622 1 -1 -2 - 996 305 14 0.417 50.60501 49.30063 55.93493 1 -1 -2 - 997 306 13 -0.834 41.36930 46.36343 34.87469 1 1 0 - 998 306 14 0.417 42.25704 46.59841 34.60463 1 1 0 - 999 306 14 0.417 40.85961 47.16333 34.74582 1 1 0 - 1000 307 13 -0.834 61.15349 47.47016 41.71779 0 1 0 - 1001 307 14 0.417 61.50139 48.29469 41.37818 0 1 0 - 1002 307 14 0.417 60.28203 47.69385 42.04454 0 1 0 - 1003 308 13 -0.834 58.35337 46.83622 34.81712 0 0 1 - 1004 308 14 0.417 57.63221 46.22391 34.67141 0 0 1 - 1005 308 14 0.417 57.97297 47.69883 34.65146 0 0 1 - 1006 309 13 -0.834 38.79812 57.92803 48.26323 1 -2 -1 - 1007 309 14 0.417 38.67444 56.98130 48.33141 1 -2 -1 - 1008 309 14 0.417 39.70990 58.06987 48.51776 1 -2 -1 - 1009 310 13 -0.834 42.15963 57.96891 45.03230 1 0 0 - 1010 310 14 0.417 42.11698 57.98663 45.98839 1 0 0 - 1011 310 14 0.417 41.83611 57.10021 44.79371 1 0 0 - 1012 311 13 -0.834 55.17551 54.72671 36.49400 0 -1 0 - 1013 311 14 0.417 55.26386 53.77738 36.57890 0 -1 0 - 1014 311 14 0.417 55.36463 55.06457 37.36939 0 -1 0 - 1015 312 13 -0.834 58.64573 63.28550 41.10609 -1 -2 -1 - 1016 312 14 0.417 58.98147 62.66636 41.75429 -1 -2 -1 - 1017 312 14 0.417 57.90273 62.83419 40.70545 -1 -2 -1 - 1018 313 13 -0.834 49.96498 59.98797 42.54359 0 -1 0 - 1019 313 14 0.417 50.57886 60.48612 42.00390 0 -1 0 - 1020 313 14 0.417 49.10600 60.17526 42.16501 0 -1 0 - 1021 314 13 -0.834 57.54750 44.35075 52.12722 -1 -1 -1 - 1022 314 14 0.417 57.86221 43.84739 51.37633 -1 -1 -1 - 1023 314 14 0.417 56.76423 44.79718 51.80558 -1 -1 -1 - 1024 315 13 -0.834 58.07892 59.46258 41.31930 1 -1 0 - 1025 315 14 0.417 58.27344 60.10968 41.99729 1 -1 0 - 1026 315 14 0.417 57.80524 59.98199 40.56328 1 -1 0 - 1027 316 13 -0.834 42.21869 44.49848 55.65511 2 1 0 - 1028 316 14 0.417 42.77458 44.78017 56.38166 2 1 0 - 1029 316 14 0.417 42.83052 44.15513 55.00395 2 1 0 - 1030 317 13 -0.834 56.38334 63.45614 43.52622 -1 -1 0 - 1031 317 14 0.417 55.66283 63.62998 42.92052 -1 -1 0 - 1032 317 14 0.417 56.48976 64.27319 44.01338 -1 -1 0 - 1033 318 13 -0.834 43.21354 46.04700 52.52965 1 1 0 - 1034 318 14 0.417 43.24360 45.09879 52.40226 1 1 0 - 1035 318 14 0.417 43.99839 46.37328 52.08943 1 1 0 - 1036 319 13 -0.834 55.96174 45.94863 35.39660 -1 0 1 - 1037 319 14 0.417 55.64687 46.44680 36.15088 -1 0 1 - 1038 319 14 0.417 55.28305 46.06527 34.73174 -1 0 1 - 1039 320 13 -0.834 47.36406 54.82690 34.84439 -1 -1 2 - 1040 320 14 0.417 47.90093 54.86776 34.05295 -1 -1 2 - 1041 320 14 0.417 47.23152 53.89118 34.99640 -1 -1 2 - 1042 321 13 -0.834 49.62685 50.00229 45.27362 1 0 -2 - 1043 321 14 0.417 49.70876 49.05477 45.38192 1 0 -2 - 1044 321 14 0.417 49.82566 50.15634 44.35005 1 0 -2 - 1045 322 13 -0.834 49.58249 46.02940 55.43310 -1 0 -2 - 1046 322 14 0.417 49.10378 46.80060 55.12924 -1 0 -2 - 1047 322 14 0.417 49.31802 45.92761 56.34739 -1 0 -2 - 1048 323 13 -0.834 51.72150 51.53491 51.55558 0 -1 -1 - 1049 323 14 0.417 51.50292 52.17946 50.88251 0 -1 -1 - 1050 323 14 0.417 52.14568 52.04382 52.24646 0 -1 -1 - 1051 324 13 -0.834 37.98107 56.66338 52.98024 0 1 0 - 1052 324 14 0.417 37.64467 57.53823 52.78607 0 1 0 - 1053 324 14 0.417 38.15999 56.27913 52.12200 0 1 0 - 1054 325 13 -0.834 59.20226 51.55233 53.16877 -1 1 0 - 1055 325 14 0.417 59.68851 51.88535 53.92302 -1 1 0 - 1056 325 14 0.417 58.63621 50.87031 53.53025 -1 1 0 - 1057 326 13 -0.834 45.75783 63.62117 39.24032 1 1 -1 - 1058 326 14 0.417 46.25179 64.38626 39.53508 1 1 -1 - 1059 326 14 0.417 44.85376 63.80686 39.49409 1 1 -1 - 1060 327 13 -0.834 58.00953 52.38584 37.67148 -1 1 1 - 1061 327 14 0.417 58.24242 51.47235 37.50553 -1 1 1 - 1062 327 14 0.417 57.26453 52.33853 38.27062 -1 1 1 - 1063 328 13 -0.834 50.62838 66.20855 42.36072 0 0 -1 - 1064 328 14 0.417 51.45434 66.68250 42.45770 0 0 -1 - 1065 328 14 0.417 49.99531 66.87945 42.10506 0 0 -1 - 1066 329 13 -0.834 53.69444 52.39171 45.41982 1 0 0 - 1067 329 14 0.417 53.84961 51.45739 45.55855 1 0 0 - 1068 329 14 0.417 52.75879 52.45359 45.22750 1 0 0 - 1069 330 13 -0.834 38.34038 60.92162 30.12773 2 0 0 - 1070 330 14 0.417 39.08908 61.47644 29.90887 2 0 0 - 1071 330 14 0.417 38.64185 60.39196 30.86585 2 0 0 - 1072 331 13 -0.834 48.03336 64.84935 43.13262 -1 0 -2 - 1073 331 14 0.417 48.90813 65.00919 43.48682 -1 0 -2 - 1074 331 14 0.417 47.46214 65.43367 43.63114 -1 0 -2 - 1075 332 13 -0.834 39.68760 66.88962 36.60665 2 0 0 - 1076 332 14 0.417 38.74743 66.72116 36.66944 2 0 0 - 1077 332 14 0.417 40.05009 66.08888 36.22764 2 0 0 - 1078 333 13 -0.834 51.94118 65.49897 51.83197 0 -1 -2 - 1079 333 14 0.417 52.71282 65.06165 51.47204 0 -1 -2 - 1080 333 14 0.417 51.22446 64.88225 51.68297 0 -1 -2 - 1081 334 13 -0.834 43.33066 57.53264 55.09930 -1 0 -2 - 1082 334 14 0.417 43.05496 56.76932 54.59178 -1 0 -2 - 1083 334 14 0.417 44.28179 57.55937 54.99503 -1 0 -2 - 1084 335 13 -0.834 47.70128 45.69178 52.17773 -1 3 -1 - 1085 335 14 0.417 47.54566 44.86273 52.63016 -1 3 -1 - 1086 335 14 0.417 48.58530 45.94693 52.44163 -1 3 -1 - 1087 336 13 -0.834 58.71603 41.81571 40.73899 -1 0 0 - 1088 336 14 0.417 57.77048 41.84330 40.88539 -1 0 0 - 1089 336 14 0.417 58.81275 41.43332 39.86682 -1 0 0 - 1090 337 13 -0.834 57.56034 60.98533 43.60766 0 -1 0 - 1091 337 14 0.417 56.67639 60.61816 43.59917 0 -1 0 - 1092 337 14 0.417 57.42830 61.92611 43.72486 0 -1 0 - 1093 338 13 -0.834 44.68088 65.08579 34.27880 -1 0 2 - 1094 338 14 0.417 45.54678 65.09564 34.68668 -1 0 2 - 1095 338 14 0.417 44.45037 64.15818 34.22739 -1 0 2 - 1096 339 13 -0.834 54.98236 48.04093 42.26075 0 0 0 - 1097 339 14 0.417 55.16505 47.86552 43.18384 0 0 0 - 1098 339 14 0.417 55.70493 48.59999 41.97513 0 0 0 - 1099 340 13 -0.834 60.57099 56.88773 56.53671 0 0 1 - 1100 340 14 0.417 60.67151 56.21616 29.83998 0 0 2 - 1101 340 14 0.417 61.34465 56.78824 55.98192 0 0 1 - 1102 341 13 -0.834 48.05045 49.69974 47.93542 -1 0 0 - 1103 341 14 0.417 48.70922 49.23613 48.45249 -1 0 0 - 1104 341 14 0.417 48.26410 49.48583 47.02721 -1 0 0 - 1105 342 13 -0.834 40.63207 55.77589 49.21695 1 0 -1 - 1106 342 14 0.417 40.84917 56.26844 50.00847 1 0 -1 - 1107 342 14 0.417 41.40772 55.85904 48.66226 1 0 -1 - 1108 343 13 -0.834 61.66015 42.71355 39.91223 0 0 0 - 1109 343 14 0.417 61.87748 41.86774 40.30419 0 0 0 - 1110 343 14 0.417 61.98864 42.65380 39.01514 0 0 0 - 1111 344 13 -0.834 38.52157 65.12766 57.04010 0 -1 -1 - 1112 344 14 0.417 38.04157 64.32142 56.85084 0 -1 -1 - 1113 344 14 0.417 39.36310 65.01535 56.59799 0 -1 -1 - 1114 345 13 -0.834 54.26556 44.72348 38.61852 -1 0 0 - 1115 345 14 0.417 54.65781 45.53245 38.94708 -1 0 0 - 1116 345 14 0.417 54.97105 44.29396 38.13473 -1 0 0 - 1117 346 13 -0.834 55.38993 55.61246 43.96322 -1 0 1 - 1118 346 14 0.417 54.74535 54.99107 43.62461 -1 0 1 - 1119 346 14 0.417 55.11835 55.77119 44.86726 -1 0 1 - 1120 347 13 -0.834 56.42023 55.00369 50.06211 -1 -1 0 - 1121 347 14 0.417 55.77599 55.59187 50.45611 -1 -1 0 - 1122 347 14 0.417 56.93756 54.68448 50.80151 -1 -1 0 - 1123 348 13 -0.834 45.79495 66.88952 36.56670 1 1 -1 - 1124 348 14 0.417 45.28578 66.71904 35.77429 1 1 -1 - 1125 348 14 0.417 46.57709 67.34552 36.25591 1 1 -1 - 1126 349 13 -0.834 62.75278 45.54084 32.23733 0 0 0 - 1127 349 14 0.417 62.61586 44.79986 31.64705 0 0 0 - 1128 349 14 0.417 62.96974 45.14017 33.07913 0 0 0 - 1129 350 13 -0.834 57.50625 65.62986 39.74454 0 0 0 - 1130 350 14 0.417 57.73342 64.85584 40.25983 0 0 0 - 1131 350 14 0.417 57.07082 66.21286 40.36642 0 0 0 - 1132 351 13 -0.834 55.96293 62.10636 50.17062 0 1 -1 - 1133 351 14 0.417 56.24333 61.70901 50.99507 0 1 -1 - 1134 351 14 0.417 56.67888 62.69531 49.93234 0 1 -1 - 1135 352 13 -0.834 37.45010 41.11856 53.00894 0 0 0 - 1136 352 14 0.417 37.99062 41.49514 53.70339 0 0 0 - 1137 352 14 0.417 37.83337 41.45341 52.19826 0 0 0 - 1138 353 13 -0.834 40.59344 47.85232 38.52244 1 0 1 - 1139 353 14 0.417 41.31256 47.71502 37.90580 1 0 1 - 1140 353 14 0.417 40.21612 48.69426 38.26747 1 0 1 - 1141 354 13 -0.834 60.77214 62.31711 30.33695 0 2 -1 - 1142 354 14 0.417 59.83662 62.43212 30.17023 0 2 -1 - 1143 354 14 0.417 60.97856 61.45964 29.96496 0 2 -1 - 1144 355 13 -0.834 47.83829 64.26042 48.43592 0 1 -1 - 1145 355 14 0.417 47.12209 64.85952 48.22523 0 1 -1 - 1146 355 14 0.417 47.44823 63.38856 48.37295 0 1 -1 - 1147 356 13 -0.834 38.69679 45.31108 42.13672 1 1 0 - 1148 356 14 0.417 39.20464 45.52138 41.35308 1 1 0 - 1149 356 14 0.417 37.90440 44.89009 41.80335 1 1 0 - 1150 357 13 -0.834 38.90832 47.67164 52.69089 0 1 0 - 1151 357 14 0.417 39.51269 48.14149 53.26554 0 1 0 - 1152 357 14 0.417 38.42834 48.36117 52.23218 0 1 0 - 1153 358 13 -0.834 45.13879 48.98199 29.96256 0 2 1 - 1154 358 14 0.417 44.63649 48.48457 30.60794 0 2 1 - 1155 358 14 0.417 44.70163 48.80464 56.50106 0 2 0 - 1156 359 13 -0.834 54.78460 57.58368 54.24956 1 1 -1 - 1157 359 14 0.417 54.71436 57.34891 55.17486 1 1 -1 - 1158 359 14 0.417 55.60599 58.07122 54.18735 1 1 -1 - 1159 360 13 -0.834 40.77006 67.09387 46.34204 0 0 1 - 1160 360 14 0.417 40.91087 66.51539 47.09156 0 0 1 - 1161 360 14 0.417 41.47386 67.73986 46.40192 0 0 1 - 1162 361 13 -0.834 53.75960 49.21723 54.03526 1 0 -1 - 1163 361 14 0.417 54.17778 50.07537 53.96484 1 0 -1 - 1164 361 14 0.417 54.18187 48.68822 53.35846 1 0 -1 - 1165 362 13 -0.834 46.41755 62.84035 30.52059 0 0 1 - 1166 362 14 0.417 46.37357 61.90548 30.72136 0 0 1 - 1167 362 14 0.417 46.76359 62.87829 57.00030 0 0 0 - 1168 363 13 -0.834 51.27491 42.28113 30.83818 0 -1 0 - 1169 363 14 0.417 51.18814 42.11416 31.77671 0 -1 0 - 1170 363 14 0.417 50.41560 42.60836 30.57220 0 -1 0 - 1171 364 13 -0.834 52.36258 42.54738 46.83477 0 -1 -1 - 1172 364 14 0.417 51.62853 42.02025 46.51928 0 -1 -1 - 1173 364 14 0.417 53.11771 42.22680 46.34158 0 -1 -1 - 1174 365 13 -0.834 40.11442 46.69570 48.71466 3 -2 1 - 1175 365 14 0.417 39.89820 47.61495 48.55824 3 -2 1 - 1176 365 14 0.417 40.87520 46.72352 49.29493 3 -2 1 - 1177 366 13 -0.834 56.56957 65.78976 45.32589 0 -2 -1 - 1178 366 14 0.417 56.86196 65.56407 46.20896 0 -2 -1 - 1179 366 14 0.417 57.34222 66.16870 44.90678 0 -2 -1 - 1180 367 13 -0.834 38.37373 47.63723 43.98242 2 0 0 - 1181 367 14 0.417 38.78516 47.21384 44.73589 2 0 0 - 1182 367 14 0.417 38.73588 47.18051 43.22315 2 0 0 - 1183 368 13 -0.834 45.69445 49.36872 40.50736 -1 0 -2 - 1184 368 14 0.417 44.73771 49.39892 40.51002 -1 0 -2 - 1185 368 14 0.417 45.90701 48.47357 40.77155 -1 0 -2 - 1186 369 13 -0.834 53.93830 54.76570 31.99728 0 -1 0 - 1187 369 14 0.417 53.94849 55.50033 32.61083 0 -1 0 - 1188 369 14 0.417 53.13070 54.29402 32.20107 0 -1 0 - 1189 370 13 -0.834 58.79125 64.07093 37.97498 -1 -1 -2 - 1190 370 14 0.417 58.48296 64.72380 38.60343 -1 -1 -2 - 1191 370 14 0.417 58.20942 64.16977 37.22136 -1 -1 -2 - 1192 371 13 -0.834 51.76123 61.42281 40.82794 0 -1 0 - 1193 371 14 0.417 52.69114 61.24136 40.69160 0 -1 0 - 1194 371 14 0.417 51.74755 62.21395 41.36660 0 -1 0 - 1195 372 13 -0.834 44.28377 63.70509 53.71234 -1 -2 -1 - 1196 372 14 0.417 44.98211 64.35001 53.59994 -1 -2 -1 - 1197 372 14 0.417 43.75271 63.78587 52.92008 -1 -2 -1 - 1198 373 13 -0.834 61.50835 48.76378 34.91047 0 0 -1 - 1199 373 14 0.417 61.23254 49.09753 34.05678 0 0 -1 - 1200 373 14 0.417 61.51672 49.53447 35.47812 0 0 -1 - 1201 374 13 -0.834 61.51337 41.63477 44.26291 -1 -1 0 - 1202 374 14 0.417 62.42662 41.58544 44.54543 -1 -1 0 - 1203 374 14 0.417 61.34749 68.16405 43.83907 -1 -2 0 - 1204 375 13 -0.834 57.73267 43.39213 33.64792 0 -1 0 - 1205 375 14 0.417 58.46456 43.28438 34.25535 0 -1 0 - 1206 375 14 0.417 58.09278 43.15396 32.79362 0 -1 0 - 1207 376 13 -0.834 63.51473 49.31549 51.59705 -1 1 -1 - 1208 376 14 0.417 63.13045 49.03534 50.76631 -1 1 -1 - 1209 376 14 0.417 62.84038 49.86142 52.00137 -1 1 -1 - 1210 377 13 -0.834 58.21462 44.79010 54.73553 -1 -1 -1 - 1211 377 14 0.417 58.08068 43.94884 55.17209 -1 -1 -1 - 1212 377 14 0.417 57.81645 44.67856 53.87224 -1 -1 -1 - 1213 378 13 -0.834 57.08090 55.14561 52.86183 0 -2 1 - 1214 378 14 0.417 57.05215 55.46811 53.76261 0 -2 1 - 1215 378 14 0.417 57.69965 54.41575 52.88786 0 -2 1 - 1216 379 13 -0.834 60.83502 54.45436 45.82182 1 0 -1 - 1217 379 14 0.417 61.05342 55.38616 45.83857 1 0 -1 - 1218 379 14 0.417 60.79443 54.20077 46.74392 1 0 -1 - 1219 380 13 -0.834 60.86442 48.23162 37.95658 0 0 2 - 1220 380 14 0.417 61.77710 48.43881 37.75572 0 0 2 - 1221 380 14 0.417 60.87611 47.30540 38.19788 0 0 2 - 1222 381 13 -0.834 43.21478 43.26953 44.97859 2 1 -1 - 1223 381 14 0.417 42.50778 42.78849 44.54850 2 1 -1 - 1224 381 14 0.417 43.42173 42.74895 45.75474 2 1 -1 - 1225 382 13 -0.834 39.01904 49.57571 48.28198 1 -1 -1 - 1226 382 14 0.417 38.68877 49.32064 47.42052 1 -1 -1 - 1227 382 14 0.417 38.42357 50.26661 48.57234 1 -1 -1 - 1228 383 13 -0.834 47.20253 45.34580 30.26781 0 0 1 - 1229 383 14 0.417 47.05738 44.40526 30.16508 0 0 1 - 1230 383 14 0.417 46.80592 45.73631 56.86044 0 0 0 - 1231 384 13 -0.834 44.57742 55.88746 33.53830 0 -1 0 - 1232 384 14 0.417 45.13093 56.49768 33.05096 0 -1 0 - 1233 384 14 0.417 44.41092 55.17196 32.92464 0 -1 0 - 1234 385 13 -0.834 42.17091 64.36626 51.74369 1 0 0 - 1235 385 14 0.417 41.78583 65.24128 51.69570 1 0 0 - 1236 385 14 0.417 41.41926 63.77568 51.79343 1 0 0 - 1237 386 13 -0.834 43.82615 43.47821 52.97551 0 0 0 - 1238 386 14 0.417 43.64099 42.56407 52.76025 0 0 0 - 1239 386 14 0.417 44.58924 43.43914 53.55207 0 0 0 - 1240 387 13 -0.834 63.58286 63.91035 38.47173 0 -1 -1 - 1241 387 14 0.417 64.14591 63.71296 39.22023 0 -1 -1 - 1242 387 14 0.417 62.70901 64.01191 38.84896 0 -1 -1 - 1243 388 13 -0.834 57.85225 42.19019 46.82252 1 1 -2 - 1244 388 14 0.417 57.61712 42.29475 47.74450 1 1 -2 - 1245 388 14 0.417 57.29406 42.81537 46.36013 1 1 -2 - 1246 389 13 -0.834 57.90802 64.30101 52.26362 1 0 1 - 1247 389 14 0.417 58.43907 64.81717 52.87010 1 0 1 - 1248 389 14 0.417 58.54387 63.78888 51.76396 1 0 1 - 1249 390 13 -0.834 53.18379 66.68791 54.05156 1 -2 0 - 1250 390 14 0.417 52.23394 66.79510 54.00115 1 -2 0 - 1251 390 14 0.417 53.33447 65.77140 53.82015 1 -2 0 - 1252 391 13 -0.834 56.95394 68.26036 36.42711 -1 1 1 - 1253 391 14 0.417 56.91362 41.83232 36.58445 -1 2 1 - 1254 391 14 0.417 57.79173 67.98998 36.80292 -1 1 1 - 1255 392 13 -0.834 64.19252 44.20158 54.88143 0 0 0 - 1256 392 14 0.417 64.09322 45.07899 54.51194 0 0 0 - 1257 392 14 0.417 63.39239 43.74201 54.62684 0 0 0 - 1258 393 13 -0.834 63.10536 65.42626 48.53464 0 0 0 - 1259 393 14 0.417 62.79665 64.63036 48.10166 0 0 0 - 1260 393 14 0.417 62.77768 65.35429 49.43112 0 0 0 - 1261 394 13 -0.834 49.28836 66.20367 32.27628 1 -1 0 - 1262 394 14 0.417 49.46858 65.88738 33.16155 1 -1 0 - 1263 394 14 0.417 49.29197 65.41476 31.73420 1 -1 0 - 1264 395 13 -0.834 46.11216 66.09570 44.77896 0 -1 0 - 1265 395 14 0.417 45.90309 66.07762 45.71287 0 -1 0 - 1266 395 14 0.417 45.36137 65.67813 44.35683 0 -1 0 - 1267 396 13 -0.834 41.43943 50.30026 52.32584 1 0 0 - 1268 396 14 0.417 41.39866 49.93140 51.44351 1 0 0 - 1269 396 14 0.417 40.92759 49.69528 52.86275 1 0 0 - 1270 397 13 -0.834 54.69177 57.80859 32.50623 0 -1 -1 - 1271 397 14 0.417 53.99890 57.66594 31.86139 0 -1 -1 - 1272 397 14 0.417 54.37599 57.37325 33.29806 0 -1 -1 - 1273 398 13 -0.834 43.56781 46.79065 37.17838 0 1 0 - 1274 398 14 0.417 43.18325 46.24795 36.49004 0 1 0 - 1275 398 14 0.417 44.03819 46.17194 37.73711 0 1 0 - 1276 399 13 -0.834 55.33436 45.90772 50.69068 -1 0 0 - 1277 399 14 0.417 55.55455 46.77982 51.01809 -1 0 0 - 1278 399 14 0.417 55.09425 46.04877 49.77488 -1 0 0 - 1279 400 13 -0.834 56.15383 51.87018 43.92178 -1 0 1 - 1280 400 14 0.417 55.25073 52.12373 44.11256 -1 0 1 - 1281 400 14 0.417 56.65027 52.68628 43.98319 -1 0 1 - 1282 401 13 -0.834 62.38946 50.01240 45.94802 0 1 -2 - 1283 401 14 0.417 62.43815 50.07607 44.99418 0 1 -2 - 1284 401 14 0.417 61.47369 50.19932 46.15457 0 1 -2 - 1285 402 13 -0.834 53.60920 58.35575 46.37412 0 0 1 - 1286 402 14 0.417 53.25556 59.03071 45.79481 0 0 1 - 1287 402 14 0.417 53.24753 57.53627 46.03666 0 0 1 - 1288 403 13 -0.834 43.13375 42.07203 50.04429 1 0 0 - 1289 403 14 0.417 43.76099 42.76922 49.85267 1 0 0 - 1290 403 14 0.417 42.35437 42.53016 50.35879 1 0 0 - 1291 404 13 -0.834 47.41498 59.41146 52.77687 -1 -1 0 - 1292 404 14 0.417 47.81303 59.83868 53.53534 -1 -1 0 - 1293 404 14 0.417 48.01011 59.60512 52.05261 -1 -1 0 - 1294 405 13 -0.834 63.75607 47.28104 38.80571 0 2 -1 - 1295 405 14 0.417 63.78573 48.20840 38.57042 0 2 -1 - 1296 405 14 0.417 37.08655 47.17376 39.44769 1 2 -1 - 1297 406 13 -0.834 46.67594 56.20863 44.42866 1 1 0 - 1298 406 14 0.417 45.82140 56.15280 44.00100 1 1 0 - 1299 406 14 0.417 46.48292 56.12468 45.36243 1 1 0 - 1300 407 13 -0.834 62.54251 68.21194 54.20445 0 -1 1 - 1301 407 14 0.417 63.31640 41.15490 53.73696 0 0 1 - 1302 407 14 0.417 62.78865 67.34176 54.51819 0 -1 1 - 1303 408 13 -0.834 60.27010 54.96049 39.87633 0 0 0 - 1304 408 14 0.417 59.62959 55.67175 39.88547 0 0 0 - 1305 408 14 0.417 61.04761 55.33233 40.29281 0 0 0 - 1306 409 13 -0.834 40.02595 44.30132 44.29580 0 -2 0 - 1307 409 14 0.417 39.70595 44.75009 45.07839 0 -2 0 - 1308 409 14 0.417 39.56836 44.72725 43.57092 0 -2 0 - 1309 410 13 -0.834 54.20011 41.08252 35.61017 0 1 0 - 1310 410 14 0.417 55.10396 68.23613 35.83794 0 0 0 - 1311 410 14 0.417 54.27044 41.57221 34.79072 0 1 0 - 1312 411 13 -0.834 60.64478 45.93023 50.84376 1 1 -1 - 1313 411 14 0.417 60.80088 46.54647 51.55941 1 1 -1 - 1314 411 14 0.417 61.20574 46.24077 50.13303 1 1 -1 - 1315 412 13 -0.834 44.55137 44.47403 38.16771 1 0 -1 - 1316 412 14 0.417 45.28189 43.86333 38.26597 1 0 -1 - 1317 412 14 0.417 43.77025 43.93754 38.30281 1 0 -1 - 1318 413 13 -0.834 58.08933 62.76987 30.45191 1 -1 0 - 1319 413 14 0.417 57.64138 63.31997 29.80927 1 -1 0 - 1320 413 14 0.417 57.43674 62.11708 30.70545 1 -1 0 - 1321 414 13 -0.834 55.65273 56.71117 38.74877 1 0 1 - 1322 414 14 0.417 56.53260 56.59636 39.10779 1 0 1 - 1323 414 14 0.417 55.14964 55.98047 39.10825 1 0 1 - 1324 415 13 -0.834 55.50009 51.16952 38.77962 0 0 0 - 1325 415 14 0.417 54.95350 51.23711 37.99672 0 0 0 - 1326 415 14 0.417 55.53220 50.23190 38.96963 0 0 0 - 1327 416 13 -0.834 47.64702 52.79911 31.71446 0 -1 0 - 1328 416 14 0.417 48.52504 53.09556 31.47481 0 -1 0 - 1329 416 14 0.417 47.06032 53.44853 31.32681 0 -1 0 - 1330 417 13 -0.834 49.26727 42.35880 39.18566 1 1 -2 - 1331 417 14 0.417 50.02784 42.93912 39.15429 1 1 -2 - 1332 417 14 0.417 49.46495 41.74196 39.89040 1 1 -2 - 1333 418 13 -0.834 47.22542 64.65021 35.82232 1 -1 0 - 1334 418 14 0.417 46.76114 65.20346 36.45050 1 -1 0 - 1335 418 14 0.417 47.98585 65.16966 35.56120 1 -1 0 - 1336 419 13 -0.834 58.53686 56.85468 40.78587 1 1 0 - 1337 419 14 0.417 58.45283 56.63469 41.71365 1 1 0 - 1338 419 14 0.417 58.36285 57.79507 40.74550 1 1 0 - 1339 420 13 -0.834 50.09436 46.17981 48.16619 -1 -1 -2 - 1340 420 14 0.417 50.67249 45.42897 48.30138 -1 -1 -2 - 1341 420 14 0.417 50.49629 46.88624 48.67183 -1 -1 -2 - 1342 421 13 -0.834 42.30297 57.95379 33.48633 0 -1 1 - 1343 421 14 0.417 41.56921 57.39445 33.23136 0 -1 1 - 1344 421 14 0.417 43.00718 57.34235 33.70193 0 -1 1 - 1345 422 13 -0.834 45.76518 43.79811 54.82490 0 -1 0 - 1346 422 14 0.417 46.45133 43.55343 54.20397 0 -1 0 - 1347 422 14 0.417 45.87205 43.18693 55.55379 0 -1 0 - 1348 423 13 -0.834 59.33326 61.34125 37.96927 -1 -1 1 - 1349 423 14 0.417 59.29007 62.29004 38.08827 -1 -1 1 - 1350 423 14 0.417 59.90006 61.03609 38.67769 -1 -1 1 - 1351 424 13 -0.834 40.95662 63.48104 42.72192 1 -1 0 - 1352 424 14 0.417 40.33618 63.69074 42.02383 1 -1 0 - 1353 424 14 0.417 41.73946 63.17568 42.26346 1 -1 0 - 1354 425 13 -0.834 38.13662 59.25720 46.08402 1 -1 -1 - 1355 425 14 0.417 38.31499 59.03616 46.99811 1 -1 -1 - 1356 425 14 0.417 38.55502 58.55783 45.58196 1 -1 -1 - 1357 426 13 -0.834 48.88681 66.85051 54.82298 1 -2 0 - 1358 426 14 0.417 49.16879 67.45078 54.13275 1 -2 0 - 1359 426 14 0.417 49.42353 66.06836 54.69484 1 -2 0 - 1360 427 13 -0.834 45.88049 57.05477 48.46508 0 0 -1 - 1361 427 14 0.417 45.73709 57.90911 48.05793 0 0 -1 - 1362 427 14 0.417 45.83791 57.22701 49.40569 0 0 -1 - 1363 428 13 -0.834 39.37333 50.31613 37.93447 0 1 0 - 1364 428 14 0.417 39.11456 50.97624 37.29140 0 1 0 - 1365 428 14 0.417 38.97424 50.60960 38.75352 0 1 0 - 1366 429 13 -0.834 37.89753 62.82745 47.39297 0 -1 0 - 1367 429 14 0.417 38.39122 62.78202 46.57414 0 -1 0 - 1368 429 14 0.417 37.01605 63.08963 47.12747 0 -1 0 - 1369 430 13 -0.834 43.16514 41.31420 47.01379 0 1 0 - 1370 430 14 0.417 42.71409 41.22965 47.85382 0 1 0 - 1371 430 14 0.417 44.05112 68.36565 47.18386 0 0 0 - 1372 431 13 -0.834 47.03179 42.44477 42.46475 1 0 0 - 1373 431 14 0.417 46.12350 42.65285 42.24573 1 0 0 - 1374 431 14 0.417 47.53228 43.19970 42.15516 1 0 0 - 1375 432 13 -0.834 55.35894 54.15040 46.85340 0 -1 0 - 1376 432 14 0.417 54.76544 53.43667 46.61975 0 -1 0 - 1377 432 14 0.417 56.17133 53.71318 47.10853 0 -1 0 - 1378 433 13 -0.834 47.00663 55.28313 38.22800 -1 -2 1 - 1379 433 14 0.417 46.53490 56.00706 38.63987 -1 -2 1 - 1380 433 14 0.417 47.07459 54.61953 38.91449 -1 -2 1 - 1381 434 13 -0.834 57.16336 58.62297 32.33349 -1 0 2 - 1382 434 14 0.417 57.63330 57.80350 32.48798 -1 0 2 - 1383 434 14 0.417 56.24209 58.36680 32.29014 -1 0 2 - 1384 435 13 -0.834 37.23245 47.62479 56.34765 0 1 -1 - 1385 435 14 0.417 37.24274 47.21497 55.48268 0 1 -1 - 1386 435 14 0.417 37.36000 46.89905 56.95860 0 1 -1 - 1387 436 13 -0.834 48.77030 41.06015 29.86683 2 1 0 - 1388 436 14 0.417 48.81141 67.97117 56.39997 2 0 -1 - 1389 436 14 0.417 49.05230 67.78232 30.51123 2 0 0 - 1390 437 13 -0.834 49.10149 56.15638 36.66346 0 0 1 - 1391 437 14 0.417 48.50786 55.61659 36.14146 0 0 1 - 1392 437 14 0.417 48.61812 56.33305 37.47053 0 0 1 - 1393 438 13 -0.834 58.15731 59.39698 29.96092 0 -1 1 - 1394 438 14 0.417 58.20240 59.10993 30.87296 0 -1 1 - 1395 438 14 0.417 57.30076 59.81721 29.88367 0 -1 1 - 1396 439 13 -0.834 59.37068 41.03089 37.87324 1 0 0 - 1397 439 14 0.417 59.56889 41.95335 37.71194 1 0 0 - 1398 439 14 0.417 60.22643 67.97433 37.90167 1 -1 0 - 1399 440 13 -0.834 38.32241 55.03397 50.58952 1 0 0 - 1400 440 14 0.417 38.22793 54.19584 50.13692 1 0 0 - 1401 440 14 0.417 39.21785 55.31153 50.39614 1 0 0 - 1402 441 13 -0.834 36.94673 59.01778 33.00159 1 -1 2 - 1403 441 14 0.417 36.95260 59.97305 32.94091 1 -1 2 - 1404 441 14 0.417 63.71798 58.82680 33.72245 0 -1 2 - 1405 442 13 -0.834 62.50746 54.84239 54.03343 0 -1 0 - 1406 442 14 0.417 61.69710 54.35984 54.19681 0 -1 0 - 1407 442 14 0.417 63.09119 54.20097 53.62833 0 -1 0 - 1408 443 13 -0.834 40.59690 62.80012 38.69405 1 -1 1 - 1409 443 14 0.417 41.53881 62.90970 38.82458 1 -1 1 - 1410 443 14 0.417 40.36980 62.03187 39.21794 1 -1 1 - 1411 444 13 -0.834 37.67477 67.71471 42.59127 0 -1 -1 - 1412 444 14 0.417 38.12213 68.13627 41.85751 0 -1 -1 - 1413 444 14 0.417 38.28279 67.03643 42.88534 0 -1 -1 - 1414 445 13 -0.834 42.73681 50.65782 33.30839 1 1 0 - 1415 445 14 0.417 42.84587 51.15085 34.12157 1 1 0 - 1416 445 14 0.417 42.32631 51.27747 32.70527 1 1 0 - 1417 446 13 -0.834 37.13349 57.05842 55.81927 0 0 0 - 1418 446 14 0.417 37.95375 57.53453 55.68979 0 0 0 - 1419 446 14 0.417 36.99014 56.59807 54.99236 0 0 0 - 1420 447 13 -0.834 61.08039 63.50929 36.52096 -1 0 0 - 1421 447 14 0.417 60.44389 63.87414 37.13579 -1 0 0 - 1422 447 14 0.417 61.70642 63.04107 37.07331 -1 0 0 - 1423 448 13 -0.834 57.12289 46.04019 38.75954 0 0 0 - 1424 448 14 0.417 56.81351 45.55997 39.52760 0 0 0 - 1425 448 14 0.417 57.99543 45.68504 38.58988 0 0 0 - 1426 449 13 -0.834 45.45003 49.45347 49.54397 0 0 -1 - 1427 449 14 0.417 45.96611 49.34591 48.74502 0 0 -1 - 1428 449 14 0.417 46.09930 49.60861 50.22999 0 0 -1 - 1429 450 13 -0.834 37.77009 64.51990 42.66941 1 0 0 - 1430 450 14 0.417 38.49339 64.80040 43.23011 1 0 0 - 1431 450 14 0.417 38.14071 64.50928 41.78694 1 0 0 - 1432 451 13 -0.834 45.78323 57.65378 39.37062 1 0 0 - 1433 451 14 0.417 46.03758 58.03295 40.21190 1 0 0 - 1434 451 14 0.417 44.96217 58.09258 39.14803 1 0 0 - 1435 452 13 -0.834 56.96672 60.41636 47.59314 0 -1 1 - 1436 452 14 0.417 56.18373 60.11455 48.05365 0 -1 1 - 1437 452 14 0.417 56.65889 61.13663 47.04297 0 -1 1 - 1438 453 13 -0.834 52.44356 65.82746 35.82081 -1 -1 0 - 1439 453 14 0.417 53.10567 65.14225 35.91211 -1 -1 0 - 1440 453 14 0.417 52.93741 66.64611 35.86748 -1 -1 0 - 1441 454 13 -0.834 50.70912 51.42252 40.30021 0 0 -1 - 1442 454 14 0.417 50.97387 50.70177 39.72866 0 0 -1 - 1443 454 14 0.417 50.17774 51.98938 39.74116 0 0 -1 - 1444 455 13 -0.834 39.22290 45.94023 39.69239 2 1 -1 - 1445 455 14 0.417 39.63836 46.66722 39.22859 2 1 -1 - 1446 455 14 0.417 38.97218 45.32685 39.00164 2 1 -1 - 1447 456 13 -0.834 43.73041 61.86387 55.46954 2 0 0 - 1448 456 14 0.417 43.61274 62.32163 56.30192 2 0 0 - 1449 456 14 0.417 43.90401 62.55964 54.83549 2 0 0 - 1450 457 13 -0.834 61.51877 56.42039 33.84869 0 0 1 - 1451 457 14 0.417 62.17805 55.74211 33.70200 0 0 1 - 1452 457 14 0.417 62.00943 57.15723 34.21276 0 0 1 - 1453 458 13 -0.834 51.72050 63.63199 42.34406 1 0 1 - 1454 458 14 0.417 51.24482 64.43296 42.56407 1 0 1 - 1455 458 14 0.417 52.62118 63.92057 42.19669 1 0 1 - 1456 459 13 -0.834 54.73666 56.51839 51.73687 0 0 -1 - 1457 459 14 0.417 54.77503 56.56844 52.69200 0 0 -1 - 1458 459 14 0.417 54.91702 57.41111 51.44234 0 0 -1 - 1459 460 13 -0.834 50.97984 54.35591 33.27919 0 1 0 - 1460 460 14 0.417 50.47200 55.12727 33.02747 0 1 0 - 1461 460 14 0.417 50.36917 53.82187 33.78725 0 1 0 - 1462 461 13 -0.834 44.82656 54.45280 36.09973 1 0 2 - 1463 461 14 0.417 45.75766 54.23599 36.14740 1 0 2 - 1464 461 14 0.417 44.76968 55.11700 35.41283 1 0 2 - 1465 462 13 -0.834 58.05791 56.64716 55.29041 1 1 0 - 1466 462 14 0.417 58.98499 56.81997 55.45441 1 1 0 - 1467 462 14 0.417 57.82639 55.96338 55.91897 1 1 0 - 1468 463 13 -0.834 55.95112 61.02029 30.79757 1 0 1 - 1469 463 14 0.417 55.28483 61.63344 30.48711 1 0 1 - 1470 463 14 0.417 55.45357 60.27206 31.12748 1 0 1 - 1471 464 13 -0.834 54.80996 46.88659 45.41700 -1 0 0 - 1472 464 14 0.417 55.42348 46.16300 45.28950 -1 0 0 - 1473 464 14 0.417 54.08129 46.68997 44.82826 -1 0 0 - 1474 465 13 -0.834 60.19361 64.43268 31.92053 0 -1 2 - 1475 465 14 0.417 60.05792 63.85315 32.67017 0 -1 2 - 1476 465 14 0.417 60.47170 63.84993 31.21392 0 -1 2 - 1477 466 13 -0.834 45.55496 65.56032 30.88251 0 -1 1 - 1478 466 14 0.417 45.97644 64.70102 30.89691 0 -1 1 - 1479 466 14 0.417 45.82502 65.97384 31.70248 0 -1 1 - 1480 467 13 -0.834 52.92714 44.06759 29.88429 0 1 0 - 1481 467 14 0.417 52.39641 43.38446 30.29405 0 1 0 - 1482 467 14 0.417 53.79372 43.96686 30.27818 0 1 0 - 1483 468 13 -0.834 40.71534 55.31247 44.93070 1 0 0 - 1484 468 14 0.417 39.81994 55.07165 45.16841 1 0 0 - 1485 468 14 0.417 41.16802 54.47609 44.82218 1 0 0 - 1486 469 13 -0.834 64.04777 59.80626 42.91634 0 -1 -1 - 1487 469 14 0.417 37.09051 60.51146 43.41377 1 -1 -1 - 1488 469 14 0.417 37.01609 59.00291 43.31068 1 -1 -1 - 1489 470 13 -0.834 57.05030 49.72625 41.88829 -1 1 1 - 1490 470 14 0.417 56.75150 50.53290 42.30818 -1 1 1 - 1491 470 14 0.417 57.52176 50.02159 41.10935 -1 1 1 - 1492 471 13 -0.834 62.59447 67.67898 41.14714 -2 -2 1 - 1493 471 14 0.417 63.45155 67.57764 41.56112 -2 -2 1 - 1494 471 14 0.417 61.96974 67.40478 41.81854 -2 -2 1 - 1495 472 13 -0.834 62.98029 58.34420 35.34278 0 0 1 - 1496 472 14 0.417 62.45371 58.26151 36.13783 0 0 1 - 1497 472 14 0.417 63.83636 58.64077 35.65169 0 0 1 - 1498 473 13 -0.834 63.44584 56.74146 44.14484 0 1 -2 - 1499 473 14 0.417 64.13590 56.53036 44.77371 0 1 -2 - 1500 473 14 0.417 62.70665 57.02149 44.68470 0 1 -2 - 1501 474 13 -0.834 44.05905 56.56929 51.60681 1 0 -1 - 1502 474 14 0.417 43.57850 56.15764 52.32504 1 0 -1 - 1503 474 14 0.417 43.90344 55.99747 50.85512 1 0 -1 - 1504 475 13 -0.834 37.49588 59.31379 39.05252 0 0 0 - 1505 475 14 0.417 37.07904 58.45297 39.09112 0 0 0 - 1506 475 14 0.417 37.58867 59.49374 38.11696 0 0 0 - 1507 476 13 -0.834 54.75747 41.52122 56.48609 -1 1 0 - 1508 476 14 0.417 54.79987 42.39714 56.86981 -1 1 0 - 1509 476 14 0.417 54.80582 41.67034 55.54179 -1 1 0 - 1510 477 13 -0.834 42.91665 58.39379 47.91495 1 0 0 - 1511 477 14 0.417 43.70923 58.91951 47.80683 1 0 0 - 1512 477 14 0.417 42.28811 58.98861 48.32409 1 0 0 - 1513 478 13 -0.834 60.63731 64.78822 56.03697 -2 1 -1 - 1514 478 14 0.417 60.86485 63.91302 56.35082 -2 1 -1 - 1515 478 14 0.417 60.50973 65.30321 56.83369 -2 1 -1 - 1516 479 13 -0.834 52.85180 54.69512 43.09842 0 0 1 - 1517 479 14 0.417 52.31485 55.13373 42.43846 0 0 1 - 1518 479 14 0.417 53.08000 53.85428 42.70200 0 0 1 - 1519 480 13 -0.834 51.49497 54.97356 38.95012 -2 1 -1 - 1520 480 14 0.417 50.77717 54.34090 38.97811 -2 1 -1 - 1521 480 14 0.417 51.51597 55.35169 39.82923 -2 1 -1 - 1522 481 13 -0.834 40.46924 62.02458 56.36341 1 0 -1 - 1523 481 14 0.417 40.45814 61.65439 55.48076 1 0 -1 - 1524 481 14 0.417 40.81799 62.90856 56.24853 1 0 -1 - 1525 482 13 -0.834 52.26692 56.29032 45.24820 0 2 1 - 1526 482 14 0.417 51.65227 56.79794 44.71834 0 2 1 - 1527 482 14 0.417 52.43092 55.49973 44.73408 0 2 1 - 1528 483 13 -0.834 53.46372 44.63556 52.39623 -1 1 1 - 1529 483 14 0.417 53.51664 45.03502 53.26448 -1 1 1 - 1530 483 14 0.417 54.08491 45.13343 51.86474 -1 1 1 - 1531 484 13 -0.834 42.90202 49.87822 40.32919 0 2 1 - 1532 484 14 0.417 42.40392 49.63281 41.10889 0 2 1 - 1533 484 14 0.417 42.31302 50.45172 39.83885 0 2 1 - 1534 485 13 -0.834 43.07357 64.57931 39.44006 2 1 1 - 1535 485 14 0.417 42.79300 64.80186 38.55237 2 1 1 - 1536 485 14 0.417 43.26869 65.42268 39.84860 2 1 1 - 1537 486 13 -0.834 38.86691 42.35197 55.12826 1 1 -1 - 1538 486 14 0.417 38.06621 42.87541 55.16185 1 1 -1 - 1539 486 14 0.417 39.52681 42.89488 55.55954 1 1 -1 - 1540 487 13 -0.834 59.15412 47.19863 55.46904 0 -1 0 - 1541 487 14 0.417 59.83963 46.99833 56.10636 0 -1 0 - 1542 487 14 0.417 58.74433 46.35364 55.28381 0 -1 0 - 1543 488 13 -0.834 52.12071 45.94110 44.23903 1 1 0 - 1544 488 14 0.417 51.89927 45.05144 44.51416 1 1 0 - 1545 488 14 0.417 52.26697 45.87115 43.29566 1 1 0 - 1546 489 13 -0.834 41.73140 52.23741 31.27732 0 0 1 - 1547 489 14 0.417 40.84403 52.55314 31.44796 0 0 1 - 1548 489 14 0.417 41.81503 52.26011 30.32405 0 0 1 - 1549 490 13 -0.834 38.46034 66.01701 52.27886 1 0 -1 - 1550 490 14 0.417 39.39276 66.02392 52.49517 1 0 -1 - 1551 490 14 0.417 38.11246 66.80769 52.69121 1 0 -1 - 1552 491 13 -0.834 42.13838 67.12262 54.88509 0 0 -3 - 1553 491 14 0.417 42.22460 67.38235 53.96784 0 0 -3 - 1554 491 14 0.417 42.96673 67.38388 55.28736 0 0 -3 - 1555 492 13 -0.834 37.89607 66.86351 46.16867 -1 -1 -1 - 1556 492 14 0.417 38.03129 66.98073 47.10899 -1 -1 -1 - 1557 492 14 0.417 38.75367 66.60168 45.83369 -1 -1 -1 - 1558 493 13 -0.834 40.37538 58.21424 30.88318 0 -1 0 - 1559 493 14 0.417 41.23010 58.63566 30.79307 0 -1 0 - 1560 493 14 0.417 40.45502 57.40101 30.38463 0 -1 0 - 1561 494 13 -0.834 54.56531 48.85249 32.17940 1 -2 2 - 1562 494 14 0.417 54.90082 48.98086 31.29216 1 -2 2 - 1563 494 14 0.417 54.03604 49.63141 32.35086 1 -2 2 - 1564 495 13 -0.834 63.56488 49.70113 37.88594 0 -1 1 - 1565 495 14 0.417 63.93261 49.40780 37.05228 0 -1 1 - 1566 495 14 0.417 63.98151 50.54765 38.04739 0 -1 1 - 1567 496 13 -0.834 39.26126 54.76920 54.71493 2 -1 2 - 1568 496 14 0.417 38.75402 55.21237 54.03483 2 -1 2 - 1569 496 14 0.417 38.67139 54.73109 55.46781 2 -1 2 - 1570 497 13 -0.834 42.78607 47.20625 49.30057 2 -1 0 - 1571 497 14 0.417 42.93670 46.34815 48.90404 2 -1 0 - 1572 497 14 0.417 43.53800 47.33917 49.87780 2 -1 0 - 1573 498 13 -0.834 59.99490 55.30114 50.55687 0 1 -1 - 1574 498 14 0.417 60.84158 55.66821 50.81111 0 1 -1 - 1575 498 14 0.417 59.38335 56.03363 50.63237 0 1 -1 - 1576 499 13 -0.834 57.95276 49.30660 54.37087 1 -1 -1 - 1577 499 14 0.417 57.34184 49.29544 55.10769 1 -1 -1 - 1578 499 14 0.417 58.55272 48.58151 54.54557 1 -1 -1 - 1579 500 13 -0.834 43.43041 64.04345 57.10111 1 -1 -1 - 1580 500 14 0.417 43.03742 64.07155 30.60210 1 -1 0 - 1581 500 14 0.417 44.26016 64.51104 29.82515 1 -1 0 - 1582 501 13 -0.834 40.71066 57.82778 50.85579 1 -1 -1 - 1583 501 14 0.417 41.04411 57.83612 51.75299 1 -1 -1 - 1584 501 14 0.417 40.96886 58.67633 50.49590 1 -1 -1 - 1585 502 13 -0.834 61.21331 60.53661 39.63578 1 -1 0 - 1586 502 14 0.417 61.87151 61.23113 39.61011 1 -1 0 - 1587 502 14 0.417 61.32085 60.13583 40.49837 1 -1 0 - 1588 503 13 -0.834 43.54081 65.33296 49.47114 1 -1 -1 - 1589 503 14 0.417 42.67637 65.41138 49.06762 1 -1 -1 - 1590 503 14 0.417 43.36562 64.99829 50.35065 1 -1 -1 - 1591 504 13 -0.834 50.27329 53.06087 30.87109 -1 0 1 - 1592 504 14 0.417 50.38769 53.42204 29.99204 -1 0 1 - 1593 504 14 0.417 50.86354 53.57620 31.42092 -1 0 1 - 1594 505 13 -0.834 40.29157 66.01889 32.67757 0 -1 0 - 1595 505 14 0.417 40.18198 66.27998 31.76320 0 -1 0 - 1596 505 14 0.417 39.39873 65.90460 33.00317 0 -1 0 - 1597 506 13 -0.834 48.15372 67.97019 44.25255 1 -1 1 - 1598 506 14 0.417 47.34263 67.52534 44.49854 1 -1 1 - 1599 506 14 0.417 47.87159 41.31478 43.68328 1 0 1 - 1600 507 13 -0.834 53.38019 63.98437 38.13827 0 0 -1 - 1601 507 14 0.417 54.19463 63.69976 37.72362 0 0 -1 - 1602 507 14 0.417 53.59582 64.82739 38.53711 0 0 -1 - 1603 508 13 -0.834 40.87597 58.12305 53.50808 0 0 0 - 1604 508 14 0.417 40.17916 58.26636 54.14852 0 0 0 - 1605 508 14 0.417 41.66044 58.48234 53.92256 0 0 0 - 1606 509 13 -0.834 38.19887 52.28056 36.30714 2 0 -1 - 1607 509 14 0.417 38.20463 53.19038 36.60452 2 0 -1 - 1608 509 14 0.417 38.09924 52.33929 35.35695 2 0 -1 - 1609 510 13 -0.834 49.63883 57.32410 43.72359 0 -1 0 - 1610 510 14 0.417 49.72446 58.17232 43.28833 0 -1 0 - 1611 510 14 0.417 48.76183 57.33851 44.10688 0 -1 0 - 1612 511 13 -0.834 42.58791 59.61362 29.86455 1 0 0 - 1613 511 14 0.417 43.07246 58.91969 56.78877 1 0 -1 - 1614 511 14 0.417 42.69535 60.38141 56.67447 1 0 -1 - 1615 512 13 -0.834 50.76111 60.95449 46.98165 -1 0 -1 - 1616 512 14 0.417 50.90477 61.15450 47.90663 -1 0 -1 - 1617 512 14 0.417 50.20825 61.66875 46.66473 -1 0 -1 - 1618 513 13 -0.834 43.18406 55.61939 48.08539 1 0 0 - 1619 513 14 0.417 43.11229 56.55752 47.90932 1 0 0 - 1620 513 14 0.417 44.01330 55.36231 47.68228 1 0 0 - 1621 514 13 -0.834 54.67377 64.76817 41.62522 1 0 1 - 1622 514 14 0.417 54.39407 65.19031 40.81294 1 0 1 - 1623 514 14 0.417 55.29742 65.38243 42.01250 1 0 1 - 1624 515 13 -0.834 53.87383 68.12810 51.72031 0 -1 0 - 1625 515 14 0.417 53.06918 41.24938 51.55887 0 0 0 - 1626 515 14 0.417 53.74278 67.72971 52.58074 0 -1 0 - 1627 516 13 -0.834 38.24785 41.26767 33.50598 2 0 0 - 1628 516 14 0.417 38.16490 67.75301 33.15337 2 -1 0 - 1629 516 14 0.417 37.95757 41.83753 32.79377 2 0 0 - 1630 517 13 -0.834 47.35008 61.96125 42.94580 2 -2 0 - 1631 517 14 0.417 47.46077 62.90828 43.03015 2 -2 0 - 1632 517 14 0.417 47.09087 61.83022 42.03373 2 -2 0 - 1633 518 13 -0.834 40.55210 54.00820 41.89137 1 -1 1 - 1634 518 14 0.417 39.80099 54.24986 41.34946 1 -1 1 - 1635 518 14 0.417 40.19429 53.40377 42.54166 1 -1 1 - 1636 519 13 -0.834 57.17705 64.40362 55.44286 1 -1 -1 - 1637 519 14 0.417 56.34510 64.78670 55.72097 1 -1 -1 - 1638 519 14 0.417 57.64987 65.12814 55.03330 1 -1 -1 - 1639 520 13 -0.834 41.86955 59.84132 42.65268 0 -1 1 - 1640 520 14 0.417 41.72011 59.11980 43.26367 0 -1 1 - 1641 520 14 0.417 42.24995 60.53605 43.19017 0 -1 1 - 1642 521 13 -0.834 61.62566 57.26645 46.18447 0 -1 -1 - 1643 521 14 0.417 60.68119 57.41642 46.22577 0 -1 -1 - 1644 521 14 0.417 61.98987 57.84356 46.85569 0 -1 -1 - 1645 522 13 -0.834 46.82701 65.68647 41.03579 0 0 0 - 1646 522 14 0.417 46.01385 65.85266 41.51264 0 0 0 - 1647 522 14 0.417 47.44009 65.38297 41.70531 0 0 0 - 1648 523 13 -0.834 54.12960 45.94549 32.81485 0 0 1 - 1649 523 14 0.417 53.25962 45.65636 32.53955 0 0 1 - 1650 523 14 0.417 54.18942 46.85072 32.50950 0 0 1 - 1651 524 13 -0.834 43.71268 59.97805 32.34985 1 1 0 - 1652 524 14 0.417 43.46300 59.27568 32.95033 1 1 0 - 1653 524 14 0.417 42.94131 60.10757 31.79808 1 1 0 - 1654 525 13 -0.834 50.10604 48.47250 49.62054 1 0 -2 - 1655 525 14 0.417 50.96037 48.77303 49.31064 1 0 -2 - 1656 525 14 0.417 50.19320 48.44287 50.57331 1 0 -2 - 1657 526 13 -0.834 54.68660 60.38920 43.62499 0 0 0 - 1658 526 14 0.417 54.62862 59.85089 42.83561 0 0 0 - 1659 526 14 0.417 53.78667 60.44045 43.94712 0 0 0 - 1660 527 13 -0.834 56.35115 44.75736 40.87552 0 -1 -1 - 1661 527 14 0.417 56.99705 44.99197 41.54186 0 -1 -1 - 1662 527 14 0.417 55.55387 44.56808 41.37024 0 -1 -1 - 1663 528 13 -0.834 48.77009 62.36934 40.44473 0 -1 0 - 1664 528 14 0.417 49.30266 62.60520 41.20432 0 -1 0 - 1665 528 14 0.417 49.04689 62.97756 39.75939 0 -1 0 - 1666 529 13 -0.834 45.88757 58.55209 41.94547 0 1 0 - 1667 529 14 0.417 46.76719 58.27665 42.20365 0 1 0 - 1668 529 14 0.417 45.35604 57.75963 42.02128 0 1 0 - 1669 530 13 -0.834 39.44116 52.22097 43.65725 1 0 2 - 1670 530 14 0.417 39.30570 52.06689 44.59221 1 0 2 - 1671 530 14 0.417 38.61744 52.60378 43.35530 1 0 2 - 1672 531 13 -0.834 43.95976 66.73852 41.23250 1 0 1 - 1673 531 14 0.417 44.64454 67.13772 40.69588 1 0 1 - 1674 531 14 0.417 43.40678 67.47232 41.50081 1 0 1 - 1675 532 13 -0.834 62.99634 65.50241 54.70446 0 -1 -1 - 1676 532 14 0.417 63.58398 64.98613 55.25617 0 -1 -1 - 1677 532 14 0.417 62.12519 65.14960 54.88585 0 -1 -1 - 1678 533 13 -0.834 62.92898 53.27582 44.77167 0 0 0 - 1679 533 14 0.417 62.08998 53.60880 45.09018 0 0 0 - 1680 533 14 0.417 62.85751 52.32504 44.85618 0 0 0 - 1681 534 13 -0.834 63.31201 43.08081 48.29805 -1 0 -1 - 1682 534 14 0.417 63.01276 42.23705 47.95930 -1 0 -1 - 1683 534 14 0.417 63.67142 43.53221 47.53431 -1 0 -1 - 1684 535 13 -0.834 47.11867 63.34781 55.06249 0 0 -1 - 1685 535 14 0.417 47.19267 64.30022 55.00160 0 0 -1 - 1686 535 14 0.417 46.22495 63.15783 54.77716 0 0 -1 - 1687 536 13 -0.834 60.37216 67.91341 52.27568 -1 0 0 - 1688 536 14 0.417 61.05051 68.14950 52.90839 -1 0 0 - 1689 536 14 0.417 60.81546 67.93922 51.42771 -1 0 0 - 1690 537 13 -0.834 60.04315 43.26291 35.25445 -1 1 1 - 1691 537 14 0.417 60.42501 44.05815 35.62593 -1 1 1 - 1692 537 14 0.417 60.79709 42.72574 35.01102 -1 1 1 - 1693 538 13 -0.834 53.03851 55.52589 47.75769 0 0 -1 - 1694 538 14 0.417 53.93635 55.46537 47.43136 0 0 -1 - 1695 538 14 0.417 52.51527 55.73342 46.98347 0 0 -1 - 1696 539 13 -0.834 37.91895 50.43697 56.37325 0 0 0 - 1697 539 14 0.417 37.51622 49.56884 56.35299 0 0 0 - 1698 539 14 0.417 38.37591 50.50915 55.53527 0 0 0 - 1699 540 13 -0.834 50.50006 63.56852 38.27177 1 1 0 - 1700 540 14 0.417 50.22462 63.18436 37.43944 1 1 0 - 1701 540 14 0.417 51.44083 63.71275 38.16986 1 1 0 - 1702 541 13 -0.834 49.44600 43.95446 42.01861 0 0 1 - 1703 541 14 0.417 49.59639 44.80378 41.60354 0 0 1 - 1704 541 14 0.417 49.73882 44.07372 42.92211 0 0 1 - 1705 542 13 -0.834 50.98365 47.23031 39.51901 1 0 1 - 1706 542 14 0.417 51.18743 48.09631 39.16579 1 0 1 - 1707 542 14 0.417 50.03928 47.13635 39.39410 1 0 1 - 1708 543 13 -0.834 45.54625 60.20130 44.30493 0 0 2 - 1709 543 14 0.417 46.27140 60.62480 43.84553 0 0 2 - 1710 543 14 0.417 45.09838 59.69256 43.62904 0 0 2 - 1711 544 13 -0.834 60.48207 53.69772 48.42686 0 0 1 - 1712 544 14 0.417 60.03677 54.31581 49.00644 0 0 1 - 1713 544 14 0.417 59.89364 52.94407 48.38216 0 0 1 - 1714 545 13 -0.834 63.04952 45.83903 48.97963 -1 1 1 - 1715 545 14 0.417 63.88202 45.63831 49.40729 -1 1 1 - 1716 545 14 0.417 62.76408 45.00498 48.60667 -1 1 1 - 1717 546 13 -0.834 40.62890 44.95273 52.60003 2 -1 -2 - 1718 546 14 0.417 41.29110 45.55853 52.26721 2 -1 -2 - 1719 546 14 0.417 40.33885 45.34348 53.42431 2 -1 -2 - 1720 547 13 -0.834 39.91743 46.12102 55.72693 -1 1 -1 - 1721 547 14 0.417 40.70381 45.68274 56.05216 -1 1 -1 - 1722 547 14 0.417 39.19323 45.65943 56.14967 -1 1 -1 - 1723 548 13 -0.834 42.06829 45.07566 41.79962 0 0 -1 - 1724 548 14 0.417 41.61985 45.91039 41.93531 0 0 -1 - 1725 548 14 0.417 41.86481 44.56390 42.58253 0 0 -1 - 1726 549 13 -0.834 44.17588 49.40877 37.86902 1 1 0 - 1727 549 14 0.417 43.85185 49.35470 38.76808 1 1 0 - 1728 549 14 0.417 43.95346 48.56183 37.48242 1 1 0 - 1729 550 13 -0.834 52.64793 63.92130 45.68237 0 1 0 - 1730 550 14 0.417 52.63502 62.96908 45.58561 0 1 0 - 1731 550 14 0.417 52.43571 64.07178 46.60356 0 1 0 - 1732 551 13 -0.834 51.57615 43.64864 38.83377 1 1 0 - 1733 551 14 0.417 51.74260 43.03820 38.11551 1 1 0 - 1734 551 14 0.417 52.20192 44.35945 38.69449 1 1 0 - 1735 552 13 -0.834 62.02099 63.12241 47.73587 0 1 0 - 1736 552 14 0.417 61.17806 62.75352 47.99973 0 1 0 - 1737 552 14 0.417 62.48263 62.39363 47.32116 0 1 0 - 1738 553 13 -0.834 38.41497 51.40373 50.93034 1 1 0 - 1739 553 14 0.417 37.60807 51.12879 50.49494 1 1 0 - 1740 553 14 0.417 38.99796 51.65996 50.21571 1 1 0 - 1741 554 13 -0.834 51.96339 44.25313 49.02477 0 0 0 - 1742 554 14 0.417 52.81680 44.60151 49.28274 0 0 0 - 1743 554 14 0.417 52.16570 43.57682 48.37831 0 0 0 - 1744 555 13 -0.834 43.58422 51.42052 49.88959 0 1 -1 - 1745 555 14 0.417 42.74054 51.00549 50.06897 0 1 -1 - 1746 555 14 0.417 44.20160 50.69175 49.82657 0 1 -1 - 1747 556 13 -0.834 52.39836 53.43568 49.29165 1 0 -1 - 1748 556 14 0.417 51.88756 52.90169 48.68323 1 0 -1 - 1749 556 14 0.417 52.64451 54.20889 48.78391 1 0 -1 - 1750 557 13 -0.834 57.76885 46.61656 49.32842 0 1 0 - 1751 557 14 0.417 57.83718 46.26991 48.43879 0 1 0 - 1752 557 14 0.417 58.65246 46.53329 49.68694 0 1 0 - 1753 558 13 -0.834 59.20868 56.75211 36.79427 0 1 -1 - 1754 558 14 0.417 59.74268 56.20033 36.22276 0 1 -1 - 1755 558 14 0.417 58.75094 56.13459 37.36470 0 1 -1 - 1756 559 13 -0.834 51.74055 42.45875 36.24184 0 1 1 - 1757 559 14 0.417 51.04879 41.79745 36.22260 0 1 1 - 1758 559 14 0.417 52.52794 41.99055 35.96429 0 1 1 - 1759 560 13 -0.834 56.37631 67.32150 33.05439 -1 0 1 - 1760 560 14 0.417 56.52797 66.39716 33.25152 -1 0 1 - 1761 560 14 0.417 56.88845 67.79399 33.71068 -1 0 1 - 1762 561 13 -0.834 54.61713 62.99597 56.69158 0 1 -1 - 1763 561 14 0.417 54.59393 63.94258 56.83172 0 1 -1 - 1764 561 14 0.417 54.12883 62.86158 55.87934 0 1 -1 - 1765 562 13 -0.834 59.12420 67.78462 34.49420 0 -1 1 - 1766 562 14 0.417 59.61921 67.94665 33.69111 0 -1 1 - 1767 562 14 0.417 59.22686 41.21594 35.00547 0 0 1 - 1768 563 13 -0.834 63.35827 53.14027 38.43168 -1 0 0 - 1769 563 14 0.417 62.48186 53.05933 38.05538 -1 0 0 - 1770 563 14 0.417 63.87715 53.55740 37.74392 -1 0 0 - 1771 564 13 -0.834 50.05518 64.80335 44.94078 1 0 -2 - 1772 564 14 0.417 50.16173 65.71408 44.66608 1 0 -2 - 1773 564 14 0.417 50.94818 64.48993 45.08424 1 0 -2 - 1774 565 13 -0.834 61.91076 61.67486 44.00650 0 -3 0 - 1775 565 14 0.417 61.40514 60.86646 44.09077 0 -3 0 - 1776 565 14 0.417 62.58390 61.60857 44.68380 0 -3 0 - 1777 566 13 -0.834 61.53884 41.33016 50.02212 -1 0 -1 - 1778 566 14 0.417 61.75835 68.35836 49.15591 -1 -1 -1 - 1779 566 14 0.417 62.19075 42.01255 50.18215 -1 0 -1 - 1780 567 13 -0.834 54.81641 49.94673 49.66324 0 -1 -1 - 1781 567 14 0.417 54.81533 50.72359 50.22249 0 -1 -1 - 1782 567 14 0.417 53.94410 49.93341 49.26932 0 -1 -1 - 1783 568 13 -0.834 60.68933 64.00249 53.56679 -1 -1 -1 - 1784 568 14 0.417 60.72666 63.10922 53.90872 -1 -1 -1 - 1785 568 14 0.417 60.37485 64.52808 54.30238 -1 -1 -1 - 1786 569 13 -0.834 55.51605 42.60469 53.96890 0 -1 0 - 1787 569 14 0.417 55.82084 42.66633 53.06360 0 -1 0 - 1788 569 14 0.417 54.99565 43.39708 54.10137 0 -1 0 - 1789 570 13 -0.834 43.79008 68.23755 52.31171 2 -1 1 - 1790 570 14 0.417 43.47705 41.06627 51.42954 2 0 1 - 1791 570 14 0.417 44.72624 68.07073 52.20206 2 -1 1 - 1792 571 13 -0.834 40.19615 44.94623 32.57234 0 0 1 - 1793 571 14 0.417 40.90940 45.49825 32.25173 0 0 1 - 1794 571 14 0.417 40.42796 44.75889 33.48196 0 0 1 - 1795 572 13 -0.834 51.93921 56.60019 36.60262 -1 0 1 - 1796 572 14 0.417 51.78399 56.35099 37.51368 -1 0 1 - 1797 572 14 0.417 51.06469 56.74242 36.24039 -1 0 1 - 1798 573 13 -0.834 61.66916 50.48338 53.29865 -1 0 -2 - 1799 573 14 0.417 61.63036 50.41309 54.25248 -1 0 -2 - 1800 573 14 0.417 60.77283 50.69388 53.03687 -1 0 -2 - 1801 574 13 -0.834 51.74160 54.87485 56.16871 0 -1 0 - 1802 574 14 0.417 50.91429 55.26706 56.44795 0 -1 0 - 1803 574 14 0.417 51.91124 55.25931 55.30869 0 -1 0 - 1804 575 13 -0.834 40.85698 68.18248 30.13155 1 -1 0 - 1805 575 14 0.417 41.30492 67.87357 56.71541 1 -1 -1 - 1806 575 14 0.417 41.55175 41.19073 30.66952 1 0 0 - 1807 576 13 -0.834 50.89809 58.89690 54.50288 -1 0 0 - 1808 576 14 0.417 50.06229 58.64352 54.89466 -1 0 0 - 1809 576 14 0.417 51.37024 59.33797 55.20914 -1 0 0 - 1810 577 13 -0.834 58.37524 67.95427 49.91095 0 1 0 - 1811 577 14 0.417 57.83519 41.29391 50.25604 0 2 0 - 1812 577 14 0.417 59.26942 68.19076 50.15744 0 1 0 - 1813 578 13 -0.834 51.40785 46.48357 30.68744 1 0 1 - 1814 578 14 0.417 52.21871 45.99275 30.55389 1 0 1 - 1815 578 14 0.417 50.76683 45.82189 30.94725 1 0 1 - 1816 579 13 -0.834 57.04032 43.52295 36.91237 0 0 0 - 1817 579 14 0.417 56.97310 44.35969 36.45239 0 0 0 - 1818 579 14 0.417 57.91622 43.53095 37.29833 0 0 0 - 1819 580 13 -0.834 48.05479 47.92450 33.11226 0 0 1 - 1820 580 14 0.417 47.68291 48.79527 32.97186 0 0 1 - 1821 580 14 0.417 48.92592 48.09081 33.47242 0 0 1 - 1822 581 13 -0.834 52.31083 59.89064 56.95945 1 -2 -1 - 1823 581 14 0.417 51.77727 60.32576 30.25310 1 -2 0 - 1824 581 14 0.417 52.84806 60.59010 56.58744 1 -2 -1 - 1825 582 13 -0.834 49.28190 53.14534 38.62511 0 0 1 - 1826 582 14 0.417 48.56647 53.70668 38.92395 0 0 1 - 1827 582 14 0.417 48.86634 52.52585 38.02526 0 0 1 - 1828 583 13 -0.834 48.15214 51.90611 34.43290 2 0 0 - 1829 583 14 0.417 48.57405 51.97443 33.57642 2 0 0 - 1830 583 14 0.417 47.22654 51.76503 34.23389 2 0 0 - 1831 584 13 -0.834 61.27546 54.09168 30.34511 0 1 1 - 1832 584 14 0.417 61.26898 53.84689 31.27046 0 1 1 - 1833 584 14 0.417 62.02427 53.62196 29.97785 0 1 1 - 1834 585 13 -0.834 47.15916 50.47662 53.78471 0 -1 0 - 1835 585 14 0.417 47.32648 50.93912 54.60588 0 -1 0 - 1836 585 14 0.417 46.29671 50.78520 53.50690 0 -1 0 - 1837 586 13 -0.834 58.58091 63.09753 49.23949 0 -1 1 - 1838 586 14 0.417 59.43607 63.50227 49.38484 0 -1 1 - 1839 586 14 0.417 58.76326 62.34843 48.67219 0 -1 1 - 1840 587 13 -0.834 55.82082 49.65937 30.11648 0 1 1 - 1841 587 14 0.417 56.52757 49.92139 30.70647 0 1 1 - 1842 587 14 0.417 55.68213 50.42183 56.92602 0 1 0 - 1843 588 13 -0.834 63.79581 52.53565 53.17702 0 -2 1 - 1844 588 14 0.417 36.89869 52.41207 52.35479 1 -2 1 - 1845 588 14 0.417 63.12882 51.84908 53.17487 0 -2 1 - 1846 589 13 -0.834 58.30874 56.36537 43.52715 0 0 3 - 1847 589 14 0.417 58.58025 56.80205 44.33452 0 0 3 - 1848 589 14 0.417 57.40732 56.09029 43.69457 0 0 3 - 1849 590 13 -0.834 38.42652 61.06904 33.48425 0 -2 -1 - 1850 590 14 0.417 39.08604 61.75763 33.56856 0 -2 -1 - 1851 590 14 0.417 38.90648 60.25628 33.64334 0 -2 -1 - 1852 591 13 -0.834 46.61439 51.58566 41.81121 1 -1 0 - 1853 591 14 0.417 46.97646 51.37067 42.67082 1 -1 0 - 1854 591 14 0.417 46.41089 50.73724 41.41750 1 -1 0 - 1855 592 13 -0.834 60.01555 43.31814 42.71405 1 0 1 - 1856 592 14 0.417 60.52150 42.79903 43.33920 1 0 1 - 1857 592 14 0.417 59.90024 42.74003 41.95989 1 0 1 - 1858 593 13 -0.834 44.88246 59.34852 51.75271 1 0 -1 - 1859 593 14 0.417 45.75263 59.37400 52.15069 1 0 -1 - 1860 593 14 0.417 44.67274 58.41644 51.69374 1 0 -1 - 1861 594 13 -0.834 58.22051 53.10280 51.15729 0 -1 0 - 1862 594 14 0.417 58.53381 52.60654 51.91346 0 -1 0 - 1863 594 14 0.417 58.92607 53.72100 50.96688 0 -1 0 - 1864 595 13 -0.834 52.85332 67.67658 42.66705 0 -1 0 - 1865 595 14 0.417 53.29462 67.40699 41.86157 0 -1 0 - 1866 595 14 0.417 53.28090 67.16860 43.35652 0 -1 0 - 1867 596 13 -0.834 60.42773 53.38162 37.56585 0 0 1 - 1868 596 14 0.417 60.55482 53.97513 38.30601 0 0 1 - 1869 596 14 0.417 59.53313 53.05721 37.66924 0 0 1 - 1870 597 13 -0.834 56.52028 65.87791 50.38146 0 0 1 - 1871 597 14 0.417 56.94337 66.73645 50.39389 0 0 1 - 1872 597 14 0.417 57.02985 65.35034 50.99649 0 0 1 - 1873 598 13 -0.834 54.80064 62.49993 33.68680 1 0 1 - 1874 598 14 0.417 55.58425 61.96146 33.79744 1 0 1 - 1875 598 14 0.417 55.10591 63.27334 33.21259 1 0 1 - 1876 599 13 -0.834 44.11783 61.90196 34.52932 1 1 -1 - 1877 599 14 0.417 44.98641 61.86349 34.92975 1 1 -1 - 1878 599 14 0.417 44.21923 61.44892 33.69223 1 1 -1 - 1879 600 13 -0.834 47.64060 51.80694 44.33090 -1 -1 0 - 1880 600 14 0.417 48.33775 51.24158 44.66345 -1 -1 0 - 1881 600 14 0.417 47.96940 52.69619 44.46262 -1 -1 0 - 1882 601 13 -0.834 56.93644 64.17109 32.73010 0 -2 0 - 1883 601 14 0.417 57.35484 63.79547 31.95543 0 -2 0 - 1884 601 14 0.417 57.46604 63.85913 33.46389 0 -2 0 - 1885 602 13 -0.834 40.19928 60.95715 53.68963 1 0 -1 - 1886 602 14 0.417 41.08822 60.76154 53.39341 1 0 -1 - 1887 602 14 0.417 39.80336 61.43545 52.96114 1 0 -1 - 1888 603 13 -0.834 56.02366 41.52320 41.07986 0 1 0 - 1889 603 14 0.417 55.42766 41.48842 40.33165 0 1 0 - 1890 603 14 0.417 55.93467 42.41489 41.41631 0 1 0 - 1891 604 13 -0.834 52.35261 67.43639 29.83633 -1 0 0 - 1892 604 14 0.417 53.08703 67.77971 56.69878 -1 0 -1 - 1893 604 14 0.417 51.97673 68.20568 30.26426 -1 0 0 - 1894 605 13 -0.834 51.14102 49.90060 37.90539 1 0 1 - 1895 605 14 0.417 51.41236 49.08269 37.48865 1 0 1 - 1896 605 14 0.417 50.32915 50.13989 37.45830 1 0 1 - 1897 606 13 -0.834 48.40753 57.18555 40.43062 0 0 0 - 1898 606 14 0.417 47.74030 57.19949 39.74445 0 0 0 - 1899 606 14 0.417 48.68357 58.09814 40.51553 0 0 0 - 1900 607 13 -0.834 38.43185 54.52830 40.23522 1 -2 1 - 1901 607 14 0.417 37.76601 54.24704 40.86274 1 -2 1 - 1902 607 14 0.417 37.95756 54.62565 39.40951 1 -2 1 - 1903 608 13 -0.834 52.97765 52.38562 41.57118 0 0 0 - 1904 608 14 0.417 52.16773 52.00413 41.23247 0 0 0 - 1905 608 14 0.417 53.62059 51.67937 41.50742 0 0 0 - 1906 609 13 -0.834 52.82978 61.35779 35.40768 0 1 -2 - 1907 609 14 0.417 53.63682 61.71145 35.03372 0 1 -2 - 1908 609 14 0.417 53.10766 60.57217 35.87865 0 1 -2 - 1909 610 13 -0.834 55.37636 43.79165 30.66790 0 0 0 - 1910 610 14 0.417 55.82860 43.25432 31.31827 0 0 0 - 1911 610 14 0.417 55.97415 44.52040 30.50110 0 0 0 - 1912 611 13 -0.834 37.90570 54.55715 45.50029 1 -2 -1 - 1913 611 14 0.417 37.12871 54.09851 45.18066 1 -2 -1 - 1914 611 14 0.417 38.24821 53.99402 46.19441 1 -2 -1 - 1915 612 13 -0.834 60.01324 50.96528 45.16358 1 1 0 - 1916 612 14 0.417 59.85669 51.13906 44.23539 1 1 0 - 1917 612 14 0.417 59.48415 50.19096 45.35532 1 1 0 - 1918 613 13 -0.834 38.84394 52.32942 30.93040 2 1 0 - 1919 613 14 0.417 38.51878 51.61086 30.38802 2 1 0 - 1920 613 14 0.417 38.41000 53.10831 30.58218 2 1 0 - 1921 614 13 -0.834 38.99542 61.66171 44.80992 1 0 2 - 1922 614 14 0.417 38.78488 60.74588 44.99207 1 0 2 - 1923 614 14 0.417 39.68427 61.62223 44.14648 1 0 2 - 1924 615 13 -0.834 57.70791 41.72720 55.47643 0 1 -2 - 1925 615 14 0.417 57.25844 41.36846 56.24163 0 1 -2 - 1926 615 14 0.417 57.00496 41.93588 54.86116 0 1 -2 - 1927 616 13 -0.834 58.08999 54.20225 35.53764 0 -1 0 - 1928 616 14 0.417 58.28608 53.46338 36.11372 0 -1 0 - 1929 616 14 0.417 57.15628 54.11553 35.34551 0 -1 0 - 1930 617 13 -0.834 53.05217 52.71850 54.07873 0 0 -1 - 1931 617 14 0.417 52.72353 53.45661 54.59199 0 0 -1 - 1932 617 14 0.417 52.69237 51.94509 54.51306 0 0 -1 - 1933 618 13 -0.834 49.92059 65.13477 35.13462 0 1 1 - 1934 618 14 0.417 50.86780 65.25694 35.19866 0 1 1 - 1935 618 14 0.417 49.79534 64.18846 35.20565 0 1 1 - 1936 619 13 -0.834 41.32410 62.50943 46.98364 1 -1 0 - 1937 619 14 0.417 40.63048 62.20572 46.39807 1 -1 0 - 1938 619 14 0.417 41.96090 61.79482 46.99226 1 -1 0 - 1939 620 13 -0.834 53.94559 67.39201 49.11860 0 0 0 - 1940 620 14 0.417 54.46912 66.60137 48.98810 0 0 0 - 1941 620 14 0.417 54.03461 67.58755 50.05138 0 0 0 - 1942 621 13 -0.834 62.73724 52.28919 56.37358 -2 0 0 - 1943 621 14 0.417 61.94239 51.76764 56.26203 -2 0 0 - 1944 621 14 0.417 63.44036 51.64333 56.44233 -2 0 0 - 1945 622 13 -0.834 40.38118 67.16060 39.18721 2 1 1 - 1946 622 14 0.417 41.33280 67.21360 39.09858 2 1 1 - 1947 622 14 0.417 40.05780 67.12713 38.28691 2 1 1 - 1948 623 13 -0.834 62.86517 42.00727 34.57539 -1 0 -1 - 1949 623 14 0.417 63.37239 42.81882 34.59420 -1 0 -1 - 1950 623 14 0.417 63.40838 41.39624 34.07760 -1 0 -1 - 1951 624 13 -0.834 45.52270 49.32960 34.34348 1 -1 1 - 1952 624 14 0.417 45.92383 49.19413 33.48500 1 -1 1 - 1953 624 14 0.417 45.24004 50.24407 34.33468 1 -1 1 - 1954 625 13 -0.834 61.03811 44.77668 56.49913 1 1 0 - 1955 625 14 0.417 60.72892 43.87199 56.45248 1 1 0 - 1956 625 14 0.417 60.93423 45.11202 55.60864 1 1 0 - 1957 626 13 -0.834 37.82896 51.65548 39.75440 0 1 1 - 1958 626 14 0.417 37.05574 52.05171 39.35268 0 1 1 - 1959 626 14 0.417 38.46628 52.36806 39.80236 0 1 1 - 1960 627 13 -0.834 57.87448 65.36125 35.56679 -1 -1 0 - 1961 627 14 0.417 58.45940 64.84211 35.01489 -1 -1 0 - 1962 627 14 0.417 58.01580 66.26448 35.28319 -1 -1 0 - 1963 628 13 -0.834 41.02352 64.37669 36.41484 0 0 1 - 1964 628 14 0.417 40.85775 63.95254 37.25679 0 0 1 - 1965 628 14 0.417 41.32667 63.66948 35.84545 0 0 1 - 1966 629 13 -0.834 48.62923 67.86173 41.06030 1 0 1 - 1967 629 14 0.417 48.15680 41.13844 41.58283 1 1 1 - 1968 629 14 0.417 47.94185 67.35115 40.63246 1 0 1 - 1969 630 13 -0.834 57.99331 55.69311 47.88478 1 2 0 - 1970 630 14 0.417 57.70999 55.65425 48.79826 1 2 0 - 1971 630 14 0.417 57.37284 55.13407 47.41709 1 2 0 - 1972 631 13 -0.834 48.67013 62.47689 45.75332 -1 -1 0 - 1973 631 14 0.417 49.00300 63.35392 45.56291 -1 -1 0 - 1974 631 14 0.417 48.17776 62.23177 44.96992 -1 -1 0 - 1975 632 13 -0.834 63.70160 54.96100 33.30497 -1 0 0 - 1976 632 14 0.417 64.21034 55.41699 32.63452 -1 0 0 - 1977 632 14 0.417 36.84822 54.18301 33.51151 0 0 0 - 1978 633 13 -0.834 61.71933 50.02843 40.52579 1 0 -1 - 1979 633 14 0.417 61.89605 49.89083 39.59516 1 0 -1 - 1980 633 14 0.417 61.20325 50.83404 40.55551 1 0 -1 - 1981 634 13 -0.834 49.51254 64.46386 53.41539 0 -1 -1 - 1982 634 14 0.417 48.93704 63.81647 53.00803 0 -1 -1 - 1983 634 14 0.417 49.96102 63.98252 54.11066 0 -1 -1 - 1984 635 13 -0.834 49.54405 44.64373 31.53722 1 2 1 - 1985 635 14 0.417 49.17415 44.45447 32.39954 1 2 1 - 1986 635 14 0.417 48.78808 44.87386 30.99705 1 2 1 - 1987 636 13 -0.834 55.54392 65.92737 37.61921 0 -1 -1 - 1988 636 14 0.417 56.11408 65.75233 38.36791 0 -1 -1 - 1989 636 14 0.417 56.12096 66.32174 36.96519 0 -1 -1 - 1990 637 13 -0.834 55.12269 51.83986 35.86341 1 0 1 - 1991 637 14 0.417 55.56426 51.26412 35.23910 1 0 1 - 1992 637 14 0.417 54.23658 51.93728 35.51477 1 0 1 - 1993 638 13 -0.834 55.63681 62.23759 37.50835 1 -1 0 - 1994 638 14 0.417 55.30920 61.35525 37.33403 1 -1 0 - 1995 638 14 0.417 56.23965 62.41667 36.78672 1 -1 0 - 1996 639 13 -0.834 39.91450 42.04260 35.59226 0 0 0 - 1997 639 14 0.417 39.72903 41.27571 36.13422 0 0 0 - 1998 639 14 0.417 39.23583 42.02933 34.91737 0 0 0 - 1999 640 13 -0.834 48.26433 59.84813 40.16126 0 1 0 - 2000 640 14 0.417 48.74870 60.67004 40.23938 0 1 0 - 2001 640 14 0.417 47.50743 60.06639 39.61748 0 1 0 - 2002 641 13 -0.834 57.35097 49.28414 48.37687 1 1 1 - 2003 641 14 0.417 57.35715 48.51028 48.94022 1 1 1 - 2004 641 14 0.417 56.55074 49.75049 48.61854 1 1 1 - -Velocities - - 1 -0.000671 -0.002823 0.003832 - 2 -0.001597 0.002405 -0.003777 - 3 0.005494 0.003807 -0.002300 - 4 -0.000077 0.004524 -0.000287 - 5 0.003116 -0.007135 -0.034325 - 6 -0.006676 0.004889 -0.001939 - 7 0.003499 -0.004774 0.000159 - 8 -0.003460 0.000694 0.000994 - 9 -0.000065 -0.001353 -0.002848 - 10 -0.001260 -0.002649 0.000699 - 11 -0.002820 -0.002457 -0.005671 - 12 0.005156 -0.005914 0.000984 - 13 -0.002342 -0.001592 0.004306 - 14 0.004397 -0.000231 0.003308 - 15 -0.003258 -0.000006 0.001838 - 16 -0.001637 -0.004429 0.003154 - 17 0.007073 -0.000472 -0.003331 - 18 -0.003380 -0.001390 0.005013 - 19 -0.011019 -0.005332 -0.010451 - 20 -0.005433 0.000844 0.004938 - 21 0.002988 0.000244 -0.009941 - 22 -0.003695 0.006546 -0.007678 - 23 0.009473 0.023276 0.019457 - 24 -0.010016 -0.024193 0.018017 - 25 0.004015 0.008726 -0.000397 - 26 -0.001741 -0.001861 0.007862 - 27 -0.009771 -0.011577 -0.005703 - 28 0.003573 0.006265 -0.005932 - 29 0.004789 0.001987 -0.004620 - 30 0.008858 -0.001064 -0.001455 - 31 -0.001403 0.000613 0.002330 - 32 -0.005808 -0.001620 0.000816 - 33 -0.004160 0.001188 -0.019638 - 34 -0.006899 0.006285 0.013256 - 35 0.000717 -0.000432 -0.006883 - 36 0.002110 0.002628 -0.004683 - 37 0.000765 -0.007298 0.000289 - 38 -0.000128 -0.002893 0.004065 - 39 -0.000411 -0.021741 0.010968 - 40 0.002858 0.000302 0.000042 - 41 0.014233 -0.004599 -0.004060 - 42 -0.001473 -0.003572 -0.006228 - 43 0.009129 -0.002755 0.001456 - 44 0.003931 0.000151 0.003472 - 45 0.001621 0.005391 -0.006087 - 46 -0.004269 -0.001973 0.002735 - 47 -0.006898 -0.001187 -0.003394 - 48 -0.008556 -0.000163 -0.001387 - 49 -0.000633 -0.001754 0.011460 - 50 0.004854 -0.002902 -0.005057 - 51 0.000678 0.003272 0.006218 - 52 0.006502 0.006365 -0.000215 - 53 0.005708 0.012368 0.002955 - 54 0.008627 -0.007839 0.003177 - 55 0.004394 0.000132 0.002346 - 56 -0.004641 0.009426 -0.005548 - 57 -0.004801 -0.024766 0.002851 - 58 -0.002703 0.001589 0.007521 - 59 0.023718 -0.006559 0.003743 - 60 -0.010013 -0.042894 -0.029745 - 61 0.016140 -0.000721 -0.001747 - 62 -0.004871 0.002439 0.001990 - 63 0.009632 0.007144 0.001203 - 64 -0.001150 0.001648 -0.003018 - 65 0.006658 -0.002268 0.006874 - 66 -0.002617 0.003321 0.002230 - 67 -0.000803 0.002802 0.003258 - 68 -0.000984 -0.001579 -0.001813 - 69 0.001316 0.000607 0.003431 - 70 -0.010901 0.000580 -0.004134 - 71 0.005370 -0.003909 0.013130 - 72 -0.012282 0.007114 -0.015100 - 73 0.004641 -0.007554 0.004302 - 74 0.017455 0.013344 0.004896 - 75 0.006200 0.026885 0.020665 - 76 -0.010372 0.000470 -0.005601 - 77 -0.003368 -0.004484 0.010962 - 78 0.012416 -0.004728 0.000719 - 79 -0.005789 0.005198 -0.007541 - 80 0.005480 -0.004049 0.003455 - 81 -0.004935 0.005839 -0.006405 - 82 0.001157 -0.011200 0.018491 - 83 -0.029013 -0.016935 0.021131 - 84 -0.020335 0.020972 0.006071 - 85 0.003304 0.007374 -0.005056 - 86 0.029227 0.010776 -0.013183 - 87 0.001651 0.006570 -0.002085 - 88 0.001533 -0.009172 0.007562 - 89 0.018153 -0.022223 0.015786 - 90 -0.010012 -0.004911 0.002561 - 91 0.000435 0.003941 -0.005468 - 92 0.003301 0.001183 -0.006999 - 93 0.006788 0.011331 -0.004427 - 94 0.001392 0.005663 -0.002907 - 95 -0.001849 -0.002229 -0.003422 - 96 -0.000820 0.005872 0.004561 - 97 -0.003264 0.002461 -0.009257 - 98 0.000160 0.016954 -0.015355 - 99 -0.006597 0.011858 0.000426 - 100 0.001816 -0.005854 -0.001317 - 101 -0.001936 -0.006103 0.018111 - 102 0.024621 -0.022735 -0.000704 - 103 -0.001102 0.008384 -0.003086 - 104 0.012559 0.004375 -0.000361 - 105 0.008377 0.014814 -0.037755 - 106 -0.002851 -0.000200 -0.000722 - 107 0.010701 0.006888 -0.007831 - 108 -0.008490 0.011514 0.009399 - 109 -0.001181 0.001853 0.002176 - 110 -0.018912 -0.023868 0.006706 - 111 -0.000415 -0.001525 0.005751 - 112 -0.001172 0.001329 -0.001270 - 113 -0.006700 -0.006243 -0.006459 - 114 0.000018 0.001429 0.001376 - 115 0.001269 0.002521 0.005249 - 116 -0.002179 0.015666 0.006861 - 117 -0.007158 0.000981 0.007353 - 118 0.001047 0.000840 -0.004404 - 119 0.000974 -0.012527 0.005053 - 120 0.026729 0.008884 -0.003350 - 121 0.001181 -0.004040 -0.002037 - 122 0.006556 -0.007438 0.002656 - 123 0.005056 -0.015002 -0.003727 - 124 -0.002704 -0.003683 -0.001021 - 125 0.025048 0.007258 0.008873 - 126 0.019645 -0.020824 -0.002539 - 127 0.000061 0.001072 0.002612 - 128 0.005132 0.013203 0.018763 - 129 0.033473 0.004804 0.018651 - 130 -0.003459 -0.000309 -0.001348 - 131 -0.008088 0.023660 0.011047 - 132 0.010962 0.031994 0.008711 - 133 0.000181 -0.002894 -0.001677 - 134 0.024049 -0.000711 -0.009405 - 135 0.018702 0.003422 -0.019522 - 136 -0.000836 -0.003270 -0.005700 - 137 0.012246 0.016524 0.001525 - 138 0.006270 -0.011288 0.002224 - 139 -0.005169 0.005097 -0.000688 - 140 -0.006982 0.003044 -0.001383 - 141 0.012227 0.012767 0.004047 - 142 -0.001169 0.006070 -0.007989 - 143 0.005451 0.002569 -0.009841 - 144 0.001825 -0.002822 -0.005341 - 145 0.000911 0.004242 -0.002026 - 146 0.012072 -0.001187 -0.010498 - 147 0.007366 0.005541 0.012099 - 148 0.009820 0.000588 0.001087 - 149 0.013758 0.005140 0.015262 - 150 0.015580 0.003311 0.013079 - 151 0.002031 0.000411 0.003403 - 152 -0.001996 0.003750 0.007387 - 153 0.000790 0.000281 -0.000919 - 154 -0.004168 0.001886 -0.004993 - 155 -0.011049 0.015294 0.001052 - 156 -0.012308 0.010348 -0.003128 - 157 -0.001609 -0.004040 -0.002294 - 158 -0.005715 -0.015529 -0.005700 - 159 0.014489 0.026653 0.004024 - 160 0.004070 0.000866 0.003373 - 161 0.004691 0.005062 0.002569 - 162 0.007082 -0.019961 -0.026174 - 163 0.005501 0.000902 -0.001325 - 164 0.007503 0.001448 -0.001472 - 165 0.013628 0.003649 -0.005952 - 166 -0.000639 0.003162 -0.007271 - 167 0.007342 -0.011001 -0.016849 - 168 -0.018400 -0.004772 0.020839 - 169 0.000214 -0.000386 0.002706 - 170 -0.005862 0.010449 -0.003793 - 171 -0.013612 0.011870 -0.006417 - 172 -0.005485 0.006465 0.005343 - 173 0.001788 0.008428 0.005641 - 174 -0.018354 0.029579 0.010717 - 175 0.002627 -0.000754 0.000071 - 176 -0.018080 0.018546 0.001794 - 177 0.006754 -0.000962 -0.007786 - 178 0.002343 0.002166 0.004945 - 179 -0.001724 0.003155 0.010761 - 180 0.010728 0.003441 0.001544 - 181 -0.000849 -0.002856 0.001461 - 182 0.009366 -0.003672 -0.001935 - 183 0.016615 -0.001746 0.005238 - 184 -0.002730 -0.000316 -0.004583 - 185 -0.014755 -0.011310 0.003338 - 186 0.005862 0.008235 -0.003200 - 187 -0.003189 -0.006285 0.009536 - 188 -0.005114 -0.007060 0.006450 - 189 -0.000516 -0.008757 0.009854 - 190 -0.000859 0.005266 0.001864 - 191 0.003108 -0.007021 0.009190 - 192 -0.015949 -0.002050 0.007021 - 193 -0.007008 0.002608 -0.004583 - 194 -0.020431 -0.004004 0.008047 - 195 -0.000364 0.001236 -0.011425 - 196 0.002420 0.006931 0.002031 - 197 0.007178 0.006129 0.009924 - 198 -0.005981 0.016623 -0.013067 - 199 0.003142 -0.001394 -0.001846 - 200 0.011374 -0.002895 -0.000674 - 201 0.032698 -0.002552 0.007288 - 202 -0.005709 0.000071 0.005037 - 203 -0.013193 -0.012592 -0.008102 - 204 -0.008194 0.014723 0.003840 - 205 -0.003270 -0.006146 0.004301 - 206 0.004399 -0.010132 -0.001197 - 207 -0.030308 0.012803 0.003540 - 208 0.002110 0.002374 0.006075 - 209 -0.000845 -0.004182 -0.002795 - 210 0.002582 -0.004671 0.002224 - 211 -0.003768 0.002130 0.001339 - 212 0.022509 0.017397 0.002782 - 213 0.020609 0.006682 -0.014082 - 214 0.003956 0.004282 -0.005023 - 215 0.007499 0.004128 0.002237 - 216 0.034882 -0.005096 0.008948 - 217 -0.002552 -0.000287 -0.001907 - 218 0.025445 0.005560 -0.016526 - 219 0.002741 0.000814 -0.004654 - 220 0.002162 -0.001203 0.000936 - 221 0.004071 0.004725 0.001938 - 222 0.002393 -0.013063 -0.003950 - 223 -0.001609 -0.003218 -0.004310 - 224 -0.012550 0.009033 -0.007868 - 225 0.014344 0.000886 -0.013005 - 226 0.005863 0.010335 -0.003424 - 227 0.011104 -0.005602 -0.012415 - 228 0.001222 0.002408 0.001546 - 229 -0.002038 0.001858 0.002991 - 230 -0.017517 -0.020932 0.016099 - 231 0.005257 0.011588 -0.018236 - 232 -0.002660 -0.006193 0.003186 - 233 -0.021995 0.012375 0.004372 - 234 -0.013906 0.028004 -0.004997 - 235 0.002339 -0.001255 -0.003548 - 236 0.001689 0.005243 -0.006337 - 237 0.000498 -0.007782 -0.015260 - 238 0.001142 0.002234 0.003408 - 239 0.007521 0.004622 -0.003272 - 240 -0.001154 0.006952 0.006739 - 241 -0.000938 -0.004609 0.002499 - 242 0.004903 0.001117 0.013021 - 243 0.008126 -0.013873 -0.001075 - 244 -0.004097 0.002491 -0.002459 - 245 0.002093 -0.002989 0.010881 - 246 0.008552 0.010436 0.008330 - 247 -0.000211 0.002295 0.001935 - 248 0.004346 0.003486 0.008405 - 249 -0.006182 0.002873 -0.007955 - 250 0.002466 0.001439 -0.002302 - 251 -0.003246 0.007233 0.009469 - 252 -0.002606 0.002646 0.002563 - 253 0.000833 -0.001794 -0.003483 - 254 -0.001066 -0.001277 -0.012569 - 255 -0.003354 -0.002604 -0.016130 - 256 0.007379 0.006324 -0.003535 - 257 0.025411 0.006788 -0.010928 - 258 0.011648 0.000201 0.004051 - 259 -0.000385 -0.000823 -0.000593 - 260 -0.001070 -0.019569 0.006235 - 261 0.011350 0.009136 0.002805 - 262 -0.001688 0.002178 0.004704 - 263 -0.011748 0.007674 0.002198 - 264 -0.005358 0.003728 -0.002879 - 265 -0.004209 0.000686 -0.004990 - 266 0.000586 0.011928 0.008080 - 267 0.004512 -0.002493 -0.000297 - 268 -0.000130 0.007801 -0.005732 - 269 -0.006259 -0.000991 -0.001515 - 270 0.015560 -0.011483 0.001826 - 271 -0.003544 0.003178 0.000326 - 272 0.006639 0.005731 0.008812 - 273 -0.009361 -0.001371 -0.002830 - 274 -0.000226 0.001739 0.001787 - 275 -0.001846 -0.005637 -0.002071 - 276 0.009461 0.005629 -0.001253 - 277 0.003294 -0.005377 -0.000680 - 278 0.027740 0.013288 0.002669 - 279 0.003403 0.012169 -0.019874 - 280 -0.001383 0.000386 -0.006636 - 281 -0.005910 0.003429 -0.006992 - 282 0.002649 -0.004178 -0.006969 - 283 0.004768 -0.001680 0.000104 - 284 -0.012916 0.017467 -0.012201 - 285 0.010278 -0.007970 0.003734 - 286 0.000005 0.000300 0.006224 - 287 0.003150 -0.001535 0.007443 - 288 -0.000547 -0.003737 0.010794 - 289 0.003054 0.005656 0.000426 - 290 0.006673 0.002252 0.007300 - 291 0.004185 0.001696 0.005292 - 292 -0.001277 -0.005156 -0.001765 - 293 0.005969 -0.004326 -0.002540 - 294 -0.026915 -0.005145 0.019233 - 295 -0.003352 -0.000356 -0.001610 - 296 -0.023375 -0.003718 -0.017075 - 297 0.006387 -0.025086 0.000315 - 298 -0.005064 0.001395 0.004436 - 299 -0.004111 0.000853 -0.032909 - 300 0.000933 0.005949 0.017391 - 301 0.000607 0.002490 -0.002786 - 302 0.002638 0.008857 0.008537 - 303 0.001294 0.011357 -0.003275 - 304 -0.001798 -0.003127 -0.000795 - 305 -0.003320 0.000996 0.004122 - 306 -0.008728 -0.000634 0.002033 - 307 -0.003535 -0.002662 -0.002777 - 308 -0.005954 -0.002781 -0.004403 - 309 -0.002147 -0.001477 -0.001223 - 310 -0.002595 -0.001397 0.002359 - 311 -0.003605 -0.000224 0.015269 - 312 -0.014002 -0.002828 0.000027 - 313 0.001583 -0.005357 0.002380 - 314 -0.002955 -0.014106 -0.011581 - 315 0.000151 -0.006411 0.002865 - 316 0.004278 -0.004088 0.000114 - 317 -0.019291 0.001584 0.015204 - 318 -0.013439 -0.000674 0.010987 - 319 0.000024 0.000995 0.005326 - 320 -0.009041 0.020464 0.014139 - 321 0.004208 -0.003482 0.004723 - 322 0.001489 -0.003292 0.000500 - 323 0.000364 0.006211 0.006844 - 324 0.007467 0.021162 -0.001636 - 325 0.009527 -0.000863 -0.005483 - 326 -0.009936 0.006496 -0.014136 - 327 -0.007595 -0.006469 -0.002090 - 328 -0.002856 -0.010388 -0.000678 - 329 -0.026693 -0.007624 -0.001572 - 330 0.029582 -0.010319 0.009090 - 331 -0.009062 0.000913 0.000368 - 332 -0.019327 0.020501 -0.000560 - 333 -0.018764 -0.008632 0.002570 - 334 0.004502 0.001200 -0.008087 - 335 0.008714 -0.005091 -0.008624 - 336 0.004610 0.003623 -0.007048 - 337 0.002461 -0.000759 0.003913 - 338 0.021591 -0.013925 0.009416 - 339 -0.017190 0.002325 0.006138 - 340 0.003361 0.004027 0.006986 - 341 0.006850 0.012752 0.018496 - 342 0.019589 0.009932 -0.004987 - 343 0.000463 0.005037 -0.000723 - 344 0.008333 0.006382 -0.005532 - 345 0.004288 0.006565 0.007800 - 346 -0.001505 -0.001295 0.001190 - 347 -0.015747 0.011253 0.025149 - 348 0.014871 -0.012646 -0.016815 - 349 -0.000186 0.002115 -0.002539 - 350 0.001936 0.000958 -0.003366 - 351 -0.014299 0.007078 -0.001653 - 352 -0.000876 -0.001637 -0.002032 - 353 -0.001168 0.005556 -0.012749 - 354 -0.003162 -0.016318 -0.009468 - 355 -0.000674 -0.001888 -0.003265 - 356 0.017652 -0.009515 0.007889 - 357 0.015313 -0.006079 0.010454 - 358 -0.000964 -0.004354 0.000067 - 359 0.004137 -0.002540 0.004500 - 360 -0.011376 -0.000921 -0.006123 - 361 0.002023 0.003210 -0.000511 - 362 0.012560 -0.011698 0.016109 - 363 -0.013295 -0.009379 -0.009014 - 364 0.003315 0.003249 0.007620 - 365 -0.010739 0.000915 -0.008118 - 366 -0.015293 0.007564 -0.004343 - 367 0.000192 0.002269 -0.000485 - 368 0.002520 -0.012494 -0.004632 - 369 0.010222 0.003093 -0.002247 - 370 0.003953 0.000628 0.004147 - 371 0.001165 -0.005271 0.007550 - 372 -0.013412 -0.019696 0.026961 - 373 0.001883 0.002252 -0.003560 - 374 0.005482 -0.004609 0.002380 - 375 -0.008048 0.004473 -0.008866 - 376 -0.002663 0.001073 0.001951 - 377 0.010178 0.018964 0.000820 - 378 0.007583 -0.018984 0.016464 - 379 0.001136 0.007646 0.002719 - 380 0.006251 0.008125 0.009187 - 381 0.001284 0.011634 -0.004097 - 382 -0.000767 0.000265 -0.000818 - 383 -0.000089 0.001579 -0.002300 - 384 -0.004565 -0.011251 0.008186 - 385 0.004778 -0.000871 0.002405 - 386 0.006618 -0.002801 0.006849 - 387 0.029884 -0.012377 0.019662 - 388 -0.002799 -0.005785 0.000693 - 389 -0.006988 0.014716 -0.008738 - 390 -0.003130 0.004832 0.002982 - 391 0.000036 -0.002467 0.000498 - 392 -0.001382 -0.006847 0.003863 - 393 -0.003623 0.001391 0.001664 - 394 0.004431 0.000182 0.002043 - 395 0.007177 -0.001675 0.008884 - 396 0.000324 0.003728 0.003379 - 397 0.004107 -0.000618 0.000098 - 398 0.019272 -0.008832 -0.013192 - 399 -0.025041 0.027976 -0.020594 - 400 0.002982 -0.002889 -0.005826 - 401 0.010564 -0.003899 -0.002078 - 402 0.005218 -0.003308 -0.010357 - 403 0.002304 -0.003833 -0.008812 - 404 -0.013421 -0.017603 -0.023172 - 405 -0.003134 -0.000582 0.001712 - 406 -0.003398 -0.002176 0.001635 - 407 -0.015813 0.008046 0.010515 - 408 0.003940 -0.004144 -0.002666 - 409 0.008428 -0.002203 -0.004077 - 410 -0.004859 0.004207 -0.016803 - 411 -0.022714 0.005614 0.004119 - 412 -0.000677 -0.000486 0.001019 - 413 0.004137 0.001524 0.004810 - 414 -0.011495 -0.003293 -0.002498 - 415 -0.004277 -0.004620 -0.002973 - 416 0.005727 -0.002611 0.021922 - 417 0.009759 0.016284 -0.017136 - 418 0.001140 -0.003169 0.001021 - 419 0.002072 0.019101 -0.019824 - 420 0.029356 -0.011686 0.004675 - 421 0.001175 0.002540 0.001846 - 422 0.009479 -0.017538 0.002696 - 423 0.008327 0.028039 -0.001246 - 424 0.002971 -0.004730 0.000069 - 425 0.010168 -0.005904 -0.016535 - 426 0.009223 0.011295 0.006248 - 427 -0.003323 0.000861 0.005020 - 428 -0.005244 0.001685 -0.001864 - 429 0.000994 0.014826 0.000976 - 430 -0.002795 0.003958 -0.004848 - 431 0.010698 -0.011688 -0.000537 - 432 0.008158 0.021591 -0.003259 - 433 0.000363 0.002223 0.004053 - 434 -0.002225 0.004315 -0.010042 - 435 -0.000151 -0.000572 0.000675 - 436 0.006996 -0.000559 0.003307 - 437 -0.011410 -0.004708 0.006782 - 438 -0.015909 0.022113 0.004877 - 439 -0.002401 -0.002279 0.002655 - 440 -0.002478 0.000164 0.005849 - 441 -0.003545 0.002314 0.007358 - 442 0.002189 0.006935 -0.001251 - 443 -0.007190 0.031224 0.006804 - 444 0.004661 -0.003296 0.013412 - 445 0.003709 0.001514 -0.003921 - 446 0.015678 0.007604 0.000133 - 447 -0.004648 -0.004474 -0.027064 - 448 0.001807 -0.004146 0.004203 - 449 0.029598 0.003434 0.012408 - 450 -0.004603 -0.006201 0.002287 - 451 -0.003031 -0.004136 -0.006564 - 452 0.009003 0.019264 0.004529 - 453 -0.000188 0.010449 0.001077 - 454 0.003891 0.002752 0.005629 - 455 0.001092 0.012776 0.008682 - 456 -0.002762 0.015371 -0.005857 - 457 0.002697 -0.003406 -0.002865 - 458 0.007823 -0.013511 0.002023 - 459 -0.030492 -0.008107 -0.020624 - 460 0.000483 0.001162 0.002651 - 461 0.002571 -0.007508 -0.009384 - 462 -0.010774 -0.027329 0.003619 - 463 0.005791 0.000086 0.004298 - 464 0.008820 0.016257 -0.002226 - 465 0.000317 -0.014932 -0.013621 - 466 0.003540 0.001551 -0.001349 - 467 0.008241 0.020014 0.019807 - 468 -0.004258 -0.010227 -0.029599 - 469 0.007640 0.001287 -0.003128 - 470 0.004600 -0.001555 -0.010230 - 471 0.007870 0.002461 0.000094 - 472 0.001001 0.005160 -0.001529 - 473 0.006073 0.015127 0.022819 - 474 0.006356 -0.012345 -0.003131 - 475 -0.005549 -0.000151 0.001312 - 476 -0.015747 0.009610 0.004075 - 477 0.009345 0.004620 -0.013632 - 478 -0.005694 -0.004777 0.002781 - 479 -0.015785 0.018249 0.008919 - 480 0.007264 0.001342 -0.012954 - 481 -0.002601 -0.003124 -0.001775 - 482 -0.010924 -0.002942 0.001676 - 483 0.020644 0.001519 0.001050 - 484 -0.003829 -0.001681 0.001973 - 485 -0.009248 -0.008096 0.002166 - 486 -0.004627 -0.003317 0.000426 - 487 0.004750 0.008629 -0.001691 - 488 -0.009177 0.001481 0.019567 - 489 -0.000748 -0.004703 -0.011184 - 490 -0.000930 -0.004032 -0.001796 - 491 -0.007051 -0.001375 -0.004647 - 492 -0.000505 0.005436 -0.004029 - 493 -0.000767 -0.000313 -0.004426 - 494 0.007019 0.022441 0.008035 - 495 0.002030 -0.018016 0.012244 - 496 -0.000430 -0.004092 0.001186 - 497 0.012447 -0.008156 0.016405 - 498 -0.008008 0.011043 -0.000527 - 499 0.001752 0.001451 -0.008850 - 500 -0.001696 0.002950 -0.000035 - 501 0.006054 -0.001180 -0.028952 - 502 0.001434 -0.008124 -0.001958 - 503 0.001762 -0.007034 -0.009244 - 504 -0.008796 -0.004759 -0.009928 - 505 0.000249 0.001170 0.006380 - 506 -0.005081 0.014461 -0.003259 - 507 -0.002522 0.001324 0.007841 - 508 0.003441 0.001538 0.006742 - 509 0.007735 -0.006583 0.003492 - 510 0.009681 0.006088 0.008608 - 511 -0.006695 -0.001970 0.000807 - 512 0.004268 0.004052 0.001263 - 513 -0.004129 -0.012886 -0.007489 - 514 -0.002878 0.001158 0.006535 - 515 -0.007680 -0.001896 0.002953 - 516 -0.000917 -0.006257 -0.002762 - 517 -0.001401 -0.003523 -0.005778 - 518 -0.001854 0.007834 0.015061 - 519 -0.010095 0.007049 -0.021128 - 520 -0.000766 -0.000153 0.007009 - 521 0.009064 -0.003223 0.017921 - 522 0.000864 -0.000043 0.007876 - 523 -0.001025 0.001319 -0.006573 - 524 -0.006395 0.000755 -0.002686 - 525 -0.032670 0.007943 0.004175 - 526 0.002953 0.006520 0.004065 - 527 0.009139 -0.008077 -0.010889 - 528 -0.002820 0.012454 -0.005504 - 529 -0.008727 0.003418 0.002451 - 530 -0.007112 -0.005703 0.023446 - 531 -0.011285 0.014165 -0.019563 - 532 -0.002562 0.003192 -0.002295 - 533 -0.003618 0.007211 0.002298 - 534 0.010325 0.001834 0.002853 - 535 0.002563 0.000345 -0.002878 - 536 0.002396 0.022293 -0.006961 - 537 0.001693 -0.002677 0.010576 - 538 -0.001561 0.000734 0.001793 - 539 -0.008542 0.015338 0.007321 - 540 -0.015880 0.015140 0.014642 - 541 0.001092 0.000090 0.000997 - 542 -0.004522 -0.004004 0.003687 - 543 0.003258 -0.006156 0.000500 - 544 -0.001608 0.002026 0.003790 - 545 -0.010430 -0.004583 0.015482 - 546 0.002628 0.011416 0.004923 - 547 -0.002068 0.005845 0.001850 - 548 0.001194 0.007931 0.007672 - 549 -0.020261 -0.007195 -0.008896 - 550 0.005399 0.001999 0.000211 - 551 0.004420 0.012603 0.006214 - 552 0.007790 0.005534 0.000006 - 553 -0.004249 0.001186 -0.000260 - 554 0.006385 -0.014925 0.000020 - 555 0.009902 0.016988 -0.004080 - 556 0.006637 -0.003469 0.000450 - 557 -0.002010 0.011423 -0.004361 - 558 -0.009074 0.013716 -0.002539 - 559 0.003243 -0.003710 -0.002565 - 560 -0.000480 -0.009433 0.000267 - 561 0.002981 -0.005587 -0.010088 - 562 0.002665 0.008169 0.002667 - 563 -0.001817 0.009035 0.022525 - 564 0.005689 0.010678 0.000603 - 565 0.003217 0.002617 0.001072 - 566 0.025108 0.001061 -0.027288 - 567 -0.003091 0.028727 0.028529 - 568 0.003991 -0.002246 0.002528 - 569 0.011195 -0.007917 0.010511 - 570 -0.006686 -0.007088 -0.000640 - 571 0.005302 0.003751 0.001484 - 572 0.001250 0.007658 -0.006666 - 573 0.018145 -0.005375 0.000139 - 574 -0.003857 0.003583 0.000238 - 575 0.006752 0.001063 0.004538 - 576 -0.006479 0.014326 -0.017669 - 577 0.001793 0.003661 0.002509 - 578 0.010186 -0.003147 0.008687 - 579 -0.001160 -0.005645 -0.003812 - 580 -0.002296 0.006997 0.000837 - 581 -0.031138 0.017223 0.000984 - 582 0.002587 -0.007480 0.015277 - 583 0.000288 -0.000668 0.001548 - 584 0.016041 -0.004051 0.004629 - 585 -0.025116 0.003224 0.009356 - 586 -0.000853 0.003188 0.004014 - 587 -0.001700 -0.004491 0.006716 - 588 -0.008947 -0.009004 -0.023328 - 589 0.005432 -0.003893 -0.001000 - 590 -0.019524 0.021049 -0.035976 - 591 0.009404 0.004475 -0.004525 - 592 -0.006508 -0.002709 0.000481 - 593 0.010852 -0.015643 0.005754 - 594 0.006526 0.026156 0.009018 - 595 -0.004611 -0.001841 0.002205 - 596 -0.013411 -0.011893 -0.011510 - 597 -0.002150 -0.000804 -0.006730 - 598 -0.002593 -0.000356 0.003104 - 599 0.009483 0.002951 -0.001362 - 600 -0.015523 -0.003843 0.010828 - 601 -0.001229 0.003953 0.000471 - 602 -0.017788 0.002114 0.033354 - 603 0.015187 -0.017947 -0.007994 - 604 -0.001335 -0.000196 0.007281 - 605 0.015188 0.007448 0.005030 - 606 -0.001538 0.002386 -0.009662 - 607 -0.001172 0.004261 0.002894 - 608 -0.002229 0.015661 0.009134 - 609 0.017428 0.004976 0.006974 - 610 -0.001490 0.003604 0.004586 - 611 -0.017720 0.006222 -0.023144 - 612 0.010016 -0.015847 -0.004678 - 613 -0.002648 0.000934 0.000698 - 614 -0.011832 0.016782 0.007626 - 615 -0.005427 0.001385 0.015386 - 616 0.003669 -0.001949 0.003946 - 617 0.005164 0.000243 0.009975 - 618 -0.000161 0.003111 0.001353 - 619 0.002976 -0.004733 0.001868 - 620 -0.002832 -0.014197 -0.023534 - 621 -0.003347 -0.011551 0.000693 - 622 0.004912 0.001701 -0.000793 - 623 0.013809 0.007164 -0.016905 - 624 0.024958 -0.010962 -0.008428 - 625 0.007422 -0.002948 -0.001308 - 626 -0.016590 -0.032000 -0.001025 - 627 0.011367 0.004098 0.010259 - 628 -0.002045 -0.000742 0.000577 - 629 -0.030845 0.001448 0.030396 - 630 0.001781 -0.017639 0.014980 - 631 0.002233 -0.004427 -0.002429 - 632 0.018586 -0.001402 0.006993 - 633 -0.012356 0.003736 0.007796 - 634 -0.004338 0.007766 0.000310 - 635 0.001990 0.000209 0.007107 - 636 -0.006343 0.005190 -0.018263 - 637 -0.005455 0.000492 -0.002847 - 638 0.000522 0.006495 0.003755 - 639 -0.001841 -0.009429 -0.001507 - 640 -0.002314 -0.002516 -0.005613 - 641 0.018652 0.002237 -0.015930 - 642 -0.002326 -0.000776 -0.003132 - 643 -0.005512 -0.000623 -0.000619 - 644 -0.001015 0.005882 0.003225 - 645 0.000586 0.023218 -0.004529 - 646 -0.001138 0.000800 0.002687 - 647 0.003627 0.013371 -0.016172 - 648 0.018968 0.017228 -0.000038 - 649 -0.002086 -0.000112 -0.007393 - 650 0.016103 0.035588 0.008775 - 651 -0.038516 0.012158 -0.009536 - 652 0.002958 0.004862 -0.007554 - 653 0.024333 0.013052 -0.023133 - 654 0.002379 -0.000049 -0.006601 - 655 0.003804 -0.003076 -0.001112 - 656 -0.004763 0.002283 -0.025897 - 657 -0.036538 -0.010672 -0.010599 - 658 -0.000713 0.003957 0.002151 - 659 -0.016531 0.001472 0.004862 - 660 -0.009287 0.028134 0.010480 - 661 0.004192 -0.003835 0.000568 - 662 0.011523 0.002433 0.036479 - 663 -0.009197 -0.041577 0.000393 - 664 0.000280 -0.002373 -0.004460 - 665 0.002206 -0.003211 0.000957 - 666 0.006211 0.013469 -0.005353 - 667 -0.000522 0.001664 -0.004748 - 668 0.004459 -0.024042 -0.023029 - 669 0.011377 0.013403 0.030836 - 670 0.003382 -0.002813 0.000451 - 671 0.000766 0.000074 -0.006820 - 672 0.013252 -0.015598 0.024274 - 673 -0.003243 0.006406 -0.002570 - 674 0.019962 -0.008888 -0.019769 - 675 -0.027628 -0.005508 -0.000297 - 676 -0.007770 -0.003882 0.002155 - 677 -0.001777 0.012358 0.000036 - 678 -0.024978 0.005564 -0.015024 - 679 0.000188 0.001017 0.004117 - 680 -0.006440 -0.003105 0.019733 - 681 -0.016780 0.005575 -0.004078 - 682 0.000151 0.001697 -0.001387 - 683 -0.002925 0.000955 -0.004378 - 684 0.000826 0.008069 0.003052 - 685 -0.003543 -0.000321 -0.000587 - 686 -0.012205 0.000432 -0.005990 - 687 0.004010 0.009678 -0.003793 - 688 0.001940 -0.000340 0.003900 - 689 0.005837 0.014815 -0.005621 - 690 -0.008710 -0.017653 0.020395 - 691 -0.001931 -0.003975 -0.002577 - 692 -0.003368 -0.014386 -0.006878 - 693 -0.013782 -0.002984 0.003522 - 694 0.004968 -0.000283 -0.003322 - 695 0.019160 0.006665 -0.007077 - 696 0.022604 -0.000847 -0.016983 - 697 0.002571 0.000550 -0.007379 - 698 -0.001443 -0.002487 -0.007727 - 699 -0.011487 -0.013883 0.019460 - 700 0.001096 -0.004750 0.003965 - 701 -0.016603 -0.010473 0.014272 - 702 0.023559 -0.001392 -0.008500 - 703 -0.002022 -0.005262 -0.004485 - 704 0.002332 -0.014942 -0.004917 - 705 -0.009402 0.006267 -0.002020 - 706 -0.000288 0.003264 -0.003564 - 707 0.004565 0.033122 -0.006655 - 708 -0.018922 -0.009521 0.000208 - 709 -0.003485 0.003285 -0.000556 - 710 0.004587 -0.002798 -0.000984 - 711 -0.006054 0.007231 -0.001425 - 712 0.004718 0.000201 -0.003948 - 713 -0.014114 0.009800 -0.004955 - 714 -0.008099 -0.004168 0.008689 - 715 0.000410 -0.000654 0.009605 - 716 0.008711 0.018707 0.002740 - 717 0.003459 -0.008185 0.010239 - 718 0.003479 0.000757 0.004467 - 719 0.000433 -0.000495 0.007710 - 720 0.012945 0.003286 -0.002052 - 721 -0.010010 -0.003567 0.006956 - 722 0.005307 -0.001615 -0.002198 - 723 -0.012515 0.011984 0.016669 - 724 0.001378 -0.002186 -0.001614 - 725 0.012587 -0.019891 0.012237 - 726 0.012601 0.007024 0.014776 - 727 -0.002983 -0.001722 -0.004228 - 728 0.015268 -0.011359 -0.002815 - 729 -0.003967 0.028638 0.000653 - 730 -0.000313 -0.000495 0.001546 - 731 -0.030938 -0.009463 -0.008649 - 732 -0.033474 -0.019299 0.015331 - 733 0.000845 -0.003919 -0.003202 - 734 -0.027178 0.011071 -0.026350 - 735 -0.007741 0.001470 -0.016184 - 736 -0.001239 0.001989 -0.002789 - 737 0.011285 0.001382 -0.006222 - 738 0.022813 -0.006205 -0.006536 - 739 0.003987 -0.004190 -0.005010 - 740 -0.007915 0.002670 -0.013878 - 741 0.004194 0.006086 -0.010350 - 742 0.006539 -0.005074 0.002196 - 743 0.015306 0.008181 0.005081 - 744 0.007865 0.003022 -0.004716 - 745 -0.001784 -0.010062 0.004309 - 746 -0.002378 -0.011275 0.006933 - 747 -0.008336 -0.001053 0.004620 - 748 -0.002979 0.004768 -0.002497 - 749 -0.000959 0.004004 -0.002600 - 750 -0.019512 -0.002978 0.005044 - 751 -0.004903 -0.000550 0.000659 - 752 -0.005086 0.005639 -0.022167 - 753 -0.008131 0.001631 -0.018889 - 754 -0.001761 -0.001628 0.000503 - 755 -0.003957 -0.007199 -0.006609 - 756 0.003155 -0.001306 0.005143 - 757 0.000937 0.008247 -0.008723 - 758 0.028994 0.004889 0.007225 - 759 -0.000469 -0.025903 0.001925 - 760 -0.001834 -0.000370 -0.001605 - 761 0.007234 -0.001225 -0.019036 - 762 -0.003442 -0.001966 0.000209 - 763 0.000445 0.007510 0.001158 - 764 -0.008348 0.004439 -0.007776 - 765 -0.012793 0.011539 0.019680 - 766 0.000065 -0.000962 -0.004032 - 767 -0.002013 -0.005477 0.003901 - 768 0.003529 0.021570 0.007224 - 769 -0.002661 0.002604 -0.003268 - 770 0.005668 -0.003962 -0.004196 - 771 -0.003633 0.008263 -0.012842 - 772 0.001811 0.001915 0.002764 - 773 0.007995 -0.017893 0.012738 - 774 -0.018466 -0.002519 -0.001997 - 775 -0.002231 0.000080 0.000338 - 776 -0.020092 -0.012422 0.010443 - 777 0.017610 0.006562 -0.019411 - 778 -0.001733 0.005494 0.004582 - 779 0.013495 0.017522 0.004058 - 780 0.014733 0.026971 -0.010419 - 781 0.001950 0.000577 -0.000870 - 782 -0.025830 0.001269 0.005271 - 783 0.007534 -0.015453 0.006553 - 784 0.004959 0.000931 -0.005022 - 785 -0.008754 0.005835 0.049441 - 786 0.010447 0.012462 0.001546 - 787 -0.001107 0.002522 0.000433 - 788 0.009871 0.011686 0.008446 - 789 -0.006988 0.002247 0.021211 - 790 0.004245 0.001822 -0.000253 - 791 0.000153 -0.002603 0.008675 - 792 0.006252 0.003177 -0.013109 - 793 -0.002534 0.003863 0.000617 - 794 -0.000057 0.004391 -0.016346 - 795 0.005974 -0.000584 -0.004834 - 796 0.001827 -0.002339 -0.002010 - 797 -0.023150 0.007693 0.012507 - 798 0.012203 0.000464 -0.020004 - 799 -0.000293 -0.001883 -0.002470 - 800 -0.004248 0.006084 0.002613 - 801 -0.013517 0.015693 0.003574 - 802 -0.009450 0.005229 -0.003400 - 803 -0.015058 -0.007700 0.001796 - 804 -0.000196 -0.003546 0.002537 - 805 0.008758 -0.003257 0.005431 - 806 0.012998 -0.011952 -0.017276 - 807 0.008558 -0.002765 0.006723 - 808 -0.001470 -0.000539 0.002965 - 809 0.024028 -0.019423 -0.012788 - 810 0.003892 0.003966 -0.001573 - 811 0.000254 0.001510 0.000089 - 812 0.024395 0.007424 -0.013783 - 813 0.006830 0.017138 0.017010 - 814 -0.001535 -0.003749 -0.001708 - 815 0.013748 -0.018314 -0.006646 - 816 0.003900 0.002047 0.006451 - 817 0.006585 0.003832 -0.000629 - 818 0.021540 0.003252 0.001280 - 819 0.007897 0.007247 -0.003727 - 820 -0.002115 -0.002434 -0.005025 - 821 -0.016735 0.003360 -0.019137 - 822 0.003237 -0.017804 -0.004111 - 823 -0.003907 0.002878 -0.003988 - 824 -0.005419 -0.002010 -0.004476 - 825 -0.006449 0.003104 -0.002766 - 826 -0.013638 -0.002258 -0.002448 - 827 -0.007838 0.000023 -0.005866 - 828 -0.006633 0.001312 -0.008943 - 829 0.001696 0.003761 -0.002125 - 830 -0.001113 -0.010288 -0.008692 - 831 0.010380 0.008838 -0.015548 - 832 -0.003164 0.004544 -0.002070 - 833 -0.001495 -0.013094 -0.000890 - 834 0.011945 -0.015741 -0.003378 - 835 -0.008802 -0.001939 -0.005442 - 836 -0.002949 -0.007279 -0.004665 - 837 0.008414 -0.021459 -0.000948 - 838 0.001330 0.000622 0.000916 - 839 -0.001965 0.001331 0.006138 - 840 0.003081 -0.004825 0.007272 - 841 0.001557 -0.005770 -0.001563 - 842 0.014285 0.020628 -0.029634 - 843 -0.006815 0.003616 0.008747 - 844 0.001116 -0.003881 -0.003556 - 845 0.008316 -0.005783 -0.005256 - 846 -0.011615 0.015346 0.026431 - 847 0.004309 0.003546 -0.004311 - 848 0.007868 -0.013572 0.000073 - 849 -0.011699 0.005875 0.003604 - 850 0.000505 -0.004069 -0.002113 - 851 0.001211 -0.005770 -0.003436 - 852 -0.004651 0.001028 0.007154 - 853 -0.003913 -0.006795 -0.004733 - 854 -0.004339 -0.014527 -0.023555 - 855 -0.006756 -0.006056 -0.008714 - 856 0.007493 0.001588 -0.006408 - 857 0.020526 0.022065 -0.006921 - 858 0.010862 0.004031 -0.001655 - 859 0.003459 -0.001125 -0.001494 - 860 -0.000710 0.004855 0.022662 - 861 -0.000022 0.009082 0.012428 - 862 -0.000591 0.002648 0.002517 - 863 0.017910 0.003993 0.005847 - 864 -0.004999 0.014284 -0.016199 - 865 -0.001700 -0.002300 0.001206 - 866 -0.016994 -0.008747 -0.012103 - 867 -0.008118 -0.008616 0.003715 - 868 -0.002056 -0.003732 -0.006667 - 869 -0.002586 -0.005666 -0.002032 - 870 -0.002179 -0.001361 -0.001378 - 871 0.001952 0.000747 -0.004175 - 872 -0.000006 -0.004573 0.003592 - 873 -0.004377 -0.012174 0.000091 - 874 -0.006945 -0.004708 0.004295 - 875 -0.011724 -0.010397 0.002368 - 876 0.006805 0.012734 0.019238 - 877 0.004959 0.005871 -0.001277 - 878 -0.012228 -0.000867 -0.006672 - 879 0.014516 0.032640 0.025985 - 880 0.000767 -0.000179 0.004816 - 881 0.006242 0.002132 0.007465 - 882 0.006812 0.003103 0.007707 - 883 0.005120 -0.003059 -0.001062 - 884 -0.008255 -0.016076 -0.002362 - 885 -0.001789 -0.014152 -0.001194 - 886 -0.009000 0.001340 0.001690 - 887 -0.020559 -0.017599 0.000329 - 888 -0.003544 -0.006539 0.004087 - 889 -0.000933 0.000538 -0.001999 - 890 0.032797 0.013397 0.000525 - 891 -0.012354 -0.008526 -0.038077 - 892 0.002953 -0.002317 -0.004454 - 893 -0.029479 -0.014864 0.005868 - 894 0.019223 0.000709 -0.013773 - 895 0.002346 -0.003694 -0.004486 - 896 -0.005275 -0.001221 -0.010755 - 897 0.010883 0.001918 -0.002099 - 898 -0.000263 -0.000830 0.005518 - 899 0.000399 -0.005578 0.011643 - 900 -0.007207 -0.006080 -0.006632 - 901 -0.000868 0.002637 -0.000416 - 902 -0.003601 0.001456 0.001019 - 903 0.003465 0.009000 0.002627 - 904 -0.005492 0.001153 0.005034 - 905 0.008501 0.009963 0.005133 - 906 0.002740 0.005510 0.005387 - 907 0.001230 0.003701 -0.010904 - 908 0.005640 0.000943 -0.026378 - 909 -0.001655 0.006661 0.001080 - 910 0.000417 -0.004485 0.000899 - 911 0.004051 -0.003590 0.002016 - 912 0.010109 -0.002124 0.001500 - 913 0.002439 0.006335 0.003103 - 914 -0.006325 0.005901 0.006397 - 915 0.008058 0.002545 0.004591 - 916 -0.001774 -0.003954 -0.005522 - 917 -0.001697 -0.002110 -0.006988 - 918 0.000641 -0.012660 -0.001878 - 919 0.000840 0.002158 -0.002127 - 920 -0.006972 -0.005865 -0.019536 - 921 -0.009078 -0.009093 0.005319 - 922 -0.002466 0.001612 -0.002348 - 923 -0.007997 0.000173 -0.007016 - 924 -0.005167 0.000122 -0.004809 - 925 0.000182 0.007626 -0.005820 - 926 -0.000187 0.006758 -0.004766 - 927 -0.005146 0.010941 -0.001145 - 928 -0.001035 0.003329 -0.000156 - 929 -0.002925 0.005286 0.005381 - 930 -0.007353 0.014383 0.015446 - 931 0.001566 0.003779 -0.001844 - 932 0.014111 -0.006162 0.016836 - 933 -0.008051 -0.000942 0.006114 - 934 0.000472 0.000581 0.003898 - 935 0.010438 -0.015336 0.026259 - 936 -0.009803 0.018803 -0.011113 - 937 -0.002622 0.001845 -0.004649 - 938 0.000192 0.006195 -0.003034 - 939 -0.004379 0.004856 -0.008876 - 940 0.005312 -0.005320 -0.000644 - 941 0.004197 0.002434 0.005873 - 942 0.001054 -0.002144 -0.009156 - 943 0.001818 0.002764 0.000410 - 944 0.002489 0.005354 -0.014128 - 945 0.003819 0.010472 0.007403 - 946 0.005262 -0.000699 0.001191 - 947 -0.002052 -0.008290 0.017377 - 948 -0.012921 -0.009037 0.007720 - 949 0.002875 -0.000206 -0.005514 - 950 0.004620 -0.003924 -0.007344 - 951 0.004396 0.015332 -0.008395 - 952 -0.001773 -0.005567 0.004807 - 953 0.014650 -0.004337 0.011316 - 954 0.007355 -0.004603 0.004796 - 955 0.001050 0.002663 -0.000049 - 956 -0.000422 0.019759 -0.003121 - 957 -0.011736 0.001700 0.005445 - 958 0.002314 -0.007359 0.001422 - 959 0.000226 -0.009157 0.011161 - 960 0.002971 -0.007641 -0.001658 - 961 0.002025 0.003310 0.000085 - 962 0.003783 0.005544 -0.002440 - 963 -0.003390 -0.001680 0.007759 - 964 -0.000259 -0.001517 -0.001671 - 965 -0.009891 -0.000275 0.002930 - 966 -0.004798 -0.018121 0.000493 - 967 0.002742 0.002196 0.002639 - 968 -0.032110 0.008681 0.017593 - 969 -0.005767 -0.003804 -0.003447 - 970 -0.001025 -0.001901 0.007377 - 971 -0.025416 -0.005633 -0.009650 - 972 -0.002448 -0.002342 0.009184 - 973 0.000510 -0.004313 0.003297 - 974 -0.004244 -0.006185 -0.015114 - 975 0.002817 0.008222 0.025232 - 976 -0.005979 0.000432 0.003264 - 977 0.000348 0.000126 0.007237 - 978 -0.031461 0.008376 -0.002490 - 979 -0.003066 -0.005264 0.001528 - 980 0.000500 -0.005194 -0.000082 - 981 -0.006145 0.003915 -0.013465 - 982 -0.002081 -0.001596 0.001268 - 983 0.004918 -0.004802 -0.009499 - 984 -0.008729 0.005751 0.010881 - 985 0.002456 -0.001947 -0.001558 - 986 -0.006566 -0.000024 0.003315 - 987 0.007532 0.005898 -0.002575 - 988 -0.004247 -0.003264 -0.000409 - 989 0.002165 -0.007499 0.004990 - 990 -0.000419 0.003692 -0.004472 - 991 -0.001571 -0.000159 -0.000431 - 992 0.005413 0.009517 0.004397 - 993 -0.002643 -0.002292 -0.001478 - 994 -0.003884 0.005066 -0.000457 - 995 0.006816 0.009263 -0.003376 - 996 -0.007273 0.011919 0.000514 - 997 0.000030 0.001409 0.005477 - 998 0.005334 -0.020033 0.004464 - 999 0.016228 0.009598 -0.007106 - 1000 -0.002283 -0.004481 0.001317 - 1001 -0.002631 -0.006631 -0.004233 - 1002 0.004184 0.000805 0.014756 - 1003 0.000408 -0.003693 0.003308 - 1004 0.004530 -0.006410 -0.006453 - 1005 -0.004928 -0.003846 0.015168 - 1006 0.003101 -0.001511 0.005308 - 1007 0.014081 -0.002443 0.012313 - 1008 0.002846 0.010440 -0.000376 - 1009 0.003569 -0.002175 -0.006662 - 1010 -0.008368 -0.011644 -0.006989 - 1011 0.019824 -0.004949 -0.018661 - 1012 0.003202 -0.011850 0.003160 - 1013 0.014918 -0.009378 0.018579 - 1014 -0.002594 0.004575 -0.001959 - 1015 -0.002298 0.000413 -0.003910 - 1016 0.012837 -0.003799 -0.015681 - 1017 -0.005955 -0.000660 0.004171 - 1018 0.001582 0.000975 0.000146 - 1019 0.006776 -0.014144 -0.007821 - 1020 0.004234 -0.001693 -0.007198 - 1021 -0.001802 -0.002656 0.003257 - 1022 0.028537 0.012512 0.005966 - 1023 -0.000026 -0.011732 -0.013572 - 1024 0.006685 0.008417 -0.002619 - 1025 -0.018380 0.006240 0.006444 - 1026 0.014195 0.009753 -0.004447 - 1027 -0.000769 -0.006799 -0.003510 - 1028 -0.003532 0.013774 -0.009337 - 1029 0.005263 0.018084 -0.010946 - 1030 0.004102 0.004262 -0.002426 - 1031 -0.003256 -0.005354 0.003498 - 1032 -0.021894 -0.003478 0.016467 - 1033 0.001456 -0.004355 -0.002070 - 1034 -0.005859 -0.004113 -0.005871 - 1035 -0.005758 -0.006886 -0.016585 - 1036 0.001562 0.006459 -0.000209 - 1037 0.001331 0.004667 0.000892 - 1038 0.012898 0.027063 -0.008125 - 1039 0.002117 0.007131 0.002457 - 1040 0.026605 0.010046 0.019045 - 1041 -0.017364 0.007077 -0.014953 - 1042 -0.000452 0.009291 0.004625 - 1043 -0.011059 0.009571 0.015357 - 1044 0.027928 -0.000208 0.009437 - 1045 0.003475 -0.004274 -0.000546 - 1046 0.012160 -0.001385 -0.006922 - 1047 -0.016274 -0.008100 -0.006675 - 1048 -0.003853 -0.003278 -0.001388 - 1049 0.014697 -0.003341 -0.007454 - 1050 0.011346 -0.009086 -0.006461 - 1051 -0.001161 -0.003940 -0.002833 - 1052 0.011182 0.001281 -0.000803 - 1053 -0.001345 -0.002375 -0.003580 - 1054 0.004028 0.002256 0.000990 - 1055 0.013302 0.008212 -0.007566 - 1056 0.029179 -0.014499 0.008878 - 1057 0.000706 0.001652 0.001826 - 1058 0.000498 -0.007266 0.024956 - 1059 0.001324 -0.008155 0.011295 - 1060 0.000971 -0.006253 -0.004688 - 1061 -0.004746 -0.005680 -0.016047 - 1062 -0.000356 -0.009050 -0.006561 - 1063 -0.000866 0.005460 0.000045 - 1064 -0.006882 0.011747 0.020163 - 1065 -0.000733 0.001409 -0.010900 - 1066 -0.003804 0.003558 0.001444 - 1067 0.004513 0.002071 -0.017536 - 1068 -0.000869 -0.002704 -0.014336 - 1069 -0.003015 0.003241 -0.002075 - 1070 0.003734 -0.005456 -0.000879 - 1071 -0.006686 -0.008010 -0.008654 - 1072 -0.000541 -0.003669 -0.004373 - 1073 0.003151 -0.002513 -0.013951 - 1074 0.003979 -0.005557 0.002931 - 1075 -0.005175 -0.004387 0.000228 - 1076 -0.005613 -0.012392 -0.029351 - 1077 0.009704 0.009953 -0.015680 - 1078 -0.000915 0.003660 -0.003078 - 1079 0.002529 0.001465 0.006987 - 1080 0.000880 0.001866 -0.004217 - 1081 0.000835 -0.000410 0.000029 - 1082 0.003324 -0.009356 0.012151 - 1083 -0.000797 0.009753 -0.012613 - 1084 0.004557 -0.006851 0.000257 - 1085 0.014378 -0.010986 -0.004036 - 1086 0.001889 0.001865 0.000904 - 1087 0.003881 0.000306 -0.000266 - 1088 0.006043 -0.030376 0.018797 - 1089 -0.001012 -0.002296 0.000324 - 1090 0.007042 0.008682 0.007323 - 1091 0.010016 0.002442 -0.028255 - 1092 -0.004827 0.009414 -0.012200 - 1093 0.002178 0.003272 0.000190 - 1094 0.003486 0.001815 -0.002585 - 1095 0.006020 0.002953 -0.010998 - 1096 0.002573 -0.000704 0.002051 - 1097 -0.010233 0.004335 0.005568 - 1098 0.003397 0.002649 0.010631 - 1099 -0.000367 -0.008657 0.004003 - 1100 0.006810 -0.008282 0.003316 - 1101 -0.008301 -0.011638 -0.006525 - 1102 -0.001900 -0.008810 0.001531 - 1103 0.003628 0.008111 0.009571 - 1104 0.017147 0.000173 0.003988 - 1105 0.006161 0.005444 0.001389 - 1106 -0.033784 0.028714 -0.002486 - 1107 0.022179 0.015181 0.025221 - 1108 0.002935 0.001125 -0.009560 - 1109 0.013392 0.009490 0.002655 - 1110 0.015380 -0.002935 -0.004728 - 1111 0.002760 -0.001052 0.002516 - 1112 -0.006737 0.002302 0.012384 - 1113 -0.004649 -0.009652 -0.009326 - 1114 -0.003333 0.004385 -0.006004 - 1115 -0.014175 0.007089 0.000199 - 1116 0.009875 0.004925 0.012791 - 1117 -0.004828 0.000366 0.001718 - 1118 0.009618 -0.007069 -0.012330 - 1119 -0.021489 -0.009155 -0.001603 - 1120 -0.001360 0.002089 -0.003585 - 1121 0.003530 -0.001847 0.010254 - 1122 0.016468 0.005240 -0.014692 - 1123 0.001989 -0.000949 0.003286 - 1124 0.022107 -0.012110 -0.007316 - 1125 0.012518 -0.010337 0.015891 - 1126 0.000850 -0.001413 -0.001737 - 1127 -0.014943 0.000360 -0.000490 - 1128 -0.027983 -0.005206 0.004037 - 1129 0.011232 0.000349 -0.006679 - 1130 -0.005484 -0.003095 -0.004430 - 1131 -0.005050 -0.002005 -0.015837 - 1132 -0.000470 0.001924 0.001131 - 1133 -0.016506 0.005240 0.008171 - 1134 0.011977 -0.012388 0.003671 - 1135 -0.000818 0.001081 0.001571 - 1136 0.009956 -0.006601 -0.002667 - 1137 -0.013344 0.009962 -0.000602 - 1138 -0.004379 0.004681 0.005655 - 1139 -0.022717 0.009805 -0.016911 - 1140 -0.017223 0.002867 0.018671 - 1141 -0.000339 -0.000149 -0.001276 - 1142 0.002292 0.016872 -0.004987 - 1143 -0.012964 -0.000693 -0.007140 - 1144 -0.002149 0.004008 -0.001355 - 1145 0.012575 0.018012 -0.011467 - 1146 -0.018572 0.011663 -0.005755 - 1147 0.000951 -0.000232 0.005705 - 1148 0.001030 -0.002411 0.005162 - 1149 -0.004871 0.010528 0.006213 - 1150 -0.003431 0.005236 0.003321 - 1151 -0.006083 0.008172 0.003730 - 1152 0.021201 0.002738 -0.026021 - 1153 -0.000559 -0.001274 0.002074 - 1154 -0.000342 -0.008595 -0.003314 - 1155 -0.004563 0.013150 0.001114 - 1156 0.002547 -0.003346 0.000793 - 1157 -0.004000 0.002915 0.001908 - 1158 0.008526 -0.013385 0.001263 - 1159 0.003331 -0.001629 -0.001592 - 1160 0.012216 0.004263 0.001290 - 1161 -0.024729 0.027722 0.012828 - 1162 -0.004556 0.005331 -0.000790 - 1163 -0.001260 0.004809 0.012624 - 1164 0.009151 0.007740 0.005908 - 1165 0.006739 -0.002486 0.000962 - 1166 0.002801 -0.001010 0.007063 - 1167 0.006266 -0.009780 0.000447 - 1168 -0.001756 -0.006121 -0.000399 - 1169 0.002128 0.011752 0.003187 - 1170 -0.000744 -0.004455 -0.001624 - 1171 -0.003120 -0.007987 0.008768 - 1172 -0.001279 -0.014309 0.014916 - 1173 -0.003496 -0.005392 0.006518 - 1174 -0.005252 -0.000094 0.002610 - 1175 -0.004319 0.000327 0.003799 - 1176 0.014469 -0.001407 -0.023557 - 1177 -0.001733 0.011173 0.001097 - 1178 0.019607 0.000729 -0.008577 - 1179 -0.013430 0.021297 -0.011104 - 1180 0.005550 -0.002953 -0.004489 - 1181 -0.021164 -0.004283 0.009224 - 1182 0.020762 -0.011806 0.008058 - 1183 -0.003934 -0.006346 0.000789 - 1184 -0.004154 -0.012917 -0.000804 - 1185 0.001834 -0.003234 0.006486 - 1186 -0.003359 -0.000166 0.000482 - 1187 -0.010938 -0.009570 0.011838 - 1188 -0.006339 -0.002743 -0.017319 - 1189 -0.002008 -0.000238 -0.002842 - 1190 0.009730 0.002797 -0.000255 - 1191 0.004802 0.018470 -0.005529 - 1192 0.002978 0.003254 0.000406 - 1193 0.001762 -0.016118 0.017481 - 1194 0.009625 0.005549 -0.002833 - 1195 -0.005277 -0.000015 -0.004247 - 1196 0.008535 -0.018189 -0.023760 - 1197 -0.020839 0.008581 0.007193 - 1198 0.001976 -0.001531 0.001386 - 1199 -0.012488 -0.005613 0.004418 - 1200 0.012387 0.001324 -0.002579 - 1201 0.004612 0.001574 0.002430 - 1202 0.004011 0.024078 0.008286 - 1203 0.028635 -0.001749 -0.000378 - 1204 -0.001292 -0.004163 0.001688 - 1205 0.018917 -0.005327 -0.022863 - 1206 -0.021498 0.026796 -0.015481 - 1207 -0.004360 -0.003023 -0.007483 - 1208 0.015222 -0.007834 -0.014901 - 1209 -0.015487 -0.004003 -0.024684 - 1210 0.000162 -0.000232 -0.002511 - 1211 0.005663 0.001759 0.003041 - 1212 -0.026577 0.001752 0.009499 - 1213 -0.002118 -0.004800 0.002106 - 1214 0.012772 0.013880 -0.004149 - 1215 0.008831 0.004495 0.004278 - 1216 -0.001002 0.000396 0.000450 - 1217 0.001493 -0.000300 0.006615 - 1218 0.022789 -0.011336 -0.001626 - 1219 -0.002165 0.002305 -0.004399 - 1220 -0.001727 0.010653 0.006150 - 1221 0.001799 -0.000399 -0.015101 - 1222 -0.002535 -0.001664 0.000167 - 1223 -0.007939 0.009699 -0.003581 - 1224 -0.009214 -0.009452 -0.003331 - 1225 -0.002745 0.003249 0.011490 - 1226 0.010727 -0.015563 0.011870 - 1227 -0.003771 0.013856 -0.015486 - 1228 -0.000932 0.001513 0.000721 - 1229 -0.002528 0.000192 0.015301 - 1230 -0.027023 -0.007231 0.009659 - 1231 -0.005525 0.001099 -0.001369 - 1232 -0.002318 -0.008510 -0.009719 - 1233 -0.005945 -0.008347 0.009845 - 1234 -0.000817 -0.006097 -0.001394 - 1235 0.026844 0.005400 -0.013998 - 1236 -0.019837 0.017329 -0.010038 - 1237 -0.002691 -0.005371 -0.000786 - 1238 -0.007304 -0.006372 0.007409 - 1239 -0.014066 -0.005252 0.014237 - 1240 -0.000660 -0.004157 -0.007445 - 1241 -0.015343 -0.015681 0.000525 - 1242 -0.004856 0.008296 -0.020506 - 1243 -0.000451 -0.006253 0.005274 - 1244 -0.016626 -0.024128 0.003146 - 1245 0.003430 -0.001516 0.006995 - 1246 0.002369 0.000761 -0.000692 - 1247 -0.011034 0.017913 -0.003576 - 1248 0.014886 0.005052 0.010870 - 1249 0.000976 0.003044 0.004043 - 1250 0.002084 0.009119 -0.003484 - 1251 -0.004682 -0.003095 0.024419 - 1252 -0.001872 0.005519 -0.003878 - 1253 0.014045 0.004474 0.006660 - 1254 -0.006683 -0.012923 -0.006357 - 1255 -0.007125 -0.002296 0.002894 - 1256 -0.009126 -0.000293 0.008175 - 1257 -0.005668 -0.002902 -0.000640 - 1258 -0.009805 0.000500 -0.001546 - 1259 -0.007254 -0.007274 0.010849 - 1260 0.005786 0.004719 0.004479 - 1261 0.000767 -0.007091 -0.002809 - 1262 -0.010861 -0.024470 -0.006678 - 1263 0.010352 0.003874 -0.018616 - 1264 -0.001332 -0.000776 -0.001533 - 1265 0.005055 -0.002761 -0.000154 - 1266 0.001293 -0.010766 0.003695 - 1267 0.004101 0.005423 0.004161 - 1268 -0.006495 -0.001645 0.007645 - 1269 0.024277 0.000761 0.018148 - 1270 0.000384 -0.004677 0.001777 - 1271 -0.000305 -0.022286 0.006378 - 1272 0.014900 -0.009298 0.005029 - 1273 -0.002201 -0.002422 -0.001266 - 1274 0.002419 0.000621 -0.006170 - 1275 0.002242 -0.003567 -0.006329 - 1276 0.001155 0.006214 -0.002164 - 1277 -0.025679 0.011598 0.001775 - 1278 -0.016652 0.005061 0.002255 - 1279 -0.000163 0.000193 -0.001041 - 1280 -0.002822 -0.004131 -0.007696 - 1281 -0.007029 0.005316 -0.012422 - 1282 -0.001259 -0.001443 0.001295 - 1283 -0.000992 -0.027820 -0.000474 - 1284 -0.012190 -0.043729 -0.008054 - 1285 -0.001840 -0.001572 0.001104 - 1286 0.008311 0.001263 -0.001841 - 1287 0.001277 0.000429 -0.007113 - 1288 -0.005029 -0.002280 -0.002761 - 1289 -0.024723 0.012515 -0.012864 - 1290 -0.013845 -0.020399 0.001674 - 1291 -0.000161 0.002303 0.004199 - 1292 -0.010956 -0.010528 0.017163 - 1293 0.023554 -0.006815 0.021159 - 1294 0.000772 -0.000829 0.004462 - 1295 0.024106 -0.007189 -0.017980 - 1296 -0.011795 0.000225 0.018351 - 1297 -0.002503 0.000288 -0.000931 - 1298 -0.001901 -0.006775 -0.001166 - 1299 -0.002626 0.004209 -0.000596 - 1300 -0.003248 -0.009856 0.001496 - 1301 -0.008616 0.000206 -0.000660 - 1302 0.012991 -0.001944 0.010735 - 1303 0.000183 0.003767 -0.002207 - 1304 0.002875 0.006021 0.006091 - 1305 -0.003343 -0.008883 0.015455 - 1306 -0.003761 0.009400 -0.007147 - 1307 -0.002601 -0.012510 0.005900 - 1308 -0.013464 0.021935 0.006364 - 1309 0.007717 -0.006568 -0.004280 - 1310 0.004551 -0.013432 0.001741 - 1311 0.016676 -0.009730 -0.005415 - 1312 -0.003518 -0.000115 0.000120 - 1313 -0.018566 -0.004441 0.007076 - 1314 0.011422 0.004168 0.013848 - 1315 -0.002232 0.003004 -0.005210 - 1316 -0.004985 -0.000655 -0.007286 - 1317 -0.004756 0.005461 -0.010032 - 1318 0.003296 -0.000345 0.003797 - 1319 0.000013 0.003387 0.009258 - 1320 -0.001175 0.009021 0.016554 - 1321 0.004610 0.000563 0.001890 - 1322 0.001511 0.004957 0.010795 - 1323 -0.000517 0.009529 0.012695 - 1324 0.003561 -0.002127 -0.002139 - 1325 -0.016355 -0.004573 0.011414 - 1326 0.002437 -0.000969 0.003958 - 1327 -0.003191 0.002772 0.003706 - 1328 0.002188 0.004078 0.024902 - 1329 0.005804 0.008997 0.000514 - 1330 0.000169 -0.001823 0.006601 - 1331 -0.012837 0.016738 0.032499 - 1332 -0.003787 -0.003993 0.005792 - 1333 -0.006500 -0.001952 -0.005568 - 1334 0.004632 0.002607 -0.001417 - 1335 0.007826 -0.018417 0.003893 - 1336 0.001400 0.000629 -0.002329 - 1337 -0.026090 -0.010827 -0.007428 - 1338 0.014757 0.003359 0.005866 - 1339 0.005344 0.002452 0.000637 - 1340 0.002304 0.001516 0.008371 - 1341 0.003116 0.003502 0.000920 - 1342 0.000219 0.006872 -0.006361 - 1343 0.004872 0.004948 -0.015461 - 1344 0.002293 0.008990 -0.007103 - 1345 -0.000248 -0.001405 -0.000404 - 1346 0.016050 0.005473 0.014883 - 1347 0.000661 0.010958 0.009762 - 1348 0.002507 0.004854 0.004016 - 1349 -0.000026 0.005865 -0.004933 - 1350 -0.003541 0.012071 0.011984 - 1351 -0.000388 -0.001662 -0.002624 - 1352 -0.008781 0.002236 0.005933 - 1353 -0.002303 0.010321 -0.013971 - 1354 0.000266 0.005381 0.006218 - 1355 -0.030793 -0.017551 0.006520 - 1356 -0.001710 0.006198 0.003481 - 1357 -0.000575 0.000387 0.003498 - 1358 0.011844 0.006387 0.013823 - 1359 -0.004149 -0.001630 0.001064 - 1360 0.002966 -0.001211 -0.000529 - 1361 0.011026 0.001160 0.001568 - 1362 0.015143 -0.001234 0.000065 - 1363 0.000976 0.001952 -0.002769 - 1364 0.013527 0.011152 0.001594 - 1365 -0.000179 -0.000211 -0.002554 - 1366 -0.005351 -0.004969 -0.002979 - 1367 -0.006889 0.021662 -0.005435 - 1368 -0.002462 0.016113 0.008657 - 1369 -0.000975 0.000751 -0.000755 - 1370 -0.003243 0.006738 -0.001393 - 1371 -0.002267 -0.000779 0.003167 - 1372 0.001566 -0.003190 -0.000583 - 1373 -0.002018 -0.005136 0.012563 - 1374 -0.006828 0.007134 0.011132 - 1375 0.005244 -0.004715 -0.003319 - 1376 -0.010064 -0.001392 0.024842 - 1377 -0.003331 -0.012180 0.011450 - 1378 0.005044 -0.003538 0.000197 - 1379 0.014932 -0.005316 0.014871 - 1380 0.002959 -0.015155 -0.010790 - 1381 0.004288 0.003508 0.003045 - 1382 0.010516 0.006731 0.001181 - 1383 0.003157 0.002004 0.039661 - 1384 -0.003464 -0.000341 -0.002519 - 1385 0.000767 -0.010574 0.002375 - 1386 0.012132 0.009405 0.005728 - 1387 -0.002537 0.005096 -0.000141 - 1388 0.008455 -0.000335 0.003398 - 1389 0.000567 0.012932 0.006368 - 1390 0.007440 -0.002304 0.001444 - 1391 0.003946 0.007849 -0.005030 - 1392 0.012038 -0.016280 0.007159 - 1393 -0.001061 -0.002610 -0.000083 - 1394 0.010905 -0.006613 -0.001941 - 1395 -0.013885 -0.027620 0.005494 - 1396 0.013746 0.003525 0.007163 - 1397 0.003586 0.002644 -0.010792 - 1398 0.018544 0.013850 0.017322 - 1399 0.004571 0.000027 -0.001760 - 1400 0.012220 0.001858 -0.006751 - 1401 0.009850 -0.002003 0.019339 - 1402 -0.001383 0.002281 -0.007042 - 1403 -0.003363 0.001654 -0.017801 - 1404 0.011330 0.009635 0.005470 - 1405 0.000650 -0.001098 -0.005942 - 1406 0.005198 -0.008028 -0.003832 - 1407 0.017668 -0.005738 0.026099 - 1408 -0.001891 0.001162 0.003476 - 1409 -0.003537 0.018838 0.000972 - 1410 0.007980 0.016250 0.030292 - 1411 -0.001348 0.000197 0.004181 - 1412 -0.002255 -0.008393 -0.001355 - 1413 -0.008567 -0.008184 -0.000151 - 1414 -0.001145 0.001777 -0.004250 - 1415 -0.002565 -0.000609 -0.002622 - 1416 0.017182 0.009342 -0.008899 - 1417 -0.000336 -0.000833 -0.006619 - 1418 0.006594 -0.014023 -0.011705 - 1419 -0.010047 -0.002912 -0.003804 - 1420 0.005759 0.000406 0.005233 - 1421 -0.013174 -0.018780 -0.002966 - 1422 -0.003551 -0.005212 0.011087 - 1423 -0.001811 -0.005836 -0.002120 - 1424 -0.008296 0.022099 0.012646 - 1425 0.010130 0.006059 0.033707 - 1426 0.001039 -0.001025 -0.000459 - 1427 0.004468 0.000527 0.001539 - 1428 -0.001728 -0.005304 0.003140 - 1429 -0.000141 -0.003112 0.003400 - 1430 0.007530 -0.026022 0.005020 - 1431 -0.011982 0.032142 -0.001998 - 1432 -0.001642 0.003923 -0.003350 - 1433 0.016086 -0.002664 -0.005695 - 1434 -0.010354 0.000136 0.021071 - 1435 0.001502 -0.001507 0.005856 - 1436 -0.003359 -0.017617 -0.013060 - 1437 -0.001621 -0.013764 -0.008355 - 1438 -0.006074 0.001165 0.001910 - 1439 -0.004946 0.003618 0.011324 - 1440 -0.007761 0.002697 -0.006763 - 1441 -0.009332 0.000898 0.000750 - 1442 -0.017083 -0.010335 0.011191 - 1443 0.020780 0.013466 -0.015083 - 1444 -0.008140 -0.008032 -0.000180 - 1445 -0.001836 -0.008988 0.003973 - 1446 -0.008280 -0.004548 -0.003224 - 1447 0.000996 -0.002062 -0.001184 - 1448 -0.001863 -0.012096 0.003957 - 1449 -0.027050 0.007989 0.002157 - 1450 -0.001321 -0.000325 0.001355 - 1451 -0.006885 -0.000536 -0.022446 - 1452 0.008792 -0.007975 0.003329 - 1453 -0.003682 -0.004782 -0.002567 - 1454 -0.001180 -0.009011 0.018662 - 1455 -0.000958 -0.004899 0.013723 - 1456 0.000545 0.011919 -0.001753 - 1457 0.023799 0.010298 -0.002649 - 1458 0.014717 0.007757 -0.005400 - 1459 -0.004576 -0.007691 0.001365 - 1460 -0.006577 -0.016846 -0.022862 - 1461 -0.005206 0.003687 0.012428 - 1462 0.001923 -0.004758 -0.001993 - 1463 0.006600 0.017503 0.006935 - 1464 -0.006747 -0.003482 -0.000067 - 1465 0.000613 0.004580 0.004038 - 1466 -0.001945 0.022605 -0.000652 - 1467 0.017624 -0.001392 0.003829 - 1468 -0.003065 -0.003003 -0.000747 - 1469 -0.012664 -0.016566 -0.007030 - 1470 0.008660 -0.008358 0.004763 - 1471 -0.004008 0.000421 -0.006040 - 1472 0.003555 0.008566 -0.015842 - 1473 -0.001032 0.001700 -0.010204 - 1474 -0.000556 0.000599 0.003074 - 1475 0.001542 0.002939 0.005269 - 1476 -0.005281 -0.001944 0.003338 - 1477 -0.000195 -0.000293 -0.001004 - 1478 -0.009991 -0.005354 -0.013386 - 1479 -0.000476 -0.017594 0.007900 - 1480 0.000550 -0.000431 0.001422 - 1481 0.018094 -0.005183 0.016234 - 1482 0.010706 0.011668 -0.017772 - 1483 0.001291 0.006499 0.000951 - 1484 0.009985 -0.016962 0.009714 - 1485 0.020849 0.018365 -0.008351 - 1486 0.006940 0.004692 -0.002409 - 1487 0.022308 0.010182 -0.022897 - 1488 0.000269 0.008847 0.011834 - 1489 0.002051 0.007334 -0.000125 - 1490 -0.023048 0.013759 -0.030276 - 1491 0.023523 -0.005817 0.007754 - 1492 -0.001269 0.002979 0.001311 - 1493 -0.005596 0.006174 0.011007 - 1494 -0.009061 0.022719 0.002133 - 1495 -0.001128 0.004307 -0.002381 - 1496 -0.004340 0.013891 -0.003505 - 1497 0.001822 -0.005505 -0.001135 - 1498 -0.000910 0.001437 0.000165 - 1499 0.004510 -0.000360 -0.006425 - 1500 0.003993 0.000498 0.007321 - 1501 -0.002868 -0.000316 -0.000509 - 1502 0.000620 0.011286 0.008461 - 1503 -0.013079 -0.008157 0.007561 - 1504 -0.003002 0.003413 0.004968 - 1505 0.015262 -0.005133 0.012052 - 1506 -0.003968 -0.003643 0.003514 - 1507 0.005087 -0.001882 -0.000518 - 1508 0.000932 -0.002238 0.000800 - 1509 -0.008149 0.000695 -0.000827 - 1510 -0.001261 -0.003375 0.000333 - 1511 -0.001224 -0.004135 -0.003080 - 1512 0.009246 -0.010372 0.026354 - 1513 0.000697 -0.003200 0.001222 - 1514 -0.002319 0.003800 0.022860 - 1515 -0.018205 0.011600 -0.011416 - 1516 -0.001731 -0.001076 0.002612 - 1517 -0.004661 -0.010783 -0.001505 - 1518 0.016208 0.002810 0.004482 - 1519 0.003508 -0.001750 0.002537 - 1520 0.024576 -0.026041 -0.004083 - 1521 -0.019140 0.000844 0.001909 - 1522 -0.000341 0.001152 0.001967 - 1523 -0.020076 0.003364 0.001315 - 1524 -0.000942 0.000692 -0.003283 - 1525 -0.006519 -0.000419 0.000991 - 1526 -0.004033 0.006531 0.004791 - 1527 0.005626 0.012187 -0.014266 - 1528 0.001113 -0.004253 0.011930 - 1529 -0.010144 0.003567 0.009059 - 1530 -0.003464 0.001115 0.011591 - 1531 0.000006 0.000074 0.005751 - 1532 0.003604 0.008464 0.010627 - 1533 -0.004351 -0.009621 -0.000453 - 1534 -0.000196 -0.001160 0.002795 - 1535 -0.006855 0.001414 0.005552 - 1536 -0.000894 -0.002102 0.005053 - 1537 -0.002040 -0.005887 -0.003590 - 1538 -0.006852 -0.011947 -0.023080 - 1539 -0.016070 0.000160 0.010390 - 1540 0.004712 0.002848 -0.002998 - 1541 -0.004259 0.007840 0.008142 - 1542 -0.004861 0.004263 0.011728 - 1543 0.006968 -0.004871 0.004119 - 1544 -0.016558 -0.002046 -0.006090 - 1545 -0.006229 0.004475 0.001436 - 1546 -0.002341 -0.004733 -0.003946 - 1547 0.003563 0.004733 0.009615 - 1548 -0.013018 0.004747 -0.004733 - 1549 0.001703 -0.000331 0.003605 - 1550 0.005459 -0.002653 -0.012447 - 1551 0.013689 0.008625 -0.003301 - 1552 0.003195 0.001205 -0.000779 - 1553 -0.003336 -0.011439 -0.004979 - 1554 0.001015 0.018568 -0.007361 - 1555 -0.001647 -0.003759 0.001214 - 1556 0.015583 -0.016961 0.000384 - 1557 -0.011138 -0.013161 -0.015913 - 1558 0.005848 -0.002193 -0.007682 - 1559 0.009577 -0.005765 0.010025 - 1560 0.006984 0.005858 -0.020668 - 1561 -0.005040 0.001396 0.001932 - 1562 0.007071 0.009231 0.007700 - 1563 0.001743 0.005137 0.005850 - 1564 0.001857 0.002145 -0.004455 - 1565 -0.007462 0.014047 -0.012730 - 1566 0.013730 -0.006385 0.009586 - 1567 -0.002000 0.003453 -0.001882 - 1568 -0.009622 -0.007424 -0.003371 - 1569 -0.006993 -0.018224 -0.006858 - 1570 0.001461 0.001281 -0.002568 - 1571 0.018901 0.002357 0.001811 - 1572 -0.001592 0.019333 -0.002732 - 1573 -0.001308 -0.005730 -0.002519 - 1574 -0.014074 0.007287 0.021518 - 1575 -0.017324 -0.018775 -0.005647 - 1576 0.002340 -0.001593 0.004994 - 1577 -0.000516 0.003608 0.002676 - 1578 -0.014840 -0.017283 -0.001508 - 1579 -0.001557 -0.002471 -0.002555 - 1580 0.016654 -0.033672 0.006595 - 1581 0.013351 -0.030070 0.003443 - 1582 0.003752 0.001449 0.001862 - 1583 -0.011257 -0.002704 0.007355 - 1584 0.002139 0.006577 0.012771 - 1585 0.002251 0.002492 -0.002180 - 1586 0.010691 -0.005615 -0.001517 - 1587 -0.018738 0.016070 0.006914 - 1588 -0.001600 0.000180 0.001378 - 1589 0.004891 -0.007732 -0.013906 - 1590 -0.015149 0.011285 0.002913 - 1591 0.003944 -0.001162 -0.002407 - 1592 -0.013220 -0.006427 -0.006873 - 1593 -0.008388 0.022805 -0.011588 - 1594 0.000621 -0.004836 0.005509 - 1595 0.006148 -0.013451 0.002326 - 1596 -0.001161 -0.012639 -0.002024 - 1597 -0.005042 0.000613 0.003072 - 1598 -0.002560 -0.009516 -0.007164 - 1599 -0.007736 0.003315 0.007824 - 1600 -0.002409 -0.002549 -0.003082 - 1601 -0.002839 0.004415 -0.008830 - 1602 -0.006633 -0.001003 -0.004060 - 1603 -0.004810 -0.007495 -0.004047 - 1604 0.005200 -0.017270 0.009101 - 1605 0.000670 -0.009280 -0.012848 - 1606 -0.003830 0.001924 -0.002728 - 1607 -0.035525 0.007821 -0.020602 - 1608 0.016575 -0.019547 -0.006176 - 1609 0.003828 0.000099 -0.002605 - 1610 0.017387 0.007652 0.014875 - 1611 0.012190 0.014852 0.016071 - 1612 -0.003436 0.002187 -0.001035 - 1613 -0.005586 -0.003901 0.006033 - 1614 -0.005884 -0.005331 -0.011796 - 1615 -0.001799 -0.005019 0.004011 - 1616 0.002094 -0.028579 0.008471 - 1617 0.023334 0.020189 0.016696 - 1618 -0.000653 -0.003079 -0.001689 - 1619 -0.005925 -0.004542 -0.007489 - 1620 0.003980 0.000361 0.005598 - 1621 -0.000999 0.004025 -0.003724 - 1622 0.000058 0.024442 0.006515 - 1623 0.011473 -0.013431 0.004073 - 1624 0.002923 -0.003314 0.001931 - 1625 0.003377 -0.006029 -0.008704 - 1626 0.002413 0.015094 0.010447 - 1627 0.003654 -0.000619 -0.001261 - 1628 -0.004232 -0.000930 0.001384 - 1629 0.019160 0.000313 -0.006734 - 1630 0.003534 0.002394 -0.000501 - 1631 -0.008068 0.002953 0.008451 - 1632 0.014612 0.006975 -0.004278 - 1633 0.001620 0.003004 0.003226 - 1634 -0.007605 -0.007788 0.011245 - 1635 0.020296 -0.014907 -0.003043 - 1636 -0.002678 -0.006261 0.001869 - 1637 -0.007968 -0.013586 -0.003793 - 1638 -0.015202 -0.007224 -0.014352 - 1639 -0.005816 -0.003019 0.006480 - 1640 -0.001607 -0.004084 0.006246 - 1641 0.008520 -0.008049 0.002824 - 1642 -0.000658 -0.004008 -0.000300 - 1643 -0.000444 0.000650 -0.012168 - 1644 -0.006399 -0.006883 0.005254 - 1645 -0.001317 0.006093 0.001522 - 1646 -0.010770 -0.004270 -0.010989 - 1647 -0.005520 0.020979 0.012203 - 1648 -0.004763 0.001957 0.003649 - 1649 -0.010531 0.001095 0.022741 - 1650 0.001695 -0.009764 -0.029750 - 1651 0.000561 0.003660 0.004562 - 1652 0.004814 -0.011887 -0.011791 - 1653 0.015151 -0.017660 -0.020515 - 1654 -0.003720 -0.008154 0.002101 - 1655 -0.006836 0.005342 0.006830 - 1656 -0.008891 -0.005752 0.002656 - 1657 -0.004211 -0.006534 0.001470 - 1658 0.024344 -0.009232 0.001415 - 1659 -0.010793 -0.032076 -0.013330 - 1660 -0.000393 0.010082 -0.000260 - 1661 -0.003386 0.024037 -0.002341 - 1662 0.005231 -0.007154 0.002310 - 1663 0.004778 0.000685 -0.001247 - 1664 0.006845 -0.000146 -0.002439 - 1665 0.002831 0.001509 -0.001312 - 1666 -0.004575 0.002015 0.002231 - 1667 -0.008714 0.004773 0.019310 - 1668 -0.009036 0.006437 0.017025 - 1669 -0.001102 -0.003004 0.003294 - 1670 0.004690 0.016121 0.007181 - 1671 -0.000881 -0.003815 0.001639 - 1672 -0.000053 -0.001708 0.002633 - 1673 -0.004620 0.003536 0.000715 - 1674 -0.002636 -0.005429 0.007498 - 1675 0.002307 0.001406 0.002665 - 1676 -0.005270 -0.001969 0.007587 - 1677 0.001417 -0.009022 -0.021912 - 1678 0.000203 0.002930 -0.002177 - 1679 0.003819 0.012652 -0.002939 - 1680 -0.001040 0.005171 0.022221 - 1681 -0.001765 0.004140 -0.001020 - 1682 0.015888 -0.002384 -0.000464 - 1683 -0.019573 0.014814 -0.003047 - 1684 -0.002840 -0.000626 0.000097 - 1685 0.019011 -0.004434 -0.031132 - 1686 -0.011722 0.011711 0.019623 - 1687 -0.000720 0.008278 0.001232 - 1688 -0.000014 -0.005707 0.005722 - 1689 0.006445 -0.004607 0.004541 - 1690 -0.008451 -0.005406 -0.003097 - 1691 -0.025859 -0.004092 0.011942 - 1692 0.003198 0.017013 -0.015979 - 1693 0.001237 0.005482 0.001012 - 1694 -0.003233 0.012773 -0.012817 - 1695 -0.013658 -0.008102 0.007350 - 1696 0.004867 0.002547 -0.001769 - 1697 0.019074 -0.004173 0.005165 - 1698 0.008487 0.001064 0.000080 - 1699 0.002766 -0.001251 -0.001561 - 1700 -0.019200 0.027169 -0.007481 - 1701 0.006036 -0.028485 -0.009388 - 1702 -0.005460 0.002563 0.001784 - 1703 -0.017462 0.006398 0.005231 - 1704 -0.014453 0.005484 0.004388 - 1705 0.002956 -0.001348 0.006512 - 1706 0.009654 0.004653 0.025184 - 1707 0.006226 -0.001478 -0.018062 - 1708 0.003757 -0.000921 -0.000401 - 1709 0.004307 -0.009700 -0.007768 - 1710 0.003780 -0.012914 0.008582 - 1711 0.004846 -0.002032 -0.000808 - 1712 -0.000823 -0.002500 -0.004619 - 1713 0.014769 -0.010350 0.008970 - 1714 -0.001580 -0.000837 0.000021 - 1715 -0.002003 -0.002972 -0.000158 - 1716 -0.004469 -0.000404 0.001257 - 1717 -0.001782 0.001231 -0.003624 - 1718 -0.009550 0.008477 -0.006010 - 1719 -0.003240 -0.001801 -0.002707 - 1720 -0.003131 -0.002749 -0.002782 - 1721 -0.003319 -0.008008 -0.009572 - 1722 -0.003280 -0.008289 -0.009069 - 1723 -0.006776 0.001807 0.000809 - 1724 0.000630 0.005359 0.003033 - 1725 0.016012 0.013546 0.014364 - 1726 -0.005383 0.003683 -0.001052 - 1727 -0.000343 -0.021814 -0.000655 - 1728 0.015975 0.004809 -0.015863 - 1729 -0.002843 0.002136 0.000031 - 1730 0.008511 0.002265 -0.002748 - 1731 -0.026285 -0.002274 -0.004757 - 1732 0.005294 -0.003565 0.004694 - 1733 -0.002668 0.001103 -0.001112 - 1734 -0.009429 0.006969 -0.008965 - 1735 -0.001634 0.000110 0.001819 - 1736 -0.004942 0.001203 -0.007254 - 1737 -0.002655 0.002573 -0.003610 - 1738 -0.004831 0.005860 0.001407 - 1739 -0.014232 0.009476 0.016389 - 1740 -0.017895 0.005674 -0.009379 - 1741 0.003013 -0.002508 -0.001228 - 1742 0.000746 0.006449 -0.005992 - 1743 0.006650 -0.002762 0.000152 - 1744 0.002550 -0.008457 0.001324 - 1745 -0.001868 -0.010233 -0.023525 - 1746 0.003968 -0.007880 0.008439 - 1747 -0.000591 0.004322 -0.003592 - 1748 -0.014424 0.009132 0.003708 - 1749 0.012052 -0.004950 -0.011581 - 1750 0.001849 0.003842 -0.009164 - 1751 0.009453 -0.005684 -0.004817 - 1752 0.001564 0.018776 -0.004831 - 1753 0.000794 0.000968 -0.001710 - 1754 -0.003816 -0.004723 -0.000498 - 1755 -0.011972 0.005633 -0.006975 - 1756 -0.004635 0.005064 -0.004764 - 1757 -0.010722 0.012077 -0.027297 - 1758 -0.003376 0.000707 0.006078 - 1759 0.001092 0.005159 -0.000557 - 1760 0.014326 0.002844 -0.021424 - 1761 0.019579 -0.002405 -0.009532 - 1762 -0.000565 0.006632 0.002294 - 1763 -0.025047 0.006219 0.001583 - 1764 -0.004637 -0.007484 0.007079 - 1765 0.002563 -0.001616 -0.003316 - 1766 -0.001239 0.014897 -0.002355 - 1767 -0.001256 -0.009226 0.009450 - 1768 0.001056 0.005329 -0.003831 - 1769 -0.012555 0.037676 0.021233 - 1770 -0.005969 -0.003116 -0.014248 - 1771 0.000691 0.001302 0.002405 - 1772 -0.015733 0.001224 -0.004288 - 1773 0.006783 0.015986 -0.003342 - 1774 0.002355 0.002897 -0.002965 - 1775 -0.000435 0.005789 0.007980 - 1776 0.014211 0.000855 -0.014841 - 1777 -0.004596 -0.002169 0.000774 - 1778 0.002630 -0.027237 0.012553 - 1779 -0.000727 -0.003394 -0.009924 - 1780 0.001821 -0.001310 0.000540 - 1781 0.005476 -0.002057 0.001588 - 1782 0.008060 0.013457 -0.013767 - 1783 0.003078 -0.007047 0.009501 - 1784 -0.004392 -0.004982 0.015684 - 1785 -0.021173 -0.003917 -0.003013 - 1786 0.001492 -0.007162 -0.003460 - 1787 0.020179 0.025050 0.005018 - 1788 -0.018378 -0.021938 0.007656 - 1789 -0.000363 0.004076 -0.003991 - 1790 0.012179 0.023942 -0.003853 - 1791 0.002207 0.011773 0.006443 - 1792 0.001993 0.000538 0.002365 - 1793 0.008602 -0.013779 -0.007218 - 1794 0.007374 0.001122 0.001108 - 1795 0.003207 -0.011319 -0.004081 - 1796 0.010332 -0.007827 -0.001929 - 1797 0.001869 0.022609 0.012256 - 1798 0.001101 0.003835 0.002357 - 1799 -0.003624 0.011759 0.002745 - 1800 0.001557 -0.002337 -0.004179 - 1801 0.003327 -0.001910 -0.005250 - 1802 0.011996 0.003017 0.013309 - 1803 -0.013682 -0.002775 -0.008939 - 1804 -0.002064 -0.000934 0.000427 - 1805 -0.012146 0.024406 -0.015171 - 1806 0.005030 -0.019570 0.004311 - 1807 0.003003 0.004365 0.002257 - 1808 0.000823 0.000086 -0.005161 - 1809 -0.003001 0.001206 0.008241 - 1810 0.005602 -0.001423 0.002945 - 1811 0.000330 0.001483 -0.011075 - 1812 0.003652 0.009252 -0.000166 - 1813 0.004531 -0.000860 -0.000170 - 1814 0.018728 0.013621 0.031510 - 1815 0.011579 -0.009257 -0.004100 - 1816 0.002862 0.000330 -0.002342 - 1817 -0.003456 -0.001426 -0.004566 - 1818 -0.006589 0.018593 0.018322 - 1819 -0.001663 0.002113 0.003120 - 1820 0.002523 0.005185 0.010725 - 1821 -0.006456 -0.005159 0.018366 - 1822 -0.000677 -0.000638 0.005530 - 1823 0.006499 0.011396 0.003392 - 1824 0.000945 -0.008826 -0.007441 - 1825 -0.002582 0.001006 0.000170 - 1826 -0.000739 0.010378 -0.012944 - 1827 -0.004082 -0.009693 0.012271 - 1828 -0.002259 -0.002179 0.001812 - 1829 0.004365 0.028602 0.007523 - 1830 -0.001047 0.006781 -0.010318 - 1831 0.003053 0.002227 0.004523 - 1832 -0.004297 -0.007295 0.001900 - 1833 0.002925 0.002066 0.004473 - 1834 0.003171 0.000025 0.002189 - 1835 0.001188 0.002838 0.001014 - 1836 0.006142 0.003073 -0.003689 - 1837 0.009818 0.005253 0.006222 - 1838 0.013907 -0.003607 0.006764 - 1839 -0.000327 0.015573 -0.010930 - 1840 -0.003110 -0.005538 0.000400 - 1841 0.006244 -0.021206 -0.003853 - 1842 -0.010299 0.008474 0.021147 - 1843 -0.001053 -0.000598 0.004581 - 1844 -0.013621 0.002557 -0.003175 - 1845 -0.002495 0.000789 0.011106 - 1846 -0.000137 -0.004006 -0.000014 - 1847 -0.017819 -0.013981 0.011316 - 1848 -0.005844 -0.000863 -0.025248 - 1849 -0.002799 0.002996 -0.002499 - 1850 -0.012455 0.012490 -0.004469 - 1851 0.010514 0.009490 -0.009495 - 1852 -0.000560 -0.004144 -0.000656 - 1853 -0.007255 0.002559 0.003817 - 1854 0.004602 -0.007276 0.003469 - 1855 0.000128 0.001144 -0.008402 - 1856 0.008157 0.001721 -0.014464 - 1857 -0.004034 0.002739 -0.008982 - 1858 0.002856 0.004731 -0.003812 - 1859 0.008481 -0.004184 -0.015612 - 1860 -0.004966 0.006658 -0.006541 - 1861 0.005415 -0.007185 0.002622 - 1862 -0.000791 0.004294 0.012806 - 1863 0.006266 -0.008943 0.000048 - 1864 -0.004891 -0.000259 0.002435 - 1865 0.000775 -0.012600 0.009738 - 1866 -0.000239 0.020688 0.014963 - 1867 0.007752 0.006605 0.003522 - 1868 0.005559 0.005449 0.004823 - 1869 0.001382 0.020031 -0.009484 - 1870 0.000269 -0.000837 -0.001948 - 1871 -0.015324 0.006379 0.032972 - 1872 -0.010895 -0.006739 0.002233 - 1873 0.002406 -0.005817 -0.007929 - 1874 0.011974 0.013774 0.020789 - 1875 -0.005616 -0.012309 -0.023698 - 1876 -0.002712 -0.000118 0.000894 - 1877 -0.000559 -0.018665 -0.005699 - 1878 -0.022904 -0.016730 0.007620 - 1879 -0.006235 -0.000119 -0.005440 - 1880 -0.008616 0.001720 0.002602 - 1881 -0.019263 0.001295 0.018377 - 1882 -0.002493 0.002824 -0.002915 - 1883 0.007384 0.000692 0.003462 - 1884 -0.019228 -0.005451 0.005676 - 1885 0.002956 0.004628 -0.002177 - 1886 0.005617 0.021792 -0.005623 - 1887 -0.010771 -0.007154 -0.002600 - 1888 -0.006932 -0.006388 0.001795 - 1889 -0.026638 0.002211 0.017012 - 1890 -0.006429 -0.013703 0.021233 - 1891 0.004179 0.001508 -0.002942 - 1892 -0.015358 0.009799 -0.025507 - 1893 -0.009827 0.001263 -0.015038 - 1894 0.002515 0.004808 -0.006083 - 1895 -0.001395 -0.005178 0.010798 - 1896 0.005498 0.001296 -0.013456 - 1897 -0.006679 0.000004 0.000833 - 1898 -0.006339 0.003210 0.000555 - 1899 -0.007815 -0.000155 0.006317 - 1900 -0.003334 -0.000730 -0.000139 - 1901 -0.003197 -0.021225 -0.009098 - 1902 0.003310 -0.008203 -0.004863 - 1903 -0.007379 0.001152 -0.003847 - 1904 -0.008175 0.003836 -0.004939 - 1905 -0.007216 0.002039 -0.012076 - 1906 -0.002751 -0.006050 -0.001404 - 1907 -0.005827 0.008129 0.005351 - 1908 0.010377 0.010628 0.018761 - 1909 -0.002571 -0.007065 0.006215 - 1910 -0.004848 -0.014622 0.001577 - 1911 -0.004351 -0.002361 0.020679 - 1912 0.006139 0.001291 0.002464 - 1913 0.004939 0.003608 0.002097 - 1914 0.004274 0.000152 0.002451 - 1915 0.002989 0.000832 -0.000352 - 1916 -0.014159 -0.000914 0.002187 - 1917 0.012237 -0.003167 0.009134 - 1918 -0.004575 -0.001662 0.000082 - 1919 -0.007883 -0.002056 0.002571 - 1920 -0.003336 -0.001305 -0.000658 - 1921 0.004366 0.000439 0.001158 - 1922 -0.000155 0.003368 0.010592 - 1923 -0.014972 -0.009424 -0.018312 - 1924 -0.000613 -0.002374 0.000797 - 1925 0.007460 -0.016336 -0.000977 - 1926 -0.006787 0.004573 0.010255 - 1927 -0.002452 -0.000122 0.000124 - 1928 -0.015584 -0.009431 -0.007285 - 1929 -0.000101 0.008080 -0.015191 - 1930 0.002197 0.002310 -0.001612 - 1931 0.016237 -0.005090 0.018070 - 1932 0.001709 -0.003220 -0.011865 - 1933 -0.001150 0.000898 0.004173 - 1934 0.000323 -0.000312 -0.014495 - 1935 0.000516 -0.000491 -0.011422 - 1936 -0.005815 -0.002965 0.000187 - 1937 0.008195 0.018425 -0.027236 - 1938 -0.010921 -0.007575 -0.002217 - 1939 -0.004740 0.002745 0.006330 - 1940 0.002035 0.006523 0.010880 - 1941 -0.012191 0.004818 0.006605 - 1942 -0.003197 -0.004418 -0.003375 - 1943 0.003590 -0.017196 0.008070 - 1944 0.004548 0.006106 0.016045 - 1945 0.005444 0.002200 0.004561 - 1946 0.004448 0.009092 -0.001577 - 1947 -0.000522 0.006033 0.006559 - 1948 0.005450 0.001267 0.002269 - 1949 0.027952 -0.012604 0.001935 - 1950 -0.004826 -0.018174 0.014813 - 1951 0.005498 -0.000626 0.001156 - 1952 0.001428 -0.010472 0.000805 - 1953 -0.010198 -0.005573 -0.014564 - 1954 0.001605 -0.006572 0.005587 - 1955 -0.002403 -0.004981 0.000460 - 1956 0.010287 -0.003414 0.005774 - 1957 -0.005679 0.003540 -0.003175 - 1958 -0.005054 0.005203 -0.002733 - 1959 -0.006462 0.003843 0.002657 - 1960 -0.006606 -0.002499 -0.001538 - 1961 0.027567 -0.002565 0.034908 - 1962 0.001905 -0.003739 -0.001134 - 1963 -0.000871 0.002779 0.006534 - 1964 -0.013473 -0.002631 0.001200 - 1965 -0.008136 0.003625 0.001725 - 1966 0.002375 -0.002767 -0.000214 - 1967 0.015603 0.001192 0.006785 - 1968 -0.008229 0.002751 0.010337 - 1969 -0.002111 -0.006139 0.006236 - 1970 0.025783 -0.003684 0.015052 - 1971 -0.008026 -0.018580 0.028847 - 1972 -0.001966 -0.005103 0.002533 - 1973 0.025504 -0.012928 0.014439 - 1974 0.015919 0.008653 -0.013047 - 1975 -0.002145 -0.003853 -0.002353 - 1976 0.020573 0.023626 0.033600 - 1977 0.002418 -0.000127 0.000258 - 1978 -0.000168 -0.002747 0.002505 - 1979 0.011847 0.007945 0.003222 - 1980 0.002222 -0.001343 0.005437 - 1981 -0.004734 0.003071 -0.000955 - 1982 0.003752 -0.001882 -0.005052 - 1983 -0.008195 0.007844 0.004577 - 1984 0.007575 0.002209 -0.000466 - 1985 -0.005510 0.009650 -0.004399 - 1986 0.018263 0.019292 -0.008157 - 1987 -0.005098 -0.001581 -0.000328 - 1988 -0.004522 -0.021884 -0.005509 - 1989 -0.001598 -0.001668 0.002704 - 1990 -0.000494 0.002205 0.012458 - 1991 0.003153 0.001522 0.015672 - 1992 -0.000092 -0.002603 0.010098 - 1993 0.001919 -0.007389 0.001539 - 1994 -0.002690 -0.003376 -0.009963 - 1995 -0.005006 0.002932 -0.001670 - 1996 -0.003089 -0.005736 0.003689 - 1997 0.010713 -0.027613 -0.023000 - 1998 -0.006878 0.009457 0.006998 - 1999 -0.001817 0.000266 -0.004238 - 2000 -0.010974 0.005190 0.000117 - 2001 -0.008937 -0.003277 0.004337 - 2002 -0.000987 -0.001334 -0.004265 - 2003 -0.022280 -0.011677 -0.018343 - 2004 -0.010076 -0.005729 -0.026032 - -Bonds - - 1 3 1 7 - 2 2 1 3 - 3 1 1 2 - 4 4 2 5 - 5 4 2 6 - 6 4 2 4 - 7 6 7 19 - 8 5 7 8 - 9 1 8 9 - 10 7 8 11 - 11 8 8 20 - 12 3 9 28 - 13 2 9 10 - 14 10 11 21 - 15 9 11 12 - 16 10 11 22 - 17 11 12 14 - 18 11 12 13 - 19 12 13 23 - 20 11 13 15 - 21 12 14 24 - 22 11 14 16 - 23 11 15 17 - 24 12 15 25 - 25 11 16 17 - 26 12 16 26 - 27 13 17 18 - 28 14 18 27 - 29 5 28 29 - 30 6 28 32 - 31 1 29 30 - 32 8 29 33 - 33 8 29 34 - 34 3 30 35 - 35 2 30 31 - 36 5 35 36 - 37 6 35 39 - 38 1 36 37 - 39 8 36 40 - 40 8 36 41 - 41 2 37 38 - 42 3 37 42 - 43 6 42 53 - 44 5 42 43 - 45 1 43 44 - 46 7 43 46 - 47 8 43 54 - 48 3 44 62 - 49 2 44 45 - 50 10 46 56 - 51 10 46 55 - 52 9 46 47 - 53 11 47 48 - 54 11 47 49 - 55 11 48 50 - 56 12 48 57 - 57 11 49 51 - 58 12 49 58 - 59 11 50 52 - 60 12 50 59 - 61 11 51 52 - 62 12 51 60 - 63 12 52 61 - 64 6 62 70 - 65 5 62 63 - 66 7 63 66 - 67 1 63 64 - 68 8 63 71 - 69 2 64 65 - 70 3 64 79 - 71 15 66 67 - 72 10 66 73 - 73 10 66 72 - 74 10 67 75 - 75 10 67 74 - 76 16 67 68 - 77 17 68 69 - 78 4 69 76 - 79 4 69 78 - 80 4 69 77 - 81 5 79 80 - 82 6 79 81 - 83 4 80 84 - 84 4 80 83 - 85 4 80 82 - 86 18 85 86 - 87 18 85 87 - 88 18 88 90 - 89 18 88 89 - 90 18 91 93 - 91 18 91 92 - 92 18 94 96 - 93 18 94 95 - 94 18 97 98 - 95 18 97 99 - 96 18 100 101 - 97 18 100 102 - 98 18 103 104 - 99 18 103 105 - 100 18 106 107 - 101 18 106 108 - 102 18 109 111 - 103 18 109 110 - 104 18 112 114 - 105 18 112 113 - 106 18 115 116 - 107 18 115 117 - 108 18 118 120 - 109 18 118 119 - 110 18 121 123 - 111 18 121 122 - 112 18 124 126 - 113 18 124 125 - 114 18 127 128 - 115 18 127 129 - 116 18 130 132 - 117 18 130 131 - 118 18 133 134 - 119 18 133 135 - 120 18 136 137 - 121 18 136 138 - 122 18 139 140 - 123 18 139 141 - 124 18 142 144 - 125 18 142 143 - 126 18 145 147 - 127 18 145 146 - 128 18 148 150 - 129 18 148 149 - 130 18 151 152 - 131 18 151 153 - 132 18 154 156 - 133 18 154 155 - 134 18 157 159 - 135 18 157 158 - 136 18 160 162 - 137 18 160 161 - 138 18 163 164 - 139 18 163 165 - 140 18 166 168 - 141 18 166 167 - 142 18 169 171 - 143 18 169 170 - 144 18 172 174 - 145 18 172 173 - 146 18 175 177 - 147 18 175 176 - 148 18 178 180 - 149 18 178 179 - 150 18 181 182 - 151 18 181 183 - 152 18 184 186 - 153 18 184 185 - 154 18 187 188 - 155 18 187 189 - 156 18 190 191 - 157 18 190 192 - 158 18 193 194 - 159 18 193 195 - 160 18 196 197 - 161 18 196 198 - 162 18 199 201 - 163 18 199 200 - 164 18 202 204 - 165 18 202 203 - 166 18 205 206 - 167 18 205 207 - 168 18 208 210 - 169 18 208 209 - 170 18 211 212 - 171 18 211 213 - 172 18 214 215 - 173 18 214 216 - 174 18 217 219 - 175 18 217 218 - 176 18 220 222 - 177 18 220 221 - 178 18 223 224 - 179 18 223 225 - 180 18 226 228 - 181 18 226 227 - 182 18 229 231 - 183 18 229 230 - 184 18 232 233 - 185 18 232 234 - 186 18 235 236 - 187 18 235 237 - 188 18 238 240 - 189 18 238 239 - 190 18 241 242 - 191 18 241 243 - 192 18 244 246 - 193 18 244 245 - 194 18 247 248 - 195 18 247 249 - 196 18 250 251 - 197 18 250 252 - 198 18 253 254 - 199 18 253 255 - 200 18 256 257 - 201 18 256 258 - 202 18 259 261 - 203 18 259 260 - 204 18 262 264 - 205 18 262 263 - 206 18 265 266 - 207 18 265 267 - 208 18 268 269 - 209 18 268 270 - 210 18 271 272 - 211 18 271 273 - 212 18 274 275 - 213 18 274 276 - 214 18 277 279 - 215 18 277 278 - 216 18 280 282 - 217 18 280 281 - 218 18 283 284 - 219 18 283 285 - 220 18 286 287 - 221 18 286 288 - 222 18 289 290 - 223 18 289 291 - 224 18 292 294 - 225 18 292 293 - 226 18 295 296 - 227 18 295 297 - 228 18 298 299 - 229 18 298 300 - 230 18 301 303 - 231 18 301 302 - 232 18 304 305 - 233 18 304 306 - 234 18 307 309 - 235 18 307 308 - 236 18 310 311 - 237 18 310 312 - 238 18 313 314 - 239 18 313 315 - 240 18 316 317 - 241 18 316 318 - 242 18 319 321 - 243 18 319 320 - 244 18 322 323 - 245 18 322 324 - 246 18 325 327 - 247 18 325 326 - 248 18 328 329 - 249 18 328 330 - 250 18 331 332 - 251 18 331 333 - 252 18 334 335 - 253 18 334 336 - 254 18 337 339 - 255 18 337 338 - 256 18 340 341 - 257 18 340 342 - 258 18 343 344 - 259 18 343 345 - 260 18 346 347 - 261 18 346 348 - 262 18 349 350 - 263 18 349 351 - 264 18 352 353 - 265 18 352 354 - 266 18 355 356 - 267 18 355 357 - 268 18 358 359 - 269 18 358 360 - 270 18 361 362 - 271 18 361 363 - 272 18 364 365 - 273 18 364 366 - 274 18 367 369 - 275 18 367 368 - 276 18 370 372 - 277 18 370 371 - 278 18 373 374 - 279 18 373 375 - 280 18 376 378 - 281 18 376 377 - 282 18 379 381 - 283 18 379 380 - 284 18 382 383 - 285 18 382 384 - 286 18 385 386 - 287 18 385 387 - 288 18 388 390 - 289 18 388 389 - 290 18 391 393 - 291 18 391 392 - 292 18 394 395 - 293 18 394 396 - 294 18 397 399 - 295 18 397 398 - 296 18 400 402 - 297 18 400 401 - 298 18 403 405 - 299 18 403 404 - 300 18 406 407 - 301 18 406 408 - 302 18 409 411 - 303 18 409 410 - 304 18 412 413 - 305 18 412 414 - 306 18 415 417 - 307 18 415 416 - 308 18 418 420 - 309 18 418 419 - 310 18 421 422 - 311 18 421 423 - 312 18 424 425 - 313 18 424 426 - 314 18 427 428 - 315 18 427 429 - 316 18 430 432 - 317 18 430 431 - 318 18 433 435 - 319 18 433 434 - 320 18 436 437 - 321 18 436 438 - 322 18 439 440 - 323 18 439 441 - 324 18 442 443 - 325 18 442 444 - 326 18 445 447 - 327 18 445 446 - 328 18 448 449 - 329 18 448 450 - 330 18 451 453 - 331 18 451 452 - 332 18 454 456 - 333 18 454 455 - 334 18 457 458 - 335 18 457 459 - 336 18 460 462 - 337 18 460 461 - 338 18 463 465 - 339 18 463 464 - 340 18 466 467 - 341 18 466 468 - 342 18 469 470 - 343 18 469 471 - 344 18 472 473 - 345 18 472 474 - 346 18 475 476 - 347 18 475 477 - 348 18 478 479 - 349 18 478 480 - 350 18 481 482 - 351 18 481 483 - 352 18 484 485 - 353 18 484 486 - 354 18 487 489 - 355 18 487 488 - 356 18 490 492 - 357 18 490 491 - 358 18 493 495 - 359 18 493 494 - 360 18 496 497 - 361 18 496 498 - 362 18 499 501 - 363 18 499 500 - 364 18 502 503 - 365 18 502 504 - 366 18 505 507 - 367 18 505 506 - 368 18 508 509 - 369 18 508 510 - 370 18 511 513 - 371 18 511 512 - 372 18 514 516 - 373 18 514 515 - 374 18 517 518 - 375 18 517 519 - 376 18 520 521 - 377 18 520 522 - 378 18 523 525 - 379 18 523 524 - 380 18 526 528 - 381 18 526 527 - 382 18 529 530 - 383 18 529 531 - 384 18 532 533 - 385 18 532 534 - 386 18 535 536 - 387 18 535 537 - 388 18 538 540 - 389 18 538 539 - 390 18 541 542 - 391 18 541 543 - 392 18 544 546 - 393 18 544 545 - 394 18 547 549 - 395 18 547 548 - 396 18 550 551 - 397 18 550 552 - 398 18 553 555 - 399 18 553 554 - 400 18 556 557 - 401 18 556 558 - 402 18 559 561 - 403 18 559 560 - 404 18 562 563 - 405 18 562 564 - 406 18 565 567 - 407 18 565 566 - 408 18 568 570 - 409 18 568 569 - 410 18 571 573 - 411 18 571 572 - 412 18 574 575 - 413 18 574 576 - 414 18 577 579 - 415 18 577 578 - 416 18 580 581 - 417 18 580 582 - 418 18 583 585 - 419 18 583 584 - 420 18 586 588 - 421 18 586 587 - 422 18 589 590 - 423 18 589 591 - 424 18 592 594 - 425 18 592 593 - 426 18 595 597 - 427 18 595 596 - 428 18 598 600 - 429 18 598 599 - 430 18 601 602 - 431 18 601 603 - 432 18 604 606 - 433 18 604 605 - 434 18 607 609 - 435 18 607 608 - 436 18 610 611 - 437 18 610 612 - 438 18 613 615 - 439 18 613 614 - 440 18 616 618 - 441 18 616 617 - 442 18 619 620 - 443 18 619 621 - 444 18 622 623 - 445 18 622 624 - 446 18 625 627 - 447 18 625 626 - 448 18 628 629 - 449 18 628 630 - 450 18 631 632 - 451 18 631 633 - 452 18 634 635 - 453 18 634 636 - 454 18 637 639 - 455 18 637 638 - 456 18 640 642 - 457 18 640 641 - 458 18 643 644 - 459 18 643 645 - 460 18 646 647 - 461 18 646 648 - 462 18 649 650 - 463 18 649 651 - 464 18 652 653 - 465 18 652 654 - 466 18 655 657 - 467 18 655 656 - 468 18 658 660 - 469 18 658 659 - 470 18 661 663 - 471 18 661 662 - 472 18 664 665 - 473 18 664 666 - 474 18 667 669 - 475 18 667 668 - 476 18 670 672 - 477 18 670 671 - 478 18 673 674 - 479 18 673 675 - 480 18 676 677 - 481 18 676 678 - 482 18 679 681 - 483 18 679 680 - 484 18 682 684 - 485 18 682 683 - 486 18 685 686 - 487 18 685 687 - 488 18 688 690 - 489 18 688 689 - 490 18 691 693 - 491 18 691 692 - 492 18 694 695 - 493 18 694 696 - 494 18 697 698 - 495 18 697 699 - 496 18 700 701 - 497 18 700 702 - 498 18 703 704 - 499 18 703 705 - 500 18 706 707 - 501 18 706 708 - 502 18 709 710 - 503 18 709 711 - 504 18 712 714 - 505 18 712 713 - 506 18 715 716 - 507 18 715 717 - 508 18 718 719 - 509 18 718 720 - 510 18 721 722 - 511 18 721 723 - 512 18 724 726 - 513 18 724 725 - 514 18 727 728 - 515 18 727 729 - 516 18 730 731 - 517 18 730 732 - 518 18 733 735 - 519 18 733 734 - 520 18 736 737 - 521 18 736 738 - 522 18 739 741 - 523 18 739 740 - 524 18 742 743 - 525 18 742 744 - 526 18 745 746 - 527 18 745 747 - 528 18 748 750 - 529 18 748 749 - 530 18 751 753 - 531 18 751 752 - 532 18 754 756 - 533 18 754 755 - 534 18 757 758 - 535 18 757 759 - 536 18 760 762 - 537 18 760 761 - 538 18 763 764 - 539 18 763 765 - 540 18 766 767 - 541 18 766 768 - 542 18 769 770 - 543 18 769 771 - 544 18 772 774 - 545 18 772 773 - 546 18 775 777 - 547 18 775 776 - 548 18 778 780 - 549 18 778 779 - 550 18 781 783 - 551 18 781 782 - 552 18 784 786 - 553 18 784 785 - 554 18 787 789 - 555 18 787 788 - 556 18 790 791 - 557 18 790 792 - 558 18 793 795 - 559 18 793 794 - 560 18 796 797 - 561 18 796 798 - 562 18 799 801 - 563 18 799 800 - 564 18 802 803 - 565 18 802 804 - 566 18 805 806 - 567 18 805 807 - 568 18 808 809 - 569 18 808 810 - 570 18 811 813 - 571 18 811 812 - 572 18 814 815 - 573 18 814 816 - 574 18 817 818 - 575 18 817 819 - 576 18 820 821 - 577 18 820 822 - 578 18 823 824 - 579 18 823 825 - 580 18 826 828 - 581 18 826 827 - 582 18 829 830 - 583 18 829 831 - 584 18 832 834 - 585 18 832 833 - 586 18 835 837 - 587 18 835 836 - 588 18 838 839 - 589 18 838 840 - 590 18 841 842 - 591 18 841 843 - 592 18 844 845 - 593 18 844 846 - 594 18 847 848 - 595 18 847 849 - 596 18 850 852 - 597 18 850 851 - 598 18 853 854 - 599 18 853 855 - 600 18 856 858 - 601 18 856 857 - 602 18 859 861 - 603 18 859 860 - 604 18 862 863 - 605 18 862 864 - 606 18 865 866 - 607 18 865 867 - 608 18 868 869 - 609 18 868 870 - 610 18 871 873 - 611 18 871 872 - 612 18 874 875 - 613 18 874 876 - 614 18 877 878 - 615 18 877 879 - 616 18 880 882 - 617 18 880 881 - 618 18 883 884 - 619 18 883 885 - 620 18 886 887 - 621 18 886 888 - 622 18 889 891 - 623 18 889 890 - 624 18 892 894 - 625 18 892 893 - 626 18 895 896 - 627 18 895 897 - 628 18 898 899 - 629 18 898 900 - 630 18 901 903 - 631 18 901 902 - 632 18 904 905 - 633 18 904 906 - 634 18 907 908 - 635 18 907 909 - 636 18 910 911 - 637 18 910 912 - 638 18 913 915 - 639 18 913 914 - 640 18 916 917 - 641 18 916 918 - 642 18 919 920 - 643 18 919 921 - 644 18 922 924 - 645 18 922 923 - 646 18 925 927 - 647 18 925 926 - 648 18 928 930 - 649 18 928 929 - 650 18 931 932 - 651 18 931 933 - 652 18 934 935 - 653 18 934 936 - 654 18 937 939 - 655 18 937 938 - 656 18 940 942 - 657 18 940 941 - 658 18 943 945 - 659 18 943 944 - 660 18 946 948 - 661 18 946 947 - 662 18 949 950 - 663 18 949 951 - 664 18 952 953 - 665 18 952 954 - 666 18 955 956 - 667 18 955 957 - 668 18 958 960 - 669 18 958 959 - 670 18 961 963 - 671 18 961 962 - 672 18 964 965 - 673 18 964 966 - 674 18 967 969 - 675 18 967 968 - 676 18 970 972 - 677 18 970 971 - 678 18 973 975 - 679 18 973 974 - 680 18 976 978 - 681 18 976 977 - 682 18 979 981 - 683 18 979 980 - 684 18 982 983 - 685 18 982 984 - 686 18 985 987 - 687 18 985 986 - 688 18 988 989 - 689 18 988 990 - 690 18 991 993 - 691 18 991 992 - 692 18 994 996 - 693 18 994 995 - 694 18 997 998 - 695 18 997 999 - 696 18 1000 1001 - 697 18 1000 1002 - 698 18 1003 1005 - 699 18 1003 1004 - 700 18 1006 1007 - 701 18 1006 1008 - 702 18 1009 1011 - 703 18 1009 1010 - 704 18 1012 1013 - 705 18 1012 1014 - 706 18 1015 1017 - 707 18 1015 1016 - 708 18 1018 1020 - 709 18 1018 1019 - 710 18 1021 1023 - 711 18 1021 1022 - 712 18 1024 1025 - 713 18 1024 1026 - 714 18 1027 1028 - 715 18 1027 1029 - 716 18 1030 1032 - 717 18 1030 1031 - 718 18 1033 1034 - 719 18 1033 1035 - 720 18 1036 1037 - 721 18 1036 1038 - 722 18 1039 1041 - 723 18 1039 1040 - 724 18 1042 1043 - 725 18 1042 1044 - 726 18 1045 1046 - 727 18 1045 1047 - 728 18 1048 1050 - 729 18 1048 1049 - 730 18 1051 1053 - 731 18 1051 1052 - 732 18 1054 1056 - 733 18 1054 1055 - 734 18 1057 1058 - 735 18 1057 1059 - 736 18 1060 1062 - 737 18 1060 1061 - 738 18 1063 1064 - 739 18 1063 1065 - 740 18 1066 1068 - 741 18 1066 1067 - 742 18 1069 1071 - 743 18 1069 1070 - 744 18 1072 1074 - 745 18 1072 1073 - 746 18 1075 1077 - 747 18 1075 1076 - 748 18 1078 1079 - 749 18 1078 1080 - 750 18 1081 1082 - 751 18 1081 1083 - 752 18 1084 1085 - 753 18 1084 1086 - 754 18 1087 1089 - 755 18 1087 1088 - 756 18 1090 1092 - 757 18 1090 1091 - 758 18 1093 1095 - 759 18 1093 1094 - 760 18 1096 1097 - 761 18 1096 1098 - 762 18 1099 1100 - 763 18 1099 1101 - 764 18 1102 1103 - 765 18 1102 1104 - 766 18 1105 1107 - 767 18 1105 1106 - 768 18 1108 1110 - 769 18 1108 1109 - 770 18 1111 1112 - 771 18 1111 1113 - 772 18 1114 1116 - 773 18 1114 1115 - 774 18 1117 1119 - 775 18 1117 1118 - 776 18 1120 1121 - 777 18 1120 1122 - 778 18 1123 1124 - 779 18 1123 1125 - 780 18 1126 1128 - 781 18 1126 1127 - 782 18 1129 1130 - 783 18 1129 1131 - 784 18 1132 1133 - 785 18 1132 1134 - 786 18 1135 1137 - 787 18 1135 1136 - 788 18 1138 1140 - 789 18 1138 1139 - 790 18 1141 1142 - 791 18 1141 1143 - 792 18 1144 1146 - 793 18 1144 1145 - 794 18 1147 1149 - 795 18 1147 1148 - 796 18 1150 1152 - 797 18 1150 1151 - 798 18 1153 1155 - 799 18 1153 1154 - 800 18 1156 1158 - 801 18 1156 1157 - 802 18 1159 1160 - 803 18 1159 1161 - 804 18 1162 1164 - 805 18 1162 1163 - 806 18 1165 1166 - 807 18 1165 1167 - 808 18 1168 1170 - 809 18 1168 1169 - 810 18 1171 1172 - 811 18 1171 1173 - 812 18 1174 1175 - 813 18 1174 1176 - 814 18 1177 1179 - 815 18 1177 1178 - 816 18 1180 1182 - 817 18 1180 1181 - 818 18 1183 1185 - 819 18 1183 1184 - 820 18 1186 1187 - 821 18 1186 1188 - 822 18 1189 1190 - 823 18 1189 1191 - 824 18 1192 1194 - 825 18 1192 1193 - 826 18 1195 1196 - 827 18 1195 1197 - 828 18 1198 1199 - 829 18 1198 1200 - 830 18 1201 1202 - 831 18 1201 1203 - 832 18 1204 1205 - 833 18 1204 1206 - 834 18 1207 1209 - 835 18 1207 1208 - 836 18 1210 1212 - 837 18 1210 1211 - 838 18 1213 1214 - 839 18 1213 1215 - 840 18 1216 1218 - 841 18 1216 1217 - 842 18 1219 1221 - 843 18 1219 1220 - 844 18 1222 1224 - 845 18 1222 1223 - 846 18 1225 1226 - 847 18 1225 1227 - 848 18 1228 1229 - 849 18 1228 1230 - 850 18 1231 1232 - 851 18 1231 1233 - 852 18 1234 1236 - 853 18 1234 1235 - 854 18 1237 1239 - 855 18 1237 1238 - 856 18 1240 1242 - 857 18 1240 1241 - 858 18 1243 1244 - 859 18 1243 1245 - 860 18 1246 1248 - 861 18 1246 1247 - 862 18 1249 1250 - 863 18 1249 1251 - 864 18 1252 1254 - 865 18 1252 1253 - 866 18 1255 1256 - 867 18 1255 1257 - 868 18 1258 1259 - 869 18 1258 1260 - 870 18 1261 1263 - 871 18 1261 1262 - 872 18 1264 1265 - 873 18 1264 1266 - 874 18 1267 1268 - 875 18 1267 1269 - 876 18 1270 1271 - 877 18 1270 1272 - 878 18 1273 1274 - 879 18 1273 1275 - 880 18 1276 1277 - 881 18 1276 1278 - 882 18 1279 1280 - 883 18 1279 1281 - 884 18 1282 1283 - 885 18 1282 1284 - 886 18 1285 1286 - 887 18 1285 1287 - 888 18 1288 1289 - 889 18 1288 1290 - 890 18 1291 1293 - 891 18 1291 1292 - 892 18 1294 1295 - 893 18 1294 1296 - 894 18 1297 1299 - 895 18 1297 1298 - 896 18 1300 1302 - 897 18 1300 1301 - 898 18 1303 1304 - 899 18 1303 1305 - 900 18 1306 1308 - 901 18 1306 1307 - 902 18 1309 1311 - 903 18 1309 1310 - 904 18 1312 1314 - 905 18 1312 1313 - 906 18 1315 1317 - 907 18 1315 1316 - 908 18 1318 1320 - 909 18 1318 1319 - 910 18 1321 1323 - 911 18 1321 1322 - 912 18 1324 1325 - 913 18 1324 1326 - 914 18 1327 1329 - 915 18 1327 1328 - 916 18 1330 1332 - 917 18 1330 1331 - 918 18 1333 1334 - 919 18 1333 1335 - 920 18 1336 1337 - 921 18 1336 1338 - 922 18 1339 1340 - 923 18 1339 1341 - 924 18 1342 1344 - 925 18 1342 1343 - 926 18 1345 1347 - 927 18 1345 1346 - 928 18 1348 1350 - 929 18 1348 1349 - 930 18 1351 1352 - 931 18 1351 1353 - 932 18 1354 1355 - 933 18 1354 1356 - 934 18 1357 1358 - 935 18 1357 1359 - 936 18 1360 1362 - 937 18 1360 1361 - 938 18 1363 1365 - 939 18 1363 1364 - 940 18 1366 1368 - 941 18 1366 1367 - 942 18 1369 1370 - 943 18 1369 1371 - 944 18 1372 1373 - 945 18 1372 1374 - 946 18 1375 1377 - 947 18 1375 1376 - 948 18 1378 1379 - 949 18 1378 1380 - 950 18 1381 1382 - 951 18 1381 1383 - 952 18 1384 1385 - 953 18 1384 1386 - 954 18 1387 1388 - 955 18 1387 1389 - 956 18 1390 1392 - 957 18 1390 1391 - 958 18 1393 1395 - 959 18 1393 1394 - 960 18 1396 1397 - 961 18 1396 1398 - 962 18 1399 1401 - 963 18 1399 1400 - 964 18 1402 1403 - 965 18 1402 1404 - 966 18 1405 1406 - 967 18 1405 1407 - 968 18 1408 1409 - 969 18 1408 1410 - 970 18 1411 1412 - 971 18 1411 1413 - 972 18 1414 1416 - 973 18 1414 1415 - 974 18 1417 1419 - 975 18 1417 1418 - 976 18 1420 1422 - 977 18 1420 1421 - 978 18 1423 1425 - 979 18 1423 1424 - 980 18 1426 1428 - 981 18 1426 1427 - 982 18 1429 1430 - 983 18 1429 1431 - 984 18 1432 1434 - 985 18 1432 1433 - 986 18 1435 1436 - 987 18 1435 1437 - 988 18 1438 1439 - 989 18 1438 1440 - 990 18 1441 1442 - 991 18 1441 1443 - 992 18 1444 1445 - 993 18 1444 1446 - 994 18 1447 1448 - 995 18 1447 1449 - 996 18 1450 1451 - 997 18 1450 1452 - 998 18 1453 1455 - 999 18 1453 1454 - 1000 18 1456 1457 - 1001 18 1456 1458 - 1002 18 1459 1461 - 1003 18 1459 1460 - 1004 18 1462 1463 - 1005 18 1462 1464 - 1006 18 1465 1466 - 1007 18 1465 1467 - 1008 18 1468 1470 - 1009 18 1468 1469 - 1010 18 1471 1472 - 1011 18 1471 1473 - 1012 18 1474 1476 - 1013 18 1474 1475 - 1014 18 1477 1478 - 1015 18 1477 1479 - 1016 18 1480 1482 - 1017 18 1480 1481 - 1018 18 1483 1485 - 1019 18 1483 1484 - 1020 18 1486 1488 - 1021 18 1486 1487 - 1022 18 1489 1491 - 1023 18 1489 1490 - 1024 18 1492 1493 - 1025 18 1492 1494 - 1026 18 1495 1496 - 1027 18 1495 1497 - 1028 18 1498 1499 - 1029 18 1498 1500 - 1030 18 1501 1502 - 1031 18 1501 1503 - 1032 18 1504 1505 - 1033 18 1504 1506 - 1034 18 1507 1509 - 1035 18 1507 1508 - 1036 18 1510 1512 - 1037 18 1510 1511 - 1038 18 1513 1515 - 1039 18 1513 1514 - 1040 18 1516 1518 - 1041 18 1516 1517 - 1042 18 1519 1520 - 1043 18 1519 1521 - 1044 18 1522 1524 - 1045 18 1522 1523 - 1046 18 1525 1526 - 1047 18 1525 1527 - 1048 18 1528 1529 - 1049 18 1528 1530 - 1050 18 1531 1533 - 1051 18 1531 1532 - 1052 18 1534 1536 - 1053 18 1534 1535 - 1054 18 1537 1539 - 1055 18 1537 1538 - 1056 18 1540 1541 - 1057 18 1540 1542 - 1058 18 1543 1545 - 1059 18 1543 1544 - 1060 18 1546 1547 - 1061 18 1546 1548 - 1062 18 1549 1551 - 1063 18 1549 1550 - 1064 18 1552 1553 - 1065 18 1552 1554 - 1066 18 1555 1557 - 1067 18 1555 1556 - 1068 18 1558 1559 - 1069 18 1558 1560 - 1070 18 1561 1562 - 1071 18 1561 1563 - 1072 18 1564 1565 - 1073 18 1564 1566 - 1074 18 1567 1569 - 1075 18 1567 1568 - 1076 18 1570 1571 - 1077 18 1570 1572 - 1078 18 1573 1575 - 1079 18 1573 1574 - 1080 18 1576 1578 - 1081 18 1576 1577 - 1082 18 1579 1581 - 1083 18 1579 1580 - 1084 18 1582 1584 - 1085 18 1582 1583 - 1086 18 1585 1586 - 1087 18 1585 1587 - 1088 18 1588 1590 - 1089 18 1588 1589 - 1090 18 1591 1592 - 1091 18 1591 1593 - 1092 18 1594 1596 - 1093 18 1594 1595 - 1094 18 1597 1598 - 1095 18 1597 1599 - 1096 18 1600 1602 - 1097 18 1600 1601 - 1098 18 1603 1605 - 1099 18 1603 1604 - 1100 18 1606 1608 - 1101 18 1606 1607 - 1102 18 1609 1610 - 1103 18 1609 1611 - 1104 18 1612 1614 - 1105 18 1612 1613 - 1106 18 1615 1617 - 1107 18 1615 1616 - 1108 18 1618 1620 - 1109 18 1618 1619 - 1110 18 1621 1623 - 1111 18 1621 1622 - 1112 18 1624 1625 - 1113 18 1624 1626 - 1114 18 1627 1629 - 1115 18 1627 1628 - 1116 18 1630 1631 - 1117 18 1630 1632 - 1118 18 1633 1635 - 1119 18 1633 1634 - 1120 18 1636 1637 - 1121 18 1636 1638 - 1122 18 1639 1641 - 1123 18 1639 1640 - 1124 18 1642 1643 - 1125 18 1642 1644 - 1126 18 1645 1646 - 1127 18 1645 1647 - 1128 18 1648 1650 - 1129 18 1648 1649 - 1130 18 1651 1653 - 1131 18 1651 1652 - 1132 18 1654 1656 - 1133 18 1654 1655 - 1134 18 1657 1658 - 1135 18 1657 1659 - 1136 18 1660 1661 - 1137 18 1660 1662 - 1138 18 1663 1664 - 1139 18 1663 1665 - 1140 18 1666 1668 - 1141 18 1666 1667 - 1142 18 1669 1670 - 1143 18 1669 1671 - 1144 18 1672 1674 - 1145 18 1672 1673 - 1146 18 1675 1676 - 1147 18 1675 1677 - 1148 18 1678 1680 - 1149 18 1678 1679 - 1150 18 1681 1683 - 1151 18 1681 1682 - 1152 18 1684 1685 - 1153 18 1684 1686 - 1154 18 1687 1688 - 1155 18 1687 1689 - 1156 18 1690 1691 - 1157 18 1690 1692 - 1158 18 1693 1695 - 1159 18 1693 1694 - 1160 18 1696 1697 - 1161 18 1696 1698 - 1162 18 1699 1701 - 1163 18 1699 1700 - 1164 18 1702 1703 - 1165 18 1702 1704 - 1166 18 1705 1707 - 1167 18 1705 1706 - 1168 18 1708 1709 - 1169 18 1708 1710 - 1170 18 1711 1712 - 1171 18 1711 1713 - 1172 18 1714 1716 - 1173 18 1714 1715 - 1174 18 1717 1718 - 1175 18 1717 1719 - 1176 18 1720 1721 - 1177 18 1720 1722 - 1178 18 1723 1724 - 1179 18 1723 1725 - 1180 18 1726 1727 - 1181 18 1726 1728 - 1182 18 1729 1730 - 1183 18 1729 1731 - 1184 18 1732 1734 - 1185 18 1732 1733 - 1186 18 1735 1737 - 1187 18 1735 1736 - 1188 18 1738 1740 - 1189 18 1738 1739 - 1190 18 1741 1743 - 1191 18 1741 1742 - 1192 18 1744 1745 - 1193 18 1744 1746 - 1194 18 1747 1749 - 1195 18 1747 1748 - 1196 18 1750 1751 - 1197 18 1750 1752 - 1198 18 1753 1755 - 1199 18 1753 1754 - 1200 18 1756 1758 - 1201 18 1756 1757 - 1202 18 1759 1760 - 1203 18 1759 1761 - 1204 18 1762 1764 - 1205 18 1762 1763 - 1206 18 1765 1767 - 1207 18 1765 1766 - 1208 18 1768 1769 - 1209 18 1768 1770 - 1210 18 1771 1773 - 1211 18 1771 1772 - 1212 18 1774 1776 - 1213 18 1774 1775 - 1214 18 1777 1779 - 1215 18 1777 1778 - 1216 18 1780 1781 - 1217 18 1780 1782 - 1218 18 1783 1784 - 1219 18 1783 1785 - 1220 18 1786 1787 - 1221 18 1786 1788 - 1222 18 1789 1790 - 1223 18 1789 1791 - 1224 18 1792 1793 - 1225 18 1792 1794 - 1226 18 1795 1796 - 1227 18 1795 1797 - 1228 18 1798 1799 - 1229 18 1798 1800 - 1230 18 1801 1803 - 1231 18 1801 1802 - 1232 18 1804 1806 - 1233 18 1804 1805 - 1234 18 1807 1809 - 1235 18 1807 1808 - 1236 18 1810 1812 - 1237 18 1810 1811 - 1238 18 1813 1815 - 1239 18 1813 1814 - 1240 18 1816 1818 - 1241 18 1816 1817 - 1242 18 1819 1821 - 1243 18 1819 1820 - 1244 18 1822 1823 - 1245 18 1822 1824 - 1246 18 1825 1827 - 1247 18 1825 1826 - 1248 18 1828 1830 - 1249 18 1828 1829 - 1250 18 1831 1832 - 1251 18 1831 1833 - 1252 18 1834 1835 - 1253 18 1834 1836 - 1254 18 1837 1838 - 1255 18 1837 1839 - 1256 18 1840 1842 - 1257 18 1840 1841 - 1258 18 1843 1845 - 1259 18 1843 1844 - 1260 18 1846 1848 - 1261 18 1846 1847 - 1262 18 1849 1851 - 1263 18 1849 1850 - 1264 18 1852 1854 - 1265 18 1852 1853 - 1266 18 1855 1856 - 1267 18 1855 1857 - 1268 18 1858 1859 - 1269 18 1858 1860 - 1270 18 1861 1862 - 1271 18 1861 1863 - 1272 18 1864 1866 - 1273 18 1864 1865 - 1274 18 1867 1869 - 1275 18 1867 1868 - 1276 18 1870 1871 - 1277 18 1870 1872 - 1278 18 1873 1874 - 1279 18 1873 1875 - 1280 18 1876 1877 - 1281 18 1876 1878 - 1282 18 1879 1881 - 1283 18 1879 1880 - 1284 18 1882 1883 - 1285 18 1882 1884 - 1286 18 1885 1886 - 1287 18 1885 1887 - 1288 18 1888 1890 - 1289 18 1888 1889 - 1290 18 1891 1892 - 1291 18 1891 1893 - 1292 18 1894 1896 - 1293 18 1894 1895 - 1294 18 1897 1898 - 1295 18 1897 1899 - 1296 18 1900 1902 - 1297 18 1900 1901 - 1298 18 1903 1905 - 1299 18 1903 1904 - 1300 18 1906 1908 - 1301 18 1906 1907 - 1302 18 1909 1911 - 1303 18 1909 1910 - 1304 18 1912 1913 - 1305 18 1912 1914 - 1306 18 1915 1916 - 1307 18 1915 1917 - 1308 18 1918 1920 - 1309 18 1918 1919 - 1310 18 1921 1923 - 1311 18 1921 1922 - 1312 18 1924 1926 - 1313 18 1924 1925 - 1314 18 1927 1929 - 1315 18 1927 1928 - 1316 18 1930 1932 - 1317 18 1930 1931 - 1318 18 1933 1935 - 1319 18 1933 1934 - 1320 18 1936 1937 - 1321 18 1936 1938 - 1322 18 1939 1940 - 1323 18 1939 1941 - 1324 18 1942 1944 - 1325 18 1942 1943 - 1326 18 1945 1947 - 1327 18 1945 1946 - 1328 18 1948 1950 - 1329 18 1948 1949 - 1330 18 1951 1953 - 1331 18 1951 1952 - 1332 18 1954 1955 - 1333 18 1954 1956 - 1334 18 1957 1959 - 1335 18 1957 1958 - 1336 18 1960 1961 - 1337 18 1960 1962 - 1338 18 1963 1965 - 1339 18 1963 1964 - 1340 18 1966 1967 - 1341 18 1966 1968 - 1342 18 1969 1970 - 1343 18 1969 1971 - 1344 18 1972 1974 - 1345 18 1972 1973 - 1346 18 1975 1977 - 1347 18 1975 1976 - 1348 18 1978 1979 - 1349 18 1978 1980 - 1350 18 1981 1982 - 1351 18 1981 1983 - 1352 18 1984 1986 - 1353 18 1984 1985 - 1354 18 1987 1988 - 1355 18 1987 1989 - 1356 18 1990 1992 - 1357 18 1990 1991 - 1358 18 1993 1995 - 1359 18 1993 1994 - 1360 18 1996 1998 - 1361 18 1996 1997 - 1362 18 1999 2000 - 1363 18 1999 2001 - 1364 18 2002 2004 - 1365 18 2002 2003 - -Angles - - 1 5 2 1 7 - 2 4 2 1 3 - 3 6 3 1 7 - 4 7 4 2 5 - 5 7 5 2 6 - 6 1 1 2 5 - 7 1 1 2 6 - 8 1 1 2 4 - 9 7 4 2 6 - 10 2 1 7 8 - 11 3 1 7 19 - 12 11 8 7 19 - 13 9 7 8 11 - 14 8 7 8 9 - 15 16 11 8 20 - 16 15 9 8 20 - 17 14 9 8 11 - 18 10 7 8 20 - 19 5 8 9 28 - 20 4 8 9 10 - 21 6 10 9 28 - 22 18 12 11 22 - 23 23 21 11 22 - 24 12 8 11 12 - 25 13 8 11 21 - 26 18 12 11 21 - 27 13 8 11 22 - 28 19 13 12 14 - 29 17 11 12 14 - 30 17 11 12 13 - 31 20 15 13 23 - 32 20 12 13 23 - 33 19 12 13 15 - 34 20 12 14 24 - 35 20 16 14 24 - 36 19 12 14 16 - 37 20 13 15 25 - 38 20 17 15 25 - 39 19 13 15 17 - 40 20 14 16 26 - 41 19 14 16 17 - 42 20 17 16 26 - 43 21 15 17 18 - 44 19 15 17 16 - 45 21 16 17 18 - 46 22 17 18 27 - 47 2 9 28 29 - 48 3 9 28 32 - 49 11 29 28 32 - 50 15 30 29 34 - 51 10 28 29 33 - 52 10 28 29 34 - 53 15 30 29 33 - 54 24 33 29 34 - 55 8 28 29 30 - 56 6 31 30 35 - 57 5 29 30 35 - 58 4 29 30 31 - 59 2 30 35 36 - 60 3 30 35 39 - 61 11 36 35 39 - 62 8 35 36 37 - 63 10 35 36 41 - 64 10 35 36 40 - 65 24 40 36 41 - 66 15 37 36 40 - 67 15 37 36 41 - 68 6 38 37 42 - 69 5 36 37 42 - 70 4 36 37 38 - 71 11 43 42 53 - 72 2 37 42 43 - 73 3 37 42 53 - 74 10 42 43 54 - 75 16 46 43 54 - 76 14 44 43 46 - 77 9 42 43 46 - 78 8 42 43 44 - 79 15 44 43 54 - 80 5 43 44 62 - 81 6 45 44 62 - 82 4 43 44 45 - 83 13 43 46 55 - 84 13 43 46 56 - 85 12 43 46 47 - 86 23 55 46 56 - 87 18 47 46 56 - 88 18 47 46 55 - 89 17 46 47 49 - 90 17 46 47 48 - 91 19 48 47 49 - 92 20 50 48 57 - 93 19 47 48 50 - 94 20 47 48 57 - 95 20 51 49 58 - 96 19 47 49 51 - 97 20 47 49 58 - 98 20 48 50 59 - 99 19 48 50 52 - 100 20 52 50 59 - 101 20 52 51 60 - 102 20 49 51 60 - 103 19 49 51 52 - 104 20 50 52 61 - 105 19 50 52 51 - 106 20 51 52 61 - 107 2 44 62 63 - 108 3 44 62 70 - 109 11 63 62 70 - 110 16 66 63 71 - 111 15 64 63 71 - 112 14 64 63 66 - 113 10 62 63 71 - 114 9 62 63 66 - 115 8 62 63 64 - 116 4 63 64 65 - 117 6 65 64 79 - 118 5 63 64 79 - 119 23 72 66 73 - 120 27 67 66 73 - 121 27 67 66 72 - 122 25 63 66 67 - 123 13 63 66 73 - 124 13 63 66 72 - 125 29 68 67 75 - 126 23 74 67 75 - 127 29 68 67 74 - 128 26 66 67 68 - 129 27 66 67 74 - 130 27 66 67 75 - 131 28 67 68 69 - 132 29 68 69 76 - 133 29 68 69 77 - 134 29 68 69 78 - 135 7 76 69 78 - 136 7 76 69 77 - 137 7 77 69 78 - 138 3 64 79 81 - 139 2 64 79 80 - 140 11 80 79 81 - 141 7 83 80 84 - 142 30 79 80 84 - 143 7 82 80 83 - 144 30 79 80 83 - 145 30 79 80 82 - 146 7 82 80 84 - 147 31 86 85 87 - 148 31 89 88 90 - 149 31 92 91 93 - 150 31 95 94 96 - 151 31 98 97 99 - 152 31 101 100 102 - 153 31 104 103 105 - 154 31 107 106 108 - 155 31 110 109 111 - 156 31 113 112 114 - 157 31 116 115 117 - 158 31 119 118 120 - 159 31 122 121 123 - 160 31 125 124 126 - 161 31 128 127 129 - 162 31 131 130 132 - 163 31 134 133 135 - 164 31 137 136 138 - 165 31 140 139 141 - 166 31 143 142 144 - 167 31 146 145 147 - 168 31 149 148 150 - 169 31 152 151 153 - 170 31 155 154 156 - 171 31 158 157 159 - 172 31 161 160 162 - 173 31 164 163 165 - 174 31 167 166 168 - 175 31 170 169 171 - 176 31 173 172 174 - 177 31 176 175 177 - 178 31 179 178 180 - 179 31 182 181 183 - 180 31 185 184 186 - 181 31 188 187 189 - 182 31 191 190 192 - 183 31 194 193 195 - 184 31 197 196 198 - 185 31 200 199 201 - 186 31 203 202 204 - 187 31 206 205 207 - 188 31 209 208 210 - 189 31 212 211 213 - 190 31 215 214 216 - 191 31 218 217 219 - 192 31 221 220 222 - 193 31 224 223 225 - 194 31 227 226 228 - 195 31 230 229 231 - 196 31 233 232 234 - 197 31 236 235 237 - 198 31 239 238 240 - 199 31 242 241 243 - 200 31 245 244 246 - 201 31 248 247 249 - 202 31 251 250 252 - 203 31 254 253 255 - 204 31 257 256 258 - 205 31 260 259 261 - 206 31 263 262 264 - 207 31 266 265 267 - 208 31 269 268 270 - 209 31 272 271 273 - 210 31 275 274 276 - 211 31 278 277 279 - 212 31 281 280 282 - 213 31 284 283 285 - 214 31 287 286 288 - 215 31 290 289 291 - 216 31 293 292 294 - 217 31 296 295 297 - 218 31 299 298 300 - 219 31 302 301 303 - 220 31 305 304 306 - 221 31 308 307 309 - 222 31 311 310 312 - 223 31 314 313 315 - 224 31 317 316 318 - 225 31 320 319 321 - 226 31 323 322 324 - 227 31 326 325 327 - 228 31 329 328 330 - 229 31 332 331 333 - 230 31 335 334 336 - 231 31 338 337 339 - 232 31 341 340 342 - 233 31 344 343 345 - 234 31 347 346 348 - 235 31 350 349 351 - 236 31 353 352 354 - 237 31 356 355 357 - 238 31 359 358 360 - 239 31 362 361 363 - 240 31 365 364 366 - 241 31 368 367 369 - 242 31 371 370 372 - 243 31 374 373 375 - 244 31 377 376 378 - 245 31 380 379 381 - 246 31 383 382 384 - 247 31 386 385 387 - 248 31 389 388 390 - 249 31 392 391 393 - 250 31 395 394 396 - 251 31 398 397 399 - 252 31 401 400 402 - 253 31 404 403 405 - 254 31 407 406 408 - 255 31 410 409 411 - 256 31 413 412 414 - 257 31 416 415 417 - 258 31 419 418 420 - 259 31 422 421 423 - 260 31 425 424 426 - 261 31 428 427 429 - 262 31 431 430 432 - 263 31 434 433 435 - 264 31 437 436 438 - 265 31 440 439 441 - 266 31 443 442 444 - 267 31 446 445 447 - 268 31 449 448 450 - 269 31 452 451 453 - 270 31 455 454 456 - 271 31 458 457 459 - 272 31 461 460 462 - 273 31 464 463 465 - 274 31 467 466 468 - 275 31 470 469 471 - 276 31 473 472 474 - 277 31 476 475 477 - 278 31 479 478 480 - 279 31 482 481 483 - 280 31 485 484 486 - 281 31 488 487 489 - 282 31 491 490 492 - 283 31 494 493 495 - 284 31 497 496 498 - 285 31 500 499 501 - 286 31 503 502 504 - 287 31 506 505 507 - 288 31 509 508 510 - 289 31 512 511 513 - 290 31 515 514 516 - 291 31 518 517 519 - 292 31 521 520 522 - 293 31 524 523 525 - 294 31 527 526 528 - 295 31 530 529 531 - 296 31 533 532 534 - 297 31 536 535 537 - 298 31 539 538 540 - 299 31 542 541 543 - 300 31 545 544 546 - 301 31 548 547 549 - 302 31 551 550 552 - 303 31 554 553 555 - 304 31 557 556 558 - 305 31 560 559 561 - 306 31 563 562 564 - 307 31 566 565 567 - 308 31 569 568 570 - 309 31 572 571 573 - 310 31 575 574 576 - 311 31 578 577 579 - 312 31 581 580 582 - 313 31 584 583 585 - 314 31 587 586 588 - 315 31 590 589 591 - 316 31 593 592 594 - 317 31 596 595 597 - 318 31 599 598 600 - 319 31 602 601 603 - 320 31 605 604 606 - 321 31 608 607 609 - 322 31 611 610 612 - 323 31 614 613 615 - 324 31 617 616 618 - 325 31 620 619 621 - 326 31 623 622 624 - 327 31 626 625 627 - 328 31 629 628 630 - 329 31 632 631 633 - 330 31 635 634 636 - 331 31 638 637 639 - 332 31 641 640 642 - 333 31 644 643 645 - 334 31 647 646 648 - 335 31 650 649 651 - 336 31 653 652 654 - 337 31 656 655 657 - 338 31 659 658 660 - 339 31 662 661 663 - 340 31 665 664 666 - 341 31 668 667 669 - 342 31 671 670 672 - 343 31 674 673 675 - 344 31 677 676 678 - 345 31 680 679 681 - 346 31 683 682 684 - 347 31 686 685 687 - 348 31 689 688 690 - 349 31 692 691 693 - 350 31 695 694 696 - 351 31 698 697 699 - 352 31 701 700 702 - 353 31 704 703 705 - 354 31 707 706 708 - 355 31 710 709 711 - 356 31 713 712 714 - 357 31 716 715 717 - 358 31 719 718 720 - 359 31 722 721 723 - 360 31 725 724 726 - 361 31 728 727 729 - 362 31 731 730 732 - 363 31 734 733 735 - 364 31 737 736 738 - 365 31 740 739 741 - 366 31 743 742 744 - 367 31 746 745 747 - 368 31 749 748 750 - 369 31 752 751 753 - 370 31 755 754 756 - 371 31 758 757 759 - 372 31 761 760 762 - 373 31 764 763 765 - 374 31 767 766 768 - 375 31 770 769 771 - 376 31 773 772 774 - 377 31 776 775 777 - 378 31 779 778 780 - 379 31 782 781 783 - 380 31 785 784 786 - 381 31 788 787 789 - 382 31 791 790 792 - 383 31 794 793 795 - 384 31 797 796 798 - 385 31 800 799 801 - 386 31 803 802 804 - 387 31 806 805 807 - 388 31 809 808 810 - 389 31 812 811 813 - 390 31 815 814 816 - 391 31 818 817 819 - 392 31 821 820 822 - 393 31 824 823 825 - 394 31 827 826 828 - 395 31 830 829 831 - 396 31 833 832 834 - 397 31 836 835 837 - 398 31 839 838 840 - 399 31 842 841 843 - 400 31 845 844 846 - 401 31 848 847 849 - 402 31 851 850 852 - 403 31 854 853 855 - 404 31 857 856 858 - 405 31 860 859 861 - 406 31 863 862 864 - 407 31 866 865 867 - 408 31 869 868 870 - 409 31 872 871 873 - 410 31 875 874 876 - 411 31 878 877 879 - 412 31 881 880 882 - 413 31 884 883 885 - 414 31 887 886 888 - 415 31 890 889 891 - 416 31 893 892 894 - 417 31 896 895 897 - 418 31 899 898 900 - 419 31 902 901 903 - 420 31 905 904 906 - 421 31 908 907 909 - 422 31 911 910 912 - 423 31 914 913 915 - 424 31 917 916 918 - 425 31 920 919 921 - 426 31 923 922 924 - 427 31 926 925 927 - 428 31 929 928 930 - 429 31 932 931 933 - 430 31 935 934 936 - 431 31 938 937 939 - 432 31 941 940 942 - 433 31 944 943 945 - 434 31 947 946 948 - 435 31 950 949 951 - 436 31 953 952 954 - 437 31 956 955 957 - 438 31 959 958 960 - 439 31 962 961 963 - 440 31 965 964 966 - 441 31 968 967 969 - 442 31 971 970 972 - 443 31 974 973 975 - 444 31 977 976 978 - 445 31 980 979 981 - 446 31 983 982 984 - 447 31 986 985 987 - 448 31 989 988 990 - 449 31 992 991 993 - 450 31 995 994 996 - 451 31 998 997 999 - 452 31 1001 1000 1002 - 453 31 1004 1003 1005 - 454 31 1007 1006 1008 - 455 31 1010 1009 1011 - 456 31 1013 1012 1014 - 457 31 1016 1015 1017 - 458 31 1019 1018 1020 - 459 31 1022 1021 1023 - 460 31 1025 1024 1026 - 461 31 1028 1027 1029 - 462 31 1031 1030 1032 - 463 31 1034 1033 1035 - 464 31 1037 1036 1038 - 465 31 1040 1039 1041 - 466 31 1043 1042 1044 - 467 31 1046 1045 1047 - 468 31 1049 1048 1050 - 469 31 1052 1051 1053 - 470 31 1055 1054 1056 - 471 31 1058 1057 1059 - 472 31 1061 1060 1062 - 473 31 1064 1063 1065 - 474 31 1067 1066 1068 - 475 31 1070 1069 1071 - 476 31 1073 1072 1074 - 477 31 1076 1075 1077 - 478 31 1079 1078 1080 - 479 31 1082 1081 1083 - 480 31 1085 1084 1086 - 481 31 1088 1087 1089 - 482 31 1091 1090 1092 - 483 31 1094 1093 1095 - 484 31 1097 1096 1098 - 485 31 1100 1099 1101 - 486 31 1103 1102 1104 - 487 31 1106 1105 1107 - 488 31 1109 1108 1110 - 489 31 1112 1111 1113 - 490 31 1115 1114 1116 - 491 31 1118 1117 1119 - 492 31 1121 1120 1122 - 493 31 1124 1123 1125 - 494 31 1127 1126 1128 - 495 31 1130 1129 1131 - 496 31 1133 1132 1134 - 497 31 1136 1135 1137 - 498 31 1139 1138 1140 - 499 31 1142 1141 1143 - 500 31 1145 1144 1146 - 501 31 1148 1147 1149 - 502 31 1151 1150 1152 - 503 31 1154 1153 1155 - 504 31 1157 1156 1158 - 505 31 1160 1159 1161 - 506 31 1163 1162 1164 - 507 31 1166 1165 1167 - 508 31 1169 1168 1170 - 509 31 1172 1171 1173 - 510 31 1175 1174 1176 - 511 31 1178 1177 1179 - 512 31 1181 1180 1182 - 513 31 1184 1183 1185 - 514 31 1187 1186 1188 - 515 31 1190 1189 1191 - 516 31 1193 1192 1194 - 517 31 1196 1195 1197 - 518 31 1199 1198 1200 - 519 31 1202 1201 1203 - 520 31 1205 1204 1206 - 521 31 1208 1207 1209 - 522 31 1211 1210 1212 - 523 31 1214 1213 1215 - 524 31 1217 1216 1218 - 525 31 1220 1219 1221 - 526 31 1223 1222 1224 - 527 31 1226 1225 1227 - 528 31 1229 1228 1230 - 529 31 1232 1231 1233 - 530 31 1235 1234 1236 - 531 31 1238 1237 1239 - 532 31 1241 1240 1242 - 533 31 1244 1243 1245 - 534 31 1247 1246 1248 - 535 31 1250 1249 1251 - 536 31 1253 1252 1254 - 537 31 1256 1255 1257 - 538 31 1259 1258 1260 - 539 31 1262 1261 1263 - 540 31 1265 1264 1266 - 541 31 1268 1267 1269 - 542 31 1271 1270 1272 - 543 31 1274 1273 1275 - 544 31 1277 1276 1278 - 545 31 1280 1279 1281 - 546 31 1283 1282 1284 - 547 31 1286 1285 1287 - 548 31 1289 1288 1290 - 549 31 1292 1291 1293 - 550 31 1295 1294 1296 - 551 31 1298 1297 1299 - 552 31 1301 1300 1302 - 553 31 1304 1303 1305 - 554 31 1307 1306 1308 - 555 31 1310 1309 1311 - 556 31 1313 1312 1314 - 557 31 1316 1315 1317 - 558 31 1319 1318 1320 - 559 31 1322 1321 1323 - 560 31 1325 1324 1326 - 561 31 1328 1327 1329 - 562 31 1331 1330 1332 - 563 31 1334 1333 1335 - 564 31 1337 1336 1338 - 565 31 1340 1339 1341 - 566 31 1343 1342 1344 - 567 31 1346 1345 1347 - 568 31 1349 1348 1350 - 569 31 1352 1351 1353 - 570 31 1355 1354 1356 - 571 31 1358 1357 1359 - 572 31 1361 1360 1362 - 573 31 1364 1363 1365 - 574 31 1367 1366 1368 - 575 31 1370 1369 1371 - 576 31 1373 1372 1374 - 577 31 1376 1375 1377 - 578 31 1379 1378 1380 - 579 31 1382 1381 1383 - 580 31 1385 1384 1386 - 581 31 1388 1387 1389 - 582 31 1391 1390 1392 - 583 31 1394 1393 1395 - 584 31 1397 1396 1398 - 585 31 1400 1399 1401 - 586 31 1403 1402 1404 - 587 31 1406 1405 1407 - 588 31 1409 1408 1410 - 589 31 1412 1411 1413 - 590 31 1415 1414 1416 - 591 31 1418 1417 1419 - 592 31 1421 1420 1422 - 593 31 1424 1423 1425 - 594 31 1427 1426 1428 - 595 31 1430 1429 1431 - 596 31 1433 1432 1434 - 597 31 1436 1435 1437 - 598 31 1439 1438 1440 - 599 31 1442 1441 1443 - 600 31 1445 1444 1446 - 601 31 1448 1447 1449 - 602 31 1451 1450 1452 - 603 31 1454 1453 1455 - 604 31 1457 1456 1458 - 605 31 1460 1459 1461 - 606 31 1463 1462 1464 - 607 31 1466 1465 1467 - 608 31 1469 1468 1470 - 609 31 1472 1471 1473 - 610 31 1475 1474 1476 - 611 31 1478 1477 1479 - 612 31 1481 1480 1482 - 613 31 1484 1483 1485 - 614 31 1487 1486 1488 - 615 31 1490 1489 1491 - 616 31 1493 1492 1494 - 617 31 1496 1495 1497 - 618 31 1499 1498 1500 - 619 31 1502 1501 1503 - 620 31 1505 1504 1506 - 621 31 1508 1507 1509 - 622 31 1511 1510 1512 - 623 31 1514 1513 1515 - 624 31 1517 1516 1518 - 625 31 1520 1519 1521 - 626 31 1523 1522 1524 - 627 31 1526 1525 1527 - 628 31 1529 1528 1530 - 629 31 1532 1531 1533 - 630 31 1535 1534 1536 - 631 31 1538 1537 1539 - 632 31 1541 1540 1542 - 633 31 1544 1543 1545 - 634 31 1547 1546 1548 - 635 31 1550 1549 1551 - 636 31 1553 1552 1554 - 637 31 1556 1555 1557 - 638 31 1559 1558 1560 - 639 31 1562 1561 1563 - 640 31 1565 1564 1566 - 641 31 1568 1567 1569 - 642 31 1571 1570 1572 - 643 31 1574 1573 1575 - 644 31 1577 1576 1578 - 645 31 1580 1579 1581 - 646 31 1583 1582 1584 - 647 31 1586 1585 1587 - 648 31 1589 1588 1590 - 649 31 1592 1591 1593 - 650 31 1595 1594 1596 - 651 31 1598 1597 1599 - 652 31 1601 1600 1602 - 653 31 1604 1603 1605 - 654 31 1607 1606 1608 - 655 31 1610 1609 1611 - 656 31 1613 1612 1614 - 657 31 1616 1615 1617 - 658 31 1619 1618 1620 - 659 31 1622 1621 1623 - 660 31 1625 1624 1626 - 661 31 1628 1627 1629 - 662 31 1631 1630 1632 - 663 31 1634 1633 1635 - 664 31 1637 1636 1638 - 665 31 1640 1639 1641 - 666 31 1643 1642 1644 - 667 31 1646 1645 1647 - 668 31 1649 1648 1650 - 669 31 1652 1651 1653 - 670 31 1655 1654 1656 - 671 31 1658 1657 1659 - 672 31 1661 1660 1662 - 673 31 1664 1663 1665 - 674 31 1667 1666 1668 - 675 31 1670 1669 1671 - 676 31 1673 1672 1674 - 677 31 1676 1675 1677 - 678 31 1679 1678 1680 - 679 31 1682 1681 1683 - 680 31 1685 1684 1686 - 681 31 1688 1687 1689 - 682 31 1691 1690 1692 - 683 31 1694 1693 1695 - 684 31 1697 1696 1698 - 685 31 1700 1699 1701 - 686 31 1703 1702 1704 - 687 31 1706 1705 1707 - 688 31 1709 1708 1710 - 689 31 1712 1711 1713 - 690 31 1715 1714 1716 - 691 31 1718 1717 1719 - 692 31 1721 1720 1722 - 693 31 1724 1723 1725 - 694 31 1727 1726 1728 - 695 31 1730 1729 1731 - 696 31 1733 1732 1734 - 697 31 1736 1735 1737 - 698 31 1739 1738 1740 - 699 31 1742 1741 1743 - 700 31 1745 1744 1746 - 701 31 1748 1747 1749 - 702 31 1751 1750 1752 - 703 31 1754 1753 1755 - 704 31 1757 1756 1758 - 705 31 1760 1759 1761 - 706 31 1763 1762 1764 - 707 31 1766 1765 1767 - 708 31 1769 1768 1770 - 709 31 1772 1771 1773 - 710 31 1775 1774 1776 - 711 31 1778 1777 1779 - 712 31 1781 1780 1782 - 713 31 1784 1783 1785 - 714 31 1787 1786 1788 - 715 31 1790 1789 1791 - 716 31 1793 1792 1794 - 717 31 1796 1795 1797 - 718 31 1799 1798 1800 - 719 31 1802 1801 1803 - 720 31 1805 1804 1806 - 721 31 1808 1807 1809 - 722 31 1811 1810 1812 - 723 31 1814 1813 1815 - 724 31 1817 1816 1818 - 725 31 1820 1819 1821 - 726 31 1823 1822 1824 - 727 31 1826 1825 1827 - 728 31 1829 1828 1830 - 729 31 1832 1831 1833 - 730 31 1835 1834 1836 - 731 31 1838 1837 1839 - 732 31 1841 1840 1842 - 733 31 1844 1843 1845 - 734 31 1847 1846 1848 - 735 31 1850 1849 1851 - 736 31 1853 1852 1854 - 737 31 1856 1855 1857 - 738 31 1859 1858 1860 - 739 31 1862 1861 1863 - 740 31 1865 1864 1866 - 741 31 1868 1867 1869 - 742 31 1871 1870 1872 - 743 31 1874 1873 1875 - 744 31 1877 1876 1878 - 745 31 1880 1879 1881 - 746 31 1883 1882 1884 - 747 31 1886 1885 1887 - 748 31 1889 1888 1890 - 749 31 1892 1891 1893 - 750 31 1895 1894 1896 - 751 31 1898 1897 1899 - 752 31 1901 1900 1902 - 753 31 1904 1903 1905 - 754 31 1907 1906 1908 - 755 31 1910 1909 1911 - 756 31 1913 1912 1914 - 757 31 1916 1915 1917 - 758 31 1919 1918 1920 - 759 31 1922 1921 1923 - 760 31 1925 1924 1926 - 761 31 1928 1927 1929 - 762 31 1931 1930 1932 - 763 31 1934 1933 1935 - 764 31 1937 1936 1938 - 765 31 1940 1939 1941 - 766 31 1943 1942 1944 - 767 31 1946 1945 1947 - 768 31 1949 1948 1950 - 769 31 1952 1951 1953 - 770 31 1955 1954 1956 - 771 31 1958 1957 1959 - 772 31 1961 1960 1962 - 773 31 1964 1963 1965 - 774 31 1967 1966 1968 - 775 31 1970 1969 1971 - 776 31 1973 1972 1974 - 777 31 1976 1975 1977 - 778 31 1979 1978 1980 - 779 31 1982 1981 1983 - 780 31 1985 1984 1986 - 781 31 1988 1987 1989 - 782 31 1991 1990 1992 - 783 31 1994 1993 1995 - 784 31 1997 1996 1998 - 785 31 2000 1999 2001 - 786 31 2003 2002 2004 - -Dihedrals - - 1 6 3 1 7 8 - 2 6 2 1 7 19 - 3 4 2 1 7 8 - 4 5 2 1 7 8 - 5 6 3 1 7 19 - 6 3 3 1 2 4 - 7 3 3 1 2 6 - 8 3 3 1 2 5 - 9 3 5 2 1 7 - 10 3 4 2 1 7 - 11 3 6 2 1 7 - 12 3 19 7 8 20 - 13 1 1 7 8 9 - 14 3 1 7 8 20 - 15 2 1 7 8 11 - 16 8 9 8 11 22 - 17 3 7 8 9 10 - 18 7 7 8 9 28 - 19 8 7 8 11 21 - 20 8 7 8 11 12 - 21 3 9 8 7 19 - 22 3 11 8 9 28 - 23 8 7 8 11 22 - 24 3 11 8 7 19 - 25 10 9 8 11 12 - 26 3 20 8 9 28 - 27 8 9 8 11 21 - 28 8 20 8 11 22 - 29 8 20 8 11 21 - 30 4 8 9 28 29 - 31 5 8 9 28 29 - 32 6 10 9 28 29 - 33 11 10 9 8 11 - 34 6 10 9 28 32 - 35 3 10 9 8 20 - 36 6 8 9 28 32 - 37 9 8 11 12 13 - 38 8 12 11 8 20 - 39 9 8 11 12 14 - 40 14 14 12 13 15 - 41 13 13 12 14 24 - 42 3 13 12 11 22 - 43 14 13 12 14 16 - 44 3 14 12 11 22 - 45 3 13 12 11 21 - 46 13 11 12 14 24 - 47 12 11 12 14 16 - 48 3 14 12 11 21 - 49 13 11 12 13 23 - 50 13 14 12 13 23 - 51 12 11 12 13 15 - 52 16 23 13 15 25 - 53 13 12 13 15 25 - 54 14 12 13 15 17 - 55 14 12 14 16 17 - 56 13 12 14 16 26 - 57 16 24 14 16 26 - 58 12 13 15 17 18 - 59 13 17 15 13 23 - 60 14 13 15 17 16 - 61 12 14 16 17 18 - 62 13 17 16 14 24 - 63 14 14 16 17 15 - 64 15 16 17 18 27 - 65 13 15 17 16 26 - 66 13 18 17 15 25 - 67 15 15 17 18 27 - 68 13 16 17 15 25 - 69 13 18 17 16 26 - 70 1 9 28 29 30 - 71 3 32 28 29 33 - 72 3 9 28 29 33 - 73 3 9 28 29 34 - 74 3 32 28 29 34 - 75 3 33 29 30 35 - 76 3 30 29 28 32 - 77 3 34 29 30 35 - 78 7 28 29 30 35 - 79 3 28 29 30 31 - 80 6 29 30 35 39 - 81 4 29 30 35 36 - 82 5 29 30 35 36 - 83 3 31 30 29 34 - 84 3 31 30 29 33 - 85 6 31 30 35 39 - 86 6 31 30 35 36 - 87 1 30 35 36 37 - 88 3 39 35 36 41 - 89 3 30 35 36 40 - 90 3 30 35 36 41 - 91 3 39 35 36 40 - 92 3 40 36 37 42 - 93 3 41 36 37 42 - 94 7 35 36 37 42 - 95 3 35 36 37 38 - 96 3 37 36 35 39 - 97 6 38 37 42 53 - 98 3 38 37 36 40 - 99 6 38 37 42 43 - 100 4 36 37 42 43 - 101 6 36 37 42 53 - 102 5 36 37 42 43 - 103 3 38 37 36 41 - 104 3 37 42 43 54 - 105 1 37 42 43 44 - 106 3 53 42 43 54 - 107 2 37 42 43 46 - 108 10 44 43 46 47 - 109 3 44 43 42 53 - 110 8 42 43 46 56 - 111 8 42 43 46 55 - 112 8 42 43 46 47 - 113 3 46 43 42 53 - 114 8 44 43 46 55 - 115 8 54 43 46 56 - 116 7 42 43 44 62 - 117 3 42 43 44 45 - 118 3 46 43 44 62 - 119 3 54 43 44 62 - 120 8 54 43 46 55 - 121 8 44 43 46 56 - 122 5 43 44 62 63 - 123 6 45 44 62 70 - 124 6 43 44 62 70 - 125 4 43 44 62 63 - 126 11 45 44 43 46 - 127 3 45 44 43 54 - 128 6 45 44 62 63 - 129 9 43 46 47 48 - 130 8 47 46 43 54 - 131 9 43 46 47 49 - 132 3 49 47 46 55 - 133 13 46 47 48 57 - 134 14 49 47 48 50 - 135 3 49 47 46 56 - 136 12 46 47 48 50 - 137 12 46 47 49 51 - 138 14 48 47 49 51 - 139 13 46 47 49 58 - 140 3 48 47 46 55 - 141 3 48 47 46 56 - 142 13 48 47 49 58 - 143 13 49 47 48 57 - 144 14 47 48 50 52 - 145 16 57 48 50 59 - 146 13 47 48 50 59 - 147 16 58 49 51 60 - 148 13 47 49 51 60 - 149 14 47 49 51 52 - 150 13 48 50 52 61 - 151 14 48 50 52 51 - 152 16 59 50 52 61 - 153 13 52 50 48 57 - 154 14 49 51 52 50 - 155 13 49 51 52 61 - 156 13 52 51 49 58 - 157 16 60 51 52 61 - 158 13 51 52 50 59 - 159 13 50 52 51 60 - 160 3 70 62 63 71 - 161 2 44 62 63 66 - 162 1 44 62 63 64 - 163 3 44 62 63 71 - 164 8 62 63 66 72 - 165 8 62 63 66 67 - 166 3 71 63 64 79 - 167 3 62 63 64 65 - 168 3 64 63 62 70 - 169 8 62 63 66 73 - 170 7 62 63 64 79 - 171 8 64 63 66 67 - 172 3 66 63 64 79 - 173 8 64 63 66 72 - 174 3 66 63 62 70 - 175 8 71 63 66 73 - 176 8 64 63 66 73 - 177 8 71 63 66 72 - 178 6 63 64 79 81 - 179 6 65 64 79 80 - 180 3 65 64 63 71 - 181 4 63 64 79 80 - 182 6 65 64 79 81 - 183 5 63 64 79 80 - 184 11 65 64 63 66 - 185 8 67 66 63 71 - 186 17 63 66 67 74 - 187 17 72 66 67 75 - 188 17 63 66 67 75 - 189 17 63 66 67 68 - 190 17 73 66 67 74 - 191 17 73 66 67 75 - 192 17 72 66 67 74 - 193 19 66 67 68 69 - 194 21 68 67 66 72 - 195 18 66 67 68 69 - 196 21 68 67 66 73 - 197 20 69 68 67 74 - 198 20 69 68 67 75 - 199 20 67 68 69 77 - 200 20 67 68 69 76 - 201 20 67 68 69 78 - 202 3 81 79 80 83 - 203 3 81 79 80 84 - 204 3 64 79 80 84 - 205 3 81 79 80 82 - 206 3 64 79 80 83 - 207 3 64 79 80 82 - -Impropers - - 1 2 7 1 8 19 - 2 1 1 2 7 3 - 3 1 9 8 28 10 - 4 2 28 9 29 32 - 5 1 30 29 35 31 - 6 2 35 30 36 39 - 7 1 37 36 42 38 - 8 2 42 37 43 53 - 9 1 44 43 62 45 - 10 2 62 44 63 70 - 11 1 64 63 79 65 - 12 2 79 64 80 81 diff --git a/tools/replica/example/data.peptide b/tools/replica/example/data.peptide new file mode 120000 index 0000000000..f523fc92c1 --- /dev/null +++ b/tools/replica/example/data.peptide @@ -0,0 +1 @@ +../../../examples/peptide/data.peptide \ No newline at end of file From bb0225c02ed7470b3e2a01a824a0a83c1038998e Mon Sep 17 00:00:00 2001 From: Axel Kohlmeyer Date: Thu, 5 Sep 2019 14:29:10 -0400 Subject: [PATCH 095/192] clear svector for every invocation. document changes --- doc/src/compute_pair_local.txt | 5 ++++- src/pair_hybrid.cpp | 3 ++- 2 files changed, 6 insertions(+), 2 deletions(-) diff --git a/doc/src/compute_pair_local.txt b/doc/src/compute_pair_local.txt index 1460ba18a5..baf394505f 100644 --- a/doc/src/compute_pair_local.txt +++ b/doc/src/compute_pair_local.txt @@ -62,7 +62,10 @@ pair styles do not define any additional quantities, so N = 0. An example of ones that do are the "granular pair styles"_pair_gran.html which calculate the tangential force between two particles and return its components and magnitude acting on atom I for N = 1,2,3,4. See -individual pair styles for details. +individual pair styles for details. When using hybrid pair styles, +these quantities are the combined lists of the individual quantities +for the pair styles active for a given pair of atom types padded with +zeros. The value {dist} will be in distance "units"_units.html. The value {eng} will be in energy "units"_units.html. The values {force}, {fx}, diff --git a/src/pair_hybrid.cpp b/src/pair_hybrid.cpp index 31f017df12..8374e0cfe6 100644 --- a/src/pair_hybrid.cpp +++ b/src/pair_hybrid.cpp @@ -363,7 +363,7 @@ void PairHybrid::flags() if (styles[m]->compute_flag) compute_flag = 1; } - // single_extra = sum of all sub-style single_extra + // single_extra = list all sub-style single_extra // allocate svector single_extra = 0; @@ -759,6 +759,7 @@ double PairHybrid::single(int i, int j, int itype, int jtype, fforce = 0.0; double esum = 0.0; int n = 0; + if (single_extra) memset(svector,0,single_extra*sizeof(double)); for (int m = 0; m < nmap[itype][jtype]; m++) { if (rsq < styles[map[itype][jtype][m]]->cutsq[itype][jtype]) { From 4fdece59a593d9257d298eeda8db2869d3041e49 Mon Sep 17 00:00:00 2001 From: "tanmoy.7989" Date: Thu, 5 Sep 2019 21:19:57 -0700 Subject: [PATCH 096/192] (a)fixed bz2 import, (b)linked to data.peptide in examples/peptide, (c)added a runlog --- tools/replica/example/data.peptide | 6531 -------------------------- tools/replica/example/in.peptide | 2 +- tools/replica/example/run.sh | 7 +- tools/replica/example/runlog.05Sep19 | 249 + tools/replica/reorder_remd_traj.py | 2 +- 5 files changed, 256 insertions(+), 6535 deletions(-) delete mode 100644 tools/replica/example/data.peptide create mode 100644 tools/replica/example/runlog.05Sep19 diff --git a/tools/replica/example/data.peptide b/tools/replica/example/data.peptide deleted file mode 100644 index f9dfb6e485..0000000000 --- a/tools/replica/example/data.peptide +++ /dev/null @@ -1,6531 +0,0 @@ -LAMMPS Description - - 2004 atoms - 1365 bonds - 786 angles - 207 dihedrals - 12 impropers - - 14 atom types - 18 bond types - 31 angle types - 21 dihedral types - 2 improper types - - 36.840194 64.211560 xlo xhi - 41.013691 68.385058 ylo yhi - 29.768095 57.139462 zlo zhi - -Masses - - 1 12.0110 - 2 12.0110 - 3 15.9990 - 4 1.0080 - 5 14.0070 - 6 12.0110 - 7 12.0110 - 8 12.0110 - 9 15.9990 - 10 1.0080 - 11 1.0080 - 12 32.0660 - 13 16.0000 - 14 1.0100 - -Pair Coeffs - - 1 0.110000 3.563595 0.110000 3.563595 - 2 0.080000 3.670503 0.010000 3.385415 - 3 0.120000 3.029056 0.120000 2.494516 - 4 0.022000 2.351973 0.022000 2.351973 - 5 0.200000 3.296325 0.200000 2.761786 - 6 0.020000 4.053589 0.010000 3.385415 - 7 0.055000 3.875410 0.010000 3.385415 - 8 0.070000 3.550053 0.070000 3.550053 - 9 0.152100 3.153782 0.152100 3.153782 - 10 0.046000 0.400014 0.046000 0.400014 - 11 0.030000 2.420037 0.030000 2.420037 - 12 0.450000 3.563595 0.450000 3.563595 - 13 0.152100 3.150570 0.152100 3.150570 - 14 0.046000 0.400014 0.046000 0.400014 - -Bond Coeffs - - 1 249.999999 1.490000 - 2 620.000001 1.230000 - 3 370.000000 1.345000 - 4 322.000001 1.111000 - 5 319.999999 1.430000 - 6 440.000000 0.997000 - 7 222.500001 1.538000 - 8 330.000001 1.080000 - 9 230.000000 1.490000 - 10 309.000001 1.111000 - 11 305.000000 1.375000 - 12 340.000001 1.080000 - 13 334.300000 1.411000 - 14 545.000001 0.960000 - 15 222.500001 1.530000 - 16 198.000000 1.818000 - 17 239.999999 1.816000 - 18 450.000000 0.957200 - -Angle Coeffs - - 1 33.000000 109.500000 30.000000 2.163000 - 2 50.000000 120.000000 0.000000 0.000000 - 3 34.000000 123.000000 0.000000 0.000000 - 4 80.000000 121.000000 0.000000 0.000000 - 5 80.000000 116.500000 0.000000 0.000000 - 6 80.000000 122.500000 0.000000 0.000000 - 7 35.500000 108.400000 5.400000 1.802000 - 8 50.000000 107.000000 0.000000 0.000000 - 9 70.000000 113.500000 0.000000 0.000000 - 10 48.000000 108.000000 0.000000 0.000000 - 11 35.000000 117.000000 0.000000 0.000000 - 12 51.800000 107.500000 0.000000 0.000000 - 13 33.430000 110.100000 22.530000 2.179000 - 14 52.000000 108.000000 0.000000 0.000000 - 15 50.000000 109.500000 0.000000 0.000000 - 16 35.000000 111.000000 0.000000 0.000000 - 17 45.800000 122.300000 0.000000 0.000000 - 18 49.300000 107.500000 0.000000 0.000000 - 19 40.000000 120.000000 35.000000 2.416200 - 20 30.000000 120.000000 22.000000 2.152500 - 21 45.200000 120.000000 0.000000 0.000000 - 22 65.000000 108.000000 0.000000 0.000000 - 23 35.500000 109.000000 5.400000 1.802000 - 24 36.000000 115.000000 0.000000 0.000000 - 25 58.350000 113.500000 11.160000 2.561000 - 26 58.000000 114.500000 0.000000 0.000000 - 27 26.500000 110.100000 22.530000 2.179000 - 28 34.000000 95.000000 0.000000 0.000000 - 29 46.100000 111.300000 0.000000 0.000000 - 30 51.500000 109.500000 0.000000 0.000000 - 31 55.000000 104.520000 0.000000 0.000000 - -Dihedral Coeffs - - 1 0.200000 1 180 1.000000 - 2 1.800000 1 0 1.000000 - 3 0.000000 1 0 1.000000 - 4 1.600000 1 0 0.500000 - 5 2.500000 2 180 0.500000 - 6 2.500000 2 180 1.000000 - 7 0.600000 1 0 1.000000 - 8 0.200000 3 0 1.000000 - 9 0.230000 2 180 1.000000 - 10 0.040000 3 0 1.000000 - 11 1.400000 1 0 1.000000 - 12 3.100000 2 180 1.000000 - 13 4.200000 2 180 1.000000 - 14 3.100000 2 180 0.500000 - 15 0.990000 2 180 1.000000 - 16 2.400000 2 180 1.000000 - 17 0.195000 3 0 1.000000 - 18 0.240000 1 180 0.500000 - 19 0.370000 3 0 0.500000 - 20 0.280000 3 0 1.000000 - 21 0.010000 3 0 1.000000 - -Improper Coeffs - - 1 120.000000 0.000000 - 2 20.000000 0.000000 - -Atoms - - 1 1 1 0.510 43.99993 58.52678 36.78550 0 0 0 - 2 1 2 -0.270 45.10395 58.23499 35.86693 0 0 0 - 3 1 3 -0.510 43.81519 59.54928 37.43995 0 0 0 - 4 1 4 0.090 45.71714 57.34797 36.13434 0 0 0 - 5 1 4 0.090 45.72261 59.13657 35.67007 0 0 0 - 6 1 4 0.090 44.66624 58.09539 34.85538 0 0 0 - 7 1 5 -0.470 43.28193 57.47427 36.91953 0 0 0 - 8 1 6 0.070 42.07157 57.45486 37.62418 0 0 0 - 9 1 1 0.510 42.19985 57.57789 39.12163 0 0 0 - 10 1 3 -0.510 41.88641 58.62251 39.70398 0 0 0 - 11 1 7 -0.180 41.25052 56.15304 37.41811 0 0 0 - 12 1 8 0.000 40.88511 55.94638 35.97460 0 0 0 - 13 1 8 -0.115 41.48305 54.96372 35.11223 0 0 0 - 14 1 8 -0.115 39.74003 56.60996 35.46443 0 0 0 - 15 1 8 -0.115 41.02111 54.75715 33.80764 0 0 0 - 16 1 8 -0.115 39.26180 56.39194 34.12024 0 0 0 - 17 1 8 0.110 39.92330 55.46092 33.27135 0 0 0 - 18 1 9 -0.540 39.48164 55.22919 31.91865 0 0 0 - 19 1 10 0.310 43.60633 56.61693 36.52744 0 0 0 - 20 1 4 0.090 41.49619 58.31145 37.30543 0 0 0 - 21 1 4 0.090 41.88498 55.29476 37.72657 0 0 0 - 22 1 4 0.090 40.30899 56.19690 38.00627 0 0 0 - 23 1 11 0.115 42.31528 54.36176 35.44606 0 0 0 - 24 1 11 0.115 39.26330 57.31216 36.13230 0 0 0 - 25 1 11 0.115 41.62695 54.10606 33.19490 0 0 0 - 26 1 11 0.115 38.42147 56.98236 33.78612 0 0 0 - 27 1 10 0.430 38.78233 55.86217 31.74004 0 0 0 - 28 1 5 -0.470 42.79933 56.56370 39.79000 0 0 0 - 29 1 7 -0.020 42.96709 56.75379 41.28116 0 0 0 - 30 1 1 0.510 43.83019 55.68988 41.92255 0 0 0 - 31 1 3 -0.510 44.98521 55.93104 42.21713 0 0 0 - 32 1 10 0.310 43.13466 55.75696 39.30966 0 0 0 - 33 1 4 0.090 42.04692 56.86721 41.83507 0 0 0 - 34 1 4 0.090 43.52938 57.66324 41.43329 0 0 0 - 35 1 5 -0.470 43.26792 54.43342 42.07043 0 0 0 - 36 1 7 -0.020 43.92411 53.28930 42.63327 0 0 0 - 37 1 1 0.510 43.51012 53.02289 44.10510 0 0 0 - 38 1 3 -0.510 42.35086 53.07863 44.50806 0 0 0 - 39 1 10 0.310 42.28859 54.34993 41.90323 0 0 0 - 40 1 4 0.090 44.98464 53.47473 42.54797 0 0 0 - 41 1 4 0.090 43.49715 52.54787 41.97419 0 0 0 - 42 1 5 -0.470 44.51925 52.64535 44.88133 0 0 0 - 43 1 6 0.070 44.47588 52.35054 46.24397 0 0 0 - 44 1 1 0.510 45.40218 53.34579 46.94730 0 0 0 - 45 1 3 -0.510 45.23520 54.55893 46.92038 0 0 0 - 46 1 7 -0.180 44.77960 50.82831 46.50232 0 0 0 - 47 1 8 0.000 43.72184 49.84551 45.98093 0 0 0 - 48 1 8 -0.115 44.14810 49.00477 44.97195 0 0 0 - 49 1 8 -0.115 42.43499 49.66652 46.53541 0 0 0 - 50 1 8 -0.115 43.26154 48.00434 44.46769 0 0 0 - 51 1 8 -0.115 41.54732 48.79670 45.95416 0 0 0 - 52 1 8 -0.115 41.98220 47.90746 44.95574 0 0 0 - 53 1 10 0.310 45.39510 52.50937 44.42482 0 0 0 - 54 1 4 0.090 43.51312 52.58974 46.67092 0 0 0 - 55 1 4 0.090 44.89709 50.54313 47.56965 0 0 0 - 56 1 4 0.090 45.72096 50.49337 46.01654 0 0 0 - 57 1 11 0.115 45.13573 49.07933 44.54134 0 0 0 - 58 1 11 0.115 42.07869 50.34816 47.29358 0 0 0 - 59 1 11 0.115 43.47793 47.29281 43.68456 0 0 0 - 60 1 11 0.115 40.52625 48.76134 46.30425 0 0 0 - 61 1 11 0.115 41.35446 47.13287 44.54059 0 0 0 - 62 1 5 -0.470 46.41448 52.86278 47.68291 0 0 0 - 63 1 6 0.070 47.25136 53.68184 48.51163 0 0 0 - 64 1 1 0.510 48.33905 54.40097 47.73886 0 0 0 - 65 1 3 -0.510 49.27132 53.85220 47.16549 0 0 0 - 66 1 7 -0.180 47.88329 52.75681 49.60227 0 0 0 - 67 1 7 -0.140 48.82515 53.51102 50.61578 0 0 0 - 68 1 12 -0.090 48.12492 55.00373 51.43039 0 0 0 - 69 1 2 -0.220 47.70783 54.12980 53.04072 0 0 0 - 70 1 10 0.310 46.67199 51.90088 47.73231 0 0 0 - 71 1 4 0.090 46.64593 54.43552 48.99310 0 0 0 - 72 1 4 0.090 48.41361 51.90817 49.11968 0 0 0 - 73 1 4 0.090 47.08748 52.35196 50.26341 0 0 0 - 74 1 4 0.090 49.16067 52.81305 51.41238 0 0 0 - 75 1 4 0.090 49.73705 53.67062 50.00155 0 0 0 - 76 1 4 0.090 47.18593 54.84215 53.71488 0 0 0 - 77 1 4 0.090 48.69939 53.91624 53.49408 0 0 0 - 78 1 4 0.090 47.19749 53.18294 52.76264 0 0 0 - 79 1 5 -0.470 48.34472 55.71775 47.80498 0 0 0 - 80 1 2 -0.110 49.37792 56.51754 47.29492 0 0 0 - 81 1 10 0.310 47.51777 56.11617 48.19410 0 0 0 - 82 1 4 0.090 50.41495 56.13038 47.38980 0 0 0 - 83 1 4 0.090 49.23515 57.51193 47.76940 0 0 0 - 84 1 4 0.090 49.28612 56.52094 46.18773 0 0 0 - 85 2 13 -0.834 52.28049 45.72878 41.48140 -1 0 1 - 86 2 14 0.417 51.97210 46.07066 40.64218 -1 0 1 - 87 2 14 0.417 52.43689 44.79855 41.31868 -1 0 1 - 88 3 13 -0.834 43.84472 45.66062 47.17660 -2 -1 -1 - 89 3 14 0.417 43.42120 44.88337 46.81226 -2 -1 -1 - 90 3 14 0.417 44.31099 46.04907 46.43636 -2 -1 -1 - 91 4 13 -0.834 51.27805 50.25403 54.67397 0 0 -1 - 92 4 14 0.417 50.81295 50.23728 53.83753 0 0 -1 - 93 4 14 0.417 52.00273 49.63953 54.55795 0 0 -1 - 94 5 13 -0.834 44.71976 53.72011 56.43834 -1 0 -1 - 95 5 14 0.417 44.56050 53.84218 55.50241 -1 0 -1 - 96 5 14 0.417 44.91937 52.78829 56.52828 -1 0 -1 - 97 6 13 -0.834 37.07074 62.07204 53.35752 -1 -1 -1 - 98 6 14 0.417 64.17057 61.77089 52.49043 -2 -1 -1 - 99 6 14 0.417 37.90147 62.52273 53.20573 -1 -1 -1 - 100 7 13 -0.834 38.31817 66.10834 49.17406 0 -1 0 - 101 7 14 0.417 37.39300 65.93985 48.99534 0 -1 0 - 102 7 14 0.417 38.36506 66.20528 50.12520 0 -1 0 - 103 8 13 -0.834 60.90915 45.97690 35.53863 -1 -1 1 - 104 8 14 0.417 61.19898 46.87819 35.39745 -1 -1 1 - 105 8 14 0.417 59.98680 45.97855 35.28269 -1 -1 1 - 106 9 13 -0.834 54.33913 64.47210 51.00391 -1 -2 0 - 107 9 14 0.417 54.43191 63.71377 50.42724 -1 -2 0 - 108 9 14 0.417 55.16289 64.94980 50.90662 -1 -2 0 - 109 10 13 -0.834 44.58017 54.03749 53.84708 1 0 -1 - 110 10 14 0.417 43.87040 54.43768 53.34476 1 0 -1 - 111 10 14 0.417 45.02999 53.47261 53.21873 1 0 -1 - 112 11 13 -0.834 45.48693 52.12363 34.38241 0 -1 1 - 113 11 14 0.417 45.46898 52.67450 33.59981 0 -1 1 - 114 11 14 0.417 44.61476 52.22113 34.76457 0 -1 1 - 115 12 13 -0.834 60.15770 61.68799 54.74753 1 0 -2 - 116 12 14 0.417 59.23977 61.46439 54.59378 1 0 -2 - 117 12 14 0.417 60.43785 61.08922 55.43980 1 0 -2 - 118 13 13 -0.834 60.74732 66.72156 42.80906 1 -2 0 - 119 13 14 0.417 60.34713 66.21969 42.09898 1 -2 0 - 120 13 14 0.417 60.92444 66.07344 43.49082 1 -2 0 - 121 14 13 -0.834 60.82245 64.17281 50.54212 0 0 0 - 122 14 14 0.417 61.43571 64.88448 50.35863 0 0 0 - 123 14 14 0.417 60.87804 64.04633 51.48930 0 0 0 - 124 15 13 -0.834 36.92704 63.01353 56.05215 0 -1 0 - 125 15 14 0.417 37.10744 62.17054 56.46815 0 -1 0 - 126 15 14 0.417 64.06237 62.79109 55.15157 -1 -1 0 - 127 16 13 -0.834 48.35559 58.70568 56.14001 1 0 0 - 128 16 14 0.417 48.11655 59.48087 55.63191 1 0 0 - 129 16 14 0.417 47.93212 58.83502 56.98865 1 0 0 - 130 17 13 -0.834 58.14651 57.18542 51.08241 0 -1 -1 - 131 17 14 0.417 57.88523 56.72609 51.88052 0 -1 -1 - 132 17 14 0.417 57.35121 57.63116 50.79076 0 -1 -1 - 133 18 13 -0.834 58.09837 59.68005 36.16995 -1 0 0 - 134 18 14 0.417 58.25901 58.76822 36.41283 -1 0 0 - 135 18 14 0.417 58.56239 60.19049 36.83355 -1 0 0 - 136 19 13 -0.834 52.29019 60.51169 50.55611 0 -2 1 - 137 19 14 0.417 52.61972 60.01708 51.30645 0 -2 1 - 138 19 14 0.417 52.55621 59.99722 49.79401 0 -2 1 - 139 20 13 -0.834 41.36642 50.33705 42.98530 0 -1 -1 - 140 20 14 0.417 41.27846 50.09969 43.90844 0 -1 -1 - 141 20 14 0.417 40.99321 51.21659 42.92708 0 -1 -1 - 142 21 13 -0.834 53.76920 67.02645 32.18667 -1 0 1 - 143 21 14 0.417 53.59447 67.18509 31.25901 -1 0 1 - 144 21 14 0.417 54.65308 67.36647 32.32596 -1 0 1 - 145 22 13 -0.834 57.83691 45.33663 46.94671 0 0 -2 - 146 22 14 0.417 57.36287 45.59552 46.15647 0 0 -2 - 147 22 14 0.417 58.62995 44.91017 46.62197 0 0 -2 - 148 23 13 -0.834 60.34518 45.83000 45.57964 -1 0 0 - 149 23 14 0.417 60.61871 44.93757 45.79176 -1 0 0 - 150 23 14 0.417 61.09971 46.21212 45.13141 -1 0 0 - 151 24 13 -0.834 55.97902 46.85046 56.80163 0 1 1 - 152 24 14 0.417 56.57528 46.69952 30.16370 0 1 2 - 153 24 14 0.417 55.81156 47.79276 56.81850 0 1 1 - 154 25 13 -0.834 57.54668 45.52135 31.46139 -1 0 1 - 155 25 14 0.417 58.36291 46.00311 31.32743 -1 0 1 - 156 25 14 0.417 57.54151 45.31312 32.39566 -1 0 1 - 157 26 13 -0.834 58.03029 52.86783 46.33564 -1 -1 0 - 158 26 14 0.417 58.13662 52.56730 47.23820 -1 -1 0 - 159 26 14 0.417 58.81317 52.55269 45.88396 -1 -1 0 - 160 27 13 -0.834 62.89253 60.86549 46.75131 -2 -1 0 - 161 27 14 0.417 63.83924 60.74010 46.81653 -2 -1 0 - 162 27 14 0.417 62.51896 60.12788 47.23361 -2 -1 0 - 163 28 13 -0.834 43.29171 48.58106 31.82206 -1 0 2 - 164 28 14 0.417 43.07532 49.46362 32.12290 -1 0 2 - 165 28 14 0.417 43.82286 48.21072 32.52701 -1 0 2 - 166 29 13 -0.834 64.19867 44.17673 45.81391 -1 1 -1 - 167 29 14 0.417 63.72986 44.44010 45.02202 -1 1 -1 - 168 29 14 0.417 37.02069 43.24876 45.68087 0 1 -1 - 169 30 13 -0.834 50.42749 42.01163 53.60484 0 2 0 - 170 30 14 0.417 51.03177 41.90084 52.87081 0 2 0 - 171 30 14 0.417 50.77279 42.76181 54.08882 0 2 0 - 172 31 13 -0.834 38.63739 61.71113 49.95150 1 0 0 - 173 31 14 0.417 38.55432 62.15607 49.10808 1 0 0 - 174 31 14 0.417 37.81718 61.22751 50.04950 1 0 0 - 175 32 13 -0.834 61.47262 53.02922 33.08309 -1 -1 0 - 176 32 14 0.417 61.21894 52.67931 33.93717 -1 -1 0 - 177 32 14 0.417 61.89351 53.86564 33.28182 -1 -1 0 - 178 33 13 -0.834 54.44545 60.06011 48.63522 -1 0 1 - 179 33 14 0.417 54.80032 60.94424 48.72810 -1 0 1 - 180 33 14 0.417 54.09041 60.03614 47.74662 -1 0 1 - 181 34 13 -0.834 56.34364 60.90201 52.60838 -1 -1 0 - 182 34 14 0.417 56.48857 60.19161 53.23333 -1 -1 0 - 183 34 14 0.417 56.17362 61.67024 53.15351 -1 -1 0 - 184 35 13 -0.834 56.05881 51.84328 55.76103 -1 0 0 - 185 35 14 0.417 55.59060 51.75146 54.93121 -1 0 0 - 186 35 14 0.417 55.46974 52.35732 56.31335 -1 0 0 - 187 36 13 -0.834 39.00621 42.74743 30.97845 0 0 1 - 188 36 14 0.417 39.67620 42.11390 30.72152 0 0 1 - 189 36 14 0.417 39.43456 43.29673 31.63499 0 0 1 - 190 37 13 -0.834 46.77585 55.39774 30.24026 0 1 0 - 191 37 14 0.417 46.10274 54.90237 29.77360 0 1 0 - 192 37 14 0.417 46.39626 56.26890 30.35527 0 1 0 - 193 38 13 -0.834 45.10722 57.60431 31.54688 -1 0 0 - 194 38 14 0.417 44.80783 58.50032 31.70105 -1 0 0 - 195 38 14 0.417 44.44237 57.22463 30.97238 -1 0 0 - 196 39 13 -0.834 43.94230 46.99244 34.45668 -2 1 1 - 197 39 14 0.417 44.62010 46.49140 34.00306 -2 1 1 - 198 39 14 0.417 44.38150 47.79794 34.72964 -2 1 1 - 199 40 13 -0.834 51.39443 50.96507 34.69072 -1 1 0 - 200 40 14 0.417 51.18729 50.42829 35.45570 -1 1 0 - 201 40 14 0.417 51.33198 51.86665 35.00616 -1 1 0 - 202 41 13 -0.834 58.96398 48.19727 42.98856 -2 1 0 - 203 41 14 0.417 58.42587 48.90112 42.62618 -2 1 0 - 204 41 14 0.417 58.82383 48.25054 43.93397 -2 1 0 - 205 42 13 -0.834 62.89335 41.94260 37.40820 0 0 0 - 206 42 14 0.417 62.48690 41.07818 37.46980 0 0 0 - 207 42 14 0.417 63.01802 42.08284 36.46957 0 0 0 - 208 43 13 -0.834 54.19388 47.88689 36.24110 -1 0 1 - 209 43 14 0.417 54.32054 48.63090 35.65235 -1 0 1 - 210 43 14 0.417 53.24370 47.78935 36.30358 -1 0 1 - 211 44 13 -0.834 39.19734 57.40342 41.28495 0 0 -2 - 212 44 14 0.417 39.05428 57.72940 40.39641 0 0 -2 - 213 44 14 0.417 39.30846 56.45861 41.17895 0 0 -2 - 214 45 13 -0.834 52.85483 61.73749 54.63897 0 0 0 - 215 45 14 0.417 53.34938 62.52765 54.42147 0 0 0 - 216 45 14 0.417 53.01046 61.14656 53.90221 0 0 0 - 217 46 13 -0.834 47.09467 62.01384 35.02302 1 0 1 - 218 46 14 0.417 47.54527 61.47644 35.67448 1 0 1 - 219 46 14 0.417 47.10116 62.89626 35.39385 1 0 1 - 220 47 13 -0.834 46.80497 49.60334 37.05700 0 0 1 - 221 47 14 0.417 46.70216 49.79770 36.12540 0 0 1 - 222 47 14 0.417 45.91311 49.45393 37.37084 0 0 1 - 223 48 13 -0.834 63.21969 59.12311 54.43455 -1 -1 -1 - 224 48 14 0.417 63.94585 59.72833 54.28405 -1 -1 -1 - 225 48 14 0.417 63.63016 58.34481 54.81141 -1 -1 -1 - 226 49 13 -0.834 59.88416 59.64215 44.04914 -2 1 0 - 227 49 14 0.417 59.74255 59.14412 44.85422 -2 1 0 - 228 49 14 0.417 59.02635 60.01323 43.84248 -2 1 0 - 229 50 13 -0.834 40.50825 42.85328 50.81112 -1 1 0 - 230 50 14 0.417 40.34650 43.39801 51.58141 -1 1 0 - 231 50 14 0.417 39.63964 42.69867 50.43985 -1 1 0 - 232 51 13 -0.834 63.77522 64.97067 44.83010 -2 0 0 - 233 51 14 0.417 37.00507 65.56132 45.28388 -1 0 0 - 234 51 14 0.417 64.14243 64.88383 43.95041 -2 0 0 - 235 52 13 -0.834 62.47161 67.86189 47.38235 -1 0 -1 - 236 52 14 0.417 61.58819 67.64608 47.08360 -1 0 -1 - 237 52 14 0.417 62.79136 67.05596 47.78790 -1 0 -1 - 238 53 13 -0.834 43.90800 54.16107 50.35199 0 0 0 - 239 53 14 0.417 43.96769 53.24711 50.07388 0 0 0 - 240 53 14 0.417 43.72593 54.64554 49.54677 0 0 0 - 241 54 13 -0.834 63.46829 44.63390 34.73615 -1 1 1 - 242 54 14 0.417 62.63731 45.04623 34.97217 -1 1 1 - 243 54 14 0.417 64.11050 45.03645 35.32075 -1 1 1 - 244 55 13 -0.834 37.30679 58.22047 51.04345 0 0 0 - 245 55 14 0.417 38.18596 58.37862 50.69950 0 0 0 - 246 55 14 0.417 36.85723 59.06017 50.94824 0 0 0 - 247 56 13 -0.834 58.72649 42.45768 31.23820 -1 1 -1 - 248 56 14 0.417 59.43634 42.77561 30.68028 -1 1 -1 - 249 56 14 0.417 58.76581 41.50474 31.15690 -1 1 -1 - 250 57 13 -0.834 52.47101 42.85691 41.60986 0 1 -1 - 251 57 14 0.417 51.62289 42.91562 41.16997 0 1 -1 - 252 57 14 0.417 52.53109 41.94497 41.89448 0 1 -1 - 253 58 13 -0.834 60.63476 59.78356 56.53663 -2 -1 -1 - 254 58 14 0.417 60.87428 58.86269 56.43247 -2 -1 -1 - 255 58 14 0.417 59.72615 59.76269 56.83705 -2 -1 -1 - 256 59 13 -0.834 52.78127 57.47386 30.66786 -1 -1 0 - 257 59 14 0.417 52.55495 58.26092 30.17228 -1 -1 0 - 258 59 14 0.417 53.05203 56.84104 30.00267 -1 -1 0 - 259 60 13 -0.834 46.04848 57.65321 54.89998 0 3 -1 - 260 60 14 0.417 46.96883 57.71336 55.15607 0 3 -1 - 261 60 14 0.417 46.02768 57.98076 54.00081 0 3 -1 - 262 61 13 -0.834 60.39356 51.43705 35.66109 -1 1 -1 - 263 61 14 0.417 60.57739 52.08235 36.34376 -1 1 -1 - 264 61 14 0.417 59.59475 50.99860 35.95414 -1 1 -1 - 265 62 13 -0.834 50.32338 62.46972 35.65752 -1 0 2 - 266 62 14 0.417 51.24156 62.23287 35.52678 -1 0 2 - 267 62 14 0.417 49.89601 61.64851 35.90085 -1 0 2 - 268 63 13 -0.834 38.23983 45.11908 50.02773 0 1 0 - 269 63 14 0.417 38.61336 45.27494 50.89515 0 1 0 - 270 63 14 0.417 38.91224 45.42406 49.41856 0 1 0 - 271 64 13 -0.834 58.93720 57.36605 46.08362 -3 0 0 - 272 64 14 0.417 58.65753 56.63297 46.63190 -3 0 0 - 273 64 14 0.417 58.29914 58.05674 46.26268 -3 0 0 - 274 65 13 -0.834 47.99806 43.44789 47.43046 -1 0 0 - 275 65 14 0.417 48.39580 43.78289 46.62684 -1 0 0 - 276 65 14 0.417 47.85848 44.22523 47.97128 -1 0 0 - 277 66 13 -0.834 51.26744 52.05593 47.09995 -1 0 0 - 278 66 14 0.417 51.36736 52.09873 46.14894 -1 0 0 - 279 66 14 0.417 50.33779 52.22629 47.25149 -1 0 0 - 280 67 13 -0.834 39.06132 52.11517 46.39010 0 0 -1 - 281 67 14 0.417 38.53402 51.36282 46.65876 0 0 -1 - 282 67 14 0.417 39.47133 52.42190 47.19884 0 0 -1 - 283 68 13 -0.834 60.17907 58.95174 50.22759 -1 1 0 - 284 68 14 0.417 60.34080 59.56538 50.94420 -1 1 0 - 285 68 14 0.417 59.41497 58.44908 50.50992 -1 1 0 - 286 69 13 -0.834 40.47698 59.65154 34.92537 0 -1 1 - 287 69 14 0.417 40.89044 60.49055 35.12877 0 -1 1 - 288 69 14 0.417 41.17964 59.12336 34.54648 0 -1 1 - 289 70 13 -0.834 60.12998 66.51474 47.03971 -1 0 -1 - 290 70 14 0.417 59.26620 66.39701 47.43506 -1 0 -1 - 291 70 14 0.417 60.21358 65.78625 46.42443 -1 0 -1 - 292 71 13 -0.834 49.25986 47.27506 43.03372 -1 0 1 - 293 71 14 0.417 49.11810 48.15331 42.68041 -1 0 1 - 294 71 14 0.417 49.86162 47.40550 43.76662 -1 0 1 - 295 72 13 -0.834 41.48105 63.65699 31.84433 0 0 1 - 296 72 14 0.417 41.11022 64.48589 32.14713 0 0 1 - 297 72 14 0.417 40.89461 63.37379 31.14281 0 0 1 - 298 73 13 -0.834 47.82875 47.97039 54.56720 0 2 0 - 299 73 14 0.417 46.99167 47.50633 54.55352 0 2 0 - 300 73 14 0.417 47.60488 48.87558 54.35102 0 2 0 - 301 74 13 -0.834 62.36735 58.64445 48.35778 -2 1 0 - 302 74 14 0.417 62.88767 57.90867 48.68045 -2 1 0 - 303 74 14 0.417 61.65918 58.73544 48.99531 -2 1 0 - 304 75 13 -0.834 52.09508 65.08907 32.87560 0 0 0 - 305 75 14 0.417 52.67402 65.75058 32.49683 0 0 0 - 306 75 14 0.417 52.41855 64.97003 33.76859 0 0 0 - 307 76 13 -0.834 39.06932 41.62988 40.69498 1 1 0 - 308 76 14 0.417 39.51114 41.04433 40.08003 1 1 0 - 309 76 14 0.417 38.93584 42.43936 40.20186 1 1 0 - 310 77 13 -0.834 37.68325 49.50718 46.00750 0 2 0 - 311 77 14 0.417 64.11601 49.67107 45.91568 -1 2 0 - 312 77 14 0.417 37.90845 48.96991 45.24796 0 2 0 - 313 78 13 -0.834 53.00757 59.49351 52.98404 -2 1 -1 - 314 78 14 0.417 52.16721 59.28329 53.39127 -2 1 -1 - 315 78 14 0.417 53.61000 58.83023 53.32076 -2 1 -1 - 316 79 13 -0.834 51.89369 64.75001 56.68467 1 0 0 - 317 79 14 0.417 51.88079 65.63682 56.32462 1 0 0 - 318 79 14 0.417 52.40589 64.82531 30.11841 1 0 1 - 319 80 13 -0.834 48.43261 63.10155 32.63566 0 0 1 - 320 80 14 0.417 47.68021 63.01753 32.04993 0 0 1 - 321 80 14 0.417 48.13916 62.71424 33.46035 0 0 1 - 322 81 13 -0.834 62.41171 68.18251 30.67168 0 -1 2 - 323 81 14 0.417 61.79235 41.16145 30.03143 0 0 2 - 324 81 14 0.417 63.18314 67.94790 30.15584 0 -1 2 - 325 82 13 -0.834 42.57575 41.32197 37.66791 0 0 1 - 326 82 14 0.417 42.98116 41.36016 36.80164 0 0 1 - 327 82 14 0.417 42.32522 42.22654 37.85569 0 0 1 - 328 83 13 -0.834 50.17315 67.44398 36.91606 0 -2 0 - 329 83 14 0.417 50.08765 67.03449 37.77701 0 -2 0 - 330 83 14 0.417 50.35347 66.71621 36.32101 0 -2 0 - 331 84 13 -0.834 39.70163 60.45247 40.03790 0 -2 -1 - 332 84 14 0.417 38.85282 60.01540 40.10676 0 -2 -1 - 333 84 14 0.417 40.20579 60.11563 40.77858 0 -2 -1 - 334 85 13 -0.834 51.74323 42.80814 51.33239 0 0 -1 - 335 85 14 0.417 52.44810 43.22892 51.82466 0 0 -1 - 336 85 14 0.417 51.80961 43.17998 50.45286 0 0 -1 - 337 86 13 -0.834 51.34695 47.68316 36.38089 0 0 1 - 338 86 14 0.417 50.77701 46.92707 36.52138 0 0 1 - 339 86 14 0.417 51.27109 47.87031 35.44523 0 0 1 - 340 87 13 -0.834 62.66950 50.66085 43.15883 -2 0 0 - 341 87 14 0.417 63.57796 50.36318 43.11051 -2 0 0 - 342 87 14 0.417 62.24654 50.26548 42.39659 -2 0 0 - 343 88 13 -0.834 46.37996 60.13914 31.06428 -2 -1 1 - 344 88 14 0.417 46.89125 59.89673 31.83632 -2 -1 1 - 345 88 14 0.417 45.51811 60.37092 31.41028 -2 -1 1 - 346 89 13 -0.834 50.23251 41.17559 46.18435 0 1 2 - 347 89 14 0.417 49.40509 68.16142 45.89628 0 0 2 - 348 89 14 0.417 50.55747 67.94506 46.85395 0 0 2 - 349 90 13 -0.834 56.10446 66.70018 42.60390 0 -2 1 - 350 90 14 0.417 56.27454 67.42915 42.00732 0 -2 1 - 351 90 14 0.417 56.27819 67.05729 43.47483 0 -2 1 - 352 91 13 -0.834 55.53824 48.43866 51.97225 -1 0 1 - 353 91 14 0.417 56.26440 48.96682 52.30388 -1 0 1 - 354 91 14 0.417 55.26306 48.88494 51.17140 -1 0 1 - 355 92 13 -0.834 37.88016 52.62502 33.55552 0 -1 0 - 356 92 14 0.417 37.58757 51.72397 33.41859 0 -1 0 - 357 92 14 0.417 38.51960 52.77804 32.85986 0 -1 0 - 358 93 13 -0.834 50.40592 66.14455 39.40035 -1 -2 -1 - 359 93 14 0.417 49.74974 66.37168 40.05920 -1 -2 -1 - 360 93 14 0.417 50.22642 65.22843 39.18876 -1 -2 -1 - 361 94 13 -0.834 59.56315 43.63477 50.02876 -1 0 0 - 362 94 14 0.417 60.08533 44.36640 50.35782 -1 0 0 - 363 94 14 0.417 60.10101 42.86112 50.19730 -1 0 0 - 364 95 13 -0.834 57.16125 61.75981 55.17964 0 0 -1 - 365 95 14 0.417 56.45534 61.68609 55.82189 0 0 -1 - 366 95 14 0.417 57.38335 62.69087 55.17297 0 0 -1 - 367 96 13 -0.834 54.81274 43.48714 43.13392 -1 2 1 - 368 96 14 0.417 53.88771 43.40698 42.90124 -1 2 1 - 369 96 14 0.417 54.97915 42.74512 43.71525 -1 2 1 - 370 97 13 -0.834 41.23040 49.49766 49.75568 0 -2 0 - 371 97 14 0.417 40.54278 49.43865 49.09241 0 -2 0 - 372 97 14 0.417 41.81904 48.76959 49.55653 0 -2 0 - 373 98 13 -0.834 54.20957 45.39084 54.97428 -1 0 0 - 374 98 14 0.417 54.66721 46.06623 55.47493 -1 0 0 - 375 98 14 0.417 53.74016 44.87996 55.63374 -1 0 0 - 376 99 13 -0.834 61.27515 64.38553 39.98716 -1 0 1 - 377 99 14 0.417 61.56153 64.23410 40.88787 -1 0 1 - 378 99 14 0.417 60.44736 63.91029 39.91542 -1 0 1 - 379 100 13 -0.834 55.67284 58.14856 42.21767 -1 1 2 - 380 100 14 0.417 55.46369 57.24253 42.44485 -1 1 2 - 381 100 14 0.417 56.62771 58.19397 42.26677 -1 1 2 - 382 101 13 -0.834 43.66528 51.07118 53.71174 0 0 0 - 383 101 14 0.417 42.87715 50.89079 53.19934 0 0 0 - 384 101 14 0.417 43.37793 51.68815 54.38481 0 0 0 - 385 102 13 -0.834 39.90899 44.53973 36.42818 0 2 0 - 386 102 14 0.417 39.84006 43.65427 36.07118 0 2 0 - 387 102 14 0.417 40.52179 44.98683 35.84438 0 2 0 - 388 103 13 -0.834 51.24695 66.96031 48.71611 -1 -1 1 - 389 103 14 0.417 50.88275 67.26607 49.54684 -1 -1 1 - 390 103 14 0.417 52.19366 66.95318 48.85726 -1 -1 1 - 391 104 13 -0.834 55.15911 56.17347 57.08906 -1 0 0 - 392 104 14 0.417 55.86241 55.65189 56.70232 -1 0 0 - 393 104 14 0.417 54.93977 55.71619 30.52949 -1 0 1 - 394 105 13 -0.834 37.33282 54.30424 56.96734 0 0 0 - 395 105 14 0.417 64.15558 54.97773 29.99806 -1 0 1 - 396 105 14 0.417 64.13467 53.88397 56.32293 -1 0 0 - 397 106 13 -0.834 53.07827 51.20543 32.31512 -1 0 1 - 398 106 14 0.417 52.39494 50.78813 31.79057 -1 0 1 - 399 106 14 0.417 52.65819 51.38698 33.15584 -1 0 1 - 400 107 13 -0.834 43.06086 51.65229 35.75926 1 1 1 - 401 107 14 0.417 42.70958 52.01746 36.57135 1 1 1 - 402 107 14 0.417 43.42908 50.80682 36.01586 1 1 1 - 403 108 13 -0.834 53.92253 56.24460 34.48089 0 0 1 - 404 108 14 0.417 53.22007 56.39276 35.11401 0 0 1 - 405 108 14 0.417 54.59075 55.76600 34.97147 0 0 1 - 406 109 13 -0.834 61.71524 66.84153 38.60005 -1 -1 0 - 407 109 14 0.417 61.25397 66.04877 38.87388 -1 -1 0 - 408 109 14 0.417 62.23260 67.09437 39.36467 -1 -1 0 - 409 110 13 -0.834 43.52824 62.78695 41.49939 0 -1 -1 - 410 110 14 0.417 43.61050 61.97218 41.00379 0 -1 -1 - 411 110 14 0.417 43.53140 63.47437 40.83330 0 -1 -1 - 412 111 13 -0.834 51.13822 55.54090 53.50461 0 1 -2 - 413 111 14 0.417 50.69587 56.38179 53.62064 0 1 -2 - 414 111 14 0.417 51.43262 55.54828 52.59383 0 1 -2 - 415 112 13 -0.834 46.94709 50.11761 31.92599 0 0 0 - 416 112 14 0.417 47.19652 51.02564 31.75423 0 0 0 - 417 112 14 0.417 46.57462 49.81059 31.09941 0 0 0 - 418 113 13 -0.834 47.96666 45.13049 44.46108 -1 2 -1 - 419 113 14 0.417 47.01871 45.24108 44.53489 -1 2 -1 - 420 113 14 0.417 48.26343 45.91034 43.99202 -1 2 -1 - 421 114 13 -0.834 44.43868 43.44849 32.90814 -1 -1 1 - 422 114 14 0.417 43.86055 43.24165 33.64245 -1 -1 1 - 423 114 14 0.417 45.31670 43.24154 33.22828 -1 -1 1 - 424 115 13 -0.834 61.07172 47.80130 53.14504 -1 1 -1 - 425 115 14 0.417 61.34864 48.71600 53.19864 -1 1 -1 - 426 115 14 0.417 60.72118 47.60538 54.01394 -1 1 -1 - 427 116 13 -0.834 51.38727 44.10864 54.92855 -1 0 -1 - 428 116 14 0.417 50.77962 44.80360 55.18160 -1 0 -1 - 429 116 14 0.417 52.05111 44.10744 55.61815 -1 0 -1 - 430 117 13 -0.834 41.05585 60.12319 49.44785 1 -1 0 - 431 117 14 0.417 41.72702 60.76812 49.67116 1 -1 0 - 432 117 14 0.417 40.24373 60.62784 49.40265 1 -1 0 - 433 118 13 -0.834 50.88548 68.33364 33.37284 -1 0 -1 - 434 118 14 0.417 50.48275 67.46671 33.32310 -1 0 -1 - 435 118 14 0.417 51.82702 68.16119 33.37343 -1 0 -1 - 436 119 13 -0.834 38.79644 59.29061 55.22446 1 1 -1 - 437 119 14 0.417 38.82887 59.83550 56.01077 1 1 -1 - 438 119 14 0.417 39.26097 59.79985 54.56028 1 1 -1 - 439 120 13 -0.834 56.31813 41.68729 51.11871 -2 0 -1 - 440 120 14 0.417 55.45155 41.35580 51.35412 -2 0 -1 - 441 120 14 0.417 56.14879 42.34135 50.44062 -2 0 -1 - 442 121 13 -0.834 45.53697 59.28154 47.22033 -1 0 -1 - 443 121 14 0.417 45.45062 59.55577 46.30733 -1 0 -1 - 444 121 14 0.417 46.00774 59.99977 47.64313 -1 0 -1 - 445 122 13 -0.834 60.47636 43.28130 46.20944 -1 0 -1 - 446 122 14 0.417 60.97762 42.59184 45.77396 -1 0 -1 - 447 122 14 0.417 59.72992 42.82584 46.59884 -1 0 -1 - 448 123 13 -0.834 58.49080 48.18289 45.77215 0 0 -1 - 449 123 14 0.417 58.74342 47.25991 45.74879 0 0 -1 - 450 123 14 0.417 58.17926 48.32386 46.66621 0 0 -1 - 451 124 13 -0.834 50.93473 56.12663 41.58575 -1 0 0 - 452 124 14 0.417 50.36171 56.05214 42.34885 -1 0 0 - 453 124 14 0.417 50.40135 56.57242 40.92771 -1 0 0 - 454 125 13 -0.834 60.55008 41.95542 56.22749 -1 0 -1 - 455 125 14 0.417 59.65163 41.78987 55.94175 -1 0 -1 - 456 125 14 0.417 61.09463 41.59967 55.52524 -1 0 -1 - 457 126 13 -0.834 58.58373 51.69338 48.78985 -1 1 0 - 458 126 14 0.417 58.38773 52.01803 49.66874 -1 1 0 - 459 126 14 0.417 58.66973 50.74614 48.89756 -1 1 0 - 460 127 13 -0.834 37.82769 45.69808 30.85100 0 1 3 - 461 127 14 0.417 38.37007 45.10637 31.37248 0 1 3 - 462 127 14 0.417 37.14646 45.99401 31.45481 0 1 3 - 463 128 13 -0.834 50.96455 60.06361 33.68049 0 0 0 - 464 128 14 0.417 51.72055 60.15430 34.26055 0 0 0 - 465 128 14 0.417 51.05673 60.77997 33.05234 0 0 0 - 466 129 13 -0.834 46.43413 68.11245 51.48833 -1 0 -1 - 467 129 14 0.417 46.82151 41.36005 50.86943 -1 1 -1 - 468 129 14 0.417 47.09847 67.43153 51.59433 -1 0 -1 - 469 130 13 -0.834 61.79997 47.41648 57.05141 -1 -1 0 - 470 130 14 0.417 62.68713 47.23872 56.73898 -1 -1 0 - 471 130 14 0.417 61.48917 46.57417 30.01195 -1 -1 1 - 472 131 13 -0.834 45.30689 46.58119 54.43763 0 1 -1 - 473 131 14 0.417 45.67282 45.73922 54.70859 0 1 -1 - 474 131 14 0.417 44.46622 46.35973 54.03705 0 1 -1 - 475 132 13 -0.834 62.60829 48.56385 49.02640 -1 1 0 - 476 132 14 0.417 62.44761 48.65968 48.08766 -1 1 0 - 477 132 14 0.417 62.98242 47.68753 49.11762 -1 1 0 - 478 133 13 -0.834 63.49107 56.77075 38.74961 -1 0 2 - 479 133 14 0.417 63.12281 56.39554 39.54952 -1 0 2 - 480 133 14 0.417 62.84612 57.42058 38.47033 -1 0 2 - 481 134 13 -0.834 50.74846 48.34849 33.46075 0 0 1 - 482 134 14 0.417 50.75342 49.30521 33.43086 0 0 1 - 483 134 14 0.417 50.91203 48.07929 32.55686 0 0 1 - 484 135 13 -0.834 44.40923 67.37148 56.42156 0 0 0 - 485 135 14 0.417 43.93400 67.78902 29.76856 0 0 1 - 486 135 14 0.417 44.94884 66.70468 56.84633 0 0 0 - 487 136 13 -0.834 44.25343 64.95349 43.22104 0 0 0 - 488 136 14 0.417 44.13229 64.08173 42.84472 0 0 0 - 489 136 14 0.417 44.01188 65.55470 42.51643 0 0 0 - 490 137 13 -0.834 46.68300 67.52863 32.69859 -1 -1 0 - 491 137 14 0.417 46.68369 68.22637 33.35389 -1 -1 0 - 492 137 14 0.417 47.60248 67.43099 32.45106 -1 -1 0 - 493 138 13 -0.834 57.25376 61.01737 33.86507 -2 1 1 - 494 138 14 0.417 57.40827 60.52366 34.67043 -2 1 1 - 495 138 14 0.417 57.35792 60.37307 33.16488 -2 1 1 - 496 139 13 -0.834 57.39946 54.16835 56.70699 0 -1 -1 - 497 139 14 0.417 57.31939 53.23092 56.53080 0 -1 -1 - 498 139 14 0.417 57.32300 54.24112 30.28699 0 -1 0 - 499 140 13 -0.834 52.36697 48.69246 41.49227 -1 1 0 - 500 140 14 0.417 51.78735 47.93629 41.40021 -1 1 0 - 501 140 14 0.417 53.21603 48.31702 41.72547 -1 1 0 - 502 141 13 -0.834 54.69200 49.57915 45.55048 0 0 -1 - 503 141 14 0.417 54.95958 48.66911 45.42211 0 0 -1 - 504 141 14 0.417 55.28513 50.08439 44.99446 0 0 -1 - 505 142 13 -0.834 37.26724 53.17896 42.50469 1 -1 -1 - 506 142 14 0.417 63.93194 53.34801 43.12782 0 -1 -1 - 507 142 14 0.417 36.94831 52.45044 41.97199 1 -1 -1 - 508 143 13 -0.834 42.56283 66.92379 33.49577 -1 0 1 - 509 143 14 0.417 41.71356 66.58931 33.20750 -1 0 1 - 510 143 14 0.417 43.03645 66.14842 33.79697 -1 0 1 - 511 144 13 -0.834 61.43331 45.62855 38.97695 0 1 1 - 512 144 14 0.417 61.20190 45.98514 39.83458 0 1 1 - 513 144 14 0.417 62.31351 45.96414 38.80708 0 1 1 - 514 145 13 -0.834 49.37935 56.26031 56.72879 1 1 0 - 515 145 14 0.417 49.03977 57.11146 56.45221 1 1 0 - 516 145 14 0.417 48.60052 55.75658 56.96530 1 1 0 - 517 146 13 -0.834 63.13959 56.23999 49.92079 -1 0 -1 - 518 146 14 0.417 63.72474 55.58123 50.29478 -1 0 -1 - 519 146 14 0.417 63.40966 57.06154 50.33112 -1 0 -1 - 520 147 13 -0.834 58.55937 66.56287 54.17345 -1 0 0 - 521 147 14 0.417 59.28260 66.81524 53.59945 -1 0 0 - 522 147 14 0.417 58.28559 67.38088 54.58834 -1 0 0 - 523 148 13 -0.834 55.49901 62.14366 46.01274 -1 0 -1 - 524 148 14 0.417 55.08057 61.57956 45.36238 -1 0 -1 - 525 148 14 0.417 55.53371 63.00495 45.59652 -1 0 -1 - 526 149 13 -0.834 48.09589 47.38106 38.97384 0 1 0 - 527 149 14 0.417 47.94178 48.02346 38.28116 0 1 0 - 528 149 14 0.417 47.26125 47.32494 39.43910 0 1 0 - 529 150 13 -0.834 40.27661 53.03711 48.83757 0 0 0 - 530 150 14 0.417 40.32476 53.91333 49.21992 0 0 0 - 531 150 14 0.417 41.18363 52.81848 48.62365 0 0 0 - 532 151 13 -0.834 36.85277 41.68065 44.81488 1 2 0 - 533 151 14 0.417 36.95709 68.34807 45.45504 1 1 0 - 534 151 14 0.417 37.14062 41.29651 43.98673 1 2 0 - 535 152 13 -0.834 37.74881 65.81650 33.58759 -1 0 1 - 536 152 14 0.417 37.69052 65.99217 34.52673 -1 0 1 - 537 152 14 0.417 37.02193 65.21970 33.40951 -1 0 1 - 538 153 13 -0.834 63.01838 46.13766 43.99274 -2 0 0 - 539 153 14 0.417 62.72780 46.33504 43.10232 -2 0 0 - 540 153 14 0.417 63.75125 46.73459 44.14387 -2 0 0 - 541 154 13 -0.834 43.83288 53.92104 38.64974 0 2 1 - 542 154 14 0.417 44.46072 53.30394 39.02556 0 2 1 - 543 154 14 0.417 44.17373 54.10726 37.77488 0 2 1 - 544 155 13 -0.834 54.48021 41.30441 45.39416 1 1 -2 - 545 155 14 0.417 54.42996 67.86451 44.88861 1 0 -2 - 546 155 14 0.417 54.84291 41.03852 46.23914 1 1 -2 - 547 156 13 -0.834 51.26407 63.10699 50.73012 0 0 -2 - 548 156 14 0.417 51.64016 62.23294 50.83411 0 0 -2 - 549 156 14 0.417 51.56733 63.39797 49.87011 0 0 -2 - 550 157 13 -0.834 54.61161 63.67709 53.56970 0 1 1 - 551 157 14 0.417 55.55339 63.81655 53.47054 0 1 1 - 552 157 14 0.417 54.24805 63.87070 52.70565 0 1 1 - 553 158 13 -0.834 46.57444 42.69363 30.13287 -1 0 1 - 554 158 14 0.417 45.93025 42.28051 30.70783 -1 0 1 - 555 158 14 0.417 47.27305 42.04459 30.04973 -1 0 1 - 556 159 13 -0.834 37.92811 50.36816 42.31352 1 1 0 - 557 159 14 0.417 38.62401 50.90050 42.69899 1 1 0 - 558 159 14 0.417 38.11553 50.37135 41.37484 1 1 0 - 559 160 13 -0.834 40.53318 48.69302 33.52502 -1 0 0 - 560 160 14 0.417 40.10720 48.55075 32.67972 -1 0 0 - 561 160 14 0.417 41.22323 49.33057 33.34173 -1 0 0 - 562 161 13 -0.834 58.20095 45.48345 42.83426 1 0 -1 - 563 161 14 0.417 58.76156 46.25356 42.92849 1 0 -1 - 564 161 14 0.417 58.80813 44.74348 42.83158 1 0 -1 - 565 162 13 -0.834 59.85909 67.06752 31.43173 -1 1 0 - 566 162 14 0.417 59.95062 66.12180 31.54782 -1 1 0 - 567 162 14 0.417 60.75672 67.38534 31.33437 -1 1 0 - 568 163 13 -0.834 48.48808 51.17807 55.92072 -2 0 0 - 569 163 14 0.417 49.24951 51.62602 55.55219 -2 0 0 - 570 163 14 0.417 48.81105 50.30745 56.15303 -2 0 0 - 571 164 13 -0.834 47.51169 45.69616 48.99410 0 0 -1 - 572 164 14 0.417 48.36822 46.03425 48.73281 0 0 -1 - 573 164 14 0.417 47.56201 45.62598 49.94740 0 0 -1 - 574 165 13 -0.834 51.10678 64.23082 47.99167 0 -2 -1 - 575 165 14 0.417 51.33188 65.16116 47.98611 0 -2 -1 - 576 165 14 0.417 50.15837 64.21415 48.12002 0 -2 -1 - 577 166 13 -0.834 42.97263 56.29674 30.18230 0 0 0 - 578 166 14 0.417 42.45756 55.50818 30.01170 0 0 0 - 579 166 14 0.417 42.79675 56.86516 56.80386 0 0 -1 - 580 167 13 -0.834 44.45917 53.64338 31.85015 -1 0 0 - 581 167 14 0.417 44.64093 54.17218 31.07325 -1 0 0 - 582 167 14 0.417 43.66299 53.15965 31.63030 -1 0 0 - 583 168 13 -0.834 52.20677 49.92062 48.65330 1 0 0 - 584 168 14 0.417 52.24176 50.63538 49.28902 1 0 0 - 585 168 14 0.417 52.01918 50.35058 47.81890 1 0 0 - 586 169 13 -0.834 45.94013 51.43638 56.49888 0 0 0 - 587 169 14 0.417 46.89200 51.34153 56.53372 0 0 0 - 588 169 14 0.417 45.60504 50.66051 56.94833 0 0 0 - 589 170 13 -0.834 45.61845 41.38709 48.05698 1 0 0 - 590 170 14 0.417 46.42604 41.83441 47.80406 1 0 0 - 591 170 14 0.417 45.31743 41.85685 48.83477 1 0 0 - 592 171 13 -0.834 47.68232 42.84819 52.92728 0 1 0 - 593 171 14 0.417 47.61830 42.41414 52.07654 0 1 0 - 594 171 14 0.417 48.39202 42.39011 53.37758 0 1 0 - 595 172 13 -0.834 37.01774 65.84057 36.39542 1 -1 0 - 596 172 14 0.417 36.84918 65.13561 37.02061 1 -1 0 - 597 172 14 0.417 63.52368 66.19949 36.19938 0 -1 0 - 598 173 13 -0.834 51.52891 58.65207 39.31760 -1 -3 -1 - 599 173 14 0.417 51.57384 59.35596 39.96472 -1 -3 -1 - 600 173 14 0.417 51.00435 59.01522 38.60403 -1 -3 -1 - 601 174 13 -0.834 49.06578 54.25781 44.33488 0 -1 -1 - 602 174 14 0.417 48.81980 55.18018 44.26437 0 -1 -1 - 603 174 14 0.417 49.41695 54.17018 45.22104 0 -1 -1 - 604 175 13 -0.834 47.03819 42.38557 34.31948 -1 -1 0 - 605 175 14 0.417 47.39035 41.82883 35.01393 -1 -1 0 - 606 175 14 0.417 47.47024 43.23019 34.44673 -1 -1 0 - 607 176 13 -0.834 41.64025 43.65472 38.33192 0 1 0 - 608 176 14 0.417 41.17224 44.02383 37.58295 0 1 0 - 609 176 14 0.417 41.46027 44.26142 39.05008 0 1 0 - 610 177 13 -0.834 61.41261 58.14241 37.49312 -2 0 0 - 611 177 14 0.417 61.24368 59.06676 37.67551 -2 0 0 - 612 177 14 0.417 60.57871 57.80631 37.16465 -2 0 0 - 613 178 13 -0.834 48.58355 55.60536 32.34542 0 -2 -2 - 614 178 14 0.417 48.05292 55.64371 31.54969 0 -2 -2 - 615 178 14 0.417 49.00004 56.46561 32.39784 0 -2 -2 - 616 179 13 -0.834 51.18618 52.33768 44.26866 0 -1 0 - 617 179 14 0.417 50.47419 52.97535 44.21659 0 -1 0 - 618 179 14 0.417 51.18053 51.90159 43.41657 0 -1 0 - 619 180 13 -0.834 63.77008 46.64985 53.45124 -2 0 -1 - 620 180 14 0.417 37.25943 46.94040 53.14955 -1 0 -1 - 621 180 14 0.417 63.15834 47.28506 53.07904 -2 0 -1 - 622 181 13 -0.834 37.28071 56.79400 31.30862 1 1 0 - 623 181 14 0.417 37.34297 57.68998 31.63963 1 1 0 - 624 181 14 0.417 36.99543 56.89301 30.40030 1 1 0 - 625 182 13 -0.834 38.98742 57.66608 44.07685 1 0 1 - 626 182 14 0.417 39.04152 57.61214 43.12270 1 0 1 - 627 182 14 0.417 39.46043 56.89430 44.38805 1 0 1 - 628 183 13 -0.834 64.13749 51.25767 48.28997 0 -1 0 - 629 183 14 0.417 64.05120 52.19840 48.13566 0 -1 0 - 630 183 14 0.417 63.26932 50.90255 48.09918 0 -1 0 - 631 184 13 -0.834 41.02949 42.14202 43.02064 0 0 -1 - 632 184 14 0.417 40.60130 42.82178 43.54104 0 0 -1 - 633 184 14 0.417 40.43829 41.99723 42.28189 0 0 -1 - 634 185 13 -0.834 49.87332 48.21836 52.83028 0 1 0 - 635 185 14 0.417 49.13733 48.15035 53.43849 0 1 0 - 636 185 14 0.417 50.32176 47.37567 52.90100 0 1 0 - 637 186 13 -0.834 56.06860 48.51217 38.12813 -1 1 0 - 638 186 14 0.417 56.55702 47.73454 38.39826 -1 1 0 - 639 186 14 0.417 55.52690 48.21357 37.39762 -1 1 0 - 640 187 13 -0.834 54.22718 59.47740 40.22374 -1 0 1 - 641 187 14 0.417 53.93839 59.03820 39.42377 -1 0 1 - 642 187 14 0.417 54.74005 58.81629 40.68868 -1 0 1 - 643 188 13 -0.834 60.09461 46.88146 32.04739 -1 0 -1 - 644 188 14 0.417 60.91535 46.43611 31.83683 -1 0 -1 - 645 188 14 0.417 60.13630 47.02716 32.99253 -1 0 -1 - 646 189 13 -0.834 45.18646 44.57845 41.54076 0 0 0 - 647 189 14 0.417 44.28239 44.89208 41.51774 0 0 0 - 648 189 14 0.417 45.34481 44.23786 40.66033 0 0 0 - 649 190 13 -0.834 42.47099 45.68692 31.56356 1 0 1 - 650 190 14 0.417 43.26152 45.18821 31.76995 1 0 1 - 651 190 14 0.417 42.78187 46.58070 31.41951 1 0 1 - 652 191 13 -0.834 41.23413 47.67043 41.85221 0 1 0 - 653 191 14 0.417 41.04508 48.58329 42.06946 0 1 0 - 654 191 14 0.417 40.84394 47.54379 40.98737 0 1 0 - 655 192 13 -0.834 48.84750 60.39708 36.57115 0 0 0 - 656 192 14 0.417 48.57626 59.48478 36.46920 0 0 0 - 657 192 14 0.417 48.59448 60.62409 37.46597 0 0 0 - 658 193 13 -0.834 56.78263 43.55464 49.12966 -1 0 -1 - 659 193 14 0.417 56.56851 44.25428 48.51250 -1 0 -1 - 660 193 14 0.417 57.66563 43.76469 49.43365 -1 0 -1 - 661 194 13 -0.834 59.52236 53.66894 43.24587 -1 2 0 - 662 194 14 0.417 59.44365 54.61174 43.10041 -1 2 0 - 663 194 14 0.417 59.73284 53.58637 44.17598 -1 2 0 - 664 195 13 -0.834 63.61393 61.54696 40.57053 -1 -1 1 - 665 195 14 0.417 36.90989 60.94398 40.24291 0 -1 1 - 666 195 14 0.417 63.74510 61.55794 41.51864 -1 -1 1 - 667 196 13 -0.834 54.91742 43.16160 33.69639 0 0 -1 - 668 196 14 0.417 55.84062 43.16106 33.94925 0 0 -1 - 669 196 14 0.417 54.73416 44.07060 33.45898 0 0 -1 - 670 197 13 -0.834 41.09699 64.92982 48.38401 0 -1 -1 - 671 197 14 0.417 40.19042 64.83711 48.67687 0 -1 -1 - 672 197 14 0.417 41.27055 64.13206 47.88433 0 -1 -1 - 673 198 13 -0.834 49.09688 60.43369 49.80048 0 0 -1 - 674 198 14 0.417 49.75346 61.03633 50.14971 0 0 -1 - 675 198 14 0.417 49.51718 59.57440 49.83534 0 0 -1 - 676 199 13 -0.834 45.06873 45.25146 44.50830 0 1 0 - 677 199 14 0.417 45.08807 45.11881 43.56053 0 1 0 - 678 199 14 0.417 44.41198 44.63084 44.82413 0 1 0 - 679 200 13 -0.834 37.63886 45.88962 36.45768 0 0 2 - 680 200 14 0.417 38.32892 45.23766 36.58017 0 0 2 - 681 200 14 0.417 37.24627 45.98938 37.32495 0 0 2 - 682 201 13 -0.834 45.25770 47.01692 51.04211 -1 0 -2 - 683 201 14 0.417 45.49830 47.82868 50.59555 -1 0 -2 - 684 201 14 0.417 46.08295 46.68269 51.39354 -1 0 -2 - 685 202 13 -0.834 63.44567 60.77839 50.98507 -2 0 0 - 686 202 14 0.417 62.95029 60.46072 51.74001 -2 0 0 - 687 202 14 0.417 62.77774 61.08133 50.36998 -2 0 0 - 688 203 13 -0.834 48.00038 59.99003 33.31045 0 1 1 - 689 203 14 0.417 48.92391 59.89924 33.54518 0 1 1 - 690 203 14 0.417 47.68314 60.70831 33.85788 0 1 1 - 691 204 13 -0.834 51.29617 53.45952 36.10138 -1 -1 1 - 692 204 14 0.417 50.79623 53.20605 36.87731 -1 -1 1 - 693 204 14 0.417 51.41983 54.40421 36.19363 -1 -1 1 - 694 205 13 -0.834 48.55343 45.13540 34.47517 0 0 0 - 695 205 14 0.417 48.10547 45.97105 34.34382 0 0 0 - 696 205 14 0.417 49.13373 45.28879 35.22081 0 0 0 - 697 206 13 -0.834 48.34844 61.02741 54.77908 1 -1 -1 - 698 206 14 0.417 47.77364 61.75290 55.02301 1 -1 -1 - 699 206 14 0.417 49.14675 61.17253 55.28690 1 -1 -1 - 700 207 13 -0.834 38.97661 48.73541 31.27301 2 -1 0 - 701 207 14 0.417 38.86774 47.99634 30.67453 2 -1 0 - 702 207 14 0.417 38.60214 49.48112 30.80404 2 -1 0 - 703 208 13 -0.834 56.37687 61.69299 40.12439 0 -1 -1 - 704 208 14 0.417 56.35009 61.71409 39.16778 0 -1 -1 - 705 208 14 0.417 55.62486 61.15580 40.37371 0 -1 -1 - 706 209 13 -0.834 47.86700 41.38854 36.76722 -1 0 0 - 707 209 14 0.417 48.79854 41.26117 36.94678 -1 0 0 - 708 209 14 0.417 47.57553 42.00602 37.43804 -1 0 0 - 709 210 13 -0.834 43.22089 60.92576 39.48904 -1 -1 0 - 710 210 14 0.417 42.70029 60.20976 39.85311 -1 -1 0 - 711 210 14 0.417 43.25319 60.74538 38.54954 -1 -1 0 - 712 211 13 -0.834 56.26248 49.03317 34.29585 -1 0 0 - 713 211 14 0.417 56.69244 49.86416 34.09381 -1 0 0 - 714 211 14 0.417 55.61194 48.92467 33.60212 -1 0 0 - 715 212 13 -0.834 47.52063 49.37901 51.21673 1 0 0 - 716 212 14 0.417 48.35964 48.95385 51.03909 1 0 0 - 717 212 14 0.417 47.47856 49.43746 52.17122 1 0 0 - 718 213 13 -0.834 62.35532 56.31018 41.33556 0 0 0 - 719 213 14 0.417 62.07506 57.22150 41.42032 0 0 0 - 720 213 14 0.417 62.92184 56.16192 42.09274 0 0 0 - 721 214 13 -0.834 61.09797 64.53756 45.11003 -1 0 1 - 722 214 14 0.417 61.11801 63.59600 44.93887 -1 0 1 - 723 214 14 0.417 61.95676 64.85132 44.82670 -1 0 1 - 724 215 13 -0.834 51.22661 62.08872 31.93454 0 0 0 - 725 215 14 0.417 51.98994 62.65586 32.04369 0 0 0 - 726 215 14 0.417 50.47877 62.65171 32.13456 0 0 0 - 727 216 13 -0.834 40.65443 48.64853 54.43476 0 0 -1 - 728 216 14 0.417 40.25608 47.97845 54.99023 0 0 -1 - 729 216 14 0.417 41.58025 48.64240 54.67776 0 0 -1 - 730 217 13 -0.834 39.34873 63.07587 52.07209 1 1 -1 - 731 217 14 0.417 39.17266 63.98076 51.81438 1 1 -1 - 732 217 14 0.417 39.29792 62.57948 51.25523 1 1 -1 - 733 218 13 -0.834 45.66307 65.90840 47.75613 -1 0 0 - 734 218 14 0.417 44.99427 65.52542 48.32381 -1 0 0 - 735 218 14 0.417 45.75913 66.80721 48.07102 -1 0 0 - 736 219 13 -0.834 45.83158 51.91442 38.93974 0 0 0 - 737 219 14 0.417 46.07939 51.87422 39.86344 0 0 0 - 738 219 14 0.417 45.49928 51.03877 38.74210 0 0 0 - 739 220 13 -0.834 58.03934 67.88594 44.36036 -1 1 -1 - 740 220 14 0.417 58.69084 68.22520 43.74661 -1 1 -1 - 741 220 14 0.417 58.24719 68.31309 45.19138 -1 1 -1 - 742 221 13 -0.834 57.23319 66.95459 30.42832 0 0 0 - 743 221 14 0.417 56.95316 66.93560 31.34345 0 0 0 - 744 221 14 0.417 58.18154 66.82998 30.46491 0 0 0 - 745 222 13 -0.834 60.87005 44.72970 53.74755 -1 0 -1 - 746 222 14 0.417 60.02694 44.42275 53.41412 -1 0 -1 - 747 222 14 0.417 61.31963 45.07903 52.97808 -1 0 -1 - 748 223 13 -0.834 50.61352 50.44308 31.66369 0 -1 0 - 749 223 14 0.417 50.38691 49.95555 30.87173 0 -1 0 - 750 223 14 0.417 50.16704 51.28387 31.56391 0 -1 0 - 751 224 13 -0.834 42.70363 42.07925 34.73823 0 1 0 - 752 224 14 0.417 42.74630 41.15512 34.49249 0 1 0 - 753 224 14 0.417 41.77538 42.23983 34.90796 0 1 0 - 754 225 13 -0.834 50.34157 43.80796 44.49841 -1 1 0 - 755 225 14 0.417 49.44649 44.14718 44.50119 -1 1 0 - 756 225 14 0.417 50.24323 42.86994 44.66171 -1 1 0 - 757 226 13 -0.834 62.39528 64.92163 33.72829 -3 -1 1 - 758 226 14 0.417 61.94679 64.42233 34.41078 -3 -1 1 - 759 226 14 0.417 61.94061 64.68505 32.91986 -3 -1 1 - 760 227 13 -0.834 46.62188 47.13429 41.79430 0 1 1 - 761 227 14 0.417 46.21721 46.28415 41.62178 0 1 1 - 762 227 14 0.417 47.40198 46.92861 42.30946 0 1 1 - 763 228 13 -0.834 41.35469 54.31275 56.45453 0 0 -1 - 764 228 14 0.417 41.79769 53.47653 56.31055 0 0 -1 - 765 228 14 0.417 40.57273 54.26794 55.90425 0 0 -1 - 766 229 13 -0.834 48.43878 42.20000 49.94999 0 0 0 - 767 229 14 0.417 49.34431 42.29756 50.24447 0 0 0 - 768 229 14 0.417 48.41583 42.63350 49.09688 0 0 0 - 769 230 13 -0.834 37.29829 50.04209 33.34795 0 1 0 - 770 230 14 0.417 36.96213 49.51969 34.07619 0 1 0 - 771 230 14 0.417 37.98470 49.49933 32.96002 0 1 0 - 772 231 13 -0.834 58.91995 56.17895 33.02333 -1 0 0 - 773 231 14 0.417 59.83980 56.43785 32.96791 -1 0 0 - 774 231 14 0.417 58.89269 55.54120 33.73661 -1 0 0 - 775 232 13 -0.834 39.86900 65.81481 43.81866 0 0 -1 - 776 232 14 0.417 40.31483 64.99515 43.60502 0 0 -1 - 777 232 14 0.417 40.41298 66.21397 44.49762 0 0 -1 - 778 233 13 -0.834 62.71324 65.93556 51.55400 -1 0 0 - 779 233 14 0.417 62.38032 66.39597 52.32436 -1 0 0 - 780 233 14 0.417 63.52336 65.52245 51.85285 -1 0 0 - 781 234 13 -0.834 59.23324 49.58642 31.35843 0 0 0 - 782 234 14 0.417 59.28102 48.68976 31.69001 0 0 0 - 783 234 14 0.417 59.95115 50.04304 31.79700 0 0 0 - 784 235 13 -0.834 41.02310 67.21389 51.60243 0 0 0 - 785 235 14 0.417 41.77450 67.79064 51.74021 0 0 0 - 786 235 14 0.417 40.36922 67.76899 51.17753 0 0 0 - 787 236 13 -0.834 41.38918 62.43794 34.42449 0 0 1 - 788 236 14 0.417 41.26665 63.14612 33.79227 0 0 1 - 789 236 14 0.417 42.30454 62.51275 34.69423 0 0 1 - 790 237 13 -0.834 52.28796 56.01034 50.59905 0 -1 -1 - 791 237 14 0.417 53.14113 56.07317 51.02851 0 -1 -1 - 792 237 14 0.417 52.14509 55.07070 50.48548 0 -1 -1 - 793 238 13 -0.834 53.25204 66.52198 39.76351 0 -1 0 - 794 238 14 0.417 52.30774 66.44732 39.62571 0 -1 0 - 795 238 14 0.417 53.47725 67.38617 39.41895 0 -1 0 - 796 239 13 -0.834 59.77604 60.82055 48.12264 -1 -1 -1 - 797 239 14 0.417 59.80699 60.05926 48.70205 -1 -1 -1 - 798 239 14 0.417 58.96049 60.71611 47.63253 -1 -1 -1 - 799 240 13 -0.834 48.99693 51.07559 36.89084 0 -1 1 - 800 240 14 0.417 48.22315 50.55308 37.10175 0 -1 1 - 801 240 14 0.417 48.88824 51.30348 35.96753 0 -1 1 - 802 241 13 -0.834 50.67863 62.63916 55.60559 1 0 -2 - 803 241 14 0.417 51.43406 62.16856 55.25331 1 0 -2 - 804 241 14 0.417 51.05760 63.36945 56.09477 1 0 -2 - 805 242 13 -0.834 41.05301 64.77947 55.72335 1 -1 -1 - 806 242 14 0.417 41.95836 64.58666 55.96711 1 -1 -1 - 807 242 14 0.417 41.07998 65.67647 55.39035 1 -1 -1 - 808 243 13 -0.834 59.16096 63.30207 34.55147 0 -1 2 - 809 243 14 0.417 58.62636 62.51316 34.64131 0 -1 2 - 810 243 14 0.417 59.80830 63.23451 35.25333 0 -1 2 - 811 244 13 -0.834 59.86542 53.52546 55.50419 0 -1 -1 - 812 244 14 0.417 60.26921 53.79963 56.32761 0 -1 -1 - 813 244 14 0.417 58.96256 53.83773 55.56399 0 -1 -1 - 814 245 13 -0.834 56.48528 44.99075 44.65443 1 0 0 - 815 245 14 0.417 55.84854 44.49932 44.13551 1 0 0 - 816 245 14 0.417 57.18258 45.20803 44.03571 1 0 0 - 817 246 13 -0.834 37.25407 54.85866 36.86076 0 -1 -1 - 818 246 14 0.417 37.37951 55.31820 36.03050 0 -1 -1 - 819 246 14 0.417 36.91899 55.52805 37.45731 0 -1 -1 - 820 247 13 -0.834 54.42875 47.21339 48.23883 -1 -1 -1 - 821 247 14 0.417 54.60966 48.13349 48.43097 -1 -1 -1 - 822 247 14 0.417 54.44092 47.16092 47.28312 -1 -1 -1 - 823 248 13 -0.834 42.61226 41.78391 40.84493 1 0 1 - 824 248 14 0.417 41.98531 41.90233 41.55849 1 0 1 - 825 248 14 0.417 42.35866 42.43623 40.19194 1 0 1 - 826 249 13 -0.834 37.83522 41.95649 50.31377 0 0 -2 - 827 249 14 0.417 37.42231 42.81133 50.19124 0 0 -2 - 828 249 14 0.417 37.46684 41.41031 49.61934 0 0 -2 - 829 250 13 -0.834 44.80898 44.15062 49.20688 0 -1 0 - 830 250 14 0.417 44.80289 44.55594 48.33975 0 -1 0 - 831 250 14 0.417 45.29722 44.76463 49.75537 0 -1 0 - 832 251 13 -0.834 37.44321 44.03405 38.75076 1 0 1 - 833 251 14 0.417 37.12277 44.06014 39.65235 1 0 1 - 834 251 14 0.417 64.13547 43.56266 38.26824 0 0 1 - 835 252 13 -0.834 38.82113 46.15070 46.12915 1 0 0 - 836 252 14 0.417 38.96657 46.44867 47.02709 1 0 0 - 837 252 14 0.417 38.09796 45.52731 46.19733 1 0 0 - 838 253 13 -0.834 43.08482 60.65520 45.34135 -1 0 1 - 839 253 14 0.417 42.82882 59.73347 45.30784 -1 0 1 - 840 253 14 0.417 44.00885 60.65685 45.09147 -1 0 1 - 841 254 13 -0.834 45.72190 46.51173 32.51384 1 0 0 - 842 254 14 0.417 46.00925 45.78294 31.96381 1 0 0 - 843 254 14 0.417 46.53186 46.95248 32.77064 1 0 0 - 844 255 13 -0.834 63.64359 44.33728 41.24417 -1 0 0 - 845 255 14 0.417 63.60411 43.61794 41.87443 -1 0 0 - 846 255 14 0.417 62.76926 44.36407 40.85550 -1 0 0 - 847 256 13 -0.834 48.53353 66.27879 51.60437 0 0 -1 - 848 256 14 0.417 49.21611 66.24938 50.93396 0 0 -1 - 849 256 14 0.417 48.67507 65.48862 52.12577 0 0 -1 - 850 257 13 -0.834 54.11962 54.32751 39.83526 -1 1 1 - 851 257 14 0.417 53.37975 54.47391 39.24585 -1 1 1 - 852 257 14 0.417 53.95747 53.46346 40.21391 -1 1 1 - 853 258 13 -0.834 53.72785 66.08707 44.78384 -1 -1 0 - 854 258 14 0.417 54.65423 65.85662 44.85413 -1 -1 0 - 855 258 14 0.417 53.26300 65.26936 44.96130 -1 -1 0 - 856 259 13 -0.834 39.06287 51.40870 53.96063 0 0 -1 - 857 259 14 0.417 39.12854 51.34243 53.00796 0 0 -1 - 858 259 14 0.417 38.38057 52.06341 54.10916 0 0 -1 - 859 260 13 -0.834 58.77064 49.77012 37.45292 0 0 0 - 860 260 14 0.417 59.49652 49.20688 37.72142 0 0 0 - 861 260 14 0.417 57.98575 49.25379 37.63621 0 0 0 - 862 261 13 -0.834 37.94204 48.36591 35.22049 -1 0 0 - 863 261 14 0.417 37.94000 47.48368 35.59187 -1 0 0 - 864 261 14 0.417 38.86901 48.59216 35.14453 -1 0 0 - 865 262 13 -0.834 47.05754 54.06564 40.63628 0 -2 1 - 866 262 14 0.417 47.01965 53.22193 41.08679 0 -2 1 - 867 262 14 0.417 46.68660 54.68838 41.26145 0 -2 1 - 868 263 13 -0.834 46.01283 65.88108 53.59469 0 0 0 - 869 263 14 0.417 45.30729 66.50296 53.77277 0 0 0 - 870 263 14 0.417 46.76378 66.42902 53.36650 0 0 0 - 871 264 13 -0.834 45.32546 67.91008 39.11365 -1 -1 0 - 872 264 14 0.417 44.38981 67.96233 38.91853 -1 -1 0 - 873 264 14 0.417 45.70517 67.47097 38.35257 -1 -1 0 - 874 265 13 -0.834 55.39761 51.53823 53.16553 -1 1 -1 - 875 265 14 0.417 54.64975 52.10179 53.36389 -1 1 -1 - 876 265 14 0.417 55.78119 51.91789 52.37499 -1 1 -1 - 877 266 13 -0.834 57.06415 51.22923 32.75117 -1 -1 0 - 878 266 14 0.417 56.79908 52.11139 32.49079 -1 -1 0 - 879 266 14 0.417 57.98399 51.16910 32.49322 -1 -1 0 - 880 267 13 -0.834 50.05222 47.30342 45.67457 0 0 -2 - 881 267 14 0.417 49.85957 46.82324 46.47990 0 0 -2 - 882 267 14 0.417 50.60617 46.70964 45.16781 0 0 -2 - 883 268 13 -0.834 50.46819 45.47822 52.51129 0 1 -1 - 884 268 14 0.417 50.78823 45.07196 53.31677 0 1 -1 - 885 268 14 0.417 51.03886 45.13243 51.82499 0 1 -1 - 886 269 13 -0.834 47.44130 61.30175 47.80124 0 0 0 - 887 269 14 0.417 48.02715 60.89314 48.43850 0 0 0 - 888 269 14 0.417 47.98636 61.43626 47.02595 0 0 0 - 889 270 13 -0.834 41.31630 52.47434 39.71677 1 0 0 - 890 270 14 0.417 41.07609 52.94514 40.51485 1 0 0 - 891 270 14 0.417 42.05418 52.96849 39.35955 1 0 0 - 892 271 13 -0.834 55.90762 58.63213 50.47814 0 1 0 - 893 271 14 0.417 55.80273 59.37784 51.06903 0 1 0 - 894 271 14 0.417 55.41449 58.87554 49.69468 0 1 0 - 895 272 13 -0.834 42.23424 55.62725 53.35280 0 1 -1 - 896 272 14 0.417 41.62946 55.10926 53.88399 0 1 -1 - 897 272 14 0.417 41.75761 56.43615 53.16647 0 1 -1 - 898 273 13 -0.834 62.31754 63.97065 42.48774 0 0 1 - 899 273 14 0.417 63.27023 64.05391 42.44669 0 0 1 - 900 273 14 0.417 62.16851 63.13573 42.93152 0 0 1 - 901 274 13 -0.834 60.93154 49.79182 56.13812 0 -1 0 - 902 274 14 0.417 61.38991 48.97402 56.33134 0 -1 0 - 903 274 14 0.417 60.29808 49.88575 56.84955 0 -1 0 - 904 275 13 -0.834 50.39572 45.11274 36.60756 0 1 -1 - 905 275 14 0.417 50.88541 44.33834 36.33051 0 1 -1 - 906 275 14 0.417 50.38352 45.05976 37.56322 0 1 -1 - 907 276 13 -0.834 46.57204 43.12189 39.29488 -1 2 -1 - 908 276 14 0.417 46.48449 42.17951 39.43813 -1 2 -1 - 909 276 14 0.417 47.49357 43.30747 39.47547 -1 2 -1 - 910 277 13 -0.834 54.39979 41.37518 38.62483 0 0 1 - 911 277 14 0.417 54.27469 42.27221 38.31511 0 0 1 - 912 277 14 0.417 54.57135 68.24024 37.83080 0 -1 1 - 913 278 13 -0.834 60.57638 52.40343 41.12327 -1 1 -1 - 914 278 14 0.417 60.40196 53.27982 40.78010 -1 1 -1 - 915 278 14 0.417 60.37657 52.46726 42.05721 -1 1 -1 - 916 279 13 -0.834 61.77806 59.06524 41.98029 0 0 0 - 917 279 14 0.417 62.58317 59.36537 42.40214 0 0 0 - 918 279 14 0.417 61.10430 59.16112 42.65342 0 0 0 - 919 280 13 -0.834 43.46789 48.64833 54.88223 0 1 -2 - 920 280 14 0.417 43.60676 49.48200 54.43286 0 1 -2 - 921 280 14 0.417 43.74339 47.98554 54.24895 0 1 -2 - 922 281 13 -0.834 51.98628 58.37454 48.60562 -1 0 0 - 923 281 14 0.417 51.81372 57.54909 49.05852 -1 0 0 - 924 281 14 0.417 52.67545 58.16319 47.97583 -1 0 0 - 925 282 13 -0.834 55.00551 65.64176 56.63926 0 -1 -1 - 926 282 14 0.417 55.59134 66.11131 29.86167 0 -1 0 - 927 282 14 0.417 54.80211 66.27584 55.95165 0 -1 -1 - 928 283 13 -0.834 55.02996 52.59142 50.59986 -1 1 0 - 929 283 14 0.417 54.13615 52.66743 50.26585 -1 1 0 - 930 283 14 0.417 55.48513 53.35419 50.24316 -1 1 0 - 931 284 13 -0.834 37.39245 67.88600 56.81733 0 -1 -1 - 932 284 14 0.417 38.13326 41.09044 56.62787 0 0 -1 - 933 284 14 0.417 37.74351 67.00148 56.71419 0 -1 -1 - 934 285 13 -0.834 42.83234 60.22766 53.36959 0 0 0 - 935 285 14 0.417 43.51497 59.86233 52.80672 0 0 0 - 936 285 14 0.417 43.27782 60.90528 53.87815 0 0 0 - 937 286 13 -0.834 59.24806 43.81265 38.44265 1 0 0 - 938 286 14 0.417 59.12140 43.55748 39.35647 1 0 0 - 939 286 14 0.417 60.07673 44.29174 38.43991 1 0 0 - 940 287 13 -0.834 61.29263 60.52642 52.74164 -1 1 -1 - 941 287 14 0.417 61.73918 60.02180 53.42149 -1 1 -1 - 942 287 14 0.417 60.93759 61.28711 53.20156 -1 1 -1 - 943 288 13 -0.834 63.43980 43.30119 30.90384 -1 1 0 - 944 288 14 0.417 63.34979 42.36405 30.73085 -1 1 0 - 945 288 14 0.417 64.20504 43.56693 30.39393 -1 1 0 - 946 289 13 -0.834 57.11924 59.06522 54.48909 -1 0 0 - 947 289 14 0.417 57.40605 59.83488 54.98062 -1 0 0 - 948 289 14 0.417 57.59698 58.33614 54.88463 -1 0 0 - 949 290 13 -0.834 51.89759 59.82680 44.82923 1 1 -1 - 950 290 14 0.417 51.33588 59.94068 44.06258 1 1 -1 - 951 290 14 0.417 51.32846 60.01914 45.57443 1 1 -1 - 952 291 13 -0.834 57.64696 65.49112 47.86068 -1 0 0 - 953 291 14 0.417 57.31105 65.98457 48.60895 -1 0 0 - 954 291 14 0.417 57.73765 64.59519 48.18521 -1 0 0 - 955 292 13 -0.834 50.35232 57.73892 32.55459 0 1 0 - 956 292 14 0.417 51.07441 57.69034 31.92813 0 1 0 - 957 292 14 0.417 50.48339 58.57180 33.00777 0 1 0 - 958 293 13 -0.834 46.20166 60.82812 38.38269 0 1 1 - 959 293 14 0.417 46.12191 61.76977 38.53504 0 1 1 - 960 293 14 0.417 45.30555 60.53505 38.21735 0 1 1 - 961 294 13 -0.834 41.42660 51.46433 55.94150 1 0 -1 - 962 294 14 0.417 40.58025 51.71240 55.56944 1 0 -1 - 963 294 14 0.417 41.63094 50.62307 55.53311 1 0 -1 - 964 295 13 -0.834 56.72642 53.95840 32.00323 0 -1 0 - 965 295 14 0.417 57.12177 54.49254 32.69216 0 -1 0 - 966 295 14 0.417 55.80349 54.21231 32.00259 0 -1 0 - 967 296 13 -0.834 43.25852 41.40642 31.27656 0 1 0 - 968 296 14 0.417 43.58058 42.21308 31.67880 0 1 0 - 969 296 14 0.417 43.16985 68.16459 32.00619 0 0 0 - 970 297 13 -0.834 54.50477 52.62435 30.30235 -2 1 0 - 971 297 14 0.417 54.04985 52.22243 31.04245 -2 1 0 - 972 297 14 0.417 54.36900 53.56465 30.41915 -2 1 0 - 973 298 13 -0.834 38.11258 59.33341 36.21749 1 0 0 - 974 298 14 0.417 38.95754 58.91929 36.04205 1 0 0 - 975 298 14 0.417 38.14750 60.16192 35.73940 1 0 0 - 976 299 13 -0.834 39.65020 64.70254 40.48616 -1 0 1 - 977 299 14 0.417 39.87581 65.58596 40.19474 -1 0 1 - 978 299 14 0.417 39.66086 64.17611 39.68676 -1 0 1 - 979 300 13 -0.834 63.26661 53.84973 48.10281 -1 1 1 - 980 300 14 0.417 63.38261 54.75210 48.40032 -1 1 1 - 981 300 14 0.417 62.32830 53.68505 48.19603 -1 1 1 - 982 301 13 -0.834 43.65966 61.04202 50.03088 0 0 0 - 983 301 14 0.417 44.11377 60.35973 50.52538 0 0 0 - 984 301 14 0.417 44.30508 61.74317 49.94108 0 0 0 - 985 302 13 -0.834 61.75204 50.20037 32.39414 0 0 0 - 986 302 14 0.417 62.04749 51.09027 32.58663 0 0 0 - 987 302 14 0.417 62.55370 49.67736 32.38826 0 0 0 - 988 303 13 -0.834 53.79071 58.98335 36.25336 -1 -2 -1 - 989 303 14 0.417 53.17711 58.26833 36.42220 -1 -2 -1 - 990 303 14 0.417 54.65389 58.60140 36.41235 -1 -2 -1 - 991 304 13 -0.834 50.47963 50.13918 42.58243 1 -1 -2 - 992 304 14 0.417 51.28111 49.63880 42.42915 1 -1 -2 - 993 304 14 0.417 50.33279 50.61369 41.76419 1 -1 -2 - 994 305 13 -0.834 50.28770 49.02182 56.79391 1 -1 -2 - 995 305 14 0.417 50.66164 48.14920 56.91622 1 -1 -2 - 996 305 14 0.417 50.60501 49.30063 55.93493 1 -1 -2 - 997 306 13 -0.834 41.36930 46.36343 34.87469 1 1 0 - 998 306 14 0.417 42.25704 46.59841 34.60463 1 1 0 - 999 306 14 0.417 40.85961 47.16333 34.74582 1 1 0 - 1000 307 13 -0.834 61.15349 47.47016 41.71779 0 1 0 - 1001 307 14 0.417 61.50139 48.29469 41.37818 0 1 0 - 1002 307 14 0.417 60.28203 47.69385 42.04454 0 1 0 - 1003 308 13 -0.834 58.35337 46.83622 34.81712 0 0 1 - 1004 308 14 0.417 57.63221 46.22391 34.67141 0 0 1 - 1005 308 14 0.417 57.97297 47.69883 34.65146 0 0 1 - 1006 309 13 -0.834 38.79812 57.92803 48.26323 1 -2 -1 - 1007 309 14 0.417 38.67444 56.98130 48.33141 1 -2 -1 - 1008 309 14 0.417 39.70990 58.06987 48.51776 1 -2 -1 - 1009 310 13 -0.834 42.15963 57.96891 45.03230 1 0 0 - 1010 310 14 0.417 42.11698 57.98663 45.98839 1 0 0 - 1011 310 14 0.417 41.83611 57.10021 44.79371 1 0 0 - 1012 311 13 -0.834 55.17551 54.72671 36.49400 0 -1 0 - 1013 311 14 0.417 55.26386 53.77738 36.57890 0 -1 0 - 1014 311 14 0.417 55.36463 55.06457 37.36939 0 -1 0 - 1015 312 13 -0.834 58.64573 63.28550 41.10609 -1 -2 -1 - 1016 312 14 0.417 58.98147 62.66636 41.75429 -1 -2 -1 - 1017 312 14 0.417 57.90273 62.83419 40.70545 -1 -2 -1 - 1018 313 13 -0.834 49.96498 59.98797 42.54359 0 -1 0 - 1019 313 14 0.417 50.57886 60.48612 42.00390 0 -1 0 - 1020 313 14 0.417 49.10600 60.17526 42.16501 0 -1 0 - 1021 314 13 -0.834 57.54750 44.35075 52.12722 -1 -1 -1 - 1022 314 14 0.417 57.86221 43.84739 51.37633 -1 -1 -1 - 1023 314 14 0.417 56.76423 44.79718 51.80558 -1 -1 -1 - 1024 315 13 -0.834 58.07892 59.46258 41.31930 1 -1 0 - 1025 315 14 0.417 58.27344 60.10968 41.99729 1 -1 0 - 1026 315 14 0.417 57.80524 59.98199 40.56328 1 -1 0 - 1027 316 13 -0.834 42.21869 44.49848 55.65511 2 1 0 - 1028 316 14 0.417 42.77458 44.78017 56.38166 2 1 0 - 1029 316 14 0.417 42.83052 44.15513 55.00395 2 1 0 - 1030 317 13 -0.834 56.38334 63.45614 43.52622 -1 -1 0 - 1031 317 14 0.417 55.66283 63.62998 42.92052 -1 -1 0 - 1032 317 14 0.417 56.48976 64.27319 44.01338 -1 -1 0 - 1033 318 13 -0.834 43.21354 46.04700 52.52965 1 1 0 - 1034 318 14 0.417 43.24360 45.09879 52.40226 1 1 0 - 1035 318 14 0.417 43.99839 46.37328 52.08943 1 1 0 - 1036 319 13 -0.834 55.96174 45.94863 35.39660 -1 0 1 - 1037 319 14 0.417 55.64687 46.44680 36.15088 -1 0 1 - 1038 319 14 0.417 55.28305 46.06527 34.73174 -1 0 1 - 1039 320 13 -0.834 47.36406 54.82690 34.84439 -1 -1 2 - 1040 320 14 0.417 47.90093 54.86776 34.05295 -1 -1 2 - 1041 320 14 0.417 47.23152 53.89118 34.99640 -1 -1 2 - 1042 321 13 -0.834 49.62685 50.00229 45.27362 1 0 -2 - 1043 321 14 0.417 49.70876 49.05477 45.38192 1 0 -2 - 1044 321 14 0.417 49.82566 50.15634 44.35005 1 0 -2 - 1045 322 13 -0.834 49.58249 46.02940 55.43310 -1 0 -2 - 1046 322 14 0.417 49.10378 46.80060 55.12924 -1 0 -2 - 1047 322 14 0.417 49.31802 45.92761 56.34739 -1 0 -2 - 1048 323 13 -0.834 51.72150 51.53491 51.55558 0 -1 -1 - 1049 323 14 0.417 51.50292 52.17946 50.88251 0 -1 -1 - 1050 323 14 0.417 52.14568 52.04382 52.24646 0 -1 -1 - 1051 324 13 -0.834 37.98107 56.66338 52.98024 0 1 0 - 1052 324 14 0.417 37.64467 57.53823 52.78607 0 1 0 - 1053 324 14 0.417 38.15999 56.27913 52.12200 0 1 0 - 1054 325 13 -0.834 59.20226 51.55233 53.16877 -1 1 0 - 1055 325 14 0.417 59.68851 51.88535 53.92302 -1 1 0 - 1056 325 14 0.417 58.63621 50.87031 53.53025 -1 1 0 - 1057 326 13 -0.834 45.75783 63.62117 39.24032 1 1 -1 - 1058 326 14 0.417 46.25179 64.38626 39.53508 1 1 -1 - 1059 326 14 0.417 44.85376 63.80686 39.49409 1 1 -1 - 1060 327 13 -0.834 58.00953 52.38584 37.67148 -1 1 1 - 1061 327 14 0.417 58.24242 51.47235 37.50553 -1 1 1 - 1062 327 14 0.417 57.26453 52.33853 38.27062 -1 1 1 - 1063 328 13 -0.834 50.62838 66.20855 42.36072 0 0 -1 - 1064 328 14 0.417 51.45434 66.68250 42.45770 0 0 -1 - 1065 328 14 0.417 49.99531 66.87945 42.10506 0 0 -1 - 1066 329 13 -0.834 53.69444 52.39171 45.41982 1 0 0 - 1067 329 14 0.417 53.84961 51.45739 45.55855 1 0 0 - 1068 329 14 0.417 52.75879 52.45359 45.22750 1 0 0 - 1069 330 13 -0.834 38.34038 60.92162 30.12773 2 0 0 - 1070 330 14 0.417 39.08908 61.47644 29.90887 2 0 0 - 1071 330 14 0.417 38.64185 60.39196 30.86585 2 0 0 - 1072 331 13 -0.834 48.03336 64.84935 43.13262 -1 0 -2 - 1073 331 14 0.417 48.90813 65.00919 43.48682 -1 0 -2 - 1074 331 14 0.417 47.46214 65.43367 43.63114 -1 0 -2 - 1075 332 13 -0.834 39.68760 66.88962 36.60665 2 0 0 - 1076 332 14 0.417 38.74743 66.72116 36.66944 2 0 0 - 1077 332 14 0.417 40.05009 66.08888 36.22764 2 0 0 - 1078 333 13 -0.834 51.94118 65.49897 51.83197 0 -1 -2 - 1079 333 14 0.417 52.71282 65.06165 51.47204 0 -1 -2 - 1080 333 14 0.417 51.22446 64.88225 51.68297 0 -1 -2 - 1081 334 13 -0.834 43.33066 57.53264 55.09930 -1 0 -2 - 1082 334 14 0.417 43.05496 56.76932 54.59178 -1 0 -2 - 1083 334 14 0.417 44.28179 57.55937 54.99503 -1 0 -2 - 1084 335 13 -0.834 47.70128 45.69178 52.17773 -1 3 -1 - 1085 335 14 0.417 47.54566 44.86273 52.63016 -1 3 -1 - 1086 335 14 0.417 48.58530 45.94693 52.44163 -1 3 -1 - 1087 336 13 -0.834 58.71603 41.81571 40.73899 -1 0 0 - 1088 336 14 0.417 57.77048 41.84330 40.88539 -1 0 0 - 1089 336 14 0.417 58.81275 41.43332 39.86682 -1 0 0 - 1090 337 13 -0.834 57.56034 60.98533 43.60766 0 -1 0 - 1091 337 14 0.417 56.67639 60.61816 43.59917 0 -1 0 - 1092 337 14 0.417 57.42830 61.92611 43.72486 0 -1 0 - 1093 338 13 -0.834 44.68088 65.08579 34.27880 -1 0 2 - 1094 338 14 0.417 45.54678 65.09564 34.68668 -1 0 2 - 1095 338 14 0.417 44.45037 64.15818 34.22739 -1 0 2 - 1096 339 13 -0.834 54.98236 48.04093 42.26075 0 0 0 - 1097 339 14 0.417 55.16505 47.86552 43.18384 0 0 0 - 1098 339 14 0.417 55.70493 48.59999 41.97513 0 0 0 - 1099 340 13 -0.834 60.57099 56.88773 56.53671 0 0 1 - 1100 340 14 0.417 60.67151 56.21616 29.83998 0 0 2 - 1101 340 14 0.417 61.34465 56.78824 55.98192 0 0 1 - 1102 341 13 -0.834 48.05045 49.69974 47.93542 -1 0 0 - 1103 341 14 0.417 48.70922 49.23613 48.45249 -1 0 0 - 1104 341 14 0.417 48.26410 49.48583 47.02721 -1 0 0 - 1105 342 13 -0.834 40.63207 55.77589 49.21695 1 0 -1 - 1106 342 14 0.417 40.84917 56.26844 50.00847 1 0 -1 - 1107 342 14 0.417 41.40772 55.85904 48.66226 1 0 -1 - 1108 343 13 -0.834 61.66015 42.71355 39.91223 0 0 0 - 1109 343 14 0.417 61.87748 41.86774 40.30419 0 0 0 - 1110 343 14 0.417 61.98864 42.65380 39.01514 0 0 0 - 1111 344 13 -0.834 38.52157 65.12766 57.04010 0 -1 -1 - 1112 344 14 0.417 38.04157 64.32142 56.85084 0 -1 -1 - 1113 344 14 0.417 39.36310 65.01535 56.59799 0 -1 -1 - 1114 345 13 -0.834 54.26556 44.72348 38.61852 -1 0 0 - 1115 345 14 0.417 54.65781 45.53245 38.94708 -1 0 0 - 1116 345 14 0.417 54.97105 44.29396 38.13473 -1 0 0 - 1117 346 13 -0.834 55.38993 55.61246 43.96322 -1 0 1 - 1118 346 14 0.417 54.74535 54.99107 43.62461 -1 0 1 - 1119 346 14 0.417 55.11835 55.77119 44.86726 -1 0 1 - 1120 347 13 -0.834 56.42023 55.00369 50.06211 -1 -1 0 - 1121 347 14 0.417 55.77599 55.59187 50.45611 -1 -1 0 - 1122 347 14 0.417 56.93756 54.68448 50.80151 -1 -1 0 - 1123 348 13 -0.834 45.79495 66.88952 36.56670 1 1 -1 - 1124 348 14 0.417 45.28578 66.71904 35.77429 1 1 -1 - 1125 348 14 0.417 46.57709 67.34552 36.25591 1 1 -1 - 1126 349 13 -0.834 62.75278 45.54084 32.23733 0 0 0 - 1127 349 14 0.417 62.61586 44.79986 31.64705 0 0 0 - 1128 349 14 0.417 62.96974 45.14017 33.07913 0 0 0 - 1129 350 13 -0.834 57.50625 65.62986 39.74454 0 0 0 - 1130 350 14 0.417 57.73342 64.85584 40.25983 0 0 0 - 1131 350 14 0.417 57.07082 66.21286 40.36642 0 0 0 - 1132 351 13 -0.834 55.96293 62.10636 50.17062 0 1 -1 - 1133 351 14 0.417 56.24333 61.70901 50.99507 0 1 -1 - 1134 351 14 0.417 56.67888 62.69531 49.93234 0 1 -1 - 1135 352 13 -0.834 37.45010 41.11856 53.00894 0 0 0 - 1136 352 14 0.417 37.99062 41.49514 53.70339 0 0 0 - 1137 352 14 0.417 37.83337 41.45341 52.19826 0 0 0 - 1138 353 13 -0.834 40.59344 47.85232 38.52244 1 0 1 - 1139 353 14 0.417 41.31256 47.71502 37.90580 1 0 1 - 1140 353 14 0.417 40.21612 48.69426 38.26747 1 0 1 - 1141 354 13 -0.834 60.77214 62.31711 30.33695 0 2 -1 - 1142 354 14 0.417 59.83662 62.43212 30.17023 0 2 -1 - 1143 354 14 0.417 60.97856 61.45964 29.96496 0 2 -1 - 1144 355 13 -0.834 47.83829 64.26042 48.43592 0 1 -1 - 1145 355 14 0.417 47.12209 64.85952 48.22523 0 1 -1 - 1146 355 14 0.417 47.44823 63.38856 48.37295 0 1 -1 - 1147 356 13 -0.834 38.69679 45.31108 42.13672 1 1 0 - 1148 356 14 0.417 39.20464 45.52138 41.35308 1 1 0 - 1149 356 14 0.417 37.90440 44.89009 41.80335 1 1 0 - 1150 357 13 -0.834 38.90832 47.67164 52.69089 0 1 0 - 1151 357 14 0.417 39.51269 48.14149 53.26554 0 1 0 - 1152 357 14 0.417 38.42834 48.36117 52.23218 0 1 0 - 1153 358 13 -0.834 45.13879 48.98199 29.96256 0 2 1 - 1154 358 14 0.417 44.63649 48.48457 30.60794 0 2 1 - 1155 358 14 0.417 44.70163 48.80464 56.50106 0 2 0 - 1156 359 13 -0.834 54.78460 57.58368 54.24956 1 1 -1 - 1157 359 14 0.417 54.71436 57.34891 55.17486 1 1 -1 - 1158 359 14 0.417 55.60599 58.07122 54.18735 1 1 -1 - 1159 360 13 -0.834 40.77006 67.09387 46.34204 0 0 1 - 1160 360 14 0.417 40.91087 66.51539 47.09156 0 0 1 - 1161 360 14 0.417 41.47386 67.73986 46.40192 0 0 1 - 1162 361 13 -0.834 53.75960 49.21723 54.03526 1 0 -1 - 1163 361 14 0.417 54.17778 50.07537 53.96484 1 0 -1 - 1164 361 14 0.417 54.18187 48.68822 53.35846 1 0 -1 - 1165 362 13 -0.834 46.41755 62.84035 30.52059 0 0 1 - 1166 362 14 0.417 46.37357 61.90548 30.72136 0 0 1 - 1167 362 14 0.417 46.76359 62.87829 57.00030 0 0 0 - 1168 363 13 -0.834 51.27491 42.28113 30.83818 0 -1 0 - 1169 363 14 0.417 51.18814 42.11416 31.77671 0 -1 0 - 1170 363 14 0.417 50.41560 42.60836 30.57220 0 -1 0 - 1171 364 13 -0.834 52.36258 42.54738 46.83477 0 -1 -1 - 1172 364 14 0.417 51.62853 42.02025 46.51928 0 -1 -1 - 1173 364 14 0.417 53.11771 42.22680 46.34158 0 -1 -1 - 1174 365 13 -0.834 40.11442 46.69570 48.71466 3 -2 1 - 1175 365 14 0.417 39.89820 47.61495 48.55824 3 -2 1 - 1176 365 14 0.417 40.87520 46.72352 49.29493 3 -2 1 - 1177 366 13 -0.834 56.56957 65.78976 45.32589 0 -2 -1 - 1178 366 14 0.417 56.86196 65.56407 46.20896 0 -2 -1 - 1179 366 14 0.417 57.34222 66.16870 44.90678 0 -2 -1 - 1180 367 13 -0.834 38.37373 47.63723 43.98242 2 0 0 - 1181 367 14 0.417 38.78516 47.21384 44.73589 2 0 0 - 1182 367 14 0.417 38.73588 47.18051 43.22315 2 0 0 - 1183 368 13 -0.834 45.69445 49.36872 40.50736 -1 0 -2 - 1184 368 14 0.417 44.73771 49.39892 40.51002 -1 0 -2 - 1185 368 14 0.417 45.90701 48.47357 40.77155 -1 0 -2 - 1186 369 13 -0.834 53.93830 54.76570 31.99728 0 -1 0 - 1187 369 14 0.417 53.94849 55.50033 32.61083 0 -1 0 - 1188 369 14 0.417 53.13070 54.29402 32.20107 0 -1 0 - 1189 370 13 -0.834 58.79125 64.07093 37.97498 -1 -1 -2 - 1190 370 14 0.417 58.48296 64.72380 38.60343 -1 -1 -2 - 1191 370 14 0.417 58.20942 64.16977 37.22136 -1 -1 -2 - 1192 371 13 -0.834 51.76123 61.42281 40.82794 0 -1 0 - 1193 371 14 0.417 52.69114 61.24136 40.69160 0 -1 0 - 1194 371 14 0.417 51.74755 62.21395 41.36660 0 -1 0 - 1195 372 13 -0.834 44.28377 63.70509 53.71234 -1 -2 -1 - 1196 372 14 0.417 44.98211 64.35001 53.59994 -1 -2 -1 - 1197 372 14 0.417 43.75271 63.78587 52.92008 -1 -2 -1 - 1198 373 13 -0.834 61.50835 48.76378 34.91047 0 0 -1 - 1199 373 14 0.417 61.23254 49.09753 34.05678 0 0 -1 - 1200 373 14 0.417 61.51672 49.53447 35.47812 0 0 -1 - 1201 374 13 -0.834 61.51337 41.63477 44.26291 -1 -1 0 - 1202 374 14 0.417 62.42662 41.58544 44.54543 -1 -1 0 - 1203 374 14 0.417 61.34749 68.16405 43.83907 -1 -2 0 - 1204 375 13 -0.834 57.73267 43.39213 33.64792 0 -1 0 - 1205 375 14 0.417 58.46456 43.28438 34.25535 0 -1 0 - 1206 375 14 0.417 58.09278 43.15396 32.79362 0 -1 0 - 1207 376 13 -0.834 63.51473 49.31549 51.59705 -1 1 -1 - 1208 376 14 0.417 63.13045 49.03534 50.76631 -1 1 -1 - 1209 376 14 0.417 62.84038 49.86142 52.00137 -1 1 -1 - 1210 377 13 -0.834 58.21462 44.79010 54.73553 -1 -1 -1 - 1211 377 14 0.417 58.08068 43.94884 55.17209 -1 -1 -1 - 1212 377 14 0.417 57.81645 44.67856 53.87224 -1 -1 -1 - 1213 378 13 -0.834 57.08090 55.14561 52.86183 0 -2 1 - 1214 378 14 0.417 57.05215 55.46811 53.76261 0 -2 1 - 1215 378 14 0.417 57.69965 54.41575 52.88786 0 -2 1 - 1216 379 13 -0.834 60.83502 54.45436 45.82182 1 0 -1 - 1217 379 14 0.417 61.05342 55.38616 45.83857 1 0 -1 - 1218 379 14 0.417 60.79443 54.20077 46.74392 1 0 -1 - 1219 380 13 -0.834 60.86442 48.23162 37.95658 0 0 2 - 1220 380 14 0.417 61.77710 48.43881 37.75572 0 0 2 - 1221 380 14 0.417 60.87611 47.30540 38.19788 0 0 2 - 1222 381 13 -0.834 43.21478 43.26953 44.97859 2 1 -1 - 1223 381 14 0.417 42.50778 42.78849 44.54850 2 1 -1 - 1224 381 14 0.417 43.42173 42.74895 45.75474 2 1 -1 - 1225 382 13 -0.834 39.01904 49.57571 48.28198 1 -1 -1 - 1226 382 14 0.417 38.68877 49.32064 47.42052 1 -1 -1 - 1227 382 14 0.417 38.42357 50.26661 48.57234 1 -1 -1 - 1228 383 13 -0.834 47.20253 45.34580 30.26781 0 0 1 - 1229 383 14 0.417 47.05738 44.40526 30.16508 0 0 1 - 1230 383 14 0.417 46.80592 45.73631 56.86044 0 0 0 - 1231 384 13 -0.834 44.57742 55.88746 33.53830 0 -1 0 - 1232 384 14 0.417 45.13093 56.49768 33.05096 0 -1 0 - 1233 384 14 0.417 44.41092 55.17196 32.92464 0 -1 0 - 1234 385 13 -0.834 42.17091 64.36626 51.74369 1 0 0 - 1235 385 14 0.417 41.78583 65.24128 51.69570 1 0 0 - 1236 385 14 0.417 41.41926 63.77568 51.79343 1 0 0 - 1237 386 13 -0.834 43.82615 43.47821 52.97551 0 0 0 - 1238 386 14 0.417 43.64099 42.56407 52.76025 0 0 0 - 1239 386 14 0.417 44.58924 43.43914 53.55207 0 0 0 - 1240 387 13 -0.834 63.58286 63.91035 38.47173 0 -1 -1 - 1241 387 14 0.417 64.14591 63.71296 39.22023 0 -1 -1 - 1242 387 14 0.417 62.70901 64.01191 38.84896 0 -1 -1 - 1243 388 13 -0.834 57.85225 42.19019 46.82252 1 1 -2 - 1244 388 14 0.417 57.61712 42.29475 47.74450 1 1 -2 - 1245 388 14 0.417 57.29406 42.81537 46.36013 1 1 -2 - 1246 389 13 -0.834 57.90802 64.30101 52.26362 1 0 1 - 1247 389 14 0.417 58.43907 64.81717 52.87010 1 0 1 - 1248 389 14 0.417 58.54387 63.78888 51.76396 1 0 1 - 1249 390 13 -0.834 53.18379 66.68791 54.05156 1 -2 0 - 1250 390 14 0.417 52.23394 66.79510 54.00115 1 -2 0 - 1251 390 14 0.417 53.33447 65.77140 53.82015 1 -2 0 - 1252 391 13 -0.834 56.95394 68.26036 36.42711 -1 1 1 - 1253 391 14 0.417 56.91362 41.83232 36.58445 -1 2 1 - 1254 391 14 0.417 57.79173 67.98998 36.80292 -1 1 1 - 1255 392 13 -0.834 64.19252 44.20158 54.88143 0 0 0 - 1256 392 14 0.417 64.09322 45.07899 54.51194 0 0 0 - 1257 392 14 0.417 63.39239 43.74201 54.62684 0 0 0 - 1258 393 13 -0.834 63.10536 65.42626 48.53464 0 0 0 - 1259 393 14 0.417 62.79665 64.63036 48.10166 0 0 0 - 1260 393 14 0.417 62.77768 65.35429 49.43112 0 0 0 - 1261 394 13 -0.834 49.28836 66.20367 32.27628 1 -1 0 - 1262 394 14 0.417 49.46858 65.88738 33.16155 1 -1 0 - 1263 394 14 0.417 49.29197 65.41476 31.73420 1 -1 0 - 1264 395 13 -0.834 46.11216 66.09570 44.77896 0 -1 0 - 1265 395 14 0.417 45.90309 66.07762 45.71287 0 -1 0 - 1266 395 14 0.417 45.36137 65.67813 44.35683 0 -1 0 - 1267 396 13 -0.834 41.43943 50.30026 52.32584 1 0 0 - 1268 396 14 0.417 41.39866 49.93140 51.44351 1 0 0 - 1269 396 14 0.417 40.92759 49.69528 52.86275 1 0 0 - 1270 397 13 -0.834 54.69177 57.80859 32.50623 0 -1 -1 - 1271 397 14 0.417 53.99890 57.66594 31.86139 0 -1 -1 - 1272 397 14 0.417 54.37599 57.37325 33.29806 0 -1 -1 - 1273 398 13 -0.834 43.56781 46.79065 37.17838 0 1 0 - 1274 398 14 0.417 43.18325 46.24795 36.49004 0 1 0 - 1275 398 14 0.417 44.03819 46.17194 37.73711 0 1 0 - 1276 399 13 -0.834 55.33436 45.90772 50.69068 -1 0 0 - 1277 399 14 0.417 55.55455 46.77982 51.01809 -1 0 0 - 1278 399 14 0.417 55.09425 46.04877 49.77488 -1 0 0 - 1279 400 13 -0.834 56.15383 51.87018 43.92178 -1 0 1 - 1280 400 14 0.417 55.25073 52.12373 44.11256 -1 0 1 - 1281 400 14 0.417 56.65027 52.68628 43.98319 -1 0 1 - 1282 401 13 -0.834 62.38946 50.01240 45.94802 0 1 -2 - 1283 401 14 0.417 62.43815 50.07607 44.99418 0 1 -2 - 1284 401 14 0.417 61.47369 50.19932 46.15457 0 1 -2 - 1285 402 13 -0.834 53.60920 58.35575 46.37412 0 0 1 - 1286 402 14 0.417 53.25556 59.03071 45.79481 0 0 1 - 1287 402 14 0.417 53.24753 57.53627 46.03666 0 0 1 - 1288 403 13 -0.834 43.13375 42.07203 50.04429 1 0 0 - 1289 403 14 0.417 43.76099 42.76922 49.85267 1 0 0 - 1290 403 14 0.417 42.35437 42.53016 50.35879 1 0 0 - 1291 404 13 -0.834 47.41498 59.41146 52.77687 -1 -1 0 - 1292 404 14 0.417 47.81303 59.83868 53.53534 -1 -1 0 - 1293 404 14 0.417 48.01011 59.60512 52.05261 -1 -1 0 - 1294 405 13 -0.834 63.75607 47.28104 38.80571 0 2 -1 - 1295 405 14 0.417 63.78573 48.20840 38.57042 0 2 -1 - 1296 405 14 0.417 37.08655 47.17376 39.44769 1 2 -1 - 1297 406 13 -0.834 46.67594 56.20863 44.42866 1 1 0 - 1298 406 14 0.417 45.82140 56.15280 44.00100 1 1 0 - 1299 406 14 0.417 46.48292 56.12468 45.36243 1 1 0 - 1300 407 13 -0.834 62.54251 68.21194 54.20445 0 -1 1 - 1301 407 14 0.417 63.31640 41.15490 53.73696 0 0 1 - 1302 407 14 0.417 62.78865 67.34176 54.51819 0 -1 1 - 1303 408 13 -0.834 60.27010 54.96049 39.87633 0 0 0 - 1304 408 14 0.417 59.62959 55.67175 39.88547 0 0 0 - 1305 408 14 0.417 61.04761 55.33233 40.29281 0 0 0 - 1306 409 13 -0.834 40.02595 44.30132 44.29580 0 -2 0 - 1307 409 14 0.417 39.70595 44.75009 45.07839 0 -2 0 - 1308 409 14 0.417 39.56836 44.72725 43.57092 0 -2 0 - 1309 410 13 -0.834 54.20011 41.08252 35.61017 0 1 0 - 1310 410 14 0.417 55.10396 68.23613 35.83794 0 0 0 - 1311 410 14 0.417 54.27044 41.57221 34.79072 0 1 0 - 1312 411 13 -0.834 60.64478 45.93023 50.84376 1 1 -1 - 1313 411 14 0.417 60.80088 46.54647 51.55941 1 1 -1 - 1314 411 14 0.417 61.20574 46.24077 50.13303 1 1 -1 - 1315 412 13 -0.834 44.55137 44.47403 38.16771 1 0 -1 - 1316 412 14 0.417 45.28189 43.86333 38.26597 1 0 -1 - 1317 412 14 0.417 43.77025 43.93754 38.30281 1 0 -1 - 1318 413 13 -0.834 58.08933 62.76987 30.45191 1 -1 0 - 1319 413 14 0.417 57.64138 63.31997 29.80927 1 -1 0 - 1320 413 14 0.417 57.43674 62.11708 30.70545 1 -1 0 - 1321 414 13 -0.834 55.65273 56.71117 38.74877 1 0 1 - 1322 414 14 0.417 56.53260 56.59636 39.10779 1 0 1 - 1323 414 14 0.417 55.14964 55.98047 39.10825 1 0 1 - 1324 415 13 -0.834 55.50009 51.16952 38.77962 0 0 0 - 1325 415 14 0.417 54.95350 51.23711 37.99672 0 0 0 - 1326 415 14 0.417 55.53220 50.23190 38.96963 0 0 0 - 1327 416 13 -0.834 47.64702 52.79911 31.71446 0 -1 0 - 1328 416 14 0.417 48.52504 53.09556 31.47481 0 -1 0 - 1329 416 14 0.417 47.06032 53.44853 31.32681 0 -1 0 - 1330 417 13 -0.834 49.26727 42.35880 39.18566 1 1 -2 - 1331 417 14 0.417 50.02784 42.93912 39.15429 1 1 -2 - 1332 417 14 0.417 49.46495 41.74196 39.89040 1 1 -2 - 1333 418 13 -0.834 47.22542 64.65021 35.82232 1 -1 0 - 1334 418 14 0.417 46.76114 65.20346 36.45050 1 -1 0 - 1335 418 14 0.417 47.98585 65.16966 35.56120 1 -1 0 - 1336 419 13 -0.834 58.53686 56.85468 40.78587 1 1 0 - 1337 419 14 0.417 58.45283 56.63469 41.71365 1 1 0 - 1338 419 14 0.417 58.36285 57.79507 40.74550 1 1 0 - 1339 420 13 -0.834 50.09436 46.17981 48.16619 -1 -1 -2 - 1340 420 14 0.417 50.67249 45.42897 48.30138 -1 -1 -2 - 1341 420 14 0.417 50.49629 46.88624 48.67183 -1 -1 -2 - 1342 421 13 -0.834 42.30297 57.95379 33.48633 0 -1 1 - 1343 421 14 0.417 41.56921 57.39445 33.23136 0 -1 1 - 1344 421 14 0.417 43.00718 57.34235 33.70193 0 -1 1 - 1345 422 13 -0.834 45.76518 43.79811 54.82490 0 -1 0 - 1346 422 14 0.417 46.45133 43.55343 54.20397 0 -1 0 - 1347 422 14 0.417 45.87205 43.18693 55.55379 0 -1 0 - 1348 423 13 -0.834 59.33326 61.34125 37.96927 -1 -1 1 - 1349 423 14 0.417 59.29007 62.29004 38.08827 -1 -1 1 - 1350 423 14 0.417 59.90006 61.03609 38.67769 -1 -1 1 - 1351 424 13 -0.834 40.95662 63.48104 42.72192 1 -1 0 - 1352 424 14 0.417 40.33618 63.69074 42.02383 1 -1 0 - 1353 424 14 0.417 41.73946 63.17568 42.26346 1 -1 0 - 1354 425 13 -0.834 38.13662 59.25720 46.08402 1 -1 -1 - 1355 425 14 0.417 38.31499 59.03616 46.99811 1 -1 -1 - 1356 425 14 0.417 38.55502 58.55783 45.58196 1 -1 -1 - 1357 426 13 -0.834 48.88681 66.85051 54.82298 1 -2 0 - 1358 426 14 0.417 49.16879 67.45078 54.13275 1 -2 0 - 1359 426 14 0.417 49.42353 66.06836 54.69484 1 -2 0 - 1360 427 13 -0.834 45.88049 57.05477 48.46508 0 0 -1 - 1361 427 14 0.417 45.73709 57.90911 48.05793 0 0 -1 - 1362 427 14 0.417 45.83791 57.22701 49.40569 0 0 -1 - 1363 428 13 -0.834 39.37333 50.31613 37.93447 0 1 0 - 1364 428 14 0.417 39.11456 50.97624 37.29140 0 1 0 - 1365 428 14 0.417 38.97424 50.60960 38.75352 0 1 0 - 1366 429 13 -0.834 37.89753 62.82745 47.39297 0 -1 0 - 1367 429 14 0.417 38.39122 62.78202 46.57414 0 -1 0 - 1368 429 14 0.417 37.01605 63.08963 47.12747 0 -1 0 - 1369 430 13 -0.834 43.16514 41.31420 47.01379 0 1 0 - 1370 430 14 0.417 42.71409 41.22965 47.85382 0 1 0 - 1371 430 14 0.417 44.05112 68.36565 47.18386 0 0 0 - 1372 431 13 -0.834 47.03179 42.44477 42.46475 1 0 0 - 1373 431 14 0.417 46.12350 42.65285 42.24573 1 0 0 - 1374 431 14 0.417 47.53228 43.19970 42.15516 1 0 0 - 1375 432 13 -0.834 55.35894 54.15040 46.85340 0 -1 0 - 1376 432 14 0.417 54.76544 53.43667 46.61975 0 -1 0 - 1377 432 14 0.417 56.17133 53.71318 47.10853 0 -1 0 - 1378 433 13 -0.834 47.00663 55.28313 38.22800 -1 -2 1 - 1379 433 14 0.417 46.53490 56.00706 38.63987 -1 -2 1 - 1380 433 14 0.417 47.07459 54.61953 38.91449 -1 -2 1 - 1381 434 13 -0.834 57.16336 58.62297 32.33349 -1 0 2 - 1382 434 14 0.417 57.63330 57.80350 32.48798 -1 0 2 - 1383 434 14 0.417 56.24209 58.36680 32.29014 -1 0 2 - 1384 435 13 -0.834 37.23245 47.62479 56.34765 0 1 -1 - 1385 435 14 0.417 37.24274 47.21497 55.48268 0 1 -1 - 1386 435 14 0.417 37.36000 46.89905 56.95860 0 1 -1 - 1387 436 13 -0.834 48.77030 41.06015 29.86683 2 1 0 - 1388 436 14 0.417 48.81141 67.97117 56.39997 2 0 -1 - 1389 436 14 0.417 49.05230 67.78232 30.51123 2 0 0 - 1390 437 13 -0.834 49.10149 56.15638 36.66346 0 0 1 - 1391 437 14 0.417 48.50786 55.61659 36.14146 0 0 1 - 1392 437 14 0.417 48.61812 56.33305 37.47053 0 0 1 - 1393 438 13 -0.834 58.15731 59.39698 29.96092 0 -1 1 - 1394 438 14 0.417 58.20240 59.10993 30.87296 0 -1 1 - 1395 438 14 0.417 57.30076 59.81721 29.88367 0 -1 1 - 1396 439 13 -0.834 59.37068 41.03089 37.87324 1 0 0 - 1397 439 14 0.417 59.56889 41.95335 37.71194 1 0 0 - 1398 439 14 0.417 60.22643 67.97433 37.90167 1 -1 0 - 1399 440 13 -0.834 38.32241 55.03397 50.58952 1 0 0 - 1400 440 14 0.417 38.22793 54.19584 50.13692 1 0 0 - 1401 440 14 0.417 39.21785 55.31153 50.39614 1 0 0 - 1402 441 13 -0.834 36.94673 59.01778 33.00159 1 -1 2 - 1403 441 14 0.417 36.95260 59.97305 32.94091 1 -1 2 - 1404 441 14 0.417 63.71798 58.82680 33.72245 0 -1 2 - 1405 442 13 -0.834 62.50746 54.84239 54.03343 0 -1 0 - 1406 442 14 0.417 61.69710 54.35984 54.19681 0 -1 0 - 1407 442 14 0.417 63.09119 54.20097 53.62833 0 -1 0 - 1408 443 13 -0.834 40.59690 62.80012 38.69405 1 -1 1 - 1409 443 14 0.417 41.53881 62.90970 38.82458 1 -1 1 - 1410 443 14 0.417 40.36980 62.03187 39.21794 1 -1 1 - 1411 444 13 -0.834 37.67477 67.71471 42.59127 0 -1 -1 - 1412 444 14 0.417 38.12213 68.13627 41.85751 0 -1 -1 - 1413 444 14 0.417 38.28279 67.03643 42.88534 0 -1 -1 - 1414 445 13 -0.834 42.73681 50.65782 33.30839 1 1 0 - 1415 445 14 0.417 42.84587 51.15085 34.12157 1 1 0 - 1416 445 14 0.417 42.32631 51.27747 32.70527 1 1 0 - 1417 446 13 -0.834 37.13349 57.05842 55.81927 0 0 0 - 1418 446 14 0.417 37.95375 57.53453 55.68979 0 0 0 - 1419 446 14 0.417 36.99014 56.59807 54.99236 0 0 0 - 1420 447 13 -0.834 61.08039 63.50929 36.52096 -1 0 0 - 1421 447 14 0.417 60.44389 63.87414 37.13579 -1 0 0 - 1422 447 14 0.417 61.70642 63.04107 37.07331 -1 0 0 - 1423 448 13 -0.834 57.12289 46.04019 38.75954 0 0 0 - 1424 448 14 0.417 56.81351 45.55997 39.52760 0 0 0 - 1425 448 14 0.417 57.99543 45.68504 38.58988 0 0 0 - 1426 449 13 -0.834 45.45003 49.45347 49.54397 0 0 -1 - 1427 449 14 0.417 45.96611 49.34591 48.74502 0 0 -1 - 1428 449 14 0.417 46.09930 49.60861 50.22999 0 0 -1 - 1429 450 13 -0.834 37.77009 64.51990 42.66941 1 0 0 - 1430 450 14 0.417 38.49339 64.80040 43.23011 1 0 0 - 1431 450 14 0.417 38.14071 64.50928 41.78694 1 0 0 - 1432 451 13 -0.834 45.78323 57.65378 39.37062 1 0 0 - 1433 451 14 0.417 46.03758 58.03295 40.21190 1 0 0 - 1434 451 14 0.417 44.96217 58.09258 39.14803 1 0 0 - 1435 452 13 -0.834 56.96672 60.41636 47.59314 0 -1 1 - 1436 452 14 0.417 56.18373 60.11455 48.05365 0 -1 1 - 1437 452 14 0.417 56.65889 61.13663 47.04297 0 -1 1 - 1438 453 13 -0.834 52.44356 65.82746 35.82081 -1 -1 0 - 1439 453 14 0.417 53.10567 65.14225 35.91211 -1 -1 0 - 1440 453 14 0.417 52.93741 66.64611 35.86748 -1 -1 0 - 1441 454 13 -0.834 50.70912 51.42252 40.30021 0 0 -1 - 1442 454 14 0.417 50.97387 50.70177 39.72866 0 0 -1 - 1443 454 14 0.417 50.17774 51.98938 39.74116 0 0 -1 - 1444 455 13 -0.834 39.22290 45.94023 39.69239 2 1 -1 - 1445 455 14 0.417 39.63836 46.66722 39.22859 2 1 -1 - 1446 455 14 0.417 38.97218 45.32685 39.00164 2 1 -1 - 1447 456 13 -0.834 43.73041 61.86387 55.46954 2 0 0 - 1448 456 14 0.417 43.61274 62.32163 56.30192 2 0 0 - 1449 456 14 0.417 43.90401 62.55964 54.83549 2 0 0 - 1450 457 13 -0.834 61.51877 56.42039 33.84869 0 0 1 - 1451 457 14 0.417 62.17805 55.74211 33.70200 0 0 1 - 1452 457 14 0.417 62.00943 57.15723 34.21276 0 0 1 - 1453 458 13 -0.834 51.72050 63.63199 42.34406 1 0 1 - 1454 458 14 0.417 51.24482 64.43296 42.56407 1 0 1 - 1455 458 14 0.417 52.62118 63.92057 42.19669 1 0 1 - 1456 459 13 -0.834 54.73666 56.51839 51.73687 0 0 -1 - 1457 459 14 0.417 54.77503 56.56844 52.69200 0 0 -1 - 1458 459 14 0.417 54.91702 57.41111 51.44234 0 0 -1 - 1459 460 13 -0.834 50.97984 54.35591 33.27919 0 1 0 - 1460 460 14 0.417 50.47200 55.12727 33.02747 0 1 0 - 1461 460 14 0.417 50.36917 53.82187 33.78725 0 1 0 - 1462 461 13 -0.834 44.82656 54.45280 36.09973 1 0 2 - 1463 461 14 0.417 45.75766 54.23599 36.14740 1 0 2 - 1464 461 14 0.417 44.76968 55.11700 35.41283 1 0 2 - 1465 462 13 -0.834 58.05791 56.64716 55.29041 1 1 0 - 1466 462 14 0.417 58.98499 56.81997 55.45441 1 1 0 - 1467 462 14 0.417 57.82639 55.96338 55.91897 1 1 0 - 1468 463 13 -0.834 55.95112 61.02029 30.79757 1 0 1 - 1469 463 14 0.417 55.28483 61.63344 30.48711 1 0 1 - 1470 463 14 0.417 55.45357 60.27206 31.12748 1 0 1 - 1471 464 13 -0.834 54.80996 46.88659 45.41700 -1 0 0 - 1472 464 14 0.417 55.42348 46.16300 45.28950 -1 0 0 - 1473 464 14 0.417 54.08129 46.68997 44.82826 -1 0 0 - 1474 465 13 -0.834 60.19361 64.43268 31.92053 0 -1 2 - 1475 465 14 0.417 60.05792 63.85315 32.67017 0 -1 2 - 1476 465 14 0.417 60.47170 63.84993 31.21392 0 -1 2 - 1477 466 13 -0.834 45.55496 65.56032 30.88251 0 -1 1 - 1478 466 14 0.417 45.97644 64.70102 30.89691 0 -1 1 - 1479 466 14 0.417 45.82502 65.97384 31.70248 0 -1 1 - 1480 467 13 -0.834 52.92714 44.06759 29.88429 0 1 0 - 1481 467 14 0.417 52.39641 43.38446 30.29405 0 1 0 - 1482 467 14 0.417 53.79372 43.96686 30.27818 0 1 0 - 1483 468 13 -0.834 40.71534 55.31247 44.93070 1 0 0 - 1484 468 14 0.417 39.81994 55.07165 45.16841 1 0 0 - 1485 468 14 0.417 41.16802 54.47609 44.82218 1 0 0 - 1486 469 13 -0.834 64.04777 59.80626 42.91634 0 -1 -1 - 1487 469 14 0.417 37.09051 60.51146 43.41377 1 -1 -1 - 1488 469 14 0.417 37.01609 59.00291 43.31068 1 -1 -1 - 1489 470 13 -0.834 57.05030 49.72625 41.88829 -1 1 1 - 1490 470 14 0.417 56.75150 50.53290 42.30818 -1 1 1 - 1491 470 14 0.417 57.52176 50.02159 41.10935 -1 1 1 - 1492 471 13 -0.834 62.59447 67.67898 41.14714 -2 -2 1 - 1493 471 14 0.417 63.45155 67.57764 41.56112 -2 -2 1 - 1494 471 14 0.417 61.96974 67.40478 41.81854 -2 -2 1 - 1495 472 13 -0.834 62.98029 58.34420 35.34278 0 0 1 - 1496 472 14 0.417 62.45371 58.26151 36.13783 0 0 1 - 1497 472 14 0.417 63.83636 58.64077 35.65169 0 0 1 - 1498 473 13 -0.834 63.44584 56.74146 44.14484 0 1 -2 - 1499 473 14 0.417 64.13590 56.53036 44.77371 0 1 -2 - 1500 473 14 0.417 62.70665 57.02149 44.68470 0 1 -2 - 1501 474 13 -0.834 44.05905 56.56929 51.60681 1 0 -1 - 1502 474 14 0.417 43.57850 56.15764 52.32504 1 0 -1 - 1503 474 14 0.417 43.90344 55.99747 50.85512 1 0 -1 - 1504 475 13 -0.834 37.49588 59.31379 39.05252 0 0 0 - 1505 475 14 0.417 37.07904 58.45297 39.09112 0 0 0 - 1506 475 14 0.417 37.58867 59.49374 38.11696 0 0 0 - 1507 476 13 -0.834 54.75747 41.52122 56.48609 -1 1 0 - 1508 476 14 0.417 54.79987 42.39714 56.86981 -1 1 0 - 1509 476 14 0.417 54.80582 41.67034 55.54179 -1 1 0 - 1510 477 13 -0.834 42.91665 58.39379 47.91495 1 0 0 - 1511 477 14 0.417 43.70923 58.91951 47.80683 1 0 0 - 1512 477 14 0.417 42.28811 58.98861 48.32409 1 0 0 - 1513 478 13 -0.834 60.63731 64.78822 56.03697 -2 1 -1 - 1514 478 14 0.417 60.86485 63.91302 56.35082 -2 1 -1 - 1515 478 14 0.417 60.50973 65.30321 56.83369 -2 1 -1 - 1516 479 13 -0.834 52.85180 54.69512 43.09842 0 0 1 - 1517 479 14 0.417 52.31485 55.13373 42.43846 0 0 1 - 1518 479 14 0.417 53.08000 53.85428 42.70200 0 0 1 - 1519 480 13 -0.834 51.49497 54.97356 38.95012 -2 1 -1 - 1520 480 14 0.417 50.77717 54.34090 38.97811 -2 1 -1 - 1521 480 14 0.417 51.51597 55.35169 39.82923 -2 1 -1 - 1522 481 13 -0.834 40.46924 62.02458 56.36341 1 0 -1 - 1523 481 14 0.417 40.45814 61.65439 55.48076 1 0 -1 - 1524 481 14 0.417 40.81799 62.90856 56.24853 1 0 -1 - 1525 482 13 -0.834 52.26692 56.29032 45.24820 0 2 1 - 1526 482 14 0.417 51.65227 56.79794 44.71834 0 2 1 - 1527 482 14 0.417 52.43092 55.49973 44.73408 0 2 1 - 1528 483 13 -0.834 53.46372 44.63556 52.39623 -1 1 1 - 1529 483 14 0.417 53.51664 45.03502 53.26448 -1 1 1 - 1530 483 14 0.417 54.08491 45.13343 51.86474 -1 1 1 - 1531 484 13 -0.834 42.90202 49.87822 40.32919 0 2 1 - 1532 484 14 0.417 42.40392 49.63281 41.10889 0 2 1 - 1533 484 14 0.417 42.31302 50.45172 39.83885 0 2 1 - 1534 485 13 -0.834 43.07357 64.57931 39.44006 2 1 1 - 1535 485 14 0.417 42.79300 64.80186 38.55237 2 1 1 - 1536 485 14 0.417 43.26869 65.42268 39.84860 2 1 1 - 1537 486 13 -0.834 38.86691 42.35197 55.12826 1 1 -1 - 1538 486 14 0.417 38.06621 42.87541 55.16185 1 1 -1 - 1539 486 14 0.417 39.52681 42.89488 55.55954 1 1 -1 - 1540 487 13 -0.834 59.15412 47.19863 55.46904 0 -1 0 - 1541 487 14 0.417 59.83963 46.99833 56.10636 0 -1 0 - 1542 487 14 0.417 58.74433 46.35364 55.28381 0 -1 0 - 1543 488 13 -0.834 52.12071 45.94110 44.23903 1 1 0 - 1544 488 14 0.417 51.89927 45.05144 44.51416 1 1 0 - 1545 488 14 0.417 52.26697 45.87115 43.29566 1 1 0 - 1546 489 13 -0.834 41.73140 52.23741 31.27732 0 0 1 - 1547 489 14 0.417 40.84403 52.55314 31.44796 0 0 1 - 1548 489 14 0.417 41.81503 52.26011 30.32405 0 0 1 - 1549 490 13 -0.834 38.46034 66.01701 52.27886 1 0 -1 - 1550 490 14 0.417 39.39276 66.02392 52.49517 1 0 -1 - 1551 490 14 0.417 38.11246 66.80769 52.69121 1 0 -1 - 1552 491 13 -0.834 42.13838 67.12262 54.88509 0 0 -3 - 1553 491 14 0.417 42.22460 67.38235 53.96784 0 0 -3 - 1554 491 14 0.417 42.96673 67.38388 55.28736 0 0 -3 - 1555 492 13 -0.834 37.89607 66.86351 46.16867 -1 -1 -1 - 1556 492 14 0.417 38.03129 66.98073 47.10899 -1 -1 -1 - 1557 492 14 0.417 38.75367 66.60168 45.83369 -1 -1 -1 - 1558 493 13 -0.834 40.37538 58.21424 30.88318 0 -1 0 - 1559 493 14 0.417 41.23010 58.63566 30.79307 0 -1 0 - 1560 493 14 0.417 40.45502 57.40101 30.38463 0 -1 0 - 1561 494 13 -0.834 54.56531 48.85249 32.17940 1 -2 2 - 1562 494 14 0.417 54.90082 48.98086 31.29216 1 -2 2 - 1563 494 14 0.417 54.03604 49.63141 32.35086 1 -2 2 - 1564 495 13 -0.834 63.56488 49.70113 37.88594 0 -1 1 - 1565 495 14 0.417 63.93261 49.40780 37.05228 0 -1 1 - 1566 495 14 0.417 63.98151 50.54765 38.04739 0 -1 1 - 1567 496 13 -0.834 39.26126 54.76920 54.71493 2 -1 2 - 1568 496 14 0.417 38.75402 55.21237 54.03483 2 -1 2 - 1569 496 14 0.417 38.67139 54.73109 55.46781 2 -1 2 - 1570 497 13 -0.834 42.78607 47.20625 49.30057 2 -1 0 - 1571 497 14 0.417 42.93670 46.34815 48.90404 2 -1 0 - 1572 497 14 0.417 43.53800 47.33917 49.87780 2 -1 0 - 1573 498 13 -0.834 59.99490 55.30114 50.55687 0 1 -1 - 1574 498 14 0.417 60.84158 55.66821 50.81111 0 1 -1 - 1575 498 14 0.417 59.38335 56.03363 50.63237 0 1 -1 - 1576 499 13 -0.834 57.95276 49.30660 54.37087 1 -1 -1 - 1577 499 14 0.417 57.34184 49.29544 55.10769 1 -1 -1 - 1578 499 14 0.417 58.55272 48.58151 54.54557 1 -1 -1 - 1579 500 13 -0.834 43.43041 64.04345 57.10111 1 -1 -1 - 1580 500 14 0.417 43.03742 64.07155 30.60210 1 -1 0 - 1581 500 14 0.417 44.26016 64.51104 29.82515 1 -1 0 - 1582 501 13 -0.834 40.71066 57.82778 50.85579 1 -1 -1 - 1583 501 14 0.417 41.04411 57.83612 51.75299 1 -1 -1 - 1584 501 14 0.417 40.96886 58.67633 50.49590 1 -1 -1 - 1585 502 13 -0.834 61.21331 60.53661 39.63578 1 -1 0 - 1586 502 14 0.417 61.87151 61.23113 39.61011 1 -1 0 - 1587 502 14 0.417 61.32085 60.13583 40.49837 1 -1 0 - 1588 503 13 -0.834 43.54081 65.33296 49.47114 1 -1 -1 - 1589 503 14 0.417 42.67637 65.41138 49.06762 1 -1 -1 - 1590 503 14 0.417 43.36562 64.99829 50.35065 1 -1 -1 - 1591 504 13 -0.834 50.27329 53.06087 30.87109 -1 0 1 - 1592 504 14 0.417 50.38769 53.42204 29.99204 -1 0 1 - 1593 504 14 0.417 50.86354 53.57620 31.42092 -1 0 1 - 1594 505 13 -0.834 40.29157 66.01889 32.67757 0 -1 0 - 1595 505 14 0.417 40.18198 66.27998 31.76320 0 -1 0 - 1596 505 14 0.417 39.39873 65.90460 33.00317 0 -1 0 - 1597 506 13 -0.834 48.15372 67.97019 44.25255 1 -1 1 - 1598 506 14 0.417 47.34263 67.52534 44.49854 1 -1 1 - 1599 506 14 0.417 47.87159 41.31478 43.68328 1 0 1 - 1600 507 13 -0.834 53.38019 63.98437 38.13827 0 0 -1 - 1601 507 14 0.417 54.19463 63.69976 37.72362 0 0 -1 - 1602 507 14 0.417 53.59582 64.82739 38.53711 0 0 -1 - 1603 508 13 -0.834 40.87597 58.12305 53.50808 0 0 0 - 1604 508 14 0.417 40.17916 58.26636 54.14852 0 0 0 - 1605 508 14 0.417 41.66044 58.48234 53.92256 0 0 0 - 1606 509 13 -0.834 38.19887 52.28056 36.30714 2 0 -1 - 1607 509 14 0.417 38.20463 53.19038 36.60452 2 0 -1 - 1608 509 14 0.417 38.09924 52.33929 35.35695 2 0 -1 - 1609 510 13 -0.834 49.63883 57.32410 43.72359 0 -1 0 - 1610 510 14 0.417 49.72446 58.17232 43.28833 0 -1 0 - 1611 510 14 0.417 48.76183 57.33851 44.10688 0 -1 0 - 1612 511 13 -0.834 42.58791 59.61362 29.86455 1 0 0 - 1613 511 14 0.417 43.07246 58.91969 56.78877 1 0 -1 - 1614 511 14 0.417 42.69535 60.38141 56.67447 1 0 -1 - 1615 512 13 -0.834 50.76111 60.95449 46.98165 -1 0 -1 - 1616 512 14 0.417 50.90477 61.15450 47.90663 -1 0 -1 - 1617 512 14 0.417 50.20825 61.66875 46.66473 -1 0 -1 - 1618 513 13 -0.834 43.18406 55.61939 48.08539 1 0 0 - 1619 513 14 0.417 43.11229 56.55752 47.90932 1 0 0 - 1620 513 14 0.417 44.01330 55.36231 47.68228 1 0 0 - 1621 514 13 -0.834 54.67377 64.76817 41.62522 1 0 1 - 1622 514 14 0.417 54.39407 65.19031 40.81294 1 0 1 - 1623 514 14 0.417 55.29742 65.38243 42.01250 1 0 1 - 1624 515 13 -0.834 53.87383 68.12810 51.72031 0 -1 0 - 1625 515 14 0.417 53.06918 41.24938 51.55887 0 0 0 - 1626 515 14 0.417 53.74278 67.72971 52.58074 0 -1 0 - 1627 516 13 -0.834 38.24785 41.26767 33.50598 2 0 0 - 1628 516 14 0.417 38.16490 67.75301 33.15337 2 -1 0 - 1629 516 14 0.417 37.95757 41.83753 32.79377 2 0 0 - 1630 517 13 -0.834 47.35008 61.96125 42.94580 2 -2 0 - 1631 517 14 0.417 47.46077 62.90828 43.03015 2 -2 0 - 1632 517 14 0.417 47.09087 61.83022 42.03373 2 -2 0 - 1633 518 13 -0.834 40.55210 54.00820 41.89137 1 -1 1 - 1634 518 14 0.417 39.80099 54.24986 41.34946 1 -1 1 - 1635 518 14 0.417 40.19429 53.40377 42.54166 1 -1 1 - 1636 519 13 -0.834 57.17705 64.40362 55.44286 1 -1 -1 - 1637 519 14 0.417 56.34510 64.78670 55.72097 1 -1 -1 - 1638 519 14 0.417 57.64987 65.12814 55.03330 1 -1 -1 - 1639 520 13 -0.834 41.86955 59.84132 42.65268 0 -1 1 - 1640 520 14 0.417 41.72011 59.11980 43.26367 0 -1 1 - 1641 520 14 0.417 42.24995 60.53605 43.19017 0 -1 1 - 1642 521 13 -0.834 61.62566 57.26645 46.18447 0 -1 -1 - 1643 521 14 0.417 60.68119 57.41642 46.22577 0 -1 -1 - 1644 521 14 0.417 61.98987 57.84356 46.85569 0 -1 -1 - 1645 522 13 -0.834 46.82701 65.68647 41.03579 0 0 0 - 1646 522 14 0.417 46.01385 65.85266 41.51264 0 0 0 - 1647 522 14 0.417 47.44009 65.38297 41.70531 0 0 0 - 1648 523 13 -0.834 54.12960 45.94549 32.81485 0 0 1 - 1649 523 14 0.417 53.25962 45.65636 32.53955 0 0 1 - 1650 523 14 0.417 54.18942 46.85072 32.50950 0 0 1 - 1651 524 13 -0.834 43.71268 59.97805 32.34985 1 1 0 - 1652 524 14 0.417 43.46300 59.27568 32.95033 1 1 0 - 1653 524 14 0.417 42.94131 60.10757 31.79808 1 1 0 - 1654 525 13 -0.834 50.10604 48.47250 49.62054 1 0 -2 - 1655 525 14 0.417 50.96037 48.77303 49.31064 1 0 -2 - 1656 525 14 0.417 50.19320 48.44287 50.57331 1 0 -2 - 1657 526 13 -0.834 54.68660 60.38920 43.62499 0 0 0 - 1658 526 14 0.417 54.62862 59.85089 42.83561 0 0 0 - 1659 526 14 0.417 53.78667 60.44045 43.94712 0 0 0 - 1660 527 13 -0.834 56.35115 44.75736 40.87552 0 -1 -1 - 1661 527 14 0.417 56.99705 44.99197 41.54186 0 -1 -1 - 1662 527 14 0.417 55.55387 44.56808 41.37024 0 -1 -1 - 1663 528 13 -0.834 48.77009 62.36934 40.44473 0 -1 0 - 1664 528 14 0.417 49.30266 62.60520 41.20432 0 -1 0 - 1665 528 14 0.417 49.04689 62.97756 39.75939 0 -1 0 - 1666 529 13 -0.834 45.88757 58.55209 41.94547 0 1 0 - 1667 529 14 0.417 46.76719 58.27665 42.20365 0 1 0 - 1668 529 14 0.417 45.35604 57.75963 42.02128 0 1 0 - 1669 530 13 -0.834 39.44116 52.22097 43.65725 1 0 2 - 1670 530 14 0.417 39.30570 52.06689 44.59221 1 0 2 - 1671 530 14 0.417 38.61744 52.60378 43.35530 1 0 2 - 1672 531 13 -0.834 43.95976 66.73852 41.23250 1 0 1 - 1673 531 14 0.417 44.64454 67.13772 40.69588 1 0 1 - 1674 531 14 0.417 43.40678 67.47232 41.50081 1 0 1 - 1675 532 13 -0.834 62.99634 65.50241 54.70446 0 -1 -1 - 1676 532 14 0.417 63.58398 64.98613 55.25617 0 -1 -1 - 1677 532 14 0.417 62.12519 65.14960 54.88585 0 -1 -1 - 1678 533 13 -0.834 62.92898 53.27582 44.77167 0 0 0 - 1679 533 14 0.417 62.08998 53.60880 45.09018 0 0 0 - 1680 533 14 0.417 62.85751 52.32504 44.85618 0 0 0 - 1681 534 13 -0.834 63.31201 43.08081 48.29805 -1 0 -1 - 1682 534 14 0.417 63.01276 42.23705 47.95930 -1 0 -1 - 1683 534 14 0.417 63.67142 43.53221 47.53431 -1 0 -1 - 1684 535 13 -0.834 47.11867 63.34781 55.06249 0 0 -1 - 1685 535 14 0.417 47.19267 64.30022 55.00160 0 0 -1 - 1686 535 14 0.417 46.22495 63.15783 54.77716 0 0 -1 - 1687 536 13 -0.834 60.37216 67.91341 52.27568 -1 0 0 - 1688 536 14 0.417 61.05051 68.14950 52.90839 -1 0 0 - 1689 536 14 0.417 60.81546 67.93922 51.42771 -1 0 0 - 1690 537 13 -0.834 60.04315 43.26291 35.25445 -1 1 1 - 1691 537 14 0.417 60.42501 44.05815 35.62593 -1 1 1 - 1692 537 14 0.417 60.79709 42.72574 35.01102 -1 1 1 - 1693 538 13 -0.834 53.03851 55.52589 47.75769 0 0 -1 - 1694 538 14 0.417 53.93635 55.46537 47.43136 0 0 -1 - 1695 538 14 0.417 52.51527 55.73342 46.98347 0 0 -1 - 1696 539 13 -0.834 37.91895 50.43697 56.37325 0 0 0 - 1697 539 14 0.417 37.51622 49.56884 56.35299 0 0 0 - 1698 539 14 0.417 38.37591 50.50915 55.53527 0 0 0 - 1699 540 13 -0.834 50.50006 63.56852 38.27177 1 1 0 - 1700 540 14 0.417 50.22462 63.18436 37.43944 1 1 0 - 1701 540 14 0.417 51.44083 63.71275 38.16986 1 1 0 - 1702 541 13 -0.834 49.44600 43.95446 42.01861 0 0 1 - 1703 541 14 0.417 49.59639 44.80378 41.60354 0 0 1 - 1704 541 14 0.417 49.73882 44.07372 42.92211 0 0 1 - 1705 542 13 -0.834 50.98365 47.23031 39.51901 1 0 1 - 1706 542 14 0.417 51.18743 48.09631 39.16579 1 0 1 - 1707 542 14 0.417 50.03928 47.13635 39.39410 1 0 1 - 1708 543 13 -0.834 45.54625 60.20130 44.30493 0 0 2 - 1709 543 14 0.417 46.27140 60.62480 43.84553 0 0 2 - 1710 543 14 0.417 45.09838 59.69256 43.62904 0 0 2 - 1711 544 13 -0.834 60.48207 53.69772 48.42686 0 0 1 - 1712 544 14 0.417 60.03677 54.31581 49.00644 0 0 1 - 1713 544 14 0.417 59.89364 52.94407 48.38216 0 0 1 - 1714 545 13 -0.834 63.04952 45.83903 48.97963 -1 1 1 - 1715 545 14 0.417 63.88202 45.63831 49.40729 -1 1 1 - 1716 545 14 0.417 62.76408 45.00498 48.60667 -1 1 1 - 1717 546 13 -0.834 40.62890 44.95273 52.60003 2 -1 -2 - 1718 546 14 0.417 41.29110 45.55853 52.26721 2 -1 -2 - 1719 546 14 0.417 40.33885 45.34348 53.42431 2 -1 -2 - 1720 547 13 -0.834 39.91743 46.12102 55.72693 -1 1 -1 - 1721 547 14 0.417 40.70381 45.68274 56.05216 -1 1 -1 - 1722 547 14 0.417 39.19323 45.65943 56.14967 -1 1 -1 - 1723 548 13 -0.834 42.06829 45.07566 41.79962 0 0 -1 - 1724 548 14 0.417 41.61985 45.91039 41.93531 0 0 -1 - 1725 548 14 0.417 41.86481 44.56390 42.58253 0 0 -1 - 1726 549 13 -0.834 44.17588 49.40877 37.86902 1 1 0 - 1727 549 14 0.417 43.85185 49.35470 38.76808 1 1 0 - 1728 549 14 0.417 43.95346 48.56183 37.48242 1 1 0 - 1729 550 13 -0.834 52.64793 63.92130 45.68237 0 1 0 - 1730 550 14 0.417 52.63502 62.96908 45.58561 0 1 0 - 1731 550 14 0.417 52.43571 64.07178 46.60356 0 1 0 - 1732 551 13 -0.834 51.57615 43.64864 38.83377 1 1 0 - 1733 551 14 0.417 51.74260 43.03820 38.11551 1 1 0 - 1734 551 14 0.417 52.20192 44.35945 38.69449 1 1 0 - 1735 552 13 -0.834 62.02099 63.12241 47.73587 0 1 0 - 1736 552 14 0.417 61.17806 62.75352 47.99973 0 1 0 - 1737 552 14 0.417 62.48263 62.39363 47.32116 0 1 0 - 1738 553 13 -0.834 38.41497 51.40373 50.93034 1 1 0 - 1739 553 14 0.417 37.60807 51.12879 50.49494 1 1 0 - 1740 553 14 0.417 38.99796 51.65996 50.21571 1 1 0 - 1741 554 13 -0.834 51.96339 44.25313 49.02477 0 0 0 - 1742 554 14 0.417 52.81680 44.60151 49.28274 0 0 0 - 1743 554 14 0.417 52.16570 43.57682 48.37831 0 0 0 - 1744 555 13 -0.834 43.58422 51.42052 49.88959 0 1 -1 - 1745 555 14 0.417 42.74054 51.00549 50.06897 0 1 -1 - 1746 555 14 0.417 44.20160 50.69175 49.82657 0 1 -1 - 1747 556 13 -0.834 52.39836 53.43568 49.29165 1 0 -1 - 1748 556 14 0.417 51.88756 52.90169 48.68323 1 0 -1 - 1749 556 14 0.417 52.64451 54.20889 48.78391 1 0 -1 - 1750 557 13 -0.834 57.76885 46.61656 49.32842 0 1 0 - 1751 557 14 0.417 57.83718 46.26991 48.43879 0 1 0 - 1752 557 14 0.417 58.65246 46.53329 49.68694 0 1 0 - 1753 558 13 -0.834 59.20868 56.75211 36.79427 0 1 -1 - 1754 558 14 0.417 59.74268 56.20033 36.22276 0 1 -1 - 1755 558 14 0.417 58.75094 56.13459 37.36470 0 1 -1 - 1756 559 13 -0.834 51.74055 42.45875 36.24184 0 1 1 - 1757 559 14 0.417 51.04879 41.79745 36.22260 0 1 1 - 1758 559 14 0.417 52.52794 41.99055 35.96429 0 1 1 - 1759 560 13 -0.834 56.37631 67.32150 33.05439 -1 0 1 - 1760 560 14 0.417 56.52797 66.39716 33.25152 -1 0 1 - 1761 560 14 0.417 56.88845 67.79399 33.71068 -1 0 1 - 1762 561 13 -0.834 54.61713 62.99597 56.69158 0 1 -1 - 1763 561 14 0.417 54.59393 63.94258 56.83172 0 1 -1 - 1764 561 14 0.417 54.12883 62.86158 55.87934 0 1 -1 - 1765 562 13 -0.834 59.12420 67.78462 34.49420 0 -1 1 - 1766 562 14 0.417 59.61921 67.94665 33.69111 0 -1 1 - 1767 562 14 0.417 59.22686 41.21594 35.00547 0 0 1 - 1768 563 13 -0.834 63.35827 53.14027 38.43168 -1 0 0 - 1769 563 14 0.417 62.48186 53.05933 38.05538 -1 0 0 - 1770 563 14 0.417 63.87715 53.55740 37.74392 -1 0 0 - 1771 564 13 -0.834 50.05518 64.80335 44.94078 1 0 -2 - 1772 564 14 0.417 50.16173 65.71408 44.66608 1 0 -2 - 1773 564 14 0.417 50.94818 64.48993 45.08424 1 0 -2 - 1774 565 13 -0.834 61.91076 61.67486 44.00650 0 -3 0 - 1775 565 14 0.417 61.40514 60.86646 44.09077 0 -3 0 - 1776 565 14 0.417 62.58390 61.60857 44.68380 0 -3 0 - 1777 566 13 -0.834 61.53884 41.33016 50.02212 -1 0 -1 - 1778 566 14 0.417 61.75835 68.35836 49.15591 -1 -1 -1 - 1779 566 14 0.417 62.19075 42.01255 50.18215 -1 0 -1 - 1780 567 13 -0.834 54.81641 49.94673 49.66324 0 -1 -1 - 1781 567 14 0.417 54.81533 50.72359 50.22249 0 -1 -1 - 1782 567 14 0.417 53.94410 49.93341 49.26932 0 -1 -1 - 1783 568 13 -0.834 60.68933 64.00249 53.56679 -1 -1 -1 - 1784 568 14 0.417 60.72666 63.10922 53.90872 -1 -1 -1 - 1785 568 14 0.417 60.37485 64.52808 54.30238 -1 -1 -1 - 1786 569 13 -0.834 55.51605 42.60469 53.96890 0 -1 0 - 1787 569 14 0.417 55.82084 42.66633 53.06360 0 -1 0 - 1788 569 14 0.417 54.99565 43.39708 54.10137 0 -1 0 - 1789 570 13 -0.834 43.79008 68.23755 52.31171 2 -1 1 - 1790 570 14 0.417 43.47705 41.06627 51.42954 2 0 1 - 1791 570 14 0.417 44.72624 68.07073 52.20206 2 -1 1 - 1792 571 13 -0.834 40.19615 44.94623 32.57234 0 0 1 - 1793 571 14 0.417 40.90940 45.49825 32.25173 0 0 1 - 1794 571 14 0.417 40.42796 44.75889 33.48196 0 0 1 - 1795 572 13 -0.834 51.93921 56.60019 36.60262 -1 0 1 - 1796 572 14 0.417 51.78399 56.35099 37.51368 -1 0 1 - 1797 572 14 0.417 51.06469 56.74242 36.24039 -1 0 1 - 1798 573 13 -0.834 61.66916 50.48338 53.29865 -1 0 -2 - 1799 573 14 0.417 61.63036 50.41309 54.25248 -1 0 -2 - 1800 573 14 0.417 60.77283 50.69388 53.03687 -1 0 -2 - 1801 574 13 -0.834 51.74160 54.87485 56.16871 0 -1 0 - 1802 574 14 0.417 50.91429 55.26706 56.44795 0 -1 0 - 1803 574 14 0.417 51.91124 55.25931 55.30869 0 -1 0 - 1804 575 13 -0.834 40.85698 68.18248 30.13155 1 -1 0 - 1805 575 14 0.417 41.30492 67.87357 56.71541 1 -1 -1 - 1806 575 14 0.417 41.55175 41.19073 30.66952 1 0 0 - 1807 576 13 -0.834 50.89809 58.89690 54.50288 -1 0 0 - 1808 576 14 0.417 50.06229 58.64352 54.89466 -1 0 0 - 1809 576 14 0.417 51.37024 59.33797 55.20914 -1 0 0 - 1810 577 13 -0.834 58.37524 67.95427 49.91095 0 1 0 - 1811 577 14 0.417 57.83519 41.29391 50.25604 0 2 0 - 1812 577 14 0.417 59.26942 68.19076 50.15744 0 1 0 - 1813 578 13 -0.834 51.40785 46.48357 30.68744 1 0 1 - 1814 578 14 0.417 52.21871 45.99275 30.55389 1 0 1 - 1815 578 14 0.417 50.76683 45.82189 30.94725 1 0 1 - 1816 579 13 -0.834 57.04032 43.52295 36.91237 0 0 0 - 1817 579 14 0.417 56.97310 44.35969 36.45239 0 0 0 - 1818 579 14 0.417 57.91622 43.53095 37.29833 0 0 0 - 1819 580 13 -0.834 48.05479 47.92450 33.11226 0 0 1 - 1820 580 14 0.417 47.68291 48.79527 32.97186 0 0 1 - 1821 580 14 0.417 48.92592 48.09081 33.47242 0 0 1 - 1822 581 13 -0.834 52.31083 59.89064 56.95945 1 -2 -1 - 1823 581 14 0.417 51.77727 60.32576 30.25310 1 -2 0 - 1824 581 14 0.417 52.84806 60.59010 56.58744 1 -2 -1 - 1825 582 13 -0.834 49.28190 53.14534 38.62511 0 0 1 - 1826 582 14 0.417 48.56647 53.70668 38.92395 0 0 1 - 1827 582 14 0.417 48.86634 52.52585 38.02526 0 0 1 - 1828 583 13 -0.834 48.15214 51.90611 34.43290 2 0 0 - 1829 583 14 0.417 48.57405 51.97443 33.57642 2 0 0 - 1830 583 14 0.417 47.22654 51.76503 34.23389 2 0 0 - 1831 584 13 -0.834 61.27546 54.09168 30.34511 0 1 1 - 1832 584 14 0.417 61.26898 53.84689 31.27046 0 1 1 - 1833 584 14 0.417 62.02427 53.62196 29.97785 0 1 1 - 1834 585 13 -0.834 47.15916 50.47662 53.78471 0 -1 0 - 1835 585 14 0.417 47.32648 50.93912 54.60588 0 -1 0 - 1836 585 14 0.417 46.29671 50.78520 53.50690 0 -1 0 - 1837 586 13 -0.834 58.58091 63.09753 49.23949 0 -1 1 - 1838 586 14 0.417 59.43607 63.50227 49.38484 0 -1 1 - 1839 586 14 0.417 58.76326 62.34843 48.67219 0 -1 1 - 1840 587 13 -0.834 55.82082 49.65937 30.11648 0 1 1 - 1841 587 14 0.417 56.52757 49.92139 30.70647 0 1 1 - 1842 587 14 0.417 55.68213 50.42183 56.92602 0 1 0 - 1843 588 13 -0.834 63.79581 52.53565 53.17702 0 -2 1 - 1844 588 14 0.417 36.89869 52.41207 52.35479 1 -2 1 - 1845 588 14 0.417 63.12882 51.84908 53.17487 0 -2 1 - 1846 589 13 -0.834 58.30874 56.36537 43.52715 0 0 3 - 1847 589 14 0.417 58.58025 56.80205 44.33452 0 0 3 - 1848 589 14 0.417 57.40732 56.09029 43.69457 0 0 3 - 1849 590 13 -0.834 38.42652 61.06904 33.48425 0 -2 -1 - 1850 590 14 0.417 39.08604 61.75763 33.56856 0 -2 -1 - 1851 590 14 0.417 38.90648 60.25628 33.64334 0 -2 -1 - 1852 591 13 -0.834 46.61439 51.58566 41.81121 1 -1 0 - 1853 591 14 0.417 46.97646 51.37067 42.67082 1 -1 0 - 1854 591 14 0.417 46.41089 50.73724 41.41750 1 -1 0 - 1855 592 13 -0.834 60.01555 43.31814 42.71405 1 0 1 - 1856 592 14 0.417 60.52150 42.79903 43.33920 1 0 1 - 1857 592 14 0.417 59.90024 42.74003 41.95989 1 0 1 - 1858 593 13 -0.834 44.88246 59.34852 51.75271 1 0 -1 - 1859 593 14 0.417 45.75263 59.37400 52.15069 1 0 -1 - 1860 593 14 0.417 44.67274 58.41644 51.69374 1 0 -1 - 1861 594 13 -0.834 58.22051 53.10280 51.15729 0 -1 0 - 1862 594 14 0.417 58.53381 52.60654 51.91346 0 -1 0 - 1863 594 14 0.417 58.92607 53.72100 50.96688 0 -1 0 - 1864 595 13 -0.834 52.85332 67.67658 42.66705 0 -1 0 - 1865 595 14 0.417 53.29462 67.40699 41.86157 0 -1 0 - 1866 595 14 0.417 53.28090 67.16860 43.35652 0 -1 0 - 1867 596 13 -0.834 60.42773 53.38162 37.56585 0 0 1 - 1868 596 14 0.417 60.55482 53.97513 38.30601 0 0 1 - 1869 596 14 0.417 59.53313 53.05721 37.66924 0 0 1 - 1870 597 13 -0.834 56.52028 65.87791 50.38146 0 0 1 - 1871 597 14 0.417 56.94337 66.73645 50.39389 0 0 1 - 1872 597 14 0.417 57.02985 65.35034 50.99649 0 0 1 - 1873 598 13 -0.834 54.80064 62.49993 33.68680 1 0 1 - 1874 598 14 0.417 55.58425 61.96146 33.79744 1 0 1 - 1875 598 14 0.417 55.10591 63.27334 33.21259 1 0 1 - 1876 599 13 -0.834 44.11783 61.90196 34.52932 1 1 -1 - 1877 599 14 0.417 44.98641 61.86349 34.92975 1 1 -1 - 1878 599 14 0.417 44.21923 61.44892 33.69223 1 1 -1 - 1879 600 13 -0.834 47.64060 51.80694 44.33090 -1 -1 0 - 1880 600 14 0.417 48.33775 51.24158 44.66345 -1 -1 0 - 1881 600 14 0.417 47.96940 52.69619 44.46262 -1 -1 0 - 1882 601 13 -0.834 56.93644 64.17109 32.73010 0 -2 0 - 1883 601 14 0.417 57.35484 63.79547 31.95543 0 -2 0 - 1884 601 14 0.417 57.46604 63.85913 33.46389 0 -2 0 - 1885 602 13 -0.834 40.19928 60.95715 53.68963 1 0 -1 - 1886 602 14 0.417 41.08822 60.76154 53.39341 1 0 -1 - 1887 602 14 0.417 39.80336 61.43545 52.96114 1 0 -1 - 1888 603 13 -0.834 56.02366 41.52320 41.07986 0 1 0 - 1889 603 14 0.417 55.42766 41.48842 40.33165 0 1 0 - 1890 603 14 0.417 55.93467 42.41489 41.41631 0 1 0 - 1891 604 13 -0.834 52.35261 67.43639 29.83633 -1 0 0 - 1892 604 14 0.417 53.08703 67.77971 56.69878 -1 0 -1 - 1893 604 14 0.417 51.97673 68.20568 30.26426 -1 0 0 - 1894 605 13 -0.834 51.14102 49.90060 37.90539 1 0 1 - 1895 605 14 0.417 51.41236 49.08269 37.48865 1 0 1 - 1896 605 14 0.417 50.32915 50.13989 37.45830 1 0 1 - 1897 606 13 -0.834 48.40753 57.18555 40.43062 0 0 0 - 1898 606 14 0.417 47.74030 57.19949 39.74445 0 0 0 - 1899 606 14 0.417 48.68357 58.09814 40.51553 0 0 0 - 1900 607 13 -0.834 38.43185 54.52830 40.23522 1 -2 1 - 1901 607 14 0.417 37.76601 54.24704 40.86274 1 -2 1 - 1902 607 14 0.417 37.95756 54.62565 39.40951 1 -2 1 - 1903 608 13 -0.834 52.97765 52.38562 41.57118 0 0 0 - 1904 608 14 0.417 52.16773 52.00413 41.23247 0 0 0 - 1905 608 14 0.417 53.62059 51.67937 41.50742 0 0 0 - 1906 609 13 -0.834 52.82978 61.35779 35.40768 0 1 -2 - 1907 609 14 0.417 53.63682 61.71145 35.03372 0 1 -2 - 1908 609 14 0.417 53.10766 60.57217 35.87865 0 1 -2 - 1909 610 13 -0.834 55.37636 43.79165 30.66790 0 0 0 - 1910 610 14 0.417 55.82860 43.25432 31.31827 0 0 0 - 1911 610 14 0.417 55.97415 44.52040 30.50110 0 0 0 - 1912 611 13 -0.834 37.90570 54.55715 45.50029 1 -2 -1 - 1913 611 14 0.417 37.12871 54.09851 45.18066 1 -2 -1 - 1914 611 14 0.417 38.24821 53.99402 46.19441 1 -2 -1 - 1915 612 13 -0.834 60.01324 50.96528 45.16358 1 1 0 - 1916 612 14 0.417 59.85669 51.13906 44.23539 1 1 0 - 1917 612 14 0.417 59.48415 50.19096 45.35532 1 1 0 - 1918 613 13 -0.834 38.84394 52.32942 30.93040 2 1 0 - 1919 613 14 0.417 38.51878 51.61086 30.38802 2 1 0 - 1920 613 14 0.417 38.41000 53.10831 30.58218 2 1 0 - 1921 614 13 -0.834 38.99542 61.66171 44.80992 1 0 2 - 1922 614 14 0.417 38.78488 60.74588 44.99207 1 0 2 - 1923 614 14 0.417 39.68427 61.62223 44.14648 1 0 2 - 1924 615 13 -0.834 57.70791 41.72720 55.47643 0 1 -2 - 1925 615 14 0.417 57.25844 41.36846 56.24163 0 1 -2 - 1926 615 14 0.417 57.00496 41.93588 54.86116 0 1 -2 - 1927 616 13 -0.834 58.08999 54.20225 35.53764 0 -1 0 - 1928 616 14 0.417 58.28608 53.46338 36.11372 0 -1 0 - 1929 616 14 0.417 57.15628 54.11553 35.34551 0 -1 0 - 1930 617 13 -0.834 53.05217 52.71850 54.07873 0 0 -1 - 1931 617 14 0.417 52.72353 53.45661 54.59199 0 0 -1 - 1932 617 14 0.417 52.69237 51.94509 54.51306 0 0 -1 - 1933 618 13 -0.834 49.92059 65.13477 35.13462 0 1 1 - 1934 618 14 0.417 50.86780 65.25694 35.19866 0 1 1 - 1935 618 14 0.417 49.79534 64.18846 35.20565 0 1 1 - 1936 619 13 -0.834 41.32410 62.50943 46.98364 1 -1 0 - 1937 619 14 0.417 40.63048 62.20572 46.39807 1 -1 0 - 1938 619 14 0.417 41.96090 61.79482 46.99226 1 -1 0 - 1939 620 13 -0.834 53.94559 67.39201 49.11860 0 0 0 - 1940 620 14 0.417 54.46912 66.60137 48.98810 0 0 0 - 1941 620 14 0.417 54.03461 67.58755 50.05138 0 0 0 - 1942 621 13 -0.834 62.73724 52.28919 56.37358 -2 0 0 - 1943 621 14 0.417 61.94239 51.76764 56.26203 -2 0 0 - 1944 621 14 0.417 63.44036 51.64333 56.44233 -2 0 0 - 1945 622 13 -0.834 40.38118 67.16060 39.18721 2 1 1 - 1946 622 14 0.417 41.33280 67.21360 39.09858 2 1 1 - 1947 622 14 0.417 40.05780 67.12713 38.28691 2 1 1 - 1948 623 13 -0.834 62.86517 42.00727 34.57539 -1 0 -1 - 1949 623 14 0.417 63.37239 42.81882 34.59420 -1 0 -1 - 1950 623 14 0.417 63.40838 41.39624 34.07760 -1 0 -1 - 1951 624 13 -0.834 45.52270 49.32960 34.34348 1 -1 1 - 1952 624 14 0.417 45.92383 49.19413 33.48500 1 -1 1 - 1953 624 14 0.417 45.24004 50.24407 34.33468 1 -1 1 - 1954 625 13 -0.834 61.03811 44.77668 56.49913 1 1 0 - 1955 625 14 0.417 60.72892 43.87199 56.45248 1 1 0 - 1956 625 14 0.417 60.93423 45.11202 55.60864 1 1 0 - 1957 626 13 -0.834 37.82896 51.65548 39.75440 0 1 1 - 1958 626 14 0.417 37.05574 52.05171 39.35268 0 1 1 - 1959 626 14 0.417 38.46628 52.36806 39.80236 0 1 1 - 1960 627 13 -0.834 57.87448 65.36125 35.56679 -1 -1 0 - 1961 627 14 0.417 58.45940 64.84211 35.01489 -1 -1 0 - 1962 627 14 0.417 58.01580 66.26448 35.28319 -1 -1 0 - 1963 628 13 -0.834 41.02352 64.37669 36.41484 0 0 1 - 1964 628 14 0.417 40.85775 63.95254 37.25679 0 0 1 - 1965 628 14 0.417 41.32667 63.66948 35.84545 0 0 1 - 1966 629 13 -0.834 48.62923 67.86173 41.06030 1 0 1 - 1967 629 14 0.417 48.15680 41.13844 41.58283 1 1 1 - 1968 629 14 0.417 47.94185 67.35115 40.63246 1 0 1 - 1969 630 13 -0.834 57.99331 55.69311 47.88478 1 2 0 - 1970 630 14 0.417 57.70999 55.65425 48.79826 1 2 0 - 1971 630 14 0.417 57.37284 55.13407 47.41709 1 2 0 - 1972 631 13 -0.834 48.67013 62.47689 45.75332 -1 -1 0 - 1973 631 14 0.417 49.00300 63.35392 45.56291 -1 -1 0 - 1974 631 14 0.417 48.17776 62.23177 44.96992 -1 -1 0 - 1975 632 13 -0.834 63.70160 54.96100 33.30497 -1 0 0 - 1976 632 14 0.417 64.21034 55.41699 32.63452 -1 0 0 - 1977 632 14 0.417 36.84822 54.18301 33.51151 0 0 0 - 1978 633 13 -0.834 61.71933 50.02843 40.52579 1 0 -1 - 1979 633 14 0.417 61.89605 49.89083 39.59516 1 0 -1 - 1980 633 14 0.417 61.20325 50.83404 40.55551 1 0 -1 - 1981 634 13 -0.834 49.51254 64.46386 53.41539 0 -1 -1 - 1982 634 14 0.417 48.93704 63.81647 53.00803 0 -1 -1 - 1983 634 14 0.417 49.96102 63.98252 54.11066 0 -1 -1 - 1984 635 13 -0.834 49.54405 44.64373 31.53722 1 2 1 - 1985 635 14 0.417 49.17415 44.45447 32.39954 1 2 1 - 1986 635 14 0.417 48.78808 44.87386 30.99705 1 2 1 - 1987 636 13 -0.834 55.54392 65.92737 37.61921 0 -1 -1 - 1988 636 14 0.417 56.11408 65.75233 38.36791 0 -1 -1 - 1989 636 14 0.417 56.12096 66.32174 36.96519 0 -1 -1 - 1990 637 13 -0.834 55.12269 51.83986 35.86341 1 0 1 - 1991 637 14 0.417 55.56426 51.26412 35.23910 1 0 1 - 1992 637 14 0.417 54.23658 51.93728 35.51477 1 0 1 - 1993 638 13 -0.834 55.63681 62.23759 37.50835 1 -1 0 - 1994 638 14 0.417 55.30920 61.35525 37.33403 1 -1 0 - 1995 638 14 0.417 56.23965 62.41667 36.78672 1 -1 0 - 1996 639 13 -0.834 39.91450 42.04260 35.59226 0 0 0 - 1997 639 14 0.417 39.72903 41.27571 36.13422 0 0 0 - 1998 639 14 0.417 39.23583 42.02933 34.91737 0 0 0 - 1999 640 13 -0.834 48.26433 59.84813 40.16126 0 1 0 - 2000 640 14 0.417 48.74870 60.67004 40.23938 0 1 0 - 2001 640 14 0.417 47.50743 60.06639 39.61748 0 1 0 - 2002 641 13 -0.834 57.35097 49.28414 48.37687 1 1 1 - 2003 641 14 0.417 57.35715 48.51028 48.94022 1 1 1 - 2004 641 14 0.417 56.55074 49.75049 48.61854 1 1 1 - -Velocities - - 1 -0.000671 -0.002823 0.003832 - 2 -0.001597 0.002405 -0.003777 - 3 0.005494 0.003807 -0.002300 - 4 -0.000077 0.004524 -0.000287 - 5 0.003116 -0.007135 -0.034325 - 6 -0.006676 0.004889 -0.001939 - 7 0.003499 -0.004774 0.000159 - 8 -0.003460 0.000694 0.000994 - 9 -0.000065 -0.001353 -0.002848 - 10 -0.001260 -0.002649 0.000699 - 11 -0.002820 -0.002457 -0.005671 - 12 0.005156 -0.005914 0.000984 - 13 -0.002342 -0.001592 0.004306 - 14 0.004397 -0.000231 0.003308 - 15 -0.003258 -0.000006 0.001838 - 16 -0.001637 -0.004429 0.003154 - 17 0.007073 -0.000472 -0.003331 - 18 -0.003380 -0.001390 0.005013 - 19 -0.011019 -0.005332 -0.010451 - 20 -0.005433 0.000844 0.004938 - 21 0.002988 0.000244 -0.009941 - 22 -0.003695 0.006546 -0.007678 - 23 0.009473 0.023276 0.019457 - 24 -0.010016 -0.024193 0.018017 - 25 0.004015 0.008726 -0.000397 - 26 -0.001741 -0.001861 0.007862 - 27 -0.009771 -0.011577 -0.005703 - 28 0.003573 0.006265 -0.005932 - 29 0.004789 0.001987 -0.004620 - 30 0.008858 -0.001064 -0.001455 - 31 -0.001403 0.000613 0.002330 - 32 -0.005808 -0.001620 0.000816 - 33 -0.004160 0.001188 -0.019638 - 34 -0.006899 0.006285 0.013256 - 35 0.000717 -0.000432 -0.006883 - 36 0.002110 0.002628 -0.004683 - 37 0.000765 -0.007298 0.000289 - 38 -0.000128 -0.002893 0.004065 - 39 -0.000411 -0.021741 0.010968 - 40 0.002858 0.000302 0.000042 - 41 0.014233 -0.004599 -0.004060 - 42 -0.001473 -0.003572 -0.006228 - 43 0.009129 -0.002755 0.001456 - 44 0.003931 0.000151 0.003472 - 45 0.001621 0.005391 -0.006087 - 46 -0.004269 -0.001973 0.002735 - 47 -0.006898 -0.001187 -0.003394 - 48 -0.008556 -0.000163 -0.001387 - 49 -0.000633 -0.001754 0.011460 - 50 0.004854 -0.002902 -0.005057 - 51 0.000678 0.003272 0.006218 - 52 0.006502 0.006365 -0.000215 - 53 0.005708 0.012368 0.002955 - 54 0.008627 -0.007839 0.003177 - 55 0.004394 0.000132 0.002346 - 56 -0.004641 0.009426 -0.005548 - 57 -0.004801 -0.024766 0.002851 - 58 -0.002703 0.001589 0.007521 - 59 0.023718 -0.006559 0.003743 - 60 -0.010013 -0.042894 -0.029745 - 61 0.016140 -0.000721 -0.001747 - 62 -0.004871 0.002439 0.001990 - 63 0.009632 0.007144 0.001203 - 64 -0.001150 0.001648 -0.003018 - 65 0.006658 -0.002268 0.006874 - 66 -0.002617 0.003321 0.002230 - 67 -0.000803 0.002802 0.003258 - 68 -0.000984 -0.001579 -0.001813 - 69 0.001316 0.000607 0.003431 - 70 -0.010901 0.000580 -0.004134 - 71 0.005370 -0.003909 0.013130 - 72 -0.012282 0.007114 -0.015100 - 73 0.004641 -0.007554 0.004302 - 74 0.017455 0.013344 0.004896 - 75 0.006200 0.026885 0.020665 - 76 -0.010372 0.000470 -0.005601 - 77 -0.003368 -0.004484 0.010962 - 78 0.012416 -0.004728 0.000719 - 79 -0.005789 0.005198 -0.007541 - 80 0.005480 -0.004049 0.003455 - 81 -0.004935 0.005839 -0.006405 - 82 0.001157 -0.011200 0.018491 - 83 -0.029013 -0.016935 0.021131 - 84 -0.020335 0.020972 0.006071 - 85 0.003304 0.007374 -0.005056 - 86 0.029227 0.010776 -0.013183 - 87 0.001651 0.006570 -0.002085 - 88 0.001533 -0.009172 0.007562 - 89 0.018153 -0.022223 0.015786 - 90 -0.010012 -0.004911 0.002561 - 91 0.000435 0.003941 -0.005468 - 92 0.003301 0.001183 -0.006999 - 93 0.006788 0.011331 -0.004427 - 94 0.001392 0.005663 -0.002907 - 95 -0.001849 -0.002229 -0.003422 - 96 -0.000820 0.005872 0.004561 - 97 -0.003264 0.002461 -0.009257 - 98 0.000160 0.016954 -0.015355 - 99 -0.006597 0.011858 0.000426 - 100 0.001816 -0.005854 -0.001317 - 101 -0.001936 -0.006103 0.018111 - 102 0.024621 -0.022735 -0.000704 - 103 -0.001102 0.008384 -0.003086 - 104 0.012559 0.004375 -0.000361 - 105 0.008377 0.014814 -0.037755 - 106 -0.002851 -0.000200 -0.000722 - 107 0.010701 0.006888 -0.007831 - 108 -0.008490 0.011514 0.009399 - 109 -0.001181 0.001853 0.002176 - 110 -0.018912 -0.023868 0.006706 - 111 -0.000415 -0.001525 0.005751 - 112 -0.001172 0.001329 -0.001270 - 113 -0.006700 -0.006243 -0.006459 - 114 0.000018 0.001429 0.001376 - 115 0.001269 0.002521 0.005249 - 116 -0.002179 0.015666 0.006861 - 117 -0.007158 0.000981 0.007353 - 118 0.001047 0.000840 -0.004404 - 119 0.000974 -0.012527 0.005053 - 120 0.026729 0.008884 -0.003350 - 121 0.001181 -0.004040 -0.002037 - 122 0.006556 -0.007438 0.002656 - 123 0.005056 -0.015002 -0.003727 - 124 -0.002704 -0.003683 -0.001021 - 125 0.025048 0.007258 0.008873 - 126 0.019645 -0.020824 -0.002539 - 127 0.000061 0.001072 0.002612 - 128 0.005132 0.013203 0.018763 - 129 0.033473 0.004804 0.018651 - 130 -0.003459 -0.000309 -0.001348 - 131 -0.008088 0.023660 0.011047 - 132 0.010962 0.031994 0.008711 - 133 0.000181 -0.002894 -0.001677 - 134 0.024049 -0.000711 -0.009405 - 135 0.018702 0.003422 -0.019522 - 136 -0.000836 -0.003270 -0.005700 - 137 0.012246 0.016524 0.001525 - 138 0.006270 -0.011288 0.002224 - 139 -0.005169 0.005097 -0.000688 - 140 -0.006982 0.003044 -0.001383 - 141 0.012227 0.012767 0.004047 - 142 -0.001169 0.006070 -0.007989 - 143 0.005451 0.002569 -0.009841 - 144 0.001825 -0.002822 -0.005341 - 145 0.000911 0.004242 -0.002026 - 146 0.012072 -0.001187 -0.010498 - 147 0.007366 0.005541 0.012099 - 148 0.009820 0.000588 0.001087 - 149 0.013758 0.005140 0.015262 - 150 0.015580 0.003311 0.013079 - 151 0.002031 0.000411 0.003403 - 152 -0.001996 0.003750 0.007387 - 153 0.000790 0.000281 -0.000919 - 154 -0.004168 0.001886 -0.004993 - 155 -0.011049 0.015294 0.001052 - 156 -0.012308 0.010348 -0.003128 - 157 -0.001609 -0.004040 -0.002294 - 158 -0.005715 -0.015529 -0.005700 - 159 0.014489 0.026653 0.004024 - 160 0.004070 0.000866 0.003373 - 161 0.004691 0.005062 0.002569 - 162 0.007082 -0.019961 -0.026174 - 163 0.005501 0.000902 -0.001325 - 164 0.007503 0.001448 -0.001472 - 165 0.013628 0.003649 -0.005952 - 166 -0.000639 0.003162 -0.007271 - 167 0.007342 -0.011001 -0.016849 - 168 -0.018400 -0.004772 0.020839 - 169 0.000214 -0.000386 0.002706 - 170 -0.005862 0.010449 -0.003793 - 171 -0.013612 0.011870 -0.006417 - 172 -0.005485 0.006465 0.005343 - 173 0.001788 0.008428 0.005641 - 174 -0.018354 0.029579 0.010717 - 175 0.002627 -0.000754 0.000071 - 176 -0.018080 0.018546 0.001794 - 177 0.006754 -0.000962 -0.007786 - 178 0.002343 0.002166 0.004945 - 179 -0.001724 0.003155 0.010761 - 180 0.010728 0.003441 0.001544 - 181 -0.000849 -0.002856 0.001461 - 182 0.009366 -0.003672 -0.001935 - 183 0.016615 -0.001746 0.005238 - 184 -0.002730 -0.000316 -0.004583 - 185 -0.014755 -0.011310 0.003338 - 186 0.005862 0.008235 -0.003200 - 187 -0.003189 -0.006285 0.009536 - 188 -0.005114 -0.007060 0.006450 - 189 -0.000516 -0.008757 0.009854 - 190 -0.000859 0.005266 0.001864 - 191 0.003108 -0.007021 0.009190 - 192 -0.015949 -0.002050 0.007021 - 193 -0.007008 0.002608 -0.004583 - 194 -0.020431 -0.004004 0.008047 - 195 -0.000364 0.001236 -0.011425 - 196 0.002420 0.006931 0.002031 - 197 0.007178 0.006129 0.009924 - 198 -0.005981 0.016623 -0.013067 - 199 0.003142 -0.001394 -0.001846 - 200 0.011374 -0.002895 -0.000674 - 201 0.032698 -0.002552 0.007288 - 202 -0.005709 0.000071 0.005037 - 203 -0.013193 -0.012592 -0.008102 - 204 -0.008194 0.014723 0.003840 - 205 -0.003270 -0.006146 0.004301 - 206 0.004399 -0.010132 -0.001197 - 207 -0.030308 0.012803 0.003540 - 208 0.002110 0.002374 0.006075 - 209 -0.000845 -0.004182 -0.002795 - 210 0.002582 -0.004671 0.002224 - 211 -0.003768 0.002130 0.001339 - 212 0.022509 0.017397 0.002782 - 213 0.020609 0.006682 -0.014082 - 214 0.003956 0.004282 -0.005023 - 215 0.007499 0.004128 0.002237 - 216 0.034882 -0.005096 0.008948 - 217 -0.002552 -0.000287 -0.001907 - 218 0.025445 0.005560 -0.016526 - 219 0.002741 0.000814 -0.004654 - 220 0.002162 -0.001203 0.000936 - 221 0.004071 0.004725 0.001938 - 222 0.002393 -0.013063 -0.003950 - 223 -0.001609 -0.003218 -0.004310 - 224 -0.012550 0.009033 -0.007868 - 225 0.014344 0.000886 -0.013005 - 226 0.005863 0.010335 -0.003424 - 227 0.011104 -0.005602 -0.012415 - 228 0.001222 0.002408 0.001546 - 229 -0.002038 0.001858 0.002991 - 230 -0.017517 -0.020932 0.016099 - 231 0.005257 0.011588 -0.018236 - 232 -0.002660 -0.006193 0.003186 - 233 -0.021995 0.012375 0.004372 - 234 -0.013906 0.028004 -0.004997 - 235 0.002339 -0.001255 -0.003548 - 236 0.001689 0.005243 -0.006337 - 237 0.000498 -0.007782 -0.015260 - 238 0.001142 0.002234 0.003408 - 239 0.007521 0.004622 -0.003272 - 240 -0.001154 0.006952 0.006739 - 241 -0.000938 -0.004609 0.002499 - 242 0.004903 0.001117 0.013021 - 243 0.008126 -0.013873 -0.001075 - 244 -0.004097 0.002491 -0.002459 - 245 0.002093 -0.002989 0.010881 - 246 0.008552 0.010436 0.008330 - 247 -0.000211 0.002295 0.001935 - 248 0.004346 0.003486 0.008405 - 249 -0.006182 0.002873 -0.007955 - 250 0.002466 0.001439 -0.002302 - 251 -0.003246 0.007233 0.009469 - 252 -0.002606 0.002646 0.002563 - 253 0.000833 -0.001794 -0.003483 - 254 -0.001066 -0.001277 -0.012569 - 255 -0.003354 -0.002604 -0.016130 - 256 0.007379 0.006324 -0.003535 - 257 0.025411 0.006788 -0.010928 - 258 0.011648 0.000201 0.004051 - 259 -0.000385 -0.000823 -0.000593 - 260 -0.001070 -0.019569 0.006235 - 261 0.011350 0.009136 0.002805 - 262 -0.001688 0.002178 0.004704 - 263 -0.011748 0.007674 0.002198 - 264 -0.005358 0.003728 -0.002879 - 265 -0.004209 0.000686 -0.004990 - 266 0.000586 0.011928 0.008080 - 267 0.004512 -0.002493 -0.000297 - 268 -0.000130 0.007801 -0.005732 - 269 -0.006259 -0.000991 -0.001515 - 270 0.015560 -0.011483 0.001826 - 271 -0.003544 0.003178 0.000326 - 272 0.006639 0.005731 0.008812 - 273 -0.009361 -0.001371 -0.002830 - 274 -0.000226 0.001739 0.001787 - 275 -0.001846 -0.005637 -0.002071 - 276 0.009461 0.005629 -0.001253 - 277 0.003294 -0.005377 -0.000680 - 278 0.027740 0.013288 0.002669 - 279 0.003403 0.012169 -0.019874 - 280 -0.001383 0.000386 -0.006636 - 281 -0.005910 0.003429 -0.006992 - 282 0.002649 -0.004178 -0.006969 - 283 0.004768 -0.001680 0.000104 - 284 -0.012916 0.017467 -0.012201 - 285 0.010278 -0.007970 0.003734 - 286 0.000005 0.000300 0.006224 - 287 0.003150 -0.001535 0.007443 - 288 -0.000547 -0.003737 0.010794 - 289 0.003054 0.005656 0.000426 - 290 0.006673 0.002252 0.007300 - 291 0.004185 0.001696 0.005292 - 292 -0.001277 -0.005156 -0.001765 - 293 0.005969 -0.004326 -0.002540 - 294 -0.026915 -0.005145 0.019233 - 295 -0.003352 -0.000356 -0.001610 - 296 -0.023375 -0.003718 -0.017075 - 297 0.006387 -0.025086 0.000315 - 298 -0.005064 0.001395 0.004436 - 299 -0.004111 0.000853 -0.032909 - 300 0.000933 0.005949 0.017391 - 301 0.000607 0.002490 -0.002786 - 302 0.002638 0.008857 0.008537 - 303 0.001294 0.011357 -0.003275 - 304 -0.001798 -0.003127 -0.000795 - 305 -0.003320 0.000996 0.004122 - 306 -0.008728 -0.000634 0.002033 - 307 -0.003535 -0.002662 -0.002777 - 308 -0.005954 -0.002781 -0.004403 - 309 -0.002147 -0.001477 -0.001223 - 310 -0.002595 -0.001397 0.002359 - 311 -0.003605 -0.000224 0.015269 - 312 -0.014002 -0.002828 0.000027 - 313 0.001583 -0.005357 0.002380 - 314 -0.002955 -0.014106 -0.011581 - 315 0.000151 -0.006411 0.002865 - 316 0.004278 -0.004088 0.000114 - 317 -0.019291 0.001584 0.015204 - 318 -0.013439 -0.000674 0.010987 - 319 0.000024 0.000995 0.005326 - 320 -0.009041 0.020464 0.014139 - 321 0.004208 -0.003482 0.004723 - 322 0.001489 -0.003292 0.000500 - 323 0.000364 0.006211 0.006844 - 324 0.007467 0.021162 -0.001636 - 325 0.009527 -0.000863 -0.005483 - 326 -0.009936 0.006496 -0.014136 - 327 -0.007595 -0.006469 -0.002090 - 328 -0.002856 -0.010388 -0.000678 - 329 -0.026693 -0.007624 -0.001572 - 330 0.029582 -0.010319 0.009090 - 331 -0.009062 0.000913 0.000368 - 332 -0.019327 0.020501 -0.000560 - 333 -0.018764 -0.008632 0.002570 - 334 0.004502 0.001200 -0.008087 - 335 0.008714 -0.005091 -0.008624 - 336 0.004610 0.003623 -0.007048 - 337 0.002461 -0.000759 0.003913 - 338 0.021591 -0.013925 0.009416 - 339 -0.017190 0.002325 0.006138 - 340 0.003361 0.004027 0.006986 - 341 0.006850 0.012752 0.018496 - 342 0.019589 0.009932 -0.004987 - 343 0.000463 0.005037 -0.000723 - 344 0.008333 0.006382 -0.005532 - 345 0.004288 0.006565 0.007800 - 346 -0.001505 -0.001295 0.001190 - 347 -0.015747 0.011253 0.025149 - 348 0.014871 -0.012646 -0.016815 - 349 -0.000186 0.002115 -0.002539 - 350 0.001936 0.000958 -0.003366 - 351 -0.014299 0.007078 -0.001653 - 352 -0.000876 -0.001637 -0.002032 - 353 -0.001168 0.005556 -0.012749 - 354 -0.003162 -0.016318 -0.009468 - 355 -0.000674 -0.001888 -0.003265 - 356 0.017652 -0.009515 0.007889 - 357 0.015313 -0.006079 0.010454 - 358 -0.000964 -0.004354 0.000067 - 359 0.004137 -0.002540 0.004500 - 360 -0.011376 -0.000921 -0.006123 - 361 0.002023 0.003210 -0.000511 - 362 0.012560 -0.011698 0.016109 - 363 -0.013295 -0.009379 -0.009014 - 364 0.003315 0.003249 0.007620 - 365 -0.010739 0.000915 -0.008118 - 366 -0.015293 0.007564 -0.004343 - 367 0.000192 0.002269 -0.000485 - 368 0.002520 -0.012494 -0.004632 - 369 0.010222 0.003093 -0.002247 - 370 0.003953 0.000628 0.004147 - 371 0.001165 -0.005271 0.007550 - 372 -0.013412 -0.019696 0.026961 - 373 0.001883 0.002252 -0.003560 - 374 0.005482 -0.004609 0.002380 - 375 -0.008048 0.004473 -0.008866 - 376 -0.002663 0.001073 0.001951 - 377 0.010178 0.018964 0.000820 - 378 0.007583 -0.018984 0.016464 - 379 0.001136 0.007646 0.002719 - 380 0.006251 0.008125 0.009187 - 381 0.001284 0.011634 -0.004097 - 382 -0.000767 0.000265 -0.000818 - 383 -0.000089 0.001579 -0.002300 - 384 -0.004565 -0.011251 0.008186 - 385 0.004778 -0.000871 0.002405 - 386 0.006618 -0.002801 0.006849 - 387 0.029884 -0.012377 0.019662 - 388 -0.002799 -0.005785 0.000693 - 389 -0.006988 0.014716 -0.008738 - 390 -0.003130 0.004832 0.002982 - 391 0.000036 -0.002467 0.000498 - 392 -0.001382 -0.006847 0.003863 - 393 -0.003623 0.001391 0.001664 - 394 0.004431 0.000182 0.002043 - 395 0.007177 -0.001675 0.008884 - 396 0.000324 0.003728 0.003379 - 397 0.004107 -0.000618 0.000098 - 398 0.019272 -0.008832 -0.013192 - 399 -0.025041 0.027976 -0.020594 - 400 0.002982 -0.002889 -0.005826 - 401 0.010564 -0.003899 -0.002078 - 402 0.005218 -0.003308 -0.010357 - 403 0.002304 -0.003833 -0.008812 - 404 -0.013421 -0.017603 -0.023172 - 405 -0.003134 -0.000582 0.001712 - 406 -0.003398 -0.002176 0.001635 - 407 -0.015813 0.008046 0.010515 - 408 0.003940 -0.004144 -0.002666 - 409 0.008428 -0.002203 -0.004077 - 410 -0.004859 0.004207 -0.016803 - 411 -0.022714 0.005614 0.004119 - 412 -0.000677 -0.000486 0.001019 - 413 0.004137 0.001524 0.004810 - 414 -0.011495 -0.003293 -0.002498 - 415 -0.004277 -0.004620 -0.002973 - 416 0.005727 -0.002611 0.021922 - 417 0.009759 0.016284 -0.017136 - 418 0.001140 -0.003169 0.001021 - 419 0.002072 0.019101 -0.019824 - 420 0.029356 -0.011686 0.004675 - 421 0.001175 0.002540 0.001846 - 422 0.009479 -0.017538 0.002696 - 423 0.008327 0.028039 -0.001246 - 424 0.002971 -0.004730 0.000069 - 425 0.010168 -0.005904 -0.016535 - 426 0.009223 0.011295 0.006248 - 427 -0.003323 0.000861 0.005020 - 428 -0.005244 0.001685 -0.001864 - 429 0.000994 0.014826 0.000976 - 430 -0.002795 0.003958 -0.004848 - 431 0.010698 -0.011688 -0.000537 - 432 0.008158 0.021591 -0.003259 - 433 0.000363 0.002223 0.004053 - 434 -0.002225 0.004315 -0.010042 - 435 -0.000151 -0.000572 0.000675 - 436 0.006996 -0.000559 0.003307 - 437 -0.011410 -0.004708 0.006782 - 438 -0.015909 0.022113 0.004877 - 439 -0.002401 -0.002279 0.002655 - 440 -0.002478 0.000164 0.005849 - 441 -0.003545 0.002314 0.007358 - 442 0.002189 0.006935 -0.001251 - 443 -0.007190 0.031224 0.006804 - 444 0.004661 -0.003296 0.013412 - 445 0.003709 0.001514 -0.003921 - 446 0.015678 0.007604 0.000133 - 447 -0.004648 -0.004474 -0.027064 - 448 0.001807 -0.004146 0.004203 - 449 0.029598 0.003434 0.012408 - 450 -0.004603 -0.006201 0.002287 - 451 -0.003031 -0.004136 -0.006564 - 452 0.009003 0.019264 0.004529 - 453 -0.000188 0.010449 0.001077 - 454 0.003891 0.002752 0.005629 - 455 0.001092 0.012776 0.008682 - 456 -0.002762 0.015371 -0.005857 - 457 0.002697 -0.003406 -0.002865 - 458 0.007823 -0.013511 0.002023 - 459 -0.030492 -0.008107 -0.020624 - 460 0.000483 0.001162 0.002651 - 461 0.002571 -0.007508 -0.009384 - 462 -0.010774 -0.027329 0.003619 - 463 0.005791 0.000086 0.004298 - 464 0.008820 0.016257 -0.002226 - 465 0.000317 -0.014932 -0.013621 - 466 0.003540 0.001551 -0.001349 - 467 0.008241 0.020014 0.019807 - 468 -0.004258 -0.010227 -0.029599 - 469 0.007640 0.001287 -0.003128 - 470 0.004600 -0.001555 -0.010230 - 471 0.007870 0.002461 0.000094 - 472 0.001001 0.005160 -0.001529 - 473 0.006073 0.015127 0.022819 - 474 0.006356 -0.012345 -0.003131 - 475 -0.005549 -0.000151 0.001312 - 476 -0.015747 0.009610 0.004075 - 477 0.009345 0.004620 -0.013632 - 478 -0.005694 -0.004777 0.002781 - 479 -0.015785 0.018249 0.008919 - 480 0.007264 0.001342 -0.012954 - 481 -0.002601 -0.003124 -0.001775 - 482 -0.010924 -0.002942 0.001676 - 483 0.020644 0.001519 0.001050 - 484 -0.003829 -0.001681 0.001973 - 485 -0.009248 -0.008096 0.002166 - 486 -0.004627 -0.003317 0.000426 - 487 0.004750 0.008629 -0.001691 - 488 -0.009177 0.001481 0.019567 - 489 -0.000748 -0.004703 -0.011184 - 490 -0.000930 -0.004032 -0.001796 - 491 -0.007051 -0.001375 -0.004647 - 492 -0.000505 0.005436 -0.004029 - 493 -0.000767 -0.000313 -0.004426 - 494 0.007019 0.022441 0.008035 - 495 0.002030 -0.018016 0.012244 - 496 -0.000430 -0.004092 0.001186 - 497 0.012447 -0.008156 0.016405 - 498 -0.008008 0.011043 -0.000527 - 499 0.001752 0.001451 -0.008850 - 500 -0.001696 0.002950 -0.000035 - 501 0.006054 -0.001180 -0.028952 - 502 0.001434 -0.008124 -0.001958 - 503 0.001762 -0.007034 -0.009244 - 504 -0.008796 -0.004759 -0.009928 - 505 0.000249 0.001170 0.006380 - 506 -0.005081 0.014461 -0.003259 - 507 -0.002522 0.001324 0.007841 - 508 0.003441 0.001538 0.006742 - 509 0.007735 -0.006583 0.003492 - 510 0.009681 0.006088 0.008608 - 511 -0.006695 -0.001970 0.000807 - 512 0.004268 0.004052 0.001263 - 513 -0.004129 -0.012886 -0.007489 - 514 -0.002878 0.001158 0.006535 - 515 -0.007680 -0.001896 0.002953 - 516 -0.000917 -0.006257 -0.002762 - 517 -0.001401 -0.003523 -0.005778 - 518 -0.001854 0.007834 0.015061 - 519 -0.010095 0.007049 -0.021128 - 520 -0.000766 -0.000153 0.007009 - 521 0.009064 -0.003223 0.017921 - 522 0.000864 -0.000043 0.007876 - 523 -0.001025 0.001319 -0.006573 - 524 -0.006395 0.000755 -0.002686 - 525 -0.032670 0.007943 0.004175 - 526 0.002953 0.006520 0.004065 - 527 0.009139 -0.008077 -0.010889 - 528 -0.002820 0.012454 -0.005504 - 529 -0.008727 0.003418 0.002451 - 530 -0.007112 -0.005703 0.023446 - 531 -0.011285 0.014165 -0.019563 - 532 -0.002562 0.003192 -0.002295 - 533 -0.003618 0.007211 0.002298 - 534 0.010325 0.001834 0.002853 - 535 0.002563 0.000345 -0.002878 - 536 0.002396 0.022293 -0.006961 - 537 0.001693 -0.002677 0.010576 - 538 -0.001561 0.000734 0.001793 - 539 -0.008542 0.015338 0.007321 - 540 -0.015880 0.015140 0.014642 - 541 0.001092 0.000090 0.000997 - 542 -0.004522 -0.004004 0.003687 - 543 0.003258 -0.006156 0.000500 - 544 -0.001608 0.002026 0.003790 - 545 -0.010430 -0.004583 0.015482 - 546 0.002628 0.011416 0.004923 - 547 -0.002068 0.005845 0.001850 - 548 0.001194 0.007931 0.007672 - 549 -0.020261 -0.007195 -0.008896 - 550 0.005399 0.001999 0.000211 - 551 0.004420 0.012603 0.006214 - 552 0.007790 0.005534 0.000006 - 553 -0.004249 0.001186 -0.000260 - 554 0.006385 -0.014925 0.000020 - 555 0.009902 0.016988 -0.004080 - 556 0.006637 -0.003469 0.000450 - 557 -0.002010 0.011423 -0.004361 - 558 -0.009074 0.013716 -0.002539 - 559 0.003243 -0.003710 -0.002565 - 560 -0.000480 -0.009433 0.000267 - 561 0.002981 -0.005587 -0.010088 - 562 0.002665 0.008169 0.002667 - 563 -0.001817 0.009035 0.022525 - 564 0.005689 0.010678 0.000603 - 565 0.003217 0.002617 0.001072 - 566 0.025108 0.001061 -0.027288 - 567 -0.003091 0.028727 0.028529 - 568 0.003991 -0.002246 0.002528 - 569 0.011195 -0.007917 0.010511 - 570 -0.006686 -0.007088 -0.000640 - 571 0.005302 0.003751 0.001484 - 572 0.001250 0.007658 -0.006666 - 573 0.018145 -0.005375 0.000139 - 574 -0.003857 0.003583 0.000238 - 575 0.006752 0.001063 0.004538 - 576 -0.006479 0.014326 -0.017669 - 577 0.001793 0.003661 0.002509 - 578 0.010186 -0.003147 0.008687 - 579 -0.001160 -0.005645 -0.003812 - 580 -0.002296 0.006997 0.000837 - 581 -0.031138 0.017223 0.000984 - 582 0.002587 -0.007480 0.015277 - 583 0.000288 -0.000668 0.001548 - 584 0.016041 -0.004051 0.004629 - 585 -0.025116 0.003224 0.009356 - 586 -0.000853 0.003188 0.004014 - 587 -0.001700 -0.004491 0.006716 - 588 -0.008947 -0.009004 -0.023328 - 589 0.005432 -0.003893 -0.001000 - 590 -0.019524 0.021049 -0.035976 - 591 0.009404 0.004475 -0.004525 - 592 -0.006508 -0.002709 0.000481 - 593 0.010852 -0.015643 0.005754 - 594 0.006526 0.026156 0.009018 - 595 -0.004611 -0.001841 0.002205 - 596 -0.013411 -0.011893 -0.011510 - 597 -0.002150 -0.000804 -0.006730 - 598 -0.002593 -0.000356 0.003104 - 599 0.009483 0.002951 -0.001362 - 600 -0.015523 -0.003843 0.010828 - 601 -0.001229 0.003953 0.000471 - 602 -0.017788 0.002114 0.033354 - 603 0.015187 -0.017947 -0.007994 - 604 -0.001335 -0.000196 0.007281 - 605 0.015188 0.007448 0.005030 - 606 -0.001538 0.002386 -0.009662 - 607 -0.001172 0.004261 0.002894 - 608 -0.002229 0.015661 0.009134 - 609 0.017428 0.004976 0.006974 - 610 -0.001490 0.003604 0.004586 - 611 -0.017720 0.006222 -0.023144 - 612 0.010016 -0.015847 -0.004678 - 613 -0.002648 0.000934 0.000698 - 614 -0.011832 0.016782 0.007626 - 615 -0.005427 0.001385 0.015386 - 616 0.003669 -0.001949 0.003946 - 617 0.005164 0.000243 0.009975 - 618 -0.000161 0.003111 0.001353 - 619 0.002976 -0.004733 0.001868 - 620 -0.002832 -0.014197 -0.023534 - 621 -0.003347 -0.011551 0.000693 - 622 0.004912 0.001701 -0.000793 - 623 0.013809 0.007164 -0.016905 - 624 0.024958 -0.010962 -0.008428 - 625 0.007422 -0.002948 -0.001308 - 626 -0.016590 -0.032000 -0.001025 - 627 0.011367 0.004098 0.010259 - 628 -0.002045 -0.000742 0.000577 - 629 -0.030845 0.001448 0.030396 - 630 0.001781 -0.017639 0.014980 - 631 0.002233 -0.004427 -0.002429 - 632 0.018586 -0.001402 0.006993 - 633 -0.012356 0.003736 0.007796 - 634 -0.004338 0.007766 0.000310 - 635 0.001990 0.000209 0.007107 - 636 -0.006343 0.005190 -0.018263 - 637 -0.005455 0.000492 -0.002847 - 638 0.000522 0.006495 0.003755 - 639 -0.001841 -0.009429 -0.001507 - 640 -0.002314 -0.002516 -0.005613 - 641 0.018652 0.002237 -0.015930 - 642 -0.002326 -0.000776 -0.003132 - 643 -0.005512 -0.000623 -0.000619 - 644 -0.001015 0.005882 0.003225 - 645 0.000586 0.023218 -0.004529 - 646 -0.001138 0.000800 0.002687 - 647 0.003627 0.013371 -0.016172 - 648 0.018968 0.017228 -0.000038 - 649 -0.002086 -0.000112 -0.007393 - 650 0.016103 0.035588 0.008775 - 651 -0.038516 0.012158 -0.009536 - 652 0.002958 0.004862 -0.007554 - 653 0.024333 0.013052 -0.023133 - 654 0.002379 -0.000049 -0.006601 - 655 0.003804 -0.003076 -0.001112 - 656 -0.004763 0.002283 -0.025897 - 657 -0.036538 -0.010672 -0.010599 - 658 -0.000713 0.003957 0.002151 - 659 -0.016531 0.001472 0.004862 - 660 -0.009287 0.028134 0.010480 - 661 0.004192 -0.003835 0.000568 - 662 0.011523 0.002433 0.036479 - 663 -0.009197 -0.041577 0.000393 - 664 0.000280 -0.002373 -0.004460 - 665 0.002206 -0.003211 0.000957 - 666 0.006211 0.013469 -0.005353 - 667 -0.000522 0.001664 -0.004748 - 668 0.004459 -0.024042 -0.023029 - 669 0.011377 0.013403 0.030836 - 670 0.003382 -0.002813 0.000451 - 671 0.000766 0.000074 -0.006820 - 672 0.013252 -0.015598 0.024274 - 673 -0.003243 0.006406 -0.002570 - 674 0.019962 -0.008888 -0.019769 - 675 -0.027628 -0.005508 -0.000297 - 676 -0.007770 -0.003882 0.002155 - 677 -0.001777 0.012358 0.000036 - 678 -0.024978 0.005564 -0.015024 - 679 0.000188 0.001017 0.004117 - 680 -0.006440 -0.003105 0.019733 - 681 -0.016780 0.005575 -0.004078 - 682 0.000151 0.001697 -0.001387 - 683 -0.002925 0.000955 -0.004378 - 684 0.000826 0.008069 0.003052 - 685 -0.003543 -0.000321 -0.000587 - 686 -0.012205 0.000432 -0.005990 - 687 0.004010 0.009678 -0.003793 - 688 0.001940 -0.000340 0.003900 - 689 0.005837 0.014815 -0.005621 - 690 -0.008710 -0.017653 0.020395 - 691 -0.001931 -0.003975 -0.002577 - 692 -0.003368 -0.014386 -0.006878 - 693 -0.013782 -0.002984 0.003522 - 694 0.004968 -0.000283 -0.003322 - 695 0.019160 0.006665 -0.007077 - 696 0.022604 -0.000847 -0.016983 - 697 0.002571 0.000550 -0.007379 - 698 -0.001443 -0.002487 -0.007727 - 699 -0.011487 -0.013883 0.019460 - 700 0.001096 -0.004750 0.003965 - 701 -0.016603 -0.010473 0.014272 - 702 0.023559 -0.001392 -0.008500 - 703 -0.002022 -0.005262 -0.004485 - 704 0.002332 -0.014942 -0.004917 - 705 -0.009402 0.006267 -0.002020 - 706 -0.000288 0.003264 -0.003564 - 707 0.004565 0.033122 -0.006655 - 708 -0.018922 -0.009521 0.000208 - 709 -0.003485 0.003285 -0.000556 - 710 0.004587 -0.002798 -0.000984 - 711 -0.006054 0.007231 -0.001425 - 712 0.004718 0.000201 -0.003948 - 713 -0.014114 0.009800 -0.004955 - 714 -0.008099 -0.004168 0.008689 - 715 0.000410 -0.000654 0.009605 - 716 0.008711 0.018707 0.002740 - 717 0.003459 -0.008185 0.010239 - 718 0.003479 0.000757 0.004467 - 719 0.000433 -0.000495 0.007710 - 720 0.012945 0.003286 -0.002052 - 721 -0.010010 -0.003567 0.006956 - 722 0.005307 -0.001615 -0.002198 - 723 -0.012515 0.011984 0.016669 - 724 0.001378 -0.002186 -0.001614 - 725 0.012587 -0.019891 0.012237 - 726 0.012601 0.007024 0.014776 - 727 -0.002983 -0.001722 -0.004228 - 728 0.015268 -0.011359 -0.002815 - 729 -0.003967 0.028638 0.000653 - 730 -0.000313 -0.000495 0.001546 - 731 -0.030938 -0.009463 -0.008649 - 732 -0.033474 -0.019299 0.015331 - 733 0.000845 -0.003919 -0.003202 - 734 -0.027178 0.011071 -0.026350 - 735 -0.007741 0.001470 -0.016184 - 736 -0.001239 0.001989 -0.002789 - 737 0.011285 0.001382 -0.006222 - 738 0.022813 -0.006205 -0.006536 - 739 0.003987 -0.004190 -0.005010 - 740 -0.007915 0.002670 -0.013878 - 741 0.004194 0.006086 -0.010350 - 742 0.006539 -0.005074 0.002196 - 743 0.015306 0.008181 0.005081 - 744 0.007865 0.003022 -0.004716 - 745 -0.001784 -0.010062 0.004309 - 746 -0.002378 -0.011275 0.006933 - 747 -0.008336 -0.001053 0.004620 - 748 -0.002979 0.004768 -0.002497 - 749 -0.000959 0.004004 -0.002600 - 750 -0.019512 -0.002978 0.005044 - 751 -0.004903 -0.000550 0.000659 - 752 -0.005086 0.005639 -0.022167 - 753 -0.008131 0.001631 -0.018889 - 754 -0.001761 -0.001628 0.000503 - 755 -0.003957 -0.007199 -0.006609 - 756 0.003155 -0.001306 0.005143 - 757 0.000937 0.008247 -0.008723 - 758 0.028994 0.004889 0.007225 - 759 -0.000469 -0.025903 0.001925 - 760 -0.001834 -0.000370 -0.001605 - 761 0.007234 -0.001225 -0.019036 - 762 -0.003442 -0.001966 0.000209 - 763 0.000445 0.007510 0.001158 - 764 -0.008348 0.004439 -0.007776 - 765 -0.012793 0.011539 0.019680 - 766 0.000065 -0.000962 -0.004032 - 767 -0.002013 -0.005477 0.003901 - 768 0.003529 0.021570 0.007224 - 769 -0.002661 0.002604 -0.003268 - 770 0.005668 -0.003962 -0.004196 - 771 -0.003633 0.008263 -0.012842 - 772 0.001811 0.001915 0.002764 - 773 0.007995 -0.017893 0.012738 - 774 -0.018466 -0.002519 -0.001997 - 775 -0.002231 0.000080 0.000338 - 776 -0.020092 -0.012422 0.010443 - 777 0.017610 0.006562 -0.019411 - 778 -0.001733 0.005494 0.004582 - 779 0.013495 0.017522 0.004058 - 780 0.014733 0.026971 -0.010419 - 781 0.001950 0.000577 -0.000870 - 782 -0.025830 0.001269 0.005271 - 783 0.007534 -0.015453 0.006553 - 784 0.004959 0.000931 -0.005022 - 785 -0.008754 0.005835 0.049441 - 786 0.010447 0.012462 0.001546 - 787 -0.001107 0.002522 0.000433 - 788 0.009871 0.011686 0.008446 - 789 -0.006988 0.002247 0.021211 - 790 0.004245 0.001822 -0.000253 - 791 0.000153 -0.002603 0.008675 - 792 0.006252 0.003177 -0.013109 - 793 -0.002534 0.003863 0.000617 - 794 -0.000057 0.004391 -0.016346 - 795 0.005974 -0.000584 -0.004834 - 796 0.001827 -0.002339 -0.002010 - 797 -0.023150 0.007693 0.012507 - 798 0.012203 0.000464 -0.020004 - 799 -0.000293 -0.001883 -0.002470 - 800 -0.004248 0.006084 0.002613 - 801 -0.013517 0.015693 0.003574 - 802 -0.009450 0.005229 -0.003400 - 803 -0.015058 -0.007700 0.001796 - 804 -0.000196 -0.003546 0.002537 - 805 0.008758 -0.003257 0.005431 - 806 0.012998 -0.011952 -0.017276 - 807 0.008558 -0.002765 0.006723 - 808 -0.001470 -0.000539 0.002965 - 809 0.024028 -0.019423 -0.012788 - 810 0.003892 0.003966 -0.001573 - 811 0.000254 0.001510 0.000089 - 812 0.024395 0.007424 -0.013783 - 813 0.006830 0.017138 0.017010 - 814 -0.001535 -0.003749 -0.001708 - 815 0.013748 -0.018314 -0.006646 - 816 0.003900 0.002047 0.006451 - 817 0.006585 0.003832 -0.000629 - 818 0.021540 0.003252 0.001280 - 819 0.007897 0.007247 -0.003727 - 820 -0.002115 -0.002434 -0.005025 - 821 -0.016735 0.003360 -0.019137 - 822 0.003237 -0.017804 -0.004111 - 823 -0.003907 0.002878 -0.003988 - 824 -0.005419 -0.002010 -0.004476 - 825 -0.006449 0.003104 -0.002766 - 826 -0.013638 -0.002258 -0.002448 - 827 -0.007838 0.000023 -0.005866 - 828 -0.006633 0.001312 -0.008943 - 829 0.001696 0.003761 -0.002125 - 830 -0.001113 -0.010288 -0.008692 - 831 0.010380 0.008838 -0.015548 - 832 -0.003164 0.004544 -0.002070 - 833 -0.001495 -0.013094 -0.000890 - 834 0.011945 -0.015741 -0.003378 - 835 -0.008802 -0.001939 -0.005442 - 836 -0.002949 -0.007279 -0.004665 - 837 0.008414 -0.021459 -0.000948 - 838 0.001330 0.000622 0.000916 - 839 -0.001965 0.001331 0.006138 - 840 0.003081 -0.004825 0.007272 - 841 0.001557 -0.005770 -0.001563 - 842 0.014285 0.020628 -0.029634 - 843 -0.006815 0.003616 0.008747 - 844 0.001116 -0.003881 -0.003556 - 845 0.008316 -0.005783 -0.005256 - 846 -0.011615 0.015346 0.026431 - 847 0.004309 0.003546 -0.004311 - 848 0.007868 -0.013572 0.000073 - 849 -0.011699 0.005875 0.003604 - 850 0.000505 -0.004069 -0.002113 - 851 0.001211 -0.005770 -0.003436 - 852 -0.004651 0.001028 0.007154 - 853 -0.003913 -0.006795 -0.004733 - 854 -0.004339 -0.014527 -0.023555 - 855 -0.006756 -0.006056 -0.008714 - 856 0.007493 0.001588 -0.006408 - 857 0.020526 0.022065 -0.006921 - 858 0.010862 0.004031 -0.001655 - 859 0.003459 -0.001125 -0.001494 - 860 -0.000710 0.004855 0.022662 - 861 -0.000022 0.009082 0.012428 - 862 -0.000591 0.002648 0.002517 - 863 0.017910 0.003993 0.005847 - 864 -0.004999 0.014284 -0.016199 - 865 -0.001700 -0.002300 0.001206 - 866 -0.016994 -0.008747 -0.012103 - 867 -0.008118 -0.008616 0.003715 - 868 -0.002056 -0.003732 -0.006667 - 869 -0.002586 -0.005666 -0.002032 - 870 -0.002179 -0.001361 -0.001378 - 871 0.001952 0.000747 -0.004175 - 872 -0.000006 -0.004573 0.003592 - 873 -0.004377 -0.012174 0.000091 - 874 -0.006945 -0.004708 0.004295 - 875 -0.011724 -0.010397 0.002368 - 876 0.006805 0.012734 0.019238 - 877 0.004959 0.005871 -0.001277 - 878 -0.012228 -0.000867 -0.006672 - 879 0.014516 0.032640 0.025985 - 880 0.000767 -0.000179 0.004816 - 881 0.006242 0.002132 0.007465 - 882 0.006812 0.003103 0.007707 - 883 0.005120 -0.003059 -0.001062 - 884 -0.008255 -0.016076 -0.002362 - 885 -0.001789 -0.014152 -0.001194 - 886 -0.009000 0.001340 0.001690 - 887 -0.020559 -0.017599 0.000329 - 888 -0.003544 -0.006539 0.004087 - 889 -0.000933 0.000538 -0.001999 - 890 0.032797 0.013397 0.000525 - 891 -0.012354 -0.008526 -0.038077 - 892 0.002953 -0.002317 -0.004454 - 893 -0.029479 -0.014864 0.005868 - 894 0.019223 0.000709 -0.013773 - 895 0.002346 -0.003694 -0.004486 - 896 -0.005275 -0.001221 -0.010755 - 897 0.010883 0.001918 -0.002099 - 898 -0.000263 -0.000830 0.005518 - 899 0.000399 -0.005578 0.011643 - 900 -0.007207 -0.006080 -0.006632 - 901 -0.000868 0.002637 -0.000416 - 902 -0.003601 0.001456 0.001019 - 903 0.003465 0.009000 0.002627 - 904 -0.005492 0.001153 0.005034 - 905 0.008501 0.009963 0.005133 - 906 0.002740 0.005510 0.005387 - 907 0.001230 0.003701 -0.010904 - 908 0.005640 0.000943 -0.026378 - 909 -0.001655 0.006661 0.001080 - 910 0.000417 -0.004485 0.000899 - 911 0.004051 -0.003590 0.002016 - 912 0.010109 -0.002124 0.001500 - 913 0.002439 0.006335 0.003103 - 914 -0.006325 0.005901 0.006397 - 915 0.008058 0.002545 0.004591 - 916 -0.001774 -0.003954 -0.005522 - 917 -0.001697 -0.002110 -0.006988 - 918 0.000641 -0.012660 -0.001878 - 919 0.000840 0.002158 -0.002127 - 920 -0.006972 -0.005865 -0.019536 - 921 -0.009078 -0.009093 0.005319 - 922 -0.002466 0.001612 -0.002348 - 923 -0.007997 0.000173 -0.007016 - 924 -0.005167 0.000122 -0.004809 - 925 0.000182 0.007626 -0.005820 - 926 -0.000187 0.006758 -0.004766 - 927 -0.005146 0.010941 -0.001145 - 928 -0.001035 0.003329 -0.000156 - 929 -0.002925 0.005286 0.005381 - 930 -0.007353 0.014383 0.015446 - 931 0.001566 0.003779 -0.001844 - 932 0.014111 -0.006162 0.016836 - 933 -0.008051 -0.000942 0.006114 - 934 0.000472 0.000581 0.003898 - 935 0.010438 -0.015336 0.026259 - 936 -0.009803 0.018803 -0.011113 - 937 -0.002622 0.001845 -0.004649 - 938 0.000192 0.006195 -0.003034 - 939 -0.004379 0.004856 -0.008876 - 940 0.005312 -0.005320 -0.000644 - 941 0.004197 0.002434 0.005873 - 942 0.001054 -0.002144 -0.009156 - 943 0.001818 0.002764 0.000410 - 944 0.002489 0.005354 -0.014128 - 945 0.003819 0.010472 0.007403 - 946 0.005262 -0.000699 0.001191 - 947 -0.002052 -0.008290 0.017377 - 948 -0.012921 -0.009037 0.007720 - 949 0.002875 -0.000206 -0.005514 - 950 0.004620 -0.003924 -0.007344 - 951 0.004396 0.015332 -0.008395 - 952 -0.001773 -0.005567 0.004807 - 953 0.014650 -0.004337 0.011316 - 954 0.007355 -0.004603 0.004796 - 955 0.001050 0.002663 -0.000049 - 956 -0.000422 0.019759 -0.003121 - 957 -0.011736 0.001700 0.005445 - 958 0.002314 -0.007359 0.001422 - 959 0.000226 -0.009157 0.011161 - 960 0.002971 -0.007641 -0.001658 - 961 0.002025 0.003310 0.000085 - 962 0.003783 0.005544 -0.002440 - 963 -0.003390 -0.001680 0.007759 - 964 -0.000259 -0.001517 -0.001671 - 965 -0.009891 -0.000275 0.002930 - 966 -0.004798 -0.018121 0.000493 - 967 0.002742 0.002196 0.002639 - 968 -0.032110 0.008681 0.017593 - 969 -0.005767 -0.003804 -0.003447 - 970 -0.001025 -0.001901 0.007377 - 971 -0.025416 -0.005633 -0.009650 - 972 -0.002448 -0.002342 0.009184 - 973 0.000510 -0.004313 0.003297 - 974 -0.004244 -0.006185 -0.015114 - 975 0.002817 0.008222 0.025232 - 976 -0.005979 0.000432 0.003264 - 977 0.000348 0.000126 0.007237 - 978 -0.031461 0.008376 -0.002490 - 979 -0.003066 -0.005264 0.001528 - 980 0.000500 -0.005194 -0.000082 - 981 -0.006145 0.003915 -0.013465 - 982 -0.002081 -0.001596 0.001268 - 983 0.004918 -0.004802 -0.009499 - 984 -0.008729 0.005751 0.010881 - 985 0.002456 -0.001947 -0.001558 - 986 -0.006566 -0.000024 0.003315 - 987 0.007532 0.005898 -0.002575 - 988 -0.004247 -0.003264 -0.000409 - 989 0.002165 -0.007499 0.004990 - 990 -0.000419 0.003692 -0.004472 - 991 -0.001571 -0.000159 -0.000431 - 992 0.005413 0.009517 0.004397 - 993 -0.002643 -0.002292 -0.001478 - 994 -0.003884 0.005066 -0.000457 - 995 0.006816 0.009263 -0.003376 - 996 -0.007273 0.011919 0.000514 - 997 0.000030 0.001409 0.005477 - 998 0.005334 -0.020033 0.004464 - 999 0.016228 0.009598 -0.007106 - 1000 -0.002283 -0.004481 0.001317 - 1001 -0.002631 -0.006631 -0.004233 - 1002 0.004184 0.000805 0.014756 - 1003 0.000408 -0.003693 0.003308 - 1004 0.004530 -0.006410 -0.006453 - 1005 -0.004928 -0.003846 0.015168 - 1006 0.003101 -0.001511 0.005308 - 1007 0.014081 -0.002443 0.012313 - 1008 0.002846 0.010440 -0.000376 - 1009 0.003569 -0.002175 -0.006662 - 1010 -0.008368 -0.011644 -0.006989 - 1011 0.019824 -0.004949 -0.018661 - 1012 0.003202 -0.011850 0.003160 - 1013 0.014918 -0.009378 0.018579 - 1014 -0.002594 0.004575 -0.001959 - 1015 -0.002298 0.000413 -0.003910 - 1016 0.012837 -0.003799 -0.015681 - 1017 -0.005955 -0.000660 0.004171 - 1018 0.001582 0.000975 0.000146 - 1019 0.006776 -0.014144 -0.007821 - 1020 0.004234 -0.001693 -0.007198 - 1021 -0.001802 -0.002656 0.003257 - 1022 0.028537 0.012512 0.005966 - 1023 -0.000026 -0.011732 -0.013572 - 1024 0.006685 0.008417 -0.002619 - 1025 -0.018380 0.006240 0.006444 - 1026 0.014195 0.009753 -0.004447 - 1027 -0.000769 -0.006799 -0.003510 - 1028 -0.003532 0.013774 -0.009337 - 1029 0.005263 0.018084 -0.010946 - 1030 0.004102 0.004262 -0.002426 - 1031 -0.003256 -0.005354 0.003498 - 1032 -0.021894 -0.003478 0.016467 - 1033 0.001456 -0.004355 -0.002070 - 1034 -0.005859 -0.004113 -0.005871 - 1035 -0.005758 -0.006886 -0.016585 - 1036 0.001562 0.006459 -0.000209 - 1037 0.001331 0.004667 0.000892 - 1038 0.012898 0.027063 -0.008125 - 1039 0.002117 0.007131 0.002457 - 1040 0.026605 0.010046 0.019045 - 1041 -0.017364 0.007077 -0.014953 - 1042 -0.000452 0.009291 0.004625 - 1043 -0.011059 0.009571 0.015357 - 1044 0.027928 -0.000208 0.009437 - 1045 0.003475 -0.004274 -0.000546 - 1046 0.012160 -0.001385 -0.006922 - 1047 -0.016274 -0.008100 -0.006675 - 1048 -0.003853 -0.003278 -0.001388 - 1049 0.014697 -0.003341 -0.007454 - 1050 0.011346 -0.009086 -0.006461 - 1051 -0.001161 -0.003940 -0.002833 - 1052 0.011182 0.001281 -0.000803 - 1053 -0.001345 -0.002375 -0.003580 - 1054 0.004028 0.002256 0.000990 - 1055 0.013302 0.008212 -0.007566 - 1056 0.029179 -0.014499 0.008878 - 1057 0.000706 0.001652 0.001826 - 1058 0.000498 -0.007266 0.024956 - 1059 0.001324 -0.008155 0.011295 - 1060 0.000971 -0.006253 -0.004688 - 1061 -0.004746 -0.005680 -0.016047 - 1062 -0.000356 -0.009050 -0.006561 - 1063 -0.000866 0.005460 0.000045 - 1064 -0.006882 0.011747 0.020163 - 1065 -0.000733 0.001409 -0.010900 - 1066 -0.003804 0.003558 0.001444 - 1067 0.004513 0.002071 -0.017536 - 1068 -0.000869 -0.002704 -0.014336 - 1069 -0.003015 0.003241 -0.002075 - 1070 0.003734 -0.005456 -0.000879 - 1071 -0.006686 -0.008010 -0.008654 - 1072 -0.000541 -0.003669 -0.004373 - 1073 0.003151 -0.002513 -0.013951 - 1074 0.003979 -0.005557 0.002931 - 1075 -0.005175 -0.004387 0.000228 - 1076 -0.005613 -0.012392 -0.029351 - 1077 0.009704 0.009953 -0.015680 - 1078 -0.000915 0.003660 -0.003078 - 1079 0.002529 0.001465 0.006987 - 1080 0.000880 0.001866 -0.004217 - 1081 0.000835 -0.000410 0.000029 - 1082 0.003324 -0.009356 0.012151 - 1083 -0.000797 0.009753 -0.012613 - 1084 0.004557 -0.006851 0.000257 - 1085 0.014378 -0.010986 -0.004036 - 1086 0.001889 0.001865 0.000904 - 1087 0.003881 0.000306 -0.000266 - 1088 0.006043 -0.030376 0.018797 - 1089 -0.001012 -0.002296 0.000324 - 1090 0.007042 0.008682 0.007323 - 1091 0.010016 0.002442 -0.028255 - 1092 -0.004827 0.009414 -0.012200 - 1093 0.002178 0.003272 0.000190 - 1094 0.003486 0.001815 -0.002585 - 1095 0.006020 0.002953 -0.010998 - 1096 0.002573 -0.000704 0.002051 - 1097 -0.010233 0.004335 0.005568 - 1098 0.003397 0.002649 0.010631 - 1099 -0.000367 -0.008657 0.004003 - 1100 0.006810 -0.008282 0.003316 - 1101 -0.008301 -0.011638 -0.006525 - 1102 -0.001900 -0.008810 0.001531 - 1103 0.003628 0.008111 0.009571 - 1104 0.017147 0.000173 0.003988 - 1105 0.006161 0.005444 0.001389 - 1106 -0.033784 0.028714 -0.002486 - 1107 0.022179 0.015181 0.025221 - 1108 0.002935 0.001125 -0.009560 - 1109 0.013392 0.009490 0.002655 - 1110 0.015380 -0.002935 -0.004728 - 1111 0.002760 -0.001052 0.002516 - 1112 -0.006737 0.002302 0.012384 - 1113 -0.004649 -0.009652 -0.009326 - 1114 -0.003333 0.004385 -0.006004 - 1115 -0.014175 0.007089 0.000199 - 1116 0.009875 0.004925 0.012791 - 1117 -0.004828 0.000366 0.001718 - 1118 0.009618 -0.007069 -0.012330 - 1119 -0.021489 -0.009155 -0.001603 - 1120 -0.001360 0.002089 -0.003585 - 1121 0.003530 -0.001847 0.010254 - 1122 0.016468 0.005240 -0.014692 - 1123 0.001989 -0.000949 0.003286 - 1124 0.022107 -0.012110 -0.007316 - 1125 0.012518 -0.010337 0.015891 - 1126 0.000850 -0.001413 -0.001737 - 1127 -0.014943 0.000360 -0.000490 - 1128 -0.027983 -0.005206 0.004037 - 1129 0.011232 0.000349 -0.006679 - 1130 -0.005484 -0.003095 -0.004430 - 1131 -0.005050 -0.002005 -0.015837 - 1132 -0.000470 0.001924 0.001131 - 1133 -0.016506 0.005240 0.008171 - 1134 0.011977 -0.012388 0.003671 - 1135 -0.000818 0.001081 0.001571 - 1136 0.009956 -0.006601 -0.002667 - 1137 -0.013344 0.009962 -0.000602 - 1138 -0.004379 0.004681 0.005655 - 1139 -0.022717 0.009805 -0.016911 - 1140 -0.017223 0.002867 0.018671 - 1141 -0.000339 -0.000149 -0.001276 - 1142 0.002292 0.016872 -0.004987 - 1143 -0.012964 -0.000693 -0.007140 - 1144 -0.002149 0.004008 -0.001355 - 1145 0.012575 0.018012 -0.011467 - 1146 -0.018572 0.011663 -0.005755 - 1147 0.000951 -0.000232 0.005705 - 1148 0.001030 -0.002411 0.005162 - 1149 -0.004871 0.010528 0.006213 - 1150 -0.003431 0.005236 0.003321 - 1151 -0.006083 0.008172 0.003730 - 1152 0.021201 0.002738 -0.026021 - 1153 -0.000559 -0.001274 0.002074 - 1154 -0.000342 -0.008595 -0.003314 - 1155 -0.004563 0.013150 0.001114 - 1156 0.002547 -0.003346 0.000793 - 1157 -0.004000 0.002915 0.001908 - 1158 0.008526 -0.013385 0.001263 - 1159 0.003331 -0.001629 -0.001592 - 1160 0.012216 0.004263 0.001290 - 1161 -0.024729 0.027722 0.012828 - 1162 -0.004556 0.005331 -0.000790 - 1163 -0.001260 0.004809 0.012624 - 1164 0.009151 0.007740 0.005908 - 1165 0.006739 -0.002486 0.000962 - 1166 0.002801 -0.001010 0.007063 - 1167 0.006266 -0.009780 0.000447 - 1168 -0.001756 -0.006121 -0.000399 - 1169 0.002128 0.011752 0.003187 - 1170 -0.000744 -0.004455 -0.001624 - 1171 -0.003120 -0.007987 0.008768 - 1172 -0.001279 -0.014309 0.014916 - 1173 -0.003496 -0.005392 0.006518 - 1174 -0.005252 -0.000094 0.002610 - 1175 -0.004319 0.000327 0.003799 - 1176 0.014469 -0.001407 -0.023557 - 1177 -0.001733 0.011173 0.001097 - 1178 0.019607 0.000729 -0.008577 - 1179 -0.013430 0.021297 -0.011104 - 1180 0.005550 -0.002953 -0.004489 - 1181 -0.021164 -0.004283 0.009224 - 1182 0.020762 -0.011806 0.008058 - 1183 -0.003934 -0.006346 0.000789 - 1184 -0.004154 -0.012917 -0.000804 - 1185 0.001834 -0.003234 0.006486 - 1186 -0.003359 -0.000166 0.000482 - 1187 -0.010938 -0.009570 0.011838 - 1188 -0.006339 -0.002743 -0.017319 - 1189 -0.002008 -0.000238 -0.002842 - 1190 0.009730 0.002797 -0.000255 - 1191 0.004802 0.018470 -0.005529 - 1192 0.002978 0.003254 0.000406 - 1193 0.001762 -0.016118 0.017481 - 1194 0.009625 0.005549 -0.002833 - 1195 -0.005277 -0.000015 -0.004247 - 1196 0.008535 -0.018189 -0.023760 - 1197 -0.020839 0.008581 0.007193 - 1198 0.001976 -0.001531 0.001386 - 1199 -0.012488 -0.005613 0.004418 - 1200 0.012387 0.001324 -0.002579 - 1201 0.004612 0.001574 0.002430 - 1202 0.004011 0.024078 0.008286 - 1203 0.028635 -0.001749 -0.000378 - 1204 -0.001292 -0.004163 0.001688 - 1205 0.018917 -0.005327 -0.022863 - 1206 -0.021498 0.026796 -0.015481 - 1207 -0.004360 -0.003023 -0.007483 - 1208 0.015222 -0.007834 -0.014901 - 1209 -0.015487 -0.004003 -0.024684 - 1210 0.000162 -0.000232 -0.002511 - 1211 0.005663 0.001759 0.003041 - 1212 -0.026577 0.001752 0.009499 - 1213 -0.002118 -0.004800 0.002106 - 1214 0.012772 0.013880 -0.004149 - 1215 0.008831 0.004495 0.004278 - 1216 -0.001002 0.000396 0.000450 - 1217 0.001493 -0.000300 0.006615 - 1218 0.022789 -0.011336 -0.001626 - 1219 -0.002165 0.002305 -0.004399 - 1220 -0.001727 0.010653 0.006150 - 1221 0.001799 -0.000399 -0.015101 - 1222 -0.002535 -0.001664 0.000167 - 1223 -0.007939 0.009699 -0.003581 - 1224 -0.009214 -0.009452 -0.003331 - 1225 -0.002745 0.003249 0.011490 - 1226 0.010727 -0.015563 0.011870 - 1227 -0.003771 0.013856 -0.015486 - 1228 -0.000932 0.001513 0.000721 - 1229 -0.002528 0.000192 0.015301 - 1230 -0.027023 -0.007231 0.009659 - 1231 -0.005525 0.001099 -0.001369 - 1232 -0.002318 -0.008510 -0.009719 - 1233 -0.005945 -0.008347 0.009845 - 1234 -0.000817 -0.006097 -0.001394 - 1235 0.026844 0.005400 -0.013998 - 1236 -0.019837 0.017329 -0.010038 - 1237 -0.002691 -0.005371 -0.000786 - 1238 -0.007304 -0.006372 0.007409 - 1239 -0.014066 -0.005252 0.014237 - 1240 -0.000660 -0.004157 -0.007445 - 1241 -0.015343 -0.015681 0.000525 - 1242 -0.004856 0.008296 -0.020506 - 1243 -0.000451 -0.006253 0.005274 - 1244 -0.016626 -0.024128 0.003146 - 1245 0.003430 -0.001516 0.006995 - 1246 0.002369 0.000761 -0.000692 - 1247 -0.011034 0.017913 -0.003576 - 1248 0.014886 0.005052 0.010870 - 1249 0.000976 0.003044 0.004043 - 1250 0.002084 0.009119 -0.003484 - 1251 -0.004682 -0.003095 0.024419 - 1252 -0.001872 0.005519 -0.003878 - 1253 0.014045 0.004474 0.006660 - 1254 -0.006683 -0.012923 -0.006357 - 1255 -0.007125 -0.002296 0.002894 - 1256 -0.009126 -0.000293 0.008175 - 1257 -0.005668 -0.002902 -0.000640 - 1258 -0.009805 0.000500 -0.001546 - 1259 -0.007254 -0.007274 0.010849 - 1260 0.005786 0.004719 0.004479 - 1261 0.000767 -0.007091 -0.002809 - 1262 -0.010861 -0.024470 -0.006678 - 1263 0.010352 0.003874 -0.018616 - 1264 -0.001332 -0.000776 -0.001533 - 1265 0.005055 -0.002761 -0.000154 - 1266 0.001293 -0.010766 0.003695 - 1267 0.004101 0.005423 0.004161 - 1268 -0.006495 -0.001645 0.007645 - 1269 0.024277 0.000761 0.018148 - 1270 0.000384 -0.004677 0.001777 - 1271 -0.000305 -0.022286 0.006378 - 1272 0.014900 -0.009298 0.005029 - 1273 -0.002201 -0.002422 -0.001266 - 1274 0.002419 0.000621 -0.006170 - 1275 0.002242 -0.003567 -0.006329 - 1276 0.001155 0.006214 -0.002164 - 1277 -0.025679 0.011598 0.001775 - 1278 -0.016652 0.005061 0.002255 - 1279 -0.000163 0.000193 -0.001041 - 1280 -0.002822 -0.004131 -0.007696 - 1281 -0.007029 0.005316 -0.012422 - 1282 -0.001259 -0.001443 0.001295 - 1283 -0.000992 -0.027820 -0.000474 - 1284 -0.012190 -0.043729 -0.008054 - 1285 -0.001840 -0.001572 0.001104 - 1286 0.008311 0.001263 -0.001841 - 1287 0.001277 0.000429 -0.007113 - 1288 -0.005029 -0.002280 -0.002761 - 1289 -0.024723 0.012515 -0.012864 - 1290 -0.013845 -0.020399 0.001674 - 1291 -0.000161 0.002303 0.004199 - 1292 -0.010956 -0.010528 0.017163 - 1293 0.023554 -0.006815 0.021159 - 1294 0.000772 -0.000829 0.004462 - 1295 0.024106 -0.007189 -0.017980 - 1296 -0.011795 0.000225 0.018351 - 1297 -0.002503 0.000288 -0.000931 - 1298 -0.001901 -0.006775 -0.001166 - 1299 -0.002626 0.004209 -0.000596 - 1300 -0.003248 -0.009856 0.001496 - 1301 -0.008616 0.000206 -0.000660 - 1302 0.012991 -0.001944 0.010735 - 1303 0.000183 0.003767 -0.002207 - 1304 0.002875 0.006021 0.006091 - 1305 -0.003343 -0.008883 0.015455 - 1306 -0.003761 0.009400 -0.007147 - 1307 -0.002601 -0.012510 0.005900 - 1308 -0.013464 0.021935 0.006364 - 1309 0.007717 -0.006568 -0.004280 - 1310 0.004551 -0.013432 0.001741 - 1311 0.016676 -0.009730 -0.005415 - 1312 -0.003518 -0.000115 0.000120 - 1313 -0.018566 -0.004441 0.007076 - 1314 0.011422 0.004168 0.013848 - 1315 -0.002232 0.003004 -0.005210 - 1316 -0.004985 -0.000655 -0.007286 - 1317 -0.004756 0.005461 -0.010032 - 1318 0.003296 -0.000345 0.003797 - 1319 0.000013 0.003387 0.009258 - 1320 -0.001175 0.009021 0.016554 - 1321 0.004610 0.000563 0.001890 - 1322 0.001511 0.004957 0.010795 - 1323 -0.000517 0.009529 0.012695 - 1324 0.003561 -0.002127 -0.002139 - 1325 -0.016355 -0.004573 0.011414 - 1326 0.002437 -0.000969 0.003958 - 1327 -0.003191 0.002772 0.003706 - 1328 0.002188 0.004078 0.024902 - 1329 0.005804 0.008997 0.000514 - 1330 0.000169 -0.001823 0.006601 - 1331 -0.012837 0.016738 0.032499 - 1332 -0.003787 -0.003993 0.005792 - 1333 -0.006500 -0.001952 -0.005568 - 1334 0.004632 0.002607 -0.001417 - 1335 0.007826 -0.018417 0.003893 - 1336 0.001400 0.000629 -0.002329 - 1337 -0.026090 -0.010827 -0.007428 - 1338 0.014757 0.003359 0.005866 - 1339 0.005344 0.002452 0.000637 - 1340 0.002304 0.001516 0.008371 - 1341 0.003116 0.003502 0.000920 - 1342 0.000219 0.006872 -0.006361 - 1343 0.004872 0.004948 -0.015461 - 1344 0.002293 0.008990 -0.007103 - 1345 -0.000248 -0.001405 -0.000404 - 1346 0.016050 0.005473 0.014883 - 1347 0.000661 0.010958 0.009762 - 1348 0.002507 0.004854 0.004016 - 1349 -0.000026 0.005865 -0.004933 - 1350 -0.003541 0.012071 0.011984 - 1351 -0.000388 -0.001662 -0.002624 - 1352 -0.008781 0.002236 0.005933 - 1353 -0.002303 0.010321 -0.013971 - 1354 0.000266 0.005381 0.006218 - 1355 -0.030793 -0.017551 0.006520 - 1356 -0.001710 0.006198 0.003481 - 1357 -0.000575 0.000387 0.003498 - 1358 0.011844 0.006387 0.013823 - 1359 -0.004149 -0.001630 0.001064 - 1360 0.002966 -0.001211 -0.000529 - 1361 0.011026 0.001160 0.001568 - 1362 0.015143 -0.001234 0.000065 - 1363 0.000976 0.001952 -0.002769 - 1364 0.013527 0.011152 0.001594 - 1365 -0.000179 -0.000211 -0.002554 - 1366 -0.005351 -0.004969 -0.002979 - 1367 -0.006889 0.021662 -0.005435 - 1368 -0.002462 0.016113 0.008657 - 1369 -0.000975 0.000751 -0.000755 - 1370 -0.003243 0.006738 -0.001393 - 1371 -0.002267 -0.000779 0.003167 - 1372 0.001566 -0.003190 -0.000583 - 1373 -0.002018 -0.005136 0.012563 - 1374 -0.006828 0.007134 0.011132 - 1375 0.005244 -0.004715 -0.003319 - 1376 -0.010064 -0.001392 0.024842 - 1377 -0.003331 -0.012180 0.011450 - 1378 0.005044 -0.003538 0.000197 - 1379 0.014932 -0.005316 0.014871 - 1380 0.002959 -0.015155 -0.010790 - 1381 0.004288 0.003508 0.003045 - 1382 0.010516 0.006731 0.001181 - 1383 0.003157 0.002004 0.039661 - 1384 -0.003464 -0.000341 -0.002519 - 1385 0.000767 -0.010574 0.002375 - 1386 0.012132 0.009405 0.005728 - 1387 -0.002537 0.005096 -0.000141 - 1388 0.008455 -0.000335 0.003398 - 1389 0.000567 0.012932 0.006368 - 1390 0.007440 -0.002304 0.001444 - 1391 0.003946 0.007849 -0.005030 - 1392 0.012038 -0.016280 0.007159 - 1393 -0.001061 -0.002610 -0.000083 - 1394 0.010905 -0.006613 -0.001941 - 1395 -0.013885 -0.027620 0.005494 - 1396 0.013746 0.003525 0.007163 - 1397 0.003586 0.002644 -0.010792 - 1398 0.018544 0.013850 0.017322 - 1399 0.004571 0.000027 -0.001760 - 1400 0.012220 0.001858 -0.006751 - 1401 0.009850 -0.002003 0.019339 - 1402 -0.001383 0.002281 -0.007042 - 1403 -0.003363 0.001654 -0.017801 - 1404 0.011330 0.009635 0.005470 - 1405 0.000650 -0.001098 -0.005942 - 1406 0.005198 -0.008028 -0.003832 - 1407 0.017668 -0.005738 0.026099 - 1408 -0.001891 0.001162 0.003476 - 1409 -0.003537 0.018838 0.000972 - 1410 0.007980 0.016250 0.030292 - 1411 -0.001348 0.000197 0.004181 - 1412 -0.002255 -0.008393 -0.001355 - 1413 -0.008567 -0.008184 -0.000151 - 1414 -0.001145 0.001777 -0.004250 - 1415 -0.002565 -0.000609 -0.002622 - 1416 0.017182 0.009342 -0.008899 - 1417 -0.000336 -0.000833 -0.006619 - 1418 0.006594 -0.014023 -0.011705 - 1419 -0.010047 -0.002912 -0.003804 - 1420 0.005759 0.000406 0.005233 - 1421 -0.013174 -0.018780 -0.002966 - 1422 -0.003551 -0.005212 0.011087 - 1423 -0.001811 -0.005836 -0.002120 - 1424 -0.008296 0.022099 0.012646 - 1425 0.010130 0.006059 0.033707 - 1426 0.001039 -0.001025 -0.000459 - 1427 0.004468 0.000527 0.001539 - 1428 -0.001728 -0.005304 0.003140 - 1429 -0.000141 -0.003112 0.003400 - 1430 0.007530 -0.026022 0.005020 - 1431 -0.011982 0.032142 -0.001998 - 1432 -0.001642 0.003923 -0.003350 - 1433 0.016086 -0.002664 -0.005695 - 1434 -0.010354 0.000136 0.021071 - 1435 0.001502 -0.001507 0.005856 - 1436 -0.003359 -0.017617 -0.013060 - 1437 -0.001621 -0.013764 -0.008355 - 1438 -0.006074 0.001165 0.001910 - 1439 -0.004946 0.003618 0.011324 - 1440 -0.007761 0.002697 -0.006763 - 1441 -0.009332 0.000898 0.000750 - 1442 -0.017083 -0.010335 0.011191 - 1443 0.020780 0.013466 -0.015083 - 1444 -0.008140 -0.008032 -0.000180 - 1445 -0.001836 -0.008988 0.003973 - 1446 -0.008280 -0.004548 -0.003224 - 1447 0.000996 -0.002062 -0.001184 - 1448 -0.001863 -0.012096 0.003957 - 1449 -0.027050 0.007989 0.002157 - 1450 -0.001321 -0.000325 0.001355 - 1451 -0.006885 -0.000536 -0.022446 - 1452 0.008792 -0.007975 0.003329 - 1453 -0.003682 -0.004782 -0.002567 - 1454 -0.001180 -0.009011 0.018662 - 1455 -0.000958 -0.004899 0.013723 - 1456 0.000545 0.011919 -0.001753 - 1457 0.023799 0.010298 -0.002649 - 1458 0.014717 0.007757 -0.005400 - 1459 -0.004576 -0.007691 0.001365 - 1460 -0.006577 -0.016846 -0.022862 - 1461 -0.005206 0.003687 0.012428 - 1462 0.001923 -0.004758 -0.001993 - 1463 0.006600 0.017503 0.006935 - 1464 -0.006747 -0.003482 -0.000067 - 1465 0.000613 0.004580 0.004038 - 1466 -0.001945 0.022605 -0.000652 - 1467 0.017624 -0.001392 0.003829 - 1468 -0.003065 -0.003003 -0.000747 - 1469 -0.012664 -0.016566 -0.007030 - 1470 0.008660 -0.008358 0.004763 - 1471 -0.004008 0.000421 -0.006040 - 1472 0.003555 0.008566 -0.015842 - 1473 -0.001032 0.001700 -0.010204 - 1474 -0.000556 0.000599 0.003074 - 1475 0.001542 0.002939 0.005269 - 1476 -0.005281 -0.001944 0.003338 - 1477 -0.000195 -0.000293 -0.001004 - 1478 -0.009991 -0.005354 -0.013386 - 1479 -0.000476 -0.017594 0.007900 - 1480 0.000550 -0.000431 0.001422 - 1481 0.018094 -0.005183 0.016234 - 1482 0.010706 0.011668 -0.017772 - 1483 0.001291 0.006499 0.000951 - 1484 0.009985 -0.016962 0.009714 - 1485 0.020849 0.018365 -0.008351 - 1486 0.006940 0.004692 -0.002409 - 1487 0.022308 0.010182 -0.022897 - 1488 0.000269 0.008847 0.011834 - 1489 0.002051 0.007334 -0.000125 - 1490 -0.023048 0.013759 -0.030276 - 1491 0.023523 -0.005817 0.007754 - 1492 -0.001269 0.002979 0.001311 - 1493 -0.005596 0.006174 0.011007 - 1494 -0.009061 0.022719 0.002133 - 1495 -0.001128 0.004307 -0.002381 - 1496 -0.004340 0.013891 -0.003505 - 1497 0.001822 -0.005505 -0.001135 - 1498 -0.000910 0.001437 0.000165 - 1499 0.004510 -0.000360 -0.006425 - 1500 0.003993 0.000498 0.007321 - 1501 -0.002868 -0.000316 -0.000509 - 1502 0.000620 0.011286 0.008461 - 1503 -0.013079 -0.008157 0.007561 - 1504 -0.003002 0.003413 0.004968 - 1505 0.015262 -0.005133 0.012052 - 1506 -0.003968 -0.003643 0.003514 - 1507 0.005087 -0.001882 -0.000518 - 1508 0.000932 -0.002238 0.000800 - 1509 -0.008149 0.000695 -0.000827 - 1510 -0.001261 -0.003375 0.000333 - 1511 -0.001224 -0.004135 -0.003080 - 1512 0.009246 -0.010372 0.026354 - 1513 0.000697 -0.003200 0.001222 - 1514 -0.002319 0.003800 0.022860 - 1515 -0.018205 0.011600 -0.011416 - 1516 -0.001731 -0.001076 0.002612 - 1517 -0.004661 -0.010783 -0.001505 - 1518 0.016208 0.002810 0.004482 - 1519 0.003508 -0.001750 0.002537 - 1520 0.024576 -0.026041 -0.004083 - 1521 -0.019140 0.000844 0.001909 - 1522 -0.000341 0.001152 0.001967 - 1523 -0.020076 0.003364 0.001315 - 1524 -0.000942 0.000692 -0.003283 - 1525 -0.006519 -0.000419 0.000991 - 1526 -0.004033 0.006531 0.004791 - 1527 0.005626 0.012187 -0.014266 - 1528 0.001113 -0.004253 0.011930 - 1529 -0.010144 0.003567 0.009059 - 1530 -0.003464 0.001115 0.011591 - 1531 0.000006 0.000074 0.005751 - 1532 0.003604 0.008464 0.010627 - 1533 -0.004351 -0.009621 -0.000453 - 1534 -0.000196 -0.001160 0.002795 - 1535 -0.006855 0.001414 0.005552 - 1536 -0.000894 -0.002102 0.005053 - 1537 -0.002040 -0.005887 -0.003590 - 1538 -0.006852 -0.011947 -0.023080 - 1539 -0.016070 0.000160 0.010390 - 1540 0.004712 0.002848 -0.002998 - 1541 -0.004259 0.007840 0.008142 - 1542 -0.004861 0.004263 0.011728 - 1543 0.006968 -0.004871 0.004119 - 1544 -0.016558 -0.002046 -0.006090 - 1545 -0.006229 0.004475 0.001436 - 1546 -0.002341 -0.004733 -0.003946 - 1547 0.003563 0.004733 0.009615 - 1548 -0.013018 0.004747 -0.004733 - 1549 0.001703 -0.000331 0.003605 - 1550 0.005459 -0.002653 -0.012447 - 1551 0.013689 0.008625 -0.003301 - 1552 0.003195 0.001205 -0.000779 - 1553 -0.003336 -0.011439 -0.004979 - 1554 0.001015 0.018568 -0.007361 - 1555 -0.001647 -0.003759 0.001214 - 1556 0.015583 -0.016961 0.000384 - 1557 -0.011138 -0.013161 -0.015913 - 1558 0.005848 -0.002193 -0.007682 - 1559 0.009577 -0.005765 0.010025 - 1560 0.006984 0.005858 -0.020668 - 1561 -0.005040 0.001396 0.001932 - 1562 0.007071 0.009231 0.007700 - 1563 0.001743 0.005137 0.005850 - 1564 0.001857 0.002145 -0.004455 - 1565 -0.007462 0.014047 -0.012730 - 1566 0.013730 -0.006385 0.009586 - 1567 -0.002000 0.003453 -0.001882 - 1568 -0.009622 -0.007424 -0.003371 - 1569 -0.006993 -0.018224 -0.006858 - 1570 0.001461 0.001281 -0.002568 - 1571 0.018901 0.002357 0.001811 - 1572 -0.001592 0.019333 -0.002732 - 1573 -0.001308 -0.005730 -0.002519 - 1574 -0.014074 0.007287 0.021518 - 1575 -0.017324 -0.018775 -0.005647 - 1576 0.002340 -0.001593 0.004994 - 1577 -0.000516 0.003608 0.002676 - 1578 -0.014840 -0.017283 -0.001508 - 1579 -0.001557 -0.002471 -0.002555 - 1580 0.016654 -0.033672 0.006595 - 1581 0.013351 -0.030070 0.003443 - 1582 0.003752 0.001449 0.001862 - 1583 -0.011257 -0.002704 0.007355 - 1584 0.002139 0.006577 0.012771 - 1585 0.002251 0.002492 -0.002180 - 1586 0.010691 -0.005615 -0.001517 - 1587 -0.018738 0.016070 0.006914 - 1588 -0.001600 0.000180 0.001378 - 1589 0.004891 -0.007732 -0.013906 - 1590 -0.015149 0.011285 0.002913 - 1591 0.003944 -0.001162 -0.002407 - 1592 -0.013220 -0.006427 -0.006873 - 1593 -0.008388 0.022805 -0.011588 - 1594 0.000621 -0.004836 0.005509 - 1595 0.006148 -0.013451 0.002326 - 1596 -0.001161 -0.012639 -0.002024 - 1597 -0.005042 0.000613 0.003072 - 1598 -0.002560 -0.009516 -0.007164 - 1599 -0.007736 0.003315 0.007824 - 1600 -0.002409 -0.002549 -0.003082 - 1601 -0.002839 0.004415 -0.008830 - 1602 -0.006633 -0.001003 -0.004060 - 1603 -0.004810 -0.007495 -0.004047 - 1604 0.005200 -0.017270 0.009101 - 1605 0.000670 -0.009280 -0.012848 - 1606 -0.003830 0.001924 -0.002728 - 1607 -0.035525 0.007821 -0.020602 - 1608 0.016575 -0.019547 -0.006176 - 1609 0.003828 0.000099 -0.002605 - 1610 0.017387 0.007652 0.014875 - 1611 0.012190 0.014852 0.016071 - 1612 -0.003436 0.002187 -0.001035 - 1613 -0.005586 -0.003901 0.006033 - 1614 -0.005884 -0.005331 -0.011796 - 1615 -0.001799 -0.005019 0.004011 - 1616 0.002094 -0.028579 0.008471 - 1617 0.023334 0.020189 0.016696 - 1618 -0.000653 -0.003079 -0.001689 - 1619 -0.005925 -0.004542 -0.007489 - 1620 0.003980 0.000361 0.005598 - 1621 -0.000999 0.004025 -0.003724 - 1622 0.000058 0.024442 0.006515 - 1623 0.011473 -0.013431 0.004073 - 1624 0.002923 -0.003314 0.001931 - 1625 0.003377 -0.006029 -0.008704 - 1626 0.002413 0.015094 0.010447 - 1627 0.003654 -0.000619 -0.001261 - 1628 -0.004232 -0.000930 0.001384 - 1629 0.019160 0.000313 -0.006734 - 1630 0.003534 0.002394 -0.000501 - 1631 -0.008068 0.002953 0.008451 - 1632 0.014612 0.006975 -0.004278 - 1633 0.001620 0.003004 0.003226 - 1634 -0.007605 -0.007788 0.011245 - 1635 0.020296 -0.014907 -0.003043 - 1636 -0.002678 -0.006261 0.001869 - 1637 -0.007968 -0.013586 -0.003793 - 1638 -0.015202 -0.007224 -0.014352 - 1639 -0.005816 -0.003019 0.006480 - 1640 -0.001607 -0.004084 0.006246 - 1641 0.008520 -0.008049 0.002824 - 1642 -0.000658 -0.004008 -0.000300 - 1643 -0.000444 0.000650 -0.012168 - 1644 -0.006399 -0.006883 0.005254 - 1645 -0.001317 0.006093 0.001522 - 1646 -0.010770 -0.004270 -0.010989 - 1647 -0.005520 0.020979 0.012203 - 1648 -0.004763 0.001957 0.003649 - 1649 -0.010531 0.001095 0.022741 - 1650 0.001695 -0.009764 -0.029750 - 1651 0.000561 0.003660 0.004562 - 1652 0.004814 -0.011887 -0.011791 - 1653 0.015151 -0.017660 -0.020515 - 1654 -0.003720 -0.008154 0.002101 - 1655 -0.006836 0.005342 0.006830 - 1656 -0.008891 -0.005752 0.002656 - 1657 -0.004211 -0.006534 0.001470 - 1658 0.024344 -0.009232 0.001415 - 1659 -0.010793 -0.032076 -0.013330 - 1660 -0.000393 0.010082 -0.000260 - 1661 -0.003386 0.024037 -0.002341 - 1662 0.005231 -0.007154 0.002310 - 1663 0.004778 0.000685 -0.001247 - 1664 0.006845 -0.000146 -0.002439 - 1665 0.002831 0.001509 -0.001312 - 1666 -0.004575 0.002015 0.002231 - 1667 -0.008714 0.004773 0.019310 - 1668 -0.009036 0.006437 0.017025 - 1669 -0.001102 -0.003004 0.003294 - 1670 0.004690 0.016121 0.007181 - 1671 -0.000881 -0.003815 0.001639 - 1672 -0.000053 -0.001708 0.002633 - 1673 -0.004620 0.003536 0.000715 - 1674 -0.002636 -0.005429 0.007498 - 1675 0.002307 0.001406 0.002665 - 1676 -0.005270 -0.001969 0.007587 - 1677 0.001417 -0.009022 -0.021912 - 1678 0.000203 0.002930 -0.002177 - 1679 0.003819 0.012652 -0.002939 - 1680 -0.001040 0.005171 0.022221 - 1681 -0.001765 0.004140 -0.001020 - 1682 0.015888 -0.002384 -0.000464 - 1683 -0.019573 0.014814 -0.003047 - 1684 -0.002840 -0.000626 0.000097 - 1685 0.019011 -0.004434 -0.031132 - 1686 -0.011722 0.011711 0.019623 - 1687 -0.000720 0.008278 0.001232 - 1688 -0.000014 -0.005707 0.005722 - 1689 0.006445 -0.004607 0.004541 - 1690 -0.008451 -0.005406 -0.003097 - 1691 -0.025859 -0.004092 0.011942 - 1692 0.003198 0.017013 -0.015979 - 1693 0.001237 0.005482 0.001012 - 1694 -0.003233 0.012773 -0.012817 - 1695 -0.013658 -0.008102 0.007350 - 1696 0.004867 0.002547 -0.001769 - 1697 0.019074 -0.004173 0.005165 - 1698 0.008487 0.001064 0.000080 - 1699 0.002766 -0.001251 -0.001561 - 1700 -0.019200 0.027169 -0.007481 - 1701 0.006036 -0.028485 -0.009388 - 1702 -0.005460 0.002563 0.001784 - 1703 -0.017462 0.006398 0.005231 - 1704 -0.014453 0.005484 0.004388 - 1705 0.002956 -0.001348 0.006512 - 1706 0.009654 0.004653 0.025184 - 1707 0.006226 -0.001478 -0.018062 - 1708 0.003757 -0.000921 -0.000401 - 1709 0.004307 -0.009700 -0.007768 - 1710 0.003780 -0.012914 0.008582 - 1711 0.004846 -0.002032 -0.000808 - 1712 -0.000823 -0.002500 -0.004619 - 1713 0.014769 -0.010350 0.008970 - 1714 -0.001580 -0.000837 0.000021 - 1715 -0.002003 -0.002972 -0.000158 - 1716 -0.004469 -0.000404 0.001257 - 1717 -0.001782 0.001231 -0.003624 - 1718 -0.009550 0.008477 -0.006010 - 1719 -0.003240 -0.001801 -0.002707 - 1720 -0.003131 -0.002749 -0.002782 - 1721 -0.003319 -0.008008 -0.009572 - 1722 -0.003280 -0.008289 -0.009069 - 1723 -0.006776 0.001807 0.000809 - 1724 0.000630 0.005359 0.003033 - 1725 0.016012 0.013546 0.014364 - 1726 -0.005383 0.003683 -0.001052 - 1727 -0.000343 -0.021814 -0.000655 - 1728 0.015975 0.004809 -0.015863 - 1729 -0.002843 0.002136 0.000031 - 1730 0.008511 0.002265 -0.002748 - 1731 -0.026285 -0.002274 -0.004757 - 1732 0.005294 -0.003565 0.004694 - 1733 -0.002668 0.001103 -0.001112 - 1734 -0.009429 0.006969 -0.008965 - 1735 -0.001634 0.000110 0.001819 - 1736 -0.004942 0.001203 -0.007254 - 1737 -0.002655 0.002573 -0.003610 - 1738 -0.004831 0.005860 0.001407 - 1739 -0.014232 0.009476 0.016389 - 1740 -0.017895 0.005674 -0.009379 - 1741 0.003013 -0.002508 -0.001228 - 1742 0.000746 0.006449 -0.005992 - 1743 0.006650 -0.002762 0.000152 - 1744 0.002550 -0.008457 0.001324 - 1745 -0.001868 -0.010233 -0.023525 - 1746 0.003968 -0.007880 0.008439 - 1747 -0.000591 0.004322 -0.003592 - 1748 -0.014424 0.009132 0.003708 - 1749 0.012052 -0.004950 -0.011581 - 1750 0.001849 0.003842 -0.009164 - 1751 0.009453 -0.005684 -0.004817 - 1752 0.001564 0.018776 -0.004831 - 1753 0.000794 0.000968 -0.001710 - 1754 -0.003816 -0.004723 -0.000498 - 1755 -0.011972 0.005633 -0.006975 - 1756 -0.004635 0.005064 -0.004764 - 1757 -0.010722 0.012077 -0.027297 - 1758 -0.003376 0.000707 0.006078 - 1759 0.001092 0.005159 -0.000557 - 1760 0.014326 0.002844 -0.021424 - 1761 0.019579 -0.002405 -0.009532 - 1762 -0.000565 0.006632 0.002294 - 1763 -0.025047 0.006219 0.001583 - 1764 -0.004637 -0.007484 0.007079 - 1765 0.002563 -0.001616 -0.003316 - 1766 -0.001239 0.014897 -0.002355 - 1767 -0.001256 -0.009226 0.009450 - 1768 0.001056 0.005329 -0.003831 - 1769 -0.012555 0.037676 0.021233 - 1770 -0.005969 -0.003116 -0.014248 - 1771 0.000691 0.001302 0.002405 - 1772 -0.015733 0.001224 -0.004288 - 1773 0.006783 0.015986 -0.003342 - 1774 0.002355 0.002897 -0.002965 - 1775 -0.000435 0.005789 0.007980 - 1776 0.014211 0.000855 -0.014841 - 1777 -0.004596 -0.002169 0.000774 - 1778 0.002630 -0.027237 0.012553 - 1779 -0.000727 -0.003394 -0.009924 - 1780 0.001821 -0.001310 0.000540 - 1781 0.005476 -0.002057 0.001588 - 1782 0.008060 0.013457 -0.013767 - 1783 0.003078 -0.007047 0.009501 - 1784 -0.004392 -0.004982 0.015684 - 1785 -0.021173 -0.003917 -0.003013 - 1786 0.001492 -0.007162 -0.003460 - 1787 0.020179 0.025050 0.005018 - 1788 -0.018378 -0.021938 0.007656 - 1789 -0.000363 0.004076 -0.003991 - 1790 0.012179 0.023942 -0.003853 - 1791 0.002207 0.011773 0.006443 - 1792 0.001993 0.000538 0.002365 - 1793 0.008602 -0.013779 -0.007218 - 1794 0.007374 0.001122 0.001108 - 1795 0.003207 -0.011319 -0.004081 - 1796 0.010332 -0.007827 -0.001929 - 1797 0.001869 0.022609 0.012256 - 1798 0.001101 0.003835 0.002357 - 1799 -0.003624 0.011759 0.002745 - 1800 0.001557 -0.002337 -0.004179 - 1801 0.003327 -0.001910 -0.005250 - 1802 0.011996 0.003017 0.013309 - 1803 -0.013682 -0.002775 -0.008939 - 1804 -0.002064 -0.000934 0.000427 - 1805 -0.012146 0.024406 -0.015171 - 1806 0.005030 -0.019570 0.004311 - 1807 0.003003 0.004365 0.002257 - 1808 0.000823 0.000086 -0.005161 - 1809 -0.003001 0.001206 0.008241 - 1810 0.005602 -0.001423 0.002945 - 1811 0.000330 0.001483 -0.011075 - 1812 0.003652 0.009252 -0.000166 - 1813 0.004531 -0.000860 -0.000170 - 1814 0.018728 0.013621 0.031510 - 1815 0.011579 -0.009257 -0.004100 - 1816 0.002862 0.000330 -0.002342 - 1817 -0.003456 -0.001426 -0.004566 - 1818 -0.006589 0.018593 0.018322 - 1819 -0.001663 0.002113 0.003120 - 1820 0.002523 0.005185 0.010725 - 1821 -0.006456 -0.005159 0.018366 - 1822 -0.000677 -0.000638 0.005530 - 1823 0.006499 0.011396 0.003392 - 1824 0.000945 -0.008826 -0.007441 - 1825 -0.002582 0.001006 0.000170 - 1826 -0.000739 0.010378 -0.012944 - 1827 -0.004082 -0.009693 0.012271 - 1828 -0.002259 -0.002179 0.001812 - 1829 0.004365 0.028602 0.007523 - 1830 -0.001047 0.006781 -0.010318 - 1831 0.003053 0.002227 0.004523 - 1832 -0.004297 -0.007295 0.001900 - 1833 0.002925 0.002066 0.004473 - 1834 0.003171 0.000025 0.002189 - 1835 0.001188 0.002838 0.001014 - 1836 0.006142 0.003073 -0.003689 - 1837 0.009818 0.005253 0.006222 - 1838 0.013907 -0.003607 0.006764 - 1839 -0.000327 0.015573 -0.010930 - 1840 -0.003110 -0.005538 0.000400 - 1841 0.006244 -0.021206 -0.003853 - 1842 -0.010299 0.008474 0.021147 - 1843 -0.001053 -0.000598 0.004581 - 1844 -0.013621 0.002557 -0.003175 - 1845 -0.002495 0.000789 0.011106 - 1846 -0.000137 -0.004006 -0.000014 - 1847 -0.017819 -0.013981 0.011316 - 1848 -0.005844 -0.000863 -0.025248 - 1849 -0.002799 0.002996 -0.002499 - 1850 -0.012455 0.012490 -0.004469 - 1851 0.010514 0.009490 -0.009495 - 1852 -0.000560 -0.004144 -0.000656 - 1853 -0.007255 0.002559 0.003817 - 1854 0.004602 -0.007276 0.003469 - 1855 0.000128 0.001144 -0.008402 - 1856 0.008157 0.001721 -0.014464 - 1857 -0.004034 0.002739 -0.008982 - 1858 0.002856 0.004731 -0.003812 - 1859 0.008481 -0.004184 -0.015612 - 1860 -0.004966 0.006658 -0.006541 - 1861 0.005415 -0.007185 0.002622 - 1862 -0.000791 0.004294 0.012806 - 1863 0.006266 -0.008943 0.000048 - 1864 -0.004891 -0.000259 0.002435 - 1865 0.000775 -0.012600 0.009738 - 1866 -0.000239 0.020688 0.014963 - 1867 0.007752 0.006605 0.003522 - 1868 0.005559 0.005449 0.004823 - 1869 0.001382 0.020031 -0.009484 - 1870 0.000269 -0.000837 -0.001948 - 1871 -0.015324 0.006379 0.032972 - 1872 -0.010895 -0.006739 0.002233 - 1873 0.002406 -0.005817 -0.007929 - 1874 0.011974 0.013774 0.020789 - 1875 -0.005616 -0.012309 -0.023698 - 1876 -0.002712 -0.000118 0.000894 - 1877 -0.000559 -0.018665 -0.005699 - 1878 -0.022904 -0.016730 0.007620 - 1879 -0.006235 -0.000119 -0.005440 - 1880 -0.008616 0.001720 0.002602 - 1881 -0.019263 0.001295 0.018377 - 1882 -0.002493 0.002824 -0.002915 - 1883 0.007384 0.000692 0.003462 - 1884 -0.019228 -0.005451 0.005676 - 1885 0.002956 0.004628 -0.002177 - 1886 0.005617 0.021792 -0.005623 - 1887 -0.010771 -0.007154 -0.002600 - 1888 -0.006932 -0.006388 0.001795 - 1889 -0.026638 0.002211 0.017012 - 1890 -0.006429 -0.013703 0.021233 - 1891 0.004179 0.001508 -0.002942 - 1892 -0.015358 0.009799 -0.025507 - 1893 -0.009827 0.001263 -0.015038 - 1894 0.002515 0.004808 -0.006083 - 1895 -0.001395 -0.005178 0.010798 - 1896 0.005498 0.001296 -0.013456 - 1897 -0.006679 0.000004 0.000833 - 1898 -0.006339 0.003210 0.000555 - 1899 -0.007815 -0.000155 0.006317 - 1900 -0.003334 -0.000730 -0.000139 - 1901 -0.003197 -0.021225 -0.009098 - 1902 0.003310 -0.008203 -0.004863 - 1903 -0.007379 0.001152 -0.003847 - 1904 -0.008175 0.003836 -0.004939 - 1905 -0.007216 0.002039 -0.012076 - 1906 -0.002751 -0.006050 -0.001404 - 1907 -0.005827 0.008129 0.005351 - 1908 0.010377 0.010628 0.018761 - 1909 -0.002571 -0.007065 0.006215 - 1910 -0.004848 -0.014622 0.001577 - 1911 -0.004351 -0.002361 0.020679 - 1912 0.006139 0.001291 0.002464 - 1913 0.004939 0.003608 0.002097 - 1914 0.004274 0.000152 0.002451 - 1915 0.002989 0.000832 -0.000352 - 1916 -0.014159 -0.000914 0.002187 - 1917 0.012237 -0.003167 0.009134 - 1918 -0.004575 -0.001662 0.000082 - 1919 -0.007883 -0.002056 0.002571 - 1920 -0.003336 -0.001305 -0.000658 - 1921 0.004366 0.000439 0.001158 - 1922 -0.000155 0.003368 0.010592 - 1923 -0.014972 -0.009424 -0.018312 - 1924 -0.000613 -0.002374 0.000797 - 1925 0.007460 -0.016336 -0.000977 - 1926 -0.006787 0.004573 0.010255 - 1927 -0.002452 -0.000122 0.000124 - 1928 -0.015584 -0.009431 -0.007285 - 1929 -0.000101 0.008080 -0.015191 - 1930 0.002197 0.002310 -0.001612 - 1931 0.016237 -0.005090 0.018070 - 1932 0.001709 -0.003220 -0.011865 - 1933 -0.001150 0.000898 0.004173 - 1934 0.000323 -0.000312 -0.014495 - 1935 0.000516 -0.000491 -0.011422 - 1936 -0.005815 -0.002965 0.000187 - 1937 0.008195 0.018425 -0.027236 - 1938 -0.010921 -0.007575 -0.002217 - 1939 -0.004740 0.002745 0.006330 - 1940 0.002035 0.006523 0.010880 - 1941 -0.012191 0.004818 0.006605 - 1942 -0.003197 -0.004418 -0.003375 - 1943 0.003590 -0.017196 0.008070 - 1944 0.004548 0.006106 0.016045 - 1945 0.005444 0.002200 0.004561 - 1946 0.004448 0.009092 -0.001577 - 1947 -0.000522 0.006033 0.006559 - 1948 0.005450 0.001267 0.002269 - 1949 0.027952 -0.012604 0.001935 - 1950 -0.004826 -0.018174 0.014813 - 1951 0.005498 -0.000626 0.001156 - 1952 0.001428 -0.010472 0.000805 - 1953 -0.010198 -0.005573 -0.014564 - 1954 0.001605 -0.006572 0.005587 - 1955 -0.002403 -0.004981 0.000460 - 1956 0.010287 -0.003414 0.005774 - 1957 -0.005679 0.003540 -0.003175 - 1958 -0.005054 0.005203 -0.002733 - 1959 -0.006462 0.003843 0.002657 - 1960 -0.006606 -0.002499 -0.001538 - 1961 0.027567 -0.002565 0.034908 - 1962 0.001905 -0.003739 -0.001134 - 1963 -0.000871 0.002779 0.006534 - 1964 -0.013473 -0.002631 0.001200 - 1965 -0.008136 0.003625 0.001725 - 1966 0.002375 -0.002767 -0.000214 - 1967 0.015603 0.001192 0.006785 - 1968 -0.008229 0.002751 0.010337 - 1969 -0.002111 -0.006139 0.006236 - 1970 0.025783 -0.003684 0.015052 - 1971 -0.008026 -0.018580 0.028847 - 1972 -0.001966 -0.005103 0.002533 - 1973 0.025504 -0.012928 0.014439 - 1974 0.015919 0.008653 -0.013047 - 1975 -0.002145 -0.003853 -0.002353 - 1976 0.020573 0.023626 0.033600 - 1977 0.002418 -0.000127 0.000258 - 1978 -0.000168 -0.002747 0.002505 - 1979 0.011847 0.007945 0.003222 - 1980 0.002222 -0.001343 0.005437 - 1981 -0.004734 0.003071 -0.000955 - 1982 0.003752 -0.001882 -0.005052 - 1983 -0.008195 0.007844 0.004577 - 1984 0.007575 0.002209 -0.000466 - 1985 -0.005510 0.009650 -0.004399 - 1986 0.018263 0.019292 -0.008157 - 1987 -0.005098 -0.001581 -0.000328 - 1988 -0.004522 -0.021884 -0.005509 - 1989 -0.001598 -0.001668 0.002704 - 1990 -0.000494 0.002205 0.012458 - 1991 0.003153 0.001522 0.015672 - 1992 -0.000092 -0.002603 0.010098 - 1993 0.001919 -0.007389 0.001539 - 1994 -0.002690 -0.003376 -0.009963 - 1995 -0.005006 0.002932 -0.001670 - 1996 -0.003089 -0.005736 0.003689 - 1997 0.010713 -0.027613 -0.023000 - 1998 -0.006878 0.009457 0.006998 - 1999 -0.001817 0.000266 -0.004238 - 2000 -0.010974 0.005190 0.000117 - 2001 -0.008937 -0.003277 0.004337 - 2002 -0.000987 -0.001334 -0.004265 - 2003 -0.022280 -0.011677 -0.018343 - 2004 -0.010076 -0.005729 -0.026032 - -Bonds - - 1 3 1 7 - 2 2 1 3 - 3 1 1 2 - 4 4 2 5 - 5 4 2 6 - 6 4 2 4 - 7 6 7 19 - 8 5 7 8 - 9 1 8 9 - 10 7 8 11 - 11 8 8 20 - 12 3 9 28 - 13 2 9 10 - 14 10 11 21 - 15 9 11 12 - 16 10 11 22 - 17 11 12 14 - 18 11 12 13 - 19 12 13 23 - 20 11 13 15 - 21 12 14 24 - 22 11 14 16 - 23 11 15 17 - 24 12 15 25 - 25 11 16 17 - 26 12 16 26 - 27 13 17 18 - 28 14 18 27 - 29 5 28 29 - 30 6 28 32 - 31 1 29 30 - 32 8 29 33 - 33 8 29 34 - 34 3 30 35 - 35 2 30 31 - 36 5 35 36 - 37 6 35 39 - 38 1 36 37 - 39 8 36 40 - 40 8 36 41 - 41 2 37 38 - 42 3 37 42 - 43 6 42 53 - 44 5 42 43 - 45 1 43 44 - 46 7 43 46 - 47 8 43 54 - 48 3 44 62 - 49 2 44 45 - 50 10 46 56 - 51 10 46 55 - 52 9 46 47 - 53 11 47 48 - 54 11 47 49 - 55 11 48 50 - 56 12 48 57 - 57 11 49 51 - 58 12 49 58 - 59 11 50 52 - 60 12 50 59 - 61 11 51 52 - 62 12 51 60 - 63 12 52 61 - 64 6 62 70 - 65 5 62 63 - 66 7 63 66 - 67 1 63 64 - 68 8 63 71 - 69 2 64 65 - 70 3 64 79 - 71 15 66 67 - 72 10 66 73 - 73 10 66 72 - 74 10 67 75 - 75 10 67 74 - 76 16 67 68 - 77 17 68 69 - 78 4 69 76 - 79 4 69 78 - 80 4 69 77 - 81 5 79 80 - 82 6 79 81 - 83 4 80 84 - 84 4 80 83 - 85 4 80 82 - 86 18 85 86 - 87 18 85 87 - 88 18 88 90 - 89 18 88 89 - 90 18 91 93 - 91 18 91 92 - 92 18 94 96 - 93 18 94 95 - 94 18 97 98 - 95 18 97 99 - 96 18 100 101 - 97 18 100 102 - 98 18 103 104 - 99 18 103 105 - 100 18 106 107 - 101 18 106 108 - 102 18 109 111 - 103 18 109 110 - 104 18 112 114 - 105 18 112 113 - 106 18 115 116 - 107 18 115 117 - 108 18 118 120 - 109 18 118 119 - 110 18 121 123 - 111 18 121 122 - 112 18 124 126 - 113 18 124 125 - 114 18 127 128 - 115 18 127 129 - 116 18 130 132 - 117 18 130 131 - 118 18 133 134 - 119 18 133 135 - 120 18 136 137 - 121 18 136 138 - 122 18 139 140 - 123 18 139 141 - 124 18 142 144 - 125 18 142 143 - 126 18 145 147 - 127 18 145 146 - 128 18 148 150 - 129 18 148 149 - 130 18 151 152 - 131 18 151 153 - 132 18 154 156 - 133 18 154 155 - 134 18 157 159 - 135 18 157 158 - 136 18 160 162 - 137 18 160 161 - 138 18 163 164 - 139 18 163 165 - 140 18 166 168 - 141 18 166 167 - 142 18 169 171 - 143 18 169 170 - 144 18 172 174 - 145 18 172 173 - 146 18 175 177 - 147 18 175 176 - 148 18 178 180 - 149 18 178 179 - 150 18 181 182 - 151 18 181 183 - 152 18 184 186 - 153 18 184 185 - 154 18 187 188 - 155 18 187 189 - 156 18 190 191 - 157 18 190 192 - 158 18 193 194 - 159 18 193 195 - 160 18 196 197 - 161 18 196 198 - 162 18 199 201 - 163 18 199 200 - 164 18 202 204 - 165 18 202 203 - 166 18 205 206 - 167 18 205 207 - 168 18 208 210 - 169 18 208 209 - 170 18 211 212 - 171 18 211 213 - 172 18 214 215 - 173 18 214 216 - 174 18 217 219 - 175 18 217 218 - 176 18 220 222 - 177 18 220 221 - 178 18 223 224 - 179 18 223 225 - 180 18 226 228 - 181 18 226 227 - 182 18 229 231 - 183 18 229 230 - 184 18 232 233 - 185 18 232 234 - 186 18 235 236 - 187 18 235 237 - 188 18 238 240 - 189 18 238 239 - 190 18 241 242 - 191 18 241 243 - 192 18 244 246 - 193 18 244 245 - 194 18 247 248 - 195 18 247 249 - 196 18 250 251 - 197 18 250 252 - 198 18 253 254 - 199 18 253 255 - 200 18 256 257 - 201 18 256 258 - 202 18 259 261 - 203 18 259 260 - 204 18 262 264 - 205 18 262 263 - 206 18 265 266 - 207 18 265 267 - 208 18 268 269 - 209 18 268 270 - 210 18 271 272 - 211 18 271 273 - 212 18 274 275 - 213 18 274 276 - 214 18 277 279 - 215 18 277 278 - 216 18 280 282 - 217 18 280 281 - 218 18 283 284 - 219 18 283 285 - 220 18 286 287 - 221 18 286 288 - 222 18 289 290 - 223 18 289 291 - 224 18 292 294 - 225 18 292 293 - 226 18 295 296 - 227 18 295 297 - 228 18 298 299 - 229 18 298 300 - 230 18 301 303 - 231 18 301 302 - 232 18 304 305 - 233 18 304 306 - 234 18 307 309 - 235 18 307 308 - 236 18 310 311 - 237 18 310 312 - 238 18 313 314 - 239 18 313 315 - 240 18 316 317 - 241 18 316 318 - 242 18 319 321 - 243 18 319 320 - 244 18 322 323 - 245 18 322 324 - 246 18 325 327 - 247 18 325 326 - 248 18 328 329 - 249 18 328 330 - 250 18 331 332 - 251 18 331 333 - 252 18 334 335 - 253 18 334 336 - 254 18 337 339 - 255 18 337 338 - 256 18 340 341 - 257 18 340 342 - 258 18 343 344 - 259 18 343 345 - 260 18 346 347 - 261 18 346 348 - 262 18 349 350 - 263 18 349 351 - 264 18 352 353 - 265 18 352 354 - 266 18 355 356 - 267 18 355 357 - 268 18 358 359 - 269 18 358 360 - 270 18 361 362 - 271 18 361 363 - 272 18 364 365 - 273 18 364 366 - 274 18 367 369 - 275 18 367 368 - 276 18 370 372 - 277 18 370 371 - 278 18 373 374 - 279 18 373 375 - 280 18 376 378 - 281 18 376 377 - 282 18 379 381 - 283 18 379 380 - 284 18 382 383 - 285 18 382 384 - 286 18 385 386 - 287 18 385 387 - 288 18 388 390 - 289 18 388 389 - 290 18 391 393 - 291 18 391 392 - 292 18 394 395 - 293 18 394 396 - 294 18 397 399 - 295 18 397 398 - 296 18 400 402 - 297 18 400 401 - 298 18 403 405 - 299 18 403 404 - 300 18 406 407 - 301 18 406 408 - 302 18 409 411 - 303 18 409 410 - 304 18 412 413 - 305 18 412 414 - 306 18 415 417 - 307 18 415 416 - 308 18 418 420 - 309 18 418 419 - 310 18 421 422 - 311 18 421 423 - 312 18 424 425 - 313 18 424 426 - 314 18 427 428 - 315 18 427 429 - 316 18 430 432 - 317 18 430 431 - 318 18 433 435 - 319 18 433 434 - 320 18 436 437 - 321 18 436 438 - 322 18 439 440 - 323 18 439 441 - 324 18 442 443 - 325 18 442 444 - 326 18 445 447 - 327 18 445 446 - 328 18 448 449 - 329 18 448 450 - 330 18 451 453 - 331 18 451 452 - 332 18 454 456 - 333 18 454 455 - 334 18 457 458 - 335 18 457 459 - 336 18 460 462 - 337 18 460 461 - 338 18 463 465 - 339 18 463 464 - 340 18 466 467 - 341 18 466 468 - 342 18 469 470 - 343 18 469 471 - 344 18 472 473 - 345 18 472 474 - 346 18 475 476 - 347 18 475 477 - 348 18 478 479 - 349 18 478 480 - 350 18 481 482 - 351 18 481 483 - 352 18 484 485 - 353 18 484 486 - 354 18 487 489 - 355 18 487 488 - 356 18 490 492 - 357 18 490 491 - 358 18 493 495 - 359 18 493 494 - 360 18 496 497 - 361 18 496 498 - 362 18 499 501 - 363 18 499 500 - 364 18 502 503 - 365 18 502 504 - 366 18 505 507 - 367 18 505 506 - 368 18 508 509 - 369 18 508 510 - 370 18 511 513 - 371 18 511 512 - 372 18 514 516 - 373 18 514 515 - 374 18 517 518 - 375 18 517 519 - 376 18 520 521 - 377 18 520 522 - 378 18 523 525 - 379 18 523 524 - 380 18 526 528 - 381 18 526 527 - 382 18 529 530 - 383 18 529 531 - 384 18 532 533 - 385 18 532 534 - 386 18 535 536 - 387 18 535 537 - 388 18 538 540 - 389 18 538 539 - 390 18 541 542 - 391 18 541 543 - 392 18 544 546 - 393 18 544 545 - 394 18 547 549 - 395 18 547 548 - 396 18 550 551 - 397 18 550 552 - 398 18 553 555 - 399 18 553 554 - 400 18 556 557 - 401 18 556 558 - 402 18 559 561 - 403 18 559 560 - 404 18 562 563 - 405 18 562 564 - 406 18 565 567 - 407 18 565 566 - 408 18 568 570 - 409 18 568 569 - 410 18 571 573 - 411 18 571 572 - 412 18 574 575 - 413 18 574 576 - 414 18 577 579 - 415 18 577 578 - 416 18 580 581 - 417 18 580 582 - 418 18 583 585 - 419 18 583 584 - 420 18 586 588 - 421 18 586 587 - 422 18 589 590 - 423 18 589 591 - 424 18 592 594 - 425 18 592 593 - 426 18 595 597 - 427 18 595 596 - 428 18 598 600 - 429 18 598 599 - 430 18 601 602 - 431 18 601 603 - 432 18 604 606 - 433 18 604 605 - 434 18 607 609 - 435 18 607 608 - 436 18 610 611 - 437 18 610 612 - 438 18 613 615 - 439 18 613 614 - 440 18 616 618 - 441 18 616 617 - 442 18 619 620 - 443 18 619 621 - 444 18 622 623 - 445 18 622 624 - 446 18 625 627 - 447 18 625 626 - 448 18 628 629 - 449 18 628 630 - 450 18 631 632 - 451 18 631 633 - 452 18 634 635 - 453 18 634 636 - 454 18 637 639 - 455 18 637 638 - 456 18 640 642 - 457 18 640 641 - 458 18 643 644 - 459 18 643 645 - 460 18 646 647 - 461 18 646 648 - 462 18 649 650 - 463 18 649 651 - 464 18 652 653 - 465 18 652 654 - 466 18 655 657 - 467 18 655 656 - 468 18 658 660 - 469 18 658 659 - 470 18 661 663 - 471 18 661 662 - 472 18 664 665 - 473 18 664 666 - 474 18 667 669 - 475 18 667 668 - 476 18 670 672 - 477 18 670 671 - 478 18 673 674 - 479 18 673 675 - 480 18 676 677 - 481 18 676 678 - 482 18 679 681 - 483 18 679 680 - 484 18 682 684 - 485 18 682 683 - 486 18 685 686 - 487 18 685 687 - 488 18 688 690 - 489 18 688 689 - 490 18 691 693 - 491 18 691 692 - 492 18 694 695 - 493 18 694 696 - 494 18 697 698 - 495 18 697 699 - 496 18 700 701 - 497 18 700 702 - 498 18 703 704 - 499 18 703 705 - 500 18 706 707 - 501 18 706 708 - 502 18 709 710 - 503 18 709 711 - 504 18 712 714 - 505 18 712 713 - 506 18 715 716 - 507 18 715 717 - 508 18 718 719 - 509 18 718 720 - 510 18 721 722 - 511 18 721 723 - 512 18 724 726 - 513 18 724 725 - 514 18 727 728 - 515 18 727 729 - 516 18 730 731 - 517 18 730 732 - 518 18 733 735 - 519 18 733 734 - 520 18 736 737 - 521 18 736 738 - 522 18 739 741 - 523 18 739 740 - 524 18 742 743 - 525 18 742 744 - 526 18 745 746 - 527 18 745 747 - 528 18 748 750 - 529 18 748 749 - 530 18 751 753 - 531 18 751 752 - 532 18 754 756 - 533 18 754 755 - 534 18 757 758 - 535 18 757 759 - 536 18 760 762 - 537 18 760 761 - 538 18 763 764 - 539 18 763 765 - 540 18 766 767 - 541 18 766 768 - 542 18 769 770 - 543 18 769 771 - 544 18 772 774 - 545 18 772 773 - 546 18 775 777 - 547 18 775 776 - 548 18 778 780 - 549 18 778 779 - 550 18 781 783 - 551 18 781 782 - 552 18 784 786 - 553 18 784 785 - 554 18 787 789 - 555 18 787 788 - 556 18 790 791 - 557 18 790 792 - 558 18 793 795 - 559 18 793 794 - 560 18 796 797 - 561 18 796 798 - 562 18 799 801 - 563 18 799 800 - 564 18 802 803 - 565 18 802 804 - 566 18 805 806 - 567 18 805 807 - 568 18 808 809 - 569 18 808 810 - 570 18 811 813 - 571 18 811 812 - 572 18 814 815 - 573 18 814 816 - 574 18 817 818 - 575 18 817 819 - 576 18 820 821 - 577 18 820 822 - 578 18 823 824 - 579 18 823 825 - 580 18 826 828 - 581 18 826 827 - 582 18 829 830 - 583 18 829 831 - 584 18 832 834 - 585 18 832 833 - 586 18 835 837 - 587 18 835 836 - 588 18 838 839 - 589 18 838 840 - 590 18 841 842 - 591 18 841 843 - 592 18 844 845 - 593 18 844 846 - 594 18 847 848 - 595 18 847 849 - 596 18 850 852 - 597 18 850 851 - 598 18 853 854 - 599 18 853 855 - 600 18 856 858 - 601 18 856 857 - 602 18 859 861 - 603 18 859 860 - 604 18 862 863 - 605 18 862 864 - 606 18 865 866 - 607 18 865 867 - 608 18 868 869 - 609 18 868 870 - 610 18 871 873 - 611 18 871 872 - 612 18 874 875 - 613 18 874 876 - 614 18 877 878 - 615 18 877 879 - 616 18 880 882 - 617 18 880 881 - 618 18 883 884 - 619 18 883 885 - 620 18 886 887 - 621 18 886 888 - 622 18 889 891 - 623 18 889 890 - 624 18 892 894 - 625 18 892 893 - 626 18 895 896 - 627 18 895 897 - 628 18 898 899 - 629 18 898 900 - 630 18 901 903 - 631 18 901 902 - 632 18 904 905 - 633 18 904 906 - 634 18 907 908 - 635 18 907 909 - 636 18 910 911 - 637 18 910 912 - 638 18 913 915 - 639 18 913 914 - 640 18 916 917 - 641 18 916 918 - 642 18 919 920 - 643 18 919 921 - 644 18 922 924 - 645 18 922 923 - 646 18 925 927 - 647 18 925 926 - 648 18 928 930 - 649 18 928 929 - 650 18 931 932 - 651 18 931 933 - 652 18 934 935 - 653 18 934 936 - 654 18 937 939 - 655 18 937 938 - 656 18 940 942 - 657 18 940 941 - 658 18 943 945 - 659 18 943 944 - 660 18 946 948 - 661 18 946 947 - 662 18 949 950 - 663 18 949 951 - 664 18 952 953 - 665 18 952 954 - 666 18 955 956 - 667 18 955 957 - 668 18 958 960 - 669 18 958 959 - 670 18 961 963 - 671 18 961 962 - 672 18 964 965 - 673 18 964 966 - 674 18 967 969 - 675 18 967 968 - 676 18 970 972 - 677 18 970 971 - 678 18 973 975 - 679 18 973 974 - 680 18 976 978 - 681 18 976 977 - 682 18 979 981 - 683 18 979 980 - 684 18 982 983 - 685 18 982 984 - 686 18 985 987 - 687 18 985 986 - 688 18 988 989 - 689 18 988 990 - 690 18 991 993 - 691 18 991 992 - 692 18 994 996 - 693 18 994 995 - 694 18 997 998 - 695 18 997 999 - 696 18 1000 1001 - 697 18 1000 1002 - 698 18 1003 1005 - 699 18 1003 1004 - 700 18 1006 1007 - 701 18 1006 1008 - 702 18 1009 1011 - 703 18 1009 1010 - 704 18 1012 1013 - 705 18 1012 1014 - 706 18 1015 1017 - 707 18 1015 1016 - 708 18 1018 1020 - 709 18 1018 1019 - 710 18 1021 1023 - 711 18 1021 1022 - 712 18 1024 1025 - 713 18 1024 1026 - 714 18 1027 1028 - 715 18 1027 1029 - 716 18 1030 1032 - 717 18 1030 1031 - 718 18 1033 1034 - 719 18 1033 1035 - 720 18 1036 1037 - 721 18 1036 1038 - 722 18 1039 1041 - 723 18 1039 1040 - 724 18 1042 1043 - 725 18 1042 1044 - 726 18 1045 1046 - 727 18 1045 1047 - 728 18 1048 1050 - 729 18 1048 1049 - 730 18 1051 1053 - 731 18 1051 1052 - 732 18 1054 1056 - 733 18 1054 1055 - 734 18 1057 1058 - 735 18 1057 1059 - 736 18 1060 1062 - 737 18 1060 1061 - 738 18 1063 1064 - 739 18 1063 1065 - 740 18 1066 1068 - 741 18 1066 1067 - 742 18 1069 1071 - 743 18 1069 1070 - 744 18 1072 1074 - 745 18 1072 1073 - 746 18 1075 1077 - 747 18 1075 1076 - 748 18 1078 1079 - 749 18 1078 1080 - 750 18 1081 1082 - 751 18 1081 1083 - 752 18 1084 1085 - 753 18 1084 1086 - 754 18 1087 1089 - 755 18 1087 1088 - 756 18 1090 1092 - 757 18 1090 1091 - 758 18 1093 1095 - 759 18 1093 1094 - 760 18 1096 1097 - 761 18 1096 1098 - 762 18 1099 1100 - 763 18 1099 1101 - 764 18 1102 1103 - 765 18 1102 1104 - 766 18 1105 1107 - 767 18 1105 1106 - 768 18 1108 1110 - 769 18 1108 1109 - 770 18 1111 1112 - 771 18 1111 1113 - 772 18 1114 1116 - 773 18 1114 1115 - 774 18 1117 1119 - 775 18 1117 1118 - 776 18 1120 1121 - 777 18 1120 1122 - 778 18 1123 1124 - 779 18 1123 1125 - 780 18 1126 1128 - 781 18 1126 1127 - 782 18 1129 1130 - 783 18 1129 1131 - 784 18 1132 1133 - 785 18 1132 1134 - 786 18 1135 1137 - 787 18 1135 1136 - 788 18 1138 1140 - 789 18 1138 1139 - 790 18 1141 1142 - 791 18 1141 1143 - 792 18 1144 1146 - 793 18 1144 1145 - 794 18 1147 1149 - 795 18 1147 1148 - 796 18 1150 1152 - 797 18 1150 1151 - 798 18 1153 1155 - 799 18 1153 1154 - 800 18 1156 1158 - 801 18 1156 1157 - 802 18 1159 1160 - 803 18 1159 1161 - 804 18 1162 1164 - 805 18 1162 1163 - 806 18 1165 1166 - 807 18 1165 1167 - 808 18 1168 1170 - 809 18 1168 1169 - 810 18 1171 1172 - 811 18 1171 1173 - 812 18 1174 1175 - 813 18 1174 1176 - 814 18 1177 1179 - 815 18 1177 1178 - 816 18 1180 1182 - 817 18 1180 1181 - 818 18 1183 1185 - 819 18 1183 1184 - 820 18 1186 1187 - 821 18 1186 1188 - 822 18 1189 1190 - 823 18 1189 1191 - 824 18 1192 1194 - 825 18 1192 1193 - 826 18 1195 1196 - 827 18 1195 1197 - 828 18 1198 1199 - 829 18 1198 1200 - 830 18 1201 1202 - 831 18 1201 1203 - 832 18 1204 1205 - 833 18 1204 1206 - 834 18 1207 1209 - 835 18 1207 1208 - 836 18 1210 1212 - 837 18 1210 1211 - 838 18 1213 1214 - 839 18 1213 1215 - 840 18 1216 1218 - 841 18 1216 1217 - 842 18 1219 1221 - 843 18 1219 1220 - 844 18 1222 1224 - 845 18 1222 1223 - 846 18 1225 1226 - 847 18 1225 1227 - 848 18 1228 1229 - 849 18 1228 1230 - 850 18 1231 1232 - 851 18 1231 1233 - 852 18 1234 1236 - 853 18 1234 1235 - 854 18 1237 1239 - 855 18 1237 1238 - 856 18 1240 1242 - 857 18 1240 1241 - 858 18 1243 1244 - 859 18 1243 1245 - 860 18 1246 1248 - 861 18 1246 1247 - 862 18 1249 1250 - 863 18 1249 1251 - 864 18 1252 1254 - 865 18 1252 1253 - 866 18 1255 1256 - 867 18 1255 1257 - 868 18 1258 1259 - 869 18 1258 1260 - 870 18 1261 1263 - 871 18 1261 1262 - 872 18 1264 1265 - 873 18 1264 1266 - 874 18 1267 1268 - 875 18 1267 1269 - 876 18 1270 1271 - 877 18 1270 1272 - 878 18 1273 1274 - 879 18 1273 1275 - 880 18 1276 1277 - 881 18 1276 1278 - 882 18 1279 1280 - 883 18 1279 1281 - 884 18 1282 1283 - 885 18 1282 1284 - 886 18 1285 1286 - 887 18 1285 1287 - 888 18 1288 1289 - 889 18 1288 1290 - 890 18 1291 1293 - 891 18 1291 1292 - 892 18 1294 1295 - 893 18 1294 1296 - 894 18 1297 1299 - 895 18 1297 1298 - 896 18 1300 1302 - 897 18 1300 1301 - 898 18 1303 1304 - 899 18 1303 1305 - 900 18 1306 1308 - 901 18 1306 1307 - 902 18 1309 1311 - 903 18 1309 1310 - 904 18 1312 1314 - 905 18 1312 1313 - 906 18 1315 1317 - 907 18 1315 1316 - 908 18 1318 1320 - 909 18 1318 1319 - 910 18 1321 1323 - 911 18 1321 1322 - 912 18 1324 1325 - 913 18 1324 1326 - 914 18 1327 1329 - 915 18 1327 1328 - 916 18 1330 1332 - 917 18 1330 1331 - 918 18 1333 1334 - 919 18 1333 1335 - 920 18 1336 1337 - 921 18 1336 1338 - 922 18 1339 1340 - 923 18 1339 1341 - 924 18 1342 1344 - 925 18 1342 1343 - 926 18 1345 1347 - 927 18 1345 1346 - 928 18 1348 1350 - 929 18 1348 1349 - 930 18 1351 1352 - 931 18 1351 1353 - 932 18 1354 1355 - 933 18 1354 1356 - 934 18 1357 1358 - 935 18 1357 1359 - 936 18 1360 1362 - 937 18 1360 1361 - 938 18 1363 1365 - 939 18 1363 1364 - 940 18 1366 1368 - 941 18 1366 1367 - 942 18 1369 1370 - 943 18 1369 1371 - 944 18 1372 1373 - 945 18 1372 1374 - 946 18 1375 1377 - 947 18 1375 1376 - 948 18 1378 1379 - 949 18 1378 1380 - 950 18 1381 1382 - 951 18 1381 1383 - 952 18 1384 1385 - 953 18 1384 1386 - 954 18 1387 1388 - 955 18 1387 1389 - 956 18 1390 1392 - 957 18 1390 1391 - 958 18 1393 1395 - 959 18 1393 1394 - 960 18 1396 1397 - 961 18 1396 1398 - 962 18 1399 1401 - 963 18 1399 1400 - 964 18 1402 1403 - 965 18 1402 1404 - 966 18 1405 1406 - 967 18 1405 1407 - 968 18 1408 1409 - 969 18 1408 1410 - 970 18 1411 1412 - 971 18 1411 1413 - 972 18 1414 1416 - 973 18 1414 1415 - 974 18 1417 1419 - 975 18 1417 1418 - 976 18 1420 1422 - 977 18 1420 1421 - 978 18 1423 1425 - 979 18 1423 1424 - 980 18 1426 1428 - 981 18 1426 1427 - 982 18 1429 1430 - 983 18 1429 1431 - 984 18 1432 1434 - 985 18 1432 1433 - 986 18 1435 1436 - 987 18 1435 1437 - 988 18 1438 1439 - 989 18 1438 1440 - 990 18 1441 1442 - 991 18 1441 1443 - 992 18 1444 1445 - 993 18 1444 1446 - 994 18 1447 1448 - 995 18 1447 1449 - 996 18 1450 1451 - 997 18 1450 1452 - 998 18 1453 1455 - 999 18 1453 1454 - 1000 18 1456 1457 - 1001 18 1456 1458 - 1002 18 1459 1461 - 1003 18 1459 1460 - 1004 18 1462 1463 - 1005 18 1462 1464 - 1006 18 1465 1466 - 1007 18 1465 1467 - 1008 18 1468 1470 - 1009 18 1468 1469 - 1010 18 1471 1472 - 1011 18 1471 1473 - 1012 18 1474 1476 - 1013 18 1474 1475 - 1014 18 1477 1478 - 1015 18 1477 1479 - 1016 18 1480 1482 - 1017 18 1480 1481 - 1018 18 1483 1485 - 1019 18 1483 1484 - 1020 18 1486 1488 - 1021 18 1486 1487 - 1022 18 1489 1491 - 1023 18 1489 1490 - 1024 18 1492 1493 - 1025 18 1492 1494 - 1026 18 1495 1496 - 1027 18 1495 1497 - 1028 18 1498 1499 - 1029 18 1498 1500 - 1030 18 1501 1502 - 1031 18 1501 1503 - 1032 18 1504 1505 - 1033 18 1504 1506 - 1034 18 1507 1509 - 1035 18 1507 1508 - 1036 18 1510 1512 - 1037 18 1510 1511 - 1038 18 1513 1515 - 1039 18 1513 1514 - 1040 18 1516 1518 - 1041 18 1516 1517 - 1042 18 1519 1520 - 1043 18 1519 1521 - 1044 18 1522 1524 - 1045 18 1522 1523 - 1046 18 1525 1526 - 1047 18 1525 1527 - 1048 18 1528 1529 - 1049 18 1528 1530 - 1050 18 1531 1533 - 1051 18 1531 1532 - 1052 18 1534 1536 - 1053 18 1534 1535 - 1054 18 1537 1539 - 1055 18 1537 1538 - 1056 18 1540 1541 - 1057 18 1540 1542 - 1058 18 1543 1545 - 1059 18 1543 1544 - 1060 18 1546 1547 - 1061 18 1546 1548 - 1062 18 1549 1551 - 1063 18 1549 1550 - 1064 18 1552 1553 - 1065 18 1552 1554 - 1066 18 1555 1557 - 1067 18 1555 1556 - 1068 18 1558 1559 - 1069 18 1558 1560 - 1070 18 1561 1562 - 1071 18 1561 1563 - 1072 18 1564 1565 - 1073 18 1564 1566 - 1074 18 1567 1569 - 1075 18 1567 1568 - 1076 18 1570 1571 - 1077 18 1570 1572 - 1078 18 1573 1575 - 1079 18 1573 1574 - 1080 18 1576 1578 - 1081 18 1576 1577 - 1082 18 1579 1581 - 1083 18 1579 1580 - 1084 18 1582 1584 - 1085 18 1582 1583 - 1086 18 1585 1586 - 1087 18 1585 1587 - 1088 18 1588 1590 - 1089 18 1588 1589 - 1090 18 1591 1592 - 1091 18 1591 1593 - 1092 18 1594 1596 - 1093 18 1594 1595 - 1094 18 1597 1598 - 1095 18 1597 1599 - 1096 18 1600 1602 - 1097 18 1600 1601 - 1098 18 1603 1605 - 1099 18 1603 1604 - 1100 18 1606 1608 - 1101 18 1606 1607 - 1102 18 1609 1610 - 1103 18 1609 1611 - 1104 18 1612 1614 - 1105 18 1612 1613 - 1106 18 1615 1617 - 1107 18 1615 1616 - 1108 18 1618 1620 - 1109 18 1618 1619 - 1110 18 1621 1623 - 1111 18 1621 1622 - 1112 18 1624 1625 - 1113 18 1624 1626 - 1114 18 1627 1629 - 1115 18 1627 1628 - 1116 18 1630 1631 - 1117 18 1630 1632 - 1118 18 1633 1635 - 1119 18 1633 1634 - 1120 18 1636 1637 - 1121 18 1636 1638 - 1122 18 1639 1641 - 1123 18 1639 1640 - 1124 18 1642 1643 - 1125 18 1642 1644 - 1126 18 1645 1646 - 1127 18 1645 1647 - 1128 18 1648 1650 - 1129 18 1648 1649 - 1130 18 1651 1653 - 1131 18 1651 1652 - 1132 18 1654 1656 - 1133 18 1654 1655 - 1134 18 1657 1658 - 1135 18 1657 1659 - 1136 18 1660 1661 - 1137 18 1660 1662 - 1138 18 1663 1664 - 1139 18 1663 1665 - 1140 18 1666 1668 - 1141 18 1666 1667 - 1142 18 1669 1670 - 1143 18 1669 1671 - 1144 18 1672 1674 - 1145 18 1672 1673 - 1146 18 1675 1676 - 1147 18 1675 1677 - 1148 18 1678 1680 - 1149 18 1678 1679 - 1150 18 1681 1683 - 1151 18 1681 1682 - 1152 18 1684 1685 - 1153 18 1684 1686 - 1154 18 1687 1688 - 1155 18 1687 1689 - 1156 18 1690 1691 - 1157 18 1690 1692 - 1158 18 1693 1695 - 1159 18 1693 1694 - 1160 18 1696 1697 - 1161 18 1696 1698 - 1162 18 1699 1701 - 1163 18 1699 1700 - 1164 18 1702 1703 - 1165 18 1702 1704 - 1166 18 1705 1707 - 1167 18 1705 1706 - 1168 18 1708 1709 - 1169 18 1708 1710 - 1170 18 1711 1712 - 1171 18 1711 1713 - 1172 18 1714 1716 - 1173 18 1714 1715 - 1174 18 1717 1718 - 1175 18 1717 1719 - 1176 18 1720 1721 - 1177 18 1720 1722 - 1178 18 1723 1724 - 1179 18 1723 1725 - 1180 18 1726 1727 - 1181 18 1726 1728 - 1182 18 1729 1730 - 1183 18 1729 1731 - 1184 18 1732 1734 - 1185 18 1732 1733 - 1186 18 1735 1737 - 1187 18 1735 1736 - 1188 18 1738 1740 - 1189 18 1738 1739 - 1190 18 1741 1743 - 1191 18 1741 1742 - 1192 18 1744 1745 - 1193 18 1744 1746 - 1194 18 1747 1749 - 1195 18 1747 1748 - 1196 18 1750 1751 - 1197 18 1750 1752 - 1198 18 1753 1755 - 1199 18 1753 1754 - 1200 18 1756 1758 - 1201 18 1756 1757 - 1202 18 1759 1760 - 1203 18 1759 1761 - 1204 18 1762 1764 - 1205 18 1762 1763 - 1206 18 1765 1767 - 1207 18 1765 1766 - 1208 18 1768 1769 - 1209 18 1768 1770 - 1210 18 1771 1773 - 1211 18 1771 1772 - 1212 18 1774 1776 - 1213 18 1774 1775 - 1214 18 1777 1779 - 1215 18 1777 1778 - 1216 18 1780 1781 - 1217 18 1780 1782 - 1218 18 1783 1784 - 1219 18 1783 1785 - 1220 18 1786 1787 - 1221 18 1786 1788 - 1222 18 1789 1790 - 1223 18 1789 1791 - 1224 18 1792 1793 - 1225 18 1792 1794 - 1226 18 1795 1796 - 1227 18 1795 1797 - 1228 18 1798 1799 - 1229 18 1798 1800 - 1230 18 1801 1803 - 1231 18 1801 1802 - 1232 18 1804 1806 - 1233 18 1804 1805 - 1234 18 1807 1809 - 1235 18 1807 1808 - 1236 18 1810 1812 - 1237 18 1810 1811 - 1238 18 1813 1815 - 1239 18 1813 1814 - 1240 18 1816 1818 - 1241 18 1816 1817 - 1242 18 1819 1821 - 1243 18 1819 1820 - 1244 18 1822 1823 - 1245 18 1822 1824 - 1246 18 1825 1827 - 1247 18 1825 1826 - 1248 18 1828 1830 - 1249 18 1828 1829 - 1250 18 1831 1832 - 1251 18 1831 1833 - 1252 18 1834 1835 - 1253 18 1834 1836 - 1254 18 1837 1838 - 1255 18 1837 1839 - 1256 18 1840 1842 - 1257 18 1840 1841 - 1258 18 1843 1845 - 1259 18 1843 1844 - 1260 18 1846 1848 - 1261 18 1846 1847 - 1262 18 1849 1851 - 1263 18 1849 1850 - 1264 18 1852 1854 - 1265 18 1852 1853 - 1266 18 1855 1856 - 1267 18 1855 1857 - 1268 18 1858 1859 - 1269 18 1858 1860 - 1270 18 1861 1862 - 1271 18 1861 1863 - 1272 18 1864 1866 - 1273 18 1864 1865 - 1274 18 1867 1869 - 1275 18 1867 1868 - 1276 18 1870 1871 - 1277 18 1870 1872 - 1278 18 1873 1874 - 1279 18 1873 1875 - 1280 18 1876 1877 - 1281 18 1876 1878 - 1282 18 1879 1881 - 1283 18 1879 1880 - 1284 18 1882 1883 - 1285 18 1882 1884 - 1286 18 1885 1886 - 1287 18 1885 1887 - 1288 18 1888 1890 - 1289 18 1888 1889 - 1290 18 1891 1892 - 1291 18 1891 1893 - 1292 18 1894 1896 - 1293 18 1894 1895 - 1294 18 1897 1898 - 1295 18 1897 1899 - 1296 18 1900 1902 - 1297 18 1900 1901 - 1298 18 1903 1905 - 1299 18 1903 1904 - 1300 18 1906 1908 - 1301 18 1906 1907 - 1302 18 1909 1911 - 1303 18 1909 1910 - 1304 18 1912 1913 - 1305 18 1912 1914 - 1306 18 1915 1916 - 1307 18 1915 1917 - 1308 18 1918 1920 - 1309 18 1918 1919 - 1310 18 1921 1923 - 1311 18 1921 1922 - 1312 18 1924 1926 - 1313 18 1924 1925 - 1314 18 1927 1929 - 1315 18 1927 1928 - 1316 18 1930 1932 - 1317 18 1930 1931 - 1318 18 1933 1935 - 1319 18 1933 1934 - 1320 18 1936 1937 - 1321 18 1936 1938 - 1322 18 1939 1940 - 1323 18 1939 1941 - 1324 18 1942 1944 - 1325 18 1942 1943 - 1326 18 1945 1947 - 1327 18 1945 1946 - 1328 18 1948 1950 - 1329 18 1948 1949 - 1330 18 1951 1953 - 1331 18 1951 1952 - 1332 18 1954 1955 - 1333 18 1954 1956 - 1334 18 1957 1959 - 1335 18 1957 1958 - 1336 18 1960 1961 - 1337 18 1960 1962 - 1338 18 1963 1965 - 1339 18 1963 1964 - 1340 18 1966 1967 - 1341 18 1966 1968 - 1342 18 1969 1970 - 1343 18 1969 1971 - 1344 18 1972 1974 - 1345 18 1972 1973 - 1346 18 1975 1977 - 1347 18 1975 1976 - 1348 18 1978 1979 - 1349 18 1978 1980 - 1350 18 1981 1982 - 1351 18 1981 1983 - 1352 18 1984 1986 - 1353 18 1984 1985 - 1354 18 1987 1988 - 1355 18 1987 1989 - 1356 18 1990 1992 - 1357 18 1990 1991 - 1358 18 1993 1995 - 1359 18 1993 1994 - 1360 18 1996 1998 - 1361 18 1996 1997 - 1362 18 1999 2000 - 1363 18 1999 2001 - 1364 18 2002 2004 - 1365 18 2002 2003 - -Angles - - 1 5 2 1 7 - 2 4 2 1 3 - 3 6 3 1 7 - 4 7 4 2 5 - 5 7 5 2 6 - 6 1 1 2 5 - 7 1 1 2 6 - 8 1 1 2 4 - 9 7 4 2 6 - 10 2 1 7 8 - 11 3 1 7 19 - 12 11 8 7 19 - 13 9 7 8 11 - 14 8 7 8 9 - 15 16 11 8 20 - 16 15 9 8 20 - 17 14 9 8 11 - 18 10 7 8 20 - 19 5 8 9 28 - 20 4 8 9 10 - 21 6 10 9 28 - 22 18 12 11 22 - 23 23 21 11 22 - 24 12 8 11 12 - 25 13 8 11 21 - 26 18 12 11 21 - 27 13 8 11 22 - 28 19 13 12 14 - 29 17 11 12 14 - 30 17 11 12 13 - 31 20 15 13 23 - 32 20 12 13 23 - 33 19 12 13 15 - 34 20 12 14 24 - 35 20 16 14 24 - 36 19 12 14 16 - 37 20 13 15 25 - 38 20 17 15 25 - 39 19 13 15 17 - 40 20 14 16 26 - 41 19 14 16 17 - 42 20 17 16 26 - 43 21 15 17 18 - 44 19 15 17 16 - 45 21 16 17 18 - 46 22 17 18 27 - 47 2 9 28 29 - 48 3 9 28 32 - 49 11 29 28 32 - 50 15 30 29 34 - 51 10 28 29 33 - 52 10 28 29 34 - 53 15 30 29 33 - 54 24 33 29 34 - 55 8 28 29 30 - 56 6 31 30 35 - 57 5 29 30 35 - 58 4 29 30 31 - 59 2 30 35 36 - 60 3 30 35 39 - 61 11 36 35 39 - 62 8 35 36 37 - 63 10 35 36 41 - 64 10 35 36 40 - 65 24 40 36 41 - 66 15 37 36 40 - 67 15 37 36 41 - 68 6 38 37 42 - 69 5 36 37 42 - 70 4 36 37 38 - 71 11 43 42 53 - 72 2 37 42 43 - 73 3 37 42 53 - 74 10 42 43 54 - 75 16 46 43 54 - 76 14 44 43 46 - 77 9 42 43 46 - 78 8 42 43 44 - 79 15 44 43 54 - 80 5 43 44 62 - 81 6 45 44 62 - 82 4 43 44 45 - 83 13 43 46 55 - 84 13 43 46 56 - 85 12 43 46 47 - 86 23 55 46 56 - 87 18 47 46 56 - 88 18 47 46 55 - 89 17 46 47 49 - 90 17 46 47 48 - 91 19 48 47 49 - 92 20 50 48 57 - 93 19 47 48 50 - 94 20 47 48 57 - 95 20 51 49 58 - 96 19 47 49 51 - 97 20 47 49 58 - 98 20 48 50 59 - 99 19 48 50 52 - 100 20 52 50 59 - 101 20 52 51 60 - 102 20 49 51 60 - 103 19 49 51 52 - 104 20 50 52 61 - 105 19 50 52 51 - 106 20 51 52 61 - 107 2 44 62 63 - 108 3 44 62 70 - 109 11 63 62 70 - 110 16 66 63 71 - 111 15 64 63 71 - 112 14 64 63 66 - 113 10 62 63 71 - 114 9 62 63 66 - 115 8 62 63 64 - 116 4 63 64 65 - 117 6 65 64 79 - 118 5 63 64 79 - 119 23 72 66 73 - 120 27 67 66 73 - 121 27 67 66 72 - 122 25 63 66 67 - 123 13 63 66 73 - 124 13 63 66 72 - 125 29 68 67 75 - 126 23 74 67 75 - 127 29 68 67 74 - 128 26 66 67 68 - 129 27 66 67 74 - 130 27 66 67 75 - 131 28 67 68 69 - 132 29 68 69 76 - 133 29 68 69 77 - 134 29 68 69 78 - 135 7 76 69 78 - 136 7 76 69 77 - 137 7 77 69 78 - 138 3 64 79 81 - 139 2 64 79 80 - 140 11 80 79 81 - 141 7 83 80 84 - 142 30 79 80 84 - 143 7 82 80 83 - 144 30 79 80 83 - 145 30 79 80 82 - 146 7 82 80 84 - 147 31 86 85 87 - 148 31 89 88 90 - 149 31 92 91 93 - 150 31 95 94 96 - 151 31 98 97 99 - 152 31 101 100 102 - 153 31 104 103 105 - 154 31 107 106 108 - 155 31 110 109 111 - 156 31 113 112 114 - 157 31 116 115 117 - 158 31 119 118 120 - 159 31 122 121 123 - 160 31 125 124 126 - 161 31 128 127 129 - 162 31 131 130 132 - 163 31 134 133 135 - 164 31 137 136 138 - 165 31 140 139 141 - 166 31 143 142 144 - 167 31 146 145 147 - 168 31 149 148 150 - 169 31 152 151 153 - 170 31 155 154 156 - 171 31 158 157 159 - 172 31 161 160 162 - 173 31 164 163 165 - 174 31 167 166 168 - 175 31 170 169 171 - 176 31 173 172 174 - 177 31 176 175 177 - 178 31 179 178 180 - 179 31 182 181 183 - 180 31 185 184 186 - 181 31 188 187 189 - 182 31 191 190 192 - 183 31 194 193 195 - 184 31 197 196 198 - 185 31 200 199 201 - 186 31 203 202 204 - 187 31 206 205 207 - 188 31 209 208 210 - 189 31 212 211 213 - 190 31 215 214 216 - 191 31 218 217 219 - 192 31 221 220 222 - 193 31 224 223 225 - 194 31 227 226 228 - 195 31 230 229 231 - 196 31 233 232 234 - 197 31 236 235 237 - 198 31 239 238 240 - 199 31 242 241 243 - 200 31 245 244 246 - 201 31 248 247 249 - 202 31 251 250 252 - 203 31 254 253 255 - 204 31 257 256 258 - 205 31 260 259 261 - 206 31 263 262 264 - 207 31 266 265 267 - 208 31 269 268 270 - 209 31 272 271 273 - 210 31 275 274 276 - 211 31 278 277 279 - 212 31 281 280 282 - 213 31 284 283 285 - 214 31 287 286 288 - 215 31 290 289 291 - 216 31 293 292 294 - 217 31 296 295 297 - 218 31 299 298 300 - 219 31 302 301 303 - 220 31 305 304 306 - 221 31 308 307 309 - 222 31 311 310 312 - 223 31 314 313 315 - 224 31 317 316 318 - 225 31 320 319 321 - 226 31 323 322 324 - 227 31 326 325 327 - 228 31 329 328 330 - 229 31 332 331 333 - 230 31 335 334 336 - 231 31 338 337 339 - 232 31 341 340 342 - 233 31 344 343 345 - 234 31 347 346 348 - 235 31 350 349 351 - 236 31 353 352 354 - 237 31 356 355 357 - 238 31 359 358 360 - 239 31 362 361 363 - 240 31 365 364 366 - 241 31 368 367 369 - 242 31 371 370 372 - 243 31 374 373 375 - 244 31 377 376 378 - 245 31 380 379 381 - 246 31 383 382 384 - 247 31 386 385 387 - 248 31 389 388 390 - 249 31 392 391 393 - 250 31 395 394 396 - 251 31 398 397 399 - 252 31 401 400 402 - 253 31 404 403 405 - 254 31 407 406 408 - 255 31 410 409 411 - 256 31 413 412 414 - 257 31 416 415 417 - 258 31 419 418 420 - 259 31 422 421 423 - 260 31 425 424 426 - 261 31 428 427 429 - 262 31 431 430 432 - 263 31 434 433 435 - 264 31 437 436 438 - 265 31 440 439 441 - 266 31 443 442 444 - 267 31 446 445 447 - 268 31 449 448 450 - 269 31 452 451 453 - 270 31 455 454 456 - 271 31 458 457 459 - 272 31 461 460 462 - 273 31 464 463 465 - 274 31 467 466 468 - 275 31 470 469 471 - 276 31 473 472 474 - 277 31 476 475 477 - 278 31 479 478 480 - 279 31 482 481 483 - 280 31 485 484 486 - 281 31 488 487 489 - 282 31 491 490 492 - 283 31 494 493 495 - 284 31 497 496 498 - 285 31 500 499 501 - 286 31 503 502 504 - 287 31 506 505 507 - 288 31 509 508 510 - 289 31 512 511 513 - 290 31 515 514 516 - 291 31 518 517 519 - 292 31 521 520 522 - 293 31 524 523 525 - 294 31 527 526 528 - 295 31 530 529 531 - 296 31 533 532 534 - 297 31 536 535 537 - 298 31 539 538 540 - 299 31 542 541 543 - 300 31 545 544 546 - 301 31 548 547 549 - 302 31 551 550 552 - 303 31 554 553 555 - 304 31 557 556 558 - 305 31 560 559 561 - 306 31 563 562 564 - 307 31 566 565 567 - 308 31 569 568 570 - 309 31 572 571 573 - 310 31 575 574 576 - 311 31 578 577 579 - 312 31 581 580 582 - 313 31 584 583 585 - 314 31 587 586 588 - 315 31 590 589 591 - 316 31 593 592 594 - 317 31 596 595 597 - 318 31 599 598 600 - 319 31 602 601 603 - 320 31 605 604 606 - 321 31 608 607 609 - 322 31 611 610 612 - 323 31 614 613 615 - 324 31 617 616 618 - 325 31 620 619 621 - 326 31 623 622 624 - 327 31 626 625 627 - 328 31 629 628 630 - 329 31 632 631 633 - 330 31 635 634 636 - 331 31 638 637 639 - 332 31 641 640 642 - 333 31 644 643 645 - 334 31 647 646 648 - 335 31 650 649 651 - 336 31 653 652 654 - 337 31 656 655 657 - 338 31 659 658 660 - 339 31 662 661 663 - 340 31 665 664 666 - 341 31 668 667 669 - 342 31 671 670 672 - 343 31 674 673 675 - 344 31 677 676 678 - 345 31 680 679 681 - 346 31 683 682 684 - 347 31 686 685 687 - 348 31 689 688 690 - 349 31 692 691 693 - 350 31 695 694 696 - 351 31 698 697 699 - 352 31 701 700 702 - 353 31 704 703 705 - 354 31 707 706 708 - 355 31 710 709 711 - 356 31 713 712 714 - 357 31 716 715 717 - 358 31 719 718 720 - 359 31 722 721 723 - 360 31 725 724 726 - 361 31 728 727 729 - 362 31 731 730 732 - 363 31 734 733 735 - 364 31 737 736 738 - 365 31 740 739 741 - 366 31 743 742 744 - 367 31 746 745 747 - 368 31 749 748 750 - 369 31 752 751 753 - 370 31 755 754 756 - 371 31 758 757 759 - 372 31 761 760 762 - 373 31 764 763 765 - 374 31 767 766 768 - 375 31 770 769 771 - 376 31 773 772 774 - 377 31 776 775 777 - 378 31 779 778 780 - 379 31 782 781 783 - 380 31 785 784 786 - 381 31 788 787 789 - 382 31 791 790 792 - 383 31 794 793 795 - 384 31 797 796 798 - 385 31 800 799 801 - 386 31 803 802 804 - 387 31 806 805 807 - 388 31 809 808 810 - 389 31 812 811 813 - 390 31 815 814 816 - 391 31 818 817 819 - 392 31 821 820 822 - 393 31 824 823 825 - 394 31 827 826 828 - 395 31 830 829 831 - 396 31 833 832 834 - 397 31 836 835 837 - 398 31 839 838 840 - 399 31 842 841 843 - 400 31 845 844 846 - 401 31 848 847 849 - 402 31 851 850 852 - 403 31 854 853 855 - 404 31 857 856 858 - 405 31 860 859 861 - 406 31 863 862 864 - 407 31 866 865 867 - 408 31 869 868 870 - 409 31 872 871 873 - 410 31 875 874 876 - 411 31 878 877 879 - 412 31 881 880 882 - 413 31 884 883 885 - 414 31 887 886 888 - 415 31 890 889 891 - 416 31 893 892 894 - 417 31 896 895 897 - 418 31 899 898 900 - 419 31 902 901 903 - 420 31 905 904 906 - 421 31 908 907 909 - 422 31 911 910 912 - 423 31 914 913 915 - 424 31 917 916 918 - 425 31 920 919 921 - 426 31 923 922 924 - 427 31 926 925 927 - 428 31 929 928 930 - 429 31 932 931 933 - 430 31 935 934 936 - 431 31 938 937 939 - 432 31 941 940 942 - 433 31 944 943 945 - 434 31 947 946 948 - 435 31 950 949 951 - 436 31 953 952 954 - 437 31 956 955 957 - 438 31 959 958 960 - 439 31 962 961 963 - 440 31 965 964 966 - 441 31 968 967 969 - 442 31 971 970 972 - 443 31 974 973 975 - 444 31 977 976 978 - 445 31 980 979 981 - 446 31 983 982 984 - 447 31 986 985 987 - 448 31 989 988 990 - 449 31 992 991 993 - 450 31 995 994 996 - 451 31 998 997 999 - 452 31 1001 1000 1002 - 453 31 1004 1003 1005 - 454 31 1007 1006 1008 - 455 31 1010 1009 1011 - 456 31 1013 1012 1014 - 457 31 1016 1015 1017 - 458 31 1019 1018 1020 - 459 31 1022 1021 1023 - 460 31 1025 1024 1026 - 461 31 1028 1027 1029 - 462 31 1031 1030 1032 - 463 31 1034 1033 1035 - 464 31 1037 1036 1038 - 465 31 1040 1039 1041 - 466 31 1043 1042 1044 - 467 31 1046 1045 1047 - 468 31 1049 1048 1050 - 469 31 1052 1051 1053 - 470 31 1055 1054 1056 - 471 31 1058 1057 1059 - 472 31 1061 1060 1062 - 473 31 1064 1063 1065 - 474 31 1067 1066 1068 - 475 31 1070 1069 1071 - 476 31 1073 1072 1074 - 477 31 1076 1075 1077 - 478 31 1079 1078 1080 - 479 31 1082 1081 1083 - 480 31 1085 1084 1086 - 481 31 1088 1087 1089 - 482 31 1091 1090 1092 - 483 31 1094 1093 1095 - 484 31 1097 1096 1098 - 485 31 1100 1099 1101 - 486 31 1103 1102 1104 - 487 31 1106 1105 1107 - 488 31 1109 1108 1110 - 489 31 1112 1111 1113 - 490 31 1115 1114 1116 - 491 31 1118 1117 1119 - 492 31 1121 1120 1122 - 493 31 1124 1123 1125 - 494 31 1127 1126 1128 - 495 31 1130 1129 1131 - 496 31 1133 1132 1134 - 497 31 1136 1135 1137 - 498 31 1139 1138 1140 - 499 31 1142 1141 1143 - 500 31 1145 1144 1146 - 501 31 1148 1147 1149 - 502 31 1151 1150 1152 - 503 31 1154 1153 1155 - 504 31 1157 1156 1158 - 505 31 1160 1159 1161 - 506 31 1163 1162 1164 - 507 31 1166 1165 1167 - 508 31 1169 1168 1170 - 509 31 1172 1171 1173 - 510 31 1175 1174 1176 - 511 31 1178 1177 1179 - 512 31 1181 1180 1182 - 513 31 1184 1183 1185 - 514 31 1187 1186 1188 - 515 31 1190 1189 1191 - 516 31 1193 1192 1194 - 517 31 1196 1195 1197 - 518 31 1199 1198 1200 - 519 31 1202 1201 1203 - 520 31 1205 1204 1206 - 521 31 1208 1207 1209 - 522 31 1211 1210 1212 - 523 31 1214 1213 1215 - 524 31 1217 1216 1218 - 525 31 1220 1219 1221 - 526 31 1223 1222 1224 - 527 31 1226 1225 1227 - 528 31 1229 1228 1230 - 529 31 1232 1231 1233 - 530 31 1235 1234 1236 - 531 31 1238 1237 1239 - 532 31 1241 1240 1242 - 533 31 1244 1243 1245 - 534 31 1247 1246 1248 - 535 31 1250 1249 1251 - 536 31 1253 1252 1254 - 537 31 1256 1255 1257 - 538 31 1259 1258 1260 - 539 31 1262 1261 1263 - 540 31 1265 1264 1266 - 541 31 1268 1267 1269 - 542 31 1271 1270 1272 - 543 31 1274 1273 1275 - 544 31 1277 1276 1278 - 545 31 1280 1279 1281 - 546 31 1283 1282 1284 - 547 31 1286 1285 1287 - 548 31 1289 1288 1290 - 549 31 1292 1291 1293 - 550 31 1295 1294 1296 - 551 31 1298 1297 1299 - 552 31 1301 1300 1302 - 553 31 1304 1303 1305 - 554 31 1307 1306 1308 - 555 31 1310 1309 1311 - 556 31 1313 1312 1314 - 557 31 1316 1315 1317 - 558 31 1319 1318 1320 - 559 31 1322 1321 1323 - 560 31 1325 1324 1326 - 561 31 1328 1327 1329 - 562 31 1331 1330 1332 - 563 31 1334 1333 1335 - 564 31 1337 1336 1338 - 565 31 1340 1339 1341 - 566 31 1343 1342 1344 - 567 31 1346 1345 1347 - 568 31 1349 1348 1350 - 569 31 1352 1351 1353 - 570 31 1355 1354 1356 - 571 31 1358 1357 1359 - 572 31 1361 1360 1362 - 573 31 1364 1363 1365 - 574 31 1367 1366 1368 - 575 31 1370 1369 1371 - 576 31 1373 1372 1374 - 577 31 1376 1375 1377 - 578 31 1379 1378 1380 - 579 31 1382 1381 1383 - 580 31 1385 1384 1386 - 581 31 1388 1387 1389 - 582 31 1391 1390 1392 - 583 31 1394 1393 1395 - 584 31 1397 1396 1398 - 585 31 1400 1399 1401 - 586 31 1403 1402 1404 - 587 31 1406 1405 1407 - 588 31 1409 1408 1410 - 589 31 1412 1411 1413 - 590 31 1415 1414 1416 - 591 31 1418 1417 1419 - 592 31 1421 1420 1422 - 593 31 1424 1423 1425 - 594 31 1427 1426 1428 - 595 31 1430 1429 1431 - 596 31 1433 1432 1434 - 597 31 1436 1435 1437 - 598 31 1439 1438 1440 - 599 31 1442 1441 1443 - 600 31 1445 1444 1446 - 601 31 1448 1447 1449 - 602 31 1451 1450 1452 - 603 31 1454 1453 1455 - 604 31 1457 1456 1458 - 605 31 1460 1459 1461 - 606 31 1463 1462 1464 - 607 31 1466 1465 1467 - 608 31 1469 1468 1470 - 609 31 1472 1471 1473 - 610 31 1475 1474 1476 - 611 31 1478 1477 1479 - 612 31 1481 1480 1482 - 613 31 1484 1483 1485 - 614 31 1487 1486 1488 - 615 31 1490 1489 1491 - 616 31 1493 1492 1494 - 617 31 1496 1495 1497 - 618 31 1499 1498 1500 - 619 31 1502 1501 1503 - 620 31 1505 1504 1506 - 621 31 1508 1507 1509 - 622 31 1511 1510 1512 - 623 31 1514 1513 1515 - 624 31 1517 1516 1518 - 625 31 1520 1519 1521 - 626 31 1523 1522 1524 - 627 31 1526 1525 1527 - 628 31 1529 1528 1530 - 629 31 1532 1531 1533 - 630 31 1535 1534 1536 - 631 31 1538 1537 1539 - 632 31 1541 1540 1542 - 633 31 1544 1543 1545 - 634 31 1547 1546 1548 - 635 31 1550 1549 1551 - 636 31 1553 1552 1554 - 637 31 1556 1555 1557 - 638 31 1559 1558 1560 - 639 31 1562 1561 1563 - 640 31 1565 1564 1566 - 641 31 1568 1567 1569 - 642 31 1571 1570 1572 - 643 31 1574 1573 1575 - 644 31 1577 1576 1578 - 645 31 1580 1579 1581 - 646 31 1583 1582 1584 - 647 31 1586 1585 1587 - 648 31 1589 1588 1590 - 649 31 1592 1591 1593 - 650 31 1595 1594 1596 - 651 31 1598 1597 1599 - 652 31 1601 1600 1602 - 653 31 1604 1603 1605 - 654 31 1607 1606 1608 - 655 31 1610 1609 1611 - 656 31 1613 1612 1614 - 657 31 1616 1615 1617 - 658 31 1619 1618 1620 - 659 31 1622 1621 1623 - 660 31 1625 1624 1626 - 661 31 1628 1627 1629 - 662 31 1631 1630 1632 - 663 31 1634 1633 1635 - 664 31 1637 1636 1638 - 665 31 1640 1639 1641 - 666 31 1643 1642 1644 - 667 31 1646 1645 1647 - 668 31 1649 1648 1650 - 669 31 1652 1651 1653 - 670 31 1655 1654 1656 - 671 31 1658 1657 1659 - 672 31 1661 1660 1662 - 673 31 1664 1663 1665 - 674 31 1667 1666 1668 - 675 31 1670 1669 1671 - 676 31 1673 1672 1674 - 677 31 1676 1675 1677 - 678 31 1679 1678 1680 - 679 31 1682 1681 1683 - 680 31 1685 1684 1686 - 681 31 1688 1687 1689 - 682 31 1691 1690 1692 - 683 31 1694 1693 1695 - 684 31 1697 1696 1698 - 685 31 1700 1699 1701 - 686 31 1703 1702 1704 - 687 31 1706 1705 1707 - 688 31 1709 1708 1710 - 689 31 1712 1711 1713 - 690 31 1715 1714 1716 - 691 31 1718 1717 1719 - 692 31 1721 1720 1722 - 693 31 1724 1723 1725 - 694 31 1727 1726 1728 - 695 31 1730 1729 1731 - 696 31 1733 1732 1734 - 697 31 1736 1735 1737 - 698 31 1739 1738 1740 - 699 31 1742 1741 1743 - 700 31 1745 1744 1746 - 701 31 1748 1747 1749 - 702 31 1751 1750 1752 - 703 31 1754 1753 1755 - 704 31 1757 1756 1758 - 705 31 1760 1759 1761 - 706 31 1763 1762 1764 - 707 31 1766 1765 1767 - 708 31 1769 1768 1770 - 709 31 1772 1771 1773 - 710 31 1775 1774 1776 - 711 31 1778 1777 1779 - 712 31 1781 1780 1782 - 713 31 1784 1783 1785 - 714 31 1787 1786 1788 - 715 31 1790 1789 1791 - 716 31 1793 1792 1794 - 717 31 1796 1795 1797 - 718 31 1799 1798 1800 - 719 31 1802 1801 1803 - 720 31 1805 1804 1806 - 721 31 1808 1807 1809 - 722 31 1811 1810 1812 - 723 31 1814 1813 1815 - 724 31 1817 1816 1818 - 725 31 1820 1819 1821 - 726 31 1823 1822 1824 - 727 31 1826 1825 1827 - 728 31 1829 1828 1830 - 729 31 1832 1831 1833 - 730 31 1835 1834 1836 - 731 31 1838 1837 1839 - 732 31 1841 1840 1842 - 733 31 1844 1843 1845 - 734 31 1847 1846 1848 - 735 31 1850 1849 1851 - 736 31 1853 1852 1854 - 737 31 1856 1855 1857 - 738 31 1859 1858 1860 - 739 31 1862 1861 1863 - 740 31 1865 1864 1866 - 741 31 1868 1867 1869 - 742 31 1871 1870 1872 - 743 31 1874 1873 1875 - 744 31 1877 1876 1878 - 745 31 1880 1879 1881 - 746 31 1883 1882 1884 - 747 31 1886 1885 1887 - 748 31 1889 1888 1890 - 749 31 1892 1891 1893 - 750 31 1895 1894 1896 - 751 31 1898 1897 1899 - 752 31 1901 1900 1902 - 753 31 1904 1903 1905 - 754 31 1907 1906 1908 - 755 31 1910 1909 1911 - 756 31 1913 1912 1914 - 757 31 1916 1915 1917 - 758 31 1919 1918 1920 - 759 31 1922 1921 1923 - 760 31 1925 1924 1926 - 761 31 1928 1927 1929 - 762 31 1931 1930 1932 - 763 31 1934 1933 1935 - 764 31 1937 1936 1938 - 765 31 1940 1939 1941 - 766 31 1943 1942 1944 - 767 31 1946 1945 1947 - 768 31 1949 1948 1950 - 769 31 1952 1951 1953 - 770 31 1955 1954 1956 - 771 31 1958 1957 1959 - 772 31 1961 1960 1962 - 773 31 1964 1963 1965 - 774 31 1967 1966 1968 - 775 31 1970 1969 1971 - 776 31 1973 1972 1974 - 777 31 1976 1975 1977 - 778 31 1979 1978 1980 - 779 31 1982 1981 1983 - 780 31 1985 1984 1986 - 781 31 1988 1987 1989 - 782 31 1991 1990 1992 - 783 31 1994 1993 1995 - 784 31 1997 1996 1998 - 785 31 2000 1999 2001 - 786 31 2003 2002 2004 - -Dihedrals - - 1 6 3 1 7 8 - 2 6 2 1 7 19 - 3 4 2 1 7 8 - 4 5 2 1 7 8 - 5 6 3 1 7 19 - 6 3 3 1 2 4 - 7 3 3 1 2 6 - 8 3 3 1 2 5 - 9 3 5 2 1 7 - 10 3 4 2 1 7 - 11 3 6 2 1 7 - 12 3 19 7 8 20 - 13 1 1 7 8 9 - 14 3 1 7 8 20 - 15 2 1 7 8 11 - 16 8 9 8 11 22 - 17 3 7 8 9 10 - 18 7 7 8 9 28 - 19 8 7 8 11 21 - 20 8 7 8 11 12 - 21 3 9 8 7 19 - 22 3 11 8 9 28 - 23 8 7 8 11 22 - 24 3 11 8 7 19 - 25 10 9 8 11 12 - 26 3 20 8 9 28 - 27 8 9 8 11 21 - 28 8 20 8 11 22 - 29 8 20 8 11 21 - 30 4 8 9 28 29 - 31 5 8 9 28 29 - 32 6 10 9 28 29 - 33 11 10 9 8 11 - 34 6 10 9 28 32 - 35 3 10 9 8 20 - 36 6 8 9 28 32 - 37 9 8 11 12 13 - 38 8 12 11 8 20 - 39 9 8 11 12 14 - 40 14 14 12 13 15 - 41 13 13 12 14 24 - 42 3 13 12 11 22 - 43 14 13 12 14 16 - 44 3 14 12 11 22 - 45 3 13 12 11 21 - 46 13 11 12 14 24 - 47 12 11 12 14 16 - 48 3 14 12 11 21 - 49 13 11 12 13 23 - 50 13 14 12 13 23 - 51 12 11 12 13 15 - 52 16 23 13 15 25 - 53 13 12 13 15 25 - 54 14 12 13 15 17 - 55 14 12 14 16 17 - 56 13 12 14 16 26 - 57 16 24 14 16 26 - 58 12 13 15 17 18 - 59 13 17 15 13 23 - 60 14 13 15 17 16 - 61 12 14 16 17 18 - 62 13 17 16 14 24 - 63 14 14 16 17 15 - 64 15 16 17 18 27 - 65 13 15 17 16 26 - 66 13 18 17 15 25 - 67 15 15 17 18 27 - 68 13 16 17 15 25 - 69 13 18 17 16 26 - 70 1 9 28 29 30 - 71 3 32 28 29 33 - 72 3 9 28 29 33 - 73 3 9 28 29 34 - 74 3 32 28 29 34 - 75 3 33 29 30 35 - 76 3 30 29 28 32 - 77 3 34 29 30 35 - 78 7 28 29 30 35 - 79 3 28 29 30 31 - 80 6 29 30 35 39 - 81 4 29 30 35 36 - 82 5 29 30 35 36 - 83 3 31 30 29 34 - 84 3 31 30 29 33 - 85 6 31 30 35 39 - 86 6 31 30 35 36 - 87 1 30 35 36 37 - 88 3 39 35 36 41 - 89 3 30 35 36 40 - 90 3 30 35 36 41 - 91 3 39 35 36 40 - 92 3 40 36 37 42 - 93 3 41 36 37 42 - 94 7 35 36 37 42 - 95 3 35 36 37 38 - 96 3 37 36 35 39 - 97 6 38 37 42 53 - 98 3 38 37 36 40 - 99 6 38 37 42 43 - 100 4 36 37 42 43 - 101 6 36 37 42 53 - 102 5 36 37 42 43 - 103 3 38 37 36 41 - 104 3 37 42 43 54 - 105 1 37 42 43 44 - 106 3 53 42 43 54 - 107 2 37 42 43 46 - 108 10 44 43 46 47 - 109 3 44 43 42 53 - 110 8 42 43 46 56 - 111 8 42 43 46 55 - 112 8 42 43 46 47 - 113 3 46 43 42 53 - 114 8 44 43 46 55 - 115 8 54 43 46 56 - 116 7 42 43 44 62 - 117 3 42 43 44 45 - 118 3 46 43 44 62 - 119 3 54 43 44 62 - 120 8 54 43 46 55 - 121 8 44 43 46 56 - 122 5 43 44 62 63 - 123 6 45 44 62 70 - 124 6 43 44 62 70 - 125 4 43 44 62 63 - 126 11 45 44 43 46 - 127 3 45 44 43 54 - 128 6 45 44 62 63 - 129 9 43 46 47 48 - 130 8 47 46 43 54 - 131 9 43 46 47 49 - 132 3 49 47 46 55 - 133 13 46 47 48 57 - 134 14 49 47 48 50 - 135 3 49 47 46 56 - 136 12 46 47 48 50 - 137 12 46 47 49 51 - 138 14 48 47 49 51 - 139 13 46 47 49 58 - 140 3 48 47 46 55 - 141 3 48 47 46 56 - 142 13 48 47 49 58 - 143 13 49 47 48 57 - 144 14 47 48 50 52 - 145 16 57 48 50 59 - 146 13 47 48 50 59 - 147 16 58 49 51 60 - 148 13 47 49 51 60 - 149 14 47 49 51 52 - 150 13 48 50 52 61 - 151 14 48 50 52 51 - 152 16 59 50 52 61 - 153 13 52 50 48 57 - 154 14 49 51 52 50 - 155 13 49 51 52 61 - 156 13 52 51 49 58 - 157 16 60 51 52 61 - 158 13 51 52 50 59 - 159 13 50 52 51 60 - 160 3 70 62 63 71 - 161 2 44 62 63 66 - 162 1 44 62 63 64 - 163 3 44 62 63 71 - 164 8 62 63 66 72 - 165 8 62 63 66 67 - 166 3 71 63 64 79 - 167 3 62 63 64 65 - 168 3 64 63 62 70 - 169 8 62 63 66 73 - 170 7 62 63 64 79 - 171 8 64 63 66 67 - 172 3 66 63 64 79 - 173 8 64 63 66 72 - 174 3 66 63 62 70 - 175 8 71 63 66 73 - 176 8 64 63 66 73 - 177 8 71 63 66 72 - 178 6 63 64 79 81 - 179 6 65 64 79 80 - 180 3 65 64 63 71 - 181 4 63 64 79 80 - 182 6 65 64 79 81 - 183 5 63 64 79 80 - 184 11 65 64 63 66 - 185 8 67 66 63 71 - 186 17 63 66 67 74 - 187 17 72 66 67 75 - 188 17 63 66 67 75 - 189 17 63 66 67 68 - 190 17 73 66 67 74 - 191 17 73 66 67 75 - 192 17 72 66 67 74 - 193 19 66 67 68 69 - 194 21 68 67 66 72 - 195 18 66 67 68 69 - 196 21 68 67 66 73 - 197 20 69 68 67 74 - 198 20 69 68 67 75 - 199 20 67 68 69 77 - 200 20 67 68 69 76 - 201 20 67 68 69 78 - 202 3 81 79 80 83 - 203 3 81 79 80 84 - 204 3 64 79 80 84 - 205 3 81 79 80 82 - 206 3 64 79 80 83 - 207 3 64 79 80 82 - -Impropers - - 1 2 7 1 8 19 - 2 1 1 2 7 3 - 3 1 9 8 28 10 - 4 2 28 9 29 32 - 5 1 30 29 35 31 - 6 2 35 30 36 39 - 7 1 37 36 42 38 - 8 2 42 37 43 53 - 9 1 44 43 62 45 - 10 2 62 44 63 70 - 11 1 64 63 79 65 - 12 2 79 64 80 81 diff --git a/tools/replica/example/in.peptide b/tools/replica/example/in.peptide index 5d321e34c3..ada6941af1 100644 --- a/tools/replica/example/in.peptide +++ b/tools/replica/example/in.peptide @@ -14,7 +14,7 @@ dihedral_style charmm improper_style harmonic kspace_style pppm 0.0001 -read_data data.peptide +read_data ../../../examples/peptide/data.peptide neighbor 2.0 bin neigh_modify delay 5 diff --git a/tools/replica/example/run.sh b/tools/replica/example/run.sh index 419dc6625f..f190bf5dfa 100755 --- a/tools/replica/example/run.sh +++ b/tools/replica/example/run.sh @@ -1,10 +1,13 @@ #!/bin/bash ## run REMD using LAMMPS -#mpirun -np 16 ~/mysoftware/lammps/src/lmp_mpi -partition 16x1 -in in.peptide -log log.peptide +mpirun -np 16 ~/mysoftware/lammps/src/lmp_mpi -partition 16x1 -in in.peptide -log log.peptide ## collect all energies from different replica logs -#python parse_ene.py temps.txt log.peptide +echo ; echo +echo "Parsing energies from replica logs" +python parse_ene.py temps.txt log.peptide ## run the reordering tool to get reordered trajectories @ 200 K, 276 K, 400 K +echo ; echo mpirun -np 16 python ../reorder_remd_traj.py peptide -logfn log.peptide -tfn temps.txt -ns 10 -nw 20 -np 1000 -ot 200 276 400 -logw -e ene.peptide -od ./output diff --git a/tools/replica/example/runlog.05Sep19 b/tools/replica/example/runlog.05Sep19 new file mode 100644 index 0000000000..b4eeafdc9e --- /dev/null +++ b/tools/replica/example/runlog.05Sep19 @@ -0,0 +1,249 @@ +LAMMPS (7 Aug 2019) +Running on 16 partitions of processors +Setting up tempering ... +Step T0 T1 T2 T3 T4 T5 T6 T7 T8 T9 T10 T11 T12 T13 T14 T15 +0 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 +10 1 0 3 2 5 4 7 6 9 8 11 10 13 12 15 14 +20 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 +30 0 2 1 4 3 6 5 8 7 10 9 12 11 14 13 15 +40 1 3 0 5 2 7 4 9 6 11 8 13 10 15 12 14 +50 2 4 0 6 1 8 3 10 5 12 7 14 9 15 11 13 +60 3 5 1 7 0 9 2 11 4 13 6 15 8 14 10 12 +70 4 6 2 8 0 10 1 12 3 14 5 15 7 13 9 11 +80 3 5 1 7 0 9 2 11 4 13 6 15 8 14 10 12 +90 2 4 0 6 1 8 3 10 5 12 7 14 9 15 11 13 +100 1 3 0 5 2 7 4 9 6 11 8 13 10 15 12 14 +110 0 2 1 4 3 6 5 8 7 10 9 12 11 14 13 15 +120 1 3 0 5 2 7 4 9 6 11 8 13 10 15 12 14 +130 2 4 0 6 1 8 3 10 5 12 7 14 9 15 11 13 +140 1 3 0 5 2 7 4 9 6 11 8 13 10 15 12 14 +150 2 4 0 6 1 8 3 10 5 12 7 14 9 15 11 13 +160 1 3 0 5 2 7 4 9 6 11 8 13 10 15 12 14 +170 2 4 0 6 1 8 3 10 5 12 7 14 9 15 11 13 +180 1 3 0 5 2 7 4 9 6 11 8 13 10 15 12 14 +190 0 2 1 4 3 6 5 8 7 10 9 12 11 14 13 15 +200 1 3 0 5 2 7 4 9 6 11 8 13 10 15 12 14 +210 0 2 1 4 3 6 5 8 7 10 9 12 11 14 13 15 +220 1 3 0 5 2 7 4 9 6 11 8 13 10 15 12 14 +230 2 4 0 6 1 8 3 10 5 12 7 14 9 15 11 13 +240 3 5 1 7 0 9 2 11 4 13 6 15 8 14 10 12 +250 2 4 0 6 1 8 3 10 5 12 7 14 9 15 11 13 +260 3 5 1 7 0 9 2 11 4 13 6 15 8 14 10 12 +270 4 6 2 8 0 10 1 12 3 14 5 15 7 13 9 11 +280 3 5 1 7 0 9 2 11 4 13 6 15 8 14 10 12 +290 2 4 0 6 1 8 3 10 5 12 7 14 9 15 11 13 +300 3 5 1 7 0 9 2 11 4 13 6 15 8 14 10 12 +310 2 4 0 6 1 8 3 10 5 12 7 14 9 15 11 13 +320 3 5 1 7 0 9 2 11 4 13 6 15 8 14 10 12 +330 4 6 2 8 0 10 1 12 3 14 5 15 7 13 9 11 +340 3 5 1 7 0 9 2 11 4 13 6 15 8 14 10 12 +350 4 6 2 8 0 10 1 12 3 14 5 15 7 13 9 11 +360 3 5 1 7 0 9 2 11 4 13 6 15 8 14 10 12 +370 4 6 2 8 0 10 1 12 3 14 5 15 7 13 9 11 +380 3 5 1 7 0 9 2 11 4 13 6 15 8 14 10 12 +390 4 6 2 8 0 10 1 12 3 14 5 15 7 13 9 11 +400 5 7 3 9 1 11 0 13 2 15 4 14 6 12 8 10 +410 4 6 2 8 0 10 1 12 3 14 5 15 7 13 9 11 +420 3 5 1 7 0 9 2 11 4 13 6 15 8 14 10 12 +430 2 4 0 6 1 8 3 10 5 12 7 14 9 15 11 13 +440 3 5 1 7 0 9 2 11 4 13 6 15 8 14 10 12 +450 2 4 0 6 1 8 3 10 5 12 7 14 9 15 11 13 +460 1 3 0 5 2 7 4 9 6 11 8 13 10 15 12 14 +470 2 4 0 6 1 8 3 10 5 12 7 14 9 15 11 13 +480 3 5 1 7 0 9 2 11 4 13 6 15 8 14 10 12 +490 2 4 0 6 1 8 3 10 5 12 7 14 9 15 11 13 +500 1 3 0 5 2 7 4 9 6 11 8 13 10 15 12 14 +510 2 4 0 6 1 8 3 10 5 12 7 14 9 15 11 13 +520 1 3 0 5 2 7 4 9 6 11 8 13 10 15 12 14 +530 2 4 0 6 1 8 3 10 5 12 7 14 9 15 11 13 +540 1 3 0 5 2 7 4 9 6 11 8 13 10 15 12 14 +550 0 2 1 4 3 6 5 8 7 10 9 12 11 14 13 15 +560 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 +570 0 2 1 4 3 6 5 8 7 10 9 12 11 14 13 15 +580 1 3 0 5 2 7 4 9 6 11 8 13 10 15 12 14 +590 2 4 0 6 1 8 3 10 5 12 7 14 9 15 11 13 +600 1 3 0 5 2 7 4 9 6 11 8 13 10 15 12 14 +610 0 2 1 4 3 6 5 8 7 10 9 12 11 14 13 15 +620 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 +630 1 0 3 2 5 4 7 6 9 8 11 10 13 12 15 14 +640 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 +650 0 2 1 4 3 6 5 8 7 10 9 12 11 14 13 15 +660 1 3 0 5 2 7 4 9 6 11 8 13 10 15 12 14 +670 2 4 0 6 1 8 3 10 5 12 7 14 9 15 11 13 +680 3 5 1 7 0 9 2 11 4 13 6 15 8 14 10 12 +690 2 4 0 6 1 8 3 10 5 12 7 14 9 15 11 13 +700 1 3 0 5 2 7 4 9 6 11 8 13 10 15 12 14 +710 0 2 1 4 3 6 5 8 7 10 9 12 11 14 13 15 +720 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 +730 0 2 1 4 3 6 5 8 7 10 9 12 11 14 13 15 +740 1 3 0 5 2 7 4 9 6 11 8 13 10 15 12 14 +750 2 4 0 6 1 8 3 10 5 12 7 14 9 15 11 13 +760 1 3 0 5 2 7 4 9 6 11 8 13 10 15 12 14 +770 2 4 0 6 1 8 3 10 5 12 7 14 9 15 11 13 +780 1 3 0 5 2 7 4 9 6 11 8 13 10 15 12 14 +790 2 4 0 6 1 8 3 10 5 12 7 14 9 15 11 13 +800 1 3 0 5 2 7 4 9 6 11 8 13 10 15 12 14 +810 2 4 0 6 1 8 3 10 5 12 7 14 9 15 11 13 +820 3 5 1 7 0 9 2 11 4 13 6 15 8 14 10 12 +830 2 4 0 6 1 8 3 10 5 12 7 14 9 15 11 13 +840 3 5 1 7 0 9 2 11 4 13 6 15 8 14 10 12 +850 2 4 0 6 1 8 3 10 5 12 7 14 9 15 11 13 +860 1 3 0 5 2 7 4 9 6 11 8 13 10 15 12 14 +870 0 2 1 4 3 6 5 8 7 10 9 12 11 14 13 15 +880 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 +890 0 2 1 4 3 6 5 8 7 10 9 12 11 14 13 15 +900 1 3 0 5 2 7 4 9 6 11 8 13 10 15 12 14 +910 0 2 1 4 3 6 5 8 7 10 9 12 11 14 13 15 +920 1 3 0 5 2 7 4 9 6 11 8 13 10 15 12 14 +930 0 2 1 4 3 6 5 8 7 10 9 12 11 14 13 15 +940 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 +950 1 0 3 2 5 4 7 6 9 8 11 10 13 12 15 14 +960 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 +970 1 0 3 2 5 4 7 6 9 8 11 10 13 12 15 14 +980 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 +990 1 0 3 2 5 4 7 6 9 8 11 10 13 12 15 14 +1000 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 +1010 1 0 3 2 5 4 7 6 9 8 11 10 13 12 15 14 +1020 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 +1030 0 2 1 4 3 6 5 8 7 10 9 12 11 14 13 15 +1040 1 3 0 5 2 7 4 9 6 11 8 13 10 15 12 14 +1050 0 2 1 4 3 6 5 8 7 10 9 12 11 14 13 15 +1060 1 3 0 5 2 7 4 9 6 11 8 13 10 15 12 14 +1070 2 4 0 6 1 8 3 10 5 12 7 14 9 15 11 13 +1080 3 5 1 7 0 9 2 11 4 13 6 15 8 14 10 12 +1090 2 4 0 6 1 8 3 10 5 12 7 14 9 15 11 13 +1100 1 3 0 5 2 7 4 9 6 11 8 13 10 15 12 14 +1110 0 2 1 4 3 6 5 8 7 10 9 12 11 14 13 15 +1120 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 +1130 1 0 3 2 5 4 7 6 9 8 11 10 13 12 15 14 +1140 2 0 4 1 6 3 8 5 10 7 12 9 14 11 15 13 +1150 1 0 3 2 5 4 7 6 9 8 11 10 13 12 15 14 +1160 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 +1170 0 2 1 4 3 6 5 8 7 10 9 12 11 14 13 15 +1180 1 3 0 5 2 7 4 9 6 11 8 13 10 15 12 14 +1190 0 2 1 4 3 6 5 8 7 10 9 12 11 14 13 15 +1200 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 +1210 1 0 3 2 5 4 7 6 9 8 11 10 13 12 15 14 +1220 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 +1230 0 2 1 4 3 6 5 8 7 10 9 12 11 14 13 15 +1240 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 +1250 1 0 3 2 5 4 7 6 9 8 11 10 13 12 15 14 +1260 2 0 4 1 6 3 8 5 10 7 12 9 14 11 15 13 +1270 3 1 5 0 7 2 9 4 11 6 13 8 15 10 14 12 +1280 4 2 6 0 8 1 10 3 12 5 14 7 15 9 13 11 +1290 3 1 5 0 7 2 9 4 11 6 13 8 15 10 14 12 +1300 4 2 6 0 8 1 10 3 12 5 14 7 15 9 13 11 +1310 5 3 7 1 9 0 11 2 13 4 15 6 14 8 12 10 +1320 4 2 6 0 8 1 10 3 12 5 14 7 15 9 13 11 +1330 5 3 7 1 9 0 11 2 13 4 15 6 14 8 12 10 +1340 4 2 6 0 8 1 10 3 12 5 14 7 15 9 13 11 +1350 5 3 7 1 9 0 11 2 13 4 15 6 14 8 12 10 +1360 6 4 8 2 10 0 12 1 14 3 15 5 13 7 11 9 +1370 5 3 7 1 9 0 11 2 13 4 15 6 14 8 12 10 +1380 6 4 8 2 10 0 12 1 14 3 15 5 13 7 11 9 +1390 5 3 7 1 9 0 11 2 13 4 15 6 14 8 12 10 +1400 6 4 8 2 10 0 12 1 14 3 15 5 13 7 11 9 +1410 7 5 9 3 11 1 13 0 15 2 14 4 12 6 10 8 +1420 6 4 8 2 10 0 12 1 14 3 15 5 13 7 11 9 +1430 7 5 9 3 11 1 13 0 15 2 14 4 12 6 10 8 +1440 8 6 10 4 12 2 14 0 15 1 13 3 11 5 9 7 +1450 7 5 9 3 11 1 13 0 15 2 14 4 12 6 10 8 +1460 8 6 10 4 12 2 14 0 15 1 13 3 11 5 9 7 +1470 7 5 9 3 11 1 13 0 15 2 14 4 12 6 10 8 +1480 6 4 8 2 10 0 12 1 14 3 15 5 13 7 11 9 +1490 5 3 7 1 9 0 11 2 13 4 15 6 14 8 12 10 +1500 4 2 6 0 8 1 10 3 12 5 14 7 15 9 13 11 +1510 5 3 7 1 9 0 11 2 13 4 15 6 14 8 12 10 +1520 4 2 6 0 8 1 10 3 12 5 14 7 15 9 13 11 +1530 3 1 5 0 7 2 9 4 11 6 13 8 15 10 14 12 +1540 2 0 4 1 6 3 8 5 10 7 12 9 14 11 15 13 +1550 3 1 5 0 7 2 9 4 11 6 13 8 15 10 14 12 +1560 4 2 6 0 8 1 10 3 12 5 14 7 15 9 13 11 +1570 5 3 7 1 9 0 11 2 13 4 15 6 14 8 12 10 +1580 4 2 6 0 8 1 10 3 12 5 14 7 15 9 13 11 +1590 5 3 7 1 9 0 11 2 13 4 15 6 14 8 12 10 +1600 4 2 6 0 8 1 10 3 12 5 14 7 15 9 13 11 +1610 5 3 7 1 9 0 11 2 13 4 15 6 14 8 12 10 +1620 6 4 8 2 10 0 12 1 14 3 15 5 13 7 11 9 +1630 5 3 7 1 9 0 11 2 13 4 15 6 14 8 12 10 +1640 6 4 8 2 10 0 12 1 14 3 15 5 13 7 11 9 +1650 7 5 9 3 11 1 13 0 15 2 14 4 12 6 10 8 +1660 8 6 10 4 12 2 14 0 15 1 13 3 11 5 9 7 +1670 7 5 9 3 11 1 13 0 15 2 14 4 12 6 10 8 +1680 6 4 8 2 10 0 12 1 14 3 15 5 13 7 11 9 +1690 5 3 7 1 9 0 11 2 13 4 15 6 14 8 12 10 +1700 4 2 6 0 8 1 10 3 12 5 14 7 15 9 13 11 +1710 3 1 5 0 7 2 9 4 11 6 13 8 15 10 14 12 +1720 2 0 4 1 6 3 8 5 10 7 12 9 14 11 15 13 +1730 1 0 3 2 5 4 7 6 9 8 11 10 13 12 15 14 +1740 2 0 4 1 6 3 8 5 10 7 12 9 14 11 15 13 +1750 3 1 5 0 7 2 9 4 11 6 13 8 15 10 14 12 +1760 2 0 4 1 6 3 8 5 10 7 12 9 14 11 15 13 +1770 1 0 3 2 5 4 7 6 9 8 11 10 13 12 15 14 +1780 2 0 4 1 6 3 8 5 10 7 12 9 14 11 15 13 +1790 1 0 3 2 5 4 7 6 9 8 11 10 13 12 15 14 +1800 2 0 4 1 6 3 8 5 10 7 12 9 14 11 15 13 +1810 1 0 3 2 5 4 7 6 9 8 11 10 13 12 15 14 +1820 2 0 4 1 6 3 8 5 10 7 12 9 14 11 15 13 +1830 3 1 5 0 7 2 9 4 11 6 13 8 15 10 14 12 +1840 2 0 4 1 6 3 8 5 10 7 12 9 14 11 15 13 +1850 1 0 3 2 5 4 7 6 9 8 11 10 13 12 15 14 +1860 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 +1870 1 0 3 2 5 4 7 6 9 8 11 10 13 12 15 14 +1880 2 0 4 1 6 3 8 5 10 7 12 9 14 11 15 13 +1890 3 1 5 0 7 2 9 4 11 6 13 8 15 10 14 12 +1900 4 2 6 0 8 1 10 3 12 5 14 7 15 9 13 11 +1910 3 1 5 0 7 2 9 4 11 6 13 8 15 10 14 12 +1920 2 0 4 1 6 3 8 5 10 7 12 9 14 11 15 13 +1930 1 0 3 2 5 4 7 6 9 8 11 10 13 12 15 14 +1940 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 +1950 0 2 1 4 3 6 5 8 7 10 9 12 11 14 13 15 +1960 1 3 0 5 2 7 4 9 6 11 8 13 10 15 12 14 +1970 2 4 0 6 1 8 3 10 5 12 7 14 9 15 11 13 +1980 3 5 1 7 0 9 2 11 4 13 6 15 8 14 10 12 +1990 2 4 0 6 1 8 3 10 5 12 7 14 9 15 11 13 +2000 1 3 0 5 2 7 4 9 6 11 8 13 10 15 12 14 + + +Parsing energies from replica logs + + +Getting frames from all replicas at temperature: +200.00 K +209.00 K +219.00 K +230.00 K +241.00 K +252.00 K +264.00 K +276.00 K +289.00 K +303.00 K +317.00 K +332.00 K +348.00 K +365.00 K +382.00 K +400.00 K + +Releasing 13 excess procs +Writing buffer to file + +Running pymbar... +K (total states) = 16, total samples = 800 +N_k = +[50 50 50 50 50 50 50 50 50 50 50 50 50 50 50 50] +There are 16 states with samples. +Initializing free energies to zero. +Initial dimensionless free energies with method zeros +f_k = +[0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.] +Final dimensionless free energies +f_k = +[ 0. 889.75988663 1792.61111609 2695.06980154 + 3515.14636632 4263.62894529 5009.01862104 5689.59180324 + 6363.10021193 7023.7847743 7626.11234062 8215.09228661 + 8787.37318432 9340.44739436 9844.29510404 10331.10090589] +MBAR initialization complete. + +Extracting log-weights... diff --git a/tools/replica/reorder_remd_traj.py b/tools/replica/reorder_remd_traj.py index 6d40b69ec4..c8c467ffe0 100644 --- a/tools/replica/reorder_remd_traj.py +++ b/tools/replica/reorder_remd_traj.py @@ -43,7 +43,7 @@ from scipy.special import logsumexp from mpi4py import MPI from tqdm import tqdm, trange -import gzip +import gzip, bz2 try: # python-2 from StringIO import StringIO as IOBuffer From 49b5825e8da3fc7caea9fe9cc28a655664e101dc Mon Sep 17 00:00:00 2001 From: jrgissing Date: Thu, 5 Sep 2019 23:50:57 -0600 Subject: [PATCH 097/192] bond/react docs tweak: address a common mistake no atom of a small molecule should be specified as an edge atom --- doc/src/fix_bond_react.txt | 29 ++++++++++++++++------------- 1 file changed, 16 insertions(+), 13 deletions(-) diff --git a/doc/src/fix_bond_react.txt b/doc/src/fix_bond_react.txt index 5aff35787d..3fe3d8547e 100644 --- a/doc/src/fix_bond_react.txt +++ b/doc/src/fix_bond_react.txt @@ -186,19 +186,22 @@ reacting atoms. Some atoms in the pre-reacted template that are not reacting may have missing topology with respect to the simulation. For example, the -pre-reacted template may contain an atom that would connect to the -rest of a long polymer chain. These are referred to as edge atoms, and -are also specified in the map file. When the pre-reaction template -contains edge atoms, not all atoms, bonds, charges, etc. specified in -the reaction templates will be updated. Specifically, topology that -involves only atoms that are 'too near' to template edges will not be -updated. The definition of 'too near the edge' depends on which -interactions are defined in the simulation. If the simulation has -defined dihedrals, atoms within two bonds of edge atoms are considered -'too near the edge.' If the simulation defines angles, but not -dihedrals, atoms within one bond of edge atoms are considered 'too -near the edge.' If just bonds are defined, only edge atoms are -considered 'too near the edge.' +pre-reacted template may contain an atom that, in the simulation, is +currently connected to the rest of a long polymer chain. These are +referred to as edge atoms, and are also specified in the map file. +When the pre-reaction template contains edge atoms, not all atoms, +bonds, charges, etc. specified in the reaction templates will be +updated. Specifically, topology that involves only atoms that are 'too +near' to template edges will not be updated. The definition of 'too +near the edge' depends on which interactions are defined in the +simulation. If the simulation has defined dihedrals, atoms within two +bonds of edge atoms are considered 'too near the edge.' If the +simulation defines angles, but not dihedrals, atoms within one bond of +edge atoms are considered 'too near the edge.' If just bonds are +defined, only edge atoms are considered 'too near the edge.' + +NOTE: Small molecules, i.e. ones that have all their atoms contained +within the reaction templates, never have edge atoms. Note that some care must be taken when a building a molecule template for a given simulation. All atom types in the pre-reacted template From 0235b1a286209bd11fc9087357cfd88fc6269223 Mon Sep 17 00:00:00 2001 From: jrgissing Date: Fri, 6 Sep 2019 00:18:24 -0600 Subject: [PATCH 098/192] bond/react: move MAXLINE to header --- src/USER-MISC/fix_bond_react.cpp | 1 - src/USER-MISC/fix_bond_react.h | 4 +++- 2 files changed, 3 insertions(+), 2 deletions(-) diff --git a/src/USER-MISC/fix_bond_react.cpp b/src/USER-MISC/fix_bond_react.cpp index 07f009360a..6b61a7b84d 100644 --- a/src/USER-MISC/fix_bond_react.cpp +++ b/src/USER-MISC/fix_bond_react.cpp @@ -56,7 +56,6 @@ static const char cite_fix_bond_react[] = #define BIG 1.0e20 #define DELTA 16 -#define MAXLINE 256 #define MAXGUESS 20 // max # of guesses allowed by superimpose algorithm #define MAXCONARGS 5 // max # of arguments for any type of constraint diff --git a/src/USER-MISC/fix_bond_react.h b/src/USER-MISC/fix_bond_react.h index 2be20cf8ec..169409c3aa 100644 --- a/src/USER-MISC/fix_bond_react.h +++ b/src/USER-MISC/fix_bond_react.h @@ -26,6 +26,8 @@ FixStyle(bond/react,FixBondReact) #include "fix.h" +#define MAXLINE 256 + namespace LAMMPS_NS { class FixBondReact : public Fix { @@ -175,7 +177,7 @@ class FixBondReact : public Fix { struct Set { int nreacts; - char rxn_name[256]; + char rxn_name[MAXLINE]; int reaction_count_total; }; Set *set; From 82423ff4e09c50ec49ad81d21d5bc2efb27ee141 Mon Sep 17 00:00:00 2001 From: Axel Kohlmeyer Date: Fri, 6 Sep 2019 13:25:31 -0400 Subject: [PATCH 099/192] re-add link to data.peptide file, which got deleted somehow --- tools/replica/example/data.peptide | 1 + 1 file changed, 1 insertion(+) create mode 120000 tools/replica/example/data.peptide diff --git a/tools/replica/example/data.peptide b/tools/replica/example/data.peptide new file mode 120000 index 0000000000..f523fc92c1 --- /dev/null +++ b/tools/replica/example/data.peptide @@ -0,0 +1 @@ +../../../examples/peptide/data.peptide \ No newline at end of file From ce02cb58a58787f91f3d2a5304b77c88c33ea5fa Mon Sep 17 00:00:00 2001 From: Axel Kohlmeyer Date: Fri, 6 Sep 2019 13:37:49 -0400 Subject: [PATCH 100/192] replace explicit potential files with links to the potentials folder --- bench/POTENTIALS/CH.airebo | 37593 +------------------------- bench/POTENTIALS/CdTe.bop.table | 4834 +--- bench/POTENTIALS/Cu_u3.eam | 306 +- bench/POTENTIALS/Ni.adp | 43008 +----------------------------- 4 files changed, 4 insertions(+), 85737 deletions(-) mode change 100644 => 120000 bench/POTENTIALS/CH.airebo mode change 100644 => 120000 bench/POTENTIALS/CdTe.bop.table mode change 100644 => 120000 bench/POTENTIALS/Cu_u3.eam mode change 100644 => 120000 bench/POTENTIALS/Ni.adp diff --git a/bench/POTENTIALS/CH.airebo b/bench/POTENTIALS/CH.airebo deleted file mode 100644 index 3be02a9d8c..0000000000 --- a/bench/POTENTIALS/CH.airebo +++ /dev/null @@ -1,37592 +0,0 @@ -# AI-REBO Brenner/Stuart potential -# need to cite the appropriate papers here - -1.7 rcmin_CC -1.3 rcmin_CH -1.1 rcmin_HH -2.0 rcmax_CC -1.8 rcmax_CH -1.7 rcmax_HH -2.0 rcmaxp_CC -1.6 rcmaxp_CH -1.7 rcmaxp_HH -0.1 smin -2.0 Nmin -3.0 Nmax -3.2 NCmin -3.7 NCmax -0.31346 Q_CC -0.340776 Q_CH -0.370471 Q_HH -4.7465391 alpha_CC -4.1025498 alpha_CH -3.5362986 alpha_HH -10953.544 A_CC -149.94099 A_CH -32.817356 A_HH -12388.792 BIJc_CC1 -17.567065 BIJc_CC2 -30.714932 BIJc_CC3 -32.355187 BIJc_CH1 -0.0 BIJc_CH2 -0.0 BIJc_CH3 -29.632593 BIJc_HH1 -0.0 BIJc_HH2 -0.0 BIJc_HH3 -4.7204523 Beta_CC1 -1.4332132 Beta_CC2 -1.3826913 Beta_CC3 -1.4344581 Beta_CH1 -0.0 Beta_CH2 -0.0 Beta_CH3 -1.7158922 Beta_HH1 -0.0 Beta_HH2 -0.0 Beta_HH3 -0.0 rho_CC -1.09 rho_CH -0.7415887 rho_HH -3.4 rcLJmin_CC -3.025 rcLJmin_CH -2.65 rcLJmin_HH -3.816370964 rcLJmax_CC -3.395447696 rcLJmax_CH -2.974524428 rcLJmax_HH -0.77 bLJmin_CC -0.75 bLJmin_CH -0.32 bLJmin_HH -0.81 bLJmax_CC -0.9 bLJmax_CH -0.42 bLJmax_HH -0.00284 epsilon_CC -0.0020639767 epsilon_CH -0.0015 epsilon_HH -3.4 sigma_CC -3.025 sigma_CH -2.65 sigma_HH -0.3079 epsilonT_CCCC -0.1787 epsilonT_CCCH -0.125 epsilonT_HCCH - -# gC1 and gC2 - -5 --1.0 --0.6666666667 --0.5 --0.3333333333 -1.0 - - 0.2816950000 - 1.0627430000 - 2.1363075000 - 2.5334145000 - 1.5544035000 - 0.3862485000 - 0.2827390000 - 1.0718770000 - 2.1681365000 - 2.5885710000 - 1.6019100000 - 0.4025160000 - 0.6900250000 - 5.4601600000 - 23.0108000000 - 54.9086400000 - 68.6124000000 - 34.7051520000 - 0.2718560918 - 0.4892740137 - -0.4328177539 - -0.5616817383 - 1.2708702246 - -0.0375008379 - - 0.2816950000 - 1.0627430000 - 2.1363075000 - 2.5334145000 - 1.5544035000 - 0.3862485000 - 0.2827390000 - 1.0718770000 - 2.1681365000 - 2.5885710000 - 1.6019100000 - 0.4025160000 - 0.6900250000 - 5.4601600000 - 23.0108000000 - 54.9086400000 - 68.6124000000 - 34.7051520000 - 0.3754514434 - 1.4072691309 - 2.2551320117 - 2.0288747461 - 1.4269207324 - 0.5063519355 - -# gH - -4 --1.0 --0.8333333333 --0.5 -1.0 - - 270.4568000026 - 1549.6358000143 - 3781.7719000316 - 4582.1544000348 - 2721.4308000191 - 630.6336000042 - 16.9534406250 - -21.0823875000 - -102.4683000000 - -210.6432299999 - -229.8471299999 - -94.9946400000 - 19.0650249321 - 2.0177562840 - -2.5664219198 - 3.2913322346 - -2.6535615062 - 0.8376699753 - -# pCC - -4 -0.0 -4.0 -0.0 -4.0 - - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.0986400000 - 0.0657600000 - 0.0000000000 - 0.0000000000 - 0.0657600000 - -0.0438400000 - -0.0025000000 - 0.0060000000 - -0.0045000000 - 0.0010000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.2339100000 - -0.6402960000 - 0.4802220000 - -0.1067160000 - -0.1559400000 - 0.4268640000 - -0.3201480000 - 0.0711440000 - 0.4650000000 - -0.5985000000 - 0.2493750000 - -0.0332500000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -1.9074060000 - 2.4787080000 - -1.0327950000 - 0.1377060000 - 1.2716040000 - -1.6524720000 - 0.6885300000 - -0.0918040000 - -1.2900000000 - 1.1610000000 - -0.3386250000 - 0.0322500000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 3.8700000000 - -3.4830000000 - 1.0158750000 - -0.0967500000 - -2.5800000000 - 2.3220000000 - -0.6772500000 - 0.0645000000 - -0.1380150000 - 0.0000000000 - 0.5932650000 - -0.3955100000 - 0.3312360000 - 0.0000000000 - -1.5027480000 - 1.0018320000 - -0.2484270000 - 0.0000000000 - 1.1270610000 - -0.7513740000 - 0.0552060000 - 0.0000000000 - -0.2504580000 - 0.1669720000 - -0.3654800000 - 1.0205280000 - -0.7653960000 - 0.1700880000 - 1.0582800000 - -2.9471040000 - 2.2103280000 - -0.4911840000 - -0.7937100000 - 2.2103280000 - -1.6577460000 - 0.3683880000 - 0.1763800000 - -0.4911840000 - 0.3683880000 - -0.0818640000 - 0.6832080000 - -0.9109440000 - 0.3795600000 - -0.0506080000 - -2.0496240000 - 2.7328320000 - -1.1386800000 - 0.1518240000 - 1.5372180000 - -2.0496240000 - 0.8540100000 - -0.1138680000 - -0.3416040000 - 0.4554720000 - -0.1897800000 - 0.0253040000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.7452810000 - 0.0000000000 - -2.4934230000 - 1.6622820000 - -0.9937080000 - 0.0000000000 - 3.3245640000 - -2.2163760000 - 0.4140450000 - 0.0000000000 - -1.3852350000 - 0.9234900000 - -0.0552060000 - 0.0000000000 - 0.1846980000 - -0.1231320000 - 0.3434400000 - -1.0303200000 - 0.7727400000 - -0.1717200000 - -0.4579200000 - 1.3737600000 - -1.0303200000 - 0.2289600000 - 0.1908000000 - -0.5724000000 - 0.4293000000 - -0.0954000000 - -0.0254400000 - 0.0763200000 - -0.0572400000 - 0.0127200000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -# PCH - -4 -0.0 -4.0 -0.0 -4.0 - - 0.0000000000 - 0.0000000000 - 0.6280110000 - -0.4186740000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0300000000 - 0.0000000000 - -3.1001400000 - 2.0667600000 - -0.0200000000 - 0.0000000000 - 2.0667600000 - -1.3778400000 - -1.1595980000 - 3.2854440000 - -2.4640830000 - 0.5475740000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.4966950000 - -3.6001800000 - 2.7001350000 - -0.6000300000 - -0.3311300000 - 2.4001200000 - -1.8000900000 - 0.4000200000 - -6.7698340000 - 8.6212080000 - -3.5921700000 - 0.4789560000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 44.5208070000 - -58.1453640000 - 24.2272350000 - -3.2302980000 - -29.6805380000 - 38.7635760000 - -16.1514900000 - 2.1535320000 - 24.3142400000 - -21.8828160000 - 6.3824880000 - -0.6078560000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -72.9427200000 - 65.6484480000 - -19.1474640000 - 1.8235680000 - 48.6284800000 - -43.7656320000 - 12.7649760000 - -1.2157120000 - -0.6502100000 - 0.0000000000 - -1.0558290000 - 0.7038860000 - 1.5845040000 - 0.0000000000 - 1.5611040000 - -1.0407360000 - -1.1883780000 - 0.0000000000 - -1.1708280000 - 0.7805520000 - 0.2640840000 - 0.0000000000 - 0.2601840000 - -0.1734560000 - 9.9867120000 - -26.3732760000 - 19.7799570000 - -4.3955460000 - -26.3537880000 - 68.3007840000 - -51.2255880000 - 11.3834640000 - 19.7653410000 - -51.2255880000 - 38.4191910000 - -8.5375980000 - -4.3922980000 - 11.3834640000 - -8.5375980000 - 1.8972440000 - -32.2817400000 - 43.0423200000 - -17.9343000000 - 2.3912400000 - 96.8452200000 - -129.1269600000 - 53.8029000000 - -7.1737200000 - -72.6339150000 - 96.8452200000 - -40.3521750000 - 5.3802900000 - 16.1408700000 - -21.5211600000 - 8.9671500000 - -1.1956200000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -5.3172460000 - 0.0000000000 - 40.2945870000 - -26.8630580000 - 6.6795480000 - 0.0000000000 - -52.4957760000 - 34.9971840000 - -2.7831450000 - 0.0000000000 - 21.8732400000 - -14.5821600000 - 0.3710860000 - 0.0000000000 - -2.9164320000 - 1.9442880000 - -32.4571320000 - 97.3713960000 - -73.0285470000 - 16.2285660000 - 43.2761760000 - -129.8285280000 - 97.3713960000 - -21.6380880000 - -18.0317400000 - 54.0952200000 - -40.5714150000 - 9.0158700000 - 2.4042320000 - -7.2126960000 - 5.4095220000 - -1.2021160000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 24.6068000000 - 0.0000000000 - -73.8204000000 - 49.2136000000 - -22.1461200000 - 0.0000000000 - 66.4383600000 - -44.2922400000 - 6.4592850000 - 0.0000000000 - -19.3778550000 - 12.9185700000 - -0.6151700000 - 0.0000000000 - 1.8455100000 - -1.2303400000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -# piCC - -6 -0.0 -4.0 -0.0 -4.0 -0.0 -9.0 - - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.1952460000 - -0.1301640000 - 0.0000000000 - 0.0000000000 - -0.1301640000 - 0.0867760000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.1952460000 - -0.1301640000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.2460240000 - -0.1640160000 - 0.0000000000 - 0.0000000000 - -0.1640160000 - 0.1093440000 - 0.0000000000 - 0.0000000000 - -0.1301640000 - 0.0867760000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.1640160000 - 0.1093440000 - 0.0000000000 - 0.0000000000 - 0.1093440000 - -0.0728960000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.1859430000 - 0.6024600000 - -0.4518450000 - 0.1004100000 - 0.1239620000 - -0.4016400000 - 0.3012300000 - -0.0669400000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.1859430000 - 0.6024600000 - -0.4518450000 - 0.1004100000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.8683470000 - 2.2808520000 - -1.7106390000 - 0.3801420000 - 0.5788980000 - -1.5205680000 - 1.1404260000 - -0.2534280000 - 0.1239620000 - -0.4016400000 - 0.3012300000 - -0.0669400000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.5788980000 - -1.5205680000 - 1.1404260000 - -0.2534280000 - -0.3859320000 - 1.0137120000 - -0.7602840000 - 0.1689520000 - 0.1388520000 - -0.1785240000 - 0.0743850000 - -0.0099180000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.4016790000 - 0.5355720000 - -0.2231550000 - 0.0297540000 - 0.2677860000 - -0.3570480000 - 0.1487700000 - -0.0198360000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.4016790000 - 0.5355720000 - -0.2231550000 - 0.0297540000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.3588030000 - 0.3223800000 - -0.1343250000 - 0.0179100000 - 0.2392020000 - -0.2149200000 - 0.0895500000 - -0.0119400000 - 0.2677860000 - -0.3570480000 - 0.1487700000 - -0.0198360000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.2392020000 - -0.2149200000 - 0.0895500000 - -0.0119400000 - -0.1594680000 - 0.1432800000 - -0.0597000000 - 0.0079600000 - 0.0049590000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.1170180000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0780120000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0780120000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.0520080000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0049590000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.1170180000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0780120000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0780120000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.0520080000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0049590000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.1170180000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0780120000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0780120000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.0520080000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0049590000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.1170180000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0780120000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0780120000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.0520080000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0049590000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.1170180000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0780120000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0780120000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.0520080000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0049590000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.1170180000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0780120000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0780120000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.0520080000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.1101570000 - -0.0734380000 - 0.0000000000 - 0.0000000000 - -0.1081800000 - 0.0721200000 - 0.0000000000 - 0.0000000000 - 0.0811350000 - -0.0540900000 - 0.0000000000 - 0.0000000000 - -0.0180300000 - 0.0120200000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -1.5308460000 - 1.0205640000 - 0.0000000000 - 0.0000000000 - 4.2921900000 - -2.8614600000 - 0.0000000000 - 0.0000000000 - -3.1600800000 - 2.1067200000 - 0.0000000000 - 0.0000000000 - 0.6759900000 - -0.4506600000 - 0.0000000000 - 0.0000000000 - 1.0205640000 - -0.6803760000 - 0.0000000000 - 0.0000000000 - -2.8614600000 - 1.9076400000 - 0.0000000000 - 0.0000000000 - 2.1067200000 - -1.4044800000 - 0.0000000000 - 0.0000000000 - -0.4506600000 - 0.3004400000 - -0.3953310000 - 1.0369200000 - -0.7776900000 - 0.1728200000 - 0.8000400000 - -2.0066400000 - 1.5049800000 - -0.3344400000 - -0.6000300000 - 1.5049800000 - -1.1287350000 - 0.2508300000 - 0.1333400000 - -0.3344400000 - 0.2508300000 - -0.0557400000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 4.0368330000 - -10.9130760000 - 8.1848070000 - -1.8188460000 - -10.7663400000 - 29.2729680000 - -21.9547260000 - 4.8788280000 - 7.9960050000 - -21.7184760000 - 16.2888570000 - -3.6197460000 - -1.7418900000 - 4.7213280000 - -3.5409960000 - 0.7868880000 - -2.6912220000 - 7.2753840000 - -5.4565380000 - 1.2125640000 - 7.1775600000 - -19.5153120000 - 14.6364840000 - -3.2525520000 - -5.3306700000 - 14.4789840000 - -10.8592380000 - 2.4131640000 - 1.1612600000 - -3.1475520000 - 2.3606640000 - -0.5245920000 - 1.4805090000 - -1.9674000000 - 0.8197500000 - -0.1093000000 - -3.5413200000 - 4.7217600000 - -1.9674000000 - 0.2623200000 - 2.6559900000 - -3.5413200000 - 1.4755500000 - -0.1967400000 - -0.5902200000 - 0.7869600000 - -0.3279000000 - 0.0437200000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -12.6909150000 - 16.8300720000 - -7.0125300000 - 0.9350040000 - 29.2071240000 - -38.8488960000 - 16.1870400000 - -2.1582720000 - -21.9053430000 - 29.1366720000 - -12.1402800000 - 1.6187040000 - 4.8678540000 - -6.4748160000 - 2.6978400000 - -0.3597120000 - 8.4606100000 - -11.2200480000 - 4.6750200000 - -0.6233360000 - -19.4714160000 - 25.8992640000 - -10.7913600000 - 1.4388480000 - 14.6035620000 - -19.4244480000 - 8.0935200000 - -1.0791360000 - -3.2452360000 - 4.3165440000 - -1.7985600000 - 0.2398080000 - 0.0049590000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 3.2913840000 - -3.1367700000 - 0.9712650000 - -0.0996600000 - -7.9929360000 - 7.5282480000 - -2.3310360000 - 0.2391840000 - 5.9947020000 - -5.6461860000 - 1.7482770000 - -0.1793880000 - -1.3321560000 - 1.2547080000 - -0.3885060000 - 0.0398640000 - -2.1942560000 - 2.0911800000 - -0.6475100000 - 0.0664400000 - 5.3286240000 - -5.0188320000 - 1.5540240000 - -0.1594560000 - -3.9964680000 - 3.7641240000 - -1.1655180000 - 0.1195920000 - 0.8881040000 - -0.8364720000 - 0.2590040000 - -0.0265760000 - 0.0049590000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000001 - -0.0000000001 - 0.0000000000 - 0.0000000000 - -0.0000000001 - 0.0000000001 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 51.2172720000 - -34.7250900000 - 7.7793210000 - -0.5762460000 - -125.8861200000 - 85.2977520000 - -19.1108160000 - 1.4156160000 - 98.0034060000 - -66.4202340000 - 14.8836690000 - -1.1024940000 - -23.3735640000 - 15.8475720000 - -3.5521740000 - 0.2631240000 - -34.1448480000 - 23.1500600000 - -5.1862140000 - 0.3841640000 - 83.9240800000 - -56.8651680000 - 12.7405440000 - -0.9437440000 - -65.3356040000 - 44.2801560000 - -9.9224460000 - 0.7349960000 - 15.5823760000 - -10.5650480000 - 2.3681160000 - -0.1754160000 - 0.0049590000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 18.8696220000 - -9.8713800000 - 1.7195550000 - -0.0996600000 - -45.3970200000 - 23.6913120000 - -4.1269320000 - 0.2391840000 - 34.0681560000 - -17.7684840000 - 3.0951990000 - -0.1793880000 - -7.5797640000 - 3.9485520000 - -0.6878220000 - 0.0398640000 - -12.5797480000 - 6.5809200000 - -1.1463700000 - 0.0664400000 - 30.2646800000 - -15.7942080000 - 2.7512880000 - -0.1594560000 - -22.7121040000 - 11.8456560000 - -2.0634660000 - 0.1195920000 - 5.0531760000 - -2.6323680000 - 0.4585480000 - -0.0265760000 - 0.0049590000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0187620000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.1549560000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.1366080000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.0394200000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.0125080000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.1033040000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.0910720000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0262800000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0049590000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0187620000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.1549560000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.1366080000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.0394200000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.0125080000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.1033040000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.0910720000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0262800000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0049590000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0187620000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.1549560000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.1366080000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.0394200000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.0125080000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.1033040000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.0910720000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0262800000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -10.3921350000 - 6.9280900000 - 0.0000000000 - 0.0000000000 - 13.4565840000 - -8.9710560000 - 0.0000000000 - 0.0000000000 - -5.6069100000 - 3.7379400000 - 0.0000000000 - 0.0000000000 - 0.7475880000 - -0.4983920000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 34.2564300000 - -22.8376200000 - 0.0000000000 - 0.0000000000 - -43.7677020000 - 29.1784680000 - 0.0000000000 - 0.0000000000 - 18.0593550000 - -12.0395700000 - 0.0000000000 - 0.0000000000 - -2.3921640000 - 1.5947760000 - 0.0000000000 - 0.0000000000 - -22.8376200000 - 15.2250800000 - 0.0000000000 - 0.0000000000 - 29.1784680000 - -19.4523120000 - 0.0000000000 - 0.0000000000 - -12.0395700000 - 8.0263800000 - 0.0000000000 - 0.0000000000 - 1.5947760000 - -1.0631840000 - 0.6764050000 - -9.9370800000 - 7.4528100000 - -1.6561800000 - -1.0350720000 - 13.2494400000 - -9.9370800000 - 2.2082400000 - 0.4312800000 - -5.5206000000 - 4.1404500000 - -0.9201000000 - -0.0575040000 - 0.7360800000 - -0.5520600000 - 0.1226800000 - 0.0000000000 - 0.0000000001 - -0.0000000001 - 0.0000000000 - 0.0000000000 - -0.0000000001 - 0.0000000001 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -43.6827750000 - 132.2438040000 - -99.1828530000 - 22.0406340000 - 56.1996360000 - -169.8932880000 - 127.4199660000 - -28.3155480000 - -23.1802650000 - 70.0801200000 - -52.5600900000 - 11.6800200000 - 3.0697020000 - -9.2810160000 - 6.9607620000 - -1.5468360000 - 30.8739500000 - -92.3675760000 - 69.2756820000 - -15.3945960000 - -39.7191240000 - 118.6686720000 - -89.0015040000 - 19.7781120000 - 16.3921350000 - -48.9727800000 - 36.7295850000 - -8.1621300000 - -2.1716180000 - 6.4877040000 - -4.8657780000 - 1.0812840000 - 71.3096370000 - -95.0729040000 - 39.6137100000 - -5.2818280000 - -91.2980160000 - 121.7306880000 - -50.7211200000 - 6.7628160000 - 38.0408400000 - -50.7211200000 - 21.1338000000 - -2.8178400000 - -5.0721120000 - 6.7628160000 - -2.8178400000 - 0.3757120000 - -0.0000000001 - 0.0000000001 - 0.0000000000 - 0.0000000000 - 0.0000000001 - -0.0000000001 - 0.0000000001 - 0.0000000000 - 0.0000000000 - 0.0000000001 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -135.3030030000 - 174.4733520000 - -72.6972300000 - 9.6929640000 - 170.1614520000 - -219.3337440000 - 91.3890600000 - -12.1852080000 - -70.9006050000 - 91.3890600000 - -38.0787750000 - 5.0771700000 - 9.4534140000 - -12.1852080000 - 5.0771700000 - -0.6769560000 - 80.7406620000 - -103.7004480000 - 43.2085200000 - -5.7611360000 - -101.2763880000 - 130.0030560000 - -54.1679400000 - 7.2223920000 - 42.1984950000 - -54.1679400000 - 22.5699750000 - -3.0093300000 - -5.6264660000 - 7.2223920000 - -3.0093300000 - 0.4012440000 - 0.0049590000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -22.5906120000 - 16.9385580000 - -5.2448310000 - 0.5381640000 - 29.8513080000 - -22.5847440000 - 6.9931080000 - -0.7175520000 - -12.4380450000 - 9.4103100000 - -2.9137950000 - 0.2989800000 - 1.6584060000 - -1.2547080000 - 0.3885060000 - -0.0398640000 - 15.0604080000 - -11.2923720000 - 3.4965540000 - -0.3587760000 - -19.9008720000 - 15.0564960000 - -4.6620720000 - 0.4783680000 - 8.2920300000 - -6.2735400000 - 1.9425300000 - -0.1993200000 - -1.1056040000 - 0.8364720000 - -0.2590040000 - 0.0265760000 - 0.0049590000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000002 - -0.0000000002 - 0.0000000000 - 0.0000000000 - -0.0000000003 - 0.0000000002 - 0.0000000000 - 0.0000000000 - 0.0000000001 - -0.0000000001 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 132.0411960000 - -94.3696980000 - 21.4158330000 - -1.5863580000 - -133.2586440000 - 96.4632240000 - -21.9477600000 - 1.6257600000 - 44.7579870000 - -32.8522500000 - 7.4932290000 - -0.5550540000 - -5.0107140000 - 3.7277880000 - -0.8522820000 - 0.0631320000 - -88.0274640000 - 62.9131320000 - -14.2772220000 - 1.0575720000 - 88.8390960000 - -64.3088160000 - 14.6318400000 - -1.0838400000 - -29.8386580000 - 21.9015000000 - -4.9954860000 - 0.3700360000 - 3.3404760000 - -2.4851920000 - 0.5681880000 - -0.0420880000 - 0.0049590000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -104.3640539999 - 53.3054519999 - -9.2855970000 - 0.5381640000 - 139.1272559998 - -71.0739359999 - 12.3807960000 - -0.7175520000 - -58.0308629999 - 29.6141400000 - -5.1586650000 - 0.2989800000 - 7.7428860000 - -3.9485520000 - 0.6878220000 - -0.0398640000 - 69.5760360000 - -35.5369680000 - 6.1903980000 - -0.3587760000 - -92.7515040000 - 47.3826240000 - -8.2538640000 - 0.4783680000 - 38.6872420000 - -19.7427600000 - 3.4391100000 - -0.1993200000 - -5.1619240000 - 2.6323680000 - -0.4585480000 - 0.0265760000 - 0.0049590000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -2.5694100000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 3.4010640000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -1.4782830000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.2025420000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 1.7129400000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -2.2673760000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.9855220000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.1350280000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0049590000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -2.5694100000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 3.4010640000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -1.4782830000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.2025420000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 1.7129400000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -2.2673760000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.9855220000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.1350280000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0049590000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -2.5694100000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 3.4010640000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -1.4782830000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.2025420000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 1.7129400000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -2.2673760000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.9855220000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.1350280000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 23.9757600000 - -15.9838400000 - 0.0000000000 - 0.0000000000 - -21.5781840000 - 14.3854560000 - 0.0000000000 - 0.0000000000 - 6.2936370000 - -4.1957580000 - 0.0000000000 - 0.0000000000 - -0.5993940000 - 0.3995960000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -71.9272800000 - 47.9515200000 - 0.0000000000 - 0.0000000000 - 64.7345520000 - -43.1563680000 - 0.0000000000 - 0.0000000000 - -18.8809110000 - 12.5872740000 - 0.0000000000 - 0.0000000000 - 1.7981820000 - -1.1987880000 - 0.0000000000 - 0.0000000000 - 47.9515200000 - -31.9676800000 - 0.0000000000 - 0.0000000000 - -43.1563680000 - 28.7709120000 - 0.0000000000 - 0.0000000000 - 12.5872740000 - -8.3915160000 - 0.0000000000 - 0.0000000000 - -1.1987880000 - 0.7991920000 - 7.9919200000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -7.1927280000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 2.0978790000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.1997980000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000001 - -0.0000000002 - 0.0000000001 - 0.0000000000 - -0.0000000001 - 0.0000000002 - -0.0000000001 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 65.9438400000 - -215.8070400000 - 161.8552800000 - -35.9678400000 - -59.3494560000 - 194.2263360000 - -145.6697520000 - 32.3710560000 - 17.3102580000 - -56.6493480000 - 42.4870110000 - -9.4415580000 - -1.6485960000 - 5.3951760000 - -4.0463820000 - 0.8991960000 - -48.9685600000 - 155.8857600000 - -116.9143200000 - 25.9809600000 - 44.0717040000 - -140.2971840000 - 105.2228880000 - -23.3828640000 - -12.8542470000 - 40.9200120000 - -30.6900090000 - 6.8200020000 - 1.2242140000 - -3.8971440000 - 2.9228580000 - -0.6495240000 - -226.8900000000 - 301.9910400000 - -125.8296000000 - 16.7772800000 - 204.2010000000 - -271.7919360000 - 113.2466400000 - -15.0995520000 - -59.5586250000 - 79.2726480000 - -33.0302700000 - 4.4040360000 - 5.6722500000 - -7.5497760000 - 3.1457400000 - -0.4194320000 - -0.0000000004 - 0.0000000005 - -0.0000000002 - 0.0000000000 - 0.0000000003 - -0.0000000005 - 0.0000000002 - 0.0000000000 - -0.0000000001 - 0.0000000001 - -0.0000000001 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 614.5531200001 - -797.8435200001 - 332.4348000001 - -44.3246400000 - -553.0978080001 - 718.0591680001 - -299.1913200001 - 39.8921760000 - 161.3201940000 - -209.4339240000 - 87.2641350000 - -11.6352180000 - -15.3638280000 - 19.9460880000 - -8.3108700000 - 1.1081160000 - -382.6696800000 - 495.8524800000 - -206.6052000000 - 27.5473600000 - 344.4027120000 - -446.2672320000 - 185.9446800000 - -24.7926240000 - -100.4507910000 - 130.1612760000 - -54.2338650000 - 7.2311820000 - 9.5667420000 - -12.3963120000 - 5.1651300000 - -0.6886840000 - -0.3967200000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.3570480000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.1041390000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0099180000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 16.1704800000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -14.5534320000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 4.2447510000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.4042620000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -10.7803200000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 9.7022880000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -2.8298340000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.2695080000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.3967200000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.3570480000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.1041390000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0099180000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 16.1704800000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -14.5534320000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 4.2447510000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.4042620000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -10.7803200000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 9.7022880000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -2.8298340000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.2695080000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.3967200000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.3570480000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.1041390000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0099180000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 16.1704800000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -14.5534320000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 4.2447510000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.4042620000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -10.7803200000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 9.7022880000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -2.8298340000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.2695080000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.3967200000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.3570480000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.1041390000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0099180000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 16.1704800000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -14.5534320000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 4.2447510000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.4042620000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -10.7803200000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 9.7022880000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -2.8298340000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.2695080000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.3967200000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.3570480000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.1041390000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0099180000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 16.1704800000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -14.5534320000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 4.2447510000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.4042620000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -10.7803200000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 9.7022880000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -2.8298340000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.2695080000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.3967200000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.3570480000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.1041390000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0099180000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 16.1704800000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -14.5534320000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 4.2447510000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.4042620000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -10.7803200000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 9.7022880000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -2.8298340000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.2695080000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.1101570000 - -0.0734380000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -1.5308460000 - 1.0205640000 - 0.0000000000 - 0.0000000000 - 1.0205640000 - -0.6803760000 - 0.0000000000 - 0.0000000000 - -0.1081800000 - 0.0721200000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 4.2921900000 - -2.8614600000 - 0.0000000000 - 0.0000000000 - -2.8614600000 - 1.9076400000 - 0.0000000000 - 0.0000000000 - 0.0811350000 - -0.0540900000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -3.1600800000 - 2.1067200000 - 0.0000000000 - 0.0000000000 - 2.1067200000 - -1.4044800000 - 0.0000000000 - 0.0000000000 - -0.0180300000 - 0.0120200000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.6759900000 - -0.4506600000 - 0.0000000000 - 0.0000000000 - -0.4506600000 - 0.3004400000 - -0.3953310000 - 1.0369200000 - -0.7776900000 - 0.1728200000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 4.0368330000 - -10.9130760000 - 8.1848070000 - -1.8188460000 - -2.6912220000 - 7.2753840000 - -5.4565380000 - 1.2125640000 - 0.8000400000 - -2.0066400000 - 1.5049800000 - -0.3344400000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -10.7663400000 - 29.2729680000 - -21.9547260000 - 4.8788280000 - 7.1775600000 - -19.5153120000 - 14.6364840000 - -3.2525520000 - -0.6000300000 - 1.5049800000 - -1.1287350000 - 0.2508300000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 7.9960050000 - -21.7184760000 - 16.2888570000 - -3.6197460000 - -5.3306700000 - 14.4789840000 - -10.8592380000 - 2.4131640000 - 0.1333400000 - -0.3344400000 - 0.2508300000 - -0.0557400000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -1.7418900000 - 4.7213280000 - -3.5409960000 - 0.7868880000 - 1.1612600000 - -3.1475520000 - 2.3606640000 - -0.5245920000 - 1.4805090000 - -1.9674000000 - 0.8197500000 - -0.1093000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -12.6909150000 - 16.8300720000 - -7.0125300000 - 0.9350040000 - 8.4606100000 - -11.2200480000 - 4.6750200000 - -0.6233360000 - -3.5413200000 - 4.7217600000 - -1.9674000000 - 0.2623200000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 29.2071240000 - -38.8488960000 - 16.1870400000 - -2.1582720000 - -19.4714160000 - 25.8992640000 - -10.7913600000 - 1.4388480000 - 2.6559900000 - -3.5413200000 - 1.4755500000 - -0.1967400000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -21.9053430000 - 29.1366720000 - -12.1402800000 - 1.6187040000 - 14.6035620000 - -19.4244480000 - 8.0935200000 - -1.0791360000 - -0.5902200000 - 0.7869600000 - -0.3279000000 - 0.0437200000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 4.8678540000 - -6.4748160000 - 2.6978400000 - -0.3597120000 - -3.2452360000 - 4.3165440000 - -1.7985600000 - 0.2398080000 - 0.0049590000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 3.2913840000 - -3.1367700000 - 0.9712650000 - -0.0996600000 - -2.1942560000 - 2.0911800000 - -0.6475100000 - 0.0664400000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -7.9929360000 - 7.5282480000 - -2.3310360000 - 0.2391840000 - 5.3286240000 - -5.0188320000 - 1.5540240000 - -0.1594560000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 5.9947020000 - -5.6461860000 - 1.7482770000 - -0.1793880000 - -3.9964680000 - 3.7641240000 - -1.1655180000 - 0.1195920000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -1.3321560000 - 1.2547080000 - -0.3885060000 - 0.0398640000 - 0.8881040000 - -0.8364720000 - 0.2590040000 - -0.0265760000 - 0.0049590000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 51.2172720000 - -34.7250900000 - 7.7793210000 - -0.5762460000 - -34.1448480000 - 23.1500600000 - -5.1862140000 - 0.3841640000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -125.8861200000 - 85.2977520000 - -19.1108160000 - 1.4156160000 - 83.9240800000 - -56.8651680000 - 12.7405440000 - -0.9437440000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 98.0034060000 - -66.4202340000 - 14.8836690000 - -1.1024940000 - -65.3356040000 - 44.2801560000 - -9.9224460000 - 0.7349960000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -23.3735640000 - 15.8475720000 - -3.5521740000 - 0.2631240000 - 15.5823760000 - -10.5650480000 - 2.3681160000 - -0.1754160000 - 0.0049590000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 18.8696220000 - -9.8713800000 - 1.7195550000 - -0.0996600000 - -12.5797480000 - 6.5809200000 - -1.1463700000 - 0.0664400000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -45.3970200000 - 23.6913120000 - -4.1269320000 - 0.2391840000 - 30.2646800000 - -15.7942080000 - 2.7512880000 - -0.1594560000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 34.0681560000 - -17.7684840000 - 3.0951990000 - -0.1793880000 - -22.7121040000 - 11.8456560000 - -2.0634660000 - 0.1195920000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -7.5797640000 - 3.9485520000 - -0.6878220000 - 0.0398640000 - 5.0531760000 - -2.6323680000 - 0.4585480000 - -0.0265760000 - 0.0049590000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0187620000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.0125080000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.1549560000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.1033040000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.1366080000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.0910720000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.0394200000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0262800000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0049590000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0187620000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.0125080000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.1549560000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.1033040000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.1366080000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.0910720000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.0394200000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0262800000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0049590000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0187620000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.0125080000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.1549560000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.1033040000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.1366080000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.0910720000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.0394200000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0262800000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 4.2228750000 - -2.8152500000 - 0.0000000000 - 0.0000000000 - -11.0322000000 - 7.3548000000 - 0.0000000000 - 0.0000000000 - 8.1954000000 - -5.4636000000 - 0.0000000000 - 0.0000000000 - -1.7862000000 - 1.1908000000 - 0.0000000000 - 0.0000000000 - -11.0322000000 - 7.3548000000 - 0.0000000000 - 0.0000000000 - 29.4624000000 - -19.6416000000 - 0.0000000000 - 0.0000000000 - -21.8605500000 - 14.5737000000 - 0.0000000000 - 0.0000000000 - 4.7529000000 - -3.1686000000 - 0.0000000000 - 0.0000000000 - 8.1954000000 - -5.4636000000 - 0.0000000000 - 0.0000000000 - -21.8605500000 - 14.5737000000 - 0.0000000000 - 0.0000000000 - 16.2182250000 - -10.8121500000 - 0.0000000000 - 0.0000000000 - -3.5253000000 - 2.3502000000 - 0.0000000000 - 0.0000000000 - -1.7862000000 - 1.1908000000 - 0.0000000000 - 0.0000000000 - 4.7529000000 - -3.1686000000 - 0.0000000000 - 0.0000000000 - -3.5253000000 - 2.3502000000 - 0.0000000000 - 0.0000000000 - 0.7659000000 - -0.5106000000 - -7.4226200000 - 21.1925880000 - -15.8944410000 - 3.5320980000 - 20.0109600000 - -56.8520640000 - 42.6390480000 - -9.4753440000 - -14.9032200000 - 42.3240480000 - -31.7430360000 - 7.0540080000 - 3.2651600000 - -9.2653440000 - 6.9490080000 - -1.5442240000 - 20.0109600000 - -56.8520640000 - 42.6390480000 - -9.4753440000 - -54.4672800000 - 154.2913920000 - -115.7185440000 - 25.7152320000 - 40.5354600000 - -114.7735440000 - 86.0801580000 - -19.1289240000 - -8.8678800000 - 25.0852320000 - -18.8139240000 - 4.1808720000 - -14.9032200000 - 42.3240480000 - -31.7430360000 - 7.0540080000 - 40.5354600000 - -114.7735440000 - 86.0801580000 - -19.1289240000 - -30.1653450000 - 85.3714080000 - -64.0285560000 - 14.2285680000 - 6.5984100000 - -18.6564240000 - 13.9923180000 - -3.1094040000 - 3.2651600000 - -9.2653440000 - 6.9490080000 - -1.5442240000 - -8.8678800000 - 25.0852320000 - -18.8139240000 - 4.1808720000 - 6.5984100000 - -18.6564240000 - 13.9923180000 - -3.1094040000 - -1.4429800000 - 4.0758720000 - -3.0569040000 - 0.6793120000 - 31.1712840000 - -40.5381960000 - 16.8909150000 - -2.2521220000 - -81.4105920000 - 106.0339680000 - -44.1808200000 - 5.8907760000 - 61.0579440000 - -79.5254760000 - 33.1356150000 - -4.4180820000 - -13.5684320000 - 17.6723280000 - -7.3634700000 - 0.9817960000 - -81.4105920000 - 106.0339680000 - -44.1808200000 - 5.8907760000 - 210.2519520000 - -274.2284160000 - 114.2618400000 - -15.2349120000 - -157.6889640000 - 205.6713120000 - -85.6963800000 - 11.4261840000 - 35.0419920000 - -45.7047360000 - 19.0436400000 - -2.5391520000 - 61.0579440000 - -79.5254760000 - 33.1356150000 - -4.4180820000 - -157.6889640000 - 205.6713120000 - -85.6963800000 - 11.4261840000 - 118.2667230000 - -154.2534840000 - 64.2722850000 - -8.5696380000 - -26.2814940000 - 34.2785520000 - -14.2827300000 - 1.9043640000 - -13.5684320000 - 17.6723280000 - -7.3634700000 - 0.9817960000 - 35.0419920000 - -45.7047360000 - 19.0436400000 - -2.5391520000 - -26.2814940000 - 34.2785520000 - -14.2827300000 - 1.9043640000 - 5.8403320000 - -7.6174560000 - 3.1739400000 - -0.4231920000 - -11.9143080000 - 11.5909950000 - -3.5000150000 - 0.3484850000 - 31.2393479999 - -30.3278039999 - 9.1770480000 - -0.9160920000 - -23.4295110000 - 22.7458530000 - -6.8827860000 - 0.6870690000 - 5.2065580000 - -5.0546340000 - 1.5295080000 - -0.1526820000 - 31.2393480000 - -30.3278040000 - 9.1770480000 - -0.9160920000 - -81.3687839999 - 78.8093279999 - -23.8897440000 - 2.3899680000 - 61.0265880000 - -59.1069960000 - 17.9173080000 - -1.7924760000 - -13.5614640000 - 13.1348880000 - -3.9816240000 - 0.3983280000 - -23.4295110000 - 22.7458530000 - -6.8827860000 - 0.6870690000 - 61.0265880000 - -59.1069960000 - 17.9173080000 - -1.7924760000 - -45.7699410000 - 44.3302470000 - -13.4379810000 - 1.3443570000 - 10.1710980000 - -9.8511660000 - 2.9862180000 - -0.2987460000 - 5.2065580000 - -5.0546340000 - 1.5295080000 - -0.1526820000 - -13.5614640000 - 13.1348880000 - -3.9816240000 - 0.3983280000 - 10.1710980000 - -9.8511660000 - 2.9862180000 - -0.2987460000 - -2.2602440000 - 2.1891480000 - -0.6636040000 - 0.0663880000 - -135.7458759999 - 92.5175150000 - -20.7448560000 - 1.5366560000 - 370.6038919998 - -252.4321559999 - 56.5983720000 - -4.1924720000 - -282.7380069998 - 192.5866769999 - -43.1828550000 - 3.1987300000 - 64.9573740000 - -44.2470660000 - 9.9224460000 - -0.7349960000 - 370.6038920000 - -252.4321560000 - 56.5983720000 - -4.1924720000 - -1001.6424479999 - 681.9055199999 - -152.8865280000 - 11.3249280000 - 765.5870999998 - -521.2168199999 - 116.8671240000 - -8.6568240000 - -176.5105840000 - 120.1760400000 - -26.9492400000 - 1.9962400000 - -282.7380070001 - 192.5866770000 - -43.1828550000 - 3.1987300000 - 765.5871000001 - -521.2168200000 - 116.8671240000 - -8.6568240000 - -584.9567730000 - 398.2533750000 - -89.3020140000 - 6.6149640000 - 134.7754820000 - -91.7633100000 - 20.5789680000 - -1.5243680000 - 64.9573740000 - -44.2470660000 - 9.9224460000 - -0.7349960000 - -176.5105840000 - 120.1760400000 - -26.9492400000 - 1.9962400000 - 134.7754820000 - -91.7633100000 - 20.5789680000 - -1.5243680000 - -31.0134600000 - 21.1168600000 - -4.7362320000 - 0.3508320000 - -49.4854760001 - 26.2409550000 - -4.5854800000 - 0.2657600000 - 133.8944920002 - -70.8753960001 - 12.3807960000 - -0.7175520000 - -100.4480570001 - 53.1565470001 - -9.2855970000 - 0.5381640000 - 22.3338740000 - -11.8125660000 - 2.0634660000 - -0.1195920000 - 133.8944920001 - -70.8753960000 - 12.3807960000 - -0.7175520000 - -357.7296480001 - 189.0540000001 - -33.0154560000 - 1.9134720000 - 268.3788000001 - -141.7905000001 - 24.7615920000 - -1.4351040000 - -59.6759840000 - 31.5090000000 - -5.5025760000 - 0.3189120000 - -100.4480570000 - 53.1565470000 - -9.2855970000 - 0.5381640000 - 268.3788000000 - -141.7905000000 - 24.7615920000 - -1.4351040000 - -201.3452730000 - 106.3428750000 - -18.5711940000 - 1.0763280000 - 44.7705820000 - -23.6317500000 - 4.1269320000 - -0.2391840000 - 22.3338740000 - -11.8125660000 - 2.0634660000 - -0.1195920000 - -59.6759840000 - 31.5090000000 - -5.5025760000 - 0.3189120000 - 44.7705820000 - -23.6317500000 - 4.1269320000 - -0.2391840000 - -9.9550600000 - 5.2515000000 - -0.9170960000 - 0.0531520000 - 0.7969840000 - -0.0890250000 - 0.0009750000 - -0.0000500000 - -1.8641000000 - 0.2136600000 - -0.0023400000 - 0.0001200000 - 1.3708870000 - -0.1602450000 - 0.0017550000 - -0.0000900000 - -0.2925580000 - 0.0356100000 - -0.0003900000 - 0.0000200000 - -1.8641000000 - 0.2136600000 - -0.0023400000 - 0.0001200000 - 4.2846240000 - -0.5127840000 - 0.0056160000 - -0.0002880000 - -3.1319040000 - 0.3845880000 - -0.0042120000 - 0.0002160000 - 0.6597280000 - -0.0854640000 - 0.0009360000 - -0.0000480000 - 1.3708870000 - -0.1602450000 - 0.0017550000 - -0.0000900000 - -3.1319040000 - 0.3845880000 - -0.0042120000 - 0.0002160000 - 2.2877550000 - -0.2884410000 - 0.0031590000 - -0.0001620000 - -0.4812020000 - 0.0640980000 - -0.0007020000 - 0.0000360000 - -0.2925580000 - 0.0356100000 - -0.0003900000 - 0.0000200000 - 0.6597280000 - -0.0854640000 - 0.0009360000 - -0.0000480000 - -0.4812020000 - 0.0640980000 - -0.0007020000 - 0.0000360000 - 0.1008920000 - -0.0142440000 - 0.0001560000 - -0.0000080000 - 0.7835090000 - -0.0827250000 - 0.0000000000 - 0.0000000000 - -1.8317600000 - 0.1985400000 - 0.0000000000 - 0.0000000000 - 1.3466320000 - -0.1489050000 - 0.0000000000 - 0.0000000000 - -0.2871680000 - 0.0330900000 - 0.0000000000 - 0.0000000000 - -1.8317600000 - 0.1985400000 - 0.0000000000 - 0.0000000000 - 4.2070080000 - -0.4764960000 - 0.0000000000 - 0.0000000000 - -3.0736920000 - 0.3573720000 - 0.0000000000 - 0.0000000000 - 0.6467920000 - -0.0794160000 - 0.0000000000 - 0.0000000000 - 1.3466320000 - -0.1489050000 - 0.0000000000 - 0.0000000000 - -3.0736920000 - 0.3573720000 - 0.0000000000 - 0.0000000000 - 2.2440960000 - -0.2680290000 - 0.0000000000 - 0.0000000000 - -0.4715000000 - 0.0595620000 - 0.0000000000 - 0.0000000000 - -0.2871680000 - 0.0330900000 - 0.0000000000 - 0.0000000000 - 0.6467920000 - -0.0794160000 - 0.0000000000 - 0.0000000000 - -0.4715000000 - 0.0595620000 - 0.0000000000 - 0.0000000000 - 0.0987360000 - -0.0132360000 - 0.0000000000 - 0.0000000000 - -46.8660909997 - 17.1240749999 - -2.0681250000 - 0.0827250000 - 112.5272799994 - -41.0977799998 - 4.9635000000 - -0.1985400000 - -84.4226479996 - 30.8233349999 - -3.7226250000 - 0.1489050000 - 18.7726719999 - -6.8496300000 - 0.8272500000 - -0.0330900000 - 112.5272799995 - -41.0977799998 - 4.9635000000 - -0.1985400000 - -270.2546879991 - 98.6346719997 - -11.9124000000 - 0.4764960000 - 202.7725799994 - -73.9760039998 - 8.9343000000 - -0.3573720000 - -45.0968239999 - 16.4391120000 - -1.9854000000 - 0.0794160000 - -84.4226479998 - 30.8233349999 - -3.7226250000 - 0.1489050000 - 202.7725799997 - -73.9760039999 - 8.9343000000 - -0.3573720000 - -152.1406079998 - 55.4820029999 - -6.7007250000 - 0.2680290000 - 33.8362120000 - -12.3293340000 - 1.4890500000 - -0.0595620000 - 18.7726720000 - -6.8496300000 - 0.8272500000 - -0.0330900000 - -45.0968240000 - 16.4391120000 - -1.9854000000 - 0.0794160000 - 33.8362120000 - -12.3293340000 - 1.4890500000 - -0.0595620000 - -7.5252000000 - 2.7398520000 - -0.3309000000 - 0.0132360000 - 0.0000000000 - 0.0000000000 - -32.6219250000 - 21.7479500000 - 0.0000000000 - 0.0000000000 - 42.1038000000 - -28.0692000000 - 0.0000000000 - 0.0000000000 - -17.3070000000 - 11.5380000000 - 0.0000000000 - 0.0000000000 - 2.2866000000 - -1.5244000000 - 0.0000000000 - 0.0000000000 - 80.7566400000 - -53.8377600000 - 0.0000000000 - 0.0000000000 - -103.7674800000 - 69.1783200000 - 0.0000000000 - 0.0000000000 - 42.5277000000 - -28.3518000000 - 0.0000000000 - 0.0000000000 - -5.6073600000 - 3.7382400000 - 0.0000000000 - 0.0000000000 - -60.5674800000 - 40.3783200000 - 0.0000000000 - 0.0000000000 - 77.8256100000 - -51.8837400000 - 0.0000000000 - 0.0000000000 - -31.8957750000 - 21.2638500000 - 0.0000000000 - 0.0000000000 - 4.2055200000 - -2.8036800000 - 0.0000000000 - 0.0000000000 - 13.4594400000 - -8.9729600000 - 0.0000000000 - 0.0000000000 - -17.2945800000 - 11.5297200000 - 0.0000000000 - 0.0000000000 - 7.0879500000 - -4.7253000000 - 0.0000000000 - 0.0000000000 - -0.9345600000 - 0.6230400000 - 24.9742400000 - -86.0357160001 - 64.5267870000 - -14.3392860000 - -32.3569800000 - 111.3397920001 - -83.5048440000 - 18.5566320000 - 13.1670750000 - -45.4465800000 - 34.0849350000 - -7.5744300000 - -1.7276100000 - 5.9755440000 - -4.4816580000 - 0.9959240000 - -95.7183600000 - 294.3293760001 - -220.7470320000 - 49.0548960000 - 123.2917200000 - -378.9141120001 - 284.1855840000 - -63.1523520000 - -50.4265500000 - 155.0458800000 - -116.2844100000 - 25.8409800000 - 6.6395400000 - -20.4207840000 - 15.3155880000 - -3.4034640000 - 74.8604400000 - -228.1190400000 - 171.0892800000 - -38.0198400000 - -96.4180800000 - 293.6638800000 - -220.2479100000 - 48.9439800000 - 39.4654500000 - -120.2337000000 - 90.1752750000 - -20.0389500000 - -5.1990600000 - 15.8421600000 - -11.8816200000 - 2.6403600000 - -16.2487400000 - 49.7645280000 - -37.3233960000 - 8.2940880000 - 20.9287800000 - -64.0647360000 - 48.0485520000 - -10.6774560000 - -8.5628250000 - 26.2211400000 - -19.6658550000 - 4.3701900000 - 1.1277100000 - -3.4541520000 - 2.5906140000 - -0.5756920000 - 4.9724479999 - -11.1558599999 - 4.6482749999 - -0.6197700000 - -1.2060359999 - 7.6658399999 - -3.1940999999 - 0.4258800000 - 0.5025150000 - -3.1940999999 - 1.3308750000 - -0.1774500000 - -0.0670020000 - 0.4258800000 - -0.1774500000 - 0.0236600000 - 74.0236080001 - -92.0985120001 - 38.3743800001 - -5.1165840000 - -109.7359920001 - 137.2152960002 - -57.1730400001 - 7.6230720000 - 45.7233300000 - -57.1730400001 - 23.8221000000 - -3.1762800000 - -6.0964440000 - 7.6230720000 - -3.1762800000 - 0.4235040000 - -84.3386520000 - 106.9192440000 - -44.5496850000 - 5.9399580000 - 119.3574960000 - -151.5697920000 - 63.1540800000 - -8.4205440000 - -49.7322900000 - 63.1540800000 - -26.3142000000 - 3.5085600000 - 6.6309720000 - -8.4205440000 - 3.5085600000 - -0.4678080000 - 22.0898920000 - -27.9648720000 - 11.6520300000 - -1.5536040000 - -30.8284200000 - 39.0886560000 - -16.2869400000 - 2.1715920000 - 12.8451750000 - -16.2869400000 - 6.7862250000 - -0.9048300000 - -1.7126900000 - 2.1715920000 - -0.9048300000 - 0.1206440000 - 40.8978920001 - -40.0066290001 - 11.9069730000 - -1.1642670000 - -54.5131080001 - 53.3421720001 - -15.8759640000 - 1.5523560000 - 22.7137950000 - -22.2259050000 - 6.6149850000 - -0.6468150000 - -3.0285060000 - 2.9634540000 - -0.8819980000 - 0.0862420000 - -115.8659880001 - 109.5667560001 - -32.7726000000 - 3.2247720000 - 154.2630960001 - -146.0890080001 - 43.6968000000 - -4.2996960000 - -64.2762900000 - 60.8704200000 - -18.2070000000 - 1.7915400000 - 8.5701720000 - -8.1160560000 - 2.4276000000 - -0.2388720000 - 86.4625650000 - -82.1750670000 - 24.5794500000 - -2.4185790000 - -115.1355600000 - 109.5667560000 - -32.7726000000 - 3.2247720000 - 47.9731500000 - -45.6528150000 - 13.6552500000 - -1.3436550000 - -6.3964200000 - 6.0870420000 - -1.8207000000 - 0.1791540000 - -19.0197140000 - 18.2611260000 - -5.4621000000 - 0.5374620000 - 25.3360080000 - -24.3481680000 - 7.2828000000 - -0.7166160000 - -10.5566700000 - 10.1450700000 - -3.0345000000 - 0.2985900000 - 1.4075560000 - -1.3526760000 - 0.4046000000 - -0.0398120000 - -186.7201720006 - 126.2729790004 - -28.5544440001 - 2.1151440000 - 191.5565880008 - -129.2132520005 - 29.2636800001 - -2.1676800000 - -65.4599810003 - 44.0511750002 - -9.9909720000 - 0.7400720000 - 7.4519740000 - -5.0034740000 - 1.1363760000 - -0.0841760000 - 554.1228120007 - -378.5509080004 - 85.6633320001 - -6.3454320000 - -566.7921360009 - 387.2823840006 - -87.7910400001 - 6.5030400000 - 193.0975980004 - -132.0046200002 - 29.9729160000 - -2.2202160000 - -21.9182760000 - 14.9905680000 - -3.4091280000 - 0.2525280000 - -416.0290350000 - 283.9131810000 - -64.2474990000 - 4.7590740000 - 425.6558640000 - -290.4617880000 - 65.8432800000 - -4.8772800000 - -145.0572660000 - 99.0034650000 - -22.4796870000 - 1.6651620000 - 16.4699160000 - -11.2429260000 - 2.5568460000 - -0.1893960000 - 92.6450860000 - -63.0918180000 - 14.2772220000 - -1.0575720000 - -94.8398640000 - 64.5470640000 - -14.6318400000 - 1.0838400000 - 32.3389780000 - -22.0007700000 - 4.9954860000 - -0.3700360000 - -3.6738520000 - 2.4984280000 - -0.5681880000 - 0.0420880000 - 128.4868280012 - -70.6272210007 - 12.3807960001 - -0.7175520000 - -171.6246120015 - 94.1696280009 - -16.5077280002 - 0.9567360000 - 71.5918190006 - -39.2373450004 - 6.8782200001 - -0.3986400000 - -9.5528260001 - 5.2316460000 - -0.9170960000 - 0.0531520000 - -391.4981880012 - 212.1496920007 - -37.1423880001 - 2.1526560000 - 522.7514640016 - -282.8662560009 - 49.5231840002 - -2.8702080000 - -218.0578020006 - 117.8609400004 - -20.6346600001 - 1.1959200000 - 29.0961240001 - -15.7147920000 - 2.7512880000 - -0.1594560000 - 293.1867150000 - -159.1122690000 - 27.8567910000 - -1.6144920000 - -391.5018360000 - 212.1496920000 - -37.1423880000 - 2.1526560000 - 163.3092840000 - -88.3957050000 - 15.4759950000 - -0.8969400000 - -21.7908840000 - 11.7860940000 - -2.0634660000 - 0.1195920000 - -64.9584140000 - 35.3582820000 - -6.1903980000 - 0.3587760000 - 86.7507360000 - -47.1443760000 - 8.2538640000 - -0.4783680000 - -36.1869220000 - 19.6434900000 - -3.4391100000 - 0.1993200000 - 4.8285480000 - -2.6191320000 - 0.4585480000 - -0.0265760000 - -7.3122640000 - 0.4807350000 - -0.0052650000 - 0.0002700000 - 9.4408440000 - -0.6409800000 - 0.0070200000 - -0.0003600000 - -3.8521210000 - 0.2670750000 - -0.0029250000 - 0.0001500000 - 0.5063660000 - -0.0356100000 - 0.0003900000 - -0.0000200000 - 15.8553480000 - -1.1537640000 - 0.0126360000 - -0.0006480000 - -20.3865840000 - 1.5383520000 - -0.0168480000 - 0.0008640000 - 8.2497180000 - -0.6409800000 - 0.0070200000 - -0.0003600000 - -1.0782120000 - 0.0854640000 - -0.0009360000 - 0.0000480000 - -12.3284370000 - 0.8653230000 - -0.0094770000 - 0.0004860000 - 15.8517000000 - -1.1537640000 - 0.0126360000 - -0.0006480000 - -6.4213560000 - 0.4807350000 - -0.0052650000 - 0.0002700000 - 0.8398680000 - -0.0640980000 - 0.0007020000 - -0.0000360000 - 2.9338420000 - -0.1922940000 - 0.0021060000 - -0.0001080000 - -3.7722720000 - 0.2563920000 - -0.0028080000 - 0.0001440000 - 1.5309980000 - -0.1068300000 - 0.0011700000 - -0.0000600000 - -0.2005080000 - 0.0142440000 - -0.0001560000 - 0.0000080000 - -7.2394990000 - 0.4467150000 - 0.0000000000 - 0.0000000000 - 9.3438240000 - -0.5956200000 - 0.0000000000 - 0.0000000000 - -3.8116960000 - 0.2481750000 - 0.0000000000 - 0.0000000000 - 0.5009760000 - -0.0330900000 - 0.0000000000 - 0.0000000000 - 15.6807120000 - -1.0721160000 - 0.0000000000 - 0.0000000000 - -20.1537360000 - 1.4294880000 - 0.0000000000 - 0.0000000000 - 8.1526980000 - -0.5956200000 - 0.0000000000 - 0.0000000000 - -1.0652760000 - 0.0794160000 - 0.0000000000 - 0.0000000000 - -12.1974600000 - 0.8040870000 - 0.0000000000 - 0.0000000000 - 15.6770640000 - -1.0721160000 - 0.0000000000 - 0.0000000000 - -6.3485910000 - 0.4467150000 - 0.0000000000 - 0.0000000000 - 0.8301660000 - -0.0595620000 - 0.0000000000 - 0.0000000000 - 2.9047360000 - -0.1786860000 - 0.0000000000 - 0.0000000000 - -3.7334640000 - 0.2382480000 - 0.0000000000 - 0.0000000000 - 1.5148280000 - -0.0992700000 - 0.0000000000 - 0.0000000000 - -0.1983520000 - 0.0132360000 - 0.0000000000 - 0.0000000000 - 250.0683410015 - -92.4700050005 - 11.1678750001 - -0.4467150000 - -333.7332960014 - 123.2933400005 - -14.8905000001 - 0.5956200000 - 139.1371040004 - -51.3722250002 - 6.2043750000 - -0.2481750000 - -18.5588640001 - 6.8496300000 - -0.8272500000 - 0.0330900000 - -601.8581040035 - 221.9280120013 - -26.8029000002 - 1.0721160000 - 803.2313520033 - -295.9040160012 - 35.7372000001 - -1.4294880000 - -334.9244220011 - 123.2933400004 - -14.8905000000 - 0.5956200000 - 44.6783400002 - -16.4391120001 - 1.9854000000 - -0.0794160000 - 450.9566520023 - -166.4460090008 - 20.1021750001 - -0.8040870000 - -601.8617520020 - 221.9280120007 - -26.8029000001 - 1.0721160000 - 250.9592490006 - -92.4700050002 - 11.1678750000 - -0.4467150000 - -33.4775460001 - 12.3293340000 - -1.4890500000 - 0.0595620000 - -100.0184000003 - 36.9880020001 - -4.4671500000 - 0.1786860000 - 133.4973840001 - -49.3173360000 - 5.9562000000 - -0.2382480000 - -55.6646920000 - 20.5488900000 - -2.4817500000 - 0.0992700000 - 7.4255840000 - -2.7398520000 - 0.3309000000 - -0.0132360000 - 0.0000000000 - 0.0000000000 - 26.8260000000 - -17.8840000000 - 0.0000000000 - 0.0000000000 - -24.1434000000 - 16.0956000000 - 0.0000000000 - 0.0000000000 - 7.0418250000 - -4.6945500000 - 0.0000000000 - 0.0000000000 - -0.6706500000 - 0.4471000000 - 0.0000000000 - 0.0000000000 - -64.3824000000 - 42.9216000000 - 0.0000000000 - 0.0000000000 - 57.9441600000 - -38.6294400000 - 0.0000000000 - 0.0000000000 - -16.9003800000 - 11.2669200000 - 0.0000000000 - 0.0000000000 - 1.6095600000 - -1.0730400000 - 0.0000000000 - 0.0000000000 - 48.2868000000 - -32.1912000000 - 0.0000000000 - 0.0000000000 - -43.4581200000 - 28.9720800000 - 0.0000000000 - 0.0000000000 - 12.6752850000 - -8.4501900000 - 0.0000000000 - 0.0000000000 - -1.2071700000 - 0.8047800000 - 0.0000000000 - 0.0000000000 - -10.7304000000 - 7.1536000000 - 0.0000000000 - 0.0000000000 - 9.6573600000 - -6.4382400000 - 0.0000000000 - 0.0000000000 - -2.8167300000 - 1.8778200000 - 0.0000000000 - 0.0000000000 - 0.2682600000 - -0.1788400000 - 19.0795999999 - -24.3302399999 - 18.2476799999 - -4.0550400000 - -17.1716400000 - 21.8972159999 - -16.4229119999 - 3.6495360000 - 5.0083950000 - -6.3866880000 - 4.7900160000 - -1.0644480000 - -0.4769900000 - 0.6082560000 - -0.4561920000 - 0.1013760000 - 33.1656000001 - -131.1033600001 - 98.3275200001 - -21.8505600000 - -29.8490400000 - 117.9930240001 - -88.4947680001 - 19.6655040000 - 8.7059700000 - -34.4146320000 - 25.8109740000 - -5.7357720000 - -0.8291400000 - 3.2775840000 - -2.4581880000 - 0.5462640000 - -33.6504000000 - 119.3904000000 - -89.5428000000 - 19.8984000000 - 30.2853600000 - -107.4513600000 - 80.5885200000 - -17.9085600000 - -8.8332300000 - 31.3399800000 - -23.5049850000 - 5.2233300000 - 0.8412600000 - -2.9847600000 - 2.2385700000 - -0.4974600000 - 6.3724000000 - -23.8780800000 - 17.9085600000 - -3.9796800000 - -5.7351600000 - 21.4902720000 - -16.1177040000 - 3.5817120000 - 1.6727550000 - -6.2679960000 - 4.7009970000 - -1.0446660000 - -0.1593100000 - 0.5969520000 - -0.4477140000 - 0.0994920000 - -325.4336799995 - 432.5183999994 - -180.2159999997 - 24.0288000000 - 292.8903119996 - -389.2665599994 - 162.1943999997 - -21.6259200000 - -85.4263409999 - 113.5360799998 - -47.3066999999 - 6.3075600000 - 8.1358420000 - -10.8129600000 - 4.5054000000 - -0.6007200000 - 662.2708799995 - -865.0367999993 - 360.4319999997 - -48.0576000000 - -596.0437919995 - 778.5331199994 - -324.3887999997 - 43.2518400000 - 173.8461059999 - -227.0721599998 - 94.6133999999 - -12.6151200000 - -16.5567720000 - 21.6259200000 - -9.0108000000 - 1.2014400000 - -414.3575999999 - 540.6479999999 - -225.2700000000 - 30.0360000000 - 372.9218399999 - -486.5831999999 - 202.7430000000 - -27.0324000000 - -108.7688700000 - 141.9201000000 - -59.1333750000 - 7.8844500000 - 10.3589400000 - -13.5162000000 - 5.6317500000 - -0.7509000000 - 82.5138400000 - -108.1296000000 - 45.0540000000 - -6.0072000000 - -74.2624560000 - 97.3166400000 - -40.5486000000 - 5.4064800000 - 21.6598830000 - -28.3840200000 - 11.8266750000 - -1.5768900000 - -2.0628460000 - 2.7032400000 - -1.1263500000 - 0.1501800000 - -1.0448800000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.9403920000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.2742810000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0261220000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 13.4932800000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -12.1439520000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 3.5419860000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.3373320000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -8.8716000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 7.9844400000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -2.3287950000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.2217900000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 1.4166400000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -1.2749760000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.3718680000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.0354160000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -1.0448800000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.9403920000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.2742810000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0261220000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 13.4932800000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -12.1439520000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 3.5419860000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.3373320000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -8.8716000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 7.9844400000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -2.3287950000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.2217900000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 1.4166400000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -1.2749760000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.3718680000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.0354160000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -1.0448800000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.9403920000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.2742810000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0261220000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 13.4932800000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -12.1439520000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 3.5419860000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.3373320000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -8.8716000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 7.9844400000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -2.3287950000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.2217900000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 1.4166400000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -1.2749760000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.3718680000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.0354160000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -1.0448800000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.9403920000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.2742810000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0261220000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 13.4932800000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -12.1439520000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 3.5419860000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.3373320000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -8.8716000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 7.9844400000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -2.3287950000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.2217900000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 1.4166400000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -1.2749760000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.3718680000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.0354160000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -1.0448800000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.9403920000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.2742810000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0261220000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 13.4932800000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -12.1439520000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 3.5419860000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.3373320000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -8.8716000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 7.9844400000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -2.3287950000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.2217900000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 1.4166400000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -1.2749760000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.3718680000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.0354160000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -1.0448800000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.9403920000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.2742810000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0261220000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 13.4932800000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -12.1439520000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 3.5419860000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.3373320000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -8.8716000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 7.9844400000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -2.3287950000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.2217900000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 1.4166400000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -1.2749760000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.3718680000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.0354160000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -10.3921350000 - 6.9280900000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 34.2564300000 - -22.8376200000 - 0.0000000000 - 0.0000000000 - -22.8376200000 - 15.2250800000 - 0.0000000000 - 0.0000000000 - 13.4565840000 - -8.9710560000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -43.7677020000 - 29.1784680000 - 0.0000000000 - 0.0000000000 - 29.1784680000 - -19.4523120000 - 0.0000000000 - 0.0000000000 - -5.6069100000 - 3.7379400000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 18.0593550000 - -12.0395700000 - 0.0000000000 - 0.0000000000 - -12.0395700000 - 8.0263800000 - 0.0000000000 - 0.0000000000 - 0.7475880000 - -0.4983920000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -2.3921640000 - 1.5947760000 - 0.0000000000 - 0.0000000000 - 1.5947760000 - -1.0631840000 - 0.6764050000 - -9.9370800000 - 7.4528100000 - -1.6561800000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -43.6827750000 - 132.2438040000 - -99.1828530000 - 22.0406340000 - 30.8739500000 - -92.3675760000 - 69.2756820000 - -15.3945960000 - -1.0350720000 - 13.2494400000 - -9.9370800000 - 2.2082400000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 56.1996360000 - -169.8932880000 - 127.4199660000 - -28.3155480000 - -39.7191240000 - 118.6686720000 - -89.0015040000 - 19.7781120000 - 0.4312800000 - -5.5206000000 - 4.1404500000 - -0.9201000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -23.1802650000 - 70.0801200000 - -52.5600900000 - 11.6800200000 - 16.3921350000 - -48.9727800000 - 36.7295850000 - -8.1621300000 - -0.0575040000 - 0.7360800000 - -0.5520600000 - 0.1226800000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 3.0697020000 - -9.2810160000 - 6.9607620000 - -1.5468360000 - -2.1716180000 - 6.4877040000 - -4.8657780000 - 1.0812840000 - 71.3096370000 - -95.0729040000 - 39.6137100000 - -5.2818280000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -135.3030030000 - 174.4733520000 - -72.6972300000 - 9.6929640000 - 80.7406620000 - -103.7004480000 - 43.2085200000 - -5.7611360000 - -91.2980160000 - 121.7306880000 - -50.7211200000 - 6.7628160000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 170.1614520000 - -219.3337440000 - 91.3890600000 - -12.1852080000 - -101.2763880000 - 130.0030560000 - -54.1679400000 - 7.2223920000 - 38.0408400000 - -50.7211200000 - 21.1338000000 - -2.8178400000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -70.9006050000 - 91.3890600000 - -38.0787750000 - 5.0771700000 - 42.1984950000 - -54.1679400000 - 22.5699750000 - -3.0093300000 - -5.0721120000 - 6.7628160000 - -2.8178400000 - 0.3757120000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 9.4534140000 - -12.1852080000 - 5.0771700000 - -0.6769560000 - -5.6264660000 - 7.2223920000 - -3.0093300000 - 0.4012440000 - 0.0049590000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -22.5906120000 - 16.9385580000 - -5.2448310000 - 0.5381640000 - 15.0604080000 - -11.2923720000 - 3.4965540000 - -0.3587760000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 29.8513080000 - -22.5847440000 - 6.9931080000 - -0.7175520000 - -19.9008720000 - 15.0564960000 - -4.6620720000 - 0.4783680000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -12.4380450000 - 9.4103100000 - -2.9137950000 - 0.2989800000 - 8.2920300000 - -6.2735400000 - 1.9425300000 - -0.1993200000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 1.6584060000 - -1.2547080000 - 0.3885060000 - -0.0398640000 - -1.1056040000 - 0.8364720000 - -0.2590040000 - 0.0265760000 - 0.0049590000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 132.0411960000 - -94.3696980000 - 21.4158330000 - -1.5863580000 - -88.0274640000 - 62.9131320000 - -14.2772220000 - 1.0575720000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -133.2586440000 - 96.4632240000 - -21.9477600000 - 1.6257600000 - 88.8390960000 - -64.3088160000 - 14.6318400000 - -1.0838400000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 44.7579870000 - -32.8522500000 - 7.4932290000 - -0.5550540000 - -29.8386580000 - 21.9015000000 - -4.9954860000 - 0.3700360000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -5.0107140000 - 3.7277880000 - -0.8522820000 - 0.0631320000 - 3.3404760000 - -2.4851920000 - 0.5681880000 - -0.0420880000 - 0.0049590000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000001 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -104.3640540001 - 53.3054520000 - -9.2855970000 - 0.5381640000 - 69.5760360000 - -35.5369680000 - 6.1903980000 - -0.3587760000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.0000000001 - 0.0000000001 - 0.0000000000 - 0.0000000000 - 139.1272560000 - -71.0739360000 - 12.3807960000 - -0.7175520000 - -92.7515040000 - 47.3826240000 - -8.2538640000 - 0.4783680000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -58.0308630000 - 29.6141400000 - -5.1586650000 - 0.2989800000 - 38.6872420000 - -19.7427600000 - 3.4391100000 - -0.1993200000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 7.7428860000 - -3.9485520000 - 0.6878220000 - -0.0398640000 - -5.1619240000 - 2.6323680000 - -0.4585480000 - 0.0265760000 - 0.0049590000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -2.5694100000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 1.7129400000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 3.4010640000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -2.2673760000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -1.4782830000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.9855220000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.2025420000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.1350280000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0049590000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -2.5694100000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 1.7129400000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 3.4010640000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -2.2673760000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -1.4782830000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.9855220000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.2025420000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.1350280000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0049590000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -2.5694100000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 1.7129400000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 3.4010640000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -2.2673760000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -1.4782830000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.9855220000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.2025420000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.1350280000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -32.6219250000 - 21.7479500000 - 0.0000000000 - 0.0000000000 - 80.7566400000 - -53.8377600000 - 0.0000000000 - 0.0000000000 - -60.5674800000 - 40.3783200000 - 0.0000000000 - 0.0000000000 - 13.4594400000 - -8.9729600000 - 0.0000000000 - 0.0000000000 - 42.1038000000 - -28.0692000000 - 0.0000000000 - 0.0000000000 - -103.7674800000 - 69.1783200000 - 0.0000000000 - 0.0000000000 - 77.8256100000 - -51.8837400000 - 0.0000000000 - 0.0000000000 - -17.2945800000 - 11.5297200000 - 0.0000000000 - 0.0000000000 - -17.3070000000 - 11.5380000000 - 0.0000000000 - 0.0000000000 - 42.5277000000 - -28.3518000000 - 0.0000000000 - 0.0000000000 - -31.8957750000 - 21.2638500000 - 0.0000000000 - 0.0000000000 - 7.0879500000 - -4.7253000000 - 0.0000000000 - 0.0000000000 - 2.2866000000 - -1.5244000000 - 0.0000000000 - 0.0000000000 - -5.6073600000 - 3.7382400000 - 0.0000000000 - 0.0000000000 - 4.2055200000 - -2.8036800000 - 0.0000000000 - 0.0000000000 - -0.9345600000 - 0.6230400000 - 24.9742400000 - -86.0357160000 - 64.5267870000 - -14.3392860000 - -95.7183600000 - 294.3293760000 - -220.7470320000 - 49.0548960000 - 74.8604400000 - -228.1190400000 - 171.0892800000 - -38.0198400000 - -16.2487400000 - 49.7645280000 - -37.3233960000 - 8.2940880000 - -32.3569800000 - 111.3397920000 - -83.5048440000 - 18.5566320000 - 123.2917200000 - -378.9141120000 - 284.1855840000 - -63.1523520000 - -96.4180800000 - 293.6638800000 - -220.2479100000 - 48.9439800000 - 20.9287800000 - -64.0647360000 - 48.0485520000 - -10.6774560000 - 13.1670750000 - -45.4465800000 - 34.0849350000 - -7.5744300000 - -50.4265500000 - 155.0458800000 - -116.2844100000 - 25.8409800000 - 39.4654500000 - -120.2337000000 - 90.1752750000 - -20.0389500000 - -8.5628250000 - 26.2211400000 - -19.6658550000 - 4.3701900000 - -1.7276100000 - 5.9755440000 - -4.4816580000 - 0.9959240000 - 6.6395400000 - -20.4207840000 - 15.3155880000 - -3.4034640000 - -5.1990600000 - 15.8421600000 - -11.8816200000 - 2.6403600000 - 1.1277100000 - -3.4541520000 - 2.5906140000 - -0.5756920000 - 4.9724480000 - -11.1558600000 - 4.6482750000 - -0.6197700000 - 74.0236080000 - -92.0985120001 - 38.3743800000 - -5.1165840000 - -84.3386520000 - 106.9192440000 - -44.5496850000 - 5.9399580000 - 22.0898920000 - -27.9648720000 - 11.6520300000 - -1.5536040000 - -1.2060360000 - 7.6658400000 - -3.1941000000 - 0.4258800000 - -109.7359920000 - 137.2152960000 - -57.1730400000 - 7.6230720000 - 119.3574960000 - -151.5697920000 - 63.1540800000 - -8.4205440000 - -30.8284200000 - 39.0886560000 - -16.2869400000 - 2.1715920000 - 0.5025150000 - -3.1941000000 - 1.3308750000 - -0.1774500000 - 45.7233300000 - -57.1730400000 - 23.8221000000 - -3.1762800000 - -49.7322900000 - 63.1540800000 - -26.3142000000 - 3.5085600000 - 12.8451750000 - -16.2869400000 - 6.7862250000 - -0.9048300000 - -0.0670020000 - 0.4258800000 - -0.1774500000 - 0.0236600000 - -6.0964440000 - 7.6230720000 - -3.1762800000 - 0.4235040000 - 6.6309720000 - -8.4205440000 - 3.5085600000 - -0.4678080000 - -1.7126900000 - 2.1715920000 - -0.9048300000 - 0.1206440000 - 40.8978920001 - -40.0066290000 - 11.9069730000 - -1.1642670000 - -115.8659880001 - 109.5667560001 - -32.7726000000 - 3.2247720000 - 86.4625650001 - -82.1750670001 - 24.5794500000 - -2.4185790000 - -19.0197140000 - 18.2611260000 - -5.4621000000 - 0.5374620000 - -54.5131080000 - 53.3421720000 - -15.8759640000 - 1.5523560000 - 154.2630960001 - -146.0890080001 - 43.6968000000 - -4.2996960000 - -115.1355600000 - 109.5667560000 - -32.7726000000 - 3.2247720000 - 25.3360080000 - -24.3481680000 - 7.2828000000 - -0.7166160000 - 22.7137950000 - -22.2259050000 - 6.6149850000 - -0.6468150000 - -64.2762900000 - 60.8704200000 - -18.2070000000 - 1.7915400000 - 47.9731500000 - -45.6528150000 - 13.6552500000 - -1.3436550000 - -10.5566700000 - 10.1450700000 - -3.0345000000 - 0.2985900000 - -3.0285060000 - 2.9634540000 - -0.8819980000 - 0.0862420000 - 8.5701720000 - -8.1160560000 - 2.4276000000 - -0.2388720000 - -6.3964200000 - 6.0870420000 - -1.8207000000 - 0.1791540000 - 1.4075560000 - -1.3526760000 - 0.4046000000 - -0.0398120000 - -186.7201720002 - 126.2729790001 - -28.5544440000 - 2.1151440000 - 554.1228120005 - -378.5509080003 - 85.6633320001 - -6.3454320000 - -416.0290350004 - 283.9131810002 - -64.2474990001 - 4.7590740000 - 92.6450860001 - -63.0918180001 - 14.2772220000 - -1.0575720000 - 191.5565880001 - -129.2132520001 - 29.2636800000 - -2.1676800000 - -566.7921360002 - 387.2823840002 - -87.7910400000 - 6.5030400000 - 425.6558640002 - -290.4617880001 - 65.8432800000 - -4.8772800000 - -94.8398640000 - 64.5470640000 - -14.6318400000 - 1.0838400000 - -65.4599810000 - 44.0511750000 - -9.9909720000 - 0.7400720000 - 193.0975980000 - -132.0046200000 - 29.9729160000 - -2.2202160000 - -145.0572660000 - 99.0034650000 - -22.4796870000 - 1.6651620000 - 32.3389780000 - -22.0007700000 - 4.9954860000 - -0.3700360000 - 7.4519740000 - -5.0034740000 - 1.1363760000 - -0.0841760000 - -21.9182760000 - 14.9905680000 - -3.4091280000 - 0.2525280000 - 16.4699160000 - -11.2429260000 - 2.5568460000 - -0.1893960000 - -3.6738520000 - 2.4984280000 - -0.5681880000 - 0.0420880000 - 128.4868280000 - -70.6272210000 - 12.3807960000 - -0.7175520000 - -391.4981880000 - 212.1496920000 - -37.1423880000 - 2.1526560000 - 293.1867150000 - -159.1122690000 - 27.8567910000 - -1.6144920000 - -64.9584140000 - 35.3582820000 - -6.1903980000 - 0.3587760000 - -171.6246120001 - 94.1696280001 - -16.5077280000 - 0.9567360000 - 522.7514640001 - -282.8662560001 - 49.5231840000 - -2.8702080000 - -391.5018360000 - 212.1496920000 - -37.1423880000 - 2.1526560000 - 86.7507360000 - -47.1443760000 - 8.2538640000 - -0.4783680000 - 71.5918190001 - -39.2373450000 - 6.8782200000 - -0.3986400000 - -218.0578020001 - 117.8609400000 - -20.6346600000 - 1.1959200000 - 163.3092840000 - -88.3957050000 - 15.4759950000 - -0.8969400000 - -36.1869220000 - 19.6434900000 - -3.4391100000 - 0.1993200000 - -9.5528260000 - 5.2316460000 - -0.9170960000 - 0.0531520000 - 29.0961240000 - -15.7147920000 - 2.7512880000 - -0.1594560000 - -21.7908840000 - 11.7860940000 - -2.0634660000 - 0.1195920000 - 4.8285480000 - -2.6191320000 - 0.4585480000 - -0.0265760000 - -7.3122640000 - 0.4807350000 - -0.0052650000 - 0.0002700000 - 15.8553480000 - -1.1537640000 - 0.0126360000 - -0.0006480000 - -12.3284370000 - 0.8653230000 - -0.0094770000 - 0.0004860000 - 2.9338420000 - -0.1922940000 - 0.0021060000 - -0.0001080000 - 9.4408440000 - -0.6409800000 - 0.0070200000 - -0.0003600000 - -20.3865840000 - 1.5383520000 - -0.0168480000 - 0.0008640000 - 15.8517000000 - -1.1537640000 - 0.0126360000 - -0.0006480000 - -3.7722720000 - 0.2563920000 - -0.0028080000 - 0.0001440000 - -3.8521210000 - 0.2670750000 - -0.0029250000 - 0.0001500000 - 8.2497180000 - -0.6409800000 - 0.0070200000 - -0.0003600000 - -6.4213560000 - 0.4807350000 - -0.0052650000 - 0.0002700000 - 1.5309980000 - -0.1068300000 - 0.0011700000 - -0.0000600000 - 0.5063660000 - -0.0356100000 - 0.0003900000 - -0.0000200000 - -1.0782120000 - 0.0854640000 - -0.0009360000 - 0.0000480000 - 0.8398680000 - -0.0640980000 - 0.0007020000 - -0.0000360000 - -0.2005080000 - 0.0142440000 - -0.0001560000 - 0.0000080000 - -7.2394990000 - 0.4467150000 - 0.0000000000 - 0.0000000000 - 15.6807120000 - -1.0721160000 - 0.0000000000 - 0.0000000000 - -12.1974600000 - 0.8040870000 - 0.0000000000 - 0.0000000000 - 2.9047360000 - -0.1786860000 - 0.0000000000 - 0.0000000000 - 9.3438240000 - -0.5956200000 - 0.0000000000 - 0.0000000000 - -20.1537360000 - 1.4294880000 - 0.0000000000 - 0.0000000000 - 15.6770640000 - -1.0721160000 - 0.0000000000 - 0.0000000000 - -3.7334640000 - 0.2382480000 - 0.0000000000 - 0.0000000000 - -3.8116960000 - 0.2481750000 - 0.0000000000 - 0.0000000000 - 8.1526980000 - -0.5956200000 - 0.0000000000 - 0.0000000000 - -6.3485910000 - 0.4467150000 - 0.0000000000 - 0.0000000000 - 1.5148280000 - -0.0992700000 - 0.0000000000 - 0.0000000000 - 0.5009760000 - -0.0330900000 - 0.0000000000 - 0.0000000000 - -1.0652760000 - 0.0794160000 - 0.0000000000 - 0.0000000000 - 0.8301660000 - -0.0595620000 - 0.0000000000 - 0.0000000000 - -0.1983520000 - 0.0132360000 - 0.0000000000 - 0.0000000000 - 250.0683409981 - -92.4700049993 - 11.1678749999 - -0.4467150000 - -601.8581039954 - 221.9280119984 - -26.8028999998 - 1.0721160000 - 450.9566519965 - -166.4460089988 - 20.1021749999 - -0.8040870000 - -100.0183999992 - 36.9880019997 - -4.4671500000 - 0.1786860000 - -333.7332959987 - 123.2933399995 - -14.8904999999 - 0.5956200000 - 803.2313519972 - -295.9040159990 - 35.7371999999 - -1.4294880000 - -601.8617519980 - 221.9280119993 - -26.8028999999 - 1.0721160000 - 133.4973839995 - -49.3173359998 - 5.9562000000 - -0.2382480000 - 139.1371039998 - -51.3722249999 - 6.2043750000 - -0.2481750000 - -334.9244219997 - 123.2933399999 - -14.8905000000 - 0.5956200000 - 250.9592489999 - -92.4700050000 - 11.1678750000 - -0.4467150000 - -55.6646920000 - 20.5488900000 - -2.4817500000 - 0.0992700000 - -18.5588640000 - 6.8496300000 - -0.8272500000 - 0.0330900000 - 44.6783400000 - -16.4391120000 - 1.9854000000 - -0.0794160000 - -33.4775460000 - 12.3293340000 - -1.4890500000 - 0.0595620000 - 7.4255840000 - -2.7398520000 - 0.3309000000 - -0.0132360000 - 0.0000000000 - 0.0000000000 - 204.6833550000 - -136.4555700000 - 0.0000000000 - 0.0000000000 - -270.4968000000 - 180.3312000000 - 0.0000000000 - 0.0000000000 - 112.7070000000 - -75.1380000000 - 0.0000000000 - 0.0000000000 - -15.0276000000 - 10.0184000000 - 0.0000000000 - 0.0000000000 - -270.4968000000 - 180.3312000000 - 0.0000000000 - 0.0000000000 - 357.4432800000 - -238.2955200000 - 0.0000000000 - 0.0000000000 - -148.9347000000 - 99.2898000000 - 0.0000000000 - 0.0000000000 - 19.8579600000 - -13.2386400000 - 0.0000000000 - 0.0000000000 - 112.7070000000 - -75.1380000000 - 0.0000000000 - 0.0000000000 - -148.9347000000 - 99.2898000000 - 0.0000000000 - 0.0000000000 - 62.0561250000 - -41.3707500000 - 0.0000000000 - 0.0000000000 - -8.2741500000 - 5.5161000000 - 0.0000000000 - 0.0000000000 - -15.0276000000 - 10.0184000000 - 0.0000000000 - 0.0000000000 - 19.8579600000 - -13.2386400000 - 0.0000000000 - 0.0000000000 - -8.2741500000 - 5.5161000000 - 0.0000000000 - 0.0000000000 - 1.1032200000 - -0.7354800000 - -378.3990599998 - 1071.9044279997 - -803.9283209998 - 178.6507379999 - 471.6311399998 - -1348.3121759996 - 1011.2341319997 - -224.7186959999 - -189.9590849999 - 546.0674039998 - -409.5505529999 - 91.0112340000 - 24.7453100000 - -71.4108240000 - 53.5581180000 - -11.9018040000 - 471.6311399999 - -1348.3121759998 - 1011.2341319999 - -224.7186960000 - -587.4703199999 - 1695.8833919998 - -1271.9125439998 - 282.6472320000 - 236.3528700000 - -686.3946479999 - 514.7959859999 - -114.3991080000 - -30.7647000000 - 89.7216480000 - -67.2912360000 - 14.9536080000 - -189.9590850000 - 546.0674040000 - -409.5505530000 - 91.0112340000 - 236.3528700000 - -686.3946480000 - 514.7959860000 - -114.3991080000 - -94.9693500000 - 277.5713400000 - -208.1785050000 - 46.2618900000 - 12.3504900000 - -36.2604960000 - 27.1953720000 - -6.0434160000 - 24.7453100000 - -71.4108240000 - 53.5581180000 - -11.9018040000 - -30.7647000000 - 89.7216480000 - -67.2912360000 - 14.9536080000 - 12.3504900000 - -36.2604960000 - 27.1953720000 - -6.0434160000 - -1.6051200000 - 4.7348640000 - -3.5511480000 - 0.7891440000 - 159.6098520000 - -232.3381320000 - 96.8075550000 - -12.9076740000 - -218.7495000001 - 309.7841760001 - -129.0767400000 - 17.2102320000 - 92.4564030000 - -129.0767400000 - 53.7819750000 - -7.1709300000 - -12.4440340000 - 17.2102320000 - -7.1709300000 - 0.9561240000 - -218.7495000000 - 309.7841760000 - -129.0767400000 - 17.2102320000 - 299.0818080000 - -413.0455680000 - 172.1023200000 - -22.9469760000 - -126.3027060000 - 172.1023200000 - -71.7093000000 - 9.5612400000 - 16.9901640000 - -22.9469760000 - 9.5612400000 - -1.2748320000 - 92.4564030000 - -129.0767400000 - 53.7819750000 - -7.1709300000 - -126.3027060000 - 172.1023200000 - -71.7093000000 - 9.5612400000 - 53.3283300000 - -71.7093000000 - 29.8788750000 - -3.9838500000 - -7.1728620000 - 9.5612400000 - -3.9838500000 - 0.5311800000 - -12.4440340000 - 17.2102320000 - -7.1709300000 - 0.9561240000 - 16.9901640000 - -22.9469760000 - 9.5612400000 - -1.2748320000 - -7.1728620000 - 9.5612400000 - -3.9838500000 - 0.5311800000 - 0.9647040000 - -1.2748320000 - 0.5311800000 - -0.0708240000 - -123.1954919996 - 94.0781789996 - -26.5348709999 - 2.4122610000 - 158.3242919995 - -125.4375719995 - 35.3798279999 - -3.2163480000 - -64.6576769998 - 52.2656549998 - -14.7415949999 - 1.3401450000 - 8.5045100000 - -6.9687540000 - 1.9655460000 - -0.1786860000 - 158.3242919998 - -125.4375719998 - 35.3798280000 - -3.2163480000 - -203.6832479998 - 167.2500959998 - -47.1731039999 - 4.2884640000 - 83.1827339999 - -69.6875399999 - 19.6554600000 - -1.7868600000 - -10.9412280000 - 9.2916720000 - -2.6207280000 - 0.2382480000 - -64.6576770000 - 52.2656550000 - -14.7415950000 - 1.3401450000 - 83.1827340000 - -69.6875400000 - 19.6554600000 - -1.7868600000 - -33.9572700000 - 29.0364750000 - -8.1897750000 - 0.7445250000 - 4.4652180000 - -3.8715300000 - 1.0919700000 - -0.0992700000 - 8.5045100000 - -6.9687540000 - 1.9655460000 - -0.1786860000 - -10.9412280000 - 9.2916720000 - -2.6207280000 - 0.2382480000 - 4.4652180000 - -3.8715300000 - 1.0919700000 - -0.0992700000 - -0.5870400000 - 0.5162040000 - -0.1455960000 - 0.0132360000 - -7.4069640000 - -2.4122610000 - 0.0000000000 - 0.0000000000 - 3.9395880000 - 3.2163480000 - 0.0000000000 - 0.0000000000 - -0.3307170000 - -1.3401450000 - 0.0000000000 - 0.0000000000 - -0.0724180000 - 0.1786860000 - 0.0000000000 - 0.0000000000 - 3.9395880000 - 3.2163480000 - 0.0000000000 - 0.0000000000 - 2.1630240000 - -4.2884640000 - 0.0000000000 - 0.0000000000 - -2.5865460000 - 1.7868600000 - 0.0000000000 - 0.0000000000 - 0.4946760000 - -0.2382480000 - 0.0000000000 - 0.0000000000 - -0.3307170000 - -1.3401450000 - 0.0000000000 - 0.0000000000 - -2.5865460000 - 1.7868600000 - 0.0000000000 - 0.0000000000 - 1.7799300000 - -0.7445250000 - 0.0000000000 - 0.0000000000 - -0.2997420000 - 0.0992700000 - 0.0000000000 - 0.0000000000 - -0.0724180000 - 0.1786860000 - 0.0000000000 - 0.0000000000 - 0.4946760000 - -0.2382480000 - 0.0000000000 - 0.0000000000 - -0.2997420000 - 0.0992700000 - 0.0000000000 - 0.0000000000 - 0.0482880000 - -0.0132360000 - 0.0000000000 - 0.0000000000 - -7.4069640000 - -2.4122610000 - 0.0000000000 - 0.0000000000 - 3.9395880000 - 3.2163480000 - 0.0000000000 - 0.0000000000 - -0.3307170000 - -1.3401450000 - 0.0000000000 - 0.0000000000 - -0.0724180000 - 0.1786860000 - 0.0000000000 - 0.0000000000 - 3.9395880000 - 3.2163480000 - 0.0000000000 - 0.0000000000 - 2.1630240000 - -4.2884640000 - 0.0000000000 - 0.0000000000 - -2.5865460000 - 1.7868600000 - 0.0000000000 - 0.0000000000 - 0.4946760000 - -0.2382480000 - 0.0000000000 - 0.0000000000 - -0.3307170000 - -1.3401450000 - 0.0000000000 - 0.0000000000 - -2.5865460000 - 1.7868600000 - 0.0000000000 - 0.0000000000 - 1.7799300000 - -0.7445250000 - 0.0000000000 - 0.0000000000 - -0.2997420000 - 0.0992700000 - 0.0000000000 - 0.0000000000 - -0.0724180000 - 0.1786860000 - 0.0000000000 - 0.0000000000 - 0.4946760000 - -0.2382480000 - 0.0000000000 - 0.0000000000 - -0.2997420000 - 0.0992700000 - 0.0000000000 - 0.0000000000 - 0.0482880000 - -0.0132360000 - 0.0000000000 - 0.0000000000 - -7.0133040000 - -2.5959690000 - 0.0284310000 - -0.0014580000 - 3.4147080000 - 3.4612920000 - -0.0379080000 - 0.0019440000 - -0.1120170000 - -1.4422050000 - 0.0157950000 - -0.0008100000 - -0.1015780000 - 0.1922940000 - -0.0021060000 - 0.0001080000 - 3.4147080000 - 3.4612920000 - -0.0379080000 - 0.0019440000 - 2.8628640000 - -4.6150560000 - 0.0505440000 - -0.0025920000 - -2.8781460000 - 1.9229400000 - -0.0210600000 - 0.0010800000 - 0.5335560000 - -0.2563920000 - 0.0028080000 - -0.0001440000 - -0.1120170000 - -1.4422050000 - 0.0157950000 - -0.0008100000 - -2.8781460000 - 1.9229400000 - -0.0210600000 - 0.0010800000 - 1.9014300000 - -0.8012250000 - 0.0087750000 - -0.0004500000 - -0.3159420000 - 0.1068300000 - -0.0011700000 - 0.0000600000 - -0.1015780000 - 0.1922940000 - -0.0021060000 - 0.0001080000 - 0.5335560000 - -0.2563920000 - 0.0028080000 - -0.0001440000 - -0.3159420000 - 0.1068300000 - -0.0011700000 - 0.0000600000 - 0.0504480000 - -0.0142440000 - 0.0001560000 - -0.0000080000 - -7.4062350000 - -2.4122610000 - 0.0000000000 - 0.0000000000 - 3.9386160000 - 3.2163480000 - 0.0000000000 - 0.0000000000 - -0.3303120000 - -1.3401450000 - 0.0000000000 - 0.0000000000 - -0.0724720000 - 0.1786860000 - 0.0000000000 - 0.0000000000 - 3.9386160000 - 3.2163480000 - 0.0000000000 - 0.0000000000 - 2.1643200000 - -4.2884640000 - 0.0000000000 - 0.0000000000 - -2.5870860000 - 1.7868600000 - 0.0000000000 - 0.0000000000 - 0.4947480000 - -0.2382480000 - 0.0000000000 - 0.0000000000 - -0.3303120000 - -1.3401450000 - 0.0000000000 - 0.0000000000 - -2.5870860000 - 1.7868600000 - 0.0000000000 - 0.0000000000 - 1.7801550000 - -0.7445250000 - 0.0000000000 - 0.0000000000 - -0.2997720000 - 0.0992700000 - 0.0000000000 - 0.0000000000 - -0.0724720000 - 0.1786860000 - 0.0000000000 - 0.0000000000 - 0.4947480000 - -0.2382480000 - 0.0000000000 - 0.0000000000 - -0.2997720000 - 0.0992700000 - 0.0000000000 - 0.0000000000 - 0.0482920000 - -0.0132360000 - 0.0000000000 - 0.0000000000 - -1396.8685710143 - 499.3380270052 - -60.3065250006 - 2.4122610000 - 1856.5550640177 - -665.7840360064 - 80.4087000008 - -3.2163480000 - -772.2538320071 - 277.4100150026 - -33.5036250003 - 1.3401450000 - 102.8506640009 - -36.9880020003 - 4.4671500000 - -0.1786860000 - 1856.5550640090 - -665.7840360032 - 80.4087000004 - -3.2163480000 - -2467.9909440112 - 887.7120480040 - -107.2116000005 - 4.2884640000 - 1026.6442740045 - -369.8800200016 - 44.6715000002 - -1.7868600000 - -136.7361000006 - 49.3173360002 - -5.9562000000 - 0.2382480000 - -772.2538320009 - 277.4100150003 - -33.5036250000 - 1.3401450000 - 1026.6442740011 - -369.8800200004 - 44.6715000000 - -1.7868600000 - -427.0662450005 - 154.1166750002 - -18.6131250000 - 0.7445250000 - 56.8797480001 - -20.5488900000 - 2.4817500000 - -0.0992700000 - 102.8506640000 - -36.9880020000 - 4.4671500000 - -0.1786860000 - -136.7361000000 - 49.3173360000 - -5.9562000000 - 0.2382480000 - 56.8797480000 - -20.5488900000 - 2.4817500000 - -0.0992700000 - -7.5756440000 - 2.7398520000 - -0.3309000000 - 0.0132360000 - 0.0000000000 - 0.0000000000 - -144.8604000000 - 96.5736000000 - 0.0000000000 - 0.0000000000 - 130.3743600000 - -86.9162400000 - 0.0000000000 - 0.0000000000 - -38.0258550000 - 25.3505700000 - 0.0000000000 - 0.0000000000 - 3.6215100000 - -2.4143400000 - 0.0000000000 - 0.0000000000 - 193.1472000000 - -128.7648000000 - 0.0000000000 - 0.0000000000 - -173.8324800000 - 115.8883200000 - 0.0000000000 - 0.0000000000 - 50.7011400000 - -33.8007600000 - 0.0000000000 - 0.0000000000 - -4.8286800000 - 3.2191200000 - 0.0000000000 - 0.0000000000 - -80.4780000000 - 53.6520000000 - 0.0000000000 - 0.0000000000 - 72.4302000000 - -48.2868000000 - 0.0000000000 - 0.0000000000 - -21.1254750000 - 14.0836500000 - 0.0000000000 - 0.0000000000 - 2.0119500000 - -1.3413000000 - 0.0000000000 - 0.0000000000 - 10.7304000000 - -7.1536000000 - 0.0000000000 - 0.0000000000 - -9.6573600000 - 6.4382400000 - 0.0000000000 - 0.0000000000 - 2.8167300000 - -1.8778200000 - 0.0000000000 - 0.0000000000 - -0.2682600000 - 0.1788400000 - 401.1227999998 - -1078.5830399996 - 808.9372799997 - -179.7638399999 - -361.0105199999 - 970.7247359997 - -728.0435519998 - 161.7874559999 - 105.2947350000 - -283.1280479999 - 212.3460359999 - -47.1880080000 - -10.0280700000 - 26.9645760000 - -20.2234320000 - 4.4940960000 - -459.9287999999 - 1258.3468799998 - -943.7601599999 - 209.7244800000 - 413.9359199999 - -1132.5121919998 - 849.3841439999 - -188.7520320000 - -120.7313100000 - 330.3160559999 - -247.7370420000 - 55.0526760000 - 11.4982200000 - -31.4586720000 - 23.5940040000 - -5.2431120000 - 172.9116000000 - -479.3702400000 - 359.5276800000 - -79.8950400000 - -155.6204400000 - 431.4332160000 - -323.5749120000 - 71.9055360000 - 45.3892950000 - -125.8346880000 - 94.3760160000 - -20.9724480000 - -4.3227900000 - 11.9842560000 - -8.9881920000 - 1.9973760000 - -21.3904000000 - 59.9212800000 - -44.9409600000 - 9.9868800000 - 19.2513600000 - -53.9291520000 - 40.4468640000 - -8.9881920000 - -5.6149800000 - 15.7293360000 - -11.7970020000 - 2.6215560000 - 0.5347600000 - -1.4980320000 - 1.1235240000 - -0.2496720000 - 41.5951200000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -37.4356080000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 10.9187190000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -1.0398780000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -40.4798400000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 36.4318560000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -10.6259580000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 1.0119960000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 13.1215200000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -11.8093680000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 3.4443990000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.3280380000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -1.4166400000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 1.2749760000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.3718680000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0354160000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 41.5951200000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -37.4356080000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 10.9187190000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -1.0398780000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -40.4798400000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 36.4318560000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -10.6259580000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 1.0119960000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 13.1215200000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -11.8093680000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 3.4443990000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.3280380000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -1.4166400000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 1.2749760000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.3718680000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0354160000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 41.5951200000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -37.4356080000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 10.9187190000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -1.0398780000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -40.4798400000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 36.4318560000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -10.6259580000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 1.0119960000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 13.1215200000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -11.8093680000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 3.4443990000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.3280380000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -1.4166400000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 1.2749760000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.3718680000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0354160000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 41.5951200000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -37.4356080000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 10.9187190000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -1.0398780000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -40.4798400000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 36.4318560000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -10.6259580000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 1.0119960000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 13.1215200000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -11.8093680000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 3.4443990000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.3280380000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -1.4166400000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 1.2749760000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.3718680000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0354160000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 41.5951200000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -37.4356080000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 10.9187190000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -1.0398780000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -40.4798400000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 36.4318560000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -10.6259580000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 1.0119960000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 13.1215200000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -11.8093680000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 3.4443990000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.3280380000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -1.4166400000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 1.2749760000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.3718680000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0354160000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 41.5951200000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -37.4356080000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 10.9187190000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -1.0398780000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -40.4798400000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 36.4318560000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -10.6259580000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 1.0119960000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 13.1215200000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -11.8093680000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 3.4443990000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.3280380000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -1.4166400000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 1.2749760000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.3718680000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0354160000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 41.5951200000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -37.4356080000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 10.9187190000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -1.0398780000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -40.4798400000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 36.4318560000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -10.6259580000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 1.0119960000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 13.1215200000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -11.8093680000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 3.4443990000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.3280380000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -1.4166400000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 1.2749760000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.3718680000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0354160000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 23.9757600000 - -15.9838400000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -71.9272800000 - 47.9515200000 - 0.0000000000 - 0.0000000000 - 47.9515200000 - -31.9676800000 - 0.0000000000 - 0.0000000000 - -21.5781840000 - 14.3854560000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 64.7345520000 - -43.1563680000 - 0.0000000000 - 0.0000000000 - -43.1563680000 - 28.7709120000 - 0.0000000000 - 0.0000000000 - 6.2936370000 - -4.1957580000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -18.8809110000 - 12.5872740000 - 0.0000000000 - 0.0000000000 - 12.5872740000 - -8.3915160000 - 0.0000000000 - 0.0000000000 - -0.5993940000 - 0.3995960000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 1.7981820000 - -1.1987880000 - 0.0000000000 - 0.0000000000 - -1.1987880000 - 0.7991920000 - 7.9919200000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 65.9438400000 - -215.8070400000 - 161.8552800000 - -35.9678400000 - -48.9685600000 - 155.8857600000 - -116.9143200000 - 25.9809600000 - -7.1927280000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -59.3494560000 - 194.2263360000 - -145.6697520000 - 32.3710560000 - 44.0717040000 - -140.2971840000 - 105.2228880000 - -23.3828640000 - 2.0978790000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 17.3102580000 - -56.6493480000 - 42.4870110000 - -9.4415580000 - -12.8542470000 - 40.9200120000 - -30.6900090000 - 6.8200020000 - -0.1997980000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -1.6485960000 - 5.3951760000 - -4.0463820000 - 0.8991960000 - 1.2242140000 - -3.8971440000 - 2.9228580000 - -0.6495240000 - -226.8900000000 - 301.9910400000 - -125.8296000000 - 16.7772800000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 614.5531200000 - -797.8435199999 - 332.4348000000 - -44.3246400000 - -382.6696800000 - 495.8524800000 - -206.6052000000 - 27.5473600000 - 204.2010000000 - -271.7919360000 - 113.2466400000 - -15.0995520000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -553.0978080000 - 718.0591680000 - -299.1913200000 - 39.8921760000 - 344.4027120000 - -446.2672320000 - 185.9446800000 - -24.7926240000 - -59.5586250000 - 79.2726480000 - -33.0302700000 - 4.4040360000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 161.3201940000 - -209.4339240000 - 87.2641350000 - -11.6352180000 - -100.4507910000 - 130.1612760000 - -54.2338650000 - 7.2311820000 - 5.6722500000 - -7.5497760000 - 3.1457400000 - -0.4194320000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -15.3638280000 - 19.9460880000 - -8.3108700000 - 1.1081160000 - 9.5667420000 - -12.3963120000 - 5.1651300000 - -0.6886840000 - -0.3967200000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 16.1704800000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -10.7803200000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.3570480000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -14.5534320000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 9.7022880000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.1041390000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 4.2447510000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -2.8298340000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0099180000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.4042620000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.2695080000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.3967200000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 16.1704800000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -10.7803200000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.3570480000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -14.5534320000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 9.7022880000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.1041390000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 4.2447510000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -2.8298340000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0099180000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.4042620000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.2695080000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.3967200000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 16.1704800000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -10.7803200000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.3570480000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -14.5534320000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 9.7022880000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.1041390000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 4.2447510000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -2.8298340000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0099180000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.4042620000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.2695080000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.3967200000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 16.1704800000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -10.7803200000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.3570480000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -14.5534320000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 9.7022880000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.1041390000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 4.2447510000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -2.8298340000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0099180000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.4042620000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.2695080000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.3967200000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 16.1704800000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -10.7803200000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.3570480000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -14.5534320000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 9.7022880000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.1041390000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 4.2447510000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -2.8298340000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0099180000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.4042620000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.2695080000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.3967200000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 16.1704800000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -10.7803200000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.3570480000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -14.5534320000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 9.7022880000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.1041390000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 4.2447510000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -2.8298340000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0099180000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.4042620000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.2695080000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 26.8260000000 - -17.8840000000 - 0.0000000000 - 0.0000000000 - -64.3824000000 - 42.9216000000 - 0.0000000000 - 0.0000000000 - 48.2868000000 - -32.1912000000 - 0.0000000000 - 0.0000000000 - -10.7304000000 - 7.1536000000 - 0.0000000000 - 0.0000000000 - -24.1434000000 - 16.0956000000 - 0.0000000000 - 0.0000000000 - 57.9441600000 - -38.6294400000 - 0.0000000000 - 0.0000000000 - -43.4581200000 - 28.9720800000 - 0.0000000000 - 0.0000000000 - 9.6573600000 - -6.4382400000 - 0.0000000000 - 0.0000000000 - 7.0418250000 - -4.6945500000 - 0.0000000000 - 0.0000000000 - -16.9003800000 - 11.2669200000 - 0.0000000000 - 0.0000000000 - 12.6752850000 - -8.4501900000 - 0.0000000000 - 0.0000000000 - -2.8167300000 - 1.8778200000 - 0.0000000000 - 0.0000000000 - -0.6706500000 - 0.4471000000 - 0.0000000000 - 0.0000000000 - 1.6095600000 - -1.0730400000 - 0.0000000000 - 0.0000000000 - -1.2071700000 - 0.8047800000 - 0.0000000000 - 0.0000000000 - 0.2682600000 - -0.1788400000 - 19.0796000000 - -24.3302400000 - 18.2476800000 - -4.0550400000 - 33.1656000000 - -131.1033600000 - 98.3275200000 - -21.8505600000 - -33.6504000000 - 119.3904000000 - -89.5428000000 - 19.8984000000 - 6.3724000000 - -23.8780800000 - 17.9085600000 - -3.9796800000 - -17.1716400000 - 21.8972160000 - -16.4229120000 - 3.6495360000 - -29.8490400000 - 117.9930240000 - -88.4947680000 - 19.6655040000 - 30.2853600000 - -107.4513600000 - 80.5885200000 - -17.9085600000 - -5.7351600000 - 21.4902720000 - -16.1177040000 - 3.5817120000 - 5.0083950000 - -6.3866880000 - 4.7900160000 - -1.0644480000 - 8.7059700000 - -34.4146320000 - 25.8109740000 - -5.7357720000 - -8.8332300000 - 31.3399800000 - -23.5049850000 - 5.2233300000 - 1.6727550000 - -6.2679960000 - 4.7009970000 - -1.0446660000 - -0.4769900000 - 0.6082560000 - -0.4561920000 - 0.1013760000 - -0.8291400000 - 3.2775840000 - -2.4581880000 - 0.5462640000 - 0.8412600000 - -2.9847600000 - 2.2385700000 - -0.4974600000 - -0.1593100000 - 0.5969520000 - -0.4477140000 - 0.0994920000 - -325.4336800000 - 432.5184000000 - -180.2160000000 - 24.0288000000 - 662.2708800000 - -865.0368000000 - 360.4320000000 - -48.0576000000 - -414.3576000000 - 540.6480000000 - -225.2700000000 - 30.0360000000 - 82.5138400000 - -108.1296000000 - 45.0540000000 - -6.0072000000 - 292.8903120000 - -389.2665600000 - 162.1944000000 - -21.6259200000 - -596.0437920000 - 778.5331200000 - -324.3888000000 - 43.2518400000 - 372.9218400000 - -486.5832000000 - 202.7430000000 - -27.0324000000 - -74.2624560000 - 97.3166400000 - -40.5486000000 - 5.4064800000 - -85.4263410000 - 113.5360800000 - -47.3067000000 - 6.3075600000 - 173.8461060000 - -227.0721600000 - 94.6134000000 - -12.6151200000 - -108.7688700000 - 141.9201000000 - -59.1333750000 - 7.8844500000 - 21.6598830000 - -28.3840200000 - 11.8266750000 - -1.5768900000 - 8.1358420000 - -10.8129600000 - 4.5054000000 - -0.6007200000 - -16.5567720000 - 21.6259200000 - -9.0108000000 - 1.2014400000 - 10.3589400000 - -13.5162000000 - 5.6317500000 - -0.7509000000 - -2.0628460000 - 2.7032400000 - -1.1263500000 - 0.1501800000 - -1.0448800000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 13.4932800000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -8.8716000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 1.4166400000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.9403920000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -12.1439520000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 7.9844400000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -1.2749760000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.2742810000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 3.5419860000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -2.3287950000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.3718680000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0261220000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.3373320000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.2217900000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.0354160000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -1.0448800000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 13.4932800000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -8.8716000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 1.4166400000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.9403920000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -12.1439520000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 7.9844400000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -1.2749760000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.2742810000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 3.5419860000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -2.3287950000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.3718680000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0261220000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.3373320000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.2217900000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.0354160000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -1.0448800000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 13.4932800000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -8.8716000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 1.4166400000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.9403920000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -12.1439520000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 7.9844400000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -1.2749760000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.2742810000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 3.5419860000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -2.3287950000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.3718680000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0261220000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.3373320000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.2217900000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.0354160000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -1.0448800000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 13.4932800000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -8.8716000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 1.4166400000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.9403920000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -12.1439520000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 7.9844400000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -1.2749760000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.2742810000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 3.5419860000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -2.3287950000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.3718680000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0261220000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.3373320000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.2217900000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.0354160000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -1.0448800000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 13.4932800000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -8.8716000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 1.4166400000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.9403920000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -12.1439520000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 7.9844400000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -1.2749760000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.2742810000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 3.5419860000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -2.3287950000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.3718680000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0261220000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.3373320000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.2217900000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.0354160000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -1.0448800000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 13.4932800000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -8.8716000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 1.4166400000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.9403920000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -12.1439520000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 7.9844400000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -1.2749760000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.2742810000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 3.5419860000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -2.3287950000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.3718680000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0261220000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.3373320000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.2217900000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.0354160000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -144.8604000000 - 96.5736000000 - 0.0000000000 - 0.0000000000 - 193.1472000000 - -128.7648000000 - 0.0000000000 - 0.0000000000 - -80.4780000000 - 53.6520000000 - 0.0000000000 - 0.0000000000 - 10.7304000000 - -7.1536000000 - 0.0000000000 - 0.0000000000 - 130.3743600000 - -86.9162400000 - 0.0000000000 - 0.0000000000 - -173.8324800000 - 115.8883200000 - 0.0000000000 - 0.0000000000 - 72.4302000000 - -48.2868000000 - 0.0000000000 - 0.0000000000 - -9.6573600000 - 6.4382400000 - 0.0000000000 - 0.0000000000 - -38.0258550000 - 25.3505700000 - 0.0000000000 - 0.0000000000 - 50.7011400000 - -33.8007600000 - 0.0000000000 - 0.0000000000 - -21.1254750000 - 14.0836500000 - 0.0000000000 - 0.0000000000 - 2.8167300000 - -1.8778200000 - 0.0000000000 - 0.0000000000 - 3.6215100000 - -2.4143400000 - 0.0000000000 - 0.0000000000 - -4.8286800000 - 3.2191200000 - 0.0000000000 - 0.0000000000 - 2.0119500000 - -1.3413000000 - 0.0000000000 - 0.0000000000 - -0.2682600000 - 0.1788400000 - 401.1228000000 - -1078.5830400001 - 808.9372800001 - -179.7638400000 - -459.9288000000 - 1258.3468800001 - -943.7601600001 - 209.7244800000 - 172.9116000000 - -479.3702400000 - 359.5276800000 - -79.8950400000 - -21.3904000000 - 59.9212800000 - -44.9409600000 - 9.9868800000 - -361.0105200000 - 970.7247360000 - -728.0435520000 - 161.7874560000 - 413.9359200000 - -1132.5121920000 - 849.3841440000 - -188.7520320000 - -155.6204400000 - 431.4332160000 - -323.5749120000 - 71.9055360000 - 19.2513600000 - -53.9291520000 - 40.4468640000 - -8.9881920000 - 105.2947350000 - -283.1280480000 - 212.3460360000 - -47.1880080000 - -120.7313100000 - 330.3160560000 - -247.7370420000 - 55.0526760000 - 45.3892950000 - -125.8346880000 - 94.3760160000 - -20.9724480000 - -5.6149800000 - 15.7293360000 - -11.7970020000 - 2.6215560000 - -10.0280700000 - 26.9645760000 - -20.2234320000 - 4.4940960000 - 11.4982200000 - -31.4586720000 - 23.5940040000 - -5.2431120000 - -4.3227900000 - 11.9842560000 - -8.9881920000 - 1.9973760000 - 0.5347600000 - -1.4980320000 - 1.1235240000 - -0.2496720000 - 41.5951200000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -40.4798400000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 13.1215200000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -1.4166400000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -37.4356080000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 36.4318560000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -11.8093680000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 1.2749760000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 10.9187190000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -10.6259580000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 3.4443990000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.3718680000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -1.0398780000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 1.0119960000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.3280380000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0354160000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 41.5951200000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -40.4798400000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 13.1215200000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -1.4166400000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -37.4356080000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 36.4318560000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -11.8093680000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 1.2749760000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 10.9187190000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -10.6259580000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 3.4443990000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.3718680000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -1.0398780000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 1.0119960000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.3280380000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0354160000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 41.5951200000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -40.4798400000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 13.1215200000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -1.4166400000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -37.4356080000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 36.4318560000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -11.8093680000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 1.2749760000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 10.9187190000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -10.6259580000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 3.4443990000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.3718680000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -1.0398780000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 1.0119960000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.3280380000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0354160000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 41.5951200000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -40.4798400000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 13.1215200000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -1.4166400000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -37.4356080000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 36.4318560000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -11.8093680000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 1.2749760000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 10.9187190000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -10.6259580000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 3.4443990000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.3718680000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -1.0398780000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 1.0119960000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.3280380000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0354160000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 41.5951200000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -40.4798400000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 13.1215200000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -1.4166400000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -37.4356080000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 36.4318560000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -11.8093680000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 1.2749760000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 10.9187190000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -10.6259580000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 3.4443990000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.3718680000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -1.0398780000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 1.0119960000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.3280380000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0354160000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 41.5951200000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -40.4798400000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 13.1215200000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -1.4166400000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -37.4356080000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 36.4318560000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -11.8093680000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 1.2749760000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 10.9187190000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -10.6259580000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 3.4443990000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.3718680000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -1.0398780000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 1.0119960000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.3280380000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0354160000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 41.5951200000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -40.4798400000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 13.1215200000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -1.4166400000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -37.4356080000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 36.4318560000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -11.8093680000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 1.2749760000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 10.9187190000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -10.6259580000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 3.4443990000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.3718680000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -1.0398780000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 1.0119960000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.3280380000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0354160000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -# piCH - -6 -0.0 -4.0 -0.0 -4.0 -0.0 -9.0 - - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -1.3500000000 - 0.9000000000 - 0.0000000000 - 0.0000000000 - 0.9000000000 - -0.6000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.9000000000 - -0.6000000000 - 0.0000000000 - 0.0000000000 - -0.6000000000 - 0.4000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.4500000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.3000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.3000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.2000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -63.4500000000 - 81.0000000000 - -33.7500000000 - 4.5000000000 - 42.3000000000 - -54.0000000000 - 22.5000000000 - -3.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 42.3000000000 - -54.0000000000 - 22.5000000000 - -3.0000000000 - -28.2000000000 - 36.0000000000 - -15.0000000000 - 2.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 179.5500000000 - -162.0000000000 - 47.2500000000 - -4.5000000000 - -119.7000000000 - 108.0000000000 - -31.5000000000 - 3.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -119.7000000000 - 108.0000000000 - -31.5000000000 - 3.0000000000 - 79.8000000000 - -72.0000000000 - 21.0000000000 - -2.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.4500000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.3000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.3000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.2000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.4500000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.3000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.3000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.2000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.4500000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.3000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.3000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.2000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.4500000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.3000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.3000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.2000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.4500000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.3000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.3000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.2000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 1.8000000000 - -1.2000000000 - 0.0000000000 - 0.0000000000 - -5.4000000000 - 3.6000000000 - 0.0000000000 - 0.0000000000 - 4.0500000000 - -2.7000000000 - 0.0000000000 - 0.0000000000 - -0.9000000000 - 0.6000000000 - 0.0000000000 - 0.0000000000 - -1.2000000000 - 0.8000000000 - 0.0000000000 - 0.0000000000 - 3.6000000000 - -2.4000000000 - 0.0000000000 - 0.0000000000 - -2.7000000000 - 1.8000000000 - 0.0000000000 - 0.0000000000 - 0.6000000000 - -0.4000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -18.1500000000 - 45.0000000000 - -33.7500000000 - 7.5000000000 - 43.2000000000 - -108.0000000000 - 81.0000000000 - -18.0000000000 - -32.4000000000 - 81.0000000000 - -60.7500000000 - 13.5000000000 - 7.2000000000 - -18.0000000000 - 13.5000000000 - -3.0000000000 - 12.1000000000 - -30.0000000000 - 22.5000000000 - -5.0000000000 - -28.8000000000 - 72.0000000000 - -54.0000000000 - 12.0000000000 - 21.6000000000 - -54.0000000000 - 40.5000000000 - -9.0000000000 - -4.8000000000 - 12.0000000000 - -9.0000000000 - 2.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 80.8500000000 - -108.0000000000 - 45.0000000000 - -6.0000000000 - -244.8000000000 - 324.0000000000 - -135.0000000000 - 18.0000000000 - 183.6000000000 - -243.0000000000 - 101.2500000000 - -13.5000000000 - -40.8000000000 - 54.0000000000 - -22.5000000000 - 3.0000000000 - -53.9000000000 - 72.0000000000 - -30.0000000000 - 4.0000000000 - 163.2000000000 - -216.0000000000 - 90.0000000000 - -12.0000000000 - -122.4000000000 - 162.0000000000 - -67.5000000000 - 9.0000000000 - 27.2000000000 - -36.0000000000 - 15.0000000000 - -2.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 60.6000000000 - -54.0000000000 - 15.7500000000 - -1.5000000000 - -1.8000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 1.3500000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.3000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -40.4000000000 - 36.0000000000 - -10.5000000000 - 1.0000000000 - 1.2000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.9000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.2000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -3.9811200000 - 2.7144000000 - -0.6107400000 - 0.0452400000 - 9.5546880000 - -6.5145600000 - 1.4657760000 - -0.1085760000 - -7.1660160000 - 4.8859200000 - -1.0993320000 - 0.0814320000 - 1.5924480000 - -1.0857600000 - 0.2442960000 - -0.0180960000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 12.5433600000 - -8.1432000000 - 1.8322200000 - -0.1357200000 - -30.4640640000 - 19.5436800000 - -4.3973280000 - 0.3257280000 - 22.8480480000 - -14.6577600000 - 3.2979960000 - -0.2442960000 - -5.0773440000 - 3.2572800000 - -0.7328880000 - 0.0542880000 - -8.3622400000 - 5.4288000000 - -1.2214800000 - 0.0904800000 - 20.3093760000 - -13.0291200000 - 2.9315520000 - -0.2171520000 - -15.2320320000 - 9.7718400000 - -2.1986640000 - 0.1628640000 - 3.3848960000 - -2.1715200000 - 0.4885920000 - -0.0361920000 - -0.0226200000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0542880000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.0407160000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0090480000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.6678600000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -1.9628640000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 1.4721480000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.3271440000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.4452400000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 1.3085760000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.9814320000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.2180960000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.0226200000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0542880000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.0407160000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0090480000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.6678600000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -1.9628640000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 1.4721480000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.3271440000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.4452400000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 1.3085760000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.9814320000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.2180960000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.0226200000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0542880000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.0407160000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0090480000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.6678600000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -1.9628640000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 1.4721480000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.3271440000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.4452400000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 1.3085760000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.9814320000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.2180960000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.0226200000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0542880000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.0407160000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0090480000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.6678600000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -1.9628640000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 1.4721480000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.3271440000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.4452400000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 1.3085760000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.9814320000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.2180960000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -25.2000000000 - 16.8000000000 - 0.0000000000 - 0.0000000000 - 32.4000000000 - -21.6000000000 - 0.0000000000 - 0.0000000000 - -13.5000000000 - 9.0000000000 - 0.0000000000 - 0.0000000000 - 1.8000000000 - -1.2000000000 - 0.0000000000 - 0.0000000000 - 16.8000000000 - -11.2000000000 - 0.0000000000 - 0.0000000000 - -21.6000000000 - 14.4000000000 - 0.0000000000 - 0.0000000000 - 9.0000000000 - -6.0000000000 - 0.0000000000 - 0.0000000000 - -1.2000000000 - 0.8000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 82.3500000000 - -217.8000000000 - 163.3500000000 - -36.3000000000 - -110.7000000000 - 291.6000000000 - -218.7000000000 - 48.6000000000 - 46.1250000000 - -121.5000000000 - 91.1250000000 - -20.2500000000 - -6.1500000000 - 16.2000000000 - -12.1500000000 - 2.7000000000 - -54.9000000000 - 145.2000000000 - -108.9000000000 - 24.2000000000 - 73.8000000000 - -194.4000000000 - 145.8000000000 - -32.4000000000 - -30.7500000000 - 81.0000000000 - -60.7500000000 - 13.5000000000 - 4.1000000000 - -10.8000000000 - 8.1000000000 - -1.8000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 9.7500000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -13.5000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 5.6250000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.7500000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -6.5000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 9.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -3.7500000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.5000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.0000000007 - 0.0000000007 - -0.0000000002 - 0.0000000000 - 0.0000000010 - -0.0000000009 - 0.0000000003 - 0.0000000000 - -0.0000000004 - 0.0000000004 - -0.0000000001 - 0.0000000000 - 0.0000000001 - -0.0000000001 - 0.0000000000 - 0.0000000000 - -1460.3999999993 - 1306.7999999994 - -381.1499999998 - 36.3000000000 - 1954.7999999992 - -1749.5999999992 - 510.2999999998 - -48.6000000000 - -814.4999999997 - 728.9999999997 - -212.6249999999 - 20.2500000000 - 108.6000000000 - -97.2000000000 - 28.3500000000 - -2.7000000000 - 973.6000000000 - -871.2000000000 - 254.1000000000 - -24.2000000000 - -1303.2000000000 - 1166.4000000000 - -340.2000000000 - 32.4000000000 - 543.0000000000 - -486.0000000000 - 141.7500000000 - -13.5000000000 - -72.4000000000 - 64.8000000000 - -18.9000000000 - 1.8000000000 - 21.4980480000 - -14.6577600000 - 3.2979960000 - -0.2442960000 - -28.6640640000 - 19.5436800000 - -4.3973280000 - 0.3257280000 - 11.9433600000 - -8.1432000000 - 1.8322200000 - -0.1357200000 - -1.5924480000 - 1.0857600000 - -0.2442960000 - 0.0180960000 - 0.0000000001 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.0000000001 - 0.0000000001 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -72.8941440000 - 43.9732800000 - -9.8939880000 - 0.7328880000 - 96.7921920000 - -58.6310400000 - 13.1919840000 - -0.9771840000 - -40.3300800000 - 24.4296000000 - -5.4966600000 - 0.4071600000 - 5.3773440000 - -3.2572800000 - 0.7328880000 - -0.0542880000 - 48.5960960000 - -29.3155200000 - 6.5959920000 - -0.4885920000 - -64.5281280000 - 39.0873600000 - -8.7946560000 - 0.6514560000 - 26.8867200000 - -16.2864000000 - 3.6644400000 - -0.2714400000 - -3.5848960000 - 2.1715200000 - -0.4885920000 - 0.0361920000 - 0.1221480000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.1628640000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0678600000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.0090480000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -8.7664440000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 11.2885920000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -4.7035800000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.6271440000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 5.8442960000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -7.5257280000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 3.1357200000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.4180960000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.1221480000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.1628640000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0678600000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.0090480000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -8.7664440000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 11.2885920000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -4.7035800000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.6271440000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 5.8442960000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -7.5257280000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 3.1357200000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.4180960000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.1221480000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.1628640000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0678600000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.0090480000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -8.7664440000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 11.2885920000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -4.7035800000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.6271440000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 5.8442960000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -7.5257280000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 3.1357200000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.4180960000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.1221480000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.1628640000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0678600000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.0090480000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -8.7664440000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 11.2885920000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -4.7035800000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.6271440000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 5.8442960000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -7.5257280000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 3.1357200000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.4180960000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 72.0000000000 - -48.0000000000 - 0.0000000000 - 0.0000000000 - -64.8000000000 - 43.2000000000 - 0.0000000000 - 0.0000000000 - 18.9000000000 - -12.6000000000 - 0.0000000000 - 0.0000000000 - -1.8000000000 - 1.2000000000 - 0.0000000000 - 0.0000000000 - -48.0000000000 - 32.0000000000 - 0.0000000000 - 0.0000000000 - 43.2000000000 - -28.8000000000 - 0.0000000000 - 0.0000000000 - -12.6000000000 - 8.4000000000 - 0.0000000000 - 0.0000000000 - 1.2000000000 - -0.8000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000001 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.0000000001 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 54.0000000000 - -72.0000000000 - 54.0000000000 - -12.0000000000 - -48.6000000000 - 64.8000000000 - -48.6000000000 - 10.8000000000 - 14.1750000000 - -18.9000000000 - 14.1750000000 - -3.1500000000 - -1.3500000000 - 1.8000000000 - -1.3500000000 - 0.3000000000 - -36.0000000000 - 48.0000000000 - -36.0000000000 - 8.0000000000 - 32.4000000000 - -43.2000000000 - 32.4000000000 - -7.2000000000 - -9.4500000000 - 12.6000000000 - -9.4500000000 - 2.1000000000 - 0.9000000000 - -1.2000000000 - 0.9000000000 - -0.2000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 30.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -27.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 7.8750000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.7500000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -20.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 18.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -5.2500000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.5000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -455.9999999998 - 431.9999999998 - -125.9999999999 - 12.0000000000 - 410.3999999998 - -388.7999999998 - 113.3999999999 - -10.8000000000 - -119.6999999999 - 113.3999999999 - -33.0750000000 - 3.1500000000 - 11.4000000000 - -10.8000000000 - 3.1500000000 - -0.3000000000 - 304.0000000000 - -288.0000000000 - 84.0000000000 - -8.0000000000 - -273.6000000000 - 259.2000000000 - -75.6000000000 - 7.2000000000 - 79.8000000000 - -75.6000000000 - 22.0500000000 - -2.1000000000 - -7.6000000000 - 7.2000000000 - -2.1000000000 - 0.2000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 24.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -21.6000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 6.3000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.6000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -16.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 14.4000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -4.2000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.4000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 24.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -21.6000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 6.3000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.6000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -16.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 14.4000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -4.2000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.4000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 24.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -21.6000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 6.3000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.6000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -16.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 14.4000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -4.2000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.4000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 24.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -21.6000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 6.3000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.6000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -16.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 14.4000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -4.2000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.4000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 24.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -21.6000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 6.3000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.6000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -16.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 14.4000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -4.2000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.4000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 1.8000000000 - -1.2000000000 - 0.0000000000 - 0.0000000000 - -1.2000000000 - 0.8000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -5.4000000000 - 3.6000000000 - 0.0000000000 - 0.0000000000 - 3.6000000000 - -2.4000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 4.0500000000 - -2.7000000000 - 0.0000000000 - 0.0000000000 - -2.7000000000 - 1.8000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.9000000000 - 0.6000000000 - 0.0000000000 - 0.0000000000 - 0.6000000000 - -0.4000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -18.1500000000 - 45.0000000000 - -33.7500000000 - 7.5000000000 - 12.1000000000 - -30.0000000000 - 22.5000000000 - -5.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 43.2000000000 - -108.0000000000 - 81.0000000000 - -18.0000000000 - -28.8000000000 - 72.0000000000 - -54.0000000000 - 12.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -32.4000000000 - 81.0000000000 - -60.7500000000 - 13.5000000000 - 21.6000000000 - -54.0000000000 - 40.5000000000 - -9.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 7.2000000000 - -18.0000000000 - 13.5000000000 - -3.0000000000 - -4.8000000000 - 12.0000000000 - -9.0000000000 - 2.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 80.8500000000 - -108.0000000000 - 45.0000000000 - -6.0000000000 - -53.9000000000 - 72.0000000000 - -30.0000000000 - 4.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -244.8000000000 - 324.0000000000 - -135.0000000000 - 18.0000000000 - 163.2000000000 - -216.0000000000 - 90.0000000000 - -12.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 183.6000000000 - -243.0000000000 - 101.2500000000 - -13.5000000000 - -122.4000000000 - 162.0000000000 - -67.5000000000 - 9.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -40.8000000000 - 54.0000000000 - -22.5000000000 - 3.0000000000 - 27.2000000000 - -36.0000000000 - 15.0000000000 - -2.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 60.6000000000 - -54.0000000000 - 15.7500000000 - -1.5000000000 - -40.4000000000 - 36.0000000000 - -10.5000000000 - 1.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -1.8000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 1.2000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 1.3500000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.9000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.3000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.2000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -3.9811200000 - 2.7144000000 - -0.6107400000 - 0.0452400000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 12.5433600000 - -8.1432000000 - 1.8322200000 - -0.1357200000 - -8.3622400000 - 5.4288000000 - -1.2214800000 - 0.0904800000 - 9.5546880000 - -6.5145600000 - 1.4657760000 - -0.1085760000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -30.4640640000 - 19.5436800000 - -4.3973280000 - 0.3257280000 - 20.3093760000 - -13.0291200000 - 2.9315520000 - -0.2171520000 - -7.1660160000 - 4.8859200000 - -1.0993320000 - 0.0814320000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 22.8480480000 - -14.6577600000 - 3.2979960000 - -0.2442960000 - -15.2320320000 - 9.7718400000 - -2.1986640000 - 0.1628640000 - 1.5924480000 - -1.0857600000 - 0.2442960000 - -0.0180960000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -5.0773440000 - 3.2572800000 - -0.7328880000 - 0.0542880000 - 3.3848960000 - -2.1715200000 - 0.4885920000 - -0.0361920000 - -0.0226200000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.6678600000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.4452400000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0542880000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -1.9628640000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 1.3085760000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.0407160000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 1.4721480000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.9814320000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0090480000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.3271440000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.2180960000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.0226200000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.6678600000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.4452400000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0542880000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -1.9628640000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 1.3085760000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.0407160000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 1.4721480000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.9814320000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0090480000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.3271440000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.2180960000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.0226200000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.6678600000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.4452400000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0542880000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -1.9628640000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 1.3085760000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.0407160000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 1.4721480000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.9814320000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0090480000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.3271440000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.2180960000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.0226200000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.6678600000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.4452400000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0542880000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -1.9628640000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 1.3085760000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.0407160000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 1.4721480000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.9814320000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0090480000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.3271440000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.2180960000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -2.4000000000 - 1.6000000000 - 0.0000000000 - 0.0000000000 - 7.2000000000 - -4.8000000000 - 0.0000000000 - 0.0000000000 - -5.4000000000 - 3.6000000000 - 0.0000000000 - 0.0000000000 - 1.2000000000 - -0.8000000000 - 0.0000000000 - 0.0000000000 - 7.2000000000 - -4.8000000000 - 0.0000000000 - 0.0000000000 - -21.6000000000 - 14.4000000000 - 0.0000000000 - 0.0000000000 - 16.2000000000 - -10.8000000000 - 0.0000000000 - 0.0000000000 - -3.6000000000 - 2.4000000000 - 0.0000000000 - 0.0000000000 - -5.4000000000 - 3.6000000000 - 0.0000000000 - 0.0000000000 - 16.2000000000 - -10.8000000000 - 0.0000000000 - 0.0000000000 - -12.1500000000 - 8.1000000000 - 0.0000000000 - 0.0000000000 - 2.7000000000 - -1.8000000000 - 0.0000000000 - 0.0000000000 - 1.2000000000 - -0.8000000000 - 0.0000000000 - 0.0000000000 - -3.6000000000 - 2.4000000000 - 0.0000000000 - 0.0000000000 - 2.7000000000 - -1.8000000000 - 0.0000000000 - 0.0000000000 - -0.6000000000 - 0.4000000000 - 49.2000000000 - -120.0000000000 - 90.0000000000 - -20.0000000000 - -132.6000000000 - 324.0000000000 - -243.0000000000 - 54.0000000000 - 99.4500000000 - -243.0000000000 - 182.2500000000 - -40.5000000000 - -22.1000000000 - 54.0000000000 - -40.5000000000 - 9.0000000000 - -132.6000000000 - 324.0000000000 - -243.0000000000 - 54.0000000000 - 352.8000000000 - -864.0000000000 - 648.0000000000 - -144.0000000000 - -264.6000000000 - 648.0000000000 - -486.0000000000 - 108.0000000000 - 58.8000000000 - -144.0000000000 - 108.0000000000 - -24.0000000000 - 99.4500000000 - -243.0000000000 - 182.2500000000 - -40.5000000000 - -264.6000000000 - 648.0000000000 - -486.0000000000 - 108.0000000000 - 198.4500000000 - -486.0000000000 - 364.5000000000 - -81.0000000000 - -44.1000000000 - 108.0000000000 - -81.0000000000 - 18.0000000000 - -22.1000000000 - 54.0000000000 - -40.5000000000 - 9.0000000000 - 58.8000000000 - -144.0000000000 - 108.0000000000 - -24.0000000000 - -44.1000000000 - 108.0000000000 - -81.0000000000 - 18.0000000000 - 9.8000000000 - -24.0000000000 - 18.0000000000 - -4.0000000000 - -102.7999999999 - 143.9999999999 - -60.0000000000 - 8.0000000000 - 311.3999999998 - -431.9999999998 - 179.9999999999 - -24.0000000000 - -233.5499999999 - 323.9999999998 - -134.9999999999 - 18.0000000000 - 51.9000000000 - -72.0000000000 - 30.0000000000 - -4.0000000000 - 311.3999999999 - -431.9999999999 - 180.0000000000 - -24.0000000000 - -943.1999999998 - 1295.9999999998 - -539.9999999999 - 72.0000000000 - 707.3999999999 - -971.9999999998 - 404.9999999999 - -54.0000000000 - -157.2000000000 - 216.0000000000 - -90.0000000000 - 12.0000000000 - -233.5500000000 - 324.0000000000 - -135.0000000000 - 18.0000000000 - 707.4000000000 - -972.0000000000 - 405.0000000000 - -54.0000000000 - -530.5500000000 - 729.0000000000 - -303.7500000000 - 40.5000000000 - 117.9000000000 - -162.0000000000 - 67.5000000000 - -9.0000000000 - 51.9000000000 - -72.0000000000 - 30.0000000000 - -4.0000000000 - -157.2000000000 - 216.0000000000 - -90.0000000000 - 12.0000000000 - 117.9000000000 - -162.0000000000 - 67.5000000000 - -9.0000000000 - -26.2000000000 - 36.0000000000 - -15.0000000000 - 2.0000000000 - -480.8000000000 - 432.0000000000 - -126.0000000000 - 12.0000000000 - 1202.4000000000 - -1080.0000000000 - 315.0000000000 - -30.0000000000 - -901.8000000000 - 810.0000000000 - -236.2500000000 - 22.5000000000 - 200.4000000000 - -180.0000000000 - 52.5000000000 - -5.0000000000 - 1202.4000000000 - -1080.0000000000 - 315.0000000000 - -30.0000000000 - -2887.2000000000 - 2592.0000000000 - -756.0000000000 - 72.0000000000 - 2165.4000000000 - -1944.0000000000 - 567.0000000000 - -54.0000000000 - -481.2000000000 - 432.0000000000 - -126.0000000000 - 12.0000000000 - -901.8000000000 - 810.0000000000 - -236.2500000000 - 22.5000000000 - 2165.4000000000 - -1944.0000000000 - 567.0000000000 - -54.0000000000 - -1624.0500000000 - 1458.0000000000 - -425.2500000000 - 40.5000000000 - 360.9000000000 - -324.0000000000 - 94.5000000000 - -9.0000000000 - 200.4000000000 - -180.0000000000 - 52.5000000000 - -5.0000000000 - -481.2000000000 - 432.0000000000 - -126.0000000000 - 12.0000000000 - 360.9000000000 - -324.0000000000 - 94.5000000000 - -9.0000000000 - -80.2000000000 - 72.0000000000 - -21.0000000000 - 2.0000000000 - -0.8000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 2.4000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -1.8000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.4000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 2.4000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -7.2000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 5.4000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -1.2000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -1.8000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 5.4000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -4.0500000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.9000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.4000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -1.2000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.9000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.2000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.8000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 2.4000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -1.8000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.4000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 2.4000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -7.2000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 5.4000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -1.2000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -1.8000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 5.4000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -4.0500000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.9000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.4000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -1.2000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.9000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.2000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.8000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 2.4000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -1.8000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.4000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 2.4000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -7.2000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 5.4000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -1.2000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -1.8000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 5.4000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -4.0500000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.9000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.4000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -1.2000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.9000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.2000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.8000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 2.4000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -1.8000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.4000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 2.4000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -7.2000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 5.4000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -1.2000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -1.8000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 5.4000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -4.0500000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.9000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.4000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -1.2000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.9000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.2000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.8000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 2.4000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -1.8000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.4000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 2.4000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -7.2000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 5.4000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -1.2000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -1.8000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 5.4000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -4.0500000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.9000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.4000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -1.2000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.9000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.2000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 33.6000000000 - -22.4000000000 - 0.0000000000 - 0.0000000000 - -43.2000000000 - 28.8000000000 - 0.0000000000 - 0.0000000000 - 18.0000000000 - -12.0000000000 - 0.0000000000 - 0.0000000000 - -2.4000000000 - 1.6000000000 - 0.0000000000 - 0.0000000000 - -100.8000000000 - 67.2000000000 - 0.0000000000 - 0.0000000000 - 129.6000000000 - -86.4000000000 - 0.0000000000 - 0.0000000000 - -54.0000000000 - 36.0000000000 - 0.0000000000 - 0.0000000000 - 7.2000000000 - -4.8000000000 - 0.0000000000 - 0.0000000000 - 75.6000000000 - -50.4000000000 - 0.0000000000 - 0.0000000000 - -97.2000000000 - 64.8000000000 - 0.0000000000 - 0.0000000000 - 40.5000000000 - -27.0000000000 - 0.0000000000 - 0.0000000000 - -5.4000000000 - 3.6000000000 - 0.0000000000 - 0.0000000000 - -16.8000000000 - 11.2000000000 - 0.0000000000 - 0.0000000000 - 21.6000000000 - -14.4000000000 - 0.0000000000 - 0.0000000000 - -9.0000000000 - 6.0000000000 - 0.0000000000 - 0.0000000000 - 1.2000000000 - -0.8000000000 - -109.7999999999 - 290.3999999998 - -217.7999999998 - 48.4000000000 - 147.5999999999 - -388.7999999997 - 291.5999999998 - -64.7999999999 - -61.5000000000 - 161.9999999999 - -121.4999999999 - 27.0000000000 - 8.2000000000 - -21.6000000000 - 16.2000000000 - -3.6000000000 - 329.3999999999 - -871.1999999998 - 653.3999999998 - -145.2000000000 - -442.7999999999 - 1166.3999999997 - -874.7999999998 - 194.3999999999 - 184.5000000000 - -485.9999999999 - 364.4999999999 - -81.0000000000 - -24.6000000000 - 64.8000000000 - -48.6000000000 - 10.8000000000 - -247.0500000000 - 653.4000000000 - -490.0500000000 - 108.9000000000 - 332.1000000000 - -874.8000000000 - 656.1000000000 - -145.8000000000 - -138.3750000000 - 364.5000000000 - -273.3750000000 - 60.7500000000 - 18.4500000000 - -48.6000000000 - 36.4500000000 - -8.1000000000 - 54.9000000000 - -145.2000000000 - 108.9000000000 - -24.2000000000 - -73.8000000000 - 194.4000000000 - -145.8000000000 - 32.4000000000 - 30.7500000000 - -81.0000000000 - 60.7500000000 - -13.5000000000 - -4.1000000000 - 10.8000000000 - -8.1000000000 - 1.8000000000 - -13.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 18.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -7.5000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 1.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 39.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -54.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 22.5000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -3.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -29.2500000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 40.5000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -16.8750000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 2.2500000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 6.5000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -9.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 3.7500000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.5000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 1947.2000000055 - -1742.4000000048 - 508.2000000014 - -48.4000000001 - -2606.4000000073 - 2332.8000000064 - -680.4000000019 - 64.8000000002 - 1086.0000000032 - -972.0000000028 - 283.5000000008 - -27.0000000001 - -144.8000000004 - 129.6000000004 - -37.8000000001 - 3.6000000000 - -5841.6000000049 - 5227.2000000043 - -1524.6000000012 - 145.2000000001 - 7819.2000000068 - -6998.4000000059 - 2041.2000000017 - -194.4000000002 - -3258.0000000030 - 2916.0000000026 - -850.5000000008 - 81.0000000001 - 434.4000000004 - -388.8000000004 - 113.4000000001 - -10.8000000000 - 4381.1999999994 - -3920.3999999995 - 1143.4499999998 - -108.9000000000 - -5864.3999999995 - 5248.7999999995 - -1530.8999999999 - 145.8000000000 - 2443.4999999998 - -2186.9999999998 - 637.8750000000 - -60.7500000000 - -325.8000000000 - 291.6000000000 - -85.0500000000 - 8.1000000000 - -973.6000000000 - 871.2000000000 - -254.1000000000 - 24.2000000000 - 1303.2000000000 - -1166.4000000000 - 340.2000000000 - -32.4000000000 - -543.0000000000 - 486.0000000000 - -141.7500000000 - 13.5000000000 - 72.4000000000 - -64.8000000000 - 18.9000000000 - -1.8000000000 - 11.2000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -14.4000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 6.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.8000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -33.6000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 43.2000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -18.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 2.4000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 25.2000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -32.4000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 13.5000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -1.8000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -5.6000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 7.2000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -3.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.4000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 11.2000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -14.4000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 6.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.8000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -33.6000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 43.2000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -18.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 2.4000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 25.2000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -32.4000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 13.5000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -1.8000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -5.6000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 7.2000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -3.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.4000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 11.2000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -14.4000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 6.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.8000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -33.6000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 43.2000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -18.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 2.4000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 25.2000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -32.4000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 13.5000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -1.8000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -5.6000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 7.2000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -3.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.4000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 11.2000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -14.4000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 6.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.8000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -33.6000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 43.2000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -18.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 2.4000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 25.2000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -32.4000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 13.5000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -1.8000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -5.6000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 7.2000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -3.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.4000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 11.2000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -14.4000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 6.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.8000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -33.6000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 43.2000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -18.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 2.4000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 25.2000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -32.4000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 13.5000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -1.8000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -5.6000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 7.2000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -3.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.4000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -96.0000000000 - 64.0000000000 - 0.0000000000 - 0.0000000000 - 86.4000000000 - -57.6000000000 - 0.0000000000 - 0.0000000000 - -25.2000000000 - 16.8000000000 - 0.0000000000 - 0.0000000000 - 2.4000000000 - -1.6000000000 - 0.0000000000 - 0.0000000000 - 288.0000000000 - -192.0000000000 - 0.0000000000 - 0.0000000000 - -259.2000000000 - 172.8000000000 - 0.0000000000 - 0.0000000000 - 75.6000000000 - -50.4000000000 - 0.0000000000 - 0.0000000000 - -7.2000000000 - 4.8000000000 - 0.0000000000 - 0.0000000000 - -216.0000000000 - 144.0000000000 - 0.0000000000 - 0.0000000000 - 194.4000000000 - -129.6000000000 - 0.0000000000 - 0.0000000000 - -56.7000000000 - 37.8000000000 - 0.0000000000 - 0.0000000000 - 5.4000000000 - -3.6000000000 - 0.0000000000 - 0.0000000000 - 48.0000000000 - -32.0000000000 - 0.0000000000 - 0.0000000000 - -43.2000000000 - 28.8000000000 - 0.0000000000 - 0.0000000000 - 12.6000000000 - -8.4000000000 - 0.0000000000 - 0.0000000000 - -1.2000000000 - 0.8000000000 - -72.0000000000 - 96.0000000001 - -72.0000000001 - 16.0000000000 - 64.8000000000 - -86.4000000001 - 64.8000000000 - -14.4000000000 - -18.9000000000 - 25.2000000000 - -18.9000000000 - 4.2000000000 - 1.8000000000 - -2.4000000000 - 1.8000000000 - -0.4000000000 - 216.0000000000 - -288.0000000001 - 216.0000000000 - -48.0000000000 - -194.4000000000 - 259.2000000001 - -194.4000000000 - 43.2000000000 - 56.7000000000 - -75.6000000000 - 56.7000000000 - -12.6000000000 - -5.4000000000 - 7.2000000000 - -5.4000000000 - 1.2000000000 - -162.0000000000 - 216.0000000000 - -162.0000000000 - 36.0000000000 - 145.8000000000 - -194.4000000000 - 145.8000000000 - -32.4000000000 - -42.5250000000 - 56.7000000000 - -42.5250000000 - 9.4500000000 - 4.0500000000 - -5.4000000000 - 4.0500000000 - -0.9000000000 - 36.0000000000 - -48.0000000000 - 36.0000000000 - -8.0000000000 - -32.4000000000 - 43.2000000000 - -32.4000000000 - 7.2000000000 - 9.4500000000 - -12.6000000000 - 9.4500000000 - -2.1000000000 - -0.9000000000 - 1.2000000000 - -0.9000000000 - 0.2000000000 - -40.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 36.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -10.5000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 1.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 120.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -108.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 31.5000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -3.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -90.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 81.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -23.6250000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 2.2500000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 20.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -18.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 5.2500000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.5000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 608.0000000034 - -576.0000000029 - 168.0000000009 - -16.0000000001 - -547.2000000031 - 518.4000000027 - -151.2000000008 - 14.4000000001 - 159.6000000009 - -151.2000000008 - 44.1000000002 - -4.2000000000 - -15.2000000001 - 14.4000000001 - -4.2000000000 - 0.4000000000 - -1824.0000000034 - 1728.0000000029 - -504.0000000009 - 48.0000000001 - 1641.6000000030 - -1555.2000000026 - 453.6000000008 - -43.2000000001 - -478.8000000009 - 453.6000000008 - -132.3000000002 - 12.6000000000 - 45.6000000001 - -43.2000000001 - 12.6000000000 - -1.2000000000 - 1368.0000000000 - -1296.0000000000 - 378.0000000000 - -36.0000000000 - -1231.2000000000 - 1166.4000000000 - -340.2000000000 - 32.4000000000 - 359.1000000000 - -340.2000000000 - 99.2250000000 - -9.4500000000 - -34.2000000000 - 32.4000000000 - -9.4500000000 - 0.9000000000 - -304.0000000000 - 288.0000000000 - -84.0000000000 - 8.0000000000 - 273.6000000000 - -259.2000000000 - 75.6000000000 - -7.2000000000 - -79.8000000000 - 75.6000000000 - -22.0500000000 - 2.1000000000 - 7.6000000000 - -7.2000000000 - 2.1000000000 - -0.2000000000 - -32.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 28.8000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -8.4000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.8000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 96.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -86.4000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 25.2000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -2.4000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -72.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 64.8000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -18.9000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 1.8000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 16.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -14.4000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 4.2000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.4000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -32.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 28.8000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -8.4000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.8000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 96.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -86.4000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 25.2000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -2.4000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -72.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 64.8000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -18.9000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 1.8000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 16.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -14.4000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 4.2000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.4000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -32.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 28.8000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -8.4000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.8000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 96.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -86.4000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 25.2000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -2.4000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -72.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 64.8000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -18.9000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 1.8000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 16.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -14.4000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 4.2000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.4000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -32.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 28.8000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -8.4000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.8000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 96.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -86.4000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 25.2000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -2.4000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -72.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 64.8000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -18.9000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 1.8000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 16.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -14.4000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 4.2000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.4000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -32.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 28.8000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -8.4000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.8000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 96.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -86.4000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 25.2000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -2.4000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -72.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 64.8000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -18.9000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 1.8000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 16.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -14.4000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 4.2000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.4000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -25.2000000000 - 16.8000000000 - 0.0000000000 - 0.0000000000 - 16.8000000000 - -11.2000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 32.4000000000 - -21.6000000000 - 0.0000000000 - 0.0000000000 - -21.6000000000 - 14.4000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -13.5000000000 - 9.0000000000 - 0.0000000000 - 0.0000000000 - 9.0000000000 - -6.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 1.8000000000 - -1.2000000000 - 0.0000000000 - 0.0000000000 - -1.2000000000 - 0.8000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 82.3500000000 - -217.8000000000 - 163.3500000000 - -36.3000000000 - -54.9000000000 - 145.2000000000 - -108.9000000000 - 24.2000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -110.7000000000 - 291.6000000000 - -218.7000000000 - 48.6000000000 - 73.8000000000 - -194.4000000000 - 145.8000000000 - -32.4000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 46.1250000000 - -121.5000000000 - 91.1250000000 - -20.2500000000 - -30.7500000000 - 81.0000000000 - -60.7500000000 - 13.5000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -6.1500000000 - 16.2000000000 - -12.1500000000 - 2.7000000000 - 4.1000000000 - -10.8000000000 - 8.1000000000 - -1.8000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 9.7500000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -6.5000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -13.5000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 9.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 5.6250000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -3.7500000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.7500000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.5000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000001 - -0.0000000001 - 0.0000000000 - 0.0000000000 - -1460.4000000001 - 1306.8000000001 - -381.1500000000 - 36.3000000000 - 973.6000000001 - -871.2000000001 - 254.1000000000 - -24.2000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.0000000001 - 0.0000000001 - 0.0000000000 - 0.0000000000 - 1954.8000000001 - -1749.6000000001 - 510.3000000000 - -48.6000000000 - -1303.2000000001 - 1166.4000000001 - -340.2000000000 - 32.4000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -814.5000000000 - 729.0000000000 - -212.6250000000 - 20.2500000000 - 543.0000000000 - -486.0000000000 - 141.7500000000 - -13.5000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 108.6000000000 - -97.2000000000 - 28.3500000000 - -2.7000000000 - -72.4000000000 - 64.8000000000 - -18.9000000000 - 1.8000000000 - 21.4980480000 - -14.6577600000 - 3.2979960000 - -0.2442960000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -72.8941440000 - 43.9732800000 - -9.8939880000 - 0.7328880000 - 48.5960960000 - -29.3155200000 - 6.5959920000 - -0.4885920000 - -28.6640640000 - 19.5436800000 - -4.3973280000 - 0.3257280000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 96.7921920000 - -58.6310400000 - 13.1919840000 - -0.9771840000 - -64.5281280000 - 39.0873600000 - -8.7946560000 - 0.6514560000 - 11.9433600000 - -8.1432000000 - 1.8322200000 - -0.1357200000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -40.3300800000 - 24.4296000000 - -5.4966600000 - 0.4071600000 - 26.8867200000 - -16.2864000000 - 3.6644400000 - -0.2714400000 - -1.5924480000 - 1.0857600000 - -0.2442960000 - 0.0180960000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 5.3773440000 - -3.2572800000 - 0.7328880000 - -0.0542880000 - -3.5848960000 - 2.1715200000 - -0.4885920000 - 0.0361920000 - 0.1221480000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -8.7664440000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 5.8442960000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.1628640000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 11.2885920000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -7.5257280000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0678600000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -4.7035800000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 3.1357200000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.0090480000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.6271440000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.4180960000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.1221480000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -8.7664440000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 5.8442960000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.1628640000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 11.2885920000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -7.5257280000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0678600000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -4.7035800000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 3.1357200000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.0090480000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.6271440000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.4180960000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.1221480000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -8.7664440000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 5.8442960000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.1628640000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 11.2885920000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -7.5257280000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0678600000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -4.7035800000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 3.1357200000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.0090480000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.6271440000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.4180960000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.1221480000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -8.7664440000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 5.8442960000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.1628640000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 11.2885920000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -7.5257280000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0678600000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -4.7035800000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 3.1357200000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.0090480000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.6271440000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.4180960000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 33.6000000000 - -22.4000000000 - 0.0000000000 - 0.0000000000 - -100.8000000000 - 67.2000000000 - 0.0000000000 - 0.0000000000 - 75.6000000000 - -50.4000000000 - 0.0000000000 - 0.0000000000 - -16.8000000000 - 11.2000000000 - 0.0000000000 - 0.0000000000 - -43.2000000000 - 28.8000000000 - 0.0000000000 - 0.0000000000 - 129.6000000000 - -86.4000000000 - 0.0000000000 - 0.0000000000 - -97.2000000000 - 64.8000000000 - 0.0000000000 - 0.0000000000 - 21.6000000000 - -14.4000000000 - 0.0000000000 - 0.0000000000 - 18.0000000000 - -12.0000000000 - 0.0000000000 - 0.0000000000 - -54.0000000000 - 36.0000000000 - 0.0000000000 - 0.0000000000 - 40.5000000000 - -27.0000000000 - 0.0000000000 - 0.0000000000 - -9.0000000000 - 6.0000000000 - 0.0000000000 - 0.0000000000 - -2.4000000000 - 1.6000000000 - 0.0000000000 - 0.0000000000 - 7.2000000000 - -4.8000000000 - 0.0000000000 - 0.0000000000 - -5.4000000000 - 3.6000000000 - 0.0000000000 - 0.0000000000 - 1.2000000000 - -0.8000000000 - -109.8000000000 - 290.4000000000 - -217.8000000000 - 48.4000000000 - 329.4000000000 - -871.2000000000 - 653.4000000000 - -145.2000000000 - -247.0500000000 - 653.4000000000 - -490.0500000000 - 108.9000000000 - 54.9000000000 - -145.2000000000 - 108.9000000000 - -24.2000000000 - 147.6000000000 - -388.8000000000 - 291.6000000000 - -64.8000000000 - -442.8000000000 - 1166.4000000000 - -874.8000000000 - 194.4000000000 - 332.1000000000 - -874.8000000000 - 656.1000000000 - -145.8000000000 - -73.8000000000 - 194.4000000000 - -145.8000000000 - 32.4000000000 - -61.5000000000 - 162.0000000000 - -121.5000000000 - 27.0000000000 - 184.5000000000 - -486.0000000000 - 364.5000000000 - -81.0000000000 - -138.3750000000 - 364.5000000000 - -273.3750000000 - 60.7500000000 - 30.7500000000 - -81.0000000000 - 60.7500000000 - -13.5000000000 - 8.2000000000 - -21.6000000000 - 16.2000000000 - -3.6000000000 - -24.6000000000 - 64.8000000000 - -48.6000000000 - 10.8000000000 - 18.4500000000 - -48.6000000000 - 36.4500000000 - -8.1000000000 - -4.1000000000 - 10.8000000000 - -8.1000000000 - 1.8000000000 - -13.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 39.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -29.2500000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 6.5000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 18.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -54.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 40.5000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -9.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -7.5000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 22.5000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -16.8750000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 3.7500000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 1.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -3.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 2.2500000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.5000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 1947.2000000009 - -1742.4000000008 - 508.2000000002 - -48.4000000000 - -5841.6000000028 - 5227.2000000024 - -1524.6000000007 - 145.2000000001 - 4381.2000000026 - -3920.4000000022 - 1143.4500000006 - -108.9000000001 - -973.6000000006 - 871.2000000005 - -254.1000000001 - 24.2000000000 - -2606.4000000000 - 2332.7999999999 - -680.4000000000 - 64.8000000000 - 7819.2000000007 - -6998.4000000006 - 2041.2000000002 - -194.4000000000 - -5864.4000000010 - 5248.8000000008 - -1530.9000000002 - 145.8000000000 - 1303.2000000002 - -1166.4000000002 - 340.2000000001 - -32.4000000000 - 1085.9999999997 - -971.9999999997 - 283.4999999999 - -27.0000000000 - -3257.9999999996 - 2915.9999999996 - -850.4999999999 - 81.0000000000 - 2443.4999999998 - -2186.9999999999 - 637.8750000000 - -60.7500000000 - -543.0000000000 - 486.0000000000 - -141.7500000000 - 13.5000000000 - -144.8000000000 - 129.6000000000 - -37.8000000000 - 3.6000000000 - 434.4000000000 - -388.8000000000 - 113.4000000000 - -10.8000000000 - -325.8000000000 - 291.6000000000 - -85.0500000000 - 8.1000000000 - 72.4000000000 - -64.8000000000 - 18.9000000000 - -1.8000000000 - 11.2000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -33.6000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 25.2000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -5.6000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -14.4000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 43.2000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -32.4000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 7.2000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 6.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -18.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 13.5000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -3.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.8000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 2.4000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -1.8000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.4000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 11.2000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -33.6000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 25.2000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -5.6000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -14.4000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 43.2000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -32.4000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 7.2000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 6.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -18.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 13.5000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -3.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.8000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 2.4000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -1.8000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.4000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 11.2000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -33.6000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 25.2000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -5.6000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -14.4000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 43.2000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -32.4000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 7.2000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 6.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -18.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 13.5000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -3.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.8000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 2.4000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -1.8000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.4000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 11.2000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -33.6000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 25.2000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -5.6000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -14.4000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 43.2000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -32.4000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 7.2000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 6.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -18.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 13.5000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -3.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.8000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 2.4000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -1.8000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.4000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 11.2000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -33.6000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 25.2000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -5.6000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -14.4000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 43.2000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -32.4000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 7.2000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 6.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -18.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 13.5000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -3.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.8000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 2.4000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -1.8000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.4000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 72.0000000000 - -48.0000000000 - 0.0000000000 - 0.0000000000 - -48.0000000000 - 32.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -64.8000000000 - 43.2000000000 - 0.0000000000 - 0.0000000000 - 43.2000000000 - -28.8000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 18.9000000000 - -12.6000000000 - 0.0000000000 - 0.0000000000 - -12.6000000000 - 8.4000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -1.8000000000 - 1.2000000000 - 0.0000000000 - 0.0000000000 - 1.2000000000 - -0.8000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 54.0000000000 - -72.0000000000 - 54.0000000000 - -12.0000000000 - -36.0000000000 - 48.0000000000 - -36.0000000000 - 8.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -48.6000000000 - 64.8000000000 - -48.6000000000 - 10.8000000000 - 32.4000000000 - -43.2000000000 - 32.4000000000 - -7.2000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 14.1750000000 - -18.9000000000 - 14.1750000000 - -3.1500000000 - -9.4500000000 - 12.6000000000 - -9.4500000000 - 2.1000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -1.3500000000 - 1.8000000000 - -1.3500000000 - 0.3000000000 - 0.9000000000 - -1.2000000000 - 0.9000000000 - -0.2000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 30.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -20.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -27.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 18.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 7.8750000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -5.2500000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.7500000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.5000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -456.0000000000 - 432.0000000000 - -126.0000000000 - 12.0000000000 - 304.0000000000 - -288.0000000000 - 84.0000000000 - -8.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 410.4000000000 - -388.8000000000 - 113.4000000000 - -10.8000000000 - -273.6000000000 - 259.2000000000 - -75.6000000000 - 7.2000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -119.7000000000 - 113.4000000000 - -33.0750000000 - 3.1500000000 - 79.8000000000 - -75.6000000000 - 22.0500000000 - -2.1000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 11.4000000000 - -10.8000000000 - 3.1500000000 - -0.3000000000 - -7.6000000000 - 7.2000000000 - -2.1000000000 - 0.2000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 24.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -16.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -21.6000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 14.4000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 6.3000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -4.2000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.6000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.4000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 24.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -16.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -21.6000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 14.4000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 6.3000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -4.2000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.6000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.4000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 24.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -16.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -21.6000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 14.4000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 6.3000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -4.2000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.6000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.4000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 24.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -16.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -21.6000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 14.4000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 6.3000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -4.2000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.6000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.4000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 24.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -16.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -21.6000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 14.4000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 6.3000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -4.2000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.6000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.4000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -96.0000000000 - 64.0000000000 - 0.0000000000 - 0.0000000000 - 288.0000000000 - -192.0000000000 - 0.0000000000 - 0.0000000000 - -216.0000000000 - 144.0000000000 - 0.0000000000 - 0.0000000000 - 48.0000000000 - -32.0000000000 - 0.0000000000 - 0.0000000000 - 86.4000000000 - -57.6000000000 - 0.0000000000 - 0.0000000000 - -259.2000000000 - 172.8000000000 - 0.0000000000 - 0.0000000000 - 194.4000000000 - -129.6000000000 - 0.0000000000 - 0.0000000000 - -43.2000000000 - 28.8000000000 - 0.0000000000 - 0.0000000000 - -25.2000000000 - 16.8000000000 - 0.0000000000 - 0.0000000000 - 75.6000000000 - -50.4000000000 - 0.0000000000 - 0.0000000000 - -56.7000000000 - 37.8000000000 - 0.0000000000 - 0.0000000000 - 12.6000000000 - -8.4000000000 - 0.0000000000 - 0.0000000000 - 2.4000000000 - -1.6000000000 - 0.0000000000 - 0.0000000000 - -7.2000000000 - 4.8000000000 - 0.0000000000 - 0.0000000000 - 5.4000000000 - -3.6000000000 - 0.0000000000 - 0.0000000000 - -1.2000000000 - 0.8000000000 - -72.0000000000 - 96.0000000000 - -72.0000000000 - 16.0000000000 - 216.0000000000 - -288.0000000000 - 216.0000000000 - -48.0000000000 - -162.0000000000 - 216.0000000000 - -162.0000000000 - 36.0000000000 - 36.0000000000 - -48.0000000000 - 36.0000000000 - -8.0000000000 - 64.8000000000 - -86.4000000000 - 64.8000000000 - -14.4000000000 - -194.4000000000 - 259.2000000000 - -194.4000000000 - 43.2000000000 - 145.8000000000 - -194.4000000000 - 145.8000000000 - -32.4000000000 - -32.4000000000 - 43.2000000000 - -32.4000000000 - 7.2000000000 - -18.9000000000 - 25.2000000000 - -18.9000000000 - 4.2000000000 - 56.7000000000 - -75.6000000000 - 56.7000000000 - -12.6000000000 - -42.5250000000 - 56.7000000000 - -42.5250000000 - 9.4500000000 - 9.4500000000 - -12.6000000000 - 9.4500000000 - -2.1000000000 - 1.8000000000 - -2.4000000000 - 1.8000000000 - -0.4000000000 - -5.4000000000 - 7.2000000000 - -5.4000000000 - 1.2000000000 - 4.0500000000 - -5.4000000000 - 4.0500000000 - -0.9000000000 - -0.9000000000 - 1.2000000000 - -0.9000000000 - 0.2000000000 - -40.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 120.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -90.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 20.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 36.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -108.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 81.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -18.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -10.5000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 31.5000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -23.6250000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 5.2500000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 1.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -3.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 2.2500000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.5000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 608.0000000005 - -576.0000000004 - 168.0000000001 - -16.0000000000 - -1824.0000000013 - 1728.0000000011 - -504.0000000003 - 48.0000000000 - 1368.0000000010 - -1296.0000000008 - 378.0000000002 - -36.0000000000 - -304.0000000002 - 288.0000000002 - -84.0000000001 - 8.0000000000 - -547.2000000001 - 518.4000000001 - -151.2000000000 - 14.4000000000 - 1641.6000000004 - -1555.2000000003 - 453.6000000001 - -43.2000000000 - -1231.2000000003 - 1166.4000000003 - -340.2000000001 - 32.4000000000 - 273.6000000001 - -259.2000000001 - 75.6000000000 - -7.2000000000 - 159.6000000000 - -151.2000000000 - 44.1000000000 - -4.2000000000 - -478.8000000000 - 453.6000000000 - -132.3000000000 - 12.6000000000 - 359.1000000000 - -340.2000000000 - 99.2250000000 - -9.4500000000 - -79.8000000000 - 75.6000000000 - -22.0500000000 - 2.1000000000 - -15.2000000000 - 14.4000000000 - -4.2000000000 - 0.4000000000 - 45.6000000000 - -43.2000000000 - 12.6000000000 - -1.2000000000 - -34.2000000000 - 32.4000000000 - -9.4500000000 - 0.9000000000 - 7.6000000000 - -7.2000000000 - 2.1000000000 - -0.2000000000 - -32.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 96.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -72.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 16.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 28.8000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -86.4000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 64.8000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -14.4000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -8.4000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 25.2000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -18.9000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 4.2000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.8000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -2.4000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 1.8000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.4000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -32.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 96.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -72.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 16.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 28.8000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -86.4000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 64.8000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -14.4000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -8.4000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 25.2000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -18.9000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 4.2000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.8000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -2.4000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 1.8000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.4000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -32.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 96.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -72.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 16.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 28.8000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -86.4000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 64.8000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -14.4000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -8.4000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 25.2000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -18.9000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 4.2000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.8000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -2.4000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 1.8000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.4000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -32.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 96.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -72.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 16.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 28.8000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -86.4000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 64.8000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -14.4000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -8.4000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 25.2000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -18.9000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 4.2000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.8000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -2.4000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 1.8000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.4000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -32.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 96.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -72.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 16.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 28.8000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -86.4000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 64.8000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -14.4000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -8.4000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 25.2000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -18.9000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 4.2000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.8000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -2.4000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 1.8000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.4000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -# piHH - -6 -0.0 -4.0 -0.0 -4.0 -0.0 -9.0 - - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 3.3727320000 - -2.2484880000 - 0.0000000000 - 0.0000000000 - -2.2484880000 - 1.4989920000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -2.2484880000 - 1.4989920000 - 0.0000000000 - 0.0000000000 - 1.4989920000 - -0.9993280000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -4.4969760000 - 13.4909280000 - -10.1181960000 - 2.2484880000 - 2.9979840000 - -8.9939520000 - 6.7454640000 - -1.4989920000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 2.9979840000 - -8.9939520000 - 6.7454640000 - -1.4989920000 - -1.9986560000 - 5.9959680000 - -4.4969760000 - 0.9993280000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -4.4969760000 - 2.9979840000 - 0.0000000000 - 0.0000000000 - 13.4909280000 - -8.9939520000 - 0.0000000000 - 0.0000000000 - -10.1181960000 - 6.7454640000 - 0.0000000000 - 0.0000000000 - 2.2484880000 - -1.4989920000 - 0.0000000000 - 0.0000000000 - 2.9979840000 - -1.9986560000 - 0.0000000000 - 0.0000000000 - -8.9939520000 - 5.9959680000 - 0.0000000000 - 0.0000000000 - 6.7454640000 - -4.4969760000 - 0.0000000000 - 0.0000000000 - -1.4989920000 - 0.9993280000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 5.9959680000 - -17.9879040000 - 13.4909280000 - -2.9979840000 - -17.9879040000 - 53.9637120000 - -40.4727840000 - 8.9939520000 - 13.4909280000 - -40.4727840000 - 30.3545880000 - -6.7454640000 - -2.9979840000 - 8.9939520000 - -6.7454640000 - 1.4989920000 - -3.9973120000 - 11.9919360000 - -8.9939520000 - 1.9986560000 - 11.9919360000 - -35.9758080000 - 26.9818560000 - -5.9959680000 - -8.9939520000 - 26.9818560000 - -20.2363920000 - 4.4969760000 - 1.9986560000 - -5.9959680000 - 4.4969760000 - -0.9993280000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -4.4969760000 - 2.9979840000 - 0.0000000000 - 0.0000000000 - 2.9979840000 - -1.9986560000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 13.4909280000 - -8.9939520000 - 0.0000000000 - 0.0000000000 - -8.9939520000 - 5.9959680000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -10.1181960000 - 6.7454640000 - 0.0000000000 - 0.0000000000 - 6.7454640000 - -4.4969760000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 2.2484880000 - -1.4989920000 - 0.0000000000 - 0.0000000000 - -1.4989920000 - 0.9993280000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 5.9959680000 - -17.9879040000 - 13.4909280000 - -2.9979840000 - -3.9973120000 - 11.9919360000 - -8.9939520000 - 1.9986560000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -17.9879040000 - 53.9637120000 - -40.4727840000 - 8.9939520000 - 11.9919360000 - -35.9758080000 - 26.9818560000 - -5.9959680000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 13.4909280000 - -40.4727840000 - 30.3545880000 - -6.7454640000 - -8.9939520000 - 26.9818560000 - -20.2363920000 - 4.4969760000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -2.9979840000 - 8.9939520000 - -6.7454640000 - 1.4989920000 - 1.9986560000 - -5.9959680000 - 4.4969760000 - -0.9993280000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 5.9959680000 - -3.9973120000 - 0.0000000000 - 0.0000000000 - -17.9879040000 - 11.9919360000 - 0.0000000000 - 0.0000000000 - 13.4909280000 - -8.9939520000 - 0.0000000000 - 0.0000000000 - -2.9979840000 - 1.9986560000 - 0.0000000000 - 0.0000000000 - -17.9879040000 - 11.9919360000 - 0.0000000000 - 0.0000000000 - 53.9637120000 - -35.9758080000 - 0.0000000000 - 0.0000000000 - -40.4727840000 - 26.9818560000 - 0.0000000000 - 0.0000000000 - 8.9939520000 - -5.9959680000 - 0.0000000000 - 0.0000000000 - 13.4909280000 - -8.9939520000 - 0.0000000000 - 0.0000000000 - -40.4727840000 - 26.9818560000 - 0.0000000000 - 0.0000000000 - 30.3545880000 - -20.2363920000 - 0.0000000000 - 0.0000000000 - -6.7454640000 - 4.4969760000 - 0.0000000000 - 0.0000000000 - -2.9979840000 - 1.9986560000 - 0.0000000000 - 0.0000000000 - 8.9939520000 - -5.9959680000 - 0.0000000000 - 0.0000000000 - -6.7454640000 - 4.4969760000 - 0.0000000000 - 0.0000000000 - 1.4989920000 - -0.9993280000 - -7.9946240000 - 23.9838720000 - -17.9879040000 - 3.9973120000 - 23.9838720000 - -71.9516160000 - 53.9637120000 - -11.9919360000 - -17.9879040000 - 53.9637120000 - -40.4727840000 - 8.9939520000 - 3.9973120000 - -11.9919360000 - 8.9939520000 - -1.9986560000 - 23.9838720000 - -71.9516160000 - 53.9637120000 - -11.9919360000 - -71.9516160000 - 215.8548480000 - -161.8911360000 - 35.9758080000 - 53.9637120000 - -161.8911360000 - 121.4183520000 - -26.9818560000 - -11.9919360000 - 35.9758080000 - -26.9818560000 - 5.9959680000 - -17.9879040000 - 53.9637120000 - -40.4727840000 - 8.9939520000 - 53.9637120000 - -161.8911360000 - 121.4183520000 - -26.9818560000 - -40.4727840000 - 121.4183520000 - -91.0637640000 - 20.2363920000 - 8.9939520000 - -26.9818560000 - 20.2363920000 - -4.4969760000 - 3.9973120000 - -11.9919360000 - 8.9939520000 - -1.9986560000 - -11.9919360000 - 35.9758080000 - -26.9818560000 - 5.9959680000 - 8.9939520000 - -26.9818560000 - 20.2363920000 - -4.4969760000 - -1.9986560000 - 5.9959680000 - -4.4969760000 - 0.9993280000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -# Tij - -6 -0.0 -4.0 -0.0 -4.0 -0.0 -9.0 - - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -2.6355000000 - 1.7570000000 - 0.0000000000 - 0.0000000000 - 6.3252000000 - -4.2168000000 - 0.0000000000 - 0.0000000000 - -4.7439000000 - 3.1626000000 - 0.0000000000 - 0.0000000000 - 1.0542000000 - -0.7028000000 - 0.0000000000 - 0.0000000000 - 6.3252000000 - -4.2168000000 - 0.0000000000 - 0.0000000000 - -15.1804800000 - 10.1203200000 - 0.0000000000 - 0.0000000000 - 11.3853600000 - -7.5902400000 - 0.0000000000 - 0.0000000000 - -2.5300800000 - 1.6867200000 - 0.0000000000 - 0.0000000000 - -4.7439000000 - 3.1626000000 - 0.0000000000 - 0.0000000000 - 11.3853600000 - -7.5902400000 - 0.0000000000 - 0.0000000000 - -8.5390200000 - 5.6926800000 - 0.0000000000 - 0.0000000000 - 1.8975600000 - -1.2650400000 - 0.0000000000 - 0.0000000000 - 1.0542000000 - -0.7028000000 - 0.0000000000 - 0.0000000000 - -2.5300800000 - 1.6867200000 - 0.0000000000 - 0.0000000000 - 1.8975600000 - -1.2650400000 - 0.0000000000 - 0.0000000000 - -0.4216800000 - 0.2811200000 - 3.0080000000 - -9.3276000000 - 6.9957000000 - -1.5546000000 - -7.2192000000 - 22.3862400000 - -16.7896800000 - 3.7310400000 - 5.4144000000 - -16.7896800000 - 12.5922600000 - -2.7982800000 - -1.2032000000 - 3.7310400000 - -2.7982800000 - 0.6218400000 - -7.2192000000 - 22.3862400000 - -16.7896800000 - 3.7310400000 - 17.3260800000 - -53.7269760000 - 40.2952320000 - -8.9544960000 - -12.9945600000 - 40.2952320000 - -30.2214240000 - 6.7158720000 - 2.8876800000 - -8.9544960000 - 6.7158720000 - -1.4924160000 - 5.4144000000 - -16.7896800000 - 12.5922600000 - -2.7982800000 - -12.9945600000 - 40.2952320000 - -30.2214240000 - 6.7158720000 - 9.7459200000 - -30.2214240000 - 22.6660680000 - -5.0369040000 - -2.1657600000 - 6.7158720000 - -5.0369040000 - 1.1193120000 - -1.2032000000 - 3.7310400000 - -2.7982800000 - 0.6218400000 - 2.8876800000 - -8.9544960000 - 6.7158720000 - -1.4924160000 - -2.1657600000 - 6.7158720000 - -5.0369040000 - 1.1193120000 - 0.4812800000 - -1.4924160000 - 1.1193120000 - -0.2487360000 - -0.1012000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.2428800000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.1821600000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0404800000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.2428800000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.5829120000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.4371840000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.0971520000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.1821600000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.4371840000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.3278880000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0728640000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0404800000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.0971520000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0728640000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.0161920000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.1012000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.2428800000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.1821600000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0404800000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.2428800000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.5829120000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.4371840000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.0971520000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.1821600000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.4371840000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.3278880000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0728640000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0404800000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.0971520000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0728640000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.0161920000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.1012000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.2428800000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.1821600000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0404800000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.2428800000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.5829120000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.4371840000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.0971520000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.1821600000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.4371840000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.3278880000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0728640000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0404800000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.0971520000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0728640000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.0161920000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.1012000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.2428800000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.1821600000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0404800000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.2428800000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.5829120000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.4371840000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.0971520000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.1821600000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.4371840000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.3278880000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0728640000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0404800000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.0971520000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0728640000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.0161920000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.1012000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.2428800000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.1821600000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0404800000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.2428800000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.5829120000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.4371840000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.0971520000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.1821600000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.4371840000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.3278880000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0728640000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0404800000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.0971520000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0728640000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.0161920000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.1012000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.2428800000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.1821600000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0404800000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.2428800000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.5829120000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.4371840000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.0971520000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.1821600000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.4371840000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.3278880000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0728640000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0404800000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.0971520000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0728640000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.0161920000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.1012000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.2428800000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.1821600000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0404800000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.2428800000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.5829120000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.4371840000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.0971520000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.1821600000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.4371840000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.3278880000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0728640000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0404800000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.0971520000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0728640000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.0161920000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 14.2317000000 - -9.4878000000 - 0.0000000000 - 0.0000000000 - -18.9756000000 - 12.6504000000 - 0.0000000000 - 0.0000000000 - 7.9065000000 - -5.2710000000 - 0.0000000000 - 0.0000000000 - -1.0542000000 - 0.7028000000 - 0.0000000000 - 0.0000000000 - -34.1560800000 - 22.7707200000 - 0.0000000000 - 0.0000000000 - 45.5414400000 - -30.3609600000 - 0.0000000000 - 0.0000000000 - -18.9756000000 - 12.6504000000 - 0.0000000000 - 0.0000000000 - 2.5300800000 - -1.6867200000 - 0.0000000000 - 0.0000000000 - 25.6170600000 - -17.0780400000 - 0.0000000000 - 0.0000000000 - -34.1560800000 - 22.7707200000 - 0.0000000000 - 0.0000000000 - 14.2317000000 - -9.4878000000 - 0.0000000000 - 0.0000000000 - -1.8975600000 - 1.2650400000 - 0.0000000000 - 0.0000000000 - -5.6926800000 - 3.7951200000 - 0.0000000000 - 0.0000000000 - 7.5902400000 - -5.0601600000 - 0.0000000000 - 0.0000000000 - -3.1626000000 - 2.1084000000 - 0.0000000000 - 0.0000000000 - 0.4216800000 - -0.2811200000 - -16.2432000000 - 50.3690400000 - -37.7767800000 - 8.3948400000 - 21.6576000000 - -67.1587200000 - 50.3690400000 - -11.1931200000 - -9.0240000000 - 27.9828000000 - -20.9871000000 - 4.6638000000 - 1.2032000000 - -3.7310400000 - 2.7982800000 - -0.6218400000 - 38.9836800000 - -120.8856960000 - 90.6642720000 - -20.1476160000 - -51.9782400000 - 161.1809280000 - -120.8856960000 - 26.8634880000 - 21.6576000000 - -67.1587200000 - 50.3690400000 - -11.1931200000 - -2.8876800000 - 8.9544960000 - -6.7158720000 - 1.4924160000 - -29.2377600000 - 90.6642720000 - -67.9982040000 - 15.1107120000 - 38.9836800000 - -120.8856960000 - 90.6642720000 - -20.1476160000 - -16.2432000000 - 50.3690400000 - -37.7767800000 - 8.3948400000 - 2.1657600000 - -6.7158720000 - 5.0369040000 - -1.1193120000 - 6.4972800000 - -20.1476160000 - 15.1107120000 - -3.3579360000 - -8.6630400000 - 26.8634880000 - -20.1476160000 - 4.4772480000 - 3.6096000000 - -11.1931200000 - 8.3948400000 - -1.8655200000 - -0.4812800000 - 1.4924160000 - -1.1193120000 - 0.2487360000 - 0.5464800000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.7286400000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.3036000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.0404800000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -1.3115520000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 1.7487360000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.7286400000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0971520000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.9836640000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -1.3115520000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.5464800000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.0728640000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.2185920000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.2914560000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.1214400000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0161920000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.5464800000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.7286400000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.3036000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.0404800000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -1.3115520000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 1.7487360000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.7286400000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0971520000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.9836640000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -1.3115520000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.5464800000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.0728640000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.2185920000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.2914560000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.1214400000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0161920000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.5464800000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.7286400000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.3036000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.0404800000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -1.3115520000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 1.7487360000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.7286400000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0971520000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.9836640000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -1.3115520000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.5464800000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.0728640000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.2185920000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.2914560000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.1214400000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0161920000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.5464800000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.7286400000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.3036000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.0404800000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -1.3115520000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 1.7487360000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.7286400000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0971520000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.9836640000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -1.3115520000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.5464800000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.0728640000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.2185920000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.2914560000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.1214400000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0161920000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.5464800000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.7286400000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.3036000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.0404800000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -1.3115520000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 1.7487360000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.7286400000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0971520000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.9836640000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -1.3115520000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.5464800000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.0728640000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.2185920000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.2914560000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.1214400000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0161920000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.5464800000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.7286400000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.3036000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.0404800000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -1.3115520000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 1.7487360000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.7286400000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0971520000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.9836640000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -1.3115520000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.5464800000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.0728640000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.2185920000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.2914560000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.1214400000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0161920000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.5464800000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.7286400000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.3036000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.0404800000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -1.3115520000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 1.7487360000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.7286400000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0971520000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.9836640000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -1.3115520000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.5464800000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.0728640000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.2185920000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.2914560000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.1214400000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0161920000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 14.2317000000 - -9.4878000000 - 0.0000000000 - 0.0000000000 - -34.1560800000 - 22.7707200000 - 0.0000000000 - 0.0000000000 - 25.6170600000 - -17.0780400000 - 0.0000000000 - 0.0000000000 - -5.6926800000 - 3.7951200000 - 0.0000000000 - 0.0000000000 - -18.9756000000 - 12.6504000000 - 0.0000000000 - 0.0000000000 - 45.5414400000 - -30.3609600000 - 0.0000000000 - 0.0000000000 - -34.1560800000 - 22.7707200000 - 0.0000000000 - 0.0000000000 - 7.5902400000 - -5.0601600000 - 0.0000000000 - 0.0000000000 - 7.9065000000 - -5.2710000000 - 0.0000000000 - 0.0000000000 - -18.9756000000 - 12.6504000000 - 0.0000000000 - 0.0000000000 - 14.2317000000 - -9.4878000000 - 0.0000000000 - 0.0000000000 - -3.1626000000 - 2.1084000000 - 0.0000000000 - 0.0000000000 - -1.0542000000 - 0.7028000000 - 0.0000000000 - 0.0000000000 - 2.5300800000 - -1.6867200000 - 0.0000000000 - 0.0000000000 - -1.8975600000 - 1.2650400000 - 0.0000000000 - 0.0000000000 - 0.4216800000 - -0.2811200000 - -16.2432000000 - 50.3690400000 - -37.7767800000 - 8.3948400000 - 38.9836800000 - -120.8856960000 - 90.6642720000 - -20.1476160000 - -29.2377600000 - 90.6642720000 - -67.9982040000 - 15.1107120000 - 6.4972800000 - -20.1476160000 - 15.1107120000 - -3.3579360000 - 21.6576000000 - -67.1587200000 - 50.3690400000 - -11.1931200000 - -51.9782400000 - 161.1809280000 - -120.8856960000 - 26.8634880000 - 38.9836800000 - -120.8856960000 - 90.6642720000 - -20.1476160000 - -8.6630400000 - 26.8634880000 - -20.1476160000 - 4.4772480000 - -9.0240000000 - 27.9828000000 - -20.9871000000 - 4.6638000000 - 21.6576000000 - -67.1587200000 - 50.3690400000 - -11.1931200000 - -16.2432000000 - 50.3690400000 - -37.7767800000 - 8.3948400000 - 3.6096000000 - -11.1931200000 - 8.3948400000 - -1.8655200000 - 1.2032000000 - -3.7310400000 - 2.7982800000 - -0.6218400000 - -2.8876800000 - 8.9544960000 - -6.7158720000 - 1.4924160000 - 2.1657600000 - -6.7158720000 - 5.0369040000 - -1.1193120000 - -0.4812800000 - 1.4924160000 - -1.1193120000 - 0.2487360000 - 0.5464800000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -1.3115520000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.9836640000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.2185920000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.7286400000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 1.7487360000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -1.3115520000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.2914560000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.3036000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.7286400000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.5464800000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.1214400000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.0404800000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0971520000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.0728640000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0161920000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.5464800000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -1.3115520000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.9836640000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.2185920000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.7286400000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 1.7487360000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -1.3115520000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.2914560000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.3036000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.7286400000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.5464800000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.1214400000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.0404800000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0971520000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.0728640000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0161920000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.5464800000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -1.3115520000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.9836640000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.2185920000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.7286400000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 1.7487360000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -1.3115520000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.2914560000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.3036000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.7286400000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.5464800000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.1214400000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.0404800000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0971520000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.0728640000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0161920000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.5464800000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -1.3115520000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.9836640000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.2185920000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.7286400000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 1.7487360000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -1.3115520000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.2914560000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.3036000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.7286400000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.5464800000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.1214400000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.0404800000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0971520000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.0728640000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0161920000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.5464800000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -1.3115520000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.9836640000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.2185920000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.7286400000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 1.7487360000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -1.3115520000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.2914560000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.3036000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.7286400000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.5464800000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.1214400000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.0404800000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0971520000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.0728640000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0161920000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.5464800000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -1.3115520000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.9836640000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.2185920000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.7286400000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 1.7487360000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -1.3115520000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.2914560000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.3036000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.7286400000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.5464800000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.1214400000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.0404800000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0971520000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.0728640000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0161920000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.5464800000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -1.3115520000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.9836640000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.2185920000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.7286400000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 1.7487360000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -1.3115520000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.2914560000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.3036000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.7286400000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.5464800000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.1214400000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.0404800000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0971520000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.0728640000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0161920000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -76.8511800000 - 51.2341200000 - 0.0000000000 - 0.0000000000 - 102.4682400000 - -68.3121600000 - 0.0000000000 - 0.0000000000 - -42.6951000000 - 28.4634000000 - 0.0000000000 - 0.0000000000 - 5.6926800000 - -3.7951200000 - 0.0000000000 - 0.0000000000 - 102.4682400000 - -68.3121600000 - 0.0000000000 - 0.0000000000 - -136.6243200000 - 91.0828800000 - 0.0000000000 - 0.0000000000 - 56.9268000000 - -37.9512000000 - 0.0000000000 - 0.0000000000 - -7.5902400000 - 5.0601600000 - 0.0000000000 - 0.0000000000 - -42.6951000000 - 28.4634000000 - 0.0000000000 - 0.0000000000 - 56.9268000000 - -37.9512000000 - 0.0000000000 - 0.0000000000 - -23.7195000000 - 15.8130000000 - 0.0000000000 - 0.0000000000 - 3.1626000000 - -2.1084000000 - 0.0000000000 - 0.0000000000 - 5.6926800000 - -3.7951200000 - 0.0000000000 - 0.0000000000 - -7.5902400000 - 5.0601600000 - 0.0000000000 - 0.0000000000 - 3.1626000000 - -2.1084000000 - 0.0000000000 - 0.0000000000 - -0.4216800000 - 0.2811200000 - 87.7132800000 - -271.9928159999 - 203.9946120000 - -45.3321360000 - -116.9510400000 - 362.6570879999 - -271.9928159999 - 60.4428480000 - 48.7296000000 - -151.1071200000 - 113.3303400000 - -25.1845200000 - -6.4972800000 - 20.1476160000 - -15.1107120000 - 3.3579360000 - -116.9510400000 - 362.6570880000 - -271.9928160000 - 60.4428480000 - 155.9347200000 - -483.5427840000 - 362.6570880000 - -80.5904640000 - -64.9728000000 - 201.4761600000 - -151.1071200000 - 33.5793600000 - 8.6630400000 - -26.8634880000 - 20.1476160000 - -4.4772480000 - 48.7296000000 - -151.1071200000 - 113.3303400000 - -25.1845200000 - -64.9728000000 - 201.4761600000 - -151.1071200000 - 33.5793600000 - 27.0720000000 - -83.9484000000 - 62.9613000000 - -13.9914000000 - -3.6096000000 - 11.1931200000 - -8.3948400000 - 1.8655200000 - -6.4972800000 - 20.1476160000 - -15.1107120000 - 3.3579360000 - 8.6630400000 - -26.8634880000 - 20.1476160000 - -4.4772480000 - -3.6096000000 - 11.1931200000 - -8.3948400000 - 1.8655200000 - 0.4812800000 - -1.4924160000 - 1.1193120000 - -0.2487360000 - -2.9509920000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 3.9346560000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -1.6394400000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.2185920000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 3.9346560000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -5.2462080000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 2.1859200000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.2914560000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -1.6394400000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 2.1859200000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.9108000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.1214400000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.2185920000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.2914560000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.1214400000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.0161920000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -2.9509920000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 3.9346560000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -1.6394400000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.2185920000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 3.9346560000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -5.2462080000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 2.1859200000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.2914560000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -1.6394400000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 2.1859200000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.9108000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.1214400000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.2185920000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.2914560000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.1214400000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.0161920000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -2.9509920000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 3.9346560000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -1.6394400000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.2185920000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 3.9346560000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -5.2462080000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 2.1859200000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.2914560000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -1.6394400000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 2.1859200000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.9108000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.1214400000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.2185920000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.2914560000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.1214400000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.0161920000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -2.9509920000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 3.9346560000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -1.6394400000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.2185920000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 3.9346560000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -5.2462080000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 2.1859200000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.2914560000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -1.6394400000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 2.1859200000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.9108000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.1214400000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.2185920000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.2914560000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.1214400000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.0161920000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -2.9509920000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 3.9346560000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -1.6394400000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.2185920000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 3.9346560000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -5.2462080000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 2.1859200000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.2914560000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -1.6394400000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 2.1859200000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.9108000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.1214400000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.2185920000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.2914560000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.1214400000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.0161920000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -2.9509920000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 3.9346560000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -1.6394400000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.2185920000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 3.9346560000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -5.2462080000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 2.1859200000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.2914560000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -1.6394400000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 2.1859200000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.9108000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.1214400000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.2185920000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.2914560000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.1214400000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.0161920000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -2.9509920000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 3.9346560000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -1.6394400000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.2185920000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 3.9346560000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -5.2462080000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 2.1859200000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.2914560000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -1.6394400000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 2.1859200000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.9108000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.1214400000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.2185920000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.2914560000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.1214400000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - -0.0161920000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 - 0.0000000000 diff --git a/bench/POTENTIALS/CH.airebo b/bench/POTENTIALS/CH.airebo new file mode 120000 index 0000000000..60249102a5 --- /dev/null +++ b/bench/POTENTIALS/CH.airebo @@ -0,0 +1 @@ +../../potentials/CH.airebo \ No newline at end of file diff --git a/bench/POTENTIALS/CdTe.bop.table b/bench/POTENTIALS/CdTe.bop.table deleted file mode 100644 index 83f1c2b750..0000000000 --- a/bench/POTENTIALS/CdTe.bop.table +++ /dev/null @@ -1,4833 +0,0 @@ -### DATE: 2012-06-25 CONTRIBUTOR: Don Ward, donward@sandia.gov CITATION: Ward, Zhou, Wong, Doty, and Zimmerman, Phys Rev B, 85, 115206 (2012) - 2 - 48 0.11241180E+03 Cd - 52 0.12760300E+03 Te - 2000 2000 - 0.10E-04 0.10E-04 0.10E-04 0.10E-04 0.10E-04 0.10E-02 0.10E-04 - 0.42000000E+00 - 0.46068630E+00 - 0.43330000E+01 - 0.56112980E+00 0.00000000E+00 0.10000000E+01 0.10000000E+01 - 0.00000000E+00 0.00000000E+00 - 0.43186280E+00 0.15000000E+02 0.10000000E+07 - 0.44465000E+01 - 0.10148090E+01 0.00000000E+00 0.10000000E+01 0.10000000E+01 - 0.00000000E+00 0.00000000E+00 - 0.33122690E+00 -0.28601900E+01 0.10000000E+07 - 0.49000000E+01 - 0.12869550E+01 0.00000000E+00 0.10000000E+01 0.10000000E+01 - 0.00000000E+00 0.00000000E+00 - 0.50000000E+00 0.00000000E+00 0.10000000E+07 - 0.39687010E+00 0.88101950E+00 -0.27788970E+00 - -0.10071280E+00 0.10000000E+01 0.10071280E+00 - 0.20952380E+00 0.60000000E+00 0.19047620E+00 - 0.39284960E-02 0.99992720E+00 -0.38556650E-02 - -0.10071280E+00 0.10000000E+01 0.10071280E+00 - 0.20073220E+00 0.60000000E+00 0.19926780E+00 - 0.39284960E-02 0.99992720E+00 -0.38556650E-02 - 0.11718170E+00 0.83481160E+00 0.48006700E-01 - 0.37236414E+06 0.37236414E+06 0.37236414E+06 0.37236414E+06 0.37236414E+06 - 0.37236414E+06 0.37236414E+06 0.37236414E+06 0.37236414E+06 0.37236414E+06 - 0.37236414E+06 0.37236414E+06 0.37236414E+06 0.37236414E+06 0.37236414E+06 - 0.37236414E+06 0.37236414E+06 0.37236414E+06 0.37236414E+06 0.37236414E+06 - 0.37236414E+06 0.37236414E+06 0.37236414E+06 0.37236414E+06 0.37236414E+06 - 0.37236414E+06 0.37236414E+06 0.37236414E+06 0.37236414E+06 0.37236414E+06 - 0.37236414E+06 0.37236414E+06 0.37236414E+06 0.37236414E+06 0.37236414E+06 - 0.37236414E+06 0.37236414E+06 0.37236414E+06 0.37236414E+06 0.37236414E+06 - 0.37236414E+06 0.37236414E+06 0.37236414E+06 0.37236414E+06 0.37236414E+06 - 0.37236414E+06 0.37236414E+06 0.35044271E+06 0.32717105E+06 0.30587762E+06 - 0.28635889E+06 0.26843578E+06 0.25195028E+06 0.23676268E+06 0.22274912E+06 - 0.20979957E+06 0.19781604E+06 0.18671109E+06 0.17640656E+06 0.16683242E+06 - 0.15792578E+06 0.14963014E+06 0.14189457E+06 0.13467311E+06 0.12792424E+06 - 0.12161035E+06 0.11569735E+06 0.11015428E+06 0.10495298E+06 0.10006781E+06 - 0.95475381E+05 0.91154339E+05 0.87085159E+05 0.83249960E+05 0.79632356E+05 - 0.76217307E+05 0.72990993E+05 0.69940704E+05 0.67054733E+05 0.64322291E+05 - 0.61733417E+05 0.59278915E+05 0.56950278E+05 0.54739633E+05 0.52639687E+05 - 0.50643676E+05 0.48745323E+05 0.46938796E+05 0.45218674E+05 0.43579912E+05 - 0.42017812E+05 0.40527994E+05 0.39106374E+05 0.37749140E+05 0.36452730E+05 - 0.35213814E+05 0.34029276E+05 0.32896201E+05 0.31811857E+05 0.30773682E+05 - 0.29779273E+05 0.28826376E+05 0.27912873E+05 0.27036771E+05 0.26196199E+05 - 0.25389395E+05 0.24614700E+05 0.23870552E+05 0.23155477E+05 0.22468085E+05 - 0.21807067E+05 0.21171183E+05 0.20559266E+05 0.19970209E+05 0.19402967E+05 - 0.18856552E+05 0.18330028E+05 0.17822510E+05 0.17333156E+05 0.16861172E+05 - 0.16405802E+05 0.15966332E+05 0.15542080E+05 0.15132402E+05 0.14736685E+05 - 0.14354347E+05 0.13984833E+05 0.13627616E+05 0.13282196E+05 0.12948096E+05 - 0.12624860E+05 0.12312056E+05 0.12009273E+05 0.11716116E+05 0.11432210E+05 - 0.11157198E+05 0.10890739E+05 0.10632507E+05 0.10382190E+05 0.10139491E+05 - 0.99041265E+04 0.96758242E+04 0.94543246E+04 0.92393793E+04 0.90307506E+04 - 0.88282110E+04 0.86315426E+04 0.84405368E+04 0.82549938E+04 0.80747220E+04 - 0.78995378E+04 0.77292653E+04 0.75637356E+04 0.74027867E+04 0.72462631E+04 - 0.70940158E+04 0.69459014E+04 0.68017824E+04 0.66615266E+04 0.65250071E+04 - 0.63921017E+04 0.62626932E+04 0.61366686E+04 0.60139195E+04 0.58943415E+04 - 0.57778341E+04 0.56643006E+04 0.55536478E+04 0.54457861E+04 0.53406292E+04 - 0.52380938E+04 0.51380999E+04 0.50405700E+04 0.49454298E+04 0.48526073E+04 - 0.47620334E+04 0.46736412E+04 0.45873662E+04 0.45031463E+04 0.44209212E+04 - 0.43406332E+04 0.42622262E+04 0.41856460E+04 0.41108406E+04 0.40377594E+04 - 0.39663536E+04 0.38965762E+04 0.38283815E+04 0.37617256E+04 0.36965657E+04 - 0.36328608E+04 0.35705709E+04 0.35096574E+04 0.34500831E+04 0.33918118E+04 - 0.33348085E+04 0.32790394E+04 0.32244716E+04 0.31710735E+04 0.31188142E+04 - 0.30676640E+04 0.30175939E+04 0.29685760E+04 0.29205830E+04 0.28735888E+04 - 0.28275679E+04 0.27824953E+04 0.27383473E+04 0.26951004E+04 0.26527322E+04 - 0.26112207E+04 0.25705447E+04 0.25306834E+04 0.24916170E+04 0.24533258E+04 - 0.24157912E+04 0.23789946E+04 0.23429183E+04 0.23075450E+04 0.22728578E+04 - 0.22388405E+04 0.22054771E+04 0.21727523E+04 0.21406509E+04 0.21091585E+04 - 0.20782609E+04 0.20479442E+04 0.20181951E+04 0.19890006E+04 0.19603478E+04 - 0.19322246E+04 0.19046188E+04 0.18775188E+04 0.18509132E+04 0.18247910E+04 - 0.17991414E+04 0.17739538E+04 0.17492181E+04 0.17249242E+04 0.17010626E+04 - 0.16776238E+04 0.16545986E+04 0.16319780E+04 0.16097533E+04 0.15879160E+04 - 0.15664577E+04 0.15453706E+04 0.15246465E+04 0.15042780E+04 0.14842575E+04 - 0.14645776E+04 0.14452313E+04 0.14262117E+04 0.14075120E+04 0.13891255E+04 - 0.13710458E+04 0.13532667E+04 0.13357820E+04 0.13185858E+04 0.13016721E+04 - 0.12850354E+04 0.12686699E+04 0.12525704E+04 0.12367315E+04 0.12211480E+04 - 0.12058148E+04 0.11907271E+04 0.11758800E+04 0.11612688E+04 0.11468889E+04 - 0.11327358E+04 0.11188052E+04 0.11050927E+04 0.10915941E+04 0.10783053E+04 - 0.10652225E+04 0.10523415E+04 0.10396586E+04 0.10271702E+04 0.10148724E+04 - 0.10027618E+04 0.99083481E+03 0.97908807E+03 0.96751823E+03 0.95612200E+03 - 0.94489621E+03 0.93383772E+03 0.92294347E+03 0.91221048E+03 0.90163580E+03 - 0.89121659E+03 0.88095004E+03 0.87083339E+03 0.86086398E+03 0.85103917E+03 - 0.84135639E+03 0.83181312E+03 0.82240689E+03 0.81313530E+03 0.80399598E+03 - 0.79498662E+03 0.78610494E+03 0.77734874E+03 0.76871584E+03 0.76020410E+03 - 0.75181145E+03 0.74353585E+03 0.73537528E+03 0.72732780E+03 0.71939147E+03 - 0.71156443E+03 0.70384481E+03 0.69623083E+03 0.68872070E+03 0.68131268E+03 - 0.67400509E+03 0.66679624E+03 0.65968451E+03 0.65266828E+03 0.64574600E+03 - 0.63891611E+03 0.63217711E+03 0.62552752E+03 0.61896587E+03 0.61249075E+03 - 0.60610076E+03 0.59979453E+03 0.59357071E+03 0.58742798E+03 0.58136506E+03 - 0.57538066E+03 0.56947354E+03 0.56364249E+03 0.55788630E+03 0.55220379E+03 - 0.54659381E+03 0.54105523E+03 0.53558694E+03 0.53018783E+03 0.52485685E+03 - 0.51959293E+03 0.51439505E+03 0.50926219E+03 0.50419335E+03 0.49918756E+03 - 0.49424386E+03 0.48936131E+03 0.48453897E+03 0.47977595E+03 0.47507134E+03 - 0.47042428E+03 0.46583389E+03 0.46129935E+03 0.45681980E+03 0.45239444E+03 - 0.44802247E+03 0.44370310E+03 0.43943555E+03 0.43521907E+03 0.43105290E+03 - 0.42693631E+03 0.42286859E+03 0.41884902E+03 0.41487690E+03 0.41095155E+03 - 0.40707230E+03 0.40323848E+03 0.39944945E+03 0.39570456E+03 0.39200319E+03 - 0.38834471E+03 0.38472853E+03 0.38115404E+03 0.37762066E+03 0.37412781E+03 - 0.37067491E+03 0.36726142E+03 0.36388678E+03 0.36055046E+03 0.35725192E+03 - 0.35399063E+03 0.35076609E+03 0.34757780E+03 0.34442524E+03 0.34130794E+03 - 0.33822541E+03 0.33517717E+03 0.33216277E+03 0.32918175E+03 0.32623365E+03 - 0.32331803E+03 0.32043445E+03 0.31758249E+03 0.31476171E+03 0.31197171E+03 - 0.30921208E+03 0.30648241E+03 0.30378230E+03 0.30111137E+03 0.29846923E+03 - 0.29585550E+03 0.29326982E+03 0.29071180E+03 0.28818110E+03 0.28567735E+03 - 0.28320021E+03 0.28074933E+03 0.27832438E+03 0.27592501E+03 0.27355091E+03 - 0.27120174E+03 0.26887719E+03 0.26657694E+03 0.26430068E+03 0.26204812E+03 - 0.25981894E+03 0.25761285E+03 0.25542957E+03 0.25326880E+03 0.25113027E+03 - 0.24901368E+03 0.24691878E+03 0.24484529E+03 0.24279294E+03 0.24076148E+03 - 0.23875063E+03 0.23676016E+03 0.23478980E+03 0.23283931E+03 0.23090845E+03 - 0.22899698E+03 0.22710465E+03 0.22523125E+03 0.22337653E+03 0.22154027E+03 - 0.21972225E+03 0.21792225E+03 0.21614004E+03 0.21437543E+03 0.21262819E+03 - 0.21089812E+03 0.20918501E+03 0.20748867E+03 0.20580888E+03 0.20414547E+03 - 0.20249822E+03 0.20086696E+03 0.19925150E+03 0.19765164E+03 0.19606721E+03 - 0.19449802E+03 0.19294390E+03 0.19140468E+03 0.18988017E+03 0.18837021E+03 - 0.18687464E+03 0.18539328E+03 0.18392596E+03 0.18247254E+03 0.18103285E+03 - 0.17960673E+03 0.17819403E+03 0.17679460E+03 0.17540828E+03 0.17403493E+03 - 0.17267440E+03 0.17132654E+03 0.16999121E+03 0.16866827E+03 0.16735759E+03 - 0.16605902E+03 0.16477243E+03 0.16349769E+03 0.16223466E+03 0.16098321E+03 - 0.15974322E+03 0.15851456E+03 0.15729710E+03 0.15609072E+03 0.15489530E+03 - 0.15371072E+03 0.15253686E+03 0.15137361E+03 0.15022084E+03 0.14907844E+03 - 0.14794631E+03 0.14682432E+03 0.14571237E+03 0.14461036E+03 0.14351817E+03 - 0.14243570E+03 0.14136285E+03 0.14029950E+03 0.13924557E+03 0.13820095E+03 - 0.13716554E+03 0.13613924E+03 0.13512196E+03 0.13411360E+03 0.13311407E+03 - 0.13212327E+03 0.13114112E+03 0.13016752E+03 0.12920238E+03 0.12824561E+03 - 0.12729713E+03 0.12635685E+03 0.12542469E+03 0.12450056E+03 0.12358438E+03 - 0.12267606E+03 0.12177553E+03 0.12088270E+03 0.11999750E+03 0.11911984E+03 - 0.11824966E+03 0.11738687E+03 0.11653140E+03 0.11568318E+03 0.11484213E+03 - 0.11400817E+03 0.11318124E+03 0.11236127E+03 0.11154818E+03 0.11074191E+03 - 0.10994239E+03 0.10914954E+03 0.10836332E+03 0.10758364E+03 0.10681044E+03 - 0.10604366E+03 0.10528323E+03 0.10452910E+03 0.10378119E+03 0.10303946E+03 - 0.10230383E+03 0.10157424E+03 0.10085065E+03 0.10013298E+03 0.99421188E+02 - 0.98715207E+02 0.98014984E+02 0.97320461E+02 0.96631585E+02 0.95948300E+02 - 0.95270552E+02 0.94598288E+02 0.93931454E+02 0.93270000E+02 0.92613872E+02 - 0.91963020E+02 0.91317394E+02 0.90676943E+02 0.90041619E+02 0.89411372E+02 - 0.88786155E+02 0.88165919E+02 0.87550618E+02 0.86940204E+02 0.86334632E+02 - 0.85733857E+02 0.85137832E+02 0.84546514E+02 0.83959859E+02 0.83377822E+02 - 0.82800361E+02 0.82227433E+02 0.81658996E+02 0.81095009E+02 0.80535429E+02 - 0.79980217E+02 0.79429331E+02 0.78882733E+02 0.78340382E+02 0.77802240E+02 - 0.77268268E+02 0.76738428E+02 0.76212681E+02 0.75690991E+02 0.75173321E+02 - 0.74659634E+02 0.74149894E+02 0.73644065E+02 0.73142112E+02 0.72644000E+02 - 0.72149693E+02 0.71659159E+02 0.71172363E+02 0.70689271E+02 0.70209850E+02 - 0.69734068E+02 0.69261891E+02 0.68793289E+02 0.68328228E+02 0.67866678E+02 - 0.67408607E+02 0.66953985E+02 0.66502780E+02 0.66054964E+02 0.65610506E+02 - 0.65169376E+02 0.64731545E+02 0.64296985E+02 0.63865666E+02 0.63437561E+02 - 0.63012641E+02 0.62590879E+02 0.62172246E+02 0.61756717E+02 0.61344263E+02 - 0.60934859E+02 0.60528478E+02 0.60125094E+02 0.59724681E+02 0.59327213E+02 - 0.58932666E+02 0.58541014E+02 0.58152232E+02 0.57766296E+02 0.57383182E+02 - 0.57002865E+02 0.56625322E+02 0.56250529E+02 0.55878463E+02 0.55509100E+02 - 0.55142419E+02 0.54778396E+02 0.54417008E+02 0.54058235E+02 0.53702053E+02 - 0.53348440E+02 0.52997377E+02 0.52648840E+02 0.52302810E+02 0.51959264E+02 - 0.51618183E+02 0.51279546E+02 0.50943332E+02 0.50609522E+02 0.50278096E+02 - 0.49949033E+02 0.49622315E+02 0.49297922E+02 0.48975835E+02 0.48656035E+02 - 0.48338503E+02 0.48023221E+02 0.47710171E+02 0.47399333E+02 0.47090690E+02 - 0.46784225E+02 0.46479919E+02 0.46177755E+02 0.45877715E+02 0.45579783E+02 - 0.45283941E+02 0.44990173E+02 0.44698461E+02 0.44408790E+02 0.44121142E+02 - 0.43835502E+02 0.43551854E+02 0.43270181E+02 0.42990467E+02 0.42712698E+02 - 0.42436858E+02 0.42162931E+02 0.41890901E+02 0.41620755E+02 0.41352477E+02 - 0.41086052E+02 0.40821466E+02 0.40558705E+02 0.40297753E+02 0.40038596E+02 - 0.39781221E+02 0.39525614E+02 0.39271760E+02 0.39019646E+02 0.38769258E+02 - 0.38520584E+02 0.38273609E+02 0.38028320E+02 0.37784704E+02 0.37542749E+02 - 0.37302441E+02 0.37063767E+02 0.36826716E+02 0.36591274E+02 0.36357429E+02 - 0.36125169E+02 0.35894482E+02 0.35665355E+02 0.35437776E+02 0.35211735E+02 - 0.34987218E+02 0.34764214E+02 0.34542713E+02 0.34322702E+02 0.34104170E+02 - 0.33887105E+02 0.33671497E+02 0.33457335E+02 0.33244608E+02 0.33033305E+02 - 0.32823414E+02 0.32614926E+02 0.32407830E+02 0.32202116E+02 0.31997772E+02 - 0.31794790E+02 0.31593158E+02 0.31392867E+02 0.31193906E+02 0.30996266E+02 - 0.30799936E+02 0.30604908E+02 0.30411171E+02 0.30218715E+02 0.30027533E+02 - 0.29837613E+02 0.29648946E+02 0.29461524E+02 0.29275337E+02 0.29090376E+02 - 0.28906632E+02 0.28724096E+02 0.28542759E+02 0.28362612E+02 0.28183648E+02 - 0.28005856E+02 0.27829229E+02 0.27653758E+02 0.27479435E+02 0.27306251E+02 - 0.27134198E+02 0.26963267E+02 0.26793451E+02 0.26624742E+02 0.26457132E+02 - 0.26290612E+02 0.26125175E+02 0.25960813E+02 0.25797518E+02 0.25635283E+02 - 0.25474099E+02 0.25313960E+02 0.25154858E+02 0.24996786E+02 0.24839736E+02 - 0.24683701E+02 0.24528673E+02 0.24374646E+02 0.24221612E+02 0.24069565E+02 - 0.23918496E+02 0.23768401E+02 0.23619270E+02 0.23471099E+02 0.23323879E+02 - 0.23177605E+02 0.23032269E+02 0.22887865E+02 0.22744386E+02 0.22601826E+02 - 0.22460179E+02 0.22319438E+02 0.22179596E+02 0.22040648E+02 0.21902587E+02 - 0.21765407E+02 0.21629102E+02 0.21493665E+02 0.21359092E+02 0.21225375E+02 - 0.21092508E+02 0.20960487E+02 0.20829305E+02 0.20698956E+02 0.20569434E+02 - 0.20440734E+02 0.20312851E+02 0.20185777E+02 0.20059509E+02 0.19934040E+02 - 0.19809365E+02 0.19685479E+02 0.19562375E+02 0.19440049E+02 0.19318496E+02 - 0.19197710E+02 0.19077685E+02 0.18958417E+02 0.18839901E+02 0.18722131E+02 - 0.18605103E+02 0.18488811E+02 0.18373250E+02 0.18258415E+02 0.18144302E+02 - 0.18030906E+02 0.17918221E+02 0.17806244E+02 0.17694968E+02 0.17584390E+02 - 0.17474505E+02 0.17365308E+02 0.17256794E+02 0.17148959E+02 0.17041799E+02 - 0.16935308E+02 0.16829483E+02 0.16724319E+02 0.16619811E+02 0.16515956E+02 - 0.16412748E+02 0.16310184E+02 0.16208258E+02 0.16106968E+02 0.16006309E+02 - 0.15906276E+02 0.15806866E+02 0.15708074E+02 0.15609896E+02 0.15512328E+02 - 0.15415367E+02 0.15319007E+02 0.15223246E+02 0.15128079E+02 0.15033502E+02 - 0.14939512E+02 0.14846104E+02 0.14753276E+02 0.14661022E+02 0.14569339E+02 - 0.14478224E+02 0.14387673E+02 0.14297681E+02 0.14208247E+02 0.14119365E+02 - 0.14031032E+02 0.13943245E+02 0.13856000E+02 0.13769294E+02 0.13683122E+02 - 0.13597483E+02 0.13512371E+02 0.13427784E+02 0.13343719E+02 0.13260172E+02 - 0.13177139E+02 0.13094618E+02 0.13012605E+02 0.12931096E+02 0.12850089E+02 - 0.12769580E+02 0.12689567E+02 0.12610045E+02 0.12531012E+02 0.12452465E+02 - 0.12374400E+02 0.12296815E+02 0.12219706E+02 0.12143070E+02 0.12066905E+02 - 0.11991207E+02 0.11915973E+02 0.11841201E+02 0.11766887E+02 0.11693028E+02 - 0.11619623E+02 0.11546667E+02 0.11474157E+02 0.11402092E+02 0.11330469E+02 - 0.11259283E+02 0.11188534E+02 0.11118217E+02 0.11048330E+02 0.10978871E+02 - 0.10909837E+02 0.10841225E+02 0.10773032E+02 0.10705256E+02 0.10637894E+02 - 0.10570944E+02 0.10504403E+02 0.10438268E+02 0.10372537E+02 0.10307208E+02 - 0.10242277E+02 0.10177743E+02 0.10113602E+02 0.10049853E+02 0.99864932E+01 - 0.99235197E+01 0.98609302E+01 0.97987224E+01 0.97368940E+01 0.96754426E+01 - 0.96143658E+01 0.95536613E+01 0.94933268E+01 0.94333599E+01 0.93737585E+01 - 0.93145203E+01 0.92556429E+01 0.91971242E+01 0.91389620E+01 0.90811539E+01 - 0.90236980E+01 0.89665918E+01 0.89098334E+01 0.88534206E+01 0.87973512E+01 - 0.87416231E+01 0.86862342E+01 0.86311824E+01 0.85764657E+01 0.85220820E+01 - 0.84680292E+01 0.84143053E+01 0.83609083E+01 0.83078362E+01 0.82550869E+01 - 0.82026586E+01 0.81505492E+01 0.80987569E+01 0.80472795E+01 0.79961153E+01 - 0.79452623E+01 0.78947186E+01 0.78444824E+01 0.77945517E+01 0.77449246E+01 - 0.76955994E+01 0.76465742E+01 0.75978471E+01 0.75494164E+01 0.75012803E+01 - 0.74534368E+01 0.74058844E+01 0.73586212E+01 0.73116454E+01 0.72649553E+01 - 0.72185492E+01 0.71724254E+01 0.71265820E+01 0.70810176E+01 0.70357302E+01 - 0.69907184E+01 0.69459804E+01 0.69015145E+01 0.68573191E+01 0.68133926E+01 - 0.67697333E+01 0.67263397E+01 0.66832101E+01 0.66403429E+01 0.65977366E+01 - 0.65553896E+01 0.65133003E+01 0.64714672E+01 0.64298887E+01 0.63885633E+01 - 0.63474895E+01 0.63066658E+01 0.62660906E+01 0.62257625E+01 0.61856799E+01 - 0.61458415E+01 0.61062457E+01 0.60668911E+01 0.60277763E+01 0.59888998E+01 - 0.59502601E+01 0.59118559E+01 0.58736858E+01 0.58357483E+01 0.57980420E+01 - 0.57605657E+01 0.57233178E+01 0.56862971E+01 0.56495022E+01 0.56129317E+01 - 0.55765843E+01 0.55404586E+01 0.55045534E+01 0.54688673E+01 0.54333990E+01 - 0.53981473E+01 0.53631107E+01 0.53282881E+01 0.52936782E+01 0.52592797E+01 - 0.52250913E+01 0.51911118E+01 0.51573400E+01 0.51237746E+01 0.50904143E+01 - 0.50572581E+01 0.50243046E+01 0.49915527E+01 0.49590011E+01 0.49266486E+01 - 0.48944942E+01 0.48625366E+01 0.48307746E+01 0.47992071E+01 0.47678329E+01 - 0.47366509E+01 0.47056599E+01 0.46748589E+01 0.46442466E+01 0.46138220E+01 - 0.45835840E+01 0.45535314E+01 0.45236632E+01 0.44939782E+01 0.44644754E+01 - 0.44351536E+01 0.44060120E+01 0.43770492E+01 0.43482644E+01 0.43196565E+01 - 0.42912243E+01 0.42629669E+01 0.42348832E+01 0.42069723E+01 0.41792330E+01 - 0.41516644E+01 0.41242655E+01 0.40970352E+01 0.40699726E+01 0.40430767E+01 - 0.40163465E+01 0.39897810E+01 0.39633792E+01 0.39371402E+01 0.39110630E+01 - 0.38851467E+01 0.38593903E+01 0.38337929E+01 0.38083535E+01 0.37830712E+01 - 0.37579451E+01 0.37329743E+01 0.37081578E+01 0.36834947E+01 0.36589841E+01 - 0.36346252E+01 0.36104170E+01 0.35863586E+01 0.35624492E+01 0.35386879E+01 - 0.35150739E+01 0.34916061E+01 0.34682838E+01 0.34451062E+01 0.34220724E+01 - 0.33991814E+01 0.33764326E+01 0.33538250E+01 0.33313578E+01 0.33090302E+01 - 0.32868414E+01 0.32647906E+01 0.32428769E+01 0.32210995E+01 0.31994576E+01 - 0.31779505E+01 0.31565773E+01 0.31353373E+01 0.31142296E+01 0.30932536E+01 - 0.30724083E+01 0.30516931E+01 0.30311071E+01 0.30106497E+01 0.29903201E+01 - 0.29701174E+01 0.29500410E+01 0.29300901E+01 0.29102640E+01 0.28905619E+01 - 0.28709832E+01 0.28515270E+01 0.28321927E+01 0.28129796E+01 0.27938868E+01 - 0.27749138E+01 0.27560599E+01 0.27373242E+01 0.27187061E+01 0.27002050E+01 - 0.26818201E+01 0.26635508E+01 0.26453963E+01 0.26273561E+01 0.26094293E+01 - 0.25916154E+01 0.25739137E+01 0.25563236E+01 0.25388443E+01 0.25214752E+01 - 0.25042156E+01 0.24870650E+01 0.24700227E+01 0.24530880E+01 0.24362603E+01 - 0.24195390E+01 0.24029234E+01 0.23864129E+01 0.23700069E+01 0.23537048E+01 - 0.23375060E+01 0.23214098E+01 0.23054157E+01 0.22895231E+01 0.22737312E+01 - 0.22580397E+01 0.22424478E+01 0.22269549E+01 0.22115606E+01 0.21962641E+01 - 0.21810650E+01 0.21659626E+01 0.21509564E+01 0.21360458E+01 0.21212303E+01 - 0.21065092E+01 0.20918821E+01 0.20773483E+01 0.20629073E+01 0.20485586E+01 - 0.20343016E+01 0.20201357E+01 0.20060605E+01 0.19920754E+01 0.19781798E+01 - 0.19643733E+01 0.19506552E+01 0.19370252E+01 0.19234825E+01 0.19100268E+01 - 0.18966576E+01 0.18833742E+01 0.18701762E+01 0.18570631E+01 0.18440344E+01 - 0.18310896E+01 0.18182281E+01 0.18054495E+01 0.17927533E+01 0.17801390E+01 - 0.17676061E+01 0.17551542E+01 0.17427827E+01 0.17304911E+01 0.17182791E+01 - 0.17061460E+01 0.16940915E+01 0.16821151E+01 0.16702163E+01 0.16583946E+01 - 0.16466496E+01 0.16349809E+01 0.16233879E+01 0.16118702E+01 0.16004274E+01 - 0.15890590E+01 0.15777646E+01 0.15665437E+01 0.15553959E+01 0.15443208E+01 - 0.15333179E+01 0.15223868E+01 0.15115270E+01 0.15007382E+01 0.14900199E+01 - 0.14793716E+01 0.14687930E+01 0.14582837E+01 0.14478432E+01 0.14374711E+01 - 0.14271670E+01 0.14169304E+01 0.14067611E+01 0.13966586E+01 0.13866224E+01 - 0.13766522E+01 0.13667476E+01 0.13569082E+01 0.13471336E+01 0.13374234E+01 - 0.13277772E+01 0.13181947E+01 0.13086753E+01 0.12992189E+01 0.12898249E+01 - 0.12804931E+01 0.12712229E+01 0.12620142E+01 0.12528664E+01 0.12437792E+01 - 0.12347523E+01 0.12257853E+01 0.12168778E+01 0.12080294E+01 0.11992399E+01 - 0.11905088E+01 0.11818358E+01 0.11732205E+01 0.11646626E+01 0.11561618E+01 - 0.11477176E+01 0.11393298E+01 0.11309980E+01 0.11227219E+01 0.11145011E+01 - 0.11063353E+01 0.10982241E+01 0.10901673E+01 0.10821644E+01 0.10742152E+01 - 0.10663193E+01 0.10584765E+01 0.10506863E+01 0.10429484E+01 0.10352627E+01 - 0.10276286E+01 0.10200459E+01 0.10125143E+01 0.10050335E+01 0.99760317E+00 - 0.99022297E+00 0.98289262E+00 0.97561181E+00 0.96838024E+00 0.96119760E+00 - 0.95406359E+00 0.94697791E+00 0.93994026E+00 0.93295035E+00 0.92600789E+00 - 0.91911258E+00 0.91226413E+00 0.90546225E+00 0.89870665E+00 0.89199706E+00 - 0.88533317E+00 0.87871472E+00 0.87214142E+00 0.86561298E+00 0.85912914E+00 - 0.85268961E+00 0.84629413E+00 0.83994241E+00 0.83363419E+00 0.82736920E+00 - 0.82114716E+00 0.81496781E+00 0.80883089E+00 0.80273613E+00 0.79668326E+00 - 0.79067204E+00 0.78470219E+00 0.77877346E+00 0.77288559E+00 0.76703833E+00 - 0.76123142E+00 0.75546461E+00 0.74973766E+00 0.74405031E+00 0.73840230E+00 - 0.73279341E+00 0.72722338E+00 0.72169196E+00 0.71619892E+00 0.71074402E+00 - 0.70532701E+00 0.69994765E+00 0.69460572E+00 0.68930097E+00 0.68403317E+00 - 0.67880208E+00 0.67360748E+00 0.66844914E+00 0.66332682E+00 0.65824030E+00 - 0.65318936E+00 0.64817376E+00 0.64319329E+00 0.63824771E+00 0.63333682E+00 - 0.62846039E+00 0.62361820E+00 0.61881003E+00 0.61403568E+00 0.60929491E+00 - 0.60458753E+00 0.59991331E+00 0.59527205E+00 0.59066354E+00 0.58608757E+00 - 0.58154392E+00 0.57703240E+00 0.57255280E+00 0.56810491E+00 0.56368854E+00 - 0.55930347E+00 0.55494952E+00 0.55062647E+00 0.54633414E+00 0.54207232E+00 - 0.53784083E+00 0.53363946E+00 0.52946801E+00 0.52532631E+00 0.52121416E+00 - 0.51713136E+00 0.51307773E+00 0.50905308E+00 0.50505722E+00 0.50108997E+00 - 0.49715114E+00 0.49324055E+00 0.48935802E+00 0.48550336E+00 0.48167639E+00 - 0.47787694E+00 0.47410482E+00 0.47035987E+00 0.46664189E+00 0.46295072E+00 - 0.45928618E+00 0.45564810E+00 0.45203631E+00 0.44845063E+00 0.44489090E+00 - 0.44135694E+00 0.43784859E+00 0.43436568E+00 0.43090805E+00 0.42747552E+00 - 0.42406793E+00 0.42068513E+00 0.41732694E+00 0.41399322E+00 0.41068378E+00 - 0.40739848E+00 0.40413716E+00 0.40089966E+00 0.39768583E+00 0.39449550E+00 - 0.39132852E+00 0.38818474E+00 0.38506400E+00 0.38196616E+00 0.37889105E+00 - 0.37583854E+00 0.37280847E+00 0.36980069E+00 0.36681506E+00 0.36385142E+00 - 0.36090964E+00 0.35798956E+00 0.35509104E+00 0.35221394E+00 0.34935812E+00 - 0.34652343E+00 0.34370974E+00 0.34091690E+00 0.33814477E+00 0.33539322E+00 - 0.33266210E+00 0.32995129E+00 0.32726064E+00 0.32459002E+00 0.32193929E+00 - 0.31930833E+00 0.31669699E+00 0.31410516E+00 0.31153269E+00 0.30897945E+00 - 0.30644532E+00 0.30393017E+00 0.30143387E+00 0.29895629E+00 0.29649730E+00 - 0.29405678E+00 0.29163461E+00 0.28923066E+00 0.28684480E+00 0.28447692E+00 - 0.28212689E+00 0.27979460E+00 0.27747991E+00 0.27518271E+00 0.27290288E+00 - 0.27064031E+00 0.26839487E+00 0.26616645E+00 0.26395493E+00 0.26176020E+00 - 0.25958214E+00 0.25742064E+00 0.25527558E+00 0.25314685E+00 0.25103434E+00 - 0.24893794E+00 0.24685754E+00 0.24479303E+00 0.24274429E+00 0.24071122E+00 - 0.23869372E+00 0.23669166E+00 0.23470496E+00 0.23273349E+00 0.23077717E+00 - 0.22883587E+00 0.22690950E+00 0.22499795E+00 0.22310113E+00 0.22121892E+00 - 0.21935123E+00 0.21749795E+00 0.21565900E+00 0.21383425E+00 0.21202363E+00 - 0.21022702E+00 0.20844434E+00 0.20667547E+00 0.20492034E+00 0.20317883E+00 - 0.20145086E+00 0.19973633E+00 0.19803515E+00 0.19634722E+00 0.19467245E+00 - 0.19301074E+00 0.19136202E+00 0.18972617E+00 0.18810312E+00 0.18649277E+00 - 0.18489503E+00 0.18330982E+00 0.18173704E+00 0.18017661E+00 0.17862844E+00 - 0.17709244E+00 0.17556853E+00 0.17405662E+00 0.17255663E+00 0.17106846E+00 - 0.16959205E+00 0.16812729E+00 0.16667412E+00 0.16523244E+00 0.16380218E+00 - 0.16238325E+00 0.16097558E+00 0.15957908E+00 0.15819366E+00 0.15681927E+00 - 0.15545580E+00 0.15410319E+00 0.15276136E+00 0.15143023E+00 0.15010972E+00 - 0.14879975E+00 0.14750026E+00 0.14621116E+00 0.14493238E+00 0.14366384E+00 - 0.14240548E+00 0.14115721E+00 0.13991897E+00 0.13869067E+00 0.13747226E+00 - 0.13626365E+00 0.13506478E+00 0.13387557E+00 0.13269596E+00 0.13152588E+00 - 0.13036524E+00 0.12921400E+00 0.12807207E+00 0.12693939E+00 0.12581590E+00 - 0.12470152E+00 0.12359618E+00 0.12249983E+00 0.12141239E+00 0.12033380E+00 - 0.11926400E+00 0.11820292E+00 0.11715049E+00 0.11610666E+00 0.11507135E+00 - 0.11404451E+00 0.11302607E+00 0.11201598E+00 0.11101416E+00 0.11002056E+00 - 0.10903511E+00 0.10805776E+00 0.10708845E+00 0.10612712E+00 0.10517370E+00 - 0.10422814E+00 0.10329037E+00 0.10236035E+00 0.10143801E+00 0.10052330E+00 - 0.99616157E-01 0.98716525E-01 0.97824348E-01 0.96939571E-01 0.96062139E-01 - 0.95191995E-01 0.94329085E-01 0.93473355E-01 0.92624750E-01 0.91783217E-01 - 0.90948702E-01 0.90121153E-01 0.89300516E-01 0.88486740E-01 0.87679772E-01 - 0.86879561E-01 0.86086055E-01 0.85299204E-01 0.84518957E-01 0.83745264E-01 - 0.82978075E-01 0.82217339E-01 0.81463009E-01 0.80715035E-01 0.79973369E-01 - 0.79237962E-01 0.78508766E-01 0.77785734E-01 0.77068818E-01 0.76357972E-01 - 0.75653150E-01 0.74954303E-01 0.74261388E-01 0.73574357E-01 0.72893166E-01 - 0.72217769E-01 0.71548122E-01 0.70884181E-01 0.70225901E-01 0.69573238E-01 - 0.68926148E-01 0.68284590E-01 0.67648519E-01 0.67017893E-01 0.66392669E-01 - 0.65772806E-01 0.65158262E-01 0.64548995E-01 0.63944964E-01 0.63346128E-01 - 0.62752447E-01 0.62163879E-01 0.61580386E-01 0.61001927E-01 0.60428463E-01 - 0.59859955E-01 0.59296363E-01 0.58737648E-01 0.58183774E-01 0.57634700E-01 - 0.57090390E-01 0.56550805E-01 0.56015909E-01 0.55485664E-01 0.54960034E-01 - 0.54438981E-01 0.53922470E-01 0.53410464E-01 0.52902928E-01 0.52399825E-01 - 0.51901122E-01 0.51406782E-01 0.50916770E-01 0.50431053E-01 0.49949596E-01 - 0.49472364E-01 0.48999325E-01 0.48530444E-01 0.48065687E-01 0.47605022E-01 - 0.47148417E-01 0.46695837E-01 0.46247251E-01 0.45802627E-01 0.45361932E-01 - 0.44925136E-01 0.44492205E-01 0.44063110E-01 0.43637818E-01 0.43216300E-01 - 0.42798524E-01 0.42384460E-01 0.41974078E-01 0.41567348E-01 0.41164240E-01 - 0.40764725E-01 0.40368772E-01 0.39976355E-01 0.39587442E-01 0.39202006E-01 - 0.38820017E-01 0.38441449E-01 0.38066272E-01 0.37694459E-01 0.37325983E-01 - 0.36960815E-01 0.36598928E-01 0.36240295E-01 0.35884890E-01 0.35532686E-01 - 0.35183656E-01 0.34837773E-01 0.34495013E-01 0.34155348E-01 0.33818754E-01 - 0.33485204E-01 0.33154674E-01 0.32827138E-01 0.32502571E-01 0.32180948E-01 - 0.31862245E-01 0.31546437E-01 0.31233501E-01 0.30923411E-01 0.30616144E-01 - 0.30311677E-01 0.30009986E-01 0.29711047E-01 0.29414837E-01 0.29121334E-01 - 0.28830514E-01 0.28542355E-01 0.28256834E-01 0.27973928E-01 0.27693617E-01 - 0.27415877E-01 0.27140687E-01 0.26868025E-01 0.26597869E-01 0.26330199E-01 - 0.26064993E-01 0.25802229E-01 0.25541888E-01 0.25283948E-01 0.25028389E-01 - 0.24775190E-01 0.24524331E-01 0.24275792E-01 0.24029553E-01 0.23785594E-01 - 0.23543896E-01 0.23304439E-01 0.23067203E-01 0.22832170E-01 0.22599320E-01 - 0.22368634E-01 0.22140094E-01 0.21913681E-01 0.21689376E-01 0.21467161E-01 - 0.21247019E-01 0.21028930E-01 0.20812876E-01 0.20598841E-01 0.20386806E-01 - 0.20176754E-01 0.19968667E-01 0.19762529E-01 0.19558321E-01 0.19356027E-01 - 0.19155630E-01 0.18957114E-01 0.18760461E-01 0.18565656E-01 0.18372681E-01 - 0.18181521E-01 0.17992160E-01 0.17804581E-01 0.17618769E-01 0.17434707E-01 - 0.17252381E-01 0.17071775E-01 0.16892873E-01 0.16715660E-01 0.16540121E-01 - 0.16366241E-01 0.16194006E-01 0.16023399E-01 0.15854407E-01 0.15687015E-01 - 0.15521209E-01 0.15356974E-01 0.15194296E-01 0.15033161E-01 0.14873555E-01 - 0.14715464E-01 0.14558875E-01 0.14403773E-01 0.14250144E-01 0.14097977E-01 - 0.13947257E-01 0.13797970E-01 0.13650105E-01 0.13503647E-01 0.13358585E-01 - 0.13214904E-01 0.13072593E-01 0.12931638E-01 0.12792027E-01 0.12653749E-01 - 0.12516789E-01 0.12381137E-01 0.12246780E-01 0.12113706E-01 0.11981903E-01 - 0.11851360E-01 0.11722063E-01 0.11594003E-01 0.11467167E-01 0.11341544E-01 - 0.11217122E-01 0.11093891E-01 0.10971838E-01 0.10850953E-01 0.10731226E-01 - 0.10612644E-01 0.10495197E-01 0.10378875E-01 0.10263667E-01 0.10149562E-01 - 0.10036550E-01 0.99246196E-02 0.98137616E-02 0.97039655E-02 0.95952210E-02 - 0.94875183E-02 0.93808472E-02 0.92751979E-02 0.91705606E-02 0.90669256E-02 - 0.89642833E-02 0.88626240E-02 0.87619384E-02 0.86622170E-02 0.85634505E-02 - 0.84656297E-02 0.83687454E-02 0.82727886E-02 0.81777502E-02 0.80836213E-02 - 0.79903931E-02 0.78980567E-02 0.78066036E-02 0.77160251E-02 0.76263126E-02 - 0.75374577E-02 0.74494520E-02 0.73622871E-02 0.72759548E-02 0.71904470E-02 - 0.71057555E-02 0.70218724E-02 0.69387895E-02 0.68564992E-02 0.67749935E-02 - 0.66942647E-02 0.66143051E-02 0.65351072E-02 0.64566634E-02 0.63789662E-02 - 0.63020083E-02 0.62257823E-02 0.61502811E-02 0.60754973E-02 0.60014238E-02 - 0.59280538E-02 0.58553800E-02 0.57833957E-02 0.57120940E-02 0.56414681E-02 - 0.55715114E-02 0.55022171E-02 0.54335786E-02 0.53655896E-02 0.52982434E-02 - 0.52315339E-02 0.51654545E-02 0.50999992E-02 0.50351617E-02 0.49709358E-02 - 0.49073156E-02 0.48442951E-02 0.47818683E-02 0.47200294E-02 0.46587726E-02 - 0.45980921E-02 0.45379824E-02 0.44784377E-02 0.44194527E-02 0.43610217E-02 - 0.43031395E-02 0.42458007E-02 0.41889999E-02 0.41327320E-02 0.40769919E-02 - 0.40217745E-02 0.39670747E-02 0.39128876E-02 0.38592083E-02 0.38060320E-02 - 0.37533539E-02 0.37011694E-02 0.36494738E-02 0.35982625E-02 0.35475310E-02 - 0.34972750E-02 0.34474900E-02 0.33981718E-02 0.33493160E-02 0.33009186E-02 - 0.32529753E-02 0.32054823E-02 0.31584354E-02 0.31118308E-02 0.30656646E-02 - 0.30199330E-02 0.29746324E-02 0.29297590E-02 0.28853093E-02 0.28412798E-02 - 0.27976669E-02 0.27544674E-02 0.27116779E-02 0.26692952E-02 0.26273159E-02 - 0.25857372E-02 0.25445557E-02 0.25037687E-02 0.24633732E-02 0.24233662E-02 - 0.23837451E-02 0.23445070E-02 0.23056494E-02 0.22671697E-02 0.22290653E-02 - 0.21913337E-02 0.21539726E-02 0.21169797E-02 0.20803527E-02 0.20440894E-02 - 0.20081877E-02 0.19726455E-02 0.19374608E-02 0.19026318E-02 0.18681564E-02 - 0.18340331E-02 0.18002599E-02 0.17668353E-02 0.17337576E-02 0.17010253E-02 - 0.16686369E-02 0.16365911E-02 0.16048863E-02 0.15735214E-02 0.15424951E-02 - 0.15118062E-02 0.14814536E-02 0.14514362E-02 0.14217531E-02 0.13924033E-02 - 0.13633859E-02 0.13347000E-02 0.13063449E-02 0.12783198E-02 0.12506240E-02 - 0.12232569E-02 0.11962179E-02 0.11695065E-02 0.11431221E-02 0.11170642E-02 - 0.10913325E-02 0.10659266E-02 0.10408460E-02 0.10160905E-02 0.99165985E-03 - 0.96755368E-03 0.94377180E-03 0.92031400E-03 0.89718009E-03 0.87436990E-03 - 0.85188327E-03 0.82972007E-03 0.80788015E-03 0.78636340E-03 0.76516969E-03 - 0.74429890E-03 0.72375091E-03 0.70352559E-03 0.68362280E-03 0.66404239E-03 - 0.64478418E-03 0.62584799E-03 0.60723360E-03 0.58894078E-03 0.57096924E-03 - 0.55331867E-03 0.53598874E-03 0.51897903E-03 0.50228912E-03 0.48591850E-03 - 0.46986662E-03 0.45413289E-03 0.43871661E-03 0.42361705E-03 0.40883340E-03 - 0.39436476E-03 0.38021016E-03 0.36636855E-03 0.35283878E-03 0.33961963E-03 - 0.32670975E-03 0.31410772E-03 0.30181202E-03 0.28982100E-03 0.27813293E-03 - 0.26674595E-03 0.25565810E-03 0.24486728E-03 0.23437130E-03 0.22416784E-03 - 0.21425445E-03 0.20462856E-03 0.19528747E-03 0.18622838E-03 0.17744834E-03 - 0.16894426E-03 0.16071296E-03 0.15275111E-03 0.14505525E-03 0.13762181E-03 - 0.13044709E-03 0.12352726E-03 0.11685839E-03 0.11043642E-03 0.10425717E-03 - 0.98316362E-04 0.92609607E-04 0.87132410E-04 0.81880180E-04 0.76848230E-04 - 0.72031786E-04 0.67425991E-04 0.63025911E-04 0.58826538E-04 0.54822803E-04 - 0.51009579E-04 0.47381685E-04 0.43933900E-04 0.40660966E-04 0.37557597E-04 - 0.34618485E-04 0.31838314E-04 0.29211760E-04 0.26733505E-04 0.24398243E-04 - 0.22200690E-04 0.20135590E-04 0.18197725E-04 0.16381922E-04 0.14683062E-04 - 0.13096087E-04 0.11616008E-04 0.10237913E-04 0.89569732E-05 0.77684493E-05 - 0.66676997E-05 0.56501858E-05 0.47114772E-05 0.38472578E-05 0.30533303E-05 - 0.23256206E-05 0.16601819E-05 0.10531979E-05 0.50098619E-06 0.00000000E+00 - 0.50528773E+05 0.50528773E+05 0.50528773E+05 0.50528773E+05 0.50528773E+05 - 0.50528773E+05 0.50528773E+05 0.50528773E+05 0.50528773E+05 0.50528773E+05 - 0.50528773E+05 0.50528773E+05 0.50528773E+05 0.50528773E+05 0.50528773E+05 - 0.50528773E+05 0.50528773E+05 0.50528773E+05 0.50528773E+05 0.50528773E+05 - 0.50528773E+05 0.50528773E+05 0.50528773E+05 0.50528773E+05 0.50528773E+05 - 0.50528773E+05 0.50528773E+05 0.50528773E+05 0.50528773E+05 0.50528773E+05 - 0.50528773E+05 0.50528773E+05 0.50528773E+05 0.50528773E+05 0.50528773E+05 - 0.50528773E+05 0.50528773E+05 0.50528773E+05 0.50528773E+05 0.50528773E+05 - 0.50528773E+05 0.50528773E+05 0.50528773E+05 0.50528773E+05 0.50528773E+05 - 0.50409310E+05 0.47756885E+05 0.45296626E+05 0.43010952E+05 0.40884215E+05 - 0.38902450E+05 0.37053162E+05 0.35325154E+05 0.33708362E+05 0.32193728E+05 - 0.30773080E+05 0.29439033E+05 0.28184899E+05 0.27004612E+05 0.25892661E+05 - 0.24844029E+05 0.23854144E+05 0.22918830E+05 0.22034271E+05 0.21196970E+05 - 0.20403722E+05 0.19651584E+05 0.18937850E+05 0.18260029E+05 0.17615825E+05 - 0.17003119E+05 0.16419954E+05 0.15864517E+05 0.15335134E+05 0.14830248E+05 - 0.14348419E+05 0.13888307E+05 0.13448665E+05 0.13028335E+05 0.12626237E+05 - 0.12241364E+05 0.11872777E+05 0.11519597E+05 0.11181004E+05 0.10856231E+05 - 0.10544560E+05 0.10245315E+05 0.99578671E+04 0.96816222E+04 0.94160240E+04 - 0.91605492E+04 0.89147058E+04 0.86780308E+04 0.84500880E+04 0.82304665E+04 - 0.80187787E+04 0.78146589E+04 0.76177620E+04 0.74277616E+04 0.72443495E+04 - 0.70672342E+04 0.68961395E+04 0.67308043E+04 0.65709810E+04 0.64164348E+04 - 0.62669434E+04 0.61222956E+04 0.59822908E+04 0.58467387E+04 0.57154585E+04 - 0.55882780E+04 0.54650336E+04 0.53455698E+04 0.52297383E+04 0.51173980E+04 - 0.50084143E+04 0.49026590E+04 0.48000100E+04 0.47003504E+04 0.46035691E+04 - 0.45095597E+04 0.44182208E+04 0.43294552E+04 0.42431702E+04 0.41592773E+04 - 0.40776916E+04 0.39983318E+04 0.39211204E+04 0.38459828E+04 0.37728479E+04 - 0.37016473E+04 0.36323156E+04 0.35647899E+04 0.34990101E+04 0.34349184E+04 - 0.33724594E+04 0.33115797E+04 0.32522284E+04 0.31943562E+04 0.31379160E+04 - 0.30828624E+04 0.30291517E+04 0.29767422E+04 0.29255932E+04 0.28756662E+04 - 0.28269236E+04 0.27793294E+04 0.27328491E+04 0.26874492E+04 0.26430976E+04 - 0.25997632E+04 0.25574162E+04 0.25160277E+04 0.24755699E+04 0.24360161E+04 - 0.23973403E+04 0.23595175E+04 0.23225238E+04 0.22863356E+04 0.22509307E+04 - 0.22162872E+04 0.21823842E+04 0.21492014E+04 0.21167191E+04 0.20849185E+04 - 0.20537811E+04 0.20232893E+04 0.19934259E+04 0.19641742E+04 0.19355182E+04 - 0.19074424E+04 0.18799317E+04 0.18529715E+04 0.18265476E+04 0.18006465E+04 - 0.17752548E+04 0.17503597E+04 0.17259487E+04 0.17020097E+04 0.16785311E+04 - 0.16555015E+04 0.16329099E+04 0.16107455E+04 0.15889981E+04 0.15676575E+04 - 0.15467140E+04 0.15261581E+04 0.15059806E+04 0.14861726E+04 0.14667254E+04 - 0.14476305E+04 0.14288798E+04 0.14104653E+04 0.13923793E+04 0.13746142E+04 - 0.13571628E+04 0.13400178E+04 0.13231725E+04 0.13066201E+04 0.12903541E+04 - 0.12743680E+04 0.12586558E+04 0.12432113E+04 0.12280288E+04 0.12131025E+04 - 0.11984269E+04 0.11839966E+04 0.11698062E+04 0.11558508E+04 0.11421252E+04 - 0.11286247E+04 0.11153445E+04 0.11022799E+04 0.10894265E+04 0.10767799E+04 - 0.10643358E+04 0.10520901E+04 0.10400386E+04 0.10281775E+04 0.10165029E+04 - 0.10050110E+04 0.99369808E+03 0.98256064E+03 0.97159515E+03 0.96079820E+03 - 0.95016647E+03 0.93969671E+03 0.92938574E+03 0.91923048E+03 0.90922790E+03 - 0.89937505E+03 0.88966906E+03 0.88010710E+03 0.87068644E+03 0.86140439E+03 - 0.85225833E+03 0.84324570E+03 0.83436399E+03 0.82561077E+03 0.81698364E+03 - 0.80848027E+03 0.80009838E+03 0.79183574E+03 0.78369016E+03 0.77565952E+03 - 0.76774173E+03 0.75993475E+03 0.75223659E+03 0.74464530E+03 0.73715896E+03 - 0.72977573E+03 0.72249376E+03 0.71531128E+03 0.70822653E+03 0.70123782E+03 - 0.69434345E+03 0.68754180E+03 0.68083127E+03 0.67421027E+03 0.66767729E+03 - 0.66123080E+03 0.65486935E+03 0.64859149E+03 0.64239579E+03 0.63628090E+03 - 0.63024543E+03 0.62428808E+03 0.61840754E+03 0.61260253E+03 0.60687182E+03 - 0.60121416E+03 0.59562838E+03 0.59011329E+03 0.58466774E+03 0.57929061E+03 - 0.57398078E+03 0.56873718E+03 0.56355874E+03 0.55844443E+03 0.55339321E+03 - 0.54840409E+03 0.54347609E+03 0.53860824E+03 0.53379960E+03 0.52904924E+03 - 0.52435625E+03 0.51971975E+03 0.51513885E+03 0.51061271E+03 0.50614047E+03 - 0.50172131E+03 0.49735442E+03 0.49303900E+03 0.48877428E+03 0.48455949E+03 - 0.48039388E+03 0.47627670E+03 0.47220724E+03 0.46818477E+03 0.46420861E+03 - 0.46027807E+03 0.45639247E+03 0.45255115E+03 0.44875347E+03 0.44499878E+03 - 0.44128646E+03 0.43761589E+03 0.43398647E+03 0.43039761E+03 0.42684872E+03 - 0.42333923E+03 0.41986857E+03 0.41643620E+03 0.41304157E+03 0.40968414E+03 - 0.40636340E+03 0.40307882E+03 0.39982990E+03 0.39661613E+03 0.39343704E+03 - 0.39029214E+03 0.38718095E+03 0.38410302E+03 0.38105787E+03 0.37804507E+03 - 0.37506417E+03 0.37211474E+03 0.36919635E+03 0.36630857E+03 0.36345100E+03 - 0.36062323E+03 0.35782485E+03 0.35505549E+03 0.35231474E+03 0.34960222E+03 - 0.34691757E+03 0.34426042E+03 0.34163039E+03 0.33902715E+03 0.33645032E+03 - 0.33389958E+03 0.33137458E+03 0.32887498E+03 0.32640046E+03 0.32395069E+03 - 0.32152535E+03 0.31912414E+03 0.31674673E+03 0.31439284E+03 0.31206215E+03 - 0.30975437E+03 0.30746922E+03 0.30520641E+03 0.30296566E+03 0.30074669E+03 - 0.29854922E+03 0.29637300E+03 0.29421775E+03 0.29208321E+03 0.28996914E+03 - 0.28787527E+03 0.28580136E+03 0.28374717E+03 0.28171244E+03 0.27969695E+03 - 0.27770047E+03 0.27572275E+03 0.27376357E+03 0.27182272E+03 0.26989996E+03 - 0.26799509E+03 0.26610788E+03 0.26423813E+03 0.26238563E+03 0.26055018E+03 - 0.25873156E+03 0.25692960E+03 0.25514407E+03 0.25337481E+03 0.25162161E+03 - 0.24988428E+03 0.24816265E+03 0.24645652E+03 0.24476573E+03 0.24309009E+03 - 0.24142942E+03 0.23978356E+03 0.23815234E+03 0.23653558E+03 0.23493313E+03 - 0.23334482E+03 0.23177049E+03 0.23020998E+03 0.22866314E+03 0.22712981E+03 - 0.22560984E+03 0.22410307E+03 0.22260938E+03 0.22112860E+03 0.21966059E+03 - 0.21820521E+03 0.21676233E+03 0.21533180E+03 0.21391349E+03 0.21250726E+03 - 0.21111298E+03 0.20973053E+03 0.20835977E+03 0.20700057E+03 0.20565281E+03 - 0.20431637E+03 0.20299112E+03 0.20167695E+03 0.20037373E+03 0.19908135E+03 - 0.19779969E+03 0.19652864E+03 0.19526808E+03 0.19401790E+03 0.19277800E+03 - 0.19154826E+03 0.19032858E+03 0.18911885E+03 0.18791897E+03 0.18672883E+03 - 0.18554834E+03 0.18437739E+03 0.18321588E+03 0.18206372E+03 0.18092081E+03 - 0.17978706E+03 0.17866236E+03 0.17754663E+03 0.17643977E+03 0.17534170E+03 - 0.17425233E+03 0.17317156E+03 0.17209931E+03 0.17103550E+03 0.16998003E+03 - 0.16893283E+03 0.16789380E+03 0.16686288E+03 0.16583998E+03 0.16482501E+03 - 0.16381790E+03 0.16281858E+03 0.16182696E+03 0.16084296E+03 0.15986652E+03 - 0.15889756E+03 0.15793600E+03 0.15698178E+03 0.15603481E+03 0.15509504E+03 - 0.15416238E+03 0.15323678E+03 0.15231816E+03 0.15140645E+03 0.15050159E+03 - 0.14960352E+03 0.14871216E+03 0.14782746E+03 0.14694934E+03 0.14607776E+03 - 0.14521263E+03 0.14435391E+03 0.14350153E+03 0.14265544E+03 0.14181557E+03 - 0.14098186E+03 0.14015426E+03 0.13933271E+03 0.13851715E+03 0.13770753E+03 - 0.13690379E+03 0.13610588E+03 0.13531374E+03 0.13452732E+03 0.13374657E+03 - 0.13297144E+03 0.13220186E+03 0.13143780E+03 0.13067920E+03 0.12992602E+03 - 0.12917819E+03 0.12843568E+03 0.12769844E+03 0.12696641E+03 0.12623955E+03 - 0.12551782E+03 0.12480117E+03 0.12408954E+03 0.12338291E+03 0.12268122E+03 - 0.12198443E+03 0.12129249E+03 0.12060536E+03 0.11992300E+03 0.11924538E+03 - 0.11857243E+03 0.11790413E+03 0.11724043E+03 0.11658130E+03 0.11592669E+03 - 0.11527656E+03 0.11463088E+03 0.11398960E+03 0.11335269E+03 0.11272010E+03 - 0.11209181E+03 0.11146778E+03 0.11084796E+03 0.11023233E+03 0.10962084E+03 - 0.10901346E+03 0.10841016E+03 0.10781090E+03 0.10721564E+03 0.10662436E+03 - 0.10603701E+03 0.10545357E+03 0.10487400E+03 0.10429828E+03 0.10372636E+03 - 0.10315821E+03 0.10259381E+03 0.10203312E+03 0.10147611E+03 0.10092276E+03 - 0.10037302E+03 0.99826872E+02 0.99284287E+02 0.98745233E+02 0.98209681E+02 - 0.97677602E+02 0.97148968E+02 0.96623751E+02 0.96101922E+02 0.95583454E+02 - 0.95068320E+02 0.94556492E+02 0.94047943E+02 0.93542648E+02 0.93040579E+02 - 0.92541710E+02 0.92046017E+02 0.91553473E+02 0.91064052E+02 0.90577731E+02 - 0.90094484E+02 0.89614287E+02 0.89137115E+02 0.88662944E+02 0.88191751E+02 - 0.87723511E+02 0.87258203E+02 0.86795801E+02 0.86336285E+02 0.85879630E+02 - 0.85425814E+02 0.84974816E+02 0.84526612E+02 0.84081183E+02 0.83638504E+02 - 0.83198557E+02 0.82761318E+02 0.82326767E+02 0.81894884E+02 0.81465648E+02 - 0.81039038E+02 0.80615035E+02 0.80193618E+02 0.79774767E+02 0.79358463E+02 - 0.78944686E+02 0.78533418E+02 0.78124638E+02 0.77718329E+02 0.77314471E+02 - 0.76913047E+02 0.76514036E+02 0.76117422E+02 0.75723187E+02 0.75331312E+02 - 0.74941780E+02 0.74554573E+02 0.74169674E+02 0.73787066E+02 0.73406732E+02 - 0.73028654E+02 0.72652816E+02 0.72279202E+02 0.71907796E+02 0.71538579E+02 - 0.71171538E+02 0.70806655E+02 0.70443916E+02 0.70083303E+02 0.69724802E+02 - 0.69368398E+02 0.69014074E+02 0.68661816E+02 0.68311610E+02 0.67963439E+02 - 0.67617289E+02 0.67273147E+02 0.66930996E+02 0.66590824E+02 0.66252615E+02 - 0.65916356E+02 0.65582032E+02 0.65249631E+02 0.64919138E+02 0.64590539E+02 - 0.64263822E+02 0.63938972E+02 0.63615977E+02 0.63294823E+02 0.62975498E+02 - 0.62657989E+02 0.62342282E+02 0.62028365E+02 0.61716227E+02 0.61405853E+02 - 0.61097232E+02 0.60790352E+02 0.60485201E+02 0.60181766E+02 0.59880036E+02 - 0.59579998E+02 0.59281642E+02 0.58984955E+02 0.58689926E+02 0.58396544E+02 - 0.58104797E+02 0.57814675E+02 0.57526165E+02 0.57239258E+02 0.56953941E+02 - 0.56670205E+02 0.56388038E+02 0.56107430E+02 0.55828370E+02 0.55550848E+02 - 0.55274854E+02 0.55000377E+02 0.54727406E+02 0.54455933E+02 0.54185946E+02 - 0.53917436E+02 0.53650393E+02 0.53384807E+02 0.53120669E+02 0.52857968E+02 - 0.52596696E+02 0.52336843E+02 0.52078399E+02 0.51821355E+02 0.51565702E+02 - 0.51311430E+02 0.51058532E+02 0.50806997E+02 0.50556816E+02 0.50307982E+02 - 0.50060484E+02 0.49814315E+02 0.49569465E+02 0.49325927E+02 0.49083691E+02 - 0.48842749E+02 0.48603093E+02 0.48364714E+02 0.48127605E+02 0.47891756E+02 - 0.47657161E+02 0.47423810E+02 0.47191697E+02 0.46960812E+02 0.46731148E+02 - 0.46502698E+02 0.46275454E+02 0.46049407E+02 0.45824551E+02 0.45600877E+02 - 0.45378379E+02 0.45157049E+02 0.44936880E+02 0.44717863E+02 0.44499993E+02 - 0.44283261E+02 0.44067661E+02 0.43853186E+02 0.43639828E+02 0.43427581E+02 - 0.43216438E+02 0.43006391E+02 0.42797434E+02 0.42589560E+02 0.42382763E+02 - 0.42177036E+02 0.41972372E+02 0.41768765E+02 0.41566208E+02 0.41364695E+02 - 0.41164219E+02 0.40964774E+02 0.40766353E+02 0.40568952E+02 0.40372562E+02 - 0.40177179E+02 0.39982795E+02 0.39789405E+02 0.39597003E+02 0.39405584E+02 - 0.39215140E+02 0.39025666E+02 0.38837156E+02 0.38649605E+02 0.38463006E+02 - 0.38277354E+02 0.38092644E+02 0.37908869E+02 0.37726024E+02 0.37544104E+02 - 0.37363103E+02 0.37183016E+02 0.37003836E+02 0.36825560E+02 0.36648180E+02 - 0.36471693E+02 0.36296093E+02 0.36121374E+02 0.35947532E+02 0.35774561E+02 - 0.35602456E+02 0.35431212E+02 0.35260825E+02 0.35091288E+02 0.34922598E+02 - 0.34754749E+02 0.34587736E+02 0.34421554E+02 0.34256199E+02 0.34091666E+02 - 0.33927950E+02 0.33765047E+02 0.33602951E+02 0.33441658E+02 0.33281163E+02 - 0.33121463E+02 0.32962551E+02 0.32804425E+02 0.32647078E+02 0.32490508E+02 - 0.32334709E+02 0.32179676E+02 0.32025407E+02 0.31871896E+02 0.31719139E+02 - 0.31567131E+02 0.31415869E+02 0.31265349E+02 0.31115565E+02 0.30966515E+02 - 0.30818193E+02 0.30670596E+02 0.30523720E+02 0.30377561E+02 0.30232114E+02 - 0.30087376E+02 0.29943343E+02 0.29800010E+02 0.29657375E+02 0.29515432E+02 - 0.29374179E+02 0.29233611E+02 0.29093724E+02 0.28954516E+02 0.28815981E+02 - 0.28678117E+02 0.28540920E+02 0.28404386E+02 0.28268511E+02 0.28133292E+02 - 0.27998725E+02 0.27864806E+02 0.27731533E+02 0.27598902E+02 0.27466908E+02 - 0.27335549E+02 0.27204821E+02 0.27074721E+02 0.26945246E+02 0.26816391E+02 - 0.26688154E+02 0.26560531E+02 0.26433520E+02 0.26307116E+02 0.26181316E+02 - 0.26056118E+02 0.25931517E+02 0.25807512E+02 0.25684098E+02 0.25561272E+02 - 0.25439032E+02 0.25317373E+02 0.25196294E+02 0.25075791E+02 0.24955861E+02 - 0.24836501E+02 0.24717708E+02 0.24599479E+02 0.24481810E+02 0.24364700E+02 - 0.24248145E+02 0.24132141E+02 0.24016687E+02 0.23901780E+02 0.23787415E+02 - 0.23673592E+02 0.23560306E+02 0.23447555E+02 0.23335337E+02 0.23223648E+02 - 0.23112485E+02 0.23001847E+02 0.22891730E+02 0.22782131E+02 0.22673048E+02 - 0.22564479E+02 0.22456420E+02 0.22348869E+02 0.22241823E+02 0.22135280E+02 - 0.22029237E+02 0.21923691E+02 0.21818641E+02 0.21714082E+02 0.21610014E+02 - 0.21506434E+02 0.21403338E+02 0.21300724E+02 0.21198591E+02 0.21096935E+02 - 0.20995755E+02 0.20895047E+02 0.20794810E+02 0.20695040E+02 0.20595736E+02 - 0.20496895E+02 0.20398516E+02 0.20300594E+02 0.20203130E+02 0.20106119E+02 - 0.20009559E+02 0.19913450E+02 0.19817787E+02 0.19722569E+02 0.19627794E+02 - 0.19533460E+02 0.19439564E+02 0.19346104E+02 0.19253078E+02 0.19160483E+02 - 0.19068319E+02 0.18976581E+02 0.18885270E+02 0.18794381E+02 0.18703914E+02 - 0.18613866E+02 0.18524235E+02 0.18435019E+02 0.18346216E+02 0.18257823E+02 - 0.18169840E+02 0.18082264E+02 0.17995092E+02 0.17908323E+02 0.17821956E+02 - 0.17735987E+02 0.17650415E+02 0.17565238E+02 0.17480455E+02 0.17396063E+02 - 0.17312060E+02 0.17228444E+02 0.17145214E+02 0.17062368E+02 0.16979904E+02 - 0.16897819E+02 0.16816113E+02 0.16734783E+02 0.16653828E+02 0.16573245E+02 - 0.16493033E+02 0.16413190E+02 0.16333715E+02 0.16254605E+02 0.16175859E+02 - 0.16097475E+02 0.16019451E+02 0.15941786E+02 0.15864478E+02 0.15787526E+02 - 0.15710926E+02 0.15634679E+02 0.15558781E+02 0.15483232E+02 0.15408030E+02 - 0.15333173E+02 0.15258660E+02 0.15184488E+02 0.15110657E+02 0.15037164E+02 - 0.14964009E+02 0.14891189E+02 0.14818702E+02 0.14746549E+02 0.14674725E+02 - 0.14603231E+02 0.14532065E+02 0.14461225E+02 0.14390709E+02 0.14320517E+02 - 0.14250646E+02 0.14181095E+02 0.14111862E+02 0.14042947E+02 0.13974347E+02 - 0.13906061E+02 0.13838088E+02 0.13770426E+02 0.13703073E+02 0.13636029E+02 - 0.13569292E+02 0.13502860E+02 0.13436732E+02 0.13370907E+02 0.13305383E+02 - 0.13240159E+02 0.13175233E+02 0.13110604E+02 0.13046270E+02 0.12982231E+02 - 0.12918485E+02 0.12855031E+02 0.12791867E+02 0.12728991E+02 0.12666403E+02 - 0.12604102E+02 0.12542085E+02 0.12480352E+02 0.12418901E+02 0.12357732E+02 - 0.12296842E+02 0.12236230E+02 0.12175896E+02 0.12115837E+02 0.12056053E+02 - 0.11996543E+02 0.11937305E+02 0.11878337E+02 0.11819640E+02 0.11761211E+02 - 0.11703049E+02 0.11645153E+02 0.11587521E+02 0.11530154E+02 0.11473049E+02 - 0.11416205E+02 0.11359621E+02 0.11303296E+02 0.11247229E+02 0.11191418E+02 - 0.11135862E+02 0.11080561E+02 0.11025513E+02 0.10970717E+02 0.10916171E+02 - 0.10861875E+02 0.10807828E+02 0.10754028E+02 0.10700475E+02 0.10647166E+02 - 0.10594102E+02 0.10541281E+02 0.10488702E+02 0.10436363E+02 0.10384264E+02 - 0.10332404E+02 0.10280782E+02 0.10229396E+02 0.10178245E+02 0.10127329E+02 - 0.10076647E+02 0.10026197E+02 0.99759777E+01 0.99259890E+01 0.98762296E+01 - 0.98266984E+01 0.97773945E+01 0.97283167E+01 0.96794642E+01 0.96308358E+01 - 0.95824307E+01 0.95342477E+01 0.94862860E+01 0.94385446E+01 0.93910224E+01 - 0.93437185E+01 0.92966320E+01 0.92497618E+01 0.92031071E+01 0.91566668E+01 - 0.91104400E+01 0.90644258E+01 0.90186232E+01 0.89730313E+01 0.89276492E+01 - 0.88824760E+01 0.88375106E+01 0.87927523E+01 0.87482001E+01 0.87038530E+01 - 0.86597103E+01 0.86157709E+01 0.85720340E+01 0.85284987E+01 0.84851642E+01 - 0.84420295E+01 0.83990937E+01 0.83563560E+01 0.83138156E+01 0.82714715E+01 - 0.82293229E+01 0.81873689E+01 0.81456087E+01 0.81040414E+01 0.80626663E+01 - 0.80214823E+01 0.79804888E+01 0.79396849E+01 0.78990698E+01 0.78586425E+01 - 0.78184024E+01 0.77783485E+01 0.77384802E+01 0.76987965E+01 0.76592966E+01 - 0.76199799E+01 0.75808454E+01 0.75418923E+01 0.75031199E+01 0.74645275E+01 - 0.74261141E+01 0.73878791E+01 0.73498216E+01 0.73119409E+01 0.72742362E+01 - 0.72367067E+01 0.71993518E+01 0.71621705E+01 0.71251623E+01 0.70883262E+01 - 0.70516616E+01 0.70151678E+01 0.69788439E+01 0.69426893E+01 0.69067032E+01 - 0.68708849E+01 0.68352336E+01 0.67997487E+01 0.67644294E+01 0.67292749E+01 - 0.66942847E+01 0.66594579E+01 0.66247938E+01 0.65902919E+01 0.65559512E+01 - 0.65217713E+01 0.64877513E+01 0.64538905E+01 0.64201883E+01 0.63866441E+01 - 0.63532570E+01 0.63200264E+01 0.62869517E+01 0.62540322E+01 0.62212672E+01 - 0.61886560E+01 0.61561980E+01 0.61238925E+01 0.60917389E+01 0.60597365E+01 - 0.60278846E+01 0.59961826E+01 0.59646298E+01 0.59332256E+01 0.59019694E+01 - 0.58708605E+01 0.58398983E+01 0.58090822E+01 0.57784115E+01 0.57478855E+01 - 0.57175038E+01 0.56872655E+01 0.56571702E+01 0.56272172E+01 0.55974059E+01 - 0.55677357E+01 0.55382060E+01 0.55088161E+01 0.54795655E+01 0.54504536E+01 - 0.54214797E+01 0.53926433E+01 0.53639438E+01 0.53353805E+01 0.53069530E+01 - 0.52786605E+01 0.52505026E+01 0.52224787E+01 0.51945881E+01 0.51668303E+01 - 0.51392048E+01 0.51117109E+01 0.50843481E+01 0.50571158E+01 0.50300134E+01 - 0.50030405E+01 0.49761964E+01 0.49494805E+01 0.49228924E+01 0.48964315E+01 - 0.48700972E+01 0.48438890E+01 0.48178063E+01 0.47918486E+01 0.47660154E+01 - 0.47403061E+01 0.47147202E+01 0.46892571E+01 0.46639163E+01 0.46386974E+01 - 0.46135997E+01 0.45886227E+01 0.45637660E+01 0.45390289E+01 0.45144111E+01 - 0.44899119E+01 0.44655308E+01 0.44412674E+01 0.44171212E+01 0.43930916E+01 - 0.43691781E+01 0.43453802E+01 0.43216974E+01 0.42981293E+01 0.42746753E+01 - 0.42513349E+01 0.42281077E+01 0.42049931E+01 0.41819907E+01 0.41591000E+01 - 0.41363205E+01 0.41136516E+01 0.40910930E+01 0.40686442E+01 0.40463047E+01 - 0.40240739E+01 0.40019515E+01 0.39799370E+01 0.39580298E+01 0.39362296E+01 - 0.39145359E+01 0.38929481E+01 0.38714659E+01 0.38500888E+01 0.38288163E+01 - 0.38076480E+01 0.37865835E+01 0.37656221E+01 0.37447636E+01 0.37240075E+01 - 0.37033534E+01 0.36828007E+01 0.36623490E+01 0.36419980E+01 0.36217471E+01 - 0.36015959E+01 0.35815441E+01 0.35615911E+01 0.35417365E+01 0.35219800E+01 - 0.35023210E+01 0.34827592E+01 0.34632941E+01 0.34439252E+01 0.34246523E+01 - 0.34054749E+01 0.33863925E+01 0.33674047E+01 0.33485111E+01 0.33297114E+01 - 0.33110050E+01 0.32923917E+01 0.32738709E+01 0.32554423E+01 0.32371054E+01 - 0.32188599E+01 0.32007054E+01 0.31826415E+01 0.31646677E+01 0.31467837E+01 - 0.31289891E+01 0.31112835E+01 0.30936664E+01 0.30761376E+01 0.30586966E+01 - 0.30413431E+01 0.30240765E+01 0.30068967E+01 0.29898031E+01 0.29727955E+01 - 0.29558733E+01 0.29390363E+01 0.29222841E+01 0.29056163E+01 0.28890325E+01 - 0.28725324E+01 0.28561156E+01 0.28397816E+01 0.28235303E+01 0.28073611E+01 - 0.27912737E+01 0.27752678E+01 0.27593430E+01 0.27434990E+01 0.27277353E+01 - 0.27120517E+01 0.26964477E+01 0.26809230E+01 0.26654773E+01 0.26501102E+01 - 0.26348214E+01 0.26196105E+01 0.26044772E+01 0.25894211E+01 0.25744419E+01 - 0.25595392E+01 0.25447128E+01 0.25299621E+01 0.25152871E+01 0.25006871E+01 - 0.24861621E+01 0.24717115E+01 0.24573352E+01 0.24430326E+01 0.24288036E+01 - 0.24146478E+01 0.24005649E+01 0.23865545E+01 0.23726162E+01 0.23587499E+01 - 0.23449552E+01 0.23312317E+01 0.23175791E+01 0.23039971E+01 0.22904854E+01 - 0.22770436E+01 0.22636716E+01 0.22503688E+01 0.22371351E+01 0.22239701E+01 - 0.22108736E+01 0.21978451E+01 0.21848844E+01 0.21719912E+01 0.21591652E+01 - 0.21464060E+01 0.21337134E+01 0.21210871E+01 0.21085268E+01 0.20960322E+01 - 0.20836029E+01 0.20712387E+01 0.20589393E+01 0.20467043E+01 0.20345336E+01 - 0.20224267E+01 0.20103835E+01 0.19984036E+01 0.19864868E+01 0.19746326E+01 - 0.19628410E+01 0.19511115E+01 0.19394439E+01 0.19278379E+01 0.19162933E+01 - 0.19048097E+01 0.18933868E+01 0.18820245E+01 0.18707223E+01 0.18594801E+01 - 0.18482976E+01 0.18371744E+01 0.18261104E+01 0.18151052E+01 0.18041585E+01 - 0.17932702E+01 0.17824399E+01 0.17716673E+01 0.17609523E+01 0.17502945E+01 - 0.17396936E+01 0.17291495E+01 0.17186618E+01 0.17082303E+01 0.16978547E+01 - 0.16875348E+01 0.16772703E+01 0.16670609E+01 0.16569064E+01 0.16468065E+01 - 0.16367611E+01 0.16267697E+01 0.16168323E+01 0.16069484E+01 0.15971180E+01 - 0.15873406E+01 0.15776162E+01 0.15679444E+01 0.15583249E+01 0.15487576E+01 - 0.15392422E+01 0.15297785E+01 0.15203662E+01 0.15110050E+01 0.15016948E+01 - 0.14924353E+01 0.14832262E+01 0.14740673E+01 0.14649584E+01 0.14558993E+01 - 0.14468896E+01 0.14379293E+01 0.14290180E+01 0.14201555E+01 0.14113416E+01 - 0.14025760E+01 0.13938585E+01 0.13851890E+01 0.13765671E+01 0.13679927E+01 - 0.13594654E+01 0.13509852E+01 0.13425518E+01 0.13341648E+01 0.13258242E+01 - 0.13175298E+01 0.13092812E+01 0.13010782E+01 0.12929207E+01 0.12848085E+01 - 0.12767412E+01 0.12687188E+01 0.12607409E+01 0.12528074E+01 0.12449181E+01 - 0.12370727E+01 0.12292710E+01 0.12215129E+01 0.12137981E+01 0.12061264E+01 - 0.11984976E+01 0.11909115E+01 0.11833678E+01 0.11758665E+01 0.11684072E+01 - 0.11609898E+01 0.11536141E+01 0.11462798E+01 0.11389868E+01 0.11317349E+01 - 0.11245238E+01 0.11173534E+01 0.11102235E+01 0.11031339E+01 0.10960843E+01 - 0.10890746E+01 0.10821046E+01 0.10751741E+01 0.10682829E+01 0.10614308E+01 - 0.10546176E+01 0.10478432E+01 0.10411073E+01 0.10344097E+01 0.10277503E+01 - 0.10211289E+01 0.10145452E+01 0.10079992E+01 0.10014906E+01 0.99501919E+00 - 0.98858484E+00 0.98218735E+00 0.97582655E+00 0.96950225E+00 0.96321427E+00 - 0.95696242E+00 0.95074654E+00 0.94456644E+00 0.93842195E+00 0.93231288E+00 - 0.92623907E+00 0.92020033E+00 0.91419649E+00 0.90822738E+00 0.90229282E+00 - 0.89639265E+00 0.89052668E+00 0.88469475E+00 0.87889669E+00 0.87313233E+00 - 0.86740150E+00 0.86170403E+00 0.85603975E+00 0.85040850E+00 0.84481011E+00 - 0.83924441E+00 0.83371124E+00 0.82821044E+00 0.82274184E+00 0.81730529E+00 - 0.81190060E+00 0.80652764E+00 0.80118623E+00 0.79587621E+00 0.79059744E+00 - 0.78534973E+00 0.78013295E+00 0.77494693E+00 0.76979152E+00 0.76466655E+00 - 0.75957188E+00 0.75450735E+00 0.74947281E+00 0.74446809E+00 0.73949306E+00 - 0.73454755E+00 0.72963142E+00 0.72474451E+00 0.71988667E+00 0.71505777E+00 - 0.71025764E+00 0.70548613E+00 0.70074311E+00 0.69602842E+00 0.69134192E+00 - 0.68668345E+00 0.68205289E+00 0.67745008E+00 0.67287487E+00 0.66832713E+00 - 0.66380671E+00 0.65931347E+00 0.65484727E+00 0.65040797E+00 0.64599543E+00 - 0.64160950E+00 0.63725005E+00 0.63291695E+00 0.62861004E+00 0.62432921E+00 - 0.62007430E+00 0.61584518E+00 0.61164172E+00 0.60746379E+00 0.60331124E+00 - 0.59918395E+00 0.59508178E+00 0.59100460E+00 0.58695228E+00 0.58292469E+00 - 0.57892169E+00 0.57494315E+00 0.57098895E+00 0.56705896E+00 0.56315304E+00 - 0.55927108E+00 0.55541294E+00 0.55157849E+00 0.54776761E+00 0.54398018E+00 - 0.54021607E+00 0.53647515E+00 0.53275730E+00 0.52906240E+00 0.52539032E+00 - 0.52174094E+00 0.51811414E+00 0.51450980E+00 0.51092780E+00 0.50736802E+00 - 0.50383033E+00 0.50031462E+00 0.49682077E+00 0.49334866E+00 0.48989817E+00 - 0.48646919E+00 0.48306161E+00 0.47967529E+00 0.47631014E+00 0.47296602E+00 - 0.46964284E+00 0.46634047E+00 0.46305880E+00 0.45979772E+00 0.45655712E+00 - 0.45333688E+00 0.45013690E+00 0.44695705E+00 0.44379724E+00 0.44065735E+00 - 0.43753727E+00 0.43443689E+00 0.43135611E+00 0.42829482E+00 0.42525290E+00 - 0.42223025E+00 0.41922677E+00 0.41624235E+00 0.41327689E+00 0.41033027E+00 - 0.40740239E+00 0.40449316E+00 0.40160246E+00 0.39873020E+00 0.39587626E+00 - 0.39304056E+00 0.39022298E+00 0.38742343E+00 0.38464180E+00 0.38187799E+00 - 0.37913191E+00 0.37640345E+00 0.37369252E+00 0.37099901E+00 0.36832283E+00 - 0.36566389E+00 0.36302208E+00 0.36039730E+00 0.35778947E+00 0.35519848E+00 - 0.35262424E+00 0.35006666E+00 0.34752563E+00 0.34500107E+00 0.34249289E+00 - 0.34000098E+00 0.33752526E+00 0.33506563E+00 0.33262200E+00 0.33019429E+00 - 0.32778239E+00 0.32538623E+00 0.32300570E+00 0.32064072E+00 0.31829120E+00 - 0.31595704E+00 0.31363818E+00 0.31133450E+00 0.30904593E+00 0.30677238E+00 - 0.30451376E+00 0.30226998E+00 0.30004096E+00 0.29782662E+00 0.29562686E+00 - 0.29344161E+00 0.29127077E+00 0.28911427E+00 0.28697202E+00 0.28484394E+00 - 0.28272994E+00 0.28062994E+00 0.27854387E+00 0.27647163E+00 0.27441314E+00 - 0.27236834E+00 0.27033712E+00 0.26831943E+00 0.26631516E+00 0.26432425E+00 - 0.26234662E+00 0.26038219E+00 0.25843087E+00 0.25649260E+00 0.25456729E+00 - 0.25265487E+00 0.25075525E+00 0.24886837E+00 0.24699415E+00 0.24513251E+00 - 0.24328337E+00 0.24144667E+00 0.23962232E+00 0.23781025E+00 0.23601039E+00 - 0.23422267E+00 0.23244700E+00 0.23068333E+00 0.22893157E+00 0.22719165E+00 - 0.22546350E+00 0.22374706E+00 0.22204224E+00 0.22034898E+00 0.21866721E+00 - 0.21699686E+00 0.21533785E+00 0.21369012E+00 0.21205360E+00 0.21042823E+00 - 0.20881392E+00 0.20721061E+00 0.20561825E+00 0.20403675E+00 0.20246605E+00 - 0.20090608E+00 0.19935679E+00 0.19781809E+00 0.19628993E+00 0.19477224E+00 - 0.19326495E+00 0.19176801E+00 0.19028134E+00 0.18880488E+00 0.18733857E+00 - 0.18588234E+00 0.18443613E+00 0.18299988E+00 0.18157352E+00 0.18015700E+00 - 0.17875024E+00 0.17735319E+00 0.17596579E+00 0.17458797E+00 0.17321968E+00 - 0.17186085E+00 0.17051142E+00 0.16917134E+00 0.16784054E+00 0.16651896E+00 - 0.16520655E+00 0.16390324E+00 0.16260898E+00 0.16132371E+00 0.16004737E+00 - 0.15877991E+00 0.15752125E+00 0.15627136E+00 0.15503017E+00 0.15379762E+00 - 0.15257366E+00 0.15135824E+00 0.15015129E+00 0.14895276E+00 0.14776259E+00 - 0.14658074E+00 0.14540714E+00 0.14424175E+00 0.14308450E+00 0.14193534E+00 - 0.14079423E+00 0.13966110E+00 0.13853590E+00 0.13741859E+00 0.13630910E+00 - 0.13520739E+00 0.13411340E+00 0.13302708E+00 0.13194838E+00 0.13087725E+00 - 0.12981363E+00 0.12875749E+00 0.12770876E+00 0.12666739E+00 0.12563334E+00 - 0.12460655E+00 0.12358698E+00 0.12257458E+00 0.12156929E+00 0.12057107E+00 - 0.11957988E+00 0.11859565E+00 0.11761834E+00 0.11664792E+00 0.11568431E+00 - 0.11472749E+00 0.11377740E+00 0.11283400E+00 0.11189724E+00 0.11096706E+00 - 0.11004344E+00 0.10912631E+00 0.10821564E+00 0.10731138E+00 0.10641348E+00 - 0.10552189E+00 0.10463659E+00 0.10375750E+00 0.10288461E+00 0.10201785E+00 - 0.10115718E+00 0.10030257E+00 0.99453968E-01 0.98611328E-01 0.97774609E-01 - 0.96943768E-01 0.96118763E-01 0.95299550E-01 0.94486087E-01 0.93678333E-01 - 0.92876245E-01 0.92079781E-01 0.91288900E-01 0.90503561E-01 0.89723723E-01 - 0.88949344E-01 0.88180384E-01 0.87416802E-01 0.86658559E-01 0.85905614E-01 - 0.85157927E-01 0.84415459E-01 0.83678170E-01 0.82946021E-01 0.82218973E-01 - 0.81496986E-01 0.80780023E-01 0.80068045E-01 0.79361013E-01 0.78658890E-01 - 0.77961638E-01 0.77269219E-01 0.76581595E-01 0.75898729E-01 0.75220585E-01 - 0.74547126E-01 0.73878314E-01 0.73214113E-01 0.72554488E-01 0.71899401E-01 - 0.71248818E-01 0.70602702E-01 0.69961018E-01 0.69323731E-01 0.68690806E-01 - 0.68062207E-01 0.67437901E-01 0.66817852E-01 0.66202027E-01 0.65590391E-01 - 0.64982910E-01 0.64379552E-01 0.63780281E-01 0.63185066E-01 0.62593873E-01 - 0.62006669E-01 0.61423421E-01 0.60844097E-01 0.60268666E-01 0.59697094E-01 - 0.59129350E-01 0.58565403E-01 0.58005220E-01 0.57448771E-01 0.56896025E-01 - 0.56346952E-01 0.55801519E-01 0.55259698E-01 0.54721457E-01 0.54186768E-01 - 0.53655600E-01 0.53127924E-01 0.52603711E-01 0.52082932E-01 0.51565557E-01 - 0.51051559E-01 0.50540909E-01 0.50033579E-01 0.49529541E-01 0.49028768E-01 - 0.48531231E-01 0.48036905E-01 0.47545762E-01 0.47057775E-01 0.46572918E-01 - 0.46091165E-01 0.45612490E-01 0.45136868E-01 0.44664273E-01 0.44194679E-01 - 0.43728063E-01 0.43264399E-01 0.42803664E-01 0.42345833E-01 0.41890883E-01 - 0.41438789E-01 0.40989530E-01 0.40543082E-01 0.40099422E-01 0.39658529E-01 - 0.39220380E-01 0.38784953E-01 0.38352228E-01 0.37922184E-01 0.37494799E-01 - 0.37070053E-01 0.36647927E-01 0.36228400E-01 0.35811453E-01 0.35397068E-01 - 0.34985225E-01 0.34575906E-01 0.34169093E-01 0.33764770E-01 0.33362918E-01 - 0.32963520E-01 0.32566561E-01 0.32172023E-01 0.31779893E-01 0.31390153E-01 - 0.31002790E-01 0.30617789E-01 0.30235136E-01 0.29854817E-01 0.29476819E-01 - 0.29101129E-01 0.28727736E-01 0.28356626E-01 0.27987790E-01 0.27621215E-01 - 0.27256892E-01 0.26894810E-01 0.26534960E-01 0.26177333E-01 0.25821920E-01 - 0.25468712E-01 0.25117704E-01 0.24768887E-01 0.24422255E-01 0.24077801E-01 - 0.23735521E-01 0.23395410E-01 0.23057462E-01 0.22721674E-01 0.22388043E-01 - 0.22056566E-01 0.21727240E-01 0.21400063E-01 0.21075035E-01 0.20752155E-01 - 0.20431423E-01 0.20112839E-01 0.19796405E-01 0.19482121E-01 0.19169991E-01 - 0.18860017E-01 0.18552202E-01 0.18246551E-01 0.17943067E-01 0.17641757E-01 - 0.17342625E-01 0.17045678E-01 0.16750923E-01 0.16458366E-01 0.16168017E-01 - 0.15879884E-01 0.15593974E-01 0.15310299E-01 0.15028869E-01 0.14749693E-01 - 0.14472783E-01 0.14198152E-01 0.13925810E-01 0.13655771E-01 0.13388049E-01 - 0.13122656E-01 0.12859607E-01 0.12598916E-01 0.12340599E-01 0.12084671E-01 - 0.11831148E-01 0.11580046E-01 0.11331381E-01 0.11085171E-01 0.10841432E-01 - 0.10600182E-01 0.10361440E-01 0.10125222E-01 0.98915469E-02 0.96604334E-02 - 0.94318998E-02 0.92059648E-02 0.89826471E-02 0.87619655E-02 0.85439387E-02 - 0.83285856E-02 0.81159249E-02 0.79059752E-02 0.76987549E-02 0.74942825E-02 - 0.72925759E-02 0.70936531E-02 0.68975315E-02 0.67042284E-02 0.65137604E-02 - 0.63261440E-02 0.61413949E-02 0.59595286E-02 0.57805596E-02 0.56045021E-02 - 0.54313695E-02 0.52611743E-02 0.50939285E-02 0.49296430E-02 0.47683280E-02 - 0.46099927E-02 0.44546452E-02 0.43022927E-02 0.41529412E-02 0.40065957E-02 - 0.38632598E-02 0.37229361E-02 0.35856257E-02 0.34513286E-02 0.33200432E-02 - 0.31917666E-02 0.30664946E-02 0.29442212E-02 0.28249390E-02 0.27086393E-02 - 0.25953115E-02 0.24849435E-02 0.23775215E-02 0.22730301E-02 0.21714524E-02 - 0.20727694E-02 0.19769608E-02 0.18840044E-02 0.17938763E-02 0.17065509E-02 - 0.16220009E-02 0.15401973E-02 0.14611096E-02 0.13847052E-02 0.13109504E-02 - 0.12398095E-02 0.11712453E-02 0.11052191E-02 0.10416907E-02 0.98061856E-03 - 0.92195948E-03 0.86566907E-03 0.81170163E-03 0.76001021E-03 0.71054671E-03 - 0.66326194E-03 0.61810569E-03 0.57502681E-03 0.53397332E-03 0.49489244E-03 - 0.45773073E-03 0.42243417E-03 0.38894821E-03 0.35721793E-03 0.32718808E-03 - 0.29880323E-03 0.27200781E-03 0.24674624E-03 0.22296306E-03 0.20060295E-03 - 0.17961090E-03 0.15993225E-03 0.14151285E-03 0.12429906E-03 0.10823794E-03 - 0.93277267E-04 0.79365628E-04 0.66452530E-04 0.54488447E-04 0.43424905E-04 - 0.33214542E-04 0.23811174E-04 0.15169849E-04 0.72469031E-05 0.00000000E+00 - 0.62792166E+05 0.62792166E+05 0.62792166E+05 0.62792166E+05 0.62792166E+05 - 0.62792166E+05 0.62792166E+05 0.62792166E+05 0.62792166E+05 0.62792166E+05 - 0.62792166E+05 0.62792166E+05 0.62792166E+05 0.62792166E+05 0.62792166E+05 - 0.62792166E+05 0.62792166E+05 0.62792166E+05 0.62792166E+05 0.62792166E+05 - 0.62792166E+05 0.62792166E+05 0.62792166E+05 0.62792166E+05 0.62792166E+05 - 0.62792166E+05 0.62792166E+05 0.62792166E+05 0.62792166E+05 0.62792166E+05 - 0.62792166E+05 0.62792166E+05 0.62792166E+05 0.62792166E+05 0.62792166E+05 - 0.62792166E+05 0.62792166E+05 0.62792166E+05 0.62792166E+05 0.62792166E+05 - 0.62792166E+05 0.61986382E+05 0.58238277E+05 0.54797131E+05 0.51631518E+05 - 0.48713845E+05 0.46019812E+05 0.43527957E+05 0.41219277E+05 0.39076902E+05 - 0.37085813E+05 0.35232615E+05 0.33505328E+05 0.31893216E+05 0.30386639E+05 - 0.28976921E+05 0.27656239E+05 0.26417527E+05 0.25254390E+05 0.24161031E+05 - 0.23132185E+05 0.22163064E+05 0.21249304E+05 0.20386926E+05 0.19572291E+05 - 0.18802071E+05 0.18073216E+05 0.17382927E+05 0.16728633E+05 0.16107968E+05 - 0.15518752E+05 0.14958977E+05 0.14426788E+05 0.13920469E+05 0.13438433E+05 - 0.12979212E+05 0.12541443E+05 0.12123860E+05 0.11725288E+05 0.11344634E+05 - 0.10980882E+05 0.10633082E+05 0.10300352E+05 0.99818665E+04 0.96768543E+04 - 0.93845954E+04 0.91044157E+04 0.88356841E+04 0.85778091E+04 0.83302361E+04 - 0.80924446E+04 0.78639458E+04 0.76442802E+04 0.74330159E+04 0.72297463E+04 - 0.70340885E+04 0.68456818E+04 0.66641860E+04 0.64892803E+04 0.63206617E+04 - 0.61580441E+04 0.60011570E+04 0.58497448E+04 0.57035653E+04 0.55623896E+04 - 0.54260007E+04 0.52941930E+04 0.51667715E+04 0.50435512E+04 0.49243567E+04 - 0.48090212E+04 0.46973864E+04 0.45893017E+04 0.44846241E+04 0.43832175E+04 - 0.42849521E+04 0.41897047E+04 0.40973576E+04 0.40077990E+04 0.39209220E+04 - 0.38366248E+04 0.37548101E+04 0.36753854E+04 0.35982619E+04 0.35233552E+04 - 0.34505843E+04 0.33798720E+04 0.33111445E+04 0.32443309E+04 0.31793637E+04 - 0.31161781E+04 0.30547120E+04 0.29949062E+04 0.29367036E+04 0.28800497E+04 - 0.28248922E+04 0.27711809E+04 0.27188677E+04 0.26679063E+04 0.26182524E+04 - 0.25698633E+04 0.25226983E+04 0.24767179E+04 0.24318843E+04 0.23881612E+04 - 0.23455137E+04 0.23039082E+04 0.22633123E+04 0.22236949E+04 0.21850260E+04 - 0.21472768E+04 0.21104195E+04 0.20744272E+04 0.20392743E+04 0.20049358E+04 - 0.19713878E+04 0.19386070E+04 0.19065713E+04 0.18752591E+04 0.18446496E+04 - 0.18147228E+04 0.17854593E+04 0.17568404E+04 0.17288481E+04 0.17014650E+04 - 0.16746741E+04 0.16484592E+04 0.16228045E+04 0.15976949E+04 0.15731156E+04 - 0.15490523E+04 0.15254913E+04 0.15024193E+04 0.14798232E+04 0.14576908E+04 - 0.14360097E+04 0.14147684E+04 0.13939555E+04 0.13735600E+04 0.13535713E+04 - 0.13339789E+04 0.13147730E+04 0.12959439E+04 0.12774820E+04 0.12593784E+04 - 0.12416241E+04 0.12242107E+04 0.12071296E+04 0.11903730E+04 0.11739329E+04 - 0.11578018E+04 0.11419722E+04 0.11264370E+04 0.11111892E+04 0.10962220E+04 - 0.10815289E+04 0.10671035E+04 0.10529395E+04 0.10390310E+04 0.10253721E+04 - 0.10119570E+04 0.99878025E+03 0.98583644E+03 0.97312033E+03 0.96062682E+03 - 0.94835094E+03 0.93628787E+03 0.92443291E+03 0.91278149E+03 0.90132916E+03 - 0.89007159E+03 0.87900456E+03 0.86812396E+03 0.85742580E+03 0.84690618E+03 - 0.83656130E+03 0.82638747E+03 0.81638108E+03 0.80653863E+03 0.79685670E+03 - 0.78733195E+03 0.77796112E+03 0.76874106E+03 0.75966867E+03 0.75074094E+03 - 0.74195494E+03 0.73330779E+03 0.72479669E+03 0.71641894E+03 0.70817185E+03 - 0.70005284E+03 0.69205937E+03 0.68418897E+03 0.67643923E+03 0.66880778E+03 - 0.66129233E+03 0.65389063E+03 0.64660049E+03 0.63941977E+03 0.63234636E+03 - 0.62537824E+03 0.61851340E+03 0.61174989E+03 0.60508580E+03 0.59851928E+03 - 0.59204850E+03 0.58567169E+03 0.57938710E+03 0.57319304E+03 0.56708784E+03 - 0.56106988E+03 0.55513757E+03 0.54928936E+03 0.54352373E+03 0.53783919E+03 - 0.53223428E+03 0.52670760E+03 0.52125774E+03 0.51588334E+03 0.51058307E+03 - 0.50535564E+03 0.50019975E+03 0.49511418E+03 0.49009768E+03 0.48514908E+03 - 0.48026719E+03 0.47545087E+03 0.47069900E+03 0.46601047E+03 0.46138422E+03 - 0.45681919E+03 0.45231434E+03 0.44786866E+03 0.44348117E+03 0.43915089E+03 - 0.43487687E+03 0.43065818E+03 0.42649391E+03 0.42238316E+03 0.41832505E+03 - 0.41431874E+03 0.41036336E+03 0.40645810E+03 0.40260215E+03 0.39879472E+03 - 0.39503502E+03 0.39132229E+03 0.38765579E+03 0.38403479E+03 0.38045855E+03 - 0.37692639E+03 0.37343759E+03 0.36999150E+03 0.36658743E+03 0.36322474E+03 - 0.35990279E+03 0.35662094E+03 0.35337858E+03 0.35017510E+03 0.34700992E+03 - 0.34388244E+03 0.34079209E+03 0.33773832E+03 0.33472056E+03 0.33173829E+03 - 0.32879096E+03 0.32587805E+03 0.32299906E+03 0.32015348E+03 0.31734081E+03 - 0.31456057E+03 0.31181229E+03 0.30909549E+03 0.30640972E+03 0.30375452E+03 - 0.30112945E+03 0.29853408E+03 0.29596797E+03 0.29343071E+03 0.29092189E+03 - 0.28844109E+03 0.28598792E+03 0.28356199E+03 0.28116290E+03 0.27879029E+03 - 0.27644378E+03 0.27412301E+03 0.27182761E+03 0.26955723E+03 0.26731152E+03 - 0.26509015E+03 0.26289278E+03 0.26071907E+03 0.25856870E+03 0.25644135E+03 - 0.25433671E+03 0.25225448E+03 0.25019434E+03 0.24815599E+03 0.24613915E+03 - 0.24414353E+03 0.24216883E+03 0.24021479E+03 0.23828112E+03 0.23636756E+03 - 0.23447384E+03 0.23259969E+03 0.23074487E+03 0.22890911E+03 0.22709217E+03 - 0.22529380E+03 0.22351376E+03 0.22175181E+03 0.22000772E+03 0.21828126E+03 - 0.21657220E+03 0.21488032E+03 0.21320539E+03 0.21154721E+03 0.20990555E+03 - 0.20828021E+03 0.20667099E+03 0.20507768E+03 0.20350007E+03 0.20193798E+03 - 0.20039121E+03 0.19885956E+03 0.19734285E+03 0.19584090E+03 0.19435352E+03 - 0.19288053E+03 0.19142175E+03 0.18997702E+03 0.18854615E+03 0.18712898E+03 - 0.18572534E+03 0.18433508E+03 0.18295802E+03 0.18159400E+03 0.18024288E+03 - 0.17890449E+03 0.17757868E+03 0.17626531E+03 0.17496422E+03 0.17367527E+03 - 0.17239831E+03 0.17113321E+03 0.16987981E+03 0.16863800E+03 0.16740762E+03 - 0.16618855E+03 0.16498065E+03 0.16378380E+03 0.16259786E+03 0.16142271E+03 - 0.16025823E+03 0.15910429E+03 0.15796076E+03 0.15682754E+03 0.15570451E+03 - 0.15459154E+03 0.15348852E+03 0.15239535E+03 0.15131190E+03 0.15023808E+03 - 0.14917376E+03 0.14811885E+03 0.14707324E+03 0.14603682E+03 0.14500949E+03 - 0.14399116E+03 0.14298172E+03 0.14198107E+03 0.14098911E+03 0.14000576E+03 - 0.13903092E+03 0.13806448E+03 0.13710637E+03 0.13615649E+03 0.13521475E+03 - 0.13428106E+03 0.13335534E+03 0.13243750E+03 0.13152745E+03 0.13062511E+03 - 0.12973040E+03 0.12884324E+03 0.12796354E+03 0.12709123E+03 0.12622623E+03 - 0.12536846E+03 0.12451785E+03 0.12367431E+03 0.12283778E+03 0.12200818E+03 - 0.12118544E+03 0.12036948E+03 0.11956025E+03 0.11875766E+03 0.11796164E+03 - 0.11717214E+03 0.11638908E+03 0.11561240E+03 0.11484202E+03 0.11407790E+03 - 0.11331995E+03 0.11256813E+03 0.11182236E+03 0.11108259E+03 0.11034875E+03 - 0.10962078E+03 0.10889864E+03 0.10818225E+03 0.10747155E+03 0.10676650E+03 - 0.10606704E+03 0.10537311E+03 0.10468465E+03 0.10400161E+03 0.10332394E+03 - 0.10265158E+03 0.10198449E+03 0.10132261E+03 0.10066588E+03 0.10001426E+03 - 0.99367702E+02 0.98726151E+02 0.98089561E+02 0.97457883E+02 0.96831070E+02 - 0.96209074E+02 0.95591850E+02 0.94979350E+02 0.94371531E+02 0.93768346E+02 - 0.93169752E+02 0.92575706E+02 0.91986162E+02 0.91401080E+02 0.90820416E+02 - 0.90244130E+02 0.89672178E+02 0.89104522E+02 0.88541120E+02 0.87981932E+02 - 0.87426920E+02 0.86876043E+02 0.86329264E+02 0.85786545E+02 0.85247847E+02 - 0.84713134E+02 0.84182369E+02 0.83655516E+02 0.83132538E+02 0.82613399E+02 - 0.82098066E+02 0.81586502E+02 0.81078674E+02 0.80574548E+02 0.80074089E+02 - 0.79577265E+02 0.79084043E+02 0.78594391E+02 0.78108275E+02 0.77625665E+02 - 0.77146529E+02 0.76670836E+02 0.76198555E+02 0.75729655E+02 0.75264107E+02 - 0.74801881E+02 0.74342948E+02 0.73887277E+02 0.73434841E+02 0.72985612E+02 - 0.72539560E+02 0.72096658E+02 0.71656878E+02 0.71220194E+02 0.70786577E+02 - 0.70356003E+02 0.69928443E+02 0.69503872E+02 0.69082264E+02 0.68663594E+02 - 0.68247836E+02 0.67834965E+02 0.67424957E+02 0.67017786E+02 0.66613429E+02 - 0.66211862E+02 0.65813061E+02 0.65417002E+02 0.65023662E+02 0.64633018E+02 - 0.64245048E+02 0.63859729E+02 0.63477038E+02 0.63096954E+02 0.62719454E+02 - 0.62344518E+02 0.61972123E+02 0.61602248E+02 0.61234873E+02 0.60869977E+02 - 0.60507539E+02 0.60147539E+02 0.59789957E+02 0.59434773E+02 0.59081967E+02 - 0.58731520E+02 0.58383412E+02 0.58037624E+02 0.57694138E+02 0.57352934E+02 - 0.57013995E+02 0.56677301E+02 0.56342835E+02 0.56010578E+02 0.55680513E+02 - 0.55352622E+02 0.55026888E+02 0.54703292E+02 0.54381820E+02 0.54062452E+02 - 0.53745173E+02 0.53429966E+02 0.53116814E+02 0.52805701E+02 0.52496611E+02 - 0.52189528E+02 0.51884436E+02 0.51581320E+02 0.51280164E+02 0.50980952E+02 - 0.50683670E+02 0.50388302E+02 0.50094833E+02 0.49803249E+02 0.49513535E+02 - 0.49225676E+02 0.48939658E+02 0.48655467E+02 0.48373089E+02 0.48092510E+02 - 0.47813715E+02 0.47536692E+02 0.47261427E+02 0.46987905E+02 0.46716115E+02 - 0.46446043E+02 0.46177675E+02 0.45910999E+02 0.45646002E+02 0.45382671E+02 - 0.45120994E+02 0.44860958E+02 0.44602551E+02 0.44345761E+02 0.44090575E+02 - 0.43836981E+02 0.43584969E+02 0.43334525E+02 0.43085638E+02 0.42838297E+02 - 0.42592490E+02 0.42348205E+02 0.42105432E+02 0.41864160E+02 0.41624376E+02 - 0.41386071E+02 0.41149234E+02 0.40913853E+02 0.40679919E+02 0.40447419E+02 - 0.40216345E+02 0.39986686E+02 0.39758431E+02 0.39531570E+02 0.39306093E+02 - 0.39081990E+02 0.38859252E+02 0.38637868E+02 0.38417828E+02 0.38199124E+02 - 0.37981745E+02 0.37765681E+02 0.37550925E+02 0.37337465E+02 0.37125293E+02 - 0.36914401E+02 0.36704777E+02 0.36496415E+02 0.36289305E+02 0.36083437E+02 - 0.35878804E+02 0.35675396E+02 0.35473205E+02 0.35272222E+02 0.35072440E+02 - 0.34873849E+02 0.34676441E+02 0.34480208E+02 0.34285141E+02 0.34091234E+02 - 0.33898477E+02 0.33706863E+02 0.33516384E+02 0.33327031E+02 0.33138798E+02 - 0.32951676E+02 0.32765658E+02 0.32580737E+02 0.32396904E+02 0.32214152E+02 - 0.32032475E+02 0.31851864E+02 0.31672312E+02 0.31493813E+02 0.31316358E+02 - 0.31139942E+02 0.30964557E+02 0.30790195E+02 0.30616851E+02 0.30444517E+02 - 0.30273186E+02 0.30102853E+02 0.29933509E+02 0.29765148E+02 0.29597765E+02 - 0.29431352E+02 0.29265903E+02 0.29101411E+02 0.28937870E+02 0.28775275E+02 - 0.28613618E+02 0.28452893E+02 0.28293094E+02 0.28134216E+02 0.27976252E+02 - 0.27819196E+02 0.27663042E+02 0.27507784E+02 0.27353416E+02 0.27199933E+02 - 0.27047329E+02 0.26895598E+02 0.26744735E+02 0.26594733E+02 0.26445587E+02 - 0.26297293E+02 0.26149843E+02 0.26003233E+02 0.25857457E+02 0.25712510E+02 - 0.25568387E+02 0.25425082E+02 0.25282591E+02 0.25140907E+02 0.25000026E+02 - 0.24859942E+02 0.24720651E+02 0.24582148E+02 0.24444427E+02 0.24307484E+02 - 0.24171313E+02 0.24035910E+02 0.23901270E+02 0.23767388E+02 0.23634259E+02 - 0.23501879E+02 0.23370243E+02 0.23239346E+02 0.23109184E+02 0.22979752E+02 - 0.22851045E+02 0.22723059E+02 0.22595789E+02 0.22469232E+02 0.22343382E+02 - 0.22218235E+02 0.22093787E+02 0.21970034E+02 0.21846970E+02 0.21724593E+02 - 0.21602898E+02 0.21481880E+02 0.21361535E+02 0.21241860E+02 0.21122850E+02 - 0.21004501E+02 0.20886809E+02 0.20769770E+02 0.20653380E+02 0.20537635E+02 - 0.20422531E+02 0.20308065E+02 0.20194232E+02 0.20081029E+02 0.19968452E+02 - 0.19856496E+02 0.19745159E+02 0.19634437E+02 0.19524325E+02 0.19414820E+02 - 0.19305919E+02 0.19197618E+02 0.19089914E+02 0.18982802E+02 0.18876279E+02 - 0.18770342E+02 0.18664987E+02 0.18560211E+02 0.18456011E+02 0.18352382E+02 - 0.18249322E+02 0.18146827E+02 0.18044894E+02 0.17943519E+02 0.17842700E+02 - 0.17742432E+02 0.17642714E+02 0.17543540E+02 0.17444909E+02 0.17346817E+02 - 0.17249261E+02 0.17152238E+02 0.17055745E+02 0.16959778E+02 0.16864335E+02 - 0.16769412E+02 0.16675007E+02 0.16581116E+02 0.16487736E+02 0.16394866E+02 - 0.16302500E+02 0.16210638E+02 0.16119275E+02 0.16028409E+02 0.15938037E+02 - 0.15848156E+02 0.15758763E+02 0.15669856E+02 0.15581432E+02 0.15493488E+02 - 0.15406021E+02 0.15319029E+02 0.15232508E+02 0.15146456E+02 0.15060871E+02 - 0.14975750E+02 0.14891090E+02 0.14806888E+02 0.14723142E+02 0.14639850E+02 - 0.14557008E+02 0.14474615E+02 0.14392667E+02 0.14311162E+02 0.14230098E+02 - 0.14149473E+02 0.14069283E+02 0.13989526E+02 0.13910200E+02 0.13831303E+02 - 0.13752831E+02 0.13674784E+02 0.13597157E+02 0.13519950E+02 0.13443159E+02 - 0.13366782E+02 0.13290817E+02 0.13215262E+02 0.13140114E+02 0.13065372E+02 - 0.12991032E+02 0.12917093E+02 0.12843552E+02 0.12770407E+02 0.12697657E+02 - 0.12625298E+02 0.12553329E+02 0.12481748E+02 0.12410552E+02 0.12339739E+02 - 0.12269307E+02 0.12199254E+02 0.12129579E+02 0.12060278E+02 0.11991350E+02 - 0.11922793E+02 0.11854605E+02 0.11786784E+02 0.11719327E+02 0.11652233E+02 - 0.11585500E+02 0.11519126E+02 0.11453108E+02 0.11387446E+02 0.11322137E+02 - 0.11257178E+02 0.11192569E+02 0.11128307E+02 0.11064391E+02 0.11000818E+02 - 0.10937587E+02 0.10874696E+02 0.10812143E+02 0.10749926E+02 0.10688043E+02 - 0.10626493E+02 0.10565273E+02 0.10504383E+02 0.10443820E+02 0.10383583E+02 - 0.10323669E+02 0.10264077E+02 0.10204805E+02 0.10145852E+02 0.10087216E+02 - 0.10028895E+02 0.99708877E+01 0.99131920E+01 0.98558064E+01 0.97987294E+01 - 0.97419592E+01 0.96854942E+01 0.96293328E+01 0.95734733E+01 0.95179143E+01 - 0.94626540E+01 0.94076909E+01 0.93530234E+01 0.92986500E+01 0.92445690E+01 - 0.91907790E+01 0.91372784E+01 0.90840657E+01 0.90311393E+01 0.89784978E+01 - 0.89261396E+01 0.88740633E+01 0.88222673E+01 0.87707502E+01 0.87195105E+01 - 0.86685468E+01 0.86178576E+01 0.85674414E+01 0.85172969E+01 0.84674226E+01 - 0.84178171E+01 0.83684789E+01 0.83194068E+01 0.82705992E+01 0.82220548E+01 - 0.81737722E+01 0.81257501E+01 0.80779871E+01 0.80304819E+01 0.79832330E+01 - 0.79362392E+01 0.78894991E+01 0.78430114E+01 0.77967748E+01 0.77507880E+01 - 0.77050497E+01 0.76595585E+01 0.76143133E+01 0.75693127E+01 0.75245555E+01 - 0.74800403E+01 0.74357660E+01 0.73917313E+01 0.73479349E+01 0.73043756E+01 - 0.72610522E+01 0.72179635E+01 0.71751082E+01 0.71324852E+01 0.70900931E+01 - 0.70479310E+01 0.70059974E+01 0.69642914E+01 0.69228116E+01 0.68815570E+01 - 0.68405263E+01 0.67997185E+01 0.67591323E+01 0.67187666E+01 0.66786203E+01 - 0.66386923E+01 0.65989814E+01 0.65594865E+01 0.65202065E+01 0.64811403E+01 - 0.64422868E+01 0.64036449E+01 0.63652135E+01 0.63269915E+01 0.62889779E+01 - 0.62511716E+01 0.62135715E+01 0.61761765E+01 0.61389857E+01 0.61019979E+01 - 0.60652122E+01 0.60286274E+01 0.59922426E+01 0.59560567E+01 0.59200688E+01 - 0.58842777E+01 0.58486825E+01 0.58132822E+01 0.57780758E+01 0.57430623E+01 - 0.57082407E+01 0.56736100E+01 0.56391693E+01 0.56049176E+01 0.55708539E+01 - 0.55369772E+01 0.55032866E+01 0.54697812E+01 0.54364599E+01 0.54033219E+01 - 0.53703663E+01 0.53375920E+01 0.53049982E+01 0.52725840E+01 0.52403484E+01 - 0.52082904E+01 0.51764093E+01 0.51447041E+01 0.51131740E+01 0.50818179E+01 - 0.50506350E+01 0.50196246E+01 0.49887855E+01 0.49581171E+01 0.49276184E+01 - 0.48972885E+01 0.48671266E+01 0.48371319E+01 0.48073034E+01 0.47776404E+01 - 0.47481420E+01 0.47188074E+01 0.46896356E+01 0.46606260E+01 0.46317776E+01 - 0.46030897E+01 0.45745614E+01 0.45461919E+01 0.45179804E+01 0.44899261E+01 - 0.44620282E+01 0.44342859E+01 0.44066984E+01 0.43792649E+01 0.43519847E+01 - 0.43248569E+01 0.42978808E+01 0.42710556E+01 0.42443805E+01 0.42178548E+01 - 0.41914777E+01 0.41652484E+01 0.41391662E+01 0.41132304E+01 0.40874402E+01 - 0.40617948E+01 0.40362935E+01 0.40109357E+01 0.39857204E+01 0.39606471E+01 - 0.39357150E+01 0.39109234E+01 0.38862715E+01 0.38617587E+01 0.38373842E+01 - 0.38131474E+01 0.37890475E+01 0.37650838E+01 0.37412556E+01 0.37175623E+01 - 0.36940032E+01 0.36705775E+01 0.36472846E+01 0.36241238E+01 0.36010944E+01 - 0.35781958E+01 0.35554273E+01 0.35327882E+01 0.35102779E+01 0.34878957E+01 - 0.34656409E+01 0.34435129E+01 0.34215111E+01 0.33996348E+01 0.33778833E+01 - 0.33562561E+01 0.33347524E+01 0.33133717E+01 0.32921133E+01 0.32709766E+01 - 0.32499610E+01 0.32290658E+01 0.32082905E+01 0.31876343E+01 0.31670968E+01 - 0.31466773E+01 0.31263751E+01 0.31061897E+01 0.30861206E+01 0.30661670E+01 - 0.30463284E+01 0.30266042E+01 0.30069938E+01 0.29874966E+01 0.29681121E+01 - 0.29488396E+01 0.29296786E+01 0.29106286E+01 0.28916888E+01 0.28728589E+01 - 0.28541381E+01 0.28355260E+01 0.28170220E+01 0.27986255E+01 0.27803359E+01 - 0.27621528E+01 0.27440755E+01 0.27261036E+01 0.27082364E+01 0.26904735E+01 - 0.26728142E+01 0.26552581E+01 0.26378046E+01 0.26204532E+01 0.26032034E+01 - 0.25860546E+01 0.25690062E+01 0.25520579E+01 0.25352091E+01 0.25184591E+01 - 0.25018077E+01 0.24852541E+01 0.24687980E+01 0.24524387E+01 0.24361759E+01 - 0.24200090E+01 0.24039374E+01 0.23879608E+01 0.23720786E+01 0.23562902E+01 - 0.23405954E+01 0.23249934E+01 0.23094839E+01 0.22940664E+01 0.22787403E+01 - 0.22635053E+01 0.22483608E+01 0.22333063E+01 0.22183415E+01 0.22034657E+01 - 0.21886786E+01 0.21739797E+01 0.21593685E+01 0.21448445E+01 0.21304074E+01 - 0.21160566E+01 0.21017917E+01 0.20876122E+01 0.20735178E+01 0.20595078E+01 - 0.20455820E+01 0.20317398E+01 0.20179808E+01 0.20043046E+01 0.19907107E+01 - 0.19771987E+01 0.19637682E+01 0.19504187E+01 0.19371499E+01 0.19239612E+01 - 0.19108522E+01 0.18978226E+01 0.18848719E+01 0.18719996E+01 0.18592055E+01 - 0.18464890E+01 0.18338497E+01 0.18212873E+01 0.18088013E+01 0.17963913E+01 - 0.17840570E+01 0.17717978E+01 0.17596135E+01 0.17475035E+01 0.17354676E+01 - 0.17235052E+01 0.17116161E+01 0.16997998E+01 0.16880560E+01 0.16763842E+01 - 0.16647841E+01 0.16532552E+01 0.16417972E+01 0.16304098E+01 0.16190925E+01 - 0.16078449E+01 0.15966667E+01 0.15855576E+01 0.15745170E+01 0.15635447E+01 - 0.15526404E+01 0.15418035E+01 0.15310338E+01 0.15203309E+01 0.15096945E+01 - 0.14991241E+01 0.14886195E+01 0.14781802E+01 0.14678059E+01 0.14574963E+01 - 0.14472509E+01 0.14370696E+01 0.14269518E+01 0.14168973E+01 0.14069057E+01 - 0.13969767E+01 0.13871099E+01 0.13773050E+01 0.13675617E+01 0.13578796E+01 - 0.13482583E+01 0.13386976E+01 0.13291971E+01 0.13197565E+01 0.13103754E+01 - 0.13010536E+01 0.12917907E+01 0.12825863E+01 0.12734402E+01 0.12643521E+01 - 0.12553215E+01 0.12463483E+01 0.12374320E+01 0.12285724E+01 0.12197691E+01 - 0.12110219E+01 0.12023304E+01 0.11936944E+01 0.11851134E+01 0.11765873E+01 - 0.11681156E+01 0.11596982E+01 0.11513346E+01 0.11430246E+01 0.11347680E+01 - 0.11265643E+01 0.11184134E+01 0.11103148E+01 0.11022684E+01 0.10942738E+01 - 0.10863307E+01 0.10784389E+01 0.10705980E+01 0.10628078E+01 0.10550680E+01 - 0.10473783E+01 0.10397384E+01 0.10321480E+01 0.10246070E+01 0.10171149E+01 - 0.10096715E+01 0.10022765E+01 0.99492969E+00 0.98763077E+00 0.98037946E+00 - 0.97317550E+00 0.96601861E+00 0.95890853E+00 0.95184499E+00 0.94482773E+00 - 0.93785648E+00 0.93093098E+00 0.92405097E+00 0.91721619E+00 0.91042638E+00 - 0.90368129E+00 0.89698065E+00 0.89032422E+00 0.88371174E+00 0.87714296E+00 - 0.87061763E+00 0.86413549E+00 0.85769630E+00 0.85129982E+00 0.84494579E+00 - 0.83863397E+00 0.83236412E+00 0.82613599E+00 0.81994934E+00 0.81380394E+00 - 0.80769954E+00 0.80163591E+00 0.79561281E+00 0.78963000E+00 0.78368726E+00 - 0.77778433E+00 0.77192101E+00 0.76609705E+00 0.76031222E+00 0.75456630E+00 - 0.74885906E+00 0.74319026E+00 0.73755970E+00 0.73196714E+00 0.72641236E+00 - 0.72089513E+00 0.71541525E+00 0.70997248E+00 0.70456661E+00 0.69919742E+00 - 0.69386470E+00 0.68856822E+00 0.68330779E+00 0.67808317E+00 0.67289417E+00 - 0.66774056E+00 0.66262215E+00 0.65753871E+00 0.65249005E+00 0.64747595E+00 - 0.64249622E+00 0.63755063E+00 0.63263900E+00 0.62776112E+00 0.62291679E+00 - 0.61810580E+00 0.61332796E+00 0.60858306E+00 0.60387092E+00 0.59919133E+00 - 0.59454410E+00 0.58992903E+00 0.58534593E+00 0.58079461E+00 0.57627488E+00 - 0.57178654E+00 0.56732940E+00 0.56290328E+00 0.55850799E+00 0.55414334E+00 - 0.54980914E+00 0.54550522E+00 0.54123138E+00 0.53698744E+00 0.53277323E+00 - 0.52858856E+00 0.52443324E+00 0.52030711E+00 0.51620998E+00 0.51214167E+00 - 0.50810201E+00 0.50409082E+00 0.50010793E+00 0.49615316E+00 0.49222635E+00 - 0.48832731E+00 0.48445588E+00 0.48061188E+00 0.47679515E+00 0.47300552E+00 - 0.46924283E+00 0.46550689E+00 0.46179756E+00 0.45811466E+00 0.45445803E+00 - 0.45082750E+00 0.44722292E+00 0.44364411E+00 0.44009093E+00 0.43656321E+00 - 0.43306080E+00 0.42958352E+00 0.42613123E+00 0.42270378E+00 0.41930099E+00 - 0.41592273E+00 0.41256882E+00 0.40923913E+00 0.40593350E+00 0.40265178E+00 - 0.39939381E+00 0.39615945E+00 0.39294854E+00 0.38976095E+00 0.38659651E+00 - 0.38345509E+00 0.38033653E+00 0.37724070E+00 0.37416744E+00 0.37111662E+00 - 0.36808809E+00 0.36508171E+00 0.36209733E+00 0.35913482E+00 0.35619404E+00 - 0.35327484E+00 0.35037709E+00 0.34750066E+00 0.34464539E+00 0.34181116E+00 - 0.33899784E+00 0.33620528E+00 0.33343336E+00 0.33068193E+00 0.32795087E+00 - 0.32524005E+00 0.32254933E+00 0.31987858E+00 0.31722768E+00 0.31459649E+00 - 0.31198489E+00 0.30939275E+00 0.30681994E+00 0.30426634E+00 0.30173181E+00 - 0.29921625E+00 0.29671951E+00 0.29424148E+00 0.29178204E+00 0.28934105E+00 - 0.28691841E+00 0.28451399E+00 0.28212768E+00 0.27975934E+00 0.27740886E+00 - 0.27507613E+00 0.27276103E+00 0.27046344E+00 0.26818324E+00 0.26592032E+00 - 0.26367456E+00 0.26144585E+00 0.25923408E+00 0.25703913E+00 0.25486089E+00 - 0.25269925E+00 0.25055410E+00 0.24842533E+00 0.24631283E+00 0.24421648E+00 - 0.24213619E+00 0.24007183E+00 0.23802331E+00 0.23599052E+00 0.23397336E+00 - 0.23197171E+00 0.22998547E+00 0.22801454E+00 0.22605881E+00 0.22411819E+00 - 0.22219256E+00 0.22028183E+00 0.21838589E+00 0.21650465E+00 0.21463800E+00 - 0.21278585E+00 0.21094809E+00 0.20912464E+00 0.20731538E+00 0.20552022E+00 - 0.20373906E+00 0.20197182E+00 0.20021839E+00 0.19847868E+00 0.19675259E+00 - 0.19504003E+00 0.19334091E+00 0.19165513E+00 0.18998261E+00 0.18832324E+00 - 0.18667694E+00 0.18504362E+00 0.18342319E+00 0.18181555E+00 0.18022062E+00 - 0.17863832E+00 0.17706854E+00 0.17551121E+00 0.17396623E+00 0.17243353E+00 - 0.17091301E+00 0.16940459E+00 0.16790819E+00 0.16642372E+00 0.16495109E+00 - 0.16349022E+00 0.16204103E+00 0.16060344E+00 0.15917737E+00 0.15776273E+00 - 0.15635944E+00 0.15496742E+00 0.15358659E+00 0.15221688E+00 0.15085820E+00 - 0.14951048E+00 0.14817363E+00 0.14684758E+00 0.14553225E+00 0.14422757E+00 - 0.14293345E+00 0.14164983E+00 0.14037663E+00 0.13911377E+00 0.13786118E+00 - 0.13661878E+00 0.13538650E+00 0.13416427E+00 0.13295202E+00 0.13174967E+00 - 0.13055715E+00 0.12937440E+00 0.12820133E+00 0.12703788E+00 0.12588398E+00 - 0.12473956E+00 0.12360455E+00 0.12247888E+00 0.12136248E+00 0.12025529E+00 - 0.11915724E+00 0.11806827E+00 0.11698829E+00 0.11591726E+00 0.11485509E+00 - 0.11380174E+00 0.11275713E+00 0.11172120E+00 0.11069388E+00 0.10967511E+00 - 0.10866483E+00 0.10766298E+00 0.10666948E+00 0.10568429E+00 0.10470733E+00 - 0.10373856E+00 0.10277789E+00 0.10182529E+00 0.10088068E+00 0.99944001E-01 - 0.99015202E-01 0.98094221E-01 0.97180998E-01 0.96275476E-01 0.95377596E-01 - 0.94487302E-01 0.93604536E-01 0.92729241E-01 0.91861361E-01 0.91000840E-01 - 0.90147622E-01 0.89301652E-01 0.88462875E-01 0.87631237E-01 0.86806683E-01 - 0.85989159E-01 0.85178612E-01 0.84374989E-01 0.83578236E-01 0.82788302E-01 - 0.82005134E-01 0.81228680E-01 0.80458889E-01 0.79695711E-01 0.78939093E-01 - 0.78188986E-01 0.77445339E-01 0.76708103E-01 0.75977228E-01 0.75252665E-01 - 0.74534366E-01 0.73822282E-01 0.73116364E-01 0.72416565E-01 0.71722837E-01 - 0.71035134E-01 0.70353408E-01 0.69677612E-01 0.69007702E-01 0.68343629E-01 - 0.67685350E-01 0.67032818E-01 0.66385988E-01 0.65744816E-01 0.65109258E-01 - 0.64479269E-01 0.63854805E-01 0.63235824E-01 0.62622281E-01 0.62014134E-01 - 0.61411340E-01 0.60813856E-01 0.60221642E-01 0.59634654E-01 0.59052852E-01 - 0.58476194E-01 0.57904639E-01 0.57338147E-01 0.56776678E-01 0.56220190E-01 - 0.55668645E-01 0.55122003E-01 0.54580225E-01 0.54043271E-01 0.53511103E-01 - 0.52983682E-01 0.52460971E-01 0.51942931E-01 0.51429525E-01 0.50920715E-01 - 0.50416465E-01 0.49916737E-01 0.49421494E-01 0.48930701E-01 0.48444321E-01 - 0.47962318E-01 0.47484658E-01 0.47011303E-01 0.46542220E-01 0.46077374E-01 - 0.45616730E-01 0.45160253E-01 0.44707909E-01 0.44259665E-01 0.43815487E-01 - 0.43375342E-01 0.42939196E-01 0.42507017E-01 0.42078771E-01 0.41654427E-01 - 0.41233952E-01 0.40817314E-01 0.40404481E-01 0.39995423E-01 0.39590107E-01 - 0.39188502E-01 0.38790578E-01 0.38396304E-01 0.38005650E-01 0.37618585E-01 - 0.37235080E-01 0.36855105E-01 0.36478630E-01 0.36105625E-01 0.35736063E-01 - 0.35369913E-01 0.35007148E-01 0.34647738E-01 0.34291656E-01 0.33938874E-01 - 0.33589363E-01 0.33243096E-01 0.32900045E-01 0.32560184E-01 0.32223485E-01 - 0.31889922E-01 0.31559468E-01 0.31232095E-01 0.30907779E-01 0.30586494E-01 - 0.30268212E-01 0.29952909E-01 0.29640559E-01 0.29331137E-01 0.29024618E-01 - 0.28720977E-01 0.28420189E-01 0.28122229E-01 0.27827074E-01 0.27534699E-01 - 0.27245080E-01 0.26958194E-01 0.26674017E-01 0.26392525E-01 0.26113695E-01 - 0.25837504E-01 0.25563929E-01 0.25292948E-01 0.25024537E-01 0.24758675E-01 - 0.24495339E-01 0.24234508E-01 0.23976159E-01 0.23720271E-01 0.23466821E-01 - 0.23215790E-01 0.22967155E-01 0.22720896E-01 0.22476991E-01 0.22235421E-01 - 0.21996163E-01 0.21759199E-01 0.21524508E-01 0.21292069E-01 0.21061863E-01 - 0.20833871E-01 0.20608071E-01 0.20384446E-01 0.20162975E-01 0.19943640E-01 - 0.19726421E-01 0.19511301E-01 0.19298259E-01 0.19087277E-01 0.18878338E-01 - 0.18671422E-01 0.18466513E-01 0.18263590E-01 0.18062638E-01 0.17863638E-01 - 0.17666573E-01 0.17471425E-01 0.17278177E-01 0.17086812E-01 0.16897313E-01 - 0.16709662E-01 0.16523845E-01 0.16339843E-01 0.16157640E-01 0.15977221E-01 - 0.15798568E-01 0.15621667E-01 0.15446500E-01 0.15273052E-01 0.15101308E-01 - 0.14931252E-01 0.14762868E-01 0.14596142E-01 0.14431058E-01 0.14267601E-01 - 0.14105757E-01 0.13945510E-01 0.13786846E-01 0.13629750E-01 0.13474208E-01 - 0.13320205E-01 0.13167729E-01 0.13016763E-01 0.12867295E-01 0.12719311E-01 - 0.12572797E-01 0.12427739E-01 0.12284124E-01 0.12141939E-01 0.12001170E-01 - 0.11861805E-01 0.11723829E-01 0.11587231E-01 0.11451998E-01 0.11318116E-01 - 0.11185574E-01 0.11054358E-01 0.10924457E-01 0.10795858E-01 0.10668549E-01 - 0.10542518E-01 0.10417753E-01 0.10294243E-01 0.10171975E-01 0.10050937E-01 - 0.99311196E-02 0.98125096E-02 0.96950963E-02 0.95788683E-02 0.94638146E-02 - 0.93499240E-02 0.92371858E-02 0.91255890E-02 0.90151229E-02 0.89057769E-02 - 0.87975405E-02 0.86904031E-02 0.85843544E-02 0.84793842E-02 0.83754823E-02 - 0.82726385E-02 0.81708430E-02 0.80700858E-02 0.79703571E-02 0.78716472E-02 - 0.77739465E-02 0.76772453E-02 0.75815344E-02 0.74868042E-02 0.73930455E-02 - 0.73002492E-02 0.72084061E-02 0.71175071E-02 0.70275434E-02 0.69385061E-02 - 0.68503865E-02 0.67631757E-02 0.66768653E-02 0.65914467E-02 0.65069114E-02 - 0.64232511E-02 0.63404575E-02 0.62585224E-02 0.61774376E-02 0.60971952E-02 - 0.60177870E-02 0.59392054E-02 0.58614423E-02 0.57844902E-02 0.57083412E-02 - 0.56329879E-02 0.55584226E-02 0.54846381E-02 0.54116268E-02 0.53393815E-02 - 0.52678950E-02 0.51971601E-02 0.51271697E-02 0.50579168E-02 0.49893946E-02 - 0.49215960E-02 0.48545144E-02 0.47881429E-02 0.47224750E-02 0.46575040E-02 - 0.45932234E-02 0.45296267E-02 0.44667076E-02 0.44044596E-02 0.43428767E-02 - 0.42819525E-02 0.42216809E-02 0.41620559E-02 0.41030715E-02 0.40447216E-02 - 0.39870005E-02 0.39299024E-02 0.38734214E-02 0.38175519E-02 0.37622882E-02 - 0.37076249E-02 0.36535563E-02 0.36000770E-02 0.35471817E-02 0.34948649E-02 - 0.34431215E-02 0.33919462E-02 0.33413338E-02 0.32912793E-02 0.32417777E-02 - 0.31928238E-02 0.31444128E-02 0.30965398E-02 0.30492000E-02 0.30023886E-02 - 0.29561009E-02 0.29103322E-02 0.28650780E-02 0.28203336E-02 0.27760945E-02 - 0.27323564E-02 0.26891147E-02 0.26463653E-02 0.26041036E-02 0.25623255E-02 - 0.25210268E-02 0.24802033E-02 0.24398510E-02 0.23999657E-02 0.23605434E-02 - 0.23215802E-02 0.22830721E-02 0.22450153E-02 0.22074059E-02 0.21702402E-02 - 0.21335144E-02 0.20972248E-02 0.20613677E-02 0.20259396E-02 0.19909368E-02 - 0.19563559E-02 0.19221932E-02 0.18884455E-02 0.18551092E-02 0.18221811E-02 - 0.17896577E-02 0.17575358E-02 0.17258121E-02 0.16944834E-02 0.16635465E-02 - 0.16329982E-02 0.16028355E-02 0.15730553E-02 0.15436545E-02 0.15146301E-02 - 0.14859791E-02 0.14576986E-02 0.14297856E-02 0.14022373E-02 0.13750509E-02 - 0.13482234E-02 0.13217522E-02 0.12956343E-02 0.12698672E-02 0.12444480E-02 - 0.12193741E-02 0.11946429E-02 0.11702516E-02 0.11461977E-02 0.11224786E-02 - 0.10990917E-02 0.10760344E-02 0.10533043E-02 0.10308989E-02 0.10088156E-02 - 0.98705198E-03 0.96560563E-03 0.94447410E-03 0.92365498E-03 0.90314588E-03 - 0.88294442E-03 0.86304824E-03 0.84345498E-03 0.82416231E-03 0.80516791E-03 - 0.78646945E-03 0.76806465E-03 0.74995122E-03 0.73212686E-03 0.71458931E-03 - 0.69733631E-03 0.68036559E-03 0.66367491E-03 0.64726203E-03 0.63112470E-03 - 0.61526069E-03 0.59966778E-03 0.58434372E-03 0.56928630E-03 0.55449329E-03 - 0.53996248E-03 0.52569162E-03 0.51167851E-03 0.49792092E-03 0.48441662E-03 - 0.47116338E-03 0.45815897E-03 0.44540115E-03 0.43288768E-03 0.42061633E-03 - 0.40858483E-03 0.39679093E-03 0.38523236E-03 0.37390687E-03 0.36281216E-03 - 0.35194595E-03 0.34130595E-03 0.33088986E-03 0.32069535E-03 0.31072012E-03 - 0.30096181E-03 0.29141811E-03 0.28208663E-03 0.27296504E-03 0.26405094E-03 - 0.25534195E-03 0.24683568E-03 0.23852971E-03 0.23042161E-03 0.22250897E-03 - 0.21478932E-03 0.20726022E-03 0.19991920E-03 0.19276377E-03 0.18579144E-03 - 0.17899971E-03 0.17238607E-03 0.16594798E-03 0.15968292E-03 0.15358833E-03 - 0.14766167E-03 0.14190036E-03 0.13630183E-03 0.13086349E-03 0.12558277E-03 - 0.12045705E-03 0.11548373E-03 0.11066021E-03 0.10598386E-03 0.10145206E-03 - 0.97062192E-04 0.92811624E-04 0.88697726E-04 0.84717866E-04 0.80869413E-04 - 0.77149734E-04 0.73556200E-04 0.70086184E-04 0.66737063E-04 0.63506217E-04 - 0.60391034E-04 0.57388907E-04 0.54497240E-04 0.51713444E-04 0.49034941E-04 - 0.46459166E-04 0.43983564E-04 0.41605598E-04 0.39322743E-04 0.37132494E-04 - 0.35032362E-04 0.33019876E-04 0.31092589E-04 0.29248072E-04 0.27483921E-04 - 0.25797757E-04 0.24187223E-04 0.22649993E-04 0.21183765E-04 0.19786268E-04 - 0.18455261E-04 0.17188533E-04 0.15983905E-04 0.14839234E-04 0.13752408E-04 - 0.12721352E-04 0.11744026E-04 0.10818429E-04 0.99425949E-05 0.91145990E-05 - 0.83325543E-05 0.75946143E-05 0.68989732E-05 0.62438661E-05 0.56275702E-05 - 0.50484045E-05 0.45047309E-05 0.39949538E-05 0.35175209E-05 0.30709234E-05 - 0.26536956E-05 0.22644158E-05 0.19017056E-05 0.15642301E-05 0.12506980E-05 - 0.95986098E-06 0.69051399E-06 0.44149456E-06 0.21168260E-06 0.00000000E+00 - 0.23974391E+03 0.23974391E+03 0.23974391E+03 0.23974391E+03 0.23974391E+03 - 0.23974391E+03 0.23974391E+03 0.23974391E+03 0.23974391E+03 0.23974391E+03 - 0.23974391E+03 0.23974391E+03 0.23974391E+03 0.23974391E+03 0.23974391E+03 - 0.23974391E+03 0.23974391E+03 0.23974391E+03 0.23974391E+03 0.23974391E+03 - 0.23974391E+03 0.23974391E+03 0.23974391E+03 0.23974391E+03 0.23974391E+03 - 0.23974391E+03 0.23974391E+03 0.23974391E+03 0.23974391E+03 0.23974391E+03 - 0.23974391E+03 0.23974391E+03 0.23974391E+03 0.23974391E+03 0.23974391E+03 - 0.23974391E+03 0.23974391E+03 0.23974391E+03 0.23974391E+03 0.23974391E+03 - 0.23974391E+03 0.23974391E+03 0.23974391E+03 0.23974391E+03 0.23974391E+03 - 0.23974391E+03 0.23974391E+03 0.23291613E+03 0.22541822E+03 0.21830884E+03 - 0.21156053E+03 0.20514827E+03 0.19904921E+03 0.19324246E+03 0.18770888E+03 - 0.18243091E+03 0.17739242E+03 0.17257854E+03 0.16797557E+03 0.16357088E+03 - 0.15935277E+03 0.15531042E+03 0.15143380E+03 0.14771361E+03 0.14414119E+03 - 0.14070850E+03 0.13740805E+03 0.13423286E+03 0.13117640E+03 0.12823258E+03 - 0.12539571E+03 0.12266045E+03 0.12002181E+03 0.11747510E+03 0.11501593E+03 - 0.11264016E+03 0.11034390E+03 0.10812350E+03 0.10597552E+03 0.10389671E+03 - 0.10188400E+03 0.99934506E+02 0.98045499E+02 0.96214397E+02 0.94438757E+02 - 0.92716268E+02 0.91044740E+02 0.89422099E+02 0.87846376E+02 0.86315704E+02 - 0.84828309E+02 0.83382506E+02 0.81976693E+02 0.80609347E+02 0.79279018E+02 - 0.77984324E+02 0.76723950E+02 0.75496643E+02 0.74301206E+02 0.73136500E+02 - 0.72001433E+02 0.70894968E+02 0.69816109E+02 0.68763906E+02 0.67737452E+02 - 0.66735876E+02 0.65758348E+02 0.64804069E+02 0.63872278E+02 0.62962243E+02 - 0.62073262E+02 0.61204663E+02 0.60355801E+02 0.59526057E+02 0.58714836E+02 - 0.57921567E+02 0.57145701E+02 0.56386711E+02 0.55644090E+02 0.54917350E+02 - 0.54206022E+02 0.53509654E+02 0.52827812E+02 0.52160076E+02 0.51506043E+02 - 0.50865324E+02 0.50237545E+02 0.49622344E+02 0.49019373E+02 0.48428295E+02 - 0.47848787E+02 0.47280534E+02 0.46723235E+02 0.46176597E+02 0.45640338E+02 - 0.45114185E+02 0.44597876E+02 0.44091154E+02 0.43593774E+02 0.43105496E+02 - 0.42626092E+02 0.42155336E+02 0.41693014E+02 0.41238916E+02 0.40792839E+02 - 0.40354588E+02 0.39923971E+02 0.39500805E+02 0.39084911E+02 0.38676116E+02 - 0.38274253E+02 0.37879157E+02 0.37490672E+02 0.37108644E+02 0.36732923E+02 - 0.36363367E+02 0.35999834E+02 0.35642189E+02 0.35290299E+02 0.34944036E+02 - 0.34603275E+02 0.34267894E+02 0.33937777E+02 0.33612808E+02 0.33292876E+02 - 0.32977872E+02 0.32667692E+02 0.32362232E+02 0.32061394E+02 0.31765080E+02 - 0.31473195E+02 0.31185648E+02 0.30902348E+02 0.30623210E+02 0.30348149E+02 - 0.30077080E+02 0.29809925E+02 0.29546604E+02 0.29287041E+02 0.29031161E+02 - 0.28778893E+02 0.28530164E+02 0.28284907E+02 0.28043053E+02 0.27804538E+02 - 0.27569296E+02 0.27337266E+02 0.27108387E+02 0.26882598E+02 0.26659843E+02 - 0.26440064E+02 0.26223206E+02 0.26009215E+02 0.25798039E+02 0.25589625E+02 - 0.25383924E+02 0.25180887E+02 0.24980465E+02 0.24782611E+02 0.24587280E+02 - 0.24394427E+02 0.24204008E+02 0.24015981E+02 0.23830303E+02 0.23646934E+02 - 0.23465833E+02 0.23286962E+02 0.23110283E+02 0.22935757E+02 0.22763349E+02 - 0.22593023E+02 0.22424743E+02 0.22258475E+02 0.22094186E+02 0.21931843E+02 - 0.21771414E+02 0.21612867E+02 0.21456171E+02 0.21301297E+02 0.21148215E+02 - 0.20996896E+02 0.20847311E+02 0.20699433E+02 0.20553235E+02 0.20408690E+02 - 0.20265772E+02 0.20124455E+02 0.19984715E+02 0.19846526E+02 0.19709866E+02 - 0.19574709E+02 0.19441033E+02 0.19308816E+02 0.19178035E+02 0.19048668E+02 - 0.18920694E+02 0.18794093E+02 0.18668842E+02 0.18544923E+02 0.18422316E+02 - 0.18301001E+02 0.18180958E+02 0.18062170E+02 0.17944619E+02 0.17828285E+02 - 0.17713152E+02 0.17599201E+02 0.17486417E+02 0.17374782E+02 0.17264281E+02 - 0.17154896E+02 0.17046612E+02 0.16939414E+02 0.16833286E+02 0.16728213E+02 - 0.16624181E+02 0.16521176E+02 0.16419182E+02 0.16318187E+02 0.16218176E+02 - 0.16119136E+02 0.16021053E+02 0.15923916E+02 0.15827711E+02 0.15732425E+02 - 0.15638046E+02 0.15544562E+02 0.15451962E+02 0.15360233E+02 0.15269364E+02 - 0.15179343E+02 0.15090160E+02 0.15001804E+02 0.14914263E+02 0.14827528E+02 - 0.14741587E+02 0.14656432E+02 0.14572050E+02 0.14488434E+02 0.14405572E+02 - 0.14323456E+02 0.14242075E+02 0.14161421E+02 0.14081485E+02 0.14002258E+02 - 0.13923730E+02 0.13845893E+02 0.13768739E+02 0.13692258E+02 0.13616444E+02 - 0.13541287E+02 0.13466780E+02 0.13392915E+02 0.13319683E+02 0.13247078E+02 - 0.13175091E+02 0.13103716E+02 0.13032945E+02 0.12962771E+02 0.12893186E+02 - 0.12824184E+02 0.12755758E+02 0.12687901E+02 0.12620606E+02 0.12553868E+02 - 0.12487678E+02 0.12422032E+02 0.12356922E+02 0.12292343E+02 0.12228289E+02 - 0.12164752E+02 0.12101729E+02 0.12039212E+02 0.11977195E+02 0.11915675E+02 - 0.11854643E+02 0.11794096E+02 0.11734028E+02 0.11674433E+02 0.11615306E+02 - 0.11556642E+02 0.11498436E+02 0.11440683E+02 0.11383377E+02 0.11326515E+02 - 0.11270090E+02 0.11214098E+02 0.11158536E+02 0.11103397E+02 0.11048677E+02 - 0.10994372E+02 0.10940478E+02 0.10886990E+02 0.10833903E+02 0.10781213E+02 - 0.10728917E+02 0.10677010E+02 0.10625488E+02 0.10574347E+02 0.10523582E+02 - 0.10473191E+02 0.10423168E+02 0.10373511E+02 0.10324215E+02 0.10275277E+02 - 0.10226693E+02 0.10178460E+02 0.10130573E+02 0.10083029E+02 0.10035826E+02 - 0.99889583E+01 0.99424239E+01 0.98962191E+01 0.98503405E+01 0.98047850E+01 - 0.97595492E+01 0.97146300E+01 0.96700243E+01 0.96257289E+01 0.95817407E+01 - 0.95380568E+01 0.94946741E+01 0.94515896E+01 0.94088006E+01 0.93663040E+01 - 0.93240971E+01 0.92821770E+01 0.92405409E+01 0.91991862E+01 0.91581101E+01 - 0.91173099E+01 0.90767830E+01 0.90365268E+01 0.89965388E+01 0.89568163E+01 - 0.89173568E+01 0.88781580E+01 0.88392172E+01 0.88005322E+01 0.87621005E+01 - 0.87239197E+01 0.86859875E+01 0.86483017E+01 0.86108598E+01 0.85736597E+01 - 0.85366991E+01 0.84999759E+01 0.84634878E+01 0.84272327E+01 0.83912085E+01 - 0.83554131E+01 0.83198444E+01 0.82845003E+01 0.82493789E+01 0.82144781E+01 - 0.81797959E+01 0.81453304E+01 0.81110797E+01 0.80770418E+01 0.80432148E+01 - 0.80095969E+01 0.79761862E+01 0.79429810E+01 0.79099793E+01 0.78771794E+01 - 0.78445796E+01 0.78121780E+01 0.77799730E+01 0.77479629E+01 0.77161459E+01 - 0.76845204E+01 0.76530848E+01 0.76218373E+01 0.75907765E+01 0.75599007E+01 - 0.75292082E+01 0.74986977E+01 0.74683674E+01 0.74382159E+01 0.74082417E+01 - 0.73784433E+01 0.73488192E+01 0.73193679E+01 0.72900879E+01 0.72609780E+01 - 0.72320365E+01 0.72032622E+01 0.71746537E+01 0.71462095E+01 0.71179284E+01 - 0.70898089E+01 0.70618497E+01 0.70340497E+01 0.70064073E+01 0.69789214E+01 - 0.69515906E+01 0.69244138E+01 0.68973896E+01 0.68705169E+01 0.68437944E+01 - 0.68172209E+01 0.67907952E+01 0.67645161E+01 0.67383825E+01 0.67123931E+01 - 0.66865469E+01 0.66608428E+01 0.66352795E+01 0.66098560E+01 0.65845711E+01 - 0.65594239E+01 0.65344131E+01 0.65095378E+01 0.64847969E+01 0.64601893E+01 - 0.64357140E+01 0.64113699E+01 0.63871561E+01 0.63630716E+01 0.63391153E+01 - 0.63152863E+01 0.62915836E+01 0.62680062E+01 0.62445532E+01 0.62212236E+01 - 0.61980165E+01 0.61749309E+01 0.61519660E+01 0.61291208E+01 0.61063945E+01 - 0.60837860E+01 0.60612947E+01 0.60389195E+01 0.60166596E+01 0.59945141E+01 - 0.59724822E+01 0.59505631E+01 0.59287560E+01 0.59070599E+01 0.58854740E+01 - 0.58639977E+01 0.58426300E+01 0.58213702E+01 0.58002174E+01 0.57791710E+01 - 0.57582300E+01 0.57373939E+01 0.57166617E+01 0.56960328E+01 0.56755064E+01 - 0.56550817E+01 0.56347581E+01 0.56145348E+01 0.55944111E+01 0.55743863E+01 - 0.55544596E+01 0.55346305E+01 0.55148981E+01 0.54952619E+01 0.54757211E+01 - 0.54562750E+01 0.54369230E+01 0.54176645E+01 0.53984987E+01 0.53794251E+01 - 0.53604430E+01 0.53415517E+01 0.53227506E+01 0.53040392E+01 0.52854167E+01 - 0.52668825E+01 0.52484362E+01 0.52300770E+01 0.52118043E+01 0.51936176E+01 - 0.51755163E+01 0.51574998E+01 0.51395675E+01 0.51217188E+01 0.51039532E+01 - 0.50862702E+01 0.50686691E+01 0.50511494E+01 0.50337106E+01 0.50163521E+01 - 0.49990734E+01 0.49818740E+01 0.49647533E+01 0.49477108E+01 0.49307460E+01 - 0.49138583E+01 0.48970474E+01 0.48803125E+01 0.48636534E+01 0.48470693E+01 - 0.48305600E+01 0.48141248E+01 0.47977634E+01 0.47814751E+01 0.47652596E+01 - 0.47491163E+01 0.47330449E+01 0.47170448E+01 0.47011155E+01 0.46852567E+01 - 0.46694679E+01 0.46537485E+01 0.46380983E+01 0.46225166E+01 0.46070032E+01 - 0.45915575E+01 0.45761792E+01 0.45608678E+01 0.45456229E+01 0.45304440E+01 - 0.45153308E+01 0.45002828E+01 0.44852996E+01 0.44703809E+01 0.44555261E+01 - 0.44407350E+01 0.44260072E+01 0.44113421E+01 0.43967395E+01 0.43821990E+01 - 0.43677201E+01 0.43533025E+01 0.43389459E+01 0.43246498E+01 0.43104138E+01 - 0.42962377E+01 0.42821210E+01 0.42680634E+01 0.42540645E+01 0.42401239E+01 - 0.42262414E+01 0.42124166E+01 0.41986490E+01 0.41849384E+01 0.41712845E+01 - 0.41576868E+01 0.41441451E+01 0.41306590E+01 0.41172281E+01 0.41038523E+01 - 0.40905310E+01 0.40772641E+01 0.40640512E+01 0.40508919E+01 0.40377859E+01 - 0.40247330E+01 0.40117329E+01 0.39987851E+01 0.39858895E+01 0.39730456E+01 - 0.39602533E+01 0.39475122E+01 0.39348219E+01 0.39221823E+01 0.39095930E+01 - 0.38970538E+01 0.38845643E+01 0.38721242E+01 0.38597333E+01 0.38473913E+01 - 0.38350979E+01 0.38228529E+01 0.38106559E+01 0.37985067E+01 0.37864050E+01 - 0.37743506E+01 0.37623431E+01 0.37503824E+01 0.37384681E+01 0.37266000E+01 - 0.37147778E+01 0.37030013E+01 0.36912703E+01 0.36795844E+01 0.36679434E+01 - 0.36563471E+01 0.36447952E+01 0.36332875E+01 0.36218237E+01 0.36104036E+01 - 0.35990269E+01 0.35876935E+01 0.35764030E+01 0.35651553E+01 0.35539501E+01 - 0.35427871E+01 0.35316662E+01 0.35205871E+01 0.35095496E+01 0.34985535E+01 - 0.34875985E+01 0.34766844E+01 0.34658110E+01 0.34549781E+01 0.34441855E+01 - 0.34334329E+01 0.34227201E+01 0.34120470E+01 0.34014133E+01 0.33908188E+01 - 0.33802633E+01 0.33697465E+01 0.33592684E+01 0.33488286E+01 0.33384270E+01 - 0.33280634E+01 0.33177376E+01 0.33074493E+01 0.32971985E+01 0.32869848E+01 - 0.32768081E+01 0.32666683E+01 0.32565650E+01 0.32464982E+01 0.32364676E+01 - 0.32264731E+01 0.32165144E+01 0.32065914E+01 0.31967040E+01 0.31868518E+01 - 0.31770348E+01 0.31672527E+01 0.31575054E+01 0.31477927E+01 0.31381145E+01 - 0.31284705E+01 0.31188606E+01 0.31092846E+01 0.30997423E+01 0.30902336E+01 - 0.30807583E+01 0.30713163E+01 0.30619073E+01 0.30525312E+01 0.30431879E+01 - 0.30338772E+01 0.30245988E+01 0.30153527E+01 0.30061388E+01 0.29969567E+01 - 0.29878065E+01 0.29786879E+01 0.29696007E+01 0.29605449E+01 0.29515202E+01 - 0.29425265E+01 0.29335638E+01 0.29246317E+01 0.29157302E+01 0.29068591E+01 - 0.28980182E+01 0.28892075E+01 0.28804268E+01 0.28716759E+01 0.28629547E+01 - 0.28542631E+01 0.28456009E+01 0.28369679E+01 0.28283641E+01 0.28197892E+01 - 0.28112432E+01 0.28027260E+01 0.27942373E+01 0.27857770E+01 0.27773451E+01 - 0.27689414E+01 0.27605657E+01 0.27522179E+01 0.27438979E+01 0.27356056E+01 - 0.27273408E+01 0.27191034E+01 0.27108933E+01 0.27027103E+01 0.26945544E+01 - 0.26864253E+01 0.26783230E+01 0.26702474E+01 0.26621983E+01 0.26541756E+01 - 0.26461792E+01 0.26382090E+01 0.26302648E+01 0.26223466E+01 0.26144541E+01 - 0.26065874E+01 0.25987462E+01 0.25909305E+01 0.25831402E+01 0.25753751E+01 - 0.25676351E+01 0.25599201E+01 0.25522301E+01 0.25445648E+01 0.25369242E+01 - 0.25293081E+01 0.25217165E+01 0.25141493E+01 0.25066063E+01 0.24990875E+01 - 0.24915927E+01 0.24841218E+01 0.24766747E+01 0.24692514E+01 0.24618516E+01 - 0.24544754E+01 0.24471226E+01 0.24397930E+01 0.24324867E+01 0.24252035E+01 - 0.24179433E+01 0.24107060E+01 0.24034915E+01 0.23962997E+01 0.23891306E+01 - 0.23819839E+01 0.23748596E+01 0.23677577E+01 0.23606780E+01 0.23536205E+01 - 0.23465849E+01 0.23395714E+01 0.23325796E+01 0.23256097E+01 0.23186614E+01 - 0.23117347E+01 0.23048294E+01 0.22979456E+01 0.22910831E+01 0.22842418E+01 - 0.22774216E+01 0.22706225E+01 0.22638443E+01 0.22570870E+01 0.22503504E+01 - 0.22436346E+01 0.22369394E+01 0.22302647E+01 0.22236105E+01 0.22169766E+01 - 0.22103630E+01 0.22037695E+01 0.21971962E+01 0.21906429E+01 0.21841096E+01 - 0.21775961E+01 0.21711024E+01 0.21646285E+01 0.21581741E+01 0.21517393E+01 - 0.21453240E+01 0.21389280E+01 0.21325514E+01 0.21261940E+01 0.21198558E+01 - 0.21135366E+01 0.21072365E+01 0.21009553E+01 0.20946930E+01 0.20884494E+01 - 0.20822245E+01 0.20760183E+01 0.20698307E+01 0.20636615E+01 0.20575107E+01 - 0.20513783E+01 0.20452642E+01 0.20391683E+01 0.20330905E+01 0.20270308E+01 - 0.20209890E+01 0.20149652E+01 0.20089592E+01 0.20029710E+01 0.19970006E+01 - 0.19910478E+01 0.19851125E+01 0.19791948E+01 0.19732945E+01 0.19674116E+01 - 0.19615460E+01 0.19556977E+01 0.19498666E+01 0.19440525E+01 0.19382556E+01 - 0.19324756E+01 0.19267125E+01 0.19209663E+01 0.19152369E+01 0.19095242E+01 - 0.19038282E+01 0.18981489E+01 0.18924860E+01 0.18868397E+01 0.18812098E+01 - 0.18755962E+01 0.18699990E+01 0.18644180E+01 0.18588532E+01 0.18533045E+01 - 0.18477719E+01 0.18422553E+01 0.18367546E+01 0.18312698E+01 0.18258009E+01 - 0.18203477E+01 0.18149103E+01 0.18094885E+01 0.18040824E+01 0.17986918E+01 - 0.17933166E+01 0.17879569E+01 0.17826126E+01 0.17772837E+01 0.17719700E+01 - 0.17666715E+01 0.17613882E+01 0.17561200E+01 0.17508668E+01 0.17456287E+01 - 0.17404055E+01 0.17351972E+01 0.17300037E+01 0.17248250E+01 0.17196611E+01 - 0.17145119E+01 0.17093773E+01 0.17042573E+01 0.16991518E+01 0.16940608E+01 - 0.16889843E+01 0.16839221E+01 0.16788743E+01 0.16738408E+01 0.16688214E+01 - 0.16638163E+01 0.16588253E+01 0.16538484E+01 0.16488856E+01 0.16439367E+01 - 0.16390018E+01 0.16340808E+01 0.16291737E+01 0.16242803E+01 0.16194007E+01 - 0.16145348E+01 0.16096826E+01 0.16048440E+01 0.16000190E+01 0.15952075E+01 - 0.15904094E+01 0.15856249E+01 0.15808537E+01 0.15760958E+01 0.15713513E+01 - 0.15666200E+01 0.15619019E+01 0.15571970E+01 0.15525052E+01 0.15478266E+01 - 0.15431609E+01 0.15385083E+01 0.15338686E+01 0.15292418E+01 0.15246279E+01 - 0.15200268E+01 0.15154385E+01 0.15108629E+01 0.15063001E+01 0.15017499E+01 - 0.14972123E+01 0.14926874E+01 0.14881749E+01 0.14836750E+01 0.14791875E+01 - 0.14747124E+01 0.14702497E+01 0.14657994E+01 0.14613613E+01 0.14569356E+01 - 0.14525220E+01 0.14481206E+01 0.14437314E+01 0.14393542E+01 0.14349892E+01 - 0.14306362E+01 0.14262951E+01 0.14219660E+01 0.14176489E+01 0.14133436E+01 - 0.14090501E+01 0.14047685E+01 0.14004986E+01 0.13962405E+01 0.13919940E+01 - 0.13877592E+01 0.13835360E+01 0.13793245E+01 0.13751244E+01 0.13709359E+01 - 0.13667589E+01 0.13625933E+01 0.13584391E+01 0.13542963E+01 0.13501648E+01 - 0.13460447E+01 0.13419358E+01 0.13378381E+01 0.13337517E+01 0.13296764E+01 - 0.13256122E+01 0.13215592E+01 0.13175172E+01 0.13134862E+01 0.13094663E+01 - 0.13054573E+01 0.13014592E+01 0.12974721E+01 0.12934958E+01 0.12895304E+01 - 0.12855757E+01 0.12816318E+01 0.12776987E+01 0.12737763E+01 0.12698645E+01 - 0.12659634E+01 0.12620730E+01 0.12581931E+01 0.12543237E+01 0.12504649E+01 - 0.12466165E+01 0.12427786E+01 0.12389512E+01 0.12351341E+01 0.12313274E+01 - 0.12275311E+01 0.12237450E+01 0.12199692E+01 0.12162037E+01 0.12124484E+01 - 0.12087033E+01 0.12049683E+01 0.12012435E+01 0.11975287E+01 0.11938241E+01 - 0.11901295E+01 0.11864449E+01 0.11827702E+01 0.11791056E+01 0.11754508E+01 - 0.11718060E+01 0.11681710E+01 0.11645459E+01 0.11609306E+01 0.11573251E+01 - 0.11537293E+01 0.11501433E+01 0.11465669E+01 0.11430003E+01 0.11394433E+01 - 0.11358959E+01 0.11323581E+01 0.11288299E+01 0.11253113E+01 0.11218021E+01 - 0.11183025E+01 0.11148123E+01 0.11113315E+01 0.11078602E+01 0.11043982E+01 - 0.11009456E+01 0.10975023E+01 0.10940684E+01 0.10906437E+01 0.10872283E+01 - 0.10838221E+01 0.10804251E+01 0.10770373E+01 0.10736586E+01 0.10702891E+01 - 0.10669287E+01 0.10635774E+01 0.10602351E+01 0.10569018E+01 0.10535776E+01 - 0.10502623E+01 0.10469560E+01 0.10436587E+01 0.10403702E+01 0.10370907E+01 - 0.10338199E+01 0.10305581E+01 0.10273050E+01 0.10240608E+01 0.10208253E+01 - 0.10175985E+01 0.10143805E+01 0.10111711E+01 0.10079705E+01 0.10047785E+01 - 0.10015951E+01 0.99842029E+00 0.99525409E+00 0.99209646E+00 0.98894736E+00 - 0.98580677E+00 0.98267468E+00 0.97955105E+00 0.97643588E+00 0.97332913E+00 - 0.97023078E+00 0.96714081E+00 0.96405920E+00 0.96098593E+00 0.95792098E+00 - 0.95486432E+00 0.95181593E+00 0.94877579E+00 0.94574388E+00 0.94272018E+00 - 0.93970467E+00 0.93669732E+00 0.93369811E+00 0.93070703E+00 0.92772406E+00 - 0.92474916E+00 0.92178232E+00 0.91882353E+00 0.91587275E+00 0.91292997E+00 - 0.90999517E+00 0.90706833E+00 0.90414943E+00 0.90123844E+00 0.89833535E+00 - 0.89544014E+00 0.89255279E+00 0.88967327E+00 0.88680157E+00 0.88393767E+00 - 0.88108154E+00 0.87823317E+00 0.87539254E+00 0.87255963E+00 0.86973442E+00 - 0.86691689E+00 0.86410701E+00 0.86130478E+00 0.85851017E+00 0.85572317E+00 - 0.85294375E+00 0.85017189E+00 0.84740758E+00 0.84465079E+00 0.84190152E+00 - 0.83915973E+00 0.83642542E+00 0.83369855E+00 0.83097912E+00 0.82826711E+00 - 0.82556249E+00 0.82286525E+00 0.82017537E+00 0.81749283E+00 0.81481762E+00 - 0.81214971E+00 0.80948909E+00 0.80683574E+00 0.80418964E+00 0.80155078E+00 - 0.79891913E+00 0.79629468E+00 0.79367741E+00 0.79106730E+00 0.78846434E+00 - 0.78586850E+00 0.78327978E+00 0.78069815E+00 0.77812360E+00 0.77555610E+00 - 0.77299565E+00 0.77044222E+00 0.76789579E+00 0.76535636E+00 0.76282390E+00 - 0.76029840E+00 0.75777983E+00 0.75526819E+00 0.75276345E+00 0.75026561E+00 - 0.74777463E+00 0.74529051E+00 0.74281323E+00 0.74034277E+00 0.73787912E+00 - 0.73542226E+00 0.73297217E+00 0.73052884E+00 0.72809224E+00 0.72566238E+00 - 0.72323922E+00 0.72082275E+00 0.71841296E+00 0.71600983E+00 0.71361335E+00 - 0.71122349E+00 0.70884025E+00 0.70646360E+00 0.70409353E+00 0.70173003E+00 - 0.69937308E+00 0.69702266E+00 0.69467876E+00 0.69234137E+00 0.69001046E+00 - 0.68768602E+00 0.68536804E+00 0.68305650E+00 0.68075139E+00 0.67845269E+00 - 0.67616038E+00 0.67387446E+00 0.67159490E+00 0.66932169E+00 0.66705481E+00 - 0.66479426E+00 0.66254001E+00 0.66029205E+00 0.65805036E+00 0.65581494E+00 - 0.65358577E+00 0.65136282E+00 0.64914609E+00 0.64693557E+00 0.64473123E+00 - 0.64253306E+00 0.64034105E+00 0.63815519E+00 0.63597546E+00 0.63380184E+00 - 0.63163432E+00 0.62947289E+00 0.62731753E+00 0.62516823E+00 0.62302497E+00 - 0.62088774E+00 0.61875653E+00 0.61663131E+00 0.61451209E+00 0.61239884E+00 - 0.61029155E+00 0.60819020E+00 0.60609479E+00 0.60400529E+00 0.60192170E+00 - 0.59984400E+00 0.59777217E+00 0.59570621E+00 0.59364610E+00 0.59159182E+00 - 0.58954336E+00 0.58750071E+00 0.58546386E+00 0.58343279E+00 0.58140749E+00 - 0.57938794E+00 0.57737413E+00 0.57536605E+00 0.57336368E+00 0.57136702E+00 - 0.56937604E+00 0.56739074E+00 0.56541110E+00 0.56343711E+00 0.56146876E+00 - 0.55950603E+00 0.55754890E+00 0.55559738E+00 0.55365143E+00 0.55171106E+00 - 0.54977624E+00 0.54784697E+00 0.54592323E+00 0.54400501E+00 0.54209230E+00 - 0.54018508E+00 0.53828334E+00 0.53638707E+00 0.53449625E+00 0.53261088E+00 - 0.53073094E+00 0.52885642E+00 0.52698730E+00 0.52512357E+00 0.52326523E+00 - 0.52141225E+00 0.51956463E+00 0.51772235E+00 0.51588540E+00 0.51405377E+00 - 0.51222744E+00 0.51040641E+00 0.50859067E+00 0.50678019E+00 0.50497497E+00 - 0.50317499E+00 0.50138025E+00 0.49959073E+00 0.49780641E+00 0.49602730E+00 - 0.49425337E+00 0.49248461E+00 0.49072101E+00 0.48896257E+00 0.48720926E+00 - 0.48546107E+00 0.48371800E+00 0.48198003E+00 0.48024715E+00 0.47851935E+00 - 0.47679662E+00 0.47507894E+00 0.47336630E+00 0.47165870E+00 0.46995611E+00 - 0.46825854E+00 0.46656596E+00 0.46487836E+00 0.46319574E+00 0.46151808E+00 - 0.45984537E+00 0.45817760E+00 0.45651476E+00 0.45485684E+00 0.45320382E+00 - 0.45155570E+00 0.44991245E+00 0.44827408E+00 0.44664057E+00 0.44501191E+00 - 0.44338808E+00 0.44176908E+00 0.44015490E+00 0.43854552E+00 0.43694093E+00 - 0.43534113E+00 0.43374609E+00 0.43215582E+00 0.43057029E+00 0.42898950E+00 - 0.42741344E+00 0.42584210E+00 0.42427546E+00 0.42271351E+00 0.42115624E+00 - 0.41960365E+00 0.41805572E+00 0.41651244E+00 0.41497380E+00 0.41343979E+00 - 0.41191039E+00 0.41038561E+00 0.40886542E+00 0.40734981E+00 0.40583878E+00 - 0.40433232E+00 0.40283041E+00 0.40133305E+00 0.39984021E+00 0.39835190E+00 - 0.39686810E+00 0.39538880E+00 0.39391400E+00 0.39244367E+00 0.39097781E+00 - 0.38951641E+00 0.38805947E+00 0.38660696E+00 0.38515887E+00 0.38371521E+00 - 0.38227595E+00 0.38084110E+00 0.37941062E+00 0.37798453E+00 0.37656280E+00 - 0.37514543E+00 0.37373240E+00 0.37232371E+00 0.37091934E+00 0.36951930E+00 - 0.36812355E+00 0.36673210E+00 0.36534494E+00 0.36396205E+00 0.36258343E+00 - 0.36120906E+00 0.35983893E+00 0.35847305E+00 0.35711138E+00 0.35575393E+00 - 0.35440069E+00 0.35305164E+00 0.35170678E+00 0.35036609E+00 0.34902957E+00 - 0.34769721E+00 0.34636899E+00 0.34504490E+00 0.34372494E+00 0.34240910E+00 - 0.34109737E+00 0.33978973E+00 0.33848618E+00 0.33718671E+00 0.33589130E+00 - 0.33459996E+00 0.33331266E+00 0.33202940E+00 0.33075017E+00 0.32947496E+00 - 0.32820376E+00 0.32693656E+00 0.32567336E+00 0.32441413E+00 0.32315888E+00 - 0.32190759E+00 0.32066025E+00 0.31941685E+00 0.31817739E+00 0.31694186E+00 - 0.31571024E+00 0.31448252E+00 0.31325870E+00 0.31203877E+00 0.31082272E+00 - 0.30961054E+00 0.30840221E+00 0.30719774E+00 0.30599710E+00 0.30480030E+00 - 0.30360732E+00 0.30241815E+00 0.30123279E+00 0.30005122E+00 0.29887344E+00 - 0.29769943E+00 0.29652919E+00 0.29536271E+00 0.29419997E+00 0.29304098E+00 - 0.29188572E+00 0.29073417E+00 0.28958634E+00 0.28844222E+00 0.28730179E+00 - 0.28616504E+00 0.28503197E+00 0.28390257E+00 0.28277683E+00 0.28165474E+00 - 0.28053628E+00 0.27942146E+00 0.27831027E+00 0.27720268E+00 0.27609870E+00 - 0.27499832E+00 0.27390153E+00 0.27280831E+00 0.27171867E+00 0.27063258E+00 - 0.26955005E+00 0.26847106E+00 0.26739560E+00 0.26632368E+00 0.26525526E+00 - 0.26419036E+00 0.26312896E+00 0.26207105E+00 0.26101662E+00 0.25996566E+00 - 0.25891817E+00 0.25787414E+00 0.25683356E+00 0.25579641E+00 0.25476270E+00 - 0.25373240E+00 0.25270553E+00 0.25168205E+00 0.25066198E+00 0.24964529E+00 - 0.24863198E+00 0.24762204E+00 0.24661547E+00 0.24561225E+00 0.24461238E+00 - 0.24361584E+00 0.24262263E+00 0.24163275E+00 0.24064617E+00 0.23966290E+00 - 0.23868293E+00 0.23770624E+00 0.23673283E+00 0.23576270E+00 0.23479582E+00 - 0.23383220E+00 0.23287183E+00 0.23191469E+00 0.23096078E+00 0.23001009E+00 - 0.22906262E+00 0.22811835E+00 0.22717727E+00 0.22623939E+00 0.22530468E+00 - 0.22437315E+00 0.22344478E+00 0.22251957E+00 0.22159750E+00 0.22067857E+00 - 0.21976278E+00 0.21885011E+00 0.21794055E+00 0.21703410E+00 0.21613075E+00 - 0.21523049E+00 0.21433331E+00 0.21343921E+00 0.21254818E+00 0.21166020E+00 - 0.21077528E+00 0.20989340E+00 0.20901455E+00 0.20813873E+00 0.20726594E+00 - 0.20639615E+00 0.20552936E+00 0.20466558E+00 0.20380478E+00 0.20294696E+00 - 0.20209211E+00 0.20124022E+00 0.20039130E+00 0.19954532E+00 0.19870228E+00 - 0.19786218E+00 0.19702500E+00 0.19619074E+00 0.19535938E+00 0.19453093E+00 - 0.19370538E+00 0.19288271E+00 0.19206292E+00 0.19124600E+00 0.19043195E+00 - 0.18962075E+00 0.18881240E+00 0.18800689E+00 0.18720421E+00 0.18640436E+00 - 0.18560732E+00 0.18481310E+00 0.18402168E+00 0.18323305E+00 0.18244721E+00 - 0.18166415E+00 0.18088387E+00 0.18010635E+00 0.17933158E+00 0.17855957E+00 - 0.17779029E+00 0.17702375E+00 0.17625994E+00 0.17549885E+00 0.17474047E+00 - 0.17398480E+00 0.17323182E+00 0.17248153E+00 0.17173393E+00 0.17098900E+00 - 0.17024674E+00 0.16950714E+00 0.16877019E+00 0.16803589E+00 0.16730422E+00 - 0.16657519E+00 0.16584878E+00 0.16512498E+00 0.16440380E+00 0.16368521E+00 - 0.16296922E+00 0.16225582E+00 0.16154500E+00 0.16083675E+00 0.16013106E+00 - 0.15942794E+00 0.15872736E+00 0.15802932E+00 0.15733383E+00 0.15664086E+00 - 0.15595041E+00 0.15526248E+00 0.15457705E+00 0.15389413E+00 0.15321370E+00 - 0.15253575E+00 0.15186028E+00 0.15118729E+00 0.15051676E+00 0.14984868E+00 - 0.14918306E+00 0.14851987E+00 0.14785913E+00 0.14720081E+00 0.14654491E+00 - 0.14589143E+00 0.14524036E+00 0.14459169E+00 0.14394541E+00 0.14330151E+00 - 0.14266000E+00 0.14202085E+00 0.14138408E+00 0.14074966E+00 0.14011759E+00 - 0.13948786E+00 0.13886048E+00 0.13823542E+00 0.13761269E+00 0.13699227E+00 - 0.13637416E+00 0.13575835E+00 0.13514484E+00 0.13453361E+00 0.13392467E+00 - 0.13331800E+00 0.13271360E+00 0.13211146E+00 0.13151157E+00 0.13091393E+00 - 0.13031853E+00 0.12972536E+00 0.12913441E+00 0.12854569E+00 0.12795917E+00 - 0.12737487E+00 0.12679275E+00 0.12621284E+00 0.12563510E+00 0.12505954E+00 - 0.12448615E+00 0.12391493E+00 0.12334586E+00 0.12277895E+00 0.12221417E+00 - 0.12165153E+00 0.12109102E+00 0.12053264E+00 0.11997636E+00 0.11942220E+00 - 0.11887014E+00 0.11832017E+00 0.11777230E+00 0.11722650E+00 0.11668278E+00 - 0.11614112E+00 0.11560153E+00 0.11506398E+00 0.11452849E+00 0.11399504E+00 - 0.11346362E+00 0.11293422E+00 0.11240685E+00 0.11188149E+00 0.11135813E+00 - 0.11083677E+00 0.11031741E+00 0.10980003E+00 0.10928463E+00 0.10877120E+00 - 0.10825973E+00 0.10775023E+00 0.10724267E+00 0.10673706E+00 0.10623339E+00 - 0.10573165E+00 0.10523183E+00 0.10473392E+00 0.10423793E+00 0.10374384E+00 - 0.10325165E+00 0.10276134E+00 0.10227292E+00 0.10178638E+00 0.10130170E+00 - 0.10081888E+00 0.10033792E+00 0.99858808E-01 0.99381536E-01 0.98906098E-01 - 0.98432487E-01 0.97960696E-01 0.97490719E-01 0.97022547E-01 0.96556176E-01 - 0.96091596E-01 0.95628802E-01 0.95167787E-01 0.94708543E-01 0.94251063E-01 - 0.93795341E-01 0.93341369E-01 0.92889141E-01 0.92438648E-01 0.91989886E-01 - 0.91542845E-01 0.91097519E-01 0.90653902E-01 0.90211986E-01 0.89771763E-01 - 0.89333227E-01 0.88896371E-01 0.88461187E-01 0.88027668E-01 0.87595808E-01 - 0.87165598E-01 0.86737032E-01 0.86310103E-01 0.85884802E-01 0.85461124E-01 - 0.85039060E-01 0.84618604E-01 0.84199748E-01 0.83782485E-01 0.83366807E-01 - 0.82952707E-01 0.82540178E-01 0.82129212E-01 0.81719802E-01 0.81311940E-01 - 0.80905619E-01 0.80500832E-01 0.80097571E-01 0.79695828E-01 0.79295596E-01 - 0.78896867E-01 0.78499634E-01 0.78103889E-01 0.77709624E-01 0.77316833E-01 - 0.76925506E-01 0.76535636E-01 0.76147217E-01 0.75760239E-01 0.75374695E-01 - 0.74990577E-01 0.74607877E-01 0.74226588E-01 0.73846702E-01 0.73468210E-01 - 0.73091104E-01 0.72715377E-01 0.72341021E-01 0.71968027E-01 0.71596387E-01 - 0.71226094E-01 0.70857139E-01 0.70489513E-01 0.70123209E-01 0.69758219E-01 - 0.69394533E-01 0.69032144E-01 0.68671043E-01 0.68311222E-01 0.67952673E-01 - 0.67595386E-01 0.67239354E-01 0.66884568E-01 0.66531018E-01 0.66178697E-01 - 0.65827596E-01 0.65477707E-01 0.65129019E-01 0.64781525E-01 0.64435215E-01 - 0.64090082E-01 0.63746114E-01 0.63403305E-01 0.63061645E-01 0.62721124E-01 - 0.62381734E-01 0.62043465E-01 0.61706308E-01 0.61370254E-01 0.61035294E-01 - 0.60701418E-01 0.60368617E-01 0.60036881E-01 0.59706201E-01 0.59376567E-01 - 0.59047970E-01 0.58720400E-01 0.58393847E-01 0.58068302E-01 0.57743755E-01 - 0.57420196E-01 0.57097615E-01 0.56776002E-01 0.56455347E-01 0.56135640E-01 - 0.55816871E-01 0.55499031E-01 0.55182107E-01 0.54866091E-01 0.54550973E-01 - 0.54236740E-01 0.53923385E-01 0.53610895E-01 0.53299260E-01 0.52988470E-01 - 0.52678515E-01 0.52369383E-01 0.52061064E-01 0.51753547E-01 0.51446821E-01 - 0.51140876E-01 0.50835700E-01 0.50531283E-01 0.50227614E-01 0.49924681E-01 - 0.49622474E-01 0.49320981E-01 0.49020191E-01 0.48720093E-01 0.48420677E-01 - 0.48121929E-01 0.47823840E-01 0.47526398E-01 0.47229592E-01 0.46933409E-01 - 0.46637839E-01 0.46342870E-01 0.46048490E-01 0.45754689E-01 0.45461454E-01 - 0.45168774E-01 0.44876638E-01 0.44585033E-01 0.44293948E-01 0.44003372E-01 - 0.43713292E-01 0.43423697E-01 0.43134576E-01 0.42845917E-01 0.42557707E-01 - 0.42269936E-01 0.41982592E-01 0.41695663E-01 0.41409137E-01 0.41123004E-01 - 0.40837251E-01 0.40551866E-01 0.40266839E-01 0.39982158E-01 0.39697811E-01 - 0.39413787E-01 0.39130075E-01 0.38846663E-01 0.38563541E-01 0.38280697E-01 - 0.37998120E-01 0.37715800E-01 0.37433724E-01 0.37151884E-01 0.36870267E-01 - 0.36588864E-01 0.36307664E-01 0.36026657E-01 0.35745833E-01 0.35465181E-01 - 0.35184692E-01 0.34904357E-01 0.34624165E-01 0.34344107E-01 0.34064175E-01 - 0.33784360E-01 0.33504652E-01 0.33225043E-01 0.32945526E-01 0.32666091E-01 - 0.32386733E-01 0.32107442E-01 0.31828212E-01 0.31549036E-01 0.31269907E-01 - 0.30990820E-01 0.30711769E-01 0.30432747E-01 0.30153750E-01 0.29874773E-01 - 0.29595812E-01 0.29316863E-01 0.29037922E-01 0.28758986E-01 0.28480053E-01 - 0.28201120E-01 0.27922186E-01 0.27643250E-01 0.27364311E-01 0.27085369E-01 - 0.26806425E-01 0.26527480E-01 0.26248535E-01 0.25969593E-01 0.25690658E-01 - 0.25411731E-01 0.25132819E-01 0.24853925E-01 0.24575057E-01 0.24296219E-01 - 0.24017420E-01 0.23738668E-01 0.23459971E-01 0.23181338E-01 0.22902782E-01 - 0.22624312E-01 0.22345941E-01 0.22067683E-01 0.21789550E-01 0.21511559E-01 - 0.21233726E-01 0.20956066E-01 0.20678598E-01 0.20401341E-01 0.20124315E-01 - 0.19847541E-01 0.19571041E-01 0.19294837E-01 0.19018955E-01 0.18743419E-01 - 0.18468256E-01 0.18193494E-01 0.17919161E-01 0.17645286E-01 0.17371902E-01 - 0.17099040E-01 0.16826733E-01 0.16555016E-01 0.16283924E-01 0.16013495E-01 - 0.15743766E-01 0.15474777E-01 0.15206568E-01 0.14939180E-01 0.14672656E-01 - 0.14407041E-01 0.14142378E-01 0.13878715E-01 0.13616098E-01 0.13354575E-01 - 0.13094196E-01 0.12835012E-01 0.12577073E-01 0.12320432E-01 0.12065143E-01 - 0.11811259E-01 0.11558835E-01 0.11307928E-01 0.11058594E-01 0.10810890E-01 - 0.10564875E-01 0.10320606E-01 0.10078145E-01 0.98375490E-02 0.95988795E-02 - 0.93621966E-02 0.91275611E-02 0.88950340E-02 0.86646764E-02 0.84365493E-02 - 0.82107137E-02 0.79872307E-02 0.77661607E-02 0.75475643E-02 0.73315012E-02 - 0.71180309E-02 0.69072119E-02 0.66991023E-02 0.64937590E-02 0.62912383E-02 - 0.60915951E-02 0.58948831E-02 0.57011549E-02 0.55104615E-02 0.53228523E-02 - 0.51383750E-02 0.49570757E-02 0.47789983E-02 0.46041849E-02 0.44326752E-02 - 0.42645069E-02 0.40997151E-02 0.39383324E-02 0.37803890E-02 0.36259121E-02 - 0.34749263E-02 0.33274532E-02 0.31835115E-02 0.30431166E-02 0.29062809E-02 - 0.27730135E-02 0.26433203E-02 0.25172037E-02 0.23946626E-02 0.22756928E-02 - 0.21602862E-02 0.20484313E-02 0.19401132E-02 0.18353133E-02 0.17340096E-02 - 0.16361764E-02 0.15417845E-02 0.14508015E-02 0.13631912E-02 0.12789144E-02 - 0.11979283E-02 0.11201871E-02 0.10456417E-02 0.97424019E-03 0.90592753E-03 - 0.84064603E-03 0.77833529E-03 0.71893240E-03 0.66237211E-03 0.60858692E-03 - 0.55750733E-03 0.50906196E-03 0.46317774E-03 0.41978011E-03 0.37879322E-03 - 0.34014007E-03 0.30374279E-03 0.26952277E-03 0.23740090E-03 0.20729778E-03 - 0.17913386E-03 0.15282974E-03 0.12830627E-03 0.10548479E-03 0.84287317E-04 - 0.64636727E-04 0.46456913E-04 0.29672970E-04 0.14211347E-04 0.00000000E+00 - 0.18374826E+03 0.18374826E+03 0.18374826E+03 0.18374826E+03 0.18374826E+03 - 0.18374826E+03 0.18374826E+03 0.18374826E+03 0.18374826E+03 0.18374826E+03 - 0.18374826E+03 0.18374826E+03 0.18374826E+03 0.18374826E+03 0.18374826E+03 - 0.18374826E+03 0.18374826E+03 0.18374826E+03 0.18374826E+03 0.18374826E+03 - 0.18374826E+03 0.18374826E+03 0.18374826E+03 0.18374826E+03 0.18374826E+03 - 0.18374826E+03 0.18374826E+03 0.18374826E+03 0.18374826E+03 0.18374826E+03 - 0.18374826E+03 0.18374826E+03 0.18374826E+03 0.18374826E+03 0.18374826E+03 - 0.18374826E+03 0.18374826E+03 0.18374826E+03 0.18374826E+03 0.18374826E+03 - 0.18374826E+03 0.18374826E+03 0.18374826E+03 0.18374826E+03 0.18374826E+03 - 0.18353199E+03 0.17866225E+03 0.17402229E+03 0.16959671E+03 0.16537144E+03 - 0.16133361E+03 0.15747138E+03 0.15377390E+03 0.15023116E+03 0.14683396E+03 - 0.14357377E+03 0.14044274E+03 0.13743356E+03 0.13453948E+03 0.13175422E+03 - 0.12907195E+03 0.12648724E+03 0.12399502E+03 0.12159057E+03 0.11926947E+03 - 0.11702760E+03 0.11486110E+03 0.11276634E+03 0.11073994E+03 0.10877869E+03 - 0.10687962E+03 0.10503989E+03 0.10325686E+03 0.10152802E+03 0.99851023E+02 - 0.98223640E+02 0.96643769E+02 0.95109424E+02 0.93618727E+02 0.92169899E+02 - 0.90761256E+02 0.89391200E+02 0.88058216E+02 0.86760866E+02 0.85497786E+02 - 0.84267676E+02 0.83069302E+02 0.81901491E+02 0.80763123E+02 0.79653135E+02 - 0.78570509E+02 0.77514279E+02 0.76483520E+02 0.75477351E+02 0.74494929E+02 - 0.73535450E+02 0.72598143E+02 0.71682273E+02 0.70787135E+02 0.69912055E+02 - 0.69056387E+02 0.68219512E+02 0.67400837E+02 0.66599793E+02 0.65815833E+02 - 0.65048434E+02 0.64297092E+02 0.63561325E+02 0.62840667E+02 0.62134673E+02 - 0.61442912E+02 0.60764973E+02 0.60100456E+02 0.59448981E+02 0.58810178E+02 - 0.58183692E+02 0.57569182E+02 0.56966317E+02 0.56374780E+02 0.55794264E+02 - 0.55224473E+02 0.54665122E+02 0.54115935E+02 0.53576646E+02 0.53046998E+02 - 0.52526742E+02 0.52015638E+02 0.51513453E+02 0.51019964E+02 0.50534954E+02 - 0.50058211E+02 0.49589533E+02 0.49128724E+02 0.48675591E+02 0.48229951E+02 - 0.47791625E+02 0.47360440E+02 0.46936227E+02 0.46518824E+02 0.46108073E+02 - 0.45703821E+02 0.45305919E+02 0.44914223E+02 0.44528594E+02 0.44148895E+02 - 0.43774996E+02 0.43406767E+02 0.43044084E+02 0.42686827E+02 0.42334879E+02 - 0.41988125E+02 0.41646454E+02 0.41309759E+02 0.40977935E+02 0.40650879E+02 - 0.40328494E+02 0.40010681E+02 0.39697348E+02 0.39388403E+02 0.39083757E+02 - 0.38783324E+02 0.38487018E+02 0.38194759E+02 0.37906465E+02 0.37622059E+02 - 0.37341465E+02 0.37064610E+02 0.36791420E+02 0.36521825E+02 0.36255758E+02 - 0.35993150E+02 0.35733937E+02 0.35478056E+02 0.35225443E+02 0.34976039E+02 - 0.34729784E+02 0.34486621E+02 0.34246493E+02 0.34009346E+02 0.33775125E+02 - 0.33543779E+02 0.33315255E+02 0.33089505E+02 0.32866478E+02 0.32646129E+02 - 0.32428409E+02 0.32213273E+02 0.32000676E+02 0.31790576E+02 0.31582929E+02 - 0.31377694E+02 0.31174830E+02 0.30974298E+02 0.30776057E+02 0.30580071E+02 - 0.30386302E+02 0.30194713E+02 0.30005269E+02 0.29817934E+02 0.29632676E+02 - 0.29449459E+02 0.29268252E+02 0.29089021E+02 0.28911737E+02 0.28736368E+02 - 0.28562883E+02 0.28391254E+02 0.28221452E+02 0.28053447E+02 0.27887214E+02 - 0.27722723E+02 0.27559948E+02 0.27398865E+02 0.27239446E+02 0.27081666E+02 - 0.26925502E+02 0.26770929E+02 0.26617923E+02 0.26466461E+02 0.26316520E+02 - 0.26168079E+02 0.26021114E+02 0.25875606E+02 0.25731532E+02 0.25588871E+02 - 0.25447605E+02 0.25307712E+02 0.25169174E+02 0.25031970E+02 0.24896083E+02 - 0.24761494E+02 0.24628184E+02 0.24496136E+02 0.24365332E+02 0.24235756E+02 - 0.24107389E+02 0.23980217E+02 0.23854222E+02 0.23729389E+02 0.23605701E+02 - 0.23483144E+02 0.23361702E+02 0.23241361E+02 0.23122105E+02 0.23003921E+02 - 0.22886794E+02 0.22770711E+02 0.22655657E+02 0.22541620E+02 0.22428586E+02 - 0.22316542E+02 0.22205475E+02 0.22095374E+02 0.21986225E+02 0.21878017E+02 - 0.21770737E+02 0.21664374E+02 0.21558917E+02 0.21454354E+02 0.21350673E+02 - 0.21247865E+02 0.21145917E+02 0.21044820E+02 0.20944564E+02 0.20845137E+02 - 0.20746530E+02 0.20648732E+02 0.20551734E+02 0.20455527E+02 0.20360101E+02 - 0.20265446E+02 0.20171553E+02 0.20078413E+02 0.19986018E+02 0.19894358E+02 - 0.19803425E+02 0.19713211E+02 0.19623706E+02 0.19534903E+02 0.19446794E+02 - 0.19359370E+02 0.19272625E+02 0.19186549E+02 0.19101135E+02 0.19016376E+02 - 0.18932264E+02 0.18848793E+02 0.18765954E+02 0.18683741E+02 0.18602147E+02 - 0.18521164E+02 0.18440787E+02 0.18361008E+02 0.18281820E+02 0.18203218E+02 - 0.18125194E+02 0.18047743E+02 0.17970859E+02 0.17894534E+02 0.17818764E+02 - 0.17743541E+02 0.17668861E+02 0.17594717E+02 0.17521104E+02 0.17448016E+02 - 0.17375447E+02 0.17303392E+02 0.17231846E+02 0.17160803E+02 0.17090258E+02 - 0.17020205E+02 0.16950641E+02 0.16881559E+02 0.16812954E+02 0.16744822E+02 - 0.16677158E+02 0.16609957E+02 0.16543215E+02 0.16476926E+02 0.16411086E+02 - 0.16345690E+02 0.16280735E+02 0.16216215E+02 0.16152126E+02 0.16088464E+02 - 0.16025225E+02 0.15962405E+02 0.15899999E+02 0.15838003E+02 0.15776413E+02 - 0.15715226E+02 0.15654437E+02 0.15594042E+02 0.15534038E+02 0.15474421E+02 - 0.15415187E+02 0.15356332E+02 0.15297853E+02 0.15239746E+02 0.15182008E+02 - 0.15124635E+02 0.15067623E+02 0.15010970E+02 0.14954672E+02 0.14898725E+02 - 0.14843126E+02 0.14787872E+02 0.14732960E+02 0.14678387E+02 0.14624148E+02 - 0.14570243E+02 0.14516666E+02 0.14463416E+02 0.14410488E+02 0.14357882E+02 - 0.14305592E+02 0.14253617E+02 0.14201954E+02 0.14150599E+02 0.14099550E+02 - 0.14048805E+02 0.13998360E+02 0.13948213E+02 0.13898361E+02 0.13848802E+02 - 0.13799533E+02 0.13750551E+02 0.13701854E+02 0.13653439E+02 0.13605305E+02 - 0.13557447E+02 0.13509865E+02 0.13462556E+02 0.13415516E+02 0.13368745E+02 - 0.13322239E+02 0.13275997E+02 0.13230015E+02 0.13184293E+02 0.13138827E+02 - 0.13093615E+02 0.13048656E+02 0.13003947E+02 0.12959486E+02 0.12915271E+02 - 0.12871300E+02 0.12827570E+02 0.12784080E+02 0.12740828E+02 0.12697812E+02 - 0.12655030E+02 0.12612480E+02 0.12570159E+02 0.12528067E+02 0.12486201E+02 - 0.12444560E+02 0.12403141E+02 0.12361942E+02 0.12320963E+02 0.12280201E+02 - 0.12239654E+02 0.12199321E+02 0.12159199E+02 0.12119288E+02 0.12079586E+02 - 0.12040090E+02 0.12000800E+02 0.11961713E+02 0.11922829E+02 0.11884144E+02 - 0.11845659E+02 0.11807370E+02 0.11769278E+02 0.11731379E+02 0.11693673E+02 - 0.11656159E+02 0.11618834E+02 0.11581697E+02 0.11544747E+02 0.11507982E+02 - 0.11471401E+02 0.11435002E+02 0.11398785E+02 0.11362747E+02 0.11326887E+02 - 0.11291204E+02 0.11255697E+02 0.11220364E+02 0.11185204E+02 0.11150216E+02 - 0.11115398E+02 0.11080749E+02 0.11046268E+02 0.11011953E+02 0.10977804E+02 - 0.10943819E+02 0.10909996E+02 0.10876335E+02 0.10842835E+02 0.10809494E+02 - 0.10776311E+02 0.10743285E+02 0.10710415E+02 0.10677699E+02 0.10645137E+02 - 0.10612727E+02 0.10580469E+02 0.10548360E+02 0.10516401E+02 0.10484590E+02 - 0.10452926E+02 0.10421408E+02 0.10390034E+02 0.10358805E+02 0.10327718E+02 - 0.10296773E+02 0.10265969E+02 0.10235305E+02 0.10204779E+02 0.10174392E+02 - 0.10144141E+02 0.10114026E+02 0.10084046E+02 0.10054200E+02 0.10024488E+02 - 0.99949070E+01 0.99654576E+01 0.99361385E+01 0.99069489E+01 0.98778878E+01 - 0.98489543E+01 0.98201476E+01 0.97914668E+01 0.97629111E+01 0.97344796E+01 - 0.97061714E+01 0.96779858E+01 0.96499218E+01 0.96219787E+01 0.95941556E+01 - 0.95664518E+01 0.95388664E+01 0.95113987E+01 0.94840478E+01 0.94568130E+01 - 0.94296935E+01 0.94026885E+01 0.93757974E+01 0.93490192E+01 0.93223534E+01 - 0.92957990E+01 0.92693555E+01 0.92430221E+01 0.92167980E+01 0.91906826E+01 - 0.91646751E+01 0.91387749E+01 0.91129812E+01 0.90872934E+01 0.90617107E+01 - 0.90362325E+01 0.90108581E+01 0.89855869E+01 0.89604181E+01 0.89353512E+01 - 0.89103855E+01 0.88855203E+01 0.88607550E+01 0.88360890E+01 0.88115216E+01 - 0.87870523E+01 0.87626803E+01 0.87384051E+01 0.87142261E+01 0.86901426E+01 - 0.86661542E+01 0.86422601E+01 0.86184598E+01 0.85947527E+01 0.85711382E+01 - 0.85476158E+01 0.85241849E+01 0.85008450E+01 0.84775954E+01 0.84544356E+01 - 0.84313650E+01 0.84083832E+01 0.83854896E+01 0.83626836E+01 0.83399647E+01 - 0.83173324E+01 0.82947861E+01 0.82723254E+01 0.82499497E+01 0.82276585E+01 - 0.82054513E+01 0.81833275E+01 0.81612868E+01 0.81393286E+01 0.81174524E+01 - 0.80956577E+01 0.80739441E+01 0.80523110E+01 0.80307580E+01 0.80092846E+01 - 0.79878903E+01 0.79665747E+01 0.79453374E+01 0.79241777E+01 0.79030954E+01 - 0.78820900E+01 0.78611609E+01 0.78403078E+01 0.78195303E+01 0.77988278E+01 - 0.77782000E+01 0.77576464E+01 0.77371666E+01 0.77167601E+01 0.76964266E+01 - 0.76761657E+01 0.76559768E+01 0.76358597E+01 0.76158139E+01 0.75958390E+01 - 0.75759346E+01 0.75561003E+01 0.75363356E+01 0.75166403E+01 0.74970140E+01 - 0.74774561E+01 0.74579664E+01 0.74385445E+01 0.74191900E+01 0.73999025E+01 - 0.73806817E+01 0.73615271E+01 0.73424384E+01 0.73234153E+01 0.73044574E+01 - 0.72855643E+01 0.72667357E+01 0.72479713E+01 0.72292705E+01 0.72106333E+01 - 0.71920591E+01 0.71735476E+01 0.71550985E+01 0.71367115E+01 0.71183862E+01 - 0.71001223E+01 0.70819195E+01 0.70637774E+01 0.70456957E+01 0.70276741E+01 - 0.70097122E+01 0.69918098E+01 0.69739665E+01 0.69561821E+01 0.69384561E+01 - 0.69207884E+01 0.69031785E+01 0.68856262E+01 0.68681312E+01 0.68506932E+01 - 0.68333118E+01 0.68159869E+01 0.67987180E+01 0.67815049E+01 0.67643474E+01 - 0.67472450E+01 0.67301976E+01 0.67132049E+01 0.66962665E+01 0.66793822E+01 - 0.66625517E+01 0.66457748E+01 0.66290511E+01 0.66123804E+01 0.65957624E+01 - 0.65791969E+01 0.65626836E+01 0.65462222E+01 0.65298124E+01 0.65134540E+01 - 0.64971468E+01 0.64808905E+01 0.64646848E+01 0.64485294E+01 0.64324242E+01 - 0.64163689E+01 0.64003632E+01 0.63844068E+01 0.63684996E+01 0.63526413E+01 - 0.63368316E+01 0.63210703E+01 0.63053572E+01 0.62896920E+01 0.62740745E+01 - 0.62585045E+01 0.62429817E+01 0.62275059E+01 0.62120769E+01 0.61966944E+01 - 0.61813583E+01 0.61660682E+01 0.61508240E+01 0.61356255E+01 0.61204724E+01 - 0.61053645E+01 0.60903016E+01 0.60752834E+01 0.60603099E+01 0.60453807E+01 - 0.60304956E+01 0.60156545E+01 0.60008571E+01 0.59861032E+01 0.59713926E+01 - 0.59567252E+01 0.59421006E+01 0.59275188E+01 0.59129794E+01 0.58984824E+01 - 0.58840275E+01 0.58696145E+01 0.58552432E+01 0.58409134E+01 0.58266250E+01 - 0.58123777E+01 0.57981713E+01 0.57840057E+01 0.57698807E+01 0.57557961E+01 - 0.57417517E+01 0.57277473E+01 0.57137828E+01 0.56998579E+01 0.56859724E+01 - 0.56721263E+01 0.56583193E+01 0.56445513E+01 0.56308220E+01 0.56171313E+01 - 0.56034791E+01 0.55898650E+01 0.55762891E+01 0.55627511E+01 0.55492508E+01 - 0.55357881E+01 0.55223627E+01 0.55089747E+01 0.54956237E+01 0.54823096E+01 - 0.54690322E+01 0.54557915E+01 0.54425872E+01 0.54294191E+01 0.54162872E+01 - 0.54031912E+01 0.53901310E+01 0.53771064E+01 0.53641173E+01 0.53511636E+01 - 0.53382450E+01 0.53253615E+01 0.53125128E+01 0.52996989E+01 0.52869196E+01 - 0.52741746E+01 0.52614640E+01 0.52487875E+01 0.52361450E+01 0.52235363E+01 - 0.52109614E+01 0.51984200E+01 0.51859121E+01 0.51734374E+01 0.51609958E+01 - 0.51485873E+01 0.51362116E+01 0.51238687E+01 0.51115583E+01 0.50992804E+01 - 0.50870349E+01 0.50748215E+01 0.50626401E+01 0.50504907E+01 0.50383731E+01 - 0.50262871E+01 0.50142327E+01 0.50022097E+01 0.49902179E+01 0.49782573E+01 - 0.49663277E+01 0.49544290E+01 0.49425611E+01 0.49307238E+01 0.49189170E+01 - 0.49071407E+01 0.48953946E+01 0.48836786E+01 0.48719927E+01 0.48603367E+01 - 0.48487105E+01 0.48371140E+01 0.48255470E+01 0.48140095E+01 0.48025013E+01 - 0.47910223E+01 0.47795724E+01 0.47681514E+01 0.47567594E+01 0.47453961E+01 - 0.47340614E+01 0.47227552E+01 0.47114775E+01 0.47002281E+01 0.46890069E+01 - 0.46778137E+01 0.46666486E+01 0.46555113E+01 0.46444018E+01 0.46333199E+01 - 0.46222656E+01 0.46112387E+01 0.46002392E+01 0.45892669E+01 0.45783218E+01 - 0.45674037E+01 0.45565125E+01 0.45456481E+01 0.45348105E+01 0.45239995E+01 - 0.45132150E+01 0.45024570E+01 0.44917252E+01 0.44810197E+01 0.44703404E+01 - 0.44596871E+01 0.44490597E+01 0.44384582E+01 0.44278824E+01 0.44173322E+01 - 0.44068077E+01 0.43963085E+01 0.43858348E+01 0.43753864E+01 0.43649631E+01 - 0.43545649E+01 0.43441918E+01 0.43338435E+01 0.43235201E+01 0.43132214E+01 - 0.43029474E+01 0.42926979E+01 0.42824729E+01 0.42722722E+01 0.42620959E+01 - 0.42519438E+01 0.42418158E+01 0.42317118E+01 0.42216318E+01 0.42115756E+01 - 0.42015433E+01 0.41915346E+01 0.41815496E+01 0.41715881E+01 0.41616500E+01 - 0.41517353E+01 0.41418439E+01 0.41319758E+01 0.41221307E+01 0.41123087E+01 - 0.41025096E+01 0.40927335E+01 0.40829802E+01 0.40732495E+01 0.40635416E+01 - 0.40538562E+01 0.40441933E+01 0.40345529E+01 0.40249348E+01 0.40153390E+01 - 0.40057653E+01 0.39962138E+01 0.39866844E+01 0.39771769E+01 0.39676913E+01 - 0.39582276E+01 0.39487856E+01 0.39393653E+01 0.39299666E+01 0.39205894E+01 - 0.39112337E+01 0.39018994E+01 0.38925864E+01 0.38832947E+01 0.38740242E+01 - 0.38647748E+01 0.38555464E+01 0.38463390E+01 0.38371526E+01 0.38279870E+01 - 0.38188421E+01 0.38097180E+01 0.38006145E+01 0.37915316E+01 0.37824692E+01 - 0.37734272E+01 0.37644057E+01 0.37554044E+01 0.37464234E+01 0.37374626E+01 - 0.37285219E+01 0.37196013E+01 0.37107006E+01 0.37018199E+01 0.36929591E+01 - 0.36841181E+01 0.36752968E+01 0.36664952E+01 0.36577132E+01 0.36489508E+01 - 0.36402079E+01 0.36314845E+01 0.36227804E+01 0.36140957E+01 0.36054302E+01 - 0.35967839E+01 0.35881568E+01 0.35795487E+01 0.35709597E+01 0.35623896E+01 - 0.35538385E+01 0.35453062E+01 0.35367928E+01 0.35282981E+01 0.35198220E+01 - 0.35113646E+01 0.35029258E+01 0.34945055E+01 0.34861036E+01 0.34777202E+01 - 0.34693551E+01 0.34610084E+01 0.34526798E+01 0.34443695E+01 0.34360773E+01 - 0.34278032E+01 0.34195472E+01 0.34113091E+01 0.34030889E+01 0.33948867E+01 - 0.33867022E+01 0.33785356E+01 0.33703866E+01 0.33622553E+01 0.33541417E+01 - 0.33460456E+01 0.33379671E+01 0.33299060E+01 0.33218623E+01 0.33138360E+01 - 0.33058271E+01 0.32978354E+01 0.32898609E+01 0.32819036E+01 0.32739635E+01 - 0.32660404E+01 0.32581344E+01 0.32502453E+01 0.32423732E+01 0.32345179E+01 - 0.32266796E+01 0.32188580E+01 0.32110531E+01 0.32032650E+01 0.31954936E+01 - 0.31877387E+01 0.31800004E+01 0.31722787E+01 0.31645734E+01 0.31568845E+01 - 0.31492121E+01 0.31415560E+01 0.31339162E+01 0.31262926E+01 0.31186853E+01 - 0.31110941E+01 0.31035191E+01 0.30959601E+01 0.30884172E+01 0.30808903E+01 - 0.30733793E+01 0.30658843E+01 0.30584051E+01 0.30509418E+01 0.30434942E+01 - 0.30360624E+01 0.30286463E+01 0.30212459E+01 0.30138611E+01 0.30064918E+01 - 0.29991382E+01 0.29918000E+01 0.29844773E+01 0.29771700E+01 0.29698781E+01 - 0.29626015E+01 0.29553403E+01 0.29480943E+01 0.29408635E+01 0.29336480E+01 - 0.29264475E+01 0.29192622E+01 0.29120920E+01 0.29049368E+01 0.28977966E+01 - 0.28906714E+01 0.28835611E+01 0.28764657E+01 0.28693851E+01 0.28623193E+01 - 0.28552684E+01 0.28482321E+01 0.28412106E+01 0.28342037E+01 0.28272115E+01 - 0.28202338E+01 0.28132707E+01 0.28063222E+01 0.27993881E+01 0.27924685E+01 - 0.27855633E+01 0.27786725E+01 0.27717960E+01 0.27649338E+01 0.27580860E+01 - 0.27512523E+01 0.27444329E+01 0.27376277E+01 0.27308366E+01 0.27240596E+01 - 0.27172967E+01 0.27105479E+01 0.27038130E+01 0.26970921E+01 0.26903852E+01 - 0.26836922E+01 0.26770131E+01 0.26703478E+01 0.26636963E+01 0.26570586E+01 - 0.26504347E+01 0.26438245E+01 0.26372280E+01 0.26306451E+01 0.26240758E+01 - 0.26175202E+01 0.26109781E+01 0.26044495E+01 0.25979345E+01 0.25914329E+01 - 0.25849448E+01 0.25784700E+01 0.25720087E+01 0.25655606E+01 0.25591260E+01 - 0.25527046E+01 0.25462964E+01 0.25399015E+01 0.25335198E+01 0.25271512E+01 - 0.25207958E+01 0.25144535E+01 0.25081243E+01 0.25018082E+01 0.24955050E+01 - 0.24892149E+01 0.24829378E+01 0.24766735E+01 0.24704222E+01 0.24641838E+01 - 0.24579582E+01 0.24517455E+01 0.24455455E+01 0.24393584E+01 0.24331839E+01 - 0.24270222E+01 0.24208732E+01 0.24147369E+01 0.24086131E+01 0.24025020E+01 - 0.23964035E+01 0.23903175E+01 0.23842441E+01 0.23781831E+01 0.23721347E+01 - 0.23660986E+01 0.23600750E+01 0.23540639E+01 0.23480650E+01 0.23420785E+01 - 0.23361044E+01 0.23301425E+01 0.23241929E+01 0.23182556E+01 0.23123304E+01 - 0.23064175E+01 0.23005167E+01 0.22946281E+01 0.22887516E+01 0.22828871E+01 - 0.22770348E+01 0.22711945E+01 0.22653662E+01 0.22595499E+01 0.22537455E+01 - 0.22479531E+01 0.22421727E+01 0.22364041E+01 0.22306474E+01 0.22249026E+01 - 0.22191696E+01 0.22134483E+01 0.22077389E+01 0.22020412E+01 0.21963553E+01 - 0.21906810E+01 0.21850185E+01 0.21793676E+01 0.21737283E+01 0.21681007E+01 - 0.21624846E+01 0.21568802E+01 0.21512872E+01 0.21457058E+01 0.21401359E+01 - 0.21345775E+01 0.21290306E+01 0.21234951E+01 0.21179709E+01 0.21124582E+01 - 0.21069569E+01 0.21014669E+01 0.20959882E+01 0.20905208E+01 0.20850647E+01 - 0.20796199E+01 0.20741863E+01 0.20687640E+01 0.20633528E+01 0.20579528E+01 - 0.20525640E+01 0.20471862E+01 0.20418196E+01 0.20364641E+01 0.20311197E+01 - 0.20257863E+01 0.20204640E+01 0.20151526E+01 0.20098523E+01 0.20045629E+01 - 0.19992844E+01 0.19940169E+01 0.19887603E+01 0.19835145E+01 0.19782797E+01 - 0.19730557E+01 0.19678425E+01 0.19626401E+01 0.19574485E+01 0.19522676E+01 - 0.19470975E+01 0.19419382E+01 0.19367895E+01 0.19316515E+01 0.19265242E+01 - 0.19214076E+01 0.19163016E+01 0.19112061E+01 0.19061213E+01 0.19010471E+01 - 0.18959834E+01 0.18909302E+01 0.18858875E+01 0.18808554E+01 0.18758337E+01 - 0.18708225E+01 0.18658217E+01 0.18608313E+01 0.18558514E+01 0.18508818E+01 - 0.18459226E+01 0.18409737E+01 0.18360352E+01 0.18311070E+01 0.18261890E+01 - 0.18212814E+01 0.18163840E+01 0.18114968E+01 0.18066199E+01 0.18017531E+01 - 0.17968966E+01 0.17920502E+01 0.17872139E+01 0.17823878E+01 0.17775718E+01 - 0.17727659E+01 0.17679701E+01 0.17631843E+01 0.17584086E+01 0.17536429E+01 - 0.17488872E+01 0.17441415E+01 0.17394058E+01 0.17346801E+01 0.17299642E+01 - 0.17252583E+01 0.17205624E+01 0.17158762E+01 0.17112000E+01 0.17065336E+01 - 0.17018771E+01 0.16972304E+01 0.16925935E+01 0.16879664E+01 0.16833490E+01 - 0.16787414E+01 0.16741436E+01 0.16695554E+01 0.16649770E+01 0.16604083E+01 - 0.16558492E+01 0.16512998E+01 0.16467601E+01 0.16422299E+01 0.16377094E+01 - 0.16331985E+01 0.16286971E+01 0.16242053E+01 0.16197230E+01 0.16152503E+01 - 0.16107871E+01 0.16063334E+01 0.16018892E+01 0.15974544E+01 0.15930291E+01 - 0.15886132E+01 0.15842067E+01 0.15798097E+01 0.15754220E+01 0.15710437E+01 - 0.15666747E+01 0.15623151E+01 0.15579649E+01 0.15536239E+01 0.15492922E+01 - 0.15449698E+01 0.15406567E+01 0.15363528E+01 0.15320582E+01 0.15277728E+01 - 0.15234966E+01 0.15192295E+01 0.15149717E+01 0.15107230E+01 0.15064835E+01 - 0.15022530E+01 0.14980317E+01 0.14938195E+01 0.14896164E+01 0.14854224E+01 - 0.14812374E+01 0.14770615E+01 0.14728945E+01 0.14687366E+01 0.14645877E+01 - 0.14604478E+01 0.14563169E+01 0.14521949E+01 0.14480818E+01 0.14439777E+01 - 0.14398825E+01 0.14357962E+01 0.14317187E+01 0.14276502E+01 0.14235904E+01 - 0.14195396E+01 0.14154975E+01 0.14114643E+01 0.14074399E+01 0.14034242E+01 - 0.13994174E+01 0.13954192E+01 0.13914299E+01 0.13874492E+01 0.13834773E+01 - 0.13795140E+01 0.13755595E+01 0.13716136E+01 0.13676764E+01 0.13637478E+01 - 0.13598279E+01 0.13559166E+01 0.13520139E+01 0.13481198E+01 0.13442342E+01 - 0.13403573E+01 0.13364888E+01 0.13326290E+01 0.13287776E+01 0.13249347E+01 - 0.13211004E+01 0.13172745E+01 0.13134571E+01 0.13096482E+01 0.13058477E+01 - 0.13020556E+01 0.12982720E+01 0.12944967E+01 0.12907299E+01 0.12869714E+01 - 0.12832213E+01 0.12794795E+01 0.12757461E+01 0.12720210E+01 0.12683042E+01 - 0.12645957E+01 0.12608955E+01 0.12572036E+01 0.12535199E+01 0.12498445E+01 - 0.12461773E+01 0.12425183E+01 0.12388676E+01 0.12352250E+01 0.12315906E+01 - 0.12279644E+01 0.12243464E+01 0.12207365E+01 0.12171347E+01 0.12135411E+01 - 0.12099555E+01 0.12063781E+01 0.12028087E+01 0.11992474E+01 0.11956942E+01 - 0.11921490E+01 0.11886118E+01 0.11850826E+01 0.11815615E+01 0.11780483E+01 - 0.11745432E+01 0.11710460E+01 0.11675567E+01 0.11640754E+01 0.11606021E+01 - 0.11571366E+01 0.11536791E+01 0.11502294E+01 0.11467877E+01 0.11433538E+01 - 0.11399277E+01 0.11365096E+01 0.11330992E+01 0.11296967E+01 0.11263019E+01 - 0.11229150E+01 0.11195359E+01 0.11161645E+01 0.11128009E+01 0.11094450E+01 - 0.11060969E+01 0.11027565E+01 0.10994238E+01 0.10960988E+01 0.10927815E+01 - 0.10894719E+01 0.10861699E+01 0.10828756E+01 0.10795889E+01 0.10763099E+01 - 0.10730385E+01 0.10697747E+01 0.10665184E+01 0.10632698E+01 0.10600287E+01 - 0.10567952E+01 0.10535692E+01 0.10503508E+01 0.10471399E+01 0.10439365E+01 - 0.10407405E+01 0.10375521E+01 0.10343712E+01 0.10311977E+01 0.10280317E+01 - 0.10248731E+01 0.10217219E+01 0.10185782E+01 0.10154418E+01 0.10123129E+01 - 0.10091913E+01 0.10060771E+01 0.10029703E+01 0.99987077E+00 0.99677861E+00 - 0.99369378E+00 0.99061626E+00 0.98754604E+00 0.98448311E+00 0.98142746E+00 - 0.97837908E+00 0.97533795E+00 0.97230406E+00 0.96927741E+00 0.96625798E+00 - 0.96324576E+00 0.96024073E+00 0.95724289E+00 0.95425223E+00 0.95126873E+00 - 0.94829239E+00 0.94532318E+00 0.94236111E+00 0.93940615E+00 0.93645830E+00 - 0.93351755E+00 0.93058388E+00 0.92765729E+00 0.92473776E+00 0.92182528E+00 - 0.91891984E+00 0.91602143E+00 0.91313003E+00 0.91024565E+00 0.90736825E+00 - 0.90449785E+00 0.90163441E+00 0.89877794E+00 0.89592842E+00 0.89308583E+00 - 0.89025018E+00 0.88742144E+00 0.88459961E+00 0.88178468E+00 0.87897662E+00 - 0.87617545E+00 0.87338113E+00 0.87059366E+00 0.86781304E+00 0.86503924E+00 - 0.86227226E+00 0.85951209E+00 0.85675872E+00 0.85401212E+00 0.85127231E+00 - 0.84853925E+00 0.84581295E+00 0.84309339E+00 0.84038056E+00 0.83767445E+00 - 0.83497505E+00 0.83228234E+00 0.82959632E+00 0.82691698E+00 0.82424430E+00 - 0.82157827E+00 0.81891889E+00 0.81626614E+00 0.81362001E+00 0.81098049E+00 - 0.80834757E+00 0.80572124E+00 0.80310149E+00 0.80048830E+00 0.79788168E+00 - 0.79528159E+00 0.79268804E+00 0.79010102E+00 0.78752051E+00 0.78494650E+00 - 0.78237898E+00 0.77981794E+00 0.77726338E+00 0.77471527E+00 0.77217361E+00 - 0.76963839E+00 0.76710959E+00 0.76458722E+00 0.76207125E+00 0.75956167E+00 - 0.75705848E+00 0.75456166E+00 0.75207120E+00 0.74958710E+00 0.74710934E+00 - 0.74463791E+00 0.74217280E+00 0.73971400E+00 0.73726149E+00 0.73481528E+00 - 0.73237534E+00 0.72994168E+00 0.72751426E+00 0.72509310E+00 0.72267816E+00 - 0.72026946E+00 0.71786697E+00 0.71547068E+00 0.71308058E+00 0.71069666E+00 - 0.70831892E+00 0.70594734E+00 0.70358191E+00 0.70122261E+00 0.69886945E+00 - 0.69652241E+00 0.69418147E+00 0.69184663E+00 0.68951788E+00 0.68719521E+00 - 0.68487860E+00 0.68256804E+00 0.68026354E+00 0.67796506E+00 0.67567261E+00 - 0.67338617E+00 0.67110574E+00 0.66883129E+00 0.66656283E+00 0.66430034E+00 - 0.66204381E+00 0.65979323E+00 0.65754859E+00 0.65530988E+00 0.65307709E+00 - 0.65085020E+00 0.64862921E+00 0.64641411E+00 0.64420489E+00 0.64200153E+00 - 0.63980403E+00 0.63761237E+00 0.63542654E+00 0.63324654E+00 0.63107236E+00 - 0.62890397E+00 0.62674138E+00 0.62458457E+00 0.62243354E+00 0.62028826E+00 - 0.61814873E+00 0.61601495E+00 0.61388689E+00 0.61176455E+00 0.60964792E+00 - 0.60753699E+00 0.60543174E+00 0.60333218E+00 0.60123827E+00 0.59915003E+00 - 0.59706743E+00 0.59499046E+00 0.59291912E+00 0.59085340E+00 0.58879327E+00 - 0.58673874E+00 0.58468979E+00 0.58264642E+00 0.58060860E+00 0.57857634E+00 - 0.57654961E+00 0.57452842E+00 0.57251274E+00 0.57050258E+00 0.56849791E+00 - 0.56649872E+00 0.56450502E+00 0.56251678E+00 0.56053400E+00 0.55855666E+00 - 0.55658476E+00 0.55461828E+00 0.55265722E+00 0.55070155E+00 0.54875128E+00 - 0.54680640E+00 0.54486688E+00 0.54293272E+00 0.54100392E+00 0.53908045E+00 - 0.53716231E+00 0.53524949E+00 0.53334198E+00 0.53143976E+00 0.52954283E+00 - 0.52765117E+00 0.52576478E+00 0.52388364E+00 0.52200775E+00 0.52013709E+00 - 0.51827165E+00 0.51641142E+00 0.51455639E+00 0.51270655E+00 0.51086189E+00 - 0.50902240E+00 0.50718806E+00 0.50535887E+00 0.50353482E+00 0.50171589E+00 - 0.49990207E+00 0.49809336E+00 0.49628974E+00 0.49449120E+00 0.49269773E+00 - 0.49090932E+00 0.48912596E+00 0.48734763E+00 0.48557433E+00 0.48380605E+00 - 0.48204277E+00 0.48028449E+00 0.47853119E+00 0.47678286E+00 0.47503948E+00 - 0.47330106E+00 0.47156758E+00 0.46983902E+00 0.46811538E+00 0.46639664E+00 - 0.46468280E+00 0.46297384E+00 0.46126975E+00 0.45957052E+00 0.45787614E+00 - 0.45618659E+00 0.45450187E+00 0.45282196E+00 0.45114686E+00 0.44947655E+00 - 0.44781102E+00 0.44615026E+00 0.44449425E+00 0.44284299E+00 0.44119646E+00 - 0.43955466E+00 0.43791756E+00 0.43628517E+00 0.43465746E+00 0.43303443E+00 - 0.43141606E+00 0.42980235E+00 0.42819327E+00 0.42658882E+00 0.42498899E+00 - 0.42339377E+00 0.42180313E+00 0.42021708E+00 0.41863560E+00 0.41705867E+00 - 0.41548629E+00 0.41391844E+00 0.41235510E+00 0.41079628E+00 0.40924195E+00 - 0.40769211E+00 0.40614674E+00 0.40460582E+00 0.40306935E+00 0.40153732E+00 - 0.40000970E+00 0.39848649E+00 0.39696768E+00 0.39545326E+00 0.39394320E+00 - 0.39243750E+00 0.39093614E+00 0.38943911E+00 0.38794641E+00 0.38645801E+00 - 0.38497390E+00 0.38349407E+00 0.38201850E+00 0.38054719E+00 0.37908012E+00 - 0.37761728E+00 0.37615864E+00 0.37470421E+00 0.37325396E+00 0.37180788E+00 - 0.37036596E+00 0.36892819E+00 0.36749454E+00 0.36606501E+00 0.36463959E+00 - 0.36321825E+00 0.36180098E+00 0.36038778E+00 0.35897862E+00 0.35757349E+00 - 0.35617238E+00 0.35477527E+00 0.35338215E+00 0.35199300E+00 0.35060780E+00 - 0.34922655E+00 0.34784923E+00 0.34647582E+00 0.34510631E+00 0.34374068E+00 - 0.34237892E+00 0.34102100E+00 0.33966693E+00 0.33831667E+00 0.33697022E+00 - 0.33562755E+00 0.33428866E+00 0.33295353E+00 0.33162213E+00 0.33029446E+00 - 0.32897049E+00 0.32765022E+00 0.32633362E+00 0.32502067E+00 0.32371137E+00 - 0.32240569E+00 0.32110361E+00 0.31980513E+00 0.31851021E+00 0.31721885E+00 - 0.31593103E+00 0.31464672E+00 0.31336592E+00 0.31208859E+00 0.31081473E+00 - 0.30954432E+00 0.30827733E+00 0.30701376E+00 0.30575357E+00 0.30449675E+00 - 0.30324328E+00 0.30199315E+00 0.30074633E+00 0.29950280E+00 0.29826255E+00 - 0.29702555E+00 0.29579179E+00 0.29456124E+00 0.29333388E+00 0.29210969E+00 - 0.29088866E+00 0.28967075E+00 0.28845596E+00 0.28724426E+00 0.28603562E+00 - 0.28483003E+00 0.28362746E+00 0.28242789E+00 0.28123131E+00 0.28003768E+00 - 0.27884698E+00 0.27765920E+00 0.27647430E+00 0.27529227E+00 0.27411309E+00 - 0.27293672E+00 0.27176314E+00 0.27059234E+00 0.26942428E+00 0.26825894E+00 - 0.26709631E+00 0.26593634E+00 0.26477902E+00 0.26362432E+00 0.26247222E+00 - 0.26132268E+00 0.26017569E+00 0.25903122E+00 0.25788924E+00 0.25674972E+00 - 0.25561264E+00 0.25447797E+00 0.25334569E+00 0.25221575E+00 0.25108814E+00 - 0.24996283E+00 0.24883979E+00 0.24771899E+00 0.24660040E+00 0.24548400E+00 - 0.24436974E+00 0.24325761E+00 0.24214757E+00 0.24103959E+00 0.23993364E+00 - 0.23882969E+00 0.23772771E+00 0.23662766E+00 0.23552952E+00 0.23443325E+00 - 0.23333883E+00 0.23224621E+00 0.23115536E+00 0.23006626E+00 0.22897886E+00 - 0.22789314E+00 0.22680905E+00 0.22572658E+00 0.22464567E+00 0.22356629E+00 - 0.22248842E+00 0.22141201E+00 0.22033703E+00 0.21926344E+00 0.21819120E+00 - 0.21712028E+00 0.21605065E+00 0.21498226E+00 0.21391507E+00 0.21284906E+00 - 0.21178417E+00 0.21072037E+00 0.20965763E+00 0.20859590E+00 0.20753514E+00 - 0.20647532E+00 0.20541640E+00 0.20435832E+00 0.20330106E+00 0.20224458E+00 - 0.20118882E+00 0.20013376E+00 0.19907935E+00 0.19802554E+00 0.19697230E+00 - 0.19591958E+00 0.19486734E+00 0.19381555E+00 0.19276414E+00 0.19171309E+00 - 0.19066235E+00 0.18961188E+00 0.18856162E+00 0.18751155E+00 0.18646161E+00 - 0.18541176E+00 0.18436196E+00 0.18331216E+00 0.18226232E+00 0.18121239E+00 - 0.18016233E+00 0.17911209E+00 0.17806163E+00 0.17701091E+00 0.17595988E+00 - 0.17490849E+00 0.17385671E+00 0.17280448E+00 0.17175176E+00 0.17069851E+00 - 0.16964468E+00 0.16859023E+00 0.16753511E+00 0.16647929E+00 0.16542271E+00 - 0.16436533E+00 0.16330711E+00 0.16224801E+00 0.16118799E+00 0.16012699E+00 - 0.15906498E+00 0.15800192E+00 0.15693777E+00 0.15587249E+00 0.15480603E+00 - 0.15373835E+00 0.15266942E+00 0.15159920E+00 0.15052765E+00 0.14945474E+00 - 0.14838042E+00 0.14730466E+00 0.14622743E+00 0.14514869E+00 0.14406842E+00 - 0.14298657E+00 0.14190311E+00 0.14081803E+00 0.13973128E+00 0.13864284E+00 - 0.13755269E+00 0.13646080E+00 0.13536714E+00 0.13427170E+00 0.13317445E+00 - 0.13207537E+00 0.13097445E+00 0.12987167E+00 0.12876702E+00 0.12766048E+00 - 0.12655204E+00 0.12544170E+00 0.12432945E+00 0.12321529E+00 0.12209920E+00 - 0.12098120E+00 0.11986129E+00 0.11873946E+00 0.11761574E+00 0.11649012E+00 - 0.11536263E+00 0.11423327E+00 0.11310206E+00 0.11196904E+00 0.11083421E+00 - 0.10969761E+00 0.10855927E+00 0.10741923E+00 0.10627751E+00 0.10513417E+00 - 0.10398924E+00 0.10284278E+00 0.10169483E+00 0.10054545E+00 0.99394707E-01 - 0.98242654E-01 0.97089363E-01 0.95934906E-01 0.94779358E-01 0.93622800E-01 - 0.92465316E-01 0.91306996E-01 0.90147934E-01 0.88988228E-01 0.87827981E-01 - 0.86667301E-01 0.85506301E-01 0.84345099E-01 0.83183818E-01 0.82022585E-01 - 0.80861534E-01 0.79700801E-01 0.78540532E-01 0.77380873E-01 0.76221978E-01 - 0.75064008E-01 0.73907124E-01 0.72751498E-01 0.71597304E-01 0.70444722E-01 - 0.69293937E-01 0.68145140E-01 0.66998527E-01 0.65854300E-01 0.64712663E-01 - 0.63573829E-01 0.62438014E-01 0.61305439E-01 0.60176331E-01 0.59050921E-01 - 0.57929443E-01 0.56812139E-01 0.55699252E-01 0.54591032E-01 0.53487732E-01 - 0.52389607E-01 0.51296920E-01 0.50209933E-01 0.49128914E-01 0.48054134E-01 - 0.46985866E-01 0.45924385E-01 0.44869970E-01 0.43822901E-01 0.42783458E-01 - 0.41751927E-01 0.40728590E-01 0.39713733E-01 0.38707641E-01 0.37710598E-01 - 0.36722891E-01 0.35744802E-01 0.34776614E-01 0.33818609E-01 0.32871064E-01 - 0.31934257E-01 0.31008460E-01 0.30093944E-01 0.29190973E-01 0.28299809E-01 - 0.27420708E-01 0.26553922E-01 0.25699694E-01 0.24858263E-01 0.24029861E-01 - 0.23214710E-01 0.22413028E-01 0.21625020E-01 0.20850886E-01 0.20090814E-01 - 0.19344982E-01 0.18613559E-01 0.17896702E-01 0.17194557E-01 0.16507257E-01 - 0.15834923E-01 0.15177666E-01 0.14535581E-01 0.13908750E-01 0.13297242E-01 - 0.12701111E-01 0.12120398E-01 0.11555129E-01 0.11005313E-01 0.10470947E-01 - 0.99520121E-02 0.94484729E-02 0.89602798E-02 0.84873675E-02 0.80296556E-02 - 0.75870481E-02 0.71594341E-02 0.67466875E-02 0.63486676E-02 0.59652187E-02 - 0.55961711E-02 0.52413411E-02 0.49005311E-02 0.45735305E-02 0.42601159E-02 - 0.39600516E-02 0.36730901E-02 0.33989729E-02 0.31374308E-02 0.28881848E-02 - 0.26509466E-02 0.24254195E-02 0.22112990E-02 0.20082734E-02 0.18160252E-02 - 0.16342311E-02 0.14625634E-02 0.13006905E-02 0.11482780E-02 0.10049892E-02 - 0.87048637E-03 0.74443115E-03 0.62648565E-03 0.51631316E-03 0.41357893E-03 - 0.31795099E-03 0.22910086E-03 0.14670429E-03 0.70441929E-04 0.00000000E+00 - 0.25420062E+03 0.25420062E+03 0.25420062E+03 0.25420062E+03 0.25420062E+03 - 0.25420062E+03 0.25420062E+03 0.25420062E+03 0.25420062E+03 0.25420062E+03 - 0.25420062E+03 0.25420062E+03 0.25420062E+03 0.25420062E+03 0.25420062E+03 - 0.25420062E+03 0.25420062E+03 0.25420062E+03 0.25420062E+03 0.25420062E+03 - 0.25420062E+03 0.25420062E+03 0.25420062E+03 0.25420062E+03 0.25420062E+03 - 0.25420062E+03 0.25420062E+03 0.25420062E+03 0.25420062E+03 0.25420062E+03 - 0.25420062E+03 0.25420062E+03 0.25420062E+03 0.25420062E+03 0.25420062E+03 - 0.25420062E+03 0.25420062E+03 0.25420062E+03 0.25420062E+03 0.25420062E+03 - 0.25420062E+03 0.25257244E+03 0.24485527E+03 0.23754720E+03 0.23061776E+03 - 0.22403937E+03 0.21778703E+03 0.21183801E+03 0.20617158E+03 0.20076885E+03 - 0.19561254E+03 0.19068679E+03 0.18597707E+03 0.18147002E+03 0.17715334E+03 - 0.17301568E+03 0.16904654E+03 0.16523625E+03 0.16157581E+03 0.15805689E+03 - 0.15467177E+03 0.15141324E+03 0.14827461E+03 0.14524964E+03 0.14233250E+03 - 0.13951775E+03 0.13680030E+03 0.13417539E+03 0.13163855E+03 0.12918559E+03 - 0.12681259E+03 0.12451584E+03 0.12229188E+03 0.12013742E+03 0.11804940E+03 - 0.11602490E+03 0.11406118E+03 0.11215564E+03 0.11030585E+03 0.10850948E+03 - 0.10676435E+03 0.10506837E+03 0.10341959E+03 0.10181613E+03 0.10025622E+03 - 0.98738185E+02 0.97260422E+02 0.95821412E+02 0.94419711E+02 0.93053941E+02 - 0.91722793E+02 0.90425018E+02 0.89159424E+02 0.87924876E+02 0.86720289E+02 - 0.85544628E+02 0.84396904E+02 0.83276170E+02 0.82181524E+02 0.81112099E+02 - 0.80067068E+02 0.79045637E+02 0.78047046E+02 0.77070569E+02 0.76115505E+02 - 0.75181187E+02 0.74266970E+02 0.73372238E+02 0.72496399E+02 0.71638883E+02 - 0.70799144E+02 0.69976655E+02 0.69170910E+02 0.68381423E+02 0.67607726E+02 - 0.66849367E+02 0.66105913E+02 0.65376944E+02 0.64662058E+02 0.63960866E+02 - 0.63272992E+02 0.62598077E+02 0.61935770E+02 0.61285734E+02 0.60647646E+02 - 0.60021190E+02 0.59406064E+02 0.58801975E+02 0.58208638E+02 0.57625781E+02 - 0.57053139E+02 0.56490455E+02 0.55937481E+02 0.55393978E+02 0.54859714E+02 - 0.54334462E+02 0.53818007E+02 0.53310137E+02 0.52810647E+02 0.52319340E+02 - 0.51836022E+02 0.51360509E+02 0.50892620E+02 0.50432178E+02 0.49979015E+02 - 0.49532966E+02 0.49093869E+02 0.48661571E+02 0.48235919E+02 0.47816768E+02 - 0.47403975E+02 0.46997401E+02 0.46596912E+02 0.46202377E+02 0.45813669E+02 - 0.45430666E+02 0.45053245E+02 0.44681291E+02 0.44314690E+02 0.43953332E+02 - 0.43597107E+02 0.43245913E+02 0.42899646E+02 0.42558207E+02 0.42221500E+02 - 0.41889429E+02 0.41561905E+02 0.41238836E+02 0.40920135E+02 0.40605719E+02 - 0.40295503E+02 0.39989407E+02 0.39687353E+02 0.39389263E+02 0.39095063E+02 - 0.38804679E+02 0.38518040E+02 0.38235077E+02 0.37955722E+02 0.37679908E+02 - 0.37407571E+02 0.37138648E+02 0.36873076E+02 0.36610796E+02 0.36351750E+02 - 0.36095878E+02 0.35843126E+02 0.35593438E+02 0.35346760E+02 0.35103042E+02 - 0.34862230E+02 0.34624275E+02 0.34389129E+02 0.34156743E+02 0.33927070E+02 - 0.33700065E+02 0.33475683E+02 0.33253881E+02 0.33034614E+02 0.32817842E+02 - 0.32603523E+02 0.32391618E+02 0.32182086E+02 0.31974890E+02 0.31769991E+02 - 0.31567354E+02 0.31366941E+02 0.31168718E+02 0.30972649E+02 0.30778701E+02 - 0.30586841E+02 0.30397036E+02 0.30209254E+02 0.30023464E+02 0.29839636E+02 - 0.29657738E+02 0.29477743E+02 0.29299620E+02 0.29123342E+02 0.28948881E+02 - 0.28776210E+02 0.28605303E+02 0.28436132E+02 0.28268673E+02 0.28102899E+02 - 0.27938788E+02 0.27776314E+02 0.27615453E+02 0.27456183E+02 0.27298480E+02 - 0.27142323E+02 0.26987688E+02 0.26834555E+02 0.26682902E+02 0.26532709E+02 - 0.26383954E+02 0.26236618E+02 0.26090682E+02 0.25946125E+02 0.25802929E+02 - 0.25661075E+02 0.25520545E+02 0.25381321E+02 0.25243384E+02 0.25106719E+02 - 0.24971307E+02 0.24837132E+02 0.24704177E+02 0.24572427E+02 0.24441865E+02 - 0.24312475E+02 0.24184242E+02 0.24057152E+02 0.23931189E+02 0.23806338E+02 - 0.23682586E+02 0.23559917E+02 0.23438319E+02 0.23317778E+02 0.23198279E+02 - 0.23079810E+02 0.22962359E+02 0.22845911E+02 0.22730455E+02 0.22615978E+02 - 0.22502468E+02 0.22389913E+02 0.22278301E+02 0.22167621E+02 0.22057861E+02 - 0.21949010E+02 0.21841057E+02 0.21733991E+02 0.21627801E+02 0.21522478E+02 - 0.21418009E+02 0.21314386E+02 0.21211598E+02 0.21109636E+02 0.21008489E+02 - 0.20908147E+02 0.20808603E+02 0.20709845E+02 0.20611866E+02 0.20514655E+02 - 0.20418205E+02 0.20322506E+02 0.20227549E+02 0.20133327E+02 0.20039831E+02 - 0.19947052E+02 0.19854983E+02 0.19763615E+02 0.19672941E+02 0.19582952E+02 - 0.19493642E+02 0.19405002E+02 0.19317026E+02 0.19229705E+02 0.19143033E+02 - 0.19057002E+02 0.18971605E+02 0.18886836E+02 0.18802688E+02 0.18719154E+02 - 0.18636227E+02 0.18553901E+02 0.18472169E+02 0.18391025E+02 0.18310463E+02 - 0.18230476E+02 0.18151058E+02 0.18072204E+02 0.17993908E+02 0.17916163E+02 - 0.17838964E+02 0.17762305E+02 0.17686180E+02 0.17610584E+02 0.17535512E+02 - 0.17460958E+02 0.17386917E+02 0.17313383E+02 0.17240352E+02 0.17167818E+02 - 0.17095776E+02 0.17024222E+02 0.16953149E+02 0.16882554E+02 0.16812432E+02 - 0.16742778E+02 0.16673587E+02 0.16604854E+02 0.16536576E+02 0.16468748E+02 - 0.16401365E+02 0.16334422E+02 0.16267916E+02 0.16201843E+02 0.16136197E+02 - 0.16070976E+02 0.16006174E+02 0.15941788E+02 0.15877814E+02 0.15814248E+02 - 0.15751086E+02 0.15688324E+02 0.15625958E+02 0.15563985E+02 0.15502400E+02 - 0.15441201E+02 0.15380383E+02 0.15319943E+02 0.15259878E+02 0.15200184E+02 - 0.15140857E+02 0.15081894E+02 0.15023292E+02 0.14965048E+02 0.14907158E+02 - 0.14849618E+02 0.14792427E+02 0.14735579E+02 0.14679074E+02 0.14622906E+02 - 0.14567074E+02 0.14511574E+02 0.14456403E+02 0.14401559E+02 0.14347038E+02 - 0.14292838E+02 0.14238955E+02 0.14185387E+02 0.14132131E+02 0.14079184E+02 - 0.14026544E+02 0.13974208E+02 0.13922174E+02 0.13870437E+02 0.13818997E+02 - 0.13767851E+02 0.13716995E+02 0.13666428E+02 0.13616146E+02 0.13566148E+02 - 0.13516432E+02 0.13466993E+02 0.13417832E+02 0.13368944E+02 0.13320327E+02 - 0.13271980E+02 0.13223900E+02 0.13176085E+02 0.13128533E+02 0.13081241E+02 - 0.13034207E+02 0.12987429E+02 0.12940905E+02 0.12894633E+02 0.12848611E+02 - 0.12802836E+02 0.12757308E+02 0.12712022E+02 0.12666979E+02 0.12622175E+02 - 0.12577609E+02 0.12533279E+02 0.12489183E+02 0.12445319E+02 0.12401684E+02 - 0.12358279E+02 0.12315100E+02 0.12272145E+02 0.12229413E+02 0.12186903E+02 - 0.12144612E+02 0.12102538E+02 0.12060681E+02 0.12019037E+02 0.11977607E+02 - 0.11936387E+02 0.11895376E+02 0.11854573E+02 0.11813976E+02 0.11773583E+02 - 0.11733393E+02 0.11693405E+02 0.11653616E+02 0.11614025E+02 0.11574631E+02 - 0.11535432E+02 0.11496426E+02 0.11457613E+02 0.11418990E+02 0.11380557E+02 - 0.11342312E+02 0.11304253E+02 0.11266379E+02 0.11228688E+02 0.11191180E+02 - 0.11153853E+02 0.11116706E+02 0.11079736E+02 0.11042944E+02 0.11006327E+02 - 0.10969884E+02 0.10933615E+02 0.10897517E+02 0.10861590E+02 0.10825832E+02 - 0.10790241E+02 0.10754818E+02 0.10719560E+02 0.10684467E+02 0.10649537E+02 - 0.10614769E+02 0.10580162E+02 0.10545714E+02 0.10511425E+02 0.10477293E+02 - 0.10443318E+02 0.10409498E+02 0.10375832E+02 0.10342319E+02 0.10308958E+02 - 0.10275748E+02 0.10242687E+02 0.10209775E+02 0.10177011E+02 0.10144394E+02 - 0.10111922E+02 0.10079595E+02 0.10047412E+02 0.10015371E+02 0.99834717E+01 - 0.99517133E+01 0.99200945E+01 0.98886145E+01 0.98572723E+01 0.98260669E+01 - 0.97949976E+01 0.97640632E+01 0.97332629E+01 0.97025958E+01 0.96720610E+01 - 0.96416576E+01 0.96113847E+01 0.95812415E+01 0.95512270E+01 0.95213404E+01 - 0.94915810E+01 0.94619477E+01 0.94324399E+01 0.94030565E+01 0.93737970E+01 - 0.93446603E+01 0.93156458E+01 0.92867526E+01 0.92579799E+01 0.92293269E+01 - 0.92007929E+01 0.91723770E+01 0.91440786E+01 0.91158969E+01 0.90878310E+01 - 0.90598803E+01 0.90320440E+01 0.90043214E+01 0.89767117E+01 0.89492143E+01 - 0.89218284E+01 0.88945533E+01 0.88673884E+01 0.88403328E+01 0.88133860E+01 - 0.87865471E+01 0.87598157E+01 0.87331909E+01 0.87066722E+01 0.86802588E+01 - 0.86539500E+01 0.86277454E+01 0.86016441E+01 0.85756456E+01 0.85497492E+01 - 0.85239543E+01 0.84982603E+01 0.84726666E+01 0.84471724E+01 0.84217773E+01 - 0.83964807E+01 0.83712818E+01 0.83461802E+01 0.83211752E+01 0.82962663E+01 - 0.82714529E+01 0.82467343E+01 0.82221101E+01 0.81975797E+01 0.81731425E+01 - 0.81487979E+01 0.81245454E+01 0.81003845E+01 0.80763146E+01 0.80523351E+01 - 0.80284456E+01 0.80046455E+01 0.79809343E+01 0.79573114E+01 0.79337764E+01 - 0.79103287E+01 0.78869678E+01 0.78636932E+01 0.78405045E+01 0.78174010E+01 - 0.77943824E+01 0.77714481E+01 0.77485977E+01 0.77258306E+01 0.77031464E+01 - 0.76805447E+01 0.76580249E+01 0.76355865E+01 0.76132292E+01 0.75909524E+01 - 0.75687558E+01 0.75466388E+01 0.75246010E+01 0.75026419E+01 0.74807611E+01 - 0.74589583E+01 0.74372328E+01 0.74155844E+01 0.73940126E+01 0.73725169E+01 - 0.73510969E+01 0.73297523E+01 0.73084825E+01 0.72872873E+01 0.72661661E+01 - 0.72451186E+01 0.72241444E+01 0.72032430E+01 0.71824141E+01 0.71616573E+01 - 0.71409722E+01 0.71203584E+01 0.70998155E+01 0.70793431E+01 0.70589409E+01 - 0.70386085E+01 0.70183455E+01 0.69981515E+01 0.69780262E+01 0.69579692E+01 - 0.69379801E+01 0.69180586E+01 0.68982044E+01 0.68784170E+01 0.68586961E+01 - 0.68390414E+01 0.68194525E+01 0.67999291E+01 0.67804708E+01 0.67610773E+01 - 0.67417483E+01 0.67224835E+01 0.67032824E+01 0.66841448E+01 0.66650703E+01 - 0.66460586E+01 0.66271095E+01 0.66082225E+01 0.65893973E+01 0.65706338E+01 - 0.65519314E+01 0.65332900E+01 0.65147091E+01 0.64961886E+01 0.64777281E+01 - 0.64593273E+01 0.64409858E+01 0.64227035E+01 0.64044800E+01 0.63863150E+01 - 0.63682082E+01 0.63501594E+01 0.63321682E+01 0.63142344E+01 0.62963577E+01 - 0.62785377E+01 0.62607743E+01 0.62430671E+01 0.62254159E+01 0.62078204E+01 - 0.61902803E+01 0.61727954E+01 0.61553653E+01 0.61379899E+01 0.61206689E+01 - 0.61034019E+01 0.60861888E+01 0.60690293E+01 0.60519230E+01 0.60348699E+01 - 0.60178696E+01 0.60009218E+01 0.59840264E+01 0.59671830E+01 0.59503915E+01 - 0.59336515E+01 0.59169629E+01 0.59003254E+01 0.58837387E+01 0.58672027E+01 - 0.58507170E+01 0.58342815E+01 0.58178959E+01 0.58015600E+01 0.57852736E+01 - 0.57690364E+01 0.57528482E+01 0.57367087E+01 0.57206179E+01 0.57045753E+01 - 0.56885809E+01 0.56726344E+01 0.56567356E+01 0.56408842E+01 0.56250801E+01 - 0.56093230E+01 0.55936127E+01 0.55779491E+01 0.55623318E+01 0.55467608E+01 - 0.55312357E+01 0.55157565E+01 0.55003228E+01 0.54849345E+01 0.54695914E+01 - 0.54542933E+01 0.54390399E+01 0.54238312E+01 0.54086668E+01 0.53935467E+01 - 0.53784706E+01 0.53634382E+01 0.53484496E+01 0.53335043E+01 0.53186023E+01 - 0.53037434E+01 0.52889273E+01 0.52741540E+01 0.52594231E+01 0.52447346E+01 - 0.52300883E+01 0.52154839E+01 0.52009213E+01 0.51864003E+01 0.51719208E+01 - 0.51574825E+01 0.51430854E+01 0.51287291E+01 0.51144136E+01 0.51001387E+01 - 0.50859042E+01 0.50717100E+01 0.50575558E+01 0.50434415E+01 0.50293670E+01 - 0.50153321E+01 0.50013366E+01 0.49873803E+01 0.49734632E+01 0.49595850E+01 - 0.49457456E+01 0.49319448E+01 0.49181824E+01 0.49044584E+01 0.48907725E+01 - 0.48771247E+01 0.48635147E+01 0.48499424E+01 0.48364076E+01 0.48229102E+01 - 0.48094501E+01 0.47960271E+01 0.47826411E+01 0.47692919E+01 0.47559793E+01 - 0.47427032E+01 0.47294636E+01 0.47162601E+01 0.47030928E+01 0.46899614E+01 - 0.46768658E+01 0.46638059E+01 0.46507816E+01 0.46377926E+01 0.46248389E+01 - 0.46119204E+01 0.45990368E+01 0.45861881E+01 0.45733741E+01 0.45605947E+01 - 0.45478498E+01 0.45351392E+01 0.45224629E+01 0.45098206E+01 0.44972122E+01 - 0.44846377E+01 0.44720968E+01 0.44595895E+01 0.44471157E+01 0.44346752E+01 - 0.44222679E+01 0.44098936E+01 0.43975523E+01 0.43852438E+01 0.43729681E+01 - 0.43607249E+01 0.43485142E+01 0.43363358E+01 0.43241897E+01 0.43120757E+01 - 0.42999937E+01 0.42879435E+01 0.42759252E+01 0.42639385E+01 0.42519833E+01 - 0.42400596E+01 0.42281672E+01 0.42163060E+01 0.42044759E+01 0.41926767E+01 - 0.41809085E+01 0.41691710E+01 0.41574641E+01 0.41457878E+01 0.41341420E+01 - 0.41225265E+01 0.41109412E+01 0.40993861E+01 0.40878609E+01 0.40763657E+01 - 0.40649003E+01 0.40534646E+01 0.40420585E+01 0.40306820E+01 0.40193348E+01 - 0.40080169E+01 0.39967283E+01 0.39854687E+01 0.39742382E+01 0.39630365E+01 - 0.39518637E+01 0.39407196E+01 0.39296041E+01 0.39185172E+01 0.39074586E+01 - 0.38964284E+01 0.38854265E+01 0.38744526E+01 0.38635069E+01 0.38525891E+01 - 0.38416991E+01 0.38308370E+01 0.38200025E+01 0.38091956E+01 0.37984163E+01 - 0.37876643E+01 0.37769397E+01 0.37662423E+01 0.37555721E+01 0.37449289E+01 - 0.37343127E+01 0.37237234E+01 0.37131609E+01 0.37026251E+01 0.36921159E+01 - 0.36816333E+01 0.36711771E+01 0.36607474E+01 0.36503439E+01 0.36399667E+01 - 0.36296155E+01 0.36192905E+01 0.36089914E+01 0.35987181E+01 0.35884707E+01 - 0.35782491E+01 0.35680530E+01 0.35578826E+01 0.35477376E+01 0.35376180E+01 - 0.35275238E+01 0.35174548E+01 0.35074110E+01 0.34973923E+01 0.34873987E+01 - 0.34774300E+01 0.34674861E+01 0.34575671E+01 0.34476728E+01 0.34378031E+01 - 0.34279580E+01 0.34181375E+01 0.34083413E+01 0.33985695E+01 0.33888220E+01 - 0.33790987E+01 0.33693996E+01 0.33597245E+01 0.33500735E+01 0.33404463E+01 - 0.33308431E+01 0.33212636E+01 0.33117078E+01 0.33021757E+01 0.32926672E+01 - 0.32831822E+01 0.32737206E+01 0.32642825E+01 0.32548676E+01 0.32454760E+01 - 0.32361076E+01 0.32267623E+01 0.32174400E+01 0.32081407E+01 0.31988644E+01 - 0.31896109E+01 0.31803802E+01 0.31711722E+01 0.31619869E+01 0.31528242E+01 - 0.31436840E+01 0.31345663E+01 0.31254710E+01 0.31163980E+01 0.31073474E+01 - 0.30983189E+01 0.30893127E+01 0.30803285E+01 0.30713664E+01 0.30624263E+01 - 0.30535081E+01 0.30446117E+01 0.30357372E+01 0.30268844E+01 0.30180533E+01 - 0.30092438E+01 0.30004559E+01 0.29916895E+01 0.29829445E+01 0.29742210E+01 - 0.29655188E+01 0.29568379E+01 0.29481782E+01 0.29395397E+01 0.29309223E+01 - 0.29223259E+01 0.29137506E+01 0.29051962E+01 0.28966627E+01 0.28881500E+01 - 0.28796582E+01 0.28711870E+01 0.28627366E+01 0.28543067E+01 0.28458975E+01 - 0.28375087E+01 0.28291404E+01 0.28207926E+01 0.28124650E+01 0.28041578E+01 - 0.27958709E+01 0.27876042E+01 0.27793576E+01 0.27711311E+01 0.27629247E+01 - 0.27547382E+01 0.27465718E+01 0.27384252E+01 0.27302985E+01 0.27221916E+01 - 0.27141044E+01 0.27060369E+01 0.26979891E+01 0.26899609E+01 0.26819523E+01 - 0.26739631E+01 0.26659934E+01 0.26580432E+01 0.26501123E+01 0.26422007E+01 - 0.26343084E+01 0.26264353E+01 0.26185814E+01 0.26107466E+01 0.26029309E+01 - 0.25951343E+01 0.25873566E+01 0.25795979E+01 0.25718581E+01 0.25641371E+01 - 0.25564350E+01 0.25487516E+01 0.25410869E+01 0.25334409E+01 0.25258136E+01 - 0.25182048E+01 0.25106146E+01 0.25030429E+01 0.24954896E+01 0.24879547E+01 - 0.24804383E+01 0.24729401E+01 0.24654602E+01 0.24579986E+01 0.24505552E+01 - 0.24431299E+01 0.24357227E+01 0.24283337E+01 0.24209626E+01 0.24136095E+01 - 0.24062744E+01 0.23989572E+01 0.23916579E+01 0.23843763E+01 0.23771126E+01 - 0.23698666E+01 0.23626383E+01 0.23554277E+01 0.23482347E+01 0.23410593E+01 - 0.23339014E+01 0.23267610E+01 0.23196381E+01 0.23125327E+01 0.23054446E+01 - 0.22983738E+01 0.22913204E+01 0.22842842E+01 0.22772653E+01 0.22702636E+01 - 0.22632790E+01 0.22563115E+01 0.22493611E+01 0.22424278E+01 0.22355114E+01 - 0.22286120E+01 0.22217296E+01 0.22148640E+01 0.22080154E+01 0.22011835E+01 - 0.21943684E+01 0.21875700E+01 0.21807884E+01 0.21740234E+01 0.21672751E+01 - 0.21605434E+01 0.21538282E+01 0.21471295E+01 0.21404474E+01 0.21337817E+01 - 0.21271325E+01 0.21204996E+01 0.21138831E+01 0.21072829E+01 0.21006989E+01 - 0.20941313E+01 0.20875798E+01 0.20810445E+01 0.20745254E+01 0.20680224E+01 - 0.20615354E+01 0.20550645E+01 0.20486096E+01 0.20421707E+01 0.20357477E+01 - 0.20293406E+01 0.20229494E+01 0.20165741E+01 0.20102145E+01 0.20038708E+01 - 0.19975427E+01 0.19912304E+01 0.19849338E+01 0.19786528E+01 0.19723874E+01 - 0.19661376E+01 0.19599034E+01 0.19536846E+01 0.19474814E+01 0.19412936E+01 - 0.19351212E+01 0.19289642E+01 0.19228226E+01 0.19166963E+01 0.19105853E+01 - 0.19044895E+01 0.18984090E+01 0.18923437E+01 0.18862935E+01 0.18802585E+01 - 0.18742386E+01 0.18682338E+01 0.18622440E+01 0.18562693E+01 0.18503095E+01 - 0.18443647E+01 0.18384348E+01 0.18325198E+01 0.18266197E+01 0.18207344E+01 - 0.18148639E+01 0.18090082E+01 0.18031673E+01 0.17973410E+01 0.17915295E+01 - 0.17857326E+01 0.17799503E+01 0.17741827E+01 0.17684296E+01 0.17626910E+01 - 0.17569670E+01 0.17512575E+01 0.17455624E+01 0.17398817E+01 0.17342155E+01 - 0.17285636E+01 0.17229260E+01 0.17173028E+01 0.17116938E+01 0.17060992E+01 - 0.17005187E+01 0.16949524E+01 0.16894004E+01 0.16838624E+01 0.16783386E+01 - 0.16728289E+01 0.16673332E+01 0.16618516E+01 0.16563840E+01 0.16509303E+01 - 0.16454906E+01 0.16400649E+01 0.16346530E+01 0.16292550E+01 0.16238709E+01 - 0.16185006E+01 0.16131440E+01 0.16078013E+01 0.16024722E+01 0.15971569E+01 - 0.15918553E+01 0.15865673E+01 0.15812930E+01 0.15760322E+01 0.15707851E+01 - 0.15655515E+01 0.15603314E+01 0.15551248E+01 0.15499317E+01 0.15447521E+01 - 0.15395858E+01 0.15344330E+01 0.15292935E+01 0.15241674E+01 0.15190546E+01 - 0.15139551E+01 0.15088689E+01 0.15037959E+01 0.14987361E+01 0.14936896E+01 - 0.14886562E+01 0.14836359E+01 0.14786288E+01 0.14736347E+01 0.14686537E+01 - 0.14636858E+01 0.14587308E+01 0.14537889E+01 0.14488599E+01 0.14439439E+01 - 0.14390408E+01 0.14341506E+01 0.14292732E+01 0.14244087E+01 0.14195571E+01 - 0.14147182E+01 0.14098921E+01 0.14050787E+01 0.14002780E+01 0.13954901E+01 - 0.13907148E+01 0.13859522E+01 0.13812022E+01 0.13764648E+01 0.13717400E+01 - 0.13670277E+01 0.13623280E+01 0.13576408E+01 0.13529661E+01 0.13483038E+01 - 0.13436539E+01 0.13390165E+01 0.13343915E+01 0.13297788E+01 0.13251784E+01 - 0.13205904E+01 0.13160147E+01 0.13114512E+01 0.13069000E+01 0.13023611E+01 - 0.12978343E+01 0.12933197E+01 0.12888172E+01 0.12843269E+01 0.12798487E+01 - 0.12753826E+01 0.12709285E+01 0.12664865E+01 0.12620565E+01 0.12576385E+01 - 0.12532325E+01 0.12488384E+01 0.12444563E+01 0.12400860E+01 0.12357276E+01 - 0.12313811E+01 0.12270465E+01 0.12227236E+01 0.12184125E+01 0.12141132E+01 - 0.12098257E+01 0.12055499E+01 0.12012857E+01 0.11970333E+01 0.11927925E+01 - 0.11885634E+01 0.11843458E+01 0.11801399E+01 0.11759455E+01 0.11717627E+01 - 0.11675914E+01 0.11634316E+01 0.11592833E+01 0.11551464E+01 0.11510210E+01 - 0.11469070E+01 0.11428044E+01 0.11387131E+01 0.11346332E+01 0.11305647E+01 - 0.11265074E+01 0.11224615E+01 0.11184268E+01 0.11144033E+01 0.11103911E+01 - 0.11063900E+01 0.11024002E+01 0.10984215E+01 0.10944539E+01 0.10904974E+01 - 0.10865521E+01 0.10826178E+01 0.10786946E+01 0.10747823E+01 0.10708811E+01 - 0.10669909E+01 0.10631117E+01 0.10592434E+01 0.10553860E+01 0.10515395E+01 - 0.10477039E+01 0.10438792E+01 0.10400653E+01 0.10362622E+01 0.10324699E+01 - 0.10286884E+01 0.10249177E+01 0.10211577E+01 0.10174084E+01 0.10136698E+01 - 0.10099418E+01 0.10062246E+01 0.10025179E+01 0.99882189E+00 0.99513644E+00 - 0.99146157E+00 0.98779724E+00 0.98414344E+00 0.98050016E+00 0.97686736E+00 - 0.97324502E+00 0.96963314E+00 0.96603168E+00 0.96244062E+00 0.95885995E+00 - 0.95528965E+00 0.95172969E+00 0.94818006E+00 0.94464073E+00 0.94111169E+00 - 0.93759291E+00 0.93408437E+00 0.93058606E+00 0.92709795E+00 0.92362003E+00 - 0.92015227E+00 0.91669465E+00 0.91324716E+00 0.90980976E+00 0.90638246E+00 - 0.90296521E+00 0.89955801E+00 0.89616083E+00 0.89277366E+00 0.88939647E+00 - 0.88602925E+00 0.88267196E+00 0.87932461E+00 0.87598715E+00 0.87265958E+00 - 0.86934188E+00 0.86603402E+00 0.86273599E+00 0.85944776E+00 0.85616932E+00 - 0.85290065E+00 0.84964172E+00 0.84639252E+00 0.84315303E+00 0.83992322E+00 - 0.83670309E+00 0.83349260E+00 0.83029174E+00 0.82710050E+00 0.82391884E+00 - 0.82074675E+00 0.81758422E+00 0.81443122E+00 0.81128773E+00 0.80815374E+00 - 0.80502922E+00 0.80191415E+00 0.79880852E+00 0.79571231E+00 0.79262550E+00 - 0.78954806E+00 0.78647998E+00 0.78342124E+00 0.78037182E+00 0.77733170E+00 - 0.77430087E+00 0.77127929E+00 0.76826697E+00 0.76526386E+00 0.76226996E+00 - 0.75928525E+00 0.75630970E+00 0.75334331E+00 0.75038604E+00 0.74743788E+00 - 0.74449882E+00 0.74156883E+00 0.73864789E+00 0.73573598E+00 0.73283309E+00 - 0.72993920E+00 0.72705429E+00 0.72417834E+00 0.72131132E+00 0.71845323E+00 - 0.71560404E+00 0.71276373E+00 0.70993229E+00 0.70710970E+00 0.70429593E+00 - 0.70149098E+00 0.69869481E+00 0.69590741E+00 0.69312877E+00 0.69035886E+00 - 0.68759767E+00 0.68484518E+00 0.68210136E+00 0.67936621E+00 0.67663969E+00 - 0.67392180E+00 0.67121251E+00 0.66851181E+00 0.66581967E+00 0.66313609E+00 - 0.66046103E+00 0.65779449E+00 0.65513644E+00 0.65248686E+00 0.64984575E+00 - 0.64721306E+00 0.64458880E+00 0.64197295E+00 0.63936547E+00 0.63676636E+00 - 0.63417559E+00 0.63159316E+00 0.62901903E+00 0.62645320E+00 0.62389564E+00 - 0.62134633E+00 0.61880526E+00 0.61627241E+00 0.61374776E+00 0.61123130E+00 - 0.60872299E+00 0.60622284E+00 0.60373081E+00 0.60124689E+00 0.59877106E+00 - 0.59630331E+00 0.59384361E+00 0.59139195E+00 0.58894831E+00 0.58651267E+00 - 0.58408501E+00 0.58166532E+00 0.57925358E+00 0.57684977E+00 0.57445386E+00 - 0.57206586E+00 0.56968572E+00 0.56731345E+00 0.56494901E+00 0.56259240E+00 - 0.56024359E+00 0.55790257E+00 0.55556931E+00 0.55324381E+00 0.55092604E+00 - 0.54861599E+00 0.54631363E+00 0.54401895E+00 0.54173193E+00 0.53945256E+00 - 0.53718081E+00 0.53491667E+00 0.53266012E+00 0.53041115E+00 0.52816973E+00 - 0.52593585E+00 0.52370949E+00 0.52149063E+00 0.51927925E+00 0.51707535E+00 - 0.51487889E+00 0.51268987E+00 0.51050826E+00 0.50833404E+00 0.50616721E+00 - 0.50400774E+00 0.50185561E+00 0.49971081E+00 0.49757332E+00 0.49544312E+00 - 0.49332020E+00 0.49120453E+00 0.48909611E+00 0.48699490E+00 0.48490090E+00 - 0.48281409E+00 0.48073445E+00 0.47866196E+00 0.47659660E+00 0.47453837E+00 - 0.47248723E+00 0.47044318E+00 0.46840620E+00 0.46637626E+00 0.46435335E+00 - 0.46233746E+00 0.46032857E+00 0.45832666E+00 0.45633171E+00 0.45434370E+00 - 0.45236263E+00 0.45038846E+00 0.44842119E+00 0.44646080E+00 0.44450726E+00 - 0.44256057E+00 0.44062070E+00 0.43868764E+00 0.43676138E+00 0.43484188E+00 - 0.43292915E+00 0.43102315E+00 0.42912388E+00 0.42723131E+00 0.42534544E+00 - 0.42346623E+00 0.42159368E+00 0.41972777E+00 0.41786848E+00 0.41601579E+00 - 0.41416969E+00 0.41233016E+00 0.41049719E+00 0.40867075E+00 0.40685083E+00 - 0.40503742E+00 0.40323049E+00 0.40143002E+00 0.39963602E+00 0.39784844E+00 - 0.39606729E+00 0.39429254E+00 0.39252417E+00 0.39076217E+00 0.38900652E+00 - 0.38725721E+00 0.38551421E+00 0.38377752E+00 0.38204711E+00 0.38032297E+00 - 0.37860508E+00 0.37689343E+00 0.37518799E+00 0.37348876E+00 0.37179571E+00 - 0.37010882E+00 0.36842809E+00 0.36675350E+00 0.36508502E+00 0.36342264E+00 - 0.36176635E+00 0.36011613E+00 0.35847196E+00 0.35683382E+00 0.35520171E+00 - 0.35357559E+00 0.35195546E+00 0.35034131E+00 0.34873310E+00 0.34713083E+00 - 0.34553448E+00 0.34394404E+00 0.34235948E+00 0.34078080E+00 0.33920796E+00 - 0.33764097E+00 0.33607980E+00 0.33452443E+00 0.33297485E+00 0.33143105E+00 - 0.32989300E+00 0.32836069E+00 0.32683410E+00 0.32531322E+00 0.32379803E+00 - 0.32228852E+00 0.32078467E+00 0.31928646E+00 0.31779387E+00 0.31630689E+00 - 0.31482551E+00 0.31334970E+00 0.31187946E+00 0.31041476E+00 0.30895559E+00 - 0.30750193E+00 0.30605377E+00 0.30461108E+00 0.30317386E+00 0.30174209E+00 - 0.30031576E+00 0.29889483E+00 0.29747931E+00 0.29606917E+00 0.29466439E+00 - 0.29326497E+00 0.29187089E+00 0.29048212E+00 0.28909865E+00 0.28772048E+00 - 0.28634757E+00 0.28497992E+00 0.28361751E+00 0.28226032E+00 0.28090834E+00 - 0.27956155E+00 0.27821993E+00 0.27688347E+00 0.27555216E+00 0.27422597E+00 - 0.27290490E+00 0.27158891E+00 0.27027801E+00 0.26897218E+00 0.26767139E+00 - 0.26637563E+00 0.26508489E+00 0.26379914E+00 0.26251838E+00 0.26124259E+00 - 0.25997176E+00 0.25870585E+00 0.25744487E+00 0.25618880E+00 0.25493761E+00 - 0.25369130E+00 0.25244984E+00 0.25121323E+00 0.24998144E+00 0.24875446E+00 - 0.24753227E+00 0.24631487E+00 0.24510222E+00 0.24389433E+00 0.24269116E+00 - 0.24149271E+00 0.24029896E+00 0.23910989E+00 0.23792550E+00 0.23674575E+00 - 0.23557064E+00 0.23440016E+00 0.23323427E+00 0.23207298E+00 0.23091626E+00 - 0.22976411E+00 0.22861649E+00 0.22747340E+00 0.22633482E+00 0.22520074E+00 - 0.22407114E+00 0.22294600E+00 0.22182531E+00 0.22070906E+00 0.21959722E+00 - 0.21848979E+00 0.21738674E+00 0.21628806E+00 0.21519374E+00 0.21410376E+00 - 0.21301810E+00 0.21193675E+00 0.21085969E+00 0.20978691E+00 0.20871839E+00 - 0.20765412E+00 0.20659408E+00 0.20553825E+00 0.20448663E+00 0.20343919E+00 - 0.20239591E+00 0.20135679E+00 0.20032181E+00 0.19929095E+00 0.19826419E+00 - 0.19724153E+00 0.19622294E+00 0.19520841E+00 0.19419793E+00 0.19319148E+00 - 0.19218903E+00 0.19119059E+00 0.19019613E+00 0.18920563E+00 0.18821909E+00 - 0.18723648E+00 0.18625780E+00 0.18528302E+00 0.18431212E+00 0.18334511E+00 - 0.18238195E+00 0.18142263E+00 0.18046714E+00 0.17951547E+00 0.17856759E+00 - 0.17762349E+00 0.17668316E+00 0.17574657E+00 0.17481373E+00 0.17388460E+00 - 0.17295918E+00 0.17203744E+00 0.17111938E+00 0.17020498E+00 0.16929421E+00 - 0.16838708E+00 0.16748356E+00 0.16658363E+00 0.16568729E+00 0.16479451E+00 - 0.16390528E+00 0.16301958E+00 0.16213740E+00 0.16125873E+00 0.16038355E+00 - 0.15951183E+00 0.15864358E+00 0.15777877E+00 0.15691738E+00 0.15605941E+00 - 0.15520483E+00 0.15435363E+00 0.15350580E+00 0.15266132E+00 0.15182017E+00 - 0.15098234E+00 0.15014782E+00 0.14931658E+00 0.14848862E+00 0.14766391E+00 - 0.14684245E+00 0.14602421E+00 0.14520919E+00 0.14439736E+00 0.14358871E+00 - 0.14278323E+00 0.14198090E+00 0.14118170E+00 0.14038563E+00 0.13959265E+00 - 0.13880277E+00 0.13801596E+00 0.13723221E+00 0.13645151E+00 0.13567383E+00 - 0.13489916E+00 0.13412749E+00 0.13335881E+00 0.13259309E+00 0.13183032E+00 - 0.13107049E+00 0.13031358E+00 0.12955957E+00 0.12880846E+00 0.12806022E+00 - 0.12731485E+00 0.12657232E+00 0.12583261E+00 0.12509573E+00 0.12436164E+00 - 0.12363034E+00 0.12290181E+00 0.12217603E+00 0.12145299E+00 0.12073268E+00 - 0.12001507E+00 0.11930016E+00 0.11858793E+00 0.11787837E+00 0.11717145E+00 - 0.11646716E+00 0.11576550E+00 0.11506644E+00 0.11436997E+00 0.11367607E+00 - 0.11298474E+00 0.11229595E+00 0.11160969E+00 0.11092594E+00 0.11024469E+00 - 0.10956593E+00 0.10888964E+00 0.10821581E+00 0.10754442E+00 0.10687545E+00 - 0.10620890E+00 0.10554474E+00 0.10488297E+00 0.10422356E+00 0.10356651E+00 - 0.10291180E+00 0.10225942E+00 0.10160934E+00 0.10096156E+00 0.10031607E+00 - 0.99672837E-01 0.99031862E-01 0.98393126E-01 0.97756615E-01 0.97122316E-01 - 0.96490214E-01 0.95860295E-01 0.95232546E-01 0.94606951E-01 0.93983499E-01 - 0.93362174E-01 0.92742963E-01 0.92125853E-01 0.91510830E-01 0.90897880E-01 - 0.90286990E-01 0.89678146E-01 0.89071336E-01 0.88466546E-01 0.87863763E-01 - 0.87262973E-01 0.86664164E-01 0.86067323E-01 0.85472437E-01 0.84879493E-01 - 0.84288479E-01 0.83699382E-01 0.83112189E-01 0.82526888E-01 0.81943467E-01 - 0.81361914E-01 0.80782216E-01 0.80204362E-01 0.79628339E-01 0.79054136E-01 - 0.78481742E-01 0.77911144E-01 0.77342331E-01 0.76775293E-01 0.76210017E-01 - 0.75646493E-01 0.75084711E-01 0.74524658E-01 0.73966325E-01 0.73409701E-01 - 0.72854776E-01 0.72301539E-01 0.71749981E-01 0.71200092E-01 0.70651862E-01 - 0.70105281E-01 0.69560341E-01 0.69017031E-01 0.68475344E-01 0.67935270E-01 - 0.67396800E-01 0.66859926E-01 0.66324640E-01 0.65790934E-01 0.65258799E-01 - 0.64728229E-01 0.64199216E-01 0.63671753E-01 0.63145832E-01 0.62621447E-01 - 0.62098591E-01 0.61577258E-01 0.61057443E-01 0.60539138E-01 0.60022340E-01 - 0.59507041E-01 0.58993238E-01 0.58480925E-01 0.57970099E-01 0.57460754E-01 - 0.56952887E-01 0.56446495E-01 0.55941573E-01 0.55438119E-01 0.54936130E-01 - 0.54435603E-01 0.53936537E-01 0.53438929E-01 0.52942779E-01 0.52448084E-01 - 0.51954845E-01 0.51463060E-01 0.50972729E-01 0.50483853E-01 0.49996433E-01 - 0.49510468E-01 0.49025961E-01 0.48542913E-01 0.48061326E-01 0.47581202E-01 - 0.47102545E-01 0.46625357E-01 0.46149642E-01 0.45675405E-01 0.45202649E-01 - 0.44731380E-01 0.44261602E-01 0.43793321E-01 0.43326544E-01 0.42861277E-01 - 0.42397527E-01 0.41935302E-01 0.41474608E-01 0.41015456E-01 0.40557852E-01 - 0.40101807E-01 0.39647331E-01 0.39194433E-01 0.38743124E-01 0.38293415E-01 - 0.37845318E-01 0.37398845E-01 0.36954008E-01 0.36510820E-01 0.36069295E-01 - 0.35629448E-01 0.35191291E-01 0.34754841E-01 0.34320112E-01 0.33887121E-01 - 0.33455885E-01 0.33026419E-01 0.32598742E-01 0.32172871E-01 0.31748824E-01 - 0.31326621E-01 0.30906281E-01 0.30487824E-01 0.30071270E-01 0.29656640E-01 - 0.29243954E-01 0.28833236E-01 0.28424506E-01 0.28017787E-01 0.27613104E-01 - 0.27210478E-01 0.26809934E-01 0.26411497E-01 0.26015191E-01 0.25621041E-01 - 0.25229073E-01 0.24839313E-01 0.24451787E-01 0.24066522E-01 0.23683546E-01 - 0.23302884E-01 0.22924566E-01 0.22548619E-01 0.22175072E-01 0.21803953E-01 - 0.21435291E-01 0.21069115E-01 0.20705455E-01 0.20344340E-01 0.19985801E-01 - 0.19629866E-01 0.19276566E-01 0.18925932E-01 0.18577994E-01 0.18232781E-01 - 0.17890326E-01 0.17550657E-01 0.17213806E-01 0.16879804E-01 0.16548680E-01 - 0.16220465E-01 0.15895190E-01 0.15572884E-01 0.15253578E-01 0.14937302E-01 - 0.14624084E-01 0.14313955E-01 0.14006944E-01 0.13703079E-01 0.13402389E-01 - 0.13104901E-01 0.12810644E-01 0.12519645E-01 0.12231930E-01 0.11947525E-01 - 0.11666456E-01 0.11388748E-01 0.11114425E-01 0.10843512E-01 0.10576031E-01 - 0.10312003E-01 0.10051452E-01 0.97943967E-02 0.95408577E-02 0.92908537E-02 - 0.90444027E-02 0.88015217E-02 0.85622266E-02 0.83265324E-02 0.80944530E-02 - 0.78660012E-02 0.76411886E-02 0.74200257E-02 0.72025216E-02 0.69886844E-02 - 0.67785209E-02 0.65720364E-02 0.63692351E-02 0.61701198E-02 0.59746917E-02 - 0.57829508E-02 0.55948957E-02 0.54105234E-02 0.52298296E-02 0.50528082E-02 - 0.48794520E-02 0.47097520E-02 0.45436977E-02 0.43812771E-02 0.42224765E-02 - 0.40672810E-02 0.39156737E-02 0.37676363E-02 0.36231491E-02 0.34821905E-02 - 0.33447375E-02 0.32107656E-02 0.30802487E-02 0.29531591E-02 0.28294677E-02 - 0.27091436E-02 0.25921548E-02 0.24784677E-02 0.23680470E-02 0.22608563E-02 - 0.21568578E-02 0.20560121E-02 0.19582788E-02 0.18636160E-02 0.17719805E-02 - 0.16833282E-02 0.15976135E-02 0.15147900E-02 0.14348101E-02 0.13576251E-02 - 0.12831856E-02 0.12114409E-02 0.11423400E-02 0.10758306E-02 0.10118600E-02 - 0.95037475E-03 0.89132078E-03 0.83464352E-03 0.78028791E-03 0.72819850E-03 - 0.67831951E-03 0.63059487E-03 0.58496835E-03 0.54138356E-03 0.49978405E-03 - 0.46011338E-03 0.42231518E-03 0.38633324E-03 0.35211151E-03 0.31959426E-03 - 0.28872607E-03 0.25945191E-03 0.23171724E-03 0.20546801E-03 0.18065078E-03 - 0.15721273E-03 0.13510173E-03 0.11426639E-03 0.94656136E-04 0.76221215E-04 - 0.58912771E-04 0.42682877E-04 0.27484576E-04 0.13271919E-04 0.00000000E+00 - 0.98182606E+02 0.98182606E+02 0.98182606E+02 0.98182606E+02 0.98182606E+02 - 0.98182606E+02 0.98182606E+02 0.98182606E+02 0.98182606E+02 0.98182606E+02 - 0.98182606E+02 0.98182606E+02 0.98182606E+02 0.98182606E+02 0.98182606E+02 - 0.98182606E+02 0.98182606E+02 0.98182606E+02 0.98182606E+02 0.98182606E+02 - 0.98182606E+02 0.98182606E+02 0.98182606E+02 0.98182606E+02 0.98182606E+02 - 0.98182606E+02 0.98182606E+02 0.98182606E+02 0.98182606E+02 0.98182606E+02 - 0.98182606E+02 0.98182606E+02 0.98182606E+02 0.98182606E+02 0.98182606E+02 - 0.98182606E+02 0.98182606E+02 0.98182606E+02 0.98182606E+02 0.98182606E+02 - 0.98182606E+02 0.98182606E+02 0.98182606E+02 0.98182606E+02 0.98182606E+02 - 0.98182606E+02 0.98182606E+02 0.95386420E+02 0.92315792E+02 0.89404279E+02 - 0.86640635E+02 0.84014613E+02 0.81516857E+02 0.79138812E+02 0.76872640E+02 - 0.74711148E+02 0.72647728E+02 0.70676293E+02 0.68791236E+02 0.66987376E+02 - 0.65259928E+02 0.63604460E+02 0.62016864E+02 0.60493329E+02 0.59030312E+02 - 0.57624520E+02 0.56272883E+02 0.54972542E+02 0.53720825E+02 0.52515239E+02 - 0.51353452E+02 0.50233279E+02 0.49152673E+02 0.48109717E+02 0.47102609E+02 - 0.46129657E+02 0.45189268E+02 0.44279946E+02 0.43400280E+02 0.42548941E+02 - 0.41724674E+02 0.40926297E+02 0.40152690E+02 0.39402796E+02 0.38675616E+02 - 0.37970203E+02 0.37285660E+02 0.36621138E+02 0.35975830E+02 0.35348972E+02 - 0.34739838E+02 0.34147736E+02 0.33572012E+02 0.33012041E+02 0.32467230E+02 - 0.31937012E+02 0.31420850E+02 0.30918230E+02 0.30428661E+02 0.29951677E+02 - 0.29486832E+02 0.29033700E+02 0.28591874E+02 0.28160964E+02 0.27740599E+02 - 0.27330422E+02 0.26930094E+02 0.26539287E+02 0.26157690E+02 0.25785002E+02 - 0.25420936E+02 0.25065218E+02 0.24717583E+02 0.24377777E+02 0.24045556E+02 - 0.23720688E+02 0.23402947E+02 0.23092117E+02 0.22787990E+02 0.22490368E+02 - 0.22199057E+02 0.21913872E+02 0.21634636E+02 0.21361178E+02 0.21093331E+02 - 0.20830936E+02 0.20573841E+02 0.20321897E+02 0.20074962E+02 0.19832897E+02 - 0.19595570E+02 0.19362853E+02 0.19134622E+02 0.18910756E+02 0.18691142E+02 - 0.18475666E+02 0.18264221E+02 0.18056702E+02 0.17853010E+02 0.17653045E+02 - 0.17456714E+02 0.17263925E+02 0.17074590E+02 0.16888622E+02 0.16705940E+02 - 0.16526462E+02 0.16350111E+02 0.16176811E+02 0.16006490E+02 0.15839076E+02 - 0.15674500E+02 0.15512696E+02 0.15353599E+02 0.15197147E+02 0.15043278E+02 - 0.14891933E+02 0.14743055E+02 0.14596588E+02 0.14452478E+02 0.14310672E+02 - 0.14171120E+02 0.14033771E+02 0.13898578E+02 0.13765493E+02 0.13634471E+02 - 0.13505467E+02 0.13378439E+02 0.13253343E+02 0.13130141E+02 0.13008791E+02 - 0.12889255E+02 0.12771495E+02 0.12655475E+02 0.12541160E+02 0.12428513E+02 - 0.12317502E+02 0.12208094E+02 0.12100256E+02 0.11993956E+02 0.11889166E+02 - 0.11785854E+02 0.11683992E+02 0.11583551E+02 0.11484505E+02 0.11386825E+02 - 0.11290486E+02 0.11195463E+02 0.11101730E+02 0.11009262E+02 0.10918037E+02 - 0.10828031E+02 0.10739221E+02 0.10651585E+02 0.10565101E+02 0.10479750E+02 - 0.10395509E+02 0.10312358E+02 0.10230279E+02 0.10149252E+02 0.10069258E+02 - 0.99902786E+01 0.99122961E+01 0.98352930E+01 0.97592522E+01 0.96841568E+01 - 0.96099905E+01 0.95367373E+01 0.94643815E+01 0.93929079E+01 0.93223014E+01 - 0.92525474E+01 0.91836315E+01 0.91155396E+01 0.90482582E+01 0.89817737E+01 - 0.89160729E+01 0.88511429E+01 0.87869713E+01 0.87235455E+01 0.86608536E+01 - 0.85988836E+01 0.85376240E+01 0.84770635E+01 0.84171908E+01 0.83579950E+01 - 0.82994656E+01 0.82415920E+01 0.81843640E+01 0.81277714E+01 0.80718046E+01 - 0.80164537E+01 0.79617094E+01 0.79075623E+01 0.78540034E+01 0.78010237E+01 - 0.77486144E+01 0.76967670E+01 0.76454732E+01 0.75947245E+01 0.75445129E+01 - 0.74948305E+01 0.74456694E+01 0.73970221E+01 0.73488809E+01 0.73012386E+01 - 0.72540880E+01 0.72074218E+01 0.71612331E+01 0.71155152E+01 0.70702613E+01 - 0.70254648E+01 0.69811192E+01 0.69372181E+01 0.68937555E+01 0.68507250E+01 - 0.68081207E+01 0.67659367E+01 0.67241671E+01 0.66828063E+01 0.66418487E+01 - 0.66012887E+01 0.65611210E+01 0.65213402E+01 0.64819411E+01 0.64429185E+01 - 0.64042675E+01 0.63659830E+01 0.63280602E+01 0.62904943E+01 0.62532805E+01 - 0.62164144E+01 0.61798911E+01 0.61437064E+01 0.61078559E+01 0.60723350E+01 - 0.60371397E+01 0.60022658E+01 0.59677090E+01 0.59334654E+01 0.58995309E+01 - 0.58659017E+01 0.58325739E+01 0.57995437E+01 0.57668073E+01 0.57343612E+01 - 0.57022016E+01 0.56703250E+01 0.56387279E+01 0.56074068E+01 0.55763584E+01 - 0.55455794E+01 0.55150664E+01 0.54848162E+01 0.54548256E+01 0.54250915E+01 - 0.53956108E+01 0.53663804E+01 0.53373974E+01 0.53086588E+01 0.52801617E+01 - 0.52519033E+01 0.52238807E+01 0.51960911E+01 0.51685319E+01 0.51412003E+01 - 0.51140937E+01 0.50872095E+01 0.50605451E+01 0.50340979E+01 0.50078656E+01 - 0.49818455E+01 0.49560353E+01 0.49304326E+01 0.49050350E+01 0.48798403E+01 - 0.48548461E+01 0.48300502E+01 0.48054503E+01 0.47810443E+01 0.47568301E+01 - 0.47328054E+01 0.47089682E+01 0.46853164E+01 0.46618480E+01 0.46385609E+01 - 0.46154533E+01 0.45925230E+01 0.45697683E+01 0.45471872E+01 0.45247778E+01 - 0.45025383E+01 0.44804669E+01 0.44585617E+01 0.44368211E+01 0.44152431E+01 - 0.43938262E+01 0.43725686E+01 0.43514687E+01 0.43305247E+01 0.43097350E+01 - 0.42890981E+01 0.42686124E+01 0.42482762E+01 0.42280881E+01 0.42080464E+01 - 0.41881497E+01 0.41683966E+01 0.41487855E+01 0.41293149E+01 0.41099835E+01 - 0.40907899E+01 0.40717326E+01 0.40528103E+01 0.40340216E+01 0.40153652E+01 - 0.39968398E+01 0.39784439E+01 0.39601765E+01 0.39420361E+01 0.39240216E+01 - 0.39061317E+01 0.38883651E+01 0.38707207E+01 0.38531972E+01 0.38357936E+01 - 0.38185085E+01 0.38013409E+01 0.37842897E+01 0.37673536E+01 0.37505317E+01 - 0.37338227E+01 0.37172257E+01 0.37007395E+01 0.36843632E+01 0.36680956E+01 - 0.36519357E+01 0.36358826E+01 0.36199351E+01 0.36040924E+01 0.35883534E+01 - 0.35727172E+01 0.35571828E+01 0.35417492E+01 0.35264156E+01 0.35111810E+01 - 0.34960445E+01 0.34810052E+01 0.34660622E+01 0.34512146E+01 0.34364616E+01 - 0.34218022E+01 0.34072357E+01 0.33927612E+01 0.33783779E+01 0.33640849E+01 - 0.33498815E+01 0.33357668E+01 0.33217401E+01 0.33078005E+01 0.32939473E+01 - 0.32801797E+01 0.32664970E+01 0.32528984E+01 0.32393832E+01 0.32259506E+01 - 0.32126000E+01 0.31993305E+01 0.31861416E+01 0.31730324E+01 0.31600024E+01 - 0.31470507E+01 0.31341769E+01 0.31213801E+01 0.31086597E+01 0.30960151E+01 - 0.30834456E+01 0.30709505E+01 0.30585294E+01 0.30461814E+01 0.30339060E+01 - 0.30217026E+01 0.30095706E+01 0.29975094E+01 0.29855183E+01 0.29735969E+01 - 0.29617445E+01 0.29499605E+01 0.29382444E+01 0.29265956E+01 0.29150136E+01 - 0.29034978E+01 0.28920477E+01 0.28806627E+01 0.28693423E+01 0.28580859E+01 - 0.28468931E+01 0.28357634E+01 0.28246962E+01 0.28136909E+01 0.28027472E+01 - 0.27918645E+01 0.27810424E+01 0.27702803E+01 0.27595778E+01 0.27489343E+01 - 0.27383495E+01 0.27278228E+01 0.27173539E+01 0.27069421E+01 0.26965872E+01 - 0.26862886E+01 0.26760459E+01 0.26658587E+01 0.26557265E+01 0.26456490E+01 - 0.26356256E+01 0.26256559E+01 0.26157396E+01 0.26058763E+01 0.25960654E+01 - 0.25863067E+01 0.25765997E+01 0.25669440E+01 0.25573393E+01 0.25477851E+01 - 0.25382810E+01 0.25288268E+01 0.25194219E+01 0.25100661E+01 0.25007590E+01 - 0.24915001E+01 0.24822892E+01 0.24731258E+01 0.24640097E+01 0.24549405E+01 - 0.24459177E+01 0.24369412E+01 0.24280104E+01 0.24191252E+01 0.24102852E+01 - 0.24014899E+01 0.23927392E+01 0.23840326E+01 0.23753699E+01 0.23667507E+01 - 0.23581748E+01 0.23496417E+01 0.23411512E+01 0.23327031E+01 0.23242968E+01 - 0.23159323E+01 0.23076092E+01 0.22993271E+01 0.22910858E+01 0.22828850E+01 - 0.22747244E+01 0.22666038E+01 0.22585228E+01 0.22504811E+01 0.22424785E+01 - 0.22345148E+01 0.22265895E+01 0.22187026E+01 0.22108536E+01 0.22030423E+01 - 0.21952686E+01 0.21875320E+01 0.21798324E+01 0.21721694E+01 0.21645429E+01 - 0.21569526E+01 0.21493983E+01 0.21418796E+01 0.21343964E+01 0.21269484E+01 - 0.21195353E+01 0.21121570E+01 0.21048132E+01 0.20975036E+01 0.20902280E+01 - 0.20829863E+01 0.20757781E+01 0.20686032E+01 0.20614615E+01 0.20543526E+01 - 0.20472765E+01 0.20402328E+01 0.20332213E+01 0.20262419E+01 0.20192942E+01 - 0.20123782E+01 0.20054936E+01 0.19986402E+01 0.19918177E+01 0.19850260E+01 - 0.19782650E+01 0.19715342E+01 0.19648337E+01 0.19581632E+01 0.19515224E+01 - 0.19449112E+01 0.19383295E+01 0.19317769E+01 0.19252534E+01 0.19187587E+01 - 0.19122927E+01 0.19058551E+01 0.18994459E+01 0.18930647E+01 0.18867115E+01 - 0.18803860E+01 0.18740881E+01 0.18678176E+01 0.18615743E+01 0.18553581E+01 - 0.18491688E+01 0.18430061E+01 0.18368701E+01 0.18307604E+01 0.18246769E+01 - 0.18186195E+01 0.18125880E+01 0.18065822E+01 0.18006019E+01 0.17946471E+01 - 0.17887176E+01 0.17828131E+01 0.17769336E+01 0.17710789E+01 0.17652489E+01 - 0.17594433E+01 0.17536621E+01 0.17479051E+01 0.17421721E+01 0.17364630E+01 - 0.17307777E+01 0.17251159E+01 0.17194777E+01 0.17138628E+01 0.17082711E+01 - 0.17027024E+01 0.16971566E+01 0.16916337E+01 0.16861333E+01 0.16806555E+01 - 0.16752000E+01 0.16697668E+01 0.16643557E+01 0.16589665E+01 0.16535993E+01 - 0.16482537E+01 0.16429297E+01 0.16376272E+01 0.16323460E+01 0.16270861E+01 - 0.16218472E+01 0.16166293E+01 0.16114323E+01 0.16062560E+01 0.16011003E+01 - 0.15959650E+01 0.15908502E+01 0.15857556E+01 0.15806812E+01 0.15756267E+01 - 0.15705922E+01 0.15655775E+01 0.15605824E+01 0.15556069E+01 0.15506509E+01 - 0.15457143E+01 0.15407968E+01 0.15358985E+01 0.15310193E+01 0.15261589E+01 - 0.15213174E+01 0.15164945E+01 0.15116903E+01 0.15069045E+01 0.15021372E+01 - 0.14973881E+01 0.14926573E+01 0.14879445E+01 0.14832497E+01 0.14785729E+01 - 0.14739138E+01 0.14692724E+01 0.14646486E+01 0.14600423E+01 0.14554534E+01 - 0.14508818E+01 0.14463274E+01 0.14417902E+01 0.14372700E+01 0.14327668E+01 - 0.14282803E+01 0.14238107E+01 0.14193577E+01 0.14149213E+01 0.14105014E+01 - 0.14060978E+01 0.14017106E+01 0.13973397E+01 0.13929848E+01 0.13886460E+01 - 0.13843232E+01 0.13800163E+01 0.13757252E+01 0.13714497E+01 0.13671900E+01 - 0.13629457E+01 0.13587170E+01 0.13545036E+01 0.13503056E+01 0.13461228E+01 - 0.13419551E+01 0.13378025E+01 0.13336649E+01 0.13295423E+01 0.13254344E+01 - 0.13213413E+01 0.13172630E+01 0.13131992E+01 0.13091500E+01 0.13051152E+01 - 0.13010948E+01 0.12970888E+01 0.12930969E+01 0.12891193E+01 0.12851557E+01 - 0.12812062E+01 0.12772707E+01 0.12733490E+01 0.12694411E+01 0.12655470E+01 - 0.12616666E+01 0.12577998E+01 0.12539465E+01 0.12501067E+01 0.12462803E+01 - 0.12424673E+01 0.12386675E+01 0.12348810E+01 0.12311076E+01 0.12273472E+01 - 0.12235999E+01 0.12198656E+01 0.12161441E+01 0.12124354E+01 0.12087396E+01 - 0.12050564E+01 0.12013858E+01 0.11977279E+01 0.11940824E+01 0.11904494E+01 - 0.11868288E+01 0.11832206E+01 0.11796246E+01 0.11760408E+01 0.11724692E+01 - 0.11689097E+01 0.11653623E+01 0.11618268E+01 0.11583033E+01 0.11547916E+01 - 0.11512918E+01 0.11478037E+01 0.11443273E+01 0.11408626E+01 0.11374094E+01 - 0.11339678E+01 0.11305377E+01 0.11271191E+01 0.11237118E+01 0.11203158E+01 - 0.11169311E+01 0.11135576E+01 0.11101953E+01 0.11068442E+01 0.11035040E+01 - 0.11001749E+01 0.10968568E+01 0.10935496E+01 0.10902532E+01 0.10869677E+01 - 0.10836929E+01 0.10804289E+01 0.10771755E+01 0.10739327E+01 0.10707005E+01 - 0.10674788E+01 0.10642676E+01 0.10610669E+01 0.10578765E+01 0.10546964E+01 - 0.10515266E+01 0.10483671E+01 0.10452178E+01 0.10420786E+01 0.10389496E+01 - 0.10358306E+01 0.10327216E+01 0.10296226E+01 0.10265335E+01 0.10234543E+01 - 0.10203849E+01 0.10173253E+01 0.10142755E+01 0.10112354E+01 0.10082050E+01 - 0.10051842E+01 0.10021730E+01 0.99917134E+00 0.99617917E+00 0.99319647E+00 - 0.99022319E+00 0.98725929E+00 0.98430473E+00 0.98135947E+00 0.97842347E+00 - 0.97549669E+00 0.97257908E+00 0.96967063E+00 0.96677127E+00 0.96388098E+00 - 0.96099971E+00 0.95812743E+00 0.95526410E+00 0.95240969E+00 0.94956414E+00 - 0.94672743E+00 0.94389953E+00 0.94108038E+00 0.93826996E+00 0.93546824E+00 - 0.93267516E+00 0.92989070E+00 0.92711483E+00 0.92434750E+00 0.92158868E+00 - 0.91883834E+00 0.91609644E+00 0.91336295E+00 0.91063782E+00 0.90792104E+00 - 0.90521256E+00 0.90251235E+00 0.89982037E+00 0.89713660E+00 0.89446099E+00 - 0.89179352E+00 0.88913416E+00 0.88648286E+00 0.88383960E+00 0.88120435E+00 - 0.87857707E+00 0.87595774E+00 0.87334631E+00 0.87074276E+00 0.86814705E+00 - 0.86555917E+00 0.86297906E+00 0.86040671E+00 0.85784209E+00 0.85528515E+00 - 0.85273588E+00 0.85019424E+00 0.84766020E+00 0.84513374E+00 0.84261481E+00 - 0.84010340E+00 0.83759947E+00 0.83510300E+00 0.83261395E+00 0.83013230E+00 - 0.82765802E+00 0.82519108E+00 0.82273145E+00 0.82027910E+00 0.81783401E+00 - 0.81539615E+00 0.81296548E+00 0.81054199E+00 0.80812564E+00 0.80571641E+00 - 0.80331428E+00 0.80091920E+00 0.79853116E+00 0.79615014E+00 0.79377609E+00 - 0.79140901E+00 0.78904885E+00 0.78669560E+00 0.78434924E+00 0.78200972E+00 - 0.77967703E+00 0.77735115E+00 0.77503204E+00 0.77271969E+00 0.77041406E+00 - 0.76811514E+00 0.76582289E+00 0.76353730E+00 0.76125834E+00 0.75898598E+00 - 0.75672020E+00 0.75446098E+00 0.75220828E+00 0.74996210E+00 0.74772240E+00 - 0.74548917E+00 0.74326237E+00 0.74104198E+00 0.73882799E+00 0.73662036E+00 - 0.73441908E+00 0.73222413E+00 0.73003547E+00 0.72785309E+00 0.72567696E+00 - 0.72350707E+00 0.72134338E+00 0.71918589E+00 0.71703456E+00 0.71488937E+00 - 0.71275031E+00 0.71061735E+00 0.70849047E+00 0.70636965E+00 0.70425486E+00 - 0.70214609E+00 0.70004331E+00 0.69794651E+00 0.69585566E+00 0.69377074E+00 - 0.69169174E+00 0.68961862E+00 0.68755138E+00 0.68548999E+00 0.68343442E+00 - 0.68138467E+00 0.67934071E+00 0.67730251E+00 0.67527007E+00 0.67324336E+00 - 0.67122236E+00 0.66920705E+00 0.66719742E+00 0.66519344E+00 0.66319509E+00 - 0.66120236E+00 0.65921522E+00 0.65723366E+00 0.65525766E+00 0.65328720E+00 - 0.65132226E+00 0.64936282E+00 0.64740887E+00 0.64546039E+00 0.64351735E+00 - 0.64157974E+00 0.63964754E+00 0.63772074E+00 0.63579931E+00 0.63388324E+00 - 0.63197252E+00 0.63006711E+00 0.62816701E+00 0.62627220E+00 0.62438266E+00 - 0.62249837E+00 0.62061932E+00 0.61874549E+00 0.61687686E+00 0.61501342E+00 - 0.61315514E+00 0.61130202E+00 0.60945404E+00 0.60761117E+00 0.60577340E+00 - 0.60394072E+00 0.60211311E+00 0.60029056E+00 0.59847304E+00 0.59666054E+00 - 0.59485305E+00 0.59305055E+00 0.59125302E+00 0.58946045E+00 0.58767282E+00 - 0.58589012E+00 0.58411233E+00 0.58233943E+00 0.58057142E+00 0.57880826E+00 - 0.57704996E+00 0.57529650E+00 0.57354785E+00 0.57180401E+00 0.57006495E+00 - 0.56833068E+00 0.56660116E+00 0.56487638E+00 0.56315634E+00 0.56144101E+00 - 0.55973038E+00 0.55802444E+00 0.55632318E+00 0.55462657E+00 0.55293460E+00 - 0.55124727E+00 0.54956455E+00 0.54788643E+00 0.54621290E+00 0.54454394E+00 - 0.54287954E+00 0.54121969E+00 0.53956437E+00 0.53791357E+00 0.53626727E+00 - 0.53462547E+00 0.53298814E+00 0.53135528E+00 0.52972687E+00 0.52810289E+00 - 0.52648334E+00 0.52486821E+00 0.52325747E+00 0.52165111E+00 0.52004913E+00 - 0.51845151E+00 0.51685823E+00 0.51526929E+00 0.51368467E+00 0.51210436E+00 - 0.51052834E+00 0.50895661E+00 0.50738914E+00 0.50582594E+00 0.50426698E+00 - 0.50271225E+00 0.50116175E+00 0.49961545E+00 0.49807335E+00 0.49653543E+00 - 0.49500169E+00 0.49347210E+00 0.49194667E+00 0.49042537E+00 0.48890819E+00 - 0.48739513E+00 0.48588617E+00 0.48438129E+00 0.48288050E+00 0.48138377E+00 - 0.47989109E+00 0.47840246E+00 0.47691786E+00 0.47543727E+00 0.47396070E+00 - 0.47248812E+00 0.47101953E+00 0.46955492E+00 0.46809426E+00 0.46663756E+00 - 0.46518480E+00 0.46373597E+00 0.46229106E+00 0.46085006E+00 0.45941295E+00 - 0.45797973E+00 0.45655039E+00 0.45512491E+00 0.45370329E+00 0.45228551E+00 - 0.45087156E+00 0.44946143E+00 0.44805512E+00 0.44665261E+00 0.44525388E+00 - 0.44385894E+00 0.44246777E+00 0.44108036E+00 0.43969670E+00 0.43831677E+00 - 0.43694058E+00 0.43556810E+00 0.43419933E+00 0.43283427E+00 0.43147289E+00 - 0.43011518E+00 0.42876115E+00 0.42741078E+00 0.42606405E+00 0.42472096E+00 - 0.42338151E+00 0.42204567E+00 0.42071344E+00 0.41938481E+00 0.41805978E+00 - 0.41673832E+00 0.41542043E+00 0.41410611E+00 0.41279534E+00 0.41148811E+00 - 0.41018442E+00 0.40888424E+00 0.40758759E+00 0.40629444E+00 0.40500478E+00 - 0.40371862E+00 0.40243593E+00 0.40115670E+00 0.39988094E+00 0.39860863E+00 - 0.39733976E+00 0.39607432E+00 0.39481231E+00 0.39355371E+00 0.39229851E+00 - 0.39104671E+00 0.38979830E+00 0.38855327E+00 0.38731161E+00 0.38607331E+00 - 0.38483837E+00 0.38360676E+00 0.38237849E+00 0.38115355E+00 0.37993193E+00 - 0.37871362E+00 0.37749861E+00 0.37628689E+00 0.37507845E+00 0.37387329E+00 - 0.37267140E+00 0.37147277E+00 0.37027739E+00 0.36908525E+00 0.36789634E+00 - 0.36671066E+00 0.36552820E+00 0.36434895E+00 0.36317290E+00 0.36200004E+00 - 0.36083037E+00 0.35966387E+00 0.35850054E+00 0.35734038E+00 0.35618337E+00 - 0.35502950E+00 0.35387877E+00 0.35273117E+00 0.35158669E+00 0.35044532E+00 - 0.34930706E+00 0.34817190E+00 0.34703983E+00 0.34591084E+00 0.34478493E+00 - 0.34366208E+00 0.34254229E+00 0.34142556E+00 0.34031186E+00 0.33920121E+00 - 0.33809358E+00 0.33698898E+00 0.33588739E+00 0.33478881E+00 0.33369323E+00 - 0.33260063E+00 0.33151103E+00 0.33042440E+00 0.32934074E+00 0.32826004E+00 - 0.32718230E+00 0.32610750E+00 0.32503565E+00 0.32396673E+00 0.32290073E+00 - 0.32183766E+00 0.32077750E+00 0.31972024E+00 0.31866588E+00 0.31761441E+00 - 0.31656582E+00 0.31552011E+00 0.31447727E+00 0.31343730E+00 0.31240018E+00 - 0.31136590E+00 0.31033447E+00 0.30930588E+00 0.30828011E+00 0.30725716E+00 - 0.30623703E+00 0.30521971E+00 0.30420518E+00 0.30319345E+00 0.30218451E+00 - 0.30117835E+00 0.30017496E+00 0.29917434E+00 0.29817648E+00 0.29718137E+00 - 0.29618901E+00 0.29519940E+00 0.29421251E+00 0.29322835E+00 0.29224692E+00 - 0.29126820E+00 0.29029219E+00 0.28931887E+00 0.28834826E+00 0.28738033E+00 - 0.28641509E+00 0.28545252E+00 0.28449262E+00 0.28353538E+00 0.28258080E+00 - 0.28162887E+00 0.28067959E+00 0.27973294E+00 0.27878892E+00 0.27784753E+00 - 0.27690876E+00 0.27597260E+00 0.27503905E+00 0.27410810E+00 0.27317975E+00 - 0.27225398E+00 0.27133079E+00 0.27041018E+00 0.26949215E+00 0.26857667E+00 - 0.26766375E+00 0.26675339E+00 0.26584557E+00 0.26494029E+00 0.26403754E+00 - 0.26313733E+00 0.26223963E+00 0.26134445E+00 0.26045178E+00 0.25956162E+00 - 0.25867395E+00 0.25778878E+00 0.25690609E+00 0.25602588E+00 0.25514815E+00 - 0.25427289E+00 0.25340009E+00 0.25252975E+00 0.25166186E+00 0.25079642E+00 - 0.24993342E+00 0.24907285E+00 0.24821472E+00 0.24735900E+00 0.24650571E+00 - 0.24565482E+00 0.24480635E+00 0.24396027E+00 0.24311659E+00 0.24227530E+00 - 0.24143639E+00 0.24059986E+00 0.23976571E+00 0.23893392E+00 0.23810450E+00 - 0.23727743E+00 0.23645271E+00 0.23563034E+00 0.23481031E+00 0.23399261E+00 - 0.23317725E+00 0.23236420E+00 0.23155348E+00 0.23074507E+00 0.22993897E+00 - 0.22913517E+00 0.22833366E+00 0.22753445E+00 0.22673753E+00 0.22594288E+00 - 0.22515052E+00 0.22436042E+00 0.22357259E+00 0.22278702E+00 0.22200370E+00 - 0.22122264E+00 0.22044381E+00 0.21966723E+00 0.21889288E+00 0.21812077E+00 - 0.21735087E+00 0.21658319E+00 0.21581773E+00 0.21505448E+00 0.21429343E+00 - 0.21353458E+00 0.21277792E+00 0.21202345E+00 0.21127116E+00 0.21052105E+00 - 0.20977311E+00 0.20902734E+00 0.20828374E+00 0.20754229E+00 0.20680300E+00 - 0.20606585E+00 0.20533085E+00 0.20459798E+00 0.20386725E+00 0.20313865E+00 - 0.20241217E+00 0.20168781E+00 0.20096556E+00 0.20024542E+00 0.19952738E+00 - 0.19881145E+00 0.19809761E+00 0.19738585E+00 0.19667619E+00 0.19596860E+00 - 0.19526308E+00 0.19455964E+00 0.19385826E+00 0.19315894E+00 0.19246168E+00 - 0.19176647E+00 0.19107331E+00 0.19038219E+00 0.18969310E+00 0.18900605E+00 - 0.18832102E+00 0.18763802E+00 0.18695703E+00 0.18627806E+00 0.18560110E+00 - 0.18492614E+00 0.18425318E+00 0.18358222E+00 0.18291324E+00 0.18224625E+00 - 0.18158125E+00 0.18091822E+00 0.18025716E+00 0.17959807E+00 0.17894094E+00 - 0.17828577E+00 0.17763255E+00 0.17698128E+00 0.17633196E+00 0.17568458E+00 - 0.17503913E+00 0.17439562E+00 0.17375403E+00 0.17311436E+00 0.17247662E+00 - 0.17184078E+00 0.17120685E+00 0.17057483E+00 0.16994471E+00 0.16931649E+00 - 0.16869015E+00 0.16806570E+00 0.16744314E+00 0.16682245E+00 0.16620364E+00 - 0.16558669E+00 0.16497162E+00 0.16435840E+00 0.16374704E+00 0.16313753E+00 - 0.16252986E+00 0.16192405E+00 0.16132007E+00 0.16071792E+00 0.16011761E+00 - 0.15951912E+00 0.15892245E+00 0.15832760E+00 0.15773457E+00 0.15714334E+00 - 0.15655392E+00 0.15596630E+00 0.15538048E+00 0.15479645E+00 0.15421421E+00 - 0.15363375E+00 0.15305507E+00 0.15247817E+00 0.15190304E+00 0.15132967E+00 - 0.15075807E+00 0.15018823E+00 0.14962015E+00 0.14905381E+00 0.14848922E+00 - 0.14792637E+00 0.14736527E+00 0.14680589E+00 0.14624825E+00 0.14569233E+00 - 0.14513813E+00 0.14458566E+00 0.14403489E+00 0.14348584E+00 0.14293849E+00 - 0.14239285E+00 0.14184890E+00 0.14130665E+00 0.14076608E+00 0.14022721E+00 - 0.13969001E+00 0.13915449E+00 0.13862065E+00 0.13808847E+00 0.13755796E+00 - 0.13702912E+00 0.13650193E+00 0.13597639E+00 0.13545251E+00 0.13493027E+00 - 0.13440968E+00 0.13389072E+00 0.13337340E+00 0.13285770E+00 0.13234364E+00 - 0.13183119E+00 0.13132037E+00 0.13081116E+00 0.13030356E+00 0.12979757E+00 - 0.12929319E+00 0.12879040E+00 0.12828921E+00 0.12778961E+00 0.12729160E+00 - 0.12679517E+00 0.12630032E+00 0.12580705E+00 0.12531536E+00 0.12482523E+00 - 0.12433667E+00 0.12384966E+00 0.12336422E+00 0.12288033E+00 0.12239799E+00 - 0.12191720E+00 0.12143795E+00 0.12096024E+00 0.12048406E+00 0.12000942E+00 - 0.11953630E+00 0.11906471E+00 0.11859464E+00 0.11812608E+00 0.11765904E+00 - 0.11719351E+00 0.11672948E+00 0.11626696E+00 0.11580593E+00 0.11534640E+00 - 0.11488836E+00 0.11443180E+00 0.11397673E+00 0.11352314E+00 0.11307103E+00 - 0.11262039E+00 0.11217122E+00 0.11172351E+00 0.11127727E+00 0.11083248E+00 - 0.11038915E+00 0.10994727E+00 0.10950684E+00 0.10906785E+00 0.10863030E+00 - 0.10819419E+00 0.10775951E+00 0.10732627E+00 0.10689444E+00 0.10646405E+00 - 0.10603507E+00 0.10560750E+00 0.10518135E+00 0.10475661E+00 0.10433327E+00 - 0.10391133E+00 0.10349079E+00 0.10307165E+00 0.10265390E+00 0.10223753E+00 - 0.10182255E+00 0.10140895E+00 0.10099673E+00 0.10058588E+00 0.10017640E+00 - 0.99768284E-01 0.99361534E-01 0.98956145E-01 0.98552112E-01 0.98149433E-01 - 0.97748103E-01 0.97348119E-01 0.96949478E-01 0.96552176E-01 0.96156211E-01 - 0.95761578E-01 0.95368274E-01 0.94976297E-01 0.94585641E-01 0.94196305E-01 - 0.93808285E-01 0.93421577E-01 0.93036178E-01 0.92652085E-01 0.92269294E-01 - 0.91887802E-01 0.91507606E-01 0.91128702E-01 0.90751087E-01 0.90374758E-01 - 0.89999711E-01 0.89625944E-01 0.89253452E-01 0.88882232E-01 0.88512282E-01 - 0.88143598E-01 0.87776176E-01 0.87410014E-01 0.87045107E-01 0.86681454E-01 - 0.86319050E-01 0.85957892E-01 0.85597977E-01 0.85239303E-01 0.84881864E-01 - 0.84525659E-01 0.84170684E-01 0.83816936E-01 0.83464411E-01 0.83113107E-01 - 0.82763020E-01 0.82414147E-01 0.82066485E-01 0.81720031E-01 0.81374781E-01 - 0.81030732E-01 0.80687881E-01 0.80346224E-01 0.80005760E-01 0.79666484E-01 - 0.79328393E-01 0.78991485E-01 0.78655755E-01 0.78321202E-01 0.77987821E-01 - 0.77655610E-01 0.77324565E-01 0.76994684E-01 0.76665962E-01 0.76338398E-01 - 0.76011988E-01 0.75686728E-01 0.75362616E-01 0.75039649E-01 0.74717824E-01 - 0.74397137E-01 0.74077585E-01 0.73759165E-01 0.73441875E-01 0.73125710E-01 - 0.72810669E-01 0.72496748E-01 0.72183943E-01 0.71872253E-01 0.71561673E-01 - 0.71252200E-01 0.70943833E-01 0.70636567E-01 0.70330400E-01 0.70025328E-01 - 0.69721348E-01 0.69418459E-01 0.69116655E-01 0.68815935E-01 0.68516296E-01 - 0.68217734E-01 0.67920246E-01 0.67623830E-01 0.67328482E-01 0.67034199E-01 - 0.66740979E-01 0.66448819E-01 0.66157715E-01 0.65867664E-01 0.65578664E-01 - 0.65290711E-01 0.65003803E-01 0.64717937E-01 0.64433109E-01 0.64149316E-01 - 0.63866557E-01 0.63584827E-01 0.63304124E-01 0.63024445E-01 0.62745787E-01 - 0.62468147E-01 0.62191522E-01 0.61915909E-01 0.61641305E-01 0.61367708E-01 - 0.61095113E-01 0.60823520E-01 0.60552924E-01 0.60283322E-01 0.60014712E-01 - 0.59747092E-01 0.59480457E-01 0.59214805E-01 0.58950133E-01 0.58686438E-01 - 0.58423718E-01 0.58161969E-01 0.57901189E-01 0.57641374E-01 0.57382522E-01 - 0.57124630E-01 0.56867696E-01 0.56611715E-01 0.56356686E-01 0.56102605E-01 - 0.55849470E-01 0.55597278E-01 0.55346025E-01 0.55095710E-01 0.54846329E-01 - 0.54597879E-01 0.54350358E-01 0.54103762E-01 0.53858089E-01 0.53613336E-01 - 0.53369501E-01 0.53126579E-01 0.52884569E-01 0.52643468E-01 0.52403272E-01 - 0.52163980E-01 0.51925587E-01 0.51688092E-01 0.51451491E-01 0.51215782E-01 - 0.50980962E-01 0.50747028E-01 0.50513978E-01 0.50281807E-01 0.50050514E-01 - 0.49820096E-01 0.49590550E-01 0.49361873E-01 0.49134063E-01 0.48907116E-01 - 0.48681029E-01 0.48455801E-01 0.48231428E-01 0.48007907E-01 0.47785235E-01 - 0.47563411E-01 0.47342430E-01 0.47122290E-01 0.46902989E-01 0.46684523E-01 - 0.46466889E-01 0.46250086E-01 0.46034110E-01 0.45818958E-01 0.45604627E-01 - 0.45391115E-01 0.45178419E-01 0.44966536E-01 0.44755463E-01 0.44545198E-01 - 0.44335737E-01 0.44127079E-01 0.43919219E-01 0.43712156E-01 0.43505885E-01 - 0.43300406E-01 0.43095714E-01 0.42891808E-01 0.42688683E-01 0.42486338E-01 - 0.42284770E-01 0.42083975E-01 0.41883951E-01 0.41684695E-01 0.41486204E-01 - 0.41288476E-01 0.41091508E-01 0.40895296E-01 0.40699838E-01 0.40505131E-01 - 0.40311173E-01 0.40117960E-01 0.39925489E-01 0.39733759E-01 0.39542765E-01 - 0.39352505E-01 0.39162977E-01 0.38974176E-01 0.38786102E-01 0.38598750E-01 - 0.38412117E-01 0.38226201E-01 0.38041000E-01 0.37856509E-01 0.37672727E-01 - 0.37489650E-01 0.37307275E-01 0.37125600E-01 0.36944621E-01 0.36764336E-01 - 0.36584742E-01 0.36405836E-01 0.36227615E-01 0.36050075E-01 0.35873215E-01 - 0.35697031E-01 0.35521519E-01 0.35346679E-01 0.35172505E-01 0.34998995E-01 - 0.34826147E-01 0.34653957E-01 0.34482423E-01 0.34311540E-01 0.34141307E-01 - 0.33971720E-01 0.33802777E-01 0.33634473E-01 0.33466807E-01 0.33299775E-01 - 0.33133374E-01 0.32967601E-01 0.32802453E-01 0.32637927E-01 0.32474019E-01 - 0.32310727E-01 0.32148048E-01 0.31985978E-01 0.31824514E-01 0.31663654E-01 - 0.31503394E-01 0.31343730E-01 0.31184660E-01 0.31026180E-01 0.30868288E-01 - 0.30710980E-01 0.30554252E-01 0.30398103E-01 0.30242527E-01 0.30087523E-01 - 0.29933086E-01 0.29779215E-01 0.29625904E-01 0.29473151E-01 0.29320953E-01 - 0.29169307E-01 0.29018208E-01 0.28867654E-01 0.28717641E-01 0.28568166E-01 - 0.28419225E-01 0.28270816E-01 0.28122934E-01 0.27975576E-01 0.27828739E-01 - 0.27682419E-01 0.27536612E-01 0.27391316E-01 0.27246527E-01 0.27102240E-01 - 0.26958454E-01 0.26815163E-01 0.26672364E-01 0.26530055E-01 0.26388230E-01 - 0.26246887E-01 0.26106022E-01 0.25965631E-01 0.25825710E-01 0.25686256E-01 - 0.25547265E-01 0.25408734E-01 0.25270657E-01 0.25133033E-01 0.24995856E-01 - 0.24859124E-01 0.24722831E-01 0.24586975E-01 0.24451551E-01 0.24316556E-01 - 0.24181985E-01 0.24047835E-01 0.23914101E-01 0.23780781E-01 0.23647868E-01 - 0.23515361E-01 0.23383254E-01 0.23251543E-01 0.23120225E-01 0.22989295E-01 - 0.22858750E-01 0.22728584E-01 0.22598794E-01 0.22469375E-01 0.22340324E-01 - 0.22211637E-01 0.22083308E-01 0.21955333E-01 0.21827709E-01 0.21700431E-01 - 0.21573495E-01 0.21446895E-01 0.21320629E-01 0.21194691E-01 0.21069078E-01 - 0.20943783E-01 0.20818805E-01 0.20694136E-01 0.20569774E-01 0.20445714E-01 - 0.20321950E-01 0.20198480E-01 0.20075297E-01 0.19952398E-01 0.19829777E-01 - 0.19707431E-01 0.19585354E-01 0.19463542E-01 0.19341991E-01 0.19220695E-01 - 0.19099649E-01 0.18978850E-01 0.18858293E-01 0.18737972E-01 0.18617883E-01 - 0.18498022E-01 0.18378383E-01 0.18258961E-01 0.18139753E-01 0.18020753E-01 - 0.17901956E-01 0.17783358E-01 0.17664954E-01 0.17546739E-01 0.17428708E-01 - 0.17310857E-01 0.17193181E-01 0.17075674E-01 0.16958333E-01 0.16841152E-01 - 0.16724128E-01 0.16607254E-01 0.16490526E-01 0.16373940E-01 0.16257491E-01 - 0.16141175E-01 0.16024986E-01 0.15908920E-01 0.15792973E-01 0.15677139E-01 - 0.15561415E-01 0.15445796E-01 0.15330277E-01 0.15214855E-01 0.15099524E-01 - 0.14984281E-01 0.14869121E-01 0.14754040E-01 0.14639033E-01 0.14524098E-01 - 0.14409229E-01 0.14294423E-01 0.14179675E-01 0.14064983E-01 0.13950342E-01 - 0.13835749E-01 0.13721200E-01 0.13606691E-01 0.13492220E-01 0.13377783E-01 - 0.13263377E-01 0.13148999E-01 0.13034645E-01 0.12920314E-01 0.12806002E-01 - 0.12691707E-01 0.12577427E-01 0.12463159E-01 0.12348901E-01 0.12234651E-01 - 0.12120408E-01 0.12006170E-01 0.11891934E-01 0.11777702E-01 0.11663470E-01 - 0.11549238E-01 0.11435006E-01 0.11320773E-01 0.11206539E-01 0.11092303E-01 - 0.10978067E-01 0.10863830E-01 0.10749594E-01 0.10635358E-01 0.10521125E-01 - 0.10406896E-01 0.10292673E-01 0.10178458E-01 0.10064252E-01 0.99500595E-02 - 0.98358826E-02 0.97217247E-02 0.96075896E-02 0.94934810E-02 0.93794033E-02 - 0.92653613E-02 0.91513598E-02 0.90374042E-02 0.89235004E-02 0.88096544E-02 - 0.86958728E-02 0.85821624E-02 0.84685307E-02 0.83549854E-02 0.82415346E-02 - 0.81281869E-02 0.80149514E-02 0.79018375E-02 0.77888552E-02 0.76760147E-02 - 0.75633269E-02 0.74508032E-02 0.73384551E-02 0.72262950E-02 0.71143356E-02 - 0.70025900E-02 0.68910718E-02 0.67797951E-02 0.66687747E-02 0.65580255E-02 - 0.64475632E-02 0.63374037E-02 0.62275637E-02 0.61180601E-02 0.60089104E-02 - 0.59001325E-02 0.57917450E-02 0.56837666E-02 0.55762167E-02 0.54691150E-02 - 0.53624818E-02 0.52563377E-02 0.51507037E-02 0.50456012E-02 0.49410522E-02 - 0.48370787E-02 0.47337034E-02 0.46309490E-02 0.45288389E-02 0.44273965E-02 - 0.43266456E-02 0.42266102E-02 0.41273145E-02 0.40287831E-02 0.39310405E-02 - 0.38341115E-02 0.37380209E-02 0.36427938E-02 0.35484552E-02 0.34550300E-02 - 0.33625433E-02 0.32710200E-02 0.31804850E-02 0.30909630E-02 0.30024784E-02 - 0.29150556E-02 0.28287187E-02 0.27434913E-02 0.26593968E-02 0.25764583E-02 - 0.24946981E-02 0.24141385E-02 0.23348007E-02 0.22567058E-02 0.21798740E-02 - 0.21043248E-02 0.20300771E-02 0.19571488E-02 0.18855573E-02 0.18153187E-02 - 0.17464486E-02 0.16789612E-02 0.16128700E-02 0.15481872E-02 0.14849241E-02 - 0.14230907E-02 0.13626959E-02 0.13037472E-02 0.12462511E-02 0.11902126E-02 - 0.11356355E-02 0.10825221E-02 0.10308734E-02 0.98068902E-03 0.93196716E-03 - 0.88470455E-03 0.83889650E-03 0.79453686E-03 0.75161805E-03 0.71013100E-03 - 0.67006525E-03 0.63140884E-03 0.59414845E-03 0.55826932E-03 0.52375533E-03 - 0.49058900E-03 0.45875154E-03 0.42822289E-03 0.39898174E-03 0.37100558E-03 - 0.34427076E-03 0.31875257E-03 0.29442524E-03 0.27126203E-03 0.24923532E-03 - 0.22831664E-03 0.20847675E-03 0.18968573E-03 0.17191305E-03 0.15512763E-03 - 0.13929797E-03 0.12439214E-03 0.11037798E-03 0.97223073E-04 0.84894904E-04 - 0.73360904E-04 0.62588545E-04 0.52545417E-04 0.43199310E-04 0.34518285E-04 - 0.26470755E-04 0.19025555E-04 0.12152007E-04 0.58199898E-05 0.00000000E+00 - 0.12471708E+03 0.12471708E+03 0.12471708E+03 0.12471708E+03 0.12471708E+03 - 0.12471708E+03 0.12471708E+03 0.12471708E+03 0.12471708E+03 0.12471708E+03 - 0.12471708E+03 0.12471708E+03 0.12471708E+03 0.12471708E+03 0.12471708E+03 - 0.12471708E+03 0.12471708E+03 0.12471708E+03 0.12471708E+03 0.12471708E+03 - 0.12471708E+03 0.12471708E+03 0.12471708E+03 0.12471708E+03 0.12471708E+03 - 0.12471708E+03 0.12471708E+03 0.12471708E+03 0.12471708E+03 0.12471708E+03 - 0.12471708E+03 0.12471708E+03 0.12471708E+03 0.12471708E+03 0.12471708E+03 - 0.12471708E+03 0.12471708E+03 0.12471708E+03 0.12471708E+03 0.12471708E+03 - 0.12471708E+03 0.12471708E+03 0.12471708E+03 0.12471708E+03 0.12471708E+03 - 0.12457030E+03 0.12126502E+03 0.11811569E+03 0.11511188E+03 0.11224403E+03 - 0.10950339E+03 0.10688194E+03 0.10437232E+03 0.10196773E+03 0.99661915E+02 - 0.97449101E+02 0.95323945E+02 0.93281498E+02 0.91317174E+02 0.89426712E+02 - 0.87606152E+02 0.85851807E+02 0.84160239E+02 0.82528243E+02 0.80952825E+02 - 0.79431181E+02 0.77960692E+02 0.76538900E+02 0.75163499E+02 0.73832327E+02 - 0.72543350E+02 0.71294656E+02 0.70084442E+02 0.68911014E+02 0.67772771E+02 - 0.66668202E+02 0.65595882E+02 0.64554463E+02 0.63542669E+02 0.62559294E+02 - 0.61603192E+02 0.60673282E+02 0.59768534E+02 0.58887973E+02 0.58030671E+02 - 0.57195747E+02 0.56382365E+02 0.55589726E+02 0.54817071E+02 0.54063679E+02 - 0.53328859E+02 0.52611954E+02 0.51912338E+02 0.51229412E+02 0.50562604E+02 - 0.49911368E+02 0.49275181E+02 0.48653545E+02 0.48045980E+02 0.47452029E+02 - 0.46871254E+02 0.46303235E+02 0.45747568E+02 0.45203868E+02 0.44671764E+02 - 0.44150901E+02 0.43640936E+02 0.43141542E+02 0.42652404E+02 0.42173218E+02 - 0.41703693E+02 0.41243549E+02 0.40792516E+02 0.40350334E+02 0.39916754E+02 - 0.39491534E+02 0.39074441E+02 0.38665254E+02 0.38263755E+02 0.37869736E+02 - 0.37482997E+02 0.37103343E+02 0.36730589E+02 0.36364552E+02 0.36005059E+02 - 0.35651941E+02 0.35305035E+02 0.34964183E+02 0.34629233E+02 0.34300037E+02 - 0.33976454E+02 0.33658344E+02 0.33345574E+02 0.33038016E+02 0.32735543E+02 - 0.32438034E+02 0.32145371E+02 0.31857442E+02 0.31574134E+02 0.31295341E+02 - 0.31020960E+02 0.30750888E+02 0.30485029E+02 0.30223288E+02 0.29965571E+02 - 0.29711791E+02 0.29461860E+02 0.29215693E+02 0.28973209E+02 0.28734328E+02 - 0.28498972E+02 0.28267067E+02 0.28038539E+02 0.27813317E+02 0.27591332E+02 - 0.27372516E+02 0.27156805E+02 0.26944133E+02 0.26734440E+02 0.26527665E+02 - 0.26323749E+02 0.26122635E+02 0.25924267E+02 0.25728591E+02 0.25535554E+02 - 0.25345104E+02 0.25157191E+02 0.24971767E+02 0.24788782E+02 0.24608192E+02 - 0.24429950E+02 0.24254012E+02 0.24080335E+02 0.23908877E+02 0.23739597E+02 - 0.23572454E+02 0.23407410E+02 0.23244426E+02 0.23083465E+02 0.22924490E+02 - 0.22767466E+02 0.22612359E+02 0.22459133E+02 0.22307756E+02 0.22158196E+02 - 0.22010421E+02 0.21864400E+02 0.21720103E+02 0.21577500E+02 0.21436562E+02 - 0.21297261E+02 0.21159569E+02 0.21023460E+02 0.20888906E+02 0.20755883E+02 - 0.20624364E+02 0.20494325E+02 0.20365742E+02 0.20238591E+02 0.20112849E+02 - 0.19988492E+02 0.19865500E+02 0.19743850E+02 0.19623520E+02 0.19504490E+02 - 0.19386739E+02 0.19270248E+02 0.19154996E+02 0.19040965E+02 0.18928136E+02 - 0.18816490E+02 0.18706008E+02 0.18596674E+02 0.18488471E+02 0.18381380E+02 - 0.18275385E+02 0.18170470E+02 0.18066619E+02 0.17963816E+02 0.17862045E+02 - 0.17761292E+02 0.17661542E+02 0.17562779E+02 0.17464991E+02 0.17368162E+02 - 0.17272279E+02 0.17177328E+02 0.17083297E+02 0.16990171E+02 0.16897939E+02 - 0.16806588E+02 0.16716106E+02 0.16626480E+02 0.16537698E+02 0.16449749E+02 - 0.16362622E+02 0.16276305E+02 0.16190788E+02 0.16106059E+02 0.16022107E+02 - 0.15938923E+02 0.15856495E+02 0.15774815E+02 0.15693872E+02 0.15613655E+02 - 0.15534157E+02 0.15455367E+02 0.15377275E+02 0.15299874E+02 0.15223153E+02 - 0.15147104E+02 0.15071719E+02 0.14996989E+02 0.14922905E+02 0.14849460E+02 - 0.14776645E+02 0.14704453E+02 0.14632875E+02 0.14561904E+02 0.14491532E+02 - 0.14421752E+02 0.14352556E+02 0.14283938E+02 0.14215890E+02 0.14148405E+02 - 0.14081476E+02 0.14015097E+02 0.13949261E+02 0.13883961E+02 0.13819192E+02 - 0.13754946E+02 0.13691217E+02 0.13628000E+02 0.13565287E+02 0.13503074E+02 - 0.13441355E+02 0.13380122E+02 0.13319372E+02 0.13259098E+02 0.13199295E+02 - 0.13139957E+02 0.13081079E+02 0.13022656E+02 0.12964683E+02 0.12907154E+02 - 0.12850064E+02 0.12793408E+02 0.12737182E+02 0.12681381E+02 0.12626000E+02 - 0.12571034E+02 0.12516479E+02 0.12462330E+02 0.12408582E+02 0.12355232E+02 - 0.12302274E+02 0.12249705E+02 0.12197520E+02 0.12145716E+02 0.12094288E+02 - 0.12043231E+02 0.11992543E+02 0.11942218E+02 0.11892254E+02 0.11842646E+02 - 0.11793391E+02 0.11744485E+02 0.11695924E+02 0.11647704E+02 0.11599822E+02 - 0.11552275E+02 0.11505059E+02 0.11458170E+02 0.11411606E+02 0.11365362E+02 - 0.11319436E+02 0.11273824E+02 0.11228523E+02 0.11183530E+02 0.11138842E+02 - 0.11094455E+02 0.11050367E+02 0.11006575E+02 0.10963076E+02 0.10919866E+02 - 0.10876943E+02 0.10834305E+02 0.10791947E+02 0.10749868E+02 0.10708065E+02 - 0.10666535E+02 0.10625275E+02 0.10584282E+02 0.10543555E+02 0.10503091E+02 - 0.10462886E+02 0.10422939E+02 0.10383247E+02 0.10343808E+02 0.10304619E+02 - 0.10265678E+02 0.10226982E+02 0.10188529E+02 0.10150317E+02 0.10112344E+02 - 0.10074607E+02 0.10037104E+02 0.99998327E+01 0.99627915E+01 0.99259780E+01 - 0.98893900E+01 0.98530255E+01 0.98168824E+01 0.97809587E+01 0.97452523E+01 - 0.97097614E+01 0.96744839E+01 0.96394179E+01 0.96045615E+01 0.95699128E+01 - 0.95354700E+01 0.95012311E+01 0.94671944E+01 0.94333580E+01 0.93997202E+01 - 0.93662793E+01 0.93330334E+01 0.92999809E+01 0.92671201E+01 0.92344492E+01 - 0.92019666E+01 0.91696707E+01 0.91375599E+01 0.91056324E+01 0.90738869E+01 - 0.90423216E+01 0.90109351E+01 0.89797257E+01 0.89486920E+01 0.89178325E+01 - 0.88871457E+01 0.88566301E+01 0.88262843E+01 0.87961069E+01 0.87660963E+01 - 0.87362513E+01 0.87065704E+01 0.86770523E+01 0.86476955E+01 0.86184988E+01 - 0.85894609E+01 0.85605803E+01 0.85318558E+01 0.85032862E+01 0.84748702E+01 - 0.84466064E+01 0.84184937E+01 0.83905308E+01 0.83627164E+01 0.83350495E+01 - 0.83075288E+01 0.82801531E+01 0.82529213E+01 0.82258321E+01 0.81988845E+01 - 0.81720773E+01 0.81454095E+01 0.81188798E+01 0.80924872E+01 0.80662306E+01 - 0.80401090E+01 0.80141212E+01 0.79882663E+01 0.79625431E+01 0.79369507E+01 - 0.79114880E+01 0.78861541E+01 0.78609478E+01 0.78358683E+01 0.78109146E+01 - 0.77860856E+01 0.77613805E+01 0.77367982E+01 0.77123379E+01 0.76879986E+01 - 0.76637793E+01 0.76396793E+01 0.76156975E+01 0.75918330E+01 0.75680851E+01 - 0.75444528E+01 0.75209352E+01 0.74975315E+01 0.74742408E+01 0.74510623E+01 - 0.74279952E+01 0.74050385E+01 0.73821916E+01 0.73594536E+01 0.73368237E+01 - 0.73143011E+01 0.72918850E+01 0.72695747E+01 0.72473693E+01 0.72252681E+01 - 0.72032703E+01 0.71813753E+01 0.71595821E+01 0.71378902E+01 0.71162988E+01 - 0.70948071E+01 0.70734145E+01 0.70521202E+01 0.70309235E+01 0.70098238E+01 - 0.69888203E+01 0.69679124E+01 0.69470993E+01 0.69263805E+01 0.69057552E+01 - 0.68852229E+01 0.68647828E+01 0.68444342E+01 0.68241767E+01 0.68040094E+01 - 0.67839319E+01 0.67639434E+01 0.67440434E+01 0.67242313E+01 0.67045064E+01 - 0.66848681E+01 0.66653159E+01 0.66458492E+01 0.66264673E+01 0.66071697E+01 - 0.65879558E+01 0.65688251E+01 0.65497770E+01 0.65308109E+01 0.65119264E+01 - 0.64931227E+01 0.64743994E+01 0.64557560E+01 0.64371919E+01 0.64187066E+01 - 0.64002995E+01 0.63819702E+01 0.63637181E+01 0.63455428E+01 0.63274436E+01 - 0.63094201E+01 0.62914719E+01 0.62735984E+01 0.62557991E+01 0.62380735E+01 - 0.62204213E+01 0.62028418E+01 0.61853346E+01 0.61678992E+01 0.61505353E+01 - 0.61332422E+01 0.61160197E+01 0.60988671E+01 0.60817841E+01 0.60647702E+01 - 0.60478250E+01 0.60309480E+01 0.60141389E+01 0.59973971E+01 0.59807222E+01 - 0.59641139E+01 0.59475717E+01 0.59310952E+01 0.59146840E+01 0.58983376E+01 - 0.58820557E+01 0.58658378E+01 0.58496837E+01 0.58335927E+01 0.58175647E+01 - 0.58015991E+01 0.57856957E+01 0.57698539E+01 0.57540735E+01 0.57383541E+01 - 0.57226952E+01 0.57070965E+01 0.56915577E+01 0.56760784E+01 0.56606582E+01 - 0.56452968E+01 0.56299938E+01 0.56147488E+01 0.55995615E+01 0.55844316E+01 - 0.55693587E+01 0.55543425E+01 0.55393826E+01 0.55244787E+01 0.55096305E+01 - 0.54948376E+01 0.54800997E+01 0.54654165E+01 0.54507876E+01 0.54362128E+01 - 0.54216916E+01 0.54072239E+01 0.53928093E+01 0.53784475E+01 0.53641381E+01 - 0.53498809E+01 0.53356755E+01 0.53215217E+01 0.53074192E+01 0.52933676E+01 - 0.52793667E+01 0.52654161E+01 0.52515157E+01 0.52376650E+01 0.52238639E+01 - 0.52101120E+01 0.51964091E+01 0.51827548E+01 0.51691489E+01 0.51555912E+01 - 0.51420813E+01 0.51286190E+01 0.51152039E+01 0.51018360E+01 0.50885148E+01 - 0.50752401E+01 0.50620117E+01 0.50488293E+01 0.50356926E+01 0.50226015E+01 - 0.50095555E+01 0.49965546E+01 0.49835984E+01 0.49706867E+01 0.49578192E+01 - 0.49449957E+01 0.49322160E+01 0.49194798E+01 0.49067869E+01 0.48941371E+01 - 0.48815300E+01 0.48689656E+01 0.48564435E+01 0.48439635E+01 0.48315254E+01 - 0.48191290E+01 0.48067740E+01 0.47944603E+01 0.47821875E+01 0.47699556E+01 - 0.47577642E+01 0.47456131E+01 0.47335022E+01 0.47214312E+01 0.47093999E+01 - 0.46974081E+01 0.46854556E+01 0.46735422E+01 0.46616676E+01 0.46498318E+01 - 0.46380344E+01 0.46262752E+01 0.46145542E+01 0.46028710E+01 0.45912255E+01 - 0.45796175E+01 0.45680467E+01 0.45565131E+01 0.45450164E+01 0.45335563E+01 - 0.45221328E+01 0.45107457E+01 0.44993947E+01 0.44880796E+01 0.44768003E+01 - 0.44655567E+01 0.44543484E+01 0.44431754E+01 0.44320375E+01 0.44209344E+01 - 0.44098661E+01 0.43988323E+01 0.43878329E+01 0.43768676E+01 0.43659364E+01 - 0.43550390E+01 0.43441753E+01 0.43333451E+01 0.43225482E+01 0.43117846E+01 - 0.43010539E+01 0.42903561E+01 0.42796910E+01 0.42690585E+01 0.42584583E+01 - 0.42478903E+01 0.42373544E+01 0.42268503E+01 0.42163781E+01 0.42059374E+01 - 0.41955281E+01 0.41851502E+01 0.41748034E+01 0.41644875E+01 0.41542025E+01 - 0.41439482E+01 0.41337244E+01 0.41235310E+01 0.41133679E+01 0.41032349E+01 - 0.40931318E+01 0.40830585E+01 0.40730150E+01 0.40630009E+01 0.40530163E+01 - 0.40430609E+01 0.40331347E+01 0.40232374E+01 0.40133690E+01 0.40035293E+01 - 0.39937182E+01 0.39839355E+01 0.39741811E+01 0.39644550E+01 0.39547568E+01 - 0.39450866E+01 0.39354442E+01 0.39258295E+01 0.39162423E+01 0.39066826E+01 - 0.38971501E+01 0.38876447E+01 0.38781665E+01 0.38687151E+01 0.38592905E+01 - 0.38498926E+01 0.38405213E+01 0.38311764E+01 0.38218578E+01 0.38125654E+01 - 0.38032990E+01 0.37940587E+01 0.37848442E+01 0.37756554E+01 0.37664922E+01 - 0.37573545E+01 0.37482423E+01 0.37391553E+01 0.37300934E+01 0.37210566E+01 - 0.37120448E+01 0.37030578E+01 0.36940955E+01 0.36851578E+01 0.36762446E+01 - 0.36673559E+01 0.36584914E+01 0.36496511E+01 0.36408349E+01 0.36320427E+01 - 0.36232744E+01 0.36145298E+01 0.36058090E+01 0.35971117E+01 0.35884378E+01 - 0.35797873E+01 0.35711601E+01 0.35625561E+01 0.35539751E+01 0.35454172E+01 - 0.35368821E+01 0.35283697E+01 0.35198801E+01 0.35114130E+01 0.35029685E+01 - 0.34945463E+01 0.34861465E+01 0.34777688E+01 0.34694133E+01 0.34610798E+01 - 0.34527683E+01 0.34444786E+01 0.34362106E+01 0.34279644E+01 0.34197397E+01 - 0.34115365E+01 0.34033546E+01 0.33951941E+01 0.33870549E+01 0.33789367E+01 - 0.33708397E+01 0.33627636E+01 0.33547083E+01 0.33466739E+01 0.33386602E+01 - 0.33306671E+01 0.33226946E+01 0.33147425E+01 0.33068108E+01 0.32988995E+01 - 0.32910083E+01 0.32831373E+01 0.32752863E+01 0.32674554E+01 0.32596443E+01 - 0.32518530E+01 0.32440815E+01 0.32363297E+01 0.32285975E+01 0.32208848E+01 - 0.32131915E+01 0.32055176E+01 0.31978629E+01 0.31902275E+01 0.31826112E+01 - 0.31750140E+01 0.31674358E+01 0.31598765E+01 0.31523360E+01 0.31448143E+01 - 0.31373113E+01 0.31298270E+01 0.31223612E+01 0.31149138E+01 0.31074850E+01 - 0.31000744E+01 0.30926821E+01 0.30853081E+01 0.30779521E+01 0.30706143E+01 - 0.30632945E+01 0.30559925E+01 0.30487085E+01 0.30414423E+01 0.30341938E+01 - 0.30269630E+01 0.30197497E+01 0.30125541E+01 0.30053759E+01 0.29982151E+01 - 0.29910717E+01 0.29839455E+01 0.29768366E+01 0.29697448E+01 0.29626701E+01 - 0.29556125E+01 0.29485718E+01 0.29415481E+01 0.29345411E+01 0.29275510E+01 - 0.29205776E+01 0.29136209E+01 0.29066808E+01 0.28997572E+01 0.28928502E+01 - 0.28859595E+01 0.28790852E+01 0.28722273E+01 0.28653856E+01 0.28585601E+01 - 0.28517507E+01 0.28449575E+01 0.28381802E+01 0.28314190E+01 0.28246736E+01 - 0.28179442E+01 0.28112305E+01 0.28045326E+01 0.27978503E+01 0.27911838E+01 - 0.27845328E+01 0.27778973E+01 0.27712773E+01 0.27646728E+01 0.27580836E+01 - 0.27515098E+01 0.27449512E+01 0.27384079E+01 0.27318797E+01 0.27253666E+01 - 0.27188686E+01 0.27123857E+01 0.27059177E+01 0.26994646E+01 0.26930263E+01 - 0.26866029E+01 0.26801943E+01 0.26738003E+01 0.26674211E+01 0.26610564E+01 - 0.26547063E+01 0.26483708E+01 0.26420497E+01 0.26357431E+01 0.26294508E+01 - 0.26231729E+01 0.26169092E+01 0.26106598E+01 0.26044246E+01 0.25982035E+01 - 0.25919966E+01 0.25858037E+01 0.25796248E+01 0.25734599E+01 0.25673089E+01 - 0.25611717E+01 0.25550485E+01 0.25489389E+01 0.25428432E+01 0.25367611E+01 - 0.25306927E+01 0.25246380E+01 0.25185968E+01 0.25125691E+01 0.25065549E+01 - 0.25005541E+01 0.24945668E+01 0.24885928E+01 0.24826321E+01 0.24766848E+01 - 0.24707506E+01 0.24648297E+01 0.24589219E+01 0.24530272E+01 0.24471456E+01 - 0.24412770E+01 0.24354215E+01 0.24295788E+01 0.24237491E+01 0.24179323E+01 - 0.24121283E+01 0.24063372E+01 0.24005587E+01 0.23947930E+01 0.23890400E+01 - 0.23832997E+01 0.23775719E+01 0.23718567E+01 0.23661540E+01 0.23604639E+01 - 0.23547862E+01 0.23491209E+01 0.23434680E+01 0.23378275E+01 0.23321992E+01 - 0.23265833E+01 0.23209796E+01 0.23153881E+01 0.23098087E+01 0.23042415E+01 - 0.22986864E+01 0.22931434E+01 0.22876124E+01 0.22820934E+01 0.22765863E+01 - 0.22710912E+01 0.22656080E+01 0.22601366E+01 0.22546771E+01 0.22492293E+01 - 0.22437933E+01 0.22383691E+01 0.22329565E+01 0.22275556E+01 0.22221663E+01 - 0.22167886E+01 0.22114224E+01 0.22060678E+01 0.22007247E+01 0.21953931E+01 - 0.21900728E+01 0.21847640E+01 0.21794666E+01 0.21741805E+01 0.21689057E+01 - 0.21636422E+01 0.21583899E+01 0.21531488E+01 0.21479190E+01 0.21427002E+01 - 0.21374927E+01 0.21322962E+01 0.21271107E+01 0.21219363E+01 0.21167729E+01 - 0.21116205E+01 0.21064790E+01 0.21013485E+01 0.20962288E+01 0.20911200E+01 - 0.20860220E+01 0.20809348E+01 0.20758584E+01 0.20707928E+01 0.20657378E+01 - 0.20606936E+01 0.20556600E+01 0.20506370E+01 0.20456247E+01 0.20406229E+01 - 0.20356316E+01 0.20306509E+01 0.20256807E+01 0.20207210E+01 0.20157717E+01 - 0.20108328E+01 0.20059043E+01 0.20009862E+01 0.19960784E+01 0.19911809E+01 - 0.19862937E+01 0.19814168E+01 0.19765500E+01 0.19716935E+01 0.19668472E+01 - 0.19620110E+01 0.19571850E+01 0.19523691E+01 0.19475632E+01 0.19427674E+01 - 0.19379816E+01 0.19332058E+01 0.19284401E+01 0.19236842E+01 0.19189383E+01 - 0.19142023E+01 0.19094762E+01 0.19047599E+01 0.19000535E+01 0.18953569E+01 - 0.18906701E+01 0.18859930E+01 0.18813257E+01 0.18766681E+01 0.18720202E+01 - 0.18673819E+01 0.18627533E+01 0.18581343E+01 0.18535250E+01 0.18489252E+01 - 0.18443349E+01 0.18397542E+01 0.18351830E+01 0.18306213E+01 0.18260690E+01 - 0.18215262E+01 0.18169928E+01 0.18124688E+01 0.18079542E+01 0.18034490E+01 - 0.17989531E+01 0.17944665E+01 0.17899891E+01 0.17855211E+01 0.17810623E+01 - 0.17766127E+01 0.17721723E+01 0.17677411E+01 0.17633191E+01 0.17589062E+01 - 0.17545025E+01 0.17501078E+01 0.17457223E+01 0.17413457E+01 0.17369783E+01 - 0.17326198E+01 0.17282703E+01 0.17239299E+01 0.17195984E+01 0.17152758E+01 - 0.17109621E+01 0.17066574E+01 0.17023615E+01 0.16980745E+01 0.16937963E+01 - 0.16895269E+01 0.16852664E+01 0.16810146E+01 0.16767716E+01 0.16725373E+01 - 0.16683118E+01 0.16640950E+01 0.16598868E+01 0.16556873E+01 0.16514965E+01 - 0.16473143E+01 0.16431407E+01 0.16389758E+01 0.16348194E+01 0.16306715E+01 - 0.16265322E+01 0.16224014E+01 0.16182791E+01 0.16141653E+01 0.16100600E+01 - 0.16059631E+01 0.16018747E+01 0.15977946E+01 0.15937230E+01 0.15896597E+01 - 0.15856049E+01 0.15815583E+01 0.15775201E+01 0.15734902E+01 0.15694685E+01 - 0.15654552E+01 0.15614501E+01 0.15574533E+01 0.15534646E+01 0.15494842E+01 - 0.15455120E+01 0.15415480E+01 0.15375921E+01 0.15336443E+01 0.15297047E+01 - 0.15257732E+01 0.15218497E+01 0.15179344E+01 0.15140271E+01 0.15101279E+01 - 0.15062366E+01 0.15023534E+01 0.14984782E+01 0.14946110E+01 0.14907517E+01 - 0.14869004E+01 0.14830570E+01 0.14792215E+01 0.14753939E+01 0.14715742E+01 - 0.14677624E+01 0.14639584E+01 0.14601623E+01 0.14563740E+01 0.14525935E+01 - 0.14488207E+01 0.14450558E+01 0.14412986E+01 0.14375492E+01 0.14338075E+01 - 0.14300735E+01 0.14263473E+01 0.14226287E+01 0.14189178E+01 0.14152145E+01 - 0.14115189E+01 0.14078309E+01 0.14041505E+01 0.14004777E+01 0.13968126E+01 - 0.13931549E+01 0.13895049E+01 0.13858624E+01 0.13822274E+01 0.13785999E+01 - 0.13749799E+01 0.13713674E+01 0.13677624E+01 0.13641648E+01 0.13605747E+01 - 0.13569920E+01 0.13534168E+01 0.13498489E+01 0.13462884E+01 0.13427353E+01 - 0.13391896E+01 0.13356512E+01 0.13321201E+01 0.13285964E+01 0.13250799E+01 - 0.13215708E+01 0.13180689E+01 0.13145743E+01 0.13110870E+01 0.13076069E+01 - 0.13041340E+01 0.13006684E+01 0.12972099E+01 0.12937586E+01 0.12903145E+01 - 0.12868776E+01 0.12834478E+01 0.12800252E+01 0.12766097E+01 0.12732012E+01 - 0.12697999E+01 0.12664057E+01 0.12630186E+01 0.12596385E+01 0.12562654E+01 - 0.12528994E+01 0.12495404E+01 0.12461884E+01 0.12428435E+01 0.12395055E+01 - 0.12361745E+01 0.12328504E+01 0.12295333E+01 0.12262231E+01 0.12229199E+01 - 0.12196235E+01 0.12163341E+01 0.12130516E+01 0.12097759E+01 0.12065071E+01 - 0.12032451E+01 0.11999900E+01 0.11967417E+01 0.11935003E+01 0.11902656E+01 - 0.11870377E+01 0.11838167E+01 0.11806023E+01 0.11773948E+01 0.11741940E+01 - 0.11709999E+01 0.11678125E+01 0.11646319E+01 0.11614580E+01 0.11582907E+01 - 0.11551301E+01 0.11519762E+01 0.11488290E+01 0.11456884E+01 0.11425544E+01 - 0.11394271E+01 0.11363063E+01 0.11331922E+01 0.11300846E+01 0.11269836E+01 - 0.11238892E+01 0.11208014E+01 0.11177201E+01 0.11146453E+01 0.11115770E+01 - 0.11085153E+01 0.11054600E+01 0.11024113E+01 0.10993690E+01 0.10963332E+01 - 0.10933038E+01 0.10902809E+01 0.10872644E+01 0.10842544E+01 0.10812507E+01 - 0.10782535E+01 0.10752627E+01 0.10722782E+01 0.10693001E+01 0.10663284E+01 - 0.10633630E+01 0.10604040E+01 0.10574513E+01 0.10545049E+01 0.10515649E+01 - 0.10486311E+01 0.10457036E+01 0.10427824E+01 0.10398675E+01 0.10369588E+01 - 0.10340563E+01 0.10311601E+01 0.10282702E+01 0.10253864E+01 0.10225089E+01 - 0.10196375E+01 0.10167724E+01 0.10139134E+01 0.10110606E+01 0.10082139E+01 - 0.10053734E+01 0.10025390E+01 0.99971078E+00 0.99688865E+00 0.99407263E+00 - 0.99126271E+00 0.98845887E+00 0.98566111E+00 0.98286942E+00 0.98008379E+00 - 0.97730421E+00 0.97453067E+00 0.97176315E+00 0.96900166E+00 0.96624617E+00 - 0.96349669E+00 0.96075320E+00 0.95801569E+00 0.95528415E+00 0.95255858E+00 - 0.94983895E+00 0.94712527E+00 0.94441753E+00 0.94171571E+00 0.93901980E+00 - 0.93632980E+00 0.93364570E+00 0.93096748E+00 0.92829515E+00 0.92562868E+00 - 0.92296807E+00 0.92031330E+00 0.91766438E+00 0.91502130E+00 0.91238403E+00 - 0.90975258E+00 0.90712693E+00 0.90450707E+00 0.90189300E+00 0.89928471E+00 - 0.89668219E+00 0.89408542E+00 0.89149440E+00 0.88890912E+00 0.88632958E+00 - 0.88375575E+00 0.88118764E+00 0.87862523E+00 0.87606852E+00 0.87351750E+00 - 0.87097215E+00 0.86843247E+00 0.86589845E+00 0.86337008E+00 0.86084735E+00 - 0.85833026E+00 0.85581879E+00 0.85331293E+00 0.85081268E+00 0.84831803E+00 - 0.84582897E+00 0.84334549E+00 0.84086758E+00 0.83839523E+00 0.83592844E+00 - 0.83346719E+00 0.83101148E+00 0.82856130E+00 0.82611664E+00 0.82367749E+00 - 0.82124384E+00 0.81881569E+00 0.81639302E+00 0.81397583E+00 0.81156410E+00 - 0.80915784E+00 0.80675702E+00 0.80436165E+00 0.80197172E+00 0.79958720E+00 - 0.79720811E+00 0.79483443E+00 0.79246614E+00 0.79010325E+00 0.78774574E+00 - 0.78539360E+00 0.78304684E+00 0.78070543E+00 0.77836937E+00 0.77603865E+00 - 0.77371327E+00 0.77139321E+00 0.76907847E+00 0.76676904E+00 0.76446490E+00 - 0.76216606E+00 0.75987251E+00 0.75758423E+00 0.75530121E+00 0.75302346E+00 - 0.75075095E+00 0.74848369E+00 0.74622167E+00 0.74396487E+00 0.74171329E+00 - 0.73946691E+00 0.73722575E+00 0.73498977E+00 0.73275898E+00 0.73053337E+00 - 0.72831293E+00 0.72609765E+00 0.72388752E+00 0.72168254E+00 0.71948269E+00 - 0.71728798E+00 0.71509838E+00 0.71291390E+00 0.71073453E+00 0.70856025E+00 - 0.70639106E+00 0.70422696E+00 0.70206793E+00 0.69991396E+00 0.69776505E+00 - 0.69562119E+00 0.69348237E+00 0.69134859E+00 0.68921983E+00 0.68709609E+00 - 0.68497736E+00 0.68286364E+00 0.68075490E+00 0.67865116E+00 0.67655239E+00 - 0.67445860E+00 0.67236976E+00 0.67028589E+00 0.66820696E+00 0.66613297E+00 - 0.66406391E+00 0.66199978E+00 0.65994056E+00 0.65788626E+00 0.65583685E+00 - 0.65379234E+00 0.65175271E+00 0.64971796E+00 0.64768808E+00 0.64566306E+00 - 0.64364290E+00 0.64162759E+00 0.63961711E+00 0.63761147E+00 0.63561065E+00 - 0.63361465E+00 0.63162345E+00 0.62963706E+00 0.62765546E+00 0.62567865E+00 - 0.62370661E+00 0.62173935E+00 0.61977685E+00 0.61781910E+00 0.61586610E+00 - 0.61391785E+00 0.61197432E+00 0.61003552E+00 0.60810144E+00 0.60617207E+00 - 0.60424740E+00 0.60232743E+00 0.60041214E+00 0.59850154E+00 0.59659560E+00 - 0.59469433E+00 0.59279772E+00 0.59090576E+00 0.58901844E+00 0.58713576E+00 - 0.58525770E+00 0.58338427E+00 0.58151544E+00 0.57965123E+00 0.57779161E+00 - 0.57593658E+00 0.57408613E+00 0.57224026E+00 0.57039895E+00 0.56856221E+00 - 0.56673002E+00 0.56490238E+00 0.56307927E+00 0.56126069E+00 0.55944664E+00 - 0.55763711E+00 0.55583208E+00 0.55403156E+00 0.55223553E+00 0.55044398E+00 - 0.54865692E+00 0.54687433E+00 0.54509620E+00 0.54332253E+00 0.54155331E+00 - 0.53978853E+00 0.53802819E+00 0.53627227E+00 0.53452078E+00 0.53277370E+00 - 0.53103103E+00 0.52929275E+00 0.52755887E+00 0.52582937E+00 0.52410424E+00 - 0.52238349E+00 0.52066710E+00 0.51895506E+00 0.51724738E+00 0.51554403E+00 - 0.51384502E+00 0.51215033E+00 0.51045996E+00 0.50877390E+00 0.50709215E+00 - 0.50541469E+00 0.50374153E+00 0.50207264E+00 0.50040803E+00 0.49874769E+00 - 0.49709161E+00 0.49543979E+00 0.49379221E+00 0.49214887E+00 0.49050976E+00 - 0.48887488E+00 0.48724421E+00 0.48561776E+00 0.48399551E+00 0.48237745E+00 - 0.48076358E+00 0.47915390E+00 0.47754839E+00 0.47594705E+00 0.47434986E+00 - 0.47275683E+00 0.47116795E+00 0.46958320E+00 0.46800259E+00 0.46642610E+00 - 0.46485373E+00 0.46328546E+00 0.46172130E+00 0.46016124E+00 0.45860526E+00 - 0.45705337E+00 0.45550555E+00 0.45396180E+00 0.45242210E+00 0.45088646E+00 - 0.44935487E+00 0.44782731E+00 0.44630379E+00 0.44478429E+00 0.44326880E+00 - 0.44175733E+00 0.44024986E+00 0.43874638E+00 0.43724690E+00 0.43575139E+00 - 0.43425986E+00 0.43277230E+00 0.43128870E+00 0.42980904E+00 0.42833334E+00 - 0.42686157E+00 0.42539374E+00 0.42392983E+00 0.42246984E+00 0.42101375E+00 - 0.41956157E+00 0.41811329E+00 0.41666889E+00 0.41522838E+00 0.41379174E+00 - 0.41235897E+00 0.41093006E+00 0.40950500E+00 0.40808379E+00 0.40666641E+00 - 0.40525287E+00 0.40384316E+00 0.40243726E+00 0.40103517E+00 0.39963688E+00 - 0.39824239E+00 0.39685169E+00 0.39546477E+00 0.39408163E+00 0.39270225E+00 - 0.39132663E+00 0.38995477E+00 0.38858665E+00 0.38722227E+00 0.38586163E+00 - 0.38450470E+00 0.38315150E+00 0.38180201E+00 0.38045621E+00 0.37911412E+00 - 0.37777571E+00 0.37644099E+00 0.37510993E+00 0.37378255E+00 0.37245883E+00 - 0.37113876E+00 0.36982233E+00 0.36850954E+00 0.36720039E+00 0.36589486E+00 - 0.36459294E+00 0.36329463E+00 0.36199993E+00 0.36070882E+00 0.35942130E+00 - 0.35813736E+00 0.35685699E+00 0.35558019E+00 0.35430695E+00 0.35303726E+00 - 0.35177111E+00 0.35050850E+00 0.34924942E+00 0.34799386E+00 0.34674182E+00 - 0.34549329E+00 0.34424825E+00 0.34300671E+00 0.34176865E+00 0.34053407E+00 - 0.33930297E+00 0.33807532E+00 0.33685114E+00 0.33563040E+00 0.33441310E+00 - 0.33319924E+00 0.33198880E+00 0.33078178E+00 0.32957818E+00 0.32837797E+00 - 0.32718117E+00 0.32598775E+00 0.32479772E+00 0.32361106E+00 0.32242776E+00 - 0.32124783E+00 0.32007125E+00 0.31889801E+00 0.31772811E+00 0.31656153E+00 - 0.31539828E+00 0.31423834E+00 0.31308171E+00 0.31192837E+00 0.31077833E+00 - 0.30963157E+00 0.30848809E+00 0.30734787E+00 0.30621091E+00 0.30507721E+00 - 0.30394674E+00 0.30281952E+00 0.30169552E+00 0.30057475E+00 0.29945719E+00 - 0.29834283E+00 0.29723167E+00 0.29612370E+00 0.29501891E+00 0.29391730E+00 - 0.29281885E+00 0.29172356E+00 0.29063142E+00 0.28954242E+00 0.28845655E+00 - 0.28737381E+00 0.28629418E+00 0.28521767E+00 0.28414425E+00 0.28307393E+00 - 0.28200669E+00 0.28094253E+00 0.27988144E+00 0.27882340E+00 0.27776842E+00 - 0.27671648E+00 0.27566758E+00 0.27462170E+00 0.27357884E+00 0.27253898E+00 - 0.27150213E+00 0.27046827E+00 0.26943740E+00 0.26840950E+00 0.26738456E+00 - 0.26636258E+00 0.26534355E+00 0.26432746E+00 0.26331431E+00 0.26230407E+00 - 0.26129675E+00 0.26029233E+00 0.25929081E+00 0.25829217E+00 0.25729641E+00 - 0.25630352E+00 0.25531349E+00 0.25432631E+00 0.25334197E+00 0.25236046E+00 - 0.25138177E+00 0.25040590E+00 0.24943283E+00 0.24846255E+00 0.24749506E+00 - 0.24653034E+00 0.24556839E+00 0.24460919E+00 0.24365274E+00 0.24269903E+00 - 0.24174804E+00 0.24079977E+00 0.23985420E+00 0.23891133E+00 0.23797114E+00 - 0.23703364E+00 0.23609879E+00 0.23516661E+00 0.23423707E+00 0.23331016E+00 - 0.23238588E+00 0.23146421E+00 0.23054515E+00 0.22962867E+00 0.22871478E+00 - 0.22780347E+00 0.22689471E+00 0.22598850E+00 0.22508483E+00 0.22418369E+00 - 0.22328506E+00 0.22238894E+00 0.22149531E+00 0.22060416E+00 0.21971549E+00 - 0.21882927E+00 0.21794550E+00 0.21706417E+00 0.21618526E+00 0.21530877E+00 - 0.21443467E+00 0.21356296E+00 0.21269363E+00 0.21182666E+00 0.21096204E+00 - 0.21009976E+00 0.20923981E+00 0.20838217E+00 0.20752683E+00 0.20667378E+00 - 0.20582300E+00 0.20497449E+00 0.20412823E+00 0.20328420E+00 0.20244239E+00 - 0.20160279E+00 0.20076538E+00 0.19993016E+00 0.19909710E+00 0.19826620E+00 - 0.19743744E+00 0.19661080E+00 0.19578627E+00 0.19496384E+00 0.19414349E+00 - 0.19332521E+00 0.19250898E+00 0.19169479E+00 0.19088262E+00 0.19007246E+00 - 0.18926429E+00 0.18845809E+00 0.18765386E+00 0.18685157E+00 0.18605121E+00 - 0.18525276E+00 0.18445621E+00 0.18366154E+00 0.18286873E+00 0.18207777E+00 - 0.18128864E+00 0.18050133E+00 0.17971581E+00 0.17893207E+00 0.17815010E+00 - 0.17736986E+00 0.17659136E+00 0.17581456E+00 0.17503945E+00 0.17426602E+00 - 0.17349424E+00 0.17272409E+00 0.17195556E+00 0.17118863E+00 0.17042328E+00 - 0.16965949E+00 0.16889724E+00 0.16813651E+00 0.16737728E+00 0.16661953E+00 - 0.16586324E+00 0.16510839E+00 0.16435497E+00 0.16360294E+00 0.16285229E+00 - 0.16210299E+00 0.16135503E+00 0.16060839E+00 0.15986304E+00 0.15911896E+00 - 0.15837613E+00 0.15763453E+00 0.15689413E+00 0.15615491E+00 0.15541685E+00 - 0.15467993E+00 0.15394412E+00 0.15320940E+00 0.15247575E+00 0.15174313E+00 - 0.15101154E+00 0.15028094E+00 0.14955130E+00 0.14882262E+00 0.14809485E+00 - 0.14736798E+00 0.14664197E+00 0.14591681E+00 0.14519247E+00 0.14446893E+00 - 0.14374615E+00 0.14302411E+00 0.14230278E+00 0.14158215E+00 0.14086217E+00 - 0.14014283E+00 0.13942409E+00 0.13870594E+00 0.13798833E+00 0.13727126E+00 - 0.13655467E+00 0.13583856E+00 0.13512289E+00 0.13440763E+00 0.13369275E+00 - 0.13297823E+00 0.13226404E+00 0.13155014E+00 0.13083652E+00 0.13012313E+00 - 0.12940995E+00 0.12869695E+00 0.12798410E+00 0.12727138E+00 0.12655874E+00 - 0.12584617E+00 0.12513363E+00 0.12442109E+00 0.12370852E+00 0.12299589E+00 - 0.12228317E+00 0.12157034E+00 0.12085735E+00 0.12014419E+00 0.11943081E+00 - 0.11871719E+00 0.11800331E+00 0.11728912E+00 0.11657460E+00 0.11585971E+00 - 0.11514444E+00 0.11442874E+00 0.11371259E+00 0.11299596E+00 0.11227882E+00 - 0.11156114E+00 0.11084289E+00 0.11012403E+00 0.10940455E+00 0.10868441E+00 - 0.10796359E+00 0.10724205E+00 0.10651977E+00 0.10579672E+00 0.10507287E+00 - 0.10434819E+00 0.10362267E+00 0.10289627E+00 0.10216897E+00 0.10144074E+00 - 0.10071156E+00 0.99981400E-01 0.99250242E-01 0.98518061E-01 0.97784834E-01 - 0.97050540E-01 0.96315159E-01 0.95578669E-01 0.94841051E-01 0.94102286E-01 - 0.93362357E-01 0.92621247E-01 0.91878939E-01 0.91135419E-01 0.90390673E-01 - 0.89644687E-01 0.88897450E-01 0.88148950E-01 0.87399179E-01 0.86648128E-01 - 0.85895790E-01 0.85142159E-01 0.84387231E-01 0.83631004E-01 0.82873475E-01 - 0.82114645E-01 0.81354515E-01 0.80593090E-01 0.79830374E-01 0.79066374E-01 - 0.78301099E-01 0.77534559E-01 0.76766767E-01 0.75997737E-01 0.75227487E-01 - 0.74456034E-01 0.73683399E-01 0.72909606E-01 0.72134680E-01 0.71358648E-01 - 0.70581541E-01 0.69803392E-01 0.69024235E-01 0.68244108E-01 0.67463051E-01 - 0.66681108E-01 0.65898325E-01 0.65114750E-01 0.64330435E-01 0.63545434E-01 - 0.62759804E-01 0.61973608E-01 0.61186907E-01 0.60399769E-01 0.59612264E-01 - 0.58824466E-01 0.58036450E-01 0.57248297E-01 0.56460091E-01 0.55671917E-01 - 0.54883866E-01 0.54096032E-01 0.53308512E-01 0.52521406E-01 0.51734820E-01 - 0.50948860E-01 0.50163638E-01 0.49379270E-01 0.48595873E-01 0.47813571E-01 - 0.47032489E-01 0.46252756E-01 0.45474505E-01 0.44697873E-01 0.43923000E-01 - 0.43150029E-01 0.42379107E-01 0.41610385E-01 0.40844015E-01 0.40080155E-01 - 0.39318965E-01 0.38560607E-01 0.37805247E-01 0.37053055E-01 0.36304203E-01 - 0.35558863E-01 0.34817213E-01 0.34079433E-01 0.33345704E-01 0.32616209E-01 - 0.31891134E-01 0.31170665E-01 0.30454993E-01 0.29744306E-01 0.29038796E-01 - 0.28338656E-01 0.27644077E-01 0.26955254E-01 0.26272380E-01 0.25595649E-01 - 0.24925254E-01 0.24261387E-01 0.23604240E-01 0.22954004E-01 0.22310869E-01 - 0.21675022E-01 0.21046647E-01 0.20425929E-01 0.19813048E-01 0.19208180E-01 - 0.18611501E-01 0.18023179E-01 0.17443381E-01 0.16872269E-01 0.16310000E-01 - 0.15756726E-01 0.15212593E-01 0.14677742E-01 0.14152307E-01 0.13636416E-01 - 0.13130191E-01 0.12633746E-01 0.12147187E-01 0.11670614E-01 0.11204117E-01 - 0.10747778E-01 0.10301672E-01 0.98658640E-02 0.94404095E-02 0.90253551E-02 - 0.86207381E-02 0.82265856E-02 0.78429150E-02 0.74697338E-02 0.71070390E-02 - 0.67548175E-02 0.64130458E-02 0.60816902E-02 0.57607062E-02 0.54500393E-02 - 0.51496245E-02 0.48593862E-02 0.45792391E-02 0.43090875E-02 0.40488258E-02 - 0.37983389E-02 0.35575019E-02 0.33261809E-02 0.31042329E-02 0.28915063E-02 - 0.26878409E-02 0.24930690E-02 0.23070150E-02 0.21294962E-02 0.19603233E-02 - 0.17993005E-02 0.16462265E-02 0.15008946E-02 0.13630932E-02 0.12326069E-02 - 0.11092162E-02 0.99269863E-03 0.88282921E-03 0.77938090E-03 0.68212524E-03 - 0.59083293E-03 0.50527436E-03 0.42522016E-03 0.35044181E-03 0.28071209E-03 - 0.21580569E-03 0.15549966E-03 0.99573903E-04 0.47811675E-04 0.00000000E+00 - 0.97771570E+01 0.97771570E+01 0.97771570E+01 0.97771570E+01 0.97771570E+01 - 0.97771570E+01 0.97771570E+01 0.97771570E+01 0.97771570E+01 0.97771570E+01 - 0.97771570E+01 0.97771570E+01 0.97771570E+01 0.97771570E+01 0.97771570E+01 - 0.97771570E+01 0.97771570E+01 0.97771570E+01 0.97771570E+01 0.97771570E+01 - 0.97771570E+01 0.97771570E+01 0.97771570E+01 0.97771570E+01 0.97771570E+01 - 0.97771570E+01 0.97771570E+01 0.97771570E+01 0.97771570E+01 0.97771570E+01 - 0.97771570E+01 0.97771570E+01 0.97771570E+01 0.97771570E+01 0.97771570E+01 - 0.97771570E+01 0.97771570E+01 0.97771570E+01 0.97771570E+01 0.97771570E+01 - 0.97771570E+01 0.97145336E+01 0.94177130E+01 0.91366271E+01 0.88701043E+01 - 0.86170840E+01 0.83766043E+01 0.81477908E+01 0.79298467E+01 0.77220450E+01 - 0.75237208E+01 0.73342648E+01 0.71531180E+01 0.69797664E+01 0.68137366E+01 - 0.66545921E+01 0.65019299E+01 0.63553768E+01 0.62145876E+01 0.60792419E+01 - 0.59490420E+01 0.58237113E+01 0.57029923E+01 0.55866448E+01 0.54744447E+01 - 0.53661828E+01 0.52616633E+01 0.51607029E+01 0.50631300E+01 0.49687835E+01 - 0.48775121E+01 0.47891738E+01 0.47036349E+01 0.46207695E+01 0.45404591E+01 - 0.44625920E+01 0.43870626E+01 0.43137713E+01 0.42426239E+01 0.41735314E+01 - 0.41064094E+01 0.40411782E+01 0.39777620E+01 0.39160891E+01 0.38560914E+01 - 0.37977041E+01 0.37408659E+01 0.36855181E+01 0.36316054E+01 0.35790747E+01 - 0.35278756E+01 0.34779601E+01 0.34292823E+01 0.33817987E+01 0.33354674E+01 - 0.32902487E+01 0.32461045E+01 0.32029985E+01 0.31608958E+01 0.31197632E+01 - 0.30795688E+01 0.30402821E+01 0.30018740E+01 0.29643164E+01 0.29275824E+01 - 0.28916463E+01 0.28564833E+01 0.28220698E+01 0.27883830E+01 0.27554009E+01 - 0.27231025E+01 0.26914676E+01 0.26604768E+01 0.26301113E+01 0.26003530E+01 - 0.25711848E+01 0.25425898E+01 0.25145519E+01 0.24870557E+01 0.24600862E+01 - 0.24336289E+01 0.24076701E+01 0.23821962E+01 0.23571943E+01 0.23326519E+01 - 0.23085569E+01 0.22848977E+01 0.22616630E+01 0.22388419E+01 0.22164238E+01 - 0.21943987E+01 0.21727565E+01 0.21514878E+01 0.21305834E+01 0.21100343E+01 - 0.20898319E+01 0.20699679E+01 0.20504340E+01 0.20312224E+01 0.20123255E+01 - 0.19937360E+01 0.19754467E+01 0.19574505E+01 0.19397409E+01 0.19223111E+01 - 0.19051550E+01 0.18882663E+01 0.18716391E+01 0.18552675E+01 0.18391460E+01 - 0.18232690E+01 0.18076312E+01 0.17922274E+01 0.17770527E+01 0.17621021E+01 - 0.17473709E+01 0.17328544E+01 0.17185481E+01 0.17044478E+01 0.16905491E+01 - 0.16768479E+01 0.16633401E+01 0.16500218E+01 0.16368893E+01 0.16239387E+01 - 0.16111665E+01 0.15985692E+01 0.15861432E+01 0.15738852E+01 0.15617920E+01 - 0.15498604E+01 0.15380872E+01 0.15264695E+01 0.15150042E+01 0.15036886E+01 - 0.14925197E+01 0.14814949E+01 0.14706115E+01 0.14598668E+01 0.14492584E+01 - 0.14387837E+01 0.14284402E+01 0.14182257E+01 0.14081378E+01 0.13981743E+01 - 0.13883328E+01 0.13786114E+01 0.13690078E+01 0.13595200E+01 0.13501460E+01 - 0.13408838E+01 0.13317315E+01 0.13226872E+01 0.13137491E+01 0.13049154E+01 - 0.12961842E+01 0.12875540E+01 0.12790229E+01 0.12705894E+01 0.12622518E+01 - 0.12540086E+01 0.12458582E+01 0.12377991E+01 0.12298299E+01 0.12219490E+01 - 0.12141551E+01 0.12064467E+01 0.11988226E+01 0.11912813E+01 0.11838216E+01 - 0.11764423E+01 0.11691419E+01 0.11619194E+01 0.11547734E+01 0.11477030E+01 - 0.11407068E+01 0.11337837E+01 0.11269327E+01 0.11201526E+01 0.11134425E+01 - 0.11068011E+01 0.11002276E+01 0.10937209E+01 0.10872800E+01 0.10809040E+01 - 0.10745919E+01 0.10683427E+01 0.10621556E+01 0.10560297E+01 0.10499641E+01 - 0.10439579E+01 0.10380103E+01 0.10321205E+01 0.10262875E+01 0.10205107E+01 - 0.10147893E+01 0.10091224E+01 0.10035093E+01 0.99794933E+00 0.99244167E+00 - 0.98698564E+00 0.98158052E+00 0.97622563E+00 0.97092027E+00 0.96566379E+00 - 0.96045553E+00 0.95529485E+00 0.95018110E+00 0.94511366E+00 0.94009193E+00 - 0.93511529E+00 0.93018317E+00 0.92529497E+00 0.92045012E+00 0.91564807E+00 - 0.91088826E+00 0.90617015E+00 0.90149319E+00 0.89685688E+00 0.89226068E+00 - 0.88770410E+00 0.88318662E+00 0.87870777E+00 0.87426706E+00 0.86986400E+00 - 0.86549814E+00 0.86116900E+00 0.85687615E+00 0.85261913E+00 0.84839750E+00 - 0.84421084E+00 0.84005871E+00 0.83594070E+00 0.83185640E+00 0.82780540E+00 - 0.82378730E+00 0.81980171E+00 0.81584824E+00 0.81192652E+00 0.80803616E+00 - 0.80417680E+00 0.80034808E+00 0.79654963E+00 0.79278111E+00 0.78904216E+00 - 0.78533245E+00 0.78165164E+00 0.77799939E+00 0.77437538E+00 0.77077929E+00 - 0.76721080E+00 0.76366960E+00 0.76015538E+00 0.75666783E+00 0.75320667E+00 - 0.74977158E+00 0.74636228E+00 0.74297849E+00 0.73961993E+00 0.73628631E+00 - 0.73297736E+00 0.72969281E+00 0.72643240E+00 0.72319586E+00 0.71998293E+00 - 0.71679337E+00 0.71362691E+00 0.71048330E+00 0.70736231E+00 0.70426370E+00 - 0.70118722E+00 0.69813264E+00 0.69509972E+00 0.69208825E+00 0.68909800E+00 - 0.68612873E+00 0.68318024E+00 0.68025231E+00 0.67734473E+00 0.67445728E+00 - 0.67158976E+00 0.66874196E+00 0.66591368E+00 0.66310472E+00 0.66031489E+00 - 0.65754399E+00 0.65479183E+00 0.65205821E+00 0.64934297E+00 0.64664590E+00 - 0.64396683E+00 0.64130558E+00 0.63866198E+00 0.63603584E+00 0.63342699E+00 - 0.63083527E+00 0.62826051E+00 0.62570254E+00 0.62316120E+00 0.62063632E+00 - 0.61812774E+00 0.61563532E+00 0.61315889E+00 0.61069829E+00 0.60825339E+00 - 0.60582402E+00 0.60341004E+00 0.60101130E+00 0.59862766E+00 0.59625898E+00 - 0.59390511E+00 0.59156591E+00 0.58924126E+00 0.58693101E+00 0.58463502E+00 - 0.58235317E+00 0.58008533E+00 0.57783136E+00 0.57559114E+00 0.57336454E+00 - 0.57115144E+00 0.56895171E+00 0.56676524E+00 0.56459189E+00 0.56243156E+00 - 0.56028412E+00 0.55814946E+00 0.55602747E+00 0.55391802E+00 0.55182102E+00 - 0.54973634E+00 0.54766388E+00 0.54560353E+00 0.54355518E+00 0.54151873E+00 - 0.53949408E+00 0.53748111E+00 0.53547973E+00 0.53348983E+00 0.53151132E+00 - 0.52954410E+00 0.52758807E+00 0.52564313E+00 0.52370919E+00 0.52178616E+00 - 0.51987393E+00 0.51797242E+00 0.51608154E+00 0.51420119E+00 0.51233130E+00 - 0.51047176E+00 0.50862249E+00 0.50678341E+00 0.50495442E+00 0.50313546E+00 - 0.50132642E+00 0.49952724E+00 0.49773782E+00 0.49595809E+00 0.49418796E+00 - 0.49242737E+00 0.49067622E+00 0.48893445E+00 0.48720197E+00 0.48547871E+00 - 0.48376459E+00 0.48205955E+00 0.48036351E+00 0.47867639E+00 0.47699812E+00 - 0.47532863E+00 0.47366786E+00 0.47201573E+00 0.47037217E+00 0.46873711E+00 - 0.46711050E+00 0.46549225E+00 0.46388231E+00 0.46228061E+00 0.46068708E+00 - 0.45910167E+00 0.45752430E+00 0.45595492E+00 0.45439346E+00 0.45283986E+00 - 0.45129406E+00 0.44975600E+00 0.44822562E+00 0.44670286E+00 0.44518767E+00 - 0.44367998E+00 0.44217974E+00 0.44068689E+00 0.43920138E+00 0.43772314E+00 - 0.43625213E+00 0.43478830E+00 0.43333157E+00 0.43188191E+00 0.43043927E+00 - 0.42900358E+00 0.42757479E+00 0.42615286E+00 0.42473774E+00 0.42332937E+00 - 0.42192770E+00 0.42053268E+00 0.41914428E+00 0.41776243E+00 0.41638709E+00 - 0.41501821E+00 0.41365575E+00 0.41229965E+00 0.41094988E+00 0.40960638E+00 - 0.40826912E+00 0.40693804E+00 0.40561311E+00 0.40429427E+00 0.40298149E+00 - 0.40167472E+00 0.40037391E+00 0.39907904E+00 0.39779005E+00 0.39650690E+00 - 0.39522956E+00 0.39395797E+00 0.39269211E+00 0.39143193E+00 0.39017739E+00 - 0.38892845E+00 0.38768507E+00 0.38644722E+00 0.38521485E+00 0.38398794E+00 - 0.38276643E+00 0.38155030E+00 0.38033950E+00 0.37913401E+00 0.37793378E+00 - 0.37673877E+00 0.37554896E+00 0.37436431E+00 0.37318478E+00 0.37201034E+00 - 0.37084095E+00 0.36967659E+00 0.36851721E+00 0.36736278E+00 0.36621327E+00 - 0.36506865E+00 0.36392889E+00 0.36279395E+00 0.36166379E+00 0.36053840E+00 - 0.35941774E+00 0.35830177E+00 0.35719047E+00 0.35608380E+00 0.35498174E+00 - 0.35388426E+00 0.35279132E+00 0.35170289E+00 0.35061895E+00 0.34953947E+00 - 0.34846442E+00 0.34739377E+00 0.34632750E+00 0.34526557E+00 0.34420795E+00 - 0.34315462E+00 0.34210556E+00 0.34106073E+00 0.34002011E+00 0.33898367E+00 - 0.33795139E+00 0.33692323E+00 0.33589918E+00 0.33487920E+00 0.33386328E+00 - 0.33285139E+00 0.33184349E+00 0.33083958E+00 0.32983961E+00 0.32884358E+00 - 0.32785145E+00 0.32686319E+00 0.32587880E+00 0.32489823E+00 0.32392148E+00 - 0.32294851E+00 0.32197930E+00 0.32101383E+00 0.32005208E+00 0.31909402E+00 - 0.31813964E+00 0.31718891E+00 0.31624180E+00 0.31529830E+00 0.31435839E+00 - 0.31342204E+00 0.31248923E+00 0.31155995E+00 0.31063416E+00 0.30971185E+00 - 0.30879301E+00 0.30787760E+00 0.30696561E+00 0.30605702E+00 0.30515180E+00 - 0.30424995E+00 0.30335144E+00 0.30245624E+00 0.30156435E+00 0.30067573E+00 - 0.29979038E+00 0.29890828E+00 0.29802939E+00 0.29715372E+00 0.29628123E+00 - 0.29541191E+00 0.29454575E+00 0.29368272E+00 0.29282280E+00 0.29196599E+00 - 0.29111225E+00 0.29026158E+00 0.28941395E+00 0.28856935E+00 0.28772777E+00 - 0.28688918E+00 0.28605357E+00 0.28522092E+00 0.28439121E+00 0.28356444E+00 - 0.28274057E+00 0.28191961E+00 0.28110152E+00 0.28028631E+00 0.27947393E+00 - 0.27866440E+00 0.27785768E+00 0.27705376E+00 0.27625264E+00 0.27545428E+00 - 0.27465868E+00 0.27386583E+00 0.27307570E+00 0.27228828E+00 0.27150356E+00 - 0.27072153E+00 0.26994217E+00 0.26916546E+00 0.26839139E+00 0.26761995E+00 - 0.26685112E+00 0.26608490E+00 0.26532126E+00 0.26456019E+00 0.26380167E+00 - 0.26304571E+00 0.26229227E+00 0.26154136E+00 0.26079294E+00 0.26004703E+00 - 0.25930359E+00 0.25856261E+00 0.25782409E+00 0.25708802E+00 0.25635437E+00 - 0.25562313E+00 0.25489430E+00 0.25416787E+00 0.25344381E+00 0.25272212E+00 - 0.25200278E+00 0.25128578E+00 0.25057112E+00 0.24985878E+00 0.24914874E+00 - 0.24844100E+00 0.24773555E+00 0.24703237E+00 0.24633145E+00 0.24563278E+00 - 0.24493635E+00 0.24424215E+00 0.24355017E+00 0.24286039E+00 0.24217281E+00 - 0.24148741E+00 0.24080419E+00 0.24012313E+00 0.23944422E+00 0.23876745E+00 - 0.23809282E+00 0.23742031E+00 0.23674991E+00 0.23608161E+00 0.23541540E+00 - 0.23475127E+00 0.23408922E+00 0.23342922E+00 0.23277127E+00 0.23211537E+00 - 0.23146150E+00 0.23080965E+00 0.23015981E+00 0.22951197E+00 0.22886613E+00 - 0.22822227E+00 0.22758039E+00 0.22694047E+00 0.22630251E+00 0.22566649E+00 - 0.22503241E+00 0.22440027E+00 0.22377004E+00 0.22314172E+00 0.22251531E+00 - 0.22189078E+00 0.22126815E+00 0.22064739E+00 0.22002849E+00 0.21941146E+00 - 0.21879628E+00 0.21818294E+00 0.21757143E+00 0.21696175E+00 0.21635388E+00 - 0.21574783E+00 0.21514358E+00 0.21454111E+00 0.21394044E+00 0.21334154E+00 - 0.21274441E+00 0.21214904E+00 0.21155542E+00 0.21096355E+00 0.21037342E+00 - 0.20978502E+00 0.20919834E+00 0.20861338E+00 0.20803012E+00 0.20744856E+00 - 0.20686870E+00 0.20629052E+00 0.20571402E+00 0.20513919E+00 0.20456602E+00 - 0.20399451E+00 0.20342465E+00 0.20285644E+00 0.20228985E+00 0.20172490E+00 - 0.20116156E+00 0.20059985E+00 0.20003973E+00 0.19948122E+00 0.19892431E+00 - 0.19836898E+00 0.19781523E+00 0.19726305E+00 0.19671244E+00 0.19616340E+00 - 0.19561591E+00 0.19506996E+00 0.19452556E+00 0.19398269E+00 0.19344135E+00 - 0.19290153E+00 0.19236323E+00 0.19182644E+00 0.19129116E+00 0.19075737E+00 - 0.19022507E+00 0.18969426E+00 0.18916493E+00 0.18863707E+00 0.18811068E+00 - 0.18758575E+00 0.18706228E+00 0.18654025E+00 0.18601968E+00 0.18550054E+00 - 0.18498283E+00 0.18446655E+00 0.18395169E+00 0.18343824E+00 0.18292621E+00 - 0.18241558E+00 0.18190635E+00 0.18139852E+00 0.18089207E+00 0.18038701E+00 - 0.17988332E+00 0.17938101E+00 0.17888006E+00 0.17838047E+00 0.17788224E+00 - 0.17738537E+00 0.17688983E+00 0.17639564E+00 0.17590279E+00 0.17541126E+00 - 0.17492106E+00 0.17443218E+00 0.17394462E+00 0.17345837E+00 0.17297342E+00 - 0.17248977E+00 0.17200742E+00 0.17152636E+00 0.17104659E+00 0.17056810E+00 - 0.17009088E+00 0.16961494E+00 0.16914026E+00 0.16866685E+00 0.16819469E+00 - 0.16772379E+00 0.16725414E+00 0.16678573E+00 0.16631856E+00 0.16585263E+00 - 0.16538793E+00 0.16492445E+00 0.16446220E+00 0.16400116E+00 0.16354134E+00 - 0.16308272E+00 0.16262531E+00 0.16216910E+00 0.16171409E+00 0.16126026E+00 - 0.16080763E+00 0.16035618E+00 0.15990590E+00 0.15945681E+00 0.15900888E+00 - 0.15856212E+00 0.15811652E+00 0.15767208E+00 0.15722880E+00 0.15678667E+00 - 0.15634568E+00 0.15590584E+00 0.15546713E+00 0.15502956E+00 0.15459312E+00 - 0.15415781E+00 0.15372362E+00 0.15329055E+00 0.15285860E+00 0.15242776E+00 - 0.15199803E+00 0.15156940E+00 0.15114187E+00 0.15071544E+00 0.15029010E+00 - 0.14986585E+00 0.14944269E+00 0.14902061E+00 0.14859961E+00 0.14817969E+00 - 0.14776084E+00 0.14734305E+00 0.14692633E+00 0.14651067E+00 0.14609607E+00 - 0.14568253E+00 0.14527003E+00 0.14485859E+00 0.14444818E+00 0.14403882E+00 - 0.14363050E+00 0.14322321E+00 0.14281695E+00 0.14241172E+00 0.14200751E+00 - 0.14160432E+00 0.14120216E+00 0.14080100E+00 0.14040086E+00 0.14000173E+00 - 0.13960360E+00 0.13920647E+00 0.13881034E+00 0.13841521E+00 0.13802107E+00 - 0.13762792E+00 0.13723576E+00 0.13684458E+00 0.13645438E+00 0.13606516E+00 - 0.13567691E+00 0.13528963E+00 0.13490332E+00 0.13451798E+00 0.13413360E+00 - 0.13375018E+00 0.13336772E+00 0.13298621E+00 0.13260565E+00 0.13222604E+00 - 0.13184737E+00 0.13146965E+00 0.13109287E+00 0.13071702E+00 0.13034211E+00 - 0.12996813E+00 0.12959508E+00 0.12922295E+00 0.12885175E+00 0.12848147E+00 - 0.12811210E+00 0.12774365E+00 0.12737612E+00 0.12700949E+00 0.12664377E+00 - 0.12627895E+00 0.12591504E+00 0.12555202E+00 0.12518991E+00 0.12482868E+00 - 0.12446835E+00 0.12410891E+00 0.12375035E+00 0.12339268E+00 0.12303589E+00 - 0.12267998E+00 0.12232494E+00 0.12197078E+00 0.12161749E+00 0.12126507E+00 - 0.12091352E+00 0.12056283E+00 0.12021301E+00 0.11986404E+00 0.11951593E+00 - 0.11916867E+00 0.11882227E+00 0.11847672E+00 0.11813202E+00 0.11778816E+00 - 0.11744514E+00 0.11710297E+00 0.11676163E+00 0.11642113E+00 0.11608147E+00 - 0.11574263E+00 0.11540463E+00 0.11506745E+00 0.11473110E+00 0.11439557E+00 - 0.11406087E+00 0.11372698E+00 0.11339391E+00 0.11306165E+00 0.11273020E+00 - 0.11239957E+00 0.11206974E+00 0.11174072E+00 0.11141250E+00 0.11108508E+00 - 0.11075846E+00 0.11043264E+00 0.11010762E+00 0.10978339E+00 0.10945995E+00 - 0.10913730E+00 0.10881543E+00 0.10849435E+00 0.10817406E+00 0.10785454E+00 - 0.10753581E+00 0.10721785E+00 0.10690067E+00 0.10658426E+00 0.10626862E+00 - 0.10595375E+00 0.10563965E+00 0.10532631E+00 0.10501374E+00 0.10470193E+00 - 0.10439087E+00 0.10408058E+00 0.10377104E+00 0.10346226E+00 0.10315423E+00 - 0.10284695E+00 0.10254041E+00 0.10223463E+00 0.10192959E+00 0.10162529E+00 - 0.10132173E+00 0.10101891E+00 0.10071683E+00 0.10041549E+00 0.10011488E+00 - 0.99815002E-01 0.99515855E-01 0.99217436E-01 0.98919745E-01 0.98622778E-01 - 0.98326535E-01 0.98031014E-01 0.97736213E-01 0.97442130E-01 0.97148764E-01 - 0.96856113E-01 0.96564175E-01 0.96272949E-01 0.95982432E-01 0.95692624E-01 - 0.95403522E-01 0.95115125E-01 0.94827432E-01 0.94540440E-01 0.94254148E-01 - 0.93968554E-01 0.93683657E-01 0.93399456E-01 0.93115948E-01 0.92833131E-01 - 0.92551005E-01 0.92269568E-01 0.91988818E-01 0.91708754E-01 0.91429373E-01 - 0.91150675E-01 0.90872658E-01 0.90595321E-01 0.90318661E-01 0.90042677E-01 - 0.89767369E-01 0.89492733E-01 0.89218769E-01 0.88945476E-01 0.88672851E-01 - 0.88400894E-01 0.88129602E-01 0.87858974E-01 0.87589009E-01 0.87319706E-01 - 0.87051062E-01 0.86783077E-01 0.86515749E-01 0.86249076E-01 0.85983057E-01 - 0.85717690E-01 0.85452975E-01 0.85188910E-01 0.84925493E-01 0.84662723E-01 - 0.84400598E-01 0.84139117E-01 0.83878279E-01 0.83618083E-01 0.83358526E-01 - 0.83099607E-01 0.82841326E-01 0.82583681E-01 0.82326670E-01 0.82070292E-01 - 0.81814545E-01 0.81559429E-01 0.81304942E-01 0.81051083E-01 0.80797849E-01 - 0.80545241E-01 0.80293257E-01 0.80041894E-01 0.79791153E-01 0.79541031E-01 - 0.79291528E-01 0.79042641E-01 0.78794371E-01 0.78546715E-01 0.78299672E-01 - 0.78053241E-01 0.77807420E-01 0.77562209E-01 0.77317606E-01 0.77073610E-01 - 0.76830219E-01 0.76587432E-01 0.76345248E-01 0.76103667E-01 0.75862685E-01 - 0.75622303E-01 0.75382519E-01 0.75143332E-01 0.74904740E-01 0.74666743E-01 - 0.74429338E-01 0.74192526E-01 0.73956304E-01 0.73720672E-01 0.73485628E-01 - 0.73251171E-01 0.73017300E-01 0.72784013E-01 0.72551310E-01 0.72319190E-01 - 0.72087650E-01 0.71856691E-01 0.71626310E-01 0.71396507E-01 0.71167280E-01 - 0.70938628E-01 0.70710551E-01 0.70483046E-01 0.70256114E-01 0.70029752E-01 - 0.69803959E-01 0.69578735E-01 0.69354078E-01 0.69129987E-01 0.68906461E-01 - 0.68683499E-01 0.68461100E-01 0.68239262E-01 0.68017985E-01 0.67797267E-01 - 0.67577107E-01 0.67357504E-01 0.67138458E-01 0.66919966E-01 0.66702028E-01 - 0.66484643E-01 0.66267810E-01 0.66051527E-01 0.65835794E-01 0.65620609E-01 - 0.65405971E-01 0.65191880E-01 0.64978333E-01 0.64765331E-01 0.64552872E-01 - 0.64340955E-01 0.64129579E-01 0.63918742E-01 0.63708445E-01 0.63498685E-01 - 0.63289462E-01 0.63080774E-01 0.62872621E-01 0.62665002E-01 0.62457915E-01 - 0.62251360E-01 0.62045335E-01 0.61839839E-01 0.61634872E-01 0.61430432E-01 - 0.61226519E-01 0.61023131E-01 0.60820267E-01 0.60617927E-01 0.60416109E-01 - 0.60214812E-01 0.60014036E-01 0.59813778E-01 0.59614040E-01 0.59414818E-01 - 0.59216113E-01 0.59017922E-01 0.58820247E-01 0.58623084E-01 0.58426434E-01 - 0.58230295E-01 0.58034667E-01 0.57839548E-01 0.57644937E-01 0.57450834E-01 - 0.57257237E-01 0.57064146E-01 0.56871559E-01 0.56679476E-01 0.56487895E-01 - 0.56296816E-01 0.56106238E-01 0.55916159E-01 0.55726580E-01 0.55537498E-01 - 0.55348913E-01 0.55160823E-01 0.54973229E-01 0.54786129E-01 0.54599522E-01 - 0.54413407E-01 0.54227783E-01 0.54042650E-01 0.53858006E-01 0.53673850E-01 - 0.53490182E-01 0.53307000E-01 0.53124304E-01 0.52942093E-01 0.52760365E-01 - 0.52579121E-01 0.52398358E-01 0.52218076E-01 0.52038275E-01 0.51858952E-01 - 0.51680108E-01 0.51501742E-01 0.51323851E-01 0.51146437E-01 0.50969497E-01 - 0.50793031E-01 0.50617038E-01 0.50441516E-01 0.50266466E-01 0.50091886E-01 - 0.49917776E-01 0.49744133E-01 0.49570959E-01 0.49398251E-01 0.49226008E-01 - 0.49054231E-01 0.48882917E-01 0.48712067E-01 0.48541679E-01 0.48371752E-01 - 0.48202286E-01 0.48033279E-01 0.47864731E-01 0.47696641E-01 0.47529008E-01 - 0.47361831E-01 0.47195109E-01 0.47028842E-01 0.46863028E-01 0.46697667E-01 - 0.46532758E-01 0.46368299E-01 0.46204291E-01 0.46040732E-01 0.45877621E-01 - 0.45714958E-01 0.45552742E-01 0.45390971E-01 0.45229646E-01 0.45068764E-01 - 0.44908326E-01 0.44748330E-01 0.44588776E-01 0.44429663E-01 0.44270989E-01 - 0.44112755E-01 0.43954959E-01 0.43797600E-01 0.43640678E-01 0.43484191E-01 - 0.43328140E-01 0.43172522E-01 0.43017338E-01 0.42862587E-01 0.42708266E-01 - 0.42554377E-01 0.42400918E-01 0.42247887E-01 0.42095285E-01 0.41943111E-01 - 0.41791363E-01 0.41640041E-01 0.41489144E-01 0.41338671E-01 0.41188622E-01 - 0.41038995E-01 0.40889790E-01 0.40741006E-01 0.40592642E-01 0.40444697E-01 - 0.40297171E-01 0.40150063E-01 0.40003371E-01 0.39857096E-01 0.39711236E-01 - 0.39565790E-01 0.39420758E-01 0.39276139E-01 0.39131933E-01 0.38988137E-01 - 0.38844752E-01 0.38701777E-01 0.38559210E-01 0.38417052E-01 0.38275301E-01 - 0.38133957E-01 0.37993018E-01 0.37852485E-01 0.37712355E-01 0.37572629E-01 - 0.37433305E-01 0.37294384E-01 0.37155863E-01 0.37017743E-01 0.36880022E-01 - 0.36742699E-01 0.36605775E-01 0.36469248E-01 0.36333117E-01 0.36197381E-01 - 0.36062041E-01 0.35927094E-01 0.35792541E-01 0.35658380E-01 0.35524611E-01 - 0.35391233E-01 0.35258244E-01 0.35125646E-01 0.34993435E-01 0.34861613E-01 - 0.34730178E-01 0.34599129E-01 0.34468465E-01 0.34338187E-01 0.34208292E-01 - 0.34078780E-01 0.33949651E-01 0.33820904E-01 0.33692538E-01 0.33564552E-01 - 0.33436945E-01 0.33309717E-01 0.33182867E-01 0.33056394E-01 0.32930297E-01 - 0.32804576E-01 0.32679230E-01 0.32554258E-01 0.32429660E-01 0.32305434E-01 - 0.32181580E-01 0.32058097E-01 0.31934984E-01 0.31812241E-01 0.31689867E-01 - 0.31567861E-01 0.31446223E-01 0.31324951E-01 0.31204045E-01 0.31083504E-01 - 0.30963328E-01 0.30843515E-01 0.30724065E-01 0.30604978E-01 0.30486251E-01 - 0.30367886E-01 0.30249880E-01 0.30132234E-01 0.30014946E-01 0.29898016E-01 - 0.29781443E-01 0.29665226E-01 0.29549365E-01 0.29433858E-01 0.29318706E-01 - 0.29203907E-01 0.29089460E-01 0.28975365E-01 0.28861622E-01 0.28748229E-01 - 0.28635185E-01 0.28522491E-01 0.28410145E-01 0.28298146E-01 0.28186494E-01 - 0.28075188E-01 0.27964228E-01 0.27853612E-01 0.27743339E-01 0.27633410E-01 - 0.27523824E-01 0.27414579E-01 0.27305675E-01 0.27197112E-01 0.27088887E-01 - 0.26981002E-01 0.26873455E-01 0.26766245E-01 0.26659372E-01 0.26552835E-01 - 0.26446633E-01 0.26340765E-01 0.26235232E-01 0.26130031E-01 0.26025163E-01 - 0.25920626E-01 0.25816421E-01 0.25712545E-01 0.25608999E-01 0.25505782E-01 - 0.25402893E-01 0.25300332E-01 0.25198097E-01 0.25096188E-01 0.24994604E-01 - 0.24893345E-01 0.24792410E-01 0.24691798E-01 0.24591508E-01 0.24491540E-01 - 0.24391893E-01 0.24292567E-01 0.24193560E-01 0.24094872E-01 0.23996502E-01 - 0.23898449E-01 0.23800714E-01 0.23703295E-01 0.23606191E-01 0.23509401E-01 - 0.23412926E-01 0.23316764E-01 0.23220915E-01 0.23125377E-01 0.23030151E-01 - 0.22935236E-01 0.22840630E-01 0.22746333E-01 0.22652345E-01 0.22558664E-01 - 0.22465291E-01 0.22372224E-01 0.22279463E-01 0.22187006E-01 0.22094854E-01 - 0.22003006E-01 0.21911460E-01 0.21820217E-01 0.21729275E-01 0.21638634E-01 - 0.21548294E-01 0.21458252E-01 0.21368510E-01 0.21279066E-01 0.21189919E-01 - 0.21101068E-01 0.21012514E-01 0.20924255E-01 0.20836291E-01 0.20748621E-01 - 0.20661244E-01 0.20574160E-01 0.20487368E-01 0.20400867E-01 0.20314657E-01 - 0.20228737E-01 0.20143106E-01 0.20057763E-01 0.19972708E-01 0.19887941E-01 - 0.19803460E-01 0.19719265E-01 0.19635355E-01 0.19551730E-01 0.19468388E-01 - 0.19385330E-01 0.19302554E-01 0.19220060E-01 0.19137847E-01 0.19055914E-01 - 0.18974262E-01 0.18892888E-01 0.18811793E-01 0.18730976E-01 0.18650436E-01 - 0.18570172E-01 0.18490184E-01 0.18410471E-01 0.18331033E-01 0.18251868E-01 - 0.18172976E-01 0.18094357E-01 0.18016010E-01 0.17937934E-01 0.17860128E-01 - 0.17782592E-01 0.17705326E-01 0.17628327E-01 0.17551597E-01 0.17475133E-01 - 0.17398937E-01 0.17323005E-01 0.17247340E-01 0.17171938E-01 0.17096801E-01 - 0.17021926E-01 0.16947314E-01 0.16872964E-01 0.16798876E-01 0.16725047E-01 - 0.16651479E-01 0.16578170E-01 0.16505119E-01 0.16432327E-01 0.16359792E-01 - 0.16287513E-01 0.16215490E-01 0.16143723E-01 0.16072210E-01 0.16000951E-01 - 0.15929946E-01 0.15859193E-01 0.15788693E-01 0.15718444E-01 0.15648445E-01 - 0.15578697E-01 0.15509198E-01 0.15439948E-01 0.15370946E-01 0.15302192E-01 - 0.15233685E-01 0.15165423E-01 0.15097408E-01 0.15029637E-01 0.14962111E-01 - 0.14894828E-01 0.14827788E-01 0.14760991E-01 0.14694436E-01 0.14628121E-01 - 0.14562047E-01 0.14496213E-01 0.14430618E-01 0.14365261E-01 0.14300142E-01 - 0.14235261E-01 0.14170616E-01 0.14106207E-01 0.14042033E-01 0.13978094E-01 - 0.13914389E-01 0.13850918E-01 0.13787679E-01 0.13724673E-01 0.13661898E-01 - 0.13599354E-01 0.13537040E-01 0.13474955E-01 0.13413100E-01 0.13351473E-01 - 0.13290074E-01 0.13228901E-01 0.13167955E-01 0.13107235E-01 0.13046741E-01 - 0.12986470E-01 0.12926424E-01 0.12866601E-01 0.12807000E-01 0.12747622E-01 - 0.12688465E-01 0.12629529E-01 0.12570813E-01 0.12512316E-01 0.12454038E-01 - 0.12395979E-01 0.12338137E-01 0.12280512E-01 0.12223104E-01 0.12165911E-01 - 0.12108934E-01 0.12052171E-01 0.11995622E-01 0.11939286E-01 0.11883163E-01 - 0.11827251E-01 0.11771552E-01 0.11716063E-01 0.11660784E-01 0.11605715E-01 - 0.11550854E-01 0.11496202E-01 0.11441758E-01 0.11387520E-01 0.11333490E-01 - 0.11279665E-01 0.11226045E-01 0.11172629E-01 0.11119418E-01 0.11066410E-01 - 0.11013605E-01 0.10961002E-01 0.10908600E-01 0.10856399E-01 0.10804399E-01 - 0.10752598E-01 0.10700997E-01 0.10649593E-01 0.10598388E-01 0.10547379E-01 - 0.10496568E-01 0.10445952E-01 0.10395532E-01 0.10345306E-01 0.10295275E-01 - 0.10245437E-01 0.10195792E-01 0.10146339E-01 0.10097078E-01 0.10048008E-01 - 0.99991286E-02 0.99504391E-02 0.99019388E-02 0.98536271E-02 0.98055035E-02 - 0.97575673E-02 0.97098180E-02 0.96622548E-02 0.96148773E-02 0.95676848E-02 - 0.95206767E-02 0.94738523E-02 0.94272112E-02 0.93807526E-02 0.93344761E-02 - 0.92883808E-02 0.92424664E-02 0.91967321E-02 0.91511773E-02 0.91058015E-02 - 0.90606041E-02 0.90155844E-02 0.89707418E-02 0.89260758E-02 0.88815857E-02 - 0.88372709E-02 0.87931309E-02 0.87491650E-02 0.87053726E-02 0.86617531E-02 - 0.86183060E-02 0.85750305E-02 0.85319262E-02 0.84889924E-02 0.84462285E-02 - 0.84036340E-02 0.83612081E-02 0.83189504E-02 0.82768601E-02 0.82349368E-02 - 0.81931798E-02 0.81515886E-02 0.81101624E-02 0.80689008E-02 0.80278030E-02 - 0.79868686E-02 0.79460970E-02 0.79054874E-02 0.78650394E-02 0.78247523E-02 - 0.77846255E-02 0.77446585E-02 0.77048506E-02 0.76652013E-02 0.76257099E-02 - 0.75863758E-02 0.75471985E-02 0.75081773E-02 0.74693117E-02 0.74306011E-02 - 0.73920448E-02 0.73536423E-02 0.73153930E-02 0.72772962E-02 0.72393514E-02 - 0.72015580E-02 0.71639154E-02 0.71264230E-02 0.70890802E-02 0.70518864E-02 - 0.70148410E-02 0.69779435E-02 0.69411931E-02 0.69045894E-02 0.68681317E-02 - 0.68318194E-02 0.67956520E-02 0.67596289E-02 0.67237494E-02 0.66880129E-02 - 0.66524190E-02 0.66169669E-02 0.65816561E-02 0.65464859E-02 0.65114559E-02 - 0.64765654E-02 0.64418138E-02 0.64072005E-02 0.63727249E-02 0.63383865E-02 - 0.63041846E-02 0.62701186E-02 0.62361880E-02 0.62023922E-02 0.61687305E-02 - 0.61352024E-02 0.61018073E-02 0.60685446E-02 0.60354136E-02 0.60024139E-02 - 0.59695448E-02 0.59368058E-02 0.59041961E-02 0.58717154E-02 0.58393628E-02 - 0.58071380E-02 0.57750402E-02 0.57430688E-02 0.57112234E-02 0.56795033E-02 - 0.56479079E-02 0.56164365E-02 0.55850888E-02 0.55538639E-02 0.55227615E-02 - 0.54917807E-02 0.54609212E-02 0.54301822E-02 0.53995632E-02 0.53690637E-02 - 0.53386829E-02 0.53084204E-02 0.52782755E-02 0.52482477E-02 0.52183363E-02 - 0.51885408E-02 0.51588606E-02 0.51292951E-02 0.50998437E-02 0.50705059E-02 - 0.50412810E-02 0.50121684E-02 0.49831676E-02 0.49542781E-02 0.49254991E-02 - 0.48968301E-02 0.48682706E-02 0.48398200E-02 0.48114776E-02 0.47832429E-02 - 0.47551153E-02 0.47270942E-02 0.46991791E-02 0.46713693E-02 0.46436644E-02 - 0.46160636E-02 0.45885665E-02 0.45611724E-02 0.45338808E-02 0.45066910E-02 - 0.44796026E-02 0.44526150E-02 0.44257275E-02 0.43989396E-02 0.43722507E-02 - 0.43456603E-02 0.43191677E-02 0.42927725E-02 0.42664740E-02 0.42402716E-02 - 0.42141649E-02 0.41881532E-02 0.41622359E-02 0.41364126E-02 0.41106826E-02 - 0.40850454E-02 0.40595004E-02 0.40340470E-02 0.40086848E-02 0.39834131E-02 - 0.39582313E-02 0.39331390E-02 0.39081356E-02 0.38832205E-02 0.38583932E-02 - 0.38336531E-02 0.38089996E-02 0.37844323E-02 0.37599506E-02 0.37355540E-02 - 0.37112419E-02 0.36870137E-02 0.36628689E-02 0.36388071E-02 0.36148276E-02 - 0.35909300E-02 0.35671137E-02 0.35433782E-02 0.35197229E-02 0.34961474E-02 - 0.34726512E-02 0.34492336E-02 0.34258943E-02 0.34026326E-02 0.33794481E-02 - 0.33563403E-02 0.33333087E-02 0.33103528E-02 0.32874721E-02 0.32646661E-02 - 0.32419343E-02 0.32192762E-02 0.31966914E-02 0.31741793E-02 0.31517396E-02 - 0.31293716E-02 0.31070751E-02 0.30848494E-02 0.30626943E-02 0.30406091E-02 - 0.30185934E-02 0.29966469E-02 0.29747690E-02 0.29529594E-02 0.29312175E-02 - 0.29095431E-02 0.28879356E-02 0.28663946E-02 0.28449198E-02 0.28235107E-02 - 0.28021670E-02 0.27808882E-02 0.27596740E-02 0.27385239E-02 0.27174377E-02 - 0.26964149E-02 0.26754552E-02 0.26545583E-02 0.26337237E-02 0.26129511E-02 - 0.25922403E-02 0.25715909E-02 0.25510025E-02 0.25304749E-02 0.25100078E-02 - 0.24896008E-02 0.24692537E-02 0.24489662E-02 0.24287380E-02 0.24085689E-02 - 0.23884587E-02 0.23684070E-02 0.23484137E-02 0.23284784E-02 0.23086011E-02 - 0.22887816E-02 0.22690195E-02 0.22493147E-02 0.22296671E-02 0.22100765E-02 - 0.21905428E-02 0.21710657E-02 0.21516452E-02 0.21322812E-02 0.21129735E-02 - 0.20937220E-02 0.20745268E-02 0.20553876E-02 0.20363045E-02 0.20172774E-02 - 0.19983062E-02 0.19793910E-02 0.19605317E-02 0.19417284E-02 0.19229811E-02 - 0.19042897E-02 0.18856544E-02 0.18670752E-02 0.18485523E-02 0.18300856E-02 - 0.18116753E-02 0.17933215E-02 0.17750244E-02 0.17567841E-02 0.17386008E-02 - 0.17204747E-02 0.17024059E-02 0.16843947E-02 0.16664414E-02 0.16485461E-02 - 0.16307092E-02 0.16129309E-02 0.15952115E-02 0.15775514E-02 0.15599509E-02 - 0.15424104E-02 0.15249301E-02 0.15075106E-02 0.14901522E-02 0.14728553E-02 - 0.14556204E-02 0.14384480E-02 0.14213385E-02 0.14042925E-02 0.13873104E-02 - 0.13703928E-02 0.13535403E-02 0.13367534E-02 0.13200327E-02 0.13033788E-02 - 0.12867925E-02 0.12702742E-02 0.12538247E-02 0.12374447E-02 0.12211349E-02 - 0.12048960E-02 0.11887287E-02 0.11726338E-02 0.11566122E-02 0.11406645E-02 - 0.11247916E-02 0.11089944E-02 0.10932737E-02 0.10776304E-02 0.10620653E-02 - 0.10465793E-02 0.10311735E-02 0.10158486E-02 0.10006058E-02 0.98544583E-03 - 0.97036982E-03 0.95537873E-03 0.94047357E-03 0.92565537E-03 0.91092518E-03 - 0.89628404E-03 0.88173303E-03 0.86727322E-03 0.85290571E-03 0.83863159E-03 - 0.82445198E-03 0.81036800E-03 0.79638078E-03 0.78249145E-03 0.76870117E-03 - 0.75501108E-03 0.74142234E-03 0.72793612E-03 0.71455358E-03 0.70127590E-03 - 0.68810424E-03 0.67503979E-03 0.66208371E-03 0.64923718E-03 0.63650137E-03 - 0.62387746E-03 0.61136660E-03 0.59896996E-03 0.58668870E-03 0.57452395E-03 - 0.56247687E-03 0.55054858E-03 0.53874020E-03 0.52705283E-03 0.51548757E-03 - 0.50404550E-03 0.49272768E-03 0.48153515E-03 0.47046894E-03 0.45953006E-03 - 0.44871949E-03 0.43803819E-03 0.42748709E-03 0.41706712E-03 0.40677915E-03 - 0.39662404E-03 0.38660261E-03 0.37671566E-03 0.36696395E-03 0.35734821E-03 - 0.34786912E-03 0.33852734E-03 0.32932349E-03 0.32025813E-03 0.31133181E-03 - 0.30254501E-03 0.29389819E-03 0.28539174E-03 0.27702602E-03 0.26880133E-03 - 0.26071795E-03 0.25277607E-03 0.24497585E-03 0.23731740E-03 0.22980077E-03 - 0.22242597E-03 0.21519292E-03 0.20810153E-03 0.20115161E-03 0.19434296E-03 - 0.18767527E-03 0.18114820E-03 0.17476136E-03 0.16851428E-03 0.16240643E-03 - 0.15643725E-03 0.15060607E-03 0.14491220E-03 0.13935488E-03 0.13393328E-03 - 0.12864652E-03 0.12349364E-03 0.11847365E-03 0.11358549E-03 0.10882802E-03 - 0.10420007E-03 0.99700406E-04 0.95327728E-04 0.91080688E-04 0.86957882E-04 - 0.82957852E-04 0.79079090E-04 0.75320035E-04 0.71679078E-04 0.68154561E-04 - 0.64744783E-04 0.61447995E-04 0.58262408E-04 0.55186190E-04 0.52217473E-04 - 0.49354351E-04 0.46594883E-04 0.43937097E-04 0.41378989E-04 0.38918529E-04 - 0.36553661E-04 0.34282306E-04 0.32102364E-04 0.30011719E-04 0.28008237E-04 - 0.26089773E-04 0.24254170E-04 0.22499266E-04 0.20822892E-04 0.19222876E-04 - 0.17697049E-04 0.16243241E-04 0.14859290E-04 0.13543042E-04 0.12292351E-04 - 0.11105087E-04 0.99791342E-05 0.89123930E-05 0.79027858E-05 0.69482564E-05 - 0.60467735E-05 0.51963320E-05 0.43949557E-05 0.36406989E-05 0.29316482E-05 - 0.22659245E-05 0.16416844E-05 0.10571218E-05 0.51046941E-06 0.00000000E+00 - 0.22206215E-01 0.22672190E-01 0.23138164E-01 0.23604139E-01 0.24070113E-01 - 0.24536088E-01 0.25002062E-01 0.25468037E-01 0.25934011E-01 0.26399986E-01 - 0.26865960E-01 0.27331935E-01 0.27797909E-01 0.28263884E-01 0.28729858E-01 - 0.29195832E-01 0.29661807E-01 0.30127781E-01 0.30593756E-01 0.31059730E-01 - 0.31525705E-01 0.31991679E-01 0.32457654E-01 0.32923628E-01 0.33389603E-01 - 0.33855577E-01 0.34321552E-01 0.34787526E-01 0.35253501E-01 0.35719475E-01 - 0.36185450E-01 0.36651424E-01 0.37117399E-01 0.37583373E-01 0.38049348E-01 - 0.38515322E-01 0.38981297E-01 0.39447271E-01 0.39913246E-01 0.40379220E-01 - 0.40845194E-01 0.41311169E-01 0.41777143E-01 0.42243118E-01 0.42709092E-01 - 0.43175067E-01 0.43641041E-01 0.44107016E-01 0.44572990E-01 0.45038965E-01 - 0.45504939E-01 0.45970914E-01 0.46436888E-01 0.46902863E-01 0.47368837E-01 - 0.47834812E-01 0.48300786E-01 0.48766761E-01 0.49232735E-01 0.49698710E-01 - 0.50164684E-01 0.50630659E-01 0.51096633E-01 0.51562607E-01 0.52028582E-01 - 0.52494556E-01 0.52960531E-01 0.53426505E-01 0.53892480E-01 0.54358454E-01 - 0.54824429E-01 0.55290403E-01 0.55756378E-01 0.56222352E-01 0.56688327E-01 - 0.57154301E-01 0.57620276E-01 0.58086250E-01 0.58552225E-01 0.59018199E-01 - 0.59484174E-01 0.59950148E-01 0.60416123E-01 0.60882097E-01 0.61348072E-01 - 0.61814046E-01 0.62280021E-01 0.62745995E-01 0.63211969E-01 0.63677944E-01 - 0.64143918E-01 0.64609893E-01 0.65075867E-01 0.65541842E-01 0.66007816E-01 - 0.66473791E-01 0.66939765E-01 0.67405740E-01 0.67871714E-01 0.68337689E-01 - 0.68803663E-01 0.69269638E-01 0.69735612E-01 0.70201587E-01 0.70667561E-01 - 0.71133536E-01 0.71599510E-01 0.72065485E-01 0.72531459E-01 0.72997434E-01 - 0.73463408E-01 0.73929383E-01 0.74395357E-01 0.74861331E-01 0.75327306E-01 - 0.75793280E-01 0.76259255E-01 0.76725229E-01 0.77191204E-01 0.77657178E-01 - 0.78123153E-01 0.78589127E-01 0.79055102E-01 0.79521076E-01 0.79987051E-01 - 0.80453025E-01 0.80919000E-01 0.81384974E-01 0.81850949E-01 0.82316923E-01 - 0.82782898E-01 0.83248872E-01 0.83714847E-01 0.84180821E-01 0.84646796E-01 - 0.85112770E-01 0.85578744E-01 0.86044719E-01 0.86510693E-01 0.86976668E-01 - 0.87442642E-01 0.87908617E-01 0.88374591E-01 0.88840566E-01 0.89306540E-01 - 0.89772515E-01 0.90238489E-01 0.90704464E-01 0.91170438E-01 0.91636413E-01 - 0.92102387E-01 0.92568362E-01 0.93034336E-01 0.93500311E-01 0.93966285E-01 - 0.94432260E-01 0.94898234E-01 0.95364209E-01 0.95830183E-01 0.96296158E-01 - 0.96762132E-01 0.97228106E-01 0.97694081E-01 0.98160055E-01 0.98626030E-01 - 0.99092004E-01 0.99557979E-01 0.10002395E+00 0.10048993E+00 0.10095590E+00 - 0.10142188E+00 0.10188785E+00 0.10235383E+00 0.10281980E+00 0.10328577E+00 - 0.10375175E+00 0.10421772E+00 0.10468370E+00 0.10514967E+00 0.10561565E+00 - 0.10608162E+00 0.10654760E+00 0.10701357E+00 0.10747955E+00 0.10794552E+00 - 0.10841149E+00 0.10887747E+00 0.10934344E+00 0.10980942E+00 0.11027539E+00 - 0.11074137E+00 0.11120734E+00 0.11167332E+00 0.11213929E+00 0.11260526E+00 - 0.11307124E+00 0.11353721E+00 0.11400319E+00 0.11446916E+00 0.11493514E+00 - 0.11540111E+00 0.11586709E+00 0.11633306E+00 0.11679903E+00 0.11726501E+00 - 0.11773098E+00 0.11819696E+00 0.11866293E+00 0.11912891E+00 0.11959488E+00 - 0.12006086E+00 0.12052683E+00 0.12099280E+00 0.12145878E+00 0.12192475E+00 - 0.12239073E+00 0.12285670E+00 0.12332268E+00 0.12378865E+00 0.12425463E+00 - 0.12472060E+00 0.12518658E+00 0.12565255E+00 0.12611852E+00 0.12658450E+00 - 0.12705047E+00 0.12751645E+00 0.12798242E+00 0.12844840E+00 0.12891437E+00 - 0.12938035E+00 0.12984632E+00 0.13031229E+00 0.13077827E+00 0.13124424E+00 - 0.13171022E+00 0.13217619E+00 0.13264217E+00 0.13310814E+00 0.13357412E+00 - 0.13404009E+00 0.13450606E+00 0.13497204E+00 0.13543801E+00 0.13590399E+00 - 0.13636996E+00 0.13683594E+00 0.13730191E+00 0.13776789E+00 0.13823386E+00 - 0.13869984E+00 0.13916581E+00 0.13963178E+00 0.14009776E+00 0.14056373E+00 - 0.14102971E+00 0.14149568E+00 0.14196166E+00 0.14242763E+00 0.14289361E+00 - 0.14335958E+00 0.14382555E+00 0.14429153E+00 0.14475750E+00 0.14522348E+00 - 0.14568945E+00 0.14615543E+00 0.14662140E+00 0.14708738E+00 0.14755335E+00 - 0.14801932E+00 0.14848530E+00 0.14895127E+00 0.14941725E+00 0.14988322E+00 - 0.15034920E+00 0.15081517E+00 0.15128115E+00 0.15174712E+00 0.15221310E+00 - 0.15267907E+00 0.15314504E+00 0.15361102E+00 0.15407699E+00 0.15454297E+00 - 0.15500894E+00 0.15547492E+00 0.15594089E+00 0.15640687E+00 0.15687284E+00 - 0.15733881E+00 0.15780479E+00 0.15827076E+00 0.15873674E+00 0.15920271E+00 - 0.15966869E+00 0.16013466E+00 0.16060064E+00 0.16106661E+00 0.16153258E+00 - 0.16199856E+00 0.16246453E+00 0.16293051E+00 0.16339648E+00 0.16386246E+00 - 0.16432843E+00 0.16479441E+00 0.16526038E+00 0.16572635E+00 0.16619233E+00 - 0.16665830E+00 0.16712428E+00 0.16759025E+00 0.16805623E+00 0.16852220E+00 - 0.16898818E+00 0.16945415E+00 0.16992013E+00 0.17038610E+00 0.17085207E+00 - 0.17131805E+00 0.17178402E+00 0.17225000E+00 0.17271597E+00 0.17318195E+00 - 0.17364792E+00 0.17411390E+00 0.17457987E+00 0.17504584E+00 0.17551182E+00 - 0.17597779E+00 0.17644377E+00 0.17690974E+00 0.17737572E+00 0.17784169E+00 - 0.17830767E+00 0.17877364E+00 0.17923961E+00 0.17970559E+00 0.18017156E+00 - 0.18063754E+00 0.18110351E+00 0.18156949E+00 0.18203546E+00 0.18250144E+00 - 0.18296741E+00 0.18343339E+00 0.18389936E+00 0.18436533E+00 0.18483131E+00 - 0.18529728E+00 0.18576326E+00 0.18622923E+00 0.18669521E+00 0.18716118E+00 - 0.18762716E+00 0.18809313E+00 0.18855910E+00 0.18902508E+00 0.18949105E+00 - 0.18995703E+00 0.19042300E+00 0.19088898E+00 0.19135495E+00 0.19182093E+00 - 0.19228690E+00 0.19275287E+00 0.19321885E+00 0.19368482E+00 0.19415080E+00 - 0.19461677E+00 0.19508275E+00 0.19554872E+00 0.19601470E+00 0.19648067E+00 - 0.19694665E+00 0.19741262E+00 0.19787859E+00 0.19834457E+00 0.19881054E+00 - 0.19927652E+00 0.19974249E+00 0.20020847E+00 0.20067444E+00 0.20114042E+00 - 0.20160639E+00 0.20207236E+00 0.20253834E+00 0.20300431E+00 0.20347029E+00 - 0.20393626E+00 0.20440224E+00 0.20486821E+00 0.20533419E+00 0.20580016E+00 - 0.20626613E+00 0.20673211E+00 0.20719808E+00 0.20766406E+00 0.20813003E+00 - 0.20859601E+00 0.20906198E+00 0.20952796E+00 0.20999393E+00 0.21045990E+00 - 0.21092588E+00 0.21139185E+00 0.21185783E+00 0.21232380E+00 0.21278978E+00 - 0.21325575E+00 0.21372173E+00 0.21418770E+00 0.21465368E+00 0.21511965E+00 - 0.21558562E+00 0.21605160E+00 0.21651757E+00 0.21698355E+00 0.21744952E+00 - 0.21791550E+00 0.21838147E+00 0.21884745E+00 0.21931342E+00 0.21977939E+00 - 0.22024537E+00 0.22071134E+00 0.22117732E+00 0.22164329E+00 0.22210927E+00 - 0.22257524E+00 0.22304122E+00 0.22350719E+00 0.22397316E+00 0.22443914E+00 - 0.22490511E+00 0.22537109E+00 0.22583706E+00 0.22630304E+00 0.22676901E+00 - 0.22723499E+00 0.22770096E+00 0.22816694E+00 0.22863291E+00 0.22909888E+00 - 0.22956486E+00 0.23003083E+00 0.23049681E+00 0.23096278E+00 0.23142876E+00 - 0.23189473E+00 0.23236071E+00 0.23282668E+00 0.23329265E+00 0.23375863E+00 - 0.23422460E+00 0.23469058E+00 0.23515655E+00 0.23562253E+00 0.23608850E+00 - 0.23655448E+00 0.23702045E+00 0.23748642E+00 0.23795240E+00 0.23841837E+00 - 0.23888435E+00 0.23935032E+00 0.23981630E+00 0.24028227E+00 0.24074825E+00 - 0.24121422E+00 0.24168020E+00 0.24214617E+00 0.24261214E+00 0.24307812E+00 - 0.24354409E+00 0.24401007E+00 0.24447604E+00 0.24494202E+00 0.24540799E+00 - 0.24587397E+00 0.24633994E+00 0.24680591E+00 0.24727189E+00 0.24773786E+00 - 0.24820384E+00 0.24866981E+00 0.24913579E+00 0.24960176E+00 0.25006774E+00 - 0.25053371E+00 0.25099968E+00 0.25146566E+00 0.25193163E+00 0.25239761E+00 - 0.25286358E+00 0.25332956E+00 0.25379553E+00 0.25426151E+00 0.25472748E+00 - 0.25519345E+00 0.25565943E+00 0.25612540E+00 0.25659138E+00 0.25705735E+00 - 0.25752333E+00 0.25798930E+00 0.25845528E+00 0.25892125E+00 0.25938723E+00 - 0.25985320E+00 0.26031917E+00 0.26078515E+00 0.26125112E+00 0.26171710E+00 - 0.26218307E+00 0.26264905E+00 0.26311502E+00 0.26358100E+00 0.26404697E+00 - 0.26451294E+00 0.26497892E+00 0.26544489E+00 0.26591087E+00 0.26637684E+00 - 0.26684282E+00 0.26730879E+00 0.26777477E+00 0.26824074E+00 0.26870671E+00 - 0.26917269E+00 0.26963866E+00 0.27010464E+00 0.27057061E+00 0.27103659E+00 - 0.27150256E+00 0.27196854E+00 0.27243451E+00 0.27290049E+00 0.27336646E+00 - 0.27383243E+00 0.27429841E+00 0.27476438E+00 0.27523036E+00 0.27569633E+00 - 0.27616231E+00 0.27662828E+00 0.27709426E+00 0.27756023E+00 0.27802620E+00 - 0.27849218E+00 0.27895815E+00 0.27942413E+00 0.27989010E+00 0.28035608E+00 - 0.28082205E+00 0.28128803E+00 0.28175400E+00 0.28221997E+00 0.28268595E+00 - 0.28315192E+00 0.28361790E+00 0.28408387E+00 0.28454985E+00 0.28501582E+00 - 0.28548180E+00 0.28594777E+00 0.28641375E+00 0.28687972E+00 0.28734569E+00 - 0.28781167E+00 0.28827764E+00 0.28874362E+00 0.28920959E+00 0.28967557E+00 - 0.29014154E+00 0.29060752E+00 0.29107349E+00 0.29153946E+00 0.29200544E+00 - 0.29247141E+00 0.29293739E+00 0.29340336E+00 0.29386934E+00 0.29433531E+00 - 0.29480129E+00 0.29526726E+00 0.29573323E+00 0.29619921E+00 0.29666518E+00 - 0.29713116E+00 0.29759713E+00 0.29806311E+00 0.29852908E+00 0.29899506E+00 - 0.29946103E+00 0.29992701E+00 0.30039298E+00 0.30085895E+00 0.30132493E+00 - 0.30179090E+00 0.30225688E+00 0.30272285E+00 0.30318883E+00 0.30365480E+00 - 0.30412078E+00 0.30458675E+00 0.30505272E+00 0.30551870E+00 0.30598467E+00 - 0.30645065E+00 0.30691662E+00 0.30738260E+00 0.30784857E+00 0.30831455E+00 - 0.30878052E+00 0.30924649E+00 0.30971247E+00 0.31017844E+00 0.31064442E+00 - 0.31111039E+00 0.31157637E+00 0.31204234E+00 0.31250832E+00 0.31297429E+00 - 0.31344026E+00 0.31390624E+00 0.31437221E+00 0.31483819E+00 0.31530416E+00 - 0.31577014E+00 0.31623611E+00 0.31670209E+00 0.31716806E+00 0.31763404E+00 - 0.31810001E+00 0.31856598E+00 0.31903196E+00 0.31949793E+00 0.31996391E+00 - 0.32042988E+00 0.32089586E+00 0.32136183E+00 0.32182781E+00 0.32229378E+00 - 0.32275975E+00 0.32322573E+00 0.32369170E+00 0.32415768E+00 0.32462365E+00 - 0.32508963E+00 0.32555560E+00 0.32602158E+00 0.32648755E+00 0.32695352E+00 - 0.32741950E+00 0.32788547E+00 0.32835145E+00 0.32881742E+00 0.32928340E+00 - 0.32974937E+00 0.33021535E+00 0.33068132E+00 0.33114730E+00 0.33161327E+00 - 0.33207924E+00 0.33254522E+00 0.33301119E+00 0.33347717E+00 0.33394314E+00 - 0.33440912E+00 0.33487509E+00 0.33534107E+00 0.33580704E+00 0.33627301E+00 - 0.33673899E+00 0.33720496E+00 0.33767094E+00 0.33813691E+00 0.33860289E+00 - 0.33906886E+00 0.33953484E+00 0.34000081E+00 0.34046678E+00 0.34093276E+00 - 0.34139873E+00 0.34186471E+00 0.34233068E+00 0.34279666E+00 0.34326263E+00 - 0.34372861E+00 0.34419458E+00 0.34466056E+00 0.34512653E+00 0.34559250E+00 - 0.34605848E+00 0.34652445E+00 0.34699043E+00 0.34745640E+00 0.34792238E+00 - 0.34838835E+00 0.34885433E+00 0.34932030E+00 0.34978627E+00 0.35025225E+00 - 0.35071822E+00 0.35118420E+00 0.35165017E+00 0.35211615E+00 0.35258212E+00 - 0.35304810E+00 0.35351407E+00 0.35398004E+00 0.35444602E+00 0.35491199E+00 - 0.35537797E+00 0.35584394E+00 0.35630992E+00 0.35677589E+00 0.35724187E+00 - 0.35770784E+00 0.35817381E+00 0.35863979E+00 0.35910576E+00 0.35957174E+00 - 0.36003771E+00 0.36050369E+00 0.36096966E+00 0.36143564E+00 0.36190161E+00 - 0.36236759E+00 0.36283356E+00 0.36329953E+00 0.36376551E+00 0.36423148E+00 - 0.36469746E+00 0.36516343E+00 0.36562941E+00 0.36609538E+00 0.36656136E+00 - 0.36702733E+00 0.36749330E+00 0.36795928E+00 0.36842525E+00 0.36889123E+00 - 0.36935720E+00 0.36982318E+00 0.37028915E+00 0.37075513E+00 0.37122110E+00 - 0.37168707E+00 0.37215305E+00 0.37261902E+00 0.37308500E+00 0.37355097E+00 - 0.37401695E+00 0.37448292E+00 0.37494890E+00 0.37541487E+00 0.37588085E+00 - 0.37634682E+00 0.37681279E+00 0.37727877E+00 0.37774474E+00 0.37821072E+00 - 0.37867669E+00 0.37914267E+00 0.37960864E+00 0.38007462E+00 0.38054059E+00 - 0.38100656E+00 0.38147254E+00 0.38193851E+00 0.38240449E+00 0.38287046E+00 - 0.38333644E+00 0.38380241E+00 0.38426839E+00 0.38473436E+00 0.38520033E+00 - 0.38566631E+00 0.38613228E+00 0.38659826E+00 0.38706423E+00 0.38753021E+00 - 0.38799618E+00 0.38846216E+00 0.38892813E+00 0.38939411E+00 0.38986008E+00 - 0.39032605E+00 0.39079203E+00 0.39125800E+00 0.39172398E+00 0.39218995E+00 - 0.39265593E+00 0.39312190E+00 0.39358788E+00 0.39405385E+00 0.39451982E+00 - 0.39498580E+00 0.39545177E+00 0.39591775E+00 0.39638372E+00 0.39684970E+00 - 0.39731567E+00 0.39778165E+00 0.39824762E+00 0.39871359E+00 0.39917957E+00 - 0.39964554E+00 0.40011152E+00 0.40057749E+00 0.40104347E+00 0.40150944E+00 - 0.40197542E+00 0.40244139E+00 0.40290736E+00 0.40337334E+00 0.40383931E+00 - 0.40430529E+00 0.40477126E+00 0.40523724E+00 0.40570321E+00 0.40616919E+00 - 0.40663516E+00 0.40710114E+00 0.40756711E+00 0.40803308E+00 0.40849906E+00 - 0.40896503E+00 0.40943101E+00 0.40989698E+00 0.41036296E+00 0.41082893E+00 - 0.41129491E+00 0.41176088E+00 0.41222685E+00 0.41269283E+00 0.41315880E+00 - 0.41362478E+00 0.41409075E+00 0.41455673E+00 0.41502270E+00 0.41548868E+00 - 0.41595465E+00 0.41642062E+00 0.41688660E+00 0.41735257E+00 0.41781855E+00 - 0.41828452E+00 0.41875050E+00 0.41921647E+00 0.41968245E+00 0.42014842E+00 - 0.42061440E+00 0.42108037E+00 0.42154634E+00 0.42201232E+00 0.42247829E+00 - 0.42294427E+00 0.42341024E+00 0.42387622E+00 0.42434219E+00 0.42480817E+00 - 0.42527414E+00 0.42574011E+00 0.42620609E+00 0.42667206E+00 0.42713804E+00 - 0.42760401E+00 0.42806999E+00 0.42853596E+00 0.42900194E+00 0.42946791E+00 - 0.42993388E+00 0.43039986E+00 0.43086583E+00 0.43133181E+00 0.43179778E+00 - 0.43226376E+00 0.43272973E+00 0.43319571E+00 0.43366168E+00 0.43412766E+00 - 0.43459363E+00 0.43505960E+00 0.43552558E+00 0.43599155E+00 0.43645753E+00 - 0.43692350E+00 0.43738948E+00 0.43785545E+00 0.43832143E+00 0.43878740E+00 - 0.43925337E+00 0.43971935E+00 0.44018532E+00 0.44065130E+00 0.44111727E+00 - 0.44158325E+00 0.44204922E+00 0.44251520E+00 0.44298117E+00 0.44344714E+00 - 0.44391312E+00 0.44437909E+00 0.44484507E+00 0.44531104E+00 0.44577702E+00 - 0.44624299E+00 0.44670897E+00 0.44717494E+00 0.44764091E+00 0.44810689E+00 - 0.44857286E+00 0.44903884E+00 0.44950481E+00 0.44997079E+00 0.45043676E+00 - 0.45090274E+00 0.45136871E+00 0.45183469E+00 0.45230066E+00 0.45276663E+00 - 0.45323261E+00 0.45369858E+00 0.45416456E+00 0.45463053E+00 0.45509651E+00 - 0.45556248E+00 0.45602846E+00 0.45649443E+00 0.45696040E+00 0.45742638E+00 - 0.45789235E+00 0.45835833E+00 0.45882430E+00 0.45929028E+00 0.45975625E+00 - 0.46022223E+00 0.46068820E+00 0.46115417E+00 0.46162015E+00 0.46208612E+00 - 0.46255210E+00 0.46301807E+00 0.46348405E+00 0.46395002E+00 0.46441600E+00 - 0.46488197E+00 0.46534795E+00 0.46581392E+00 0.46627989E+00 0.46674587E+00 - 0.46721184E+00 0.46767782E+00 0.46814379E+00 0.46860977E+00 0.46907574E+00 - 0.46954172E+00 0.47000769E+00 0.47047366E+00 0.47093964E+00 0.47140561E+00 - 0.47187159E+00 0.47233756E+00 0.47280354E+00 0.47326951E+00 0.47373549E+00 - 0.47420146E+00 0.47466743E+00 0.47513341E+00 0.47559938E+00 0.47606536E+00 - 0.47653133E+00 0.47699731E+00 0.47746328E+00 0.47792926E+00 0.47839523E+00 - 0.47886121E+00 0.47932718E+00 0.47979315E+00 0.48025913E+00 0.48072510E+00 - 0.48119108E+00 0.48165705E+00 0.48212303E+00 0.48258900E+00 0.48305498E+00 - 0.48352095E+00 0.48398692E+00 0.48445290E+00 0.48491887E+00 0.48538485E+00 - 0.48585082E+00 0.48631680E+00 0.48678277E+00 0.48724875E+00 0.48771472E+00 - 0.48818069E+00 0.48864667E+00 0.48911264E+00 0.48957862E+00 0.49004459E+00 - 0.49051057E+00 0.49097654E+00 0.49144252E+00 0.49190849E+00 0.49237446E+00 - 0.49284044E+00 0.49330641E+00 0.49377239E+00 0.49423836E+00 0.49470434E+00 - 0.49517031E+00 0.49563629E+00 0.49610226E+00 0.49656824E+00 0.49703421E+00 - 0.49750018E+00 0.49796616E+00 0.49843213E+00 0.49889811E+00 0.49936408E+00 - 0.49983006E+00 0.50029603E+00 0.50076201E+00 0.50122798E+00 0.50169395E+00 - 0.50215993E+00 0.50262590E+00 0.50309188E+00 0.50355785E+00 0.50402383E+00 - 0.50448980E+00 0.50495578E+00 0.50542175E+00 0.50588772E+00 0.50635370E+00 - 0.50681967E+00 0.50728565E+00 0.50775162E+00 0.50821760E+00 0.50868357E+00 - 0.50914955E+00 0.50961552E+00 0.51008150E+00 0.51054747E+00 0.51101344E+00 - 0.51147942E+00 0.51194539E+00 0.51241137E+00 0.51287734E+00 0.51334332E+00 - 0.51380929E+00 0.51427527E+00 0.51474124E+00 0.51520721E+00 0.51567319E+00 - 0.51613916E+00 0.51660514E+00 0.51707111E+00 0.51753709E+00 0.51800306E+00 - 0.51846904E+00 0.51893501E+00 0.51940098E+00 0.51986696E+00 0.52033293E+00 - 0.52079891E+00 0.52126488E+00 0.52173086E+00 0.52219683E+00 0.52266281E+00 - 0.52312878E+00 0.52359476E+00 0.52406073E+00 0.52452670E+00 0.52499268E+00 - 0.52545865E+00 0.52592463E+00 0.52639060E+00 0.52685658E+00 0.52732255E+00 - 0.52778853E+00 0.52825450E+00 0.52872047E+00 0.52918645E+00 0.52965242E+00 - 0.53011840E+00 0.53058437E+00 0.53105035E+00 0.53151632E+00 0.53198230E+00 - 0.53244827E+00 0.53291424E+00 0.53338022E+00 0.53384619E+00 0.53431217E+00 - 0.53477814E+00 0.53524412E+00 0.53571009E+00 0.53617607E+00 0.53664204E+00 - 0.53710801E+00 0.53757399E+00 0.53803996E+00 0.53850594E+00 0.53897191E+00 - 0.53943789E+00 0.53990386E+00 0.54036984E+00 0.54083581E+00 0.54130179E+00 - 0.54176776E+00 0.54223373E+00 0.54269971E+00 0.54316568E+00 0.54363166E+00 - 0.54409763E+00 0.54456361E+00 0.54502958E+00 0.54549556E+00 0.54596153E+00 - 0.54642750E+00 0.54689348E+00 0.54735945E+00 0.54782543E+00 0.54829140E+00 - 0.54875738E+00 0.54922335E+00 0.54968933E+00 0.55015530E+00 0.55062127E+00 - 0.55108725E+00 0.55155322E+00 0.55201920E+00 0.55248517E+00 0.55295115E+00 - 0.55341712E+00 0.55388310E+00 0.55434907E+00 0.55481505E+00 0.55528102E+00 - 0.55574699E+00 0.55621297E+00 0.55667894E+00 0.55714492E+00 0.55761089E+00 - 0.55807687E+00 0.55854284E+00 0.55900882E+00 0.55947479E+00 0.55994076E+00 - 0.56040674E+00 0.56087271E+00 0.56133869E+00 0.56180466E+00 0.56227064E+00 - 0.56273661E+00 0.56320259E+00 0.56366856E+00 0.56413453E+00 0.56460051E+00 - 0.56506648E+00 0.56553246E+00 0.56599843E+00 0.56646441E+00 0.56693038E+00 - 0.56739636E+00 0.56786233E+00 0.56832830E+00 0.56879428E+00 0.56926025E+00 - 0.56972623E+00 0.57019220E+00 0.57065818E+00 0.57112415E+00 0.57159013E+00 - 0.57205610E+00 0.57252208E+00 0.57298805E+00 0.57345402E+00 0.57392000E+00 - 0.57438597E+00 0.57485195E+00 0.57531792E+00 0.57578390E+00 0.57624987E+00 - 0.57671585E+00 0.57718182E+00 0.57764779E+00 0.57811377E+00 0.57857974E+00 - 0.57904572E+00 0.57951169E+00 0.57997767E+00 0.58044364E+00 0.58090962E+00 - 0.58137559E+00 0.58184156E+00 0.58230754E+00 0.58277351E+00 0.58323949E+00 - 0.58370546E+00 0.58417144E+00 0.58463741E+00 0.58510339E+00 0.58556936E+00 - 0.58603534E+00 0.58650131E+00 0.58696728E+00 0.58743326E+00 0.58789923E+00 - 0.58836521E+00 0.58883118E+00 0.58929716E+00 0.58976313E+00 0.59022911E+00 - 0.59069508E+00 0.59116105E+00 0.59162703E+00 0.59209300E+00 0.59255898E+00 - 0.59302495E+00 0.59349093E+00 0.59395690E+00 0.59442288E+00 0.59488885E+00 - 0.59535482E+00 0.59582080E+00 0.59628677E+00 0.59675275E+00 0.59721872E+00 - 0.59768470E+00 0.59815067E+00 0.59861665E+00 0.59908262E+00 0.59954860E+00 - 0.60001457E+00 0.60048054E+00 0.60094652E+00 0.60141249E+00 0.60187847E+00 - 0.60234444E+00 0.60281042E+00 0.60327639E+00 0.60374237E+00 0.60420834E+00 - 0.60467431E+00 0.60514029E+00 0.60560626E+00 0.60607224E+00 0.60653821E+00 - 0.60700419E+00 0.60747016E+00 0.60793614E+00 0.60840211E+00 0.60886808E+00 - 0.60933406E+00 0.60980003E+00 0.61026601E+00 0.61073198E+00 0.61119796E+00 - 0.61166393E+00 0.61212991E+00 0.61259588E+00 0.61306185E+00 0.61352783E+00 - 0.61399380E+00 0.61445978E+00 0.61492575E+00 0.61539173E+00 0.61585770E+00 - 0.61632368E+00 0.61678965E+00 0.61725563E+00 0.61772160E+00 0.61818757E+00 - 0.61865355E+00 0.61911952E+00 0.61958550E+00 0.62005147E+00 0.62051745E+00 - 0.62098342E+00 0.62144940E+00 0.62191537E+00 0.62238134E+00 0.62284732E+00 - 0.62331329E+00 0.62377927E+00 0.62424524E+00 0.62471122E+00 0.62517719E+00 - 0.62564317E+00 0.62610914E+00 0.62657511E+00 0.62704109E+00 0.62750706E+00 - 0.62797304E+00 0.62843901E+00 0.62890499E+00 0.62937096E+00 0.62983694E+00 - 0.63030291E+00 0.63076889E+00 0.63123486E+00 0.63170083E+00 0.63216681E+00 - 0.63263278E+00 0.63309876E+00 0.63356473E+00 0.63403071E+00 0.63449668E+00 - 0.63496266E+00 0.63542863E+00 0.63589460E+00 0.63636058E+00 0.63682655E+00 - 0.63729253E+00 0.63775850E+00 0.63822448E+00 0.63869045E+00 0.63915643E+00 - 0.63962240E+00 0.64008837E+00 0.64055435E+00 0.64102032E+00 0.64148630E+00 - 0.64195227E+00 0.64241825E+00 0.64288422E+00 0.64335020E+00 0.64381617E+00 - 0.64428214E+00 0.64474812E+00 0.64521409E+00 0.64568007E+00 0.64614604E+00 - 0.64661202E+00 0.64707799E+00 0.64754397E+00 0.64800994E+00 0.64847592E+00 - 0.64894189E+00 0.64940786E+00 0.64987384E+00 0.65033981E+00 0.65080579E+00 - 0.65127176E+00 0.65173774E+00 0.65220371E+00 0.65266969E+00 0.65313566E+00 - 0.65360163E+00 0.65406761E+00 0.65453358E+00 0.65499956E+00 0.65546553E+00 - 0.65593151E+00 0.65639748E+00 0.65686346E+00 0.65732943E+00 0.65779540E+00 - 0.65826138E+00 0.65872735E+00 0.65919333E+00 0.65965930E+00 0.66012528E+00 - 0.66059125E+00 0.66105723E+00 0.66152320E+00 0.66198918E+00 0.66245515E+00 - 0.66292112E+00 0.66338710E+00 0.66385307E+00 0.66431905E+00 0.66478502E+00 - 0.66525100E+00 0.66571697E+00 0.66618295E+00 0.66664892E+00 0.66711489E+00 - 0.66758087E+00 0.66804684E+00 0.66851282E+00 0.66897879E+00 0.66944477E+00 - 0.66991074E+00 0.67037672E+00 0.67084269E+00 0.67130866E+00 0.67177464E+00 - 0.67224061E+00 0.67270659E+00 0.67317256E+00 0.67363854E+00 0.67410451E+00 - 0.67457049E+00 0.67503646E+00 0.67550244E+00 0.67596841E+00 0.67643438E+00 - 0.67690036E+00 0.67736633E+00 0.67783231E+00 0.67829828E+00 0.67876426E+00 - 0.67923023E+00 0.67969621E+00 0.68016218E+00 0.68062815E+00 0.68109413E+00 - 0.68156010E+00 0.68202608E+00 0.68249205E+00 0.68295803E+00 0.68342400E+00 - 0.68388998E+00 0.68435595E+00 0.68482192E+00 0.68528790E+00 0.68575387E+00 - 0.68621985E+00 0.68668582E+00 0.68715180E+00 0.68761777E+00 0.68808375E+00 - 0.68854972E+00 0.68901569E+00 0.68948167E+00 0.68994764E+00 0.69041362E+00 - 0.69087959E+00 0.69134557E+00 0.69181154E+00 0.69227752E+00 0.69274349E+00 - 0.69320947E+00 0.69367544E+00 0.69414141E+00 0.69460739E+00 0.69507336E+00 - 0.69553934E+00 0.69600531E+00 0.69647129E+00 0.69693726E+00 0.69740324E+00 - 0.69786921E+00 0.69833518E+00 0.69880116E+00 0.69926713E+00 0.69973311E+00 - 0.70019908E+00 0.70066506E+00 0.70113103E+00 0.70159701E+00 0.70206298E+00 - 0.70252895E+00 0.70299493E+00 0.70346090E+00 0.70392688E+00 0.70439285E+00 - 0.70485883E+00 0.70532480E+00 0.70579078E+00 0.70625675E+00 0.70672272E+00 - 0.70718870E+00 0.70765467E+00 0.70812065E+00 0.70858662E+00 0.70905260E+00 - 0.70951857E+00 0.70998455E+00 0.71045052E+00 0.71091650E+00 0.71138247E+00 - 0.71184844E+00 0.71231442E+00 0.71278039E+00 0.71324637E+00 0.71371234E+00 - 0.71417832E+00 0.71464429E+00 0.71511027E+00 0.71557624E+00 0.71604221E+00 - 0.71650819E+00 0.71697416E+00 0.71744014E+00 0.71790611E+00 0.71837209E+00 - 0.71883806E+00 0.71930404E+00 0.71977001E+00 0.72023598E+00 0.72070196E+00 - 0.72116793E+00 0.72163391E+00 0.72209988E+00 0.72256586E+00 0.72303183E+00 - 0.72349781E+00 0.72396378E+00 0.72442976E+00 0.72489573E+00 0.72536170E+00 - 0.72582768E+00 0.72629365E+00 0.72675963E+00 0.72722560E+00 0.72769158E+00 - 0.72815755E+00 0.72862353E+00 0.72908950E+00 0.72955547E+00 0.73002145E+00 - 0.73048742E+00 0.73095340E+00 0.73141937E+00 0.73188535E+00 0.73235132E+00 - 0.73281730E+00 0.73328327E+00 0.73374924E+00 0.73421522E+00 0.73468119E+00 - 0.73514717E+00 0.73561314E+00 0.73607912E+00 0.73654509E+00 0.73701107E+00 - 0.73747704E+00 0.73794301E+00 0.73840899E+00 0.73887496E+00 0.73934094E+00 - 0.73980691E+00 0.74027289E+00 0.74073886E+00 0.74120484E+00 0.74167081E+00 - 0.74213679E+00 0.74260276E+00 0.74306873E+00 0.74353471E+00 0.74400068E+00 - 0.74446666E+00 0.74493263E+00 0.74539861E+00 0.74586458E+00 0.74633056E+00 - 0.74679653E+00 0.74726250E+00 0.74772848E+00 0.74819445E+00 0.74866043E+00 - 0.74912640E+00 0.74959238E+00 0.75005835E+00 0.75052433E+00 0.75099030E+00 - 0.75145627E+00 0.75192225E+00 0.75238822E+00 0.75285420E+00 0.75332017E+00 - 0.75378615E+00 0.75425212E+00 0.75471810E+00 0.75518407E+00 0.75565004E+00 - 0.75611602E+00 0.75658199E+00 0.75704797E+00 0.75751394E+00 0.75797992E+00 - 0.75844589E+00 0.75891187E+00 0.75937784E+00 0.75984382E+00 0.76030979E+00 - 0.76077576E+00 0.76124174E+00 0.76170771E+00 0.76217369E+00 0.76263966E+00 - 0.76310564E+00 0.76357161E+00 0.76403759E+00 0.76450356E+00 0.76496953E+00 - 0.76543551E+00 0.76590148E+00 0.76636746E+00 0.76683343E+00 0.76729941E+00 - 0.76776538E+00 0.76823136E+00 0.76869733E+00 0.76916330E+00 0.76962928E+00 - 0.77009525E+00 0.77056123E+00 0.77102720E+00 0.77149318E+00 0.77195915E+00 - 0.77242513E+00 0.77289110E+00 0.77335707E+00 0.77382305E+00 0.77428902E+00 - 0.77475500E+00 0.77522097E+00 0.77568695E+00 0.77615292E+00 0.77661890E+00 - 0.77708487E+00 0.77755085E+00 0.77801682E+00 0.77848279E+00 0.77894877E+00 - 0.77941474E+00 0.77988072E+00 0.78034669E+00 0.78081267E+00 0.78127864E+00 - 0.78174462E+00 0.78221059E+00 0.78267656E+00 0.78314254E+00 0.78360851E+00 - 0.78407449E+00 0.78454046E+00 0.78500644E+00 0.78547241E+00 0.78593839E+00 - 0.78640436E+00 0.78687033E+00 0.78733631E+00 0.78780228E+00 0.78826826E+00 - 0.78873423E+00 0.78920021E+00 0.78966618E+00 0.79013216E+00 0.79059813E+00 - 0.79106410E+00 0.79153008E+00 0.79199605E+00 0.79246203E+00 0.79292800E+00 - 0.79339398E+00 0.79385995E+00 0.79432593E+00 0.79479190E+00 0.79525787E+00 - 0.79572385E+00 0.79618982E+00 0.79665580E+00 0.79712177E+00 0.79758775E+00 - 0.79805372E+00 0.79851970E+00 0.79898567E+00 0.79945165E+00 0.79991762E+00 - 0.80038359E+00 0.80084957E+00 0.80131554E+00 0.80178152E+00 0.80224749E+00 - 0.80271347E+00 0.80317944E+00 0.80364542E+00 0.80411139E+00 0.80457736E+00 - 0.80504334E+00 0.80550931E+00 0.80597529E+00 0.80644126E+00 0.80690724E+00 - 0.80737321E+00 0.80783919E+00 0.80830516E+00 0.80877113E+00 0.80923711E+00 - 0.80970308E+00 0.81016906E+00 0.81063503E+00 0.81110101E+00 0.81156698E+00 - 0.81203296E+00 0.81249893E+00 0.81296490E+00 0.81343088E+00 0.81389685E+00 - 0.81436283E+00 0.81482880E+00 0.81529478E+00 0.81576075E+00 0.81622673E+00 - 0.81669270E+00 0.81715867E+00 0.81762465E+00 0.81809062E+00 0.81855660E+00 - 0.81902257E+00 0.81948855E+00 0.81995452E+00 0.82042050E+00 0.82088647E+00 - 0.82135244E+00 0.82181842E+00 0.82228439E+00 0.82275037E+00 0.82321634E+00 - 0.82368232E+00 0.82414829E+00 0.82461427E+00 0.82508024E+00 0.82554621E+00 - 0.82601219E+00 0.82647816E+00 0.82694414E+00 0.82741011E+00 0.82787609E+00 - 0.82834206E+00 0.82880804E+00 0.82927401E+00 0.82973998E+00 0.83020596E+00 - 0.83067193E+00 0.83113791E+00 0.83160388E+00 0.83206986E+00 0.83253583E+00 - 0.83300181E+00 0.83346778E+00 0.83393375E+00 0.83439973E+00 0.83486570E+00 - 0.83533168E+00 0.83579765E+00 0.83626363E+00 0.83672960E+00 0.83719557E+00 - 0.83766155E+00 0.83812752E+00 0.83859350E+00 0.83905947E+00 0.83952545E+00 - 0.83999142E+00 0.84045740E+00 0.84092337E+00 0.84138934E+00 0.84185532E+00 - 0.84232129E+00 0.84278727E+00 0.84325324E+00 0.84371922E+00 0.84418519E+00 - 0.84465116E+00 0.84511714E+00 0.84558311E+00 0.84604909E+00 0.84651506E+00 - 0.84698104E+00 0.84744701E+00 0.84791298E+00 0.84837896E+00 0.84884493E+00 - 0.84931091E+00 0.84977688E+00 0.85024286E+00 0.85070883E+00 0.85117480E+00 - 0.85164078E+00 0.85210675E+00 0.85257273E+00 0.85303870E+00 0.85350467E+00 - 0.85397065E+00 0.85443662E+00 0.85490259E+00 0.85536857E+00 0.85583454E+00 - 0.85630052E+00 0.85676649E+00 0.85723246E+00 0.85769843E+00 0.85816441E+00 - 0.85863038E+00 0.85909635E+00 0.85956232E+00 0.86002829E+00 0.86049426E+00 - 0.86096023E+00 0.86142619E+00 0.86189215E+00 0.86235810E+00 0.86282402E+00 - 0.86328984E+00 0.86372164E+00 0.86372532E+00 0.86372546E+00 0.86372550E+00 - 0.86372553E+00 0.86372554E+00 0.86372555E+00 0.86372556E+00 0.86372556E+00 - 0.86372557E+00 0.86372557E+00 0.86372557E+00 0.86372558E+00 0.86372558E+00 - 0.86372558E+00 0.86372558E+00 0.86372558E+00 0.86372558E+00 0.86372558E+00 - 0.86372558E+00 0.86372559E+00 0.86372559E+00 0.86372559E+00 0.86372559E+00 - 0.86372559E+00 0.86372559E+00 0.86372559E+00 0.86372559E+00 0.86372559E+00 - 0.86372559E+00 0.86372559E+00 0.86372559E+00 0.86372559E+00 0.86372559E+00 - 0.86372559E+00 0.86372559E+00 0.86372559E+00 0.86372559E+00 0.86372559E+00 - 0.86372559E+00 0.86372559E+00 0.86372559E+00 0.86372559E+00 0.86372559E+00 - 0.86372559E+00 0.86372559E+00 0.86372559E+00 0.86372559E+00 0.86372559E+00 - 0.86372559E+00 0.86372559E+00 0.86372559E+00 0.86372559E+00 0.86372559E+00 - 0.86372559E+00 0.86372559E+00 0.86372559E+00 0.86372559E+00 0.86372559E+00 - 0.86372560E+00 0.86372560E+00 0.86372560E+00 0.86372560E+00 0.86372560E+00 - 0.86372560E+00 0.86372560E+00 0.86372560E+00 0.86372560E+00 0.86372560E+00 - 0.86372560E+00 0.86372560E+00 0.86372560E+00 0.86372560E+00 0.86372560E+00 - 0.86372560E+00 0.86372560E+00 0.86372560E+00 0.86372560E+00 0.86372560E+00 - 0.86372560E+00 0.86372560E+00 0.86372560E+00 0.86372560E+00 0.86372560E+00 - 0.86372560E+00 0.86372560E+00 0.86372560E+00 0.86372560E+00 0.86372560E+00 - 0.86372560E+00 0.86372560E+00 0.86372560E+00 0.86372560E+00 0.86372560E+00 - 0.86372560E+00 0.86372560E+00 0.86372560E+00 0.86372560E+00 0.86372560E+00 - 0.86372560E+00 0.86372560E+00 0.86372560E+00 0.86372560E+00 0.86372560E+00 - 0.86372560E+00 0.86372560E+00 0.86372560E+00 0.86372560E+00 0.86372560E+00 - 0.86372560E+00 0.86372560E+00 0.86372560E+00 0.86372560E+00 0.86372560E+00 - 0.86372560E+00 0.86372560E+00 0.86372560E+00 0.86372560E+00 0.86372560E+00 - 0.86372560E+00 0.86372560E+00 0.86372560E+00 0.86372560E+00 0.86372560E+00 - 0.86372560E+00 0.86372560E+00 0.86372560E+00 0.86372560E+00 0.86372560E+00 - 0.86372560E+00 0.86372560E+00 0.86372560E+00 0.86372560E+00 0.86372560E+00 - 0.86372560E+00 0.86372560E+00 0.86372560E+00 0.86372560E+00 0.86372560E+00 - 0.86372560E+00 0.86372560E+00 0.86372560E+00 0.86372560E+00 0.86372560E+00 - 0.86372560E+00 0.86372560E+00 0.86372560E+00 0.86372560E+00 0.86372560E+00 - 0.86372560E+00 0.86372560E+00 0.86372560E+00 0.86372560E+00 0.86372560E+00 - 0.86372560E+00 0.86372560E+00 0.86372560E+00 0.86372560E+00 0.86372560E+00 - 0.86372560E+00 0.86372560E+00 0.86372560E+00 0.86372560E+00 0.86372560E+00 - 0.86372560E+00 0.86372560E+00 0.86372560E+00 0.86372560E+00 0.86372560E+00 - 0.86372560E+00 0.86372560E+00 0.86372560E+00 0.86372560E+00 0.86372560E+00 - 0.86372560E+00 0.86372560E+00 0.86372560E+00 0.86372560E+00 0.86372560E+00 - 0.86372560E+00 0.86372560E+00 0.86372560E+00 0.86372560E+00 0.86372560E+00 - 0.86372560E+00 0.86372560E+00 0.86372560E+00 0.86372560E+00 0.86372560E+00 - 0.86372560E+00 0.86372560E+00 0.86372560E+00 0.86372560E+00 0.86372560E+00 - 0.10909710E+00 0.10944794E+00 0.10979877E+00 0.11014961E+00 0.11050045E+00 - 0.11085128E+00 0.11120212E+00 0.11155295E+00 0.11190379E+00 0.11225463E+00 - 0.11260546E+00 0.11295630E+00 0.11330713E+00 0.11365797E+00 0.11400880E+00 - 0.11435964E+00 0.11471048E+00 0.11506131E+00 0.11541215E+00 0.11576298E+00 - 0.11611382E+00 0.11646466E+00 0.11681549E+00 0.11716633E+00 0.11751716E+00 - 0.11786800E+00 0.11821883E+00 0.11856967E+00 0.11892051E+00 0.11927134E+00 - 0.11962218E+00 0.11997301E+00 0.12032385E+00 0.12067469E+00 0.12102552E+00 - 0.12137636E+00 0.12172719E+00 0.12207803E+00 0.12242886E+00 0.12277970E+00 - 0.12313054E+00 0.12348137E+00 0.12383221E+00 0.12418304E+00 0.12453388E+00 - 0.12488472E+00 0.12523555E+00 0.12558639E+00 0.12593722E+00 0.12628806E+00 - 0.12663889E+00 0.12698973E+00 0.12734057E+00 0.12769140E+00 0.12804224E+00 - 0.12839307E+00 0.12874391E+00 0.12909475E+00 0.12944558E+00 0.12979642E+00 - 0.13014725E+00 0.13049809E+00 0.13084893E+00 0.13119976E+00 0.13155060E+00 - 0.13190143E+00 0.13225227E+00 0.13260310E+00 0.13295394E+00 0.13330478E+00 - 0.13365561E+00 0.13400645E+00 0.13435728E+00 0.13470812E+00 0.13505896E+00 - 0.13540979E+00 0.13576063E+00 0.13611146E+00 0.13646230E+00 0.13681313E+00 - 0.13716397E+00 0.13751481E+00 0.13786564E+00 0.13821648E+00 0.13856731E+00 - 0.13891815E+00 0.13926899E+00 0.13961982E+00 0.13997066E+00 0.14032149E+00 - 0.14067233E+00 0.14102316E+00 0.14137400E+00 0.14172484E+00 0.14207567E+00 - 0.14242651E+00 0.14277734E+00 0.14312818E+00 0.14347902E+00 0.14382985E+00 - 0.14418069E+00 0.14453152E+00 0.14488236E+00 0.14523319E+00 0.14558403E+00 - 0.14593487E+00 0.14628570E+00 0.14663654E+00 0.14698737E+00 0.14733821E+00 - 0.14768905E+00 0.14803988E+00 0.14839072E+00 0.14874155E+00 0.14909239E+00 - 0.14944322E+00 0.14979406E+00 0.15014490E+00 0.15049573E+00 0.15084657E+00 - 0.15119740E+00 0.15154824E+00 0.15189908E+00 0.15224991E+00 0.15260075E+00 - 0.15295158E+00 0.15330242E+00 0.15365325E+00 0.15400409E+00 0.15435493E+00 - 0.15470576E+00 0.15505660E+00 0.15540743E+00 0.15575827E+00 0.15610911E+00 - 0.15645994E+00 0.15681078E+00 0.15716161E+00 0.15751245E+00 0.15786328E+00 - 0.15821412E+00 0.15856496E+00 0.15891579E+00 0.15926663E+00 0.15961746E+00 - 0.15996830E+00 0.16031914E+00 0.16066997E+00 0.16102081E+00 0.16137164E+00 - 0.16172248E+00 0.16207331E+00 0.16242415E+00 0.16277499E+00 0.16312582E+00 - 0.16347666E+00 0.16382749E+00 0.16417833E+00 0.16452917E+00 0.16488000E+00 - 0.16523084E+00 0.16558167E+00 0.16593251E+00 0.16628334E+00 0.16663418E+00 - 0.16698502E+00 0.16733585E+00 0.16768669E+00 0.16803752E+00 0.16838836E+00 - 0.16873920E+00 0.16909003E+00 0.16944087E+00 0.16979170E+00 0.17014254E+00 - 0.17049337E+00 0.17084421E+00 0.17119505E+00 0.17154588E+00 0.17189672E+00 - 0.17224755E+00 0.17259839E+00 0.17294923E+00 0.17330006E+00 0.17365090E+00 - 0.17400173E+00 0.17435257E+00 0.17470340E+00 0.17505424E+00 0.17540508E+00 - 0.17575591E+00 0.17610675E+00 0.17645758E+00 0.17680842E+00 0.17715926E+00 - 0.17751009E+00 0.17786093E+00 0.17821176E+00 0.17856260E+00 0.17891343E+00 - 0.17926427E+00 0.17961511E+00 0.17996594E+00 0.18031678E+00 0.18066761E+00 - 0.18101845E+00 0.18136929E+00 0.18172012E+00 0.18207096E+00 0.18242179E+00 - 0.18277263E+00 0.18312346E+00 0.18347430E+00 0.18382514E+00 0.18417597E+00 - 0.18452681E+00 0.18487764E+00 0.18522848E+00 0.18557932E+00 0.18593015E+00 - 0.18628099E+00 0.18663182E+00 0.18698266E+00 0.18733350E+00 0.18768433E+00 - 0.18803517E+00 0.18838600E+00 0.18873684E+00 0.18908767E+00 0.18943851E+00 - 0.18978935E+00 0.19014018E+00 0.19049102E+00 0.19084185E+00 0.19119269E+00 - 0.19154353E+00 0.19189436E+00 0.19224520E+00 0.19259603E+00 0.19294687E+00 - 0.19329770E+00 0.19364854E+00 0.19399938E+00 0.19435021E+00 0.19470105E+00 - 0.19505188E+00 0.19540272E+00 0.19575356E+00 0.19610439E+00 0.19645523E+00 - 0.19680606E+00 0.19715690E+00 0.19750773E+00 0.19785857E+00 0.19820941E+00 - 0.19856024E+00 0.19891108E+00 0.19926191E+00 0.19961275E+00 0.19996359E+00 - 0.20031442E+00 0.20066526E+00 0.20101609E+00 0.20136693E+00 0.20171776E+00 - 0.20206860E+00 0.20241944E+00 0.20277027E+00 0.20312111E+00 0.20347194E+00 - 0.20382278E+00 0.20417362E+00 0.20452445E+00 0.20487529E+00 0.20522612E+00 - 0.20557696E+00 0.20592779E+00 0.20627863E+00 0.20662947E+00 0.20698030E+00 - 0.20733114E+00 0.20768197E+00 0.20803281E+00 0.20838365E+00 0.20873448E+00 - 0.20908532E+00 0.20943615E+00 0.20978699E+00 0.21013782E+00 0.21048866E+00 - 0.21083950E+00 0.21119033E+00 0.21154117E+00 0.21189200E+00 0.21224284E+00 - 0.21259368E+00 0.21294451E+00 0.21329535E+00 0.21364618E+00 0.21399702E+00 - 0.21434785E+00 0.21469869E+00 0.21504953E+00 0.21540036E+00 0.21575120E+00 - 0.21610203E+00 0.21645287E+00 0.21680371E+00 0.21715454E+00 0.21750538E+00 - 0.21785621E+00 0.21820705E+00 0.21855788E+00 0.21890872E+00 0.21925956E+00 - 0.21961039E+00 0.21996123E+00 0.22031206E+00 0.22066290E+00 0.22101374E+00 - 0.22136457E+00 0.22171541E+00 0.22206624E+00 0.22241708E+00 0.22276791E+00 - 0.22311875E+00 0.22346959E+00 0.22382042E+00 0.22417126E+00 0.22452209E+00 - 0.22487293E+00 0.22522377E+00 0.22557460E+00 0.22592544E+00 0.22627627E+00 - 0.22662711E+00 0.22697794E+00 0.22732878E+00 0.22767962E+00 0.22803045E+00 - 0.22838129E+00 0.22873212E+00 0.22908296E+00 0.22943380E+00 0.22978463E+00 - 0.23013547E+00 0.23048630E+00 0.23083714E+00 0.23118797E+00 0.23153881E+00 - 0.23188965E+00 0.23224048E+00 0.23259132E+00 0.23294215E+00 0.23329299E+00 - 0.23364383E+00 0.23399466E+00 0.23434550E+00 0.23469633E+00 0.23504717E+00 - 0.23539800E+00 0.23574884E+00 0.23609968E+00 0.23645051E+00 0.23680135E+00 - 0.23715218E+00 0.23750302E+00 0.23785386E+00 0.23820469E+00 0.23855553E+00 - 0.23890636E+00 0.23925720E+00 0.23960803E+00 0.23995887E+00 0.24030971E+00 - 0.24066054E+00 0.24101138E+00 0.24136221E+00 0.24171305E+00 0.24206389E+00 - 0.24241472E+00 0.24276556E+00 0.24311639E+00 0.24346723E+00 0.24381806E+00 - 0.24416890E+00 0.24451974E+00 0.24487057E+00 0.24522141E+00 0.24557224E+00 - 0.24592308E+00 0.24627392E+00 0.24662475E+00 0.24697559E+00 0.24732642E+00 - 0.24767726E+00 0.24802810E+00 0.24837893E+00 0.24872977E+00 0.24908060E+00 - 0.24943144E+00 0.24978227E+00 0.25013311E+00 0.25048395E+00 0.25083478E+00 - 0.25118562E+00 0.25153645E+00 0.25188729E+00 0.25223813E+00 0.25258896E+00 - 0.25293980E+00 0.25329063E+00 0.25364147E+00 0.25399230E+00 0.25434314E+00 - 0.25469398E+00 0.25504481E+00 0.25539565E+00 0.25574648E+00 0.25609732E+00 - 0.25644816E+00 0.25679899E+00 0.25714983E+00 0.25750066E+00 0.25785150E+00 - 0.25820233E+00 0.25855317E+00 0.25890401E+00 0.25925484E+00 0.25960568E+00 - 0.25995651E+00 0.26030735E+00 0.26065819E+00 0.26100902E+00 0.26135986E+00 - 0.26171069E+00 0.26206153E+00 0.26241236E+00 0.26276320E+00 0.26311404E+00 - 0.26346487E+00 0.26381571E+00 0.26416654E+00 0.26451738E+00 0.26486822E+00 - 0.26521905E+00 0.26556989E+00 0.26592072E+00 0.26627156E+00 0.26662239E+00 - 0.26697323E+00 0.26732407E+00 0.26767490E+00 0.26802574E+00 0.26837657E+00 - 0.26872741E+00 0.26907825E+00 0.26942908E+00 0.26977992E+00 0.27013075E+00 - 0.27048159E+00 0.27083242E+00 0.27118326E+00 0.27153410E+00 0.27188493E+00 - 0.27223577E+00 0.27258660E+00 0.27293744E+00 0.27328828E+00 0.27363911E+00 - 0.27398995E+00 0.27434078E+00 0.27469162E+00 0.27504245E+00 0.27539329E+00 - 0.27574413E+00 0.27609496E+00 0.27644580E+00 0.27679663E+00 0.27714747E+00 - 0.27749831E+00 0.27784914E+00 0.27819998E+00 0.27855081E+00 0.27890165E+00 - 0.27925248E+00 0.27960332E+00 0.27995416E+00 0.28030499E+00 0.28065583E+00 - 0.28100666E+00 0.28135750E+00 0.28170834E+00 0.28205917E+00 0.28241001E+00 - 0.28276084E+00 0.28311168E+00 0.28346251E+00 0.28381335E+00 0.28416419E+00 - 0.28451502E+00 0.28486586E+00 0.28521669E+00 0.28556753E+00 0.28591837E+00 - 0.28626920E+00 0.28662004E+00 0.28697087E+00 0.28732171E+00 0.28767254E+00 - 0.28802338E+00 0.28837422E+00 0.28872505E+00 0.28907589E+00 0.28942672E+00 - 0.28977756E+00 0.29012840E+00 0.29047923E+00 0.29083007E+00 0.29118090E+00 - 0.29153174E+00 0.29188257E+00 0.29223341E+00 0.29258425E+00 0.29293508E+00 - 0.29328592E+00 0.29363675E+00 0.29398759E+00 0.29433843E+00 0.29468926E+00 - 0.29504010E+00 0.29539093E+00 0.29574177E+00 0.29609260E+00 0.29644344E+00 - 0.29679428E+00 0.29714511E+00 0.29749595E+00 0.29784678E+00 0.29819762E+00 - 0.29854846E+00 0.29889929E+00 0.29925013E+00 0.29960096E+00 0.29995180E+00 - 0.30030263E+00 0.30065347E+00 0.30100431E+00 0.30135514E+00 0.30170598E+00 - 0.30205681E+00 0.30240765E+00 0.30275849E+00 0.30310932E+00 0.30346016E+00 - 0.30381099E+00 0.30416183E+00 0.30451267E+00 0.30486350E+00 0.30521434E+00 - 0.30556517E+00 0.30591601E+00 0.30626684E+00 0.30661768E+00 0.30696852E+00 - 0.30731935E+00 0.30767019E+00 0.30802102E+00 0.30837186E+00 0.30872270E+00 - 0.30907353E+00 0.30942437E+00 0.30977520E+00 0.31012604E+00 0.31047687E+00 - 0.31082771E+00 0.31117855E+00 0.31152938E+00 0.31188022E+00 0.31223105E+00 - 0.31258189E+00 0.31293273E+00 0.31328356E+00 0.31363440E+00 0.31398523E+00 - 0.31433607E+00 0.31468690E+00 0.31503774E+00 0.31538858E+00 0.31573941E+00 - 0.31609025E+00 0.31644108E+00 0.31679192E+00 0.31714276E+00 0.31749359E+00 - 0.31784443E+00 0.31819526E+00 0.31854610E+00 0.31889693E+00 0.31924777E+00 - 0.31959861E+00 0.31994944E+00 0.32030028E+00 0.32065111E+00 0.32100195E+00 - 0.32135279E+00 0.32170362E+00 0.32205446E+00 0.32240529E+00 0.32275613E+00 - 0.32310696E+00 0.32345780E+00 0.32380864E+00 0.32415947E+00 0.32451031E+00 - 0.32486114E+00 0.32521198E+00 0.32556282E+00 0.32591365E+00 0.32626449E+00 - 0.32661532E+00 0.32696616E+00 0.32731699E+00 0.32766783E+00 0.32801867E+00 - 0.32836950E+00 0.32872034E+00 0.32907117E+00 0.32942201E+00 0.32977285E+00 - 0.33012368E+00 0.33047452E+00 0.33082535E+00 0.33117619E+00 0.33152702E+00 - 0.33187786E+00 0.33222870E+00 0.33257953E+00 0.33293037E+00 0.33328120E+00 - 0.33363204E+00 0.33398288E+00 0.33433371E+00 0.33468455E+00 0.33503538E+00 - 0.33538622E+00 0.33573705E+00 0.33608789E+00 0.33643873E+00 0.33678956E+00 - 0.33714040E+00 0.33749123E+00 0.33784207E+00 0.33819291E+00 0.33854374E+00 - 0.33889458E+00 0.33924541E+00 0.33959625E+00 0.33994708E+00 0.34029792E+00 - 0.34064876E+00 0.34099959E+00 0.34135043E+00 0.34170126E+00 0.34205210E+00 - 0.34240294E+00 0.34275377E+00 0.34310461E+00 0.34345544E+00 0.34380628E+00 - 0.34415711E+00 0.34450795E+00 0.34485879E+00 0.34520962E+00 0.34556046E+00 - 0.34591129E+00 0.34626213E+00 0.34661297E+00 0.34696380E+00 0.34731464E+00 - 0.34766547E+00 0.34801631E+00 0.34836714E+00 0.34871798E+00 0.34906882E+00 - 0.34941965E+00 0.34977049E+00 0.35012132E+00 0.35047216E+00 0.35082300E+00 - 0.35117383E+00 0.35152467E+00 0.35187550E+00 0.35222634E+00 0.35257717E+00 - 0.35292801E+00 0.35327885E+00 0.35362968E+00 0.35398052E+00 0.35433135E+00 - 0.35468219E+00 0.35503303E+00 0.35538386E+00 0.35573470E+00 0.35608553E+00 - 0.35643637E+00 0.35678720E+00 0.35713804E+00 0.35748888E+00 0.35783971E+00 - 0.35819055E+00 0.35854138E+00 0.35889222E+00 0.35924306E+00 0.35959389E+00 - 0.35994473E+00 0.36029556E+00 0.36064640E+00 0.36099723E+00 0.36134807E+00 - 0.36169891E+00 0.36204974E+00 0.36240058E+00 0.36275141E+00 0.36310225E+00 - 0.36345309E+00 0.36380392E+00 0.36415476E+00 0.36450559E+00 0.36485643E+00 - 0.36520726E+00 0.36555810E+00 0.36590894E+00 0.36625977E+00 0.36661061E+00 - 0.36696144E+00 0.36731228E+00 0.36766312E+00 0.36801395E+00 0.36836479E+00 - 0.36871562E+00 0.36906646E+00 0.36941730E+00 0.36976813E+00 0.37011897E+00 - 0.37046980E+00 0.37082064E+00 0.37117147E+00 0.37152231E+00 0.37187315E+00 - 0.37222398E+00 0.37257482E+00 0.37292565E+00 0.37327649E+00 0.37362733E+00 - 0.37397816E+00 0.37432900E+00 0.37467983E+00 0.37503067E+00 0.37538150E+00 - 0.37573234E+00 0.37608318E+00 0.37643401E+00 0.37678485E+00 0.37713568E+00 - 0.37748652E+00 0.37783736E+00 0.37818819E+00 0.37853903E+00 0.37888986E+00 - 0.37924070E+00 0.37959153E+00 0.37994237E+00 0.38029321E+00 0.38064404E+00 - 0.38099488E+00 0.38134571E+00 0.38169655E+00 0.38204739E+00 0.38239822E+00 - 0.38274906E+00 0.38309989E+00 0.38345073E+00 0.38380156E+00 0.38415240E+00 - 0.38450324E+00 0.38485407E+00 0.38520491E+00 0.38555574E+00 0.38590658E+00 - 0.38625742E+00 0.38660825E+00 0.38695909E+00 0.38730992E+00 0.38766076E+00 - 0.38801159E+00 0.38836243E+00 0.38871327E+00 0.38906410E+00 0.38941494E+00 - 0.38976577E+00 0.39011661E+00 0.39046745E+00 0.39081828E+00 0.39116912E+00 - 0.39151995E+00 0.39187079E+00 0.39222162E+00 0.39257246E+00 0.39292330E+00 - 0.39327413E+00 0.39362497E+00 0.39397580E+00 0.39432664E+00 0.39467748E+00 - 0.39502831E+00 0.39537915E+00 0.39572998E+00 0.39608082E+00 0.39643165E+00 - 0.39678249E+00 0.39713333E+00 0.39748416E+00 0.39783500E+00 0.39818583E+00 - 0.39853667E+00 0.39888751E+00 0.39923834E+00 0.39958918E+00 0.39994001E+00 - 0.40029085E+00 0.40064168E+00 0.40099252E+00 0.40134336E+00 0.40169419E+00 - 0.40204503E+00 0.40239586E+00 0.40274670E+00 0.40309754E+00 0.40344837E+00 - 0.40379921E+00 0.40415004E+00 0.40450088E+00 0.40485171E+00 0.40520255E+00 - 0.40555339E+00 0.40590422E+00 0.40625506E+00 0.40660589E+00 0.40695673E+00 - 0.40730757E+00 0.40765840E+00 0.40800924E+00 0.40836007E+00 0.40871091E+00 - 0.40906174E+00 0.40941258E+00 0.40976342E+00 0.41011425E+00 0.41046509E+00 - 0.41081592E+00 0.41116676E+00 0.41151760E+00 0.41186843E+00 0.41221927E+00 - 0.41257010E+00 0.41292094E+00 0.41327177E+00 0.41362261E+00 0.41397345E+00 - 0.41432428E+00 0.41467512E+00 0.41502595E+00 0.41537679E+00 0.41572763E+00 - 0.41607846E+00 0.41642930E+00 0.41678013E+00 0.41713097E+00 0.41748180E+00 - 0.41783264E+00 0.41818348E+00 0.41853431E+00 0.41888515E+00 0.41923598E+00 - 0.41958682E+00 0.41993766E+00 0.42028849E+00 0.42063933E+00 0.42099016E+00 - 0.42134100E+00 0.42169183E+00 0.42204267E+00 0.42239351E+00 0.42274434E+00 - 0.42309518E+00 0.42344601E+00 0.42379685E+00 0.42414769E+00 0.42449852E+00 - 0.42484936E+00 0.42520019E+00 0.42555103E+00 0.42590186E+00 0.42625270E+00 - 0.42660354E+00 0.42695437E+00 0.42730521E+00 0.42765604E+00 0.42800688E+00 - 0.42835772E+00 0.42870855E+00 0.42905939E+00 0.42941022E+00 0.42976106E+00 - 0.43011190E+00 0.43046273E+00 0.43081357E+00 0.43116440E+00 0.43151524E+00 - 0.43186607E+00 0.43221691E+00 0.43256775E+00 0.43291858E+00 0.43326942E+00 - 0.43362025E+00 0.43397109E+00 0.43432193E+00 0.43467276E+00 0.43502360E+00 - 0.43537443E+00 0.43572527E+00 0.43607610E+00 0.43642694E+00 0.43677778E+00 - 0.43712861E+00 0.43747945E+00 0.43783028E+00 0.43818112E+00 0.43853196E+00 - 0.43888279E+00 0.43923363E+00 0.43958446E+00 0.43993530E+00 0.44028613E+00 - 0.44063697E+00 0.44098781E+00 0.44133864E+00 0.44168948E+00 0.44204031E+00 - 0.44239115E+00 0.44274199E+00 0.44309282E+00 0.44344366E+00 0.44379449E+00 - 0.44414533E+00 0.44449616E+00 0.44484700E+00 0.44519784E+00 0.44554867E+00 - 0.44589951E+00 0.44625034E+00 0.44660118E+00 0.44695202E+00 0.44730285E+00 - 0.44765369E+00 0.44800452E+00 0.44835536E+00 0.44870619E+00 0.44905703E+00 - 0.44940787E+00 0.44975870E+00 0.45010954E+00 0.45046037E+00 0.45081121E+00 - 0.45116205E+00 0.45151288E+00 0.45186372E+00 0.45221455E+00 0.45256539E+00 - 0.45291622E+00 0.45326706E+00 0.45361790E+00 0.45396873E+00 0.45431957E+00 - 0.45467040E+00 0.45502124E+00 0.45537208E+00 0.45572291E+00 0.45607375E+00 - 0.45642458E+00 0.45677542E+00 0.45712625E+00 0.45747709E+00 0.45782793E+00 - 0.45817876E+00 0.45852960E+00 0.45888043E+00 0.45923127E+00 0.45958211E+00 - 0.45993294E+00 0.46028378E+00 0.46063461E+00 0.46098545E+00 0.46133628E+00 - 0.46168712E+00 0.46203796E+00 0.46238879E+00 0.46273963E+00 0.46309046E+00 - 0.46344130E+00 0.46379214E+00 0.46414297E+00 0.46449381E+00 0.46484464E+00 - 0.46519548E+00 0.46554631E+00 0.46589715E+00 0.46624799E+00 0.46659882E+00 - 0.46694966E+00 0.46730049E+00 0.46765133E+00 0.46800217E+00 0.46835300E+00 - 0.46870384E+00 0.46905467E+00 0.46940551E+00 0.46975634E+00 0.47010718E+00 - 0.47045802E+00 0.47080885E+00 0.47115969E+00 0.47151052E+00 0.47186136E+00 - 0.47221220E+00 0.47256303E+00 0.47291387E+00 0.47326470E+00 0.47361554E+00 - 0.47396637E+00 0.47431721E+00 0.47466805E+00 0.47501888E+00 0.47536972E+00 - 0.47572055E+00 0.47607139E+00 0.47642223E+00 0.47677306E+00 0.47712390E+00 - 0.47747473E+00 0.47782557E+00 0.47817640E+00 0.47852724E+00 0.47887808E+00 - 0.47922891E+00 0.47957975E+00 0.47993058E+00 0.48028142E+00 0.48063226E+00 - 0.48098309E+00 0.48133393E+00 0.48168476E+00 0.48203560E+00 0.48238643E+00 - 0.48273727E+00 0.48308811E+00 0.48343894E+00 0.48378978E+00 0.48414061E+00 - 0.48449145E+00 0.48484229E+00 0.48519312E+00 0.48554396E+00 0.48589479E+00 - 0.48624563E+00 0.48659646E+00 0.48694730E+00 0.48729814E+00 0.48764897E+00 - 0.48799981E+00 0.48835064E+00 0.48870148E+00 0.48905232E+00 0.48940315E+00 - 0.48975399E+00 0.49010482E+00 0.49045566E+00 0.49080649E+00 0.49115733E+00 - 0.49150817E+00 0.49185900E+00 0.49220984E+00 0.49256067E+00 0.49291151E+00 - 0.49326235E+00 0.49361318E+00 0.49396402E+00 0.49431485E+00 0.49466569E+00 - 0.49501652E+00 0.49536736E+00 0.49571820E+00 0.49606903E+00 0.49641987E+00 - 0.49677070E+00 0.49712154E+00 0.49747238E+00 0.49782321E+00 0.49817405E+00 - 0.49852488E+00 0.49887572E+00 0.49922655E+00 0.49957739E+00 0.49992823E+00 - 0.50027906E+00 0.50062990E+00 0.50098073E+00 0.50133157E+00 0.50168241E+00 - 0.50203324E+00 0.50238408E+00 0.50273491E+00 0.50308575E+00 0.50343659E+00 - 0.50378742E+00 0.50413826E+00 0.50448909E+00 0.50483993E+00 0.50519076E+00 - 0.50554160E+00 0.50589244E+00 0.50624327E+00 0.50659411E+00 0.50694494E+00 - 0.50729578E+00 0.50764662E+00 0.50799745E+00 0.50834829E+00 0.50869912E+00 - 0.50904996E+00 0.50940079E+00 0.50975163E+00 0.51010247E+00 0.51045330E+00 - 0.51080414E+00 0.51115497E+00 0.51150581E+00 0.51185665E+00 0.51220748E+00 - 0.51255832E+00 0.51290915E+00 0.51325999E+00 0.51361082E+00 0.51396166E+00 - 0.51431250E+00 0.51466333E+00 0.51501417E+00 0.51536500E+00 0.51571584E+00 - 0.51606668E+00 0.51641751E+00 0.51676835E+00 0.51711918E+00 0.51747002E+00 - 0.51782085E+00 0.51817169E+00 0.51852253E+00 0.51887336E+00 0.51922420E+00 - 0.51957503E+00 0.51992587E+00 0.52027671E+00 0.52062754E+00 0.52097838E+00 - 0.52132921E+00 0.52168005E+00 0.52203088E+00 0.52238172E+00 0.52273256E+00 - 0.52308339E+00 0.52343423E+00 0.52378506E+00 0.52413590E+00 0.52448674E+00 - 0.52483757E+00 0.52518841E+00 0.52553924E+00 0.52589008E+00 0.52624091E+00 - 0.52659175E+00 0.52694259E+00 0.52729342E+00 0.52764426E+00 0.52799509E+00 - 0.52834593E+00 0.52869677E+00 0.52904760E+00 0.52939844E+00 0.52974927E+00 - 0.53010011E+00 0.53045094E+00 0.53080178E+00 0.53115262E+00 0.53150345E+00 - 0.53185429E+00 0.53220512E+00 0.53255596E+00 0.53290680E+00 0.53325763E+00 - 0.53360847E+00 0.53395930E+00 0.53431014E+00 0.53466097E+00 0.53501181E+00 - 0.53536265E+00 0.53571348E+00 0.53606432E+00 0.53641515E+00 0.53676599E+00 - 0.53711683E+00 0.53746766E+00 0.53781850E+00 0.53816933E+00 0.53852017E+00 - 0.53887100E+00 0.53922184E+00 0.53957268E+00 0.53992351E+00 0.54027435E+00 - 0.54062518E+00 0.54097602E+00 0.54132686E+00 0.54167769E+00 0.54202853E+00 - 0.54237936E+00 0.54273020E+00 0.54308103E+00 0.54343187E+00 0.54378271E+00 - 0.54413354E+00 0.54448438E+00 0.54483521E+00 0.54518605E+00 0.54553689E+00 - 0.54588772E+00 0.54623856E+00 0.54658939E+00 0.54694023E+00 0.54729106E+00 - 0.54764190E+00 0.54799274E+00 0.54834357E+00 0.54869441E+00 0.54904524E+00 - 0.54939608E+00 0.54974692E+00 0.55009775E+00 0.55044859E+00 0.55079942E+00 - 0.55115026E+00 0.55150109E+00 0.55185193E+00 0.55220277E+00 0.55255360E+00 - 0.55290444E+00 0.55325527E+00 0.55360611E+00 0.55395695E+00 0.55430778E+00 - 0.55465862E+00 0.55500945E+00 0.55536029E+00 0.55571112E+00 0.55606196E+00 - 0.55641280E+00 0.55676363E+00 0.55711447E+00 0.55746530E+00 0.55781614E+00 - 0.55816698E+00 0.55851781E+00 0.55886865E+00 0.55921948E+00 0.55957032E+00 - 0.55992115E+00 0.56027199E+00 0.56062283E+00 0.56097366E+00 0.56132450E+00 - 0.56167533E+00 0.56202617E+00 0.56237701E+00 0.56272784E+00 0.56307868E+00 - 0.56342951E+00 0.56378035E+00 0.56413118E+00 0.56448202E+00 0.56483286E+00 - 0.56518369E+00 0.56553453E+00 0.56588536E+00 0.56623620E+00 0.56658704E+00 - 0.56693787E+00 0.56728871E+00 0.56763954E+00 0.56799038E+00 0.56834121E+00 - 0.56869205E+00 0.56904289E+00 0.56939372E+00 0.56974456E+00 0.57009539E+00 - 0.57044623E+00 0.57079707E+00 0.57114790E+00 0.57149874E+00 0.57184957E+00 - 0.57220041E+00 0.57255124E+00 0.57290208E+00 0.57325292E+00 0.57360375E+00 - 0.57395459E+00 0.57430542E+00 0.57465626E+00 0.57500710E+00 0.57535793E+00 - 0.57570877E+00 0.57605960E+00 0.57641044E+00 0.57676127E+00 0.57711211E+00 - 0.57746295E+00 0.57781378E+00 0.57816462E+00 0.57851545E+00 0.57886629E+00 - 0.57921713E+00 0.57956796E+00 0.57991880E+00 0.58026963E+00 0.58062047E+00 - 0.58097130E+00 0.58132214E+00 0.58167298E+00 0.58202381E+00 0.58237465E+00 - 0.58272548E+00 0.58307632E+00 0.58342716E+00 0.58377799E+00 0.58412883E+00 - 0.58447966E+00 0.58483050E+00 0.58518133E+00 0.58553217E+00 0.58588301E+00 - 0.58623384E+00 0.58658468E+00 0.58693551E+00 0.58728635E+00 0.58763719E+00 - 0.58798802E+00 0.58833886E+00 0.58868969E+00 0.58904053E+00 0.58939136E+00 - 0.58974220E+00 0.59009304E+00 0.59044387E+00 0.59079471E+00 0.59114554E+00 - 0.59149638E+00 0.59184722E+00 0.59219805E+00 0.59254889E+00 0.59289972E+00 - 0.59325056E+00 0.59360139E+00 0.59395223E+00 0.59430307E+00 0.59465390E+00 - 0.59500474E+00 0.59535557E+00 0.59570641E+00 0.59605725E+00 0.59640808E+00 - 0.59675892E+00 0.59710975E+00 0.59746059E+00 0.59781142E+00 0.59816226E+00 - 0.59851310E+00 0.59886393E+00 0.59921477E+00 0.59956560E+00 0.59991644E+00 - 0.60026728E+00 0.60061811E+00 0.60096895E+00 0.60131978E+00 0.60167062E+00 - 0.60202145E+00 0.60237229E+00 0.60272313E+00 0.60307396E+00 0.60342480E+00 - 0.60377563E+00 0.60412647E+00 0.60447731E+00 0.60482814E+00 0.60517898E+00 - 0.60552981E+00 0.60588065E+00 0.60623148E+00 0.60658232E+00 0.60693316E+00 - 0.60728399E+00 0.60763483E+00 0.60798566E+00 0.60833650E+00 0.60868734E+00 - 0.60903817E+00 0.60938901E+00 0.60973984E+00 0.61009068E+00 0.61044151E+00 - 0.61079235E+00 0.61114319E+00 0.61149402E+00 0.61184486E+00 0.61219569E+00 - 0.61254653E+00 0.61289736E+00 0.61324820E+00 0.61359904E+00 0.61394987E+00 - 0.61430071E+00 0.61465154E+00 0.61500238E+00 0.61535322E+00 0.61570405E+00 - 0.61605489E+00 0.61640572E+00 0.61675656E+00 0.61710739E+00 0.61745823E+00 - 0.61780907E+00 0.61815990E+00 0.61851074E+00 0.61886157E+00 0.61921241E+00 - 0.61956325E+00 0.61991408E+00 0.62026492E+00 0.62061575E+00 0.62096659E+00 - 0.62131742E+00 0.62166826E+00 0.62201910E+00 0.62236993E+00 0.62272077E+00 - 0.62307160E+00 0.62342244E+00 0.62377328E+00 0.62412411E+00 0.62447495E+00 - 0.62482578E+00 0.62517662E+00 0.62552745E+00 0.62587829E+00 0.62622913E+00 - 0.62657996E+00 0.62693080E+00 0.62728163E+00 0.62763247E+00 0.62798330E+00 - 0.62833414E+00 0.62868498E+00 0.62903581E+00 0.62938665E+00 0.62973748E+00 - 0.63008832E+00 0.63043916E+00 0.63078999E+00 0.63114083E+00 0.63149166E+00 - 0.63184250E+00 0.63219333E+00 0.63254417E+00 0.63289501E+00 0.63324584E+00 - 0.63359668E+00 0.63394751E+00 0.63429835E+00 0.63464919E+00 0.63500002E+00 - 0.63535086E+00 0.63570169E+00 0.63605253E+00 0.63640336E+00 0.63675420E+00 - 0.63710504E+00 0.63745587E+00 0.63780671E+00 0.63815754E+00 0.63850838E+00 - 0.63885921E+00 0.63921005E+00 0.63956089E+00 0.63991172E+00 0.64026256E+00 - 0.64061339E+00 0.64096423E+00 0.64131506E+00 0.64166590E+00 0.64201674E+00 - 0.64236757E+00 0.64271841E+00 0.64306924E+00 0.64342008E+00 0.64377091E+00 - 0.64412175E+00 0.64447259E+00 0.64482342E+00 0.64517426E+00 0.64552509E+00 - 0.64587593E+00 0.64622676E+00 0.64657760E+00 0.64692844E+00 0.64727927E+00 - 0.64763011E+00 0.64798094E+00 0.64833178E+00 0.64868261E+00 0.64903345E+00 - 0.64938429E+00 0.64973512E+00 0.65008596E+00 0.65043679E+00 0.65078763E+00 - 0.65113846E+00 0.65148930E+00 0.65184013E+00 0.65219097E+00 0.65254180E+00 - 0.65289264E+00 0.65324348E+00 0.65359431E+00 0.65394515E+00 0.65429598E+00 - 0.65464682E+00 0.65499765E+00 0.65534849E+00 0.65569932E+00 0.65605016E+00 - 0.65640099E+00 0.65675183E+00 0.65710266E+00 0.65745349E+00 0.65780433E+00 - 0.65815516E+00 0.65850600E+00 0.65885683E+00 0.65920766E+00 0.65955849E+00 - 0.65990932E+00 0.66026015E+00 0.66061098E+00 0.66096180E+00 0.66131261E+00 - 0.66166339E+00 0.66201411E+00 0.66236386E+00 0.66245334E+00 0.66245360E+00 - 0.66245367E+00 0.66245371E+00 0.66245373E+00 0.66245374E+00 0.66245375E+00 - 0.66245376E+00 0.66245376E+00 0.66245376E+00 0.66245377E+00 0.66245377E+00 - 0.66245377E+00 0.66245377E+00 0.66245378E+00 0.66245378E+00 0.66245378E+00 - 0.66245378E+00 0.66245378E+00 0.66245378E+00 0.66245378E+00 0.66245378E+00 - 0.66245378E+00 0.66245379E+00 0.66245379E+00 0.66245379E+00 0.66245379E+00 - 0.66245379E+00 0.66245379E+00 0.66245379E+00 0.66245379E+00 0.66245379E+00 - 0.66245379E+00 0.66245379E+00 0.66245379E+00 0.66245379E+00 0.66245379E+00 - 0.66245379E+00 0.66245379E+00 0.66245379E+00 0.66245379E+00 0.66245379E+00 - 0.66245379E+00 0.66245379E+00 0.66245379E+00 0.66245379E+00 0.66245379E+00 - 0.66245379E+00 0.66245379E+00 0.66245379E+00 0.66245379E+00 0.66245379E+00 - 0.66245379E+00 0.66245379E+00 0.66245379E+00 0.66245379E+00 0.66245379E+00 - 0.66245379E+00 0.66245379E+00 0.66245379E+00 0.66245379E+00 0.66245379E+00 - 0.66245379E+00 0.66245379E+00 0.66245379E+00 0.66245379E+00 0.66245379E+00 - 0.66245379E+00 0.66245379E+00 0.66245380E+00 0.66245380E+00 0.66245380E+00 - 0.66245380E+00 0.66245380E+00 0.66245380E+00 0.66245380E+00 0.66245380E+00 - 0.66245380E+00 0.66245380E+00 0.66245380E+00 0.66245380E+00 0.66245380E+00 - 0.66245380E+00 0.66245380E+00 0.66245380E+00 0.66245380E+00 0.66245380E+00 - 0.66245380E+00 0.66245380E+00 0.66245380E+00 0.66245380E+00 0.66245380E+00 - 0.66245380E+00 0.66245380E+00 0.66245380E+00 0.66245380E+00 0.66245380E+00 - 0.66245380E+00 0.66245380E+00 0.66245380E+00 0.66245380E+00 0.66245380E+00 - 0.66245380E+00 0.66245380E+00 0.66245380E+00 0.66245380E+00 0.66245380E+00 - 0.66245380E+00 0.66245380E+00 0.66245380E+00 0.66245380E+00 0.66245380E+00 - 0.66245380E+00 0.66245380E+00 0.66245380E+00 0.66245380E+00 0.66245380E+00 - 0.66245380E+00 0.66245380E+00 0.66245380E+00 0.66245380E+00 0.66245380E+00 - 0.66245380E+00 0.66245380E+00 0.66245380E+00 0.66245380E+00 0.66245380E+00 - 0.66245380E+00 0.66245380E+00 0.66245380E+00 0.66245380E+00 0.66245380E+00 - 0.66245380E+00 0.66245380E+00 0.66245380E+00 0.66245380E+00 0.66245380E+00 - 0.66245380E+00 0.66245380E+00 0.66245380E+00 0.66245380E+00 0.66245380E+00 - 0.66245380E+00 0.66245380E+00 0.66245380E+00 0.66245380E+00 0.66245380E+00 - 0.66245380E+00 0.66245380E+00 0.66245380E+00 0.66245380E+00 0.66245380E+00 - 0.66245380E+00 0.66245380E+00 0.66245380E+00 0.66245380E+00 0.66245380E+00 - 0.66245380E+00 0.66245380E+00 0.66245380E+00 0.66245380E+00 0.66245380E+00 - 0.66245380E+00 0.66245380E+00 0.66245380E+00 0.66245380E+00 0.66245380E+00 - 0.66245380E+00 0.66245380E+00 0.66245380E+00 0.66245380E+00 0.66245380E+00 - 0.66245380E+00 0.66245380E+00 0.66245380E+00 0.66245380E+00 0.66245380E+00 - 0.66245380E+00 0.66245380E+00 0.66245380E+00 0.66245380E+00 0.66245380E+00 - 0.66245380E+00 0.66245380E+00 0.66245380E+00 0.66245380E+00 0.66245380E+00 - 0.66245380E+00 0.66245380E+00 0.66245380E+00 0.66245380E+00 0.66245380E+00 - 0.66245380E+00 0.66245380E+00 0.66245380E+00 0.66245380E+00 0.66245380E+00 - 0.66245380E+00 0.66245380E+00 0.66245380E+00 0.66245380E+00 0.66245380E+00 - 0.66245380E+00 0.66245380E+00 0.66245380E+00 0.66245380E+00 0.66245380E+00 - 0.66245380E+00 0.66245380E+00 0.66245380E+00 0.66245380E+00 0.66245380E+00 - 0.66245380E+00 0.66245380E+00 0.66245380E+00 0.66245380E+00 0.66245380E+00 - 0.66245380E+00 0.66245380E+00 0.66245380E+00 0.66245380E+00 0.66245380E+00 - 0.66245380E+00 0.66245380E+00 0.66245380E+00 0.66245380E+00 0.66245380E+00 - 0.66245380E+00 0.66245380E+00 0.66245380E+00 0.66245380E+00 0.66245380E+00 - 0.66245380E+00 0.66245380E+00 0.66245380E+00 0.66245380E+00 0.66245380E+00 - 0.66245380E+00 0.66245380E+00 0.66245380E+00 0.66245380E+00 0.66245380E+00 - 0.66245380E+00 0.66245380E+00 0.66245380E+00 0.66245380E+00 0.66245380E+00 - 0.66245380E+00 0.66245380E+00 0.66245380E+00 0.66245380E+00 0.66245380E+00 - 0.66245380E+00 0.66245380E+00 0.66245380E+00 0.66245380E+00 0.66245380E+00 - 0.66245380E+00 0.66245380E+00 0.66245380E+00 0.66245380E+00 0.66245380E+00 - 0.66245380E+00 0.66245380E+00 0.66245380E+00 0.66245380E+00 0.66245380E+00 - 0.66245380E+00 0.66245380E+00 0.66245380E+00 0.66245380E+00 0.66245380E+00 - 0.66245380E+00 0.66245380E+00 0.66245380E+00 0.66245380E+00 0.66245380E+00 - 0.66245380E+00 0.66245380E+00 0.66245380E+00 0.66245380E+00 0.66245380E+00 - 0.66245380E+00 0.66245380E+00 0.66245380E+00 0.66245380E+00 0.66245380E+00 - 0.66245380E+00 0.66245380E+00 0.66245380E+00 0.66245380E+00 0.66245380E+00 - 0.66245380E+00 0.66245380E+00 0.66245380E+00 0.66245380E+00 0.66245380E+00 - 0.66245380E+00 0.66245380E+00 0.66245380E+00 0.66245380E+00 0.66245380E+00 - 0.66245380E+00 0.66245380E+00 0.66245380E+00 0.66245380E+00 0.66245380E+00 - 0.66245380E+00 0.66245380E+00 0.66245380E+00 0.66245380E+00 0.66245380E+00 - 0.66245380E+00 0.66245380E+00 0.66245380E+00 0.66245380E+00 0.66245380E+00 - 0.66245380E+00 0.66245380E+00 0.66245380E+00 0.66245380E+00 0.66245380E+00 - 0.66245380E+00 0.66245380E+00 0.66245380E+00 0.66245380E+00 0.66245380E+00 - 0.66245380E+00 0.66245380E+00 0.66245380E+00 0.66245380E+00 0.66245380E+00 - 0.66245380E+00 0.66245380E+00 0.66245380E+00 0.66245380E+00 0.66245380E+00 - 0.66245380E+00 0.66245380E+00 0.66245380E+00 0.66245380E+00 0.66245380E+00 - 0.66245380E+00 0.66245380E+00 0.66245380E+00 0.66245380E+00 0.66245380E+00 - 0.66245380E+00 0.66245380E+00 0.66245380E+00 0.66245380E+00 0.66245380E+00 - 0.66245380E+00 0.66245380E+00 0.66245380E+00 0.66245380E+00 0.66245380E+00 - 0.66245380E+00 0.66245380E+00 0.66245380E+00 0.66245380E+00 0.66245380E+00 - 0.66245380E+00 0.66245380E+00 0.66245380E+00 0.66245380E+00 0.66245380E+00 - 0.66245380E+00 0.66245380E+00 0.66245380E+00 0.66245380E+00 0.66245380E+00 - 0.66245380E+00 0.66245380E+00 0.66245380E+00 0.66245380E+00 0.66245380E+00 - 0.66245380E+00 0.66245380E+00 0.66245380E+00 0.66245380E+00 0.66245380E+00 - 0.66245380E+00 0.66245380E+00 0.66245380E+00 0.66245380E+00 0.66245380E+00 - 0.66245380E+00 0.66245380E+00 0.66245380E+00 0.66245380E+00 0.66245380E+00 - 0.66245380E+00 0.66245380E+00 0.66245380E+00 0.66245380E+00 0.66245380E+00 - 0.66245380E+00 0.66245380E+00 0.66245380E+00 0.66245380E+00 0.66245380E+00 - 0.66245380E+00 0.66245380E+00 0.66245380E+00 0.66245380E+00 0.66245380E+00 - 0.66245380E+00 0.66245380E+00 0.66245380E+00 0.66245380E+00 0.66245380E+00 - 0.66245380E+00 0.66245380E+00 0.66245380E+00 0.66245380E+00 0.66245380E+00 - 0.66245380E+00 0.66245380E+00 0.66245380E+00 0.66245380E+00 0.66245380E+00 - -0.14142132E-09 0.50025000E-03 0.10005001E-02 0.15007503E-02 0.20010004E-02 - 0.25012506E-02 0.30015007E-02 0.35017509E-02 0.40020010E-02 0.45022511E-02 - 0.50025013E-02 0.55027514E-02 0.60030016E-02 0.65032517E-02 0.70035018E-02 - 0.75037520E-02 0.80040021E-02 0.85042523E-02 0.90045024E-02 0.95047526E-02 - 0.10005003E-01 0.10505253E-01 0.11005503E-01 0.11505753E-01 0.12006003E-01 - 0.12506253E-01 0.13006504E-01 0.13506754E-01 0.14007004E-01 0.14507254E-01 - 0.15007504E-01 0.15507754E-01 0.16008004E-01 0.16508255E-01 0.17008505E-01 - 0.17508755E-01 0.18009005E-01 0.18509255E-01 0.19009505E-01 0.19509755E-01 - 0.20010006E-01 0.20510256E-01 0.21010506E-01 0.21510756E-01 0.22011006E-01 - 0.22511256E-01 0.23011506E-01 0.23511757E-01 0.24012007E-01 0.24512257E-01 - 0.25012507E-01 0.25512757E-01 0.26013007E-01 0.26513257E-01 0.27013508E-01 - 0.27513758E-01 0.28014008E-01 0.28514258E-01 0.29014508E-01 0.29514758E-01 - 0.30015008E-01 0.30515259E-01 0.31015509E-01 0.31515759E-01 0.32016009E-01 - 0.32516259E-01 0.33016509E-01 0.33516759E-01 0.34017010E-01 0.34517260E-01 - 0.35017510E-01 0.35517760E-01 0.36018010E-01 0.36518260E-01 0.37018510E-01 - 0.37518761E-01 0.38019011E-01 0.38519261E-01 0.39019511E-01 0.39519761E-01 - 0.40020011E-01 0.40520261E-01 0.41020512E-01 0.41520762E-01 0.42021012E-01 - 0.42521262E-01 0.43021512E-01 0.43521762E-01 0.44022012E-01 0.44522262E-01 - 0.45022513E-01 0.45522763E-01 0.46023013E-01 0.46523263E-01 0.47023513E-01 - 0.47523763E-01 0.48024013E-01 0.48524264E-01 0.49024514E-01 0.49524764E-01 - 0.50025014E-01 0.50525264E-01 0.51025514E-01 0.51525764E-01 0.52026015E-01 - 0.52526265E-01 0.53026515E-01 0.53526765E-01 0.54027015E-01 0.54527265E-01 - 0.55027515E-01 0.55527766E-01 0.56028016E-01 0.56528266E-01 0.57028516E-01 - 0.57528766E-01 0.58029016E-01 0.58529266E-01 0.59029517E-01 0.59529767E-01 - 0.60030017E-01 0.60530267E-01 0.61030517E-01 0.61530767E-01 0.62031017E-01 - 0.62531268E-01 0.63031518E-01 0.63531768E-01 0.64032018E-01 0.64532268E-01 - 0.65032518E-01 0.65532768E-01 0.66033019E-01 0.66533269E-01 0.67033519E-01 - 0.67533769E-01 0.68034019E-01 0.68534269E-01 0.69034519E-01 0.69534770E-01 - 0.70035020E-01 0.70535270E-01 0.71035520E-01 0.71535770E-01 0.72036020E-01 - 0.72536270E-01 0.73036521E-01 0.73536771E-01 0.74037021E-01 0.74537271E-01 - 0.75037521E-01 0.75537771E-01 0.76038021E-01 0.76538272E-01 0.77038522E-01 - 0.77538772E-01 0.78039022E-01 0.78539272E-01 0.79039522E-01 0.79539772E-01 - 0.80040023E-01 0.80540273E-01 0.81040523E-01 0.81540773E-01 0.82041023E-01 - 0.82541273E-01 0.83041523E-01 0.83541774E-01 0.84042024E-01 0.84542274E-01 - 0.85042524E-01 0.85542774E-01 0.86043024E-01 0.86543274E-01 0.87043525E-01 - 0.87543775E-01 0.88044025E-01 0.88544275E-01 0.89044525E-01 0.89544775E-01 - 0.90045025E-01 0.90545276E-01 0.91045526E-01 0.91545776E-01 0.92046026E-01 - 0.92546276E-01 0.93046526E-01 0.93546776E-01 0.94047027E-01 0.94547277E-01 - 0.95047527E-01 0.95547777E-01 0.96048027E-01 0.96548277E-01 0.97048527E-01 - 0.97548778E-01 0.98049028E-01 0.98549278E-01 0.99049528E-01 0.99549778E-01 - 0.10005003E+00 0.10055028E+00 0.10105053E+00 0.10155078E+00 0.10205103E+00 - 0.10255128E+00 0.10305153E+00 0.10355178E+00 0.10405203E+00 0.10455228E+00 - 0.10505253E+00 0.10555278E+00 0.10605303E+00 0.10655328E+00 0.10705353E+00 - 0.10755378E+00 0.10805403E+00 0.10855428E+00 0.10905453E+00 0.10955478E+00 - 0.11005503E+00 0.11055528E+00 0.11105553E+00 0.11155578E+00 0.11205603E+00 - 0.11255628E+00 0.11305653E+00 0.11355678E+00 0.11405703E+00 0.11455728E+00 - 0.11505753E+00 0.11555778E+00 0.11605803E+00 0.11655828E+00 0.11705853E+00 - 0.11755878E+00 0.11805903E+00 0.11855928E+00 0.11905953E+00 0.11955978E+00 - 0.12006003E+00 0.12056028E+00 0.12106053E+00 0.12156078E+00 0.12206103E+00 - 0.12256128E+00 0.12306153E+00 0.12356178E+00 0.12406204E+00 0.12456229E+00 - 0.12506254E+00 0.12556279E+00 0.12606304E+00 0.12656329E+00 0.12706354E+00 - 0.12756379E+00 0.12806404E+00 0.12856429E+00 0.12906454E+00 0.12956479E+00 - 0.13006504E+00 0.13056529E+00 0.13106554E+00 0.13156579E+00 0.13206604E+00 - 0.13256629E+00 0.13306654E+00 0.13356679E+00 0.13406704E+00 0.13456729E+00 - 0.13506754E+00 0.13556779E+00 0.13606804E+00 0.13656829E+00 0.13706854E+00 - 0.13756879E+00 0.13806904E+00 0.13856929E+00 0.13906954E+00 0.13956979E+00 - 0.14007004E+00 0.14057029E+00 0.14107054E+00 0.14157079E+00 0.14207104E+00 - 0.14257129E+00 0.14307154E+00 0.14357179E+00 0.14407204E+00 0.14457229E+00 - 0.14507254E+00 0.14557279E+00 0.14607304E+00 0.14657329E+00 0.14707354E+00 - 0.14757379E+00 0.14807404E+00 0.14857429E+00 0.14907454E+00 0.14957479E+00 - 0.15007504E+00 0.15057529E+00 0.15107554E+00 0.15157579E+00 0.15207604E+00 - 0.15257629E+00 0.15307654E+00 0.15357679E+00 0.15407704E+00 0.15457729E+00 - 0.15507754E+00 0.15557779E+00 0.15607804E+00 0.15657829E+00 0.15707854E+00 - 0.15757879E+00 0.15807904E+00 0.15857929E+00 0.15907955E+00 0.15957980E+00 - 0.16008005E+00 0.16058030E+00 0.16108055E+00 0.16158080E+00 0.16208105E+00 - 0.16258130E+00 0.16308155E+00 0.16358180E+00 0.16408205E+00 0.16458230E+00 - 0.16508255E+00 0.16558280E+00 0.16608305E+00 0.16658330E+00 0.16708355E+00 - 0.16758380E+00 0.16808405E+00 0.16858430E+00 0.16908455E+00 0.16958480E+00 - 0.17008505E+00 0.17058530E+00 0.17108555E+00 0.17158580E+00 0.17208605E+00 - 0.17258630E+00 0.17308655E+00 0.17358680E+00 0.17408705E+00 0.17458730E+00 - 0.17508755E+00 0.17558780E+00 0.17608805E+00 0.17658830E+00 0.17708855E+00 - 0.17758880E+00 0.17808905E+00 0.17858930E+00 0.17908955E+00 0.17958980E+00 - 0.18009005E+00 0.18059030E+00 0.18109055E+00 0.18159080E+00 0.18209105E+00 - 0.18259130E+00 0.18309155E+00 0.18359180E+00 0.18409205E+00 0.18459230E+00 - 0.18509255E+00 0.18559280E+00 0.18609305E+00 0.18659330E+00 0.18709355E+00 - 0.18759380E+00 0.18809405E+00 0.18859430E+00 0.18909455E+00 0.18959480E+00 - 0.19009505E+00 0.19059530E+00 0.19109555E+00 0.19159580E+00 0.19209605E+00 - 0.19259630E+00 0.19309655E+00 0.19359680E+00 0.19409705E+00 0.19459731E+00 - 0.19509756E+00 0.19559781E+00 0.19609806E+00 0.19659831E+00 0.19709856E+00 - 0.19759881E+00 0.19809906E+00 0.19859931E+00 0.19909956E+00 0.19959981E+00 - 0.20010006E+00 0.20060031E+00 0.20110056E+00 0.20160081E+00 0.20210106E+00 - 0.20260131E+00 0.20310156E+00 0.20360181E+00 0.20410206E+00 0.20460231E+00 - 0.20510256E+00 0.20560281E+00 0.20610306E+00 0.20660331E+00 0.20710356E+00 - 0.20760381E+00 0.20810406E+00 0.20860431E+00 0.20910456E+00 0.20960481E+00 - 0.21010506E+00 0.21060531E+00 0.21110556E+00 0.21160581E+00 0.21210606E+00 - 0.21260631E+00 0.21310656E+00 0.21360681E+00 0.21410706E+00 0.21460731E+00 - 0.21510756E+00 0.21560781E+00 0.21610806E+00 0.21660831E+00 0.21710856E+00 - 0.21760881E+00 0.21810906E+00 0.21860931E+00 0.21910956E+00 0.21960981E+00 - 0.22011006E+00 0.22061031E+00 0.22111056E+00 0.22161081E+00 0.22211106E+00 - 0.22261131E+00 0.22311156E+00 0.22361181E+00 0.22411206E+00 0.22461231E+00 - 0.22511256E+00 0.22561281E+00 0.22611306E+00 0.22661331E+00 0.22711356E+00 - 0.22761381E+00 0.22811406E+00 0.22861431E+00 0.22911456E+00 0.22961482E+00 - 0.23011507E+00 0.23061532E+00 0.23111557E+00 0.23161582E+00 0.23211607E+00 - 0.23261632E+00 0.23311657E+00 0.23361682E+00 0.23411707E+00 0.23461732E+00 - 0.23511757E+00 0.23561782E+00 0.23611807E+00 0.23661832E+00 0.23711857E+00 - 0.23761882E+00 0.23811907E+00 0.23861932E+00 0.23911957E+00 0.23961982E+00 - 0.24012007E+00 0.24062032E+00 0.24112057E+00 0.24162082E+00 0.24212107E+00 - 0.24262132E+00 0.24312157E+00 0.24362182E+00 0.24412207E+00 0.24462232E+00 - 0.24512257E+00 0.24562282E+00 0.24612307E+00 0.24662332E+00 0.24712357E+00 - 0.24762382E+00 0.24812407E+00 0.24862432E+00 0.24912457E+00 0.24962482E+00 - 0.25012507E+00 0.25062532E+00 0.25112557E+00 0.25162582E+00 0.25212607E+00 - 0.25262632E+00 0.25312657E+00 0.25362682E+00 0.25412707E+00 0.25462732E+00 - 0.25512757E+00 0.25562782E+00 0.25612807E+00 0.25662832E+00 0.25712857E+00 - 0.25762882E+00 0.25812907E+00 0.25862932E+00 0.25912957E+00 0.25962982E+00 - 0.26013007E+00 0.26063032E+00 0.26113057E+00 0.26163082E+00 0.26213107E+00 - 0.26263132E+00 0.26313157E+00 0.26363182E+00 0.26413207E+00 0.26463232E+00 - 0.26513258E+00 0.26563283E+00 0.26613308E+00 0.26663333E+00 0.26713358E+00 - 0.26763383E+00 0.26813408E+00 0.26863433E+00 0.26913458E+00 0.26963483E+00 - 0.27013508E+00 0.27063533E+00 0.27113558E+00 0.27163583E+00 0.27213608E+00 - 0.27263633E+00 0.27313658E+00 0.27363683E+00 0.27413708E+00 0.27463733E+00 - 0.27513758E+00 0.27563783E+00 0.27613808E+00 0.27663833E+00 0.27713858E+00 - 0.27763883E+00 0.27813908E+00 0.27863933E+00 0.27913958E+00 0.27963983E+00 - 0.28014008E+00 0.28064033E+00 0.28114058E+00 0.28164083E+00 0.28214108E+00 - 0.28264133E+00 0.28314158E+00 0.28364183E+00 0.28414208E+00 0.28464233E+00 - 0.28514258E+00 0.28564283E+00 0.28614308E+00 0.28664333E+00 0.28714358E+00 - 0.28764383E+00 0.28814408E+00 0.28864433E+00 0.28914458E+00 0.28964483E+00 - 0.29014508E+00 0.29064533E+00 0.29114558E+00 0.29164583E+00 0.29214608E+00 - 0.29264633E+00 0.29314658E+00 0.29364683E+00 0.29414708E+00 0.29464733E+00 - 0.29514758E+00 0.29564783E+00 0.29614808E+00 0.29664833E+00 0.29714858E+00 - 0.29764883E+00 0.29814908E+00 0.29864933E+00 0.29914958E+00 0.29964983E+00 - 0.30015009E+00 0.30065034E+00 0.30115059E+00 0.30165084E+00 0.30215109E+00 - 0.30265134E+00 0.30315159E+00 0.30365184E+00 0.30415209E+00 0.30465234E+00 - 0.30515259E+00 0.30565284E+00 0.30615309E+00 0.30665334E+00 0.30715359E+00 - 0.30765384E+00 0.30815409E+00 0.30865434E+00 0.30915459E+00 0.30965484E+00 - 0.31015509E+00 0.31065534E+00 0.31115559E+00 0.31165584E+00 0.31215609E+00 - 0.31265634E+00 0.31315659E+00 0.31365684E+00 0.31415709E+00 0.31465734E+00 - 0.31515759E+00 0.31565784E+00 0.31615809E+00 0.31665834E+00 0.31715859E+00 - 0.31765884E+00 0.31815909E+00 0.31865934E+00 0.31915959E+00 0.31965984E+00 - 0.32016009E+00 0.32066034E+00 0.32116059E+00 0.32166084E+00 0.32216109E+00 - 0.32266134E+00 0.32316159E+00 0.32366184E+00 0.32416209E+00 0.32466234E+00 - 0.32516259E+00 0.32566284E+00 0.32616309E+00 0.32666334E+00 0.32716359E+00 - 0.32766384E+00 0.32816409E+00 0.32866434E+00 0.32916459E+00 0.32966484E+00 - 0.33016509E+00 0.33066534E+00 0.33116559E+00 0.33166584E+00 0.33216609E+00 - 0.33266634E+00 0.33316659E+00 0.33366684E+00 0.33416709E+00 0.33466734E+00 - 0.33516759E+00 0.33566785E+00 0.33616810E+00 0.33666835E+00 0.33716860E+00 - 0.33766885E+00 0.33816910E+00 0.33866935E+00 0.33916960E+00 0.33966985E+00 - 0.34017010E+00 0.34067035E+00 0.34117060E+00 0.34167085E+00 0.34217110E+00 - 0.34267135E+00 0.34317160E+00 0.34367185E+00 0.34417210E+00 0.34467235E+00 - 0.34517260E+00 0.34567285E+00 0.34617310E+00 0.34667335E+00 0.34717360E+00 - 0.34767385E+00 0.34817410E+00 0.34867435E+00 0.34917460E+00 0.34967485E+00 - 0.35017510E+00 0.35067535E+00 0.35117560E+00 0.35167585E+00 0.35217610E+00 - 0.35267635E+00 0.35317660E+00 0.35367685E+00 0.35417710E+00 0.35467735E+00 - 0.35517760E+00 0.35567785E+00 0.35617810E+00 0.35667835E+00 0.35717860E+00 - 0.35767885E+00 0.35817910E+00 0.35867935E+00 0.35917960E+00 0.35967985E+00 - 0.36018010E+00 0.36068035E+00 0.36118060E+00 0.36168085E+00 0.36218110E+00 - 0.36268135E+00 0.36318160E+00 0.36368185E+00 0.36418210E+00 0.36468235E+00 - 0.36518260E+00 0.36568285E+00 0.36618310E+00 0.36668335E+00 0.36718360E+00 - 0.36768385E+00 0.36818410E+00 0.36868435E+00 0.36918460E+00 0.36968485E+00 - 0.37018510E+00 0.37068536E+00 0.37118561E+00 0.37168586E+00 0.37218611E+00 - 0.37268636E+00 0.37318661E+00 0.37368686E+00 0.37418711E+00 0.37468736E+00 - 0.37518761E+00 0.37568786E+00 0.37618811E+00 0.37668836E+00 0.37718861E+00 - 0.37768886E+00 0.37818911E+00 0.37868936E+00 0.37918961E+00 0.37968986E+00 - 0.38019011E+00 0.38069036E+00 0.38119061E+00 0.38169086E+00 0.38219111E+00 - 0.38269136E+00 0.38319161E+00 0.38369186E+00 0.38419211E+00 0.38469236E+00 - 0.38519261E+00 0.38569286E+00 0.38619311E+00 0.38669336E+00 0.38719361E+00 - 0.38769386E+00 0.38819411E+00 0.38869436E+00 0.38919461E+00 0.38969486E+00 - 0.39019511E+00 0.39069536E+00 0.39119561E+00 0.39169586E+00 0.39219611E+00 - 0.39269636E+00 0.39319661E+00 0.39369686E+00 0.39419711E+00 0.39469736E+00 - 0.39519761E+00 0.39569786E+00 0.39619811E+00 0.39669836E+00 0.39719861E+00 - 0.39769886E+00 0.39819911E+00 0.39869936E+00 0.39919961E+00 0.39969986E+00 - 0.40020011E+00 0.40070036E+00 0.40120061E+00 0.40170086E+00 0.40220111E+00 - 0.40270136E+00 0.40320161E+00 0.40370186E+00 0.40420211E+00 0.40470236E+00 - 0.40520261E+00 0.40570286E+00 0.40620312E+00 0.40670337E+00 0.40720362E+00 - 0.40770387E+00 0.40820412E+00 0.40870437E+00 0.40920462E+00 0.40970487E+00 - 0.41020512E+00 0.41070537E+00 0.41120562E+00 0.41170587E+00 0.41220612E+00 - 0.41270637E+00 0.41320662E+00 0.41370687E+00 0.41420712E+00 0.41470737E+00 - 0.41520762E+00 0.41570787E+00 0.41620812E+00 0.41670837E+00 0.41720862E+00 - 0.41770887E+00 0.41820912E+00 0.41870937E+00 0.41920962E+00 0.41970987E+00 - 0.42021012E+00 0.42071037E+00 0.42121062E+00 0.42171087E+00 0.42221112E+00 - 0.42271137E+00 0.42321162E+00 0.42371187E+00 0.42421212E+00 0.42471237E+00 - 0.42521262E+00 0.42571287E+00 0.42621312E+00 0.42671337E+00 0.42721362E+00 - 0.42771387E+00 0.42821412E+00 0.42871437E+00 0.42921462E+00 0.42971487E+00 - 0.43021512E+00 0.43071537E+00 0.43121562E+00 0.43171587E+00 0.43221612E+00 - 0.43271637E+00 0.43321662E+00 0.43371687E+00 0.43421712E+00 0.43471737E+00 - 0.43521762E+00 0.43571787E+00 0.43621812E+00 0.43671837E+00 0.43721862E+00 - 0.43771887E+00 0.43821912E+00 0.43871937E+00 0.43921962E+00 0.43971987E+00 - 0.44022012E+00 0.44072037E+00 0.44122063E+00 0.44172088E+00 0.44222113E+00 - 0.44272138E+00 0.44322163E+00 0.44372188E+00 0.44422213E+00 0.44472238E+00 - 0.44522263E+00 0.44572288E+00 0.44622313E+00 0.44672338E+00 0.44722363E+00 - 0.44772388E+00 0.44822413E+00 0.44872438E+00 0.44922463E+00 0.44972488E+00 - 0.45022513E+00 0.45072538E+00 0.45122563E+00 0.45172588E+00 0.45222613E+00 - 0.45272638E+00 0.45322663E+00 0.45372688E+00 0.45422713E+00 0.45472738E+00 - 0.45522763E+00 0.45572788E+00 0.45622813E+00 0.45672838E+00 0.45722863E+00 - 0.45772888E+00 0.45822913E+00 0.45872938E+00 0.45922963E+00 0.45972988E+00 - 0.46023013E+00 0.46073038E+00 0.46123063E+00 0.46173088E+00 0.46223113E+00 - 0.46273138E+00 0.46323163E+00 0.46373188E+00 0.46423213E+00 0.46473238E+00 - 0.46523263E+00 0.46573288E+00 0.46623313E+00 0.46673338E+00 0.46723363E+00 - 0.46773388E+00 0.46823413E+00 0.46873438E+00 0.46923463E+00 0.46973488E+00 - 0.47023513E+00 0.47073538E+00 0.47123563E+00 0.47173588E+00 0.47223613E+00 - 0.47273638E+00 0.47323663E+00 0.47373688E+00 0.47423713E+00 0.47473738E+00 - 0.47523763E+00 0.47573788E+00 0.47623813E+00 0.47673839E+00 0.47723864E+00 - 0.47773889E+00 0.47823914E+00 0.47873939E+00 0.47923964E+00 0.47973989E+00 - 0.48024014E+00 0.48074039E+00 0.48124064E+00 0.48174089E+00 0.48224114E+00 - 0.48274139E+00 0.48324164E+00 0.48374189E+00 0.48424214E+00 0.48474239E+00 - 0.48524264E+00 0.48574289E+00 0.48624314E+00 0.48674339E+00 0.48724364E+00 - 0.48774389E+00 0.48824414E+00 0.48874439E+00 0.48924464E+00 0.48974489E+00 - 0.49024514E+00 0.49074539E+00 0.49124564E+00 0.49174589E+00 0.49224614E+00 - 0.49274639E+00 0.49324664E+00 0.49374689E+00 0.49424714E+00 0.49474739E+00 - 0.49524764E+00 0.49574789E+00 0.49624814E+00 0.49674839E+00 0.49724864E+00 - 0.49774889E+00 0.49824914E+00 0.49874939E+00 0.49924964E+00 0.49974989E+00 - 0.50025014E+00 0.50075039E+00 0.50125064E+00 0.50175089E+00 0.50225114E+00 - 0.50275139E+00 0.50325164E+00 0.50375189E+00 0.50425214E+00 0.50475239E+00 - 0.50525264E+00 0.50575289E+00 0.50625314E+00 0.50675339E+00 0.50725364E+00 - 0.50775389E+00 0.50825414E+00 0.50875439E+00 0.50925464E+00 0.50975489E+00 - 0.51025514E+00 0.51075539E+00 0.51125564E+00 0.51175590E+00 0.51225615E+00 - 0.51275640E+00 0.51325665E+00 0.51375690E+00 0.51425715E+00 0.51475740E+00 - 0.51525765E+00 0.51575790E+00 0.51625815E+00 0.51675840E+00 0.51725865E+00 - 0.51775890E+00 0.51825915E+00 0.51875940E+00 0.51925965E+00 0.51975990E+00 - 0.52026015E+00 0.52076040E+00 0.52126065E+00 0.52176090E+00 0.52226115E+00 - 0.52276140E+00 0.52326165E+00 0.52376190E+00 0.52426215E+00 0.52476240E+00 - 0.52526265E+00 0.52576290E+00 0.52626315E+00 0.52676340E+00 0.52726365E+00 - 0.52776390E+00 0.52826415E+00 0.52876440E+00 0.52926465E+00 0.52976490E+00 - 0.53026515E+00 0.53076540E+00 0.53126565E+00 0.53176590E+00 0.53226615E+00 - 0.53276640E+00 0.53326665E+00 0.53376690E+00 0.53426715E+00 0.53476740E+00 - 0.53526765E+00 0.53576790E+00 0.53626815E+00 0.53676840E+00 0.53726865E+00 - 0.53776890E+00 0.53826915E+00 0.53876940E+00 0.53926965E+00 0.53976990E+00 - 0.54027015E+00 0.54077040E+00 0.54127065E+00 0.54177090E+00 0.54227115E+00 - 0.54277140E+00 0.54327165E+00 0.54377190E+00 0.54427215E+00 0.54477240E+00 - 0.54527265E+00 0.54577290E+00 0.54627315E+00 0.54677340E+00 0.54727366E+00 - 0.54777391E+00 0.54827416E+00 0.54877441E+00 0.54927466E+00 0.54977491E+00 - 0.55027516E+00 0.55077541E+00 0.55127566E+00 0.55177591E+00 0.55227616E+00 - 0.55277641E+00 0.55327666E+00 0.55377691E+00 0.55427716E+00 0.55477741E+00 - 0.55527766E+00 0.55577791E+00 0.55627816E+00 0.55677841E+00 0.55727866E+00 - 0.55777891E+00 0.55827916E+00 0.55877941E+00 0.55927966E+00 0.55977991E+00 - 0.56028016E+00 0.56078041E+00 0.56128066E+00 0.56178091E+00 0.56228116E+00 - 0.56278141E+00 0.56328166E+00 0.56378191E+00 0.56428216E+00 0.56478241E+00 - 0.56528266E+00 0.56578291E+00 0.56628316E+00 0.56678341E+00 0.56728366E+00 - 0.56778391E+00 0.56828416E+00 0.56878441E+00 0.56928466E+00 0.56978491E+00 - 0.57028516E+00 0.57078541E+00 0.57128566E+00 0.57178591E+00 0.57228616E+00 - 0.57278641E+00 0.57328666E+00 0.57378691E+00 0.57428716E+00 0.57478741E+00 - 0.57528766E+00 0.57578791E+00 0.57628816E+00 0.57678841E+00 0.57728866E+00 - 0.57778891E+00 0.57828916E+00 0.57878941E+00 0.57928966E+00 0.57978991E+00 - 0.58029016E+00 0.58079041E+00 0.58129066E+00 0.58179091E+00 0.58229117E+00 - 0.58279142E+00 0.58329167E+00 0.58379192E+00 0.58429217E+00 0.58479242E+00 - 0.58529267E+00 0.58579292E+00 0.58629317E+00 0.58679342E+00 0.58729367E+00 - 0.58779392E+00 0.58829417E+00 0.58879442E+00 0.58929467E+00 0.58979492E+00 - 0.59029517E+00 0.59079542E+00 0.59129567E+00 0.59179592E+00 0.59229617E+00 - 0.59279642E+00 0.59329667E+00 0.59379692E+00 0.59429717E+00 0.59479742E+00 - 0.59529767E+00 0.59579792E+00 0.59629817E+00 0.59679842E+00 0.59729867E+00 - 0.59779892E+00 0.59829917E+00 0.59879942E+00 0.59929967E+00 0.59979992E+00 - 0.60030017E+00 0.60080042E+00 0.60130067E+00 0.60180092E+00 0.60230117E+00 - 0.60280142E+00 0.60330167E+00 0.60380192E+00 0.60430217E+00 0.60480242E+00 - 0.60530267E+00 0.60580292E+00 0.60630317E+00 0.60680342E+00 0.60730367E+00 - 0.60780392E+00 0.60830417E+00 0.60880442E+00 0.60930467E+00 0.60980492E+00 - 0.61030517E+00 0.61080542E+00 0.61130567E+00 0.61180592E+00 0.61230617E+00 - 0.61280642E+00 0.61330667E+00 0.61380692E+00 0.61430717E+00 0.61480742E+00 - 0.61530767E+00 0.61580792E+00 0.61630817E+00 0.61680842E+00 0.61730867E+00 - 0.61780893E+00 0.61830918E+00 0.61880943E+00 0.61930968E+00 0.61980993E+00 - 0.62031018E+00 0.62081043E+00 0.62131068E+00 0.62181093E+00 0.62231118E+00 - 0.62281143E+00 0.62331168E+00 0.62381193E+00 0.62431218E+00 0.62481243E+00 - 0.62531268E+00 0.62581293E+00 0.62631318E+00 0.62681343E+00 0.62731368E+00 - 0.62781393E+00 0.62831418E+00 0.62881443E+00 0.62931468E+00 0.62981493E+00 - 0.63031518E+00 0.63081543E+00 0.63131568E+00 0.63181593E+00 0.63231618E+00 - 0.63281643E+00 0.63331668E+00 0.63381693E+00 0.63431718E+00 0.63481743E+00 - 0.63531768E+00 0.63581793E+00 0.63631818E+00 0.63681843E+00 0.63731868E+00 - 0.63781893E+00 0.63831918E+00 0.63881943E+00 0.63931968E+00 0.63981993E+00 - 0.64032018E+00 0.64082043E+00 0.64132068E+00 0.64182093E+00 0.64232118E+00 - 0.64282143E+00 0.64332168E+00 0.64382193E+00 0.64432218E+00 0.64482243E+00 - 0.64532268E+00 0.64582293E+00 0.64632318E+00 0.64682343E+00 0.64732368E+00 - 0.64782393E+00 0.64832418E+00 0.64882443E+00 0.64932468E+00 0.64982493E+00 - 0.65032518E+00 0.65082543E+00 0.65132568E+00 0.65182593E+00 0.65232618E+00 - 0.65282643E+00 0.65332669E+00 0.65382694E+00 0.65432719E+00 0.65482744E+00 - 0.65532769E+00 0.65582794E+00 0.65632819E+00 0.65682844E+00 0.65732869E+00 - 0.65782894E+00 0.65832919E+00 0.65882944E+00 0.65932969E+00 0.65982994E+00 - 0.66033019E+00 0.66083044E+00 0.66133069E+00 0.66183094E+00 0.66233119E+00 - 0.66283144E+00 0.66333169E+00 0.66383194E+00 0.66433219E+00 0.66483244E+00 - 0.66533269E+00 0.66583294E+00 0.66633319E+00 0.66683344E+00 0.66733369E+00 - 0.66783394E+00 0.66833419E+00 0.66883444E+00 0.66933469E+00 0.66983494E+00 - 0.67033519E+00 0.67083544E+00 0.67133569E+00 0.67183594E+00 0.67233619E+00 - 0.67283644E+00 0.67333669E+00 0.67383694E+00 0.67433719E+00 0.67483744E+00 - 0.67533769E+00 0.67583794E+00 0.67633819E+00 0.67683844E+00 0.67733869E+00 - 0.67783894E+00 0.67833919E+00 0.67883944E+00 0.67933969E+00 0.67983994E+00 - 0.68034019E+00 0.68084044E+00 0.68134069E+00 0.68184094E+00 0.68234119E+00 - 0.68284144E+00 0.68334169E+00 0.68384194E+00 0.68434219E+00 0.68484244E+00 - 0.68534269E+00 0.68584294E+00 0.68634319E+00 0.68684344E+00 0.68734369E+00 - 0.68784394E+00 0.68834420E+00 0.68884445E+00 0.68934470E+00 0.68984495E+00 - 0.69034520E+00 0.69084545E+00 0.69134570E+00 0.69184595E+00 0.69234620E+00 - 0.69284645E+00 0.69334670E+00 0.69384695E+00 0.69434720E+00 0.69484745E+00 - 0.69534770E+00 0.69584795E+00 0.69634820E+00 0.69684845E+00 0.69734870E+00 - 0.69784895E+00 0.69834920E+00 0.69884945E+00 0.69934970E+00 0.69984995E+00 - 0.70035020E+00 0.70085045E+00 0.70135070E+00 0.70185095E+00 0.70235120E+00 - 0.70285145E+00 0.70335170E+00 0.70385195E+00 0.70435220E+00 0.70485245E+00 - 0.70535270E+00 0.70585295E+00 0.70635320E+00 0.70685345E+00 0.70735370E+00 - 0.70785395E+00 0.70835420E+00 0.70885445E+00 0.70935470E+00 0.70985495E+00 - 0.71035520E+00 0.71085545E+00 0.71135570E+00 0.71185595E+00 0.71235620E+00 - 0.71285645E+00 0.71335670E+00 0.71385695E+00 0.71435720E+00 0.71485745E+00 - 0.71535770E+00 0.71585795E+00 0.71635820E+00 0.71685845E+00 0.71735870E+00 - 0.71785895E+00 0.71835920E+00 0.71885945E+00 0.71935970E+00 0.71985995E+00 - 0.72036020E+00 0.72086045E+00 0.72136070E+00 0.72186095E+00 0.72236120E+00 - 0.72286145E+00 0.72336170E+00 0.72386196E+00 0.72436221E+00 0.72486246E+00 - 0.72536271E+00 0.72586296E+00 0.72636321E+00 0.72686346E+00 0.72736371E+00 - 0.72786396E+00 0.72836421E+00 0.72886446E+00 0.72936471E+00 0.72986496E+00 - 0.73036521E+00 0.73086546E+00 0.73136571E+00 0.73186596E+00 0.73236621E+00 - 0.73286646E+00 0.73336671E+00 0.73386696E+00 0.73436721E+00 0.73486746E+00 - 0.73536771E+00 0.73586796E+00 0.73636821E+00 0.73686846E+00 0.73736871E+00 - 0.73786896E+00 0.73836921E+00 0.73886946E+00 0.73936971E+00 0.73986996E+00 - 0.74037021E+00 0.74087046E+00 0.74137071E+00 0.74187096E+00 0.74237121E+00 - 0.74287146E+00 0.74337171E+00 0.74387196E+00 0.74437221E+00 0.74487246E+00 - 0.74537271E+00 0.74587296E+00 0.74637321E+00 0.74687346E+00 0.74737371E+00 - 0.74787396E+00 0.74837421E+00 0.74887446E+00 0.74937471E+00 0.74987496E+00 - 0.75037521E+00 0.75087546E+00 0.75137571E+00 0.75187596E+00 0.75237621E+00 - 0.75287646E+00 0.75337671E+00 0.75387696E+00 0.75437721E+00 0.75487746E+00 - 0.75537771E+00 0.75587796E+00 0.75637821E+00 0.75687846E+00 0.75737871E+00 - 0.75787896E+00 0.75837921E+00 0.75887946E+00 0.75937972E+00 0.75987997E+00 - 0.76038022E+00 0.76088047E+00 0.76138072E+00 0.76188097E+00 0.76238122E+00 - 0.76288147E+00 0.76338172E+00 0.76388197E+00 0.76438222E+00 0.76488247E+00 - 0.76538272E+00 0.76588297E+00 0.76638322E+00 0.76688347E+00 0.76738372E+00 - 0.76788397E+00 0.76838422E+00 0.76888447E+00 0.76938472E+00 0.76988497E+00 - 0.77038522E+00 0.77088547E+00 0.77138572E+00 0.77188597E+00 0.77238622E+00 - 0.77288647E+00 0.77338672E+00 0.77388697E+00 0.77438722E+00 0.77488747E+00 - 0.77538772E+00 0.77588797E+00 0.77638822E+00 0.77688847E+00 0.77738872E+00 - 0.77788897E+00 0.77838922E+00 0.77888947E+00 0.77938972E+00 0.77988997E+00 - 0.78039022E+00 0.78089047E+00 0.78139072E+00 0.78189097E+00 0.78239122E+00 - 0.78289147E+00 0.78339172E+00 0.78389197E+00 0.78439222E+00 0.78489247E+00 - 0.78539272E+00 0.78589297E+00 0.78639322E+00 0.78689347E+00 0.78739372E+00 - 0.78789397E+00 0.78839422E+00 0.78889447E+00 0.78939472E+00 0.78989497E+00 - 0.79039522E+00 0.79089547E+00 0.79139572E+00 0.79189597E+00 0.79239622E+00 - 0.79289647E+00 0.79339672E+00 0.79389697E+00 0.79439722E+00 0.79489748E+00 - 0.79539773E+00 0.79589798E+00 0.79639823E+00 0.79689848E+00 0.79739873E+00 - 0.79789898E+00 0.79839923E+00 0.79889948E+00 0.79939973E+00 0.79989998E+00 - 0.80040023E+00 0.80090048E+00 0.80140073E+00 0.80190098E+00 0.80240123E+00 - 0.80290148E+00 0.80340173E+00 0.80390198E+00 0.80440223E+00 0.80490248E+00 - 0.80540273E+00 0.80590298E+00 0.80640323E+00 0.80690348E+00 0.80740373E+00 - 0.80790398E+00 0.80840423E+00 0.80890448E+00 0.80940473E+00 0.80990498E+00 - 0.81040523E+00 0.81090548E+00 0.81140573E+00 0.81190598E+00 0.81240623E+00 - 0.81290648E+00 0.81340673E+00 0.81390698E+00 0.81440723E+00 0.81490748E+00 - 0.81540773E+00 0.81590798E+00 0.81640823E+00 0.81690848E+00 0.81740873E+00 - 0.81790898E+00 0.81840923E+00 0.81890948E+00 0.81940973E+00 0.81990998E+00 - 0.82041023E+00 0.82091048E+00 0.82141073E+00 0.82191098E+00 0.82241123E+00 - 0.82291148E+00 0.82341173E+00 0.82391198E+00 0.82441223E+00 0.82491248E+00 - 0.82541273E+00 0.82591298E+00 0.82641323E+00 0.82691348E+00 0.82741373E+00 - 0.82791398E+00 0.82841423E+00 0.82891448E+00 0.82941473E+00 0.82991498E+00 - 0.83041523E+00 0.83091549E+00 0.83141574E+00 0.83191599E+00 0.83241624E+00 - 0.83291649E+00 0.83341674E+00 0.83391699E+00 0.83441724E+00 0.83491749E+00 - 0.83541774E+00 0.83591799E+00 0.83641824E+00 0.83691849E+00 0.83741874E+00 - 0.83791899E+00 0.83841924E+00 0.83891949E+00 0.83941974E+00 0.83991999E+00 - 0.84042024E+00 0.84092049E+00 0.84142074E+00 0.84192099E+00 0.84242124E+00 - 0.84292149E+00 0.84342174E+00 0.84392199E+00 0.84442224E+00 0.84492249E+00 - 0.84542274E+00 0.84592299E+00 0.84642324E+00 0.84692349E+00 0.84742374E+00 - 0.84792399E+00 0.84842424E+00 0.84892449E+00 0.84942474E+00 0.84992499E+00 - 0.85042524E+00 0.85092549E+00 0.85142574E+00 0.85192599E+00 0.85242624E+00 - 0.85292649E+00 0.85342674E+00 0.85392699E+00 0.85442724E+00 0.85492749E+00 - 0.85542774E+00 0.85592799E+00 0.85642824E+00 0.85692849E+00 0.85742874E+00 - 0.85792899E+00 0.85842924E+00 0.85892949E+00 0.85942974E+00 0.85992999E+00 - 0.86043024E+00 0.86093049E+00 0.86143074E+00 0.86193099E+00 0.86243124E+00 - 0.86293149E+00 0.86343174E+00 0.86393199E+00 0.86443224E+00 0.86493249E+00 - 0.86543274E+00 0.86593299E+00 0.86643325E+00 0.86693350E+00 0.86743375E+00 - 0.86793400E+00 0.86843425E+00 0.86893450E+00 0.86943475E+00 0.86993500E+00 - 0.87043525E+00 0.87093550E+00 0.87143575E+00 0.87193600E+00 0.87243625E+00 - 0.87293650E+00 0.87343675E+00 0.87393700E+00 0.87443725E+00 0.87493750E+00 - 0.87543775E+00 0.87593800E+00 0.87643825E+00 0.87693850E+00 0.87743875E+00 - 0.87793900E+00 0.87843925E+00 0.87893950E+00 0.87943975E+00 0.87994000E+00 - 0.88044025E+00 0.88094050E+00 0.88144075E+00 0.88194100E+00 0.88244125E+00 - 0.88294150E+00 0.88344175E+00 0.88394200E+00 0.88444225E+00 0.88494250E+00 - 0.88544275E+00 0.88594300E+00 0.88644325E+00 0.88694350E+00 0.88744375E+00 - 0.88794400E+00 0.88844425E+00 0.88894450E+00 0.88944475E+00 0.88994500E+00 - 0.89044525E+00 0.89094550E+00 0.89144575E+00 0.89194600E+00 0.89244625E+00 - 0.89294650E+00 0.89344675E+00 0.89394700E+00 0.89444725E+00 0.89494750E+00 - 0.89544775E+00 0.89594800E+00 0.89644825E+00 0.89694850E+00 0.89744875E+00 - 0.89794900E+00 0.89844925E+00 0.89894950E+00 0.89944975E+00 0.89995000E+00 - 0.90045025E+00 0.90095050E+00 0.90145075E+00 0.90195100E+00 0.90245125E+00 - 0.90295150E+00 0.90345176E+00 0.90395201E+00 0.90445226E+00 0.90495251E+00 - 0.90545276E+00 0.90595301E+00 0.90645326E+00 0.90695351E+00 0.90745376E+00 - 0.90795401E+00 0.90845426E+00 0.90895451E+00 0.90945476E+00 0.90995501E+00 - 0.91045526E+00 0.91095551E+00 0.91145576E+00 0.91195601E+00 0.91245626E+00 - 0.91295651E+00 0.91345676E+00 0.91395701E+00 0.91445726E+00 0.91495751E+00 - 0.91545776E+00 0.91595801E+00 0.91645826E+00 0.91695851E+00 0.91745876E+00 - 0.91795901E+00 0.91845926E+00 0.91895951E+00 0.91945976E+00 0.91996001E+00 - 0.92046026E+00 0.92096051E+00 0.92146076E+00 0.92196101E+00 0.92246126E+00 - 0.92296151E+00 0.92346176E+00 0.92396201E+00 0.92446226E+00 0.92496251E+00 - 0.92546276E+00 0.92596301E+00 0.92646326E+00 0.92696351E+00 0.92746376E+00 - 0.92796401E+00 0.92846426E+00 0.92896451E+00 0.92946476E+00 0.92996501E+00 - 0.93046526E+00 0.93096551E+00 0.93146576E+00 0.93196601E+00 0.93246626E+00 - 0.93296651E+00 0.93346676E+00 0.93396701E+00 0.93446726E+00 0.93496751E+00 - 0.93546776E+00 0.93596801E+00 0.93646826E+00 0.93696851E+00 0.93746876E+00 - 0.93796901E+00 0.93846926E+00 0.93896951E+00 0.93946976E+00 0.93997001E+00 - 0.94047026E+00 0.94097051E+00 0.94147076E+00 0.94197102E+00 0.94247127E+00 - 0.94297152E+00 0.94347177E+00 0.94397202E+00 0.94447227E+00 0.94497252E+00 - 0.94547277E+00 0.94597302E+00 0.94647327E+00 0.94697352E+00 0.94747377E+00 - 0.94797402E+00 0.94847427E+00 0.94897452E+00 0.94947477E+00 0.94997502E+00 - 0.95047527E+00 0.95097552E+00 0.95147577E+00 0.95197602E+00 0.95247627E+00 - 0.95297652E+00 0.95347677E+00 0.95397702E+00 0.95447727E+00 0.95497752E+00 - 0.95547777E+00 0.95597802E+00 0.95647827E+00 0.95697852E+00 0.95747877E+00 - 0.95797902E+00 0.95847927E+00 0.95897952E+00 0.95947977E+00 0.95998002E+00 - 0.96048027E+00 0.96098052E+00 0.96148077E+00 0.96198102E+00 0.96248127E+00 - 0.96298152E+00 0.96348177E+00 0.96398202E+00 0.96448227E+00 0.96498252E+00 - 0.96548277E+00 0.96598302E+00 0.96648327E+00 0.96698352E+00 0.96748377E+00 - 0.96798402E+00 0.96848427E+00 0.96898452E+00 0.96948477E+00 0.96998502E+00 - 0.97048527E+00 0.97098552E+00 0.97148577E+00 0.97198602E+00 0.97248627E+00 - 0.97298652E+00 0.97348677E+00 0.97398702E+00 0.97448727E+00 0.97498752E+00 - 0.97548777E+00 0.97598802E+00 0.97648827E+00 0.97698852E+00 0.97748877E+00 - 0.97798902E+00 0.97848927E+00 0.97898952E+00 0.97948977E+00 0.97999002E+00 - 0.98049027E+00 0.98099052E+00 0.98149077E+00 0.98199102E+00 0.98249127E+00 - 0.98299152E+00 0.98349177E+00 0.98399202E+00 0.98449227E+00 0.98499252E+00 - 0.98549277E+00 0.98599302E+00 0.98649327E+00 0.98699352E+00 0.98749377E+00 - 0.98799402E+00 0.98849427E+00 0.98899452E+00 0.98949477E+00 0.98999502E+00 - 0.99049527E+00 0.99099552E+00 0.99149576E+00 0.99199601E+00 0.99249626E+00 - 0.99299651E+00 0.99349676E+00 0.99399701E+00 0.99449726E+00 0.99499750E+00 - 0.99549775E+00 0.99599800E+00 0.99649824E+00 0.99699849E+00 0.99749873E+00 - 0.99799896E+00 0.99849919E+00 0.99899939E+00 0.99949950E+00 0.99998812E+00 - 0.10000000E+01 - 0.10000000E+01 - 0.00000000E+00 - 0.00000000E+00 - 0.00000000E+00 diff --git a/bench/POTENTIALS/CdTe.bop.table b/bench/POTENTIALS/CdTe.bop.table new file mode 120000 index 0000000000..8083830292 --- /dev/null +++ b/bench/POTENTIALS/CdTe.bop.table @@ -0,0 +1 @@ +../../potentials/CdTe.bop.table \ No newline at end of file diff --git a/bench/POTENTIALS/Cu_u3.eam b/bench/POTENTIALS/Cu_u3.eam deleted file mode 100644 index 3a9fd413ca..0000000000 --- a/bench/POTENTIALS/Cu_u3.eam +++ /dev/null @@ -1,305 +0,0 @@ -Cu functions (universal 3), SM Foiles et al, PRB, 33, 7983 (1986) - 29 63.550 3.6150 FCC - 500 5.0100200400801306e-04 500 1.0000000000000009e-02 4.9499999999999886e+00 - 0. -3.1561636903424350e-01 -5.2324876182494506e-01 -6.9740831416804383e-01 -8.5202525457518519e-01 - -9.9329216586042435e-01 -1.1246331970890324e+00 -1.2481882647347859e+00 -1.3654054700363645e+00 -1.4773214276236644e+00 - -1.5847099936904741e+00 -1.6865851873526410e+00 -1.7843534091637920e+00 -1.8790616476576076e+00 -1.9710188604521761e+00 - -2.0604838665854572e+00 -2.1476762477372944e+00 -2.2327843595560068e+00 -2.3159713409697673e+00 -2.3973797031286352e+00 - -2.4771348895887826e+00 -2.5553480773272810e+00 -2.6321184083774227e+00 -2.7075347880408458e+00 -2.7816773487592030e+00 - -2.8546186529652005e+00 -2.9264246898861899e+00 -2.9971557080624507e+00 -3.0668669157065978e+00 -3.1356090736776849e+00 - -3.2034290008357829e+00 -3.2703700069757247e+00 -3.3364722658277230e+00 -3.4017731379735778e+00 -3.4663074517059016e+00 - -3.5301077484029122e+00 -3.5932044977085980e+00 -3.6556262870729199e+00 -3.7173999892229403e+00 -3.7785509106421671e+00 - -3.8391029237823773e+00 -3.8990785849196925e+00 -3.9584992397079333e+00 -4.0173851179270912e+00 -4.0744518500210916e+00 - -4.1306733564032641e+00 -4.1864034067843932e+00 -4.2416582335814326e+00 -4.2964533268445280e+00 -4.3508034838872618e+00 - -4.4047228547107977e+00 -4.4582249835318351e+00 -4.5113228468570128e+00 -4.5640288884490872e+00 -4.6163550514904443e+00 - -4.6683128082199232e+00 -4.7199131872767452e+00 -4.7711667990036801e+00 -4.8220838587683374e+00 -4.8726742087289665e+00 - -4.9229473379113813e+00 -4.9729124009208192e+00 -5.0225782353423369e+00 -5.0719533779533492e+00 -5.1210460798461668e+00 - -5.1698643205481289e+00 -5.2184158212228908e+00 -5.2667080570261362e+00 -5.3147482686812282e+00 -5.3625434733324937e+00 - -5.4101004747367369e+00 -5.4574258728391953e+00 -5.5045260727784751e+00 -5.5514072933650311e+00 -5.5980755750691458e+00 - -5.6445367875538750e+00 -5.6907966367860183e+00 -5.7368606717507191e+00 -5.7827342908000219e+00 -5.8284227476608805e+00 - -5.8739311571204382e+00 -5.9192645004390272e+00 -5.9644276303605182e+00 -6.0094252761103064e+00 -6.0542620478988169e+00 - -6.0989424413057520e+00 -6.1434708414539330e+00 -6.1878515269578429e+00 -6.2320886736884802e+00 -6.2761863583589275e+00 - -6.3201485619430571e+00 -6.3639791729330000e+00 -6.4076819904493902e+00 -6.4512607272098990e+00 -6.4947190123648113e+00 - -6.5380603942065250e+00 -6.5812883427622069e+00 -6.6243939095620874e+00 -6.6670830925929181e+00 -6.7096660473058591e+00 - -6.7521459135001862e+00 -6.7945257643836499e+00 -6.8368086085521611e+00 -6.8789973918942735e+00 -6.9210949994162263e+00 - -6.9631042569970703e+00 -7.0050279330721992e+00 -7.0468687402560874e+00 -7.0886293368973554e+00 -7.1303123285804020e+00 - -7.1719202695651916e+00 -7.2134556641788095e+00 -7.2549209681507421e+00 -7.2963185899023415e+00 -7.3376508917899628e+00 - -7.3789201913012903e+00 -7.4201287622117036e+00 -7.4612788356982946e+00 -7.5023726014152032e+00 -7.5434122085331978e+00 - -7.5843997667427345e+00 -7.6253373472216595e+00 -7.6662269835740062e+00 -7.7070706727342895e+00 -7.7478703758424388e+00 - -7.7886280190928119e+00 -7.8293454945503811e+00 -7.8700246609474789e+00 -7.9106673444489104e+00 -7.9512753393968865e+00 - -7.9918504090315139e+00 -8.0323942861870705e+00 -8.0729086739704030e+00 -8.1133952464140293e+00 -8.1538556491162808e+00 - -8.1942914998523975e+00 -8.2347043891773524e+00 -8.2750958810033808e+00 -8.3154675131659701e+00 -8.3558207979692725e+00 - -8.3961572227176475e+00 -8.4364782502312892e+00 -8.4767853193496308e+00 -8.5170798454139458e+00 -8.5573632207473906e+00 - -8.5976368151087286e+00 -8.6379019761436666e+00 -8.6781600298199919e+00 -8.7184122808490656e+00 -8.7586600130993020e+00 - -8.7989044899963460e+00 -8.8391469549140993e+00 -8.8793886315543773e+00 -8.9196307243150841e+00 -8.9598744186541239e+00 - -9.0001208814363167e+00 -9.0403712612778122e+00 -9.0806266888772029e+00 -9.1208882773446476e+00 -9.1611571225108719e+00 - -9.2014343032440138e+00 -9.2417208817437881e+00 -9.2820179038447463e+00 -9.3223263992829857e+00 -9.3626473819958278e+00 - -9.4029818503831279e+00 -9.4433307875392529e+00 -9.4836951616705960e+00 -9.5237840547885071e+00 -9.5637918926951784e+00 - -9.6038142178817338e+00 -9.6438519061474608e+00 -9.6839058194810832e+00 -9.7239768064614509e+00 -9.7640657024289226e+00 - -9.8041733297054634e+00 -9.8443004978059889e+00 -9.8844480036373170e+00 -9.9246166317080906e+00 -9.9648071543198853e+00 - -1.0005020331762637e+01 -1.0045256912501884e+01 -1.0085517633366123e+01 -1.0125803219723423e+01 -1.0166114385662183e+01 - -1.0206451834160134e+01 -1.0246816257258331e+01 -1.0287208336224353e+01 -1.0327628741713852e+01 -1.0368078133934148e+01 - -1.0408557162795717e+01 -1.0449066468066974e+01 -1.0489606679525650e+01 -1.0530178417100558e+01 -1.0570782291022510e+01 - -1.0611418901960292e+01 -1.0652088841158786e+01 -1.0692792690577562e+01 -1.0733531023022920e+01 -1.0774304402276016e+01 - -1.0815113383222808e+01 -1.0855958511980305e+01 -1.0896840326017184e+01 -1.0937759354276295e+01 -1.0978716117290730e+01 - -1.1019711127305925e+01 -1.1060744888386239e+01 -1.1101817896531486e+01 -1.1142930639787664e+01 -1.1184083598352004e+01 - -1.1225277244679319e+01 -1.1266512043589387e+01 -1.1307788452364719e+01 -1.1349106920870327e+01 -1.1390467891550486e+01 - -1.1431871799781504e+01 -1.1473319073642074e+01 -1.1514810134213008e+01 -1.1556345395619132e+01 -1.1597925265115521e+01 - -1.1639550143177303e+01 -1.1681220423591583e+01 -1.1722936493536452e+01 -1.1764698733669888e+01 -1.1806507518187232e+01 - -1.1848363215029394e+01 -1.1890266185706139e+01 -1.1932216785634637e+01 -1.1974215364086319e+01 -1.2016262264291129e+01 - -1.2058357823507606e+01 -1.2100502373105996e+01 -1.2142696238631970e+01 -1.2184939739884385e+01 -1.2227233190982815e+01 - -1.2269576900438324e+01 -1.2311971171220080e+01 -1.2354416300827552e+01 -1.2396912581348374e+01 -1.2439460299532641e+01 - -1.2482059736851909e+01 -1.2524711169562636e+01 -1.2567414868772744e+01 -1.2610171100495961e+01 -1.2652980125719694e+01 - -1.2695842200459083e+01 -1.2738757575819193e+01 -1.2781726498053729e+01 -1.2824749208615117e+01 -1.2867825944219817e+01 - -1.2910956936899197e+01 -1.2954142414054047e+01 -1.2997382598508125e+01 -1.3040677708563408e+01 -1.3084027958052218e+01 - -1.3127433556386677e+01 -1.3170894708610035e+01 -1.3214411615448739e+01 -1.3257984473359954e+01 -1.3301613474583519e+01 - -1.3345298807190659e+01 -1.3389040655121903e+01 -1.3432839198243016e+01 -1.3476694612386723e+01 -1.3520607069407617e+01 - -1.3564576737214225e+01 -1.3608603779754390e+01 -1.3652688357330362e+01 -1.3696830626228689e+01 -1.3741030739041094e+01 - -1.3785288844633044e+01 -1.3829605088192579e+01 -1.3873979611263849e+01 -1.3918412551792358e+01 -1.3962904044165157e+01 - -1.4007454219246995e+01 -1.4052063204422609e+01 -1.4096731123636516e+01 -1.4141458097424390e+01 -1.4186244242962175e+01 - -1.4231089674089560e+01 -1.4275994501358696e+01 -1.4320958832063411e+01 -1.4365982770278379e+01 -1.4411066416893846e+01 - -1.4456209869649911e+01 -1.4501413223171539e+01 -1.4546676569005058e+01 -1.4591999995647598e+01 -1.4637383588581656e+01 - -1.4682827430315228e+01 -1.4728331600403862e+01 -1.4773896175488971e+01 -1.4819521229330235e+01 -1.4865206832833337e+01 - -1.4910953054084985e+01 -1.4956759958383259e+01 -1.5002627608264334e+01 -1.5048556063539081e+01 -1.5094545381317744e+01 - -1.5140595616041765e+01 -1.5186706819511983e+01 -1.5232879040916600e+01 -1.5279112326867676e+01 -1.5325406721414765e+01 - -1.5371762266086876e+01 -1.5418178999911675e+01 -1.5464656959446415e+01 -1.5511196178805903e+01 -1.5557796689685119e+01 - -1.5604458521389688e+01 -1.5651181700861002e+01 -1.5697966252703509e+01 -1.5744812199205967e+01 -1.5791719560374304e+01 - -1.5838688353945599e+01 -1.5885718595428898e+01 -1.5932810298111235e+01 -1.5979963473102316e+01 -1.6027178129340314e+01 - -1.6074454273625634e+01 -1.6121791910645470e+01 -1.6169191042992907e+01 -1.6216651671189425e+01 -1.6264173793714576e+01 - -1.6311757407021901e+01 -1.6359402505566209e+01 -1.6407109081822910e+01 -1.6454877126310635e+01 -1.6502706627614998e+01 - -1.6550597572407241e+01 -1.6598549945469813e+01 -1.6646563729715353e+01 -1.6694638906205682e+01 -1.6742775454176012e+01 - -1.6790973351056778e+01 -1.6839232572488413e+01 -1.6887553092348412e+01 -1.6935934882766333e+01 -1.6984377914146876e+01 - -1.7032882155186826e+01 -1.7081447572897673e+01 -1.7130074132623690e+01 -1.7178761798061373e+01 -1.7227510531275698e+01 - -1.7276320292724563e+01 -1.7325191041271864e+01 -1.7374122734215121e+01 -1.7423115327299456e+01 -1.7472168774711918e+01 - -1.7521283029136725e+01 -1.7570458041655343e+01 -1.7619693762170868e+01 -1.7668990138814479e+01 -1.7718347118374936e+01 - -1.7767764646209685e+01 -1.7817242666259403e+01 -1.7866781121071881e+01 -1.7916379951810882e+01 -1.7966039098283659e+01 - -1.8015758498943796e+01 -1.8065538090918608e+01 -1.8115377810021755e+01 -1.8165277590764617e+01 -1.8215237366381530e+01 - -1.8265257068836149e+01 -1.8315336628844307e+01 -1.8365475975885602e+01 -1.8415675038220570e+01 -1.8465933742903644e+01 - -1.8516252015799409e+01 -1.8566629781600568e+01 -1.8617066963838965e+01 -1.8667563484898778e+01 -1.8718119266039025e+01 - -1.8768734227397317e+01 -1.8819408288014415e+01 -1.8870141365839345e+01 -1.8920933377750998e+01 -1.8971784239569388e+01 - -1.9022693866067016e+01 -1.9073662170983084e+01 -1.9124689067045438e+01 -1.9175774465969539e+01 -1.9226918278483254e+01 - -1.9278120414338218e+01 -1.9329380782317116e+01 -1.9380699290257098e+01 -1.9432075845048644e+01 -1.9483510352663075e+01 - -1.9535002718153464e+01 -1.9586552845676124e+01 -1.9638160638497766e+01 -1.9689825999008235e+01 -1.9741548828738019e+01 - -1.9793329028359494e+01 -1.9845166497711489e+01 -1.9897061135804051e+01 -1.9949012840833348e+01 -2.0001021510188707e+01 - -2.0053087040468540e+01 -2.0105209327494322e+01 -2.0157388266314911e+01 -2.0209623751249865e+01 -2.0261915675825890e+01 - -2.0314263932714312e+01 -2.0366668414255741e+01 -2.0419129011700647e+01 -2.0471645615726288e+01 -2.0524218116314501e+01 - -2.0576846402769888e+01 -2.0629530363722893e+01 -2.0682269887147754e+01 -2.0735064860369221e+01 -2.0787915170073120e+01 - -2.0840820702317274e+01 -2.0893781342541502e+01 -2.0946796975575580e+01 -2.0999867485656864e+01 -2.1052992756428125e+01 - -2.1106172670961428e+01 -2.1159407111702421e+01 -2.1212695960751944e+01 -2.1266039099329419e+01 -2.1319436408360275e+01 - -2.1372887768154328e+01 -2.1426393058473991e+01 -2.1479952158748461e+01 -2.1533564947619766e+01 -2.1587231303431395e+01 - -2.1640951103995235e+01 -2.1694724226644553e+01 -2.1748550548245930e+01 -2.1802429945213817e+01 -2.1856362293508028e+01 - -2.1910347468648524e+01 -2.1964385345728829e+01 -2.2018475799410339e+01 -2.2072618703948137e+01 -2.2126813933181779e+01 - -2.2181061360561898e+01 -2.2235360859143157e+01 -2.2289712301596296e+01 -2.2344115560361388e+01 -2.2398570507087584e+01 - -2.2453077013515781e+01 -2.2507634950890292e+01 -2.2562244190064348e+01 -2.2616904601590250e+01 -2.2671616055687764e+01 - -2.2726378422261405e+01 -2.2781191570901910e+01 -2.2836055370890790e+01 -2.2890969691219198e+01 -2.2945934400583837e+01 - -2.3000949367399926e+01 -2.3056014459808921e+01 -2.3111129545678523e+01 -2.3166294492618363e+01 -2.3221509167983868e+01 - -2.3276773438880355e+01 -2.3332087172173260e+01 -2.3387450234495873e+01 -2.3442862492249787e+01 -2.3498323811618320e+01 - -2.3553834058571510e+01 -2.3609393098863848e+01 -2.3665000798062465e+01 -2.3720657021526677e+01 -2.3776361634436626e+01 - -2.3832114501780552e+01 -2.3887915488378439e+01 -2.3943764458878377e+01 -2.3999661277761106e+01 -2.4055605809352301e+01 - -2.4111597917826657e+01 -2.4167637467209488e+01 -2.4223724321393092e+01 -2.4279858344124932e+01 -2.4336039399030597e+01 - -2.4392267349614485e+01 -2.4448542059257761e+01 -2.4504863391234494e+01 -2.4561231208711206e+01 -2.4617645374753693e+01 - -2.4674105752332935e+01 -2.4730612204329191e+01 -2.4787164593538137e+01 -2.4843762782677913e+01 -2.4900406634392539e+01 - -2.4957096011252133e+01 -2.5013830775771112e+01 -2.5070610790396586e+01 -2.5127435917366029e+01 -2.5184306019355063e+01 - -2.5241220958503845e+01 -2.5298180597080318e+01 -2.5355184797285347e+01 -2.5412233421340488e+01 -2.5469326331427965e+01 - 1.0000000000000000e+01 1.0801534951171448e+01 1.0617375158244670e+01 1.0436688151228793e+01 1.0259403283230313e+01 - 1.0085451405601304e+01 9.9147648356938589e+00 9.7472773253084029e+00 9.5829240298195373e+00 9.4216414779654656e+00 - 9.2633675422888473e+00 9.1080414102110012e+00 8.9556035557302494e+00 8.8059957117284853e+00 8.6591608428743143e+00 - 8.5150431191084976e+00 8.3735878897014118e+00 8.2347416578681987e+00 8.0984520559319435e+00 7.9646678210201571e+00 - 7.8333387712866624e+00 7.7044157826449009e+00 7.5778507660022569e+00 7.4535966449878401e+00 7.3316073341564731e+00 - 7.2118377176659578e+00 7.0942436284134374e+00 6.9787818276207929e+00 6.8654099848621115e+00 6.7540866585212882e+00 - 6.6447712766712357e+00 6.5374241183666584e+00 6.4320062953403578e+00 6.3284797340946000e+00 6.2268071583795574e+00 - 6.1269520720505000e+00 6.0288787422946655e+00 5.9325521832211621e+00 5.8379381398054591e+00 5.7450030721804524e+00 - 5.6537141402680220e+00 5.5640391887418730e+00 5.4759467323160322e+00 5.3894059413519244e+00 5.3043866277758980e+00 - 5.2208592313018016e+00 5.1387948059520454e+00 5.0581650068698707e+00 4.9789420774166615e+00 4.9010988365496075e+00 - 4.8246086664712777e+00 4.7494455005478358e+00 4.6755838114879396e+00 4.6029985997776066e+00 4.5316653823665547e+00 - 4.4615601815980312e+00 4.3926595143797726e+00 4.3249403815888456e+00 4.2583802577058805e+00 4.1929570806747449e+00 - 4.1286492419807814e+00 4.0654355769448500e+00 4.0032953552278059e+00 3.9422082715398403e+00 3.8821544365521561e+00 - 3.8231143680053350e+00 3.7650689820101348e+00 3.7079995845373759e+00 3.6518878630917868e+00 3.5967158785670392e+00 - 3.5424660572764992e+00 3.4891211831576925e+00 3.4366643901451397e+00 3.3850791547089756e+00 3.3343492885547761e+00 - 3.2844589314827459e+00 3.2353925444006251e+00 3.1871349024889781e+00 3.1396710885139782e+00 3.0929864862859660e+00 - 3.0470667742591075e+00 3.0018979192706325e+00 2.9574661704151453e+00 2.9137580530522627e+00 2.8707603629438552e+00 - 2.8284601605189152e+00 2.7868447652620318e+00 2.7459017502243626e+00 2.7056189366531243e+00 2.6659843887374848e+00 - 2.6269864084689516e+00 2.5886135306124487e+00 2.5508545177868598e+00 2.5136983556521244e+00 2.4771342482006986e+00 - 2.4411516131510069e+00 2.4057400774406830e+00 2.3708894728175807e+00 2.3365898315265383e+00 2.3028313820887689e+00 - 2.2696045451740474e+00 2.2368999295609058e+00 2.2047083281853901e+00 2.1730207142748128e+00 2.1418282375653348e+00 - 2.1111222206016862e+00 2.0808941551166384e+00 2.0511356984892615e+00 2.0218386702793651e+00 1.9929950488372441e+00 - 1.9645969679867363e+00 1.9366367137799969e+00 1.9091067213223525e+00 1.8819995716660998e+00 1.8553079887710169e+00 - 1.8290248365311754e+00 1.8031431158652609e+00 1.7776559618705363e+00 1.7525566410377422e+00 1.7278385485262007e+00 - 1.7034952054980579e+00 1.6795202565098251e+00 1.6559074669601728e+00 1.6326507205929630e+00 1.6097440170540054e+00 - 1.5871814695006066e+00 1.5649573022624637e+00 1.5430658485530984e+00 1.5215015482308161e+00 1.5002589456071576e+00 - 1.4793326873036463e+00 1.4587175201534635e+00 1.4384082891492156e+00 1.4183999354343300e+00 1.3986874943378140e+00 - 1.3792660934511431e+00 1.3601309507466510e+00 1.3412773727360872e+00 1.3227007526689576e+00 1.3043965687692420e+00 - 1.2863603825102174e+00 1.2685878369261090e+00 1.2510746549598935e+00 1.2338166378466084e+00 1.2168096635312082e+00 - 1.2000496851203266e+00 1.1835327293670588e+00 1.1672548951882362e+00 1.1512123522134416e+00 1.1354013393647548e+00 - 1.1198181634671940e+00 1.1044591978884952e+00 1.0893208812080033e+00 1.0743997159140335e+00 1.0596922671287743e+00 - 1.0451951613605601e+00 1.0309050852825337e+00 1.0168187845373140e+00 1.0029330625671378e+00 9.8924477946872713e-01 - 9.7575085087259694e-01 9.6244824684604424e-01 9.4933399081931213e-01 9.3640515853477169e-01 9.2365887701803118e-01 - 9.1109232357100112e-01 8.9870272478628266e-01 8.8648735558209424e-01 8.7444353825798160e-01 8.6256864157006774e-01 - 8.5086007982605949e-01 8.3931531199913678e-01 8.2793184086057892e-01 8.1670721213066955e-01 8.0563901364725510e-01 - 7.9472487455206675e-01 7.8396246449372953e-01 7.7334949284779597e-01 7.6288370795296245e-01 7.5256289636327622e-01 - 7.4238488211596021e-01 7.3234752601463171e-01 7.2244872492728618e-01 7.1268641109915265e-01 7.0305855147956464e-01 - 6.9356314706317335e-01 6.8419823224459719e-01 6.7496187418651843e-01 6.6585217220099224e-01 6.5686725714346750e-01 - 6.4800529081937697e-01 6.3926446540306614e-01 6.3064300286859520e-01 6.2213915443241774e-01 6.1375120000748140e-01 - 6.0547744766850542e-01 5.9731623312840654e-01 5.8926591922531912e-01 5.8132489542033028e-01 5.7349157730523359e-01 - 5.6576440612064971e-01 5.5814184828379609e-01 5.5062239492602316e-01 5.4320456143964790e-01 5.3588688703414888e-01 - 5.2866793430138515e-01 5.2154628878946241e-01 5.1452055858552015e-01 5.0758937390678227e-01 5.0075138669987496e-01 - 4.9400527024841523e-01 4.8734971878830358e-01 4.8078344713093557e-01 4.7430519029390972e-01 4.6791370313911962e-01 - 4.6160776001828552e-01 4.5538615442535857e-01 4.4924769865602876e-01 4.4319122347399365e-01 4.3721557778390086e-01 - 4.3131962831075654e-01 4.2550225928575891e-01 4.1976237213834899e-01 4.1409888519439697e-01 4.0851073338028954e-01 - 4.0299686793291478e-01 3.9755625611540779e-01 3.9218788093843493e-01 3.8689074088692443e-01 3.8166384965228239e-01 - 3.7650623586976018e-01 3.7141694286095728e-01 3.6639502838144544e-01 3.6143956437320846e-01 3.5654963672189943e-01 - 3.5172434501901328e-01 3.4696280232829579e-01 3.4226413495707497e-01 3.3762748223177219e-01 3.3305199627774762e-01 - 3.2853684180349596e-01 3.2408119588894380e-01 3.1968424777773841e-01 3.1534519867361155e-01 3.1106326154055530e-01 - 3.0683766090688813e-01 3.0266763267296426e-01 2.9855242392259740e-01 2.9449129273803010e-01 2.9048350801842027e-01 - 2.8652834930171167e-01 2.8262510658997009e-01 2.7877308017785829e-01 2.7497158048439907e-01 2.7121992788793392e-01 - 2.6751745256412462e-01 2.6386349432690004e-01 2.6025740247248841e-01 2.5669853562631850e-01 2.5318626159266877e-01 - 2.4971995720718354e-01 2.4629900819206618e-01 2.4292280901402563e-01 2.3959076274464408e-01 2.3630228092351846e-01 - 2.3305678342376535e-01 2.2985369832002167e-01 2.2669246175884616e-01 2.2357251783148069e-01 2.2049331844890929e-01 - 2.1745432321916880e-01 2.1445499932688783e-01 2.1149482141498144e-01 2.0857327146848004e-01 2.0568983870040114e-01 - 2.0284401943976604e-01 2.0003531702142130e-01 1.9726324167804599e-01 1.9452731043391402e-01 1.9182704700056608e-01 - 1.8916198167437770e-01 1.8653165123588344e-01 1.8393559885088084e-01 1.8137337397327791e-01 1.7884453224959973e-01 - 1.7634863542523593e-01 1.7388525125224241e-01 1.7145395339876757e-01 1.6905432136008169e-01 1.6668594037109052e-01 - 1.6434840132036665e-01 1.6204130066570688e-01 1.5976424035106618e-01 1.5751682772493769e-01 1.5529867546015819e-01 - 1.5310940147503249e-01 1.5094862885580707e-01 1.4881598578045718e-01 1.4671110544379484e-01 1.4463362598375351e-01 - 1.4258319040899092e-01 1.4055944652768915e-01 1.3856204687748974e-01 1.3659064865666881e-01 1.3464491365640630e-01 - 1.3272450819420012e-01 1.3082910304837103e-01 1.2895837339364213e-01 1.2711199873781265e-01 1.2528966285941134e-01 - 1.2349105374641756e-01 1.2171586353596986e-01 1.1996378845505173e-01 1.1823452876211782e-01 1.1652778868972380e-01 - 1.1484327638801961e-01 1.1318070386919254e-01 1.1153978695277944e-01 1.0992024521187505e-01 1.0832180192018548e-01 - 1.0674418399992769e-01 1.0518712197055757e-01 1.0365034989832456e-01 1.0213360534659532e-01 1.0063662932698936e-01 - 9.9159166251264974e-02 9.7700963883974534e-02 9.6261773295835962e-02 9.4841348817873428e-02 9.3439447996227276e-02 - 9.2055831547688260e-02 9.0690263315935660e-02 8.9342510228411331e-02 8.8012342253891429e-02 8.6699532360706044e-02 - 8.5403856475584128e-02 8.4125093443141896e-02 8.2863024985984080e-02 8.1617435665412685e-02 8.0388112842733062e-02 - 7.9174846641143493e-02 7.7977429908209661e-02 7.6795658178889781e-02 7.5629329639115728e-02 7.4478245089953710e-02 - 7.3342207912248103e-02 7.2221024031827064e-02 7.1114501885225945e-02 7.0022452385910761e-02 6.8944688890991479e-02 - 6.7881027168450458e-02 6.6831285364849169e-02 6.5795283973477225e-02 6.4772845803028556e-02 6.3763795946680801e-02 - 6.2767961751651669e-02 6.1785172789201148e-02 6.0815260825057393e-02 5.9858059790287577e-02 5.8913405752569759e-02 - 5.7981136887894191e-02 5.7061093452682510e-02 5.6153117756271964e-02 5.5257054133826422e-02 5.4372748919636837e-02 - 5.3500050420772105e-02 5.2638808891131372e-02 5.1788876505864945e-02 5.0950107336147354e-02 5.0122357324306366e-02 - 4.9305484259319243e-02 4.8499347752635869e-02 4.7703809214351578e-02 4.6918731829721727e-02 4.6143980535982010e-02 - 4.5379421999521163e-02 4.4624924593352100e-02 4.3880358374905226e-02 4.3145595064128850e-02 4.2420508021892900e-02 - 4.1704972228691739e-02 4.0998864263647405e-02 4.0302062283785300e-02 3.9614446003616965e-02 3.8935896674993531e-02 - 3.8266297067221844e-02 3.7605531447481688e-02 3.6953485561492139e-02 3.6310046614435487e-02 3.5675103252157392e-02 - 3.5048545542616605e-02 3.4430264957581835e-02 3.3820154354582632e-02 3.3218107959093635e-02 3.2624021346983278e-02 - 3.2037791427166340e-02 3.1459316424514716e-02 3.0888495862994469e-02 3.0325230549015147e-02 2.9769422555015357e-02 - 2.9220975203265720e-02 2.8679793049885216e-02 2.8145781869070463e-02 2.7618848637539717e-02 2.7098901519172047e-02 - 2.6585849849867671e-02 2.6079604122596356e-02 2.5580075972643668e-02 2.5087178163056167e-02 2.4600824570288671e-02 - 2.4120930170012267e-02 2.3647411023137499e-02 2.3180184262011627e-02 2.2719168076792418e-02 2.2264281702001121e-02 - 2.1815445403263078e-02 2.1372580464206647e-02 2.0935609173537761e-02 2.0504454812290795e-02 2.0079041641240414e-02 - 1.9659294888467183e-02 1.9245140737102040e-02 1.8836506313223755e-02 1.8433319673904158e-02 1.8035509795416238e-02 - 1.7643006561603891e-02 1.7255740752380899e-02 1.6873644032391555e-02 1.6496648939823388e-02 1.6124688875347792e-02 - 1.5757698091213634e-02 1.5395611680482646e-02 1.5038365566394485e-02 1.4685896491875350e-02 1.4338142009180710e-02 - 1.3995040469664266e-02 1.3656531013687800e-02 1.3322553560652262e-02 1.2993048799157525e-02 1.2667958177290606e-02 - 1.2347223893038994e-02 1.2030788884814458e-02 1.1718596822117511e-02 1.1410592096299910e-02 1.1106719811460941e-02 - 1.0806925775450060e-02 1.0511156490982998e-02 1.0219359146882878e-02 9.9314816094114855e-03 9.6474724137328716e-03 - 9.3672807554677773e-03 9.0908564823645177e-03 8.8181500860711193e-03 8.5491126940134832e-03 8.2836960613733579e-03 - 8.0218525631707838e-03 7.7635351864465685e-03 7.5086975225370223e-03 7.2572937594544973e-03 7.0092786743605195e-03 - 6.7646076261301813e-03 6.5232365480138998e-03 6.2851219403949887e-03 6.0502208636273869e-03 5.8184909309735300e-03 - 5.5898903016277091e-03 5.3643776738254711e-03 5.1419122780385074e-03 4.9224538702609122e-03 4.7059627253757674e-03 - 4.4923996305976099e-03 4.2817258790122659e-03 4.0739032631877392e-03 3.8688940688609841e-03 3.6666610687164924e-03 - 3.4671675162341598e-03 3.2703771396105918e-03 3.0762541357672313e-03 2.8847631644254856e-03 2.6958693422570179e-03 - 2.5095382371091990e-03 2.3257358623008373e-03 2.1444286709895732e-03 1.9655835506104946e-03 1.7891678173820869e-03 - 1.6151492108847365e-03 1.4434958887007410e-03 1.2741764211267048e-03 1.1071597859496629e-03 9.4241536328815156e-04 - 7.7991293049733956e-04 6.1962265713921827e-04 4.6151510001329887e-04 3.0556119825198014e-04 1.5173226847375876e-04 - 0. 0. 0. 0. 0. - 0. 5.4383329664155645e-05 9.3944898415945083e-04 4.3251847212615047e-03 1.2334244035325348e-02 - 2.7137722173468548e-02 5.0697119791449641e-02 8.4607638668976470e-02 1.3001641279549414e-01 1.8759487452762702e-01 - 2.5754900895683441e-01 3.3965493779430744e-01 4.3331024634064264e-01 5.3759384878832961e-01 6.5132908316254046e-01 - 7.7314622535699939e-01 9.0154178511424377e-01 1.0349328562818201e+00 1.1717054897399350e+00 1.3102565818166738e+00 - 1.4490291582473986e+00 1.5865412121263560e+00 1.7214084470448441e+00 1.8523614026473965e+00 1.9782575145276269e+00 - 2.0980886961566938e+00 2.2109850373516764e+00 2.3162151996095730e+00 2.4131840597491703e+00 2.5014281146549706e+00 - 2.5806091153285706e+00 2.6505063508648590e+00 2.7110079545661563e+00 2.7621015568249447e+00 2.8038645637913220e+00 - 2.8364542979766156e+00 2.8600981973448825e+00 2.8750842333755031e+00 2.8817516761559574e+00 2.8804823057701157e+00 - 2.8716921439699092e+00 2.8558237581894161e+00 2.8333391711552594e+00 2.8047133934346959e+00 2.7704285829676252e+00 - 2.7309688247181469e+00 2.6868155147671331e+00 2.6384433262347358e+00 2.5863167291097398e+00 2.5308870321738226e+00 - 2.4725899125317596e+00 2.4118433966060167e+00 2.3490462556752334e+00 2.2845767789603002e+00 2.2187918877813502e+00 - 2.1520265552815943e+00 2.0845934975626363e+00 2.0167831036919637e+00 1.9488635738636404e+00 1.8810812369508270e+00 - 1.8136610207193371e+00 1.7468070500507196e+00 1.6807033505858371e+00 1.6155146372447149e+00 1.5513871690559142e+00 - 1.4884496536383409e+00 1.4268141864958608e+00 1.3665772120042590e+00 1.3078204945836447e+00 1.2506120900523854e+00 - 1.1950073085502879e+00 1.1410496616995687e+00 1.0887717878420631e+00 1.0381963502565981e+00 9.8933690422003551e-01 - 9.4219872964247031e-01 8.9677962677415124e-01 8.5307067316958651e-01 8.1105694069385592e-01 7.7071817188505065e-01 - 7.3202941544290212e-01 6.9496162100761794e-01 6.5948219372701189e-01 6.2555550939233484e-01 5.9314339115629977e-01 - 5.6220554903693554e-01 5.3269998356387660e-01 5.0458335504023211e-01 4.7781131998032222e-01 4.5233883634534777e-01 - 4.2812043923464138e-01 4.0511048870905242e-01 3.8326339142174781e-01 3.6253379771729577e-01 3.4287677583286325e-01 - 3.2424796479760154e-01 3.0660370758054967e-01 2.8990116598452254e-01 2.7409841872609064e-01 2.5915454407883409e-01 - 2.4502968839369110e-01 2.3168512174254197e-01 2.1908328186436687e-01 2.0718780752542632e-01 1.9596356233750800e-01 - 1.8537665001230508e-01 1.7539442196444632e-01 1.6598547811304609e-01 1.5711966166996927e-01 1.4876804864444715e-01 - 1.4090293273673637e-01 1.3349780623990259e-01 1.2652733751724909e-01 1.1996734557434463e-01 1.1379477219856060e-01 - 1.0798765209582406e-01 1.0252508141368288e-01 9.7387185001678311e-02 9.2555082724584015e-02 8.8010855111109620e-02 - 8.3737508589961873e-02 7.9718940536826377e-02 7.5939904329596963e-02 7.2385974585237101e-02 6.9043512729294765e-02 - 6.5899633029043336e-02 6.2942169202580001e-02 6.0159641699440547e-02 5.7541225732930634e-02 5.5076720130546430e-02 - 5.2756517056398833e-02 5.0571572648238083e-02 4.8513378601664936e-02 4.6573934725081756e-02 4.4745722480991068e-02 - 4.3021679522073253e-02 4.1395175224364866e-02 3.9859987214311721e-02 3.8410278881708670e-02 3.7040577866510604e-02 - 3.5745755503880039e-02 3.4521007208912380e-02 3.3361833779917971e-02 3.2264023597108116e-02 3.1223635691821294e-02 - 3.0236983660070216e-02 2.9300620393215571e-02 2.8411323597772320e-02 2.7566082075896281e-02 2.6762082737777249e-02 - 2.5996698317105604e-02 2.5267475760840985e-02 2.4572125264713973e-02 2.3908509926274246e-02 2.3274635987705516e-02 - 2.2668643641204911e-02 2.2088798370316409e-02 2.1533482801290083e-02 2.1001189039288493e-02 2.0490511464994254e-02 - 2.0000139967999431e-02 1.9528853594166895e-02 1.9075514584991349e-02 1.8639062787818239e-02 1.8218510416650235e-02 - 1.7812937144080498e-02 1.7421485505751177e-02 1.7043356599549031e-02 1.6677806062561751e-02 1.6324140309613155e-02 - 1.5981713017976018e-02 1.5649921843605585e-02 1.5328205354974755e-02 1.5016040171312250e-02 1.4712938292708366e-02 - 1.4418444610242331e-02 1.4132134584901757e-02 1.3853612084676337e-02 1.3582507369821917e-02 1.3318475216818060e-02 - 1.3061193172097418e-02 1.2810359927147186e-02 1.2565693807050415e-02 1.2326931365025051e-02 1.2093826075940506e-02 - 1.1866147122233661e-02 1.1643678266026136e-02 1.1426216801644407e-02 1.1213572583084475e-02 1.1005567121320226e-02 - 1.0802032746662471e-02 1.0602811831688208e-02 1.0407756070544782e-02 1.0216725810699157e-02 1.0029589433467268e-02 - 9.8462227798860602e-03 9.6665086187306404e-03 9.4903361536790021e-03 9.3176005668363371e-03 9.1482025960089031e-03 - 8.9820481433065535e-03 8.8190479128032462e-03 8.6591170751522117e-03 8.5021749571883021e-03 8.3481447546937537e-03 - 8.1969532666261724e-03 8.0485306492223962e-03 7.9028101885199598e-03 7.7597280899136256e-03 7.6192232834934315e-03 - 7.4812372439735375e-03 7.3457138241272979e-03 7.2125991007052359e-03 7.0818412319012813e-03 6.9533903254870300e-03 - 6.8271983168139705e-03 6.7032188559211503e-03 6.5814072030662141e-03 6.4617201320263939e-03 6.3441158405819764e-03 - 6.2285538676237207e-03 6.1149950163802147e-03 6.0034012832899109e-03 5.8937357920846312e-03 5.7859627326801166e-03 - 5.6800473044990030e-03 5.5759556638887986e-03 5.4736548753111791e-03 5.3731128660109428e-03 5.2742983838981461e-03 - 5.1771809583849582e-03 5.0817308639591330e-03 4.9879190862693046e-03 4.8957172905357560e-03 4.8050977921015592e-03 - 4.7160335289582467e-03 4.6284980360953021e-03 4.5424654215287241e-03 4.4579103438822931e-03 4.3748079913988880e-03 - 4.2931340622749670e-03 4.2128647462132407e-03 4.1339767071033873e-03 4.0564470667446839e-03 3.9802533895282599e-03 - 3.9053736680121076e-03 3.8317863093158128e-03 3.7594701222811860e-03 3.6884043053326127e-03 3.6185684349951674e-03 - 3.5499424550168301e-03 3.4825066660512660e-03 3.4162417158645347e-03 3.3511285900229004e-03 3.2871486030347646e-03 - 3.2242833899080170e-03 3.1625148980992668e-03 3.1018253798278661e-03 3.0421973847258310e-03 2.9836137528083811e-03 - 2.9260576077371064e-03 2.8695123503632708e-03 2.8139616525287708e-03 2.7593894511106498e-03 2.7057799422959966e-03 - 2.6531175760685227e-03 2.6013870509009052e-03 2.5505733086344240e-03 2.5006615295404683e-03 2.4516371275501436e-03 - 2.4034857456453340e-03 2.3561932514012535e-03 2.3097457326723414e-03 2.2641294934160616e-03 2.2193310496436136e-03 - 2.1753371254977782e-03 2.1321346494441173e-03 2.0897107505768314e-03 2.0480527550303662e-03 2.0071481824917164e-03 - 1.9669847428123305e-03 1.9275503327108034e-03 1.8888330325659355e-03 1.8508211032951805e-03 1.8135029833145980e-03 - 1.7768672855772646e-03 1.7409027946878666e-03 1.7055984640891586e-03 1.6709434133182904e-03 1.6369269253308227e-03 - 1.6035384438881917e-03 1.5707675710093030e-03 1.5386040644797400e-03 1.5070378354209296e-03 1.4760589459142243e-03 - 1.4456576066784674e-03 1.4158241748004133e-03 1.3865491515145517e-03 1.3578231800324136e-03 1.3296370434173130e-03 - 1.3019816625059188e-03 1.2748480938728074e-03 1.2482275278369870e-03 1.2221112865106742e-03 1.1964908218862064e-03 - 1.1713577139624703e-03 1.1467036689077198e-03 1.1225205172586891e-03 1.0988002121543120e-03 1.0755348276031765e-03 - 1.0527165567835728e-03 1.0303377103750150e-03 1.0083907149206553e-03 9.8686811121878604e-04 9.6576255274356815e-04 - 9.4506680409354657e-04 9.2477373946662708e-04 9.0487634116191706e-04 8.8536769810608137e-04 8.6624100440530968e-04 - 8.4748955791986991e-04 8.2910675886310736e-04 8.1108610842155551e-04 7.9342120739794852e-04 7.7610575487466887e-04 - 7.5913354689786591e-04 7.4249847518158968e-04 7.2619452583109687e-04 7.1021577808524222e-04 6.9455640307671332e-04 - 6.7921066261025093e-04 6.6417290795844214e-04 6.4943757867335500e-04 6.3499920141575628e-04 6.2085238879914031e-04 - 6.0699183824991856e-04 5.9341233088238896e-04 5.8010873038847818e-04 5.6707598194186137e-04 5.5430911111587280e-04 - 5.4180322281523891e-04 5.2955350022104025e-04 5.1755520374872563e-04 5.0580367001857793e-04 4.9429431083891986e-04 - 4.8302261220136561e-04 4.7198413328763435e-04 4.6117450548847222e-04 4.5058943143359842e-04 4.4022468403297037e-04 - 4.3007610552883886e-04 4.2013960655883260e-04 4.1041116522908330e-04 4.0088682619821882e-04 3.9156269977118005e-04 - 3.8243496100300207e-04 3.7349984881274514e-04 3.6475366510662147e-04 3.5619277391102898e-04 3.4781360051482253e-04 - 3.3961263062063513e-04 3.3158640950565685e-04 3.2373154119109092e-04 3.1604468762060252e-04 3.0852256784754707e-04 - 3.0116195723081836e-04 2.9395968663908575e-04 2.8691264166377101e-04 2.8001776184017647e-04 2.7327203987681688e-04 - 2.6667252089326854e-04 2.6021630166557681e-04 2.5390052988028163e-04 2.4772240339593181e-04 2.4167916951265550e-04 - 2.3576812424967210e-04 2.2998661163024531e-04 2.2433202297460642e-04 2.1880179620031078e-04 2.1339341513026532e-04 - 2.0810440880823181e-04 2.0293235082175821e-04 1.9787485863260665e-04 1.9292959291436311e-04 1.8809425689761319e-04 - 1.8336659572205580e-04 1.7874439579616125e-04 1.7422548416372047e-04 1.6980772787763936e-04 1.6548903338088530e-04 - 1.6126734589430591e-04 1.5714064881157744e-04 1.5310696310104604e-04 1.4916434671449329e-04 1.4531089400280153e-04 - 1.4154473513841234e-04 1.3786403554466153e-04 1.3426699533172857e-04 1.3075184873951283e-04 1.2731686358694039e-04 - 1.2396034072819674e-04 1.2068061351527565e-04 1.1747604726729168e-04 1.1434503874632306e-04 1.1128601563955686e-04 - 1.0829743604811193e-04 1.0537778798212988e-04 1.0252558886227753e-04 9.9739385027582898e-05 9.7017751249615057e-05 - 9.4359290252773662e-05 9.1762632240957511e-05 8.9226434430383569e-05 8.6749380588361721e-05 8.4330180578390864e-05 - 8.1967569911181246e-05 7.9660309301724484e-05 7.7407184232279429e-05 7.5207004521348451e-05 7.3058603898526649e-05 - 7.0960839585107720e-05 6.8912591880629977e-05 6.6912763755002085e-05 6.4960280446513426e-05 6.3054089065330086e-05 - 6.1193158202771814e-05 5.9376477546041213e-05 5.7603057498502742e-05 5.5871928805544500e-05 5.4182142185708361e-05 - 5.2532767967318744e-05 5.0922895730446966e-05 4.9351633954125953e-05 4.7818109668823321e-05 4.6321468114150300e-05 - 4.4860872401664663e-05 4.3435503182825573e-05 4.2044558321957873e-05 4.0687252574273750e-05 3.9362817268785450e-05 - 3.8070499996214428e-05 3.6809564301621984e-05 3.5579289382025496e-05 3.4378969788611451e-05 3.3207915133769052e-05 - 3.2065449802711312e-05 3.0950912669766876e-05 2.9863656819185611e-05 2.8803049270468119e-05 2.7768470708167169e-05 - 2.6759315216115260e-05 2.5774990015931323e-05 2.4814915209964844e-05 2.3878523528387922e-05 2.2965260080560611e-05 - 2.2074582110528148e-05 2.1205958756658535e-05 2.0358870815317476e-05 1.9532810508535560e-05 1.8727281255713447e-05 - 1.7941797449145505e-05 1.7175884233475961e-05 1.6429077288930018e-05 1.5700922618341645e-05 1.4990976337865471e-05 - 1.4298804471386687e-05 1.3623982748522034e-05 1.2966096406226424e-05 1.2324739993882115e-05 1.1699517181902770e-05 - 1.1090040573734860e-05 1.0495931521266495e-05 9.9168199435395021e-06 9.3523441487842465e-06 8.8021506596591475e-06 - 8.2658940417265321e-06 7.7432367350197678e-06 7.2338488887770244e-06 6.7374081991923703e-06 6.2535997501888662e-06 - 5.7821158571569505e-06 5.3226559136389283e-06 4.8749262408651290e-06 4.4386399401326240e-06 4.0135167480073166e-06 - 3.5992828942305738e-06 3.1956709623667747e-06 2.8024197531120341e-06 2.4192741502208947e-06 2.0459849890155880e-06 - 1.6823089274468580e-06 1.3280083196495871e-06 9.8285109196557868e-07 6.4661062138351467e-07 3.1906561636122974e-07 - 0. 0. 0. 0. 0. - - diff --git a/bench/POTENTIALS/Cu_u3.eam b/bench/POTENTIALS/Cu_u3.eam new file mode 120000 index 0000000000..892d592f81 --- /dev/null +++ b/bench/POTENTIALS/Cu_u3.eam @@ -0,0 +1 @@ +../../potentials/Cu_u3.eam \ No newline at end of file diff --git a/bench/POTENTIALS/Ni.adp b/bench/POTENTIALS/Ni.adp deleted file mode 100644 index 7cc301c678..0000000000 --- a/bench/POTENTIALS/Ni.adp +++ /dev/null @@ -1,43007 +0,0 @@ -Nickel ADP potential: Mishin et al. Acta Mater 2005 pp 4029 -Data below r=1.5 A is extrapolated -F(rho) data not extrapolated -1 Ni -3001 9.7054386687161695E-04 10000 5.1685168516851690E-04 5.1680000000000001E+00 -28 58.690000 3.520000 bcc -0.0000000000000000E+00 --3.0290737299999999E-02 --5.0634721479999999E-02 --6.9797312240000006E-02 --8.8564051170000005E-02 --1.0717802630000001E-01 --1.2573466940000000E-01 --1.4427463460000001E-01 --1.6281478960000001E-01 --1.8136070720000000E-01 --1.9991233659999999E-01 --2.1846679510000000E-01 --2.3701981929999999E-01 --2.5556654820000002E-01 --2.7410195389999997E-01 --2.9262107840000001E-01 --3.1111916309999998E-01 --3.2959171329999998E-01 --3.4803452779999999E-01 --3.6644370580000002E-01 --3.8481564250000000E-01 --4.0314701679999998E-01 --4.2143477629999998E-01 --4.3967611990000000E-01 --4.5786848019999998E-01 --4.7600950640000000E-01 --4.9409704809999999E-01 --5.1212913940000004E-01 --5.3010398489999999E-01 --5.4801994549999999E-01 --5.6587552679999997E-01 --5.8366936719999996E-01 --6.0140022810000004E-01 --6.1906698350000000E-01 --6.3666861190000001E-01 --6.5420418790000001E-01 --6.7167287529999997E-01 --6.8907391990000000E-01 --7.0640664360000005E-01 --7.2367043900000005E-01 --7.4086476369999998E-01 --7.5798913580000005E-01 --7.7504312980000001E-01 --7.9202637200000003E-01 --8.0893853729999998E-01 --8.2577934590000002E-01 --8.4254855930000006E-01 --8.5924597840000005E-01 --8.7587144029999997E-01 --8.9242481610000002E-01 --9.0890600820000000E-01 --9.2531494839999995E-01 --9.4165159590000003E-01 --9.5791593580000001E-01 --9.7410797689999995E-01 --9.9022775019999998E-01 --1.0062753080000000E+00 --1.0222507210000000E+00 --1.0381540800000000E+00 --1.0539854900000001E+00 --1.0697450749999999E+00 --1.0854329720000000E+00 --1.1010493330000000E+00 --1.1165943210000000E+00 --1.1320681130000001E+00 --1.1474708970000000E+00 --1.1628028710000000E+00 --1.1780642440000000E+00 --1.1932552329999999E+00 --1.2083760649999999E+00 --1.2234269739999999E+00 --1.2384082009999999E+00 --1.2533199970000000E+00 --1.2681626150000000E+00 --1.2829363170000001E+00 --1.2976413720000000E+00 --1.3122780510000001E+00 --1.3268466230000000E+00 --1.3413473300000001E+00 --1.3557803710000000E+00 --1.3701459140000001E+00 --1.3844440910000000E+00 --1.3986750180000000E+00 --1.4128387830000000E+00 --1.4269354599999999E+00 --1.4409651070000000E+00 --1.4549277709999999E+00 --1.4688234890000000E+00 --1.4826522929999999E+00 --1.4964142090000001E+00 --1.5101092580000000E+00 --1.5237374640000001E+00 --1.5372988460000001E+00 --1.5507934280000000E+00 --1.5642212350000000E+00 --1.5775822930000001E+00 --1.5908766360000000E+00 --1.6041043010000000E+00 --1.6172653290000001E+00 --1.6303597679999999E+00 --1.6433876740000000E+00 --1.6563491070000000E+00 --1.6692441370000000E+00 --1.6820728410000001E+00 --1.6948353009999999E+00 --1.7075316100000000E+00 --1.7201618670000001E+00 --1.7327261800000000E+00 --1.7452246659999999E+00 --1.7576574469999999E+00 --1.7700246570000000E+00 --1.7823264360000000E+00 --1.7945629320000001E+00 --1.8067343020000000E+00 --1.8188407110000000E+00 --1.8308823310000000E+00 --1.8428593400000000E+00 --1.8547719279999999E+00 --1.8666202890000001E+00 --1.8784046260000000E+00 --1.8901251480000001E+00 --1.9017820710000000E+00 --1.9133756200000001E+00 --1.9249060240000000E+00 --1.9363735179999999E+00 --1.9477783479999999E+00 --1.9591207589999999E+00 --1.9704010100000000E+00 --1.9816193580000001E+00 --1.9927760720000001E+00 --2.0038714230000001E+00 --2.0149056879999998E+00 --2.0258791480000000E+00 --2.0367920900000001E+00 --2.0476448060000001E+00 --2.0584375929999998E+00 --2.0691707490000000E+00 --2.0798445810000001E+00 --2.0904593960000000E+00 --2.1010155089999998E+00 --2.1115132330000002E+00 --2.1219528880000000E+00 --2.1323347990000001E+00 --2.1426592900000001E+00 --2.1529266909999998E+00 --2.1631373350000000E+00 --2.1732915560000001E+00 --2.1833896920000000E+00 --2.1934320820000002E+00 --2.2034190680000001E+00 --2.2133509960000000E+00 --2.2232282099999998E+00 --2.2330510609999998E+00 --2.2428198970000000E+00 --2.2525350720000001E+00 --2.2621969370000001E+00 --2.2718058490000002E+00 --2.2813621629999998E+00 --2.2908662350000002E+00 --2.3003184260000000E+00 --2.3097190940000001E+00 --2.3190685990000000E+00 --2.3283673029999998E+00 --2.3376155679999999E+00 --2.3468137560000000E+00 --2.3559622290000002E+00 --2.3650613510000000E+00 --2.3741114859999999E+00 --2.3831129970000000E+00 --2.3920662490000000E+00 --2.4009716060000001E+00 --2.4098294320000000E+00 --2.4186400920000000E+00 --2.4274039470000002E+00 --2.4361213639999999E+00 --2.4447927049999998E+00 --2.4534183340000002E+00 --2.4619986130000000E+00 --2.4705339039999998E+00 --2.4790245700000000E+00 --2.4874709710000000E+00 --2.4958734690000002E+00 --2.5042324219999998E+00 --2.5125481900000000E+00 --2.5208211309999999E+00 --2.5290516030000001E+00 --2.5372399630000002E+00 --2.5453865659999999E+00 --2.5534917660000001E+00 --2.5615559189999999E+00 --2.5695793750000000E+00 --2.5775624869999998E+00 --2.5855056059999999E+00 --2.5934090790000002E+00 --2.6012732559999998E+00 --2.6090984829999999E+00 --2.6168851059999998E+00 --2.6246334689999999E+00 --2.6323439160000000E+00 --2.6400167870000000E+00 --2.6476524220000002E+00 --2.6552511609999998E+00 --2.6628133410000001E+00 --2.6703392969999999E+00 --2.6778293650000000E+00 --2.6852838769999998E+00 --2.6927031650000002E+00 --2.7000875579999999E+00 --2.7074373839999999E+00 --2.7147529709999998E+00 --2.7220346430000002E+00 --2.7292827250000000E+00 --2.7364975370000000E+00 --2.7436794010000001E+00 --2.7508286360000000E+00 --2.7579455560000001E+00 --2.7650304790000000E+00 --2.7720837180000002E+00 --2.7791055839999999E+00 --2.7860963879999998E+00 --2.7930564379999998E+00 --2.7999860409999999E+00 --2.8068855030000002E+00 --2.8137551269999999E+00 --2.8205952120000002E+00 --2.8274060610000000E+00 --2.8341879699999999E+00 --2.8409412359999999E+00 --2.8476661530000000E+00 --2.8543630140000000E+00 --2.8610321110000001E+00 --2.8676737330000002E+00 --2.8742881649999998E+00 --2.8808756949999998E+00 --2.8874366060000001E+00 --2.8939711789999998E+00 --2.9004796960000001E+00 --2.9069624340000000E+00 --2.9134196710000002E+00 --2.9198516809999999E+00 --2.9262587390000001E+00 --2.9326411120000002E+00 --2.9389990730000002E+00 --2.9453328889999999E+00 --2.9516428250000000E+00 --2.9579291470000002E+00 --2.9641921160000000E+00 --2.9704319920000000E+00 --2.9766490360000000E+00 --2.9828435029999998E+00 --2.9890156490000002E+00 --2.9951657279999999E+00 --3.0012939909999998E+00 --3.0074006889999998E+00 --3.0134860689999998E+00 --3.0195503779999999E+00 --3.0255938630000001E+00 --3.0316167630000002E+00 --3.0376193229999999E+00 --3.0436017799999999E+00 --3.0495643729999999E+00 --3.0555073380000000E+00 --3.0614309110000000E+00 --3.0673353219999999E+00 --3.0732208040000000E+00 --3.0790875870000001E+00 --3.0849358969999998E+00 --3.0907659600000001E+00 --3.0965780020000002E+00 --3.1023722440000001E+00 --3.1081489080000000E+00 --3.1139082149999999E+00 --3.1196503799999999E+00 --3.1253756209999999E+00 --3.1310841510000000E+00 --3.1367761850000000E+00 --3.1424519320000002E+00 --3.1481116039999999E+00 --3.1537554079999999E+00 --3.1593835499999998E+00 --3.1649962359999999E+00 --3.1705936700000001E+00 --3.1761760529999998E+00 --3.1817435850000000E+00 --3.1872964650000002E+00 --3.1928348910000000E+00 --3.1983590569999998E+00 --3.2038691579999998E+00 --3.2093653880000002E+00 --3.2148479360000000E+00 --3.2203169960000002E+00 --3.2257727530000002E+00 --3.2312153740000000E+00 --3.2366450169999998E+00 --3.2420618420000000E+00 --3.2474659899999998E+00 --3.2528575829999999E+00 --3.2582367400000001E+00 --3.2636035780000001E+00 --3.2689581909999998E+00 --3.2743006669999999E+00 --3.2796310960000001E+00 --3.2849495510000000E+00 --3.2902560950000002E+00 --3.2955507869999998E+00 --3.3008336859999998E+00 --3.3061048309999999E+00 --3.3113642610000000E+00 --3.3166120100000001E+00 --3.3218481049999999E+00 --3.3270725649999999E+00 --3.3322854030000002E+00 --3.3374866349999999E+00 --3.3426762630000000E+00 --3.3478542860000000E+00 --3.3530207019999998E+00 --3.3581755040000001E+00 --3.3633186780000002E+00 --3.3684502059999999E+00 --3.3735700729999998E+00 --3.3786782550000001E+00 --3.3837747249999999E+00 --3.3888594529999998E+00 --3.3939324110000002E+00 --3.3989935640000000E+00 --3.4040428729999999E+00 --3.4090802999999998E+00 --3.4141058059999998E+00 --3.4191193470000001E+00 --3.4241208780000001E+00 --3.4291103530000000E+00 --3.4340877249999999E+00 --3.4390529459999999E+00 --3.4440059640000000E+00 --3.4489467280000001E+00 --3.4538751870000000E+00 --3.4587912869999999E+00 --3.4636949750000001E+00 --3.4685861970000000E+00 --3.4734648990000001E+00 --3.4783310250000001E+00 --3.4831845200000000E+00 --3.4880253280000000E+00 --3.4928533939999999E+00 --3.4976686629999998E+00 --3.5024710790000002E+00 --3.5072605879999998E+00 --3.5120371339999998E+00 --3.5168006639999998E+00 --3.5215511230000001E+00 --3.5262884570000002E+00 --3.5310126140000002E+00 --3.5357235409999999E+00 --3.5404211870000002E+00 --3.5451055010000001E+00 --3.5497764340000000E+00 --3.5544339360000001E+00 --3.5590779600000002E+00 --3.5637084570000002E+00 --3.5683253819999998E+00 --3.5729286910000000E+00 --3.5775183390000000E+00 --3.5820942840000001E+00 --3.5866564849999998E+00 --3.5912049019999999E+00 --3.5957394950000001E+00 --3.6002602270000001E+00 --3.6047670620000001E+00 --3.6092599669999998E+00 --3.6137389049999999E+00 --3.6182038470000002E+00 --3.6226547629999999E+00 --3.6270916230000001E+00 --3.6315143989999998E+00 --3.6359230660000001E+00 --3.6403176010000000E+00 --3.6446979800000001E+00 --3.6490641820000000E+00 --3.6534161869999999E+00 --3.6577539790000002E+00 --3.6620775409999999E+00 --3.6663868570000000E+00 --3.6706819159999999E+00 --3.6749627060000001E+00 --3.6792292180000001E+00 --3.6834814429999998E+00 --3.6877193739999998E+00 --3.6919430100000001E+00 --3.6961523449999998E+00 --3.7003473790000001E+00 --3.7045281110000001E+00 --3.7086945450000002E+00 --3.7128466850000001E+00 --3.7169845349999999E+00 --3.7211081010000000E+00 --3.7252173940000000E+00 --3.7293124240000002E+00 --3.7333932040000000E+00 --3.7374597450000002E+00 --3.7415120650000002E+00 --3.7455501800000000E+00 --3.7495741090000001E+00 --3.7535838710000000E+00 --3.7575794870000001E+00 --3.7615609839999999E+00 --3.7655283850000001E+00 --3.7694817150000000E+00 --3.7734210039999998E+00 --3.7773462800000002E+00 --3.7812575759999998E+00 --3.7851549229999999E+00 --3.7890383540000001E+00 --3.7929079070000000E+00 --3.7967636180000000E+00 --3.8006055249999999E+00 --3.8044336670000001E+00 --3.8082480869999999E+00 --3.8120488269999999E+00 --3.8158359300000000E+00 --3.8196094420000000E+00 --3.8233694080000000E+00 --3.8271158779999999E+00 --3.8308489020000001E+00 --3.8345685280000001E+00 --3.8382748080000000E+00 --3.8419677950000000E+00 --3.8456475440000002E+00 --3.8493141099999999E+00 --3.8529675490000002E+00 --3.8566079169999998E+00 --3.8602352760000000E+00 --3.8638496839999998E+00 --3.8674512029999999E+00 --3.8710398939999999E+00 --3.8746158190000002E+00 --3.8781790429999998E+00 --3.8817296319999999E+00 --3.8852676499999999E+00 --3.8887931640000000E+00 --3.8923062430000002E+00 --3.8958069570000000E+00 --3.8992953739999998E+00 --3.9027715619999999E+00 --3.9062355960000001E+00 --3.9096875459999998E+00 --3.9131274870000001E+00 --3.9165554899999999E+00 --3.9199716310000001E+00 --3.9233759849999998E+00 --3.9267686290000001E+00 --3.9301496380000001E+00 --3.9335190889999998E+00 --3.9368770590000000E+00 --3.9402236290000001E+00 --3.9435588770000001E+00 --3.9468828829999998E+00 --3.9501957260000000E+00 --3.9534974880000000E+00 --3.9567882499999998E+00 --3.9600680929999998E+00 --3.9633370999999999E+00 --3.9665953520000001E+00 --3.9698429339999999E+00 --3.9730799299999999E+00 --3.9763064220000000E+00 --3.9795224949999999E+00 --3.9827282340000001E+00 --3.9859237230000000E+00 --3.9891090480000000E+00 --3.9922842940000001E+00 --3.9954495470000002E+00 --3.9986048940000001E+00 --4.0017504190000004E+00 --4.0048862109999996E+00 --4.0080123550000000E+00 --4.0111289399999999E+00 --4.0142360500000001E+00 --4.0173337739999999E+00 --4.0204221990000004E+00 --4.0235014119999999E+00 --4.0265715000000002E+00 --4.0296325519999998E+00 --4.0326846549999997E+00 --4.0357278970000001E+00 --4.0387623640000001E+00 --4.0417881449999999E+00 --4.0448053269999997E+00 --4.0478139979999996E+00 --4.0508142459999998E+00 --4.0538061570000004E+00 --4.0567898199999997E+00 --4.0597653229999997E+00 --4.0627327500000003E+00 --4.0656921890000000E+00 --4.0686437289999997E+00 --4.0715874550000004E+00 --4.0745234549999996E+00 --4.0774518129999997E+00 --4.0803726180000002E+00 --4.0832859539999999E+00 --4.0861919080000000E+00 --4.0890905650000002E+00 --4.0919820109999998E+00 --4.0948663290000002E+00 --4.0977436049999998E+00 --4.1006139240000001E+00 --4.1034773700000002E+00 --4.1063340269999999E+00 --4.1091839779999999E+00 --4.1120273049999998E+00 --4.1148640929999996E+00 --4.1176944239999997E+00 --4.1205183800000000E+00 --4.1233360420000000E+00 --4.1261474910000002E+00 --4.1289528090000003E+00 --4.1317520769999998E+00 --4.1345453740000000E+00 --4.1373327800000004E+00 --4.1401143740000004E+00 --4.1428902369999996E+00 --4.1456604459999999E+00 --4.1484250800000000E+00 --4.1511842120000004E+00 --4.1539379170000004E+00 --4.1566862709999999E+00 --4.1594293459999996E+00 --4.1621672140000001E+00 --4.1648999399999997E+00 --4.1676275870000001E+00 --4.1703502200000004E+00 --4.1730679019999997E+00 --4.1757806970000004E+00 --4.1784886620000004E+00 --4.1811918500000003E+00 --4.1838903170000004E+00 --4.1865841179999999E+00 --4.1892733079999998E+00 --4.1919579369999997E+00 --4.1946380530000003E+00 --4.1973137019999998E+00 --4.1999849310000004E+00 --4.2026517869999998E+00 --4.2053143149999999E+00 --4.2079725549999996E+00 --4.2106265479999996E+00 --4.2132763320000004E+00 --4.2159219470000000E+00 --4.2185634329999999E+00 --4.2212008240000003E+00 --4.2238341569999998E+00 --4.2264634609999998E+00 --4.2290887689999996E+00 --4.2317101160000004E+00 --4.2343275330000001E+00 --4.2369410490000003E+00 --4.2395506909999998E+00 --4.2421564849999998E+00 --4.2447584599999999E+00 --4.2473566409999997E+00 --4.2499510530000002E+00 --4.2525417210000001E+00 --4.2551286639999999E+00 --4.2577119059999999E+00 --4.2602914670000001E+00 --4.2628673690000003E+00 --4.2654396329999997E+00 --4.2680082749999997E+00 --4.2705733129999999E+00 --4.2731347619999998E+00 --4.2756926410000000E+00 --4.2782469670000003E+00 --4.2807977529999999E+00 --4.2833450140000000E+00 --4.2858887609999998E+00 --4.2884290099999998E+00 --4.2909657699999997E+00 --4.2934990559999999E+00 --4.2960288770000004E+00 --4.2985552440000001E+00 --4.3010781659999999E+00 --4.3035976509999996E+00 --4.3061137079999998E+00 --4.3086263479999998E+00 --4.3111355769999999E+00 --4.3136413999999998E+00 --4.3161438240000001E+00 --4.3186428540000001E+00 --4.3211384969999997E+00 --4.3236307580000002E+00 --4.3261196410000000E+00 --4.3286051490000004E+00 --4.3310872859999998E+00 --4.3335660530000002E+00 --4.3360414550000002E+00 --4.3385134929999998E+00 --4.3409821700000002E+00 --4.3434474859999996E+00 --4.3459094409999999E+00 --4.3483680350000000E+00 --4.3508232710000003E+00 --4.3532751459999997E+00 --4.3557236599999998E+00 --4.3581688119999997E+00 --4.3606106000000002E+00 --4.3630490220000002E+00 --4.3654840750000004E+00 --4.3679157589999997E+00 --4.3703440689999997E+00 --4.3727690050000003E+00 --4.3751905579999999E+00 --4.3776087280000002E+00 --4.3800235079999998E+00 --4.3824348960000004E+00 --4.3848428879999997E+00 --4.3872474769999998E+00 --4.3896486570000004E+00 --4.3920464250000002E+00 --4.3944407720000003E+00 --4.3968316930000002E+00 --4.3992191820000004E+00 --4.4016032330000003E+00 --4.4039838370000002E+00 --4.4063609890000004E+00 --4.4087346790000002E+00 --4.4111048999999998E+00 --4.4134716469999997E+00 --4.4158349090000000E+00 --4.4181946779999999E+00 --4.4205509440000004E+00 --4.4229037000000000E+00 --4.4252529369999998E+00 --4.4275986439999997E+00 --4.4299408140000001E+00 --4.4322794360000000E+00 --4.4346145000000003E+00 --4.4369459950000003E+00 --4.4392739109999999E+00 --4.4415982380000001E+00 --4.4439189649999999E+00 --4.4462360820000004E+00 --4.4485495779999997E+00 --4.4508594410000004E+00 --4.4531656589999997E+00 --4.4554682200000002E+00 --4.4577671140000001E+00 --4.4600623280000002E+00 --4.4623538500000004E+00 --4.4646416689999997E+00 --4.4669257699999996E+00 --4.4692061409999999E+00 --4.4714827719999999E+00 --4.4737556459999999E+00 --4.4760247529999999E+00 --4.4782900789999998E+00 --4.4805516100000000E+00 --4.4828093320000004E+00 --4.4850632319999999E+00 --4.4873132970000000E+00 --4.4895595119999996E+00 --4.4918018640000001E+00 --4.4940403370000004E+00 --4.4962749180000001E+00 --4.4985055919999999E+00 --4.5007323440000002E+00 --4.5029551600000000E+00 --4.5051740249999996E+00 --4.5073889249999999E+00 --4.5095998420000001E+00 --4.5118067630000001E+00 --4.5140096710000002E+00 --4.5162085520000002E+00 --4.5184033899999996E+00 --4.5205941689999998E+00 --4.5227808740000004E+00 --4.5249634880000000E+00 --4.5271419950000000E+00 --4.5293163789999999E+00 --4.5314866230000002E+00 --4.5336527120000003E+00 --4.5358146279999998E+00 --4.5379723560000000E+00 --4.5401258779999996E+00 --4.5422751769999996E+00 --4.5444202379999998E+00 --4.5465610410000004E+00 --4.5486975699999999E+00 --4.5508298089999997E+00 --4.5529577400000001E+00 --4.5550813449999996E+00 --4.5572006070000004E+00 --4.5593155070000000E+00 --4.5614260289999997E+00 --4.5635321549999999E+00 --4.5656338659999998E+00 --4.5677311449999998E+00 --4.5698239730000001E+00 --4.5719123330000002E+00 --4.5739962050000003E+00 --4.5760755719999997E+00 --4.5781504149999996E+00 --4.5802207170000004E+00 --4.5822864560000003E+00 --4.5843476169999997E+00 --4.5864041780000004E+00 --4.5884561220000002E+00 --4.5905034290000000E+00 --4.5925460810000001E+00 --4.5945840579999997E+00 --4.5966173430000001E+00 --4.5986459139999996E+00 --4.6006697519999999E+00 --4.6026888379999997E+00 --4.6047031519999999E+00 --4.6067126759999999E+00 --4.6087173879999996E+00 --4.6107172700000003E+00 --4.6127123020000003E+00 --4.6147024649999997E+00 --4.6166877360000003E+00 --4.6186680969999996E+00 --4.6206435280000004E+00 --4.6226140080000002E+00 --4.6245795169999999E+00 --4.6265400349999997E+00 --4.6284955410000004E+00 --4.6304460159999996E+00 --4.6323914380000000E+00 --4.6343317859999997E+00 --4.6362670410000000E+00 --4.6381971799999997E+00 --4.6401221850000001E+00 --4.6420420330000001E+00 --4.6439567039999998E+00 --4.6458661770000003E+00 --4.6477704309999996E+00 --4.6496694429999996E+00 --4.6515631940000004E+00 --4.6534516620000002E+00 --4.6553348259999998E+00 --4.6572126650000003E+00 --4.6590851559999997E+00 --4.6609522790000000E+00 --4.6628140130000002E+00 --4.6646703340000002E+00 --4.6665212220000001E+00 --4.6683666549999998E+00 --4.6702066110000002E+00 --4.6720410689999996E+00 --4.6738700059999996E+00 --4.6756934010000002E+00 --4.6775112319999996E+00 --4.6793234750000003E+00 --4.6811301099999998E+00 --4.6829311130000004E+00 --4.6847264629999996E+00 --4.6865161380000000E+00 --4.6883001149999997E+00 --4.6900783730000004E+00 --4.6918508880000003E+00 --4.6936176400000003E+00 --4.6953786040000001E+00 --4.6971337589999997E+00 --4.6988830830000001E+00 --4.7006265520000001E+00 --4.7023641429999996E+00 --4.7040958320000001E+00 --4.7058215949999997E+00 --4.7075414100000001E+00 --4.7092552510000001E+00 --4.7109630950000003E+00 --4.7126649179999998E+00 --4.7143606919999996E+00 --4.7160503870000001E+00 --4.7177339720000004E+00 --4.7194114159999998E+00 --4.7210826890000002E+00 --4.7227477609999999E+00 --4.7244066000000000E+00 --4.7260591749999996E+00 --4.7277054539999996E+00 --4.7293453999999997E+00 --4.7309789770000004E+00 --4.7326061490000004E+00 --4.7342268790000004E+00 --4.7358411320000000E+00 --4.7374488689999996E+00 --4.7390500570000000E+00 --4.7406446559999997E+00 --4.7422326269999999E+00 --4.7438139289999999E+00 --4.7453885209999997E+00 --4.7469563639999999E+00 --4.7485174160000003E+00 --4.7500716350000003E+00 --4.7516189820000001E+00 --4.7531594159999999E+00 --4.7546928939999997E+00 --4.7562193710000003E+00 --4.7577388049999998E+00 --4.7592511499999999E+00 --4.7607563629999996E+00 --4.7622544019999999E+00 --4.7637452199999997E+00 --4.7652287729999996E+00 --4.7667050189999998E+00 --4.7681739099999998E+00 --4.7696354000000003E+00 --4.7710894430000002E+00 --4.7725359930000000E+00 --4.7739750040000004E+00 --4.7754064290000002E+00 --4.7768302220000001E+00 --4.7782463369999997E+00 --4.7796547269999996E+00 --4.7810553450000004E+00 --4.7824481419999998E+00 --4.7838330700000000E+00 --4.7852100850000001E+00 --4.7865791350000002E+00 --4.7879401740000000E+00 --4.7892931550000002E+00 --4.7906380300000002E+00 --4.7919747509999997E+00 --4.7933032689999999E+00 --4.7946235369999997E+00 --4.7959355050000001E+00 --4.7972391270000001E+00 --4.7985343530000000E+00 --4.7998211350000002E+00 --4.8010994250000003E+00 --4.8023691749999999E+00 --4.8036303360000003E+00 --4.8048828610000003E+00 --4.8061267000000001E+00 --4.8073618079999996E+00 --4.8085881319999997E+00 --4.8098056280000003E+00 --4.8110142450000000E+00 --4.8122139360000000E+00 --4.8134046520000000E+00 --4.8145863469999997E+00 --4.8157589710000002E+00 --4.8169224789999996E+00 --4.8180768220000001E+00 --4.8192219510000003E+00 --4.8203578199999999E+00 --4.8214843810000003E+00 --4.8226015870000003E+00 --4.8237093880000002E+00 --4.8248077399999998E+00 --4.8258965949999997E+00 --4.8269759079999996E+00 --4.8280456300000001E+00 --4.8291057159999999E+00 --4.8301561179999997E+00 --4.8311967899999999E+00 --4.8322276869999996E+00 --4.8332487600000000E+00 --4.8342599640000001E+00 --4.8352612570000000E+00 --4.8362525889999999E+00 --4.8372339169999998E+00 --4.8382051959999997E+00 --4.8391663810000001E+00 --4.8401174259999999E+00 --4.8410582870000001E+00 --4.8419889170000001E+00 --4.8429092740000002E+00 --4.8438193140000001E+00 --4.8447189919999998E+00 --4.8456082660000002E+00 --4.8464870910000002E+00 --4.8473554260000000E+00 --4.8482132260000004E+00 --4.8490604480000004E+00 --4.8498970490000000E+00 --4.8507229870000002E+00 --4.8515382169999999E+00 --4.8523427000000003E+00 --4.8531363939999999E+00 --4.8539192580000003E+00 --4.8546912510000002E+00 --4.8554523300000003E+00 --4.8562024560000001E+00 --4.8569415850000004E+00 --4.8576696789999998E+00 --4.8583866950000001E+00 --4.8590925939999998E+00 --4.8597873380000003E+00 --4.8604708870000000E+00 --4.8611432030000001E+00 --4.8618042450000001E+00 --4.8624539760000003E+00 --4.8630923560000001E+00 --4.8637193449999998E+00 --4.8643349049999998E+00 --4.8649389989999996E+00 --4.8655315889999997E+00 --4.8661126389999998E+00 --4.8666821120000003E+00 --4.8672399710000001E+00 --4.8677861809999996E+00 --4.8683207040000003E+00 --4.8688435019999998E+00 --4.8693545399999998E+00 --4.8698537809999998E+00 --4.8703411909999996E+00 --4.8708167350000000E+00 --4.8712803779999998E+00 --4.8717320879999999E+00 --4.8721718300000001E+00 --4.8725995680000000E+00 --4.8730152699999998E+00 --4.8734188999999999E+00 --4.8738104250000003E+00 --4.8741898099999998E+00 --4.8745570249999997E+00 --4.8749120359999996E+00 --4.8752548139999998E+00 --4.8755853240000002E+00 --4.8759035360000000E+00 --4.8762094190000003E+00 --4.8765029400000000E+00 --4.8767840690000002E+00 --4.8770527719999999E+00 --4.8773090200000002E+00 --4.8775527820000004E+00 --4.8777840310000000E+00 --4.8780027339999998E+00 --4.8782088650000004E+00 --4.8784023940000001E+00 --4.8785832920000001E+00 --4.8787515289999996E+00 --4.8789070780000001E+00 --4.8790499079999998E+00 --4.8791799930000002E+00 --4.8792973010000003E+00 --4.8794018090000000E+00 --4.8794934879999996E+00 --4.8795723139999998E+00 --4.8796382590000000E+00 --4.8796912980000000E+00 --4.8797314020000000E+00 --4.8797585479999999E+00 --4.8797727059999998E+00 --4.8797738519999996E+00 --4.8797619579999996E+00 --4.8797370019999997E+00 --4.8796989599999998E+00 --4.8796478069999996E+00 --4.8795835199999997E+00 --4.8795060750000001E+00 --4.8794154479999996E+00 --4.8793116149999998E+00 --4.8791945510000003E+00 --4.8790642330000003E+00 --4.8789206380000003E+00 --4.8787637430000004E+00 --4.8785935269999996E+00 --4.8784099679999997E+00 --4.8782130459999999E+00 --4.8780027380000002E+00 --4.8777790220000004E+00 --4.8775418789999998E+00 --4.8772912860000002E+00 --4.8770272219999997E+00 --4.8767496650000002E+00 --4.8764585960000000E+00 --4.8761539930000000E+00 --4.8758358399999997E+00 --4.8755041160000001E+00 --4.8751588019999996E+00 --4.8747998790000002E+00 --4.8744273299999996E+00 --4.8740411339999996E+00 --4.8736412720000004E+00 --4.8732277269999997E+00 --4.8728004790000004E+00 --4.8723595089999998E+00 --4.8719048000000003E+00 --4.8714363369999996E+00 --4.8709541019999998E+00 --4.8704580799999997E+00 --4.8699482520000004E+00 --4.8694246039999998E+00 --4.8688871190000000E+00 --4.8683357779999996E+00 --4.8677705659999999E+00 --4.8671914669999996E+00 --4.8665984640000000E+00 --4.8659915439999999E+00 --4.8653706899999998E+00 --4.8647358909999996E+00 --4.8640871299999997E+00 --4.8634243950000000E+00 --4.8627476690000000E+00 --4.8620569390000004E+00 --4.8613521899999999E+00 --4.8606334090000001E+00 --4.8599005799999997E+00 --4.8591536910000004E+00 --4.8583927280000001E+00 --4.8576176799999997E+00 --4.8568285339999999E+00 --4.8560252769999996E+00 --4.8552078979999997E+00 --4.8543763850000001E+00 --4.8535307249999997E+00 --4.8526709060000002E+00 --4.8517969159999996E+00 --4.8509087429999997E+00 --4.8500063740000003E+00 --4.8490897989999997E+00 --4.8481590079999997E+00 --4.8472139900000002E+00 --4.8462547349999996E+00 --4.8452812339999998E+00 --4.8442934749999997E+00 --4.8432914489999996E+00 --4.8422751460000004E+00 --4.8412445550000003E+00 --4.8401996650000001E+00 --4.8391404680000001E+00 --4.8380669520000001E+00 --4.8369791109999998E+00 --4.8358769360000000E+00 --4.8347604180000001E+00 --4.8336295509999996E+00 --4.8324843230000001E+00 --4.8313247290000003E+00 --4.8301507580000003E+00 --4.8289624050000004E+00 --4.8277596589999998E+00 --4.8265425119999996E+00 --4.8253109580000002E+00 --4.8240649869999999E+00 --4.8228045950000000E+00 --4.8215297709999998E+00 --4.8202405089999996E+00 --4.8189368029999997E+00 --4.8176186449999996E+00 --4.8162860280000004E+00 --4.8149389439999997E+00 --4.8135773869999996E+00 --4.8122013509999997E+00 --4.8108108249999999E+00 --4.8094058049999999E+00 --4.8079862830000000E+00 --4.8065522539999996E+00 --4.8051037100000000E+00 --4.8036406439999997E+00 --4.8021630520000000E+00 --4.8006709259999996E+00 --4.7991642590000003E+00 --4.7976430450000001E+00 --4.7961072780000000E+00 --4.7945569509999997E+00 --4.7929920570000002E+00 --4.7914125910000003E+00 --4.7898185460000002E+00 --4.7882099179999997E+00 --4.7865867000000000E+00 --4.7849488869999997E+00 --4.7832964720000000E+00 --4.7816294519999998E+00 --4.7799478190000002E+00 --4.7782515679999999E+00 --4.7765406949999996E+00 --4.7748151920000002E+00 --4.7730750559999997E+00 --4.7713202800000003E+00 --4.7695508579999997E+00 --4.7677667870000002E+00 --4.7659680619999998E+00 --4.7641546779999997E+00 --4.7623266309999996E+00 --4.7604839160000001E+00 --4.7586265269999997E+00 --4.7567544630000000E+00 --4.7548677149999996E+00 --4.7529662799999999E+00 --4.7510501539999996E+00 --4.7491193320000002E+00 --4.7471738099999996E+00 --4.7452135830000000E+00 --4.7432386500000003E+00 --4.7412490050000002E+00 --4.7392446450000003E+00 --4.7372255660000002E+00 --4.7351917649999997E+00 --4.7331432380000003E+00 --4.7310799809999997E+00 --4.7290019900000004E+00 --4.7269092629999996E+00 --4.7248017950000003E+00 --4.7226795819999996E+00 --4.7205426220000000E+00 --4.7183909130000004E+00 --4.7162244500000003E+00 --4.7140432329999999E+00 --4.7118472579999997E+00 --4.7096365220000003E+00 --4.7074110219999996E+00 --4.7051707580000004E+00 --4.7029157240000004E+00 --4.7006459180000002E+00 --4.6983613379999998E+00 --4.6960619819999998E+00 --4.6937478459999999E+00 --4.6914189300000002E+00 --4.6890752310000003E+00 --4.6867167490000003E+00 --4.6843434799999999E+00 --4.6819554229999998E+00 --4.6795525769999999E+00 --4.6771349400000002E+00 --4.6747025100000004E+00 --4.6722552860000004E+00 --4.6697932650000000E+00 --4.6673164470000001E+00 --4.6648248299999997E+00 --4.6623184110000002E+00 --4.6597971910000000E+00 --4.6572611679999998E+00 --4.6547103429999996E+00 --4.6521447130000002E+00 --4.6495642799999999E+00 --4.6469690410000002E+00 --4.6443589970000003E+00 --4.6417341460000001E+00 --4.6390944870000004E+00 --4.6364400200000002E+00 --4.6337707440000004E+00 --4.6310866590000002E+00 --4.6283877630000001E+00 --4.6256740580000004E+00 --4.6229455450000003E+00 --4.6202022219999996E+00 --4.6174440890000001E+00 --4.6146711470000001E+00 --4.6118833969999997E+00 --4.6090808389999998E+00 --4.6062634720000002E+00 --4.6034312970000002E+00 --4.6005843149999999E+00 --4.5977225250000000E+00 --4.5948459279999998E+00 --4.5919545230000001E+00 --4.5890483130000002E+00 --4.5861272980000001E+00 --4.5831914789999999E+00 --4.5802408579999998E+00 --4.5772754349999998E+00 --4.5742952130000001E+00 --4.5713001909999997E+00 --4.5682903699999997E+00 --4.5652657530000003E+00 --4.5622263390000004E+00 --4.5591721310000004E+00 --4.5561031290000003E+00 --4.5530193340000000E+00 --4.5499207500000001E+00 --4.5468073760000003E+00 --4.5436792150000000E+00 --4.5405362680000003E+00 --4.5373785389999997E+00 --4.5342060289999999E+00 --4.5310187400000004E+00 --4.5278166730000002E+00 --4.5245998309999997E+00 --4.5213682170000000E+00 --4.5181218310000002E+00 --4.5148606750000004E+00 --4.5115847520000001E+00 --4.5082940630000001E+00 --4.5049886120000000E+00 --4.5016684009999999E+00 --4.4983334330000000E+00 --4.4949837109999997E+00 --4.4916192370000001E+00 --4.4882400139999996E+00 --4.4848460450000003E+00 --4.4814373319999996E+00 --4.4780138789999997E+00 --4.4745756879999998E+00 --4.4711227610000002E+00 --4.4676551020000002E+00 --4.4641727140000000E+00 --4.4606755979999999E+00 --4.4571637590000002E+00 --4.4536372010000003E+00 --4.4500959260000004E+00 --4.4465399379999999E+00 --4.4429692400000000E+00 --4.4393838370000003E+00 --4.4357837309999999E+00 --4.4321689260000001E+00 --4.4285394260000004E+00 --4.4248952330000000E+00 --4.4212363510000001E+00 --4.4175627840000002E+00 --4.4138745359999998E+00 --4.4101716089999998E+00 --4.4064540100000000E+00 --4.4027217390000004E+00 --4.3989748029999998E+00 --4.3952132050000001E+00 --4.3914369500000001E+00 --4.3876460410000000E+00 --4.3838404830000002E+00 --4.3800202800000001E+00 --4.3761854350000000E+00 --4.3723359549999996E+00 --4.3684718409999999E+00 --4.3645930990000004E+00 --4.3606997319999996E+00 --4.3567917439999997E+00 --4.3528691410000002E+00 --4.3489319269999998E+00 --4.3449801069999996E+00 --4.3410136860000001E+00 --4.3370326669999999E+00 --4.3330370560000002E+00 --4.3290268579999998E+00 --4.3250020769999997E+00 --4.3209627169999996E+00 --4.3169087849999999E+00 --4.3128402840000000E+00 --4.3087572190000003E+00 --4.3046595959999996E+00 --4.3005474169999998E+00 --4.2964206889999996E+00 --4.2922794169999996E+00 --4.2881236060000001E+00 --4.2839532609999997E+00 --4.2797683869999998E+00 --4.2755689900000000E+00 --4.2713550759999999E+00 --4.2671266479999996E+00 --4.2628837129999999E+00 --4.2586262750000001E+00 --4.2543543399999999E+00 --4.2500679129999996E+00 --4.2457669989999998E+00 --4.2414516039999999E+00 --4.2371217339999996E+00 --4.2327773920000000E+00 --4.2284185850000000E+00 --4.2240453179999999E+00 --4.2196575980000004E+00 --4.2152554310000001E+00 --4.2108388210000003E+00 --4.2064077739999997E+00 --4.2019622969999997E+00 --4.1975023949999999E+00 --4.1930280729999998E+00 --4.1885393369999999E+00 --4.1840361929999998E+00 --4.1795186470000001E+00 --4.1749867030000001E+00 --4.1704403689999996E+00 --4.1658796489999999E+00 --4.1613045519999998E+00 --4.1567150809999998E+00 --4.1521112430000002E+00 --4.1474930429999999E+00 --4.1428604900000003E+00 --4.1382135870000001E+00 --4.1335523419999998E+00 --4.1288767609999999E+00 --4.1241868490000000E+00 --4.1194826119999997E+00 --4.1147640570000004E+00 --4.1100311899999999E+00 --4.1052840159999997E+00 --4.1005225420000002E+00 --4.0957467750000003E+00 --4.0909567190000002E+00 --4.0861523829999999E+00 --4.0813337719999998E+00 --4.0765008920000003E+00 --4.0716537510000004E+00 --4.0667923540000004E+00 --4.0619167080000000E+00 --4.0570268189999998E+00 --4.0521226940000004E+00 --4.0472043380000002E+00 --4.0422717590000001E+00 --4.0373249629999997E+00 --4.0323639560000002E+00 --4.0273887449999997E+00 --4.0223993350000002E+00 --4.0173957339999999E+00 --4.0123779490000002E+00 --4.0073459849999997E+00 --4.0022998489999999E+00 --3.9972395490000001E+00 --3.9921650899999999E+00 --3.9870764790000002E+00 --3.9819737229999999E+00 --3.9768568279999998E+00 --3.9717258009999998E+00 --3.9665806479999999E+00 --3.9614213770000002E+00 --3.9562479929999999E+00 --3.9510605040000000E+00 --3.9458589150000001E+00 --3.9406432350000000E+00 --3.9354134680000001E+00 --3.9301696239999999E+00 --3.9249117080000002E+00 --3.9196397279999999E+00 --3.9143536900000000E+00 --3.9090536020000002E+00 --3.9037394710000002E+00 --3.8984113020000000E+00 --3.8930691049999999E+00 --3.8877128850000000E+00 --3.8823426489999999E+00 --3.8769584039999998E+00 --3.8715601579999999E+00 --3.8661479170000002E+00 --3.8607216879999999E+00 --3.8552814780000002E+00 --3.8498272920000001E+00 --3.8443591360000000E+00 --3.8388770170000002E+00 --3.8333809400000001E+00 --3.8278709119999998E+00 --3.8223469390000000E+00 --3.8168090270000001E+00 --3.8112571810000002E+00 --3.8056914079999999E+00 --3.8001117139999998E+00 --3.7945181049999999E+00 --3.7889105870000002E+00 --3.7832891659999999E+00 --3.7776538490000000E+00 --3.7720046400000000E+00 --3.7663415439999999E+00 --3.7606645639999998E+00 --3.7549737030000001E+00 --3.7492689650000002E+00 --3.7435503529999998E+00 --3.7378178690000001E+00 --3.7320715180000001E+00 --3.7263113020000000E+00 --3.7205372240000001E+00 --3.7147492889999998E+00 --3.7089474980000001E+00 --3.7031318560000002E+00 --3.6973023660000002E+00 --3.6914590299999999E+00 --3.6856018530000001E+00 --3.6797308360000001E+00 --3.6738459830000001E+00 --3.6679472949999998E+00 --3.6620347729999998E+00 --3.6561084190000002E+00 --3.6501682340000001E+00 --3.6442142190000002E+00 --3.6382463750000000E+00 --3.6322647049999999E+00 --3.6262692090000002E+00 --3.6202598890000002E+00 --3.6142367460000000E+00 --3.6081997810000002E+00 --3.6021489970000000E+00 --3.5960843929999999E+00 --3.5900059729999998E+00 --3.5839137360000000E+00 --3.5778076840000002E+00 --3.5716878180000000E+00 --3.5655541369999999E+00 --3.5594066419999999E+00 --3.5532453330000000E+00 --3.5470702080000001E+00 --3.5408812699999999E+00 --3.5346785180000002E+00 --3.5284619510000002E+00 --3.5222315700000002E+00 --3.5159873749999999E+00 --3.5097293660000002E+00 --3.5034575430000001E+00 --3.4971719050000001E+00 --3.4908724539999998E+00 --3.4845591900000001E+00 --3.4782321110000001E+00 --3.4718912180000001E+00 --3.4655365109999998E+00 --3.4591679879999999E+00 --3.4527856500000000E+00 --3.4463894939999999E+00 --3.4399795210000002E+00 --3.4335557300000001E+00 --3.4271181199999998E+00 --3.4206666900000000E+00 --3.4142014390000002E+00 --3.4077223679999999E+00 --3.4012294740000000E+00 --3.3947227579999999E+00 --3.3882022180000000E+00 --3.3816678539999998E+00 --3.3751196650000002E+00 --3.3685576510000002E+00 --3.3619818100000001E+00 --3.3553921419999999E+00 --3.3487886450000000E+00 --3.3421713190000002E+00 --3.3355401609999999E+00 --3.3288951720000002E+00 --3.3222363499999998E+00 --3.3155636940000002E+00 --3.3088772030000002E+00 --3.3021768759999999E+00 --3.2954627109999999E+00 --3.2887347079999998E+00 --3.2819928649999999E+00 --3.2752371820000001E+00 --3.2684676570000000E+00 --3.2616842890000002E+00 --3.2548870779999999E+00 --3.2480760210000001E+00 --3.2412511180000001E+00 --3.2344123680000001E+00 --3.2275597700000001E+00 --3.2206933219999998E+00 --3.2138130239999998E+00 --3.2069188739999999E+00 --3.2000108720000000E+00 --3.1930890150000000E+00 --3.1861533039999999E+00 --3.1792037369999999E+00 --3.1722403120000000E+00 --3.1652630290000001E+00 --3.1582718870000002E+00 --3.1512668850000001E+00 --3.1442480210000001E+00 --3.1372152940000002E+00 --3.1301687029999998E+00 --3.1231082479999999E+00 --3.1160339270000001E+00 --3.1089457390000002E+00 --3.1018436839999999E+00 --3.0947277610000001E+00 --3.0875979689999999E+00 --3.0804543060000000E+00 --3.0732967740000001E+00 --3.0661253689999999E+00 --3.0589400929999999E+00 --3.0517409430000000E+00 --3.0445279190000001E+00 --3.0373010200000001E+00 --3.0300602460000001E+00 --3.0228055949999999E+00 --3.0155370659999998E+00 --3.0082546600000000E+00 --3.0009583740000001E+00 --2.9936482089999998E+00 --2.9863241629999999E+00 --2.9789862370000000E+00 --2.9716344310000000E+00 --2.9642687429999999E+00 --2.9568891740000001E+00 --2.9494957230000001E+00 --2.9420883899999999E+00 --2.9346671739999999E+00 --2.9272320760000001E+00 --2.9197830940000000E+00 --2.9123202290000001E+00 --2.9048434799999998E+00 --2.8973528470000001E+00 --2.8898483289999999E+00 --2.8823299269999998E+00 --2.8747976390000001E+00 --2.8672514659999999E+00 --2.8596914070000001E+00 --2.8521174629999999E+00 --2.8445296330000001E+00 --2.8369279189999999E+00 --2.8293123200000001E+00 --2.8216828370000000E+00 --2.8140394700000000E+00 --2.8063822190000001E+00 --2.7987110849999999E+00 --2.7910260679999999E+00 --2.7833271690000001E+00 --2.7756143870000001E+00 --2.7678877239999999E+00 --2.7601471790000001E+00 --2.7523927520000000E+00 --2.7446244449999999E+00 --2.7368422560000001E+00 --2.7290461879999999E+00 --2.7212362400000001E+00 --2.7134124119999998E+00 --2.7055747069999998E+00 --2.6977231239999999E+00 --2.6898576660000000E+00 --2.6819783319999999E+00 --2.6740851250000000E+00 --2.6661780460000002E+00 --2.6582570950000002E+00 --2.6503222730000000E+00 --2.6423735829999999E+00 --2.6344110249999999E+00 --2.6264345990000000E+00 --2.6184443079999999E+00 --2.6104401519999998E+00 --2.6024221320000001E+00 --2.5943902500000000E+00 --2.5863445060000001E+00 --2.5782849020000000E+00 --2.5702114389999999E+00 --2.5621241189999999E+00 --2.5540229430000001E+00 --2.5459079139999998E+00 --2.5377790330000001E+00 --2.5296363030000002E+00 --2.5214797259999999E+00 --2.5133093030000002E+00 --2.5051250359999999E+00 --2.4969269299999999E+00 --2.4887149819999999E+00 --2.4804891969999998E+00 --2.4722495769999999E+00 --2.4639961229999998E+00 --2.4557288370000001E+00 --2.4474477220000002E+00 --2.4391527790000000E+00 --2.4308440110000000E+00 --2.4225214190000002E+00 --2.4141850059999999E+00 --2.4058347730000000E+00 --2.3974707249999998E+00 --2.3890928630000001E+00 --2.3807011910000000E+00 --2.3722957110000000E+00 --2.3638764280000002E+00 --2.3554433430000001E+00 --2.3469964590000001E+00 --2.3385357789999999E+00 --2.3300613069999998E+00 --2.3215730440000000E+00 --2.3130709949999999E+00 --2.3045551610000001E+00 --2.2960255460000001E+00 --2.2874821540000001E+00 --2.2789249850000002E+00 --2.2703540439999998E+00 --2.2617693330000002E+00 --2.2531708560000001E+00 --2.2445586149999999E+00 --2.2359326149999998E+00 --2.2272928580000002E+00 --2.2186393500000001E+00 --2.2099720949999999E+00 --2.2012910950000002E+00 --2.1925963540000000E+00 --2.1838878770000001E+00 --2.1751656669999999E+00 --2.1664297289999999E+00 --2.1576800650000001E+00 --2.1489166800000001E+00 --2.1401395790000000E+00 --2.1313487630000001E+00 --2.1225442380000001E+00 --2.1137260069999999E+00 --2.1048940740000002E+00 --2.0960484429999999E+00 --2.0871891169999999E+00 --2.0783161010000000E+00 --2.0694293990000001E+00 --2.0605290180000000E+00 --2.0516149580000000E+00 --2.0426872280000001E+00 --2.0337458300000000E+00 --2.0247907710000002E+00 --2.0158220540000000E+00 --2.0068396840000000E+00 --1.9978436680000000E+00 --1.9888340090000001E+00 --1.9798107110000001E+00 --1.9707737789999999E+00 --1.9617232190000000E+00 --1.9526590349999999E+00 --1.9435812320000001E+00 --1.9344898150000001E+00 --1.9253847879999999E+00 --1.9162661580000000E+00 --1.9071339260000000E+00 --1.8979880990000000E+00 --1.8888286830000001E+00 --1.8796556830000000E+00 --1.8704691040000001E+00 --1.8612689529999999E+00 --1.8520552340000001E+00 --1.8428279550000000E+00 --1.8335871200000000E+00 --1.8243327350000000E+00 --1.8150648050000000E+00 --1.8057833370000000E+00 --1.7964883359999999E+00 --1.7871798070000000E+00 --1.7778577570000000E+00 --1.7685221910000000E+00 --1.7591731159999999E+00 --1.7498105349999999E+00 --1.7404344549999999E+00 --1.7310448820000000E+00 --1.7216418210000000E+00 --1.7122252790000001E+00 --1.7027952609999999E+00 --1.6933517730000001E+00 --1.6838948229999999E+00 --1.6744244180000001E+00 --1.6649405620000000E+00 --1.6554432630000000E+00 --1.6459325279999999E+00 --1.6364083629999999E+00 --1.6268707739999999E+00 --1.6173197690000001E+00 --1.6077553529999999E+00 --1.5981775340000000E+00 --1.5885863170000001E+00 --1.5789817100000001E+00 --1.5693637180000000E+00 --1.5597323489999999E+00 --1.5500876079999999E+00 --1.5404295029999999E+00 --1.5307580400000000E+00 --1.5210732270000000E+00 --1.5113750680000000E+00 --1.5016635709999999E+00 --1.4919387440000000E+00 --1.4822005930000000E+00 --1.4724491270000000E+00 --1.4626843530000000E+00 --1.4529062779999999E+00 --1.4431149080000001E+00 --1.4333102540000000E+00 --1.4234923190000000E+00 --1.4136611120000000E+00 --1.4038166409999999E+00 --1.3939589120000000E+00 --1.3840879330000000E+00 --1.3742037119999999E+00 --1.3643062560000001E+00 --1.3543955720000000E+00 --1.3444716670000001E+00 --1.3345345490000000E+00 --1.3245842240000001E+00 --1.3146207000000001E+00 --1.3046439860000001E+00 --1.2946540870000001E+00 --1.2846510130000000E+00 --1.2746347720000000E+00 --1.2646053700000000E+00 --1.2545628150000001E+00 --1.2445071169999999E+00 --1.2344382810000001E+00 --1.2243563180000001E+00 --1.2142612330000000E+00 --1.2041530350000000E+00 --1.1940317330000001E+00 --1.1838973340000001E+00 --1.1737498449999999E+00 --1.1635892740000000E+00 --1.1534156300000000E+00 --1.1432289190000000E+00 --1.1330291509999999E+00 --1.1228163330000001E+00 --1.1125904719999999E+00 --1.1023515779999999E+00 --1.0920996569999999E+00 --1.0818347170000000E+00 --1.0715567669999999E+00 --1.0612658159999999E+00 --1.0509618720000000E+00 --1.0406449430000000E+00 --1.0303150370000000E+00 --1.0199721630000000E+00 --1.0096163309999999E+00 --9.9924754569999996E-01 --9.8886581880000002E-01 --9.7847115699999998E-01 --9.6806356910000002E-01 --9.5764306320000003E-01 --9.4720964829999998E-01 --9.3676333140000001E-01 --9.2630412360000003E-01 --9.1583203069999997E-01 --9.0534706180000002E-01 --8.9484922489999996E-01 --8.8433852999999996E-01 --8.7381498420000003E-01 --8.6327859529999995E-01 --8.5272937339999999E-01 --8.4216732750000001E-01 --8.3159246560000000E-01 --8.2100479680000005E-01 --8.1040433089999997E-01 --7.9979107500000002E-01 --7.8916503910000002E-01 --7.7852623219999995E-01 --7.6787466329999998E-01 --7.5721033950000005E-01 --7.4653327260000002E-01 --7.3584346869999995E-01 --7.2514093879999997E-01 --7.1442569089999997E-01 --7.0369773309999994E-01 --6.9295707520000005E-01 --6.8220372630000004E-01 --6.7143769539999998E-01 --6.6065898950000002E-01 --6.4986761969999995E-01 --6.3906359380000000E-01 --6.2824692090000001E-01 --6.1741761100000003E-01 --6.0657567209999996E-01 --5.9572111429999997E-01 --5.8485394739999996E-01 --5.7397417949999996E-01 --5.6308182159999998E-01 --5.5217688070000004E-01 --5.4125936880000003E-01 --5.3032929299999998E-01 --5.1938666410000001E-01 --5.0843149020000000E-01 --4.9746378130000002E-01 --4.8648354739999999E-01 --4.7549079659999999E-01 --4.6448553970000001E-01 --4.5346778380000002E-01 --4.4243754089999998E-01 --4.3139481800000001E-01 --4.2033962520000001E-01 --4.0927197230000001E-01 --3.9819186839999998E-01 --3.8709932349999998E-01 --3.7599434560000000E-01 --3.6487694580000002E-01 --3.5374713390000001E-01 --3.4260491799999998E-01 --3.3145030910000001E-01 --3.2028331719999997E-01 --3.0910395239999999E-01 --2.9791222249999999E-01 --2.8670813860000000E-01 --2.7549170969999998E-01 --2.6426294680000001E-01 --2.5302185890000001E-01 --2.4176845510000000E-01 --2.3050274620000000E-01 --2.1922474130000000E-01 --2.0793444940000000E-01 --1.9663188249999999E-01 --1.8531704869999999E-01 --1.7398995680000001E-01 --1.6265061889999999E-01 --1.5129904299999999E-01 --1.3993524010000000E-01 --1.2855921830000000E-01 --1.1717098939999999E-01 --1.0577056150000000E-01 --9.4357946619999994E-02 --8.2933154740000001E-02 --7.1496193860000001E-02 --6.0047075980000003E-02 --4.8585811090000000E-02 --3.7112408210000003E-02 --2.5626878329999998E-02 --1.4129230450000000E-02 --2.6194765709999998E-03 -8.9023753100000002E-03 -2.0436314189999999E-02 -3.1982330070000002E-02 -4.3540411950000003E-02 -5.5110551830000000E-02 -6.6692737710000005E-02 -7.8286960589999996E-02 -8.9893209480000000E-02 -1.0151147639999999E-01 -1.1314174820000000E-01 -1.2478401710000001E-01 -1.3643827200000000E-01 -1.4810450289999999E-01 -1.5978269980000001E-01 -1.7147285160000000E-01 -1.8317494849999999E-01 -1.9488897940000000E-01 -2.0661493530000000E-01 -2.1835280520000000E-01 -2.3010257800000000E-01 -2.4186424390000000E-01 -2.5363779279999998E-01 -2.6542321369999999E-01 -2.7722049760000000E-01 -2.8902963240000001E-01 -3.0085060930000002E-01 -3.1268341719999998E-01 -3.2452804510000000E-01 -3.3638448399999998E-01 -3.4825272190000001E-01 -3.6013275070000000E-01 -3.7202455760000003E-01 -3.8392813450000002E-01 -3.9584346939999998E-01 -4.0777055229999998E-01 -4.1970937310000000E-01 -4.3165992100000000E-01 -4.4362218590000002E-01 -4.5559615679999999E-01 -4.6758182370000001E-01 -4.7957917449999998E-01 -4.9158820040000001E-01 -5.0360888930000003E-01 -5.1564123220000002E-01 -5.2768521710000005E-01 -5.3974083490000002E-01 -5.5180807379999997E-01 -5.6388692370000004E-01 -5.7597737360000001E-01 -5.8807941350000004E-01 -6.0019303329999996E-01 -6.1231822120000001E-01 -6.2445496710000004E-01 -6.3660326099999998E-01 -6.4876309190000003E-01 -6.6093444879999996E-01 -6.7311732160000004E-01 -6.8531170050000001E-01 -6.9751757339999998E-01 -7.0973493030000001E-01 -7.2196376019999997E-01 -7.3420405300000002E-01 -7.4645579890000002E-01 -7.5871898480000000E-01 -7.7099360169999998E-01 -7.8327963759999997E-01 -7.9557708340000000E-01 -8.0788592729999997E-01 -8.2020615919999995E-01 -8.3253776710000005E-01 -8.4488074199999996E-01 -8.5723507180000003E-01 -8.6960074769999995E-01 -8.8197775660000000E-01 -8.9436608849999999E-01 -9.0676573340000000E-01 -9.1917668129999996E-01 -9.3159891910000003E-01 -9.4403243800000003E-01 -9.5647722589999995E-01 -9.6893327380000005E-01 -9.8140056970000000E-01 -9.9387910349999997E-01 -1.0063688630000001E+00 -1.0188698400000000E+00 -1.0313820220000001E+00 -1.0439053990000000E+00 -1.0564399590000000E+00 -1.0689856920000000E+00 -1.0815425880000000E+00 -1.0941106340000000E+00 -1.1066898199999999E+00 -1.1192801370000001E+00 -1.1318815730000000E+00 -1.1444941170000000E+00 -1.1571177589999999E+00 -1.1697524870000000E+00 -1.1823982909999999E+00 -1.1950551590000000E+00 -1.2077230820000000E+00 -1.2204020480000000E+00 -1.2330920470000000E+00 -1.2457930669999999E+00 -1.2585050990000000E+00 -1.2712281310000000E+00 -1.2839621520000000E+00 -1.2967071520000000E+00 -1.3094631200000000E+00 -1.3222300440000001E+00 -1.3350079150000000E+00 -1.3477967209999999E+00 -1.3605964520000000E+00 -1.3734070970000001E+00 -1.3862286440000000E+00 -1.3990610840000000E+00 -1.4119044050000000E+00 -1.4247585960000000E+00 -1.4376236469999999E+00 -1.4504995469999999E+00 -1.4633862860000000E+00 -1.4762838510000000E+00 -1.4891922330000000E+00 -1.5021114209999999E+00 -1.5150414029999999E+00 -1.5279821700000000E+00 -1.5409337089999999E+00 -1.5538960110000000E+00 -1.5668690640000000E+00 -1.5798528590000001E+00 -1.5928473830000001E+00 -1.6058526270000000E+00 -1.6188685789999999E+00 -1.6318952280000001E+00 -1.6449325630000000E+00 -1.6579805750000001E+00 -1.6710392530000000E+00 -1.6841085840000001E+00 -1.6971885600000001E+00 -1.7102791680000000E+00 -1.7233803990000001E+00 -1.7364922400000000E+00 -1.7496146829999999E+00 -1.7627477140000001E+00 -1.7758913249999999E+00 -1.7890455050000000E+00 -1.8022102419999999E+00 -1.8153855260000000E+00 -1.8285713459999999E+00 -1.8417676910000000E+00 -1.8549745510000000E+00 -1.8681919130000000E+00 -1.8814197699999999E+00 -1.8946581080000000E+00 -1.9079069179999999E+00 -1.9211661890000000E+00 -1.9344359090000001E+00 -1.9477160689999999E+00 -1.9610066559999999E+00 -1.9743076610000001E+00 -1.9876190730000001E+00 -2.0009408820000001E+00 -2.0142730759999998E+00 -2.0276156450000000E+00 -2.0409685789999998E+00 -2.0543318660000001E+00 -2.0677054959999999E+00 -2.0810894580000001E+00 -2.0944837399999998E+00 -2.1078883350000002E+00 -2.1213032300000001E+00 -2.1347284150000001E+00 -2.1481638780000001E+00 -2.1616096100000002E+00 -2.1750655999999999E+00 -2.1885318360000001E+00 -2.2020083079999999E+00 -2.2154950059999998E+00 -2.2289919189999998E+00 -2.2424990370000000E+00 -2.2560163480000002E+00 -2.2695438420000000E+00 -2.2830815090000001E+00 -2.2966293370000002E+00 -2.3101873149999999E+00 -2.3237554349999998E+00 -2.3373336839999999E+00 -2.3509220530000001E+00 -2.3645205300000001E+00 -2.3781291059999998E+00 -2.3917477690000002E+00 -2.4053765100000000E+00 -2.4190153180000000E+00 -2.4326641809999998E+00 -2.4463230910000000E+00 -2.4599920370000001E+00 -2.4736710070000001E+00 -2.4873599920000000E+00 -2.5010589799999998E+00 -2.5147679620000001E+00 -2.5284869269999999E+00 -2.5422158630000000E+00 -2.5559547629999999E+00 -2.5697036130000002E+00 -2.5834624050000001E+00 -2.5972311270000001E+00 -2.6110097689999998E+00 -2.6247983200000000E+00 -2.6385967699999999E+00 -2.6524051090000000E+00 -2.6662233249999998E+00 -2.6800514089999998E+00 -2.6938893510000002E+00 -2.7077371399999999E+00 -2.7215947670000000E+00 -2.7354622229999999E+00 -2.7493394960000002E+00 -2.7632265789999999E+00 -2.7771234599999999E+00 -2.7910301309999999E+00 -2.8049465819999999E+00 -2.8188728020000000E+00 -2.8328087829999999E+00 -2.8467545150000002E+00 -2.8607099869999999E+00 -2.8746751910000001E+00 -2.8886501149999999E+00 -2.9026347520000000E+00 -2.9166290909999999E+00 -2.9306331229999998E+00 -2.9446468370000001E+00 -2.9586702240000000E+00 -2.9727032740000001E+00 -2.9867459780000001E+00 -3.0007983260000000E+00 -3.0148603070000002E+00 -3.0289319130000001E+00 -3.0430131340000002E+00 -3.0571039600000001E+00 -3.0712043819999999E+00 -3.0853143909999998E+00 -3.0994339769999999E+00 -3.1135631330000000E+00 -3.1277018470000000E+00 -3.1418501129999998E+00 -3.1560079220000001E+00 -3.1701752630000000E+00 -3.1843521290000001E+00 -3.1985385100000001E+00 -3.2127343970000002E+00 -3.2269397820000001E+00 -3.2411546549999999E+00 -3.2553790070000002E+00 -3.2696128299999998E+00 -3.2838561140000002E+00 -3.2981088509999998E+00 -3.3123710320000002E+00 -3.3266426480000000E+00 -3.3409236899999999E+00 -3.3552141480000000E+00 -3.3695140129999999E+00 -3.3838232790000000E+00 -3.3981419339999999E+00 -3.4124699700000001E+00 -3.4268073790000000E+00 -3.4411541510000001E+00 -3.4555102770000001E+00 -3.4698757489999998E+00 -3.4842505579999998E+00 -3.4986346970000000E+00 -3.5130281569999999E+00 -3.5274309289999999E+00 -3.5418430050000000E+00 -3.5562643779999998E+00 -3.5706950370000001E+00 -3.5851349760000000E+00 -3.5995841849999999E+00 -3.6140426560000001E+00 -3.6285103809999999E+00 -3.6429873530000001E+00 -3.6574735610000002E+00 -3.6719689980000001E+00 -3.6864736560000000E+00 -3.7009875249999999E+00 -3.7155105989999999E+00 -3.7300428669999999E+00 -3.7445843230000002E+00 -3.7591349570000001E+00 -3.7736947619999999E+00 -3.7882637280000000E+00 -3.8028418490000000E+00 -3.8174291139999998E+00 -3.8320255159999999E+00 -3.8466310469999998E+00 -3.8612456960000001E+00 -3.8758694590000000E+00 -3.8905023270000001E+00 -3.9051442910000000E+00 -3.9197953430000001E+00 -3.9344554770000002E+00 -3.9491246819999999E+00 -3.9638029530000001E+00 -3.9784902799999999E+00 -3.9931866569999999E+00 -4.0078920750000000E+00 -4.0226065259999997E+00 -4.0373300030000001E+00 -4.0520624969999997E+00 -4.0668040000000003E+00 -4.0815545059999998E+00 -4.0963140039999999E+00 -4.1110824890000002E+00 -4.1258599509999998E+00 -4.1406463840000001E+00 -4.1554417790000002E+00 -4.1702461279999996E+00 -4.1850594240000003E+00 -4.1998816569999997E+00 -4.2147128220000001E+00 -4.2295529079999996E+00 -4.2444019099999997E+00 -4.2592598180000003E+00 -4.2741266250000001E+00 -4.2890023240000001E+00 -4.3038869069999999E+00 -4.3187803660000004E+00 -4.3336826930000001E+00 -4.3485938810000002E+00 -4.3635139240000003E+00 -4.3784428120000003E+00 -4.3933805389999998E+00 -4.4083270969999999E+00 -4.4232824790000000E+00 -4.4382466770000004E+00 -4.4532196830000004E+00 -4.4682014890000001E+00 -4.4831920890000001E+00 -4.4981914749999996E+00 -4.5131996399999998E+00 -4.5282165750000001E+00 -4.5432422729999997E+00 -4.5582767270000000E+00 -4.5733199300000003E+00 -4.5883718719999997E+00 -4.6034325469999997E+00 -4.6185019489999997E+00 -4.6335800679999997E+00 -4.6486668980000001E+00 -4.6637624310000003E+00 -4.6788666589999997E+00 -4.6939795750000002E+00 -4.7091011710000004E+00 -4.7242314399999996E+00 -4.7393703750000000E+00 -4.7545179710000003E+00 -4.7696742160000003E+00 -4.7848391010000002E+00 -4.8000126260000000E+00 -4.8151947909999997E+00 -4.8303855660000004E+00 -4.8455849610000001E+00 -4.8607929550000000E+00 -4.8760095600000000E+00 -4.8912347550000002E+00 -4.9064685399999997E+00 -4.9217108950000004E+00 -4.9369618300000004E+00 -4.9522213250000000E+00 -4.9674893800000000E+00 -4.9827659840000003E+00 -4.9980511290000003E+00 -5.0133448139999999E+00 -5.0286470190000001E+00 -5.0439577540000000E+00 -5.0592769989999997E+00 -5.0746047540000001E+00 -5.0899409990000004E+00 -5.1052857429999996E+00 -5.1206389679999997E+00 -5.1360006729999998E+00 -5.1513708480000000E+00 -5.1667494930000002E+00 -5.1821365879999997E+00 -5.1975321330000002E+00 -5.2129361180000000E+00 -5.2283485430000001E+00 -5.2437693870000004E+00 -5.2591986620000002E+00 -5.2746363470000004E+00 -5.2900824320000002E+00 -5.3055369270000003E+00 -5.3209998120000002E+00 -5.3364710869999996E+00 -5.3519507419999997E+00 -5.3674387560000003E+00 -5.3829351509999999E+00 -5.3984398960000002E+00 -5.4139529910000004E+00 -5.4294744359999996E+00 -5.4450042109999996E+00 -5.4605423259999997E+00 -5.4760887609999997E+00 -5.4916435060000000E+00 -5.5072065600000002E+00 -5.5227779249999998E+00 -5.5383575799999996E+00 -5.5539455249999996E+00 -5.5695417500000000E+00 -5.5851462449999998E+00 -5.6007590100000000E+00 -5.6163800349999997E+00 -5.6320093189999998E+00 -5.6476468439999996E+00 -5.6632926090000000E+00 -5.6789466040000001E+00 -5.6946088289999999E+00 -5.7102792740000003E+00 -5.7259579289999998E+00 -5.7416447939999999E+00 -5.7573398579999999E+00 -5.7730431030000000E+00 -5.7887545480000000E+00 -5.8044741630000001E+00 -5.8202019480000002E+00 -5.8359379029999996E+00 -5.8516820180000000E+00 -5.8674342829999997E+00 -5.8831946879999997E+00 -5.8989632319999998E+00 -5.9147399070000004E+00 -5.9305247019999996E+00 -5.9463176270000000E+00 -5.9621186520000000E+00 -5.9779277869999996E+00 -5.9937450119999998E+00 -6.0095703269999996E+00 -6.0254037309999999E+00 -6.0412452060000001E+00 -6.0570947510000002E+00 -6.0729523660000000E+00 -6.0888180309999997E+00 -6.1046917460000003E+00 -6.1205735109999999E+00 -6.1364633059999996E+00 -6.1523611310000001E+00 -6.1682669749999999E+00 -6.1841808399999998E+00 -6.2001027049999999E+00 -6.2160325800000003E+00 -6.2319704549999999E+00 -6.2479163199999999E+00 -6.2638701650000002E+00 -6.2798319800000000E+00 -6.2958017740000001E+00 -6.3117795289999998E+00 -6.3277652340000001E+00 -6.3437588990000000E+00 -6.3597605039999996E+00 -6.3757700389999998E+00 -6.3917875139999998E+00 -6.4078129089999996E+00 -6.4238462130000000E+00 -6.4398874380000004E+00 -6.4559365629999999E+00 -6.4719935880000001E+00 -6.4880584929999996E+00 -6.5041312880000000E+00 -6.5202119630000004E+00 -6.5363005080000001E+00 -6.5523969129999999E+00 -6.5685011769999999E+00 -6.5846132920000002E+00 -6.6007332470000000E+00 -6.6168610420000000E+00 -6.6329966669999996E+00 -6.6491401220000004E+00 -6.6652913869999999E+00 -6.6814504719999999E+00 -6.6976173560000003E+00 -6.7137920409999996E+00 -6.7299745160000004E+00 -6.7461647810000001E+00 -6.7623628160000004E+00 -6.7785686309999997E+00 -6.7947822159999998E+00 -6.8110035609999997E+00 -6.8272326559999996E+00 -6.8434694900000004E+00 -6.8597140750000003E+00 -6.8759663900000003E+00 -6.8922264350000004E+00 -6.9084941999999998E+00 -6.9247696750000003E+00 -6.9410528600000001E+00 -6.9573437550000001E+00 -6.9736423390000004E+00 -6.9899486140000002E+00 -7.0062625690000004E+00 -7.0225841940000002E+00 -7.0389134990000004E+00 -7.0552504540000003E+00 -7.0715950789999997E+00 -7.0879473439999998E+00 -7.1043072580000004E+00 -7.1206748129999999E+00 -7.1370499880000002E+00 -7.1534327930000003E+00 -7.1698232180000003E+00 -7.1862212530000003E+00 -7.2026268980000001E+00 -7.2190401330000000E+00 -7.2354609679999999E+00 -7.2518893919999998E+00 -7.2683253870000000E+00 -7.2847689620000002E+00 -7.3012201069999998E+00 -7.3176788119999996E+00 -7.3341450669999997E+00 -7.3506188720000001E+00 -7.3671002269999999E+00 -7.3835891110000000E+00 -7.4000855259999998E+00 -7.4165894610000000E+00 -7.4331009159999999E+00 -7.4496198810000003E+00 -7.4661463560000003E+00 -7.4826803210000001E+00 -7.4992217859999997E+00 -7.5157707299999998E+00 -7.5323271549999999E+00 -7.5488910599999999E+00 -7.5654624249999998E+00 -7.5820412499999996E+00 -7.5986275350000003E+00 -7.6152212600000002E+00 -7.6318224250000002E+00 -7.6484310300000002E+00 -7.6650470640000004E+00 -7.6816705189999999E+00 -7.6983013939999996E+00 -7.7149396790000004E+00 -7.7315853639999998E+00 -7.7482384489999996E+00 -7.7648989339999996E+00 -7.7815667990000001E+00 -7.7982420330000002E+00 -7.8149246579999998E+00 -7.8316146430000000E+00 -7.8483119879999999E+00 -7.8650166830000003E+00 -7.8817287379999996E+00 -7.8984481329999996E+00 -7.9151748580000003E+00 -7.9319089229999999E+00 -7.9486503070000003E+00 -7.9653990019999998E+00 -7.9821550170000002E+00 -7.9989183419999996E+00 -8.0156889570000001E+00 -8.0324668720000005E+00 -8.0492520669999994E+00 -8.0660445519999993E+00 -8.0828443060000001E+00 -8.0996513310000005E+00 -8.1164656159999993E+00 -8.1332871610000002E+00 -8.1501159560000005E+00 -8.1669519909999995E+00 -8.1837952660000006E+00 -8.2006457810000004E+00 -8.2175035150000006E+00 -8.2343684699999997E+00 -8.2512406350000003E+00 -8.2681200199999996E+00 -8.2850065950000005E+00 -8.3019003799999993E+00 -8.3188013549999997E+00 -8.3357095099999992E+00 -8.3526248449999994E+00 -8.3695473590000002E+00 -8.3864770439999994E+00 -8.4034138889999994E+00 -8.4203578839999995E+00 -8.4373090390000005E+00 -8.4542673340000007E+00 -8.4712327789999993E+00 -8.4882053440000007E+00 -8.5051850479999995E+00 -8.5221718729999996E+00 -8.5391658079999999E+00 -8.5561668530000006E+00 -8.5731750079999998E+00 -8.5901902630000002E+00 -8.6072126180000001E+00 -8.6242420529999997E+00 -8.6412785680000006E+00 -8.6583221619999993E+00 -8.6753728270000003E+00 -8.6924305519999994E+00 -8.7094953369999999E+00 -8.7265671820000001E+00 -8.7436460670000002E+00 -8.7607319920000002E+00 -8.7778249570000000E+00 -8.7949249609999995E+00 -8.8120319760000001E+00 -8.8291460209999997E+00 -8.8462670760000002E+00 -8.8633951409999998E+00 -8.8805302160000004E+00 -8.8976722810000002E+00 -8.9148213460000001E+00 -8.9319773900000001E+00 -8.9491404249999995E+00 -8.9663104300000001E+00 -8.9834874150000008E+00 -9.0006713600000001E+00 -9.0178622649999998E+00 -9.0350601299999997E+00 -9.0522649449999992E+00 -9.0694766999999992E+00 -9.0866953939999995E+00 -9.1039210189999995E+00 -9.1211535739999992E+00 -9.1383930590000002E+00 -9.1556394539999992E+00 -9.1728927589999998E+00 -9.1901529740000001E+00 -9.2074200889999993E+00 -9.2246941029999991E+00 -9.2419750080000007E+00 -9.2592627929999995E+00 -9.2765574579999992E+00 -9.2938590029999997E+00 -9.3111674079999993E+00 -9.3284826830000007E+00 -9.3458048080000005E+00 -9.3631337929999994E+00 -9.3804696270000001E+00 -9.3978122919999993E+00 -9.4151618070000005E+00 -9.4325181520000001E+00 -9.4498813169999991E+00 -9.4672513120000001E+00 -9.4846281270000006E+00 -9.5020117420000005E+00 -9.5194021759999998E+00 -9.5367994009999997E+00 -9.5542034260000008E+00 -9.5716142509999997E+00 -9.5890318459999992E+00 -9.6064562309999992E+00 -9.6238873960000006E+00 -9.6413253310000009E+00 -9.6587700250000008E+00 -9.6762214800000006E+00 -9.6936796950000002E+00 -9.7111446600000004E+00 -9.7286163650000006E+00 -9.7460948100000007E+00 -9.7635799950000006E+00 -9.7810719099999996E+00 -9.7985705450000005E+00 -9.8160758989999994E+00 -9.8335879740000003E+00 -9.8511067489999995E+00 -9.8686322339999997E+00 -9.8861644190000000E+00 -9.9037032939999996E+00 -9.9212488590000003E+00 -9.9388011039999995E+00 -9.9563600379999997E+00 -9.9739256330000003E+00 -9.9914979079999995E+00 -1.0009076830000000E+01 -1.0026662430000000E+01 -1.0044254670000001E+01 -1.0061853579999999E+01 -1.0079459110000000E+01 -1.0097071300000000E+01 -1.0114690110000000E+01 -1.0132315560000000E+01 -1.0149947620000001E+01 -1.0167586310000001E+01 -1.0185231610000001E+01 -1.0202883529999999E+01 -1.0220542040000000E+01 -1.0238207170000001E+01 -1.0255878879999999E+01 -1.0273557179999999E+01 -1.0291242069999999E+01 -1.0308933540000000E+01 -1.0326631580000001E+01 -1.0344336210000000E+01 -1.0362047380000000E+01 -1.0379765129999999E+01 -1.0397489419999999E+01 -1.0415220280000000E+01 -1.0432957670000000E+01 -1.0450701609999999E+01 -1.0468452080000000E+01 -1.0486209080000000E+01 -1.0503972620000001E+01 -1.0521742670000000E+01 -1.0539519240000001E+01 -1.0557302320000000E+01 -1.0575091909999999E+01 -1.0592888000000000E+01 -1.0610690590000001E+01 -1.0628499670000000E+01 -1.0646315240000000E+01 -1.0664137289999999E+01 -1.0681965829999999E+01 -1.0699800829999999E+01 -1.0717642310000000E+01 -1.0735490250000000E+01 -1.0753344650000001E+01 -1.0771205500000001E+01 -1.0789072810000000E+01 -1.0806946560000000E+01 -1.0824826760000001E+01 -1.0842713379999999E+01 -1.0860606450000001E+01 -1.0878505929999999E+01 -1.0896411840000001E+01 -1.0914324160000000E+01 -1.0932242909999999E+01 -1.0950168050000000E+01 -1.0968099609999999E+01 -1.0986037550000001E+01 -1.1003981899999999E+01 -1.1021932619999999E+01 -1.1039889740000000E+01 -1.1057853229999999E+01 -1.1075823110000000E+01 -1.1093799340000000E+01 -1.1111781960000000E+01 -1.1129770920000000E+01 -1.1147766239999999E+01 -1.1165767910000000E+01 -1.1183775940000000E+01 -1.1201790290000000E+01 -1.1219810989999999E+01 -1.1237838020000000E+01 -1.1255871380000000E+01 -1.1273911070000000E+01 -1.1291957070000000E+01 -1.1310009389999999E+01 -1.1328068010000001E+01 -1.1346132949999999E+01 -1.1364204170000001E+01 -1.1382281710000001E+01 -1.1400365519999999E+01 -1.1418455639999999E+01 -1.1436552020000001E+01 -1.1454654700000001E+01 -1.1472763629999999E+01 -1.1490878850000000E+01 -1.1509000320000000E+01 -1.1527128060000001E+01 -1.1545262040000001E+01 -1.1563402280000000E+01 -1.1581548760000000E+01 -1.1599701500000000E+01 -1.1617860459999999E+01 -1.1636025660000000E+01 -1.1654197070000000E+01 -1.1672374730000000E+01 -1.1690558590000000E+01 -1.1708748670000000E+01 -1.1726944950000000E+01 -1.1745147449999999E+01 -1.1763356140000001E+01 -1.1781571030000000E+01 -1.1799792110000000E+01 -1.1818019380000001E+01 -1.1836252820000000E+01 -1.1854492450000000E+01 -1.1872738249999999E+01 -1.1890990220000001E+01 -1.1909248340000000E+01 -1.1927512640000000E+01 -1.1945783080000000E+01 -1.1964059680000000E+01 -1.1982342420000000E+01 -1.2000631300000000E+01 -1.2018926329999999E+01 -1.2037227480000000E+01 -1.2055534770000000E+01 -1.2073848170000000E+01 -1.2092167710000000E+01 -1.2110493340000000E+01 -1.2128825100000000E+01 -1.2147162959999999E+01 -1.2165506929999999E+01 -1.2183856980000000E+01 -1.2202213140000000E+01 -1.2220575380000000E+01 -1.2238943709999999E+01 -1.2257318110000000E+01 -1.2275698600000000E+01 -1.2294085150000001E+01 -1.2312477769999999E+01 -1.2330876450000000E+01 -1.2349281189999999E+01 -1.2367691980000000E+01 -1.2386108830000000E+01 -1.2404531710000001E+01 -1.2422960639999999E+01 -1.2441395600000000E+01 -1.2459836590000000E+01 -1.2478283610000000E+01 -1.2496736650000001E+01 -1.2515195710000000E+01 -1.2533660780000000E+01 -1.2552131859999999E+01 -1.2570608950000000E+01 -1.2589092030000000E+01 -1.2607581120000001E+01 -1.2626076189999999E+01 -1.2644577260000000E+01 -1.2663084300000000E+01 -1.2681597330000001E+01 -1.2700116319999999E+01 -1.2718641300000000E+01 -1.2737172230000001E+01 -1.2755709120000001E+01 -1.2774251980000001E+01 -1.2792800780000000E+01 -1.2811355539999999E+01 -1.2829916239999999E+01 -1.2848482880000001E+01 -1.2867055450000001E+01 -1.2885633970000001E+01 -1.2904218400000000E+01 -1.2922808760000001E+01 -1.2941405030000000E+01 -1.2960007230000000E+01 -1.2978615319999999E+01 -1.2997229330000000E+01 -1.3015849240000000E+01 -1.3034475049999999E+01 -1.3053106740000000E+01 -1.3071744330000000E+01 -1.3090387800000000E+01 -1.3109037150000001E+01 -1.3127692370000000E+01 -1.3146353469999999E+01 -1.3165020430000000E+01 -1.3183693260000000E+01 -1.3202371940000001E+01 -1.3221056490000000E+01 -1.3239746869999999E+01 -1.3258443110000000E+01 -1.3277145180000000E+01 -1.3295853100000000E+01 -1.3314566839999999E+01 -1.3333286420000000E+01 -1.3352011810000000E+01 -1.3370743030000000E+01 -1.3389480060000000E+01 -1.3408222920000000E+01 -1.3426971569999999E+01 -1.3445726029999999E+01 -1.3464486279999999E+01 -1.3483252340000000E+01 -1.3502024179999999E+01 -1.3520801820000001E+01 -1.3539585230000000E+01 -1.3558374420000000E+01 -1.3577169390000000E+01 -1.3595970120000000E+01 -1.3614776630000000E+01 -1.3633588890000000E+01 -1.3652406910000000E+01 -1.3671230680000001E+01 -1.3690060210000000E+01 -1.3708895480000001E+01 -1.3727736500000001E+01 -1.3746583240000000E+01 -1.3765435719999999E+01 -1.3784293920000000E+01 -1.3803157860000001E+01 -1.3822027510000000E+01 -1.3840902880000000E+01 -1.3859783950000001E+01 -1.3878670750000000E+01 -1.3897563229999999E+01 -1.3916461419999999E+01 -1.3935365300000001E+01 -1.3954274880000000E+01 -1.3973190130000001E+01 -1.3992111080000001E+01 -1.4011037699999999E+01 -1.4029970000000000E+01 -1.4048907959999999E+01 -1.4067851590000000E+01 -1.4086800880000000E+01 -1.4105755840000000E+01 -1.4124716440000000E+01 -1.4143682699999999E+01 -1.4162654590000001E+01 -1.4181632140000000E+01 -1.4200615320000001E+01 -1.4219604140000000E+01 -1.4238598580000000E+01 -1.4257598650000000E+01 -1.4276604340000000E+01 -1.4295615650000000E+01 -1.4314632570000001E+01 -1.4333655090000001E+01 -1.4352683230000000E+01 -1.4371716960000001E+01 -1.4390756300000000E+01 -1.4409801229999999E+01 -1.4428851750000000E+01 -1.4447907839999999E+01 -1.4466969530000000E+01 -1.4486036779999999E+01 -1.4505109620000001E+01 -1.4524188010000000E+01 -1.4543271980000000E+01 -1.4562361500000000E+01 -1.4581456590000000E+01 -1.4600557220000001E+01 -1.4619663409999999E+01 -1.4638775130000001E+01 -1.4657892400000000E+01 -1.4677015200000000E+01 -1.4696143540000000E+01 -1.4715277400000000E+01 -1.4734416789999999E+01 -1.4753561690000000E+01 -1.4772712120000000E+01 -1.4791868050000000E+01 -1.4811029500000000E+01 -1.4830196450000001E+01 -1.4849368900000000E+01 -1.4868546840000000E+01 -1.4887730290000000E+01 -1.4906919210000000E+01 -1.4926113630000000E+01 -1.4945313519999999E+01 -1.4964518900000000E+01 -1.4983729739999999E+01 -1.5002946059999999E+01 -1.5022167830000001E+01 -1.5041395079999999E+01 -1.5060627770000000E+01 -1.5079865930000000E+01 -1.5099109530000000E+01 -1.5118358580000001E+01 -1.5137613070000000E+01 -1.5156872990000000E+01 -1.5176138359999999E+01 -1.5195409150000000E+01 -1.5214685370000000E+01 -1.5233967000000000E+01 -1.5253254070000001E+01 -1.5272546540000000E+01 -1.5291844429999999E+01 -1.5311147710000000E+01 -1.5330456410000000E+01 -1.5349770500000000E+01 -1.5369089990000001E+01 -1.5388414859999999E+01 -1.5407745130000000E+01 -1.5427080770000000E+01 -1.5446421800000000E+01 -1.5465768199999999E+01 -1.5485119980000000E+01 -1.5504477120000001E+01 -1.5523839629999999E+01 -1.5543207490000000E+01 -1.5562580720000000E+01 -1.5581959299999999E+01 -1.5601343240000000E+01 -1.5620732510000000E+01 -1.5640127140000001E+01 -1.5659527110000001E+01 -1.5678932420000001E+01 -1.5698343050000000E+01 -1.5717759030000000E+01 -1.5737180320000000E+01 -1.5756606950000000E+01 -1.5776038890000001E+01 -1.5795476160000000E+01 -1.5814918730000000E+01 -1.5834366620000001E+01 -1.5853819809999999E+01 -1.5873278320000001E+01 -1.5892742119999999E+01 -1.5912211220000000E+01 -1.5931685610000001E+01 -1.5951165290000000E+01 -1.5970650259999999E+01 -1.5990140510000000E+01 -1.6009636050000001E+01 -1.6029136860000001E+01 -1.6048642950000001E+01 -1.6068154310000001E+01 -1.6087670939999999E+01 -1.6107192820000002E+01 -1.6126719980000001E+01 -1.6146252380000000E+01 -1.6165790040000001E+01 -1.6185332949999999E+01 -1.6204881109999999E+01 -1.6224434509999998E+01 -1.6243993159999999E+01 -1.6263557030000001E+01 -1.6283126150000001E+01 -1.6302700479999999E+01 -1.6322280050000000E+01 -1.6341864829999999E+01 -1.6361454840000000E+01 -1.6381050049999999E+01 -1.6400650469999999E+01 -1.6420256100000000E+01 -1.6439866930000001E+01 -1.6459482940000001E+01 -1.6479104159999999E+01 -1.6498730559999998E+01 -1.6518362150000002E+01 -1.6537998909999999E+01 -1.6557640849999999E+01 -1.6577287960000000E+01 -1.6596940239999999E+01 -1.6616597680000002E+01 -1.6636260279999998E+01 -1.6655928029999998E+01 -1.6675600939999999E+01 -1.6695278989999998E+01 -1.6714962190000001E+01 -1.6734650510000002E+01 -1.6754343989999999E+01 -1.6774042580000000E+01 -1.6793746290000001E+01 -1.6813455139999999E+01 -1.6833169099999999E+01 -1.6852888180000001E+01 -1.6872612360000002E+01 -1.6892341660000000E+01 -1.6912076050000000E+01 -1.6931815539999999E+01 -1.6951560120000000E+01 -1.6971309789999999E+01 -1.6991064540000000E+01 -1.7010824390000000E+01 -1.7030589299999999E+01 -1.7050359289999999E+01 -1.7070134339999999E+01 -1.7089914459999999E+01 -1.7109699639999999E+01 -1.7129489899999999E+01 -1.7149285209999999E+01 -1.7169085599999999E+01 -1.7188891040000001E+01 -1.7208701550000001E+01 -1.7228517109999999E+01 -1.7248337750000001E+01 -1.7268163439999999E+01 -1.7287994200000000E+01 -1.7307830010000000E+01 -1.7327670890000000E+01 -1.7347516819999999E+01 -1.7367367819999998E+01 -1.7387223870000000E+01 -1.7407084990000001E+01 -1.7426951160000002E+01 -1.7446822390000001E+01 -1.7466698670000000E+01 -1.7486580020000002E+01 -1.7506466410000002E+01 -1.7526357869999998E+01 -1.7546254380000001E+01 -1.7566155949999999E+01 -1.7586062559999998E+01 -1.7605974230000001E+01 -1.7625890960000000E+01 -1.7645812729999999E+01 -1.7665739570000000E+01 -1.7685671450000001E+01 -1.7705608389999998E+01 -1.7725550370000001E+01 -1.7745497409999999E+01 -1.7765449490000002E+01 -1.7785406640000001E+01 -1.7805368820000002E+01 -1.7825336060000001E+01 -1.7845308330000002E+01 -1.7865285669999999E+01 -1.7885268040000000E+01 -1.7905255470000000E+01 -1.7925247939999998E+01 -1.7945245440000001E+01 -1.7965247959999999E+01 -1.7985255490000000E+01 -1.8005268010000002E+01 -1.8025285510000000E+01 -1.8045307980000000E+01 -1.8065335409999999E+01 -1.8085367770000001E+01 -1.8105405070000000E+01 -1.8125447279999999E+01 -1.8145494410000001E+01 -1.8165546410000001E+01 -1.8185603300000000E+01 -1.8205665040000000E+01 -1.8225731650000000E+01 -1.8245803089999999E+01 -1.8265879360000000E+01 -1.8285960440000000E+01 -1.8306046330000001E+01 -1.8326136989999998E+01 -1.8346232440000001E+01 -1.8366332650000000E+01 -1.8386437610000002E+01 -1.8406547289999999E+01 -1.8426661719999998E+01 -1.8446780839999999E+01 -1.8466904660000001E+01 -1.8487033170000000E+01 -1.8507166340000001E+01 -1.8527304189999999E+01 -1.8547446669999999E+01 -1.8567593790000000E+01 -1.8587745529999999E+01 -1.8607901880000000E+01 -1.8628062809999999E+01 -1.8648228339999999E+01 -1.8668398430000000E+01 -1.8688573080000001E+01 -1.8708752270000002E+01 -1.8728935990000000E+01 -1.8749124230000000E+01 -1.8769316969999998E+01 -1.8789514210000000E+01 -1.8809715969999999E+01 -1.8829922280000002E+01 -1.8850133180000000E+01 -1.8870348700000001E+01 -1.8890568869999999E+01 -1.8910793720000001E+01 -1.8931023289999999E+01 -1.8951257609999999E+01 -1.8971496710000000E+01 -1.8991740629999999E+01 -1.9011989400000001E+01 -1.9032243040000001E+01 -1.9052501599999999E+01 -1.9072765109999999E+01 -1.9093033599999998E+01 -1.9113307089999999E+01 -1.9133585640000000E+01 -1.9153869250000000E+01 -1.9174157990000001E+01 -1.9194451860000001E+01 -1.9214750920000000E+01 -1.9235055169999999E+01 -1.9255364680000000E+01 -1.9275679449999998E+01 -1.9295999530000000E+01 -1.9316324949999998E+01 -1.9336655749999998E+01 -1.9356991950000001E+01 -1.9377333589999999E+01 -1.9397680699999999E+01 -1.9418033309999998E+01 -1.9438391469999999E+01 -1.9458755190000002E+01 -1.9479124519999999E+01 -1.9499499470000000E+01 -1.9519880100000002E+01 -1.9540266429999999E+01 -1.9560658490000002E+01 -1.9581056319999998E+01 -1.9601459949999999E+01 -1.9621869400000001E+01 -1.9642284730000000E+01 -1.9662705949999999E+01 -1.9683133080000001E+01 -1.9703566030000001E+01 -1.9724004669999999E+01 -1.9744448850000001E+01 -1.9764898460000001E+01 -1.9785353350000001E+01 -1.9805813400000002E+01 -1.9826278469999998E+01 -1.9846748439999999E+01 -1.9867223160000002E+01 -1.9887702520000001E+01 -1.9908186359999998E+01 -1.9928674579999999E+01 -1.9949167010000000E+01 -1.9969663550000000E+01 -1.9990164050000001E+01 -2.0010668389999999E+01 -2.0031176429999999E+01 -2.0051688039999998E+01 -2.0072203080000001E+01 -2.0092721439999998E+01 -2.0113242960000001E+01 -2.0133767530000000E+01 -2.0154294990000000E+01 -2.0174825240000001E+01 -2.0195358140000000E+01 -2.0215893540000000E+01 -2.0236431320000001E+01 -2.0256971350000001E+01 -2.0277513500000001E+01 -2.0298057629999999E+01 -2.0318603610000000E+01 -2.0339151309999998E+01 -2.0359700600000000E+01 -2.0380251330000000E+01 -2.0400803400000001E+01 -2.0421356650000000E+01 -2.0441910960000001E+01 -2.0462466190000001E+01 -2.0483022230000000E+01 -2.0503578910000002E+01 -2.0524136129999999E+01 -2.0544693740000000E+01 -2.0565251629999999E+01 -2.0585809630000000E+01 -4.0069918689567927E-02 -4.0129013151347412E-02 -4.0188064100443864E-02 -4.0247071549486133E-02 -4.0306035511102990E-02 -4.0364955997923294E-02 -4.0423833022575836E-02 -4.0482666597689475E-02 -4.0541456735893024E-02 -4.0600203449815297E-02 -4.0658906752085097E-02 -4.0717566655331307E-02 -4.0776183172182685E-02 -4.0834756315268103E-02 -4.0893286097216340E-02 -4.0951772530656246E-02 -4.1010215628216655E-02 -4.1068615402526376E-02 -4.1126971866214196E-02 -4.1185285031909005E-02 -4.1243554912239598E-02 -4.1301781519834789E-02 -4.1359964867323386E-02 -4.1418104967334252E-02 -4.1476201832496194E-02 -4.1534255475438028E-02 -4.1592265908788548E-02 -4.1650233145176636E-02 -4.1708157197231095E-02 -4.1766038077580732E-02 -4.1823875798854354E-02 -4.1881670373680853E-02 -4.1939421814688974E-02 -4.1997130134507614E-02 -4.2054795345765505E-02 -4.2112417461091539E-02 -4.2169996493114544E-02 -4.2227532454463299E-02 -4.2285025357766647E-02 -4.2342475215653423E-02 -4.2399882040752422E-02 -4.2457245845692521E-02 -4.2514566643102450E-02 -4.2571844445611115E-02 -4.2629079265847337E-02 -4.2686271116439876E-02 -4.2743420010017588E-02 -4.2800525959209343E-02 -4.2857588976643893E-02 -4.2914609074950101E-02 -4.2971586266756762E-02 -4.3028520564692724E-02 -4.3085411981386802E-02 -4.3142260529467825E-02 -4.3199066221564587E-02 -4.3255829070305965E-02 -4.3312549088320745E-02 -4.3369226288237722E-02 -4.3425860682685807E-02 -4.3482452284293725E-02 -4.3539001105690374E-02 -4.3595507159504512E-02 -4.3651970458365011E-02 -4.3708391014900691E-02 -4.3764768841740360E-02 -4.3821103951512813E-02 -4.3877396356846926E-02 -4.3933646070371514E-02 -4.3989853104715378E-02 -4.4046017472507318E-02 -4.4102139186376225E-02 -4.4158218258950874E-02 -4.4214254702860105E-02 -4.4270248530732706E-02 -4.4326199755197547E-02 -4.4382108388883450E-02 -4.4437974444419194E-02 -4.4493797934433622E-02 -4.4549578871555598E-02 -4.4605317268413880E-02 -4.4661013137637359E-02 -4.4716666491854767E-02 -4.4772277343695016E-02 -4.4827845705786906E-02 -4.4883371590759218E-02 -4.4938855011240807E-02 -4.4994295979860502E-02 -4.5049694509247111E-02 -4.5105050612029497E-02 -4.5160364300836399E-02 -4.5215635588296700E-02 -4.5270864487039250E-02 -4.5326051009692808E-02 -4.5381195168886203E-02 -4.5436296977248325E-02 -4.5491356447407920E-02 -4.5546373591993865E-02 -4.5601348423634940E-02 -4.5656280954959987E-02 -4.5711171198597848E-02 -4.5766019167177333E-02 -4.5820824873327219E-02 -4.5875588329676406E-02 -4.5930309548853687E-02 -4.5984988543487870E-02 -4.6039625326207777E-02 -4.6094219909642242E-02 -4.6148772306420102E-02 -4.6203282529170150E-02 -4.6257750590521229E-02 -4.6312176503102168E-02 -4.6366560279541773E-02 -4.6420901932468860E-02 -4.6475201474512270E-02 -4.6529458918300834E-02 -4.6583674276463365E-02 -4.6637847561628656E-02 -4.6691978786425579E-02 -4.6746067963482942E-02 -4.6800115105429557E-02 -4.6854120224894220E-02 -4.6908083334505815E-02 -4.6962004446893135E-02 -4.7015883574684995E-02 -4.7069720730510224E-02 -4.7123515926997657E-02 -4.7177269176776102E-02 -4.7230980492474414E-02 -4.7284649886721333E-02 -4.7338277372145764E-02 -4.7391862961376534E-02 -4.7445406667042396E-02 -4.7498908501772227E-02 -4.7552368478194842E-02 -4.7605786608939049E-02 -4.7659162906633704E-02 -4.7712497383907565E-02 -4.7765790053389511E-02 -4.7819040927708382E-02 -4.7872250019492926E-02 -4.7925417341372005E-02 -4.7978542905974496E-02 -4.8031626725929137E-02 -4.8084668813864799E-02 -4.8137669182410275E-02 -4.8190627844194409E-02 -4.8243544811846041E-02 -4.8296420097993960E-02 -4.8349253715266979E-02 -4.8402045676293984E-02 -4.8454795993703739E-02 -4.8507504680125088E-02 -4.8560171748186859E-02 -4.8612797210517852E-02 -4.8665381079746911E-02 -4.8717923368502870E-02 -4.8770424089414503E-02 -4.8822883255110687E-02 -4.8875300878220236E-02 -4.8927676971371931E-02 -4.8980011547194641E-02 -4.9032304618317188E-02 -4.9084556197368359E-02 -4.9136766296977025E-02 -4.9188934929771930E-02 -4.9241062108382000E-02 -4.9293147845435981E-02 -4.9345192153562707E-02 -4.9397195045391050E-02 -4.9449156533549796E-02 -4.9501076630667752E-02 -4.9552955349373790E-02 -4.9604792702296660E-02 -4.9656588702065241E-02 -4.9708343361308374E-02 -4.9760056692654805E-02 -4.9811728708733419E-02 -4.9863359422173049E-02 -4.9914948845602478E-02 -4.9966496991650518E-02 -5.0018003872946047E-02 -5.0069469502117839E-02 -5.0120893891794770E-02 -5.0172277054605578E-02 -5.0223619003179149E-02 -5.0274919750144337E-02 -5.0326179308129881E-02 -5.0377397689764625E-02 -5.0428574907677472E-02 -5.0479710974497147E-02 -5.0530805902852520E-02 -5.0581859705372399E-02 -5.0632872394685599E-02 -5.0683843983420990E-02 -5.0734774484207351E-02 -5.0785663909673498E-02 -5.0836512272448273E-02 -5.0887319585160518E-02 -5.0938085860439034E-02 -5.0988811110912635E-02 -5.1039495349210151E-02 -5.1090138587960424E-02 -5.1140740839792261E-02 -5.1191302117334456E-02 -5.1241822433215900E-02 -5.1292301800065360E-02 -5.1342740230511663E-02 -5.1393137737183653E-02 -5.1443494332710164E-02 -5.1493810029719991E-02 -5.1544084840841956E-02 -5.1594318778704906E-02 -5.1644511855937644E-02 -5.1694664085169012E-02 -5.1744775479027810E-02 -5.1794846050142861E-02 -5.1844875811143026E-02 -5.1894864774657067E-02 -5.1944812953313851E-02 -5.1994720359742209E-02 -5.2044587006570928E-02 -5.2094412906428869E-02 -5.2144198071944814E-02 -5.2193942515747591E-02 -5.2243646250466076E-02 -5.2293309288729037E-02 -5.2342931643165308E-02 -5.2392513326403739E-02 -5.2442054351073110E-02 -5.2491554729802298E-02 -5.2541014475220055E-02 -5.2590433599955244E-02 -5.2639812116636722E-02 -5.2689150037893262E-02 -5.2738447376353678E-02 -5.2787704144646855E-02 -5.2836920355401565E-02 -5.2886096021246637E-02 -5.2935231154810913E-02 -5.2984325768723188E-02 -5.3033379875612310E-02 -5.3082393488107116E-02 -5.3131366618836356E-02 -5.3180299280428944E-02 -5.3229191485513659E-02 -5.3278043246719323E-02 -5.3326854576674756E-02 -5.3375625488008782E-02 -5.3424355993350242E-02 -5.3473046105327958E-02 -5.3521695836570710E-02 -5.3570305199707388E-02 -5.3618874207366760E-02 -5.3667402872177666E-02 -5.3715891206768937E-02 -5.3764339223769414E-02 -5.3812746935807877E-02 -5.3861114355513176E-02 -5.3909441495514104E-02 -5.3957728368439539E-02 -5.4005974986918254E-02 -5.4054181363579083E-02 -5.4102347511050870E-02 -5.4150473441962430E-02 -5.4198559168942562E-02 -5.4246604704620151E-02 -5.4294610061623921E-02 -5.4342575252582764E-02 -5.4390500290125515E-02 -5.4438385186880933E-02 -5.4486229955477895E-02 -5.4534034608545230E-02 -5.4581799158711725E-02 -5.4629523618606221E-02 -5.4677208000857513E-02 -5.4724852318094472E-02 -5.4772456582945904E-02 -5.4820020808040597E-02 -5.4867545006007407E-02 -5.4915029189475176E-02 -5.4962473371072691E-02 -5.5009877563428788E-02 -5.5057241779172289E-02 -5.5104566030932001E-02 -5.5151850331336780E-02 -5.5199094693015427E-02 -5.5246299128596771E-02 -5.5293463650709640E-02 -5.5340588271982849E-02 -5.5387673005045227E-02 -5.5434717862525559E-02 -5.5481722857052738E-02 -5.5528688001255551E-02 -5.5575613307762804E-02 -5.5622498789203348E-02 -5.5669344458205997E-02 -5.5716150327399572E-02 -5.5762916409412874E-02 -5.5809642716874767E-02 -5.5856329262414059E-02 -5.5902976058659556E-02 -5.5949583118240095E-02 -5.5996150453784511E-02 -5.6042678077921626E-02 -5.6089166003280233E-02 -5.6135614242489147E-02 -5.6182022808177259E-02 -5.6228391712973336E-02 -5.6274720969506205E-02 -5.6321010590404702E-02 -5.6367260588297649E-02 -5.6413470975813867E-02 -5.6459641765582172E-02 -5.6505772970231412E-02 -5.6551864602390381E-02 -5.6597916674687929E-02 -5.6643929199752835E-02 -5.6689902190213942E-02 -5.6735835658700128E-02 -5.6781729617840136E-02 -5.6827584080262811E-02 -5.6873399058597021E-02 -5.6919174565471534E-02 -5.6964910613515211E-02 -5.7010607215356834E-02 -5.7056264383625245E-02 -5.7101882130949314E-02 -5.7147460469957785E-02 -5.7192999413279502E-02 -5.7238498973543356E-02 -5.7283959163378084E-02 -5.7329379995412558E-02 -5.7374761482275584E-02 -5.7420103636595970E-02 -5.7465406471002567E-02 -5.7510669998124195E-02 -5.7555894230589641E-02 -5.7601079181027776E-02 -5.7646224862067413E-02 -5.7691331286337355E-02 -5.7736398466466443E-02 -5.7781426415083458E-02 -5.7826415144817289E-02 -5.7871364668296732E-02 -5.7916274998150566E-02 -5.7961146147007675E-02 -5.8005978127496874E-02 -5.8050770952246949E-02 -5.8095524633886758E-02 -5.8140239185045114E-02 -5.8184914618350847E-02 -5.8229550946432757E-02 -5.8274148181919665E-02 -5.8318706337440421E-02 -5.8363225425623853E-02 -5.8407705459098749E-02 -5.8452146450493944E-02 -5.8496548412438294E-02 -5.8540911357560579E-02 -5.8585235298489663E-02 -5.8629520247854297E-02 -5.8673766218283380E-02 -5.8717973222405719E-02 -5.8762141272850101E-02 -5.8806270382245368E-02 -5.8850360563220377E-02 -5.8894411828403902E-02 -5.8938424190424797E-02 -5.8982397661911851E-02 -5.9026332255493918E-02 -5.9070227983799836E-02 -5.9114084859458377E-02 -5.9157902895098397E-02 -5.9201682103348738E-02 -5.9245422496838160E-02 -5.9289124088195547E-02 -5.9332786890049692E-02 -5.9376410915029432E-02 -5.9419996175763587E-02 -5.9463542684880959E-02 -5.9507050455010396E-02 -5.9550519498780721E-02 -5.9593949828820755E-02 -5.9637341457759306E-02 -5.9680694398225195E-02 -5.9724008662847272E-02 -5.9767284264254344E-02 -5.9810521215075220E-02 -5.9853719527938748E-02 -5.9896879215473736E-02 -5.9940000290309020E-02 -5.9983082765073407E-02 -6.0026126652395720E-02 -6.0069131964904821E-02 -6.0112098715229469E-02 -6.0155026915998520E-02 -6.0197916579840811E-02 -6.0240767719385149E-02 -6.0283580347260363E-02 -6.0326354476095259E-02 -6.0369090118518667E-02 -6.0411787287159430E-02 -6.0454445994646347E-02 -6.0497066253608248E-02 -6.0539648076673974E-02 -6.0582191476472314E-02 -6.0624696465632136E-02 -6.0667163056782214E-02 -6.0709591262551377E-02 -6.0751981095568508E-02 -6.0794332568462353E-02 -6.0836645693861754E-02 -6.0878920484395596E-02 -6.0921156952692623E-02 -6.0963355111381699E-02 -6.1005514973091646E-02 -6.1047636550451249E-02 -6.1089719856089394E-02 -6.1131764902634847E-02 -6.1173771702716442E-02 -6.1215740268963058E-02 -6.1257670614003445E-02 -6.1299562750466469E-02 -6.1341416690980921E-02 -6.1383232448175645E-02 -6.1425010034679470E-02 -6.1466749463121223E-02 -6.1508450746129678E-02 -6.1550113896333719E-02 -6.1591738926362140E-02 -6.1633325848843776E-02 -6.1674874676407421E-02 -6.1716385421681938E-02 -6.1757858097296128E-02 -6.1799292715878820E-02 -6.1840689290058801E-02 -6.1882047832464968E-02 -6.1923368355726094E-02 -6.1964650872471001E-02 -6.2005895395328525E-02 -6.2047101936927494E-02 -6.2088270509896709E-02 -6.2129401126865005E-02 -6.2170493800461232E-02 -6.2211548543314170E-02 -6.2252565368052667E-02 -6.2293544287305526E-02 -6.2334485313701601E-02 -6.2375388459869688E-02 -6.2416253738438621E-02 -6.2457081162037215E-02 -6.2497870743294305E-02 -6.2538622494838700E-02 -6.2579336429299248E-02 -6.2620012559304730E-02 -6.2660650897484002E-02 -6.2701251456465906E-02 -6.2741814248879216E-02 -6.2782339287352745E-02 -6.2822826584515407E-02 -6.2863276152995931E-02 -6.2903688005423189E-02 -6.2944062154425981E-02 -6.2984398612633136E-02 -6.3024697392673495E-02 -6.3064958507175861E-02 -6.3105181968769034E-02 -6.3145367790081910E-02 -6.3185515983743237E-02 -6.3225626562381884E-02 -6.3265699538626638E-02 -6.3305734925106355E-02 -6.3345732734449850E-02 -6.3385692979285924E-02 -6.3425615672243418E-02 -6.3465500825951177E-02 -6.3505348453037985E-02 -6.3545158566132687E-02 -6.3584931177864068E-02 -6.3624666300861027E-02 -6.3664363947752323E-02 -6.3704024131166784E-02 -6.3743646863733280E-02 -6.3783232158080586E-02 -6.3822780026837556E-02 -6.3862290482632977E-02 -6.3901763538095679E-02 -6.3941199205854532E-02 -6.3980597498538308E-02 -6.4019958428775836E-02 -6.4059282009195972E-02 -6.4098568252427518E-02 -6.4137817171099301E-02 -6.4177028777840123E-02 -6.4216203085278825E-02 -6.4255340106044251E-02 -6.4294439852765173E-02 -6.4333502338070447E-02 -6.4372527574588889E-02 -6.4411515574949341E-02 -6.4450466351780616E-02 -6.4489379917711517E-02 -6.4528256285370872E-02 -6.4567095467387522E-02 -6.4605897476390284E-02 -6.4644662325007957E-02 -6.4683390025869411E-02 -6.4722080591603434E-02 -6.4760734034838854E-02 -6.4799350368204514E-02 -6.4837929604329186E-02 -6.4876471755841769E-02 -6.4914976835371008E-02 -6.4953444855545772E-02 -6.4991875828994891E-02 -6.5030269768347151E-02 -6.5068626686231409E-02 -6.5106946595276480E-02 -6.5145229508111149E-02 -6.5183475437364302E-02 -6.5221684395664739E-02 -6.5259856395641247E-02 -6.5297991449922696E-02 -6.5336089571137887E-02 -6.5374150771915648E-02 -6.5412175064884809E-02 -6.5450162462674155E-02 -6.5488112977912558E-02 -6.5526026623228831E-02 -6.5563903411251748E-02 -6.5601743354610206E-02 -6.5639546465933007E-02 -6.5677312757848924E-02 -6.5715042242986826E-02 -6.5752734933975543E-02 -6.5790390843443874E-02 -6.5828009984020663E-02 -6.5865592368334669E-02 -6.5903138009014803E-02 -6.5940646918689866E-02 -6.5978119109988645E-02 -6.6015554595539969E-02 -6.6052953387972693E-02 -6.6090315499915619E-02 -6.6127640943997590E-02 -6.6164929732847377E-02 -6.6202181879093866E-02 -6.6239397395365857E-02 -6.6276576294292136E-02 -6.6313718588501575E-02 -6.6350824290623001E-02 -6.6387893413285187E-02 -6.6424925969117005E-02 -6.6461921970747240E-02 -6.6498881430804735E-02 -6.6535804361918333E-02 -6.6572690776716806E-02 -6.6609540687829025E-02 -6.6646354107883804E-02 -6.6683131049509931E-02 -6.6719871525336275E-02 -6.6756575547991637E-02 -6.6793243130104818E-02 -6.6829874284304688E-02 -6.6866469023220035E-02 -6.6903027359479686E-02 -6.6939549305712484E-02 -6.6976034874547230E-02 -6.7012484078612780E-02 -6.7048896930537893E-02 -6.7085273442951468E-02 -6.7121613628482291E-02 -6.7157917499759162E-02 -6.7194185069410939E-02 -6.7230416350066435E-02 -6.7266611354354452E-02 -6.7302770094903874E-02 -6.7338892584343460E-02 -6.7374978835302066E-02 -6.7411028860408492E-02 -6.7447042672291568E-02 -6.7483020283580136E-02 -6.7518961706903011E-02 -6.7554866954888992E-02 -6.7590736040166938E-02 -6.7626568975365661E-02 -6.7662365773113964E-02 -6.7698126446040702E-02 -6.7733851006774648E-02 -6.7769539467944673E-02 -6.7805191842179591E-02 -6.7840808142108217E-02 -6.7876388380359351E-02 -6.7911932569561878E-02 -6.7947440722344557E-02 -6.7982912851336258E-02 -6.8018348969165754E-02 -6.8053749088461915E-02 -6.8089113221853542E-02 -6.8124441381969464E-02 -6.8159733581438495E-02 -6.8194989832889477E-02 -6.8230210148951226E-02 -6.8265394542252542E-02 -6.8300543025422267E-02 -6.8335655611089230E-02 -6.8370732311882246E-02 -6.8405773140430129E-02 -6.8440778109361736E-02 -6.8475747231305839E-02 -6.8510680518891309E-02 -6.8545577984746947E-02 -6.8580439641501553E-02 -6.8615265501783984E-02 -6.8650055578223068E-02 -6.8684809883447592E-02 -6.8719528430086413E-02 -6.8754211230768345E-02 -6.8788858298122202E-02 -6.8823469644776814E-02 -6.8858045283360994E-02 -6.8892585226503572E-02 -6.8927089486833376E-02 -6.8961558076979221E-02 -6.8995991009569949E-02 -6.9030388297234360E-02 -6.9064749952601284E-02 -6.9099075988299549E-02 -6.9133366416957956E-02 -6.9167621251205347E-02 -6.9201840503670564E-02 -6.9236024186982381E-02 -6.9270172313769682E-02 -6.9304284896661239E-02 -6.9338361948285909E-02 -6.9372403481272493E-02 -6.9406409508249792E-02 -6.9440380041846689E-02 -6.9474315094691985E-02 -6.9508214679414454E-02 -6.9542078808642993E-02 -6.9575907495006376E-02 -6.9609700751133458E-02 -6.9643458589653012E-02 -6.9677181023193924E-02 -6.9710868064384979E-02 -6.9744519725855006E-02 -6.9778136020232806E-02 -6.9811716960147263E-02 -6.9845262558227150E-02 -6.9878772827101296E-02 -6.9912247779398529E-02 -6.9945687427747677E-02 -6.9979091784777556E-02 -7.0012460863117007E-02 -7.0045794675394818E-02 -7.0079093234239845E-02 -7.0112356552280902E-02 -7.0145584642146791E-02 -7.0178777516466367E-02 -7.0211935187868446E-02 -7.0245057668981842E-02 -7.0278144972435369E-02 -7.0311197110857843E-02 -7.0344214096878147E-02 -7.0377195943125040E-02 -7.0410142662227351E-02 -7.0443054266813937E-02 -7.0475930769513598E-02 -7.0508772182955162E-02 -7.0541578519767459E-02 -7.0574349792579288E-02 -7.0607086014019493E-02 -7.0639787196716902E-02 -7.0672453353300316E-02 -7.0705084496398576E-02 -7.0737680638640499E-02 -7.0770241792654912E-02 -7.0802767971070643E-02 -7.0835259186516480E-02 -7.0867715451621294E-02 -7.0900136779013884E-02 -7.0932523181323065E-02 -7.0964874671177680E-02 -7.0997191261206544E-02 -7.1029472964038470E-02 -7.1061719792302289E-02 -7.1093931758626827E-02 -7.1126108875640914E-02 -7.1158251155973365E-02 -7.1190358612252980E-02 -7.1222431257108615E-02 -7.1254469103169085E-02 -7.1286472163063191E-02 -7.1318440449419790E-02 -7.1350373974867695E-02 -7.1382272752035722E-02 -7.1414136793552685E-02 -7.1445966112047427E-02 -7.1477760720148747E-02 -7.1509520630485490E-02 -7.1541245855686469E-02 -7.1572936408380514E-02 -7.1604592301196451E-02 -7.1636213546763083E-02 -7.1667800157709252E-02 -7.1699352146663758E-02 -7.1730869526255459E-02 -7.1762352309113153E-02 -7.1793800507865657E-02 -7.1825214135141827E-02 -7.1856593203570462E-02 -7.1887937725780379E-02 -7.1919247714400419E-02 -7.1950523182059384E-02 -7.1981764141386115E-02 -7.2012970605009427E-02 -7.2044142585558149E-02 -7.2075280095661096E-02 -7.2106383147947109E-02 -7.2137451755044976E-02 -7.2168485929583553E-02 -7.2199485684191642E-02 -7.2230451031498083E-02 -7.2261381984131706E-02 -7.2292278554721284E-02 -7.2323140755895701E-02 -7.2353968600283758E-02 -7.2384762100514269E-02 -7.2415521269216049E-02 -7.2446246119017940E-02 -7.2476936662548758E-02 -7.2507592912437330E-02 -7.2538214881312471E-02 -7.2568802581803010E-02 -7.2599356026537776E-02 -7.2629875228145582E-02 -7.2660360199255258E-02 -7.2690810952495605E-02 -7.2721227500495492E-02 -7.2751609855883692E-02 -7.2781958031289062E-02 -7.2812272039340403E-02 -7.2842551892666557E-02 -7.2872797603896339E-02 -7.2903009185658577E-02 -7.2933186650582058E-02 -7.2963330011295652E-02 -7.2993439280428174E-02 -7.3023514470608425E-02 -7.3053555594465247E-02 -7.3083562664627455E-02 -7.3113535693723891E-02 -7.3143474694383329E-02 -7.3173379679234637E-02 -7.3203250660906632E-02 -7.3233087652028128E-02 -7.3262890665227939E-02 -7.3292659713134908E-02 -7.3322394808377864E-02 -7.3352095963585592E-02 -7.3381763191386951E-02 -7.3411396504410739E-02 -7.3440995915285801E-02 -7.3470561436640949E-02 -7.3500093081104986E-02 -7.3529590861306782E-02 -7.3559054789875122E-02 -7.3588484879438851E-02 -7.3617881142626768E-02 -7.3647243592067715E-02 -7.3676572240390509E-02 -7.3705867100223990E-02 -7.3735128184196932E-02 -7.3764355504938206E-02 -7.3793549075076639E-02 -7.3822708907241005E-02 -7.3851835014060174E-02 -7.3880927408162947E-02 -7.3909986102178152E-02 -7.3939011108734617E-02 -7.3968002440461145E-02 -7.3996960109986590E-02 -7.4025884129939754E-02 -7.4054774512949451E-02 -7.4083631271644537E-02 -7.4112454418653800E-02 -7.4141243966606082E-02 -7.4169999928130226E-02 -7.4198722315855004E-02 -7.4227411142409286E-02 -7.4256066420421860E-02 -7.4284688162521567E-02 -7.4313276381337223E-02 -7.4341831089497670E-02 -7.4370352299631709E-02 -7.4398840024368168E-02 -7.4427294276335876E-02 -7.4455715068163661E-02 -7.4484102412480324E-02 -7.4512456321914694E-02 -7.4540776809095613E-02 -7.4569063886651910E-02 -7.4597317567212371E-02 -7.4625537863405825E-02 -7.4653724787861142E-02 -7.4681878353207096E-02 -7.4709998572072514E-02 -7.4738085457086240E-02 -7.4766139020877087E-02 -7.4794159276073885E-02 -7.4822146235305448E-02 -7.4850099911200590E-02 -7.4878020316388155E-02 -7.4905907463496957E-02 -7.4933761365155824E-02 -7.4961582033993557E-02 -7.4989369482638998E-02 -7.5017123723720977E-02 -7.5044844769868307E-02 -7.5072532633709804E-02 -7.5100187327874296E-02 -7.5127808864990625E-02 -7.5155397257687592E-02 -7.5182952518594012E-02 -7.5210474660338741E-02 -7.5237963695550567E-02 -7.5265419636858330E-02 -7.5292842496890847E-02 -7.5320232288276959E-02 -7.5347589023645467E-02 -7.5374912715625214E-02 -7.5402203376845001E-02 -7.5429461019933655E-02 -7.5456685657520020E-02 -7.5483877302232882E-02 -7.5511035966701112E-02 -7.5538161663553496E-02 -7.5565254405418864E-02 -7.5592314204926056E-02 -7.5619341074703861E-02 -7.5646335027381148E-02 -7.5673296075586705E-02 -7.5700224231949359E-02 -7.5727119509097940E-02 -7.5753981919661276E-02 -7.5780811476268181E-02 -7.5807608191547485E-02 -7.5834372078128001E-02 -7.5861103148638573E-02 -7.5887801415708001E-02 -7.5914466891965099E-02 -7.5941099590038724E-02 -7.5967699522557691E-02 -7.5994266702150787E-02 -7.6020801141446895E-02 -7.6047302853074775E-02 -7.6073771849663296E-02 -7.6100208143841275E-02 -7.6126611748237497E-02 -7.6152982675480832E-02 -7.6179320938200082E-02 -7.6205626549024075E-02 -7.6231899520581639E-02 -7.6258139865501562E-02 -7.6284347596412713E-02 -7.6310522725943894E-02 -7.6336665266723919E-02 -7.6362775231381644E-02 -7.6388852632545856E-02 -7.6414897482845384E-02 -7.6440909794909084E-02 -7.6466889581365730E-02 -7.6492836854844176E-02 -7.6518751627973253E-02 -7.6544633913381746E-02 -7.6570483723698513E-02 -7.6596301071552367E-02 -7.6622085969572110E-02 -7.6647838430386625E-02 -7.6673558466624658E-02 -7.6699246090915066E-02 -7.6724901315886704E-02 -7.6750524154168331E-02 -7.6776114618388819E-02 -7.6801672721176995E-02 -7.6827198475161632E-02 -7.6852691892971600E-02 -7.6878152987235701E-02 -7.6903581770582749E-02 -7.6928978255641614E-02 -7.6954342455041069E-02 -7.6979674381409957E-02 -7.7004974047377092E-02 -7.7030241465571289E-02 -7.7055476648621418E-02 -7.7080679609156252E-02 -7.7105850359804620E-02 -7.7130988913195378E-02 -7.7156095281957313E-02 -7.7181169478719266E-02 -7.7206211516110054E-02 -7.7231221406758491E-02 -7.7256199163293432E-02 -7.7281144798343665E-02 -7.7306058324538018E-02 -7.7330939754505362E-02 -7.7355789100874442E-02 -7.7380606376274141E-02 -7.7405391593333248E-02 -7.7430144764680603E-02 -7.7454865902945022E-02 -7.7479555020755334E-02 -7.7504212130740352E-02 -7.7528837245528920E-02 -7.7553430377749838E-02 -7.7577991540031935E-02 -7.7602520745004039E-02 -7.7627018005294965E-02 -7.7651483333533555E-02 -7.7675916742348611E-02 -7.7700318244368960E-02 -7.7724687852223445E-02 -7.7749025578540853E-02 -7.7773331435950041E-02 -7.7797605437079809E-02 -7.7821847594558985E-02 -7.7846057921016398E-02 -7.7870236429080891E-02 -7.7894383131381237E-02 -7.7918498040546291E-02 -7.7942581169204883E-02 -7.7966632529985827E-02 -7.7990652135517924E-02 -7.8014639998430030E-02 -7.8038596131350946E-02 -7.8062520546909514E-02 -7.8086413257734535E-02 -7.8110274276454852E-02 -7.8134103615699294E-02 -7.8157901288096659E-02 -7.8181667306275765E-02 -7.8205401682865452E-02 -7.8229104430494564E-02 -7.8252775561791887E-02 -7.8276415089386250E-02 -7.8300023025906496E-02 -7.8323599383981438E-02 -7.8347144176239905E-02 -7.8370657415310685E-02 -7.8394139113822647E-02 -7.8417589284404607E-02 -7.8441007939685364E-02 -7.8464395092293748E-02 -7.8487750754858587E-02 -7.8511074940008710E-02 -7.8534367660372945E-02 -7.8557628928580078E-02 -7.8580858757258981E-02 -7.8604057159038454E-02 -7.8627224146547312E-02 -7.8650359732414382E-02 -7.8673463929268508E-02 -7.8696536749738477E-02 -7.8719578206453145E-02 -7.8742588312041312E-02 -7.8765567079131821E-02 -7.8788514520353473E-02 -7.8811430648335123E-02 -7.8834315475705546E-02 -7.8857169015093612E-02 -7.8879991279128120E-02 -7.8902782280437886E-02 -7.8925542031651766E-02 -7.8948270545398547E-02 -7.8970967834307057E-02 -7.8993633911006153E-02 -7.9016268788124608E-02 -7.9038872478291292E-02 -7.9061444994134991E-02 -7.9083986348284549E-02 -7.9106496553368780E-02 -7.9128975622016512E-02 -7.9151423566856574E-02 -7.9173840400517767E-02 -7.9196226135628947E-02 -7.9218580784818901E-02 -7.9240904360716471E-02 -7.9263196875950487E-02 -7.9285458343149762E-02 -7.9307688774943111E-02 -7.9329888183959377E-02 -7.9352056582827360E-02 -7.9374193984175917E-02 -7.9396300400633835E-02 -7.9418375844829942E-02 -7.9440420329393080E-02 -7.9462433866952065E-02 -7.9484416470135724E-02 -7.9506368151572859E-02 -7.9528288923892299E-02 -7.9550178799722898E-02 -7.9572037791693445E-02 -7.9593865912432768E-02 -7.9615663174569709E-02 -7.9637429590733069E-02 -7.9659165173551691E-02 -7.9680869935654375E-02 -7.9702543889669963E-02 -7.9724187048227257E-02 -7.9745799423955113E-02 -7.9767381029482332E-02 -7.9788931877437727E-02 -7.9810451980450142E-02 -7.9831941351148392E-02 -7.9853400002161304E-02 -7.9874827946117694E-02 -7.9896225195646389E-02 -7.9917591763376220E-02 -7.9938927661935985E-02 -7.9960232903954528E-02 -7.9981507502060664E-02 -8.0002751468883235E-02 -8.0023964817051027E-02 -8.0045147559192897E-02 -8.0066299707937647E-02 -8.0087421275914117E-02 -8.0108512275751109E-02 -8.0129572720077466E-02 -8.0150602621522002E-02 -8.0171601992713545E-02 -8.0192570846280911E-02 -8.0213509194852928E-02 -8.0234417051058410E-02 -8.0255294427526200E-02 -8.0276141336885098E-02 -8.0296957791763934E-02 -8.0317743804791536E-02 -8.0338499388596718E-02 -8.0359224555808323E-02 -8.0379919319055165E-02 -8.0400583690966046E-02 -8.0421217684169821E-02 -8.0441821311295292E-02 -8.0462394584971286E-02 -8.0482937517826619E-02 -8.0503450122490133E-02 -8.0523932411590643E-02 -8.0544384397756977E-02 -8.0564806093617936E-02 -8.0585197511802362E-02 -8.0605558664939070E-02 -8.0625889565656902E-02 -8.0646190226584646E-02 -8.0666460660351158E-02 -8.0686700879585238E-02 -8.0706910896915729E-02 -8.0727090724971445E-02 -8.0747240376381202E-02 -8.0767359863773827E-02 -8.0787449199778150E-02 -8.0807508397022984E-02 -8.0827537468137159E-02 -8.0847536425749489E-02 -8.0867505282488816E-02 -8.0887444050983942E-02 -8.0907352743863695E-02 -8.0927231373756917E-02 -8.0947079953292395E-02 -8.0966898495098999E-02 -8.0986687011805503E-02 -8.1006445516040762E-02 -8.1026174020433592E-02 -8.1045872537612806E-02 -8.1065541080207235E-02 -8.1085179660845705E-02 -8.1104788292157046E-02 -8.1124366986770058E-02 -8.1143915757313570E-02 -8.1163434616416424E-02 -8.1182923576707436E-02 -8.1202382650815419E-02 -8.1221811851369188E-02 -8.1241211190997586E-02 -8.1260580682329428E-02 -8.1279920337993541E-02 -8.1299230170618741E-02 -8.1318510192833857E-02 -8.1337760417267715E-02 -8.1356980856549119E-02 -8.1376171523306923E-02 -8.1395332430169914E-02 -8.1414463589766950E-02 -8.1433565014726816E-02 -8.1452636717678384E-02 -8.1471678711250439E-02 -8.1490691008071811E-02 -8.1509673620771328E-02 -8.1528626561977804E-02 -8.1547549844320083E-02 -8.1566443480426964E-02 -8.1585307482927277E-02 -8.1604141864449864E-02 -8.1622946637623511E-02 -8.1641721815077090E-02 -8.1660467409439372E-02 -8.1679183433339214E-02 -8.1697869899405445E-02 -8.1716526820266838E-02 -8.1735154208552277E-02 -8.1753752076890548E-02 -8.1772320437910495E-02 -8.1790859304240918E-02 -8.1809368688510659E-02 -8.1827848603348532E-02 -8.1846299061383368E-02 -8.1864720075243966E-02 -8.1883111657559182E-02 -8.1901473820957832E-02 -8.1919806578068716E-02 -8.1938109941520676E-02 -8.1956383923942541E-02 -8.1974628537963112E-02 -8.1992843796211232E-02 -8.2011029711315714E-02 -8.2029186295905387E-02 -8.2047313562609067E-02 -8.2065411524055581E-02 -8.2083480192873745E-02 -8.2101519581692400E-02 -8.2119529703140348E-02 -8.2137510569846417E-02 -8.2155462194439449E-02 -8.2173384589548232E-02 -8.2191277767801621E-02 -8.2209141741828445E-02 -8.2226976524257492E-02 -8.2244782127717603E-02 -8.2262558564837593E-02 -8.2280305848246305E-02 -8.2298023990572539E-02 -8.2315713004445124E-02 -8.2333372902492902E-02 -8.2351003697344674E-02 -8.2368605401629269E-02 -8.2386178027975515E-02 -8.2403721589012227E-02 -8.2421236097368233E-02 -8.2438721565672363E-02 -8.2456178006553416E-02 -8.2473605432640248E-02 -8.2491003856561648E-02 -8.2508373290946471E-02 -8.2525713748423532E-02 -8.2543025241621631E-02 -8.2560307783169612E-02 -8.2577561385696288E-02 -8.2594786061830489E-02 -8.2611981824201042E-02 -8.2629148685436762E-02 -8.2646286658166465E-02 -8.2663395755019006E-02 -8.2680475988623159E-02 -8.2697527371607793E-02 -8.2714549916601696E-02 -8.2731543636233709E-02 -8.2748508543132648E-02 -8.2765444649927356E-02 -8.2782351969246631E-02 -8.2799230513719305E-02 -8.2816080295974204E-02 -8.2832901328640143E-02 -8.2849693624345952E-02 -8.2866457195720444E-02 -8.2883192055392463E-02 -8.2899898215990822E-02 -8.2916575690144323E-02 -8.2933224490481822E-02 -8.2949844629632119E-02 -8.2966436120224057E-02 -8.2982998974886424E-02 -8.2999533206248088E-02 -8.3016038826937838E-02 -8.3032515849584515E-02 -8.3048964286816934E-02 -8.3065384151263924E-02 -8.3081775455554299E-02 -8.3098138212316888E-02 -8.3114472434180506E-02 -8.3130778133773994E-02 -8.3147055323726154E-02 -8.3163304016665815E-02 -8.3179524225221818E-02 -8.3195715962022965E-02 -8.3211879239698097E-02 -8.3228014070876002E-02 -8.3244120468185551E-02 -8.3260198444255529E-02 -8.3276248011714779E-02 -8.3292269183192116E-02 -8.3308261971316355E-02 -8.3324226388716338E-02 -8.3340162448020894E-02 -8.3356070161858808E-02 -8.3371949542858925E-02 -8.3387800603650086E-02 -8.3403623356861079E-02 -8.3419417815120758E-02 -8.3435183991057926E-02 -8.3450921897301411E-02 -8.3466631546480041E-02 -8.3482312951222645E-02 -8.3497966124158024E-02 -8.3513591077915020E-02 -8.3529187825122447E-02 -8.3544756378409121E-02 -8.3560296750403898E-02 -8.3575808953735564E-02 -8.3591293001032949E-02 -8.3606748904924894E-02 -8.3622176678040200E-02 -8.3637576333007710E-02 -8.3652947882456238E-02 -8.3668291339014600E-02 -8.3683606715311637E-02 -8.3698894023976150E-02 -8.3714153277636968E-02 -8.3729384488922934E-02 -8.3744587670462847E-02 -8.3759762834885537E-02 -8.3774909994819832E-02 -8.3790029162894547E-02 -8.3805120351738510E-02 -8.3820183573980550E-02 -8.3835218842249482E-02 -8.3850226169174119E-02 -8.3865205567383305E-02 -8.3880157049505855E-02 -8.3895080628170596E-02 -8.3909976316006329E-02 -8.3924844125641912E-02 -8.3939684069706130E-02 -8.3954496160827841E-02 -8.3969280411635858E-02 -8.3984036834758982E-02 -8.3998765442826057E-02 -8.4013466248465896E-02 -8.4028139264307342E-02 -8.4042784502979195E-02 -8.4057401977110285E-02 -8.4071991699329440E-02 -8.4086553682265475E-02 -8.4101087938547231E-02 -8.4115594480803496E-02 -8.4130073321663126E-02 -8.4144524473754936E-02 -8.4158947949707741E-02 -8.4173343762150368E-02 -8.4187711923711647E-02 -8.4202052447020379E-02 -8.4216365344705418E-02 -8.4230650629395568E-02 -8.4244908313719655E-02 -8.4259138410306494E-02 -8.4273340931784929E-02 -8.4287515890783760E-02 -8.4301663299931814E-02 -8.4315783171857936E-02 -8.4329875519190925E-02 -8.4343940354559624E-02 -8.4357977690592834E-02 -8.4371987539919382E-02 -8.4385969915168113E-02 -8.4399924828967826E-02 -8.4413852293947350E-02 -8.4427752322735514E-02 -8.4441624927961131E-02 -8.4455470122253046E-02 -8.4469287918240057E-02 -8.4483078328550981E-02 -8.4496841365814673E-02 -8.4510577042659935E-02 -8.4524285371715607E-02 -8.4537966365610479E-02 -8.4551620036973404E-02 -8.4565246398433200E-02 -8.4578845462618679E-02 -8.4592417242158671E-02 -8.4605961749681990E-02 -8.4619478997817479E-02 -8.4632968999193939E-02 -8.4646431766440211E-02 -8.4659867312185111E-02 -8.4673275649057467E-02 -8.4686656789686079E-02 -8.4700010746699805E-02 -8.4713337532727431E-02 -8.4726637160397814E-02 -8.4739909642339753E-02 -8.4753154991182092E-02 -8.4766373219553631E-02 -8.4779564340083213E-02 -8.4792728365399639E-02 -8.4805865308131750E-02 -8.4818975180908376E-02 -8.4832057996358318E-02 -8.4845113767110403E-02 -8.4858142505793474E-02 -8.4871144225036332E-02 -8.4884118937467806E-02 -8.4897066655716724E-02 -8.4909987392411901E-02 -8.4922881160182179E-02 -8.4935747971656358E-02 -8.4948587839463269E-02 -8.4961400776231738E-02 -8.4974186794590581E-02 -8.4986945907168640E-02 -8.4999678126594702E-02 -8.5012383465497637E-02 -8.5025061936506233E-02 -8.5037713552249303E-02 -8.5050338325355718E-02 -8.5062936268454264E-02 -8.5075507394173772E-02 -8.5088051715143068E-02 -8.5100569243990967E-02 -8.5113059993346299E-02 -8.5125523975837891E-02 -8.5137961204094545E-02 -8.5150371690745116E-02 -8.5162755448418406E-02 -8.5175112489743257E-02 -8.5187442827348456E-02 -8.5199746473862858E-02 -8.5212023441915280E-02 -8.5224273744134535E-02 -8.5236497393149452E-02 -8.5248694401588859E-02 -8.5260864782081558E-02 -8.5273008547256404E-02 -8.5285125709742199E-02 -8.5297216282167770E-02 -8.5309280277161947E-02 -8.5321317707353544E-02 -8.5333328585371376E-02 -8.5345312923844285E-02 -8.5357270735401086E-02 -8.5369202032670607E-02 -8.5381106828281664E-02 -8.5392985134863070E-02 -8.5404836965043668E-02 -8.5416662331452273E-02 -8.5428461246717713E-02 -8.5440233723468789E-02 -8.5451979774334358E-02 -8.5463699411943220E-02 -8.5475392648924203E-02 -8.5487059497906137E-02 -8.5498699971517836E-02 -8.5510314082388114E-02 -8.5521901843145814E-02 -8.5533463266419751E-02 -8.5544998364838754E-02 -8.5556507151031636E-02 -8.5567989637627212E-02 -8.5579445837254325E-02 -8.5590875762541790E-02 -8.5602279426118436E-02 -8.5613656840613062E-02 -8.5625008018654525E-02 -8.5636332972871626E-02 -8.5647631715893194E-02 -8.5658904260348057E-02 -8.5670150618865029E-02 -8.5681370804072926E-02 -8.5692564828600590E-02 -8.5703732705076835E-02 -8.5714874446130490E-02 -8.5725990064390370E-02 -8.5737079572485303E-02 -8.5748142983044104E-02 -8.5759180308695601E-02 -8.5770191562068623E-02 -8.5781176755791985E-02 -8.5792135902494515E-02 -8.5803069014805028E-02 -8.5813976105352352E-02 -8.5824857186765316E-02 -8.5835712271672734E-02 -8.5846541372703436E-02 -8.5857344502486235E-02 -8.5868121673649961E-02 -8.5878872898823441E-02 -8.5889598190635491E-02 -8.5900297561714939E-02 -8.5910971024690599E-02 -8.5921618592191301E-02 -8.5932240276845873E-02 -8.5942836091283142E-02 -8.5953406048131897E-02 -8.5963950160021008E-02 -8.5974468439579260E-02 -8.5984960899435511E-02 -8.5995427552218548E-02 -8.6005868410557212E-02 -8.6016283487080319E-02 -8.6026672794416711E-02 -8.6037036345195189E-02 -8.6047374152044581E-02 -8.6057686227593730E-02 -8.6067972584471422E-02 -8.6078233235306514E-02 -8.6088468192727807E-02 -8.6098677469364143E-02 -8.6108861077844323E-02 -8.6119019030797189E-02 -8.6129151340851556E-02 -8.6139258020636239E-02 -8.6149339082780066E-02 -8.6159394539911879E-02 -8.6169424404660480E-02 -8.6179428689654697E-02 -8.6189407407523344E-02 -8.6199360570895264E-02 -8.6209288192399272E-02 -8.6219190284664168E-02 -8.6229066860318809E-02 -8.6238917931992010E-02 -8.6248743512312584E-02 -8.6258543613909361E-02 -8.6268318249411155E-02 -8.6278067431446795E-02 -8.6287791172645109E-02 -8.6297489485634912E-02 -8.6307162383045033E-02 -8.6316809877504286E-02 -8.6326431981641499E-02 -8.6336028708085502E-02 -8.6345600069465123E-02 -8.6355146078409162E-02 -8.6364666747546448E-02 -8.6374162089505824E-02 -8.6383632116916090E-02 -8.6393076842406075E-02 -8.6402496278604621E-02 -8.6411890438140515E-02 -8.6421259333642614E-02 -8.6430602977739718E-02 -8.6439921383060669E-02 -8.6449214562234269E-02 -8.6458482527889360E-02 -8.6467725292654757E-02 -8.6476942869159287E-02 -8.6486135270031753E-02 -8.6495302507901009E-02 -8.6504444595395857E-02 -8.6513561545145126E-02 -8.6522653369777644E-02 -8.6531720081922225E-02 -8.6540761694207699E-02 -8.6549778219262880E-02 -8.6558769669716595E-02 -8.6567736058197675E-02 -8.6576677397334934E-02 -8.6585593699757199E-02 -8.6594484978093300E-02 -8.6603351244972052E-02 -8.6612192513022268E-02 -8.6621008794872778E-02 -8.6629800103152410E-02 -8.6638566450489993E-02 -8.6647307849514341E-02 -8.6656024312854268E-02 -8.6664715853138619E-02 -8.6673382482996206E-02 -8.6682024215055831E-02 -8.6690641061946364E-02 -8.6699233036296577E-02 -8.6707800150735329E-02 -8.6716342417891432E-02 -8.6724859850393701E-02 -8.6733352460870980E-02 -8.6741820261952068E-02 -8.6750263266265781E-02 -8.6758681486440989E-02 -8.6767074935106464E-02 -8.6775443624891063E-02 -8.6783787568423587E-02 -8.6792106778332864E-02 -8.6800401267247737E-02 -8.6808671047796993E-02 -8.6816916132609487E-02 -8.6825136534314035E-02 -8.6833332265539451E-02 -8.6841503338914550E-02 -8.6849649767068174E-02 -8.6857771562629138E-02 -8.6865868738226271E-02 -8.6873941306488386E-02 -8.6881989280044314E-02 -8.6890012671522882E-02 -8.6898011493552890E-02 -8.6905985758763182E-02 -8.6913935479782573E-02 -8.6921860669239903E-02 -8.6929761339763961E-02 -8.6937637503983603E-02 -8.6945489174527629E-02 -8.6953316364024882E-02 -8.6961119085104163E-02 -8.6968897350394314E-02 -8.6976651172524150E-02 -8.6984380564122499E-02 -8.6992085537818176E-02 -8.6999766106240009E-02 -8.7007422282016814E-02 -8.7015054077777432E-02 -8.7022661506150664E-02 -8.7030244579765340E-02 -8.7037803311250286E-02 -8.7045337713234333E-02 -8.7052847798346294E-02 -8.7060333579214985E-02 -8.7067795068469234E-02 -8.7075232278737882E-02 -8.7082645222649732E-02 -8.7090033912833612E-02 -8.7097398361918349E-02 -8.7104738582532759E-02 -8.7112054587305671E-02 -8.7119346388865898E-02 -8.7126613999842284E-02 -8.7133857432863629E-02 -8.7141076700558762E-02 -8.7148271815556511E-02 -8.7155442790485704E-02 -8.7162589637975157E-02 -8.7169712370653685E-02 -8.7176811001150128E-02 -8.7183885542093303E-02 -8.7190936006112024E-02 -8.7197962405835119E-02 -8.7204964753891417E-02 -8.7211943062909733E-02 -8.7218897345518895E-02 -8.7225827614347717E-02 -8.7232733882025043E-02 -8.7239616161179673E-02 -8.7246474464440449E-02 -8.7253308804436172E-02 -8.7260119193795685E-02 -8.7266905645147802E-02 -8.7273668171121352E-02 -8.7280406784345135E-02 -8.7287121497448009E-02 -8.7293812323058786E-02 -8.7300479273806270E-02 -8.7307122362319300E-02 -8.7313741601226694E-02 -8.7320337003157292E-02 -8.7326908580739881E-02 -8.7333456346603319E-02 -8.7339980313376420E-02 -8.7346480493687984E-02 -8.7352956900166867E-02 -8.7359409545441871E-02 -8.7365838442141824E-02 -8.7372243602895555E-02 -8.7378625040331892E-02 -8.7384982767079636E-02 -8.7391316795767615E-02 -8.7397627139024672E-02 -8.7403913809479608E-02 -8.7410176819761265E-02 -8.7416416182498458E-02 -8.7422631910320001E-02 -8.7428824015854723E-02 -8.7434992511731452E-02 -8.7441137410579003E-02 -8.7447258725026206E-02 -8.7453356467701873E-02 -8.7459430651234848E-02 -8.7465481288253932E-02 -8.7471508391387967E-02 -8.7477511973265754E-02 -8.7483492046516134E-02 -8.7489448623767924E-02 -8.7495381717649950E-02 -8.7501291340791029E-02 -8.7507177505819989E-02 -8.7513040225365657E-02 -8.7518879512056835E-02 -8.7524695378522366E-02 -8.7530487837391077E-02 -8.7536256901291770E-02 -8.7542002582853287E-02 -8.7547724894704443E-02 -8.7553423849474066E-02 -8.7559099459790971E-02 -8.7564751738283986E-02 -8.7570380697581940E-02 -8.7575986350313634E-02 -8.7581568709107910E-02 -8.7587127786593597E-02 -8.7592663595399495E-02 -8.7598176148154461E-02 -8.7603665457487281E-02 -8.7609131536026785E-02 -8.7614574396401829E-02 -8.7619994051241185E-02 -8.7625390513173723E-02 -8.7630763794828231E-02 -8.7636113908833566E-02 -8.7641440867818513E-02 -8.7646744684411929E-02 -8.7652025371242615E-02 -8.7657282940939399E-02 -8.7662517406131110E-02 -8.7667728779446563E-02 -8.7672917073514586E-02 -8.7678082300964008E-02 -8.7683224474423643E-02 -8.7688343606522307E-02 -8.7693439709888840E-02 -8.7698512797152045E-02 -8.7703562880940764E-02 -8.7708589973883824E-02 -8.7713594088610028E-02 -8.7718575237748203E-02 -8.7723533433927178E-02 -8.7728468689775782E-02 -8.7733381017922829E-02 -8.7738270430997134E-02 -8.7743136941627539E-02 -8.7747980562442859E-02 -8.7752801306071909E-02 -8.7757599185143517E-02 -8.7762374212286526E-02 -8.7767126400129722E-02 -8.7771855761301948E-02 -8.7776562308432032E-02 -8.7781246054148790E-02 -8.7785907011081049E-02 -8.7790545191857625E-02 -8.7795160609107345E-02 -8.7799753275459025E-02 -8.7804323203541507E-02 -8.7808870405983591E-02 -8.7813394895414121E-02 -8.7817896684461896E-02 -8.7822375785755774E-02 -8.7826832211924541E-02 -8.7831265975597039E-02 -8.7835677089402084E-02 -8.7840065565968503E-02 -8.7844431417925126E-02 -8.7848774657900752E-02 -8.7853095298524239E-02 -8.7857393352424387E-02 -8.7861668832230025E-02 -8.7865921750569967E-02 -8.7870152120073042E-02 -8.7874359953368092E-02 -8.7878545263083904E-02 -8.7882708061849335E-02 -8.7886848362293185E-02 -8.7890966177044283E-02 -8.7895061518731443E-02 -8.7899134399983522E-02 -8.7903184833429307E-02 -8.7907212831697626E-02 -8.7911218407417321E-02 -8.7915201573217194E-02 -8.7919162341726087E-02 -8.7923100725572814E-02 -8.7927016737386191E-02 -8.7930910389795058E-02 -8.7934781695428219E-02 -8.7938630666914500E-02 -8.7942457316882744E-02 -8.7946261657961752E-02 -8.7950043702780353E-02 -8.7953803463967375E-02 -8.7957540954151633E-02 -8.7961256185961956E-02 -8.7964949172027157E-02 -8.7968619924976080E-02 -8.7972268457437539E-02 -8.7975894782040348E-02 -8.7979498911413323E-02 -8.7983080858185320E-02 -8.7986640634985125E-02 -8.7990178254441581E-02 -8.7993693729183517E-02 -8.7997187071839733E-02 -8.8000658295039072E-02 -8.8004107411410348E-02 -8.8007534433582391E-02 -8.8010939374184027E-02 -8.8014322245844059E-02 -8.8017683061191315E-02 -8.8021021832854637E-02 -8.8024338573462840E-02 -8.8027633295644739E-02 -8.8030906012029161E-02 -8.8034156735244923E-02 -8.8037385477920865E-02 -8.8040592252685790E-02 -8.8043777072168539E-02 -8.8046939948997927E-02 -8.8050080895802768E-02 -8.8053199925211892E-02 -8.8056297049854126E-02 -8.8059372282358300E-02 -8.8062425635353214E-02 -8.8065457121467711E-02 -8.8068466753330604E-02 -8.8071454543570724E-02 -8.8074420504816883E-02 -8.8077364649697912E-02 -8.8080286990842638E-02 -8.8083187540879876E-02 -8.8086066312438441E-02 -8.8088923318147175E-02 -8.8091758570634893E-02 -8.8094572082530409E-02 -8.8097363866462566E-02 -8.8100133935060165E-02 -8.8102882300952048E-02 -8.8105608976767030E-02 -8.8108313975133926E-02 -8.8110997308681563E-02 -8.8113658990038785E-02 -8.8116299031834378E-02 -8.8118917446697184E-02 -8.8121514247256033E-02 -8.8124089446139753E-02 -8.8126643055977130E-02 -8.8129175089397035E-02 -8.8131685559028256E-02 -8.8134174477499633E-02 -8.8136641857439982E-02 -8.8139087711478131E-02 -8.8141512052242882E-02 -8.8143914892363090E-02 -8.8146296244467570E-02 -8.8148656121185137E-02 -8.8150994535144606E-02 -8.8153311498974818E-02 -8.8155607025304589E-02 -8.8157881126762733E-02 -8.8160133815978092E-02 -8.8162365105579482E-02 -8.8164575008195703E-02 -8.8166763536455611E-02 -8.8168930702988008E-02 -8.8171076520421734E-02 -8.8173201001385593E-02 -8.8175304158508411E-02 -8.8177386004419031E-02 -8.8179446551746254E-02 -8.8181485813118909E-02 -8.8183503801165825E-02 -8.8185500528515828E-02 -8.8187476007797722E-02 -8.8189430251640347E-02 -8.8191363272672518E-02 -8.8193275083523065E-02 -8.8195165696820801E-02 -8.8197035125194556E-02 -8.8198883381273158E-02 -8.8200710477685421E-02 -8.8202516427060174E-02 -8.8204301242026231E-02 -8.8206064935212422E-02 -8.8207807519247575E-02 -8.8209529006760490E-02 -8.8211229410380024E-02 -8.8212908742734977E-02 -8.8214567016454179E-02 -8.8216204244166457E-02 -8.8217820438500613E-02 -8.8219415612085503E-02 -8.8220989777549913E-02 -8.8222542947522700E-02 -8.8224075134632679E-02 -8.8225586351508650E-02 -8.8227076610779470E-02 -8.8228545925073926E-02 -8.8229994307020873E-02 -8.8231421769249127E-02 -8.8232828324387488E-02 -8.8234213985064799E-02 -8.8235578763909889E-02 -8.8236922673551571E-02 -8.8238245726618661E-02 -8.8239547935739987E-02 -8.8240829313544378E-02 -8.8242089872660662E-02 -8.8243329625717654E-02 -8.8244548585344168E-02 -8.8245746764169034E-02 -8.8246924174821079E-02 -8.8248080829929132E-02 -8.8249216742121994E-02 -8.8250331924028508E-02 -8.8251426388277487E-02 -8.8252500147497775E-02 -8.8253553214318159E-02 -8.8254585601367480E-02 -8.8255597321274581E-02 -8.8256588386668250E-02 -8.8257558810177328E-02 -8.8258508604430630E-02 -8.8259437782056999E-02 -8.8260346355685221E-02 -8.8261234337944167E-02 -8.8262101741462623E-02 -8.8262948578869418E-02 -8.8263774862793382E-02 -8.8264580605863341E-02 -8.8265365820708111E-02 -8.8266130519956520E-02 -8.8266874716237398E-02 -8.8267598422179544E-02 -8.8268301650411801E-02 -8.8268984413562984E-02 -8.8269646724261921E-02 -8.8270288595137428E-02 -8.8270910038818332E-02 -8.8271511067933461E-02 -8.8272091695111632E-02 -8.8272651932981672E-02 -8.8273191794172395E-02 -8.8273711291312645E-02 -8.8274210437031222E-02 -8.8274689243956955E-02 -8.8275147724718672E-02 -8.8275585891945188E-02 -8.8276003758265331E-02 -8.8276401336307930E-02 -8.8276778638701800E-02 -8.8277135678075769E-02 -8.8277472467058651E-02 -8.8277789018279290E-02 -8.8278085344366486E-02 -8.8278361457949067E-02 -8.8278617371655863E-02 -8.8278853098115687E-02 -8.8279068649957368E-02 -8.8279264039809735E-02 -8.8279439280301603E-02 -8.8279594384061799E-02 -8.8279729363719153E-02 -8.8279844231902466E-02 -8.8279939001240579E-02 -8.8280013684362307E-02 -8.8280068293896480E-02 -8.8280102842471911E-02 -8.8280117342717443E-02 -8.8280111807261877E-02 -8.8280086248734041E-02 -8.8280040679762764E-02 -8.8279975112976861E-02 -8.8279889561005173E-02 -8.8279784036476502E-02 -8.8279658552019677E-02 -8.8279513120263525E-02 -8.8279347753836876E-02 -8.8279162465368530E-02 -8.8278957267487329E-02 -8.8278732172822102E-02 -8.8278487194001651E-02 -8.8278222343654802E-02 -8.8277937634410400E-02 -8.8277633078897244E-02 -8.8277308689744177E-02 -8.8276964479580000E-02 -8.8276600461033541E-02 -8.8276216646733643E-02 -8.8275813049309121E-02 -8.8275389681388775E-02 -8.8274946555601447E-02 -8.8274483684575966E-02 -8.8274001080941147E-02 -8.8273498757325805E-02 -8.8272976726358782E-02 -8.8272435000668878E-02 -8.8271873592884936E-02 -8.8271292515635771E-02 -8.8270691781550198E-02 -8.8270071403257058E-02 -8.8269431393385167E-02 -8.8268771764563325E-02 -8.8268092529420389E-02 -8.8267393700585173E-02 -8.8266675290686492E-02 -8.8265937312353174E-02 -8.8265179778214034E-02 -8.8264402700897901E-02 -8.8263606093033589E-02 -8.8262789967249955E-02 -8.8261954336175771E-02 -8.8261099212439909E-02 -8.8260224608671153E-02 -8.8259330537498348E-02 -8.8258417011550308E-02 -8.8257484043455847E-02 -8.8256531645843822E-02 -8.8255559831343020E-02 -8.8254568612582282E-02 -8.8253558002190424E-02 -8.8252528012796289E-02 -8.8251478657028662E-02 -8.8250409947516401E-02 -8.8249321896888305E-02 -8.8248214517773205E-02 -8.8247087822799941E-02 -8.8245941824597302E-02 -8.8244776535794142E-02 -8.8243591969019264E-02 -8.8242388136901509E-02 -8.8241165052069678E-02 -8.8239922727152614E-02 -8.8238661174779132E-02 -8.8237380407578059E-02 -8.8236080438178197E-02 -8.8234761279208401E-02 -8.8233422943297474E-02 -8.8232065443074242E-02 -8.8230688791167536E-02 -8.8229293000206169E-02 -8.8227878082818956E-02 -8.8226444051634753E-02 -8.8224990919282348E-02 -8.8223518698390582E-02 -8.8222027401588271E-02 -8.8220517041504243E-02 -8.8218987630767326E-02 -8.8217439182006321E-02 -8.8215871707850071E-02 -8.8214285220927391E-02 -8.8212679733867122E-02 -8.8211055259298052E-02 -8.8209411809849037E-02 -8.8207749398148877E-02 -8.8206068036826416E-02 -8.8204367738510453E-02 -8.8202648515829832E-02 -8.8200910381413367E-02 -8.8199153347889886E-02 -8.8197377427888204E-02 -8.8195582634037137E-02 -8.8193768978965525E-02 -8.8191936475302199E-02 -8.8190085135675944E-02 -8.8188214972715617E-02 -8.8186325999050047E-02 -8.8184418227308020E-02 -8.8182491670118379E-02 -8.8180546340109953E-02 -8.8178582249911569E-02 -8.8176599412152029E-02 -8.8174597839460161E-02 -8.8172577544464809E-02 -8.8170538539794785E-02 -8.8168480838078891E-02 -8.8166404451945984E-02 -8.8164309394024865E-02 -8.8162195676944347E-02 -8.8160063313333287E-02 -8.8157912315820486E-02 -8.8155742697034772E-02 -8.8153554469604961E-02 -8.8151347646159881E-02 -8.8149122239328359E-02 -8.8146878261739212E-02 -8.8144615726021266E-02 -8.8142334644803352E-02 -8.8140035030714270E-02 -8.8137716896382862E-02 -8.8135380254437956E-02 -8.8133025117508354E-02 -8.8130651498222898E-02 -8.8128259409210402E-02 -8.8125848863099682E-02 -8.8123419872519579E-02 -8.8120972450098894E-02 -8.8118506608466485E-02 -8.8116022360251137E-02 -8.8113519718081693E-02 -8.8110998694586967E-02 -8.8108459302395789E-02 -8.8105901554136973E-02 -8.8103325462439347E-02 -8.8100731039931754E-02 -8.8098118299242981E-02 -8.8095487253001870E-02 -8.8092837913837249E-02 -8.8090170294377934E-02 -8.8087484407252739E-02 -8.8084780265090507E-02 -8.8082057880520051E-02 -8.8079317266170187E-02 -8.8076558434669744E-02 -8.8073781398647549E-02 -8.8070986170732418E-02 -8.8068172763553179E-02 -8.8065341189738647E-02 -8.8062491461917664E-02 -8.8059623592719030E-02 -8.8056737594771575E-02 -8.8053833480704141E-02 -8.8050911263145515E-02 -8.8047970954724553E-02 -8.8045012568070069E-02 -8.8042036115810879E-02 -8.8039041610575797E-02 -8.8036029064993665E-02 -8.8032998491693312E-02 -8.8029949903303539E-02 -8.8026883312453175E-02 -8.8023798731771047E-02 -8.8020696173885971E-02 -8.8017575651426788E-02 -8.8014437177022314E-02 -8.8011280763301350E-02 -8.8008106422892737E-02 -8.8004914168425305E-02 -8.8001704012527868E-02 -8.7998475967829254E-02 -8.7995230046958278E-02 -8.7991966262543769E-02 -8.7988684627214542E-02 -8.7985385153599438E-02 -8.7982067854327259E-02 -8.7978732742026833E-02 -8.7975379829326988E-02 -8.7972009128856554E-02 -8.7968620653244345E-02 -8.7965214415119189E-02 -8.7961790427109887E-02 -8.7958348701845296E-02 -8.7954889251954216E-02 -8.7951412090065489E-02 -8.7947917228807904E-02 -8.7944404680810329E-02 -8.7940874458701551E-02 -8.7937326575110414E-02 -8.7933761042665717E-02 -8.7930177873996318E-02 -8.7926577081731003E-02 -8.7922958678498628E-02 -8.7919322676927994E-02 -8.7915669089647930E-02 -8.7911997929287264E-02 -8.7908309208474811E-02 -8.7904602939839399E-02 -8.7900879136009857E-02 -8.7897137809614986E-02 -8.7893378973283642E-02 -8.7889602639644612E-02 -8.7885808821326752E-02 -8.7881997530958864E-02 -8.7878168781169774E-02 -8.7874322584588313E-02 -8.7870458953843295E-02 -8.7866577901563547E-02 -8.7862679440377886E-02 -8.7858763582915153E-02 -8.7854830341804149E-02 -8.7850879729673717E-02 -8.7846911759152657E-02 -8.7842926442869812E-02 -8.7838923793453996E-02 -8.7834903823534038E-02 -8.7830866545738753E-02 -8.7826811972696969E-02 -8.7822740117037501E-02 -8.7818650991389191E-02 -8.7814544608380840E-02 -8.7810420980641291E-02 -8.7806280120799343E-02 -8.7802122041483840E-02 -8.7797946755323597E-02 -8.7793754274947441E-02 -8.7789544612984188E-02 -8.7785317782062666E-02 -8.7781073794811690E-02 -8.7776812663860102E-02 -8.7772534401836702E-02 -8.7768239021370334E-02 -8.7763926535089798E-02 -8.7759596955623936E-02 -8.7755250295601578E-02 -8.7750886567651509E-02 -8.7746505784402601E-02 -8.7742107958483639E-02 -8.7737693102523454E-02 -8.7733261229150886E-02 -8.7728812350994737E-02 -8.7724346480683849E-02 -8.7719863630847023E-02 -8.7715363814113115E-02 -8.7710847043110912E-02 -8.7706313330469257E-02 -8.7701762688816964E-02 -8.7697195130782862E-02 -8.7692610668995780E-02 -8.7688009316084517E-02 -8.7683391084677931E-02 -8.7678755987404822E-02 -8.7674104036894018E-02 -8.7669435245774335E-02 -8.7664749626674601E-02 -8.7660047192223645E-02 -8.7655327955050294E-02 -8.7650591927783350E-02 -8.7645839123051655E-02 -8.7641069553484025E-02 -8.7636283231709272E-02 -8.7631480170356241E-02 -8.7626660382053745E-02 -8.7621823879430599E-02 -8.7616970675115646E-02 -8.7612100781737687E-02 -8.7607214211925563E-02 -8.7602310978308076E-02 -8.7597391093514068E-02 -8.7592454570172354E-02 -8.7587501420911762E-02 -8.7582531658361107E-02 -8.7577545295149217E-02 -8.7572542343904922E-02 -8.7567522817257035E-02 -8.7562486727834371E-02 -8.7557434088265773E-02 -8.7552364911180056E-02 -8.7547279209206033E-02 -8.7542176994972534E-02 -8.7537058281108401E-02 -8.7531923080242421E-02 -8.7526771405003437E-02 -8.7521603268020276E-02 -8.7516418681921754E-02 -8.7511217659336699E-02 -8.7506000212893925E-02 -8.7500766355222262E-02 -8.7495516098950524E-02 -8.7490249456707553E-02 -8.7484966441122150E-02 -8.7479667064823158E-02 -8.7474351340439391E-02 -8.7469019280599664E-02 -8.7463670897932805E-02 -8.7458306205067643E-02 -8.7452925214633007E-02 -8.7447527939257697E-02 -8.7442114391570555E-02 -8.7436684584200397E-02 -8.7431238529776051E-02 -8.7425776240926317E-02 -8.7420297730280067E-02 -8.7414803010466072E-02 -8.7409292094113189E-02 -8.7403764993850219E-02 -8.7398221722306005E-02 -8.7392662292109347E-02 -8.7387086715889101E-02 -8.7381495006274054E-02 -8.7375887175893049E-02 -8.7370263237374901E-02 -8.7364623203348452E-02 -8.7358967086442502E-02 -8.7353294899285880E-02 -8.7347606654507401E-02 -8.7341902364735921E-02 -8.7336182042600227E-02 -8.7330445700729148E-02 -8.7324693351751526E-02 -8.7318925008296175E-02 -8.7313140682991897E-02 -8.7307340388467547E-02 -8.7301524137351927E-02 -8.7295691942273879E-02 -8.7289843815862203E-02 -8.7283979770745729E-02 -8.7278099819553298E-02 -8.7272203974913712E-02 -8.7266292249455799E-02 -8.7260364655808387E-02 -8.7254421206600305E-02 -8.7248461914460354E-02 -8.7242486792017362E-02 -8.7236495851900187E-02 -8.7230489106737599E-02 -8.7224466569158457E-02 -8.7218428251791574E-02 -8.7212374167265780E-02 -8.7206304328209874E-02 -8.7200218747252714E-02 -8.7194117437023100E-02 -8.7188000410149846E-02 -8.7181867679261810E-02 -8.7175719256987777E-02 -8.7169555155956591E-02 -8.7163375388797079E-02 -8.7157179968138043E-02 -8.7150968906608325E-02 -8.7144742216836740E-02 -8.7138499911452116E-02 -8.7132242003083282E-02 -8.7125968504359039E-02 -8.7119679427908228E-02 -8.7113374786359665E-02 -8.7107054592342179E-02 -8.7100718858484583E-02 -8.7094367597415706E-02 -8.7088000821764364E-02 -8.7081618544159398E-02 -8.7075220777229623E-02 -8.7068807533603854E-02 -8.7062378825910919E-02 -8.7055934666779633E-02 -8.7049475068838825E-02 -8.7043000044717336E-02 -8.7036509607043955E-02 -8.7030003768447536E-02 -8.7023482541556896E-02 -8.7016945939000834E-02 -8.7010393973408193E-02 -8.7003826657407787E-02 -8.6997244003628460E-02 -8.6990646024699012E-02 -8.6984032733248270E-02 -8.6977404141905065E-02 -8.6970760263298211E-02 -8.6964101110056549E-02 -8.6957426694808881E-02 -8.6950737030184036E-02 -8.6944032128810828E-02 -8.6937312003318112E-02 -8.6930576666334677E-02 -8.6923826130489351E-02 -8.6917060408410990E-02 -8.6910279512728367E-02 -8.6903483456070338E-02 -8.6896672251065718E-02 -8.6889845910343336E-02 -8.6883004446531992E-02 -8.6876147872260542E-02 -8.6869276200157788E-02 -8.6862389442852558E-02 -8.6855487612973667E-02 -8.6848570723149957E-02 -8.6841638786010228E-02 -8.6834691814183323E-02 -8.6827729820298044E-02 -8.6820752816983246E-02 -8.6813760816867716E-02 -8.6806753832580311E-02 -8.6799731876749817E-02 -8.6792694962005090E-02 -8.6785643100974932E-02 -8.6778576306288172E-02 -8.6771494590573650E-02 -8.6764397966460155E-02 -8.6757286446576543E-02 -8.6750160043551613E-02 -8.6743018770014196E-02 -8.6735862638593120E-02 -8.6728691661917198E-02 -8.6721505852615274E-02 -8.6714305223316149E-02 -8.6707089786648650E-02 -8.6699859555241607E-02 -8.6692614541723834E-02 -8.6685354758724173E-02 -8.6678080218871412E-02 -8.6670790934794406E-02 -8.6663486919121971E-02 -8.6656168184482935E-02 -8.6648834743506098E-02 -8.6641486608820303E-02 -8.6634123793054366E-02 -8.6626746308837113E-02 -8.6619354168797361E-02 -8.6611947385563937E-02 -8.6604525971765670E-02 -8.6597089940031360E-02 -8.6589639302989865E-02 -8.6582174073269985E-02 -8.6574694263500562E-02 -8.6567199886310384E-02 -8.6559690954328306E-02 -8.6552167480183143E-02 -8.6544629476503709E-02 -8.6537076955918835E-02 -8.6529509931057347E-02 -8.6521928414548060E-02 -8.6514332419019790E-02 -8.6506721957101379E-02 -8.6499097041421641E-02 -8.6491457684609405E-02 -8.6483803899293485E-02 -8.6476135698102696E-02 -8.6468453093665881E-02 -8.6460756098611855E-02 -8.6453044725569445E-02 -8.6445318987167466E-02 -8.6437578896034734E-02 -8.6429824464800090E-02 -8.6422055706092349E-02 -8.6414272632540340E-02 -8.6406475256772863E-02 -8.6398663591418776E-02 -8.6390837649106877E-02 -8.6382997442465997E-02 -8.6375142984124964E-02 -8.6367274286712592E-02 -8.6359391362857696E-02 -8.6351494225189118E-02 -8.6343582886335674E-02 -8.6335657358926177E-02 -8.6327717655589470E-02 -8.6319763788954368E-02 -8.6311795771649685E-02 -8.6303813616304251E-02 -8.6295817335546893E-02 -8.6287806942006412E-02 -8.6279782448311665E-02 -8.6271743867091452E-02 -8.6263691210974602E-02 -8.6255624492589944E-02 -8.6247543724566278E-02 -8.6239448919532460E-02 -8.6231340090117292E-02 -8.6223217248949602E-02 -8.6215080408658218E-02 -8.6206929581871955E-02 -8.6198764781219642E-02 -8.6190586019330093E-02 -8.6182393308832136E-02 -8.6174186662354602E-02 -8.6165966092526289E-02 -8.6157731611976054E-02 -8.6149483233332699E-02 -8.6141220969225066E-02 -8.6132944832281941E-02 -8.6124654835132181E-02 -8.6116350990404600E-02 -8.6108033310728013E-02 -8.6099701808731263E-02 -8.6091356497043137E-02 -8.6082997388292490E-02 -8.6074624495108137E-02 -8.6066237830118908E-02 -8.6057837405953602E-02 -8.6049423235241063E-02 -8.6040995330610104E-02 -8.6032553704689554E-02 -8.6024098370108229E-02 -8.6015629339494970E-02 -8.6007146625478578E-02 -8.5998650240687882E-02 -8.5990140197751710E-02 -8.5981616509298892E-02 -8.5973079187958226E-02 -8.5964528246358557E-02 -8.5955963697128712E-02 -8.5947385552897493E-02 -8.5938793826293727E-02 -8.5930188529946258E-02 -8.5921569676483886E-02 -8.5912937278535453E-02 -8.5904291348729761E-02 -8.5895631899695651E-02 -8.5886958944061925E-02 -8.5878272494457439E-02 -8.5869572563510979E-02 -8.5860859163851402E-02 -8.5852132308107509E-02 -8.5843392008908115E-02 -8.5834638278882075E-02 -8.5825871130658191E-02 -8.5817090576865276E-02 -8.5808296630132175E-02 -8.5799489303087700E-02 -8.5790668608360682E-02 -8.5781834558579934E-02 -8.5772987166374270E-02 -8.5764126444372535E-02 -8.5755252405203555E-02 -8.5746365061496119E-02 -8.5737464425879081E-02 -8.5728550510981258E-02 -8.5719623329431477E-02 -8.5710682893858539E-02 -8.5701729216891287E-02 -8.5692762311158535E-02 -8.5683782189289112E-02 -8.5674788863911847E-02 -8.5665782347655539E-02 -8.5656762653149032E-02 -8.5647729793021141E-02 -8.5638683779900693E-02 -8.5629624626416517E-02 -8.5620552345197429E-02 -8.5611466948872242E-02 -8.5602368450069799E-02 -8.5593256861418901E-02 -8.5584132195548390E-02 -8.5574994465087081E-02 -8.5565843682663789E-02 -8.5556679860907356E-02 -8.5547503012446596E-02 -8.5538313149910325E-02 -8.5529110285927371E-02 -8.5519894433126548E-02 -8.5510665604136699E-02 -8.5501423811586638E-02 -8.5492169068105181E-02 -8.5482901386321170E-02 -8.5473620778863404E-02 -8.5464327258360714E-02 -8.5455020837441928E-02 -8.5445701528735860E-02 -8.5436369344871352E-02 -8.5427024298477205E-02 -8.5417666402182249E-02 -8.5408295668615311E-02 -8.5398912110405220E-02 -8.5389515740180791E-02 -8.5380106570570838E-02 -8.5370684614204204E-02 -8.5361249883709689E-02 -8.5351802391716136E-02 -8.5342342150852360E-02 -8.5332869173747189E-02 -8.5323383473029438E-02 -8.5313885061327935E-02 -8.5304373951271495E-02 -8.5294850155488947E-02 -8.5285313686609118E-02 -8.5275764557260825E-02 -8.5266202780072894E-02 -8.5256628367674142E-02 -8.5247041332693410E-02 -8.5237441687759499E-02 -8.5227829445501252E-02 -8.5218204618547469E-02 -8.5208567219526979E-02 -8.5198917261068624E-02 -8.5189254755801205E-02 -8.5179579716353565E-02 -8.5169892155354518E-02 -8.5160192085432879E-02 -8.5150479519217476E-02 -8.5140754469337138E-02 -8.5131016948420679E-02 -8.5121266969096915E-02 -8.5111504543994701E-02 -8.5101729685742825E-02 -8.5091942406970128E-02 -8.5082142720305426E-02 -8.5072330638377561E-02 -8.5062506173815319E-02 -8.5052669339247558E-02 -8.5042820147303078E-02 -8.5032958610610707E-02 -8.5023084741799287E-02 -8.5013198553497621E-02 -8.5003300058334536E-02 -8.4993389268938860E-02 -8.4983466197939408E-02 -8.4973530857964996E-02 -8.4963583261644465E-02 -8.4953623421606644E-02 -8.4943651350480334E-02 -8.4933667060894363E-02 -8.4923670565477560E-02 -8.4913661876858754E-02 -8.4903641007666744E-02 -8.4893607970530388E-02 -8.4883562778078486E-02 -8.4873505442939839E-02 -8.4863435977743332E-02 -8.4853354395117736E-02 -8.4843260707691881E-02 -8.4833154928094609E-02 -8.4823037068954735E-02 -8.4812907142901073E-02 -8.4802765162562466E-02 -8.4792611140567714E-02 -8.4782445089545647E-02 -8.4772267022125092E-02 -8.4762076950934878E-02 -8.4751874888603820E-02 -8.4741660847760733E-02 -8.4731434841034459E-02 -8.4721196881053798E-02 -8.4710946980447593E-02 -8.4700685151844660E-02 -8.4690411407873825E-02 -8.4680125761163905E-02 -8.4669828224343727E-02 -8.4659518810042106E-02 -8.4649197530887885E-02 -8.4638864399509864E-02 -8.4628519428536886E-02 -8.4618162630597751E-02 -8.4607794018321303E-02 -8.4597413604336341E-02 -8.4587021401271723E-02 -8.4576617421756248E-02 -8.4566201678418745E-02 -8.4555774183888030E-02 -8.4545334950792930E-02 -8.4534883991762275E-02 -8.4524421319424878E-02 -8.4513946946409582E-02 -8.4503460885345175E-02 -8.4492963148860512E-02 -8.4482453749584394E-02 -8.4471932700145663E-02 -8.4461400013173135E-02 -8.4450855701295624E-02 -8.4440299777141958E-02 -8.4429732253340967E-02 -8.4419153142521464E-02 -8.4408562457312278E-02 -8.4397960210342238E-02 -8.4387346414240144E-02 -8.4376721081634840E-02 -8.4366084225155152E-02 -8.4355435857429883E-02 -8.4344775991087875E-02 -8.4334104638757942E-02 -8.4323421813068913E-02 -8.4312727526649603E-02 -8.4302021792128840E-02 -8.4291304622135438E-02 -8.4280576029298240E-02 -8.4269836026246048E-02 -8.4259084625607703E-02 -8.4248321840012005E-02 -8.4237547682087799E-02 -8.4226762164463898E-02 -8.4215965299769130E-02 -8.4205157100632311E-02 -8.4194337579682255E-02 -8.4183506749547818E-02 -8.4172664622857787E-02 -8.4161811212241006E-02 -8.4150946530326301E-02 -8.4140070589742474E-02 -8.4129183403118368E-02 -8.4118284983082797E-02 -8.4107375342264590E-02 -8.4096454493292561E-02 -8.4085522448795538E-02 -8.4074579221402337E-02 -8.4063624823741787E-02 -8.4052659268442728E-02 -8.4041682568133949E-02 -8.4030694735444292E-02 -8.4019695783002585E-02 -8.4008685723437643E-02 -8.3997664569378294E-02 -8.3986632333453354E-02 -8.3975589028291650E-02 -8.3964534666521998E-02 -8.3953469260773239E-02 -8.3942392823674175E-02 -8.3931305367853634E-02 -8.3920206905940459E-02 -8.3909097450563450E-02 -8.3897977014351435E-02 -8.3886845609933230E-02 -8.3875703249937691E-02 -8.3864549946993605E-02 -8.3853385713729800E-02 -8.3842210562775119E-02 -8.3831024506758361E-02 -8.3819827558308371E-02 -8.3808619730053949E-02 -8.3797401034623936E-02 -8.3786171484647148E-02 -8.3774931092752414E-02 -8.3763679871568547E-02 -8.3752417833724377E-02 -8.3741144991848732E-02 -8.3729861358570426E-02 -8.3718566946518275E-02 -8.3707261768321120E-02 -8.3695945836607777E-02 -8.3684619164007060E-02 -8.3673281763147797E-02 -8.3661933646658818E-02 -8.3650574827168936E-02 -8.3639205317306994E-02 -8.3627825129701780E-02 -8.3616434276982149E-02 -8.3605032771776916E-02 -8.3593620626714896E-02 -8.3582197854424903E-02 -8.3570764467535794E-02 -8.3559320478676355E-02 -8.3547865900475443E-02 -8.3536400745561845E-02 -8.3524925026564403E-02 -8.3513438756111960E-02 -8.3501941946833302E-02 -8.3490434611357259E-02 -8.3478916762312685E-02 -8.3467388412328355E-02 -8.3455849574033139E-02 -8.3444300260055837E-02 -8.3432740483025264E-02 -8.3421170255570262E-02 -8.3409589590319647E-02 -8.3397998499902232E-02 -8.3386396996946846E-02 -8.3374785094082318E-02 -8.3363162803937477E-02 -8.3351530139141122E-02 -8.3339887112322097E-02 -8.3328233736109217E-02 -8.3316570023131295E-02 -8.3304895986017188E-02 -8.3293211637395684E-02 -8.3281516989895610E-02 -8.3269812056145795E-02 -8.3258096848775082E-02 -8.3246371380412271E-02 -8.3234635663686177E-02 -8.3222889711225656E-02 -8.3211133535659482E-02 -8.3199367149616538E-02 -8.3187590565725597E-02 -8.3175803796615502E-02 -8.3164006854915082E-02 -8.3152199753253150E-02 -8.3140382504258536E-02 -8.3128555120560055E-02 -8.3116717614786534E-02 -8.3104869999566788E-02 -8.3093012287529661E-02 -8.3081144491303952E-02 -8.3069266623518503E-02 -8.3057378696802131E-02 -8.3045480723783649E-02 -8.3033572717091886E-02 -8.3021654689355670E-02 -8.3009726653203830E-02 -8.2997788621265167E-02 -8.2985840606168523E-02 -8.2973882620542713E-02 -8.2961914677016552E-02 -8.2949936788218881E-02 -8.2937948966778516E-02 -8.2925951225324285E-02 -8.2913943576485002E-02 -8.2901926032889484E-02 -8.2889898607166571E-02 -8.2877861311945078E-02 -8.2865814159853821E-02 -8.2853757163521641E-02 -8.2841690335577339E-02 -8.2829613688649759E-02 -8.2817527235367699E-02 -8.2805430988360004E-02 -8.2793324960255488E-02 -8.2781209163682978E-02 -8.2769083611271305E-02 -8.2756948315649267E-02 -8.2744803289445695E-02 -8.2732648545289444E-02 -8.2720484095809288E-02 -8.2708309953634082E-02 -8.2696126131392642E-02 -8.2683932641713781E-02 -8.2671729497226343E-02 -8.2659516710559142E-02 -8.2647294294340992E-02 -8.2635062261200709E-02 -8.2622820623767149E-02 -8.2610569394669098E-02 -8.2598308586535399E-02 -8.2586038211994880E-02 -8.2573758283676343E-02 -8.2561468814208630E-02 -8.2549169816220555E-02 -8.2536861302340961E-02 -8.2524543285198634E-02 -8.2512215777422418E-02 -8.2499878791641140E-02 -8.2487532340483616E-02 -8.2475176436578673E-02 -8.2462811092555127E-02 -8.2450436321041806E-02 -8.2438052134667539E-02 -8.2425658546061140E-02 -8.2413255567851423E-02 -8.2400843212667232E-02 -8.2388421493137382E-02 -8.2375990421890685E-02 -8.2363550011555986E-02 -8.2351100274762085E-02 -8.2338641224137823E-02 -8.2326172872312017E-02 -8.2313695231913481E-02 -8.2301208315571056E-02 -8.2288712135913530E-02 -8.2276206705569774E-02 -8.2263692037168587E-02 -8.2251168143338785E-02 -8.2238635036709196E-02 -8.2226092729908648E-02 -8.2213541235565957E-02 -8.2200980566309964E-02 -8.2188410734769471E-02 -8.2175831753573306E-02 -8.2163243635350297E-02 -8.2150646392729260E-02 -8.2138040038339022E-02 -8.2125424584808412E-02 -8.2112800044766246E-02 -8.2100166430841351E-02 -8.2087523755662528E-02 -8.2074872031858648E-02 -8.2062211272058483E-02 -8.2049541488890890E-02 -8.2036862694984683E-02 -8.2024174902968677E-02 -8.2011478125471687E-02 -8.1998772375122569E-02 -8.1986057664550124E-02 -8.1973334006383167E-02 -8.1960601413250539E-02 -8.1947859897781042E-02 -8.1935109472603532E-02 -8.1922350150346809E-02 -8.1909581943639689E-02 -8.1896804865111014E-02 -8.1884018927389585E-02 -8.1871224143104243E-02 -8.1858420524883818E-02 -8.1845608085357111E-02 -8.1832786837152963E-02 -8.1819956792900189E-02 -8.1807117965227591E-02 -8.1794270366764038E-02 -8.1781414010138317E-02 -8.1768548907979258E-02 -8.1755675072915701E-02 -8.1742792517576449E-02 -8.1729901254590329E-02 -8.1717001296586170E-02 -8.1704092656192800E-02 -8.1691175346039022E-02 -8.1678249378753676E-02 -8.1665314766965577E-02 -8.1652371523303555E-02 -8.1639419660396437E-02 -8.1626459190873024E-02 -8.1613490127362159E-02 -8.1600512482492657E-02 -8.1587526268893346E-02 -8.1574531499193040E-02 -8.1561528186020568E-02 -8.1548516342004759E-02 -8.1535495979774428E-02 -8.1522467111958402E-02 -8.1509429751185497E-02 -8.1496383910084541E-02 -8.1483329601284363E-02 -8.1470266837413777E-02 -8.1457195631101612E-02 -8.1444115994976682E-02 -8.1431027941667816E-02 -8.1417931483803843E-02 -8.1404826634013577E-02 -8.1391713404925847E-02 -8.1378591809169468E-02 -8.1365461859373267E-02 -8.1352323568166060E-02 -8.1339176948176703E-02 -8.1326022012033969E-02 -8.1312858772366714E-02 -8.1299687241803753E-02 -8.1286507432973915E-02 -8.1273319358506013E-02 -8.1260123031028877E-02 -8.1246918463171322E-02 -8.1233705667562175E-02 -8.1220484656830266E-02 -8.1207255443604395E-02 -8.1194018040513419E-02 -8.1180772460186137E-02 -8.1167518715251380E-02 -8.1154256818337975E-02 -8.1140986782074737E-02 -8.1127708619090494E-02 -8.1114422342014061E-02 -8.1101127963474268E-02 -8.1087825496099927E-02 -8.1074514952519897E-02 -8.1061196345362949E-02 -8.1047869687257940E-02 -8.1034534990833698E-02 -8.1021192268719011E-02 -8.1007841533542735E-02 -8.0994482797933684E-02 -8.0981116074520673E-02 -8.0967741375932531E-02 -8.0954358714798086E-02 -8.0940968103746153E-02 -8.0927569555405546E-02 -8.0914163082405122E-02 -8.0900748697373667E-02 -8.0887326412940025E-02 -8.0873896241733009E-02 -8.0860458196381449E-02 -8.0847012289514159E-02 -8.0833558533759967E-02 -8.0820096941747702E-02 -8.0806627526106178E-02 -8.0793150299464225E-02 -8.0779665274450657E-02 -8.0766172463694316E-02 -8.0752671879824003E-02 -8.0739163535468547E-02 -8.0725647443256762E-02 -8.0712123615817505E-02 -8.0698592065779562E-02 -8.0685052805771776E-02 -8.0671505848422975E-02 -8.0657951206361947E-02 -8.0644388892217561E-02 -8.0630818918618605E-02 -8.0617241298193920E-02 -8.0603656043572336E-02 -8.0590063167382653E-02 -8.0576462682253699E-02 -8.0562854600814318E-02 -8.0549238935693310E-02 -8.0535615699519517E-02 -8.0521984904921740E-02 -8.0508346564528807E-02 -8.0494700690969562E-02 -8.0481047296872804E-02 -8.0467386394867377E-02 -8.0453717997582080E-02 -8.0440042117645758E-02 -8.0426358767687223E-02 -8.0412667960335291E-02 -8.0398969708218804E-02 -8.0385264023966563E-02 -8.0371550920207410E-02 -8.0357830409570161E-02 -8.0344102504683629E-02 -8.0330367218176657E-02 -8.0316624562678060E-02 -8.0302874550816652E-02 -8.0289117195221263E-02 -8.0275352508520720E-02 -8.0261580503343824E-02 -8.0247801192319432E-02 -8.0234014588076344E-02 -8.0220220703243389E-02 -8.0206419550449395E-02 -8.0192611142323178E-02 -8.0178795491493565E-02 -8.0164972610589372E-02 -8.0151142512239440E-02 -8.0137305209072571E-02 -8.0123460713717592E-02 -8.0109609038803334E-02 -8.0095750196958609E-02 -8.0081884200812262E-02 -8.0068011062993091E-02 -8.0054130796129927E-02 -8.0040243412851597E-02 -8.0026348925786930E-02 -8.0012447347564741E-02 -7.9998538690813845E-02 -7.9984622968163083E-02 -7.9970700192241256E-02 -7.9956770375677208E-02 -7.9942833531099752E-02 -7.9928889671137704E-02 -7.9914938808419905E-02 -7.9900980955575157E-02 -7.9887016125232316E-02 -7.9873044330020168E-02 -7.9859065582567557E-02 -7.9845079895503282E-02 -7.9831087281456201E-02 -7.9817087753055113E-02 -7.9803081322928848E-02 -7.9789068003706234E-02 -7.9775047808016100E-02 -7.9761020748487232E-02 -7.9746986837748501E-02 -7.9732946088428708E-02 -7.9718898513156666E-02 -7.9704844124561205E-02 -7.9690782935271154E-02 -7.9676714956051289E-02 -7.9662640179466268E-02 -7.9648558588023957E-02 -7.9634470176030925E-02 -7.9620374955446674E-02 -7.9606272935452471E-02 -7.9592164107605654E-02 -7.9578048459823122E-02 -7.9563925993592396E-02 -7.9549796720297342E-02 -7.9535660645825762E-02 -7.9521517765034827E-02 -7.9507368071255843E-02 -7.9493211556296878E-02 -7.9479048211865772E-02 -7.9464878038681255E-02 -7.9450701045979372E-02 -7.9436517240280960E-02 -7.9422326620388062E-02 -7.9408129184470988E-02 -7.9393924935061616E-02 -7.9379713876387800E-02 -7.9365496001970334E-02 -7.9351271292254735E-02 -7.9337039735340550E-02 -7.9322801347732438E-02 -7.9308556150069334E-02 -7.9294304143583669E-02 -7.9280045317838235E-02 -7.9265779663490868E-02 -7.9251507173181746E-02 -7.9237227841916447E-02 -7.9222941674560982E-02 -7.9208648678620458E-02 -7.9194348859550803E-02 -7.9180042221173697E-02 -7.9165728761948120E-02 -7.9151408469386494E-02 -7.9137081332775083E-02 -7.9122747360301074E-02 -7.9108406566503003E-02 -7.9094058949044393E-02 -7.9079704488605254E-02 -7.9065343174677380E-02 -7.9050975022657954E-02 -7.9036600049455688E-02 -7.9022218248578302E-02 -7.9007829602320612E-02 -7.8993434105341417E-02 -7.8979031768462257E-02 -7.8964622600128390E-02 -7.8950206596310551E-02 -7.8935783751051106E-02 -7.8921354068616681E-02 -7.8906917559658910E-02 -7.8892474221363001E-02 -7.8878024028070662E-02 -7.8863566960823417E-02 -7.8849103043662855E-02 -7.8834632311401642E-02 -7.8820154761687397E-02 -7.8805670361374675E-02 -7.8791179091313196E-02 -7.8776680965176357E-02 -7.8762175998158740E-02 -7.8747664186902072E-02 -7.8733145521169251E-02 -7.8718620005276074E-02 -7.8704087659134767E-02 -7.8689548490691569E-02 -7.8675002470924918E-02 -7.8660449569023932E-02 -7.8645889797813895E-02 -7.8631323192523916E-02 -7.8616749763573163E-02 -7.8602169486789358E-02 -7.8587582342889178E-02 -7.8572988341366570E-02 -7.8558387497417156E-02 -7.8543779810233666E-02 -7.8529165268120829E-02 -7.8514543864577194E-02 -7.8499915602804490E-02 -7.8485280485861203E-02 -7.8470638510806087E-02 -7.8455989673307164E-02 -7.8441333979302350E-02 -7.8426671443767679E-02 -7.8412002071145376E-02 -7.8397325840384488E-02 -7.8382642731235824E-02 -7.8367952754807041E-02 -7.8353255934917196E-02 -7.8338552273753248E-02 -7.8323841748793518E-02 -7.8309124346650258E-02 -7.8294400086560342E-02 -7.8279668991028270E-02 -7.8264931052877962E-02 -7.8250186248496556E-02 -7.8235434566009524E-02 -7.8220676011103121E-02 -7.8205910590489855E-02 -7.8191138309293320E-02 -7.8176359171905019E-02 -7.8161573178321078E-02 -7.8146780325367857E-02 -7.8131980613519447E-02 -7.8117174050374882E-02 -7.8102360640327953E-02 -7.8087540365362251E-02 -7.8072713201155788E-02 -7.8057879153849666E-02 -7.8043038258196182E-02 -7.8028190531579236E-02 -7.8013335944907489E-02 -7.7998474467191076E-02 -7.7983606107581996E-02 -7.7968730893080651E-02 -7.7953848832184272E-02 -7.7938959910830538E-02 -7.7924064117119954E-02 -7.7909161450909786E-02 -7.7894251914978369E-02 -7.7879335517043138E-02 -7.7864412267582006E-02 -7.7849482164909597E-02 -7.7834545188190218E-02 -7.7819601321975782E-02 -7.7804650582397050E-02 -7.7789692992868989E-02 -7.7774728553525796E-02 -7.7759757246506508E-02 -7.7744779062800792E-02 -7.7729794012462577E-02 -7.7714802104641739E-02 -7.7699803329040168E-02 -7.7684797668937752E-02 -7.7669785126326871E-02 -7.7654765721924146E-02 -7.7639739468617061E-02 -7.7624706356016551E-02 -7.7609666371562788E-02 -7.7594619516687974E-02 -7.7579565799429678E-02 -7.7564505218356103E-02 -7.7549437759748652E-02 -7.7534363415967505E-02 -7.7519282204085591E-02 -7.7504194144264946E-02 -7.7489099228628275E-02 -7.7473997431655062E-02 -7.7458888746275795E-02 -7.7443773196769372E-02 -7.7428650803311044E-02 -7.7413521552027784E-02 -7.7398385419911897E-02 -7.7383242401886099E-02 -7.7368092507679981E-02 -7.7352935747584770E-02 -7.7337772132149832E-02 -7.7322601668840529E-02 -7.7307424344931833E-02 -7.7292240140275567E-02 -7.7277049050686802E-02 -7.7261851088997552E-02 -7.7246646265276914E-02 -7.7231434579239464E-02 -7.7216216028229229E-02 -7.7200990605026457E-02 -7.7185758300274271E-02 -7.7170519115656408E-02 -7.7155273068062871E-02 -7.7140020170208115E-02 -7.7124760414475177E-02 -7.7109493789138173E-02 -7.7094220292265300E-02 -7.7078939928557938E-02 -7.7063652700415736E-02 -7.7048358605904962E-02 -7.7033057642966238E-02 -7.7017749811204544E-02 -7.7002435110806816E-02 -7.6987113542814900E-02 -7.6971785109016866E-02 -7.6956449809946051E-02 -7.6941107643145490E-02 -7.6925758606880904E-02 -7.6910402707436362E-02 -7.6895039954088404E-02 -7.6879670343759074E-02 -7.6864293859360749E-02 -7.6848910490344605E-02 -7.6833520248722378E-02 -7.6818123149974590E-02 -7.6802719201122860E-02 -7.6787308404296706E-02 -7.6771890752697594E-02 -7.6756466226530276E-02 -7.6741034811895412E-02 -7.6725596523546741E-02 -7.6710151382207895E-02 -7.6694699388977564E-02 -7.6679240530804660E-02 -7.6663774801469436E-02 -7.6648302208359859E-02 -7.6632822759388000E-02 -7.6617336456907215E-02 -7.6601843301084882E-02 -7.6586343286599551E-02 -7.6570836403016623E-02 -7.6555322646299523E-02 -7.6539802028891143E-02 -7.6524274563052982E-02 -7.6508740240611883E-02 -7.6493199044620833E-02 -7.6477650975832701E-02 -7.6462096056399850E-02 -7.6446534300712132E-02 -7.6430965693169539E-02 -7.6415390213721776E-02 -7.6399807860717525E-02 -7.6384218643466492E-02 -7.6368622572079645E-02 -7.6353019657691160E-02 -7.6337409906453449E-02 -7.6321793301998911E-02 -7.6306169823251627E-02 -7.6290539472259958E-02 -7.6274902268842454E-02 -7.6259258224378026E-02 -7.6243607332158417E-02 -7.6227949583939358E-02 -7.6212284975409758E-02 -7.6196613504200844E-02 -7.6180935179080395E-02 -7.6165250019871636E-02 -7.6149558033900916E-02 -7.6133859193786041E-02 -7.6118153471603806E-02 -7.6102440881757036E-02 -7.6086721458579323E-02 -7.6070995211048709E-02 -7.6055262115420311E-02 -7.6039522153261749E-02 -7.6023775332712373E-02 -7.6008021666952141E-02 -7.5992261159242888E-02 -7.5976493806561976E-02 -7.5960719606351368E-02 -7.5944938556992220E-02 -7.5929150658453251E-02 -7.5913355917854489E-02 -7.5897554343889229E-02 -7.5881745936048989E-02 -7.5865930686279295E-02 -7.5850108587743839E-02 -7.5834279636735974E-02 -7.5818443832440768E-02 -7.5802601189998514E-02 -7.5786751729876492E-02 -7.5770895447326625E-02 -7.5755032310905010E-02 -7.5739162302781840E-02 -7.5723285447826999E-02 -7.5707401775179872E-02 -7.5691511284639870E-02 -7.5675613960923691E-02 -7.5659709795952448E-02 -7.5643798791671241E-02 -7.5627880950348947E-02 -7.5611956272730541E-02 -7.5596024759401526E-02 -7.5580086413486097E-02 -7.5564141239782140E-02 -7.5548189239361130E-02 -7.5532230406629569E-02 -7.5516264736973635E-02 -7.5500292234309430E-02 -7.5484312905032727E-02 -7.5468326751037040E-02 -7.5452333770286178E-02 -7.5436333961767188E-02 -7.5420327327149289E-02 -7.5404313868155784E-02 -7.5388293584254348E-02 -7.5372266473971147E-02 -7.5356232536222589E-02 -7.5340191770369741E-02 -7.5324144177750338E-02 -7.5308089765703343E-02 -7.5292028541795633E-02 -7.5275960504805936E-02 -7.5259885648738423E-02 -7.5243803972637746E-02 -7.5227715482960603E-02 -7.5211620183503081E-02 -7.5195518064732320E-02 -7.5179409114938714E-02 -7.5163293339291892E-02 -7.5147170755027873E-02 -7.5131041370110063E-02 -7.5114905174452795E-02 -7.5098762158907706E-02 -7.5082612330565401E-02 -7.5066455701381762E-02 -7.5050292269141172E-02 -7.5034122018477353E-02 -7.5017944943777531E-02 -7.5001761064889025E-02 -7.4985570401470289E-02 -7.4969372942723086E-02 -7.4953168664659758E-02 -7.4936957562864823E-02 -7.4920739656467686E-02 -7.4904514961249724E-02 -7.4888283477372961E-02 -7.4872045201486173E-02 -7.4855800127135316E-02 -7.4839548246138130E-02 -7.4823289556742889E-02 -7.4807024067206504E-02 -7.4790751785124926E-02 -7.4774472711377535E-02 -7.4758186844837635E-02 -7.4741894182081492E-02 -7.4725594717983609E-02 -7.4709288455666961E-02 -7.4692975415004886E-02 -7.4676655611920481E-02 -7.4660329026942140E-02 -7.4643995628956197E-02 -7.4627655417436475E-02 -7.4611308422112638E-02 -7.4594954662854165E-02 -7.4578594129890527E-02 -7.4562226810428497E-02 -7.4545852706598331E-02 -7.4529471827539898E-02 -7.4513084174580330E-02 -7.4496689739017033E-02 -7.4480288515113902E-02 -7.4463880509939212E-02 -7.4447465732727369E-02 -7.4431044185223477E-02 -7.4414615864453706E-02 -7.4398180767664121E-02 -7.4381738892586619E-02 -7.4365290239616438E-02 -7.4348834821555243E-02 -7.4332372653756501E-02 -7.4315903733250269E-02 -7.4299428042160678E-02 -7.4282945570890505E-02 -7.4266456328647867E-02 -7.4249960325345532E-02 -7.4233457559763863E-02 -7.4216948026607929E-02 -7.4200431728220925E-02 -7.4183908674992236E-02 -7.4167378873890077E-02 -7.4150842321049945E-02 -7.4134299011325899E-02 -7.4117748945112569E-02 -7.4101192125609977E-02 -7.4084628553583637E-02 -7.4068058226459135E-02 -7.4051481143315084E-02 -7.4034897310416584E-02 -7.4018306735281036E-02 -7.4001709419843603E-02 -7.3985105362294037E-02 -7.3968494561245587E-02 -7.3951877016180806E-02 -7.3935252726605699E-02 -7.3918621691695344E-02 -7.3901983910792030E-02 -7.3885339388159776E-02 -7.3868688132320351E-02 -7.3852030147731645E-02 -7.3835365429150590E-02 -7.3818693971808236E-02 -7.3802015783578701E-02 -7.3785330877216282E-02 -7.3768639252966353E-02 -7.3751940897047105E-02 -7.3735235800913762E-02 -7.3718523974272823E-02 -7.3701805429053982E-02 -7.3685080165375075E-02 -7.3668348176919543E-02 -7.3651609461207065E-02 -7.3634864021406260E-02 -7.3618111860714625E-02 -7.3601352980644741E-02 -7.3584587382841168E-02 -7.3567815076497525E-02 -7.3551036076082363E-02 -7.3534250382319283E-02 -7.3517457969865543E-02 -7.3500658818047113E-02 -7.3483852947514694E-02 -7.3467040391516053E-02 -7.3450221153764289E-02 -7.3433395210689867E-02 -7.3416562546541025E-02 -7.3399723167384967E-02 -7.3382877083014081E-02 -7.3366024306336972E-02 -7.3349164851243903E-02 -7.3332298718059200E-02 -7.3315425890931374E-02 -7.3298546357990713E-02 -7.3281660123505954E-02 -7.3264767194876707E-02 -7.3247867577783246E-02 -7.3230961276871703E-02 -7.3214048295414585E-02 -7.3197128634586939E-02 -7.3180202294609129E-02 -7.3163269272302822E-02 -7.3146329564109921E-02 -7.3129383174594276E-02 -7.3112430114457436E-02 -7.3095470387412723E-02 -7.3078503982833054E-02 -7.3061530891488938E-02 -7.3044551122482690E-02 -7.3027564691241761E-02 -7.3010571605075902E-02 -7.2993571863297121E-02 -7.2976565462253756E-02 -7.2959552391357554E-02 -7.2942532641402616E-02 -7.2925506223345773E-02 -7.2908473157411210E-02 -7.2891433448124598E-02 -7.2874387080018019E-02 -7.2857334043122876E-02 -7.2840274351329323E-02 -7.2823208022261679E-02 -7.2806135056716847E-02 -7.2789055444982140E-02 -7.2771969179953655E-02 -7.2754876259080253E-02 -7.2737776683132582E-02 -7.2720670466524653E-02 -7.2703557626522960E-02 -7.2686438161608580E-02 -7.2669312055072682E-02 -7.2652179298907174E-02 -7.2635039904703727E-02 -7.2617893885300350E-02 -7.2600741245374731E-02 -7.2583581986267159E-02 -7.2566416105593265E-02 -7.2549243597082244E-02 -7.2532064457210499E-02 -7.2514878690744911E-02 -7.2497686303447217E-02 -7.2480487297078969E-02 -7.2463281671389601E-02 -7.2446069427887477E-02 -7.2428850570479333E-02 -7.2411625103697669E-02 -7.2394393033795412E-02 -7.2377154366746466E-02 -7.2359909100175410E-02 -7.2342657226190987E-02 -7.2325398742067615E-02 -7.2308133654307827E-02 -7.2290861968910228E-02 -7.2273583684607720E-02 -7.2256298798138358E-02 -7.2239007311561007E-02 -7.2221709231530998E-02 -7.2204404565201635E-02 -7.2187093320521464E-02 -7.2169775503688735E-02 -7.2152451108183857E-02 -7.2135120122482979E-02 -7.2117782543878822E-02 -7.2100438379501100E-02 -7.2083087637172472E-02 -7.2065730325255040E-02 -7.2048366450752785E-02 -7.2030996006948872E-02 -7.2013618979890157E-02 -7.1996235369519296E-02 -7.1978845195877036E-02 -7.1961448474096870E-02 -7.1944045193107459E-02 -7.1926635336855158E-02 -7.1909218911352435E-02 -7.1891795938195752E-02 -7.1874366426939951E-02 -7.1856930364006547E-02 -7.1839487736518548E-02 -7.1822038549203743E-02 -7.1804582812604476E-02 -7.1787120534468882E-02 -7.1769651719966451E-02 -7.1752176371842030E-02 -7.1734694487130476E-02 -7.1717206062433730E-02 -7.1699711097494415E-02 -7.1682209593557311E-02 -7.1664701554988927E-02 -7.1647186989846318E-02 -7.1629665903281695E-02 -7.1612138290301303E-02 -7.1594604144892104E-02 -7.1577063471652311E-02 -7.1559516281282376E-02 -7.1541962578730509E-02 -7.1524402360011244E-02 -7.1506835622345499E-02 -7.1489262371498274E-02 -7.1471682615242921E-02 -7.1454096356736135E-02 -7.1436503595623008E-02 -7.1418904329625277E-02 -7.1401298552800710E-02 -7.1383686261868209E-02 -7.1366067471657177E-02 -7.1348442202647758E-02 -7.1330810455104449E-02 -7.1313172209538797E-02 -7.1295527456502639E-02 -7.1277876215060765E-02 -7.1260218506188883E-02 -7.1242554329290539E-02 -7.1224883673506892E-02 -7.1207206529591213E-02 -7.1189522890411180E-02 -7.1171832755993425E-02 -7.1154136150887282E-02 -7.1136433102039792E-02 -7.1118723603660200E-02 -7.1101007629805563E-02 -7.1083285171460134E-02 -7.1065556247756415E-02 -7.1047820876479720E-02 -7.1030079056974338E-02 -7.1012330783328859E-02 -7.0994576051719049E-02 -7.0976814860040233E-02 -7.0959047212403772E-02 -7.0941273126065033E-02 -7.0923492615577913E-02 -7.0905705667863958E-02 -7.0887912260072475E-02 -7.0870112392984810E-02 -7.0852306091983147E-02 -7.0834493376198723E-02 -7.0816674243965941E-02 -7.0798848689663796E-02 -7.0781016704846461E-02 -7.0763178279981909E-02 -7.0745333420425133E-02 -7.0727482151535695E-02 -7.0709624490938983E-02 -7.0691760422002911E-02 -7.0673889922264491E-02 -7.0656012995804165E-02 -7.0638129664202229E-02 -7.0620239938738311E-02 -7.0602343812203580E-02 -7.0584441278003715E-02 -7.0566532341947083E-02 -7.0548617013373852E-02 -7.0530695295328683E-02 -7.0512767185459652E-02 -7.0494832683328831E-02 -7.0476891793257460E-02 -7.0458944519826511E-02 -7.0440990864905351E-02 -7.0423030829242977E-02 -7.0405064413760474E-02 -7.0387091619575140E-02 -7.0369112450382285E-02 -7.0351126917613971E-02 -7.0333135032258687E-02 -7.0315136787630142E-02 -7.0297132167679119E-02 -7.0279121169115555E-02 -7.0261103807031738E-02 -7.0243080095988675E-02 -7.0225050042717133E-02 -7.0207013651425607E-02 -7.0188970919024554E-02 -7.0170921837307457E-02 -7.0152866402645980E-02 -7.0134804620118632E-02 -7.0116736495859297E-02 -7.0098662036585935E-02 -7.0080581248871177E-02 -7.0062494132575745E-02 -7.0044400681449154E-02 -7.0026300895738400E-02 -7.0008194792067754E-02 -6.9990082386531594E-02 -6.9971963673441204E-02 -6.9953838637794127E-02 -6.9935707276080269E-02 -6.9917569598379484E-02 -6.9899425614083285E-02 -6.9881275327837139E-02 -6.9863118742940183E-02 -6.9844955858751903E-02 -6.9826786672415334E-02 -6.9808611185204802E-02 -6.9790429404730625E-02 -6.9772241338205546E-02 -6.9754046988822760E-02 -6.9735846358668419E-02 -6.9717639449528662E-02 -6.9699426262950795E-02 -6.9681206798817882E-02 -6.9662981053724066E-02 -6.9644749025831204E-02 -6.9626510724660612E-02 -6.9608266163504143E-02 -6.9590015348634876E-02 -6.9571758279495313E-02 -6.9553494954029113E-02 -6.9535225367007070E-02 -6.9516949514661461E-02 -6.9498667408810874E-02 -6.9480379068249304E-02 -6.9462084496478296E-02 -6.9443783677769377E-02 -6.9425476602510403E-02 -6.9407163286525547E-02 -6.9388843749521215E-02 -6.9370517993279535E-02 -6.9352186008545549E-02 -6.9333847790385331E-02 -6.9315503341147888E-02 -6.9297152664993297E-02 -6.9278795771397089E-02 -6.9260432670951264E-02 -6.9242063367469464E-02 -6.9223687859326158E-02 -6.9205306144111176E-02 -6.9186918218076432E-02 -6.9168524079512725E-02 -6.9150123740526773E-02 -6.9131717218085309E-02 -6.9113304517665078E-02 -6.9094885632849587E-02 -6.9076460558620378E-02 -6.9058029295396908E-02 -6.9039591844877915E-02 -6.9021148211643985E-02 -6.9002698401693707E-02 -6.8984242419224878E-02 -6.8965780266016297E-02 -6.8947311945208006E-02 -6.8928837465635495E-02 -6.8910356836261455E-02 -6.8891870051675033E-02 -6.8873377097154145E-02 -6.8854877972394007E-02 -6.8836372702334156E-02 -6.8817861308440545E-02 -6.8799343782307801E-02 -6.8780820107093507E-02 -6.8762290281109459E-02 -6.8743754315592501E-02 -6.8725212219711354E-02 -6.8706663997014208E-02 -6.8688109650432830E-02 -6.8669549183954501E-02 -6.8650982601965171E-02 -6.8632409907830233E-02 -6.8613831103788644E-02 -6.8595246189647324E-02 -6.8576655158105945E-02 -6.8558058002916866E-02 -6.8539454739835068E-02 -6.8520845396092045E-02 -6.8502229978155138E-02 -6.8483608462809570E-02 -6.8464980833628508E-02 -6.8446347110381708E-02 -6.8427707319924841E-02 -6.8409061463416215E-02 -6.8390409524056686E-02 -6.8371751496114727E-02 -6.8353087394987286E-02 -6.8334417235746250E-02 -6.8315741019482221E-02 -6.8297058742623165E-02 -6.8278370401708241E-02 -6.8259675993397662E-02 -6.8240975519733654E-02 -6.8222268995777907E-02 -6.8203556436152765E-02 -6.8184837838255033E-02 -6.8166113192358865E-02 -6.8147382503782258E-02 -6.8128645795497988E-02 -6.8109903080092918E-02 -6.8091154333585910E-02 -6.8072399529025648E-02 -6.8053638683186479E-02 -6.8034871837616834E-02 -6.8016099007232447E-02 -6.7997320166158712E-02 -6.7978535292824105E-02 -6.7959744398735061E-02 -6.7940947503583607E-02 -6.7922144617109589E-02 -6.7903335741591409E-02 -6.7884520877963359E-02 -6.7865700024865722E-02 -6.7846873181353184E-02 -6.7828040350418964E-02 -6.7809201536516900E-02 -6.7790356745204103E-02 -6.7771505983096558E-02 -6.7752649254222780E-02 -6.7733786555794692E-02 -6.7714917885307355E-02 -6.7696043251023977E-02 -6.7677162666078358E-02 -6.7658276136117107E-02 -6.7639383657416605E-02 -6.7620485228116659E-02 -6.7601580854802806E-02 -6.7582670545316983E-02 -6.7563754301374457E-02 -6.7544832120929543E-02 -6.7525904002659398E-02 -6.7506969946496659E-02 -6.7488029955369205E-02 -6.7469084045497174E-02 -6.7450132235690519E-02 -6.7431174525178508E-02 -6.7412210897638686E-02 -6.7393241345880220E-02 -6.7374265882844633E-02 -6.7355284522896006E-02 -6.7336297273422038E-02 -6.7317304138993297E-02 -6.7298305120722463E-02 -6.7279300216174592E-02 -6.7260289424701677E-02 -6.7241272751064451E-02 -6.7222250200393519E-02 -6.7203221773064301E-02 -6.7184187467191195E-02 -6.7165147286425572E-02 -6.7146101241790615E-02 -6.7127049343778195E-02 -6.7107991599033537E-02 -6.7088928012465465E-02 -6.7069858578903893E-02 -6.7050783286716542E-02 -6.7031702136425675E-02 -6.7012615149662780E-02 -6.6993522344975701E-02 -6.6974423715294981E-02 -6.6955319246613174E-02 -6.6936208942062383E-02 -6.6917092819286497E-02 -6.6897970889131006E-02 -6.6878843146112699E-02 -6.6859709584040528E-02 -6.6840570206906619E-02 -6.6821425022932632E-02 -6.6802274041746865E-02 -6.6783117274499107E-02 -6.6763954727210306E-02 -6.6744786390418448E-02 -6.6725612253923164E-02 -6.6706432327062429E-02 -6.6687246629412708E-02 -6.6668055167640863E-02 -6.6648857930028338E-02 -6.6629654909596908E-02 -6.6610446123720954E-02 -6.6591231593882985E-02 -6.6572011316381616E-02 -6.6552785270086692E-02 -6.6533553450995264E-02 -6.6514315887197417E-02 -6.6495072604061317E-02 -6.6475823594128083E-02 -6.6456568839912564E-02 -6.6437308340559706E-02 -6.6418042110228517E-02 -6.6398770160995296E-02 -6.6379492498628956E-02 -6.6360209127338560E-02 -6.6340920046782478E-02 -6.6321625254721100E-02 -6.6302324751954217E-02 -6.6283018542830613E-02 -6.6263706632367733E-02 -6.6244389027077411E-02 -6.6225065733358415E-02 -6.6205736753519692E-02 -6.6186402087601737E-02 -6.6167061740016922E-02 -6.6147715721800310E-02 -6.6128364041162041E-02 -6.6109006691925709E-02 -6.6089643665206699E-02 -6.6070274968174011E-02 -6.6050900619876729E-02 -6.6031520630850035E-02 -6.6012134994395608E-02 -6.5992743704044510E-02 -6.5973346766106500E-02 -6.5953944191118566E-02 -6.5934535982841602E-02 -6.5915122138533094E-02 -6.5895702660797403E-02 -6.5876277566681254E-02 -6.5856846872733868E-02 -6.5837410573775346E-02 -6.5817968654806255E-02 -6.5798521113829694E-02 -6.5779067965034507E-02 -6.5759609221539381E-02 -6.5740144889355270E-02 -6.5720674972409784E-02 -6.5701199468521099E-02 -6.5681718371907255E-02 -6.5662231685917408E-02 -6.5642739428633551E-02 -6.5623241614142375E-02 -6.5603738232140038E-02 -6.5584229266696492E-02 -6.5564714723091749E-02 -6.5545194623381917E-02 -6.5525668984597232E-02 -6.5506137812290671E-02 -6.5486601108901921E-02 -6.5467058866555544E-02 -6.5447511073996767E-02 -6.5427957733117284E-02 -6.5408398859252426E-02 -6.5388834465141224E-02 -6.5369264554688347E-02 -6.5349689130235172E-02 -6.5330108193668898E-02 -6.5310521746725192E-02 -6.5290929794194250E-02 -6.5271332344898292E-02 -6.5251729405960232E-02 -6.5232120977245928E-02 -6.5212507056950336E-02 -6.5192887643213737E-02 -6.5173262734268919E-02 -6.5153632338521991E-02 -6.5133996481777048E-02 -6.5114355184270278E-02 -6.5094708430430220E-02 -6.5075056195354086E-02 -6.5055398482937607E-02 -6.5035735321317567E-02 -6.5016066727776420E-02 -6.4996392693633109E-02 -6.4976713209780226E-02 -6.4957028287666599E-02 -6.4937337946486789E-02 -6.4917642188382224E-02 -6.4897940996924308E-02 -6.4878234364608045E-02 -6.4858522313057457E-02 -6.4838804866859626E-02 -6.4819082028805236E-02 -6.4799353790102654E-02 -6.4779620145343331E-02 -6.4759881094025668E-02 -6.4740136639176535E-02 -6.4720386796293800E-02 -6.4700631583071988E-02 -6.4680871005880658E-02 -6.4661105063199734E-02 -6.4641333751453187E-02 -6.4621557063604673E-02 -6.4601774996498787E-02 -6.4581987569466107E-02 -6.4562194808064341E-02 -6.4542396715270831E-02 -6.4522593273820927E-02 -6.4502784475388042E-02 -6.4482970334730855E-02 -6.4463150868366542E-02 -6.4443326081221497E-02 -6.4423495973244232E-02 -6.4403660546698202E-02 -6.4383819806551196E-02 -6.4363973758285550E-02 -6.4344122408535792E-02 -6.4324265763426550E-02 -6.4304403821788619E-02 -6.4284536578430154E-02 -6.4264664035707422E-02 -6.4244786207344001E-02 -6.4224903105869161E-02 -6.4205014734802918E-02 -6.4185121095193906E-02 -6.4165222186887444E-02 -6.4145318008872632E-02 -6.4125408564288264E-02 -6.4105493864392085E-02 -6.4085573920221975E-02 -6.4065648736240238E-02 -6.4045718314685890E-02 -6.4025782659907937E-02 -6.4005841778266917E-02 -6.3985895673246695E-02 -6.3965944340766731E-02 -6.3945987777165827E-02 -6.3926025991245500E-02 -6.3906058997448958E-02 -6.3886086804445005E-02 -6.3866109413748318E-02 -6.3846126827833735E-02 -6.3826139053939399E-02 -6.3806146099491506E-02 -6.3786147963066434E-02 -6.3766144637977723E-02 -6.3746136125324468E-02 -6.3726122438741137E-02 -6.3706103591154625E-02 -6.3686079587171610E-02 -6.3666050429075069E-02 -6.3646016119804374E-02 -6.3625976662821937E-02 -6.3605932062520160E-02 -6.3585882325195353E-02 -6.3565827456913249E-02 -6.3545767460873745E-02 -6.3525702339303533E-02 -6.3505632097068332E-02 -6.3485556741714952E-02 -6.3465476278830937E-02 -6.3445390708307667E-02 -6.3425300029903736E-02 -6.3405204250347943E-02 -6.3385103379743402E-02 -6.3364997424397981E-02 -6.3344886385608631E-02 -6.3324770264900632E-02 -6.3304649065872964E-02 -6.3284522792663070E-02 -6.3264391450175969E-02 -6.3244255043837141E-02 -6.3224113580860636E-02 -6.3203967071486317E-02 -6.3183815524518780E-02 -6.3163658940305137E-02 -6.3143497316768479E-02 -6.3123330654520915E-02 -6.3103158956444194E-02 -6.3082982228384071E-02 -6.3062800482615589E-02 -6.3042613730450323E-02 -6.3022421971134598E-02 -6.3002225199366962E-02 -6.2982023418883204E-02 -6.2961816643205964E-02 -6.2941604884102623E-02 -6.2921388146755575E-02 -6.2901166434389796E-02 -6.2880939743394398E-02 -6.2860708066804230E-02 -6.2840471410471402E-02 -6.2820229798194335E-02 -6.2799983248072261E-02 -6.2779731750636780E-02 -6.2759475291128727E-02 -6.2739213873478111E-02 -6.2718947514458459E-02 -6.2698676224657052E-02 -6.2678400002979751E-02 -6.2658118849822475E-02 -6.2637832779894112E-02 -6.2617541811511399E-02 -6.2597245942612720E-02 -6.2576945153000871E-02 -6.2556639437379477E-02 -6.2536328827361612E-02 -6.2516013354184732E-02 -6.2495693008284427E-02 -6.2475367763218194E-02 -6.2455037616630141E-02 -6.2434702593964227E-02 -6.2414362715787215E-02 -6.2394017982474966E-02 -6.2373668391268212E-02 -6.2353313947527723E-02 -6.2332954661082775E-02 -6.2312590534461421E-02 -6.2292221559252785E-02 -6.2271847731931930E-02 -6.2251469073284181E-02 -6.2231085608903371E-02 -6.2210697342175970E-02 -6.2190304260218529E-02 -6.2169906357946739E-02 -6.2149503646098718E-02 -6.2129096135699100E-02 -6.2108683829163513E-02 -6.2088266726193657E-02 -6.2067844832953058E-02 -6.2047418161740357E-02 -6.2026986723131922E-02 -6.2006550522709626E-02 -6.1986109564509687E-02 -6.1965663846704142E-02 -6.1945213364917415E-02 -6.1924758120541532E-02 -6.1904298122051268E-02 -6.1883833380292644E-02 -6.1863363912659557E-02 -6.1842889735765232E-02 -6.1822410843174309E-02 -6.1801927214785862E-02 -6.1781438847749011E-02 -6.1760945766860892E-02 -6.1740447995019120E-02 -6.1719945535450606E-02 -6.1699438385913269E-02 -6.1678926545517362E-02 -6.1658410014453026E-02 -6.1637888796064522E-02 -6.1617362900154071E-02 -6.1596832336481021E-02 -6.1576297109683646E-02 -6.1555757222536416E-02 -6.1535212679259779E-02 -6.1514663485537413E-02 -6.1494109646096147E-02 -6.1473551162882271E-02 -6.1452988038419296E-02 -6.1432420283908495E-02 -6.1411847914584566E-02 -6.1391270935479227E-02 -6.1370689338281416E-02 -6.1350103118553254E-02 -6.1329512289150359E-02 -6.1308916865843270E-02 -6.1288316852753752E-02 -6.1267712246601783E-02 -6.1247103052162299E-02 -6.1226489288030941E-02 -6.1205870969058628E-02 -6.1185248085429411E-02 -6.1164620621060657E-02 -6.1143988580389996E-02 -6.1123351984936306E-02 -6.1102710850880530E-02 -6.1082065181465139E-02 -6.1061414978407481E-02 -6.1040760244762411E-02 -6.1020100984178968E-02 -6.0999437201770541E-02 -6.0978768904222311E-02 -6.0958096097015850E-02 -6.0937418781896110E-02 -6.0916736960338488E-02 -6.0896050637481366E-02 -6.0875359820395970E-02 -6.0854664516062106E-02 -6.0833964731308289E-02 -6.0813260472884031E-02 -6.0792551747274541E-02 -6.0771838560782152E-02 -6.0751120918207287E-02 -6.0730398823309995E-02 -6.0709672278994514E-02 -6.0688941286659269E-02 -6.0668205849148941E-02 -6.0647465977682377E-02 -6.0626721685875594E-02 -6.0605972981231437E-02 -6.0585219865822014E-02 -6.0564462340109974E-02 -6.0543700401203576E-02 -6.0522934047890962E-02 -6.0502163294241670E-02 -6.0481388160492700E-02 -6.0460608654630460E-02 -6.0439824770596472E-02 -6.0419036504406373E-02 -6.0398243860967718E-02 -6.0377446846971092E-02 -6.0356645469592768E-02 -6.0335839736358206E-02 -6.0315029658796773E-02 -6.0294215254353814E-02 -6.0273396534147594E-02 -6.0252573480845915E-02 -6.0231746072440681E-02 -6.0210914325196534E-02 -6.0190078283147985E-02 -6.0169237964966163E-02 -6.0148393339318346E-02 -6.0127544378142404E-02 -6.0106691103604580E-02 -6.0085833554136825E-02 -6.0064971742197215E-02 -6.0044105655722033E-02 -6.0023235289351017E-02 -6.0002360657077598E-02 -5.9981481773709849E-02 -5.9960598637335404E-02 -5.9939711238800868E-02 -5.9918819584329278E-02 -5.9897923698915993E-02 -5.9877023599997012E-02 -5.9856119275834452E-02 -5.9835210710823379E-02 -5.9814297913102665E-02 -5.9793380904952377E-02 -5.9772459700536983E-02 -5.9751534300927202E-02 -5.9730604706780356E-02 -5.9709670922068747E-02 -5.9688732951792021E-02 -5.9667790802427352E-02 -5.9646844481579295E-02 -5.9625893993418271E-02 -5.9604939335001182E-02 -5.9583980505688167E-02 -5.9563017524030822E-02 -5.9542050414858813E-02 -5.9521079182317589E-02 -5.9500103809775308E-02 -5.9479124289164506E-02 -5.9458140638041182E-02 -5.9437152876810680E-02 -5.9416161014024332E-02 -5.9395165052316623E-02 -5.9374164990935431E-02 -5.9353160824791494E-02 -5.9332152553817422E-02 -5.9311140197072766E-02 -5.9290123776202491E-02 -5.9269103293053939E-02 -5.9248078736916128E-02 -5.9227050106449457E-02 -5.9206017416401878E-02 -5.9184980680860477E-02 -5.9163939903294729E-02 -5.9142895084414490E-02 -5.9121846232286009E-02 -5.9100793361041210E-02 -5.9079736478644160E-02 -5.9058675579123830E-02 -5.9037610656659148E-02 -5.9016541718435143E-02 -5.8995468776842620E-02 -5.8974391844373690E-02 -5.8953310933609490E-02 -5.8932226052389833E-02 -5.8911137194804078E-02 -5.8890044354160537E-02 -5.8868947538878842E-02 -5.8847846765181192E-02 -5.8826742043435298E-02 -5.8805633375831945E-02 -5.8784520763665256E-02 -5.8763404207073051E-02 -5.8742283707092474E-02 -5.8721159279575399E-02 -5.8700030950308769E-02 -5.8678898728842632E-02 -5.8657762595294781E-02 -5.8636622533375385E-02 -5.8615478561287307E-02 -5.8594330707468778E-02 -5.8573178983475305E-02 -5.8552023385972700E-02 -5.8530863913296725E-02 -5.8509700568898475E-02 -5.8488533357879700E-02 -5.8467362291780609E-02 -5.8446187384571399E-02 -5.8425008640677886E-02 -5.8403826053659388E-02 -5.8382639620914951E-02 -5.8361449353603871E-02 -5.8340255265072000E-02 -5.8319057364048354E-02 -5.8297855656681927E-02 -5.8276650149446114E-02 -5.8255440849333165E-02 -5.8234227762569368E-02 -5.8213010892027024E-02 -5.8191790239751205E-02 -5.8170565808382896E-02 -5.8149337601023698E-02 -5.8128105623899702E-02 -5.8106869889189824E-02 -5.8085630408220991E-02 -5.8064387183829641E-02 -5.8043140216267795E-02 -5.8021889513137324E-02 -5.8000635088926139E-02 -5.7979376952259278E-02 -5.7958115096379229E-02 -5.7936849514718058E-02 -5.7915580220109807E-02 -5.7894307234030808E-02 -5.7873030570182983E-02 -5.7851750232800404E-02 -5.7830466222982477E-02 -5.7809178533272922E-02 -5.7787887156308851E-02 -5.7766592104396226E-02 -5.7745293401413406E-02 -5.7723991060258467E-02 -5.7702685076385207E-02 -5.7681375446666384E-02 -5.7660062181094089E-02 -5.7638745292878116E-02 -5.7617424788598791E-02 -5.7596100669718327E-02 -5.7574772939679275E-02 -5.7553441606237918E-02 -5.7532106677465812E-02 -5.7510768160170728E-02 -5.7489426060613517E-02 -5.7468080383270247E-02 -5.7446731130838175E-02 -5.7425378307815196E-02 -5.7404021923744809E-02 -5.7382661988311101E-02 -5.7361298505490578E-02 -5.7339931476589452E-02 -5.7318560907464809E-02 -5.7297186809862490E-02 -5.7275809193686071E-02 -5.7254428060857322E-02 -5.7233043412009937E-02 -5.7211655253446174E-02 -5.7190263595056821E-02 -5.7168868445143552E-02 -5.7147469809258361E-02 -5.7126067692667759E-02 -5.7104662100521675E-02 -5.7083253037962127E-02 -5.7061840510577860E-02 -5.7040424524327837E-02 -5.7019005085554797E-02 -5.6997582201414231E-02 -5.6976155879019358E-02 -5.6954726124517976E-02 -5.6933292943677348E-02 -5.6911856342343178E-02 -5.6890416326445994E-02 -5.6868972902105908E-02 -5.6847526075976984E-02 -5.6826075854572194E-02 -5.6804622242310615E-02 -5.6783165242594774E-02 -5.6761704862179865E-02 -5.6740241112433920E-02 -5.6718774002979977E-02 -5.6697303535453110E-02 -5.6675829710130562E-02 -5.6654352534270230E-02 -5.6632872019829014E-02 -5.6611388175391436E-02 -5.6589901003377525E-02 -5.6568410506363416E-02 -5.6546916691004007E-02 -5.6525419565240577E-02 -5.6503919136593334E-02 -5.6482415412209497E-02 -5.6460908398440209E-02 -5.6439398099810183E-02 -5.6417884520882214E-02 -5.6396367668292584E-02 -5.6374847549542383E-02 -5.6353324171646187E-02 -5.6331797541064210E-02 -5.6310267663495082E-02 -5.6288734542378920E-02 -5.6267198181362998E-02 -5.6245658590247959E-02 -5.6224115782149281E-02 -5.6202569764460780E-02 -5.6181020536161225E-02 -5.6159468097711225E-02 -5.6137912458438445E-02 -5.6116353629692403E-02 -5.6094791619214900E-02 -5.6073226432137753E-02 -5.6051658073296269E-02 -5.6030086547072692E-02 -5.6008511858388822E-02 -5.5986934015435280E-02 -5.5965353027391536E-02 -5.5943768900661398E-02 -5.5922181639059890E-02 -5.5900591247291971E-02 -5.5878997732529037E-02 -5.5857401102263581E-02 -5.5835801363560894E-02 -5.5814198523277354E-02 -5.5792592587783255E-02 -5.5770983562865174E-02 -5.5749371454399149E-02 -5.5727756268672268E-02 -5.5706138011979642E-02 -5.5684516689814133E-02 -5.5662892307221573E-02 -5.5641264871023804E-02 -5.5619634390817546E-02 -5.5598000875105823E-02 -5.5576364326480665E-02 -5.5554724746350294E-02 -5.5533082142896512E-02 -5.5511436529484044E-02 -5.5489787915275215E-02 -5.5468136300637662E-02 -5.5446481686251374E-02 -5.5424824080999704E-02 -5.5403163496600648E-02 -5.5381499940435605E-02 -5.5359833415577347E-02 -5.5338163926221380E-02 -5.5316491480054582E-02 -5.5294816085078830E-02 -5.5273137747174433E-02 -5.5251456471232932E-02 -5.5229772263716718E-02 -5.5208085133109208E-02 -5.5186395087537768E-02 -5.5164702133394021E-02 -5.5143006276562073E-02 -5.5121307521541860E-02 -5.5099605871994063E-02 -5.5077901334274260E-02 -5.5056193919232742E-02 -5.5034483636730969E-02 -5.5012770489907138E-02 -5.4991054480226731E-02 -5.4969335614520602E-02 -5.4947613904002726E-02 -5.4925889357679530E-02 -5.4904161979493701E-02 -5.4882431773123352E-02 -5.4860698744799041E-02 -5.4838962901783077E-02 -5.4817224251944026E-02 -5.4795482803787161E-02 -5.4773738564792333E-02 -5.4751991539419023E-02 -5.4730241731838353E-02 -5.4708489148400458E-02 -5.4686733796580192E-02 -5.4664975683623829E-02 -5.4643214816452561E-02 -5.4621451201755065E-02 -5.4599684845421902E-02 -5.4577915753192117E-02 -5.4556143931286057E-02 -5.4534369386257657E-02 -5.4512592125452126E-02 -5.4490812157604263E-02 -5.4469029490865191E-02 -5.4447244129672695E-02 -5.4425456077465170E-02 -5.4403665341042823E-02 -5.4381871930129985E-02 -5.4360075852604592E-02 -5.4338277111840826E-02 -5.4316475711332746E-02 -5.4294671659799953E-02 -5.4272864968051310E-02 -5.4251055643490566E-02 -5.4229243689684910E-02 -5.4207429110850844E-02 -5.4185611913822138E-02 -5.4163792105979769E-02 -5.4141969695155376E-02 -5.4120144689411523E-02 -5.4098317095870124E-02 -5.4076486920283086E-02 -5.4054654168285636E-02 -5.4032818845476574E-02 -5.4010980957554182E-02 -5.3989140511686615E-02 -5.3967297516093943E-02 -5.3945451978531733E-02 -5.3923603905834928E-02 -5.3901753304601452E-02 -5.3879900180687300E-02 -5.3858044539731871E-02 -5.3836186388123333E-02 -5.3814325732944382E-02 -5.3792462581208768E-02 -5.3770596939693945E-02 -5.3748728815138473E-02 -5.3726858214258606E-02 -5.3704985143767370E-02 -5.3683109610599043E-02 -5.3661231621952556E-02 -5.3639351184640048E-02 -5.3617468304150137E-02 -5.3595582985868209E-02 -5.3573695236920481E-02 -5.3551805065456239E-02 -5.3529912479363687E-02 -5.3508017486106070E-02 -5.3486120092426613E-02 -5.3464220302059377E-02 -5.3442318118266170E-02 -5.3420413549579153E-02 -5.3398506608536712E-02 -5.3376597304145235E-02 -5.3354685638085438E-02 -5.3332771612315109E-02 -5.3310855235639672E-02 -5.3288936519211967E-02 -5.3267015470547595E-02 -5.3245092093570076E-02 -5.3223166393539911E-02 -5.3201238379668558E-02 -5.3179308061217664E-02 -5.3157375442634207E-02 -5.3135440526168268E-02 -5.3113503318806439E-02 -5.3091563833586639E-02 -5.3069622081135394E-02 -5.3047678062180741E-02 -5.3025731776116809E-02 -5.3003783231886696E-02 -5.2981832444369582E-02 -5.2959879423259922E-02 -5.2937924169545743E-02 -5.2915966684982954E-02 -5.2894006978807154E-02 -5.2872045062218841E-02 -5.2850080942442069E-02 -5.2828114623470736E-02 -5.2806146110760614E-02 -5.2784175413118417E-02 -5.2762202539301209E-02 -5.2740227494977719E-02 -5.2718250284692729E-02 -5.2696270915202195E-02 -5.2674289395586743E-02 -5.2652305733862634E-02 -5.2630319934708771E-02 -5.2608332002678955E-02 -5.2586341946368943E-02 -5.2564349776385598E-02 -5.2542355500230530E-02 -5.2520359121171367E-02 -5.2498360643262514E-02 -5.2476360074683870E-02 -5.2454357424433745E-02 -5.2432352699561161E-02 -5.2410345905819743E-02 -5.2388337049968280E-02 -5.2366326140575993E-02 -5.2344313185853829E-02 -5.2322298191257756E-02 -5.2300281161501275E-02 -5.2278262103646389E-02 -5.2256241026785326E-02 -5.2234217938673048E-02 -5.2212192843831016E-02 -5.2190165746954287E-02 -5.2168136657040828E-02 -5.2146105584763534E-02 -5.2124072537058419E-02 -5.2102037516678329E-02 -5.2080000527939763E-02 -5.2057961580593691E-02 -5.2035920685001784E-02 -5.2013877847555900E-02 -5.1991833072498855E-02 -5.1969786365814105E-02 -5.1947737736031174E-02 -5.1925687191466778E-02 -5.1903634738762514E-02 -5.1881580384174064E-02 -5.1859524134497965E-02 -5.1837465996912857E-02 -5.1815405978156377E-02 -5.1793344084122839E-02 -5.1771280321164369E-02 -5.1749214698641910E-02 -5.1727147226742182E-02 -5.1705077911727695E-02 -5.1683006756246951E-02 -5.1660933765106977E-02 -5.1638858948762897E-02 -5.1616782317739821E-02 -5.1594703876758949E-02 -5.1572623628069643E-02 -5.1550541578230545E-02 -5.1528457738940880E-02 -5.1506372120633970E-02 -5.1484284728627573E-02 -5.1462195567362153E-02 -5.1440104642979309E-02 -5.1418011962623723E-02 -5.1395917533729282E-02 -5.1373821364155463E-02 -5.1351723461597179E-02 -5.1329623832871790E-02 -5.1307522484556792E-02 -5.1285419423228173E-02 -5.1263314655463944E-02 -5.1241208188251078E-02 -5.1219100029396301E-02 -5.1196990186717022E-02 -5.1174878667519158E-02 -5.1152765478863250E-02 -5.1130650626494169E-02 -5.1108534114869063E-02 -5.1086415950144848E-02 -5.1064296143101075E-02 -5.1042174704672427E-02 -5.1020051641014010E-02 -5.0997926956050446E-02 -5.0975800655999853E-02 -5.0953672750002760E-02 -5.0931543246406211E-02 -5.0909412150116011E-02 -5.0887279465604403E-02 -5.0865145200915736E-02 -5.0843009366299423E-02 -5.0820871969945260E-02 -5.0798733016609698E-02 -5.0776592511260307E-02 -5.0754450461351235E-02 -5.0732306875064623E-02 -5.0710161760559716E-02 -5.0688015125971084E-02 -5.0665866978388936E-02 -5.0643717322669694E-02 -5.0621566163919385E-02 -5.0599413510645404E-02 -5.0577259372607757E-02 -5.0555103757737786E-02 -5.0532946672053929E-02 -5.0510788121786679E-02 -5.0488628114018400E-02 -5.0466466655888241E-02 -5.0444303753735452E-02 -5.0422139413526953E-02 -5.0399973642815385E-02 -5.0377806451295283E-02 -5.0355637847872593E-02 -5.0333467837914071E-02 -5.0311296426128020E-02 -5.0289123619343692E-02 -5.0266949425801961E-02 -5.0244773853576577E-02 -5.0222596910404239E-02 -5.0200418603795156E-02 -5.0178238940288437E-02 -5.0156057926172483E-02 -5.0133875568718150E-02 -5.0111691876041163E-02 -5.0089506855828463E-02 -5.0067320514723068E-02 -5.0045132859236494E-02 -5.0022943895974718E-02 -5.0000753631600260E-02 -4.9978562073254372E-02 -4.9956369228610360E-02 -4.9934175105404474E-02 -4.9911979711479926E-02 -4.9889783054590325E-02 -4.9867585141461467E-02 -4.9845385978273801E-02 -4.9823185572031414E-02 -4.9800983930928980E-02 -4.9778781062877406E-02 -4.9756576974268087E-02 -4.9734371671211010E-02 -4.9712165161181598E-02 -4.9689957452615612E-02 -4.9667748552987161E-02 -4.9645538467938406E-02 -4.9623327203529487E-02 -4.9601114769175572E-02 -4.9578901175213720E-02 -4.9556686427814335E-02 -4.9534470529333838E-02 -4.9512253484642811E-02 -4.9490035305108343E-02 -4.9467816002253466E-02 -4.9445595581577344E-02 -4.9423374046027813E-02 -4.9401151402884230E-02 -4.9378927664562422E-02 -4.9356702841329807E-02 -4.9334476935516347E-02 -4.9312249948476522E-02 -4.9290021887996673E-02 -4.9267792765587508E-02 -4.9245562591209484E-02 -4.9223331372380413E-02 -4.9201099115978003E-02 -4.9178865826995002E-02 -4.9156631510155889E-02 -4.9134396173728230E-02 -4.9112159828636315E-02 -4.9089922482870668E-02 -4.9067684138448787E-02 -4.9045444798262339E-02 -4.9023204474431606E-02 -4.9000963182080949E-02 -4.8978720928971924E-02 -4.8956477715681727E-02 -4.8934233545049999E-02 -4.8911988426623525E-02 -4.8889742370752290E-02 -4.8867495385553357E-02 -4.8845247478072465E-02 -4.8822998655118008E-02 -4.8800748923207814E-02 -4.8778498289077536E-02 -4.8756246760286025E-02 -4.8733994344577737E-02 -4.8711741049768963E-02 -4.8689486883711622E-02 -4.8667231853637798E-02 -4.8644975965768167E-02 -4.8622719226555144E-02 -4.8600461643966676E-02 -4.8578203226317743E-02 -4.8555943980408488E-02 -4.8533683911827497E-02 -4.8511423027492055E-02 -4.8489161337219089E-02 -4.8466898850513321E-02 -4.8444635572586908E-02 -4.8422371507147850E-02 -4.8400106661819237E-02 -4.8377841048290626E-02 -4.8355574676443427E-02 -4.8333307550557300E-02 -4.8311039674497500E-02 -4.8288771056942965E-02 -4.8266501708934401E-02 -4.8244231637784268E-02 -4.8221960845782931E-02 -4.8199689336806059E-02 -4.8177417121974410E-02 -4.8155144213767140E-02 -4.8132870620621070E-02 -4.8110596348291693E-02 -4.8088321402287366E-02 -4.8066045787770337E-02 -4.8043769510514783E-02 -4.8021492579535988E-02 -4.7999215004704540E-02 -4.7976936793094269E-02 -4.7954657949391931E-02 -4.7932378480365370E-02 -4.7910098397688630E-02 -4.7887817712581666E-02 -4.7865536428599628E-02 -4.7843254546332932E-02 -4.7820972072276605E-02 -4.7798689019459321E-02 -4.7776405399431628E-02 -4.7754121218283978E-02 -4.7731836481219383E-02 -4.7709551194690426E-02 -4.7687265365829130E-02 -4.7664979001781807E-02 -4.7642692109705335E-02 -4.7620404697153423E-02 -4.7598116773269986E-02 -4.7575828347385843E-02 -4.7553539426031813E-02 -4.7531250013775124E-02 -4.7508960116493720E-02 -4.7486669742572353E-02 -4.7464378900364756E-02 -4.7442087596591423E-02 -4.7419795837573289E-02 -4.7397503632533616E-02 -4.7375210993332736E-02 -4.7352917928864126E-02 -4.7330624440573454E-02 -4.7308330529968537E-02 -4.7286036207115759E-02 -4.7263741485725201E-02 -4.7241446374766308E-02 -4.7219150877615114E-02 -4.7196854998783101E-02 -4.7174558747476211E-02 -4.7152262133611816E-02 -4.7129965164756600E-02 -4.7107667847112150E-02 -4.7085370186749617E-02 -4.7063072189567359E-02 -4.7040773862248066E-02 -4.7018475214921106E-02 -4.6996176258388964E-02 -4.6973876999756414E-02 -4.6951577443357831E-02 -4.6929277594672830E-02 -4.6906977461581484E-02 -4.6884677052273435E-02 -4.6862376375098318E-02 -4.6840075438455323E-02 -4.6817774250571188E-02 -4.6795472819503629E-02 -4.6773171152468693E-02 -4.6750869254510635E-02 -4.6728567130698263E-02 -4.6706264789043390E-02 -4.6683962238929809E-02 -4.6661659488932840E-02 -4.6639356546605670E-02 -4.6617053419140082E-02 -4.6594750112700652E-02 -4.6572446633419695E-02 -4.6550142989512953E-02 -4.6527839190464493E-02 -4.6505535244443043E-02 -4.6483231157455507E-02 -4.6460926935628449E-02 -4.6438622586557100E-02 -4.6416318118241900E-02 -4.6394013538365253E-02 -4.6371708854355383E-02 -4.6349404073688899E-02 -4.6327099203959513E-02 -4.6304794252760240E-02 -4.6282489227586265E-02 -4.6260184135903173E-02 -4.6237878985372682E-02 -4.6215573783858474E-02 -4.6193268538879492E-02 -4.6170963256967644E-02 -4.6148657944563694E-02 -4.6126352608784421E-02 -4.6104047257105076E-02 -4.6081741897674604E-02 -4.6059436539535897E-02 -4.6037131191230457E-02 -4.6014825859206257E-02 -4.5992520549514103E-02 -4.5970215269269518E-02 -4.5947910026290256E-02 -4.5925604828476504E-02 -4.5903299683849291E-02 -4.5880994600085434E-02 -4.5858689583087482E-02 -4.5836384638383569E-02 -4.5814079774596235E-02 -4.5791775002974315E-02 -4.5769470332698861E-02 -4.5747165768090244E-02 -4.5724861313434166E-02 -4.5702556977267252E-02 -4.5680252769789674E-02 -4.5657948698798807E-02 -4.5635644769447564E-02 -4.5613340987943007E-02 -4.5591037364045461E-02 -4.5568733907699208E-02 -4.5546430624448797E-02 -4.5524127517544845E-02 -4.5501824594182193E-02 -4.5479521867184333E-02 -4.5457219348049145E-02 -4.5434917041277931E-02 -4.5412614949827020E-02 -4.5390313079265845E-02 -4.5368011437015028E-02 -4.5345710032286844E-02 -4.5323408877524944E-02 -4.5301107983985518E-02 -4.5278807354706754E-02 -4.5256506990322930E-02 -4.5234206897948902E-02 -4.5211907090569478E-02 -4.5189607579419644E-02 -4.5167308370993982E-02 -4.5145009470964531E-02 -4.5122710884125429E-02 -4.5100412615003936E-02 -4.5078114671842563E-02 -4.5055817067228027E-02 -4.5033519811997560E-02 -4.5011222910594520E-02 -4.4988926366634686E-02 -4.4966630188241645E-02 -4.4944334386089461E-02 -4.4922038968213819E-02 -4.4899743938615788E-02 -4.4877449302075552E-02 -4.4855155068148043E-02 -4.4832861247535417E-02 -4.4810567849054114E-02 -4.4788274880105533E-02 -4.4765982347311870E-02 -4.4743690255829686E-02 -4.4721398611092512E-02 -4.4699107421112168E-02 -4.4676816694825629E-02 -4.4654526441263373E-02 -4.4632236669542462E-02 -4.4609947387606839E-02 -4.4587658600358064E-02 -4.4565370312615094E-02 -4.4543082532346789E-02 -4.4520795268983018E-02 -4.4498508531162849E-02 -4.4476222326530535E-02 -4.4453936662270342E-02 -4.4431651544199244E-02 -4.4409366978139381E-02 -4.4387082973167201E-02 -4.4364799540322748E-02 -4.4342516688266734E-02 -4.4320234421781131E-02 -4.4297952745728425E-02 -4.4275671666958442E-02 -4.4253391193019985E-02 -4.4231111333468916E-02 -4.4208832099441500E-02 -4.4186553499439542E-02 -4.4164275536338636E-02 -4.4141998213317248E-02 -4.4119721539829307E-02 -4.4097445527590075E-02 -4.4075170184968177E-02 -4.4052895516894057E-02 -4.4030621529333729E-02 -4.4008348231554251E-02 -4.3986075633091273E-02 -4.3963803740959463E-02 -4.3941532560928018E-02 -4.3919262099684421E-02 -4.3896992365145146E-02 -4.3874723365233632E-02 -4.3852455107587250E-02 -4.3830187599751116E-02 -4.3807920848959035E-02 -4.3785654862252235E-02 -4.3763389647568339E-02 -4.3741125214390268E-02 -4.3718861571636028E-02 -4.3696598724677072E-02 -4.3674336677946499E-02 -4.3652075438586325E-02 -4.3629815016030304E-02 -4.3607555419228478E-02 -4.3585296655882566E-02 -4.3563038733346222E-02 -4.3540781657784904E-02 -4.3518525434959758E-02 -4.3496270072856044E-02 -4.3474015581888889E-02 -4.3451761971711550E-02 -4.3429509249350726E-02 -4.3407257421185293E-02 -4.3385006492099663E-02 -4.3362756466253975E-02 -4.3340507351479644E-02 -4.3318259160796610E-02 -4.3296011905559956E-02 -4.3273765588975097E-02 -4.3251520212762469E-02 -4.3229275785559233E-02 -4.3207032320794557E-02 -4.3184789828675012E-02 -4.3162548313324778E-02 -4.3140307778876487E-02 -4.3118068232963234E-02 -4.3095829684321234E-02 -4.3073592140617026E-02 -4.3051355608555254E-02 -4.3029120095653524E-02 -4.3006885611463611E-02 -4.2984652165301382E-02 -4.2962419762632958E-02 -4.2940188407347271E-02 -4.2917958106659923E-02 -4.2895728871660273E-02 -4.2873500712422428E-02 -4.2851273635096859E-02 -4.2829047645211754E-02 -4.2806822749852258E-02 -4.2784598956995316E-02 -4.2762376274629567E-02 -4.2740154710745333E-02 -4.2717934272921851E-02 -4.2695714966988402E-02 -4.2673496798538386E-02 -4.2651279776426909E-02 -4.2629063911912880E-02 -4.2606849213908393E-02 -4.2584635686626009E-02 -4.2562423334485261E-02 -4.2540212166200908E-02 -4.2518002191896401E-02 -4.2495793419238030E-02 -4.2473585853536465E-02 -4.2451379501132466E-02 -4.2429174371256831E-02 -4.2406970473291269E-02 -4.2384767814234135E-02 -4.2362566399989116E-02 -4.2340366237184145E-02 -4.2318167333350906E-02 -4.2295969696368216E-02 -4.2273773335109018E-02 -4.2251578258486980E-02 -4.2229384473565279E-02 -4.2207191986288424E-02 -4.2185000803350199E-02 -4.2162810932669825E-02 -4.2140622382167550E-02 -4.2118435159264778E-02 -4.2096249271270897E-02 -4.2074064725968273E-02 -4.2051881531508288E-02 -4.2029699695217887E-02 -4.2007519222681873E-02 -4.1985340119875633E-02 -4.1963162396520204E-02 -4.1940986063626555E-02 -4.1918811129016791E-02 -4.1896637597257480E-02 -4.1874465473481080E-02 -4.1852294764780237E-02 -4.1830125478857672E-02 -4.1807957625732931E-02 -4.1785791216491883E-02 -4.1763626258533373E-02 -4.1741462754390404E-02 -4.1719300707994372E-02 -4.1697140129619926E-02 -4.1674981030680548E-02 -4.1652823418888561E-02 -4.1630667299558798E-02 -4.1608512678916215E-02 -4.1586359564809203E-02 -4.1564207965246881E-02 -4.1542057888248371E-02 -4.1519909341751107E-02 -4.1497762332236385E-02 -4.1475616864968402E-02 -4.1453472947059859E-02 -4.1431330589831845E-02 -4.1409189804178494E-02 -4.1387050594390788E-02 -4.1364912962276172E-02 -4.1342776915073792E-02 -4.1320642465926621E-02 -4.1298509626069776E-02 -4.1276378400240038E-02 -4.1254248792321417E-02 -4.1232120809281056E-02 -4.1209994459719859E-02 -4.1187869751711334E-02 -4.1165746692568041E-02 -4.1143625289614329E-02 -4.1121505550445386E-02 -4.1099387482711906E-02 -4.1077271093923451E-02 -4.1055156391493701E-02 -4.1033043383033721E-02 -4.1010932076517660E-02 -4.0988822479688637E-02 -4.0966714598866805E-02 -4.0944608439997456E-02 -4.0922504010798007E-02 -4.0900401320571218E-02 -4.0878300377922394E-02 -4.0856201189659269E-02 -4.0834103762211256E-02 -4.0812008101179034E-02 -4.0789914211920415E-02 -4.0767822103362196E-02 -4.0745731788555319E-02 -4.0723643278117928E-02 -4.0701556574251493E-02 -4.0679471678174761E-02 -4.0657388597780286E-02 -4.0635307344727069E-02 -4.0613227928876179E-02 -4.0591150357337999E-02 -4.0569074636863760E-02 -4.0547000773636488E-02 -4.0524928773834311E-02 -4.0502858645677639E-02 -4.0480790398882506E-02 -4.0458724041621499E-02 -4.0436659579000181E-02 -4.0414597016085033E-02 -4.0392536359721662E-02 -4.0370477617457073E-02 -4.0348420798404075E-02 -4.0326365913163992E-02 -4.0304312970774504E-02 -4.0282261976130704E-02 -4.0260212933830634E-02 -4.0238165851205925E-02 -4.0216120736835267E-02 -4.0194077598454989E-02 -4.0172036442757075E-02 -4.0149997277066529E-02 -4.0127960111073065E-02 -4.0105924954545048E-02 -4.0083891812723586E-02 -4.0061860688153018E-02 -4.0039831586708166E-02 -4.0017804519624979E-02 -3.9995779497644109E-02 -3.9973756527086464E-02 -3.9951735613147819E-02 -3.9929716763018201E-02 -3.9907699985448589E-02 -3.9885685288107015E-02 -3.9863672676327219E-02 -3.9841662155870490E-02 -3.9819653736884376E-02 -3.9797647430977155E-02 -3.9775643245143870E-02 -3.9753641181699724E-02 -3.9731641244989839E-02 -3.9709643445478345E-02 -3.9687647794278372E-02 -3.9665654299276189E-02 -3.9643662966732877E-02 -3.9621673802041797E-02 -3.9599686809475641E-02 -3.9577701994875397E-02 -3.9555719370069409E-02 -3.9533738947696115E-02 -3.9511760733945217E-02 -3.9489784730872474E-02 -3.9467810943524508E-02 -3.9445839382140656E-02 -3.9423870056674117E-02 -3.9401902973225295E-02 -3.9379938136886394E-02 -3.9357975555561781E-02 -3.9336015239500650E-02 -3.9314057197110182E-02 -3.9292101432553621E-02 -3.9270147950200028E-02 -3.9248196759524817E-02 -3.9226247871946958E-02 -3.9204301295691746E-02 -3.9182357035531259E-02 -3.9160415096447604E-02 -3.9138475484540754E-02 -3.9116538206428152E-02 -3.9094603271560245E-02 -3.9072670690831902E-02 -3.9050740472465879E-02 -3.9028812620941662E-02 -3.9006887141189578E-02 -3.8984964040988695E-02 -3.8963043328758648E-02 -3.8941125012207936E-02 -3.8919209098557693E-02 -3.8897295595283182E-02 -3.8875384510337174E-02 -3.8853475851482563E-02 -3.8831569625222384E-02 -3.8809665837710609E-02 -3.8787764496276675E-02 -3.8765865609294646E-02 -3.8743969184409574E-02 -3.8722075227451629E-02 -3.8700183744393511E-02 -3.8678294744085254E-02 -3.8656408236528682E-02 -3.8634524228960285E-02 -3.8612642725434999E-02 -3.8590763731252781E-02 -3.8568887256174633E-02 -3.8547013310395430E-02 -3.8525141899805909E-02 -3.8503273027920983E-02 -3.8481406701460399E-02 -3.8459542931942620E-02 -3.8437681729912417E-02 -3.8415823100190795E-02 -3.8393967046400898E-02 -3.8372113576417330E-02 -3.8350262701212737E-02 -3.8328414429041689E-02 -3.8306568762771352E-02 -3.8284725705743629E-02 -3.8262885267444195E-02 -3.8241047459367641E-02 -3.8219212290022224E-02 -3.8197379765084152E-02 -3.8175549890454033E-02 -3.8153722672884763E-02 -3.8131898119326733E-02 -3.8110076237224462E-02 -3.8088257034251408E-02 -3.8066440518106363E-02 -3.8044626696517390E-02 -3.8022815577015340E-02 -3.8001007166460619E-02 -3.7979201471542441E-02 -3.7957398498630258E-02 -3.7935598253918866E-02 -3.7913800744767030E-02 -3.7892005980378951E-02 -3.7870213969655057E-02 -3.7848424719389241E-02 -3.7826638235796115E-02 -3.7804854525311717E-02 -3.7783073594548418E-02 -3.7761295450577888E-02 -3.7739520101409400E-02 -3.7717747554961933E-02 -3.7695977817904382E-02 -3.7674210896470557E-02 -3.7652446797685764E-02 -3.7630685529374458E-02 -3.7608927099351985E-02 -3.7587171515313302E-02 -3.7565418784864357E-02 -3.7543668915041732E-02 -3.7521921912593917E-02 -3.7500177783993720E-02 -3.7478436535358144E-02 -3.7456698173435672E-02 -3.7434962707345601E-02 -3.7413230146518581E-02 -3.7391500497784703E-02 -3.7369773766305452E-02 -3.7348049957545877E-02 -3.7326329077529523E-02 -3.7304611133053570E-02 -3.7282896134404324E-02 -3.7261184092663616E-02 -3.7239475014524341E-02 -3.7217768903035207E-02 -3.7196065762769924E-02 -3.7174365601906706E-02 -3.7152668429014844E-02 -3.7130974252078293E-02 -3.7109283078808911E-02 -3.7087594915953537E-02 -3.7065909769224831E-02 -3.7044227645350446E-02 -3.7022548554159637E-02 -3.7000872505515141E-02 -3.6979199504552904E-02 -3.6957529553989128E-02 -3.6935862659794157E-02 -3.6914198832478047E-02 -3.6892538081683988E-02 -3.6870880412391352E-02 -3.6849225828721723E-02 -3.6827574338268193E-02 -3.6805925950988264E-02 -3.6784280675518893E-02 -3.6762638518038432E-02 -3.6740999484614581E-02 -3.6719363582076919E-02 -3.6697730817487985E-02 -3.6676101197643654E-02 -3.6654474729104471E-02 -3.6632851418679002E-02 -3.6611231273779368E-02 -3.6589614302018680E-02 -3.6568000511814726E-02 -3.6546389911840213E-02 -3.6524782508083789E-02 -3.6503178303468227E-02 -3.6481577302690929E-02 -3.6459979516508978E-02 -3.6438384956361806E-02 -3.6416793628869452E-02 -3.6395205537976420E-02 -3.6373620689480073E-02 -3.6352039091956986E-02 -3.6330460753797283E-02 -3.6308885681681211E-02 -3.6287313881875338E-02 -3.6265745361090923E-02 -3.6244180126362081E-02 -3.6222618184517441E-02 -3.6201059541977144E-02 -3.6179504205333557E-02 -3.6157952182402350E-02 -3.6136403481370920E-02 -3.6114858109307160E-02 -3.6093316072225511E-02 -3.6071777376784457E-02 -3.6050242031369174E-02 -3.6028710044308743E-02 -3.6007181421469435E-02 -3.5985656167636847E-02 -3.5964134289295575E-02 -3.5942615795002388E-02 -3.5921100692879140E-02 -3.5899588989173337E-02 -3.5878080689897777E-02 -3.5856575802721745E-02 -3.5835074336285334E-02 -3.5813576297801721E-02 -3.5792081692219181E-02 -3.5770590524855310E-02 -3.5749102803572561E-02 -3.5727618536864195E-02 -3.5706137731982363E-02 -3.5684660395216339E-02 -3.5663186533101035E-02 -3.5641716152726426E-02 -3.5620249261113485E-02 -3.5598785864457319E-02 -3.5577325968731803E-02 -3.5555869581915589E-02 -3.5534416713995313E-02 -3.5512967373496657E-02 -3.5491521564765871E-02 -3.5470079291707431E-02 -3.5448640560329890E-02 -3.5427205377694823E-02 -3.5405773751656974E-02 -3.5384345691087733E-02 -3.5362921204574425E-02 -3.5341500299440616E-02 -3.5320082982557836E-02 -3.5298669258864851E-02 -3.5277259132093702E-02 -3.5255852608155537E-02 -3.5234449696647414E-02 -3.5213050407024708E-02 -3.5191654746366700E-02 -3.5170262721007442E-02 -3.5148874336761914E-02 -3.5127489599020283E-02 -3.5106108514026735E-02 -3.5084731089923528E-02 -3.5063357334903185E-02 -3.5041987255853745E-02 -3.5020620859152592E-02 -3.4999258151433940E-02 -3.4977899139607596E-02 -3.4956543830551252E-02 -3.4935192231011165E-02 -3.4913844347726715E-02 -3.4892500187586363E-02 -3.4871159757549730E-02 -3.4849823064265879E-02 -3.4828490113955474E-02 -3.4807160913303138E-02 -3.4785835470904830E-02 -3.4764513795540318E-02 -3.4743195892516517E-02 -3.4721881764804251E-02 -3.4700571418072292E-02 -3.4679264862893570E-02 -3.4657962109270912E-02 -3.4636663161627217E-02 -3.4615368022793469E-02 -3.4594076699429259E-02 -3.4572789201562322E-02 -3.4551505538380885E-02 -3.4530225716838711E-02 -3.4508949743339581E-02 -3.4487677622672484E-02 -3.4466409359007306E-02 -3.4445144958573204E-02 -3.4423884429939773E-02 -3.4402627781320992E-02 -3.4381375019435813E-02 -3.4360126150710275E-02 -3.4338881181530556E-02 -3.4317640118279299E-02 -3.4296402968311969E-02 -3.4275169740411511E-02 -3.4253940442584417E-02 -3.4232715079147637E-02 -3.4211493653704197E-02 -3.4190276173171885E-02 -3.4169062646859927E-02 -3.4147853082555225E-02 -3.4126647485037784E-02 -3.4105445859299047E-02 -3.4084248213386230E-02 -3.4063054556290807E-02 -3.4041864894703511E-02 -3.4020679233161780E-02 -3.3999497577376393E-02 -3.3978319936204225E-02 -3.3957146318500067E-02 -3.3935976729445254E-02 -3.3914811172607667E-02 -3.3893649653667486E-02 -3.3872492180867193E-02 -3.3851338762570231E-02 -3.3830189407032647E-02 -3.3809044122249242E-02 -3.3787902913713683E-02 -3.3766765785449494E-02 -3.3745632742776456E-02 -3.3724503793071479E-02 -3.3703378943743915E-02 -3.3682258201550991E-02 -3.3661141573080894E-02 -3.3640029065107942E-02 -3.3618920684549407E-02 -3.3597816438203511E-02 -3.3576716332618564E-02 -3.3555620374450430E-02 -3.3534528571180805E-02 -3.3513440930499148E-02 -3.3492357457850543E-02 -3.3471278156445863E-02 -3.3450203031429059E-02 -3.3429132093386257E-02 -3.3408065352992351E-02 -3.3387002814285215E-02 -3.3365944478194749E-02 -3.3344890350554490E-02 -3.3323840443532801E-02 -3.3302794767975999E-02 -3.3281753328523095E-02 -3.3260716128573418E-02 -3.3239683173176771E-02 -3.3218654468443819E-02 -3.3197630021353369E-02 -3.3176609840302858E-02 -3.3155593933343920E-02 -3.3134582306232105E-02 -3.3113574964112380E-02 -3.3092571913371345E-02 -3.3071573161414652E-02 -3.3050578715251556E-02 -3.3029588580962804E-02 -3.3008602764408972E-02 -3.2987621270818016E-02 -3.2966644105265133E-02 -3.2945671275339837E-02 -3.2924702791297576E-02 -3.2903738661912388E-02 -3.2882778891333141E-02 -3.2861823483209499E-02 -3.2840872444068560E-02 -3.2819925781911112E-02 -3.2798983503652374E-02 -3.2778045614703197E-02 -3.2757112120661493E-02 -3.2736183028258529E-02 -3.2715258344518210E-02 -3.2694338076726885E-02 -3.2673422232335179E-02 -3.2652510817599387E-02 -3.2631603836647503E-02 -3.2610701293993016E-02 -3.2589803197255088E-02 -3.2568909555001198E-02 -3.2548020374947730E-02 -3.2527135664062991E-02 -3.2506255428589821E-02 -3.2485379673142238E-02 -3.2464508402365269E-02 -3.2443641622724881E-02 -3.2422779341462711E-02 -3.2401921565908952E-02 -3.2381068303490156E-02 -3.2360219560862755E-02 -3.2339375342295903E-02 -3.2318535651928840E-02 -3.2297700497040525E-02 -3.2276869886626945E-02 -3.2256043828271221E-02 -3.2235222327468664E-02 -3.2214405389639579E-02 -3.2193593020575360E-02 -3.2172785226223133E-02 -3.2151982013350219E-02 -3.2131183389309988E-02 -3.2110389360838001E-02 -3.2089599933473961E-02 -3.2068815112843228E-02 -3.2048034905782015E-02 -3.2027259319520794E-02 -3.2006488360850342E-02 -3.1985722036149689E-02 -3.1964960351051216E-02 -3.1944203309368861E-02 -3.1923450915282647E-02 -3.1902703177801292E-02 -3.1881960107995509E-02 -3.1861221712714938E-02 -3.1840487993726185E-02 -3.1819758954230247E-02 -3.1799034603161552E-02 -3.1778314950254662E-02 -3.1757600001273811E-02 -3.1736889759658542E-02 -3.1716184230556485E-02 -3.1695483421817335E-02 -3.1674787341070341E-02 -3.1654095993939167E-02 -3.1633409385595321E-02 -3.1612727522730505E-02 -3.1592050413196071E-02 -3.1571378063732870E-02 -3.1550710478773454E-02 -3.1530047662806739E-02 -3.1509389622312804E-02 -3.1488736364516455E-02 -3.1468087896911440E-02 -3.1447444227254491E-02 -3.1426805362026175E-02 -3.1406171304277065E-02 -3.1385542057028377E-02 -3.1364917627637816E-02 -3.1344298025514632E-02 -3.1323683258180572E-02 -3.1303073330726044E-02 -3.1282468248479960E-02 -3.1261868018178818E-02 -3.1241272646670471E-02 -3.1220682138535159E-02 -3.1200096496964553E-02 -3.1179515728329329E-02 -3.1158939844302097E-02 -3.1138368855079205E-02 -3.1117802761478033E-02 -3.1097241562039454E-02 -3.1076685263597179E-02 -3.1056133879745904E-02 -3.1035587420589428E-02 -3.1015045888253320E-02 -3.0994509284622912E-02 -3.0973977616709378E-02 -3.0953450893443077E-02 -3.0932929121201717E-02 -3.0912412303667171E-02 -3.0891900445521606E-02 -3.0871393554669606E-02 -3.0850891639227555E-02 -3.0830394704164835E-02 -3.0809902752883297E-02 -3.0789415791434550E-02 -3.0768933829496133E-02 -3.0748456875657446E-02 -3.0727984933376272E-02 -3.0707518005167675E-02 -3.0687056096980799E-02 -3.0666599217065452E-02 -3.0646147372707773E-02 -3.0625700569416003E-02 -3.0605258812686581E-02 -3.0584822108882814E-02 -3.0564390464579632E-02 -3.0543963885189006E-02 -3.0523542375114381E-02 -3.0503125939617879E-02 -3.0482714586024546E-02 -3.0462308321796198E-02 -3.0441907153334120E-02 -3.0421511086574635E-02 -3.0401120126943633E-02 -3.0380734279296242E-02 -3.0360353548811128E-02 -3.0339977941749190E-02 -3.0319607464520022E-02 -3.0299242122985966E-02 -3.0278881922722389E-02 -3.0258526870074985E-02 -3.0238176972510702E-02 -3.0217832237168812E-02 -3.0197492669488776E-02 -3.0177158274440268E-02 -3.0156829056516000E-02 -3.0136505019884435E-02 -3.0116186170640172E-02 -3.0095872518520989E-02 -3.0075564072527653E-02 -3.0055260835402015E-02 -3.0034962807984993E-02 -3.0014669995837271E-02 -2.9994382408887708E-02 -2.9974100055728748E-02 -2.9953822941240816E-02 -2.9933551069743828E-02 -2.9913284445580595E-02 -2.9893023073180036E-02 -2.9872766959426859E-02 -2.9852516114137879E-02 -2.9832270545487899E-02 -2.9812030255697820E-02 -2.9791795246207762E-02 -2.9771565522980416E-02 -2.9751341094621159E-02 -2.9731121968459447E-02 -2.9710908149801003E-02 -2.9690699644070274E-02 -2.9670496457973962E-02 -2.9650298598418012E-02 -2.9630106070051836E-02 -2.9609918875814361E-02 -2.9589737020354404E-02 -2.9569560511847656E-02 -2.9549389358330642E-02 -2.9529223564522738E-02 -2.9509063134050904E-02 -2.9488908073242445E-02 -2.9468758391083427E-02 -2.9448614094654588E-02 -2.9428475185695809E-02 -2.9408341665786247E-02 -2.9388213542235930E-02 -2.9368090825048002E-02 -2.9347973521723161E-02 -2.9327861636558723E-02 -2.9307755173867439E-02 -2.9287654138746469E-02 -2.9267558536531593E-02 -2.9247468373299522E-02 -2.9227383655583587E-02 -2.9207304389296581E-02 -2.9187230579318109E-02 -2.9167162230607585E-02 -2.9147099348956113E-02 -2.9127041940441488E-02 -2.9106990011819305E-02 -2.9086943570385822E-02 -2.9066902621588942E-02 -2.9046867166870768E-02 -2.9026837208242503E-02 -2.9006812754631114E-02 -2.8986793817498604E-02 -2.8966780403969106E-02 -2.8946772516613175E-02 -2.8926770158656797E-02 -2.8906773335794750E-02 -2.8886782054066109E-02 -2.8866796318724984E-02 -2.8846816134634485E-02 -2.8826841507202185E-02 -2.8806872442576854E-02 -2.8786908947029777E-02 -2.8766951027095984E-02 -2.8746998689236615E-02 -2.8727051938246127E-02 -2.8707110777812499E-02 -2.8687175212383689E-02 -2.8667245247777477E-02 -2.8647320890316484E-02 -2.8627402148178546E-02 -2.8607489029871130E-02 -2.8587581539285794E-02 -2.8567679676332350E-02 -2.8547783443695875E-02 -2.8527892850737962E-02 -2.8508007907201319E-02 -2.8488128619042843E-02 -2.8468254990626534E-02 -2.8448387026128914E-02 -2.8428524729523726E-02 -2.8408668105426093E-02 -2.8388817160432907E-02 -2.8368971901351729E-02 -2.8349132333440920E-02 -2.8329298461129689E-02 -2.8309470289908076E-02 -2.8289647826807623E-02 -2.8269831078338560E-02 -2.8250020048407192E-02 -2.8230214740416749E-02 -2.8210415159883914E-02 -2.8190621313825121E-02 -2.8170833208552667E-02 -2.8151050848999510E-02 -2.8131274240038102E-02 -2.8111503387037797E-02 -2.8091738295517473E-02 -2.8071978970620932E-02 -2.8052225417148295E-02 -2.8032477640475145E-02 -2.8012735647422769E-02 -2.7992999444711755E-02 -2.7973269036709051E-02 -2.7953544426776184E-02 -2.7933825619848893E-02 -2.7914112622737776E-02 -2.7894405442026086E-02 -2.7874704083200533E-02 -2.7855008551436914E-02 -2.7835318851012873E-02 -2.7815634985700451E-02 -2.7795956960457228E-02 -2.7776284782071288E-02 -2.7756618457148514E-02 -2.7736957990821761E-02 -2.7717303387863660E-02 -2.7697654653652693E-02 -2.7678011794022184E-02 -2.7658374814119552E-02 -2.7638743717698186E-02 -2.7619118508723599E-02 -2.7599499193377196E-02 -2.7579885778595856E-02 -2.7560278270215576E-02 -2.7540676672993366E-02 -2.7521080991930586E-02 -2.7501491232789905E-02 -2.7481907401268671E-02 -2.7462329501555478E-02 -2.7442757537162514E-02 -2.7423191513280942E-02 -2.7403631437229157E-02 -2.7384077315609743E-02 -2.7364529152043158E-02 -2.7344986949753083E-02 -2.7325450714799755E-02 -2.7305920454983763E-02 -2.7286396175987580E-02 -2.7266877879983480E-02 -2.7247365569606868E-02 -2.7227859251184851E-02 -2.7208358932038740E-02 -2.7188864618097063E-02 -2.7169376314163489E-02 -2.7149894025143520E-02 -2.7130417756228781E-02 -2.7110947512730174E-02 -2.7091483300478659E-02 -2.7072025125438017E-02 -2.7052572991846741E-02 -2.7033126902145706E-02 -2.7013686859815620E-02 -2.6994252871503584E-02 -2.6974824944260446E-02 -2.6955403083844955E-02 -2.6935987295345933E-02 -2.6916577583463195E-02 -2.6897173952380421E-02 -2.6877776406485820E-02 -2.6858384951072876E-02 -2.6838999591649492E-02 -2.6819620333746932E-02 -2.6800247182905891E-02 -2.6780880144148055E-02 -2.6761519221589227E-02 -2.6742164419453110E-02 -2.6722815742966116E-02 -2.6703473197669109E-02 -2.6684136789096705E-02 -2.6664806522776235E-02 -2.6645482403827640E-02 -2.6626164436441477E-02 -2.6606852624806190E-02 -2.6587546973973981E-02 -2.6568247489366283E-02 -2.6548954176674491E-02 -2.6529667041887636E-02 -2.6510386090199456E-02 -2.6491111324355662E-02 -2.6471842746978603E-02 -2.6452580363841186E-02 -2.6433324182407320E-02 -2.6414074208759877E-02 -2.6394830446978296E-02 -2.6375592900996347E-02 -2.6356361574783261E-02 -2.6337136472458635E-02 -2.6317917600015700E-02 -2.6298704964761672E-02 -2.6279498572576328E-02 -2.6260298426629788E-02 -2.6241104529910041E-02 -2.6221916886018205E-02 -2.6202735498895839E-02 -2.6183560375121706E-02 -2.6164391523681742E-02 -2.6145228951436842E-02 -2.6126072659842993E-02 -2.6106922650047038E-02 -2.6087778926864702E-02 -2.6068641496728742E-02 -2.6049510365547115E-02 -2.6030385538599512E-02 -2.6011267020934155E-02 -2.5992154816966588E-02 -2.5973048931014063E-02 -2.5953949367692884E-02 -2.5934856131786588E-02 -2.5915769227683100E-02 -2.5896688659163097E-02 -2.5877614430531905E-02 -2.5858546548590131E-02 -2.5839485020632404E-02 -2.5820429851314664E-02 -2.5801381043306242E-02 -2.5782338599878593E-02 -2.5763302525596839E-02 -2.5744272825288989E-02 -2.5725249504424078E-02 -2.5706232568669253E-02 -2.5687222022962232E-02 -2.5668217871530247E-02 -2.5649220118694818E-02 -2.5630228769100760E-02 -2.5611243827406000E-02 -2.5592265297960153E-02 -2.5573293184983321E-02 -2.5554327493321503E-02 -2.5535368228608024E-02 -2.5516415396354089E-02 -2.5497469001472695E-02 -2.5478529048619906E-02 -2.5459595541050664E-02 -2.5440668481181591E-02 -2.5421747873570794E-02 -2.5402833726280886E-02 -2.5383926046548391E-02 -2.5365024836267624E-02 -2.5346130096046002E-02 -2.5327241830745920E-02 -2.5308360048638262E-02 -2.5289484756331117E-02 -2.5270615956698890E-02 -2.5251753652375426E-02 -2.5232897847475250E-02 -2.5214048546711193E-02 -2.5195205755431861E-02 -2.5176369479642587E-02 -2.5157539724643553E-02 -2.5138716493676206E-02 -2.5119899789782137E-02 -2.5101089617352985E-02 -2.5082285981455656E-02 -2.5063488886709343E-02 -2.5044698337127250E-02 -2.5025914337081814E-02 -2.5007136892443875E-02 -2.4988366009275117E-02 -2.4969601691727603E-02 -2.4950843942699103E-02 -2.4932092765785095E-02 -2.4913348165830167E-02 -2.4894610147734173E-02 -2.4875878716049779E-02 -2.4857153875221309E-02 -2.4838435629690979E-02 -2.4819723983899963E-02 -2.4801018942440349E-02 -2.4782320510246470E-02 -2.4763628692095224E-02 -2.4744943491380837E-02 -2.4726264910984484E-02 -2.4707592955412753E-02 -2.4688927630966133E-02 -2.4670268943364645E-02 -2.4651616896309542E-02 -2.4632971493101820E-02 -2.4614332736826009E-02 -2.4595700630485710E-02 -2.4577075178846157E-02 -2.4558456389183223E-02 -2.4539844268290312E-02 -2.4521238820257418E-02 -2.4502640048417818E-02 -2.4484047955059936E-02 -2.4465462541758479E-02 -2.4446883812369508E-02 -2.4428311774998220E-02 -2.4409746437217585E-02 -2.4391187801266499E-02 -2.4372635867786197E-02 -2.4354090641075420E-02 -2.4335552128756117E-02 -2.4317020336597540E-02 -2.4298495265580231E-02 -2.4279976916756624E-02 -2.4261465296889793E-02 -2.4242960415121605E-02 -2.4224462275973743E-02 -2.4205970878533576E-02 -2.4187486223718527E-02 -2.4169008319332240E-02 -2.4150537174062254E-02 -2.4132072791577985E-02 -2.4113615172680042E-02 -2.4095164320120384E-02 -2.4076720239665336E-02 -2.4058282936770852E-02 -2.4039852414472995E-02 -2.4021428675334886E-02 -2.4003011724483641E-02 -2.3984601568955280E-02 -2.3966198213917767E-02 -2.3947801660758012E-02 -2.3929411911131727E-02 -2.3911028970812476E-02 -2.3892652846927896E-02 -2.3874283543936097E-02 -2.3855921063709661E-02 -2.3837565408524500E-02 -2.3819216581979188E-02 -2.3800874588030076E-02 -2.3782539431780610E-02 -2.3764211118872804E-02 -2.3745889654808262E-02 -2.3727575044909112E-02 -2.3709267293521161E-02 -2.3690966401657784E-02 -2.3672672369975844E-02 -2.3654385203096852E-02 -2.3636104908066710E-02 -2.3617831490493943E-02 -2.3599564953604799E-02 -2.3581305300481251E-02 -2.3563052534540989E-02 -2.3544806659368245E-02 -2.3526567679647847E-02 -2.3508335600936108E-02 -2.3490110427551541E-02 -2.3471892161150292E-02 -2.3453680803668799E-02 -2.3435476360888940E-02 -2.3417278839955022E-02 -2.3399088245224273E-02 -2.3380904578180546E-02 -2.3362727841140161E-02 -2.3344558039100651E-02 -2.3326395177416123E-02 -2.3308239260541406E-02 -2.3290090292449158E-02 -2.3271948275968440E-02 -2.3253813212412315E-02 -2.3235685104441954E-02 -2.3217563960105138E-02 -2.3199449788150611E-02 -2.3181342590802397E-02 -2.3163242366038644E-02 -2.3145149115365436E-02 -2.3127062846500245E-02 -2.3108983566736307E-02 -2.3090911278204635E-02 -2.3072845981647466E-02 -2.3054787681498153E-02 -2.3036736385319292E-02 -2.3018692098763404E-02 -2.3000654822952587E-02 -2.2982624558714658E-02 -2.2964601309063071E-02 -2.2946585077953018E-02 -2.2928575870521165E-02 -2.2910573693195525E-02 -2.2892578551440151E-02 -2.2874590447649695E-02 -2.2856609383813901E-02 -2.2838635363436933E-02 -2.2820668390832723E-02 -2.2802708470004100E-02 -2.2784755604502237E-02 -2.2766809797968406E-02 -2.2748871054539127E-02 -2.2730939378381724E-02 -2.2713014772458278E-02 -2.2695097238897812E-02 -2.2677186780915511E-02 -2.2659283403755923E-02 -2.2641387112607454E-02 -2.2623497911194158E-02 -2.2605615802779581E-02 -2.2587740791133955E-02 -2.2569872880484714E-02 -2.2552012074596239E-02 -2.2534158376076668E-02 -2.2516311787511588E-02 -2.2498472312557260E-02 -2.2480639955334846E-02 -2.2462814719778856E-02 -2.2444996609603821E-02 -2.2427185628515169E-02 -2.2409381780229151E-02 -2.2391585068485768E-02 -2.2373795497240397E-02 -2.2356013070562463E-02 -2.2338237791969692E-02 -2.2320469664145533E-02 -2.2302708689855923E-02 -2.2284954872514796E-02 -2.2267208215789699E-02 -2.2249468724496749E-02 -2.2231736404296539E-02 -2.2214011259349142E-02 -2.2196293290829196E-02 -2.2178582499992060E-02 -2.2160878890552183E-02 -2.2143182467074557E-02 -2.2125493233573528E-02 -2.2107811193532625E-02 -2.2090136350603421E-02 -2.2072468708926558E-02 -2.2054808272568671E-02 -2.2037155044410783E-02 -2.2019509026804437E-02 -2.2001870223079669E-02 -2.1984238637785244E-02 -2.1966614275006027E-02 -2.1948997136974683E-02 -2.1931387225759144E-02 -2.1913784545948056E-02 -2.1896189103646289E-02 -2.1878600903017922E-02 -2.1861019945071638E-02 -2.1843446231083693E-02 -2.1825879764868258E-02 -2.1808320550941163E-02 -2.1790768593403620E-02 -2.1773223896026154E-02 -2.1755686462362381E-02 -2.1738156295530317E-02 -2.1720633398493189E-02 -2.1703117773596507E-02 -2.1685609423039019E-02 -2.1668108351156644E-02 -2.1650614564472433E-02 -2.1633128067709662E-02 -2.1615648860344724E-02 -2.1598176941651833E-02 -2.1580712316783816E-02 -2.1563254993768745E-02 -2.1545804977583360E-02 -2.1528362269141725E-02 -2.1510926869493470E-02 -2.1493498781213805E-02 -2.1476078007367099E-02 -2.1458664552651288E-02 -2.1441258422812068E-02 -2.1423859622003594E-02 -2.1406468151621522E-02 -2.1389084013083717E-02 -2.1371707209255061E-02 -2.1354337743459465E-02 -2.1336975619252914E-02 -2.1319620840388267E-02 -2.1302273410780639E-02 -2.1284933334694865E-02 -2.1267600616186905E-02 -2.1250275257604815E-02 -2.1232957260616598E-02 -2.1215646627364967E-02 -2.1198343360512857E-02 -2.1181047463422434E-02 -2.1163758941448334E-02 -2.1146477800039858E-02 -2.1129204042156364E-02 -2.1111937669421283E-02 -2.1094678683370439E-02 -2.1077427085434180E-02 -2.1060182877855819E-02 -2.1042946066124956E-02 -2.1025716656287084E-02 -2.1008494651202143E-02 -2.0991280051526451E-02 -2.0974072859295118E-02 -2.0956873079145549E-02 -2.0939680715680472E-02 -2.0922495771846829E-02 -2.0905318250076500E-02 -2.0888148153412084E-02 -2.0870985485443555E-02 -2.0853830249158295E-02 -2.0836682446053169E-02 -2.0819542077723373E-02 -2.0802409148039398E-02 -2.0785283661822921E-02 -2.0768165622585568E-02 -2.0751055032314815E-02 -2.0733951893692683E-02 -2.0716856211877768E-02 -2.0699767992069146E-02 -2.0682687235005222E-02 -2.0665613938929742E-02 -2.0648548105120963E-02 -2.0631489739451496E-02 -2.0614438847822981E-02 -2.0597395434656666E-02 -2.0580359503836590E-02 -2.0563331057205411E-02 -2.0546310095101192E-02 -2.0529296618946775E-02 -2.0512290632350872E-02 -2.0495292139005760E-02 -2.0478301141640332E-02 -2.0461317642695914E-02 -2.0444341645752494E-02 -2.0427373155478414E-02 -2.0410412175754435E-02 -2.0393458708330436E-02 -2.0376512754765992E-02 -2.0359574317754814E-02 -2.0342643400527646E-02 -2.0325720006565712E-02 -2.0308804139655776E-02 -2.0291895802798679E-02 -2.0274994996253130E-02 -2.0258101720067537E-02 -2.0241215978311675E-02 -2.0224337777477629E-02 -2.0207467122180484E-02 -2.0190604013981043E-02 -2.0173748454254122E-02 -2.0156900444774636E-02 -2.0140059987529737E-02 -2.0123227086032768E-02 -2.0106401744996314E-02 -2.0089583968273702E-02 -2.0072773757860103E-02 -2.0055971115521480E-02 -2.0039176043041906E-02 -2.0022388542269776E-02 -2.0005608616418816E-02 -1.9988836270092278E-02 -1.9972071507370296E-02 -1.9955314330725546E-02 -1.9938564742205081E-02 -1.9921822742579923E-02 -1.9905088332048574E-02 -1.9888361513364095E-02 -1.9871642292642495E-02 -1.9854930675379235E-02 -1.9838226663963003E-02 -1.9821530260016526E-02 -1.9804841464507710E-02 -1.9788160277999723E-02 -1.9771486702682122E-02 -1.9754820743526733E-02 -1.9738162405223445E-02 -1.9721511689751111E-02 -1.9704868598338157E-02 -1.9688233133565762E-02 -1.9671605299149408E-02 -1.9654985098332949E-02 -1.9638372533231575E-02 -1.9621767605810657E-02 -1.9605170318052138E-02 -1.9588580671973738E-02 -1.9571998670369069E-02 -1.9555424316872041E-02 -1.9538857614657373E-02 -1.9522298565425356E-02 -1.9505747170791447E-02 -1.9489203434049151E-02 -1.9472667359348977E-02 -1.9456138949153459E-02 -1.9439618203551445E-02 -1.9423105123355541E-02 -1.9406599712916698E-02 -1.9390101977307832E-02 -1.9373611919721808E-02 -1.9357129542046901E-02 -1.9340654845829627E-02 -1.9324187832043111E-02 -1.9307728501929175E-02 -1.9291276858465167E-02 -1.9274832905184010E-02 -1.9258396645354305E-02 -1.9241968082007597E-02 -1.9225547218022207E-02 -1.9209134055931686E-02 -1.9192728598055084E-02 -1.9176330845539585E-02 -1.9159940799073610E-02 -1.9143558460853551E-02 -1.9127183834817006E-02 -1.9110816924436225E-02 -1.9094457731410719E-02 -1.9078106257261414E-02 -1.9061762505182624E-02 -1.9045426479291524E-02 -1.9029098182192665E-02 -1.9012777614219999E-02 -1.8996464776179757E-02 -1.8980159671651769E-02 -1.8963862304807486E-02 -1.8947572677857273E-02 -1.8931290791568838E-02 -1.8915016647021960E-02 -1.8898750245966822E-02 -1.8882491590660844E-02 -1.8866240685799521E-02 -1.8849997536774223E-02 -1.8833762145569453E-02 -1.8817534510930507E-02 -1.8801314632970995E-02 -1.8785102515617307E-02 -1.8768898163140851E-02 -1.8752701577864940E-02 -1.8736512761233448E-02 -1.8720331715542767E-02 -1.8704158444141375E-02 -1.8687992949484398E-02 -1.8671835230784792E-02 -1.8655685287034603E-02 -1.8639543122190488E-02 -1.8623408743181236E-02 -1.8607282154655076E-02 -1.8591163357571359E-02 -1.8575052352399823E-02 -1.8558949138877161E-02 -1.8542853716749502E-02 -1.8526766089106101E-02 -1.8510686261648646E-02 -1.8494614238412307E-02 -1.8478550019836105E-02 -1.8462493606265670E-02 -1.8446445000196619E-02 -1.8430404204875274E-02 -1.8414371222151428E-02 -1.8398346052460903E-02 -1.8382328697106983E-02 -1.8366319159930741E-02 -1.8350317444935007E-02 -1.8334323553903024E-02 -1.8318337487532293E-02 -1.8302359247098898E-02 -1.8286388834645284E-02 -1.8270426252714151E-02 -1.8254471505478456E-02 -1.8238524597151813E-02 -1.8222585528111554E-02 -1.8206654296285128E-02 -1.8190730901707315E-02 -1.8174815348050932E-02 -1.8158907639360098E-02 -1.8143007779774064E-02 -1.8127115773254154E-02 -1.8111231620251161E-02 -1.8095355318295404E-02 -1.8079486867300758E-02 -1.8063626272653139E-02 -1.8047773539946584E-02 -1.8031928671327850E-02 -1.8016091667538762E-02 -1.8000262528940030E-02 -1.7984441255486865E-02 -1.7968627848036510E-02 -1.7952822310141520E-02 -1.7937024645707837E-02 -1.7921234857412843E-02 -1.7905452947278702E-02 -1.7889678917101595E-02 -1.7873912768371480E-02 -1.7858154502505229E-02 -1.7842404120722619E-02 -1.7826661624272121E-02 -1.7810927015377748E-02 -1.7795200296927317E-02 -1.7779481471116312E-02 -1.7763770538866162E-02 -1.7748067501243622E-02 -1.7732372360775905E-02 -1.7716685120406639E-02 -1.7701005781958695E-02 -1.7685334346260233E-02 -1.7669670814671194E-02 -1.7654015189891105E-02 -1.7638367474663921E-02 -1.7622727670676637E-02 -1.7607095779160493E-02 -1.7591471801355701E-02 -1.7575855738514886E-02 -1.7560247592221568E-02 -1.7544647365093986E-02 -1.7529055059844763E-02 -1.7513470678134239E-02 -1.7497894221035076E-02 -1.7482325689974321E-02 -1.7466765086913857E-02 -1.7451212413537236E-02 -1.7435667670179972E-02 -1.7420130857106485E-02 -1.7404601978503909E-02 -1.7389081041399128E-02 -1.7373568048775056E-02 -1.7358062995694958E-02 -1.7342565877833220E-02 -1.7327076699374364E-02 -1.7311595467304410E-02 -1.7296122185010886E-02 -1.7280656852475821E-02 -1.7265199470226762E-02 -1.7249750040510492E-02 -1.7234308565566084E-02 -1.7218875045527174E-02 -1.7203449479635178E-02 -1.7188031869807989E-02 -1.7172622221235299E-02 -1.7157220537731936E-02 -1.7141826817822250E-02 -1.7126441059336927E-02 -1.7111063264531517E-02 -1.7095693438303316E-02 -1.7080331584094995E-02 -1.7064977702995171E-02 -1.7049631795840521E-02 -1.7034293863268341E-02 -1.7018963905885972E-02 -1.7003641924699275E-02 -1.6988327921028876E-02 -1.6973021896763009E-02 -1.6957723854941088E-02 -1.6942433798354233E-02 -1.6927151727432060E-02 -1.6911877641794519E-02 -1.6896611542794100E-02 -1.6881353433528187E-02 -1.6866103316732960E-02 -1.6850861193957657E-02 -1.6835627066487828E-02 -1.6820400935075534E-02 -1.6805182800217876E-02 -1.6789972662718807E-02 -1.6774770523783112E-02 -1.6759576385088161E-02 -1.6744390249920114E-02 -1.6729212121635122E-02 -1.6714042000206486E-02 -1.6698879883470276E-02 -1.6683725771859653E-02 -1.6668579670238149E-02 -1.6653441583060570E-02 -1.6638311510748866E-02 -1.6623189452607542E-02 -1.6608075409622985E-02 -1.6592969384175243E-02 -1.6577871378037276E-02 -1.6562781391554100E-02 -1.6547699425012018E-02 -1.6532625479552587E-02 -1.6517559556686399E-02 -1.6502501658609923E-02 -1.6487451788252658E-02 -1.6472409947965481E-02 -1.6457376138314567E-02 -1.6442350359567478E-02 -1.6427332612201851E-02 -1.6412322896817769E-02 -1.6397321214551369E-02 -1.6382327567278681E-02 -1.6367341956727430E-02 -1.6352364383840367E-02 -1.6337394849520518E-02 -1.6322433356567217E-02 -1.6307479909048808E-02 -1.6292534508463519E-02 -1.6277597151651692E-02 -1.6262667836182763E-02 -1.6247746565938526E-02 -1.6232833346630164E-02 -1.6217928179973407E-02 -1.6203031064155399E-02 -1.6188141998261227E-02 -1.6173260983772496E-02 -1.6158388022684201E-02 -1.6143523118182342E-02 -1.6128666273861631E-02 -1.6113817490310371E-02 -1.6098976764688893E-02 -1.6084144095434436E-02 -1.6069319485541030E-02 -1.6054502938715784E-02 -1.6039694457007519E-02 -1.6024894041531446E-02 -1.6010101693257252E-02 -1.5995317412955526E-02 -1.5980541201324933E-02 -1.5965773058831154E-02 -1.5951012985949153E-02 -1.5936260984117500E-02 -1.5921517055470989E-02 -1.5906781201483353E-02 -1.5892053422332030E-02 -1.5877333718308222E-02 -1.5862622091157460E-02 -1.5847918543077121E-02 -1.5833223075167078E-02 -1.5818535687495944E-02 -1.5803856380641339E-02 -1.5789185156561608E-02 -1.5774522017277717E-02 -1.5759866963664854E-02 -1.5745219996080934E-02 -1.5730581115150532E-02 -1.5715950321824858E-02 -1.5701327616941697E-02 -1.5686713000894088E-02 -1.5672106474097273E-02 -1.5657508038176168E-02 -1.5642917695461937E-02 -1.5628335447181917E-02 -1.5613761292815642E-02 -1.5599195232513989E-02 -1.5584637270112627E-02 -1.5570087410119846E-02 -1.5555545651641928E-02 -1.5541011989619763E-02 -1.5526486422531342E-02 -1.5511968956311527E-02 -1.5497459596627424E-02 -1.5482958342055026E-02 -1.5468465188718509E-02 -1.5453980137026745E-02 -1.5439503191678167E-02 -1.5425034355921578E-02 -1.5410573628599305E-02 -1.5396121008164792E-02 -1.5381676495901242E-02 -1.5367240094451404E-02 -1.5352811805452359E-02 -1.5338391629230496E-02 -1.5323979566146806E-02 -1.5309575616997783E-02 -1.5295179782668488E-02 -1.5280792063941295E-02 -1.5266412461533357E-02 -1.5252040976181097E-02 -1.5237677608655078E-02 -1.5223322359721722E-02 -1.5208975230112195E-02 -1.5194636220551918E-02 -1.5180305331847093E-02 -1.5165982564869769E-02 -1.5151667920331950E-02 -1.5137361398591872E-02 -1.5123063000169574E-02 -1.5108772726935936E-02 -1.5094490581240553E-02 -1.5080216563903218E-02 -1.5065950674113756E-02 -1.5051692911445777E-02 -1.5037443276808666E-02 -1.5023201771329023E-02 -1.5008968395936777E-02 -1.4994743151452262E-02 -1.4980526038395064E-02 -1.4966317056872614E-02 -1.4952116207536770E-02 -1.4937923493250724E-02 -1.4923738917049225E-02 -1.4909562477459410E-02 -1.4895394169982212E-02 -1.4881233993592756E-02 -1.4867081953568301E-02 -1.4852938054952971E-02 -1.4838802298222716E-02 -1.4824674682357278E-02 -1.4810555205848336E-02 -1.4796443866765771E-02 -1.4782340664858420E-02 -1.4768245603830499E-02 -1.4754158687421528E-02 -1.4740079915681945E-02 -1.4726009287142065E-02 -1.4711946801838294E-02 -1.4697892461519932E-02 -1.4683846267356644E-02 -1.4669808218439478E-02 -1.4655778313752293E-02 -1.4641756555100086E-02 -1.4627742945813047E-02 -1.4613737486695848E-02 -1.4599740174830298E-02 -1.4585751008314895E-02 -1.4571769990676083E-02 -1.4557797126527017E-02 -1.4543832416158645E-02 -1.4529875856745929E-02 -1.4515927447021274E-02 -1.4501987188814746E-02 -1.4488055083896683E-02 -1.4474131131778197E-02 -1.4460215331291945E-02 -1.4446307683333305E-02 -1.4432408190724251E-02 -1.4418516855289325E-02 -1.4404633676175435E-02 -1.4390758652403871E-02 -1.4376891785148232E-02 -1.4363033076497250E-02 -1.4349182526378011E-02 -1.4335340132105157E-02 -1.4321505892339154E-02 -1.4307679810723223E-02 -1.4293861891541360E-02 -1.4280052134991388E-02 -1.4266250538851980E-02 -1.4252457101653472E-02 -1.4238671823149123E-02 -1.4224894703643189E-02 -1.4211125745416050E-02 -1.4197364951119180E-02 -1.4183612320744615E-02 -1.4169867852240387E-02 -1.4156131544474924E-02 -1.4142403398294937E-02 -1.4128683414918812E-02 -1.4114971596351746E-02 -1.4101267944815817E-02 -1.4087572460849017E-02 -1.4073885143313000E-02 -1.4060205990808759E-02 -1.4046535001433174E-02 -1.4032872173703454E-02 -1.4019217510235825E-02 -1.4005571015558698E-02 -1.3991932691062589E-02 -1.3978302534093143E-02 -1.3964680542747146E-02 -1.3951066718742388E-02 -1.3937461064340054E-02 -1.3923863578818802E-02 -1.3910274259594914E-02 -1.3896693106229775E-02 -1.3883120121901564E-02 -1.3869555309310794E-02 -1.3855998667248706E-02 -1.3842450193463135E-02 -1.3828909887704825E-02 -1.3815377751368331E-02 -1.3801853785806194E-02 -1.3788337992174198E-02 -1.3774830371345628E-02 -1.3761330922543270E-02 -1.3747839644363926E-02 -1.3734356536100467E-02 -1.3720881597784720E-02 -1.3707414829734607E-02 -1.3693956232986419E-02 -1.3680505808610331E-02 -1.3667063556847778E-02 -1.3653629477507661E-02 -1.3640203570315101E-02 -1.3626785834885826E-02 -1.3613376271202919E-02 -1.3599974880684739E-02 -1.3586581664915694E-02 -1.3573196623285299E-02 -1.3559819753715761E-02 -1.3546451055556847E-02 -1.3533090530739299E-02 -1.3519738180901892E-02 -1.3506394004828871E-02 -1.3493058000501748E-02 -1.3479730167901648E-02 -1.3466410508754578E-02 -1.3453099024222336E-02 -1.3439795714020663E-02 -1.3426500577721077E-02 -1.3413213615313722E-02 -1.3399934826960573E-02 -1.3386664212666079E-02 -1.3373401772256628E-02 -1.3360147505709552E-02 -1.3346901413494910E-02 -1.3333663496011058E-02 -1.3320433752071937E-02 -1.3307212179652689E-02 -1.3293998778755945E-02 -1.3280793552349103E-02 -1.3267596502843211E-02 -1.3254407629403664E-02 -1.3241226930387368E-02 -1.3228054404486390E-02 -1.3214890050641180E-02 -1.3201733868582727E-02 -1.3188585859527554E-02 -1.3175446024700908E-02 -1.3162314364464441E-02 -1.3149190878841876E-02 -1.3136075567008262E-02 -1.3122968427352328E-02 -1.3109869459170221E-02 -1.3096778664085557E-02 -1.3083696043763988E-02 -1.3070621597530621E-02 -1.3057555323679913E-02 -1.3044497221453099E-02 -1.3031447291232680E-02 -1.3018405533366027E-02 -1.3005371947862695E-02 -1.2992346534654130E-02 -1.2979329293583586E-02 -1.2966320224448893E-02 -1.2953319327457531E-02 -1.2940326603453046E-02 -1.2927342052687732E-02 -1.2914365672563903E-02 -1.2901397459950540E-02 -1.2888437415469691E-02 -1.2875485542608886E-02 -1.2862541843272396E-02 -1.2849606316018808E-02 -1.2836678959126373E-02 -1.2823759771601013E-02 -1.2810848752736010E-02 -1.2797945902280734E-02 -1.2785051220435169E-02 -1.2772164707328060E-02 -1.2759286362847807E-02 -1.2746416186884567E-02 -1.2733554179661393E-02 -1.2720700341542514E-02 -1.2707854672149190E-02 -1.2695017170153367E-02 -1.2682187834547293E-02 -1.2669366665675421E-02 -1.2656553664087428E-02 -1.2643748829276305E-02 -1.2630952160072380E-02 -1.2618163655559398E-02 -1.2605383315257259E-02 -1.2592611139199929E-02 -1.2579847129664128E-02 -1.2567091289277483E-02 -1.2554343615548334E-02 -1.2541604101827707E-02 -1.2528872745087901E-02 -1.2516149550377848E-02 -1.2503434522776311E-02 -1.2490727660838537E-02 -1.2478028960645229E-02 -1.2465338420567214E-02 -1.2452656041392139E-02 -1.2439981823908302E-02 -1.2427315768578206E-02 -1.2414657875601937E-02 -1.2402008143389725E-02 -1.2389366569456500E-02 -1.2376733152577580E-02 -1.2364107893251128E-02 -1.2351490791996040E-02 -1.2338881848942095E-02 -1.2326281064089417E-02 -1.2313688436980332E-02 -1.2301103966846623E-02 -1.2288527652673058E-02 -1.2275959493019059E-02 -1.2263399486875312E-02 -1.2250847635649258E-02 -1.2238303941378030E-02 -1.2225768403609982E-02 -1.2213241019733971E-02 -1.2200721787669320E-02 -1.2188210706724722E-02 -1.2175707776462902E-02 -1.2163212996851700E-02 -1.2150726368026298E-02 -1.2138247890032755E-02 -1.2125777562816553E-02 -1.2113315386352496E-02 -1.2100861360721126E-02 -1.2088415485707103E-02 -1.2075977758103099E-02 -1.2063548173134764E-02 -1.2051126730148579E-02 -1.2038713434478637E-02 -1.2026308290204514E-02 -1.2013911294377034E-02 -1.2001522442432222E-02 -1.1989141732194224E-02 -1.1976769163203668E-02 -1.1964404735799182E-02 -1.1952048451750295E-02 -1.1939700312423855E-02 -1.1927360316116735E-02 -1.1915028460148877E-02 -1.1902704743211642E-02 -1.1890389165263412E-02 -1.1878081725837122E-02 -1.1865782423298551E-02 -1.1853491256220089E-02 -1.1841208226020163E-02 -1.1828933335300836E-02 -1.1816666583536764E-02 -1.1804407966468203E-02 -1.1792157480849389E-02 -1.1779915127470680E-02 -1.1767680907740620E-02 -1.1755454820942431E-02 -1.1743236865133249E-02 -1.1731027039754408E-02 -1.1718825346405398E-02 -1.1706631785816185E-02 -1.1694446354098562E-02 -1.1682269046480806E-02 -1.1670099863808311E-02 -1.1657938811180733E-02 -1.1645785890132017E-02 -1.1633641094822173E-02 -1.1621504419662988E-02 -1.1609375865742309E-02 -1.1597255436445922E-02 -1.1585143132078193E-02 -1.1573038949910403E-02 -1.1560942887502602E-02 -1.1548854943515220E-02 -1.1536775117108124E-02 -1.1524703410006091E-02 -1.1512639825062879E-02 -1.1500584361296775E-02 -1.1488537012850355E-02 -1.1476497775399693E-02 -1.1464466651115361E-02 -1.1452443643216835E-02 -1.1440428750705811E-02 -1.1428421969968870E-02 -1.1416423299400558E-02 -1.1404432740761205E-02 -1.1392450295181765E-02 -1.1380475959356696E-02 -1.1368509728916310E-02 -1.1356551603383634E-02 -1.1344601585432214E-02 -1.1332659676449209E-02 -1.1320725874867966E-02 -1.1308800178527017E-02 -1.1296882583914047E-02 -1.1284973087149267E-02 -1.1273071688360586E-02 -1.1261178391868312E-02 -1.1249293199995250E-02 -1.1237416108853825E-02 -1.1225547113944247E-02 -1.1213686214916960E-02 -1.1201833413515253E-02 -1.1189988709873479E-02 -1.1178152101929463E-02 -1.1166323587505618E-02 -1.1154503164575945E-02 -1.1142690831294721E-02 -1.1130886587579009E-02 -1.1119090434509184E-02 -1.1107302371966181E-02 -1.1095522397692077E-02 -1.1083750509499085E-02 -1.1071986706647744E-02 -1.1060230988836918E-02 -1.1048483355434454E-02 -1.1036743805522796E-02 -1.1025012338282410E-02 -1.1013288953140134E-02 -1.1001573649472159E-02 -1.0989866426073429E-02 -1.0978167281475276E-02 -1.0966476213628762E-02 -1.0954793219840591E-02 -1.0943118298691846E-02 -1.0931451452731037E-02 -1.0919792684664427E-02 -1.0908141991638124E-02 -1.0896499367816188E-02 -1.0884864810536295E-02 -1.0873238321745800E-02 -1.0861619902829729E-02 -1.0850009551445152E-02 -1.0838407264515923E-02 -1.0826813041778916E-02 -1.0815226884955389E-02 -1.0803648793986976E-02 -1.0792078765408945E-02 -1.0780516795844030E-02 -1.0768962884420762E-02 -1.0757417031100920E-02 -1.0745879235558545E-02 -1.0734349497201513E-02 -1.0722827815034433E-02 -1.0711314187097087E-02 -1.0699808611460906E-02 -1.0688311087500350E-02 -1.0676821615141977E-02 -1.0665340193341232E-02 -1.0653866819899705E-02 -1.0642401493021217E-02 -1.0630944212435500E-02 -1.0619494978039134E-02 -1.0608053788270904E-02 -1.0596620640736770E-02 -1.0585195534158662E-02 -1.0573778468984978E-02 -1.0562369445033141E-02 -1.0550968458737701E-02 -1.0539575505918664E-02 -1.0528190586862553E-02 -1.0516813705217495E-02 -1.0505444861703682E-02 -1.0494084051032412E-02 -1.0482731268107722E-02 -1.0471386513133637E-02 -1.0460049788133913E-02 -1.0448721092887111E-02 -1.0437400424974506E-02 -1.0426087782222570E-02 -1.0414783163341924E-02 -1.0403486567122248E-02 -1.0392197991842237E-02 -1.0380917435558674E-02 -1.0369644897136526E-02 -1.0358380376462001E-02 -1.0347123873044588E-02 -1.0335875384850811E-02 -1.0324634909658950E-02 -1.0313402446893650E-02 -1.0302177996982386E-02 -1.0290961558762933E-02 -1.0279753128451667E-02 -1.0268552702884768E-02 -1.0257360282927260E-02 -1.0246175870417373E-02 -1.0234999463925030E-02 -1.0223831059392492E-02 -1.0212670654174048E-02 -1.0201518248793178E-02 -1.0190373843663000E-02 -1.0179237435940442E-02 -1.0168109021632623E-02 -1.0156988599574189E-02 -1.0145876171542806E-02 -1.0134771738181527E-02 -1.0123675296558280E-02 -1.0112586843278995E-02 -1.0101506376340282E-02 -1.0090433894457506E-02 -1.0079369396730988E-02 -1.0068312882770245E-02 -1.0057264351959338E-02 -1.0046223802703088E-02 -1.0035191233196485E-02 -1.0024166641870605E-02 -1.0013150027312514E-02 -1.0002141388046731E-02 -9.9911407224837281E-03 -9.9801480290688405E-03 -9.9691633064799140E-03 -9.9581865534718629E-03 -9.9472177688736813E-03 -9.9362569515768443E-03 -9.9253041002172540E-03 -9.9143592128438963E-03 -9.9034222875040399E-03 -9.8924933227850943E-03 -9.8815723174957796E-03 -9.8706592703609024E-03 -9.8597541800115283E-03 -9.8488570451510851E-03 -9.8379678647153614E-03 -9.8270866375751217E-03 -9.8162133615879409E-03 -9.8053480340778067E-03 -9.7944906532557770E-03 -9.7836412186093225E-03 -9.7727997294636930E-03 -9.7619661840962733E-03 -9.7511405805557044E-03 -9.7403229173525698E-03 -9.7295131933214755E-03 -9.7187114070289085E-03 -9.7079175565305108E-03 -9.6971316399707651E-03 -9.6863536562743543E-03 -9.6755836045864258E-03 -9.6648214832321024E-03 -9.6540672897885392E-03 -9.6433210222638729E-03 -9.6325826797832824E-03 -9.6218522615301068E-03 -9.6111297658927741E-03 -9.6004151909081566E-03 -9.5897085346634617E-03 -9.5790097953072362E-03 -9.5683189711521042E-03 -9.5576360610298006E-03 -9.5469610638186913E-03 -9.5362939778104085E-03 -9.5256348009616649E-03 -9.5149835315655289E-03 -9.5043401684338450E-03 -9.4937047103635912E-03 -9.4830771558987274E-03 -9.4724575034867402E-03 -9.4618457511680600E-03 -9.4512418966802673E-03 -9.4406459382387498E-03 -9.4300578750213110E-03 -9.4194777061074268E-03 -9.4089054293463974E-03 -9.3983410421564096E-03 -9.3877845422176628E-03 -9.3772359274671199E-03 -9.3666951965708824E-03 -9.3561623500688033E-03 -9.3456373883823874E-03 -9.3351203086140099E-03 -9.3246111063304670E-03 -9.3141097785503883E-03 -9.3036163241246861E-03 -9.2931307423062895E-03 -9.2826530333398934E-03 -9.2721831973788318E-03 -9.2617212312055587E-03 -9.2512671295523520E-03 -9.2408208897016113E-03 -9.2303825131258791E-03 -9.2199520007931485E-03 -9.2095293495467884E-03 -9.1991145551683379E-03 -9.1887076155861367E-03 -9.1783085304468891E-03 -9.1679172989030944E-03 -9.1575339189578463E-03 -9.1471583885294784E-03 -9.1367907059218233E-03 -9.1264308695682209E-03 -9.1160788774333028E-03 -9.1057347269970224E-03 -9.0953984160849124E-03 -9.0850699435500587E-03 -9.0747493083683014E-03 -9.0644365090434414E-03 -9.0541315438322379E-03 -9.0438344106774111E-03 -9.0335451071051152E-03 -9.0232636308923402E-03 -9.0129899808583588E-03 -9.0027241559977496E-03 -8.9924661544984706E-03 -8.9822159740179531E-03 -8.9719736123667331E-03 -8.9617390676366860E-03 -8.9515123380041733E-03 -8.9412934219275930E-03 -8.9310823179424344E-03 -8.9208790243950082E-03 -8.9106835394692548E-03 -8.9004958611278995E-03 -8.8903159868448517E-03 -8.8801439142261688E-03 -8.8699796422217203E-03 -8.8598231702849729E-03 -8.8496744964598525E-03 -8.8395336172375737E-03 -8.8294005296958092E-03 -8.8192752329065670E-03 -8.8091577262264312E-03 -8.7990480082069857E-03 -8.7889460769532204E-03 -8.7788519300447190E-03 -8.7687655643203834E-03 -8.7586869771421709E-03 -8.7486161681894561E-03 -8.7385531375328996E-03 -8.7284978827800990E-03 -8.7184503998173953E-03 -8.7084106855831404E-03 -8.6983787390246189E-03 -8.6883545592174542E-03 -8.6783381447617641E-03 -8.6683294940760932E-03 -8.6583286051339879E-03 -8.6483354755051631E-03 -8.6383501027950792E-03 -8.6283724847313545E-03 -8.6184026191098561E-03 -8.6084405040904657E-03 -8.5984861379970121E-03 -8.5885395192535317E-03 -8.5786006464004614E-03 -8.5686695177735143E-03 -8.5587461310298266E-03 -8.5488304837056401E-03 -8.5389225734872100E-03 -8.5290223981506260E-03 -8.5191299556492094E-03 -8.5092452442029360E-03 -8.4993682621459649E-03 -8.4894990082073733E-03 -8.4796374811317299E-03 -8.4697836783643923E-03 -8.4599375963841893E-03 -8.4500992324590112E-03 -8.4402685854579971E-03 -8.4304456541939524E-03 -8.4206304360742966E-03 -8.4108229280773356E-03 -8.4010231287810922E-03 -8.3912310383075003E-03 -8.3814466555707564E-03 -8.3716699761921826E-03 -8.3619009956888805E-03 -8.3521397128892491E-03 -8.3423861281324372E-03 -8.3326402399193297E-03 -8.3229020444479072E-03 -8.3131715383538609E-03 -8.3034487202789282E-03 -8.2937335891982260E-03 -8.2840261430135766E-03 -8.2743263789770132E-03 -8.2646342950815008E-03 -8.2549498905312400E-03 -8.2452731640320492E-03 -8.2356041114833196E-03 -8.2259427281844225E-03 -8.2162890127286878E-03 -8.2066429663245170E-03 -8.1970045884519095E-03 -8.1873738747995223E-03 -8.1777508210020625E-03 -8.1681354253370520E-03 -8.1585276870542664E-03 -8.1489276044160088E-03 -8.1393351746674239E-03 -8.1297503952709113E-03 -8.1201732644207384E-03 -8.1106037803621162E-03 -8.1010419407047882E-03 -8.0914877427547462E-03 -8.0819411844913515E-03 -8.0724022647908258E-03 -8.0628709820777262E-03 -8.0533473328769176E-03 -8.0438313134379730E-03 -8.0343229219595504E-03 -8.0248221579080920E-03 -8.0153290198600215E-03 -8.0058435048222330E-03 -7.9963656098185464E-03 -7.9868953327244443E-03 -7.9774326716584021E-03 -7.9679776243832181E-03 -7.9585301883616580E-03 -7.9490903614580048E-03 -7.9396581424611805E-03 -7.9302335300084903E-03 -7.9208165208778467E-03 -7.9114071111329610E-03 -7.9020052981599066E-03 -7.8926110807939470E-03 -7.8832244577273919E-03 -7.8738454270081155E-03 -7.8644739864831351E-03 -7.8551101332490023E-03 -7.8457538640177328E-03 -7.8364051764082052E-03 -7.8270640693262269E-03 -7.8177305414180755E-03 -7.8084045899126054E-03 -7.7990862117385115E-03 -7.7897754044981490E-03 -7.7804721662633140E-03 -7.7711764949735494E-03 -7.7618883883078449E-03 -7.7526078439816119E-03 -7.7433348600530506E-03 -7.7340694346390857E-03 -7.7248115647977319E-03 -7.7155612466341334E-03 -7.7063184772338386E-03 -7.6970832561233911E-03 -7.6878555829079627E-03 -7.6786354551659827E-03 -7.6694228695852514E-03 -7.6602178228154958E-03 -7.6510203114667765E-03 -7.6418303327808494E-03 -7.6326478860215307E-03 -7.6234729706701979E-03 -7.6143055843677582E-03 -7.6051457237064964E-03 -7.5959933857052053E-03 -7.5868485680436097E-03 -7.5777112684253080E-03 -7.5685814844228391E-03 -7.5594592136115722E-03 -7.5503444541038574E-03 -7.5412372044046981E-03 -7.5321374621414930E-03 -7.5230452232040810E-03 -7.5139604837890428E-03 -7.5048832430069145E-03 -7.4958135009101914E-03 -7.4867512555338127E-03 -7.4776965029737050E-03 -7.4686492395459048E-03 -7.4596094623347892E-03 -7.4505771687145535E-03 -7.4415523573669335E-03 -7.4325350275423908E-03 -7.4235251769305417E-03 -7.4145228012824334E-03 -7.4055278969991350E-03 -7.3965404631187387E-03 -7.3875604990242053E-03 -7.3785880017277986E-03 -7.3696229668133864E-03 -7.3606653913341263E-03 -7.3517152747334972E-03 -7.3427726161186925E-03 -7.3338374120689460E-03 -7.3249096585244105E-03 -7.3159893527487288E-03 -7.3070764930522874E-03 -7.2981710774302688E-03 -7.2892731031583696E-03 -7.2803825675037941E-03 -7.2714994682382163E-03 -7.2626238033135998E-03 -7.2537555703977991E-03 -7.2448947668677134E-03 -7.2360413900423139E-03 -7.2271954371171008E-03 -7.2183569053326730E-03 -7.2095257924867946E-03 -7.2007020966491399E-03 -7.1918858155998622E-03 -7.1830769467343143E-03 -7.1742754873615902E-03 -7.1654814345706915E-03 -7.1566947854546188E-03 -7.1479155377507913E-03 -7.1391436896145744E-03 -7.1303792390179288E-03 -7.1216221836067793E-03 -7.1128725207744489E-03 -7.1041302468278274E-03 -7.0953953578449481E-03 -7.0866678517138171E-03 -7.0779477278450752E-03 -7.0692349847783758E-03 -7.0605296189996895E-03 -7.0518316268054267E-03 -7.0431410050830166E-03 -7.0344577509997919E-03 -7.0257818627735159E-03 -7.0171133397631379E-03 -7.0084521804550139E-03 -6.9997983805875508E-03 -6.9911519356014905E-03 -6.9825128428286426E-03 -6.9738811006109921E-03 -6.9652567072456886E-03 -6.9566396609535433E-03 -6.9480299595156602E-03 -6.9394275990009120E-03 -6.9308325751932312E-03 -6.9222448856459604E-03 -6.9136645291386382E-03 -6.9050915041408319E-03 -6.8965258085114320E-03 -6.8879674397046503E-03 -6.8794163933768443E-03 -6.8708726647397520E-03 -6.8623362518259083E-03 -6.8538071551946548E-03 -6.8452853737601353E-03 -6.8367709022889188E-03 -6.8282637354219466E-03 -6.8197638712459334E-03 -6.8112713093129796E-03 -6.8027860480462379E-03 -6.7943080845547449E-03 -6.7858374157420080E-03 -6.7773740380926602E-03 -6.7689179481517786E-03 -6.7604691438806503E-03 -6.7520276240248351E-03 -6.7435933860361648E-03 -6.7351664254166428E-03 -6.7267467381562302E-03 -6.7183343229898530E-03 -6.7099291792427638E-03 -6.7015313043110383E-03 -6.6931406941700593E-03 -6.6847573456233159E-03 -6.6763812571516579E-03 -6.6680124270961502E-03 -6.6596508519021361E-03 -6.6512965274033191E-03 -6.6429494506648132E-03 -6.6346096199276809E-03 -6.6262770330458845E-03 -6.6179516867629984E-03 -6.6096335777810133E-03 -6.6013227038342484E-03 -6.5930190631283310E-03 -6.5847226535290992E-03 -6.5764334724803504E-03 -6.5681515170836246E-03 -6.5598767833652989E-03 -6.5516092672729537E-03 -6.5433489663610832E-03 -6.5350958791550156E-03 -6.5268500037523932E-03 -6.5186113375467637E-03 -6.5103798777141056E-03 -6.5021556207265985E-03 -6.4939385629502579E-03 -6.4857287022089070E-03 -6.4775260374674145E-03 -6.4693305665324587E-03 -6.4611422847384260E-03 -6.4529611875471385E-03 -6.4447872730883865E-03 -6.4366205404421013E-03 -6.4284609872798572E-03 -6.4203086098403792E-03 -6.4121634046335153E-03 -6.4040253690875876E-03 -6.3958945007902106E-03 -6.3877707973571474E-03 -6.3796542564063825E-03 -6.3715448750859350E-03 -6.3634426499273545E-03 -6.3553475776654223E-03 -6.3472596559293170E-03 -6.3391788824780793E-03 -6.3311052542022947E-03 -6.3230387674404016E-03 -6.3149794193733200E-03 -6.3069272086302653E-03 -6.2988821335331104E-03 -6.2908441902122100E-03 -6.2828133742228315E-03 -6.2747896827214950E-03 -6.2667731142053828E-03 -6.2587636667137255E-03 -6.2507613371760896E-03 -6.2427661223615882E-03 -6.2347780189662694E-03 -6.2267970236792626E-03 -6.2188231337922993E-03 -6.2108563472485692E-03 -6.2028966615871248E-03 -6.1949440730651815E-03 -6.1869985778989682E-03 -6.1790601740511165E-03 -6.1711288603850034E-03 -6.1632046345003718E-03 -6.1552874922203649E-03 -6.1473774295424067E-03 -6.1394744436646153E-03 -6.1315785321027355E-03 -6.1236896926727914E-03 -6.1158079233891880E-03 -6.1079332214136629E-03 -6.1000655823545136E-03 -6.0922050020890380E-03 -6.0843514787700340E-03 -6.0765050112251374E-03 -6.0686655969552474E-03 -6.0608332322773942E-03 -6.0530079136540942E-03 -6.0451896379921993E-03 -6.0373784023293872E-03 -6.0295742041750139E-03 -6.0217770412287607E-03 -6.0139869107683581E-03 -6.0062038095848513E-03 -5.9984277344185552E-03 -5.9906586819347728E-03 -5.9828966488694778E-03 -5.9751416327971452E-03 -5.9673936317544817E-03 -5.9596526430676930E-03 -5.9519186629979869E-03 -5.9441916880429288E-03 -5.9364717160595038E-03 -5.9287587451583397E-03 -5.9210527719953058E-03 -5.9133537921643269E-03 -5.9056618022260126E-03 -5.8979768006593740E-03 -5.8902987858564845E-03 -5.8826277544777837E-03 -5.8749637025910899E-03 -5.8673066265835828E-03 -5.8596565231475066E-03 -5.8520133894575709E-03 -5.8443772238842267E-03 -5.8367480247703126E-03 -5.8291257888095950E-03 -5.8215105119440985E-03 -5.8139021905283667E-03 -5.8063008214274056E-03 -5.7987064017368745E-03 -5.7911189292262424E-03 -5.7835384017298425E-03 -5.7759648162576151E-03 -5.7683981693240315E-03 -5.7608384576316599E-03 -5.7532856781922145E-03 -5.7457398280705545E-03 -5.7382009044480188E-03 -5.7306689045274048E-03 -5.7231438253353729E-03 -5.7156256637610862E-03 -5.7081144167608995E-03 -5.7006100814374905E-03 -5.6931126548944904E-03 -5.6856221341310288E-03 -5.6781385161060998E-03 -5.6706617977572964E-03 -5.6631919760008302E-03 -5.6557290478331402E-03 -5.6482730104715304E-03 -5.6408238611402681E-03 -5.6333815968126243E-03 -5.6259462143367989E-03 -5.6185177105297929E-03 -5.6110960821690288E-03 -5.6036813261578248E-03 -5.5962734398654363E-03 -5.5888724207214368E-03 -5.5814782656302591E-03 -5.5740909711609063E-03 -5.5667105341184967E-03 -5.5593369517165630E-03 -5.5519702211403107E-03 -5.5446103392458321E-03 -5.5372573028013581E-03 -5.5299111087770752E-03 -5.5225717543112675E-03 -5.5152392365056657E-03 -5.5079135523699316E-03 -5.5005946988763285E-03 -5.4932826728330266E-03 -5.4859774709867005E-03 -5.4786790902048273E-03 -5.4713875274848937E-03 -5.4641027798563377E-03 -5.4568248444230635E-03 -5.4495537182846776E-03 -5.4422893983811123E-03 -5.4350318815682523E-03 -5.4277811647132027E-03 -5.4205372446998164E-03 -5.4133001184374398E-03 -5.4060697829299790E-03 -5.3988462351978921E-03 -5.3916294721803645E-03 -5.3844194907607199E-03 -5.3772162878157580E-03 -5.3700198602125255E-03 -5.3628302048434797E-03 -5.3556473187391087E-03 -5.3484711989648069E-03 -5.3413018423994017E-03 -5.3341392457565487E-03 -5.3269834058400946E-03 -5.3198343196804642E-03 -5.3126919843274794E-03 -5.3055563967369492E-03 -5.2984275538209575E-03 -5.2913054523944401E-03 -5.2841900891614363E-03 -5.2770814609389982E-03 -5.2699795649166353E-03 -5.2628843983147083E-03 -5.2557959579467529E-03 -5.2487142403994727E-03 -5.2416392423890032E-03 -5.2345709608267255E-03 -5.2275093926723278E-03 -5.2204545350219211E-03 -5.2134063849791417E-03 -5.2063649392571050E-03 -5.1993301942855775E-03 -5.1923021467499345E-03 -5.1852807938395969E-03 -5.1782661327631927E-03 -5.1712581605159189E-03 -5.1642568740084055E-03 -5.1572622699400938E-03 -5.1502743448115394E-03 -5.1432930952890468E-03 -5.1363185184770850E-03 -5.1293506115086844E-03 -5.1223893712156188E-03 -5.1154347942951733E-03 -5.1084868775881018E-03 -5.1015456181107231E-03 -5.0946110128099100E-03 -5.0876830583638094E-03 -5.0807617514153176E-03 -5.0738470888299289E-03 -5.0669390676057234E-03 -5.0600376846673687E-03 -5.0531429368209655E-03 -5.0462548208606104E-03 -5.0393733335731212E-03 -5.0324984717520435E-03 -5.0256302323246262E-03 -5.0187686123210791E-03 -5.0119136086133652E-03 -5.0050652177428970E-03 -4.9982234362668659E-03 -4.9913882610831623E-03 -4.9845596892127159E-03 -4.9777377175781960E-03 -4.9709223430032387E-03 -4.9641135622702625E-03 -4.9573113720620164E-03 -4.9505157690720074E-03 -4.9437267502201263E-03 -4.9369443125332826E-03 -4.9301684528713684E-03 -4.9233991678768012E-03 -4.9166364542410452E-03 -4.9098803088844060E-03 -4.9031307287527972E-03 -4.8963877104940875E-03 -4.8896512505690430E-03 -4.8829213457232071E-03 -4.8761979931857598E-03 -4.8694811901008137E-03 -4.8627709329788181E-03 -4.8560672181622560E-03 -4.8493700423783356E-03 -4.8426794026729999E-03 -4.8359952960512062E-03 -4.8293177194069538E-03 -4.8226466695717295E-03 -4.8159821430659852E-03 -4.8093241362991493E-03 -4.8026726460283350E-03 -4.7960276693825802E-03 -4.7893892033482720E-03 -4.7827572444459543E-03 -4.7761317891623191E-03 -4.7695128344298230E-03 -4.7629003774073610E-03 -4.7562944149131718E-03 -4.7496949432924316E-03 -4.7431019590087357E-03 -4.7365154591173199E-03 -4.7299354407770175E-03 -4.7233619006510769E-03 -4.7167948350674005E-03 -4.7102342406214939E-03 -4.7036801143997579E-03 -4.6971324534654203E-03 -4.6905912544967301E-03 -4.6840565140518478E-03 -4.6775282287681540E-03 -4.6710063953529562E-03 -4.6644910105051434E-03 -4.6579820708981699E-03 -4.6514795732432732E-03 -4.6449835145421772E-03 -4.6384938919074737E-03 -4.6320107020580712E-03 -4.6255339412645813E-03 -4.6190636059429335E-03 -4.6125996930358850E-03 -4.6061421995571630E-03 -4.5996911222203323E-03 -4.5932464575729219E-03 -4.5868082022757859E-03 -4.5803763531590807E-03 -4.5739509070269850E-03 -4.5675318605196240E-03 -4.5611192102437779E-03 -4.5547129529334637E-03 -4.5483130854145565E-03 -4.5419196044433280E-03 -4.5355325066390789E-03 -4.5291517886308650E-03 -4.5227774471883527E-03 -4.5164094791256080E-03 -4.5100478811676611E-03 -4.5036926499559026E-03 -4.4973437821421627E-03 -4.4910012744126026E-03 -4.4846651234559456E-03 -4.4783353259403632E-03 -4.4720118785256417E-03 -4.4656947779049367E-03 -4.4593840208118924E-03 -4.4530796040177217E-03 -4.4467815244108476E-03 -4.4404897788601063E-03 -4.4342043637731190E-03 -4.4279252752888040E-03 -4.4216525099648324E-03 -4.4153860650205613E-03 -4.4091259375702262E-03 -4.4028721240014458E-03 -4.3966246205332784E-03 -4.3903834238974634E-03 -4.3841485312207749E-03 -4.3779199393638316E-03 -4.3716976446230484E-03 -4.3654816433213138E-03 -4.3592719323528439E-03 -4.3530685088074249E-03 -4.3468713693953697E-03 -4.3406805104478866E-03 -4.3344959283950065E-03 -4.3283176199765917E-03 -4.3221455819682066E-03 -4.3159798110161095E-03 -4.3098203037072553E-03 -4.3036670567773378E-03 -4.2975200671541633E-03 -4.2913793316351539E-03 -4.2852448465057671E-03 -4.2791166079828285E-03 -4.2729946128062125E-03 -4.2668788580461463E-03 -4.2607693405690957E-03 -4.2546660568923709E-03 -4.2485690035153597E-03 -4.2424781770104376E-03 -4.2363935739766993E-03 -4.2303151910940201E-03 -4.2242430251084309E-03 -4.2181770726890779E-03 -4.2121173303330253E-03 -4.2060637945634128E-03 -4.2000164622182116E-03 -4.1939753302464812E-03 -4.1879403952372685E-03 -4.1819116533968366E-03 -4.1758891010954570E-03 -4.1698727352288151E-03 -4.1638625527438073E-03 -4.1578585502089760E-03 -4.1518607239982791E-03 -4.1458690706122642E-03 -4.1398835867275455E-03 -4.1339042690762022E-03 -4.1279311145544784E-03 -4.1219641200594655E-03 -4.1160032820074313E-03 -4.1100485964916241E-03 -4.1041000599001658E-03 -4.0981576691572147E-03 -4.0922214211826062E-03 -4.0862913125892233E-03 -4.0803673398930171E-03 -4.0744494996396898E-03 -4.0685377884012910E-03 -4.0626322028139584E-03 -4.0567327396611938E-03 -4.0508393956987286E-03 -4.0449521673432557E-03 -4.0390710508756734E-03 -4.0331960428183497E-03 -4.0273271399673500E-03 -4.0214643390771307E-03 -4.0156076367283801E-03 -4.0097570294722424E-03 -4.0039125138972070E-03 -3.9980740866126839E-03 -3.9922417442339424E-03 -3.9864154833845001E-03 -3.9805953006689897E-03 -3.9747811926112726E-03 -3.9689731557150708E-03 -3.9631711864934731E-03 -3.9573752814678100E-03 -3.9515854373217219E-03 -3.9458016510469547E-03 -3.9400239195353081E-03 -3.9342522389341703E-03 -3.9284866051666999E-03 -3.9227270148079387E-03 -3.9169734650408771E-03 -3.9112259528251061E-03 -3.9054844745051286E-03 -3.8997490263517030E-03 -3.8940196047896050E-03 -3.8882962063193005E-03 -3.8825788276282856E-03 -3.8768674656286185E-03 -3.8711621171242392E-03 -3.8654627785168908E-03 -3.8597694461356513E-03 -3.8540821164183632E-03 -3.8484007858694343E-03 -3.8427254511126693E-03 -3.8370561089563909E-03 -3.8313927561404578E-03 -3.8257353890306157E-03 -3.8200840039094401E-03 -3.8144385973655857E-03 -3.8087991662224944E-03 -3.8031657072027623E-03 -3.7975382168120592E-03 -3.7919166915220291E-03 -3.7863011277579949E-03 -3.7806915219320458E-03 -3.7750878705441670E-03 -3.7694901701817501E-03 -3.7638984174957523E-03 -3.7583126092967578E-03 -3.7527327423672071E-03 -3.7471588130472450E-03 -3.7415908174709108E-03 -3.7360287521027978E-03 -3.7304726138327978E-03 -3.7249223994570055E-03 -3.7193781053393104E-03 -3.7138397277703427E-03 -3.7083072632982132E-03 -3.7027807086329333E-03 -3.6972600604068370E-03 -3.6917453151191172E-03 -3.6862364692577098E-03 -3.6807335193169036E-03 -3.6752364617989143E-03 -3.6697452933050073E-03 -3.6642600105171452E-03 -3.6587806100297090E-03 -3.6533070882421633E-03 -3.6478394415433708E-03 -3.6423776664178476E-03 -3.6369217593910192E-03 -3.6314717170678004E-03 -3.6260275361369239E-03 -3.6205892132047742E-03 -3.6151567446307876E-03 -3.6097301267605836E-03 -3.6043093562041079E-03 -3.5988944297042987E-03 -3.5934853438252040E-03 -3.5880820948853277E-03 -3.5826846792642517E-03 -3.5772930936418933E-03 -3.5719073347492514E-03 -3.5665273990631925E-03 -3.5611532828908345E-03 -3.5557849826848274E-03 -3.5504224951610633E-03 -3.5450658170098591E-03 -3.5397149446526901E-03 -3.5343698744332110E-03 -3.5290306028391443E-03 -3.5236971264835841E-03 -3.5183694419104864E-03 -3.5130475454939864E-03 -3.5077314336151274E-03 -3.5024211028683960E-03 -3.4971165499358739E-03 -3.4918177714252006E-03 -3.4865247638599136E-03 -3.4812375237324141E-03 -3.4759560474533343E-03 -3.4706803314309004E-03 -3.4654103721987873E-03 -3.4601461663581459E-03 -3.4548877104111464E-03 -3.4496350007150204E-03 -3.4443880336757836E-03 -3.4391468059460830E-03 -3.4339113142288209E-03 -3.4286815550524838E-03 -3.4234575248201751E-03 -3.4182392199275089E-03 -3.4130266367611108E-03 -3.4078197717512977E-03 -3.4026186215742474E-03 -3.3974231829759561E-03 -3.3922334524153774E-03 -3.3870494260854951E-03 -3.3818711003188637E-03 -3.3766984718187525E-03 -3.3715315373135024E-03 -3.3663702932975170E-03 -3.3612147361595100E-03 -3.3560648622887662E-03 -3.3509206680759260E-03 -3.3457821499845194E-03 -3.3406493047177157E-03 -3.3355221289968510E-03 -3.3304006192228066E-03 -3.3252847716100280E-03 -3.3201745825379957E-03 -3.3150700486454512E-03 -3.3099711665392378E-03 -3.3048779325879785E-03 -3.2997903431139660E-03 -3.2947083947239158E-03 -3.2896320842403220E-03 -3.2845614082329523E-03 -3.2794963627510651E-03 -3.2744369438950783E-03 -3.2693831484382966E-03 -3.2643349733786440E-03 -3.2592924152197674E-03 -3.2542554699773688E-03 -3.2492241338429408E-03 -3.2441984035293733E-03 -3.2391782758059385E-03 -3.2341637472077852E-03 -3.2291548141547572E-03 -3.2241514729811844E-03 -3.2191537199134394E-03 -3.2141615513087457E-03 -3.2091749640108433E-03 -3.2041939549238654E-03 -3.1992185204241237E-03 -3.1942486565589932E-03 -3.1892843596016880E-03 -3.1843256262065272E-03 -3.1793724530168269E-03 -3.1744248364553394E-03 -3.1694827728869523E-03 -3.1645462587950109E-03 -3.1596152907591457E-03 -3.1546898653285298E-03 -3.1497699789806957E-03 -3.1448556281615508E-03 -3.1399468091745726E-03 -3.1350435182774766E-03 -3.1301457519822859E-03 -3.1252535070681068E-03 -3.1203667801890898E-03 -3.1154855676082728E-03 -3.1106098655539517E-03 -3.1057396705529245E-03 -3.1008749792816753E-03 -3.0960157882371398E-03 -3.0911620936710320E-03 -3.0863138918873377E-03 -3.0814711794544310E-03 -3.0766339529925330E-03 -3.0718022089899159E-03 -3.0669759438466835E-03 -3.0621551539888919E-03 -3.0573398358910583E-03 -3.0525299860206436E-03 -3.0477256007842308E-03 -3.0429266765772678E-03 -3.0381332099424260E-03 -3.0333451975493400E-03 -3.0285626359055086E-03 -3.0237855211355641E-03 -3.0190138493817963E-03 -3.0142476172762911E-03 -3.0094868216463625E-03 -3.0047314590244878E-03 -2.9999815256128988E-03 -2.9952370177018686E-03 -2.9904979319029840E-03 -2.9857642648638705E-03 -2.9810360129968148E-03 -2.9763131725859216E-03 -2.9715957399799992E-03 -2.9668837116232469E-03 -2.9621770839940872E-03 -2.9574758536800279E-03 -2.9527800172809873E-03 -2.9480895711908005E-03 -2.9434045116573746E-03 -2.9387248350604199E-03 -2.9340505380330288E-03 -2.9293816171890416E-03 -2.9247180688848121E-03 -2.9200598893953321E-03 -2.9154070751176496E-03 -2.9107596225613815E-03 -2.9061175282050675E-03 -2.9014807884403747E-03 -2.8968493996710766E-03 -2.8922233584879691E-03 -2.8876026615577296E-03 -2.8829873052861731E-03 -2.8783772857683756E-03 -2.8737725992307259E-03 -2.8691732423877419E-03 -2.8645792120224832E-03 -2.8599905046000343E-03 -2.8554071163992352E-03 -2.8508290437172000E-03 -2.8462562828828206E-03 -2.8416888302758110E-03 -2.8371266824861116E-03 -2.8325698361459433E-03 -2.8280182876644117E-03 -2.8234720332818387E-03 -2.8189310693657156E-03 -2.8143953925467572E-03 -2.8098649994439256E-03 -2.8053398864223639E-03 -2.8008200497596993E-03 -2.7963054858422213E-03 -2.7917961911629549E-03 -2.7872921622053353E-03 -2.7827933954156820E-03 -2.7782998872346158E-03 -2.7738116341054077E-03 -2.7693286324730593E-03 -2.7648508787994435E-03 -2.7603783695677279E-03 -2.7559111012313521E-03 -2.7514490701346941E-03 -2.7469922726066974E-03 -2.7425407050708232E-03 -2.7380943640094857E-03 -2.7336532458936331E-03 -2.7292173471738976E-03 -2.7247866642956041E-03 -2.7203611936880397E-03 -2.7159409317800438E-03 -2.7115258750699703E-03 -2.7071160201116388E-03 -2.7027113633135199E-03 -2.6983119007696495E-03 -2.6939176286328377E-03 -2.6895285436842539E-03 -2.6851446429289028E-03 -2.6807659228451973E-03 -2.6763923793612339E-03 -2.6720240085661034E-03 -2.6676608070764166E-03 -2.6633027715805978E-03 -2.6589498985887978E-03 -2.6546021845188514E-03 -2.6502596257489677E-03 -2.6459222186049451E-03 -2.6415899594480533E-03 -2.6372628447871500E-03 -2.6329408711501068E-03 -2.6286240348735229E-03 -2.6243123321691825E-03 -2.6200057594755730E-03 -2.6157043136316024E-03 -2.6114079913864127E-03 -2.6071167888324408E-03 -2.6028307018852725E-03 -2.5985497269928335E-03 -2.5942738610608630E-03 -2.5900031007649290E-03 -2.5857374422196991E-03 -2.5814768815266248E-03 -2.5772214152292184E-03 -2.5729710400470055E-03 -2.5687257524628160E-03 -2.5644855486958362E-03 -2.5602504250590899E-03 -2.5560203781911837E-03 -2.5517954047567866E-03 -2.5475755010897004E-03 -2.5433606633455132E-03 -2.5391508878111440E-03 -2.5349461709647018E-03 -2.5307465093135388E-03 -2.5265518994233151E-03 -2.5223623378644667E-03 -2.5181778210749111E-03 -2.5139983453983192E-03 -2.5098239071635587E-03 -2.5056545026756177E-03 -2.5014901282848809E-03 -2.4973307806021440E-03 -2.4931764563099396E-03 -2.4890271517711122E-03 -2.4848828630558485E-03 -2.4807435864343101E-03 -2.4766093186924403E-03 -2.4724800566278209E-03 -2.4683557965544602E-03 -2.4642365345767434E-03 -2.4601222669941416E-03 -2.4560129903379909E-03 -2.4519087011289856E-03 -2.4478093958098203E-03 -2.4437150708087581E-03 -2.4396257225683519E-03 -2.4355413475396063E-03 -2.4314619421816142E-03 -2.4273875029656306E-03 -2.4233180263471860E-03 -2.4192535087091296E-03 -2.4151939464131418E-03 -2.4111393358003949E-03 -2.4070896731971715E-03 -2.4030449550099284E-03 -2.3990051778055399E-03 -2.3949703381588713E-03 -2.3909404325806387E-03 -2.3869154575512658E-03 -2.3828954093959962E-03 -2.3788802842889126E-03 -2.3748700785144196E-03 -2.3708647886623510E-03 -2.3668644113556776E-03 -2.3628689430882604E-03 -2.3588783802912837E-03 -2.3548927193550902E-03 -2.3509119566191066E-03 -2.3469360884457004E-03 -2.3429651112884852E-03 -2.3389990216209342E-03 -2.3350378159162212E-03 -2.3310814906466679E-03 -2.3271300422361058E-03 -2.3231834670293760E-03 -2.3192417613767391E-03 -2.3153049216877546E-03 -2.3113729443969100E-03 -2.3074458260610455E-03 -2.3035235633345466E-03 -2.2996061527097646E-03 -2.2956935903284945E-03 -2.2917858723549367E-03 -2.2878829953759407E-03 -2.2839849561288659E-03 -2.2800917510244667E-03 -2.2762033761342614E-03 -2.2723198276929091E-03 -2.2684411024368484E-03 -2.2645671971494780E-03 -2.2606981082676177E-03 -2.2568338320528556E-03 -2.2529743648189455E-03 -2.2491197029514713E-03 -2.2452698428478356E-03 -2.2414247809308791E-03 -2.2375845136373197E-03 -2.2337490374998185E-03 -2.2299183491135467E-03 -2.2260924449861146E-03 -2.2222713214710443E-03 -2.2184549749014416E-03 -2.2146434015853167E-03 -2.2108365978348375E-03 -2.2070345601739516E-03 -2.2032372853072273E-03 -2.1994447697500736E-03 -2.1956570095746832E-03 -2.1918740008893944E-03 -2.1880957404618851E-03 -2.1843222253142458E-03 -2.1805534519424518E-03 -2.1767894162603345E-03 -2.1730301143450437E-03 -2.1692755428551662E-03 -2.1655256985214657E-03 -2.1617805777340042E-03 -2.1580401767013731E-03 -2.1543044918132699E-03 -2.1505735197203798E-03 -2.1468472570269600E-03 -2.1431257000704032E-03 -2.1394088451306588E-03 -2.1356966886143715E-03 -2.1319892270174291E-03 -2.1282864568189955E-03 -2.1245883744638139E-03 -2.1208949763928896E-03 -2.1172062590473924E-03 -2.1135222188699769E-03 -2.1098428523314071E-03 -2.1061681559279614E-03 -2.1024981260975434E-03 -2.0988327591340027E-03 -2.0951720513435459E-03 -2.0915159992793693E-03 -2.0878645995981776E-03 -2.0842178487670907E-03 -2.0805757430298203E-03 -2.0769382787060118E-03 -2.0733054524013869E-03 -2.0696772607562883E-03 -2.0660537001790050E-03 -2.0624347669447908E-03 -2.0588204574121301E-03 -2.0552107680685216E-03 -2.0516056954029264E-03 -2.0480052358639485E-03 -2.0444093858899446E-03 -2.0408181419280815E-03 -2.0372315004321202E-03 -2.0336494578546385E-03 -2.0300720106455178E-03 -2.0264991552544714E-03 -2.0229308881321898E-03 -2.0193672057296748E-03 -2.0158081044971171E-03 -2.0122535808839602E-03 -2.0087036313408916E-03 -2.0051582523219406E-03 -2.0016174402801424E-03 -1.9980811916566351E-03 -1.9945495028877562E-03 -1.9910223704400630E-03 -1.9874997908180107E-03 -1.9839817604772616E-03 -1.9804682756963399E-03 -1.9769593327442314E-03 -1.9734549282053142E-03 -1.9699550588560813E-03 -1.9664597212810746E-03 -1.9629689117491929E-03 -1.9594826265388826E-03 -1.9560008621061580E-03 -1.9525236149559894E-03 -1.9490508815539688E-03 -1.9455826583342037E-03 -1.9421189417387437E-03 -1.9386597282282547E-03 -1.9352050142610652E-03 -1.9317547962662991E-03 -1.9283090706647184E-03 -1.9248678339482566E-03 -1.9214310826822321E-03 -1.9179988134107012E-03 -1.9145710226090864E-03 -1.9111477067276892E-03 -1.9077288621041949E-03 -1.9043144850230975E-03 -1.9009045719258185E-03 -1.8974991194634799E-03 -1.8940981242206423E-03 -1.8907015824806020E-03 -1.8873094904813738E-03 -1.8839218447561298E-03 -1.8805386420314648E-03 -1.8771598789482466E-03 -1.8737855519934097E-03 -1.8704156575873115E-03 -1.8670501918948113E-03 -1.8636891510278866E-03 -1.8603325315622058E-03 -1.8569803304672922E-03 -1.8536325444623697E-03 -1.8502891696727743E-03 -1.8469502021989620E-03 -1.8436156385218071E-03 -1.8402854752776138E-03 -1.8369597090675716E-03 -1.8336383364536950E-03 -1.8303213539338889E-03 -1.8270087578205177E-03 -1.8237005444111591E-03 -1.8203967101851363E-03 -1.8170972517198329E-03 -1.8138021655881023E-03 -1.8105114483549880E-03 -1.8072250965440952E-03 -1.8039431065161415E-03 -1.8006654745948514E-03 -1.7973921971513914E-03 -1.7941232705914157E-03 -1.7908586914383519E-03 -1.7875984564313864E-03 -1.7843425622582204E-03 -1.7810910052066637E-03 -1.7778437814498468E-03 -1.7746008875200153E-03 -1.7713623202743262E-03 -1.7681280763450881E-03 -1.7648981517929768E-03 -1.7616725426854505E-03 -1.7584512457522725E-03 -1.7552342580004368E-03 -1.7520215759848116E-03 -1.7488131957302795E-03 -1.7456091133968862E-03 -1.7424093256737773E-03 -1.7392138293345113E-03 -1.7360226209388097E-03 -1.7328356969213423E-03 -1.7296530536148411E-03 -1.7264746872001759E-03 -1.7233005939969843E-03 -1.7201307709735754E-03 -1.7169652152200956E-03 -1.7138039230841094E-03 -1.7106468903613609E-03 -1.7074941132418126E-03 -1.7043455887170047E-03 -1.7012013137424169E-03 -1.6980612845278800E-03 -1.6949254970394249E-03 -1.6917939477285736E-03 -1.6886666335151196E-03 -1.6855435511937533E-03 -1.6824246971864822E-03 -1.6793100678519903E-03 -1.6761996595184390E-03 -1.6730934685034984E-03 -1.6699914912603482E-03 -1.6668937244109111E-03 -1.6638001646134338E-03 -1.6607108086146986E-03 -1.6576256531348884E-03 -1.6545446943973966E-03 -1.6514679283258207E-03 -1.6483953512036289E-03 -1.6453269599009822E-03 -1.6422627512736666E-03 -1.6392027218666383E-03 -1.6361468681339434E-03 -1.6330951865058266E-03 -1.6300476733939341E-03 -1.6270043252668382E-03 -1.6239651387137519E-03 -1.6209301103102180E-03 -1.6178992364526714E-03 -1.6148725134780340E-03 -1.6118499379405389E-03 -1.6088315066173622E-03 -1.6058172161412952E-03 -1.6028070627172777E-03 -1.5998010425353414E-03 -1.5967991522808464E-03 -1.5938013888807806E-03 -1.5908077489561771E-03 -1.5878182287203592E-03 -1.5848328244284537E-03 -1.5818515325934208E-03 -1.5788743497929625E-03 -1.5759012726669268E-03 -1.5729322978943207E-03 -1.5699674220273554E-03 -1.5670066413993107E-03 -1.5640499523839209E-03 -1.5610973516615111E-03 -1.5581488359898128E-03 -1.5552044018276509E-03 -1.5522640453813059E-03 -1.5493277629860115E-03 -1.5463955512842833E-03 -1.5434674069595197E-03 -1.5405433266885641E-03 -1.5376233071380003E-03 -1.5347073447704192E-03 -1.5317954358256736E-03 -1.5288875766283228E-03 -1.5259837637877553E-03 -1.5230839939706239E-03 -1.5201882638865905E-03 -1.5172965702624057E-03 -1.5144089095423623E-03 -1.5115252777721509E-03 -1.5086456711331814E-03 -1.5057700864640939E-03 -1.5028985207444390E-03 -1.5000309706703551E-03 -1.4971674327391834E-03 -1.4943079033398468E-03 -1.4914523786701372E-03 -1.4886008550149940E-03 -1.4857533292312564E-03 -1.4829097983416681E-03 -1.4800702589192506E-03 -1.4772347071319955E-03 -1.4744031392500650E-03 -1.4715755518236440E-03 -1.4687519414481596E-03 -1.4659323047484282E-03 -1.4631166383596930E-03 -1.4603049388417326E-03 -1.4574972026665611E-03 -1.4546934263393019E-03 -1.4518936064860874E-03 -1.4490977397505652E-03 -1.4463058227119072E-03 -1.4435178519109505E-03 -1.4407338238113657E-03 -1.4379537347615952E-03 -1.4351775811736096E-03 -1.4324053597703718E-03 -1.4296370673458094E-03 -1.4268727005273976E-03 -1.4241122558185384E-03 -1.4213557296715174E-03 -1.4186031184444830E-03 -1.4158544185379511E-03 -1.4131096266569918E-03 -1.4103687396067209E-03 -1.4076317540206451E-03 -1.4048986663676591E-03 -1.4021694731180029E-03 -1.3994441707624794E-03 -1.3967227558131727E-03 -1.3940052249219793E-03 -1.3912915748004839E-03 -1.3885818019585530E-03 -1.3858759026561002E-03 -1.3831738732859699E-03 -1.3804757107477997E-03 -1.3777814120078491E-03 -1.3750909735841602E-03 -1.3724043917236945E-03 -1.3697216628484189E-03 -1.3670427836666502E-03 -1.3643677508686568E-03 -1.3616965609445266E-03 -1.3590292103359658E-03 -1.3563656956219873E-03 -1.3537060134896826E-03 -1.3510501605467498E-03 -1.3483981332289394E-03 -1.3457499279920021E-03 -1.3431055415473775E-03 -1.3404649706958152E-03 -1.3378282120505782E-03 -1.3351952620335580E-03 -1.3325661171247232E-03 -1.3299407739875710E-03 -1.3273192292965049E-03 -1.3247014795548702E-03 -1.3220875211843331E-03 -1.3194773507603833E-03 -1.3168709650619090E-03 -1.3142683608238456E-03 -1.3116695345691235E-03 -1.3090744827717101E-03 -1.3064832019007721E-03 -1.3038956884238821E-03 -1.3013119389305473E-03 -1.2987319502184387E-03 -1.2961557190390468E-03 -1.2935832418170304E-03 -1.2910145148984744E-03 -1.2884495350011984E-03 -1.2858882991546089E-03 -1.2833308041119216E-03 -1.2807770459884549E-03 -1.2782270209162386E-03 -1.2756807257101135E-03 -1.2731381574459062E-03 -1.2705993127499124E-03 -1.2680641877597051E-03 -1.2655327788211870E-03 -1.2630050829668883E-03 -1.2604810972927851E-03 -1.2579608183270077E-03 -1.2554442422983291E-03 -1.2529313656041729E-03 -1.2504221848824576E-03 -1.2479166968073106E-03 -1.2454148981246159E-03 -1.2429167855800174E-03 -1.2404223556888782E-03 -1.2379316048090278E-03 -1.2354445295035647E-03 -1.2329611267150769E-03 -1.2304813933327558E-03 -1.2280053257510927E-03 -1.2255329202168375E-03 -1.2230641732602677E-03 -1.2205990816656841E-03 -1.2181376421899000E-03 -1.2156798515027155E-03 -1.2132257062597910E-03 -1.2107752031063838E-03 -1.2083283386795233E-03 -1.2058851095046953E-03 -1.2034455119785210E-03 -1.2010095426092696E-03 -1.1985771982808550E-03 -1.1961484759111362E-03 -1.1937233720223464E-03 -1.1913018829164972E-03 -1.1888840051688999E-03 -1.1864697357668872E-03 -1.1840590715921906E-03 -1.1816520089376814E-03 -1.1792485439793528E-03 -1.1768486734383245E-03 -1.1744523944362060E-03 -1.1720597038411286E-03 -1.1696705980104730E-03 -1.1672850733039355E-03 -1.1649031264276224E-03 -1.1625247542009923E-03 -1.1601499532581997E-03 -1.1577787200569376E-03 -1.1554110511816746E-03 -1.1530469435584306E-03 -1.1506863940993180E-03 -1.1483293991947070E-03 -1.1459759550045765E-03 -1.1436260581125061E-03 -1.1412797056245671E-03 -1.1389368945090000E-03 -1.1365976211575451E-03 -1.1342618818763843E-03 -1.1319296733637802E-03 -1.1296009925534710E-03 -1.1272758362180163E-03 -1.1249542008681384E-03 -1.1226360830253032E-03 -1.1203214793658379E-03 -1.1180103866091015E-03 -1.1157028014604400E-03 -1.1133987206139561E-03 -1.1110981407251210E-03 -1.1088010583699482E-03 -1.1065074701235376E-03 -1.1042173726159429E-03 -1.1019307625028754E-03 -1.0996476365552686E-03 -1.0973679916607372E-03 -1.0950918245690568E-03 -1.0928191316390537E-03 -1.0905499092225732E-03 -1.0882841541651755E-03 -1.0860218635495571E-03 -1.0837630341352471E-03 -1.0815076622564214E-03 -1.0792557443165785E-03 -1.0770072770762622E-03 -1.0747622573773542E-03 -1.0725206820623924E-03 -1.0702825479719338E-03 -1.0680478517582361E-03 -1.0658165897541039E-03 -1.0635887583705457E-03 -1.0613643545512640E-03 -1.0591433753758127E-03 -1.0569258174746902E-03 -1.0547116771036412E-03 -1.0525009507441699E-03 -1.0502936354039461E-03 -1.0480897280963348E-03 -1.0458892254070961E-03 -1.0436921237572648E-03 -1.0414984197834917E-03 -1.0393081103556190E-03 -1.0371211922869036E-03 -1.0349376621909565E-03 -1.0327575166648672E-03 -1.0305807524848317E-03 -1.0284073665184172E-03 -1.0262373554664867E-03 -1.0240707157963306E-03 -1.0219074440410178E-03 -1.0197475370585323E-03 -1.0175909917589125E-03 -1.0154378047034082E-03 -1.0132879722166139E-03 -1.0111414909811166E-03 -1.0089983583357817E-03 -1.0068585715025168E-03 -1.0047221267274076E-03 -1.0025890199725892E-03 -1.0004592478568678E-03 -9.9833280758347990E-04 -9.9620969619528595E-04 -9.9408991030649498E-04 -9.9197344648830894E-04 -9.8986030144761769E-04 -9.8775047194858559E-04 -9.8564395471468016E-04 -9.8354074642233776E-04 -9.8144084374922032E-04 -9.7934424338503114E-04 -9.7725094203126792E-04 -9.7516093648198287E-04 -9.7307422358196847E-04 -9.7099080008881879E-04 -9.6891066262983969E-04 -9.6683380784267823E-04 -9.6476023245287796E-04 -9.6268993320985680E-04 -9.6062290687388280E-04 -9.5855915021314693E-04 -9.5649865998655647E-04 -9.5444143293477537E-04 -9.5238746579216630E-04 -9.5033675526928676E-04 -9.4828929806929792E-04 -9.4624509091474824E-04 -9.4420413054656913E-04 -9.4216641371011101E-04 -9.4013193716006741E-04 -9.3810069765573871E-04 -9.3607269198062420E-04 -9.3404791692841321E-04 -9.3202636925920359E-04 -9.3000804569193978E-04 -9.2799294294361771E-04 -9.2598105773307167E-04 -9.2397238678071575E-04 -9.2196692681976858E-04 -9.1996467459221835E-04 -9.1796562690658477E-04 -9.1596978067648731E-04 -9.1397713275444248E-04 -9.1198767967540857E-04 -9.1000141790879678E-04 -9.0801834429123031E-04 -9.0603845594505468E-04 -9.0406174979552575E-04 -9.0208822234582426E-04 -9.0011787009992806E-04 -8.9815068988281321E-04 -8.9618667863654094E-04 -8.9422583322453072E-04 -8.9226815043062216E-04 -8.9031362700993410E-04 -8.8836225964906924E-04 -8.8641404503308021E-04 -8.8446897992931121E-04 -8.8252706114554894E-04 -8.8058828548176406E-04 -8.7865264972733221E-04 -8.7672015066918611E-04 -8.7479078508793560E-04 -8.7286454976561291E-04 -8.7094144151740409E-04 -8.6902145717940998E-04 -8.6710459355827767E-04 -8.6519084741037804E-04 -8.6328021547645332E-04 -8.6137269444503035E-04 -8.5946828099979305E-04 -8.5756697200978118E-04 -8.5566876449764604E-04 -8.5377365536622098E-04 -8.5188164124407853E-04 -8.4999271875282401E-04 -8.4810688470766287E-04 -8.4622413599999514E-04 -8.4434446948022381E-04 -8.4246788195455004E-04 -8.4059437020884650E-04 -8.3872393097622047E-04 -8.3685656099583808E-04 -8.3499225714661390E-04 -8.3313101637775145E-04 -8.3127283548563953E-04 -8.2941771105403731E-04 -8.2756563975158639E-04 -8.2571661863738545E-04 -8.2387064483467490E-04 -8.2202771507905816E-04 -8.2018782584270314E-04 -8.1835097380289360E-04 -8.1651715601509830E-04 -8.1468636951449898E-04 -8.1285861102484483E-04 -8.1103387717716680E-04 -8.0921216475860218E-04 -8.0739347069449477E-04 -8.0557779189380100E-04 -8.0376512521564700E-04 -8.0195546750427631E-04 -8.0014881554976930E-04 -7.9834516611909743E-04 -7.9654451598425288E-04 -7.9474686192310010E-04 -7.9295220075089831E-04 -7.9116052939857951E-04 -7.8937184480919740E-04 -7.8758614382485790E-04 -7.8580342323157192E-04 -7.8402367984982521E-04 -7.8224691055195957E-04 -7.8047311219726293E-04 -7.7870228157316120E-04 -7.7693441545463886E-04 -7.7516951070361875E-04 -7.7340756424490713E-04 -7.7164857293880143E-04 -7.6989253351899102E-04 -7.6813944274629756E-04 -7.6638929761367841E-04 -7.6464209518439872E-04 -7.6289783230477904E-04 -7.6115650561682003E-04 -7.5941811184742324E-04 -7.5768264795748777E-04 -7.5595011092788084E-04 -7.5422049761529966E-04 -7.5249380482080648E-04 -7.5077002939293979E-04 -7.4904916823828941E-04 -7.4733121824531381E-04 -7.4561617623011053E-04 -7.4390403900167232E-04 -7.4219480345385450E-04 -7.4048846653080420E-04 -7.3878502513833558E-04 -7.3708447612090826E-04 -7.3538681631895913E-04 -7.3369204257906395E-04 -7.3200015175197081E-04 -7.3031114072569724E-04 -7.2862500641711857E-04 -7.2694174572558723E-04 -7.2526135551298086E-04 -7.2358383263563392E-04 -7.2190917394408176E-04 -7.2023737629150824E-04 -7.1856843664217440E-04 -7.1690235207153789E-04 -7.1523911953658050E-04 -7.1357873566146152E-04 -7.1192119706619931E-04 -7.1026650079336682E-04 -7.0861464408560591E-04 -7.0696562390484049E-04 -7.0531943684797309E-04 -7.0367607958707942E-04 -7.0203554915153463E-04 -7.0039784264089690E-04 -6.9876295703938114E-04 -6.9713088925633633E-04 -6.9550163611781636E-04 -6.9387519431229644E-04 -6.9225156059041356E-04 -6.9063073206540918E-04 -6.8901270594374662E-04 -6.8739747916847721E-04 -6.8578504846509376E-04 -6.8417541062263624E-04 -6.8256856258360735E-04 -6.8096450129985725E-04 -6.7936322365194581E-04 -6.7776472649555661E-04 -6.7616900677843611E-04 -6.7457606154662389E-04 -6.7298588780878208E-04 -6.7139848245165309E-04 -6.6981384234329202E-04 -6.6823196438024356E-04 -6.6665284547398683E-04 -6.6507648253572970E-04 -6.6350287247611398E-04 -6.6193201222185043E-04 -6.6036389876172278E-04 -6.5879852909500429E-04 -6.5723590016476981E-04 -6.5567600887573218E-04 -6.5411885212807825E-04 -6.5256442681518618E-04 -6.5101272984823412E-04 -6.4946375823410351E-04 -6.4791750900484134E-04 -6.4637397908745987E-04 -6.4483316531670698E-04 -6.4329506458596212E-04 -6.4175967393327496E-04 -6.4022699040286544E-04 -6.3869701093765326E-04 -6.3716973243802108E-04 -6.3564515182521690E-04 -6.3412326604437403E-04 -6.3260407205514998E-04 -6.3108756685825490E-04 -6.2957374745802172E-04 -6.2806261081725775E-04 -6.2655415387547690E-04 -6.2504837356750084E-04 -6.2354526682163194E-04 -6.2204483057694217E-04 -6.2054706181925636E-04 -6.1905195754661808E-04 -6.1755951475868213E-04 -6.1606973045603411E-04 -6.1458260161314701E-04 -6.1309812515462513E-04 -6.1161629801101305E-04 -6.1013711717703431E-04 -6.0866057966867614E-04 -6.0718668248313707E-04 -6.0571542259993155E-04 -6.0424679697691362E-04 -6.0278080251942691E-04 -6.0131743614752335E-04 -5.9985669495337475E-04 -5.9839857610396779E-04 -5.9694307664164220E-04 -5.9549019345766477E-04 -5.9403992343840797E-04 -5.9259226348407253E-04 -5.9114721051437349E-04 -5.8970476162329203E-04 -5.8826491400640714E-04 -5.8682766471696869E-04 -5.8539301058361149E-04 -5.8396094846223368E-04 -5.8253147541707372E-04 -5.8110458856543048E-04 -5.7968028495075207E-04 -5.7825856155945530E-04 -5.7683941537937402E-04 -5.7542284340419525E-04 -5.7400884262927211E-04 -5.7259741005557423E-04 -5.7118854268713994E-04 -5.6978223755036329E-04 -5.6837849169388876E-04 -5.6697730215302371E-04 -5.6557866592471518E-04 -5.6418258000362140E-04 -5.6278904141768542E-04 -5.6139804721086375E-04 -5.6000959441897832E-04 -5.5862368006723740E-04 -5.5724030117643316E-04 -5.5585945475406038E-04 -5.5448113780739755E-04 -5.5310534737514332E-04 -5.5173208051588496E-04 -5.5036133428265665E-04 -5.4899310571872675E-04 -5.4762739186184101E-04 -5.4626418972775626E-04 -5.4490349632752640E-04 -5.4354530870289711E-04 -5.4218962392083253E-04 -5.4083643904334535E-04 -5.3948575112006591E-04 -5.3813755719650503E-04 -5.3679185430211061E-04 -5.3544863946131485E-04 -5.3410790973303177E-04 -5.3276966221274069E-04 -5.3143389397701903E-04 -5.3010060204306008E-04 -5.2876978342487261E-04 -5.2744143520195479E-04 -5.2611555448687456E-04 -5.2479213834754821E-04 -5.2347118379030921E-04 -5.2215268783690593E-04 -5.2083664758519142E-04 -5.1952306014793040E-04 -5.1821192259669975E-04 -5.1690323197533139E-04 -5.1559698534115004E-04 -5.1429317977641433E-04 -5.1299181236552779E-04 -5.1169288019081174E-04 -5.1039638033309638E-04 -5.0910230985845432E-04 -5.0781066582013246E-04 -5.0652144529100504E-04 -5.0523464539065739E-04 -5.0395026323762232E-04 -5.0266829589709541E-04 -5.0138874041289502E-04 -5.0011159386477357E-04 -4.9883685337314559E-04 -4.9756451604873666E-04 -4.9629457896571748E-04 -4.9502703919445908E-04 -4.9376189383590157E-04 -4.9249914000789187E-04 -4.9123877482365431E-04 -4.8998079538939789E-04 -4.8872519880327253E-04 -4.8747198213251974E-04 -4.8622114244079208E-04 -4.8497267685096267E-04 -4.8372658252830096E-04 -4.8248285660350461E-04 -4.8124149613992752E-04 -4.8000249820633598E-04 -4.7876585994295357E-04 -4.7753157851214060E-04 -4.7629965102742984E-04 -4.7507007455693839E-04 -4.7384284619382533E-04 -4.7261796309788350E-04 -4.7139542243156726E-04 -4.7017522130096061E-04 -4.6895735678753944E-04 -4.6774182600454415E-04 -4.6652862610353693E-04 -4.6531775423375084E-04 -4.6410920752922008E-04 -4.6290298311931426E-04 -4.6169907811742316E-04 -4.6049748962799465E-04 -4.5929821478718464E-04 -4.5810125078061306E-04 -4.5690659478451860E-04 -4.5571424391471391E-04 -4.5452419527215228E-04 -4.5333644598498444E-04 -4.5215099320230096E-04 -4.5096783408132569E-04 -4.4978696579464947E-04 -4.4860838551022587E-04 -4.4743209035745681E-04 -4.4625807745316248E-04 -4.4508634395082954E-04 -4.4391688704025259E-04 -4.4274970389712932E-04 -4.4158479165547465E-04 -4.4042214744585521E-04 -4.3926176842663795E-04 -4.3810365176989903E-04 -4.3694779465661880E-04 -4.3579419427906401E-04 -4.3464284781451147E-04 -4.3349375238450796E-04 -4.3234690510504848E-04 -4.3120230316894453E-04 -4.3005994381692652E-04 -4.2891982424419237E-04 -4.2778194156929938E-04 -4.2664629292012531E-04 -4.2551287550307457E-04 -4.2438168654557521E-04 -4.2325272323786304E-04 -4.2212598273981620E-04 -4.2100146221875226E-04 -4.1987915885999597E-04 -4.1875906985135023E-04 -4.1764119238133434E-04 -4.1652552363897750E-04 -4.1541206081891532E-04 -4.1430080112168829E-04 -4.1319174174724282E-04 -4.1208487989301409E-04 -4.1098021275622640E-04 -4.0987773753609709E-04 -4.0877745143278442E-04 -4.0767935164276388E-04 -4.0658343535747860E-04 -4.0548969977385142E-04 -4.0439814211107073E-04 -4.0330875959207143E-04 -4.0222154942066741E-04 -4.0113650878802459E-04 -4.0005363490412091E-04 -3.9897292501258594E-04 -3.9789437635327632E-04 -3.9681798612928738E-04 -3.9574375153287098E-04 -3.9467166977180847E-04 -3.9360173806743702E-04 -3.9253395364837021E-04 -3.9146831375899043E-04 -3.9040481564228582E-04 -3.8934345651626148E-04 -3.8828423358904109E-04 -3.8722714408732147E-04 -3.8617218525868112E-04 -3.8511935434421820E-04 -3.8406864856176917E-04 -3.8302006512820402E-04 -3.8197360129321191E-04 -3.8092925432424538E-04 -3.7988702147068041E-04 -3.7884689995539190E-04 -3.7780888700629772E-04 -3.7677297988041134E-04 -3.7573917584066499E-04 -3.7470747212964202E-04 -3.7367786597548538E-04 -3.7265035462479722E-04 -3.7162493535957146E-04 -3.7060160545849597E-04 -3.6958036216069336E-04 -3.6856120269293828E-04 -3.6754412430540026E-04 -3.6652912426992501E-04 -3.6551619986124672E-04 -3.6450534835923924E-04 -3.6349656704170416E-04 -3.6248985316521211E-04 -3.6148520397726117E-04 -3.6048261674102996E-04 -3.5948208873850065E-04 -3.5848361724867859E-04 -3.5748719953720807E-04 -3.5649283286955092E-04 -3.5550051453750442E-04 -3.5451024184796846E-04 -3.5352201208291051E-04 -3.5253582248547498E-04 -3.5155167030916963E-04 -3.5056955286759183E-04 -3.4958946748838310E-04 -3.4861141146307913E-04 -3.4763538205572929E-04 -3.4666137654230825E-04 -3.4568939222417110E-04 -3.4471942640493269E-04 -3.4375147638355630E-04 -3.4278553945702914E-04 -3.4182161291629169E-04 -3.4085969404634936E-04 -3.3989978014597468E-04 -3.3894186855106342E-04 -3.3798595659736324E-04 -3.3703204157062376E-04 -3.3608012073345643E-04 -3.3513019138330905E-04 -3.3418225086211069E-04 -3.3323629650973272E-04 -3.3229232564867516E-04 -3.3135033559637865E-04 -3.3041032365629144E-04 -3.2947228712324714E-04 -3.2853622330335669E-04 -3.2760212952151447E-04 -3.2667000310881739E-04 -3.2573984141732445E-04 -3.2481164180308056E-04 -3.2388540158639662E-04 -3.2296111805862345E-04 -3.2203878852729860E-04 -3.2111841033651462E-04 -3.2019998083667486E-04 -3.1928349738814430E-04 -3.1836895735378753E-04 -3.1745635806145579E-04 -3.1654569680229468E-04 -3.1563697088945119E-04 -3.1473017770336129E-04 -3.1382531463173489E-04 -3.1292237902260398E-04 -3.1202136820376582E-04 -3.1112227951116692E-04 -3.1022511029201968E-04 -3.0932985789923251E-04 -3.0843651970428350E-04 -3.0754509308111318E-04 -3.0665557538020466E-04 -3.0576796393652248E-04 -3.0488225610071071E-04 -3.0399844925145606E-04 -3.0311654076886971E-04 -3.0223652802587806E-04 -3.0135840839304095E-04 -3.0048217923910330E-04 -2.9960783793121304E-04 -2.9873538183085741E-04 -2.9786480828662953E-04 -2.9699611465323352E-04 -2.9612929833956557E-04 -2.9526435677575163E-04 -2.9440128735003143E-04 -2.9354008740383180E-04 -2.9268075428900969E-04 -2.9182328539658568E-04 -2.9096767812439810E-04 -2.9011392986472108E-04 -2.8926203800694810E-04 -2.8841199994932996E-04 -2.8756381310292289E-04 -2.8671747487371357E-04 -2.8587298264306528E-04 -2.8503033378750201E-04 -2.8418952570259345E-04 -2.8335055579745383E-04 -2.8251342147831966E-04 -2.8167812014550406E-04 -2.8084464919924637E-04 -2.8001300604293098E-04 -2.7918318808191431E-04 -2.7835519273943676E-04 -2.7752901745517537E-04 -2.7670465965436559E-04 -2.7588211672527384E-04 -2.7506138605561082E-04 -2.7424246507009898E-04 -2.7342535120949317E-04 -2.7261004189661720E-04 -2.7179653453291152E-04 -2.7098482653091635E-04 -2.7017491534338895E-04 -2.6936679842746802E-04 -2.6856047320136437E-04 -2.6775593706090793E-04 -2.6695318742646541E-04 -2.6615222175649459E-04 -2.6535303750976463E-04 -2.6455563213225304E-04 -2.6376000306515786E-04 -2.6296614773066402E-04 -2.6217406353667625E-04 -2.6138374791201846E-04 -2.6059519832804661E-04 -2.5980841225956475E-04 -2.5902338717196635E-04 -2.5824012052597979E-04 -2.5745860975496902E-04 -2.5667885226554680E-04 -2.5590084548897867E-04 -2.5512458692431971E-04 -2.5435007407460406E-04 -2.5357730438678764E-04 -2.5280627528183227E-04 -2.5203698421201172E-04 -2.5126942866938957E-04 -2.5050360614338062E-04 -2.4973951410520471E-04 -2.4897715002156163E-04 -2.4821651135305939E-04 -2.4745759555662146E-04 -2.4670040009769286E-04 -2.4594492245575030E-04 -2.4519116011228326E-04 -2.4443911055212171E-04 -2.4368877126110957E-04 -2.4294013972568765E-04 -2.4219321343274782E-04 -2.4144798986642848E-04 -2.4070446650494769E-04 -2.3996264082951698E-04 -2.3922251034507767E-04 -2.3848407256491744E-04 -2.3774732498037137E-04 -2.3701226505989595E-04 -2.3627889028476990E-04 -2.3554719817543818E-04 -2.3481718625514202E-04 -2.3408885201225643E-04 -2.3336219291806594E-04 -2.3263720647495094E-04 -2.3191389022732891E-04 -2.3119224171020834E-04 -2.3047225841212445E-04 -2.2975393781380146E-04 -2.2903727743349295E-04 -2.2832227481420016E-04 -2.2760892747940965E-04 -2.2689723291778352E-04 -2.2618718862464738E-04 -2.2547879214646776E-04 -2.2477204104376689E-04 -2.2406693284121297E-04 -2.2336346503271494E-04 -2.2266163512935880E-04 -2.2196144068372696E-04 -2.2126287924886782E-04 -2.2056594834178020E-04 -2.1987064546557627E-04 -2.1917696815486627E-04 -2.1848491397922975E-04 -2.1779448050130592E-04 -2.1710566525727973E-04 -2.1641846577840417E-04 -2.1573287959633812E-04 -2.1504890424325695E-04 -2.1436653726598443E-04 -2.1368577623232307E-04 -2.1300661870922709E-04 -2.1232906225371803E-04 -2.1165310441933737E-04 -2.1097874274670980E-04 -2.1030597476750625E-04 -2.0963479803354969E-04 -2.0896521013453835E-04 -2.0829720865874716E-04 -2.0763079116440554E-04 -2.0696595520037665E-04 -2.0630269833039682E-04 -2.0564101813180737E-04 -2.0498091217509076E-04 -2.0432237801275508E-04 -2.0366541320171696E-04 -2.0301001535094954E-04 -2.0235618209093353E-04 -2.0170391099941267E-04 -2.0105319959175976E-04 -2.0040404540584144E-04 -1.9975644606400923E-04 -1.9911039920142800E-04 -1.9846590241004279E-04 -1.9782295325680957E-04 -1.9718154931896122E-04 -1.9654168818988588E-04 -1.9590336746511502E-04 -1.9526658474358852E-04 -1.9463133762504146E-04 -1.9399762370735882E-04 -1.9336544058705613E-04 -1.9273478586323285E-04 -1.9210565714020909E-04 -1.9147805202457602E-04 -1.9085196813261294E-04 -1.9022740308359553E-04 -1.8960435448584303E-04 -1.8898281993702155E-04 -1.8836279704182037E-04 -1.8774428342445052E-04 -1.8712727671168708E-04 -1.8651177452567013E-04 -1.8589777448633880E-04 -1.8528527421344282E-04 -1.8467427132651899E-04 -1.8406476344682009E-04 -1.8345674820158112E-04 -1.8285022321985276E-04 -1.8224518613630853E-04 -1.8164163458910483E-04 -1.8103956621557470E-04 -1.8043897865162352E-04 -1.7983986953304225E-04 -1.7924223649568260E-04 -1.7864607717548041E-04 -1.7805138920948312E-04 -1.7745817023569240E-04 -1.7686641790296592E-04 -1.7627612988315599E-04 -1.7568730384499132E-04 -1.7509993741922497E-04 -1.7451402822311698E-04 -1.7392957390317650E-04 -1.7334657213625109E-04 -1.7276502059852627E-04 -1.7218491696041258E-04 -1.7160625888939390E-04 -1.7102904403647112E-04 -1.7045327004452354E-04 -1.6987893456680311E-04 -1.6930603527052032E-04 -1.6873456982653096E-04 -1.6816453591564601E-04 -1.6759593122124740E-04 -1.6702875342969429E-04 -1.6646300022917168E-04 -1.6589866929560122E-04 -1.6533575828357229E-04 -1.6477426485186653E-04 -1.6421418669086346E-04 -1.6365552150023445E-04 -1.6309826696971262E-04 -1.6254242078055751E-04 -1.6198798062196028E-04 -1.6143494420170287E-04 -1.6088330922511067E-04 -1.6033307336360924E-04 -1.5978423427610527E-04 -1.5923678966336423E-04 -1.5869073727234161E-04 -1.5814607483297490E-04 -1.5760280001701979E-04 -1.5706091049060928E-04 -1.5652040396856642E-04 -1.5598127819169773E-04 -1.5544353088041941E-04 -1.5490715972574524E-04 -1.5437216242304185E-04 -1.5383853669415781E-04 -1.5330628026692170E-04 -1.5277539086049345E-04 -1.5224586618800621E-04 -1.5171770396981638E-04 -1.5119090193988944E-04 -1.5066545783009577E-04 -1.5014136935311920E-04 -1.4961863421648271E-04 -1.4909725015222551E-04 -1.4857721491467275E-04 -1.4805852625091170E-04 -1.4754118188849033E-04 -1.4702517955447343E-04 -1.4651051699355715E-04 -1.4599719195774064E-04 -1.4548520218332506E-04 -1.4497454538815131E-04 -1.4446521930336050E-04 -1.4395722170626872E-04 -1.4345055037979352E-04 -1.4294520306995287E-04 -1.4244117750169535E-04 -1.4193847141585130E-04 -1.4143708257774876E-04 -1.4093700875181204E-04 -1.4043824768977077E-04 -1.3994079714119305E-04 -1.3944465487374105E-04 -1.3894981866859448E-04 -1.3845628630000998E-04 -1.3796405552792993E-04 -1.3747312411226898E-04 -1.3698348982248552E-04 -1.3649515043169145E-04 -1.3600810371793413E-04 -1.3552234746402794E-04 -1.3503787945053455E-04 -1.3455469745164556E-04 -1.3407279924285948E-04 -1.3359218261792204E-04 -1.3311284537847811E-04 -1.3263478529994960E-04 -1.3215800012494230E-04 -1.3168248761856813E-04 -1.3120824563077482E-04 -1.3073527202279788E-04 -1.3026356457915796E-04 -1.2979312103747684E-04 -1.2932393916424565E-04 -1.2885601677374673E-04 -1.2838935168237270E-04 -1.2792394169615671E-04 -1.2745978461899059E-04 -1.2699687826834508E-04 -1.2653522047246114E-04 -1.2607480904763284E-04 -1.2561564178432727E-04 -1.2515771647488008E-04 -1.2470103094366379E-04 -1.2424558302695488E-04 -1.2379137055128019E-04 -1.2333839133310041E-04 -1.2288664318559577E-04 -1.2243612391412206E-04 -1.2198683132765044E-04 -1.2153876327736009E-04 -1.2109191763494040E-04 -1.2064629223897621E-04 -1.2020188488382239E-04 -1.1975869337434858E-04 -1.1931671556574904E-04 -1.1887594932298578E-04 -1.1843639248842238E-04 -1.1799804288972014E-04 -1.1756089836720396E-04 -1.1712495678347432E-04 -1.1669021599463508E-04 -1.1625667381357130E-04 -1.1582432804371164E-04 -1.1539317655729180E-04 -1.1496321728485507E-04 -1.1453444811676964E-04 -1.1410686684864633E-04 -1.1368047127740235E-04 -1.1325525929572411E-04 -1.1283122883348140E-04 -1.1240837776079333E-04 -1.1198670388216198E-04 -1.1156620502140996E-04 -1.1114687906992648E-04 -1.1072872393109012E-04 -1.1031173750329993E-04 -1.0989591768169766E-04 -1.0948126233394042E-04 -1.0906776928881729E-04 -1.0865543638998033E-04 -1.0824426155198736E-04 -1.0783424270345686E-04 -1.0742537772628307E-04 -1.0701766446993445E-04 -1.0661110081358107E-04 -1.0620568469224166E-04 -1.0580141403398707E-04 -1.0539828669771091E-04 -1.0499630052194790E-04 -1.0459545339622522E-04 -1.0419574325618418E-04 -1.0379716803150123E-04 -1.0339972563345354E-04 -1.0300341396782983E-04 -1.0260823092035458E-04 -1.0221417436885522E-04 -1.0182124221980284E-04 -1.0142943241312456E-04 -1.0103874288093433E-04 -1.0064917152433971E-04 -1.0026071624097474E-04 -9.9873374955596422E-05 -9.9487145608315408E-05 -9.9102026125888387E-05 -9.8718014414646613E-05 -9.8335108386024710E-05 -9.7953305980525736E-05 -9.7572605145278390E-05 -9.7193003811110542E-05 -9.6814499896751406E-05 -9.6437091327374440E-05 -9.6060776041380515E-05 -9.5685551980031509E-05 -9.5311417092173783E-05 -9.4938369328841901E-05 -9.4566406629991616E-05 -9.4195526924932535E-05 -9.3825728151024181E-05 -9.3457008267507470E-05 -9.3089365235696480E-05 -9.2722797005895334E-05 -9.2357301523510353E-05 -9.1992876743739630E-05 -9.1629520633974273E-05 -9.1267231159325668E-05 -9.0906006274484865E-05 -9.0545843932583398E-05 -9.0186742094073481E-05 -8.9828698723978342E-05 -8.9471711792927995E-05 -8.9115779280456574E-05 -8.8760899165391934E-05 -8.8407069419635021E-05 -8.8054288013531611E-05 -8.7702552924215767E-05 -8.7351862134199085E-05 -8.7002213623497735E-05 -8.6653605366587762E-05 -8.6306035339161986E-05 -8.5959501528752821E-05 -8.5614001927489456E-05 -8.5269534529277231E-05 -8.4926097329836376E-05 -8.4583688323535769E-05 -8.4242305500781503E-05 -8.3901946852473375E-05 -8.3562610379383129E-05 -8.3224294087111923E-05 -8.2886995976054823E-05 -8.2550714039673675E-05 -8.2215446276485301E-05 -8.1881190705353741E-05 -8.1547945348697012E-05 -8.1215708215571543E-05 -8.0884477306409735E-05 -8.0554250630729320E-05 -8.0225026213866959E-05 -7.9896802080628039E-05 -7.9569576245518489E-05 -7.9243346720392360E-05 -7.8918111526121311E-05 -7.8593868691210258E-05 -7.8270616247047282E-05 -7.7948352230950631E-05 -7.7627074678804719E-05 -7.7306781611604535E-05 -7.6987471044910908E-05 -7.6669141011771020E-05 -7.6351789564310744E-05 -7.6035414754020014E-05 -7.5720014627657796E-05 -7.5405587229888211E-05 -7.5092130594193627E-05 -7.4779642748366910E-05 -7.4468121734227387E-05 -7.4157565613415942E-05 -7.3847972448730779E-05 -7.3539340301645670E-05 -7.3231667232302128E-05 -7.2924951287844730E-05 -7.2619190506537768E-05 -7.2314382942821766E-05 -7.2010526681037348E-05 -7.1707619804398895E-05 -7.1405660373229148E-05 -7.1104646440854922E-05 -7.0804576071446888E-05 -7.0505447338938885E-05 -7.0207258319636908E-05 -6.9910007094701915E-05 -6.9613691744623157E-05 -6.9318310339979331E-05 -6.9023860947613934E-05 -6.8730341652682085E-05 -6.8437750561598450E-05 -6.8146085772463765E-05 -6.7855345353211110E-05 -6.7565527368836596E-05 -6.7276629914453766E-05 -6.6988651102286442E-05 -6.6701589038629082E-05 -6.6415441820587569E-05 -6.6130207543890052E-05 -6.5845884301619280E-05 -6.5562470186698068E-05 -6.5279963299665698E-05 -6.4998361746743295E-05 -6.4717663637937014E-05 -6.4437867090374551E-05 -6.4158970221313302E-05 -6.3880971144044269E-05 -6.3603867970433870E-05 -6.3327658811871321E-05 -6.3052341779307511E-05 -6.2777914991892555E-05 -6.2504376589829575E-05 -6.2231724712780774E-05 -6.1959957470426167E-05 -6.1689072959282223E-05 -6.1419069305071152E-05 -6.1149944669662624E-05 -6.0881697207537162E-05 -6.0614325040378435E-05 -6.0347826284485078E-05 -6.0082199073351376E-05 -5.9817441551002304E-05 -5.9553551864781782E-05 -5.9290528167101380E-05 -5.9028368608709621E-05 -5.8767071330695509E-05 -5.8506634472157313E-05 -5.8247056184018002E-05 -5.7988334626524780E-05 -5.7730467958327895E-05 -5.7473454334226121E-05 -5.7217291909289666E-05 -5.6961978843209292E-05 -5.6707513297527025E-05 -5.6453893436095068E-05 -5.6201117425115373E-05 -5.5949183432121417E-05 -5.5698089628008121E-05 -5.5447834184366195E-05 -5.5198415273820867E-05 -5.4949831069578144E-05 -5.4702079747426482E-05 -5.4455159486536580E-05 -5.4209068467222183E-05 -5.3963804873129969E-05 -5.3719366888711982E-05 -5.3475752698946390E-05 -5.3232960489194142E-05 -5.2990988448097982E-05 -5.2749834769884177E-05 -5.2509497648991556E-05 -5.2269975278246946E-05 -5.2031265850402013E-05 -5.1793367565427378E-05 -5.1556278629351544E-05 -5.1319997246173980E-05 -5.1084521614965929E-05 -5.0849849935819710E-05 -5.0615980419977756E-05 -5.0382911283085579E-05 -5.0150640737440521E-05 -4.9919166991702863E-05 -4.9688488256994422E-05 -4.9458602752212406E-05 -4.9229508697727461E-05 -4.9001204314341413E-05 -4.8773687823155510E-05 -4.8546957448419930E-05 -4.8321011418786571E-05 -4.8095847963106104E-05 -4.7871465309718114E-05 -4.7647861687218709E-05 -4.7425035329081160E-05 -4.7202984472160822E-05 -4.6981707354117794E-05 -4.6761202213944308E-05 -4.6541467291408781E-05 -4.6322500829623726E-05 -4.6104301072922965E-05 -4.5886866268004345E-05 -4.5670194663680772E-05 -4.5454284509753717E-05 -4.5239134058197857E-05 -4.5024741561690880E-05 -4.4811105275676165E-05 -4.4598223456891299E-05 -4.4386094364902494E-05 -4.4174716262534582E-05 -4.3964087413196718E-05 -4.3754206081570294E-05 -4.3545070532834690E-05 -4.3336679034593555E-05 -4.3129029855891976E-05 -4.2922121269209403E-05 -4.2715951552121040E-05 -4.2510518982022062E-05 -4.2305821833784141E-05 -4.2101858382208800E-05 -4.1898626910420451E-05 -4.1696125707659053E-05 -4.1494353061054797E-05 -4.1293307253368492E-05 -4.1092986568402661E-05 -4.0893389298707314E-05 -4.0694513739883622E-05 -4.0496358187039280E-05 -4.0298920934809789E-05 -4.0102200280045529E-05 -3.9906194525282804E-05 -3.9710901973743922E-05 -3.9516320927074140E-05 -3.9322449686371657E-05 -3.9129286559098808E-05 -3.8936829860535617E-05 -3.8745077905060938E-05 -3.8554029002390594E-05 -3.8363681461978594E-05 -3.8174033601044165E-05 -3.7985083741510094E-05 -3.7796830205106845E-05 -3.7609271313160169E-05 -3.7422405388083151E-05 -3.7236230757386758E-05 -3.7050745750086385E-05 -3.6865948696141373E-05 -3.6681837926260146E-05 -3.6498411772186114E-05 -3.6315668567762926E-05 -3.6133606648362242E-05 -3.5952224357067474E-05 -3.5771520039754966E-05 -3.5591492039620418E-05 -3.5412138697143017E-05 -3.5233458355231157E-05 -3.5055449363746729E-05 -3.4878110074000757E-05 -3.4701438839579799E-05 -3.4525434015216486E-05 -3.4350093956383284E-05 -3.4175417019507451E-05 -3.4001401562427795E-05 -3.3828045947882552E-05 -3.3655348539970996E-05 -3.3483307705691823E-05 -3.3311921813913606E-05 -3.3141189233403375E-05 -3.2971108332701737E-05 -3.2801677481697763E-05 -3.2632895056957487E-05 -3.2464759437102214E-05 -3.2297269001202565E-05 -3.2130422128712145E-05 -3.1964217200402128E-05 -3.1798652599932010E-05 -3.1633726712129357E-05 -3.1469437926943989E-05 -3.1305784636388271E-05 -3.1142765232367010E-05 -3.0980378106664622E-05 -3.0818621652543362E-05 -3.0657494267595346E-05 -3.0496994350575461E-05 -3.0337120303610408E-05 -3.0177870530636715E-05 -3.0019243436773230E-05 -2.9861237428758167E-05 -2.9703850914369493E-05 -2.9547082304971764E-05 -2.9390930012924271E-05 -2.9235392452127342E-05 -2.9080468037561083E-05 -2.8926155186325528E-05 -2.8772452319312524E-05 -2.8619357858281780E-05 -2.8466870227462741E-05 -2.8314987852047505E-05 -2.8163709160215317E-05 -2.8013032582799873E-05 -2.7862956550693833E-05 -2.7713479494714869E-05 -2.7564599846808227E-05 -2.7416316046991112E-05 -2.7268626538685009E-05 -2.7121529762916156E-05 -2.6975024157953621E-05 -2.6829108164739752E-05 -2.6683780233073894E-05 -2.6539038814305876E-05 -2.6394882358029457E-05 -2.6251309312933061E-05 -2.6108318132245544E-05 -2.5965907275938815E-05 -2.5824075203897826E-05 -2.5682820373355191E-05 -2.5542141241363230E-05 -2.5402036272140492E-05 -2.5262503935148601E-05 -2.5123542699045181E-05 -2.4985151030704980E-05 -2.4847327398221836E-05 -2.4710070277686576E-05 -2.4573378147862151E-05 -2.4437249484969820E-05 -2.4301682762831027E-05 -2.4166676458481781E-05 -2.4032229057335314E-05 -2.3898339046356966E-05 -2.3765004914399325E-05 -2.3632225151156433E-05 -2.3499998245302063E-05 -2.3368322684260508E-05 -2.3237196958451594E-05 -2.3106619568625745E-05 -2.2976589017396704E-05 -2.2847103804136727E-05 -2.2718162426330756E-05 -2.2589763385481456E-05 -2.2461905189475964E-05 -2.2334586347073200E-05 -2.2207805368416785E-05 -2.2081560764156024E-05 -2.1955851046686135E-05 -2.1830674729780680E-05 -2.1706030329521479E-05 -2.1581916366661106E-05 -2.1458331362833948E-05 -2.1335273841525236E-05 -2.1212742326988991E-05 -2.1090735345259893E-05 -2.0969251424163985E-05 -2.0848289092783950E-05 -2.0727846883392725E-05 -2.0607923329425088E-05 -2.0488516969498952E-05 -2.0369626344761488E-05 -2.0251249995472701E-05 -2.0133386460718331E-05 -2.0016034281240179E-05 -1.9899192004047285E-05 -1.9782858177824954E-05 -1.9667031354304600E-05 -1.9551710087157209E-05 -1.9436892928891724E-05 -1.9322578430009005E-05 -1.9208765143202665E-05 -1.9095451632701936E-05 -1.8982636465992633E-05 -1.8870318206749681E-05 -1.8758495415499720E-05 -1.8647166656045205E-05 -1.8536330499602881E-05 -1.8425985518467134E-05 -1.8316130285528004E-05 -1.8206763374041837E-05 -1.8097883360574582E-05 -1.7989488825236206E-05 -1.7881578348803511E-05 -1.7774150513483156E-05 -1.7667203902200854E-05 -1.7560737102007914E-05 -1.7454748702147577E-05 -1.7349237292852827E-05 -1.7244201465697901E-05 -1.7139639813413780E-05 -1.7035550932835711E-05 -1.6931933421999810E-05 -1.6828785881565887E-05 -1.6726106913996637E-05 -1.6623895122589264E-05 -1.6522149112077661E-05 -1.6420867488412903E-05 -1.6320048863093821E-05 -1.6219691849422429E-05 -1.6119795060804718E-05 -1.6020357110748591E-05 -1.5921376615172092E-05 -1.5822852195654185E-05 -1.5724782474630629E-05 -1.5627166074848184E-05 -1.5530001619298081E-05 -1.5433287734224660E-05 -1.5337023049579581E-05 -1.5241206196931930E-05 -1.5145835812255466E-05 -1.5050910532240360E-05 -1.4956428992222764E-05 -1.4862389826862626E-05 -1.4768791675192729E-05 -1.4675633182696231E-05 -1.4582912995668978E-05 -1.4490629761632613E-05 -1.4398782128582594E-05 -1.4307368746641591E-05 -1.4216388267496368E-05 -1.4125839344572155E-05 -1.4035720634555505E-05 -1.3946030795258669E-05 -1.3856768488730929E-05 -1.3767932378503516E-05 -1.3679521128357813E-05 -1.3591533402315565E-05 -1.3503967866877318E-05 -1.3416823194754939E-05 -1.3330098059759952E-05 -1.3243791136760043E-05 -1.3157901101129529E-05 -1.3072426629002303E-05 -1.2987366397432024E-05 -1.2902719086298069E-05 -1.2818483384733514E-05 -1.2734657983370363E-05 -1.2651241568299897E-05 -1.2568232822994544E-05 -1.2485630437116839E-05 -1.2403433110100218E-05 -1.2321639541384170E-05 -1.2240248426612540E-05 -1.2159258460738085E-05 -1.2078668344295626E-05 -1.1998476782159647E-05 -1.1918682480805136E-05 -1.1839284149747331E-05 -1.1760280499055472E-05 -1.1681670239898445E-05 -1.1603452083988023E-05 -1.1525624746124710E-05 -1.1448186944200701E-05 -1.1371137397266655E-05 -1.1294474827131306E-05 -1.1218197956346460E-05 -1.1142305509797754E-05 -1.1066796213599168E-05 -1.0991668797148788E-05 -1.0916921994075796E-05 -1.0842554538472627E-05 -1.0768565165087785E-05 -1.0694952609134591E-05 -1.0621715609459829E-05 -1.0548852907256507E-05 -1.0476363245686102E-05 -1.0404245371141361E-05 -1.0332498030796454E-05 -1.0261119974096854E-05 -1.0190109951278417E-05 -1.0119466714382576E-05 -1.0049189016955059E-05 -9.9792756150597011E-06 -9.9097252701636905E-06 -9.8405367445577411E-06 -9.7717088012415467E-06 -9.7032402035967999E-06 -9.6351297175913404E-06 -9.5673761119459430E-06 -9.4999781570993637E-06 -9.4329346280587694E-06 -9.3662443006866527E-06 -9.2999059511647240E-06 -9.2339183559190557E-06 -9.1682802948221436E-06 -9.1029905524818935E-06 -9.0380479143922860E-06 -8.9734511681364236E-06 -8.9091991019905053E-06 -8.8452905066210690E-06 -8.7817241743398363E-06 -8.7184988992657701E-06 -8.6556134786866563E-06 -8.5930667109083011E-06 -8.5308573978022176E-06 -8.4689843424700075E-06 -8.4074463495414367E-06 -8.3462422249956064E-06 -8.2853707765356367E-06 -8.2248308157843501E-06 -8.1646211553355025E-06 -8.1047406106578899E-06 -8.0451879985047575E-06 -7.9859621373688240E-06 -7.9270618477090073E-06 -7.8684859516268591E-06 -7.8102332759762994E-06 -7.7523026485519306E-06 -7.6946928973822636E-06 -7.6374028506990257E-06 -7.5804313405085231E-06 -7.5237772043411075E-06 -7.4674392802064398E-06 -7.4114164062814228E-06 -7.3557074211353045E-06 -7.3003111681196816E-06 -7.2452264940524723E-06 -7.1904522462493239E-06 -7.1359872728265969E-06 -7.0818304228597742E-06 -7.0279805502541661E-06 -6.9744365106367758E-06 -6.9211971607733544E-06 -6.8682613584996272E-06 -6.8156279639607839E-06 -6.7632958429720347E-06 -6.7112638621482104E-06 -6.6595308875656548E-06 -6.6080957851991592E-06 -6.5569574257526956E-06 -6.5061146856352833E-06 -6.4555664412799878E-06 -6.4053115680691619E-06 -6.3553489418036423E-06 -6.3056774449209124E-06 -6.2562959638005135E-06 -6.2072033843677953E-06 -6.1583985917575776E-06 -6.1098804724784390E-06 -6.0616479194437483E-06 -6.0136998274428864E-06 -5.9660350927473075E-06 -5.9186526127802158E-06 -5.8715512862981331E-06 -5.8247300147080214E-06 -5.7781877003848976E-06 -5.7319232495652040E-06 -5.6859355699996054E-06 -5.6402235714277701E-06 -5.5947861655679880E-06 -5.5496222654769261E-06 -5.5047307875647888E-06 -5.4601106491517261E-06 -5.4157607704475270E-06 -5.3716800731213237E-06 -5.3278674808312240E-06 -5.2843219197765462E-06 -5.2410423172430006E-06 -5.1980276037927266E-06 -5.1552767109715587E-06 -5.1127885732182528E-06 -5.0705621268289042E-06 -5.0285963097096752E-06 -4.9868900623950538E-06 -4.9454423263857783E-06 -4.9042520466070335E-06 -4.8633181691414052E-06 -4.8226396423414168E-06 -4.7822154164308269E-06 -4.7420444433156562E-06 -4.7021256784331629E-06 -4.6624580780812902E-06 -4.6230406011150760E-06 -4.5838722075044843E-06 -4.5449518598662696E-06 -4.5062785236172868E-06 -4.4678511652500304E-06 -4.4296687539550963E-06 -4.3917302597828918E-06 -4.3540346561278093E-06 -4.3165809181621932E-06 -4.2793680228150603E-06 -4.2423949493966829E-06 -4.2056606783082498E-06 -4.1691641934691689E-06 -4.1329044798430313E-06 -4.0968805249130064E-06 -4.0610913178864476E-06 -4.0255358498340866E-06 -3.9902131150744438E-06 -3.9551221087962057E-06 -3.9202618289406813E-06 -3.8856312744842244E-06 -3.8512294472257735E-06 -3.8170553514350308E-06 -3.7831079927073068E-06 -3.7493863795218073E-06 -3.7158895212129401E-06 -3.6826164302129396E-06 -3.6495661203445401E-06 -3.6167376076927376E-06 -3.5841299108861383E-06 -3.5517420497584157E-06 -3.5195730474284118E-06 -3.4876219279271516E-06 -3.4558877179903654E-06 -3.4243694458959866E-06 -3.3930661420789265E-06 -3.3619768400907003E-06 -3.3311005743984336E-06 -3.3004363822209814E-06 -3.2699833017109795E-06 -3.2397403741059285E-06 -3.2097066428770117E-06 -3.1798811529444592E-06 -3.1502629518778604E-06 -3.1208510882002869E-06 -3.0916446140659932E-06 -3.0626425829797903E-06 -3.0338440505889759E-06 -3.0052480745354237E-06 -2.9768537139086944E-06 -2.9486600312053566E-06 -2.9206660898490095E-06 -2.8928709563058712E-06 -2.8652736984842106E-06 -2.8378733863914340E-06 -2.8106690925434959E-06 -2.7836598905921071E-06 -2.7568448574441654E-06 -2.7302230709860156E-06 -2.7037936123141132E-06 -2.6775555644490886E-06 -2.6515080119639403E-06 -2.6256500417997715E-06 -2.5999807419612791E-06 -2.5744992042462983E-06 -2.5492045216556893E-06 -2.5240957895357369E-06 -2.4991721050425783E-06 -2.4744325670485173E-06 -2.4498762778000284E-06 -2.4255023404561060E-06 -2.4013098611787505E-06 -2.3772979473413851E-06 -2.3534657087678677E-06 -2.3298122577069528E-06 -2.3063367077209086E-06 -2.2830381755896583E-06 -2.2599157790052320E-06 -2.2369686387562140E-06 -2.2141958771854224E-06 -2.1915966187389025E-06 -2.1691699905344864E-06 -2.1469151207921456E-06 -2.1248311410163034E-06 -2.1029171836788804E-06 -2.0811723839700644E-06 -2.0595958788226895E-06 -2.0381868072205753E-06 -2.0169443114928703E-06 -1.9958675348665105E-06 -1.9749556233370300E-06 -1.9542077239024836E-06 -1.9336229865560561E-06 -1.9132005637418359E-06 -1.8929396092292028E-06 -1.8728392794927084E-06 -1.8528987319226495E-06 -1.8331171275089578E-06 -1.8134936287424723E-06 -1.7940274002732282E-06 -1.7747176090218727E-06 -1.7555634232571433E-06 -1.7365640147792247E-06 -1.7177185563348911E-06 -1.6990262234869676E-06 -1.6804861933018269E-06 -1.6620976449476900E-06 -1.6438597604323110E-06 -1.6257717228489145E-06 -1.6078327186439004E-06 -1.5900419352925592E-06 -1.5723985631298505E-06 -1.5549017944322238E-06 -1.5375508232487059E-06 -1.5203448466892258E-06 -1.5032830627970157E-06 -1.4863646727796240E-06 -1.4695888789957901E-06 -1.4529548864468153E-06 -1.4364619024341967E-06 -1.4201091356922016E-06 -1.4038957980833822E-06 -1.3878211024180649E-06 -1.3718842650031140E-06 -1.3560845036866452E-06 -1.3404210383139227E-06 -1.3248930909615549E-06 -1.3094998849946228E-06 -1.2942406473516087E-06 -1.2791146059778994E-06 -1.2641209919217818E-06 -1.2492590379788012E-06 -1.2345279788048518E-06 -1.2199270517216015E-06 -1.2054554951218118E-06 -1.1911125509182469E-06 -1.1768974621247436E-06 -1.1628094744901091E-06 -1.1488478357369063E-06 -1.1350117953488845E-06 -1.1213006060418905E-06 -1.1077135214377395E-06 -1.0942497981640648E-06 -1.0809086940164243E-06 -1.0676894696843575E-06 -1.0545913885346986E-06 -1.0416137151651130E-06 -1.0287557169621336E-06 -1.0160166622085969E-06 -1.0033958227042214E-06 -9.9089247189757711E-07 -9.7850588538889516E-07 -9.6623534133406952E-07 -9.5408011906427994E-07 -9.4203950126971009E-07 -9.3011277162870253E-07 -9.1829921692009290E-07 -9.0659812577715686E-07 -8.9500878870503011E-07 -8.8353049905822365E-07 -8.7216255122086107E-07 -8.6090424302326463E-07 -8.4975487342286912E-07 -8.3871374408033250E-07 -8.2778015872880997E-07 -8.1695342281688979E-07 -8.0623284513274228E-07 -7.9561773538344580E-07 -7.8510740633698749E-07 -7.7470117199871451E-07 -7.6439834906116053E-07 -7.5419825686038011E-07 -7.4410021602961348E-07 -7.3410355033378906E-07 -7.2420758445948930E-07 -7.1441164638553297E-07 -7.0471506573163680E-07 -6.9511717426006036E-07 -6.8561730643841403E-07 -6.7621479787357438E-07 -6.6690898756300989E-07 -6.5769921552550727E-07 -6.4858482487543706E-07 -6.3956516069223876E-07 -6.3063956982384014E-07 -6.2180740197434663E-07 -6.1306800789221696E-07 -6.0442074199167308E-07 -5.9586495991737938E-07 -5.8740001979202233E-07 -5.7902528175761432E-07 -5.7074010764497430E-07 -5.6254386278187207E-07 -5.5443591345035755E-07 -5.4641562911867357E-07 -5.3848238059842046E-07 -5.3063554116304666E-07 -5.2287448666046123E-07 -5.1519859425831227E-07 -5.0760724451523747E-07 -5.0009981894772744E-07 -4.9267570221551304E-07 -4.8533428064259740E-07 -4.7807494270228695E-07 -4.7089707975298757E-07 -4.6380008426150834E-07 -4.5678335210633829E-07 -4.4984628021431567E-07 -4.4298826848349211E-07 -4.3620871881745664E-07 -4.2950703492488721E-07 -4.2288262361312964E-07 -4.1633489267922734E-07 -4.0986325334240247E-07 -4.0346711805224142E-07 -3.9714590195894780E-07 -3.9089902255025133E-07 -3.8472589882463144E-07 -3.7862595306776293E-07 -3.7259860851151395E-07 -3.6664329171983775E-07 -3.6075943073452432E-07 -3.5494645598246297E-07 -3.4920380054172802E-07 -3.4353089876073769E-07 -3.3792718841977060E-07 -3.3239210828105913E-07 -3.2692510024404008E-07 -3.2152560796916980E-07 -3.1619307720144139E-07 -3.1092695665899075E-07 -3.0572669614098446E-07 -3.0059174889368896E-07 -2.9552156925602801E-07 -2.9051561449160364E-07 -2.8557334396137995E-07 -2.8069421878576696E-07 -2.7587770329024159E-07 -2.7112326278065837E-07 -2.6643036598363881E-07 -2.6179848291596118E-07 -2.5722708623191497E-07 -2.5271565101254043E-07 -2.4826365381284060E-07 -2.4387057458061709E-07 -2.3953589422146589E-07 -2.3525909693853996E-07 -2.3103966848220164E-07 -2.2687709692715629E-07 -2.2277087309446836E-07 -2.1872048904524169E-07 -2.1472544035674023E-07 -2.1078522362304459E-07 -2.0689933852965954E-07 -2.0306728660325195E-07 -1.9928857138248745E-07 -1.9556269945433998E-07 -1.9188917847631552E-07 -1.8826751964218515E-07 -1.8469723530193395E-07 -1.8117784064421338E-07 -1.7770885302085733E-07 -1.7428979149453142E-07 -1.7092017843470941E-07 -1.6759953719138641E-07 -1.6432739455462337E-07 -1.6110327867765414E-07 -1.5792672027692554E-07 -1.5479725257593036E-07 -1.5171441023231290E-07 -1.4867773139288369E-07 -1.4568675518020145E-07 -1.4274102398331292E-07 -1.3984008181463729E-07 -1.3698347497019109E-07 -1.3417075261393355E-07 -1.3140146509900367E-07 -1.2867516629052576E-07 -1.2599141110091216E-07 -1.2334975756351389E-07 -1.2074976568377207E-07 -1.1819099738754025E-07 -1.1567301768882173E-07 -1.1319539265387757E-07 -1.1075769193722002E-07 -1.0835948641598438E-07 -1.0600034977500811E-07 -1.0367985797275288E-07 -1.0139758860378547E-07 -9.9153122611751501E-08 -9.6946041922598454E-08 -9.4775931942105357E-08 -9.2642379528014414E-08 -9.0544974033340335E-08 -8.8483307405510301E-08 -8.6456972978318020E-08 -8.4465567642688606E-08 -8.2508689288109891E-08 -8.0585939059857060E-08 -7.8696919817248824E-08 -7.6841236633443348E-08 -7.5018497536375005E-08 -7.3228311716505649E-08 -7.1470291944577024E-08 -6.9744052083400514E-08 -6.8049209058768608E-08 -6.6385381852382120E-08 -6.4752191323758533E-08 -6.3149261538474673E-08 -6.1576217594041876E-08 -6.0032688157468506E-08 -5.8518303171491160E-08 -5.7032695364927129E-08 -5.5575499864421187E-08 -5.4146353374627317E-08 -5.2744896017523444E-08 -5.1370768898627600E-08 -5.0023616584907976E-08 -4.8703085170182478E-08 -4.7408823215993472E-08 -4.6140482011285367E-08 -4.4897714169819019E-08 -4.3680175870988625E-08 -4.2487524314376957E-08 -4.1319419976464438E-08 -4.0175525162077451E-08 -3.9055504313917110E-08 -3.7959024906009665E-08 -3.6885755546601572E-08 -3.5835368471682633E-08 -3.4807537058771332E-08 -3.3801937708221364E-08 -3.2818248975779787E-08 -3.1856151238818242E-08 -3.0915328174770870E-08 -2.9995464482902133E-08 -2.9096248442583249E-08 -2.8217369675561873E-08 -2.7358520537668847E-08 -2.6519395885967688E-08 -2.5699692104064112E-08 -2.4899109070983037E-08 -2.4117347659916912E-08 -2.3354112198376755E-08 -2.2609108625133710E-08 -2.1882045288510795E-08 -2.1172633367554306E-08 -2.0480585324630079E-08 -1.9805617244235977E-08 -1.9147446262456073E-08 -1.8505792766993109E-08 -1.7880379070622431E-08 -1.7270929563521603E-08 -1.6677171764773835E-08 -1.6098834302492423E-08 -1.5535649463666866E-08 -1.4987350730056162E-08 -1.4453674568325066E-08 -1.3934359706561301E-08 -1.3429146634614714E-08 -1.2937779226486110E-08 -1.2460002373056446E-08 -1.1995564556761548E-08 -1.1544215676214430E-08 -1.1105708308847815E-08 -1.0679797637220186E-08 -1.0266240321664285E-08 -9.8647965955417552E-09 -9.4752277021165834E-09 -9.0972983216374280E-09 -8.7307748317899885E-09 -8.3754259635767138E-09 -8.0310233864621537E-09 -7.6973400146873315E-09 -7.3741524343282016E-09 -7.0612383196436033E-09 -6.7583785662903493E-09 -6.4653560945417070E-09 -6.1819558421144049E-09 -5.9079659734818731E-09 -5.6431757420881947E-09 -5.3873780875038043E-09 -5.1403672033293462E-09 -4.9019402233904631E-09 -4.6718966488059959E-09 -4.4500376850971491E-09 -4.2361680068748094E-09 -4.0300933055269846E-09 -3.8316228675867074E-09 -3.6405674738335173E-09 -3.4567405308062599E-09 -3.2799581594975672E-09 -3.1100379084695907E-09 -2.9468009634269509E-09 -2.7900695409134002E-09 -2.6396692830401005E-09 -2.4954276244364112E-09 -2.3571742898322502E-09 -2.2247420427823886E-09 -2.0979648578936294E-09 -1.9766804318094848E-09 -1.8607275929541803E-09 -1.7499483556785178E-09 -1.6441868607328526E-09 -1.5432892064474067E-09 -1.4471048148864479E-09 -1.3554841814370679E-09 -1.2682815074443349E-09 -1.1853523127741092E-09 -1.1065550116955543E-09 -1.0317504953567838E-09 -9.6080130240527892E-10 -8.9357352113818461E-10 -8.2993426174423119E-10 -7.6975422997690995E-10 -7.1290570941731815E-10 -6.5926355213010325E-10 -6.0870543272240160E-10 -5.6111040728941775E-10 -5.1636123347238485E-10 -4.7434172637979906E-10 -4.3493910600519401E-10 -3.9804248168282196E-10 -3.6354319171961963E-10 -3.3133571705868044E-10 -3.0131571927621377E-10 -2.7338262297431223E-10 -2.4743703356504616E-10 -2.2338270543977930E-10 -2.0112562558507132E-10 -1.8057367776073524E-10 -1.6163816280207742E-10 -1.4423144437514660E-10 -1.2826960866823061E-10 -1.1367013099245353E-10 -1.0035333076435870E-10 -8.8242114453893185E-11 -7.7260981333563132E-11 -6.7338059414798230E-11 -5.8402509029938659E-11 -5.0387080318949032E-11 -4.3226189075409649E-11 -3.6856760935599544E-11 -3.1218653270911080E-11 -2.6253061802947050E-11 -2.1904943657724451E-11 -1.8120345795644439E-11 -1.4848694978908011E-11 -1.2041407856701085E-11 -9.6520682967366322E-12 -7.6375060085854840E-12 -5.9557052272264676E-12 -4.5684473540379521E-12 -3.4387497760183598E-12 -2.5327421664576602E-12 -1.8188986331067647E-12 -1.2675207651160692E-12 -8.5240064359752175E-13 -5.4839808310236725E-13 -3.3417856365135441E-13 -1.8988920008789678E-13 -9.8267529741170064E-14 -4.4556738485030801E-14 -1.5915537527962123E-14 -4.2006131159619414E-15 -2.0194880235886256E-15 -1.9796850254619370E-15 -0.0000000000000000E+00 -1.5153406509907930E-03 -3.0369579249289419E-03 -4.5648417413541370E-03 -6.0989820247555025E-03 -7.6393687045716177E-03 -9.1859917151904825E-03 -1.0738840995949560E-02 -1.2297906491135756E-02 -1.3863178149985384E-02 -1.5434645926684242E-02 -1.7012299780367571E-02 -1.8596129675119998E-02 -2.0186125579975660E-02 -2.1782277468918070E-02 -2.3384575320880271E-02 -2.4993009119744680E-02 -2.6607568854343146E-02 -2.8228244518456971E-02 -2.9855026110816970E-02 -3.1487903635103343E-02 -3.3126867099945681E-02 -3.4771906518923076E-02 -3.6423011910564122E-02 -3.8080173298346738E-02 -3.9743380710698342E-02 -4.1412624180995741E-02 -4.3087893747565303E-02 -4.4769179453682757E-02 -4.6456471347573233E-02 -4.8149759482411382E-02 -4.9849033916321298E-02 -5.1554284712376421E-02 -5.3265501938599774E-02 -5.4982675667963637E-02 -5.6705795978389956E-02 -5.8434852952749972E-02 -6.0169836678864372E-02 -6.1910737249503300E-02 -6.3657544762386400E-02 -6.5410249320182717E-02 -6.7168841030510712E-02 -6.8933310005938289E-02 -7.0703646363982894E-02 -7.2479840227111209E-02 -7.4261881722739634E-02 -7.6049760983233752E-02 -7.7843468145908715E-02 -7.9642993353029184E-02 -8.1448326751809047E-02 -8.3259458494411839E-02 -8.5076378737950487E-02 -8.6899077644487302E-02 -8.8727545381034126E-02 -9.0561772119552048E-02 -9.2401748036951878E-02 -9.4247463315093705E-02 -9.6098908140786962E-02 -9.7956072705790889E-02 -9.9818947206813710E-02 -1.0168752184551345E-01 -1.0356178682849726E-01 -1.0544173236732207E-01 -1.0732734867849407E-01 -1.0921862598346886E-01 -1.1111555450865147E-01 -1.1301812448539660E-01 -1.1492632615000807E-01 -1.1684014974373942E-01 -1.1875958551279336E-01 -1.2068462370832232E-01 -1.2261525458642808E-01 -1.2455146840816163E-01 -1.2649325543952372E-01 -1.2844060595146456E-01 -1.3039351021988344E-01 -1.3235195852562948E-01 -1.3431594115450080E-01 -1.3628544839724557E-01 -1.3826047054956089E-01 -1.4024099791209366E-01 -1.4222702079043972E-01 -1.4421852949514496E-01 -1.4621551434170435E-01 -1.4821796565056236E-01 -1.5022587374711285E-01 -1.5223922896169936E-01 -1.5425802162961455E-01 -1.5628224209110089E-01 -1.5831188069134974E-01 -1.6034692778050247E-01 -1.6238737371364978E-01 -1.6443320885083146E-01 -1.6648442355703696E-01 -1.6854100820220552E-01 -1.7060295316122515E-01 -1.7267024881393381E-01 -1.7474288554511849E-01 -1.7682085374451631E-01 -1.7890414380681305E-01 -1.8099274613164446E-01 -1.8308665112359535E-01 -1.8518584919220030E-01 -1.8729033075194326E-01 -1.8940008622225743E-01 -1.9151510602752556E-01 -1.9363538059708008E-01 -1.9576090036520238E-01 -1.9789165577112364E-01 -2.0002763725902462E-01 -2.0216883527803498E-01 -2.0431524028223438E-01 -2.0646684273065158E-01 -2.0862363308726478E-01 -2.1078560182100203E-01 -2.1295273940574022E-01 -2.1512503632030605E-01 -2.1730248304847569E-01 -2.1948507007897480E-01 -2.2167278790547809E-01 -2.2386562702660984E-01 -2.2606357794594439E-01 -2.2826663117200455E-01 -2.3047477721826345E-01 -2.3268800660314279E-01 -2.3490630985001448E-01 -2.3712967748719971E-01 -2.3935810004796870E-01 -2.4159156807054133E-01 -2.4383007209808744E-01 -2.4607360267872533E-01 -2.4832215036552366E-01 -2.5057570571649979E-01 -2.5283425929462106E-01 -2.5509780166780421E-01 -2.5736632340891502E-01 -2.5963981509576889E-01 -2.6191826731113099E-01 -2.6420167064271571E-01 -2.6649001568318686E-01 -2.6878329303015708E-01 -2.7108149328618991E-01 -2.7338460705879702E-01 -2.7569262496044017E-01 -2.7800553760852997E-01 -2.8032333562542733E-01 -2.8264600963844205E-01 -2.8497355027983334E-01 -2.8730594818680988E-01 -2.8964319400153032E-01 -2.9198527837110200E-01 -2.9433219194758209E-01 -2.9668392538797689E-01 -2.9904046935424278E-01 -3.0140181451328513E-01 -3.0376795153695862E-01 -3.0613887110206756E-01 -3.0851456389036602E-01 -3.1089502058855689E-01 -3.1328023188829279E-01 -3.1567018848617601E-01 -3.1806488108375813E-01 -3.2046430038753987E-01 -3.2286843710897195E-01 -3.2527728196445377E-01 -3.2769082567533486E-01 -3.3010905896791420E-01 -3.3253197257343953E-01 -3.3495955722810866E-01 -3.3739180367306898E-01 -3.3982870265441639E-01 -3.4227024492319741E-01 -3.4471642123540680E-01 -3.4716722235198982E-01 -3.4962263903884094E-01 -3.5208266206680316E-01 -3.5454728221167037E-01 -3.5701649025418503E-01 -3.5949027698003871E-01 -3.6196863317987321E-01 -3.6445154964927956E-01 -3.6693901718879812E-01 -3.6943102660391841E-01 -3.7192756870507981E-01 -3.7442863430767137E-01 -3.7693421423203066E-01 -3.7944429930344575E-01 -3.8195888035215309E-01 -3.8447794821333958E-01 -3.8700149372714127E-01 -3.8952950773864298E-01 -3.9206198109787971E-01 -3.9459890465983599E-01 -3.9714026928444507E-01 -3.9968606583659044E-01 -4.0223628518610427E-01 -4.0479091820776864E-01 -4.0734995578131539E-01 -4.0991338879142503E-01 -4.1248120812772748E-01 -4.1505340468480351E-01 -4.1762996936218166E-01 -4.2021089306434078E-01 -4.2279616670070841E-01 -4.2538578118566328E-01 -4.2797972743853119E-01 -4.3057799638358918E-01 -4.3318057895006296E-01 -4.3578746607212748E-01 -4.3839864868890838E-01 -4.4101411774447885E-01 -4.4363386418786305E-01 -4.4625787897303398E-01 -4.4888615305891427E-01 -4.5151867740937551E-01 -4.5415544299323940E-01 -4.5679644078427656E-01 -4.5944166176120760E-01 -4.6209109690770162E-01 -4.6474473721237852E-01 -4.6740257366880650E-01 -4.7006459727550381E-01 -4.7273079903593801E-01 -4.7540116995852510E-01 -4.7807570105663277E-01 -4.8075438334857606E-01 -4.8343720785762045E-01 -4.8612416561198063E-01 -4.8881524764482087E-01 -4.9151044499425461E-01 -4.9420974870334466E-01 -4.9691314982010354E-01 -4.9962063939749346E-01 -5.0233220849342586E-01 -5.0504784817076109E-01 -5.0776754949730940E-01 -5.1049130354583117E-01 -5.1321910139403470E-01 -5.1595093412457860E-01 -5.1868679282507180E-01 -5.2142666858807052E-01 -5.2417055251108269E-01 -5.2691843569656349E-01 -5.2967030925191982E-01 -5.3242616428950651E-01 -5.3518599192662786E-01 -5.3794978328553822E-01 -5.4071752949344143E-01 -5.4348922168249003E-01 -5.4626485098978683E-01 -5.4904440855738290E-01 -5.5182788553228057E-01 -5.5461527306643010E-01 -5.5740656231673180E-01 -5.6020174444503501E-01 -5.6300081061813900E-01 -5.6580375200779254E-01 -5.6861055979069308E-01 -5.7142122514848837E-01 -5.7423573926777538E-01 -5.7705409334010016E-01 -5.7987627856195822E-01 -5.8270228613479536E-01 -5.8553210726500549E-01 -5.8836573316393348E-01 -5.9120315504787180E-01 -5.9404436413806405E-01 -5.9688935166070267E-01 -5.9973810884692924E-01 -6.0259062693283472E-01 -6.0544689715946054E-01 -6.0830691077279642E-01 -6.1117065902378220E-01 -6.1403813316830647E-01 -6.1690932446720781E-01 -6.1978422418627432E-01 -6.2266282359624392E-01 -6.2554511397280199E-01 -6.2843108659658609E-01 -6.3132073275318146E-01 -6.3421404373312296E-01 -6.3711101083189559E-01 -6.4001162534993294E-01 -6.4291587859261856E-01 -6.4582376187028590E-01 -6.4873526649821622E-01 -6.5165038379664220E-01 -6.5456910509074517E-01 -6.5749142171065467E-01 -6.6041732499145245E-01 -6.6334680627316589E-01 -6.6627985690077629E-01 -6.6921646822421088E-01 -6.7215663159834704E-01 -6.7510033838301331E-01 -6.7804757994298559E-01 -6.8099834764799072E-01 -6.8395263287270358E-01 -6.8691042699674976E-01 -6.8987172140470399E-01 -6.9283650748608938E-01 -6.9580477663537987E-01 -6.9877652025199866E-01 -7.0175172974031752E-01 -7.0473039650965863E-01 -7.0771251197429264E-01 -7.1069806755344023E-01 -7.1368705467127203E-01 -7.1667946475690691E-01 -7.1967528924441393E-01 -7.2267451957281181E-01 -7.2567714718606835E-01 -7.2868316353310014E-01 -7.3169256006777483E-01 -7.3470532824890811E-01 -7.3772145954026580E-01 -7.4074094541056235E-01 -7.4376377733346288E-01 -7.4678994678758071E-01 -7.4981944525648025E-01 -7.5285226422867302E-01 -7.5588839519762219E-01 -7.5892782966173911E-01 -7.6197055912438494E-01 -7.6501657509387022E-01 -7.6806586908345498E-01 -7.7111843261134849E-01 -7.7417425720071054E-01 -7.7723333437964759E-01 -7.8029565568121950E-01 -7.8336121264343295E-01 -7.8642999680924375E-01 -7.8950199972655866E-01 -7.9257721294823280E-01 -7.9565562803207179E-01 -7.9873723654082973E-01 -8.0182203004221042E-01 -8.0491000010886760E-01 -8.0800113831840359E-01 -8.1109543625337077E-01 -8.1419288550127045E-01 -8.1729347765455407E-01 -8.2039720431062257E-01 -8.2350405707182495E-01 -8.2661402754546143E-01 -8.2972710734378041E-01 -8.3284328808398045E-01 -8.3596256138820924E-01 -8.3908491888356340E-01 -8.4221035220209073E-01 -8.4533885298078659E-01 -8.4847041286159630E-01 -8.5160502349141498E-01 -8.5474267652208702E-01 -8.5788336361040685E-01 -8.6102707641811671E-01 -8.6417380661190979E-01 -8.6732354586342875E-01 -8.7047628584926451E-01 -8.7363201825095860E-01 -8.7679073475500080E-01 -8.7995242705283161E-01 -8.8311708684084045E-01 -8.8628470582036589E-01 -8.8945527569769611E-01 -8.9262878818406943E-01 -8.9580523499567200E-01 -8.9898460785364132E-01 -9.0216689848406229E-01 -9.0535209861797183E-01 -9.0854019999135416E-01 -9.1173119434514271E-01 -9.1492507342522322E-01 -9.1812182898242711E-01 -9.2132145277253852E-01 -9.2452393655628828E-01 -9.2772927209935852E-01 -9.3093745117238047E-01 -9.3414846555093423E-01 -9.3736230701554968E-01 -9.4057896735170654E-01 -9.4379843834983301E-01 -9.4702071180530811E-01 -9.5024577951845834E-01 -9.5347363329456158E-01 -9.5670426494384453E-01 -9.5993766628148258E-01 -9.6317382912760152E-01 -9.6641274530727617E-01 -9.6965440665053082E-01 -9.7289880499233927E-01 -9.7614593217262446E-01 -9.7939578003625904E-01 -9.8264834043306537E-01 -9.8590360521781506E-01 -9.8916156625022866E-01 -9.9242221539497666E-01 -9.9568554452167923E-01 -9.9895154550490517E-01 -1.0022202102241742E+00 -1.0054915305639529E+00 -1.0087654984136598E+00 -1.0120421056676621E+00 -1.0153213442252760E+00 -1.0186032059907673E+00 -1.0218876828733521E+00 -1.0251747667871942E+00 -1.0284644496514090E+00 -1.0317567233900589E+00 -1.0350515799321580E+00 -1.0383490112116684E+00 -1.0416490091675026E+00 -1.0449515657435215E+00 -1.0482566728885367E+00 -1.0515643225563083E+00 -1.0548745067055461E+00 -1.0581872172999078E+00 -1.0615024463080052E+00 -1.0648201857033939E+00 -1.0681404274645823E+00 -1.0714631635750276E+00 -1.0747883860231362E+00 -1.0781160868022637E+00 -1.0814462579107154E+00 -1.0847788913517462E+00 -1.0881139791335610E+00 -1.0914515132693121E+00 -1.0947914857771035E+00 -1.0981338886799881E+00 -1.1014787140059670E+00 -1.1048259537879921E+00 -1.1081756000639633E+00 -1.1115276448767331E+00 -1.1148820802740995E+00 -1.1182388983088118E+00 -1.1215980910385692E+00 -1.1249596505260195E+00 -1.1283235688387607E+00 -1.1316898380493388E+00 -1.1350584502352505E+00 -1.1384293974789428E+00 -1.1418026718678091E+00 -1.1451782654941955E+00 -1.1485561704553964E+00 -1.1519363788536543E+00 -1.1553188827961629E+00 -1.1587036743950643E+00 -1.1620907457674508E+00 -1.1654800890353638E+00 -1.1688716963257944E+00 -1.1722655597706815E+00 -1.1756616715069164E+00 -1.1790600236763380E+00 -1.1824606084257343E+00 -1.1858634179068430E+00 -1.1892684442763530E+00 -1.1926756796959002E+00 -1.1960851163320714E+00 -1.1994967463564015E+00 -1.2029105619453764E+00 -1.2063265552804316E+00 -1.2097447185479497E+00 -1.2131650439392649E+00 -1.2165875236506611E+00 -1.2200121498833696E+00 -1.2234389148435727E+00 -1.2268678107424016E+00 -1.2302988297959372E+00 -1.2337319642252103E+00 -1.2371672062561989E+00 -1.2406045481198336E+00 -1.2440439820519931E+00 -1.2474855002935046E+00 -1.2509290950901450E+00 -1.2543747586926428E+00 -1.2578224833566733E+00 -1.2612722613428624E+00 -1.2647240849167856E+00 -1.2681779463489671E+00 -1.2716338379148810E+00 -1.2750917518949514E+00 -1.2785516805745500E+00 -1.2820136162440010E+00 -1.2854775511985754E+00 -1.2889434777384938E+00 -1.2924113881689283E+00 -1.2958812747999979E+00 -1.2993531299467729E+00 -1.3028269459292718E+00 -1.3063027150724635E+00 -1.3097804297062663E+00 -1.3132600821655471E+00 -1.3167416647901227E+00 -1.3202251699247600E+00 -1.3237105899191730E+00 -1.3271979171280295E+00 -1.3306871439109422E+00 -1.3341782626324752E+00 -1.3376712656621428E+00 -1.3411661453744077E+00 -1.3446628941486822E+00 -1.3481615043693278E+00 -1.3516619684256557E+00 -1.3551642787119274E+00 -1.3586684276273522E+00 -1.3621744075760898E+00 -1.3656822109672504E+00 -1.3691918302148904E+00 -1.3727032577380196E+00 -1.3762164859605941E+00 -1.3797315073115211E+00 -1.3832483142246572E+00 -1.3867668991388076E+00 -1.3902872544977274E+00 -1.3938093727501206E+00 -1.3973332463496435E+00 -1.4008588677548970E+00 -1.4043862294294356E+00 -1.4079153238417597E+00 -1.4114461434653232E+00 -1.4149786807785270E+00 -1.4185129282647202E+00 -1.4220488784122038E+00 -1.4255865237142284E+00 -1.4291258566689915E+00 -1.4326668697796423E+00 -1.4362095555542780E+00 -1.4397539065059464E+00 -1.4432999151526447E+00 -1.4468475740173179E+00 -1.4503968756278618E+00 -1.4539478125171226E+00 -1.4575003772228947E+00 -1.4610545622879205E+00 -1.4646103602598943E+00 -1.4681677636914601E+00 -1.4717267651402091E+00 -1.4752873571686818E+00 -1.4788495323443716E+00 -1.4824132832397177E+00 -1.4859786024321111E+00 -1.4895454825038901E+00 -1.4931139160423448E+00 -1.4966838956397128E+00 -1.5002554138931827E+00 -1.5038284634048904E+00 -1.5074030367819242E+00 -1.5109791266363193E+00 -1.5145567255850614E+00 -1.5181358262500861E+00 -1.5217164212582768E+00 -1.5252985032414685E+00 -1.5288820648364436E+00 -1.5324670986849356E+00 -1.5360535974336262E+00 -1.5396415537341479E+00 -1.5432309602430807E+00 -1.5468218096219561E+00 -1.5504140945372542E+00 -1.5540078076604036E+00 -1.5576029416677837E+00 -1.5611994892407228E+00 -1.5647974430654983E+00 -1.5683967958333385E+00 -1.5719975402404185E+00 -1.5755996689878653E+00 -1.5792031747817548E+00 -1.5828080503331106E+00 -1.5864142883579098E+00 -1.5900218815770732E+00 -1.5936308227164755E+00 -1.5972411045069397E+00 -1.6008527196842368E+00 -1.6044656609890908E+00 -1.6080799211671710E+00 -1.6116954929690970E+00 -1.6153123691504412E+00 -1.6189305424717215E+00 -1.6225500056984077E+00 -1.6261707516009158E+00 -1.6297927729546162E+00 -1.6334160625398253E+00 -1.6370406131418089E+00 -1.6406664175507837E+00 -1.6442934685619153E+00 -1.6479217589753188E+00 -1.6515512815960578E+00 -1.6551820292341461E+00 -1.6588139947045477E+00 -1.6624471708271762E+00 -1.6660815504268911E+00 -1.6697171263335058E+00 -1.6733538913817811E+00 -1.6769918384114284E+00 -1.6806309602671057E+00 -1.6842712497984234E+00 -1.6879126998599401E+00 -1.6915553033111639E+00 -1.6951990530165530E+00 -1.6988439418455141E+00 -1.7024899626724039E+00 -1.7061371083765293E+00 -1.7097853718421436E+00 -1.7134347459584542E+00 -1.7170852236196130E+00 -1.7207367977247257E+00 -1.7243894611778450E+00 -1.7280432068879730E+00 -1.7316980277690621E+00 -1.7353539167400147E+00 -1.7390108667246806E+00 -1.7426688706518609E+00 -1.7463279214553047E+00 -1.7499880120737121E+00 -1.7536491354507320E+00 -1.7573112845349612E+00 -1.7609744522799493E+00 -1.7646386316441924E+00 -1.7683038155911375E+00 -1.7719699970891798E+00 -1.7756371691116644E+00 -1.7793053246368875E+00 -1.7829744566480925E+00 -1.7866445581334736E+00 -1.7903156220861733E+00 -1.7939876415042855E+00 -1.7976606093908511E+00 -1.8013345187538619E+00 -1.8050093626062580E+00 -1.8086851339659318E+00 -1.8123618258557221E+00 -1.8160394313034174E+00 -1.8197179433417574E+00 -1.8233973550084297E+00 -1.8270776593460731E+00 -1.8307588494022728E+00 -1.8344409182295660E+00 -1.8381238588854392E+00 -1.8418076644323278E+00 -1.8454923279376159E+00 -1.8491778424736374E+00 -1.8528642011176775E+00 -1.8565513969519685E+00 -1.8602394230636921E+00 -1.8639282725449815E+00 -1.8676179384929184E+00 -1.8713084140095333E+00 -1.8749996922018055E+00 -1.8786917661816660E+00 -1.8823846290659940E+00 -1.8860782739766180E+00 -1.8897726940403152E+00 -1.8934678823888145E+00 -1.8971638321587925E+00 -1.9008605364918756E+00 -1.9045579885346382E+00 -1.9082561814386088E+00 -1.9119551083602595E+00 -1.9156547624610154E+00 -1.9193551369072508E+00 -1.9230562248702872E+00 -1.9267580195263985E+00 -1.9304605140568063E+00 -1.9341637016476818E+00 -1.9378675754901462E+00 -1.9415721287802694E+00 -1.9452773547190712E+00 -1.9489832465125214E+00 -1.9526897973715378E+00 -1.9563970005119897E+00 -1.9601048491546926E+00 -1.9638133365254151E+00 -1.9675224558548736E+00 -1.9712322003787328E+00 -1.9749425633376085E+00 -1.9786535379770660E+00 -1.9823651175476191E+00 -1.9860772953047308E+00 -1.9897900645088158E+00 -1.9935034184252343E+00 -1.9972173503242998E+00 -2.0009318534812732E+00 -2.0046469211763660E+00 -2.0083625466947370E+00 -2.0120787233264976E+00 -2.0157954443667054E+00 -2.0195127031153692E+00 -2.0232304928774489E+00 -2.0269488069628498E+00 -2.0306676386864297E+00 -2.0343869813679953E+00 -2.0381068283323018E+00 -2.0418271729090542E+00 -2.0455480084329070E+00 -2.0492693282434655E+00 -2.0529911256852831E+00 -2.0567133941078621E+00 -2.0604361268656550E+00 -2.0641593173180639E+00 -2.0678829588294407E+00 -2.0716070447690846E+00 -2.0753315685112472E+00 -2.0790565234351281E+00 -2.0827819029248755E+00 -2.0865077003695891E+00 -2.0902339091633162E+00 -2.0939605227050540E+00 -2.0976875343987507E+00 -2.1014149376533005E+00 -2.1051427258825499E+00 -2.1088708925052955E+00 -2.1125994309452807E+00 -2.1163283346311994E+00 -2.1200575969966957E+00 -2.1237872114803622E+00 -2.1275171715257417E+00 -2.1312474705813256E+00 -2.1349781021005554E+00 -2.1387090595418212E+00 -2.1424403363684648E+00 -2.1461719260487739E+00 -2.1499038220559896E+00 -2.1536360178682985E+00 -2.1573685069688389E+00 -2.1611012828456992E+00 -2.1648343389919154E+00 -2.1685676689054740E+00 -2.1723012660893111E+00 -2.1760351240513107E+00 -2.1797692363043084E+00 -2.1835035963660880E+00 -2.1872381977593824E+00 -2.1909730340118760E+00 -2.1947080986561995E+00 -2.1984433852299357E+00 -2.2021788872756156E+00 -2.2059145983407196E+00 -2.2096505119776784E+00 -2.2133866217438700E+00 -2.2171229212016264E+00 -2.2208594039182232E+00 -2.2245960634658899E+00 -2.2283328934218032E+00 -2.2320698873680898E+00 -2.2358070388918265E+00 -2.2395443415850389E+00 -2.2432817890447003E+00 -2.2470193748727385E+00 -2.2507570926760256E+00 -2.2544949360663842E+00 -2.2582328986605886E+00 -2.2619709740803606E+00 -2.2657091559523725E+00 -2.2694474379082443E+00 -2.2731858135845475E+00 -2.2769242766228026E+00 -2.2806628206694786E+00 -2.2844014393759937E+00 -2.2881401263987171E+00 -2.2918788753989672E+00 -2.2956176800430117E+00 -2.2993565340020639E+00 -2.3030954309522937E+00 -2.3068343645748155E+00 -2.3105733285556949E+00 -2.3143123165859452E+00 -2.3180513223615304E+00 -2.3217903395833654E+00 -2.3255293619573116E+00 -2.3292683831941816E+00 -2.3330073970097378E+00 -2.3367463971246902E+00 -2.3404853772647010E+00 -2.3442243311603783E+00 -2.3479632525472831E+00 -2.3517021351659237E+00 -2.3554409727617576E+00 -2.3591797590851948E+00 -2.3629184878915908E+00 -2.3666571529412530E+00 -2.3703957479994373E+00 -2.3741342668363488E+00 -2.3778727032271436E+00 -2.3816110509519257E+00 -2.3853493037957483E+00 -2.3890874555486157E+00 -2.3928255000054808E+00 -2.3965634309662445E+00 -2.4003012422357601E+00 -2.4040389276238274E+00 -2.4077764809451976E+00 -2.4115138960195703E+00 -2.4152511666715957E+00 -2.4189882867308721E+00 -2.4227252500319474E+00 -2.4264620504143215E+00 -2.4301986817224379E+00 -2.4339351378056966E+00 -2.4376714125184424E+00 -2.4414074997199706E+00 -2.4451433932745270E+00 -2.4488790870513051E+00 -2.4526145749244490E+00 -2.4563498507730523E+00 -2.4600849084811571E+00 -2.4638197419377570E+00 -2.4675543450367923E+00 -2.4712887116771540E+00 -2.4750228357626836E+00 -2.4787567112021702E+00 -2.4824903319093536E+00 -2.4862236918029228E+00 -2.4899567848065156E+00 -2.4936896048487203E+00 -2.4974221458630734E+00 -2.5011544017880620E+00 -2.5048863665671215E+00 -2.5086180341486388E+00 -2.5123493984859473E+00 -2.5160804535373322E+00 -2.5198111932660270E+00 -2.5235416116402143E+00 -2.5272717026330294E+00 -2.5310014602225506E+00 -2.5347308783918119E+00 -2.5384599511287953E+00 -2.5421886724264282E+00 -2.5459170362825927E+00 -2.5496450367001184E+00 -2.5533726676867827E+00 -2.5570999232553153E+00 -2.5608267974233918E+00 -2.5645532842136407E+00 -2.5682793776536395E+00 -2.5720050717759122E+00 -2.5757303606179347E+00 -2.5794552382221334E+00 -2.5831796986358815E+00 -2.5869037359115032E+00 -2.5906273441062702E+00 -2.5943505172824066E+00 -2.5980732495070846E+00 -2.6017955348524260E+00 -2.6055173673954997E+00 -2.6092387412183289E+00 -2.6129596504078814E+00 -2.6166800890560773E+00 -2.6204000512597863E+00 -2.6241195311208241E+00 -2.6278385227459609E+00 -2.6315570202469125E+00 -2.6352750177403452E+00 -2.6389925093478754E+00 -2.6427094891960690E+00 -2.6464259514164392E+00 -2.6501418901454539E+00 -2.6538572995245220E+00 -2.6575721737000100E+00 -2.6612865068232296E+00 -2.6650002930504417E+00 -2.6687135265428608E+00 -2.6724262014666440E+00 -2.6761383119929043E+00 -2.6798498522977017E+00 -2.6835608165620433E+00 -2.6872711989718896E+00 -2.6909809937181484E+00 -2.6946901949966766E+00 -2.6983987970082830E+00 -2.7021067939587216E+00 -2.7058141800586997E+00 -2.7095209495238737E+00 -2.7132270965748462E+00 -2.7169326154371727E+00 -2.7206375003413568E+00 -2.7243417455228509E+00 -2.7280453452220592E+00 -2.7317482936843311E+00 -2.7354505851599704E+00 -2.7391522139042279E+00 -2.7428531741773026E+00 -2.7465534602443440E+00 -2.7502530663754539E+00 -2.7539519868456788E+00 -2.7576502159350165E+00 -2.7613477479284163E+00 -2.7650445771157739E+00 -2.7687406977919369E+00 -2.7724361042566992E+00 -2.7761307908148072E+00 -2.7798247517759567E+00 -2.7835179814547897E+00 -2.7872104741709016E+00 -2.7909022242488359E+00 -2.7945932260180832E+00 -2.7982834738130871E+00 -2.8019729619732372E+00 -2.8056616848428755E+00 -2.8093496367712936E+00 -2.8130368121127289E+00 -2.8167232052263720E+00 -2.8204088104763616E+00 -2.8240936222317847E+00 -2.8277776348666790E+00 -2.8314608427600323E+00 -2.8351432402957806E+00 -2.8388248218628100E+00 -2.8425055818549545E+00 -2.8461855146710007E+00 -2.8498646147146811E+00 -2.8535428763946800E+00 -2.8572202941246312E+00 -2.8608968623231159E+00 -2.8645725754136664E+00 -2.8682474278247647E+00 -2.8719214139898406E+00 -2.8755945283472748E+00 -2.8792667653403976E+00 -2.8829381194174868E+00 -2.8866085850317722E+00 -2.8902781566414317E+00 -2.8939468287095917E+00 -2.8976145957043307E+00 -2.9012814520986736E+00 -2.9049473923705964E+00 -2.9086124110030260E+00 -2.9122765024838344E+00 -2.9159396613058477E+00 -2.9196018819668392E+00 -2.9232631589695313E+00 -2.9269234868215954E+00 -2.9305828600356572E+00 -2.9342412731292833E+00 -2.9378987206249967E+00 -2.9415551970502691E+00 -2.9452106969375169E+00 -2.9488652148241123E+00 -2.9525187452523713E+00 -2.9561712827695632E+00 -2.9598228219279052E+00 -2.9634733572845655E+00 -2.9671228834016570E+00 -2.9707713948462486E+00 -2.9744188861903549E+00 -2.9780653520109390E+00 -2.9817107868899160E+00 -2.9853551854141496E+00 -2.9889985421754530E+00 -2.9926408517705880E+00 -2.9962821088012661E+00 -2.9999223078741490E+00 -3.0035614436008480E+00 -3.0071995105979221E+00 -3.0108365034868823E+00 -3.0144724168941863E+00 -3.0181072454512434E+00 -3.0217409837944120E+00 -3.0253736265649973E+00 -3.0290051684092587E+00 -3.0326356039784015E+00 -3.0362649279285803E+00 -3.0398931349209013E+00 -3.0435202196214193E+00 -3.0471461767011387E+00 -3.0507710008360109E+00 -3.0543946867069400E+00 -3.0580172289997809E+00 -3.0616386224053302E+00 -3.0652588616193435E+00 -3.0688779413425196E+00 -3.0724958562805087E+00 -3.0761126011439104E+00 -3.0797281706482749E+00 -3.0833425595140995E+00 -3.0869557624668325E+00 -3.0905677742368693E+00 -3.0941785895595593E+00 -3.0977882031751984E+00 -3.1013966098290302E+00 -3.1050038042712513E+00 -3.1086097812570079E+00 -3.1122145355463902E+00 -3.1158180619044447E+00 -3.1194203551011639E+00 -3.1230214099114884E+00 -3.1266212211153110E+00 -3.1302197834974730E+00 -3.1338170918477641E+00 -3.1374131409609265E+00 -3.1410079256366474E+00 -3.1446014406795677E+00 -3.1481936808992748E+00 -3.1517846411103054E+00 -3.1553743161321486E+00 -3.1589627007892407E+00 -3.1625497899109667E+00 -3.1661355783316645E+00 -3.1697200608906169E+00 -3.1733032324320596E+00 -3.1768850878051778E+00 -3.1804656218641010E+00 -3.1840448294679153E+00 -3.1876227054806519E+00 -3.1911992447712922E+00 -3.1947744422137685E+00 -3.1983482926869597E+00 -3.2019207910746981E+00 -3.2054919322657618E+00 -3.2090617111538791E+00 -3.2126301226377283E+00 -3.2161971616209399E+00 -3.2197628230120872E+00 -3.2233271017247009E+00 -3.2268899926772532E+00 -3.2304514907931727E+00 -3.2340115910008338E+00 -3.2375702882335586E+00 -3.2411275774296233E+00 -3.2446834535322515E+00 -3.2482379114896149E+00 -3.2517909462548364E+00 -3.2553425527859865E+00 -3.2588927260460876E+00 -3.2624414610031107E+00 -3.2659887526299736E+00 -3.2695345959045463E+00 -3.2730789858096503E+00 -3.2766219173330500E+00 -3.2801633854674654E+00 -3.2837033852105648E+00 -3.2872419115649634E+00 -3.2907789595382266E+00 -3.2943145241428704E+00 -3.2978486003963603E+00 -3.3013811833211113E+00 -3.3049122679444842E+00 -3.3084418492987959E+00 -3.3119699224213082E+00 -3.3154964823542317E+00 -3.3190215241447301E+00 -3.3225450428449133E+00 -3.3260670335118414E+00 -3.3295874912075254E+00 -3.3331064109989237E+00 -3.3366237879579455E+00 -3.3401396171614497E+00 -3.3436538936912434E+00 -3.3471666126340840E+00 -3.3506777690816780E+00 -3.3541873581306811E+00 -3.3576953748826988E+00 -3.3612018144442861E+00 -3.3647066719269483E+00 -3.3682099424471383E+00 -3.3717116211262592E+00 -3.3752117030906645E+00 -3.3787101834716564E+00 -3.3822070574054850E+00 -3.3857023200333525E+00 -3.3891959665014078E+00 -3.3926879919607535E+00 -3.3961783915674375E+00 -3.3996671604824580E+00 -3.4031542938717649E+00 -3.4066397869062537E+00 -3.4101236347617729E+00 -3.4136058326191185E+00 -3.4170863756640375E+00 -3.4205652590872240E+00 -3.4240424780843242E+00 -3.4275180278559305E+00 -3.4309919036075889E+00 -3.4344641005497922E+00 -3.4379346138979803E+00 -3.4414034388725487E+00 -3.4448705706988378E+00 -3.4483360046071376E+00 -3.4517997358326902E+00 -3.4552617596156838E+00 -3.4587220712012590E+00 -3.4621806658395040E+00 -3.4656375387854568E+00 -3.4690926852991049E+00 -3.4725461006453862E+00 -3.4759977800941861E+00 -3.4794477189203414E+00 -3.4828959124036376E+00 -3.4863423558288091E+00 -3.4897870444855412E+00 -3.4932299736684653E+00 -3.4966711386771654E+00 -3.5001105348161761E+00 -3.5035481573949765E+00 -3.5069840017280001E+00 -3.5104180631346287E+00 -3.5138503369391896E+00 -3.5172808184709647E+00 -3.5207095030641837E+00 -3.5241363860580237E+00 -3.5275614627966139E+00 -3.5309847286290306E+00 -3.5344061789093022E+00 -3.5378258089964056E+00 -3.5412436142542645E+00 -3.5446595900517566E+00 -3.5480737317627056E+00 -3.5514860347658859E+00 -3.5548964944450208E+00 -3.5583051061887834E+00 -3.5617118653907966E+00 -3.5651167674496329E+00 -3.5685198077688125E+00 -3.5719209817568083E+00 -3.5753202848270385E+00 -3.5787177123978733E+00 -3.5821132598926329E+00 -3.5855069227395857E+00 -3.5888986963719480E+00 -3.5922885762278898E+00 -3.5956765577505272E+00 -3.5990626363879268E+00 -3.6024468075931035E+00 -3.6058290668240232E+00 -3.6092094095436003E+00 -3.6125878312197002E+00 -3.6159643273251354E+00 -3.6193388933376704E+00 -3.6227115247400152E+00 -3.6260822170198335E+00 -3.6294509656697369E+00 -3.6328177661872858E+00 -3.6361826140749893E+00 -3.6395455048403091E+00 -3.6429064339956532E+00 -3.6462653970583800E+00 -3.6496223895507995E+00 -3.6529774070001673E+00 -3.6563304449386909E+00 -3.6596814989035256E+00 -3.6630305644367782E+00 -3.6663776370855050E+00 -3.6697227124017084E+00 -3.6730657859423439E+00 -3.6764068532693162E+00 -3.6797459099494758E+00 -3.6830829515546282E+00 -3.6864179736615226E+00 -3.6897509718518609E+00 -3.6930819417122951E+00 -3.6964108788344237E+00 -3.6997377788147974E+00 -3.7030626372549165E+00 -3.7063854497612274E+00 -3.7097062119451305E+00 -3.7130249194229705E+00 -3.7163415678160461E+00 -3.7196561527506034E+00 -3.7229686698578370E+00 -3.7262791147738934E+00 -3.7295874831398668E+00 -3.7328937706018013E+00 -3.7361979728106918E+00 -3.7395000854224794E+00 -3.7428001040980563E+00 -3.7460980245032665E+00 -3.7493938423088986E+00 -3.7526875531906958E+00 -3.7559791528293474E+00 -3.7592686369104920E+00 -3.7625560011247208E+00 -3.7658412411675704E+00 -3.7691243527395297E+00 -3.7724053315460360E+00 -3.7756841732974764E+00 -3.7789608737091860E+00 -3.7822354285014521E+00 -3.7855078333995080E+00 -3.7887780841335403E+00 -3.7920461764386828E+00 -3.7953121060550186E+00 -3.7985758687275788E+00 -3.8018374602063489E+00 -3.8050968762462580E+00 -3.8083541126071903E+00 -3.8116091650539738E+00 -3.8148620293563895E+00 -3.8181127012891687E+00 -3.8213611766319873E+00 -3.8246074511694759E+00 -3.8278515206912127E+00 -3.8310933809917231E+00 -3.8343330278704855E+00 -3.8375704571319260E+00 -3.8408056645854205E+00 -3.8440386460452936E+00 -3.8472693973308187E+00 -3.8504979142662221E+00 -3.8537241926806769E+00 -3.8569482284083034E+00 -3.8601700172881763E+00 -3.8633895551643183E+00 -3.8666068378856981E+00 -3.8698218613062392E+00 -3.8730346212848086E+00 -3.8762451136852270E+00 -3.8794533343762647E+00 -3.8826592792316386E+00 -3.8858629441300168E+00 -3.8890643249550174E+00 -3.8922634175952062E+00 -3.8954602179441009E+00 -3.8986547219001650E+00 -3.9018469253668155E+00 -3.9050368242524169E+00 -3.9082244144702809E+00 -3.9114096919386721E+00 -3.9145926525808052E+00 -3.9177732923248398E+00 -3.9209516071038899E+00 -3.9241275928560153E+00 -3.9273012455242262E+00 -3.9304725610564843E+00 -3.9336415354056977E+00 -3.9368081645297255E+00 -3.9399724443913771E+00 -3.9431343709584090E+00 -3.9462939402035300E+00 -3.9494511481043961E+00 -3.9526059906436122E+00 -3.9557584638087357E+00 -3.9589085635922707E+00 -3.9620562859916721E+00 -3.9652016270093440E+00 -3.9683445826526391E+00 -3.9714851489338607E+00 -3.9746233218702613E+00 -3.9777590974840416E+00 -3.9808924718023526E+00 -3.9840234408572974E+00 -3.9871520006859229E+00 -3.9902781473302311E+00 -3.9934018768371686E+00 -3.9965231852586358E+00 -3.9996420686514798E+00 -4.0027585230774960E+00 -4.0058725446034336E+00 -4.0089841293009885E+00 -4.0120932732468040E+00 -4.0151999725224767E+00 -4.0183042232145523E+00 -4.0214060214145233E+00 -4.0245053632188332E+00 -4.0276022447288735E+00 -4.0306966620509881E+00 -4.0337886112964680E+00 -4.0368780885815543E+00 -4.0399650900274375E+00 -4.0430496117602583E+00 -4.0461316499111053E+00 -4.0492112006160186E+00 -4.0522882600159846E+00 -4.0553628242569415E+00 -4.0584348894897779E+00 -4.0615044518703289E+00 -4.0645715075593802E+00 -4.0676360527226700E+00 -4.0706980835308810E+00 -4.0737575961596475E+00 -4.0768145867895553E+00 -4.0798690516061349E+00 -4.0829209867998717E+00 -4.0859703885661958E+00 -4.0890172531054896E+00 -4.0920615766230846E+00 -4.0951033553292593E+00 -4.0981425854392475E+00 -4.1011792631732265E+00 -4.1042133847563225E+00 -4.1072449464186178E+00 -4.1102739443951375E+00 -4.1133003749258608E+00 -4.1163242342557131E+00 -4.1193455186345700E+00 -4.1223642243172574E+00 -4.1253803475635520E+00 -4.1283938846381742E+00 -4.1314048318108014E+00 -4.1344131853560544E+00 -4.1374189415535074E+00 -4.1404220966876828E+00 -4.1434226470480509E+00 -4.1464205889290335E+00 -4.1494159186300017E+00 -4.1524086324552725E+00 -4.1553987267141181E+00 -4.1583861977207572E+00 -4.1613710417943564E+00 -4.1643532552590345E+00 -4.1673328344438580E+00 -4.1703097756828447E+00 -4.1732840753149585E+00 -4.1762557296841170E+00 -4.1792247351391829E+00 -4.1821910880339725E+00 -4.1851547847272483E+00 -4.1881158215827234E+00 -4.1910741949690626E+00 -4.1940299012598752E+00 -4.1969829368337237E+00 -4.1999332980741189E+00 -4.2028809813695220E+00 -4.2058259831133418E+00 -4.2087682997039382E+00 -4.2117079275446203E+00 -4.2146448630436453E+00 -4.2175791026142218E+00 -4.2205106426745074E+00 -4.2234394796476060E+00 -4.2263656099615758E+00 -4.2292890300494212E+00 -4.2322097363490983E+00 -4.2351277253035091E+00 -4.2380429933605095E+00 -4.2409555369729004E+00 -4.2438653525984380E+00 -4.2467724366998212E+00 -4.2496767857447022E+00 -4.2525783962056822E+00 -4.2554772645603105E+00 -4.2583733872910887E+00 -4.2612667608854657E+00 -4.2641573818358385E+00 -4.2670452466395581E+00 -4.2699303517989193E+00 -4.2728126938211703E+00 -4.2756922692185064E+00 -4.2785690745080762E+00 -4.2814431062119720E+00 -4.2843143608572412E+00 -4.2871828349758765E+00 -4.2900485251048224E+00 -4.2929114277859712E+00 -4.2957715395661644E+00 -4.2986288569971967E+00 -4.3014833766358080E+00 -4.3043350950436894E+00 -4.3071840087874813E+00 -4.3100301144387725E+00 -4.3128734085741041E+00 -4.3157138877749626E+00 -4.3185515486277879E+00 -4.3213863877239653E+00 -4.3242184016598344E+00 -4.3270475870366800E+00 -4.3298739404607396E+00 -4.3326974585431959E+00 -4.3355181379001859E+00 -4.3383359751527930E+00 -4.3411509669270503E+00 -4.3439631098539406E+00 -4.3467724005693986E+00 -4.3495788357143033E+00 -4.3523824119344887E+00 -4.3551831258807336E+00 -4.3579809742087701E+00 -4.3607759535792772E+00 -4.3635680606578822E+00 -4.3663572921151665E+00 -4.3691436446266563E+00 -4.3719271148728298E+00 -4.3747076995391136E+00 -4.3774853953158850E+00 -4.3802601988984691E+00 -4.3830321069871419E+00 -4.3858011162871273E+00 -4.3885672235085984E+00 -4.3913304253666805E+00 -4.3940907185814453E+00 -4.3968480998779169E+00 -4.3996025659860667E+00 -4.4023541136408149E+00 -4.4051027395820324E+00 -4.4078484405545417E+00 -4.4105912133081091E+00 -4.4133310545974567E+00 -4.4160679611822511E+00 -4.4188019298271115E+00 -4.4215329573016051E+00 -4.4242610403802471E+00 -4.4269861758425080E+00 -4.4297083604727989E+00 -4.4324275910604864E+00 -4.4351438643998859E+00 -4.4378571772902626E+00 -4.4405675265358271E+00 -4.4432749089457459E+00 -4.4459793213341277E+00 -4.4486807605200367E+00 -4.4513792233274838E+00 -4.4540747065854296E+00 -4.4567672071277835E+00 -4.4594567217934076E+00 -4.4621432474261082E+00 -4.4648267808746454E+00 -4.4675073189927268E+00 -4.4701848586390085E+00 -4.4728593966770998E+00 -4.4755309299755552E+00 -4.4781994554078803E+00 -4.4808649698525311E+00 -4.4835274701929126E+00 -4.4861869533173770E+00 -4.4888434161192308E+00 -4.4914968554967238E+00 -4.4941472683530614E+00 -4.4967946515963915E+00 -4.4994390021398178E+00 -4.5020803169013925E+00 -4.5047185928041129E+00 -4.5073538267759297E+00 -4.5099860157497416E+00 -4.5126151566633990E+00 -4.5152412464596976E+00 -4.5178642820863848E+00 -4.5204842604961577E+00 -4.5231011786466642E+00 -4.5257150335004965E+00 -4.5283258220252032E+00 -4.5309335411932770E+00 -4.5335381879821623E+00 -4.5361397593742536E+00 -4.5387382523568931E+00 -4.5413336639223711E+00 -4.5439259910679324E+00 -4.5465152307957659E+00 -4.5491013801130142E+00 -4.5516844360317670E+00 -4.5542643955690618E+00 -4.5568412557468898E+00 -4.5594150135921891E+00 -4.5619856661368470E+00 -4.5645532104177002E+00 -4.5671176434765384E+00 -4.5696789623600926E+00 -4.5722371641200548E+00 -4.5747922458130539E+00 -4.5773442045006796E+00 -4.5798930372494624E+00 -4.5824387411308871E+00 -4.5849813132213857E+00 -4.5875207506023425E+00 -4.5900570503600866E+00 -4.5925902095859001E+00 -4.5951202253760153E+00 -4.5976470948316095E+00 -4.6001708150588154E+00 -4.6026913831687084E+00 -4.6052087962773189E+00 -4.6077230515056247E+00 -4.6102341459795522E+00 -4.6127420768299796E+00 -4.6152468411927314E+00 -4.6177484362085846E+00 -4.6202468590232639E+00 -4.6227421067874417E+00 -4.6252341766567442E+00 -4.6277230657917450E+00 -4.6302087713579656E+00 -4.6326912905258792E+00 -4.6351706204709062E+00 -4.6376467583734193E+00 -4.6401197014187394E+00 -4.6425894467971336E+00 -4.6450559917038241E+00 -4.6475193333389786E+00 -4.6499794689077154E+00 -4.6524363956201027E+00 -4.6548901106911584E+00 -4.6573406113408478E+00 -4.6597878947940883E+00 -4.6622319582807439E+00 -4.6646727990356300E+00 -4.6671104142985129E+00 -4.6695448013141041E+00 -4.6719759573320685E+00 -4.6744038796070173E+00 -4.6768285653985151E+00 -4.6792500119710709E+00 -4.6816682165941472E+00 -4.6840831765421544E+00 -4.6864948890944529E+00 -4.6889033515353500E+00 -4.6913085611541074E+00 -4.6937105152449314E+00 -4.6961092111069807E+00 -4.6985046460443627E+00 -4.7008968173661332E+00 -4.7032857223862985E+00 -4.7056713584238157E+00 -4.7080537228025854E+00 -4.7104328128514661E+00 -4.7128086259042616E+00 -4.7151811592997221E+00 -4.7175504103815529E+00 -4.7199163764984062E+00 -4.7222790550038818E+00 -4.7246384432565316E+00 -4.7269945386198575E+00 -4.7293473384623068E+00 -4.7316968401572810E+00 -4.7340430410831278E+00 -4.7363859386231466E+00 -4.7387255301655831E+00 -4.7410618131036371E+00 -4.7433947848354521E+00 -4.7457244427641259E+00 -4.7480507842977042E+00 -4.7503738068491819E+00 -4.7526935078365016E+00 -4.7550098846825604E+00 -4.7573229348151989E+00 -4.7596326556672093E+00 -4.7619390446763354E+00 -4.7642420992852683E+00 -4.7665418169416487E+00 -4.7688381950980672E+00 -4.7711312312120642E+00 -4.7734209227461291E+00 -4.7757072671676992E+00 -4.7779902619491628E+00 -4.7802699045678585E+00 -4.7825461925060742E+00 -4.7848191232510446E+00 -4.7870886942949573E+00 -4.7893549031349467E+00 -4.7916177472730981E+00 -4.7938772242164456E+00 -4.7961333314769723E+00 -4.7983860665716120E+00 -4.8006354270222484E+00 -4.8028814103557114E+00 -4.8051240141037841E+00 -4.8073632358031979E+00 -4.8095990729956304E+00 -4.8118315232277151E+00 -4.8140605840510284E+00 -4.8162862530221009E+00 -4.8185085277024093E+00 -4.8207274056583822E+00 -4.8229428844613969E+00 -4.8251549616877787E+00 -4.8273636349188047E+00 -4.8295689017406991E+00 -4.8317707597446375E+00 -4.8339692065267448E+00 -4.8361642396880926E+00 -4.8383558568347063E+00 -4.8405440555775563E+00 -4.8427288335325676E+00 -4.8449101883206094E+00 -4.8470881175675018E+00 -4.8492626189040191E+00 -4.8514336899658757E+00 -4.8536013283937445E+00 -4.8557655318332440E+00 -4.8579262979349416E+00 -4.8600836243543553E+00 -4.8622375087519503E+00 -4.8643879487931452E+00 -4.8665349421483048E+00 -4.8686784864927448E+00 -4.8708185795067305E+00 -4.8729552188754752E+00 -4.8750884022891423E+00 -4.8772181274428457E+00 -4.8793443920366482E+00 -4.8814671937755616E+00 -4.8835865303695467E+00 -4.8857023995335149E+00 -4.8878147989873257E+00 -4.8899237264557902E+00 -4.8920291796686657E+00 -4.8941311563606620E+00 -4.8962296542714379E+00 -4.8983246711456010E+00 -4.9004162047327062E+00 -4.9025042527872618E+00 -4.9045888130687221E+00 -4.9066698833414941E+00 -4.9087474613749320E+00 -4.9108215449433388E+00 -4.9128921318259691E+00 -4.9149592198070247E+00 -4.9170228066756616E+00 -4.9190828902259778E+00 -4.9211394682570271E+00 -4.9231925385728088E+00 -4.9252420989822747E+00 -4.9272881472993229E+00 -4.9293306813428028E+00 -4.9313696989365150E+00 -4.9334051979092042E+00 -4.9354371760945712E+00 -4.9374656313312606E+00 -4.9394905614628692E+00 -4.9415119643379439E+00 -4.9435298378099803E+00 -4.9455441797374196E+00 -4.9475549879836604E+00 -4.9495622604170419E+00 -4.9515659949108617E+00 -4.9535661893433591E+00 -4.9555628415977262E+00 -4.9575559495621055E+00 -4.9595455111295870E+00 -4.9615315241982119E+00 -4.9635139866709688E+00 -4.9654928964557969E+00 -4.9674682514655855E+00 -4.9694400496181705E+00 -4.9714082888363418E+00 -4.9733729670478359E+00 -4.9753340821853396E+00 -4.9772916321864846E+00 -4.9792456149938618E+00 -4.9811960285550025E+00 -4.9831428708223910E+00 -4.9850861397534620E+00 -4.9870258333105966E+00 -4.9889619494611290E+00 -4.9908944861773410E+00 -4.9928234414364621E+00 -4.9947488132206752E+00 -4.9966705995171097E+00 -4.9985887983178445E+00 -5.0005034076199095E+00 -5.0024144254252825E+00 -5.0043218497408919E+00 -5.0062256785786161E+00 -5.0081259099552797E+00 -5.0100225418926607E+00 -5.0119155724174833E+00 -5.0138049995614242E+00 -5.0156908213611073E+00 -5.0175730358581081E+00 -5.0194516410989474E+00 -5.0213266351351002E+00 -5.0231980160229863E+00 -5.0250657818239803E+00 -5.0269299306044042E+00 -5.0287904604355251E+00 -5.0306473693935656E+00 -5.0325006555596943E+00 -5.0343503170200314E+00 -5.0361963518656427E+00 -5.0380387581925508E+00 -5.0398775341017172E+00 -5.0417126776990635E+00 -5.0435441870954545E+00 -5.0453720604067041E+00 -5.0471962957535794E+00 -5.0490168912617941E+00 -5.0508338450620132E+00 -5.0526471552898480E+00 -5.0544568200858642E+00 -5.0562628375955709E+00 -5.0580652059694335E+00 -5.0598639233628608E+00 -5.0616589879362142E+00 -5.0634503978548011E+00 -5.0652381512888871E+00 -5.0670222464136758E+00 -5.0688026814093279E+00 -5.0705794544609502E+00 -5.0723525637586011E+00 -5.0741220074972855E+00 -5.0758877838769623E+00 -5.0776498911025358E+00 -5.0794083273838613E+00 -5.0811630909357408E+00 -5.0829141799779327E+00 -5.0846615927351371E+00 -5.0864053274370082E+00 -5.0881453823181477E+00 -5.0898817556181069E+00 -5.0916144455813885E+00 -5.0933434504574420E+00 -5.0950687685006688E+00 -5.0967903979704152E+00 -5.0985083371309834E+00 -5.1002225842516209E+00 -5.1019331376065233E+00 -5.1036399954748424E+00 -5.1053431561406715E+00 -5.1070426178930566E+00 -5.1087383790259944E+00 -5.1104304378384287E+00 -5.1121187926342557E+00 -5.1138034417223190E+00 -5.1154843834164128E+00 -5.1171616160352764E+00 -5.1188351379026047E+00 -5.1205049473470385E+00 -5.1221710427021705E+00 -5.1238334223065403E+00 -5.1254920845036365E+00 -5.1271470276418993E+00 -5.1287982500747198E+00 -5.1304457501604332E+00 -5.1320895262623303E+00 -5.1337295767486442E+00 -5.1353658999925651E+00 -5.1369984943722278E+00 -5.1386273582707185E+00 -5.1402524900760715E+00 -5.1418738881812720E+00 -5.1434915509842520E+00 -5.1451054768878963E+00 -5.1467156643000385E+00 -5.1483221116334583E+00 -5.1499248173058909E+00 -5.1515237797400131E+00 -5.1531189973634586E+00 -5.1547104686088057E+00 -5.1562981919135842E+00 -5.1578821657202747E+00 -5.1594623884763031E+00 -5.1610388586340470E+00 -5.1626115746508354E+00 -5.1641805349889438E+00 -5.1657457381155991E+00 -5.1673071825029755E+00 -5.1688648666281996E+00 -5.1704187889733442E+00 -5.1719689480254329E+00 -5.1735153422764402E+00 -5.1750579702232891E+00 -5.1765968303678509E+00 -5.1781319212169468E+00 -5.1796632412823485E+00 -5.1811907890807758E+00 -5.1827145631339002E+00 -5.1842345619683403E+00 -5.1857507841156636E+00 -5.1872632281123892E+00 -5.1887718924999859E+00 -5.1902767758248691E+00 -5.1917778766384055E+00 -5.1932751934969144E+00 -5.1947687249616559E+00 -5.1962584695988481E+00 -5.1977444259796552E+00 -5.1992265926801915E+00 -5.2007049682815181E+00 -5.2021795513696487E+00 -5.2036503405355461E+00 -5.2051173343751209E+00 -5.2065805314892346E+00 -5.2080399304836975E+00 -5.2094955299692698E+00 -5.2109473285616614E+00 -5.2123953248815278E+00 -5.2138395175544812E+00 -5.2152799052110774E+00 -5.2167164864868241E+00 -5.2181492600221775E+00 -5.2195782244625413E+00 -5.2210033784582750E+00 -5.2224247206646810E+00 -5.2238422497420149E+00 -5.2252559643554788E+00 -5.2266658631752279E+00 -5.2280719448763628E+00 -5.2294742081389360E+00 -5.2308726516479496E+00 -5.2322672740933545E+00 -5.2336580741700507E+00 -5.2350450505778889E+00 -5.2364282020216670E+00 -5.2378075272111353E+00 -5.2391830248609903E+00 -5.2405546936908802E+00 -5.2419225324254040E+00 -5.2432865397941040E+00 -5.2446467145314797E+00 -5.2460030553769759E+00 -5.2473555610749862E+00 -5.2487042303748552E+00 -5.2500490620308771E+00 -5.2513900548022949E+00 -5.2527272074533018E+00 -5.2540605187530369E+00 -5.2553899874755956E+00 -5.2567156124000167E+00 -5.2580373923102908E+00 -5.2593553259953572E+00 -5.2606694122491060E+00 -5.2619796498703764E+00 -5.2632860376629544E+00 -5.2645885744355789E+00 -5.2658872590019374E+00 -5.2671820901806656E+00 -5.2684730667953499E+00 -5.2697601876745237E+00 -5.2710434516516740E+00 -5.2723228575652357E+00 -5.2735984042585891E+00 -5.2748700905800705E+00 -5.2761379153829608E+00 -5.2774018775254916E+00 -5.2786619758708460E+00 -5.2799182092871542E+00 -5.2811705766474955E+00 -5.2824190768299006E+00 -5.2836637087173477E+00 -5.2849044711977680E+00 -5.2861413631640355E+00 -5.2873743835139813E+00 -5.2886035311503798E+00 -5.2898288049809592E+00 -5.2910502039183953E+00 -5.2922677268803113E+00 -5.2934813727892847E+00 -5.2946911405728381E+00 -5.2958970291634451E+00 -5.2970990374985298E+00 -5.2982971645204637E+00 -5.2994914091765679E+00 -5.3006817704191151E+00 -5.3018682472053262E+00 -5.3030508384973709E+00 -5.3042295432623696E+00 -5.3054043604723899E+00 -5.3065752891044520E+00 -5.3077423281405229E+00 -5.3089054765675208E+00 -5.3100647333773114E+00 -5.3112200975667134E+00 -5.3123715681374897E+00 -5.3135191440963583E+00 -5.3146628244549809E+00 -5.3158026082299736E+00 -5.3169384944429003E+00 -5.3180704821202731E+00 -5.3191985702935547E+00 -5.3203227579991568E+00 -5.3214430442784408E+00 -5.3225594281777182E+00 -5.3236719087482474E+00 -5.3247804850462384E+00 -5.3258851561328528E+00 -5.3269859210741979E+00 -5.3280827789413294E+00 -5.3291757288102586E+00 -5.3302647697619374E+00 -5.3313499008822758E+00 -5.3324311212621307E+00 -5.3335084299973037E+00 -5.3345818261885514E+00 -5.3356513089415776E+00 -5.3367168773670350E+00 -5.3377785305805281E+00 -5.3388362677026082E+00 -5.3398900878587767E+00 -5.3409399901794874E+00 -5.3419859738001376E+00 -5.3430280378610790E+00 -5.3440661815076131E+00 -5.3451004038899850E+00 -5.3461307041633974E+00 -5.3471570814879952E+00 -5.3481795350288754E+00 -5.3491980639560888E+00 -5.3502126674446275E+00 -5.3512233446744384E+00 -5.3522300948304178E+00 -5.3532329171024085E+00 -5.3542318106852074E+00 -5.3552267747785542E+00 -5.3562178085871448E+00 -5.3572049113206202E+00 -5.3581880821935721E+00 -5.3591673204255423E+00 -5.3601426252410214E+00 -5.3611139958694487E+00 -5.3620814315452154E+00 -5.3630449315076589E+00 -5.3640044950010681E+00 -5.3649601212746827E+00 -5.3659118095826868E+00 -5.3668595591842188E+00 -5.3678033693433660E+00 -5.3687432393291621E+00 -5.3696791684155940E+00 -5.3706111558815950E+00 -5.3715392010110499E+00 -5.3724633030927906E+00 -5.3733834614206000E+00 -5.3742996752932131E+00 -5.3752119440143105E+00 -5.3761202668925216E+00 -5.3770246432414286E+00 -5.3779250723795622E+00 -5.3788215536303996E+00 -5.3797140863223722E+00 -5.3806026697888578E+00 -5.3814873033681820E+00 -5.3823679864036249E+00 -5.3832447182434136E+00 -5.3841174982407205E+00 -5.3849863257536752E+00 -5.3858512001453516E+00 -5.3867121207837725E+00 -5.3875690870419142E+00 -5.3884220982976982E+00 -5.3892711539339988E+00 -5.3901162533386371E+00 -5.3909573959043859E+00 -5.3917945810289654E+00 -5.3926278081150461E+00 -5.3934570765702494E+00 -5.3942823858071431E+00 -5.3951037352432483E+00 -5.3959211243010303E+00 -5.3967345524079091E+00 -5.3975440189962516E+00 -5.3983495235033745E+00 -5.3991510653715435E+00 -5.3999486440479743E+00 -5.4007422589848320E+00 -5.4015319096392318E+00 -5.4023175954732361E+00 -5.4030993159538596E+00 -5.4038770705530652E+00 -5.4046508587477637E+00 -5.4054206800198159E+00 -5.4061865338560366E+00 -5.4069484197481836E+00 -5.4077063371929679E+00 -5.4084602856920485E+00 -5.4092102647520335E+00 -5.4099562738844824E+00 -5.4106983126059029E+00 -5.4114363804377525E+00 -5.4121704769064367E+00 -5.4129006015433125E+00 -5.4136267538846843E+00 -5.4143489334718078E+00 -5.4150671398508896E+00 -5.4157813725730790E+00 -5.4164916311944831E+00 -5.4171979152761525E+00 -5.4179002243840912E+00 -5.4185985580892488E+00 -5.4192929159675280E+00 -5.4199832975997788E+00 -5.4206697025718000E+00 -5.4213521304743422E+00 -5.4220305809031046E+00 -5.4227050534587349E+00 -5.4233755477468302E+00 -5.4240420633779385E+00 -5.4247045999675567E+00 -5.4253631571361298E+00 -5.4260177345090534E+00 -5.4266683317166740E+00 -5.4273149483942840E+00 -5.4279575841821277E+00 -5.4285962387253992E+00 -5.4292309116742405E+00 -5.4298616026837445E+00 -5.4304883114139511E+00 -5.4311110375298535E+00 -5.4317297807013905E+00 -5.4323445406034523E+00 -5.4329553169158800E+00 -5.4335621093234590E+00 -5.4341649175159308E+00 -5.4347637411879797E+00 -5.4353585800392468E+00 -5.4359494337743159E+00 -5.4365363021027244E+00 -5.4371191847389566E+00 -5.4376980814024476E+00 -5.4382729918175832E+00 -5.4388439157136945E+00 -5.4394108528250671E+00 -5.4399738028909326E+00 -5.4405327656554734E+00 -5.4410877408678200E+00 -5.4416387282820553E+00 -5.4421857276572085E+00 -5.4427287387572596E+00 -5.4432677613511382E+00 -5.4438027952127213E+00 -5.4443338401208399E+00 -5.4448608958592706E+00 -5.4453839622167397E+00 -5.4459030389869243E+00 -5.4464181259684494E+00 -5.4469292229648927E+00 -5.4474363297847770E+00 -5.4479394462415760E+00 -5.4484385721537167E+00 -5.4489337073445689E+00 -5.4494248516424566E+00 -5.4499120048806509E+00 -5.4503951668973754E+00 -5.4508743375357991E+00 -5.4513495166440435E+00 -5.4518207040751774E+00 -5.4522878996872208E+00 -5.4527511033431422E+00 -5.4532103149108604E+00 -5.4536655342632416E+00 -5.4541167612781036E+00 -5.4545639958382122E+00 -5.4550072378312846E+00 -5.4554464871499864E+00 -5.4558817436919300E+00 -5.4563130073596824E+00 -5.4567402780607548E+00 -5.4571635557076128E+00 -5.4575828402176656E+00 -5.4579981315132793E+00 -5.4584094295217627E+00 -5.4588167341753779E+00 -5.4592200454113335E+00 -5.4596193631717913E+00 -5.4600146874038593E+00 -5.4604060180595964E+00 -5.4607933550960110E+00 -5.4611766984750609E+00 -5.4615560481636516E+00 -5.4619314041336411E+00 -5.4623027663618346E+00 -5.4626701348299882E+00 -5.4630335095248057E+00 -5.4633928904379410E+00 -5.4637482775659993E+00 -5.4640996709105316E+00 -5.4644470704780428E+00 -5.4647904762799824E+00 -5.4651298883327533E+00 -5.4654653066577064E+00 -5.4657967312811415E+00 -5.4661241622343084E+00 -5.4664475995534056E+00 -5.4667670432795843E+00 -5.4670824934589390E+00 -5.4673939501425188E+00 -5.4677014133863224E+00 -5.4680048832512931E+00 -5.4683043598033292E+00 -5.4685998431132736E+00 -5.4688913332569236E+00 -5.4691788303150215E+00 -5.4694623343732607E+00 -5.4697418455222859E+00 -5.4700173638576883E+00 -5.4702888894800106E+00 -5.4705564224947443E+00 -5.4708199630123282E+00 -5.4710795111481554E+00 -5.4713350670225642E+00 -5.4715866307608421E+00 -5.4718342024932305E+00 -5.4720777823549156E+00 -5.4723173704860359E+00 -5.4725529670316782E+00 -5.4727845721418777E+00 -5.4730121859716210E+00 -5.4732358086808439E+00 -5.4734554404344307E+00 -5.4736710814022143E+00 -5.4738827317589802E+00 -5.4740903916844585E+00 -5.4742940613633362E+00 -5.4744937409852410E+00 -5.4746894307447569E+00 -5.4748811308414114E+00 -5.4750688414796880E+00 -5.4752525628690156E+00 -5.4754322952237731E+00 -5.4756080387632871E+00 -5.4757797937118386E+00 -5.4759475602986534E+00 -5.4761113387579075E+00 -5.4762711293287296E+00 -5.4764269322551939E+00 -5.4765787477863253E+00 -5.4767265761760990E+00 -5.4768704176834389E+00 -5.4770102725722181E+00 -5.4771461411112616E+00 -5.4772780235743390E+00 -5.4774059202401739E+00 -5.4775298313924372E+00 -5.4776497573197487E+00 -5.4777656983156797E+00 -5.4778776546787498E+00 -5.4779856267124263E+00 -5.4780896147251301E+00 -5.4781896190302293E+00 -5.4782856399460371E+00 -5.4783776777958249E+00 -5.4784657329078073E+00 -5.4785498056151498E+00 -5.4786298962559670E+00 -5.4787060051733265E+00 -5.4787781327152381E+00 -5.4788462792346673E+00 -5.4789104450895261E+00 -5.4789706306426789E+00 -5.4790268362619354E+00 -5.4790790623200580E+00 -5.4791273091947588E+00 -5.4791715772686933E+00 -5.4792118669294751E+00 -5.4792481785696623E+00 -5.4792805125867625E+00 -5.4793088693832335E+00 -5.4793332493664835E+00 -5.4793536529488698E+00 -5.4793700805476977E+00 -5.4793825325852223E+00 -5.4793910094886504E+00 -5.4793955116901341E+00 -5.4793960396267787E+00 -5.4793925937406387E+00 -5.4793851744787165E+00 -5.4793737822929618E+00 -5.4793584176402792E+00 -5.4793390809825198E+00 -5.4793157727864834E+00 -5.4792884935239190E+00 -5.4792572436715288E+00 -5.4792220237109595E+00 -5.4791828341288094E+00 -5.4791396754166275E+00 -5.4790925480709118E+00 -5.4790414525931066E+00 -5.4789863894896103E+00 -5.4789273592717675E+00 -5.4788643624558730E+00 -5.4787973995631720E+00 -5.4787264711198578E+00 -5.4786515776570743E+00 -5.4785727197109146E+00 -5.4784898978224197E+00 -5.4784031125375812E+00 -5.4783123644073424E+00 -5.4782176539875929E+00 -5.4781189818391720E+00 -5.4780163485278690E+00 -5.4779097546244246E+00 -5.4777992007045251E+00 -5.4776846873488081E+00 -5.4775662151428630E+00 -5.4774437846772255E+00 -5.4773173965473818E+00 -5.4771870513537655E+00 -5.4770527497017651E+00 -5.4769144922017121E+00 -5.4767722794688929E+00 -5.4766261121235384E+00 -5.4764759907908331E+00 -5.4763219161009085E+00 -5.4761638886888457E+00 -5.4760019091946761E+00 -5.4758359782633814E+00 -5.4756660965448916E+00 -5.4754922646940836E+00 -5.4753144833707896E+00 -5.4751327532397847E+00 -5.4749470749707987E+00 -5.4747574492385080E+00 -5.4745638767225406E+00 -5.4743663581074706E+00 -5.4741648940828256E+00 -5.4739594853430775E+00 -5.4737501325876536E+00 -5.4735368365209274E+00 -5.4733195978522211E+00 -5.4730984172958070E+00 -5.4728732955709098E+00 -5.4726442334016969E+00 -5.4724112315172944E+00 -5.4721742906517683E+00 -5.4719334115441427E+00 -5.4716885949383833E+00 -5.4714398415834111E+00 -5.4711871522330924E+00 -5.4709305276462468E+00 -5.4706699685866429E+00 -5.4704054758229930E+00 -5.4701370501289661E+00 -5.4698646922831768E+00 -5.4695884030691904E+00 -5.4693081832755208E+00 -5.4690240336956313E+00 -5.4687359551279373E+00 -5.4684439483757989E+00 -5.4681480142475314E+00 -5.4678481535563925E+00 -5.4675443671205946E+00 -5.4672366557633003E+00 -5.4669250203126163E+00 -5.4666094616016041E+00 -5.4662899804682716E+00 -5.4659665777555784E+00 -5.4656392543114301E+00 -5.4653080109886840E+00 -5.4649728486451483E+00 -5.4646337681435790E+00 -5.4642907703516785E+00 -5.4639438561421052E+00 -5.4635930263924610E+00 -5.4632382819853014E+00 -5.4628796238081296E+00 -5.4625170527533964E+00 -5.4621505697185055E+00 -5.4617801756058073E+00 -5.4614058713226035E+00 -5.4610276577811447E+00 -5.4606455358986299E+00 -5.4602595065972102E+00 -5.4598695708039813E+00 -5.4594757294509941E+00 -5.4590779834752441E+00 -5.4586763338186808E+00 -5.4582707814281992E+00 -5.4578613272556451E+00 -5.4574479722578140E+00 -5.4570307173964521E+00 -5.4566095636382519E+00 -5.4561845119548584E+00 -5.4557555633228629E+00 -5.4553227187238100E+00 -5.4548859791441906E+00 -5.4544453455754471E+00 -5.4540008190139693E+00 -5.4535524004610982E+00 -5.4531000909231233E+00 -5.4526438914112854E+00 -5.4521838029417697E+00 -5.4517198265357178E+00 -5.4512519632192165E+00 -5.4507802140233022E+00 -5.4503045799839605E+00 -5.4498250621421294E+00 -5.4493416615436914E+00 -5.4488543792394850E+00 -5.4483632162852915E+00 -5.4478681737418446E+00 -5.4473692526748296E+00 -5.4468664541548772E+00 -5.4463597792575706E+00 -5.4458492290634410E+00 -5.4453348046579677E+00 -5.4448165071315824E+00 -5.4442943375796649E+00 -5.4437682971025438E+00 -5.4432383868054988E+00 -5.4427046077987571E+00 -5.4421669611974961E+00 -5.4416254481218429E+00 -5.4410800696968744E+00 -5.4405308270526165E+00 -5.4399777213240439E+00 -5.4394207536510821E+00 -5.4388599251786047E+00 -5.4382952370564350E+00 -5.4377266904393471E+00 -5.4371542864870621E+00 -5.4365780263642538E+00 -5.4359979112405412E+00 -5.4354139422904977E+00 -5.4348261206936428E+00 -5.4342344476344442E+00 -5.4336389243023238E+00 -5.4330395518916488E+00 -5.4324363316017381E+00 -5.4318292646368587E+00 -5.4312183522062254E+00 -5.4306035955240084E+00 -5.4299849958093214E+00 -5.4293625542862305E+00 -5.4287362721837491E+00 -5.4281061507358430E+00 -5.4274721911814234E+00 -5.4268343947643567E+00 -5.4261927627334519E+00 -5.4255472963424740E+00 -5.4248979968501319E+00 -5.4242448655200866E+00 -5.4235879036209500E+00 -5.4229271124262821E+00 -5.4222624932145882E+00 -5.4215940472693323E+00 -5.4209217758789174E+00 -5.4202456803367030E+00 -5.4195657619409978E+00 -5.4188820219950546E+00 -5.4181944618070821E+00 -5.4175030826902342E+00 -5.4168078859626156E+00 -5.4161088729472802E+00 -5.4154060449722330E+00 -5.4146994033704248E+00 -5.4139889494797595E+00 -5.4132746846430893E+00 -5.4125566102082132E+00 -5.4118347275278849E+00 -5.4111090379598030E+00 -5.4103795428666173E+00 -5.4096462436159261E+00 -5.4089091415802795E+00 -5.4081682381371738E+00 -5.4074235346690589E+00 -5.4066750325633288E+00 -5.4059227332123321E+00 -5.4051666380133616E+00 -5.4044067483686664E+00 -5.4036430656854373E+00 -5.4028755913758220E+00 -5.4021043268569100E+00 -5.4013292735507479E+00 -5.4005504328843257E+00 -5.3997678062895860E+00 -5.3989813952034202E+00 -5.3981912010676689E+00 -5.3973972253291231E+00 -5.3965994694395203E+00 -5.3957979348555511E+00 -5.3949926230388527E+00 -5.3941835354560155E+00 -5.3933706735785742E+00 -5.3925540388830173E+00 -5.3917336328507810E+00 -5.3909094569682496E+00 -5.3900815127267601E+00 -5.3892498016225945E+00 -5.3884143251569894E+00 -5.3875750848361275E+00 -5.3867320821711413E+00 -5.3858853186781115E+00 -5.3850347958780738E+00 -5.3841805152970066E+00 -5.3833224784658400E+00 -5.3824606869204557E+00 -5.3815951422016832E+00 -5.3807258458553022E+00 -5.3798527994320384E+00 -5.3789760044875718E+00 -5.3780954625825288E+00 -5.3772111752824880E+00 -5.3763231441579720E+00 -5.3754313707844608E+00 -5.3745358567423773E+00 -5.3736366036170944E+00 -5.3727336129989389E+00 -5.3718268864831815E+00 -5.3709164256700488E+00 -5.3700022321647092E+00 -5.3690843075772872E+00 -5.3681626535228508E+00 -5.3672372716214252E+00 -5.3663081634979770E+00 -5.3653753307824257E+00 -5.3644387751096430E+00 -5.3634984981194442E+00 -5.3625545014565983E+00 -5.3616067867708237E+00 -5.3606553557167853E+00 -5.3597002099541005E+00 -5.3587413511473336E+00 -5.3577787809660000E+00 -5.3568125010845673E+00 -5.3558425131824441E+00 -5.3548688189439977E+00 -5.3538914200585399E+00 -5.3529103182203324E+00 -5.3519255151285856E+00 -5.3509370124874645E+00 -5.3499448120060764E+00 -5.3489489153984824E+00 -5.3479493243836931E+00 -5.3469460406856646E+00 -5.3459390660333064E+00 -5.3449284021604768E+00 -5.3439140508059841E+00 -5.3428960137135846E+00 -5.3418742926319815E+00 -5.3408488893148327E+00 -5.3398198055207446E+00 -5.3387870430132685E+00 -5.3377506035609104E+00 -5.3367104889371229E+00 -5.3356667009203074E+00 -5.3346192412938205E+00 -5.3335681118459579E+00 -5.3325133143699768E+00 -5.3314548506640724E+00 -5.3303927225313972E+00 -5.3293269317800505E+00 -5.3282574802230798E+00 -5.3271843696784869E+00 -5.3261076019692162E+00 -5.3250271789231656E+00 -5.3239431023731827E+00 -5.3228553741570623E+00 -5.3217639961175500E+00 -5.3206689701023420E+00 -5.3195702979640815E+00 -5.3184679815603628E+00 -5.3173620227537306E+00 -5.3162524234116741E+00 -5.3151391854066388E+00 -5.3140223106160152E+00 -5.3129018009221429E+00 -5.3117776582123142E+00 -5.3106498843787691E+00 -5.3095184813186966E+00 -5.3083834509342340E+00 -5.3072447951324717E+00 -5.3061025158254456E+00 -5.3049566149301448E+00 -5.3038070943685041E+00 -5.3026539560674104E+00 -5.3014972019586999E+00 -5.3003368339791557E+00 -5.2991728540705143E+00 -5.2980052641794568E+00 -5.2968340662576194E+00 -5.2956592622615828E+00 -5.2944808541528792E+00 -5.2932988438979907E+00 -5.2921132334683474E+00 -5.2909240248403329E+00 -5.2897312199952724E+00 -5.2885348209194492E+00 -5.2873348296040881E+00 -5.2861312480453710E+00 -5.2849240782444245E+00 -5.2837133222073254E+00 -5.2824989819451007E+00 -5.2812810594737245E+00 -5.2800595568141233E+00 -5.2788344759921735E+00 -5.2776058190386994E+00 -5.2763735879894709E+00 -5.2751377848852146E+00 -5.2738984117716026E+00 -5.2726554706992568E+00 -5.2714089637237489E+00 -5.2701588929055987E+00 -5.2689052603102784E+00 -5.2676480680082074E+00 -5.2663873180747531E+00 -5.2651230125902364E+00 -5.2638551536399243E+00 -5.2625837433140346E+00 -5.2613087837077357E+00 -5.2600302769211433E+00 -5.2587482250593203E+00 -5.2574626302322880E+00 -5.2561734945550063E+00 -5.2548808201473909E+00 -5.2535846091343066E+00 -5.2522848636455652E+00 -5.2509815858159303E+00 -5.2496747777851134E+00 -5.2483644416977757E+00 -5.2470505797035294E+00 -5.2457331939569318E+00 -5.2444122866174956E+00 -5.2430878598496804E+00 -5.2417599158228931E+00 -5.2404284567114914E+00 -5.2390934846947852E+00 -5.2377550019570300E+00 -5.2364130106874320E+00 -5.2350675130801481E+00 -5.2337185113342821E+00 -5.2323660076538916E+00 -5.2310100042479766E+00 -5.2296505033304950E+00 -5.2282875071203465E+00 -5.2269210178413870E+00 -5.2255510377224157E+00 -5.2241775689971846E+00 -5.2228006139043952E+00 -5.2214201746876974E+00 -5.2200362535956915E+00 -5.2186488528819268E+00 -5.2172579748049017E+00 -5.2158636216280616E+00 -5.2144657956198088E+00 -5.2130644990534876E+00 -5.2116597342073945E+00 -5.2102515033647752E+00 -5.2088398088138250E+00 -5.2074246528476911E+00 -5.2060060377644630E+00 -5.2045839658671893E+00 -5.2031584394638593E+00 -5.2017294608674165E+00 -5.2002970323957536E+00 -5.1988611563717129E+00 -5.1974218351230830E+00 -5.1959790709826050E+00 -5.1945328662879691E+00 -5.1930832233818123E+00 -5.1916301446117270E+00 -5.1901736323302483E+00 -5.1887136888948646E+00 -5.1872503166680133E+00 -5.1857835180170797E+00 -5.1843132953144000E+00 -5.1828396509372601E+00 -5.1813625872678939E+00 -5.1798821066934861E+00 -5.1783982116061695E+00 -5.1769109044030275E+00 -5.1754201874860941E+00 -5.1739260632623481E+00 -5.1724285341437231E+00 -5.1709276025471000E+00 -5.1694232708943071E+00 -5.1679155416121265E+00 -5.1664044171322852E+00 -5.1648898998914632E+00 -5.1633719923312880E+00 -5.1618506968983358E+00 -5.1603260160441362E+00 -5.1587979522251635E+00 -5.1572665079028441E+00 -5.1557316855435520E+00 -5.1541934876186142E+00 -5.1526519166043014E+00 -5.1511069749818414E+00 -5.1495586652374037E+00 -5.1480069898621128E+00 -5.1464519513520406E+00 -5.1448935522082060E+00 -5.1433317949365804E+00 -5.1417666820480870E+00 -5.1401982160585922E+00 -5.1386263994889161E+00 -5.1370512348648276E+00 -5.1354727247170437E+00 -5.1338908715812330E+00 -5.1323056779980121E+00 -5.1307171465129464E+00 -5.1291252796765523E+00 -5.1275300800442949E+00 -5.1259315501765892E+00 -5.1243296926387973E+00 -5.1227245100012349E+00 -5.1211160048391635E+00 -5.1195041797327967E+00 -5.1178890372672958E+00 -5.1162705800327721E+00 -5.1146488106242867E+00 -5.1130237316418476E+00 -5.1113953456904166E+00 -5.1097636553799024E+00 -5.1081286633251635E+00 -5.1064903721460073E+00 -5.1048487844671913E+00 -5.1032039029184224E+00 -5.1015557301343559E+00 -5.0999042687545995E+00 -5.0982495214237060E+00 -5.0965914907911820E+00 -5.0949301795114810E+00 -5.0932655902440045E+00 -5.0915977256531084E+00 -5.0899265884080931E+00 -5.0882521811832113E+00 -5.0865745066576631E+00 -5.0848935675155991E+00 -5.0832093664461215E+00 -5.0815219061432773E+00 -5.0798311893060673E+00 -5.0781372186384388E+00 -5.0764399968492908E+00 -5.0747395266524693E+00 -5.0730358107667719E+00 -5.0713288519159443E+00 -5.0696186528286820E+00 -5.0679052162386311E+00 -5.0661885448843851E+00 -5.0644686415094879E+00 -5.0627455088624336E+00 -5.0610191496966657E+00 -5.0592895667705742E+00 -5.0575567628475024E+00 -5.0558207406957418E+00 -5.0540815030885309E+00 -5.0523390528040633E+00 -5.0505933926254754E+00 -5.0488445253408578E+00 -5.0470924537432484E+00 -5.0453371806306331E+00 -5.0435787088059527E+00 -5.0418170410770919E+00 -5.0400521802568878E+00 -5.0382841291631237E+00 -5.0365128906185372E+00 -5.0347384674508104E+00 -5.0329608624925806E+00 -5.0311800785814276E+00 -5.0293961185598857E+00 -5.0276089852754389E+00 -5.0258186815805148E+00 -5.0240252103324989E+00 -5.0222285743937185E+00 -5.0204287766314568E+00 -5.0186258199179390E+00 -5.0168197071303480E+00 -5.0150104411508085E+00 -5.0131980248664014E+00 -5.0113824611691529E+00 -5.0095637529560397E+00 -5.0077419031289878E+00 -5.0059169145948710E+00 -5.0040887902655173E+00 -5.0022575330576995E+00 -5.0004231458931425E+00 -4.9985856316985169E+00 -4.9967449934054491E+00 -4.9949012339505092E+00 -4.9930543562752181E+00 -4.9912043633260499E+00 -4.9893512580544215E+00 -4.9874950434167058E+00 -4.9856357223742194E+00 -4.9837732978932348E+00 -4.9819077729449663E+00 -4.9800391505055845E+00 -4.9781674335562061E+00 -4.9762926250828956E+00 -4.9744147280766731E+00 -4.9725337455334992E+00 -4.9706496804542937E+00 -4.9687625358449168E+00 -4.9668723147161851E+00 -4.9649790200838595E+00 -4.9630826549686553E+00 -4.9611832223962340E+00 -4.9592807253972060E+00 -4.9573751670071333E+00 -4.9554665502665252E+00 -4.9535548782208432E+00 -4.9516401539204962E+00 -4.9497223804208428E+00 -4.9478015607821915E+00 -4.9458776980697987E+00 -4.9439507953538717E+00 -4.9420208557095693E+00 -4.9400878822169965E+00 -4.9381518779612081E+00 -4.9362128460322081E+00 -4.9342707895249527E+00 -4.9323257115393453E+00 -4.9303776151802392E+00 -4.9284265035574357E+00 -4.9264723797856886E+00 -4.9245152469846980E+00 -4.9225551082791164E+00 -4.9205919667985425E+00 -4.9186258256775277E+00 -4.9166566880555713E+00 -4.9146845570771207E+00 -4.9127094358915757E+00 -4.9107313276532825E+00 -4.9087502355215396E+00 -4.9067661626605918E+00 -4.9047791122396367E+00 -4.9027890874328186E+00 -4.9007960914192328E+00 -4.8988001273829243E+00 -4.8968011985128861E+00 -4.8947993080030612E+00 -4.8927944590523422E+00 -4.8907866548645709E+00 -4.8887758986485403E+00 -4.8867621936179892E+00 -4.8847455429916105E+00 -4.8827259499930422E+00 -4.8807034178508735E+00 -4.8786779497986439E+00 -4.8766495490748420E+00 -4.8746182189229046E+00 -4.8725839625912188E+00 -4.8705467833331220E+00 -4.8685066844068965E+00 -4.8664636690757828E+00 -4.8644177406079629E+00 -4.8623689022765726E+00 -4.8603171573596926E+00 -4.8582625091403582E+00 -4.8562049609065525E+00 -4.8541445159512060E+00 -4.8520811775722024E+00 -4.8500149490723699E+00 -4.8479458337594910E+00 -4.8458738349462926E+00 -4.8437989559504580E+00 -4.8417212000946126E+00 -4.8396405707063366E+00 -4.8375570711181561E+00 -4.8354707046675474E+00 -4.8333814746969406E+00 -4.8312893845537070E+00 -4.8291944375901750E+00 -4.8270966371636188E+00 -4.8249959866362619E+00 -4.8228924893752785E+00 -4.8207861487527905E+00 -4.8186769681458728E+00 -4.8165649509365451E+00 -4.8144501005117810E+00 -4.8123324202634974E+00 -4.8102119135885708E+00 -4.8080885838888143E+00 -4.8059624345710024E+00 -4.8038334690468512E+00 -4.8017016907330277E+00 -4.7995671030511522E+00 -4.7974297094277896E+00 -4.7952895132944580E+00 -4.7931465180876209E+00 -4.7910007272486963E+00 -4.7888521442240464E+00 -4.7867007724649859E+00 -4.7845466154277805E+00 -4.7823896765736409E+00 -4.7802299593687314E+00 -4.7780674672841617E+00 -4.7759022037959955E+00 -4.7737341723852422E+00 -4.7715633765378636E+00 -4.7693898197447657E+00 -4.7672135055018119E+00 -4.7650344373098079E+00 -4.7628526186745139E+00 -4.7606680531066372E+00 -4.7584807441218322E+00 -4.7562906952407085E+00 -4.7540979099888174E+00 -4.7519023918966701E+00 -4.7497041444997166E+00 -4.7475031713383631E+00 -4.7452994759579630E+00 -4.7430930619088185E+00 -4.7408839327461827E+00 -4.7386720920302583E+00 -4.7364575433261953E+00 -4.7342402902040943E+00 -4.7320203362390059E+00 -4.7297976850109302E+00 -4.7275723401048158E+00 -4.7253443051105624E+00 -4.7231135836230163E+00 -4.7208801792419761E+00 -4.7186440955721869E+00 -4.7164053362233487E+00 -4.7141639048101034E+00 -4.7119198049520481E+00 -4.7096730402737279E+00 -4.7074236144046351E+00 -4.7051715309792135E+00 -4.7029167936368568E+00 -4.7006594060219085E+00 -4.6983993717836592E+00 -4.6961366945763485E+00 -4.6938713780591703E+00 -4.6916034258962629E+00 -4.6893328417567171E+00 -4.6870596293145708E+00 -4.6847837922488136E+00 -4.6825053342433813E+00 -4.6802242589871632E+00 -4.6779405701739956E+00 -4.6756542715026654E+00 -4.6733653666769079E+00 -4.6710738594054071E+00 -4.6687797534017994E+00 -4.6664830523846677E+00 -4.6641837600775462E+00 -4.6618818802089166E+00 -4.6595774165122119E+00 -4.6572703727258151E+00 -4.6549607525930554E+00 -4.6526485598622163E+00 -4.6503337982865238E+00 -4.6480164716241621E+00 -4.6456965836382560E+00 -4.6433741380968865E+00 -4.6410491387730808E+00 -4.6387215894448159E+00 -4.6363914938950206E+00 -4.6340588559115679E+00 -4.6317236792872851E+00 -4.6293859678199478E+00 -4.6270457253122803E+00 -4.6247029555719559E+00 -4.6223576624115985E+00 -4.6200098496487820E+00 -4.6176595211060247E+00 -4.6153066806108045E+00 -4.6129513319955384E+00 -4.6105934790975978E+00 -4.6082331257593028E+00 -4.6058702758279235E+00 -4.6035049331556772E+00 -4.6011371015997353E+00 -4.5987667850222138E+00 -4.5963939872901793E+00 -4.5940187122756511E+00 -4.5916409638555908E+00 -4.5892607459119192E+00 -4.5868780623314978E+00 -4.5844929170061430E+00 -4.5821053138326189E+00 -4.5797152567126362E+00 -4.5773227495528621E+00 -4.5749277962649053E+00 -4.5725304007653289E+00 -4.5701305669756422E+00 -4.5677282988223089E+00 -4.5653236002367370E+00 -4.5629164751552862E+00 -4.5605069275192678E+00 -4.5580949612749357E+00 -4.5556805803735019E+00 -4.5532637887711189E+00 -4.5508445904289001E+00 -4.5484229893128960E+00 -4.5459989893941142E+00 -4.5435725946485102E+00 -4.5411438090569858E+00 -4.5387126366053989E+00 -4.5362790812845502E+00 -4.5338431470901943E+00 -4.5314048380230307E+00 -4.5289641580887148E+00 -4.5265211112978427E+00 -4.5240757016659705E+00 -4.5216279332135940E+00 -4.5191778099661644E+00 -4.5167253359540807E+00 -4.5142705152126901E+00 -4.5118133517822931E+00 -4.5093538497081331E+00 -4.5068920130404093E+00 -4.5044278458342673E+00 -4.5019613521498023E+00 -4.4994925360520588E+00 -4.4970214016110317E+00 -4.4945479529016668E+00 -4.4920721940038542E+00 -4.4895941290024393E+00 -4.4871137619872101E+00 -4.4846310970529144E+00 -4.4821461382992380E+00 -4.4796588898308238E+00 -4.4771693557572627E+00 -4.4746775401930909E+00 -4.4721834472577999E+00 -4.4696870810758274E+00 -4.4671884457765616E+00 -4.4646875454943373E+00 -4.4621843843684443E+00 -4.4596789665431160E+00 -4.4571712961675392E+00 -4.4546613773958503E+00 -4.4521492143871297E+00 -4.4496348113054163E+00 -4.4471181723196871E+00 -4.4445993016038807E+00 -4.4420782033368758E+00 -4.4395548817025059E+00 -4.4370293408895511E+00 -4.4345015850917413E+00 -4.4319716185077569E+00 -4.4294394453412274E+00 -4.4269050698007328E+00 -4.4243684960997998E+00 -4.4218297284569053E+00 -4.4192887710954780E+00 -4.4167456282438939E+00 -4.4142003041354805E+00 -4.4116528030085096E+00 -4.4091031291062102E+00 -4.4065512866767538E+00 -4.4039972799732645E+00 -4.4014411132538172E+00 -4.3988827907814327E+00 -4.3963223168240848E+00 -4.3937596956546932E+00 -4.3911949315511309E+00 -4.3886280287962158E+00 -4.3860589916777206E+00 -4.3834878244883626E+00 -4.3809145315258107E+00 -4.3783391170926853E+00 -4.3757615855090419E+00 -4.3731819412219322E+00 -4.3706001887563977E+00 -4.3680163328523216E+00 -4.3654303785646089E+00 -4.3628423308154503E+00 -4.3602521938465566E+00 -4.3576599717847673E+00 -4.3550656695979937E+00 -4.3524692928668260E+00 -4.3498708464533200E+00 -4.3472703338002141E+00 -4.3446677584633351E+00 -4.3420631255312196E+00 -4.3394564405966785E+00 -4.3368477085053918E+00 -4.3342369333954505E+00 -4.3316241196493541E+00 -4.3290092723326037E+00 -4.3263923965151596E+00 -4.3237734964543986E+00 -4.3211525760528104E+00 -4.3185296398278732E+00 -4.3159046930499940E+00 -4.3132777408523184E+00 -4.3106487877389439E+00 -4.3080178381045293E+00 -4.3053848965489001E+00 -4.3027499677953633E+00 -4.3001130564247507E+00 -4.2974741667870200E+00 -4.2948333033054524E+00 -4.2921904708105520E+00 -4.2895456742534339E+00 -4.2868989186210031E+00 -4.2842502089263332E+00 -4.2815995497302506E+00 -4.2789469446548996E+00 -4.2762923974865883E+00 -4.2736359136912538E+00 -4.2709774993156282E+00 -4.2683171591792224E+00 -4.2656548968635839E+00 -4.2629907162699610E+00 -4.2603246223088158E+00 -4.2576566200548100E+00 -4.2549867145064155E+00 -4.2523149106164455E+00 -4.2496412129209773E+00 -4.2469656254128498E+00 -4.2442881523165088E+00 -4.2416087988143660E+00 -4.2389275702477205E+00 -4.2362444712474359E+00 -4.2335595059928464E+00 -4.2308726789313758E+00 -4.2281839949718236E+00 -4.2254934590084652E+00 -4.2228010756325887E+00 -4.2201068493593992E+00 -4.2174107849124729E+00 -4.2147128871890116E+00 -4.2120131609826972E+00 -4.2093116108417226E+00 -4.2066082412671699E+00 -4.2039030566435747E+00 -4.2011960613318786E+00 -4.1984872602314782E+00 -4.1957766588188630E+00 -4.1930642622339818E+00 -4.1903500745457132E+00 -4.1876340997162123E+00 -4.1849163424580924E+00 -4.1821968078777241E+00 -4.1794755009034388E+00 -4.1767524262100784E+00 -4.1740275884497784E+00 -4.1713009922459818E+00 -4.1685726422175531E+00 -4.1658425429719506E+00 -4.1631106991109403E+00 -4.1603771152963569E+00 -4.1576417962945253E+00 -4.1549047468954150E+00 -4.1521659719369248E+00 -4.1494254762642937E+00 -4.1466832645110854E+00 -4.1439393411242591E+00 -4.1411937106131873E+00 -4.1384463776434712E+00 -4.1356973469233331E+00 -4.1329466232785750E+00 -4.1301942115846622E+00 -4.1274401166128438E+00 -4.1246843430144873E+00 -4.1219268954598469E+00 -4.1191677786890981E+00 -4.1164069974506772E+00 -4.1136445564081301E+00 -4.1108804601778708E+00 -4.1081147133025695E+00 -4.1053473202147588E+00 -4.1025782854964810E+00 -4.0998076143768332E+00 -4.0970353121963337E+00 -4.0942613834559838E+00 -4.0914858320499370E+00 -4.0887086623876083E+00 -4.0859298798895871E+00 -4.0831494899163410E+00 -4.0803674968300214E+00 -4.0775839046708882E+00 -4.0747987179480347E+00 -4.0720119416127449E+00 -4.0692235806093091E+00 -4.0664336398140009E+00 -4.0636421240562033E+00 -4.0608490378627327E+00 -4.0580543856323024E+00 -4.0552581720498715E+00 -4.0524604021480366E+00 -4.0496610808441602E+00 -4.0468602125894702E+00 -4.0440578017840272E+00 -4.0412538532825177E+00 -4.0384483722086983E+00 -4.0356413633520063E+00 -4.0328328309679486E+00 -4.0300227793935735E+00 -4.0272112135275293E+00 -4.0243981384191612E+00 -4.0215835589719253E+00 -4.0187674799761233E+00 -4.0159499060945070E+00 -4.0131308417300797E+00 -4.0103102913185511E+00 -4.0074882596656929E+00 -4.0046647517098481E+00 -4.0018397722035273E+00 -3.9990133257128422E+00 -3.9961854168766666E+00 -3.9933560505449144E+00 -3.9905252315947428E+00 -3.9876929648102393E+00 -3.9848592549278488E+00 -3.9820241065213358E+00 -3.9791875239532195E+00 -3.9763495117702123E+00 -3.9735100752205428E+00 -3.9706692196313558E+00 -3.9678269493889142E+00 -3.9649832682886510E+00 -3.9621381808009897E+00 -3.9592916925408312E+00 -3.9564438089873342E+00 -3.9535945344238095E+00 -3.9507438728084976E+00 -3.9478918286263243E+00 -3.9450384067985427E+00 -3.9421836122552483E+00 -3.9393274499119748E+00 -3.9364699246706247E+00 -3.9336110413354981E+00 -3.9307508046608222E+00 -3.9278892190466612E+00 -3.9250262885155980E+00 -3.9221620174865595E+00 -3.9192964115696309E+00 -3.9164294764455181E+00 -3.9135612164889735E+00 -3.9106916354083086E+00 -3.9078207376082301E+00 -3.9049485284590788E+00 -3.9020750131942039E+00 -3.8992001962350007E+00 -3.8963240818548059E+00 -3.8934466748887204E+00 -3.8905679805511340E+00 -3.8876880036370811E+00 -3.8848067481758171E+00 -3.8819242182817053E+00 -3.8790404189057437E+00 -3.8761553552677066E+00 -3.8732690325191736E+00 -3.8703814557507092E+00 -3.8674926296707275E+00 -3.8646025580929790E+00 -3.8617112449043662E+00 -3.8588186953786190E+00 -3.8559249153503701E+00 -3.8530299096737832E+00 -3.8501336820873244E+00 -3.8472362366035151E+00 -3.8443375782637279E+00 -3.8414377122879908E+00 -3.8385366436727382E+00 -3.8356343772858184E+00 -3.8327309177062130E+00 -3.8298262690894100E+00 -3.8269204357595394E+00 -3.8240134228681284E+00 -3.8211052357332069E+00 -3.8181958789771198E+00 -3.8152853567213265E+00 -3.8123736733775107E+00 -3.8094608339288185E+00 -3.8065468433949197E+00 -3.8036317066241425E+00 -3.8007154283941986E+00 -3.7977980131951581E+00 -3.7948794652488052E+00 -3.7919597890701278E+00 -3.7890389899282799E+00 -3.7861170731164595E+00 -3.7831940432084856E+00 -3.7802699044588008E+00 -3.7773446613467554E+00 -3.7744183186245892E+00 -3.7714908810299832E+00 -3.7685623531893473E+00 -3.7656327397194009E+00 -3.7627020453475706E+00 -3.7597702748700534E+00 -3.7568374331554608E+00 -3.7539035251818165E+00 -3.7509685558039410E+00 -3.7480325292733681E+00 -3.7450954497218909E+00 -3.7421573219664448E+00 -3.7392181513515448E+00 -3.7362779428707391E+00 -3.7333367007710172E+00 -3.7303944292821050E+00 -3.7274511330578677E+00 -3.7245068169138049E+00 -3.7215614857177872E+00 -3.7186151443895170E+00 -3.7156677977797159E+00 -3.7127194505417225E+00 -3.7097701072741138E+00 -3.7068197723730516E+00 -3.7038684501478221E+00 -3.7009161452882475E+00 -3.6979628629730894E+00 -3.6950086082176488E+00 -3.6920533853294399E+00 -3.6890971985198644E+00 -3.6861400526739456E+00 -3.6831819530997141E+00 -3.6802229046380486E+00 -3.6772629113378206E+00 -3.6743019773571564E+00 -3.6713401077230263E+00 -3.6683773076961006E+00 -3.6654135820692777E+00 -3.6624489352516667E+00 -3.6594833716654427E+00 -3.6565168957819156E+00 -3.6535495121432109E+00 -3.6505812256888723E+00 -3.6476120414996900E+00 -3.6446419641801424E+00 -3.6416709978293089E+00 -3.6386991468210601E+00 -3.6357264163818068E+00 -3.6327528118119092E+00 -3.6297783376959414E+00 -3.6268029982517218E+00 -3.6238267978769003E+00 -3.6208497412183593E+00 -3.6178718329681523E+00 -3.6148930779127322E+00 -3.6119134808529334E+00 -3.6089330464544127E+00 -3.6059517792929112E+00 -3.6029696839809269E+00 -3.5999867651964896E+00 -3.5970030276062515E+00 -3.5940184757703064E+00 -3.5910331142329257E+00 -3.5880469478307271E+00 -3.5850599816551978E+00 -3.5820722204417264E+00 -3.5790836680731513E+00 -3.5760943284826059E+00 -3.5731042067760939E+00 -3.5701133085359880E+00 -3.5671216386729250E+00 -3.5641292013371739E+00 -3.5611360007372133E+00 -3.5581420413796772E+00 -3.5551473278606349E+00 -3.5521518650607216E+00 -3.5491556580142190E+00 -3.5461587114446553E+00 -3.5431610296184264E+00 -3.5401626168597073E+00 -3.5371634778696750E+00 -3.5341636174524744E+00 -3.5311630404605161E+00 -3.5281617517795385E+00 -3.5251597560160666E+00 -3.5221570572430383E+00 -3.5191536596189805E+00 -3.5161495680910444E+00 -3.5131447878577515E+00 -3.5101393236772380E+00 -3.5071331798977416E+00 -3.5041263608879687E+00 -3.5011188711016987E+00 -3.4981107150412036E+00 -3.4951018974562600E+00 -3.4920924232086707E+00 -3.4890822970907931E+00 -3.4860715238101521E+00 -3.4830601079794907E+00 -3.4800480539076912E+00 -3.4770353658728368E+00 -3.4740220484598550E+00 -3.4710081064363782E+00 -3.4679935445448855E+00 -3.4649783674830941E+00 -3.4619625799213085E+00 -3.4589461864148134E+00 -3.4559291914910677E+00 -3.4529115997023698E+00 -3.4498934156209278E+00 -3.4468746438287465E+00 -3.4438552889232539E+00 -3.4408353554938889E+00 -3.4378148480569601E+00 -3.4347937711136374E+00 -3.4317721293859473E+00 -3.4287499278143772E+00 -3.4257271711254207E+00 -3.4227038634454825E+00 -3.4196800088806873E+00 -3.4166556121548481E+00 -3.4136306782845112E+00 -3.4106052119778103E+00 -3.4075792175452526E+00 -3.4045526993658064E+00 -3.4015256621454952E+00 -3.3984981106431236E+00 -3.3954700493688081E+00 -3.3924414826792475E+00 -3.3894124151074378E+00 -3.3863828514801875E+00 -3.3833527965453700E+00 -3.3803222545337839E+00 -3.3772912295608899E+00 -3.3742597263320739E+00 -3.3712277500333387E+00 -3.3681953054653508E+00 -3.3651623965617019E+00 -3.3621290272849405E+00 -3.3590952024932190E+00 -3.3560609273795272E+00 -3.3530262066329408E+00 -3.3499910444104604E+00 -3.3469554450022336E+00 -3.3439194131453620E+00 -3.3408829535989732E+00 -3.3378460706012660E+00 -3.3348087681337120E+00 -3.3317710506699014E+00 -3.3287329233550005E+00 -3.3256943912190997E+00 -3.3226554586621990E+00 -3.3196161299497762E+00 -3.3165764095097692E+00 -3.3135363018797892E+00 -3.3104958115433174E+00 -3.3074549428823894E+00 -3.3044137003257439E+00 -3.3013720885820383E+00 -3.2983301124305382E+00 -3.2952877762790411E+00 -3.2922450842136741E+00 -3.2892020405793589E+00 -3.2861586503399374E+00 -3.2831149184718167E+00 -3.2800708494201034E+00 -3.2770264474088755E+00 -3.2739817166959830E+00 -3.2709366615777422E+00 -3.2678912864757179E+00 -3.2648455961823943E+00 -3.2617995955154178E+00 -3.2587532888384745E+00 -3.2557066802731573E+00 -3.2526597743050103E+00 -3.2496125759494037E+00 -3.2465650900297671E+00 -3.2435173204062875E+00 -3.2404692707676324E+00 -3.2374209457830694E+00 -3.2343723508204985E+00 -3.2313234907033461E+00 -3.2282743691979761E+00 -3.2252249901169630E+00 -3.2221753581579069E+00 -3.2191254783092300E+00 -3.2160753552993278E+00 -3.2130249936153392E+00 -3.2099743975360195E+00 -3.2069235708437684E+00 -3.2038725174248106E+00 -3.2008212424843712E+00 -3.1977697517847741E+00 -3.1947180498225523E+00 -3.1916661395794317E+00 -3.1886140244731020E+00 -3.1855617096381348E+00 -3.1825092004938935E+00 -3.1794565017480445E+00 -3.1764036176899464E+00 -3.1733505525765189E+00 -3.1702973106214642E+00 -3.1672438960333231E+00 -3.1641903130063049E+00 -3.1611365657678911E+00 -3.1580826590689126E+00 -3.1550285980571009E+00 -3.1519743874374089E+00 -3.1489200310013552E+00 -3.1458655325519778E+00 -3.1428108965958725E+00 -3.1397561278883237E+00 -3.1367012309582627E+00 -3.1336462101113920E+00 -3.1305910696575610E+00 -3.1275358139383678E+00 -3.1244804473259471E+00 -3.1214249743801177E+00 -3.1183693997474968E+00 -3.1153137278884815E+00 -3.1122579630253808E+00 -3.1092021093563713E+00 -3.1061461710428495E+00 -3.1030901522757834E+00 -3.1000340576479366E+00 -3.0969778919997673E+00 -3.0939216597773336E+00 -3.0908653647695625E+00 -3.0878090109132499E+00 -3.0847526031229995E+00 -3.0816961465514807E+00 -3.0786396455078955E+00 -3.0755831036182677E+00 -3.0725265247895073E+00 -3.0694699135717673E+00 -3.0664132745878945E+00 -3.0633566123804092E+00 -3.0602999314526533E+00 -3.0572432360725106E+00 -3.0541865302612163E+00 -3.0511298181666078E+00 -3.0480731043239695E+00 -3.0450163933201617E+00 -3.0419596895803815E+00 -3.0389029974451511E+00 -3.0358463211341462E+00 -3.0327896647036208E+00 -3.0297330323227269E+00 -3.0266764286248393E+00 -3.0236198583139444E+00 -3.0205633255930979E+00 -3.0175068343329774E+00 -3.0144503885657139E+00 -3.0113939926157713E+00 -3.0083376509081114E+00 -3.0052813682174100E+00 -3.0022251493794552E+00 -2.9991689983108687E+00 -2.9961129181367721E+00 -2.9930569127040068E+00 -2.9900009875734503E+00 -2.9869451483003053E+00 -2.9838893987442772E+00 -2.9808337420818662E+00 -2.9777781822107130E+00 -2.9747227238349634E+00 -2.9716673715870550E+00 -2.9686121297478616E+00 -2.9655570025186107E+00 -2.9625019939602559E+00 -2.9594471080632192E+00 -2.9563923490882269E+00 -2.9533377216854477E+00 -2.9502832303839259E+00 -2.9472288790909094E+00 -2.9441746716183643E+00 -2.9411206125924849E+00 -2.9380667072127693E+00 -2.9350129598749812E+00 -2.9319593734451299E+00 -2.9289059509921205E+00 -2.9258526975992112E+00 -2.9227996189702585E+00 -2.9197467195414584E+00 -2.9166940025833932E+00 -2.9136414717271406E+00 -2.9105891315929648E+00 -2.9075369868489300E+00 -2.9044850414016663E+00 -2.9014332988413463E+00 -2.8983817635048204E+00 -2.8953304406163052E+00 -2.8922793349639524E+00 -2.8892284497414447E+00 -2.8861777879549102E+00 -2.8831273539955071E+00 -2.8800771530576768E+00 -2.8770271898523538E+00 -2.8739774683313346E+00 -2.8709279923502957E+00 -2.8678787656204450E+00 -2.8648297918672534E+00 -2.8617810755826643E+00 -2.8587326218375990E+00 -2.8556844352858297E+00 -2.8526365197161168E+00 -2.8495888788389352E+00 -2.8465415165004768E+00 -2.8434944366103365E+00 -2.8404476433651773E+00 -2.8374011412426605E+00 -2.8343549346989785E+00 -2.8313090280991045E+00 -2.8282634257315764E+00 -2.8252181313798843E+00 -2.8221731485982193E+00 -2.8191284813580029E+00 -2.8160841341589875E+00 -2.8130401114002557E+00 -2.8099964170051370E+00 -2.8069530548511890E+00 -2.8039100294462238E+00 -2.8008673456820721E+00 -2.7978250077462943E+00 -2.7947830186635256E+00 -2.7917413816433974E+00 -2.7887001012606980E+00 -2.7856591824463970E+00 -2.7826186294117674E+00 -2.7795784457888151E+00 -2.7765386354841231E+00 -2.7734992030235390E+00 -2.7704601529159212E+00 -2.7674214890501738E+00 -2.7643832150835452E+00 -2.7613453348788708E+00 -2.7583078525136608E+00 -2.7552707720852063E+00 -2.7522340977147537E+00 -2.7491978335467193E+00 -2.7461619838761337E+00 -2.7431265530664213E+00 -2.7400915450768459E+00 -2.7370569633217414E+00 -2.7340228114145577E+00 -2.7309890938560355E+00 -2.7279558153070664E+00 -2.7249229798267387E+00 -2.7218905910765860E+00 -2.7188586528770804E+00 -2.7158271693371310E+00 -2.7127961445899973E+00 -2.7097655827383420E+00 -2.7067354878684071E+00 -2.7037058639219578E+00 -2.7006767147172801E+00 -2.6976480441740862E+00 -2.6946198564503678E+00 -2.6915921557019966E+00 -2.6885649458356888E+00 -2.6855382306618143E+00 -2.6825120141659506E+00 -2.6794863005280343E+00 -2.6764610938703131E+00 -2.6734363981066362E+00 -2.6704122171183253E+00 -2.6673885548361076E+00 -2.6643654152185521E+00 -2.6613428022281358E+00 -2.6583207198317429E+00 -2.6552991719822576E+00 -2.6522781625696124E+00 -2.6492576954854257E+00 -2.6462377748370889E+00 -2.6432184048834797E+00 -2.6401995896861137E+00 -2.6371813329316964E+00 -2.6341636383240443E+00 -2.6311465098740814E+00 -2.6281299516867751E+00 -2.6251139676609774E+00 -2.6220985615073542E+00 -2.6190837370305586E+00 -2.6160694982791233E+00 -2.6130558493160665E+00 -2.6100427940330690E+00 -2.6070303362451086E+00 -2.6040184797231065E+00 -2.6010072281861536E+00 -2.5979965854927896E+00 -2.5949865559589074E+00 -2.5919771439357633E+00 -2.5889683531819494E+00 -2.5859601871174664E+00 -2.5829526494791897E+00 -2.5799457444930214E+00 -2.5769394763106033E+00 -2.5739338485781387E+00 -2.5709288648264788E+00 -2.5679245288828736E+00 -2.5649208447971588E+00 -2.5619178164452738E+00 -2.5589154473453752E+00 -2.5559137410833013E+00 -2.5529127018782183E+00 -2.5499123341611063E+00 -2.5469126419724515E+00 -2.5439136289722484E+00 -2.5409152987527146E+00 -2.5379176547680466E+00 -2.5349207005177696E+00 -2.5319244400287486E+00 -2.5289288775716687E+00 -2.5259340171350009E+00 -2.5229398623505044E+00 -2.5199464168664734E+00 -2.5169536844638656E+00 -2.5139616689476281E+00 -2.5109703740577771E+00 -2.5079798034960161E+00 -2.5049899610582420E+00 -2.5020008506934812E+00 -2.4990124763528350E+00 -2.4960248419260953E+00 -2.4930379512627661E+00 -2.4900518078364815E+00 -2.4870664148215442E+00 -2.4840817757623688E+00 -2.4810978950048836E+00 -2.4781147768869007E+00 -2.4751324250459534E+00 -2.4721508428607617E+00 -2.4691700339761513E+00 -2.4661900023130259E+00 -2.4632107517283659E+00 -2.4602322858619683E+00 -2.4572546083129776E+00 -2.4542777226464194E+00 -2.4513016324162398E+00 -2.4483263414085497E+00 -2.4453518537194716E+00 -2.4423781733722905E+00 -2.4394053040337225E+00 -2.4364332492843666E+00 -2.4334620126567277E+00 -2.4304915976521517E+00 -2.4275220077894493E+00 -2.4245532466177808E+00 -2.4215853177869415E+00 -2.4186182254296402E+00 -2.4156519737926763E+00 -2.4126865664610153E+00 -2.4097220064554445E+00 -2.4067582970771988E+00 -2.4037954423031098E+00 -2.4008334461605405E+00 -2.3978723123820416E+00 -2.3949120445782350E+00 -2.3919526463367164E+00 -2.3889941212199535E+00 -2.3860364727539909E+00 -2.3830797043572960E+00 -2.3801238194758043E+00 -2.3771688219885472E+00 -2.3742147160018110E+00 -2.3712615052291652E+00 -2.3683091928212869E+00 -2.3653577820217784E+00 -2.3624072766158690E+00 -2.3594576805021878E+00 -2.3565089972759186E+00 -2.3535612303206643E+00 -2.3506143831919522E+00 -2.3476684597703734E+00 -2.3447234638807997E+00 -2.3417793988544120E+00 -2.3388362678783197E+00 -2.3358940745364745E+00 -2.3329528227733780E+00 -2.3300125163589267E+00 -2.3270731586060176E+00 -2.3241347527941301E+00 -2.3211973024482950E+00 -2.3182608112029985E+00 -2.3153252827010675E+00 -2.3123907205943053E+00 -2.3094571284442686E+00 -2.3065245095182783E+00 -2.3035928670801007E+00 -2.3006622049442367E+00 -2.2977325272338955E+00 -2.2948038374896087E+00 -2.2918761383619559E+00 -2.2889494327284909E+00 -2.2860237247604465E+00 -2.2830990189038247E+00 -2.2801753185388498E+00 -2.2772526262508967E+00 -2.2743309451238436E+00 -2.2714102792627515E+00 -2.2684906327482142E+00 -2.2655720088218749E+00 -2.2626544104464235E+00 -2.2597378410425502E+00 -2.2568223044741731E+00 -2.2539078044327492E+00 -2.2509943441132689E+00 -2.2480819266667718E+00 -2.2451705555183148E+00 -2.2422602342214781E+00 -2.2393509662766937E+00 -2.2364427551168249E+00 -2.2335356041869927E+00 -2.2306295169868187E+00 -2.2277244970183174E+00 -2.2248205476727669E+00 -2.2219176722726566E+00 -2.2190158740807195E+00 -2.2161151562642178E+00 -2.2132155221055978E+00 -2.2103169754566054E+00 -2.2074195202822242E+00 -2.2045231597264885E+00 -2.2016278962816536E+00 -2.1987337329908669E+00 -2.1958406740960164E+00 -2.1929487237982723E+00 -2.1900578850942694E+00 -2.1871681605430937E+00 -2.1842795532959025E+00 -2.1813920671142619E+00 -2.1785057056511099E+00 -2.1756204721779291E+00 -2.1727363699181548E+00 -2.1698534022399567E+00 -2.1669715725815233E+00 -2.1640908842397821E+00 -2.1612113403229056E+00 -2.1583329439814212E+00 -2.1554556985692224E+00 -2.1525796074875601E+00 -2.1497046741335102E+00 -2.1468309019005942E+00 -2.1439582940907700E+00 -2.1410868538477357E+00 -2.1382165843300198E+00 -2.1353474888448689E+00 -2.1324795707531665E+00 -2.1296128335379931E+00 -2.1267472807849335E+00 -2.1238829157577928E+00 -2.1210197409872418E+00 -2.1181577590789216E+00 -2.1152969738110152E+00 -2.1124373894131949E+00 -2.1095790092725117E+00 -2.1067218358513200E+00 -2.1038658718425762E+00 -2.1010111207656648E+00 -2.0981575862552502E+00 -2.0953052715910481E+00 -2.0924541798638616E+00 -2.0896043142547360E+00 -2.0867556780747343E+00 -2.0839082745883486E+00 -2.0810621068335120E+00 -2.0782171778037517E+00 -2.0753734906422592E+00 -2.0725310485976758E+00 -2.0696898549670970E+00 -2.0668499131320233E+00 -2.0640112263823944E+00 -2.0611737974682023E+00 -2.0583376289972541E+00 -2.0555027242903221E+00 -2.0526690873118141E+00 -2.0498367216843558E+00 -2.0470056301499593E+00 -2.0441758153762772E+00 -2.0413472804303390E+00 -2.0385200285510616E+00 -2.0356940628577984E+00 -2.0328693863295335E+00 -2.0300460020343087E+00 -2.0272239133486174E+00 -2.0244031236681934E+00 -2.0215836359615666E+00 -2.0187654529564947E+00 -2.0159485776328117E+00 -2.0131330133544361E+00 -2.0103187634807571E+00 -2.0075058312135390E+00 -2.0046942196902031E+00 -2.0018839317244628E+00 -1.9990749698909833E+00 -1.9962673370323354E+00 -1.9934610365274650E+00 -1.9906560717858623E+00 -1.9878524460310518E+00 -1.9850501624070664E+00 -1.9822492237639597E+00 -1.9794496326695523E+00 -1.9766513919191875E+00 -1.9738545049237164E+00 -1.9710589751456238E+00 -1.9682648056823595E+00 -1.9654719994558749E+00 -1.9626805592347465E+00 -1.9598904875983933E+00 -1.9571017873367855E+00 -1.9543144620011248E+00 -1.9515285152201816E+00 -1.9487439496896191E+00 -1.9459607675429014E+00 -1.9431789715395908E+00 -1.9403985654579377E+00 -1.9376195529300853E+00 -1.9348419364928817E+00 -1.9320657184087191E+00 -1.9292909015578181E+00 -1.9265174893098245E+00 -1.9237454848887792E+00 -1.9209748911848294E+00 -1.9182057110396646E+00 -1.9154379472532010E+00 -1.9126716026149766E+00 -1.9099066800430649E+00 -1.9071431825870948E+00 -1.9043811132494957E+00 -1.9016204748851639E+00 -1.8988612703320531E+00 -1.8961035024959041E+00 -1.8933471743163193E+00 -1.8905922887192705E+00 -1.8878388486122877E+00 -1.8850868568754215E+00 -1.8823363162914020E+00 -1.8795872296252991E+00 -1.8768395996956344E+00 -1.8740934293568976E+00 -1.8713487215390803E+00 -1.8686054793001468E+00 -1.8658637056419713E+00 -1.8631234032263657E+00 -1.8603845746235237E+00 -1.8576472226263072E+00 -1.8549113502154089E+00 -1.8521769603127289E+00 -1.8494440556948926E+00 -1.8467126391325823E+00 -1.8439827134868392E+00 -1.8412542816501309E+00 -1.8385273463634189E+00 -1.8358019102025585E+00 -1.8330779758411684E+00 -1.8303555462664296E+00 -1.8276346244952912E+00 -1.8249152132869364E+00 -1.8221973152632323E+00 -1.8194809330743893E+00 -1.8167660694122469E+00 -1.8140527270083655E+00 -1.8113409087383414E+00 -1.8086306175036995E+00 -1.8059218560787273E+00 -1.8032146271488818E+00 -1.8005089333639610E+00 -1.7978047773117867E+00 -1.7951021616201712E+00 -1.7924010891634348E+00 -1.7897015628841193E+00 -1.7870035854703639E+00 -1.7843071593819504E+00 -1.7816122871776463E+00 -1.7789189716725553E+00 -1.7762272157009784E+00 -1.7735370219643671E+00 -1.7708483931061614E+00 -1.7681613317667317E+00 -1.7654758405831732E+00 -1.7627919222046347E+00 -1.7601095793188897E+00 -1.7574288146131998E+00 -1.7547496306931853E+00 -1.7520720301187811E+00 -1.7493960155001420E+00 -1.7467215895234645E+00 -1.7440487548748909E+00 -1.7413775142134686E+00 -1.7387078701853695E+00 -1.7360398253552072E+00 -1.7333733822276780E+00 -1.7307085433661804E+00 -1.7280453114513052E+00 -1.7253836891578922E+00 -1.7227236790504907E+00 -1.7200652836575743E+00 -1.7174085055693866E+00 -1.7147533474351799E+00 -1.7120998118444755E+00 -1.7094479012277042E+00 -1.7067976180161839E+00 -1.7041489648429184E+00 -1.7015019444310768E+00 -1.6988565593649567E+00 -1.6962128120568853E+00 -1.6935707049600803E+00 -1.6909302407032276E+00 -1.6882914219321314E+00 -1.6856542510748735E+00 -1.6830187304291973E+00 -1.6803848624421718E+00 -1.6777526498023250E+00 -1.6751220951752150E+00 -1.6724932010229234E+00 -1.6698659697525622E+00 -1.6672404038180684E+00 -1.6646165057102080E+00 -1.6619942779070762E+00 -1.6593737228583658E+00 -1.6567548430201049E+00 -1.6541376409092783E+00 -1.6515221190611058E+00 -1.6489082798963546E+00 -1.6462961257193249E+00 -1.6436856588855411E+00 -1.6410768819056063E+00 -1.6384697973038225E+00 -1.6358644074989679E+00 -1.6332607148580034E+00 -1.6306587217821735E+00 -1.6280584307182728E+00 -1.6254598441021431E+00 -1.6228629643185914E+00 -1.6202677937381942E+00 -1.6176743347027447E+00 -1.6150825895360952E+00 -1.6124925606261804E+00 -1.6099042504706331E+00 -1.6073176615449944E+00 -1.6047327961646496E+00 -1.6021496565975821E+00 -1.5995682451407691E+00 -1.5969885641156520E+00 -1.5944106158745743E+00 -1.5918344028371971E+00 -1.5892599274114332E+00 -1.5866871918684573E+00 -1.5841161984272547E+00 -1.5815469493982275E+00 -1.5789794471909444E+00 -1.5764136941902669E+00 -1.5738496926942283E+00 -1.5712874449763234E+00 -1.5687269532332329E+00 -1.5661682196237312E+00 -1.5636112464501302E+00 -1.5610560362160855E+00 -1.5585025913531807E+00 -1.5559509139517202E+00 -1.5534010060358989E+00 -1.5508528698588557E+00 -1.5483065078309490E+00 -1.5457619222643346E+00 -1.5432191152873691E+00 -1.5406780890532497E+00 -1.5381388459494718E+00 -1.5356013884249133E+00 -1.5330657186385961E+00 -1.5305318384910593E+00 -1.5279997500498956E+00 -1.5254694558022244E+00 -1.5229409582344646E+00 -1.5204142593941155E+00 -1.5178893611461595E+00 -1.5153662656008851E+00 -1.5128449751521849E+00 -1.5103254921384073E+00 -1.5078078186737798E+00 -1.5052919568379273E+00 -1.5027779088059603E+00 -1.5002656768055560E+00 -1.4977552629838424E+00 -1.4952466693672308E+00 -1.4927398980084288E+00 -1.4902349511136910E+00 -1.4877318309231311E+00 -1.4852305395875398E+00 -1.4827310791916966E+00 -1.4802334518057176E+00 -1.4777376594746863E+00 -1.4752437042565747E+00 -1.4727515883004090E+00 -1.4702613137833918E+00 -1.4677728828074890E+00 -1.4652862974031275E+00 -1.4628015596234527E+00 -1.4603186715873213E+00 -1.4578376354099494E+00 -1.4553584531018982E+00 -1.4528811266261830E+00 -1.4504056579893174E+00 -1.4479320492515946E+00 -1.4454603025000092E+00 -1.4429904199017207E+00 -1.4405224036182616E+00 -1.4380562555734251E+00 -1.4355919775490453E+00 -1.4331295714679466E+00 -1.4306690394802346E+00 -1.4282103837327498E+00 -1.4257536062675495E+00 -1.4232987090919720E+00 -1.4208456941404057E+00 -1.4183945632901713E+00 -1.4159453184600523E+00 -1.4134979616584056E+00 -1.4110524948960819E+00 -1.4086089201338738E+00 -1.4061672393147491E+00 -1.4037274544133787E+00 -1.4012895674364847E+00 -1.3988535803450730E+00 -1.3964194949726150E+00 -1.3939873131490994E+00 -1.3915570368583032E+00 -1.3891286681573032E+00 -1.3867022089998362E+00 -1.3842776612042036E+00 -1.3818550265975362E+00 -1.3794343070737145E+00 -1.3770155045427857E+00 -1.3745986209315286E+00 -1.3721836581771563E+00 -1.3697706182035854E+00 -1.3673595029123453E+00 -1.3649503141676689E+00 -1.3625430536650920E+00 -1.3601377230635976E+00 -1.3577343242790498E+00 -1.3553328594409437E+00 -1.3529333305376228E+00 -1.3505357392315409E+00 -1.3481400871765690E+00 -1.3457463762600335E+00 -1.3433546084579031E+00 -1.3409647856117306E+00 -1.3385769094181588E+00 -1.3361909815987607E+00 -1.3338070039701921E+00 -1.3314249783585261E+00 -1.3290449065237349E+00 -1.3266667901921418E+00 -1.3242906311649545E+00 -1.3219164313481755E+00 -1.3195441926065063E+00 -1.3171739166151915E+00 -1.3148056050113621E+00 -1.3124392595413061E+00 -1.3100748820256782E+00 -1.3077124742438875E+00 -1.3053520378988139E+00 -1.3029935746882391E+00 -1.3006370863281593E+00 -1.2982825745427977E+00 -1.2959300411086403E+00 -1.2935794878481641E+00 -1.2912309164892919E+00 -1.2888843285336855E+00 -1.2865397254916802E+00 -1.2841971091707693E+00 -1.2818564814987632E+00 -1.2795178441831274E+00 -1.2771811986784836E+00 -1.2748465465050460E+00 -1.2725138894337018E+00 -1.2701832292664064E+00 -1.2678545676362820E+00 -1.2655279060827598E+00 -1.2632032462483858E+00 -1.2608805899303608E+00 -1.2585599388669659E+00 -1.2562412944997541E+00 -1.2539246582141341E+00 -1.2516100317034862E+00 -1.2492974168846545E+00 -1.2469868154635440E+00 -1.2446782287307017E+00 -1.2423716580041406E+00 -1.2400671050260181E+00 -1.2377645716740597E+00 -1.2354640595752011E+00 -1.2331655701193298E+00 -1.2308691047745339E+00 -1.2285746652315617E+00 -1.2262822531814410E+00 -1.2239918700573587E+00 -1.2217035171799635E+00 -1.2194171960999289E+00 -1.2171329086493288E+00 -1.2148506565372121E+00 -1.2125704410037730E+00 -1.2102922632276698E+00 -1.2080161247858534E+00 -1.2057420274922597E+00 -1.2034699730121703E+00 -1.2011999627716503E+00 -1.1989319981786823E+00 -1.1966660806578200E+00 -1.1944022116417061E+00 -1.1921403926254872E+00 -1.1898806251524032E+00 -1.1876229107005538E+00 -1.1853672506124833E+00 -1.1831136462530338E+00 -1.1808620992272771E+00 -1.1786126112190745E+00 -1.1763651836667992E+00 -1.1741198177618861E+00 -1.1718765147682355E+00 -1.1696352761771305E+00 -1.1673961035141234E+00 -1.1651589982788273E+00 -1.1629239619545360E+00 -1.1606909959052791E+00 -1.1584601013407256E+00 -1.1562312795368026E+00 -1.1540045320481915E+00 -1.1517798604692988E+00 -1.1495572661357787E+00 -1.1473367502183998E+00 -1.1451183139987089E+00 -1.1429019589498650E+00 -1.1406876865355884E+00 -1.1384754980887060E+00 -1.1362653949041488E+00 -1.1340573783153676E+00 -1.1318514496874221E+00 -1.1296476103545527E+00 -1.1274458615824110E+00 -1.1252462046332341E+00 -1.1230486408117342E+00 -1.1208531714411238E+00 -1.1186597979000377E+00 -1.1164685216263597E+00 -1.1142793439773280E+00 -1.1120922660697037E+00 -1.1099072889956061E+00 -1.1077244140222839E+00 -1.1055436425082403E+00 -1.1033649757998192E+00 -1.1011884152258407E+00 -1.0990139620669621E+00 -1.0968416174252638E+00 -1.0946713823777208E+00 -1.0925032582400069E+00 -1.0903372464888634E+00 -1.0881733484417371E+00 -1.0860115651256124E+00 -1.0838518975813891E+00 -1.0816943470839735E+00 -1.0795389149783157E+00 -1.0773856025174178E+00 -1.0752344108728833E+00 -1.0730853412055976E+00 -1.0709383946594055E+00 -1.0687935723824904E+00 -1.0666508755768513E+00 -1.0645103054649043E+00 -1.0623718632099073E+00 -1.0602355499078335E+00 -1.0581013666600445E+00 -1.0559693145985323E+00 -1.0538393948681788E+00 -1.0517116086895348E+00 -1.0495859573230863E+00 -1.0474624419234513E+00 -1.0453410634893241E+00 -1.0432218230377450E+00 -1.0411047217176981E+00 -1.0389897607059142E+00 -1.0368769411002337E+00 -1.0347662639409341E+00 -1.0326577302898596E+00 -1.0305513412537393E+00 -1.0284470979355194E+00 -1.0263450013937772E+00 -1.0242450526730364E+00 -1.0221472528615083E+00 -1.0200516030882629E+00 -1.0179581044308617E+00 -1.0158667578352827E+00 -1.0137775642456222E+00 -1.0116905247532348E+00 -1.0096056405140998E+00 -1.0075229126118410E+00 -1.0054423420422223E+00 -1.0033639297829615E+00 -1.0012876767720638E+00 -9.9921358394412818E-01 -9.9714165229526974E-01 -9.9507188285794768E-01 -9.9300427666986768E-01 -9.9093883477689670E-01 -9.8887555819865103E-01 -9.8681444783838890E-01 -9.8475550457266492E-01 -9.8269872937939862E-01 -9.8064412331432826E-01 -9.7859168737181568E-01 -9.7654142241796382E-01 -9.7449332931754773E-01 -9.7244740902759041E-01 -9.7040366253685162E-01 -9.6836209079410551E-01 -9.6632269470807242E-01 -9.6428547518066121E-01 -9.6225043310237612E-01 -9.6021756936406266E-01 -9.5818688488321635E-01 -9.5615838058890545E-01 -9.5413205738018025E-01 -9.5210791611765810E-01 -9.5008595766478598E-01 -9.4806618290763867E-01 -9.4604859273242448E-01 -9.4403318798018632E-01 -9.4201996946299915E-01 -9.4000893801662899E-01 -9.3800009451819355E-01 -9.3599343984454475E-01 -9.3398897485719556E-01 -9.3198670040934117E-01 -9.2998661730750487E-01 -9.2798872631956686E-01 -9.2599302823205931E-01 -9.2399952387644269E-01 -9.2200821408740830E-01 -9.2001909968891937E-01 -9.1803218149774113E-01 -9.1604746027615713E-01 -9.1406493672865030E-01 -9.1208461159594389E-01 -9.1010648573395425E-01 -9.0813056000370873E-01 -9.0615683513783429E-01 -9.0418531180264039E-01 -9.0221599072883008E-01 -9.0024887273692222E-01 -8.9828395862436783E-01 -8.9632124907863431E-01 -8.9436074476380656E-01 -8.9240244639536526E-01 -8.9044635472315037E-01 -8.8849247049045443E-01 -8.8654079442886313E-01 -8.8459132726407164E-01 -8.8264406970316667E-01 -8.8069902244409959E-01 -8.7875618614482598E-01 -8.7681556142811112E-01 -8.7487714894980984E-01 -8.7294094944776057E-01 -8.7100696365590891E-01 -8.6907519220731466E-01 -8.6714563569270031E-01 -8.6521829474595813E-01 -8.6329317005022943E-01 -8.6137026227961921E-01 -8.5944957207514427E-01 -8.5753110006970223E-01 -8.5561484689024669E-01 -8.5370081315953006E-01 -8.5178899949044973E-01 -8.4987940648225313E-01 -8.4797203473068983E-01 -8.4606688482610493E-01 -8.4416395735802341E-01 -8.4226325293871407E-01 -8.4036477219625028E-01 -8.3846851573423686E-01 -8.3657448411045954E-01 -8.3468267787027184E-01 -8.3279309752506392E-01 -8.3090574357756397E-01 -8.2902061661360482E-01 -8.2713771729639418E-01 -8.2525704622854179E-01 -8.2337860385622264E-01 -8.2150239061683927E-01 -8.1962840707169493E-01 -8.1775665383545915E-01 -8.1588713145070269E-01 -8.1401984037312780E-01 -8.1215478106318117E-01 -8.1029195401781873E-01 -8.0843135974199976E-01 -8.0657299875757416E-01 -8.0471687159525462E-01 -8.0286297875282919E-01 -8.0101132067748559E-01 -7.9916189781223801E-01 -7.9731471060627235E-01 -7.9546975951060139E-01 -7.9362704499472769E-01 -7.9178656754189358E-01 -7.8994832761488021E-01 -7.8811232563586608E-01 -7.8627856202229685E-01 -7.8444703720009745E-01 -7.8261775159723834E-01 -7.8079070564003006E-01 -7.7896589975312269E-01 -7.7714333435545102E-01 -7.7532300985358005E-01 -7.7350492664798531E-01 -7.7168908511632517E-01 -7.6987548562484209E-01 -7.6806412856007289E-01 -7.6625501433515431E-01 -7.6444814334867262E-01 -7.6264351594527147E-01 -7.6084113245937213E-01 -7.5904099325943608E-01 -7.5724309873450635E-01 -7.5544744924742591E-01 -7.5365404511806600E-01 -7.5186288666336520E-01 -7.5007397421158128E-01 -7.4828730809278798E-01 -7.4650288863060110E-01 -7.4472071614302260E-01 -7.4294079095075372E-01 -7.4116311338267182E-01 -7.3938768376166675E-01 -7.3761450237352066E-01 -7.3584356948830876E-01 -7.3407488537599119E-01 -7.3230845030654712E-01 -7.3054426455731680E-01 -7.2878232842983948E-01 -7.2702264222410973E-01 -7.2526520619994628E-01 -7.2351002059551928E-01 -7.2175708565161689E-01 -7.2000640161349694E-01 -7.1825796872797332E-01 -7.1651178725126530E-01 -7.1476785743682159E-01 -7.1302617949152125E-01 -7.1128675359056570E-01 -7.0954957994023338E-01 -7.0781465880432182E-01 -7.0608199043564734E-01 -7.0435157500720669E-01 -7.0262341266725825E-01 -7.0089750359913405E-01 -6.9917384801648719E-01 -6.9745244611268253E-01 -6.9573329803401118E-01 -6.9401640392879382E-01 -6.9230176401485910E-01 -6.9058937853561286E-01 -6.8887924765334496E-01 -6.8717137143918305E-01 -6.8546574997696064E-01 -6.8376238340817286E-01 -6.8206127188477517E-01 -6.8036241556614918E-01 -6.7866581461456088E-01 -6.7697146917037709E-01 -6.7527937934291415E-01 -6.7358954523576819E-01 -6.7190196694446891E-01 -6.7021664456055574E-01 -6.6853357816702663E-01 -6.6685276784036751E-01 -6.6517421367336405E-01 -6.6349791579153428E-01 -6.6182387430857714E-01 -6.6015208926049995E-01 -6.5848256065793265E-01 -6.5681528856038751E-01 -6.5515027307258866E-01 -6.5348751427517804E-01 -6.5182701218746419E-01 -6.5016876682326208E-01 -6.4851277823567399E-01 -6.4685904649359149E-01 -6.4520757163415177E-01 -6.4355835365672720E-01 -6.4191139255805518E-01 -6.4026668833769340E-01 -6.3862424099646697E-01 -6.3698405055661911E-01 -6.3534611705183897E-01 -6.3371044049006697E-01 -6.3207702084013206E-01 -6.3044585806817766E-01 -6.2881695214936306E-01 -6.2719030305983015E-01 -6.2556591077293355E-01 -6.2394377525939382E-01 -6.2232389648463193E-01 -6.2070627440542681E-01 -6.1909090896949348E-01 -6.1747780008548603E-01 -6.1586694764936156E-01 -6.1425835162103903E-01 -6.1265201202355346E-01 -6.1104792883524028E-01 -6.0944610191163107E-01 -6.0784653109406772E-01 -6.0624921628394846E-01 -6.0465415741052597E-01 -6.0306135439679853E-01 -6.0147080715809320E-01 -5.9988251559643957E-01 -5.9829647957332821E-01 -5.9671269894168022E-01 -5.9513117357479084E-01 -5.9355190335805375E-01 -5.9197488817664878E-01 -5.9040012791637375E-01 -5.8882762245325027E-01 -5.8725737162348546E-01 -5.8568937525067410E-01 -5.8412363316644100E-01 -5.8256014520856059E-01 -5.8099891120716640E-01 -5.7943993097782132E-01 -5.7788320433850537E-01 -5.7632873114418837E-01 -5.7477651126090124E-01 -5.7322654449645349E-01 -5.7167883059753644E-01 -5.7013336933220404E-01 -5.6859016054118949E-01 -5.6704920406706327E-01 -5.6551049966918288E-01 -5.6397404706396392E-01 -5.6243984600959029E-01 -5.6090789632217997E-01 -5.5937819780226383E-01 -5.5785075018079922E-01 -5.5632555317481025E-01 -5.5480260655064084E-01 -5.5328191010683847E-01 -5.5176346362111783E-01 -5.5024726683497394E-01 -5.4873331947561732E-01 -5.4722162122391316E-01 -5.4571217174795783E-01 -5.4420497077511787E-01 -5.4270001808379398E-01 -5.4119731342317468E-01 -5.3969685647378463E-01 -5.3819864690388919E-01 -5.3670268437428215E-01 -5.3520896854356204E-01 -5.3371749913067013E-01 -5.3222827592229716E-01 -5.3074129865556052E-01 -5.2925656690945411E-01 -5.2777408024337802E-01 -5.2629383833024113E-01 -5.2481584090356326E-01 -5.2334008764841289E-01 -5.2186657817979065E-01 -5.2039531211937684E-01 -5.1892628914434757E-01 -5.1745950893937775E-01 -5.1599497111939407E-01 -5.1453267524909574E-01 -5.1307262091982153E-01 -5.1161480777685397E-01 -5.1015923546446640E-01 -5.0870590359725021E-01 -5.0725481177756315E-01 -5.0580595959163643E-01 -5.0435934661068293E-01 -5.0291497241640204E-01 -5.0147283662075670E-01 -5.0003293883239264E-01 -4.9859527861295266E-01 -4.9715985550209524E-01 -4.9572666904902984E-01 -4.9429571881488593E-01 -4.9286700437272407E-01 -4.9144052533694643E-01 -4.9001628131790992E-01 -4.8859427181341397E-01 -4.8717449625523801E-01 -4.8575695413307762E-01 -4.8434164502833027E-01 -4.8292856851981408E-01 -4.8151772414742439E-01 -4.8010911143707619E-01 -4.7870272988700152E-01 -4.7729857897390843E-01 -4.7589665818288551E-01 -4.7449696701908767E-01 -4.7309950498876080E-01 -4.7170427159980721E-01 -4.7031126635801696E-01 -4.6892048873792086E-01 -4.6753193818330852E-01 -4.6614561414102484E-01 -4.6476151607285443E-01 -4.6337964344562210E-01 -4.6199999575984485E-01 -4.6062257252931216E-01 -4.5924737320089232E-01 -4.5787439713710459E-01 -4.5650364371981084E-01 -4.5513511242312205E-01 -4.5376880273429460E-01 -4.5240471407867566E-01 -4.5104284584230175E-01 -4.4968319743023211E-01 -4.4832576828114429E-01 -4.4697055782933226E-01 -4.4561756548114645E-01 -4.4426679063276986E-01 -4.4291823267237013E-01 -4.4157189098114064E-01 -4.4022776493138210E-01 -4.3888585387924356E-01 -4.3754615718693218E-01 -4.3620867427862037E-01 -4.3487340459814422E-01 -4.3354034750870729E-01 -4.3220950228927946E-01 -4.3088086824794763E-01 -4.2955444479021659E-01 -4.2823023132764210E-01 -4.2690822719011096E-01 -4.2558843166498589E-01 -4.2427084405817045E-01 -4.2295546370184156E-01 -4.2164228993228625E-01 -4.2033132210003193E-01 -4.1902255955501561E-01 -4.1771600161817424E-01 -4.1641164759012977E-01 -4.1510949675315911E-01 -4.1380954835975547E-01 -4.1251180167387846E-01 -4.1121625604095335E-01 -4.0992291082628540E-01 -4.0863176531748391E-01 -4.0734281873484884E-01 -4.0605607030553226E-01 -4.0477151928032468E-01 -4.0348916491950071E-01 -4.0220900653703195E-01 -4.0093104346504532E-01 -3.9965527495086306E-01 -3.9838170014767671E-01 -3.9711031824949894E-01 -3.9584112859340426E-01 -3.9457413052352858E-01 -3.9330932321218631E-01 -3.9204670573869482E-01 -3.9078627728557508E-01 -3.8952803718606954E-01 -3.8827198475293012E-01 -3.8701811917499590E-01 -3.8576643960943791E-01 -3.8451694523050300E-01 -3.8326963522402202E-01 -3.8202450878745897E-01 -3.8078156514151040E-01 -3.7954080349538288E-01 -3.7830222299110272E-01 -3.7706582274998224E-01 -3.7583160196167026E-01 -3.7459955987826277E-01 -3.7336969571224354E-01 -3.7214200857657009E-01 -3.7091649757084705E-01 -3.6969316181911649E-01 -3.6847200045620798E-01 -3.6725301265276200E-01 -3.6603619762216749E-01 -3.6482155454145099E-01 -3.6360908246628243E-01 -3.6239878043794849E-01 -3.6119064761922404E-01 -3.5998468324133831E-01 -3.5878088644640510E-01 -3.5757925623997405E-01 -3.5637979164454409E-01 -3.5518249181379674E-01 -3.5398735592996461E-01 -3.5279438309448868E-01 -3.5160357234720740E-01 -3.5041492274264319E-01 -3.4922843336991249E-01 -3.4804410332124280E-01 -3.4686193169301610E-01 -3.4568191757938493E-01 -3.4450406002343048E-01 -3.4332835801836453E-01 -3.4215481059731179E-01 -3.4098341690714495E-01 -3.3981417609607439E-01 -3.3864708718990494E-01 -3.3748214915543617E-01 -3.3631936098234588E-01 -3.3515872169022670E-01 -3.3400023030891779E-01 -3.3284388590283071E-01 -3.3168968753831024E-01 -3.3053763423809418E-01 -3.2938772499693281E-01 -3.2823995881226731E-01 -3.2709433468809912E-01 -3.2595085162814641E-01 -3.2480950863988134E-01 -3.2367030472840774E-01 -3.2253323886848601E-01 -3.2139831001010860E-01 -3.2026551712815554E-01 -3.1913485925462937E-01 -3.1800633541487444E-01 -3.1687994455715929E-01 -3.1575568559924094E-01 -3.1463355747842991E-01 -3.1351355915253776E-01 -3.1239568958594555E-01 -3.1127994776291684E-01 -3.1016633266367538E-01 -3.0905484321877813E-01 -3.0794547833284097E-01 -3.0683823693228524E-01 -3.0573311797389385E-01 -3.0463012040417797E-01 -3.0352924312932605E-01 -3.0243048504703707E-01 -3.0133384508685507E-01 -3.0023932219831195E-01 -2.9914691530241599E-01 -2.9805662327166399E-01 -2.9696844497613067E-01 -2.9588237930686406E-01 -2.9479842516102295E-01 -2.9371658145529062E-01 -2.9263684712262977E-01 -2.9155922106655902E-01 -2.9048370212533758E-01 -2.8941028912912675E-01 -2.8833898092646332E-01 -2.8726977637330042E-01 -2.8620267435762109E-01 -2.8513767380304078E-01 -2.8407477360617078E-01 -2.8301397258131311E-01 -2.8195526953099320E-01 -2.8089866330810737E-01 -2.7984415279085256E-01 -2.7879173680766900E-01 -2.7774141411656472E-01 -2.7669318349838523E-01 -2.7564704385437055E-01 -2.7460299410636368E-01 -2.7356103307035967E-01 -2.7252115948722250E-01 -2.7148337213573792E-01 -2.7044766987007096E-01 -2.6941405153648723E-01 -2.6838251590386014E-01 -2.6735306171626089E-01 -2.6632568777121535E-01 -2.6530039291474194E-01 -2.6427717596123296E-01 -2.6325603564711525E-01 -2.6223697070749385E-01 -2.6121997996603652E-01 -2.6020506228095192E-01 -2.5919221640131929E-01 -2.5818144094801815E-01 -2.5717273459140794E-01 -2.5616609619056890E-01 -2.5516152463139641E-01 -2.5415901870394125E-01 -2.5315857714097734E-01 -2.5216019863792360E-01 -2.5116388183569588E-01 -2.5016962539878224E-01 -2.4917742812082624E-01 -2.4818728882253227E-01 -2.4719920623551772E-01 -2.4621317902401238E-01 -2.4522920588385519E-01 -2.4424728557914441E-01 -2.4326741687028605E-01 -2.4228959845995363E-01 -2.4131382902858114E-01 -2.4034010725738553E-01 -2.3936843182830572E-01 -2.3839880142432132E-01 -2.3743121473484308E-01 -2.3646567045012390E-01 -2.3550216727309944E-01 -2.3454070391059983E-01 -2.3358127903815151E-01 -2.3262389129265396E-01 -2.3166853932247167E-01 -2.3071522182985554E-01 -2.2976393752156535E-01 -2.2881468504483285E-01 -2.2786746300950206E-01 -2.2692227005069160E-01 -2.2597910484694730E-01 -2.2503796607065829E-01 -2.2409885235532190E-01 -2.2316176232095425E-01 -2.2222669457852298E-01 -2.2129364773142318E-01 -2.2036262041097998E-01 -2.1943361131073941E-01 -2.1850661911530506E-01 -2.1758164241507735E-01 -2.1665867976458678E-01 -2.1573772976471392E-01 -2.1481879106437049E-01 -2.1390186229405947E-01 -2.1298694203093374E-01 -2.1207402884239168E-01 -2.1116312130683057E-01 -2.1025421800771918E-01 -2.0934731755741695E-01 -2.0844241860758325E-01 -2.0753951978052776E-01 -2.0663861958543664E-01 -2.0573971651141873E-01 -2.0484280914332922E-01 -2.0394789612784681E-01 -2.0305497607285319E-01 -2.0216404751899633E-01 -2.0127510899665296E-01 -2.0038815902725032E-01 -1.9950319613168474E-01 -1.9862021889888462E-01 -1.9773922597512728E-01 -1.9686021594149866E-01 -1.9598318723051911E-01 -1.9510813827070186E-01 -1.9423506761356274E-01 -1.9336397385902004E-01 -1.9249485558174290E-01 -1.9162771132869891E-01 -1.9076253962469800E-01 -1.8989933893724681E-01 -1.8903810772894331E-01 -1.8817884453251943E-01 -1.8732154791636690E-01 -1.8646621639385016E-01 -1.8561284840072084E-01 -1.8476144239036982E-01 -1.8391199691724505E-01 -1.8306451055193027E-01 -1.8221898176837176E-01 -1.8137540897236301E-01 -1.8053379061722805E-01 -1.7969412524867609E-01 -1.7885641140545183E-01 -1.7802064754518515E-01 -1.7718683209763003E-01 -1.7635496350741353E-01 -1.7552504023248647E-01 -1.7469706074395566E-01 -1.7387102354699116E-01 -1.7304692714007866E-01 -1.7222476994971617E-01 -1.7140455037008825E-01 -1.7058626682017411E-01 -1.6976991774856906E-01 -1.6895550161062187E-01 -1.6814301688312078E-01 -1.6733246204064300E-01 -1.6652383551040653E-01 -1.6571713569122162E-01 -1.6491236097927628E-01 -1.6410950976858790E-01 -1.6330858046874902E-01 -1.6250957156449025E-01 -1.6171248155198215E-01 -1.6091730882651428E-01 -1.6012405170757779E-01 -1.5933270855099277E-01 -1.5854327779012031E-01 -1.5775575786271875E-01 -1.5697014719013155E-01 -1.5618644418416314E-01 -1.5540464721018560E-01 -1.5462475458874844E-01 -1.5384676467876066E-01 -1.5307067594698009E-01 -1.5229648685971467E-01 -1.5152419575893236E-01 -1.5075380092847138E-01 -1.4998530071537891E-01 -1.4921869354647327E-01 -1.4845397783074432E-01 -1.4769115190430945E-01 -1.4693021408805149E-01 -1.4617116272718539E-01 -1.4541399618118808E-01 -1.4465871282676943E-01 -1.4390531106959664E-01 -1.4315378929368008E-01 -1.4240414577927576E-01 -1.4165637878052201E-01 -1.4091048663741212E-01 -1.4016646775759029E-01 -1.3942432051434192E-01 -1.3868404320741953E-01 -1.3794563412968422E-01 -1.3720909160036585E-01 -1.3647441394678822E-01 -1.3574159948399020E-01 -1.3501064651445516E-01 -1.3428155335434039E-01 -1.3355431836353340E-01 -1.3282893989626443E-01 -1.3210541621056149E-01 -1.3138374551687088E-01 -1.3066392611074479E-01 -1.2994595640188758E-01 -1.2922983476221114E-01 -1.2851555940113954E-01 -1.2780312849815137E-01 -1.2709254034412115E-01 -1.2638379330149008E-01 -1.2567688568497581E-01 -1.2497181572688372E-01 -1.2426858166609302E-01 -1.2356718182327177E-01 -1.2286761453772892E-01 -1.2216987806176155E-01 -1.2147397057373567E-01 -1.2077989029745841E-01 -1.2008763556717904E-01 -1.1939720471341872E-01 -1.1870859595325420E-01 -1.1802180745816337E-01 -1.1733683746294024E-01 -1.1665368427197689E-01 -1.1597234617553483E-01 -1.1529282141604186E-01 -1.1461510822182182E-01 -1.1393920478960710E-01 -1.1326510929909163E-01 -1.1259281998133824E-01 -1.1192233514120779E-01 -1.1125365307020971E-01 -1.1058677199153480E-01 -1.0992169010850526E-01 -1.0925840560903841E-01 -1.0859691666973094E-01 -1.0793722148646051E-01 -1.0727931829294564E-01 -1.0662320532346217E-01 -1.0596888080330967E-01 -1.0531634295265860E-01 -1.0466558998058130E-01 -1.0401662008585630E-01 -1.0336943145514529E-01 -1.0272402225028590E-01 -1.0208039063405916E-01 -1.0143853481572726E-01 -1.0079845302276071E-01 -1.0016014345788538E-01 -9.9523604295352980E-02 -9.8888833705429960E-02 -9.8255829855973600E-02 -9.7624590915914633E-02 -9.6995115087685865E-02 -9.6367400590945979E-02 -9.5741445593781949E-02 -9.5117248187656267E-02 -9.4494806478034474E-02 -9.3874118664622211E-02 -9.3255182968597056E-02 -9.2637997583717241E-02 -9.2022560682499935E-02 -9.1408870410680881E-02 -9.0796924864923523E-02 -9.0186722145415357E-02 -8.9578260415676958E-02 -8.8971537858504687E-02 -8.8366552620798788E-02 -8.7763302814920827E-02 -8.7161786572745703E-02 -8.6562002083695994E-02 -8.5963947534254237E-02 -8.5367621031173430E-02 -8.4773020643225311E-02 -8.4180144462743481E-02 -8.3588990612111710E-02 -8.2999557222076220E-02 -8.2411842451259987E-02 -8.1825844459989736E-02 -8.1241561381739893E-02 -8.0658991332301852E-02 -8.0078132406882857E-02 -7.9498982669603716E-02 -7.8921540189361580E-02 -7.8345803077929418E-02 -7.7771769457583115E-02 -7.7199437449125621E-02 -7.6628805171607015E-02 -7.6059870732240839E-02 -7.5492632216250091E-02 -7.4927087708431400E-02 -7.4363235319203191E-02 -7.3801073164991918E-02 -7.3240599308087476E-02 -7.2681811755575587E-02 -7.2124708548575056E-02 -7.1569287833010697E-02 -7.1015547763560782E-02 -7.0463486433149758E-02 -6.9913101902331409E-02 -6.9364392221089213E-02 -6.8817355426585056E-02 -6.8271989567393235E-02 -6.7728292743412424E-02 -6.7186263060592319E-02 -6.6645898577996410E-02 -6.6107197323295799E-02 -6.5570157325542444E-02 -6.5034776618818152E-02 -6.4501053251160206E-02 -6.3968985345615181E-02 -6.3438571040228667E-02 -6.2909808362479822E-02 -6.2382695246510189E-02 -6.1857229675145925E-02 -6.1333409749467466E-02 -6.0811233578920862E-02 -6.0290699234128317E-02 -5.9771804767236404E-02 -5.9254548196625095E-02 -5.8738927504256147E-02 -5.8224940685013653E-02 -5.7712585781969368E-02 -5.7201860844098902E-02 -5.6692763909971043E-02 -5.6185293011290473E-02 -5.5679446171651929E-02 -5.5175221404352985E-02 -5.4672616725415561E-02 -5.4171630171389505E-02 -5.3672259778537179E-02 -5.3174503536470692E-02 -5.2678359402078254E-02 -5.2183825372643010E-02 -5.1690899522278871E-02 -5.1199579917895463E-02 -5.0709864554531497E-02 -5.0221751402243567E-02 -4.9735238435926560E-02 -4.9250323634612972E-02 -4.8767004990557326E-02 -4.8285280530555440E-02 -4.7805148276613585E-02 -4.7326606193280607E-02 -4.6849652221007204E-02 -4.6374284369641354E-02 -4.5900500729781780E-02 -4.5428299346108050E-02 -4.4957678108708148E-02 -4.4488634887608236E-02 -4.4021167673939571E-02 -4.3555274526200526E-02 -4.3090953469659271E-02 -4.2628202479923098E-02 -4.2167019520572037E-02 -4.1707402528787615E-02 -4.1249349435886130E-02 -4.0792858212801930E-02 -4.0337926859086722E-02 -3.9884553370006785E-02 -3.9432735733441387E-02 -3.8982471925022626E-02 -3.8533759865719358E-02 -3.8086597458337902E-02 -3.7640982661831260E-02 -3.7196913488585018E-02 -3.6754387925498844E-02 -3.6313403892540494E-02 -3.5873959304731237E-02 -3.5436052134222053E-02 -3.4999680377370307E-02 -3.4564841991588685E-02 -3.4131534886746133E-02 -3.3699756979534951E-02 -3.3269506225283969E-02 -3.2840780584854158E-02 -3.2413578009231912E-02 -3.1987896442286758E-02 -3.1563733816879457E-02 -3.1141088049922685E-02 -3.0719957061588830E-02 -3.0300338801250409E-02 -2.9882231224184284E-02 -2.9465632273883321E-02 -2.9050539883894590E-02 -2.8636951963921475E-02 -2.8224866377273304E-02 -2.7814281000030958E-02 -2.7405193832754967E-02 -2.6997602916737366E-02 -2.6591506177502538E-02 -2.6186901423024378E-02 -2.5783786495710174E-02 -2.5382159350657747E-02 -2.4982017958026119E-02 -2.4583360268940851E-02 -2.4186184222705728E-02 -2.3790487712055941E-02 -2.3396268569563301E-02 -2.3003524649818311E-02 -2.2612253908586472E-02 -2.2222454317248366E-02 -2.1834123780081312E-02 -2.1447260157411673E-02 -2.1061861337188188E-02 -2.0677925257204063E-02 -2.0295449848368733E-02 -1.9914432992752251E-02 -1.9534872557459188E-02 -1.9156766435332730E-02 -1.8780112540320078E-02 -1.8404908771561378E-02 -1.8031152996743766E-02 -1.7658843083464198E-02 -1.7287976938306988E-02 -1.6918552481649727E-02 -1.6550567617759235E-02 -1.6184020233640246E-02 -1.5818908209887260E-02 -1.5455229415240974E-02 -1.5092981714616363E-02 -1.4732162973747468E-02 -1.4372771058284654E-02 -1.4014803860825664E-02 -1.3658259312515832E-02 -1.3303135325450036E-02 -1.2949429732360072E-02 -1.2597140349875441E-02 -1.2246265058422492E-02 -1.1896801781440636E-02 -1.1548748416393280E-02 -1.1202102814038184E-02 -1.0856862823589403E-02 -1.0513026321112871E-02 -1.0170591188290961E-02 -9.8295552757714112E-03 -9.4899164063863995E-03 -9.1516724358262965E-03 -8.8148213032259465E-03 -8.4793609396144089E-03 -8.1452891446936477E-03 -7.8126036630565467E-03 -7.4813023310524298E-03 -7.1513830911451451E-03 -6.8228438665235858E-03 -6.4956825060963185E-03 -6.1698968423593552E-03 -5.8454847064749902E-03 -5.5224439284050934E-03 -5.2007723689516498E-03 -4.8804679359156448E-03 -4.5615285145760680E-03 -4.2439518863967469E-03 -3.9277358123805490E-03 -3.6128781717850514E-03 -3.2993769295035086E-03 -2.9872299740083658E-03 -2.6764350443466401E-03 -2.3669898856853513E-03 -2.0588923840178311E-03 -1.7521404697275324E-03 -1.4467319991395846E-03 -1.1426647581957760E-03 -8.3993655192063463E-04 -5.3854524435418627E-04 -2.3848870386163689E-04 --6.0235225602447817E-05 --3.5762871315548055E-04 --6.5369394665958742E-04 --9.4843313630027190E-04 --1.2418484660032586E-03 --1.5339420212700616E-03 --1.8247158806852480E-03 --2.1141722524250775E-03 --2.4023134227946176E-03 --2.6891416099009916E-03 --2.9746589207597786E-03 --3.2588674616063876E-03 --3.5417693721909683E-03 --3.8233668067840076E-03 --4.1036619734988490E-03 --4.3826571228507494E-03 --4.6603544699131859E-03 --4.9367561518198939E-03 --5.2118643070713771E-03 --5.4856811306967105E-03 --5.7582088384316868E-03 --6.0294496011160286E-03 --6.2994055442365483E-03 --6.5680788146209928E-03 --6.8354716187816137E-03 --7.1015861705755468E-03 --7.3664246473550930E-03 --7.6299892101115135E-03 --7.8922820409560949E-03 --8.1533053489643084E-03 --8.4130613405086485E-03 --8.6715521999352167E-03 --8.9287801076517841E-03 --9.1847472372690499E-03 --9.4394557590837883E-03 --9.6929078625936898E-03 --9.9451057682390081E-03 --1.0196051689407144E-02 --1.0445747782748762E-02 --1.0694196191829687E-02 --1.0941399104170533E-02 --1.1187358744229383E-02 --1.1432077325331977E-02 --1.1675557031066819E-02 --1.1917800044826368E-02 --1.2158808563698805E-02 --1.2398584791325730E-02 --1.2637130924144951E-02 --1.2874449150674457E-02 --1.3110541665547277E-02 --1.3345410678189800E-02 --1.3579058399780122E-02 --1.3811487018234748E-02 --1.4042698710433349E-02 --1.4272695661538846E-02 --1.4501480067469912E-02 --1.4729054132633580E-02 --1.4955420085266300E-02 --1.5180580156246947E-02 --1.5404536516404428E-02 --1.5627291296724629E-02 --1.5848846688029390E-02 --1.6069204988499067E-02 --1.6288368480156433E-02 --1.6506339293508483E-02 --1.6723119517178458E-02 --1.6938711350388765E-02 --1.7153117090534766E-02 --1.7366338998190928E-02 --1.7578379236087429E-02 --1.7789239959751377E-02 --1.7998923361731776E-02 --1.8207431652442266E-02 --1.8414767063114058E-02 --1.8620931848363179E-02 --1.8825928238475894E-02 --1.9029758379213665E-02 --1.9232424411296273E-02 --1.9433928570895011E-02 --1.9634273147539825E-02 --1.9833460359326205E-02 --2.0031492316857847E-02 --2.0228371162235803E-02 --2.0424099198805050E-02 --2.0618678762118925E-02 --2.0812112029234508E-02 --2.1004401062820852E-02 --2.1195548019204782E-02 --2.1385555237683603E-02 --2.1574425046611063E-02 --2.1762159587347847E-02 --2.1948760942875737E-02 --2.2134231308119135E-02 --2.2318572983673575E-02 --2.2501788232653731E-02 --2.2683879209921674E-02 --2.2864848068421425E-02 --2.3044697062182325E-02 --2.3223428490561512E-02 --2.3401044574600193E-02 --2.3577547439285973E-02 --2.3752939235913234E-02 --2.3927222218572710E-02 --2.4100398659253001E-02 --2.4272470774974336E-02 --2.4443440750960149E-02 --2.4613310793472360E-02 --2.4782083141325548E-02 --2.4949760024056987E-02 --2.5116343609766882E-02 --2.5281836055953310E-02 --2.5446239598529524E-02 --2.5609556534615673E-02 --2.5771789120474824E-02 --2.5932939522982399E-02 --2.6093009904275835E-02 --2.6252002454531607E-02 --2.6409919377349184E-02 --2.6566762914724325E-02 --2.6722535347110495E-02 --2.6877238924265526E-02 --2.7030875804917438E-02 --2.7183448141754815E-02 --2.7334958150061490E-02 --2.7485408076906973E-02 --2.7634800167801635E-02 --2.7783136665308041E-02 --2.7930419787342932E-02 --2.8076651658629534E-02 --2.8221834398747814E-02 --2.8365970291804359E-02 --2.8509061726362184E-02 --2.8651110969459652E-02 --2.8792120079886335E-02 --2.8932091135406707E-02 --2.9071026393955816E-02 --2.9208928165335397E-02 --2.9345798696316705E-02 --2.9481640181853532E-02 --2.9616454817892813E-02 --2.9750244803507738E-02 --2.9883012344698236E-02 --3.0014759679595212E-02 --3.0145489058440330E-02 --3.0275202680370428E-02 --3.0403902689794735E-02 --3.0531591264036165E-02 --3.0658270679590593E-02 --3.0783943222328497E-02 --3.0908611088782300E-02 --3.1032276430573082E-02 --3.1154941441890932E-02 --3.1276608375377248E-02 --3.1397279466289951E-02 --3.1516956860616500E-02 --3.1635642694146031E-02 --3.1753339226873997E-02 --3.1870048803265515E-02 --3.1985773685659039E-02 --3.2100515984843217E-02 --3.2214277820620425E-02 --3.2327061433223891E-02 --3.2438869098899120E-02 --3.2549703015932845E-02 --3.2659565314334220E-02 --3.2768458173763039E-02 --3.2876383892984577E-02 --3.2983344772493380E-02 --3.3089342994592832E-02 --3.3194380693247635E-02 --3.3298460032503280E-02 --3.3401583210526865E-02 --3.3503752441989720E-02 --3.3604969982887339E-02 --3.3705238093892469E-02 --3.3804558988962764E-02 --3.3902934856577902E-02 --3.4000367872791704E-02 --3.4096860194861821E-02 --3.4192413993986953E-02 --3.4287031499484609E-02 --3.4380714955099353E-02 --3.4473466576125773E-02 --3.4565288557788953E-02 --3.4656183098252386E-02 --3.4746152400317733E-02 --3.4835198668042570E-02 --3.4923324101226651E-02 --3.5010530900416961E-02 --3.5096821285478974E-02 --3.5182197494450479E-02 --3.5266661737995905E-02 --3.5350216153425824E-02 --3.5432862875186155E-02 --3.5514604090383241E-02 --3.5595442011998511E-02 --3.5675378877579662E-02 --3.5754416953790377E-02 --3.5832558475737693E-02 --3.5909805563174746E-02 --3.5986160322953278E-02 --3.6061624963010831E-02 --3.6136201751986792E-02 --3.6209892931738118E-02 --3.6282700699789582E-02 --3.6354627236369542E-02 --3.6425674655488065E-02 --3.6495845061675407E-02 --3.6565140674344430E-02 --3.6633563801867219E-02 --3.6701116704259261E-02 --3.6767801536153201E-02 --3.6833620440603579E-02 --3.6898575559462507E-02 --3.6962669037933875E-02 --3.7025903080941648E-02 --3.7088279952946161E-02 --3.7149801887883159E-02 --3.7210471027583236E-02 --3.7270289507249421E-02 --3.7329259521017857E-02 --3.7387383292027898E-02 --3.7444663014338846E-02 --3.7501100843742682E-02 --3.7556698935397453E-02 --3.7611459446474996E-02 --3.7665384542461607E-02 --3.7718476462617369E-02 --3.7770737492515936E-02 --3.7822169818802119E-02 --3.7872775460563696E-02 --3.7922556470237560E-02 --3.7971515129414248E-02 --3.8019653780323605E-02 --3.8066974612955579E-02 --3.8113479692560182E-02 --3.8159171128304976E-02 --3.8204051130893459E-02 --3.8248121920476205E-02 --3.8291385682603360E-02 --3.8333844589546306E-02 --3.8375500796048775E-02 --3.8416356438164448E-02 --3.8456413656410761E-02 --3.8495674603294706E-02 --3.8534141441442564E-02 --3.8571816391494283E-02 --3.8608701703615585E-02 --3.8644799555912546E-02 --3.8680112026638763E-02 --3.8714641213560115E-02 --3.8748389312033636E-02 --3.8781358538140950E-02 --3.8813551057711844E-02 --3.8844969003302268E-02 --3.8875614522712626E-02 --3.8905489790515203E-02 --3.8934596981167947E-02 --3.8962938247198479E-02 --3.8990515735221436E-02 --3.9017331589833115E-02 --3.9043387954139128E-02 --3.9068686981368908E-02 --3.9093230845990146E-02 --3.9117021720171917E-02 --3.9140061729354657E-02 --3.9162352981833883E-02 --3.9183897633735698E-02 --3.9204697895043050E-02 --3.9224755957016119E-02 --3.9244073940515996E-02 --3.9262653954586738E-02 --3.9280498111607727E-02 --3.9297608527233158E-02 --3.9313987348193614E-02 --3.9329636765679847E-02 --3.9344558967010064E-02 --3.9358756103562792E-02 --3.9372230315493820E-02 --3.9384983698575807E-02 --3.9397018317475344E-02 --3.9408336284275876E-02 --3.9418939800731467E-02 --3.9428831067497179E-02 --3.9438012216126146E-02 --3.9446485355146735E-02 --3.9454252584357349E-02 --3.9461315995649199E-02 --3.9467677713256530E-02 --3.9473339940069373E-02 --3.9478304875240136E-02 --3.9482574589161011E-02 --3.9486151097758763E-02 --3.9489036516901908E-02 --3.9491233082585619E-02 --3.9492742989435087E-02 --3.9493568267644864E-02 --3.9493710928655307E-02 --3.9493173128498683E-02 --3.9491957108200575E-02 --3.9490065016709611E-02 --3.9487498856992223E-02 --3.9484260657020202E-02 --3.9480352605688523E-02 --3.9475776928750005E-02 --3.9470535719051736E-02 --3.9464630968197828E-02 --3.9458064739529480E-02 --3.9450839245209000E-02 --3.9442956690853112E-02 --3.9434419128021765E-02 --3.9425228556056201E-02 --3.9415387052699841E-02 --3.9404896773549816E-02 --3.9393759864563505E-02 --3.9381978434192326E-02 --3.9369554584972655E-02 --3.9356490410932574E-02 --3.9342788002526538E-02 --3.9328449437346855E-02 --3.9313476776058141E-02 --3.9297872097599398E-02 --3.9281637545468852E-02 --3.9264775271026058E-02 --3.9247287338089021E-02 --3.9229175756561666E-02 --3.9210442594437338E-02 --3.9191090016288066E-02 --3.9171120170714516E-02 --3.9150535081071296E-02 --3.9129336740096152E-02 --3.9107527229639311E-02 --3.9085108704564948E-02 --3.9062083277280876E-02 --3.9038452961648012E-02 --3.9014219776384675E-02 --3.8989385845698714E-02 --3.8963953333164623E-02 --3.8937924319189195E-02 --3.8911300796222383E-02 --3.8884084786881878E-02 --3.8856278408943970E-02 --3.8827883788991512E-02 --3.8798902971555874E-02 --3.8769337960245370E-02 --3.8739190792156007E-02 --3.8708463549874103E-02 --3.8677158315509781E-02 --3.8645277152399314E-02 --3.8612822122184996E-02 --3.8579795305880932E-02 --3.8546198797535382E-02 --3.8512034640307065E-02 --3.8477304785663739E-02 --3.8442011206979036E-02 --3.8406156031284527E-02 --3.8369741429504889E-02 --3.8332769460440133E-02 --3.8295242085580314E-02 --3.8257161301090040E-02 --3.8218529188764484E-02 --3.8179347830850939E-02 --3.8139619220704787E-02 --3.8099345318454637E-02 --3.8058528180362552E-02 --3.8017169970570842E-02 --3.7975272802967606E-02 --3.7932838616630112E-02 --3.7889869328499956E-02 --3.7846366950882109E-02 --3.7802333549753160E-02 --3.7757771202280896E-02 --3.7712682000291181E-02 --3.7667068004127058E-02 --3.7620931135756014E-02 --3.7574273294240262E-02 --3.7527096532301095E-02 --3.7479403012612489E-02 --3.7431194811024193E-02 --3.7382473833608557E-02 --3.7333241992651173E-02 --3.7283501331540438E-02 --3.7233253936424945E-02 --3.7182501831887878E-02 --3.7131246985608476E-02 --3.7079491389921330E-02 --3.7027237101181262E-02 --3.6974486174482048E-02 --3.6921240573970858E-02 --3.6867502224979636E-02 --3.6813273097277985E-02 --3.6758555213671169E-02 --3.6703350597671235E-02 --3.6647661261356657E-02 --3.6591489212495817E-02 --3.6534836426516275E-02 --3.6477704860743913E-02 --3.6420096491481160E-02 --3.6362013323867716E-02 --3.6303457364330778E-02 --3.6244430609072696E-02 --3.6184935050782352E-02 --3.6124972655615435E-02 --3.6064545369912326E-02 --3.6003655152156408E-02 --3.5942303984727378E-02 --3.5880493855356195E-02 --3.5818226759562831E-02 --3.5755504694349502E-02 --3.5692329604299293E-02 --3.5628703382382193E-02 --3.5564627956725041E-02 --3.5500105351937164E-02 --3.5435137601744791E-02 --3.5369726676670453E-02 --3.5303874517496239E-02 --3.5237583062741724E-02 --3.5170854247868699E-02 --3.5103690007088635E-02 --3.5036092267250941E-02 --3.4968062959364540E-02 --3.4899604067019009E-02 --3.4830717606725188E-02 --3.4761405544620233E-02 --3.4691669761982624E-02 --3.4621512154131145E-02 --3.4550934714958174E-02 --3.4479939461441143E-02 --3.4408528296211466E-02 --3.4336703029534489E-02 --3.4264465539443956E-02 --3.4191817853831401E-02 --3.4118762004603356E-02 --3.4045299918205318E-02 --3.3971433480089207E-02 --3.3897164561833955E-02 --3.3822495020538496E-02 --3.3747426759003149E-02 --3.3671961809038295E-02 --3.3596102208140563E-02 --3.3519849835487968E-02 --3.3443206490981557E-02 --3.3366174040024552E-02 --3.3288754437127394E-02 --3.3210949629700573E-02 --3.3132761510363894E-02 --3.3054191961084327E-02 --3.2975242879332303E-02 --3.2895916173565763E-02 --3.2816213762232940E-02 --3.2736137579864523E-02 --3.2655689548083691E-02 --3.2574871509255067E-02 --3.2493685285072120E-02 --3.2412132759662211E-02 --3.2330215871362186E-02 --3.2247936545691816E-02 --3.2165296672705068E-02 --3.2082298135120847E-02 --3.1998942792008378E-02 --3.1915232493964447E-02 --3.1831169109505265E-02 --3.1746754527020436E-02 --3.1661990633828151E-02 --3.1576879307978305E-02 --3.1491422427190024E-02 --3.1405621872679854E-02 --3.1319479527380144E-02 --3.1232997231980961E-02 --3.1146176765572218E-02 --3.1059019934953021E-02 --3.0971528675100200E-02 --3.0883704947560285E-02 --3.0795550619955106E-02 --3.0707067493490947E-02 --3.0618257389129978E-02 --3.0529122166348198E-02 --3.0439663681458649E-02 --3.0349883744775531E-02 --3.0259784154758045E-02 --3.0169366767201240E-02 --3.0078633490751780E-02 --2.9987586199748558E-02 --2.9896226677297175E-02 --2.9804556702902604E-02 --2.9712578123800262E-02 --2.9620292816921950E-02 --2.9527702613364838E-02 --2.9434809289328762E-02 --2.9341614644045035E-02 --2.9248120559388701E-02 --2.9154328924328447E-02 --2.9060241517731383E-02 --2.8965860055811265E-02 --2.8871186332115426E-02 --2.8776222259551103E-02 --2.8680969726604895E-02 --2.8585430466464824E-02 --2.8489606178492496E-02 --2.8393498674255259E-02 --2.8297109850551845E-02 --2.8200441558190396E-02 --2.8103495550318137E-02 --2.8006273573554400E-02 --2.7908777398741088E-02 --2.7811008807814810E-02 --2.7712969615359503E-02 --2.7614661667913622E-02 --2.7516086777193634E-02 --2.7417246657594395E-02 --2.7318143020098825E-02 --2.7218777667173032E-02 --2.7119152444946053E-02 --2.7019269168024124E-02 --2.6919129610428357E-02 --2.6818735534856718E-02 --2.6718088670364532E-02 --2.6617190742279181E-02 --2.6516043506072111E-02 --2.6414648736383998E-02 --2.6313008197183761E-02 --2.6211123633648074E-02 --2.6108996803128909E-02 --2.6006629523844815E-02 --2.5904023625186599E-02 --2.5801180814733187E-02 --2.5698102702257909E-02 --2.5594790979432715E-02 --2.5491247517586985E-02 --2.5387474180673403E-02 --2.5283472633636474E-02 --2.5179244469772231E-02 --2.5074791409437251E-02 --2.4970115305618084E-02 --2.4865217970704543E-02 --2.4760101082793157E-02 --2.4654766304267165E-02 --2.4549215356866407E-02 --2.4443449992826636E-02 --2.4337471943919064E-02 --2.4231282913580478E-02 --2.4124884605607022E-02 --2.4018278729426804E-02 --2.3911466997313061E-02 --2.3804451129275584E-02 --2.3697232850612714E-02 --2.3589813862758231E-02 --2.3482195824375798E-02 --2.3374380402501088E-02 --2.3266369323595677E-02 --2.3158164332445122E-02 --2.3049767152940218E-02 --2.2941179491042345E-02 --2.2832403026202985E-02 --2.2723439377111767E-02 --2.2614290167603305E-02 --2.2504957108041259E-02 --2.2395441943415612E-02 --2.2285746359107749E-02 --2.2175871974076111E-02 --2.2065820436145335E-02 --2.1955593488527443E-02 --2.1845192882066038E-02 --2.1734620262529519E-02 --2.1623877219567877E-02 --2.1512965378779343E-02 --2.1401886417626612E-02 --2.1290642007875529E-02 --2.1179233778733566E-02 --2.1067663355039075E-02 --2.0955932435278421E-02 --2.0844042769822713E-02 --2.0731996035580246E-02 --2.0619793769491600E-02 --2.0507437517403370E-02 --2.0394928951739704E-02 --2.0282269784773422E-02 --2.0169461658171132E-02 --2.0056506149089482E-02 --1.9943404866864137E-02 --1.9830159503668014E-02 --1.9716771752624498E-02 --1.9603243216194905E-02 --1.9489575457773772E-02 --1.9375770063406267E-02 --1.9261828645907385E-02 --1.9147752823507742E-02 --1.9033544224545638E-02 --1.8919204478157040E-02 --1.8804735192321433E-02 --1.8690137963547831E-02 --1.8575414410326913E-02 --1.8460566184348843E-02 --1.8345594912754320E-02 --1.8230502100539545E-02 --1.8115289229971666E-02 --1.7999957923525836E-02 --1.7884509909303483E-02 --1.7768946843615015E-02 --1.7653270233673937E-02 --1.7537481577817159E-02 --1.7421582420768016E-02 --1.7305574327164140E-02 --1.7189458916250816E-02 --1.7073237860401720E-02 --1.6956912780146941E-02 --1.6840485152887923E-02 --1.6723956447832592E-02 --1.6607328246305519E-02 --1.6490602182061383E-02 --1.6373779833601214E-02 --1.6256862709249177E-02 --1.6139852329230622E-02 --1.6022750268201272E-02 --1.5905558111340250E-02 --1.5788277420736928E-02 --1.5670909744263502E-02 --1.5553456610134202E-02 --1.5435919514234946E-02 --1.5318299966354858E-02 --1.5200599551371638E-02 --1.5082819870515816E-02 --1.4964962425433992E-02 --1.4847028638293444E-02 --1.4729019996757037E-02 --1.4610938131262744E-02 --1.4492784662772316E-02 --1.4374561033212814E-02 --1.4256268621658597E-02 --1.4137908950285669E-02 --1.4019483689713529E-02 --1.3900994437574653E-02 --1.3782442565867978E-02 --1.3663829429346394E-02 --1.3545156564996682E-02 --1.3426425600775812E-02 --1.3307638072258222E-02 --1.3188795390009599E-02 --1.3069898978526482E-02 --1.2950950344433946E-02 --1.2831951013857061E-02 --1.2712902508076086E-02 --1.2593806344891293E-02 --1.2474663990195589E-02 --1.2355476819138110E-02 --1.2236246228818403E-02 --1.2116973768082889E-02 --1.1997661026862040E-02 --1.1878309471824212E-02 --1.1758920464498930E-02 --1.1639495414797267E-02 --1.1520035848979092E-02 --1.1400543296512298E-02 --1.1281019194900403E-02 --1.1161464944868258E-02 --1.1041881967745507E-02 --1.0922271707638362E-02 --1.0802635616029174E-02 --1.0682975161143199E-02 --1.0563291808718768E-02 --1.0443586965630254E-02 --1.0323862008420332E-02 --1.0204118371168839E-02 --1.0084357570008312E-02 --9.9645810950517791E-03 --9.8447903040548134E-03 --9.7249865285623637E-03 --9.6051711834013315E-03 --9.4853457420575622E-03 --9.3655116433292180E-03 --9.2456702586860267E-03 --9.1258229629723880E-03 --9.0059711848011082E-03 --8.8861163704849425E-03 --8.7662599484755726E-03 --8.6464033309491713E-03 --8.5265479035721466E-03 --8.4066949877986026E-03 --8.2868459118789848E-03 --8.1670021184577519E-03 --8.0471650983051316E-03 --7.9273362466831081E-03 --7.8075168462589028E-03 --7.6877082090636940E-03 --7.5679117605482104E-03 --7.4481289406268603E-03 --7.3283610984939086E-03 --7.2086095321138291E-03 --7.0888755920653461E-03 --6.9691607093269265E-03 --6.8494663081170902E-03 --6.7297937517134792E-03 --6.6101443846215916E-03 --6.4905195084132500E-03 --6.3709203930179112E-03 --6.2513483569407472E-03 --6.1318048153959767E-03 --6.0122911834401592E-03 --5.8928088056184576E-03 --5.7733590013195309E-03 --5.6539430814278356E-03 --5.5345623486922459E-03 --5.4152181281472153E-03 --5.2959118022694917E-03 --5.1766447481609414E-03 --5.0574182229312934E-03 --4.9382334302620363E-03 --4.8190916785513160E-03 --4.6999944073003314E-03 --4.5809430166906789E-03 --4.4619387403792539E-03 --4.3429827857505137E-03 --4.2240764598133760E-03 --4.1052211308968802E-03 --3.9864181329802295E-03 --3.8676687424476449E-03 --3.7489742314061876E-03 --3.6303358737074425E-03 --3.5117549461550759E-03 --3.3932327555524825E-03 --3.2747706326164343E-03 --3.1563698688822661E-03 --3.0380316708471852E-03 --2.9197572496928955E-03 --2.8015479093803398E-03 --2.6834049877966469E-03 --2.5653297683535968E-03 --2.4473234782038406E-03 --2.3293873559368000E-03 --2.2115226777921840E-03 --2.0937307222639498E-03 --1.9760127266343717E-03 --1.8583699087382243E-03 --1.7408035273623894E-03 --1.6233148957328766E-03 --1.5059052944280200E-03 --1.3885758668386195E-03 --1.2713277388181534E-03 --1.1541622003920209E-03 --1.0370806483943390E-03 --9.2008435866237144E-04 --8.0317439441123873E-04 --6.8635184634164073E-04 --5.6961804402485270E-04 --4.5297438045620417E-04 --3.3642205251728892E-04 --2.1996209078459838E-04 --1.0359562503145576E-04 -1.2675980082841952E-05 -1.2885135997253472E-04 -2.4492937070156944E-04 -3.6090895530803115E-04 -4.7678896383752050E-04 -5.9256814407187815E-04 -7.0824524738481536E-04 -8.2381905292273092E-04 -9.3928835354291774E-04 -1.0546520260862622E-03 -1.1699089902826546E-03 -1.2850580657803982E-03 -1.4000979300921852E-03 -1.5150273052066214E-03 -1.6298451355058192E-03 -1.7445504068361616E-03 -1.8591419295748888E-03 -1.9736183917814700E-03 -2.0879785704780249E-03 -2.2022214117232634E-03 -2.3163458575862208E-03 -2.4303507342843611E-03 -2.5442348303485740E-03 -2.6579969599269679E-03 -2.7716359603999724E-03 -2.8851506956800413E-03 -2.9985400926406257E-03 -3.1118030762012053E-03 -3.2249384933780482E-03 -3.3379451573328179E-03 -3.4508219064953720E-03 -3.5635676090962297E-03 -3.6761811389048821E-03 -3.7886613834646932E-03 -3.9010072351531428E-03 -4.0132176121409147E-03 -4.1252914463358612E-03 -4.2372276233532949E-03 -4.3490249590128352E-03 -4.4606822890329639E-03 -4.5721985612027947E-03 -4.6835727493856087E-03 -4.7948037780409384E-03 -4.9058905345633922E-03 -5.0168319032388642E-03 -5.1276267646355031E-03 -5.2382740058772373E-03 -5.3487725571161196E-03 -5.4591213627690699E-03 -5.5693193526162562E-03 -5.6793654423110736E-03 -5.7892585544775353E-03 -5.8989976322140793E-03 -6.0085816218687395E-03 -6.1180094733813053E-03 -6.2272801376402785E-03 -6.3363925509673080E-03 -6.4453456317286450E-03 -6.5541382970394080E-03 -6.6627694650629368E-03 -6.7712380621141521E-03 -6.8795431056980156E-03 -6.9876836677632264E-03 -7.0956587344828664E-03 -7.2034671531199801E-03 -7.3111077903539644E-03 -7.4185796620409019E-03 -7.5258818219049008E-03 -7.6330132518612048E-03 -7.7399728767908738E-03 -7.8467596465028946E-03 -7.9533725670787852E-03 -8.0598106455098094E-03 -8.1660728532614458E-03 -8.2721581503399956E-03 -8.3780655562235157E-03 -8.4837941513412774E-03 -8.5893429744501350E-03 -8.6947109423741575E-03 -8.7998969628676361E-03 -8.9049000475443368E-03 -9.0097192595026063E-03 -9.1143536453736906E-03 -9.2188022296659997E-03 -9.3230640249085620E-03 -9.4271380065278493E-03 -9.5310231487388004E-03 -9.6347185176061511E-03 -9.7382232383208343E-03 -9.8415363754801068E-03 -9.9446568883761449E-03 -1.0047583737331158E-02 -1.0150315941027527E-02 -1.0252852538735400E-02 -1.0355192621229104E-02 -1.0457335322525125E-02 -1.0559279726150606E-02 -1.0661024800016508E-02 -1.0762569517166077E-02 -1.0863912992545088E-02 -1.0965054394698163E-02 -1.1065992780652947E-02 -1.1166727085697568E-02 -1.1267256301320741E-02 -1.1367579604890831E-02 -1.1467696193688261E-02 -1.1567605136821802E-02 -1.1667305434995008E-02 -1.1766796115619142E-02 -1.1866076244882475E-02 -1.1965144908606409E-02 -1.2064001260204852E-02 -1.2162644464231305E-02 -1.2261073617398154E-02 -1.2359287769232260E-02 -1.2457285992525855E-02 -1.2555067404823018E-02 -1.2652631126315072E-02 -1.2749976267828287E-02 -1.2847101936546588E-02 -1.2944007235292524E-02 -1.3040691262987623E-02 -1.3137153140287801E-02 -1.3233392040962608E-02 -1.3329407133277986E-02 -1.3425197492423822E-02 -1.3520762156016617E-02 -1.3616100265951836E-02 -1.3711211085435951E-02 -1.3806093837214478E-02 -1.3900747594728983E-02 -1.3995171411653263E-02 -1.4089364442820414E-02 -1.4183325899861690E-02 -1.4277054946268519E-02 -1.4370550672510555E-02 -1.4463812187970613E-02 -1.4556838709426699E-02 -1.4649629477054713E-02 -1.4742183662505829E-02 -1.4834500386664127E-02 -1.4926578794449386E-02 -1.5018418080496788E-02 -1.5110017441334391E-02 -1.5201376053332327E-02 -1.5292493086115220E-02 -1.5383367723675040E-02 -1.5473999163761753E-02 -1.5564386607456024E-02 -1.5654529263620254E-02 -1.5744426339438952E-02 -1.5834077021985769E-02 -1.5923480489312362E-02 -1.6012635940620929E-02 -1.6101542601412968E-02 -1.6190199695570937E-02 -1.6278606436853877E-02 -1.6366762036864158E-02 -1.6454665710459091E-02 -1.6542316674407222E-02 -1.6629714151282223E-02 -1.6716857373144326E-02 -1.6803745573970234E-02 -1.6890377993930929E-02 -1.6976753875001575E-02 -1.7062872463944705E-02 -1.7148733011157873E-02 -1.7234334757097906E-02 -1.7319676921713670E-02 -1.7404758728467119E-02 -1.7489579440012372E-02 -1.7574138333366202E-02 -1.7658434678848690E-02 -1.7742467739933116E-02 -1.7826236779543547E-02 -1.7909741060585918E-02 -1.7992979845830339E-02 -1.8075952399301733E-02 -1.8158657985739030E-02 -1.8241095880892726E-02 -1.8323265375110420E-02 -1.8405165759266560E-02 -1.8486796323439952E-02 -1.8568156357163274E-02 -1.8649245148731917E-02 -1.8730061985565181E-02 -1.8810606159417344E-02 -1.8890876969713359E-02 -1.8970873717804981E-02 -1.9050595712088288E-02 -1.9130042262828235E-02 -1.9209212679306802E-02 -1.9288106269934126E-02 -1.9366722345272983E-02 -1.9445060221161749E-02 -1.9523119215908120E-02 -1.9600898661124175E-02 -1.9678397893421243E-02 -1.9755616243705556E-02 -1.9832553036710259E-02 -1.9909207599103741E-02 -1.9985579264786647E-02 -2.0061667370137242E-02 -2.0137471264199402E-02 -2.0212990302415478E-02 -2.0288223830782531E-02 -2.0363171182114143E-02 -2.0437831696465306E-02 -2.0512204747115098E-02 -2.0586289713840786E-02 -2.0660085957801368E-02 -2.0733592827280590E-02 -2.0806809681736264E-02 -2.0879735901667456E-02 -2.0952370866358531E-02 -2.1024713938098519E-02 -2.1096764474835012E-02 -2.1168521861793278E-02 -2.1239985508541788E-02 -2.1311154813654764E-02 -2.1382029147852793E-02 -2.1452607880927878E-02 -2.1522890406591777E-02 -2.1592876128801206E-02 -2.1662564451800159E-02 -2.1731954780159771E-02 -2.1801046520643515E-02 -2.1869839087451770E-02 -2.1938331894813441E-02 -2.2006524344791101E-02 -2.2074415832692026E-02 -2.2142005769158604E-02 -2.2209293587963821E-02 -2.2276278723970772E-02 -2.2342960609455748E-02 -2.2409338675181304E-02 -2.2475412342772470E-02 -2.2541181027144967E-02 -2.2606644155439639E-02 -2.2671801179070188E-02 -2.2736651552073880E-02 -2.2801194728606748E-02 -2.2865430162237441E-02 -2.2929357296499829E-02 -2.2992975565391444E-02 -2.3056284415893996E-02 -2.3119283329430522E-02 -2.3181971788201527E-02 -2.3244349240060684E-02 -2.3306415117584103E-02 -2.3368168881069830E-02 -2.3429610025029007E-02 -2.3490738038628854E-02 -2.3551552386333611E-02 -2.3612052529981109E-02 -2.3672237961031978E-02 -2.3732108188602635E-02 -2.3791662707691091E-02 -2.3850900990585958E-02 -2.3909822512098531E-02 -2.3968426768384083E-02 -2.4026713261905204E-02 -2.4084681501371760E-02 -2.4142331000298969E-02 -2.4199661263541037E-02 -2.4256671777958021E-02 -2.4313362034512169E-02 -2.4369731563798631E-02 -2.4425779910272699E-02 -2.4481506595568900E-02 -2.4536911118188478E-02 -2.4591992986244891E-02 -2.4646751737242283E-02 -2.4701186912761266E-02 -2.4755298048113366E-02 -2.4809084675499124E-02 -2.4862546330804060E-02 -2.4915682554819647E-02 -2.4968492888815096E-02 -2.5020976875051074E-02 -2.5073134056376407E-02 -2.5124963981388557E-02 -2.5176466202402551E-02 -2.5227640276808294E-02 -2.5278485770610194E-02 -2.5329002250029722E-02 -2.5379189278875947E-02 -2.5429046420233373E-02 -2.5478573239235188E-02 -2.5527769302715352E-02 -2.5576634180757910E-02 -2.5625167450722946E-02 -2.5673368692696111E-02 -2.5721237499034089E-02 -2.5768773466387274E-02 -2.5815976176276938E-02 -2.5862845193920563E-02 -2.5909380096297951E-02 -2.5955580497451353E-02 -2.6001446016140520E-02 -2.6046976253809053E-02 -2.6092170802774789E-02 -2.6137029260551409E-02 -2.6181551232061256E-02 -2.6225736326384440E-02 -2.6269584167075095E-02 -2.6313094380157030E-02 -2.6356266579296555E-02 -2.6399100369695231E-02 -2.6441595364661154E-02 -2.6483751192565182E-02 -2.6525567485605590E-02 -2.6567043888210278E-02 -2.6608180047930214E-02 -2.6648975597434024E-02 -2.6689430156174854E-02 -2.6729543354787593E-02 -2.6769314851635282E-02 -2.6808744307051824E-02 -2.6847831367481097E-02 -2.6886575673582682E-02 -2.6924976874276911E-02 -2.6963034628007525E-02 -2.7000748596442147E-02 -2.7038118449929979E-02 -2.7075143858816288E-02 -2.7111824477527784E-02 -2.7148159951912575E-02 -2.7184149952591528E-02 -2.7219794187118073E-02 -2.7255092354849676E-02 -2.7290044108480429E-02 -2.7324649092047487E-02 -2.7358907000366004E-02 -2.7392817565264575E-02 -2.7426380495068552E-02 -2.7459595451196608E-02 -2.7492462096227816E-02 -2.7524980129763708E-02 -2.7557149264199998E-02 -2.7588969209739515E-02 -2.7620439674500522E-02 -2.7651560369888348E-02 -2.7682331015947585E-02 -2.7712751331338270E-02 -2.7742821014215123E-02 -2.7772539754013649E-02 -2.7801907266910630E-02 -2.7830923301811770E-02 -2.7859587602017212E-02 -2.7887899885390002E-02 -2.7915859865837233E-02 -2.7943467272509563E-02 -2.7970721843804343E-02 -2.7997623323344371E-02 -2.8024171462838133E-02 -2.8050366011373049E-02 -2.8076206703166941E-02 -2.8101693269434198E-02 -2.8126825460020675E-02 -2.8151603039291324E-02 -2.8176025769048593E-02 -2.8200093405064405E-02 -2.8223805701959703E-02 -2.8247162412073829E-02 -2.8270163287844381E-02 -2.8292808104523174E-02 -2.8315096660325240E-02 -2.8337028740698697E-02 -2.8358604093763576E-02 -2.8379822467391590E-02 -2.8400683659446570E-02 -2.8421187491594127E-02 -2.8441333752689871E-02 -2.8461122188725027E-02 -2.8480552557608910E-02 -2.8499624670750592E-02 -2.8518338350098624E-02 -2.8536693399912005E-02 -2.8554689613102827E-02 -2.8572326784183717E-02 -2.8589604710690272E-02 -2.8606523195176748E-02 -2.8623082063125756E-02 -2.8639281145172647E-02 -2.8655120242084411E-02 -2.8670599129941288E-02 -2.8685717612410740E-02 -2.8700475555525733E-02 -2.8714872825039976E-02 -2.8728909230604883E-02 -2.8742584560518401E-02 -2.8755898633256238E-02 -2.8768851299704700E-02 -2.8781442409467541E-02 -2.8793671803770210E-02 -2.8805539321955172E-02 -2.8817044799982955E-02 -2.8828188072272033E-02 -2.8838968983785660E-02 -2.8849387394097158E-02 -2.8859443163275881E-02 -2.8869136149097356E-02 -2.8878466209011931E-02 -2.8887433203186017E-02 -2.8896036993643535E-02 -2.8904277441581552E-02 -2.8912154406627862E-02 -2.8919667752679512E-02 -2.8926817366591986E-02 -2.8933603141333322E-02 -2.8940024944682060E-02 -2.8946082622198534E-02 -2.8951776036049977E-02 -2.8957105089240060E-02 -2.8962069690318695E-02 -2.8966669745328962E-02 -2.8970905158496096E-02 -2.8974775811321941E-02 -2.8978281559396041E-02 -2.8981422273921125E-02 -2.8984197879082768E-02 -2.8986608307051472E-02 -2.8988653467220869E-02 -2.8990333256295017E-02 -2.8991647575307432E-02 -2.8992596331859286E-02 -2.8993179438188812E-02 -2.8993396823495710E-02 -2.8993248420237466E-02 -2.8992734144262608E-02 -2.8991853899442595E-02 -2.8990607602865648E-02 -2.8988995197424809E-02 -2.8987016625866883E-02 -2.8984671813512039E-02 -2.8981960680622927E-02 -2.8978883167252320E-02 -2.8975439232067780E-02 -2.8971628825375410E-02 -2.8967451874500630E-02 -2.8962908307366256E-02 -2.8957998083064245E-02 -2.8952721174573624E-02 -2.8947077539579803E-02 -2.8941067117094762E-02 -2.8934689850105087E-02 -2.8927945698475593E-02 -2.8920834626798772E-02 -2.8913356611714770E-02 -2.8905511636895344E-02 -2.8897299672131158E-02 -2.8888720665206844E-02 -2.8879774572309887E-02 -2.8870461395581457E-02 -2.8860781147562371E-02 -2.8850733802595840E-02 -2.8840319305523981E-02 -2.8829537619699776E-02 -2.8818388747856433E-02 -2.8806872696214327E-02 -2.8794989462509055E-02 -2.8782739041258866E-02 -2.8770121424143154E-02 -2.8757136600017188E-02 -2.8743784566137701E-02 -2.8730065342559310E-02 -2.8715978950876700E-02 -2.8701525393422456E-02 -2.8686704663379817E-02 -2.8671516763011721E-02 -2.8655961706365137E-02 -2.8640039513255167E-02 -2.8623750221102945E-02 -2.8607093868825473E-02 -2.8590070466183410E-02 -2.8572680004710076E-02 -2.8554922502028107E-02 -2.8536798019860341E-02 -2.8518306616430070E-02 -2.8499448312454607E-02 -2.8480223118910908E-02 -2.8460631070722543E-02 -2.8440672222600463E-02 -2.8420346625100661E-02 -2.8399654318237391E-02 -2.8378595342403366E-02 -2.8357169748840023E-02 -2.8335377593203457E-02 -2.8313218931416233E-02 -2.8290693819664980E-02 -2.8267802315615199E-02 -2.8244544480909427E-02 -2.8220920378618970E-02 -2.8196930077226706E-02 -2.8172573647915113E-02 -2.8147851152921708E-02 -2.8122762642088437E-02 -2.8097308175470948E-02 -2.8071487855571800E-02 -2.8045301792105536E-02 -2.8018750055674425E-02 -2.7991832690581742E-02 -2.7964549765191728E-02 -2.7936901391617992E-02 -2.7908887681996213E-02 -2.7880508724544607E-02 -2.7851764600454843E-02 -2.7822655401451693E-02 -2.7793181228525747E-02 -2.7763342177714066E-02 -2.7733138332523138E-02 -2.7702569780504907E-02 -2.7671636649126436E-02 -2.7640339081915818E-02 -2.7608677191460405E-02 -2.7576651055172284E-02 -2.7544260763021140E-02 -2.7511506449400727E-02 -2.7478388254391674E-02 -2.7444906289053553E-02 -2.7411060648730404E-02 -2.7376851450176733E-02 -2.7342278841695267E-02 -2.7307342971163155E-02 -2.7272043973749584E-02 -2.7236381980870701E-02 -2.7200357115807240E-02 -2.7163969496090543E-02 -2.7127219250201916E-02 -2.7090106527569064E-02 -2.7052631479413430E-02 -2.7014794253079535E-02 -2.6976594994873718E-02 -2.6938033854774474E-02 -2.6899110986207925E-02 -2.6859826541860282E-02 -2.6820180671951889E-02 -2.6780173527046081E-02 -2.6739805262069288E-02 -2.6699076034316305E-02 -2.6657986010177114E-02 -2.6616535366962138E-02 -2.6574724277823862E-02 -2.6532552899492051E-02 -2.6490021388040273E-02 -2.6447129926766753E-02 -2.6403878714959937E-02 -2.6360267933147680E-02 -2.6316297732113723E-02 -2.6271968269061960E-02 -2.6227279740584687E-02 -2.6182232353105794E-02 -2.6136826294187322E-02 -2.6091061736960710E-02 -2.6044938865237569E-02 -2.5998457885098629E-02 -2.5951619002254490E-02 -2.5904422403064474E-02 -2.5856868268031019E-02 -2.5808956804371293E-02 -2.5760688245884390E-02 -2.5712062809535551E-02 -2.5663080663777555E-02 -2.5613741975905220E-02 -2.5564046967956423E-02 -2.5513995888262302E-02 -2.5463588966614440E-02 -2.5412826408690335E-02 -2.5361708423009853E-02 -2.5310235233324336E-02 -2.5258407065447089E-02 -2.5206224128172257E-02 -2.5153686619963141E-02 -2.5100794767841019E-02 -2.5047548846477068E-02 -2.4993949121577961E-02 -2.4939995793660016E-02 -2.4885689046855737E-02 -2.4831029113306088E-02 -2.4776016264592957E-02 -2.4720650765257264E-02 -2.4664932861707584E-02 -2.4608862796498533E-02 -2.4552440801531114E-02 -2.4495667105318811E-02 -2.4438541954092150E-02 -2.4381065612845729E-02 -2.4323238344118654E-02 -2.4265060400362404E-02 -2.4206532033499387E-02 -2.4147653505009622E-02 -2.4088425081398732E-02 -2.4028847026306765E-02 -2.3968919599301173E-02 -2.3908643063783392E-02 -2.3848017698281290E-02 -2.3787043784091338E-02 -2.3725721589673218E-02 -2.3664051374924003E-02 -2.3602033402991780E-02 -2.3539667942887293E-02 -2.3476955270882734E-02 -2.3413895696450686E-02 -2.3350489537583455E-02 -2.3286737070627134E-02 -2.3222638535647031E-02 -2.3158194197337202E-02 -2.3093404380115121E-02 -2.3028269411384816E-02 -2.2962789579140309E-02 -2.2896965155258121E-02 -2.2830796424073149E-02 -2.2764283684002604E-02 -2.2697427240525522E-02 -2.2630227417975983E-02 -2.2562684540251416E-02 -2.2494798890603140E-02 -2.2426570730697096E-02 -2.2358000365858877E-02 -2.2289088165233163E-02 -2.2219834483949669E-02 -2.2150239597956745E-02 -2.2080303767768979E-02 -2.2010027318040679E-02 -2.1939410619453658E-02 -2.1868454014079278E-02 -2.1797157787626170E-02 -2.1725522229164185E-02 -2.1653547679842466E-02 -2.1581234497895240E-02 -2.1508583022063526E-02 -2.1435593572978282E-02 -2.1362266478189746E-02 -2.1288602083740289E-02 -2.1214600737000811E-02 -2.1140262772520121E-02 -2.1065588519296012E-02 -2.0990578309697316E-02 -2.0915232480113628E-02 -2.0839551372243591E-02 -2.0763535343876639E-02 -2.0687184756257210E-02 -2.0610499969833614E-02 -2.0533481344555075E-02 -2.0456129231308882E-02 -2.0378443966760487E-02 -2.0300425892666573E-02 -2.0222075377746573E-02 -2.0143392797801769E-02 -2.0064378520209557E-02 -1.9985032905953819E-02 -1.9905356315469983E-02 -1.9825349108111467E-02 -1.9745011646313496E-02 -1.9664344310250381E-02 -1.9583347486349548E-02 -1.9502021550727271E-02 -1.9420366869290634E-02 -1.9338383810374549E-02 -1.9256072749440637E-02 -1.9173434064988486E-02 -1.9090468148745463E-02 -1.9007175398774771E-02 -1.8923556204553087E-02 -1.8839610944448831E-02 -1.8755339998668612E-02 -1.8670743755742802E-02 -1.8585822606164527E-02 -1.8500576939238740E-02 -1.8415007143731094E-02 -1.8329113615121118E-02 -1.8242896759801803E-02 -1.8156356985458259E-02 -1.8069494699935271E-02 -1.7982310310526363E-02 -1.7894804211161835E-02 -1.7806976785010264E-02 -1.7718828431988538E-02 -1.7630359588496465E-02 -1.7541570690106222E-02 -1.7452462135128945E-02 -1.7363034308285522E-02 -1.7273287616652835E-02 -1.7183222490876244E-02 -1.7092839363210568E-02 -1.7002138666696701E-02 -1.6911120831202681E-02 -1.6819786255467043E-02 -1.6728135323138927E-02 -1.6636168454515432E-02 -1.6543886119784024E-02 -1.6451288779771218E-02 -1.6358376845229641E-02 -1.6265150717734017E-02 -1.6171610829491895E-02 -1.6077757633275808E-02 -1.5983591569585686E-02 -1.5889113056337785E-02 -1.5794322516952071E-02 -1.5699220413392858E-02 -1.5603807218476887E-02 -1.5508083375634835E-02 -1.5412049302842417E-02 -1.5315705428922903E-02 -1.5219052209270480E-02 -1.5122090102806933E-02 -1.5024819565244362E-02 -1.4927241050924066E-02 -1.4829355008042295E-02 -1.4731161877875293E-02 -1.4632662111704008E-02 -1.4533856191815160E-02 -1.4434744602348828E-02 -1.4335327786608275E-02 -1.4235606166155726E-02 -1.4135580194392677E-02 -1.4035250371009687E-02 -1.3934617188363559E-02 -1.3833681093031550E-02 -1.3732442522887614E-02 -1.3630901952687438E-02 -1.3529059883570237E-02 -1.3426916802375797E-02 -1.3324473167635284E-02 -1.3221729439064724E-02 -1.3118686098613523E-02 -1.3015343635804925E-02 -1.2911702535567771E-02 -1.2807763278595320E-02 -1.2703526342765815E-02 -1.2598992198890826E-02 -1.2494161319866312E-02 -1.2389034200081965E-02 -1.2283611343476433E-02 -1.2177893243472340E-02 -1.2071880380824072E-02 -1.1965573241405023E-02 -1.1858972329517607E-02 -1.1752078152217578E-02 -1.1644891203355193E-02 -1.1537411969255661E-02 -1.1429640941896546E-02 -1.1321578621927177E-02 -1.1213225511111683E-02 -1.1104582111705185E-02 -1.0995648926882474E-02 -1.0886426467683953E-02 -1.0776915251181851E-02 -1.0667115786823752E-02 -1.0557028568062817E-02 -1.0446654090571340E-02 -1.0335992872801110E-02 -1.0225045441316888E-02 -1.0113812312969038E-02 -1.0002293995050362E-02 -9.8904909994423796E-03 -9.7784038506298528E-03 -9.6660330748168707E-03 -9.5533791932488378E-03 -9.4404427249724088E-03 -9.3272241888903082E-03 -9.2137241036386961E-03 -9.0999429913345385E-03 -8.9858813855053267E-03 -8.8715398214211424E-03 -8.7569188227384579E-03 -8.6420189061525449E-03 -8.5268406013484632E-03 -8.4113844593060368E-03 -8.2956510269075953E-03 -8.1796408210808857E-03 -8.0633543525582795E-03 -7.9467921704982694E-03 -7.8299548552052210E-03 -7.7128429652459874E-03 -7.5954570101614211E-03 -7.4777974972441621E-03 -7.3598649580351675E-03 -7.2416599346878463E-03 -7.1231829920641717E-03 -7.0044347187405579E-03 -6.8854156841472317E-03 -6.7661263996381853E-03 -6.6465673725451145E-03 -6.5267391615319390E-03 -6.4066423514204489E-03 -6.2862775098958910E-03 -6.1656451810477454E-03 -6.0447459098736684E-03 -5.9235802501179545E-03 -5.8021487585359884E-03 -5.6804520000904250E-03 -5.5584905453176514E-03 -5.4362649610972666E-03 -5.3137758074235349E-03 -5.1910236413302644E-03 -5.0680090069610221E-03 -4.9447324468334464E-03 -4.8211945427874435E-03 -4.6973959105991153E-03 -4.5733371428480557E-03 -4.4490187758286703E-03 -4.3244413455435860E-03 -4.1996054378134803E-03 -4.0745116583352885E-03 -3.9491605791084489E-03 -3.8235527344731911E-03 -3.6976886805078790E-03 -3.5715690445071824E-03 -3.4451944592703409E-03 -3.3185654798852031E-03 -3.1916826199965670E-03 -3.0645464423624418E-03 -2.9371575808917736E-03 -2.8095166606253541E-03 -2.6816242470492089E-03 -2.5534808930530676E-03 -2.4250871812459924E-03 -2.2964437154716112E-03 -2.1675510954573588E-03 -2.0384099120263981E-03 -1.9090207546180894E-03 -1.7793842088513036E-03 -1.6495008599890153E-03 -1.5193713068733406E-03 -1.3889961608391226E-03 -1.2583760241730889E-03 -1.1275114752432396E-03 -9.9640309334407713E-04 -8.6505148900307472E-04 -7.3345728648459036E-04 -6.0162109539388614E-04 -4.6954350779703999E-04 -3.3722511474252621E-04 -2.0466650641961799E-04 -7.1868275604029409E-05 --6.1168959701078245E-05 --1.9444456683258510E-04 --3.2795792845378952E-04 --4.6170845123866868E-04 --5.9569554024347640E-04 --7.2991858585391776E-04 --8.6437697400953387E-04 --9.9907008810819599E-04 --1.1339973095355290E-03 --1.2691580215386275E-03 --1.4045516115841837E-03 --1.5401774658932792E-03 --1.6760349622184356E-03 --1.8121234752384511E-03 --1.9484423851961364E-03 --2.0849910777780362E-03 --2.2217689401795057E-03 --2.3587753636017130E-03 --2.4960097365588725E-03 --2.6334714233715723E-03 --2.7711597770033263E-03 --2.9090741659344452E-03 --3.0472139784314088E-03 --3.1855785965169718E-03 --3.3241673769401721E-03 --3.4629796732783599E-03 --3.6020148684752793E-03 --3.7412723633843330E-03 --3.8807515417465049E-03 --4.0204517591415226E-03 --4.1603723683547606E-03 --4.3005127226834359E-03 --4.4408721761589358E-03 --4.5814500967609464E-03 --4.7222458636134038E-03 --4.8632588502990895E-03 --5.0044884183596695E-03 --5.1459339274614038E-03 --5.2875947371419834E-03 --5.4294702066463923E-03 --5.5715596953328211E-03 --5.7138625626889806E-03 --5.8563781633500173E-03 --5.9991058390123763E-03 --6.1420449317908113E-03 --6.2851948095562918E-03 --6.4285548526957798E-03 --6.5721244232844461E-03 --6.7159028587959989E-03 --6.8598894996361511E-03 --7.0040837047895335E-03 --7.1484848360319295E-03 --7.2930922397774480E-03 --7.4379052521614279E-03 --7.5829232151290379E-03 --7.7281454813895416E-03 --7.8735714034261824E-03 --8.0192003286831508E-03 --8.1650316025797774E-03 --8.3110645675215609E-03 --8.4572985632786757E-03 --8.6037329327108975E-03 --8.7503670264443747E-03 --8.8972001940469080E-03 --9.0442317726890653E-03 --9.1914610944017691E-03 --9.3388874983065875E-03 --9.4865103314421620E-03 --9.6343289341751792E-03 --9.7823426263323465E-03 --9.9305507271154926E-03 --1.0078952588819733E-02 --1.0227547581061751E-02 --1.0376335047760412E-02 --1.0525314295985131E-02 --1.0674484637634284E-02 --1.0823845416702222E-02 --1.0973395983418475E-02 --1.1123135667441091E-02 --1.1273063783848535E-02 --1.1423179658374697E-02 --1.1573482637500486E-02 --1.1723972064188347E-02 --1.1874647251825918E-02 --1.2025507504828146E-02 --1.2176552152155592E-02 --1.2327780545140535E-02 --1.2479192023058323E-02 --1.2630785894365412E-02 --1.2782561465394223E-02 --1.2934518062997507E-02 --1.3086655022790439E-02 --1.3238971676248965E-02 --1.3391467349995079E-02 --1.3544141366941364E-02 --1.3696993039803870E-02 --1.3850021679899448E-02 --1.4003226608355249E-02 --1.4156607151707846E-02 --1.4310162629834505E-02 --1.4463892352579742E-02 --1.4617795630417903E-02 --1.4771871781520909E-02 --1.4926120126030661E-02 --1.5080539986694310E-02 --1.5235130688050796E-02 --1.5389891545945068E-02 --1.5544821859291708E-02 --1.5699920928259503E-02 --1.5855188073768504E-02 --1.6010622623882448E-02 --1.6166223904999902E-02 --1.6321991241844414E-02 --1.6477923942584110E-02 --1.6634021273031530E-02 --1.6790282500256559E-02 --1.6946706957838793E-02 --1.7103294009871435E-02 --1.7260042988937952E-02 --1.7416953187952392E-02 --1.7574023894914768E-02 --1.7731254390514050E-02 --1.7888643957834807E-02 --1.8046191927280835E-02 --1.8203897657820552E-02 --1.8361760467151673E-02 --1.8519779605482626E-02 --1.8677954332409531E-02 --1.8836283981386967E-02 --1.8994767904342832E-02 --1.9153405410286369E-02 --1.9312195773753527E-02 --1.9471138277389034E-02 --1.9630232223566330E-02 --1.9789476917257916E-02 --1.9948871665936035E-02 --2.0108415777586191E-02 --2.0268108555277910E-02 --2.0427949297006618E-02 --2.0587937300929414E-02 --2.0748071867049876E-02 --2.0908352294207365E-02 --2.1068777871231591E-02 --2.1229347881998359E-02 --2.1390061624216420E-02 --2.1550918414270356E-02 --2.1711917562370561E-02 --2.1873058351942594E-02 --2.2034340061096124E-02 --2.2195761982685153E-02 --2.2357323419124754E-02 --2.2519023670156832E-02 --2.2680862030906329E-02 --2.2842837796254910E-02 --2.3004950263705387E-02 --2.3167198730471242E-02 --2.3329582479227964E-02 --2.3492100780236076E-02 --2.3654752918449914E-02 --2.3817538213542589E-02 --2.3980455983254129E-02 --2.4143505502131048E-02 --2.4306686027725802E-02 --2.4469996847867381E-02 --2.4633437283827130E-02 --2.4797006644856789E-02 --2.4960704199846973E-02 --2.5124529212131298E-02 --2.5288480966220203E-02 --2.5452558757957749E-02 --2.5616761885983868E-02 --2.5781089652934113E-02 --2.5945541353251646E-02 --2.6110116248555530E-02 --2.6274813595114365E-02 --2.6439632690702985E-02 --2.6604572861960107E-02 --2.6769633413851721E-02 --2.6934813610528432E-02 --2.7100112714420425E-02 --2.7265530004109997E-02 --2.7431064763465188E-02 --2.7596716279521007E-02 --2.7762483842143623E-02 --2.7928366740056290E-02 --2.8094364259545011E-02 --2.8260475686485660E-02 --2.8426700308679616E-02 --2.8593037414142909E-02 --2.8759486278239561E-02 --2.8926046161579535E-02 --2.9092716332816106E-02 --2.9259496090048902E-02 --2.9426384735227268E-02 --2.9593381552720913E-02 --2.9760485816630412E-02 --2.9927696804796389E-02 --3.0095013801137455E-02 --3.0262436086322911E-02 --3.0429962926168116E-02 --3.0597593583994005E-02 --3.0765327348832989E-02 --3.0933163528756275E-02 --3.1101101416489103E-02 --3.1269140273978327E-02 --3.1437279364015025E-02 --3.1605517976881096E-02 --3.1773855411088979E-02 --3.1942290935721429E-02 --3.2110823791418185E-02 --3.2279453238904340E-02 --3.2448178594663930E-02 --3.2616999176827130E-02 --3.2785914248777033E-02 --3.2954923048715612E-02 --3.3124024846570503E-02 --3.3293218952141698E-02 --3.3462504665012251E-02 --3.3631881241851701E-02 --3.3801347932850334E-02 --3.3970904021742104E-02 --3.4140548812431996E-02 --3.4310281586249797E-02 --3.4480101587840394E-02 --3.4650008069956703E-02 --3.4820000339592261E-02 --3.4990077715918957E-02 --3.5160239467695732E-02 --3.5330484823533952E-02 --3.5500813036981597E-02 --3.5671223416934794E-02 --3.5841715272114938E-02 --3.6012287868475754E-02 --3.6182940456093042E-02 --3.6353672303911531E-02 --3.6524482700333573E-02 --3.6695370929949622E-02 --3.6866336264998342E-02 --3.7037377976403309E-02 --3.7208495344572774E-02 --3.7379687654023698E-02 --3.7550954169965942E-02 --3.7722294132061747E-02 --3.7893706796635084E-02 --3.8065191489289399E-02 --3.8236747545015874E-02 --3.8408374223078648E-02 --3.8580070733296751E-02 --3.8751836319404522E-02 --3.8923670285332564E-02 --3.9095571935714543E-02 --3.9267540550616688E-02 --3.9439575402073927E-02 --3.9611675759366277E-02 --3.9783840889380223E-02 --3.9956070060275434E-02 --4.0128362543757651E-02 --4.0300717612742745E-02 --4.0473134547053376E-02 --4.0645612629033184E-02 --4.0818151138835086E-02 --4.0990749354243142E-02 --4.1163406549870767E-02 --4.1336121992032335E-02 --4.1508894946447807E-02 --4.1681724690300855E-02 --4.1854610506599527E-02 --4.2027551670773627E-02 --4.2200547447625754E-02 --4.2373597104373668E-02 --4.2546699922173629E-02 --4.2719855185182849E-02 --4.2893062175212271E-02 --4.3066320172227709E-02 --4.3239628447900302E-02 --4.3412986259076157E-02 --4.3586392864887087E-02 --4.3759847546745098E-02 --4.3933349593144308E-02 --4.4106898291478611E-02 --4.4280492928077703E-02 --4.4454132781121501E-02 --4.4627817109813568E-02 --4.4801545172014068E-02 --4.4975316238283054E-02 --4.5149129584907126E-02 --4.5322984499605465E-02 --4.5496880283454534E-02 --4.5670816228136964E-02 --4.5844791593770591E-02 --4.6018805634829199E-02 --4.6192857615140526E-02 --4.6366946803928298E-02 --4.6541072481311861E-02 --4.6715233943931872E-02 --4.6889430485906082E-02 --4.7063661385933805E-02 --4.7237925917510581E-02 --4.7412223342542824E-02 --4.7586552914375829E-02 --4.7760913908310151E-02 --4.7935305643467159E-02 --4.8109727433429693E-02 --4.8284178532438993E-02 --4.8458658174764677E-02 --4.8633165624649748E-02 --4.8807700175166037E-02 --4.8982261120896722E-02 --4.9156847757911161E-02 --4.9331459378835762E-02 --4.9506095249866933E-02 --4.9680754625184197E-02 --4.9855436779937375E-02 --5.0030141015467683E-02 --5.0204866625386646E-02 --5.0379612872147553E-02 --5.0554379014113471E-02 --5.0729164340702924E-02 --5.0903968159892267E-02 --5.1078789759305500E-02 --5.1253628393695877E-02 --5.1428483322635353E-02 --5.1603353842708734E-02 --5.1778239259473550E-02 --5.1953138857027847E-02 --5.2128051902435593E-02 --5.2302977672914031E-02 --5.2477915468338313E-02 --5.2652864586490995E-02 --5.2827824296427198E-02 --5.3002793856797542E-02 --5.3177772544994402E-02 --5.3352759657614823E-02 --5.3527754490686898E-02 --5.3702756336919774E-02 --5.3877764486475042E-02 --5.4052778215219026E-02 --5.4227796791951152E-02 --5.4402819497216155E-02 --5.4577845627264837E-02 --5.4752874476333306E-02 --5.4927905328255679E-02 --5.5102937464851683E-02 --5.5277970175605103E-02 --5.5453002754755704E-02 --5.5628034487550618E-02 --5.5803064643978627E-02 --5.5978092499398079E-02 --5.6153117364383213E-02 --5.6328138558270464E-02 --5.6503155368976980E-02 --5.6678167057883151E-02 --5.6853172896149801E-02 --5.7028172179149642E-02 --5.7203164206926026E-02 --5.7378148290581833E-02 --5.7553123744179320E-02 --5.7728089845683325E-02 --5.7903045833803228E-02 --5.8077990970297255E-02 --5.8252924591657110E-02 --5.8427846042092543E-02 --5.8602754613211905E-02 --5.8777649568443543E-02 --5.8952530177720300E-02 --5.9127395720652426E-02 --5.9302245487767961E-02 --5.9477078810873031E-02 --5.9651895027834224E-02 --5.9826693426541233E-02 --6.0001473260168046E-02 --6.0176233796326278E-02 --6.0350974330584589E-02 --6.0525694167035446E-02 --6.0700392640587852E-02 --6.0875069092836812E-02 --6.1049722803338285E-02 --6.1224352996015655E-02 --6.1398958936153179E-02 --6.1573539993236989E-02 --6.1748095537835043E-02 --6.1922624840750340E-02 --6.2097127130771347E-02 --6.2271601689291398E-02 --6.2446047858908491E-02 --6.2620464972522924E-02 --6.2794852322178019E-02 --6.2969209192159786E-02 --6.3143534872611970E-02 --6.3317828657217148E-02 --6.3492089859080877E-02 --6.3666317820513699E-02 --6.3840511872060607E-02 --6.4014671285274022E-02 --6.4188795319143954E-02 --6.4362883279748095E-02 --6.4536934507778990E-02 --6.4710948324699355E-02 --6.4884924013250717E-02 --6.5058860858867723E-02 --6.5232758189304407E-02 --6.5406615345484725E-02 --6.5580431634962591E-02 --6.5754206333404036E-02 --6.5927938733250757E-02 --6.6101628173706933E-02 --6.6275273996147771E-02 --6.6448875503644464E-02 --6.6622431981468958E-02 --6.6795942723715016E-02 --6.6969407035565809E-02 --6.7142824230224607E-02 --6.7316193646663594E-02 --6.7489514626450225E-02 --6.7662786482833553E-02 --6.7836008511792001E-02 --6.8009180016102427E-02 --6.8182300309998264E-02 --6.8355368710667538E-02 --6.8528384545238311E-02 --6.8701347142272065E-02 --6.8874255812303956E-02 --6.9047109851675087E-02 --6.9219908571261410E-02 --6.9392651313355827E-02 --6.9565337419656870E-02 --6.9737966205741506E-02 --6.9910536977580304E-02 --7.0083049052892185E-02 --7.0255501761364900E-02 --7.0427894429798549E-02 --7.0600226376184932E-02 --7.0772496917446845E-02 --7.0944705376237871E-02 --7.1116851077953014E-02 --7.1288933350308267E-02 --7.1460951524147068E-02 --7.1632904929706420E-02 --7.1804792895083083E-02 --7.1976614747820647E-02 --7.2148369817571681E-02 --7.2320057435166882E-02 --7.2491676926068865E-02 --7.2663227606810807E-02 --7.2834708797779896E-02 --7.3006119843692957E-02 --7.3177460095376318E-02 --7.3348728884841632E-02 --7.3519925528282182E-02 --7.3691049347376927E-02 --7.3862099677501986E-02 --7.4033075856785646E-02 --7.4203977230983653E-02 --7.4374803148352348E-02 --7.4545552946498769E-02 --7.4716225951528104E-02 --7.4886821494824146E-02 --7.5057338925590966E-02 --7.5227777593415063E-02 --7.5398136824057230E-02 --7.5568415930962710E-02 --7.5738614251247699E-02 --7.5908731155405432E-02 --7.6078766006590248E-02 --7.6248718130308230E-02 --7.6418586844640007E-02 --7.6588371493753291E-02 --7.6758071439689268E-02 --7.6927686038992318E-02 --7.7097214637847314E-02 --7.7266656579336082E-02 --7.7436011197236740E-02 --7.7605277823063146E-02 --7.7774455807196219E-02 --7.7943544516813110E-02 --7.8112543313374277E-02 --7.8281451543773833E-02 --7.8450268552639077E-02 --7.8618993685237726E-02 --7.8787626287163834E-02 --7.8956165710863571E-02 --7.9124611316725754E-02 --7.9292962465308384E-02 --7.9461218516967635E-02 --7.9629378830727737E-02 --7.9797442755175460E-02 --7.9965409633072707E-02 --8.0133278819857323E-02 --8.0301049690095494E-02 --8.0468721613685970E-02 --8.0636293935237524E-02 --8.0803765994375817E-02 --8.0971137157278036E-02 --8.1138406809471347E-02 --8.1305574323228463E-02 --8.1472639044569223E-02 --8.1639600320549663E-02 --8.1806457522408060E-02 --8.1973210029491650E-02 --8.2139857217080128E-02 --8.2306398456548413E-02 --8.2472833112849891E-02 --8.2639160535460637E-02 --8.2805380074019427E-02 --8.2971491099842962E-02 --8.3137492994120807E-02 --8.3303385137585867E-02 --8.3469166910412021E-02 --8.3634837689182118E-02 --8.3800396839138536E-02 --8.3965843723807929E-02 --8.4131177716333327E-02 --8.4296398195545061E-02 --8.4461504539597040E-02 --8.4626496125620218E-02 --8.4791372331048179E-02 --8.4956132536068374E-02 --8.5120776121404826E-02 --8.5285302467186339E-02 --8.5449710953002952E-02 --8.5614000957381184E-02 --8.5778171856995766E-02 --8.5942223030916018E-02 --8.6106153875530445E-02 --8.6269963792753909E-02 --8.6433652165418859E-02 --8.6597218357068864E-02 --8.6760661741353329E-02 --8.6923981722275917E-02 --8.7087177706323446E-02 --8.7250249079849559E-02 --8.7413195219238488E-02 --8.7576015506498156E-02 --8.7738709331160306E-02 --8.7901276087424568E-02 --8.8063715185309532E-02 --8.8226026035994567E-02 --8.8388208024807721E-02 --8.8550260520539090E-02 --8.8712182910058626E-02 --8.8873974611478501E-02 --8.9035635040807248E-02 --8.9197163590150494E-02 --8.9358559644833371E-02 --8.9519822601404911E-02 --8.9680951865729136E-02 --8.9841946842929968E-02 --9.0002806936200080E-02 --9.0163531548715953E-02 --9.0324120086601872E-02 --9.0484571956982604E-02 --9.0644886566315697E-02 --9.0805063320360965E-02 --9.0965101624173955E-02 --9.1125000881370835E-02 --9.1284760496733452E-02 --9.1444379889707397E-02 --9.1603858487097872E-02 --9.1763195703748079E-02 --9.1922390937891674E-02 --9.2081443590799145E-02 --9.2240353081101054E-02 --9.2399118831033036E-02 --9.2557740257352181E-02 --9.2716216772999183E-02 --9.2874547794061416E-02 --9.3032732742652863E-02 --9.3190771041371620E-02 --9.3348662113069761E-02 --9.3506405380577515E-02 --9.3664000267993111E-02 --9.3821446200495762E-02 --9.3978742599528237E-02 --9.4135888877971238E-02 --9.4292884450118547E-02 --9.4449728750406595E-02 --9.4606421221576836E-02 --9.4762961299578341E-02 --9.4919348412581622E-02 --9.5075581986595409E-02 --9.5231661442733748E-02 --9.5387586202521177E-02 --9.5543355702681965E-02 --9.5698969388307922E-02 --9.5854426699582565E-02 --9.6009727069407996E-02 --9.6164869930955313E-02 --9.6319854721740206E-02 --9.6474680880278274E-02 --9.6629347845674327E-02 --9.6783855057402446E-02 --9.6938201955860212E-02 --9.7092387983440873E-02 --9.7246412582586664E-02 --9.7400275195792307E-02 --9.7553975265665144E-02 --9.7707512240085545E-02 --9.7860885571893805E-02 --9.8014094710893007E-02 --9.8167139099091624E-02 --9.8320018178602878E-02 --9.8472731403007482E-02 --9.8625278230873345E-02 --9.8777658115167172E-02 --9.8929870502052195E-02 --9.9081914839868460E-02 --9.9233790586205253E-02 --9.9385497200713019E-02 --9.9537034146202102E-02 --9.9688400887163714E-02 --9.9839596880280865E-02 --9.9990621570028027E-02 --1.0014147440597544E-01 --1.0029215486622065E-01 --1.0044266243490450E-01 --1.0059299656860210E-01 --1.0074315670247305E-01 --1.0089314228871134E-01 --1.0104295281593352E-01 --1.0119258777343060E-01 --1.0134204662852557E-01 --1.0149132884031875E-01 --1.0164043387099936E-01 --1.0178936118588679E-01 --1.0193811025557398E-01 --1.0208668056493869E-01 --1.0223507159890330E-01 --1.0238328282442044E-01 --1.0253131369991930E-01 --1.0267916370076456E-01 --1.0282683232443748E-01 --1.0297431906306101E-01 --1.0312162338468167E-01 --1.0326874475343345E-01 --1.0341568265276524E-01 --1.0356243657835379E-01 --1.0370900602045978E-01 --1.0385539046005166E-01 --1.0400158937845161E-01 --1.0414760226377512E-01 --1.0429342860571088E-01 --1.0443906788846236E-01 --1.0458451959168463E-01 --1.0472978320315314E-01 --1.0487485822903324E-01 --1.0501974417541064E-01 --1.0516444053299287E-01 --1.0530894678643754E-01 --1.0545326242649426E-01 --1.0559738695046185E-01 --1.0574131985637339E-01 --1.0588506064385396E-01 --1.0602860881325911E-01 --1.0617196387031880E-01 --1.0631512532343261E-01 --1.0645809267859344E-01 --1.0660086543851906E-01 --1.0674344310478769E-01 --1.0688582517606934E-01 --1.0702801115113139E-01 --1.0717000054072084E-01 --1.0731179286364692E-01 --1.0745338763378683E-01 --1.0759478435606243E-01 --1.0773598253676459E-01 --1.0787698169492141E-01 --1.0801778135318175E-01 --1.0815838102742184E-01 --1.0829878022752690E-01 --1.0843897846702796E-01 --1.0857897526876895E-01 --1.0871877015558086E-01 --1.0885836264189083E-01 --1.0899775223896328E-01 --1.0913693847420770E-01 --1.0927592089345081E-01 --1.0941469903310408E-01 --1.0955327239759688E-01 --1.0969164048831860E-01 --1.0982980283865651E-01 --1.0996775899962669E-01 --1.1010550851052039E-01 --1.1024305089318315E-01 --1.1038038567065199E-01 --1.1051751237729844E-01 --1.1065443055010814E-01 --1.1079113972336860E-01 --1.1092763942940002E-01 --1.1106392920598950E-01 --1.1120000860163864E-01 --1.1133587716402600E-01 --1.1147153443026024E-01 --1.1160697993392583E-01 --1.1174221321397045E-01 --1.1187723381437568E-01 --1.1201204128040147E-01 --1.1214663516030328E-01 --1.1228101500289377E-01 --1.1241518035873560E-01 --1.1254913077908615E-01 --1.1268286581492333E-01 --1.1281638501692064E-01 --1.1294968793511186E-01 --1.1308277411786366E-01 --1.1321564311451456E-01 --1.1334829448964404E-01 --1.1348072781666609E-01 --1.1361294265632665E-01 --1.1374493854942697E-01 --1.1387671504118421E-01 --1.1400827170489107E-01 --1.1413960812037396E-01 --1.1427072384962612E-01 --1.1440161844086179E-01 --1.1453229145314059E-01 --1.1466274246858761E-01 --1.1479297106856166E-01 --1.1492297681367487E-01 --1.1505275925750245E-01 --1.1518231797146082E-01 --1.1531165254479614E-01 --1.1544076255936593E-01 --1.1556964757534882E-01 --1.1569830715244404E-01 --1.1582674087698740E-01 --1.1595494834785273E-01 --1.1608292914837520E-01 --1.1621068284178912E-01 --1.1633820899661756E-01 --1.1646550720548830E-01 --1.1659257706513265E-01 --1.1671941815886505E-01 --1.1684603006148664E-01 --1.1697241235491905E-01 --1.1709856463332097E-01 --1.1722448649049524E-01 --1.1735017751351080E-01 --1.1747563728788642E-01 --1.1760086540867006E-01 --1.1772586147872055E-01 --1.1785062509736392E-01 --1.1797515585589047E-01 --1.1809945334582934E-01 --1.1822351716785813E-01 --1.1834734692600156E-01 --1.1847094221907445E-01 --1.1859430264035803E-01 --1.1871742778933896E-01 --1.1884031728442927E-01 --1.1896297074477173E-01 --1.1908538776693485E-01 --1.1920756793606686E-01 --1.1932951085670936E-01 --1.1945121616022715E-01 --1.1957268347306947E-01 --1.1969391239568393E-01 --1.1981490252383459E-01 --1.1993565347411896E-01 --1.2005616487714736E-01 --1.2017643635566304E-01 --1.2029646751802434E-01 --1.2041625797397491E-01 --1.2053580734859666E-01 --1.2065511527129209E-01 --1.2077418136197064E-01 --1.2089300523222520E-01 --1.2101158650212421E-01 --1.2112992481234644E-01 --1.2124801980401656E-01 --1.2136587110160992E-01 --1.2148347832273161E-01 --1.2160084109347545E-01 --1.2171795904958875E-01 --1.2183483182734373E-01 --1.2195145906329442E-01 --1.2206784039365413E-01 --1.2218397545176674E-01 --1.2229986386944722E-01 --1.2241550528512792E-01 --1.2253089934700412E-01 --1.2264604570167567E-01 --1.2276094398632913E-01 --1.2287559383646345E-01 --1.2298999489892777E-01 --1.2310414682869462E-01 --1.2321804927520699E-01 --1.2333170187716093E-01 --1.2344510427567638E-01 --1.2355825613249155E-01 --1.2367115711539606E-01 --1.2378380687229334E-01 --1.2389620503254076E-01 --1.2400835123978728E-01 --1.2412024517529974E-01 --1.2423188652130274E-01 --1.2434327492446225E-01 --1.2445441001602127E-01 --1.2456529145423012E-01 --1.2467591892998833E-01 --1.2478629212481616E-01 --1.2489641068296749E-01 --1.2500627424413074E-01 --1.2511588248167765E-01 --1.2522523508874145E-01 --1.2533433174575456E-01 --1.2544317211301256E-01 --1.2555175585083156E-01 --1.2566008262771833E-01 --1.2576815211507072E-01 --1.2587596399472983E-01 --1.2598351795650875E-01 --1.2609081368378117E-01 --1.2619785084654289E-01 --1.2630462911461185E-01 --1.2641114816689450E-01 --1.2651740768594155E-01 --1.2662340736236743E-01 --1.2672914689478085E-01 --1.2683462597474865E-01 --1.2693984427427218E-01 --1.2704480146457559E-01 --1.2714949723747326E-01 --1.2725393129474535E-01 --1.2735810333847189E-01 --1.2746201307105906E-01 --1.2756566019125354E-01 --1.2766904438494281E-01 --1.2777216533628383E-01 --1.2787502274303739E-01 --1.2797761631151716E-01 --1.2807994574590303E-01 --1.2818201074666644E-01 --1.2828381101396261E-01 --1.2838534624842826E-01 --1.2848661615141418E-01 --1.2858762043472061E-01 --1.2868835881867904E-01 --1.2878883102045247E-01 --1.2888903674988622E-01 --1.2898897571489903E-01 --1.2908864761761835E-01 --1.2918805215836299E-01 --1.2928718905107389E-01 --1.2938605802410494E-01 --1.2948465880541996E-01 --1.2958299112003252E-01 --1.2968105469153068E-01 --1.2977884923610661E-01 --1.2987637446623046E-01 --1.2997363010123253E-01 --1.3007061586988133E-01 --1.3016733150065951E-01 --1.3026377671857969E-01 --1.3035995124869698E-01 --1.3045585482754291E-01 --1.3055148719927812E-01 --1.3064684809993424E-01 --1.3074193725094943E-01 --1.3083675437532799E-01 --1.3093129921204860E-01 --1.3102557150504940E-01 --1.3111957099662205E-01 --1.3121329742761614E-01 --1.3130675054026136E-01 --1.3139993008019085E-01 --1.3149283579171933E-01 --1.3158546740708124E-01 --1.3167782465417924E-01 --1.3176990728442201E-01 --1.3186171507568825E-01 --1.3195324779631207E-01 --1.3204450518113636E-01 --1.3213548696030350E-01 --1.3222619288067486E-01 --1.3231662269840905E-01 --1.3240677617314847E-01 --1.3249665306948741E-01 --1.3258625315338848E-01 --1.3267557619500003E-01 --1.3276462196409100E-01 --1.3285339021132811E-01 --1.3294188067375157E-01 --1.3303009310210401E-01 --1.3311802727364566E-01 --1.3320568296850052E-01 --1.3329305996655982E-01 --1.3338015804698111E-01 --1.3346697697637652E-01 --1.3355351650972802E-01 --1.3363977640945904E-01 --1.3372575645762494E-01 --1.3381145643840331E-01 --1.3389687612977730E-01 --1.3398201530701140E-01 --1.3406687374893603E-01 --1.3415145123867731E-01 --1.3423574755833745E-01 --1.3431976248592337E-01 --1.3440349579947425E-01 --1.3448694728644783E-01 --1.3457011673981303E-01 --1.3465300395055971E-01 --1.3473560870652551E-01 --1.3481793079607662E-01 --1.3489997001124412E-01 --1.3498172614505813E-01 --1.3506319899086733E-01 --1.3514438834227366E-01 --1.3522529399569197E-01 --1.3530591575324161E-01 --1.3538625341739011E-01 --1.3546630678878116E-01 --1.3554607566739751E-01 --1.3562555985397040E-01 --1.3570475914997637E-01 --1.3578367336025390E-01 --1.3586230229854057E-01 --1.3594064577834442E-01 --1.3601870359975354E-01 --1.3609647555677001E-01 --1.3617396145891325E-01 --1.3625116113554220E-01 --1.3632807441323361E-01 --1.3640470110425654E-01 --1.3648104101838565E-01 --1.3655709397313756E-01 --1.3663285979081932E-01 --1.3670833828858137E-01 --1.3678352927495793E-01 --1.3685843256398708E-01 --1.3693304799967548E-01 --1.3700737543292574E-01 --1.3708141468287149E-01 --1.3715516554286353E-01 --1.3722862782654685E-01 --1.3730180139295467E-01 --1.3737468610161863E-01 --1.3744728177771742E-01 --1.3751958823356120E-01 --1.3759160529749542E-01 --1.3766333281475360E-01 --1.3773477062814768E-01 --1.3780591857136013E-01 --1.3787677647793203E-01 --1.3794734419437393E-01 --1.3801762157370967E-01 --1.3808760846173632E-01 --1.3815730469437665E-01 --1.3822671010953153E-01 --1.3829582455532768E-01 --1.3836464788274541E-01 --1.3843317994816404E-01 --1.3850142061151102E-01 --1.3856936972659484E-01 --1.3863702713634715E-01 --1.3870439268620444E-01 --1.3877146624002057E-01 --1.3883824766684108E-01 --1.3890473682412957E-01 --1.3897093355932999E-01 --1.3903683772698855E-01 --1.3910244919879083E-01 --1.3916776784745816E-01 --1.3923279353633269E-01 --1.3929752612503432E-01 --1.3936196547948845E-01 --1.3942611147268805E-01 --1.3948996397673100E-01 --1.3955352285985706E-01 --1.3961678799016808E-01 --1.3967975924141815E-01 --1.3974243649050130E-01 --1.3980481961578714E-01 --1.3986690849773056E-01 --1.3992870301587743E-01 --1.3999020304540652E-01 --1.4005140846131267E-01 --1.4011231915105352E-01 --1.4017293501090566E-01 --1.4023325592759617E-01 --1.4029328176955441E-01 --1.4035301240858047E-01 --1.4041244774593198E-01 --1.4047158769182383E-01 --1.4053043213520205E-01 --1.4058898094541408E-01 --1.4064723400540033E-01 --1.4070519123339670E-01 --1.4076285254849852E-01 --1.4082021783651433E-01 --1.4087728696897156E-01 --1.4093405983899493E-01 --1.4099053636549977E-01 --1.4104671646463515E-01 --1.4110260003854869E-01 --1.4115818698650895E-01 --1.4121347720747290E-01 --1.4126847060036654E-01 --1.4132316707282153E-01 --1.4137756654586672E-01 --1.4143166893838738E-01 --1.4148547415483784E-01 --1.4153898209676122E-01 --1.4159219268077747E-01 --1.4164510583494588E-01 --1.4169772148198304E-01 --1.4175003953329796E-01 --1.4180205990007644E-01 --1.4185378250005595E-01 --1.4190520725367656E-01 --1.4195633408813754E-01 --1.4200716293726837E-01 --1.4205769373219590E-01 --1.4210792639614264E-01 --1.4215786085101167E-01 --1.4220749701832047E-01 --1.4225683481978810E-01 --1.4230587419093185E-01 --1.4235461508474537E-01 --1.4240305744761228E-01 --1.4245120119869850E-01 --1.4249904625340140E-01 --1.4254659255147822E-01 --1.4259384004784811E-01 --1.4264078869065314E-01 --1.4268743841651046E-01 --1.4273378916119339E-01 --1.4277984086143608E-01 --1.4282559345532272E-01 --1.4287104689788471E-01 --1.4291620115782586E-01 --1.4296105619252636E-01 --1.4300561193422984E-01 --1.4304986831599628E-01 --1.4309382529644724E-01 --1.4313748284366726E-01 --1.4318084091245431E-01 --1.4322389944370587E-01 --1.4326665838664407E-01 --1.4330911771579127E-01 --1.4335127740755502E-01 --1.4339313741596699E-01 --1.4343469768395120E-01 --1.4347595816902214E-01 --1.4351691884848716E-01 --1.4355757969784150E-01 --1.4359794068036028E-01 --1.4363800175738917E-01 --1.4367776290144380E-01 --1.4371722409241086E-01 --1.4375638530214752E-01 --1.4379524648819156E-01 --1.4383380761205025E-01 --1.4387206866241711E-01 --1.4391002963564992E-01 --1.4394769051144274E-01 --1.4398505125514391E-01 --1.4402211183649022E-01 --1.4405887223628319E-01 --1.4409533243848899E-01 --1.4413149243789122E-01 --1.4416735223332433E-01 --1.4420291180966330E-01 --1.4423817113624138E-01 --1.4427313018926805E-01 --1.4430778896813881E-01 --1.4434214747539686E-01 --1.4437620570169984E-01 --1.4440996363143421E-01 --1.4444342125917506E-01 --1.4447657859420288E-01 --1.4450943564188562E-01 --1.4454199238698204E-01 --1.4457424881091449E-01 --1.4460620491955714E-01 --1.4463786073606491E-01 --1.4466921627207377E-01 --1.4470027151697307E-01 --1.4473102646157354E-01 --1.4476148111739218E-01 --1.4479163550255797E-01 --1.4482148962682670E-01 --1.4485104349228550E-01 --1.4488029710557013E-01 --1.4490925048505973E-01 --1.4493790365079104E-01 --1.4496625662164694E-01 --1.4499430941589050E-01 --1.4502206204727044E-01 --1.4504951452418491E-01 --1.4507666686004089E-01 --1.4510351908537661E-01 --1.4513007123306748E-01 --1.4515632332389047E-01 --1.4518227537172235E-01 --1.4520792739805496E-01 --1.4523327943613126E-01 --1.4525833151917630E-01 --1.4528308367578993E-01 --1.4530753593366219E-01 --1.4533168832479762E-01 --1.4535554088447009E-01 --1.4537909364620891E-01 --1.4540234663983240E-01 --1.4542529989666414E-01 --1.4544795345906472E-01 --1.4547030737329100E-01 --1.4549236168233567E-01 --1.4551411642599710E-01 --1.4553557164223596E-01 --1.4555672736442415E-01 --1.4557758362806095E-01 --1.4559814049100167E-01 --1.4561839802128618E-01 --1.4563835626787722E-01 --1.4565801525560415E-01 --1.4567737501850433E-01 --1.4569643562789575E-01 --1.4571519716057160E-01 --1.4573365966333449E-01 --1.4575182316467056E-01 --1.4576968771462123E-01 --1.4578725339878751E-01 --1.4580452029691565E-01 --1.4582148844581569E-01 --1.4583815787220172E-01 --1.4585452864079768E-01 --1.4587060084686376E-01 --1.4588637456927428E-01 --1.4590184985007737E-01 --1.4591702673244331E-01 --1.4593190529586839E-01 --1.4594648563326124E-01 --1.4596076781961062E-01 --1.4597475191125811E-01 --1.4598843796960223E-01 --1.4600182607251577E-01 --1.4601491630028512E-01 --1.4602770872868345E-01 --1.4604020343128066E-01 --1.4605240048375709E-01 --1.4606429996461406E-01 --1.4607590195365625E-01 --1.4608720653457771E-01 --1.4609821379246360E-01 --1.4610892381736271E-01 --1.4611933670256202E-01 --1.4612945253408532E-01 --1.4613927138514937E-01 --1.4614879333092479E-01 --1.4615801846246615E-01 --1.4616694687583795E-01 --1.4617557866663267E-01 --1.4618391393005070E-01 --1.4619195276105063E-01 --1.4619969525394089E-01 --1.4620714150359163E-01 --1.4621429160876717E-01 --1.4622114566984074E-01 --1.4622770378533848E-01 --1.4623396605172920E-01 --1.4623993256795748E-01 --1.4624560344053372E-01 --1.4625097877717563E-01 --1.4625605868290883E-01 --1.4626084326140434E-01 --1.4626533261926677E-01 --1.4626952686726363E-01 --1.4627342611556232E-01 --1.4627703047032467E-01 --1.4628034003752807E-01 --1.4628335493298442E-01 --1.4628607527945864E-01 --1.4628850119702300E-01 --1.4629063280038535E-01 --1.4629247020384487E-01 --1.4629401352219348E-01 --1.4629526287063935E-01 --1.4629621836790346E-01 --1.4629688013592929E-01 --1.4629724829920146E-01 --1.4629732298793749E-01 --1.4629710433285048E-01 --1.4629659246138396E-01 --1.4629578749952138E-01 --1.4629468957093406E-01 --1.4629329879656114E-01 --1.4629161530293341E-01 --1.4628963923487900E-01 --1.4628737073917142E-01 --1.4628480994410920E-01 --1.4628195696748755E-01 --1.4627881193646783E-01 --1.4627537499259707E-01 --1.4627164627942596E-01 --1.4626762594356735E-01 --1.4626331413232713E-01 --1.4625871098983134E-01 --1.4625381665780640E-01 --1.4624863127289589E-01 --1.4624315496167486E-01 --1.4623738785573873E-01 --1.4623133012215495E-01 --1.4622498193963837E-01 --1.4621834346087587E-01 --1.4621141481329131E-01 --1.4620419613164540E-01 --1.4619668757232196E-01 --1.4618888929482807E-01 --1.4618080145514301E-01 --1.4617242420774568E-01 --1.4616375771087456E-01 --1.4615480212745402E-01 --1.4614555761889292E-01 --1.4613602434001741E-01 --1.4612620244505514E-01 --1.4611609209627086E-01 --1.4610569346091354E-01 --1.4609500670372166E-01 --1.4608403198515971E-01 --1.4607276946782591E-01 --1.4606121932557772E-01 --1.4604938173487680E-01 --1.4603725686027386E-01 --1.4602484485687467E-01 --1.4601214589073003E-01 --1.4599916015145320E-01 --1.4598588782807800E-01 --1.4597232908665206E-01 --1.4595848408507583E-01 --1.4594435299653383E-01 --1.4592993601000659E-01 --1.4591523331077783E-01 --1.4590024507154808E-01 --1.4588497146494134E-01 --1.4586941268062240E-01 --1.4585356891661042E-01 --1.4583744035668175E-01 --1.4582102716548853E-01 --1.4580432951378594E-01 --1.4578734759960721E-01 --1.4577008162661728E-01 --1.4575253178876799E-01 --1.4573469827362559E-01 --1.4571658126595524E-01 --1.4569818094577111E-01 --1.4567949749699308E-01 --1.4566053112483679E-01 --1.4564128204042995E-01 --1.4562175044076242E-01 --1.4560193651082437E-01 --1.4558184044197067E-01 --1.4556146244063178E-01 --1.4554080271434452E-01 --1.4551986146340951E-01 --1.4549863888530448E-01 --1.4547713517956240E-01 --1.4545535054797223E-01 --1.4543328519549420E-01 --1.4541093933593330E-01 --1.4538831318354728E-01 --1.4536540694052993E-01 --1.4534222080287748E-01 --1.4531875497877403E-01 --1.4529500969373041E-01 --1.4527098516982012E-01 --1.4524668160968834E-01 --1.4522209921258986E-01 --1.4519723819546637E-01 --1.4517209878765530E-01 --1.4514668121150814E-01 --1.4512098567588758E-01 --1.4509501239105893E-01 --1.4506876158198345E-01 --1.4504223347836206E-01 --1.4501542830481981E-01 --1.4498834628139123E-01 --1.4496098762842627E-01 --1.4493335256722181E-01 --1.4490544131983882E-01 --1.4487725411201424E-01 --1.4484879117139060E-01 --1.4482005273173715E-01 --1.4479103903395116E-01 --1.4476175031482880E-01 --1.4473218679637784E-01 --1.4470234869905776E-01 --1.4467223625629427E-01 --1.4464184970900745E-01 --1.4461118929531444E-01 --1.4458025524887158E-01 --1.4454904780482747E-01 --1.4451756720582173E-01 --1.4448581369596808E-01 --1.4445378751010635E-01 --1.4442148887628109E-01 --1.4438891803497886E-01 --1.4435607525133887E-01 --1.4432296078790563E-01 --1.4428957487496352E-01 --1.4425591773245583E-01 --1.4422198960378024E-01 --1.4418779075497512E-01 --1.4415332144558318E-01 --1.4411858191569032E-01 --1.4408357240387071E-01 --1.4404829316021225E-01 --1.4401274444048257E-01 --1.4397692650631574E-01 --1.4394083962656556E-01 --1.4390448406408404E-01 --1.4386786005912008E-01 --1.4383096784887242E-01 --1.4379380768892380E-01 --1.4375637984624140E-01 --1.4371868458887643E-01 --1.4368072218625186E-01 --1.4364249290506714E-01 --1.4360399699832122E-01 --1.4356523471607008E-01 --1.4352620632229812E-01 --1.4348691209210049E-01 --1.4344735229857905E-01 --1.4340752720980532E-01 --1.4336743709223129E-01 --1.4332708220539689E-01 --1.4328646280696622E-01 --1.4324557917068778E-01 --1.4320443158681873E-01 --1.4316302033930872E-01 --1.4312134569223608E-01 --1.4307940790751086E-01 --1.4303720725649238E-01 --1.4299474401546575E-01 --1.4295201846408859E-01 --1.4290903088638010E-01 --1.4286578156527685E-01 --1.4282227077814719E-01 --1.4277849880161789E-01 --1.4273446591724137E-01 --1.4269017240983822E-01 --1.4264561856242189E-01 --1.4260080465467276E-01 --1.4255573096818427E-01 --1.4251039779498809E-01 --1.4246480542991286E-01 --1.4241895415825773E-01 --1.4237284425730365E-01 --1.4232647601055953E-01 --1.4227984971586985E-01 --1.4223296567176585E-01 --1.4218582416738493E-01 --1.4213842548844580E-01 --1.4209076992946343E-01 --1.4204285779455486E-01 --1.4199468938340609E-01 --1.4194626498074320E-01 --1.4189758487107071E-01 --1.4184864936097644E-01 --1.4179945876861347E-01 --1.4175001339394636E-01 --1.4170031351103360E-01 --1.4165035940197937E-01 --1.4160015138804866E-01 --1.4154968979874658E-01 --1.4149897494277100E-01 --1.4144800711434960E-01 --1.4139678660714611E-01 --1.4134531371417974E-01 --1.4129358873391692E-01 --1.4124161199343788E-01 --1.4118938382788521E-01 --1.4113690454275557E-01 --1.4108417441688123E-01 --1.4103119374515416E-01 --1.4097796286308295E-01 --1.4092448210843608E-01 --1.4087075179116587E-01 --1.4081677220944017E-01 --1.4076254367053836E-01 --1.4070806649236317E-01 --1.4065334099372176E-01 --1.4059836749399332E-01 --1.4054314631260528E-01 --1.4048767776692236E-01 --1.4043196217331355E-01 --1.4037599985388302E-01 --1.4031979113927767E-01 --1.4026333635830615E-01 --1.4020663582834875E-01 --1.4014968986457332E-01 --1.4009249879204075E-01 --1.4003506294317850E-01 --1.3997738264575391E-01 --1.3991945821788906E-01 --1.3986128997994537E-01 --1.3980287827066323E-01 --1.3974422343455264E-01 --1.3968532579728113E-01 --1.3962618566646814E-01 --1.3956680336254748E-01 --1.3950717924046691E-01 --1.3944731365742330E-01 --1.3938720694437431E-01 --1.3932685942037215E-01 --1.3926627141415326E-01 --1.3920544326647749E-01 --1.3914437531716933E-01 --1.3908306789984234E-01 --1.3902152134782986E-01 --1.3895973600419739E-01 --1.3889771221794148E-01 --1.3883545033182645E-01 --1.3877295067837078E-01 --1.3871021359201374E-01 --1.3864723941953774E-01 --1.3858402851145157E-01 --1.3852058121919747E-01 --1.3845689789495672E-01 --1.3839297888409283E-01 --1.3832882451746445E-01 --1.3826443512817696E-01 --1.3819981107345367E-01 --1.3813495271922935E-01 --1.3806986041746189E-01 --1.3800453450582606E-01 --1.3793897532784591E-01 --1.3787318324457676E-01 --1.3780715861878587E-01 --1.3774090180119428E-01 --1.3767441313676140E-01 --1.3760769297695055E-01 --1.3754074168178657E-01 --1.3747355961133734E-01 --1.3740614712315855E-01 --1.3733850457444521E-01 --1.3727063232317047E-01 --1.3720253072789051E-01 --1.3713420014744770E-01 --1.3706564094100795E-01 --1.3699685346773499E-01 --1.3692783808587972E-01 --1.3685859515433282E-01 --1.3678912504543689E-01 --1.3671942814284196E-01 --1.3664950481840743E-01 --1.3657935541662386E-01 --1.3650898028197997E-01 --1.3643837978252185E-01 --1.3636755429588701E-01 --1.3629650419650169E-01 --1.3622522985525362E-01 --1.3615373164167449E-01 --1.3608200992142400E-01 --1.3601006506053692E-01 --1.3593789743352383E-01 --1.3586550741943751E-01 --1.3579289539345626E-01 --1.3572006172517698E-01 --1.3564700678556998E-01 --1.3557373095207634E-01 --1.3550023460354479E-01 --1.3542651811448636E-01 --1.3535258185648499E-01 --1.3527842620270641E-01 --1.3520405152913079E-01 --1.3512945821346081E-01 --1.3505464664008540E-01 --1.3497961719559351E-01 --1.3490437026389290E-01 --1.3482890622650556E-01 --1.3475322546356547E-01 --1.3467732835180304E-01 --1.3460121526849253E-01 --1.3452488659720926E-01 --1.3444834272447498E-01 --1.3437158403934810E-01 --1.3429461093376877E-01 --1.3421742379767787E-01 --1.3414002301373093E-01 --1.3406240896347435E-01 --1.3398458203013805E-01 --1.3390654259815077E-01 --1.3382829105996866E-01 --1.3374982781991504E-01 --1.3367115327912821E-01 --1.3359226782049641E-01 --1.3351317182281605E-01 --1.3343386567312104E-01 --1.3335434976461141E-01 --1.3327462449307995E-01 --1.3319469025887315E-01 --1.3311454746249171E-01 --1.3303419650140061E-01 --1.3295363777200292E-01 --1.3287287166796030E-01 --1.3279189858033805E-01 --1.3271071890290534E-01 --1.3262933303627111E-01 --1.3254774138255979E-01 --1.3246594434601072E-01 --1.3238394233169454E-01 --1.3230173573537329E-01 --1.3221932494129743E-01 --1.3213671034264329E-01 --1.3205389236478957E-01 --1.3197087143704955E-01 --1.3188764795593494E-01 --1.3180422229836852E-01 --1.3172059485749424E-01 --1.3163676605259925E-01 --1.3155273630148587E-01 --1.3146850600387427E-01 --1.3138407555546214E-01 --1.3129944536682209E-01 --1.3121461586023395E-01 --1.3112958745100636E-01 --1.3104436053908089E-01 --1.3095893552438062E-01 --1.3087331281741152E-01 --1.3078749283281074E-01 --1.3070147598512802E-01 --1.3061526268881032E-01 --1.3052885335537803E-01 --1.3044224838798432E-01 --1.3035544819110850E-01 --1.3026845319075062E-01 --1.3018126382322526E-01 --1.3009388050509252E-01 --1.3000630362686494E-01 --1.2991853358587185E-01 --1.2983057081015303E-01 --1.2974241573393586E-01 --1.2965406878010077E-01 --1.2956553036425122E-01 --1.2947680090102565E-01 --1.2938788080347463E-01 --1.2929877048653823E-01 --1.2920947037433383E-01 --1.2911998089355009E-01 --1.2903030246446051E-01 --1.2894043550202888E-01 --1.2885038042656113E-01 --1.2876013767030747E-01 --1.2866970766504890E-01 --1.2857909082777744E-01 --1.2848828756995070E-01 --1.2839729831143576E-01 --1.2830612348118348E-01 --1.2821476351095643E-01 --1.2812321883900674E-01 --1.2803148990249280E-01 --1.2793957711646511E-01 --1.2784748088471409E-01 --1.2775520162787843E-01 --1.2766273979015252E-01 --1.2757009581478498E-01 --1.2747727013384275E-01 --1.2738426317631857E-01 --1.2729107536480636E-01 --1.2719770711764991E-01 --1.2710415886204546E-01 --1.2701043104118478E-01 --1.2691652409808327E-01 --1.2682243846508540E-01 --1.2672817457125554E-01 --1.2663373284679411E-01 --1.2653911372294938E-01 --1.2644431763378070E-01 --1.2634934501961811E-01 --1.2625419632007603E-01 --1.2615887196201425E-01 --1.2606337236741325E-01 --1.2596769797367113E-01 --1.2587184923589165E-01 --1.2577582660208519E-01 --1.2567963049442124E-01 --1.2558326133307413E-01 --1.2548671956666149E-01 --1.2539000565963404E-01 --1.2529312005642443E-01 --1.2519606317134377E-01 --1.2509883542478109E-01 --1.2500143727227456E-01 --1.2490386917717136E-01 --1.2480613158064123E-01 --1.2470822490771705E-01 --1.2461014959417985E-01 --1.2451190609709040E-01 --1.2441349487160074E-01 --1.2431491634740124E-01 --1.2421617094649194E-01 --1.2411725911369056E-01 --1.2401818131545890E-01 --1.2391893801190805E-01 --1.2381952964450678E-01 --1.2371995665156059E-01 --1.2362021946814922E-01 --1.2352031852839374E-01 --1.2342025428049411E-01 --1.2332002718982676E-01 --1.2321963771767475E-01 --1.2311908630745071E-01 --1.2301837339900067E-01 --1.2291749943248427E-01 --1.2281646484849916E-01 --1.2271527009767703E-01 --1.2261391564639018E-01 --1.2251240195813690E-01 --1.2241072947638436E-01 --1.2230889863975794E-01 --1.2220690989687184E-01 --1.2210476370419879E-01 --1.2200246051748931E-01 --1.2190000079032695E-01 --1.2179738497595587E-01 --1.2169461352613205E-01 --1.2159168689210889E-01 --1.2148860552313824E-01 --1.2138536986645862E-01 --1.2128198037459481E-01 --1.2117843751428856E-01 --1.2107474175313253E-01 --1.2097089354448384E-01 --1.2086689333494155E-01 --1.2076274157728845E-01 --1.2065843873234924E-01 --1.2055398525892581E-01 --1.2044938160596295E-01 --1.2034462822169871E-01 --1.2023972557010597E-01 --1.2013467412521313E-01 --1.2002947434928948E-01 --1.1992412668431600E-01 --1.1981863157535359E-01 --1.1971298949107002E-01 --1.1960720090655401E-01 --1.1950126628200879E-01 --1.1939518606531496E-01 --1.1928896071074840E-01 --1.1918259068723902E-01 --1.1907607646352646E-01 --1.1896941849317542E-01 --1.1886261722440181E-01 --1.1875567312155919E-01 --1.1864858666632430E-01 --1.1854135833323524E-01 --1.1843398857312268E-01 --1.1832647783374356E-01 --1.1821882657224680E-01 --1.1811103525098320E-01 --1.1800310433857226E-01 --1.1789503431217055E-01 --1.1778682564354005E-01 --1.1767847878038985E-01 --1.1756999416714391E-01 --1.1746137227852979E-01 --1.1735261360991554E-01 --1.1724371863686807E-01 --1.1713468779839900E-01 --1.1702552153704454E-01 --1.1691622033276935E-01 --1.1680678467655163E-01 --1.1669721503517061E-01 --1.1658751185402280E-01 --1.1647767558867590E-01 --1.1636770672011086E-01 --1.1625760573025569E-01 --1.1614737308068009E-01 --1.1603700922482083E-01 --1.1592651463064527E-01 --1.1581588978272601E-01 --1.1570513515880232E-01 --1.1559425121196301E-01 --1.1548323839323324E-01 --1.1537209717857254E-01 --1.1526082805786517E-01 --1.1514943150973005E-01 --1.1503790799580649E-01 --1.1492625797709144E-01 --1.1481448191691966E-01 --1.1470258028012661E-01 --1.1459055354164142E-01 --1.1447840218378580E-01 --1.1436612668401251E-01 --1.1425372750988086E-01 --1.1414120512918062E-01 --1.1402856001630288E-01 --1.1391579264756824E-01 --1.1380290348858335E-01 --1.1368989299488765E-01 --1.1357676163216565E-01 --1.1346350989233028E-01 --1.1335013826810787E-01 --1.1323664722608373E-01 --1.1312303722134885E-01 --1.1300930872240279E-01 --1.1289546221407497E-01 --1.1278149817798094E-01 --1.1266741708114379E-01 --1.1255321938883150E-01 --1.1243890557824920E-01 --1.1232447613375790E-01 --1.1220993153331267E-01 --1.1209527224449986E-01 --1.1198049873640750E-01 --1.1186561148819589E-01 --1.1175061098127233E-01 --1.1163549768588538E-01 --1.1152027206372413E-01 --1.1140493458594795E-01 --1.1128948574335708E-01 --1.1117392602656755E-01 --1.1105825590949299E-01 --1.1094247585986787E-01 --1.1082658634333595E-01 --1.1071058782347254E-01 --1.1059448077494678E-01 --1.1047826570224287E-01 --1.1036194310904025E-01 --1.1024551344996369E-01 --1.1012897715671861E-01 --1.1001233470171572E-01 --1.0989558661020159E-01 --1.0977873339322253E-01 --1.0966177549754083E-01 --1.0954471335944041E-01 --1.0942754745895632E-01 --1.0931027830397466E-01 --1.0919290638577951E-01 --1.0907543216688521E-01 --1.0895785611058875E-01 --1.0884017869640865E-01 --1.0872240040865903E-01 --1.0860452172768563E-01 --1.0848654313060327E-01 --1.0836846509698773E-01 --1.0825028811174682E-01 --1.0813201265829392E-01 --1.0801363920461778E-01 --1.0789516821323872E-01 --1.0777660016111507E-01 --1.0765793554061766E-01 --1.0753917484052344E-01 --1.0742031853660941E-01 --1.0730136710326901E-01 --1.0718232102186030E-01 --1.0706318077729406E-01 --1.0694394684517797E-01 --1.0682461968816401E-01 --1.0670519977605718E-01 --1.0658568760931217E-01 --1.0646608369323840E-01 --1.0634638849915551E-01 --1.0622660247550501E-01 --1.0610672609074584E-01 --1.0598675984975471E-01 --1.0586670425333378E-01 --1.0574655976073123E-01 --1.0562632682002475E-01 --1.0550600591798202E-01 --1.0538559757540540E-01 --1.0526510229215001E-01 --1.0514452051597373E-01 --1.0502385269261121E-01 --1.0490309930464173E-01 --1.0478226085036177E-01 --1.0466133782356353E-01 --1.0454033071281937E-01 --1.0441923999935873E-01 --1.0429806614205217E-01 --1.0417680959872168E-01 --1.0405547085720182E-01 --1.0393405042188060E-01 --1.0381254877956315E-01 --1.0369096639086367E-01 --1.0356930372091207E-01 --1.0344756126157305E-01 --1.0332573951046828E-01 --1.0320383894693190E-01 --1.0308186003712907E-01 --1.0295980325234154E-01 --1.0283766907397947E-01 --1.0271545798574158E-01 --1.0259317047678464E-01 --1.0247080703762390E-01 --1.0234836814493660E-01 --1.0222585426245841E-01 --1.0210326586066534E-01 --1.0198060342784961E-01 --1.0185786745342948E-01 --1.0173505841330856E-01 --1.0161217677761518E-01 --1.0148922302572483E-01 --1.0136619764818289E-01 --1.0124310113195921E-01 --1.0111993394940177E-01 --1.0099669657055158E-01 --1.0087338947140899E-01 --1.0075001313164456E-01 --1.0062656803236338E-01 --1.0050305465671223E-01 --1.0037947348784228E-01 --1.0025582500740825E-01 --1.0013210969637584E-01 --1.0000832802926053E-01 --9.9884480475671847E-02 --9.9760567509243586E-02 --9.9636589611838827E-02 --9.9512547266541976E-02 --9.9388440956745469E-02 --9.9264271165824147E-02 --9.9140038370965328E-02 --9.9015743043190080E-02 --9.8891385656864006E-02 --9.8766966695677291E-02 --9.8642486643322994E-02 --9.8517945969537848E-02 --9.8393345137781418E-02 --9.8268684627615302E-02 --9.8143964939314488E-02 --9.8019186565262276E-02 --9.7894349964224706E-02 --9.7769455590016055E-02 --9.7644503923779838E-02 --9.7519495463942882E-02 --9.7394430695912984E-02 --9.7269310082779822E-02 --9.7144134089556036E-02 --9.7018903199822204E-02 --9.6893617901834664E-02 --9.6768278666927693E-02 --9.6642885952616317E-02 --9.6517440228903989E-02 --9.6391941993628882E-02 --9.6266391744057753E-02 --9.6140789949075572E-02 --9.6015137066715731E-02 --9.5889433562256321E-02 --9.5763679908686047E-02 --9.5637876584897641E-02 --9.5512024085282712E-02 --9.5386122903799345E-02 --9.5260173504674209E-02 --9.5134176337060880E-02 --9.5008131864099718E-02 --9.4882040568193299E-02 --9.4755902931565564E-02 --9.4629719429822540E-02 --9.4503490537449233E-02 --9.4377216732801611E-02 --9.4250898496873958E-02 --9.4124536305710063E-02 --9.3998130626295084E-02 --9.3871681924396419E-02 --9.3745190663517927E-02 --9.3618657307439818E-02 --9.3492082335787222E-02 --9.3365466242050790E-02 --9.3238809509637838E-02 --9.3112112597113370E-02 --9.2985375962277697E-02 --9.2858600081033985E-02 --9.2731785436586750E-02 --9.2604932497462433E-02 --9.2478041715557124E-02 --9.2351113551771224E-02 --9.2224148497075956E-02 --9.2097147045349645E-02 --9.1970109661464489E-02 --9.1843036794490143E-02 --9.1715928905309968E-02 --9.1588786472199812E-02 --9.1461609972774860E-02 --9.1334399875630856E-02 --9.1207156647412552E-02 --9.1079880757784296E-02 --9.0952572678632437E-02 --9.0825232880057089E-02 --9.0697861828485202E-02 --9.0570459990207339E-02 --9.0443027832171258E-02 --9.0315565821786056E-02 --9.0188074428537865E-02 --9.0060554123853803E-02 --8.9933005375404426E-02 --8.9805428641016663E-02 --8.9677824378798121E-02 --8.9550193059106345E-02 --8.9422535157701752E-02 --8.9294851141439591E-02 --8.9167141466397606E-02 --8.9039406593315135E-02 --8.8911646999995611E-02 --8.8783863165626073E-02 --8.8656055545558346E-02 --8.8528224581328724E-02 --8.8400370728675334E-02 --8.8272494465588852E-02 --8.8144596270221517E-02 --8.8016676612256178E-02 --8.7888735958255360E-02 --8.7760774760997237E-02 --8.7632793462794401E-02 --8.7504792517268573E-02 --8.7376772401283526E-02 --8.7248733592137168E-02 --8.7120676552080917E-02 --8.6992601737890946E-02 --8.6864509605000972E-02 --8.6736400607527978E-02 --8.6608275203731377E-02 --8.6480133862733441E-02 --8.6351977053899923E-02 --8.6223805232831241E-02 --8.6095618848713584E-02 --8.5967418356710665E-02 --8.5839204219633272E-02 --8.5710976898538974E-02 --8.5582736846004009E-02 --8.5454484513830462E-02 --8.5326220364690675E-02 --8.5197944868108902E-02 --8.5069658486569388E-02 --8.4941361670578086E-02 --8.4813054870378574E-02 --8.4684738539636789E-02 --8.4556413133226899E-02 --8.4428079106981968E-02 --8.4299736917542292E-02 --8.4171387018716445E-02 --8.4043029857904156E-02 --8.3914665883945486E-02 --8.3786295559306320E-02 --8.3657919351353083E-02 --8.3529537712409230E-02 --8.3401151078906832E-02 --8.3272759893629991E-02 --8.3144364619318109E-02 --8.3015965720473428E-02 --8.2887563644716195E-02 --8.2759158831221827E-02 --8.2630751728024490E-02 --8.2502342795251163E-02 --8.2373932490819229E-02 --8.2245521260399509E-02 --8.2117109547500858E-02 --8.1988697803221433E-02 --8.1860286483711575E-02 --8.1731876034085327E-02 --8.1603466879636322E-02 --8.1475059451697446E-02 --8.1346654222082510E-02 --8.1218251673660286E-02 --8.1089852253596786E-02 --8.0961456378036478E-02 --8.0833064473113989E-02 --8.0704676990226085E-02 --8.0576294383810906E-02 --8.0447917103713074E-02 --8.0319545597808920E-02 --8.0191180309933982E-02 --8.0062821679370705E-02 --7.9934470146419787E-02 --7.9806126154854315E-02 --7.9677790148609567E-02 --7.9549462565520299E-02 --7.9421143840266509E-02 --7.9292834414226160E-02 --7.9164534738454584E-02 --7.9036245262197241E-02 --7.8907966423624729E-02 --7.8779698657832589E-02 --7.8651442394869084E-02 --7.8523198061315927E-02 --7.8394966095069046E-02 --7.8266746955336988E-02 --7.8138541097988387E-02 --7.8010348946808236E-02 --7.7882170915775956E-02 --7.7754007439667830E-02 --7.7625858972526093E-02 --7.7497725959908323E-02 --7.7369608824308836E-02 --7.7241507986826399E-02 --7.7113423883248919E-02 --7.6985356955890760E-02 --7.6857307640488814E-02 --7.6729276364848387E-02 --7.6601263560391319E-02 --7.6473269671544455E-02 --7.6345295143174549E-02 --7.6217340395777392E-02 --7.6089405835848625E-02 --7.5961491887128668E-02 --7.5833599000193402E-02 --7.5705727621498964E-02 --7.5577878168696974E-02 --7.5450051052652276E-02 --7.5322246699042708E-02 --7.5194465544898961E-02 --7.5066708026418419E-02 --7.4938974577355960E-02 --7.4811265628016904E-02 --7.4683581589253964E-02 --7.4555922865871385E-02 --7.4428289884229740E-02 --7.4300683091933939E-02 --7.4173102926346351E-02 --7.4045549795025076E-02 --7.3918024103882929E-02 --7.3790526283788280E-02 --7.3663056777142369E-02 --7.3535616004472809E-02 --7.3408204358340293E-02 --7.3280822242887081E-02 --7.3153470109042204E-02 --7.3026148413734268E-02 --7.2898857564079961E-02 --7.2771597936324928E-02 --7.2644369932506003E-02 --7.2517173997828713E-02 --7.2390010575240041E-02 --7.2262880077377523E-02 --7.2135782908373372E-02 --7.2008719477443375E-02 --7.1881690197985834E-02 --7.1754695486233838E-02 --7.1627735764052070E-02 --7.1500811451767884E-02 --7.1373922954449248E-02 --7.1247070671783805E-02 --7.1120255015954398E-02 --7.0993476412250914E-02 --7.0866735281949991E-02 --7.0740032032869257E-02 --7.0613367070345823E-02 --7.0486740797670797E-02 --7.0360153617308713E-02 --7.0233605938025329E-02 --7.0107098177070060E-02 --6.9980630749541459E-02 --6.9854204059671368E-02 --6.9727818509748310E-02 --6.9601474508276695E-02 --6.9475172467879473E-02 --6.9348912792594447E-02 --6.9222695871119538E-02 --6.9096522095007107E-02 --6.8970391877571591E-02 --6.8844305638459877E-02 --6.8718263785379888E-02 --6.8592266715726380E-02 --6.8466314827004771E-02 --6.8340408517545345E-02 --6.8214548185871735E-02 --6.8088734230197859E-02 --6.7962967048740081E-02 --6.7837247040780702E-02 --6.7711574606771199E-02 --6.7585950145838278E-02 --6.7460374052567926E-02 --6.7334846721228525E-02 --6.7209368550080625E-02 --6.7083939939512074E-02 --6.6958561283018747E-02 --6.6833232964051470E-02 --6.6707955369695177E-02 --6.6582728904526919E-02 --6.6457553976666445E-02 --6.6332430980663035E-02 --6.6207360301408488E-02 --6.6082342321120022E-02 --6.5957377417257393E-02 --6.5832465971350757E-02 --6.5707608389352593E-02 --6.5582805084154080E-02 --6.5458056439719220E-02 --6.5333362813415050E-02 --6.5208724575918642E-02 --6.5084142132855974E-02 --6.4959615892154252E-02 --6.4835146238856320E-02 --6.4710733547981264E-02 --6.4586378199299438E-02 --6.4462080578252146E-02 --6.4337841069565901E-02 --6.4213660054218108E-02 --6.4089537912127695E-02 --6.3965475019031645E-02 --6.3841471748376150E-02 --6.3717528479295543E-02 --6.3593645599622425E-02 --6.3469823496308350E-02 --6.3346062548738771E-02 --6.3222363134010862E-02 --6.3098725624374782E-02 --6.2975150388453832E-02 --6.2851637797347482E-02 --6.2728188227140491E-02 --6.2604802054457773E-02 --6.2481479654959204E-02 --6.2358221404032015E-02 --6.2235027676767619E-02 --6.2111898847964253E-02 --6.1988835288882382E-02 --6.1865837361269438E-02 --6.1742905426998618E-02 --6.1620039860433962E-02 --6.1497241041733555E-02 --6.1374509341305401E-02 --6.1251845117143155E-02 --6.1129248729111518E-02 --6.1006720546070300E-02 --6.0884260938487228E-02 --6.0761870271639241E-02 --6.0639548907632693E-02 --6.0517297209788545E-02 --6.0395115543402295E-02 --6.0273004273626994E-02 --6.0150963763595966E-02 --6.0028994375614118E-02 --5.9907096466601070E-02 --5.9785270389154981E-02 --5.9663516497161520E-02 --5.9541835147362894E-02 --5.9420226698386744E-02 --5.9298691517783969E-02 --5.9177229975949368E-02 --5.9055842425498460E-02 --5.8934529200501053E-02 --5.8813290642894783E-02 --5.8692127119008737E-02 --5.8571038997548987E-02 --5.8450026630000963E-02 --5.8329090359252198E-02 --5.8208230534290202E-02 --5.8087447512362174E-02 --5.7966741649549569E-02 --5.7846113295000008E-02 --5.7725562795718374E-02 --5.7605090491281118E-02 --5.7484696716460289E-02 --5.7364381813902951E-02 --5.7244146140061319E-02 --5.7123990050667824E-02 --5.7003913890311987E-02 --5.6883918000305171E-02 --5.6764002724333282E-02 --5.6644168408123259E-02 --5.6524415391824900E-02 --5.6404744002530004E-02 --5.6285154569199650E-02 --5.6165647445204497E-02 --5.6046222993370587E-02 --5.5926881554418183E-02 --5.5807623444484762E-02 --5.5688448986245691E-02 --5.5569358525752045E-02 --5.5450352411591797E-02 --5.5331430974032453E-02 --5.5212594533600196E-02 --5.5093843420821444E-02 --5.4975177980645690E-02 --5.4856598554208304E-02 --5.4738105462383564E-02 --5.4619699022506074E-02 --5.4501379571611837E-02 --5.4383147460597046E-02 --5.4265003024965140E-02 --5.4146946570887505E-02 --5.4028978405827814E-02 --5.3911098861116134E-02 --5.3793308275867903E-02 --5.3675606982516874E-02 --5.3557995307366331E-02 --5.3440473570665260E-02 --5.3323042078251663E-02 --5.3205701137584716E-02 --5.3088451083221258E-02 --5.2971292261236737E-02 --5.2854224998007418E-02 --5.2737249596555916E-02 --5.2620366361789600E-02 --5.2503575608835507E-02 --5.2386877655273160E-02 --5.2270272821717811E-02 --5.2153761430510946E-02 --5.2037343798786537E-02 --5.1921020235626426E-02 --5.1804791051261075E-02 --5.1688656563482205E-02 --5.1572617091087423E-02 --5.1456672936518698E-02 --5.1340824390011364E-02 --5.1225071756616003E-02 --5.1109415371329854E-02 --5.0993855566030866E-02 --5.0878392633279514E-02 --5.0763026852594706E-02 --5.0647758527450459E-02 --5.0532587984661384E-02 --5.0417515538833273E-02 --5.0302541469937144E-02 --5.0187666057357277E-02 --5.0072889619512131E-02 --4.9958212492625380E-02 --4.9843634982520257E-02 --4.9729157356635419E-02 --4.9614779891956770E-02 --4.9500502906909639E-02 --4.9386326726256806E-02 --4.9272251644375098E-02 --4.9158277936939929E-02 --4.9044405888014550E-02 --4.8930635795706279E-02 --4.8816967959260292E-02 --4.8703402676840646E-02 --4.8589940245824373E-02 --4.8476580954859787E-02 --4.8363325085611003E-02 --4.8250172921598056E-02 --4.8137124750588269E-02 --4.8024180862108801E-02 --4.7911341552827225E-02 --4.7798607121678036E-02 --4.7685977853853513E-02 --4.7573454020293039E-02 --4.7461035897032412E-02 --4.7348723776056680E-02 --4.7236517950335601E-02 --4.7124418696856789E-02 --4.7012426284714526E-02 --4.6900540990588699E-02 --4.6788763101360736E-02 --4.6677092903563616E-02 --4.6565530679497584E-02 --4.6454076709934129E-02 --4.6342731268252564E-02 --4.6231494622963665E-02 --4.6120367041586098E-02 --4.6009348789995685E-02 --4.5898440137288533E-02 --4.5787641369139848E-02 --4.5676952775462895E-02 --4.5566374628452033E-02 --4.5455907185167246E-02 --4.5345550705584138E-02 --4.5235305457282923E-02 --4.5125171709329372E-02 --4.5015149733256120E-02 --4.4905239801474622E-02 --4.4795442180971146E-02 --4.4685757132731263E-02 --4.4576184916902371E-02 --4.4466725791868937E-02 --4.4357380016344698E-02 --4.4248147854540648E-02 --4.4139029573563450E-02 --4.4030025434247083E-02 --4.3921135688406492E-02 --4.3812360589734207E-02 --4.3703700401971406E-02 --4.3595155390493176E-02 --4.3486725808168494E-02 --4.3378411899128021E-02 --4.3270213912421363E-02 --4.3162132106472031E-02 --4.3054166739871405E-02 --4.2946318066293669E-02 --4.2838586337523840E-02 --4.2730971799479593E-02 --4.2623474692756028E-02 --4.2516095261421930E-02 --4.2408833758329822E-02 --4.2301690436559895E-02 --4.2194665540849954E-02 --4.2087759312356268E-02 --4.1980971994250070E-02 --4.1874303832071601E-02 --4.1767755069833636E-02 --4.1661325946015536E-02 --4.1555016698324246E-02 --4.1448827567283644E-02 --4.1342758795032651E-02 --4.1236810620872207E-02 --4.1130983279722692E-02 --4.1025277006486865E-02 --4.0919692037323069E-02 --4.0814228608582484E-02 --4.0708886953734431E-02 --4.0603667304108193E-02 --4.0498569891467003E-02 --4.0393594948459885E-02 --4.0288742707231699E-02 --4.0184013396071930E-02 --4.0079407241983132E-02 --3.9974924473010015E-02 --3.9870565318207575E-02 --3.9766330005239645E-02 --3.9662218757926360E-02 --3.9558231799486740E-02 --3.9454369352807099E-02 --3.9350631640662603E-02 --3.9247018886050707E-02 --3.9143531312227989E-02 --3.9040169141198712E-02 --3.8936932590409846E-02 --3.8833821876405897E-02 --3.8730837216055553E-02 --3.8627978826449631E-02 --3.8525246924400527E-02 --3.8422641726217427E-02 --3.8320163447538781E-02 --3.8217812300875467E-02 --3.8115588497864145E-02 --3.8013492249890847E-02 --3.7911523768149623E-02 --3.7809683262955175E-02 --3.7707970942704207E-02 --3.7606387015481205E-02 --3.7504931688633572E-02 --3.7403605169224245E-02 --3.7302407663314184E-02 --3.7201339375930557E-02 --3.7100400511106267E-02 --3.6999591270129660E-02 --3.6898911854072326E-02 --3.6798362465781304E-02 --3.6697943308946011E-02 --3.6597654583693670E-02 --3.6497496485382794E-02 --3.6397469209731165E-02 --3.6297572954854827E-02 --3.6197807919231995E-02 --3.6098174298486330E-02 --3.5998672286377167E-02 --3.5899302076048890E-02 --3.5800063859596602E-02 --3.5700957828796245E-02 --3.5601984174139345E-02 --3.5503143085686160E-02 --3.5404434752243662E-02 --3.5305859361560915E-02 --3.5207417101310909E-02 --3.5109108158998197E-02 --3.5010932721737040E-02 --3.4912890973892975E-02 --3.4814983098684103E-02 --3.4717209277986605E-02 --3.4619569692204318E-02 --3.4522064522147768E-02 --3.4424693949960200E-02 --3.4327458157631961E-02 --3.4230357323093957E-02 --3.4133391622114845E-02 --3.4036561230538526E-02 --3.3939866324325475E-02 --3.3843307079156011E-02 --3.3746883669412038E-02 --3.3650596269087098E-02 --3.3554445050841195E-02 --3.3458430186399393E-02 --3.3362551845935465E-02 --3.3266810196759797E-02 --3.3171205406279394E-02 --3.3075737643861625E-02 --3.2980407079384280E-02 --3.2885213879365008E-02 --3.2790158207281365E-02 --3.2695240226295670E-02 --3.2600460099006669E-02 --3.2505817987981224E-02 --3.2411314055902064E-02 --3.2316948465447193E-02 --3.2222721376795153E-02 --3.2128632947198213E-02 --3.2034683333754956E-02 --3.1940872693511958E-02 --3.1847201183419750E-02 --3.1753668959265131E-02 --3.1660276176154030E-02 --3.1567022987595346E-02 --3.1473909544677166E-02 --3.1380935998393221E-02 --3.1288102500067951E-02 --3.1195409201004182E-02 --3.1102856250524905E-02 --3.1010443796481803E-02 --3.0918171985969304E-02 --3.0826040964627790E-02 --3.0734050877818390E-02 --3.0642201870102477E-02 --3.0550494085715349E-02 --3.0458927667490358E-02 --3.0367502756912298E-02 --3.0276219495033955E-02 --3.0185078021876765E-02 --3.0094078477084302E-02 --3.0003220998414782E-02 --2.9912505722749422E-02 --2.9821932786666793E-02 --2.9731502326366462E-02 --2.9641214477219954E-02 --2.9551069371760587E-02 --2.9461067141892849E-02 --2.9371207919040399E-02 --2.9281491834341339E-02 --2.9191919018753898E-02 --2.9102489602933070E-02 --2.9013203716473774E-02 --2.8924061484122181E-02 --2.8835063029411547E-02 --2.8746208478367601E-02 --2.8657497958987272E-02 --2.8568931596663908E-02 --2.8480509511183742E-02 --2.8392231822083915E-02 --2.8304098651601543E-02 --2.8216110122877742E-02 --2.8128266355561603E-02 --2.8040567465722307E-02 --2.7953013569358597E-02 --2.7865604782679004E-02 --2.7778341221795715E-02 --2.7691223001534808E-02 --2.7604250236066642E-02 --2.7517423038627149E-02 --2.7430741521214049E-02 --2.7344205795158314E-02 --2.7257815969581860E-02 --2.7171572153059313E-02 --2.7085474453512268E-02 --2.6999522978430997E-02 --2.6913717834464373E-02 --2.6828059126813616E-02 --2.6742546960345170E-02 --2.6657181438896158E-02 --2.6571962665885223E-02 --2.6486890742749233E-02 --2.6401965769252085E-02 --2.6317187845153533E-02 --2.6232557070301244E-02 --2.6148073544086645E-02 --2.6063737362695877E-02 --2.5979548621031693E-02 --2.5895507414442218E-02 --2.5811613838763334E-02 --2.5727867988741982E-02 --2.5644269955795950E-02 --2.5560819830765736E-02 --2.5477517704720686E-02 --2.5394363668820485E-02 --2.5311357812348761E-02 --2.5228500221938992E-02 --2.5145790983996680E-02 --2.5063230184775458E-02 --2.4980817910385048E-02 --2.4898554245438829E-02 --2.4816439273506682E-02 --2.4734473077592734E-02 --2.4652655739695040E-02 --2.4570987341043921E-02 --2.4489467959319715E-02 --2.4408097671146853E-02 --2.4326876555286606E-02 --2.4245804692416262E-02 --2.4164882160797471E-02 --2.4084109032726390E-02 --2.4003485379934762E-02 --2.3923011276353694E-02 --2.3842686796783460E-02 --2.3762512013111584E-02 --2.3682486993840478E-02 --2.3602611807642070E-02 --2.3522886524321444E-02 --2.3443311213644707E-02 --2.3363885942721908E-02 --2.3284610777126256E-02 --2.3205485781294860E-02 --2.3126511017986590E-02 --2.3047686550049615E-02 --2.2969012441288100E-02 --2.2890488755493044E-02 --2.2812115552624839E-02 --2.2733892889811796E-02 --2.2655820825123605E-02 --2.2577899418596892E-02 --2.2500128729587034E-02 --2.2422508812253800E-02 --2.2345039718986347E-02 --2.2267721503654823E-02 --2.2190554221545457E-02 --2.2113537926414184E-02 --2.2036672667943999E-02 --2.1959958495243417E-02 --2.1883395457970706E-02 --2.1806983605994968E-02 --2.1730722987638802E-02 --2.1654613649313068E-02 --2.1578655637045085E-02 --2.1502848995965412E-02 --2.1427193770803786E-02 --2.1351690004066511E-02 --2.1276337736898264E-02 --2.1201137010224486E-02 --2.1126087864655800E-02 --2.1051190340389343E-02 --2.0976444475884808E-02 --2.0901850309037646E-02 --2.0827407876741880E-02 --2.0753117215093854E-02 --2.0678978359339087E-02 --2.0604991343005037E-02 --2.0531156199175407E-02 --2.0457472959569803E-02 --2.0383941655350103E-02 --2.0310562316855008E-02 --2.0237334973584684E-02 --2.0164259654575224E-02 --2.0091336387709133E-02 --2.0018565200360827E-02 --1.9945946117361932E-02 --1.9873479162278985E-02 --1.9801164359098053E-02 --1.9729001732371500E-02 --1.9656991305864908E-02 --1.9585133100354746E-02 --1.9513427135802563E-02 --1.9441873430755735E-02 --1.9370472002833164E-02 --1.9299222869366511E-02 --1.9228126047237035E-02 --1.9157181553126516E-02 --1.9086389403015824E-02 --1.9015749612481512E-02 --1.8945262194052466E-02 --1.8874927157694170E-02 --1.8804744513504727E-02 --1.8734714272080448E-02 --1.8664836443899654E-02 --1.8595111038307691E-02 --1.8525538064099387E-02 --1.8456117527937490E-02 --1.8386849434177351E-02 --1.8317733787218991E-02 --1.8248770591973110E-02 --1.8179959853086788E-02 --1.8111301572098178E-02 --1.8042795748880180E-02 --1.7974442383360070E-02 --1.7906241475571873E-02 --1.7838193025147189E-02 --1.7770297030167664E-02 --1.7702553488142956E-02 --1.7634962394341397E-02 --1.7567523742473817E-02 --1.7500237526508072E-02 --1.7433103740954567E-02 --1.7366122379841697E-02 --1.7299293434452485E-02 --1.7232616895049822E-02 --1.7166092749972810E-02 --1.7099720985840072E-02 --1.7033501590280171E-02 --1.6967434553508760E-02 --1.6901519865159299E-02 --1.6835757508172736E-02 --1.6770147462648214E-02 --1.6704689711175700E-02 --1.6639384239237612E-02 --1.6574231031218675E-02 --1.6509230067592851E-02 --1.6444381327814461E-02 --1.6379684789096474E-02 --1.6315140427387600E-02 --1.6250748219913430E-02 --1.6186508145842035E-02 --1.6122420183191773E-02 --1.6058484304551607E-02 --1.5994700481173116E-02 --1.5931068685963810E-02 --1.5867588893026131E-02 --1.5804261074434989E-02 --1.5741085198308948E-02 --1.5678061232397629E-02 --1.5615189145084564E-02 --1.5552468904904982E-02 --1.5489900479377932E-02 --1.5427483835049192E-02 --1.5365218937425157E-02 --1.5303105749516313E-02 --1.5241144233733298E-02 --1.5179334351105210E-02 --1.5117676062017775E-02 --1.5056169327503002E-02 --1.4994814109400532E-02 --1.4933610368296353E-02 --1.4872558060454228E-02 --1.4811657141216534E-02 --1.4750907566171279E-02 --1.4690309291027954E-02 --1.4629862270733481E-02 --1.4569566459046161E-02 --1.4509421809086674E-02 --1.4449428271703041E-02 --1.4389585797077675E-02 --1.4329894335506077E-02 --1.4270353837355134E-02 --1.4210964251658452E-02 --1.4151725524729184E-02 --1.4092637602467751E-02 --1.4033700430512917E-02 --1.3974913954315122E-02 --1.3916278117846225E-02 --1.3857792863580473E-02 --1.3799458133738104E-02 --1.3741273870104678E-02 --1.3683240014110530E-02 --1.3625356505124657E-02 --1.3567623281452560E-02 --1.3510040280729755E-02 --1.3452607439740366E-02 --1.3395324694869346E-02 --1.3338191981381305E-02 --1.3281209234210854E-02 --1.3224376387823918E-02 --1.3167693376336581E-02 --1.3111160131616709E-02 --1.3054776581767376E-02 --1.2998542655060109E-02 --1.2942458282545827E-02 --1.2886523395884874E-02 --1.2830737923307804E-02 --1.2775101790169998E-02 --1.2719614921692208E-02 --1.2664277243055468E-02 --1.2609088679166280E-02 --1.2554049153419193E-02 --1.2499158588534247E-02 --1.2444416906353390E-02 --1.2389824027778057E-02 --1.2335379873286305E-02 --1.2281084362353522E-02 --1.2226937414004270E-02 --1.2172938945205838E-02 --1.2119088871803145E-02 --1.2065387109350312E-02 --1.2011833573032406E-02 --1.1958428177786907E-02 --1.1905170837844922E-02 --1.1852061467033151E-02 --1.1799099976746412E-02 --1.1746286276687177E-02 --1.1693620276639260E-02 --1.1641101886641575E-02 --1.1588731016152544E-02 --1.1536507571681686E-02 --1.1484431458783001E-02 --1.1432502583868400E-02 --1.1380720854101356E-02 --1.1329086175248497E-02 --1.1277598449790573E-02 --1.1226257579576876E-02 --1.1175063465679782E-02 --1.1124016008812828E-02 --1.1073115110008592E-02 --1.1022360670677035E-02 --1.0971752590779225E-02 --1.0921290765797424E-02 --1.0870975090538968E-02 --1.0820805462229839E-02 --1.0770781779378737E-02 --1.0720903937471812E-02 --1.0671171827523045E-02 --1.0621585340614251E-02 --1.0572144369823054E-02 --1.0522848808518087E-02 --1.0473698547473710E-02 --1.0424693475543657E-02 --1.0375833481499787E-02 --1.0327118454102285E-02 --1.0278548281781071E-02 --1.0230122851390777E-02 --1.0181842049095963E-02 --1.0133705759046182E-02 --1.0085713863481975E-02 --1.0037866245229560E-02 --9.9901627888921898E-03 --9.9426033788506639E-03 --9.8951878960573218E-03 --9.8479162198299094E-03 --9.8007882289548355E-03 --9.7538038015963953E-03 --9.7069628155442966E-03 --9.6602651476159294E-03 --9.6137106743618521E-03 --9.5672992722177878E-03 --9.5210308174925821E-03 --9.4749051846248194E-03 --9.4289222451428272E-03 --9.3830818705848539E-03 --9.3373839339252248E-03 --9.2918283082650995E-03 --9.2464148632163106E-03 --9.2011434656573184E-03 --9.1560139834003379E-03 --9.1110262864060512E-03 --9.0661802442096612E-03 --9.0214757224959946E-03 --8.9769125854585741E-03 --8.9324906972227947E-03 --8.8882099218475525E-03 --8.8440701231105173E-03 --8.8000711641604158E-03 --8.7562129077347721E-03 --8.7124952145172137E-03 --8.6689179441425887E-03 --8.6254809563748192E-03 --8.5821841111790587E-03 --8.5390272674538015E-03 --8.4960102803916492E-03 --8.4531330044732549E-03 --8.4103952962774186E-03 --8.3677970136765006E-03 --8.3253380126102582E-03 --8.2830181457825020E-03 --8.2408372652311261E-03 --8.1987952215576802E-03 --8.1568918649516323E-03 --8.1151270468708507E-03 --8.0735006198043354E-03 --8.0320124344344310E-03 --7.9906623374965055E-03 --7.9494501753528662E-03 --7.9083757957586279E-03 --7.8674390468837091E-03 --7.8266397743872070E-03 --7.7859778212420365E-03 --7.7454530304749110E-03 --7.7050652458049186E-03 --7.6648143108890990E-03 --7.6247000682644409E-03 --7.5847223598086771E-03 --7.5448810260481192E-03 --7.5051759056795784E-03 --7.4656068373871549E-03 --7.4261736605570139E-03 --7.3868762145090378E-03 --7.3477143363473970E-03 --7.3086878616263236E-03 --7.2697966253138660E-03 --7.2310404614485922E-03 --7.1924192039687414E-03 --7.1539326871261260E-03 --7.1155807451246979E-03 --7.0773632104292414E-03 --7.0392799139558813E-03 --7.0013306862641289E-03 --6.9635153573183737E-03 --6.9258337567049489E-03 --6.8882857124158035E-03 --6.8508710517282464E-03 --6.8135896024794423E-03 --6.7764411931600689E-03 --6.7394256510025898E-03 --6.7025427993891223E-03 --6.6657924611101061E-03 --6.6291744611058192E-03 --6.5926886254313154E-03 --6.5563347773361568E-03 --6.5201127359588275E-03 --6.4840223204613206E-03 --6.4480633517472862E-03 --6.4122356510349443E-03 --6.3765390385028872E-03 --6.3409733335389011E-03 --6.3055383546282802E-03 --6.2702339186447072E-03 --6.2350598420144827E-03 --6.2000159400666943E-03 --6.1651020276803524E-03 --6.1303179195388666E-03 --6.0956634301348369E-03 --6.0611383733278354E-03 --6.0267425615423932E-03 --5.9924758068733413E-03 --5.9583379211343721E-03 --5.9243287159134184E-03 --5.8904480012496839E-03 --5.8566955853250500E-03 --5.8230712766548049E-03 --5.7895748854557682E-03 --5.7562062218022283E-03 --5.7229650912561190E-03 --5.6898512966669038E-03 --5.6568646426982585E-03 --5.6240049369759163E-03 --5.5912719865585112E-03 --5.5586655951172003E-03 --5.5261855652687679E-03 --5.4938316990067590E-03 --5.4616037978180111E-03 --5.4295016630801713E-03 --5.3975250960759859E-03 --5.3656738978480594E-03 --5.3339478685041665E-03 --5.3023468076623566E-03 --5.2708705130625104E-03 --5.2395187805655517E-03 --5.2082914065450080E-03 --5.1771881891407266E-03 --5.1462089264437899E-03 --5.1153534143392083E-03 --5.0846214475501021E-03 --5.0540128196366850E-03 --5.0235273226970963E-03 --4.9931647490914655E-03 --4.9629248927154255E-03 --4.9328075474693841E-03 --4.9028125041902073E-03 --4.8729395517351157E-03 --4.8431884799004909E-03 --4.8135590801779930E-03 --4.7840511434468882E-03 --4.7546644572207053E-03 --4.7253988079570593E-03 --4.6962539824853692E-03 --4.6672297679225365E-03 --4.6383259510141524E-03 --4.6095423177956131E-03 --4.5808786539440153E-03 --4.5523347439207149E-03 --4.5239103716232998E-03 --4.4956053204813608E-03 --4.4674193734332386E-03 --4.4393523130275827E-03 --4.4114039209464878E-03 --4.3835739785725841E-03 --4.3558622666954750E-03 --4.3282685657312116E-03 --4.3007926555031929E-03 --4.2734343150637576E-03 --4.2461933231270144E-03 --4.2190694576047906E-03 --4.1920624961034820E-03 --4.1651722157695871E-03 --4.1383983933963300E-03 --4.1117408052075309E-03 --4.0851992265061457E-03 --4.0587734322931153E-03 --4.0324631969073143E-03 --4.0062682943752814E-03 --3.9801884981810771E-03 --3.9542235813177012E-03 --3.9283733164135930E-03 --3.9026374754253432E-03 --3.8770158300100851E-03 --3.8515081509633226E-03 --3.8261142086387493E-03 --3.8008337729988702E-03 --3.7756666135788678E-03 --3.7506124995685492E-03 --3.7256711993785959E-03 --3.7008424811224515E-03 --3.6761261122674406E-03 --3.6515218598639739E-03 --3.6270294905521088E-03 --3.6026487704284372E-03 --3.5783794652888890E-03 --3.5542213401866265E-03 --3.5301741598654222E-03 --3.5062376885173726E-03 --3.4824116899004887E-03 --3.4586959274048395E-03 --3.4350901638377546E-03 --3.4115941617440990E-03 --3.3882076830302004E-03 --3.3649304892837384E-03 --3.3417623415188018E-03 --3.3187030002053836E-03 --3.2957522255223815E-03 --3.2729097771369729E-03 --3.2501754144878339E-03 --3.2275488965109490E-03 --3.2050299818319945E-03 --3.1826184283634653E-03 --3.1603139931829071E-03 --3.1381164332299075E-03 --3.1160255053992235E-03 --3.0940409664109154E-03 --3.0721625721087356E-03 --3.0503900777641363E-03 --3.0287232383359552E-03 --3.0071618083704768E-03 --2.9857055421704951E-03 --2.9643541934765258E-03 --2.9431075157579064E-03 --2.9219652619231051E-03 --2.9009271844201074E-03 --2.8799930354864206E-03 --2.8591625670724989E-03 --2.8384355308584265E-03 --2.8178116776224477E-03 --2.7972907577333522E-03 --2.7768725214243240E-03 --2.7565567187929027E-03 --2.7363430995465563E-03 --2.7162314125511286E-03 --2.6962214064012503E-03 --2.6763128293115566E-03 --2.6565054292466282E-03 --2.6367989539131287E-03 --2.6171931507217574E-03 --2.5976877667754053E-03 --2.5782825484297390E-03 --2.5589772417621572E-03 --2.5397715925220997E-03 --2.5206653462044484E-03 --2.5016582479984177E-03 --2.4827500426682081E-03 --2.4639404747325167E-03 --2.4452292881309923E-03 --2.4266162265364440E-03 --2.4081010333495854E-03 --2.3896834517248096E-03 --2.3713632245146352E-03 --2.3531400940653819E-03 --2.3350138025129818E-03 --2.3169840916248325E-03 --2.2990507029389340E-03 --2.2812133776239406E-03 --2.2634718564644783E-03 --2.2458258799701808E-03 --2.2282751881264164E-03 --2.2108195207305920E-03 --2.1934586175104908E-03 --2.1761922180891799E-03 --2.1590200615380023E-03 --2.1419418862188774E-03 --2.1249574303577844E-03 --2.1080664321697583E-03 --2.0912686297412733E-03 --2.0745637606308922E-03 --2.0579515619998101E-03 --2.0414317708116235E-03 --2.0250041237839154E-03 --2.0086683574381710E-03 --1.9924242078623558E-03 --1.9762714109181159E-03 --1.9602097022670658E-03 --1.9442388173801580E-03 --1.9283584914676043E-03 --1.9125684593021286E-03 --1.8968684554785357E-03 --1.8812582143980525E-03 --1.8657374702990080E-03 --1.8503059570117819E-03 --1.8349634079227143E-03 --1.8197095563147136E-03 --1.8045441354615701E-03 --1.7894668785031814E-03 --1.7744775181492778E-03 --1.7595757868146193E-03 --1.7447614167310629E-03 --1.7300341399234444E-03 --1.7153936882470576E-03 --1.7008397932728194E-03 --1.6863721863968513E-03 --1.6719905987619430E-03 --1.6576947612931636E-03 --1.6434844047356714E-03 --1.6293592596089844E-03 --1.6153190562977723E-03 --1.6013635250658298E-03 --1.5874923960411255E-03 --1.5737053989664154E-03 --1.5600022632177380E-03 --1.5463827181158921E-03 --1.5328464930519845E-03 --1.5193933172838534E-03 --1.5060229196543432E-03 --1.4927350287530499E-03 --1.4795293731301650E-03 --1.4664056813141352E-03 --1.4533636816494186E-03 --1.4404031021392840E-03 --1.4275236706172291E-03 --1.4147251147859467E-03 --1.4020071622206356E-03 --1.3893695404260185E-03 --1.3768119768658297E-03 --1.3643341988342846E-03 --1.3519359332706028E-03 --1.3396169069380785E-03 --1.3273768466595638E-03 --1.3152154792737732E-03 --1.3031325313936147E-03 --1.2911277292956963E-03 --1.2792007991455254E-03 --1.2673514672158965E-03 --1.2555794597364023E-03 --1.2438845027249329E-03 --1.2322663219887292E-03 --1.2207246432417375E-03 --1.2092591921665156E-03 --1.1978696943409561E-03 --1.1865558752544557E-03 --1.1753174602902423E-03 --1.1641541747384344E-03 --1.1530657438046934E-03 --1.1420518925906284E-03 --1.1311123461361808E-03 --1.1202468293939379E-03 --1.1094550674512300E-03 --1.0987367854320093E-03 --1.0880917081488746E-03 --1.0775195599764529E-03 --1.0670200652780912E-03 --1.0565929489680926E-03 --1.0462379360171971E-03 --1.0359547509538360E-03 --1.0257431179235984E-03 --1.0156027611512538E-03 --1.0055334051926163E-03 --9.9553477455694502E-04 --9.8560659374571881E-04 --9.7574858718047625E-04 --9.6596047911517676E-04 --9.5624199363403045E-04 --9.4659285484370614E-04 --9.3701278715012241E-04 --9.2750151490963073E-04 --9.1805876234880759E-04 --9.0868425357242108E-04 --8.9937771277196442E-04 --8.9013886430146195E-04 --8.8096743244368261E-04 --8.7186314147848719E-04 --8.6282571560650017E-04 --8.5385487909476955E-04 --8.4495035621656408E-04 --8.3611187129778810E-04 --8.2733914884678935E-04 --8.1863191329328464E-04 --8.0998988901074935E-04 --8.0141280028985201E-04 --7.9290037163903164E-04 --7.8445232774002483E-04 --7.7606839321017426E-04 --7.6774829265569683E-04 --7.5949175063772672E-04 --7.5129849202005465E-04 --7.4316824172812373E-04 --7.3510072471195498E-04 --7.2709566596299577E-04 --7.1915279042412267E-04 --7.1127182311443325E-04 --7.0345248902960698E-04 --6.9569451362140892E-04 --6.8799762253793752E-04 --6.8036154128123011E-04 --6.7278599519145839E-04 --6.6527070963257767E-04 --6.5781541045351641E-04 --6.5041982355745938E-04 --6.4308367500766231E-04 --6.3580669094909811E-04 --6.2858859755658605E-04 --6.2142912115969995E-04 --6.1432798807191543E-04 --6.0728492489287706E-04 --6.0029965825730673E-04 --5.9337191502306457E-04 --5.8650142224559050E-04 --5.7968790699445118E-04 --5.7293109652128255E-04 --5.6623071807342996E-04 --5.5958649929814227E-04 --5.5299816796398676E-04 --5.4646545195486068E-04 --5.3998807931388449E-04 --5.3356577811387125E-04 --5.2719827674354376E-04 --5.2088530361400472E-04 --5.1462658755893110E-04 --5.0842185761446371E-04 --5.0227084287319461E-04 --4.9617327257290775E-04 --4.9012887599437268E-04 --4.8413738290993248E-04 --4.7819852316742457E-04 --4.7231202689161888E-04 --4.6647762439216441E-04 --4.6069504610442980E-04 --4.5496402282007783E-04 --4.4928428535860739E-04 --4.4365556494569151E-04 --4.3807759289920032E-04 --4.3255010083184290E-04 --4.2707282064476684E-04 --4.2164548434268668E-04 --4.1626782435096981E-04 --4.1093957313386473E-04 --4.0566046358323871E-04 --4.0043022874650347E-04 --3.9524860193381313E-04 --3.9011531681798262E-04 --3.8503010715722826E-04 --3.7999270719302924E-04 --3.7500285123114757E-04 --3.7006027400288751E-04 --3.6516471046818956E-04 --3.6031589581858033E-04 --3.5551356569167477E-04 --3.5075745579806421E-04 --3.4604730237212586E-04 --3.4138284175457169E-04 --3.3676381070935291E-04 --3.3218994632394915E-04 --3.2766098586771284E-04 --3.2317666710372003E-04 --3.1873672787036350E-04 --3.1434090659335218E-04 --3.0998894187846268E-04 --3.0568057270643361E-04 --3.0141553845547598E-04 --2.9719357866016391E-04 --2.9301443343601069E-04 --2.8887784298864069E-04 --2.8478354811130476E-04 --2.8073128985488461E-04 --2.7672080959430950E-04 --2.7275184917765734E-04 --2.6882415059348861E-04 --2.6493745651342177E-04 --2.6109150973853152E-04 --2.5728605360626696E-04 --2.5352083178068293E-04 --2.4979558823239479E-04 --2.4611006753850274E-04 --2.4246401439387931E-04 --2.3885717416921861E-04 --2.3528929240944851E-04 --2.3176011519372800E-04 --2.2826938904922092E-04 --2.2481686075505455E-04 --2.2140227776709878E-04 --2.1802538766187531E-04 --2.1468593872472498E-04 --2.1138367949544940E-04 --2.0811835899325055E-04 --2.0488972678255960E-04 --2.0169753264448739E-04 --1.9854152713227036E-04 --1.9542146094269180E-04 --1.9233708545874614E-04 --1.8928815240240327E-04 --1.8627441392900555E-04 --1.8329562285782422E-04 --1.8035153219041013E-04 --1.7744189574832826E-04 --1.7456646754139663E-04 --1.7172500226076562E-04 --1.6891725505679221E-04 --1.6614298144328814E-04 --1.6340193768212523E-04 --1.6069388020196562E-04 --1.5801856629227715E-04 --1.5537575350271424E-04 --1.5276520002033855E-04 --1.5018666461077699E-04 --1.4763990634869710E-04 --1.4512468515387662E-04 --1.4264076111769955E-04 --1.4018789519714350E-04 --1.3776584870143439E-04 --1.3537438351745909E-04 --1.3301326223343261E-04 --1.3068224769933806E-04 --1.2838110369311597E-04 --1.2610959419443761E-04 --1.2386748403439595E-04 --1.2165453851074209E-04 --1.1947052342311985E-04 --1.1731520538294962E-04 --1.1518835123176303E-04 --1.1308972880918360E-04 --1.1101910621616365E-04 --1.0897625235200548E-04 --1.0696093670140786E-04 --1.0497292918973958E-04 --1.0301200068544597E-04 --1.0107792227090017E-04 --9.9170466028242866E-05 --9.7289404379623709E-05 --9.5434510508919665E-05 --9.3605558343344794E-05 --9.1802322170421322E-05 --9.0024577286872091E-05 --8.8272099214928412E-05 --8.6544664508034769E-05 --8.4842050184082081E-05 --8.3164033922660490E-05 --8.1510394258685348E-05 --7.9880910043021695E-05 --7.8275361250888421E-05 --7.6693528125808947E-05 --7.5135191878104651E-05 --7.3600134295932177E-05 --7.2088137763800901E-05 --7.0598985682396995E-05 --6.9132461732017748E-05 --6.7688350758013800E-05 --6.6266437943586119E-05 --6.4866509370281846E-05 --6.3488351830623269E-05 --6.2131752639655669E-05 --6.0796500279260081E-05 --5.9482383499782878E-05 --5.8189192198048941E-05 --5.6916716700441597E-05 --5.5664748188746446E-05 --5.4433078738190337E-05 --5.3221500853924548E-05 --5.2029808279362243E-05 --5.0857795045990405E-05 --4.9705256333454204E-05 --4.8571987885717402E-05 --4.7457786207323342E-05 --4.6362448847097532E-05 --4.5285773719928239E-05 --4.4227560048911545E-05 --4.3187607398383365E-05 --4.2165716444990154E-05 --4.1161688585118335E-05 --4.0175325877181225E-05 --3.9206431569420497E-05 --3.8254809238958114E-05 --3.7320263805178997E-05 --3.6402600615902135E-05 --3.5501626063629159E-05 --3.4617147429223842E-05 --3.3748972556959164E-05 --3.2896910605982699E-05 --3.2060771059989005E-05 --3.1240364754008077E-05 --3.0435503075644489E-05 --2.9645998360423207E-05 --2.8871664000356697E-05 --2.8112313866896989E-05 --2.7367763255532748E-05 --2.6637827815829915E-05 --2.5922324512728389E-05 --2.5221071012056296E-05 --2.4533885822962783E-05 --2.3860588682662877E-05 --2.3200999743672472E-05 --2.2554940653809281E-05 --2.1922233482117965E-05 --2.1302701548139890E-05 --2.0696169042568337E-05 --2.0102460887717949E-05 --1.9521403391261483E-05 --1.8952823243427120E-05 --1.8396548661240838E-05 --1.7852408390442053E-05 --1.7320232335176678E-05 --1.6799851453934370E-05 --1.6291097329537879E-05 --1.5793803066222031E-05 --1.5307802153529246E-05 --1.4832929597829065E-05 --1.4369021077199254E-05 --1.3915913314959273E-05 --1.3473444274851892E-05 --1.3041452454146599E-05 --1.2619777981464988E-05 --1.2208261412796787E-05 --1.1806744766557706E-05 --1.1415070901082499E-05 --1.1033083600857591E-05 --1.0660628078921606E-05 --1.0297550015159971E-05 --9.9436967782841585E-06 --9.5989162476936682E-06 --9.2630576887733590E-06 --8.9359714024908030E-06 --8.6175084867699044E-06 --8.3075216278896204E-06 --8.0058639510487062E-06 --7.7123902942341858E-06 --7.4269561352966987E-06 --7.1494182222825244E-06 --6.8796345375438955E-06 --6.6174637460391822E-06 --6.3627662477884830E-06 --6.1154028937153889E-06 --5.8752362136705833E-06 --5.6421295388717485E-06 --5.4159473448798706E-06 --5.1965555507802430E-06 --4.9838206597922241E-06 --4.7776110079803640E-06 --4.5777954380754293E-06 --4.3842444084648691E-06 --4.1968293739024907E-06 --4.0154227912244958E-06 --3.8398987524013030E-06 --3.6701318702153031E-06 --3.5059986473377809E-06 --3.3473761972518761E-06 --3.1941431458350472E-06 --3.0461793276526586E-06 --2.9033654402268198E-06 --2.7655839894378111E-06 --2.6327179800815733E-06 --2.5046523101562153E-06 --2.3812726378908319E-06 --2.2624660031665923E-06 --2.1481208765077795E-06 --2.0381264652071239E-06 --1.9323739260101182E-06 --1.8307549382985746E-06 --1.7331630303884202E-06 --1.6394926781349244E-06 --1.5496395896960071E-06 --1.4635011232392726E-06 --1.3809752738781330E-06 --1.3019620841974486E-06 --1.2263621924884995E-06 --1.1540779985199892E-06 --1.0850130652247535E-06 --1.0190720314579710E-06 --9.5616139113206374E-07 --8.9618821494809214E-07 --8.3906166372703315E-07 --7.8469161920758900E-07 --7.3298960081373045E-07 --6.8386852498144298E-07 --6.3724223243528717E-07 --5.9302659746188971E-07 --5.5113805803516372E-07 --5.1149512921998357E-07 --4.7401721986305185E-07 --4.3862522492195062E-07 --4.0524167649784477E-07 --3.7378989761254867E-07 --3.4419538539944439E-07 --3.1638423837153242E-07 --2.9028456799446366E-07 --2.6582559051198878E-07 --2.4293784044872722E-07 --2.2155372356109570E-07 --2.0160633578841759E-07 --1.8303103638892896E-07 --1.6576387826786613E-07 --1.4974281872359629E-07 --1.3490715871662587E-07 --1.2119734527805726E-07 --1.0855591079076116E-07 --9.6926023510697599E-08 --8.6253142811747643E-08 --7.6483570280147638E-08 --6.7565366022824746E-08 --5.9448188672952328E-08 --5.2082680027798947E-08 --4.5421749218780839E-08 --3.9418939200538479E-08 --3.4030052304184809E-08 --2.9211930523291616E-08 --2.4923002032196035E-08 --2.1123551603816595E-08 --1.7774708188211632E-08 --1.4840004768110087E-08 --1.2283662211193978E-08 --1.0072075765680320E-08 --8.1729161117859187E-09 --6.5552536844471314E-09 --5.1902627257924186E-09 --4.0498623908161411E-09 --3.1084525876479716E-09 --2.3412351004530040E-09 --1.7254578605217315E-09 --1.2399087068752733E-09 --8.6458172271089042E-10 --5.8178382260726852E-10 --3.7452781396295662E-10 --2.2836778144045774E-10 --1.2984454235602814E-10 --6.7236827672240006E-11 --3.0505124743462454E-11 --1.0905646398647518E-11 --2.8805883124883647E-12 --1.3797189552921306E-12 --1.3507849106008097E-12 --5.9470967841909250E-02 --5.9484924489087571E-02 --5.9498861482588324E-02 --5.9512778827167129E-02 --5.9526676527579578E-02 --5.9540554588581249E-02 --5.9554413014927747E-02 --5.9568251811374671E-02 --5.9582070982677621E-02 --5.9595870533592180E-02 --5.9609650468873940E-02 --5.9623410793278500E-02 --5.9637151511561466E-02 --5.9650872628478423E-02 --5.9664574148784962E-02 --5.9678256077236688E-02 --5.9691918418589188E-02 --5.9705561177598065E-02 --5.9719184359018893E-02 --5.9732787967607288E-02 --5.9746372008118859E-02 --5.9759936485309167E-02 --5.9773481403933820E-02 --5.9787006768748409E-02 --5.9800512584508539E-02 --5.9813998855969802E-02 --5.9827465587887790E-02 --5.9840912785018102E-02 --5.9854340452116322E-02 --5.9867748593938057E-02 --5.9881137215238897E-02 --5.9894506320774435E-02 --5.9907855915300276E-02 --5.9921186003571998E-02 --5.9934496590345207E-02 --5.9947787680375501E-02 --5.9961059278418466E-02 --5.9974311389229706E-02 --5.9987544017564801E-02 --6.0000757168179368E-02 --6.0013950845828987E-02 --6.0027125055269262E-02 --6.0040279801255765E-02 --6.0053415088544115E-02 --6.0066530921889898E-02 --6.0079627306048711E-02 --6.0092704245776146E-02 --6.0105761745827803E-02 --6.0118799810959286E-02 --6.0131818445926161E-02 --6.0144817655484045E-02 --6.0157797444388525E-02 --6.0170757817395205E-02 --6.0183698779259664E-02 --6.0196620334737508E-02 --6.0209522488584341E-02 --6.0222405245555735E-02 --6.0235268610407303E-02 --6.0248112587894635E-02 --6.0260937182773325E-02 --6.0273742399798963E-02 --6.0286528243727155E-02 --6.0299294719313487E-02 --6.0312041831313550E-02 --6.0324769584482955E-02 --6.0337477983577290E-02 --6.0350167033352137E-02 --6.0362836738563103E-02 --6.0375487103965800E-02 --6.0388118134315771E-02 --6.0400729834368665E-02 --6.0413322208880058E-02 --6.0425895262605542E-02 --6.0438449000300702E-02 --6.0450983426721158E-02 --6.0463498546622481E-02 --6.0475994364760283E-02 --6.0488470885890142E-02 --6.0500928114767670E-02 --6.0513366056148446E-02 --6.0525784714788082E-02 --6.0538184095442156E-02 --6.0550564202866274E-02 --6.0562925041816026E-02 --6.0575266617047013E-02 --6.0587588933314826E-02 --6.0599891995375056E-02 --6.0612175807983310E-02 --6.0624440375895164E-02 --6.0636685703866225E-02 --6.0648911796652091E-02 --6.0661118659008348E-02 --6.0673306295690593E-02 --6.0685474711454426E-02 --6.0697623911055446E-02 --6.0709753899249229E-02 --6.0721864680791396E-02 --6.0733956260437510E-02 --6.0746028642943192E-02 --6.0758081833064040E-02 --6.0770115835555624E-02 --6.0782130655173558E-02 --6.0794126296673426E-02 --6.0806102764810827E-02 --6.0818060064341359E-02 --6.0829998200020621E-02 --6.0841917176604199E-02 --6.0853816998847690E-02 --6.0865697671506694E-02 --6.0877559199336795E-02 --6.0889401587093592E-02 --6.0901224839532697E-02 --6.0913028961409668E-02 --6.0924813957480131E-02 --6.0936579832499685E-02 --6.0948326591223900E-02 --6.0960054238408390E-02 --6.0971762778808739E-02 --6.0983452217180545E-02 --6.0995122558279401E-02 --6.1006773806860905E-02 --6.1018405967680656E-02 --6.1030019045494238E-02 --6.1041613045057258E-02 --6.1053187971125307E-02 --6.1064743828453977E-02 --6.1076280621798859E-02 --6.1087798355915567E-02 --6.1099297035559663E-02 --6.1110776665486782E-02 --6.1122237250452488E-02 --6.1133678795212379E-02 --6.1145101304522054E-02 --6.1156504783137125E-02 --6.1167889235813164E-02 --6.1179254667305782E-02 --6.1190601082370552E-02 --6.1201928485763099E-02 --6.1213236882238987E-02 --6.1224526276553837E-02 --6.1235796673463225E-02 --6.1247048077722757E-02 --6.1258280494088026E-02 --6.1269493927314622E-02 --6.1280688382158152E-02 --6.1291863863374194E-02 --6.1303020375718359E-02 --6.1314157923946233E-02 --6.1325276512813401E-02 --6.1336376147075475E-02 --6.1347456831488054E-02 --6.1358518570806708E-02 --6.1369561369787058E-02 --6.1380585233184681E-02 --6.1391590165755183E-02 --6.1402576172254156E-02 --6.1413543257437184E-02 --6.1424491426059880E-02 --6.1435420682877842E-02 --6.1446331032646635E-02 --6.1457222480121879E-02 --6.1468095030059157E-02 --6.1478948687214069E-02 --6.1489783456342213E-02 --6.1500599342199182E-02 --6.1511396349540573E-02 --6.1522174483121979E-02 --6.1532933747698984E-02 --6.1543674148027194E-02 --6.1554395688862208E-02 --6.1565098374959611E-02 --6.1575782211075000E-02 --6.1586447201963976E-02 --6.1597093352382129E-02 --6.1607720667085059E-02 --6.1618329150828349E-02 --6.1628918808367607E-02 --6.1639489644458423E-02 --6.1650041663856389E-02 --6.1660574871317098E-02 --6.1671089271596161E-02 --6.1681584869449149E-02 --6.1692061669631676E-02 --6.1702519676899326E-02 --6.1712958896007711E-02 --6.1723379331712402E-02 --6.1733780988769013E-02 --6.1744163871933114E-02 --6.1754527985960331E-02 --6.1764873335606249E-02 --6.1775199925626439E-02 --6.1785507760776529E-02 --6.1795796845812101E-02 --6.1806067185488749E-02 --6.1816318784562063E-02 --6.1826551647787636E-02 --6.1836765779921095E-02 --6.1846961185717995E-02 --6.1857137869933951E-02 --6.1867295837324539E-02 --6.1877435092645379E-02 --6.1887555640652049E-02 --6.1897657486100155E-02 --6.1907740633745281E-02 --6.1917805088343034E-02 --6.1927850854648997E-02 --6.1937877937418770E-02 --6.1947886341407944E-02 --6.1957876071372125E-02 --6.1967847132066892E-02 --6.1977799528247862E-02 --6.1987733264670608E-02 --6.1997648346090742E-02 --6.2007544777263841E-02 --6.2017422562945512E-02 --6.2027281707891346E-02 --6.2037122216856949E-02 --6.2046944094597899E-02 --6.2056747345869800E-02 --6.2066531975428232E-02 --6.2076297988028828E-02 --6.2086045388427137E-02 --6.2095774181378779E-02 --6.2105484371639347E-02 --6.2115175963964438E-02 --6.2124848963109644E-02 --6.2134503373830550E-02 --6.2144139200882763E-02 --6.2153756449021866E-02 --6.2163355123003472E-02 --6.2172935227583159E-02 --6.2182496767516540E-02 --6.2192039747559186E-02 --6.2201564172466708E-02 --6.2211070046994707E-02 --6.2220557375898766E-02 --6.2230026163934471E-02 --6.2239476415857441E-02 --6.2248908136423253E-02 --6.2258321330387500E-02 --6.2267716002505802E-02 --6.2277092157533714E-02 --6.2286449800226865E-02 --6.2295788935340844E-02 --6.2305109567631231E-02 --6.2314411701853638E-02 --6.2323695342763635E-02 --6.2332960495116857E-02 --6.2342207163668860E-02 --6.2351435353175264E-02 --6.2360645068391639E-02 --6.2369836314073598E-02 --6.2379009094976748E-02 --6.2388163415856665E-02 --6.2397299281468935E-02 --6.2406416696569184E-02 --6.2415515665912968E-02 --6.2424596194255916E-02 --6.2433658286353610E-02 --6.2442701946961637E-02 --6.2451727180835602E-02 --6.2460733992731103E-02 --6.2469722387403726E-02 --6.2478692369609068E-02 --6.2487643944102722E-02 --6.2496577115640287E-02 --6.2505491888977360E-02 --6.2514388268869542E-02 --6.2523266260072402E-02 --6.2532125867341554E-02 --6.2540967095432595E-02 --6.2549789949101112E-02 --6.2558594433102716E-02 --6.2567380552192978E-02 --6.2576148311127511E-02 --6.2584897714661900E-02 --6.2593628767551729E-02 --6.2602341474552625E-02 --6.2611035840420159E-02 --6.2619711869909930E-02 --6.2628369567777536E-02 --6.2637008938778577E-02 --6.2645629987668622E-02 --6.2654232719203312E-02 --6.2662817138138205E-02 --6.2671383249228899E-02 --6.2679931057231006E-02 --6.2688460566900098E-02 --6.2696971782991787E-02 --6.2705464710261671E-02 --6.2713939353465337E-02 --6.2722395717358381E-02 --6.2730833806696390E-02 --6.2739253626234975E-02 --6.2747655180729708E-02 --6.2756038474936215E-02 --6.2764403513610068E-02 --6.2772750301506863E-02 --6.2781078843382201E-02 --6.2789389143991681E-02 --6.2797681208090900E-02 --6.2805955040435429E-02 --6.2814210645780896E-02 --6.2822448028882871E-02 --6.2830667194496967E-02 --6.2838868147378754E-02 --6.2847050892283846E-02 --6.2855215433967840E-02 --6.2863361777186322E-02 --6.2871489926694890E-02 --6.2879599887249144E-02 --6.2887691663604667E-02 --6.2895765260517073E-02 --6.2903820682741932E-02 --6.2911857935034857E-02 --6.2919877022151433E-02 --6.2927877948847272E-02 --6.2935860719877945E-02 --6.2943825339999065E-02 --6.2951771813966204E-02 --6.2959700146534986E-02 --6.2967610342460983E-02 --6.2975502406499823E-02 --6.2983376343407060E-02 --6.2991232157938309E-02 --6.2999069854849168E-02 --6.3006889438895222E-02 --6.3014690914832069E-02 --6.3022474287415309E-02 --6.3030239561400525E-02 --6.3037986741543331E-02 --6.3045715832599311E-02 --6.3053426839324050E-02 --6.3061119766473162E-02 --6.3068794618802243E-02 --6.3076451401066852E-02 --6.3084090118022629E-02 --6.3091710774425144E-02 --6.3099313375029997E-02 --6.3106897924592786E-02 --6.3114464427869096E-02 --6.3122012889614540E-02 --6.3129543314584702E-02 --6.3137055707535167E-02 --6.3144550073221548E-02 --6.3152026416399429E-02 --6.3159484741824409E-02 --6.3166925054252088E-02 --6.3174347358438035E-02 --6.3181751659137877E-02 --6.3189137961107200E-02 --6.3196506269101588E-02 --6.3203856587876653E-02 --6.3211188922187966E-02 --6.3218503276791155E-02 --6.3225799656441775E-02 --6.3233078065895454E-02 --6.3240338509907776E-02 --6.3247580993234326E-02 --6.3254805520630730E-02 --6.3262012096852532E-02 --6.3269200726655372E-02 --6.3276371414794835E-02 --6.3283524166026492E-02 --6.3290658985105969E-02 --6.3297775876788837E-02 --6.3304874845830708E-02 --6.3311955896987154E-02 --6.3319019035013802E-02 --6.3326064264666235E-02 --6.3333091590700039E-02 --6.3340101017870812E-02 --6.3347092550934153E-02 --6.3354066194645647E-02 --6.3361021953760907E-02 --6.3367959833035503E-02 --6.3374879837225062E-02 --6.3381781971085155E-02 --6.3388666239371366E-02 --6.3395532646839323E-02 --6.3402381198244609E-02 --6.3409211898342796E-02 --6.3416024751889510E-02 --6.3422819763640337E-02 --6.3429596938350874E-02 --6.3436356280776693E-02 --6.3443097795673420E-02 --6.3449821487796626E-02 --6.3456527361901924E-02 --6.3463215422744898E-02 --6.3469885675081147E-02 --6.3476538123666271E-02 --6.3483172773255853E-02 --6.3489789628605492E-02 --6.3496388694470787E-02 --6.3502969975607323E-02 --6.3509533476770713E-02 --6.3516079202716541E-02 --6.3522607158200392E-02 --6.3529117347977879E-02 --6.3535609776804586E-02 --6.3542084449436126E-02 --6.3548541370628056E-02 --6.3554980545136003E-02 --6.3561401977715565E-02 --6.3567805673122313E-02 --6.3574191636111846E-02 --6.3580559871439776E-02 --6.3586910383861689E-02 --6.3593243178133169E-02 --6.3599558259009842E-02 --6.3605855631247266E-02 --6.3612135299601053E-02 --6.3618397268826801E-02 --6.3624641543680097E-02 --6.3630868128916551E-02 --6.3637077029291722E-02 --6.3643268249561263E-02 --6.3649441794480718E-02 --6.3655597668805700E-02 --6.3661735877291792E-02 --6.3667856424694622E-02 --6.3673959315769746E-02 --6.3680044555272791E-02 --6.3686112147959328E-02 --6.3692162098584956E-02 --6.3698194411905287E-02 --6.3704209092675892E-02 --6.3710206145652384E-02 --6.3716185575590362E-02 --6.3722147387245395E-02 --6.3728091585373098E-02 --6.3734018174729068E-02 --6.3739927160068877E-02 --6.3745818546148150E-02 --6.3751692337722460E-02 --6.3757548539547418E-02 --6.3763387156378609E-02 --6.3769208192971619E-02 --6.3775011654082059E-02 --6.3780797544465528E-02 --6.3786565868877598E-02 --6.3792316632073895E-02 --6.3798049838809989E-02 --6.3803765493841480E-02 --6.3809463601923966E-02 --6.3815144167813032E-02 --6.3820807196264290E-02 --6.3826452692033325E-02 --6.3832080659875751E-02 --6.3837691104547123E-02 --6.3843284030803069E-02 --6.3848859443399159E-02 --6.3854417347091019E-02 --6.3859957746634222E-02 --6.3865480646784378E-02 --6.3870986052297060E-02 --6.3876473967927880E-02 --6.3881944398432422E-02 --6.3887397348566299E-02 --6.3892832823085083E-02 --6.3898250826744385E-02 --6.3903651364299791E-02 --6.3909034440506898E-02 --6.3914400060121307E-02 --6.3919748227898615E-02 --6.3925078948594394E-02 --6.3930392226964269E-02 --6.3935688067763813E-02 --6.3940966475748623E-02 --6.3946227455674326E-02 --6.3951471012296465E-02 --6.3956697150370667E-02 --6.3961905874652530E-02 --6.3967097189897626E-02 --6.3972271100861580E-02 --6.3977427612299964E-02 --6.3982566728968376E-02 --6.3987688455622416E-02 --6.3992792797017681E-02 --6.3997879757909756E-02 --6.4002949343054241E-02 --6.4008001557206734E-02 --6.4013036405122820E-02 --6.4018053891558124E-02 --6.4023054021268205E-02 --6.4028036799008675E-02 --6.4033002229535119E-02 --6.4037950317603148E-02 --6.4042881067968335E-02 --6.4047794485386292E-02 --6.4052690574612603E-02 --6.4057569340402881E-02 --6.4062430787512697E-02 --6.4067274920697678E-02 --6.4072101744713381E-02 --6.4076911264315417E-02 --6.4081703484259400E-02 --6.4086478409300901E-02 --6.4091236044195504E-02 --6.4095976393698850E-02 --6.4100699462566482E-02 --6.4105405255554027E-02 --6.4110093777417068E-02 --6.4114765032911206E-02 --6.4119419026792038E-02 --6.4124055763815135E-02 --6.4128675248736139E-02 --6.4133277486310591E-02 --6.4137862481294133E-02 --6.4142430238442322E-02 --6.4146980762510783E-02 --6.4151514058255088E-02 --6.4156030130430836E-02 --6.4160528983793638E-02 --6.4165010623099067E-02 --6.4169475053102748E-02 --6.4173922278560239E-02 --6.4178352304227165E-02 --6.4182765134859099E-02 --6.4187160775211652E-02 --6.4191539230040409E-02 --6.4195900504100969E-02 --6.4200244602148931E-02 --6.4204571528939880E-02 --6.4208881289229414E-02 --6.4213173887773131E-02 --6.4217449329326631E-02 --6.4221707618645499E-02 --6.4225948760485332E-02 --6.4230172759601731E-02 --6.4234379620750279E-02 --6.4238569348686589E-02 --6.4242741948166232E-02 --6.4246897423944835E-02 --6.4251035780777954E-02 --6.4255157023421230E-02 --6.4259261156630207E-02 --6.4263348185160524E-02 --6.4267418113767738E-02 --6.4271470947207476E-02 --6.4275506690235323E-02 --6.4279525347606864E-02 --6.4283526924077697E-02 --6.4287511424403421E-02 --6.4291478853339634E-02 --6.4295429215641922E-02 --6.4299362516065897E-02 --6.4303278759367144E-02 --6.4307177950301248E-02 --6.4311060093623806E-02 --6.4314925194090419E-02 --6.4318773256456685E-02 --6.4322604285478202E-02 --6.4326418285910555E-02 --6.4330215262509344E-02 --6.4333995220030166E-02 --6.4337758163228606E-02 --6.4341504096860264E-02 --6.4345233025680737E-02 --6.4348944954445625E-02 --6.4352639887910512E-02 --6.4356317830830984E-02 --6.4359978787962679E-02 --6.4363622764061143E-02 --6.4367249763882001E-02 --6.4370859792180823E-02 --6.4374452853713238E-02 --6.4378028953234800E-02 --6.4381588095501138E-02 --6.4385130285267836E-02 --6.4388655527290492E-02 --6.4392163826324678E-02 --6.4395655187126019E-02 --6.4399129614450101E-02 --6.4402587113052523E-02 --6.4406027687688855E-02 --6.4409451343114710E-02 --6.4412858084085700E-02 --6.4416247915357383E-02 --6.4419620841685371E-02 --6.4422976867825277E-02 --6.4426315998532685E-02 --6.4429638238563167E-02 --6.4432943592672348E-02 --6.4436232065615801E-02 --6.4439503662149136E-02 --6.4442758387027940E-02 --6.4445996245007811E-02 --6.4449217240844348E-02 --6.4452421379293134E-02 --6.4455608665109784E-02 --6.4458779103049868E-02 --6.4461932697869012E-02 --6.4465069454322774E-02 --6.4468189377166765E-02 --6.4471292471156599E-02 --6.4474378741047833E-02 --6.4477448191596107E-02 --6.4480500827556964E-02 --6.4483536653686058E-02 --6.4486555674738932E-02 --6.4489557895471200E-02 --6.4492543320638460E-02 --6.4495511954996310E-02 --6.4498463803300335E-02 --6.4501398870306148E-02 --6.4504317160769320E-02 --6.4507218679445463E-02 --6.4510103431090163E-02 --6.4512971420459017E-02 --6.4515822652307611E-02 --6.4518657131391557E-02 --6.4521474862466455E-02 --6.4524275850287874E-02 --6.4527060099611427E-02 --6.4529827615192700E-02 --6.4532578401787291E-02 --6.4535312464150799E-02 --6.4538029807038821E-02 --6.4540730435206931E-02 --6.4543414353410752E-02 --6.4546081566405872E-02 --6.4548732078947874E-02 --6.4551365895792356E-02 --6.4553983021694933E-02 --6.4556583461411160E-02 --6.4559167219696664E-02 --6.4561734301307031E-02 --6.4564284710997857E-02 --6.4566818453524744E-02 --6.4569335533643274E-02 --6.4571835956109033E-02 --6.4574319725677648E-02 --6.4576786847104689E-02 --6.4579237325145755E-02 --6.4581671164556459E-02 --6.4584088370092357E-02 --6.4586488946509077E-02 --6.4588872898562216E-02 --6.4591240231007346E-02 --6.4593590948600066E-02 --6.4595925056095987E-02 --6.4598242558250696E-02 --6.4600543459819776E-02 --6.4602827765558840E-02 --6.4605095480223473E-02 --6.4607346608569288E-02 --6.4609581155351842E-02 --6.4611799125326760E-02 --6.4614000523249629E-02 --6.4616185353876060E-02 --6.4618353621961611E-02 --6.4620505332261907E-02 --6.4622640489532535E-02 --6.4624759098529078E-02 --6.4626861164007149E-02 --6.4628946690722347E-02 --6.4631015683430243E-02 --6.4633068146886449E-02 --6.4635104085846551E-02 --6.4637123505066146E-02 --6.4639126409300834E-02 --6.4641112803306214E-02 --6.4643082691837869E-02 --6.4645036079651400E-02 --6.4646972971502403E-02 --6.4648893372146465E-02 --6.4650797286339184E-02 --6.4652684718836173E-02 --6.4654555674392988E-02 --6.4656410157765271E-02 --6.4658248173708577E-02 --6.4660069726978520E-02 --6.4661874822330698E-02 --6.4663663464520696E-02 --6.4665435658304113E-02 --6.4667191408436547E-02 --6.4668930719673584E-02 --6.4670653596770822E-02 --6.4672360044483873E-02 --6.4674050067568309E-02 --6.4675723670779728E-02 --6.4677380858873743E-02 --6.4679021636605938E-02 --6.4680646008731885E-02 --6.4682253980007209E-02 --6.4683845555187511E-02 --6.4685420739028360E-02 --6.4686979536285355E-02 --6.4688521951714109E-02 --6.4690047990070193E-02 --6.4691557656109233E-02 --6.4693050954586800E-02 --6.4694527890258480E-02 --6.4695988467879897E-02 --6.4697432692206625E-02 --6.4698860567994260E-02 --6.4700272099998415E-02 --6.4701667292974663E-02 --6.4703046151678600E-02 --6.4704408680865855E-02 --6.4705754885291969E-02 --6.4707084769712570E-02 --6.4708398338883255E-02 --6.4709695597559624E-02 --6.4710976550497235E-02 --6.4712241202451712E-02 --6.4713489558178655E-02 --6.4714721622433649E-02 --6.4715937399972279E-02 --6.4717136895550156E-02 --6.4718320113922867E-02 --6.4719487059846009E-02 --6.4720637738075182E-02 --6.4721772153365970E-02 --6.4722890310473985E-02 --6.4723992214154785E-02 --6.4725077869164011E-02 --6.4726147280257232E-02 --6.4727200452190048E-02 --6.4728237389718057E-02 --6.4729258097596845E-02 --6.4730262580582024E-02 --6.4731250843429164E-02 --6.4732222890893878E-02 --6.4733178727731766E-02 --6.4734118358698398E-02 --6.4735041788549386E-02 --6.4735949022040329E-02 --6.4736840063926826E-02 --6.4737714918964448E-02 --6.4738573591908807E-02 --6.4739416087515489E-02 --6.4740242410540105E-02 --6.4741052565738241E-02 --6.4741846557865482E-02 --6.4742624391677439E-02 --6.4743386071929698E-02 --6.4744131603377858E-02 --6.4744860990777503E-02 --6.4745574238884246E-02 --6.4746271352453671E-02 --6.4746952336241365E-02 --6.4747617195002938E-02 --6.4748265933493976E-02 --6.4748898556470078E-02 --6.4749515068686841E-02 --6.4750115474899853E-02 --6.4750699779864709E-02 --6.4751267988337011E-02 --6.4751820105072355E-02 --6.4752356134826328E-02 --6.4752876082354527E-02 --6.4753379952412551E-02 --6.4753867749755986E-02 --6.4754339479140444E-02 --6.4754795145321509E-02 --6.4755234753054766E-02 --6.4755658307095815E-02 --6.4756065812200267E-02 --6.4756457273123708E-02 --6.4756832694621722E-02 --6.4757192081449907E-02 --6.4757535438363878E-02 --6.4757862770119204E-02 --6.4758174081471498E-02 --6.4758469377176331E-02 --6.4758748661989343E-02 --6.4759011940666078E-02 --6.4759259217962162E-02 --6.4759490498633193E-02 --6.4759705787434729E-02 --6.4759905089122410E-02 --6.4760088408451807E-02 --6.4760255750178519E-02 --6.4760407119058144E-02 --6.4760542519846268E-02 --6.4760661957298502E-02 --6.4760765436170417E-02 --6.4760852961217641E-02 --6.4760924537195730E-02 --6.4760980168860310E-02 --6.4761019860966967E-02 --6.4761043618271286E-02 --6.4761051445528864E-02 --6.4761043347495301E-02 --6.4761019328926209E-02 --6.4760979394577145E-02 --6.4760923549203750E-02 --6.4760851797561581E-02 --6.4760764144406235E-02 --6.4760660594493327E-02 --6.4760541152578455E-02 --6.4760405823417189E-02 --6.4760254611765128E-02 --6.4760087522377899E-02 --6.4759904560011058E-02 --6.4759705729420219E-02 --6.4759491035360967E-02 --6.4759260482588898E-02 --6.4759014075859628E-02 --6.4758751819928739E-02 --6.4758473719551804E-02 --6.4758179779484448E-02 --6.4757870004482257E-02 --6.4757544399300815E-02 --6.4757202968695735E-02 --6.4756845717422601E-02 --6.4756472650236999E-02 --6.4756083771894540E-02 --6.4755679087150811E-02 --6.4755258600761423E-02 --6.4754822317481947E-02 --6.4754370242067982E-02 --6.4753902379275141E-02 --6.4753418733858994E-02 --6.4752919310575155E-02 --6.4752404114179207E-02 --6.4751873149426750E-02 --6.4751326421073396E-02 --6.4750763933874703E-02 --6.4750185692586296E-02 --6.4749591701963760E-02 --6.4748981966762681E-02 --6.4748356491738671E-02 --6.4747715281647328E-02 --6.4747058341244224E-02 --6.4746385675284956E-02 --6.4745697288525139E-02 --6.4744993185720356E-02 --6.4744273371626207E-02 --6.4743537850998290E-02 --6.4742786628592175E-02 --6.4742019709163490E-02 --6.4741237097467805E-02 --6.4740438798260733E-02 --6.4739624816297858E-02 --6.4738795156334766E-02 --6.4737949823127083E-02 --6.4737088821430366E-02 --6.4736212156000256E-02 --6.4735319831592295E-02 --6.4734411852962109E-02 --6.4733488224865285E-02 --6.4732548952057434E-02 --6.4731594039294127E-02 --6.4730623491330963E-02 --6.4729637312923555E-02 --6.4728635508827473E-02 --6.4727618083798330E-02 --6.4726585042591725E-02 --6.4725536389963229E-02 --6.4724472130668453E-02 --6.4723392269462998E-02 --6.4722296811102462E-02 --6.4721185760342415E-02 --6.4720059121938456E-02 --6.4718916900646212E-02 --6.4717759101221239E-02 --6.4716585728419165E-02 --6.4715396786995560E-02 --6.4714192281706023E-02 --6.4712972217306153E-02 --6.4711736598551561E-02 --6.4710485430197806E-02 --6.4709218717000513E-02 --6.4707936463715268E-02 --6.4706638675097655E-02 --6.4705325355903301E-02 --6.4703996510887762E-02 --6.4702652144806652E-02 --6.4701292262415569E-02 --6.4699916868470098E-02 --6.4698525967725837E-02 --6.4697119564938385E-02 --6.4695697664863341E-02 --6.4694260272256290E-02 --6.4692807391872831E-02 --6.4691339028468547E-02 --6.4689855186799053E-02 --6.4688355871619932E-02 --6.4686841087686783E-02 --6.4685310839755206E-02 --6.4683765132580784E-02 --6.4682203970919117E-02 --6.4680627359525802E-02 --6.4679035303156426E-02 --6.4677427806566601E-02 --6.4675804874511911E-02 --6.4674166511747941E-02 --6.4672512723030304E-02 --6.4670843513114584E-02 --6.4669158886756381E-02 --6.4667458848711279E-02 --6.4665743403734904E-02 --6.4664012556582801E-02 --6.4662266312010608E-02 --6.4660504674773911E-02 --6.4658727649628281E-02 --6.4656935241329344E-02 --6.4655127454632672E-02 --6.4653304294293890E-02 --6.4651465765068555E-02 --6.4649611871712281E-02 --6.4647742618980653E-02 --6.4645858011629281E-02 --6.4643958054413753E-02 --6.4642042752089651E-02 --6.4640112109412604E-02 --6.4638166131138181E-02 --6.4636204822021967E-02 --6.4634228186819576E-02 --6.4632236230286605E-02 --6.4630228957178640E-02 --6.4628206372251279E-02 --6.4626168480260121E-02 --6.4624115285960751E-02 --6.4622046794108767E-02 --6.4619963009459769E-02 --6.4617863936769340E-02 --6.4615749580793094E-02 --6.4613619946286616E-02 --6.4611475038005489E-02 --6.4609314860705314E-02 --6.4607139419141715E-02 --6.4604948718070238E-02 --6.4602742762246521E-02 --6.4600521556426135E-02 --6.4598285105364681E-02 --6.4596033413817755E-02 --6.4593766486540957E-02 --6.4591484328289858E-02 --6.4589186943820084E-02 --6.4586874337887207E-02 --6.4584546515246838E-02 --6.4582203480654576E-02 --6.4579845238865979E-02 --6.4577471794636687E-02 --6.4575083152722271E-02 --6.4572679317878329E-02 --6.4570260294860460E-02 --6.4567826088424263E-02 --6.4565376703325322E-02 --6.4562912144319237E-02 --6.4560432416161592E-02 --6.4557937523608000E-02 --6.4555427471414045E-02 --6.4552902264335341E-02 --6.4550361907127457E-02 --6.4547806404545993E-02 --6.4545235761346548E-02 --6.4542649982284719E-02 --6.4540049072116107E-02 --6.4537433035596295E-02 --6.4534801877480882E-02 --6.4532155602525468E-02 --6.4529494215485622E-02 --6.4526817721116986E-02 --6.4524126124175130E-02 --6.4521419429415638E-02 --6.4518697641594111E-02 --6.4515960765466146E-02 --6.4513208805787342E-02 --6.4510441767313298E-02 --6.4507659654799612E-02 --6.4504862473001856E-02 --6.4502050226675628E-02 --6.4499222920576554E-02 --6.4496380559460192E-02 --6.4493523148082169E-02 --6.4490650691198054E-02 --6.4487763193563460E-02 --6.4484860659933974E-02 --6.4481943095065178E-02 --6.4479010503712686E-02 --6.4476062890632097E-02 --6.4473100260578980E-02 --6.4470122618308950E-02 --6.4467129968577605E-02 --6.4464122316140529E-02 --6.4461099665753308E-02 --6.4458062022171567E-02 --6.4455009390150864E-02 --6.4451941774446825E-02 --6.4448859179815049E-02 --6.4445761611011093E-02 --6.4442649072790570E-02 --6.4439521569909092E-02 --6.4436379107122244E-02 --6.4433221689185596E-02 --6.4430049320854776E-02 --6.4426862006885383E-02 --6.4423659752032972E-02 --6.4420442561053171E-02 --6.4417210438701578E-02 --6.4413963389733764E-02 --6.4410701418905342E-02 --6.4407424530971882E-02 --6.4404132730689012E-02 --6.4400826022812316E-02 --6.4397504412097378E-02 --6.4394167903299798E-02 --6.4390816501175188E-02 --6.4387450210479119E-02 --6.4384069035967190E-02 --6.4380672982395012E-02 --6.4377262054518158E-02 --6.4373836257092254E-02 --6.4370395594872856E-02 --6.4366940072615578E-02 --6.4363469695076017E-02 --6.4359984467009773E-02 --6.4356484393172431E-02 --6.4352969478319574E-02 --6.4349439727206831E-02 --6.4345895144589771E-02 --6.4342335735223993E-02 --6.4338761503865083E-02 --6.4335172455268666E-02 --6.4331568594190300E-02 --6.4327949925385611E-02 --6.4324316453610170E-02 --6.4320668183619589E-02 --6.4317005120169468E-02 --6.4313327268015377E-02 --6.4309634631912915E-02 --6.4305927216617709E-02 --6.4302205026885315E-02 --6.4298468067471359E-02 --6.4294716343131400E-02 --6.4290949858621063E-02 --6.4287168618695933E-02 --6.4283372628111610E-02 --6.4279561891623690E-02 --6.4275736413987761E-02 --6.4271896199959405E-02 --6.4268041254294250E-02 --6.4264171581747853E-02 --6.4260287187075840E-02 --6.4256388075033782E-02 --6.4252474250377306E-02 --6.4248545717861968E-02 --6.4244602482243396E-02 --6.4240644548277159E-02 --6.4236671920718871E-02 --6.4232684604324131E-02 --6.4228682603848508E-02 --6.4224665924047603E-02 --6.4220634569677026E-02 --6.4216588545492378E-02 --6.4212527856249230E-02 --6.4208452506703192E-02 --6.4204362501609852E-02 --6.4200257845724806E-02 --6.4196138543803655E-02 --6.4192004600601982E-02 --6.4187856020875400E-02 --6.4183692809379481E-02 --6.4179514970869850E-02 --6.4175322510102065E-02 --6.4171115431831752E-02 --6.4166893740814496E-02 --6.4162657441805881E-02 --6.4158406539561522E-02 --6.4154141038836987E-02 --6.4149860944387904E-02 --6.4145566260969844E-02 --6.4141256993338405E-02 --6.4136933146249187E-02 --6.4132594724457787E-02 --6.4128241732719790E-02 --6.4123874175790810E-02 --6.4119492058426417E-02 --6.4115095385382223E-02 --6.4110684161413814E-02 --6.4106258391276788E-02 --6.4101818079726758E-02 --6.4097363231519280E-02 --6.4092893851409982E-02 --6.4088409944154434E-02 --6.4083911514508263E-02 --6.4079398567227039E-02 --6.4074871107066361E-02 --6.4070329138781829E-02 --6.4065772667129040E-02 --6.4061201696863565E-02 --6.4056616232741032E-02 --6.4052016279517024E-02 --6.4047401841947127E-02 --6.4042772924786939E-02 --6.4038129532792074E-02 --6.4033471670718101E-02 --6.4028799343320619E-02 --6.4024112555355242E-02 --6.4019411311577554E-02 --6.4014695616743139E-02 --6.4009965475607611E-02 --6.4005220892926540E-02 --6.4000461873455539E-02 --6.3995688421950206E-02 --6.3990900543166140E-02 --6.3986098241858913E-02 --6.3981281522784123E-02 --6.3976450390697395E-02 --6.3971604850354288E-02 --6.3966744906510414E-02 --6.3961870563921372E-02 --6.3956981827342746E-02 --6.3952078701530149E-02 --6.3947161191239152E-02 --6.3942229301225367E-02 --6.3937283036244366E-02 --6.3932322401051775E-02 --6.3927347400403178E-02 --6.3922358039054161E-02 --6.3917354321760322E-02 --6.3912336253277247E-02 --6.3907303838360560E-02 --6.3902257081765834E-02 --6.3897195988248667E-02 --6.3892120562564658E-02 --6.3887030809469392E-02 --6.3881926733718480E-02 --6.3876808340067509E-02 --6.3871675633272063E-02 --6.3866528618087753E-02 --6.3861367299270166E-02 --6.3856191681574886E-02 --6.3851001769757526E-02 --6.3845797568573698E-02 --6.3840579082778945E-02 --6.3835346317128908E-02 --6.3830099276379171E-02 --6.3824837965285305E-02 --6.3819562388602924E-02 --6.3814272551087625E-02 --6.3808968457495008E-02 --6.3803650112580657E-02 --6.3798317521100156E-02 --6.3792970687809120E-02 --6.3787609617463145E-02 --6.3782234314817818E-02 --6.3776844784628722E-02 --6.3771441031651471E-02 --6.3766023060641649E-02 --6.3760590876354856E-02 --6.3755144483546689E-02 --6.3749683886972747E-02 --6.3744209091388615E-02 --6.3738720101549878E-02 --6.3733216922212149E-02 --6.3727699558131012E-02 --6.3722168014062081E-02 --6.3716622294760938E-02 --6.3711062404983171E-02 --6.3705488349484363E-02 --6.3699900133020154E-02 --6.3694297760346102E-02 --6.3688681236217806E-02 --6.3683050565390864E-02 --6.3677405752620889E-02 --6.3671746802663437E-02 --6.3666073720274149E-02 --6.3660386510208583E-02 --6.3654685177222364E-02 --6.3648969726071064E-02 --6.3643240161510267E-02 --6.3637496488295614E-02 --6.3631738711182662E-02 --6.3625966834927009E-02 --6.3620180864284254E-02 --6.3614380804009996E-02 --6.3608566658859833E-02 --6.3602738433589365E-02 --6.3596896132954162E-02 --6.3591039761709850E-02 --6.3585169324611987E-02 --6.3579284826416199E-02 --6.3573386271878071E-02 --6.3567473665753202E-02 --6.3561547012797176E-02 --6.3555606317765606E-02 --6.3549651585414063E-02 --6.3543682820498160E-02 --6.3537700027773480E-02 --6.3531703211995638E-02 --6.3525692377920204E-02 --6.3519667530302790E-02 --6.3513628673898981E-02 --6.3507575813464376E-02 --6.3501508953754560E-02 --6.3495428099525159E-02 --6.3489333255531730E-02 --6.3483224426529899E-02 --6.3477101617275239E-02 --6.3470964832523347E-02 --6.3464814077029821E-02 --6.3458649355550262E-02 --6.3452470672840267E-02 --6.3446278033655434E-02 --6.3440071442751336E-02 --6.3433850904883571E-02 --6.3427616424807765E-02 --6.3421368007279474E-02 --6.3415105657054313E-02 --6.3408829378887893E-02 --6.3402539177535772E-02 --6.3396235057753561E-02 --6.3389917024296860E-02 --6.3383585081921281E-02 --6.3377239235382382E-02 --6.3370879489435775E-02 --6.3364505848837058E-02 --6.3358118318341816E-02 --6.3351716902705663E-02 --6.3345301606684168E-02 --6.3338872435032958E-02 --6.3332429392507592E-02 --6.3325972483863693E-02 --6.3319501713856835E-02 --6.3313017087242629E-02 --6.3306518608776674E-02 --6.3300006283214541E-02 --6.3293480115311843E-02 --6.3286940109824164E-02 --6.3280386271507116E-02 --6.3273818605116272E-02 --6.3267237115407257E-02 --6.3260641807135642E-02 --6.3254032685057027E-02 --6.3247409753926995E-02 --6.3240773018501173E-02 --6.3234122483535118E-02 --6.3227458153784444E-02 --6.3220780034004748E-02 --6.3214088128951629E-02 --6.3207382443380672E-02 --6.3200662982047476E-02 --6.3193929749707639E-02 --6.3187182751116733E-02 --6.3180421991030383E-02 --6.3173647474204175E-02 --6.3166859205393694E-02 --6.3160057189354551E-02 --6.3153241430842333E-02 --6.3146411934612623E-02 --6.3139568705421034E-02 --6.3132711748023151E-02 --6.3125841067174573E-02 --6.3118956667630899E-02 --6.3112058554147712E-02 --6.3105146731480627E-02 --6.3098221204385213E-02 --6.3091281977617070E-02 --6.3084329055931809E-02 --6.3077362444085017E-02 --6.3070382146832291E-02 --6.3063388168929216E-02 --6.3056380515131391E-02 --6.3049359190194415E-02 --6.3042324198873900E-02 --6.3035275545925404E-02 --6.3028213236104552E-02 --6.3021137274166916E-02 --6.3014047664868095E-02 --6.3006944412963714E-02 --6.2999827523209331E-02 --6.2992697000360559E-02 --6.2985552849172996E-02 --6.2978395074402227E-02 --6.2971223680803837E-02 --6.2964038673133438E-02 --6.2956840056146629E-02 --6.2949627834598995E-02 --6.2942402013246135E-02 --6.2935162596843633E-02 --6.2927909590147088E-02 --6.2920642997912113E-02 --6.2913362824894278E-02 --6.2906069075849197E-02 --6.2898761755532454E-02 --6.2891440868699647E-02 --6.2884106420106362E-02 --6.2876758414508224E-02 --6.2869396856660792E-02 --6.2862021751319677E-02 --6.2854633103240465E-02 --6.2847230917178781E-02 --6.2839815197890170E-02 --6.2832385950130271E-02 --6.2824943178654655E-02 --6.2817486888218921E-02 --6.2810017083578681E-02 --6.2802533769489507E-02 --6.2795036950706998E-02 --6.2787526631986765E-02 --6.2780002818084379E-02 --6.2772465513755468E-02 --6.2764914723755588E-02 --6.2757350452840352E-02 --6.2749772705765358E-02 --6.2742181487286205E-02 --6.2734576802158479E-02 --6.2726958655137777E-02 --6.2719327050979684E-02 --6.2711681994439814E-02 --6.2704023490273750E-02 --6.2696351543237092E-02 --6.2688666158085438E-02 --6.2680967339574359E-02 --6.2673255092459482E-02 --6.2665529421496391E-02 --6.2657790331440671E-02 --6.2650037827047922E-02 --6.2642271913073741E-02 --6.2634492594273727E-02 --6.2626699875403466E-02 --6.2618893761218569E-02 --6.2611074256474608E-02 --6.2603241365927195E-02 --6.2595395094331915E-02 --6.2587535446444381E-02 --6.2579662427020163E-02 --6.2571776040814861E-02 --6.2563876292584086E-02 --6.2555963187083424E-02 --6.2548036729068460E-02 --6.2540096923294805E-02 --6.2532143774518045E-02 --6.2524177287493779E-02 --6.2516197466977591E-02 --6.2508204317725094E-02 --6.2500197844491873E-02 --6.2492178052033526E-02 --6.2484144945105638E-02 --6.2476098528463808E-02 --6.2468038806863642E-02 --6.2459965785060717E-02 --6.2451879467810653E-02 --6.2443779859869021E-02 --6.2435666965991427E-02 --6.2427540790933461E-02 --6.2419401339450717E-02 --6.2411248616298806E-02 --6.2403082626233300E-02 --6.2394903374009811E-02 --6.2386710864383917E-02 --6.2378505102111230E-02 --6.2370286091947336E-02 --6.2362053838647832E-02 --6.2353808346968319E-02 --6.2345549621664373E-02 --6.2337277667491614E-02 --6.2328992489205620E-02 --6.2320694091561990E-02 --6.2312382479316322E-02 --6.2304057657224202E-02 --6.2295719630041241E-02 --6.2287368402523011E-02 --6.2279003979425124E-02 --6.2270626365503179E-02 --6.2262235565512761E-02 --6.2253831584209461E-02 --6.2245414426348886E-02 --6.2236984096686612E-02 --6.2228540599978260E-02 --6.2220083940979415E-02 --6.2211614124445654E-02 --6.2203131155132596E-02 --6.2194635037795820E-02 --6.2186125777190931E-02 --6.2177603378073522E-02 --6.2169067845199183E-02 --6.2160519183323507E-02 --6.2151957397202098E-02 --6.2143382491590543E-02 --6.2134794471244446E-02 --6.2126193340919400E-02 --6.2117579105370996E-02 --6.2108951769354818E-02 --6.2100311337626481E-02 --6.2091657814941567E-02 --6.2082991206055677E-02 --6.2074311515724401E-02 --6.2065618748703345E-02 --6.2056912909748088E-02 --6.2048194003614235E-02 --6.2039462035057377E-02 --6.2030717008833114E-02 --6.2021958929697037E-02 --6.2013187802404744E-02 --6.2004403631711821E-02 --6.1995606422373867E-02 --6.1986796179146486E-02 --6.1977972906785264E-02 --6.1969136610045800E-02 --6.1960287293683677E-02 --6.1951424962454510E-02 --6.1942549621113882E-02 --6.1933661274417393E-02 --6.1924759927120626E-02 --6.1915845583979195E-02 --6.1906918249748671E-02 --6.1897977929184667E-02 --6.1889024627042780E-02 --6.1880058348078582E-02 --6.1871079097047699E-02 --6.1862086878705702E-02 --6.1853081697808204E-02 --6.1844063559110790E-02 --6.1835032467369044E-02 --6.1825988427338580E-02 --6.1816931443774988E-02 --6.1807861521433860E-02 --6.1798778665070789E-02 --6.1789682879441372E-02 --6.1780574169301203E-02 --6.1771452539405879E-02 --6.1762317994510998E-02 --6.1753170539372140E-02 --6.1744010178744917E-02 --6.1734836917384919E-02 --6.1725650760047733E-02 --6.1716451711488970E-02 --6.1707239776464209E-02 --6.1698014959729056E-02 --6.1688777266039101E-02 --6.1679526700149936E-02 --6.1670263266817162E-02 --6.1660986970796361E-02 --6.1651697816843147E-02 --6.1642395809713105E-02 --6.1633080954161826E-02 --6.1623753254944916E-02 --6.1614412716817966E-02 --6.1605059344536556E-02 --6.1595693142856303E-02 --6.1586314116532787E-02 --6.1576922270321612E-02 --6.1567517608978370E-02 --6.1558100137258653E-02 --6.1548669859918061E-02 --6.1539226781712184E-02 --6.1529770907396614E-02 --6.1520302241726957E-02 --6.1510820789458798E-02 --6.1501326555347735E-02 --6.1491819544149361E-02 --6.1482299760619280E-02 --6.1472767209513071E-02 --6.1463221895586347E-02 --6.1453663823594684E-02 --6.1444092998293703E-02 --6.1434509424438968E-02 --6.1424913106786092E-02 --6.1415304050090672E-02 --6.1405682259108293E-02 --6.1396047738594556E-02 --6.1386400493305050E-02 --6.1376740527995383E-02 --6.1367067847421131E-02 --6.1357382456337907E-02 --6.1347684359501289E-02 --6.1337973561666891E-02 --6.1328250067590295E-02 --6.1318513882027095E-02 --6.1308765009732896E-02 --6.1299003455463283E-02 --6.1289229223973854E-02 --6.1279442320020208E-02 --6.1269642748357930E-02 --6.1259830513742626E-02 --6.1250005620929887E-02 --6.1240168074675305E-02 --6.1230317879734472E-02 --6.1220455040863000E-02 --6.1210579562816461E-02 --6.1200691450350460E-02 --6.1190790708220602E-02 --6.1180877341182466E-02 --6.1170951353991657E-02 --6.1161012751403759E-02 --6.1151061538174380E-02 --6.1141097719059109E-02 --6.1131121298813540E-02 --6.1121132282193277E-02 --6.1111130673953892E-02 --6.1101116478851004E-02 --6.1091089701640199E-02 --6.1081050347077073E-02 --6.1070998419917213E-02 --6.1060933924916225E-02 --6.1050856866829699E-02 --6.1040767250413228E-02 --6.1030665080422417E-02 --6.1020550361612844E-02 --6.1010423098740107E-02 --6.1000283296559821E-02 --6.0990130959827561E-02 --6.0979966093298928E-02 --6.0969788701729519E-02 --6.0959598789874926E-02 --6.0949396362490749E-02 --6.0939181424332564E-02 --6.0928953980155992E-02 --6.0918714034716610E-02 --6.0908461592770025E-02 --6.0898196659071827E-02 --6.0887919238377601E-02 --6.0877629335442954E-02 --6.0867326955023483E-02 --6.0857012101874775E-02 --6.0846684780752426E-02 --6.0836344996412037E-02 --6.0825992753609198E-02 --6.0815628057099502E-02 --6.0805250911638548E-02 --6.0794861321981919E-02 --6.0784459292885229E-02 --6.0774044829104062E-02 --6.0763617935394018E-02 --6.0753178616510695E-02 --6.0742726877209663E-02 --6.0732262722246556E-02 --6.0721786156376939E-02 --6.0711297184356416E-02 --6.0700795810940580E-02 --6.0690282040885030E-02 --6.0679755878945363E-02 --6.0669217329877165E-02 --6.0658666398436048E-02 --6.0648103089377584E-02 --6.0637527407457384E-02 --6.0626939357431034E-02 --6.0616338944054132E-02 --6.0605726172082271E-02 --6.0595101046271055E-02 --6.0584463571376070E-02 --6.0573813752152914E-02 --6.0563151593357178E-02 --6.0552477099744470E-02 --6.0541790276070359E-02 --6.0531091127090472E-02 --6.0520379657560380E-02 --6.0509655872235682E-02 --6.0498919775871990E-02 --6.0488171373224875E-02 --6.0477410669049936E-02 --6.0466637668102792E-02 --6.0455852375139008E-02 --6.0445054794914202E-02 --6.0434244932183946E-02 --6.0423422791703846E-02 --6.0412588378229506E-02 --6.0401741696516520E-02 --6.0390882751320457E-02 --6.0380011547396945E-02 --6.0369128089501560E-02 --6.0358232382389902E-02 --6.0347324430817570E-02 --6.0336404239540148E-02 --6.0325471813313242E-02 --6.0314527156892436E-02 --6.0303570275033344E-02 --6.0292601172491536E-02 --6.0281619854022618E-02 --6.0270626324382195E-02 --6.0259620588325839E-02 --6.0248602650609169E-02 --6.0237572515987770E-02 --6.0226530189217239E-02 --6.0215475675053157E-02 --6.0204408978251141E-02 --6.0193330103566776E-02 --6.0182239055755649E-02 --6.0171135839573363E-02 --6.0160020459775511E-02 --6.0148892921117691E-02 --6.0137753228355503E-02 --6.0126601386244524E-02 --6.0115437399540367E-02 --6.0104261272998623E-02 --6.0093073011374870E-02 --6.0081872619424728E-02 --6.0070660101903775E-02 --6.0059435463567609E-02 --6.0048198709171843E-02 --6.0036949843472041E-02 --6.0025688871223809E-02 --6.0014415797182752E-02 --6.0003130626104462E-02 --5.9991833362744530E-02 --5.9980524011858549E-02 --5.9969202578202124E-02 --5.9957869066530826E-02 --5.9946523481600275E-02 --5.9935165828166062E-02 --5.9923796110983779E-02 --5.9912414334809011E-02 --5.9901020504397356E-02 --5.9889614624504428E-02 --5.9878196699885797E-02 --5.9866766735297075E-02 --5.9855324735493848E-02 --5.9843870705231721E-02 --5.9832404649266271E-02 --5.9820926572353106E-02 --5.9809436479247829E-02 --5.9797934374706006E-02 --5.9786420263483263E-02 --5.9774894150335177E-02 --5.9763356040017347E-02 --5.9751805937285372E-02 --5.9740243846894844E-02 --5.9728669773601362E-02 --5.9717083722160502E-02 --5.9705485697327886E-02 --5.9693875703859089E-02 --5.9682253746509720E-02 --5.9670619830035368E-02 --5.9658973959191626E-02 --5.9647316138734086E-02 --5.9635646373418352E-02 --5.9623964668000004E-02 --5.9612271027234653E-02 --5.9600565455877899E-02 --5.9588847958685312E-02 --5.9577118540412505E-02 --5.9565377205815062E-02 --5.9553623959648590E-02 --5.9541858806668679E-02 --5.9530081751630923E-02 --5.9518292799290912E-02 --5.9506491954404245E-02 --5.9494679221726535E-02 --5.9482854606013345E-02 --5.9471018112020282E-02 --5.9459169744502952E-02 --5.9447309508216944E-02 --5.9435437407917846E-02 --5.9423553448361255E-02 --5.9411657634302770E-02 --5.9399749970497989E-02 --5.9387830461702484E-02 --5.9375899112671889E-02 --5.9363955928161773E-02 --5.9352000912927735E-02 --5.9340034071725375E-02 --5.9328055409310271E-02 --5.9316064930438034E-02 --5.9304062639864263E-02 --5.9292048542344544E-02 --5.9280022642634475E-02 --5.9267984945489641E-02 --5.9255935455665647E-02 --5.9243874177918092E-02 --5.9231801117002561E-02 --5.9219716277674653E-02 --5.9207619664689966E-02 --5.9195511282804092E-02 --5.9183391136772623E-02 --5.9171259231351150E-02 --5.9159115571295287E-02 --5.9146960161360604E-02 --5.9134793006302720E-02 --5.9122614110877214E-02 --5.9110423479839684E-02 --5.9098221117945729E-02 --5.9086007029950940E-02 --5.9073781220610910E-02 --5.9061543694681237E-02 --5.9049294456917506E-02 --5.9037033512075343E-02 --5.9024760864910306E-02 --5.9012476520178020E-02 --5.9000180482634050E-02 --5.8987872757034009E-02 --5.8975553348133494E-02 --5.8963222260688092E-02 --5.8950879499453407E-02 --5.8938525069185024E-02 --5.8926158974638543E-02 --5.8913781220569547E-02 --5.8901391811733650E-02 --5.8888990752886443E-02 --5.8876578048783511E-02 --5.8864153704180452E-02 --5.8851717723832866E-02 --5.8839270112496359E-02 --5.8826810874926493E-02 --5.8814340015878888E-02 --5.8801857540109137E-02 --5.8789363452372824E-02 --5.8776857757425555E-02 --5.8764340460022921E-02 --5.8751811564920514E-02 --5.8739271076873933E-02 --5.8726719000638770E-02 --5.8714155340970617E-02 --5.8701580102625085E-02 --5.8688993290357754E-02 --5.8676394908924220E-02 --5.8663784963080078E-02 --5.8651163457580924E-02 --5.8638530397182358E-02 --5.8625885786639971E-02 --5.8613229630709356E-02 --5.8600561934146103E-02 --5.8587882701705826E-02 --5.8575191938144096E-02 --5.8562489648216524E-02 --5.8549775836678704E-02 --5.8537050508286226E-02 --5.8524313667794675E-02 --5.8511565319959671E-02 --5.8498805469536785E-02 --5.8486034121281630E-02 --5.8473251279949789E-02 --5.8460456950296863E-02 --5.8447651137078435E-02 --5.8434833845050119E-02 --5.8422005078967498E-02 --5.8409164843586166E-02 --5.8396313143661727E-02 --5.8383449983949759E-02 --5.8370575369205882E-02 --5.8357689304185667E-02 --5.8344791793644726E-02 --5.8331882842338645E-02 --5.8318962455023021E-02 --5.8306030636453440E-02 --5.8293087391385515E-02 --5.8280132724574829E-02 --5.8267166640776975E-02 --5.8254189144747559E-02 --5.8241200241242165E-02 --5.8228199935016392E-02 --5.8215188230825846E-02 --5.8202165133426090E-02 --5.8189130647572751E-02 --5.8176084778021414E-02 --5.8163027529527664E-02 --5.8149958906847113E-02 --5.8136878914735346E-02 --5.8123787557947962E-02 --5.8110684841240552E-02 --5.8097570769368709E-02 --5.8084445347088030E-02 --5.8071308579154116E-02 --5.8058160470322556E-02 --5.8045001025348944E-02 --5.8031830248988871E-02 --5.8018648145997942E-02 --5.8005454721131756E-02 --5.7992249979145885E-02 --5.7979033924795954E-02 --5.7965806562837535E-02 --5.7952567898026219E-02 --5.7939317935117626E-02 --5.7926056678867334E-02 --5.7912784134030941E-02 --5.7899500305364046E-02 --5.7886205197622234E-02 --5.7872898815561104E-02 --5.7859581163936247E-02 --5.7846252247503283E-02 --5.7832912071017775E-02 --5.7819560639235330E-02 --5.7806197956911540E-02 --5.7792824028802009E-02 --5.7779438859662330E-02 --5.7766042454248080E-02 --5.7752634817314880E-02 --5.7739215953618306E-02 --5.7725785867913965E-02 --5.7712344564957441E-02 --5.7698892049504340E-02 --5.7685428326310254E-02 --5.7671953400130767E-02 --5.7658467275721485E-02 --5.7644969957837994E-02 --5.7631461451235905E-02 --5.7617941760670803E-02 --5.7604410890898280E-02 --5.7590868846673929E-02 --5.7577315632753354E-02 --5.7563751253892154E-02 --5.7550175714845900E-02 --5.7536589020370212E-02 --5.7522991175220667E-02 --5.7509382184152878E-02 --5.7495762051922431E-02 --5.7482130783284915E-02 --5.7468488382995939E-02 --5.7454834855811071E-02 --5.7441170206485939E-02 --5.7427494439776114E-02 --5.7413807560437208E-02 --5.7400109573224806E-02 --5.7386400482894492E-02 --5.7372680294201880E-02 --5.7358949011902569E-02 --5.7345206640752135E-02 --5.7331453185506177E-02 --5.7317688650920295E-02 --5.7303913041750094E-02 --5.7290126362751145E-02 --5.7276328618679068E-02 --5.7262519814289432E-02 --5.7248699954337859E-02 --5.7234869043579925E-02 --5.7221027086771223E-02 --5.7207174088667365E-02 --5.7193310054023928E-02 --5.7179434987596520E-02 --5.7165548894140737E-02 --5.7151651778412166E-02 --5.7137743645166390E-02 --5.7123824499159030E-02 --5.7109894345145670E-02 --5.7095953187881895E-02 --5.7082001032123325E-02 --5.7068037882625516E-02 --5.7054063744144096E-02 --5.7040078621434662E-02 --5.7026082519252785E-02 --5.7012075442354065E-02 --5.6998057395494107E-02 --5.6984028383428503E-02 --5.6969988410912845E-02 --5.6955937482702737E-02 --5.6941875603553765E-02 --5.6927802778221515E-02 --5.6913719011461597E-02 --5.6899624308029612E-02 --5.6885518672681136E-02 --5.6871402110171776E-02 --5.6857274625257123E-02 --5.6843136222692756E-02 --5.6828986907234300E-02 --5.6814826683637340E-02 --5.6800655556657462E-02 --5.6786473531050270E-02 --5.6772280611571350E-02 --5.6758076802976301E-02 --5.6743862110020714E-02 --5.6729636537460194E-02 --5.6715400090050327E-02 --5.6701152772546719E-02 --5.6686894589704953E-02 --5.6672625546280622E-02 --5.6658345647029332E-02 --5.6644054896706680E-02 --5.6629753300068246E-02 --5.6615440861869634E-02 --5.6601117586866437E-02 --5.6586783479814246E-02 --5.6572438545468673E-02 --5.6558082788585290E-02 --5.6543716213919709E-02 --5.6529338826227508E-02 --5.6514950630264293E-02 --5.6500551630785670E-02 --5.6486141832547215E-02 --5.6471721240304529E-02 --5.6457289858813209E-02 --5.6442847692828840E-02 --5.6428394747107036E-02 --5.6413931026403380E-02 --5.6399456535473472E-02 --5.6384971279072896E-02 --5.6370475261957251E-02 --5.6355968488882149E-02 --5.6341450964603162E-02 --5.6326922693875896E-02 --5.6312383681455941E-02 --5.6297833932098890E-02 --5.6283273450560348E-02 --5.6268702241595907E-02 --5.6254120309961159E-02 --5.6239527660411702E-02 --5.6224924297703129E-02 --5.6210310226591023E-02 --5.6195685451830998E-02 --5.6181049978178646E-02 --5.6166403810389551E-02 --5.6151746953219311E-02 --5.6137079411423520E-02 --5.6122401189757788E-02 --5.6107712292977688E-02 --5.6093012725838838E-02 --5.6078302493096817E-02 --5.6063581599507216E-02 --5.6048850049825641E-02 --5.6034107848807684E-02 --5.6019355001208943E-02 --5.6004591511785003E-02 --5.5989817385291470E-02 --5.5975032626483928E-02 --5.5960237240117977E-02 --5.5945431230949222E-02 --5.5930614603733241E-02 --5.5915787363225639E-02 --5.5900949514182008E-02 --5.5886101061357940E-02 --5.5871242009509034E-02 --5.5856372363390888E-02 --5.5841492127759088E-02 --5.5826601307369238E-02 --5.5811699906976930E-02 --5.5796787931337757E-02 --5.5781865385207310E-02 --5.5766932273341195E-02 --5.5751988600495003E-02 --5.5737034371424313E-02 --5.5722069590884743E-02 --5.5707094263631879E-02 --5.5692108394421305E-02 --5.5677111988008635E-02 --5.5662105049149459E-02 --5.5647087582599356E-02 --5.5632059593113944E-02 --5.5617021085448803E-02 --5.5601972064359531E-02 --5.5586912534601726E-02 --5.5571842500930974E-02 --5.5556761968102872E-02 --5.5541670940873034E-02 --5.5526569423997037E-02 --5.5511457422230473E-02 --5.5496334940328948E-02 --5.5481201983048047E-02 --5.5466058555143374E-02 --5.5450904661370523E-02 --5.5435740306485085E-02 --5.5420565495242644E-02 --5.5405380232398813E-02 --5.5390184522709177E-02 --5.5374978370929334E-02 --5.5359761781814898E-02 --5.5344534760121425E-02 --5.5329297310604542E-02 --5.5314049438019819E-02 --5.5298791147122869E-02 --5.5283522442669292E-02 --5.5268243329414657E-02 --5.5252953812114591E-02 --5.5237653895524652E-02 --5.5222343584400473E-02 --5.5207022883497624E-02 --5.5191691797571718E-02 --5.5176350331378327E-02 --5.5160998489673055E-02 --5.5145636277211502E-02 --5.5130263698749266E-02 --5.5114880759041945E-02 --5.5099487462845112E-02 --5.5084083814914378E-02 --5.5068669820005335E-02 --5.5053245482873589E-02 --5.5037810808274718E-02 --5.5022365800964326E-02 --5.5006910465697993E-02 --5.4991444807231338E-02 --5.4975968830319938E-02 --5.4960482539719392E-02 --5.4944985940185306E-02 --5.4929479036473258E-02 --5.4913961833338854E-02 --5.4898434335537677E-02 --5.4882896547825348E-02 --5.4867348474957431E-02 --5.4851790121689538E-02 --5.4836221492777268E-02 --5.4820642592976192E-02 --5.4805053427041936E-02 --5.4789453999730064E-02 --5.4773844315796211E-02 --5.4758224379995932E-02 --5.4742594197084833E-02 --5.4726953771818521E-02 --5.4711303108952579E-02 --5.4695642213242614E-02 --5.4679971089444210E-02 --5.4664289742312966E-02 --5.4648598176604474E-02 --5.4632896397074332E-02 --5.4617184408478132E-02 --5.4601462215571467E-02 --5.4585729823109955E-02 --5.4569987235849146E-02 --5.4554234458544681E-02 --5.4538471495952125E-02 --5.4522698352827088E-02 --5.4506915033925150E-02 --5.4491121544001923E-02 --5.4475317887812992E-02 --5.4459504070113948E-02 --5.4443680095660404E-02 --5.4427845969207939E-02 --5.4412001695512156E-02 --5.4396147279328635E-02 --5.4380282725412989E-02 --5.4364408038520801E-02 --5.4348523223407663E-02 --5.4332628284829196E-02 --5.4316723227540969E-02 --5.4300808056298583E-02 --5.4284882775857635E-02 --5.4268947390973724E-02 --5.4253001906402427E-02 --5.4237046326899359E-02 --5.4221080657220103E-02 --5.4205104902120264E-02 --5.4189119066355443E-02 --5.4173123154681209E-02 --5.4157117171853175E-02 --5.4141101122626933E-02 --5.4125075011758075E-02 --5.4109038844002200E-02 --5.4092992624114891E-02 --5.4076936356851769E-02 --5.4060870046968405E-02 --5.4044793699220404E-02 --5.4028707318363359E-02 --5.4012610909152867E-02 --5.3996504476344520E-02 --5.3980388024693904E-02 --5.3964261558956630E-02 --5.3948125083888285E-02 --5.3931978604244479E-02 --5.3915822124780771E-02 --5.3899655650252794E-02 --5.3883479185416125E-02 --5.3867292735026356E-02 --5.3851096303839080E-02 --5.3834889896609908E-02 --5.3818673518094426E-02 --5.3802447173048232E-02 --5.3786210866226911E-02 --5.3769964602386061E-02 --5.3753708386281296E-02 --5.3737442222668179E-02 --5.3721166116302323E-02 --5.3704880071939333E-02 --5.3688584094334774E-02 --5.3672278188244271E-02 --5.3655962358423404E-02 --5.3639636609627776E-02 --5.3623300946612967E-02 --5.3606955374134582E-02 --5.3590599896948227E-02 --5.3574234519809472E-02 --5.3557859247473930E-02 --5.3541474084697199E-02 --5.3525079036234866E-02 --5.3508674106842506E-02 --5.3492259301275755E-02 --5.3475834624290175E-02 --5.3459400080641373E-02 --5.3442955675084954E-02 --5.3426501412376481E-02 --5.3410037297271597E-02 --5.3393563334525856E-02 --5.3377079528894880E-02 --5.3360585885134232E-02 --5.3344082407999538E-02 --5.3327569102246369E-02 --5.3311045972630353E-02 --5.3294513023907045E-02 --5.3277970260832065E-02 --5.3261417688161006E-02 --5.3244855310649444E-02 --5.3228283133053007E-02 --5.3211701160127266E-02 --5.3195109396627818E-02 --5.3178507847310263E-02 --5.3161896516930193E-02 --5.3145275410243206E-02 --5.3128644532004887E-02 --5.3112003886970856E-02 --5.3095353479896676E-02 --5.3078693315537967E-02 --5.3062023398650293E-02 --5.3045343733989295E-02 --5.3028654326310529E-02 --5.3011955180369608E-02 --5.2995246300922123E-02 --5.2978527692723654E-02 --5.2961799360529832E-02 --5.2945061309096215E-02 --5.2928313543178424E-02 --5.2911556067532034E-02 --5.2894788886912646E-02 --5.2878012006075864E-02 --5.2861225429777267E-02 --5.2844429162772474E-02 --5.2827623209817057E-02 --5.2810807575666627E-02 --5.2793982265076755E-02 --5.2777147282803069E-02 --5.2760302633601139E-02 --5.2743448322226570E-02 --5.2726584353434955E-02 --5.2709710731981892E-02 --5.2692827462622965E-02 --5.2675934550113782E-02 --5.2659031999209932E-02 --5.2642119814667009E-02 --5.2625198001240610E-02 --5.2608266563686321E-02 --5.2591325506759753E-02 --5.2574374835216500E-02 --5.2557414553812146E-02 --5.2540444667302288E-02 --5.2523465180442513E-02 --5.2506476097988447E-02 --5.2489477424695646E-02 --5.2472469165319724E-02 --5.2455451324616285E-02 --5.2438423907340909E-02 --5.2421386918249185E-02 --5.2404340362096728E-02 --5.2387284243639129E-02 --5.2370218567631965E-02 --5.2353143338830843E-02 --5.2336058561991361E-02 --5.2318964241869111E-02 --5.2301860383219698E-02 --5.2284746990798686E-02 --5.2267624069361709E-02 --5.2250491623664339E-02 --5.2233349658462172E-02 --5.2216198178510795E-02 --5.2199037188565833E-02 --5.2181866693382858E-02 --5.2164686697717462E-02 --5.2147497206325250E-02 --5.2130298223961813E-02 --5.2113089755382758E-02 --5.2095871805343655E-02 --5.2078644378600110E-02 --5.2061407479907729E-02 --5.2044161114022089E-02 --5.2026905285698810E-02 --5.2009639999693463E-02 --5.1992365260761654E-02 --5.1975081073658967E-02 --5.1957787443141008E-02 --5.1940484373963369E-02 --5.1923171870881649E-02 --5.1905849938651438E-02 --5.1888518582028330E-02 --5.1871177805767915E-02 --5.1853827614625800E-02 --5.1836468013357583E-02 --5.1819099006718834E-02 --5.1801720599465174E-02 --5.1784332796352195E-02 --5.1766935602135467E-02 --5.1749529021570609E-02 --5.1732113059413214E-02 --5.1714687720418873E-02 --5.1697253009343185E-02 --5.1679808930941727E-02 --5.1662355489970113E-02 --5.1644892691183934E-02 --5.1627420539338789E-02 --5.1609939039190256E-02 --5.1592448195493953E-02 --5.1574948013005453E-02 --5.1557438496480368E-02 --5.1539919650674282E-02 --5.1522391480342794E-02 --5.1504853990241503E-02 --5.1487307185125980E-02 --5.1469751069751865E-02 --5.1452185648874715E-02 --5.1434610927250143E-02 --5.1417026909633734E-02 --5.1399433600781093E-02 --5.1381831005447798E-02 --5.1364219128389468E-02 --5.1346597974361669E-02 --5.1328967548120025E-02 --5.1311327854420115E-02 --5.1293678898017531E-02 --5.1276020683667878E-02 --5.1258353216126741E-02 --5.1240676500149733E-02 --5.1222990540492425E-02 --5.1205295341910428E-02 --5.1187590909159322E-02 --5.1169877246994719E-02 --5.1152154360172217E-02 --5.1134422253447387E-02 --5.1116680931575856E-02 --5.1098930399313174E-02 --5.1081170661414980E-02 --5.1063401722636848E-02 --5.1045623587734373E-02 --5.1027836261463164E-02 --5.1010039748578782E-02 --5.0992234053836870E-02 --5.0974419181992983E-02 --5.0956595137802742E-02 --5.0938761926021724E-02 --5.0920919551405534E-02 --5.0903068018709759E-02 --5.0885207332689995E-02 --5.0867337498101850E-02 --5.0849458519700907E-02 --5.0831570402242773E-02 --5.0813673150483012E-02 --5.0795766769177256E-02 --5.0777851263081077E-02 --5.0759926636950073E-02 --5.0741992895539857E-02 --5.0724050043606000E-02 --5.0706098085904108E-02 --5.0688137027189772E-02 --5.0670166872218599E-02 --5.0652187625746165E-02 --5.0634199292528076E-02 --5.0616201877319925E-02 --5.0598195384877302E-02 --5.0580179819955814E-02 --5.0562155187311053E-02 --5.0544121491698610E-02 --5.0526078737874069E-02 --5.0508026930593045E-02 --5.0489966074611120E-02 --5.0471896174683895E-02 --5.0453817235566960E-02 --5.0435729262015914E-02 --5.0417632258786343E-02 --5.0399526230633859E-02 --5.0381411182314047E-02 --5.0363287118582498E-02 --5.0345154044194811E-02 --5.0327011963906577E-02 --5.0308860882473397E-02 --5.0290700804650867E-02 --5.0272531735194581E-02 --5.0254353678860136E-02 --5.0236166640403111E-02 --5.0217970624579111E-02 --5.0199765636143735E-02 --5.0181551679852582E-02 --5.0163328760461236E-02 --5.0145096882725296E-02 --5.0126856051400354E-02 --5.0108606271242008E-02 --5.0090347547005858E-02 --5.0072079883447487E-02 --5.0053803285322503E-02 --5.0035517757386495E-02 --5.0017223304395043E-02 --4.9998919931103773E-02 --4.9980607642268256E-02 --4.9962286442644097E-02 --4.9943956336986887E-02 --4.9925617330052220E-02 --4.9907269426595693E-02 --4.9888912631372899E-02 --4.9870546949139442E-02 --4.9852172384650908E-02 --4.9833788942662896E-02 --4.9815396627930983E-02 --4.9796995445210795E-02 --4.9778585399257905E-02 --4.9760166494827909E-02 --4.9741738736676422E-02 --4.9723302129559006E-02 --4.9704856678231289E-02 --4.9686402387448841E-02 --4.9667939261967275E-02 --4.9649467306542169E-02 --4.9630986525929129E-02 --4.9612496924883745E-02 --4.9593998508161617E-02 --4.9575491280518344E-02 --4.9556975246709510E-02 --4.9538450411490714E-02 --4.9519916779617541E-02 --4.9501374355845611E-02 --4.9482823144930493E-02 --4.9464263151627809E-02 --4.9445694380693121E-02 --4.9427116836882036E-02 --4.9408530524950173E-02 --4.9389935449653088E-02 --4.9371331615746417E-02 --4.9352719027985714E-02 --4.9334097691126608E-02 --4.9315467609924661E-02 --4.9296828789135501E-02 --4.9278181233514698E-02 --4.9259524947817865E-02 --4.9240859936800593E-02 --4.9222186205218454E-02 --4.9203503757827075E-02 --4.9184812599382038E-02 --4.9166112734638931E-02 --4.9147404168353365E-02 --4.9128686905280911E-02 --4.9109960950177181E-02 --4.9091226307797775E-02 --4.9072482982898284E-02 --4.9053730980234286E-02 --4.9034970304561401E-02 --4.9016200960635192E-02 --4.8997422953211293E-02 --4.8978636287045275E-02 --4.8959840966892730E-02 --4.8941036997509277E-02 --4.8922224383650473E-02 --4.8903403130071944E-02 --4.8884573241529269E-02 --4.8865734722778068E-02 --4.8846887578573903E-02 --4.8828031813672373E-02 --4.8809167432829093E-02 --4.8790294440799645E-02 --4.8771412842339643E-02 --4.8752522642204643E-02 --4.8733623845150280E-02 --4.8714716455932110E-02 --4.8695800479305766E-02 --4.8676875920026820E-02 --4.8657942782850877E-02 --4.8639001072533529E-02 --4.8620050793830361E-02 --4.8601091951496977E-02 --4.8582124550288978E-02 --4.8563148594961955E-02 --4.8544164090271499E-02 --4.8525171040973203E-02 --4.8506169451822664E-02 --4.8487159327575476E-02 --4.8468140672987242E-02 --4.8449113492813549E-02 --4.8430077791810001E-02 --4.8411033574732178E-02 --4.8391980846335683E-02 --4.8372919611376110E-02 --4.8353849874609049E-02 --4.8334771640790114E-02 --4.8315684914674882E-02 --4.8296589701018945E-02 --4.8277486004577909E-02 --4.8258373830107372E-02 --4.8239253182362919E-02 --4.8220124066100142E-02 --4.8200986486074640E-02 --4.8181840447042018E-02 --4.8162685953757861E-02 --4.8143523010977768E-02 --4.8124351623457330E-02 --4.8105171795952140E-02 --4.8085983533217795E-02 --4.8066786840009895E-02 --4.8047581721084025E-02 --4.8028368181195796E-02 --4.8009146225100788E-02 --4.7989915857554598E-02 --4.7970677083312825E-02 --4.7951429907131075E-02 --4.7932174333764919E-02 --4.7912910367969963E-02 --4.7893638014501812E-02 --4.7874357278116030E-02 --4.7855068163568257E-02 --4.7835770675614050E-02 --4.7816464819009030E-02 --4.7797150598508767E-02 --4.7777828018868873E-02 --4.7758497084844941E-02 --4.7739157801192561E-02 --4.7719810172667340E-02 --4.7700454204024856E-02 --4.7681089900020714E-02 --4.7661717265410491E-02 --4.7642336304949823E-02 --4.7622947023394258E-02 --4.7603549425499422E-02 --4.7584143516020909E-02 --4.7564729299714281E-02 --4.7545306781335180E-02 --4.7525875965639161E-02 --4.7506436857381852E-02 --4.7486989461318824E-02 --4.7467533782205674E-02 --4.7448069824798003E-02 --4.7428597593851415E-02 --4.7409117094121489E-02 --4.7389628330363830E-02 --4.7370131307334029E-02 --4.7350626029787665E-02 --4.7331112502480371E-02 --4.7311590730167712E-02 --4.7292060717605292E-02 --4.7272522469548703E-02 --4.7252975990753530E-02 --4.7233421285975394E-02 --4.7213858359969871E-02 --4.7194287217492567E-02 --4.7174707863299067E-02 --4.7155120302144971E-02 --4.7135524538785861E-02 --4.7115920577977352E-02 --4.7096308424475028E-02 --4.7076688083034481E-02 --4.7057059558411322E-02 --4.7037422855361118E-02 --4.7017777978639493E-02 --4.6998124933002025E-02 --4.6978463723204321E-02 --4.6958794354001965E-02 --4.6939116830150548E-02 --4.6919431156405671E-02 --4.6899737337522937E-02 --4.6880035378257939E-02 --4.6860325283366255E-02 --4.6840607057603505E-02 --4.6820880705725251E-02 --4.6801146232487129E-02 --4.6781403642644694E-02 --4.6761652940953566E-02 --4.6741894132169344E-02 --4.6722127221047592E-02 --4.6702352212343944E-02 --4.6682569110813962E-02 --4.6662777921213275E-02 --4.6642978648297438E-02 --4.6623171296822072E-02 --4.6603355871542768E-02 --4.6583532377215110E-02 --4.6563700818594719E-02 --4.6543861200437159E-02 --4.6524013527498041E-02 --4.6504157804532945E-02 --4.6484294036297502E-02 --4.6464422227547271E-02 --4.6444542383037857E-02 --4.6424654507524865E-02 --4.6404758605763874E-02 --4.6384854682510482E-02 --4.6364942742520295E-02 --4.6345022790548911E-02 --4.6325094831351901E-02 --4.6305158869684879E-02 --4.6285214910303435E-02 --4.6265262957963162E-02 --4.6245303017419664E-02 --4.6225335093428528E-02 --4.6205359190745351E-02 --4.6185375314125726E-02 --4.6165383468325244E-02 --4.6145383658099504E-02 --4.6125375888204097E-02 --4.6105360163394636E-02 --4.6085336488426693E-02 --4.6065304868055879E-02 --4.6045265307037772E-02 --4.6025217810127993E-02 --4.6005162382082111E-02 --4.5985099027655726E-02 --4.5965027751604451E-02 --4.5944948558683849E-02 --4.5924861453649560E-02 --4.5904766441257128E-02 --4.5884663526262193E-02 --4.5864552713420312E-02 --4.5844434007487105E-02 --4.5824307413218156E-02 --4.5804172935369064E-02 --4.5784030578695435E-02 --4.5763880347952840E-02 --4.5743722247896884E-02 --4.5723556283283166E-02 --4.5703382458867285E-02 --4.5683200779404826E-02 --4.5663011249651379E-02 --4.5642813874362566E-02 --4.5622608658293942E-02 --4.5602395606201135E-02 --4.5582174722839729E-02 --4.5561946012965322E-02 --4.5541709481333494E-02 --4.5521465132699855E-02 --4.5501212971819999E-02 --4.5480953003449509E-02 --4.5460685232344006E-02 --4.5440409663259053E-02 --4.5420126300950270E-02 --4.5399835150173228E-02 --4.5379536215683546E-02 --4.5359229502236802E-02 --4.5338915014588602E-02 --4.5318592757494537E-02 --4.5298262735710186E-02 --4.5277924953991175E-02 --4.5257579417093081E-02 --4.5237226129771504E-02 --4.5216865096782029E-02 --4.5196496322880253E-02 --4.5176119812821783E-02 --4.5155735571362196E-02 --4.5135343603257119E-02 --4.5114943913262109E-02 --4.5094536506132786E-02 --4.5074121386624720E-02 --4.5053698559493538E-02 --4.5033268029494811E-02 --4.5012829801384151E-02 --4.4992383879917129E-02 --4.4971930269849358E-02 --4.4951468975936437E-02 --4.4931000002933943E-02 --4.4910523355597497E-02 --4.4890039038682668E-02 --4.4869547056945069E-02 --4.4849047415140272E-02 --4.4828540118023903E-02 --4.4808025170351526E-02 --4.4787502576878760E-02 --4.4766972342361197E-02 --4.4746434471554408E-02 --4.4725888969214020E-02 --4.4705335840095603E-02 --4.4684775088954777E-02 --4.4664206720547113E-02 --4.4643630739628209E-02 --4.4623047150953672E-02 --4.4602455959279093E-02 --4.4581857169360070E-02 --4.4561250785952182E-02 --4.4540636813811048E-02 --4.4520015257692225E-02 --4.4499386122351360E-02 --4.4478749412544004E-02 --4.4458105133025769E-02 --4.4437453288552267E-02 --4.4416793883879056E-02 --4.4396126923761756E-02 --4.4375452412955950E-02 --4.4354770356217252E-02 --4.4334080758301239E-02 --4.4313383623963504E-02 --4.4292678957959651E-02 --4.4271966765045273E-02 --4.4251247049975975E-02 --4.4230519817507329E-02 --4.4209785072394953E-02 --4.4189042819394411E-02 --4.4168293063261338E-02 --4.4147535808751304E-02 --4.4126771060619907E-02 --4.4105998823622747E-02 --4.4085219102515415E-02 --4.4064431902053502E-02 --4.4043637226992609E-02 --4.4022835082088339E-02 --4.4002025472096265E-02 --4.3981208401771998E-02 --4.3960383875871131E-02 --4.3939551899149255E-02 --4.3918712476361976E-02 --4.3897865612264872E-02 --4.3877011311613548E-02 --4.3856149579163596E-02 --4.3835280419670608E-02 --4.3814403837890190E-02 --4.3793519838577918E-02 --4.3772628426489414E-02 --4.3751729606380255E-02 --4.3730823383006025E-02 --4.3709909761122337E-02 --4.3688988745484797E-02 --4.3668060340848969E-02 --4.3647124551970465E-02 --4.3626181383604884E-02 --4.3605230840507797E-02 --4.3584272927434838E-02 --4.3563307649141569E-02 --4.3542335010383605E-02 --4.3521355015916523E-02 --4.3500367670495928E-02 --4.3479372978877419E-02 --4.3458370945816581E-02 --4.3437361576069027E-02 --4.3416344874390327E-02 --4.3395320845536087E-02 --4.3374289494261906E-02 --4.3353250825323382E-02 --4.3332204843476094E-02 --4.3311151553475646E-02 --4.3290090960077646E-02 --4.3269023068037663E-02 --4.3247947882111316E-02 --4.3226865407054178E-02 --4.3205775647621868E-02 --4.3184678608569962E-02 --4.3163574294654061E-02 --4.3142462710629756E-02 --4.3121343861252645E-02 --4.3100217751278334E-02 --4.3079084385462402E-02 --4.3057943768560453E-02 --4.3036795905328065E-02 --4.3015640800520859E-02 --4.2994478458894411E-02 --4.2973308885204328E-02 --4.2952132084206202E-02 --4.2930948060655602E-02 --4.2909756819308170E-02 --4.2888558364919470E-02 --4.2867352702245114E-02 --4.2846139836040673E-02 --4.2824919771061766E-02 --4.2803692512063958E-02 --4.2782458063802875E-02 --4.2761216431034109E-02 --4.2739967618513230E-02 --4.2718711630995866E-02 --4.2697448473237580E-02 --4.2676178149993992E-02 --4.2654900666020679E-02 --4.2633616026073254E-02 --4.2612324234907295E-02 --4.2591025297278401E-02 --4.2569719217942170E-02 --4.2548406001654202E-02 --4.2527085653170087E-02 --4.2505758177245417E-02 --4.2484423578635792E-02 --4.2463081862096790E-02 --4.2441733032384035E-02 --4.2420377094253101E-02 --4.2399014052459591E-02 --4.2377643911759105E-02 --4.2356266676907207E-02 --4.2334882352659538E-02 --4.2313490943771660E-02 --4.2292092454999194E-02 --4.2270686891097704E-02 --4.2249274256822802E-02 --4.2227854556930081E-02 --4.2206427796175131E-02 --4.2184993979313565E-02 --4.2163553111100954E-02 --4.2142105196292919E-02 --4.2120650239645015E-02 --4.2099188245912883E-02 --4.2077719219852087E-02 --4.2056243166218227E-02 --4.2034760089766920E-02 --4.2013269995253726E-02 --4.1991772887434262E-02 --4.1970268771064120E-02 --4.1948757650898894E-02 --4.1927239531694173E-02 --4.1905714418205557E-02 --4.1884182315188645E-02 --4.1862643227399021E-02 --4.1841097159592298E-02 --4.1819544116524054E-02 --4.1797984102949895E-02 --4.1776417123625398E-02 --4.1754843183306176E-02 --4.1733262286747813E-02 --4.1711674438705916E-02 --4.1690079643936076E-02 --4.1668477907193878E-02 --4.1646869233234921E-02 --4.1625253626814809E-02 --4.1603631092689136E-02 --4.1582001635613479E-02 --4.1560365260343450E-02 --4.1538721971634635E-02 --4.1517071774242638E-02 --4.1495414672923059E-02 --4.1473750672431468E-02 --4.1452079777523486E-02 --4.1430401992954689E-02 --4.1408717323480677E-02 --4.1387025773857056E-02 --4.1365327348839402E-02 --4.1343622053183336E-02 --4.1321909891644429E-02 --4.1300190868978279E-02 --4.1278464989940492E-02 --4.1256732259286666E-02 --4.1234992681772373E-02 --4.1213246262153225E-02 --4.1191493005184820E-02 --4.1169732915622731E-02 --4.1147965998222590E-02 --4.1126192257739960E-02 --4.1104411698930456E-02 --4.1082624326549654E-02 --4.1060830145353153E-02 --4.1039029160096559E-02 --4.1017221375535463E-02 --4.0995406796425465E-02 --4.0973585427522143E-02 --4.0951757273581108E-02 --4.0929922339357931E-02 --4.0908080629608247E-02 --4.0886232149087619E-02 --4.0864376902551652E-02 --4.0842514894755946E-02 --4.0820646130456079E-02 --4.0798770614407669E-02 --4.0776888351366294E-02 --4.0754999346087561E-02 --4.0733103603327048E-02 --4.0711201127840366E-02 --4.0689291924383100E-02 --4.0667375997710843E-02 --4.0645453352579214E-02 --4.0623523993743776E-02 --4.0601587925960150E-02 --4.0579645153983893E-02 --4.0557695682570651E-02 --4.0535739516475981E-02 --4.0513776660455490E-02 --4.0491807119264783E-02 --4.0469830897659424E-02 --4.0447848000395054E-02 --4.0425858432227228E-02 --4.0403862197911568E-02 --4.0381859302203643E-02 --4.0359849749859074E-02 --4.0337833545633424E-02 --4.0315810694282320E-02 --4.0293781200561346E-02 --4.0271745069226095E-02 --4.0249702305032165E-02 --4.0227652912735133E-02 --4.0205596897090627E-02 --4.0183534262854217E-02 --4.0161465014781510E-02 --4.0139389157628089E-02 --4.0117306696149553E-02 --4.0095217635101502E-02 --4.0073121979239526E-02 --4.0051019733319232E-02 --4.0028910902096197E-02 --4.0006795490326034E-02 --3.9984673502764308E-02 --3.9962544944166650E-02 --3.9940409819288633E-02 --3.9918268132885862E-02 --3.9896119889713928E-02 --3.9873965094528417E-02 --3.9851803752084941E-02 --3.9829635867139085E-02 --3.9807461444446454E-02 --3.9785280488762620E-02 --3.9763093004843195E-02 --3.9740898997443770E-02 --3.9718698471319945E-02 --3.9696491431227318E-02 --3.9674277881921467E-02 --3.9652057828158005E-02 --3.9629831274692502E-02 --3.9607598226280585E-02 --3.9585358687677825E-02 --3.9563112663639828E-02 --3.9540860158922199E-02 --3.9518601178280502E-02 --3.9496335726470357E-02 --3.9474063808247348E-02 --3.9451785428367088E-02 --3.9429500591585148E-02 --3.9407209302657127E-02 --3.9384911566338630E-02 --3.9362607387385250E-02 --3.9340296770552584E-02 --3.9317979720596218E-02 --3.9295656242271756E-02 --3.9273326340334778E-02 --3.9250990019540896E-02 --3.9228647284645694E-02 --3.9206298140404772E-02 --3.9183942591573727E-02 --3.9161580642908152E-02 --3.9139212299163631E-02 --3.9116837565095777E-02 --3.9094456445460182E-02 --3.9072068945012424E-02 --3.9049675068508115E-02 --3.9027274820702840E-02 --3.9004868206352197E-02 --3.8982455230211793E-02 --3.8960035897037205E-02 --3.8937610211584046E-02 --3.8915178178607887E-02 --3.8892739802864333E-02 --3.8870295089108983E-02 --3.8847844042097436E-02 --3.8825386666585290E-02 --3.8802922967328117E-02 --3.8780452949081529E-02 --3.8757976616601117E-02 --3.8735493974642488E-02 --3.8713005027961218E-02 --3.8690509781312908E-02 --3.8668008239453169E-02 --3.8645500407137559E-02 --3.8622986289121711E-02 --3.8600465890161202E-02 --3.8577939215011632E-02 --3.8555406268428585E-02 --3.8532867055167674E-02 --3.8510321579984477E-02 --3.8487769847634593E-02 --3.8465211862873633E-02 --3.8442647630457169E-02 --3.8420077155140821E-02 --3.8397500441680145E-02 --3.8374917494830775E-02 --3.8352328319348289E-02 --3.8329732919988278E-02 --3.8307131301506356E-02 --3.8284523468658078E-02 --3.8261909426199094E-02 --3.8239289178884958E-02 --3.8216662731471285E-02 --3.8194030088713651E-02 --3.8171391255367663E-02 --3.8148746236188913E-02 --3.8126095035933005E-02 --3.8103437659355532E-02 --3.8080774111212072E-02 --3.8058104396258244E-02 --3.8035428519249612E-02 --3.8012746484941802E-02 --3.7990058298090393E-02 --3.7967363963450983E-02 --3.7944663485779170E-02 --3.7921956869830534E-02 --3.7899244120360699E-02 --3.7876525242125238E-02 --3.7853800239879755E-02 --3.7831069118379829E-02 --3.7808331882381079E-02 --3.7785588536639068E-02 --3.7762839085909432E-02 --3.7740083534947733E-02 --3.7717321888509577E-02 --3.7694554151350569E-02 --3.7671780328226274E-02 --3.7649000423892333E-02 --3.7626214443104294E-02 --3.7603422390617793E-02 --3.7580624271188384E-02 --3.7557820089571689E-02 --3.7535009850523299E-02 --3.7512193558798805E-02 --3.7489371219153807E-02 --3.7466542836343895E-02 --3.7443708415124670E-02 --3.7420867960251701E-02 --3.7398021476480629E-02 --3.7375168968567012E-02 --3.7352310441266454E-02 --3.7329445899334568E-02 --3.7306575347526919E-02 --3.7283698790599118E-02 --3.7260816233306758E-02 --3.7237927680405444E-02 --3.7215033136650755E-02 --3.7192132606798288E-02 --3.7169226095603643E-02 --3.7146313607822418E-02 --3.7123395148210211E-02 --3.7100470721522595E-02 --3.7077540332515195E-02 --3.7054603985943568E-02 --3.7031661686563355E-02 --3.7008713439130120E-02 --3.6985759248399461E-02 --3.6962799119126991E-02 --3.6939833056068273E-02 --3.6916861063978929E-02 --3.6893883147614541E-02 --3.6870899311730716E-02 --3.6847909561083032E-02 --3.6824913900427095E-02 --3.6801912334518502E-02 --3.6778904868112840E-02 --3.6755891505965713E-02 --3.6732872252832706E-02 --3.6709847113469425E-02 --3.6686816092631448E-02 --3.6663779195074381E-02 --3.6640736425553821E-02 --3.6617687788825355E-02 --3.6594633289644601E-02 --3.6571572932767117E-02 --3.6548506722948522E-02 --3.6525434664944401E-02 --3.6502356763510373E-02 --3.6479273023401995E-02 --3.6456183449374881E-02 --3.6433088046184635E-02 --3.6409986818910410E-02 --3.6386879775790845E-02 --3.6363766926697967E-02 --3.6340648273469910E-02 --3.6317523806011900E-02 --3.6294393516896423E-02 --3.6271257413916624E-02 --3.6248115508658106E-02 --3.6224967810005927E-02 --3.6201814324821023E-02 --3.6178655054622651E-02 --3.6155489990724751E-02 --3.6132319125593879E-02 --3.6109142464716915E-02 --3.6085960018085457E-02 --3.6062771794741579E-02 --3.6039577802814159E-02 --3.6016378046165101E-02 --3.5993172517946904E-02 --3.5969961210993606E-02 --3.5946744128453501E-02 --3.5923521278268589E-02 --3.5900292669604858E-02 --3.5877058313089745E-02 --3.5853818214900093E-02 --3.5830572365949290E-02 --3.5807320755249873E-02 --3.5784063385643411E-02 --3.5760800268295048E-02 --3.5737531414077955E-02 --3.5714256833223754E-02 --3.5690976532417637E-02 --3.5667690502636074E-02 --3.5644398731324217E-02 --3.5621101219465802E-02 --3.5597797978602921E-02 --3.5574489019764483E-02 --3.5551174352347517E-02 --3.5527853983486353E-02 --3.5504527907831658E-02 --3.5481196115733207E-02 --3.5457858606219493E-02 --3.5434515387064498E-02 --3.5411166467214553E-02 --3.5387811857750591E-02 --3.5364451568448897E-02 --3.5341085595356765E-02 --3.5317713927963845E-02 --3.5294336563819848E-02 --3.5270953511004302E-02 --3.5247564778470526E-02 --3.5224170375786928E-02 --3.5200770311731175E-02 --3.5177364584347351E-02 --3.5153953184865423E-02 --3.5130536110250611E-02 --3.5107113367310205E-02 --3.5083684964386644E-02 --3.5060250912678843E-02 --3.5036811223476863E-02 --3.5013365895099867E-02 --3.4989914915129407E-02 --3.4966458277778167E-02 --3.4942995992554272E-02 --3.4919528070830125E-02 --3.4896054522866808E-02 --3.4872575358092080E-02 --3.4849090575805305E-02 --3.4825600164463774E-02 --3.4802104117185526E-02 --3.4778602442166191E-02 --3.4755095150372797E-02 --3.4731582253220150E-02 --3.4708063762128830E-02 --3.4684539678191066E-02 --3.4661009988213802E-02 --3.4637474682662019E-02 --3.4613933770237866E-02 --3.4590387263902789E-02 --3.4566835174617921E-02 --3.4543277511896030E-02 --3.4519714277817991E-02 --3.4496145461174091E-02 --3.4472571052628104E-02 --3.4448991059778902E-02 --3.4425405495573554E-02 --3.4401814370423646E-02 --3.4378217692478265E-02 --3.4354615464595194E-02 --3.4331007677377325E-02 --3.4307394321877960E-02 --3.4283775404680937E-02 --3.4260150938919307E-02 --3.4236520934479535E-02 --3.4212885397517573E-02 --3.4189244331179293E-02 --3.4165597729871273E-02 --3.4141945587306176E-02 --3.4118287906905194E-02 --3.4094624697551083E-02 --3.4070955968752377E-02 --3.4047281730850316E-02 --3.4023601990718029E-02 --3.3999916740513732E-02 --3.3976225969546303E-02 --3.3952529680627001E-02 --3.3928827886390886E-02 --3.3905120598186470E-02 --3.3881407824471625E-02 --3.3857689571135226E-02 --3.3833965831533766E-02 --3.3810236595231587E-02 --3.3786501863339258E-02 --3.3762761647828841E-02 --3.3739015960326108E-02 --3.3715264810525308E-02 --3.3691508206132426E-02 --3.3667746142038477E-02 --3.3643978607544624E-02 --3.3620205601482350E-02 --3.3596427134280189E-02 --3.3572643216839219E-02 --3.3548853859309127E-02 --3.3525059070449288E-02 --3.3501258846036351E-02 --3.3477453174232889E-02 --3.3453642052979918E-02 --3.3429825495728246E-02 --3.3406003515893068E-02 --3.3382176120664062E-02 --3.3358343315062558E-02 --3.3334505097616131E-02 --3.3310661461842327E-02 --3.3286812405108383E-02 --3.3262957932922818E-02 --3.3239098052719740E-02 --3.3215232777528518E-02 --3.3191362121848235E-02 --3.3167486086090499E-02 --3.3143604656576599E-02 --3.3119717825804876E-02 --3.3095825604557996E-02 --3.3071928006156853E-02 --3.3048025039758455E-02 --3.3024116712319911E-02 --3.3000203024632697E-02 --3.2976283969545751E-02 --3.2952359542450751E-02 --3.2928429749742173E-02 --3.2904494600403594E-02 --3.2880554104838693E-02 --3.2856608274254372E-02 --3.2832657112203338E-02 --3.2808700609410171E-02 --3.2784738758389588E-02 --3.2760771566121775E-02 --3.2736799043848130E-02 --3.2712821201529345E-02 --3.2688838048043532E-02 --3.2664849587490427E-02 --3.2640855813600107E-02 --3.2616856720169084E-02 --3.2592852310292637E-02 --3.2568842590917461E-02 --3.2544827572812629E-02 --3.2520807270800846E-02 --3.2496781693281282E-02 --3.2472750829553747E-02 --3.2448714667353822E-02 --3.2424673210911005E-02 --3.2400626473059975E-02 --3.2376574465797073E-02 --3.2352517199862443E-02 --3.2328454682024756E-02 --3.2304386904113302E-02 --3.2280313855450167E-02 --3.2256235538954223E-02 --3.2232151966783959E-02 --3.2208063150717225E-02 --3.2183969101537369E-02 --3.2159869827119256E-02 --3.2135765320854576E-02 --3.2111655572070727E-02 --3.2087540581063147E-02 --3.2063420357770794E-02 --3.2039294913478282E-02 --3.2015164261846592E-02 --3.1991028414378966E-02 --3.1966887365154281E-02 --3.1942741101197776E-02 --3.1918589620338007E-02 --3.1894432932676339E-02 --3.1870271049695593E-02 --3.1846103985105179E-02 --3.1821931751264659E-02 --3.1797754343427360E-02 --3.1773571747516584E-02 --3.1749383960523708E-02 --3.1725190995797264E-02 --3.1700992867029022E-02 --3.1676789583951592E-02 --3.1652581154514789E-02 --3.1628367576281236E-02 --3.1604148839353530E-02 --3.1579924940746650E-02 --3.1555695890952987E-02 --3.1531461701801364E-02 --3.1507222384151740E-02 --3.1482977948028339E-02 --3.1458728393202670E-02 --3.1434473709873754E-02 --3.1410213893155361E-02 --3.1385948951362264E-02 --3.1361678895036015E-02 --3.1337403736214353E-02 --3.1313123487283115E-02 --3.1288838149594857E-02 --3.1264547711194156E-02 --3.1240252164639513E-02 --3.1215951520099476E-02 --3.1191645791202923E-02 --3.1167334989620418E-02 --3.1143019125722489E-02 --3.1118698201648143E-02 --3.1094372206719800E-02 --3.1070041132734299E-02 --3.1045704987417457E-02 --3.1021363782900036E-02 --3.0997017531077489E-02 --3.0972666243616793E-02 --3.0948309925440561E-02 --3.0923948567774969E-02 --3.0899582162407457E-02 --3.0875210714402055E-02 --3.0850834233826056E-02 --3.0826452732937999E-02 --3.0802066226156367E-02 --3.0777674720834355E-02 --3.0753278205173762E-02 --3.0728876666579606E-02 --3.0704470111757219E-02 --3.0680058556716603E-02 --3.0655642014097529E-02 --3.0631220492132873E-02 --3.0606793995715531E-02 --3.0582362518872648E-02 --3.0557926054145902E-02 --3.0533484604676392E-02 --3.0509038180342177E-02 --3.0484586792044820E-02 --3.0460130452209588E-02 --3.0435669170044352E-02 --3.0411202938719347E-02 --3.0386731747428772E-02 --3.0362255598606280E-02 --3.0337774505548629E-02 --3.0313288480907155E-02 --3.0288797535233527E-02 --3.0264301676713807E-02 --3.0239800900092532E-02 --3.0215295195201799E-02 --3.0190784562268851E-02 --3.0166269012539736E-02 --3.0141748557875173E-02 --3.0117223210379060E-02 --3.0092692980547432E-02 --3.0068157864339036E-02 --3.0043617850393604E-02 --3.0019072937656401E-02 --2.9994523139244816E-02 --2.9969968468285452E-02 --2.9945408934034957E-02 --2.9920844544089661E-02 --2.9896275296931833E-02 --2.9871701184955864E-02 --2.9847122206939962E-02 --2.9822538373187560E-02 --2.9797949695067157E-02 --2.9773356183344327E-02 --2.9748757848028631E-02 --2.9724154688853602E-02 --2.9699546696598376E-02 --2.9674933867543551E-02 --2.9650316211439785E-02 --2.9625693739945190E-02 --2.9601066464726870E-02 --2.9576434397124006E-02 --2.9551797538923747E-02 --2.9527155881155117E-02 --2.9502509418574858E-02 --2.9477858159159862E-02 --2.9453202113497164E-02 --2.9428541292930807E-02 --2.9403875709069157E-02 --2.9379205365598973E-02 --2.9354530254670868E-02 --2.9329850370850279E-02 --2.9305165722358643E-02 --2.9280476320879680E-02 --2.9255782177509203E-02 --2.9231083302859385E-02 --2.9206379700872944E-02 --2.9181671362892542E-02 --2.9156958281655380E-02 --2.9132240465315699E-02 --2.9107517927219013E-02 --2.9082790678837914E-02 --2.9058058729887207E-02 --2.9033322085513572E-02 --2.9008580739685774E-02 --2.8983834686128848E-02 --2.8959083929496365E-02 --2.8934328479442727E-02 --2.8909568347361806E-02 --2.8884803546702323E-02 --2.8860034086201931E-02 --2.8835259958668345E-02 --2.8810481154913938E-02 --2.8785697679036621E-02 --2.8760909542988121E-02 --2.8736116758478692E-02 --2.8711319336685037E-02 --2.8686517285905322E-02 --2.8661710601940619E-02 --2.8636899277702580E-02 --2.8612083314365769E-02 --2.8587262719459362E-02 --2.8562437503474529E-02 --2.8537607682558613E-02 --2.8512773270330163E-02 --2.8487934261368534E-02 --2.8463090643781799E-02 --2.8438242417420000E-02 --2.8413389593759202E-02 --2.8388532185143867E-02 --2.8363670204909156E-02 --2.8338803664559913E-02 --2.8313932559501067E-02 --2.8289056877659317E-02 --2.8264176618531311E-02 --2.8239291796442884E-02 --2.8214402425562706E-02 --2.8189508516090523E-02 --2.8164610076455623E-02 --2.8139707105019882E-02 --2.8114799593890835E-02 --2.8089887541868325E-02 --2.8064970958977798E-02 --2.8040049856536745E-02 --2.8015124247000357E-02 --2.7990194142470812E-02 --2.7965259543765459E-02 --2.7940320442521847E-02 --2.7915376835483070E-02 --2.7890428730989163E-02 --2.7865476139286090E-02 --2.7840519073150778E-02 --2.7815557545891521E-02 --2.7790591559096883E-02 --2.7765621102024487E-02 --2.7740646169391488E-02 --2.7715666773134046E-02 --2.7690682927852671E-02 --2.7665694644825430E-02 --2.7640701933444159E-02 --2.7615704795768373E-02 --2.7590703223915481E-02 --2.7565697213029337E-02 --2.7540686772449696E-02 --2.7515671914825776E-02 --2.7490652652054203E-02 --2.7465628995446429E-02 --2.7440600949369225E-02 --2.7415568505966426E-02 --2.7390531658984408E-02 --2.7365490416670302E-02 --2.7340444791833098E-02 --2.7315394796510694E-02 --2.7290340442047003E-02 --2.7265281734147561E-02 --2.7240218665564666E-02 --2.7215151229248787E-02 --2.7190079432038935E-02 --2.7165003286606440E-02 --2.7139922805297013E-02 --2.7114838000065842E-02 --2.7089748877840502E-02 --2.7064655430262860E-02 --2.7039557647819831E-02 --2.7014455537583946E-02 --2.6989349115713726E-02 --2.6964238395547825E-02 --2.6939123386206409E-02 --2.6914004093934542E-02 --2.6888880514592355E-02 --2.6863752642106591E-02 --2.6838620480012839E-02 --2.6813484038733744E-02 --2.6788343329869117E-02 --2.6763198366951308E-02 --2.6738049160667021E-02 --2.6712895704953207E-02 --2.6687737988743725E-02 --2.6662576015003374E-02 --2.6637409799663562E-02 --2.6612239357186099E-02 --2.6587064697204732E-02 --2.6561885827246761E-02 --2.6536702744632185E-02 --2.6511515442353705E-02 --2.6486323921960868E-02 --2.6461128195228296E-02 --2.6435928274371540E-02 --2.6410724171091769E-02 --2.6385515895774946E-02 --2.6360303446368201E-02 --2.6335086813650162E-02 --2.6309865996937954E-02 --2.6284641008855050E-02 --2.6259411863010923E-02 --2.6234178572358085E-02 --2.6208941148796943E-02 --2.6183699591373705E-02 --2.6158453889394355E-02 --2.6133204039642789E-02 --2.6107950054408524E-02 --2.6082691947686157E-02 --2.6057429732594600E-02 --2.6032163421408083E-02 --2.6006893014679268E-02 --2.5981618501446667E-02 --2.5956339876983384E-02 --2.5931057154312865E-02 --2.5905770348951352E-02 --2.5880479473178238E-02 --2.5855184537487256E-02 --2.5829885543902465E-02 --2.5804582483715956E-02 --2.5779275352000700E-02 --2.5753964159549884E-02 --2.5728648920432497E-02 --2.5703329646748395E-02 --2.5678006349266841E-02 --2.5652679031947741E-02 --2.5627347687594983E-02 --2.5602012311099896E-02 --2.5576672912063080E-02 --2.5551329504313821E-02 --2.5525982100130209E-02 --2.5500630710499607E-02 --2.5475275340707076E-02 --2.5449915983888238E-02 --2.5424552633947391E-02 --2.5399185299619594E-02 --2.5373813995326486E-02 --2.5348438732783710E-02 --2.5323059520857786E-02 --2.5297676365205756E-02 --2.5272289262783434E-02 --2.5246898210072491E-02 --2.5221503212695274E-02 --2.5196104280988851E-02 --2.5170701426235766E-02 --2.5145294660943548E-02 --2.5119883994294857E-02 --2.5094469422597382E-02 --2.5069050939926021E-02 --2.5043628550156738E-02 --2.5018202263726440E-02 --2.4992772092374625E-02 --2.4967338049913142E-02 --2.4941900147477301E-02 --2.4916458381604334E-02 --2.4891012744741686E-02 --2.4865563238560741E-02 --2.4840109872708210E-02 --2.4814652659321913E-02 --2.4789191615649287E-02 --2.4763726756654718E-02 --2.4738258076831336E-02 --2.4712785562603274E-02 --2.4687309214192620E-02 --2.4661829047216498E-02 --2.4636345077030313E-02 --2.4610857315751102E-02 --2.4585365773610132E-02 --2.4559870448865005E-02 --2.4534371333384170E-02 --2.4508868427488520E-02 --2.4483361743753491E-02 --2.4457851295596210E-02 --2.4432337095994103E-02 --2.4406819156823890E-02 --2.4381297476776632E-02 --2.4355772045248882E-02 --2.4330242860699916E-02 --2.4304709938902436E-02 --2.4279173296345938E-02 --2.4253632943098687E-02 --2.4228088886752611E-02 --2.4202541128866717E-02 --2.4176989665468666E-02 --2.4151434495928183E-02 --2.4125875628313243E-02 --2.4100313072590002E-02 --2.4074746843070476E-02 --2.4049176955632825E-02 --2.4023603414132341E-02 --2.3998026208168696E-02 --2.3972445331959753E-02 --2.3946860797434525E-02 --2.3921272619932144E-02 --2.3895680812900687E-02 --2.3870085388535432E-02 --2.3844486350432317E-02 --2.3818883689031567E-02 --2.3793277397923033E-02 --2.3767667489255569E-02 --2.3742053979946182E-02 --2.3716436882813413E-02 --2.3690816207534108E-02 --2.3665191958854966E-02 --2.3639564131840381E-02 --2.3613932722259603E-02 --2.3588297736726674E-02 --2.3562659185952271E-02 --2.3537017084290814E-02 --2.3511371449637913E-02 --2.3485722291880579E-02 --2.3460069599500068E-02 --2.3434413360211029E-02 --2.3408753583239725E-02 --2.3383090287969789E-02 --2.3357423489403541E-02 --2.3331753196936606E-02 --2.3306079416740077E-02 --2.3280402144977806E-02 --2.3254721376510846E-02 --2.3229037115962348E-02 --2.3203349374070866E-02 --2.3177658163901292E-02 --2.3151963502167090E-02 --2.3126265401913336E-02 --2.3100563857458851E-02 --2.3074858858487722E-02 --2.3049150408088137E-02 --2.3023438520158312E-02 --2.2997723208578433E-02 --2.2972004486533765E-02 --2.2946282364978081E-02 --2.2920556841375152E-02 --2.2894827908359363E-02 --2.2869095568654331E-02 --2.2843359835491329E-02 --2.2817620722121179E-02 --2.2791878240472255E-02 --2.2766132400966175E-02 --2.2740383203038266E-02 --2.2714630640706696E-02 --2.2688874715888121E-02 --2.2663115441164963E-02 --2.2637352829580636E-02 --2.2611586893099885E-02 --2.2585817642608412E-02 --2.2560045078999197E-02 --2.2534269196601685E-02 --2.2508489995678491E-02 --2.2482707487031559E-02 --2.2456921682635293E-02 --2.2431132595044659E-02 --2.2405340236512607E-02 --2.2379544610708721E-02 --2.2353745713947982E-02 --2.2327943545521180E-02 --2.2302138112042014E-02 --2.2276329422181232E-02 --2.2250517491683570E-02 --2.2224702338765848E-02 --2.2198883968649993E-02 --2.2173062372165250E-02 --2.2147237544174456E-02 --2.2121409493942798E-02 --2.2095578233724253E-02 --2.2069743778449932E-02 --2.2043906144300671E-02 --2.2018065337311092E-02 --2.1992221348986988E-02 --2.1966374173458127E-02 --2.1940523819915479E-02 --2.1914670301491732E-02 --2.1888813633327467E-02 --2.1862953831895671E-02 --2.1837090904595052E-02 --2.1811224841912086E-02 --2.1785355635723494E-02 --2.1759483295351992E-02 --2.1733607835954620E-02 --2.1707729272118916E-02 --2.1681847617890465E-02 --2.1655962881528899E-02 --2.1630075057245426E-02 --2.1604184138946752E-02 --2.1578290133669555E-02 --2.1552393054317744E-02 --2.1526492914849146E-02 --2.1500589730430307E-02 --2.1474683511057743E-02 --2.1448774249795410E-02 --2.1422861937893938E-02 --2.1396946582808506E-02 --2.1371028201366046E-02 --2.1345106808052659E-02 --2.1319182413611810E-02 --2.1293255026211769E-02 --2.1267324644246032E-02 --2.1241391264036374E-02 --2.1215454890156533E-02 --2.1189515533405295E-02 --2.1163573205970718E-02 --2.1137627922493841E-02 --2.1111679695427887E-02 --2.1085728522836814E-02 --2.1059774398056987E-02 --2.1033817324385282E-02 --2.1007857314806880E-02 --2.0981894382507419E-02 --2.0955928540152158E-02 --2.0929959798960385E-02 --2.0903988159386155E-02 --2.0878013616949732E-02 --2.0852036173565895E-02 --2.0826055839206280E-02 --2.0800072625648897E-02 --2.0774086549167320E-02 --2.0748097625497015E-02 --2.0722105853731087E-02 --2.0696111222813184E-02 --2.0670113732397827E-02 --2.0644113399776235E-02 --2.0618110242347904E-02 --2.0592104270517490E-02 --2.0566095492301581E-02 --2.0540083910000843E-02 --2.0514069521354514E-02 --2.0488052327640959E-02 --2.0462032337906822E-02 --2.0436009562886385E-02 --2.0409984017678958E-02 --2.0383955718570504E-02 --2.0357924669681421E-02 --2.0331890862552739E-02 --2.0305854293657916E-02 --2.0279814974868221E-02 --2.0253772920718977E-02 --2.0227728145717629E-02 --2.0201680664127065E-02 --2.0175630480673789E-02 --2.0149577587354972E-02 --2.0123521979763630E-02 --2.0097463670181368E-02 --2.0071402674593571E-02 --2.0045339006826719E-02 --2.0019272679203368E-02 --1.9993203697524605E-02 --1.9967132056347748E-02 --1.9941057751766460E-02 --1.9914980793125165E-02 --1.9888901193976991E-02 --1.9862818969342239E-02 --1.9836734135459021E-02 --1.9810646701106431E-02 --1.9784556658089793E-02 --1.9758463998429104E-02 --1.9732368731321687E-02 --1.9706270873010086E-02 --1.9680170438460143E-02 --1.9654067441204851E-02 --1.9627961890320084E-02 --1.9601853781759850E-02 --1.9575743110242867E-02 --1.9549629881684794E-02 --1.9523514108107206E-02 --1.9497395803724955E-02 --1.9471274985785689E-02 --1.9445151667320294E-02 --1.9419025843572295E-02 --1.9392897506339088E-02 --1.9366766660519806E-02 --1.9340633320230900E-02 --1.9314497500227616E-02 --1.9288359216090931E-02 --1.9262218480497251E-02 --1.9236075290063173E-02 --1.9209929636636511E-02 --1.9183781523614583E-02 --1.9157630964888612E-02 --1.9131477975019216E-02 --1.9105322569265004E-02 --1.9079164761000789E-02 --1.9053004549161087E-02 --1.9026841926606766E-02 --1.9000676895613085E-02 --1.8974509469514417E-02 --1.8948339662555800E-02 --1.8922167489886475E-02 --1.8895992965515383E-02 --1.8869816090179483E-02 --1.8843636857079245E-02 --1.8817455266540068E-02 --1.8791271329816686E-02 --1.8765085059910508E-02 --1.8738896473413594E-02 --1.8712705586852930E-02 --1.8686512401980302E-02 --1.8660316909545262E-02 --1.8634119107881191E-02 --1.8607919010793561E-02 --1.8581716633872251E-02 --1.8555511992562689E-02 --1.8529305101711885E-02 --1.8503095964329575E-02 --1.8476884571998642E-02 --1.8450670921803622E-02 --1.8424455026293297E-02 --1.8398236900653744E-02 --1.8372016561371558E-02 --1.8345794025215568E-02 --1.8319569297184420E-02 --1.8293342367600884E-02 --1.8267113230909619E-02 --1.8240881898929390E-02 --1.8214648387277203E-02 --1.8188412712218351E-02 --1.8162174890277147E-02 --1.8135934928593955E-02 --1.8109692819157204E-02 --1.8083448556185568E-02 --1.8057202150534083E-02 --1.8030953617833689E-02 --1.8004702973425744E-02 --1.7978450232379182E-02 --1.7952195402994642E-02 --1.7925938479340972E-02 --1.7899679456065933E-02 --1.7873418342590555E-02 --1.7847155154010190E-02 --1.7820889905706638E-02 --1.7794622613336284E-02 --1.7768353286658926E-02 --1.7742081919037062E-02 --1.7715808502921461E-02 --1.7689533046959922E-02 --1.7663255567944468E-02 --1.7636976081893144E-02 --1.7610694603713832E-02 --1.7584411144155418E-02 --1.7558125698866518E-02 --1.7531838261137661E-02 --1.7505548837733954E-02 --1.7479257444251415E-02 --1.7452964095540941E-02 --1.7426668804906342E-02 --1.7400371583138695E-02 --1.7374072429330995E-02 --1.7347771339485712E-02 --1.7321468318783430E-02 --1.7295163380196227E-02 --1.7268856537583626E-02 --1.7242547806246001E-02 --1.7216237199543450E-02 --1.7189924716537942E-02 --1.7163610350800471E-02 --1.7137294106092573E-02 --1.7110975997345373E-02 --1.7084656039550374E-02 --1.7058334246189511E-02 --1.7032010629302562E-02 --1.7005685190246016E-02 --1.6979357924771503E-02 --1.6953028835363527E-02 --1.6926697934099240E-02 --1.6900365234501724E-02 --1.6874030752956442E-02 --1.6847694505470155E-02 --1.6821356493891753E-02 --1.6795016710250330E-02 --1.6768675154028339E-02 --1.6742331838758607E-02 --1.6715986779659877E-02 --1.6689639992911745E-02 --1.6663291494370583E-02 --1.6636941287522040E-02 --1.6610589364701476E-02 --1.6584235723965758E-02 --1.6557880378099344E-02 --1.6531523342207817E-02 --1.6505164632491267E-02 --1.6478804265265046E-02 --1.6452442245616258E-02 --1.6426078565557545E-02 --1.6399713221761859E-02 --1.6373346228115444E-02 --1.6346977601638002E-02 --1.6320607356451106E-02 --1.6294235504906513E-02 --1.6267862053445686E-02 --1.6241486999643347E-02 --1.6215110342842176E-02 --1.6188732093053392E-02 --1.6162352263239262E-02 --1.6135970867879854E-02 --1.6109587922528250E-02 --1.6083203435690804E-02 --1.6056817402019127E-02 --1.6030429817147702E-02 --1.6004040691559862E-02 --1.5977650041043505E-02 --1.5951257881921994E-02 --1.5924864231011856E-02 --1.5898469098363850E-02 --1.5872072476559154E-02 --1.5845674357701157E-02 --1.5819274751769384E-02 --1.5792873677074989E-02 --1.5766471150119830E-02 --1.5740067185103134E-02 --1.5713661792155796E-02 --1.5687254967975166E-02 --1.5660846707483952E-02 --1.5634437017487506E-02 --1.5608025912084485E-02 --1.5581613406824586E-02 --1.5555199519417145E-02 --1.5528784263970752E-02 --1.5502367637202023E-02 --1.5475949631611384E-02 --1.5449530251627092E-02 --1.5423109511142279E-02 --1.5396687426102697E-02 --1.5370264016205270E-02 --1.5343839298161957E-02 --1.5317413267369646E-02 --1.5290985911768551E-02 --1.5264557235126161E-02 --1.5238127257404383E-02 --1.5211695997246127E-02 --1.5185263467638538E-02 --1.5158829679370494E-02 --1.5132394632856056E-02 --1.5105958323516831E-02 --1.5079520754998882E-02 --1.5053081941849891E-02 --1.5026641899612173E-02 --1.5000200644743174E-02 --1.4973758192669514E-02 --1.4947314544172783E-02 --1.4920869690598946E-02 --1.4894423632456558E-02 --1.4867976386203241E-02 --1.4841527969374003E-02 --1.4815078397114509E-02 --1.4788627683187358E-02 --1.4762175830165517E-02 --1.4735722831215861E-02 --1.4709268686226037E-02 --1.4682813410767125E-02 --1.4656357022173640E-02 --1.4629899535367372E-02 --1.4603440963964591E-02 --1.4576981312925424E-02 --1.4550520577799896E-02 --1.4524058757816982E-02 --1.4497595864475668E-02 --1.4471131911840220E-02 --1.4444666916803415E-02 --1.4418200897531239E-02 --1.4391733861035906E-02 --1.4365265798640895E-02 --1.4338796705519465E-02 --1.4312326596676823E-02 --1.4285855491682431E-02 --1.4259383405897601E-02 --1.4232910351698807E-02 --1.4206436335528075E-02 --1.4179961353110388E-02 --1.4153485401849127E-02 --1.4127008494061776E-02 --1.4100530646896915E-02 --1.4074051875901907E-02 --1.4047572195166768E-02 --1.4021091613658256E-02 --1.3994610128219388E-02 --1.3968127735560332E-02 --1.3941644444143158E-02 --1.3915160267633888E-02 --1.3888675222121616E-02 --1.3862189326473765E-02 --1.3835702594164587E-02 --1.3809215021088953E-02 --1.3782726601009864E-02 --1.3756237340958958E-02 --1.3729747255557067E-02 --1.3703256360521228E-02 --1.3676764673076732E-02 --1.3650272206825260E-02 --1.3623778959488709E-02 --1.3597284925474396E-02 --1.3570790111765449E-02 --1.3544294534644400E-02 --1.3517798209671509E-02 --1.3491301150575360E-02 --1.3464803369086811E-02 --1.3438304866767800E-02 --1.3411805641902787E-02 --1.3385305699451970E-02 --1.3358805050761289E-02 --1.3332303709466597E-02 --1.3305801694408632E-02 --1.3279299023002282E-02 --1.3252795695291699E-02 --1.3226291703523099E-02 --1.3199787050254682E-02 --1.3173281750805326E-02 --1.3146775821407356E-02 --1.3120269278724766E-02 --1.3093762138301620E-02 --1.3067254402659741E-02 --1.3040746066503095E-02 --1.3014237131219656E-02 --1.2987727609033601E-02 --1.2961217514320823E-02 --1.2934706866843367E-02 --1.2908195686759411E-02 --1.2881683976625643E-02 --1.2855171725190359E-02 --1.2828658930226817E-02 --1.2802145609050099E-02 --1.2775631780890376E-02 --1.2749117461789708E-02 --1.2722602666165641E-02 --1.2696087398535661E-02 --1.2669571653364924E-02 --1.2643055430141166E-02 --1.2616538743342875E-02 --1.2590021609881732E-02 --1.2563504045745922E-02 --1.2536986066239918E-02 --1.2510467677779091E-02 --1.2483948875124915E-02 --1.2457429656352098E-02 --1.2430910034512164E-02 --1.2404390026136915E-02 --1.2377869648511796E-02 --1.2351348919287247E-02 --1.2324827846478535E-02 --1.2298306421708963E-02 --1.2271784639190353E-02 --1.2245262513587244E-02 --1.2218740065566789E-02 --1.2192217311697548E-02 --1.2165694265085769E-02 --1.2139170933777994E-02 --1.2112647314818264E-02 --1.2086123405867311E-02 --1.2059599218427147E-02 --1.2033074769545474E-02 --1.2006550074647118E-02 --1.1980025147381525E-02 --1.1953499997647247E-02 --1.1926974624592504E-02 --1.1900449026572807E-02 --1.1873923212529738E-02 --1.1847397197056325E-02 --1.1820870995911108E-02 --1.1794344626407726E-02 --1.1767818101870423E-02 --1.1741291419533976E-02 --1.1714764573743668E-02 --1.1688237572288150E-02 --1.1661710432236332E-02 --1.1635183170189998E-02 --1.1608655801568970E-02 --1.1582128339081944E-02 --1.1555600781842517E-02 --1.1529073125150115E-02 --1.1502545376341031E-02 --1.1476017553492172E-02 --1.1449489673771410E-02 --1.1422961751291427E-02 --1.1396433798094414E-02 --1.1369905814650324E-02 --1.1343377796733277E-02 --1.1316849749683720E-02 --1.1290321689874781E-02 --1.1263793633718986E-02 --1.1237265595832295E-02 --1.1210737589553819E-02 --1.1184209619150910E-02 --1.1157681683830021E-02 --1.1131153787258439E-02 --1.1104625939826229E-02 --1.1078098154099271E-02 --1.1051570449501490E-02 --1.1025042846070728E-02 --1.0998515347189115E-02 --1.0971987944058677E-02 --1.0945460636408239E-02 --1.0918933441013700E-02 --1.0892406376333345E-02 --1.0865879459314907E-02 --1.0839352705833331E-02 --1.0812826120371918E-02 --1.0786299696611377E-02 --1.0759773434212494E-02 --1.0733247349122312E-02 --1.0706721459546667E-02 --1.0680195781463672E-02 --1.0653670329566805E-02 --1.0627145109913447E-02 --1.0600620117990515E-02 --1.0574095353207963E-02 --1.0547570830405631E-02 --1.0521046567504390E-02 --1.0494522580580295E-02 --1.0467998884480766E-02 --1.0441475486843210E-02 --1.0414952383902087E-02 --1.0388429574019318E-02 --1.0361907069747418E-02 --1.0335384887633485E-02 --1.0308863044009717E-02 --1.0282341555000895E-02 --1.0255820430798720E-02 --1.0229299669346712E-02 --1.0202779269060925E-02 --1.0176259240450120E-02 --1.0149739598597650E-02 --1.0123220359236714E-02 --1.0096701538741801E-02 --1.0070183148854609E-02 --1.0043665188630469E-02 --1.0017147656274783E-02 --9.9906305606806117E-03 --9.9641139160789455E-03 --9.9375977386510234E-03 --9.9110820470716433E-03 --9.8845668554415605E-03 --9.8580521606700770E-03 --9.8315379570020258E-03 --9.8050242529661557E-03 --9.7785110662931361E-03 --9.7519984144428008E-03 --9.7254863141588363E-03 --9.6989747790758776E-03 --9.6724638080609507E-03 --9.6459533961947997E-03 --9.6194435502578012E-03 --9.5929342867870568E-03 --9.5664256228664042E-03 --9.5399175761279650E-03 --9.5134101619112083E-03 --9.4869033800549039E-03 --9.4603972245809725E-03 --9.4338917006167328E-03 --9.4073868252485537E-03 --9.3808826159896136E-03 --9.3543790898758007E-03 --9.3278762623298511E-03 --9.3013741350619836E-03 --9.2748727027358348E-03 --9.2483719689367538E-03 --9.2218719497270240E-03 --9.1953726621855653E-03 --9.1688741237684092E-03 --9.1423763509814304E-03 --9.1158793471263905E-03 --9.0893831065198948E-03 --9.0628876310500598E-03 --9.0363929365693107E-03 --9.0098990404111449E-03 --8.9834059600056530E-03 --8.9569137121801329E-03 --8.9304223018938228E-03 --8.9039317235979631E-03 --8.8774419776736398E-03 --8.8509530793606725E-03 --8.8244650460640901E-03 --8.7979778953475082E-03 --8.7714916444840019E-03 --8.7450063000924852E-03 --8.7185218566037080E-03 --8.6920383128932990E-03 --8.6655556838244469E-03 --8.6390739873104180E-03 --8.6125932406196804E-03 --8.5861134604972578E-03 --8.5596346552090190E-03 --8.5331568204890795E-03 --8.5066799546333078E-03 --8.4802040708742039E-03 --8.4537291863618289E-03 --8.4272553184430929E-03 --8.4007824845463500E-03 --8.3743106948181607E-03 --8.3478399453961547E-03 --8.3213702334767794E-03 --8.2949015711290871E-03 --8.2684339756170563E-03 --8.2419674643858017E-03 --8.2155020550317183E-03 --8.1890377592289849E-03 --8.1625745736793372E-03 --8.1361124946515376E-03 --8.1096515328521121E-03 --8.0831917056388633E-03 --8.0567330305498768E-03 --8.0302755252990472E-03 --8.0038192029720703E-03 --7.9773640610906922E-03 --7.9509100952192650E-03 --7.9244573147060800E-03 --7.8980057371832359E-03 --7.8715553802324398E-03 --7.8451062611775858E-03 --7.8186583939701734E-03 --7.7922117775172011E-03 --7.7657664073038819E-03 --7.7393222909945270E-03 --7.7128794457386948E-03 --7.6864378890610747E-03 --7.6599976387427627E-03 --7.6335587100729765E-03 --7.6071211030967929E-03 --7.5806848126481093E-03 --7.5542498447811902E-03 --7.5278162168325126E-03 --7.5013839465119300E-03 --7.4749530512011391E-03 --7.4485235465455201E-03 --7.4220954343404448E-03 --7.3956687098093591E-03 --7.3692433774178688E-03 --7.3428194536726884E-03 --7.3163969559929976E-03 --7.2899759021955090E-03 --7.2635563090166369E-03 --7.2371381797212827E-03 --7.2107215090499149E-03 --7.1843062997065223E-03 --7.1578925680068394E-03 --7.1314803316229868E-03 --7.1050696084864117E-03 --7.0786604158648665E-03 --7.0522527585901969E-03 --7.0258466312209380E-03 --6.9994420348770368E-03 --6.9730389857554278E-03 --6.9466375019672320E-03 --6.9202376010600664E-03 --6.8938392999590183E-03 --6.8674426052602426E-03 --6.8410475125237295E-03 --6.8146540218578201E-03 --6.7882621481128213E-03 --6.7618719088219552E-03 --6.7354833217720149E-03 --6.7090964046750395E-03 --6.6827111659521383E-03 --6.6563276012002381E-03 --6.6299457090836806E-03 --6.6035655037550399E-03 --6.5771870030977122E-03 --6.5508102248321614E-03 --6.5244351864855964E-03 --6.4980618980374537E-03 --6.4716903559521345E-03 --6.4453205581482308E-03 --6.4189525173698608E-03 --6.3925862511696541E-03 --6.3662217774289355E-03 --6.3398591142930271E-03 --6.3134982734857079E-03 --6.2871392516461802E-03 --6.2607820453825045E-03 --6.2344266662320335E-03 --6.2080731321220483E-03 --6.1817214610269122E-03 --6.1553716709448784E-03 --6.1290237749399403E-03 --6.1026777707434065E-03 --6.0763336545529940E-03 --6.0499914364349630E-03 --6.0236511342256632E-03 --5.9973127658070891E-03 --5.9709763490026014E-03 --5.9446418979786876E-03 --5.9183094117319594E-03 --5.8919788862337487E-03 --5.8656503300053512E-03 --5.8393237606930732E-03 --5.8129991961299778E-03 --5.7866766541126132E-03 --5.7603561497810473E-03 --5.7340376834858807E-03 --5.7077212509935365E-03 --5.6814068591761278E-03 --5.6550945253356182E-03 --5.6287842673058601E-03 --5.6024761032427628E-03 --5.5761700493934131E-03 --5.5498661071831960E-03 --5.5235642715647116E-03 --5.4972645477439509E-03 --5.4709669533821214E-03 --5.4446715067675410E-03 --5.4183782257894260E-03 --5.3920871269785252E-03 --5.3657982134791360E-03 --5.3395114805733258E-03 --5.3132269318905559E-03 --5.2869445843016878E-03 --5.2606644558267773E-03 --5.2343865644592959E-03 --5.2081109273715087E-03 --5.1818375494566624E-03 --5.1555664261492638E-03 --5.1292975595471366E-03 --5.1030309658505130E-03 --5.0767666630198247E-03 --5.0505046692600353E-03 --5.0242450023780709E-03 --4.9979876689629959E-03 --4.9717326644086249E-03 --4.9454799892459213E-03 --4.9192296591141329E-03 --4.8929816921563099E-03 --4.8667361064552760E-03 --4.8404929198146733E-03 --4.8142521405030673E-03 --4.7880137645024108E-03 --4.7617777912734175E-03 --4.7355442356248507E-03 --4.7093131157773830E-03 --4.6830844497341307E-03 --4.6568582552528525E-03 --4.6306345421750520E-03 --4.6044133071308155E-03 --4.5781945486391288E-03 --4.5519782802849844E-03 --4.5257645201657575E-03 --4.4995532864481394E-03 --4.4733445973204047E-03 --4.4471384642734086E-03 --4.4209348841931931E-03 --4.3947338543884494E-03 --4.3685353873289647E-03 --4.3423395014989445E-03 --4.3161462150955038E-03 --4.2899555459895693E-03 --4.2637675069557039E-03 --4.2375820961430078E-03 --4.2113993106323230E-03 --4.1852191611964091E-03 --4.1590416657587030E-03 --4.1328668425080891E-03 --4.1066947099125482E-03 --4.0805252823671746E-03 --4.0543585585426532E-03 --4.0281945344067044E-03 --4.0020332192943165E-03 --3.9758746316103794E-03 --3.9497187897627956E-03 --3.9235657118573937E-03 --3.8974154130740116E-03 --3.8712678936821980E-03 --3.8451231497912248E-03 --3.8189811890140075E-03 --3.7928420290542337E-03 --3.7667056880131035E-03 --3.7405721841207015E-03 --3.7144415335684387E-03 --3.6883137382246159E-03 --3.6621887942063706E-03 --3.6360667074735540E-03 --3.6099474951424809E-03 --3.5838311751655695E-03 --3.5577177662256204E-03 --3.5316072856638645E-03 --3.5054997366086079E-03 --3.4793951144460912E-03 --3.4532934234126271E-03 --3.4271946808014536E-03 --3.4010989049431048E-03 --3.3750061141763613E-03 --3.3489163259184623E-03 --3.3228295449933137E-03 --3.2967457671869197E-03 --3.2706649953463474E-03 --3.2445872461165232E-03 --3.2185125377215342E-03 --3.1924408885859279E-03 --3.1663723166434864E-03 --3.1403068284256170E-03 --3.1142444198380297E-03 --3.0881850922408723E-03 --3.0621288616103099E-03 --3.0360757461778101E-03 --3.0100257642881926E-03 --2.9839789340406651E-03 --2.9579352637427499E-03 --2.9318947499180027E-03 --2.9058573928092950E-03 --2.8798232072922278E-03 --2.8537922113205413E-03 --2.8277644234076895E-03 --2.8017398622559512E-03 --2.7757185378423045E-03 --2.7497004465530266E-03 --2.7236855871074425E-03 --2.6976739737749945E-03 --2.6716656251303682E-03 --2.6456605597359080E-03 --2.6196587960946559E-03 --2.5936603456067102E-03 --2.5676652052673389E-03 --2.5416733728935558E-03 --2.5156848615865675E-03 --2.4896996900747132E-03 --2.4637178768587053E-03 --2.4377394401949464E-03 --2.4117643928667875E-03 --2.3857927330744218E-03 --2.3598244583291970E-03 --2.3338595800906472E-03 --2.3078981165985855E-03 --2.2819400862946581E-03 --2.2559855078210732E-03 --2.2300343955080223E-03 --2.2040867483143745E-03 --2.1781425629535407E-03 --2.1522018493729594E-03 --2.1262646258999982E-03 --2.1003309110515854E-03 --2.0744007234388098E-03 --2.0484740784580072E-03 --2.0225509761594377E-03 --1.9966314127742844E-03 --1.9707153967604960E-03 --1.9448029465925730E-03 --1.9188940809093402E-03 --1.8929888180658017E-03 --1.8670871741289100E-03 --1.8411891507253840E-03 --1.8152947441894001E-03 --1.7894039612887892E-03 --1.7635168198304216E-03 --1.7376333382350159E-03 --1.7117535351658913E-03 --1.6858774277274191E-03 --1.6600050189537617E-03 --1.6341363047914113E-03 --1.6082712903046047E-03 --1.5824099930781346E-03 --1.5565524316477211E-03 --1.5306986247452606E-03 --1.5048485900919658E-03 --1.4790023323376538E-03 --1.4531598474008729E-03 --1.4273211387398831E-03 --1.4014862234477976E-03 --1.3756551200464616E-03 --1.3498278472272879E-03 --1.3240044230900180E-03 --1.2981848539888648E-03 --1.2723691360618922E-03 --1.2465572713653362E-03 --1.2207492764576750E-03 --1.1949451699444710E-03 --1.1691449704287933E-03 --1.1433486961536501E-03 --1.1175563550636100E-03 --1.0917679435274070E-03 --1.0659834622691829E-03 --1.0402029272567714E-03 --1.0144263573371424E-03 --9.8865377104823712E-04 --9.6288518658701615E-04 --9.3712061353358033E-04 --9.1136004895386673E-04 --8.8560349258616608E-04 --8.5985095915434872E-04 --8.3410246722225522E-04 --8.0835803537278143E-04 --7.8261768213634089E-04 --7.5688141878131664E-04 --7.3114924286460793E-04 --7.0542115311462495E-04 --6.7969716307380061E-04 --6.5397729135048782E-04 --6.2826155654931116E-04 --6.0254997725097282E-04 --5.7684256620305085E-04 --5.5113932170090839E-04 --5.2544024174014598E-04 --4.9974533848915208E-04 --4.7405463052078544E-04 --4.4836813645464277E-04 --4.2268587492765453E-04 --3.9700786003593852E-04 --3.7133409093678194E-04 --3.4566456501043484E-04 --3.1999929296553156E-04 --2.9433829337913967E-04 --2.6868158489572582E-04 --2.4302918610594304E-04 --2.1738111221052069E-04 --1.9173736350833025E-04 --1.6609793701579409E-04 --1.4046284185559625E-04 --1.1483209641333597E-04 --8.9205719324415622E-05 --6.3583729253772431E-05 --3.7966142396247661E-05 --1.2352960309383025E-05 -1.3255820330949283E-05 -3.8860192009087494E-05 -6.4460136499983398E-05 -9.0055635132748943E-05 -1.1564666926105000E-04 -1.4123322196974089E-04 -1.6681529026127986E-04 -1.9239287760411991E-04 -2.1796597807622220E-04 -2.4353457374040751E-04 -2.6909864589810578E-04 -2.9465817591382181E-04 -3.2021314631482545E-04 -3.4576355254470543E-04 -3.7130939806507532E-04 -3.9685067851052898E-04 -4.2238737639612838E-04 -4.4791947302074022E-04 -4.7344694973131381E-04 -4.9896978860846882E-04 -5.2448798347042361E-04 -5.5000153765927078E-04 -5.7551044828933989E-04 -6.0101469846615663E-04 -6.2651426948269484E-04 -6.5200914267432596E-04 -6.7749929980574514E-04 -7.0298473303253227E-04 -7.2846544541971259E-04 -7.5394143542531706E-04 -7.7941268694520531E-04 -8.0487918130344685E-04 -8.3034089979923344E-04 -8.5579782392915162E-04 -8.8124994420804873E-04 -9.0669726337912855E-04 -9.3213978111385352E-04 -9.5757748213822825E-04 -9.8301034765180891E-04 -1.0084383590292238E-03 -1.0338614978481898E-03 -1.0592797531190920E-03 -1.0846931269218715E-03 -1.1101016197887393E-03 -1.1355052176417744E-03 -1.1609039017704595E-03 -1.1862976534014044E-03 -1.2116864537339124E-03 -1.2370702902033195E-03 -1.2624491646023885E-03 -1.2878230786210999E-03 -1.3131920194267264E-03 -1.3385559680924677E-03 -1.3639149057956225E-03 -1.3892688138563019E-03 -1.4146176783904967E-03 -1.4399615001004585E-03 -1.4653002810414641E-03 -1.4906340099101517E-03 -1.5159626680530782E-03 -1.5412862367342552E-03 -1.5666046972090328E-03 -1.5919180343843011E-03 -1.6172262480356840E-03 -1.6425293407859843E-03 -1.6678273027114381E-03 -1.6931201149279673E-03 -1.7184077586075094E-03 -1.7436902153907168E-03 -1.7689674695423908E-03 -1.7942395193805043E-03 -1.8195063674556968E-03 -1.8447680054920167E-03 -1.8700244152229989E-03 -1.8952755780014521E-03 -1.9205214751632225E-03 -1.9457620899046291E-03 -1.9709974192199378E-03 -1.9962274659996674E-03 -2.0214522235320813E-03 -2.0466716736477551E-03 -2.0718857975936121E-03 -2.0970945768924499E-03 -2.1222979943535682E-03 -2.1474960454000930E-03 -2.1726887327226611E-03 -2.1978760511684901E-03 -2.2230579833732241E-03 -2.2482345108548562E-03 -2.2734056147906108E-03 -2.2985712770767566E-03 -2.3237314915467936E-03 -2.3488862610651956E-03 -2.3740355820930001E-03 -2.3991794378076439E-03 -2.4243178097262800E-03 -2.4494506789194581E-03 -2.4745780267847071E-03 -2.4996998456117475E-03 -2.5248161383708890E-03 -2.5499269029649373E-03 -2.5750321227573430E-03 -2.6001317787976339E-03 -2.6252258525605015E-03 -2.6503143259665597E-03 -2.6753971898250163E-03 -2.7004744461973352E-03 -2.7255460938099513E-03 -2.7506121171568822E-03 -2.7756724976097380E-03 -2.8007272164932173E-03 -2.8257762552132497E-03 -2.8508196029374765E-03 -2.8758572615607330E-03 -2.9008892310996705E-03 -2.9259154972057235E-03 -2.9509360412955038E-03 -2.9759508444464596E-03 -3.0009598874998892E-03 -3.0259631579800934E-03 -3.0509606577289079E-03 -3.0759523880957997E-03 -3.1009383356363040E-03 -3.1259184811513255E-03 -3.1508928057742708E-03 -3.1758612910055451E-03 -3.2008239233106664E-03 -3.2257807031245297E-03 -3.2507316318081121E-03 -3.2756766975567419E-03 -3.3006158818179245E-03 -3.3255491659179796E-03 -3.3504765310939273E-03 -3.3753979624229070E-03 -3.4003134594657162E-03 -3.4252230241775239E-03 -3.4501266461832571E-03 -3.4750243068876444E-03 -3.4999159875557552E-03 -3.5248016694696942E-03 -3.5496813367483439E-03 -3.5745549878188122E-03 -3.5994226249883719E-03 -3.6242842394362748E-03 -3.6491398127501480E-03 -3.6739893262063969E-03 -3.6988327610873051E-03 -3.7236701007068744E-03 -3.7485013422235208E-03 -3.7733264882192324E-03 -3.7981455313888320E-03 -3.8229584534179161E-03 -3.8477652355015084E-03 -3.8725658590884953E-03 -3.8973603070424864E-03 -3.9221485750394322E-03 -3.9469306655913056E-03 -3.9717065728725126E-03 -3.9964762789861446E-03 -4.0212397651564437E-03 -4.0459970128282558E-03 -4.0707480043889179E-03 -4.0954927340102702E-03 -4.1202312041663386E-03 -4.1449634105294045E-03 -4.1696893357525272E-03 -4.1944089610780663E-03 -4.2191222678172550E-03 -4.2438292378495189E-03 -4.2685298638334866E-03 -4.2932241482960213E-03 -4.3179120883908677E-03 -4.3425936672320349E-03 -4.3672688658789593E-03 -4.3919376657789687E-03 -4.4166000488401217E-03 -4.4412560061094985E-03 -4.4659055394403926E-03 -4.4905486470236729E-03 -4.5151853131356881E-03 -4.5398155192190263E-03 -4.5644392465593094E-03 -4.5890564764905425E-03 -4.6136671984487610E-03 -4.6382714142622324E-03 -4.6628691234713998E-03 -4.6874603111353840E-03 -4.7120449583871564E-03 -4.7366230464251586E-03 -4.7611945565481199E-03 -4.7857594767873419E-03 -4.8103178085762413E-03 -4.8348695524593997E-03 -4.8594146945336080E-03 -4.8839532156884488E-03 -4.9084850972386188E-03 -4.9330103209309058E-03 -4.9575288735887301E-03 -4.9820407552834270E-03 -5.0065459666188425E-03 -5.0310444954175994E-03 -5.0555363234005895E-03 -5.0800214320039202E-03 -5.1044998023528692E-03 -5.1289714196658797E-03 -5.1534362834896093E-03 -5.1778943953702658E-03 -5.2023457444769529E-03 -5.2267903122801300E-03 -5.2512280800523833E-03 -5.2756590289328633E-03 -5.3000831431555652E-03 -5.3245004214503211E-03 -5.3489108660459365E-03 -5.3733144675557993E-03 -5.3977112072431449E-03 -5.4221010662263694E-03 -5.4464840258798301E-03 -5.4708600697995716E-03 -5.4952291953333943E-03 -5.5195914047480804E-03 -5.5439466902418976E-03 -5.5682950335465692E-03 -5.5926364158915918E-03 -5.6169708184619551E-03 -5.6412982239903734E-03 -5.6656186285686198E-03 -5.6899320348759302E-03 -5.7142384366319883E-03 -5.7385378154772345E-03 -5.7628301523953126E-03 -5.7871154290753827E-03 -5.8113936283265060E-03 -5.8356647444748923E-03 -5.8599287793956890E-03 -5.8841857281013779E-03 -5.9084355734411028E-03 -5.9326782969921178E-03 -5.9569138800545270E-03 -5.9811423044622680E-03 -6.0053635630188864E-03 -6.0295776579010908E-03 -6.0537845857263160E-03 -6.0779843297855320E-03 -6.1021768714974523E-03 -6.1263621920754205E-03 -6.1505402730003302E-03 -6.1747111055322542E-03 -6.1988746917331127E-03 -6.2230310295851420E-03 -6.2471801031266285E-03 -6.2713218937671660E-03 -6.2954563827408213E-03 -6.3195835513596985E-03 -6.3437033893476973E-03 -6.3678158984344568E-03 -6.3919210777136472E-03 -6.4160189119929116E-03 -6.4401093825063377E-03 -6.4641924706618720E-03 -6.4882681580558741E-03 -6.5123364330396619E-03 -6.5363972964824551E-03 -6.5604507480855369E-03 -6.5844967739361092E-03 -6.6085353555492433E-03 -6.6325664743102980E-03 -6.6565901115067834E-03 -6.6806062540397211E-03 -6.7046149024667535E-03 -6.7286160575238023E-03 -6.7526097063877345E-03 -6.7765958302286773E-03 -6.8005744103776964E-03 -6.8245454283881665E-03 -6.8485088700764862E-03 -6.8724647349642102E-03 -6.8964130241123004E-03 -6.9203537262857717E-03 -6.9442868231177806E-03 -6.9682122960190163E-03 -6.9921301261948359E-03 -7.0160402981260537E-03 -7.0399428104981386E-03 -7.0638376650291410E-03 -7.0877248519229568E-03 -7.1116043527275942E-03 -7.1354761487967674E-03 -7.1593402215169646E-03 -7.1831965546460055E-03 -7.2070451456638243E-03 -7.2308859965141718E-03 -7.2547190989363545E-03 -7.2785444347631479E-03 -7.3023619853590845E-03 -7.3261717319308296E-03 -7.3499736573666395E-03 -7.3737677580124296E-03 -7.3975540363350649E-03 -7.4213324856419773E-03 -7.4451030877303315E-03 -7.4688658237337382E-03 -7.4926206750044431E-03 -7.5163676240735640E-03 -7.5401066658944763E-03 -7.5638378029837172E-03 -7.5875610300909163E-03 -7.6112763291981455E-03 -7.6349836812953488E-03 -7.6586830681762592E-03 -7.6823744725310842E-03 -7.7060578875900740E-03 -7.7297333149830083E-03 -7.7534007506005771E-03 -7.7770601777049243E-03 -7.8007115779235338E-03 -7.8243549326980893E-03 -7.8479902238051558E-03 -7.8716174429263805E-03 -7.8952365919622691E-03 -7.9188476683279344E-03 -7.9424506556282550E-03 -7.9660455351228138E-03 -7.9896322884258787E-03 -8.0132108975323885E-03 -8.0367813527185625E-03 -8.0603436552913275E-03 -8.0838978036275079E-03 -8.1074437823733213E-03 -8.1309815729956655E-03 -8.1545111570671350E-03 -8.1780325163154973E-03 -8.2015456394755690E-03 -8.2250505273836951E-03 -8.2485471793682773E-03 -8.2720355812690438E-03 -8.2955157147288228E-03 -8.3189875612723167E-03 -8.3424511023509375E-03 -8.3659063252646843E-03 -8.3893532305309108E-03 -8.4127918184966465E-03 -8.4362220761721139E-03 -8.4596439850695825E-03 -8.4830575266064030E-03 -8.5064626821177540E-03 -8.5298594375861105E-03 -8.5532477928874570E-03 -8.5766277491035256E-03 -8.5999992946018365E-03 -8.6233624108814633E-03 -8.6467170794087417E-03 -8.6700632816986076E-03 -8.6934010027363701E-03 -8.7167302413389495E-03 -8.7400509988843356E-03 -8.7633632651404284E-03 -8.7866670217279369E-03 -8.8099622501749773E-03 -8.8332489321497829E-03 -8.8565270518441014E-03 -8.8797966068754862E-03 -8.9030575987992938E-03 -8.9263100187878548E-03 -8.9495538485993547E-03 -8.9727890698178495E-03 -8.9960156644294919E-03 -9.0192336161899495E-03 -9.0424429212514843E-03 -9.0656435809479286E-03 -9.0888355879146180E-03 -9.1120189245911271E-03 -9.1351935728019602E-03 -9.1583595142536722E-03 -9.1815167318218607E-03 -9.2046652203305619E-03 -9.2278049813569307E-03 -9.2509360090865696E-03 -9.2740582864097483E-03 -9.2971717952350132E-03 -9.3202765172864105E-03 -9.3433724350040475E-03 -9.3664595417899347E-03 -9.3895378391892284E-03 -9.4126073227230201E-03 -9.4356679756775180E-03 -9.4587197798877958E-03 -9.4817627170517543E-03 -9.5047967692793202E-03 -9.5278219286276129E-03 -9.5508381967372245E-03 -9.5738455705476379E-03 -9.5968440338352577E-03 -9.6198335682813781E-03 -9.6428141555974390E-03 -9.6657857777527455E-03 -9.6887484253310886E-03 -9.7117020996332036E-03 -9.7346467987275385E-03 -9.7575825072658637E-03 -9.7805092070277974E-03 -9.8034268798858348E-03 -9.8263355078759447E-03 -9.8492350801210743E-03 -9.8721255971559764E-03 -9.8950070577472557E-03 -9.9178794477654004E-03 -9.9407427493428263E-03 -9.9635969441427604E-03 -9.9864420134955292E-03 -1.0009277945277182E-02 -1.0032104741133887E-02 -1.0054922401860823E-02 -1.0077730912215447E-02 -1.0100530250957140E-02 -1.0123320400124437E-02 -1.0146101345138811E-02 -1.0168873075033528E-02 -1.0191635588416145E-02 -1.0214388884126513E-02 -1.0237132949062464E-02 -1.0259867764145128E-02 -1.0282593311502653E-02 -1.0305309574922162E-02 -1.0328016541249692E-02 -1.0350714208199205E-02 -1.0373402575139169E-02 -1.0396081631326555E-02 -1.0418751359393175E-02 -1.0441411741614231E-02 -1.0464062759849764E-02 -1.0486704398673215E-02 -1.0509336656280156E-02 -1.0531959534410299E-02 -1.0554573023359241E-02 -1.0577177103734989E-02 -1.0599771756897297E-02 -1.0622356966580182E-02 -1.0644932718396694E-02 -1.0667499008342955E-02 -1.0690055836357243E-02 -1.0712603194018578E-02 -1.0735141063763533E-02 -1.0757669428032959E-02 -1.0780188270655853E-02 -1.0802697576672111E-02 -1.0825197339871244E-02 -1.0847687558621241E-02 -1.0870168225689224E-02 -1.0892639325879829E-02 -1.0915100842938492E-02 -1.0937552758792513E-02 -1.0959995055815261E-02 -1.0982427727998696E-02 -1.1004850777369242E-02 -1.1027264199063420E-02 -1.1049667975296705E-02 -1.1072062087075328E-02 -1.1094446516319568E-02 -1.1116821245789324E-02 -1.1139186268562588E-02 -1.1161541586998239E-02 -1.1183887198465393E-02 -1.1206223087557329E-02 -1.1228549236648957E-02 -1.1250865625661939E-02 -1.1273172233826281E-02 -1.1295469052094546E-02 -1.1317756085045656E-02 -1.1340033332750328E-02 -1.1362300778496310E-02 -1.1384558402408866E-02 -1.1406806186288171E-02 -1.1429044113022440E-02 -1.1451272172600188E-02 -1.1473490365659447E-02 -1.1495698690687556E-02 -1.1517897133280271E-02 -1.1540085675611147E-02 -1.1562264299957390E-02 -1.1584432988720628E-02 -1.1606591730159301E-02 -1.1628740523976144E-02 -1.1650879369299528E-02 -1.1673008254396728E-02 -1.1695127163545298E-02 -1.1717236078110689E-02 -1.1739334976685495E-02 -1.1761423844508527E-02 -1.1783502684179617E-02 -1.1805571499004436E-02 -1.1827630276411536E-02 -1.1849678996434515E-02 -1.1871717640348819E-02 -1.1893746191018658E-02 -1.1915764634902151E-02 -1.1937772970393791E-02 -1.1959771197512887E-02 -1.1981759306328516E-02 -1.2003737280813956E-02 -1.2025705103693789E-02 -1.2047662755832860E-02 -1.2069610220964859E-02 -1.2091547496704963E-02 -1.2113474584014853E-02 -1.2135391474212408E-02 -1.2157298150983868E-02 -1.2179194597309836E-02 -1.2201080795132853E-02 -1.2222956728405836E-02 -1.2244822394252754E-02 -1.2266677794363318E-02 -1.2288522919937060E-02 -1.2310357751461949E-02 -1.2332182270403124E-02 -1.2353996462242495E-02 -1.2375800313965379E-02 -1.2397593819435435E-02 -1.2419376975835892E-02 -1.2441149775594816E-02 -1.2462912204845699E-02 -1.2484664248589300E-02 -1.2506405889247420E-02 -1.2528137109533237E-02 -1.2549857902543222E-02 -1.2571568268062966E-02 -1.2593268200413489E-02 -1.2614957684392835E-02 -1.2636636703625853E-02 -1.2658305240545778E-02 -1.2679963277790115E-02 -1.2701610807785823E-02 -1.2723247831179492E-02 -1.2744874344149990E-02 -1.2766490332337014E-02 -1.2788095779526663E-02 -1.2809690666668405E-02 -1.2831274973993461E-02 -1.2852848693405543E-02 -1.2874411829480240E-02 -1.2895964381424690E-02 -1.2917506330743308E-02 -1.2939037656197071E-02 -1.2960558341119156E-02 -1.2982068371411070E-02 -1.3003567738937275E-02 -1.3025056443890196E-02 -1.3046534483673187E-02 -1.3068001842257052E-02 -1.3089458500503600E-02 -1.3110904441795239E-02 -1.3132339651316743E-02 -1.3153764119523632E-02 -1.3175177846401900E-02 -1.3196580830384037E-02 -1.3217973056361411E-02 -1.3239354504919389E-02 -1.3260725159435391E-02 -1.3282085005801986E-02 -1.3303434033240313E-02 -1.3324772238699717E-02 -1.3346099619242954E-02 -1.3367416164683173E-02 -1.3388721861547765E-02 -1.3410016692385550E-02 -1.3431300635165996E-02 -1.3452573673691176E-02 -1.3473835811008686E-02 -1.3495087052207134E-02 -1.3516327385082438E-02 -1.3537556787641413E-02 -1.3558775240927202E-02 -1.3579982730687737E-02 -1.3601179245266645E-02 -1.3622364782357383E-02 -1.3643539341432882E-02 -1.3664702912239783E-02 -1.3685855477343949E-02 -1.3706997019555028E-02 -1.3728127522482836E-02 -1.3749246971805792E-02 -1.3770355364427340E-02 -1.3791452700767426E-02 -1.3812538971940833E-02 -1.3833614160188456E-02 -1.3854678248211566E-02 -1.3875731220788832E-02 -1.3896773064263415E-02 -1.3917803774528264E-02 -1.3938823351694937E-02 -1.3959831788189884E-02 -1.3980829066959298E-02 -1.4001815170641306E-02 -1.4022790082805214E-02 -1.4043753788146020E-02 -1.4064706281310922E-02 -1.4085647562883604E-02 -1.4106577626666453E-02 -1.4127496455535677E-02 -1.4148404031886070E-02 -1.4169300340348861E-02 -1.4190185366693678E-02 -1.4211059104474432E-02 -1.4231921553335861E-02 -1.4252772708344286E-02 -1.4273612554725547E-02 -1.4294441076312135E-02 -1.4315258255898649E-02 -1.4336064076246626E-02 -1.4356858528585771E-02 -1.4377641612731785E-02 -1.4398413325325612E-02 -1.4419173653283443E-02 -1.4439922581601282E-02 -1.4460660092991793E-02 -1.4481386169249858E-02 -1.4502100800733497E-02 -1.4522803989020295E-02 -1.4543495732722251E-02 -1.4564176016889269E-02 -1.4584844823568843E-02 -1.4605502135787804E-02 -1.4626147937288385E-02 -1.4646782218145462E-02 -1.4667404979158388E-02 -1.4688016219433270E-02 -1.4708615924739430E-02 -1.4729204076893180E-02 -1.4749780659563177E-02 -1.4770345657989948E-02 -1.4790899061737434E-02 -1.4811440869847212E-02 -1.4831971080801594E-02 -1.4852489681023779E-02 -1.4872996652166499E-02 -1.4893491978641187E-02 -1.4913975647853366E-02 -1.4934447649238784E-02 -1.4954907977743938E-02 -1.4975356628750268E-02 -1.4995793592505535E-02 -1.5016218856483901E-02 -1.5036632405841703E-02 -1.5057034222539458E-02 -1.5077424291378694E-02 -1.5097802609197878E-02 -1.5118169175211275E-02 -1.5138523981416586E-02 -1.5158867014812533E-02 -1.5179198260088842E-02 -1.5199517697935757E-02 -1.5219825311317159E-02 -1.5240121097329621E-02 -1.5260405057238035E-02 -1.5280677183855788E-02 -1.5300937462462322E-02 -1.5321185877124666E-02 -1.5341422409660374E-02 -1.5361647043515449E-02 -1.5381859776004370E-02 -1.5402060610117225E-02 -1.5422249539233246E-02 -1.5442426545665085E-02 -1.5462591611630298E-02 -1.5482744720963736E-02 -1.5502885858821480E-02 -1.5523015020193251E-02 -1.5543132205525055E-02 -1.5563237409460915E-02 -1.5583330617937657E-02 -1.5603411815656306E-02 -1.5623480985092223E-02 -1.5643538108914633E-02 -1.5663583180645733E-02 -1.5683616201727407E-02 -1.5703637167911268E-02 -1.5723646063607009E-02 -1.5743642872130363E-02 -1.5763627577924613E-02 -1.5783600166211175E-02 -1.5803560630229401E-02 -1.5823508970806404E-02 -1.5843445184246987E-02 -1.5863369254626888E-02 -1.5883281164321136E-02 -1.5903180897304390E-02 -1.5923068438517315E-02 -1.5942943780610869E-02 -1.5962806925656121E-02 -1.5982657871964904E-02 -1.6002496603247793E-02 -1.6022323100376001E-02 -1.6042137346700128E-02 -1.6061939327175454E-02 -1.6081729033639729E-02 -1.6101506468784717E-02 -1.6121271632899344E-02 -1.6141024511102855E-02 -1.6160765084318105E-02 -1.6180493334685398E-02 -1.6200209245342195E-02 -1.6219912806335821E-02 -1.6239604021907442E-02 -1.6259282895014045E-02 -1.6278949410186747E-02 -1.6298603545281124E-02 -1.6318245283708066E-02 -1.6337874614496900E-02 -1.6357491529081794E-02 -1.6377096024754387E-02 -1.6396688098727952E-02 -1.6416267739415402E-02 -1.6435834930892904E-02 -1.6455389657579408E-02 -1.6474931904379757E-02 -1.6494461659040664E-02 -1.6513978919471609E-02 -1.6533483685126145E-02 -1.6552975946735580E-02 -1.6572455689413713E-02 -1.6591922897700225E-02 -1.6611377555323201E-02 -1.6630819648156131E-02 -1.6650249172849407E-02 -1.6669666128925162E-02 -1.6689070509347134E-02 -1.6708462301609599E-02 -1.6727841490746308E-02 -1.6747208056736820E-02 -1.6766561981511201E-02 -1.6785903264153058E-02 -1.6805231910192474E-02 -1.6824547913534715E-02 -1.6843851255591177E-02 -1.6863141918305357E-02 -1.6882419886958634E-02 -1.6901685148387299E-02 -1.6920937697949303E-02 -1.6940177535363178E-02 -1.6959404654402176E-02 -1.6978619040546136E-02 -1.6997820678658179E-02 -1.7017009553573801E-02 -1.7036185650802449E-02 -1.7055348964455035E-02 -1.7074499494483239E-02 -1.7093637235857499E-02 -1.7112762174383352E-02 -1.7131874294898587E-02 -1.7150973582187295E-02 -1.7170060021443518E-02 -1.7189133605834423E-02 -1.7208194335571178E-02 -1.7227242206478279E-02 -1.7246277203473118E-02 -1.7265299310139828E-02 -1.7284308511725355E-02 -1.7303304794430339E-02 -1.7322288151530429E-02 -1.7341258584375564E-02 -1.7360216090408741E-02 -1.7379160653506701E-02 -1.7398092255362985E-02 -1.7417010882093745E-02 -1.7435916522369990E-02 -1.7454809168415575E-02 -1.7473688817656347E-02 -1.7492555465907316E-02 -1.7511409100517756E-02 -1.7530249706667868E-02 -1.7549077270070084E-02 -1.7567891776862167E-02 -1.7586693217473779E-02 -1.7605481590553917E-02 -1.7624256893988118E-02 -1.7643019116172692E-02 -1.7661768242191501E-02 -1.7680504256912036E-02 -1.7699227145011348E-02 -1.7717936895330501E-02 -1.7736633507223990E-02 -1.7755316980381172E-02 -1.7773987304640963E-02 -1.7792644465281386E-02 -1.7811288446370994E-02 -1.7829919230538002E-02 -1.7848536804735648E-02 -1.7867141170686662E-02 -1.7885732331876059E-02 -1.7904310277810493E-02 -1.7922874989644684E-02 -1.7941426450569290E-02 -1.7959964647155390E-02 -1.7978489568358121E-02 -1.7997001212487748E-02 -1.8015499579839139E-02 -1.8033984661070614E-02 -1.8052456439360234E-02 -1.8070914899058061E-02 -1.8089360027319132E-02 -1.8107791813103145E-02 -1.8126210254175327E-02 -1.8144615351182725E-02 -1.8163007095506840E-02 -1.8181385469235745E-02 -1.8199750455597439E-02 -1.8218102041991993E-02 -1.8236440217415394E-02 -1.8254764978253249E-02 -1.8273076324355788E-02 -1.8291374249338140E-02 -1.8309658738717000E-02 -1.8327929777486270E-02 -1.8346187350694355E-02 -1.8364431444145842E-02 -1.8382662052190846E-02 -1.8400879174590313E-02 -1.8419082807150877E-02 -1.8437272938902426E-02 -1.8455449557173188E-02 -1.8473612644213488E-02 -1.8491762181502915E-02 -1.8509898163148651E-02 -1.8528020593670588E-02 -1.8546129471269619E-02 -1.8564224779624841E-02 -1.8582306501186644E-02 -1.8600374622908297E-02 -1.8618429133698142E-02 -1.8636470026558934E-02 -1.8654497298854801E-02 -1.8672510946245308E-02 -1.8690510958847172E-02 -1.8708497325174565E-02 -1.8726470028345876E-02 -1.8744429048884310E-02 -1.8762374377633520E-02 -1.8780306019686756E-02 -1.8798223976895793E-02 -1.8816128234596274E-02 -1.8834018774497020E-02 -1.8851895582773791E-02 -1.8869758648670777E-02 -1.8887607963764833E-02 -1.8905443523697756E-02 -1.8923265323732702E-02 -1.8941073354992968E-02 -1.8958867607102414E-02 -1.8976648066644310E-02 -1.8994414717542395E-02 -1.9012167548164881E-02 -1.9029906557496434E-02 -1.9047631744754809E-02 -1.9065343100178100E-02 -1.9083040610132929E-02 -1.9100724259898793E-02 -1.9118394033539397E-02 -1.9136049919153041E-02 -1.9153691917548649E-02 -1.9171320030796132E-02 -1.9188934249451037E-02 -1.9206534557645861E-02 -1.9224120940253615E-02 -1.9241693383337099E-02 -1.9259251875533921E-02 -1.9276796415759367E-02 -1.9294327004881606E-02 -1.9311843634044049E-02 -1.9329346287345797E-02 -1.9346834950157432E-02 -1.9364309610577123E-02 -1.9381770258060517E-02 -1.9399216887910277E-02 -1.9416649497260567E-02 -1.9434068079351722E-02 -1.9451472623770838E-02 -1.9468863118628180E-02 -1.9486239548688392E-02 -1.9503601899466178E-02 -1.9520950166028176E-02 -1.9538284347672158E-02 -1.9555604439396593E-02 -1.9572910430978210E-02 -1.9590202310423840E-02 -1.9607480060892659E-02 -1.9624743665730145E-02 -1.9641993120768742E-02 -1.9659228429175713E-02 -1.9676449587351725E-02 -1.9693656580965592E-02 -1.9710849395265708E-02 -1.9728028017785247E-02 -1.9745192437034556E-02 -1.9762342646664981E-02 -1.9779478644278672E-02 -1.9796600424490680E-02 -1.9813707975623106E-02 -1.9830801285188871E-02 -1.9847880340438814E-02 -1.9864945128776398E-02 -1.9881995643316160E-02 -1.9899031882861105E-02 -1.9916053843689236E-02 -1.9933061514648919E-02 -1.9950054883209105E-02 -1.9967033935636484E-02 -1.9983998657773470E-02 -2.0000949041626685E-02 -2.0017885087135409E-02 -2.0034806792404578E-02 -2.0051714147126476E-02 -2.0068607138901524E-02 -2.0085485752874693E-02 -2.0102349972729319E-02 -2.0119199789429734E-02 -2.0136035206112290E-02 -2.0152856224183700E-02 -2.0169662831266782E-02 -2.0186455011010965E-02 -2.0203232749418619E-02 -2.0219996034446144E-02 -2.0236744857571300E-02 -2.0253479217807888E-02 -2.0270199113857596E-02 -2.0286904536026339E-02 -2.0303595471301318E-02 -2.0320271906950252E-02 -2.0336933830549877E-02 -2.0353581232124704E-02 -2.0370214108687966E-02 -2.0386832457903799E-02 -2.0403436272175075E-02 -2.0420025541106047E-02 -2.0436600251720245E-02 -2.0453160387539783E-02 -2.0469705935420284E-02 -2.0486236895965043E-02 -2.0502753272204303E-02 -2.0519255056397085E-02 -2.0535742233518534E-02 -2.0552214789445543E-02 -2.0568672711902831E-02 -2.0585115990264982E-02 -2.0601544621408726E-02 -2.0617958604338450E-02 -2.0634357933016080E-02 -2.0650742596982508E-02 -2.0667112583988529E-02 -2.0683467877968213E-02 -2.0699808464187893E-02 -2.0716134340929580E-02 -2.0732445511699969E-02 -2.0748741971390375E-02 -2.0765023705145658E-02 -2.0781290698521648E-02 -2.0797542939947383E-02 -2.0813780419090482E-02 -2.0830003132193509E-02 -2.0846211079043539E-02 -2.0862404253840564E-02 -2.0878582642579243E-02 -2.0894746231369932E-02 -2.0910895009469955E-02 -2.0927028967329061E-02 -2.0943148100599905E-02 -2.0959252408649161E-02 -2.0975341886554064E-02 -2.0991416521102538E-02 -2.1007476298475169E-02 -2.1023521206605701E-02 -2.1039551234326034E-02 -2.1055566376479432E-02 -2.1071566633498236E-02 -2.1087552002520587E-02 -2.1103522471956498E-02 -2.1119478028887206E-02 -2.1135418660438159E-02 -2.1151344353932490E-02 -2.1167255102522282E-02 -2.1183150906360727E-02 -2.1199031763620570E-02 -2.1214897664561898E-02 -2.1230748597643786E-02 -2.1246584549566856E-02 -2.1262405506080790E-02 -2.1278211458444763E-02 -2.1294002406499483E-02 -2.1309778349217146E-02 -2.1325539278454837E-02 -2.1341285183934341E-02 -2.1357016052850817E-02 -2.1372731870493232E-02 -2.1388432626975654E-02 -2.1404118322278450E-02 -2.1419788956107712E-02 -2.1435444519457884E-02 -2.1451085000134609E-02 -2.1466710386336019E-02 -2.1482320666658707E-02 -2.1497915832203753E-02 -2.1513495880698917E-02 -2.1529060810216192E-02 -2.1544610612777699E-02 -2.1560145277437329E-02 -2.1575664791906056E-02 -2.1591169142202812E-02 -2.1606658317610220E-02 -2.1622132319375723E-02 -2.1637591150424074E-02 -2.1653034802676975E-02 -2.1668463261122047E-02 -2.1683876511997751E-02 -2.1699274543795527E-02 -2.1714657347013736E-02 -2.1730024920678118E-02 -2.1745377265868390E-02 -2.1760714375864909E-02 -2.1776036237572929E-02 -2.1791342838154176E-02 -2.1806634165729716E-02 -2.1821910209892874E-02 -2.1837170968858892E-02 -2.1852416443966908E-02 -2.1867646629614323E-02 -2.1882861512869677E-02 -2.1898061080806261E-02 -2.1913245321509539E-02 -2.1928414224177444E-02 -2.1943567786182363E-02 -2.1958706008986795E-02 -2.1973828887963110E-02 -2.1988936410144572E-02 -2.2004028562498328E-02 -2.2019105334014046E-02 -2.2034166714725273E-02 -2.2049212701600103E-02 -2.2064243296210265E-02 -2.2079258494458586E-02 -2.2094258282082734E-02 -2.2109242644713447E-02 -2.2124211572732852E-02 -2.2139165058218585E-02 -2.2154103096573331E-02 -2.2169025686084476E-02 -2.2183932823073078E-02 -2.2198824499092117E-02 -2.2213700704404447E-02 -2.2228561425006108E-02 -2.2243406645422327E-02 -2.2258236359559740E-02 -2.2273050571857092E-02 -2.2287849283124155E-02 -2.2302632481358851E-02 -2.2317400152393502E-02 -2.2332152284681901E-02 -2.2346888868211928E-02 -2.2361609897318797E-02 -2.2376315372618281E-02 -2.2391005292778581E-02 -2.2405679646490123E-02 -2.2420338420116079E-02 -2.2434981603023929E-02 -2.2449609186756380E-02 -2.2464221165152017E-02 -2.2478817536286857E-02 -2.2493398297686002E-02 -2.2507963441277177E-02 -2.2522512957022844E-02 -2.2537046833776393E-02 -2.2551565059375171E-02 -2.2566067625002861E-02 -2.2580554530212515E-02 -2.2595025774828633E-02 -2.2609481351238300E-02 -2.2623921248482840E-02 -2.2638345455842316E-02 -2.2652753962901857E-02 -2.2667146761201219E-02 -2.2681523848636542E-02 -2.2695885223820711E-02 -2.2710230879334461E-02 -2.2724560804219852E-02 -2.2738874988397977E-02 -2.2753173423218368E-02 -2.2767456100897789E-02 -2.2781723016924833E-02 -2.2795974167585359E-02 -2.2810209547675809E-02 -2.2824429150835723E-02 -2.2838632967980891E-02 -2.2852820984606163E-02 -2.2866993187752063E-02 -2.2881149577420129E-02 -2.2895290157920401E-02 -2.2909414923911568E-02 -2.2923523860539707E-02 -2.2937616954822524E-02 -2.2951694199797489E-02 -2.2965755589574310E-02 -2.2979801118966883E-02 -2.2993830783133606E-02 -2.3007844577426620E-02 -2.3021842497441353E-02 -2.3035824536385873E-02 -2.3049790679003257E-02 -2.3063740909382714E-02 -2.3077675225170069E-02 -2.3091593632418216E-02 -2.3105496129623961E-02 -2.3119382702627984E-02 -2.3133253337262495E-02 -2.3147108024886311E-02 -2.3160946758699893E-02 -2.3174769535372345E-02 -2.3188576354372884E-02 -2.3202367211780744E-02 -2.3216142096215458E-02 -2.3229900995809086E-02 -2.3243643901738015E-02 -2.3257370806497025E-02 -2.3271081705750707E-02 -2.3284776598481657E-02 -2.3298455481670803E-02 -2.3312118346178735E-02 -2.3325765181727250E-02 -2.3339395977503199E-02 -2.3353010722541191E-02 -2.3366609411125686E-02 -2.3380192044648900E-02 -2.3393758623103583E-02 -2.3407309139280484E-02 -2.3420843584011721E-02 -2.3434361944997498E-02 -2.3447864207918345E-02 -2.3461350365017706E-02 -2.3474820420127007E-02 -2.3488274375817821E-02 -2.3501712222322411E-02 -2.3515133946148948E-02 -2.3528539536984451E-02 -2.3541928987276143E-02 -2.3555302291661383E-02 -2.3568659449599589E-02 -2.3582000460241701E-02 -2.3595325316007366E-02 -2.3608634006486003E-02 -2.3621926520987737E-02 -2.3635202848523575E-02 -2.3648462980918831E-02 -2.3661706918600752E-02 -2.3674934662839670E-02 -2.3688146207507879E-02 -2.3701341542424949E-02 -2.3714520657842741E-02 -2.3727683544696503E-02 -2.3740830195212281E-02 -2.3753960606642976E-02 -2.3767074777272312E-02 -2.3780172702103690E-02 -2.3793254373787091E-02 -2.3806319783350682E-02 -2.3819368918879518E-02 -2.3832401770110988E-02 -2.3845418337551015E-02 -2.3858418624919369E-02 -2.3871402627236391E-02 -2.3884370331514738E-02 -2.3897321725916722E-02 -2.3910256802162917E-02 -2.3923175553277876E-02 -2.3936077977955612E-02 -2.3948964077265308E-02 -2.3961833846992749E-02 -2.3974687276636767E-02 -2.3987524355528853E-02 -2.4000345073646574E-02 -2.4013149421843585E-02 -2.4025937398589211E-02 -2.4038709006721785E-02 -2.4051464243792793E-02 -2.4064203099149816E-02 -2.4076925561710795E-02 -2.4089631621558583E-02 -2.4102321269537291E-02 -2.4114994502992822E-02 -2.4127651324179624E-02 -2.4140291731799966E-02 -2.4152915717208678E-02 -2.4165523270643561E-02 -2.4178114380918703E-02 -2.4190689036686062E-02 -2.4203247234471814E-02 -2.4215788978508835E-02 -2.4228314269340211E-02 -2.4240823096955997E-02 -2.4253315449807598E-02 -2.4265791317747108E-02 -2.4278250691435094E-02 -2.4290693566574834E-02 -2.4303119945236623E-02 -2.4315529827461709E-02 -2.4327923204763850E-02 -2.4340300066902222E-02 -2.4352660404855172E-02 -2.4365004210408776E-02 -2.4377331478605116E-02 -2.4389642209795261E-02 -2.4401936403318412E-02 -2.4414214051470592E-02 -2.4426475144516350E-02 -2.4438719673204615E-02 -2.4450947628695367E-02 -2.4463159005557657E-02 -2.4475353805616436E-02 -2.4487532030068159E-02 -2.4499693670251704E-02 -2.4511838713826731E-02 -2.4523967152324817E-02 -2.4536078981322637E-02 -2.4548174196688585E-02 -2.4560252794579556E-02 -2.4572314771137319E-02 -2.4584360121937373E-02 -2.4596388842208872E-02 -2.4608400924786177E-02 -2.4620396359284914E-02 -2.4632375137053009E-02 -2.4644337256797936E-02 -2.4656282718635091E-02 -2.4668211518797563E-02 -2.4680123650910407E-02 -2.4692019106455066E-02 -2.4703897873254204E-02 -2.4715759941121667E-02 -2.4727605311750261E-02 -2.4739433990087899E-02 -2.4751245972618442E-02 -2.4763041248548133E-02 -2.4774819807704178E-02 -2.4786581641872842E-02 -2.4798326743935332E-02 -2.4810055112369285E-02 -2.4821766747864286E-02 -2.4833461647809429E-02 -2.4845139805923667E-02 -2.4856801214438323E-02 -2.4868445861669027E-02 -2.4880073736332255E-02 -2.4891684837776082E-02 -2.4903279171024157E-02 -2.4914856734948365E-02 -2.4926417519522761E-02 -2.4937961514349780E-02 -2.4949488710301136E-02 -2.4960999099112743E-02 -2.4972492679732661E-02 -2.4983969456175193E-02 -2.4995429427834025E-02 -2.5006872585300374E-02 -2.5018298918367196E-02 -2.5029708417703380E-02 -2.5041101074624740E-02 -2.5052476887386186E-02 -2.5063835860579562E-02 -2.5075177994337988E-02 -2.5086503277337871E-02 -2.5097811697365184E-02 -2.5109103248258786E-02 -2.5120377926585221E-02 -2.5131635729946544E-02 -2.5142876657152029E-02 -2.5154100705555918E-02 -2.5165307867574659E-02 -2.5176498134768393E-02 -2.5187671500134332E-02 -2.5198827957551521E-02 -2.5209967503514299E-02 -2.5221090138492830E-02 -2.5232195861745212E-02 -2.5243284665825826E-02 -2.5254356541623221E-02 -2.5265411482199050E-02 -2.5276449482262795E-02 -2.5287470537572611E-02 -2.5298474645890131E-02 -2.5309461805026301E-02 -2.5320432011701505E-02 -2.5331385262078142E-02 -2.5342321548712361E-02 -2.5353240860655255E-02 -2.5364143190131357E-02 -2.5375028538037719E-02 -2.5385896906004554E-02 -2.5396748290387249E-02 -2.5407582684988030E-02 -2.5418400082041478E-02 -2.5429200471832301E-02 -2.5439983847240229E-02 -2.5450750210595573E-02 -2.5461499565446508E-02 -2.5472231906134960E-02 -2.5482947221326421E-02 -2.5493645502178960E-02 -2.5504326744044244E-02 -2.5514990943419222E-02 -2.5525638100340486E-02 -2.5536268215556362E-02 -2.5546881284744884E-02 -2.5557477299511022E-02 -2.5568056251466326E-02 -2.5578618132480597E-02 -2.5589162935755479E-02 -2.5599690662634188E-02 -2.5610201317338287E-02 -2.5620694897483580E-02 -2.5631171393833859E-02 -2.5641630797373333E-02 -2.5652073100591467E-02 -2.5662498296920092E-02 -2.5672906385625791E-02 -2.5683297368857917E-02 -2.5693671245354290E-02 -2.5704028009258601E-02 -2.5714367653827959E-02 -2.5724690170207589E-02 -2.5734995549627306E-02 -2.5745283790259525E-02 -2.5755554894829401E-02 -2.5765808862889386E-02 -2.5776045688347661E-02 -2.5786265364382041E-02 -2.5796467883333809E-02 -2.5806653237580815E-02 -2.5816821424745624E-02 -2.5826972446925757E-02 -2.5837106304084145E-02 -2.5847222991014544E-02 -2.5857322501395968E-02 -2.5867404826192628E-02 -2.5877469955512957E-02 -2.5887517886851594E-02 -2.5897548625849535E-02 -2.5907562175029632E-02 -2.5917558526301100E-02 -2.5927537669835802E-02 -2.5937499598075495E-02 -2.5947444304776947E-02 -2.5957371787745747E-02 -2.5967282050536694E-02 -2.5977175094751444E-02 -2.5987050912401468E-02 -2.5996909493414842E-02 -2.6006750831910581E-02 -2.6016574924968752E-02 -2.6026381770566237E-02 -2.6036171368224982E-02 -2.6045943716951323E-02 -2.6055698812079774E-02 -2.6065436647678169E-02 -2.6075157217071637E-02 -2.6084860512919888E-02 -2.6094546530930927E-02 -2.6104215274267064E-02 -2.6113866745885290E-02 -2.6123500939173528E-02 -2.6133117843423665E-02 -2.6142717452237032E-02 -2.6152299764294069E-02 -2.6161864778275697E-02 -2.6171412491931785E-02 -2.6180942902722125E-02 -2.6190456007067209E-02 -2.6199951800765311E-02 -2.6209430278427204E-02 -2.6218891432873051E-02 -2.6228335258309737E-02 -2.6237761755557181E-02 -2.6247170926940278E-02 -2.6256562770837662E-02 -2.6265937282653164E-02 -2.6275294455932852E-02 -2.6284634280696009E-02 -2.6293956748440445E-02 -2.6303261861605851E-02 -2.6312549626238205E-02 -2.6321820041478882E-02 -2.6331073099779594E-02 -2.6340308793794492E-02 -2.6349527117415412E-02 -2.6358728065262477E-02 -2.6367911636124574E-02 -2.6377077830708535E-02 -2.6386226647821875E-02 -2.6395358083885136E-02 -2.6404472134439704E-02 -2.6413568792510278E-02 -2.6422648051149765E-02 -2.6431709909663363E-02 -2.6440754371155943E-02 -2.6449781434897433E-02 -2.6458791093865307E-02 -2.6467783341058839E-02 -2.6476758172227204E-02 -2.6485715584030019E-02 -2.6494655574966532E-02 -2.6503578144998985E-02 -2.6512483293073614E-02 -2.6521371015907385E-02 -2.6530241309557414E-02 -2.6539094167732605E-02 -2.6547929583418065E-02 -2.6556747553927548E-02 -2.6565548081034843E-02 -2.6574331165457137E-02 -2.6583096804404686E-02 -2.6591844994024203E-02 -2.6600575726560195E-02 -2.6609288992458780E-02 -2.6617984789229641E-02 -2.6626663123794535E-02 -2.6635324000597434E-02 -2.6643967412482261E-02 -2.6652593349931624E-02 -2.6661201807318787E-02 -2.6669792781591574E-02 -2.6678366271076105E-02 -2.6686922276397157E-02 -2.6695460797828800E-02 -2.6703981832772006E-02 -2.6712485377603248E-02 -2.6720971426359295E-02 -2.6729439971105169E-02 -2.6737891007634774E-02 -2.6746324540289544E-02 -2.6754740573263047E-02 -2.6763139101910395E-02 -2.6771520118050771E-02 -2.6779883616170747E-02 -2.6788229593694170E-02 -2.6796558049096402E-02 -2.6804868983540182E-02 -2.6813162398068038E-02 -2.6821438288024517E-02 -2.6829696645741124E-02 -2.6837937466333405E-02 -2.6846160748900956E-02 -2.6854366492686816E-02 -2.6862554696302214E-02 -2.6870725358202834E-02 -2.6878878476866125E-02 -2.6887014050761177E-02 -2.6895132075999521E-02 -2.6903232544356788E-02 -2.6911315449021020E-02 -2.6919380793210615E-02 -2.6927428583102313E-02 -2.6935458817600805E-02 -2.6943471489032457E-02 -2.6951466590352312E-02 -2.6959444116602806E-02 -2.6967404064064001E-02 -2.6975346435737829E-02 -2.6983271237356284E-02 -2.6991178467686040E-02 -2.6999068117353378E-02 -2.7006940178392697E-02 -2.7014794648810150E-02 -2.7022631527950178E-02 -2.7030450816632749E-02 -2.7038252516475968E-02 -2.7046036626289200E-02 -2.7053803140630224E-02 -2.7061552054062063E-02 -2.7069283362676642E-02 -2.7076997063261013E-02 -2.7084693156693065E-02 -2.7092371646871994E-02 -2.7100032533993151E-02 -2.7107675810839203E-02 -2.7115301470123667E-02 -2.7122909509117343E-02 -2.7130499926770621E-02 -2.7138072723230253E-02 -2.7145627899789575E-02 -2.7153165456302288E-02 -2.7160685388787884E-02 -2.7168187692764731E-02 -2.7175672364601163E-02 -2.7183139401127585E-02 -2.7190588801378420E-02 -2.7198020567121849E-02 -2.7205434698940385E-02 -2.7212831192764846E-02 -2.7220210043704073E-02 -2.7227571248763460E-02 -2.7234914806129034E-02 -2.7242240715163162E-02 -2.7249548977091816E-02 -2.7256839592453157E-02 -2.7264112557853215E-02 -2.7271367868810143E-02 -2.7278605521473907E-02 -2.7285825512507012E-02 -2.7293027840321626E-02 -2.7300212506968288E-02 -2.7307379514362962E-02 -2.7314528860758958E-02 -2.7321660542968973E-02 -2.7328774556781021E-02 -2.7335870896939524E-02 -2.7342949560479286E-02 -2.7350010550894255E-02 -2.7357053872067549E-02 -2.7364079521829832E-02 -2.7371087494990905E-02 -2.7378077787053461E-02 -2.7385050394466346E-02 -2.7392005315105123E-02 -2.7398942551860237E-02 -2.7405862108336922E-02 -2.7412763982942612E-02 -2.7419648170693790E-02 -2.7426514667066318E-02 -2.7433363468423566E-02 -2.7440194572259005E-02 -2.7447007981212499E-02 -2.7453803699204402E-02 -2.7460581724894028E-02 -2.7467342052501294E-02 -2.7474084677747118E-02 -2.7480809600027876E-02 -2.7487516819297168E-02 -2.7494206335892755E-02 -2.7500878150237502E-02 -2.7507532260815561E-02 -2.7514168663998029E-02 -2.7520787356767655E-02 -2.7527388338234517E-02 -2.7533971607932906E-02 -2.7540537165692845E-02 -2.7547085011489923E-02 -2.7553615144696841E-02 -2.7560127563835617E-02 -2.7566622266928246E-02 -2.7573099250272310E-02 -2.7579558510063561E-02 -2.7586000046689662E-02 -2.7592423863437156E-02 -2.7598829961693848E-02 -2.7605218339268850E-02 -2.7611588993502877E-02 -2.7617941921275882E-02 -2.7624277119430319E-02 -2.7630594587003104E-02 -2.7636894325005011E-02 -2.7643176334484161E-02 -2.7649440616409716E-02 -2.7655687171131003E-02 -2.7661915994629735E-02 -2.7668127081119927E-02 -2.7674320429111304E-02 -2.7680496042104787E-02 -2.7686653922496928E-02 -2.7692794068289839E-02 -2.7698916476650483E-02 -2.7705021145093579E-02 -2.7711108071363465E-02 -2.7717177254895753E-02 -2.7723228697658340E-02 -2.7729262401435698E-02 -2.7735278366349290E-02 -2.7741276591850904E-02 -2.7747257074162177E-02 -2.7753219807141960E-02 -2.7759164788578004E-02 -2.7765092024032260E-02 -2.7771001518689487E-02 -2.7776893270460280E-02 -2.7782767274739453E-02 -2.7788623528188453E-02 -2.7794462028686944E-02 -2.7800282775531857E-02 -2.7806085771527968E-02 -2.7811871019668671E-02 -2.7817638520113562E-02 -2.7823388271666361E-02 -2.7829120272005955E-02 -2.7834834517432055E-02 -2.7840531005342086E-02 -2.7846209737164323E-02 -2.7851870715065084E-02 -2.7857513939920888E-02 -2.7863139411804391E-02 -2.7868747129633237E-02 -2.7874337090497581E-02 -2.7879909292183900E-02 -2.7885463736402431E-02 -2.7891000425780951E-02 -2.7896519359826052E-02 -2.7902020535585662E-02 -2.7907503950897614E-02 -2.7912969605384787E-02 -2.7918417499271170E-02 -2.7923847635101983E-02 -2.7929260016153881E-02 -2.7934654642165418E-02 -2.7940031509271317E-02 -2.7945390614125404E-02 -2.7950731955250972E-02 -2.7956055531870930E-02 -2.7961361346406508E-02 -2.7966649402821647E-02 -2.7971919702972046E-02 -2.7977172245927592E-02 -2.7982407030004056E-02 -2.7987624051451724E-02 -2.7992823306470443E-02 -2.7998004796210091E-02 -2.8003168525017875E-02 -2.8008314495815492E-02 -2.8013442709003689E-02 -2.8018553164031502E-02 -2.8023645856887467E-02 -2.8028720782856949E-02 -2.8033777943314409E-02 -2.8038817344737239E-02 -2.8043838990857724E-02 -2.8048842878943762E-02 -2.8053829005622886E-02 -2.8058797369056650E-02 -2.8063747968121874E-02 -2.8068680804166246E-02 -2.8073595881211794E-02 -2.8078493201986618E-02 -2.8083372765018624E-02 -2.8088234568248271E-02 -2.8093078611258145E-02 -2.8097904894507694E-02 -2.8102713418564410E-02 -2.8107504184135601E-02 -2.8112277191911225E-02 -2.8117032442472056E-02 -2.8121769936232763E-02 -2.8126489671822390E-02 -2.8131191646663341E-02 -2.8135875860976000E-02 -2.8140542320108597E-02 -2.8145191028756750E-02 -2.8149821985319391E-02 -2.8154435186230613E-02 -2.8159030629844751E-02 -2.8163608316237630E-02 -2.8168168246500768E-02 -2.8172710423999197E-02 -2.8177234851885936E-02 -2.8181741529442819E-02 -2.8186230454334212E-02 -2.8190701626140475E-02 -2.8195155046658975E-02 -2.8199590717392330E-02 -2.8204008638525329E-02 -2.8208408810085350E-02 -2.8212791233101320E-02 -2.8217155909151768E-02 -2.8221502838763346E-02 -2.8225832020885157E-02 -2.8230143455139037E-02 -2.8234437144527544E-02 -2.8238713092701755E-02 -2.8242971299904995E-02 -2.8247211763878864E-02 -2.8251434483554393E-02 -2.8255639460282016E-02 -2.8259826695644572E-02 -2.8263996190970159E-02 -2.8268147947485563E-02 -2.8272281966170647E-02 -2.8276398247770732E-02 -2.8280496793140465E-02 -2.8284577603436764E-02 -2.8288640679764294E-02 -2.8292686022460743E-02 -2.8296713631526034E-02 -2.8300723507585324E-02 -2.8304715652033453E-02 -2.8308690065980288E-02 -2.8312646749411537E-02 -2.8316585702374317E-02 -2.8320506928112804E-02 -2.8324410431752579E-02 -2.8328296214856684E-02 -2.8332164273287400E-02 -2.8336014603871508E-02 -2.8339847210103009E-02 -2.8343662097105118E-02 -2.8347459266019739E-02 -2.8351238714877814E-02 -2.8355000443749008E-02 -2.8358744457097466E-02 -2.8362470759059892E-02 -2.8366179348453580E-02 -2.8369870222248118E-02 -2.8373543381098203E-02 -2.8377198829391815E-02 -2.8380836570706901E-02 -2.8384456605959250E-02 -2.8388058935536375E-02 -2.8391643559171700E-02 -2.8395210476315678E-02 -2.8398759688045703E-02 -2.8402291197567632E-02 -2.8405805008070214E-02 -2.8409301122158729E-02 -2.8412779542047423E-02 -2.8416240266940597E-02 -2.8419683294136491E-02 -2.8423108623831430E-02 -2.8426516261183112E-02 -2.8429906211036048E-02 -2.8433278474373779E-02 -2.8436633051048283E-02 -2.8439969941619420E-02 -2.8443289147239370E-02 -2.8446590669230998E-02 -2.8449874509254531E-02 -2.8453140669074929E-02 -2.8456389150848013E-02 -2.8459619956842094E-02 -2.8462833088133108E-02 -2.8466028544512998E-02 -2.8469206326911894E-02 -2.8472366439772440E-02 -2.8475508887771648E-02 -2.8478633671949419E-02 -2.8481740791430368E-02 -2.8484830245786911E-02 -2.8487902035238821E-02 -2.8490956161075071E-02 -2.8493992628570070E-02 -2.8497011443614835E-02 -2.8500012607584283E-02 -2.8502996118761875E-02 -2.8505961976889840E-02 -2.8508910184455068E-02 -2.8511840744103324E-02 -2.8514753657803656E-02 -2.8517648927376307E-02 -2.8520526555989602E-02 -2.8523386548002582E-02 -2.8526228905594812E-02 -2.8529053625692101E-02 -2.8531860705567014E-02 -2.8534650150323335E-02 -2.8537421968278475E-02 -2.8540176162814943E-02 -2.8542912731643180E-02 -2.8545631673547761E-02 -2.8548332991656340E-02 -2.8551016689854904E-02 -2.8553682771148989E-02 -2.8556331238027088E-02 -2.8558962091922203E-02 -2.8561575332711850E-02 -2.8564170961013654E-02 -2.8566748981073923E-02 -2.8569309397880657E-02 -2.8571852213518139E-02 -2.8574377427954184E-02 -2.8576885042456115E-02 -2.8579375060889516E-02 -2.8581847486853110E-02 -2.8584302320780269E-02 -2.8586739562143790E-02 -2.8589159213453494E-02 -2.8591561280090598E-02 -2.8593945766416769E-02 -2.8596312673927805E-02 -2.8598662003731557E-02 -2.8600993757383182E-02 -2.8603307936666274E-02 -2.8605604544114420E-02 -2.8607883583174822E-02 -2.8610145057021936E-02 -2.8612388967726596E-02 -2.8614615317065325E-02 -2.8616824106150508E-02 -2.8619015335731246E-02 -2.8621189008869740E-02 -2.8623345132288480E-02 -2.8625483711632399E-02 -2.8627604746243072E-02 -2.8629708233960289E-02 -2.8631794176762260E-02 -2.8633862579849938E-02 -2.8635913447560488E-02 -2.8637946782277702E-02 -2.8639962586269940E-02 -2.8641960862562918E-02 -2.8643941614417152E-02 -2.8645904843958722E-02 -2.8647850552172779E-02 -2.8649778740943131E-02 -2.8651689414725002E-02 -2.8653582578114657E-02 -2.8655458233311112E-02 -2.8657316381352820E-02 -2.8659157024083146E-02 -2.8660980164401634E-02 -2.8662785805409343E-02 -2.8664573950680141E-02 -2.8666344603889456E-02 -2.8668097768654411E-02 -2.8669833448531381E-02 -2.8671551645311662E-02 -2.8673252357817241E-02 -2.8674935586141082E-02 -2.8676601337900343E-02 -2.8678249622569648E-02 -2.8679880442661152E-02 -2.8681493794919168E-02 -2.8683089678884759E-02 -2.8684668100632742E-02 -2.8686229066572276E-02 -2.8687772579625178E-02 -2.8689298641346537E-02 -2.8690807254101860E-02 -2.8692298421128429E-02 -2.8693772145442033E-02 -2.8695228429291095E-02 -2.8696667274994387E-02 -2.8698088686737049E-02 -2.8699492669661073E-02 -2.8700879227784370E-02 -2.8702248363558287E-02 -2.8703600079319571E-02 -2.8704934377405782E-02 -2.8706251260287724E-02 -2.8707550732112955E-02 -2.8708832798161599E-02 -2.8710097462403345E-02 -2.8711344726415990E-02 -2.8712574591588678E-02 -2.8713787059625375E-02 -2.8714982132516557E-02 -2.8716159815684601E-02 -2.8717320117574364E-02 -2.8718463043802208E-02 -2.8719588593090820E-02 -2.8720696764149223E-02 -2.8721787562545772E-02 -2.8722860996645835E-02 -2.8723917070565763E-02 -2.8724955783567010E-02 -2.8725977136216007E-02 -2.8726981133964748E-02 -2.8727967782919927E-02 -2.8728937086345639E-02 -2.8729889045929546E-02 -2.8730823664367067E-02 -2.8731740945863914E-02 -2.8732640894907079E-02 -2.8733523516650341E-02 -2.8734388816237140E-02 -2.8735236796275623E-02 -2.8736067457537925E-02 -2.8736880802022264E-02 -2.8737676834155141E-02 -2.8738455558619300E-02 -2.8739216979996752E-02 -2.8739961102811257E-02 -2.8740687931106287E-02 -2.8741397468473397E-02 -2.8742089718398801E-02 -2.8742764684147964E-02 -2.8743422368918425E-02 -2.8744062775651624E-02 -2.8744685907232070E-02 -2.8745291768569339E-02 -2.8745880367029755E-02 -2.8746451708310795E-02 -2.8747005792041921E-02 -2.8747542617185144E-02 -2.8748062188996219E-02 -2.8748564516451927E-02 -2.8749049605642205E-02 -2.8749517458046842E-02 -2.8749968075233556E-02 -2.8750401460966316E-02 -2.8750817619639008E-02 -2.8751216555892665E-02 -2.8751598274556322E-02 -2.8751962779924662E-02 -2.8752310075189431E-02 -2.8752640163653358E-02 -2.8752953050097202E-02 -2.8753248739810555E-02 -2.8753527237138855E-02 -2.8753788545481881E-02 -2.8754032668255509E-02 -2.8754259609029845E-02 -2.8754469371488792E-02 -2.8754661960038414E-02 -2.8754837379439797E-02 -2.8754995634506782E-02 -2.8755136730118144E-02 -2.8755260670752784E-02 -2.8755367459440333E-02 -2.8755457099097083E-02 -2.8755529595060541E-02 -2.8755584954187955E-02 -2.8755623181464428E-02 -2.8755644278701555E-02 -2.8755648247904188E-02 -2.8755635093456838E-02 -2.8755604820465425E-02 -2.8755557434165597E-02 -2.8755492939899704E-02 -2.8755411342957189E-02 -2.8755312648504928E-02 -2.8755196861307342E-02 -2.8755063983627611E-02 -2.8754914016855176E-02 -2.8754746965541162E-02 -2.8754562837604875E-02 -2.8754361639826812E-02 -2.8754143375230218E-02 -2.8753908046367946E-02 -2.8753655657594447E-02 -2.8753386214193617E-02 -2.8753099720891601E-02 -2.8752796181636495E-02 -2.8752475600651074E-02 -2.8752137983433387E-02 -2.8751783335745070E-02 -2.8751411662806637E-02 -2.8751022969461526E-02 -2.8750617259718537E-02 -2.8750194536110146E-02 -2.8749754801679284E-02 -2.8749298062892170E-02 -2.8748824327216135E-02 -2.8748333600271500E-02 -2.8747825886055504E-02 -2.8747301188618100E-02 -2.8746759512261393E-02 -2.8746200861380054E-02 -2.8745625240763895E-02 -2.8745032655348113E-02 -2.8744423109397694E-02 -2.8743796606418098E-02 -2.8743153151046547E-02 -2.8742492751547527E-02 -2.8741815416345587E-02 -2.8741121148681732E-02 -2.8740409948964773E-02 -2.8739681820700066E-02 -2.8738936771972822E-02 -2.8738174810326853E-02 -2.8737395939561379E-02 -2.8736600162637894E-02 -2.8735787484295675E-02 -2.8734957910559498E-02 -2.8734111447249352E-02 -2.8733248099740663E-02 -2.8732367873339673E-02 -2.8731470773245137E-02 -2.8730556804594961E-02 -2.8729625972040884E-02 -2.8728678279781386E-02 -2.8727713732484724E-02 -2.8726732336036689E-02 -2.8725734096349903E-02 -2.8724719018130330E-02 -2.8723687105574800E-02 -2.8722638364221505E-02 -2.8721572801229465E-02 -2.8720490423192788E-02 -2.8719391234510606E-02 -2.8718275239196130E-02 -2.8717142441980637E-02 -2.8715992848022582E-02 -2.8714826462473846E-02 -2.8713643290467251E-02 -2.8712443337414774E-02 -2.8711226609975552E-02 -2.8709993115054629E-02 -2.8708742858053707E-02 -2.8707475843218266E-02 -2.8706192075207127E-02 -2.8704891559579976E-02 -2.8703574302032079E-02 -2.8702240308415616E-02 -2.8700889584592666E-02 -2.8699522135328774E-02 -2.8698137964300652E-02 -2.8696737076416776E-02 -2.8695319480006649E-02 -2.8693885183498007E-02 -2.8692434191512104E-02 -2.8690966506881556E-02 -2.8689482134863869E-02 -2.8687981083844988E-02 -2.8686463361007612E-02 -2.8684928968517362E-02 -2.8683377907936711E-02 -2.8681810186662108E-02 -2.8680225815742477E-02 -2.8678624802723554E-02 -2.8677007149228183E-02 -2.8675372857417447E-02 -2.8673721934690082E-02 -2.8672054389888006E-02 -2.8670370229918692E-02 -2.8668669460098301E-02 -2.8666952085097161E-02 -2.8665218108285463E-02 -2.8663467533606560E-02 -2.8661700369785669E-02 -2.8659916627267416E-02 -2.8658116312077816E-02 -2.8656299425562005E-02 -2.8654465970684932E-02 -2.8652615955699377E-02 -2.8650749389452262E-02 -2.8648866277732769E-02 -2.8646966624770082E-02 -2.8645050436062715E-02 -2.8643117718862493E-02 -2.8641168480008899E-02 -2.8639202724281235E-02 -2.8637220456148756E-02 -2.8635221682341578E-02 -2.8633206411105852E-02 -2.8631174649624166E-02 -2.8629126403142177E-02 -2.8627061676711325E-02 -2.8624980475406393E-02 -2.8622882804369820E-02 -2.8620768669841881E-02 -2.8618638079023401E-02 -2.8616491039515583E-02 -2.8614327559774042E-02 -2.8612147647695586E-02 -2.8609951306466330E-02 -2.8607738537415776E-02 -2.8605509345847262E-02 -2.8603263741548361E-02 -2.8601001733666028E-02 -2.8598723328642928E-02 -2.8596428532318460E-02 -2.8594117349715596E-02 -2.8591789785430609E-02 -2.8589445845385950E-02 -2.8587085537441388E-02 -2.8584708869311165E-02 -2.8582315847484267E-02 -2.8579906478115143E-02 -2.8577480767087278E-02 -2.8575038720094689E-02 -2.8572580343447833E-02 -2.8570105644631558E-02 -2.8567614631157881E-02 -2.8565107309968116E-02 -2.8562583687738129E-02 -2.8560043769730085E-02 -2.8557487559895990E-02 -2.8554915063575572E-02 -2.8552326289678145E-02 -2.8549721247350949E-02 -2.8547099943448184E-02 -2.8544462383786974E-02 -2.8541808574218050E-02 -2.8539138520638569E-02 -2.8536452229111386E-02 -2.8533749706236521E-02 -2.8531030958931787E-02 -2.8528295996262665E-02 -2.8525544828499134E-02 -2.8522777461961153E-02 -2.8519993896817697E-02 -2.8517194134786643E-02 -2.8514378186754695E-02 -2.8511546065776192E-02 -2.8508697779551950E-02 -2.8505833331685975E-02 -2.8502952726715179E-02 -2.8500055971272021E-02 -2.8497143072497344E-02 -2.8494214039050215E-02 -2.8491268880037380E-02 -2.8488307602087818E-02 -2.8485330209380835E-02 -2.8482336707159654E-02 -2.8479327103773329E-02 -2.8476301407789961E-02 -2.8473259625424695E-02 -2.8470201761806563E-02 -2.8467127824010039E-02 -2.8464037821601625E-02 -2.8460931763247682E-02 -2.8457809653856234E-02 -2.8454671497771380E-02 -2.8451517302345575E-02 -2.8448347076816424E-02 -2.8445160829584291E-02 -2.8441958567616606E-02 -2.8438740297772356E-02 -2.8435506027033004E-02 -2.8432255762343220E-02 -2.8428989509451993E-02 -2.8425707273145789E-02 -2.8422409060599473E-02 -2.8419094884202738E-02 -2.8415764755735158E-02 -2.8412418678745222E-02 -2.8409056653752630E-02 -2.8405678686529816E-02 -2.8402284788384621E-02 -2.8398874969645615E-02 -2.8395449237102369E-02 -2.8392007597019195E-02 -2.8388550056538637E-02 -2.8385076623253371E-02 -2.8381587304606194E-02 -2.8378082107831125E-02 -2.8374561040164732E-02 -2.8371024108909869E-02 -2.8367471321390395E-02 -2.8363902684995140E-02 -2.8360318207153037E-02 -2.8356717894989367E-02 -2.8353101755092765E-02 -2.8349469794488835E-02 -2.8345822022706892E-02 -2.8342158449927629E-02 -2.8338479083735831E-02 -2.8334783929463883E-02 -2.8331072992990518E-02 -2.8327346281627565E-02 -2.8323603802996807E-02 -2.8319845565467360E-02 -2.8316071577686636E-02 -2.8312281847272431E-02 -2.8308476380688456E-02 -2.8304655184876043E-02 -2.8300818268420888E-02 -2.8296965640077019E-02 -2.8293097307231767E-02 -2.8289213276535927E-02 -2.8285313555482260E-02 -2.8281398152793246E-02 -2.8277467076766177E-02 -2.8273520333571254E-02 -2.8269557929134131E-02 -2.8265579873384943E-02 -2.8261586179084190E-02 -2.8257576855177366E-02 -2.8253551903319268E-02 -2.8249511325810314E-02 -2.8245455132894674E-02 -2.8241383337329506E-02 -2.8237295948027798E-02 -2.8233192970351473E-02 -2.8229074410918591E-02 -2.8224940279775856E-02 -2.8220790586947486E-02 -2.8216625338434134E-02 -2.8212444538539199E-02 -2.8208248195211741E-02 -2.8204036320756048E-02 -2.8199808925936438E-02 -2.8195566015640106E-02 -2.8191307593949222E-02 -2.8187033669018133E-02 -2.8182744251376686E-02 -2.8178439350454540E-02 -2.8174118973938126E-02 -2.8169783129497503E-02 -2.8165431825383055E-02 -2.8161065069900258E-02 -2.8156682869823521E-02 -2.8152285230778992E-02 -2.8147872160906189E-02 -2.8143443673448808E-02 -2.8138999780931692E-02 -2.8134540488050825E-02 -2.8130065796860539E-02 -2.8125575714212692E-02 -2.8121070251680216E-02 -2.8116549420437457E-02 -2.8112013230079877E-02 -2.8107461689588692E-02 -2.8102894805085325E-02 -2.8098312581364932E-02 -2.8093715025014763E-02 -2.8089102144906737E-02 -2.8084473950816164E-02 -2.8079830455175640E-02 -2.8075171670427244E-02 -2.8070497602593631E-02 -2.8065808253723023E-02 -2.8061103629320551E-02 -2.8056383740672580E-02 -2.8051648599236565E-02 -2.8046898214744570E-02 -2.8042132596294751E-02 -2.8037351750931028E-02 -2.8032555684039884E-02 -2.8027744402590059E-02 -2.8022917917046249E-02 -2.8018076238186557E-02 -2.8013219375911402E-02 -2.8008347339692923E-02 -2.8003460136870627E-02 -2.7998557772554999E-02 -2.7993640253298487E-02 -2.7988707590030547E-02 -2.7983759794107048E-02 -2.7978796873915270E-02 -2.7973818836354081E-02 -2.7968825689831674E-02 -2.7963817444811714E-02 -2.7958794110981407E-02 -2.7953755694548488E-02 -2.7948702201253839E-02 -2.7943633641152415E-02 -2.7938550027153470E-02 -2.7933451369859690E-02 -2.7928337675740818E-02 -2.7923208951133018E-02 -2.7918065203809538E-02 -2.7912906442071131E-02 -2.7907732675546550E-02 -2.7902543915007350E-02 -2.7897340170341015E-02 -2.7892121449322543E-02 -2.7886887759577490E-02 -2.7881639109724243E-02 -2.7876375508824415E-02 -2.7871096966730072E-02 -2.7865803494171375E-02 -2.7860495101085101E-02 -2.7855171794862358E-02 -2.7849833582395771E-02 -2.7844480470411319E-02 -2.7839112465621398E-02 -2.7833729578581490E-02 -2.7828331825376137E-02 -2.7822919219810872E-02 -2.7817491764716831E-02 -2.7812049460749191E-02 -2.7806592316612349E-02 -2.7801120346723895E-02 -2.7795633564116795E-02 -2.7790131979006948E-02 -2.7784615600715285E-02 -2.7779084435374812E-02 -2.7773538488165252E-02 -2.7767977766748889E-02 -2.7762402281073045E-02 -2.7756812042217940E-02 -2.7751207063833265E-02 -2.7745587358943561E-02 -2.7739952933115986E-02 -2.7734303788724525E-02 -2.7728639932642029E-02 -2.7722961377090679E-02 -2.7717268134389201E-02 -2.7711560216161731E-02 -2.7705837633543510E-02 -2.7700100394121067E-02 -2.7694348503441282E-02 -2.7688581969041112E-02 -2.7682800801546933E-02 -2.7677005011764639E-02 -2.7671194610142637E-02 -2.7665369606915863E-02 -2.7659530010620995E-02 -2.7653675828513094E-02 -2.7647807068501822E-02 -2.7641923739866570E-02 -2.7636025852612305E-02 -2.7630113420037895E-02 -2.7624186456345758E-02 -2.7618244969318903E-02 -2.7612288960469050E-02 -2.7606318434546247E-02 -2.7600333405486142E-02 -2.7594333888306399E-02 -2.7588319894788341E-02 -2.7582291435087287E-02 -2.7576248516453981E-02 -2.7570191142488158E-02 -2.7564119318875830E-02 -2.7558033059401688E-02 -2.7551932379205179E-02 -2.7545817288859499E-02 -2.7539687796098972E-02 -2.7533543909070621E-02 -2.7527385636665926E-02 -2.7521212987869210E-02 -2.7515025971777633E-02 -2.7508824597690430E-02 -2.7502608877623933E-02 -2.7496378825766526E-02 -2.7490134452982339E-02 -2.7483875762918452E-02 -2.7477602759425158E-02 -2.7471315453463756E-02 -2.7465013858709836E-02 -2.7458697987689622E-02 -2.7452367851725678E-02 -2.7446023460787870E-02 -2.7439664821201391E-02 -2.7433291939229311E-02 -2.7426904826073007E-02 -2.7420503495401594E-02 -2.7414087958707527E-02 -2.7407658224533497E-02 -2.7401214301232230E-02 -2.7394756197220656E-02 -2.7388283921007259E-02 -2.7381797482025450E-02 -2.7375296890346523E-02 -2.7368782158041983E-02 -2.7362253300646910E-02 -2.7355710331972309E-02 -2.7349153255421574E-02 -2.7342582071636774E-02 -2.7335996790130740E-02 -2.7329397428021998E-02 -2.7322784000232692E-02 -2.7316156516118968E-02 -2.7309514984258473E-02 -2.7302859413178306E-02 -2.7296189811395245E-02 -2.7289506187724129E-02 -2.7282808551310652E-02 -2.7276096912601334E-02 -2.7269371285910345E-02 -2.7262631685600908E-02 -2.7255878119726854E-02 -2.7249110592978489E-02 -2.7242329113570496E-02 -2.7235533694806476E-02 -2.7228724349766295E-02 -2.7221901089053858E-02 -2.7215063922515263E-02 -2.7208212858215123E-02 -2.7201347902981621E-02 -2.7194469066077271E-02 -2.7187576361336067E-02 -2.7180669802545004E-02 -2.7173749400551162E-02 -2.7166815165133536E-02 -2.7159867104498796E-02 -2.7152905225424153E-02 -2.7145929536685487E-02 -2.7138940052056259E-02 -2.7131936785601503E-02 -2.7124919748056819E-02 -2.7117888948675537E-02 -2.7110844396617022E-02 -2.7103786100937978E-02 -2.7096714070916020E-02 -2.7089628316561910E-02 -2.7082528848340320E-02 -2.7075415679814665E-02 -2.7068288826264733E-02 -2.7061148298180550E-02 -2.7053994098722361E-02 -2.7046826232550770E-02 -2.7039644713475707E-02 -2.7032449557584149E-02 -2.7025240778134899E-02 -2.7018018386241280E-02 -2.7010782390981057E-02 -2.7003532797499320E-02 -2.6996269611794237E-02 -2.6988992847511845E-02 -2.6981702520878236E-02 -2.6974398644298916E-02 -2.6967081226462915E-02 -2.6959750276338755E-02 -2.6952405804024037E-02 -2.6945047819774585E-02 -2.6937676333660371E-02 -2.6930291355723685E-02 -2.6922892898183403E-02 -2.6915480975987904E-02 -2.6908055602134096E-02 -2.6900616782251120E-02 -2.6893164520931226E-02 -2.6885698828922680E-02 -2.6878219720773075E-02 -2.6870727210134903E-02 -2.6863221309115313E-02 -2.6855702029051475E-02 -2.6848169378361285E-02 -2.6840623364780315E-02 -2.6833063998665401E-02 -2.6825491292475148E-02 -2.6817905258687123E-02 -2.6810305909693653E-02 -2.6802693257432605E-02 -2.6795067311067584E-02 -2.6787428078725847E-02 -2.6779775569363694E-02 -2.6772109792799689E-02 -2.6764430760810389E-02 -2.6756738490529633E-02 -2.6749032998844006E-02 -2.6741314292595807E-02 -2.6733582373673209E-02 -2.6725837249732723E-02 -2.6718078936184015E-02 -2.6710307448582472E-02 -2.6702522801016908E-02 -2.6694725006766687E-02 -2.6686914073495601E-02 -2.6679090005210442E-02 -2.6671252809970982E-02 -2.6663402502965637E-02 -2.6655539099555963E-02 -2.6647662612427622E-02 -2.6639773053292844E-02 -2.6631870431397493E-02 -2.6623954753891264E-02 -2.6616026029780970E-02 -2.6608084272429902E-02 -2.6600129495610445E-02 -2.6592161711814347E-02 -2.6584180932949768E-02 -2.6576187169415344E-02 -2.6568180429950721E-02 -2.6560160723923830E-02 -2.6552128062838441E-02 -2.6544082458744594E-02 -2.6536023925065523E-02 -2.6527952475905087E-02 -2.6519868122356249E-02 -2.6511770871221779E-02 -2.6503660730183325E-02 -2.6495537711745402E-02 -2.6487401829618860E-02 -2.6479253097526322E-02 -2.6471091529175442E-02 -2.6462917135913679E-02 -2.6454729924730472E-02 -2.6446529903039768E-02 -2.6438317083056807E-02 -2.6430091478587457E-02 -2.6421853103192540E-02 -2.6413601970205019E-02 -2.6405338091566418E-02 -2.6397061475869739E-02 -2.6388772131575783E-02 -2.6380470069794024E-02 -2.6372155302819979E-02 -2.6363827843464107E-02 -2.6355487705133608E-02 -2.6347134900408457E-02 -2.6338769439103828E-02 -2.6330391330636291E-02 -2.6322000585979950E-02 -2.6313597217022266E-02 -2.6305181236440312E-02 -2.6296752658090210E-02 -2.6288311494954454E-02 -2.6279857755841379E-02 -2.6271391448639478E-02 -2.6262912584117511E-02 -2.6254421175207852E-02 -2.6245917235763683E-02 -2.6237400781350066E-02 -2.6228871826396518E-02 -2.6220330377625320E-02 -2.6211776439290683E-02 -2.6203210021928654E-02 -2.6194631142147581E-02 -2.6186039815868520E-02 -2.6177436056588902E-02 -2.6168819876872824E-02 -2.6160191285000464E-02 -2.6151550287331848E-02 -2.6142896893827407E-02 -2.6134231118950562E-02 -2.6125552977461653E-02 -2.6116862484170437E-02 -2.6108159653433351E-02 -2.6099444494541126E-02 -2.6090717013704127E-02 -2.6081977219695289E-02 -2.6073225125496396E-02 -2.6064460744853191E-02 -2.6055684093272986E-02 -2.6046895186478680E-02 -2.6038094035583818E-02 -2.6029280648035221E-02 -2.6020455032470642E-02 -2.6011617200249332E-02 -2.6002767163625724E-02 -2.5993904938276559E-02 -2.5985030540959672E-02 -2.5976143982849597E-02 -2.5967245269379814E-02 -2.5958334407966896E-02 -2.5949411412258358E-02 -2.5940476297083456E-02 -2.5931529078203380E-02 -2.5922569771738988E-02 -2.5913598389320284E-02 -2.5904614936613116E-02 -2.5895619420623010E-02 -2.5886611854832861E-02 -2.5877592254232511E-02 -2.5868560633926122E-02 -2.5859517009048521E-02 -2.5850461391143505E-02 -2.5841393785574596E-02 -2.5832314198848735E-02 -2.5823222646165225E-02 -2.5814119145272020E-02 -2.5805003711484743E-02 -2.5795876358044506E-02 -2.5786737095931486E-02 -2.5777585931187494E-02 -2.5768422870320426E-02 -2.5759247927468504E-02 -2.5750061119863794E-02 -2.5740862463745410E-02 -2.5731651974253446E-02 -2.5722429663796703E-02 -2.5713195536827233E-02 -2.5703949597462611E-02 -2.5694691860273622E-02 -2.5685422345372209E-02 -2.5676141068967231E-02 -2.5666848041675440E-02 -2.5657543273757001E-02 -2.5648226775735319E-02 -2.5638898558289179E-02 -2.5629558633268067E-02 -2.5620207013346798E-02 -2.5610843711910400E-02 -2.5601468743616327E-02 -2.5592082122529187E-02 -2.5582683858828129E-02 -2.5573273961556040E-02 -2.5563852442697432E-02 -2.5554419316892122E-02 -2.5544974598384142E-02 -2.5535518300236006E-02 -2.5526050435082624E-02 -2.5516571013729620E-02 -2.5507080046209323E-02 -2.5497577543460454E-02 -2.5488063517481563E-02 -2.5478537981569994E-02 -2.5469000952975215E-02 -2.5459452448999931E-02 -2.5449892479642116E-02 -2.5440321050767271E-02 -2.5430738171563012E-02 -2.5421143856292600E-02 -2.5411538119904282E-02 -2.5401920978479358E-02 -2.5392292447975525E-02 -2.5382652538290335E-02 -2.5373001254842150E-02 -2.5363338606955256E-02 -2.5353664611814861E-02 -2.5343979286861391E-02 -2.5334282645769063E-02 -2.5324574700798488E-02 -2.5314855462614770E-02 -2.5305124940355393E-02 -2.5295383144808604E-02 -2.5285630091171477E-02 -2.5275865795099026E-02 -2.5266090270362754E-02 -2.5256303529805263E-02 -2.5246505584669544E-02 -2.5236696444222693E-02 -2.5226876118729244E-02 -2.5217044622287726E-02 -2.5207201969917391E-02 -2.5197348177733420E-02 -2.5187483262449396E-02 -2.5177607236015358E-02 -2.5167720102725000E-02 -2.5157821868478234E-02 -2.5147912549696116E-02 -2.5137992165606537E-02 -2.5128060732229042E-02 -2.5118118263030498E-02 -2.5108164769853145E-02 -2.5098200261286917E-02 -2.5088224746065389E-02 -2.5078238236325972E-02 -2.5068240745618500E-02 -2.5058232290269870E-02 -2.5048212889438457E-02 -2.5038182558866480E-02 -2.5028141304524441E-02 -2.5018089131745035E-02 -2.5008026054549385E-02 -2.4997952091250542E-02 -2.4987867257735896E-02 -2.4977771566649733E-02 -2.4967665029748939E-02 -2.4957547656345055E-02 -2.4947419455559162E-02 -2.4937280440892051E-02 -2.4927130628699851E-02 -2.4916970035261131E-02 -2.4906798676637903E-02 -2.4896616567440966E-02 -2.4886423715240354E-02 -2.4876220125790584E-02 -2.4866005810841928E-02 -2.4855780787203300E-02 -2.4845545071910856E-02 -2.4835298682154661E-02 -2.4825041633944125E-02 -2.4814773935306379E-02 -2.4804495591243852E-02 -2.4794206612930272E-02 -2.4783907018262163E-02 -2.4773596824276042E-02 -2.4763276044467201E-02 -2.4752944691621492E-02 -2.4742602777990678E-02 -2.4732250315539415E-02 -2.4721887316162875E-02 -2.4711513791662466E-02 -2.4701129754861231E-02 -2.4690735222641404E-02 -2.4680330212429980E-02 -2.4669914735773485E-02 -2.4659488800160848E-02 -2.4649052415814700E-02 -2.4638605598094668E-02 -2.4628148362812713E-02 -2.4617680725283728E-02 -2.4607202700515474E-02 -2.4596714300779705E-02 -2.4586215535895749E-02 -2.4575706416639406E-02 -2.4565186956281026E-02 -2.4554657168790423E-02 -2.4544117070534156E-02 -2.4533566678779924E-02 -2.4523006006417675E-02 -2.4512435061265308E-02 -2.4501853852516502E-02 -2.4491262394621145E-02 -2.4480660703146306E-02 -2.4470048794436525E-02 -2.4459426685220626E-02 -2.4448794388987623E-02 -2.4438151914371081E-02 -2.4427499270383717E-02 -2.4416836469331266E-02 -2.4406163524689658E-02 -2.4395480454140028E-02 -2.4384787278430499E-02 -2.4374084012881873E-02 -2.4363370662107281E-02 -2.4352647231319868E-02 -2.4341913736169358E-02 -2.4331170195886005E-02 -2.4320416627443067E-02 -2.4309653045649929E-02 -2.4298879463593676E-02 -2.4288095890176994E-02 -2.4277302334186755E-02 -2.4266498808615169E-02 -2.4255685328456868E-02 -2.4244861910176840E-02 -2.4234028572037696E-02 -2.4223185330222944E-02 -2.4212332193470767E-02 -2.4201469169394356E-02 -2.4190596270506463E-02 -2.4179713512310248E-02 -2.4168820910967337E-02 -2.4157918483621862E-02 -2.4147006245964806E-02 -2.4136084206673084E-02 -2.4125152372834229E-02 -2.4114210757819509E-02 -2.4103259379944973E-02 -2.4092298256671699E-02 -2.4081327403404719E-02 -2.4070346834496253E-02 -2.4059356559419660E-02 -2.4048356585983005E-02 -2.4037346926282011E-02 -2.4026327596774141E-02 -2.4015298614183354E-02 -2.4004259995428920E-02 -2.3993211756714469E-02 -2.3982153907983656E-02 -2.3971086456179371E-02 -2.3960009412840405E-02 -2.3948922795563082E-02 -2.3937826622160801E-02 -2.3926720909740361E-02 -2.3915605674688832E-02 -2.3904480926854040E-02 -2.3893346671901031E-02 -2.3882202919905428E-02 -2.3871049688561859E-02 -2.3859886996051630E-02 -2.3848714859313950E-02 -2.3837533294609147E-02 -2.3826342313074924E-02 -2.3815141921569232E-02 -2.3803932130174031E-02 -2.3792712956428121E-02 -2.3781484418531108E-02 -2.3770246532418993E-02 -2.3758999312994643E-02 -2.3747742772068880E-02 -2.3736476918113158E-02 -2.3725201761628588E-02 -2.3713917319562867E-02 -2.3702623609841180E-02 -2.3691320648584660E-02 -2.3680008450895913E-02 -2.3668687029123840E-02 -2.3657356391784245E-02 -2.3646016548796868E-02 -2.3634667516700986E-02 -2.3623309313524795E-02 -2.3611941955600839E-02 -2.3600565458066412E-02 -2.3589179833772130E-02 -2.3577785091465048E-02 -2.3566381240639356E-02 -2.3554968296992627E-02 -2.3543546278229650E-02 -2.3532115201604056E-02 -2.3520675083956086E-02 -2.3509225939347053E-02 -2.3497767775271305E-02 -2.3486300599334795E-02 -2.3474824426721736E-02 -2.3463339275858686E-02 -2.3451845163929758E-02 -2.3440342106673315E-02 -2.3428830118676209E-02 -2.3417309211152142E-02 -2.3405779394775176E-02 -2.3394240681420882E-02 -2.3382693083711367E-02 -2.3371136617783460E-02 -2.3359571304990393E-02 -2.3347997164555497E-02 -2.3336414204951229E-02 -2.3324822432262755E-02 -2.3313221858747832E-02 -2.3301612501209674E-02 -2.3289994377043360E-02 -2.3278367504585489E-02 -2.3266731900796828E-02 -2.3255087574252369E-02 -2.3243434530924419E-02 -2.3231772783938610E-02 -2.3220102353213604E-02 -2.3208423257475578E-02 -2.3196735511736816E-02 -2.3185039130016637E-02 -2.3173334123173562E-02 -2.3161620500711636E-02 -2.3149898275879949E-02 -2.3138167466524487E-02 -2.3126428090049989E-02 -2.3114680161423005E-02 -2.3102923694929247E-02 -2.3091158703076809E-02 -2.3079385197315842E-02 -2.3067603190170306E-02 -2.3055812695889823E-02 -2.3044013729451432E-02 -2.3032206308429549E-02 -2.3020390450802453E-02 -2.3008566169480202E-02 -2.2996733473417463E-02 -2.2984892373690110E-02 -2.2973042885975542E-02 -2.2961185026718192E-02 -2.2949318813564840E-02 -2.2937444264406560E-02 -2.2925561392261748E-02 -2.2913670205227055E-02 -2.2901770713040878E-02 -2.2889862930503411E-02 -2.2877946873701933E-02 -2.2866022562325672E-02 -2.2854090017662188E-02 -2.2842149253796244E-02 -2.2830200275404677E-02 -2.2818243089172650E-02 -2.2806277711358850E-02 -2.2794304160409364E-02 -2.2782322454984422E-02 -2.2770332613830796E-02 -2.2758334651762968E-02 -2.2746328576947496E-02 -2.2734314398086083E-02 -2.2722292129594916E-02 -2.2710261787740074E-02 -2.2698223390770773E-02 -2.2686176958568491E-02 -2.2674122506871838E-02 -2.2662060042162455E-02 -2.2649989571081768E-02 -2.2637911109424494E-02 -2.2625824676643636E-02 -2.2613730291508261E-02 -2.2601627972038463E-02 -2.2589517733361930E-02 -2.2577399582278709E-02 -2.2565273525154337E-02 -2.2553139578013210E-02 -2.2540997761935605E-02 -2.2528848095902894E-02 -2.2516690595918595E-02 -2.2504525276422150E-02 -2.2492352146618284E-02 -2.2480171214850991E-02 -2.2467982494700219E-02 -2.2455786003350978E-02 -2.2443581758922783E-02 -2.2431369781092156E-02 -2.2419150087793004E-02 -2.2406922687009979E-02 -2.2394687583939983E-02 -2.2382444792174473E-02 -2.2370194332749841E-02 -2.2357936225508409E-02 -2.2345670486864196E-02 -2.2333397131966620E-02 -2.2321116170525190E-02 -2.2308827610084903E-02 -2.2296531463472217E-02 -2.2284227749566864E-02 -2.2271916487151135E-02 -2.2259597693665908E-02 -2.2247271385787609E-02 -2.2234937575293975E-02 -2.2222596271250974E-02 -2.2210247485327905E-02 -2.2197891233089528E-02 -2.2185527531050249E-02 -2.2173156398382649E-02 -2.2160777854410469E-02 -2.2148391910918070E-02 -2.2135998574213042E-02 -2.2123597854854259E-02 -2.2111189771818151E-02 -2.2098774344531977E-02 -2.2086351589589499E-02 -2.2073921522466459E-02 -2.2061484155936929E-02 -2.2049039500229642E-02 -2.2036587567289580E-02 -2.2024128373647752E-02 -2.2011661936601250E-02 -2.1999188273853325E-02 -2.1986707403171008E-02 -2.1974219338165322E-02 -2.1961724087385590E-02 -2.1949221660976837E-02 -2.1936712075465443E-02 -2.1924195348685619E-02 -2.1911671498164979E-02 -2.1899140541203146E-02 -2.1886602492360456E-02 -2.1874057361885316E-02 -2.1861505160606844E-02 -2.1848945903665096E-02 -2.1836379607442644E-02 -2.1823806288821315E-02 -2.1811225965060143E-02 -2.1798638651733399E-02 -2.1786044360935026E-02 -2.1773443104546281E-02 -2.1760834895746255E-02 -2.1748219748365296E-02 -2.1735597680093244E-02 -2.1722968712490236E-02 -2.1710332863414058E-02 -2.1697690140251635E-02 -2.1685040549690383E-02 -2.1672384107091686E-02 -2.1659720832059332E-02 -2.1647050743304187E-02 -2.1634373858341195E-02 -2.1621690192830029E-02 -2.1608999756035543E-02 -2.1596302556373560E-02 -2.1583598609056995E-02 -2.1570887933634261E-02 -2.1558170548224374E-02 -2.1545446468426283E-02 -2.1532715709090291E-02 -2.1519978282618393E-02 -2.1507234200789635E-02 -2.1494483477304552E-02 -2.1481726127462963E-02 -2.1468962167858856E-02 -2.1456191617819972E-02 -2.1443414495854837E-02 -2.1430630812782184E-02 -2.1417840576520089E-02 -2.1405043799538351E-02 -2.1392240499181692E-02 -2.1379430693405383E-02 -2.1366614401243603E-02 -2.1353791641115595E-02 -2.1340962424225722E-02 -2.1328126758096894E-02 -2.1315284655008516E-02 -2.1302436133850872E-02 -2.1289581213586522E-02 -2.1276719911588787E-02 -2.1263852244536238E-02 -2.1250978225202877E-02 -2.1238097863716450E-02 -2.1225211171929804E-02 -2.1212318164877699E-02 -2.1199418858683507E-02 -2.1186513273400320E-02 -2.1173601429926144E-02 -2.1160683341279355E-02 -2.1147759013539973E-02 -2.1134828456070665E-02 -2.1121891686492662E-02 -2.1108948723799995E-02 -2.1095999588320369E-02 -2.1083044300696255E-02 -2.1070082874058944E-02 -2.1057115312994819E-02 -2.1044141625306770E-02 -2.1031161830230075E-02 -2.1018175948913004E-02 -2.1005183999599171E-02 -2.0992185998853587E-02 -2.0979181960562119E-02 -2.0966171894698828E-02 -2.0953155812119963E-02 -2.0940133728645272E-02 -2.0927105661474592E-02 -2.0914071629067148E-02 -2.0901031650764287E-02 -2.0887985742095799E-02 -2.0874933911267247E-02 -2.0861876167004276E-02 -2.0848812525534246E-02 -2.0835743005696478E-02 -2.0822667626596153E-02 -2.0809586407576509E-02 -2.0796499364520306E-02 -2.0783406504602482E-02 -2.0770307834867816E-02 -2.0757203371547725E-02 -2.0744093135057522E-02 -2.0730977145191839E-02 -2.0717855420967154E-02 -2.0704727978734211E-02 -2.0691594826114618E-02 -2.0678455969757831E-02 -2.0665311425175612E-02 -2.0652161213154458E-02 -2.0639005353251413E-02 -2.0625843862986756E-02 -2.0612676758219879E-02 -2.0599504048193072E-02 -2.0586325740774167E-02 -2.0573141850925267E-02 -2.0559952399093057E-02 -2.0546757404748695E-02 -2.0533556885080729E-02 -2.0520350856190431E-02 -2.0507139329325259E-02 -2.0493922314095258E-02 -2.0480699823880337E-02 -2.0467471875829642E-02 -2.0454238487659003E-02 -2.0440999678167739E-02 -2.0427755465580608E-02 -2.0414505861951177E-02 -2.0401250876402266E-02 -2.0387990521312658E-02 -2.0374724813283129E-02 -2.0361453769990955E-02 -2.0348177411967091E-02 -2.0334895759577584E-02 -2.0321608824014820E-02 -2.0308316610701121E-02 -2.0295019130367353E-02 -2.0281716402763467E-02 -2.0268408448290021E-02 -2.0255095286360845E-02 -2.0241776935656677E-02 -2.0228453407582784E-02 -2.0215124707575329E-02 -2.0201790845918846E-02 -2.0188451843857775E-02 -2.0175107723352129E-02 -2.0161758501655584E-02 -2.0148404194037416E-02 -2.0135044812836660E-02 -2.0121680367285635E-02 -2.0108310868959135E-02 -2.0094936336607989E-02 -2.0081556790101925E-02 -2.0068172247855006E-02 -2.0054782727426664E-02 -2.0041388242188096E-02 -2.0027988799773279E-02 -2.0014584409724735E-02 -2.0001175090514463E-02 -1.9987760862604377E-02 -1.9974341744535901E-02 -1.9960917753514114E-02 -1.9947488903758592E-02 -1.9934055204217961E-02 -1.9920616664881863E-02 -1.9907173303902376E-02 -1.9893725141903545E-02 -1.9880272196783885E-02 -1.9866814484045724E-02 -1.9853352017874137E-02 -1.9839884809573129E-02 -1.9826412870602179E-02 -1.9812936216356426E-02 -1.9799454863929936E-02 -1.9785968831152405E-02 -1.9772478136677728E-02 -1.9758982797471947E-02 -1.9745482825155241E-02 -1.9731978230592362E-02 -1.9718469027263378E-02 -1.9704955230165105E-02 -1.9691436857405539E-02 -1.9677913931615949E-02 -1.9664386472822155E-02 -1.9650854488820039E-02 -1.9637317984906127E-02 -1.9623776975298487E-02 -1.9610231480659216E-02 -1.9596681521255547E-02 -1.9583127116332408E-02 -1.9569568283369535E-02 -1.9556005030703972E-02 -1.9542437363945096E-02 -1.9528865297246220E-02 -1.9515288852733056E-02 -1.9501708051343984E-02 -1.9488122910295794E-02 -1.9474533445594459E-02 -1.9460939668433926E-02 -1.9447341587947926E-02 -1.9433739217466755E-02 -1.9420132575384566E-02 -1.9406521680409922E-02 -1.9392906551296166E-02 -1.9379287206244086E-02 -1.9365663657602804E-02 -1.9352035914296638E-02 -1.9338403988294180E-02 -1.9324767896374825E-02 -1.9311127656218893E-02 -1.9297483287654342E-02 -1.9283834810665122E-02 -1.9270182238674372E-02 -1.9256525580076230E-02 -1.9242864846053892E-02 -1.9229200053710028E-02 -1.9215531220942345E-02 -1.9201858366116441E-02 -1.9188181507603465E-02 -1.9174500659982194E-02 -1.9160815834066883E-02 -1.9147127041459849E-02 -1.9133434296298688E-02 -1.9119737613912884E-02 -1.9106037015909995E-02 -1.9092332526706612E-02 -1.9078624161664622E-02 -1.9064911924520225E-02 -1.9051195821612153E-02 -1.9037475871232164E-02 -1.9023752094298976E-02 -1.9010024511423258E-02 -1.8996293142943703E-02 -1.8982558003610022E-02 -1.8968819098902721E-02 -1.8955076436015288E-02 -1.8941330034454099E-02 -1.8927579917107619E-02 -1.8913826102287513E-02 -1.8900068604552647E-02 -1.8886307437833181E-02 -1.8872542614936570E-02 -1.8858774148757699E-02 -1.8845002053694718E-02 -1.8831226344849312E-02 -1.8817447040118580E-02 -1.8803664160348767E-02 -1.8789877723620965E-02 -1.8776087739703701E-02 -1.8762294217482069E-02 -1.8748497171051447E-02 -1.8734696617263479E-02 -1.8720892575319191E-02 -1.8707085067592884E-02 -1.8693274113537946E-02 -1.8679459720591186E-02 -1.8665641894074533E-02 -1.8651820648594421E-02 -1.8637996005012564E-02 -1.8624167983549593E-02 -1.8610336603083998E-02 -1.8596501880816754E-02 -1.8582663826069389E-02 -1.8568822446032227E-02 -1.8554977754839073E-02 -1.8541129772677262E-02 -1.8527278519530482E-02 -1.8513424014440973E-02 -1.8499566275197086E-02 -1.8485705311836513E-02 -1.8471841131336219E-02 -1.8457973746816812E-02 -1.8444103178319314E-02 -1.8430229445931954E-02 -1.8416352568758364E-02 -1.8402472564944868E-02 -1.8388589445315351E-02 -1.8374703216744989E-02 -1.8360813891373909E-02 -1.8346921489052408E-02 -1.8333026029962798E-02 -1.8319127533163192E-02 -1.8305226016953731E-02 -1.8291321493281186E-02 -1.8277413969559425E-02 -1.8263503456664824E-02 -1.8249589972200043E-02 -1.8235673534965777E-02 -1.8221754166245933E-02 -1.8207831887751918E-02 -1.8193906712689435E-02 -1.8179978646382110E-02 -1.8166047697605964E-02 -1.8152113884430880E-02 -1.8138177226374591E-02 -1.8124237743202584E-02 -1.8110295454638613E-02 -1.8096350375406824E-02 -1.8082402514248939E-02 -1.8068451881343126E-02 -1.8054498492750898E-02 -1.8040542365946041E-02 -1.8026583520515581E-02 -1.8012621977206499E-02 -1.7998657751546496E-02 -1.7984690850960983E-02 -1.7970721283939797E-02 -1.7956749066720085E-02 -1.7942774217826460E-02 -1.7928796758102335E-02 -1.7914816710121791E-02 -1.7900834090460584E-02 -1.7886848903513334E-02 -1.7872861154381268E-02 -1.7858870861007573E-02 -1.7844878045950162E-02 -1.7830882729715104E-02 -1.7816884930770598E-02 -1.7802884664639779E-02 -1.7788881939263566E-02 -1.7774876762434135E-02 -1.7760869150762158E-02 -1.7746859125073754E-02 -1.7732846704649544E-02 -1.7718831906766611E-02 -1.7704814747018988E-02 -1.7690795235517396E-02 -1.7676773381622386E-02 -1.7662749199857060E-02 -1.7648722708018223E-02 -1.7634693925690881E-02 -1.7620662875326321E-02 -1.7606629576917540E-02 -1.7592594037566116E-02 -1.7578556261140136E-02 -1.7564516260858448E-02 -1.7550474057554586E-02 -1.7536429671957739E-02 -1.7522383124095094E-02 -1.7508334432560172E-02 -1.7494283607392809E-02 -1.7480230655511502E-02 -1.7466175589750291E-02 -1.7452118429165477E-02 -1.7438059192995167E-02 -1.7423997900155332E-02 -1.7409934568754996E-02 -1.7395869210363579E-02 -1.7381801833280492E-02 -1.7367732450133549E-02 -1.7353661079457555E-02 -1.7339587740209141E-02 -1.7325512451349105E-02 -1.7311435231340232E-02 -1.7297356092528395E-02 -1.7283275043198858E-02 -1.7269192095178885E-02 -1.7255107266658829E-02 -1.7241020576555334E-02 -1.7226932044191220E-02 -1.7212841688644891E-02 -1.7198749522273998E-02 -1.7184655551626918E-02 -1.7170559787129669E-02 -1.7156462248577323E-02 -1.7142362956671951E-02 -1.7128261929325705E-02 -1.7114159183178178E-02 -1.7100054732003361E-02 -1.7085948586377523E-02 -1.7071840758045763E-02 -1.7057731262827343E-02 -1.7043620117638714E-02 -1.7029507342459223E-02 -1.7015392958817665E-02 -1.7001276981480816E-02 -1.6987159415425526E-02 -1.6973040267909741E-02 -1.6958919558586059E-02 -1.6944797310005200E-02 -1.6930673541291099E-02 -1.6916548269097414E-02 -1.6902421507618649E-02 -1.6888293266534075E-02 -1.6874163555969244E-02 -1.6860032391205728E-02 -1.6845899789379816E-02 -1.6831765769682691E-02 -1.6817630353188312E-02 -1.6803493557063325E-02 -1.6789355388680038E-02 -1.6775215855225921E-02 -1.6761074973483961E-02 -1.6746932764492954E-02 -1.6732789247607363E-02 -1.6718644440153224E-02 -1.6704498357584061E-02 -1.6690351009621036E-02 -1.6676202405414859E-02 -1.6662052560252258E-02 -1.6647901493019819E-02 -1.6633749222577668E-02 -1.6619595767674796E-02 -1.6605441145589740E-02 -1.6591285367212518E-02 -1.6577128441903930E-02 -1.6562970382203872E-02 -1.6548811203092435E-02 -1.6534650922605761E-02 -1.6520489564780708E-02 -1.6506327151914774E-02 -1.6492163691876931E-02 -1.6477999187694187E-02 -1.6463833651544340E-02 -1.6449667104593071E-02 -1.6435499567705222E-02 -1.6421331059956915E-02 -1.6407161599167479E-02 -1.6392991195431462E-02 -1.6378819855310738E-02 -1.6364647591732184E-02 -1.6350474425711244E-02 -1.6336300377558049E-02 -1.6322125463285764E-02 -1.6307949697815256E-02 -1.6293773094384865E-02 -1.6279595665197728E-02 -1.6265417423667543E-02 -1.6251238385219236E-02 -1.6237058565996190E-02 -1.6222877984640321E-02 -1.6208696660218600E-02 -1.6194514606823373E-02 -1.6180331834528269E-02 -1.6166148354958162E-02 -1.6151964183305251E-02 -1.6137779335812136E-02 -1.6123593832457147E-02 -1.6109407694388247E-02 -1.6095220935609542E-02 -1.6081033562664385E-02 -1.6066845584840193E-02 -1.6052657020160711E-02 -1.6038467888116671E-02 -1.6024278207647798E-02 -1.6010087997317783E-02 -1.5995897271730456E-02 -1.5981706040154881E-02 -1.5967514312749793E-02 -1.5953322104442686E-02 -1.5939129431510348E-02 -1.5924936312990530E-02 -1.5910742769709607E-02 -1.5896548818097090E-02 -1.5882354466836918E-02 -1.5868159725120862E-02 -1.5853964608644484E-02 -1.5839769135205777E-02 -1.5825573323588277E-02 -1.5811377193409096E-02 -1.5797180760719582E-02 -1.5782984033351519E-02 -1.5768787019176549E-02 -1.5754589734137212E-02 -1.5740392197540313E-02 -1.5726194428601761E-02 -1.5711996446422433E-02 -1.5697798267545301E-02 -1.5683599900790504E-02 -1.5669401354153584E-02 -1.5655202641541927E-02 -1.5641003780138128E-02 -1.5626804789225963E-02 -1.5612605691058342E-02 -1.5598406505241134E-02 -1.5584207239746867E-02 -1.5570007900174191E-02 -1.5555808499648703E-02 -1.5541609056643053E-02 -1.5527409589934172E-02 -1.5513210118654069E-02 -1.5499010660597480E-02 -1.5484811226092363E-02 -1.5470611823250805E-02 -1.5456412466208434E-02 -1.5442213174623510E-02 -1.5428013967294612E-02 -1.5413814860416885E-02 -1.5399615869376037E-02 -1.5385417006479260E-02 -1.5371218282720004E-02 -1.5357019710991768E-02 -1.5342821306442973E-02 -1.5328623085717004E-02 -1.5314425069887141E-02 -1.5300227279903766E-02 -1.5286029726339327E-02 -1.5271832413822182E-02 -1.5257635353264036E-02 -1.5243438565301184E-02 -1.5229242070758351E-02 -1.5215045887711718E-02 -1.5200850033135037E-02 -1.5186654518811243E-02 -1.5172459352620425E-02 -1.5158264545314198E-02 -1.5144070113554493E-02 -1.5129876075146516E-02 -1.5115682450484365E-02 -1.5101489260536845E-02 -1.5087296518309048E-02 -1.5073104229041118E-02 -1.5058912401440683E-02 -1.5044721054142030E-02 -1.5030530207146241E-02 -1.5016339878562837E-02 -1.5002150085509404E-02 -1.4987960841837407E-02 -1.4973772157294151E-02 -1.4959584042442615E-02 -1.4945396511598317E-02 -1.4931209580358379E-02 -1.4917023269463725E-02 -1.4902837602735341E-02 -1.4888652595828921E-02 -1.4874468251013670E-02 -1.4860284572598694E-02 -1.4846101580157209E-02 -1.4831919297412489E-02 -1.4817737743315500E-02 -1.4803556932966488E-02 -1.4789376879879973E-02 -1.4775197594430084E-02 -1.4761019087147779E-02 -1.4746841372074793E-02 -1.4732664464746734E-02 -1.4718488383991644E-02 -1.4704313152047569E-02 -1.4690138786692116E-02 -1.4675965292746486E-02 -1.4661792674311364E-02 -1.4647620948663882E-02 -1.4633450139687820E-02 -1.4619280266984447E-02 -1.4605111344344793E-02 -1.4590943384883906E-02 -1.4576776400709942E-02 -1.4562610403794595E-02 -1.4548445407303590E-02 -1.4534281425225584E-02 -1.4520118474205370E-02 -1.4505956575479146E-02 -1.4491795748779748E-02 -1.4477636004001213E-02 -1.4463477348253042E-02 -1.4449319793805289E-02 -1.4435163357354071E-02 -1.4421008056569238E-02 -1.4406853911009005E-02 -1.4392700939273832E-02 -1.4378549151714191E-02 -1.4364398555446863E-02 -1.4350249162763288E-02 -1.4336100991684272E-02 -1.4321954060526483E-02 -1.4307808387605401E-02 -1.4293663990496400E-02 -1.4279520879891972E-02 -1.4265379062847481E-02 -1.4251238551442370E-02 -1.4237099364978729E-02 -1.4222961522786721E-02 -1.4208825042084525E-02 -1.4194689939165308E-02 -1.4180556225122111E-02 -1.4166423907416218E-02 -1.4152292997488037E-02 -1.4138163514297891E-02 -1.4124035477230597E-02 -1.4109908903561681E-02 -1.4095783809637448E-02 -1.4081660207459721E-02 -1.4067538105077885E-02 -1.4053417512980651E-02 -1.4039298447939556E-02 -1.4025180927839201E-02 -1.4011064971854215E-02 -1.3996950599542922E-02 -1.3982837824549937E-02 -1.3968726653564552E-02 -1.3954617094959968E-02 -1.3940509163823214E-02 -1.3926402876912793E-02 -1.3912298254223696E-02 -1.3898195317506495E-02 -1.3884094081632702E-02 -1.3869994550981009E-02 -1.3855896731744345E-02 -1.3841800641734714E-02 -1.3827706301699837E-02 -1.3813613729541385E-02 -1.3799522941007968E-02 -1.3785433950061904E-02 -1.3771346767233886E-02 -1.3757261403113608E-02 -1.3743177870970957E-02 -1.3729096185219601E-02 -1.3715016364206583E-02 -1.3700938430084464E-02 -1.3686862400603610E-02 -1.3672788281652103E-02 -1.3658716078371821E-02 -1.3644645805038619E-02 -1.3630577480272563E-02 -1.3616511123270279E-02 -1.3602446753917283E-02 -1.3588384389200065E-02 -1.3574324035922212E-02 -1.3560265699426583E-02 -1.3546209393183047E-02 -1.3532155135690881E-02 -1.3518102945875276E-02 -1.3504052843230925E-02 -1.3490004845388780E-02 -1.3475958961101035E-02 -1.3461915196917605E-02 -1.3447873565225811E-02 -1.3433834083087931E-02 -1.3419796768212713E-02 -1.3405761639398318E-02 -1.3391728714183810E-02 -1.3377698001389070E-02 -1.3363669506772639E-02 -1.3349643243288405E-02 -1.3335619231323115E-02 -1.3321597490157860E-02 -1.3307578035039364E-02 -1.3293560880216970E-02 -1.3279546037382779E-02 -1.3265533516975070E-02 -1.3251523331094072E-02 -1.3237515494067724E-02 -1.3223510021547433E-02 -1.3209506933527895E-02 -1.3195506250220986E-02 -1.3181507982372479E-02 -1.3167512134550755E-02 -1.3153518716029268E-02 -1.3139527744398850E-02 -1.3125539238326604E-02 -1.3111553217728014E-02 -1.3097569702403430E-02 -1.3083588703344844E-02 -1.3069610224061216E-02 -1.3055634272290602E-02 -1.3041660865864944E-02 -1.3027690023907891E-02 -1.3013721764914785E-02 -1.2999756106921138E-02 -1.2985793062456279E-02 -1.2971832638004074E-02 -1.2957874842493661E-02 -1.2943919693082345E-02 -1.2929967208373928E-02 -1.2916017406204617E-02 -1.2902070303897359E-02 -1.2888125914064475E-02 -1.2874184242641126E-02 -1.2860245297153074E-02 -1.2846309093499151E-02 -1.2832375649792562E-02 -1.2818444985796899E-02 -1.2804517122369451E-02 -1.2790592073873093E-02 -1.2776669842659941E-02 -1.2762750432473390E-02 -1.2748833861427562E-02 -1.2734920152211957E-02 -1.2721009323390119E-02 -1.2707101389776800E-02 -1.2693196364167301E-02 -1.2679294254805741E-02 -1.2665395070063689E-02 -1.2651498824118756E-02 -1.2637605533741911E-02 -1.2623715216794675E-02 -1.2609827892399070E-02 -1.2595943576763802E-02 -1.2582062276535116E-02 -1.2568183997299530E-02 -1.2554308753168647E-02 -1.2540436563154744E-02 -1.2526567445617883E-02 -1.2512701417842867E-02 -1.2498838495260811E-02 -1.2484978685741596E-02 -1.2471121995542501E-02 -1.2457268436827531E-02 -1.2443418026185857E-02 -1.2429570781701899E-02 -1.2415726724192113E-02 -1.2401885872567422E-02 -1.2388048232935159E-02 -1.2374213807269951E-02 -1.2360382607030509E-02 -1.2346554652826851E-02 -1.2332729964718535E-02 -1.2318908560378993E-02 -1.2305090456002006E-02 -1.2291275659177875E-02 -1.2277464173660865E-02 -1.2263656010815600E-02 -1.2249851191504424E-02 -1.2236049735627091E-02 -1.2222251657731140E-02 -1.2208456971008239E-02 -1.2194665686398919E-02 -1.2180877813489477E-02 -1.2167093363779923E-02 -1.2153312351884564E-02 -1.2139534793437014E-02 -1.2125760707464310E-02 -1.2111990113403233E-02 -1.2098223021786142E-02 -1.2084459436090763E-02 -1.2070699364531990E-02 -1.2056942825686239E-02 -1.2043189838966704E-02 -1.2029440420871423E-02 -1.2015694586631993E-02 -1.2001952347830577E-02 -1.1988213712308769E-02 -1.1974478689687085E-02 -1.1960747294983788E-02 -1.1947019544266508E-02 -1.1933295454642910E-02 -1.1919575043637673E-02 -1.1905858324461605E-02 -1.1892145304606937E-02 -1.1878435992781225E-02 -1.1864730403629623E-02 -1.1851028553257793E-02 -1.1837330458849377E-02 -1.1823636138242877E-02 -1.1809945605160953E-02 -1.1796258866238443E-02 -1.1782575928746940E-02 -1.1768896806559173E-02 -1.1755221515690974E-02 -1.1741550073995331E-02 -1.1727882500860888E-02 -1.1714218811469531E-02 -1.1700559011449820E-02 -1.1686903106279291E-02 -1.1673251109115252E-02 -1.1659603036312022E-02 -1.1645958905666769E-02 -1.1632318736539169E-02 -1.1618682544941226E-02 -1.1605050336715338E-02 -1.1591422116742153E-02 -1.1577797898295970E-02 -1.1564177699162003E-02 -1.1550561537338348E-02 -1.1536949431062758E-02 -1.1523341395964061E-02 -1.1509737437259800E-02 -1.1496137558330042E-02 -1.1482541772167006E-02 -1.1468950098456415E-02 -1.1455362555773466E-02 -1.1441779160409137E-02 -1.1428199927031035E-02 -1.1414624862974402E-02 -1.1401053973479111E-02 -1.1387487270153119E-02 -1.1373924770345361E-02 -1.1360366491821584E-02 -1.1346812452854909E-02 -1.1333262670397462E-02 -1.1319717151356313E-02 -1.1306175898498815E-02 -1.1292638922517386E-02 -1.1279106243335406E-02 -1.1265577879997411E-02 -1.1252053847100558E-02 -1.1238534158079620E-02 -1.1225018823590033E-02 -1.1211507852718657E-02 -1.1198001255841835E-02 -1.1184499045301513E-02 -1.1171001234894066E-02 -1.1157507843918200E-02 -1.1144018892428040E-02 -1.1130534390426109E-02 -1.1117054340488059E-02 -1.1103578750126179E-02 -1.1090107636848673E-02 -1.1076641019058676E-02 -1.1063178913658397E-02 -1.1049721336749797E-02 -1.1036268298715591E-02 -1.1022819804462635E-02 -1.1009375862116855E-02 -1.0995936488640969E-02 -1.0982501702145472E-02 -1.0969071518785244E-02 -1.0955645953674284E-02 -1.0942225017534946E-02 -1.0928808715664479E-02 -1.0915397055641516E-02 -1.0901990053983835E-02 -1.0888587728913110E-02 -1.0875190096460765E-02 -1.0861797171278411E-02 -1.0848408965257645E-02 -1.0835025485901978E-02 -1.0821646741464777E-02 -1.0808272745430529E-02 -1.0794903512854406E-02 -1.0781539059983889E-02 -1.0768179403986326E-02 -1.0754824558380692E-02 -1.0741474529016392E-02 -1.0728129322041405E-02 -1.0714788951352144E-02 -1.0701453433782425E-02 -1.0688122785990635E-02 -1.0674797024446981E-02 -1.0661476163132627E-02 -1.0648160209204456E-02 -1.0634849169187523E-02 -1.0621543054072284E-02 -1.0608241877158326E-02 -1.0594945654829232E-02 -1.0581654407507470E-02 -1.0568368152441035E-02 -1.0555086894229933E-02 -1.0541810635328816E-02 -1.0528539387046178E-02 -1.0515273166459461E-02 -1.0502011991134187E-02 -1.0488755879300753E-02 -1.0475504847168481E-02 -1.0462258900698579E-02 -1.0449018043083496E-02 -1.0435782283927381E-02 -1.0422551638240190E-02 -1.0409326122739681E-02 -1.0396105757577162E-02 -1.0382890561376630E-02 -1.0369680539560741E-02 -1.0356475692515039E-02 -1.0343276029553984E-02 -1.0330081569702668E-02 -1.0316892331481703E-02 -1.0303708330487838E-02 -1.0290529581063163E-02 -1.0277356091016276E-02 -1.0264187864778628E-02 -1.0251024911849484E-02 -1.0237867248879441E-02 -1.0224714892777959E-02 -1.0211567859368526E-02 -1.0198426163729991E-02 -1.0185289814804373E-02 -1.0172158817314834E-02 -1.0159033179506775E-02 -1.0145912916192977E-02 -1.0132798043116779E-02 -1.0119688577255667E-02 -1.0106584535623585E-02 -1.0093485928205387E-02 -1.0080392758701576E-02 -1.0067305034558443E-02 -1.0054222772688297E-02 -1.0041145990815809E-02 -1.0028074702598864E-02 -1.0015008919870881E-02 -1.0001948652805331E-02 -9.9888939096664364E-03 -9.9758446998653143E-03 -9.9628010367749341E-03 -9.9497629346887856E-03 -9.9367304092764924E-03 -9.9237034769067058E-03 -9.9106821493616607E-03 -9.8976664315606876E-03 -9.8846563296613090E-03 -9.8716518574289442E-03 -9.8586530306484128E-03 -9.8456598652298197E-03 -9.8326723771448975E-03 -9.8196905786100200E-03 -9.8067144745417195E-03 -9.7937440703984874E-03 -9.7807793794802058E-03 -9.7678204178388139E-03 -9.7548672012696958E-03 -9.7419197453141402E-03 -9.7289780626523843E-03 -9.7160421586870716E-03 -9.7031120386198173E-03 -9.6901877149293287E-03 -9.6772692034760091E-03 -9.6643565200210980E-03 -9.6514496801803525E-03 -9.6385486973151781E-03 -9.6256535771695757E-03 -9.6127643244939727E-03 -9.5998809506868607E-03 -9.5870034711855023E-03 -9.5741319016336892E-03 -9.5612662579133527E-03 -9.5484065541488923E-03 -9.5355527963863502E-03 -9.5227049887982515E-03 -9.5098631420283079E-03 -9.4970272718079094E-03 -9.4841973938001155E-03 -9.4713735232418786E-03 -9.4585556741728985E-03 -9.4457438536410983E-03 -9.4329380662671759E-03 -9.4201383216956543E-03 -9.4073446346729771E-03 -9.3945570203739746E-03 -9.3817754945226938E-03 -9.3690000720346028E-03 -9.3562307603072686E-03 -9.3434675631282570E-03 -9.3307104892277129E-03 -9.3179595538407847E-03 -9.3052147725376597E-03 -9.2924761605064927E-03 -9.2797437323005969E-03 -9.2670174960753204E-03 -9.2542974558962564E-03 -9.2415836196844108E-03 -9.2288760020191093E-03 -9.2161746181210324E-03 -9.2034794831897301E-03 -9.1907906120758630E-03 -9.1781080137995387E-03 -9.1654316925158259E-03 -9.1527616553678127E-03 -9.1400979164559075E-03 -9.1274404908080840E-03 -9.1147893934075096E-03 -9.1021446390311053E-03 -9.0895062374721173E-03 -9.0768741931463535E-03 -9.0642485125697371E-03 -9.0516292091927276E-03 -9.0390162977580079E-03 -9.0264097932721572E-03 -9.0138097107825433E-03 -9.0012160607914841E-03 -8.9886288474647063E-03 -8.9760480764339359E-03 -8.9634737609010588E-03 -8.9509059159009041E-03 -8.9383445562461056E-03 -8.9257896965585330E-03 -8.9132413478917524E-03 -8.9006995148481777E-03 -8.8881642027070912E-03 -8.8756354238588124E-03 -8.8631131930199895E-03 -8.8505975249680811E-03 -8.8380884345226618E-03 -8.8255859334612288E-03 -8.8130900263462056E-03 -8.8006007177117412E-03 -8.7881180193107120E-03 -8.7756419460119795E-03 -8.7631725125287448E-03 -8.7507097333800448E-03 -8.7382536207991478E-03 -8.7258041798739389E-03 -8.7133614149589988E-03 -8.7009253369281156E-03 -8.6884959603442564E-03 -8.6760732997781115E-03 -8.6636573697498019E-03 -8.6512481830192823E-03 -8.6388457449713043E-03 -8.6264500594985718E-03 -8.6140611366854174E-03 -8.6016789911613593E-03 -8.5893036374889379E-03 -8.5769350898990057E-03 -8.5645733613624458E-03 -8.5522184579575281E-03 -8.5398703835983577E-03 -8.5275291474252671E-03 -8.5151947635347149E-03 -8.5028672462345752E-03 -8.4905466098734693E-03 -8.4782328679109988E-03 -8.4659260269495072E-03 -8.4536260905585681E-03 -8.4413330669677322E-03 -8.4290469701241138E-03 -8.4167678142829157E-03 -8.4044956135642442E-03 -8.3922303814767812E-03 -8.3799721253294771E-03 -8.3677208487511184E-03 -8.3554765592380228E-03 -8.3432392704862815E-03 -8.3310089966598111E-03 -8.3187857515602294E-03 -8.3065695485385633E-03 -8.2943603956096013E-03 -8.2821582966364701E-03 -8.2699632584182399E-03 -8.2577752940363597E-03 -8.2455944173718161E-03 -8.2334206424520291E-03 -8.2212539831329669E-03 -8.2090944479810794E-03 -8.1969420402321028E-03 -8.1847967655802080E-03 -8.1726586370352693E-03 -8.1605276687966664E-03 -8.1484038747267774E-03 -8.1362872684103450E-03 -8.1241778590889924E-03 -8.1120756503539268E-03 -8.0999806473750005E-03 -8.0878928624023554E-03 -8.0758123092757456E-03 -8.0637390017092442E-03 -8.0516729532887927E-03 -8.0396141740081192E-03 -8.0275626678058438E-03 -8.0155184394153766E-03 -8.0034815002464638E-03 -7.9914518637389988E-03 -7.9794295435090638E-03 -7.9674145533038410E-03 -7.9554069038548676E-03 -7.9434065992408636E-03 -7.9314136436314520E-03 -7.9194280475893206E-03 -7.9074498242630957E-03 -7.8954789872753509E-03 -7.8835155507476426E-03 -7.8715595261701250E-03 -7.8596109173042997E-03 -7.8476697272966776E-03 -7.8357359663093831E-03 -7.8238096481980587E-03 -7.8118907866000405E-03 -7.7999793948042538E-03 -7.7880754842847748E-03 -7.7761790595649114E-03 -7.7642901239522045E-03 -7.7524086867166650E-03 -7.7405347612141302E-03 -7.7286683608071951E-03 -7.7168094987270673E-03 -7.7049581868950442E-03 -7.6931144304808047E-03 -7.6812782327356187E-03 -7.6694496020031991E-03 -7.6576285511383664E-03 -7.6458150932501882E-03 -7.6340092416795026E-03 -7.6222110088400965E-03 -7.6104204003801098E-03 -7.5986374191957303E-03 -7.5868620727756351E-03 -7.5750943738659192E-03 -7.5633343354992123E-03 -7.5515819707065064E-03 -7.5398372918807754E-03 -7.5281003052193127E-03 -7.5163710135107160E-03 -7.5046494235496159E-03 -7.4929355481003004E-03 -7.4812294003118044E-03 -7.4695309929358944E-03 -7.4578403382207677E-03 -7.4461574428815770E-03 -7.4344823096235092E-03 -7.4228149444262211E-03 -7.4111553597294823E-03 -7.3995035686294066E-03 -7.3878595838001654E-03 -7.3762234175337145E-03 -7.3645950772446827E-03 -7.3529745657579222E-03 -7.3413618882941763E-03 -7.3297570565632013E-03 -7.3181600832950772E-03 -7.3065709813262001E-03 -7.2949897634029728E-03 -7.2834164376052767E-03 -7.2718510063415776E-03 -7.2602934738317717E-03 -7.2487438515057498E-03 -7.2372021522774674E-03 -7.2256683888203693E-03 -7.2141425736036375E-03 -7.2026247153515544E-03 -7.1911148169030142E-03 -7.1796128820717101E-03 -7.1681189213532301E-03 -7.1566329471255026E-03 -7.1451549719397725E-03 -7.1336850084605776E-03 -7.1222230661821080E-03 -7.1107691480950296E-03 -7.0993232574895699E-03 -7.0878854042638181E-03 -7.0764556007784840E-03 -7.0650338593756965E-03 -7.0536201923709222E-03 -7.0422146096574536E-03 -7.0308171145955136E-03 -7.0194277101934960E-03 -7.0080464055322896E-03 -6.9966732126769630E-03 -6.9853081438545203E-03 -6.9739512114746693E-03 -6.9626024260458054E-03 -6.9512617912005194E-03 -6.9399293095190042E-03 -6.9286049892279353E-03 -6.9172888421671361E-03 -6.9059808804080372E-03 -6.8946811163119381E-03 -6.8833895608235397E-03 -6.8721062179352274E-03 -6.8608310898616472E-03 -6.8495641840301312E-03 -6.8383055121812907E-03 -6.8270550862735771E-03 -6.8158129184582878E-03 -6.8045790198855999E-03 -6.7933533950416186E-03 -6.7821360459357875E-03 -6.7709269793189263E-03 -6.7597262070080112E-03 -6.7485337409237314E-03 -6.7373495925729561E-03 -6.7261737727614896E-03 -6.7150062867210635E-03 -6.7038471368452424E-03 -6.6926963291880828E-03 -6.6815538748810441E-03 -6.6704197854782210E-03 -6.6592940727359922E-03 -6.6481767480077326E-03 -6.6370678169839128E-03 -6.6259672815322740E-03 -6.6148751467214649E-03 -6.6037914234742170E-03 -6.5927161233438622E-03 -6.5816492580058590E-03 -6.5705908388959764E-03 -6.5595408722942472E-03 -6.5484993599514820E-03 -6.5374663061603926E-03 -6.5264417215265113E-03 -6.5154256175538163E-03 -6.5044180057232583E-03 -6.4934188973550496E-03 -6.4824282993553523E-03 -6.4714462136200614E-03 -6.4604726438225778E-03 -6.4495075999864782E-03 -6.4385510933777056E-03 -6.4276031354129322E-03 -6.4166637375174191E-03 -6.4057329071796646E-03 -6.3948106461113692E-03 -6.3838969572051233E-03 -6.3729918501562333E-03 -6.3620953364033452E-03 -6.3512074271295602E-03 -6.3403281333062099E-03 -6.3294574629207548E-03 -6.3185954182771436E-03 -6.3077420021249529E-03 -6.2968972232461751E-03 -6.2860610925130180E-03 -6.2752336208961824E-03 -6.2644148194502640E-03 -6.2536046967661685E-03 -6.2428032552569309E-03 -6.2320104971626666E-03 -6.2212264306005195E-03 -6.2104510663730864E-03 -6.1996844153696254E-03 -6.1889264885672439E-03 -6.1781772950252889E-03 -6.1674368374084214E-03 -6.1567051175739681E-03 -6.1459821428266380E-03 -6.1352679237223510E-03 -6.1245624710149953E-03 -6.1138657957002865E-03 -6.1031779072841987E-03 -6.0924988085477470E-03 -6.0818285007629312E-03 -6.0711669906383112E-03 -6.0605142890813677E-03 -6.0498704068465241E-03 -6.0392353541542636E-03 -6.0286091402323473E-03 -6.0179917687543825E-03 -6.0073832415144159E-03 -5.9967835643694725E-03 -5.9861927472305079E-03 -5.9756108003718861E-03 -5.9650377345722505E-03 -5.9544735599118929E-03 -5.9439182800929110E-03 -5.9333718958198443E-03 -5.9228344121039517E-03 -5.9123058395223549E-03 -5.9017861888016193E-03 -5.8912754698935881E-03 -5.8807736921465395E-03 -5.8702808600009501E-03 -5.8597969748204323E-03 -5.8493220410797495E-03 -5.8388560685204574E-03 -5.8283990673528010E-03 -5.8179510476428055E-03 -5.8075120191260756E-03 -5.7970819867769509E-03 -5.7866609516677254E-03 -5.7762489173851812E-03 -5.7658458932400118E-03 -5.7554518892988481E-03 -5.7450669156514480E-03 -5.7346909822274415E-03 -5.7243240946142004E-03 -5.7139662537952027E-03 -5.7036174626214830E-03 -5.6932777299463951E-03 -5.6829470656908059E-03 -5.6726254797449336E-03 -5.6623129819002391E-03 -5.6520095783195567E-03 -5.6417152701968235E-03 -5.6314300598746753E-03 -5.6211539554748384E-03 -5.6108869665284162E-03 -5.6006291028766995E-03 -5.5903803745349801E-03 -5.5801407882963196E-03 -5.5699103452218146E-03 -5.5596890469466441E-03 -5.5494769010875087E-03 -5.5392739171844932E-03 -5.5290801049143034E-03 -5.5188954740627259E-03 -5.5087200318793246E-03 -5.4985537797057286E-03 -5.4883967188540635E-03 -5.4782488562533380E-03 -5.4681102012214440E-03 -5.4579807632340041E-03 -5.4478605519339782E-03 -5.4377495749791732E-03 -5.4276478338862481E-03 -5.4175553295581508E-03 -5.4074720682980191E-03 -5.3973980594098428E-03 -5.3873333121946254E-03 -5.3772778359019594E-03 -5.3672316383670945E-03 -5.3571947216194925E-03 -5.3471670865415316E-03 -5.3371487387283761E-03 -5.3271396871752592E-03 -5.3171399409785878E-03 -5.3071495092838440E-03 -5.2971684001814666E-03 -5.2871966159024663E-03 -5.2772341568845839E-03 -5.2672810280183563E-03 -5.2573372383434413E-03 -5.2474027969810020E-03 -5.2374777128614425E-03 -5.2275619941491219E-03 -5.2176556434856535E-03 -5.2077586611246627E-03 -5.1978710511754230E-03 -5.1879928223938013E-03 -5.1781239837440651E-03 -5.1682645439697240E-03 -5.1584145112832077E-03 -5.1485738888523026E-03 -5.1387426769077139E-03 -5.1289208788577621E-03 -5.1191085031090282E-03 -5.1093055584473020E-03 -5.0995120534271183E-03 -5.0897279962393528E-03 -5.0799533906027167E-03 -5.0701882368185723E-03 -5.0604325376297837E-03 -5.0506863008985322E-03 -5.0409495351013429E-03 -5.0312222486926508E-03 -5.0215044499437077E-03 -5.0117961431660994E-03 -5.0020973287502055E-03 -4.9924080088375204E-03 -4.9827281906815214E-03 -4.9730578824118644E-03 -4.9633970924369344E-03 -4.9537458292015371E-03 -4.9441040974483857E-03 -4.9344718971857859E-03 -4.9248492297416444E-03 -4.9152361022188912E-03 -4.9056325229962115E-03 -4.8960385004103097E-03 -4.8864540427277850E-03 -4.8768791550559305E-03 -4.8673138372708567E-03 -4.8577580900492365E-03 -4.8482119202057309E-03 -4.8386753363408490E-03 -4.8291483464863909E-03 -4.8196309581968674E-03 -4.8101231767754410E-03 -4.8006250026870270E-03 -4.7911364366047130E-03 -4.7816574845742227E-03 -4.7721881547474147E-03 -4.7627284549945402E-03 -4.7532783928815117E-03 -4.7438379741785537E-03 -4.7344071995725299E-03 -4.7249860693926223E-03 -4.7155745887265139E-03 -4.7061727651302610E-03 -4.6967806063994604E-03 -4.6873981206274661E-03 -4.6780253143307799E-03 -4.6686621879409298E-03 -4.6593087408587633E-03 -4.6499649776304778E-03 -4.6406309062638137E-03 -4.6313065345676393E-03 -4.6219918698855427E-03 -4.6126869184956671E-03 -4.6033916814805535E-03 -4.5941061585023871E-03 -4.5848303534487848E-03 -4.5755642738843699E-03 -4.5663079273021061E-03 -4.5570613207455649E-03 -4.5478244605181998E-03 -4.5385973482544575E-03 -4.5293799837390122E-03 -4.5201723701534689E-03 -4.5109745144991421E-03 -4.5017864239936169E-03 -4.4926081058958029E-03 -4.4834395669450947E-03 -4.4742808088730143E-03 -4.4651318307114638E-03 -4.4559926348422029E-03 -4.4468632285455736E-03 -4.4377436193027723E-03 -4.4286338138452633E-03 -4.4195338184242388E-03 -4.4104436354005837E-03 -4.4013632643662192E-03 -4.3922927071605522E-03 -4.3832319699725749E-03 -4.3741810595315407E-03 -4.3651399828895134E-03 -4.3561087470032501E-03 -4.3470873547002036E-03 -4.3380758049897323E-03 -4.3290740988407243E-03 -4.3200822424235815E-03 -4.3111002426674608E-03 -4.3021281062699023E-03 -4.2931658397217364E-03 -4.2842134461937072E-03 -4.2752709248928301E-03 -4.2663382763610275E-03 -4.2574155062849502E-03 -4.2485026213849612E-03 -4.2395996281742792E-03 -4.2307065329982123E-03 -4.2218233394712276E-03 -4.2129500469922643E-03 -4.2040866557087738E-03 -4.1952331706404901E-03 -4.1863895981473168E-03 -4.1775559446332704E-03 -4.1687322165187765E-03 -4.1599184178547433E-03 -4.1511145479240039E-03 -4.1423206062837096E-03 -4.1335365974841864E-03 -4.1247625278969993E-03 -4.1159984037919626E-03 -4.1072442313325654E-03 -4.0985000148802270E-03 -4.0897657540384588E-03 -4.0810414481771131E-03 -4.0723271010434103E-03 -4.0636227184976028E-03 -4.0549283065565208E-03 -4.0462438714187511E-03 -4.0375694178632201E-03 -4.0289049456268275E-03 -4.0202504537089710E-03 -4.0116059452803884E-03 -4.0029714261332269E-03 -3.9943469021765264E-03 -3.9857323794449014E-03 -3.9771278629025016E-03 -3.9685333524073826E-03 -3.9599488465562578E-03 -3.9513743478987763E-03 -3.9428098621978047E-03 -3.9342553952657873E-03 -3.9257109528212557E-03 -3.9171765398154264E-03 -3.9086521563992454E-03 -3.9001378009835938E-03 -3.8916334754806061E-03 -3.8831391854777558E-03 -3.8746549367124133E-03 -3.8661807348541921E-03 -3.8577165850246149E-03 -3.8492624876833351E-03 -3.8408184409617022E-03 -3.8323844459787044E-03 -3.8239605079233643E-03 -3.8155466322941766E-03 -3.8071428246672788E-03 -3.7987490902877162E-03 -3.7903654301288271E-03 -3.7819918423325958E-03 -3.7736283273893004E-03 -3.7652748900036666E-03 -3.7569315353602807E-03 -3.7485982689117242E-03 -3.7402750959705513E-03 -3.7319620178120501E-03 -3.7236590322274896E-03 -3.7153661390644578E-03 -3.7070833431580826E-03 -3.6988106499651458E-03 -3.6905480644226097E-03 -3.6822955911454624E-03 -3.6740532318040478E-03 -3.6658209847851885E-03 -3.6575988497184204E-03 -3.6493868305347401E-03 -3.6411849319951902E-03 -3.6329931590103112E-03 -3.6248115165167425E-03 -3.6166400066714108E-03 -3.6084786276238184E-03 -3.6003273783444222E-03 -3.5921862624043901E-03 -3.5840552845485059E-03 -3.5759344495983176E-03 -3.5678237624071321E-03 -3.5597232253881048E-03 -3.5516328363824653E-03 -3.5435525936719598E-03 -3.5354825006777375E-03 -3.5274225625358552E-03 -3.5193727838339376E-03 -3.5113331686488247E-03 -3.5033037194145697E-03 -3.4952844345757690E-03 -3.4872753125473701E-03 -3.4792763559694812E-03 -3.4712875693705754E-03 -3.4633089571266718E-03 -3.4553405234217962E-03 -3.4473822710749660E-03 -3.4394341984909757E-03 -3.4314963035835225E-03 -3.4235685884283582E-03 -3.4156510575353029E-03 -3.4077437152369764E-03 -3.3998465655463578E-03 -3.3919596114266163E-03 -3.3840828513789947E-03 -3.3762162829508125E-03 -3.3683599075359058E-03 -3.3605137294470525E-03 -3.3526777529099784E-03 -3.3448519818307684E-03 -3.3370364193581574E-03 -3.3292310644236680E-03 -3.3214359145647180E-03 -3.3136509703820590E-03 -3.3058762354796923E-03 -3.2981117136676600E-03 -3.2903574089671061E-03 -3.2826133249021223E-03 -3.2748794607568542E-03 -3.2671558138559907E-03 -3.2594423841022751E-03 -3.2517391746725191E-03 -3.2440461891003539E-03 -3.2363634314336817E-03 -3.2286909054410856E-03 -3.2210286105329253E-03 -3.2133765434357018E-03 -3.2057347034478620E-03 -3.1981030941442613E-03 -3.1904817193948729E-03 -3.1828705825988194E-03 -3.1752696868082020E-03 -3.1676790317034680E-03 -3.1600986142513833E-03 -3.1525284333158671E-03 -3.1449684919784833E-03 -3.1374187938451297E-03 -3.1298793424074335E-03 -3.1223501409796258E-03 -3.1148311895776840E-03 -3.1073224847817816E-03 -3.0998240246760869E-03 -3.0923358120350129E-03 -3.0848578504145806E-03 -3.0773901430411706E-03 -3.0699326929102128E-03 -3.0624855003897385E-03 -3.0550485623149089E-03 -3.0476218764867828E-03 -3.0402054452699037E-03 -3.0327992720588755E-03 -3.0254033597446779E-03 -3.0180177108604985E-03 -3.0106423260044864E-03 -3.0032772024092351E-03 -2.9959223377493756E-03 -2.9885777336290135E-03 -2.9812433928840926E-03 -2.9739193183078395E-03 -2.9666055126491980E-03 -2.9593019769499815E-03 -2.9520087083582947E-03 -2.9447257040399054E-03 -2.9374529649577423E-03 -2.9301904936595369E-03 -2.9229382928014952E-03 -2.9156963651532745E-03 -2.9084647120774516E-03 -2.9012433306697992E-03 -2.8940322176274750E-03 -2.8868313734216060E-03 -2.8796408005831212E-03 -2.8724605016685447E-03 -2.8652904792411771E-03 -2.8581307348087134E-03 -2.8509812656176987E-03 -2.8438420681043031E-03 -2.8367131422064287E-03 -2.8295944903425491E-03 -2.8224861148405081E-03 -2.8153880177615260E-03 -2.8083002004663819E-03 -2.8012226606816274E-03 -2.7941553950444338E-03 -2.7870984028475093E-03 -2.7800516858156490E-03 -2.7730152459329699E-03 -2.7659890855977684E-03 -2.7589732067002360E-03 -2.7519676069478359E-03 -2.7449722822695736E-03 -2.7379872312492822E-03 -2.7310124556144690E-03 -2.7240479573393843E-03 -2.7170937386109127E-03 -2.7101498012773086E-03 -2.7032161433144216E-03 -2.6962927604841278E-03 -2.6893796508551974E-03 -2.6824768160600017E-03 -2.6755842580045127E-03 -2.6687019784797867E-03 -2.6618299790182741E-03 -2.6549682578479779E-03 -2.6481168107172553E-03 -2.6412756351815382E-03 -2.6344447325088423E-03 -2.6276241044064803E-03 -2.6208137525871988E-03 -2.6140136786295849E-03 -2.6072238811256578E-03 -2.6004443557616822E-03 -2.5936750995527403E-03 -2.5869161133012879E-03 -2.5801673984333045E-03 -2.5734289564745636E-03 -2.5667007889266817E-03 -2.5599828947009133E-03 -2.5532752694540162E-03 -2.5465779097405736E-03 -2.5398908159542074E-03 -2.5332139893344979E-03 -2.5265474312566342E-03 -2.5198911431468926E-03 -2.5132451241596993E-03 -2.5066093697520293E-03 -2.4999838759433199E-03 -2.4933686429506382E-03 -2.4867636721932636E-03 -2.4801689647993004E-03 -2.4735845216531786E-03 -2.4670103419959268E-03 -2.4604464215950998E-03 -2.4538927563456212E-03 -2.4473493457211658E-03 -2.4408161905838774E-03 -2.4342932919184587E-03 -2.4277806508316937E-03 -2.4212782669931370E-03 -2.4147861360338738E-03 -2.4083042533171780E-03 -2.4018326179190957E-03 -2.3953712307982428E-03 -2.3889200927418516E-03 -2.3824792042879974E-03 -2.3760485650273899E-03 -2.3696281710799180E-03 -2.3632180179863457E-03 -2.3568181040584464E-03 -2.3504284294443381E-03 -2.3440489946112207E-03 -2.3376798005230420E-03 -2.3313208473359740E-03 -2.3249721309177491E-03 -2.3186336459777033E-03 -2.3123053903915339E-03 -2.3059873647423121E-03 -2.2996795695717723E-03 -2.2933820051297881E-03 -2.2870946711251068E-03 -2.2808175638837471E-03 -2.2745506784161993E-03 -2.2682940120557632E-03 -2.2620475647020799E-03 -2.2558113364890713E-03 -2.2495853278569414E-03 -2.2433695389027035E-03 -2.2371639660082230E-03 -2.2309686035887873E-03 -2.2247834483942247E-03 -2.2186085005279693E-03 -2.2124437602395594E-03 -2.2062892273365269E-03 -2.2001449013120903E-03 -2.1940107789829161E-03 -2.1878868552948588E-03 -2.1817731266801201E-03 -2.1756695923938283E-03 -2.1695762520527627E-03 -2.1634931055752853E-03 -2.1574201528347706E-03 -2.1513573908554951E-03 -2.1453048140734495E-03 -2.1392624182638488E-03 -2.1332302026799070E-03 -2.1272081670834315E-03 -2.1211963111737830E-03 -2.1151946345442448E-03 -2.1092031343342109E-03 -2.1032218048039654E-03 -2.0972506412328383E-03 -2.0912896427075500E-03 -2.0853388090332674E-03 -2.0793981395541713E-03 -2.0734676333175393E-03 -2.0675472876598051E-03 -2.0616370973266869E-03 -2.0557370575846495E-03 -2.0498471668735289E-03 -2.0439674244755223E-03 -2.0380978295101745E-03 -2.0322383809639323E-03 -2.0263890764018987E-03 -2.0205499105883261E-03 -2.0147208784704737E-03 -2.0089019779529287E-03 -2.0030932080011598E-03 -1.9972945675849159E-03 -1.9915060556743064E-03 -1.9857276700840478E-03 -1.9799594056286161E-03 -1.9742012569816322E-03 -1.9684532214882798E-03 -1.9627152977625436E-03 -1.9569874846116883E-03 -1.9512697810748518E-03 -1.9455621852033840E-03 -1.9398646915873613E-03 -1.9341772943344299E-03 -1.9284999904440588E-03 -1.9228327786992808E-03 -1.9171756578724092E-03 -1.9115286266757660E-03 -1.9058916830846709E-03 -1.9002648216919469E-03 -1.8946480362883496E-03 -1.8890413234342663E-03 -1.8834446819014656E-03 -1.8778581103715505E-03 -1.8722816072058431E-03 -1.8667151702462111E-03 -1.8611587943539679E-03 -1.8556124733384305E-03 -1.8500762032654238E-03 -1.8445499825281058E-03 -1.8390338095414266E-03 -1.8335276824843596E-03 -1.8280315991822703E-03 -1.8225455547991362E-03 -1.8170695431961230E-03 -1.8116035599261865E-03 -1.8061476028055877E-03 -1.8007016698617004E-03 -1.7952657593239064E-03 -1.7898398692289866E-03 -1.7844239947572497E-03 -1.7790181292321001E-03 -1.7736222676772862E-03 -1.7682364081044524E-03 -1.7628605487625838E-03 -1.7574946876104456E-03 -1.7521388223768950E-03 -1.7467929483478009E-03 -1.7414570587382307E-03 -1.7361311480547066E-03 -1.7308152138636680E-03 -1.7255092541386286E-03 -1.7202132667741143E-03 -1.7149272495504294E-03 -1.7096511980161087E-03 -1.7043851052739329E-03 -1.6991289653816531E-03 -1.6938827756152845E-03 -1.6886465338238094E-03 -1.6834202376360505E-03 -1.6782038845255865E-03 -1.6729974702240436E-03 -1.6678009879984076E-03 -1.6626144316663394E-03 -1.6574377979819230E-03 -1.6522710844321872E-03 -1.6471142885334470E-03 -1.6419674078071011E-03 -1.6368304382332370E-03 -1.6317033729567703E-03 -1.6265862053526652E-03 -1.6214789316505744E-03 -1.6163815490395901E-03 -1.6112940549095455E-03 -1.6062164468268268E-03 -1.6011487210097792E-03 -1.5960908704113598E-03 -1.5910428879321681E-03 -1.5860047695807091E-03 -1.5809765127278769E-03 -1.5759581146167869E-03 -1.5709495723342291E-03 -1.5659508819885651E-03 -1.5609620365890642E-03 -1.5559830288258928E-03 -1.5510138543755225E-03 -1.5460545106259439E-03 -1.5411049946441639E-03 -1.5361653029820339E-03 -1.5312354315646908E-03 -1.5263153738201845E-03 -1.5214051226570158E-03 -1.5165046730927841E-03 -1.5116140217191680E-03 -1.5067331652683712E-03 -1.5018621006745916E-03 -1.4970008243482124E-03 -1.4921493295558248E-03 -1.4873076085529029E-03 -1.4824756559407768E-03 -1.4776534685800563E-03 -1.4728410432384529E-03 -1.4680383762075498E-03 -1.4632454634028833E-03 -1.4584622983949194E-03 -1.4536888737013108E-03 -1.4489251835740939E-03 -1.4441712244267853E-03 -1.4394269927201343E-03 -1.4346924846145137E-03 -1.4299676960062918E-03 -1.4252526206234124E-03 -1.4205472508848236E-03 -1.4158515805764425E-03 -1.4111656057121430E-03 -1.4064893224892149E-03 -1.4018227270232351E-03 -1.3971658152748098E-03 -1.3925185811414988E-03 -1.3878810168897790E-03 -1.3832531158929180E-03 -1.3786348739387158E-03 -1.3740262870865832E-03 -1.3694273511965986E-03 -1.3648380619812315E-03 -1.3602584134331289E-03 -1.3556883977847327E-03 -1.3511280080650936E-03 -1.3465772397250240E-03 -1.3420360886242119E-03 -1.3375045505726183E-03 -1.3329826213154604E-03 -1.3284702949876335E-03 -1.3239675635956744E-03 -1.3194744197103500E-03 -1.3149908585176058E-03 -1.3105168757874903E-03 -1.3060524670801081E-03 -1.3015976278033727E-03 -1.2971523521731238E-03 -1.2927166323665304E-03 -1.2882904608133669E-03 -1.2838738321780674E-03 -1.2794667418213287E-03 -1.2750691852453568E-03 -1.2706811580664383E-03 -1.2663026547514880E-03 -1.2619336671845995E-03 -1.2575741872546161E-03 -1.2532242092201415E-03 -1.2488837283142157E-03 -1.2445527399405371E-03 -1.2402312396849388E-03 -1.2359192221809685E-03 -1.2316166792152028E-03 -1.2273236023042677E-03 -1.2230399852911440E-03 -1.2187658232681827E-03 -1.2145011114627819E-03 -1.2102458452757164E-03 -1.2060000194025913E-03 -1.2017636256986361E-03 -1.1975366554805393E-03 -1.1933191021778818E-03 -1.1891109606925400E-03 -1.1849122260586295E-03 -1.1807228934973529E-03 -1.1765429577297111E-03 -1.1723724107175707E-03 -1.1682112436082808E-03 -1.1640594494022433E-03 -1.1599170227675145E-03 -1.1557839585561015E-03 -1.1516602519183897E-03 -1.1475458976322316E-03 -1.1434408874866585E-03 -1.1393452120354577E-03 -1.1352588639935216E-03 -1.1311818385886312E-03 -1.1271141309145043E-03 -1.1230557351924882E-03 -1.1190066452993767E-03 -1.1149668534086114E-03 -1.1109363507439758E-03 -1.1069151298450154E-03 -1.1029031852412099E-03 -1.0989005115434535E-03 -1.0949071030137794E-03 -1.0909229536942300E-03 -1.0869480558232112E-03 -1.0829824003112966E-03 -1.0790259792100537E-03 -1.0750787868583347E-03 -1.0711408177768193E-03 -1.0672120660161319E-03 -1.0632925253973144E-03 -1.0593821883965366E-03 -1.0554810462045615E-03 -1.0515890906640664E-03 -1.0477063154210276E-03 -1.0438327144104117E-03 -1.0399682815989146E-03 -1.0361130109302630E-03 -1.0322668950350775E-03 -1.0284299249229665E-03 -1.0246020920965575E-03 -1.0207833900797783E-03 -1.0169738128078421E-03 -1.0131733540130717E-03 -1.0093820072894103E-03 -1.0055997652719372E-03 -1.0018266190666637E-03 -9.9806256000829568E-04 -9.9430758109994013E-04 -9.9056167583458582E-04 -9.8682483792808680E-04 -9.8309706126555063E-04 -9.7937833868259210E-04 -9.7566866081871047E-04 -9.7196801838880754E-04 -9.6827640425519140E-04 -9.6459381209216817E-04 -9.6092023551692897E-04 -9.5725566808578088E-04 -9.5360010257953241E-04 -9.4995352965750158E-04 -9.4631593985319373E-04 -9.4268732566933980E-04 -9.3906768059030712E-04 -9.3545699807047217E-04 -9.3185527151519313E-04 -9.2826249373978702E-04 -9.2467865541327461E-04 -9.2110374686786567E-04 -9.1753776024146815E-04 -9.1398068884465319E-04 -9.1043252596454034E-04 -9.0689326481441961E-04 -9.0336289818296800E-04 -8.9984141681305918E-04 -8.9632881091256751E-04 -8.9282507224619338E-04 -8.8933019388693745E-04 -8.8584416894021739E-04 -8.8236699049323321E-04 -8.7889865132642978E-04 -8.7543914220802215E-04 -8.7198845314220310E-04 -8.6854657554257062E-04 -8.6511350235253504E-04 -8.6168922655350047E-04 -8.5827374101346836E-04 -8.5486703838230172E-04 -8.5146910951859004E-04 -8.4807994435179865E-04 -8.4469953395661338E-04 -8.4132787102259748E-04 -8.3796494834687636E-04 -8.3461075867610204E-04 -8.3126529461328665E-04 -8.2792854707917484E-04 -8.2460050584020120E-04 -8.2128116161738363E-04 -8.1797050690811835E-04 -8.1466853437774361E-04 -8.1137523658613006E-04 -8.0809060598289908E-04 -8.0481463358373186E-04 -8.0154730912459571E-04 -7.9828862303838930E-04 -7.9503856752439768E-04 -7.9179713503711550E-04 -7.8856431801729735E-04 -7.8534010885650295E-04 -7.8212449864227605E-04 -7.7891747695878243E-04 -7.7571903390617769E-04 -7.7252916147545626E-04 -7.6934785202076132E-04 -7.6617509780962793E-04 -7.6301089104098660E-04 -7.5985522286371710E-04 -7.5670808286253447E-04 -7.5356946091755710E-04 -7.5043934869295861E-04 -7.4731773832295209E-04 -7.4420462193599375E-04 -7.4109999164882062E-04 -7.3800383868143787E-04 -7.3491615251547590E-04 -7.3183692275128091E-04 -7.2876614079109378E-04 -7.2570379866807207E-04 -7.2264988835507452E-04 -7.1960440176523067E-04 -7.1656733012828678E-04 -7.1353866293920646E-04 -7.1051838963591407E-04 -7.0750650131206510E-04 -7.0450298982834751E-04 -7.0150784699522784E-04 -6.9852106455630856E-04 -6.9554263373871532E-04 -6.9257254403534934E-04 -6.8961078471420519E-04 -6.8665734655827884E-04 -6.8371222126789491E-04 -6.8077540050689772E-04 -6.7784687586088172E-04 -6.7492663853820837E-04 -6.7201467806939444E-04 -6.6911098359442086E-04 -6.6621554555531051E-04 -6.6332835541602607E-04 -6.6044940466782726E-04 -6.5757868480165117E-04 -6.5471618703254197E-04 -6.5186190089342204E-04 -6.4901581533410911E-04 -6.4617792049741251E-04 -6.4334820773512421E-04 -6.4052666841819502E-04 -6.3771329382320907E-04 -6.3490807503242938E-04 -6.3211100164412936E-04 -6.2932206254547214E-04 -6.2654124759530937E-04 -6.2376854792880662E-04 -6.2100395474992849E-04 -6.1824745920010485E-04 -6.1549905228960660E-04 -6.1275872366710110E-04 -6.1002646211218755E-04 -6.0730225718968675E-04 -6.0458609981867096E-04 -6.0187798104275724E-04 -5.9917789187435106E-04 -5.9648582324412002E-04 -5.9380176485614676E-04 -5.9112570539299452E-04 -5.8845763414246523E-04 -5.8579754180079649E-04 -5.8314541925482072E-04 -5.8050125740364579E-04 -5.7786504710898706E-04 -5.7523677811437395E-04 -5.7261643895913604E-04 -5.7000401864539918E-04 -5.6739950770217057E-04 -5.6480289692893650E-04 -5.6221417706210012E-04 -5.5963333878463655E-04 -5.5706037186707279E-04 -5.5449526481107445E-04 -5.5193800641035724E-04 -5.4938858696421957E-04 -5.4684699713441424E-04 -5.4431322752283601E-04 -5.4178726868216805E-04 -5.3926911041258000E-04 -5.3675874115693392E-04 -5.3425614949527422E-04 -5.3176132547147199E-04 -5.2927425960408187E-04 -5.2679494236513148E-04 -5.2432336418289590E-04 -5.2185951488239611E-04 -5.1940338286527972E-04 -5.1695495652480600E-04 -5.1451422565169567E-04 -5.1208118063775037E-04 -5.0965581181667120E-04 -5.0723810945268262E-04 -5.0482806335754905E-04 -5.0242566193706509E-04 -5.0003089345135505E-04 -4.9764374742030174E-04 -4.9526421407463511E-04 -4.9289228361279881E-04 -4.9052794617347078E-04 -4.8817119155476285E-04 -4.8582200814772789E-04 -4.8348038405784276E-04 -4.8114630854480370E-04 -4.7881977171374966E-04 -4.7650076364125161E-04 -4.7418927431137052E-04 -4.7188529346354276E-04 -4.6958880951986526E-04 -4.6729981048884429E-04 -4.6501828535497488E-04 -4.6274422402647051E-04 -4.6047761643498036E-04 -4.5821845247972105E-04 -4.5596672188494253E-04 -4.5372241307663224E-04 -4.5148551390757763E-04 -4.4925601309953386E-04 -4.4703390043840076E-04 -4.4481916575024415E-04 -4.4261179877904479E-04 -4.4041178914342615E-04 -4.3821912531510741E-04 -4.3603379508607961E-04 -4.3385578693890128E-04 -4.3168509046130301E-04 -4.2952169532945719E-04 -4.2736559117887313E-04 -4.2521676756500945E-04 -4.2307521299502447E-04 -4.2094091516197221E-04 -4.1881386231039592E-04 -4.1669404386407709E-04 -4.1458144938113047E-04 -4.1247606835379479E-04 -4.1037789021213504E-04 -4.0828690351346169E-04 -4.0620309593724816E-04 -4.0412645554225690E-04 -4.0205697151979406E-04 -3.9999463325142122E-04 -3.9793943012107552E-04 -3.9589135149396972E-04 -3.9385038596357350E-04 -3.9181652112107063E-04 -3.8978974481650565E-04 -3.8777004607612052E-04 -3.8575741418819695E-04 -3.8375183840365601E-04 -3.8175330794134942E-04 -3.7976181140829038E-04 -3.7777733638255136E-04 -3.7579987056948029E-04 -3.7382940276740661E-04 -3.7186592210545425E-04 -3.6990941772672525E-04 -3.6795987878326453E-04 -3.6601729390868607E-04 -3.6408165059616932E-04 -3.6215293635741811E-04 -3.6023113981418635E-04 -3.5831625003187998E-04 -3.5640825604227441E-04 -3.5450714683948236E-04 -3.5261291102986378E-04 -3.5072553609915609E-04 -3.4884500944495873E-04 -3.4697131948483785E-04 -3.4510445517211430E-04 -3.4324440542302299E-04 -3.4139115909587815E-04 -3.3954470476453877E-04 -3.3770502991677164E-04 -3.3587212184884408E-04 -3.3404596875993110E-04 -3.3222655946657319E-04 -3.3041388277332004E-04 -3.2860792744170212E-04 -3.2680868202580838E-04 -3.2501613402487076E-04 -3.2323027063836207E-04 -3.2145107984396645E-04 -3.1967855030736380E-04 -3.1791267070998994E-04 -3.1615342971469629E-04 -3.1440081584047092E-04 -3.1265481661380375E-04 -3.1091541915770734E-04 -3.0918261124607738E-04 -3.0745638139650103E-04 -3.0573671816911438E-04 -3.0402361013045782E-04 -3.0231704575246098E-04 -3.0061701257804991E-04 -2.9892349763924756E-04 -2.9723648852255079E-04 -2.9555597363958857E-04 -2.9388194146101604E-04 -2.9221438042772183E-04 -2.9055327891408289E-04 -2.8889862448384490E-04 -2.8725040411407843E-04 -2.8560860521836302E-04 -2.8397321607187429E-04 -2.8234422504164414E-04 -2.8072162046425782E-04 -2.7910539063185459E-04 -2.7749552313762843E-04 -2.7589200491829181E-04 -2.7429482323022500E-04 -2.7270396619790462E-04 -2.7111942207910285E-04 -2.6954117912400218E-04 -2.6796922556069491E-04 -2.6640354899411261E-04 -2.6484413627339814E-04 -2.6329097448122391E-04 -2.6174405163216692E-04 -2.6020335592939092E-04 -2.5866887551532933E-04 -2.5714059848825895E-04 -2.5561851246284797E-04 -2.5410260429559715E-04 -2.5259286096764017E-04 -2.5108927031389005E-04 -2.4959182040636515E-04 -2.4810049929538006E-04 -2.4661529501169936E-04 -2.4513619518936415E-04 -2.4366318665206235E-04 -2.4219625626073957E-04 -2.4073539169604241E-04 -2.3928058094294945E-04 -2.3783181197282319E-04 -2.3638907274234821E-04 -2.3495235088664938E-04 -2.3352163317672870E-04 -2.3209690633871298E-04 -2.3067815791111691E-04 -2.2926537582932055E-04 -2.2785854799088569E-04 -2.2645766224103038E-04 -2.2506270619069408E-04 -2.2367366662321260E-04 -2.2229053019881182E-04 -2.2091328429139345E-04 -2.1954191672993449E-04 -2.1817641531844965E-04 -2.1681676780688938E-04 -2.1546296178184314E-04 -2.1411498406983956E-04 -2.1277282130367333E-04 -2.1143646068584531E-04 -2.1010588988934609E-04 -2.0878109661000112E-04 -2.0746206856272830E-04 -2.0614879334443810E-04 -2.0484125777151625E-04 -2.0353944837026309E-04 -2.0224335220379890E-04 -2.0095295690768597E-04 -1.9966825013044591E-04 -1.9838921947775085E-04 -1.9711585247024084E-04 -1.9584813594232710E-04 -1.9458605637949556E-04 -1.9332960070565265E-04 -1.9207875645171592E-04 -1.9083351118671308E-04 -1.8959385245660601E-04 -1.8835976775209985E-04 -1.8713124394281541E-04 -1.8590826747986129E-04 -1.8469082515309117E-04 -1.8347890437107447E-04 -1.8227249260928312E-04 -1.8107157735829980E-04 -1.7987614608244425E-04 -1.7868618567275381E-04 -1.7750168251763799E-04 -1.7632262328363049E-04 -1.7514899532691054E-04 -1.7398078609478807E-04 -1.7281798298453505E-04 -1.7166057335675017E-04 -1.7050854412499009E-04 -1.6936188169644297E-04 -1.6822057265383113E-04 -1.6708460420724065E-04 -1.6595396369031414E-04 -1.6482863846195830E-04 -1.6370861588718802E-04 -1.6259388291833447E-04 -1.6148442590326544E-04 -1.6038023130495312E-04 -1.5928128626112152E-04 -1.5818757808212951E-04 -1.5709909405457682E-04 -1.5601582144506861E-04 -1.5493774720826069E-04 -1.5386485770575782E-04 -1.5279713934822372E-04 -1.5173457918776011E-04 -1.5067716449520415E-04 -1.4962488248958385E-04 -1.4857772034070497E-04 -1.4753566499187164E-04 -1.4649870282509530E-04 -1.4546682021236024E-04 -1.4444000409960368E-04 -1.4341824169316575E-04 -1.4240152016359607E-04 -1.4138982663666161E-04 -1.4038314806789654E-04 -1.3938147085676008E-04 -1.3838478133556710E-04 -1.3739306633822189E-04 -1.3640631299679872E-04 -1.3542450842486445E-04 -1.3444763970093111E-04 -1.3347569378278700E-04 -1.3250865710552951E-04 -1.3154651598615245E-04 -1.3058925714612844E-04 -1.2963686761897095E-04 -1.2868933446451143E-04 -1.2774664477971137E-04 -1.2680878556847611E-04 -1.2587574325209145E-04 -1.2494750405430267E-04 -1.2402405460474339E-04 -1.2310538193721664E-04 -1.2219147309676558E-04 -1.2128231511193495E-04 -1.2037789494538951E-04 -1.1947819904592357E-04 -1.1858321362147703E-04 -1.1769292523015310E-04 -1.1680732088168026E-04 -1.1592638760087640E-04 -1.1505011236074307E-04 -1.1417848208461587E-04 -1.1331148326247275E-04 -1.1244910211303779E-04 -1.1159132511902804E-04 -1.1073813920939078E-04 -1.0988953135439757E-04 -1.0904548852033879E-04 -1.0820599764770778E-04 -1.0737104527064358E-04 -1.0654061759090832E-04 -1.0571470102509379E-04 -1.0489328247761357E-04 -1.0407634890766838E-04 -1.0326388721543982E-04 -1.0245588426626628E-04 -1.0165232663241404E-04 -1.0085320057609237E-04 -1.0005849249381438E-04 -9.9268189209791456E-05 -9.8482277624125915E-05 -9.7700744634749602E-05 -9.6923577132209163E-05 -9.6150761733764423E-05 -9.5382284683217893E-05 -9.4618132315234921E-05 -9.3858291414952711E-05 -9.3102748874392569E-05 -9.2351491575743080E-05 -9.1604506392085259E-05 -9.0861779976894767E-05 -9.0123298594486787E-05 -8.9389048553488928E-05 -8.8659016594510128E-05 -8.7933189595626972E-05 -8.7211554423641155E-05 -8.6494097934795868E-05 -8.5780806815675422E-05 -8.5071667359850025E-05 -8.4366665863237105E-05 -8.3665789023473381E-05 -8.2969023707950382E-05 -8.2276356774018623E-05 -8.1587775066956975E-05 -8.0903265305281577E-05 -8.0222813819950793E-05 -7.9546406905435955E-05 -7.8874031216072307E-05 -7.8205673605720344E-05 -7.7541320926061762E-05 -7.6880960022517343E-05 -7.6224577647532394E-05 -7.5572160173688441E-05 -7.4923693899692020E-05 -7.4279165444844210E-05 -7.3638561659231523E-05 -7.3001869393543052E-05 -7.2369075489998216E-05 -7.1740166725765925E-05 -7.1115129524594730E-05 -7.0493950202698850E-05 -6.9876615351292226E-05 -6.9263111817335072E-05 -6.8653426454975264E-05 -6.8047546112090602E-05 -6.7445457592249020E-05 -6.6847147374787658E-05 -6.6252601799307858E-05 -6.5661807435589371E-05 -6.5074751130235736E-05 -6.4491419745465344E-05 -6.3911800141078359E-05 -6.3335879148053553E-05 -6.2763643303940156E-05 -6.2195078975893205E-05 -6.1630172721324728E-05 -6.1068911396169667E-05 -6.0511281879903930E-05 -5.9957271042503310E-05 -5.9406865734581652E-05 -5.8860052557904666E-05 -5.8316817924528077E-05 -5.7777148391167226E-05 -5.7241030816549612E-05 -5.6708452095363024E-05 -5.6179399119854522E-05 -5.5653858771881858E-05 -5.5131817719200144E-05 -5.4613262417998078E-05 -5.4098179430777056E-05 -5.3586555626644180E-05 -5.3078377924869780E-05 -5.2573633242965720E-05 -5.2072308492862649E-05 -5.1574390409688950E-05 -5.1079865502972788E-05 -5.0588720352991650E-05 -5.0100941842270595E-05 -4.9616516919949066E-05 -4.9135432532832558E-05 -4.8657675624315830E-05 -4.8183232998251284E-05 -4.7712091227890266E-05 -4.7244236924832391E-05 -4.6779656984844661E-05 -4.6318338387979048E-05 -4.5860268117303354E-05 -4.5405433157733033E-05 -4.4953820384384823E-05 -4.4505416435308229E-05 -4.4060207959449034E-05 -4.3618181872425413E-05 -4.3179325194847560E-05 -4.2743624950578857E-05 -4.2311068166557890E-05 -4.1881641787894538E-05 -4.1455332526256553E-05 -4.1032127079944159E-05 -4.0612012391178588E-05 -4.0194975528223870E-05 -3.9781003561369872E-05 -3.9370083562236141E-05 -3.8962202544682724E-05 -3.8557347302772259E-05 -3.8155504595654394E-05 -3.7756661394836796E-05 -3.7360804814581232E-05 -3.6967921976457758E-05 -3.6578000010241870E-05 -3.6191026005208620E-05 -3.5806986840084241E-05 -3.5425869337105877E-05 -3.5047660505807199E-05 -3.4672347518430261E-05 -3.4299917555638780E-05 -3.3930357805035724E-05 -3.3563655427618338E-05 -3.3199797394566661E-05 -3.2838770602750806E-05 -3.2480562107333635E-05 -3.2125159141068238E-05 -3.1772548948817826E-05 -3.1422718783750657E-05 -3.1075655882845380E-05 -3.0731347314860683E-05 -3.0389780058426063E-05 -3.0050941222663653E-05 -2.9714818106907963E-05 -2.9381398026744449E-05 -2.9050668303381437E-05 -2.8722616249147940E-05 -2.8397229037742612E-05 -2.8074493744577161E-05 -2.7754397543771867E-05 -2.7436927799118169E-05 -2.7122071897438306E-05 -2.6809817236956283E-05 -2.6500151214031633E-05 -2.6193061109841340E-05 -2.5888534099324165E-05 -2.5586557430048476E-05 -2.5287118538643050E-05 -2.4990204892552360E-05 -2.4695803975339482E-05 -2.4403903274806646E-05 -2.4114490181545554E-05 -2.3827551970253542E-05 -2.3543075967607491E-05 -2.3261049692702508E-05 -2.2981460705244071E-05 -2.2704296578128146E-05 -2.2429544890715659E-05 -2.2157193146191594E-05 -2.1887228730161672E-05 -2.1619639060979432E-05 -2.1354411744506260E-05 -2.1091534438583224E-05 -2.0830994810355500E-05 -2.0572780533657211E-05 -2.0316879227316414E-05 -2.0063278399386129E-05 -1.9811965573410653E-05 -1.9562928442202514E-05 -1.9316154761000689E-05 -1.9071632299797455E-05 -1.8829348842929534E-05 -1.8589292132767674E-05 -1.8351449799238462E-05 -1.8115809473693630E-05 -1.7882358946039778E-05 -1.7651086082747072E-05 -1.7421978762712993E-05 -1.7195024879981360E-05 -1.6970212300154163E-05 -1.6747528785424380E-05 -1.6526962087916232E-05 -1.6308500101083070E-05 -1.6092130807113968E-05 -1.5877842199520959E-05 -1.5665622288171842E-05 -1.5455459065706822E-05 -1.5247340436501895E-05 -1.5041254286286918E-05 -1.4837188619227422E-05 -1.4635131535633515E-05 -1.4435071148694361E-05 -1.4236995593270713E-05 -1.4040892995122509E-05 -1.3846751404554601E-05 -1.3654558846301461E-05 -1.3464303442925928E-05 -1.3275973419443249E-05 -1.3089557016741050E-05 -1.2905042506962186E-05 -1.2722418159470225E-05 -1.2541672171908327E-05 -1.2362792707136189E-05 -1.2185768014463574E-05 -1.2010586460370757E-05 -1.1837236426125426E-05 -1.1665706317481273E-05 -1.1495984541732953E-05 -1.1328059454540553E-05 -1.1161919377850716E-05 -1.0997552699534065E-05 -1.0834947924053576E-05 -1.0674093573669270E-05 -1.0514978201061120E-05 -1.0357590366161426E-05 -1.0201918586959637E-05 -1.0047951345441929E-05 -9.8956771746972076E-06 -9.7450847276739742E-06 -9.5961626785829722E-06 -9.4488997326638813E-06 -9.3032846070002195E-06 -9.1593059869520422E-06 -9.0169525225308920E-06 -8.8762129017369635E-06 -8.7370759334036514E-06 -8.5995304523494650E-06 -8.4635653231316690E-06 -8.3291694261602210E-06 -8.1963316199920029E-06 -8.0650407315139698E-06 -7.9352856140068031E-06 -7.8070552376831680E-06 -7.6803386045866125E-06 -7.5551247462129141E-06 -7.4314027148773745E-06 -7.3091615486154187E-06 -7.1883902579345816E-06 -7.0690778707535631E-06 -6.9512135260806492E-06 -6.8347864019026316E-06 -6.7197857039320784E-06 -6.6062006633040568E-06 -6.4940205032963128E-06 -6.3832344256011299E-06 -6.2738316426273001E-06 -6.1658014697106264E-06 -6.0591332690039324E-06 -5.9538164281196158E-06 -5.8498403645821452E-06 -5.7471944933116700E-06 -5.6458682151142673E-06 -5.5458509369436722E-06 -5.4471321576983257E-06 -5.3497014304250285E-06 -5.2535483324352099E-06 -5.1586624771880782E-06 -5.0650334791734789E-06 -4.9726509440430036E-06 -4.8815044806963686E-06 -4.7915837806311327E-06 -4.7028785980764117E-06 -4.6153787087012062E-06 -4.5290739278516115E-06 -4.4439540754260098E-06 -4.3600089704055245E-06 -4.2772284346435755E-06 -4.1956023607884761E-06 -4.1151207107408774E-06 -4.0357734662330574E-06 -3.9575506534570849E-06 -3.8804423064062744E-06 -3.8044384638201687E-06 -3.7295291683609491E-06 -3.6557045229566721E-06 -3.5829547065266517E-06 -3.5112699163219435E-06 -3.4406403966413189E-06 -3.3710564029831611E-06 -3.3025082012573067E-06 -3.2349860645733704E-06 -3.1684803155329384E-06 -3.1029813574036995E-06 -3.0384796114785631E-06 -2.9749655485406152E-06 -2.9124296547022433E-06 -2.8508624301664508E-06 -2.7902543867294264E-06 -2.7305960762015539E-06 -2.6718781349755641E-06 -2.6140912182112651E-06 -2.5572260309076373E-06 -2.5012732980975583E-06 -2.4462237617170613E-06 -2.3920681812810278E-06 -2.3387973478155252E-06 -2.2864021386247441E-06 -2.2348734518228086E-06 -2.1842022351296269E-06 -2.1343794620059458E-06 -2.0853961239221999E-06 -2.0372432362599204E-06 -1.9899118391693397E-06 -1.9433930593577649E-06 -1.8976780477758641E-06 -1.8527580033187238E-06 -1.8086241569277464E-06 -1.7652677576471176E-06 -1.7226800850444310E-06 -1.6808524386687009E-06 -1.6397762030849874E-06 -1.5994427920295251E-06 -1.5598436640779513E-06 -1.5209703163617487E-06 -1.4828142638716291E-06 -1.4453670594291857E-06 -1.4086202729887018E-06 -1.3725655551963209E-06 -1.3371945917148705E-06 -1.3024991096884833E-06 -1.2684708820706756E-06 -1.2351016988747810E-06 -1.2023833943588790E-06 -1.1703078191306950E-06 -1.1388668988809230E-06 -1.1080526009624446E-06 -1.0778569304810248E-06 -1.0482719459383185E-06 -1.0192897219989225E-06 -9.9090238186612715E-07 -9.6310206623159323E-07 -9.3588098550425191E-07 -9.0923139971605454E-07 -8.8314560179036284E-07 -8.5761594381693689E-07 -8.3263479412075660E-07 -8.0819457395186381E-07 -7.8428772552080625E-07 -7.6090675338612857E-07 -7.3804421913269593E-07 -7.1569271313634935E-07 -6.9384489081558751E-07 -6.7249342480741551E-07 -6.5163104265226501E-07 -6.3125049802579437E-07 -6.1134459946995355E-07 -5.9190622003854064E-07 -5.7292825801160601E-07 -5.5440368122409660E-07 -5.3632547699142542E-07 -5.1868668785382572E-07 -5.0148038925643022E-07 -4.8469970394473256E-07 -4.6833782611197439E-07 -4.5238797270467524E-07 -4.3684343310165724E-07 -4.2169751997201904E-07 -4.0694359983482836E-07 -3.9257508007049414E-07 -3.7858540814267483E-07 -3.6496810902496898E-07 -3.5171672945187971E-07 -3.3882488953156126E-07 -3.2628623813238945E-07 -3.1409447509635001E-07 -3.0224334984570227E-07 -2.9072664542887673E-07 -2.7953822724170551E-07 -2.6867198309705778E-07 -2.5812187323739856E-07 -2.4788189360269349E-07 -2.3794608707954241E-07 -2.2830855516064391E-07 -2.1896342772387490E-07 -2.0990492022301848E-07 -2.0112727298891227E-07 -1.9262479610093000E-07 -1.8439184345268616E-07 -1.7642281111580144E-07 -1.6871216258656673E-07 -1.6125438621210287E-07 -1.5404405709958989E-07 -1.4707577964485479E-07 -1.4034422382613097E-07 -1.3384411241915627E-07 -1.2757020529271328E-07 -1.2151733773739048E-07 -1.1568036838541337E-07 -1.1005424176012716E-07 -1.0463393797916402E-07 -9.9414497332427949E-08 -9.4391022311153359E-08 -8.9558647690469155E-08 -8.4912590392743696E-08 -8.0448091291407411E-08 -7.6160474345630471E-08 -7.2045106953603279E-08 -6.8097410492434935E-08 -6.4312877953614288E-08 -6.0687030677545078E-08 -5.7215477007367416E-08 -5.3893852088902188E-08 -5.0717869705167719E-08 -4.7683296113412199E-08 -4.4785944972379249E-08 -4.2021710392662330E-08 -3.9386512424390874E-08 -3.6876360619015094E-08 -3.4487296534541249E-08 -3.2215434502382282E-08 -3.0056951128111295E-08 -2.8008063992293534E-08 -2.6065078910175158E-08 -2.4224327118665168E-08 -2.2482229366658030E-08 -2.0835245753419048E-08 -1.9279902252803504E-08 -1.7812797233104470E-08 -1.6430564322938792E-08 -1.5129931572797592E-08 -1.3907654049653017E-08 -1.2760574061543463E-08 -1.1685582351816083E-08 -1.0679628026979709E-08 -9.7397424946468995E-09 -8.8629880600680239E-09 -8.0465254909654640E-09 -7.2875464919444832E-09 -6.5833256879688662E-09 -5.9311965014569381E-09 -5.3285430930688386E-09 -4.7728410651625686E-09 -4.2615945089950252E-09 -3.7924073850788373E-09 -3.3629209510883618E-09 -2.9708533357615476E-09 -2.6139925929105327E-09 -2.2901703262238967E-09 -1.9973174265931076E-09 -1.7333930969612831E-09 -1.4964552442131602E-09 -1.2846075910052033E-09 -1.0960234169194144E-09 -9.2895725245415432E-10 -7.8170104009561958E-10 -6.5265199647703687E-10 -5.4023790085085291E-10 -4.4298173193207327E-10 -3.5946252662814657E-10 -2.8832085439110457E-10 -2.2828944989855323E-10 -1.7813404308962129E-10 -1.3672909769435065E-10 -1.0298451603637484E-10 -7.5899974836367968E-11 -5.4542779555650022E-11 -3.8033345273815086E-11 -2.5593550421995773E-11 -1.6476473143976347E-11 -1.0046753489732067E-11 -5.7124861543616743E-12 -2.9581551408274362E-12 -1.3421354050304506E-12 -4.7985639959493301E-13 -1.2675640305564426E-13 -6.0650062549853318E-14 -5.9352025216684467E-14 -3.4675767914034056E-01 -3.4668560572990209E-01 -3.4661351345472829E-01 -3.4654140232722302E-01 -3.4646927235979008E-01 -3.4639712356483338E-01 -3.4632495595475682E-01 -3.4625276954196421E-01 -3.4618056433885935E-01 -3.4610834035784621E-01 -3.4603609761132859E-01 -3.4596383611171033E-01 -3.4589155587139531E-01 -3.4581925690278742E-01 -3.4574693921829047E-01 -3.4567460283030826E-01 -3.4560224775124482E-01 -3.4552987399350382E-01 -3.4545748156948924E-01 -3.4538507049160488E-01 -3.4531264077225465E-01 -3.4524019242384230E-01 -3.4516772545877183E-01 -3.4509523988944701E-01 -3.4502273572827169E-01 -3.4495021298764977E-01 -3.4487767167998512E-01 -3.4480511181768153E-01 -3.4473253341314286E-01 -3.4465993647877302E-01 -3.4458732102697587E-01 -3.4451468707015526E-01 -3.4444203462071499E-01 -3.4436936369105897E-01 -3.4429667429359112E-01 -3.4422396644071512E-01 -3.4415124014483495E-01 -3.4407849541835450E-01 -3.4400573227367753E-01 -3.4393295072320795E-01 -3.4386015077934956E-01 -3.4378733245450632E-01 -3.4371449576108210E-01 -3.4364164071148062E-01 -3.4356876731810576E-01 -3.4349587559336148E-01 -3.4342296554965163E-01 -3.4335003719937995E-01 -3.4327709055495037E-01 -3.4320412562876679E-01 -3.4313114243323301E-01 -3.4305814098075288E-01 -3.4298512128373027E-01 -3.4291208335456907E-01 -3.4283902720567311E-01 -3.4276595284944616E-01 -3.4269286029829227E-01 -3.4261974956461516E-01 -3.4254662066081876E-01 -3.4247347359930680E-01 -3.4240030839248325E-01 -3.4232712505275198E-01 -3.4225392359251683E-01 -3.4218070402418160E-01 -3.4210746636015016E-01 -3.4203421061282641E-01 -3.4196093679461420E-01 -3.4188764491791734E-01 -3.4181433499513975E-01 -3.4174100703868526E-01 -3.4166766106095769E-01 -3.4159429707436095E-01 -3.4152091509129889E-01 -3.4144751512417537E-01 -3.4137409718539424E-01 -3.4130066128735931E-01 -3.4122720744247448E-01 -3.4115373566314366E-01 -3.4108024596177067E-01 -3.4100673835075929E-01 -3.4093321284251349E-01 -3.4085966944943702E-01 -3.4078610818393379E-01 -3.4071252905840771E-01 -3.4063893208526252E-01 -3.4056531727690226E-01 -3.4049168464573060E-01 -3.4041803420415145E-01 -3.4034436596456868E-01 -3.4027067993938620E-01 -3.4019697614100780E-01 -3.4012325458183734E-01 -3.4004951527427874E-01 -3.3997575823073578E-01 -3.3990198346361233E-01 -3.3982819098531231E-01 -3.3975438080823950E-01 -3.3968055294479782E-01 -3.3960670740739113E-01 -3.3953284420842317E-01 -3.3945896336029791E-01 -3.3938506487541925E-01 -3.3931114876619090E-01 -3.3923721504501680E-01 -3.3916326372430083E-01 -3.3908929481644684E-01 -3.3901530833385862E-01 -3.3894130428894004E-01 -3.3886728269409505E-01 -3.3879324356172746E-01 -3.3871918690424108E-01 -3.3864511273403980E-01 -3.3857102106352754E-01 -3.3849691190510800E-01 -3.3842278527118519E-01 -3.3834864117416291E-01 -3.3827447962644502E-01 -3.3820030064043538E-01 -3.3812610422853784E-01 -3.3805189040315625E-01 -3.3797765917669448E-01 -3.3790341056155637E-01 -3.3782914457014585E-01 -3.3775486121486664E-01 -3.3768056050812273E-01 -3.3760624246231796E-01 -3.3753190708985609E-01 -3.3745755440314101E-01 -3.3738318441457665E-01 -3.3730879713656681E-01 -3.3723439258151539E-01 -3.3715997076182619E-01 -3.3708553168990307E-01 -3.3701107537814995E-01 -3.3693660183897062E-01 -3.3686211108476899E-01 -3.3678760312794892E-01 -3.3671307798091415E-01 -3.3663853565606872E-01 -3.3656397616581635E-01 -3.3648939952256096E-01 -3.3641480573870636E-01 -3.3634019482665645E-01 -3.3626556679881509E-01 -3.3619092166758613E-01 -3.3611625944537338E-01 -3.3604158014458074E-01 -3.3596688377761208E-01 -3.3589217035687124E-01 -3.3581743989476204E-01 -3.3574269240368843E-01 -3.3566792789605421E-01 -3.3559314638426324E-01 -3.3551834788071927E-01 -3.3544353239782637E-01 -3.3536869994798824E-01 -3.3529385054360888E-01 -3.3521898419709195E-01 -3.3514410092084146E-01 -3.3506920072726121E-01 -3.3499428362875505E-01 -3.3491934963772685E-01 -3.3484439876658051E-01 -3.3476943102771989E-01 -3.3469444643354873E-01 -3.3461944499647095E-01 -3.3454442672889045E-01 -3.3446939164321099E-01 -3.3439433975183663E-01 -3.3431927106717102E-01 -3.3424418560161806E-01 -3.3416908336758167E-01 -3.3409396437746569E-01 -3.3401882864367388E-01 -3.3394367617861026E-01 -3.3386850699467857E-01 -3.3379332110428273E-01 -3.3371811851982652E-01 -3.3364289925371388E-01 -3.3356766331834869E-01 -3.3349241072613467E-01 -3.3341714148947577E-01 -3.3334185562077584E-01 -3.3326655313243880E-01 -3.3319123403686834E-01 -3.3311589834646843E-01 -3.3304054607364292E-01 -3.3296517723079572E-01 -3.3288979183033057E-01 -3.3281438988465140E-01 -3.3273897140616204E-01 -3.3266353640726642E-01 -3.3258808490036829E-01 -3.3251261689787159E-01 -3.3243713241218009E-01 -3.3236163145569775E-01 -3.3228611404082831E-01 -3.3221058017997573E-01 -3.3213502988554383E-01 -3.3205946316993651E-01 -3.3198388004555757E-01 -3.3190828052481081E-01 -3.3183266462010019E-01 -3.3175703234382958E-01 -3.3168138370840278E-01 -3.3160571872622363E-01 -3.3153003740969605E-01 -3.3145433977122390E-01 -3.3137862582321093E-01 -3.3130289557806109E-01 -3.3122714904817824E-01 -3.3115138624596624E-01 -3.3107560718382889E-01 -3.3099981187417005E-01 -3.3092400032939367E-01 -3.3084817256190346E-01 -3.3077232858410344E-01 -3.3069646840839728E-01 -3.3062059204718908E-01 -3.3054469951288251E-01 -3.3046879081788144E-01 -3.3039286597458983E-01 -3.3031692499541149E-01 -3.3024096789275015E-01 -3.3016499467900989E-01 -3.3008900536659436E-01 -3.3001299996790756E-01 -3.2993697849535336E-01 -3.2986094096133550E-01 -3.2978488737825784E-01 -3.2970881775852440E-01 -3.2963273211453886E-01 -3.2955663045870520E-01 -3.2948051280342716E-01 -3.2940437916110865E-01 -3.2932822954415358E-01 -3.2925206396496581E-01 -3.2917588243594909E-01 -3.2909968496950737E-01 -3.2902347157804446E-01 -3.2894724227396427E-01 -3.2887099706967055E-01 -3.2879473597756731E-01 -3.2871845901005825E-01 -3.2864216617954733E-01 -3.2856585749843842E-01 -3.2848953297913530E-01 -3.2841319263404189E-01 -3.2833683647556200E-01 -3.2826046451609947E-01 -3.2818407676805827E-01 -3.2810767324384216E-01 -3.2803125395585503E-01 -3.2795481891650069E-01 -3.2787836813818305E-01 -3.2780190163330597E-01 -3.2772541941427324E-01 -3.2764892149348884E-01 -3.2757240788335656E-01 -3.2749587859628021E-01 -3.2741933364466363E-01 -3.2734277304091086E-01 -3.2726619679742558E-01 -3.2718960492661170E-01 -3.2711299744087308E-01 -3.2703637435261357E-01 -3.2695973567423697E-01 -3.2688308141814731E-01 -3.2680641159674823E-01 -3.2672972622244378E-01 -3.2665302530763768E-01 -3.2657630886473388E-01 -3.2649957690613618E-01 -3.2642282944424844E-01 -3.2634606649147457E-01 -3.2626928806021832E-01 -3.2619249416288365E-01 -3.2611568481187436E-01 -3.2603886001959442E-01 -3.2596201979844747E-01 -3.2588516416083751E-01 -3.2580829311916848E-01 -3.2573140668584410E-01 -3.2565450487326819E-01 -3.2557758769384476E-01 -3.2550065515997756E-01 -3.2542370728407050E-01 -3.2534674407852737E-01 -3.2526976555575210E-01 -3.2519277172814853E-01 -3.2511576260812047E-01 -3.2503873820807183E-01 -3.2496169854040646E-01 -3.2488464361752822E-01 -3.2480757345184091E-01 -3.2473048805574845E-01 -3.2465338744165467E-01 -3.2457627162196351E-01 -3.2449914060907870E-01 -3.2442199441540409E-01 -3.2434483305334366E-01 -3.2426765653530126E-01 -3.2419046487368058E-01 -3.2411325808088565E-01 -3.2403603616932025E-01 -3.2395879915138831E-01 -3.2388154703949357E-01 -3.2380427984603993E-01 -3.2372699758343126E-01 -3.2364970026407153E-01 -3.2357238790036441E-01 -3.2349506050471383E-01 -3.2341771808952369E-01 -3.2334036066719779E-01 -3.2326298825013999E-01 -3.2318560085075421E-01 -3.2310819848144429E-01 -3.2303078115461398E-01 -3.2295334888266725E-01 -3.2287590167800789E-01 -3.2279843955303983E-01 -3.2272096252016691E-01 -3.2264347059179294E-01 -3.2256596378032182E-01 -3.2248844209815741E-01 -3.2241090555770346E-01 -3.2233335417136399E-01 -3.2225578795154275E-01 -3.2217820691064364E-01 -3.2210061106107057E-01 -3.2202300041522725E-01 -3.2194537498551767E-01 -3.2186773478434560E-01 -3.2179007982411495E-01 -3.2171241011722956E-01 -3.2163472567609330E-01 -3.2155702651311002E-01 -3.2147931264068358E-01 -3.2140158407121783E-01 -3.2132384081711662E-01 -3.2124608289078382E-01 -3.2116831030462334E-01 -3.2109052307103891E-01 -3.2101272120243446E-01 -3.2093490471121383E-01 -3.2085707360978094E-01 -3.2077922791053959E-01 -3.2070136762589363E-01 -3.2062349276824698E-01 -3.2054560335000343E-01 -3.2046769938356684E-01 -3.2038978088134107E-01 -3.2031184785573003E-01 -3.2023390031913751E-01 -3.2015593828396743E-01 -3.2007796176262360E-01 -3.1999997076750991E-01 -3.1992196531103018E-01 -3.1984394540558830E-01 -3.1976591106358809E-01 -3.1968786229743346E-01 -3.1960979911952819E-01 -3.1953172154227627E-01 -3.1945362957808138E-01 -3.1937552323934754E-01 -3.1929740253847849E-01 -3.1921926748787816E-01 -3.1914111809995044E-01 -3.1906295438709903E-01 -3.1898477636172790E-01 -3.1890658403624089E-01 -3.1882837742304193E-01 -3.1875015653453481E-01 -3.1867192138312334E-01 -3.1859367198121136E-01 -3.1851540834120290E-01 -3.1843713047550165E-01 -3.1835883839651152E-01 -3.1828053211663637E-01 -3.1820221164828005E-01 -3.1812387700384648E-01 -3.1804552819573945E-01 -3.1796716523636281E-01 -3.1788878813812044E-01 -3.1781039691341623E-01 -3.1773199157465393E-01 -3.1765357213423751E-01 -3.1757513860457076E-01 -3.1749669099805761E-01 -3.1741822932710184E-01 -3.1733975360410732E-01 -3.1726126384147801E-01 -3.1718276005161761E-01 -3.1710424224693001E-01 -3.1702571043981920E-01 -3.1694716464268885E-01 -3.1686860486794305E-01 -3.1679003112798543E-01 -3.1671144343521990E-01 -3.1663284180205042E-01 -3.1655422624088075E-01 -3.1647559676411474E-01 -3.1639695338415635E-01 -3.1631829611340934E-01 -3.1623962496427765E-01 -3.1616093994916500E-01 -3.1608224108047533E-01 -3.1600352837061263E-01 -3.1592480183198057E-01 -3.1584606147698302E-01 -3.1576730731802388E-01 -3.1568853936750702E-01 -3.1560975763783633E-01 -3.1553096214141557E-01 -3.1545215289064871E-01 -3.1537332989793948E-01 -3.1529449317569186E-01 -3.1521564273630964E-01 -3.1513677859219669E-01 -3.1505790075575679E-01 -3.1497900923939404E-01 -3.1490010405551200E-01 -3.1482118521651470E-01 -3.1474225273480594E-01 -3.1466330662278963E-01 -3.1458434689286957E-01 -3.1450537355744962E-01 -3.1442638662893369E-01 -3.1434738611972557E-01 -3.1426837204222913E-01 -3.1418934440884827E-01 -3.1411030323198691E-01 -3.1403124852404873E-01 -3.1395218029743766E-01 -3.1387309856455758E-01 -3.1379400333781243E-01 -3.1371489462960594E-01 -3.1363577245234198E-01 -3.1355663681842444E-01 -3.1347748774025719E-01 -3.1339832523024408E-01 -3.1331914930078891E-01 -3.1323995996429560E-01 -3.1316075723316805E-01 -3.1308154111980996E-01 -3.1300231163662534E-01 -3.1292306879601800E-01 -3.1284381261039179E-01 -3.1276454309215052E-01 -3.1268526025369814E-01 -3.1260596410743846E-01 -3.1252665466577534E-01 -3.1244733194111257E-01 -3.1236799594585413E-01 -3.1228864669240386E-01 -3.1220928419316551E-01 -3.1212990846054306E-01 -3.1205051950694024E-01 -3.1197111734476107E-01 -3.1189170198640925E-01 -3.1181227344428869E-01 -3.1173283173080329E-01 -3.1165337685835692E-01 -3.1157390883935338E-01 -3.1149442768619651E-01 -3.1141493341129017E-01 -3.1133542602703829E-01 -3.1125590554584470E-01 -3.1117637198011322E-01 -3.1109682534224775E-01 -3.1101726564465210E-01 -3.1093769289973017E-01 -3.1085810711988576E-01 -3.1077850831752279E-01 -3.1069889650504512E-01 -3.1061927169485654E-01 -3.1053963389936101E-01 -3.1045998313096229E-01 -3.1038031940206429E-01 -3.1030064272507080E-01 -3.1022095311238579E-01 -3.1014125057641301E-01 -3.1006153512955642E-01 -3.0998180678421972E-01 -3.0990206555280697E-01 -3.0982231144772193E-01 -3.0974254448136834E-01 -3.0966276466615023E-01 -3.0958297201447144E-01 -3.0950316653873572E-01 -3.0942334825134704E-01 -3.0934351716470915E-01 -3.0926367329122600E-01 -3.0918381664330141E-01 -3.0910394723333923E-01 -3.0902406507374330E-01 -3.0894417017691755E-01 -3.0886426255526578E-01 -3.0878434222119189E-01 -3.0870440918709968E-01 -3.0862446346539302E-01 -3.0854450506847581E-01 -3.0846453400875185E-01 -3.0838455029862499E-01 -3.0830455395049916E-01 -3.0822454497677815E-01 -3.0814452338986592E-01 -3.0806448920216617E-01 -3.0798444242608286E-01 -3.0790438307401991E-01 -3.0782431115838105E-01 -3.0774422669157014E-01 -3.0766412968599105E-01 -3.0758402015404773E-01 -3.0750389810814399E-01 -3.0742376356068363E-01 -3.0734361652407055E-01 -3.0726345701070867E-01 -3.0718328503300174E-01 -3.0710310060335361E-01 -3.0702290373416824E-01 -3.0694269443784938E-01 -3.0686247272680101E-01 -3.0678223861342691E-01 -3.0670199211013094E-01 -3.0662173322931696E-01 -3.0654146198338883E-01 -3.0646117838475040E-01 -3.0638088244580552E-01 -3.0630057417895806E-01 -3.0622025359661192E-01 -3.0613992071117091E-01 -3.0605957553503882E-01 -3.0597921808061967E-01 -3.0589884836031722E-01 -3.0581846638653531E-01 -3.0573807217167781E-01 -3.0565766572814862E-01 -3.0557724706835154E-01 -3.0549681620469044E-01 -3.0541637314956926E-01 -3.0533591791539172E-01 -3.0525545051456177E-01 -3.0517497095948326E-01 -3.0509447926256000E-01 -3.0501397543619591E-01 -3.0493345949279482E-01 -3.0485293144476056E-01 -3.0477239130449696E-01 -3.0469183908440800E-01 -3.0461127479689748E-01 -3.0453069845436920E-01 -3.0445011006922706E-01 -3.0436950965387494E-01 -3.0428889722071661E-01 -3.0420827278215601E-01 -3.0412763635059697E-01 -3.0404698793844348E-01 -3.0396632755809916E-01 -3.0388565522196798E-01 -3.0380497094245379E-01 -3.0372427473196051E-01 -3.0364356660289188E-01 -3.0356284656765187E-01 -3.0348211463864422E-01 -3.0340137082827290E-01 -3.0332061514894171E-01 -3.0323984761305450E-01 -3.0315906823301519E-01 -3.0307827702122753E-01 -3.0299747399009552E-01 -3.0291665915202287E-01 -3.0283583251941354E-01 -3.0275499410467133E-01 -3.0267414392020009E-01 -3.0259328197840368E-01 -3.0251240829168607E-01 -3.0243152287245101E-01 -3.0235062573310234E-01 -3.0226971688604398E-01 -3.0218879634367979E-01 -3.0210786411841350E-01 -3.0202692022264910E-01 -3.0194596466879048E-01 -3.0186499746924139E-01 -3.0178401863640569E-01 -3.0170302818268735E-01 -3.0162202612049011E-01 -3.0154101246221787E-01 -3.0145998722027445E-01 -3.0137895040706381E-01 -3.0129790203498968E-01 -3.0121684211645600E-01 -3.0113577066386665E-01 -3.0105468768962534E-01 -3.0097359320613615E-01 -3.0089248722580270E-01 -3.0081136976102901E-01 -3.0073024082421895E-01 -3.0064910042777626E-01 -3.0056794858410485E-01 -3.0048678530560857E-01 -3.0040561060469134E-01 -3.0032442449375696E-01 -3.0024322698520928E-01 -3.0016201809145215E-01 -3.0008079782488944E-01 -2.9999956619792506E-01 -2.9991832322296280E-01 -2.9983706891240658E-01 -2.9975580327866014E-01 -2.9967452633412750E-01 -2.9959323809121235E-01 -2.9951193856231867E-01 -2.9943062775985024E-01 -2.9934930569621099E-01 -2.9926797238380476E-01 -2.9918662783503536E-01 -2.9910527206230669E-01 -2.9902390507802262E-01 -2.9894252689458689E-01 -2.9886113752440352E-01 -2.9877973697987625E-01 -2.9869832527340900E-01 -2.9861690241740563E-01 -2.9853546842426998E-01 -2.9845402330640586E-01 -2.9837256707621718E-01 -2.9829109974610779E-01 -2.9820962132848156E-01 -2.9812813183574233E-01 -2.9804663128029396E-01 -2.9796511967454031E-01 -2.9788359703088518E-01 -2.9780206336173259E-01 -2.9772051867948623E-01 -2.9763896299655002E-01 -2.9755739632532779E-01 -2.9747581867822337E-01 -2.9739423006764076E-01 -2.9731263050598372E-01 -2.9723102000565604E-01 -2.9714939857906170E-01 -2.9706776623860454E-01 -2.9698612299668831E-01 -2.9690446886571698E-01 -2.9682280385809434E-01 -2.9674112798622432E-01 -2.9665944126251070E-01 -2.9657774369935735E-01 -2.9649603530916818E-01 -2.9641431610434704E-01 -2.9633258609729768E-01 -2.9625084530042411E-01 -2.9616909372613009E-01 -2.9608733138681953E-01 -2.9600555829489616E-01 -2.9592377446276402E-01 -2.9584197990282690E-01 -2.9576017462748866E-01 -2.9567835864915304E-01 -2.9559653198022406E-01 -2.9551469463310553E-01 -2.9543284662020125E-01 -2.9535098795391512E-01 -2.9526911864665101E-01 -2.9518723871081276E-01 -2.9510534815880424E-01 -2.9502344700302924E-01 -2.9494153525589173E-01 -2.9485961292979551E-01 -2.9477768003714444E-01 -2.9469573659034232E-01 -2.9461378260179311E-01 -2.9453181808390055E-01 -2.9444984304906868E-01 -2.9436785750970124E-01 -2.9428586147820202E-01 -2.9420385496697499E-01 -2.9412183798842395E-01 -2.9403981055495276E-01 -2.9395777267896533E-01 -2.9387572437286541E-01 -2.9379366564905696E-01 -2.9371159651994383E-01 -2.9362951699792977E-01 -2.9354742709541881E-01 -2.9346532682481463E-01 -2.9338321619852126E-01 -2.9330109522894243E-01 -2.9321896392848207E-01 -2.9313682230954391E-01 -2.9305467038453198E-01 -2.9297250816585002E-01 -2.9289033566590195E-01 -2.9280815289709156E-01 -2.9272595987182276E-01 -2.9264375660249942E-01 -2.9256154310152538E-01 -2.9247931938130445E-01 -2.9239708545424059E-01 -2.9231484133273750E-01 -2.9223258702919924E-01 -2.9215032255602946E-01 -2.9206804792563218E-01 -2.9198576315041119E-01 -2.9190346824277036E-01 -2.9182116321511348E-01 -2.9173884807984451E-01 -2.9165652284936727E-01 -2.9157418753608561E-01 -2.9149184215240331E-01 -2.9140948671072442E-01 -2.9132712122345261E-01 -2.9124474570299180E-01 -2.9116236016174590E-01 -2.9107996461211871E-01 -2.9099755906651409E-01 -2.9091514353733594E-01 -2.9083271803698801E-01 -2.9075028257787433E-01 -2.9066783717239858E-01 -2.9058538183296473E-01 -2.9050291657197663E-01 -2.9042044140183804E-01 -2.9033795633495291E-01 -2.9025546138372516E-01 -2.9017295656055847E-01 -2.9009044187785682E-01 -2.9000791734802406E-01 -2.8992538298346399E-01 -2.8984283879658052E-01 -2.8976028479977745E-01 -2.8967772100545869E-01 -2.8959514742602810E-01 -2.8951256407388953E-01 -2.8942997096144679E-01 -2.8934736810110384E-01 -2.8926475550526443E-01 -2.8918213318633246E-01 -2.8909950115671179E-01 -2.8901685942880623E-01 -2.8893420801501979E-01 -2.8885154692775611E-01 -2.8876887617941921E-01 -2.8868619578241289E-01 -2.8860350574914101E-01 -2.8852080609200736E-01 -2.8843809682341592E-01 -2.8835537795577049E-01 -2.8827264950147502E-01 -2.8818991147293316E-01 -2.8810716388254887E-01 -2.8802440674272611E-01 -2.8794164006586859E-01 -2.8785886386438020E-01 -2.8777607815066486E-01 -2.8769328293712643E-01 -2.8761047823616864E-01 -2.8752766406019548E-01 -2.8744484042161078E-01 -2.8736200733281836E-01 -2.8727916480622206E-01 -2.8719631285422581E-01 -2.8711345148923340E-01 -2.8703058072364879E-01 -2.8694770056987573E-01 -2.8686481104031808E-01 -2.8678191214737975E-01 -2.8669900390346459E-01 -2.8661608632097640E-01 -2.8653315941231911E-01 -2.8645022318989655E-01 -2.8636727766611259E-01 -2.8628432285337102E-01 -2.8620135876407576E-01 -2.8611838541063067E-01 -2.8603540280543965E-01 -2.8595241096090646E-01 -2.8586940988943493E-01 -2.8578639960342911E-01 -2.8570338011529267E-01 -2.8562035143742948E-01 -2.8553731358224355E-01 -2.8545426656213857E-01 -2.8537121038951846E-01 -2.8528814507678707E-01 -2.8520507063634826E-01 -2.8512198708060599E-01 -2.8503889442196395E-01 -2.8495579267282606E-01 -2.8487268184559622E-01 -2.8478956195267818E-01 -2.8470643300647591E-01 -2.8462329501939326E-01 -2.8454014800383398E-01 -2.8445699197220209E-01 -2.8437382693690133E-01 -2.8429065291033551E-01 -2.8420746990490869E-01 -2.8412427793302447E-01 -2.8404107700708692E-01 -2.8395786713949978E-01 -2.8387464834266696E-01 -2.8379142062899232E-01 -2.8370818401087966E-01 -2.8362493850073289E-01 -2.8354168411095587E-01 -2.8345842085395240E-01 -2.8337514874212638E-01 -2.8329186778788168E-01 -2.8320857800362215E-01 -2.8312527940175158E-01 -2.8304197199467396E-01 -2.8295865579479301E-01 -2.8287533081451266E-01 -2.8279199706623681E-01 -2.8270865456236921E-01 -2.8262530331531377E-01 -2.8254194333747434E-01 -2.8245857464125484E-01 -2.8237519723905902E-01 -2.8229181114329077E-01 -2.8220841636635402E-01 -2.8212501292065256E-01 -2.8204160081859025E-01 -2.8195818007257095E-01 -2.8187475069499857E-01 -2.8179131269827684E-01 -2.8170786609480974E-01 -2.8162441089700113E-01 -2.8154094711725480E-01 -2.8145747476797461E-01 -2.8137399386156442E-01 -2.8129050441042813E-01 -2.8120700642696961E-01 -2.8112349992359265E-01 -2.8103998491270110E-01 -2.8095646140669889E-01 -2.8087292941798986E-01 -2.8078938895897781E-01 -2.8070584004206667E-01 -2.8062228267966022E-01 -2.8053871688416243E-01 -2.8045514266797705E-01 -2.8037156004350794E-01 -2.8028796902315906E-01 -2.8020436961933415E-01 -2.8012076184443713E-01 -2.8003714571087185E-01 -2.7995352123104211E-01 -2.7986988841735189E-01 -2.7978624728220497E-01 -2.7970259783800516E-01 -2.7961894009715643E-01 -2.7953527407206258E-01 -2.7945159977512740E-01 -2.7936791721875481E-01 -2.7928422641534872E-01 -2.7920052737731299E-01 -2.7911682011705136E-01 -2.7903310464696768E-01 -2.7894938097946598E-01 -2.7886564912695000E-01 -2.7878190910182360E-01 -2.7869816091649063E-01 -2.7861440458335496E-01 -2.7853064011482048E-01 -2.7844686752329101E-01 -2.7836308682117039E-01 -2.7827929802086254E-01 -2.7819550113477132E-01 -2.7811169617530052E-01 -2.7802788315485399E-01 -2.7794406208583561E-01 -2.7786023298064938E-01 -2.7777639585169894E-01 -2.7769255071138821E-01 -2.7760869757212109E-01 -2.7752483644630149E-01 -2.7744096734633311E-01 -2.7735709028461991E-01 -2.7727320527356580E-01 -2.7718931232557448E-01 -2.7710541145304995E-01 -2.7702150266839598E-01 -2.7693758598401652E-01 -2.7685366141231532E-01 -2.7676972896569629E-01 -2.7668578865656329E-01 -2.7660184049732017E-01 -2.7651788450037079E-01 -2.7643392067811901E-01 -2.7634994904296867E-01 -2.7626596960732364E-01 -2.7618198238358782E-01 -2.7609798738416497E-01 -2.7601398462145899E-01 -2.7592997410787379E-01 -2.7584595585581317E-01 -2.7576192987768100E-01 -2.7567789618588112E-01 -2.7559385479281739E-01 -2.7550980571089373E-01 -2.7542574895251398E-01 -2.7534168453008190E-01 -2.7525761245600150E-01 -2.7517353274267647E-01 -2.7508944540251079E-01 -2.7500535044790825E-01 -2.7492124789127276E-01 -2.7483713774500818E-01 -2.7475302002151825E-01 -2.7466889473320699E-01 -2.7458476189247816E-01 -2.7450062151173565E-01 -2.7441647360338328E-01 -2.7433231817982495E-01 -2.7424815525346452E-01 -2.7416398483670584E-01 -2.7407980694195272E-01 -2.7399562158160906E-01 -2.7391142876807878E-01 -2.7382722851376556E-01 -2.7374302083107344E-01 -2.7365880573240614E-01 -2.7357458323016765E-01 -2.7349035333676169E-01 -2.7340611606459225E-01 -2.7332187142606307E-01 -2.7323761943357810E-01 -2.7315336009954116E-01 -2.7306909343635605E-01 -2.7298481945642672E-01 -2.7290053817215698E-01 -2.7281624959595074E-01 -2.7273195374021175E-01 -2.7264765061734392E-01 -2.7256334023975121E-01 -2.7247902261983725E-01 -2.7239469777000613E-01 -2.7231036570266159E-01 -2.7222602643020749E-01 -2.7214167996504773E-01 -2.7205732631958607E-01 -2.7197296550622652E-01 -2.7188859753737282E-01 -2.7180422242542890E-01 -2.7171984018279849E-01 -2.7163545082188562E-01 -2.7155105435509402E-01 -2.7146665079482762E-01 -2.7138224015349027E-01 -2.7129782244348571E-01 -2.7121339767721797E-01 -2.7112896586709079E-01 -2.7104452702550808E-01 -2.7096008116487375E-01 -2.7087562829759149E-01 -2.7079116843606532E-01 -2.7070670159269905E-01 -2.7062222777989642E-01 -2.7053774701006150E-01 -2.7045325929559799E-01 -2.7036876464890980E-01 -2.7028426308240083E-01 -2.7019975460847484E-01 -2.7011523923953573E-01 -2.7003071698798736E-01 -2.6994618786623359E-01 -2.6986165188667832E-01 -2.6977710906172536E-01 -2.6969255940377851E-01 -2.6960800292524173E-01 -2.6952343963851888E-01 -2.6943886955601370E-01 -2.6935429269013017E-01 -2.6926970905327208E-01 -2.6918511865784334E-01 -2.6910052151624775E-01 -2.6901591764088917E-01 -2.6893130704417145E-01 -2.6884668973849857E-01 -2.6876206573627420E-01 -2.6867743504990232E-01 -2.6859279769178679E-01 -2.6850815367433140E-01 -2.6842350300994006E-01 -2.6833884571101657E-01 -2.6825418178996485E-01 -2.6816951125918875E-01 -2.6808483413109208E-01 -2.6800015041807879E-01 -2.6791546013255257E-01 -2.6783076328691746E-01 -2.6774605989357725E-01 -2.6766134996493574E-01 -2.6757663351339683E-01 -2.6749191055136440E-01 -2.6740718109124229E-01 -2.6732244514543435E-01 -2.6723770272634439E-01 -2.6715295384637644E-01 -2.6706819851793412E-01 -2.6698343675342145E-01 -2.6689866856524225E-01 -2.6681389396580041E-01 -2.6672911296749968E-01 -2.6664432558274398E-01 -2.6655953182393721E-01 -2.6647473170348313E-01 -2.6638992523378568E-01 -2.6630511242724869E-01 -2.6622029329627606E-01 -2.6613546785327158E-01 -2.6605063611063912E-01 -2.6596579808078258E-01 -2.6588095377610577E-01 -2.6579610320901254E-01 -2.6571124639190680E-01 -2.6562638333719241E-01 -2.6554151405727311E-01 -2.6545663856455293E-01 -2.6537175687143555E-01 -2.6528686899032500E-01 -2.6520197493362507E-01 -2.6511707471373952E-01 -2.6503216834307236E-01 -2.6494725583402734E-01 -2.6486233719900837E-01 -2.6477741245041930E-01 -2.6469248160066394E-01 -2.6460754466214620E-01 -2.6452260164726998E-01 -2.6443765256843899E-01 -2.6435269743805723E-01 -2.6426773626852851E-01 -2.6418276907225668E-01 -2.6409779586164561E-01 -2.6401281664909909E-01 -2.6392783144702109E-01 -2.6384284026781540E-01 -2.6375784312388584E-01 -2.6367284002763636E-01 -2.6358783099147076E-01 -2.6350281602779291E-01 -2.6341779514900671E-01 -2.6333276836751590E-01 -2.6324773569572446E-01 -2.6316269714603618E-01 -2.6307765273085498E-01 -2.6299260246258460E-01 -2.6290754635362901E-01 -2.6282248441639205E-01 -2.6273741666327755E-01 -2.6265234310668933E-01 -2.6256726375903128E-01 -2.6248217863270734E-01 -2.6239708774012122E-01 -2.6231199109367692E-01 -2.6222688870577820E-01 -2.6214178058882892E-01 -2.6205666675523298E-01 -2.6197154721739424E-01 -2.6188642198771650E-01 -2.6180129107860367E-01 -2.6171615450245961E-01 -2.6163101227168811E-01 -2.6154586439869315E-01 -2.6146071089587847E-01 -2.6137555177564797E-01 -2.6129038705040553E-01 -2.6120521673255492E-01 -2.6112004083450013E-01 -2.6103485936864496E-01 -2.6094967234739319E-01 -2.6086447978314881E-01 -2.6077928168831555E-01 -2.6069407807529738E-01 -2.6060886895649810E-01 -2.6052365434432151E-01 -2.6043843425117158E-01 -2.6035320868945216E-01 -2.6026797767156701E-01 -2.6018274120992008E-01 -2.6009749931691512E-01 -2.6001225200495609E-01 -2.5992699928644680E-01 -2.5984174117379116E-01 -2.5975647767939297E-01 -2.5967120881565614E-01 -2.5958593459498441E-01 -2.5950065502978181E-01 -2.5941537013245203E-01 -2.5933007991539903E-01 -2.5924478439102666E-01 -2.5915948357173874E-01 -2.5907417746993916E-01 -2.5898886609803173E-01 -2.5890354946842037E-01 -2.5881822759350892E-01 -2.5873290048570119E-01 -2.5864756815740109E-01 -2.5856223062101247E-01 -2.5847688788893919E-01 -2.5839153997358505E-01 -2.5830618688735396E-01 -2.5822082864264978E-01 -2.5813546525187636E-01 -2.5805009672743751E-01 -2.5796472308173718E-01 -2.5787934432717913E-01 -2.5779396047616732E-01 -2.5770857154110549E-01 -2.5762317753439762E-01 -2.5753777846844750E-01 -2.5745237435565893E-01 -2.5736696520843588E-01 -2.5728155103918215E-01 -2.5719613186030160E-01 -2.5711070768419814E-01 -2.5702527852327550E-01 -2.5693984438993767E-01 -2.5685440529658843E-01 -2.5676896125563170E-01 -2.5668351227947123E-01 -2.5659805838051097E-01 -2.5651259957115480E-01 -2.5642713586380644E-01 -2.5634166727086988E-01 -2.5625619380474896E-01 -2.5617071547784748E-01 -2.5608523230256935E-01 -2.5599974429131839E-01 -2.5591425145649854E-01 -2.5582875381051351E-01 -2.5574325136576725E-01 -2.5565774413466358E-01 -2.5557223212960639E-01 -2.5548671536299961E-01 -2.5540119384724691E-01 -2.5531566759475233E-01 -2.5523013661791960E-01 -2.5514460092915270E-01 -2.5505906054085536E-01 -2.5497351546543146E-01 -2.5488796571528494E-01 -2.5480241130281961E-01 -2.5471685224043933E-01 -2.5463128854054790E-01 -2.5454572021554928E-01 -2.5446014727784722E-01 -2.5437456973984568E-01 -2.5428898761394847E-01 -2.5420340091255944E-01 -2.5411780964808245E-01 -2.5403221383292135E-01 -2.5394661347948000E-01 -2.5386100860016231E-01 -2.5377539920737208E-01 -2.5368978531351316E-01 -2.5360416693098947E-01 -2.5351854407220475E-01 -2.5343291674956303E-01 -2.5334728497546799E-01 -2.5326164876232360E-01 -2.5317600812253366E-01 -2.5309036306850208E-01 -2.5300471361263271E-01 -2.5291905976732931E-01 -2.5283340154499584E-01 -2.5274773895803615E-01 -2.5266207201885410E-01 -2.5257640073985349E-01 -2.5249072513343823E-01 -2.5240504521201218E-01 -2.5231936098797914E-01 -2.5223367247374295E-01 -2.5214797968170760E-01 -2.5206228262427688E-01 -2.5197658131385459E-01 -2.5189087576284463E-01 -2.5180516598365088E-01 -2.5171945198867718E-01 -2.5163373379032739E-01 -2.5154801140100536E-01 -2.5146228483311495E-01 -2.5137655409906001E-01 -2.5129081921124441E-01 -2.5120508018207194E-01 -2.5111933702394656E-01 -2.5103358974927215E-01 -2.5094783837045243E-01 -2.5086208289989131E-01 -2.5077632334999267E-01 -2.5069055973316040E-01 -2.5060479206179831E-01 -2.5051902034831025E-01 -2.5043324460510014E-01 -2.5034746484457182E-01 -2.5026168107912899E-01 -2.5017589332117579E-01 -2.5009010158311579E-01 -2.5000430587735306E-01 -2.4991850621629136E-01 -2.4983270261233459E-01 -2.4974689507788655E-01 -2.4966108362535117E-01 -2.4957526826713222E-01 -2.4948944901563358E-01 -2.4940362588325921E-01 -2.4931779888241284E-01 -2.4923196802549835E-01 -2.4914613332491969E-01 -2.4906029479308062E-01 -2.4897445244238503E-01 -2.4888860628523679E-01 -2.4880275633403970E-01 -2.4871690260119772E-01 -2.4863104509911460E-01 -2.4854518384019425E-01 -2.4845931883684053E-01 -2.4837345010145728E-01 -2.4828757764644843E-01 -2.4820170148421772E-01 -2.4811582162716905E-01 -2.4802993808770629E-01 -2.4794405087823329E-01 -2.4785816001115391E-01 -2.4777226549887205E-01 -2.4768636735379146E-01 -2.4760046558831617E-01 -2.4751456021484980E-01 -2.4742865124579644E-01 -2.4734273869355977E-01 -2.4725682257054377E-01 -2.4717090288915228E-01 -2.4708497966178911E-01 -2.4699905290085805E-01 -2.4691312261876314E-01 -2.4682718882790805E-01 -2.4674125154069682E-01 -2.4665531076953318E-01 -2.4656936652682099E-01 -2.4648341882496416E-01 -2.4639746767636650E-01 -2.4631151309343197E-01 -2.4622555508856425E-01 -2.4613959367416738E-01 -2.4605362886264509E-01 -2.4596766066640124E-01 -2.4588168909783981E-01 -2.4579571416936452E-01 -2.4570973589337930E-01 -2.4562375428228800E-01 -2.4553776934849447E-01 -2.4545178110440258E-01 -2.4536578956241611E-01 -2.4527979473493905E-01 -2.4519379663437513E-01 -2.4510779527312826E-01 -2.4502179066360236E-01 -2.4493578281820116E-01 -2.4484977174932865E-01 -2.4476375746938861E-01 -2.4467773999078485E-01 -2.4459171932592133E-01 -2.4450569548720186E-01 -2.4441966848703028E-01 -2.4433363833781052E-01 -2.4424760505194631E-01 -2.4416156864184169E-01 -2.4407552911990033E-01 -2.4398948649852614E-01 -2.4390344079012310E-01 -2.4381739200709490E-01 -2.4373134016184544E-01 -2.4364528526677870E-01 -2.4355922733429841E-01 -2.4347316637680844E-01 -2.4338710240671269E-01 -2.4330103543641496E-01 -2.4321496547831917E-01 -2.4312889254482911E-01 -2.4304281664834870E-01 -2.4295673780128180E-01 -2.4287065601603225E-01 -2.4278457130500386E-01 -2.4269848368060054E-01 -2.4261239315522609E-01 -2.4252629974128448E-01 -2.4244020345117945E-01 -2.4235410429731491E-01 -2.4226800229209478E-01 -2.4218189744792279E-01 -2.4209578977720281E-01 -2.4200967929233885E-01 -2.4192356600573456E-01 -2.4183744992979395E-01 -2.4175133107692082E-01 -2.4166520945951903E-01 -2.4157908508999243E-01 -2.4149295798074494E-01 -2.4140682814418024E-01 -2.4132069559270242E-01 -2.4123456033871521E-01 -2.4114842239462247E-01 -2.4106228177282807E-01 -2.4097613848573585E-01 -2.4088999254574972E-01 -2.4080384396527349E-01 -2.4071769275671101E-01 -2.4063153893246625E-01 -2.4054538250494290E-01 -2.4045922348654492E-01 -2.4037306188967611E-01 -2.4028689772674039E-01 -2.4020073101014155E-01 -2.4011456175228352E-01 -2.4002838996557008E-01 -2.3994221566240514E-01 -2.3985603885519258E-01 -2.3976985955633617E-01 -2.3968367777823985E-01 -2.3959749353330745E-01 -2.3951130683394278E-01 -2.3942511769254976E-01 -2.3933892612153224E-01 -2.3925273213329407E-01 -2.3916653574023911E-01 -2.3908033695477121E-01 -2.3899413578929418E-01 -2.3890793225621199E-01 -2.3882172636792837E-01 -2.3873551813684724E-01 -2.3864930757537250E-01 -2.3856309469590792E-01 -2.3847687951085744E-01 -2.3839066203262482E-01 -2.3830444227361403E-01 -2.3821822024622885E-01 -2.3813199596287316E-01 -2.3804576943595079E-01 -2.3795954067786568E-01 -2.3787330970102155E-01 -2.3778707651782244E-01 -2.3770084114067203E-01 -2.3761460358197428E-01 -2.3752836385413301E-01 -2.3744212196955206E-01 -2.3735587794063534E-01 -2.3726963177978666E-01 -2.3718338349940993E-01 -2.3709713311190900E-01 -2.3701088062968761E-01 -2.3692462606514975E-01 -2.3683836943069930E-01 -2.3675211073873997E-01 -2.3666585000167573E-01 -2.3657958723191042E-01 -2.3649332244184790E-01 -2.3640705564389197E-01 -2.3632078685044661E-01 -2.3623451607391549E-01 -2.3614824332670264E-01 -2.3606196862121182E-01 -2.3597569196984691E-01 -2.3588941338501185E-01 -2.3580313287911037E-01 -2.3571685046454638E-01 -2.3563056615372374E-01 -2.3554427995904631E-01 -2.3545799189291794E-01 -2.3537170196774249E-01 -2.3528541019592381E-01 -2.3519911658986575E-01 -2.3511282116197224E-01 -2.3502652392464701E-01 -2.3494022489029404E-01 -2.3485392407131711E-01 -2.3476762148012009E-01 -2.3468131712910684E-01 -2.3459501103068126E-01 -2.3450870319724715E-01 -2.3442239364120837E-01 -2.3433608237496883E-01 -2.3424976941093234E-01 -2.3416345476150274E-01 -2.3407713843908401E-01 -2.3399082045607983E-01 -2.3390450082489417E-01 -2.3381817955793088E-01 -2.3373185666759377E-01 -2.3364553216628670E-01 -2.3355920606641362E-01 -2.3347287838037825E-01 -2.3338654912058454E-01 -2.3330021829943631E-01 -2.3321388592933745E-01 -2.3312755202269181E-01 -2.3304121659190324E-01 -2.3295487964937556E-01 -2.3286854120751266E-01 -2.3278220127871840E-01 -2.3269585987539665E-01 -2.3260951700995125E-01 -2.3252317269478603E-01 -2.3243682694230491E-01 -2.3235047976491169E-01 -2.3226413117501027E-01 -2.3217778118500446E-01 -2.3209142980729819E-01 -2.3200507705429521E-01 -2.3191872293839949E-01 -2.3183236747201477E-01 -2.3174601066754502E-01 -2.3165965253739407E-01 -2.3157329309396571E-01 -2.3148693234966389E-01 -2.3140057031689240E-01 -2.3131420700805511E-01 -2.3122784243555589E-01 -2.3114147661179857E-01 -2.3105510954918707E-01 -2.3096874126012523E-01 -2.3088237175701684E-01 -2.3079600105226583E-01 -2.3070962915827603E-01 -2.3062325608745127E-01 -2.3053688185219545E-01 -2.3045050646491239E-01 -2.3036412993800598E-01 -2.3027775228388009E-01 -2.3019137351493851E-01 -2.3010499364358517E-01 -2.3001861268222390E-01 -2.2993223064325857E-01 -2.2984584753909298E-01 -2.2975946338213105E-01 -2.2967307818477661E-01 -2.2958669195943354E-01 -2.2950030471850563E-01 -2.2941391647439685E-01 -2.2932752723951100E-01 -2.2924113702625187E-01 -2.2915474584702344E-01 -2.2906835371422948E-01 -2.2898196064027387E-01 -2.2889556663756047E-01 -2.2880917171849316E-01 -2.2872277589547574E-01 -2.2863637918091215E-01 -2.2854998158720616E-01 -2.2846358312676171E-01 -2.2837718381198258E-01 -2.2829078365527264E-01 -2.2820438266903581E-01 -2.2811798086567592E-01 -2.2803157825759679E-01 -2.2794517485720228E-01 -2.2785877067689628E-01 -2.2777236572908266E-01 -2.2768596002616523E-01 -2.2759955358054784E-01 -2.2751314640463444E-01 -2.2742673851082879E-01 -2.2734032991153480E-01 -2.2725392061915631E-01 -2.2716751064609716E-01 -2.2708110000476120E-01 -2.2699468870755235E-01 -2.2690827676687442E-01 -2.2682186419513126E-01 -2.2673545100472675E-01 -2.2664903720806473E-01 -2.2656262281754908E-01 -2.2647620784558364E-01 -2.2638979230457229E-01 -2.2630337620691882E-01 -2.2621695956502716E-01 -2.2613054239130115E-01 -2.2604412469814467E-01 -2.2595770649796149E-01 -2.2587128780315555E-01 -2.2578486862613070E-01 -2.2569844897929076E-01 -2.2561202887503959E-01 -2.2552560832578106E-01 -2.2543918734391905E-01 -2.2535276594185738E-01 -2.2526634413199995E-01 -2.2517992192675060E-01 -2.2509349933851316E-01 -2.2500707637969150E-01 -2.2492065306268949E-01 -2.2483422939991099E-01 -2.2474780540375983E-01 -2.2466138108663991E-01 -2.2457495646095504E-01 -2.2448853153910911E-01 -2.2440210633350599E-01 -2.2431568085654946E-01 -2.2422925512064346E-01 -2.2414282913819183E-01 -2.2405640292159840E-01 -2.2396997648326705E-01 -2.2388354983560163E-01 -2.2379712299100599E-01 -2.2371069596188403E-01 -2.2362426876063951E-01 -2.2353784139967639E-01 -2.2345141389139847E-01 -2.2336498624820963E-01 -2.2327855848251374E-01 -2.2319213060671464E-01 -2.2310570263321616E-01 -2.2301927457442219E-01 -2.2293284644273656E-01 -2.2284641825056320E-01 -2.2275999001030586E-01 -2.2267356173436845E-01 -2.2258713343515485E-01 -2.2250070512506892E-01 -2.2241427681651449E-01 -2.2232784852189538E-01 -2.2224142025361554E-01 -2.2215499202407873E-01 -2.2206856384568885E-01 -2.2198213573084977E-01 -2.2189570769196537E-01 -2.2180927974143944E-01 -2.2172285189167584E-01 -2.2163642415507850E-01 -2.2154999654405128E-01 -2.2146356907099793E-01 -2.2137714174832240E-01 -2.2129071458842847E-01 -2.2120428760372007E-01 -2.2111786080660106E-01 -2.2103143420947524E-01 -2.2094500782474652E-01 -2.2085858166481870E-01 -2.2077215574209569E-01 -2.2068573006898132E-01 -2.2059930465787947E-01 -2.2051287952119394E-01 -2.2042645467132865E-01 -2.2034003012068745E-01 -2.2025360588167420E-01 -2.2016718196669272E-01 -2.2008075838814689E-01 -2.1999433515844058E-01 -2.1990791228997758E-01 -2.1982148979516183E-01 -2.1973506768639717E-01 -2.1964864597608746E-01 -2.1956222467663652E-01 -2.1947580380044823E-01 -2.1938938335992644E-01 -2.1930296336747501E-01 -2.1921654383549782E-01 -2.1913012477639870E-01 -2.1904370620258151E-01 -2.1895728812645010E-01 -2.1887087056040838E-01 -2.1878445351686016E-01 -2.1869803700820922E-01 -2.1861162104685961E-01 -2.1852520564521502E-01 -2.1843879081567938E-01 -2.1835237657065654E-01 -2.1826596292255035E-01 -2.1817954988376465E-01 -2.1809313746670334E-01 -2.1800672568377022E-01 -2.1792031454736918E-01 -2.1783390406990411E-01 -2.1774749426377879E-01 -2.1766108514139715E-01 -2.1757467671516303E-01 -2.1748826899748025E-01 -2.1740186200075270E-01 -2.1731545573738423E-01 -2.1722905021977867E-01 -2.1714264546033996E-01 -2.1705624147147184E-01 -2.1696983826557828E-01 -2.1688343585506309E-01 -2.1679703425233007E-01 -2.1671063346978314E-01 -2.1662423351982618E-01 -2.1653783441486302E-01 -2.1645143616729751E-01 -2.1636503878953345E-01 -2.1627864229397481E-01 -2.1619224669302534E-01 -2.1610585199908899E-01 -2.1601945822456961E-01 -2.1593306538187099E-01 -2.1584667348339703E-01 -2.1576028254155155E-01 -2.1567389256873848E-01 -2.1558750357736162E-01 -2.1550111557982482E-01 -2.1541472858853200E-01 -2.1532834261588696E-01 -2.1524195767429352E-01 -2.1515557377615563E-01 -2.1506919093387714E-01 -2.1498280915986184E-01 -2.1489642846651363E-01 -2.1481004886623634E-01 -2.1472367037143386E-01 -2.1463729299451004E-01 -2.1455091674786875E-01 -2.1446454164391382E-01 -2.1437816769504908E-01 -2.1429179491367842E-01 -2.1420542331220571E-01 -2.1411905290303485E-01 -2.1403268369856959E-01 -2.1394631571121384E-01 -2.1385994895337146E-01 -2.1377358343744632E-01 -2.1368721917584227E-01 -2.1360085618096314E-01 -2.1351449446521281E-01 -2.1342813404099514E-01 -2.1334177492071399E-01 -2.1325541711677320E-01 -2.1316906064157665E-01 -2.1308270550752817E-01 -2.1299635172703163E-01 -2.1290999931249088E-01 -2.1282364827630978E-01 -2.1273729863089222E-01 -2.1265095038864204E-01 -2.1256460356196305E-01 -2.1247825816325916E-01 -2.1239191420493420E-01 -2.1230557169939207E-01 -2.1221923065903658E-01 -2.1213289109627159E-01 -2.1204655302350098E-01 -2.1196021645312857E-01 -2.1187388139755828E-01 -2.1178754786919393E-01 -2.1170121588043939E-01 -2.1161488544369850E-01 -2.1152855657137506E-01 -2.1144222927587303E-01 -2.1135590356959624E-01 -2.1126957946494856E-01 -2.1118325697433377E-01 -2.1109693611015584E-01 -2.1101061688481851E-01 -2.1092429931072570E-01 -2.1083798340028131E-01 -2.1075166916588911E-01 -2.1066535661995300E-01 -2.1057904577487679E-01 -2.1049273664306445E-01 -2.1040642923691977E-01 -2.1032012356884655E-01 -2.1023381965124877E-01 -2.1014751749653016E-01 -2.1006121711709463E-01 -2.0997491852534605E-01 -2.0988862173368833E-01 -2.0980232675452520E-01 -2.0971603360026064E-01 -2.0962974228329839E-01 -2.0954345281604242E-01 -2.0945716521089652E-01 -2.0937087948026456E-01 -2.0928459563655044E-01 -2.0919831369215791E-01 -2.0911203365949094E-01 -2.0902575555095332E-01 -2.0893947937894897E-01 -2.0885320515588168E-01 -2.0876693289415532E-01 -2.0868066260617379E-01 -2.0859439430434087E-01 -2.0850812800106050E-01 -2.0842186370873653E-01 -2.0833560143977278E-01 -2.0824934120657307E-01 -2.0816308302154135E-01 -2.0807682689708146E-01 -2.0799057284559716E-01 -2.0790432087949243E-01 -2.0781807101117106E-01 -2.0773182325303688E-01 -2.0764557761749383E-01 -2.0755933411694572E-01 -2.0747309276379644E-01 -2.0738685357044978E-01 -2.0730061654930965E-01 -2.0721438171277989E-01 -2.0712814907326438E-01 -2.0704191864316696E-01 -2.0695569043489145E-01 -2.0686946446084178E-01 -2.0678324073342175E-01 -2.0669701926503525E-01 -2.0661080006808613E-01 -2.0652458315497821E-01 -2.0643836853811542E-01 -2.0635215622990152E-01 -2.0626594624274047E-01 -2.0617973858903610E-01 -2.0609353328119223E-01 -2.0600733033161273E-01 -2.0592112975270144E-01 -2.0583493155686228E-01 -2.0574873575649905E-01 -2.0566254236401560E-01 -2.0557635139181585E-01 -2.0549016285230362E-01 -2.0540397675788274E-01 -2.0531779312095710E-01 -2.0523161195393058E-01 -2.0514543326920695E-01 -2.0505925707919020E-01 -2.0497308339628403E-01 -2.0488691223289243E-01 -2.0480074360141920E-01 -2.0471457751426822E-01 -2.0462841398384332E-01 -2.0454225302254836E-01 -2.0445609464278719E-01 -2.0436993885696370E-01 -2.0428378567748173E-01 -2.0419763511674516E-01 -2.0411148718715783E-01 -2.0402534190112354E-01 -2.0393919927104623E-01 -2.0385305930932973E-01 -2.0376692202837787E-01 -2.0368078744059456E-01 -2.0359465555838363E-01 -2.0350852639414890E-01 -2.0342239996029429E-01 -2.0333627626922363E-01 -2.0325015533334079E-01 -2.0316403716504955E-01 -2.0307792177675388E-01 -2.0299180918085757E-01 -2.0290569938976455E-01 -2.0281959241587860E-01 -2.0273348827160359E-01 -2.0264738696934334E-01 -2.0256128852150179E-01 -2.0247519294048277E-01 -2.0238910023869014E-01 -2.0230301042852772E-01 -2.0221692352239945E-01 -2.0213083953270905E-01 -2.0204475847186049E-01 -2.0195868035225764E-01 -2.0187260518630429E-01 -2.0178653298640431E-01 -2.0170046376496154E-01 -2.0161439753437987E-01 -2.0152833430706318E-01 -2.0144227409541529E-01 -2.0135621691184008E-01 -2.0127016276874138E-01 -2.0118411167852301E-01 -2.0109806365358895E-01 -2.0101201870634294E-01 -2.0092597684918889E-01 -2.0083993809453071E-01 -2.0075390245477209E-01 -2.0066786994231706E-01 -2.0058184056956943E-01 -2.0049581434893302E-01 -2.0040979129281170E-01 -2.0032377141360933E-01 -2.0023775472372973E-01 -2.0015174123557683E-01 -2.0006573096155450E-01 -1.9997972391406649E-01 -1.9989372010551676E-01 -1.9980771954830906E-01 -1.9972172225484738E-01 -1.9963572823753550E-01 -1.9954973750877728E-01 -1.9946375008097658E-01 -1.9937776596653722E-01 -1.9929178517786317E-01 -1.9920580772735819E-01 -1.9911983362742619E-01 -1.9903386289047098E-01 -1.9894789552889641E-01 -1.9886193155510640E-01 -1.9877597098150473E-01 -1.9869001382049534E-01 -1.9860406008448206E-01 -1.9851810978586870E-01 -1.9843216293705918E-01 -1.9834621955045731E-01 -1.9826027963846699E-01 -1.9817434321349198E-01 -1.9808841028793628E-01 -1.9800248087420369E-01 -1.9791655498469798E-01 -1.9783063263182316E-01 -1.9774471382798298E-01 -1.9765879858558133E-01 -1.9757288691702204E-01 -1.9748697883470900E-01 -1.9740107435104606E-01 -1.9731517347843708E-01 -1.9722927622928593E-01 -1.9714338261599645E-01 -1.9705749265097250E-01 -1.9697160634661787E-01 -1.9688572371533652E-01 -1.9679984476953230E-01 -1.9671396952160902E-01 -1.9662809798397055E-01 -1.9654223016902073E-01 -1.9645636608916345E-01 -1.9637050575680257E-01 -1.9628464918434191E-01 -1.9619879638418539E-01 -1.9611294736873677E-01 -1.9602710215039998E-01 -1.9594126074157889E-01 -1.9585542315467730E-01 -1.9576958940209913E-01 -1.9568375949624817E-01 -1.9559793344952831E-01 -1.9551211127434343E-01 -1.9542629298309733E-01 -1.9534047858819392E-01 -1.9525466810203707E-01 -1.9516886153703056E-01 -1.9508305890557831E-01 -1.9499726022008418E-01 -1.9491146549295199E-01 -1.9482567473658563E-01 -1.9473988796338892E-01 -1.9465410518576570E-01 -1.9456832641611993E-01 -1.9448255166685541E-01 -1.9439678095037594E-01 -1.9431101427908548E-01 -1.9422525166538779E-01 -1.9413949312168680E-01 -1.9405373866038633E-01 -1.9396798829389028E-01 -1.9388224203460241E-01 -1.9379649989492670E-01 -1.9371076188726691E-01 -1.9362502802402698E-01 -1.9353929831761069E-01 -1.9345357278042194E-01 -1.9336785142486457E-01 -1.9328213426334245E-01 -1.9319642130825943E-01 -1.9311071257201934E-01 -1.9302500806702613E-01 -1.9293930780568358E-01 -1.9285361180039554E-01 -1.9276792006356586E-01 -1.9268223260759848E-01 -1.9259654944489715E-01 -1.9251087058786581E-01 -1.9242519604890831E-01 -1.9233952584042846E-01 -1.9225385997483013E-01 -1.9216819846451721E-01 -1.9208254132189356E-01 -1.9199688855936298E-01 -1.9191124018932931E-01 -1.9182559622419654E-01 -1.9173995667636839E-01 -1.9165432155824882E-01 -1.9156869088224165E-01 -1.9148306466075071E-01 -1.9139744290617983E-01 -1.9131182563093291E-01 -1.9122621284741387E-01 -1.9114060456802645E-01 -1.9105500080517462E-01 -1.9096940157126210E-01 -1.9088380687869289E-01 -1.9079821673987077E-01 -1.9071263116719961E-01 -1.9062705017308329E-01 -1.9054147376992561E-01 -1.9045590197013046E-01 -1.9037033478610171E-01 -1.9028477223024326E-01 -1.9019921431495887E-01 -1.9011366105265246E-01 -1.9002811245572782E-01 -1.8994256853658892E-01 -1.8985702930763951E-01 -1.8977149478128350E-01 -1.8968596496992474E-01 -1.8960043988596711E-01 -1.8951491954181440E-01 -1.8942940394987054E-01 -1.8934389312253935E-01 -1.8925838707222470E-01 -1.8917288581133046E-01 -1.8908738935226044E-01 -1.8900189770741849E-01 -1.8891641088920857E-01 -1.8883092891003445E-01 -1.8874545178230001E-01 -1.8865997951840910E-01 -1.8857451213076559E-01 -1.8848904963177332E-01 -1.8840359203383616E-01 -1.8831813934935795E-01 -1.8823269159074257E-01 -1.8814724877039388E-01 -1.8806181090071572E-01 -1.8797637799411196E-01 -1.8789095006298645E-01 -1.8780552711974305E-01 -1.8772010917678558E-01 -1.8763469624651793E-01 -1.8754928834134399E-01 -1.8746388547366760E-01 -1.8737848765589260E-01 -1.8729309490042284E-01 -1.8720770721966218E-01 -1.8712232462601447E-01 -1.8703694713188362E-01 -1.8695157474967344E-01 -1.8686620749178778E-01 -1.8678084537063050E-01 -1.8669548839860550E-01 -1.8661013658811659E-01 -1.8652478995156768E-01 -1.8643944850136257E-01 -1.8635411224990517E-01 -1.8626878120959922E-01 -1.8618345539284875E-01 -1.8609813481205750E-01 -1.8601281947962933E-01 -1.8592750940796821E-01 -1.8584220460947781E-01 -1.8575690509656217E-01 -1.8567161088162504E-01 -1.8558632197707031E-01 -1.8550103839530185E-01 -1.8541576014872346E-01 -1.8533048724973905E-01 -1.8524521971075247E-01 -1.8515995754416759E-01 -1.8507470076238822E-01 -1.8498944937781830E-01 -1.8490420340286154E-01 -1.8481896284992197E-01 -1.8473372773140331E-01 -1.8464849805970954E-01 -1.8456327384724441E-01 -1.8447805510641180E-01 -1.8439284184961563E-01 -1.8430763408925965E-01 -1.8422243183774786E-01 -1.8413723510748398E-01 -1.8405204391087199E-01 -1.8396685826031561E-01 -1.8388167816821882E-01 -1.8379650364698538E-01 -1.8371133470901924E-01 -1.8362617136672421E-01 -1.8354101363250408E-01 -1.8345586151876286E-01 -1.8337071503790425E-01 -1.8328557420233227E-01 -1.8320043902445060E-01 -1.8311530951666322E-01 -1.8303018569137397E-01 -1.8294506756098666E-01 -1.8285995513790521E-01 -1.8277484843453340E-01 -1.8268974746327521E-01 -1.8260465223653433E-01 -1.8251956276671472E-01 -1.8243447906622023E-01 -1.8234940114745474E-01 -1.8226432902282208E-01 -1.8217926270472604E-01 -1.8209420220557060E-01 -1.8200914753775954E-01 -1.8192409871369675E-01 -1.8183905574578607E-01 -1.8175401864643131E-01 -1.8166898742803644E-01 -1.8158396210300520E-01 -1.8149894268374156E-01 -1.8141392918264931E-01 -1.8132892161213232E-01 -1.8124391998459438E-01 -1.8115892431243946E-01 -1.8107393460807136E-01 -1.8098895088389394E-01 -1.8090397315231110E-01 -1.8081900142572660E-01 -1.8073403571654439E-01 -1.8064907603716829E-01 -1.8056412240000219E-01 -1.8047917481744991E-01 -1.8039423330191529E-01 -1.8030929786580219E-01 -1.8022436852151452E-01 -1.8013944528145615E-01 -1.8005452815803080E-01 -1.7996961716364251E-01 -1.7988471231069503E-01 -1.7979981361159220E-01 -1.7971492107873793E-01 -1.7963003472453604E-01 -1.7954515456139047E-01 -1.7946028060170499E-01 -1.7937541285788344E-01 -1.7929055134232977E-01 -1.7920569606744780E-01 -1.7912084704564132E-01 -1.7903600428931427E-01 -1.7895116781087045E-01 -1.7886633762271376E-01 -1.7878151373724810E-01 -1.7869669616687719E-01 -1.7861188492400504E-01 -1.7852708002103540E-01 -1.7844228147037211E-01 -1.7835748928441914E-01 -1.7827270347558027E-01 -1.7818792405625938E-01 -1.7810315103886032E-01 -1.7801838443578694E-01 -1.7793362425944309E-01 -1.7784887052223269E-01 -1.7776412323655955E-01 -1.7767938241482747E-01 -1.7759464806944042E-01 -1.7750992021280215E-01 -1.7742519885731661E-01 -1.7734048401538760E-01 -1.7725577569941903E-01 -1.7717107392181466E-01 -1.7708637869497845E-01 -1.7700169003131416E-01 -1.7691700794322573E-01 -1.7683233244311705E-01 -1.7674766354339186E-01 -1.7666300125645412E-01 -1.7657834559470753E-01 -1.7649369657055616E-01 -1.7640905419640374E-01 -1.7632441848465413E-01 -1.7623978944771124E-01 -1.7615516709797885E-01 -1.7607055144786093E-01 -1.7598594250976124E-01 -1.7590134029608367E-01 -1.7581674481923210E-01 -1.7573215609161036E-01 -1.7564757412562224E-01 -1.7556299893367172E-01 -1.7547843052816262E-01 -1.7539386892149875E-01 -1.7530931412608403E-01 -1.7522476615432225E-01 -1.7514022501861734E-01 -1.7505569073137311E-01 -1.7497116330499343E-01 -1.7488664275188215E-01 -1.7480212908444312E-01 -1.7471762231508020E-01 -1.7463312245619728E-01 -1.7454862952019823E-01 -1.7446414351948680E-01 -1.7437966446646699E-01 -1.7429519237354252E-01 -1.7421072725311737E-01 -1.7412626911759529E-01 -1.7404181797938023E-01 -1.7395737385087601E-01 -1.7387293674448639E-01 -1.7378850667261542E-01 -1.7370408364766682E-01 -1.7361966768204451E-01 -1.7353525878815229E-01 -1.7345085697839405E-01 -1.7336646226517366E-01 -1.7328207466089493E-01 -1.7319769417796180E-01 -1.7311332082877806E-01 -1.7302895462574761E-01 -1.7294459558127417E-01 -1.7286024370776185E-01 -1.7277589901761428E-01 -1.7269156152323542E-01 -1.7260723123702915E-01 -1.7252290817139926E-01 -1.7243859233874961E-01 -1.7235428375148409E-01 -1.7226998242200658E-01 -1.7218568836272091E-01 -1.7210140158603088E-01 -1.7201712210434045E-01 -1.7193284993005337E-01 -1.7184858507557366E-01 -1.7176432755330498E-01 -1.7168007737565133E-01 -1.7159583455501648E-01 -1.7151159910380437E-01 -1.7142737103441877E-01 -1.7134315035926356E-01 -1.7125893709074269E-01 -1.7117473124125990E-01 -1.7109053282321907E-01 -1.7100634184902411E-01 -1.7092215833107885E-01 -1.7083798228178712E-01 -1.7075381371355280E-01 -1.7066965263877976E-01 -1.7058549906987183E-01 -1.7050135301923292E-01 -1.7041721449926681E-01 -1.7033308352237742E-01 -1.7024896010096857E-01 -1.7016484424744410E-01 -1.7008073597420792E-01 -1.6999663529366388E-01 -1.6991254221821583E-01 -1.6982845676026759E-01 -1.6974437893222305E-01 -1.6966030874648605E-01 -1.6957624621546052E-01 -1.6949219135155019E-01 -1.6940814416715902E-01 -1.6932410467469083E-01 -1.6924007288654944E-01 -1.6915604881513879E-01 -1.6907203247286268E-01 -1.6898802387212503E-01 -1.6890402302532959E-01 -1.6882002994488030E-01 -1.6873604464318095E-01 -1.6865206713263547E-01 -1.6856809742564771E-01 -1.6848413553462149E-01 -1.6840018147196067E-01 -1.6831623525006911E-01 -1.6823229688135072E-01 -1.6814836637820929E-01 -1.6806444375304869E-01 -1.6798052901827282E-01 -1.6789662218628543E-01 -1.6781272326949054E-01 -1.6772883228029187E-01 -1.6764494923109335E-01 -1.6756107413429880E-01 -1.6747720700231208E-01 -1.6739334784753707E-01 -1.6730949668237760E-01 -1.6722565351923760E-01 -1.6714181837052081E-01 -1.6705799124863119E-01 -1.6697417216597249E-01 -1.6689036113494871E-01 -1.6680655816796358E-01 -1.6672276327742103E-01 -1.6663897647572490E-01 -1.6655519777527897E-01 -1.6647142718848726E-01 -1.6638766472775346E-01 -1.6630391040548159E-01 -1.6622016423407537E-01 -1.6613642622593872E-01 -1.6605269639347542E-01 -1.6596897474908948E-01 -1.6588526130518461E-01 -1.6580155607416475E-01 -1.6571785906843373E-01 -1.6563417030039540E-01 -1.6555048978245365E-01 -1.6546681752701228E-01 -1.6538315354647523E-01 -1.6529949785324627E-01 -1.6521585045972931E-01 -1.6513221137832818E-01 -1.6504858062144676E-01 -1.6496495820148893E-01 -1.6488134413085848E-01 -1.6479773842195933E-01 -1.6471414108719523E-01 -1.6463055213897021E-01 -1.6454697158968798E-01 -1.6446339945175248E-01 -1.6437983573756754E-01 -1.6429628045953695E-01 -1.6421273363006472E-01 -1.6412919526155459E-01 -1.6404566536641046E-01 -1.6396214395703615E-01 -1.6387863104583555E-01 -1.6379512664521251E-01 -1.6371163076757086E-01 -1.6362814342531454E-01 -1.6354466463084733E-01 -1.6346119439657311E-01 -1.6337773273489567E-01 -1.6329427965821902E-01 -1.6321083517894688E-01 -1.6312739930948317E-01 -1.6304397206223176E-01 -1.6296055344959648E-01 -1.6287714348398113E-01 -1.6279374217778966E-01 -1.6271034954342592E-01 -1.6262696559329370E-01 -1.6254359033979693E-01 -1.6246022379533939E-01 -1.6237686597232501E-01 -1.6229351688315766E-01 -1.6221017654024111E-01 -1.6212684495597929E-01 -1.6204352214277595E-01 -1.6196020811303513E-01 -1.6187690287916051E-01 -1.6179360645355606E-01 -1.6171031884862563E-01 -1.6162704007677300E-01 -1.6154377015040208E-01 -1.6146050908191673E-01 -1.6137725688372082E-01 -1.6129401356821815E-01 -1.6121077914781262E-01 -1.6112755363490808E-01 -1.6104433704190838E-01 -1.6096112938121743E-01 -1.6087793066523901E-01 -1.6079474090637702E-01 -1.6071156011703530E-01 -1.6062838830961770E-01 -1.6054522549652808E-01 -1.6046207169017032E-01 -1.6037892690294830E-01 -1.6029579114726583E-01 -1.6021266443552673E-01 -1.6012954678013494E-01 -1.6004643819349432E-01 -1.5996333868800866E-01 -1.5988024827608183E-01 -1.5979716697011775E-01 -1.5971409478252016E-01 -1.5963103172569307E-01 -1.5954797781204022E-01 -1.5946493305396553E-01 -1.5938189746387280E-01 -1.5929887105416593E-01 -1.5921585383724873E-01 -1.5913284582552514E-01 -1.5904984703139899E-01 -1.5896685746727407E-01 -1.5888387714555435E-01 -1.5880090607864353E-01 -1.5871794427894564E-01 -1.5863499175886442E-01 -1.5855204853080374E-01 -1.5846911460716756E-01 -1.5838619000035956E-01 -1.5830327472278377E-01 -1.5822036878684392E-01 -1.5813747220494398E-01 -1.5805458498948771E-01 -1.5797170715287900E-01 -1.5788883870752171E-01 -1.5780597966581972E-01 -1.5772313004017688E-01 -1.5764028984299699E-01 -1.5755745908668400E-01 -1.5747463778364165E-01 -1.5739182594627393E-01 -1.5730902358698462E-01 -1.5722623071817760E-01 -1.5714344735225669E-01 -1.5706067350162572E-01 -1.5697790917868870E-01 -1.5689515439584933E-01 -1.5681240916551159E-01 -1.5672967350007921E-01 -1.5664694741195617E-01 -1.5656423091354618E-01 -1.5648152401725324E-01 -1.5639882673548117E-01 -1.5631613908063374E-01 -1.5623346106511496E-01 -1.5615079270132853E-01 -1.5606813400167843E-01 -1.5598548497856846E-01 -1.5590284564440249E-01 -1.5582021601158436E-01 -1.5573759609251794E-01 -1.5565498589960708E-01 -1.5557238544525565E-01 -1.5548979474186753E-01 -1.5540721380184649E-01 -1.5532464263759652E-01 -1.5524208126152131E-01 -1.5515952968602489E-01 -1.5507698792351102E-01 -1.5499445598638356E-01 -1.5491193388704638E-01 -1.5482942163790331E-01 -1.5474691925135831E-01 -1.5466442673981512E-01 -1.5458194411567766E-01 -1.5449947139134976E-01 -1.5441700857923529E-01 -1.5433455569173807E-01 -1.5425211274126202E-01 -1.5416967974021098E-01 -1.5408725670098877E-01 -1.5400484363599931E-01 -1.5392244055764634E-01 -1.5384004747833385E-01 -1.5375766441046565E-01 -1.5367529136644556E-01 -1.5359292835867749E-01 -1.5351057539956528E-01 -1.5342823250151277E-01 -1.5334589967692380E-01 -1.5326357693820231E-01 -1.5318126429775208E-01 -1.5309896176797699E-01 -1.5301666936128089E-01 -1.5293438709006765E-01 -1.5285211496674117E-01 -1.5276985300370519E-01 -1.5268760121336369E-01 -1.5260535960812044E-01 -1.5252312820037933E-01 -1.5244090700254423E-01 -1.5235869602701899E-01 -1.5227649528620749E-01 -1.5219430479251350E-01 -1.5211212455834097E-01 -1.5202995459609370E-01 -1.5194779491817562E-01 -1.5186564553699053E-01 -1.5178350646494226E-01 -1.5170137771443473E-01 -1.5161925929787173E-01 -1.5153715122765724E-01 -1.5145505351619498E-01 -1.5137296617588891E-01 -1.5129088921914277E-01 -1.5120882265836053E-01 -1.5112676650594598E-01 -1.5104472077430300E-01 -1.5096268547583550E-01 -1.5088066062294725E-01 -1.5079864622804212E-01 -1.5071664230352402E-01 -1.5063464886179678E-01 -1.5055266591526426E-01 -1.5047069347633030E-01 -1.5038873155739879E-01 -1.5030678017087348E-01 -1.5022483932915842E-01 -1.5014290904465732E-01 -1.5006098932977410E-01 -1.4997908019691256E-01 -1.4989718165847660E-01 -1.4981529372687008E-01 -1.4973341641449683E-01 -1.4965154973376077E-01 -1.4956969369706569E-01 -1.4948784831681547E-01 -1.4940601360541392E-01 -1.4932418957526500E-01 -1.4924237623877248E-01 -1.4916057360834023E-01 -1.4907878169637220E-01 -1.4899700051527207E-01 -1.4891523007744389E-01 -1.4883347039529138E-01 -1.4875172148121849E-01 -1.4866998334762899E-01 -1.4858825600692677E-01 -1.4850653947151571E-01 -1.4842483375379964E-01 -1.4834313886618247E-01 -1.4826145482106798E-01 -1.4817978163086010E-01 -1.4809811930796257E-01 -1.4801646786477943E-01 -1.4793482731371438E-01 -1.4785319766717137E-01 -1.4777157893755419E-01 -1.4768997113726670E-01 -1.4760837427871284E-01 -1.4752678837429639E-01 -1.4744521343642125E-01 -1.4736364947749123E-01 -1.4728209650991025E-01 -1.4720055454608205E-01 -1.4711902359841067E-01 -1.4703750367929980E-01 -1.4695599480115337E-01 -1.4687449697637525E-01 -1.4679301021736924E-01 -1.4671153453653929E-01 -1.4663006994628916E-01 -1.4654861645902278E-01 -1.4646717408714396E-01 -1.4638574284305655E-01 -1.4630432273916447E-01 -1.4622291378787150E-01 -1.4614151600158160E-01 -1.4606012939269850E-01 -1.4597875397362617E-01 -1.4589738975676833E-01 -1.4581603675452900E-01 -1.4573469497931194E-01 -1.4565336444352101E-01 -1.4557204515956013E-01 -1.4549073713983304E-01 -1.4540944039674375E-01 -1.4532815494269602E-01 -1.4524688079009371E-01 -1.4516561795134070E-01 -1.4508436643884082E-01 -1.4500312626499795E-01 -1.4492189744221592E-01 -1.4484067998289868E-01 -1.4475947389944996E-01 -1.4467827920427373E-01 -1.4459709590977371E-01 -1.4451592402835392E-01 -1.4443476357241808E-01 -1.4435361455437012E-01 -1.4427247698661394E-01 -1.4419135088155327E-01 -1.4411023625159203E-01 -1.4402913310913409E-01 -1.4394804146658335E-01 -1.4386696133634358E-01 -1.4378589273081865E-01 -1.4370483566241249E-01 -1.4362379014352886E-01 -1.4354275618657172E-01 -1.4346173380394484E-01 -1.4338072300805216E-01 -1.4329972381129744E-01 -1.4321873622608458E-01 -1.4313776026481745E-01 -1.4305679593989989E-01 -1.4297584326373580E-01 -1.4289490224872897E-01 -1.4281397290728332E-01 -1.4273305525180263E-01 -1.4265214929469089E-01 -1.4257125504835180E-01 -1.4249037252518931E-01 -1.4240950173760730E-01 -1.4232864269800949E-01 -1.4224779541879992E-01 -1.4216695991238232E-01 -1.4208613619116062E-01 -1.4200532426753859E-01 -1.4192452415392015E-01 -1.4184373586270918E-01 -1.4176295940630948E-01 -1.4168219479712496E-01 -1.4160144204755942E-01 -1.4152070117001675E-01 -1.4143997217690082E-01 -1.4135925508061548E-01 -1.4127854989356456E-01 -1.4119785662815193E-01 -1.4111717529678150E-01 -1.4103650591185701E-01 -1.4095584848578244E-01 -1.4087520303096157E-01 -1.4079456955979830E-01 -1.4071394808469645E-01 -1.4063333861805991E-01 -1.4055274117229249E-01 -1.4047215575979810E-01 -1.4039158239298061E-01 -1.4031102108424381E-01 -1.4023047184599163E-01 -1.4014993469062781E-01 -1.4006940963055639E-01 -1.3998889667818104E-01 -1.3990839584590575E-01 -1.3982790714613433E-01 -1.3974743059127059E-01 -1.3966696619371849E-01 -1.3958651396588179E-01 -1.3950607392016443E-01 -1.3942564606897018E-01 -1.3934523042470295E-01 -1.3926482699976658E-01 -1.3918443580656495E-01 -1.3910405685750193E-01 -1.3902369016498131E-01 -1.3894333574140705E-01 -1.3886299359918286E-01 -1.3878266375071274E-01 -1.3870234620840047E-01 -1.3862204098464995E-01 -1.3854174809186498E-01 -1.3846146754244948E-01 -1.3838119934880724E-01 -1.3830094352334216E-01 -1.3822070007845816E-01 -1.3814046902655897E-01 -1.3806025038004854E-01 -1.3798004415133064E-01 -1.3789985035280924E-01 -1.3781966899688811E-01 -1.3773950009597113E-01 -1.3765934366246221E-01 -1.3757919970876509E-01 -1.3749906824728375E-01 -1.3741894929042198E-01 -1.3733884285058368E-01 -1.3725874894017265E-01 -1.3717866757159278E-01 -1.3709859875724789E-01 -1.3701854250954190E-01 -1.3693849884087869E-01 -1.3685846776366201E-01 -1.3677844929029581E-01 -1.3669844343318382E-01 -1.3661845020473010E-01 -1.3653846961733834E-01 -1.3645850168341245E-01 -1.3637854641535632E-01 -1.3629860382557374E-01 -1.3621867392646861E-01 -1.3613875673044479E-01 -1.3605885224990616E-01 -1.3597896049725650E-01 -1.3589908148489971E-01 -1.3581921522523965E-01 -1.3573936173068019E-01 -1.3565952101362522E-01 -1.3557969308647849E-01 -1.3549987796164398E-01 -1.3542007565152539E-01 -1.3534028616852675E-01 -1.3526050952505181E-01 -1.3518074573350444E-01 -1.3510099480628857E-01 -1.3502125675580798E-01 -1.3494153159446654E-01 -1.3486181933466809E-01 -1.3478211998881656E-01 -1.3470243356931574E-01 -1.3462276008856949E-01 -1.3454309955898172E-01 -1.3446345199295623E-01 -1.3438381740289693E-01 -1.3430419580120762E-01 -1.3422458720029221E-01 -1.3414499161255450E-01 -1.3406540905039838E-01 -1.3398583952622772E-01 -1.3390628305244634E-01 -1.3382673964145816E-01 -1.3374720930566697E-01 -1.3366769205747667E-01 -1.3358818790929108E-01 -1.3350869687351410E-01 -1.3342921896254956E-01 -1.3334975418880132E-01 -1.3327030256467326E-01 -1.3319086410256917E-01 -1.3311143881489301E-01 -1.3303202671404857E-01 -1.3295262781243972E-01 -1.3287324212247031E-01 -1.3279386965654419E-01 -1.3271451042706522E-01 -1.3263516444643730E-01 -1.3255583172706428E-01 -1.3247651228134996E-01 -1.3239720612169822E-01 -1.3231791326051293E-01 -1.3223863371019798E-01 -1.3215936748315715E-01 -1.3208011459179436E-01 -1.3200087504851346E-01 -1.3192164886571825E-01 -1.3184243605581267E-01 -1.3176323663120051E-01 -1.3168405060428570E-01 -1.3160487798747203E-01 -1.3152571879316335E-01 -1.3144657303376359E-01 -1.3136744072167653E-01 -1.3128832186930611E-01 -1.3120921648905609E-01 -1.3113012459333043E-01 -1.3105104619453284E-01 -1.3097198130506735E-01 -1.3089292993733770E-01 -1.3081389210374780E-01 -1.3073486781670152E-01 -1.3065585708860261E-01 -1.3057685993185508E-01 -1.3049787635886270E-01 -1.3041890638202935E-01 -1.3033995001375887E-01 -1.3026100726645512E-01 -1.3018207815252192E-01 -1.3010316268436320E-01 -1.3002426087438285E-01 -1.2994537273498458E-01 -1.2986649827857238E-01 -1.2978763751755001E-01 -1.2970879046432143E-01 -1.2962995713129041E-01 -1.2955113753086089E-01 -1.2947233167543662E-01 -1.2939353957742153E-01 -1.2931476124921945E-01 -1.2923599670323427E-01 -1.2915724595186984E-01 -1.2907850900752998E-01 -1.2899978588261860E-01 -1.2892107658953947E-01 -1.2884238114069657E-01 -1.2876369954849365E-01 -1.2868503182533461E-01 -1.2860637798362334E-01 -1.2852773803576362E-01 -1.2844911199415940E-01 -1.2837049987121446E-01 -1.2829190167933271E-01 -1.2821331743091796E-01 -1.2813474713837411E-01 -1.2805619081410496E-01 -1.2797764847051443E-01 -1.2789912012000637E-01 -1.2782060577498461E-01 -1.2774210544785303E-01 -1.2766361915101540E-01 -1.2758514689687572E-01 -1.2750668869783777E-01 -1.2742824456630539E-01 -1.2734981451468252E-01 -1.2727139855537289E-01 -1.2719299670078046E-01 -1.2711460896330906E-01 -1.2703623535536254E-01 -1.2695787588934476E-01 -1.2687953057765955E-01 -1.2680119943271081E-01 -1.2672288246690236E-01 -1.2664457969263815E-01 -1.2656629112232190E-01 -1.2648801676835758E-01 -1.2640975664314896E-01 -1.2633151075909993E-01 -1.2625327912861437E-01 -1.2617506176409610E-01 -1.2609685867794904E-01 -1.2601866988257698E-01 -1.2594049539038379E-01 -1.2586233521377335E-01 -1.2578418936514954E-01 -1.2570605785691616E-01 -1.2562794070147706E-01 -1.2554983791123617E-01 -1.2547174949859730E-01 -1.2539367547596431E-01 -1.2531561585574105E-01 -1.2523757065033142E-01 -1.2515953987213924E-01 -1.2508152353356833E-01 -1.2500352164702261E-01 -1.2492553422490592E-01 -1.2484756127962214E-01 -1.2476960282357506E-01 -1.2469165886916860E-01 -1.2461372942880658E-01 -1.2453581451489290E-01 -1.2445791413983137E-01 -1.2438002831602586E-01 -1.2430215705588027E-01 -1.2422430037179835E-01 -1.2414645827618412E-01 -1.2406863078144129E-01 -1.2399081789997381E-01 -1.2391301964418547E-01 -1.2383523602648015E-01 -1.2375746705926173E-01 -1.2367971275493404E-01 -1.2360197312590099E-01 -1.2352424818456637E-01 -1.2344653794333407E-01 -1.2336884241460790E-01 -1.2329116161079182E-01 -1.2321349554428959E-01 -1.2313584422750511E-01 -1.2305820767284224E-01 -1.2298058589270479E-01 -1.2290297889949671E-01 -1.2282538670562176E-01 -1.2274780932348389E-01 -1.2267024676548685E-01 -1.2259269904403458E-01 -1.2251516617153090E-01 -1.2243764816037966E-01 -1.2236014502298478E-01 -1.2228265677175006E-01 -1.2220518341907938E-01 -1.2212772497737652E-01 -1.2205028145904548E-01 -1.2197285287649001E-01 -1.2189543924211399E-01 -1.2181804056832132E-01 -1.2174065686751576E-01 -1.2166328815210130E-01 -1.2158593443448168E-01 -1.2150859572706085E-01 -1.2143127204224259E-01 -1.2135396339243082E-01 -1.2127666979002930E-01 -1.2119939124744197E-01 -1.2112212777707274E-01 -1.2104487939132533E-01 -1.2096764610260372E-01 -1.2089042792331163E-01 -1.2081322486585308E-01 -1.2073603694263181E-01 -1.2065886416605175E-01 -1.2058170654851667E-01 -1.2050456410243050E-01 -1.2042743684019706E-01 -1.2035032477422024E-01 -1.2027322791690390E-01 -1.2019614628065185E-01 -1.2011907987786802E-01 -1.2004202872095614E-01 -1.1996499282232020E-01 -1.1988797219436401E-01 -1.1981096684949140E-01 -1.1973397680010628E-01 -1.1965700205861243E-01 -1.1958004263741381E-01 -1.1950309854891419E-01 -1.1942616980551750E-01 -1.1934925641962751E-01 -1.1927235840364814E-01 -1.1919547576998321E-01 -1.1911860853103662E-01 -1.1904175669921223E-01 -1.1896492028691384E-01 -1.1888809930654537E-01 -1.1881129377051058E-01 -1.1873450369121348E-01 -1.1865772908105779E-01 -1.1858096995244743E-01 -1.1850422631778627E-01 -1.1842749818947812E-01 -1.1835078557992686E-01 -1.1827408850153634E-01 -1.1819740696671047E-01 -1.1812074098785301E-01 -1.1804409057736788E-01 -1.1796745574765893E-01 -1.1789083651113001E-01 -1.1781423288018503E-01 -1.1773764486722775E-01 -1.1766107248466211E-01 -1.1758451574489190E-01 -1.1750797466032101E-01 -1.1743144924335330E-01 -1.1735493950639263E-01 -1.1727844546184288E-01 -1.1720196712210784E-01 -1.1712550449959142E-01 -1.1704905760669745E-01 -1.1697262645582984E-01 -1.1689621105939237E-01 -1.1681981142978894E-01 -1.1674342757942341E-01 -1.1666705952069961E-01 -1.1659070726602147E-01 -1.1651437082779276E-01 -1.1643805021841738E-01 -1.1636174545029918E-01 -1.1628545653584199E-01 -1.1620918348744971E-01 -1.1613292631752617E-01 -1.1605668503847527E-01 -1.1598045966270080E-01 -1.1590425020260667E-01 -1.1582805667059670E-01 -1.1575187907907482E-01 -1.1567571744044478E-01 -1.1559957176711050E-01 -1.1552344207147586E-01 -1.1544732836594461E-01 -1.1537123066292077E-01 -1.1529514897480805E-01 -1.1521908331401041E-01 -1.1514303369293165E-01 -1.1506700012397562E-01 -1.1499098261954621E-01 -1.1491498119204727E-01 -1.1483899585388267E-01 -1.1476302661745623E-01 -1.1468707349517185E-01 -1.1461113649943330E-01 -1.1453521564264457E-01 -1.1445931093720943E-01 -1.1438342239553174E-01 -1.1430755003001541E-01 -1.1423169385306420E-01 -1.1415585387708209E-01 -1.1408003011447285E-01 -1.1400422257764038E-01 -1.1392843127898850E-01 -1.1385265623092108E-01 -1.1377689744584199E-01 -1.1370115493615508E-01 -1.1362542871426425E-01 -1.1354971879257326E-01 -1.1347402518348608E-01 -1.1339834789940643E-01 -1.1332268695273832E-01 -1.1324704235588551E-01 -1.1317141412125187E-01 -1.1309580226124130E-01 -1.1302020678825757E-01 -1.1294462771470465E-01 -1.1286906505298631E-01 -1.1279351881550648E-01 -1.1271798901466894E-01 -1.1264247566287761E-01 -1.1256697877253626E-01 -1.1249149835604887E-01 -1.1241603442581920E-01 -1.1234058699425115E-01 -1.1226515607374858E-01 -1.1218974167671529E-01 -1.1211434381555524E-01 -1.1203896250267220E-01 -1.1196359775047010E-01 -1.1188824957135271E-01 -1.1181291797772394E-01 -1.1173760298198764E-01 -1.1166230459654765E-01 -1.1158702283380789E-01 -1.1151175770617214E-01 -1.1143650922604431E-01 -1.1136127740582819E-01 -1.1128606225792773E-01 -1.1121086379474671E-01 -1.1113568202868902E-01 -1.1106051697215855E-01 -1.1098536863755909E-01 -1.1091023703729452E-01 -1.1083512218376872E-01 -1.1076002408938555E-01 -1.1068494276654883E-01 -1.1060987822766243E-01 -1.1053483048513021E-01 -1.1045979955135606E-01 -1.1038478543874380E-01 -1.1030978815969730E-01 -1.1023480772662043E-01 -1.1015984415191697E-01 -1.1008489744799090E-01 -1.1000996762724599E-01 -1.0993505470208612E-01 -1.0986015868491518E-01 -1.0978527958813696E-01 -1.0971041742415535E-01 -1.0963557220537423E-01 -1.0956074394419746E-01 -1.0948593265302885E-01 -1.0941113834427228E-01 -1.0933636103033161E-01 -1.0926160072361070E-01 -1.0918685743651343E-01 -1.0911213118144361E-01 -1.0903742197080514E-01 -1.0896272981700184E-01 -1.0888805473243757E-01 -1.0881339672951620E-01 -1.0873875582064160E-01 -1.0866413201821765E-01 -1.0858952533464812E-01 -1.0851493578233694E-01 -1.0844036337368794E-01 -1.0836580812110502E-01 -1.0829127003699196E-01 -1.0821674913375266E-01 -1.0814224542379103E-01 -1.0806775892173009E-01 -1.0799328966386218E-01 -1.0791883769800355E-01 -1.0784440303398274E-01 -1.0776998562514058E-01 -1.0769558543248885E-01 -1.0762120246832389E-01 -1.0754683675968335E-01 -1.0747248835181135E-01 -1.0739815730297314E-01 -1.0732384363397772E-01 -1.0724954729286912E-01 -1.0717526823244108E-01 -1.0710100647880640E-01 -1.0702676208269174E-01 -1.0695253507378057E-01 -1.0687832546180384E-01 -1.0680413324766780E-01 -1.0672995841192463E-01 -1.0665580093726389E-01 -1.0658166084693303E-01 -1.0650753818248437E-01 -1.0643343297180094E-01 -1.0635934522596495E-01 -1.0628527494962009E-01 -1.0621122212918943E-01 -1.0613718674935635E-01 -1.0606316881692679E-01 -1.0598916835218396E-01 -1.0591518538513635E-01 -1.0584121996085674E-01 -1.0576727211142824E-01 -1.0569334180448423E-01 -1.0561942899221390E-01 -1.0554553366775467E-01 -1.0547165585625649E-01 -1.0539779559305143E-01 -1.0532395293267871E-01 -1.0525012792026600E-01 -1.0517632052963609E-01 -1.0510253070952023E-01 -1.0502875844599172E-01 -1.0495500376277307E-01 -1.0488126669391745E-01 -1.0480754729698635E-01 -1.0473384562357328E-01 -1.0466016164343173E-01 -1.0458649528724319E-01 -1.0451284653446931E-01 -1.0443921542829290E-01 -1.0436560201410865E-01 -1.0429200632992974E-01 -1.0421842840841576E-01 -1.0414486823962937E-01 -1.0407132578660178E-01 -1.0399780103594368E-01 -1.0392429401470267E-01 -1.0385080475283597E-01 -1.0377733327560620E-01 -1.0370387960560215E-01 -1.0363044374427564E-01 -1.0355702567555464E-01 -1.0348362538889787E-01 -1.0341024288709232E-01 -1.0333687818044003E-01 -1.0326353131668500E-01 -1.0319020235648353E-01 -1.0311689130579457E-01 -1.0304359811196805E-01 -1.0297032273898528E-01 -1.0289706520746761E-01 -1.0282382554900300E-01 -1.0275060380182906E-01 -1.0267740000692833E-01 -1.0260421417143423E-01 -1.0253104625562907E-01 -1.0245789623200834E-01 -1.0238476413371618E-01 -1.0231165000674784E-01 -1.0223855387389214E-01 -1.0216547574200296E-01 -1.0209241561199797E-01 -1.0201937347469392E-01 -1.0194634932075670E-01 -1.0187334314553827E-01 -1.0180035494836588E-01 -1.0172738477427135E-01 -1.0165443270849710E-01 -1.0158149878734431E-01 -1.0150858292881428E-01 -1.0143568505107704E-01 -1.0136280519284685E-01 -1.0128994344288061E-01 -1.0121709984144446E-01 -1.0114427437331436E-01 -1.0107146702429723E-01 -1.0099867779281235E-01 -1.0092590668109820E-01 -1.0085315370468462E-01 -1.0078041888651199E-01 -1.0070770224688727E-01 -1.0063500380211718E-01 -1.0056232356189290E-01 -1.0048966150970239E-01 -1.0041701762476431E-01 -1.0034439192143862E-01 -1.0027178443961773E-01 -1.0019919521180398E-01 -1.0012662425523632E-01 -1.0005407158062986E-01 -9.9981537171875842E-02 -9.9909021004805018E-02 -9.9836523081121925E-02 -9.9764043426879917E-02 -9.9691582071241888E-02 -9.9619139048813823E-02 -9.9546714389017701E-02 -9.9474308075565274E-02 -9.9401920072109795E-02 -9.9329550372282763E-02 -9.9257199006210731E-02 -9.9184866005848429E-02 -9.9112551401925222E-02 -9.9040255221428869E-02 -9.8967977454659323E-02 -9.8895718070313957E-02 -9.8823477059387987E-02 -9.8751254448333561E-02 -9.8679050266995388E-02 -9.8606864546518860E-02 -9.8534697316107700E-02 -9.8462548570080022E-02 -9.8390418275824815E-02 -9.8318306419290999E-02 -9.8246213025826631E-02 -9.8174138125625476E-02 -9.8102081749061223E-02 -9.8030043925319499E-02 -9.7958024654682022E-02 -9.7886023908527256E-02 -9.7814041670550272E-02 -9.7742077960998694E-02 -9.7670132806714854E-02 -9.7598206238679916E-02 -9.7526298289196942E-02 -9.7454408963525876E-02 -9.7382538231992319E-02 -9.7310686073702385E-02 -9.7238852507538928E-02 -9.7167037561593228E-02 -9.7095241267354970E-02 -9.7023463658152426E-02 -9.6951704742769179E-02 -9.6879964488873122E-02 -9.6808242870097663E-02 -9.6736539907534655E-02 -9.6664855636210120E-02 -9.6593190086182709E-02 -9.6521543283323699E-02 -9.6449915237164952E-02 -9.6378305921811153E-02 -9.6306715312688126E-02 -9.6235143424074285E-02 -9.6163590285783168E-02 -9.6092055929208497E-02 -9.6020540387369083E-02 -9.5949043677629742E-02 -9.5877565771967321E-02 -9.5806106638872068E-02 -9.5734666288077794E-02 -9.5663244750890108E-02 -9.5591842058923127E-02 -9.5520458243955803E-02 -9.5449093326617981E-02 -9.5377747284567882E-02 -9.5306420087870353E-02 -9.5235111740931661E-02 -9.5163822271525103E-02 -9.5092551709238748E-02 -9.5021300086101060E-02 -9.4950067426244261E-02 -9.4878853711735447E-02 -9.4807658912742676E-02 -9.4736483029545349E-02 -9.4665326088893428E-02 -9.4594188119948769E-02 -9.4523069155402109E-02 -9.4451969222256890E-02 -9.4380888304310281E-02 -9.4309826367954888E-02 -9.4238783408875190E-02 -9.4167759456024056E-02 -9.4096754540616556E-02 -9.4025768695317855E-02 -9.3954801948717817E-02 -9.3883854287531904E-02 -9.3812925675646974E-02 -9.3742016104581410E-02 -9.3671125606681921E-02 -9.3600254215789533E-02 -9.3529401958499694E-02 -9.3458568857445079E-02 -9.3387754906677292E-02 -9.3316960079703290E-02 -9.3246184367046805E-02 -9.3175427792502735E-02 -9.3104690383765121E-02 -9.3033972169466114E-02 -9.2963273177205638E-02 -9.2892593406865370E-02 -9.2821932832443041E-02 -9.2751291439873595E-02 -9.2680669247407879E-02 -9.2610066279406600E-02 -9.2539482568853679E-02 -9.2468918151698692E-02 -9.2398373032040196E-02 -9.2327847175546693E-02 -9.2257340559144099E-02 -9.2186853204712843E-02 -9.2116385143526186E-02 -9.2045936407699425E-02 -9.1975507029431344E-02 -9.1905097015419671E-02 -9.1834706332571736E-02 -9.1764334955126037E-02 -9.1693982905215812E-02 -9.1623650217876079E-02 -9.1553336922290424E-02 -9.1483043043021101E-02 -9.1412768588899879E-02 -9.1342513537027561E-02 -9.1272277866530610E-02 -9.1202061591625000E-02 -9.1131864739542962E-02 -9.1061687338584663E-02 -9.0991529418067707E-02 -9.0921390993200984E-02 -9.0851272041330117E-02 -9.0781172537778621E-02 -9.0711092492392592E-02 -9.0641031931894656E-02 -9.0570990885811359E-02 -9.0500969387123265E-02 -9.0430967456332806E-02 -9.0360985068691627E-02 -9.0291022192835219E-02 -9.0221078836654228E-02 -9.0151155032912822E-02 -9.0081250812541286E-02 -9.0011366202761081E-02 -8.9941501222590300E-02 -8.9871655853578675E-02 -8.9801830067944927E-02 -8.9732023868147437E-02 -8.9662237281476251E-02 -8.9592470337448216E-02 -8.9522723068819504E-02 -8.9452995501819482E-02 -8.9383287617976093E-02 -8.9313599382417772E-02 -8.9243930793244275E-02 -8.9174281883504763E-02 -8.9104652686022592E-02 -8.9035043228157126E-02 -8.8965453532422009E-02 -8.8895883587231619E-02 -8.8826333363807949E-02 -8.8756802856469780E-02 -8.8687292091307671E-02 -8.8617801097215620E-02 -8.8548329905054846E-02 -8.8478878543180303E-02 -8.8409447003052630E-02 -8.8340035251444682E-02 -8.8270643277083657E-02 -8.8201271108458087E-02 -8.8131918777548723E-02 -8.8062586313321825E-02 -8.7993273742170780E-02 -8.7923981061129905E-02 -8.7854708241646581E-02 -8.7785455269850363E-02 -8.7716222167951649E-02 -8.7647008963588971E-02 -8.7577815686635335E-02 -8.7508642366941919E-02 -8.7439489006488499E-02 -8.7370355575860870E-02 -8.7301242057338732E-02 -8.7232148474286966E-02 -8.7163074857589409E-02 -8.7094021234825708E-02 -8.7024987631332915E-02 -8.6955974051548479E-02 -8.6886980469519662E-02 -8.6818006866384162E-02 -8.6749053262248507E-02 -8.6680119687109855E-02 -8.6611206169430896E-02 -8.6542312736404781E-02 -8.6473439397015253E-02 -8.6404586125842398E-02 -8.6335752900428400E-02 -8.6266939735749185E-02 -8.6198146659731634E-02 -8.6129373702762108E-02 -8.6060620897454754E-02 -8.5991888258940982E-02 -8.5923175758728890E-02 -8.5854483367378692E-02 -8.5785811098126316E-02 -8.5717158983472069E-02 -8.5648527054091039E-02 -8.5579915338352602E-02 -8.5511323852558677E-02 -8.5442752573679587E-02 -8.5374201474093581E-02 -8.5305670562446423E-02 -8.5237159868828558E-02 -8.5168669422969204E-02 -8.5100199253603181E-02 -8.5031749380436464E-02 -8.4963319783719224E-02 -8.4894910434960599E-02 -8.4826521337430461E-02 -8.4758152518755750E-02 -8.4689804008353700E-02 -8.4621475838003224E-02 -8.4553168032605319E-02 -8.4484880574579438E-02 -8.4416613432111723E-02 -8.4348366604231076E-02 -8.4280140120497546E-02 -8.4211934011209258E-02 -8.4143748305165841E-02 -8.4075583026345324E-02 -8.4007438161767103E-02 -8.3939313681256442E-02 -8.3871209580182959E-02 -8.3803125886662264E-02 -8.3735062630643245E-02 -8.3667019841024967E-02 -8.3598997543416390E-02 -8.3530995728954921E-02 -8.3463014367340729E-02 -8.3395053449617895E-02 -8.3327113002670886E-02 -8.3259193056500813E-02 -8.3191293639960862E-02 -8.3123414779668753E-02 -8.3055556471223896E-02 -8.2987718685006623E-02 -8.2919901407832036E-02 -8.2852104663572276E-02 -8.2784328481010083E-02 -8.2716572889482143E-02 -8.2648837917467202E-02 -8.2581123566264431E-02 -8.2513429808579439E-02 -8.2445756628158090E-02 -8.2378104044062178E-02 -8.2310472082076078E-02 -8.2242860772163140E-02 -8.2175270145852658E-02 -8.2107700209132078E-02 -8.2040150933263348E-02 -8.1972622297527747E-02 -8.1905114321096872E-02 -8.1837627032689070E-02 -8.1770160461947447E-02 -8.1702714638895904E-02 -8.1635289572565134E-02 -8.1567885234966442E-02 -8.1500501602142325E-02 -8.1433138689865209E-02 -8.1365796526616796E-02 -8.1298475142569687E-02 -8.1231174569289091E-02 -8.1163894820662053E-02 -8.1096635869689362E-02 -8.1029397689553015E-02 -8.0962180294216771E-02 -8.0894983714722105E-02 -8.0827807979787142E-02 -8.0760653115454231E-02 -8.0693519136390640E-02 -8.0626406022968597E-02 -8.0559313752252060E-02 -8.0492242331726360E-02 -8.0425191785711933E-02 -8.0358162141869263E-02 -8.0291153432437465E-02 -8.0224165679346815E-02 -8.0157198861005308E-02 -8.0090252947328966E-02 -8.0023327943271702E-02 -7.9956423878858207E-02 -7.9889540783834298E-02 -7.9822678686397003E-02 -7.9755837607646832E-02 -7.9689017530763975E-02 -7.9622218427454455E-02 -7.9555440298232402E-02 -7.9488683170248611E-02 -7.9421947072168320E-02 -7.9355232033924750E-02 -7.9288538080427864E-02 -7.9221865197870903E-02 -7.9155213355827717E-02 -7.9088582549684761E-02 -7.9021972805694105E-02 -7.8955384152697136E-02 -7.8888816622102925E-02 -7.8822270242053336E-02 -7.8755745001710412E-02 -7.8689240867735766E-02 -7.8622757831403975E-02 -7.8556295922382322E-02 -7.8489855172265144E-02 -7.8423435606728820E-02 -7.8357037248003913E-02 -7.8290660091421813E-02 -7.8224304111928600E-02 -7.8157969299754756E-02 -7.8091655676847740E-02 -7.8025363269504724E-02 -7.7959092107309572E-02 -7.7892842219687716E-02 -7.7826613605762929E-02 -7.7760406234886809E-02 -7.7694220090522917E-02 -7.7628055196726164E-02 -7.7561911583828413E-02 -7.7495789279382929E-02 -7.7429688308991565E-02 -7.7363608675546078E-02 -7.7297550353139233E-02 -7.7231513324537274E-02 -7.7165497609516534E-02 -7.7099503236009781E-02 -7.7033530232282280E-02 -7.6967578626514627E-02 -7.6901648426198788E-02 -7.6835739604831685E-02 -7.6769852141016975E-02 -7.6703986052277115E-02 -7.6638141367479609E-02 -7.6572318113925605E-02 -7.6506516317560058E-02 -7.6440735989279363E-02 -7.6374977107790246E-02 -7.6309239652666491E-02 -7.6243523635359259E-02 -7.6177829079940612E-02 -7.6112156014616059E-02 -7.6046504471868531E-02 -7.5980874469013318E-02 -7.5915265979880395E-02 -7.5849678975364446E-02 -7.5784113467136885E-02 -7.5718569487719614E-02 -7.5653047066118709E-02 -7.5587546226359853E-02 -7.5522066983559705E-02 -7.5456609320544737E-02 -7.5391173214802529E-02 -7.5325758671583448E-02 -7.5260365714710564E-02 -7.5194994370673077E-02 -7.5129644670037160E-02 -7.5064316635566022E-02 -7.4999010248468695E-02 -7.4933725478677382E-02 -7.4868462328912325E-02 -7.4803220830201203E-02 -7.4738001012508548E-02 -7.4672802901229365E-02 -7.4607626516136075E-02 -7.4542471842938191E-02 -7.4477338854039621E-02 -7.4412227548199913E-02 -7.4347137953577766E-02 -7.4282070099033454E-02 -7.4217024010887214E-02 -7.4151999711640285E-02 -7.4086997192414544E-02 -7.4022016427532464E-02 -7.3957057410725946E-02 -7.3892120163898692E-02 -7.3827204712476446E-02 -7.3762311087306770E-02 -7.3697439317906954E-02 -7.3632589397761503E-02 -7.3567761294909148E-02 -7.3502954997240522E-02 -7.3438170530775004E-02 -7.3373407925408099E-02 -7.3308667209388542E-02 -7.3243948408959175E-02 -7.3179251521619096E-02 -7.3114576518501118E-02 -7.3049923384975041E-02 -7.2985292143719571E-02 -7.2920682822987776E-02 -7.2856095450748976E-02 -7.2791530054069575E-02 -7.2726986635258520E-02 -7.2662465167292647E-02 -7.2597965633049766E-02 -7.2533488053146800E-02 -7.2469032455764248E-02 -7.2404598868084771E-02 -7.2340187316355387E-02 -7.2275797806297143E-02 -7.2211430312189920E-02 -7.2147084814341483E-02 -7.2082761330887341E-02 -7.2018459890145589E-02 -7.1954180518859434E-02 -7.1889923242463308E-02 -7.1825688070957794E-02 -7.1761474983610782E-02 -7.1697283961302982E-02 -7.1633115015684909E-02 -7.1568968169724967E-02 -7.1504843449982966E-02 -7.1440740886486429E-02 -7.1376660494900310E-02 -7.1312602252816368E-02 -7.1248566135935845E-02 -7.1184552154026012E-02 -7.1120560333177749E-02 -7.1056590701220029E-02 -7.0992643288045276E-02 -7.0928718111996789E-02 -7.0864815150635210E-02 -7.0800934375759988E-02 -7.0737075793939633E-02 -7.0673239433403437E-02 -7.0609425322333136E-02 -7.0545633488296747E-02 -7.0481863950870388E-02 -7.0418116692527455E-02 -7.0354391686777193E-02 -7.0290688937203430E-02 -7.0227008471641511E-02 -7.0163350317441253E-02 -7.0099714499444854E-02 -7.0036101037033727E-02 -6.9972509917228892E-02 -6.9908941115450235E-02 -6.9845394630917768E-02 -6.9781870487641950E-02 -6.9718368712036766E-02 -6.9654889334022849E-02 -6.9591432379621329E-02 -6.9527997836015210E-02 -6.9464585671177956E-02 -6.9401195878525015E-02 -6.9337828485846492E-02 -6.9274483522692165E-02 -6.9211161016162384E-02 -6.9147860990291216E-02 -6.9084583438971725E-02 -6.9021328336282509E-02 -6.8958095672783659E-02 -6.8894885468361380E-02 -6.8831697746977921E-02 -6.8768532538298774E-02 -6.8705389871996259E-02 -6.8642269746165968E-02 -6.8579172131864194E-02 -6.8516097015161578E-02 -6.8453044418331346E-02 -6.8390014368535007E-02 -6.8327006892072328E-02 -6.8264022014036238E-02 -6.8201059735896283E-02 -6.8138120032980157E-02 -6.8075202890781283E-02 -6.8012308329507914E-02 -6.7949436375718569E-02 -6.7886587054460906E-02 -6.7823760389579504E-02 -6.7760956386373958E-02 -6.7698175023638382E-02 -6.7635416285635783E-02 -6.7572680186850809E-02 -6.7509966749736985E-02 -6.7447276001562903E-02 -6.7384607972808042E-02 -6.7321962673815586E-02 -6.7259340077389637E-02 -6.7196740159690294E-02 -6.7134162937060385E-02 -6.7071608439241884E-02 -6.7009076693900299E-02 -6.6946567726751699E-02 -6.6884081549318797E-02 -6.6821618138717787E-02 -6.6759177471649181E-02 -6.6696759559386032E-02 -6.6634364428552431E-02 -6.6571992105461511E-02 -6.6509642615974557E-02 -6.6447315975391913E-02 -6.6385012164967491E-02 -6.6322731162127432E-02 -6.6260472975041965E-02 -6.6198237629735687E-02 -6.6136025152020841E-02 -6.6073835567050529E-02 -6.6011668891918007E-02 -6.5949525109108453E-02 -6.5887404193804344E-02 -6.5825306150870552E-02 -6.5763231007522224E-02 -6.5701178790561407E-02 -6.5639149524885740E-02 -6.5577143229385029E-02 -6.5515159889349417E-02 -6.5453199479191260E-02 -6.5391262000110112E-02 -6.5329347479356425E-02 -6.5267455943748900E-02 -6.5205587416175548E-02 -6.5143741915370354E-02 -6.5081919432238122E-02 -6.5020119944994362E-02 -6.4958343450721892E-02 -6.4896589970261195E-02 -6.4834859527044250E-02 -6.4773152148273491E-02 -6.4711467859113303E-02 -6.4649806653305414E-02 -6.4588168505381696E-02 -6.4526553406917209E-02 -6.4464961377624697E-02 -6.4403392441141794E-02 -6.4341846627373425E-02 -6.4280323965927436E-02 -6.4218824452723450E-02 -6.4157348056773172E-02 -6.4095894764155850E-02 -6.4034464598706181E-02 -6.3973057588752796E-02 -6.3911673760649754E-02 -6.3850313138968842E-02 -6.3788975723310548E-02 -6.3727661487465614E-02 -6.3666370416608928E-02 -6.3605102531038071E-02 -6.3543857857073546E-02 -6.3482636420512217E-02 -6.3421438246386894E-02 -6.3360263339098249E-02 -6.3299111675509223E-02 -6.3237983238949025E-02 -6.3176878043961521E-02 -6.3115796112850994E-02 -6.3054737473872510E-02 -6.2993702158933990E-02 -6.2932690177311637E-02 -6.2871701498990004E-02 -6.2810736098879202E-02 -6.2749793995982572E-02 -6.2688875222654566E-02 -6.2627979804644643E-02 -6.2567107762008439E-02 -6.2506259102659528E-02 -6.2445433807438548E-02 -6.2384631857899914E-02 -6.2323853265498420E-02 -6.2263098054073589E-02 -6.2202366248579506E-02 -6.2141657875145855E-02 -6.2080972948578055E-02 -6.2020311449602107E-02 -6.1959673355852979E-02 -6.1899058675129702E-02 -6.1838467431582861E-02 -6.1777899650584119E-02 -6.1717355359012287E-02 -6.1656834574459654E-02 -6.1596337276922812E-02 -6.1535863439520583E-02 -6.1475413068385491E-02 -6.1414986192839666E-02 -6.1354582840143487E-02 -6.1294203032859360E-02 -6.1233846787347897E-02 -6.1173514089421344E-02 -6.1113204915942423E-02 -6.1052919268106728E-02 -6.0992657169217916E-02 -6.0932418643939376E-02 -6.0872203718282780E-02 -6.0812012413882219E-02 -6.0751844719110472E-02 -6.0691700608359843E-02 -6.0631580077998209E-02 -6.0571483150207495E-02 -6.0511409849919304E-02 -6.0451360206179361E-02 -6.0391334245220731E-02 -6.0331331956750521E-02 -6.0271353309778453E-02 -6.0211398295398434E-02 -6.0151466938531503E-02 -6.0091559266909310E-02 -6.0031675308229372E-02 -5.9971815087928815E-02 -5.9911978599115040E-02 -5.9852165810838416E-02 -5.9792376710909347E-02 -5.9732611325260983E-02 -5.9672869683279742E-02 -5.9613151808552374E-02 -5.9553457721580168E-02 -5.9493787420996772E-02 -5.9434140884329273E-02 -5.9374518099483936E-02 -5.9314919083493359E-02 -5.9255343858684577E-02 -5.9195792452400961E-02 -5.9136264893644042E-02 -5.9076761186239522E-02 -5.9017281302614272E-02 -5.8957825223723968E-02 -5.8898392966696932E-02 -5.8838984556578107E-02 -5.8779600019857700E-02 -5.8720239383617201E-02 -5.8660902654946702E-02 -5.8601589808655929E-02 -5.8542300824473065E-02 -5.8483035718339807E-02 -5.8423794516570246E-02 -5.8364577244475010E-02 -5.8305383926470784E-02 -5.8246214571653090E-02 -5.8187069156917681E-02 -5.8127947660608990E-02 -5.8068850095358802E-02 -5.8009776486940154E-02 -5.7950726861105445E-02 -5.7891701243541260E-02 -5.7832699647524848E-02 -5.7773722051906957E-02 -5.7714768433352506E-02 -5.7655838800227739E-02 -5.7596933176896986E-02 -5.7538051588575695E-02 -5.7479194061446061E-02 -5.7420360611974738E-02 -5.7361551220445180E-02 -5.7302765861479747E-02 -5.7244004541861744E-02 -5.7185267289447748E-02 -5.7126554129971203E-02 -5.7067865084880015E-02 -5.7009200169092687E-02 -5.6950559367259873E-02 -5.6891942656144154E-02 -5.6833350038143396E-02 -5.6774781537411667E-02 -5.6716237179295498E-02 -5.6657716990272673E-02 -5.6599220991525562E-02 -5.6540749167773768E-02 -5.6482301489760640E-02 -5.6423877954945884E-02 -5.6365478590070933E-02 -5.6307103422215919E-02 -5.6248752475039882E-02 -5.6190425768475022E-02 -5.6132123294029772E-02 -5.6073845028286655E-02 -5.6015590965095563E-02 -5.5957361122915467E-02 -5.5899155523698132E-02 -5.5840974195878003E-02 -5.5782817166890486E-02 -5.5724684430269296E-02 -5.5666575956040014E-02 -5.5608491732655391E-02 -5.5550431783276392E-02 -5.5492396134422924E-02 -5.5434384810695223E-02 -5.5376397834735587E-02 -5.5318435203725938E-02 -5.5260496891905202E-02 -5.5202582886740875E-02 -5.5144693209506698E-02 -5.5086827886109260E-02 -5.5028986939952028E-02 -5.4971170392674240E-02 -5.4913378245429842E-02 -5.4855610475528879E-02 -5.4797867068557264E-02 -5.4740148040781061E-02 -5.4682453414787890E-02 -5.4624783215341650E-02 -5.4567137468100255E-02 -5.4509516179028134E-02 -5.4451919324423850E-02 -5.4394346885790916E-02 -5.4336798877297435E-02 -5.4279275321938728E-02 -5.4221776244392367E-02 -5.4164301670456064E-02 -5.4106851609520827E-02 -5.4049426038784404E-02 -5.3992024937560439E-02 -5.3934648318703579E-02 -5.3877296206955048E-02 -5.3819968626218809E-02 -5.3762665599552915E-02 -5.3705387137662083E-02 -5.3648133219535661E-02 -5.3590903823307098E-02 -5.3533698959652806E-02 -5.3476518654464157E-02 -5.3419362932004846E-02 -5.3362231814411222E-02 -5.3305125314908622E-02 -5.3248043416677861E-02 -5.3190986098845150E-02 -5.3133953366186232E-02 -5.3076945239209125E-02 -5.3019961740842336E-02 -5.2963002897534549E-02 -5.2906068728101337E-02 -5.2849159214926347E-02 -5.2792274331817456E-02 -5.2735414081573222E-02 -5.2678578489961603E-02 -5.2621767582126375E-02 -5.2564981380587565E-02 -5.2508219902614527E-02 -5.2451483135123031E-02 -5.2394771054397681E-02 -5.2338083658957917E-02 -5.2281420970079540E-02 -5.2224783010942633E-02 -5.2168169807140251E-02 -5.2111581380806932E-02 -5.2055017721480079E-02 -5.1998478802877952E-02 -5.1941964619207241E-02 -5.1885475191865447E-02 -5.1829010544296075E-02 -5.1772570700627261E-02 -5.1716155682722850E-02 -5.1659765483869080E-02 -5.1603400078930967E-02 -5.1547059459936290E-02 -5.1490743648809491E-02 -5.1434452669890864E-02 -5.1378186544992974E-02 -5.1321945293812343E-02 -5.1265728912950691E-02 -5.1209537379591087E-02 -5.1153370683767692E-02 -5.1097228845603915E-02 -5.1041111889022626E-02 -5.0985019836083216E-02 -5.0928952707311764E-02 -5.0872910502433061E-02 -5.0816893198553849E-02 -5.0760900781859478E-02 -5.0704933268724280E-02 -5.0648990681360972E-02 -5.0593073044626416E-02 -5.0537180384329423E-02 -5.0481312704742862E-02 -5.0425469979867396E-02 -5.0369652190450191E-02 -5.0313859352814690E-02 -5.0258091491931701E-02 -5.0202348631145921E-02 -5.0146630792514101E-02 -5.0090937982720726E-02 -5.0035270180452063E-02 -4.9979627367257411E-02 -4.9924009555595360E-02 -4.9868416768128518E-02 -4.9812849027857667E-02 -4.9757306358036442E-02 -4.9701788768630378E-02 -4.9646296237817536E-02 -4.9590828743772838E-02 -4.9535386297956154E-02 -4.9479968926267354E-02 -4.9424576652371516E-02 -4.9369209497273657E-02 -4.9313867472318529E-02 -4.9258550558713414E-02 -4.9203258734521124E-02 -4.9147992005598842E-02 -4.9092750393694130E-02 -4.9037533922466736E-02 -4.8982342618161159E-02 -4.8927176498426372E-02 -4.8872035543588037E-02 -4.8816919726271293E-02 -4.8761829049928769E-02 -4.8706763540811757E-02 -4.8651723223745023E-02 -4.8596708119732851E-02 -4.8541718244145708E-02 -4.8486753582794542E-02 -4.8431814112134729E-02 -4.8376899831667958E-02 -4.8322010762923376E-02 -4.8267146928714269E-02 -4.8212308352886396E-02 -4.8157495055472815E-02 -4.8102707025763081E-02 -4.8047944239288543E-02 -4.7993206691317507E-02 -4.7938494401533964E-02 -4.7883807391807996E-02 -4.7829145686325888E-02 -4.7774509306968346E-02 -4.7719898245549508E-02 -4.7665312475868547E-02 -4.7610751989450951E-02 -4.7556216806499102E-02 -4.7501706950011394E-02 -4.7447222444047747E-02 -4.7392763311194380E-02 -4.7338329546516372E-02 -4.7283921123494790E-02 -4.7229538030715841E-02 -4.7175180289386880E-02 -4.7120847924135303E-02 -4.7066540955633646E-02 -4.7012259402217114E-02 -4.6958003262313211E-02 -4.6903772514133114E-02 -4.6849567145579550E-02 -4.6795387173581747E-02 -4.6741232620127561E-02 -4.6687103508319415E-02 -4.6632999861274643E-02 -4.6578921680676171E-02 -4.6524868940089878E-02 -4.6470841621198869E-02 -4.6416839742270989E-02 -4.6362863329553763E-02 -4.6308912405027422E-02 -4.6254986987711154E-02 -4.6201087081460146E-02 -4.6147212664433154E-02 -4.6093363718902811E-02 -4.6039540259478033E-02 -4.5985742310470631E-02 -4.5931969893344353E-02 -4.5878223027116923E-02 -4.5824501719186908E-02 -4.5770805951307968E-02 -4.5717135705734803E-02 -4.5663490990805918E-02 -4.5609871825528003E-02 -4.5556278231631539E-02 -4.5502710233750909E-02 -4.5449167845335640E-02 -4.5395651046578396E-02 -4.5342159814754007E-02 -4.5288694155672528E-02 -4.5235254090342458E-02 -4.5181839641296018E-02 -4.5128450832997602E-02 -4.5075087681193407E-02 -4.5021750166895760E-02 -4.4968438264849135E-02 -4.4915151978435805E-02 -4.4861891330812434E-02 -4.4808656344624893E-02 -4.4755447040879269E-02 -4.4702263434781814E-02 -4.4649105511962321E-02 -4.4595973249625713E-02 -4.4542866648762454E-02 -4.4489785731593262E-02 -4.4436730520179372E-02 -4.4383701034432593E-02 -4.4330697290131643E-02 -4.4277719275875038E-02 -4.4224766969140281E-02 -4.4171840367119908E-02 -4.4118939489750590E-02 -4.4066064358222863E-02 -4.4013214993714835E-02 -4.3960391414692428E-02 -4.3907593613025854E-02 -4.3854821565812961E-02 -4.3802075266711836E-02 -4.3749354734269906E-02 -4.3696659989548359E-02 -4.3643991055671925E-02 -4.3591347954269985E-02 -4.3538730678452008E-02 -4.3486139200485295E-02 -4.3433573508918813E-02 -4.3381033624744048E-02 -4.3328519572236622E-02 -4.3276031373263010E-02 -4.3223569047729608E-02 -4.3171132592144598E-02 -4.3118721980827515E-02 -4.3066337200339366E-02 -4.3013978270587477E-02 -4.2961645216066949E-02 -4.2909338056426584E-02 -4.2857056808578466E-02 -4.2804801472626858E-02 -4.2752572028104938E-02 -4.2700368461226774E-02 -4.2648190785013508E-02 -4.2596039018463976E-02 -4.2543913184035650E-02 -4.2491813305987738E-02 -4.2439739390136795E-02 -4.2387691413022448E-02 -4.2335669355373674E-02 -4.2283673228597884E-02 -4.2231703052875783E-02 -4.2179758850033937E-02 -4.2127840643090060E-02 -4.2075948440197776E-02 -4.2024082218730850E-02 -4.1972241957564368E-02 -4.1920427667871553E-02 -4.1868639372889829E-02 -4.1816877093984087E-02 -4.1765140850589112E-02 -4.1713430651734724E-02 -4.1661746478364167E-02 -4.1610088310051460E-02 -4.1558456154284502E-02 -4.1506850032348212E-02 -4.1455269964958401E-02 -4.1403715971960277E-02 -4.1352188065157620E-02 -4.1300686227410920E-02 -4.1249210437230725E-02 -4.1197760698753874E-02 -4.1146337032638175E-02 -4.1094939459984374E-02 -4.1043568002177754E-02 -4.0992222674250844E-02 -4.0940903460242394E-02 -4.0889610336244830E-02 -4.0838343302909301E-02 -4.0787102381361705E-02 -4.0735887592744123E-02 -4.0684698956851804E-02 -4.0633536489052817E-02 -4.0582400176889084E-02 -4.0531289997498311E-02 -4.0480205948951575E-02 -4.0429148051860216E-02 -4.0378116327088563E-02 -4.0327110792993004E-02 -4.0276131464807741E-02 -4.0225178333806670E-02 -4.0174251378964798E-02 -4.0123350595473256E-02 -4.0072476001194929E-02 -4.0021627615706261E-02 -3.9970805458748225E-02 -3.9920009548228406E-02 -3.9869239878313319E-02 -3.9818496427006682E-02 -3.9767779185232249E-02 -3.9717088167771801E-02 -3.9666423392887999E-02 -3.9615784883970724E-02 -3.9565172664642712E-02 -3.9514586731674239E-02 -3.9464027058055413E-02 -3.9413493628995100E-02 -3.9362986460493680E-02 -3.9312505573151288E-02 -3.9262050988693183E-02 -3.9211622728629297E-02 -3.9161220793689215E-02 -3.9110845160828286E-02 -3.9060495814755361E-02 -3.9010172768498143E-02 -3.8959876040788953E-02 -3.8909605652159278E-02 -3.8859361623822419E-02 -3.8809143959389024E-02 -3.8758952636424558E-02 -3.8708787637534499E-02 -3.8658648975179420E-02 -3.8608536669581701E-02 -3.8558450740406390E-02 -3.8508391206799254E-02 -3.8458358074893992E-02 -3.8408351325820524E-02 -3.8358370942283185E-02 -3.8308416931761097E-02 -3.8258489310553340E-02 -3.8208588098717126E-02 -3.8158713319817752E-02 -3.8108864984712894E-02 -3.8059043071818434E-02 -3.8009247558557627E-02 -3.7959478453221916E-02 -3.7909735778233707E-02 -3.7860019553377769E-02 -3.7810329795133900E-02 -3.7760666512302934E-02 -3.7711029688592516E-02 -3.7661419304709613E-02 -3.7611835365225318E-02 -3.7562277889064383E-02 -3.7512746895806713E-02 -3.7463242405755590E-02 -3.7413764432480144E-02 -3.7364312959019035E-02 -3.7314887961525059E-02 -3.7265489441751835E-02 -3.7216117421377481E-02 -3.7166771920820747E-02 -3.7117452956834482E-02 -3.7068160541646453E-02 -3.7018894662867542E-02 -3.6969655299768298E-02 -3.6920442451474661E-02 -3.6871256137074947E-02 -3.6822096375743997E-02 -3.6772963184523430E-02 -3.6723856577264673E-02 -3.6674776544481730E-02 -3.6625723065625844E-02 -3.6576696136147814E-02 -3.6527695772340545E-02 -3.6478721992418077E-02 -3.6429774816513369E-02 -3.6380854262895689E-02 -3.6331960323397916E-02 -3.6283092973135964E-02 -3.6234252203704104E-02 -3.6185438034837071E-02 -3.6136650487916762E-02 -3.6087889579278602E-02 -3.6039155322624861E-02 -3.5990447712998669E-02 -3.5941766730035567E-02 -3.5893112364505569E-02 -3.5844484632629493E-02 -3.5795883553743128E-02 -3.5747309145474429E-02 -3.5698761424071197E-02 -3.5650240387651605E-02 -3.5601746014963895E-02 -3.5553278293027804E-02 -3.5504837235573170E-02 -3.5456422861088722E-02 -3.5408035187612277E-02 -3.5359674232605137E-02 -3.5311339998344564E-02 -3.5263032466155010E-02 -3.5214751621818703E-02 -3.5166497474281098E-02 -3.5118270038445407E-02 -3.5070069333723627E-02 -3.5021895382428052E-02 -3.4973748190576026E-02 -3.4925627734892294E-02 -3.4877533995073477E-02 -3.4829466982015916E-02 -3.4781426716570661E-02 -3.4733413217228726E-02 -3.4685426500356602E-02 -3.4637466571940896E-02 -3.4589533413790494E-02 -3.4541627007842364E-02 -3.4493747361210546E-02 -3.4445894491803013E-02 -3.4398068418130728E-02 -3.4350269159339961E-02 -3.4302496725090711E-02 -3.4254751095465961E-02 -3.4207032247793381E-02 -3.4159340188115242E-02 -3.4111674938506260E-02 -3.4064036518243225E-02 -3.4016424942229832E-02 -3.3968840219358809E-02 -3.3921282335007755E-02 -3.3873751269947315E-02 -3.3826247025537916E-02 -3.3778769618115871E-02 -3.3731319064918767E-02 -3.3683895384261191E-02 -3.3636498589860384E-02 -3.3589128669122212E-02 -3.3541785601268484E-02 -3.3494469384690688E-02 -3.3447180035783432E-02 -3.3399917571761799E-02 -3.3352682010151784E-02 -3.3305473365127188E-02 -3.3258291625129999E-02 -3.3211136767397592E-02 -3.3164008788057982E-02 -3.3116907706181802E-02 -3.3069833541075989E-02 -3.3022786308249966E-02 -3.2975766020476555E-02 -3.2928772670100241E-02 -3.2881806237465235E-02 -3.2834866715526496E-02 -3.2787954117245798E-02 -3.2741068458201752E-02 -3.2694209757860811E-02 -3.2647378035179760E-02 -3.2600573285072008E-02 -3.2553795483922426E-02 -3.2507044620059836E-02 -3.2460320707175305E-02 -3.2413623762483822E-02 -3.2366953805790084E-02 -3.2320310856855931E-02 -3.2273694912399231E-02 -3.2227105946138979E-02 -3.2180543942305469E-02 -3.2134008916053246E-02 -3.2087500887558434E-02 -3.2041019876029038E-02 -3.1994565899696750E-02 -3.1948138957582264E-02 -3.1901739023955232E-02 -3.1855366080804165E-02 -3.1809020143579440E-02 -3.1762701234691208E-02 -3.1716409370604305E-02 -3.1670144563845204E-02 -3.1623906815644240E-02 -3.1577696108476272E-02 -3.1531512427819403E-02 -3.1485355782081996E-02 -3.1439226186585401E-02 -3.1393123657506926E-02 -3.1347048211673133E-02 -3.1300999855334834E-02 -3.1254978571640710E-02 -3.1208984344041447E-02 -3.1163017177601633E-02 -3.1117077086075990E-02 -3.1071164085790363E-02 -3.1025278195770830E-02 -3.0979419425580343E-02 -3.0933587757164170E-02 -3.0887783170153209E-02 -3.0842005667404009E-02 -3.0796255263948833E-02 -3.0750531977298740E-02 -3.0704835828221359E-02 -3.0659166829325346E-02 -3.0613524960968599E-02 -3.0567910198005841E-02 -3.0522322543214190E-02 -3.0476762018278401E-02 -3.0431228641451306E-02 -3.0385722424233694E-02 -3.0340243373942172E-02 -3.0294791479929296E-02 -3.0249366726552932E-02 -3.0203969112356701E-02 -3.0158598648335928E-02 -3.0113255348177079E-02 -3.0067939230855288E-02 -3.0022650312147028E-02 -2.9977388580319970E-02 -2.9932154012576859E-02 -2.9886946604463338E-02 -2.9841766372317311E-02 -2.9796613333287463E-02 -2.9751487503576739E-02 -2.9706388896707712E-02 -2.9661317502241956E-02 -2.9616273296715907E-02 -2.9571256272970973E-02 -2.9526266447884475E-02 -2.9481303839713244E-02 -2.9436368464542499E-02 -2.9391460336320414E-02 -2.9346579447493231E-02 -2.9301725775082759E-02 -2.9256899308939304E-02 -2.9212100063938994E-02 -2.9167328057412952E-02 -2.9122583304789687E-02 -2.9077865820009197E-02 -2.9033175600031141E-02 -2.8988512625990503E-02 -2.8943876886545043E-02 -2.8899268390622620E-02 -2.8854687150892944E-02 -2.8810133184797072E-02 -2.8765606511366580E-02 -2.8721107130568656E-02 -2.8676635019414521E-02 -2.8632190162011708E-02 -2.8587772570479345E-02 -2.8543382262528380E-02 -2.8499019253809568E-02 -2.8454683558521789E-02 -2.8410375176977185E-02 -2.8366094087893628E-02 -2.8321840274397200E-02 -2.8277613747428921E-02 -2.8233414525487593E-02 -2.8189242624909475E-02 -2.8145098060281877E-02 -2.8100980834091262E-02 -2.8056890924369391E-02 -2.8012828311239964E-02 -2.7968793004926492E-02 -2.7924785026513896E-02 -2.7880804391635445E-02 -2.7836851110481609E-02 -2.7792925186153904E-02 -2.7749026603452680E-02 -2.7705155346551203E-02 -2.7661311419053855E-02 -2.7617494834058110E-02 -2.7573705606733612E-02 -2.7529943754823694E-02 -2.7486209288433129E-02 -2.7442502189921138E-02 -2.7398822437424468E-02 -2.7355170031047940E-02 -2.7311544984827782E-02 -2.7267947314638882E-02 -2.7224377039041396E-02 -2.7180834170858242E-02 -2.7137318694395857E-02 -2.7093830586738359E-02 -2.7050369845621730E-02 -2.7006936485702172E-02 -2.6963530522185870E-02 -2.6920151970389845E-02 -2.6876800842056521E-02 -2.6833477125903518E-02 -2.6790180802165348E-02 -2.6746911866588077E-02 -2.6703670331331433E-02 -2.6660456209970488E-02 -2.6617269517878499E-02 -2.6574110268279154E-02 -2.6530978452711802E-02 -2.6487874051748201E-02 -2.6444797058080623E-02 -2.6401747481063172E-02 -2.6358725332892709E-02 -2.6315730632046241E-02 -2.6272763396411311E-02 -2.6229823618074372E-02 -2.6186911271876018E-02 -2.6144026346520216E-02 -2.6101168855820971E-02 -2.6058338816100944E-02 -2.6015536243368213E-02 -2.5972761152396370E-02 -2.5930013537329811E-02 -2.5887293374370266E-02 -2.5844600650202700E-02 -2.5801935377188823E-02 -2.5759297571328159E-02 -2.5716687248708264E-02 -2.5674104424806450E-02 -2.5631549096528070E-02 -2.5589021239902917E-02 -2.5546520839256803E-02 -2.5504047907759491E-02 -2.5461602463564822E-02 -2.5419184519827331E-02 -2.5376794086714283E-02 -2.5334431163216060E-02 -2.5292095732130246E-02 -2.5249787779927854E-02 -2.5207507313354013E-02 -2.5165254344551920E-02 -2.5123028888433624E-02 -2.5080830961778759E-02 -2.5038660568017457E-02 -2.4996517685293197E-02 -2.4954402293894770E-02 -2.4912314401347429E-02 -2.4870254024381221E-02 -2.4828221177516603E-02 -2.4786215873192415E-02 -2.4744238115228499E-02 -2.4702287886282041E-02 -2.4660365168741948E-02 -2.4618469967023743E-02 -2.4576602295480872E-02 -2.4534762168032798E-02 -2.4492949598019714E-02 -2.4451164591636574E-02 -2.4409407131688588E-02 -2.4367677198293691E-02 -2.4325974793420087E-02 -2.4284299931918017E-02 -2.4242652627714342E-02 -2.4201032893047713E-02 -2.4159440735471546E-02 -2.4117876142553049E-02 -2.4076339097356937E-02 -2.4034829597700230E-02 -2.3993347652703695E-02 -2.3951893274056901E-02 -2.3910466478049480E-02 -2.3869067277207490E-02 -2.3827695658516338E-02 -2.3786351600376766E-02 -2.3745035098605899E-02 -2.3703746166228404E-02 -2.3662484816749148E-02 -2.3621251063007088E-02 -2.3580044915244867E-02 -2.3538866363663501E-02 -2.3497715389135958E-02 -2.3456591985429688E-02 -2.3415496162814374E-02 -2.3374427933289522E-02 -2.3333387311183146E-02 -2.3292374309481324E-02 -2.3251388920309056E-02 -2.3210431122825288E-02 -2.3169500907673148E-02 -2.3128598284776297E-02 -2.3087723266291705E-02 -2.3046875866414601E-02 -2.3006056098767890E-02 -2.2965263957818276E-02 -2.2924499422487029E-02 -2.2883762481485648E-02 -2.2843053145583887E-02 -2.2802371428240754E-02 -2.2761717341798753E-02 -2.2721090897548677E-02 -2.2680492091331616E-02 -2.2639920902769770E-02 -2.2599377319071762E-02 -2.2558861351190656E-02 -2.2518373013893419E-02 -2.2477912318679051E-02 -2.2437479275090974E-02 -2.2397073881044251E-02 -2.2356696118705589E-02 -2.2316345974792248E-02 -2.2276023457522963E-02 -2.2235728580067057E-02 -2.2195461353836647E-02 -2.2155221788951379E-02 -2.2115009885622487E-02 -2.2074825626671488E-02 -2.2034668997333074E-02 -2.1994540004079421E-02 -2.1954438660033854E-02 -2.1914364976918399E-02 -2.1874318965203556E-02 -2.1834300626918286E-02 -2.1794309944754422E-02 -2.1754346901767963E-02 -2.1714411502124144E-02 -2.1674503758834739E-02 -2.1634623684436447E-02 -2.1594771290896323E-02 -2.1554946582936833E-02 -2.1515149543303452E-02 -2.1475380152766312E-02 -2.1435638412820441E-02 -2.1395924336366341E-02 -2.1356237936552381E-02 -2.1316579226713359E-02 -2.1276948214303419E-02 -2.1237344882776444E-02 -2.1197769210926354E-02 -2.1158221196938359E-02 -2.1118700852850607E-02 -2.1079208191083651E-02 -2.1039743224213731E-02 -2.1000305961022647E-02 -2.0960896389470192E-02 -2.0921514491127204E-02 -2.0882160261257079E-02 -2.0842833707764619E-02 -2.0803534840933380E-02 -2.0764263675739358E-02 -2.0725020224560756E-02 -2.0685804475283190E-02 -2.0646616405281804E-02 -2.0607456007557312E-02 -2.0568323293760439E-02 -2.0529218276308416E-02 -2.0490140966569734E-02 -2.0451091373981243E-02 -2.0412069490367422E-02 -2.0373075297389211E-02 -2.0334108786712955E-02 -2.0295169965600143E-02 -2.0256258843463076E-02 -2.0217375433312725E-02 -2.0178519747836618E-02 -2.0139691780515692E-02 -2.0100891510299871E-02 -2.0062118926378068E-02 -2.0023374039183996E-02 -1.9984656861159116E-02 -1.9945967401653525E-02 -1.9907305668353147E-02 -1.9868671656960189E-02 -1.9830065351427950E-02 -1.9791486741347012E-02 -1.9752935832467414E-02 -1.9714412633481969E-02 -1.9675917155578801E-02 -1.9637449410774877E-02 -1.9599009397556495E-02 -1.9560597097269102E-02 -1.9522212495476560E-02 -1.9483855596400666E-02 -1.9445526408735682E-02 -1.9407224945466268E-02 -1.9368951222059359E-02 -1.9330705239848256E-02 -1.9292486976924712E-02 -1.9254296414534872E-02 -1.9216133558864076E-02 -1.9177998423238182E-02 -1.9139891018152774E-02 -1.9101811351768659E-02 -1.9063759424757475E-02 -1.9025735221905996E-02 -1.8987738728510836E-02 -1.8949769946051579E-02 -1.8911828882451302E-02 -1.8873915548969278E-02 -1.8836029960322860E-02 -1.8798172122119202E-02 -1.8760342013786315E-02 -1.8722539612998971E-02 -1.8684764921951414E-02 -1.8647017955336118E-02 -1.8609298725160418E-02 -1.8571607239674267E-02 -1.8533943502201645E-02 -1.8496307498516794E-02 -1.8458699211517826E-02 -1.8421118639348630E-02 -1.8383565790334688E-02 -1.8346040674482506E-02 -1.8308543304414608E-02 -1.8271073688356478E-02 -1.8233631811011404E-02 -1.8196217650685496E-02 -1.8158831203651554E-02 -1.8121472481667122E-02 -1.8084141496654611E-02 -1.8046838259754713E-02 -1.8009562778738591E-02 -1.7972315039149311E-02 -1.7935095017868368E-02 -1.7897902708950593E-02 -1.7860738125569577E-02 -1.7823601280733289E-02 -1.7786492183929286E-02 -1.7749410842029145E-02 -1.7712357243601803E-02 -1.7675331367475254E-02 -1.7638333205588497E-02 -1.7601362768848230E-02 -1.7564420069087313E-02 -1.7527505115952878E-02 -1.7490617917282018E-02 -1.7453758464198242E-02 -1.7416926736052798E-02 -1.7380122722101259E-02 -1.7343346430544495E-02 -1.7306597871894380E-02 -1.7269877057963460E-02 -1.7233184000122134E-02 -1.7196518692310477E-02 -1.7159881112508383E-02 -1.7123271246519810E-02 -1.7086689100736695E-02 -1.7050134684887069E-02 -1.7013608010507220E-02 -1.6977109089461168E-02 -1.6940637918393557E-02 -1.6904194475947078E-02 -1.6867778746083119E-02 -1.6831390733403229E-02 -1.6795030447036046E-02 -1.6758697899635810E-02 -1.6722393105644599E-02 -1.6686116063969747E-02 -1.6649866749721985E-02 -1.6613645142530015E-02 -1.6577451250372688E-02 -1.6541285088529780E-02 -1.6505146666540092E-02 -1.6469035989547180E-02 -1.6432953055437512E-02 -1.6396897847862177E-02 -1.6360870351732618E-02 -1.6324870569152036E-02 -1.6288898508520222E-02 -1.6252954179942356E-02 -1.6217037595161441E-02 -1.6181148757072945E-02 -1.6145287645223612E-02 -1.6109454238313940E-02 -1.6073648538303342E-02 -1.6037870558180196E-02 -1.6002120308737662E-02 -1.5966397797919103E-02 -1.5930703027812024E-02 -1.5895035980736608E-02 -1.5859396636551521E-02 -1.5823784995478499E-02 -1.5788201070364036E-02 -1.5752644871538917E-02 -1.5717116404922689E-02 -1.5681615672731981E-02 -1.5646142661801640E-02 -1.5610697355311363E-02 -1.5575279749690111E-02 -1.5539889852037631E-02 -1.5504527670558389E-02 -1.5469193215162956E-02 -1.5433886492722820E-02 -1.5398607489644646E-02 -1.5363356185000798E-02 -1.5328132572500673E-02 -1.5292936661069671E-02 -1.5257768460295451E-02 -1.5222627979640002E-02 -1.5187515226354996E-02 -1.5152430188896684E-02 -1.5117372846446285E-02 -1.5082343190504374E-02 -1.5047341229182777E-02 -1.5012366971947844E-02 -1.4977420428983760E-02 -1.4942501608990980E-02 -1.4907610500752268E-02 -1.4872747080006580E-02 -1.4837911335304176E-02 -1.4803103277869331E-02 -1.4768322920184011E-02 -1.4733570269665897E-02 -1.4698845331395295E-02 -1.4664148097126033E-02 -1.4629478547229482E-02 -1.4594836669773580E-02 -1.4560222471158913E-02 -1.4525635960440333E-02 -1.4491077147487747E-02 -1.4456546041946268E-02 -1.4422042637859213E-02 -1.4387566912036163E-02 -1.4353118848304983E-02 -1.4318698454271875E-02 -1.4284305741609105E-02 -1.4249940718412806E-02 -1.4215603390623423E-02 -1.4181293753888005E-02 -1.4147011789191638E-02 -1.4112757481355695E-02 -1.4078530835127074E-02 -1.4044331860126966E-02 -1.4010160564285008E-02 -1.3976016954250893E-02 -1.3941901027831405E-02 -1.3907812766486408E-02 -1.3873752153626125E-02 -1.3839719192730426E-02 -1.3805713893872558E-02 -1.3771736264442374E-02 -1.3737786309359970E-02 -1.3703864027427124E-02 -1.3669969402790085E-02 -1.3636102419651417E-02 -1.3602263078572697E-02 -1.3568451387362691E-02 -1.3534667353638102E-02 -1.3500910984749669E-02 -1.3467182282163979E-02 -1.3433481228423215E-02 -1.3399807804072570E-02 -1.3366162007934739E-02 -1.3332543849420713E-02 -1.3298953337533229E-02 -1.3265390480456885E-02 -1.3231855281701054E-02 -1.3198347724901709E-02 -1.3164867789395740E-02 -1.3131415469816618E-02 -1.3097990772310482E-02 -1.3064593705004216E-02 -1.3031224279389877E-02 -1.2997882503226808E-02 -1.2964568360346674E-02 -1.2931281826772011E-02 -1.2898022895764496E-02 -1.2864791577319720E-02 -1.2831587881141632E-02 -1.2798411814383801E-02 -1.2765263381497376E-02 -1.2732142568855834E-02 -1.2699049354653866E-02 -1.2665983730946996E-02 -1.2632945707200787E-02 -1.2599935292820013E-02 -1.2566952493195095E-02 -1.2533997311657875E-02 -1.2501069738467731E-02 -1.2468169755924199E-02 -1.2435297354443247E-02 -1.2402452537784348E-02 -1.2369635311473476E-02 -1.2336845683577602E-02 -1.2304083661917788E-02 -1.2271349238731624E-02 -1.2238642393833895E-02 -1.2205963114854152E-02 -1.2173311406676272E-02 -1.2140687276411219E-02 -1.2108090731384276E-02 -1.2075521778438040E-02 -1.2042980410640234E-02 -1.2010466606847845E-02 -1.1977980352520163E-02 -1.1945521653338058E-02 -1.1913090518147125E-02 -1.1880686952977461E-02 -1.1848310962216332E-02 -1.1815962541278676E-02 -1.1783641673640948E-02 -1.1751348345703220E-02 -1.1719082557806080E-02 -1.1686844313774329E-02 -1.1654633620391656E-02 -1.1622450486272261E-02 -1.1590294910334737E-02 -1.1558166874690586E-02 -1.1526066362917517E-02 -1.1493993374199452E-02 -1.1461947912714130E-02 -1.1429929985193824E-02 -1.1397939600507891E-02 -1.1365976759200234E-02 -1.1334041442853156E-02 -1.1302133632971492E-02 -1.1270253328029852E-02 -1.1238400533552967E-02 -1.1206575256680727E-02 -1.1174777506298340E-02 -1.1143007284415776E-02 -1.1111264572240584E-02 -1.1079549349111520E-02 -1.1047861612818091E-02 -1.1016201371099016E-02 -1.0984568630870370E-02 -1.0952963397743222E-02 -1.0921385672901865E-02 -1.0889835440264313E-02 -1.0858312680616182E-02 -1.0826817390081209E-02 -1.0795349575543947E-02 -1.0763909243763125E-02 -1.0732496400855164E-02 -1.0701111049425730E-02 -1.0669753173660181E-02 -1.0638422752399370E-02 -1.0607119779858279E-02 -1.0575844264189437E-02 -1.0544596213287728E-02 -1.0513375633207435E-02 -1.0482182527252143E-02 -1.0451016880759155E-02 -1.0419878671574926E-02 -1.0388767890734304E-02 -1.0357684544728730E-02 -1.0326628640830256E-02 -1.0295600186003473E-02 -1.0264599185470206E-02 -1.0233625627607686E-02 -1.0202679491272302E-02 -1.0171760765713923E-02 -1.0140869456065600E-02 -1.0110005568507024E-02 -1.0079169108046786E-02 -1.0048360078473617E-02 -1.0017578470598644E-02 -9.9868242655941093E-03 -9.9560974519683678E-03 -9.9253980331163189E-03 -9.8947260142820369E-03 -9.8640814013573278E-03 -9.8334641998529485E-03 -9.8028744020671032E-03 -9.7723119875683089E-03 -9.7417769421438080E-03 -9.7112692689988022E-03 -9.6807889740975223E-03 -9.6503360632601721E-03 -9.6199105419177144E-03 -9.5895124041378860E-03 -9.5591416298522365E-03 -9.5287982032657616E-03 -9.4984821263147858E-03 -9.4681934047361280E-03 -9.4379320441950951E-03 -9.4076980501698378E-03 -9.3774914185998266E-03 -9.3473121300641140E-03 -9.3171601675707851E-03 -9.2870355317122271E-03 -9.2569382281231013E-03 -9.2268682622170823E-03 -9.1968256391845686E-03 -9.1668103565207496E-03 -9.1368223955682702E-03 -9.1068617383642560E-03 -9.0769283838763714E-03 -9.0470223375445184E-03 -9.0171436047296414E-03 -8.9872921906897236E-03 -8.9574680945417907E-03 -8.9276712984118628E-03 -8.8979017834024399E-03 -8.8681595466355984E-03 -8.8384445932911705E-03 -8.8087569285684592E-03 -8.7790965576115543E-03 -8.7494634808958499E-03 -8.7198576816805533E-03 -8.6902791404887287E-03 -8.6607278524943199E-03 -8.6312038224674939E-03 -8.6017070554402827E-03 -8.5722375566087000E-03 -8.5427953276955675E-03 -8.5133803531662004E-03 -8.4839926129289915E-03 -8.4546321002293076E-03 -8.4252988196081655E-03 -8.3959927759611596E-03 -8.3667139741792386E-03 -8.3374624167042669E-03 -8.3082380896351369E-03 -8.2790409728047566E-03 -8.2498710575503384E-03 -8.2207283477945658E-03 -8.1916128481763061E-03 -8.1625245635663108E-03 -8.1334634971664266E-03 -8.1044296364902527E-03 -8.0754229608448018E-03 -8.0464434597102719E-03 -8.0174911370280832E-03 -7.9885659976808628E-03 -7.9596680459594078E-03 -7.9307972849508458E-03 -7.9019537040418784E-03 -7.8731372831424389E-03 -7.8443480100207734E-03 -7.8155858871939796E-03 -7.7868509188478525E-03 -7.7581431096579410E-03 -7.7294624637842197E-03 -7.7008089723671598E-03 -7.6721826148364244E-03 -7.6435833769960028E-03 -7.6150112609582798E-03 -7.5864662711968532E-03 -7.5579484119300700E-03 -7.5294576869094701E-03 -7.5009940890066566E-03 -7.4725575984518483E-03 -7.4441481998313141E-03 -7.4157658938539444E-03 -7.3874106844607794E-03 -7.3590825759137814E-03 -7.3307815724845274E-03 -7.3025076688363090E-03 -7.2742608451949499E-03 -7.2460410845067514E-03 -7.2178483863640968E-03 -7.1896827547989484E-03 -7.1615441940034302E-03 -7.1334327082239858E-03 -7.1053482937215289E-03 -7.0772909311427332E-03 -7.0492606022450376E-03 -7.0212573054746954E-03 -6.9932810451764742E-03 -6.9653318252159120E-03 -6.9374096489787616E-03 -6.9095145139001658E-03 -6.8816464021777988E-03 -6.8538052954820209E-03 -6.8259911901347343E-03 -6.7982040893275423E-03 -6.7704439966968554E-03 -6.7427109163803482E-03 -6.7150048476483934E-03 -6.6873257730439483E-03 -6.6596736728810257E-03 -6.6320485419368641E-03 -6.6044503838229669E-03 -6.5768792022413017E-03 -6.5493350008362884E-03 -6.5218177796723311E-03 -6.4943275224682148E-03 -6.4668642091215423E-03 -6.4394278327466878E-03 -6.4120183969110624E-03 -6.3846359051927459E-03 -6.3572803605960486E-03 -6.3299517636155678E-03 -6.3026500997442015E-03 -6.2753753492325167E-03 -6.2481275032768568E-03 -6.2209065642537358E-03 -6.1937125352299425E-03 -6.1665454197846956E-03 -6.1394052197759211E-03 -6.1122919218668734E-03 -6.0852055053732023E-03 -6.0581459595425652E-03 -6.0311132867739313E-03 -6.0041074903202669E-03 -5.9771285732772425E-03 -5.9501765375585321E-03 -5.9232513715903297E-03 -5.8963530551202001E-03 -5.8694815758025872E-03 -5.8426369350419302E-03 -5.8158191356524605E-03 -5.7890281807730145E-03 -5.7622640729147424E-03 -5.7355268020902409E-03 -5.7088163478210691E-03 -5.6821326960062512E-03 -5.6554758475025552E-03 -5.6288458051898249E-03 -5.6022425719460932E-03 -5.5756661502462295E-03 -5.5491165317841009E-03 -5.5225936965525389E-03 -5.4960976291278983E-03 -5.4696283293314612E-03 -5.4431857997800353E-03 -5.4167700430913625E-03 -5.3903810616877630E-03 -5.3640188488986787E-03 -5.3376833853053546E-03 -5.3113746543749351E-03 -5.2850926546895681E-03 -5.2588373885626531E-03 -5.2326088584638735E-03 -5.2064070668922414E-03 -5.1802320087080975E-03 -5.1540836648629670E-03 -5.1279620176888077E-03 -5.1018670645971943E-03 -5.0757988079560001E-03 -5.0497572500875299E-03 -5.0237423932496736E-03 -4.9977542336150059E-03 -4.9717927528447415E-03 -4.9458579325004689E-03 -4.9199497685659095E-03 -4.8940682632959221E-03 -4.8682134188182645E-03 -4.8423852370823124E-03 -4.8165837154218842E-03 -4.7908088366100934E-03 -4.7650605818558697E-03 -4.7393389452539195E-03 -4.7136439282446877E-03 -4.6879755327940134E-03 -4.6623337615253942E-03 -4.6367186133724880E-03 -4.6111300714393030E-03 -4.5855681155570344E-03 -4.5600327383648791E-03 -4.5345239419606947E-03 -4.5090417284486739E-03 -4.4835860995152636E-03 -4.4581570542885822E-03 -4.4327545776410571E-03 -4.4073786499193579E-03 -4.3820292620233093E-03 -4.3567064149199423E-03 -4.3314101101624642E-03 -4.3061403497768880E-03 -4.2808971340081757E-03 -4.2556804487870990E-03 -4.2304902736669241E-03 -4.2053265978516316E-03 -4.1801894224576192E-03 -4.1550787492699061E-03 -4.1299945798584517E-03 -4.1049369145473042E-03 -4.0799057407932809E-03 -4.0549010383645057E-03 -4.0299227949323968E-03 -4.0049710109195764E-03 -3.9800456878488827E-03 -3.9551468270784765E-03 -3.9302744291694457E-03 -3.9054284830892278E-03 -3.8806089687302434E-03 -3.8558158722565056E-03 -3.8310491933526303E-03 -3.8063089333876029E-03 -3.7815950937505967E-03 -3.7569076753927733E-03 -3.7322466687497290E-03 -3.7076120535973638E-03 -3.6830038145263849E-03 -3.6584219505880386E-03 -3.6338664632454771E-03 -3.6093373536598065E-03 -3.5848346226188418E-03 -3.5603582620870426E-03 -3.5359082524808595E-03 -3.5114845773122501E-03 -3.4870872342092837E-03 -3.4627162240362225E-03 -3.4383715479354600E-03 -3.4140532071305378E-03 -3.3897611951914492E-03 -3.3654954926997439E-03 -3.3412560819477402E-03 -3.3170429597212561E-03 -3.2928561271983996E-03 -3.2686955851862886E-03 -3.2445613341523655E-03 -3.2204533687016862E-03 -3.1963716704655190E-03 -3.1723162213486951E-03 -3.1482870165253007E-03 -3.1242840565412463E-03 -3.1003073421570580E-03 -3.0763568743445630E-03 -3.0524326492222904E-03 -3.0285346486624014E-03 -3.0046628534050697E-03 -2.9808172573940477E-03 -2.9569978615692593E-03 -2.9332046665533082E-03 -2.9094376724371068E-03 -2.8856968758765246E-03 -2.8619822602481164E-03 -2.8382938065675089E-03 -2.8146315071261706E-03 -2.7909953619906273E-03 -2.7673853714388959E-03 -2.7438015358531545E-03 -2.7202438530450775E-03 -2.6967123072873344E-03 -2.6732068789705908E-03 -2.6497275586766836E-03 -2.6262743460681304E-03 -2.6028472412837280E-03 -2.5794462448384486E-03 -2.5560713554321707E-03 -2.5327225584978429E-03 -2.5093998340323166E-03 -2.4861031710264546E-03 -2.4628325688282405E-03 -2.4395880274515418E-03 -2.4163695472085123E-03 -2.3931771271941656E-03 -2.3700107540169340E-03 -2.3468704073668105E-03 -2.3237560748285585E-03 -2.3006677558263123E-03 -2.2776054505984325E-03 -2.2545691587718066E-03 -2.2315588790544675E-03 -2.2085745995774628E-03 -2.1856163007571315E-03 -2.1626839689817888E-03 -2.1397776025165421E-03 -2.1168972010049639E-03 -2.0940427642234987E-03 -2.0712142915246929E-03 -2.0484117724191044E-03 -2.0256351871007017E-03 -2.0028845204528149E-03 -1.9801597701843161E-03 -1.9574609360030661E-03 -1.9347880175885224E-03 -1.9121410143551794E-03 -1.8895199171499002E-03 -1.8669247063464920E-03 -1.8443553655918567E-03 -1.8218118917119970E-03 -1.7992942843050640E-03 -1.7768025429578812E-03 -1.7543366671352023E-03 -1.7318966489952789E-03 -1.7094824691390531E-03 -1.6870941101158779E-03 -1.6647315678752421E-03 -1.6423948421206173E-03 -1.6200839322013305E-03 -1.5977988371520587E-03 -1.5755395502595243E-03 -1.5533060529751700E-03 -1.5310983273621984E-03 -1.5089163680622100E-03 -1.4867601744293609E-03 -1.4646297456567211E-03 -1.4425250807594495E-03 -1.4204461741740505E-03 -1.3983930079234065E-03 -1.3763655633706087E-03 -1.3543638336934725E-03 -1.3323878179070593E-03 -1.3104375151553310E-03 -1.2885129246964304E-03 -1.2666140421669452E-03 -1.2447408500746385E-03 -1.2228933289423222E-03 -1.2010714706738913E-03 -1.1792752744923132E-03 -1.1575047395451742E-03 -1.1357598646487401E-03 -1.1140406459716880E-03 -1.0923470670047726E-03 -1.0706791080086480E-03 -1.0490367594598673E-03 -1.0274200203355536E-03 -1.0058288896599111E-03 -9.8426336599052367E-04 -9.6272344600297063E-04 -9.4120911447855764E-04 -9.1972035175085203E-04 -8.9825714679853358E-04 -8.7681949789135806E-04 -8.5540740372550212E-04 -8.3402086290729649E-04 -8.1265987275881278E-04 -7.9132441924128420E-04 -7.7001448249078037E-04 -7.4873005003752476E-04 -7.2747111973128819E-04 -7.0623769015067703E-04 -6.8502975975893326E-04 -6.6384732616867135E-04 -6.4269037659718032E-04 -6.2155889120296627E-04 -6.0045285617340628E-04 -5.7937226878795639E-04 -5.5831712747136421E-04 -5.3728743057819420E-04 -5.1628317593935898E-04 -4.9530435204154274E-04 -4.7435093911449771E-04 -4.5342292208016676E-04 -4.3252029758605474E-04 -4.1164306395118181E-04 -3.9079121938538831E-04 -3.6996476177658286E-04 -3.4916368087887915E-04 -3.2838795715981188E-04 -3.0763757443598802E-04 -2.8691252855611777E-04 -2.6621281769803932E-04 -2.4553843993301965E-04 -2.2488939314185643E-04 -2.0426566831710505E-04 -1.8366724628714285E-04 -1.6309410993558868E-04 -1.4254625413049929E-04 -1.2202367686252192E-04 -1.0152637608808670E-04 -8.1054349689498780E-05 -6.0607589837347853E-05 -4.0186077742309983E-05 -1.9789795470685863E-05 --5.8126316754413286E-07 --2.0927100279010266E-05 --4.1247718034199901E-05 --6.1543118678901074E-05 --8.1813309000202064E-05 --1.0205830722337805E-04 --1.2227813188363937E-04 --1.4247279038560838E-04 --1.6264228502110037E-04 --1.8278661808668632E-04 --2.0290579191790608E-04 --2.2299981235583861E-04 --2.4306869696894348E-04 --2.6311246479410666E-04 --2.8313112449857914E-04 --3.0312467852921452E-04 --3.2309312930769524E-04 --3.4303647934894640E-04 --3.6295473376603748E-04 --3.8284790927848857E-04 --4.0271602523866306E-04 --4.2255909163367068E-04 --4.4237711117222332E-04 --4.6217008641200567E-04 --4.8193801999337231E-04 --5.0168091643229258E-04 --5.2139879148821217E-04 --5.4109166475443157E-04 --5.6075954755644309E-04 --5.8040244292271418E-04 --6.0002035354325559E-04 --6.1961328217335302E-04 --6.3918123287369315E-04 --6.5872422034251731E-04 --6.7824226431415933E-04 --6.9773537742502949E-04 --7.1720356308265507E-04 --7.3664682410260439E-04 --7.5606516337621056E-04 --7.7545858466630010E-04 --7.9482710155090181E-04 --8.1417073380474908E-04 --8.3348949531177031E-04 --8.5278338991121353E-04 --8.7205242051736930E-04 --8.9129659020770007E-04 --9.1051590263142770E-04 --9.2971037017524879E-04 --9.4888001242958409E-04 --9.6802484441944545E-04 --9.8714487069894536E-04 --1.0062400944219501E-03 --1.0253105186509692E-03 --1.0443561467181541E-03 --1.0633769898913189E-03 --1.0823730679011482E-03 --1.1013443969972885E-03 --1.1202909821726795E-03 --1.1392128264261791E-03 --1.1581099330081669E-03 --1.1769823054503272E-03 --1.1958299539395205E-03 --1.2146528978277127E-03 --1.2334511542019628E-03 --1.2522247288315178E-03 --1.2709736247921396E-03 --1.2896978456111070E-03 --1.3083973951813089E-03 --1.3270722826945710E-03 --1.3457225268039084E-03 --1.3643481450691193E-03 --1.3829491443184366E-03 --1.4015255279366096E-03 --1.4200772996197069E-03 --1.4386044633549575E-03 --1.4571070273177490E-03 --1.4755850094639283E-03 --1.4940384277540956E-03 --1.5124672904071859E-03 --1.5308716014739172E-03 --1.5492513647547238E-03 --1.5676065837854042E-03 --1.5859372655450232E-03 --1.6042434277308486E-03 --1.6225250891244122E-03 --1.6407822589998423E-03 --1.6590149413143512E-03 --1.6772231399410909E-03 --1.6954068587152935E-03 --1.7135661040243542E-03 --1.7317008928452188E-03 --1.7498112442630961E-03 --1.7678971686615956E-03 --1.7859586701098533E-03 --1.8039957525332125E-03 --1.8220084198533537E-03 --1.8399966778787132E-03 --1.8579605429168890E-03 --1.8759000345210720E-03 --1.8938151643679499E-03 --1.9117059367517086E-03 --1.9295723556733686E-03 --1.9474144251126579E-03 --1.9652321503622230E-03 --1.9830255466513074E-03 --2.0007946335436210E-03 --2.0185394239040288E-03 --2.0362599224755971E-03 --2.0539561335031799E-03 --2.0716280611896734E-03 --2.0892757106021247E-03 --2.1068990959457884E-03 --2.1244982367837899E-03 --2.1420731471209495E-03 --2.1596238321604849E-03 --2.1771502962954635E-03 --2.1946525437213228E-03 --2.2121305791423930E-03 --2.2295844157468035E-03 --2.2470140732449928E-03 --2.2644195667896184E-03 --2.2818009019053638E-03 --2.2991580829553496E-03 --2.3164911143594238E-03 --2.3338000008818172E-03 --2.3510847546827488E-03 --2.3683453952887353E-03 --2.3855819388138503E-03 --2.4027943913686868E-03 --2.4199827574248791E-03 --2.4371470416162462E-03 --2.4542872488203500E-03 --2.4714033901754805E-03 --2.4884954848709497E-03 --2.5055635497727392E-03 --2.5226075915608559E-03 --2.5396276146819954E-03 --2.5566236240223152E-03 --2.5735956248156768E-03 --2.5905436273317576E-03 --2.6074676502225369E-03 --2.6243677108952457E-03 --2.6412438170082581E-03 --2.6580959733217531E-03 --2.6749241848031805E-03 --2.6917284566124783E-03 --2.7085087980159702E-03 --2.7252652272028847E-03 --2.7419977621266230E-03 --2.7587064116615981E-03 --2.7753911810704099E-03 --2.7920520753286827E-03 --2.8086890991208995E-03 --2.8253022606119019E-03 --2.8418915780045284E-03 --2.8584570702372674E-03 --2.8749987469328716E-03 --2.8915166128682668E-03 --2.9080106730558020E-03 --2.9244809328875391E-03 --2.9409274002274491E-03 --2.9573500923096943E-03 --2.9737490279683676E-03 --2.9901242180220360E-03 --3.0064756678599759E-03 --3.0228033827428931E-03 --3.0391073678859314E-03 --3.0553876303285711E-03 --3.0716441865100961E-03 --3.0878770554992083E-03 --3.1040862493797177E-03 --3.1202717741193246E-03 --3.1364336352280473E-03 --3.1525718376317763E-03 --3.1686863875762484E-03 --3.1847773010511907E-03 --3.2008445979442124E-03 --3.2168882913027586E-03 --3.2329083864368652E-03 --3.2489048884693089E-03 --3.2648778032223517E-03 --3.2808271374969657E-03 --3.2967529061728659E-03 --3.3126551285149299E-03 --3.3285338184570368E-03 --3.3443889820881593E-03 --3.3602206249454783E-03 --3.3760287528480774E-03 --3.3918133722302068E-03 --3.4075744969029450E-03 --3.4233121459605023E-03 --3.4390263343342937E-03 --3.4547170688406762E-03 --3.4703843553770398E-03 --3.4860281997646479E-03 --3.5016486081294088E-03 --3.5172455933154389E-03 --3.5328191744148610E-03 --3.5483693672636778E-03 --3.5638961790020306E-03 --3.5793996154775830E-03 --3.5948796828173526E-03 --3.6103363874452066E-03 --3.6257697413675325E-03 --3.6411797632951220E-03 --3.6565664697037793E-03 --3.6719298683737891E-03 --3.6872699653144173E-03 --3.7025867667653499E-03 --3.7178802791803058E-03 --3.7331505136950112E-03 --3.7483974887170049E-03 --3.7636212213674413E-03 --3.7788217203045759E-03 --3.7939989918430160E-03 --3.8091530422172102E-03 --3.8242838776283024E-03 --3.8393915082598519E-03 --3.8544759523588277E-03 --3.8695372277426825E-03 --3.8845753438884168E-03 --3.8995903072001270E-03 --3.9145821240053743E-03 --3.9295508005664104E-03 --3.9444963463471164E-03 --3.9594187793480931E-03 --3.9743181179633814E-03 --3.9891943723884115E-03 --4.0040475488483619E-03 --4.0188776537077543E-03 --4.0336846935430269E-03 --4.0484686773315411E-03 --4.0632296225156647E-03 --4.0779675477515855E-03 --4.0926824642178250E-03 --4.1073743783684950E-03 --4.1220432966396709E-03 --4.1366892255609196E-03 --4.1513121734787911E-03 --4.1659121573288382E-03 --4.1804891961747343E-03 --4.1950433021976149E-03 --4.2095744819516112E-03 --4.2240827419833720E-03 --4.2385680891805846E-03 --4.2530305316855598E-03 --4.2674700853859793E-03 --4.2818867690013265E-03 --4.2962805956617131E-03 --4.3106515725949944E-03 --4.3249997066995387E-03 --4.3393250047375443E-03 --4.3536274743240259E-03 --4.3679071307564377E-03 --4.3821639931925262E-03 --4.3963980757733860E-03 --4.4106093857652559E-03 --4.4247979299388640E-03 --4.4389637150530660E-03 --4.4531067484512923E-03 --4.4672270447173928E-03 --4.4813246232614998E-03 --4.4953994992955769E-03 --4.5094516804569610E-03 --4.5234811735946822E-03 --4.5374879854811661E-03 --4.5514721232281508E-03 --4.5654336005399631E-03 --4.5793724368437183E-03 --4.5932886482089787E-03 --4.6071822425022835E-03 --4.6210532265001433E-03 --4.6349016074296468E-03 --4.6487273928916498E-03 --4.6625305957398401E-03 --4.6763112347201442E-03 --4.6900693263248871E-03 --4.7038048791954168E-03 --4.7175179004867287E-03 --4.7312083974481150E-03 --4.7448763774724980E-03 --4.7585218525705852E-03 --4.7721448414470647E-03 --4.7857453613718605E-03 --4.7993234216015266E-03 --4.8128790293553905E-03 --4.8264121919986171E-03 --4.8399229170353365E-03 --4.8534112157135349E-03 --4.8668771063312029E-03 --4.8803206065658328E-03 --4.8937417264067638E-03 --4.9071404732254223E-03 --4.9205168545068245E-03 --4.9338708778515570E-03 --4.9472025538305408E-03 --4.9605119003488206E-03 --4.9737989354630124E-03 --4.9870636700700983E-03 --5.0003061118372334E-03 --5.0135262683681930E-03 --5.0267241472104025E-03 --5.0398997582362399E-03 --5.0530531189594274E-03 --5.0661842478037225E-03 --5.0792931564400522E-03 --5.0923798525606490E-03 --5.1054443438176252E-03 --5.1184866378802931E-03 --5.1315067441628911E-03 --5.1445046797369597E-03 --5.1574804633586890E-03 --5.1704341076202935E-03 --5.1833656204067127E-03 --5.1962750094532231E-03 --5.2091622824332797E-03 --5.2220274482856479E-03 --5.2348705234627913E-03 --5.2476915269196282E-03 --5.2604904721223087E-03 --5.2732673671247047E-03 --5.2860222197926524E-03 --5.2987550381004608E-03 --5.3114658308822541E-03 --5.3241546137407546E-03 --5.3368214054170561E-03 --5.3494662201206116E-03 --5.3620890662739555E-03 --5.3746899519176820E-03 --5.3872688850650262E-03 --5.3998258743007147E-03 --5.4123609346847625E-03 --5.4248740852879916E-03 --5.4373653412307862E-03 --5.4498347110264909E-03 --5.4622822025854455E-03 --5.4747078238788580E-03 --5.4871115832704027E-03 --5.4994934952148234E-03 --5.5118535790988025E-03 --5.5241918509613824E-03 --5.5365083193401072E-03 --5.5488029919096987E-03 --5.5610758770379444E-03 --5.5733269835529899E-03 --5.5855563250238119E-03 --5.5977639199864737E-03 --5.6099497848164787E-03 --5.6221139290973847E-03 --5.6342563612270776E-03 --5.6463770896887922E-03 --5.6584761231044476E-03 --5.6705534741435292E-03 --5.6826091609526556E-03 --5.6946432003398230E-03 --5.7066556025791382E-03 --5.7186463763867898E-03 --5.7306155303153208E-03 --5.7425630728480748E-03 --5.7544890159414910E-03 --5.7663933776521889E-03 --5.7782761753805536E-03 --5.7901374200668519E-03 --5.8019771205895434E-03 --5.8137952854789903E-03 --5.8255919229774460E-03 --5.8373670443132219E-03 --5.8491206675959735E-03 --5.8608528109234947E-03 --5.8725634857212704E-03 --5.8842527006186841E-03 --5.8959204642318819E-03 --5.9075667851742229E-03 --5.9191916742709428E-03 --5.9307951490707627E-03 --5.9423772277651596E-03 --5.9539379226102827E-03 --5.9654772425998008E-03 --5.9769951965246790E-03 --5.9884917929322150E-03 --5.9999670420603111E-03 --6.0114209610906393E-03 --6.0228535685444146E-03 --6.0342648772842324E-03 --6.0456548961391361E-03 --6.0570236339262543E-03 --6.0683710996028966E-03 --6.0796973033355566E-03 --6.0910022617971949E-03 --6.1022859936127336E-03 --6.1135485123521120E-03 --6.1247898269300334E-03 --6.1360099462002479E-03 --6.1472088792930684E-03 --6.1583866361912560E-03 --6.1695432328672381E-03 --6.1806786878471414E-03 --6.1917930154971349E-03 --6.2028862252293737E-03 --6.2139583261201546E-03 --6.2250093270897694E-03 --6.2360392376171426E-03 --6.2470480732191016E-03 --6.2580358528830761E-03 --6.2690025917988348E-03 --6.2799482992566330E-03 --6.2908729841507968E-03 --6.3017766558339386E-03 --6.3126593241195402E-03 --6.3235210037440193E-03 --6.3343617131595056E-03 --6.3451814680108342E-03 --6.3559802781443112E-03 --6.3667581527630992E-03 --6.3775151013446283E-03 --6.3882511336582383E-03 --6.3989662637368759E-03 --6.4096605097858275E-03 --6.4203338880027784E-03 --6.4309864088458561E-03 --6.4416180818247168E-03 --6.4522289163200051E-03 --6.4628189217590358E-03 --6.4733881115349211E-03 --6.4839365040527492E-03 --6.4944641162892240E-03 --6.5049709590992016E-03 --6.5154570419797804E-03 --6.5259223742115411E-03 --6.5363669649908711E-03 --6.5467908270697879E-03 --6.5571939790219549E-03 --6.5675764385622407E-03 --6.5779382168573942E-03 --6.5882793231657535E-03 --6.5985997668777724E-03 --6.6088995575067071E-03 --6.6191787073455804E-03 --6.6294372346168747E-03 --6.6396751572987481E-03 --6.6498924870135841E-03 --6.6600892329303106E-03 --6.6702654046987926E-03 --6.6804210124782777E-03 --6.6905560683377585E-03 --6.7006705896590609E-03 --6.7107645941303596E-03 --6.7208380940672443E-03 --6.7308910990450431E-03 --6.7409236189149378E-03 --6.7509356639290086E-03 --6.7609272457525753E-03 --6.7708983812542903E-03 --6.7808490881488817E-03 --6.7907793795949052E-03 --6.8006892657185855E-03 --6.8105787565268692E-03 --6.8204478619141593E-03 --6.8302965928781637E-03 --6.8401249660291581E-03 --6.8499329994978339E-03 --6.8597207071029757E-03 --6.8694880989541704E-03 --6.8792351850602545E-03 --6.8889619754760774E-03 --6.8986684810393179E-03 --6.9083547178680673E-03 --6.9180207041473233E-03 --6.9276664543851847E-03 --6.9372919790033852E-03 --6.9468972881236201E-03 --6.9564823916034467E-03 --6.9660472998300344E-03 --6.9755920286068600E-03 --6.9851165966211175E-03 --6.9946210190479407E-03 --7.0041053059878358E-03 --7.0135694672909229E-03 --7.0230135133761903E-03 --7.0324374551267018E-03 --7.0418413076755414E-03 --7.0512250891427430E-03 --7.0605888150804281E-03 --7.0699324961420156E-03 --7.0792561424970236E-03 --7.0885597645878682E-03 --7.0978433731391033E-03 --7.1071069826265949E-03 --7.1163506109537854E-03 --7.1255742741965066E-03 --7.1347779836597935E-03 --7.1439617499097531E-03 --7.1531255833325383E-03 --7.1622694943428728E-03 --7.1713934967958396E-03 --7.1804976086072905E-03 --7.1895818463774269E-03 --7.1986462216877701E-03 --7.2076907450963476E-03 --7.2167154270674494E-03 --7.2257202780623090E-03 --7.2347053115081406E-03 --7.2436705453601058E-03 --7.2526159967316751E-03 --7.2615416774360845E-03 --7.2704475978614133E-03 --7.2793337685439531E-03 --7.2882002001495305E-03 --7.2970469056641198E-03 --7.3058739026781510E-03 --7.3146812084930787E-03 --7.3234688355611468E-03 --7.3322367945818012E-03 --7.3409850962021916E-03 --7.3497137510246417E-03 --7.3584227715214083E-03 --7.3671121750561747E-03 --7.3757819792103817E-03 --7.3844321970392927E-03 --7.3930628394385358E-03 --7.4016739170832454E-03 --7.4102654403882728E-03 --7.4188374212866360E-03 --7.4273898770458313E-03 --7.4359228256825304E-03 --7.4444362806980963E-03 --7.4529302527917198E-03 --7.4614047526429129E-03 --7.4698597909674527E-03 --7.4782953795804897E-03 --7.4867115353990724E-03 --7.4951082765666579E-03 --7.5034856171219307E-03 --7.5118435678059288E-03 --7.5201821393418387E-03 --7.5285013426127220E-03 --7.5368011892792894E-03 --7.5450816957487689E-03 --7.5533428801215037E-03 --7.5615847570161812E-03 --7.5698073374392948E-03 --7.5780106322359464E-03 --7.5861946522678119E-03 --7.5943594089343666E-03 --7.6025049182181009E-03 --7.6106311983565071E-03 --7.6187382645201019E-03 --7.6268261277528454E-03 --7.6348947988959465E-03 --7.6429442891090046E-03 --7.6509746099443074E-03 --7.6589857767849056E-03 --7.6669778075195132E-03 --7.6749507177546507E-03 --7.6829045190605601E-03 --7.6908392225801510E-03 --7.6987548393331606E-03 --7.7066513805128314E-03 --7.7145288610479803E-03 --7.7223872990530122E-03 --7.7302267107386535E-03 --7.7380471077644437E-03 --7.7458485011951761E-03 --7.7536309023171039E-03 --7.7613943226139421E-03 --7.7691387764937288E-03 --7.7768642815878621E-03 --7.7845708542476537E-03 --7.7922585064859199E-03 --7.7999272495373351E-03 --7.8075770949337072E-03 --7.8152080544142150E-03 --7.8228201419480864E-03 --7.8304133746784597E-03 --7.8379877690701108E-03 --7.8455433378962578E-03 --7.8530800929694933E-03 --7.8605980456303778E-03 --7.8680972069101705E-03 --7.8755775902091228E-03 --7.8830392133232095E-03 --7.8904820936386445E-03 --7.8979062437798345E-03 --7.9053116747948259E-03 --7.9126983980637444E-03 --7.9200664252750148E-03 --7.9274157697372533E-03 --7.9347464486625805E-03 --7.9420584793032396E-03 --7.9493518749759011E-03 --7.9566266472547512E-03 --7.9638828076762907E-03 --7.9711203677423539E-03 --7.9783393402271738E-03 --7.9855397420053580E-03 --7.9927215904334950E-03 --7.9998848994335368E-03 --8.0070296809355134E-03 --8.0141559465953475E-03 --8.0212637076898172E-03 --8.0283529765145505E-03 --8.0354237698871834E-03 --8.0424761055947497E-03 --8.0495099978661264E-03 --8.0565254582611844E-03 --8.0635224983641868E-03 --8.0705011299354468E-03 --8.0774613654330391E-03 --8.0844032212310912E-03 --8.0913267149729257E-03 --8.0982318613648935E-03 --8.1051186722676128E-03 --8.1119871593901619E-03 --8.1188373343510437E-03 --8.1256692092535991E-03 --8.1324828001287722E-03 --8.1392781247908354E-03 --8.1460551984205553E-03 --8.1528140328956701E-03 --8.1595546399294925E-03 --8.1662770313855760E-03 --8.1729812194752029E-03 --8.1796672198623330E-03 --8.1863350503070236E-03 --8.1929847263054623E-03 --8.1996162596427186E-03 --8.2062296619202606E-03 --8.2128249454529092E-03 --8.2194021229123840E-03 --8.2259612093584754E-03 --8.2325022217503100E-03 --8.2390251757511780E-03 --8.2455300841791177E-03 --8.2520169594089855E-03 --8.2584858133022323E-03 --8.2649366576411174E-03 --8.2713695070745271E-03 --8.2777843792034827E-03 --8.2841812904253156E-03 --8.2905602534136466E-03 --8.2969212801872819E-03 --8.3032643826566888E-03 --8.3095895727385623E-03 --8.3158968648458960E-03 --8.3221862767114095E-03 --8.3284578251591503E-03 --8.3347115227929442E-03 --8.3409473812787027E-03 --8.3471654127570544E-03 --8.3533656297017818E-03 --8.3595480463013096E-03 --8.3657126796904194E-03 --8.3718595465780733E-03 --8.3779886601084604E-03 --8.3841000323303747E-03 --8.3901936754583809E-03 --8.3962696018547948E-03 --8.4023278253317121E-03 --8.4083683629588724E-03 --8.4143912317264438E-03 --8.4203964451003300E-03 --8.4263840151053634E-03 --8.4323539539789914E-03 --8.4383062741974317E-03 --8.4442409892757850E-03 --8.4501581157891484E-03 --8.4560576705886795E-03 --8.4619396678406837E-03 --8.4678041202581756E-03 --8.4736510402686378E-03 --8.4794804399151488E-03 --8.4852923321383188E-03 --8.4910867335680137E-03 --8.4968636615249671E-03 --8.5026231303703993E-03 --8.5083651523938861E-03 --8.5140897399744644E-03 --8.5197969057341644E-03 --8.5254866628495969E-03 --8.5311590273197870E-03 --8.5368140159777558E-03 --8.5424516436409699E-03 --8.5480719233020138E-03 --8.5536748676410361E-03 --8.5592604887435898E-03 --8.5648287990982268E-03 --8.5703798147430833E-03 --8.5759135532042906E-03 --8.5814300297619717E-03 --8.5869292570680076E-03 --8.5924112475689301E-03 --8.5978760135297094E-03 --8.6033235675026052E-03 --8.6087539252723971E-03 --8.6141671044466482E-03 --8.6195631206193203E-03 --8.6249419863138332E-03 --8.6303037138756554E-03 --8.6356483159773512E-03 --8.6409758055500958E-03 --8.6462861979690556E-03 --8.6515795104201380E-03 --8.6568557585931811E-03 --8.6621149551561680E-03 --8.6673571125147671E-03 --8.6725822435877124E-03 --8.6777903615614625E-03 --8.6829814814474004E-03 --8.6881556200113716E-03 --8.6933127931086603E-03 --8.6984530140617224E-03 --8.7035762957610781E-03 --8.7086826508708439E-03 --8.7137720920044560E-03 --8.7188446337357738E-03 --8.7239002930736068E-03 --8.7289390863485774E-03 --8.7339610270441379E-03 --8.7389661280150664E-03 --8.7439544019129595E-03 --8.7489258612916121E-03 --8.7538805204785686E-03 --8.7588183966551426E-03 --8.7637395065441291E-03 --8.7686438635785260E-03 --8.7735314802642270E-03 --8.7784023693699750E-03 --8.7832565438806867E-03 --8.7880940179807573E-03 --8.7929148083566479E-03 --8.7977189316031795E-03 --8.8025064018019614E-03 --8.8072772320602916E-03 --8.8120314351232288E-03 --8.8167690233684134E-03 --8.8214900103960360E-03 --8.8261944132302407E-03 --8.8308822491059268E-03 --8.8355535320872435E-03 --8.8402082746533509E-03 --8.8448464895480514E-03 --8.8494681898808065E-03 --8.8540733895004341E-03 --8.8586621048860736E-03 --8.8632343529092654E-03 --8.8677901479222478E-03 --8.8723295026334782E-03 --8.8768524299552912E-03 --8.8813589431980082E-03 --8.8858490561421789E-03 --8.8903227846958317E-03 --8.8947801453283792E-03 --8.8992211528887942E-03 --8.9036458208553697E-03 --8.9080541624698729E-03 --8.9124461905407334E-03 --8.9168219182214504E-03 --8.9211813613556974E-03 --8.9255245368227917E-03 --8.9298514597922971E-03 --8.9341621435666176E-03 --8.9384566012915296E-03 --8.9427348459283889E-03 --8.9469968906756292E-03 --8.9512427512094487E-03 --8.9554724445000591E-03 --8.9596859859452493E-03 --8.9638833887117873E-03 --8.9680646658563592E-03 --8.9722298306637392E-03 --8.9763788966151312E-03 --8.9805118790017863E-03 --8.9846287943640673E-03 --8.9887296581663088E-03 --8.9928144838594057E-03 --8.9968832846980869E-03 --9.0009360740352304E-03 --9.0049728653438538E-03 --9.0089936737759412E-03 --9.0129985159902361E-03 --9.0169874076791636E-03 --9.0209603620915926E-03 --9.0249173922003819E-03 --9.0288585115689320E-03 --9.0327837340549340E-03 --9.0366930746224421E-03 --9.0405865495172648E-03 --9.0444641744485983E-03 --9.0483259631937013E-03 --9.0521719291361599E-03 --9.0560020855494916E-03 --9.0598164456704641E-03 --9.0636150241716756E-03 --9.0673978378795744E-03 --9.0711649031508575E-03 --9.0749162335951334E-03 --9.0786518421273055E-03 --9.0823717421504389E-03 --9.0860759474359516E-03 --9.0897644725468282E-03 --9.0934373335734182E-03 --9.0970945464893434E-03 --9.1007361255958982E-03 --9.1043620845884764E-03 --9.1079724368678932E-03 --9.1115671955558138E-03 --9.1151463747019146E-03 --9.1187099907636023E-03 --9.1222580602895505E-03 --9.1257905975874291E-03 --9.1293076159216033E-03 --9.1328091286735184E-03 --9.1362951493764860E-03 --9.1397656921604099E-03 --9.1432207731560085E-03 --9.1466604087431236E-03 --9.1500846133982083E-03 --9.1534934004397963E-03 --9.1568867833304434E-03 --9.1602647757891339E-03 --9.1636273919252498E-03 --9.1669746475243740E-03 --9.1703065587594220E-03 --9.1736231403979334E-03 --9.1769244060981303E-03 --9.1802103695167968E-03 --9.1834810443706047E-03 --9.1867364446346859E-03 --9.1899765858250125E-03 --9.1932014839929584E-03 --9.1964111540269143E-03 --9.1996056096298583E-03 --9.2027848645095719E-03 --9.2059489325332037E-03 --9.2090978277460222E-03 --9.2122315654588303E-03 --9.2153501615928474E-03 --9.2184536312346216E-03 --9.2215419883677884E-03 --9.2246152468376443E-03 --9.2276734202578238E-03 --9.2307165223182788E-03 --9.2337445682262320E-03 --9.2367575741645735E-03 --9.2397555555345633E-03 --9.2427385263776675E-03 --9.2457065005327986E-03 --9.2486594914956196E-03 --9.2515975127519870E-03 --9.2545205794186073E-03 --9.2574287079785315E-03 --9.2603219141047747E-03 --9.2632002115724983E-03 --9.2660636139297158E-03 --9.2689121349159159E-03 --9.2717457883895460E-03 --9.2745645893096886E-03 --9.2773685538273878E-03 --9.2801576975991441E-03 --9.2829320346511316E-03 --9.2856915787191772E-03 --9.2884363436110898E-03 --9.2911663431912896E-03 --9.2938815921686322E-03 --9.2965821064330580E-03 --9.2992679016259388E-03 --9.3019389920662443E-03 --9.3045953917292555E-03 --9.3072371143464085E-03 --9.3098641734904713E-03 --9.3124765837043991E-03 --9.3150743612997570E-03 --9.3176575223847345E-03 --9.3202260810101717E-03 --9.3227800505750365E-03 --9.3253194449182258E-03 --9.3278442782738346E-03 --9.3303545653113003E-03 --9.3328503217032493E-03 --9.3353315630947207E-03 --9.3377983038928740E-03 --9.3402505579685720E-03 --9.3426883392296635E-03 --9.3451116616293309E-03 --9.3475205395780955E-03 --9.3499149889212634E-03 --9.3522950256361113E-03 --9.3546606642214928E-03 --9.3570119183396666E-03 --9.3593488018364149E-03 --9.3616713288454528E-03 --9.3639795137563583E-03 --9.3662733719391371E-03 --9.3685529189727109E-03 --9.3708181697401902E-03 --9.3730691386100708E-03 --9.3753058397379775E-03 --9.3775282868899940E-03 --9.3797364940327154E-03 --9.3819304765218031E-03 --9.3841102501633147E-03 --9.3862758299583793E-03 --9.3884272301414488E-03 --9.3905644648031791E-03 --9.3926875477454777E-03 --9.3947964929031319E-03 --9.3968913155821395E-03 --9.3989720317012512E-03 --9.4010386563656463E-03 --9.4030912036777593E-03 --9.4051296876595126E-03 --9.4071541222682156E-03 --9.4091645215547415E-03 --9.4111609007163730E-03 --9.4131432756334819E-03 --9.4151116614509967E-03 --9.4170660721304578E-03 --9.4190065216022863E-03 --9.4209330241325981E-03 --9.4228455941189164E-03 --9.4247442465190349E-03 --9.4266289967283624E-03 --9.4284998598298496E-03 --9.4303568502351505E-03 --9.4321999822333108E-03 --9.4340292698734847E-03 --9.4358447271502381E-03 --9.4376463689002828E-03 --9.4394342108125775E-03 --9.4412082682475973E-03 --9.4429685555664587E-03 --9.4447150869337009E-03 --9.4464478762827184E-03 --9.4481669374557892E-03 --9.4498722852202569E-03 --9.4515639355530010E-03 --9.4532419040884753E-03 --9.4549062049205726E-03 --9.4565568518286385E-03 --9.4581938590024717E-03 --9.4598172409011659E-03 --9.4614270123109089E-03 --9.4630231885641375E-03 --9.4646057848938245E-03 --9.4661748157914370E-03 --9.4677302955160480E-03 --9.4692722382067225E-03 --9.4708006579046836E-03 --9.4723155691318495E-03 --9.4738169874802828E-03 --9.4753049285182713E-03 --9.4767794067164828E-03 --9.4782404361071181E-03 --9.4796880308355112E-03 --9.4811222051704482E-03 --9.4825429736744918E-03 --9.4839503517509700E-03 --9.4853443548431754E-03 --9.4867249973785428E-03 --9.4880922932534025E-03 --9.4894462566642579E-03 --9.4907869022319864E-03 --9.4921142446984276E-03 --9.4934282991550271E-03 --9.4947290807444133E-03 --9.4960166041761062E-03 --9.4972908838599473E-03 --9.4985519340441450E-03 --9.4997997686956711E-03 --9.5010344019846437E-03 --9.5022558492987262E-03 --9.5034641263711545E-03 --9.5046592479714892E-03 --9.5058412280130556E-03 --9.5070100805717660E-03 --9.5081658201787034E-03 --9.5093084614768578E-03 --9.5104380194356210E-03 --9.5115545091545642E-03 --9.5126579454153440E-03 --9.5137483426345135E-03 --9.5148257151680144E-03 --9.5158900772447097E-03 --9.5169414431383447E-03 --9.5179798278032888E-03 --9.5190052465698293E-03 --9.5200177143175656E-03 --9.5210172452519157E-03 --9.5220038535923559E-03 --9.5229775538457091E-03 --9.5239383606130421E-03 --9.5248862887595057E-03 --9.5258213533416704E-03 --9.5267435691720262E-03 --9.5276529505841732E-03 --9.5285495118747586E-03 --9.5294332674391250E-03 --9.5303042317245890E-03 --9.5311624195430489E-03 --9.5320078460507125E-03 --9.5328405261947916E-03 --9.5336604743592665E-03 --9.5344677048434748E-03 --9.5352622319704750E-03 --9.5360440700847700E-03 --9.5368132338873868E-03 --9.5375697385142247E-03 --9.5383135989506856E-03 --9.5390448295873675E-03 --9.5397634447053348E-03 --9.5404694587484882E-03 --9.5411628862608067E-03 --9.5418437419134087E-03 --9.5425120405760056E-03 --9.5431677970855104E-03 --9.5438110260524182E-03 --9.5444417420122735E-03 --9.5450599593286112E-03 --9.5456656922324034E-03 --9.5462589551988733E-03 --9.5468397632130948E-03 --9.5474081312662430E-03 --9.5479640740063487E-03 --9.5485076059474878E-03 --9.5490387414763379E-03 --9.5495574948518541E-03 --9.5500638805170786E-03 --9.5505579134291564E-03 --9.5510396085799771E-03 --9.5515089805361612E-03 --9.5519660436566654E-03 --9.5524108123741045E-03 --9.5528433012186612E-03 --9.5532635247390744E-03 --9.5536714975275449E-03 --9.5540672341948452E-03 --9.5544507494529952E-03 --9.5548220580766868E-03 --9.5551811746641402E-03 --9.5555281135148180E-03 --9.5558628889810537E-03 --9.5561855158095271E-03 --9.5564960088481005E-03 --9.5567943826442257E-03 --9.5570806514963941E-03 --9.5573548298054384E-03 --9.5576169322138197E-03 --9.5578669734005736E-03 --9.5581049680737041E-03 --9.5583309309457496E-03 --9.5585448765446532E-03 --9.5587468192007054E-03 --9.5589367733372541E-03 --9.5591147536759988E-03 --9.5592807749642020E-03 --9.5594348516962920E-03 --9.5595769982358084E-03 --9.5597072290415034E-03 --9.5598255587054284E-03 --9.5599320018183477E-03 --9.5600265729281660E-03 --9.5601092865774968E-03 --9.5601801573732530E-03 --9.5602391999655301E-03 --9.5602864289318600E-03 --9.5603218587180031E-03 --9.5603455037704625E-03 --9.5603573786109657E-03 --9.5603574977818039E-03 --9.5603458757547582E-03 --9.5603225269396616E-03 --9.5602874658509852E-03 --9.5602407072541834E-03 --9.5601822659046893E-03 --9.5601121562342625E-03 --9.5600303925416248E-03 --9.5599369892947345E-03 --9.5598319611550076E-03 --9.5597153227164298E-03 --9.5595870883302663E-03 --9.5594472723270103E-03 --9.5592958892922603E-03 --9.5591329539523942E-03 --9.5589584809070757E-03 --9.5587724845669891E-03 --9.5585749793243406E-03 --9.5583659795575194E-03 --9.5581454996581314E-03 --9.5579135542498226E-03 --9.5576701581234456E-03 --9.5574153258619898E-03 --9.5571490716430257E-03 --9.5568714096728874E-03 --9.5565823545745304E-03 --9.5562819211083595E-03 --9.5559701238859991E-03 --9.5556469773788420E-03 --9.5553124959910744E-03 --9.5549666939715623E-03 --9.5546095855749049E-03 --9.5542411852814878E-03 --9.5538615076770205E-03 --9.5534705674080404E-03 --9.5530683791941844E-03 --9.5526549575957794E-03 --9.5522303166263381E-03 --9.5517944702487052E-03 --9.5513474330927127E-03 --9.5508892201827556E-03 --9.5504198462514154E-03 --9.5499393255648532E-03 --9.5494476723378355E-03 --9.5489449007377398E-03 --9.5484310249426465E-03 --9.5479060594929402E-03 --9.5473700192091806E-03 --9.5468229187925524E-03 --9.5462647726851143E-03 --9.5456955952682165E-03 --9.5451154007486477E-03 --9.5445242032768541E-03 --9.5439220172014640E-03 --9.5433088570695841E-03 --9.5426847374664361E-03 --9.5420496730565987E-03 --9.5414036784565847E-03 --9.5407467677805190E-03 --9.5400789549065796E-03 --9.5394002540999390E-03 --9.5387106801276093E-03 --9.5380102477334566E-03 --9.5372989714591766E-03 --9.5365768657742853E-03 --9.5358439448402828E-03 --9.5351002226244670E-03 --9.5343457132678108E-03 --9.5335804312071445E-03 --9.5328043909679895E-03 --9.5320176073666052E-03 --9.5312200952668204E-03 --9.5304118688720636E-03 --9.5295929418421285E-03 --9.5287633281392510E-03 --9.5279230424221081E-03 --9.5270720994264663E-03 --9.5262105137917438E-03 --9.5253383001032577E-03 --9.5244554725403847E-03 --9.5235620448505254E-03 --9.5226580309546709E-03 --9.5217434453351117E-03 --9.5208183025897331E-03 --9.5198826174492292E-03 --9.5189364047030302E-03 --9.5179796786656595E-03 --9.5170124529979552E-03 --9.5160347415019376E-03 --9.5150465587061084E-03 --9.5140479193045191E-03 --9.5130388378752827E-03 --9.5120193289153186E-03 --9.5109894067072018E-03 --9.5099490851537939E-03 --9.5088983781780895E-03 --9.5078373000097097E-03 --9.5067658649929179E-03 --9.5056840877665236E-03 --9.5045919832267463E-03 --9.5034895659159551E-03 --9.5023768495294640E-03 --9.5012538477257016E-03 --9.5001205747481752E-03 --9.4989770450913513E-03 --9.4978232732974167E-03 --9.4966592739615160E-03 --9.4954850615114328E-03 --9.4943006498484587E-03 --9.4931060527990285E-03 --9.4919012844455388E-03 --9.4906863590193662E-03 --9.4894612910706704E-03 --9.4882260956140694E-03 --9.4869807874062451E-03 --9.4857253799845390E-03 --9.4844598866266460E-03 --9.4831843213689128E-03 --9.4818986987973194E-03 --9.4806030335300544E-03 --9.4792973402232604E-03 --9.4779816334087559E-03 --9.4766559269047011E-03 --9.4753202343024444E-03 --9.4739745695894984E-03 --9.4726189471243429E-03 --9.4712533813956744E-03 --9.4698778871820238E-03 --9.4684924791716748E-03 --9.4670971710379657E-03 --9.4656919760104444E-03 --9.4642769079332483E-03 --9.4628519813944878E-03 --9.4614172110323424E-03 --9.4599726115040736E-03 --9.4585181973887399E-03 --9.4570539824075806E-03 --9.4555799797802712E-03 --9.4540962032678422E-03 --9.4526026674863779E-03 --9.4510993870970221E-03 --9.4495863766315275E-03 --9.4480636505469492E-03 --9.4465312227185079E-03 --9.4449891065747239E-03 --9.4434373158150727E-03 --9.4418758647132599E-03 --9.4403047676653133E-03 --9.4387240393817209E-03 --9.4371336946496645E-03 --9.4355337473551668E-03 --9.4339242104882585E-03 --9.4323050974598165E-03 --9.4306764229099439E-03 --9.4290382016374453E-03 --9.4273904480776678E-03 --9.4257331764798762E-03 --9.4240664007463094E-03 --9.4223901343352713E-03 --9.4207043908360322E-03 --9.4190091844080868E-03 --9.4173045293592036E-03 --9.4155904402399571E-03 --9.4138669317474673E-03 --9.4121340180323837E-03 --9.4103917123326396E-03 --9.4086400279701134E-03 --9.4068789790785669E-03 --9.4051085800434964E-03 --9.4033288454134466E-03 --9.4015397898677983E-03 --9.3997414275305644E-03 --9.3979337713113922E-03 --9.3961168341839783E-03 --9.3942906305577653E-03 --9.3924551753942660E-03 --9.3906104832433279E-03 --9.3887565682172856E-03 --9.3868934442093224E-03 --9.3850211245447707E-03 --9.3831396225342537E-03 --9.3812489522488978E-03 --9.3793491281540728E-03 --9.3774401646715862E-03 --9.3755220761591110E-03 --9.3735948767683045E-03 --9.3716585798805704E-03 --9.3697131987390287E-03 --9.3677587471547620E-03 --9.3657952393243083E-03 --9.3638226895858510E-03 --9.3618411125159368E-03 --9.3598505225071585E-03 --9.3578509328835855E-03 --9.3558423566631969E-03 --9.3538248075103973E-03 --9.3517982996549395E-03 --9.3497628474659908E-03 --9.3477184655922033E-03 --9.3456651685337334E-03 --9.3436029694875418E-03 --9.3415318811277577E-03 --9.3394519169626936E-03 --9.3373630914426447E-03 --9.3352654190739081E-03 --9.3331589143802966E-03 --9.3310435917700156E-03 --9.3289194645161666E-03 --9.3267865452769366E-03 --9.3246448474528995E-03 --9.3224943855349639E-03 --9.3203351740524017E-03 --9.3181672273388826E-03 --9.3159905596126441E-03 --9.3138051842077199E-03 --9.3116111138268811E-03 --9.3094083617508289E-03 --9.3071969423801654E-03 --9.3049768702368873E-03 --9.3027481598251492E-03 --9.3005108255911281E-03 --9.2982648809313111E-03 --9.2960103382678360E-03 --9.2937472105323899E-03 --9.2914755120138692E-03 --9.2891952572098906E-03 --9.2869064606305174E-03 --9.2846091367632354E-03 --9.2823032991737123E-03 --9.2799889603225241E-03 --9.2776661329929296E-03 --9.2753348312470188E-03 --9.2729950694362909E-03 --9.2706468621847199E-03 --9.2682902242601922E-03 --9.2659251693953167E-03 --9.2635517097140081E-03 --9.2611698576084665E-03 --9.2587796272652796E-03 --9.2563810333511059E-03 --9.2539740903153280E-03 --9.2515588124365781E-03 --9.2491352134015208E-03 --9.2467033057098032E-03 --9.2442631019541092E-03 --9.2418146161269196E-03 --9.2393578627282744E-03 --9.2368928561119227E-03 --9.2344196104853556E-03 --9.2319381396184647E-03 --9.2294484561344717E-03 --9.2269505726014309E-03 --9.2244445026637232E-03 --9.2219302604915829E-03 --9.2194078604497572E-03 --9.2168773171468644E-03 --9.2143386447217472E-03 --9.2117918555950622E-03 --9.2092369619242737E-03 --9.2066739771814402E-03 --9.2041029156685415E-03 --9.2015237917618120E-03 --9.1989366199387770E-03 --9.1963414143441304E-03 --9.1937381875002392E-03 --9.1911269515234199E-03 --9.1885077197417005E-03 --9.1858805064721251E-03 --9.1832453260789881E-03 --9.1806021929661582E-03 --9.1779511212911873E-03 --9.1752921236058493E-03 --9.1726252118756370E-03 --9.1699503992065234E-03 --9.1672676999065162E-03 --9.1645771283729097E-03 --9.1618786990943432E-03 --9.1591724263699256E-03 --9.1564583227012920E-03 --9.1537363996906131E-03 --9.1510066701885068E-03 --9.1482691487523062E-03 --9.1455238499604102E-03 --9.1427707880080231E-03 --9.1400099769022268E-03 --9.1372414294559091E-03 --9.1344651576878901E-03 --9.1316811743377899E-03 --9.1288894934418510E-03 --9.1260901291993161E-03 --9.1232830959670705E-03 --9.1204684080780727E-03 --9.1176460785284165E-03 --9.1148161191556207E-03 --9.1119785423961104E-03 --9.1091333621567162E-03 --9.1062805925793220E-03 --9.1034202480015543E-03 --9.1005523428025654E-03 --9.0976768901987748E-03 --9.0947939021042562E-03 --9.0919033907885492E-03 --9.0890053698165722E-03 --9.0860998530573629E-03 --9.0831868549274847E-03 --9.0802663901200405E-03 --9.0773384720599735E-03 --9.0744031123327941E-03 --9.0714603228183536E-03 --9.0685101171844047E-03 --9.0655525095649607E-03 --9.0625875142332016E-03 --9.0596151455538017E-03 --9.0566354170155457E-03 --9.0536483404561555E-03 --9.0506539278092709E-03 --9.0476521925321428E-03 --9.0446431486099176E-03 --9.0416268102106127E-03 --9.0386031916687721E-03 --9.0355723065915806E-03 --9.0325341667760496E-03 --9.0294887839548112E-03 --9.0264361714183852E-03 --9.0233763431644305E-03 --9.0203093133913309E-03 --9.0172350965325790E-03 --9.0141537063646998E-03 --9.0110651544678885E-03 --9.0079694521647581E-03 --9.0048666127444370E-03 --9.0017566506490950E-03 --8.9986395801379786E-03 --8.9955154151654792E-03 --8.9923841692799277E-03 --8.9892458543642164E-03 --8.9861004819455290E-03 --8.9829480650301836E-03 --8.9797886177513837E-03 --8.9766221542099470E-03 --8.9734486883847348E-03 --8.9702682339813534E-03 --8.9670808031816918E-03 --8.9638864076565274E-03 --8.9606850600777600E-03 --8.9574767741029057E-03 --8.9542615635794243E-03 --8.9510394427465625E-03 --8.9478104256691809E-03 --8.9445745245008857E-03 --8.9413317505073475E-03 --8.9380821160940874E-03 --8.9348256351200958E-03 --8.9315623215811320E-03 --8.9282921896242130E-03 --8.9250152532677155E-03 --8.9217315247198808E-03 --8.9184410150701700E-03 --8.9151437365196755E-03 --8.9118397031244957E-03 --8.9085289290450776E-03 --8.9052114281209446E-03 --8.9018872140146123E-03 --8.8985562990479498E-03 --8.8952186944597066E-03 --8.8918744122712928E-03 --8.8885234662496836E-03 --8.8851658704015811E-03 --8.8818016388232963E-03 --8.8784307855845190E-03 --8.8750533232145740E-03 --8.8716692626316842E-03 --8.8682786154225830E-03 --8.8648813952802406E-03 --8.8614776162489316E-03 --8.8580672922120140E-03 --8.8546504369457595E-03 --8.8512270631855711E-03 --8.8477971822619461E-03 --8.8443608058348389E-03 --8.8409179471830093E-03 --8.8374686199899823E-03 --8.8340128382194353E-03 --8.8305506160085145E-03 --8.8270819663264135E-03 --8.8236069000902934E-03 --8.8201254284334119E-03 --8.8166375646311582E-03 --8.8131433226362136E-03 --8.8096427164293147E-03 --8.8061357600113157E-03 --8.8026224664420772E-03 --8.7991028466229363E-03 --8.7955769114723831E-03 --8.7920446740839386E-03 --8.7885061484595187E-03 --8.7849613485723524E-03 --8.7814102883598550E-03 --8.7778529809919431E-03 --8.7742894373165348E-03 --8.7707196679928934E-03 --8.7671436860285151E-03 --8.7635615057106882E-03 --8.7599731409920504E-03 --8.7563786053248983E-03 --8.7527779117055372E-03 --8.7491710714394152E-03 --8.7455580955248993E-03 --8.7419389965759896E-03 --8.7383137883560186E-03 --8.7346824846250420E-03 --8.7310450990909106E-03 --8.7274016450971364E-03 --8.7237521340368801E-03 --8.7200965767143344E-03 --8.7164349853382141E-03 --8.7127673734085920E-03 --8.7090937545761613E-03 --8.7054141427431991E-03 --8.7017285515563758E-03 --8.6980369924992695E-03 --8.6943394761314578E-03 --8.6906360143884590E-03 --8.6869266208415615E-03 --8.6832113091689141E-03 --8.6794900930878462E-03 --8.6757629861297716E-03 --8.6720299998484865E-03 --8.6682911446641815E-03 --8.6645464322831420E-03 --8.6607958764046526E-03 --8.6570394908459698E-03 --8.6532772892031918E-03 --8.6495092849004397E-03 --8.6457354897280896E-03 --8.6419559142453702E-03 --8.6381705698788600E-03 --8.6343794698468760E-03 --8.6305826276240321E-03 --8.6267800569404668E-03 --8.6229717715416813E-03 --8.6191577834662317E-03 --8.6153381030851326E-03 --8.6115127414914585E-03 --8.6076817118559065E-03 --8.6038450277067767E-03 --8.6000027027389511E-03 --8.5961547506831406E-03 --8.5923011836759617E-03 --8.5884420118429675E-03 --8.5845772459032677E-03 --8.5807068990970143E-03 --8.5768309851956496E-03 --8.5729495177649835E-03 --8.5690625102260252E-03 --8.5651699748413371E-03 --8.5612719219848483E-03 --8.5573683623536689E-03 --8.5534593089707719E-03 --8.5495447755207267E-03 --8.5456247754043171E-03 --8.5416993217888766E-03 --8.5377684270526739E-03 --8.5338321019064207E-03 --8.5298903571210671E-03 --8.5259432051941891E-03 --8.5219906593033707E-03 --8.5180327328647897E-03 --8.5140694395402679E-03 --8.5101007921335164E-03 --8.5061268010039014E-03 --8.5021474763377486E-03 --8.4981628305021099E-03 --8.4941728769765221E-03 --8.4901776292325686E-03 --8.4861771007191649E-03 --8.4821713042890351E-03 --8.4781602505659328E-03 --8.4741439497865705E-03 --8.4701224138219924E-03 --8.4660956556327112E-03 --8.4620636885500995E-03 --8.4580265265172209E-03 --8.4539841829227129E-03 --8.4499366680613232E-03 --8.4458839913837125E-03 --8.4418261645657165E-03 --8.4377632011934899E-03 --8.4336951148692545E-03 --8.4296219190904947E-03 --8.4255436269564856E-03 --8.4214602489630329E-03 --8.4173717945952124E-03 --8.4132782753129163E-03 --8.4091797047659289E-03 --8.4050760965441156E-03 --8.4009674637144788E-03 --8.3968538190554009E-03 --8.3927351735680507E-03 --8.3886115373104156E-03 --8.3844829215410730E-03 --8.3803493392492386E-03 --8.3762108035600712E-03 --8.3720673276103646E-03 --8.3679189244082065E-03 --8.3637656052222547E-03 --8.3596073800999166E-03 --8.3554442600147338E-03 --8.3512762577088832E-03 --8.3471033861832432E-03 --8.3429256587968688E-03 --8.3387430889233383E-03 --8.3345556878564996E-03 --8.3303634649935180E-03 --8.3261664307531028E-03 --8.3219645982126160E-03 --8.3177579808008193E-03 --8.3135465916117316E-03 --8.3093304435439483E-03 --8.3051095480242126E-03 --8.3008839147463952E-03 --8.2966535540683270E-03 --8.2924184788152559E-03 --8.2881787022827131E-03 --8.2839342374909589E-03 --8.2796850972794486E-03 --8.2754312932897360E-03 --8.2711728353417040E-03 --8.2669097336248148E-03 --8.2626420005880372E-03 --8.2583696492872210E-03 --8.2540926927249323E-03 --8.2498111438554910E-03 --8.2455250145729731E-03 --8.2412343146711607E-03 --8.2369390540761415E-03 --8.2326392449201674E-03 --8.2283349001358880E-03 --8.2240260327812540E-03 --8.2197126560330149E-03 --8.2153947821015285E-03 --8.2110724206643435E-03 --8.2067455812736816E-03 --8.2024142757124423E-03 --8.1980785168288585E-03 --8.1937383176909611E-03 --8.1893936916342096E-03 --8.1850446511200162E-03 --8.1806912055196121E-03 --8.1763333637903009E-03 --8.1719711377019368E-03 --8.1676045407613942E-03 --8.1632335861471471E-03 --8.1588582864624056E-03 --8.1544786538121066E-03 --8.1500946982314987E-03 --8.1457064292644581E-03 --8.1413138581919592E-03 --8.1369169976882455E-03 --8.1325158605155511E-03 --8.1281104595393658E-03 --8.1237008072814459E-03 --8.1192869140315985E-03 --8.1148687892750905E-03 --8.1104464438784812E-03 --8.1060198901392096E-03 --8.1015891406647587E-03 --8.0971542087440000E-03 --8.0927151074381160E-03 --8.0882718468536091E-03 --8.0838244356401818E-03 --8.0793728841666648E-03 --8.0749172051123742E-03 --8.0704574113929489E-03 --8.0659935162053220E-03 --8.0615255325747360E-03 --8.0570534706818787E-03 --8.0525773388507426E-03 --8.0480971471089558E-03 --8.0436129084904204E-03 --8.0391246362242607E-03 --8.0346323430210316E-03 --8.0301360413209816E-03 --8.0256357416515125E-03 --8.0211314529122241E-03 --8.0166231850031331E-03 --8.0121109502072890E-03 --8.0075947611798464E-03 --8.0030746308747992E-03 --7.9985505722917037E-03 --7.9940225962890667E-03 --7.9894907113693073E-03 --7.9849549269229853E-03 --7.9804152553615108E-03 --7.9758717096323102E-03 --7.9713243024347701E-03 --7.9667730463027844E-03 --7.9622179522689292E-03 --7.9576590292336300E-03 --7.9530962865559957E-03 --7.9485297360795768E-03 --7.9439593902878528E-03 --7.9393852619127295E-03 --7.9348073638460734E-03 --7.9302257074871270E-03 --7.9256403014725200E-03 --7.9210511546830009E-03 --7.9164582789088469E-03 --7.9118616869075648E-03 --7.9072613913530217E-03 --7.9026574048390533E-03 --7.8980497388531946E-03 --7.8934384022117075E-03 --7.8888234037076000E-03 --7.8842047548442085E-03 --7.8795824683161840E-03 --7.8749565566496454E-03 --7.8703270321668801E-03 --7.8656939064403273E-03 --7.8610571886722318E-03 --7.8564168877934999E-03 --7.8517730147772396E-03 --7.8471255817803547E-03 --7.8424746012203273E-03 --7.8378200858875285E-03 --7.8331620478792972E-03 --7.8285004961829406E-03 --7.8238354391178457E-03 --7.8191668873994185E-03 --7.8144948535367204E-03 --7.8098193500118372E-03 --7.8051403891682379E-03 --7.8004579828894064E-03 --7.7957721404982167E-03 --7.7910828704920590E-03 --7.7863901833362418E-03 --7.7816940913988447E-03 --7.7769946070320676E-03 --7.7722917423454808E-03 --7.7675855091379918E-03 --7.7628759170752402E-03 --7.7581629748575487E-03 --7.7534466926541361E-03 --7.7487270824726879E-03 --7.7440041564568870E-03 --7.7392779268214982E-03 --7.7345484055900389E-03 --7.7298156025308396E-03 --7.7250795260441537E-03 --7.7203401858903717E-03 --7.7155975940574970E-03 --7.7108517627480517E-03 --7.7061027042211756E-03 --7.7013504306128302E-03 --7.6965949518574195E-03 --7.6918362761414609E-03 --7.6870744127820797E-03 --7.6823093735786802E-03 --7.6775411706722667E-03 --7.6727698163758700E-03 --7.6679953229793329E-03 --7.6632177006151023E-03 --7.6584369571984726E-03 --7.6536531016069415E-03 --7.6488661456692222E-03 --7.6440761017174596E-03 --7.6392829820476783E-03 --7.6344867988903916E-03 --7.6296875625454091E-03 --7.6248852807506585E-03 --7.6200799619563072E-03 --7.6152716179008128E-03 --7.6104602610540225E-03 --7.6056459035438138E-03 --7.6008285572571870E-03 --7.5960082327419538E-03 --7.5911849382487373E-03 --7.5863586823181626E-03 --7.5815294760525429E-03 --7.5766973313513503E-03 --7.5718622601987935E-03 --7.5670242746455939E-03 --7.5621833856083327E-03 --7.5573396014474463E-03 --7.5524929305322338E-03 --7.5476433836267499E-03 --7.5427909724854652E-03 --7.5379357090795207E-03 --7.5330776056130293E-03 --7.5282166732684071E-03 --7.5233529201542450E-03 --7.5184863541096431E-03 --7.5136169857231427E-03 --7.5087448270606269E-03 --7.5038698901024907E-03 --7.4989921866881410E-03 --7.4941117279819901E-03 --7.4892285225095180E-03 --7.4843425782998713E-03 --7.4794539054469757E-03 --7.4745625154902682E-03 --7.4696684202127869E-03 --7.4647716317902376E-03 --7.4598721618329812E-03 --7.4549700187148092E-03 --7.4500652098603544E-03 --7.4451577450932779E-03 --7.4402476364037904E-03 --7.4353348957636369E-03 --7.4304195349130051E-03 --7.4255015651889878E-03 --7.4205809952665978E-03 --7.4156578327134156E-03 --7.4107320869643313E-03 --7.4058037696343379E-03 --7.4008728925023387E-03 --7.3959394674782721E-03 --7.3910035062263188E-03 --7.3860650177016048E-03 --7.3811240093321984E-03 --7.3761804900846157E-03 --7.3712344712689613E-03 --7.3662859644824377E-03 --7.3613349817209161E-03 --7.3563815348896850E-03 --7.3514256330912365E-03 --7.3464672833543684E-03 --7.3415064942533408E-03 --7.3365432774868270E-03 --7.3315776450189659E-03 --7.3266096082569626E-03 --7.3216391783306745E-03 --7.3166663646701147E-03 --7.3116911750742584E-03 --7.3067136181528460E-03 --7.3017337047726078E-03 --7.2967514462200607E-03 --7.2917668542612796E-03 --7.2867799408242277E-03 --7.2817907156271216E-03 --7.2767991856482351E-03 --7.2718053586717903E-03 --7.2668092458234171E-03 --7.2618108589180500E-03 --7.2568102095002772E-03 --7.2518073089269100E-03 --7.2468021670808016E-03 --7.2417947914843817E-03 --7.2367851900298685E-03 --7.2317733732784268E-03 --7.2267593525642323E-03 --7.2217431393613403E-03 --7.2167247452460679E-03 --7.2117041804306108E-03 --7.2066814522674695E-03 --7.2016565682177540E-03 --7.1966295386266211E-03 --7.1916003749375500E-03 --7.1865690885914435E-03 --7.1815356910228867E-03 --7.1765001926271596E-03 --7.1714626009348713E-03 --7.1664229233046033E-03 --7.1613811697678427E-03 --7.1563373516934821E-03 --7.1512914803899454E-03 --7.1462435670726025E-03 --7.1411936222094199E-03 --7.1361416535456329E-03 --7.1310876684022272E-03 --7.1260316764719554E-03 --7.1209736889941855E-03 --7.1159137171934459E-03 --7.1108517722234437E-03 --7.1057878646790529E-03 --7.1007220024378315E-03 --7.0956541926663237E-03 --7.0905844446671751E-03 --7.0855127695452214E-03 --7.0804391784739813E-03 --7.0753636826543821E-03 --7.0702862928782601E-03 --7.0652070171950696E-03 --7.0601258626070210E-03 --7.0550428380195505E-03 --7.0499579544120753E-03 --7.0448712228914686E-03 --7.0397826546326342E-03 --7.0346922605201458E-03 --7.0296000486773681E-03 --7.0245060257908718E-03 --7.0194102003980326E-03 --7.0143125836558086E-03 --7.0092131868357849E-03 --7.0041120208869222E-03 --6.9990090964992735E-03 --6.9939044220514706E-03 --6.9887980043310746E-03 --6.9836898515726548E-03 --6.9785799747093943E-03 --6.9734683849157581E-03 --6.9683550931244377E-03 --6.9632401100732811E-03 --6.9581234443019183E-03 --6.9530051023810411E-03 --6.9478850920901523E-03 --6.9427634242655804E-03 --6.9376401101527881E-03 --6.9325151607250559E-03 --6.9273885867725911E-03 --6.9222603971271311E-03 --6.9171305983542382E-03 --6.9119991978524517E-03 --6.9068662060603981E-03 --6.9017316340145686E-03 --6.8965954927234516E-03 --6.8914577931459310E-03 --6.8863185444005930E-03 --6.8811777528526782E-03 --6.8760354254329475E-03 --6.8708915724249725E-03 --6.8657462049848657E-03 --6.8605993340502981E-03 --6.8554509703860943E-03 --6.8503011233918927E-03 --6.8451497998171483E-03 --6.8399970065843264E-03 --6.8348427533384349E-03 --6.8296870506935198E-03 --6.8245299094172656E-03 --6.8193713404204022E-03 --6.8142113534864759E-03 --6.8090499555009979E-03 --6.8038871532224814E-03 --6.7987229559599380E-03 --6.7935573742162183E-03 --6.7883904186717900E-03 --6.7832221002175879E-03 --6.7780524288289434E-03 --6.7728814113241749E-03 --6.7677090540999877E-03 --6.7625353662261901E-03 --6.7573603583993098E-03 --6.7521840413639943E-03 --6.7470064259048650E-03 --6.7418275221036959E-03 --6.7366473368267862E-03 --6.7314658761893596E-03 --6.7262831488392226E-03 --6.7210991654195352E-03 --6.7159139366064153E-03 --6.7107274730321556E-03 --6.7055397848522240E-03 --6.7003508793349693E-03 --6.6951607627410538E-03 --6.6899694433418897E-03 --6.6847769314548394E-03 --6.6795832375486763E-03 --6.6743883722561173E-03 --6.6691923458850914E-03 --6.6639951657955949E-03 --6.6587968379289743E-03 --6.6535973701706474E-03 --6.6483967729698079E-03 --6.6431950569373508E-03 --6.6379922326399911E-03 --6.6327883103935101E-03 --6.6275832976938906E-03 --6.6223772002316182E-03 --6.6171700254554888E-03 --6.6119617838556431E-03 --6.6067524861327508E-03 --6.6015421425711894E-03 --6.5963307632069916E-03 --6.5911183560035625E-03 --6.5859049271913220E-03 --6.5806904840156177E-03 --6.5754750360957522E-03 --6.5702585934496504E-03 --6.5650411666165337E-03 --6.5598227662569493E-03 --6.5546034006413022E-03 --6.5493830754553119E-03 --6.5441617973470327E-03 --6.5389395761676393E-03 --6.5337164223433254E-03 --6.5284923462123612E-03 --6.5232673580254228E-03 --6.5180414661507920E-03 --6.5128146763286342E-03 --6.5075869949423343E-03 --6.5023584316621884E-03 --6.4971289969493889E-03 --6.4918987010824051E-03 --6.4866675541976893E-03 --6.4814355649277910E-03 --6.4762027391831907E-03 --6.4709690831723406E-03 --6.4657346061798770E-03 --6.4604993184872233E-03 --6.4552632301792395E-03 --6.4500263511610527E-03 --6.4447886902547690E-03 --6.4395502537247370E-03 --6.4343110478216822E-03 --6.4290710813419260E-03 --6.4238303641906075E-03 --6.4185889064472803E-03 --6.4133467183865953E-03 --6.4081038092281628E-03 --6.4028601848366354E-03 --6.3976158507368219E-03 --6.3923708155805507E-03 --6.3871250897879345E-03 --6.3818786835220520E-03 --6.3766316065334092E-03 --6.3713838678849041E-03 --6.3661354738860981E-03 --6.3608864302929164E-03 --6.3556367452502283E-03 --6.3503864286606733E-03 --6.3451354904831133E-03 --6.3398839407063949E-03 --6.3346317887962231E-03 --6.3293790412417561E-03 --6.3241257035887228E-03 --6.3188717835104069E-03 --6.3136172907017896E-03 --6.3083622349709391E-03 --6.3031066262101872E-03 --6.2978504739662714E-03 --6.2925937850312500E-03 --6.2873365649723468E-03 --6.2820788211027847E-03 --6.2768205628829692E-03 --6.2715618000089473E-03 --6.2663025425298280E-03 --6.2610428002780171E-03 --6.2557825799806985E-03 --6.2505218865184587E-03 --6.2452607267430267E-03 --6.2399991106717604E-03 --6.2347370484626295E-03 --6.2294745496405055E-03 --6.2242116234146059E-03 --6.2189482768923885E-03 --6.2136845155432389E-03 --6.2084203460494262E-03 --6.2031557776899022E-03 --6.1978908200791159E-03 --6.1926254829178526E-03 --6.1873597758435837E-03 --6.1820937062476754E-03 --6.1768272792535554E-03 --6.1715605010475068E-03 --6.1662933809820469E-03 --6.1610259289101802E-03 --6.1557581544103464E-03 --6.1504900668781547E-03 --6.1452216738698360E-03 --6.1399529805446044E-03 --6.1346839927844746E-03 --6.1294147196760147E-03 --6.1241451710068312E-03 --6.1188753562745439E-03 --6.1136052847708833E-03 --6.1083349643358169E-03 --6.1030644003616423E-03 --6.0977935985712904E-03 --6.0925225674406600E-03 --6.0872513162954257E-03 --6.0819798547158948E-03 --6.0767081924871140E-03 --6.0714363379184471E-03 --6.0661642960473496E-03 --6.0608920719723266E-03 --6.0556196740571677E-03 --6.0503471119738488E-03 --6.0450743952334832E-03 --6.0398015331693576E-03 --6.0345285340800961E-03 --6.0292554032724257E-03 --6.0239821458310016E-03 --6.0187087697182147E-03 --6.0134352844164879E-03 --6.0081616994035643E-03 --6.0028880241316581E-03 --5.9976142671951133E-03 --5.9923404338556533E-03 --5.9870665287976351E-03 --5.9817925596661603E-03 --5.9765185361366534E-03 --5.9712444676443474E-03 --5.9659703631198087E-03 --5.9606962309713867E-03 --5.9554220771569797E-03 --5.9501479069363214E-03 --5.9448737274204787E-03 --5.9395995473643355E-03 --5.9343253757741391E-03 --5.9290512221149777E-03 --5.9237770954528651E-03 --5.9185030015678321E-03 --5.9132289449028066E-03 --5.9079549322114426E-03 --5.9026809728975581E-03 --5.8974070763393510E-03 --5.8921332513810435E-03 --5.8868595065315419E-03 --5.8815858480477136E-03 --5.8763122809444577E-03 --5.8710388116819572E-03 --5.8657654488786437E-03 --5.8604922014142040E-03 --5.8552190785333864E-03 --5.8499460893741582E-03 --5.8446732402698594E-03 --5.8394005355164062E-03 --5.8341279809813193E-03 --5.8288555856444496E-03 --5.8235833587791837E-03 --5.8183113093233478E-03 --5.8130394459932370E-03 --5.8077677753322968E-03 --5.8024963018355382E-03 --5.7972250311258957E-03 --5.7919539718773944E-03 --5.7866831332202828E-03 --5.7814125241475913E-03 --5.7761421535282706E-03 --5.7708720281760576E-03 --5.7656021524025974E-03 --5.7603325313532365E-03 --5.7550631734784256E-03 --5.7497940878991185E-03 --5.7445252835048571E-03 --5.7392567690208599E-03 --5.7339885515902403E-03 --5.7287206358664225E-03 --5.7234530269131079E-03 --5.7181857326198977E-03 --5.7129187616789439E-03 --5.7076521229278230E-03 --5.7023858253073866E-03 --5.6971198762875127E-03 --5.6918542803116468E-03 --5.6865890419841398E-03 --5.6813241691270481E-03 --5.6760596707515739E-03 --5.6707955555682045E-03 --5.6655318319817315E-03 --5.6602685074737353E-03 --5.6550055870654694E-03 --5.6497430756470542E-03 --5.6444809804205688E-03 --5.6392193097296274E-03 --5.6339580720960432E-03 --5.6286972762623491E-03 --5.6234369301588170E-03 --5.6181770387374180E-03 --5.6129176064852173E-03 --5.6076586402546572E-03 --5.6024001484162190E-03 --5.5971421395426034E-03 --5.5918846225045784E-03 --5.5866276054822774E-03 --5.5813710931859320E-03 --5.5761150894440698E-03 --5.5708596008270791E-03 --5.5656046361774797E-03 --5.5603502042434359E-03 --5.5550963134156023E-03 --5.5498429716085282E-03 --5.5445901839479709E-03 --5.5393379545251534E-03 --5.5340862895353823E-03 --5.5288351974263940E-03 --5.5235846867446696E-03 --5.5183347660039085E-03 --5.5130854433834385E-03 --5.5078367241340924E-03 --5.5025886120138234E-03 --5.4973411127747489E-03 --5.4920942349399836E-03 --5.4868479871343807E-03 --5.4816023775929729E-03 --5.4763574142750217E-03 --5.4711131028578339E-03 --5.4658694474750682E-03 --5.4606264535369898E-03 --5.4553841287942658E-03 --5.4501424813511714E-03 --5.4449015198840545E-03 --5.4396612531014306E-03 --5.4344216868806383E-03 --5.4291828246068596E-03 --5.4239446710330937E-03 --5.4187072343214165E-03 --5.4134705230570656E-03 --5.4082345453692997E-03 --5.4029993091334440E-03 --5.3977648204983977E-03 --5.3925310836504146E-03 --5.3872981034606485E-03 --5.3820658872586469E-03 --5.3768344429060005E-03 --5.3716037788058861E-03 --5.3663739036242178E-03 --5.3611448239057995E-03 --5.3559165430726290E-03 --5.3506890651360880E-03 --5.3454623975927812E-03 --5.3402365488334083E-03 --5.3350115271022062E-03 --5.3297873405239891E-03 --5.3245639957460915E-03 --5.3193414965966405E-03 --5.3141198471238563E-03 --5.3088990543744699E-03 --5.3036791264355248E-03 --5.2984600714237242E-03 --5.2932418974794230E-03 --5.2880246115091668E-03 --5.2828082173207525E-03 --5.2775927186611204E-03 --5.2723781224363825E-03 --5.2671644369893158E-03 --5.2619516703783873E-03 --5.2567398303086845E-03 --5.2515289236385243E-03 --5.2463189544746398E-03 --5.2411099266020025E-03 --5.2359018464384188E-03 --5.2306947219746547E-03 --5.2254885612013861E-03 --5.2202833720761200E-03 --5.2150791618511905E-03 --5.2098759346458417E-03 --5.2046736938752853E-03 --5.1994724455102391E-03 --5.1942721974995009E-03 --5.1890729577916111E-03 --5.1838747342294348E-03 --5.1786775341518213E-03 --5.1734813619508961E-03 --5.1682862210218139E-03 --5.1630921169820666E-03 --5.1578990576705832E-03 --5.1527070509369381E-03 --5.1475161044004453E-03 --5.1423262253288251E-03 --5.1371374184276354E-03 --5.1319496871954163E-03 --5.1267630368556283E-03 --5.1215774748654287E-03 --5.1163930088738412E-03 --5.1112096466885831E-03 --5.1060273959172434E-03 --5.1008462614752286E-03 --5.0956662465839412E-03 --5.0904873559727481E-03 --5.0853095969344807E-03 --5.0801329770596747E-03 --5.0749575041989514E-03 --5.0697831861220106E-03 --5.0646100279606978E-03 --5.0594380326802937E-03 --5.0542672045591546E-03 --5.0490975508796299E-03 --5.0439290793154396E-03 --5.0387617975116671E-03 --5.0335957130186433E-03 --5.0284308312424641E-03 --5.0232671553113997E-03 --5.0181046892619650E-03 --5.0129434400625634E-03 --5.0077834152265164E-03 --5.0026246224491016E-03 --4.9974670694730274E-03 --4.9923107619464996E-03 --4.9871557026429248E-03 --4.9820018950353677E-03 --4.9768493460851547E-03 --4.9716980635759970E-03 --4.9665480551026537E-03 --4.9613993281136491E-03 --4.9562518884378693E-03 --4.9511057390250754E-03 --4.9459608831863393E-03 --4.9408173276234346E-03 --4.9356750801032648E-03 --4.9305341479632730E-03 --4.9253945381600370E-03 --4.9202562566585369E-03 --4.9151193071424069E-03 --4.9099836932907526E-03 --4.9048494210100430E-03 --4.8997164971670759E-03 --4.8945849290115868E-03 --4.8894547242219295E-03 --4.8843258894149914E-03 --4.8791984278605729E-03 --4.8740723424732955E-03 --4.8689476389349598E-03 --4.8638243244693317E-03 --4.8587024063594299E-03 --4.8535818919505386E-03 --4.8484627878474023E-03 --4.8433450975788822E-03 --4.8382288240601491E-03 --4.8331139726533736E-03 --4.8280005504891983E-03 --4.8228885647009717E-03 --4.8177780223525373E-03 --4.8126689300276105E-03 --4.8075612916939365E-03 --4.8024551105050207E-03 --4.7973503913707263E-03 --4.7922471408415055E-03 --4.7871453657820986E-03 --4.7820450736844782E-03 --4.7769462717019325E-03 --4.7718489637204910E-03 --4.7667531522010203E-03 --4.7616588415865914E-03 --4.7565660387149031E-03 --4.7514747506171365E-03 --4.7463849844940073E-03 --4.7412967473145625E-03 --4.7362100432698853E-03 --4.7311248749273569E-03 --4.7260412464303243E-03 --4.7209591644095531E-03 --4.7158786357616271E-03 --4.7107996676072203E-03 --4.7057222669568705E-03 --4.7006464382460516E-03 --4.6955721839380465E-03 --4.6904995078258663E-03 --4.6854284165025687E-03 --4.6803589169016552E-03 --4.6752910159657086E-03 --4.6702247205432932E-03 --4.6651600352719180E-03 --4.6600969625954208E-03 --4.6550355059840204E-03 --4.6499756718994681E-03 --4.6449174672928287E-03 --4.6398608990787021E-03 --4.6348059741002368E-03 --4.6297526971769178E-03 --4.6247010705359271E-03 --4.6196510972121036E-03 --4.6146027837135704E-03 --4.6095561372715465E-03 --4.6045111645716874E-03 --4.5994678719360861E-03 --4.5944262643656418E-03 --4.5893863446779537E-03 --4.5843481160337809E-03 --4.5793115842070074E-03 --4.5742767557585438E-03 --4.5692436374180027E-03 --4.5642122360456941E-03 --4.5591825571214663E-03 --4.5541546031254302E-03 --4.5491283766158413E-03 --4.5441038831697204E-03 --4.5390811295513544E-03 --4.5340601224010211E-03 --4.5290408682239153E-03 --4.5240233725889973E-03 --4.5190076384060722E-03 --4.5139936683756708E-03 --4.5089814675090909E-03 --4.5039710420234297E-03 --4.4989623984549318E-03 --4.4939555437613085E-03 --4.4889504840475427E-03 --4.4839472220489238E-03 --4.4789457599023240E-03 --4.4739461022818405E-03 --4.4689482555743780E-03 --4.4639522262913123E-03 --4.4589580211075192E-03 --4.4539656461093534E-03 --4.4489751042866114E-03 --4.4439863977666959E-03 --4.4389995309538242E-03 --4.4340145102378043E-03 --4.4290313420750479E-03 --4.4240500329221985E-03 --4.4190705888236970E-03 --4.4140930129736595E-03 --4.4091173074299050E-03 --4.4041434762025012E-03 --4.3991715255013294E-03 --4.3942014616961487E-03 --4.3892332912879540E-03 --4.3842670205061296E-03 --4.3793026527559273E-03 --4.3743401899146812E-03 --4.3693796356379742E-03 --4.3644209961885075E-03 --4.3594642779760029E-03 --4.3545094871724945E-03 --4.3495566297198363E-03 --4.3446057092714693E-03 --4.3396567278491784E-03 --4.3347096888367029E-03 --4.3297645982572613E-03 --4.3248214624018013E-03 --4.3198802874224963E-03 --4.3149410793263294E-03 --4.3100038421493882E-03 --4.3050685781017015E-03 --4.3001352902437319E-03 --4.2952039839144543E-03 --4.2902746648798935E-03 --4.2853473395045964E-03 --4.2804220143553258E-03 --4.2754986937803847E-03 --4.2705773794722603E-03 --4.2656580739123713E-03 --4.2607407826914297E-03 --4.2558255120230719E-03 --4.2509122679620353E-03 --4.2460010564438506E-03 --4.2410918818880537E-03 --4.2361847463699472E-03 --4.2312796523922601E-03 --4.2263766052251074E-03 --4.2214756108967478E-03 --4.2165766753896241E-03 --4.2116798046416687E-03 --4.2067850032765893E-03 --4.2018922732709220E-03 --4.1970016167636650E-03 --4.1921130387373457E-03 --4.1872265452196885E-03 --4.1823421423093071E-03 --4.1774598361710661E-03 --4.1725796317596663E-03 --4.1677015308123361E-03 --4.1628255349283926E-03 --4.1579516488464635E-03 --4.1530798788140073E-03 --4.1482102308322286E-03 --4.1433427105761643E-03 --4.1384773229480752E-03 --4.1336140701966357E-03 --4.1287529542032167E-03 --4.1238939792996353E-03 --4.1190371513592809E-03 --4.1141824762251254E-03 --4.1093299596503862E-03 --4.1044796068055419E-03 --4.0996314201451195E-03 --4.0947854014433916E-03 --4.0899415544605787E-03 --4.0850998845758640E-03 --4.0802603974630846E-03 --4.0754230993291420E-03 --4.0705879959051791E-03 --4.0657550894500991E-03 --4.0609243809577112E-03 --4.0560958738729922E-03 --4.0512695742190054E-03 --4.0464454879922214E-03 --4.0416236207660257E-03 --4.0368039777554437E-03 --4.0319865617020135E-03 --4.0271713741111192E-03 --4.0223584181539674E-03 --4.0175476992748886E-03 --4.0127392231001464E-03 --4.0079329953319458E-03 --4.0031290214766922E-03 --3.9983273044198811E-03 --3.9935278453082715E-03 --3.9887306469016653E-03 --3.9839357148540892E-03 --3.9791430550101623E-03 --3.9743526726890889E-03 --3.9695645729439346E-03 --3.9647787590324874E-03 --3.9599952326604083E-03 --3.9552139964687356E-03 --3.9504350553700527E-03 --3.9456584146333228E-03 --3.9408840797880715E-03 --3.9361120564042331E-03 --3.9313423480960051E-03 --3.9265749562915741E-03 --3.9218098831482672E-03 --3.9170471333955523E-03 --3.9122867122729412E-03 --3.9075286252283972E-03 --3.9027728777903323E-03 --3.8980194737793217E-03 --3.8932684145480219E-03 --3.8885197019636144E-03 --3.8837733407714814E-03 --3.8790293364343053E-03 --3.8742876942129698E-03 --3.8695484192128112E-03 --3.8648115153115002E-03 --3.8600769840888205E-03 --3.8553448273478965E-03 --3.8506150494950469E-03 --3.8458876558194193E-03 --3.8411626515772786E-03 --3.8364400419907724E-03 --3.8317198311945940E-03 --3.8270020206489833E-03 --3.8222866117785951E-03 --3.8175736087385187E-03 --3.8128630169060097E-03 --3.8081548415380005E-03 --3.8034490877411516E-03 --3.7987457597820624E-03 --3.7940448592109224E-03 --3.7893463872737524E-03 --3.7846503477773439E-03 --3.7799567460287601E-03 --3.7752655872030356E-03 --3.7705768762426872E-03 --3.7658906175169664E-03 --3.7612068129749760E-03 --3.7565254640346836E-03 --3.7518465740264662E-03 --3.7471701477364075E-03 --3.7424961901299115E-03 --3.7378247064585981E-03 --3.7331557015087891E-03 --3.7284891771314829E-03 --3.7238251342040572E-03 --3.7191635757195082E-03 --3.7145045067487471E-03 --3.7098479323823151E-03 --3.7051938575322733E-03 --3.7005422867900945E-03 --3.6958932224149684E-03 --3.6912466655871366E-03 --3.6866026189548342E-03 --3.6819610870339331E-03 --3.6773220745759485E-03 --3.6726855867377449E-03 --3.6680516285257014E-03 --3.6634202022774068E-03 --3.6587913086823963E-03 --3.6541649499249314E-03 --3.6495411306819909E-03 --3.6449198558867156E-03 --3.6403011305896015E-03 --3.6356849597272930E-03 --3.6310713458400827E-03 --3.6264602895353117E-03 --3.6218517926786343E-03 --3.6172458599476928E-03 --3.6126424963417564E-03 --3.6080417066011797E-03 --3.6034434952934543E-03 --3.5988478651956708E-03 --3.5942548172163960E-03 --3.5896643531139320E-03 --3.5850764772933376E-03 --3.5804911946029612E-03 --3.5759085097142921E-03 --3.5713284271715190E-03 --3.5667509499687240E-03 --3.5621760790114443E-03 --3.5576038157646961E-03 --3.5530341643555969E-03 --3.5484671295321281E-03 --3.5439027159739757E-03 --3.5393409282993308E-03 --3.5347817697669046E-03 --3.5302252412600737E-03 --3.5256713439586586E-03 --3.5211200817471451E-03 --3.5165714593502072E-03 --3.5120254812932394E-03 --3.5074821519255955E-03 --3.5029414746306250E-03 --3.4984034505949830E-03 --3.4938680810443238E-03 --3.4893353695545281E-03 --3.4848053206787454E-03 --3.4802779388765966E-03 --3.4757532284996279E-03 --3.4712311930772408E-03 --3.4667118336678200E-03 --3.4621951511372502E-03 --3.4576811489117282E-03 --3.4531698318106068E-03 --3.4486612043196983E-03 --3.4441552704255630E-03 --3.4396520335873834E-03 --3.4351514952876555E-03 --3.4306536566422676E-03 --3.4261585205344856E-03 --3.4216660911034866E-03 --3.4171763726015100E-03 --3.4126893694417918E-03 --3.4082050855933142E-03 --3.4037235225190215E-03 --3.3992446809283524E-03 --3.3947685633584773E-03 --3.3902951740233723E-03 --3.3858245172150624E-03 --3.3813565972647102E-03 --3.3768914181723049E-03 --3.3724289814594643E-03 --3.3679692875957894E-03 --3.3635123387588928E-03 --3.3590581391523934E-03 --3.3546066931023472E-03 --3.3501580049522966E-03 --3.3457120788142687E-03 --3.3412689164091414E-03 --3.3368285180886853E-03 --3.3323908856788698E-03 --3.3279560232867514E-03 --3.3235239351756866E-03 --3.3190946254512046E-03 --3.3146680980449344E-03 --3.3102443549796298E-03 --3.3058233968429368E-03 --3.3014052252962208E-03 --3.2969898442096403E-03 --3.2925772577034368E-03 --3.2881674698312514E-03 --3.2837604845420633E-03 --3.2793563040118246E-03 --3.2749549286881139E-03 --3.2705563598364089E-03 --3.2661606010524241E-03 --3.2617676563394611E-03 --3.2573775299456018E-03 --3.2529902261856950E-03 --3.2486057475633757E-03 --3.2442240943015462E-03 --3.2398452672166345E-03 --3.2354692696989354E-03 --3.2310961057161669E-03 --3.2267257794270829E-03 --3.2223582950869456E-03 --3.2179936554117936E-03 --3.2136318606061144E-03 --3.2092729112214793E-03 --3.2049168105070611E-03 --3.2005635624978222E-03 --3.1962131712239979E-03 --3.1918656407050401E-03 --3.1875209737709394E-03 --3.1831791707223919E-03 --3.1788402319819888E-03 --3.1745041607722261E-03 --3.1701709613823430E-03 --3.1658406376577578E-03 --3.1615131929798338E-03 --3.1571886300503236E-03 --3.1528669497250927E-03 --3.1485481527639540E-03 --3.1442322418606442E-03 --3.1399192206960748E-03 --3.1356090930534262E-03 --3.1313018628424923E-03 --3.1269975332508773E-03 --3.1226961047318455E-03 --3.1183975773079941E-03 --3.1141019535169505E-03 --3.1098092375594693E-03 --3.1055194333589734E-03 --3.1012325443051576E-03 --3.0969485733230396E-03 --3.0926675212757803E-03 --3.0883893884829797E-03 --3.0841141770523149E-03 --3.0798418906237217E-03 --3.0755725328990911E-03 --3.0713061076085629E-03 --3.0670426181391018E-03 --3.0627820655281667E-03 --3.0585244498956012E-03 --3.0542697729264430E-03 --3.0500180380385188E-03 --3.0457692487804952E-03 --3.0415234088250298E-03 --3.0372805216231803E-03 --3.0330405883486284E-03 --3.0288036089673588E-03 --3.0245695849005568E-03 --3.0203385196636012E-03 --3.0161104169186934E-03 --3.0118852802727275E-03 --3.0076631131540207E-03 --3.0034439168212424E-03 --2.9992276910144324E-03 --2.9950144367887808E-03 --2.9908041576972842E-03 --2.9865968574891819E-03 --2.9823925395107702E-03 --2.9781912068948969E-03 --2.9739928612406395E-03 --2.9697975027513949E-03 --2.9656051324170466E-03 --2.9614157532639658E-03 --2.9572293686242041E-03 --2.9530459818456040E-03 --2.9488655962367598E-03 --2.9446882136533897E-03 --2.9405138342431859E-03 --2.9363424586962513E-03 --2.9321740897670394E-03 --2.9280087306520178E-03 --2.9238463848166706E-03 --2.9196870558558050E-03 --2.9155307458452787E-03 --2.9113774545488666E-03 --2.9072271821430386E-03 --2.9030799314202888E-03 --2.8989357058681977E-03 --2.8947945088261366E-03 --2.8906563435140810E-03 --2.8865212121193494E-03 --2.8823891147911878E-03 --2.8782600517903824E-03 --2.8741340254127860E-03 --2.8700110386937119E-03 --2.8658910948432142E-03 --2.8617741972380962E-03 --2.8576603483503132E-03 --2.8535495482794881E-03 --2.8494417970209842E-03 --2.8453370967514852E-03 --2.8412354506819381E-03 --2.8371368620467258E-03 --2.8330413341017720E-03 --2.8289488693966931E-03 --2.8248594680321502E-03 --2.8207731297647297E-03 --2.8166898563848335E-03 --2.8126096509426711E-03 --2.8085325166750750E-03 --2.8044584570910652E-03 --2.8003874750817028E-03 --2.7963195705589081E-03 --2.7922547427227983E-03 --2.7881929931631356E-03 --2.7841343253811853E-03 --2.7800787427632477E-03 --2.7760262483393248E-03 --2.7719768447202341E-03 --2.7679305321839957E-03 --2.7638873101860457E-03 --2.7598471800209397E-03 --2.7558101448834815E-03 --2.7517762079487217E-03 --2.7477453720930432E-03 --2.7437176399245223E-03 --2.7396930122043392E-03 --2.7356714887866312E-03 --2.7316530706632232E-03 --2.7276377603513407E-03 --2.7236255605755373E-03 --2.7196164744374847E-03 --2.7156105049484058E-03 --2.7116076529900592E-03 --2.7076079180555885E-03 --2.7036113007801697E-03 --2.6996178038144465E-03 --2.6956274300392394E-03 --2.6916401824853822E-03 --2.6876560641159934E-03 --2.6836750758920530E-03 --2.6796972170740137E-03 --2.6757224879610823E-03 --2.6717508913218098E-03 --2.6677824302283682E-03 --2.6638171075160162E-03 --2.6598549258664531E-03 --2.6558958864284434E-03 --2.6519399886677591E-03 --2.6479872327114526E-03 --2.6440376209191075E-03 --2.6400911560777924E-03 --2.6361478410895918E-03 --2.6322076788880809E-03 --2.6282706709434877E-03 --2.6243368166491495E-03 --2.6204061158206157E-03 --2.6164785705883879E-03 --2.6125541836686042E-03 --2.6086329578862625E-03 --2.6047148961303493E-03 --2.6008000000372960E-03 --2.5968882689326738E-03 --2.5929797023741623E-03 --2.5890743024939902E-03 --2.5851720722659980E-03 --2.5812730143497283E-03 --2.5773771311169980E-03 --2.5734844241898347E-03 --2.5695948934039733E-03 --2.5657085385861226E-03 --2.5618253614138140E-03 --2.5579453643797445E-03 --2.5540685499665489E-03 --2.5501949206406830E-03 --2.5463244782839272E-03 --2.5424572229078074E-03 --2.5385931543002514E-03 --2.5347322737528303E-03 --2.5308745834278614E-03 --2.5270200857305581E-03 --2.5231687834173662E-03 --2.5193206787040758E-03 --2.5154757713643852E-03 --2.5116340606504560E-03 --2.5077955477119588E-03 --2.5039602351162645E-03 --2.5001281254197478E-03 --2.4962992210901310E-03 --2.4924735242008783E-03 --2.4886510346156044E-03 --2.4848317514907341E-03 --2.4810156757515138E-03 --2.4772028100299047E-03 --2.4733931568728588E-03 --2.4695867184279822E-03 --2.4657834965763365E-03 --2.4619834916111104E-03 --2.4581867031090842E-03 --2.4543931317532611E-03 --2.4506027796084230E-03 --2.4468156488814501E-03 --2.4430317419704469E-03 --2.4392510611360250E-03 --2.4354736066941577E-03 --2.4316993777827398E-03 --2.4279283746490377E-03 --2.4241605993549037E-03 --2.4203960541742510E-03 --2.4166347416005960E-03 --2.4128766640701326E-03 --2.4091218221240205E-03 --2.4053702148013546E-03 --2.4016218420343733E-03 --2.3978767057188520E-03 --2.3941348080382821E-03 --2.3903961514238859E-03 --2.3866607383270372E-03 --2.3829285694007356E-03 --2.3791996434532458E-03 --2.3754739600707498E-03 --2.3717515212261613E-03 --2.3680323292939805E-03 --2.3643163865803493E-03 --2.3606036953243400E-03 --2.3568942564360417E-03 --2.3531880690657696E-03 --2.3494851327618338E-03 --2.3457854489882996E-03 --2.3420890196793613E-03 --2.3383958471040914E-03 --2.3347059337342491E-03 --2.3310192807034728E-03 --2.3273358868413567E-03 --2.3236557512755812E-03 --2.3199788757302499E-03 --2.3163052627084850E-03 --2.3126349143271188E-03 --2.3089678323720488E-03 --2.3053040178378308E-03 --2.3016434699658214E-03 --2.2979861880590832E-03 --2.2943321734269235E-03 --2.2906814281981438E-03 --2.2870339544534667E-03 --2.2833897542178122E-03 --2.2797488288116160E-03 --2.2761111774730618E-03 --2.2724767992685700E-03 --2.2688456952137696E-03 --2.2652178673698963E-03 --2.2615933177565178E-03 --2.2579720483203820E-03 --2.2543540604687577E-03 --2.2507393534926768E-03 --2.2471279263022079E-03 --2.2435197796645428E-03 --2.2399149156420326E-03 --2.2363133362743267E-03 --2.2327150435111436E-03 --2.2291200388956448E-03 --2.2255283218607152E-03 --2.2219398912213893E-03 --2.2183547473412931E-03 --2.2147728919803475E-03 --2.2111943270430845E-03 --2.2076190546612309E-03 --2.2040470766814301E-03 --2.2004783926580025E-03 --2.1969130011901795E-03 --2.1933509023671529E-03 --2.1897920980145516E-03 --2.1862365900461476E-03 --2.1826843803457383E-03 --2.1791354705981984E-03 --2.1755898605702968E-03 --2.1720475489515993E-03 --2.1685085356144022E-03 --2.1649728222273385E-03 --2.1614404105921763E-03 --2.1579113024474180E-03 --2.1543854994065938E-03 --2.1508630015491478E-03 --2.1473438078211111E-03 --2.1438279179328518E-03 --2.1403153331416573E-03 --2.1368060549550091E-03 --2.1333000852867432E-03 --2.1297974261106339E-03 --2.1262980776009925E-03 --2.1228020382084421E-03 --2.1193093072031208E-03 --2.1158198861389544E-03 --2.1123337769029839E-03 --2.1088509811603333E-03 --2.1053715004349812E-03 --2.1018953349478267E-03 --2.0984224833088456E-03 --2.0949529446932071E-03 --2.0914867205471823E-03 --2.0880238127699868E-03 --2.0845642229209978E-03 --2.0811079523382703E-03 --2.0776550014583108E-03 --2.0742053692790452E-03 --2.0707590550084077E-03 --2.0673160594055053E-03 --2.0638763837022064E-03 --2.0604400295932170E-03 --2.0570069991317688E-03 --2.0535772931821157E-03 --2.0501509101057201E-03 --2.0467278483658567E-03 --2.0433081089812491E-03 --2.0398916939235899E-03 --2.0364786047299376E-03 --2.0330688424912815E-03 --2.0296624077803535E-03 --2.0262592997994230E-03 --2.0228595176780472E-03 --2.0194630618976411E-03 --2.0160699336203829E-03 --2.0126801342082359E-03 --2.0092936652796431E-03 --2.0059105278876395E-03 --2.0025307209482392E-03 --1.9991542430348687E-03 --1.9957810944509517E-03 --1.9924112766262340E-03 --1.9890447910149963E-03 --1.9856816390805320E-03 --1.9823218218676807E-03 --1.9789653383612002E-03 --1.9756121870093978E-03 --1.9722623678954292E-03 --1.9689158824786569E-03 --1.9655727322047466E-03 --1.9622329183929632E-03 --1.9588964420717012E-03 --1.9555633024548715E-03 --1.9522334980653058E-03 --1.9489070286868044E-03 --1.9455838954746255E-03 --1.9422640996850757E-03 --1.9389476426695509E-03 --1.9356345256031765E-03 --1.9323247478996350E-03 --1.9290183080560939E-03 --1.9257152056562008E-03 --1.9224154418193086E-03 --1.9191190177935142E-03 --1.9158259348817201E-03 --1.9125361942640890E-03 --1.9092497953697601E-03 --1.9059667364248413E-03 --1.9026870167320586E-03 --1.8994106375983838E-03 --1.8961376004638434E-03 --1.8928679063481770E-03 --1.8896015560755015E-03 --1.8863385493770733E-03 --1.8830788850069920E-03 --1.8798225622402244E-03 --1.8765695816767407E-03 --1.8733199441660156E-03 --1.8700736509587015E-03 --1.8668307034320211E-03 --1.8635911015103044E-03 --1.8603548434386113E-03 --1.8571219280047947E-03 --1.8538923560082149E-03 --1.8506661286490970E-03 --1.8474432471702335E-03 --1.8442237128151935E-03 --1.8410075255529432E-03 --1.8377946834485447E-03 --1.8345851849705631E-03 --1.8313790309518465E-03 --1.8281762228281389E-03 --1.8249767617269941E-03 --1.8217806485413773E-03 --1.8185878833136182E-03 --1.8153984644438416E-03 --1.8122123904781228E-03 --1.8090296618630116E-03 --1.8058502797129435E-03 --1.8026742450988347E-03 --1.7995015590476370E-03 --1.7963322218197658E-03 --1.7931662317233670E-03 --1.7900035870365752E-03 --1.7868442881742038E-03 --1.7836883365334047E-03 --1.7805357331172941E-03 --1.7773864784375957E-03 --1.7742405725892890E-03 --1.7710980143559991E-03 --1.7679588023736257E-03 --1.7648229366725716E-03 --1.7616904181288399E-03 --1.7585612475607940E-03 --1.7554354256760847E-03 --1.7523129528651648E-03 --1.7491938281227501E-03 --1.7460780501078034E-03 --1.7429656184110502E-03 --1.7398565333580321E-03 --1.7367507956128759E-03 --1.7336484065012085E-03 --1.7305493670312971E-03 --1.7274536757696333E-03 --1.7243613304329772E-03 --1.7212723304443889E-03 --1.7181866769594419E-03 --1.7151043710592342E-03 --1.7120254134101078E-03 --1.7089498044283741E-03 --1.7058775430309227E-03 --1.7028086274180853E-03 --1.6997430569121424E-03 --1.6966808323110097E-03 --1.6936219544372972E-03 --1.6905664238400853E-03 --1.6875142409069120E-03 --1.6844654048657193E-03 --1.6814199142023052E-03 --1.6783777680311170E-03 --1.6753389665544217E-03 --1.6723035101967531E-03 --1.6692713999524357E-03 --1.6662426368823937E-03 --1.6632172202268513E-03 --1.6601951477066921E-03 --1.6571764179531664E-03 --1.6541610317197483E-03 --1.6511489899806080E-03 --1.6481402932865591E-03 --1.6451349419804120E-03 --1.6421329354283276E-03 --1.6391342719431726E-03 --1.6361389502675162E-03 --1.6331469705559687E-03 --1.6301583332541797E-03 --1.6271730391134948E-03 --1.6241910890189557E-03 --1.6212124825525107E-03 --1.6182372174778092E-03 --1.6152652920124902E-03 --1.6122967066767720E-03 --1.6093314625147907E-03 --1.6063695600749173E-03 --1.6034109995559580E-03 --1.6004557804143204E-03 --1.5975039007753268E-03 --1.5945553589863442E-03 --1.5916101552940474E-03 --1.5886682905485181E-03 --1.5857297652781632E-03 --1.5827945797224398E-03 --1.5798627335247692E-03 --1.5769342249395499E-03 --1.5740090522482727E-03 --1.5710872153530590E-03 --1.5681687148520489E-03 --1.5652535512027967E-03 --1.5623417246979471E-03 --1.5594332351587905E-03 --1.5565280809547823E-03 --1.5536262603163590E-03 --1.5507277728962602E-03 --1.5478326191512865E-03 --1.5449407994964073E-03 --1.5420523142709629E-03 --1.5391671634388201E-03 --1.5362853454126807E-03 --1.5334068582892727E-03 --1.5305317014373419E-03 --1.5276598751602004E-03 --1.5247913798411665E-03 --1.5219262159764714E-03 --1.5190643837697541E-03 --1.5162058817018377E-03 --1.5133507077059779E-03 --1.5104988608829919E-03 --1.5076503414410958E-03 --1.5048051496836894E-03 --1.5019632860448853E-03 --1.4991247507532674E-03 --1.4962895423070548E-03 --1.4934576584415315E-03 --1.4906290981480639E-03 --1.4878038619587941E-03 --1.4849819503815450E-03 --1.4821633635259985E-03 --1.4793481013122918E-03 --1.4765361625358835E-03 --1.4737275453237130E-03 --1.4709222484467043E-03 --1.4681202717093402E-03 --1.4653216151260153E-03 --1.4625262792458842E-03 --1.4597342646562742E-03 --1.4569455702207680E-03 --1.4541601934611749E-03 --1.4513781327458713E-03 --1.4485993882626593E-03 --1.4458239603954840E-03 --1.4430518493557846E-03 --1.4402830552422878E-03 --1.4375175770324170E-03 --1.4347554125737013E-03 --1.4319965602380207E-03 --1.4292410199567463E-03 --1.4264887919263074E-03 --1.4237398763664033E-03 --1.4209942734809064E-03 --1.4182519824070914E-03 --1.4155130008941079E-03 --1.4127773270770495E-03 --1.4100449608236089E-03 --1.4073159023846378E-03 --1.4045901519126847E-03 --1.4018677094860183E-03 --1.3991485743434107E-03 --1.3964327443097941E-03 --1.3937202174327881E-03 --1.3910109934987503E-03 --1.3883050728048939E-03 --1.3856024553928162E-03 --1.3829031410883745E-03 --1.3802071291256241E-03 --1.3775144174492490E-03 --1.3748250040789599E-03 --1.3721388886487388E-03 --1.3694560714330401E-03 --1.3667765524987018E-03 --1.3641003316875009E-03 --1.3614274083600334E-03 --1.3587577805089352E-03 --1.3560914460307124E-03 --1.3534284041776098E-03 --1.3507686549184819E-03 --1.3481121983087590E-03 --1.3454590345149554E-03 --1.3428091632643870E-03 --1.3401625825464674E-03 --1.3375192900337543E-03 --1.3348792847268885E-03 --1.3322425665372288E-03 --1.3296091354370984E-03 --1.3269789914764887E-03 --1.3243521344030050E-03 --1.3217285623469065E-03 --1.3191082729769230E-03 --1.3164912651448251E-03 --1.3138775387503316E-03 --1.3112670937388984E-03 --1.3086599300784338E-03 --1.3060560475146180E-03 --1.3034554442048500E-03 --1.3008581176642792E-03 --1.2982640665982763E-03 --1.2956732910744022E-03 --1.2930857911437282E-03 --1.2905015665737999E-03 --1.2879206169609694E-03 --1.2853429407740570E-03 --1.2827685358595394E-03 --1.2801974006866649E-03 --1.2776295346542596E-03 --1.2750649373515985E-03 --1.2725036088507182E-03 --1.2699455492399116E-03 --1.2673907570910222E-03 --1.2648392298750478E-03 --1.2622909657480797E-03 --1.2597459642292494E-03 --1.2572042250558156E-03 --1.2546657483221155E-03 --1.2521305341733587E-03 --1.2495985812344529E-03 --1.2470698866993211E-03 --1.2445444484380423E-03 --1.2420222661653423E-03 --1.2395033398527159E-03 --1.2369876692488473E-03 --1.2344752539753564E-03 --1.2319660928231896E-03 --1.2294601835744483E-03 --1.2269575243293062E-03 --1.2244581144565932E-03 --1.2219619535884757E-03 --1.2194690413381167E-03 --1.2169793772966403E-03 --1.2144929603910149E-03 --1.2120097885041361E-03 --1.2095298596717628E-03 --1.2070531730251164E-03 --1.2045797280164346E-03 --1.2021095243148713E-03 --1.1996425617533078E-03 --1.1971788394480834E-03 --1.1947183550382126E-03 --1.1922611062195514E-03 --1.1898070921214448E-03 --1.1873563124084453E-03 --1.1849087667636046E-03 --1.1824644548866987E-03 --1.1800233759046888E-03 --1.1775855273968253E-03 --1.1751509068812845E-03 --1.1727195134978953E-03 --1.1702913471740575E-03 --1.1678664075201143E-03 --1.1654446937290957E-03 --1.1630262047152378E-03 --1.1606109384905714E-03 --1.1581988929477327E-03 --1.1557900669350201E-03 --1.1533844599126519E-03 --1.1509820714099594E-03 --1.1485829010554750E-03 --1.1461869481620233E-03 --1.1437942104770933E-03 --1.1414046853568695E-03 --1.1390183714809505E-03 --1.1366352686230561E-03 --1.1342553764301928E-03 --1.1318786941998452E-03 --1.1295052210155622E-03 --1.1271349548725408E-03 --1.1247678933672936E-03 --1.1224040350206455E-03 --1.1200433793408327E-03 --1.1176859258713906E-03 --1.1153316741188150E-03 --1.1129806234287665E-03 --1.1106327717756313E-03 --1.1082881164370634E-03 --1.1059466556573329E-03 --1.1036083890208514E-03 --1.1012733161415099E-03 --1.0989414363699265E-03 --1.0966127489129372E-03 --1.0942872519710252E-03 --1.0919649430658485E-03 --1.0896458203351605E-03 --1.0873298830415166E-03 --1.0850171305566245E-03 --1.0827075622135052E-03 --1.0804011772867078E-03 --1.0780979742010444E-03 --1.0757979506348058E-03 --1.0735011046727561E-03 --1.0712074354109317E-03 --1.0689169420909379E-03 --1.0666296239622362E-03 --1.0643454802521271E-03 --1.0620645094415457E-03 --1.0597867091642205E-03 --1.0575120773400892E-03 --1.0552406129183739E-03 --1.0529723150793349E-03 --1.0507071833136526E-03 --1.0484452172652566E-03 --1.0461864155225213E-03 --1.0439307751224792E-03 --1.0416782934200889E-03 --1.0394289696004932E-03 --1.0371828033037239E-03 --1.0349397939071979E-03 --1.0326999405927575E-03 --1.0304632419720226E-03 --1.0282296955771274E-03 --1.0259992990177104E-03 --1.0237720510094636E-03 --1.0215479506613268E-03 --1.0193269973054809E-03 --1.0171091904811504E-03 --1.0148945290651026E-03 --1.0126830102551269E-03 --1.0104746312245144E-03 --1.0082693909135988E-03 --1.0060672890564353E-03 --1.0038683249575272E-03 --1.0016724973973569E-03 --9.9947980489764545E-04 --9.9729024522385735E-04 --9.9510381606777065E-04 --9.9292051599355626E-04 --9.9074034408661677E-04 --9.8856329949765457E-04 --9.8638938146861999E-04 --9.8421858894938517E-04 --9.8205091955434493E-04 --9.7988637059753065E-04 --9.7772494046210350E-04 --9.7556662835711155E-04 --9.7341143348224617E-04 --9.7125935497444017E-04 --9.6911039176373888E-04 --9.6696454158736692E-04 --9.6482180177938381E-04 --9.6268217055772037E-04 --9.6054564702212266E-04 --9.5841223030425468E-04 --9.5628191951910833E-04 --9.5415471364126839E-04 --9.5203061052265509E-04 --9.4990960748705174E-04 --9.4779170259661871E-04 --9.4567689486789550E-04 --9.4356518338307245E-04 --9.4145656723437657E-04 --9.3935104542415332E-04 --9.3724861590521247E-04 --9.3514927597172228E-04 --9.3305302353517922E-04 --9.3095985755342408E-04 --9.2886977708307879E-04 --9.2678278117921834E-04 --9.2469886883954811E-04 --9.2261803811888744E-04 --9.2054028629926952E-04 --9.1846561115086227E-04 --9.1639401155599863E-04 --9.1432548654352553E-04 --9.1226003514442342E-04 --9.1019765635769103E-04 --9.0813834834033397E-04 --9.0608210835663530E-04 --9.0402893403460506E-04 --9.0197882417072516E-04 --8.9993177777006458E-04 --8.9788779383856421E-04 --8.9584687136599211E-04 --8.9380900861345063E-04 --8.9177420284419339E-04 --8.8974245156490494E-04 --8.8771375349169378E-04 --8.8568810762662661E-04 --8.8366551292491245E-04 --8.8164596830366047E-04 --8.7962947211071255E-04 --8.7761602168357324E-04 --8.7560561447141624E-04 --8.7359824903160150E-04 --8.7159392427786436E-04 --8.6959263914987038E-04 --8.6759439260793928E-04 --8.6559918311704235E-04 --8.6360700798832827E-04 --8.6161786453339405E-04 --8.5963175120395985E-04 --8.5764866693479149E-04 --8.5566861063910565E-04 --8.5369158120364669E-04 --8.5171757715013670E-04 --8.4974659588053119E-04 --8.4777863468618207E-04 --8.4581369185552572E-04 --8.4385176623166390E-04 --8.4189285668736396E-04 --8.3993696212996956E-04 --8.3798408117866866E-04 --8.3603421125512444E-04 --8.3408734954480257E-04 --8.3214349421076241E-04 --8.3020264412113083E-04 --8.2826479814028021E-04 --8.2632995509585689E-04 --8.2439811361083738E-04 --8.2246927120001561E-04 --8.2054342503912095E-04 --8.1862057314791145E-04 --8.1670071433262263E-04 --8.1478384741856525E-04 --8.1286997120391463E-04 --8.1095908434427049E-04 --8.0905118445775352E-04 --8.0714626871321261E-04 --8.0524433498168116E-04 --8.0334538198051429E-04 --8.0144940848626172E-04 --7.9955641330542644E-04 --7.9766639515213404E-04 --7.9577935171659382E-04 --7.9389528009257801E-04 --7.9201417800101590E-04 --7.9013604414967088E-04 --7.8826087732001941E-04 --7.8638867624277061E-04 --7.8451943957775605E-04 --7.8265316513663192E-04 --7.8078985008289844E-04 --7.7892949203814627E-04 --7.7707208958484764E-04 --7.7521764142558878E-04 --7.7336614628736790E-04 --7.7151760287129704E-04 --7.6967200908971260E-04 --7.6782936207382647E-04 --7.6598965930583726E-04 --7.6415289929201904E-04 --7.6231908071090976E-04 --7.6048820227047936E-04 --7.5866026267448652E-04 --7.5683525993353485E-04 --7.5501319117188314E-04 --7.5319405375608584E-04 --7.5137784611701468E-04 --7.4956456692187238E-04 --7.4775421484385202E-04 --7.4594678855201995E-04 --7.4414228614186621E-04 --7.4234070475893098E-04 --7.4054204168251027E-04 --7.3874629525131784E-04 --7.3695346411765169E-04 --7.3516354692339193E-04 --7.3337654229938399E-04 --7.3159244841629150E-04 --7.2981126245033482E-04 --7.2803298160812615E-04 --7.2625760412123287E-04 --7.2448512862450241E-04 --7.2271555373676398E-04 --7.2094887805852954E-04 --7.1918509983196226E-04 --7.1742421627900516E-04 --7.1566622454892535E-04 --7.1391112273821577E-04 --7.1215890943369172E-04 --7.1040958322515595E-04 --7.0866314270083921E-04 --7.0691958617541276E-04 --7.0517891092241691E-04 --7.0344111403826328E-04 --7.0170619349009251E-04 --6.9997414783130743E-04 --6.9824497562341852E-04 --6.9651867542295349E-04 --6.9479524558810324E-04 --6.9307468346733634E-04 --6.9135698613039269E-04 --6.8964215141934491E-04 --6.8793017784847749E-04 --6.8622106394756360E-04 --6.8451480823030766E-04 --6.8281140907155979E-04 --6.8111086390391495E-04 --6.7941316978575210E-04 --6.7771832443494083E-04 --6.7602632631097957E-04 --6.7433717391350220E-04 --6.7265086574449422E-04 --6.7096740021124258E-04 --6.6928677481756075E-04 --6.6760898657964966E-04 --6.6593403308921157E-04 --6.6426191277988204E-04 --6.6259262414658298E-04 --6.6092616566482240E-04 --6.5926253574364517E-04 --6.5760173196319736E-04 --6.5594375131363650E-04 --6.5428859126211148E-04 --6.5263625019898984E-04 --6.5098672660784647E-04 --6.4934001892295173E-04 --6.4769612552651368E-04 --6.4605504409256389E-04 --6.4441677164040899E-04 --6.4278130554341114E-04 --6.4114864411148780E-04 --6.3951878579277335E-04 --6.3789172900560905E-04 --6.3626747213572270E-04 --6.3464601294627241E-04 --6.3302734845711709E-04 --6.3141147593854217E-04 --6.2979839362592037E-04 --6.2818809994727052E-04 --6.2658059327870856E-04 --6.2497587195759928E-04 --6.2337393383469857E-04 --6.2177477600977289E-04 --6.2017839571535131E-04 --6.1858479104939085E-04 --6.1699396034924179E-04 --6.1540590198002850E-04 --6.1382061432487098E-04 --6.1223809532634196E-04 --6.1065834203976081E-04 --6.0908135157442922E-04 --6.0750712198612484E-04 --6.0593565167407488E-04 --6.0436693897847240E-04 --6.0280098218025424E-04 --6.0123777925046517E-04 --5.9967732734655000E-04 --5.9811962359058394E-04 --5.9656466589003533E-04 --5.9501245253122540E-04 --5.9346298181855582E-04 --5.9191625207631160E-04 --5.9037226137615209E-04 --5.8883100689535327E-04 --5.8729248568098545E-04 --5.8575669552695666E-04 --5.8422363469663795E-04 --5.8269330148323672E-04 --5.8116569421710548E-04 --5.7964081103081930E-04 --5.7811864910742663E-04 --5.7659920539653443E-04 --5.7508247760101568E-04 --5.7356846403593478E-04 --5.7205716300529140E-04 --5.7054857275111762E-04 --5.6904269137719526E-04 --5.6753951615951773E-04 --5.6603904407460384E-04 --5.6454127271761043E-04 --5.6304620033306350E-04 --5.6155382518321864E-04 --5.6006414549353810E-04 --5.5857715939448935E-04 --5.5709286424689380E-04 --5.5561125702763086E-04 --5.5413233522596378E-04 --5.5265609702900072E-04 --5.5118254066871747E-04 --5.4971166435941301E-04 --5.4824346625174502E-04 --5.4677794376949661E-04 --5.4531509385505783E-04 --5.4385491388408665E-04 --5.4239740200849758E-04 --5.4094255645561649E-04 --5.3949037543635702E-04 --5.3804085711887148E-04 --5.3659399899639605E-04 --5.3514979797978442E-04 --5.3370825133329362E-04 --5.3226935717710943E-04 --5.3083311374225669E-04 --5.2939951919901305E-04 --5.2796857167270253E-04 --5.2654026873743751E-04 --5.2511460735263143E-04 --5.2369158471826400E-04 --5.2227119886365692E-04 --5.2085344797115761E-04 --5.1943833018586909E-04 --5.1802584362328991E-04 --5.1661598594419131E-04 --5.1520875415428120E-04 --5.1380414540089226E-04 --5.1240215761358030E-04 --5.1100278892061317E-04 --5.0960603745223143E-04 --5.0821190133639815E-04 --5.0682037830949848E-04 --5.0543146537454693E-04 --5.0404515959603946E-04 --5.0266145881282937E-04 --5.0128036112785971E-04 --4.9990186467496669E-04 --4.9852596761526308E-04 --4.9715266776861715E-04 --4.9578196211396916E-04 --4.9441384761485588E-04 --4.9304832205781884E-04 --4.9168538359661775E-04 --4.9032503033584625E-04 --4.8896726031959692E-04 --4.8761207136765778E-04 --4.8625946057993872E-04 --4.8490942497286723E-04 --4.8356196220692094E-04 --4.8221707032021185E-04 --4.8087474738075565E-04 --4.7953499149511669E-04 --4.7819780058329223E-04 --4.7686317173700537E-04 --4.7553110186717687E-04 --4.7420158854419997E-04 --4.7287462983906656E-04 --4.7155022382875468E-04 --4.7022836857724685E-04 --4.6890906201361586E-04 --4.6759230128505129E-04 --4.6627808328132572E-04 --4.6496640548350309E-04 --4.6365726595225297E-04 --4.6235066275123593E-04 --4.6104659388813854E-04 --4.5974505727741915E-04 --4.5844605016215941E-04 --4.5714956947638484E-04 --4.5585561260680162E-04 --4.5456417751473042E-04 --4.5327526220754393E-04 --4.5198886472488611E-04 --4.5070498305072309E-04 --4.4942361447109972E-04 --4.4814475584248716E-04 --4.4686840444834239E-04 --4.4559455828167870E-04 --4.4432321538654366E-04 --4.4305437373854751E-04 --4.4178803125885643E-04 --4.4052418531402289E-04 --4.3926283282415604E-04 --4.3800397101075061E-04 --4.3674759776626175E-04 --4.3549371106865850E-04 --4.3424230889099427E-04 --4.3299338918430052E-04 --4.3174694940068626E-04 --4.3050298647250647E-04 --4.2926149754721063E-04 --4.2802248044677299E-04 --4.2678593311341553E-04 --4.2555185350965329E-04 --4.2432023959782737E-04 --4.2309108889617965E-04 --4.2186439832538172E-04 --4.2064016495391203E-04 --4.1941838656364266E-04 --4.1819906110393117E-04 --4.1698218652373216E-04 --4.1576776076736197E-04 --4.1455578140791975E-04 --4.1334624537083496E-04 --4.1213914965833678E-04 --4.1093449198723292E-04 --4.0973227029870134E-04 --4.0853248253257853E-04 --4.0733512662620685E-04 --4.0614020021435571E-04 --4.0494770024127231E-04 --4.0375762365779563E-04 --4.0256996811169598E-04 --4.0138473154030350E-04 --4.0020191186409577E-04 --3.9902150698362267E-04 --3.9784351457080653E-04 --3.9666793161031294E-04 --3.9549475502716929E-04 --3.9432398239698665E-04 --3.9315561164977869E-04 --3.9198964068661078E-04 --3.9082606736192131E-04 --3.8966488937020190E-04 --3.8850610377512000E-04 --3.8734970752139981E-04 --3.8619569808575390E-04 --3.8504407332206171E-04 --3.8389483110317729E-04 --3.8274796932239699E-04 --3.8160348574576609E-04 --3.8046137743841685E-04 --3.7932164125714532E-04 --3.7818427460572845E-04 --3.7704927538868268E-04 --3.7591664149715619E-04 --3.7478637074457637E-04 --3.7365846085522103E-04 --3.7253290898469097E-04 --3.7140971204846355E-04 --3.7028886737590827E-04 --3.6917037278629385E-04 --3.6805422612472402E-04 --3.6694042522857464E-04 --3.6582896787735818E-04 --3.6471985127925428E-04 --3.6361307231601298E-04 --3.6250862822244145E-04 --3.6140651677850014E-04 --3.6030673581327561E-04 --3.5920928316978551E-04 --3.5811415665699600E-04 --3.5702135353443519E-04 --3.5593087064937439E-04 --3.5484270515484702E-04 --3.5375685483170709E-04 --3.5267331752854346E-04 --3.5159209105669958E-04 --3.5051317319311994E-04 --3.4943656125499821E-04 --3.4836225211227117E-04 --3.4729024285700999E-04 --3.4622053121023791E-04 --3.4515311499318973E-04 --3.4408799201725412E-04 --3.4302516007775233E-04 --3.4196461655844167E-04 --3.4090635832609100E-04 --3.3985038240306082E-04 --3.3879668646663640E-04 --3.3774526833402847E-04 --3.3669612579712574E-04 --3.3564925662729796E-04 --3.3460465826566931E-04 --3.3356232761656758E-04 --3.3252226166902577E-04 --3.3148445803567189E-04 --3.3044891450905643E-04 --3.2941562885961456E-04 --3.2838459883847320E-04 --3.2735582193706516E-04 --3.2632929509678516E-04 --3.2530501528267098E-04 --3.2428298004824428E-04 --3.2326318717348641E-04 --3.2224563441291974E-04 --3.2123031949392279E-04 --3.2021723994563522E-04 --3.1920639274586951E-04 --3.1819777483862701E-04 --3.1719138369833318E-04 --3.1618721706906915E-04 --3.1518527269959554E-04 --3.1418554834208298E-04 --3.1318804158694873E-04 --3.1219274942003258E-04 --3.1119966872952966E-04 --3.1020879692518721E-04 --3.0922013176155183E-04 --3.0823367098425637E-04 --3.0724941231281534E-04 --3.0626735335186962E-04 --3.0528749114448495E-04 --3.0430982258378684E-04 --3.0333434500845116E-04 --3.0236105613815870E-04 --3.0138995369737601E-04 --3.0042103539354448E-04 --2.9945429885407706E-04 --2.9848974118176525E-04 --2.9752735927578389E-04 --2.9656715040675185E-04 --2.9560911225564169E-04 --2.9465324252478901E-04 --2.9369953891721003E-04 --2.9274799908142051E-04 --2.9179862015906084E-04 --2.9085139902378863E-04 --2.8990633288356147E-04 --2.8896341942637318E-04 --2.8802265636709959E-04 --2.8708404138127065E-04 --2.8614757210157856E-04 --2.8521324572712217E-04 --2.8428105915410040E-04 --2.8335100953655226E-04 --2.8242309451737745E-04 --2.8149731178726595E-04 --2.8057365900935007E-04 --2.7965213381830103E-04 --2.7873273347308849E-04 --2.7781545489142238E-04 --2.7690029517906940E-04 --2.7598725192821939E-04 --2.7507632280280626E-04 --2.7416750546250038E-04 --2.7326079755452833E-04 --2.7235619639585354E-04 --2.7145369891593381E-04 --2.7055330217089875E-04 --2.6965500369558788E-04 --2.6875880112415347E-04 --2.6786469212323219E-04 --2.6697267437279397E-04 --2.6608274524344839E-04 --2.6519490163610167E-04 --2.6430914053838270E-04 --2.6342545948015680E-04 --2.6254385613541377E-04 --2.6166432815306792E-04 --2.6078687316143052E-04 --2.5991148855887807E-04 --2.5903817129064053E-04 --2.5816691833276367E-04 --2.5729772714673798E-04 --2.5643059536860992E-04 --2.5556552064409595E-04 --2.5470250062763829E-04 --2.5384153277649440E-04 --2.5298261403496687E-04 --2.5212574132888962E-04 --2.5127091208502366E-04 --2.5041812396628740E-04 --2.4956737460965196E-04 --2.4871866161790075E-04 --2.4787198245737504E-04 --2.4702733413070491E-04 --2.4618471357910595E-04 --2.4534411816644472E-04 --2.4450554551720812E-04 --2.4366899325069626E-04 --2.4283445897158734E-04 --2.4200194018444735E-04 --2.4117143393709935E-04 --2.4034293716829959E-04 --2.3951644717873640E-04 --2.3869196155821824E-04 --2.3786947790800430E-04 --2.3704899383650253E-04 --2.3623050688035917E-04 --2.3541401412390675E-04 --2.3459951249100967E-04 --2.3378699922799198E-04 --2.3297647191380345E-04 --2.3216792814802892E-04 --2.3136136554525091E-04 --2.3055678166863773E-04 --2.2975417362208680E-04 --2.2895353828513839E-04 --2.2815487284842659E-04 --2.2735817491861338E-04 --2.2656344211947611E-04 --2.2577067203151510E-04 --2.2497986219375849E-04 --2.2419100977002737E-04 --2.2340411168025984E-04 --2.2261916507002207E-04 --2.2183616748128380E-04 --2.2105511649729898E-04 --2.2027600971148969E-04 --2.1949884469967971E-04 --2.1872361867548027E-04 --2.1795032854545306E-04 --2.1717897140423610E-04 --2.1640954479247996E-04 --2.1564204630835352E-04 --2.1487647352632792E-04 --2.1411282400001218E-04 --2.1335109497944236E-04 --2.1259128338199792E-04 --2.1183338626121670E-04 --2.1107740112705003E-04 --2.1032332557292062E-04 --2.0957115718141169E-04 --2.0882089352361992E-04 --2.0807253190181422E-04 --2.0732606923773357E-04 --2.0658150254110729E-04 --2.0583882928685380E-04 --2.0509804706358883E-04 --2.0435915343308778E-04 --2.0362214593631632E-04 --2.0288702191304751E-04 --2.0215377833378216E-04 --2.0142241221021085E-04 --2.0069292098578913E-04 --1.9996530224544056E-04 --1.9923955353399114E-04 --1.9851567235943071E-04 --1.9779365608700361E-04 --1.9707350174099869E-04 --1.9635520634304261E-04 --1.9563876725954844E-04 --1.9492418200957022E-04 --1.9421144814433375E-04 --1.9350056325177965E-04 --1.9279152477511268E-04 --1.9208432968828573E-04 --1.9137897491488268E-04 --1.9067545781015338E-04 --1.8997377597692428E-04 --1.8927392698160614E-04 --1.8857590833120053E-04 --1.8787971744206437E-04 --1.8718535136403986E-04 --1.8649280707253049E-04 --1.8580208187847641E-04 --1.8511317334290360E-04 --1.8442607900733313E-04 --1.8374079636326036E-04 --1.8305732284115193E-04 --1.8237565555436118E-04 --1.8169579151466880E-04 --1.8101772797946748E-04 --1.8034146244275893E-04 --1.7966699241843650E-04 --1.7899431544695054E-04 --1.7832342902561460E-04 --1.7765433028189761E-04 --1.7698701617631105E-04 --1.7632148391061531E-04 --1.7565773098737739E-04 --1.7499575493451391E-04 --1.7433555330254334E-04 --1.7367712361304613E-04 --1.7302046302071277E-04 --1.7236556845860157E-04 --1.7171243708073673E-04 --1.7106106640151923E-04 --1.7041145396303034E-04 --1.6976359728500259E-04 --1.6911749386224113E-04 --1.6847314089913105E-04 --1.6783053537049040E-04 --1.6718967441414797E-04 --1.6655055552293373E-04 --1.6591317623033345E-04 --1.6527753404498496E-04 --1.6464362645577020E-04 --1.6401145070459397E-04 --1.6338100378058876E-04 --1.6275228279253714E-04 --1.6212528521151285E-04 --1.6150000856791468E-04 --1.6087645036915525E-04 --1.6025460810592556E-04 --1.5963447905907241E-04 --1.5901606023217460E-04 --1.5839934870834352E-04 --1.5778434193357673E-04 --1.5717103743559250E-04 --1.5655943272090050E-04 --1.5594952527997019E-04 --1.5534131242985811E-04 --1.5473479119087249E-04 --1.5412995862614458E-04 --1.5352681215395820E-04 --1.5292534930060343E-04 --1.5232556756901699E-04 --1.5172746444176767E-04 --1.5113103727101983E-04 --1.5053628311824784E-04 --1.4994319904955777E-04 --1.4935178242505803E-04 --1.4876203072597031E-04 --1.4817394146063705E-04 --1.4758751216647511E-04 --1.4700274025588594E-04 --1.4641962276675018E-04 --1.4583815670456661E-04 --1.4525833940948158E-04 --1.4468016840089065E-04 --1.4410364119543000E-04 --1.4352875530344864E-04 --1.4295550814705246E-04 --1.4238389680123025E-04 --1.4181391827879384E-04 --1.4124556989776938E-04 --1.4067884918849175E-04 --1.4011375366420416E-04 --1.3955028079902238E-04 --1.3898842800885375E-04 --1.3842819242296299E-04 --1.3786957108830633E-04 --1.3731256128860059E-04 --1.3675716052055810E-04 --1.3620336628502835E-04 --1.3565117607459764E-04 --1.3510058733857155E-04 --1.3455159722421546E-04 --1.3400420275436713E-04 --1.3345840118259266E-04 --1.3291419003071424E-04 --1.3237156681992276E-04 --1.3183052902172835E-04 --1.3129107407282661E-04 --1.3075319916227245E-04 --1.3021690134072312E-04 --1.2968217783189452E-04 --1.2914902612147085E-04 --1.2861744371457553E-04 --1.2808742810744715E-04 --1.2755897677596095E-04 --1.2703208694107149E-04 --1.2650675563597759E-04 --1.2598298004491164E-04 --1.2546075765542677E-04 --1.2494008598595063E-04 --1.2442096253115049E-04 --1.2390338476685799E-04 --1.2338734994698898E-04 --1.2287285511335496E-04 --1.2235989742375578E-04 --1.2184847435513384E-04 --1.2133858343242291E-04 --1.2083022216173021E-04 --1.2032338803449838E-04 --1.1981807833811492E-04 --1.1931429010814289E-04 --1.1881202046632427E-04 --1.1831126688108269E-04 --1.1781202689160460E-04 --1.1731429800465517E-04 --1.1681807770473547E-04 --1.1632336331323414E-04 --1.1583015189139841E-04 --1.1533844055106407E-04 --1.1484822674120293E-04 --1.1435950800354409E-04 --1.1387228182797149E-04 --1.1338654566284691E-04 --1.1290229686232034E-04 --1.1241953258661576E-04 --1.1193825000349261E-04 --1.1145844647571986E-04 --1.1098011944222381E-04 --1.1050326639421145E-04 --1.1002788487582048E-04 --1.0955397231953332E-04 --1.0908152584477611E-04 --1.0861054254962674E-04 --1.0814101979943245E-04 --1.0767295509281828E-04 --1.0720634592622305E-04 --1.0674118979190952E-04 --1.0627748411461539E-04 --1.0581522607309551E-04 --1.0535441280746655E-04 --1.0489504166436357E-04 --1.0443711012464600E-04 --1.0398061567486355E-04 --1.0352555580738294E-04 --1.0307192796561097E-04 --1.0261972935021965E-04 --1.0216895709848116E-04 --1.0171960853372762E-04 --1.0127168113570135E-04 --1.0082517239891865E-04 --1.0038007983998224E-04 --9.9936400938213375E-05 --9.9494132906691966E-05 --9.9053272857357533E-05 --9.8613818087263540E-05 --9.8175766094397963E-05 --9.7739114386447844E-05 --9.7303860470057579E-05 --9.6870001826171117E-05 --9.6437535704238549E-05 --9.6006459233682591E-05 --9.5576769694117545E-05 --9.5148464576919447E-05 --9.4721541389411007E-05 --9.4295997639531971E-05 --9.3871830819186475E-05 --9.3449038212800863E-05 --9.3027616962455519E-05 --9.2607564329673083E-05 --9.2188877798169769E-05 --9.1771554875953439E-05 --9.1355593075146850E-05 --9.0940989899375760E-05 --9.0527742665593786E-05 --9.0115848524168098E-05 --8.9705304719447926E-05 --8.9296108733480519E-05 --8.8888258082405402E-05 --8.8481750278725279E-05 --8.8076582828182704E-05 --8.7672753080233898E-05 --8.7270258204160767E-05 --8.6869095434010044E-05 --8.6469262239666995E-05 --8.6070756137398457E-05 --8.5673574643365611E-05 --8.5277715271248958E-05 --8.4883175403694723E-05 --8.4489952228054610E-05 --8.4098042970765137E-05 --8.3707445090301993E-05 --8.3318156106277648E-05 --8.2930173537587492E-05 --8.2543494901715094E-05 --8.2158117610207226E-05 --8.1774038869246099E-05 --8.1391255901011719E-05 --8.1009766151732669E-05 --8.0629567146383991E-05 --8.0250656408719384E-05 --7.9873031461041264E-05 --7.9496689742319018E-05 --7.9121628479389804E-05 --7.8747844893158701E-05 --7.8375336415022204E-05 --7.8004100574047199E-05 --7.7634134898352724E-05 --7.7265436914229906E-05 --7.6898004085271870E-05 --7.6531833663241131E-05 --7.6166922872991435E-05 --7.5803269130449256E-05 --7.5440869967317772E-05 --7.5079722916015913E-05 --7.4719825507536949E-05 --7.4361175226774566E-05 --7.4003769350304319E-05 --7.3647605106996446E-05 --7.3292679899443199E-05 --7.2938991266561387E-05 --7.2586536747072189E-05 --7.2235313871708913E-05 --7.1885320139056399E-05 --7.1536552857700186E-05 --7.1189009270784524E-05 --7.0842686766117171E-05 --7.0497582878105211E-05 --7.0153695147741430E-05 --6.9811021116202346E-05 --6.9469558302640849E-05 --6.9129304042733164E-05 --6.8790255584401622E-05 --6.8452410302238164E-05 --6.8115765737169088E-05 --6.7780319439197877E-05 --6.7446068950581224E-05 --6.7113011798210960E-05 --6.6781145350585636E-05 --6.6450466875187140E-05 --6.6120973737073514E-05 --6.5792663469392174E-05 --6.5465533622337789E-05 --6.5139581749965530E-05 --6.4814805398719932E-05 --6.4491201965929633E-05 --6.4168768724768018E-05 --6.3847503028357087E-05 --6.3527402415133121E-05 --6.3208464447645472E-05 --6.2890686683727108E-05 --6.2574066674592213E-05 --6.2258601846908396E-05 --6.1944289493228246E-05 --6.1631126962863393E-05 --6.1319111790423191E-05 --6.1008241543736309E-05 --6.0698513786531597E-05 --6.0389926078094229E-05 --6.0082475874181693E-05 --5.9776160486563903E-05 --5.9470977263105561E-05 --5.9166923734046478E-05 --5.8863997473795132E-05 --5.8562196052858314E-05 --5.8261517038167946E-05 --5.7961957913235905E-05 --5.7663516011042767E-05 --5.7366188681514172E-05 --5.7069973445979672E-05 --5.6774867881715606E-05 --5.6480869567397459E-05 --5.6187976082673152E-05 --5.5896184939088405E-05 --5.5605493487015541E-05 --5.5315899077033134E-05 --5.5027399226144493E-05 --5.4739991523095012E-05 --5.4453673554449203E-05 --5.4168442903930884E-05 --5.3884297104555674E-05 --5.3601233530917684E-05 --5.3319249542113043E-05 --5.3038342648126672E-05 --5.2758510444138203E-05 --5.2479750524249720E-05 --5.2202060479537806E-05 --5.1925437864104195E-05 --5.1649880078113663E-05 --5.1375384490924324E-05 --5.1101948604239373E-05 --5.0829570016755501E-05 --5.0558246330172053E-05 --5.0287975147678794E-05 --5.0018754045598328E-05 --4.9750580448108791E-05 --4.9483451731892094E-05 --4.9217365392001710E-05 --4.8952319035524326E-05 --4.8688310273915256E-05 --4.8425336718559107E-05 --4.8163395962277682E-05 --4.7902485456143793E-05 --4.7642602588845598E-05 --4.7383744850704326E-05 --4.7125909856471598E-05 --4.6869095227050252E-05 --4.6613298578636061E-05 --4.6358517514935520E-05 --4.6104749517659530E-05 --4.5851991996300355E-05 --4.5600242439070173E-05 --4.5349498460048813E-05 --4.5099757685103111E-05 --4.4851017743185896E-05 --4.4603276256643429E-05 --4.4356530733623289E-05 --4.4110778593618488E-05 --4.3866017320941566E-05 --4.3622244538123878E-05 --4.3379457884569290E-05 --4.3137654998785987E-05 --4.2896833514689727E-05 --4.2656990967144633E-05 --4.2418124791390423E-05 --4.2180232471040295E-05 --4.1943311632678892E-05 --4.1707359926558412E-05 --4.1472375000337781E-05 --4.1238354498286656E-05 --4.1005295982782159E-05 --4.0773196909858228E-05 --4.0542054767142460E-05 --4.0311867181960410E-05 --4.0082631813057188E-05 --3.9854346318168196E-05 --3.9627008353489414E-05 --3.9400615507789196E-05 --3.9175165256386466E-05 --3.8950655091948919E-05 --3.8727082643688731E-05 --3.8504445581909351E-05 --3.8282741574720851E-05 --3.8061968288140905E-05 --3.7842123335695784E-05 --3.7623204215642547E-05 --3.7405208429941003E-05 --3.7188133604684794E-05 --3.6971977415856146E-05 --3.6756737542887825E-05 --3.6542411668725228E-05 --3.6328997433906501E-05 --3.6116492355323922E-05 --3.5904893940987709E-05 --3.5694199818980407E-05 --3.5484407680535016E-05 --3.5275515216129813E-05 --3.5067520114418231E-05 --3.4860420034105630E-05 --3.4654212518337466E-05 --3.4448895090582308E-05 --3.4244465379184963E-05 --3.4040921084227180E-05 --3.3838259906941418E-05 --3.3636479548128232E-05 --3.3435577687212527E-05 --3.3235551892755416E-05 --3.3036399702311098E-05 --3.2838118744467980E-05 --3.2640706728298292E-05 --3.2444161366045407E-05 --3.2248480370900135E-05 --3.2053661441250356E-05 --3.1859702170475133E-05 --3.1666600109604985E-05 --3.1474352888565643E-05 --3.1282958227399016E-05 --3.1092413851285625E-05 --3.0902717486128829E-05 --3.0713866848028358E-05 --3.0525859556706285E-05 --3.0338693179030462E-05 --3.0152365347175085E-05 --2.9966873790379788E-05 --2.9782216245689616E-05 --2.9598390450236240E-05 --2.9415394135100471E-05 --2.9233224947586118E-05 --2.9051880474411062E-05 --2.8871358352671933E-05 --2.8691656318595554E-05 --2.8512772120145331E-05 --2.8334703508309594E-05 --2.8157448231501230E-05 --2.7981003963323751E-05 --2.7805368307125286E-05 --2.7630538904805456E-05 --2.7456513502084295E-05 --2.7283289860968171E-05 --2.7110865745170844E-05 --2.6939238917292069E-05 --2.6768407076426389E-05 --2.6598367844640813E-05 --2.6429118871190449E-05 --2.6260657911622543E-05 --2.6092982743445290E-05 --2.5926091141986189E-05 --2.5759980880473987E-05 --2.5594649682966329E-05 --2.5430095196383093E-05 --2.5266315082698557E-05 --2.5103307101367028E-05 --2.4941069039267007E-05 --2.4779598686139564E-05 --2.4618893833659839E-05 --2.4458952231775997E-05 --2.4299771544990490E-05 --2.4141349443592245E-05 --2.3983683695474181E-05 --2.3826772104807836E-05 --2.3670612475086736E-05 --2.3515202609013071E-05 --2.3360540278449698E-05 --2.3206623172313405E-05 --2.3053448976528913E-05 --2.2901015465786051E-05 --2.2749320458219390E-05 --2.2598361770955338E-05 --2.2448137219434714E-05 --2.2298644596938850E-05 --2.2149881617693889E-05 --2.2001845984879973E-05 --2.1854535478025756E-05 --2.1707947925409070E-05 --2.1562081157513013E-05 --2.1416933007192877E-05 --2.1272501291186318E-05 --2.1128783747716244E-05 --2.0985778095485246E-05 --2.0843482120254760E-05 --2.0701893663172096E-05 --2.0561010569282352E-05 --2.0420830688521419E-05 --2.0281351859563270E-05 --2.0142571843968358E-05 --2.0004488374908643E-05 --1.9867099245595305E-05 --1.9730402313254335E-05 --1.9594395439085908E-05 --1.9459076486783244E-05 --1.9324443312633822E-05 --1.9190493703259590E-05 --1.9057225410011905E-05 --1.8924636235489668E-05 --1.8792724053179960E-05 --1.8661486741308662E-05 --1.8530922176517156E-05 --1.8401028230452493E-05 --1.8271802717124157E-05 --1.8143243411765755E-05 --1.8015348126726264E-05 --1.7888114741904016E-05 --1.7761541145981359E-05 --1.7635625236929457E-05 --1.7510364912508156E-05 --1.7385758011539052E-05 --1.7261802321183784E-05 --1.7138495661262496E-05 --1.7015835931991300E-05 --1.6893821044784819E-05 --1.6772448909237580E-05 --1.6651717432663499E-05 --1.6531624478551530E-05 --1.6412167860746439E-05 --1.6293345414926938E-05 --1.6175155052582725E-05 --1.6057594699773448E-05 --1.5940662282144805E-05 --1.5824355724406020E-05 --1.5708672914820527E-05 --1.5593611688292535E-05 --1.5479169893677264E-05 --1.5365345455067079E-05 --1.5252136315894952E-05 --1.5139540418190755E-05 --1.5027555702724214E-05 --1.4916180083007877E-05 --1.4805411420714742E-05 --1.4695247583132324E-05 --1.4585686500979825E-05 --1.4476726127188395E-05 --1.4368364421447751E-05 --1.4260599349683038E-05 --1.4153428853024225E-05 --1.4046850810040626E-05 --1.3940863098759008E-05 --1.3835463665509022E-05 --1.3730650487725661E-05 --1.3626421542440013E-05 --1.3522774806003563E-05 --1.3419708238519243E-05 --1.3317219746301980E-05 --1.3215307230000117E-05 --1.3113968647426947E-05 --1.3013201990444616E-05 --1.2913005252911556E-05 --1.2813376431095597E-05 --1.2714313509134479E-05 --1.2615814416360916E-05 --1.2517877070415809E-05 --1.2420499441725019E-05 --1.2323679541419522E-05 --1.2227415381686553E-05 --1.2131704974725145E-05 --1.2036546324507321E-05 --1.1941937385866494E-05 --1.1847876097463319E-05 --1.1754360443315460E-05 --1.1661388452596143E-05 --1.1568958155731265E-05 --1.1477067581294949E-05 --1.1385714752609358E-05 --1.1294897652753160E-05 --1.1204614246080452E-05 --1.1114862529578577E-05 --1.1025640542292068E-05 --1.0936946328510642E-05 --1.0848777941376101E-05 --1.0761133432081750E-05 --1.0674010807291256E-05 --1.0587408045849778E-05 --1.0501323157689281E-05 --1.0415754205178978E-05 --1.0330699255533089E-05 --1.0246156375445611E-05 --1.0162123629587775E-05 --1.0078599051793785E-05 --9.9955806506960192E-06 --9.9130664552811632E-06 --9.8310545403509203E-06 --9.7495429876488905E-06 --9.6685298849273988E-06 --9.5880133211377926E-06 --9.5079913551515735E-06 --9.4284620140071931E-06 --9.3494233410515213E-06 --9.2708734307646031E-06 --9.1928103870525355E-06 --9.1152323166684440E-06 --9.0381373272973191E-06 --8.9615235027038153E-06 --8.8853888939462348E-06 --8.8097315626428172E-06 --8.7345496198166521E-06 --8.6598411885469491E-06 --8.5856043949718196E-06 --8.5118373670830932E-06 --8.4385382138104176E-06 --8.3657050102153365E-06 --8.2933358370387189E-06 --8.2214288219628325E-06 --8.1499821078371120E-06 --8.0789938404694542E-06 --8.0084621681893208E-06 --7.9383852246079730E-06 --7.8687611089734923E-06 --7.7995879220174115E-06 --7.7308638084540215E-06 --7.6625869317056117E-06 --7.5947554576147869E-06 --7.5273675546690823E-06 --7.4604213805483766E-06 --7.3939150592868402E-06 --7.3278467126685229E-06 --7.2622145024744096E-06 --7.1970166127077862E-06 --7.1322512294789576E-06 --7.0679165416214912E-06 --7.0040107304841284E-06 --6.9405319457901547E-06 --6.8774783317089438E-06 --6.8148480671890556E-06 --6.7526393562374500E-06 --6.6908504053501289E-06 --6.6294794246895489E-06 --6.5685246193904605E-06 --6.5079841646213308E-06 --6.4478562267808483E-06 --6.3881390026270751E-06 --6.3288307171541522E-06 --6.2699295979105651E-06 --6.2114338761248976E-06 --6.1533417799633069E-06 --6.0956515104889087E-06 --6.0383612572788145E-06 --5.9814692355126444E-06 --5.9249736911371308E-06 --5.8688728730035186E-06 --5.8131650335480449E-06 --5.7578484236679424E-06 --5.7029212706753406E-06 --5.6483817882756580E-06 --5.5942282108276149E-06 --5.5404588049973684E-06 --5.4870718410707749E-06 --5.4340655930348090E-06 --5.3814383345435387E-06 --5.3291883191399631E-06 --5.2773137850663072E-06 --5.2258129865982012E-06 --5.1746842111899795E-06 --5.1239257509386012E-06 --5.0735359017771835E-06 --5.0235129602989788E-06 --4.9738552062126123E-06 --4.9245609025462457E-06 --4.8756283241583090E-06 --4.8270557792477687E-06 --4.7788415819945173E-06 --4.7309840506375520E-06 --4.6834815050053552E-06 --4.6363322509472648E-06 --4.5895345764585251E-06 --4.5430867777386733E-06 --4.4969871841247175E-06 --4.4512341325980014E-06 --4.4058259637288020E-06 --4.3607610201988574E-06 --4.3160376337899458E-06 --4.2716541182094576E-06 --4.2276087921087104E-06 --4.1839000055975222E-06 --4.1405261183176819E-06 --4.0974854935394092E-06 --4.0547764974461487E-06 --4.0123974878072374E-06 --3.9703468040501713E-06 --3.9286227878772870E-06 --3.8872238107666813E-06 --3.8461482560135068E-06 --3.8053945096506339E-06 --3.7649609605569282E-06 --3.7248459918064029E-06 --3.6850479695568121E-06 --3.6455652599980955E-06 --3.6063962557428148E-06 --3.5675393631186650E-06 --3.5289929913307610E-06 --3.4907555533393131E-06 --3.4528254580382948E-06 --3.4152010978543670E-06 --3.3778808632404917E-06 --3.3408631684519440E-06 --3.3041464437636970E-06 --3.2677291219229268E-06 --3.2316096395101303E-06 --3.1957864306197195E-06 --3.1602579146938937E-06 --3.1250225076486440E-06 --3.0900786457498022E-06 --3.0554247829470725E-06 --3.0210593757003534E-06 --2.9869808849029418E-06 --2.9531877701530371E-06 --2.9196784778479345E-06 --2.8864514494347411E-06 --2.8535051435687225E-06 --2.8208380381998531E-06 --2.7884486138916122E-06 --2.7563353560716112E-06 --2.7244967498704376E-06 --2.6929312688515930E-06 --2.6616373804838317E-06 --2.6306135663668654E-06 --2.5998583286429589E-06 --2.5693701723187191E-06 --2.5391476075338429E-06 --2.5091891449958702E-06 --2.4794932854500534E-06 --2.4500585226187141E-06 --2.4208833616453591E-06 --2.3919663294417860E-06 --2.3633059561414307E-06 --2.3349007763535682E-06 --2.3067493258287162E-06 --2.2788501326449091E-06 --2.2512017178131888E-06 --2.2238026109077505E-06 --2.1966513632873965E-06 --2.1697465301765794E-06 --2.1430866709951379E-06 --2.1166703468780820E-06 --2.0904961134005457E-06 --2.0645625195013861E-06 --2.0388681199634696E-06 --2.0134114899782791E-06 --1.9881912094105480E-06 --1.9632058632865956E-06 --1.9384540395867863E-06 --1.9139343215371463E-06 --1.8896452849748733E-06 --1.8655855097338336E-06 --1.8417535959273677E-06 --1.8181481495370905E-06 --1.7947677811847727E-06 --1.7716111050021898E-06 --1.7486767315758273E-06 --1.7259632641969847E-06 --1.7034693086141731E-06 --1.6811934901878145E-06 --1.6591344415955235E-06 --1.6372907991074374E-06 --1.6156612025126838E-06 --1.5942442895407136E-06 --1.5730386920885780E-06 --1.5520430432410307E-06 --1.5312559932380925E-06 --1.5106762006636199E-06 --1.4903023276545274E-06 --1.4701330407884345E-06 --1.4501670054594114E-06 --1.4304028818942998E-06 --1.4108393305368447E-06 --1.3914750269451062E-06 --1.3723086561963639E-06 --1.3533389066526077E-06 --1.3345644718321278E-06 --1.3159840447725588E-06 --1.2975963139911837E-06 --1.2793999675025525E-06 --1.2613937067203951E-06 --1.2435762439434621E-06 --1.2259462943190987E-06 --1.2085025784302419E-06 --1.1912438169532785E-06 --1.1741687267038850E-06 --1.1572760234624072E-06 --1.1405644348395357E-06 --1.1240327008310562E-06 --1.1076795637744688E-06 --1.0915037709821904E-06 --1.0755040704093999E-06 --1.0596792080084400E-06 --1.0440279289173394E-06 --1.0285489873587258E-06 --1.0132411498367042E-06 --9.9810318540346301E-07 --9.8313386944449504E-07 --9.6833197867072057E-07 --9.5369628774029330E-07 --9.3922557003009968E-07 --9.2491860658426562E-07 --9.1077419192260756E-07 --8.9679112308102063E-07 --8.8296820293385034E-07 --8.6930423613655272E-07 --8.5579802626001864E-07 --8.4244837596281368E-07 --8.2925409384385505E-07 --8.1621400218834189E-07 --8.0332692602480033E-07 --7.9059169608024647E-07 --7.7800714544820006E-07 --7.6557210677487777E-07 --7.5328541220217054E-07 --7.4114589832582005E-07 --7.2915241533002745E-07 --7.1730381655060474E-07 --7.0559896082381536E-07 --6.9403670999954611E-07 --6.8261592592372563E-07 --6.7133547039243964E-07 --6.6019420846521008E-07 --6.4919101844422208E-07 --6.3832478237081207E-07 --6.2759438741203177E-07 --6.1699872438486806E-07 --6.0653668445344143E-07 --5.9620715928466557E-07 --5.8600904291036566E-07 --5.7594124192312441E-07 --5.6600266740036706E-07 --5.5619223509464361E-07 --5.4650886505250699E-07 --5.3695147792080122E-07 --5.2751899542673076E-07 --5.1821034103725653E-07 --5.0902444984506485E-07 --4.9996026227145641E-07 --4.9101672290731324E-07 --4.8219278125562616E-07 --4.7348738762087524E-07 --4.6489949398858099E-07 --4.5642805371449055E-07 --4.4807203065129811E-07 --4.3983039484887179E-07 --4.3170212001581262E-07 --4.2368618534907163E-07 --4.1578157102041880E-07 --4.0798725942179498E-07 --4.0030223418313229E-07 --3.9272548819942373E-07 --3.8525602140813855E-07 --3.7789283693115917E-07 --3.7063494389607426E-07 --3.6348135259500497E-07 --3.5643107596274289E-07 --3.4948312825495215E-07 --3.4263653174237717E-07 --3.3589031653586052E-07 --3.2924351550265555E-07 --3.2269516788514037E-07 --3.1624431433059665E-07 --3.0988999844602015E-07 --3.0363126543865000E-07 --2.9746716729444657E-07 --2.9139676453789042E-07 --2.8541912012500259E-07 --2.7953330359616575E-07 --2.7373838621593605E-07 --2.6803344244510347E-07 --2.6241754881563538E-07 --2.5688978740033513E-07 --2.5144924927158033E-07 --2.4609502776938477E-07 --2.4082622295509786E-07 --2.3564193705324875E-07 --2.3054127550738969E-07 --2.2552334638264587E-07 --2.2058726220914701E-07 --2.1573214487446110E-07 --2.1095711851803937E-07 --2.0626131389931076E-07 --2.0164386447405391E-07 --1.9710390681692767E-07 --1.9264058074559402E-07 --1.8825302962901279E-07 --1.8394040639416483E-07 --1.7970186636971915E-07 --1.7553657120934498E-07 --1.7144368586409230E-07 --1.6742237822370230E-07 --1.6347182008918821E-07 --1.5959118607361577E-07 --1.5577966030216672E-07 --1.5203642961887040E-07 --1.4836068679752336E-07 --1.4475162858072309E-07 --1.4120845439505123E-07 --1.3773036821721508E-07 --1.3431657632178286E-07 --1.3096629423619672E-07 --1.2767874069059649E-07 --1.2445313978825279E-07 --1.2128872025401995E-07 --1.1818471326019451E-07 --1.1514035521244997E-07 --1.1215488451769189E-07 --1.0922754824265955E-07 --1.0635759722683983E-07 --1.0354428717223641E-07 --1.0078687915200324E-07 --9.8084636397994985E-08 --9.5436827807157803E-08 --9.2842724202280293E-08 --9.0301604456946776E-08 --8.7812751915926455E-08 --8.5375454164323255E-08 --8.2989004787548316E-08 --8.0652699329342564E-08 --7.8365839359754679E-08 --7.6127728516170878E-08 --7.3937677718265837E-08 --7.1795003071114345E-08 --6.9699024327251605E-08 --6.7649067812870524E-08 --6.5644461714697754E-08 --6.3684540406085333E-08 --6.1768640667970903E-08 --5.9896105732860628E-08 --5.8066284734382320E-08 --5.6278529907678729E-08 --5.4532200516303043E-08 --5.2826657716173464E-08 --5.1161268828395195E-08 --4.9535404090844922E-08 --4.7948439335204572E-08 --4.6399756969035914E-08 --4.4888742046300438E-08 --4.3414786953307868E-08 --4.1977286145102631E-08 --4.0575640051610707E-08 --3.9209252656388163E-08 --3.7877532693359062E-08 --3.6579896067242194E-08 --3.5315761007868847E-08 --3.4084553194099595E-08 --3.2885700706981924E-08 --3.1718637266734964E-08 --3.0582800870761919E-08 --2.9477633477044601E-08 --2.8402584690591421E-08 --2.7357106285703514E-08 --2.6340657405740641E-08 --2.5352700085148896E-08 --2.4392701535596197E-08 --2.3460134004192362E-08 --2.2554473007610634E-08 --2.1675202046275195E-08 --2.0821806804722712E-08 --1.9993780074536437E-08 --1.9190618150830800E-08 --1.8411821962823177E-08 --1.7656898224886286E-08 --1.6925356366920838E-08 --1.6216713966422522E-08 --1.5530490974154429E-08 --1.4866214033824219E-08 --1.4223413993515892E-08 --1.3601625751322447E-08 --1.3000390679644334E-08 --1.2419252490600745E-08 --1.1857763011146499E-08 --1.1315476808619242E-08 --1.0791954599677132E-08 --1.0286762051513243E-08 --9.7994683074129686E-09 --9.3296495784861910E-09 --8.8768842354633953E-09 --8.4407585245141295E-09 --8.0208619557496970E-09 --7.6167895630817633E-09 --7.2281420904837388E-09 --6.8545232349760602E-09 --6.4955442050555536E-09 --6.1508183849660006E-09 --5.8199666338722945E-09 --5.5026137187817486E-09 --5.1983892543797646E-09 --4.9069292867461168E-09 --4.6278723979633209E-09 --4.3608649466215645E-09 --4.1055556793654406E-09 --3.8616002800722149E-09 --3.6286590616325362E-09 --3.4063965046082363E-09 --3.1944841626415147E-09 --2.9925958610998772E-09 --2.8004132501180830E-09 --2.6176207741868601E-09 --2.4439091723227222E-09 --2.2789745698618595E-09 --2.1225166208134801E-09 --1.9742425760555375E-09 --1.8338618682468397E-09 --1.7010915898259416E-09 --1.5756521986997543E-09 --1.4572697390043510E-09 --1.3456763938851140E-09 --1.2406073222362054E-09 --1.1418056470454685E-09 --1.0490167649383810E-09 --9.6199338384017097E-10 --8.8049227003083141E-10 --8.0427504250002919E-10 --7.3311016287488540E-10 --6.6676864961636898E-10 --6.0502965934625762E-10 --5.4767490229679998E-10 --4.9449289774138324E-10 --4.4527699284214277E-10 --3.9982467175762660E-10 --3.5794087314491195E-10 --3.1943284875747906E-10 --2.8411594159965001E-10 --2.5180851434792234E-10 --2.2233511707284062E-10 --1.9552592807064303E-10 --1.7121460860159049E-10 --1.4924275740892149E-10 --1.2945422976277375E-10 --1.1170072186078897E-10 --9.5837568309496897E-11 --8.1725593636869548E-11 --6.9232035143674366E-11 --5.8227065979996797E-11 --4.8589113817898478E-11 --4.0198998019636638E-11 --3.2944955130422726E-11 --2.6719588764544600E-11 --2.1420266312769912E-11 --1.6951489990687653E-11 --1.3220303816900579E-11 --1.0142115692954298E-11 --7.6350564157245434E-12 --5.6241182526454802E-12 --4.0394621565471332E-12 --2.8152841090332069E-12 --1.8934873635463345E-12 --1.2183351879044278E-12 --7.4250779871519885E-13 --4.2196259985249582E-13 --2.1839191798943897E-13 --9.9035346821695661E-14 --3.5381277322081621E-14 --9.3397035389237926E-15 --4.4862118882457237E-15 --4.3963887862075566E-15 diff --git a/bench/POTENTIALS/Ni.adp b/bench/POTENTIALS/Ni.adp new file mode 120000 index 0000000000..1c4f621747 --- /dev/null +++ b/bench/POTENTIALS/Ni.adp @@ -0,0 +1 @@ +../../potentials/Ni.adp \ No newline at end of file From bbb0f5740efd2c4ea6734a29e1fe54271f3d2f92 Mon Sep 17 00:00:00 2001 From: "tanmoy.7989" Date: Fri, 6 Sep 2019 11:18:33 -0700 Subject: [PATCH 101/192] link to data.peptide was deleted by me by mistake. Now that it's re-added, I revoked (un-necessary) changes I made since to the in.peptide input script --- tools/replica/example/in.peptide | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/tools/replica/example/in.peptide b/tools/replica/example/in.peptide index ada6941af1..5d321e34c3 100644 --- a/tools/replica/example/in.peptide +++ b/tools/replica/example/in.peptide @@ -14,7 +14,7 @@ dihedral_style charmm improper_style harmonic kspace_style pppm 0.0001 -read_data ../../../examples/peptide/data.peptide +read_data data.peptide neighbor 2.0 bin neigh_modify delay 5 From 48ea1eecb6fa3494db772069de1529baa7542ea1 Mon Sep 17 00:00:00 2001 From: alxvov Date: Sun, 8 Sep 2019 15:51:54 +0300 Subject: [PATCH 102/192] make as in master --- src/MAKE/Makefile.serial | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/MAKE/Makefile.serial b/src/MAKE/Makefile.serial index 8628d2bb73..5954d97761 100644 --- a/src/MAKE/Makefile.serial +++ b/src/MAKE/Makefile.serial @@ -7,7 +7,7 @@ SHELL = /bin/sh # specify flags and libraries needed for your compiler CC = g++ -CCFLAGS = -g -O3 -Wall +CCFLAGS = -g -O3 SHFLAGS = -fPIC DEPFLAGS = -M From f41a1f83030f343aa1df647f269405e917adbc6c Mon Sep 17 00:00:00 2001 From: "tanmoy.7989" Date: Sun, 8 Sep 2019 10:43:22 -0700 Subject: [PATCH 103/192] vectorized in parts and made changes as suggested by evoyiatzis --- tools/replica/reorder_remd_traj.py | 47 +++++++++++++++--------------- 1 file changed, 24 insertions(+), 23 deletions(-) diff --git a/tools/replica/reorder_remd_traj.py b/tools/replica/reorder_remd_traj.py index c8c467ffe0..cef417cd0b 100644 --- a/tools/replica/reorder_remd_traj.py +++ b/tools/replica/reorder_remd_traj.py @@ -38,11 +38,11 @@ StringIO (or io if in Python 3.x) -import os, sys, numpy as np, argparse, time, pickle +import os, numpy as np, argparse, time, pickle from scipy.special import logsumexp from mpi4py import MPI -from tqdm import tqdm, trange +from tqdm import tqdm import gzip, bz2 try: # python-2 @@ -78,12 +78,10 @@ def _get_nearest_temp(temps, query_temp): """ if isinstance(temps, list): temps = np.array(temps) - idx = np.argmin(abs(temps - query_temp)) - out_temp = temps[idx] - return out_temp + return temps[np.argmin(np.abs(temps-query_temp))] -def readwrite(trajfn, mode = "rb"): +def readwrite(trajfn, mode): """ Helper function for input/output LAMMPS traj files. Trajectories may be plain text, .gz or .bz2 compressed. @@ -96,11 +94,14 @@ def readwrite(trajfn, mode = "rb"): """ if trajfn.endswith(".gz"): - return gzip.GzipFile(trajfn, mode) + of = gzip.open(trajfn, mode) + #return gzip.GzipFile(trajfn, mode) elif trajfn.endswith(".bz2"): - return bz2.BZ2File(trajfn, mode) + of = bz2.open(trajfn, mode) + #return bz2.BZ2File(trajfn, mode) else: - return file(trajfn, mode) + of = open(trajfn, mode) + return of def get_replica_frames(logfn, temps, nswap, writefreq): @@ -163,7 +164,7 @@ def get_byte_index(rep_inds, byteindfns, intrajfns): if os.path.isfile(byteindfns[n]): continue # extract bytes - fobj = readwrite(intrajfns[n]) + fobj = readwrite(intrajfns[n], "rb") byteinds = [ [0,0] ] # place file pointer at first line @@ -243,7 +244,7 @@ def write_reordered_traj(temp_inds, byte_inds, outtemps, temps, for n in temp_inds: # open string-buffer and file buf = IOBuffer() - of = readwrite(outtrajfns[n], mode = "wb") + of = readwrite(outtrajfns[n], "wb") # get frames abs_temp_ind = np.argmin( abs(temps - outtemps[n]) ) @@ -281,7 +282,7 @@ def write_reordered_traj(temp_inds, byte_inds, outtemps, temps, def get_canonical_logw(enefn, frametuple_dict, temps, nprod, writefreq, - kB = 0.001987): + kB): """ Gets configurational log-weights (logw) for each frame and at each temp. from the REMD simulation. ONLY WRITTEN FOR THE CANONICAL (NVT) ensemble. @@ -348,25 +349,25 @@ def get_canonical_logw(enefn, frametuple_dict, temps, nprod, writefreq, #3) get reduced energies (*ONLY FOR THE CANONICAL ENSEMBLE*) u_kln = np.zeros([ntemps, ntemps, nframes], float) for k in range(ntemps): - for l in range(ntemps): - u_kln[ k, l, 0:nframes_k[k] ] = beta_k[l] * u_kn[k, 0:nframes_k[k]] - + u_kln[k] = np.outer(beta_k, u_kn[k]) + # run pymbar and extract the free energies print("\nRunning pymbar...") mbar = pymbar.mbar.MBAR(u_kln, nframes_k, verbose = True) - f_k = mbar.f_k + f_k = mbar.f_k # (1 x k array) # calculate the log-weights print("\nExtracting log-weights...") log_nframes = np.log(nframes) logw = dict( (k, np.zeros([ntemps, nframes], float)) for k in range(ntemps) ) - for l in range(ntemps): - # get log-weights to reweight to this temp. - for k in range(ntemps): - for n in range(nframes): - num = -beta_k[k] * u_kn[k,n] - denom = f_k - beta_k[k] * u_kn[k,n] + # get log-weights to reweight to this temp. + for k in range(ntemps): + for n in range(nframes): + num = -beta_k[k] * u_kn[k,n] + denom = f_k - beta_k[k] * u_kn[k,n] + for l in range(ntemps): logw[l][k,n] = num - logsumexp(denom) - log_nframes + return logw @@ -515,7 +516,7 @@ if __name__ == "__main__": comm.barrier() # open all replica files for reading - infobjs = [readwrite(i) for i in intrajfns] + infobjs = [readwrite(i, "rb") for i in intrajfns] # open all byteindex files byte_inds = dict( (i, np.loadtxt(fn)) for i, fn in enumerate(byteindfns) ) From 2e0fcac74418d2c23093814dbb411bf5baf01c9a Mon Sep 17 00:00:00 2001 From: jrgissing Date: Sun, 8 Sep 2019 21:11:24 -0600 Subject: [PATCH 104/192] bond/react: define MAXLINE take 2 --- src/USER-MISC/fix_bond_react.h | 5 +++-- 1 file changed, 3 insertions(+), 2 deletions(-) diff --git a/src/USER-MISC/fix_bond_react.h b/src/USER-MISC/fix_bond_react.h index 169409c3aa..e5452cb226 100644 --- a/src/USER-MISC/fix_bond_react.h +++ b/src/USER-MISC/fix_bond_react.h @@ -26,12 +26,13 @@ FixStyle(bond/react,FixBondReact) #include "fix.h" -#define MAXLINE 256 - namespace LAMMPS_NS { class FixBondReact : public Fix { public: + + enum {MAXLINE=256}; + FixBondReact(class LAMMPS *, int, char **); ~FixBondReact(); int setmask(); From 450f437d9f2f5f99ddaf56926d78cee9a1702489 Mon Sep 17 00:00:00 2001 From: jrgissing Date: Sun, 8 Sep 2019 22:59:59 -0600 Subject: [PATCH 105/192] bond/react:another edge atom clarification --- doc/src/fix_bond_react.txt | 24 +++++++++++++----------- 1 file changed, 13 insertions(+), 11 deletions(-) diff --git a/doc/src/fix_bond_react.txt b/doc/src/fix_bond_react.txt index 3fe3d8547e..ff5c14c1bd 100644 --- a/doc/src/fix_bond_react.txt +++ b/doc/src/fix_bond_react.txt @@ -188,17 +188,19 @@ Some atoms in the pre-reacted template that are not reacting may have missing topology with respect to the simulation. For example, the pre-reacted template may contain an atom that, in the simulation, is currently connected to the rest of a long polymer chain. These are -referred to as edge atoms, and are also specified in the map file. -When the pre-reaction template contains edge atoms, not all atoms, -bonds, charges, etc. specified in the reaction templates will be -updated. Specifically, topology that involves only atoms that are 'too -near' to template edges will not be updated. The definition of 'too -near the edge' depends on which interactions are defined in the -simulation. If the simulation has defined dihedrals, atoms within two -bonds of edge atoms are considered 'too near the edge.' If the -simulation defines angles, but not dihedrals, atoms within one bond of -edge atoms are considered 'too near the edge.' If just bonds are -defined, only edge atoms are considered 'too near the edge.' +referred to as edge atoms, and are also specified in the map file. All +pre-reaction template atoms should be linked to a bonding atom, via at +least one path that does not involve edge atoms. When the pre-reaction +template contains edge atoms, not all atoms, bonds, charges, etc. +specified in the reaction templates will be updated. Specifically, +topology that involves only atoms that are 'too near' to template +edges will not be updated. The definition of 'too near the edge' +depends on which interactions are defined in the simulation. If the +simulation has defined dihedrals, atoms within two bonds of edge atoms +are considered 'too near the edge.' If the simulation defines angles, +but not dihedrals, atoms within one bond of edge atoms are considered +'too near the edge.' If just bonds are defined, only edge atoms are +considered 'too near the edge.' NOTE: Small molecules, i.e. ones that have all their atoms contained within the reaction templates, never have edge atoms. From 8c113f5fdb4177c5478299d3f53e549490b38c03 Mon Sep 17 00:00:00 2001 From: "tanmoy.7989" Date: Mon, 9 Sep 2019 01:51:04 -0700 Subject: [PATCH 106/192] added LD potential and wrote html-style doc --- doc/src/Eqs/pair_local_density_energy.jpg | Bin 0 -> 3045 bytes doc/src/Eqs/pair_local_density_energy.tex | 11 + .../pair_local_density_energy_implement.jpg | Bin 0 -> 7981 bytes .../pair_local_density_energy_implement.tex | 9 + .../Eqs/pair_local_density_energy_multi.jpg | Bin 0 -> 3464 bytes .../Eqs/pair_local_density_energy_multi.tex | 9 + .../Eqs/pair_local_density_indicator_func.jpg | Bin 0 -> 9062 bytes .../Eqs/pair_local_density_indicator_func.tex | 16 + doc/src/Eqs/pair_local_density_ld.jpg | Bin 0 -> 3098 bytes doc/src/Eqs/pair_local_density_ld.tex | 10 + .../Eqs/pair_local_density_ld_implement.jpg | Bin 0 -> 4300 bytes .../Eqs/pair_local_density_ld_implement.tex | 10 + doc/src/Eqs/pair_local_density_ld_multi.jpg | Bin 0 -> 3443 bytes doc/src/Eqs/pair_local_density_ld_multi.tex | 10 + doc/src/pair_local_density.txt | 207 ++ .../benzene_water/benzene_water.data | 1406 +++++++++ .../benzene_water/benzene_water.in | 62 + .../benzene_water.localdensity.table | 2024 +++++++++++++ .../benzene_water/benzene_water.pair.table | 2024 +++++++++++++ .../benzene_water/log.04Sep19.g++.1 | 267 ++ .../methanol_implicit_water/log.04Sep19.g++.1 | 226 ++ .../methanol_implicit_water.data | 2525 +++++++++++++++++ .../methanol_implicit_water.in | 68 + ...methanol_implicit_water.localdensity.table | 509 ++++ .../methanol_implicit_water.pair.table | 1012 +++++++ src/USER-MISC/README | 1 + src/USER-MISC/pair_local_density.cpp | 871 ++++++ src/USER-MISC/pair_local_density.h | 88 + 28 files changed, 11365 insertions(+) create mode 100644 doc/src/Eqs/pair_local_density_energy.jpg create mode 100644 doc/src/Eqs/pair_local_density_energy.tex create mode 100644 doc/src/Eqs/pair_local_density_energy_implement.jpg create mode 100644 doc/src/Eqs/pair_local_density_energy_implement.tex create mode 100644 doc/src/Eqs/pair_local_density_energy_multi.jpg create mode 100644 doc/src/Eqs/pair_local_density_energy_multi.tex create mode 100644 doc/src/Eqs/pair_local_density_indicator_func.jpg create mode 100644 doc/src/Eqs/pair_local_density_indicator_func.tex create mode 100644 doc/src/Eqs/pair_local_density_ld.jpg create mode 100644 doc/src/Eqs/pair_local_density_ld.tex create mode 100644 doc/src/Eqs/pair_local_density_ld_implement.jpg create mode 100644 doc/src/Eqs/pair_local_density_ld_implement.tex create mode 100644 doc/src/Eqs/pair_local_density_ld_multi.jpg create mode 100644 doc/src/Eqs/pair_local_density_ld_multi.tex create mode 100644 doc/src/pair_local_density.txt create mode 100644 examples/USER/misc/local_density/benzene_water/benzene_water.data create mode 100644 examples/USER/misc/local_density/benzene_water/benzene_water.in create mode 100644 examples/USER/misc/local_density/benzene_water/benzene_water.localdensity.table create mode 100644 examples/USER/misc/local_density/benzene_water/benzene_water.pair.table create mode 100644 examples/USER/misc/local_density/benzene_water/log.04Sep19.g++.1 create mode 100644 examples/USER/misc/local_density/methanol_implicit_water/log.04Sep19.g++.1 create mode 100644 examples/USER/misc/local_density/methanol_implicit_water/methanol_implicit_water.data create mode 100644 examples/USER/misc/local_density/methanol_implicit_water/methanol_implicit_water.in create mode 100644 examples/USER/misc/local_density/methanol_implicit_water/methanol_implicit_water.localdensity.table create mode 100644 examples/USER/misc/local_density/methanol_implicit_water/methanol_implicit_water.pair.table create mode 100644 src/USER-MISC/pair_local_density.cpp create mode 100644 src/USER-MISC/pair_local_density.h diff --git a/doc/src/Eqs/pair_local_density_energy.jpg b/doc/src/Eqs/pair_local_density_energy.jpg new file mode 100644 index 0000000000000000000000000000000000000000..68e44ce9d95ec0592ddc3236076f0067e7cc981c GIT binary patch literal 3045 zcmbW3c{J4h9>;%UhQUm>rm`|vCq3gzSD<%c77!C^4Cn8&`m> z5#|<=LmlVYjXww7Pe!Q6q-XQW8bGmz8LBlODmXCk$K2b4oMJ1&2frDtxqgvX> zbc{~mj7>~WnpxY}+SxleIuYGH&U<=!UkC~g2@MO6xEOaOJ|XdH5`}u>=B?Xz?%vDD zdHm#QZeD)Dv$Aqp#mmYndUZo%Q!}&W^_$k7UREEwf8ZTwWOQtN;?v~R^vuHI((=mc z+WNPRpIjgS{0G*~{Rh~8a0%~laX}zp2=pfxh%0QzU||Ti9EwNeI39YAynDZT3@^ek zJ-hT3pS;HD`8{rd-TZqM&?AZqKhb_C``^G~{}$Q5!T#jp0B|s9r+HvuKp$A!P|k_w z|GWNl$#Klt5{g4?q&&z!<*QP75?jWcarYTfBODE1ZeaxXeR37j9}QcOuiui8L3;;o zJZM-Q6l(RHF-m1dV`0D4-rnf%xMNve<~txv_&jV<^7<`m<=EI$qIZ_+Rxi64{iI9t z?)jG?r;?OX!z(s zFUBN$)*7Q@SDyF5>>9m?J)!6!rEYj5#y~t|DXdA5kF%+}9^*e6+H;n*sTGC#j-z!a z3fBa-YILo5=rsk;E?@T~RV$`mT|QNW#9uu{3XGQwlTOC+YRhg=fXU?#+~HvRUf&g% zjKI{A(~z+O1y^CN{;+ZRx!`>ND|NV5{Br5mm+F$mlEdp!MISDyF3`4s1;mr-ei6Uk zIp=up)K-(6-wbut)|41?(U|fk8LmsJ`6iQ7Zod1hlD|?M+&wME(r>wuJJ(E0jJoFh zkI+conxdC7CtQz=0Ap{hD<~TUvT2dADuxumrpSF8tBqmnWxK~%Dyi-J-n35Ve zICnsXpupK{!-JU}J|PZ1kK#6sk)OEDUQE?49gLrtmq zdfR|9w5PNdj~v`2jaa}x)_Y{)t6cH?sfT2~d(C{9=Le=~@BEQ3D5Q0f;nCw&4cBYh zpgA{&Vv^IDL6k}yv909sO!;(12<=W~Xsh@bkvj#R{H$DNR6gx7l3p*{#nWuda<8Q{ zIQqz?MBbFRz0WttJj5zeL>+|j6nn#*41E#O#OV^5Y zfV`(Op&aHto@}q??0bP)aP_nR+e9~B*_0-6Iw36K{`8j4f*nQe@VgP#BUejJvp3s7 zD${v}StAZ8=THEZ_T?(+$+0a)Q1CHYk1T~Hy+G%_8&w}C$Yks<3$YX!n5j&2)qmh0 z#dVW1$1#$mDx^_`{dUNbh(Ch%AMO4clT+{S&g zpQ`#kVK46d=9!z9X`uRW>yy0|saNY%*_?*H(TW;M>%d+6iQAg*RhGXu4+Qm7md|tW zm1BO#I?e4LhO1+v8ny(42cn11VVk8vz%~a zZH_V|K#jghI@Peo(=rN8!suS;2yS!mopZZds^YTp zS?ML#v-Of0z<3>U{c>YVb#CTJrq|kq7ur=>3p$R@Sv8DPV-v3UEMT(7_b|Jo1LhH- z;6QX}Y#n?ME!rkM$zppZ)M5n_X`iljke&}FYPh(V>P045+Udo;kOBa^b^u{(VQEv^ zP5b7*qEc1l>n0ZA;rl2mX?5m;6wKP!6Zevptc0lMalqHD-8?y9nXN)gAJl#%5H*@x z`Xgz+*O_kDRQ77sYoR~*3R3zbNS2`W;OJ>wB|mGx6eRDqvu0)e?2D#PRW`4}6ih`k6qPQ3i4-f9(=2 z#=1x0nQ-cNLSl=~^{0Kqh;K({xQqqc#FrXUS&I=Rra94=$*n#8Njr1@bk=okI*NG@ z+2|_LTIHXVF(vc)k?VNhG$bBE1th5?eT%Bdwrg#7S0ql=>CM<4Z*{wqNbsxyUW4Jb&p#_R7_k#QcCH8vWlu2 zO#P{juAaVup^>GPwap7#J9{^G4^J=eS3aSy!@?sX-$W%Qy-Q9>eV>;8A-|yTV^MKQ zY0c-_y84DMjZI$>UEMvsec!&1jZaMen3|rMMJ}(buB~ruZfzeP9iN<@ouhtV{Gkg3 zVE$Fs?fI|5{!SO!tu72KEKDr$AG$yoUbluxhK0={h(oTR4Sw!&hgB#TmqIZiueuYD zP58+HrG@J#J{7wN^6udu(*C0CpA#1He^T~u!v0;?EI^0}x*a@BGC&?Uzu@{1g#Z7w zq7wUA$5_V(x{rBqOH2vn#BJ+08l;aw7C6p$z13yOT~`mndET_JP>dEN$VWaSjLQv? zDQOCYGIFFX^W8B@ULLE9mAg>u*)TSK_pbPq1=dl)T?YSXV9+d^6q!ukowXVh1A&NWf^7NT~TzQgFE)>qH%aM7pma#HQ?v$j@xV}0A zxx_!BxNOVwS_1Fin(*9DP+b7-fjy<%c1@@e`;4ffWt=P* z(Y8F~jz<5BInn&BV_`0NkKp4Tg^dQSKvELJ4~_Aky?1Ux78uY#rxhBwO3P{{1NCP|57B_DDE}f<*aQs( zAqJOrh*Sa`>qIX7e)*)NZuE}a(`5>V?n3Fsj4HE=`&}qwuj?jKc5AFdblvEE#7MxQ zokbaQ9urjE1#`}aY1+7KuA!l!BP(od^{N%G_FsE6=D-d~B1Pt9Pc<^;6_+=xoEpxx zZ}!-Sh)v3$h4mgn4BQYhMeoN1DkoT_pyI5rfbxZQ^bPwp=KA6)H2*(3GpK} zWw;)$I=*hB6|jT35feJ>n0q6eI@98T1{9o#1D9$7Z`5*$v!hn_{;Q|;H2(=NLz!Yt zoZ{P8jyo661QpQ0hmV!tzbrxmdpAPce_4d00p&+f#$-wjeFtUt==w3L`8vwT43971 z{ujUKu^5=L;NSi54(YoWgeR&_(l$oiEA$4kek9$paUV<+zZj>m6yp;BF!d_CL2M4E zuCZGr(LhKe8u-ncmrW9B|9Wm)jyjwH*2Z^u6T3V|0HNNZQ@5Q; zyw0?zbM4c%awH`mawd4@nqT4L@mG)PVaKkf_r7uZ-nU~}sK%G98%aK-C7g1KUs(!% zm?8`9rk)g#N80pTiBg+#kE>tmPCTxT98>WxId=Fdr{gK%ZmYbT{35bYI)M^x@ z`#u|2SkrjF!IRn3Wkov8^UK*MYGhm#SJZ)fT)WQV$GKL)XwnoMP(98i_{+HJ`d&_p z%u8+GtkuuWJvdfhh{{b2WYLk4YH+h7TQvV1-9LHf8`H0H`fxo_Mmg;uO}C_lAkocA z@lL6eR3=7$4Z|PgYL%x1VbzJ7-FIkozcc?<40$}}<5eN6a%4*1W#m`ERu@+yFvG6$ zGV!J+meIaIPuz^xt^&wTL6<=8dd`2)vIH1PmE6SxH>GNP2?!V%0~s zBOV!sn&Gyr$0|ramB5Zfy1K=jcJ?^iPd-QKt7NE+c`Zt0=(RZ2nh#(9j$9=<(|NAr ziO=I2gkS0OjC#3C&XF*{4vIJ1*uj26E7{|-w362ywJt++Z^FH-)$w6k9nZ|_w;P%< zl_=2*ENDPM_6evFr>w}-T+`Ai&_Q(m3yv*Yvf&CEc%{&HWp}hN*XiX1=gqkLWqu8V zn4$O^a55z1G6iJ!e9^a+xd7stHjG;GVhc)FM}hX!hrP$S?+E5;fcRp4zwQzK=!%S7fl<-X&{IVM@+ zb%1PG6ppx|AG;DRx|^K_XMl2-CxVW@LwnX83r=@-wBZG&_EKVLnZFy%?UDnxGTFT4 zUuUab*$+oLt&X)w7uySJP&~48Jl;zY+6kkNWEM(#EBGTwq_`Y{YYvyHig@WE`)sD5 zA?0xBld=Ij8Lvxr- zymKdlaOrXcdzSlS5xqu{dUP?YC=q<2V=S)Px7BL+YO7Bco^dmra}&jpj|Tjv(ZFF8 zu(MgIbSW2j!Id6=eQb#adU!sL=i8REsI(=bg3$m(=;b_T<21$%R0})(z&tXY@f@K^ zr*H^HxCG`7bIdEwcxxG4bzJb=#Kvp!ER@#g70qrpd31-J@Q7A)*+^PC#uQZmdLyF! z5OQ13rnU@$G`MTVyYr{>nt5R6YaaEMr^xW6N^jw1y+)+87j+v%`A*AR?;dTq<#2vN zrw0o-r z%!4!rD}7z*tqC#BuHW(X>`AKy5kG`zzSsW+R=Ra-qgR7%Cp1zVpw8_Xjem%bY$GGt zm6Xw4j<}qyEZ-qR10MwsaxTaqVV-iFtiC*^!t!EyUJTfQtu)eWkn>%J01=Qz=MBkt zi!`##SEnXUy3s+Gf33%KI{rPC%nJLGXR(YV<8PF+yYCCNQ-7(+lhJkZJeycgHU_I8 zmEPfeOjDC_UecCIhEl?}k*4j~TCfX{K@)LZ9{gO`UP>}u&*Nw{=hwJO{HGPHnlKxz zgl)-OLLLE3Q(GZhSKCK+SSji7>G_6x8-hA>JkK8=6&ft9?0Zlat$Z=MM1UW}q<)#S zjvG|hh zdhQAM$whI#YKZ?SOxT;F$`;b{0@Oqdm95Ne{v2{961OaiWQRS?r1W5U7kUaAE4odV zSN!~MBOsgjj|q$9no{(3#zI}*$jdOI0ZR(V1-Cu$tE{_C0Ht^io5)2)BZDj^UK+@5 z=U#4091AYSCr5Z((4D2jKWNaavXu-`qRls*4!|cU}p6U(8;aalbnlCReJ5+4)Y5FDnY8H5+0z z`^wAOUJ582*L&~5_M!9vc$z#n=@3-XOx*Lw=wX_tkX3DSOMA}wp+sD?dtkIVtFR10I*1l`G#`dLG zo}V~Pms=+|biyJ?=)`)QxArMV4#u3peu|ltm}xXD^N40G_=NRy0HZRmIdLs^ntFAO zD!wldVewUDg{jlyRK4-J$K<@8Q;_DSmv4L6&XfJ8{Tll^*yCJ`aHARQBlEPO__@zO zTTmv;!={CW9YngvJI_N#{U;MF)pa>e`)q_W(wbTlz%{(w9LHN_mW$6=Y1|djAMb~6 z+V{lgHni`gulgBcWpkj0k%Lt9B@W}TyR3>2wUEGWG_tovAeLJ|5;i#DaQ+GCk+ z&J9{8_*klsmZaPX z^6B9juZh2_w7&jwtDSp0U~g2B#~#h-H$d%|@)?;Gt;5fS-OzpA~W^z1Cw!HFhA`MMb%M<)*gnIVM z1@U;1sm3(&)sKi7(F4NpQztacrGF2+cOih}yA*PL_ez`r_OSBVSZoDG@ zI-zZQdZFf8O)F3V%D79Rf2V9-KC&f{BrNpPIB$jWSwX4G#%IQA#l>Hz7E+{ujMZ%- zKyffsn3v3s@0l1wOj1NSh!PVYKWW~j2;vvn`8KKKOee`$@TM)ygz%z_crw<_x!#;! zBv$&-8&;V68?#eZ;2w0biJcf344{EpWlydPtBaEllB^C-X0gdj#fPdJ?<#>NtYNfU zLsBDP`a%@>ZEjwDFh5xG*}?29%xZ$2(DG70z0y!4jJ?H&%RGa*CfDsJ<%tk#gl*Zzd5*qH&&ALHkwm; zlTGc%8m1lyirHeeREi__%_-5qbhp=4Vl($j0MqHA`E`tb;5RPJnh#N27}Ak!P4y`Y z*7Fp_+EWu`Aw2O1KQgLNO3KmD2+hzZb#=V;spj@%cW5o3$?A!?Lqg4;<3gI%xiAGD zj=uLJcCG@S_6afi}@2eSF#DPv%$4k zS%AmS9}edcwWg2P_&taqn$2GxQyE8FC8Tbuv1?&^5Ivq!F(%;ZvRPi&X{f6w3PGSE znWBQK&zMdJy{B$CvhN>w21zRUT)bQIG@$0mvG~=V>|WnSKT_@#cKR{8$ap>onoX|* z17yg)5RPdgV==Z5_xVL+g^Y_X$G_RpOZywdjNrV8JvC$=*%QeUA&7O-ep9i__wK6W z)2x-#-iOe{-Z;UDsELF1m~5t7SLF9xc4svyn$!G*uHJBRl+W1t1iWW3Fff{pkaWS~ zVcM?*i#i6eG}YF()%(Kxy(^jh9HXp=D?$_Addox&pn=z_2=f#EEqN3+1P$CV7SX~H zzhaf6Lj!qUFf`D?g$7XR6ZLfsH4PfR2CN}iG-}Jx()?*+Yz<|AasZWY-c*-PMDjo< z)vWD_1))&N=!xAb8nE(&bUA~4#tw;#-10ZQ^y`g0dh*?)FEb3N`Pi7iBR)CmNBczH z8C^cyCi4qda#K|v(HqAC0{8P>ARZKf_*_dQy(PIMS_fyraOB{o|b&wT}47B z>OX7ad=mrt!3suo8}bJ=GRkP+!JPTk)D?GKZ&y2Y80#D|ynJxFUu^U@mI!D|pPF>G zi#=O8mVg^$e&#)QdAPhl17!Mir;!@#(_wnLjVj^qNn;&J0y-0$p3kYw1meo{QS zpx_{3vt}rR{w)mVo!X{bKK`$b!c*@Kq*BH3V`<{LCDDi6he{$a9+N!g3Dg{~TtIF6 zlyyz{5;`OBIHcX#$w3mlUBM|Gx3p#MXhUfh_$GUTkwoUY^Wk-M3FFsSe)%^S9i;(y ze||3X1&jt5=S?-P<6)z719Ozg1rV{lXgYzwXV}lZBM@{cjg@xd-%4i@4j)bE z-&YjW+}?dE=KZR>m8b$-+57Gj&+oWIJGg1b`O7o67FIL{+jI`G-~E|b4N~;VIDhc9L$J&4iJ@W z%`?^KSE_(l1%$+ws*PbR<@i@iQ=;Y(vug`wF7H>Y zfxET9RkaH4mBG2Z0+cBU8AzN(Jo{>&^U|!^@2m0USHX38Yx4)%U#p()J#x~|L<3*@ z4ymv2I0PP>9~5(z!2SDz6Ab#bT41(3RN&Kt zfu`>I%#=i9d%D-Dqnf<0X&weS>OtjRlJ(G7Iji;9li;E>o*bZjH8LXCgY5OGcU>8N zr}8ngC{+S9Lzv8Za2OtTVUAeAV8qz3N#8_Gxi_B;xc@VAidBVa}jC70a zQqIO;I;p|Mp^>&nJ@Z26hV0-Zn`-3QX!nHMoH2hNK4LAak(2LRKf{st)_6LwP+Vz* z&b!yli~wKxbJJX+gkvk~{Yx6pIjX zoD>uok+5$Trc427|IPIARwys2yEHMjdn4P%U7oXf4pjSv-dq^%?PMQTMu@c|({{^e zo@xb;ZGW5lFia2D9EgEf*ka~Y2_6V7%V^sXQfqC~MH}@bYOLk(|9q*cH|t7l z%vLWXZ2BXjtb19W#CTh5?Zf4RKp`|hA>?i)zsrL`@}>BS54q!n@9j9OT$`{KHKTUS z-m_uRofbcl1f>wkAsH?-vtM9sCGf9YDB>Z(W3ZJ|W8-WnW3W079xFWP`Rq|Pzhmb@ zS*<}oTywVzS4Ul!;!7v{RpmhAu*4?Mhf1%n*|bRrJp%jlUH9sUSy^5!39=6_(c z4YPYWMfRR_9utX$gO~3bFu>NHK%zLPmI31xYi-%km2!nKXLl^?tRd@s(KL*ghdo3D z{$^Sw@BP93$c?FN5GUn~9XXuXiCRBuQcSacX7@;@?=1d(2`5-O!fXOm_(u)t&rEHA zQiEZMFq3d>N^~Vw?^yX@av={cpRoFM&5+V?!7?mLlo0oKR`_FS%Qh&^dX6tsVNs_q z{=7Bg*umtT6lwRcD3g!P=F#pe2Ys1Zit&7R|)65<&Cpq6}(?*qy;Pt9=gW&Mf4jEFn zvVV^hP*#QA3&ZijP*WIoOF4FLG6DuUWOhOhE2>Hi-G8h+%^WqmAi*4K8GaWxG8Cjk z2!NkIxnmv;l*u z$(!|r2J%u}YJ3W8tVA5@sYKYm{y*BExqVi1I!L@|R@V@+470qH9njaV_3rbYb6q7> zp#7z6uMMUARlf46R>M1*(j;-nb)YM8K(mBB>9p(*s-L0C5Nus%DS||b%U|I<-7Vq1 z&V`|+HE}d#S1;dIvP4Gsqf$}Eikp)IZPdIX#cW}}b+{T|AMMKC z0nQ`$e?a!15RXILoOio`oN%4-PC*0e4<1!e*1Ftx%W3f{k=)flIuQwk^ExhF`gfl+ mcsY5A9ETAOEn$8Qk`HgN{Rf*||AT}7baU+g{vHW>=3fBKG`A4| literal 0 HcmV?d00001 diff --git a/doc/src/Eqs/pair_local_density_energy_implement.tex b/doc/src/Eqs/pair_local_density_energy_implement.tex new file mode 100644 index 0000000000..4b1f1c3df2 --- /dev/null +++ b/doc/src/Eqs/pair_local_density_energy_implement.tex @@ -0,0 +1,9 @@ +\documentclass[12pt]{article} + +\begin{document} + +$$ +U_{LD} = \sum_k U_{LD}^{(k)} = \sum_i \left[ \sum_k a_\alpha^{(k)} F^{(k)} \left(\rho_i^{(k)}\right) \right] +$$ + +\end{document} diff --git a/doc/src/Eqs/pair_local_density_energy_multi.jpg b/doc/src/Eqs/pair_local_density_energy_multi.jpg new file mode 100644 index 0000000000000000000000000000000000000000..df9dbfa5c82b24e491275c21aaac682f065be945 GIT binary patch literal 3464 zcmbW3c|6qL{>MLKhOtE$WyH{oeXAIWY$?lxP$6U~5@EzJ3L!~$QMMK&+bCpT3)vb{ zj4fjwlWd8xWQ=95@4dg@z4vz?zx%k$`#fIfaUSQq-sf?i@AJ=_`HeXR96WD;F#tdy z008X|fH?}B1=!ixplqz{P$-mxgPoHbc7U6UiyO`_zzY)<7DI>%i-?FzC`pSW6;L7~ zGHS94$4{WqXfbJZty9XHN-AjOKP~}raBy&QaSI(dAf$X$FNqg8&N%3}%6VSy>^FefPcna{$7} z%766488!inYfz*QO!%QR}oQDnz!G$HIq-A8~(5ffZPN{30 zJ*RJAXoNX`>9VDj^%WaiXO|nUH{INC;r#sZ0e9{OK8Sc2`6wznCi%(Jl+?8JjAuEo zbMx{G3JFE!6_r)hHMMp1A6whnJ32oRyGZ>5gG0mLM#z+D>i3x+vvczcwAHosjo+K} zEyf>QAOQRqto`{fVE@3yx6j1_fq)^~JsaO{xf0PfT9kj;@!7=>v=YVCm8^@`Z-i zDcaqUqB^rpBD5IbXJLu+9{(s4VDL8@ZrL&c8Y3@=#_6SvlGtOXxwZ_nyTfXkz=s=X z5ZU5tT6hT3Z9;R~cRtC%uE(WIGLj}J_F^jR?VV4^dNLrB6Z3aUCv}wPnj)h`_>0UG zpjUb5pR%ES`Y^ykUs>Hb#n=#8%Y8XTy#)%ncLrh(p4-p$jFOC|UT?V~D0zi2+naD^ zQ*b7erKWbc(PsJ$!Qbn;DeA%iYhIl6#q^Tz+uvV~TzgpnN$LqyY9QptQg#h52YXdi zCkG?8FTV&$A?}EfCQa$?`NWf^?OQ=3S2mncE@IoWUVsPv$B=O;kH+Yv!^i}>tkp|3 zueHqzBWlhM3v0#_p_*VjVXF+p6BotTb&YkiIOBlZYo|p(gVCKA9)QV(3r+J5$Ue`Y zbEHWlEj^`n=pL&KYPYLw`T$mpXD&^n>a#$Pw`U~g+-Wtr`^h1$<{@FTx`pGCe6_CGcT& z>FPjS3^11S&Rg>mB2D;f(R|>;hZ#=s{%TKY9hm0vnFc|4Gf@csJ!T@CC8mI2SlI1e zV_a8NQ#Ym^^ah`Ca`T8~@9d<`L+9PZj;3{y-p~~bH6|d@3&rT;LY--)yHK>)4$PDZ z5LJ71rR?scQu=1uA&J5;D^Fj&WFz>}lMOV;(TenTy1~o+T4*z6l2t3FHdF!~V zvFz8C58CrOc1KFNJd#YFb;M~_--XS*hGK=7z+E#06`JWW z=mthQ^4f-eG-PY=jAmUih@|v|Qm2vHi-C_@jI<2cmu=TAwX84J^i{_8Tv&=3CF`vj z8QK?doZ6fYQ?j@UeY7*~+)_@jX~SJe9@pJWGK77Oy#cU3=>`&?yK!Gx#jFbzi$z|# zm6pZ3-o1N$!S4BD@21i!BIcKk?)nj<=4_t&7@2HdWqSJX&9(^`Y5l#~#frv3?`jjT zQVIQS4Q^rt)a{fLE{>Foe{kGe-JXHw~Uy^Plpg4H~(jc=Y?~(CRp4GVZ6sah}stQ$xIuR7H&qRwlAuJJ3UROMiNiMt4O} zXO-GHMO_pC2ypuwsz2tZTQ+yGyjg9+H1*qw%E_uKl%+lcg zF?rTw~uWDXj zP4m3Dw;f8VQEXJ5SuDFX9QY-#(3smxu@t8NM}bpM2rb!9?qhlsAB@u6q1Fm$mBn6_MTy} zvulT(iSQBEA8Stlnu(fO1cFR9%R5brY3aUK;iQkCfMUn8gpOfNm4JZtcteFyp8Q;z zV~pQ2bWUJ_@iaZ*L=+YJBjxKkM;wDYGraZ~7oFNNRAE-Km?`}(&EbQ&q}-LfxAs=- z^zGMmd#L0fbLd@4B99?u5gts8AIih;-P>5?Mz3b>b!o`0gK5QG)KH2CU0^TLPG=`* zM=oWuBMTrK^z7D4UF$nqlM=myr*35P?3Fdz90R$s&PI@&#lW~;e(x$Va?J2I2qS&Uq2+Zk{E$iJzSP?tvY<-ORE{){0kHC!G-J1 zyx?`pC?OSkXlRu*g^#1$b2FaeB+|z^2c|$~03=bsx49z#{L`!&>f zBq45l{cuhL0u0o>UB?Fyz^QSb)rGa`f|#mrKXV((EBWU6DkTmZ=!$l5z>h?KQU7vk z!C*Y$exW_RXt|x7Qg0ZTnm=q(76AQp0pl*@;(h(@=wm2cHMAvD_{m3xM0L$!d0c=` zfa>_?g@&_4l)#I7$8|X83c+bBsf5B?0gTl#d#>m5#w{M+vhn5>IlQNZ#QfC7{WTG$ zmh>dC-;uEeZboXDq6K`fm#7{p+Wy0RXVuc|I}Y8g#B#FDjO7|c?>cX)#N$s>PTVt5 zM0FjR^}Gj|XVfa9r=qf05Oz@j+Zzl6`z+QLv*c*12HZ&QQ*Bg zbI^PyFeMR6vB^{zT=Gg5)!xR~ZJ%y<9%RFRskO57A!qKv8GNdEQW&e>I>`2`S$Th7 za@UuM5uuq>p>URa7g%lnPm}le4d1_B|Ioy|x@DW+kTYr1jYYl_c!!Dp_<4>`vV&(S hyGg{?P^;4iO6~vv literal 0 HcmV?d00001 diff --git a/doc/src/Eqs/pair_local_density_energy_multi.tex b/doc/src/Eqs/pair_local_density_energy_multi.tex new file mode 100644 index 0000000000..4ca0b7e8b9 --- /dev/null +++ b/doc/src/Eqs/pair_local_density_energy_multi.tex @@ -0,0 +1,9 @@ +\documentclass[12pt]{article} + +\begin{document} + +$$ +U_{LD} = \sum_i a_\alpha F(\rho_i) +$$ + +\end{document} diff --git a/doc/src/Eqs/pair_local_density_indicator_func.jpg b/doc/src/Eqs/pair_local_density_indicator_func.jpg new file mode 100644 index 0000000000000000000000000000000000000000..e038b2884d004d115ae30456c126c2492600665c GIT binary patch literal 9062 zcmdUUWl&trw)P$dXRyE!Tn8s4SaA2?NpQE|?ry<-2!!BnK|+uO*8suYeQ+m%pn=Q# zo^!6%t-9~|>Yg88?|OFcs@>JqPp#Ffdp+xZ_I?$>dm$q)1AssP0D5?U`vpJ}Ku1MI zLq$PHLqo&BK*xj-VneX7AS90na0w|$sVFH($;qi9Ug!L0)vr|!6+!m$Pc6a9{vN!_$ZHPIK)v2)Qr(+ zod`LD5_8e%B&s{0FUL+`Tqe%J7??zliAhN585o(ES-5$g^YZZvNJ>e|$jZsTc=cLc zLsLsz$JEUHjfJI^wTr8pyN9QjcgWk&u<(e;D0tGlvFBYra{_)u8CWjfCYvN0 zn1icyVh~$tRZpPr8Lydk52&}W!p4q%57nb#kj4Qd8*yJN)1nGX*oy{8cR%aM$O|rS zJ@?D6hrZbUNeFU}Lij)4Z;X!=f)W*$Dc0!Ay9lJb#snVW0pL&Mn&x6CglhlC&_FFk zU_VuE7Vs5u&o48*6JjG6dKb_#ht`z91on^W8Y?)ZpITV5KAF>+C!}R1j!aQ?7O_YQ z9R^*!#vfVcX%It!QgmavIKXhsUMIdtB9DmyotaaI9O2juw35!suiN;!sJBejHI(bV zN}&+oDqCcd!#i=V#29uO_CEx?E1=t&IxY7=Xe;B62-TO?hPH|Gh(b`!R)2g{MP!cfiS{&Kk}_a~Q&bY7cRo z23)W(l?f!D55>IrHLt#$Hz+q}d&+EBmAWU&Hi`y4QMr?^`10FNFJNc7O0r7$Qrooh z(xc1K(z`eO=&*obh^B#Hq4@<#G~_U$-p8@11@r&T^?z1HR+Y?K<*kozu1!|fVF^BA zDu_Yia2)K$DQtD4K3AtKY9VUC#ozgIJrd{3N*yAgobhvMQBKQrXr72BW}6!Bt%_2; zW|gEre$ICuU3kNkbm)}jKR@`DEY4s36`T;_+QXqwPpFDUf}r5)e*b0kyA}5r0n#FN z*9GQp72U;?FZ@q>Pr~B&tXD#Lo8Np`E!)WY4;K{M5n+ix=@M!7@?ZV`qM{a!r;Cx>+}hOj3@^)L!|vF(#_w z<~^Q9Dk^F9JK*fo>FVD>tNJ#tu>_eiR&l1H>ud%6Zw<*MS z^~Z(3O}~4g``y&>^qE`{iw;8vSdirX=!p{Gw1R_^zK*3Wr1xEDe(_rc`Opnnzy1Z#+U zfJC7(U4yaD+8uh>R~$e8j>W2n^!7cf_o5uNVap=6HLb)O&3rmp7hfj zuSM20aYScxSUsyj9tx(3o{2U)$JN`Jzy5DXk-G=HUCG3^>-8g^k1V>SHr{(1dx!e;zvZ2z1yO1UzxAr;*OLqKeGUvHv_j5 z{r-DQ$4OU^v`rEGOMx4)35W9`C%NhKhSo91w=R$1TFhs#YQ{Y@Yv3%3srUAY?*cZo^L&sUj{ zXd6^sHlx+PjRbs`9{G(EkdP{B3pBpaGi>G6)YG#(B4LSk8GBl7{+(AwXHIJ*f~HS^BI-^H^bVr zQ;Wg#q&^}cfo-+mEX$-VGgESr37|49y-pmRNwqe3LK;_Mf9y-Y-jr&qSD*c+QL0t9 zPvl@&jzn|`**8C{MOcE4CKQq@l`gZ|!nHyOTr*XA=%z@WI)u?_lf0C-=PlvGj?jvU zI|GfWNfQEU+5*`TPipsX{CMb6j$bvrJk=2c`Go`@$b(e9lMXmNi>$I}g6{#X=CKX+ zXtkPHSQ_-59MrIwF83F;8-*qKO%&^g>02A)9KD{W#_zP#Yd`xGc3^N-u0B7fBmPdo zwSopv@HiQ8&r}^&x_TA3O8_qQL@IVJkr^zvAR%I^02?ad#|_lxGCs@YnC8e6&rBTXk`|Gjn^r?5H_>g z8y`STl{1D2YUK@Z;cyP)_V*I^B5!0%1iq+0ja)KN4HRT*e-bB0(NOhlf*Y~65;lMQ zwy-)&Nj!E#<5U*RJKtT{`~?|e3dw={>yaa%J0cV{jT6mWg<2~w=$pROMlolQAGwJU zZ?{p8q9*@&Db*BQ7bVudv}UekUrjzZR5Y~7MDM1Rooyya;peAzCBIQcla_Wd{dN-T zp)dja)TnYOPNyTMS(bOiHgJn6PCOzM6QoZM5NZlnT3-iEQIEQcqffqx7~$#O(-D+& z`QoK2v&BfGNyi7vz%io4Z%(jpICXD>6(4gue|xk&ry&FqqmYIg^iR%dOWWEre&vYq zs`+H$;4DURTh>91B;QU5N@B14aT&@T%``0=i9GYU`pQT$Gy3R2y!`;g_({M;P#PHy zQ{iGs!OsO{1dW;nB^`-fRLZW^WJ-3u+#knX+2>6%;5Z`ilAGC~lY&m`Ey`NiJQ*CS zXG-Wh+{rOZ12(xwBJlS~<8qCS*M{tMGX=yc#@CmmY+ZuB4uXUz-%e+~k7i@93mrQ$ zX_z?Ym4vx}NetyI*;5N*nLPr*G_g+J>yESC()m>E&9`RTc$8ZctSB-zNSUG32ReJ+ z6vS6p8t%^cKfjF4v7R0sKn>5upx14{%WXwn9kP_<1!^q6hYLddXnn+Lz{-rx|GaF$MYfi>O16*_b>_w8FUB zr$ogcwR9G3NHb;>+1b@FWi!jr8Do5BuczaxjNK4z6qnA|J^ZwzXY$w!h602)is4qT zBglyi-)FdcFLy1bgM@fxiT?F5pceb{wAV0j)k##sPIZVDB0*UKW-Q zmF{Rv%O7!0&GtU7sIWVzfX|Pk=LB=Sje=p82?wsKqS1WB zt+~}d**F~ES8A?*bvK^6LX{wz?3%WfPZXbPxCakqHFu!z6+I{w{q4|G)2v&lXE3k5 zN9yZy{)A=I{%|7q9iWaFvFjTY`Fd8tw4!`U8J!X*_z~-CpXH`v7zO6%theOBxYWT+ z;OtAoBKg8wfw6Jl^z_u&#X;|ye#MNN+jf8G%s4HZWl0qDwGk6B;H_a8!6VPz!jU#D zDyo`s_1rOFL_Xq5{7h{s-UuTHf*WqsaH>ALB^ZyVPu#boE+LzEnOiyjxtS-gINVpz zys#k4Ml8GeU5po;gYEdT+Vpa|0&p20Ks@EYO&3P~_VwVY+cR7DVY+?ApT2hYfQSLr zJ<#6JcDdyGP8IddyK4kVKt1(DKDk$b>4z0zm&|^S`P!YlKt7cSN{UI!t%+~*#Pa8U zl+T$h9J9<^dZ&WpJ~HOBW9;f?VV}BZBMfoGKhByez4#QN9K0=RHhyN&TrWA=|HI36 z<>LG8Ghv(2eNojh+d9^CpVGwXy%oo>brMp3JYKa1xjsG;H0o8SZvgM>Y=uvr$H#Eo zS_wEYMFI(csohDLziHsKtEaoKQyu_G>e>2b>bLRaM%T=Xfwn!h9#Pa4xZ)$UUFZJj z(toJj!ASp*XA&2zr$nc~FiqT}1xNFR;99RyF8^`}8M~A`sEKu)uS_%Icup9M_q~bu z$FJChni!{aWa%$D+8Q@~(rvY`^2RggO2X>TQ!9ir%bmRh5vEy7 zPQ5S2>b~ge%Gr&=t7S?s&cM(ofY);ATGQm|`|x!U))|U|xSdGdgM}o_Y!5s{))iW@ z^=^fbppTsg;qiKf{ia&bv!P#h@dxgmI3jP=n}%RZHuG%!DkkYAYg`3oF(IYY!BTq6M%nU`US+N0e&K0Lffp#cf50#fmI#U2-qm(CT(Qi4 z#BKM8Z0^|BO;CFyjik@L-m;xmY<75>(H=*}+ob+np+tx|M^A6g%0tt(nAO1oYk+N> zl5-X%zKQ%qaOUZnu-=kqsNRmi$z+wYLmh>JvXAFDy#_0}+3zXrT9jkBJYyPQ2o)#F zKPBrVg{V~}Ay4e{vY<(X;D1>^uo?X*WLb~3jyB_)eVJNUQp=elBt=|5DuAPGBk||m zlCw^qa{FZ(Kh2DrFu%Iv%Zcyv%iF%TE@wP_HX>v#Do{^*uJsnDd3k#vv300XNTPSM zn{T_AdL~c9{0{EmmdU6}fJ}tTO1O}DgJ7Pi=Sl;L?bezWd`gM}p!-Q>e5QnLZ)R61 z!|_5w4#Y1iu9+9+!27?v% zTiWJnK)ps{`)RrBCA5?Nbe@vpQ9M74()`|RitVVHJipbCl{RLt^k>)88~&VbS}bk# zD=}XWrmUf95)_SByfyseMcQFcv{5UypU3xyG(TD=T9VncTRhqhoU^eN$jy`&1+YF< zA7^)CrnBT3Qcy-mXSLW^`#pR)d#6?Lf(bl)zJg=WyH16b?^&gnFyP1Xv2Ct~gs6tR zk_IefnsK7yi$B(}_HoCaF1cB^ahp43>8>ES}`>u0}M}Y7}JPb#l#I8 z?zu<2z0TDs1Im4S-CP_4Tr7!jKmL-su%zxRhLeIcDVMTYec`Feaf#CilOO%556SKu z7*LBZ+B|B$Xdh{b%^vI@y}42!J$X(=f@tmyvz(_z#MmT5{m zzI_V`6k4D-k``9eJAATx;F>~6_8#!lxd%?8W~a_1E(%vFzb)iWRf9yfz(?Oud zv%%P=@mSWQu_?hIW^xjAVE`o#L6%+9RdtNb&8M)neoxokiFuZDPb73NB>0 z66O5?s@7D|X&Be3;x);C641Vqkg1k^L(*Q25j!+QJGN zo2M%^!EKd6vgMVrvHjjz>-@;(vE0d<#9UmKjyG}NEqFQRK5#*tsn)?&Uy&1Vslj4| zJgh@62iAGR+1hFgd|1y~yq>(ZE)%Mi$Ur#tAXZK)%l3}ud*&6=n<6R>5hPybj#2rG zStw2-G|eO3@sP#BxMKR2w;rV~+&ZpD5&Ei(gLonE;>5JwTWRw`>n!r7`f0n^;Y?aE z8=uigFggHveh?JMKg3MLA)sjl|PZ>qLk~Bd7WdH)r=X&oPRn0fXQCx0a#)U}7nUV!1Ayx3phX z{o02Bg*7E8w+ia6j$lvm!LLZdG8u8ZHc`rrG=vD&o`UGx^XQahlZmhzfjPS8M8t8O zB@H{Ai@4rrHmppwH&XSX#g;RCT*E&_8HJkQy{9~}g_m4%V_DMG+Ih7;NglsMxt^6T z`nJ36fv_@j0>zLqfu5!{K;>jQ zvCenY$!mJedFM7i!?W7*e0@f#Y0_cs*~;F9il30uH1#ZgkKYtj{9?$p7Wgx{|0BWw zBZ*MQ=c-nBRv?F%T~CzcASL9z$9ZiJ1kP@NXRdJjQ=))BqVGSz+Sx384=^fJ-UELZ zC>v+~CQ$1A>jlbxh@MC!htv(82A0XoXg_I9_+>gs(7qtY=h7Dar-lAw!7OCaTI|V0 z>-5QL-BIP7U>xz@>J6VjpVyOrO`QEpf^4Oa-pqF040j7ySt~BT1TASWl}L_8{3pMv zxQRR_sw`s_baW=e!AjIJrz*4h(q`kUqAIl3w^-D`|OI|~D;bkPx68o;3=lm!JP9Z_*)px^0 z6V+#BWQ?$*RcEhCc;K@-KU4Mbr&1wODffWFEU$t&!xh5*Dk7-C+izUOfMq$pYFFnL zoBe|iv|Tb1&+#-{Rx<3>fmj90rmw#FnpU@WN}Yh!MaX9GuVqQ-bU47uq&c}B=%%E&G%oBi&7WOTd{9NL7U*xJesF*ArCP$n9Yix& zvP3#qrk}j!MI6#~r6u?8X?S-#lljCm$#S!Y!1xT4-(3fCTxxpg;RYWZ2&wx~#U0t} z{8VF_{?t9@rC`yWYMsTib`sMpc`27YRKm{Jl?pFP=7$ z`R#zcqr@Zuab!wy!vDI7|BBT$L#-qa4C^$C$(zYiaZ~(Uka+L<16VF}eq=|r5>Dn% zbGK1?x`RcE3qGeuo9zoxZ^yV%6Ct}%Kj=CiHF4LmpWAV*vnQ@^gvr~9d}qk?HGMhs zh@b^F&(GRKoz)&P!M7vCvF`WuTO*r5Q8FK#k=T`SJF+Psr#s-h_dy~hr);qmGG9N& z{$_e}$SdC<5IZ&hlPWd;Lat&g9hMXq=rXD4_4lCkSNQyIV>AiY7sx71dkt`_b-i>| z>b|~LYj|%wTSdA~ll5V-H|p>q*ge!6A;JbL-5xW+3(76E6SmKhF2sfQ!-P9ov7;BZ z1Y6%V%7$`RP;M;C622FRjuHNi_)zR%cX%QDdDZ9TUgPt^0C$GkQ}*0q*;-uMWiofY z>rI4dc28+QCs$>_=xKStDo^%9JtqezE2?MQ)lXKX(aJ$cw!~WP9ShCZFyx0yt8Fi7 z#;^T2n>T?%1MBBg!xd|%Yb~P6Q%9s*KcLO<73IuvKG5PIIRjZjGqdpiC{3zTK8EW~ zrl_+N{t$tLI2aT2E2Kp*s!1B~a_G27mpM_YPZq9SS-|yUZmdsyAw=EAenpO*Pj}M` z_*h?t%LI#J@dh^YgEX6ClLwmQQXHG$Kln{lM4zb-%kOr=1?SfaF0ElHN8*U5P#OCI zD+YW6sh~(itwAby6cAKJGcFc~R(`N@Kn{~L34O%-B(t9oa9N=(pL9QwwXuUXOX7D2 z5qbm9SYG`5sqv3s{8##X^L(pDyQQV6*chUTMOH9|AFeA&g8=7&8m&VM4=EfB^&sGeE$Mj1b6ScJyH!fWR3!#pHFE zxUAfv$N+A1TxKy$T=(e<9_tSq5(*xHcxD#fV|@Gq$4^K~Ny}gqm6TOf)lTc_8yFfH zo1C?=wX;9x;OKeb;w7Ay_vN7AkkGL3h{*UG2{#jyl2fwo+|AC(&C4$+DJ?61SV5?) zs;eh9G?JQ{TROYCU-pn+z3v?t92y=O9UGsRo%{58eqnKGd1Z5JduR9Ccj_MPCl?3+ z|BiLI{|@#yF8CoA0|WwwK!0+97{U$>hC>*|?Q3uz^8`j|YYWSl~NNsw9@>FRoRmKAv0W z370i%944v@YptGPulq9D^W}p)R(j9n`q{zNbVp#vME1tU+T*!rTuVwVJ%x{{0bgsl z{Gn!rQc=}0W&S!dBgKuI6qVsN)d#;aouLD-xj};;oKfX;fYpM+oAqMawV75JR$R&9j8km8Y-@H^%h0+00w>=EPL-k~y(v;f48IxQ zw>53qU|MLb_e3kys9g}sFH)MuaeByR2e8uT2COVyC{AOYCt9*SlIk9QTVht>*K9^y zpbh;I)_13NbxY5lXTIz>hzM=GB`>zL#mRGQ(}NMXs^|#DsiMb)0!OhVcmonAwr&yStIH5TAlAA_sv|C#Z z64QR$+d7^EiN{;WkEQ_2QYG~v1lK4%n~}up1wq9Ec_4p>IIjeQ{bmv6%IzDV!)Qt|<&N_XB_S^THyts?b z(BX%K)p(LAZ1tPugvCK$6SCUD*2qlyt~KZdP2@&o)Lip>ymHI#dwju1hg8M(dp(ri z#p~;8imwnND`jrVx+-6_MRF|_@3F@SFQ@+y6ZeXb-)GZ7(6&mKsRj2_0I5e)kqb^f zB4@#Q3)!DYX*&DtvX9)KG3@QjoYY~zdB^Xeck0Q7yjxC}de)`fvL<(BQo3=KU`;Qu z*%?-ger8WJ;f(>GFL;#aEwyub&6k+Y)+J^*BI)km>#t9|(qYNrF)b7G{2h)$71jQ5 z-n4!2q{c5UAuuJE^-K4!HEo}Ms(OvQ!1X{k%BKE~WKXL^O!KkCh4AekpETSKVlAN_ z8il5A*f2IY3aW2oMFXToRwz;f#*)eKSFpD;Oz+J^b`70w@{-b4z79D!D7aXpqJ@x3 z3Lk;ljw)IF2K0v8$N{fzOZB8&%cDS*@G)p(!e=>7q|QW{(0$dZB_=>qH>Ft4-cBI8 zyfK%}de59&&)LLaEDn_BZ|v5tc_xyin(g!13-0PxR-)j;Ha5c*A9tTx#4tw@Z1wi3 zK^nVdvlt7eR!j3C(#`CZXIht2)p8QTWKBa#rUcK+_ce3oNyWISGGHiR%s$$-2D2*Ln&*o;i6{tHm^YSi&sT-wBLhLSxMgi# zLvcmBU(KHkBhNLk%3f(2CdoMK)dA7kh;2JU5t|=X@0ubV&|SMj2V$-0z$PZ9Q+&3T zb}ab8KEq+pBtI^Y0>OFUR@^d#=a#2{@{*?7B-&^a<||Sid&FD$dsr^+YA)~7wO=tY z-Cd1aTI&^O2Qwfes1utHA7gLsEW2uoj5n?x%e)tnco6OBK1m1og`vXcp-SI2CYS}oNQS~_GNz~W54Iv`b`kJDSTHG=$Ln%{pJagh#m*NR}|TEe9 zRaFXmBcv`?Ea&9I^0|NTNjzO4Wx+h~dSi$cSRreU1%1r+oZAf>))8@6ZFC zpd_DSBg>e&A`p!QLtQI=nj$+s5OqV)@uEw|B{g~BWIl-_3ioUafSGIB?pSzmQUUIK zUG?Q$>rV?toqKTIyu~AHWWPYIY;5<^u>-jJvJQG`vMiL>ilkTIzyP)SK?m}Lb_K(G zEFzbKSEbjHZ8-zXs1iZX{8GjtoC=h%(AZS(D0u7($PvQH7>a*2d^UNAsyOOz)8socZn9`=LieFe!mkmAGa;h0Y(D(&( z=m4mu@GPmN^+^_`Z}m&v>#h9fZwx9btp-EYaIq1Ke5k=MCyDJ^l+Hde9wJQqHdF;X z-TZxBo7b!4@Pqvi7q#Vh`A9^CYwX2#8n$|Qg!5}ARxYM)c!4Sjj-~{2w_N##NvS$x zm|s3mJu!1V-tJ0ae@OK^L+efUM;RYYPZX*-m2FDjzU0Z-d^W4w=Va>kXu17xoBo`p z%=5kjkvbgiT=DG?q*<0cOBFPGB?fe--x8|tM{t^=OigsYEF)etPSdizIU`;xh5aY^IzBY#rT_Zo#;fbFmC_a`v!#hg5z|XRMCWvP-Z~HAdNVpto zZNU`ICtP_TG*TO49^^!9!H=a$^PgI!c+tY#@bZGW~RzBOr__#8?a*h{M{AnqesvRX?H=rR1VXo#7;j{1-L7s zYVu5U2-jzH{<(~bCNZV-t9CvQZtS?=x^opCm(l^8ciG362bq%VzS#LvT$r9Hf*d%r z!$TQhWH|+ZRp(+A*?+^s(#QV^321&C literal 0 HcmV?d00001 diff --git a/doc/src/Eqs/pair_local_density_ld.tex b/doc/src/Eqs/pair_local_density_ld.tex new file mode 100644 index 0000000000..1affa67cd3 --- /dev/null +++ b/doc/src/Eqs/pair_local_density_ld.tex @@ -0,0 +1,10 @@ +\documentclass[12pt]{article} + +\begin{document} + + +$$ +\rho_i = \sum_{j \neq i} \varphi(r_{ij}) +$$ + +\end{document} diff --git a/doc/src/Eqs/pair_local_density_ld_implement.jpg b/doc/src/Eqs/pair_local_density_ld_implement.jpg new file mode 100644 index 0000000000000000000000000000000000000000..e8b98125a2b9f4cb3532792431ceded0b74ce9f4 GIT binary patch literal 4300 zcmb`K2T+qux5uAAAR&a_doR+IBp@J46A&XxkdB~8@6rWCih@WL5Rgy>M7p$4qzg)u zSHKVi=|wsQ1c`v;=6%0A@BQYRJ9F=M=boMa&OWm{JNw(`oU^;+FXVZE`Kq3Q9smLX z0Ekim@>f6yfYQ=JXlbAj2!xIf3WKvV!0GAXJgjU?>;k+(f&#q!{KDc2Qo^EgV*LEl z=g-KUQ$(RqLQ<+1RS@b5NEG7FNkDXTbZ~k&Hv=0#nn_fWef}VU&IV%tFH| zqNqj7hOvW)`miG+Q(i*Fv}?OLj7N#$$h*E#bTCdXZXR9v<={fEB(fx)rQ_;JF-m&vJx#iiwyZ>wwT8@qcy_78p@l71ci z$pr$a|A9rR{{i+dTr3nWDlnKD4Ed7_L={94H4B(VM3I(N3j?w9VG~6}LfN%bUeuUA|Hma!j*ZHK%W8QAfGl-n2#$|yCkhwhsa^@J-;va!Jyz(&H(T6eQn7BXfI#&gBT$(k@te*Ap{EyK3Y5AYx{xxg@;9>b!vGR2@xto zopG~FHHL@S=$X2s;Sw9+-}Y7BaMDoE>A9Fi8;Fth`=&c}r|U~H*L`{-g1c9zns`j{ z6~Le#R7`jR={!HIp}Tv9&~V|tN5@zU-|_vJ{uSHu1$|HtX#LsnY=m0K8NLhG$3T7H zgbAVfs&Fd;E}YeR!`oiIG3&nEJa&vWJ~T25!Sl7mB;cTc;WqOIo4#^xvDFp(xA<=^ zC*zy!S6>zTe2-uc;ezCt1tony+tA54sZ}&*=p5!3=IQ9M!Fnz89^>}LBhR&G*V^rqTU4#R#p{ z2f0u&9!MOpl{lWhmB~pL#P+e=%%boG9kZZn_u#?id*}Opm^^2^f5jv`6YH?Z`TPK@ zY_!|&GhNnA23)OQIo=mMyiTa{R5JZ6iW`5}E7G!;bXoYyT&wCbYj-yHr#Ei-x-(L} z8XQ+TH!}FRZyYZ;*pq>z{^y`^j4nHfVP&R0I_EIcxYCR$l4`(LSjr<=7Vb987%5p1 zU?;<#SfV^Q^bO3Pup{%bc7UgA+2KI-(gmk5B)XmqWSC>ybC66HCnLRKjMER5n0k*V zJs(h)YIzA%;}|lS3*q&skIWGl12Z(D0e@bF3c;2_OShUH)VW#h`VVOUzbrgqK4m0n ze@4TED<~)fsVCCjVAml(Ih~lBdggTV&Tm-FHul{}^;spPokDtPkN4}ztDau_s}WBU z&D3R-=ee)Y8Hd3AKiyO)CIe2S%z`?8rJ3kuMDlmAOYV(%boiVJ2tR6>Crq#(L0KNq ziMeJe7oRKpRgxZSqP6o;^Tf?Yl&~{#15;|lm)$36kaI6GnOLw@R3JF1Dvkx(b=i$T zx*QC6Ay-@mNUkQ+xbR9g{0UwNqsfM`$m1XX)`=eC`(0%6*=bLqF#$4!9FXm8;zTd6 z-RB27i}KogvcXF7*WJ^RjRbd}J>3RD3x;BNP=5jAYn@&24^q7qab~km?kGeDnDY>J9w(AhMKPWYdw`jekqk&x%7nlmv3-5?fMUEH$joz zl6t-=bmg@usD!bgtUsS9O~@0kOSUato9_d78G5-gnz%BiawbNG{X}lcMDN`Td=W7P zg_#_zsunP4gM^5golw_j(nha>$wv&NyIWj={EksOn3*VR6oIBk6LcQZ{tq}wm?d`^WW(dqJPd9|B|1x z85c*+8Nz5xrBZmq>n?`W4xlJ5Nr^n$(>?hM*IPPr7WrKAT$u_>#ZRN!db*Zu$2vG} z-H$B6HDMi^$EVJSon6h4yw>V)hXa87s--?$+j=N6WqbQXeWJ>LKd2>j_?;-cKEbyj zNZi4GwnqI%5NE|a+8ai)a;f$@kagL%-^=#>`t=SZ^;+0C6uO#voz{iADB=CmS$bDB zTtygmVNCW|->!Aw*&ChDV(|W+W~o=+@7sD4Wn>0TykWke9Z*;Q35|X160tMJ!+(>x zazvjawCuL6cmE9cmmG4`*M`z&h0hxHu%4<6#Zn{8zb_JqmtVbO1cdUYiLc z5KGB}7#%7xbd;&ZHchKTgwH{DxtekYs=|Py_=i`ugnN8eZ8E}aLvsrNX>PGIy6eRO zFP($sSAMSW{w5 zNQ=Rk1}$=ynISx?R{06rC-ko6Q*J~7w%DhdBdcMXuM83PA%Q;Vp_xvbFSyoPLJrt0|yo(=R1ebPewHzkEYGk<2g zCTjT+R<`HgXWy<-y8q2e7k@#crQyL&FfuYu8b$Uoqyl z8d6gpiPg$|)c2^B+O6;h#XB!#qvf48jpJMgTAI%r(sM{lD#i{mo(~&MaOTfbyNi3( zGXCK1(H}@xI}d_c6&biF9>{=Xva4kmGNQzRzAoUCC-3LCtNzCY>2p5-G!fc|P zcs3UoN`PV(VmSTCJ`T2qe=xs4;xa16EE!s za)ZN=`R|hH*L>D&Imb|qiSP`wG9DEOQ-hb-hM%>G5v_NuIF^Cx=o{hFc4i<^oj{}+ z2sSm)gj8!*exkDM$X!6A+2G~ET5nxVDsIR!>~)NRfY$T2&HLRK<=FwsDgC!h8Qd*v zh^Hxj0O3m{WK}49d`?x%R{P|pXm zF@HSLW)_jo*6L`i1j+3TuDfTTsTP1E1F*EN@O}9yGB9_847@kniCpkxdq*5*jDM}` zkao@$9DE^m-dTKvwq42ovK)p3&EH6i2s2cR16B__wZ}Br)&rYTi|-X1Pjfw606&I~ z8mK#_mvnt^I5Kle<2Sd}NIlexk=_ptQ~7F$lIE0s`Z4mkf{JH^@|Afmv1%W@{@sf3 zfWYnc*CxrXwj6BYOb;!Sm$uE;fWkOw>hxV);%Vg+XSTcB*c7^4N9o5d&Mx-X3-1b< zxDByHQO%UX!lbw&;AUw7Rh;x+f+w@NytW;6z{O!0roA#b(^B$f{6$havbZl5q?q|v ze8carq=q^-G|X&-Qeid1%k;yJkHuMNUMdIk*r>Sd)h`a3&H$#Nz-IljBNlTsCWAK z8Nx6KiDt~dJBCP)VLz@dvyV^#7%8unvKnNLZ|K+vL}MXWVUbRW!5)*)SGtkdF#4Zd{GZ+Z-)WmEXD%3W>E%k**0Bt52gEicEDCS8yrUIY__n;n^L+%P3wThD O-M>TWf0!FYp8OB0fU_h3 literal 0 HcmV?d00001 diff --git a/doc/src/Eqs/pair_local_density_ld_implement.tex b/doc/src/Eqs/pair_local_density_ld_implement.tex new file mode 100644 index 0000000000..85ee8bad21 --- /dev/null +++ b/doc/src/Eqs/pair_local_density_ld_implement.tex @@ -0,0 +1,10 @@ +\documentstyle[12pt]{article} + +\begin{document} + + +$$ +\rho_i^{(k)} = \sum_j b_\beta^{(k)} \varphi^{(k)} (r_{ij}) +$$ + +\end{document} diff --git a/doc/src/Eqs/pair_local_density_ld_multi.jpg b/doc/src/Eqs/pair_local_density_ld_multi.jpg new file mode 100644 index 0000000000000000000000000000000000000000..feef991d498dca5d2ab0e8fa5ee54b275c7b73d9 GIT binary patch literal 3443 zcmb`J2T;@5y1@S-A%Q@U&_P0%fHVmK1nG!?TojNd%|&UU7wIaPT{?!Q$g(I+6hc{% z1Q580k|iPtLXZ}U6hS~tqV!@ed-u-Ud2im_x%=jQXMShq%=zZb`OTU0ox>hye*pN; zpR+y(fIt8MI%)u$4wwU6P$&$_$pwSKxVgFDyg~?G9v)tC0l{NJC<$pPl!TlvQL7^rJuF~2VY;^yY&<>3`WAjB}TlCqe;9PBOt$pv@; zb6}7hz<~sTksvk&kUrWcC+MF6{3}2lUEZiIZ7b&0~{bQm;(al_ltfm zuBd!e_4rA34e?nMiQL@M`n>H`H|4h;>g(P&!?cn2qhsR}lXLS6iyxPkKdr2?zJA-- z+}hsR-TU1O1c3k0I_m!r`yXD&BQFjJ1Pp=w?giqAJpzn`aLQ^z1x)Q>-VuUwnA==J zW_jg}FS+Hl9GJpaBZuH33fQ?5tl!oCY4)Fq;r~x&|0VXP*CfCT1|1z97zr2y+j~kC z$?*Rt^acfX7~Qvy70;+8+Uw+mS5>e9%R-Z`@OTUP*6K700(2L7NHkqUR(eITf!u1= zHh$e8YA%D+yG4zB(LpXDT+QV>_HIL-HU*zE;)@&pqP)aBmZ582yF#G``xv~=dapHA zy(qP|u?X%k=Enk*(>2R}{M@lL`9(DA-zJq`Sz?$Hn(sIs;f*IeVjD6>NWtZA1h{xxUvG=gC!;LF*#I9Ir5gSoHAOgr$D zT9#)XarkkNB>}8_s>lSCj;ODmrLVa8j+V#ltJPn{RfSpD7aY{)+0&Wdcdo~i&`>_tEb!zqLQJQzyt4xI0M3f3^t=y?8-X ze7n}`WZ?p3Mmh=ciQnVw*c+MF*23v|!Z2UXgD&69k7j)Fym{V?3s@a8Z;gvhzYj4{Y?=t=R?RJ<*Me2a>&P;Pv}@B5pX) zc||DU&U%LP^pYEz}dX&J2$iif2@=-tscq z$XSsfSnq*)%iz+8gXoZj7rd4UI@Bbnd`EH;c%hmN__pOxVj5mOXTWyO_r2WH9bd;A zQU?6mTenLSn!ut!PANmbRZ*>a~w`J-rzU{&v2&0fRQpnEKzOL4TbY2Eq;x^`~Uq@>Wc zd{|0I{RrMJ6pWGNoYW#j-5yJFAUjDoXZfTzHuxZ$V|K%wI zT*{a)_QA;tcCmJetxlGz0P?H=XeP`|&AFiNbmY+^-NW#Hv-Q0$-=H$BHG^tsrw zs_ijt zCoP~jDQ#oz^jM(#;(>7~SmX7*_vimv$R;jOy+^j}4`aRPZ3&z7WsUFS`?j1g^6zublkX(_x zBZv*jMO_fTRhI3TP(RfiT<2cFcfjowGnTehP6W9FA2N+%SxBOeLGJB+W*lKpR7 zFpr;e#il@diGezW8995a4OFJ%H51eWA$t?fBP5#}=k}*vsNbbV=zZV&hbvlh@v~YN zKAdEIf?f!!IjV`vo3n_%+BG-7D&gJcM6u;NmiODCPH@k7v2YMjl2gQ5>&!$7p9`-9 zqtV~0{(KKLZ`jWVNy7sMtGyodyIMlvCb*Br(V~Wfzj_x;K0Q#sPFGgfeh}nNLys}K zzDF@5Ynwk)o^EF{d9u+hbp)$a$2%KpG%2>a+d%d9bgu>rH` zUk^9fz=0ER-IC%aCayp55O#PIy)zoZ1}Mk4aJi%wuM@*vUgxQi&x}71t&Q*bvw>HS zn9_$lF)y}hY=GsM^xucTEHsYxUGS~fcQ#;aUGc8Ya-t$0is*lv>PP*72!-wYJRD!I zJ!A2X^n!0?zT2vaFg&7}q;9Yfu^L}50jQMb&uo4BO>pM&)T65doMdjS@6gXI`3;#L zbI>rON)*-90=TwP%-{4rl$_X}Ltb@JYQ(nds75F&oXaXm=~Y=pIi<1xDpoZCpK_c7Tb4n%-RAFvbO-D_V^wc-Hwl{q9Q|1S|(=cdgX=&cPPXh z&+s)oWwj76Xlfw@x;Gypwv*QFmP$}}qp#-{WfQeXQXM`%$d}9IL`;x`e+tC8xS>oS zC?!9RbzC(tFXcFYq!5V2IpA7Au)Ti$CvbN5LKP6n299m)*BbNQBz_mgvjK;;U+h}% z^oUEioNy#i6kig?Yi%A6661)5&Rg=RhGMBRVntuSp6c$m3^j6+O38_E->?H&2>q{s zeG5-tjrWbV8nV%9?6T9(PlQt&M}isAL2E_PmoweXGPFw?cdhv%=gq{;Z*+G?q}0ck zXU;2T28>$K87jO#ZVLD8C>fPU%-6?rG|jF$n1{N5A=xQq7<0T?W|bj&4Ls*sD{;~k z30Ei1jD4S*u!YMr{G-9-Fr!_v4K6Gi`Yr!$s8cZ)K*5ou_>BD6051Kr%5i7%82P4y z8pJIi5$W)S`S>8-yVGiXVQ1nZ>b;m$$EJRCb6pF1eRT4?i5)&9mT_n@pUi_gH+YE! zsmBrfWbqT`6Tx(GK1yBJy*_^&fOiqEC(hqMA%^3!yxLl6Rd}0U9;b_%Wgtjm1Wu1^ zozLy8F4)6~^=hCZQ|Ye&R&g2PtBnZKUrk6Upl1O43gzYuu`_q^M-`VUu2{E{;Q27C zioVj!pB@rI^9kTSEw%X7+Mr;n__+mOPuplE?P@5x#QSxW465c|LnjO0$}CgbODJ%u O{_`IHyZ@~*d*UDCeI%d& literal 0 HcmV?d00001 diff --git a/doc/src/Eqs/pair_local_density_ld_multi.tex b/doc/src/Eqs/pair_local_density_ld_multi.tex new file mode 100644 index 0000000000..c441288c5d --- /dev/null +++ b/doc/src/Eqs/pair_local_density_ld_multi.tex @@ -0,0 +1,10 @@ +\documentclass[12pt]{article} + +\begin{document} + + +$$ +\rho_i = \sum_{j \neq i} b_\beta \varphi(r_{ij}) +$$ + +\end{document} diff --git a/doc/src/pair_local_density.txt b/doc/src/pair_local_density.txt new file mode 100644 index 0000000000..8cba705664 --- /dev/null +++ b/doc/src/pair_local_density.txt @@ -0,0 +1,207 @@ +"LAMMPS WWW Site"_lws - "LAMMPS Documentation"_ld - "LAMMPS Commands"_lc :c + +:link(lws,http://lammps.sandia.gov) +:link(ld,Manual.html) +:link(lc,Commands_all.html) + +:line + +pair_style local/density command :h3 + +[Syntax:] + +pair_style style arg :pre + +style = {local/density} +arg = name of file containing tabulated values of local density and the potential :ul + +[Examples:] + +pair_style local/density benzene_water.localdensity.table :pre + +pair_style hybrid/overlay table spline 500 local/density +pair_coeff * * local/density benzene_water.localdensity.table :pre + +[Description:] + +The local density (LD) potential is a new potential style that is, in some +sense,a generalization of embedded atom models (EAM). The name "local density +potential" arises from the fact that it assigns an energy to an atom depending +on the number of neighboring atoms of given type around it within a predefined +spherical volume (i.e., within a cutoff). The bottom-up coarse-graining (CG) +literature sugggests that such potentials can be widely useful in capturing +effective multibody forces in a computationally efficient manner so as to +improve the quality of CG models of implicit solvation"(Sanyal1)"_#Sanyal1 and +phase-segregation in liquid mixtures"(Sanyal2)"_#Sanyal2, and provide guidelines +to determine the extent of manybody correlations present in a CG +model."(Rosenberger)"_#Rosenberger The LD potential in LAMMPS is primarily +intended to be used as a corrective potential over traditional pair potentials +in bottom-up CG models, i.e., as a hybrid pair style with +other explicit pair interaction terms (e.g., table spline, Lennard Jones, etc.). +Because the LD potential is not a pair potential per se, it is implemented +simply as a single auxiliary file with all specifications that will be read +upon initialization. + +NOTE: Thus when used as the only interaction in the system, there is no +corresponding pair_coeff command and when used with other pair styles using the +hybrid/overlay option, the corresponding pair_coeff command must be supplied +* * as placeholders for the atomtypes. + +:line + +[System with a single CG atom type:] + +A system of a single atom type (e.g., LJ argon) with a single local density (LD) +potential would have an energy given by: + +:c,image(Eqs/pair_local_density_energy.jpg) + +where rho_i is the LD at atom i and F(rho) is similar in spirit to the +embedding function used in EAM potentials. The LD at atom i is given by the sum + +:c,image(Eqs/pair_local_density_ld.jpg) + +where phi is an indicator function that is one at r=0 and zero beyond a cutoff +distance R2. The choice of the functional form of phi is somewhat arbitrary, +but the following piecewise cubic function has proven sufficiently general: +"(Sanyal1)"_#Sanyal1, "(Sanyal2)"_#Sanyal2 "(Rosenberger)"_#Rosenberger + +:c,image(Eqs/pair_local_density_indicator_func.jpg) + +The constants {c} are chosen so that the indicator function smoothly +interpolates between 1 and 0 between the distances R1 and R2, which are +called the inner and outer cutoffs, respectively. Thus phi satisfies +phi(R1) = 1, phi(R2) = dphi/dr @ (r=R1) = dphi/dr @ (r=R2) = 0. The embedding +function F(rho) may or may not have a closed-form expression. To maintain +generality, it is practically represented with a spline-interpolated table +over a predetermined range of rho. Outside of that range it simply adopts zero +values at the endpoints. + +It can be shown that the total force between two atoms due to the LD potential +takes the form of a pair force, which motivates its designation as a LAMMPS +pair style. Please see "(Sanyal1)"_#Sanyal1 for details of the derivation. + +:line + +[Systems with arbitrary numbers of atom types:] + +The potential is easily generalized to systems involving multiple atom types: + +:c,image(Eqs/pair_local_density_energy_multi.jpg) + +with the LD expressed as + +:c,image(Eqs/pair_local_density_ld_multi.jpg) + +where alpha gives the type of atom i, beta the type of atom j, and the +coefficients a and b filter for atom types as specified by the user. a is +called the central atom filter as it determines to which atoms the +potential applies; a_alpha = 1 if the LD potential applies to atom type alpha +else zero. On the other hand, b is called the neighbor atom filter because it +specifies which atom types to use in the calculation of the LD; b_beta = 1 if +atom type beta contributes to the LD and zero otherwise. + +NOTE: Note that the potentials need not be symmetric with respect to atom types, +which is the reason for two distinct sets of coefficients a and b. An atom type +may contribute to the LD but not the potential, or to the potential but not the +LD. Such decisions are made by the user and should (ideally) be motivated on +physical grounds for the problem at hand. + +:line + +[General form for implementation in LAMMPS:] + +Of course, a system with many atom types may have many different possible LD +potentials, each with their own atom type filters, cutoffs, and embedding +functions. The most general form of this potential as implemented in the +pair_style local/density is: + +:c,image(Eqs/pair_local_density_energy_implement.jpg) + +where, k is an index that spans the (arbitrary) number of applied LD potentials +N_LD. Each LD is calculated as before with: + +:c,image(Eqs/pair_local_density_ld_implement.jpg) + +The superscript on the indicator function phi simply indicates that it is +associated with specific values of the cutoff distances R1(k) and R2(k). In +summary, there may be N_LD distinct LD potentials. With each potential type (k), +one must specify: + +the inner and outer cutoffs as R1 and R2 +the central type filter a(k), where k = 1,2,...N_LD +the neighbor type filter b(k), where k = 1,2,...N_LD +the LD potential function F(k)(rho), typically as a table that is later spline-interpolated :ul + +:line + +[Tabulated input file format:] + +Line 1: comment or blank (ignored) +Line 2: comment or blank (ignored) +Line 3: N_LD N_rho (# of LD potentials and # of tabulated values, single space separated) +Line 4: blank (ignored) +Line 5: R1(k) R2(k) (lower and upper cutoffs, single space separated) +Line 6: central-types (central atom types, single space separated) +Line 7: neighbor-types (neighbor atom types single space separated) +Line 8: rho_min rho_max drho (min, max and diff. in tabulated rho values, single space separated) +Line 9: F(k)(rho_min + 0.drho) +Line 10: F(k)(rho_min + 1.drho) +Line 11: F(k)(rho_min + 2.drho) +............ +Line 9+N_rho: F(k)(rho_min + N_rho . drho) +Line 10+N_rho: blank (ignored) :ul + +Block 2 :ul + +Block 3 :ul + +Block N_LD :ul + +Lines 5 to 9+N_rho constitute the first block. Thus the input file is separated +(by blank lines) into N_LD blocks each representing a separate LD potential and +each specifying its own upper and lower cutoffs, central and neighbor atoms, +and potential. In general, blank lines anywhere are ignored. + +:line + +[Mixing, shift, table, tail correction, restart, info]: +This pair style does not support automatic mixing. For atom type pairs alpha, +beta and alpha != beta, even if LD potentials of type (alpha, alpha) and +(beta, beta) are provided, you will need to explicitly provide LD potential +types (alpha, beta) and (beta, alpha) if need be (Here, the notation (alpha, +beta) means that alpha is the central atom to which the LD potential is applied +and beta is the neighbor atom which contributes to the LD potential on alpha). + +This pair style does not support the "pair_modify"_pair_modify.html +shift, table, and tail options. + +The local/density pair style does not write its information to "binary restart +files"_restart.html, since it is stored in tabulated potential files. +Thus, you need to re-specify the pair_style and pair_coeff commands in +an input script that reads a restart file. + +:line + +[Restrictions:] + +The local/density pair style is a part of the USER-MISC package. It is only +enabled if LAMMPS was built with that package. See the "Build +package"_Build_package.html doc page for more info. + +[Related commands:] + +"pair_coeff"_pair_coeff.html + +[Default:] none + +:line + + +:link(Sanyal1) +[(Sanyal1)] Sanyal and Shell, Journal of Chemical Physics, 2016, 145 (3), 034109. +:link(Sanyal2) +[(Sanyal2)] Sanyal and Shell, Journal of Physical Chemistry B, 122 (21), 5678-5693. + +:link(Rosenberger) +[(Rosenberger)] Rosenberger, Sanyal, Shell and van der Vegt, Journal of Chemical Physics, 2019, 151 (4), 044111. diff --git a/examples/USER/misc/local_density/benzene_water/benzene_water.data b/examples/USER/misc/local_density/benzene_water/benzene_water.data new file mode 100644 index 0000000000..96a969670e --- /dev/null +++ b/examples/USER/misc/local_density/benzene_water/benzene_water.data @@ -0,0 +1,1406 @@ +LAMMPS data file for 380 CG benzene, 1000 CG water particles + + 1380 atoms + 0 bonds + 0 angles + 0 dihedrals + 0 impropers + + 2 atom types + 0 bond types + 0 angle types + 0 dihedral types + 0 improper types + +-1.2865e+01 1.2865e+01 xlo xhi +-1.2865e+01 1.2865e+01 ylo yhi +-6.4829e+01 6.4829e+01 zlo zhi + +Masses + + 1 78.1100 + 2 18.0100 + +Atoms + + 1 1 1 1.13167e+01 1.36833e+00 3.59100e+01 + 2 2 1 -2.54005e+00 -6.77848e+00 6.31800e+01 + 3 3 1 3.45833e+00 2.99833e+00 1.77200e+01 + 4 4 1 -5.29338e+00 -3.98015e+00 1.79183e+01 + 5 5 1 3.53500e+00 1.13833e+01 4.63833e+01 + 6 6 1 7.65167e+00 -6.10150e-01 6.08133e+01 + 7 7 1 -3.04172e+00 -1.08435e+01 1.49817e+01 + 8 8 1 9.06000e+00 -6.93348e+00 4.72967e+01 + 9 9 1 1.24400e+01 1.15750e+01 2.26183e+01 + 10 10 1 1.03467e+01 1.12017e+01 5.86533e+01 + 11 11 1 -4.09672e+00 1.20333e+01 2.08300e+01 + 12 12 1 -3.49338e+00 -6.45682e+00 3.52333e+00 + 13 13 1 -3.49672e+00 -7.83515e+00 1.11433e+01 + 14 14 1 3.23833e+00 1.86500e+00 -5.10695e+01 + 15 15 1 -7.12672e+00 -1.15385e+01 9.44333e+00 + 16 16 1 1.28000e+00 1.09700e+01 -1.65118e+00 + 17 17 1 1.55667e+00 5.65000e-01 3.40117e+01 + 18 18 1 1.18500e+01 7.30667e+00 1.88083e+01 + 19 19 1 -4.35005e+00 7.33833e+00 3.27417e+01 + 20 20 1 -1.12884e+01 1.08583e+01 2.75500e+00 + 21 21 1 3.66167e+00 2.29500e+00 -5.68778e+01 + 22 22 1 5.64667e+00 6.78000e+00 4.53733e+01 + 23 23 1 -9.83384e-01 1.08800e+01 5.10883e+01 + 24 24 1 -1.24467e+01 5.65500e+00 -6.30578e+01 + 25 25 1 -4.58384e-01 -5.32848e+00 1.37250e+01 + 26 26 1 -1.17084e+01 -8.37515e+00 3.66933e+01 + 27 27 1 -1.12351e+01 7.00000e-01 4.80717e+01 + 28 28 1 1.93833e+00 1.73333e+00 1.49667e+00 + 29 29 1 1.50000e-02 5.44000e+00 3.67267e+01 + 30 30 1 8.41000e+00 8.69833e+00 3.12633e+01 + 31 31 1 8.89667e+00 2.18167e+00 -5.41712e+01 + 32 32 1 -1.19317e+01 -1.04301e+01 5.96933e+01 + 33 33 1 -7.92838e+00 6.11000e+00 5.62183e+01 + 34 34 1 2.62500e+00 8.58833e+00 2.83100e+01 + 35 35 1 9.49333e+00 -6.19682e+00 -5.17362e+01 + 36 36 1 5.28833e+00 -1.16185e+01 -4.91667e-01 + 37 37 1 -1.21617e+01 7.89333e+00 5.02417e+01 + 38 38 1 -6.30505e+00 9.31333e+00 -5.45045e+01 + 39 39 1 1.12983e+01 -1.00685e+01 5.51300e+01 + 40 40 1 2.81167e+00 3.13167e+00 4.17517e+01 + 41 41 1 -4.16838e+00 -9.73848e+00 4.89217e+01 + 42 42 1 1.22867e+01 -7.32515e+00 4.27650e+01 + 43 43 1 -7.50672e+00 2.53333e+00 1.66650e+01 + 44 44 1 -1.12217e+01 1.13417e+01 5.47200e+01 + 45 45 1 -9.60172e+00 -9.51682e+00 4.82750e+01 + 46 46 1 -1.18901e+01 -1.20668e+01 3.19283e+01 + 47 47 1 1.00783e+01 1.19033e+01 4.53333e-01 + 48 48 1 3.54167e+00 -6.03848e+00 -5.03478e+01 + 49 49 1 -2.29505e+00 -2.32015e+00 -6.16662e+01 + 50 50 1 7.35000e-01 -1.04018e+01 2.42833e+00 + 51 51 1 2.46616e-01 3.92500e+00 6.83667e+00 + 52 52 1 -1.05717e+01 2.61833e+00 2.64150e+01 + 53 53 1 -3.49838e+00 4.16833e+00 1.78833e+00 + 54 54 1 -2.40672e+00 6.29667e+00 1.09083e+01 + 55 55 1 -7.88838e+00 -5.84682e+00 1.22167e+01 + 56 56 1 1.55500e+00 9.39333e+00 3.31100e+01 + 57 57 1 -1.17101e+01 -1.28285e+01 4.31983e+01 + 58 58 1 1.21983e+01 1.27183e+01 -5.94678e+01 + 59 59 1 -7.46667e-01 -4.92182e+00 7.68167e+00 + 60 60 1 2.23667e+00 8.75000e+00 1.86100e+01 + 61 61 1 3.24833e+00 -7.14515e+00 -6.15512e+01 + 62 62 1 -7.86718e-01 6.28500e+00 -5.06795e+01 + 63 63 1 -6.28172e+00 -1.20368e+01 6.18483e+01 + 64 64 1 8.39949e-01 -4.31182e+00 2.17383e+01 + 65 65 1 3.80000e+00 -6.14515e+00 6.23500e+01 + 66 66 1 6.28167e+00 1.08817e+01 3.28833e+00 + 67 67 1 -1.27034e+01 -5.98182e+00 2.27400e+01 + 68 68 1 -1.21101e+01 -6.90182e+00 7.41667e+00 + 69 69 1 -1.03867e+01 -3.20182e+00 1.73550e+01 + 70 70 1 -1.42005e+00 1.09500e+00 3.86350e+01 + 71 71 1 -9.33005e+00 2.74833e+00 5.28317e+01 + 72 72 1 -9.21838e+00 -6.13848e+00 2.62017e+01 + 73 73 1 -1.19451e+01 -2.99015e+00 -5.66378e+01 + 74 74 1 1.75500e+00 1.11067e+01 2.39233e+01 + 75 75 1 1.58333e+00 -2.41848e+00 4.22083e+01 + 76 76 1 -5.46667e-01 -8.76848e+00 2.95750e+01 + 77 77 1 8.46667e+00 3.83000e+00 -5.95028e+01 + 78 78 1 6.73282e-01 -2.40515e+00 -5.34112e+01 + 79 79 1 3.56167e+00 4.83000e+00 2.25267e+01 + 80 80 1 -9.36172e+00 7.33667e+00 5.85500e+00 + 81 81 1 -1.02467e+01 5.32167e+00 4.56667e+01 + 82 82 1 9.01500e+00 -1.23868e+01 3.27317e+01 + 83 83 1 -7.55838e+00 8.65500e+00 3.66283e+01 + 84 84 1 8.31000e+00 1.27917e+01 -5.29962e+01 + 85 85 1 -3.28338e+00 3.13183e-01 2.05767e+01 + 86 86 1 -6.25838e+00 -1.15285e+01 3.60800e+01 + 87 87 1 -6.80172e+00 -2.18483e-01 3.76283e+01 + 88 88 1 -1.17067e+01 3.50000e-01 6.86500e+00 + 89 89 1 -7.09838e+00 1.20850e+01 1.55517e+01 + 90 90 1 -1.00534e+01 1.19750e+01 2.68033e+01 + 91 91 1 1.27950e+01 1.76167e+00 5.73433e+01 + 92 92 1 7.60500e+00 9.70333e+00 2.12967e+01 + 93 93 1 -7.38672e+00 5.61667e-01 -5.88578e+01 + 94 94 1 5.85333e+00 6.97000e+00 3.74850e+01 + 95 95 1 2.45000e+00 -5.00348e+00 2.80667e+00 + 96 96 1 -4.18333e-01 7.94850e-01 2.59500e+01 + 97 97 1 -3.78338e+00 7.33667e+00 5.61667e+00 + 98 98 1 7.72500e+00 1.59500e+00 2.01500e+01 + 99 99 1 8.74500e+00 9.07167e+00 -4.69278e+01 + 100 100 1 -2.94338e+00 2.91333e+00 5.77383e+01 + 101 101 1 -3.24338e+00 -3.33330e-02 -5.61162e+01 + 102 102 1 5.59833e+00 -4.42848e+00 5.76200e+01 + 103 103 1 1.04667e+00 -9.24515e+00 5.10550e+01 + 104 104 1 -4.37672e+00 7.81517e-01 6.34100e+01 + 105 105 1 -1.25034e+01 -6.78848e+00 5.11700e+01 + 106 106 1 2.33330e-02 -4.50182e+00 5.87117e+01 + 107 107 1 -1.24284e+01 1.16067e+01 1.57150e+01 + 108 108 1 1.43495e+00 -9.82848e+00 5.69350e+01 + 109 109 1 1.91333e+00 -5.52848e+00 3.47633e+01 + 110 110 1 2.61616e-01 -6.07848e+00 -5.67595e+01 + 111 111 1 6.13833e+00 -6.87015e+00 3.08283e+01 + 112 112 1 -7.20838e+00 6.06667e+00 -5.00228e+01 + 113 113 1 -7.28005e+00 -1.19602e+01 -5.05812e+01 + 114 114 1 -1.13534e+01 1.22733e+01 -5.41962e+01 + 115 115 1 1.06233e+01 -2.53682e+00 3.90083e+01 + 116 116 1 6.65833e+00 -4.72015e+00 7.56333e+00 + 117 117 1 -6.83005e+00 5.55667e+00 -6.42045e+01 + 118 118 1 -2.36672e+00 -1.22518e+01 -6.48178e+01 + 119 119 1 -5.24838e+00 -1.42667e+00 2.66817e+01 + 120 120 1 2.16167e+00 1.06000e+01 5.53217e+01 + 121 121 1 4.57333e+00 -2.99348e+00 1.17383e+01 + 122 122 1 6.76833e+00 2.61667e-01 4.27167e+01 + 123 123 1 -6.77838e+00 -4.25182e+00 5.03767e+01 + 124 124 1 1.24517e+01 -7.96817e-01 -5.15728e+01 + 125 125 1 2.84333e+00 -5.85182e+00 2.58333e+01 + 126 126 1 8.41667e+00 -9.71848e+00 3.96833e+01 + 127 127 1 6.57667e+00 -7.96515e+00 1.33400e+01 + 128 128 1 1.09900e+01 -4.06182e+00 5.68800e+01 + 129 129 1 -5.07838e+00 7.13667e+00 -1.98528e+01 + 130 130 1 2.58333e-01 -1.07068e+01 4.64467e+01 + 131 131 1 -8.13338e+00 -8.46817e-01 2.22617e+01 + 132 132 1 2.53167e+00 8.81167e+00 4.19650e+01 + 133 133 1 6.13333e+00 -9.78483e-01 2.48083e+01 + 134 134 1 7.60833e+00 -1.13718e+01 4.97700e+01 + 135 135 1 -6.00338e+00 4.18667e+00 4.08367e+01 + 136 136 1 -6.24505e+00 1.27683e+01 3.12800e+01 + 137 137 1 -1.03751e+01 9.64167e+00 1.05033e+01 + 138 138 1 1.03583e+01 -6.16015e+00 6.28883e+01 + 139 139 1 3.58167e+00 -1.01085e+01 -5.40362e+01 + 140 140 1 -9.88005e+00 8.06667e-01 -4.82545e+01 + 141 141 1 -2.32672e+00 -3.64682e+00 -7.49513e-01 + 142 142 1 -4.98333e-01 -2.78515e+00 2.95483e+01 + 143 143 1 1.14167e+00 6.22000e+00 5.85350e+01 + 144 144 1 -2.03505e+00 -8.84015e+00 1.96617e+01 + 145 145 1 1.10817e+01 -1.26682e+00 2.30250e+01 + 146 146 1 1.01333e+00 -1.09348e+00 1.69400e+01 + 147 147 1 -2.07505e+00 6.90667e+00 4.10650e+01 + 148 148 1 7.50500e+00 -6.81682e+00 3.53917e+01 + 149 149 1 3.66833e+00 -9.79515e+00 7.41500e+00 + 150 150 1 7.56333e+00 4.77333e+00 1.54983e+01 + 151 151 1 6.31333e+00 -1.07802e+01 -5.85278e+01 + 152 152 1 1.09167e+01 1.04850e+01 2.72550e+01 + 153 153 1 3.46667e+00 3.47500e+00 6.29217e+01 + 154 154 1 3.94167e+00 -6.31817e-01 6.43667e+00 + 155 155 1 -4.56338e+00 6.62833e+00 4.51317e+01 + 156 156 1 -1.03467e+01 -1.58015e+00 1.18817e+01 + 157 157 1 -2.38005e+00 -2.67515e+00 3.45367e+01 + 158 158 1 -3.91718e-01 4.89833e+00 3.10600e+01 + 159 159 1 -6.46338e+00 4.46500e+00 2.95883e+01 + 160 160 1 -9.10672e+00 -9.11682e+00 5.45550e+01 + 161 161 1 9.00333e+00 9.02167e+00 -4.21951e+00 + 162 162 1 -2.01338e+00 4.48667e+00 6.29967e+01 + 163 163 1 -1.19851e+01 -1.00935e+01 -6.46545e+01 + 164 164 1 -3.26505e+00 -5.20848e+00 3.97233e+01 + 165 165 1 -7.88384e-01 1.18817e+01 -5.17195e+01 + 166 166 1 -1.05584e+01 4.20167e+00 3.65000e+01 + 167 167 1 6.73667e+00 -5.37182e+00 2.17150e+01 + 168 168 1 9.24000e+00 -1.05015e+00 4.80400e+01 + 169 169 1 3.44833e+00 -6.55848e+00 1.72233e+01 + 170 170 1 1.13383e+01 3.78333e+00 9.67500e+00 + 171 171 1 -1.25551e+01 -1.10935e+01 5.13333e+00 + 172 172 1 2.19500e+00 -6.97348e+00 4.04667e+01 + 173 173 1 -1.27333e+00 -1.10385e+01 2.53350e+01 + 174 174 1 5.52167e+00 -1.32515e+00 3.14533e+01 + 175 175 1 8.07667e+00 -1.83348e+00 -5.80478e+01 + 176 176 1 8.67333e+00 -1.02018e+01 2.00083e+01 + 177 177 1 -1.59000e+00 5.92833e+00 2.66067e+01 + 178 178 1 -6.14838e+00 -1.06667e-01 3.13567e+01 + 179 179 1 -8.64505e+00 4.73500e+00 1.10800e+01 + 180 180 1 -8.68384e-01 1.22800e+01 5.99517e+01 + 181 181 1 -1.03967e+01 -2.55682e+00 2.96850e+01 + 182 182 1 -1.17784e+01 3.15167e+00 1.99750e+01 + 183 183 1 -8.21005e+00 -1.00568e+01 4.05383e+01 + 184 184 1 7.79000e+00 -9.15348e+00 3.68833e+00 + 185 185 1 7.55333e+00 -9.54182e+00 5.98867e+01 + 186 186 1 -1.11672e+00 1.51333e+00 4.74200e+01 + 187 187 1 -1.04284e+01 3.73000e+00 -1.90951e+00 + 188 188 1 -9.98672e+00 7.42333e+00 -5.88145e+01 + 189 189 1 1.14917e+01 1.69333e+00 5.24250e+01 + 190 190 1 9.18000e+00 4.07500e+00 4.02733e+01 + 191 191 1 -1.01167e+01 -4.44015e+00 4.04817e+01 + 192 192 1 2.08500e+00 -1.47182e+00 -5.95578e+01 + 193 193 1 1.17050e+01 6.66000e+00 1.31600e+01 + 194 194 1 -4.07172e+00 -1.16768e+01 5.46117e+01 + 195 195 1 -2.48838e+00 1.06033e+01 3.61717e+01 + 196 196 1 -1.08584e+01 -2.80848e+00 5.31700e+01 + 197 197 1 1.16333e+00 -1.16735e+01 -5.79945e+01 + 198 198 1 8.07000e+00 1.03083e+01 1.65617e+01 + 199 199 1 -1.09384e+01 7.82167e+00 3.11617e+01 + 200 200 1 -6.49172e+00 1.09500e+01 4.12067e+01 + 201 201 1 1.09100e+01 -1.15500e+00 2.98300e+01 + 202 202 1 2.23833e+00 -1.12552e+01 6.28117e+01 + 203 203 1 4.25667e+00 -1.13168e+01 3.41067e+01 + 204 204 1 -6.55838e+00 4.17000e+00 2.22950e+01 + 205 205 1 -1.22117e+01 -1.14485e+01 1.06617e+01 + 206 206 1 -9.55838e+00 9.14333e+00 6.09967e+01 + 207 207 1 1.19483e+01 1.00883e+01 6.40100e+01 + 208 208 1 9.67500e+00 -1.13501e+01 1.50117e+01 + 209 209 1 -2.24338e+00 9.01833e+00 1.57817e+01 + 210 210 1 9.67333e+00 1.06200e+01 8.67167e+00 + 211 211 1 5.55167e+00 7.27167e+00 -5.70878e+01 + 212 212 1 4.45500e+00 7.97833e+00 5.08950e+01 + 213 213 1 -6.90505e+00 -1.01318e+01 2.52033e+01 + 214 214 1 -1.36338e+00 -9.39848e+00 3.53433e+01 + 215 215 1 -1.05901e+01 4.32500e+00 -5.29012e+01 + 216 216 1 1.24717e+01 2.32833e+00 1.88667e+00 + 217 217 1 -3.94505e+00 8.05167e+00 6.02567e+01 + 218 218 1 1.28167e+01 4.57667e+00 6.12767e+01 + 219 219 1 -4.95172e+00 -5.78348e+00 2.97567e+01 + 220 220 1 1.25833e+00 1.00850e+01 6.88667e+00 + 221 221 1 -8.97338e+00 -7.86348e+00 3.21150e+01 + 222 222 1 7.88667e+00 5.52000e+00 7.05000e-01 + 223 223 1 1.27983e+01 8.15167e+00 -5.09212e+01 + 224 224 1 3.83333e+00 6.09167e+00 -4.79295e+01 + 225 225 1 -1.11667e-01 -4.16817e-01 1.03400e+01 + 226 226 1 1.07550e+01 7.84333e+00 3.53817e+01 + 227 227 1 -2.76838e+00 -6.56515e+00 5.41733e+01 + 228 228 1 8.26667e+00 9.40833e+00 -6.14178e+01 + 229 229 1 -7.21172e+00 1.13300e+01 5.11817e+01 + 230 230 1 -8.28838e+00 1.19667e+00 5.89717e+01 + 231 231 1 -2.09672e+00 -8.67682e+00 -5.22595e+01 + 232 232 1 -5.16838e+00 3.45000e+00 3.51083e+01 + 233 233 1 -5.17505e+00 4.76833e+00 -5.53045e+01 + 234 234 1 4.43167e+00 -4.74015e+00 4.74850e+01 + 235 235 1 3.95167e+00 -7.18170e-02 -2.84178e+01 + 236 236 1 3.85000e+00 3.06667e+00 2.82967e+01 + 237 237 1 -1.09784e+01 -2.53015e+00 3.50133e+01 + 238 238 1 3.62500e+00 6.34000e+00 -6.19212e+01 + 239 239 1 -1.06184e+01 -8.57348e+00 -5.71662e+01 + 240 240 1 6.00000e-01 -1.13335e+01 1.06100e+01 + 241 241 1 -8.44838e+00 7.62333e+00 1.64667e+01 + 242 242 1 -9.15672e+00 1.01167e+01 -6.37628e+01 + 243 243 1 -1.06505e+00 -2.52182e+00 -4.86678e+01 + 244 244 1 5.72833e+00 -5.72682e+00 -5.63145e+01 + 245 245 1 -6.58338e+00 -5.25015e+00 -5.87128e+01 + 246 246 1 7.71333e+00 -1.10068e+01 2.48433e+01 + 247 247 1 -2.44505e+00 1.11683e+01 4.52900e+01 + 248 248 1 -5.54172e+00 1.11900e+01 -2.25618e+00 + 249 249 1 1.17017e+01 5.46333e+00 2.39833e+01 + 250 250 1 -1.59500e+00 3.05167e+00 -6.08212e+01 + 251 251 1 7.33333e-01 8.61667e+00 6.36383e+01 + 252 252 1 2.23833e+00 3.36517e-01 5.79667e+01 + 253 253 1 -5.28172e+00 -4.06515e+00 -5.27795e+01 + 254 254 1 5.98333e-01 -7.68515e+00 -3.44951e+00 + 255 255 1 1.06717e+01 8.53167e+00 -5.61395e+01 + 256 256 1 -8.46505e+00 -9.96348e+00 -1.99785e+00 + 257 257 1 5.19333e+00 7.36500e+00 9.51667e+00 + 258 258 1 -5.94338e+00 -1.00101e+01 4.38000e+01 + 259 259 1 -8.62172e+00 -6.77515e+00 1.48167e+00 + 260 260 1 -1.09651e+01 -2.77682e+00 3.29833e+00 + 261 261 1 8.24333e+00 -1.05768e+01 -6.36662e+01 + 262 262 1 6.66833e+00 -1.73682e+00 -5.19778e+01 + 263 263 1 7.96333e+00 4.28167e+00 6.48033e+01 + 264 264 1 4.67000e+00 6.05000e-01 -6.28412e+01 + 265 265 1 3.20833e+00 7.52833e+00 1.41017e+01 + 266 266 1 8.49000e+00 -5.60348e+00 5.22600e+01 + 267 267 1 -6.09338e+00 -1.95682e+00 7.50833e+00 + 268 268 1 7.17167e+00 7.17500e+00 -5.15578e+01 + 269 269 1 -4.20672e+00 9.96333e+00 9.71333e+00 + 270 270 1 1.26950e+01 6.89167e+00 5.61933e+01 + 271 271 1 -4.09672e+00 2.40000e+00 5.24567e+01 + 272 272 1 1.10533e+01 -6.43348e+00 3.18467e+01 + 273 273 1 -8.97838e+00 1.10650e+01 2.09467e+01 + 274 274 1 -1.27505e+00 5.84833e+00 2.05150e+01 + 275 275 1 1.13717e+01 5.53333e-01 -6.22962e+01 + 276 276 1 7.04167e+00 -1.61348e+00 2.27833e+00 + 277 277 1 9.14500e+00 8.91500e+00 4.77283e+01 + 278 278 1 -1.07734e+01 -5.61348e+00 6.09833e+01 + 279 279 1 -9.55005e+00 9.78183e-01 4.21433e+01 + 280 280 1 6.32500e+00 -4.59682e+00 4.25767e+01 + 281 281 1 6.93167e+00 9.66333e+00 6.36833e+01 + 282 282 1 -4.51172e+00 2.25333e+00 8.89667e+00 + 283 283 1 -1.62505e+00 9.82333e+00 -5.69978e+01 + 284 284 1 9.66667e+00 -5.19182e+00 2.66767e+01 + 285 285 1 7.51500e+00 6.41333e+00 5.90400e+01 + 286 286 1 1.17567e+01 -2.47515e+00 4.43750e+01 + 287 287 1 3.52167e+00 2.86517e-01 5.17950e+01 + 288 288 1 2.56500e+00 1.18833e+01 3.76950e+01 + 289 289 1 4.74500e+00 4.52500e+00 5.53550e+01 + 290 290 1 9.29500e+00 1.02767e+01 5.32383e+01 + 291 291 1 9.82333e+00 -6.84182e+00 -6.04762e+01 + 292 292 1 4.22167e+00 -1.27585e+01 -4.91712e+01 + 293 293 1 3.87000e+00 6.36667e-01 4.66350e+01 + 294 294 1 5.22333e+00 -1.01318e+01 4.35450e+01 + 295 295 1 4.66333e+00 2.66167e+00 1.15517e+01 + 296 296 1 7.18500e+00 2.78500e+00 5.46833e+00 + 297 297 1 -1.18451e+01 8.21000e+00 3.99900e+01 + 298 298 1 6.81167e+00 7.91500e+00 2.58367e+01 + 299 299 1 8.34833e+00 9.49000e+00 4.07533e+01 + 300 300 1 -2.28005e+00 1.05200e+01 1.56667e+00 + 301 301 1 -8.17172e+00 1.09267e+01 4.66433e+01 + 302 302 1 -1.25601e+01 2.05667e+00 -5.71462e+01 + 303 303 1 -1.13001e+01 -9.11182e+00 1.54983e+01 + 304 304 1 -1.15301e+01 -4.64348e+00 -6.17728e+01 + 305 305 1 4.30000e+00 -1.12985e+01 2.85467e+01 + 306 306 1 9.61167e+00 3.30667e+00 -4.85445e+01 + 307 307 1 4.86000e+00 1.18850e+01 1.22533e+01 + 308 308 1 -1.09667e+00 1.83330e-02 -1.18012e+01 + 309 309 1 1.00683e+01 4.57333e+00 2.88000e+01 + 310 310 1 3.12833e+00 -1.24468e+01 1.67350e+01 + 311 311 1 3.05833e+00 1.16183e+01 -6.17128e+01 + 312 312 1 -2.86672e+00 -6.10182e+00 2.35583e+01 + 313 313 1 7.53500e+00 2.00000e-02 5.54433e+01 + 314 314 1 -1.41005e+00 1.18017e+01 3.03900e+01 + 315 315 1 -6.77005e+00 -6.68483e-01 1.35049e+00 + 316 316 1 1.15483e+01 -9.90682e+00 2.74800e+01 + 317 317 1 -6.81005e+00 1.46333e+00 4.77233e+01 + 318 318 1 -7.04505e+00 -4.14348e+00 6.47683e+01 + 319 319 1 -4.44172e+00 9.97000e+00 2.53533e+01 + 320 320 1 6.26167e+00 4.66670e-02 3.76633e+01 + 321 321 1 -7.18838e+00 -8.39015e+00 1.86550e+01 + 322 322 1 1.23800e+01 -1.23135e+01 4.93233e+01 + 323 323 1 -6.50510e-02 6.13833e+00 4.72633e+01 + 324 324 1 -1.09534e+01 -5.99682e+00 -5.09095e+01 + 325 325 1 -1.08917e+01 -9.63848e+00 2.19983e+01 + 326 326 1 -1.16505e+00 -1.31000e+00 5.40950e+01 + 327 327 1 8.61500e+00 5.27667e+00 5.23883e+01 + 328 328 1 2.62000e+00 6.57167e+00 2.86167e+00 + 329 329 1 -1.62172e+00 2.99833e+00 1.49850e+01 + 330 330 1 -4.20338e+00 1.43667e+00 -5.05678e+01 + 331 331 1 -1.63338e+00 -8.63483e-01 4.38667e+00 + 332 332 1 -2.99505e+00 -1.15952e+01 5.73833e+00 + 333 333 1 -8.51505e+00 7.22500e+00 2.58650e+01 + 334 334 1 1.00183e+01 -5.50182e+00 1.79333e+01 + 335 335 1 4.59000e+00 1.15700e+01 5.96317e+01 + 336 336 1 1.12150e+01 -4.89348e+00 1.17950e+01 + 337 337 1 -5.72172e+00 6.76500e+00 5.01783e+01 + 338 338 1 -8.14338e+00 3.48833e+00 3.82667e+00 + 339 339 1 -6.27672e+00 -2.42182e+00 5.54567e+01 + 340 340 1 -8.89005e+00 -4.91848e+00 4.48850e+01 + 341 341 1 1.07617e+01 -9.76182e+00 -5.52695e+01 + 342 342 1 -3.48672e+00 8.29833e+00 5.51450e+01 + 343 343 1 -6.81505e+00 7.57167e+00 7.86667e-01 + 344 344 1 3.36833e+00 -4.70015e+00 5.35033e+01 + 345 345 1 1.19017e+01 6.61517e-01 1.58133e+01 + 346 346 1 -6.74005e+00 -1.26752e+01 3.16167e+00 + 347 347 1 -7.87672e+00 1.25567e+01 5.74817e+01 + 348 348 1 -1.48338e+00 -5.62348e+00 4.49317e+01 + 349 349 1 -1.62833e+00 7.82000e+00 -6.08678e+01 + 350 350 1 -9.30005e+00 4.05000e-01 -6.37712e+01 + 351 351 1 -1.15751e+01 1.26117e+01 3.70600e+01 + 352 352 1 6.68167e+00 -1.15435e+01 5.50633e+01 + 353 353 1 -4.12172e+00 -1.37515e+00 4.25467e+01 + 354 354 1 1.13083e+01 6.89167e+00 4.68167e+00 + 355 355 1 -8.20005e+00 -9.47348e+00 -6.21212e+01 + 356 356 1 3.63500e+00 1.00733e+01 -5.40245e+01 + 357 357 1 -2.60005e+00 -8.37848e+00 -6.05162e+01 + 358 358 1 1.25900e+01 -1.51848e+00 6.28550e+01 + 359 359 1 8.73167e+00 -1.04252e+01 9.58833e+00 + 360 360 1 7.08667e+00 -2.11182e+00 1.61733e+01 + 361 361 1 -8.21005e+00 -6.48483e-01 -5.36795e+01 + 362 362 1 -1.16967e+01 2.42333e+00 3.17633e+01 + 363 363 1 6.76167e+00 -3.25015e+00 -6.34778e+01 + 364 364 1 -8.35000e-01 -3.41015e+00 4.92800e+01 + 365 365 1 -5.81838e+00 1.20017e+01 -6.03645e+01 + 366 366 1 9.25167e+00 -1.27385e+01 4.43900e+01 + 367 367 1 3.53667e+00 -1.03485e+01 2.17783e+01 + 368 368 1 -6.36505e+00 -5.73848e+00 3.58900e+01 + 369 369 1 -4.67005e+00 -1.07385e+01 -5.62328e+01 + 370 370 1 5.56000e+00 4.32833e+00 3.27267e+01 + 371 371 1 -4.15005e+00 -7.68182e+00 5.88083e+01 + 372 372 1 9.83833e+00 3.96167e+00 4.64567e+01 + 373 373 1 -6.84005e+00 -7.32182e+00 6.94667e+00 + 374 374 1 -4.53672e+00 -1.13000e+00 1.38617e+01 + 375 375 1 6.95000e-01 -1.69015e+00 6.39450e+01 + 376 376 1 3.63333e-01 5.22833e+00 -5.47112e+01 + 377 377 1 8.84000e+00 -4.84830e-02 1.13333e+01 + 378 378 1 -3.03172e+00 -9.20348e+00 -6.08333e-01 + 379 379 1 4.58333e-01 5.75167e+00 5.28617e+01 + 380 380 1 -2.17005e+00 -1.07718e+01 4.02383e+01 + 381 381 2 -1.02401e+01 -1.19015e+00 -1.80678e+01 + 382 382 2 1.18700e+01 -4.44015e+00 2.02154e-01 + 383 383 2 7.30000e+00 -2.06015e+00 -4.37478e+01 + 384 384 2 9.95000e+00 1.46000e+00 -4.43378e+01 + 385 385 2 -1.18801e+01 -1.24802e+01 -2.76578e+01 + 386 386 2 -6.80051e-01 9.39000e+00 -3.69778e+01 + 387 387 2 -8.28005e+00 2.09850e-01 -1.21578e+01 + 388 388 2 -2.45005e+00 -1.06901e+01 -2.57978e+01 + 389 389 2 -1.05501e+01 1.10200e+01 -3.73578e+01 + 390 390 2 -1.15801e+01 1.18700e+01 -1.38078e+01 + 391 391 2 9.62000e+00 -3.18015e+00 -3.03078e+01 + 392 392 2 8.11000e+00 -4.45015e+00 -4.69678e+01 + 393 393 2 9.05000e+00 1.22100e+01 -3.89378e+01 + 394 394 2 9.60000e-01 3.10000e+00 -4.21785e+00 + 395 395 2 1.08100e+01 4.27000e+00 -2.98378e+01 + 396 396 2 -1.22701e+01 -1.11202e+01 -1.15978e+01 + 397 397 2 -4.00005e+00 -1.15901e+01 -3.85878e+01 + 398 398 2 -8.06005e+00 6.25000e+00 -2.85378e+01 + 399 399 2 8.85000e+00 3.72000e+00 -2.46178e+01 + 400 400 2 7.00000e-01 9.29000e+00 -1.56378e+01 + 401 401 2 1.20200e+01 1.25000e+01 -1.54078e+01 + 402 402 2 5.53000e+00 1.21000e+00 -2.16978e+01 + 403 403 2 -1.03005e+00 -8.76015e+00 -4.32778e+01 + 404 404 2 6.74000e+00 -3.00150e-01 -4.71478e+01 + 405 405 2 6.26000e+00 -4.50150e-01 -1.13078e+01 + 406 406 2 2.20000e+00 -1.15302e+01 -2.55578e+01 + 407 407 2 2.51000e+00 8.13000e+00 -3.50578e+01 + 408 408 2 9.66000e+00 -5.00150e-01 -4.46785e+00 + 409 409 2 -7.00510e-02 -1.03102e+01 -8.19785e+00 + 410 410 2 -5.22005e+00 -2.46015e+00 -3.54878e+01 + 411 411 2 -3.00005e+00 5.00000e-01 -8.86785e+00 + 412 412 2 4.50000e+00 -6.97015e+00 -2.34178e+01 + 413 413 2 7.21000e+00 -2.67015e+00 -9.79785e+00 + 414 414 2 6.64000e+00 7.30000e-01 -1.68478e+01 + 415 415 2 5.07000e+00 -7.89015e+00 -4.75178e+01 + 416 416 2 -9.74005e+00 -6.40015e+00 -4.25378e+01 + 417 417 2 -4.11005e+00 7.84000e+00 -4.61278e+01 + 418 418 2 3.85000e+00 -1.70015e+00 -4.32778e+01 + 419 419 2 5.79000e+00 -2.86015e+00 -4.06785e+00 + 420 420 2 -4.76005e+00 1.16800e+01 -4.70378e+01 + 421 421 2 -6.68005e+00 -5.66015e+00 -2.77785e+00 + 422 422 2 -5.40051e-01 1.46000e+00 -7.06785e+00 + 423 423 2 8.80000e+00 1.26600e+01 -4.33578e+01 + 424 424 2 -4.34005e+00 1.36000e+00 -2.45078e+01 + 425 425 2 3.14000e+00 -7.38015e+00 -6.37785e+00 + 426 426 2 -3.12005e+00 6.33000e+00 -4.18478e+01 + 427 427 2 -5.80051e-01 8.01000e+00 -4.53878e+01 + 428 428 2 5.12000e+00 -2.50015e+00 -1.82578e+01 + 429 429 2 9.03000e+00 -2.18015e+00 -4.62178e+01 + 430 430 2 -2.10051e-01 -8.00015e+00 -4.92778e+01 + 431 431 2 1.15900e+01 -1.53015e+00 -3.57478e+01 + 432 432 2 2.39949e-01 7.50000e+00 -2.59378e+01 + 433 433 2 -1.60005e+00 6.63000e+00 -2.77785e+00 + 434 434 2 -1.25301e+01 -2.96015e+00 -2.55478e+01 + 435 435 2 8.62000e+00 -2.89015e+00 -2.06278e+01 + 436 436 2 4.57000e+00 8.15000e+00 -3.08778e+01 + 437 437 2 -8.50005e+00 1.06900e+01 -2.59678e+01 + 438 438 2 6.05000e+00 9.46000e+00 -7.65785e+00 + 439 439 2 8.38000e+00 -1.12802e+01 -3.71678e+01 + 440 440 2 -9.42005e+00 7.86000e+00 -1.77478e+01 + 441 441 2 -5.09005e+00 4.14000e+00 -4.29678e+01 + 442 442 2 5.73000e+00 -6.57015e+00 -1.60000e-01 + 443 443 2 1.03800e+01 -9.55015e+00 -3.29778e+01 + 444 444 2 8.68000e+00 -3.54015e+00 -3.51478e+01 + 445 445 2 -4.30051e-01 8.66000e+00 -8.42785e+00 + 446 446 2 -9.07005e+00 4.91000e+00 -1.08878e+01 + 447 447 2 -1.86005e+00 3.42000e+00 -2.34778e+01 + 448 448 2 9.43000e+00 -1.23802e+01 -1.31278e+01 + 449 449 2 5.28000e+00 9.97000e+00 -3.92178e+01 + 450 450 2 -4.80051e-01 7.00000e+00 -1.61578e+01 + 451 451 2 4.70000e-01 1.61000e+00 -4.71278e+01 + 452 452 2 1.15100e+01 1.17600e+01 -4.89878e+01 + 453 453 2 -7.41005e+00 -9.70150e-01 -1.63978e+01 + 454 454 2 -1.49005e+00 8.88000e+00 -4.25878e+01 + 455 455 2 -5.37005e+00 -1.14101e+01 -3.46378e+01 + 456 456 2 -1.18701e+01 1.08000e+00 -2.70278e+01 + 457 457 2 -6.47005e+00 -5.11015e+00 -7.43785e+00 + 458 458 2 7.03000e+00 7.11000e+00 -2.72078e+01 + 459 459 2 1.10000e+01 7.53000e+00 -1.49078e+01 + 460 460 2 -1.07005e+00 1.04100e+01 -4.65978e+01 + 461 461 2 -1.15201e+01 -8.59015e+00 -3.35178e+01 + 462 462 2 -5.20005e+00 2.88000e+00 -6.38785e+00 + 463 463 2 5.55000e+00 -5.10015e+00 -2.66078e+01 + 464 464 2 1.27700e+01 -1.09702e+01 -1.42678e+01 + 465 465 2 8.68000e+00 8.71000e+00 -1.45678e+01 + 466 466 2 5.20000e+00 -8.00150e-01 -2.55978e+01 + 467 467 2 1.15700e+01 -9.75015e+00 -5.44785e+00 + 468 468 2 -1.05801e+01 1.11600e+01 -9.07785e+00 + 469 469 2 2.18000e+00 -5.93015e+00 -3.15678e+01 + 470 470 2 4.14000e+00 5.64000e+00 -1.93578e+01 + 471 471 2 -1.13901e+01 9.20000e-01 -3.38078e+01 + 472 472 2 2.72000e+00 1.16400e+01 -7.09785e+00 + 473 473 2 -2.81005e+00 8.78000e+00 -9.77785e+00 + 474 474 2 1.70000e+00 6.18000e+00 -1.81278e+01 + 475 475 2 -5.05005e+00 5.20000e-01 -2.05478e+01 + 476 476 2 -6.93005e+00 -2.13015e+00 -8.39785e+00 + 477 477 2 2.92000e+00 3.99000e+00 -2.49378e+01 + 478 478 2 9.71000e+00 9.98000e+00 -2.88578e+01 + 479 479 2 -1.11001e+01 1.09600e+01 -2.64978e+01 + 480 480 2 9.31000e+00 -7.59015e+00 -1.97378e+01 + 481 481 2 -5.28005e+00 2.27000e+00 -3.52678e+01 + 482 482 2 -7.72005e+00 4.92000e+00 -4.35978e+01 + 483 483 2 -8.05005e+00 -6.37015e+00 -2.84178e+01 + 484 484 2 1.03200e+01 -7.74015e+00 -7.07785e+00 + 485 485 2 -5.72005e+00 -8.61015e+00 -2.02378e+01 + 486 486 2 -6.69005e+00 1.60000e+00 -2.56478e+01 + 487 487 2 -3.87005e+00 1.08500e+01 -2.98078e+01 + 488 488 2 9.28000e+00 -2.47015e+00 -2.45978e+01 + 489 489 2 1.19900e+01 7.50000e+00 -3.40078e+01 + 490 490 2 -5.56005e+00 1.20400e+01 -7.66785e+00 + 491 491 2 1.03900e+01 2.91000e+00 -3.20785e+00 + 492 492 2 1.10000e-01 1.28600e+01 -3.82278e+01 + 493 493 2 -4.63005e+00 -6.61015e+00 -4.37785e+00 + 494 494 2 6.90000e+00 3.45000e+00 -4.07778e+01 + 495 495 2 -6.37005e+00 -2.56015e+00 -4.10678e+01 + 496 496 2 -2.85005e+00 1.10700e+01 -2.23378e+01 + 497 497 2 5.43000e+00 -3.95015e+00 -4.26978e+01 + 498 498 2 -1.01601e+01 -2.33015e+00 -4.94785e+00 + 499 499 2 -2.95005e+00 8.48000e+00 -3.40878e+01 + 500 500 2 -1.22001e+01 7.83000e+00 -4.14878e+01 + 501 501 2 4.71000e+00 1.29000e+00 -4.80378e+01 + 502 502 2 1.17200e+01 -2.11015e+00 -1.28878e+01 + 503 503 2 1.27600e+01 -8.82015e+00 1.56000e+00 + 504 504 2 3.32000e+00 7.90000e-01 -3.13278e+01 + 505 505 2 -1.23901e+01 -1.04802e+01 -1.78678e+01 + 506 506 2 -3.10005e+00 -4.33015e+00 -3.52278e+01 + 507 507 2 2.74000e+00 7.60000e-01 -1.43778e+01 + 508 508 2 7.04000e+00 -1.01001e+01 -1.53678e+01 + 509 509 2 -3.70051e-01 -4.50015e+00 -4.33478e+01 + 510 510 2 -5.64005e+00 -4.24015e+00 -1.01078e+01 + 511 511 2 -5.51005e+00 -5.73015e+00 -2.35878e+01 + 512 512 2 -6.07005e+00 1.19600e+01 -2.83378e+01 + 513 513 2 5.23000e+00 -9.65015e+00 -2.77878e+01 + 514 514 2 -4.86005e+00 -4.43015e+00 -1.38178e+01 + 515 515 2 -9.23005e+00 -7.50015e+00 -3.28178e+01 + 516 516 2 -2.64005e+00 6.85000e+00 -3.89578e+01 + 517 517 2 7.41000e+00 8.35000e+00 -2.18478e+01 + 518 518 2 -1.21801e+01 -3.40150e-01 -2.50785e+00 + 519 519 2 1.04600e+01 -1.03602e+01 -9.28785e+00 + 520 520 2 1.23200e+01 3.38000e+00 -4.49778e+01 + 521 521 2 4.50000e-01 6.30000e+00 -3.54678e+01 + 522 522 2 1.10700e+01 8.86000e+00 -4.16678e+01 + 523 523 2 1.21700e+01 1.13400e+01 -4.44178e+01 + 524 524 2 -1.00301e+01 3.39000e+00 -2.36078e+01 + 525 525 2 -1.20601e+01 7.42000e+00 -4.59378e+01 + 526 526 2 -3.86005e+00 2.49850e-01 -2.71785e+00 + 527 527 2 -9.63005e+00 -2.27015e+00 -9.29785e+00 + 528 528 2 -5.66005e+00 7.33000e+00 -6.95785e+00 + 529 529 2 1.20500e+01 -5.85015e+00 -3.46578e+01 + 530 530 2 1.12900e+01 7.96000e+00 -6.60785e+00 + 531 531 2 1.01000e+00 -1.15201e+01 -1.08678e+01 + 532 532 2 -6.66005e+00 -1.22701e+01 -9.75785e+00 + 533 533 2 -7.33005e+00 -6.88015e+00 -5.25785e+00 + 534 534 2 1.57000e+00 3.16000e+00 -2.94278e+01 + 535 535 2 -1.21901e+01 1.18500e+01 -5.40785e+00 + 536 536 2 -1.19601e+01 9.12000e+00 -1.77378e+01 + 537 537 2 -9.90051e-01 5.90000e+00 -5.75785e+00 + 538 538 2 3.77000e+00 -3.80150e-01 -2.30978e+01 + 539 539 2 1.06000e+01 4.62000e+00 -4.24878e+01 + 540 540 2 -8.17005e+00 1.20000e-01 -7.74785e+00 + 541 541 2 2.22000e+00 -6.10150e-01 -1.80678e+01 + 542 542 2 -1.15201e+01 -8.19015e+00 -1.68478e+01 + 543 543 2 1.26900e+01 3.15000e+00 -8.55785e+00 + 544 544 2 -9.58005e+00 -1.09602e+01 -1.11978e+01 + 545 545 2 -1.23201e+01 -1.27501e+01 -1.30785e+00 + 546 546 2 -3.28005e+00 9.89000e+00 -4.48378e+01 + 547 547 2 7.10000e-01 -3.64015e+00 -1.29778e+01 + 548 548 2 -7.31005e+00 1.25000e+01 -1.33678e+01 + 549 549 2 6.30000e+00 4.32000e+00 -2.75478e+01 + 550 550 2 2.89000e+00 8.11000e+00 -2.19978e+01 + 551 551 2 7.55000e+00 2.34000e+00 -4.32278e+01 + 552 552 2 -1.21701e+01 -1.13501e+01 1.01000e+00 + 553 553 2 -1.27601e+01 3.82000e+00 -2.30478e+01 + 554 554 2 -1.20901e+01 -8.15015e+00 -9.79785e+00 + 555 555 2 -2.96005e+00 -1.25502e+01 -3.39578e+01 + 556 556 2 -9.18005e+00 9.07000e+00 -7.85785e+00 + 557 557 2 -7.59005e+00 8.80000e+00 -1.57878e+01 + 558 558 2 1.06500e+01 1.14900e+01 -2.64178e+01 + 559 559 2 9.34000e+00 1.79000e+00 -7.52785e+00 + 560 560 2 -1.09301e+01 -6.58015e+00 -2.95978e+01 + 561 561 2 2.58000e+00 -8.78015e+00 -4.64478e+01 + 562 562 2 -7.20005e+00 2.79000e+00 -1.08878e+01 + 563 563 2 7.20000e-01 1.09300e+01 -3.50578e+01 + 564 564 2 2.79000e+00 6.91000e+00 -3.93778e+01 + 565 565 2 -8.80051e-01 4.51000e+00 -2.94678e+01 + 566 566 2 -9.72005e+00 1.23400e+01 -4.31578e+01 + 567 567 2 9.10000e+00 1.01200e+01 -2.40378e+01 + 568 568 2 2.03000e+00 -8.77015e+00 -8.25785e+00 + 569 569 2 2.02000e+00 3.47000e+00 -1.71578e+01 + 570 570 2 5.03000e+00 5.90000e-01 -1.65785e+00 + 571 571 2 3.14000e+00 1.23700e+01 -4.44678e+01 + 572 572 2 -8.38005e+00 1.75000e+00 -5.17785e+00 + 573 573 2 -7.30005e+00 -6.94015e+00 -4.39378e+01 + 574 574 2 2.27000e+00 4.98000e+00 -9.04785e+00 + 575 575 2 7.60000e+00 -1.21001e+01 -2.85785e+00 + 576 576 2 1.08000e+01 7.32000e+00 -1.21878e+01 + 577 577 2 1.00700e+01 -9.64015e+00 -4.04978e+01 + 578 578 2 -6.48005e+00 5.91000e+00 -2.47078e+01 + 579 579 2 2.88000e+00 -6.88015e+00 -1.23778e+01 + 580 580 2 9.11000e+00 -5.79015e+00 -5.55785e+00 + 581 581 2 9.63000e+00 6.09000e+00 -2.57578e+01 + 582 582 2 7.96000e+00 3.77000e+00 -1.84178e+01 + 583 583 2 -1.53005e+00 -1.80150e-01 -4.56785e+00 + 584 584 2 -1.02601e+01 -6.04015e+00 -2.00078e+01 + 585 585 2 8.03000e+00 2.93000e+00 -3.03778e+01 + 586 586 2 6.30000e-01 1.79000e+00 -3.18078e+01 + 587 587 2 2.02000e+00 4.07000e+00 -3.35778e+01 + 588 588 2 6.45000e+00 7.77000e+00 -4.37678e+01 + 589 589 2 -2.30000e-01 5.55000e+00 -2.36278e+01 + 590 590 2 4.37000e+00 -4.19015e+00 -2.05278e+01 + 591 591 2 -1.17201e+01 9.47000e+00 -3.29378e+01 + 592 592 2 -9.60005e+00 3.94000e+00 -4.20078e+01 + 593 593 2 -9.29005e+00 7.65000e+00 -3.84378e+01 + 594 594 2 -3.06005e+00 -5.49015e+00 -2.83178e+01 + 595 595 2 -9.15005e+00 1.10500e+01 -1.78278e+01 + 596 596 2 3.24000e+00 5.36000e+00 -1.26178e+01 + 597 597 2 -7.20051e-01 6.48000e+00 -1.36278e+01 + 598 598 2 -6.00051e-01 -1.09201e+01 -1.91378e+01 + 599 599 2 2.52000e+00 4.33000e+00 -4.03778e+01 + 600 600 2 -4.49005e+00 -1.25101e+01 -2.27278e+01 + 601 601 2 7.37000e+00 4.90000e+00 -6.15785e+00 + 602 602 2 -1.19401e+01 7.11000e+00 -2.30278e+01 + 603 603 2 1.08300e+01 8.90000e-01 -3.94978e+01 + 604 604 2 -6.28005e+00 -1.86015e+00 -2.40678e+01 + 605 605 2 3.83000e+00 -9.94015e+00 -9.88785e+00 + 606 606 2 -1.20901e+01 1.07600e+01 -1.99178e+01 + 607 607 2 1.19000e+00 1.22200e+01 -2.84678e+01 + 608 608 2 9.01000e+00 -1.15602e+01 -2.31778e+01 + 609 609 2 3.50000e+00 7.86000e+00 -4.19378e+01 + 610 610 2 2.65000e+00 2.12000e+00 -8.10785e+00 + 611 611 2 -1.04005e+00 3.91000e+00 -4.63778e+01 + 612 612 2 6.18000e+00 4.80000e+00 -2.32078e+01 + 613 613 2 1.14100e+01 -1.01402e+01 -3.58178e+01 + 614 614 2 2.72000e+00 -4.66015e+00 -2.25578e+01 + 615 615 2 8.70000e+00 -5.46015e+00 3.04000e+00 + 616 616 2 2.33000e+00 -1.15701e+01 -1.87178e+01 + 617 617 2 -1.02501e+01 -7.67015e+00 -2.37785e+00 + 618 618 2 -7.88005e+00 5.97000e+00 -1.55678e+01 + 619 619 2 -1.16901e+01 -9.82015e+00 -4.29178e+01 + 620 620 2 -3.32005e+00 9.77000e+00 -4.82378e+01 + 621 621 2 -1.32005e+00 2.96000e+00 -3.71978e+01 + 622 622 2 6.33000e+00 -2.59015e+00 -2.19778e+01 + 623 623 2 -2.20005e+00 -1.19401e+01 -3.66278e+01 + 624 624 2 -1.87005e+00 2.94000e+00 -1.51178e+01 + 625 625 2 -2.30005e+00 5.61000e+00 -3.62678e+01 + 626 626 2 -2.33005e+00 5.10000e-01 -2.79178e+01 + 627 627 2 8.58000e+00 9.27000e+00 -1.83578e+01 + 628 628 2 5.96000e+00 -7.48015e+00 -7.07785e+00 + 629 629 2 9.85000e+00 1.16600e+01 -7.90785e+00 + 630 630 2 8.07000e+00 1.23300e+01 -2.57078e+01 + 631 631 2 -9.99005e+00 1.16300e+01 -1.15878e+01 + 632 632 2 -9.30005e+00 -8.81015e+00 -2.51778e+01 + 633 633 2 8.51000e+00 -8.90015e+00 -3.82878e+01 + 634 634 2 8.00000e-01 7.20000e-01 -4.30378e+01 + 635 635 2 1.22500e+01 1.08000e+01 -3.74878e+01 + 636 636 2 -2.84005e+00 -1.06701e+01 -4.09478e+01 + 637 637 2 -3.89005e+00 4.39000e+00 -4.01078e+01 + 638 638 2 2.29949e-01 -1.09015e+00 -2.49778e+01 + 639 639 2 5.00000e+00 6.95000e+00 -1.04678e+01 + 640 640 2 -1.15701e+01 -1.22902e+01 -7.52785e+00 + 641 641 2 7.02000e+00 -4.20150e-01 -1.96478e+01 + 642 642 2 -1.00301e+01 5.23000e+00 -1.87578e+01 + 643 643 2 -2.97005e+00 -1.23002e+01 -1.86978e+01 + 644 644 2 7.93000e+00 5.27000e+00 -4.37978e+01 + 645 645 2 -5.48005e+00 4.75000e+00 -4.51785e+00 + 646 646 2 -8.82005e+00 1.06000e+00 -2.82778e+01 + 647 647 2 -9.41005e+00 5.16000e+00 -3.96778e+01 + 648 648 2 4.60000e-01 -1.03702e+01 -4.58178e+01 + 649 649 2 6.96000e+00 -9.00000e-02 -3.29778e+01 + 650 650 2 6.64000e+00 -1.47015e+00 -2.11785e+00 + 651 651 2 -5.25005e+00 -2.20015e+00 -2.66878e+01 + 652 652 2 -2.59005e+00 2.66000e+00 -2.61378e+01 + 653 653 2 -9.07005e+00 7.51000e+00 -3.36785e+00 + 654 654 2 -9.16005e+00 -3.34015e+00 -2.84178e+01 + 655 655 2 6.03000e+00 -6.19015e+00 -1.97178e+01 + 656 656 2 1.17400e+01 -1.11302e+01 -3.02778e+01 + 657 657 2 9.60000e-01 -1.71015e+00 -3.95978e+01 + 658 658 2 6.73000e+00 -1.25201e+01 -1.38078e+01 + 659 659 2 7.33000e+00 6.32000e+00 -1.42178e+01 + 660 660 2 -4.75005e+00 -9.13015e+00 -4.77878e+01 + 661 661 2 7.23000e+00 9.68000e+00 -2.90978e+01 + 662 662 2 5.48000e+00 -1.19502e+01 -1.96878e+01 + 663 663 2 -7.24005e+00 3.12000e+00 -8.09785e+00 + 664 664 2 -5.98005e+00 6.25000e+00 -1.35478e+01 + 665 665 2 -1.14301e+01 -1.24401e+01 -3.88078e+01 + 666 666 2 6.07000e+00 1.07900e+01 -9.95785e+00 + 667 667 2 2.61000e+00 3.80000e-01 -4.62878e+01 + 668 668 2 -8.67005e+00 1.40000e-01 -1.99878e+01 + 669 669 2 3.14000e+00 -2.13015e+00 -3.74978e+01 + 670 670 2 -1.11201e+01 -9.32015e+00 -4.72978e+01 + 671 671 2 -9.30005e+00 -3.70015e+00 -1.29478e+01 + 672 672 2 8.48000e+00 -1.10801e+01 -3.40578e+01 + 673 673 2 -8.44005e+00 9.15000e+00 -2.02478e+01 + 674 674 2 2.37000e+00 -2.69015e+00 -2.45878e+01 + 675 675 2 -3.97005e+00 1.09500e+01 -3.52278e+01 + 676 676 2 1.28100e+01 -4.70150e-01 -1.86178e+01 + 677 677 2 9.96000e+00 -5.23015e+00 -2.47878e+01 + 678 678 2 -8.50051e-01 -7.20150e-01 -2.20178e+01 + 679 679 2 9.92000e+00 5.61000e+00 -6.68785e+00 + 680 680 2 2.42000e+00 -7.88015e+00 -1.72078e+01 + 681 681 2 -3.49005e+00 -4.03015e+00 -3.82478e+01 + 682 682 2 -1.22201e+01 -7.25015e+00 -1.34378e+01 + 683 683 2 -6.83005e+00 2.98000e+00 -3.06378e+01 + 684 684 2 -3.34005e+00 7.80000e-01 -3.68078e+01 + 685 685 2 -6.59005e+00 8.55000e+00 -2.74378e+01 + 686 686 2 7.10000e+00 6.20000e+00 -3.98978e+01 + 687 687 2 -1.70051e-01 -8.45015e+00 -2.37078e+01 + 688 688 2 2.24000e+00 1.20800e+01 -1.55578e+01 + 689 689 2 -8.98005e+00 1.21400e+01 -4.01678e+01 + 690 690 2 8.91000e+00 1.21300e+01 -1.76078e+01 + 691 691 2 -3.01005e+00 2.85000e+00 -3.16785e+00 + 692 692 2 5.26000e+00 9.91000e+00 -2.90785e+00 + 693 693 2 -5.15005e+00 -1.08301e+01 -1.85578e+01 + 694 694 2 -7.97005e+00 8.15000e+00 -5.65785e+00 + 695 695 2 -1.10501e+01 2.84000e+00 -3.79278e+01 + 696 696 2 2.69000e+00 -6.44015e+00 -3.78078e+01 + 697 697 2 5.02000e+00 -1.22202e+01 -2.24478e+01 + 698 698 2 -4.99005e+00 8.94000e+00 -5.03078e+01 + 699 699 2 3.48000e+00 5.17000e+00 -4.26785e+00 + 700 700 2 1.28600e+01 7.50000e+00 -4.42785e+00 + 701 701 2 -3.10005e+00 -7.26015e+00 -2.04078e+01 + 702 702 2 -6.65005e+00 -6.77015e+00 -3.06678e+01 + 703 703 2 7.00000e+00 2.51000e+00 -2.60478e+01 + 704 704 2 1.12400e+01 -1.05402e+01 -4.60678e+01 + 705 705 2 -3.08005e+00 -6.02015e+00 -4.00378e+01 + 706 706 2 -3.04005e+00 1.09400e+01 -1.94078e+01 + 707 707 2 -9.71005e+00 -1.79015e+00 -3.73978e+01 + 708 708 2 -8.50051e-01 -1.10801e+01 -3.25878e+01 + 709 709 2 -4.03005e+00 -1.26402e+01 -1.38178e+01 + 710 710 2 -9.22005e+00 -5.31015e+00 -3.25785e+00 + 711 711 2 -9.44005e+00 8.12000e+00 -1.12078e+01 + 712 712 2 3.47000e+00 9.01000e+00 -3.75778e+01 + 713 713 2 1.04600e+01 1.10000e+01 -1.05078e+01 + 714 714 2 -1.23501e+01 -7.88015e+00 -7.27846e-01 + 715 715 2 1.21100e+01 9.24000e+00 -2.20978e+01 + 716 716 2 -8.80005e+00 -8.25015e+00 -1.71778e+01 + 717 717 2 7.08000e+00 9.73000e+00 -2.56478e+01 + 718 718 2 5.51000e+00 1.11300e+01 -4.16778e+01 + 719 719 2 8.10000e+00 4.03000e+00 -1.57578e+01 + 720 720 2 8.01000e+00 2.00000e-01 -2.65878e+01 + 721 721 2 5.08000e+00 6.98000e+00 -1.56878e+01 + 722 722 2 6.43000e+00 -5.08015e+00 -8.45785e+00 + 723 723 2 1.20000e+01 7.06000e+00 -6.97846e-01 + 724 724 2 1.63000e+00 3.40000e+00 -2.26578e+01 + 725 725 2 1.28600e+01 -6.33015e+00 -2.59578e+01 + 726 726 2 1.27500e+01 -7.20150e-01 -2.30278e+01 + 727 727 2 6.13000e+00 2.62000e+00 -7.27785e+00 + 728 728 2 7.99000e+00 -1.16001e+01 -5.86785e+00 + 729 729 2 -1.70005e+00 3.16000e+00 -3.24778e+01 + 730 730 2 1.94000e+00 4.31000e+00 -3.65778e+01 + 731 731 2 -6.13005e+00 1.44000e+00 -4.29278e+01 + 732 732 2 -3.47005e+00 -6.59015e+00 -4.82478e+01 + 733 733 2 -8.05005e+00 3.96000e+00 -1.98578e+01 + 734 734 2 -1.06901e+01 -4.22015e+00 -4.02678e+01 + 735 735 2 -2.24005e+00 6.01000e+00 -3.25678e+01 + 736 736 2 -8.06005e+00 5.65000e+00 -7.65785e+00 + 737 737 2 -2.80005e+00 -1.05015e+00 -2.41578e+01 + 738 738 2 1.27700e+01 1.20000e+01 -3.05078e+01 + 739 739 2 1.14000e+01 -1.07002e+01 -2.40678e+01 + 740 740 2 -6.30005e+00 -9.66015e+00 -2.26978e+01 + 741 741 2 -1.12101e+01 -1.24015e+00 -4.09378e+01 + 742 742 2 6.13000e+00 -3.27015e+00 -3.65878e+01 + 743 743 2 6.32000e+00 -9.45015e+00 -1.95678e+01 + 744 744 2 -1.60051e-01 -1.15302e+01 -4.05178e+01 + 745 745 2 1.27900e+01 -1.01001e+01 -2.08178e+01 + 746 746 2 1.08400e+01 9.10000e+00 -3.59278e+01 + 747 747 2 -2.06005e+00 1.04300e+01 -5.77785e+00 + 748 748 2 1.62000e+00 1.08300e+01 -3.90078e+01 + 749 749 2 6.25000e+00 4.78000e+00 -3.80785e+00 + 750 750 2 2.81000e+00 1.17800e+01 -1.96678e+01 + 751 751 2 6.04000e+00 -5.27015e+00 -1.68778e+01 + 752 752 2 -6.79005e+00 -1.05701e+01 -7.19785e+00 + 753 753 2 -1.11401e+01 -4.56015e+00 -3.40778e+01 + 754 754 2 -1.18301e+01 2.02000e+00 -1.30578e+01 + 755 755 2 1.23800e+01 -2.53015e+00 -3.33785e+00 + 756 756 2 -8.15005e+00 1.76000e+00 -1.56378e+01 + 757 757 2 -1.11005e+00 6.80000e-01 -4.50278e+01 + 758 758 2 4.73000e+00 5.12000e+00 -4.18278e+01 + 759 759 2 -2.02005e+00 -1.72015e+00 -7.05785e+00 + 760 760 2 1.50000e-01 4.00000e+00 -7.44785e+00 + 761 761 2 1.06000e+01 2.02000e+00 -2.55078e+01 + 762 762 2 7.05000e+00 1.09100e+01 -2.11578e+01 + 763 763 2 -8.35005e+00 1.01400e+01 -2.30678e+01 + 764 764 2 4.99490e-02 8.79000e+00 -1.16078e+01 + 765 765 2 1.17900e+01 2.90000e-01 -9.09785e+00 + 766 766 2 -1.26001e+01 -6.16015e+00 -2.28978e+01 + 767 767 2 1.43000e+00 -3.64015e+00 -8.97785e+00 + 768 768 2 -1.21005e+00 -6.90015e+00 -4.58378e+01 + 769 769 2 -4.04005e+00 9.17000e+00 -3.94178e+01 + 770 770 2 5.08000e+00 1.06300e+01 -4.47878e+01 + 771 771 2 9.87000e+00 -7.72015e+00 -2.37878e+01 + 772 772 2 -7.38005e+00 1.23100e+01 -4.55678e+01 + 773 773 2 2.00000e-01 1.11600e+01 -4.26678e+01 + 774 774 2 -8.37005e+00 8.86000e+00 -3.42478e+01 + 775 775 2 6.17000e+00 -3.24015e+00 -2.49178e+01 + 776 776 2 1.36000e+00 -1.21402e+01 -5.64785e+00 + 777 777 2 3.67000e+00 -7.73015e+00 1.27000e+00 + 778 778 2 -9.19005e+00 1.09100e+01 -3.24578e+01 + 779 779 2 -2.78005e+00 8.95000e+00 -1.60078e+01 + 780 780 2 -8.90051e-01 -1.44015e+00 -3.71478e+01 + 781 781 2 -1.30005e+00 -1.03015e+00 -4.21178e+01 + 782 782 2 -1.23701e+01 5.71000e+00 -3.97578e+01 + 783 783 2 8.25000e+00 1.50000e+00 -1.45785e+00 + 784 784 2 -9.14005e+00 -1.08702e+01 -3.91478e+01 + 785 785 2 1.04300e+01 -1.23902e+01 -1.96978e+01 + 786 786 2 -4.73005e+00 4.30000e+00 -2.30178e+01 + 787 787 2 -2.74005e+00 -1.05001e+01 -1.26378e+01 + 788 788 2 7.75000e+00 -7.46015e+00 -4.72978e+01 + 789 789 2 -3.03005e+00 -7.99015e+00 -2.59178e+01 + 790 790 2 3.84000e+00 -4.20150e-01 -8.67785e+00 + 791 791 2 1.26400e+01 -3.81015e+00 -2.07378e+01 + 792 792 2 4.72000e+00 6.90000e+00 -3.37778e+01 + 793 793 2 -7.79005e+00 -3.59015e+00 -3.57778e+01 + 794 794 2 1.26300e+01 -1.01015e+00 -2.79678e+01 + 795 795 2 9.70000e+00 -1.19702e+01 -4.81878e+01 + 796 796 2 -1.00701e+01 -7.60015e+00 -3.69478e+01 + 797 797 2 -9.60051e-01 -8.36015e+00 -1.45878e+01 + 798 798 2 -8.08005e+00 -9.04015e+00 -4.69378e+01 + 799 799 2 1.27100e+01 5.83000e+00 -4.38678e+01 + 800 800 2 -4.50051e-01 -8.05015e+00 -2.09678e+01 + 801 801 2 3.01000e+00 1.26200e+01 -3.05578e+01 + 802 802 2 6.30000e+00 -1.17202e+01 -9.99785e+00 + 803 803 2 1.25500e+01 -6.49015e+00 -3.19785e+00 + 804 804 2 -2.21005e+00 -2.20015e+00 -1.54978e+01 + 805 805 2 -9.43005e+00 1.25500e+01 -2.88778e+01 + 806 806 2 3.69000e+00 1.01000e+00 -4.30178e+01 + 807 807 2 -4.56005e+00 -4.40015e+00 -4.19378e+01 + 808 808 2 -7.98005e+00 -9.66015e+00 -1.30278e+01 + 809 809 2 -7.92005e+00 -2.68015e+00 -4.48278e+01 + 810 810 2 -1.53005e+00 1.20400e+01 -2.99278e+01 + 811 811 2 -4.38005e+00 4.80000e+00 -2.86878e+01 + 812 812 2 2.96000e+00 -1.24502e+01 -3.46578e+01 + 813 813 2 -3.59005e+00 -4.98015e+00 -3.22878e+01 + 814 814 2 -5.10000e-05 -9.81015e+00 -3.02778e+01 + 815 815 2 4.00000e-01 7.06000e+00 -4.14878e+01 + 816 816 2 2.73000e+00 -9.17015e+00 -3.83278e+01 + 817 817 2 -6.80051e-01 -1.11102e+01 -1.42478e+01 + 818 818 2 1.95000e+00 1.11100e+01 -1.10478e+01 + 819 819 2 -1.17701e+01 -1.13201e+01 -3.29378e+01 + 820 820 2 -7.46005e+00 8.15000e+00 -4.11278e+01 + 821 821 2 1.14600e+01 2.16000e+00 -2.81678e+01 + 822 822 2 1.06400e+01 7.01000e+00 -3.76678e+01 + 823 823 2 6.58000e+00 -8.35015e+00 -9.55785e+00 + 824 824 2 1.15300e+01 -3.76015e+00 -3.27978e+01 + 825 825 2 -1.14101e+01 8.67000e+00 -3.55278e+01 + 826 826 2 7.66000e+00 -6.75015e+00 -3.67178e+01 + 827 827 2 2.67000e+00 -4.84015e+00 -2.62978e+01 + 828 828 2 1.05300e+01 -3.00015e+00 -5.10785e+00 + 829 829 2 -6.91005e+00 -1.27002e+01 -5.49785e+00 + 830 830 2 9.65000e+00 -2.01015e+00 -2.75178e+01 + 831 831 2 -6.01005e+00 1.04800e+01 -1.92878e+01 + 832 832 2 -1.00000e-02 -6.29015e+00 -3.64778e+01 + 833 833 2 -8.67005e+00 8.78000e+00 -4.62278e+01 + 834 834 2 1.14000e+01 1.12000e+01 -4.01878e+01 + 835 835 2 1.03300e+01 1.23000e+00 -1.58678e+01 + 836 836 2 -4.48005e+00 1.05000e+01 -4.18278e+01 + 837 837 2 9.81000e+00 7.99000e+00 -2.07478e+01 + 838 838 2 -3.68005e+00 3.80000e-01 -4.32378e+01 + 839 839 2 -4.05005e+00 -7.78015e+00 -3.11778e+01 + 840 840 2 8.21000e+00 4.10000e+00 -1.10478e+01 + 841 841 2 -1.25501e+01 -6.83015e+00 -3.90178e+01 + 842 842 2 9.30000e+00 7.50000e-01 -2.89078e+01 + 843 843 2 9.16000e+00 -5.87015e+00 -1.68478e+01 + 844 844 2 9.30000e-01 1.13800e+01 -1.76878e+01 + 845 845 2 3.99490e-02 -5.77015e+00 -2.57578e+01 + 846 846 2 -1.24301e+01 5.84000e+00 -2.91278e+01 + 847 847 2 2.19000e+00 2.20000e+00 -1.98678e+01 + 848 848 2 -6.86005e+00 3.31000e+00 -2.76578e+01 + 849 849 2 1.10000e+00 -6.56015e+00 -4.71878e+01 + 850 850 2 -1.27401e+01 -7.63015e+00 -3.61978e+01 + 851 851 2 -1.20501e+01 -1.26302e+01 -2.33878e+01 + 852 852 2 -2.60051e-01 -5.60150e-01 -3.31778e+01 + 853 853 2 -6.92005e+00 -4.20015e+00 -1.87878e+01 + 854 854 2 -5.40005e+00 -6.71015e+00 -2.62178e+01 + 855 855 2 8.15000e+00 1.64000e+00 -4.99785e+00 + 856 856 2 4.54000e+00 8.30000e+00 -2.76978e+01 + 857 857 2 8.66000e+00 -4.68015e+00 -3.25278e+01 + 858 858 2 -2.03005e+00 1.09400e+01 -1.12778e+01 + 859 859 2 8.89000e+00 -2.00150e-01 -4.18778e+01 + 860 860 2 -1.20901e+01 -3.23015e+00 -3.11978e+01 + 861 861 2 -7.00051e-01 -5.50015e+00 -2.99478e+01 + 862 862 2 -4.61005e+00 -1.14101e+01 -4.29878e+01 + 863 863 2 -5.63005e+00 -8.90015e+00 -1.47578e+01 + 864 864 2 -1.24301e+01 -4.10150e-01 -1.15678e+01 + 865 865 2 -5.87005e+00 -1.59015e+00 -4.35178e+01 + 866 866 2 -2.84005e+00 1.97000e+00 -2.13278e+01 + 867 867 2 4.68000e+00 9.45000e+00 -1.30678e+01 + 868 868 2 6.07000e+00 4.58000e+00 -1.26478e+01 + 869 869 2 -6.25005e+00 1.25100e+01 -3.86078e+01 + 870 870 2 1.22200e+01 1.19000e+00 -4.32785e+00 + 871 871 2 7.40000e+00 7.12000e+00 -3.44978e+01 + 872 872 2 1.97000e+00 -9.06015e+00 -2.00678e+01 + 873 873 2 9.82000e+00 -6.00015e+00 -2.90785e+00 + 874 874 2 2.06000e+00 1.85000e+00 -3.85178e+01 + 875 875 2 -1.07501e+01 -1.11202e+01 -2.52578e+01 + 876 876 2 -5.22005e+00 -1.05015e+00 -1.82478e+01 + 877 877 2 -1.17101e+01 -4.16015e+00 -2.10785e+00 + 878 878 2 1.28200e+01 -2.56015e+00 -3.80578e+01 + 879 879 2 1.21200e+01 -8.23015e+00 -4.18278e+01 + 880 880 2 -2.13005e+00 1.12600e+01 -1.46478e+01 + 881 881 2 -1.27301e+01 -5.60150e-01 -3.07178e+01 + 882 882 2 1.12900e+01 -3.57015e+00 -4.55378e+01 + 883 883 2 9.40000e-01 2.86000e+00 -2.65378e+01 + 884 884 2 9.10000e-01 2.58000e+00 -1.47378e+01 + 885 885 2 8.11000e+00 9.24000e+00 -1.15878e+01 + 886 886 2 5.44000e+00 -1.22102e+01 -4.28678e+01 + 887 887 2 -1.03801e+01 -1.20015e+00 -1.29678e+01 + 888 888 2 -1.05101e+01 5.12000e+00 -1.58278e+01 + 889 889 2 -8.91005e+00 -9.64015e+00 -8.87785e+00 + 890 890 2 1.27300e+01 1.07400e+01 -2.44778e+01 + 891 891 2 -6.96005e+00 2.40000e-01 -2.22778e+01 + 892 892 2 1.43000e+00 -8.06015e+00 -3.46778e+01 + 893 893 2 -1.28601e+01 -9.01015e+00 -2.89978e+01 + 894 894 2 4.39000e+00 -6.70015e+00 -4.51378e+01 + 895 895 2 6.22000e+00 8.14000e+00 -1.85178e+01 + 896 896 2 5.07000e+00 -1.81015e+00 -3.44078e+01 + 897 897 2 -1.83005e+00 1.18000e+00 -3.44078e+01 + 898 898 2 -4.00051e-01 -6.12015e+00 -4.07778e+01 + 899 899 2 9.24000e+00 1.57000e+00 -3.70478e+01 + 900 900 2 8.35000e+00 -1.02601e+01 -3.06978e+01 + 901 901 2 -6.83005e+00 -9.64015e+00 -4.26878e+01 + 902 902 2 1.00500e+01 1.97000e+00 -3.21878e+01 + 903 903 2 -6.39005e+00 1.23200e+01 -3.60778e+01 + 904 904 2 -4.32005e+00 -6.10015e+00 -1.15078e+01 + 905 905 2 -9.38005e+00 -1.03401e+01 -1.55778e+01 + 906 906 2 -9.78005e+00 -4.53015e+00 -4.59878e+01 + 907 907 2 6.63000e+00 -9.02015e+00 -4.33578e+01 + 908 908 2 -5.47005e+00 -1.11001e+01 -1.18378e+01 + 909 909 2 -4.23005e+00 -3.30150e-01 -1.50178e+01 + 910 910 2 -2.72005e+00 -1.80015e+00 -2.67778e+01 + 911 911 2 3.22000e+00 -6.21015e+00 -2.87578e+01 + 912 912 2 -3.01005e+00 -4.83015e+00 -4.43478e+01 + 913 913 2 -9.62005e+00 2.77000e+00 -3.02578e+01 + 914 914 2 -4.70051e-01 5.45000e+00 -1.04378e+01 + 915 915 2 -9.65005e+00 -1.23401e+01 -3.15278e+01 + 916 916 2 -8.23005e+00 -1.25001e+01 -1.92778e+01 + 917 917 2 -4.00000e-02 -2.91015e+00 -2.72778e+01 + 918 918 2 -4.21005e+00 7.16000e+00 -4.32785e+00 + 919 919 2 5.65000e+00 2.44000e+00 -3.19578e+01 + 920 920 2 -1.13005e+00 -4.74015e+00 -7.96785e+00 + 921 921 2 -5.99005e+00 -4.96015e+00 -3.85978e+01 + 922 922 2 6.67000e+00 -8.93015e+00 -4.50785e+00 + 923 923 2 1.03900e+01 -1.09602e+01 -4.35978e+01 + 924 924 2 7.40000e-01 -5.83015e+00 -1.76578e+01 + 925 925 2 1.10500e+01 5.22000e+00 -4.02785e+00 + 926 926 2 -4.67005e+00 6.76000e+00 -3.48578e+01 + 927 927 2 -4.06005e+00 -7.36015e+00 -3.59978e+01 + 928 928 2 -7.56005e+00 -1.09101e+01 -3.29778e+01 + 929 929 2 9.93000e+00 -6.33015e+00 -4.86578e+01 + 930 930 2 8.49000e+00 -7.14015e+00 -4.11078e+01 + 931 931 2 6.35000e+00 -5.46015e+00 -3.90978e+01 + 932 932 2 -4.37005e+00 2.49000e+00 -1.04578e+01 + 933 933 2 -1.35005e+00 4.67000e+00 -1.73078e+01 + 934 934 2 -9.18005e+00 -4.94015e+00 -1.04078e+01 + 935 935 2 -1.07101e+01 7.08000e+00 -2.57578e+01 + 936 936 2 -2.55005e+00 8.94000e+00 -2.43278e+01 + 937 937 2 -4.50005e+00 -7.45015e+00 -4.43778e+01 + 938 938 2 -1.16201e+01 -1.15701e+01 -4.55678e+01 + 939 939 2 -6.16005e+00 3.70000e-01 -2.87578e+01 + 940 940 2 5.89000e+00 1.28500e+01 -4.66078e+01 + 941 941 2 -4.83005e+00 -9.13015e+00 -9.38785e+00 + 942 942 2 -9.47005e+00 8.59000e+00 -2.92078e+01 + 943 943 2 2.77000e+00 -2.98015e+00 -2.46785e+00 + 944 944 2 7.66000e+00 -1.27401e+01 -2.93078e+01 + 945 945 2 1.39000e+00 -2.53015e+00 -4.22878e+01 + 946 946 2 7.71000e+00 -7.65015e+00 -2.27785e+00 + 947 947 2 2.82000e+00 1.15600e+01 -2.49278e+01 + 948 948 2 -3.37005e+00 -8.64015e+00 -2.27778e+01 + 949 949 2 -1.00601e+01 -6.51015e+00 -2.69378e+01 + 950 950 2 9.63000e+00 -9.00150e-01 -1.62785e+00 + 951 951 2 -7.22005e+00 -2.84015e+00 -1.44478e+01 + 952 952 2 -1.25801e+01 -6.22015e+00 -4.31278e+01 + 953 953 2 4.36000e+00 1.05000e+00 -1.82578e+01 + 954 954 2 7.00000e-02 -8.98015e+00 -3.88878e+01 + 955 955 2 1.15200e+01 7.68000e+00 -1.83078e+01 + 956 956 2 -1.16901e+01 3.75000e+00 -1.09578e+01 + 957 957 2 -6.34005e+00 -4.38015e+00 -2.76678e+01 + 958 958 2 -3.98005e+00 -1.57015e+00 -2.99878e+01 + 959 959 2 1.05000e+00 8.30000e+00 -1.98278e+01 + 960 960 2 1.27800e+01 -5.87015e+00 -1.64878e+01 + 961 961 2 -8.68005e+00 -1.27902e+01 -2.36778e+01 + 962 962 2 -5.28005e+00 7.20000e+00 -1.09378e+01 + 963 963 2 4.05000e+00 -3.07015e+00 -3.22978e+01 + 964 964 2 1.08000e+01 -8.53015e+00 -1.14078e+01 + 965 965 2 7.93000e+00 1.35000e+00 -1.02078e+01 + 966 966 2 4.58000e+00 1.10700e+01 -2.68578e+01 + 967 967 2 9.62000e+00 -9.25015e+00 -1.37778e+01 + 968 968 2 -7.58005e+00 -9.15015e+00 -3.10078e+01 + 969 969 2 -1.04601e+01 -7.89015e+00 -4.02578e+01 + 970 970 2 -6.66005e+00 7.36000e+00 -4.47778e+01 + 971 971 2 1.67000e+00 -1.00901e+01 -1.53178e+01 + 972 972 2 -2.82005e+00 -4.40015e+00 -1.95678e+01 + 973 973 2 1.27000e+01 1.26200e+01 -1.80078e+01 + 974 974 2 1.33000e+00 4.96000e+00 -4.40378e+01 + 975 975 2 -1.90005e+00 -1.21701e+01 -1.05778e+01 + 976 976 2 -5.54005e+00 9.34000e+00 -3.18078e+01 + 977 977 2 1.91000e+00 7.41000e+00 -4.42478e+01 + 978 978 2 1.99000e+00 -5.06015e+00 -4.50778e+01 + 979 979 2 1.17700e+01 -4.11015e+00 -2.89178e+01 + 980 980 2 -8.63005e+00 -6.07015e+00 -3.51578e+01 + 981 981 2 -1.16601e+01 -4.60150e-01 1.21540e-02 + 982 982 2 -5.00005e+00 -1.37015e+00 -3.30178e+01 + 983 983 2 3.30000e-01 1.12000e+00 -4.02878e+01 + 984 984 2 -3.85005e+00 3.72000e+00 -1.95178e+01 + 985 985 2 -3.54005e+00 -9.70150e-01 -7.00000e-02 + 986 986 2 4.20000e-01 1.24300e+01 -4.53478e+01 + 987 987 2 7.08000e+00 8.52000e+00 -4.13178e+01 + 988 988 2 -9.98005e+00 -4.13015e+00 -2.54578e+01 + 989 989 2 -7.37005e+00 1.75000e+00 -1.82378e+01 + 990 990 2 -1.41005e+00 -1.25901e+01 -7.03785e+00 + 991 991 2 2.74000e+00 -1.18702e+01 -3.75978e+01 + 992 992 2 -9.36005e+00 -4.60015e+00 -3.09878e+01 + 993 993 2 9.35000e+00 5.00000e-01 -4.71178e+01 + 994 994 2 -6.30051e-01 9.02000e+00 -2.89378e+01 + 995 995 2 1.03400e+01 -2.73015e+00 -3.90578e+01 + 996 996 2 6.01000e+00 -1.07302e+01 -2.45378e+01 + 997 997 2 -1.51005e+00 1.02200e+01 -2.67578e+01 + 998 998 2 2.08000e+00 8.18000e+00 -1.35678e+01 + 999 999 2 5.55000e+00 -7.76015e+00 -3.44178e+01 + 1000 1000 2 8.31000e+00 1.69000e+00 -2.04178e+01 + 1001 1001 2 -2.91005e+00 2.55000e+00 -2.97778e+01 + 1002 1002 2 -6.77005e+00 -7.46015e+00 -1.13278e+01 + 1003 1003 2 1.15000e+00 8.40000e-01 -2.33078e+01 + 1004 1004 2 3.18000e+00 7.08000e+00 -5.99785e+00 + 1005 1005 2 2.98000e+00 -1.11015e+00 -4.87846e-01 + 1006 1006 2 7.15000e+00 -7.78015e+00 -2.72578e+01 + 1007 1007 2 1.24200e+01 -1.26402e+01 -9.67785e+00 + 1008 1008 2 3.37000e+00 -1.00101e+01 -5.33785e+00 + 1009 1009 2 -6.43005e+00 -6.57015e+00 -3.65478e+01 + 1010 1010 2 -1.08005e+00 9.30000e+00 -1.83478e+01 + 1011 1011 2 8.58000e+00 6.30000e-01 -2.32778e+01 + 1012 1012 2 -7.16005e+00 -3.40015e+00 -3.25378e+01 + 1013 1013 2 8.62000e+00 -7.70150e-01 -3.55478e+01 + 1014 1014 2 -1.22101e+01 1.21700e+01 -4.15378e+01 + 1015 1015 2 1.14300e+01 5.08000e+00 -3.24678e+01 + 1016 1016 2 -3.49005e+00 4.98000e+00 -7.18785e+00 + 1017 1017 2 -7.44005e+00 2.90000e+00 -2.27978e+01 + 1018 1018 2 7.38000e+00 -9.39015e+00 -2.23278e+01 + 1019 1019 2 9.37000e+00 5.51000e+00 -1.97478e+01 + 1020 1020 2 4.52000e+00 -4.92015e+00 -1.04678e+01 + 1021 1021 2 8.72000e+00 -1.18002e+01 -4.09278e+01 + 1022 1022 2 6.08000e+00 1.27000e+01 -1.71478e+01 + 1023 1023 2 -6.33005e+00 -3.07015e+00 -2.50785e+00 + 1024 1024 2 -8.52005e+00 1.31000e+00 -4.15478e+01 + 1025 1025 2 5.08000e+00 1.04800e+01 -1.83978e+01 + 1026 1026 2 -4.56005e+00 7.99000e+00 -2.91778e+01 + 1027 1027 2 -8.84005e+00 -8.17015e+00 -2.27178e+01 + 1028 1028 2 1.20700e+01 -4.29015e+00 -4.14378e+01 + 1029 1029 2 1.26300e+01 1.00700e+01 -7.30785e+00 + 1030 1030 2 -7.65005e+00 4.16000e+00 -3.32278e+01 + 1031 1031 2 4.78000e+00 -5.28015e+00 -2.62785e+00 + 1032 1032 2 1.94000e+00 1.20600e+01 -2.23178e+01 + 1033 1033 2 -9.70005e+00 -1.01601e+01 -1.89678e+01 + 1034 1034 2 3.22000e+00 7.98500e-02 -3.42778e+01 + 1035 1035 2 -3.64005e+00 -1.03702e+01 -3.18678e+01 + 1036 1036 2 -4.18005e+00 -3.23015e+00 -2.31478e+01 + 1037 1037 2 1.01200e+01 -5.73015e+00 -2.73678e+01 + 1038 1038 2 2.79000e+00 9.32000e+00 -3.24878e+01 + 1039 1039 2 -3.78005e+00 -4.30015e+00 -5.36785e+00 + 1040 1040 2 5.24000e+00 3.20000e+00 -1.97878e+01 + 1041 1041 2 3.69000e+00 -9.14015e+00 -2.49378e+01 + 1042 1042 2 -1.01601e+01 2.90000e-01 -3.14878e+01 + 1043 1043 2 -6.30051e-01 3.77000e+00 -2.25785e+00 + 1044 1044 2 -8.43005e+00 4.49000e+00 -4.05785e+00 + 1045 1045 2 7.68000e+00 9.71000e+00 -3.36078e+01 + 1046 1046 2 2.81000e+00 -2.05015e+00 -1.06978e+01 + 1047 1047 2 -2.77005e+00 1.09800e+01 -3.77278e+01 + 1048 1048 2 6.80000e+00 -7.85015e+00 -2.46778e+01 + 1049 1049 2 2.05000e+00 -1.04002e+01 -3.32878e+01 + 1050 1050 2 1.01600e+01 -6.96015e+00 -3.19678e+01 + 1051 1051 2 1.27900e+01 -6.94015e+00 -3.15278e+01 + 1052 1052 2 -2.05005e+00 -8.86015e+00 -9.30785e+00 + 1053 1053 2 1.90000e-01 4.58000e+00 -3.88778e+01 + 1054 1054 2 -1.26801e+01 1.55000e+00 -2.43978e+01 + 1055 1055 2 -2.67005e+00 -4.99015e+00 -2.56178e+01 + 1056 1056 2 -1.14701e+01 -1.07015e+00 -1.54878e+01 + 1057 1057 2 8.07000e+00 -1.05201e+01 -8.31785e+00 + 1058 1058 2 -7.99005e+00 -7.19015e+00 -3.91778e+01 + 1059 1059 2 -1.12701e+01 -3.12015e+00 1.60000e-01 + 1060 1060 2 4.00000e-01 1.15300e+01 -1.32178e+01 + 1061 1061 2 -8.80005e+00 -3.04015e+00 -2.33078e+01 + 1062 1062 2 -3.06005e+00 -9.80015e+00 -4.50578e+01 + 1063 1063 2 4.20000e-01 -3.07015e+00 -3.41378e+01 + 1064 1064 2 -8.61005e+00 4.16000e+00 -4.62378e+01 + 1065 1065 2 1.26200e+01 -9.77015e+00 -2.81785e+00 + 1066 1066 2 -4.55005e+00 -1.90000e-01 -4.04678e+01 + 1067 1067 2 -6.48005e+00 -9.43015e+00 -2.65378e+01 + 1068 1068 2 -9.83005e+00 -7.96015e+00 -5.16785e+00 + 1069 1069 2 -4.91005e+00 2.67000e+00 -1.72978e+01 + 1070 1070 2 -4.20005e+00 9.96000e+00 -1.23978e+01 + 1071 1071 2 -1.12701e+01 2.22000e+00 -4.34178e+01 + 1072 1072 2 1.10100e+01 -1.15901e+01 -2.74678e+01 + 1073 1073 2 -1.04701e+01 5.56000e+00 -3.23778e+01 + 1074 1074 2 -1.17701e+01 -2.99015e+00 -4.50078e+01 + 1075 1075 2 -5.49005e+00 -8.12015e+00 -6.77785e+00 + 1076 1076 2 7.91000e+00 6.75000e+00 -1.01278e+01 + 1077 1077 2 8.49000e+00 -5.10150e-01 -1.32178e+01 + 1078 1078 2 -8.14005e+00 -7.00015e+00 -9.06785e+00 + 1079 1079 2 2.20000e+00 -7.65015e+00 -4.14578e+01 + 1080 1080 2 -1.01401e+01 5.40000e-01 -3.90078e+01 + 1081 1081 2 -2.80051e-01 8.31000e+00 -3.34378e+01 + 1082 1082 2 -1.15601e+01 3.85000e+00 -2.75978e+01 + 1083 1083 2 1.56000e+00 -1.30015e+00 -6.98785e+00 + 1084 1084 2 -5.71005e+00 -1.25001e+01 -3.14578e+01 + 1085 1085 2 -9.17005e+00 4.27000e+00 -3.67078e+01 + 1086 1086 2 7.41000e+00 1.11300e+01 -3.70878e+01 + 1087 1087 2 6.80000e+00 -2.40150e-01 -7.47785e+00 + 1088 1088 2 9.06000e+00 5.95000e+00 -2.85278e+01 + 1089 1089 2 1.06500e+01 -1.01502e+01 -1.81578e+01 + 1090 1090 2 1.00200e+01 -5.51015e+00 -3.66678e+01 + 1091 1091 2 3.99490e-02 -5.61015e+00 -2.28578e+01 + 1092 1092 2 9.72000e+00 1.12200e+01 -2.15078e+01 + 1093 1093 2 -2.21005e+00 6.87000e+00 -2.98178e+01 + 1094 1094 2 6.18000e+00 3.10000e+00 -1.44785e+00 + 1095 1095 2 -4.20051e-01 9.27000e+00 -3.84785e+00 + 1096 1096 2 -1.24501e+01 3.40000e+00 -3.34778e+01 + 1097 1097 2 -1.24601e+01 6.69000e+00 -3.71378e+01 + 1098 1098 2 -1.04301e+01 -4.22015e+00 -1.54278e+01 + 1099 1099 2 1.28300e+01 1.02500e+01 -1.14078e+01 + 1100 1100 2 8.23000e+00 4.15000e+00 -2.16678e+01 + 1101 1101 2 -2.18005e+00 -2.20015e+00 -3.21378e+01 + 1102 1102 2 5.11000e+00 1.08900e+01 -3.35978e+01 + 1103 1103 2 -5.55005e+00 -1.97015e+00 -5.71785e+00 + 1104 1104 2 -1.20301e+01 9.79000e+00 -2.89578e+01 + 1105 1105 2 9.79000e+00 -1.04401e+01 -2.58785e+00 + 1106 1106 2 -3.37005e+00 -6.63015e+00 -7.63785e+00 + 1107 1107 2 -1.09601e+01 -9.80015e+00 -7.11785e+00 + 1108 1108 2 -4.28005e+00 3.20000e-01 -6.24785e+00 + 1109 1109 2 2.84000e+00 1.05500e+01 -4.15078e+01 + 1110 1110 2 -5.60051e-01 1.23400e+01 -2.32178e+01 + 1111 1111 2 7.34000e+00 7.80000e+00 -3.12078e+01 + 1112 1112 2 1.02700e+01 8.30000e-01 -1.13778e+01 + 1113 1113 2 3.64000e+00 9.60000e+00 -9.75785e+00 + 1114 1114 2 -2.11005e+00 6.50000e+00 -4.75478e+01 + 1115 1115 2 -1.12501e+01 -5.70150e-01 -4.36178e+01 + 1116 1116 2 1.19600e+01 -8.26015e+00 -4.74978e+01 + 1117 1117 2 -1.11701e+01 -4.74015e+00 -3.74678e+01 + 1118 1118 2 -6.98005e+00 6.76000e+00 -3.31478e+01 + 1119 1119 2 -9.92005e+00 -4.97015e+00 -6.03785e+00 + 1120 1120 2 -8.02005e+00 7.10000e-01 -4.48078e+01 + 1121 1121 2 -1.01001e+01 1.24400e+01 -2.11978e+01 + 1122 1122 2 -6.31005e+00 5.71000e+00 -3.06578e+01 + 1123 1123 2 -7.32005e+00 3.10000e-01 -3.40578e+01 + 1124 1124 2 -8.78005e+00 1.27600e+01 -1.57278e+01 + 1125 1125 2 -1.16101e+01 8.41000e+00 -9.17785e+00 + 1126 1126 2 3.18000e+00 -4.59015e+00 -4.15378e+01 + 1127 1127 2 -9.44005e+00 1.12700e+01 -4.70785e+00 + 1128 1128 2 -5.88005e+00 -5.37015e+00 -1.63578e+01 + 1129 1129 2 2.80000e+00 9.60000e-01 -3.70785e+00 + 1130 1130 2 9.65000e+00 -2.18015e+00 -1.81778e+01 + 1131 1131 2 7.36000e+00 -1.04802e+01 -4.76578e+01 + 1132 1132 2 2.03000e+00 -3.68015e+00 -1.88478e+01 + 1133 1133 2 3.70000e-01 1.14100e+01 -8.54785e+00 + 1134 1134 2 -2.20051e-01 -7.72015e+00 -3.26078e+01 + 1135 1135 2 2.97000e+00 -2.37015e+00 -4.59478e+01 + 1136 1136 2 -5.10051e-01 4.37000e+00 -4.20478e+01 + 1137 1137 2 -3.46005e+00 -7.82015e+00 -1.35078e+01 + 1138 1138 2 1.17800e+01 1.18200e+01 -3.30278e+01 + 1139 1139 2 1.05800e+01 -5.78015e+00 -3.96778e+01 + 1140 1140 2 -7.71005e+00 -9.80150e-01 -4.34785e+00 + 1141 1141 2 -8.35005e+00 -3.20015e+00 -3.92678e+01 + 1142 1142 2 -2.25005e+00 -7.65015e+00 -3.79678e+01 + 1143 1143 2 -1.17201e+01 7.49000e+00 -3.11078e+01 + 1144 1144 2 -4.11005e+00 -8.31015e+00 -4.13378e+01 + 1145 1145 2 -1.07001e+01 1.09000e+01 -2.14785e+00 + 1146 1146 2 6.04000e+00 3.30000e-01 -4.43578e+01 + 1147 1147 2 -3.80005e+00 -1.16701e+01 -8.45785e+00 + 1148 1148 2 -5.57005e+00 -6.30150e-01 -4.66878e+01 + 1149 1149 2 3.59000e+00 -1.26302e+01 -9.33785e+00 + 1150 1150 2 -9.70051e-01 2.09850e-01 -1.90578e+01 + 1151 1151 2 9.07000e+00 -5.67015e+00 -1.21078e+01 + 1152 1152 2 -6.91005e+00 -1.20402e+01 -2.15278e+01 + 1153 1153 2 1.18200e+01 -6.17015e+00 -4.55878e+01 + 1154 1154 2 6.86000e+00 -9.62015e+00 -4.05178e+01 + 1155 1155 2 -6.63005e+00 9.75000e+00 -3.91578e+01 + 1156 1156 2 -5.20005e+00 -3.97015e+00 -3.00378e+01 + 1157 1157 2 -6.48005e+00 1.10400e+01 -1.12778e+01 + 1158 1158 2 -9.27005e+00 9.88000e+00 -1.37078e+01 + 1159 1159 2 4.33000e+00 4.60000e+00 -1.69178e+01 + 1160 1160 2 1.12500e+01 -6.43015e+00 2.29000e+00 + 1161 1161 2 1.11200e+01 2.43000e+00 -1.36878e+01 + 1162 1162 2 2.28000e+00 -4.94015e+00 -6.01785e+00 + 1163 1163 2 5.08000e+00 4.06000e+00 -3.41278e+01 + 1164 1164 2 4.96000e+00 2.79000e+00 -1.46078e+01 + 1165 1165 2 1.02700e+01 -9.74015e+00 -2.14278e+01 + 1166 1166 2 5.36000e+00 -1.12802e+01 -3.90478e+01 + 1167 1167 2 1.17000e+01 -4.50150e-01 -4.32178e+01 + 1168 1168 2 1.17800e+01 2.21000e+00 -4.15778e+01 + 1169 1169 2 -1.68005e+00 -9.77015e+00 -4.74678e+01 + 1170 1170 2 4.07000e+00 -1.16801e+01 -1.57978e+01 + 1171 1171 2 9.34000e+00 1.13100e+01 -3.50978e+01 + 1172 1172 2 -8.90051e-01 -5.39015e+00 -3.38878e+01 + 1173 1173 2 -5.80005e+00 -1.16001e+01 -1.58078e+01 + 1174 1174 2 1.21800e+01 5.74000e+00 -2.48078e+01 + 1175 1175 2 9.45000e+00 -3.94015e+00 -1.01785e+00 + 1176 1176 2 5.05000e+00 -6.65015e+00 -3.06478e+01 + 1177 1177 2 4.74000e+00 -1.20001e+01 -6.57785e+00 + 1178 1178 2 9.17000e+00 -5.24015e+00 -2.20178e+01 + 1179 1179 2 -4.99005e+00 -2.71015e+00 -2.04078e+01 + 1180 1180 2 5.55000e+00 -9.30150e-01 -3.77878e+01 + 1181 1181 2 4.31000e+00 1.87000e+00 -4.02478e+01 + 1182 1182 2 1.22100e+01 4.41000e+00 -3.56178e+01 + 1183 1183 2 5.39000e+00 -1.04602e+01 -1.21478e+01 + 1184 1184 2 -2.90005e+00 -9.10150e-01 -4.62178e+01 + 1185 1185 2 8.83000e+00 3.44000e+00 -3.89978e+01 + 1186 1186 2 3.74000e+00 9.80000e-01 -1.18778e+01 + 1187 1187 2 -1.17501e+01 6.50000e+00 -1.37478e+01 + 1188 1188 2 -8.12005e+00 -9.72015e+00 -3.68278e+01 + 1189 1189 2 6.79000e+00 5.28000e+00 -3.06178e+01 + 1190 1190 2 7.38000e+00 -4.65015e+00 8.60000e-01 + 1191 1191 2 1.62000e+00 9.24000e+00 -2.43778e+01 + 1192 1192 2 4.04000e+00 -4.11015e+00 -3.91378e+01 + 1193 1193 2 -5.89005e+00 -7.40150e-01 -1.29078e+01 + 1194 1194 2 -6.16005e+00 4.30000e-01 -3.14878e+01 + 1195 1195 2 6.25000e+00 -4.14015e+00 -3.08078e+01 + 1196 1196 2 1.03700e+01 -7.90150e-01 -2.17078e+01 + 1197 1197 2 3.93000e+00 2.71000e+00 -5.74785e+00 + 1198 1198 2 -1.99005e+00 3.41000e+00 -4.40178e+01 + 1199 1199 2 1.22800e+01 -9.61015e+00 -2.62478e+01 + 1200 1200 2 -3.81005e+00 9.46000e+00 -7.36785e+00 + 1201 1201 2 -7.51005e+00 1.02700e+01 -3.02278e+01 + 1202 1202 2 1.05600e+01 5.31000e+00 -1.60578e+01 + 1203 1203 2 -6.57005e+00 -3.28015e+00 -4.78478e+01 + 1204 1204 2 4.37000e+00 4.84000e+00 -3.72978e+01 + 1205 1205 2 7.88000e+00 6.40000e+00 -3.71178e+01 + 1206 1206 2 2.22000e+00 -6.26015e+00 -9.75785e+00 + 1207 1207 2 4.85000e+00 2.39000e+00 -2.42778e+01 + 1208 1208 2 -1.13501e+01 4.77000e+00 -4.62778e+01 + 1209 1209 2 1.26600e+01 -6.29015e+00 -7.86785e+00 + 1210 1210 2 4.69000e+00 4.00000e+00 -9.68785e+00 + 1211 1211 2 3.99000e+00 -8.63015e+00 -4.32778e+01 + 1212 1212 2 7.98000e+00 -8.36015e+00 -1.73778e+01 + 1213 1213 2 2.51000e+00 -4.42015e+00 -3.59478e+01 + 1214 1214 2 5.68000e+00 1.10600e+01 -2.35278e+01 + 1215 1215 2 -4.52005e+00 -7.48015e+00 -1.76978e+01 + 1216 1216 2 -1.03201e+01 -7.23015e+00 -4.57478e+01 + 1217 1217 2 -3.90051e-01 -9.95015e+00 -3.59978e+01 + 1218 1218 2 5.72000e+00 -1.04002e+01 -3.64478e+01 + 1219 1219 2 2.20000e-01 -1.32015e+00 -1.43878e+01 + 1220 1220 2 5.23000e+00 1.27000e+00 -3.60778e+01 + 1221 1221 2 -9.19005e+00 -1.06502e+01 -4.19378e+01 + 1222 1222 2 6.55000e+00 -6.27015e+00 -1.14978e+01 + 1223 1223 2 -2.72005e+00 -9.18015e+00 -3.43078e+01 + 1224 1224 2 -1.02501e+01 9.68000e+00 -4.08078e+01 + 1225 1225 2 -2.08005e+00 -9.04015e+00 -1.71978e+01 + 1226 1226 2 5.19000e+00 6.56000e+00 -7.65785e+00 + 1227 1227 2 -3.50051e-01 -6.16015e+00 -1.26578e+01 + 1228 1228 2 5.80000e-01 7.88000e+00 -6.00785e+00 + 1229 1229 2 -5.18005e+00 8.11000e+00 -4.26578e+01 + 1230 1230 2 -2.22005e+00 -4.89015e+00 -1.44978e+01 + 1231 1231 2 -9.07005e+00 -1.15502e+01 -4.63378e+01 + 1232 1232 2 1.24200e+01 1.95000e+00 -1.75978e+01 + 1233 1233 2 1.09800e+01 2.54000e+00 -2.14078e+01 + 1234 1234 2 -2.41005e+00 5.48000e+00 -2.65078e+01 + 1235 1235 2 7.17000e+00 1.18700e+01 -3.18178e+01 + 1236 1236 2 6.20000e-01 1.06500e+01 -3.09878e+01 + 1237 1237 2 7.90000e+00 -4.16015e+00 -4.09778e+01 + 1238 1238 2 -1.13701e+01 -1.62015e+00 -3.50378e+01 + 1239 1239 2 2.73000e+00 -1.08802e+01 -2.82178e+01 + 1240 1240 2 -2.52005e+00 -1.91015e+00 -3.96678e+01 + 1241 1241 2 -7.49005e+00 1.17000e+00 -3.91478e+01 + 1242 1242 2 2.32000e+00 -5.24015e+00 -1.45778e+01 + 1243 1243 2 9.11000e+00 -7.30150e-01 -3.12078e+01 + 1244 1244 2 4.66000e+00 -7.22015e+00 -1.56878e+01 + 1245 1245 2 5.32000e+00 -4.00150e-01 -5.00785e+00 + 1246 1246 2 -8.10051e-01 -2.62015e+00 -2.98778e+01 + 1247 1247 2 -1.08101e+01 7.68000e+00 -6.23785e+00 + 1248 1248 2 7.19000e+00 -7.80015e+00 -3.14078e+01 + 1249 1249 2 9.90000e+00 3.92000e+00 -8.91785e+00 + 1250 1250 2 -1.01005e+00 1.27600e+01 -2.62278e+01 + 1251 1251 2 -1.79005e+00 -5.91015e+00 -1.03678e+01 + 1252 1252 2 -1.61005e+00 -1.14201e+01 -2.87878e+01 + 1253 1253 2 -8.35005e+00 -1.69015e+00 -3.05978e+01 + 1254 1254 2 -1.01001e+01 -7.20015e+00 -1.16878e+01 + 1255 1255 2 1.12300e+01 -8.67015e+00 -1.58878e+01 + 1256 1256 2 7.40000e+00 -1.76015e+00 -1.65678e+01 + 1257 1257 2 -5.20005e+00 -1.09802e+01 -2.84278e+01 + 1258 1258 2 1.08800e+01 7.74000e+00 -2.96078e+01 + 1259 1259 2 4.80000e+00 -7.70015e+00 -3.99778e+01 + 1260 1260 2 1.49000e+00 -1.30150e-01 -3.65178e+01 + 1261 1261 2 -5.56005e+00 -9.87015e+00 -3.67178e+01 + 1262 1262 2 -9.83005e+00 -1.10602e+01 -3.49778e+01 + 1263 1263 2 -1.12001e+01 2.48000e+00 -1.58478e+01 + 1264 1264 2 -3.41005e+00 7.12000e+00 -1.40078e+01 + 1265 1265 2 1.17200e+01 4.81000e+00 -1.86578e+01 + 1266 1266 2 -1.22001e+01 2.82000e+00 -3.06378e+01 + 1267 1267 2 -9.60005e+00 1.10100e+01 -4.71878e+01 + 1268 1268 2 -9.04005e+00 5.10000e-01 -2.50878e+01 + 1269 1269 2 -5.96005e+00 -2.01500e-02 -3.72478e+01 + 1270 1270 2 1.27800e+01 -4.50015e+00 -1.37178e+01 + 1271 1271 2 9.00000e-02 7.49000e+00 -3.86678e+01 + 1272 1272 2 5.99000e+00 -8.09015e+00 -1.35178e+01 + 1273 1273 2 1.13100e+01 -5.61015e+00 -1.87778e+01 + 1274 1274 2 1.18700e+01 -1.06102e+01 -3.84478e+01 + 1275 1275 2 3.53000e+00 -6.05015e+00 -3.39678e+01 + 1276 1276 2 -6.20005e+00 3.51000e+00 -1.48878e+01 + 1277 1277 2 1.16400e+01 3.59000e+00 -3.85778e+01 + 1278 1278 2 1.14000e+01 -1.27701e+01 -3.58478e+01 + 1279 1279 2 -2.54005e+00 1.25300e+01 -4.23378e+01 + 1280 1280 2 -7.68005e+00 -6.93015e+00 -1.92678e+01 + 1281 1281 2 7.61000e+00 -1.63015e+00 -3.97078e+01 + 1282 1282 2 -3.45005e+00 3.35000e+00 -1.30978e+01 + 1283 1283 2 -4.44005e+00 -1.16402e+01 -4.82978e+01 + 1284 1284 2 -1.70000e-01 8.37000e+00 -2.26178e+01 + 1285 1285 2 9.78000e+00 6.78000e+00 -4.03278e+01 + 1286 1286 2 -6.58005e+00 3.79000e+00 -3.93778e+01 + 1287 1287 2 3.43000e+00 -1.06901e+01 -4.47078e+01 + 1288 1288 2 1.14100e+01 -1.26901e+01 -3.53785e+00 + 1289 1289 2 -2.10005e+00 -1.11701e+01 -2.25678e+01 + 1290 1290 2 -7.97005e+00 1.01400e+01 -3.68178e+01 + 1291 1291 2 -2.11005e+00 1.94000e+00 -3.94678e+01 + 1292 1292 2 4.75000e+00 1.07900e+01 -2.96878e+01 + 1293 1293 2 6.04000e+00 -1.28401e+01 -3.54278e+01 + 1294 1294 2 9.83000e+00 8.26000e+00 -3.22478e+01 + 1295 1295 2 9.44000e+00 -7.93015e+00 -2.88678e+01 + 1296 1296 2 1.16000e+01 -2.78015e+00 -7.80785e+00 + 1297 1297 2 1.06900e+01 -1.21402e+01 -5.94785e+00 + 1298 1298 2 3.51000e+00 9.25000e+00 -1.65078e+01 + 1299 1299 2 -8.50005e+00 4.88000e+00 -2.61678e+01 + 1300 1300 2 3.34000e+00 -1.03902e+01 -3.07978e+01 + 1301 1301 2 5.18000e+00 6.88000e+00 -2.16178e+01 + 1302 1302 2 -1.24001e+01 6.40000e+00 -1.09778e+01 + 1303 1303 2 -7.55005e+00 -6.93015e+00 -1.49378e+01 + 1304 1304 2 -1.18301e+01 8.58000e+00 -2.16785e+00 + 1305 1305 2 -1.11601e+01 4.20000e+00 -6.70785e+00 + 1306 1306 2 -7.07005e+00 8.69000e+00 -9.76785e+00 + 1307 1307 2 1.06600e+01 4.55000e+00 -1.20878e+01 + 1308 1308 2 2.64000e+00 -1.64015e+00 -1.54978e+01 + 1309 1309 2 2.99000e+00 2.74000e+00 -4.49278e+01 + 1310 1310 2 9.29000e+00 -7.03015e+00 -4.50078e+01 + 1311 1311 2 4.29000e+00 7.97000e+00 -4.54078e+01 + 1312 1312 2 -1.12701e+01 -8.00015e+00 -2.14078e+01 + 1313 1313 2 -8.40005e+00 -5.54015e+00 -2.24478e+01 + 1314 1314 2 -6.09005e+00 4.48000e+00 -3.67478e+01 + 1315 1315 2 9.15000e+00 5.23000e+00 -3.37778e+01 + 1316 1316 2 -4.68005e+00 -4.82015e+00 -4.66478e+01 + 1317 1317 2 7.52000e+00 1.57000e+00 -1.43878e+01 + 1318 1318 2 -2.77005e+00 1.19000e+00 -1.69778e+01 + 1319 1319 2 9.14000e+00 -1.53015e+00 -8.01785e+00 + 1320 1320 2 6.97000e+00 -3.24015e+00 -2.83078e+01 + 1321 1321 2 1.91000e+00 7.59000e+00 -9.15785e+00 + 1322 1322 2 6.85000e+00 4.06000e+00 -3.62578e+01 + 1323 1323 2 1.27000e+00 -3.27015e+00 -3.15078e+01 + 1324 1324 2 4.35000e+00 9.50000e+00 -5.44785e+00 + 1325 1325 2 -7.14005e+00 -6.48015e+00 -4.66478e+01 + 1326 1326 2 8.30000e-01 -1.06015e+00 -4.33785e+00 + 1327 1327 2 2.71000e+00 -1.11202e+01 -2.20978e+01 + 1328 1328 2 -9.59005e+00 -3.70015e+00 -1.81878e+01 + 1329 1329 2 -8.48005e+00 -1.03702e+01 -2.84678e+01 + 1330 1330 2 -9.11005e+00 9.59000e+00 -4.33878e+01 + 1331 1331 2 1.62000e+00 5.40000e+00 -1.84785e+00 + 1332 1332 2 -4.00051e-01 -3.22015e+00 -2.13578e+01 + 1333 1333 2 8.34000e+00 -3.06015e+00 -1.43378e+01 + 1334 1334 2 -8.45005e+00 7.58000e+00 -2.39178e+01 + 1335 1335 2 8.81000e+00 9.65000e+00 -4.30678e+01 + 1336 1336 2 2.17000e+00 -9.83015e+00 -1.26478e+01 + 1337 1337 2 -4.31005e+00 7.43000e+00 -2.58078e+01 + 1338 1338 2 8.92000e+00 8.37000e+00 -7.99785e+00 + 1339 1339 2 6.05000e+00 -3.75015e+00 -1.30278e+01 + 1340 1340 2 5.74000e+00 1.21100e+01 -4.43785e+00 + 1341 1341 2 3.20000e+00 5.57000e+00 -3.14378e+01 + 1342 1342 2 -5.08005e+00 -1.37015e+00 -1.01078e+01 + 1343 1343 2 -9.90051e-01 -1.26302e+01 -1.64878e+01 + 1344 1344 2 -1.15001e+01 -3.89015e+00 -8.07785e+00 + 1345 1345 2 -2.06005e+00 -5.76015e+00 -1.73478e+01 + 1346 1346 2 -1.24001e+01 1.08600e+01 -4.71578e+01 + 1347 1347 2 -3.59005e+00 5.39000e+00 -9.73785e+00 + 1348 1348 2 6.91000e+00 -4.28015e+00 -5.88785e+00 + 1349 1349 2 -9.64005e+00 6.56000e+00 -2.14178e+01 + 1350 1350 2 9.69000e+00 1.12200e+01 -1.51878e+01 + 1351 1351 2 1.14500e+01 -1.74015e+00 5.60000e-01 + 1352 1352 2 -6.61005e+00 1.20500e+01 -4.26078e+01 + 1353 1353 2 6.52000e+00 1.06600e+01 -1.45078e+01 + 1354 1354 2 1.03600e+01 -2.89015e+00 -4.28278e+01 + 1355 1355 2 9.30000e-01 -7.60015e+00 -2.89778e+01 + 1356 1356 2 7.04000e+00 -1.12002e+01 -4.48378e+01 + 1357 1357 2 7.40000e-01 4.14000e+00 -1.25878e+01 + 1358 1358 2 8.00000e-02 -4.35015e+00 -3.89678e+01 + 1359 1359 2 7.31000e+00 6.91000e+00 -2.43078e+01 + 1360 1360 2 -1.00401e+01 -3.51015e+00 -4.29978e+01 + 1361 1361 2 -1.75005e+00 -2.26015e+00 -1.81178e+01 + 1362 1362 2 1.12700e+01 -1.67015e+00 -1.57278e+01 + 1363 1363 2 1.01500e+01 2.95000e+00 -3.49478e+01 + 1364 1364 2 -1.22001e+01 9.13000e+00 -1.48778e+01 + 1365 1365 2 -9.12005e+00 2.42000e+00 -3.46778e+01 + 1366 1366 2 2.96000e+00 6.12000e+00 -2.66378e+01 + 1367 1367 2 -5.30005e+00 9.71000e+00 -1.68678e+01 + 1368 1368 2 9.84000e+00 -3.46015e+00 -1.09178e+01 + 1369 1369 2 3.99000e+00 4.59000e+00 -2.89778e+01 + 1370 1370 2 9.78000e+00 1.10400e+01 -3.14178e+01 + 1371 1371 2 1.03500e+01 -5.34015e+00 -1.44278e+01 + 1372 1372 2 -3.43005e+00 -9.17015e+00 -2.84178e+01 + 1373 1373 2 4.45000e+00 -3.71015e+00 -1.52778e+01 + 1374 1374 2 1.57000e+00 -7.99015e+00 -2.61278e+01 + 1375 1375 2 5.46000e+00 -2.57015e+00 -4.72978e+01 + 1376 1376 2 -1.14501e+01 1.47000e+00 -6.54785e+00 + 1377 1377 2 6.75000e+00 -5.59015e+00 -4.47678e+01 + 1378 1378 2 -5.04005e+00 -1.10502e+01 -2.49178e+01 + 1379 1379 2 -1.02401e+01 -9.00150e-01 -2.25278e+01 + 1380 1380 2 4.23000e+00 -7.94015e+00 -2.07378e+01 + diff --git a/examples/USER/misc/local_density/benzene_water/benzene_water.in b/examples/USER/misc/local_density/benzene_water/benzene_water.in new file mode 100644 index 0000000000..01fb3f27e5 --- /dev/null +++ b/examples/USER/misc/local_density/benzene_water/benzene_water.in @@ -0,0 +1,62 @@ +# LAMMPS input file for 26.5% benzene mole fraction solution +# with 380 benzene and 1000 water molecules, +# using all possible local density potentials +# between benzene and water +# +# Author: Tanmoy Sanyal, Shell Group, UC Santa Barbara +# +# Refer: Sanyal and Shell, JPC-B, 2018, 122 (21), 5678-5693 + + + +# Initialize simulation box +dimension 3 +boundary p p p +units real +atom_style molecular + +# Set potential styles +pair_style hybrid/overlay table spline 500 local/density + +# Read molecule data and set initial velocities +read_data benzene_water.data +velocity all create 3.0000e+02 16611 rot yes dist gaussian + +# Assign potentials +pair_coeff 1 1 table benzene_water.pair.table PairBB +pair_coeff 1 2 table benzene_water.pair.table PairWW +pair_coeff 2 2 table benzene_water.pair.table PairBW +pair_coeff * * local/density benzene_water.localdensity.table + +# Recentering during minimization and equilibration +fix recentering all recenter 0.0 0.0 0.0 units box + +# Thermostat & time integration +timestep 2.0 +thermo 100 +thermo_style custom temp ke pe etotal ebond eangle edihed evdwl + +# Minimization +minimize 1.e-4 0.0 10000 10000 + +# Set up integration parameters +fix timeintegration all nve +fix thermostat all langevin 3.0000e+02 3.0000e+02 1.0000e+02 81890 + +# Equilibration (for realistic results, run for 5000000 steps) +reset_timestep 0 +run 5000 + +# Turn off recentering during production phase +unfix recentering + +# Setup trajectory output +dump myDump all custom 100 benzene_water.lammpstrj.gz id type x y z element +dump_modify myDump element B W +dump_modify myDump sort id + +# Production (for realistic results, run for 10000000 steps) +reset_timestep 0 +run 1000 + + diff --git a/examples/USER/misc/local_density/benzene_water/benzene_water.localdensity.table b/examples/USER/misc/local_density/benzene_water/benzene_water.localdensity.table new file mode 100644 index 0000000000..b0d63dbbbf --- /dev/null +++ b/examples/USER/misc/local_density/benzene_water/benzene_water.localdensity.table @@ -0,0 +1,2024 @@ +# local density potentials: (B,B), (W,W), (B,W), (W,B) + +4 500 + + 6.5000000e+00 7.5000000e+00 +1 +1 + 0.0000000e+00 2.0000000e+01 4.0080160e-02 + 1.5200000e+00 + 1.5200000e+00 + 1.5200000e+00 + 1.5200000e+00 + 1.5200000e+00 + 1.5200000e+00 + 1.5200000e+00 + 1.5200000e+00 + 1.5200000e+00 + 1.5200000e+00 + 1.5200000e+00 + 1.5200000e+00 + 1.5200000e+00 + 1.5200000e+00 + 1.5200000e+00 + 1.5200000e+00 + 1.5200000e+00 + 1.5200000e+00 + 1.5200000e+00 + 1.5200000e+00 + 1.5200000e+00 + 1.5200000e+00 + 1.5200000e+00 + 1.5200000e+00 + 1.5200000e+00 + 1.5200000e+00 + 1.5200000e+00 + 1.5200000e+00 + 1.5200000e+00 + 1.5200000e+00 + 1.5200000e+00 + 1.5200000e+00 + 1.5200000e+00 + 1.5200000e+00 + 1.5200000e+00 + 1.5200000e+00 + 1.5200000e+00 + 1.5200000e+00 + 1.5200000e+00 + 1.5200000e+00 + 1.5200000e+00 + 1.5200000e+00 + 1.5200000e+00 + 1.5200000e+00 + 1.5200000e+00 + 1.5200000e+00 + 1.5200000e+00 + 1.5200000e+00 + 1.5200000e+00 + 1.5200000e+00 + 1.5200000e+00 + 1.5200000e+00 + 1.5200000e+00 + 1.5200000e+00 + 1.5200000e+00 + 1.5200000e+00 + 1.5200000e+00 + 1.5200000e+00 + 1.5200000e+00 + 1.5200000e+00 + 1.5200000e+00 + 1.5200000e+00 + 1.5200000e+00 + 1.5200000e+00 + 1.5200000e+00 + 1.5200000e+00 + 1.5200000e+00 + 1.5200000e+00 + 1.5200000e+00 + 1.5200000e+00 + 1.5200000e+00 + 1.5200000e+00 + 1.5200000e+00 + 1.5200000e+00 + 1.5200000e+00 + 1.5200000e+00 + 1.5200000e+00 + 1.5200000e+00 + 1.5200000e+00 + 1.5200000e+00 + 1.5200000e+00 + 1.5200000e+00 + 1.5200000e+00 + 1.5200000e+00 + 1.5200000e+00 + 1.5200000e+00 + 1.5200000e+00 + 1.5200000e+00 + 1.5200000e+00 + 1.5200000e+00 + 1.5200000e+00 + 1.5200000e+00 + 1.5200000e+00 + 1.5200000e+00 + 1.5200000e+00 + 1.5200000e+00 + 1.5200000e+00 + 1.5200000e+00 + 1.5200000e+00 + 1.5200000e+00 + 1.5200000e+00 + 1.5200000e+00 + 1.5200000e+00 + 1.5200000e+00 + 1.5200000e+00 + 1.5200000e+00 + 1.5200000e+00 + 1.5200000e+00 + 1.5200000e+00 + 1.5200000e+00 + 1.5200000e+00 + 1.5200000e+00 + 1.5200000e+00 + 1.5200000e+00 + 1.5200000e+00 + 1.5200000e+00 + 1.5200000e+00 + 1.5200000e+00 + 1.5200000e+00 + 1.5200000e+00 + 1.5200000e+00 + 1.5199986e+00 + 1.5199680e+00 + 1.5198579e+00 + 1.5196169e+00 + 1.5191936e+00 + 1.5185367e+00 + 1.5175950e+00 + 1.5163171e+00 + 1.5146518e+00 + 1.5125477e+00 + 1.5099534e+00 + 1.5068178e+00 + 1.5030895e+00 + 1.4987171e+00 + 1.4936494e+00 + 1.4878351e+00 + 1.4812228e+00 + 1.4737622e+00 + 1.4654545e+00 + 1.4563786e+00 + 1.4466198e+00 + 1.4362633e+00 + 1.4253943e+00 + 1.4140983e+00 + 1.4024604e+00 + 1.3905658e+00 + 1.3785000e+00 + 1.3663480e+00 + 1.3541953e+00 + 1.3421270e+00 + 1.3302284e+00 + 1.3185849e+00 + 1.3072816e+00 + 1.2964039e+00 + 1.2860369e+00 + 1.2762309e+00 + 1.2669431e+00 + 1.2581156e+00 + 1.2496902e+00 + 1.2416089e+00 + 1.2338138e+00 + 1.2262466e+00 + 1.2188495e+00 + 1.2115643e+00 + 1.2043330e+00 + 1.1970976e+00 + 1.1898000e+00 + 1.1823821e+00 + 1.1747860e+00 + 1.1669536e+00 + 1.1588268e+00 + 1.1503476e+00 + 1.1414684e+00 + 1.1321937e+00 + 1.1225435e+00 + 1.1125380e+00 + 1.1021975e+00 + 1.0915422e+00 + 1.0805923e+00 + 1.0693679e+00 + 1.0578893e+00 + 1.0461766e+00 + 1.0342501e+00 + 1.0221300e+00 + 1.0098365e+00 + 9.9738976e-01 + 9.8481000e-01 + 9.7211742e-01 + 9.5933222e-01 + 9.4647351e-01 + 9.3354993e-01 + 9.2056435e-01 + 9.0751957e-01 + 8.9441841e-01 + 8.8126366e-01 + 8.6805815e-01 + 8.5480466e-01 + 8.4150602e-01 + 8.2816503e-01 + 8.1478448e-01 + 8.0136720e-01 + 7.8791599e-01 + 7.7443365e-01 + 7.6092300e-01 + 7.4738683e-01 + 7.3382796e-01 + 7.2024905e-01 + 7.0664998e-01 + 6.9302788e-01 + 6.7937983e-01 + 6.6570286e-01 + 6.5199403e-01 + 6.3825039e-01 + 6.2446900e-01 + 6.1064690e-01 + 5.9678114e-01 + 5.8286879e-01 + 5.6890688e-01 + 5.5489248e-01 + 5.4082263e-01 + 5.2669439e-01 + 5.1250480e-01 + 4.9825093e-01 + 4.8392987e-01 + 4.6954274e-01 + 4.5509728e-01 + 4.4060182e-01 + 4.2606471e-01 + 4.1149429e-01 + 3.9689892e-01 + 3.8228692e-01 + 3.6766665e-01 + 3.5304645e-01 + 3.3843467e-01 + 3.2383965e-01 + 3.0926972e-01 + 2.9473325e-01 + 2.8023857e-01 + 2.6579402e-01 + 2.5140795e-01 + 2.3708871e-01 + 2.2284155e-01 + 2.0866274e-01 + 1.9454685e-01 + 1.8048847e-01 + 1.6648220e-01 + 1.5252263e-01 + 1.3860435e-01 + 1.2472194e-01 + 1.1087000e-01 + 9.7043120e-02 + 8.3235888e-02 + 6.9442895e-02 + 5.5658731e-02 + 4.1877986e-02 + 2.8095251e-02 + 1.4305116e-02 + 5.0217173e-04 +-1.3318314e-02 +-2.7157364e-02 +-4.1014743e-02 +-5.4890212e-02 +-6.8783535e-02 +-8.2694474e-02 +-9.6622792e-02 +-1.1056825e-01 +-1.2453061e-01 +-1.3850964e-01 +-1.5250510e-01 +-1.6651674e-01 +-1.8054434e-01 +-1.9458766e-01 +-2.0864645e-01 +-2.2272049e-01 +-2.3680953e-01 +-2.5091268e-01 +-2.6502202e-01 +-2.7912541e-01 +-2.9321059e-01 +-3.0726536e-01 +-3.2127748e-01 +-3.3523473e-01 +-3.4912488e-01 +-3.6293570e-01 +-3.7665496e-01 +-3.9027045e-01 +-4.0376992e-01 +-4.1714117e-01 +-4.3037195e-01 +-4.4345004e-01 +-4.5636322e-01 +-4.6909926e-01 +-4.8164636e-01 +-4.9400348e-01 +-5.0618082e-01 +-5.1818912e-01 +-5.3003911e-01 +-5.4174151e-01 +-5.5330707e-01 +-5.6474652e-01 +-5.7607059e-01 +-5.8729001e-01 +-5.9841552e-01 +-6.0945785e-01 +-6.2042773e-01 +-6.3133589e-01 +-6.4219308e-01 +-6.5301001e-01 +-6.6379743e-01 +-6.7456590e-01 +-6.8531068e-01 +-6.9599928e-01 +-7.0659631e-01 +-7.1706635e-01 +-7.2737402e-01 +-7.3748391e-01 +-7.4736063e-01 +-7.5696876e-01 +-7.6627291e-01 +-7.7523768e-01 +-7.8382768e-01 +-7.9200749e-01 +-7.9974172e-01 +-8.0699496e-01 +-8.1373183e-01 +-8.1991691e-01 +-8.2551482e-01 +-8.3050467e-01 +-8.3491291e-01 +-8.3877558e-01 +-8.4212871e-01 +-8.4500834e-01 +-8.4745052e-01 +-8.4949128e-01 +-8.5116667e-01 +-8.5251273e-01 +-8.5356549e-01 +-8.5436100e-01 +-8.5493529e-01 +-8.5532441e-01 +-8.5556440e-01 +-8.5569130e-01 +-8.5574115e-01 +-8.5574998e-01 +-8.5575000e-01 +-8.5575000e-01 +-8.5575000e-01 +-8.5575000e-01 +-8.5575000e-01 +-8.5575000e-01 +-8.5575000e-01 +-8.5575000e-01 +-8.5575000e-01 +-8.5575000e-01 +-8.5575000e-01 +-8.5575000e-01 +-8.5575000e-01 +-8.5575000e-01 +-8.5575000e-01 +-8.5575000e-01 +-8.5575000e-01 +-8.5575000e-01 +-8.5575000e-01 +-8.5575000e-01 +-8.5575000e-01 +-8.5575000e-01 +-8.5575000e-01 +-8.5575000e-01 +-8.5575000e-01 +-8.5575000e-01 +-8.5575000e-01 +-8.5575000e-01 +-8.5575000e-01 +-8.5575000e-01 +-8.5575000e-01 +-8.5575000e-01 +-8.5575000e-01 +-8.5575000e-01 +-8.5575000e-01 +-8.5575000e-01 +-8.5575000e-01 +-8.5575000e-01 +-8.5575000e-01 +-8.5575000e-01 +-8.5575000e-01 +-8.5575000e-01 +-8.5575000e-01 +-8.5575000e-01 +-8.5575000e-01 +-8.5575000e-01 +-8.5575000e-01 +-8.5575000e-01 +-8.5575000e-01 +-8.5575000e-01 +-8.5575000e-01 +-8.5575000e-01 +-8.5575000e-01 +-8.5575000e-01 +-8.5575000e-01 +-8.5575000e-01 +-8.5575000e-01 +-8.5575000e-01 +-8.5575000e-01 +-8.5575000e-01 +-8.5575000e-01 +-8.5575000e-01 +-8.5575000e-01 +-8.5575000e-01 +-8.5575000e-01 +-8.5575000e-01 +-8.5575000e-01 +-8.5575000e-01 +-8.5575000e-01 +-8.5575000e-01 +-8.5575000e-01 +-8.5575000e-01 +-8.5575000e-01 +-8.5575000e-01 +-8.5575000e-01 +-8.5575000e-01 +-8.5575000e-01 +-8.5575000e-01 +-8.5575000e-01 +-8.5575000e-01 +-8.5575000e-01 +-8.5575000e-01 +-8.5575000e-01 +-8.5575000e-01 +-8.5575000e-01 +-8.5575000e-01 +-8.5575000e-01 +-8.5575000e-01 +-8.5575000e-01 +-8.5575000e-01 +-8.5575000e-01 +-8.5575000e-01 +-8.5575000e-01 +-8.5575000e-01 +-8.5575000e-01 +-8.5575000e-01 +-8.5575000e-01 +-8.5575000e-01 +-8.5575000e-01 +-8.5575000e-01 +-8.5575000e-01 +-8.5575000e-01 +-8.5575000e-01 +-8.5575000e-01 +-8.5575000e-01 +-8.5575000e-01 +-8.5575000e-01 +-8.5575000e-01 +-8.5575000e-01 +-8.5575000e-01 +-8.5575000e-01 +-8.5575000e-01 +-8.5575000e-01 +-8.5575000e-01 +-8.5575000e-01 +-8.5575000e-01 +-8.5575000e-01 +-8.5575000e-01 +-8.5575000e-01 +-8.5575000e-01 +-8.5575000e-01 +-8.5575000e-01 +-8.5575000e-01 +-8.5575000e-01 +-8.5575000e-01 +-8.5575000e-01 +-8.5575000e-01 +-8.5575000e-01 +-8.5575000e-01 +-8.5575000e-01 +-8.5575000e-01 +-8.5575000e-01 +-8.5575000e-01 +-8.5575000e-01 +-8.5575000e-01 +-8.5575000e-01 +-8.5575000e-01 +-8.5575000e-01 +-8.5575000e-01 +-8.5575000e-01 +-8.5575000e-01 +-8.5575000e-01 +-8.5575000e-01 +-8.5575000e-01 +-8.5575000e-01 +-8.5575000e-01 +-8.5575000e-01 +-8.5575000e-01 +-8.5575000e-01 +-8.5575000e-01 +-8.5575000e-01 +-8.5575000e-01 +-8.5575000e-01 +-8.5575000e-01 +-8.5575000e-01 + + 2.5000000e+00 3.5000000e+00 +2 +2 + 0.0000000e+00 6.0000000e+00 1.2024048e-02 + 2.0462000e+00 + 2.0462000e+00 + 2.0462000e+00 + 2.0462000e+00 + 2.0462000e+00 + 2.0462000e+00 + 2.0462000e+00 + 2.0462000e+00 + 2.0462000e+00 + 2.0462000e+00 + 2.0462000e+00 + 2.0462000e+00 + 2.0462000e+00 + 2.0462000e+00 + 2.0462000e+00 + 2.0462000e+00 + 2.0462000e+00 + 2.0462000e+00 + 2.0462000e+00 + 2.0462000e+00 + 2.0462000e+00 + 2.0462000e+00 + 2.0462000e+00 + 2.0462000e+00 + 2.0462000e+00 + 2.0462000e+00 + 2.0462000e+00 + 2.0462000e+00 + 2.0462000e+00 + 2.0462000e+00 + 2.0462000e+00 + 2.0462000e+00 + 2.0462000e+00 + 2.0462000e+00 + 2.0462000e+00 + 2.0462000e+00 + 2.0462000e+00 + 2.0462000e+00 + 2.0462000e+00 + 2.0462000e+00 + 2.0462000e+00 + 2.0462000e+00 + 2.0462000e+00 + 2.0462000e+00 + 2.0462000e+00 + 2.0462000e+00 + 2.0462000e+00 + 2.0462000e+00 + 2.0462000e+00 + 2.0462000e+00 + 2.0462000e+00 + 2.0462000e+00 + 2.0462000e+00 + 2.0462000e+00 + 2.0462000e+00 + 2.0462000e+00 + 2.0462000e+00 + 2.0462000e+00 + 2.0462000e+00 + 2.0462000e+00 + 2.0460657e+00 + 2.0446594e+00 + 2.0403895e+00 + 2.0316620e+00 + 2.0168831e+00 + 1.9944587e+00 + 1.9627949e+00 + 1.9202980e+00 + 1.8654077e+00 + 1.7985181e+00 + 1.7230065e+00 + 1.6425015e+00 + 1.5606319e+00 + 1.4810262e+00 + 1.4073131e+00 + 1.3431214e+00 + 1.2920798e+00 + 1.2569864e+00 + 1.2358842e+00 + 1.2251262e+00 + 1.2210637e+00 + 1.2200475e+00 + 1.2184289e+00 + 1.2125589e+00 + 1.1987885e+00 + 1.1735526e+00 + 1.1361263e+00 + 1.0892520e+00 + 1.0358822e+00 + 9.7896980e-01 + 9.2146751e-01 + 8.6632806e-01 + 8.1650421e-01 + 7.7494869e-01 + 7.4388695e-01 + 7.2232357e-01 + 7.0837184e-01 + 7.0014504e-01 + 6.9575642e-01 + 6.9331925e-01 + 6.9094679e-01 + 6.8675230e-01 + 6.7890996e-01 + 6.6694075e-01 + 6.5168297e-01 + 6.3402998e-01 + 6.1487512e-01 + 5.9511173e-01 + 5.7563315e-01 + 5.5733272e-01 + 5.4110376e-01 + 5.2756220e-01 + 5.1637106e-01 + 5.0698887e-01 + 4.9887416e-01 + 4.9148546e-01 + 4.8428132e-01 + 4.7672025e-01 + 4.6826081e-01 + 4.5839485e-01 + 4.4712673e-01 + 4.3486244e-01 + 4.2201868e-01 + 4.0901218e-01 + 3.9625966e-01 + 3.8417784e-01 + 3.7318344e-01 + 3.6369286e-01 + 3.5593854e-01 + 3.4965997e-01 + 3.4451493e-01 + 3.4016124e-01 + 3.3625667e-01 + 3.3245903e-01 + 3.2842610e-01 + 3.2381569e-01 + 3.1831627e-01 + 3.1195884e-01 + 3.0498880e-01 + 2.9765482e-01 + 2.9020560e-01 + 2.8288981e-01 + 2.7595615e-01 + 2.6965328e-01 + 2.6422884e-01 + 2.5975489e-01 + 2.5593343e-01 + 2.5241954e-01 + 2.4886832e-01 + 2.4493489e-01 + 2.4027433e-01 + 2.3454175e-01 + 2.2739225e-01 + 2.1853384e-01 + 2.0811604e-01 + 1.9650791e-01 + 1.8408007e-01 + 1.7120316e-01 + 1.5824783e-01 + 1.4558470e-01 + 1.3358442e-01 + 1.2261513e-01 + 1.1286044e-01 + 1.0419542e-01 + 9.6465750e-02 + 8.9517133e-02 + 8.3195263e-02 + 7.7345836e-02 + 7.1814548e-02 + 6.6447095e-02 + 6.1107588e-02 + 5.5777274e-02 + 5.0483296e-02 + 4.5252904e-02 + 4.0113348e-02 + 3.5091878e-02 + 3.0215745e-02 + 2.5512199e-02 + 2.1008131e-02 + 1.6715617e-02 + 1.2626961e-02 + 8.7330951e-03 + 5.0249487e-03 + 1.4934524e-03 +-1.8704635e-03 +-5.0758685e-03 +-8.1318323e-03 +-1.1043079e-02 +-1.3793016e-02 +-1.6358529e-02 +-1.8716498e-02 +-2.0843807e-02 +-2.2717336e-02 +-2.4313969e-02 +-2.5610588e-02 +-2.6585188e-02 +-2.7244724e-02 +-2.7627095e-02 +-2.7771713e-02 +-2.7717987e-02 +-2.7505328e-02 +-2.7173148e-02 +-2.6760858e-02 +-2.6307867e-02 +-2.5841384e-02 +-2.5342224e-02 +-2.4780181e-02 +-2.4125047e-02 +-2.3346614e-02 +-2.2414676e-02 +-2.1299025e-02 +-1.9969454e-02 +-1.8398136e-02 +-1.6599321e-02 +-1.4623294e-02 +-1.2521505e-02 +-1.0345403e-02 +-8.1464389e-03 +-5.9760622e-03 +-3.8857229e-03 +-1.9268610e-03 +-1.3832164e-04 + 1.4782888e-03 + 2.9282133e-03 + 4.2166947e-03 + 5.3489760e-03 + 6.3303000e-03 + 7.1659097e-03 + 7.8610481e-03 + 8.4198995e-03 + 8.8332749e-03 + 9.0828227e-03 + 9.1500123e-03 + 9.0163131e-03 + 8.6631948e-03 + 8.0721268e-03 + 7.2245785e-03 + 6.1021765e-03 + 4.7263503e-03 + 3.2107872e-03 + 1.6822100e-03 + 2.6734188e-04 +-9.0709423e-04 +-1.7143753e-03 +-2.0277783e-03 +-1.7205802e-03 +-6.8297710e-04 + 1.0366865e-03 + 3.3037777e-03 + 5.9827919e-03 + 8.9382246e-03 + 1.2034571e-02 + 1.5136327e-02 + 1.8107989e-02 + 2.0814846e-02 + 2.3201015e-02 + 2.5355075e-02 + 2.7381061e-02 + 2.9383010e-02 + 3.1464956e-02 + 3.3730934e-02 + 3.6284981e-02 + 3.9231132e-02 + 4.2657484e-02 + 4.6539348e-02 + 5.0803371e-02 + 5.5376010e-02 + 6.0183720e-02 + 6.5152959e-02 + 7.0210181e-02 + 7.5281844e-02 + 8.0295485e-02 + 8.5234073e-02 + 9.0161482e-02 + 9.5147990e-02 + 1.0026387e-01 + 1.0557941e-01 + 1.1116488e-01 + 1.1709056e-01 + 1.2342672e-01 + 1.3023047e-01 + 1.3748721e-01 + 1.4515813e-01 + 1.5320437e-01 + 1.6158708e-01 + 1.7026744e-01 + 1.7920658e-01 + 1.8836566e-01 + 1.9770732e-01 + 2.0723997e-01 + 2.1702545e-01 + 2.2712865e-01 + 2.3761445e-01 + 2.4854771e-01 + 2.5999332e-01 + 2.7201616e-01 + 2.8468110e-01 + 2.9803349e-01 + 3.1203651e-01 + 3.2663170e-01 + 3.4176062e-01 + 3.5736482e-01 + 3.7338585e-01 + 3.8976527e-01 + 4.0644463e-01 + 4.2336952e-01 + 4.4056834e-01 + 4.5814698e-01 + 4.7621428e-01 + 4.9487913e-01 + 5.1425038e-01 + 5.3443688e-01 + 5.5554751e-01 + 5.7769109e-01 + 6.0087457e-01 + 6.2477197e-01 + 6.4898945e-01 + 6.7313316e-01 + 6.9680926e-01 + 7.1962391e-01 + 7.4118326e-01 + 7.6109347e-01 + 7.7900642e-01 + 7.9523128e-01 + 8.1056985e-01 + 8.2583586e-01 + 8.4184302e-01 + 8.5940505e-01 + 8.7933568e-01 + 9.0244863e-01 + 9.2955610e-01 + 9.6082471e-01 + 9.9477338e-01 + 1.0296620e+00 + 1.0637504e+00 + 1.0952986e+00 + 1.1225663e+00 + 1.1438135e+00 + 1.1573000e+00 + 1.1615947e+00 + 1.1585131e+00 + 1.1518130e+00 + 1.1452779e+00 + 1.1426915e+00 + 1.1478376e+00 + 1.1644998e+00 + 1.1964617e+00 + 1.2474884e+00 + 1.3187459e+00 + 1.4061740e+00 + 1.5050862e+00 + 1.6107957e+00 + 1.7186160e+00 + 1.8238603e+00 + 1.9218422e+00 + 2.0078748e+00 + 2.0778069e+00 + 2.1317113e+00 + 2.1716651e+00 + 2.1997574e+00 + 2.2180771e+00 + 2.2287133e+00 + 2.2337551e+00 + 2.2352915e+00 + 2.2354000e+00 + 2.2354000e+00 + 2.2354000e+00 + 2.2354000e+00 + 2.2354000e+00 + 2.2354000e+00 + 2.2354000e+00 + 2.2354000e+00 + 2.2354000e+00 + 2.2354000e+00 + 2.2354000e+00 + 2.2354000e+00 + 2.2354000e+00 + 2.2354000e+00 + 2.2354000e+00 + 2.2354000e+00 + 2.2354000e+00 + 2.2354000e+00 + 2.2354000e+00 + 2.2354000e+00 + 2.2354000e+00 + 2.2354000e+00 + 2.2354000e+00 + 2.2354000e+00 + 2.2354000e+00 + 2.2354000e+00 + 2.2354000e+00 + 2.2354000e+00 + 2.2354000e+00 + 2.2354000e+00 + 2.2354000e+00 + 2.2354000e+00 + 2.2354000e+00 + 2.2354000e+00 + 2.2354000e+00 + 2.2354000e+00 + 2.2354000e+00 + 2.2354000e+00 + 2.2354000e+00 + 2.2354000e+00 + 2.2354000e+00 + 2.2354000e+00 + 2.2354000e+00 + 2.2354000e+00 + 2.2354000e+00 + 2.2354000e+00 + 2.2354000e+00 + 2.2354000e+00 + 2.2354000e+00 + 2.2354000e+00 + 2.2354000e+00 + 2.2354000e+00 + 2.2354000e+00 + 2.2354000e+00 + 2.2354000e+00 + 2.2354000e+00 + 2.2354000e+00 + 2.2354000e+00 + 2.2354000e+00 + 2.2354000e+00 + 2.2354000e+00 + 2.2354000e+00 + 2.2354000e+00 + 2.2354000e+00 + 2.2354000e+00 + 2.2354000e+00 + 2.2354000e+00 + 2.2354000e+00 + 2.2354000e+00 + 2.2354000e+00 + 2.2354000e+00 + 2.2354000e+00 + 2.2354000e+00 + 2.2354000e+00 + 2.2354000e+00 + 2.2354000e+00 + 2.2354000e+00 + 2.2354000e+00 + 2.2354000e+00 + 2.2354000e+00 + 2.2354000e+00 + 2.2354000e+00 + 2.2354000e+00 + 2.2354000e+00 + 2.2354000e+00 + 2.2354000e+00 + 2.2354000e+00 + 2.2354000e+00 + 2.2354000e+00 + 2.2354000e+00 + 2.2354000e+00 + 2.2354000e+00 + 2.2354000e+00 + 2.2354000e+00 + 2.2354000e+00 + 2.2354000e+00 + 2.2354000e+00 + 2.2354000e+00 + 2.2354000e+00 + 2.2354000e+00 + 2.2354000e+00 + 2.2354000e+00 + 2.2354000e+00 + 2.2354000e+00 + 2.2354000e+00 + 2.2354000e+00 + 2.2354000e+00 + 2.2354000e+00 + 2.2354000e+00 + 2.2354000e+00 + 2.2354000e+00 + 2.2354000e+00 + 2.2354000e+00 + 2.2354000e+00 + 2.2354000e+00 + 2.2354000e+00 + 2.2354000e+00 + 2.2354000e+00 + 2.2354000e+00 + 2.2354000e+00 + 2.2354000e+00 + 2.2354000e+00 + 2.2354000e+00 + 2.2354000e+00 + 2.2354000e+00 + 2.2354000e+00 + 2.2354000e+00 + 2.2354000e+00 + 2.2354000e+00 + 2.2354000e+00 + 2.2354000e+00 + 2.2354000e+00 + 2.2354000e+00 + 2.2354000e+00 + 2.2354000e+00 + 2.2354000e+00 + + 4.5000000e+00 5.5000000e+00 +1 +2 + 0.0000000e+00 2.0000000e+01 4.0080160e-02 +-4.5439333e-01 +-4.5217352e-01 +-4.4584312e-01 +-4.3589567e-01 +-4.2282471e-01 +-4.0712378e-01 +-3.8928644e-01 +-3.6980622e-01 +-3.4917666e-01 +-3.2789131e-01 +-3.0644372e-01 +-2.8532742e-01 +-2.6503595e-01 +-2.4606287e-01 +-2.2890171e-01 +-2.1404601e-01 +-2.0198933e-01 +-1.9322519e-01 +-1.8817750e-01 +-1.8674377e-01 +-1.8858102e-01 +-1.9334503e-01 +-2.0069158e-01 +-2.1027643e-01 +-2.2175537e-01 +-2.3478417e-01 +-2.4901861e-01 +-2.6411447e-01 +-2.7972752e-01 +-2.9551355e-01 +-3.1112832e-01 +-3.2622761e-01 +-3.4046720e-01 +-3.5350288e-01 +-3.6499040e-01 +-3.7460270e-01 +-3.8228379e-01 +-3.8819407e-01 +-3.9249997e-01 +-3.9536792e-01 +-3.9696436e-01 +-3.9745571e-01 +-3.9700841e-01 +-3.9578890e-01 +-3.9396360e-01 +-3.9169894e-01 +-3.8916137e-01 +-3.8651730e-01 +-3.8393317e-01 +-3.8157542e-01 +-3.7961047e-01 +-3.7820477e-01 +-3.7752265e-01 +-3.7763665e-01 +-3.7849337e-01 +-3.8003026e-01 +-3.8218478e-01 +-3.8489440e-01 +-3.8809657e-01 +-3.9172876e-01 +-3.9572843e-01 +-4.0003303e-01 +-4.0458004e-01 +-4.0930690e-01 +-4.1415108e-01 +-4.1905005e-01 +-4.2394126e-01 +-4.2876217e-01 +-4.3345025e-01 +-4.3794302e-01 +-4.4219923e-01 +-4.4622885e-01 +-4.5004938e-01 +-4.5367833e-01 +-4.5713320e-01 +-4.6043152e-01 +-4.6359079e-01 +-4.6662853e-01 +-4.6956224e-01 +-4.7240943e-01 +-4.7518762e-01 +-4.7791432e-01 +-4.8060703e-01 +-4.8328327e-01 +-4.8596055e-01 +-4.8865638e-01 +-4.9138828e-01 +-4.9417165e-01 +-4.9701271e-01 +-4.9991507e-01 +-5.0288236e-01 +-5.0591822e-01 +-5.0902626e-01 +-5.1221011e-01 +-5.1547341e-01 +-5.1881977e-01 +-5.2225283e-01 +-5.2577622e-01 +-5.2939355e-01 +-5.3310847e-01 +-5.3692459e-01 +-5.4084554e-01 +-5.4487496e-01 +-5.4901646e-01 +-5.5327164e-01 +-5.5762480e-01 +-5.6205157e-01 +-5.6652752e-01 +-5.7102819e-01 +-5.7552916e-01 +-5.8000598e-01 +-5.8443421e-01 +-5.8878941e-01 +-5.9304715e-01 +-5.9718298e-01 +-6.0117246e-01 +-6.0499116e-01 +-6.0861463e-01 +-6.1201843e-01 +-6.1517813e-01 +-6.1806928e-01 +-6.2066863e-01 +-6.2297441e-01 +-6.2500366e-01 +-6.2677405e-01 +-6.2830323e-01 +-6.2960887e-01 +-6.3070863e-01 +-6.3162019e-01 +-6.3236119e-01 +-6.3294931e-01 +-6.3340221e-01 +-6.3373756e-01 +-6.3397301e-01 +-6.3412623e-01 +-6.3421489e-01 +-6.3425665e-01 +-6.3426917e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 +-6.3427000e-01 + + 4.5000000e+00 5.5000000e+00 +2 +1 + 0.0000000e+00 2.0000000e+01 4.0080160e-02 +-6.9546667e-02 +-6.9188143e-02 +-6.8087841e-02 +-6.6208660e-02 +-6.3513504e-02 +-5.9965274e-02 +-5.5526872e-02 +-5.0161199e-02 +-4.3831156e-02 +-3.6499647e-02 +-2.8129571e-02 +-1.8683832e-02 +-8.1253303e-03 + 3.5830320e-03 + 1.6478353e-02 + 3.0597732e-02 + 4.5978266e-02 + 6.2657054e-02 + 8.0655930e-02 + 9.9881386e-02 + 1.2018721e-01 + 1.4142692e-01 + 1.6345403e-01 + 1.8612206e-01 + 2.0928452e-01 + 2.3279493e-01 + 2.5650681e-01 + 2.8027368e-01 + 3.0394904e-01 + 3.2738642e-01 + 3.5043934e-01 + 3.7296131e-01 + 3.9480584e-01 + 4.1582646e-01 + 4.3587668e-01 + 4.5481768e-01 + 4.7263181e-01 + 4.8939812e-01 + 5.0519838e-01 + 5.2011434e-01 + 5.3422776e-01 + 5.4762041e-01 + 5.6037402e-01 + 5.7257037e-01 + 5.8429121e-01 + 5.9561831e-01 + 6.0663340e-01 + 6.1741826e-01 + 6.2805465e-01 + 6.3862431e-01 + 6.4920901e-01 + 6.5989050e-01 + 6.7074956e-01 + 6.8182350e-01 + 6.9309002e-01 + 7.0452250e-01 + 7.1609432e-01 + 7.2777886e-01 + 7.3954950e-01 + 7.5137962e-01 + 7.6324259e-01 + 7.7511180e-01 + 7.8696063e-01 + 7.9876245e-01 + 8.1049065e-01 + 8.2211860e-01 + 8.3361969e-01 + 8.4496729e-01 + 8.5613478e-01 + 8.6709556e-01 + 8.7782560e-01 + 8.8830714e-01 + 8.9852336e-01 + 9.0845742e-01 + 9.1809248e-01 + 9.2741172e-01 + 9.3639829e-01 + 9.4503537e-01 + 9.5330612e-01 + 9.6119370e-01 + 9.6868129e-01 + 9.7575205e-01 + 9.8238915e-01 + 9.8857575e-01 + 9.9429502e-01 + 9.9953012e-01 + 1.0042642e+00 + 1.0084875e+00 + 1.0122215e+00 + 1.0154963e+00 + 1.0183421e+00 + 1.0207889e+00 + 1.0228669e+00 + 1.0246062e+00 + 1.0260369e+00 + 1.0271893e+00 + 1.0280933e+00 + 1.0287791e+00 + 1.0292770e+00 + 1.0296169e+00 + 1.0298290e+00 + 1.0299435e+00 + 1.0299904e+00 + 1.0299999e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + 1.0300000e+00 + diff --git a/examples/USER/misc/local_density/benzene_water/benzene_water.pair.table b/examples/USER/misc/local_density/benzene_water/benzene_water.pair.table new file mode 100644 index 0000000000..348bccfa0e --- /dev/null +++ b/examples/USER/misc/local_density/benzene_water/benzene_water.pair.table @@ -0,0 +1,2024 @@ + +PairBB +N 500 R 2.00000e-02 1.32500e+01 + +1 2.00000e-02 2.96754e+01 5.54271e+00 +2 4.65130e-02 2.95284e+01 5.54271e+00 +3 7.30261e-02 2.93814e+01 5.54271e+00 +4 9.95391e-02 2.92345e+01 5.54271e+00 +5 1.26052e-01 2.90875e+01 5.54271e+00 +6 1.52565e-01 2.89406e+01 5.54271e+00 +7 1.79078e-01 2.87936e+01 5.54271e+00 +8 2.05591e-01 2.86467e+01 5.54271e+00 +9 2.32104e-01 2.84997e+01 5.54271e+00 +10 2.58617e-01 2.83528e+01 5.54271e+00 +11 2.85130e-01 2.82058e+01 5.54271e+00 +12 3.11643e-01 2.80589e+01 5.54271e+00 +13 3.38156e-01 2.79119e+01 5.54271e+00 +14 3.64669e-01 2.77650e+01 5.54271e+00 +15 3.91182e-01 2.76180e+01 5.54271e+00 +16 4.17695e-01 2.74710e+01 5.54271e+00 +17 4.44208e-01 2.73241e+01 5.54271e+00 +18 4.70721e-01 2.71771e+01 5.54271e+00 +19 4.97234e-01 2.70302e+01 5.54271e+00 +20 5.23747e-01 2.68832e+01 5.54271e+00 +21 5.50261e-01 2.67363e+01 5.54271e+00 +22 5.76774e-01 2.65893e+01 5.54271e+00 +23 6.03287e-01 2.64424e+01 5.54271e+00 +24 6.29800e-01 2.62954e+01 5.54271e+00 +25 6.56313e-01 2.61485e+01 5.54271e+00 +26 6.82826e-01 2.60015e+01 5.54271e+00 +27 7.09339e-01 2.58546e+01 5.54271e+00 +28 7.35852e-01 2.57076e+01 5.54271e+00 +29 7.62365e-01 2.55606e+01 5.54271e+00 +30 7.88878e-01 2.54137e+01 5.54271e+00 +31 8.15391e-01 2.52667e+01 5.54271e+00 +32 8.41904e-01 2.51198e+01 5.54271e+00 +33 8.68417e-01 2.49728e+01 5.54271e+00 +34 8.94930e-01 2.48259e+01 5.54271e+00 +35 9.21443e-01 2.46789e+01 5.54271e+00 +36 9.47956e-01 2.45320e+01 5.54271e+00 +37 9.74469e-01 2.43850e+01 5.54271e+00 +38 1.00098e+00 2.42381e+01 5.54271e+00 +39 1.02749e+00 2.40911e+01 5.54271e+00 +40 1.05401e+00 2.39441e+01 5.54271e+00 +41 1.08052e+00 2.37972e+01 5.54271e+00 +42 1.10703e+00 2.36502e+01 5.54271e+00 +43 1.13355e+00 2.35033e+01 5.54271e+00 +44 1.16006e+00 2.33563e+01 5.54271e+00 +45 1.18657e+00 2.32094e+01 5.54271e+00 +46 1.21309e+00 2.30624e+01 5.54271e+00 +47 1.23960e+00 2.29155e+01 5.54271e+00 +48 1.26611e+00 2.27685e+01 5.54271e+00 +49 1.29263e+00 2.26216e+01 5.54271e+00 +50 1.31914e+00 2.24746e+01 5.54271e+00 +51 1.34565e+00 2.23277e+01 5.54271e+00 +52 1.37216e+00 2.21807e+01 5.54271e+00 +53 1.39868e+00 2.20337e+01 5.54271e+00 +54 1.42519e+00 2.18868e+01 5.54271e+00 +55 1.45170e+00 2.17398e+01 5.54271e+00 +56 1.47822e+00 2.15929e+01 5.54271e+00 +57 1.50473e+00 2.14459e+01 5.54271e+00 +58 1.53124e+00 2.12990e+01 5.54271e+00 +59 1.55776e+00 2.11520e+01 5.54271e+00 +60 1.58427e+00 2.10051e+01 5.54271e+00 +61 1.61078e+00 2.08581e+01 5.54271e+00 +62 1.63729e+00 2.07112e+01 5.54271e+00 +63 1.66381e+00 2.05642e+01 5.54271e+00 +64 1.69032e+00 2.04173e+01 5.54271e+00 +65 1.71683e+00 2.02703e+01 5.54271e+00 +66 1.74335e+00 2.01233e+01 5.54271e+00 +67 1.76986e+00 1.99764e+01 5.54271e+00 +68 1.79637e+00 1.98294e+01 5.54271e+00 +69 1.82289e+00 1.96825e+01 5.54271e+00 +70 1.84940e+00 1.95355e+01 5.54271e+00 +71 1.87591e+00 1.93886e+01 5.54271e+00 +72 1.90242e+00 1.92416e+01 5.54271e+00 +73 1.92894e+00 1.90947e+01 5.54271e+00 +74 1.95545e+00 1.89477e+01 5.54271e+00 +75 1.98196e+00 1.88008e+01 5.54271e+00 +76 2.00848e+00 1.86538e+01 5.54271e+00 +77 2.03499e+00 1.85069e+01 5.54271e+00 +78 2.06150e+00 1.83599e+01 5.54271e+00 +79 2.08802e+00 1.82129e+01 5.54271e+00 +80 2.11453e+00 1.80660e+01 5.54271e+00 +81 2.14104e+00 1.79190e+01 5.54271e+00 +82 2.16756e+00 1.77721e+01 5.54271e+00 +83 2.19407e+00 1.76251e+01 5.54271e+00 +84 2.22058e+00 1.74782e+01 5.54271e+00 +85 2.24709e+00 1.73312e+01 5.54271e+00 +86 2.27361e+00 1.71843e+01 5.54271e+00 +87 2.30012e+00 1.70373e+01 5.54271e+00 +88 2.32663e+00 1.68904e+01 5.54271e+00 +89 2.35315e+00 1.67434e+01 5.54271e+00 +90 2.37966e+00 1.65965e+01 5.54271e+00 +91 2.40617e+00 1.64495e+01 5.54271e+00 +92 2.43269e+00 1.63025e+01 5.54271e+00 +93 2.45920e+00 1.61556e+01 5.54271e+00 +94 2.48571e+00 1.60086e+01 5.54271e+00 +95 2.51222e+00 1.58617e+01 5.54271e+00 +96 2.53874e+00 1.57147e+01 5.54271e+00 +97 2.56525e+00 1.55678e+01 5.54271e+00 +98 2.59176e+00 1.54208e+01 5.54271e+00 +99 2.61828e+00 1.52739e+01 5.54271e+00 +100 2.64479e+00 1.51269e+01 5.54271e+00 +101 2.67130e+00 1.49800e+01 5.54271e+00 +102 2.69782e+00 1.48330e+01 5.54271e+00 +103 2.72433e+00 1.46861e+01 5.54271e+00 +104 2.75084e+00 1.45391e+01 5.54271e+00 +105 2.77735e+00 1.43921e+01 5.54271e+00 +106 2.80387e+00 1.42452e+01 5.54271e+00 +107 2.83038e+00 1.40982e+01 5.54271e+00 +108 2.85689e+00 1.39513e+01 5.54271e+00 +109 2.88341e+00 1.38043e+01 5.54271e+00 +110 2.90992e+00 1.36574e+01 5.54271e+00 +111 2.93643e+00 1.35104e+01 5.54271e+00 +112 2.96295e+00 1.33635e+01 5.54271e+00 +113 2.98946e+00 1.32165e+01 5.54271e+00 +114 3.01597e+00 1.30696e+01 5.54271e+00 +115 3.04248e+00 1.29226e+01 5.54271e+00 +116 3.06900e+00 1.27757e+01 5.54271e+00 +117 3.09551e+00 1.26287e+01 5.54271e+00 +118 3.12202e+00 1.24817e+01 5.54271e+00 +119 3.14854e+00 1.23348e+01 5.54271e+00 +120 3.17505e+00 1.21878e+01 5.54271e+00 +121 3.20156e+00 1.20409e+01 5.54271e+00 +122 3.22808e+00 1.18939e+01 5.54271e+00 +123 3.25459e+00 1.17470e+01 5.54273e+00 +124 3.28110e+00 1.16000e+01 5.54277e+00 +125 3.30762e+00 1.14531e+01 5.54280e+00 +126 3.33413e+00 1.13061e+01 5.54285e+00 +127 3.36064e+00 1.11591e+01 5.54289e+00 +128 3.38715e+00 1.10122e+01 5.54295e+00 +129 3.41367e+00 1.08652e+01 5.54300e+00 +130 3.44018e+00 1.07183e+01 5.54306e+00 +131 3.46669e+00 1.05713e+01 5.54313e+00 +132 3.49321e+00 1.04243e+01 5.54320e+00 +133 3.51972e+00 1.02774e+01 5.54328e+00 +134 3.54623e+00 1.01304e+01 5.54336e+00 +135 3.57275e+00 9.98342e+00 5.54343e+00 +136 3.59926e+00 9.83645e+00 5.54350e+00 +137 3.62577e+00 9.68947e+00 5.54356e+00 +138 3.65228e+00 9.54250e+00 5.54361e+00 +139 3.67880e+00 9.39552e+00 5.54366e+00 +140 3.70531e+00 9.24854e+00 5.54370e+00 +141 3.73182e+00 9.10156e+00 5.54373e+00 +142 3.75834e+00 8.95458e+00 5.54375e+00 +143 3.78485e+00 8.80759e+00 5.54376e+00 +144 3.81136e+00 8.66061e+00 5.54377e+00 +145 3.83788e+00 8.51363e+00 5.54377e+00 +146 3.86439e+00 8.36665e+00 5.54377e+00 +147 3.89090e+00 8.21967e+00 5.54375e+00 +148 3.91741e+00 8.07268e+00 5.54373e+00 +149 3.94393e+00 7.92570e+00 5.54370e+00 +150 3.97044e+00 7.77872e+00 5.54367e+00 +151 3.99695e+00 7.63175e+00 5.54363e+00 +152 4.02347e+00 7.48477e+00 5.54359e+00 +153 4.04998e+00 7.33779e+00 5.54356e+00 +154 4.07649e+00 7.19081e+00 5.54353e+00 +155 4.10301e+00 7.04384e+00 5.54350e+00 +156 4.12952e+00 6.89686e+00 5.54348e+00 +157 4.15603e+00 6.74989e+00 5.54346e+00 +158 4.18255e+00 6.60292e+00 5.54344e+00 +159 4.20906e+00 6.45594e+00 5.54343e+00 +160 4.23557e+00 6.30897e+00 5.54342e+00 +161 4.26208e+00 6.16200e+00 5.54341e+00 +162 4.28860e+00 6.01503e+00 5.54341e+00 +163 4.31511e+00 5.86805e+00 5.54341e+00 +164 4.34162e+00 5.72108e+00 5.54341e+00 +165 4.36814e+00 5.57411e+00 5.54341e+00 +166 4.39465e+00 5.42714e+00 5.54342e+00 +167 4.42116e+00 5.28016e+00 5.54323e+00 +168 4.44768e+00 5.13329e+00 5.53372e+00 +169 4.47419e+00 4.98686e+00 5.50998e+00 +170 4.50070e+00 4.84124e+00 5.47202e+00 +171 4.52721e+00 4.69682e+00 5.41984e+00 +172 4.55373e+00 4.55398e+00 5.35343e+00 +173 4.58024e+00 4.41308e+00 5.27279e+00 +174 4.60675e+00 4.27451e+00 5.17793e+00 +175 4.63327e+00 4.13864e+00 5.06884e+00 +176 4.65978e+00 4.00585e+00 4.94553e+00 +177 4.68629e+00 3.87652e+00 4.80799e+00 +178 4.71281e+00 3.75103e+00 4.65623e+00 +179 4.73932e+00 3.62975e+00 4.49024e+00 +180 4.76583e+00 3.51305e+00 4.31003e+00 +181 4.79234e+00 3.40133e+00 4.11559e+00 +182 4.81886e+00 3.29495e+00 3.90693e+00 +183 4.84537e+00 3.19429e+00 3.68404e+00 +184 4.87188e+00 3.09971e+00 3.45062e+00 +185 4.89840e+00 3.01120e+00 3.22791e+00 +186 4.92491e+00 2.92842e+00 3.01927e+00 +187 4.95142e+00 2.85098e+00 2.82473e+00 +188 4.97794e+00 2.77851e+00 2.64426e+00 +189 5.00445e+00 2.71064e+00 2.47788e+00 +190 5.03096e+00 2.64699e+00 2.32559e+00 +191 5.05747e+00 2.58720e+00 2.18738e+00 +192 5.08399e+00 2.53088e+00 2.06325e+00 +193 5.11050e+00 2.47767e+00 1.95321e+00 +194 5.13701e+00 2.42718e+00 1.85725e+00 +195 5.16353e+00 2.37906e+00 1.77537e+00 +196 5.19004e+00 2.33292e+00 1.70758e+00 +197 5.21655e+00 2.28839e+00 1.65387e+00 +198 5.24307e+00 2.24510e+00 1.61425e+00 +199 5.26958e+00 2.20267e+00 1.58871e+00 +200 5.29609e+00 2.16073e+00 1.57725e+00 +201 5.32261e+00 2.11895e+00 1.57397e+00 +202 5.34912e+00 2.07729e+00 1.56868e+00 +203 5.37563e+00 2.03579e+00 1.56122e+00 +204 5.40214e+00 1.99452e+00 1.55158e+00 +205 5.42866e+00 1.95354e+00 1.53975e+00 +206 5.45517e+00 1.91289e+00 1.52575e+00 +207 5.48168e+00 1.87265e+00 1.50957e+00 +208 5.50820e+00 1.83287e+00 1.49121e+00 +209 5.53471e+00 1.79360e+00 1.47067e+00 +210 5.56122e+00 1.75490e+00 1.44795e+00 +211 5.58774e+00 1.71684e+00 1.42305e+00 +212 5.61425e+00 1.67946e+00 1.39597e+00 +213 5.64076e+00 1.64283e+00 1.36671e+00 +214 5.66727e+00 1.60701e+00 1.33528e+00 +215 5.69379e+00 1.57205e+00 1.30166e+00 +216 5.72030e+00 1.53801e+00 1.26587e+00 +217 5.74681e+00 1.50494e+00 1.22792e+00 +218 5.77333e+00 1.47290e+00 1.18886e+00 +219 5.79984e+00 1.44191e+00 1.14919e+00 +220 5.82635e+00 1.41197e+00 1.10891e+00 +221 5.85287e+00 1.38311e+00 1.06803e+00 +222 5.87938e+00 1.35534e+00 1.02654e+00 +223 5.90589e+00 1.32868e+00 9.84442e-01 +224 5.93240e+00 1.30315e+00 9.41738e-01 +225 5.95892e+00 1.27875e+00 8.98427e-01 +226 5.98543e+00 1.25551e+00 8.54508e-01 +227 6.01194e+00 1.23345e+00 8.09983e-01 +228 6.03846e+00 1.21257e+00 7.64850e-01 +229 6.06497e+00 1.19290e+00 7.19111e-01 +230 6.09148e+00 1.17444e+00 6.72764e-01 +231 6.11800e+00 1.15723e+00 6.25811e-01 +232 6.14451e+00 1.14126e+00 5.78250e-01 +233 6.17102e+00 1.12657e+00 5.30082e-01 +234 6.19754e+00 1.11316e+00 4.82247e-01 +235 6.22405e+00 1.10095e+00 4.39648e-01 +236 6.25056e+00 1.08979e+00 4.02990e-01 +237 6.27707e+00 1.07953e+00 3.72273e-01 +238 6.30359e+00 1.07000e+00 3.47498e-01 +239 6.33010e+00 1.06105e+00 3.28665e-01 +240 6.35661e+00 1.05252e+00 3.15774e-01 +241 6.38313e+00 1.04425e+00 3.08824e-01 +242 6.40964e+00 1.03609e+00 3.07815e-01 +243 6.43615e+00 1.02788e+00 3.12748e-01 +244 6.46267e+00 1.01945e+00 3.23623e-01 +245 6.48918e+00 1.01066e+00 3.40440e-01 +246 6.51569e+00 1.00135e+00 3.63198e-01 +247 6.54220e+00 9.91353e-01 3.91897e-01 +248 6.56872e+00 9.80516e-01 4.26538e-01 +249 6.59523e+00 9.68683e-01 4.67121e-01 +250 6.62174e+00 9.55694e-01 5.13646e-01 +251 6.64826e+00 9.41422e-01 5.62501e-01 +252 6.67477e+00 9.25897e-01 6.07985e-01 +253 6.70128e+00 9.09213e-01 6.50027e-01 +254 6.72780e+00 8.91459e-01 6.88626e-01 +255 6.75431e+00 8.72728e-01 7.23783e-01 +256 6.78082e+00 8.53111e-01 7.55497e-01 +257 6.80733e+00 8.32698e-01 7.83768e-01 +258 6.83385e+00 8.11581e-01 8.08597e-01 +259 6.86036e+00 7.89851e-01 8.29984e-01 +260 6.88687e+00 7.67601e-01 8.47928e-01 +261 6.91339e+00 7.44920e-01 8.62429e-01 +262 6.93990e+00 7.21900e-01 8.73488e-01 +263 6.96641e+00 6.98632e-01 8.81104e-01 +264 6.99293e+00 6.75209e-01 8.85278e-01 +265 7.01944e+00 6.51720e-01 8.86010e-01 +266 7.04595e+00 6.28258e-01 8.83299e-01 +267 7.07246e+00 6.04913e-01 8.77168e-01 +268 7.09898e+00 5.81769e-01 8.68269e-01 +269 7.12549e+00 5.58894e-01 8.56896e-01 +270 7.15200e+00 5.36353e-01 8.43051e-01 +271 7.17852e+00 5.14212e-01 8.26732e-01 +272 7.20503e+00 4.92536e-01 8.07941e-01 +273 7.23154e+00 4.71392e-01 7.86676e-01 +274 7.25806e+00 4.50844e-01 7.62938e-01 +275 7.28457e+00 4.30958e-01 7.36728e-01 +276 7.31108e+00 4.11800e-01 7.08044e-01 +277 7.33760e+00 3.93435e-01 6.76887e-01 +278 7.36411e+00 3.75929e-01 6.43257e-01 +279 7.39062e+00 3.59347e-01 6.07154e-01 +280 7.41713e+00 3.43756e-01 5.68578e-01 +281 7.44365e+00 3.29220e-01 5.27528e-01 +282 7.47016e+00 3.15805e-01 4.84006e-01 +283 7.49667e+00 3.03577e-01 4.38011e-01 +284 7.52319e+00 2.92596e-01 3.90579e-01 +285 7.54970e+00 2.82832e-01 3.46637e-01 +286 7.57621e+00 2.74178e-01 3.06826e-01 +287 7.60273e+00 2.66526e-01 2.71144e-01 +288 7.62924e+00 2.59764e-01 2.39591e-01 +289 7.65575e+00 2.53785e-01 2.12169e-01 +290 7.68226e+00 2.48477e-01 1.88875e-01 +291 7.70878e+00 2.43733e-01 1.69712e-01 +292 7.73529e+00 2.39442e-01 1.54678e-01 +293 7.76180e+00 2.35494e-01 1.43773e-01 +294 7.78832e+00 2.31781e-01 1.36998e-01 +295 7.81483e+00 2.28193e-01 1.34353e-01 +296 7.84134e+00 2.24621e-01 1.35837e-01 +297 7.86786e+00 2.20954e-01 1.41451e-01 +298 7.89437e+00 2.17084e-01 1.51194e-01 +299 7.92088e+00 2.12900e-01 1.65067e-01 +300 7.94739e+00 2.08294e-01 1.83070e-01 +301 7.97391e+00 2.03177e-01 2.02650e-01 +302 8.00042e+00 1.97568e-01 2.20114e-01 +303 8.02693e+00 1.91524e-01 2.35430e-01 +304 8.05345e+00 1.85103e-01 2.48600e-01 +305 8.07996e+00 1.78361e-01 2.59623e-01 +306 8.10647e+00 1.71355e-01 2.68499e-01 +307 8.13299e+00 1.64142e-01 2.75228e-01 +308 8.15950e+00 1.56780e-01 2.79809e-01 +309 8.18601e+00 1.49324e-01 2.82244e-01 +310 8.21253e+00 1.41832e-01 2.82532e-01 +311 8.23904e+00 1.34361e-01 2.80673e-01 +312 8.26555e+00 1.26968e-01 2.76667e-01 +313 8.29206e+00 1.19710e-01 2.70514e-01 +314 8.31858e+00 1.12643e-01 2.62214e-01 +315 8.34509e+00 1.05825e-01 2.51767e-01 +316 8.37160e+00 9.93116e-02 2.39174e-01 +317 8.39812e+00 9.31609e-02 2.24523e-01 +318 8.42463e+00 8.74039e-02 2.09904e-01 +319 8.45114e+00 8.20225e-02 1.96191e-01 +320 8.47766e+00 7.69927e-02 1.83383e-01 +321 8.50417e+00 7.22904e-02 1.71481e-01 +322 8.53068e+00 6.78917e-02 1.60484e-01 +323 8.55719e+00 6.37726e-02 1.50393e-01 +324 8.58371e+00 5.99089e-02 1.41208e-01 +325 8.61022e+00 5.62769e-02 1.32928e-01 +326 8.63673e+00 5.28523e-02 1.25554e-01 +327 8.66325e+00 4.96112e-02 1.19085e-01 +328 8.68976e+00 4.65297e-02 1.13522e-01 +329 8.71627e+00 4.35836e-02 1.08865e-01 +330 8.74279e+00 4.07490e-02 1.05113e-01 +331 8.76930e+00 3.80019e-02 1.02266e-01 +332 8.79581e+00 3.53182e-02 1.00326e-01 +333 8.82232e+00 3.26740e-02 9.92905e-02 +334 8.84884e+00 3.00463e-02 9.89592e-02 +335 8.87535e+00 2.74286e-02 9.84553e-02 +336 8.90186e+00 2.48280e-02 9.76771e-02 +337 8.92838e+00 2.22516e-02 9.66246e-02 +338 8.95489e+00 1.97068e-02 9.52978e-02 +339 8.98140e+00 1.72008e-02 9.36967e-02 +340 9.00792e+00 1.47409e-02 9.18212e-02 +341 9.03443e+00 1.23343e-02 8.96715e-02 +342 9.06094e+00 9.98837e-03 8.72474e-02 +343 9.08745e+00 7.71034e-03 8.45490e-02 +344 9.11397e+00 5.50750e-03 8.15763e-02 +345 9.14048e+00 3.38710e-03 7.83293e-02 +346 9.16699e+00 1.35643e-03 7.48079e-02 +347 9.19351e+00 -5.77246e-04 7.10123e-02 +348 9.22002e+00 -2.40665e-03 6.69424e-02 +349 9.24653e+00 -4.12451e-03 6.25981e-02 +350 9.27305e+00 -5.72356e-03 5.79795e-02 +351 9.29956e+00 -7.19788e-03 5.32533e-02 +352 9.32607e+00 -8.54838e-03 4.86402e-02 +353 9.35259e+00 -9.77809e-03 4.41414e-02 +354 9.37910e+00 -1.08900e-02 3.97567e-02 +355 9.40561e+00 -1.18872e-02 3.54862e-02 +356 9.43212e+00 -1.27727e-02 3.13299e-02 +357 9.45864e+00 -1.35495e-02 2.72877e-02 +358 9.48515e+00 -1.42207e-02 2.33598e-02 +359 9.51166e+00 -1.47892e-02 1.95461e-02 +360 9.53818e+00 -1.52582e-02 1.58465e-02 +361 9.56469e+00 -1.56305e-02 1.22612e-02 +362 9.59120e+00 -1.59093e-02 8.79000e-03 +363 9.61772e+00 -1.60976e-02 5.43303e-03 +364 9.64423e+00 -1.61984e-02 2.19025e-03 +365 9.67074e+00 -1.62148e-02 -9.38343e-04 +366 9.69725e+00 -1.61497e-02 -3.95274e-03 +367 9.72377e+00 -1.60062e-02 -6.85619e-03 +368 9.75028e+00 -1.57865e-02 -9.71165e-03 +369 9.77679e+00 -1.54914e-02 -1.25433e-02 +370 9.80331e+00 -1.51216e-02 -1.53513e-02 +371 9.82982e+00 -1.46776e-02 -1.81355e-02 +372 9.85633e+00 -1.41601e-02 -2.08959e-02 +373 9.88285e+00 -1.35698e-02 -2.36326e-02 +374 9.90936e+00 -1.29072e-02 -2.63455e-02 +375 9.93587e+00 -1.21730e-02 -2.90347e-02 +376 9.96238e+00 -1.13678e-02 -3.17001e-02 +377 9.98890e+00 -1.04923e-02 -3.43417e-02 +378 1.00154e+01 -9.54702e-03 -3.69596e-02 +379 1.00419e+01 -8.53267e-03 -3.95538e-02 +380 1.00684e+01 -7.44985e-03 -4.21242e-02 +381 1.00949e+01 -6.29920e-03 -4.46708e-02 +382 1.01215e+01 -5.08134e-03 -4.71937e-02 +383 1.01480e+01 -3.79691e-03 -4.96928e-02 +384 1.01745e+01 -2.44682e-03 -5.21153e-02 +385 1.02010e+01 -1.03610e-03 -5.42507e-02 +386 1.02275e+01 4.27146e-04 -5.60773e-02 +387 1.02540e+01 1.93473e-03 -5.75952e-02 +388 1.02805e+01 3.47846e-03 -5.88043e-02 +389 1.03071e+01 5.05016e-03 -5.97046e-02 +390 1.03336e+01 6.64163e-03 -6.02961e-02 +391 1.03601e+01 8.24469e-03 -6.05788e-02 +392 1.03866e+01 9.85116e-03 -6.05528e-02 +393 1.04131e+01 1.14528e-02 -6.02180e-02 +394 1.04396e+01 1.30416e-02 -5.95744e-02 +395 1.04661e+01 1.46091e-02 -5.86220e-02 +396 1.04926e+01 1.61473e-02 -5.73609e-02 +397 1.05192e+01 1.76480e-02 -5.57909e-02 +398 1.05457e+01 1.91030e-02 -5.39122e-02 +399 1.05722e+01 2.05040e-02 -5.17248e-02 +400 1.05987e+01 2.18430e-02 -4.92285e-02 +401 1.06252e+01 2.31130e-02 -4.65786e-02 +402 1.06517e+01 2.43132e-02 -4.39628e-02 +403 1.06782e+01 2.54445e-02 -4.13815e-02 +404 1.07047e+01 2.65078e-02 -3.88346e-02 +405 1.07313e+01 2.75040e-02 -3.63222e-02 +406 1.07578e+01 2.84341e-02 -3.38442e-02 +407 1.07843e+01 2.92989e-02 -3.14008e-02 +408 1.08108e+01 3.00995e-02 -2.89918e-02 +409 1.08373e+01 3.08366e-02 -2.66173e-02 +410 1.08638e+01 3.15112e-02 -2.42772e-02 +411 1.08903e+01 3.21242e-02 -2.19716e-02 +412 1.09169e+01 3.26766e-02 -1.97005e-02 +413 1.09434e+01 3.31691e-02 -1.74639e-02 +414 1.09699e+01 3.36029e-02 -1.52617e-02 +415 1.09964e+01 3.39787e-02 -1.30940e-02 +416 1.10229e+01 3.42975e-02 -1.09607e-02 +417 1.10494e+01 3.45602e-02 -8.86038e-03 +418 1.10759e+01 3.47674e-02 -6.76636e-03 +419 1.11024e+01 3.49190e-02 -4.66929e-03 +420 1.11290e+01 3.50150e-02 -2.56919e-03 +421 1.11555e+01 3.50552e-02 -4.66037e-04 +422 1.11820e+01 3.50396e-02 1.64016e-03 +423 1.12085e+01 3.49682e-02 3.74939e-03 +424 1.12350e+01 3.48408e-02 5.86167e-03 +425 1.12615e+01 3.46574e-02 7.97700e-03 +426 1.12880e+01 3.44178e-02 1.00954e-02 +427 1.13145e+01 3.41220e-02 1.22168e-02 +428 1.13411e+01 3.37699e-02 1.43412e-02 +429 1.13676e+01 3.33615e-02 1.64687e-02 +430 1.13941e+01 3.28967e-02 1.85993e-02 +431 1.14206e+01 3.23753e-02 2.07328e-02 +432 1.14471e+01 3.17972e-02 2.28695e-02 +433 1.14736e+01 3.11625e-02 2.50091e-02 +434 1.15001e+01 3.04713e-02 2.71135e-02 +435 1.15267e+01 2.97264e-02 2.90428e-02 +436 1.15532e+01 2.89329e-02 3.07843e-02 +437 1.15797e+01 2.80957e-02 3.23380e-02 +438 1.16062e+01 2.72198e-02 3.37039e-02 +439 1.16327e+01 2.63102e-02 3.48820e-02 +440 1.16592e+01 2.53718e-02 3.58722e-02 +441 1.16857e+01 2.44097e-02 3.66746e-02 +442 1.17122e+01 2.34288e-02 3.72892e-02 +443 1.17388e+01 2.24341e-02 3.77159e-02 +444 1.17653e+01 2.14305e-02 3.79549e-02 +445 1.17918e+01 2.04231e-02 3.80060e-02 +446 1.18183e+01 1.94169e-02 3.78693e-02 +447 1.18448e+01 1.84167e-02 3.75448e-02 +448 1.18713e+01 1.74277e-02 3.70325e-02 +449 1.18978e+01 1.64547e-02 3.63323e-02 +450 1.19243e+01 1.55028e-02 3.54443e-02 +451 1.19509e+01 1.45756e-02 3.45225e-02 +452 1.19774e+01 1.36710e-02 3.37366e-02 +453 1.20039e+01 1.27854e-02 3.30865e-02 +454 1.20304e+01 1.19153e-02 3.25724e-02 +455 1.20569e+01 1.10571e-02 3.21942e-02 +456 1.20834e+01 1.02070e-02 3.19519e-02 +457 1.21099e+01 9.36157e-03 3.18455e-02 +458 1.21365e+01 8.51716e-03 3.18750e-02 +459 1.21630e+01 7.67016e-03 3.20405e-02 +460 1.21895e+01 6.81698e-03 3.23418e-02 +461 1.22160e+01 5.95400e-03 3.27791e-02 +462 1.22425e+01 5.07763e-03 3.33523e-02 +463 1.22690e+01 4.18426e-03 3.40614e-02 +464 1.22955e+01 3.27029e-03 3.49065e-02 +465 1.23220e+01 2.33211e-03 3.58874e-02 +466 1.23486e+01 1.36612e-03 3.70043e-02 +467 1.23751e+01 3.68802e-04 3.82258e-02 +468 1.24016e+01 -6.57430e-04 3.91065e-02 +469 1.24281e+01 -1.70057e-03 3.95013e-02 +470 1.24546e+01 -2.74773e-03 3.94102e-02 +471 1.24811e+01 -3.78604e-03 3.88331e-02 +472 1.25076e+01 -4.80261e-03 3.77702e-02 +473 1.25341e+01 -5.78455e-03 3.62213e-02 +474 1.25607e+01 -6.71899e-03 3.41866e-02 +475 1.25872e+01 -7.59304e-03 3.16659e-02 +476 1.26137e+01 -8.39381e-03 2.86593e-02 +477 1.26402e+01 -9.10843e-03 2.51668e-02 +478 1.26667e+01 -9.72401e-03 2.11883e-02 +479 1.26932e+01 -1.02277e-02 1.67240e-02 +480 1.27197e+01 -1.06065e-02 1.17738e-02 +481 1.27463e+01 -1.08477e-02 6.33760e-03 +482 1.27728e+01 -1.09383e-02 4.15532e-04 +483 1.27993e+01 -1.08654e-02 -5.99245e-03 +484 1.28258e+01 -1.06180e-02 -1.25906e-02 +485 1.28523e+01 -1.02053e-02 -1.83901e-02 +486 1.28788e+01 -9.65056e-03 -2.33115e-02 +487 1.29053e+01 -8.97697e-03 -2.73546e-02 +488 1.29318e+01 -8.20782e-03 -3.05195e-02 +489 1.29584e+01 -7.36640e-03 -3.28063e-02 +490 1.29849e+01 -6.47599e-03 -3.42149e-02 +491 1.30114e+01 -5.55988e-03 -3.47452e-02 +492 1.30379e+01 -4.64135e-03 -3.43974e-02 +493 1.30644e+01 -3.74368e-03 -3.31714e-02 +494 1.30909e+01 -2.89016e-03 -3.10672e-02 +495 1.31174e+01 -2.10407e-03 -2.80848e-02 +496 1.31439e+01 -1.40869e-03 -2.42242e-02 +497 1.31705e+01 -8.27316e-04 -1.94855e-02 +498 1.31970e+01 -3.83218e-04 -1.38685e-02 +499 1.32235e+01 -9.96852e-05 -7.37335e-03 +500 1.32500e+01 0.00000e+00 0.00000e+00 + + + +PairWW +N 500 R 2.00000e-02 1.01250e+01 + +1 2.00000e-02 8.94382e+01 2.97884e+01 +2 4.02505e-02 8.88350e+01 2.97884e+01 +3 6.05010e-02 8.82317e+01 2.97884e+01 +4 8.07515e-02 8.76285e+01 2.97884e+01 +5 1.01002e-01 8.70253e+01 2.97884e+01 +6 1.21253e-01 8.64220e+01 2.97884e+01 +7 1.41503e-01 8.58188e+01 2.97884e+01 +8 1.61754e-01 8.52156e+01 2.97884e+01 +9 1.82004e-01 8.46124e+01 2.97884e+01 +10 2.02255e-01 8.40091e+01 2.97884e+01 +11 2.22505e-01 8.34059e+01 2.97884e+01 +12 2.42756e-01 8.28027e+01 2.97884e+01 +13 2.63006e-01 8.21994e+01 2.97884e+01 +14 2.83257e-01 8.15962e+01 2.97884e+01 +15 3.03507e-01 8.09930e+01 2.97884e+01 +16 3.23758e-01 8.03898e+01 2.97884e+01 +17 3.44008e-01 7.97865e+01 2.97884e+01 +18 3.64259e-01 7.91833e+01 2.97884e+01 +19 3.84509e-01 7.85801e+01 2.97884e+01 +20 4.04760e-01 7.79768e+01 2.97884e+01 +21 4.25010e-01 7.73736e+01 2.97884e+01 +22 4.45261e-01 7.67704e+01 2.97884e+01 +23 4.65511e-01 7.61672e+01 2.97884e+01 +24 4.85762e-01 7.55639e+01 2.97884e+01 +25 5.06012e-01 7.49607e+01 2.97884e+01 +26 5.26263e-01 7.43575e+01 2.97884e+01 +27 5.46513e-01 7.37542e+01 2.97884e+01 +28 5.66764e-01 7.31510e+01 2.97884e+01 +29 5.87014e-01 7.25478e+01 2.97884e+01 +30 6.07265e-01 7.19446e+01 2.97884e+01 +31 6.27515e-01 7.13413e+01 2.97884e+01 +32 6.47766e-01 7.07381e+01 2.97884e+01 +33 6.68016e-01 7.01349e+01 2.97884e+01 +34 6.88267e-01 6.95316e+01 2.97884e+01 +35 7.08517e-01 6.89284e+01 2.97884e+01 +36 7.28768e-01 6.83252e+01 2.97884e+01 +37 7.49018e-01 6.77219e+01 2.97884e+01 +38 7.69269e-01 6.71187e+01 2.97884e+01 +39 7.89519e-01 6.65155e+01 2.97884e+01 +40 8.09770e-01 6.59123e+01 2.97884e+01 +41 8.30020e-01 6.53090e+01 2.97884e+01 +42 8.50271e-01 6.47058e+01 2.97884e+01 +43 8.70521e-01 6.41026e+01 2.97884e+01 +44 8.90772e-01 6.34993e+01 2.97884e+01 +45 9.11022e-01 6.28961e+01 2.97884e+01 +46 9.31273e-01 6.22929e+01 2.97884e+01 +47 9.51523e-01 6.16897e+01 2.97884e+01 +48 9.71774e-01 6.10864e+01 2.97884e+01 +49 9.92024e-01 6.04832e+01 2.97884e+01 +50 1.01227e+00 5.98800e+01 2.97884e+01 +51 1.03253e+00 5.92767e+01 2.97884e+01 +52 1.05278e+00 5.86735e+01 2.97884e+01 +53 1.07303e+00 5.80703e+01 2.97884e+01 +54 1.09328e+00 5.74671e+01 2.97884e+01 +55 1.11353e+00 5.68638e+01 2.97884e+01 +56 1.13378e+00 5.62606e+01 2.97884e+01 +57 1.15403e+00 5.56574e+01 2.97884e+01 +58 1.17428e+00 5.50541e+01 2.97884e+01 +59 1.19453e+00 5.44509e+01 2.97884e+01 +60 1.21478e+00 5.38477e+01 2.97884e+01 +61 1.23503e+00 5.32445e+01 2.97884e+01 +62 1.25528e+00 5.26412e+01 2.97884e+01 +63 1.27553e+00 5.20380e+01 2.97884e+01 +64 1.29578e+00 5.14348e+01 2.97884e+01 +65 1.31603e+00 5.08315e+01 2.97884e+01 +66 1.33628e+00 5.02283e+01 2.97884e+01 +67 1.35653e+00 4.96251e+01 2.97884e+01 +68 1.37678e+00 4.90218e+01 2.97884e+01 +69 1.39703e+00 4.84186e+01 2.97884e+01 +70 1.41728e+00 4.78154e+01 2.97884e+01 +71 1.43754e+00 4.72122e+01 2.97884e+01 +72 1.45779e+00 4.66089e+01 2.97884e+01 +73 1.47804e+00 4.60057e+01 2.97884e+01 +74 1.49829e+00 4.54025e+01 2.97884e+01 +75 1.51854e+00 4.47992e+01 2.97884e+01 +76 1.53879e+00 4.41960e+01 2.97884e+01 +77 1.55904e+00 4.35928e+01 2.97884e+01 +78 1.57929e+00 4.29896e+01 2.97884e+01 +79 1.59954e+00 4.23863e+01 2.97884e+01 +80 1.61979e+00 4.17831e+01 2.97884e+01 +81 1.64004e+00 4.11799e+01 2.97884e+01 +82 1.66029e+00 4.05766e+01 2.97884e+01 +83 1.68054e+00 3.99734e+01 2.97884e+01 +84 1.70079e+00 3.93702e+01 2.97884e+01 +85 1.72104e+00 3.87670e+01 2.97884e+01 +86 1.74129e+00 3.81637e+01 2.97884e+01 +87 1.76154e+00 3.75605e+01 2.97884e+01 +88 1.78179e+00 3.69573e+01 2.97884e+01 +89 1.80204e+00 3.63540e+01 2.97884e+01 +90 1.82229e+00 3.57508e+01 2.97884e+01 +91 1.84255e+00 3.51476e+01 2.97884e+01 +92 1.86280e+00 3.45444e+01 2.97884e+01 +93 1.88305e+00 3.39411e+01 2.97884e+01 +94 1.90330e+00 3.33379e+01 2.97884e+01 +95 1.92355e+00 3.27347e+01 2.97884e+01 +96 1.94380e+00 3.21314e+01 2.97884e+01 +97 1.96405e+00 3.15282e+01 2.97884e+01 +98 1.98430e+00 3.09250e+01 2.97884e+01 +99 2.00455e+00 3.03217e+01 2.97884e+01 +100 2.02480e+00 2.97185e+01 2.97884e+01 +101 2.04505e+00 2.91153e+01 2.97884e+01 +102 2.06530e+00 2.85121e+01 2.97884e+01 +103 2.08555e+00 2.79088e+01 2.97884e+01 +104 2.10580e+00 2.73056e+01 2.97884e+01 +105 2.12605e+00 2.67024e+01 2.97884e+01 +106 2.14630e+00 2.60991e+01 2.97884e+01 +107 2.16655e+00 2.54959e+01 2.97884e+01 +108 2.18680e+00 2.48927e+01 2.97884e+01 +109 2.20705e+00 2.42895e+01 2.97884e+01 +110 2.22730e+00 2.36862e+01 2.97884e+01 +111 2.24756e+00 2.30830e+01 2.97884e+01 +112 2.26781e+00 2.24798e+01 2.97884e+01 +113 2.28806e+00 2.18765e+01 2.97884e+01 +114 2.30831e+00 2.12733e+01 2.97884e+01 +115 2.32856e+00 2.06701e+01 2.97884e+01 +116 2.34881e+00 2.00669e+01 2.97884e+01 +117 2.36906e+00 1.94636e+01 2.97884e+01 +118 2.38931e+00 1.88604e+01 2.97884e+01 +119 2.40956e+00 1.82572e+01 2.97884e+01 +120 2.42981e+00 1.76539e+01 2.97884e+01 +121 2.45006e+00 1.70507e+01 2.97884e+01 +122 2.47031e+00 1.64475e+01 2.97884e+01 +123 2.49056e+00 1.58442e+01 2.97884e+01 +124 2.51081e+00 1.52410e+01 2.97884e+01 +125 2.53106e+00 1.46378e+01 2.97884e+01 +126 2.55131e+00 1.40346e+01 2.97884e+01 +127 2.57156e+00 1.34313e+01 2.97884e+01 +128 2.59181e+00 1.28281e+01 2.97884e+01 +129 2.61206e+00 1.22249e+01 2.97884e+01 +130 2.63231e+00 1.16216e+01 2.97884e+01 +131 2.65257e+00 1.10184e+01 2.97884e+01 +132 2.67282e+00 1.04152e+01 2.97884e+01 +133 2.69307e+00 9.81196e+00 2.97884e+01 +134 2.71332e+00 9.20886e+00 2.97593e+01 +135 2.73357e+00 8.60757e+00 2.96037e+01 +136 2.75382e+00 8.01079e+00 2.93137e+01 +137 2.77407e+00 7.42124e+00 2.88892e+01 +138 2.79432e+00 6.84165e+00 2.83304e+01 +139 2.81457e+00 6.27474e+00 2.76371e+01 +140 2.83482e+00 5.72323e+00 2.68094e+01 +141 2.85507e+00 5.18984e+00 2.58474e+01 +142 2.87532e+00 4.67729e+00 2.47509e+01 +143 2.89557e+00 4.18831e+00 2.35199e+01 +144 2.91582e+00 3.72562e+00 2.21546e+01 +145 2.93607e+00 3.29193e+00 2.06549e+01 +146 2.95632e+00 2.88998e+00 1.90207e+01 +147 2.97657e+00 2.52248e+00 1.72522e+01 +148 2.99682e+00 2.19216e+00 1.53492e+01 +149 3.01707e+00 1.90173e+00 1.33118e+01 +150 3.03732e+00 1.65393e+00 1.11400e+01 +151 3.05758e+00 1.45045e+00 8.98475e+00 +152 3.07783e+00 1.28887e+00 7.00237e+00 +153 3.09808e+00 1.16568e+00 5.19285e+00 +154 3.11833e+00 1.07738e+00 3.55619e+00 +155 3.13858e+00 1.02048e+00 2.09239e+00 +156 3.15883e+00 9.91473e-01 8.01457e-01 +157 3.17908e+00 9.86856e-01 -3.16620e-01 +158 3.19933e+00 1.00313e+00 -1.26184e+00 +159 3.21958e+00 1.03679e+00 -2.03419e+00 +160 3.23983e+00 1.08435e+00 -2.63368e+00 +161 3.26008e+00 1.14229e+00 -3.06031e+00 +162 3.28033e+00 1.20713e+00 -3.31409e+00 +163 3.30058e+00 1.27535e+00 -3.39500e+00 +164 3.32083e+00 1.34346e+00 -3.30305e+00 +165 3.34108e+00 1.40796e+00 -3.03823e+00 +166 3.36133e+00 1.46535e+00 -2.60056e+00 +167 3.38158e+00 1.51215e+00 -2.00188e+00 +168 3.40183e+00 1.54654e+00 -1.40352e+00 +169 3.42208e+00 1.56934e+00 -8.56575e-01 +170 3.44233e+00 1.58158e+00 -3.61034e-01 +171 3.46259e+00 1.58431e+00 8.31010e-02 +172 3.48284e+00 1.57856e+00 4.75829e-01 +173 3.50309e+00 1.56538e+00 8.17150e-01 +174 3.52334e+00 1.54581e+00 1.10706e+00 +175 3.54359e+00 1.52089e+00 1.34557e+00 +176 3.56384e+00 1.49166e+00 1.53267e+00 +177 3.58409e+00 1.45916e+00 1.66837e+00 +178 3.60434e+00 1.42444e+00 1.75266e+00 +179 3.62459e+00 1.38853e+00 1.78554e+00 +180 3.64484e+00 1.35247e+00 1.76701e+00 +181 3.66509e+00 1.31731e+00 1.69708e+00 +182 3.68534e+00 1.28408e+00 1.57574e+00 +183 3.70559e+00 1.25384e+00 1.40299e+00 +184 3.72584e+00 1.22753e+00 1.19517e+00 +185 3.74609e+00 1.20528e+00 1.00677e+00 +186 3.76634e+00 1.18660e+00 8.42197e-01 +187 3.78659e+00 1.17101e+00 7.01434e-01 +188 3.80684e+00 1.15803e+00 5.84485e-01 +189 3.82709e+00 1.14718e+00 4.91351e-01 +190 3.84734e+00 1.13797e+00 4.22030e-01 +191 3.86760e+00 1.12992e+00 3.76524e-01 +192 3.88785e+00 1.12256e+00 3.54831e-01 +193 3.90810e+00 1.11539e+00 3.56953e-01 +194 3.92835e+00 1.10794e+00 3.82889e-01 +195 3.94860e+00 1.09972e+00 4.32638e-01 +196 3.96885e+00 1.09026e+00 5.06202e-01 +197 3.98910e+00 1.07906e+00 6.03580e-01 +198 4.00935e+00 1.06565e+00 7.24772e-01 +199 4.02960e+00 1.04955e+00 8.69778e-01 +200 4.04985e+00 1.03026e+00 1.03860e+00 +201 4.07010e+00 1.00745e+00 1.21153e+00 +202 4.09035e+00 9.81304e-01 1.36829e+00 +203 4.11060e+00 9.52145e-01 1.50886e+00 +204 4.13085e+00 9.20303e-01 1.63325e+00 +205 4.15110e+00 8.86105e-01 1.74147e+00 +206 4.17135e+00 8.49881e-01 1.83350e+00 +207 4.19160e+00 8.11956e-01 1.90936e+00 +208 4.21185e+00 7.72659e-01 1.96903e+00 +209 4.23210e+00 7.32317e-01 2.01253e+00 +210 4.25235e+00 6.91259e-01 2.03984e+00 +211 4.27261e+00 6.49811e-01 2.05098e+00 +212 4.29286e+00 6.08301e-01 2.04593e+00 +213 4.31311e+00 5.67058e-01 2.02471e+00 +214 4.33336e+00 5.26408e-01 1.98730e+00 +215 4.35361e+00 4.86679e-01 1.93372e+00 +216 4.37386e+00 4.48200e-01 1.86395e+00 +217 4.39411e+00 4.11294e-01 1.77895e+00 +218 4.41436e+00 3.76159e-01 1.69136e+00 +219 4.43461e+00 3.42783e-01 1.60520e+00 +220 4.45486e+00 3.11137e-01 1.52046e+00 +221 4.47511e+00 2.81193e-01 1.43714e+00 +222 4.49536e+00 2.52922e-01 1.35524e+00 +223 4.51561e+00 2.26295e-01 1.27476e+00 +224 4.53586e+00 2.01283e-01 1.19571e+00 +225 4.55611e+00 1.77858e-01 1.11807e+00 +226 4.57636e+00 1.55991e-01 1.04185e+00 +227 4.59661e+00 1.35652e-01 9.67052e-01 +228 4.61686e+00 1.16814e-01 8.93674e-01 +229 4.63711e+00 9.94480e-02 8.21717e-01 +230 4.65736e+00 8.35245e-02 7.51181e-01 +231 4.67762e+00 6.90149e-02 6.82064e-01 +232 4.69787e+00 5.58906e-02 6.14369e-01 +233 4.71812e+00 4.41228e-02 5.48093e-01 +234 4.73837e+00 3.36825e-02 4.83277e-01 +235 4.75862e+00 2.45388e-02 4.20047e-01 +236 4.77887e+00 1.66594e-02 3.58416e-01 +237 4.79912e+00 1.00118e-02 2.98383e-01 +238 4.81937e+00 4.56379e-03 2.39947e-01 +239 4.83962e+00 2.82945e-04 1.83109e-01 +240 4.85987e+00 -2.86308e-03 1.27868e-01 +241 4.88012e+00 -4.90663e-03 7.42254e-02 +242 4.90037e+00 -5.88007e-03 2.21805e-02 +243 4.92062e+00 -5.81574e-03 -2.82668e-02 +244 4.94087e+00 -4.74602e-03 -7.71163e-02 +245 4.96112e+00 -2.70324e-03 -1.24368e-01 +246 4.98137e+00 2.80232e-04 -1.70022e-01 +247 5.00162e+00 4.17205e-03 -2.14079e-01 +248 5.02187e+00 8.93985e-03 -2.56537e-01 +249 5.04212e+00 1.45513e-02 -2.97398e-01 +250 5.06237e+00 2.09740e-02 -3.36661e-01 +251 5.08263e+00 2.81652e-02 -3.72774e-01 +252 5.10288e+00 3.60397e-02 -4.04144e-01 +253 5.12313e+00 4.45014e-02 -4.30773e-01 +254 5.14338e+00 5.34544e-02 -4.52658e-01 +255 5.16363e+00 6.28025e-02 -4.69802e-01 +256 5.18388e+00 7.24498e-02 -4.82203e-01 +257 5.20413e+00 8.23003e-02 -4.89862e-01 +258 5.22438e+00 9.22578e-02 -4.92779e-01 +259 5.24463e+00 1.02226e-01 -4.90954e-01 +260 5.26488e+00 1.12110e-01 -4.84386e-01 +261 5.28513e+00 1.21812e-01 -4.73076e-01 +262 5.30538e+00 1.31238e-01 -4.57024e-01 +263 5.32563e+00 1.40290e-01 -4.36230e-01 +264 5.34588e+00 1.48874e-01 -4.10693e-01 +265 5.36613e+00 1.56892e-01 -3.80414e-01 +266 5.38638e+00 1.64249e-01 -3.45393e-01 +267 5.40663e+00 1.70849e-01 -3.06021e-01 +268 5.42688e+00 1.76653e-01 -2.67562e-01 +269 5.44713e+00 1.81703e-01 -2.31667e-01 +270 5.46738e+00 1.86053e-01 -1.98335e-01 +271 5.48764e+00 1.89753e-01 -1.67568e-01 +272 5.50789e+00 1.92857e-01 -1.39366e-01 +273 5.52814e+00 1.95415e-01 -1.13727e-01 +274 5.54839e+00 1.97480e-01 -9.06523e-02 +275 5.56864e+00 1.99104e-01 -7.01418e-02 +276 5.58889e+00 2.00338e-01 -5.21954e-02 +277 5.60914e+00 2.01235e-01 -3.68132e-02 +278 5.62939e+00 2.01847e-01 -2.39950e-02 +279 5.64964e+00 2.02224e-01 -1.37410e-02 +280 5.66989e+00 2.02420e-01 -6.05108e-03 +281 5.69014e+00 2.02487e-01 -9.25278e-04 +282 5.71039e+00 2.02475e-01 1.63640e-03 +283 5.73064e+00 2.02438e-01 1.63397e-03 +284 5.75089e+00 2.02423e-01 -2.80048e-04 +285 5.77114e+00 2.02447e-01 -1.94516e-03 +286 5.79139e+00 2.02499e-01 -3.19019e-03 +287 5.81164e+00 2.02573e-01 -4.01515e-03 +288 5.83189e+00 2.02659e-01 -4.42003e-03 +289 5.85214e+00 2.02749e-01 -4.40484e-03 +290 5.87239e+00 2.02835e-01 -3.96958e-03 +291 5.89265e+00 2.02907e-01 -3.11424e-03 +292 5.91290e+00 2.02958e-01 -1.83883e-03 +293 5.93315e+00 2.02979e-01 -1.43346e-04 +294 5.95340e+00 2.02961e-01 1.97221e-03 +295 5.97365e+00 2.02896e-01 4.50785e-03 +296 5.99390e+00 2.02776e-01 7.46355e-03 +297 6.01415e+00 2.02591e-01 1.08393e-02 +298 6.03440e+00 2.02334e-01 1.46352e-02 +299 6.05465e+00 2.01995e-01 1.88511e-02 +300 6.07490e+00 2.01567e-01 2.34871e-02 +301 6.09515e+00 2.01043e-01 2.83464e-02 +302 6.11540e+00 2.00419e-01 3.32284e-02 +303 6.13565e+00 1.99697e-01 3.81329e-02 +304 6.15590e+00 1.98875e-01 4.30601e-02 +305 6.17615e+00 1.97953e-01 4.80098e-02 +306 6.19640e+00 1.96930e-01 5.29822e-02 +307 6.21665e+00 1.95807e-01 5.79772e-02 +308 6.23690e+00 1.94582e-01 6.29948e-02 +309 6.25715e+00 1.93255e-01 6.80351e-02 +310 6.27740e+00 1.91826e-01 7.30979e-02 +311 6.29766e+00 1.90294e-01 7.81834e-02 +312 6.31791e+00 1.88659e-01 8.32915e-02 +313 6.33816e+00 1.86921e-01 8.84221e-02 +314 6.35841e+00 1.85078e-01 9.35755e-02 +315 6.37866e+00 1.83131e-01 9.87514e-02 +316 6.39891e+00 1.81078e-01 1.03950e-01 +317 6.41916e+00 1.78921e-01 1.09153e-01 +318 6.43941e+00 1.76659e-01 1.14117e-01 +319 6.45966e+00 1.74301e-01 1.18766e-01 +320 6.47991e+00 1.71851e-01 1.23099e-01 +321 6.50016e+00 1.69317e-01 1.27118e-01 +322 6.52041e+00 1.66705e-01 1.30822e-01 +323 6.54066e+00 1.64021e-01 1.34210e-01 +324 6.56091e+00 1.61272e-01 1.37284e-01 +325 6.58116e+00 1.58463e-01 1.40042e-01 +326 6.60141e+00 1.55602e-01 1.42485e-01 +327 6.62166e+00 1.52694e-01 1.44614e-01 +328 6.64191e+00 1.49747e-01 1.46427e-01 +329 6.66216e+00 1.46766e-01 1.47925e-01 +330 6.68241e+00 1.43758e-01 1.49108e-01 +331 6.70267e+00 1.40729e-01 1.49976e-01 +332 6.72292e+00 1.37686e-01 1.50529e-01 +333 6.74317e+00 1.34635e-01 1.50767e-01 +334 6.76342e+00 1.31581e-01 1.50789e-01 +335 6.78367e+00 1.28527e-01 1.50921e-01 +336 6.80392e+00 1.25468e-01 1.51190e-01 +337 6.82417e+00 1.22402e-01 1.51595e-01 +338 6.84442e+00 1.19327e-01 1.52136e-01 +339 6.86467e+00 1.16240e-01 1.52814e-01 +340 6.88492e+00 1.13137e-01 1.53628e-01 +341 6.90517e+00 1.10017e-01 1.54578e-01 +342 6.92542e+00 1.06876e-01 1.55664e-01 +343 6.94567e+00 1.03711e-01 1.56887e-01 +344 6.96592e+00 1.00521e-01 1.58245e-01 +345 6.98617e+00 9.73014e-02 1.59740e-01 +346 7.00642e+00 9.40502e-02 1.61372e-01 +347 7.02667e+00 9.07647e-02 1.63139e-01 +348 7.04692e+00 8.74420e-02 1.65043e-01 +349 7.06717e+00 8.40794e-02 1.67083e-01 +350 7.08742e+00 8.06741e-02 1.69260e-01 +351 7.10768e+00 7.72249e-02 1.71336e-01 +352 7.12793e+00 7.37370e-02 1.73074e-01 +353 7.14818e+00 7.02175e-02 1.74472e-01 +354 7.16843e+00 6.66730e-02 1.75531e-01 +355 7.18868e+00 6.31106e-02 1.76250e-01 +356 7.20893e+00 5.95370e-02 1.76630e-01 +357 7.22918e+00 5.59592e-02 1.76671e-01 +358 7.24943e+00 5.23840e-02 1.76373e-01 +359 7.26968e+00 4.88182e-02 1.75735e-01 +360 7.28993e+00 4.52688e-02 1.74758e-01 +361 7.31018e+00 4.17426e-02 1.73442e-01 +362 7.33043e+00 3.82465e-02 1.71786e-01 +363 7.35068e+00 3.47874e-02 1.69791e-01 +364 7.37093e+00 3.13721e-02 1.67457e-01 +365 7.39118e+00 2.80075e-02 1.64784e-01 +366 7.41143e+00 2.47005e-02 1.61771e-01 +367 7.43168e+00 2.14578e-02 1.58440e-01 +368 7.45193e+00 1.82836e-02 1.55062e-01 +369 7.47218e+00 1.51774e-02 1.51721e-01 +370 7.49243e+00 1.21385e-02 1.48419e-01 +371 7.51269e+00 9.16606e-03 1.45155e-01 +372 7.53294e+00 6.25935e-03 1.41928e-01 +373 7.55319e+00 3.41758e-03 1.38740e-01 +374 7.57344e+00 6.40000e-04 1.35589e-01 +375 7.59369e+00 -2.07416e-03 1.32476e-01 +376 7.61394e+00 -4.72568e-03 1.29401e-01 +377 7.63419e+00 -7.31531e-03 1.26365e-01 +378 7.65444e+00 -9.84383e-03 1.23366e-01 +379 7.67469e+00 -1.23120e-02 1.20405e-01 +380 7.69494e+00 -1.47206e-02 1.17482e-01 +381 7.71519e+00 -1.70704e-02 1.14597e-01 +382 7.73544e+00 -1.93621e-02 1.11750e-01 +383 7.75569e+00 -2.15966e-02 1.08940e-01 +384 7.77594e+00 -2.37743e-02 1.06100e-01 +385 7.79619e+00 -2.58919e-02 1.03001e-01 +386 7.81644e+00 -2.79441e-02 9.96253e-02 +387 7.83669e+00 -2.99250e-02 9.59734e-02 +388 7.85694e+00 -3.18292e-02 9.20451e-02 +389 7.87719e+00 -3.36511e-02 8.78405e-02 +390 7.89744e+00 -3.53850e-02 8.33595e-02 +391 7.91770e+00 -3.70253e-02 7.86021e-02 +392 7.93795e+00 -3.85666e-02 7.35683e-02 +393 7.95820e+00 -4.00031e-02 6.82582e-02 +394 7.97845e+00 -4.13292e-02 6.26717e-02 +395 7.99870e+00 -4.25395e-02 5.68088e-02 +396 8.01895e+00 -4.36282e-02 5.06695e-02 +397 8.03920e+00 -4.45898e-02 4.42538e-02 +398 8.05945e+00 -4.54186e-02 3.75618e-02 +399 8.07970e+00 -4.61092e-02 3.05934e-02 +400 8.09995e+00 -4.66558e-02 2.33486e-02 +401 8.12020e+00 -4.70552e-02 1.61643e-02 +402 8.14045e+00 -4.73132e-02 9.38066e-03 +403 8.16070e+00 -4.74379e-02 2.99764e-03 +404 8.18095e+00 -4.74373e-02 -2.98473e-03 +405 8.20120e+00 -4.73197e-02 -8.56645e-03 +406 8.22145e+00 -4.70931e-02 -1.37475e-02 +407 8.24170e+00 -4.67656e-02 -1.85279e-02 +408 8.26195e+00 -4.63454e-02 -2.29077e-02 +409 8.28220e+00 -4.58405e-02 -2.68868e-02 +410 8.30245e+00 -4.52591e-02 -3.04653e-02 +411 8.32271e+00 -4.46093e-02 -3.36431e-02 +412 8.34296e+00 -4.38993e-02 -3.64203e-02 +413 8.36321e+00 -4.31370e-02 -3.87968e-02 +414 8.38346e+00 -4.23307e-02 -4.07727e-02 +415 8.40371e+00 -4.14884e-02 -4.23479e-02 +416 8.42396e+00 -4.06182e-02 -4.35225e-02 +417 8.44421e+00 -3.97283e-02 -4.43172e-02 +418 8.46446e+00 -3.88239e-02 -4.50049e-02 +419 8.48471e+00 -3.79057e-02 -4.56703e-02 +420 8.50496e+00 -3.69743e-02 -4.63133e-02 +421 8.52521e+00 -3.60301e-02 -4.69339e-02 +422 8.54546e+00 -3.50736e-02 -4.75322e-02 +423 8.56571e+00 -3.41052e-02 -4.81081e-02 +424 8.58596e+00 -3.31253e-02 -4.86616e-02 +425 8.60621e+00 -3.21345e-02 -4.91928e-02 +426 8.62646e+00 -3.11331e-02 -4.97016e-02 +427 8.64671e+00 -3.01217e-02 -5.01880e-02 +428 8.66696e+00 -2.91006e-02 -5.06520e-02 +429 8.68721e+00 -2.80704e-02 -5.10937e-02 +430 8.70746e+00 -2.70314e-02 -5.15130e-02 +431 8.72772e+00 -2.59842e-02 -5.19100e-02 +432 8.74797e+00 -2.49292e-02 -5.22846e-02 +433 8.76822e+00 -2.38668e-02 -5.26368e-02 +434 8.78847e+00 -2.27976e-02 -5.29357e-02 +435 8.80872e+00 -2.17239e-02 -5.30803e-02 +436 8.82897e+00 -2.06489e-02 -5.30626e-02 +437 8.84922e+00 -1.95759e-02 -5.28827e-02 +438 8.86947e+00 -1.85082e-02 -5.25406e-02 +439 8.88972e+00 -1.74490e-02 -5.20363e-02 +440 8.90997e+00 -1.64018e-02 -5.13697e-02 +441 8.93022e+00 -1.53696e-02 -5.05410e-02 +442 8.95047e+00 -1.43559e-02 -4.95500e-02 +443 8.97072e+00 -1.33639e-02 -4.83968e-02 +444 8.99097e+00 -1.23969e-02 -4.70814e-02 +445 9.01122e+00 -1.14581e-02 -4.56037e-02 +446 9.03147e+00 -1.05510e-02 -4.39639e-02 +447 9.05172e+00 -9.67866e-03 -4.21618e-02 +448 9.07197e+00 -8.84448e-03 -4.01975e-02 +449 9.09222e+00 -8.05171e-03 -3.80710e-02 +450 9.11247e+00 -7.30366e-03 -3.57822e-02 +451 9.13273e+00 -6.60234e-03 -3.35176e-02 +452 9.15298e+00 -5.94474e-03 -3.14642e-02 +453 9.17323e+00 -5.32658e-03 -2.96221e-02 +454 9.19348e+00 -4.74359e-03 -2.79913e-02 +455 9.21373e+00 -4.19148e-03 -2.65718e-02 +456 9.23398e+00 -3.66597e-03 -2.53636e-02 +457 9.25423e+00 -3.16280e-03 -2.43666e-02 +458 9.27448e+00 -2.67767e-03 -2.35810e-02 +459 9.29473e+00 -2.20632e-03 -2.30066e-02 +460 9.31498e+00 -1.74446e-03 -2.26435e-02 +461 9.33523e+00 -1.28781e-03 -2.24918e-02 +462 9.35548e+00 -8.32093e-04 -2.25513e-02 +463 9.37573e+00 -3.73033e-04 -2.28220e-02 +464 9.39598e+00 9.36493e-05 -2.33041e-02 +465 9.41623e+00 5.72233e-04 -2.39975e-02 +466 9.43648e+00 1.06700e-03 -2.49021e-02 +467 9.45673e+00 1.58215e-03 -2.59847e-02 +468 9.47698e+00 2.11737e-03 -2.68103e-02 +469 9.49723e+00 2.66535e-03 -2.72445e-02 +470 9.51748e+00 3.21816e-03 -2.72874e-02 +471 9.53774e+00 3.76787e-03 -2.69390e-02 +472 9.55799e+00 4.30657e-03 -2.61993e-02 +473 9.57824e+00 4.82633e-03 -2.50682e-02 +474 9.59849e+00 5.31922e-03 -2.35458e-02 +475 9.61874e+00 5.77732e-03 -2.16321e-02 +476 9.63899e+00 6.19270e-03 -1.93271e-02 +477 9.65924e+00 6.55744e-03 -1.66308e-02 +478 9.67949e+00 6.86362e-03 -1.35431e-02 +479 9.69974e+00 7.10331e-03 -1.00641e-02 +480 9.71999e+00 7.26859e-03 -6.19383e-03 +481 9.74024e+00 7.35153e-03 -1.93221e-03 +482 9.76049e+00 7.34420e-03 2.72074e-03 +483 9.78074e+00 7.23869e-03 7.76500e-03 +484 9.80099e+00 7.02817e-03 1.29555e-02 +485 9.82124e+00 6.71866e-03 1.74943e-02 +486 9.84149e+00 6.32445e-03 2.13200e-02 +487 9.86174e+00 5.85999e-03 2.44325e-02 +488 9.88199e+00 5.33972e-03 2.68319e-02 +489 9.90224e+00 4.77809e-03 2.85182e-02 +490 9.92249e+00 4.18952e-03 2.94913e-02 +491 9.94275e+00 3.58847e-03 2.97513e-02 +492 9.96300e+00 2.98938e-03 2.92982e-02 +493 9.98325e+00 2.40668e-03 2.81319e-02 +494 1.00035e+01 1.85482e-03 2.62525e-02 +495 1.00237e+01 1.34824e-03 2.36599e-02 +496 1.00440e+01 9.01386e-04 2.03542e-02 +497 1.00642e+01 5.28692e-04 1.63354e-02 +498 1.00845e+01 2.44602e-04 1.16034e-02 +499 1.01047e+01 6.35574e-05 6.15826e-03 +500 1.01250e+01 0.00000e+00 0.00000e+00 + + + +PairBW +N 500 R 2.00000e-02 7.00000e+00 + +1 2.00000e-02 7.51383e+01 2.97885e+01 +2 3.39880e-02 7.47216e+01 2.97885e+01 +3 4.79760e-02 7.43049e+01 2.97885e+01 +4 6.19639e-02 7.38882e+01 2.97885e+01 +5 7.59519e-02 7.34715e+01 2.97885e+01 +6 8.99399e-02 7.30549e+01 2.97885e+01 +7 1.03928e-01 7.26382e+01 2.97885e+01 +8 1.17916e-01 7.22215e+01 2.97885e+01 +9 1.31904e-01 7.18048e+01 2.97885e+01 +10 1.45892e-01 7.13881e+01 2.97885e+01 +11 1.59880e-01 7.09714e+01 2.97885e+01 +12 1.73868e-01 7.05548e+01 2.97885e+01 +13 1.87856e-01 7.01381e+01 2.97885e+01 +14 2.01844e-01 6.97214e+01 2.97885e+01 +15 2.15832e-01 6.93047e+01 2.97885e+01 +16 2.29820e-01 6.88880e+01 2.97885e+01 +17 2.43808e-01 6.84714e+01 2.97885e+01 +18 2.57796e-01 6.80547e+01 2.97885e+01 +19 2.71784e-01 6.76380e+01 2.97885e+01 +20 2.85772e-01 6.72213e+01 2.97885e+01 +21 2.99760e-01 6.68046e+01 2.97885e+01 +22 3.13747e-01 6.63879e+01 2.97885e+01 +23 3.27735e-01 6.59713e+01 2.97885e+01 +24 3.41723e-01 6.55546e+01 2.97885e+01 +25 3.55711e-01 6.51379e+01 2.97885e+01 +26 3.69699e-01 6.47212e+01 2.97885e+01 +27 3.83687e-01 6.43045e+01 2.97885e+01 +28 3.97675e-01 6.38879e+01 2.97885e+01 +29 4.11663e-01 6.34712e+01 2.97885e+01 +30 4.25651e-01 6.30545e+01 2.97885e+01 +31 4.39639e-01 6.26378e+01 2.97885e+01 +32 4.53627e-01 6.22211e+01 2.97885e+01 +33 4.67615e-01 6.18045e+01 2.97885e+01 +34 4.81603e-01 6.13878e+01 2.97885e+01 +35 4.95591e-01 6.09711e+01 2.97885e+01 +36 5.09579e-01 6.05544e+01 2.97885e+01 +37 5.23567e-01 6.01377e+01 2.97885e+01 +38 5.37555e-01 5.97210e+01 2.97885e+01 +39 5.51543e-01 5.93044e+01 2.97885e+01 +40 5.65531e-01 5.88877e+01 2.97885e+01 +41 5.79519e-01 5.84710e+01 2.97885e+01 +42 5.93507e-01 5.80543e+01 2.97885e+01 +43 6.07495e-01 5.76376e+01 2.97885e+01 +44 6.21483e-01 5.72210e+01 2.97885e+01 +45 6.35471e-01 5.68043e+01 2.97885e+01 +46 6.49459e-01 5.63876e+01 2.97885e+01 +47 6.63447e-01 5.59709e+01 2.97885e+01 +48 6.77435e-01 5.55542e+01 2.97885e+01 +49 6.91423e-01 5.51375e+01 2.97885e+01 +50 7.05411e-01 5.47209e+01 2.97885e+01 +51 7.19399e-01 5.43042e+01 2.97885e+01 +52 7.33387e-01 5.38875e+01 2.97885e+01 +53 7.47375e-01 5.34708e+01 2.97885e+01 +54 7.61363e-01 5.30541e+01 2.97885e+01 +55 7.75351e-01 5.26375e+01 2.97885e+01 +56 7.89339e-01 5.22208e+01 2.97885e+01 +57 8.03327e-01 5.18041e+01 2.97885e+01 +58 8.17315e-01 5.13874e+01 2.97885e+01 +59 8.31303e-01 5.09707e+01 2.97885e+01 +60 8.45291e-01 5.05540e+01 2.97885e+01 +61 8.59279e-01 5.01374e+01 2.97885e+01 +62 8.73267e-01 4.97207e+01 2.97885e+01 +63 8.87255e-01 4.93040e+01 2.97885e+01 +64 9.01242e-01 4.88873e+01 2.97885e+01 +65 9.15230e-01 4.84706e+01 2.97885e+01 +66 9.29218e-01 4.80540e+01 2.97885e+01 +67 9.43206e-01 4.76373e+01 2.97885e+01 +68 9.57194e-01 4.72206e+01 2.97885e+01 +69 9.71182e-01 4.68039e+01 2.97885e+01 +70 9.85170e-01 4.63872e+01 2.97885e+01 +71 9.99158e-01 4.59706e+01 2.97885e+01 +72 1.01315e+00 4.55539e+01 2.97885e+01 +73 1.02713e+00 4.51372e+01 2.97885e+01 +74 1.04112e+00 4.47205e+01 2.97885e+01 +75 1.05511e+00 4.43038e+01 2.97885e+01 +76 1.06910e+00 4.38871e+01 2.97885e+01 +77 1.08309e+00 4.34705e+01 2.97885e+01 +78 1.09707e+00 4.30538e+01 2.97885e+01 +79 1.11106e+00 4.26371e+01 2.97885e+01 +80 1.12505e+00 4.22204e+01 2.97885e+01 +81 1.13904e+00 4.18037e+01 2.97885e+01 +82 1.15303e+00 4.13871e+01 2.97885e+01 +83 1.16701e+00 4.09704e+01 2.97885e+01 +84 1.18100e+00 4.05537e+01 2.97885e+01 +85 1.19499e+00 4.01370e+01 2.97885e+01 +86 1.20898e+00 3.97203e+01 2.97885e+01 +87 1.22297e+00 3.93036e+01 2.97885e+01 +88 1.23695e+00 3.88870e+01 2.97885e+01 +89 1.25094e+00 3.84703e+01 2.97885e+01 +90 1.26493e+00 3.80536e+01 2.97885e+01 +91 1.27892e+00 3.76369e+01 2.97885e+01 +92 1.29291e+00 3.72202e+01 2.97885e+01 +93 1.30689e+00 3.68036e+01 2.97885e+01 +94 1.32088e+00 3.63869e+01 2.97885e+01 +95 1.33487e+00 3.59702e+01 2.97885e+01 +96 1.34886e+00 3.55535e+01 2.97885e+01 +97 1.36285e+00 3.51368e+01 2.97885e+01 +98 1.37683e+00 3.47202e+01 2.97885e+01 +99 1.39082e+00 3.43035e+01 2.97885e+01 +100 1.40481e+00 3.38868e+01 2.97885e+01 +101 1.41880e+00 3.34701e+01 2.97885e+01 +102 1.43279e+00 3.30534e+01 2.97885e+01 +103 1.44677e+00 3.26367e+01 2.97885e+01 +104 1.46076e+00 3.22201e+01 2.97885e+01 +105 1.47475e+00 3.18034e+01 2.97885e+01 +106 1.48874e+00 3.13867e+01 2.97885e+01 +107 1.50273e+00 3.09700e+01 2.97885e+01 +108 1.51671e+00 3.05533e+01 2.97885e+01 +109 1.53070e+00 3.01367e+01 2.97885e+01 +110 1.54469e+00 2.97200e+01 2.97885e+01 +111 1.55868e+00 2.93033e+01 2.97885e+01 +112 1.57267e+00 2.88866e+01 2.97885e+01 +113 1.58665e+00 2.84699e+01 2.97885e+01 +114 1.60064e+00 2.80532e+01 2.97885e+01 +115 1.61463e+00 2.76366e+01 2.97885e+01 +116 1.62862e+00 2.72199e+01 2.97885e+01 +117 1.64261e+00 2.68032e+01 2.97885e+01 +118 1.65659e+00 2.63865e+01 2.97885e+01 +119 1.67058e+00 2.59698e+01 2.97885e+01 +120 1.68457e+00 2.55532e+01 2.97885e+01 +121 1.69856e+00 2.51365e+01 2.97885e+01 +122 1.71255e+00 2.47198e+01 2.97885e+01 +123 1.72653e+00 2.43031e+01 2.97885e+01 +124 1.74052e+00 2.38864e+01 2.97885e+01 +125 1.75451e+00 2.34698e+01 2.97885e+01 +126 1.76850e+00 2.30531e+01 2.97885e+01 +127 1.78248e+00 2.26364e+01 2.97885e+01 +128 1.79647e+00 2.22197e+01 2.97885e+01 +129 1.81046e+00 2.18030e+01 2.97885e+01 +130 1.82445e+00 2.13863e+01 2.97885e+01 +131 1.83844e+00 2.09697e+01 2.97885e+01 +132 1.85242e+00 2.05530e+01 2.97885e+01 +133 1.86641e+00 2.01363e+01 2.97885e+01 +134 1.88040e+00 1.97196e+01 2.97885e+01 +135 1.89439e+00 1.93029e+01 2.97885e+01 +136 1.90838e+00 1.88863e+01 2.97885e+01 +137 1.92236e+00 1.84696e+01 2.97885e+01 +138 1.93635e+00 1.80529e+01 2.97885e+01 +139 1.95034e+00 1.76362e+01 2.97885e+01 +140 1.96433e+00 1.72195e+01 2.97885e+01 +141 1.97832e+00 1.68028e+01 2.97885e+01 +142 1.99230e+00 1.63862e+01 2.97885e+01 +143 2.00629e+00 1.59695e+01 2.97885e+01 +144 2.02028e+00 1.55528e+01 2.97885e+01 +145 2.03427e+00 1.51361e+01 2.97885e+01 +146 2.04826e+00 1.47194e+01 2.97885e+01 +147 2.06224e+00 1.43028e+01 2.97885e+01 +148 2.07623e+00 1.38861e+01 2.97885e+01 +149 2.09022e+00 1.34694e+01 2.97885e+01 +150 2.10421e+00 1.30527e+01 2.97885e+01 +151 2.11820e+00 1.26360e+01 2.97885e+01 +152 2.13218e+00 1.22193e+01 2.97885e+01 +153 2.14617e+00 1.18027e+01 2.97885e+01 +154 2.16016e+00 1.13860e+01 2.97885e+01 +155 2.17415e+00 1.09693e+01 2.97884e+01 +156 2.18814e+00 1.05526e+01 2.97883e+01 +157 2.20212e+00 1.01360e+01 2.97882e+01 +158 2.21611e+00 9.71928e+00 2.97881e+01 +159 2.23010e+00 9.30260e+00 2.97881e+01 +160 2.24409e+00 8.88593e+00 2.97880e+01 +161 2.25808e+00 8.46925e+00 2.97880e+01 +162 2.27206e+00 8.05258e+00 2.97880e+01 +163 2.28605e+00 7.63590e+00 2.97880e+01 +164 2.30004e+00 7.21923e+00 2.97879e+01 +165 2.31403e+00 6.80256e+00 2.97879e+01 +166 2.32802e+00 6.38588e+00 2.97879e+01 +167 2.34200e+00 5.96927e+00 2.97676e+01 +168 2.35599e+00 5.55359e+00 2.96489e+01 +169 2.36998e+00 5.14031e+00 2.94242e+01 +170 2.38397e+00 4.73091e+00 2.90935e+01 +171 2.39796e+00 4.32688e+00 2.86569e+01 +172 2.41194e+00 3.92970e+00 2.81142e+01 +173 2.42593e+00 3.54085e+00 2.74656e+01 +174 2.43992e+00 3.16182e+00 2.67109e+01 +175 2.45391e+00 2.79409e+00 2.58503e+01 +176 2.46790e+00 2.43913e+00 2.48837e+01 +177 2.48188e+00 2.09843e+00 2.38111e+01 +178 2.49587e+00 1.77349e+00 2.26325e+01 +179 2.50986e+00 1.46576e+00 2.13479e+01 +180 2.52385e+00 1.17675e+00 1.99573e+01 +181 2.53784e+00 9.07935e-01 1.84607e+01 +182 2.55182e+00 6.60792e-01 1.68581e+01 +183 2.56581e+00 4.36807e-01 1.51495e+01 +184 2.57980e+00 2.37080e-01 1.34226e+01 +185 2.59379e+00 6.08637e-02 1.17882e+01 +186 2.60778e+00 -9.31403e-02 1.02467e+01 +187 2.62176e+00 -2.26231e-01 8.79811e+00 +188 2.63575e+00 -3.39709e-01 7.44237e+00 +189 2.64974e+00 -4.34872e-01 6.17953e+00 +190 2.66373e+00 -5.13020e-01 5.00957e+00 +191 2.67772e+00 -5.75452e-01 3.93249e+00 +192 2.69170e+00 -6.23468e-01 2.94830e+00 +193 2.70569e+00 -6.58367e-01 2.05700e+00 +194 2.71968e+00 -6.81448e-01 1.25859e+00 +195 2.73367e+00 -6.94011e-01 5.53061e-01 +196 2.74766e+00 -6.97354e-01 -5.95806e-02 +197 2.76164e+00 -6.92777e-01 -5.79336e-01 +198 2.77563e+00 -6.81579e-01 -1.00620e+00 +199 2.78962e+00 -6.65060e-01 -1.34019e+00 +200 2.80361e+00 -6.44516e-01 -1.58367e+00 +201 2.81760e+00 -6.20923e-01 -1.78620e+00 +202 2.83158e+00 -5.94645e-01 -1.96751e+00 +203 2.84557e+00 -5.65979e-01 -2.12762e+00 +204 2.85956e+00 -5.35222e-01 -2.26652e+00 +205 2.87355e+00 -5.02670e-01 -2.38420e+00 +206 2.88754e+00 -4.68620e-01 -2.48067e+00 +207 2.90152e+00 -4.33369e-01 -2.55594e+00 +208 2.91551e+00 -3.97214e-01 -2.60998e+00 +209 2.92950e+00 -3.60452e-01 -2.64282e+00 +210 2.94349e+00 -3.23378e-01 -2.65445e+00 +211 2.95747e+00 -2.86290e-01 -2.64486e+00 +212 2.97146e+00 -2.49484e-01 -2.61407e+00 +213 2.98545e+00 -2.13258e-01 -2.56206e+00 +214 2.99944e+00 -1.77907e-01 -2.48884e+00 +215 3.01343e+00 -1.43729e-01 -2.39441e+00 +216 3.02741e+00 -1.11020e-01 -2.27877e+00 +217 3.04140e+00 -8.00665e-02 -2.14583e+00 +218 3.05539e+00 -5.09814e-02 -2.01314e+00 +219 3.06938e+00 -2.37360e-02 -1.88280e+00 +220 3.08337e+00 1.70256e-03 -1.75480e+00 +221 3.09735e+00 2.53672e-02 -1.62916e+00 +222 3.11134e+00 4.72908e-02 -1.50587e+00 +223 3.12533e+00 6.75062e-02 -1.38492e+00 +224 3.13932e+00 8.60463e-02 -1.26633e+00 +225 3.15331e+00 1.02944e-01 -1.15009e+00 +226 3.16729e+00 1.18232e-01 -1.03619e+00 +227 3.18128e+00 1.31943e-01 -9.24647e-01 +228 3.19527e+00 1.44111e-01 -8.15452e-01 +229 3.20926e+00 1.54767e-01 -7.08608e-01 +230 3.22325e+00 1.63946e-01 -6.04113e-01 +231 3.23723e+00 1.71679e-01 -5.01968e-01 +232 3.25122e+00 1.78000e-01 -4.02173e-01 +233 3.26521e+00 1.82941e-01 -3.04727e-01 +234 3.27920e+00 1.86541e-01 -2.10906e-01 +235 3.29319e+00 1.88867e-01 -1.22592e-01 +236 3.30717e+00 1.89996e-01 -3.98024e-02 +237 3.32116e+00 1.90006e-01 3.74622e-02 +238 3.33515e+00 1.88974e-01 1.09202e-01 +239 3.34914e+00 1.86977e-01 1.75417e-01 +240 3.36313e+00 1.84092e-01 2.36108e-01 +241 3.37711e+00 1.80398e-01 2.91274e-01 +242 3.39110e+00 1.75970e-01 3.40915e-01 +243 3.40509e+00 1.70886e-01 3.85032e-01 +244 3.41908e+00 1.65224e-01 4.23624e-01 +245 3.43307e+00 1.59060e-01 4.56691e-01 +246 3.44705e+00 1.52473e-01 4.84233e-01 +247 3.46104e+00 1.45539e-01 5.06251e-01 +248 3.47503e+00 1.38336e-01 5.22745e-01 +249 3.48902e+00 1.30941e-01 5.33713e-01 +250 3.50301e+00 1.23430e-01 5.39270e-01 +251 3.51699e+00 1.15863e-01 5.42677e-01 +252 3.53098e+00 1.08252e-01 5.45441e-01 +253 3.54497e+00 1.00606e-01 5.47559e-01 +254 3.55896e+00 9.29361e-02 5.49033e-01 +255 3.57295e+00 8.52497e-02 5.49863e-01 +256 3.58693e+00 7.75562e-02 5.50047e-01 +257 3.60092e+00 6.98646e-02 5.49587e-01 +258 3.61491e+00 6.21839e-02 5.48483e-01 +259 3.62890e+00 5.45233e-02 5.46734e-01 +260 3.64289e+00 4.68915e-02 5.44340e-01 +261 3.65687e+00 3.92978e-02 5.41301e-01 +262 3.67086e+00 3.17511e-02 5.37618e-01 +263 3.68485e+00 2.42605e-02 5.33290e-01 +264 3.69884e+00 1.68348e-02 5.28318e-01 +265 3.71283e+00 9.48329e-03 5.22701e-01 +266 3.72681e+00 2.21481e-03 5.16439e-01 +267 3.74080e+00 -4.96183e-03 5.09637e-01 +268 3.75479e+00 -1.20430e-02 5.02841e-01 +269 3.76878e+00 -1.90297e-02 4.96131e-01 +270 3.78277e+00 -2.59231e-02 4.89508e-01 +271 3.79675e+00 -3.27245e-02 4.82970e-01 +272 3.81074e+00 -3.94351e-02 4.76519e-01 +273 3.82473e+00 -4.60560e-02 4.70153e-01 +274 3.83872e+00 -5.25885e-02 4.63874e-01 +275 3.85271e+00 -5.90337e-02 4.57680e-01 +276 3.86669e+00 -6.53929e-02 4.51572e-01 +277 3.88068e+00 -7.16673e-02 4.45551e-01 +278 3.89467e+00 -7.78580e-02 4.39615e-01 +279 3.90866e+00 -8.39663e-02 4.33766e-01 +280 3.92265e+00 -8.99934e-02 4.28002e-01 +281 3.93663e+00 -9.59405e-02 4.22325e-01 +282 3.95062e+00 -1.01809e-01 4.16733e-01 +283 3.96461e+00 -1.07599e-01 4.11228e-01 +284 3.97860e+00 -1.13313e-01 4.05557e-01 +285 3.99259e+00 -1.18942e-01 3.99290e-01 +286 4.00657e+00 -1.24480e-01 3.92417e-01 +287 4.02056e+00 -1.29918e-01 3.84940e-01 +288 4.03455e+00 -1.35247e-01 3.76858e-01 +289 4.04854e+00 -1.40458e-01 3.68172e-01 +290 4.06253e+00 -1.45544e-01 3.58880e-01 +291 4.07651e+00 -1.50495e-01 3.48985e-01 +292 4.09050e+00 -1.55304e-01 3.38484e-01 +293 4.10449e+00 -1.59962e-01 3.27379e-01 +294 4.11848e+00 -1.64460e-01 3.15669e-01 +295 4.13246e+00 -1.68790e-01 3.03355e-01 +296 4.14645e+00 -1.72944e-01 2.90436e-01 +297 4.16044e+00 -1.76913e-01 2.76912e-01 +298 4.17443e+00 -1.80688e-01 2.62784e-01 +299 4.18842e+00 -1.84261e-01 2.48051e-01 +300 4.20240e+00 -1.87625e-01 2.32724e-01 +301 4.21639e+00 -1.90772e-01 2.17283e-01 +302 4.23038e+00 -1.93704e-01 2.01985e-01 +303 4.24437e+00 -1.96423e-01 1.86829e-01 +304 4.25836e+00 -1.98931e-01 1.71815e-01 +305 4.27234e+00 -2.01230e-01 1.56943e-01 +306 4.28633e+00 -2.03323e-01 1.42213e-01 +307 4.30032e+00 -2.05210e-01 1.27626e-01 +308 4.31431e+00 -2.06894e-01 1.13180e-01 +309 4.32830e+00 -2.08377e-01 9.88768e-02 +310 4.34228e+00 -2.09661e-01 8.47157e-02 +311 4.35627e+00 -2.10747e-01 7.06968e-02 +312 4.37026e+00 -2.11639e-01 5.68200e-02 +313 4.38425e+00 -2.12338e-01 4.30854e-02 +314 4.39824e+00 -2.12845e-01 2.94929e-02 +315 4.41222e+00 -2.13163e-01 1.60426e-02 +316 4.42621e+00 -2.13294e-01 2.73450e-03 +317 4.44020e+00 -2.13240e-01 -1.04284e-02 +318 4.45419e+00 -2.13004e-01 -2.34265e-02 +319 4.46818e+00 -2.12586e-01 -3.62567e-02 +320 4.48216e+00 -2.11990e-01 -4.89188e-02 +321 4.49615e+00 -2.11218e-01 -6.14128e-02 +322 4.51014e+00 -2.10273e-01 -7.37388e-02 +323 4.52413e+00 -2.09156e-01 -8.58968e-02 +324 4.53812e+00 -2.07870e-01 -9.78868e-02 +325 4.55210e+00 -2.06418e-01 -1.09709e-01 +326 4.56609e+00 -2.04802e-01 -1.21363e-01 +327 4.58008e+00 -2.03024e-01 -1.32848e-01 +328 4.59407e+00 -2.01086e-01 -1.44166e-01 +329 4.60806e+00 -1.98991e-01 -1.55316e-01 +330 4.62204e+00 -1.96742e-01 -1.66298e-01 +331 4.63603e+00 -1.94340e-01 -1.77111e-01 +332 4.65002e+00 -1.91788e-01 -1.87757e-01 +333 4.66401e+00 -1.89088e-01 -1.98235e-01 +334 4.67800e+00 -1.86243e-01 -2.08492e-01 +335 4.69198e+00 -1.83257e-01 -2.18424e-01 +336 4.70597e+00 -1.80134e-01 -2.28027e-01 +337 4.71996e+00 -1.76879e-01 -2.37302e-01 +338 4.73395e+00 -1.73497e-01 -2.46250e-01 +339 4.74794e+00 -1.69991e-01 -2.54869e-01 +340 4.76192e+00 -1.66368e-01 -2.63160e-01 +341 4.77591e+00 -1.62631e-01 -2.71122e-01 +342 4.78990e+00 -1.58785e-01 -2.78757e-01 +343 4.80389e+00 -1.54834e-01 -2.86063e-01 +344 4.81788e+00 -1.50783e-01 -2.93041e-01 +345 4.83186e+00 -1.46637e-01 -2.99691e-01 +346 4.84585e+00 -1.42401e-01 -3.06013e-01 +347 4.85984e+00 -1.38078e-01 -3.12006e-01 +348 4.87383e+00 -1.33674e-01 -3.17671e-01 +349 4.88782e+00 -1.29192e-01 -3.23008e-01 +350 4.90180e+00 -1.24639e-01 -3.28019e-01 +351 4.91579e+00 -1.20017e-01 -3.32802e-01 +352 4.92978e+00 -1.15329e-01 -3.37422e-01 +353 4.94377e+00 -1.10578e-01 -3.41876e-01 +354 4.95776e+00 -1.05765e-01 -3.46167e-01 +355 4.97174e+00 -1.00894e-01 -3.50292e-01 +356 4.98573e+00 -9.59664e-02 -3.54254e-01 +357 4.99972e+00 -9.09843e-02 -3.58050e-01 +358 5.01371e+00 -8.59503e-02 -3.61683e-01 +359 5.02770e+00 -8.08667e-02 -3.65150e-01 +360 5.04168e+00 -7.57357e-02 -3.68454e-01 +361 5.05567e+00 -7.05596e-02 -3.71592e-01 +362 5.06966e+00 -6.53408e-02 -3.74567e-01 +363 5.08365e+00 -6.00815e-02 -3.77377e-01 +364 5.09764e+00 -5.47841e-02 -3.80022e-01 +365 5.11162e+00 -4.94508e-02 -3.82503e-01 +366 5.12561e+00 -4.40840e-02 -3.84819e-01 +367 5.13960e+00 -3.86861e-02 -3.86857e-01 +368 5.15359e+00 -3.32669e-02 -3.87771e-01 +369 5.16758e+00 -2.78439e-02 -3.87387e-01 +370 5.18156e+00 -2.24354e-02 -3.85706e-01 +371 5.19555e+00 -1.70595e-02 -3.82729e-01 +372 5.20954e+00 -1.17343e-02 -3.78454e-01 +373 5.22353e+00 -6.47792e-03 -3.72882e-01 +374 5.23752e+00 -1.30859e-03 -3.66012e-01 +375 5.25150e+00 3.75557e-03 -3.57846e-01 +376 5.26549e+00 8.69644e-03 -3.48382e-01 +377 5.27948e+00 1.34959e-02 -3.37622e-01 +378 5.29347e+00 1.81357e-02 -3.25564e-01 +379 5.30745e+00 2.25978e-02 -3.12209e-01 +380 5.32144e+00 2.68640e-02 -2.97557e-01 +381 5.33543e+00 3.09161e-02 -2.81607e-01 +382 5.34942e+00 3.47361e-02 -2.64361e-01 +383 5.36341e+00 3.83058e-02 -2.45817e-01 +384 5.37739e+00 4.16089e-02 -2.26496e-01 +385 5.39138e+00 4.46444e-02 -2.07598e-01 +386 5.40537e+00 4.74189e-02 -1.89169e-01 +387 5.41936e+00 4.99388e-02 -1.71211e-01 +388 5.43335e+00 5.22108e-02 -1.53723e-01 +389 5.44733e+00 5.42415e-02 -1.36705e-01 +390 5.46132e+00 5.60375e-02 -1.20158e-01 +391 5.47531e+00 5.76053e-02 -1.04081e-01 +392 5.48930e+00 5.89514e-02 -8.84740e-02 +393 5.50329e+00 6.00826e-02 -7.33374e-02 +394 5.51727e+00 6.10053e-02 -5.86710e-02 +395 5.53126e+00 6.17262e-02 -4.44749e-02 +396 5.54525e+00 6.22517e-02 -3.07490e-02 +397 5.55924e+00 6.25886e-02 -1.74934e-02 +398 5.57323e+00 6.27433e-02 -4.70807e-03 +399 5.58721e+00 6.27225e-02 7.60702e-03 +400 5.60120e+00 6.25327e-02 1.94503e-02 +401 5.61519e+00 6.21817e-02 3.05831e-02 +402 5.62918e+00 6.16812e-02 4.08330e-02 +403 5.64317e+00 6.10435e-02 5.01999e-02 +404 5.65715e+00 6.02810e-02 5.86840e-02 +405 5.67114e+00 5.94059e-02 6.62851e-02 +406 5.68513e+00 5.84307e-02 7.30034e-02 +407 5.69912e+00 5.73677e-02 7.88387e-02 +408 5.71311e+00 5.62292e-02 8.37911e-02 +409 5.72709e+00 5.50277e-02 8.78606e-02 +410 5.74108e+00 5.37754e-02 9.10472e-02 +411 5.75507e+00 5.24846e-02 9.33509e-02 +412 5.76906e+00 5.11679e-02 9.47717e-02 +413 5.78305e+00 4.98374e-02 9.53096e-02 +414 5.79703e+00 4.85056e-02 9.49645e-02 +415 5.81102e+00 4.71848e-02 9.37366e-02 +416 5.82501e+00 4.58874e-02 9.16257e-02 +417 5.83900e+00 4.46255e-02 8.87199e-02 +418 5.85299e+00 4.34050e-02 8.58142e-02 +419 5.86697e+00 4.22238e-02 8.30983e-02 +420 5.88096e+00 4.10794e-02 8.05724e-02 +421 5.89495e+00 3.99689e-02 7.82364e-02 +422 5.90894e+00 3.88897e-02 7.60904e-02 +423 5.92293e+00 3.78393e-02 7.41343e-02 +424 5.93691e+00 3.68149e-02 7.23682e-02 +425 5.95090e+00 3.58138e-02 7.07920e-02 +426 5.96489e+00 3.48335e-02 6.94057e-02 +427 5.97888e+00 3.38712e-02 6.82094e-02 +428 5.99287e+00 3.29244e-02 6.72030e-02 +429 6.00685e+00 3.19903e-02 6.63865e-02 +430 6.02084e+00 3.10663e-02 6.57600e-02 +431 6.03483e+00 3.01497e-02 6.53234e-02 +432 6.04882e+00 2.92379e-02 6.50768e-02 +433 6.06281e+00 2.83282e-02 6.50201e-02 +434 6.07679e+00 2.74183e-02 6.50695e-02 +435 6.09078e+00 2.65085e-02 6.50011e-02 +436 6.10477e+00 2.56005e-02 6.48029e-02 +437 6.11876e+00 2.46961e-02 6.44747e-02 +438 6.13275e+00 2.37973e-02 6.40165e-02 +439 6.14673e+00 2.29058e-02 6.34285e-02 +440 6.16072e+00 2.20235e-02 6.27105e-02 +441 6.17471e+00 2.11520e-02 6.18626e-02 +442 6.18870e+00 2.02934e-02 6.08847e-02 +443 6.20269e+00 1.94493e-02 5.97769e-02 +444 6.21667e+00 1.86217e-02 5.85392e-02 +445 6.23066e+00 1.78123e-02 5.71716e-02 +446 6.24465e+00 1.70229e-02 5.56740e-02 +447 6.25864e+00 1.62553e-02 5.40465e-02 +448 6.27263e+00 1.55115e-02 5.22891e-02 +449 6.28661e+00 1.47931e-02 5.04017e-02 +450 6.30060e+00 1.41020e-02 4.83846e-02 +451 6.31459e+00 1.34396e-02 4.63409e-02 +452 6.32858e+00 1.28053e-02 4.43579e-02 +453 6.34257e+00 1.21984e-02 4.24357e-02 +454 6.35655e+00 1.16179e-02 4.05742e-02 +455 6.37054e+00 1.10630e-02 3.87735e-02 +456 6.38453e+00 1.05329e-02 3.70334e-02 +457 6.39852e+00 1.00266e-02 3.53541e-02 +458 6.41251e+00 9.54350e-03 3.37356e-02 +459 6.42649e+00 9.08258e-03 3.21778e-02 +460 6.44048e+00 8.64301e-03 3.06807e-02 +461 6.45447e+00 8.22397e-03 2.92443e-02 +462 6.46846e+00 7.82459e-03 2.78687e-02 +463 6.48244e+00 7.44403e-03 2.65539e-02 +464 6.49643e+00 7.08144e-03 2.52997e-02 +465 6.51042e+00 6.73597e-03 2.41063e-02 +466 6.52441e+00 6.40676e-03 2.29736e-02 +467 6.53840e+00 6.09297e-03 2.19024e-02 +468 6.55238e+00 5.79370e-03 2.08997e-02 +469 6.56637e+00 5.50795e-03 1.99677e-02 +470 6.58036e+00 5.23475e-03 1.91064e-02 +471 6.59435e+00 4.97310e-03 1.83158e-02 +472 6.60834e+00 4.72202e-03 1.75958e-02 +473 6.62232e+00 4.48051e-03 1.69465e-02 +474 6.63631e+00 4.24760e-03 1.63679e-02 +475 6.65030e+00 4.02228e-03 1.58599e-02 +476 6.66429e+00 3.80357e-03 1.54226e-02 +477 6.67828e+00 3.59048e-03 1.50560e-02 +478 6.69226e+00 3.38203e-03 1.47600e-02 +479 6.70625e+00 3.17723e-03 1.45348e-02 +480 6.72024e+00 2.97508e-03 1.43801e-02 +481 6.73423e+00 2.77460e-03 1.42962e-02 +482 6.74822e+00 2.57480e-03 1.42829e-02 +483 6.76220e+00 2.37469e-03 1.43403e-02 +484 6.77619e+00 2.17343e-03 1.44248e-02 +485 6.79018e+00 1.97168e-03 1.44017e-02 +486 6.80417e+00 1.77107e-03 1.42615e-02 +487 6.81816e+00 1.57325e-03 1.40041e-02 +488 6.83214e+00 1.37984e-03 1.36297e-02 +489 6.84613e+00 1.19249e-03 1.31381e-02 +490 6.86012e+00 1.01284e-03 1.25294e-02 +491 6.87411e+00 8.42516e-04 1.18035e-02 +492 6.88810e+00 6.83168e-04 1.09605e-02 +493 6.90208e+00 5.36431e-04 1.00004e-02 +494 6.91607e+00 4.03943e-04 8.92318e-03 +495 6.93006e+00 2.87343e-04 7.72880e-03 +496 6.94405e+00 1.88268e-04 6.41730e-03 +497 6.95804e+00 1.08359e-04 4.98867e-03 +498 6.97202e+00 4.92516e-05 3.44291e-03 +499 6.98601e+00 1.25860e-05 1.78002e-03 +500 7.00000e+00 0.00000e+00 0.00000e+00 + + + +NonBondNull +N 500 R 0.0000000001 10.0 + +1 0.0000e+00 0.0000e+00 0.0000e+00 +2 2.0040e-02 0.0000e+00 0.0000e+00 +3 4.0080e-02 0.0000e+00 0.0000e+00 +4 6.0120e-02 0.0000e+00 0.0000e+00 +5 8.0160e-02 0.0000e+00 0.0000e+00 +6 1.0020e-01 0.0000e+00 0.0000e+00 +7 1.2024e-01 0.0000e+00 0.0000e+00 +8 1.4028e-01 0.0000e+00 0.0000e+00 +9 1.6032e-01 0.0000e+00 0.0000e+00 +10 1.8036e-01 0.0000e+00 0.0000e+00 +11 2.0040e-01 0.0000e+00 0.0000e+00 +12 2.2044e-01 0.0000e+00 0.0000e+00 +13 2.4048e-01 0.0000e+00 0.0000e+00 +14 2.6052e-01 0.0000e+00 0.0000e+00 +15 2.8056e-01 0.0000e+00 0.0000e+00 +16 3.0060e-01 0.0000e+00 0.0000e+00 +17 3.2064e-01 0.0000e+00 0.0000e+00 +18 3.4068e-01 0.0000e+00 0.0000e+00 +19 3.6072e-01 0.0000e+00 0.0000e+00 +20 3.8076e-01 0.0000e+00 0.0000e+00 +21 4.0080e-01 0.0000e+00 0.0000e+00 +22 4.2084e-01 0.0000e+00 0.0000e+00 +23 4.4088e-01 0.0000e+00 0.0000e+00 +24 4.6092e-01 0.0000e+00 0.0000e+00 +25 4.8096e-01 0.0000e+00 0.0000e+00 +26 5.0100e-01 0.0000e+00 0.0000e+00 +27 5.2104e-01 0.0000e+00 0.0000e+00 +28 5.4108e-01 0.0000e+00 0.0000e+00 +29 5.6112e-01 0.0000e+00 0.0000e+00 +30 5.8116e-01 0.0000e+00 0.0000e+00 +31 6.0120e-01 0.0000e+00 0.0000e+00 +32 6.2124e-01 0.0000e+00 0.0000e+00 +33 6.4128e-01 0.0000e+00 0.0000e+00 +34 6.6132e-01 0.0000e+00 0.0000e+00 +35 6.8136e-01 0.0000e+00 0.0000e+00 +36 7.0140e-01 0.0000e+00 0.0000e+00 +37 7.2144e-01 0.0000e+00 0.0000e+00 +38 7.4148e-01 0.0000e+00 0.0000e+00 +39 7.6152e-01 0.0000e+00 0.0000e+00 +40 7.8156e-01 0.0000e+00 0.0000e+00 +41 8.0160e-01 0.0000e+00 0.0000e+00 +42 8.2164e-01 0.0000e+00 0.0000e+00 +43 8.4168e-01 0.0000e+00 0.0000e+00 +44 8.6172e-01 0.0000e+00 0.0000e+00 +45 8.8176e-01 0.0000e+00 0.0000e+00 +46 9.0180e-01 0.0000e+00 0.0000e+00 +47 9.2184e-01 0.0000e+00 0.0000e+00 +48 9.4188e-01 0.0000e+00 0.0000e+00 +49 9.6192e-01 0.0000e+00 0.0000e+00 +50 9.8196e-01 0.0000e+00 0.0000e+00 +51 1.0020e+00 0.0000e+00 0.0000e+00 +52 1.0220e+00 0.0000e+00 0.0000e+00 +53 1.0421e+00 0.0000e+00 0.0000e+00 +54 1.0621e+00 0.0000e+00 0.0000e+00 +55 1.0822e+00 0.0000e+00 0.0000e+00 +56 1.1022e+00 0.0000e+00 0.0000e+00 +57 1.1222e+00 0.0000e+00 0.0000e+00 +58 1.1423e+00 0.0000e+00 0.0000e+00 +59 1.1623e+00 0.0000e+00 0.0000e+00 +60 1.1824e+00 0.0000e+00 0.0000e+00 +61 1.2024e+00 0.0000e+00 0.0000e+00 +62 1.2224e+00 0.0000e+00 0.0000e+00 +63 1.2425e+00 0.0000e+00 0.0000e+00 +64 1.2625e+00 0.0000e+00 0.0000e+00 +65 1.2826e+00 0.0000e+00 0.0000e+00 +66 1.3026e+00 0.0000e+00 0.0000e+00 +67 1.3226e+00 0.0000e+00 0.0000e+00 +68 1.3427e+00 0.0000e+00 0.0000e+00 +69 1.3627e+00 0.0000e+00 0.0000e+00 +70 1.3828e+00 0.0000e+00 0.0000e+00 +71 1.4028e+00 0.0000e+00 0.0000e+00 +72 1.4228e+00 0.0000e+00 0.0000e+00 +73 1.4429e+00 0.0000e+00 0.0000e+00 +74 1.4629e+00 0.0000e+00 0.0000e+00 +75 1.4830e+00 0.0000e+00 0.0000e+00 +76 1.5030e+00 0.0000e+00 0.0000e+00 +77 1.5230e+00 0.0000e+00 0.0000e+00 +78 1.5431e+00 0.0000e+00 0.0000e+00 +79 1.5631e+00 0.0000e+00 0.0000e+00 +80 1.5832e+00 0.0000e+00 0.0000e+00 +81 1.6032e+00 0.0000e+00 0.0000e+00 +82 1.6232e+00 0.0000e+00 0.0000e+00 +83 1.6433e+00 0.0000e+00 0.0000e+00 +84 1.6633e+00 0.0000e+00 0.0000e+00 +85 1.6834e+00 0.0000e+00 0.0000e+00 +86 1.7034e+00 0.0000e+00 0.0000e+00 +87 1.7234e+00 0.0000e+00 0.0000e+00 +88 1.7435e+00 0.0000e+00 0.0000e+00 +89 1.7635e+00 0.0000e+00 0.0000e+00 +90 1.7836e+00 0.0000e+00 0.0000e+00 +91 1.8036e+00 0.0000e+00 0.0000e+00 +92 1.8236e+00 0.0000e+00 0.0000e+00 +93 1.8437e+00 0.0000e+00 0.0000e+00 +94 1.8637e+00 0.0000e+00 0.0000e+00 +95 1.8838e+00 0.0000e+00 0.0000e+00 +96 1.9038e+00 0.0000e+00 0.0000e+00 +97 1.9238e+00 0.0000e+00 0.0000e+00 +98 1.9439e+00 0.0000e+00 0.0000e+00 +99 1.9639e+00 0.0000e+00 0.0000e+00 +100 1.9840e+00 0.0000e+00 0.0000e+00 +101 2.0040e+00 0.0000e+00 0.0000e+00 +102 2.0240e+00 0.0000e+00 0.0000e+00 +103 2.0441e+00 0.0000e+00 0.0000e+00 +104 2.0641e+00 0.0000e+00 0.0000e+00 +105 2.0842e+00 0.0000e+00 0.0000e+00 +106 2.1042e+00 0.0000e+00 0.0000e+00 +107 2.1242e+00 0.0000e+00 0.0000e+00 +108 2.1443e+00 0.0000e+00 0.0000e+00 +109 2.1643e+00 0.0000e+00 0.0000e+00 +110 2.1844e+00 0.0000e+00 0.0000e+00 +111 2.2044e+00 0.0000e+00 0.0000e+00 +112 2.2244e+00 0.0000e+00 0.0000e+00 +113 2.2445e+00 0.0000e+00 0.0000e+00 +114 2.2645e+00 0.0000e+00 0.0000e+00 +115 2.2846e+00 0.0000e+00 0.0000e+00 +116 2.3046e+00 0.0000e+00 0.0000e+00 +117 2.3246e+00 0.0000e+00 0.0000e+00 +118 2.3447e+00 0.0000e+00 0.0000e+00 +119 2.3647e+00 0.0000e+00 0.0000e+00 +120 2.3848e+00 0.0000e+00 0.0000e+00 +121 2.4048e+00 0.0000e+00 0.0000e+00 +122 2.4248e+00 0.0000e+00 0.0000e+00 +123 2.4449e+00 0.0000e+00 0.0000e+00 +124 2.4649e+00 0.0000e+00 0.0000e+00 +125 2.4850e+00 0.0000e+00 0.0000e+00 +126 2.5050e+00 0.0000e+00 0.0000e+00 +127 2.5251e+00 0.0000e+00 0.0000e+00 +128 2.5451e+00 0.0000e+00 0.0000e+00 +129 2.5651e+00 0.0000e+00 0.0000e+00 +130 2.5852e+00 0.0000e+00 0.0000e+00 +131 2.6052e+00 0.0000e+00 0.0000e+00 +132 2.6253e+00 0.0000e+00 0.0000e+00 +133 2.6453e+00 0.0000e+00 0.0000e+00 +134 2.6653e+00 0.0000e+00 0.0000e+00 +135 2.6854e+00 0.0000e+00 0.0000e+00 +136 2.7054e+00 0.0000e+00 0.0000e+00 +137 2.7255e+00 0.0000e+00 0.0000e+00 +138 2.7455e+00 0.0000e+00 0.0000e+00 +139 2.7655e+00 0.0000e+00 0.0000e+00 +140 2.7856e+00 0.0000e+00 0.0000e+00 +141 2.8056e+00 0.0000e+00 0.0000e+00 +142 2.8257e+00 0.0000e+00 0.0000e+00 +143 2.8457e+00 0.0000e+00 0.0000e+00 +144 2.8657e+00 0.0000e+00 0.0000e+00 +145 2.8858e+00 0.0000e+00 0.0000e+00 +146 2.9058e+00 0.0000e+00 0.0000e+00 +147 2.9259e+00 0.0000e+00 0.0000e+00 +148 2.9459e+00 0.0000e+00 0.0000e+00 +149 2.9659e+00 0.0000e+00 0.0000e+00 +150 2.9860e+00 0.0000e+00 0.0000e+00 +151 3.0060e+00 0.0000e+00 0.0000e+00 +152 3.0261e+00 0.0000e+00 0.0000e+00 +153 3.0461e+00 0.0000e+00 0.0000e+00 +154 3.0661e+00 0.0000e+00 0.0000e+00 +155 3.0862e+00 0.0000e+00 0.0000e+00 +156 3.1062e+00 0.0000e+00 0.0000e+00 +157 3.1263e+00 0.0000e+00 0.0000e+00 +158 3.1463e+00 0.0000e+00 0.0000e+00 +159 3.1663e+00 0.0000e+00 0.0000e+00 +160 3.1864e+00 0.0000e+00 0.0000e+00 +161 3.2064e+00 0.0000e+00 0.0000e+00 +162 3.2265e+00 0.0000e+00 0.0000e+00 +163 3.2465e+00 0.0000e+00 0.0000e+00 +164 3.2665e+00 0.0000e+00 0.0000e+00 +165 3.2866e+00 0.0000e+00 0.0000e+00 +166 3.3066e+00 0.0000e+00 0.0000e+00 +167 3.3267e+00 0.0000e+00 0.0000e+00 +168 3.3467e+00 0.0000e+00 0.0000e+00 +169 3.3667e+00 0.0000e+00 0.0000e+00 +170 3.3868e+00 0.0000e+00 0.0000e+00 +171 3.4068e+00 0.0000e+00 0.0000e+00 +172 3.4269e+00 0.0000e+00 0.0000e+00 +173 3.4469e+00 0.0000e+00 0.0000e+00 +174 3.4669e+00 0.0000e+00 0.0000e+00 +175 3.4870e+00 0.0000e+00 0.0000e+00 +176 3.5070e+00 0.0000e+00 0.0000e+00 +177 3.5271e+00 0.0000e+00 0.0000e+00 +178 3.5471e+00 0.0000e+00 0.0000e+00 +179 3.5671e+00 0.0000e+00 0.0000e+00 +180 3.5872e+00 0.0000e+00 0.0000e+00 +181 3.6072e+00 0.0000e+00 0.0000e+00 +182 3.6273e+00 0.0000e+00 0.0000e+00 +183 3.6473e+00 0.0000e+00 0.0000e+00 +184 3.6673e+00 0.0000e+00 0.0000e+00 +185 3.6874e+00 0.0000e+00 0.0000e+00 +186 3.7074e+00 0.0000e+00 0.0000e+00 +187 3.7275e+00 0.0000e+00 0.0000e+00 +188 3.7475e+00 0.0000e+00 0.0000e+00 +189 3.7675e+00 0.0000e+00 0.0000e+00 +190 3.7876e+00 0.0000e+00 0.0000e+00 +191 3.8076e+00 0.0000e+00 0.0000e+00 +192 3.8277e+00 0.0000e+00 0.0000e+00 +193 3.8477e+00 0.0000e+00 0.0000e+00 +194 3.8677e+00 0.0000e+00 0.0000e+00 +195 3.8878e+00 0.0000e+00 0.0000e+00 +196 3.9078e+00 0.0000e+00 0.0000e+00 +197 3.9279e+00 0.0000e+00 0.0000e+00 +198 3.9479e+00 0.0000e+00 0.0000e+00 +199 3.9679e+00 0.0000e+00 0.0000e+00 +200 3.9880e+00 0.0000e+00 0.0000e+00 +201 4.0080e+00 0.0000e+00 0.0000e+00 +202 4.0281e+00 0.0000e+00 0.0000e+00 +203 4.0481e+00 0.0000e+00 0.0000e+00 +204 4.0681e+00 0.0000e+00 0.0000e+00 +205 4.0882e+00 0.0000e+00 0.0000e+00 +206 4.1082e+00 0.0000e+00 0.0000e+00 +207 4.1283e+00 0.0000e+00 0.0000e+00 +208 4.1483e+00 0.0000e+00 0.0000e+00 +209 4.1683e+00 0.0000e+00 0.0000e+00 +210 4.1884e+00 0.0000e+00 0.0000e+00 +211 4.2084e+00 0.0000e+00 0.0000e+00 +212 4.2285e+00 0.0000e+00 0.0000e+00 +213 4.2485e+00 0.0000e+00 0.0000e+00 +214 4.2685e+00 0.0000e+00 0.0000e+00 +215 4.2886e+00 0.0000e+00 0.0000e+00 +216 4.3086e+00 0.0000e+00 0.0000e+00 +217 4.3287e+00 0.0000e+00 0.0000e+00 +218 4.3487e+00 0.0000e+00 0.0000e+00 +219 4.3687e+00 0.0000e+00 0.0000e+00 +220 4.3888e+00 0.0000e+00 0.0000e+00 +221 4.4088e+00 0.0000e+00 0.0000e+00 +222 4.4289e+00 0.0000e+00 0.0000e+00 +223 4.4489e+00 0.0000e+00 0.0000e+00 +224 4.4689e+00 0.0000e+00 0.0000e+00 +225 4.4890e+00 0.0000e+00 0.0000e+00 +226 4.5090e+00 0.0000e+00 0.0000e+00 +227 4.5291e+00 0.0000e+00 0.0000e+00 +228 4.5491e+00 0.0000e+00 0.0000e+00 +229 4.5691e+00 0.0000e+00 0.0000e+00 +230 4.5892e+00 0.0000e+00 0.0000e+00 +231 4.6092e+00 0.0000e+00 0.0000e+00 +232 4.6293e+00 0.0000e+00 0.0000e+00 +233 4.6493e+00 0.0000e+00 0.0000e+00 +234 4.6693e+00 0.0000e+00 0.0000e+00 +235 4.6894e+00 0.0000e+00 0.0000e+00 +236 4.7094e+00 0.0000e+00 0.0000e+00 +237 4.7295e+00 0.0000e+00 0.0000e+00 +238 4.7495e+00 0.0000e+00 0.0000e+00 +239 4.7695e+00 0.0000e+00 0.0000e+00 +240 4.7896e+00 0.0000e+00 0.0000e+00 +241 4.8096e+00 0.0000e+00 0.0000e+00 +242 4.8297e+00 0.0000e+00 0.0000e+00 +243 4.8497e+00 0.0000e+00 0.0000e+00 +244 4.8697e+00 0.0000e+00 0.0000e+00 +245 4.8898e+00 0.0000e+00 0.0000e+00 +246 4.9098e+00 0.0000e+00 0.0000e+00 +247 4.9299e+00 0.0000e+00 0.0000e+00 +248 4.9499e+00 0.0000e+00 0.0000e+00 +249 4.9699e+00 0.0000e+00 0.0000e+00 +250 4.9900e+00 0.0000e+00 0.0000e+00 +251 5.0100e+00 0.0000e+00 0.0000e+00 +252 5.0301e+00 0.0000e+00 0.0000e+00 +253 5.0501e+00 0.0000e+00 0.0000e+00 +254 5.0701e+00 0.0000e+00 0.0000e+00 +255 5.0902e+00 0.0000e+00 0.0000e+00 +256 5.1102e+00 0.0000e+00 0.0000e+00 +257 5.1303e+00 0.0000e+00 0.0000e+00 +258 5.1503e+00 0.0000e+00 0.0000e+00 +259 5.1703e+00 0.0000e+00 0.0000e+00 +260 5.1904e+00 0.0000e+00 0.0000e+00 +261 5.2104e+00 0.0000e+00 0.0000e+00 +262 5.2305e+00 0.0000e+00 0.0000e+00 +263 5.2505e+00 0.0000e+00 0.0000e+00 +264 5.2705e+00 0.0000e+00 0.0000e+00 +265 5.2906e+00 0.0000e+00 0.0000e+00 +266 5.3106e+00 0.0000e+00 0.0000e+00 +267 5.3307e+00 0.0000e+00 0.0000e+00 +268 5.3507e+00 0.0000e+00 0.0000e+00 +269 5.3707e+00 0.0000e+00 0.0000e+00 +270 5.3908e+00 0.0000e+00 0.0000e+00 +271 5.4108e+00 0.0000e+00 0.0000e+00 +272 5.4309e+00 0.0000e+00 0.0000e+00 +273 5.4509e+00 0.0000e+00 0.0000e+00 +274 5.4709e+00 0.0000e+00 0.0000e+00 +275 5.4910e+00 0.0000e+00 0.0000e+00 +276 5.5110e+00 0.0000e+00 0.0000e+00 +277 5.5311e+00 0.0000e+00 0.0000e+00 +278 5.5511e+00 0.0000e+00 0.0000e+00 +279 5.5711e+00 0.0000e+00 0.0000e+00 +280 5.5912e+00 0.0000e+00 0.0000e+00 +281 5.6112e+00 0.0000e+00 0.0000e+00 +282 5.6313e+00 0.0000e+00 0.0000e+00 +283 5.6513e+00 0.0000e+00 0.0000e+00 +284 5.6713e+00 0.0000e+00 0.0000e+00 +285 5.6914e+00 0.0000e+00 0.0000e+00 +286 5.7114e+00 0.0000e+00 0.0000e+00 +287 5.7315e+00 0.0000e+00 0.0000e+00 +288 5.7515e+00 0.0000e+00 0.0000e+00 +289 5.7715e+00 0.0000e+00 0.0000e+00 +290 5.7916e+00 0.0000e+00 0.0000e+00 +291 5.8116e+00 0.0000e+00 0.0000e+00 +292 5.8317e+00 0.0000e+00 0.0000e+00 +293 5.8517e+00 0.0000e+00 0.0000e+00 +294 5.8717e+00 0.0000e+00 0.0000e+00 +295 5.8918e+00 0.0000e+00 0.0000e+00 +296 5.9118e+00 0.0000e+00 0.0000e+00 +297 5.9319e+00 0.0000e+00 0.0000e+00 +298 5.9519e+00 0.0000e+00 0.0000e+00 +299 5.9719e+00 0.0000e+00 0.0000e+00 +300 5.9920e+00 0.0000e+00 0.0000e+00 +301 6.0120e+00 0.0000e+00 0.0000e+00 +302 6.0321e+00 0.0000e+00 0.0000e+00 +303 6.0521e+00 0.0000e+00 0.0000e+00 +304 6.0721e+00 0.0000e+00 0.0000e+00 +305 6.0922e+00 0.0000e+00 0.0000e+00 +306 6.1122e+00 0.0000e+00 0.0000e+00 +307 6.1323e+00 0.0000e+00 0.0000e+00 +308 6.1523e+00 0.0000e+00 0.0000e+00 +309 6.1723e+00 0.0000e+00 0.0000e+00 +310 6.1924e+00 0.0000e+00 0.0000e+00 +311 6.2124e+00 0.0000e+00 0.0000e+00 +312 6.2325e+00 0.0000e+00 0.0000e+00 +313 6.2525e+00 0.0000e+00 0.0000e+00 +314 6.2725e+00 0.0000e+00 0.0000e+00 +315 6.2926e+00 0.0000e+00 0.0000e+00 +316 6.3126e+00 0.0000e+00 0.0000e+00 +317 6.3327e+00 0.0000e+00 0.0000e+00 +318 6.3527e+00 0.0000e+00 0.0000e+00 +319 6.3727e+00 0.0000e+00 0.0000e+00 +320 6.3928e+00 0.0000e+00 0.0000e+00 +321 6.4128e+00 0.0000e+00 0.0000e+00 +322 6.4329e+00 0.0000e+00 0.0000e+00 +323 6.4529e+00 0.0000e+00 0.0000e+00 +324 6.4729e+00 0.0000e+00 0.0000e+00 +325 6.4930e+00 0.0000e+00 0.0000e+00 +326 6.5130e+00 0.0000e+00 0.0000e+00 +327 6.5331e+00 0.0000e+00 0.0000e+00 +328 6.5531e+00 0.0000e+00 0.0000e+00 +329 6.5731e+00 0.0000e+00 0.0000e+00 +330 6.5932e+00 0.0000e+00 0.0000e+00 +331 6.6132e+00 0.0000e+00 0.0000e+00 +332 6.6333e+00 0.0000e+00 0.0000e+00 +333 6.6533e+00 0.0000e+00 0.0000e+00 +334 6.6733e+00 0.0000e+00 0.0000e+00 +335 6.6934e+00 0.0000e+00 0.0000e+00 +336 6.7134e+00 0.0000e+00 0.0000e+00 +337 6.7335e+00 0.0000e+00 0.0000e+00 +338 6.7535e+00 0.0000e+00 0.0000e+00 +339 6.7735e+00 0.0000e+00 0.0000e+00 +340 6.7936e+00 0.0000e+00 0.0000e+00 +341 6.8136e+00 0.0000e+00 0.0000e+00 +342 6.8337e+00 0.0000e+00 0.0000e+00 +343 6.8537e+00 0.0000e+00 0.0000e+00 +344 6.8737e+00 0.0000e+00 0.0000e+00 +345 6.8938e+00 0.0000e+00 0.0000e+00 +346 6.9138e+00 0.0000e+00 0.0000e+00 +347 6.9339e+00 0.0000e+00 0.0000e+00 +348 6.9539e+00 0.0000e+00 0.0000e+00 +349 6.9739e+00 0.0000e+00 0.0000e+00 +350 6.9940e+00 0.0000e+00 0.0000e+00 +351 7.0140e+00 0.0000e+00 0.0000e+00 +352 7.0341e+00 0.0000e+00 0.0000e+00 +353 7.0541e+00 0.0000e+00 0.0000e+00 +354 7.0741e+00 0.0000e+00 0.0000e+00 +355 7.0942e+00 0.0000e+00 0.0000e+00 +356 7.1142e+00 0.0000e+00 0.0000e+00 +357 7.1343e+00 0.0000e+00 0.0000e+00 +358 7.1543e+00 0.0000e+00 0.0000e+00 +359 7.1743e+00 0.0000e+00 0.0000e+00 +360 7.1944e+00 0.0000e+00 0.0000e+00 +361 7.2144e+00 0.0000e+00 0.0000e+00 +362 7.2345e+00 0.0000e+00 0.0000e+00 +363 7.2545e+00 0.0000e+00 0.0000e+00 +364 7.2745e+00 0.0000e+00 0.0000e+00 +365 7.2946e+00 0.0000e+00 0.0000e+00 +366 7.3146e+00 0.0000e+00 0.0000e+00 +367 7.3347e+00 0.0000e+00 0.0000e+00 +368 7.3547e+00 0.0000e+00 0.0000e+00 +369 7.3747e+00 0.0000e+00 0.0000e+00 +370 7.3948e+00 0.0000e+00 0.0000e+00 +371 7.4148e+00 0.0000e+00 0.0000e+00 +372 7.4349e+00 0.0000e+00 0.0000e+00 +373 7.4549e+00 0.0000e+00 0.0000e+00 +374 7.4749e+00 0.0000e+00 0.0000e+00 +375 7.4950e+00 0.0000e+00 0.0000e+00 +376 7.5150e+00 0.0000e+00 0.0000e+00 +377 7.5351e+00 0.0000e+00 0.0000e+00 +378 7.5551e+00 0.0000e+00 0.0000e+00 +379 7.5752e+00 0.0000e+00 0.0000e+00 +380 7.5952e+00 0.0000e+00 0.0000e+00 +381 7.6152e+00 0.0000e+00 0.0000e+00 +382 7.6353e+00 0.0000e+00 0.0000e+00 +383 7.6553e+00 0.0000e+00 0.0000e+00 +384 7.6754e+00 0.0000e+00 0.0000e+00 +385 7.6954e+00 0.0000e+00 0.0000e+00 +386 7.7154e+00 0.0000e+00 0.0000e+00 +387 7.7355e+00 0.0000e+00 0.0000e+00 +388 7.7555e+00 0.0000e+00 0.0000e+00 +389 7.7756e+00 0.0000e+00 0.0000e+00 +390 7.7956e+00 0.0000e+00 0.0000e+00 +391 7.8156e+00 0.0000e+00 0.0000e+00 +392 7.8357e+00 0.0000e+00 0.0000e+00 +393 7.8557e+00 0.0000e+00 0.0000e+00 +394 7.8758e+00 0.0000e+00 0.0000e+00 +395 7.8958e+00 0.0000e+00 0.0000e+00 +396 7.9158e+00 0.0000e+00 0.0000e+00 +397 7.9359e+00 0.0000e+00 0.0000e+00 +398 7.9559e+00 0.0000e+00 0.0000e+00 +399 7.9760e+00 0.0000e+00 0.0000e+00 +400 7.9960e+00 0.0000e+00 0.0000e+00 +401 8.0160e+00 0.0000e+00 0.0000e+00 +402 8.0361e+00 0.0000e+00 0.0000e+00 +403 8.0561e+00 0.0000e+00 0.0000e+00 +404 8.0762e+00 0.0000e+00 0.0000e+00 +405 8.0962e+00 0.0000e+00 0.0000e+00 +406 8.1162e+00 0.0000e+00 0.0000e+00 +407 8.1363e+00 0.0000e+00 0.0000e+00 +408 8.1563e+00 0.0000e+00 0.0000e+00 +409 8.1764e+00 0.0000e+00 0.0000e+00 +410 8.1964e+00 0.0000e+00 0.0000e+00 +411 8.2164e+00 0.0000e+00 0.0000e+00 +412 8.2365e+00 0.0000e+00 0.0000e+00 +413 8.2565e+00 0.0000e+00 0.0000e+00 +414 8.2766e+00 0.0000e+00 0.0000e+00 +415 8.2966e+00 0.0000e+00 0.0000e+00 +416 8.3166e+00 0.0000e+00 0.0000e+00 +417 8.3367e+00 0.0000e+00 0.0000e+00 +418 8.3567e+00 0.0000e+00 0.0000e+00 +419 8.3768e+00 0.0000e+00 0.0000e+00 +420 8.3968e+00 0.0000e+00 0.0000e+00 +421 8.4168e+00 0.0000e+00 0.0000e+00 +422 8.4369e+00 0.0000e+00 0.0000e+00 +423 8.4569e+00 0.0000e+00 0.0000e+00 +424 8.4770e+00 0.0000e+00 0.0000e+00 +425 8.4970e+00 0.0000e+00 0.0000e+00 +426 8.5170e+00 0.0000e+00 0.0000e+00 +427 8.5371e+00 0.0000e+00 0.0000e+00 +428 8.5571e+00 0.0000e+00 0.0000e+00 +429 8.5772e+00 0.0000e+00 0.0000e+00 +430 8.5972e+00 0.0000e+00 0.0000e+00 +431 8.6172e+00 0.0000e+00 0.0000e+00 +432 8.6373e+00 0.0000e+00 0.0000e+00 +433 8.6573e+00 0.0000e+00 0.0000e+00 +434 8.6774e+00 0.0000e+00 0.0000e+00 +435 8.6974e+00 0.0000e+00 0.0000e+00 +436 8.7174e+00 0.0000e+00 0.0000e+00 +437 8.7375e+00 0.0000e+00 0.0000e+00 +438 8.7575e+00 0.0000e+00 0.0000e+00 +439 8.7776e+00 0.0000e+00 0.0000e+00 +440 8.7976e+00 0.0000e+00 0.0000e+00 +441 8.8176e+00 0.0000e+00 0.0000e+00 +442 8.8377e+00 0.0000e+00 0.0000e+00 +443 8.8577e+00 0.0000e+00 0.0000e+00 +444 8.8778e+00 0.0000e+00 0.0000e+00 +445 8.8978e+00 0.0000e+00 0.0000e+00 +446 8.9178e+00 0.0000e+00 0.0000e+00 +447 8.9379e+00 0.0000e+00 0.0000e+00 +448 8.9579e+00 0.0000e+00 0.0000e+00 +449 8.9780e+00 0.0000e+00 0.0000e+00 +450 8.9980e+00 0.0000e+00 0.0000e+00 +451 9.0180e+00 0.0000e+00 0.0000e+00 +452 9.0381e+00 0.0000e+00 0.0000e+00 +453 9.0581e+00 0.0000e+00 0.0000e+00 +454 9.0782e+00 0.0000e+00 0.0000e+00 +455 9.0982e+00 0.0000e+00 0.0000e+00 +456 9.1182e+00 0.0000e+00 0.0000e+00 +457 9.1383e+00 0.0000e+00 0.0000e+00 +458 9.1583e+00 0.0000e+00 0.0000e+00 +459 9.1784e+00 0.0000e+00 0.0000e+00 +460 9.1984e+00 0.0000e+00 0.0000e+00 +461 9.2184e+00 0.0000e+00 0.0000e+00 +462 9.2385e+00 0.0000e+00 0.0000e+00 +463 9.2585e+00 0.0000e+00 0.0000e+00 +464 9.2786e+00 0.0000e+00 0.0000e+00 +465 9.2986e+00 0.0000e+00 0.0000e+00 +466 9.3186e+00 0.0000e+00 0.0000e+00 +467 9.3387e+00 0.0000e+00 0.0000e+00 +468 9.3587e+00 0.0000e+00 0.0000e+00 +469 9.3788e+00 0.0000e+00 0.0000e+00 +470 9.3988e+00 0.0000e+00 0.0000e+00 +471 9.4188e+00 0.0000e+00 0.0000e+00 +472 9.4389e+00 0.0000e+00 0.0000e+00 +473 9.4589e+00 0.0000e+00 0.0000e+00 +474 9.4790e+00 0.0000e+00 0.0000e+00 +475 9.4990e+00 0.0000e+00 0.0000e+00 +476 9.5190e+00 0.0000e+00 0.0000e+00 +477 9.5391e+00 0.0000e+00 0.0000e+00 +478 9.5591e+00 0.0000e+00 0.0000e+00 +479 9.5792e+00 0.0000e+00 0.0000e+00 +480 9.5992e+00 0.0000e+00 0.0000e+00 +481 9.6192e+00 0.0000e+00 0.0000e+00 +482 9.6393e+00 0.0000e+00 0.0000e+00 +483 9.6593e+00 0.0000e+00 0.0000e+00 +484 9.6794e+00 0.0000e+00 0.0000e+00 +485 9.6994e+00 0.0000e+00 0.0000e+00 +486 9.7194e+00 0.0000e+00 0.0000e+00 +487 9.7395e+00 0.0000e+00 0.0000e+00 +488 9.7595e+00 0.0000e+00 0.0000e+00 +489 9.7796e+00 0.0000e+00 0.0000e+00 +490 9.7996e+00 0.0000e+00 0.0000e+00 +491 9.8196e+00 0.0000e+00 0.0000e+00 +492 9.8397e+00 0.0000e+00 0.0000e+00 +493 9.8597e+00 0.0000e+00 0.0000e+00 +494 9.8798e+00 0.0000e+00 0.0000e+00 +495 9.8998e+00 0.0000e+00 0.0000e+00 +496 9.9198e+00 0.0000e+00 0.0000e+00 +497 9.9399e+00 0.0000e+00 0.0000e+00 +498 9.9599e+00 0.0000e+00 0.0000e+00 +499 9.9800e+00 0.0000e+00 0.0000e+00 +500 1.0000e+01 0.0000e+00 0.0000e+00 + + diff --git a/examples/USER/misc/local_density/benzene_water/log.04Sep19.g++.1 b/examples/USER/misc/local_density/benzene_water/log.04Sep19.g++.1 new file mode 100644 index 0000000000..928906edbd --- /dev/null +++ b/examples/USER/misc/local_density/benzene_water/log.04Sep19.g++.1 @@ -0,0 +1,267 @@ +LAMMPS (7 Aug 2019) +# LAMMPS input file for 26.5% benzene mole fraction solution +# with 380 benzene and 1000 water molecules, +# using all possible local density potentials +# between benzene and water +# +# Author: Tanmoy Sanyal, Shell Group, UC Santa Barbara +# +# Refer: Sanyal and Shell, JPC-B, 2018, 122 (21), 5678-5693 + + + +# Initialize simulation box +dimension 3 +boundary p p p +units real +atom_style molecular + +# Set potential styles +pair_style hybrid/overlay table spline 500 local/density + +# Read molecule data and set initial velocities +read_data benzene_water.data + orthogonal box = (-12.865 -12.865 -64.829) to (12.865 12.865 64.829) + 1 by 1 by 8 MPI processor grid + reading atoms ... + 1380 atoms + 0 = max # of 1-2 neighbors + 0 = max # of 1-3 neighbors + 0 = max # of 1-4 neighbors + 1 = max # of special neighbors + special bonds CPU = 0.000566959 secs + read_data CPU = 0.00661397 secs +velocity all create 3.0000e+02 16611 rot yes dist gaussian + +# Assign potentials +pair_coeff 1 1 table benzene_water.pair.table PairBB +WARNING: 33 of 500 force values in table are inconsistent with -dE/dr. + Should only be flagged at inflection points (../pair_table.cpp:483) +WARNING: 150 of 500 distance values in table with relative error + over 1e-06 to re-computed values (../pair_table.cpp:492) +pair_coeff 1 2 table benzene_water.pair.table PairWW +WARNING: 61 of 500 force values in table are inconsistent with -dE/dr. + Should only be flagged at inflection points (../pair_table.cpp:483) +WARNING: 90 of 500 distance values in table with relative error + over 1e-06 to re-computed values (../pair_table.cpp:492) +pair_coeff 2 2 table benzene_water.pair.table PairBW +WARNING: 108 of 500 force values in table are inconsistent with -dE/dr. + Should only be flagged at inflection points (../pair_table.cpp:483) +WARNING: 135 of 500 distance values in table with relative error + over 1e-06 to re-computed values (../pair_table.cpp:492) +pair_coeff * * local/density benzene_water.localdensity.table + +# Recentering during minimization and equilibration +fix recentering all recenter 0.0 0.0 0.0 units box + +# Thermostat & time integration +timestep 2.0 +thermo 100 +thermo_style custom temp ke pe etotal ebond eangle edihed evdwl + +# Minimization +minimize 1.e-4 0.0 10000 10000 +WARNING: Using 'neigh_modify every 1 delay 0 check yes' setting during minimization (../min.cpp:168) +Neighbor list info ... + update every 1 steps, delay 0 steps, check yes + max neighbors/atom: 2000, page size: 100000 + master list distance cutoff = 15.25 + ghost atom cutoff = 15.25 + binsize = 7.625, bins = 4 4 18 + 2 neighbor lists, perpetual/occasional/extra = 2 0 0 + (1) pair table, perpetual + attributes: half, newton on + pair build: half/bin/newton + stencil: half/bin/3d/newton + bin: standard + (2) pair local/density, perpetual, copy from (1) + attributes: half, newton on + pair build: copy + stencil: none + bin: none +Per MPI rank memory allocation (min/avg/max) = 8.061 | 8.32 | 8.674 Mbytes +Temp KinEng PotEng TotEng E_bond E_angle E_dihed E_vdwl + 300 1233.1611 4162.3053 5395.4665 0 0 0 4162.3053 + 300 1233.1611 2275.526 3508.6871 0 0 0 2275.526 +Loop time of 0.352822 on 8 procs for 40 steps with 1380 atoms + +71.3% CPU use with 8 MPI tasks x no OpenMP threads + +Minimization stats: + Stopping criterion = linesearch alpha is zero + Energy initial, next-to-last, final = + 4162.30533361 2208.86525108 2275.52597861 + Force two-norm initial, final = 259.364 69.3915 + Force max component initial, final = 22.2077 8.31436 + Final line search alpha, max atom move = 2.90022e-12 2.41135e-11 + Iterations, force evaluations = 40 110 + +MPI task timing breakdown: +Section | min time | avg time | max time |%varavg| %total +--------------------------------------------------------------- +Pair | 0.053192 | 0.23903 | 0.32779 | 17.2 | 67.75 +Bond | 9.0599e-06 | 1.6302e-05 | 2.5272e-05 | 0.0 | 0.00 +Neigh | 0.00044513 | 0.0023614 | 0.0063851 | 5.1 | 0.67 +Comm | 0.015469 | 0.090432 | 0.20295 | 20.0 | 25.63 +Output | 0 | 0 | 0 | 0.0 | 0.00 +Modify | 0 | 0 | 0 | 0.0 | 0.00 +Other | | 0.02098 | | | 5.95 + +Nlocal: 172.5 ave 348 max 72 min +Histogram: 5 0 0 0 0 0 0 0 1 2 +Nghost: 2193.62 ave 4352 max 932 min +Histogram: 3 0 0 2 0 0 2 0 0 1 +Neighs: 9700.5 ave 20535 max 3685 min +Histogram: 5 0 0 0 0 0 0 1 0 2 + +Total # of neighbors = 77604 +Ave neighs/atom = 56.2348 +Ave special neighs/atom = 0 +Neighbor list builds = 2 +Dangerous builds = 0 + +# Set up integration parameters +fix timeintegration all nve +fix thermostat all langevin 3.0000e+02 3.0000e+02 1.0000e+02 81890 + +# Equilibration (for realistic results, run for 5000000 steps) +reset_timestep 0 +run 5000 +WARNING: Fix recenter should come after all other integration fixes (../fix_recenter.cpp:131) +Per MPI rank memory allocation (min/avg/max) = 6.936 | 7.195 | 7.552 Mbytes +Temp KinEng PotEng TotEng E_bond E_angle E_dihed E_vdwl + 300 1233.1611 2866.9109 4100.0721 0 0 0 2866.9109 + 273.33541 1123.5553 3983.2007 5106.756 0 0 0 3983.2007 + 293.68078 1207.1857 3319.6601 4526.8458 0 0 0 3319.6601 + 314.21462 1291.5908 3389.2178 4680.8086 0 0 0 3389.2178 + 323.77563 1330.8917 3332.9828 4663.8745 0 0 0 3332.9828 + 302.5902 1243.8082 3461.7692 4705.5774 0 0 0 3461.7692 + 295.39324 1214.2249 3411.5727 4625.7976 0 0 0 3411.5727 + 320.52341 1317.5234 3453.1931 4770.7164 0 0 0 3453.1931 + 312.00777 1282.5195 3403.3443 4685.8638 0 0 0 3403.3443 + 307.96774 1265.9128 3429.7809 4695.6937 0 0 0 3429.7809 + 294.75922 1211.6187 3388.8404 4600.4591 0 0 0 3388.8404 + 311.24567 1279.3869 3514.9603 4794.3472 0 0 0 3514.9603 + 306.6152 1260.3531 3447.2011 4707.5542 0 0 0 3447.2011 + 305.23306 1254.6718 3375.5092 4630.181 0 0 0 3375.5092 + 321.62889 1322.0675 3460.2581 4782.3256 0 0 0 3460.2581 + 316.37725 1300.4804 3437.0312 4737.5116 0 0 0 3437.0312 + 322.90522 1327.3139 3389.1262 4716.44 0 0 0 3389.1262 + 307.57893 1264.3146 3359.8491 4624.1637 0 0 0 3359.8491 + 302.22607 1242.3115 3406.1711 4648.4826 0 0 0 3406.1711 + 302.73997 1244.4239 3220.2582 4464.6821 0 0 0 3220.2582 + 303.66194 1248.2137 3318.4629 4566.6765 0 0 0 3318.4629 + 308.73862 1269.0815 3369.5894 4638.671 0 0 0 3369.5894 + 315.60294 1297.2976 3411.2405 4708.5381 0 0 0 3411.2405 + 310.0113 1274.3129 3360.1054 4634.4183 0 0 0 3360.1054 + 302.36229 1242.8714 3326.9845 4569.8559 0 0 0 3326.9845 + 317.78659 1306.2735 3355.4976 4661.7711 0 0 0 3355.4976 + 302.50479 1243.4571 3317.6846 4561.1417 0 0 0 3317.6846 + 304.29249 1250.8056 3423.5068 4674.3124 0 0 0 3423.5068 + 305.99948 1257.8222 3432.9395 4690.7617 0 0 0 3432.9395 + 309.93363 1273.9937 3393.657 4667.6506 0 0 0 3393.657 + 316.14884 1299.5415 3463.0636 4762.6051 0 0 0 3463.0636 + 300.38817 1234.7567 3309.2495 4544.0062 0 0 0 3309.2495 + 311.05735 1278.6128 3304.4418 4583.0546 0 0 0 3304.4418 + 311.11872 1278.865 3291.1891 4570.0542 0 0 0 3291.1891 + 315.74338 1297.8749 3341.3063 4639.1812 0 0 0 3341.3063 + 297.5658 1223.1552 3316.3862 4539.5414 0 0 0 3316.3862 + 311.79033 1281.6257 3357.4556 4639.0813 0 0 0 3357.4556 + 310.93666 1278.1167 3414.7694 4692.8861 0 0 0 3414.7694 + 307.37298 1263.468 3337.3889 4600.8569 0 0 0 3337.3889 + 298.84185 1228.4005 3329.6173 4558.0178 0 0 0 3329.6173 + 310.54684 1276.5143 3351.0852 4627.5995 0 0 0 3351.0852 + 300.0871 1233.5191 3302.2315 4535.7506 0 0 0 3302.2315 + 304.69078 1252.4427 3324.2508 4576.6935 0 0 0 3324.2508 + 313.50714 1288.6827 3330.4088 4619.0915 0 0 0 3330.4088 + 329.80018 1355.6559 3301.86 4657.5159 0 0 0 3301.86 + 304.57609 1251.9713 3365.2938 4617.2652 0 0 0 3365.2938 + 308.73584 1269.0701 3344.4155 4613.4856 0 0 0 3344.4155 + 306.90951 1261.5629 3304.4698 4566.0327 0 0 0 3304.4698 + 308.85761 1269.5707 3392.1511 4661.7218 0 0 0 3392.1511 + 302.78788 1244.6208 3317.0849 4561.7057 0 0 0 3317.0849 + 321.68092 1322.2813 3321.5755 4643.8568 0 0 0 3321.5755 +Loop time of 16.3061 on 8 procs for 5000 steps with 1380 atoms + +Performance: 52.986 ns/day, 0.453 hours/ns, 306.634 timesteps/s +69.6% CPU use with 8 MPI tasks x no OpenMP threads + +MPI task timing breakdown: +Section | min time | avg time | max time |%varavg| %total +--------------------------------------------------------------- +Pair | 2.1872 | 10.542 | 14.607 | 116.7 | 64.65 +Bond | 0.00044084 | 0.00069669 | 0.00095081 | 0.0 | 0.00 +Neigh | 0.026948 | 0.15225 | 0.44344 | 42.0 | 0.93 +Comm | 0.63452 | 4.2953 | 9.49 | 133.9 | 26.34 +Output | 0.0016391 | 0.012378 | 0.050919 | 13.9 | 0.08 +Modify | 0.45894 | 1.2107 | 4.4629 | 116.4 | 7.42 +Other | | 0.09292 | | | 0.57 + +Nlocal: 172.5 ave 380 max 70 min +Histogram: 5 0 0 0 0 0 0 1 1 1 +Nghost: 2213 ave 4440 max 903 min +Histogram: 3 0 0 2 0 0 2 0 0 1 +Neighs: 10042.5 ave 24051 max 3500 min +Histogram: 5 0 0 0 0 0 0 1 1 1 + +Total # of neighbors = 80340 +Ave neighs/atom = 58.2174 +Ave special neighs/atom = 0 +Neighbor list builds = 123 +Dangerous builds = 1 + +# Turn off recentering during production phase +unfix recentering + +# Setup trajectory output +dump myDump all custom 100 benzene_water.lammpstrj.gz id type x y z element +dump_modify myDump element B W +dump_modify myDump sort id + +# Production (for realistic results, run for 10000000 steps) +reset_timestep 0 +run 1000 +Per MPI rank memory allocation (min/avg/max) = 8.232 | 8.492 | 8.851 Mbytes +Temp KinEng PotEng TotEng E_bond E_angle E_dihed E_vdwl + 321.68092 1322.2813 3784.0834 5106.3647 0 0 0 3784.0834 + 310.59763 1276.7231 3318.3283 4595.0513 0 0 0 3318.3283 + 303.39445 1247.1141 3324.1191 4571.2332 0 0 0 3324.1191 + 311.37275 1279.9092 3305.0901 4584.9993 0 0 0 3305.0901 + 311.29071 1279.572 3248.216 4527.788 0 0 0 3248.216 + 314.53456 1292.906 3283.4563 4576.3623 0 0 0 3283.4563 + 316.52595 1301.0916 3258.9171 4560.0087 0 0 0 3258.9171 + 318.92447 1310.9509 3235.6256 4546.5765 0 0 0 3235.6256 + 311.79212 1281.6331 3308.099 4589.7321 0 0 0 3308.099 + 305.52477 1255.8709 3267.6907 4523.5616 0 0 0 3267.6907 + 301.07457 1237.5782 3206.3997 4443.9779 0 0 0 3206.3997 +Loop time of 4.44139 on 8 procs for 1000 steps with 1380 atoms + +Performance: 38.907 ns/day, 0.617 hours/ns, 225.155 timesteps/s +60.8% CPU use with 8 MPI tasks x no OpenMP threads + +MPI task timing breakdown: +Section | min time | avg time | max time |%varavg| %total +--------------------------------------------------------------- +Pair | 0.656 | 2.5078 | 3.5775 | 57.7 | 56.46 +Bond | 0.00013375 | 0.0001854 | 0.0002377 | 0.0 | 0.00 +Neigh | 0.0048757 | 0.029188 | 0.090432 | 18.9 | 0.66 +Comm | 0.51836 | 1.4427 | 2.6285 | 56.9 | 32.48 +Output | 0.083084 | 0.089199 | 0.10333 | 2.3 | 2.01 +Modify | 0.0087376 | 0.019705 | 0.038437 | 8.4 | 0.44 +Other | | 0.3526 | | | 7.94 + +Nlocal: 172.5 ave 388 max 69 min +Histogram: 5 0 0 0 0 0 0 2 0 1 +Nghost: 2207.88 ave 4429 max 896 min +Histogram: 3 0 0 2 0 0 2 0 0 1 +Neighs: 10094.1 ave 24847 max 3403 min +Histogram: 5 0 0 0 0 0 1 1 0 1 + +Total # of neighbors = 80753 +Ave neighs/atom = 58.5167 +Ave special neighs/atom = 0 +Neighbor list builds = 23 +Dangerous builds = 0 + + +Total wall time: 0:00:21 diff --git a/examples/USER/misc/local_density/methanol_implicit_water/log.04Sep19.g++.1 b/examples/USER/misc/local_density/methanol_implicit_water/log.04Sep19.g++.1 new file mode 100644 index 0000000000..618e994946 --- /dev/null +++ b/examples/USER/misc/local_density/methanol_implicit_water/log.04Sep19.g++.1 @@ -0,0 +1,226 @@ +LAMMPS (7 Aug 2019) +# LAMMPS input file for 50.0% methanol mole fraction solution +# with 2500 methanol molecules in implicit water. +# +# +# Author: David Rosenberger, van der Vegt Group, TU Darmstadt +# +# Refer: Rosenberger, Sanyal, Shell, van der Vegt, J. Chem. Theory Comput. 15, 2881-2895 (2019) + + +# Initialize simulation box +dimension 3 +boundary p p p +units real +atom_style molecular + +# Set potential styles +pair_style hybrid/overlay table spline 500 local/density + +# Read molecule data and set initial velocities +read_data methanol_implicit_water.data + orthogonal box = (-31.123 -31.123 -31.123) to (31.123 31.123 31.123) + 2 by 2 by 2 MPI processor grid + reading atoms ... + 2500 atoms + 0 = max # of 1-2 neighbors + 0 = max # of 1-3 neighbors + 0 = max # of 1-4 neighbors + 1 = max # of special neighbors + special bonds CPU = 0.00063014 secs + read_data CPU = 0.00599909 secs +velocity all create 3.0000e+02 12142 rot yes dist gaussian + +# Assign potentials +pair_coeff 1 1 table methanol_implicit_water.pair.table PairMM +WARNING: 93 of 500 force values in table are inconsistent with -dE/dr. + Should only be flagged at inflection points (../pair_table.cpp:483) +WARNING: 254 of 500 distance values in table with relative error + over 1e-06 to re-computed values (../pair_table.cpp:492) +pair_coeff * * local/density methanol_implicit_water.localdensity.table + + + + +#Recentering during minimization and equilibration +fix recentering all recenter 0.0 0.0 0.0 units box + +#Thermostat & time integration +timestep 1.0 +thermo 100 +thermo_style custom etotal ke pe temp evdwl + +#minimization +minimize 1.e-4 0.0 1000 1000 +WARNING: Using 'neigh_modify every 1 delay 0 check yes' setting during minimization (../min.cpp:168) +Neighbor list info ... + update every 1 steps, delay 0 steps, check yes + max neighbors/atom: 2000, page size: 100000 + master list distance cutoff = 17 + ghost atom cutoff = 17 + binsize = 8.5, bins = 8 8 8 + 2 neighbor lists, perpetual/occasional/extra = 2 0 0 + (1) pair table, perpetual + attributes: half, newton on + pair build: half/bin/newton + stencil: half/bin/3d/newton + bin: standard + (2) pair local/density, perpetual, copy from (1) + attributes: half, newton on + pair build: copy + stencil: none + bin: none +Per MPI rank memory allocation (min/avg/max) = 7.411 | 7.411 | 7.412 Mbytes +TotEng KinEng PotEng Temp E_vdwl + 1470.3564 2234.7133 -764.35689 300 -764.35689 + 46.496766 2234.7133 -2188.2165 300 -2188.2165 + 7.9030246 2234.7133 -2226.8103 300 -2226.8103 +Loop time of 0.463996 on 8 procs for 121 steps with 2500 atoms + +91.4% CPU use with 8 MPI tasks x no OpenMP threads + +Minimization stats: + Stopping criterion = linesearch alpha is zero + Energy initial, next-to-last, final = + -764.356892369 -2227.85589084 -2226.81026984 + Force two-norm initial, final = 134.911 3.83896 + Force max component initial, final = 14.1117 1.07422 + Final line search alpha, max atom move = 5.06747e-10 5.44356e-10 + Iterations, force evaluations = 121 154 + +MPI task timing breakdown: +Section | min time | avg time | max time |%varavg| %total +--------------------------------------------------------------- +Pair | 0.41442 | 0.41976 | 0.42434 | 0.5 | 90.47 +Bond | 1.1683e-05 | 2.0713e-05 | 3.5048e-05 | 0.0 | 0.00 +Neigh | 0.0084722 | 0.0090862 | 0.010038 | 0.5 | 1.96 +Comm | 0.022712 | 0.028157 | 0.034072 | 1.9 | 6.07 +Output | 3.1948e-05 | 3.6925e-05 | 6.6996e-05 | 0.0 | 0.01 +Modify | 0 | 0 | 0 | 0.0 | 0.00 +Other | | 0.006937 | | | 1.50 + +Nlocal: 312.5 ave 333 max 299 min +Histogram: 2 2 0 0 1 0 2 0 0 1 +Nghost: 2546 ave 2580 max 2517 min +Histogram: 1 1 0 3 0 1 0 0 0 2 +Neighs: 33215.4 ave 37251 max 29183 min +Histogram: 1 0 0 1 2 2 0 1 0 1 + +Total # of neighbors = 265723 +Ave neighs/atom = 106.289 +Ave special neighs/atom = 0 +Neighbor list builds = 6 +Dangerous builds = 0 + +#set up integration parameters +fix timeintegration all nve +fix thermostat all langevin 3.0000e+02 3.0000e+02 1.0000e+02 59915 + +#Equilibration (for realistic results, run for 2000000 steps) +reset_timestep 0 +thermo 200 +thermo_style custom etotal ke pe temp evdwl + +#run equilibration +run 2000 +WARNING: Fix recenter should come after all other integration fixes (../fix_recenter.cpp:131) +Per MPI rank memory allocation (min/avg/max) = 6.286 | 6.286 | 6.287 Mbytes +TotEng KinEng PotEng Temp E_vdwl + 177.26822 2234.7133 -2057.4451 300 -2057.4451 + 736.24287 2151.2608 -1415.0179 288.79688 -1415.0179 + 963.07617 2090.6433 -1127.5671 280.65926 -1127.5671 + 1148.9049 2173.1327 -1024.2279 291.73309 -1024.2279 + 1303.6409 2279.8586 -976.21767 306.06055 -976.21767 + 1355.42 2281.0383 -925.61826 306.21892 -925.61826 + 1394.5206 2276.2093 -881.68863 305.57064 -881.68863 + 1346.9764 2215.2973 -868.32091 297.3935 -868.32091 + 1381.3654 2248.8061 -867.44063 301.89189 -867.44063 + 1315.8059 2189.3193 -873.51332 293.90606 -873.51332 + 1314.4456 2209.7431 -895.29752 296.64787 -895.29752 +Loop time of 6.38989 on 8 procs for 2000 steps with 2500 atoms + +Performance: 27.043 ns/day, 0.887 hours/ns, 312.994 timesteps/s +80.5% CPU use with 8 MPI tasks x no OpenMP threads + +MPI task timing breakdown: +Section | min time | avg time | max time |%varavg| %total +--------------------------------------------------------------- +Pair | 5.2693 | 5.3572 | 5.457 | 2.1 | 83.84 +Bond | 0.00028825 | 0.00033835 | 0.00039148 | 0.0 | 0.01 +Neigh | 0.0296 | 0.032337 | 0.035071 | 0.9 | 0.51 +Comm | 0.64679 | 0.73397 | 0.80847 | 5.2 | 11.49 +Output | 0.00033498 | 0.00051582 | 0.0015228 | 0.0 | 0.01 +Modify | 0.16395 | 0.18919 | 0.21056 | 3.9 | 2.96 +Other | | 0.07636 | | | 1.19 + +Nlocal: 312.5 ave 337 max 295 min +Histogram: 2 2 0 1 0 0 0 1 1 1 +Nghost: 2551.62 ave 2582 max 2525 min +Histogram: 2 1 0 0 1 1 1 0 1 1 +Neighs: 33241.8 ave 37659 max 29705 min +Histogram: 2 0 0 2 2 0 0 0 1 1 + +Total # of neighbors = 265934 +Ave neighs/atom = 106.374 +Ave special neighs/atom = 0 +Neighbor list builds = 21 +Dangerous builds = 0 + +#turn off recentering during production run +unfix recentering + + +#setup trajectory output +dump myDump all custom 100 methanol_implicit_water.lammpstrj.gz id type x y z element +dump_modify myDump element M +dump_modify myDump sort id + +#run production (for realistic results, run for 10000000 steps) +reset_timestep 0 +thermo 1000 +thermo_style custom etotal ke pe temp evdwl +run 10000 +Per MPI rank memory allocation (min/avg/max) = 7.588 | 7.589 | 7.589 Mbytes +TotEng KinEng PotEng Temp E_vdwl + 1442.5428 2209.7431 -767.20027 296.64787 -767.20027 + 1391.8624 2262.6889 -870.82656 303.7556 -870.82656 + 1375.914 2244.6176 -868.7036 301.3296 -868.7036 + 1345.9064 2227.2324 -881.32599 298.99573 -881.32599 + 1379.2334 2278.1156 -898.88222 305.82657 -898.88222 + 1389.7928 2255.8062 -866.01341 302.83163 -866.01341 + 1380.4549 2258.2108 -877.75582 303.15443 -877.75582 + 1380.8489 2256.9432 -876.09428 302.98426 -876.09428 + 1326.5151 2225.7408 -899.22577 298.79549 -899.22577 + 1376.6025 2253.0128 -876.41028 302.45662 -876.41028 + 1331.0008 2218.1033 -887.10258 297.77019 -887.10258 +Loop time of 25.4591 on 8 procs for 10000 steps with 2500 atoms + +Performance: 33.937 ns/day, 0.707 hours/ns, 392.787 timesteps/s +89.3% CPU use with 8 MPI tasks x no OpenMP threads + +MPI task timing breakdown: +Section | min time | avg time | max time |%varavg| %total +--------------------------------------------------------------- +Pair | 21.635 | 21.916 | 22.237 | 3.9 | 86.08 +Bond | 0.0011308 | 0.0013149 | 0.0016932 | 0.5 | 0.01 +Neigh | 0.14593 | 0.15675 | 0.16667 | 1.9 | 0.62 +Comm | 1.3789 | 1.7502 | 1.9558 | 13.7 | 6.87 +Output | 0.34664 | 0.82927 | 1.2013 | 32.8 | 3.26 +Modify | 0.24904 | 0.25842 | 0.26907 | 1.2 | 1.02 +Other | | 0.5475 | | | 2.15 + +Nlocal: 312.5 ave 327 max 298 min +Histogram: 2 0 0 1 1 0 1 1 1 1 +Nghost: 2575 ave 2601 max 2559 min +Histogram: 2 0 3 1 0 0 0 0 1 1 +Neighs: 33223.2 ave 35920 max 30303 min +Histogram: 1 1 1 1 0 1 0 0 0 3 + +Total # of neighbors = 265786 +Ave neighs/atom = 106.314 +Ave special neighs/atom = 0 +Neighbor list builds = 103 +Dangerous builds = 0 + + +Total wall time: 0:00:32 diff --git a/examples/USER/misc/local_density/methanol_implicit_water/methanol_implicit_water.data b/examples/USER/misc/local_density/methanol_implicit_water/methanol_implicit_water.data new file mode 100644 index 0000000000..1dd9eccc7c --- /dev/null +++ b/examples/USER/misc/local_density/methanol_implicit_water/methanol_implicit_water.data @@ -0,0 +1,2525 @@ +LAMMPS Description + + 2500 atoms + 0 bonds + 0 angles + 0 dihedrals + 0 impropers + + 1 atom types + 0 bond types + 0 angle types + 0 dihedral types + 0 improper types + +-3.1123e+01 3.1123e+01 xlo xhi +-3.1123e+01 3.1123e+01 ylo yhi +-3.1123e+01 3.1123e+01 zlo zhi + +Masses + + 1 32.0000 + +Atoms + + 1 1 1 -1.20055e+01 1.00800e+01 5.26000e+00 + 2 2 1 -5.60545e+00 2.34700e+01 3.10400e+01 + 3 3 1 1.33900e+01 1.50700e+01 -1.56654e+01 + 4 4 1 -3.57545e+00 -1.71754e+01 -7.17545e+00 + 5 5 1 1.09000e+01 1.67100e+01 -2.57554e+01 + 6 6 1 1.96400e+01 -6.07545e+00 -2.72454e+01 + 7 7 1 -7.56545e+00 -1.92354e+01 -2.37154e+01 + 8 8 1 -5.72545e+00 -2.45654e+01 -2.34154e+01 + 9 9 1 -1.71655e+01 2.46700e+01 1.76300e+01 + 10 10 1 8.06000e+00 4.73000e+00 -7.34545e+00 + 11 11 1 2.32300e+01 -2.01054e+01 1.78600e+01 + 12 12 1 -2.05955e+01 1.44500e+01 -6.35545e+00 + 13 13 1 1.80700e+01 2.19800e+01 -4.22545e+00 + 14 14 1 -1.26355e+01 -2.92545e+00 -2.09154e+01 + 15 15 1 -2.05255e+01 -2.12254e+01 -2.21454e+01 + 16 16 1 6.69000e+00 2.60700e+01 1.22700e+01 + 17 17 1 1.08600e+01 -2.00054e+01 -2.82854e+01 + 18 18 1 -1.89255e+01 3.30000e-01 1.15200e+01 + 19 19 1 1.85400e+01 1.31900e+01 -7.98545e+00 + 20 20 1 -1.49055e+01 1.45900e+01 -2.19354e+01 + 21 21 1 1.91400e+01 -2.43054e+01 -2.54454e+01 + 22 22 1 1.04200e+01 -2.94954e+01 -2.95654e+01 + 23 23 1 -7.37545e+00 2.08500e+01 2.58700e+01 + 24 24 1 1.25600e+01 2.80000e-01 -1.38054e+01 + 25 25 1 -2.11055e+01 1.01500e+01 3.10000e+01 + 26 26 1 2.78800e+01 -1.10254e+01 1.86300e+01 + 27 27 1 2.17000e+00 -3.01454e+01 1.67700e+01 + 28 28 1 2.76700e+01 1.44600e+01 -1.37954e+01 + 29 29 1 2.15200e+01 -3.45545e+00 4.45000e+00 + 30 30 1 -8.15545e+00 1.89500e+01 -2.73954e+01 + 31 31 1 -5.89545e+00 -1.45954e+01 2.62100e+01 + 32 32 1 2.29600e+01 -1.23154e+01 2.91800e+01 + 33 33 1 4.87000e+00 -2.65754e+01 8.54000e+00 + 34 34 1 1.93000e+00 -1.43554e+01 1.85200e+01 + 35 35 1 -2.78355e+01 -2.84754e+01 -2.38454e+01 + 36 36 1 3.08000e+00 -2.54354e+01 1.99500e+01 + 37 37 1 2.12700e+01 -6.71545e+00 1.28000e+00 + 38 38 1 -3.45545e+00 -2.41754e+01 1.49600e+01 + 39 39 1 2.54700e+01 1.63000e+01 6.99000e+00 + 40 40 1 -1.80855e+01 2.44800e+01 4.97000e+00 + 41 41 1 1.28400e+01 -1.15446e-01 -2.87954e+01 + 42 42 1 -7.86545e+00 2.17000e+00 1.67100e+01 + 43 43 1 2.42300e+01 -8.29545e+00 2.04200e+01 + 44 44 1 -4.35545e+00 4.68000e+00 2.66200e+01 + 45 45 1 -1.53655e+01 -1.15154e+01 1.35000e+00 + 46 46 1 -2.67255e+01 -2.33054e+01 -3.01254e+01 + 47 47 1 1.13800e+01 -3.05554e+01 -2.18054e+01 + 48 48 1 2.05100e+01 1.55100e+01 -6.31545e+00 + 49 49 1 -7.45545e+00 2.28000e+00 -2.04754e+01 + 50 50 1 -6.11545e+00 2.97900e+01 -2.21154e+01 + 51 51 1 -1.21355e+01 2.64200e+01 1.95100e+01 + 52 52 1 1.78800e+01 1.04000e+00 2.19500e+01 + 53 53 1 -1.64755e+01 1.01300e+01 1.40700e+01 + 54 54 1 -1.92955e+01 -2.53654e+01 -2.21754e+01 + 55 55 1 2.55800e+01 -2.55154e+01 3.60000e-01 + 56 56 1 1.79800e+01 1.51100e+01 2.99700e+01 + 57 57 1 2.65400e+01 2.17200e+01 2.76100e+01 + 58 58 1 -3.43545e+00 9.65000e+00 2.66700e+01 + 59 59 1 -1.77455e+01 3.02400e+01 1.95100e+01 + 60 60 1 2.93400e+01 3.01500e+01 -7.77545e+00 + 61 61 1 1.95600e+01 -1.14354e+01 -2.76154e+01 + 62 62 1 2.69600e+01 -1.91054e+01 1.92300e+01 + 63 63 1 -2.29855e+01 1.28800e+01 2.24600e+01 + 64 64 1 2.91000e+01 -9.55446e-01 1.35600e+01 + 65 65 1 2.06800e+01 -1.73545e+00 -1.27454e+01 + 66 66 1 -5.86545e+00 -1.14854e+01 1.16000e+01 + 67 67 1 2.67700e+01 -2.98654e+01 -1.12545e+00 + 68 68 1 -1.23655e+01 -2.27554e+01 -2.15654e+01 + 69 69 1 -4.60545e+00 2.12800e+01 -7.00000e-02 + 70 70 1 -5.55450e-01 -7.06545e+00 1.73000e+01 + 71 71 1 -5.79545e+00 -1.63354e+01 -2.29654e+01 + 72 72 1 4.00000e-02 1.56000e+00 1.93200e+01 + 73 73 1 3.02400e+01 -1.67854e+01 -2.48154e+01 + 74 74 1 -3.09355e+01 1.86700e+01 -1.22454e+01 + 75 75 1 -1.19955e+01 -8.34545e+00 2.04400e+01 + 76 76 1 3.89000e+00 -2.16854e+01 1.56300e+01 + 77 77 1 2.14900e+01 -1.14254e+01 8.10000e-01 + 78 78 1 2.74400e+01 1.13900e+01 -2.49545e+00 + 79 79 1 -2.99545e+00 -1.55154e+01 -1.94554e+01 + 80 80 1 2.07000e+00 9.21000e+00 -1.05154e+01 + 81 81 1 6.50000e-01 2.59100e+01 -2.39854e+01 + 82 82 1 -1.04255e+01 1.96100e+01 8.64000e+00 + 83 83 1 8.40000e+00 -1.56954e+01 8.10000e-01 + 84 84 1 7.39000e+00 -2.82254e+01 -4.90545e+00 + 85 85 1 1.14500e+01 -1.95054e+01 -7.24545e+00 + 86 86 1 2.47300e+01 -4.21545e+00 -1.81254e+01 + 87 87 1 1.06900e+01 1.46200e+01 -1.34754e+01 + 88 88 1 6.61000e+00 2.26100e+01 -1.62454e+01 + 89 89 1 1.64000e+01 2.74400e+01 8.31000e+00 + 90 90 1 -6.37545e+00 -4.54457e-02 -4.79545e+00 + 91 91 1 2.96500e+01 -2.74154e+01 -1.73854e+01 + 92 92 1 1.20600e+01 9.85000e+00 -6.06545e+00 + 93 93 1 2.11300e+01 4.90000e-01 9.35000e+00 + 94 94 1 -2.94255e+01 -2.17554e+01 -1.88354e+01 + 95 95 1 9.67000e+00 -1.47154e+01 -1.30854e+01 + 96 96 1 -1.04355e+01 1.95200e+01 3.58000e+00 + 97 97 1 1.39600e+01 -7.77545e+00 2.75700e+01 + 98 98 1 1.22700e+01 4.36000e+00 -7.43545e+00 + 99 99 1 -3.38545e+00 1.87500e+01 2.47000e+01 + 100 100 1 -1.34055e+01 -2.84054e+01 -2.52554e+01 + 101 101 1 1.13900e+01 -7.85545e+00 1.70300e+01 + 102 102 1 -4.00000e-01 2.16200e+01 -1.14954e+01 + 103 103 1 6.01000e+00 -5.74545e+00 -3.00854e+01 + 104 104 1 -1.96655e+01 -1.18854e+01 -2.29854e+01 + 105 105 1 2.12000e+00 -2.43654e+01 2.36400e+01 + 106 106 1 -2.53545e+00 -2.06554e+01 2.50000e+00 + 107 107 1 -3.06555e+01 -1.93654e+01 2.53600e+01 + 108 108 1 2.62600e+01 1.55000e+01 -3.03054e+01 + 109 109 1 -1.65055e+01 -5.86545e+00 -5.13545e+00 + 110 110 1 -1.66055e+01 -2.46754e+01 -1.04554e+01 + 111 111 1 -2.04545e+00 2.36200e+01 3.02600e+01 + 112 112 1 7.06000e+00 2.82900e+01 -2.83545e+00 + 113 113 1 2.48200e+01 -2.12545e+00 -2.29854e+01 + 114 114 1 -2.89655e+01 2.78300e+01 6.81000e+00 + 115 115 1 1.70900e+01 1.87200e+01 1.21000e+01 + 116 116 1 -1.67855e+01 4.83000e+00 1.19600e+01 + 117 117 1 2.31900e+01 -2.17554e+01 -2.28054e+01 + 118 118 1 1.88400e+01 1.95000e+01 2.83400e+01 + 119 119 1 -9.95545e+00 1.46300e+01 -3.17545e+00 + 120 120 1 1.72000e+01 -2.67354e+01 -2.82654e+01 + 121 121 1 2.95000e+00 -1.74354e+01 1.54900e+01 + 122 122 1 8.31000e+00 -3.22545e+00 -2.01254e+01 + 123 123 1 2.75400e+01 6.82000e+00 1.73800e+01 + 124 124 1 2.94000e+01 2.36900e+01 2.82500e+01 + 125 125 1 1.44600e+01 -4.81545e+00 5.55000e+00 + 126 126 1 -2.36545e+00 3.55000e+00 -1.71154e+01 + 127 127 1 1.93600e+01 1.67700e+01 2.56200e+01 + 128 128 1 -9.42545e+00 2.30900e+01 -1.49154e+01 + 129 129 1 3.28000e+00 -2.20454e+01 -7.81545e+00 + 130 130 1 -9.65545e+00 1.68700e+01 -8.51545e+00 + 131 131 1 -2.03155e+01 2.34000e+01 -1.09754e+01 + 132 132 1 2.63100e+01 -8.29545e+00 -4.80545e+00 + 133 133 1 1.92100e+01 -2.67954e+01 1.41700e+01 + 134 134 1 4.99000e+00 1.44600e+01 2.29400e+01 + 135 135 1 4.54000e+00 1.01600e+01 3.10900e+01 + 136 136 1 -2.98255e+01 -1.41354e+01 6.76000e+00 + 137 137 1 -1.96355e+01 9.70000e+00 -1.20254e+01 + 138 138 1 4.51000e+00 -2.61354e+01 4.06000e+00 + 139 139 1 2.83500e+01 -9.33545e+00 2.76000e+00 + 140 140 1 1.62900e+01 -2.42454e+01 -9.21545e+00 + 141 141 1 1.90800e+01 6.11000e+00 3.07600e+01 + 142 142 1 6.91000e+00 1.34300e+01 -1.55654e+01 + 143 143 1 -1.40455e+01 6.54000e+00 -1.42654e+01 + 144 144 1 -2.58055e+01 -1.85754e+01 -5.04545e+00 + 145 145 1 -1.53545e+00 -6.00000e-02 -1.42154e+01 + 146 146 1 2.66500e+01 -1.94754e+01 2.72900e+01 + 147 147 1 2.43000e+00 9.24000e+00 -2.74854e+01 + 148 148 1 1.48300e+01 1.95700e+01 -9.12545e+00 + 149 149 1 -9.55450e-01 9.74000e+00 3.86000e+00 + 150 150 1 -2.44755e+01 2.04500e+01 2.88900e+01 + 151 151 1 1.95300e+01 -2.43854e+01 -2.16545e+00 + 152 152 1 -1.09455e+01 2.69200e+01 3.77000e+00 + 153 153 1 1.53800e+01 -3.76545e+00 3.07900e+01 + 154 154 1 1.67600e+01 1.62700e+01 3.40000e-01 + 155 155 1 8.93000e+00 1.94500e+01 -1.11354e+01 + 156 156 1 -6.31545e+00 1.26100e+01 -4.73545e+00 + 157 157 1 2.10000e+00 -1.34854e+01 7.48000e+00 + 158 158 1 -2.89155e+01 -1.09154e+01 -6.11545e+00 + 159 159 1 2.63300e+01 1.57700e+01 1.93100e+01 + 160 160 1 -2.52545e+00 -3.48545e+00 3.57000e+00 + 161 161 1 1.42800e+01 -7.95446e-01 -9.53545e+00 + 162 162 1 1.22800e+01 -2.67154e+01 -2.48654e+01 + 163 163 1 8.20000e+00 2.65600e+01 2.05400e+01 + 164 164 1 -1.84545e+00 -2.55854e+01 2.31200e+01 + 165 165 1 -7.61545e+00 2.56100e+01 -2.44854e+01 + 166 166 1 2.30000e+01 -1.11754e+01 5.15000e+00 + 167 167 1 -1.33545e+00 -2.37554e+01 2.01200e+01 + 168 168 1 -9.42545e+00 -5.70545e+00 -1.97854e+01 + 169 169 1 -1.70855e+01 1.65100e+01 2.09000e+01 + 170 170 1 1.31000e+00 1.66400e+01 2.15700e+01 + 171 171 1 -1.45055e+01 1.04700e+01 -1.30545e+00 + 172 172 1 9.88000e+00 1.13000e+01 -1.25354e+01 + 173 173 1 1.04600e+01 -2.47354e+01 -1.17545e+00 + 174 174 1 -1.69545e+00 1.84100e+01 5.75000e+00 + 175 175 1 2.24600e+01 -1.59354e+01 1.91400e+01 + 176 176 1 -8.75545e+00 1.22500e+01 1.82900e+01 + 177 177 1 4.01000e+00 -2.14754e+01 2.28400e+01 + 178 178 1 -1.66955e+01 6.24554e-01 5.77000e+00 + 179 179 1 -1.31655e+01 9.33000e+00 -2.86754e+01 + 180 180 1 1.70300e+01 -2.79654e+01 2.25900e+01 + 181 181 1 1.10000e+01 2.78400e+01 -3.04854e+01 + 182 182 1 -7.71545e+00 -5.27545e+00 6.51000e+00 + 183 183 1 -2.44855e+01 -2.84954e+01 2.70500e+01 + 184 184 1 -1.43555e+01 2.45000e+00 2.09200e+01 + 185 185 1 2.78600e+01 -2.01545e+00 4.68000e+00 + 186 186 1 2.29200e+01 -1.75654e+01 2.57100e+01 + 187 187 1 3.00000e+00 -1.10454e+01 -1.75545e+00 + 188 188 1 3.09800e+01 -7.41545e+00 -1.94054e+01 + 189 189 1 1.22700e+01 5.92000e+00 1.33000e+00 + 190 190 1 -2.61355e+01 1.75800e+01 -2.44754e+01 + 191 191 1 1.57000e+01 1.72800e+01 1.98700e+01 + 192 192 1 7.09000e+00 -1.20054e+01 -1.01054e+01 + 193 193 1 6.83000e+00 2.39000e+01 3.05700e+01 + 194 194 1 3.03100e+01 -7.11545e+00 -1.39254e+01 + 195 195 1 -2.43255e+01 -1.14554e+01 2.51400e+01 + 196 196 1 -1.70855e+01 -2.04954e+01 -1.11354e+01 + 197 197 1 -2.27255e+01 2.68300e+01 -2.55254e+01 + 198 198 1 2.93800e+01 -1.77545e+00 -1.87754e+01 + 199 199 1 -2.14545e+00 -2.81654e+01 1.86900e+01 + 200 200 1 6.96000e+00 1.00100e+01 2.71700e+01 + 201 201 1 -1.53255e+01 5.22000e+00 8.90000e-01 + 202 202 1 1.84900e+01 2.95800e+01 -2.82254e+01 + 203 203 1 -2.42255e+01 -2.38054e+01 8.18000e+00 + 204 204 1 2.15000e+00 1.13700e+01 2.53400e+01 + 205 205 1 -1.88355e+01 -3.03254e+01 -2.76954e+01 + 206 206 1 1.58300e+01 -2.00654e+01 1.22200e+01 + 207 207 1 -2.68655e+01 3.56000e+00 -2.15054e+01 + 208 208 1 8.45000e+00 -1.15446e-01 2.97500e+01 + 209 209 1 -2.89555e+01 9.44000e+00 -5.89545e+00 + 210 210 1 -7.37545e+00 -1.25154e+01 -3.03654e+01 + 211 211 1 -2.91155e+01 -2.54654e+01 1.57700e+01 + 212 212 1 -2.90555e+01 -1.25545e+00 -3.02554e+01 + 213 213 1 -9.68545e+00 1.88500e+01 -1.45554e+01 + 214 214 1 2.84200e+01 -1.89154e+01 -3.01554e+01 + 215 215 1 9.65000e+00 -6.89545e+00 2.45500e+01 + 216 216 1 -2.42755e+01 -1.45154e+01 -1.51054e+01 + 217 217 1 -1.12155e+01 1.82700e+01 1.68400e+01 + 218 218 1 -2.43255e+01 -2.32854e+01 2.69500e+01 + 219 219 1 2.04900e+01 -3.00754e+01 -9.01545e+00 + 220 220 1 2.49500e+01 -1.10254e+01 -9.03545e+00 + 221 221 1 -1.34455e+01 1.81900e+01 -6.45445e-01 + 222 222 1 1.57400e+01 2.45800e+01 1.83100e+01 + 223 223 1 -2.14155e+01 9.58000e+00 1.14600e+01 + 224 224 1 1.68200e+01 -7.32545e+00 -2.60754e+01 + 225 225 1 2.89500e+01 1.17700e+01 9.22000e+00 + 226 226 1 1.03000e+00 1.80600e+01 -2.96054e+01 + 227 227 1 1.92900e+01 2.09600e+01 -1.11654e+01 + 228 228 1 1.32400e+01 1.29500e+01 -2.67054e+01 + 229 229 1 2.60400e+01 1.60700e+01 3.47000e+00 + 230 230 1 5.60000e+00 1.22900e+01 -2.65954e+01 + 231 231 1 1.96100e+01 1.44800e+01 1.66200e+01 + 232 232 1 3.03000e+00 1.65900e+01 -2.13454e+01 + 233 233 1 3.11100e+01 1.77400e+01 3.69000e+00 + 234 234 1 2.03700e+01 1.44100e+01 -7.25445e-01 + 235 235 1 2.51400e+01 -5.76545e+00 2.88700e+01 + 236 236 1 5.56000e+00 -3.17545e+00 -4.09545e+00 + 237 237 1 1.46000e+01 -2.76354e+01 -2.15354e+01 + 238 238 1 -2.10000e-01 3.08100e+01 -2.98545e+00 + 239 239 1 2.19600e+01 9.17000e+00 2.89400e+01 + 240 240 1 -3.02555e+01 1.78900e+01 -2.30654e+01 + 241 241 1 -1.64855e+01 3.58000e+00 7.26000e+00 + 242 242 1 2.94800e+01 -3.02254e+01 7.30000e+00 + 243 243 1 -1.79655e+01 2.97600e+01 4.83000e+00 + 244 244 1 -2.35655e+01 1.11300e+01 2.88000e+01 + 245 245 1 5.73000e+00 -7.06545e+00 -9.55545e+00 + 246 246 1 -2.15155e+01 -2.51054e+01 2.76900e+01 + 247 247 1 2.63900e+01 1.94100e+01 1.39500e+01 + 248 248 1 -1.89855e+01 1.64200e+01 7.29000e+00 + 249 249 1 1.73800e+01 -1.07054e+01 -5.63545e+00 + 250 250 1 -8.08545e+00 -9.68545e+00 1.06000e+00 + 251 251 1 2.44200e+01 2.75200e+01 -1.28654e+01 + 252 252 1 -1.02655e+01 -1.51554e+01 -2.30954e+01 + 253 253 1 -1.41155e+01 -7.46545e+00 1.69800e+01 + 254 254 1 1.96000e+01 -1.03754e+01 2.81800e+01 + 255 255 1 -2.89545e+00 -2.15354e+01 -3.06545e+00 + 256 256 1 2.18400e+01 -2.93854e+01 4.10000e+00 + 257 257 1 -1.09955e+01 1.53800e+01 2.07500e+01 + 258 258 1 2.11900e+01 2.80600e+01 1.14500e+01 + 259 259 1 8.66000e+00 1.14900e+01 1.67500e+01 + 260 260 1 -1.59255e+01 -1.73954e+01 7.80000e+00 + 261 261 1 -1.97755e+01 -2.67754e+01 -3.04854e+01 + 262 262 1 -8.69545e+00 -1.61554e+01 2.01900e+01 + 263 263 1 2.66100e+01 5.44000e+00 2.13300e+01 + 264 264 1 -1.24055e+01 -2.69254e+01 -1.21354e+01 + 265 265 1 -2.18655e+01 -1.06854e+01 1.32700e+01 + 266 266 1 -1.08055e+01 3.52000e+00 -2.70054e+01 + 267 267 1 1.15800e+01 -2.67154e+01 1.77900e+01 + 268 268 1 -1.47955e+01 -2.53754e+01 -2.37354e+01 + 269 269 1 -1.29055e+01 6.56000e+00 -2.51054e+01 + 270 270 1 2.06000e+01 2.95900e+01 -3.10854e+01 + 271 271 1 1.76300e+01 1.65700e+01 9.29000e+00 + 272 272 1 2.33000e+00 -1.81554e+01 -1.51354e+01 + 273 273 1 -2.61955e+01 -3.96545e+00 1.46500e+01 + 274 274 1 -2.81455e+01 -1.76545e+00 6.58000e+00 + 275 275 1 -2.35545e+00 1.43200e+01 2.95400e+01 + 276 276 1 9.70000e+00 -2.13854e+01 1.55500e+01 + 277 277 1 -1.59455e+01 5.44000e+00 2.09100e+01 + 278 278 1 1.19000e+00 1.47700e+01 1.14500e+01 + 279 279 1 -2.93755e+01 6.87000e+00 1.19600e+01 + 280 280 1 -9.41545e+00 1.63700e+01 3.09200e+01 + 281 281 1 7.25000e+00 8.46000e+00 2.04000e+00 + 282 282 1 -1.22455e+01 -2.06954e+01 6.37000e+00 + 283 283 1 2.22900e+01 3.00700e+01 2.53900e+01 + 284 284 1 -8.90545e+00 2.02200e+01 -2.36954e+01 + 285 285 1 -3.06755e+01 -2.74854e+01 3.35000e+00 + 286 286 1 2.61000e+01 1.75600e+01 2.89100e+01 + 287 287 1 -1.28255e+01 -1.38545e+00 -2.94754e+01 + 288 288 1 -1.61755e+01 -1.09545e+00 -2.48654e+01 + 289 289 1 -9.85545e+00 -1.40054e+01 -1.51054e+01 + 290 290 1 1.39000e+01 4.77000e+00 5.77000e+00 + 291 291 1 -1.84755e+01 1.66600e+01 2.86300e+01 + 292 292 1 -1.42655e+01 3.02500e+01 1.89000e+00 + 293 293 1 7.72000e+00 7.29000e+00 -1.14254e+01 + 294 294 1 -6.12545e+00 3.54000e+00 1.30100e+01 + 295 295 1 -2.31555e+01 -2.60545e+00 -2.92554e+01 + 296 296 1 2.89800e+01 2.88700e+01 3.04100e+01 + 297 297 1 2.43600e+01 -7.75446e-01 1.21200e+01 + 298 298 1 -2.73355e+01 3.07000e+00 1.39800e+01 + 299 299 1 1.19000e+01 -2.84754e+01 -1.70754e+01 + 300 300 1 1.30300e+01 2.12200e+01 2.86600e+01 + 301 301 1 -4.75545e+00 2.55000e+00 2.20700e+01 + 302 302 1 -1.79355e+01 2.91500e+01 9.04000e+00 + 303 303 1 -2.77855e+01 1.29400e+01 -2.89554e+01 + 304 304 1 1.97200e+01 1.70300e+01 -2.76954e+01 + 305 305 1 -9.37545e+00 -2.93254e+01 2.23400e+01 + 306 306 1 2.52500e+01 2.64600e+01 2.63400e+01 + 307 307 1 2.64400e+01 -1.30545e+00 -1.25754e+01 + 308 308 1 2.91000e+01 -2.27754e+01 -2.74854e+01 + 309 309 1 -1.26955e+01 -2.56454e+01 2.03000e+00 + 310 310 1 1.32000e+00 9.31000e+00 1.39100e+01 + 311 311 1 -4.90000e-01 -7.72545e+00 -7.09545e+00 + 312 312 1 1.04000e+00 -2.77545e+00 -2.27254e+01 + 313 313 1 1.72900e+01 -6.57545e+00 -1.28754e+01 + 314 314 1 -2.89355e+01 6.59000e+00 2.80200e+01 + 315 315 1 -1.10855e+01 2.34900e+01 1.62000e+01 + 316 316 1 -1.64055e+01 -9.88545e+00 2.38500e+01 + 317 317 1 1.27300e+01 -8.04545e+00 -2.20554e+01 + 318 318 1 -3.01855e+01 6.00000e+00 -1.65545e+00 + 319 319 1 -5.89545e+00 -5.75446e-01 1.14200e+01 + 320 320 1 2.35700e+01 -2.12354e+01 2.71900e+01 + 321 321 1 2.05800e+01 -2.24154e+01 -1.20354e+01 + 322 322 1 1.61300e+01 -2.61854e+01 8.20000e+00 + 323 323 1 -7.84545e+00 2.75100e+01 2.51500e+01 + 324 324 1 -2.06755e+01 -1.37554e+01 -1.83254e+01 + 325 325 1 2.29700e+01 3.05500e+01 -1.26545e+00 + 326 326 1 1.23300e+01 -1.86554e+01 -1.91554e+01 + 327 327 1 1.38100e+01 2.07000e+00 -2.25445e-01 + 328 328 1 5.98000e+00 6.22000e+00 1.08900e+01 + 329 329 1 -2.29155e+01 2.31900e+01 -2.93054e+01 + 330 330 1 -1.92255e+01 2.32100e+01 -1.67354e+01 + 331 331 1 -2.95255e+01 -1.81854e+01 -1.54154e+01 + 332 332 1 -2.24755e+01 3.28000e+00 2.39100e+01 + 333 333 1 -1.91655e+01 2.93700e+01 2.58000e+01 + 334 334 1 -2.39855e+01 3.13000e+00 -3.13545e+00 + 335 335 1 -2.30055e+01 -3.57545e+00 -3.14545e+00 + 336 336 1 3.03200e+01 -2.05654e+01 -2.30254e+01 + 337 337 1 2.81000e+01 -1.28854e+01 -6.35445e-01 + 338 338 1 5.79000e+00 -7.01545e+00 1.42700e+01 + 339 339 1 1.50700e+01 1.92100e+01 1.57000e+01 + 340 340 1 -1.69255e+01 -2.18754e+01 2.23400e+01 + 341 341 1 -1.14155e+01 1.39700e+01 1.26600e+01 + 342 342 1 2.81900e+01 -2.97654e+01 -1.48454e+01 + 343 343 1 2.59800e+01 7.38000e+00 -2.26954e+01 + 344 344 1 9.13000e+00 -2.89254e+01 1.98400e+01 + 345 345 1 -1.40055e+01 1.45000e+01 9.41000e+00 + 346 346 1 -2.69455e+01 1.15200e+01 -9.94545e+00 + 347 347 1 1.20400e+01 3.00600e+01 -1.36545e+00 + 348 348 1 2.90000e+00 2.30400e+01 2.66700e+01 + 349 349 1 1.48900e+01 9.89000e+00 -1.42154e+01 + 350 350 1 -1.34955e+01 1.81000e+01 4.59000e+00 + 351 351 1 5.16000e+00 -4.54545e+00 -1.74354e+01 + 352 352 1 -1.68555e+01 -2.70545e+00 -2.86654e+01 + 353 353 1 -1.52655e+01 -2.50554e+01 -8.15445e-01 + 354 354 1 -2.33755e+01 -1.99254e+01 -1.92254e+01 + 355 355 1 1.37900e+01 1.21100e+01 -9.66545e+00 + 356 356 1 2.97700e+01 7.78000e+00 -1.27054e+01 + 357 357 1 1.58700e+01 -1.82754e+01 -1.08054e+01 + 358 358 1 -3.77545e+00 2.01800e+01 -1.69154e+01 + 359 359 1 -1.89545e+00 -4.41545e+00 8.80000e+00 + 360 360 1 -1.71455e+01 -1.48854e+01 1.34500e+01 + 361 361 1 1.00400e+01 -1.40054e+01 -2.72054e+01 + 362 362 1 -9.92545e+00 2.28400e+01 2.09300e+01 + 363 363 1 -2.93355e+01 -1.18154e+01 -1.52554e+01 + 364 364 1 1.02600e+01 -1.37154e+01 -7.84545e+00 + 365 365 1 7.91000e+00 1.78800e+01 2.18400e+01 + 366 366 1 3.08000e+00 -2.03654e+01 2.70900e+01 + 367 367 1 -2.78545e+00 -2.92454e+01 2.87000e+01 + 368 368 1 1.61000e+00 -8.31545e+00 -2.40754e+01 + 369 369 1 -1.31255e+01 -1.38354e+01 -2.65054e+01 + 370 370 1 1.84000e+00 -2.36754e+01 2.78500e+01 + 371 371 1 2.81600e+01 -2.74354e+01 -9.37545e+00 + 372 372 1 2.83900e+01 2.14800e+01 -1.45354e+01 + 373 373 1 1.78000e+01 2.32000e+01 -8.50545e+00 + 374 374 1 -1.59155e+01 7.13000e+00 -2.66554e+01 + 375 375 1 2.97300e+01 2.19400e+01 -2.70354e+01 + 376 376 1 6.18000e+00 2.33000e+01 -1.20554e+01 + 377 377 1 -8.86545e+00 -2.58354e+01 -2.72754e+01 + 378 378 1 -5.01545e+00 -2.90954e+01 2.74000e+00 + 379 379 1 -1.64755e+01 -1.01554e+01 -2.39654e+01 + 380 380 1 3.07500e+01 1.17300e+01 -1.84654e+01 + 381 381 1 -1.40755e+01 1.85000e+01 2.21800e+01 + 382 382 1 2.21300e+01 2.73100e+01 2.76000e+01 + 383 383 1 1.48000e+01 -1.10654e+01 -1.30354e+01 + 384 384 1 2.03200e+01 2.32000e+00 -2.70545e+00 + 385 385 1 2.44600e+01 2.27900e+01 1.36000e+00 + 386 386 1 -3.13545e+00 -1.61154e+01 6.87000e+00 + 387 387 1 1.57500e+01 1.15900e+01 1.98200e+01 + 388 388 1 1.22700e+01 2.71800e+01 2.28300e+01 + 389 389 1 1.32300e+01 2.62300e+01 -1.31554e+01 + 390 390 1 1.71700e+01 -1.90654e+01 -3.10454e+01 + 391 391 1 3.65000e+00 2.84500e+01 -4.05445e-01 + 392 392 1 5.36000e+00 -1.36254e+01 -6.50545e+00 + 393 393 1 2.73000e+01 -2.25054e+01 1.75800e+01 + 394 394 1 2.47400e+01 -1.51854e+01 3.05000e+01 + 395 395 1 -1.65555e+01 1.74200e+01 -1.17854e+01 + 396 396 1 1.17700e+01 -1.60545e+00 -1.42545e+00 + 397 397 1 -2.81055e+01 1.98400e+01 -6.14545e+00 + 398 398 1 -1.39055e+01 2.89000e+01 2.26300e+01 + 399 399 1 -9.55545e+00 -6.10545e+00 2.81600e+01 + 400 400 1 9.96000e+00 -1.67454e+01 2.24900e+01 + 401 401 1 -1.40355e+01 -1.66154e+01 2.04000e+01 + 402 402 1 -4.74545e+00 1.50000e-01 -1.89254e+01 + 403 403 1 -1.74255e+01 2.13500e+01 2.41800e+01 + 404 404 1 3.10200e+01 -2.70754e+01 -5.74545e+00 + 405 405 1 -1.11855e+01 -1.30545e+00 -1.69854e+01 + 406 406 1 1.95300e+01 2.47300e+01 -2.55754e+01 + 407 407 1 2.55900e+01 -1.43754e+01 2.60300e+01 + 408 408 1 -2.59155e+01 1.75500e+01 -2.95954e+01 + 409 409 1 1.74000e+01 -1.65554e+01 3.45000e+00 + 410 410 1 -1.09055e+01 -1.05254e+01 -2.94654e+01 + 411 411 1 2.39500e+01 1.00900e+01 -8.27545e+00 + 412 412 1 -2.39255e+01 1.56200e+01 -9.03545e+00 + 413 413 1 2.03600e+01 8.71000e+00 -1.41545e+00 + 414 414 1 -5.93545e+00 1.80400e+01 -1.24254e+01 + 415 415 1 -2.29055e+01 -2.88854e+01 9.03000e+00 + 416 416 1 3.34000e+00 -1.36054e+01 -9.39545e+00 + 417 417 1 2.39300e+01 -2.87054e+01 2.77600e+01 + 418 418 1 -2.04655e+01 -2.44454e+01 2.12000e+00 + 419 419 1 1.83100e+01 -1.29754e+01 1.98000e+00 + 420 420 1 2.04400e+01 -2.71954e+01 2.11300e+01 + 421 421 1 -2.02255e+01 6.04000e+00 1.85100e+01 + 422 422 1 1.11600e+01 1.35900e+01 2.02700e+01 + 423 423 1 -1.86545e+00 -2.87754e+01 -2.98545e+00 + 424 424 1 -4.90545e+00 -1.79154e+01 2.02000e+01 + 425 425 1 -4.58545e+00 7.26000e+00 2.01000e+00 + 426 426 1 -2.60255e+01 8.34000e+00 -1.23754e+01 + 427 427 1 3.96000e+00 1.41600e+01 -5.36545e+00 + 428 428 1 7.55000e+00 2.75300e+01 5.51000e+00 + 429 429 1 -9.11545e+00 2.47200e+01 2.81500e+01 + 430 430 1 -5.67545e+00 -4.90545e+00 -1.82254e+01 + 431 431 1 3.08800e+01 -2.53754e+01 -2.98054e+01 + 432 432 1 -1.29255e+01 -1.05854e+01 -2.38254e+01 + 433 433 1 -1.84755e+01 6.93000e+00 1.51900e+01 + 434 434 1 -1.75545e+00 -3.14545e+00 -1.25654e+01 + 435 435 1 1.74550e-01 -1.92654e+01 5.84000e+00 + 436 436 1 -4.75450e-01 -1.91254e+01 -5.50545e+00 + 437 437 1 2.87300e+01 1.62000e+01 -1.62654e+01 + 438 438 1 2.37500e+01 7.45543e-02 -1.90654e+01 + 439 439 1 3.02500e+01 1.41600e+01 1.30000e+01 + 440 440 1 1.28000e+01 9.87000e+00 -2.23054e+01 + 441 441 1 1.92500e+01 -2.02054e+01 2.67000e+01 + 442 442 1 1.18000e+01 -4.72545e+00 -2.83554e+01 + 443 443 1 1.79900e+01 -3.03454e+01 4.59000e+00 + 444 444 1 -2.33255e+01 1.14200e+01 2.49000e+00 + 445 445 1 2.68200e+01 1.52600e+01 -4.15445e-01 + 446 446 1 2.51000e+01 -9.06545e+00 2.62500e+01 + 447 447 1 3.36000e+00 -2.23754e+01 -1.52054e+01 + 448 448 1 -1.67255e+01 -1.59354e+01 8.90000e-01 + 449 449 1 -9.29545e+00 -2.35654e+01 7.09000e+00 + 450 450 1 -1.52255e+01 3.45543e-02 2.90200e+01 + 451 451 1 -2.24955e+01 -9.39545e+00 5.71000e+00 + 452 452 1 5.22000e+00 -1.71954e+01 9.30000e-01 + 453 453 1 -2.45555e+01 1.88000e+00 1.85600e+01 + 454 454 1 1.07300e+01 -2.77545e+00 4.40000e+00 + 455 455 1 -2.38155e+01 -6.46545e+00 -6.15445e-01 + 456 456 1 2.52500e+01 -2.39954e+01 2.03900e+01 + 457 457 1 -2.41155e+01 -2.30000e-01 1.48500e+01 + 458 458 1 -3.08355e+01 2.68300e+01 2.30000e-01 + 459 459 1 -2.82055e+01 -2.22254e+01 8.23000e+00 + 460 460 1 1.31600e+01 -2.17254e+01 8.13000e+00 + 461 461 1 -1.11255e+01 5.62000e+00 1.06900e+01 + 462 462 1 -1.74545e+00 1.12400e+01 3.30000e-01 + 463 463 1 -1.32255e+01 1.10500e+01 2.50300e+01 + 464 464 1 2.86500e+01 9.85000e+00 -2.96854e+01 + 465 465 1 -2.61655e+01 -1.54654e+01 -3.08354e+01 + 466 466 1 -7.26545e+00 7.11000e+00 2.40500e+01 + 467 467 1 2.22600e+01 -1.61854e+01 -1.93354e+01 + 468 468 1 1.85900e+01 -1.38545e+00 1.08900e+01 + 469 469 1 2.00300e+01 2.43100e+01 9.93000e+00 + 470 470 1 1.22700e+01 -1.39754e+01 8.80000e+00 + 471 471 1 -2.46955e+01 -2.68554e+01 3.00400e+01 + 472 472 1 2.93600e+01 -2.97654e+01 1.18900e+01 + 473 473 1 -2.76455e+01 -2.70854e+01 -2.44545e+00 + 474 474 1 -1.95355e+01 -8.05545e+00 2.08800e+01 + 475 475 1 5.95000e+00 -1.98545e+00 -2.96254e+01 + 476 476 1 2.15100e+01 -9.19545e+00 1.19600e+01 + 477 477 1 -1.02355e+01 5.13000e+00 2.42400e+01 + 478 478 1 -9.86545e+00 1.27600e+01 2.26100e+01 + 479 479 1 -1.99555e+01 6.75000e+00 -2.85654e+01 + 480 480 1 -2.07655e+01 -5.00000e-02 1.75000e+01 + 481 481 1 6.77000e+00 -9.94545e+00 6.86000e+00 + 482 482 1 -2.11355e+01 4.20000e+00 -3.07154e+01 + 483 483 1 -1.97655e+01 9.81000e+00 2.64700e+01 + 484 484 1 2.95100e+01 2.67900e+01 1.49600e+01 + 485 485 1 2.58000e+01 -9.81545e+00 5.40000e-01 + 486 486 1 1.46900e+01 7.72000e+00 2.60300e+01 + 487 487 1 -2.50755e+01 -5.87545e+00 4.08000e+00 + 488 488 1 -2.81855e+01 2.86900e+01 1.53700e+01 + 489 489 1 -8.22545e+00 -3.08554e+01 5.10000e-01 + 490 490 1 -7.20545e+00 2.89100e+01 4.08000e+00 + 491 491 1 -2.52255e+01 7.34000e+00 -2.59954e+01 + 492 492 1 2.58600e+01 2.45000e+00 1.89100e+01 + 493 493 1 3.85000e+00 -1.36354e+01 2.35700e+01 + 494 494 1 3.12000e+00 2.66900e+01 2.98800e+01 + 495 495 1 -2.96545e+00 8.27000e+00 -1.59054e+01 + 496 496 1 2.89800e+01 -2.45954e+01 2.05600e+01 + 497 497 1 2.92000e+00 7.00000e-02 2.50000e+00 + 498 498 1 2.49900e+01 1.01400e+01 2.70900e+01 + 499 499 1 -1.99255e+01 1.31000e+00 -9.63545e+00 + 500 500 1 1.27400e+01 2.97200e+01 8.57000e+00 + 501 501 1 -5.96545e+00 1.38200e+01 7.49000e+00 + 502 502 1 -4.25450e-01 2.88700e+01 1.29500e+01 + 503 503 1 1.77100e+01 9.09000e+00 -1.08454e+01 + 504 504 1 2.65000e+01 2.37300e+01 -2.66154e+01 + 505 505 1 -4.97545e+00 -8.12545e+00 6.45000e+00 + 506 506 1 -1.89545e+00 -1.05954e+01 1.38300e+01 + 507 507 1 -2.32755e+01 -1.24054e+01 -2.51554e+01 + 508 508 1 -2.03455e+01 1.95400e+01 5.54555e-01 + 509 509 1 -1.87055e+01 -2.44545e+00 -7.80545e+00 + 510 510 1 -1.62655e+01 1.81000e+00 2.53000e+01 + 511 511 1 1.13900e+01 4.05000e+00 -2.75954e+01 + 512 512 1 1.46600e+01 2.17900e+01 -1.27754e+01 + 513 513 1 1.09600e+01 -1.75854e+01 9.21000e+00 + 514 514 1 -1.32755e+01 -1.69545e+00 2.07300e+01 + 515 515 1 1.65700e+01 2.75100e+01 3.93000e+00 + 516 516 1 -2.74545e+00 6.74000e+00 -1.89754e+01 + 517 517 1 2.89300e+01 -1.68854e+01 2.91400e+01 + 518 518 1 -1.70455e+01 1.08200e+01 -2.84854e+01 + 519 519 1 2.81300e+01 -1.75754e+01 -1.51754e+01 + 520 520 1 1.29400e+01 1.58700e+01 -2.23954e+01 + 521 521 1 -2.60955e+01 2.69500e+01 2.81700e+01 + 522 522 1 2.00700e+01 2.40000e+01 2.02600e+01 + 523 523 1 7.57000e+00 1.79900e+01 2.93500e+01 + 524 524 1 2.33200e+01 -2.37754e+01 2.93500e+01 + 525 525 1 1.45100e+01 -1.07654e+01 -2.40754e+01 + 526 526 1 3.01100e+01 2.91500e+01 -1.24154e+01 + 527 527 1 2.87500e+01 -2.30954e+01 8.52000e+00 + 528 528 1 2.74200e+01 1.06700e+01 1.29100e+01 + 529 529 1 -2.04155e+01 -1.74154e+01 1.11000e+01 + 530 530 1 1.76800e+01 2.73600e+01 -7.27545e+00 + 531 531 1 -1.40755e+01 -8.53545e+00 -1.49954e+01 + 532 532 1 -4.75450e-01 -2.23654e+01 1.21600e+01 + 533 533 1 -1.85755e+01 -3.09054e+01 -7.11545e+00 + 534 534 1 -4.04545e+00 -8.68545e+00 -2.96354e+01 + 535 535 1 -3.00955e+01 1.40200e+01 8.11000e+00 + 536 536 1 -3.27545e+00 1.66000e+00 -1.11154e+01 + 537 537 1 1.00000e-01 1.86000e+01 2.47000e+01 + 538 538 1 -1.43855e+01 -1.03454e+01 1.11200e+01 + 539 539 1 2.18800e+01 2.18500e+01 -1.71545e+00 + 540 540 1 -1.57355e+01 2.43200e+01 -8.55445e-01 + 541 541 1 2.01900e+01 3.43000e+00 -1.32554e+01 + 542 542 1 -1.60955e+01 -2.98154e+01 -1.02254e+01 + 543 543 1 1.96200e+01 -8.30545e+00 5.50000e+00 + 544 544 1 -3.05055e+01 1.32400e+01 1.78700e+01 + 545 545 1 1.14200e+01 -1.06154e+01 2.71600e+01 + 546 546 1 2.59000e+01 -2.91754e+01 -2.44054e+01 + 547 547 1 4.14550e-01 -1.12254e+01 3.00300e+01 + 548 548 1 8.18000e+00 8.37000e+00 1.42800e+01 + 549 549 1 -2.51055e+01 2.48200e+01 1.47000e+01 + 550 550 1 1.31000e+01 1.17800e+01 -1.95754e+01 + 551 551 1 -3.19545e+00 2.55000e+01 -1.26954e+01 + 552 552 1 1.22000e+01 -2.83054e+01 8.42000e+00 + 553 553 1 2.11600e+01 3.07600e+01 -2.38554e+01 + 554 554 1 1.59900e+01 2.79400e+01 -2.96954e+01 + 555 555 1 1.07700e+01 1.52700e+01 -9.12545e+00 + 556 556 1 -1.75855e+01 -5.97545e+00 1.28900e+01 + 557 557 1 -1.47545e+00 1.00900e+01 1.14400e+01 + 558 558 1 -1.22455e+01 4.09000e+00 -9.83545e+00 + 559 559 1 1.75500e+01 1.88000e+00 5.86000e+00 + 560 560 1 -3.55450e-01 2.34554e-01 -2.00954e+01 + 561 561 1 2.66700e+01 1.76100e+01 -9.32545e+00 + 562 562 1 -2.30655e+01 -3.85545e+00 2.84900e+01 + 563 563 1 -6.48545e+00 2.81700e+01 1.76000e+01 + 564 564 1 -2.14055e+01 -1.05554e+01 2.00900e+01 + 565 565 1 -2.52755e+01 4.94000e+00 1.02700e+01 + 566 566 1 -2.19555e+01 1.76700e+01 1.14400e+01 + 567 567 1 -1.05555e+01 -2.12654e+01 -9.36545e+00 + 568 568 1 -8.30545e+00 -1.93054e+01 -1.38254e+01 + 569 569 1 -1.63255e+01 2.43100e+01 -2.64854e+01 + 570 570 1 -2.49545e+00 2.02300e+01 -3.77545e+00 + 571 571 1 1.87100e+01 1.25400e+01 -1.27254e+01 + 572 572 1 -1.75655e+01 6.80000e+00 -1.47454e+01 + 573 573 1 2.63700e+01 7.22000e+00 1.02500e+01 + 574 574 1 1.80000e+01 -2.35054e+01 -1.76954e+01 + 575 575 1 -9.35545e+00 -1.99954e+01 9.56000e+00 + 576 576 1 -8.74545e+00 1.64000e+00 -7.30545e+00 + 577 577 1 7.71000e+00 -1.07654e+01 1.64800e+01 + 578 578 1 1.09800e+01 1.85200e+01 2.61300e+01 + 579 579 1 -2.69155e+01 3.01900e+01 -3.06654e+01 + 580 580 1 -1.99955e+01 5.70000e+00 2.30800e+01 + 581 581 1 3.10700e+01 -1.47954e+01 -8.96545e+00 + 582 582 1 -1.66755e+01 -2.57754e+01 2.67800e+01 + 583 583 1 5.69000e+00 -1.98454e+01 3.64000e+00 + 584 584 1 2.77500e+01 -2.04554e+01 3.60000e+00 + 585 585 1 -2.16255e+01 2.71500e+01 -1.80654e+01 + 586 586 1 -2.74755e+01 -1.06454e+01 1.80400e+01 + 587 587 1 3.50000e+00 -9.61545e+00 4.09000e+00 + 588 588 1 -1.81155e+01 1.59600e+01 -1.95154e+01 + 589 589 1 1.68000e+00 -9.85545e+00 2.14100e+01 + 590 590 1 -3.55545e+00 2.87200e+01 -4.00545e+00 + 591 591 1 -1.32055e+01 4.39000e+00 4.34000e+00 + 592 592 1 4.92000e+00 -3.09554e+01 -2.68454e+01 + 593 593 1 -1.74655e+01 2.24200e+01 -7.87545e+00 + 594 594 1 2.36300e+01 -1.40054e+01 2.30000e+01 + 595 595 1 1.08200e+01 3.77000e+00 -1.16554e+01 + 596 596 1 -1.35055e+01 -2.10545e+00 4.95000e+00 + 597 597 1 -3.05655e+01 1.78300e+01 -4.61545e+00 + 598 598 1 -1.23545e+00 -2.85554e+01 -1.36254e+01 + 599 599 1 2.72500e+01 -1.60254e+01 7.30000e+00 + 600 600 1 3.09200e+01 5.50000e+00 -6.47545e+00 + 601 601 1 -1.38455e+01 3.30000e-01 -2.02254e+01 + 602 602 1 2.68100e+01 -2.85954e+01 4.36000e+00 + 603 603 1 -2.45450e-01 2.54800e+01 2.10400e+01 + 604 604 1 -2.80755e+01 -3.34545e+00 1.84000e+01 + 605 605 1 -5.39545e+00 2.30500e+01 1.57800e+01 + 606 606 1 -2.07155e+01 -3.73545e+00 1.53300e+01 + 607 607 1 1.76000e+00 2.72000e+00 6.36000e+00 + 608 608 1 2.62000e+00 -2.62054e+01 -2.20254e+01 + 609 609 1 -3.50545e+00 1.01500e+01 1.85100e+01 + 610 610 1 -5.25545e+00 5.98000e+00 -2.97854e+01 + 611 611 1 1.28200e+01 7.30000e-01 -2.31054e+01 + 612 612 1 -2.39355e+01 2.55900e+01 -1.56654e+01 + 613 613 1 -2.08755e+01 -7.82545e+00 2.61000e+01 + 614 614 1 -7.10545e+00 2.26700e+01 -2.63554e+01 + 615 615 1 3.90000e+00 1.39200e+01 -1.97254e+01 + 616 616 1 -1.54855e+01 7.14000e+00 -2.03545e+00 + 617 617 1 -1.84555e+01 2.95200e+01 -8.85445e-01 + 618 618 1 2.05100e+01 1.95000e+01 -6.02545e+00 + 619 619 1 -1.38055e+01 1.63900e+01 -5.08545e+00 + 620 620 1 -2.94055e+01 -1.93254e+01 -3.06154e+01 + 621 621 1 -1.30655e+01 9.23000e+00 1.84600e+01 + 622 622 1 2.30300e+01 1.45600e+01 -1.08254e+01 + 623 623 1 -1.00555e+01 -1.60545e+00 3.15000e+00 + 624 624 1 -1.58755e+01 -1.29454e+01 4.13000e+00 + 625 625 1 -2.62555e+01 -2.20154e+01 1.29700e+01 + 626 626 1 -1.34545e+00 2.46000e+01 -4.83545e+00 + 627 627 1 -1.29355e+01 3.01200e+01 7.81000e+00 + 628 628 1 1.00600e+01 1.26500e+01 5.26000e+00 + 629 629 1 -1.47255e+01 3.52000e+00 -2.99545e+00 + 630 630 1 5.66000e+00 2.47900e+01 -2.31454e+01 + 631 631 1 2.53900e+01 8.69000e+00 3.24000e+00 + 632 632 1 5.19000e+00 -7.15545e+00 -1.33854e+01 + 633 633 1 -2.68545e+00 2.10500e+01 -2.04954e+01 + 634 634 1 -1.87155e+01 -2.45654e+01 1.92200e+01 + 635 635 1 2.81300e+01 2.16100e+01 1.61800e+01 + 636 636 1 1.21000e+00 7.50000e+00 6.15000e+00 + 637 637 1 -1.67755e+01 -1.76654e+01 2.61600e+01 + 638 638 1 -1.38355e+01 -6.44545e+00 2.39300e+01 + 639 639 1 -2.01555e+01 5.67000e+00 1.24000e+00 + 640 640 1 -1.48155e+01 -9.78545e+00 5.60000e+00 + 641 641 1 1.01800e+01 -1.13954e+01 -1.16954e+01 + 642 642 1 1.79700e+01 1.09100e+01 -2.26654e+01 + 643 643 1 -5.72545e+00 -2.59545e+00 -8.40545e+00 + 644 644 1 1.77200e+01 1.58800e+01 -2.35254e+01 + 645 645 1 -3.48545e+00 -1.54554e+01 1.22200e+01 + 646 646 1 -5.53545e+00 2.99900e+01 -2.73354e+01 + 647 647 1 -2.94455e+01 -1.34545e+00 2.15500e+01 + 648 648 1 9.38000e+00 2.98000e+01 1.61000e+00 + 649 649 1 5.42000e+00 -3.00854e+01 6.68000e+00 + 650 650 1 8.67000e+00 2.33500e+01 1.96200e+01 + 651 651 1 2.31300e+01 7.53000e+00 1.82300e+01 + 652 652 1 2.79900e+01 3.06200e+01 -1.83754e+01 + 653 653 1 1.12500e+01 -3.60545e+00 -1.06854e+01 + 654 654 1 -2.97455e+01 2.35800e+01 -3.00754e+01 + 655 655 1 2.25800e+01 -1.73954e+01 1.30000e-01 + 656 656 1 -1.73955e+01 -2.25454e+01 2.59700e+01 + 657 657 1 -2.61155e+01 -3.06454e+01 1.25200e+01 + 658 658 1 -1.72055e+01 -2.85754e+01 2.18000e+00 + 659 659 1 2.90700e+01 1.95600e+01 7.56000e+00 + 660 660 1 -2.58055e+01 1.37300e+01 8.66000e+00 + 661 661 1 2.49200e+01 2.41000e+00 2.48900e+01 + 662 662 1 -2.18355e+01 3.05300e+01 2.09600e+01 + 663 663 1 -2.47355e+01 3.00300e+01 1.53000e+01 + 664 664 1 2.40400e+01 -2.17954e+01 2.37000e+00 + 665 665 1 2.59500e+01 -1.59754e+01 -2.85454e+01 + 666 666 1 -1.17755e+01 2.06800e+01 2.55000e+01 + 667 667 1 -1.49055e+01 7.41000e+00 1.29000e+01 + 668 668 1 2.95500e+01 -1.49545e+00 -6.22545e+00 + 669 669 1 7.46000e+00 -2.13454e+01 -1.76254e+01 + 670 670 1 -2.96555e+01 2.09200e+01 1.47900e+01 + 671 671 1 -1.65655e+01 2.12300e+01 -1.65545e+00 + 672 672 1 -2.89855e+01 1.87700e+01 -1.71454e+01 + 673 673 1 4.12000e+00 -1.85454e+01 1.96400e+01 + 674 674 1 -3.04755e+01 2.53900e+01 1.27600e+01 + 675 675 1 -2.39355e+01 -3.64545e+00 -2.18954e+01 + 676 676 1 -1.00455e+01 1.44900e+01 -2.21154e+01 + 677 677 1 2.45200e+01 -1.49354e+01 1.07100e+01 + 678 678 1 -2.39855e+01 3.84554e-01 7.77000e+00 + 679 679 1 -2.48545e+00 -1.37654e+01 2.75800e+01 + 680 680 1 -2.63155e+01 -2.60754e+01 6.73000e+00 + 681 681 1 2.33600e+01 -2.46554e+01 1.66700e+01 + 682 682 1 7.46000e+00 2.80700e+01 2.88800e+01 + 683 683 1 -5.25545e+00 3.07300e+01 7.55000e+00 + 684 684 1 -3.80545e+00 3.76000e+00 -4.12545e+00 + 685 685 1 -1.11655e+01 8.13000e+00 2.16600e+01 + 686 686 1 2.17900e+01 1.76700e+01 -2.50954e+01 + 687 687 1 -1.70855e+01 2.98800e+01 -1.71654e+01 + 688 688 1 -7.03545e+00 -9.05446e-01 -1.56254e+01 + 689 689 1 -2.51955e+01 -8.29545e+00 -5.49545e+00 + 690 690 1 2.02700e+01 -2.12554e+01 -2.88154e+01 + 691 691 1 -1.52655e+01 -5.77545e+00 9.77000e+00 + 692 692 1 -2.56545e+00 1.46500e+01 -5.20545e+00 + 693 693 1 -3.03955e+01 -2.04454e+01 1.40800e+01 + 694 694 1 3.30000e+00 1.69800e+01 2.69200e+01 + 695 695 1 1.46900e+01 -2.63754e+01 1.59900e+01 + 696 696 1 -8.65545e+00 -9.62545e+00 1.48700e+01 + 697 697 1 -6.15450e-01 2.33300e+01 -1.61754e+01 + 698 698 1 -8.43545e+00 1.00000e-01 -1.17254e+01 + 699 699 1 4.30000e+00 3.09800e+01 -2.01854e+01 + 700 700 1 1.71700e+01 -1.84545e+00 -3.61545e+00 + 701 701 1 2.92100e+01 -1.00254e+01 -2.25454e+01 + 702 702 1 -3.74545e+00 -3.08354e+01 -1.70954e+01 + 703 703 1 8.03000e+00 5.45000e+00 -1.85545e+00 + 704 704 1 -4.86545e+00 -6.28545e+00 -1.19454e+01 + 705 705 1 2.72300e+01 -1.43545e+00 2.27200e+01 + 706 706 1 -2.45555e+01 -1.85754e+01 2.59000e+01 + 707 707 1 -2.90155e+01 -4.22545e+00 -1.71454e+01 + 708 708 1 -5.39545e+00 1.58400e+01 1.72300e+01 + 709 709 1 3.57000e+00 1.84000e+00 -7.42545e+00 + 710 710 1 -1.52755e+01 -2.71954e+01 -1.42754e+01 + 711 711 1 -4.61545e+00 -2.66454e+01 -8.20545e+00 + 712 712 1 2.75600e+01 2.16700e+01 2.00700e+01 + 713 713 1 -1.33355e+01 8.37000e+00 2.57000e+00 + 714 714 1 2.83400e+01 -2.83454e+01 2.88800e+01 + 715 715 1 2.32100e+01 -1.98754e+01 -9.54545e+00 + 716 716 1 2.03100e+01 5.04000e+00 -2.43654e+01 + 717 717 1 -1.65355e+01 2.64100e+01 -2.33154e+01 + 718 718 1 2.68900e+01 -2.62254e+01 -1.23754e+01 + 719 719 1 -1.35055e+01 3.10600e+01 2.99000e+01 + 720 720 1 2.48400e+01 2.93900e+01 -1.69154e+01 + 721 721 1 -2.08655e+01 -2.48545e+00 -1.31454e+01 + 722 722 1 -1.07655e+01 2.09300e+01 -2.96354e+01 + 723 723 1 2.55400e+01 -3.65545e+00 -1.40545e+00 + 724 724 1 1.48000e+00 2.83100e+01 1.73900e+01 + 725 725 1 3.00000e+00 -5.11545e+00 -2.86754e+01 + 726 726 1 -2.96355e+01 3.10300e+01 -1.82754e+01 + 727 727 1 -7.90545e+00 -1.92754e+01 4.30000e+00 + 728 728 1 -2.88555e+01 1.29200e+01 1.14000e+01 + 729 729 1 -2.32155e+01 -8.52545e+00 1.69800e+01 + 730 730 1 2.15100e+01 -2.88254e+01 -2.88354e+01 + 731 731 1 7.80000e-01 -1.48254e+01 -2.56545e+00 + 732 732 1 9.81000e+00 9.40000e-01 1.91500e+01 + 733 733 1 3.03200e+01 -5.07545e+00 2.99800e+01 + 734 734 1 -2.58955e+01 -2.96454e+01 1.99700e+01 + 735 735 1 -1.06655e+01 -1.31854e+01 9.69000e+00 + 736 736 1 2.73600e+01 2.24600e+01 7.84000e+00 + 737 737 1 5.56000e+00 -2.04454e+01 -2.77854e+01 + 738 738 1 1.06900e+01 2.17300e+01 -9.87545e+00 + 739 739 1 2.46500e+01 2.64200e+01 1.55000e+01 + 740 740 1 -1.05855e+01 3.08500e+01 5.69000e+00 + 741 741 1 -4.13545e+00 -1.61654e+01 -3.07654e+01 + 742 742 1 -2.92545e+00 1.47000e+00 1.48500e+01 + 743 743 1 1.92000e+00 4.17000e+00 3.10000e+00 + 744 744 1 1.22000e+01 -2.02254e+01 3.18000e+00 + 745 745 1 2.19000e+01 -3.03454e+01 -1.52454e+01 + 746 746 1 1.14000e+01 3.05600e+01 -9.02545e+00 + 747 747 1 -9.92545e+00 -6.28545e+00 -2.97754e+01 + 748 748 1 1.63000e+01 1.13500e+01 1.56400e+01 + 749 749 1 -1.75155e+01 -3.00554e+01 -2.44054e+01 + 750 750 1 -2.15455e+01 -6.18545e+00 -1.52054e+01 + 751 751 1 4.49000e+00 6.81000e+00 -2.82654e+01 + 752 752 1 2.74500e+01 -8.52545e+00 9.82000e+00 + 753 753 1 2.99000e+01 -2.36354e+01 -1.90254e+01 + 754 754 1 5.93000e+00 1.31600e+01 3.01700e+01 + 755 755 1 7.90000e-01 -2.71154e+01 -1.67054e+01 + 756 756 1 -5.91545e+00 -2.70554e+01 -3.06354e+01 + 757 757 1 -7.52545e+00 2.10400e+01 -1.77545e+00 + 758 758 1 -1.91455e+01 -3.74545e+00 6.79000e+00 + 759 759 1 -7.91545e+00 -3.90545e+00 -2.67154e+01 + 760 760 1 1.83300e+01 -1.64154e+01 1.82400e+01 + 761 761 1 1.45900e+01 -7.51545e+00 -6.34545e+00 + 762 762 1 7.13000e+00 1.50100e+01 -2.33954e+01 + 763 763 1 -9.00000e-02 2.91200e+01 -1.11154e+01 + 764 764 1 -9.35545e+00 4.60000e-01 2.02600e+01 + 765 765 1 1.95600e+01 -2.82154e+01 -1.45445e-01 + 766 766 1 2.67100e+01 -2.13454e+01 -2.36454e+01 + 767 767 1 2.79000e+01 -6.48545e+00 -8.01545e+00 + 768 768 1 -2.26455e+01 9.89000e+00 -2.26545e+00 + 769 769 1 2.57200e+01 3.03900e+01 1.70100e+01 + 770 770 1 -1.39555e+01 -1.40954e+01 1.21500e+01 + 771 771 1 -1.84545e+00 -2.53854e+01 -3.00654e+01 + 772 772 1 1.67700e+01 -2.17054e+01 4.98000e+00 + 773 773 1 -2.23655e+01 1.90000e+00 1.24555e-01 + 774 774 1 8.11000e+00 -4.54545e+00 2.97200e+01 + 775 775 1 -2.30755e+01 -2.51254e+01 -9.09545e+00 + 776 776 1 -1.89755e+01 -2.03554e+01 -2.62854e+01 + 777 777 1 1.42800e+01 5.69000e+00 1.66100e+01 + 778 778 1 5.75000e+00 -2.22154e+01 -2.47854e+01 + 779 779 1 3.68000e+00 1.92900e+01 5.11000e+00 + 780 780 1 5.02000e+00 -1.63545e+00 -1.43954e+01 + 781 781 1 2.81400e+01 -1.44654e+01 -2.13454e+01 + 782 782 1 -7.80545e+00 -8.52545e+00 -1.54254e+01 + 783 783 1 -5.98545e+00 1.21500e+01 3.39000e+00 + 784 784 1 -2.95455e+01 -9.05545e+00 -2.71354e+01 + 785 785 1 1.67300e+01 9.35000e+00 -1.89654e+01 + 786 786 1 1.34500e+01 -2.69354e+01 -5.72545e+00 + 787 787 1 -7.15450e-01 -2.11854e+01 -1.45054e+01 + 788 788 1 -1.95545e+00 -2.54354e+01 -2.03554e+01 + 789 789 1 1.75600e+01 -9.86545e+00 -6.15445e-01 + 790 790 1 1.76900e+01 2.64000e+00 -1.00954e+01 + 791 791 1 1.61600e+01 -1.85254e+01 -3.68545e+00 + 792 792 1 -8.15450e-01 -2.06854e+01 -3.07354e+01 + 793 793 1 -6.44545e+00 -1.38545e+00 2.09000e+01 + 794 794 1 1.81400e+01 -2.26545e+00 -1.59254e+01 + 795 795 1 -2.27055e+01 -2.51654e+01 1.59400e+01 + 796 796 1 -2.80455e+01 1.37200e+01 -2.06654e+01 + 797 797 1 -1.39055e+01 -3.04154e+01 -1.64054e+01 + 798 798 1 4.95000e+00 -2.37154e+01 1.27000e+00 + 799 799 1 2.04000e+01 -1.30254e+01 1.61000e+01 + 800 800 1 2.22900e+01 -8.35446e-01 1.82900e+01 + 801 801 1 7.38000e+00 -1.75954e+01 1.31000e+01 + 802 802 1 1.78000e+00 5.18000e+00 -1.75654e+01 + 803 803 1 7.60000e+00 -2.95054e+01 -1.84254e+01 + 804 804 1 -1.40755e+01 -2.21545e+00 -1.32854e+01 + 805 805 1 -1.82255e+01 -2.61154e+01 -1.77754e+01 + 806 806 1 2.90900e+01 1.41200e+01 -1.05654e+01 + 807 807 1 -1.21755e+01 -5.92545e+00 4.63000e+00 + 808 808 1 1.95600e+01 -2.08054e+01 8.21000e+00 + 809 809 1 -1.06155e+01 1.07900e+01 -8.48545e+00 + 810 810 1 -3.10155e+01 1.46400e+01 -1.38354e+01 + 811 811 1 -3.08455e+01 -2.07954e+01 3.50000e-01 + 812 812 1 1.41800e+01 -2.23054e+01 1.98800e+01 + 813 813 1 -1.66755e+01 8.61000e+00 3.98000e+00 + 814 814 1 4.64000e+00 1.84100e+01 1.58100e+01 + 815 815 1 2.63500e+01 -2.00454e+01 -8.08545e+00 + 816 816 1 -2.67955e+01 -2.96354e+01 -5.10545e+00 + 817 817 1 -2.87855e+01 2.06300e+01 2.67200e+01 + 818 818 1 1.72600e+01 1.47600e+01 2.11100e+01 + 819 819 1 -1.90955e+01 1.01900e+01 -7.13545e+00 + 820 820 1 1.74700e+01 -2.27954e+01 -2.96354e+01 + 821 821 1 2.04200e+01 1.81700e+01 7.25000e+00 + 822 822 1 2.56100e+01 1.20600e+01 -2.81954e+01 + 823 823 1 -1.22545e+00 -1.17454e+01 1.82400e+01 + 824 824 1 2.46000e+01 5.40000e+00 -1.21545e+00 + 825 825 1 -1.85755e+01 -2.50354e+01 -1.36954e+01 + 826 826 1 -3.05450e-01 1.67500e+01 -2.46954e+01 + 827 827 1 2.71300e+01 2.57100e+01 4.10000e+00 + 828 828 1 3.00500e+01 1.01700e+01 -2.15654e+01 + 829 829 1 -9.69545e+00 2.29900e+01 -9.75545e+00 + 830 830 1 -2.55355e+01 2.33900e+01 5.50000e+00 + 831 831 1 -6.00000e-02 -2.47554e+01 5.73000e+00 + 832 832 1 4.26000e+00 3.25000e+00 -2.06354e+01 + 833 833 1 -2.55555e+01 2.70700e+01 1.94200e+01 + 834 834 1 -1.70955e+01 1.96800e+01 4.74000e+00 + 835 835 1 -2.75450e-01 2.94000e+01 -2.70554e+01 + 836 836 1 1.88900e+01 -5.30545e+00 -1.14545e+00 + 837 837 1 -2.16355e+01 1.87500e+01 2.57300e+01 + 838 838 1 -1.09055e+01 3.08000e+00 1.66200e+01 + 839 839 1 2.32400e+01 6.01000e+00 2.72800e+01 + 840 840 1 -2.73955e+01 -2.33954e+01 -2.11554e+01 + 841 841 1 1.64600e+01 2.05000e+01 -2.98754e+01 + 842 842 1 -2.36855e+01 7.41000e+00 2.58900e+01 + 843 843 1 -1.84855e+01 1.43000e+00 -1.69454e+01 + 844 844 1 -2.99655e+01 7.06000e+00 2.49000e+00 + 845 845 1 9.18000e+00 1.78200e+01 -4.78545e+00 + 846 846 1 2.19100e+01 9.99000e+00 1.01000e+01 + 847 847 1 1.57100e+01 -2.31254e+01 2.71300e+01 + 848 848 1 -2.80000e-01 -2.96954e+01 -3.05854e+01 + 849 849 1 1.59900e+01 1.12900e+01 -6.47545e+00 + 850 850 1 1.05100e+01 2.41300e+01 -1.89554e+01 + 851 851 1 2.11700e+01 7.85000e+00 -1.25854e+01 + 852 852 1 -2.56555e+01 -1.17554e+01 2.18000e+01 + 853 853 1 2.80600e+01 -1.98354e+01 -2.07154e+01 + 854 854 1 1.18700e+01 2.22800e+01 -2.55445e-01 + 855 855 1 -1.34855e+01 7.60000e-01 1.71900e+01 + 856 856 1 1.43600e+01 2.37900e+01 -1.96454e+01 + 857 857 1 -1.97955e+01 2.16100e+01 -2.32254e+01 + 858 858 1 1.41200e+01 1.66900e+01 3.03700e+01 + 859 859 1 -1.79545e+00 -2.90654e+01 -2.35554e+01 + 860 860 1 -1.13255e+01 1.75200e+01 -2.80154e+01 + 861 861 1 -2.88355e+01 2.46000e+01 2.39900e+01 + 862 862 1 1.97600e+01 -6.65545e+00 -7.10545e+00 + 863 863 1 5.09000e+00 -2.69554e+01 2.26100e+01 + 864 864 1 3.20000e-01 5.71000e+00 -2.14154e+01 + 865 865 1 1.68200e+01 9.00000e+00 7.96000e+00 + 866 866 1 2.20500e+01 -2.45854e+01 2.46900e+01 + 867 867 1 2.62200e+01 2.93000e+00 -2.86654e+01 + 868 868 1 1.29700e+01 5.96000e+00 -3.78545e+00 + 869 869 1 -1.24255e+01 -1.23545e+00 -9.95545e+00 + 870 870 1 -2.88545e+00 -1.78154e+01 2.82000e+01 + 871 871 1 1.99700e+01 2.69500e+01 -1.09354e+01 + 872 872 1 2.86700e+01 1.32700e+01 1.89000e+01 + 873 873 1 6.25000e+00 -4.94545e+00 2.54900e+01 + 874 874 1 -1.42255e+01 1.27300e+01 2.09400e+01 + 875 875 1 -8.01545e+00 2.40600e+01 1.49000e+00 + 876 876 1 1.18400e+01 2.80500e+01 1.39200e+01 + 877 877 1 1.32600e+01 -1.15454e+01 1.64800e+01 + 878 878 1 -1.98555e+01 1.07300e+01 2.13700e+01 + 879 879 1 -7.69545e+00 -2.35754e+01 -2.07054e+01 + 880 880 1 -2.34055e+01 -1.46454e+01 5.79000e+00 + 881 881 1 2.70800e+01 -2.36754e+01 4.17000e+00 + 882 882 1 -5.90545e+00 -1.90754e+01 8.67000e+00 + 883 883 1 -2.18055e+01 2.26500e+01 -5.52545e+00 + 884 884 1 2.55800e+01 3.01100e+01 2.81000e+00 + 885 885 1 2.18400e+01 2.24800e+01 3.01600e+01 + 886 886 1 2.83000e+00 -7.92545e+00 1.59000e+00 + 887 887 1 -2.92545e+00 -1.97454e+01 2.52900e+01 + 888 888 1 -6.65450e-01 -4.10545e+00 -6.75445e-01 + 889 889 1 1.63800e+01 1.46300e+01 -1.94654e+01 + 890 890 1 -4.66545e+00 2.16400e+01 -1.36354e+01 + 891 891 1 1.57400e+01 1.32000e+01 7.26000e+00 + 892 892 1 7.34000e+00 2.44100e+01 -2.61054e+01 + 893 893 1 -2.23655e+01 4.46000e+00 1.57900e+01 + 894 894 1 -1.74155e+01 -1.36454e+01 2.11300e+01 + 895 895 1 2.47100e+01 -2.35754e+01 -1.25454e+01 + 896 896 1 -1.39455e+01 1.40100e+01 -1.17554e+01 + 897 897 1 3.20000e+00 2.32900e+01 5.08000e+00 + 898 898 1 -1.32255e+01 3.04000e+01 1.72700e+01 + 899 899 1 -2.27755e+01 7.74000e+00 -9.11545e+00 + 900 900 1 8.29000e+00 1.89400e+01 1.46900e+01 + 901 901 1 2.11800e+01 1.82100e+01 3.03500e+01 + 902 902 1 -1.20055e+01 -1.62254e+01 4.27000e+00 + 903 903 1 -2.01155e+01 1.97800e+01 -1.69754e+01 + 904 904 1 1.26900e+01 -1.53554e+01 1.66100e+01 + 905 905 1 1.52500e+01 -3.04854e+01 2.55500e+01 + 906 906 1 1.04100e+01 -1.88854e+01 -2.32545e+00 + 907 907 1 -8.36545e+00 8.42000e+00 2.07000e+00 + 908 908 1 -2.21055e+01 6.18000e+00 7.89000e+00 + 909 909 1 -2.00055e+01 2.57000e+01 2.60500e+01 + 910 910 1 5.73000e+00 9.65000e+00 -1.30554e+01 + 911 911 1 -2.87155e+01 2.93500e+01 -7.50545e+00 + 912 912 1 -1.70855e+01 -1.41354e+01 -2.04254e+01 + 913 913 1 -8.51545e+00 -2.27054e+01 1.13100e+01 + 914 914 1 -6.12545e+00 5.60000e-01 -2.92354e+01 + 915 915 1 -9.92545e+00 1.07900e+01 1.47500e+01 + 916 916 1 -2.14755e+01 7.70000e-01 -2.56254e+01 + 917 917 1 -2.61655e+01 -6.59545e+00 -1.56454e+01 + 918 918 1 1.69200e+01 -9.54545e+00 7.69000e+00 + 919 919 1 -2.96455e+01 -6.82545e+00 -4.45445e-01 + 920 920 1 7.70000e+00 2.35800e+01 8.64000e+00 + 921 921 1 -1.89355e+01 -2.64854e+01 1.00600e+01 + 922 922 1 8.63000e+00 -4.52545e+00 2.12200e+01 + 923 923 1 1.85200e+01 -2.09354e+01 1.71700e+01 + 924 924 1 -1.05855e+01 1.97000e+00 -1.34954e+01 + 925 925 1 -2.45450e-01 2.50000e+00 1.13500e+01 + 926 926 1 -2.19455e+01 -1.23254e+01 2.26000e+00 + 927 927 1 1.73100e+01 -2.87854e+01 -8.09545e+00 + 928 928 1 -9.80545e+00 -1.91754e+01 -1.96754e+01 + 929 929 1 5.13000e+00 2.59000e+00 -2.63054e+01 + 930 930 1 -1.36055e+01 -3.00545e+00 1.50300e+01 + 931 931 1 2.08000e+00 8.30000e-01 -4.49545e+00 + 932 932 1 -1.18755e+01 -1.92254e+01 1.31500e+01 + 933 933 1 -2.14955e+01 1.59400e+01 2.03500e+01 + 934 934 1 -1.24055e+01 8.16000e+00 -4.96545e+00 + 935 935 1 1.06300e+01 2.54200e+01 2.95600e+01 + 936 936 1 -1.43555e+01 -1.00954e+01 -1.96654e+01 + 937 937 1 2.55700e+01 1.30900e+01 -7.05545e+00 + 938 938 1 -9.40545e+00 1.52300e+01 -1.17754e+01 + 939 939 1 2.07000e+00 -1.80154e+01 2.38400e+01 + 940 940 1 1.35200e+01 1.98300e+01 9.96000e+00 + 941 941 1 1.26000e+01 -2.00545e+00 2.65500e+01 + 942 942 1 1.57800e+01 3.20000e-01 1.49200e+01 + 943 943 1 8.67000e+00 2.64500e+01 2.57800e+01 + 944 944 1 -2.87255e+01 6.67000e+00 -1.01454e+01 + 945 945 1 2.09000e+00 -6.12545e+00 1.28300e+01 + 946 946 1 -1.72055e+01 3.74000e+00 -2.08054e+01 + 947 947 1 7.30000e-01 5.72000e+00 1.05500e+01 + 948 948 1 1.87800e+01 -1.56954e+01 6.46000e+00 + 949 949 1 2.29600e+01 7.80000e+00 1.42500e+01 + 950 950 1 -1.22155e+01 2.73400e+01 -2.88554e+01 + 951 951 1 2.31700e+01 -2.62154e+01 1.19000e+01 + 952 952 1 1.03100e+01 -1.60000e-01 9.87000e+00 + 953 953 1 -1.98255e+01 -2.82954e+01 -1.11754e+01 + 954 954 1 -2.43955e+01 2.30200e+01 1.73300e+01 + 955 955 1 1.25500e+01 2.75200e+01 1.11000e+00 + 956 956 1 -1.93755e+01 -1.81545e+00 2.59900e+01 + 957 957 1 -5.22545e+00 -3.06054e+01 -5.32545e+00 + 958 958 1 2.97700e+01 7.90000e-01 -1.60854e+01 + 959 959 1 2.39500e+01 1.57600e+01 -4.82545e+00 + 960 960 1 -2.60255e+01 -3.23545e+00 -1.64545e+00 + 961 961 1 -1.26955e+01 1.36900e+01 4.35000e+00 + 962 962 1 -2.22855e+01 3.62000e+00 -1.51554e+01 + 963 963 1 2.19700e+01 -1.61654e+01 -1.01954e+01 + 964 964 1 -2.62755e+01 -2.78854e+01 1.59200e+01 + 965 965 1 2.05700e+01 1.65800e+01 2.56000e+00 + 966 966 1 -9.24545e+00 -1.81545e+00 8.19000e+00 + 967 967 1 -1.08355e+01 -1.22454e+01 -1.90554e+01 + 968 968 1 -2.10155e+01 -1.71854e+01 2.33100e+01 + 969 969 1 -4.40545e+00 -1.28545e+00 -2.22354e+01 + 970 970 1 -2.95955e+01 -2.89854e+01 2.22400e+01 + 971 971 1 -1.23545e+00 -1.16854e+01 -8.34545e+00 + 972 972 1 -5.23545e+00 2.34600e+01 -1.72654e+01 + 973 973 1 4.94000e+00 1.87600e+01 2.43200e+01 + 974 974 1 3.38000e+00 -1.51054e+01 -1.41154e+01 + 975 975 1 -1.13545e+00 -7.63545e+00 -2.21454e+01 + 976 976 1 3.03600e+01 -9.91545e+00 2.22000e+01 + 977 977 1 -1.91155e+01 1.56500e+01 1.66300e+01 + 978 978 1 1.80000e-01 -1.22554e+01 -2.78354e+01 + 979 979 1 2.98200e+01 9.37000e+00 -2.63054e+01 + 980 980 1 -2.21055e+01 1.12100e+01 -2.69754e+01 + 981 981 1 -1.97755e+01 2.71200e+01 -1.33354e+01 + 982 982 1 1.85600e+01 1.34200e+01 -2.74954e+01 + 983 983 1 -1.23855e+01 2.49800e+01 -2.42354e+01 + 984 984 1 -3.07055e+01 1.71400e+01 2.51800e+01 + 985 985 1 -4.55545e+00 2.39900e+01 -3.79545e+00 + 986 986 1 1.50800e+01 -4.60545e+00 2.17300e+01 + 987 987 1 2.77000e+00 2.25600e+01 -1.43354e+01 + 988 988 1 1.11500e+01 1.90200e+01 2.17000e+01 + 989 989 1 -1.50955e+01 -2.01254e+01 -2.39954e+01 + 990 990 1 -2.00855e+01 -9.66545e+00 -6.45445e-01 + 991 991 1 -1.12355e+01 -3.49545e+00 -2.59054e+01 + 992 992 1 1.78200e+01 -2.85254e+01 -1.17354e+01 + 993 993 1 1.49400e+01 2.33100e+01 6.58000e+00 + 994 994 1 -1.35755e+01 -2.12554e+01 2.61600e+01 + 995 995 1 -1.43355e+01 1.27500e+01 2.98700e+01 + 996 996 1 7.60000e+00 2.72200e+01 -1.06654e+01 + 997 997 1 1.05800e+01 -1.24545e+00 2.28500e+01 + 998 998 1 -9.75545e+00 -1.28354e+01 -2.62254e+01 + 999 999 1 1.35300e+01 -1.82854e+01 -1.85445e-01 + 1000 1000 1 -2.73255e+01 -9.72545e+00 -1.83654e+01 + 1001 1001 1 -2.62455e+01 2.21000e+00 6.39000e+00 + 1002 1002 1 -1.63055e+01 -2.37854e+01 -2.70754e+01 + 1003 1003 1 -1.53455e+01 1.39600e+01 -2.74654e+01 + 1004 1004 1 -2.53055e+01 -2.03545e+00 -1.12454e+01 + 1005 1005 1 1.17700e+01 -1.07254e+01 -3.07454e+01 + 1006 1006 1 2.68000e+01 -1.58354e+01 -2.09545e+00 + 1007 1007 1 1.25600e+01 2.70700e+01 -1.67654e+01 + 1008 1008 1 -1.61455e+01 -1.69154e+01 -1.00854e+01 + 1009 1009 1 -2.49255e+01 5.11000e+00 1.98500e+01 + 1010 1010 1 -2.36655e+01 -3.90545e+00 2.43500e+01 + 1011 1011 1 2.48800e+01 3.00700e+01 2.03400e+01 + 1012 1012 1 -7.26545e+00 8.69000e+00 -4.91545e+00 + 1013 1013 1 2.09200e+01 -1.20754e+01 7.82000e+00 + 1014 1014 1 -2.99455e+01 1.00200e+01 -1.02054e+01 + 1015 1015 1 -2.55450e-01 1.73300e+01 -7.60545e+00 + 1016 1016 1 -2.06755e+01 -1.50454e+01 1.81000e+01 + 1017 1017 1 3.59000e+00 1.30000e+01 -1.02545e+00 + 1018 1018 1 -2.40255e+01 2.49000e+00 -7.18545e+00 + 1019 1019 1 3.36000e+00 -1.65054e+01 -3.67545e+00 + 1020 1020 1 5.94000e+00 1.08700e+01 2.11000e+01 + 1021 1021 1 -2.57655e+01 -1.58954e+01 -2.13654e+01 + 1022 1022 1 2.23000e+00 -3.17545e+00 1.96000e+01 + 1023 1023 1 1.04000e+01 2.22300e+01 -2.37054e+01 + 1024 1024 1 2.26300e+01 -1.31654e+01 -6.14545e+00 + 1025 1025 1 -1.51055e+01 1.65000e+01 -2.97354e+01 + 1026 1026 1 -2.26855e+01 2.22200e+01 -1.29354e+01 + 1027 1027 1 3.36000e+00 -1.28545e+00 2.29500e+01 + 1028 1028 1 2.56000e+00 2.79200e+01 2.62800e+01 + 1029 1029 1 -4.36545e+00 -2.65854e+01 7.22000e+00 + 1030 1030 1 -2.84545e+00 1.65100e+01 -2.26254e+01 + 1031 1031 1 2.32000e+01 -1.32154e+01 -2.84954e+01 + 1032 1032 1 -8.86545e+00 -2.37545e+00 -2.08954e+01 + 1033 1033 1 -8.97545e+00 1.54400e+01 1.53500e+01 + 1034 1034 1 -6.10545e+00 2.95200e+01 -9.73545e+00 + 1035 1035 1 2.72900e+01 1.09400e+01 -1.93154e+01 + 1036 1036 1 -2.34555e+01 9.18000e+00 2.05800e+01 + 1037 1037 1 2.19700e+01 2.38100e+01 2.61000e+01 + 1038 1038 1 -1.90455e+01 -1.09454e+01 1.64900e+01 + 1039 1039 1 -3.03545e+00 1.71200e+01 9.06000e+00 + 1040 1040 1 1.82500e+01 -1.27354e+01 1.23800e+01 + 1041 1041 1 -2.30545e+00 2.76400e+01 -2.39054e+01 + 1042 1042 1 2.08100e+01 -2.43654e+01 -1.94154e+01 + 1043 1043 1 -8.10545e+00 1.92300e+01 2.09100e+01 + 1044 1044 1 -5.39545e+00 1.39000e+01 1.16600e+01 + 1045 1045 1 1.01600e+01 -1.52854e+01 3.01400e+01 + 1046 1046 1 -2.71355e+01 8.22000e+00 2.57900e+01 + 1047 1047 1 2.96900e+01 -2.41154e+01 -2.46545e+00 + 1048 1048 1 -1.00655e+01 -9.79545e+00 -2.15454e+01 + 1049 1049 1 -3.45450e-01 1.84000e+00 -1.05545e+00 + 1050 1050 1 -1.83955e+01 -6.44545e+00 1.66600e+01 + 1051 1051 1 -8.90545e+00 -1.22854e+01 -1.09545e+00 + 1052 1052 1 1.03000e+01 -9.80545e+00 -2.40254e+01 + 1053 1053 1 -5.98545e+00 -6.05446e-01 3.53000e+00 + 1054 1054 1 -1.29545e+00 -1.17854e+01 -1.91954e+01 + 1055 1055 1 2.24600e+01 -2.43554e+01 4.04000e+00 + 1056 1056 1 2.25700e+01 -1.15254e+01 -1.14854e+01 + 1057 1057 1 2.37700e+01 2.57800e+01 7.02000e+00 + 1058 1058 1 -1.00555e+01 -1.56754e+01 -8.85545e+00 + 1059 1059 1 -1.59455e+01 -4.21545e+00 -8.91545e+00 + 1060 1060 1 -1.47055e+01 -3.00654e+01 -9.45445e-01 + 1061 1061 1 3.35000e+00 3.07100e+01 9.95000e+00 + 1062 1062 1 1.20200e+01 1.68500e+01 7.34000e+00 + 1063 1063 1 1.58800e+01 -1.48354e+01 -2.13354e+01 + 1064 1064 1 -1.31955e+01 -7.00545e+00 -1.86154e+01 + 1065 1065 1 -7.14545e+00 9.28000e+00 1.67900e+01 + 1066 1066 1 9.12000e+00 -1.33754e+01 1.43400e+01 + 1067 1067 1 2.16600e+01 2.71600e+01 -1.82854e+01 + 1068 1068 1 -2.66155e+01 -2.60954e+01 1.99700e+01 + 1069 1069 1 1.76700e+01 -2.89554e+01 1.68700e+01 + 1070 1070 1 2.13200e+01 -1.56545e+00 -2.68754e+01 + 1071 1071 1 -2.15555e+01 1.34300e+01 2.70000e+01 + 1072 1072 1 -1.14155e+01 -7.99545e+00 -1.43545e+00 + 1073 1073 1 -1.17955e+01 2.21800e+01 -4.90545e+00 + 1074 1074 1 2.94500e+01 1.89100e+01 -2.87554e+01 + 1075 1075 1 -2.83255e+01 -4.55446e-01 1.13500e+01 + 1076 1076 1 -2.38655e+01 -8.82545e+00 -9.63545e+00 + 1077 1077 1 2.05700e+01 -3.71545e+00 1.50900e+01 + 1078 1078 1 2.98000e+00 2.13000e+01 2.25900e+01 + 1079 1079 1 -2.91055e+01 -2.59754e+01 -1.70154e+01 + 1080 1080 1 -4.35545e+00 -7.09545e+00 2.29300e+01 + 1081 1081 1 2.75300e+01 7.59000e+00 -1.56754e+01 + 1082 1082 1 -2.56545e+00 1.80100e+01 -1.01954e+01 + 1083 1083 1 -9.68545e+00 -1.66254e+01 -2.83545e+00 + 1084 1084 1 1.85200e+01 -7.94545e+00 2.19600e+01 + 1085 1085 1 -2.00000e-01 2.24100e+01 7.12000e+00 + 1086 1086 1 -6.62545e+00 6.54000e+00 9.47000e+00 + 1087 1087 1 -5.43545e+00 -2.14554e+01 6.49000e+00 + 1088 1088 1 6.29000e+00 3.08100e+01 3.02400e+01 + 1089 1089 1 -2.94955e+01 1.74100e+01 8.89000e+00 + 1090 1090 1 -8.23545e+00 6.58000e+00 1.39400e+01 + 1091 1091 1 -1.35555e+01 2.16600e+01 5.16000e+00 + 1092 1092 1 -9.14545e+00 1.60200e+01 4.40000e-01 + 1093 1093 1 -8.15545e+00 -1.24254e+01 7.25000e+00 + 1094 1094 1 1.40900e+01 1.93500e+01 -2.25854e+01 + 1095 1095 1 9.80000e+00 -3.03454e+01 1.54400e+01 + 1096 1096 1 -8.60545e+00 1.26500e+01 2.68500e+01 + 1097 1097 1 -3.06955e+01 -4.63545e+00 1.50800e+01 + 1098 1098 1 -1.30055e+01 2.63100e+01 -1.96354e+01 + 1099 1099 1 1.82800e+01 2.41200e+01 -1.40354e+01 + 1100 1100 1 5.84000e+00 2.69600e+01 1.57000e+00 + 1101 1101 1 -1.52155e+01 -9.95545e+00 -6.42545e+00 + 1102 1102 1 1.80000e+00 2.09400e+01 -3.26545e+00 + 1103 1103 1 -8.03545e+00 -2.68854e+01 6.96000e+00 + 1104 1104 1 2.96600e+01 -1.03854e+01 6.72000e+00 + 1105 1105 1 2.66600e+01 1.22400e+01 5.26000e+00 + 1106 1106 1 -2.29855e+01 -1.75545e+00 1.18900e+01 + 1107 1107 1 -7.95450e-01 4.65000e+00 -1.40154e+01 + 1108 1108 1 -1.35455e+01 1.87000e+00 -1.66754e+01 + 1109 1109 1 -2.44355e+01 2.45500e+01 1.00700e+01 + 1110 1110 1 -1.95155e+01 1.45600e+01 -2.61954e+01 + 1111 1111 1 -2.09755e+01 2.31300e+01 -2.03654e+01 + 1112 1112 1 -3.06355e+01 -2.77654e+01 2.50000e+01 + 1113 1113 1 -9.68545e+00 -1.50854e+01 2.91400e+01 + 1114 1114 1 -1.53955e+01 -5.63545e+00 -2.35554e+01 + 1115 1115 1 1.47300e+01 -1.57154e+01 2.41200e+01 + 1116 1116 1 -6.91545e+00 9.32000e+00 6.79000e+00 + 1117 1117 1 1.21000e+01 -5.20545e+00 2.04000e+01 + 1118 1118 1 -1.58955e+01 2.15600e+01 -1.78654e+01 + 1119 1119 1 -1.50855e+01 2.90500e+01 -1.32454e+01 + 1120 1120 1 2.35000e+00 -1.46854e+01 -2.41954e+01 + 1121 1121 1 1.15500e+01 -7.48545e+00 3.01200e+01 + 1122 1122 1 -2.68055e+01 1.03000e+01 -1.56054e+01 + 1123 1123 1 2.68200e+01 -7.20545e+00 -2.67054e+01 + 1124 1124 1 -1.02555e+01 -5.85545e+00 -2.32854e+01 + 1125 1125 1 -1.19855e+01 9.60000e-01 2.91200e+01 + 1126 1126 1 1.93000e+00 9.92000e+00 1.07200e+01 + 1127 1127 1 6.47000e+00 -2.91154e+01 -9.32545e+00 + 1128 1128 1 -2.70855e+01 1.60300e+01 4.92000e+00 + 1129 1129 1 -1.09155e+01 -1.70754e+01 2.43600e+01 + 1130 1130 1 -2.20155e+01 1.57900e+01 -2.98545e+00 + 1131 1131 1 6.18000e+00 -2.06545e+00 3.32000e+00 + 1132 1132 1 8.10000e-01 -2.72054e+01 -2.70554e+01 + 1133 1133 1 9.20000e-01 -1.91854e+01 7.30000e-01 + 1134 1134 1 2.53100e+01 -3.12545e+00 -9.90545e+00 + 1135 1135 1 -4.83545e+00 3.03400e+01 1.11200e+01 + 1136 1136 1 -9.66545e+00 -4.44545e+00 2.05100e+01 + 1137 1137 1 -8.25545e+00 2.78900e+01 9.54000e+00 + 1138 1138 1 -3.02255e+01 8.95000e+00 1.79800e+01 + 1139 1139 1 -9.05450e-01 2.78500e+01 -1.60254e+01 + 1140 1140 1 2.01900e+01 -1.76254e+01 -2.33854e+01 + 1141 1141 1 -9.76545e+00 6.95000e+00 1.73800e+01 + 1142 1142 1 -2.16255e+01 -1.05654e+01 -2.90054e+01 + 1143 1143 1 1.81000e+00 -1.70545e+00 -8.16545e+00 + 1144 1144 1 -1.01555e+01 3.94000e+00 2.78000e+00 + 1145 1145 1 -2.09655e+01 -2.69254e+01 5.72000e+00 + 1146 1146 1 -1.45855e+01 -8.55545e+00 3.07700e+01 + 1147 1147 1 1.76400e+01 2.09800e+01 8.76000e+00 + 1148 1148 1 -9.71545e+00 2.40800e+01 -2.04054e+01 + 1149 1149 1 -2.03655e+01 -4.60545e+00 -5.47545e+00 + 1150 1150 1 -1.24545e+00 1.58700e+01 1.73700e+01 + 1151 1151 1 -1.50255e+01 -2.53054e+01 1.11700e+01 + 1152 1152 1 2.66800e+01 9.10000e+00 2.08700e+01 + 1153 1153 1 1.90000e+01 -2.89254e+01 3.09500e+01 + 1154 1154 1 7.07000e+00 -2.37954e+01 -3.81545e+00 + 1155 1155 1 9.82000e+00 4.13000e+00 1.34500e+01 + 1156 1156 1 2.01700e+01 -2.53654e+01 2.88300e+01 + 1157 1157 1 2.50000e+01 -3.96545e+00 2.12300e+01 + 1158 1158 1 2.91900e+01 1.49500e+01 2.74900e+01 + 1159 1159 1 4.15000e+00 -1.30254e+01 -1.76454e+01 + 1160 1160 1 1.40300e+01 2.93200e+01 -2.58754e+01 + 1161 1161 1 -3.40545e+00 2.22600e+01 7.75000e+00 + 1162 1162 1 1.35700e+01 -1.43754e+01 1.32000e+00 + 1163 1163 1 3.07300e+01 -9.04545e+00 1.80700e+01 + 1164 1164 1 4.63000e+00 -1.04154e+01 -3.00954e+01 + 1165 1165 1 -4.78545e+00 8.20000e+00 -1.17054e+01 + 1166 1166 1 -2.87855e+01 2.35000e+00 -2.81554e+01 + 1167 1167 1 -4.12545e+00 -2.72754e+01 -1.05545e+00 + 1168 1168 1 -8.40545e+00 -2.71454e+01 -8.45545e+00 + 1169 1169 1 -6.04545e+00 2.33500e+01 2.28200e+01 + 1170 1170 1 -2.93355e+01 3.67000e+00 9.81000e+00 + 1171 1171 1 -2.73255e+01 -4.35446e-01 2.78900e+01 + 1172 1172 1 -1.07855e+01 -1.55054e+01 1.60900e+01 + 1173 1173 1 -2.40555e+01 -2.96454e+01 2.31700e+01 + 1174 1174 1 2.52700e+01 -1.54154e+01 -1.83754e+01 + 1175 1175 1 -1.99355e+01 1.33500e+01 1.41200e+01 + 1176 1176 1 -1.43755e+01 6.89000e+00 6.60000e+00 + 1177 1177 1 2.97000e+01 -1.23554e+01 -4.87545e+00 + 1178 1178 1 2.16100e+01 1.40000e+01 8.82000e+00 + 1179 1179 1 1.28000e+00 2.95100e+01 -2.22054e+01 + 1180 1180 1 1.64600e+01 -2.85054e+01 -2.52654e+01 + 1181 1181 1 8.26000e+00 -2.49554e+01 -2.28954e+01 + 1182 1182 1 -2.87755e+01 3.27000e+00 2.23800e+01 + 1183 1183 1 -1.45655e+01 2.91300e+01 -5.05545e+00 + 1184 1184 1 -2.24455e+01 3.03500e+01 -1.49754e+01 + 1185 1185 1 -2.41755e+01 -1.34354e+01 -1.07354e+01 + 1186 1186 1 -2.17655e+01 4.17000e+00 -2.49754e+01 + 1187 1187 1 2.64100e+01 -1.12154e+01 1.51000e+01 + 1188 1188 1 1.90600e+01 -1.56654e+01 -8.03545e+00 + 1189 1189 1 -3.03255e+01 5.45000e+00 -1.93654e+01 + 1190 1190 1 -1.24855e+01 -1.19554e+01 2.66900e+01 + 1191 1191 1 1.82600e+01 -1.62354e+01 1.29600e+01 + 1192 1192 1 2.36100e+01 2.55000e+00 -2.15354e+01 + 1193 1193 1 2.24300e+01 -2.74254e+01 -1.22454e+01 + 1194 1194 1 2.09000e+00 -8.95446e-01 1.01900e+01 + 1195 1195 1 2.50900e+01 3.08900e+01 -9.69545e+00 + 1196 1196 1 3.90000e-01 2.11100e+01 -7.11545e+00 + 1197 1197 1 -7.51545e+00 5.62000e+00 5.75000e+00 + 1198 1198 1 -1.05355e+01 -2.71054e+01 -5.46545e+00 + 1199 1199 1 1.17700e+01 2.64400e+01 1.76800e+01 + 1200 1200 1 1.45700e+01 2.40600e+01 1.23900e+01 + 1201 1201 1 2.74300e+01 -1.06954e+01 -1.88554e+01 + 1202 1202 1 -3.06355e+01 -2.31554e+01 2.87000e+00 + 1203 1203 1 -1.75855e+01 -1.78545e+00 1.82700e+01 + 1204 1204 1 1.64900e+01 1.16000e+01 -2.45445e-01 + 1205 1205 1 -3.00055e+01 5.86000e+00 7.13000e+00 + 1206 1206 1 8.50000e-01 1.08300e+01 -4.04545e+00 + 1207 1207 1 1.49800e+01 -1.22654e+01 4.13000e+00 + 1208 1208 1 -3.05555e+01 -2.14554e+01 2.91700e+01 + 1209 1209 1 -3.04455e+01 2.29500e+01 1.58000e+00 + 1210 1210 1 -4.17545e+00 -7.76545e+00 2.85500e+01 + 1211 1211 1 2.73600e+01 -2.28154e+01 3.01200e+01 + 1212 1212 1 -1.46655e+01 8.46000e+00 -8.55545e+00 + 1213 1213 1 -2.76355e+01 2.95200e+01 1.80000e+00 + 1214 1214 1 -7.43545e+00 1.79300e+01 6.63000e+00 + 1215 1215 1 1.25000e+01 7.50000e+00 -2.59954e+01 + 1216 1216 1 2.33100e+01 3.07300e+01 -2.62454e+01 + 1217 1217 1 2.35500e+01 1.85100e+01 4.60000e-01 + 1218 1218 1 2.40800e+01 1.52700e+01 2.36400e+01 + 1219 1219 1 -2.29455e+01 1.75300e+01 -2.68954e+01 + 1220 1220 1 -1.03755e+01 2.62100e+01 -1.71654e+01 + 1221 1221 1 -1.09455e+01 1.91200e+01 -4.40545e+00 + 1222 1222 1 2.29100e+01 1.17000e+01 -3.07554e+01 + 1223 1223 1 -1.93955e+01 -4.83545e+00 1.91400e+01 + 1224 1224 1 2.35800e+01 -1.17554e+01 -2.14154e+01 + 1225 1225 1 1.89600e+01 -1.31545e+00 2.81100e+01 + 1226 1226 1 1.84700e+01 9.87000e+00 -2.68954e+01 + 1227 1227 1 -7.63545e+00 2.01400e+01 1.05700e+01 + 1228 1228 1 2.05500e+01 -1.89654e+01 1.49900e+01 + 1229 1229 1 2.50800e+01 2.00200e+01 -3.09154e+01 + 1230 1230 1 -2.55055e+01 -2.91554e+01 -1.80054e+01 + 1231 1231 1 -2.60555e+01 2.04900e+01 1.19800e+01 + 1232 1232 1 8.69000e+00 6.50000e-01 -6.15445e-01 + 1233 1233 1 -3.04355e+01 2.12800e+01 1.07800e+01 + 1234 1234 1 -8.75450e-01 -1.57454e+01 1.69400e+01 + 1235 1235 1 2.31500e+01 2.55500e+01 -3.03854e+01 + 1236 1236 1 -2.64355e+01 -4.92545e+00 2.79000e+01 + 1237 1237 1 -3.10555e+01 -3.05254e+01 2.99500e+01 + 1238 1238 1 7.28000e+00 -1.03954e+01 1.96000e+00 + 1239 1239 1 1.31600e+01 3.08000e+01 2.88100e+01 + 1240 1240 1 8.43000e+00 1.37400e+01 2.37000e+01 + 1241 1241 1 -2.45655e+01 -2.82254e+01 -1.38054e+01 + 1242 1242 1 2.23500e+01 1.20400e+01 -2.52154e+01 + 1243 1243 1 -1.13055e+01 2.94700e+01 -2.34554e+01 + 1244 1244 1 1.42000e+01 1.84700e+01 -3.98545e+00 + 1245 1245 1 -2.57455e+01 1.20800e+01 2.46700e+01 + 1246 1246 1 -2.54545e+00 1.07400e+01 -1.06654e+01 + 1247 1247 1 1.30000e+00 -9.58545e+00 9.84000e+00 + 1248 1248 1 -2.05450e-01 8.12000e+00 1.78300e+01 + 1249 1249 1 1.82400e+01 -5.30545e+00 2.98900e+01 + 1250 1250 1 8.80000e+00 -5.03545e+00 -1.25254e+01 + 1251 1251 1 -8.12545e+00 2.29100e+01 6.17000e+00 + 1252 1252 1 -1.43955e+01 -1.83454e+01 1.56700e+01 + 1253 1253 1 1.54550e-01 4.05000e+00 2.83800e+01 + 1254 1254 1 -1.01755e+01 1.48800e+01 -1.84254e+01 + 1255 1255 1 -3.01955e+01 1.21900e+01 2.75400e+01 + 1256 1256 1 -2.24155e+01 -2.04054e+01 1.07400e+01 + 1257 1257 1 -7.95450e-01 7.63000e+00 -2.43154e+01 + 1258 1258 1 7.49000e+00 1.42800e+01 -1.17254e+01 + 1259 1259 1 2.67800e+01 -2.37454e+01 -5.73545e+00 + 1260 1260 1 -1.73455e+01 2.41000e+00 1.87500e+01 + 1261 1261 1 1.66700e+01 5.47000e+00 -7.55445e-01 + 1262 1262 1 -6.52545e+00 9.75000e+00 -2.09554e+01 + 1263 1263 1 1.55400e+01 -2.70554e+01 3.27000e+00 + 1264 1264 1 2.31100e+01 6.80000e-01 3.87000e+00 + 1265 1265 1 3.03400e+01 6.25000e+00 -2.31354e+01 + 1266 1266 1 -1.78655e+01 2.25700e+01 1.35500e+01 + 1267 1267 1 -2.65755e+01 -1.62554e+01 -1.13154e+01 + 1268 1268 1 -2.25455e+01 1.12200e+01 -7.16545e+00 + 1269 1269 1 -2.87155e+01 2.26100e+01 -2.44954e+01 + 1270 1270 1 -7.82545e+00 -2.82754e+01 1.84100e+01 + 1271 1271 1 -2.50055e+01 2.50000e-01 3.08200e+01 + 1272 1272 1 2.83200e+01 -4.15545e+00 -1.56354e+01 + 1273 1273 1 -2.44155e+01 2.09200e+01 3.29000e+00 + 1274 1274 1 -2.12545e+00 2.61000e+00 2.84000e+00 + 1275 1275 1 2.50800e+01 2.72000e+01 -3.26545e+00 + 1276 1276 1 6.85000e+00 2.26400e+01 1.57300e+01 + 1277 1277 1 1.83500e+01 -1.60454e+01 2.84400e+01 + 1278 1278 1 1.68000e+00 -2.44854e+01 -2.49854e+01 + 1279 1279 1 -8.83545e+00 4.42000e+00 -2.40354e+01 + 1280 1280 1 5.50000e+00 1.74000e+00 1.85500e+01 + 1281 1281 1 1.48400e+01 -4.32545e+00 1.73000e+01 + 1282 1282 1 -1.45955e+01 9.93000e+00 -2.15554e+01 + 1283 1283 1 8.01000e+00 -3.74545e+00 -1.56954e+01 + 1284 1284 1 3.06600e+01 2.03500e+01 2.24900e+01 + 1285 1285 1 -7.10545e+00 1.06700e+01 2.35400e+01 + 1286 1286 1 -2.15455e+01 -1.65054e+01 -4.38545e+00 + 1287 1287 1 1.11100e+01 -2.09954e+01 2.81300e+01 + 1288 1288 1 -1.97255e+01 -1.16654e+01 -1.24654e+01 + 1289 1289 1 2.62000e+01 9.76000e+00 -1.32154e+01 + 1290 1290 1 -1.73545e+00 5.58000e+00 -9.53545e+00 + 1291 1291 1 2.91000e+01 -2.55254e+01 1.65000e+00 + 1292 1292 1 -2.10855e+01 -1.08154e+01 -1.64154e+01 + 1293 1293 1 -1.22055e+01 2.74200e+01 1.55300e+01 + 1294 1294 1 1.92600e+01 1.97500e+01 1.65400e+01 + 1295 1295 1 -1.12255e+01 -1.49154e+01 -3.00154e+01 + 1296 1296 1 -8.70545e+00 -1.87754e+01 2.60700e+01 + 1297 1297 1 -2.77955e+01 2.73700e+01 1.16300e+01 + 1298 1298 1 -8.67545e+00 -2.86154e+01 9.80000e+00 + 1299 1299 1 2.06200e+01 -1.66545e+00 -5.23545e+00 + 1300 1300 1 6.88000e+00 -2.02554e+01 1.68800e+01 + 1301 1301 1 -7.88545e+00 2.10800e+01 -1.85154e+01 + 1302 1302 1 1.15500e+01 1.84300e+01 1.21700e+01 + 1303 1303 1 -1.55255e+01 3.67000e+00 2.86100e+01 + 1304 1304 1 1.34100e+01 -7.45545e+00 1.40100e+01 + 1305 1305 1 -2.78855e+01 1.95600e+01 2.06200e+01 + 1306 1306 1 2.93000e+00 2.05100e+01 9.99000e+00 + 1307 1307 1 2.38000e+01 -2.87254e+01 2.34600e+01 + 1308 1308 1 -1.98255e+01 -6.64545e+00 -1.80954e+01 + 1309 1309 1 -1.68545e+00 -4.41545e+00 -1.97854e+01 + 1310 1310 1 1.00900e+01 1.72800e+01 -1.37545e+00 + 1311 1311 1 4.50000e+00 1.21600e+01 1.72500e+01 + 1312 1312 1 -2.96055e+01 -7.49545e+00 -5.04545e+00 + 1313 1313 1 -4.00000e-02 -1.02054e+01 4.04555e-01 + 1314 1314 1 -2.60545e+00 -2.91554e+01 -2.68854e+01 + 1315 1315 1 1.46600e+01 4.32000e+00 -2.52954e+01 + 1316 1316 1 -8.85450e-01 3.00600e+01 2.73800e+01 + 1317 1317 1 -4.71545e+00 -2.15754e+01 1.78400e+01 + 1318 1318 1 1.87700e+01 1.60600e+01 -1.37554e+01 + 1319 1319 1 2.86800e+01 -1.42954e+01 -2.97854e+01 + 1320 1320 1 -2.41355e+01 -1.40000e-01 -2.20854e+01 + 1321 1321 1 2.70000e+01 -3.08354e+01 2.40000e+01 + 1322 1322 1 5.53000e+00 2.84800e+01 8.47000e+00 + 1323 1323 1 1.92400e+01 -2.68154e+01 5.05000e+00 + 1324 1324 1 -1.00855e+01 8.16000e+00 -1.23254e+01 + 1325 1325 1 -1.67255e+01 1.58400e+01 -1.65254e+01 + 1326 1326 1 -1.14855e+01 -1.41554e+01 2.04555e-01 + 1327 1327 1 -2.57355e+01 2.68000e+00 -1.80454e+01 + 1328 1328 1 1.54600e+01 -1.10545e+00 2.28800e+01 + 1329 1329 1 -2.01545e+00 2.45543e-02 9.87000e+00 + 1330 1330 1 -5.73545e+00 1.60200e+01 1.00000e+00 + 1331 1331 1 -2.17255e+01 -1.65054e+01 2.93900e+01 + 1332 1332 1 9.11000e+00 9.02000e+00 -1.73754e+01 + 1333 1333 1 1.94000e+01 -2.29454e+01 3.30000e+00 + 1334 1334 1 -2.68055e+01 -2.85454e+01 4.70000e-01 + 1335 1335 1 -2.23255e+01 3.60000e+00 5.51000e+00 + 1336 1336 1 -2.68545e+00 -6.08545e+00 -2.61554e+01 + 1337 1337 1 1.82200e+01 -2.44354e+01 2.11700e+01 + 1338 1338 1 -2.52855e+01 4.91000e+00 -2.98054e+01 + 1339 1339 1 -5.54502e-02 -1.61554e+01 -7.07545e+00 + 1340 1340 1 -9.59545e+00 -6.91545e+00 1.68700e+01 + 1341 1341 1 8.53000e+00 -1.81554e+01 -2.45854e+01 + 1342 1342 1 -1.65855e+01 1.83100e+01 -2.55554e+01 + 1343 1343 1 -6.75450e-01 1.21800e+01 2.05600e+01 + 1344 1344 1 -2.00555e+01 2.84800e+01 1.59600e+01 + 1345 1345 1 -1.37155e+01 -4.76545e+00 -2.87254e+01 + 1346 1346 1 2.24100e+01 2.80000e+01 -6.95545e+00 + 1347 1347 1 1.02300e+01 2.56500e+01 1.18700e+01 + 1348 1348 1 2.48000e+00 -2.16054e+01 -2.21254e+01 + 1349 1349 1 1.07000e+00 -3.03254e+01 2.18300e+01 + 1350 1350 1 -8.84545e+00 -2.36354e+01 -7.66545e+00 + 1351 1351 1 2.82700e+01 2.10900e+01 2.87000e+00 + 1352 1352 1 -7.27545e+00 -1.47545e+00 2.85700e+01 + 1353 1353 1 2.51400e+01 -2.30054e+01 -1.99354e+01 + 1354 1354 1 2.86400e+01 -2.08754e+01 -1.24754e+01 + 1355 1355 1 2.77500e+01 2.50300e+01 -6.24545e+00 + 1356 1356 1 1.76700e+01 2.62000e+00 1.11100e+01 + 1357 1357 1 -3.89545e+00 -2.50554e+01 -1.63454e+01 + 1358 1358 1 2.25700e+01 2.63000e+01 -5.55445e-01 + 1359 1359 1 3.28000e+00 -1.79554e+01 -2.42454e+01 + 1360 1360 1 -2.11555e+01 9.32000e+00 1.47800e+01 + 1361 1361 1 1.29600e+01 7.30000e-01 2.65000e+00 + 1362 1362 1 3.62000e+00 3.75000e+00 2.84900e+01 + 1363 1363 1 -2.78545e+00 -1.18154e+01 2.25000e+01 + 1364 1364 1 1.62500e+01 -2.71754e+01 -3.28545e+00 + 1365 1365 1 1.52200e+01 4.35000e+00 1.24400e+01 + 1366 1366 1 -2.30255e+01 2.09100e+01 2.08600e+01 + 1367 1367 1 2.50100e+01 -1.61654e+01 -7.28545e+00 + 1368 1368 1 1.02200e+01 2.32300e+01 2.33900e+01 + 1369 1369 1 4.18000e+00 -1.85854e+01 -2.06954e+01 + 1370 1370 1 -1.20555e+01 -1.84854e+01 2.90300e+01 + 1371 1371 1 -1.29755e+01 1.50000e+00 8.78000e+00 + 1372 1372 1 -2.24555e+01 2.90200e+01 -6.40545e+00 + 1373 1373 1 -2.56155e+01 1.86300e+01 1.62300e+01 + 1374 1374 1 3.05000e+01 4.09000e+00 1.28100e+01 + 1375 1375 1 -3.05955e+01 -2.56554e+01 8.23000e+00 + 1376 1376 1 1.52900e+01 -2.37654e+01 1.41500e+01 + 1377 1377 1 -7.61545e+00 -1.86754e+01 -3.04754e+01 + 1378 1378 1 -5.24545e+00 -5.01545e+00 -1.49454e+01 + 1379 1379 1 2.32500e+01 -5.39545e+00 -2.61554e+01 + 1380 1380 1 1.54900e+01 -8.66545e+00 -3.08854e+01 + 1381 1381 1 -2.93455e+01 1.23000e+00 -1.76754e+01 + 1382 1382 1 -2.66355e+01 2.40700e+01 -4.80545e+00 + 1383 1383 1 -1.67545e+00 2.76000e+01 -2.96754e+01 + 1384 1384 1 7.36000e+00 -2.52454e+01 1.53300e+01 + 1385 1385 1 -3.05155e+01 -1.02754e+01 -2.40000e-01 + 1386 1386 1 1.41000e+00 1.22500e+01 -3.07354e+01 + 1387 1387 1 8.98000e+00 5.26000e+00 -1.91954e+01 + 1388 1388 1 -2.44155e+01 -2.34854e+01 -2.40854e+01 + 1389 1389 1 1.58600e+01 -1.29154e+01 1.99500e+01 + 1390 1390 1 -1.16155e+01 -2.14054e+01 3.08900e+01 + 1391 1391 1 1.64000e+00 -5.25446e-01 -2.91654e+01 + 1392 1392 1 -1.77155e+01 -2.02545e+00 -2.80545e+00 + 1393 1393 1 1.56700e+01 2.98800e+01 1.19000e+01 + 1394 1394 1 -2.85055e+01 -2.77854e+01 -1.35854e+01 + 1395 1395 1 -5.99545e+00 -2.12254e+01 2.82500e+01 + 1396 1396 1 -1.14755e+01 -2.07454e+01 -1.72254e+01 + 1397 1397 1 -1.83755e+01 -2.65054e+01 -2.68854e+01 + 1398 1398 1 -5.75545e+00 2.25800e+01 -9.33545e+00 + 1399 1399 1 1.88600e+01 2.96600e+01 -1.55954e+01 + 1400 1400 1 7.17000e+00 1.58900e+01 -8.83545e+00 + 1401 1401 1 1.85000e+01 -2.96854e+01 9.04000e+00 + 1402 1402 1 -2.46955e+01 -8.65545e+00 2.26500e+01 + 1403 1403 1 -1.50155e+01 3.49000e+00 -2.47354e+01 + 1404 1404 1 1.59600e+01 -1.99054e+01 -2.29454e+01 + 1405 1405 1 -1.52655e+01 -2.72754e+01 -1.95254e+01 + 1406 1406 1 2.81400e+01 -6.78545e+00 -1.79254e+01 + 1407 1407 1 1.13500e+01 -2.52354e+01 2.80900e+01 + 1408 1408 1 2.43400e+01 1.78400e+01 -1.58454e+01 + 1409 1409 1 4.11000e+00 5.12000e+00 -9.44545e+00 + 1410 1410 1 -2.84455e+01 -2.36254e+01 2.51800e+01 + 1411 1411 1 -6.58545e+00 -5.48545e+00 1.04300e+01 + 1412 1412 1 2.46000e+01 -1.86654e+01 -1.22554e+01 + 1413 1413 1 1.96800e+01 1.02000e+00 -2.29354e+01 + 1414 1414 1 1.58000e+01 3.21000e+00 -1.33954e+01 + 1415 1415 1 -2.54855e+01 1.72800e+01 2.10800e+01 + 1416 1416 1 -8.96545e+00 -1.12854e+01 -1.20654e+01 + 1417 1417 1 -2.55855e+01 2.90500e+01 -1.07754e+01 + 1418 1418 1 6.82000e+00 -5.76545e+00 3.40000e+00 + 1419 1419 1 1.19700e+01 2.27900e+01 1.53600e+01 + 1420 1420 1 -2.71455e+01 -2.21054e+01 -7.87545e+00 + 1421 1421 1 -2.35055e+01 -2.62354e+01 -2.71954e+01 + 1422 1422 1 -3.15450e-01 -1.59654e+01 2.18700e+01 + 1423 1423 1 -2.15545e+00 1.36000e+00 2.51500e+01 + 1424 1424 1 2.95000e+01 5.83000e+00 3.06900e+01 + 1425 1425 1 -2.77955e+01 -7.22545e+00 1.81400e+01 + 1426 1426 1 5.66000e+00 1.03200e+01 4.93000e+00 + 1427 1427 1 -1.17955e+01 2.91900e+01 1.12900e+01 + 1428 1428 1 3.03400e+01 1.56600e+01 6.13000e+00 + 1429 1429 1 4.76000e+00 1.50000e+00 -3.09354e+01 + 1430 1430 1 -2.98055e+01 3.84000e+00 3.08000e+00 + 1431 1431 1 2.81000e+01 1.01000e+00 -2.16454e+01 + 1432 1432 1 8.44000e+00 -2.26554e+01 7.18000e+00 + 1433 1433 1 -1.92255e+01 1.91800e+01 -1.38354e+01 + 1434 1434 1 -2.72545e+00 3.76000e+00 6.15000e+00 + 1435 1435 1 -5.31545e+00 -6.36545e+00 1.79200e+01 + 1436 1436 1 -1.65855e+01 -1.03854e+01 -1.60654e+01 + 1437 1437 1 -8.48545e+00 -2.06554e+01 1.59800e+01 + 1438 1438 1 9.08000e+00 -1.06054e+01 -1.71754e+01 + 1439 1439 1 -2.77655e+01 3.05000e+00 -4.41545e+00 + 1440 1440 1 -2.73855e+01 -1.84854e+01 2.10200e+01 + 1441 1441 1 2.11700e+01 1.71900e+01 2.03200e+01 + 1442 1442 1 -2.85455e+01 -1.29354e+01 5.20000e-01 + 1443 1443 1 9.27000e+00 4.44000e+00 2.38000e+00 + 1444 1444 1 2.99100e+01 -2.52254e+01 1.20600e+01 + 1445 1445 1 1.07800e+01 5.29000e+00 -2.39254e+01 + 1446 1446 1 -2.69655e+01 -4.26545e+00 -1.37154e+01 + 1447 1447 1 -1.88555e+01 -2.78754e+01 1.63800e+01 + 1448 1448 1 2.68300e+01 1.41100e+01 -4.10545e+00 + 1449 1449 1 -2.54655e+01 8.94000e+00 1.65800e+01 + 1450 1450 1 2.57000e+01 2.98000e+00 -1.72354e+01 + 1451 1451 1 1.63900e+01 1.26200e+01 2.63700e+01 + 1452 1452 1 1.80000e+01 -3.35545e+00 -1.94054e+01 + 1453 1453 1 -1.36755e+01 1.11600e+01 1.02400e+01 + 1454 1454 1 -2.18755e+01 8.11000e+00 3.74000e+00 + 1455 1455 1 -1.13355e+01 -3.07854e+01 2.62500e+01 + 1456 1456 1 2.85100e+01 -1.07054e+01 -1.50454e+01 + 1457 1457 1 -2.42455e+01 -1.50054e+01 9.99000e+00 + 1458 1458 1 2.29400e+01 -1.85754e+01 5.08000e+00 + 1459 1459 1 2.79000e+00 1.87000e+00 -1.52654e+01 + 1460 1460 1 8.59000e+00 2.16100e+01 -1.11545e+00 + 1461 1461 1 3.06400e+01 1.56000e+01 -2.82754e+01 + 1462 1462 1 2.90200e+01 4.76000e+00 -1.55054e+01 + 1463 1463 1 -2.68655e+01 3.05500e+01 7.44000e+00 + 1464 1464 1 -2.80055e+01 -2.97654e+01 2.77000e+01 + 1465 1465 1 -3.89545e+00 -1.19154e+01 8.57000e+00 + 1466 1466 1 -1.93255e+01 -5.51545e+00 -2.19454e+01 + 1467 1467 1 -2.81355e+01 1.08600e+01 8.30000e-01 + 1468 1468 1 3.08600e+01 -9.65446e-01 4.12000e+00 + 1469 1469 1 1.21700e+01 -4.20545e+00 1.78000e+00 + 1470 1470 1 -1.26155e+01 -1.33354e+01 6.65000e+00 + 1471 1471 1 -2.58255e+01 -2.85446e-01 -2.59554e+01 + 1472 1472 1 2.11200e+01 -3.52545e+00 -2.31454e+01 + 1473 1473 1 3.10100e+01 -2.64654e+01 -2.11554e+01 + 1474 1474 1 -3.07455e+01 -1.61954e+01 -2.99354e+01 + 1475 1475 1 -2.30155e+01 -2.37554e+01 4.54000e+00 + 1476 1476 1 -7.23545e+00 -1.50854e+01 2.84000e+00 + 1477 1477 1 -1.31455e+01 -4.22545e+00 1.47000e+00 + 1478 1478 1 2.54000e+00 -1.49754e+01 2.18000e+00 + 1479 1479 1 1.93800e+01 -4.28545e+00 2.47900e+01 + 1480 1480 1 -6.91545e+00 -1.81154e+01 -8.33545e+00 + 1481 1481 1 2.33800e+01 1.22000e+00 2.12200e+01 + 1482 1482 1 2.05800e+01 -1.87154e+01 -6.41545e+00 + 1483 1483 1 -2.41455e+01 -1.60654e+01 1.88000e+00 + 1484 1484 1 3.01700e+01 6.60000e-01 2.89300e+01 + 1485 1485 1 1.28400e+01 -1.17545e+00 1.81700e+01 + 1486 1486 1 -2.60555e+01 2.76000e+00 -2.46454e+01 + 1487 1487 1 -2.97655e+01 2.22000e+01 -1.39354e+01 + 1488 1488 1 1.58100e+01 -6.28545e+00 -1.80654e+01 + 1489 1489 1 1.60700e+01 -1.10554e+01 -1.97354e+01 + 1490 1490 1 6.40000e+00 -2.41054e+01 1.90600e+01 + 1491 1491 1 -1.89555e+01 1.25300e+01 -3.85545e+00 + 1492 1492 1 1.75800e+01 -2.83154e+01 -1.87654e+01 + 1493 1493 1 -2.08755e+01 -2.32854e+01 -1.21754e+01 + 1494 1494 1 5.58000e+00 2.48700e+01 -1.92554e+01 + 1495 1495 1 1.69200e+01 8.12000e+00 2.30200e+01 + 1496 1496 1 -2.92855e+01 -1.69854e+01 -1.30545e+00 + 1497 1497 1 -1.79355e+01 -1.59954e+01 3.01700e+01 + 1498 1498 1 2.72000e+01 1.58000e+00 1.43700e+01 + 1499 1499 1 -1.02555e+01 -2.76654e+01 -1.96654e+01 + 1500 1500 1 1.85700e+01 5.66000e+00 -9.36545e+00 + 1501 1501 1 1.65900e+01 -1.92654e+01 2.48700e+01 + 1502 1502 1 -2.51455e+01 2.89500e+01 -2.78754e+01 + 1503 1503 1 2.94400e+01 -3.07554e+01 2.04300e+01 + 1504 1504 1 -1.79255e+01 -2.11954e+01 1.23600e+01 + 1505 1505 1 1.75700e+01 1.38300e+01 -3.63545e+00 + 1506 1506 1 1.13700e+01 2.15200e+01 -3.89545e+00 + 1507 1507 1 1.87000e+00 1.23200e+01 -1.58554e+01 + 1508 1508 1 3.08200e+01 2.98000e+01 -2.49154e+01 + 1509 1509 1 -2.88545e+00 -2.08454e+01 -1.77854e+01 + 1510 1510 1 1.08800e+01 -8.35446e-01 -7.86545e+00 + 1511 1511 1 -5.21545e+00 -2.56154e+01 -1.21754e+01 + 1512 1512 1 -4.67545e+00 3.07900e+01 -1.38254e+01 + 1513 1513 1 -1.64455e+01 6.80000e-01 1.38100e+01 + 1514 1514 1 5.68000e+00 -1.29254e+01 -2.46754e+01 + 1515 1515 1 -4.96545e+00 -2.91054e+01 1.56600e+01 + 1516 1516 1 6.77000e+00 4.10000e-01 -4.15545e+00 + 1517 1517 1 4.76000e+00 2.04000e+00 1.24200e+01 + 1518 1518 1 2.79800e+01 8.84000e+00 2.44000e+01 + 1519 1519 1 -1.38855e+01 2.35500e+01 -3.09554e+01 + 1520 1520 1 2.18300e+01 1.30700e+01 -3.72545e+00 + 1521 1521 1 -2.79555e+01 -1.13154e+01 -2.42154e+01 + 1522 1522 1 2.06000e+01 2.88200e+01 1.49900e+01 + 1523 1523 1 2.38100e+01 -1.20054e+01 -2.90545e+00 + 1524 1524 1 -1.47655e+01 2.92600e+01 2.69500e+01 + 1525 1525 1 1.49600e+01 1.57400e+01 -1.20954e+01 + 1526 1526 1 -1.12555e+01 -2.66054e+01 -1.04545e+00 + 1527 1527 1 7.90000e-01 4.46000e+00 1.45900e+01 + 1528 1528 1 1.45400e+01 -1.87154e+01 6.87000e+00 + 1529 1529 1 -3.04155e+01 -1.64854e+01 -1.95454e+01 + 1530 1530 1 8.22000e+00 7.55000e+00 -2.76754e+01 + 1531 1531 1 1.25200e+01 -8.13545e+00 -2.74154e+01 + 1532 1532 1 -7.49545e+00 -1.35054e+01 1.53200e+01 + 1533 1533 1 2.27200e+01 -9.25545e+00 -2.45754e+01 + 1534 1534 1 -4.53545e+00 2.77400e+01 1.33200e+01 + 1535 1535 1 -1.54655e+01 1.99700e+01 -2.09454e+01 + 1536 1536 1 2.48000e+01 3.04100e+01 -2.17154e+01 + 1537 1537 1 -2.87055e+01 -6.18545e+00 1.00500e+01 + 1538 1538 1 1.12900e+01 -1.90454e+01 1.90300e+01 + 1539 1539 1 -3.06455e+01 -2.83545e+00 -1.44545e+00 + 1540 1540 1 1.51500e+01 2.34800e+01 -2.37854e+01 + 1541 1541 1 -2.08545e+00 -8.29545e+00 -3.08545e+00 + 1542 1542 1 1.73900e+01 -1.90545e+00 -2.46154e+01 + 1543 1543 1 -2.77055e+01 9.11000e+00 -2.80854e+01 + 1544 1544 1 2.66600e+01 2.45543e-02 6.20000e-01 + 1545 1545 1 -2.72655e+01 -8.48545e+00 2.61300e+01 + 1546 1546 1 -1.34555e+01 -2.83554e+01 1.05900e+01 + 1547 1547 1 -2.00000e-01 -6.89545e+00 4.35000e+00 + 1548 1548 1 -9.25450e-01 -8.54457e-02 -4.14545e+00 + 1549 1549 1 1.75200e+01 2.65900e+01 1.41100e+01 + 1550 1550 1 3.03000e+01 1.00700e+01 2.05800e+01 + 1551 1551 1 -1.91655e+01 8.91000e+00 -2.45154e+01 + 1552 1552 1 -2.31255e+01 -9.17545e+00 2.97100e+01 + 1553 1553 1 1.08100e+01 1.95400e+01 3.43000e+00 + 1554 1554 1 2.20800e+01 -9.46545e+00 -6.60545e+00 + 1555 1555 1 2.31300e+01 4.44000e+00 -2.96554e+01 + 1556 1556 1 -1.89655e+01 -8.46545e+00 6.72000e+00 + 1557 1557 1 4.94000e+00 6.56000e+00 -1.76054e+01 + 1558 1558 1 1.71100e+01 7.20000e-01 -2.68054e+01 + 1559 1559 1 -2.74555e+01 -1.92854e+01 -2.24354e+01 + 1560 1560 1 -1.61855e+01 2.48900e+01 1.00400e+01 + 1561 1561 1 3.03700e+01 1.24100e+01 3.09600e+01 + 1562 1562 1 -4.92545e+00 3.08100e+01 2.62300e+01 + 1563 1563 1 -1.76455e+01 -6.90545e+00 -2.77554e+01 + 1564 1564 1 2.82600e+01 1.01100e+01 -8.34545e+00 + 1565 1565 1 1.62000e+01 1.23000e+00 2.99800e+01 + 1566 1566 1 6.69000e+00 2.24000e+01 -2.06454e+01 + 1567 1567 1 -1.78545e+00 1.05100e+01 -2.12754e+01 + 1568 1568 1 2.66100e+01 2.75000e+00 5.30000e+00 + 1569 1569 1 3.40000e-01 -1.28654e+01 2.56100e+01 + 1570 1570 1 -8.55545e+00 2.39400e+01 1.16800e+01 + 1571 1571 1 -2.62655e+01 -7.96545e+00 1.40600e+01 + 1572 1572 1 -2.60545e+00 -3.08754e+01 -8.15545e+00 + 1573 1573 1 1.22300e+01 -7.18545e+00 -2.58545e+00 + 1574 1574 1 1.84200e+01 2.43300e+01 2.76300e+01 + 1575 1575 1 -1.70255e+01 2.54000e+01 -9.83545e+00 + 1576 1576 1 5.24000e+00 -1.26154e+01 4.71000e+00 + 1577 1577 1 -2.03955e+01 -2.28354e+01 2.39000e+01 + 1578 1578 1 7.95000e+00 1.88000e+00 -2.23554e+01 + 1579 1579 1 1.20300e+01 1.16500e+01 1.64200e+01 + 1580 1580 1 3.77000e+00 1.29500e+01 -1.02054e+01 + 1581 1581 1 -1.52855e+01 5.40000e+00 1.59200e+01 + 1582 1582 1 -3.74545e+00 -1.10454e+01 -1.17354e+01 + 1583 1583 1 1.98300e+01 6.12000e+00 1.98200e+01 + 1584 1584 1 2.34800e+01 -9.65446e-01 -3.02254e+01 + 1585 1585 1 -2.81555e+01 -3.09954e+01 -1.11154e+01 + 1586 1586 1 -1.21755e+01 8.48000e+00 -1.63254e+01 + 1587 1587 1 5.45000e+00 -2.57454e+01 -2.84354e+01 + 1588 1588 1 -8.35450e-01 2.95700e+01 2.00800e+01 + 1589 1589 1 -1.70155e+01 3.07400e+01 1.48900e+01 + 1590 1590 1 2.66700e+01 6.20000e+00 2.85600e+01 + 1591 1591 1 -2.57545e+00 -7.61545e+00 -1.02954e+01 + 1592 1592 1 -5.99545e+00 -1.89454e+01 -1.93254e+01 + 1593 1593 1 -2.85655e+01 1.30300e+01 -2.47754e+01 + 1594 1594 1 -1.45155e+01 1.99300e+01 1.53800e+01 + 1595 1595 1 -2.46855e+01 7.21000e+00 3.50000e-01 + 1596 1596 1 8.31000e+00 -2.67854e+01 2.38700e+01 + 1597 1597 1 9.66000e+00 -2.59454e+01 -1.82454e+01 + 1598 1598 1 2.92700e+01 -2.84954e+01 1.51600e+01 + 1599 1599 1 -3.80000e-01 -1.51154e+01 -3.11054e+01 + 1600 1600 1 1.98200e+01 4.89000e+00 1.49500e+01 + 1601 1601 1 -2.04155e+01 -1.71545e+00 3.06700e+01 + 1602 1602 1 -3.07655e+01 2.68300e+01 2.67200e+01 + 1603 1603 1 2.74300e+01 -2.62454e+01 -2.88254e+01 + 1604 1604 1 -2.24055e+01 1.53300e+01 6.27000e+00 + 1605 1605 1 2.97300e+01 -4.96545e+00 -1.12354e+01 + 1606 1606 1 1.42600e+01 2.47900e+01 -8.94545e+00 + 1607 1607 1 2.24900e+01 2.34200e+01 -2.09654e+01 + 1608 1608 1 1.46500e+01 1.71400e+01 -2.68454e+01 + 1609 1609 1 -2.03955e+01 1.82400e+01 3.87000e+00 + 1610 1610 1 1.19800e+01 -3.02554e+01 1.25800e+01 + 1611 1611 1 1.19800e+01 1.11700e+01 2.91900e+01 + 1612 1612 1 7.75000e+00 -1.56654e+01 -9.53545e+00 + 1613 1613 1 -2.52455e+01 2.43000e+01 -8.13545e+00 + 1614 1614 1 -1.71155e+01 1.35600e+01 3.84000e+00 + 1615 1615 1 2.86600e+01 2.86800e+01 8.92000e+00 + 1616 1616 1 2.67800e+01 -5.75545e+00 -2.23854e+01 + 1617 1617 1 4.38000e+00 -1.76154e+01 3.09500e+01 + 1618 1618 1 -7.82545e+00 -2.04954e+01 2.01500e+01 + 1619 1619 1 8.66000e+00 -1.79454e+01 -2.93754e+01 + 1620 1620 1 -2.34755e+01 -2.72545e+00 1.80000e+00 + 1621 1621 1 -2.70155e+01 -8.46545e+00 1.86000e+00 + 1622 1622 1 4.81000e+00 -1.63454e+01 2.79400e+01 + 1623 1623 1 4.81000e+00 -1.03754e+01 1.32800e+01 + 1624 1624 1 -2.32655e+01 -1.20854e+01 1.74200e+01 + 1625 1625 1 -6.55545e+00 -8.16545e+00 -2.37154e+01 + 1626 1626 1 8.79000e+00 9.42000e+00 8.93000e+00 + 1627 1627 1 2.23600e+01 -2.22054e+01 -1.53454e+01 + 1628 1628 1 -1.11555e+01 -1.12854e+01 -7.46545e+00 + 1629 1629 1 2.50000e+00 2.64800e+01 -3.91545e+00 + 1630 1630 1 -4.41545e+00 -2.98545e+00 -2.97554e+01 + 1631 1631 1 3.05200e+01 -2.45554e+01 -1.20054e+01 + 1632 1632 1 -1.66355e+01 -2.21054e+01 -1.94554e+01 + 1633 1633 1 -2.36355e+01 1.41500e+01 1.81700e+01 + 1634 1634 1 -2.45155e+01 -1.69754e+01 1.71600e+01 + 1635 1635 1 -2.95755e+01 1.17400e+01 3.97000e+00 + 1636 1636 1 2.13000e+00 -3.82545e+00 -1.17454e+01 + 1637 1637 1 2.86900e+01 8.00000e+00 -4.36545e+00 + 1638 1638 1 -1.06355e+01 8.99000e+00 2.63700e+01 + 1639 1639 1 1.57400e+01 2.78900e+01 1.69200e+01 + 1640 1640 1 3.36000e+00 1.19500e+01 2.95000e+00 + 1641 1641 1 -2.88855e+01 -2.07454e+01 -2.66654e+01 + 1642 1642 1 3.06300e+01 1.91900e+01 2.86800e+01 + 1643 1643 1 1.14200e+01 1.02000e+01 2.56500e+01 + 1644 1644 1 2.19800e+01 -1.06354e+01 2.36100e+01 + 1645 1645 1 -2.14755e+01 -2.36354e+01 -1.65354e+01 + 1646 1646 1 -2.27055e+01 1.97900e+01 1.76000e+01 + 1647 1647 1 1.57200e+01 1.69700e+01 4.48000e+00 + 1648 1648 1 -1.17055e+01 -3.03154e+01 -1.11454e+01 + 1649 1649 1 -1.62155e+01 -2.05454e+01 5.13000e+00 + 1650 1650 1 2.87600e+01 2.79000e+00 -1.25354e+01 + 1651 1651 1 -2.29455e+01 2.12500e+01 -2.54545e+00 + 1652 1652 1 -6.25545e+00 -4.54457e-02 2.57700e+01 + 1653 1653 1 1.64400e+01 7.53000e+00 1.30800e+01 + 1654 1654 1 -3.08755e+01 3.10800e+01 1.62800e+01 + 1655 1655 1 -2.93055e+01 1.99700e+01 -1.01545e+00 + 1656 1656 1 2.69000e+01 -4.22545e+00 1.00900e+01 + 1657 1657 1 6.80000e-01 1.83100e+01 -1.45254e+01 + 1658 1658 1 2.47600e+01 2.00300e+01 7.76000e+00 + 1659 1659 1 -1.32755e+01 -1.23154e+01 1.95500e+01 + 1660 1660 1 -1.66755e+01 -2.67545e+00 -1.92454e+01 + 1661 1661 1 2.83400e+01 2.42300e+01 2.28400e+01 + 1662 1662 1 -1.34545e+00 -8.85446e-01 5.79000e+00 + 1663 1663 1 3.12000e+00 -2.94254e+01 1.60000e+00 + 1664 1664 1 -1.74555e+01 1.34554e-01 -1.27554e+01 + 1665 1665 1 -1.48055e+01 8.94000e+00 2.93200e+01 + 1666 1666 1 -2.17255e+01 -6.96545e+00 1.42200e+01 + 1667 1667 1 1.14000e+00 1.01200e+01 -1.96554e+01 + 1668 1668 1 -2.87055e+01 2.00900e+01 5.09000e+00 + 1669 1669 1 -9.08545e+00 -1.79154e+01 -2.66554e+01 + 1670 1670 1 2.02900e+01 -1.20454e+01 2.05500e+01 + 1671 1671 1 2.18000e+00 -2.89954e+01 5.86000e+00 + 1672 1672 1 -8.70545e+00 -3.00254e+01 1.39900e+01 + 1673 1673 1 2.22500e+01 1.91000e+01 2.63800e+01 + 1674 1674 1 1.01500e+01 -3.94545e+00 -3.21545e+00 + 1675 1675 1 -4.59545e+00 1.41000e+01 -1.34154e+01 + 1676 1676 1 2.31400e+01 -2.66754e+01 -2.36054e+01 + 1677 1677 1 1.40600e+01 3.06300e+01 -1.40354e+01 + 1678 1678 1 -1.36355e+01 2.42000e+00 1.24400e+01 + 1679 1679 1 -6.27545e+00 1.02000e+00 -2.53054e+01 + 1680 1680 1 -1.05255e+01 -2.85254e+01 3.09000e+00 + 1681 1681 1 -2.36155e+01 -2.09154e+01 1.90000e+00 + 1682 1682 1 2.96000e+00 -2.36654e+01 1.21100e+01 + 1683 1683 1 -3.84545e+00 2.00500e+01 2.03700e+01 + 1684 1684 1 1.79000e+01 -1.94054e+01 2.24555e-01 + 1685 1685 1 2.68400e+01 -1.18554e+01 2.33000e+01 + 1686 1686 1 -2.32255e+01 -2.49354e+01 2.06000e+01 + 1687 1687 1 -1.65755e+01 -1.20554e+01 -8.62545e+00 + 1688 1688 1 -1.45255e+01 2.88600e+01 -2.33154e+01 + 1689 1689 1 -3.11155e+01 -2.48545e+00 9.69000e+00 + 1690 1690 1 -2.71655e+01 -6.05446e-01 2.37300e+01 + 1691 1691 1 1.52300e+01 1.15900e+01 3.03100e+01 + 1692 1692 1 2.18100e+01 1.28700e+01 2.53400e+01 + 1693 1693 1 -3.04655e+01 -1.09554e+01 1.56200e+01 + 1694 1694 1 2.21700e+01 -2.25754e+01 2.19100e+01 + 1695 1695 1 -9.03545e+00 -1.94754e+01 -1.95445e-01 + 1696 1696 1 1.14000e+00 2.77000e+00 2.48000e+01 + 1697 1697 1 -2.68455e+01 9.32000e+00 8.59000e+00 + 1698 1698 1 -1.69545e+00 -2.40000e-01 -2.68254e+01 + 1699 1699 1 -2.77755e+01 -1.15254e+01 -1.01654e+01 + 1700 1700 1 1.38700e+01 1.28300e+01 -2.89545e+00 + 1701 1701 1 -7.25545e+00 1.20800e+01 -1.57545e+00 + 1702 1702 1 -7.68545e+00 5.20000e+00 -1.40545e+00 + 1703 1703 1 -9.31545e+00 3.06100e+01 -1.94754e+01 + 1704 1704 1 1.32000e+01 1.46900e+01 2.29600e+01 + 1705 1705 1 -1.37955e+01 1.86200e+01 -7.62545e+00 + 1706 1706 1 -1.41855e+01 1.32700e+01 -1.64754e+01 + 1707 1707 1 -1.27555e+01 2.60900e+01 9.00000e-02 + 1708 1708 1 -1.30545e+00 -2.62854e+01 3.06000e+00 + 1709 1709 1 -2.20155e+01 -1.63054e+01 -2.18254e+01 + 1710 1710 1 4.50000e-01 1.39800e+01 2.90000e-01 + 1711 1711 1 2.34300e+01 1.29200e+01 4.60000e+00 + 1712 1712 1 -3.67545e+00 -2.49654e+01 2.83700e+01 + 1713 1713 1 -2.96255e+01 2.45000e+00 1.82900e+01 + 1714 1714 1 1.85400e+01 4.56000e+00 -1.70754e+01 + 1715 1715 1 -3.35545e+00 -1.08254e+01 2.93000e+00 + 1716 1716 1 -2.48855e+01 2.05500e+01 -9.42545e+00 + 1717 1717 1 3.85000e+00 9.60000e+00 -1.61545e+00 + 1718 1718 1 2.91200e+01 1.33000e+00 1.88600e+01 + 1719 1719 1 9.92000e+00 2.34800e+01 -1.54554e+01 + 1720 1720 1 -7.38545e+00 -2.75554e+01 -4.71545e+00 + 1721 1721 1 -2.39355e+01 5.92000e+00 2.89000e+01 + 1722 1722 1 1.89900e+01 2.93600e+01 2.80000e-01 + 1723 1723 1 6.93000e+00 -2.36354e+01 -1.43054e+01 + 1724 1724 1 -1.52055e+01 -1.33254e+01 3.00400e+01 + 1725 1725 1 5.12000e+00 -3.20000e-01 9.10000e+00 + 1726 1726 1 -3.42545e+00 2.61500e+01 -8.03545e+00 + 1727 1727 1 1.98900e+01 2.10000e-01 1.46300e+01 + 1728 1728 1 -1.99955e+01 7.15000e+00 -2.25545e+00 + 1729 1729 1 -2.91155e+01 -2.40154e+01 -2.44154e+01 + 1730 1730 1 9.70000e+00 3.50000e+00 5.96000e+00 + 1731 1731 1 -2.07955e+01 2.33200e+01 1.66300e+01 + 1732 1732 1 -4.36545e+00 -2.73545e+00 1.53300e+01 + 1733 1733 1 1.41200e+01 -2.18954e+01 -1.66254e+01 + 1734 1734 1 1.62700e+01 2.50000e+00 1.92000e+01 + 1735 1735 1 1.51600e+01 5.36000e+00 -1.06254e+01 + 1736 1736 1 -2.73555e+01 -3.05354e+01 4.44000e+00 + 1737 1737 1 -1.79955e+01 -6.05545e+00 2.48400e+01 + 1738 1738 1 -1.02855e+01 1.24600e+01 -2.74054e+01 + 1739 1739 1 -1.38255e+01 2.27800e+01 2.15900e+01 + 1740 1740 1 9.18000e+00 7.36000e+00 2.98400e+01 + 1741 1741 1 -1.91955e+01 2.61800e+01 1.23900e+01 + 1742 1742 1 -6.84545e+00 1.89700e+01 3.08600e+01 + 1743 1743 1 -2.95355e+01 1.44300e+01 -6.99545e+00 + 1744 1744 1 -1.59855e+01 -1.29954e+01 2.50400e+01 + 1745 1745 1 -2.82455e+01 5.59000e+00 1.66100e+01 + 1746 1746 1 4.36000e+00 -2.61354e+01 -1.73254e+01 + 1747 1747 1 -2.25955e+01 1.88600e+01 -6.65545e+00 + 1748 1748 1 -4.39545e+00 -1.98854e+01 1.16500e+01 + 1749 1749 1 1.05000e+00 -2.95754e+01 -1.94554e+01 + 1750 1750 1 -3.02545e+00 2.13900e+01 -6.92545e+00 + 1751 1751 1 -6.22545e+00 -1.83554e+01 1.71600e+01 + 1752 1752 1 9.04000e+00 -2.38954e+01 3.16000e+00 + 1753 1753 1 -8.15450e-01 -1.62554e+01 -1.29454e+01 + 1754 1754 1 -2.88545e+00 4.42000e+00 1.03700e+01 + 1755 1755 1 3.06800e+01 9.07000e+00 7.36000e+00 + 1756 1756 1 1.63700e+01 -5.24545e+00 2.57500e+01 + 1757 1757 1 -1.07355e+01 1.26800e+01 1.24000e+00 + 1758 1758 1 -8.50545e+00 7.03000e+00 -1.50954e+01 + 1759 1759 1 -2.33555e+01 1.59000e+01 1.11000e+00 + 1760 1760 1 4.19000e+00 2.44300e+01 -2.80554e+01 + 1761 1761 1 -3.34545e+00 2.25500e+01 2.98000e+00 + 1762 1762 1 1.35700e+01 2.91000e+01 -1.98454e+01 + 1763 1763 1 1.53300e+01 -7.55545e+00 -1.02954e+01 + 1764 1764 1 2.85800e+01 5.54000e+00 -2.70854e+01 + 1765 1765 1 -9.74545e+00 -2.82654e+01 2.81400e+01 + 1766 1766 1 -3.81545e+00 -1.32554e+01 -1.43654e+01 + 1767 1767 1 3.30000e+00 2.41900e+01 9.53000e+00 + 1768 1768 1 -1.14255e+01 -9.70545e+00 2.23000e+00 + 1769 1769 1 -2.86355e+01 -1.84545e+00 -2.06554e+01 + 1770 1770 1 -2.18855e+01 -2.86054e+01 -2.02154e+01 + 1771 1771 1 8.26000e+00 -3.07954e+01 1.06000e+01 + 1772 1772 1 7.53000e+00 -9.08545e+00 -1.98354e+01 + 1773 1773 1 -1.70755e+01 -4.99545e+00 3.01500e+01 + 1774 1774 1 -2.21355e+01 2.24000e+01 1.30400e+01 + 1775 1775 1 -2.49255e+01 -1.88254e+01 -3.08554e+01 + 1776 1776 1 -6.45545e+00 -1.08954e+01 2.41300e+01 + 1777 1777 1 1.57400e+01 -1.70954e+01 2.07200e+01 + 1778 1778 1 1.69000e+00 2.24900e+01 -2.66254e+01 + 1779 1779 1 3.02000e+01 -1.99254e+01 6.06000e+00 + 1780 1780 1 5.23000e+00 1.18600e+01 1.38700e+01 + 1781 1781 1 -5.57545e+00 1.03600e+01 -3.04054e+01 + 1782 1782 1 9.38000e+00 -2.27054e+01 1.98600e+01 + 1783 1783 1 2.24600e+01 -9.80545e+00 -1.87354e+01 + 1784 1784 1 1.33000e+00 2.51700e+01 1.48000e+01 + 1785 1785 1 -2.19545e+00 1.76300e+01 1.03000e+00 + 1786 1786 1 4.41000e+00 -1.57554e+01 8.60000e+00 + 1787 1787 1 -3.65545e+00 -1.65254e+01 -1.05954e+01 + 1788 1788 1 2.06400e+01 -2.08454e+01 -1.50545e+00 + 1789 1789 1 -1.91655e+01 -7.55446e-01 1.34000e+00 + 1790 1790 1 7.03000e+00 4.34000e+00 2.31400e+01 + 1791 1791 1 -8.03545e+00 1.66900e+01 2.56700e+01 + 1792 1792 1 1.31000e+00 2.58300e+01 -1.16454e+01 + 1793 1793 1 2.75100e+01 1.70600e+01 -1.94054e+01 + 1794 1794 1 6.36000e+00 -2.27454e+01 2.77300e+01 + 1795 1795 1 -2.83955e+01 -1.29545e+00 2.78000e+00 + 1796 1796 1 -2.81055e+01 -2.63054e+01 2.82500e+01 + 1797 1797 1 2.63400e+01 2.95800e+01 -2.66254e+01 + 1798 1798 1 1.85800e+01 -1.47554e+01 -1.18054e+01 + 1799 1799 1 8.02000e+00 -1.05354e+01 2.18500e+01 + 1800 1800 1 -2.45545e+00 -2.12254e+01 8.88000e+00 + 1801 1801 1 -3.10155e+01 5.32000e+00 1.99100e+01 + 1802 1802 1 -7.67545e+00 1.10900e+01 -1.26654e+01 + 1803 1803 1 -2.46755e+01 -2.32654e+01 -1.22754e+01 + 1804 1804 1 3.08600e+01 1.10700e+01 -1.43554e+01 + 1805 1805 1 1.30700e+01 2.13600e+01 -2.70554e+01 + 1806 1806 1 9.51000e+00 1.08100e+01 -2.53354e+01 + 1807 1807 1 -2.38555e+01 -2.18854e+01 -2.18545e+00 + 1808 1808 1 2.57300e+01 -1.44954e+01 1.93400e+01 + 1809 1809 1 1.43400e+01 -2.36854e+01 1.12000e+00 + 1810 1810 1 1.81000e+00 3.04900e+01 -5.95545e+00 + 1811 1811 1 -1.11355e+01 3.05200e+01 -9.25445e-01 + 1812 1812 1 3.05600e+01 -3.06354e+01 -2.11654e+01 + 1813 1813 1 -2.48055e+01 2.22000e+00 -1.32554e+01 + 1814 1814 1 -3.04255e+01 -1.96545e+00 -1.23054e+01 + 1815 1815 1 4.77000e+00 -2.84554e+01 2.78800e+01 + 1816 1816 1 8.55000e+00 8.48000e+00 -2.27254e+01 + 1817 1817 1 1.22000e+00 4.09000e+00 -2.91754e+01 + 1818 1818 1 1.60900e+01 -2.36754e+01 -2.17954e+01 + 1819 1819 1 1.25600e+01 -2.36554e+01 3.11200e+01 + 1820 1820 1 2.43200e+01 -5.06545e+00 1.65600e+01 + 1821 1821 1 -2.29555e+01 -1.51354e+01 -2.87054e+01 + 1822 1822 1 1.31900e+01 1.56500e+01 1.35300e+01 + 1823 1823 1 -2.48255e+01 -1.26254e+01 -2.00354e+01 + 1824 1824 1 2.04100e+01 1.19000e+01 1.38400e+01 + 1825 1825 1 -1.45855e+01 -2.58954e+01 2.38500e+01 + 1826 1826 1 1.96400e+01 -2.16354e+01 -7.91545e+00 + 1827 1827 1 2.93500e+01 3.09100e+01 2.08000e+00 + 1828 1828 1 2.19800e+01 -1.88854e+01 2.93400e+01 + 1829 1829 1 3.00600e+01 -2.33354e+01 -7.52545e+00 + 1830 1830 1 1.15000e+00 2.05800e+01 -1.81354e+01 + 1831 1831 1 -3.07155e+01 2.68900e+01 1.89300e+01 + 1832 1832 1 -6.05545e+00 -2.78354e+01 -1.58854e+01 + 1833 1833 1 -8.00545e+00 2.74700e+01 -3.01054e+01 + 1834 1834 1 7.56000e+00 -1.52054e+01 1.76200e+01 + 1835 1835 1 -3.26545e+00 2.01500e+01 -2.85654e+01 + 1836 1836 1 -2.33955e+01 1.04900e+01 7.06000e+00 + 1837 1837 1 -1.82055e+01 -1.22554e+01 -4.73545e+00 + 1838 1838 1 -1.06855e+01 -2.07354e+01 -4.46545e+00 + 1839 1839 1 2.55300e+01 1.32900e+01 1.11100e+01 + 1840 1840 1 1.99000e+00 7.20000e+00 3.03900e+01 + 1841 1841 1 2.26000e+01 1.91900e+01 -1.98554e+01 + 1842 1842 1 1.48400e+01 4.81000e+00 -2.91054e+01 + 1843 1843 1 -2.27355e+01 -3.97545e+00 -1.79154e+01 + 1844 1844 1 -6.75545e+00 -2.63254e+01 1.22500e+01 + 1845 1845 1 -2.25545e+00 7.32000e+00 -5.79545e+00 + 1846 1846 1 6.93000e+00 -1.14954e+01 -4.44545e+00 + 1847 1847 1 -2.13355e+01 -1.31954e+01 1.00500e+01 + 1848 1848 1 2.36000e+00 4.67000e+00 -2.53354e+01 + 1849 1849 1 -1.24255e+01 2.50000e+01 8.10000e+00 + 1850 1850 1 2.95900e+01 -3.98545e+00 1.92900e+01 + 1851 1851 1 1.98700e+01 -1.35454e+01 -3.01054e+01 + 1852 1852 1 7.64000e+00 9.90000e-01 -1.00754e+01 + 1853 1853 1 1.67400e+01 -1.20054e+01 2.89200e+01 + 1854 1854 1 2.92900e+01 2.52100e+01 -1.95545e+00 + 1855 1855 1 4.12000e+00 2.91900e+01 -1.05854e+01 + 1856 1856 1 3.06400e+01 -7.13545e+00 2.72300e+01 + 1857 1857 1 1.52000e+00 2.06400e+01 2.87000e+01 + 1858 1858 1 -1.88155e+01 2.93000e+01 -2.53054e+01 + 1859 1859 1 6.03000e+00 -7.67545e+00 1.95300e+01 + 1860 1860 1 -7.43545e+00 -1.26754e+01 -2.09854e+01 + 1861 1861 1 2.34000e+01 3.45543e-02 -6.77545e+00 + 1862 1862 1 2.49000e+01 6.30000e-01 -2.50854e+01 + 1863 1863 1 -8.19545e+00 -2.41254e+01 2.86400e+01 + 1864 1864 1 -3.17545e+00 -1.48454e+01 -5.54454e-02 + 1865 1865 1 1.80000e+00 -1.53654e+01 -2.06554e+01 + 1866 1866 1 -2.71055e+01 -1.58254e+01 -1.68554e+01 + 1867 1867 1 -1.73255e+01 2.01900e+01 -3.01854e+01 + 1868 1868 1 2.31000e+00 1.48900e+01 1.55000e+01 + 1869 1869 1 -2.63155e+01 -1.84054e+01 -2.65054e+01 + 1870 1870 1 1.16500e+01 -1.27254e+01 -1.52554e+01 + 1871 1871 1 1.99000e+01 -2.55854e+01 -1.05954e+01 + 1872 1872 1 2.02600e+01 -1.19054e+01 -4.04545e+00 + 1873 1873 1 1.49800e+01 -2.81454e+01 2.97800e+01 + 1874 1874 1 1.21400e+01 2.44200e+01 3.65000e+00 + 1875 1875 1 -2.07455e+01 -1.38154e+01 2.71100e+01 + 1876 1876 1 3.37000e+00 -1.81754e+01 4.71000e+00 + 1877 1877 1 8.08000e+00 1.78600e+01 -2.91354e+01 + 1878 1878 1 2.11900e+01 -2.18545e+00 -5.54454e-02 + 1879 1879 1 1.13000e+01 -1.82354e+01 2.53100e+01 + 1880 1880 1 -2.82355e+01 -8.15545e+00 -2.25154e+01 + 1881 1881 1 3.62000e+00 -5.63545e+00 9.16000e+00 + 1882 1882 1 2.37200e+01 1.51100e+01 2.88000e+01 + 1883 1883 1 -3.09255e+01 3.44554e-01 1.57700e+01 + 1884 1884 1 -3.62545e+00 -2.58054e+01 -2.72354e+01 + 1885 1885 1 -2.44355e+01 -2.76054e+01 1.30300e+01 + 1886 1886 1 2.56000e+00 2.93100e+01 -3.03954e+01 + 1887 1887 1 -1.86955e+01 2.21000e+00 -2.85854e+01 + 1888 1888 1 -3.07155e+01 -8.16545e+00 -8.80545e+00 + 1889 1889 1 -4.60545e+00 -2.91154e+01 -2.13354e+01 + 1890 1890 1 -2.35545e+00 2.54000e+00 -3.10154e+01 + 1891 1891 1 2.05900e+01 -3.65545e+00 1.89700e+01 + 1892 1892 1 8.71000e+00 -2.86354e+01 -2.54154e+01 + 1893 1893 1 1.60800e+01 7.41000e+00 3.89000e+00 + 1894 1894 1 1.96000e+01 1.34800e+01 -1.69854e+01 + 1895 1895 1 -1.29955e+01 2.16500e+01 -3.25445e-01 + 1896 1896 1 -3.13545e+00 -7.74545e+00 1.12000e+00 + 1897 1897 1 9.01000e+00 1.55900e+01 -1.81954e+01 + 1898 1898 1 4.96000e+00 -2.77654e+01 -2.57254e+01 + 1899 1899 1 -9.26545e+00 1.02500e+01 9.56000e+00 + 1900 1900 1 -7.26545e+00 -6.39545e+00 -5.34545e+00 + 1901 1901 1 -8.15450e-01 -1.13954e+01 -3.65545e+00 + 1902 1902 1 -1.22255e+01 -6.31545e+00 -7.46545e+00 + 1903 1903 1 -8.90545e+00 8.60000e-01 -2.73545e+00 + 1904 1904 1 1.80900e+01 -1.51754e+01 2.36300e+01 + 1905 1905 1 -2.37455e+01 2.67400e+01 -3.03545e+00 + 1906 1906 1 4.96000e+00 2.27700e+01 1.90600e+01 + 1907 1907 1 -4.51545e+00 7.45000e+00 1.57200e+01 + 1908 1908 1 2.18300e+01 4.21000e+00 -1.95254e+01 + 1909 1909 1 1.48700e+01 2.49500e+01 3.10600e+01 + 1910 1910 1 -1.76955e+01 1.99900e+01 1.83000e+01 + 1911 1911 1 3.28000e+00 6.04000e+00 -1.39854e+01 + 1912 1912 1 2.54500e+01 1.38100e+01 1.50700e+01 + 1913 1913 1 -1.14955e+01 9.34000e+00 -2.00054e+01 + 1914 1914 1 1.09200e+01 -9.79545e+00 2.17000e+00 + 1915 1915 1 -3.86545e+00 -6.40000e-01 -1.37545e+00 + 1916 1916 1 2.03300e+01 1.21600e+01 -2.04954e+01 + 1917 1917 1 -2.61555e+01 1.71900e+01 2.44600e+01 + 1918 1918 1 2.29600e+01 2.06100e+01 -1.39354e+01 + 1919 1919 1 1.48300e+01 1.49100e+01 1.75400e+01 + 1920 1920 1 -1.94255e+01 2.50500e+01 -4.63545e+00 + 1921 1921 1 3.03200e+01 -1.15454e+01 2.81700e+01 + 1922 1922 1 1.70400e+01 1.24200e+01 1.15200e+01 + 1923 1923 1 3.02500e+01 -2.19254e+01 2.39000e+01 + 1924 1924 1 3.02400e+01 -1.73154e+01 1.37000e+00 + 1925 1925 1 1.00100e+01 1.27400e+01 -2.20154e+01 + 1926 1926 1 -1.79655e+01 -2.97354e+01 2.93100e+01 + 1927 1927 1 1.01300e+01 -1.85754e+01 -1.69154e+01 + 1928 1928 1 8.40000e+00 -1.65154e+01 5.28000e+00 + 1929 1929 1 -2.71155e+01 -8.74545e+00 -1.22754e+01 + 1930 1930 1 1.58400e+01 -8.65545e+00 1.64700e+01 + 1931 1931 1 7.56000e+00 -8.85446e-01 6.43000e+00 + 1932 1932 1 -2.41655e+01 -5.34545e+00 7.88000e+00 + 1933 1933 1 1.39300e+01 -2.99754e+01 2.44000e+00 + 1934 1934 1 1.13200e+01 1.60500e+01 2.57000e+00 + 1935 1935 1 2.03000e+00 -2.57545e+00 -1.56654e+01 + 1936 1936 1 -2.04455e+01 2.36100e+01 7.76000e+00 + 1937 1937 1 2.95500e+01 -1.37154e+01 1.50400e+01 + 1938 1938 1 -2.16055e+01 2.99500e+01 4.46000e+00 + 1939 1939 1 -3.03955e+01 -4.15446e-01 2.61400e+01 + 1940 1940 1 -2.34355e+01 -2.28754e+01 -3.09354e+01 + 1941 1941 1 1.64200e+01 1.99600e+01 -2.62554e+01 + 1942 1942 1 -1.17655e+01 -9.23545e+00 7.75000e+00 + 1943 1943 1 -1.71555e+01 1.70100e+01 2.54900e+01 + 1944 1944 1 8.81000e+00 -5.64545e+00 1.35000e+01 + 1945 1945 1 -2.47555e+01 1.61700e+01 -1.36554e+01 + 1946 1946 1 -1.51955e+01 1.95300e+01 9.64000e+00 + 1947 1947 1 1.59800e+01 -2.79154e+01 -1.48954e+01 + 1948 1948 1 -8.41545e+00 -9.28545e+00 4.69000e+00 + 1949 1949 1 -2.63655e+01 -2.26554e+01 5.27000e+00 + 1950 1950 1 1.18700e+01 9.90000e+00 3.56000e+00 + 1951 1951 1 9.72000e+00 -1.33954e+01 -1.32545e+00 + 1952 1952 1 -3.27545e+00 2.30500e+01 -2.52554e+01 + 1953 1953 1 1.68000e+00 -9.73545e+00 2.54100e+01 + 1954 1954 1 1.22000e+01 -1.00854e+01 -8.43545e+00 + 1955 1955 1 -5.12545e+00 -2.15754e+01 -3.08454e+01 + 1956 1956 1 -1.16155e+01 4.18000e+00 3.05800e+01 + 1957 1957 1 -5.97545e+00 -3.65545e+00 1.95000e+00 + 1958 1958 1 -1.16555e+01 -2.84354e+01 1.98200e+01 + 1959 1959 1 -1.25450e-01 -1.62554e+01 -1.67954e+01 + 1960 1960 1 5.17000e+00 2.73700e+01 1.76000e+01 + 1961 1961 1 1.93400e+01 -7.74545e+00 -2.24654e+01 + 1962 1962 1 -2.76255e+01 1.03200e+01 1.40700e+01 + 1963 1963 1 9.31000e+00 2.93300e+01 -2.68554e+01 + 1964 1964 1 6.33000e+00 2.38000e+00 -1.32554e+01 + 1965 1965 1 -3.95450e-01 -1.06454e+01 -1.53554e+01 + 1966 1966 1 -7.78545e+00 2.65900e+01 -1.11954e+01 + 1967 1967 1 -2.74855e+01 -4.14545e+00 -2.66454e+01 + 1968 1968 1 -2.07545e+00 2.96000e+01 -1.99654e+01 + 1969 1969 1 2.73200e+01 -1.79545e+00 1.72800e+01 + 1970 1970 1 -7.36545e+00 -2.59054e+01 2.56700e+01 + 1971 1971 1 1.44100e+01 -8.40545e+00 5.22000e+00 + 1972 1972 1 1.74300e+01 -6.83545e+00 1.36100e+01 + 1973 1973 1 1.25700e+01 3.01100e+01 -5.02545e+00 + 1974 1974 1 1.20800e+01 1.93600e+01 -2.96854e+01 + 1975 1975 1 1.43400e+01 -1.70754e+01 -1.51654e+01 + 1976 1976 1 9.77000e+00 -1.04154e+01 1.18100e+01 + 1977 1977 1 2.09600e+01 2.26000e+01 6.16000e+00 + 1978 1978 1 -4.53545e+00 -1.37154e+01 1.93300e+01 + 1979 1979 1 -2.56955e+01 -1.49754e+01 -7.24545e+00 + 1980 1980 1 6.91000e+00 -2.01054e+01 8.62000e+00 + 1981 1981 1 6.60000e-01 -2.69654e+01 2.73000e+01 + 1982 1982 1 7.24000e+00 -1.74354e+01 2.61700e+01 + 1983 1983 1 -6.18545e+00 -6.34545e+00 1.40100e+01 + 1984 1984 1 1.84200e+01 -2.35154e+01 1.08500e+01 + 1985 1985 1 -4.68545e+00 5.50000e+00 1.90200e+01 + 1986 1986 1 2.73900e+01 -1.26154e+01 4.85000e+00 + 1987 1987 1 1.76600e+01 2.40400e+01 2.99000e+00 + 1988 1988 1 3.10300e+01 2.32500e+01 -2.21454e+01 + 1989 1989 1 2.64800e+01 2.22900e+01 -2.23054e+01 + 1990 1990 1 -2.34555e+01 -2.90854e+01 -3.45545e+00 + 1991 1991 1 -3.25450e-01 2.49600e+01 1.00600e+01 + 1992 1992 1 -1.48455e+01 1.64200e+01 1.79000e+00 + 1993 1993 1 -1.97555e+01 -1.69154e+01 -1.58254e+01 + 1994 1994 1 2.25800e+01 2.01900e+01 -1.00354e+01 + 1995 1995 1 7.03000e+00 -7.93545e+00 2.75800e+01 + 1996 1996 1 2.61700e+01 1.89500e+01 -2.62254e+01 + 1997 1997 1 2.57600e+01 -2.80054e+01 -1.73254e+01 + 1998 1998 1 2.38600e+01 -6.79545e+00 -9.84545e+00 + 1999 1999 1 -2.02855e+01 -7.06545e+00 -2.49054e+01 + 2000 2000 1 1.55000e+01 2.52700e+01 -5.18545e+00 + 2001 2001 1 9.38000e+00 -3.01454e+01 -1.22754e+01 + 2002 2002 1 1.67300e+01 -1.63545e+00 1.77300e+01 + 2003 2003 1 1.42900e+01 1.59000e+00 8.88000e+00 + 2004 2004 1 7.16000e+00 2.06500e+01 -7.35545e+00 + 2005 2005 1 -2.31355e+01 1.57000e+01 2.97700e+01 + 2006 2006 1 9.60000e-01 0.00000e+00 2.84200e+01 + 2007 2007 1 -1.25355e+01 2.19200e+01 1.05700e+01 + 2008 2008 1 -2.66855e+01 1.78300e+01 -2.22545e+00 + 2009 2009 1 -1.85955e+01 3.22000e+00 3.37000e+00 + 2010 2010 1 -1.24955e+01 -1.88054e+01 -1.19054e+01 + 2011 2011 1 -1.47955e+01 -2.00545e+00 2.37800e+01 + 2012 2012 1 2.50500e+01 4.61000e+00 -2.53454e+01 + 2013 2013 1 -1.83555e+01 2.35600e+01 -3.04354e+01 + 2014 2014 1 2.85400e+01 1.81300e+01 1.61500e+01 + 2015 2015 1 2.32900e+01 -5.97545e+00 -2.15854e+01 + 2016 2016 1 -1.87655e+01 3.02800e+01 -2.00054e+01 + 2017 2017 1 1.10000e+00 -3.08154e+01 -1.45654e+01 + 2018 2018 1 -1.78755e+01 -2.83854e+01 2.23400e+01 + 2019 2019 1 1.19100e+01 -2.59545e+00 7.91000e+00 + 2020 2020 1 -4.85545e+00 2.71800e+01 2.19100e+01 + 2021 2021 1 -6.45545e+00 2.12000e+01 3.40000e+00 + 2022 2022 1 -2.36545e+00 5.05000e+00 2.37000e+01 + 2023 2023 1 6.80000e-01 8.18000e+00 2.51600e+01 + 2024 2024 1 1.80500e+01 2.31300e+01 1.50600e+01 + 2025 2025 1 -7.94545e+00 1.49100e+01 -2.70954e+01 + 2026 2026 1 1.11700e+01 -1.87254e+01 -1.29954e+01 + 2027 2027 1 -8.25450e-01 2.56200e+01 2.79500e+01 + 2028 2028 1 3.59000e+00 -4.72545e+00 -7.09545e+00 + 2029 2029 1 2.32000e+01 2.44900e+01 -1.04354e+01 + 2030 2030 1 -5.54545e+00 1.77300e+01 -5.34545e+00 + 2031 2031 1 3.02200e+01 -5.01545e+00 -4.03545e+00 + 2032 2032 1 -1.78155e+01 1.89700e+01 -5.57545e+00 + 2033 2033 1 1.47700e+01 -2.67654e+01 1.15400e+01 + 2034 2034 1 -1.26755e+01 1.70800e+01 -1.56954e+01 + 2035 2035 1 8.63000e+00 -2.20454e+01 -1.19354e+01 + 2036 2036 1 -5.15545e+00 2.39700e+01 -2.24154e+01 + 2037 2037 1 1.43100e+01 -2.16954e+01 -1.14554e+01 + 2038 2038 1 6.99000e+00 2.69900e+01 -3.00154e+01 + 2039 2039 1 -1.13755e+01 -2.58545e+00 -2.58545e+00 + 2040 2040 1 1.22700e+01 2.54000e+00 2.67800e+01 + 2041 2041 1 -1.28255e+01 -2.78254e+01 -7.86545e+00 + 2042 2042 1 7.27000e+00 -2.33654e+01 -8.92545e+00 + 2043 2043 1 7.17000e+00 -1.83354e+01 -1.38454e+01 + 2044 2044 1 2.39100e+01 1.19000e+01 1.78300e+01 + 2045 2045 1 1.35900e+01 -1.81754e+01 -3.01954e+01 + 2046 2046 1 9.58000e+00 8.60000e-01 -1.77854e+01 + 2047 2047 1 9.52000e+00 1.84300e+01 -2.15454e+01 + 2048 2048 1 -1.43155e+01 -1.23154e+01 1.54300e+01 + 2049 2049 1 2.70700e+01 -1.22954e+01 -2.60154e+01 + 2050 2050 1 6.80000e-01 1.70600e+01 -3.29545e+00 + 2051 2051 1 -1.21355e+01 2.91200e+01 -9.16545e+00 + 2052 2052 1 -7.75450e-01 -2.64454e+01 -7.64545e+00 + 2053 2053 1 -9.75545e+00 -1.33545e+00 2.53700e+01 + 2054 2054 1 -2.86555e+01 2.32500e+01 1.70300e+01 + 2055 2055 1 2.19000e+00 2.17100e+01 -2.10154e+01 + 2056 2056 1 -1.20755e+01 -2.79554e+01 5.93000e+00 + 2057 2057 1 1.01900e+01 -2.79254e+01 -9.08545e+00 + 2058 2058 1 -3.11055e+01 -1.17754e+01 -1.14154e+01 + 2059 2059 1 1.69300e+01 2.03400e+01 1.88900e+01 + 2060 2060 1 -7.33545e+00 1.88000e+00 2.96000e+01 + 2061 2061 1 2.85300e+01 -6.66545e+00 -1.00545e+00 + 2062 2062 1 2.62200e+01 -2.34454e+01 -9.50545e+00 + 2063 2063 1 -3.05855e+01 -2.74654e+01 1.83700e+01 + 2064 2064 1 -2.94655e+01 -2.34154e+01 -5.62545e+00 + 2065 2065 1 1.90500e+01 -8.45446e-01 -8.28545e+00 + 2066 2066 1 2.85200e+01 -1.74554e+01 1.17500e+01 + 2067 2067 1 -2.64155e+01 2.37800e+01 -1.20954e+01 + 2068 2068 1 -2.37545e+00 8.58000e+00 -2.78054e+01 + 2069 2069 1 1.80100e+01 2.56400e+01 -1.37545e+00 + 2070 2070 1 2.57900e+01 -2.86454e+01 1.77800e+01 + 2071 2071 1 5.15000e+00 -2.00254e+01 -2.20545e+00 + 2072 2072 1 1.10700e+01 -1.46854e+01 -2.26454e+01 + 2073 2073 1 -8.66545e+00 1.08200e+01 -1.73954e+01 + 2074 2074 1 -3.35545e+00 -4.00545e+00 2.67700e+01 + 2075 2075 1 -2.27455e+01 -6.93545e+00 -2.78854e+01 + 2076 2076 1 1.13200e+01 2.36200e+01 -2.85054e+01 + 2077 2077 1 -8.56545e+00 2.74600e+01 1.28100e+01 + 2078 2078 1 -1.54502e-02 -5.60545e+00 2.47000e+01 + 2079 2079 1 -2.41555e+01 -1.92454e+01 7.48000e+00 + 2080 2080 1 -2.50355e+01 -1.97254e+01 -1.54554e+01 + 2081 2081 1 5.65000e+00 -3.75545e+00 1.28300e+01 + 2082 2082 1 -1.14455e+01 3.06300e+01 -4.63545e+00 + 2083 2083 1 3.55000e+00 1.54200e+01 -2.48454e+01 + 2084 2084 1 3.05900e+01 -2.41954e+01 2.82500e+01 + 2085 2085 1 -2.97355e+01 -2.04154e+01 -1.18354e+01 + 2086 2086 1 6.53000e+00 -1.63254e+01 -3.25545e+00 + 2087 2087 1 9.06000e+00 1.56400e+01 1.58000e+01 + 2088 2088 1 1.17000e+00 -8.96545e+00 -1.21954e+01 + 2089 2089 1 4.94000e+00 -2.69454e+01 -1.30554e+01 + 2090 2090 1 1.97800e+01 -2.66654e+01 -4.77545e+00 + 2091 2091 1 1.31000e+01 -1.49754e+01 1.20700e+01 + 2092 2092 1 -2.88555e+01 -1.57754e+01 1.48000e+01 + 2093 2093 1 -1.94755e+01 4.45000e+00 -6.58545e+00 + 2094 2094 1 9.20000e+00 -7.27545e+00 1.02800e+01 + 2095 2095 1 4.80000e-01 1.89200e+01 1.45700e+01 + 2096 2096 1 -3.08555e+01 -5.53545e+00 4.66000e+00 + 2097 2097 1 4.57000e+00 -3.32545e+00 -2.22154e+01 + 2098 2098 1 1.27500e+01 6.44000e+00 -1.40754e+01 + 2099 2099 1 8.02000e+00 -1.87854e+01 -1.02454e+01 + 2100 2100 1 -1.15155e+01 2.06900e+01 1.36400e+01 + 2101 2101 1 1.18800e+01 -3.37545e+00 -2.28754e+01 + 2102 2102 1 3.94000e+00 -1.76854e+01 -1.08254e+01 + 2103 2103 1 -5.65450e-01 2.76000e+01 -1.79545e+00 + 2104 2104 1 2.75200e+01 2.15500e+01 -8.93545e+00 + 2105 2105 1 3.04500e+01 1.47400e+01 -2.27754e+01 + 2106 2106 1 -1.63255e+01 -8.52545e+00 -8.55445e-01 + 2107 2107 1 7.47000e+00 -3.00554e+01 -3.15445e-01 + 2108 2108 1 2.31700e+01 -1.50754e+01 -2.44754e+01 + 2109 2109 1 -5.01545e+00 2.60500e+01 2.80700e+01 + 2110 2110 1 -2.36555e+01 2.71800e+01 4.25000e+00 + 2111 2111 1 -2.24655e+01 -2.84354e+01 -2.44154e+01 + 2112 2112 1 2.01000e+01 1.62700e+01 -1.81854e+01 + 2113 2113 1 2.88000e+01 -1.67454e+01 -4.98545e+00 + 2114 2114 1 -1.19755e+01 2.51500e+01 2.37500e+01 + 2115 2115 1 -1.86755e+01 1.69600e+01 -2.33154e+01 + 2116 2116 1 2.29200e+01 4.36000e+00 -9.64545e+00 + 2117 2117 1 2.17300e+01 -8.76545e+00 -1.43545e+00 + 2118 2118 1 2.71400e+01 5.12000e+00 -6.03545e+00 + 2119 2119 1 -2.31955e+01 -2.47854e+01 1.00000e-01 + 2120 2120 1 -2.95545e+00 1.65500e+01 -1.80854e+01 + 2121 2121 1 -2.26855e+01 -2.84054e+01 1.88100e+01 + 2122 2122 1 2.04600e+01 -2.16054e+01 -2.07254e+01 + 2123 2123 1 2.18000e+01 -1.33954e+01 -1.54854e+01 + 2124 2124 1 7.84000e+00 6.74000e+00 6.42000e+00 + 2125 2125 1 1.10200e+01 -2.15054e+01 1.12900e+01 + 2126 2126 1 1.82400e+01 -3.02454e+01 -3.60545e+00 + 2127 2127 1 -5.94545e+00 -2.37254e+01 -3.84545e+00 + 2128 2128 1 1.50000e-01 1.46000e+01 -1.05654e+01 + 2129 2129 1 -2.47155e+01 -2.19254e+01 1.81400e+01 + 2130 2130 1 2.25800e+01 -3.43545e+00 1.14600e+01 + 2131 2131 1 1.60900e+01 -6.55545e+00 -3.51545e+00 + 2132 2132 1 -1.30555e+01 1.45300e+01 2.48500e+01 + 2133 2133 1 2.04000e+01 -3.07854e+01 -1.85054e+01 + 2134 2134 1 2.14000e+00 4.89000e+00 -3.42545e+00 + 2135 2135 1 -1.59355e+01 -4.77545e+00 4.40000e+00 + 2136 2136 1 -2.39555e+01 -2.18154e+01 -2.70254e+01 + 2137 2137 1 -2.99355e+01 -9.11545e+00 8.53000e+00 + 2138 2138 1 1.27400e+01 8.34000e+00 -1.55545e+00 + 2139 2139 1 -8.23545e+00 -1.94545e+00 1.56700e+01 + 2140 2140 1 -2.61655e+01 1.48100e+01 -6.21545e+00 + 2141 2141 1 -7.85545e+00 -2.40754e+01 1.73600e+01 + 2142 2142 1 1.39800e+01 -1.20254e+01 -3.61545e+00 + 2143 2143 1 -5.71545e+00 -2.49454e+01 1.97700e+01 + 2144 2144 1 1.57900e+01 -6.54545e+00 7.10000e-01 + 2145 2145 1 -1.38855e+01 6.23000e+00 -2.18454e+01 + 2146 2146 1 2.05700e+01 -1.73154e+01 2.29700e+01 + 2147 2147 1 -9.67545e+00 -2.51454e+01 2.14100e+01 + 2148 2148 1 -2.59155e+01 -1.03854e+01 -1.21545e+00 + 2149 2149 1 2.55500e+01 -1.68654e+01 -2.29854e+01 + 2150 2150 1 -1.94545e+00 7.36000e+00 7.76000e+00 + 2151 2151 1 2.77600e+01 -2.71754e+01 -4.53545e+00 + 2152 2152 1 2.33000e+01 -1.20754e+01 1.34100e+01 + 2153 2153 1 7.83000e+00 -1.38454e+01 -1.72554e+01 + 2154 2154 1 -4.38545e+00 2.66100e+01 4.43000e+00 + 2155 2155 1 9.25000e+00 -7.59545e+00 -7.34545e+00 + 2156 2156 1 -2.07855e+01 -2.41654e+01 -2.82554e+01 + 2157 2157 1 2.10900e+01 9.25000e+00 -1.73554e+01 + 2158 2158 1 -2.85955e+01 -1.83054e+01 -8.89545e+00 + 2159 2159 1 -1.56155e+01 2.67000e+01 1.29000e+01 + 2160 2160 1 1.15600e+01 7.25000e+00 1.26700e+01 + 2161 2161 1 2.93900e+01 2.68900e+01 -2.36554e+01 + 2162 2162 1 -3.04855e+01 1.95100e+01 1.82900e+01 + 2163 2163 1 -1.34455e+01 1.69200e+01 -2.49754e+01 + 2164 2164 1 -6.33545e+00 -1.03454e+01 -6.15545e+00 + 2165 2165 1 1.97200e+01 2.69700e+01 7.71000e+00 + 2166 2166 1 -3.70545e+00 2.78800e+01 7.84000e+00 + 2167 2167 1 -8.54502e-02 2.54900e+01 2.50000e+00 + 2168 2168 1 -1.83555e+01 6.30000e+00 5.46000e+00 + 2169 2169 1 -1.85155e+01 -1.24545e+00 2.16200e+01 + 2170 2170 1 -1.71655e+01 1.69700e+01 1.28700e+01 + 2171 2171 1 -4.07545e+00 1.21900e+01 -1.84354e+01 + 2172 2172 1 -2.35855e+01 -2.82154e+01 -7.83545e+00 + 2173 2173 1 2.30100e+01 2.81600e+01 3.03000e+00 + 2174 2174 1 -1.63855e+01 2.55500e+01 2.39600e+01 + 2175 2175 1 -4.06545e+00 9.53000e+00 2.19200e+01 + 2176 2176 1 -2.03655e+01 1.22000e+00 -2.19354e+01 + 2177 2177 1 4.84000e+00 -3.08254e+01 -1.68854e+01 + 2178 2178 1 -2.51055e+01 8.94000e+00 -3.04754e+01 + 2179 2179 1 -2.49545e+00 1.49800e+01 2.18200e+01 + 2180 2180 1 2.43100e+01 2.40000e+00 1.10700e+01 + 2181 2181 1 -7.97545e+00 -1.15654e+01 1.98200e+01 + 2182 2182 1 1.63900e+01 -4.84545e+00 -8.47545e+00 + 2183 2183 1 2.44500e+01 2.87600e+01 8.10000e+00 + 2184 2184 1 5.77000e+00 1.44000e+00 4.37000e+00 + 2185 2185 1 2.32800e+01 -4.40545e+00 -1.30354e+01 + 2186 2186 1 -1.29955e+01 2.17000e+01 -2.71854e+01 + 2187 2187 1 2.88200e+01 3.39000e+00 7.64000e+00 + 2188 2188 1 -1.98755e+01 -2.04454e+01 -1.80454e+01 + 2189 2189 1 5.00000e-02 1.46200e+01 -2.02754e+01 + 2190 2190 1 2.56900e+01 -2.12754e+01 2.28500e+01 + 2191 2191 1 1.74500e+01 -2.21354e+01 -4.48545e+00 + 2192 2192 1 1.29900e+01 -1.38554e+01 -1.82754e+01 + 2193 2193 1 1.03100e+01 -2.64354e+01 -1.21454e+01 + 2194 2194 1 -1.58155e+01 7.74000e+00 2.49300e+01 + 2195 2195 1 -1.53255e+01 -2.13854e+01 -8.20545e+00 + 2196 2196 1 5.70000e-01 1.83600e+01 -4.60000e-01 + 2197 2197 1 -2.31855e+01 7.40000e-01 3.36000e+00 + 2198 2198 1 7.31000e+00 -2.01754e+01 2.04200e+01 + 2199 2199 1 2.66500e+01 -1.04354e+01 2.96000e+01 + 2200 2200 1 2.17300e+01 -7.93545e+00 2.90000e+01 + 2201 2201 1 1.74700e+01 -5.86545e+00 3.58000e+00 + 2202 2202 1 -1.95055e+01 -2.37954e+01 -7.48545e+00 + 2203 2203 1 2.19900e+01 4.25000e+00 1.76200e+01 + 2204 2204 1 1.33700e+01 3.98000e+00 -1.72654e+01 + 2205 2205 1 2.51700e+01 5.42000e+00 1.53700e+01 + 2206 2206 1 6.64000e+00 1.21600e+01 9.82000e+00 + 2207 2207 1 -3.07655e+01 2.28500e+01 -4.59545e+00 + 2208 2208 1 -2.04155e+01 -2.57854e+01 -2.01545e+00 + 2209 2209 1 -4.85545e+00 -2.14545e+00 -1.15654e+01 + 2210 2210 1 1.77600e+01 5.91000e+00 2.59500e+01 + 2211 2211 1 -1.93155e+01 2.72000e+00 2.92800e+01 + 2212 2212 1 2.19800e+01 -1.82154e+01 -2.92854e+01 + 2213 2213 1 -1.22655e+01 -2.49954e+01 2.87100e+01 + 2214 2214 1 2.77900e+01 2.06000e+00 -8.24545e+00 + 2215 2215 1 6.11000e+00 1.84700e+01 -1.98454e+01 + 2216 2216 1 2.88500e+01 6.79000e+00 6.02000e+00 + 2217 2217 1 -5.63545e+00 -1.86554e+01 -7.05445e-01 + 2218 2218 1 8.77000e+00 1.27800e+01 -1.90545e+00 + 2219 2219 1 2.22000e+01 5.48000e+00 -5.16545e+00 + 2220 2220 1 -1.39855e+01 1.47700e+01 1.61500e+01 + 2221 2221 1 -1.50955e+01 -1.78154e+01 -2.10154e+01 + 2222 2222 1 -3.07855e+01 -1.27554e+01 3.76000e+00 + 2223 2223 1 -9.31545e+00 -8.39545e+00 2.36300e+01 + 2224 2224 1 2.58000e+00 9.75000e+00 2.13500e+01 + 2225 2225 1 -8.46545e+00 4.01000e+00 -1.66454e+01 + 2226 2226 1 2.34200e+01 7.60000e-01 -2.94545e+00 + 2227 2227 1 1.39800e+01 -2.31754e+01 -2.60254e+01 + 2228 2228 1 1.50400e+01 -9.73545e+00 2.36500e+01 + 2229 2229 1 2.65000e+01 -2.80554e+01 -2.11254e+01 + 2230 2230 1 -1.13755e+01 -2.31354e+01 -2.27545e+00 + 2231 2231 1 -2.71955e+01 1.26500e+01 -1.35454e+01 + 2232 2232 1 5.72000e+00 1.92700e+01 -2.32154e+01 + 2233 2233 1 -1.72555e+01 -2.06954e+01 -5.10545e+00 + 2234 2234 1 -5.07545e+00 9.12000e+00 1.16500e+01 + 2235 2235 1 7.25000e+00 -2.46054e+01 1.10900e+01 + 2236 2236 1 1.20200e+01 -1.41154e+01 2.65100e+01 + 2237 2237 1 1.35400e+01 9.46000e+00 7.16000e+00 + 2238 2238 1 3.68000e+00 -1.28545e+00 -6.55445e-01 + 2239 2239 1 3.09900e+01 -1.59954e+01 -1.34554e+01 + 2240 2240 1 -1.40355e+01 1.10100e+01 -2.57554e+01 + 2241 2241 1 -1.68355e+01 -7.64545e+00 2.46000e+00 + 2242 2242 1 -2.50855e+01 -1.48054e+01 -3.83545e+00 + 2243 2243 1 -1.13155e+01 -2.56154e+01 1.31800e+01 + 2244 2244 1 -2.40545e+00 7.92000e+00 -2.27545e+00 + 2245 2245 1 -3.07755e+01 2.34900e+01 5.98000e+00 + 2246 2246 1 -1.02545e+00 -1.31054e+01 1.03600e+01 + 2247 2247 1 -7.86545e+00 5.83000e+00 2.04200e+01 + 2248 2248 1 -1.41455e+01 3.01800e+01 -1.95454e+01 + 2249 2249 1 -7.88545e+00 2.85500e+01 -3.47545e+00 + 2250 2250 1 -1.93155e+01 2.83000e+00 -1.33554e+01 + 2251 2251 1 7.63000e+00 9.13000e+00 -4.21545e+00 + 2252 2252 1 2.52600e+01 6.34000e+00 -1.04354e+01 + 2253 2253 1 -2.79755e+01 1.45000e+01 3.04800e+01 + 2254 2254 1 -2.62455e+01 2.93000e+00 2.42900e+01 + 2255 2255 1 -7.65450e-01 2.45700e+01 -1.92954e+01 + 2256 2256 1 -1.85255e+01 -2.04254e+01 3.01400e+01 + 2257 2257 1 -1.25055e+01 2.11800e+01 -1.34354e+01 + 2258 2258 1 -2.52855e+01 7.09000e+00 4.40000e+00 + 2259 2259 1 -1.70655e+01 2.59200e+01 -1.84254e+01 + 2260 2260 1 -2.33655e+01 -1.67554e+01 -9.26545e+00 + 2261 2261 1 -2.01555e+01 -1.41854e+01 -2.11545e+00 + 2262 2262 1 -2.50155e+01 7.65000e+00 1.25400e+01 + 2263 2263 1 6.50000e+00 2.95500e+01 -2.35954e+01 + 2264 2264 1 5.98000e+00 -8.04545e+00 -2.56054e+01 + 2265 2265 1 5.15000e+00 8.46000e+00 -2.49454e+01 + 2266 2266 1 2.84000e+01 -6.63545e+00 1.77500e+01 + 2267 2267 1 -5.64545e+00 3.92000e+00 -1.43854e+01 + 2268 2268 1 -2.21655e+01 1.44900e+01 1.03900e+01 + 2269 2269 1 -9.59545e+00 1.05500e+01 -2.36854e+01 + 2270 2270 1 -1.55555e+01 -9.39545e+00 -1.12854e+01 + 2271 2271 1 2.46100e+01 -2.92854e+01 1.39100e+01 + 2272 2272 1 8.20000e+00 -2.14554e+01 3.05500e+01 + 2273 2273 1 -2.97055e+01 2.72000e+01 -2.16754e+01 + 2274 2274 1 1.96200e+01 1.12300e+01 5.52000e+00 + 2275 2275 1 9.16000e+00 2.60500e+01 8.70000e-01 + 2276 2276 1 -2.63255e+01 2.93500e+01 2.36800e+01 + 2277 2277 1 2.01500e+01 -7.54545e+00 -3.03154e+01 + 2278 2278 1 2.15800e+01 1.10100e+01 -1.37154e+01 + 2279 2279 1 1.60600e+01 1.62900e+01 -6.28545e+00 + 2280 2280 1 2.44400e+01 2.08900e+01 -1.73154e+01 + 2281 2281 1 2.57800e+01 -2.01254e+01 -1.41545e+00 + 2282 2282 1 -2.97855e+01 -1.21954e+01 -1.93354e+01 + 2283 2283 1 1.71600e+01 2.50100e+01 -2.17354e+01 + 2284 2284 1 5.39000e+00 1.79700e+01 -2.49545e+00 + 2285 2285 1 -1.08655e+01 2.85400e+01 -1.34254e+01 + 2286 2286 1 -7.19545e+00 1.48300e+01 -7.88545e+00 + 2287 2287 1 1.72700e+01 -1.07854e+01 -1.59954e+01 + 2288 2288 1 2.15500e+01 -8.76545e+00 -1.46154e+01 + 2289 2289 1 2.66500e+01 1.21600e+01 -2.25254e+01 + 2290 2290 1 6.80000e+00 6.22000e+00 1.83100e+01 + 2291 2291 1 -1.35455e+01 2.96200e+01 -2.66054e+01 + 2292 2292 1 -1.39055e+01 -1.74954e+01 -5.57545e+00 + 2293 2293 1 2.06400e+01 2.82000e+00 2.55400e+01 + 2294 2294 1 -2.44855e+01 1.94000e+01 6.83000e+00 + 2295 2295 1 1.15600e+01 1.48000e+01 -4.48545e+00 + 2296 2296 1 8.18000e+00 2.76700e+01 -1.54754e+01 + 2297 2297 1 9.80000e+00 2.74000e+00 -5.06545e+00 + 2298 2298 1 3.56000e+00 1.53300e+01 -2.91654e+01 + 2299 2299 1 2.17000e+00 -1.74545e+00 5.63000e+00 + 2300 2300 1 -6.45450e-01 3.72000e+00 -5.17545e+00 + 2301 2301 1 -2.98155e+01 -1.32054e+01 1.90600e+01 + 2302 2302 1 -3.95545e+00 3.16000e+00 -2.20654e+01 + 2303 2303 1 1.52900e+01 2.05500e+01 -1.49545e+00 + 2304 2304 1 -1.15055e+01 4.39000e+00 1.96600e+01 + 2305 2305 1 -2.42655e+01 -7.97545e+00 -2.41654e+01 + 2306 2306 1 2.00300e+01 -1.21154e+01 -2.10854e+01 + 2307 2307 1 6.78000e+00 1.43400e+01 2.62000e+00 + 2308 2308 1 8.85000e+00 1.95900e+01 9.39000e+00 + 2309 2309 1 -9.07545e+00 -5.23545e+00 2.84555e-01 + 2310 2310 1 2.30700e+01 2.66600e+01 -2.57454e+01 + 2311 2311 1 1.74600e+01 2.92800e+01 2.92200e+01 + 2312 2312 1 -2.60255e+01 -1.14354e+01 8.13000e+00 + 2313 2313 1 2.55400e+01 -2.49454e+01 2.55600e+01 + 2314 2314 1 2.10100e+01 -1.44954e+01 2.69300e+01 + 2315 2315 1 -2.56755e+01 6.68000e+00 -1.53854e+01 + 2316 2316 1 1.20600e+01 1.34700e+01 9.81000e+00 + 2317 2317 1 -1.93755e+01 -6.32545e+00 -1.33545e+00 + 2318 2318 1 -1.05545e+00 -1.87454e+01 -2.48154e+01 + 2319 2319 1 -2.76755e+01 -1.79154e+01 4.79000e+00 + 2320 2320 1 6.57000e+00 -1.90654e+01 -5.63545e+00 + 2321 2321 1 2.22700e+01 2.37800e+01 -6.41545e+00 + 2322 2322 1 -2.48955e+01 2.29100e+01 2.62000e+01 + 2323 2323 1 -1.57655e+01 3.22000e+00 -6.73545e+00 + 2324 2324 1 -2.66655e+01 2.06600e+01 -1.38154e+01 + 2325 2325 1 2.17300e+01 1.53200e+01 -2.11554e+01 + 2326 2326 1 -2.27855e+01 3.01500e+01 -9.53545e+00 + 2327 2327 1 1.93200e+01 4.51000e+00 4.18000e+00 + 2328 2328 1 1.66200e+01 2.72500e+01 -1.27254e+01 + 2329 2329 1 1.94600e+01 -3.77545e+00 7.76000e+00 + 2330 2330 1 2.50700e+01 -2.72454e+01 -7.29545e+00 + 2331 2331 1 -1.34955e+01 2.47200e+01 -6.81545e+00 + 2332 2332 1 1.91000e+00 1.09700e+01 -2.27754e+01 + 2333 2333 1 2.96000e+00 -5.73545e+00 -2.78545e+00 + 2334 2334 1 6.41000e+00 1.15000e+01 -9.14545e+00 + 2335 2335 1 2.45200e+01 -2.56754e+01 8.44000e+00 + 2336 2336 1 3.00000e+01 2.69700e+01 -2.80354e+01 + 2337 2337 1 1.34100e+01 -6.46545e+00 -1.32954e+01 + 2338 2338 1 -1.64155e+01 -9.25545e+00 2.04200e+01 + 2339 2339 1 1.32700e+01 1.66900e+01 -8.65445e-01 + 2340 2340 1 -2.66655e+01 -9.05545e+00 3.00700e+01 + 2341 2341 1 2.17500e+01 -6.26545e+00 2.30300e+01 + 2342 2342 1 -9.50545e+00 -2.70545e+00 -7.15545e+00 + 2343 2343 1 2.51800e+01 -5.48545e+00 3.46000e+00 + 2344 2344 1 -9.18545e+00 -2.29954e+01 -2.56154e+01 + 2345 2345 1 -8.55450e-01 -4.34545e+00 -2.99954e+01 + 2346 2346 1 -2.12955e+01 2.80000e+01 2.33800e+01 + 2347 2347 1 2.24800e+01 1.81300e+01 1.25800e+01 + 2348 2348 1 -2.14545e+00 -1.05545e+00 -7.82545e+00 + 2349 2349 1 2.31700e+01 -6.76545e+00 8.48000e+00 + 2350 2350 1 1.79900e+01 3.02200e+01 1.96900e+01 + 2351 2351 1 1.62700e+01 2.79700e+01 2.25100e+01 + 2352 2352 1 3.00000e+00 2.26700e+01 -3.05354e+01 + 2353 2353 1 -2.52555e+01 7.48000e+00 -2.07454e+01 + 2354 2354 1 -4.48545e+00 1.45400e+01 -9.90545e+00 + 2355 2355 1 2.74300e+01 1.22800e+01 2.38100e+01 + 2356 2356 1 2.70600e+01 2.74200e+01 -4.40000e-01 + 2357 2357 1 2.43000e+01 -2.43754e+01 -2.64954e+01 + 2358 2358 1 3.00000e-02 2.67500e+01 -7.40545e+00 + 2359 2359 1 -1.84555e+01 7.94000e+00 8.91000e+00 + 2360 2360 1 2.84300e+01 -6.44545e+00 1.38300e+01 + 2361 2361 1 1.16900e+01 2.56100e+01 -2.33854e+01 + 2362 2362 1 2.43500e+01 -2.25054e+01 1.37700e+01 + 2363 2363 1 -5.72545e+00 -1.51454e+01 -4.23545e+00 + 2364 2364 1 7.14000e+00 -1.69554e+01 -2.03754e+01 + 2365 2365 1 8.78000e+00 2.72300e+01 1.63000e+01 + 2366 2366 1 -2.32455e+01 2.37700e+01 -3.20000e-01 + 2367 2367 1 5.13000e+00 5.12000e+00 -4.98545e+00 + 2368 2368 1 2.50700e+01 2.53000e+01 1.15700e+01 + 2369 2369 1 2.01800e+01 9.82000e+00 -7.58545e+00 + 2370 2370 1 1.95800e+01 -2.11545e+00 -2.97354e+01 + 2371 2371 1 -1.66155e+01 -2.80454e+01 6.57000e+00 + 2372 2372 1 2.09200e+01 -2.55754e+01 -1.48554e+01 + 2373 2373 1 1.04300e+01 -2.01754e+01 -2.27754e+01 + 2374 2374 1 1.27700e+01 -2.05454e+01 1.56900e+01 + 2375 2375 1 -2.27555e+01 2.99200e+01 1.09000e+00 + 2376 2376 1 1.13700e+01 -2.28454e+01 -8.52545e+00 + 2377 2377 1 1.64000e+01 2.79000e+00 2.51700e+01 + 2378 2378 1 -2.21255e+01 2.82500e+01 8.29000e+00 + 2379 2379 1 2.01700e+01 1.14600e+01 2.05800e+01 + 2380 2380 1 7.60000e-01 1.95000e+01 1.92900e+01 + 2381 2381 1 2.45000e+00 -3.77545e+00 2.80000e+00 + 2382 2382 1 -2.22155e+01 -2.76854e+01 -1.62254e+01 + 2383 2383 1 -4.60545e+00 -2.18545e+00 8.36000e+00 + 2384 2384 1 1.74400e+01 5.72000e+00 -2.16454e+01 + 2385 2385 1 -1.91355e+01 1.19600e+01 9.58000e+00 + 2386 2386 1 -3.02545e+00 -8.32545e+00 1.10400e+01 + 2387 2387 1 -2.87155e+01 2.05000e+00 -1.14454e+01 + 2388 2388 1 -2.03755e+01 -4.75545e+00 1.07900e+01 + 2389 2389 1 4.50000e+00 -2.02754e+01 1.12000e+01 + 2390 2390 1 -1.96655e+01 -2.01954e+01 1.81300e+01 + 2391 2391 1 1.72000e+00 -2.16754e+01 3.50000e+00 + 2392 2392 1 -1.57555e+01 1.90900e+01 2.89600e+01 + 2393 2393 1 1.55600e+01 2.06100e+01 2.57500e+01 + 2394 2394 1 6.97000e+00 -2.16654e+01 2.38000e+01 + 2395 2395 1 -2.48545e+00 -1.44545e+00 -1.68654e+01 + 2396 2396 1 -3.06545e+00 2.52600e+01 2.52100e+01 + 2397 2397 1 3.32000e+00 -3.94545e+00 2.62800e+01 + 2398 2398 1 1.88600e+01 9.49000e+00 1.72100e+01 + 2399 2399 1 6.42000e+00 2.79300e+01 -6.67545e+00 + 2400 2400 1 5.25000e+00 -1.34954e+01 1.53800e+01 + 2401 2401 1 1.66900e+01 -2.41354e+01 -1.38754e+01 + 2402 2402 1 -2.30155e+01 -1.76754e+01 -9.35445e-01 + 2403 2403 1 2.81000e+00 5.18000e+00 1.86400e+01 + 2404 2404 1 -2.76855e+01 -1.80545e+00 -7.64545e+00 + 2405 2405 1 1.40400e+01 -1.42254e+01 -2.59354e+01 + 2406 2406 1 2.13000e+01 7.99000e+00 -2.88654e+01 + 2407 2407 1 4.02000e+00 5.24000e+00 1.40900e+01 + 2408 2408 1 1.12100e+01 4.18000e+00 9.61000e+00 + 2409 2409 1 2.87000e+00 2.76600e+01 2.08300e+01 + 2410 2410 1 -9.44545e+00 3.06100e+01 -2.84154e+01 + 2411 2411 1 2.43000e+01 -2.27545e+00 7.06000e+00 + 2412 2412 1 -1.56855e+01 2.43900e+01 2.71800e+01 + 2413 2413 1 -1.99855e+01 2.12400e+01 2.83900e+01 + 2414 2414 1 -3.07955e+01 -2.84054e+01 -2.28545e+00 + 2415 2415 1 1.16200e+01 1.43600e+01 2.65300e+01 + 2416 2416 1 -2.83055e+01 2.40000e+00 2.97400e+01 + 2417 2417 1 6.02000e+00 3.05500e+01 1.41000e+01 + 2418 2418 1 1.39900e+01 -1.74254e+01 2.70700e+01 + 2419 2419 1 1.45900e+01 2.33000e+01 -1.56854e+01 + 2420 2420 1 7.22000e+00 1.47900e+01 2.71200e+01 + 2421 2421 1 -1.65545e+00 9.43000e+00 3.00000e+01 + 2422 2422 1 2.05000e+01 2.14800e+01 2.82000e+00 + 2423 2423 1 -1.36955e+01 -1.38254e+01 -7.32545e+00 + 2424 2424 1 2.80600e+01 -3.98545e+00 1.47000e+00 + 2425 2425 1 -8.25545e+00 3.03100e+01 -1.52754e+01 + 2426 2426 1 2.63000e+01 2.34900e+01 -3.08354e+01 + 2427 2427 1 1.47100e+01 -1.81545e+00 -1.96354e+01 + 2428 2428 1 2.92100e+01 3.91000e+00 -1.43545e+00 + 2429 2429 1 3.02900e+01 -1.98454e+01 -3.98545e+00 + 2430 2430 1 -5.95545e+00 3.73000e+00 -8.50545e+00 + 2431 2431 1 -1.69155e+01 6.19000e+00 3.04300e+01 + 2432 2432 1 -1.04055e+01 1.15000e+01 -3.07454e+01 + 2433 2433 1 1.34000e+00 -2.81854e+01 1.17800e+01 + 2434 2434 1 4.70000e-01 2.57000e+00 -9.66545e+00 + 2435 2435 1 9.77000e+00 -9.08545e+00 -9.75445e-01 + 2436 2436 1 2.26500e+01 -1.37545e+00 2.27500e+01 + 2437 2437 1 -7.61545e+00 -1.60554e+01 1.28600e+01 + 2438 2438 1 -1.38655e+01 -2.36254e+01 6.92000e+00 + 2439 2439 1 -5.26545e+00 2.66800e+01 -1.54454e-02 + 2440 2440 1 2.10800e+01 -3.02654e+01 1.74900e+01 + 2441 2441 1 -9.28545e+00 5.37000e+00 2.83200e+01 + 2442 2442 1 -2.09955e+01 -1.78854e+01 -2.83754e+01 + 2443 2443 1 -2.33855e+01 2.21600e+01 -2.41954e+01 + 2444 2444 1 1.70000e+00 -2.10454e+01 9.08000e+00 + 2445 2445 1 5.41000e+00 3.10100e+01 2.12800e+01 + 2446 2446 1 -1.89545e+00 -2.22454e+01 -2.46154e+01 + 2447 2447 1 -2.23855e+01 1.60600e+01 -1.73054e+01 + 2448 2448 1 0.00000e+00 1.14000e+01 8.34000e+00 + 2449 2449 1 -2.38055e+01 1.22900e+01 -1.24254e+01 + 2450 2450 1 -9.13545e+00 2.80100e+01 -8.04545e+00 + 2451 2451 1 -2.53955e+01 5.66000e+00 -9.85545e+00 + 2452 2452 1 1.24000e+00 -1.46454e+01 1.38000e+01 + 2453 2453 1 1.55800e+01 -1.92054e+01 -6.92545e+00 + 2454 2454 1 -2.39055e+01 2.14500e+01 9.28000e+00 + 2455 2455 1 9.10000e+00 -2.29654e+01 -2.76054e+01 + 2456 2456 1 1.47400e+01 -1.52654e+01 -5.68545e+00 + 2457 2457 1 2.52000e+01 -2.98754e+01 -3.01254e+01 + 2458 2458 1 -5.72545e+00 1.19700e+01 1.52700e+01 + 2459 2459 1 -2.35855e+01 1.24400e+01 -1.93554e+01 + 2460 2460 1 -2.15655e+01 -1.56254e+01 1.42700e+01 + 2461 2461 1 1.30000e+00 8.94000e+00 -1.39054e+01 + 2462 2462 1 2.11000e+00 2.45800e+01 -6.85445e-01 + 2463 2463 1 -1.42255e+01 -1.86154e+01 -8.55445e-01 + 2464 2464 1 -2.48955e+01 -2.38154e+01 -1.70054e+01 + 2465 2465 1 1.53500e+01 -3.53545e+00 1.22400e+01 + 2466 2466 1 -1.49055e+01 3.45000e+00 -2.90454e+01 + 2467 2467 1 -1.21545e+00 -3.08154e+01 9.53000e+00 + 2468 2468 1 -2.10855e+01 1.01900e+01 -2.01354e+01 + 2469 2469 1 -1.79155e+01 -1.39654e+01 -2.76854e+01 + 2470 2470 1 -2.26855e+01 2.89000e+00 -1.96254e+01 + 2471 2471 1 -2.71655e+01 -1.89354e+01 1.59700e+01 + 2472 2472 1 4.56000e+00 1.10000e-01 2.60200e+01 + 2473 2473 1 1.43100e+01 -1.03854e+01 1.00700e+01 + 2474 2474 1 -2.18755e+01 2.62700e+01 -3.00554e+01 + 2475 2475 1 2.33700e+01 -2.06454e+01 -4.30545e+00 + 2476 2476 1 7.68000e+00 5.30000e-01 1.42800e+01 + 2477 2477 1 9.41000e+00 4.83000e+00 -1.61654e+01 + 2478 2478 1 1.92100e+01 6.84000e+00 6.71000e+00 + 2479 2479 1 1.35600e+01 -2.63654e+01 2.47600e+01 + 2480 2480 1 6.48000e+00 5.47000e+00 -3.05754e+01 + 2481 2481 1 1.68800e+01 -1.59254e+01 -2.66554e+01 + 2482 2482 1 7.69000e+00 2.89600e+01 -1.85754e+01 + 2483 2483 1 -2.06055e+01 1.30400e+01 -2.26654e+01 + 2484 2484 1 7.78000e+00 1.75100e+01 -1.57754e+01 + 2485 2485 1 7.59000e+00 -9.68545e+00 3.03100e+01 + 2486 2486 1 -3.04655e+01 -2.75554e+01 -2.73554e+01 + 2487 2487 1 -2.33255e+01 2.94500e+01 -2.39954e+01 + 2488 2488 1 1.32100e+01 2.24900e+01 1.94500e+01 + 2489 2489 1 2.46500e+01 -2.09354e+01 6.67000e+00 + 2490 2490 1 -2.42555e+01 1.60800e+01 1.39400e+01 + 2491 2491 1 -2.91855e+01 -8.43545e+00 2.32500e+01 + 2492 2492 1 2.81900e+01 3.17000e+00 2.42000e+01 + 2493 2493 1 -2.47355e+01 1.11400e+01 -2.31454e+01 + 2494 2494 1 -2.98455e+01 6.67000e+00 2.34500e+01 + 2495 2495 1 1.05700e+01 4.19000e+00 2.24900e+01 + 2496 2496 1 2.57900e+01 7.07000e+00 -2.83454e+01 + 2497 2497 1 -5.55545e+00 1.41600e+01 2.53600e+01 + 2498 2498 1 -1.19855e+01 -2.52754e+01 -2.81154e+01 + 2499 2499 1 2.19000e+00 -3.04154e+01 2.90800e+01 + 2500 2500 1 5.98000e+00 -2.65154e+01 -5.44540e-03 + diff --git a/examples/USER/misc/local_density/methanol_implicit_water/methanol_implicit_water.in b/examples/USER/misc/local_density/methanol_implicit_water/methanol_implicit_water.in new file mode 100644 index 0000000000..ef92fbe655 --- /dev/null +++ b/examples/USER/misc/local_density/methanol_implicit_water/methanol_implicit_water.in @@ -0,0 +1,68 @@ +# LAMMPS input file for 50.0% methanol mole fraction solution +# with 2500 methanol molecules in implicit water. +# +# +# Author: David Rosenberger, van der Vegt Group, TU Darmstadt +# +# Refer: Rosenberger, Sanyal, Shell, van der Vegt, J. Chem. Theory Comput. 15, 2881-2895 (2019) + + +# Initialize simulation box +dimension 3 +boundary p p p +units real +atom_style molecular + +# Set potential styles +pair_style hybrid/overlay table spline 500 local/density + +# Read molecule data and set initial velocities +read_data methanol_implicit_water.data +velocity all create 3.0000e+02 12142 rot yes dist gaussian + +# Assign potentials +pair_coeff 1 1 table methanol_implicit_water.pair.table PairMM +pair_coeff * * local/density methanol_implicit_water.localdensity.table + + + + +#Recentering during minimization and equilibration +fix recentering all recenter 0.0 0.0 0.0 units box + +#Thermostat & time integration +timestep 1.0 +thermo 100 +thermo_style custom etotal ke pe temp evdwl + +#minimization +minimize 1.e-4 0.0 1000 1000 + +#set up integration parameters +fix timeintegration all nve +fix thermostat all langevin 3.0000e+02 3.0000e+02 1.0000e+02 59915 + +#Equilibration (for realistic results, run for 2000000 steps) +reset_timestep 0 +thermo 200 +thermo_style custom etotal ke pe temp evdwl + +#run equilibration +run 2000 + +#turn off recentering during production run +unfix recentering + + +#setup trajectory output +dump myDump all custom 100 methanol_implicit_water.lammpstrj.gz id type x y z element +dump_modify myDump element M +dump_modify myDump sort id + +#run production (for realistic results, run for 10000000 steps) +reset_timestep 0 +thermo 1000 +thermo_style custom etotal ke pe temp evdwl +run 10000 + + diff --git a/examples/USER/misc/local_density/methanol_implicit_water/methanol_implicit_water.localdensity.table b/examples/USER/misc/local_density/methanol_implicit_water/methanol_implicit_water.localdensity.table new file mode 100644 index 0000000000..b9b4a082bc --- /dev/null +++ b/examples/USER/misc/local_density/methanol_implicit_water/methanol_implicit_water.localdensity.table @@ -0,0 +1,509 @@ +#LOCAL DENSITY POTENTIALS + +1 500 + + 5.3000000e+00 6.3000000e+00 +1 +1 + 0.0000000e+00 2.6000000e+01 5.2104208e-02 + 1.4810000e-01 + 1.4810000e-01 + 1.4810000e-01 + 1.4810000e-01 + 1.4810000e-01 + 1.4810000e-01 + 1.4810000e-01 + 1.4810000e-01 + 1.4810000e-01 + 1.4810000e-01 + 1.4810000e-01 + 1.4810000e-01 + 1.4810000e-01 + 1.4810000e-01 + 1.4810000e-01 + 1.4810000e-01 + 1.4810000e-01 + 1.4810000e-01 + 1.4810000e-01 + 1.4810000e-01 + 1.4810000e-01 + 1.4810000e-01 + 1.4810000e-01 + 1.4810000e-01 + 1.4810000e-01 + 1.4810000e-01 + 1.4810000e-01 + 1.4810000e-01 + 1.4810000e-01 + 1.4810000e-01 + 1.4810000e-01 + 1.4810000e-01 + 1.4810000e-01 + 1.4810000e-01 + 1.4810000e-01 + 1.4810000e-01 + 1.4810000e-01 + 1.4810000e-01 + 1.4810000e-01 + 1.4810000e-01 + 1.4810000e-01 + 1.4810000e-01 + 1.4810000e-01 + 1.4810000e-01 + 1.4810000e-01 + 1.4810000e-01 + 1.4810000e-01 + 1.4810000e-01 + 1.4810000e-01 + 1.4810000e-01 + 1.4810000e-01 + 1.4810000e-01 + 1.4810000e-01 + 1.4810000e-01 + 1.4810000e-01 + 1.4810000e-01 + 1.4810000e-01 + 1.4810000e-01 + 1.4810000e-01 + 1.4810000e-01 + 1.4810000e-01 + 1.4810000e-01 + 1.4810000e-01 + 1.4810000e-01 + 1.4810000e-01 + 1.4810000e-01 + 1.4810000e-01 + 1.4810000e-01 + 1.4810000e-01 + 1.4810000e-01 + 1.4810000e-01 + 1.4810000e-01 + 1.4810000e-01 + 1.4810000e-01 + 1.4810000e-01 + 1.4810000e-01 + 1.4810000e-01 + 1.4810000e-01 + 1.4810000e-01 + 1.4810000e-01 + 1.4810000e-01 + 1.4810000e-01 + 1.4810000e-01 + 1.4807157e-01 + 1.4782582e-01 + 1.4711763e-01 + 1.4570179e-01 + 1.4333312e-01 + 1.3976643e-01 + 1.3478059e-01 + 1.2856173e-01 + 1.2163552e-01 + 1.1453802e-01 + 1.0780525e-01 + 1.0197328e-01 + 9.7575837e-02 + 9.4875548e-02 + 9.3613063e-02 + 9.3469690e-02 + 9.4126738e-02 + 9.5265515e-02 + 9.6567329e-02 + 9.7735007e-02 + 9.8575495e-02 + 9.8927186e-02 + 9.8628481e-02 + 9.7517779e-02 + 9.5433481e-02 + 9.2235018e-02 + 8.8072568e-02 + 8.3308496e-02 + 7.8309990e-02 + 7.3444241e-02 + 6.9078438e-02 + 6.5577180e-02 + 6.3110699e-02 + 6.1523109e-02 + 6.0627357e-02 + 6.0236386e-02 + 6.0163144e-02 + 6.0220573e-02 + 6.0233006e-02 + 6.0072080e-02 + 5.9621717e-02 + 5.8765838e-02 + 5.7388366e-02 + 5.5373224e-02 + 5.2623498e-02 + 4.9261717e-02 + 4.5550390e-02 + 4.1754290e-02 + 3.8138193e-02 + 3.4966871e-02 + 3.2501662e-02 + 3.0825931e-02 + 2.9762256e-02 + 2.9112455e-02 + 2.8678347e-02 + 2.8261751e-02 + 2.7664487e-02 + 2.6737788e-02 + 2.5509284e-02 + 2.4045951e-02 + 2.2414767e-02 + 2.0682707e-02 + 1.8916748e-02 + 1.7179645e-02 + 1.5493687e-02 + 1.3858641e-02 + 1.2274032e-02 + 1.0739385e-02 + 9.2542252e-03 + 7.8179601e-03 + 6.4255437e-03 + 5.0662231e-03 + 3.7288715e-03 + 2.4023618e-03 + 1.0755673e-03 +-2.6263394e-04 +-1.6141074e-03 +-2.9522803e-03 +-4.2451362e-03 +-5.4606586e-03 +-6.5668312e-03 +-7.5316377e-03 +-8.3294239e-03 +-8.9860017e-03 +-9.5521117e-03 +-1.0078658e-02 +-1.0616544e-02 +-1.1216675e-02 +-1.1929199e-02 +-1.2782684e-02 +-1.3781467e-02 +-1.4928602e-02 +-1.6227139e-02 +-1.7680132e-02 +-1.9290577e-02 +-2.1031059e-02 +-2.2793537e-02 +-2.4456753e-02 +-2.5899451e-02 +-2.7000374e-02 +-2.7638267e-02 +-2.7719868e-02 +-2.7344330e-02 +-2.6691680e-02 +-2.5942229e-02 +-2.5276286e-02 +-2.4874159e-02 +-2.4909370e-02 +-2.5403835e-02 +-2.6230347e-02 +-2.7255409e-02 +-2.8345523e-02 +-2.9367192e-02 +-3.0187085e-02 +-3.0712590e-02 +-3.0944560e-02 +-3.0896910e-02 +-3.0583557e-02 +-3.0018416e-02 +-2.9215405e-02 +-2.8195478e-02 +-2.7020910e-02 +-2.5768997e-02 +-2.4517057e-02 +-2.3342408e-02 +-2.2322368e-02 +-2.1532406e-02 +-2.1015034e-02 +-2.0784355e-02 +-2.0853543e-02 +-2.1235771e-02 +-2.1944214e-02 +-2.2991215e-02 +-2.4278363e-02 +-2.5486458e-02 +-2.6270119e-02 +-2.6283964e-02 +-2.5182614e-02 +-2.2620686e-02 +-1.8367122e-02 +-1.2765600e-02 +-6.3400224e-03 + 3.8564733e-04 + 6.8874449e-03 + 1.2641406e-02 + 1.7151899e-02 + 2.0334733e-02 + 2.2416173e-02 + 2.3630118e-02 + 2.4210466e-02 + 2.4391115e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + 2.4405000e-02 + diff --git a/examples/USER/misc/local_density/methanol_implicit_water/methanol_implicit_water.pair.table b/examples/USER/misc/local_density/methanol_implicit_water/methanol_implicit_water.pair.table new file mode 100644 index 0000000000..b74fe398e8 --- /dev/null +++ b/examples/USER/misc/local_density/methanol_implicit_water/methanol_implicit_water.pair.table @@ -0,0 +1,1012 @@ + +PairMM +N 500 R 2.00000e-02 1.50000e+01 + +1 2.00000e-02 9.19945e+01 2.97871e+01 +2 5.00200e-02 9.11003e+01 2.97871e+01 +3 8.00401e-02 9.02061e+01 2.97871e+01 +4 1.10060e-01 8.93119e+01 2.97871e+01 +5 1.40080e-01 8.84177e+01 2.97871e+01 +6 1.70100e-01 8.75235e+01 2.97871e+01 +7 2.00120e-01 8.66293e+01 2.97871e+01 +8 2.30140e-01 8.57350e+01 2.97871e+01 +9 2.60160e-01 8.48408e+01 2.97871e+01 +10 2.90180e-01 8.39466e+01 2.97871e+01 +11 3.20200e-01 8.30524e+01 2.97871e+01 +12 3.50220e-01 8.21582e+01 2.97871e+01 +13 3.80240e-01 8.12640e+01 2.97871e+01 +14 4.10261e-01 8.03698e+01 2.97871e+01 +15 4.40281e-01 7.94756e+01 2.97871e+01 +16 4.70301e-01 7.85814e+01 2.97871e+01 +17 5.00321e-01 7.76872e+01 2.97871e+01 +18 5.30341e-01 7.67929e+01 2.97871e+01 +19 5.60361e-01 7.58987e+01 2.97871e+01 +20 5.90381e-01 7.50045e+01 2.97871e+01 +21 6.20401e-01 7.41103e+01 2.97871e+01 +22 6.50421e-01 7.32161e+01 2.97871e+01 +23 6.80441e-01 7.23219e+01 2.97871e+01 +24 7.10461e-01 7.14277e+01 2.97871e+01 +25 7.40481e-01 7.05335e+01 2.97871e+01 +26 7.70501e-01 6.96393e+01 2.97871e+01 +27 8.00521e-01 6.87450e+01 2.97871e+01 +28 8.30541e-01 6.78508e+01 2.97871e+01 +29 8.60561e-01 6.69566e+01 2.97871e+01 +30 8.90581e-01 6.60624e+01 2.97871e+01 +31 9.20601e-01 6.51682e+01 2.97871e+01 +32 9.50621e-01 6.42740e+01 2.97871e+01 +33 9.80641e-01 6.33798e+01 2.97871e+01 +34 1.01066e+00 6.24856e+01 2.97871e+01 +35 1.04068e+00 6.15914e+01 2.97871e+01 +36 1.07070e+00 6.06972e+01 2.97871e+01 +37 1.10072e+00 5.98029e+01 2.97871e+01 +38 1.13074e+00 5.89087e+01 2.97871e+01 +39 1.16076e+00 5.80145e+01 2.97871e+01 +40 1.19078e+00 5.71203e+01 2.97871e+01 +41 1.22080e+00 5.62261e+01 2.97871e+01 +42 1.25082e+00 5.53319e+01 2.97871e+01 +43 1.28084e+00 5.44377e+01 2.97871e+01 +44 1.31086e+00 5.35435e+01 2.97871e+01 +45 1.34088e+00 5.26493e+01 2.97871e+01 +46 1.37090e+00 5.17551e+01 2.97871e+01 +47 1.40092e+00 5.08608e+01 2.97871e+01 +48 1.43094e+00 4.99666e+01 2.97871e+01 +49 1.46096e+00 4.90724e+01 2.97871e+01 +50 1.49098e+00 4.81782e+01 2.97871e+01 +51 1.52100e+00 4.72840e+01 2.97871e+01 +52 1.55102e+00 4.63898e+01 2.97871e+01 +53 1.58104e+00 4.54956e+01 2.97871e+01 +54 1.61106e+00 4.46014e+01 2.97871e+01 +55 1.64108e+00 4.37072e+01 2.97871e+01 +56 1.67110e+00 4.28130e+01 2.97871e+01 +57 1.70112e+00 4.19187e+01 2.97871e+01 +58 1.73114e+00 4.10245e+01 2.97871e+01 +59 1.76116e+00 4.01303e+01 2.97871e+01 +60 1.79118e+00 3.92361e+01 2.97871e+01 +61 1.82120e+00 3.83419e+01 2.97871e+01 +62 1.85122e+00 3.74477e+01 2.97871e+01 +63 1.88124e+00 3.65535e+01 2.97871e+01 +64 1.91126e+00 3.56593e+01 2.97871e+01 +65 1.94128e+00 3.47651e+01 2.97871e+01 +66 1.97130e+00 3.38709e+01 2.97871e+01 +67 2.00132e+00 3.29766e+01 2.97871e+01 +68 2.03134e+00 3.20824e+01 2.97871e+01 +69 2.06136e+00 3.11882e+01 2.97871e+01 +70 2.09138e+00 3.02940e+01 2.97871e+01 +71 2.12140e+00 2.93998e+01 2.97871e+01 +72 2.15142e+00 2.85056e+01 2.97871e+01 +73 2.18144e+00 2.76114e+01 2.97871e+01 +74 2.21146e+00 2.67172e+01 2.97871e+01 +75 2.24148e+00 2.58230e+01 2.97871e+01 +76 2.27150e+00 2.49288e+01 2.97871e+01 +77 2.30152e+00 2.40345e+01 2.97871e+01 +78 2.33154e+00 2.31403e+01 2.97871e+01 +79 2.36156e+00 2.22461e+01 2.97871e+01 +80 2.39158e+00 2.13519e+01 2.97871e+01 +81 2.42160e+00 2.04577e+01 2.97871e+01 +82 2.45162e+00 1.95635e+01 2.97871e+01 +83 2.48164e+00 1.86693e+01 2.97871e+01 +84 2.51166e+00 1.77751e+01 2.97871e+01 +85 2.54168e+00 1.68809e+01 2.97871e+01 +86 2.57170e+00 1.59867e+01 2.97871e+01 +87 2.60172e+00 1.50924e+01 2.97871e+01 +88 2.63174e+00 1.41982e+01 2.97871e+01 +89 2.66176e+00 1.33040e+01 2.97871e+01 +90 2.69178e+00 1.24098e+01 2.97871e+01 +91 2.72180e+00 1.15156e+01 2.97871e+01 +92 2.75182e+00 1.06214e+01 2.97869e+01 +93 2.78184e+00 9.72719e+00 2.97870e+01 +94 2.81186e+00 8.83299e+00 2.97872e+01 +95 2.84188e+00 7.94090e+00 2.95697e+01 +96 2.87190e+00 7.06217e+00 2.88975e+01 +97 2.90192e+00 6.21045e+00 2.77704e+01 +98 2.93194e+00 5.39938e+00 2.61886e+01 +99 2.96196e+00 4.64263e+00 2.41520e+01 +100 2.99198e+00 3.95385e+00 2.16606e+01 +101 3.02200e+00 3.34529e+00 1.89044e+01 +102 3.05202e+00 2.81637e+00 1.63756e+01 +103 3.08204e+00 2.35957e+00 1.40993e+01 +104 3.11206e+00 1.96731e+00 1.20757e+01 +105 3.14208e+00 1.63202e+00 1.03046e+01 +106 3.17210e+00 1.34610e+00 8.78617e+00 +107 3.20212e+00 1.10205e+00 7.50421e+00 +108 3.23214e+00 8.94281e-01 6.35707e+00 +109 3.26216e+00 7.19196e-01 5.32692e+00 +110 3.29218e+00 5.73281e-01 4.41377e+00 +111 3.32220e+00 4.53023e-01 3.61760e+00 +112 3.35222e+00 3.54909e-01 2.93842e+00 +113 3.38224e+00 2.75435e-01 2.37392e+00 +114 3.41226e+00 2.11828e-01 1.86993e+00 +115 3.44228e+00 1.62787e-01 1.40363e+00 +116 3.47230e+00 1.27177e-01 9.75004e-01 +117 3.50232e+00 1.03870e-01 5.84063e-01 +118 3.53234e+00 9.17332e-02 2.30805e-01 +119 3.56236e+00 8.96354e-02 -8.47700e-02 +120 3.59238e+00 9.62368e-02 -3.41692e-01 +121 3.62240e+00 1.09350e-01 -5.18612e-01 +122 3.65242e+00 1.26574e-01 -6.15527e-01 +123 3.68244e+00 1.45506e-01 -6.32440e-01 +124 3.71246e+00 1.63745e-01 -5.69349e-01 +125 3.74248e+00 1.78889e-01 -4.26254e-01 +126 3.77251e+00 1.88729e-01 -2.28844e-01 +127 3.80253e+00 1.92736e-01 -3.99828e-02 +128 3.83255e+00 1.91244e-01 1.37465e-01 +129 3.86257e+00 1.84597e-01 3.03500e-01 +130 3.89259e+00 1.73136e-01 4.58121e-01 +131 3.92261e+00 1.57205e-01 6.01329e-01 +132 3.95263e+00 1.37160e-01 7.30471e-01 +133 3.98265e+00 1.13658e-01 8.29879e-01 +134 4.01267e+00 8.76572e-02 8.96980e-01 +135 4.04269e+00 6.01267e-02 9.31775e-01 +136 4.07271e+00 3.20367e-02 9.34263e-01 +137 4.10273e+00 4.35682e-03 9.04444e-01 +138 4.13275e+00 -2.19459e-02 8.43457e-01 +139 4.16277e+00 -4.62335e-02 7.74951e-01 +140 4.19279e+00 -6.84930e-02 7.08340e-01 +141 4.22281e+00 -8.87812e-02 6.43625e-01 +142 4.25283e+00 -1.07155e-01 5.80805e-01 +143 4.28285e+00 -1.23672e-01 5.19881e-01 +144 4.31287e+00 -1.38388e-01 4.60852e-01 +145 4.34289e+00 -1.51360e-01 4.03717e-01 +146 4.37291e+00 -1.62646e-01 3.48474e-01 +147 4.40293e+00 -1.72302e-01 2.95121e-01 +148 4.43295e+00 -1.80384e-01 2.43661e-01 +149 4.46297e+00 -1.86950e-01 1.94092e-01 +150 4.49299e+00 -1.92056e-01 1.46414e-01 +151 4.52301e+00 -1.95763e-01 1.01113e-01 +152 4.55303e+00 -1.98162e-01 5.93143e-02 +153 4.58305e+00 -1.99360e-01 2.10616e-02 +154 4.61307e+00 -1.99462e-01 -1.36446e-02 +155 4.64309e+00 -1.98576e-01 -4.48045e-02 +156 4.67311e+00 -1.96808e-01 -7.24180e-02 +157 4.70313e+00 -1.94262e-01 -9.67717e-02 +158 4.73315e+00 -1.91013e-01 -1.19452e-01 +159 4.76317e+00 -1.87105e-01 -1.40703e-01 +160 4.79319e+00 -1.82580e-01 -1.60523e-01 +161 4.82321e+00 -1.77481e-01 -1.78913e-01 +162 4.85323e+00 -1.71852e-01 -1.95873e-01 +163 4.88325e+00 -1.65735e-01 -2.11359e-01 +164 4.91327e+00 -1.59186e-01 -2.24534e-01 +165 4.94329e+00 -1.52281e-01 -2.35084e-01 +166 4.97331e+00 -1.45098e-01 -2.43010e-01 +167 5.00333e+00 -1.37717e-01 -2.48312e-01 +168 5.03335e+00 -1.30215e-01 -2.50989e-01 +169 5.06337e+00 -1.22673e-01 -2.51043e-01 +170 5.09339e+00 -1.15153e-01 -2.50013e-01 +171 5.12341e+00 -1.07660e-01 -2.49271e-01 +172 5.15343e+00 -1.00184e-01 -2.48818e-01 +173 5.18345e+00 -9.27178e-02 -2.48655e-01 +174 5.21347e+00 -8.52520e-02 -2.48780e-01 +175 5.24349e+00 -7.77781e-02 -2.49195e-01 +176 5.27351e+00 -7.02942e-02 -2.49037e-01 +177 5.30353e+00 -6.28510e-02 -2.46424e-01 +178 5.33355e+00 -5.55241e-02 -2.41290e-01 +179 5.36357e+00 -4.83892e-02 -2.33634e-01 +180 5.39359e+00 -4.15219e-02 -2.23458e-01 +181 5.42361e+00 -3.49980e-02 -2.10761e-01 +182 5.45363e+00 -2.88902e-02 -1.96059e-01 +183 5.48365e+00 -2.32177e-02 -1.82031e-01 +184 5.51367e+00 -1.79505e-02 -1.69060e-01 +185 5.54369e+00 -1.30568e-02 -1.57145e-01 +186 5.57371e+00 -8.50494e-03 -1.46287e-01 +187 5.60373e+00 -4.26314e-03 -1.36487e-01 +188 5.63375e+00 -2.99795e-04 -1.27712e-01 +189 5.66377e+00 3.40924e-03 -1.19447e-01 +190 5.69379e+00 6.87508e-03 -1.11509e-01 +191 5.72381e+00 1.01075e-02 -1.03898e-01 +192 5.75383e+00 1.31164e-02 -9.66146e-02 +193 5.78385e+00 1.59115e-02 -8.96578e-02 +194 5.81387e+00 1.85027e-02 -8.30284e-02 +195 5.84389e+00 2.09020e-02 -7.69319e-02 +196 5.87391e+00 2.31288e-02 -7.15406e-02 +197 5.90393e+00 2.52043e-02 -6.68545e-02 +198 5.93395e+00 2.71498e-02 -6.28736e-02 +199 5.96397e+00 2.89863e-02 -5.95979e-02 +200 5.99399e+00 3.07351e-02 -5.70274e-02 +201 6.02401e+00 3.24185e-02 -5.53056e-02 +202 6.05403e+00 3.40672e-02 -5.47288e-02 +203 6.08405e+00 3.57159e-02 -5.53060e-02 +204 6.11407e+00 3.73993e-02 -5.70373e-02 +205 6.14409e+00 3.91520e-02 -5.99226e-02 +206 6.17411e+00 4.10086e-02 -6.39619e-02 +207 6.20413e+00 4.29997e-02 -6.84095e-02 +208 6.23415e+00 4.50810e-02 -6.96340e-02 +209 6.26417e+00 4.71434e-02 -6.71518e-02 +210 6.29419e+00 4.90757e-02 -6.09627e-02 +211 6.32421e+00 5.07666e-02 -5.10669e-02 +212 6.35423e+00 5.21047e-02 -3.74643e-02 +213 6.38425e+00 5.29795e-02 -2.03798e-02 +214 6.41427e+00 5.33308e-02 -3.19178e-03 +215 6.44429e+00 5.31815e-02 1.29657e-02 +216 6.47431e+00 5.25626e-02 2.80925e-02 +217 6.50433e+00 5.15051e-02 4.21888e-02 +218 6.53435e+00 5.00399e-02 5.52546e-02 +219 6.56437e+00 4.81979e-02 6.72903e-02 +220 6.59439e+00 4.60085e-02 7.84476e-02 +221 6.62441e+00 4.34955e-02 8.88459e-02 +222 6.65443e+00 4.06818e-02 9.84851e-02 +223 6.68445e+00 3.75901e-02 1.07365e-01 +224 6.71447e+00 3.42431e-02 1.15487e-01 +225 6.74449e+00 3.06638e-02 1.22849e-01 +226 6.77451e+00 2.68771e-02 1.29179e-01 +227 6.80453e+00 2.29237e-02 1.33943e-01 +228 6.83455e+00 1.88510e-02 1.37127e-01 +229 6.86457e+00 1.47064e-02 1.38733e-01 +230 6.89459e+00 1.05373e-02 1.38759e-01 +231 6.92461e+00 6.39110e-03 1.37205e-01 +232 6.95463e+00 2.31403e-03 1.34290e-01 +233 6.98465e+00 -1.66868e-03 1.31007e-01 +234 7.01467e+00 -5.54918e-03 1.27480e-01 +235 7.04469e+00 -9.32014e-03 1.23709e-01 +236 7.07471e+00 -1.29742e-02 1.19694e-01 +237 7.10473e+00 -1.65041e-02 1.15435e-01 +238 7.13475e+00 -1.99024e-02 1.10910e-01 +239 7.16477e+00 -2.31572e-02 1.05819e-01 +240 7.19479e+00 -2.62492e-02 1.00067e-01 +241 7.22481e+00 -2.91586e-02 9.36550e-02 +242 7.25483e+00 -3.18656e-02 8.65822e-02 +243 7.28485e+00 -3.43504e-02 7.88488e-02 +244 7.31487e+00 -3.65931e-02 7.04591e-02 +245 7.34489e+00 -3.85827e-02 6.22193e-02 +246 7.37491e+00 -4.03362e-02 5.47266e-02 +247 7.40493e+00 -4.18760e-02 4.79808e-02 +248 7.43495e+00 -4.32245e-02 4.19821e-02 +249 7.46497e+00 -4.44041e-02 3.67304e-02 +250 7.49499e+00 -4.54373e-02 3.22257e-02 +251 7.52501e+00 -4.63434e-02 2.81128e-02 +252 7.55503e+00 -4.71224e-02 2.37374e-02 +253 7.58505e+00 -4.77659e-02 1.90852e-02 +254 7.61507e+00 -4.82655e-02 1.41564e-02 +255 7.64509e+00 -4.86130e-02 8.95088e-03 +256 7.67511e+00 -4.88002e-02 3.46862e-03 +257 7.70513e+00 -4.88193e-02 -2.16133e-03 +258 7.73515e+00 -4.86748e-02 -7.38361e-03 +259 7.76517e+00 -4.83807e-02 -1.21345e-02 +260 7.79519e+00 -4.79510e-02 -1.64140e-02 +261 7.82521e+00 -4.73999e-02 -2.02221e-02 +262 7.85523e+00 -4.67416e-02 -2.35587e-02 +263 7.88525e+00 -4.59901e-02 -2.64574e-02 +264 7.91527e+00 -4.51529e-02 -2.93326e-02 +265 7.94529e+00 -4.42279e-02 -3.23085e-02 +266 7.97531e+00 -4.32121e-02 -3.53849e-02 +267 8.00533e+00 -4.21024e-02 -3.85620e-02 +268 8.03535e+00 -4.08958e-02 -4.18397e-02 +269 8.06537e+00 -3.95893e-02 -4.52148e-02 +270 8.09539e+00 -3.81847e-02 -4.82641e-02 +271 8.12541e+00 -3.66978e-02 -5.06928e-02 +272 8.15543e+00 -3.51473e-02 -5.25007e-02 +273 8.18545e+00 -3.35518e-02 -5.36880e-02 +274 8.21547e+00 -3.19301e-02 -5.42545e-02 +275 8.24549e+00 -3.03006e-02 -5.42004e-02 +276 8.27551e+00 -2.86797e-02 -5.38072e-02 +277 8.30553e+00 -2.70684e-02 -5.35644e-02 +278 8.33555e+00 -2.54621e-02 -5.34807e-02 +279 8.36557e+00 -2.38558e-02 -5.35562e-02 +280 8.39559e+00 -2.22450e-02 -5.37909e-02 +281 8.42561e+00 -2.06246e-02 -5.41848e-02 +282 8.45563e+00 -1.89910e-02 -5.45876e-02 +283 8.48565e+00 -1.73536e-02 -5.43905e-02 +284 8.51567e+00 -1.57321e-02 -5.35288e-02 +285 8.54569e+00 -1.41464e-02 -5.20025e-02 +286 8.57571e+00 -1.26165e-02 -4.98117e-02 +287 8.60573e+00 -1.11623e-02 -4.69563e-02 +288 8.63575e+00 -9.80364e-03 -4.34980e-02 +289 8.66577e+00 -8.54900e-03 -4.01388e-02 +290 8.69579e+00 -7.39073e-03 -3.70767e-02 +291 8.72581e+00 -6.31993e-03 -3.43119e-02 +292 8.75583e+00 -5.32767e-03 -3.18442e-02 +293 8.78585e+00 -4.40503e-03 -2.96736e-02 +294 8.81587e+00 -3.54310e-03 -2.77981e-02 +295 8.84589e+00 -2.73537e-03 -2.60045e-02 +296 8.87591e+00 -1.98236e-03 -2.41530e-02 +297 8.90593e+00 -1.28581e-03 -2.22435e-02 +298 8.93595e+00 -6.47440e-04 -2.02762e-02 +299 8.96597e+00 -6.90006e-05 -1.82510e-02 +300 8.99599e+00 4.47772e-04 -1.61678e-02 +301 9.02601e+00 9.01672e-04 -1.40883e-02 +302 9.05603e+00 1.29469e-03 -1.21134e-02 +303 9.08605e+00 1.63002e-03 -1.02444e-02 +304 9.11607e+00 1.91083e-03 -8.48151e-03 +305 9.14609e+00 2.14031e-03 -6.82462e-03 +306 9.17611e+00 2.32164e-03 -5.27374e-03 +307 9.20613e+00 2.45778e-03 -3.79164e-03 +308 9.23615e+00 2.54847e-03 -2.23608e-03 +309 9.26617e+00 2.59116e-03 -5.93158e-04 +310 9.29619e+00 2.58321e-03 1.13714e-03 +311 9.32621e+00 2.52201e-03 2.95480e-03 +312 9.35623e+00 2.40493e-03 4.85983e-03 +313 9.38625e+00 2.22951e-03 6.81084e-03 +314 9.41627e+00 2.00031e-03 8.37517e-03 +315 9.44629e+00 1.73168e-03 9.43770e-03 +316 9.47631e+00 1.43869e-03 9.99843e-03 +317 9.50633e+00 1.13640e-03 1.00573e-02 +318 9.53635e+00 8.39868e-04 9.61445e-03 +319 9.56637e+00 5.64157e-04 8.67672e-03 +320 9.59639e+00 3.18325e-04 7.75710e-03 +321 9.62641e+00 9.50596e-05 7.17332e-03 +322 9.65643e+00 -1.15722e-04 6.92537e-03 +323 9.68645e+00 -3.24101e-04 7.01327e-03 +324 9.71647e+00 -5.40160e-04 7.43701e-03 +325 9.74649e+00 -7.73980e-04 8.19658e-03 +326 9.77651e+00 -1.03304e-03 8.99735e-03 +327 9.80653e+00 -1.30999e-03 9.38361e-03 +328 9.83655e+00 -1.59223e-03 9.35021e-03 +329 9.86657e+00 -1.86718e-03 8.89715e-03 +330 9.89659e+00 -2.12222e-03 8.02442e-03 +331 9.92661e+00 -2.34476e-03 6.73203e-03 +332 9.95663e+00 -2.52320e-03 5.17469e-03 +333 9.98665e+00 -2.65869e-03 3.90930e-03 +334 1.00167e+01 -2.76134e-03 2.98596e-03 +335 1.00467e+01 -2.84139e-03 2.40466e-03 +336 1.00767e+01 -2.90913e-03 2.16541e-03 +337 1.01067e+01 -2.97483e-03 2.26820e-03 +338 1.01368e+01 -3.04855e-03 2.66546e-03 +339 1.01668e+01 -3.13277e-03 2.89884e-03 +340 1.01968e+01 -3.21981e-03 2.85342e-03 +341 1.02268e+01 -3.30130e-03 2.52919e-03 +342 1.02568e+01 -3.36887e-03 1.92616e-03 +343 1.02869e+01 -3.41416e-03 1.04432e-03 +344 1.03169e+01 -3.42879e-03 -1.09405e-04 +345 1.03469e+01 -3.40928e-03 -1.12840e-03 +346 1.03769e+01 -3.36477e-03 -1.77503e-03 +347 1.04069e+01 -3.30644e-03 -2.04930e-03 +348 1.04370e+01 -3.24546e-03 -1.95122e-03 +349 1.04670e+01 -3.19301e-03 -1.48077e-03 +350 1.04970e+01 -3.16028e-03 -6.37969e-04 +351 1.05270e+01 -3.15596e-03 3.01993e-04 +352 1.05570e+01 -3.17534e-03 9.38012e-04 +353 1.05871e+01 -3.20920e-03 1.26668e-03 +354 1.06171e+01 -3.24831e-03 1.28800e-03 +355 1.06471e+01 -3.28345e-03 1.00196e-03 +356 1.06771e+01 -3.30540e-03 4.08580e-04 +357 1.07071e+01 -3.30566e-03 -3.78073e-04 +358 1.07372e+01 -3.28485e-03 -9.70614e-04 +359 1.07672e+01 -3.24964e-03 -1.33712e-03 +360 1.07972e+01 -3.20683e-03 -1.47760e-03 +361 1.08272e+01 -3.16319e-03 -1.39204e-03 +362 1.08572e+01 -3.12551e-03 -1.08046e-03 +363 1.08873e+01 -3.10045e-03 -5.74729e-04 +364 1.09173e+01 -3.08983e-03 -1.58731e-04 +365 1.09473e+01 -3.08935e-03 1.00508e-04 +366 1.09773e+01 -3.09430e-03 2.02989e-04 +367 1.10073e+01 -3.09997e-03 1.48712e-04 +368 1.10374e+01 -3.10166e-03 -6.23237e-05 +369 1.10674e+01 -3.09466e-03 -4.27258e-04 +370 1.10974e+01 -3.07597e-03 -8.08158e-04 +371 1.11274e+01 -3.04674e-03 -1.12894e-03 +372 1.11574e+01 -3.00879e-03 -1.38962e-03 +373 1.11875e+01 -2.96391e-03 -1.59017e-03 +374 1.12175e+01 -2.91392e-03 -1.73062e-03 +375 1.12475e+01 -2.86061e-03 -1.81095e-03 +376 1.12775e+01 -2.80553e-03 -1.85938e-03 +377 1.13075e+01 -2.74890e-03 -1.91463e-03 +378 1.13376e+01 -2.69051e-03 -1.97693e-03 +379 1.13676e+01 -2.63013e-03 -2.04629e-03 +380 1.13976e+01 -2.56758e-03 -2.12270e-03 +381 1.14276e+01 -2.50262e-03 -2.20617e-03 +382 1.14576e+01 -2.43503e-03 -2.29944e-03 +383 1.14877e+01 -2.36437e-03 -2.41127e-03 +384 1.15177e+01 -2.29006e-03 -2.54235e-03 +385 1.15477e+01 -2.21153e-03 -2.69266e-03 +386 1.15777e+01 -2.12820e-03 -2.86220e-03 +387 1.16077e+01 -2.03949e-03 -3.05099e-03 +388 1.16378e+01 -1.94486e-03 -3.25094e-03 +389 1.16678e+01 -1.84492e-03 -3.39558e-03 +390 1.16978e+01 -1.74169e-03 -3.47012e-03 +391 1.17278e+01 -1.63728e-03 -3.47457e-03 +392 1.17578e+01 -1.53378e-03 -3.40893e-03 +393 1.17879e+01 -1.43331e-03 -3.27320e-03 +394 1.18179e+01 -1.33796e-03 -3.06968e-03 +395 1.18479e+01 -1.24867e-03 -2.89115e-03 +396 1.18779e+01 -1.16364e-03 -2.78593e-03 +397 1.19079e+01 -1.08067e-03 -2.75402e-03 +398 1.19380e+01 -9.97552e-04 -2.79543e-03 +399 1.19680e+01 -9.12094e-04 -2.91016e-03 +400 1.19980e+01 -8.22092e-04 -3.09820e-03 +401 1.20280e+01 -7.25645e-04 -3.32741e-03 +402 1.20580e+01 -6.22319e-04 -3.55632e-03 +403 1.20881e+01 -5.12128e-04 -3.78474e-03 +404 1.21181e+01 -3.95087e-04 -4.01269e-03 +405 1.21481e+01 -2.71211e-04 -4.24016e-03 +406 1.21781e+01 -1.40513e-04 -4.46715e-03 +407 1.22081e+01 -3.33537e-06 -4.64603e-03 +408 1.22382e+01 1.36445e-04 -4.63274e-03 +409 1.22682e+01 2.72793e-04 -4.41741e-03 +410 1.22982e+01 3.99645e-04 -4.00005e-03 +411 1.23282e+01 5.10935e-04 -3.38066e-03 +412 1.23582e+01 6.00598e-04 -2.55924e-03 +413 1.23883e+01 6.62774e-04 -1.58184e-03 +414 1.24183e+01 6.97865e-04 -8.01087e-04 +415 1.24483e+01 7.13576e-04 -2.90631e-04 +416 1.24783e+01 7.18019e-04 -5.04698e-05 +417 1.25083e+01 7.19311e-04 -8.06022e-05 +418 1.25384e+01 7.25563e-04 -3.81028e-04 +419 1.25684e+01 7.44874e-04 -9.42536e-04 +420 1.25984e+01 7.81298e-04 -1.44902e-03 +421 1.26284e+01 8.29767e-04 -1.74498e-03 +422 1.26584e+01 8.83961e-04 -1.83043e-03 +423 1.26885e+01 9.37559e-04 -1.70535e-03 +424 1.27185e+01 9.84244e-04 -1.36976e-03 +425 1.27485e+01 1.01769e-03 -8.23649e-04 +426 1.27785e+01 1.03293e-03 -2.08014e-04 +427 1.28085e+01 1.03120e-03 3.06031e-04 +428 1.28386e+01 1.01558e-03 7.18094e-04 +429 1.28686e+01 9.89109e-04 1.02818e-03 +430 1.28986e+01 9.54864e-04 1.23627e-03 +431 1.29286e+01 9.15903e-04 1.34239e-03 +432 1.29586e+01 8.75242e-04 1.35306e-03 +433 1.29887e+01 8.35426e-04 1.28692e-03 +434 1.30187e+01 7.98731e-04 1.14515e-03 +435 1.30487e+01 7.67428e-04 9.27723e-04 +436 1.30787e+01 7.43788e-04 6.34655e-04 +437 1.31087e+01 7.30081e-04 2.65942e-04 +438 1.31388e+01 7.28458e-04 -1.52323e-04 +439 1.31688e+01 7.37694e-04 -4.34209e-04 +440 1.31988e+01 7.52798e-04 -5.43256e-04 +441 1.32288e+01 7.68582e-04 -4.79464e-04 +442 1.32588e+01 7.79856e-04 -2.42834e-04 +443 1.32889e+01 7.81432e-04 1.66636e-04 +444 1.33189e+01 7.68136e-04 7.42231e-04 +445 1.33489e+01 7.37388e-04 1.28546e-03 +446 1.33789e+01 6.92203e-04 1.70409e-03 +447 1.34089e+01 6.36322e-04 1.99810e-03 +448 1.34390e+01 5.73484e-04 2.16751e-03 +449 1.34690e+01 5.07431e-04 2.21231e-03 +450 1.34990e+01 4.41904e-04 2.13250e-03 +451 1.35290e+01 3.79886e-04 2.00628e-03 +452 1.35590e+01 3.21019e-04 1.92274e-03 +453 1.35891e+01 2.64017e-04 1.88196e-03 +454 1.36191e+01 2.07597e-04 1.88396e-03 +455 1.36491e+01 1.50476e-04 1.92873e-03 +456 1.36791e+01 9.13683e-05 2.01627e-03 +457 1.37091e+01 2.90559e-05 2.13758e-03 +458 1.37392e+01 -3.70569e-05 2.26836e-03 +459 1.37692e+01 -1.07218e-04 2.40726e-03 +460 1.37992e+01 -1.81670e-04 2.55428e-03 +461 1.38292e+01 -2.60658e-04 2.70943e-03 +462 1.38592e+01 -3.44426e-04 2.87270e-03 +463 1.38893e+01 -4.33097e-04 3.01891e-03 +464 1.39193e+01 -5.23690e-04 2.98077e-03 +465 1.39493e+01 -6.09910e-04 2.72751e-03 +466 1.39793e+01 -6.85298e-04 2.25913e-03 +467 1.40093e+01 -7.43395e-04 1.57563e-03 +468 1.40394e+01 -7.77746e-04 6.77007e-04 +469 1.40694e+01 -7.81926e-04 -4.21254e-04 +470 1.40994e+01 -7.54850e-04 -1.32019e-03 +471 1.41294e+01 -7.06409e-04 -1.84461e-03 +472 1.41594e+01 -6.47847e-04 -1.99453e-03 +473 1.41895e+01 -5.90405e-04 -1.76993e-03 +474 1.42195e+01 -5.45328e-04 -1.17081e-03 +475 1.42495e+01 -5.23857e-04 -1.97186e-04 +476 1.42795e+01 -5.33670e-04 7.88500e-04 +477 1.43095e+01 -5.67444e-04 1.39908e-03 +478 1.43396e+01 -6.13917e-04 1.63446e-03 +479 1.43696e+01 -6.61823e-04 1.49463e-03 +480 1.43996e+01 -6.99900e-04 9.79593e-04 +481 1.44296e+01 -7.16883e-04 8.93484e-05 +482 1.44596e+01 -7.02817e-04 -9.98994e-04 +483 1.44897e+01 -6.59607e-04 -1.83371e-03 +484 1.45197e+01 -5.95483e-04 -2.39236e-03 +485 1.45497e+01 -5.18732e-04 -2.67493e-03 +486 1.45797e+01 -4.37642e-04 -2.68144e-03 +487 1.46097e+01 -3.60501e-04 -2.41188e-03 +488 1.46398e+01 -2.95370e-04 -1.91209e-03 +489 1.46698e+01 -2.44915e-04 -1.46649e-03 +490 1.46998e+01 -2.06289e-04 -1.12409e-03 +491 1.47298e+01 -1.76392e-04 -8.84885e-04 +492 1.47598e+01 -1.52128e-04 -7.48875e-04 +493 1.47899e+01 -1.30397e-04 -7.16060e-04 +494 1.48199e+01 -1.08115e-04 -7.81211e-04 +495 1.48499e+01 -8.38208e-05 -8.25705e-04 +496 1.48799e+01 -5.92393e-05 -8.00320e-04 +497 1.49099e+01 -3.64687e-05 -7.05058e-04 +498 1.49400e+01 -1.76068e-05 -5.39917e-04 +499 1.49700e+01 -4.75133e-06 -3.04897e-04 +500 1.50000e+01 0.00000e+00 0.00000e+00 + + + +NonBondNull +N 500 R 0.0000000001 10.0 + +1 0.0000e+00 0.0000e+00 0.0000e+00 +2 2.0040e-02 0.0000e+00 0.0000e+00 +3 4.0080e-02 0.0000e+00 0.0000e+00 +4 6.0120e-02 0.0000e+00 0.0000e+00 +5 8.0160e-02 0.0000e+00 0.0000e+00 +6 1.0020e-01 0.0000e+00 0.0000e+00 +7 1.2024e-01 0.0000e+00 0.0000e+00 +8 1.4028e-01 0.0000e+00 0.0000e+00 +9 1.6032e-01 0.0000e+00 0.0000e+00 +10 1.8036e-01 0.0000e+00 0.0000e+00 +11 2.0040e-01 0.0000e+00 0.0000e+00 +12 2.2044e-01 0.0000e+00 0.0000e+00 +13 2.4048e-01 0.0000e+00 0.0000e+00 +14 2.6052e-01 0.0000e+00 0.0000e+00 +15 2.8056e-01 0.0000e+00 0.0000e+00 +16 3.0060e-01 0.0000e+00 0.0000e+00 +17 3.2064e-01 0.0000e+00 0.0000e+00 +18 3.4068e-01 0.0000e+00 0.0000e+00 +19 3.6072e-01 0.0000e+00 0.0000e+00 +20 3.8076e-01 0.0000e+00 0.0000e+00 +21 4.0080e-01 0.0000e+00 0.0000e+00 +22 4.2084e-01 0.0000e+00 0.0000e+00 +23 4.4088e-01 0.0000e+00 0.0000e+00 +24 4.6092e-01 0.0000e+00 0.0000e+00 +25 4.8096e-01 0.0000e+00 0.0000e+00 +26 5.0100e-01 0.0000e+00 0.0000e+00 +27 5.2104e-01 0.0000e+00 0.0000e+00 +28 5.4108e-01 0.0000e+00 0.0000e+00 +29 5.6112e-01 0.0000e+00 0.0000e+00 +30 5.8116e-01 0.0000e+00 0.0000e+00 +31 6.0120e-01 0.0000e+00 0.0000e+00 +32 6.2124e-01 0.0000e+00 0.0000e+00 +33 6.4128e-01 0.0000e+00 0.0000e+00 +34 6.6132e-01 0.0000e+00 0.0000e+00 +35 6.8136e-01 0.0000e+00 0.0000e+00 +36 7.0140e-01 0.0000e+00 0.0000e+00 +37 7.2144e-01 0.0000e+00 0.0000e+00 +38 7.4148e-01 0.0000e+00 0.0000e+00 +39 7.6152e-01 0.0000e+00 0.0000e+00 +40 7.8156e-01 0.0000e+00 0.0000e+00 +41 8.0160e-01 0.0000e+00 0.0000e+00 +42 8.2164e-01 0.0000e+00 0.0000e+00 +43 8.4168e-01 0.0000e+00 0.0000e+00 +44 8.6172e-01 0.0000e+00 0.0000e+00 +45 8.8176e-01 0.0000e+00 0.0000e+00 +46 9.0180e-01 0.0000e+00 0.0000e+00 +47 9.2184e-01 0.0000e+00 0.0000e+00 +48 9.4188e-01 0.0000e+00 0.0000e+00 +49 9.6192e-01 0.0000e+00 0.0000e+00 +50 9.8196e-01 0.0000e+00 0.0000e+00 +51 1.0020e+00 0.0000e+00 0.0000e+00 +52 1.0220e+00 0.0000e+00 0.0000e+00 +53 1.0421e+00 0.0000e+00 0.0000e+00 +54 1.0621e+00 0.0000e+00 0.0000e+00 +55 1.0822e+00 0.0000e+00 0.0000e+00 +56 1.1022e+00 0.0000e+00 0.0000e+00 +57 1.1222e+00 0.0000e+00 0.0000e+00 +58 1.1423e+00 0.0000e+00 0.0000e+00 +59 1.1623e+00 0.0000e+00 0.0000e+00 +60 1.1824e+00 0.0000e+00 0.0000e+00 +61 1.2024e+00 0.0000e+00 0.0000e+00 +62 1.2224e+00 0.0000e+00 0.0000e+00 +63 1.2425e+00 0.0000e+00 0.0000e+00 +64 1.2625e+00 0.0000e+00 0.0000e+00 +65 1.2826e+00 0.0000e+00 0.0000e+00 +66 1.3026e+00 0.0000e+00 0.0000e+00 +67 1.3226e+00 0.0000e+00 0.0000e+00 +68 1.3427e+00 0.0000e+00 0.0000e+00 +69 1.3627e+00 0.0000e+00 0.0000e+00 +70 1.3828e+00 0.0000e+00 0.0000e+00 +71 1.4028e+00 0.0000e+00 0.0000e+00 +72 1.4228e+00 0.0000e+00 0.0000e+00 +73 1.4429e+00 0.0000e+00 0.0000e+00 +74 1.4629e+00 0.0000e+00 0.0000e+00 +75 1.4830e+00 0.0000e+00 0.0000e+00 +76 1.5030e+00 0.0000e+00 0.0000e+00 +77 1.5230e+00 0.0000e+00 0.0000e+00 +78 1.5431e+00 0.0000e+00 0.0000e+00 +79 1.5631e+00 0.0000e+00 0.0000e+00 +80 1.5832e+00 0.0000e+00 0.0000e+00 +81 1.6032e+00 0.0000e+00 0.0000e+00 +82 1.6232e+00 0.0000e+00 0.0000e+00 +83 1.6433e+00 0.0000e+00 0.0000e+00 +84 1.6633e+00 0.0000e+00 0.0000e+00 +85 1.6834e+00 0.0000e+00 0.0000e+00 +86 1.7034e+00 0.0000e+00 0.0000e+00 +87 1.7234e+00 0.0000e+00 0.0000e+00 +88 1.7435e+00 0.0000e+00 0.0000e+00 +89 1.7635e+00 0.0000e+00 0.0000e+00 +90 1.7836e+00 0.0000e+00 0.0000e+00 +91 1.8036e+00 0.0000e+00 0.0000e+00 +92 1.8236e+00 0.0000e+00 0.0000e+00 +93 1.8437e+00 0.0000e+00 0.0000e+00 +94 1.8637e+00 0.0000e+00 0.0000e+00 +95 1.8838e+00 0.0000e+00 0.0000e+00 +96 1.9038e+00 0.0000e+00 0.0000e+00 +97 1.9238e+00 0.0000e+00 0.0000e+00 +98 1.9439e+00 0.0000e+00 0.0000e+00 +99 1.9639e+00 0.0000e+00 0.0000e+00 +100 1.9840e+00 0.0000e+00 0.0000e+00 +101 2.0040e+00 0.0000e+00 0.0000e+00 +102 2.0240e+00 0.0000e+00 0.0000e+00 +103 2.0441e+00 0.0000e+00 0.0000e+00 +104 2.0641e+00 0.0000e+00 0.0000e+00 +105 2.0842e+00 0.0000e+00 0.0000e+00 +106 2.1042e+00 0.0000e+00 0.0000e+00 +107 2.1242e+00 0.0000e+00 0.0000e+00 +108 2.1443e+00 0.0000e+00 0.0000e+00 +109 2.1643e+00 0.0000e+00 0.0000e+00 +110 2.1844e+00 0.0000e+00 0.0000e+00 +111 2.2044e+00 0.0000e+00 0.0000e+00 +112 2.2244e+00 0.0000e+00 0.0000e+00 +113 2.2445e+00 0.0000e+00 0.0000e+00 +114 2.2645e+00 0.0000e+00 0.0000e+00 +115 2.2846e+00 0.0000e+00 0.0000e+00 +116 2.3046e+00 0.0000e+00 0.0000e+00 +117 2.3246e+00 0.0000e+00 0.0000e+00 +118 2.3447e+00 0.0000e+00 0.0000e+00 +119 2.3647e+00 0.0000e+00 0.0000e+00 +120 2.3848e+00 0.0000e+00 0.0000e+00 +121 2.4048e+00 0.0000e+00 0.0000e+00 +122 2.4248e+00 0.0000e+00 0.0000e+00 +123 2.4449e+00 0.0000e+00 0.0000e+00 +124 2.4649e+00 0.0000e+00 0.0000e+00 +125 2.4850e+00 0.0000e+00 0.0000e+00 +126 2.5050e+00 0.0000e+00 0.0000e+00 +127 2.5251e+00 0.0000e+00 0.0000e+00 +128 2.5451e+00 0.0000e+00 0.0000e+00 +129 2.5651e+00 0.0000e+00 0.0000e+00 +130 2.5852e+00 0.0000e+00 0.0000e+00 +131 2.6052e+00 0.0000e+00 0.0000e+00 +132 2.6253e+00 0.0000e+00 0.0000e+00 +133 2.6453e+00 0.0000e+00 0.0000e+00 +134 2.6653e+00 0.0000e+00 0.0000e+00 +135 2.6854e+00 0.0000e+00 0.0000e+00 +136 2.7054e+00 0.0000e+00 0.0000e+00 +137 2.7255e+00 0.0000e+00 0.0000e+00 +138 2.7455e+00 0.0000e+00 0.0000e+00 +139 2.7655e+00 0.0000e+00 0.0000e+00 +140 2.7856e+00 0.0000e+00 0.0000e+00 +141 2.8056e+00 0.0000e+00 0.0000e+00 +142 2.8257e+00 0.0000e+00 0.0000e+00 +143 2.8457e+00 0.0000e+00 0.0000e+00 +144 2.8657e+00 0.0000e+00 0.0000e+00 +145 2.8858e+00 0.0000e+00 0.0000e+00 +146 2.9058e+00 0.0000e+00 0.0000e+00 +147 2.9259e+00 0.0000e+00 0.0000e+00 +148 2.9459e+00 0.0000e+00 0.0000e+00 +149 2.9659e+00 0.0000e+00 0.0000e+00 +150 2.9860e+00 0.0000e+00 0.0000e+00 +151 3.0060e+00 0.0000e+00 0.0000e+00 +152 3.0261e+00 0.0000e+00 0.0000e+00 +153 3.0461e+00 0.0000e+00 0.0000e+00 +154 3.0661e+00 0.0000e+00 0.0000e+00 +155 3.0862e+00 0.0000e+00 0.0000e+00 +156 3.1062e+00 0.0000e+00 0.0000e+00 +157 3.1263e+00 0.0000e+00 0.0000e+00 +158 3.1463e+00 0.0000e+00 0.0000e+00 +159 3.1663e+00 0.0000e+00 0.0000e+00 +160 3.1864e+00 0.0000e+00 0.0000e+00 +161 3.2064e+00 0.0000e+00 0.0000e+00 +162 3.2265e+00 0.0000e+00 0.0000e+00 +163 3.2465e+00 0.0000e+00 0.0000e+00 +164 3.2665e+00 0.0000e+00 0.0000e+00 +165 3.2866e+00 0.0000e+00 0.0000e+00 +166 3.3066e+00 0.0000e+00 0.0000e+00 +167 3.3267e+00 0.0000e+00 0.0000e+00 +168 3.3467e+00 0.0000e+00 0.0000e+00 +169 3.3667e+00 0.0000e+00 0.0000e+00 +170 3.3868e+00 0.0000e+00 0.0000e+00 +171 3.4068e+00 0.0000e+00 0.0000e+00 +172 3.4269e+00 0.0000e+00 0.0000e+00 +173 3.4469e+00 0.0000e+00 0.0000e+00 +174 3.4669e+00 0.0000e+00 0.0000e+00 +175 3.4870e+00 0.0000e+00 0.0000e+00 +176 3.5070e+00 0.0000e+00 0.0000e+00 +177 3.5271e+00 0.0000e+00 0.0000e+00 +178 3.5471e+00 0.0000e+00 0.0000e+00 +179 3.5671e+00 0.0000e+00 0.0000e+00 +180 3.5872e+00 0.0000e+00 0.0000e+00 +181 3.6072e+00 0.0000e+00 0.0000e+00 +182 3.6273e+00 0.0000e+00 0.0000e+00 +183 3.6473e+00 0.0000e+00 0.0000e+00 +184 3.6673e+00 0.0000e+00 0.0000e+00 +185 3.6874e+00 0.0000e+00 0.0000e+00 +186 3.7074e+00 0.0000e+00 0.0000e+00 +187 3.7275e+00 0.0000e+00 0.0000e+00 +188 3.7475e+00 0.0000e+00 0.0000e+00 +189 3.7675e+00 0.0000e+00 0.0000e+00 +190 3.7876e+00 0.0000e+00 0.0000e+00 +191 3.8076e+00 0.0000e+00 0.0000e+00 +192 3.8277e+00 0.0000e+00 0.0000e+00 +193 3.8477e+00 0.0000e+00 0.0000e+00 +194 3.8677e+00 0.0000e+00 0.0000e+00 +195 3.8878e+00 0.0000e+00 0.0000e+00 +196 3.9078e+00 0.0000e+00 0.0000e+00 +197 3.9279e+00 0.0000e+00 0.0000e+00 +198 3.9479e+00 0.0000e+00 0.0000e+00 +199 3.9679e+00 0.0000e+00 0.0000e+00 +200 3.9880e+00 0.0000e+00 0.0000e+00 +201 4.0080e+00 0.0000e+00 0.0000e+00 +202 4.0281e+00 0.0000e+00 0.0000e+00 +203 4.0481e+00 0.0000e+00 0.0000e+00 +204 4.0681e+00 0.0000e+00 0.0000e+00 +205 4.0882e+00 0.0000e+00 0.0000e+00 +206 4.1082e+00 0.0000e+00 0.0000e+00 +207 4.1283e+00 0.0000e+00 0.0000e+00 +208 4.1483e+00 0.0000e+00 0.0000e+00 +209 4.1683e+00 0.0000e+00 0.0000e+00 +210 4.1884e+00 0.0000e+00 0.0000e+00 +211 4.2084e+00 0.0000e+00 0.0000e+00 +212 4.2285e+00 0.0000e+00 0.0000e+00 +213 4.2485e+00 0.0000e+00 0.0000e+00 +214 4.2685e+00 0.0000e+00 0.0000e+00 +215 4.2886e+00 0.0000e+00 0.0000e+00 +216 4.3086e+00 0.0000e+00 0.0000e+00 +217 4.3287e+00 0.0000e+00 0.0000e+00 +218 4.3487e+00 0.0000e+00 0.0000e+00 +219 4.3687e+00 0.0000e+00 0.0000e+00 +220 4.3888e+00 0.0000e+00 0.0000e+00 +221 4.4088e+00 0.0000e+00 0.0000e+00 +222 4.4289e+00 0.0000e+00 0.0000e+00 +223 4.4489e+00 0.0000e+00 0.0000e+00 +224 4.4689e+00 0.0000e+00 0.0000e+00 +225 4.4890e+00 0.0000e+00 0.0000e+00 +226 4.5090e+00 0.0000e+00 0.0000e+00 +227 4.5291e+00 0.0000e+00 0.0000e+00 +228 4.5491e+00 0.0000e+00 0.0000e+00 +229 4.5691e+00 0.0000e+00 0.0000e+00 +230 4.5892e+00 0.0000e+00 0.0000e+00 +231 4.6092e+00 0.0000e+00 0.0000e+00 +232 4.6293e+00 0.0000e+00 0.0000e+00 +233 4.6493e+00 0.0000e+00 0.0000e+00 +234 4.6693e+00 0.0000e+00 0.0000e+00 +235 4.6894e+00 0.0000e+00 0.0000e+00 +236 4.7094e+00 0.0000e+00 0.0000e+00 +237 4.7295e+00 0.0000e+00 0.0000e+00 +238 4.7495e+00 0.0000e+00 0.0000e+00 +239 4.7695e+00 0.0000e+00 0.0000e+00 +240 4.7896e+00 0.0000e+00 0.0000e+00 +241 4.8096e+00 0.0000e+00 0.0000e+00 +242 4.8297e+00 0.0000e+00 0.0000e+00 +243 4.8497e+00 0.0000e+00 0.0000e+00 +244 4.8697e+00 0.0000e+00 0.0000e+00 +245 4.8898e+00 0.0000e+00 0.0000e+00 +246 4.9098e+00 0.0000e+00 0.0000e+00 +247 4.9299e+00 0.0000e+00 0.0000e+00 +248 4.9499e+00 0.0000e+00 0.0000e+00 +249 4.9699e+00 0.0000e+00 0.0000e+00 +250 4.9900e+00 0.0000e+00 0.0000e+00 +251 5.0100e+00 0.0000e+00 0.0000e+00 +252 5.0301e+00 0.0000e+00 0.0000e+00 +253 5.0501e+00 0.0000e+00 0.0000e+00 +254 5.0701e+00 0.0000e+00 0.0000e+00 +255 5.0902e+00 0.0000e+00 0.0000e+00 +256 5.1102e+00 0.0000e+00 0.0000e+00 +257 5.1303e+00 0.0000e+00 0.0000e+00 +258 5.1503e+00 0.0000e+00 0.0000e+00 +259 5.1703e+00 0.0000e+00 0.0000e+00 +260 5.1904e+00 0.0000e+00 0.0000e+00 +261 5.2104e+00 0.0000e+00 0.0000e+00 +262 5.2305e+00 0.0000e+00 0.0000e+00 +263 5.2505e+00 0.0000e+00 0.0000e+00 +264 5.2705e+00 0.0000e+00 0.0000e+00 +265 5.2906e+00 0.0000e+00 0.0000e+00 +266 5.3106e+00 0.0000e+00 0.0000e+00 +267 5.3307e+00 0.0000e+00 0.0000e+00 +268 5.3507e+00 0.0000e+00 0.0000e+00 +269 5.3707e+00 0.0000e+00 0.0000e+00 +270 5.3908e+00 0.0000e+00 0.0000e+00 +271 5.4108e+00 0.0000e+00 0.0000e+00 +272 5.4309e+00 0.0000e+00 0.0000e+00 +273 5.4509e+00 0.0000e+00 0.0000e+00 +274 5.4709e+00 0.0000e+00 0.0000e+00 +275 5.4910e+00 0.0000e+00 0.0000e+00 +276 5.5110e+00 0.0000e+00 0.0000e+00 +277 5.5311e+00 0.0000e+00 0.0000e+00 +278 5.5511e+00 0.0000e+00 0.0000e+00 +279 5.5711e+00 0.0000e+00 0.0000e+00 +280 5.5912e+00 0.0000e+00 0.0000e+00 +281 5.6112e+00 0.0000e+00 0.0000e+00 +282 5.6313e+00 0.0000e+00 0.0000e+00 +283 5.6513e+00 0.0000e+00 0.0000e+00 +284 5.6713e+00 0.0000e+00 0.0000e+00 +285 5.6914e+00 0.0000e+00 0.0000e+00 +286 5.7114e+00 0.0000e+00 0.0000e+00 +287 5.7315e+00 0.0000e+00 0.0000e+00 +288 5.7515e+00 0.0000e+00 0.0000e+00 +289 5.7715e+00 0.0000e+00 0.0000e+00 +290 5.7916e+00 0.0000e+00 0.0000e+00 +291 5.8116e+00 0.0000e+00 0.0000e+00 +292 5.8317e+00 0.0000e+00 0.0000e+00 +293 5.8517e+00 0.0000e+00 0.0000e+00 +294 5.8717e+00 0.0000e+00 0.0000e+00 +295 5.8918e+00 0.0000e+00 0.0000e+00 +296 5.9118e+00 0.0000e+00 0.0000e+00 +297 5.9319e+00 0.0000e+00 0.0000e+00 +298 5.9519e+00 0.0000e+00 0.0000e+00 +299 5.9719e+00 0.0000e+00 0.0000e+00 +300 5.9920e+00 0.0000e+00 0.0000e+00 +301 6.0120e+00 0.0000e+00 0.0000e+00 +302 6.0321e+00 0.0000e+00 0.0000e+00 +303 6.0521e+00 0.0000e+00 0.0000e+00 +304 6.0721e+00 0.0000e+00 0.0000e+00 +305 6.0922e+00 0.0000e+00 0.0000e+00 +306 6.1122e+00 0.0000e+00 0.0000e+00 +307 6.1323e+00 0.0000e+00 0.0000e+00 +308 6.1523e+00 0.0000e+00 0.0000e+00 +309 6.1723e+00 0.0000e+00 0.0000e+00 +310 6.1924e+00 0.0000e+00 0.0000e+00 +311 6.2124e+00 0.0000e+00 0.0000e+00 +312 6.2325e+00 0.0000e+00 0.0000e+00 +313 6.2525e+00 0.0000e+00 0.0000e+00 +314 6.2725e+00 0.0000e+00 0.0000e+00 +315 6.2926e+00 0.0000e+00 0.0000e+00 +316 6.3126e+00 0.0000e+00 0.0000e+00 +317 6.3327e+00 0.0000e+00 0.0000e+00 +318 6.3527e+00 0.0000e+00 0.0000e+00 +319 6.3727e+00 0.0000e+00 0.0000e+00 +320 6.3928e+00 0.0000e+00 0.0000e+00 +321 6.4128e+00 0.0000e+00 0.0000e+00 +322 6.4329e+00 0.0000e+00 0.0000e+00 +323 6.4529e+00 0.0000e+00 0.0000e+00 +324 6.4729e+00 0.0000e+00 0.0000e+00 +325 6.4930e+00 0.0000e+00 0.0000e+00 +326 6.5130e+00 0.0000e+00 0.0000e+00 +327 6.5331e+00 0.0000e+00 0.0000e+00 +328 6.5531e+00 0.0000e+00 0.0000e+00 +329 6.5731e+00 0.0000e+00 0.0000e+00 +330 6.5932e+00 0.0000e+00 0.0000e+00 +331 6.6132e+00 0.0000e+00 0.0000e+00 +332 6.6333e+00 0.0000e+00 0.0000e+00 +333 6.6533e+00 0.0000e+00 0.0000e+00 +334 6.6733e+00 0.0000e+00 0.0000e+00 +335 6.6934e+00 0.0000e+00 0.0000e+00 +336 6.7134e+00 0.0000e+00 0.0000e+00 +337 6.7335e+00 0.0000e+00 0.0000e+00 +338 6.7535e+00 0.0000e+00 0.0000e+00 +339 6.7735e+00 0.0000e+00 0.0000e+00 +340 6.7936e+00 0.0000e+00 0.0000e+00 +341 6.8136e+00 0.0000e+00 0.0000e+00 +342 6.8337e+00 0.0000e+00 0.0000e+00 +343 6.8537e+00 0.0000e+00 0.0000e+00 +344 6.8737e+00 0.0000e+00 0.0000e+00 +345 6.8938e+00 0.0000e+00 0.0000e+00 +346 6.9138e+00 0.0000e+00 0.0000e+00 +347 6.9339e+00 0.0000e+00 0.0000e+00 +348 6.9539e+00 0.0000e+00 0.0000e+00 +349 6.9739e+00 0.0000e+00 0.0000e+00 +350 6.9940e+00 0.0000e+00 0.0000e+00 +351 7.0140e+00 0.0000e+00 0.0000e+00 +352 7.0341e+00 0.0000e+00 0.0000e+00 +353 7.0541e+00 0.0000e+00 0.0000e+00 +354 7.0741e+00 0.0000e+00 0.0000e+00 +355 7.0942e+00 0.0000e+00 0.0000e+00 +356 7.1142e+00 0.0000e+00 0.0000e+00 +357 7.1343e+00 0.0000e+00 0.0000e+00 +358 7.1543e+00 0.0000e+00 0.0000e+00 +359 7.1743e+00 0.0000e+00 0.0000e+00 +360 7.1944e+00 0.0000e+00 0.0000e+00 +361 7.2144e+00 0.0000e+00 0.0000e+00 +362 7.2345e+00 0.0000e+00 0.0000e+00 +363 7.2545e+00 0.0000e+00 0.0000e+00 +364 7.2745e+00 0.0000e+00 0.0000e+00 +365 7.2946e+00 0.0000e+00 0.0000e+00 +366 7.3146e+00 0.0000e+00 0.0000e+00 +367 7.3347e+00 0.0000e+00 0.0000e+00 +368 7.3547e+00 0.0000e+00 0.0000e+00 +369 7.3747e+00 0.0000e+00 0.0000e+00 +370 7.3948e+00 0.0000e+00 0.0000e+00 +371 7.4148e+00 0.0000e+00 0.0000e+00 +372 7.4349e+00 0.0000e+00 0.0000e+00 +373 7.4549e+00 0.0000e+00 0.0000e+00 +374 7.4749e+00 0.0000e+00 0.0000e+00 +375 7.4950e+00 0.0000e+00 0.0000e+00 +376 7.5150e+00 0.0000e+00 0.0000e+00 +377 7.5351e+00 0.0000e+00 0.0000e+00 +378 7.5551e+00 0.0000e+00 0.0000e+00 +379 7.5752e+00 0.0000e+00 0.0000e+00 +380 7.5952e+00 0.0000e+00 0.0000e+00 +381 7.6152e+00 0.0000e+00 0.0000e+00 +382 7.6353e+00 0.0000e+00 0.0000e+00 +383 7.6553e+00 0.0000e+00 0.0000e+00 +384 7.6754e+00 0.0000e+00 0.0000e+00 +385 7.6954e+00 0.0000e+00 0.0000e+00 +386 7.7154e+00 0.0000e+00 0.0000e+00 +387 7.7355e+00 0.0000e+00 0.0000e+00 +388 7.7555e+00 0.0000e+00 0.0000e+00 +389 7.7756e+00 0.0000e+00 0.0000e+00 +390 7.7956e+00 0.0000e+00 0.0000e+00 +391 7.8156e+00 0.0000e+00 0.0000e+00 +392 7.8357e+00 0.0000e+00 0.0000e+00 +393 7.8557e+00 0.0000e+00 0.0000e+00 +394 7.8758e+00 0.0000e+00 0.0000e+00 +395 7.8958e+00 0.0000e+00 0.0000e+00 +396 7.9158e+00 0.0000e+00 0.0000e+00 +397 7.9359e+00 0.0000e+00 0.0000e+00 +398 7.9559e+00 0.0000e+00 0.0000e+00 +399 7.9760e+00 0.0000e+00 0.0000e+00 +400 7.9960e+00 0.0000e+00 0.0000e+00 +401 8.0160e+00 0.0000e+00 0.0000e+00 +402 8.0361e+00 0.0000e+00 0.0000e+00 +403 8.0561e+00 0.0000e+00 0.0000e+00 +404 8.0762e+00 0.0000e+00 0.0000e+00 +405 8.0962e+00 0.0000e+00 0.0000e+00 +406 8.1162e+00 0.0000e+00 0.0000e+00 +407 8.1363e+00 0.0000e+00 0.0000e+00 +408 8.1563e+00 0.0000e+00 0.0000e+00 +409 8.1764e+00 0.0000e+00 0.0000e+00 +410 8.1964e+00 0.0000e+00 0.0000e+00 +411 8.2164e+00 0.0000e+00 0.0000e+00 +412 8.2365e+00 0.0000e+00 0.0000e+00 +413 8.2565e+00 0.0000e+00 0.0000e+00 +414 8.2766e+00 0.0000e+00 0.0000e+00 +415 8.2966e+00 0.0000e+00 0.0000e+00 +416 8.3166e+00 0.0000e+00 0.0000e+00 +417 8.3367e+00 0.0000e+00 0.0000e+00 +418 8.3567e+00 0.0000e+00 0.0000e+00 +419 8.3768e+00 0.0000e+00 0.0000e+00 +420 8.3968e+00 0.0000e+00 0.0000e+00 +421 8.4168e+00 0.0000e+00 0.0000e+00 +422 8.4369e+00 0.0000e+00 0.0000e+00 +423 8.4569e+00 0.0000e+00 0.0000e+00 +424 8.4770e+00 0.0000e+00 0.0000e+00 +425 8.4970e+00 0.0000e+00 0.0000e+00 +426 8.5170e+00 0.0000e+00 0.0000e+00 +427 8.5371e+00 0.0000e+00 0.0000e+00 +428 8.5571e+00 0.0000e+00 0.0000e+00 +429 8.5772e+00 0.0000e+00 0.0000e+00 +430 8.5972e+00 0.0000e+00 0.0000e+00 +431 8.6172e+00 0.0000e+00 0.0000e+00 +432 8.6373e+00 0.0000e+00 0.0000e+00 +433 8.6573e+00 0.0000e+00 0.0000e+00 +434 8.6774e+00 0.0000e+00 0.0000e+00 +435 8.6974e+00 0.0000e+00 0.0000e+00 +436 8.7174e+00 0.0000e+00 0.0000e+00 +437 8.7375e+00 0.0000e+00 0.0000e+00 +438 8.7575e+00 0.0000e+00 0.0000e+00 +439 8.7776e+00 0.0000e+00 0.0000e+00 +440 8.7976e+00 0.0000e+00 0.0000e+00 +441 8.8176e+00 0.0000e+00 0.0000e+00 +442 8.8377e+00 0.0000e+00 0.0000e+00 +443 8.8577e+00 0.0000e+00 0.0000e+00 +444 8.8778e+00 0.0000e+00 0.0000e+00 +445 8.8978e+00 0.0000e+00 0.0000e+00 +446 8.9178e+00 0.0000e+00 0.0000e+00 +447 8.9379e+00 0.0000e+00 0.0000e+00 +448 8.9579e+00 0.0000e+00 0.0000e+00 +449 8.9780e+00 0.0000e+00 0.0000e+00 +450 8.9980e+00 0.0000e+00 0.0000e+00 +451 9.0180e+00 0.0000e+00 0.0000e+00 +452 9.0381e+00 0.0000e+00 0.0000e+00 +453 9.0581e+00 0.0000e+00 0.0000e+00 +454 9.0782e+00 0.0000e+00 0.0000e+00 +455 9.0982e+00 0.0000e+00 0.0000e+00 +456 9.1182e+00 0.0000e+00 0.0000e+00 +457 9.1383e+00 0.0000e+00 0.0000e+00 +458 9.1583e+00 0.0000e+00 0.0000e+00 +459 9.1784e+00 0.0000e+00 0.0000e+00 +460 9.1984e+00 0.0000e+00 0.0000e+00 +461 9.2184e+00 0.0000e+00 0.0000e+00 +462 9.2385e+00 0.0000e+00 0.0000e+00 +463 9.2585e+00 0.0000e+00 0.0000e+00 +464 9.2786e+00 0.0000e+00 0.0000e+00 +465 9.2986e+00 0.0000e+00 0.0000e+00 +466 9.3186e+00 0.0000e+00 0.0000e+00 +467 9.3387e+00 0.0000e+00 0.0000e+00 +468 9.3587e+00 0.0000e+00 0.0000e+00 +469 9.3788e+00 0.0000e+00 0.0000e+00 +470 9.3988e+00 0.0000e+00 0.0000e+00 +471 9.4188e+00 0.0000e+00 0.0000e+00 +472 9.4389e+00 0.0000e+00 0.0000e+00 +473 9.4589e+00 0.0000e+00 0.0000e+00 +474 9.4790e+00 0.0000e+00 0.0000e+00 +475 9.4990e+00 0.0000e+00 0.0000e+00 +476 9.5190e+00 0.0000e+00 0.0000e+00 +477 9.5391e+00 0.0000e+00 0.0000e+00 +478 9.5591e+00 0.0000e+00 0.0000e+00 +479 9.5792e+00 0.0000e+00 0.0000e+00 +480 9.5992e+00 0.0000e+00 0.0000e+00 +481 9.6192e+00 0.0000e+00 0.0000e+00 +482 9.6393e+00 0.0000e+00 0.0000e+00 +483 9.6593e+00 0.0000e+00 0.0000e+00 +484 9.6794e+00 0.0000e+00 0.0000e+00 +485 9.6994e+00 0.0000e+00 0.0000e+00 +486 9.7194e+00 0.0000e+00 0.0000e+00 +487 9.7395e+00 0.0000e+00 0.0000e+00 +488 9.7595e+00 0.0000e+00 0.0000e+00 +489 9.7796e+00 0.0000e+00 0.0000e+00 +490 9.7996e+00 0.0000e+00 0.0000e+00 +491 9.8196e+00 0.0000e+00 0.0000e+00 +492 9.8397e+00 0.0000e+00 0.0000e+00 +493 9.8597e+00 0.0000e+00 0.0000e+00 +494 9.8798e+00 0.0000e+00 0.0000e+00 +495 9.8998e+00 0.0000e+00 0.0000e+00 +496 9.9198e+00 0.0000e+00 0.0000e+00 +497 9.9399e+00 0.0000e+00 0.0000e+00 +498 9.9599e+00 0.0000e+00 0.0000e+00 +499 9.9800e+00 0.0000e+00 0.0000e+00 +500 1.0000e+01 0.0000e+00 0.0000e+00 + + diff --git a/src/USER-MISC/README b/src/USER-MISC/README index 442feedf87..3b96f3685d 100644 --- a/src/USER-MISC/README +++ b/src/USER-MISC/README @@ -84,6 +84,7 @@ pair_style lebedeva/z, Zbigniew Koziol (National Center for Nuclear Research), s pair_style lennard/mdf, Paolo Raiteri, p.raiteri at curtin.edu.au, 2 Dec 15 pair_style list, Axel Kohlmeyer (Temple U), akohlmey at gmail.com, 1 Jun 13 pair_style lj/mdf, Paolo Raiteri, p.raiteri at curtin.edu.au, 2 Dec 15 +pair_style local/density, Tanmoy Sanyal (tanmoy dot 7989 at gmail.com) and M. Scott Shell (UCSB), and David Rosenberger (TU Darmstadt), 9 Sept 19 pair_style kolmogorov/crespi/full, Wengen Ouyang (Tel Aviv University), w.g.ouyang at gmail dot com, 30 Mar 18 pair_style kolmogorov/crespi/z, Jaap Kroes (Radboud U), jaapkroes at gmail dot com, 28 Feb 17 pair_style meam/spline, Alexander Stukowski (LLNL), alex at stukowski.com, 1 Feb 12 diff --git a/src/USER-MISC/pair_local_density.cpp b/src/USER-MISC/pair_local_density.cpp new file mode 100644 index 0000000000..883075c80e --- /dev/null +++ b/src/USER-MISC/pair_local_density.cpp @@ -0,0 +1,871 @@ +/* -*- c++ -*- ---------------------------------------------------------- + LAMMPS - Large-scale Atomic/Molecular Massively Parallel Simulator + http://lammps.sandia.gov, Sandia National Laboratories + Steve Plimpton, sjplimp@sandia.gov + + Copyright (2003) Sandia Corporation. Under the terms of Contract + DE-AC04-94AL85000 with Sandia Corporation, the U.S. Government retains + certain rights in this software. This software is distributed under + the GNU General Public License. + + See the README file in the top-level LAMMPS directory. +------------------------------------------------------------------------- */ + +/* ---------------------------------------------------------------------- + Contributing authors: + Tanmoy Sanyal, M.Scott Shell, UC Santa Barbara + David Rosenberger, TU Darmstadt +------------------------------------------------------------------------- */ + +#include "pair_local_density.h" +#include +#include +#include +#include +#include +#include "atom.h" +#include "force.h" +#include "comm.h" +#include "neighbor.h" +#include "neigh_list.h" +#include "neigh_request.h" +#include "memory.h" +#include "error.h" +#include "domain.h" + +using namespace LAMMPS_NS; + +#define MAXLINE 1024 + +/* ---------------------------------------------------------------------- */ + +PairLocalDensity::PairLocalDensity(LAMMPS *lmp) : Pair(lmp) +{ + restartinfo = 0; + one_coeff = 1; + single_enable = 1; + + // stuff read from tabulated file + nLD = 0; + nrho = 0; + rho_min = NULL; + rho_max = NULL; + a = NULL; + b = NULL; + c0 = NULL; + c2 = NULL; + c4 = NULL; + c6 = NULL; + uppercut = NULL; + lowercut = NULL; + uppercutsq = NULL; + lowercutsq = NULL; + frho = NULL; + rho = NULL; + + // splined arrays + frho_spline = NULL; + + // per-atom arrays + nmax = 0; + fp = NULL; + localrho = NULL; + + // set comm size needed by this pair + comm_forward = 1; + comm_reverse = 1; +} + +/* ---------------------------------------------------------------------- + check if allocated, since class can be destructed when incomplete +------------------------------------------------------------------------- */ + +PairLocalDensity::~PairLocalDensity() +{ + + memory->destroy(localrho); + memory->destroy(fp); + + if (allocated) { + memory->destroy(setflag); + memory->destroy(cutsq); + } + + memory->destroy(frho_spline); + + memory->destroy(rho_min); + memory->destroy(rho_max); + memory->destroy(delta_rho); + memory->destroy(c0); + memory->destroy(c2); + memory->destroy(c4); + memory->destroy(c6); + memory->destroy(uppercut); + memory->destroy(lowercut); + memory->destroy(uppercutsq); + memory->destroy(lowercutsq); + memory->destroy(frho); + memory->destroy(rho); + + memory->destroy(a); + memory->destroy(b); +} + +/* ---------------------------------------------------------------------- */ + +void PairLocalDensity::compute(int eflag, int vflag) +{ + + int i,j,ii,jj,m,k,inum,jnum,itype,jtype; + double xtmp,ytmp,ztmp,delx,dely,delz,rsq; + double rsqinv, phi, uLD, dphi, evdwl,fpair; + double p, *coeff; + int *ilist,*jlist,*numneigh,**firstneigh; + + phi = uLD = evdwl = fpair = rsqinv = 0.0; + + if (eflag || vflag) ev_setup(eflag,vflag); + else evflag = vflag_fdotr = eflag_global = eflag_atom = 0; + + /* localrho = LD at each atom + fp = derivative of embedding energy at each atom for each LD potential + uLD = embedding energy of each atom due to each LD potential*/ + + // grow LD and fp arrays if necessary + // need to be atom->nmax in length + + if (atom->nmax > nmax) { + memory->destroy(localrho); + memory->destroy(fp); + nmax = atom->nmax; + memory->create(localrho, nLD, nmax, "pairLD:localrho"); + memory->create(fp, nLD, nmax, "pairLD:fp"); + } + + double **x = atom->x; + double **f = atom->f; + int *type = atom->type; + int nlocal = atom->nlocal; + int newton_pair = force->newton_pair; + + inum = list->inum; + ilist = list->ilist; + numneigh = list->numneigh; + firstneigh = list->firstneigh; + + // zero out LD and fp + + if (newton_pair) { + m = nlocal + atom->nghost; + for (k = 0; k < nLD; k++) { + for (i = 0; i < m; i++) { + localrho[k][i] = 0.0; + fp[k][i] = 0.0; + } + } + } + else { + for (k = 0; k < nLD; k++){ + for (i = 0; i < nlocal; i++) { + localrho[k][i] = 0.0; + fp[k][i] = 0.0; + } + } + } + + // loop over neighs of central atoms and types of LDs + + for (ii = 0; ii < inum; ii++) { + i = ilist[ii]; + xtmp = x[i][0]; + ytmp = x[i][1]; + ztmp = x[i][2]; + itype = type[i]; + jlist = firstneigh[i]; + jnum = numneigh[i]; + + for (jj = 0; jj < jnum; jj++) { + j = jlist[jj]; + j &= NEIGHMASK; + jtype = type[j]; + + // calculate distance-squared between i,j atom-types + + delx = xtmp - x[j][0]; + dely = ytmp - x[j][1]; + delz = ztmp - x[j][2]; + rsq = delx*delx + dely*dely + delz*delz; + + // calculating LDs based on central and neigh filters + + for (k = 0; k < nLD; k++) { + if (rsq < lowercutsq[k]) { + phi = 1.0; + } + else if (rsq > uppercutsq[k]) { + phi = 0.0; + } + else { + phi = c0[k] + rsq * (c2[k] + rsq * (c4[k] + c6[k]*rsq)); + } + localrho[k][i] += (phi * b[k][jtype]); + + /*checking for both i,j is necessary + since a half neighbor list is processed.*/ + + if (newton_pair || jreverse_comm_pair(this); + + // + + for (ii = 0; ii < inum; ii++) { + i = ilist[ii]; + itype = type[i]; + uLD = 0.0; + + for (k = 0; k < nLD; k++) { + + /*skip over this loop if the LD potential + is not intendend for central atomtype */ + if (!(a[k][itype])) continue; + + // linear extrapolation at rho_min and rho_max + + if (localrho[k][i] <= rho_min[k]) { + coeff = frho_spline[k][0]; + fp[k][i] = coeff[2]; + uLD += a[k][itype] * ( coeff[6] + fp[k][i]*(localrho[k][i] - rho_min[k]) ); + } + else if (localrho[k][i] >= rho_max[k]) { + coeff = frho_spline[k][nrho-2]; + fp[k][i] = coeff[0] + coeff[1] + coeff[2]; + uLD += a[k][itype] * ( (coeff[3] + coeff[4] + coeff[5] + coeff[6]) + fp[k][i]*(localrho[k][i] - rho_max[k]) ); + } + else { + p = (localrho[k][i] - rho_min[k]) / delta_rho[k]; + m = static_cast (p); + m = MAX(0, MIN(m, nrho-2)); + p -= m; + p = MIN(p, 1.0); + coeff = frho_spline[k][m]; + fp[k][i] = (coeff[0]*p + coeff[1])*p + coeff[2]; + uLD += a[k][itype] * (((coeff[3]*p + coeff[4])*p + coeff[5])*p + coeff[6]); + } + } + + if (eflag) { + if (eflag_global) eng_vdwl += uLD; + if (eflag_atom) eatom[i] += uLD; + } + } + + // communicate LD and fp to all procs + + comm->forward_comm_pair(this); + + // compute forces on each atom + // loop over neighbors of my atoms + + for (ii = 0; ii < inum; ii++) { + i = ilist[ii]; + xtmp = x[i][0]; + ytmp = x[i][1]; + ztmp = x[i][2]; + itype = type[i]; + + jlist = firstneigh[i]; + jnum = numneigh[i]; + + for (jj = 0; jj < jnum; jj++) { + j = jlist[jj]; + j &= NEIGHMASK; + jtype = type[j]; + + // calculate square of distance between i,j atoms + + delx = xtmp - x[j][0]; + dely = ytmp - x[j][1]; + delz = ztmp - x[j][2]; + rsq = delx*delx + dely*dely + delz*delz; + + // calculate force between two atoms + fpair = 0.0; + if (rsq < cutforcesq) { // global cutoff check + rsqinv = 1.0/rsq; + for (k = 0; k < nLD; k++) { + if (rsq >= lowercutsq[k] && rsq < uppercutsq[k]) { + dphi = rsq * (2.0*c2[k] + rsq * (4.0*c4[k] + 6.0*c6[k]*rsq)); + fpair += -(a[k][itype]*b[k][jtype]*fp[k][i] + a[k][jtype]*b[k][itype]*fp[k][j]) * dphi; + } + } + fpair *= rsqinv; + + f[i][0] += delx*fpair; + f[i][1] += dely*fpair; + f[i][2] += delz*fpair; + if (newton_pair || j < nlocal) { + f[j][0] -= delx*fpair; + f[j][1] -= dely*fpair; + f[j][2] -= delz*fpair; + } + + /*eng_vdwl has already been completely built, + so no need to add anything here*/ + + if (eflag) evdwl = 0.0; + + if (evflag) ev_tally(i,j,nlocal,newton_pair, + evdwl,0.0,fpair,delx,dely,delz); + } + + } + } + + if (vflag_fdotr) virial_fdotr_compute(); +} + + +/* ---------------------------------------------------------------------- + allocate all arrays +------------------------------------------------------------------------- */ + +void PairLocalDensity::allocate() +{ + allocated = 1; + int n = atom->ntypes; + + memory->create(cutsq,n+1,n+1,"pair:cutsq"); + + memory->create(setflag,n+1,n+1,"pair:setflag"); + for (int i = 1; i <= n; i++) + for (int j = i; j <= n; j++) + setflag[i][j] = 0; +} + +/* ---------------------------------------------------------------------- + global settings +------------------------------------------------------------------------- */ + +void PairLocalDensity::settings(int narg, char **arg) +{ + if (narg > 0) error->all(FLERR,"Illegal pair_style command"); +} + +/* ---------------------------------------------------------------------- + set coeffs for all type pairs + read tabulated LD input file +------------------------------------------------------------------------- */ + +void PairLocalDensity::coeff(int narg, char **arg) +{ + int i, j; + if (!allocated) allocate(); + + if (narg != 3) error->all(FLERR,"Incorrect args for pair coefficients"); + + // insure I,J args are * * + + if (strcmp(arg[0],"*") != 0 || strcmp(arg[1],"*") != 0) + error->all(FLERR,"Incorrect args for pair coefficients"); + + // parse LD file + + parse_file(arg[2]); + + + // clear setflag since coeff() called once with I,J = * * + + for (i = 1; i <= atom->ntypes; i++) + for (j = i; j <= atom->ntypes; j++) + setflag[i][j] = 0; + + // set setflag for all i,j type pairs + + int count = 0; + for (i = 1; i <= atom->ntypes; i++) { + for (j = i; j <= atom->ntypes; j++) { + setflag[i][j] = 1; + count++; + } + } + if (count == 0) error->all(FLERR,"Incorrect args for pair coefficients"); +} + +/* ---------------------------------------------------------------------- + init specific to this pair style +------------------------------------------------------------------------- */ + +void PairLocalDensity::init_style() +{ + // spline rho and frho arrays + // request half neighbor list + + array2spline(); + + // half neighbor request + neighbor->request(this); +} + +/* ---------------------------------------------------------------------- + init for one type pair i,j and corresponding j,i +------------------------------------------------------------------------- */ + +double PairLocalDensity::init_one(int i, int j) +{ + // single global cutoff = max of all uppercuts read in from LD file + + cutmax = 0.0; + for (int k = 0; k < nLD; k++) + cutmax = MAX(cutmax,uppercut[k]); + + cutforcesq = cutmax*cutmax; + + return cutmax; +} + + +/*-------------------------------------------------------------------------- + pair_write functionality for this pair style that gives just a snap-shot + of the LD potential without doing an actual MD run + ---------------------------------------------------------------------------*/ + +double PairLocalDensity::single(int i, int j, int itype, int jtype, double rsq, + double factor_coul, double factor_lj, + double &fforce) +{ + int m, k, index; + double rsqinv, p, uLD; + double *coeff, **LD; + double dFdrho, phi, dphi; + + uLD = dFdrho = dphi = 0.0; + + memory->create(LD, nLD, 3, "pairLD:LD"); + for (k = 0; k < nLD; k++) { + LD[k][1] = 0.0; // itype:- 1 + LD[k][2] = 0.0; // jtype:- 2 + } + + rsqinv = 1.0/rsq; + for (k = 0; k < nLD; k++) { + if (rsq < lowercutsq[k]) { + phi = 1.0; + } + else if (rsq > uppercutsq[k]) { + phi = 0.0; + } + else { + phi = c0[k] + rsq * (c2[k] + rsq * (c4[k] + c6[k]*rsq)); + } + LD[k][1] += (phi * b[k][jtype]); + LD[k][2] += (phi * b[k][itype]); + } + + for (k = 0; k < nLD; k++) { + if (a[k][itype]) index = 1; + if (a[k][jtype]) index = 2; + + if (LD[k][index] <= rho_min[k]) { + coeff = frho_spline[k][0]; + dFdrho = coeff[2]; + uLD += a[k][itype] * ( coeff[6] + dFdrho*(LD[k][index] - rho_min[k]) ); + } + else if (LD[k][index] >= rho_max[k]) { + coeff = frho_spline[k][nrho-1]; + dFdrho = coeff[0] + coeff[1] + coeff[2]; + uLD += a[k][itype] * ( (coeff[3] + coeff[4] + coeff[5] + coeff[6]) + dFdrho*(LD[k][index] - rho_max[k]) ); + } + else { + p = (LD[k][index] - rho_min[k]) / delta_rho[k]; + m = static_cast (p); + m = MAX(0, MIN(m, nrho-2)); + p -= m; + p = MIN(p, 1.0); + coeff = frho_spline[k][m]; + dFdrho = (coeff[0]*p + coeff[1])*p + coeff[2]; + uLD += a[k][itype] * (((coeff[3]*p + coeff[4])*p + coeff[5])*p + coeff[6]); + } + + if (rsq < lowercutsq[k]) { + dphi = 0.0; + } + else if (rsq > uppercutsq[k]) { + dphi = 0.0; + } + else { + dphi = rsq * (2.0*c2[k] + rsq * (4.0*c4[k] + 6.0*c6[k]*rsq)); + } + fforce += -(a[k][itype]*b[k][jtype]*dFdrho + a[k][jtype]*b[k][itype]*dFdrho) * dphi *rsqinv; + } + memory->destroy(LD); + + return uLD; +} + +/*-------------------------------------------------------------------- + spline the array frho read in from the file to create + frho_spline +---------------------------------------------------------------------- */ + +void PairLocalDensity::array2spline() { + memory->destroy(frho_spline); + memory->create(frho_spline, nLD, nrho, 7, "pairLD:frho_spline"); + + for (int k = 0; k < nLD; k++) + interpolate_cbspl(nrho, delta_rho[k], frho[k], frho_spline[k]); + +} + +/* ---------------------------------------------------------------------- + (one-dimensional) cubic spline interpolation sub-routine, + which determines the coeffs for a clamped cubic spline + given tabulated data + ------------------------------------------------------------------------*/ + +void PairLocalDensity::interpolate_cbspl(int n, double delta, + double *f, double **spline) +{ +/* inputs: + n number of interpolating points + + f array containing function values to + be interpolated; f[i] is the function + value corresponding to x[i] + ('x' refers to the independent var) + + delta difference in tabulated values of x + + outputs: (packaged as columns of the coeff matrix) + coeff_b coeffs of linear terms + coeff_c coeffs of quadratic terms + coeff_d coeffs of cubic terms + spline matrix that collects b,c,d + + + other parameters: + fpa derivative of function at x=a + fpb derivative of function at x=b +*/ + + double *dl, *dd, *du; + double *coeff_b, *coeff_c, *coeff_d; + double fpa, fpb; + + int i; + + coeff_b = new double [n]; + coeff_c = new double [n]; + coeff_d = new double [n]; + dl = new double [n]; + dd = new double [n]; + du = new double [n]; + + // initialize values + for ( i = 0; i= 0; i-- ) + coeff_c[i] -= coeff_c[i+1] * du[i]; + + for ( i = 0; i < n-1; i++ ) { + coeff_d[i] = ( coeff_c[i+1] - coeff_c[i] ) / ( 3.0 * delta ); + coeff_b[i] = ( f[i+1] - f[i] ) / delta - delta * ( coeff_c[i+1] + 2.0*coeff_c[i] ) / 3.0; + } + + // normalize + for ( i = 0; i < n-1; i++ ) { + coeff_b[i] = coeff_b[i] * delta ; + coeff_c[i] = coeff_c[i] * delta*delta ; + coeff_d[i] = coeff_d[i] * delta*delta*delta; + } + + //copy to coefficient matrix + for ( i = 0; i < n; i++) { + spline[i][3] = coeff_d[i]; + spline[i][4] = coeff_c[i]; + spline[i][5] = coeff_b[i]; + spline[i][6] = f[i]; + spline[i][2] = spline[i][5]/delta; + spline[i][1] = 2.0*spline[i][4]/delta; + spline[i][0] = 3.0*spline[i][3]/delta; + } + + delete [] coeff_b; + delete [] coeff_c; + delete [] coeff_d; + delete [] du; + delete [] dd; + delete [] dl; +} + +/* ---------------------------------------------------------------------- + read potential values from tabulated LD input file +------------------------------------------------------------------------- */ + +void PairLocalDensity::parse_file(char *filename) { + + int k, n; + int me = comm->me; + FILE *fptr; + char line[MAXLINE]; + double ratio, lc2, uc2, denom; + + + if (me == 0) { + fptr = fopen(filename, "r"); + if (fptr == NULL) { + char str[128]; + sprintf(str,"Cannot open Local Density potential file %s",filename); + error->one(FLERR,str); + } + } + + double *ftmp; // tmp var to extract the complete 2D frho array from file + + // broadcast number of LD potentials and number of (rho,frho) pairs + if (me == 0) { + + // first 2 comment lines ignored + fgets(line,MAXLINE,fptr); + fgets(line,MAXLINE,fptr); + + // extract number of potentials and number of (frho, rho) points + fgets(line,MAXLINE,fptr); + sscanf(line, "%d %d", &nLD, &nrho); + fgets(line,MAXLINE,fptr); + } + + MPI_Bcast(&nLD,1,MPI_INT,0,world); + MPI_Bcast(&nrho,1,MPI_INT,0,world); + + // setting up all arrays to be read from files and broadcasted + memory->create(uppercut, nLD, "pairLD:uppercut"); + memory->create(lowercut, nLD, "pairLD:lowercut"); + memory->create(uppercutsq, nLD, "pairLD:uppercutsq"); + memory->create(lowercutsq, nLD, "pairLD:lowercutsq"); + memory->create(c0, nLD, "pairLD:c0"); + memory->create(c2, nLD, "pairLD:c2"); + memory->create(c4, nLD, "pairLD:c4"); + memory->create(c6, nLD, "pairLD:c6"); + memory->create(rho_min, nLD, "pairLD:rho_min"); + memory->create(rho_max, nLD, "pairLD:rho_max"); + memory->create(delta_rho, nLD,"pairLD:delta_rho"); + memory->create(ftmp, nrho*nLD, "pairLD:ftmp"); + + // setting up central and neighbor atom filters + memory->create(a, nLD, atom->ntypes+1 , "pairLD:a"); + memory->create(b, nLD, atom->ntypes+1, "pairLD:b"); + if (me == 0) { + for (n = 1; n <= atom->ntypes; n++){ + for (k = 0; k < nLD; k++) { + a[k][n] = 0; + b[k][n] = 0; + } + } + } + + // read file block by block + + if (me == 0) { + for (k = 0; k < nLD; k++) { + + // parse upper and lower cut values + if (fgets(line,MAXLINE,fptr)==NULL) break; + sscanf(line, "%lf %lf", &lowercut[k], &uppercut[k]); + + // parse and broadcast central atom filter + fgets(line, MAXLINE, fptr); + char *tmp = strtok(line, " /t/n/r/f"); + while (tmp != NULL) { + a[k][atoi(tmp)] = 1; + tmp = strtok(NULL, " /t/n/r/f"); + } + + // parse neighbor atom filter + fgets(line, MAXLINE, fptr); + tmp = strtok(line, " /t/n/r/f"); + while (tmp != NULL) { + b[k][atoi(tmp)] = 1; + tmp = strtok(NULL, " /t/n/r/f"); + } + + // parse min, max and delta rho values + fgets(line, MAXLINE, fptr); + sscanf(line, "%lf %lf %lf", &rho_min[k], &rho_max[k], &delta_rho[k]); + // recompute delta_rho from scratch for precision + delta_rho[k] = (rho_max[k] - rho_min[k]) / (nrho - 1); + + // parse tabulated frho values from each line into temporary array + for (n = 0; n < nrho; n++) { + fgets(line,MAXLINE,fptr); + sscanf(line, "%lf", &ftmp[k*nrho + n]); + } + + // ignore blank line at the end of every block + fgets(line,MAXLINE,fptr); + + // set coefficients for local density indicator function + uc2 = uppercut[k] * uppercut[k]; + uppercutsq[k] = uc2; + lc2 = lowercut[k] * lowercut[k]; + lowercutsq[k] = lc2; + ratio = lc2/uc2; + denom = 1.0 - ratio; + denom = denom*denom*denom; + c0[k] = (1 - 3.0 * ratio) / denom; + c2[k] = (6.0 * ratio) / (uc2 * denom); + c4[k] = -(3.0 + 3.0*ratio) / (uc2*uc2 * denom); + c6[k] = 2.0 / (uc2*uc2*uc2 * denom); + } + } + + // Broadcast all parsed arrays + MPI_Bcast(&lowercut[0], nLD, MPI_DOUBLE, 0, world); + MPI_Bcast(&uppercut[0], nLD, MPI_DOUBLE, 0, world); + MPI_Bcast(&lowercutsq[0], nLD, MPI_DOUBLE, 0, world); + MPI_Bcast(&uppercutsq[0], nLD, MPI_DOUBLE, 0, world); + MPI_Bcast(&c0[0], nLD, MPI_DOUBLE, 0, world); + MPI_Bcast(&c2[0], nLD, MPI_DOUBLE, 0, world); + MPI_Bcast(&c4[0], nLD, MPI_DOUBLE, 0, world); + MPI_Bcast(&c6[0], nLD, MPI_DOUBLE, 0, world); + for (k = 0; k < nLD; k++) { + MPI_Bcast(&a[k][1], atom->ntypes, MPI_INT, 0, world); + MPI_Bcast(&b[k][1], atom->ntypes, MPI_INT, 0, world); + } + MPI_Bcast(&rho_min[0], nLD, MPI_DOUBLE, 0, world); + MPI_Bcast(&rho_max[0], nLD, MPI_DOUBLE, 0, world); + MPI_Bcast(&delta_rho[0], nLD, MPI_DOUBLE, 0, world); + MPI_Bcast(&ftmp[0], nLD*nrho, MPI_DOUBLE, 0, world); + + if (me == 0) fclose(fptr); + + // set up rho and frho arrays + memory->create(rho, nLD, nrho, "pairLD:rho"); + memory->create(frho, nLD, nrho, "pairLD:frho"); + + for (k = 0; k < nLD; k++) { + for (n = 0; n < nrho; n++) { + rho[k][n] = rho_min[k] + n*delta_rho[k]; + frho[k][n] = ftmp[k*nrho + n]; + } + } + + // delete temporary array + memory->destroy(ftmp); +} + +/* ---------------------------------------------------------------------- + communication routines +------------------------------------------------------------------------- */ + +int PairLocalDensity::pack_comm(int n, int *list, double *buf, int pbc_flag, int *pbc) { + int i,j,k; + int m; + + m = 0; + for (i = 0; i < n; i++) { + j = list[i]; + for (k = 0; k < nLD; k++) { + buf[m++] = fp[k][j]; + } + } + + return nLD; +} + +/* ---------------------------------------------------------------------- */ + +void PairLocalDensity::unpack_comm(int n, int first, double *buf) { + + int i,k,m,last; + + m = 0; + last = first + n; + for (i = first; i < last; i++) { + for (k = 0; k < nLD; k++) { + fp[k][i] = buf[m++]; + } + } +} + +/* ---------------------------------------------------------------------- */ + +int PairLocalDensity::pack_reverse_comm(int n, int first, double *buf) { + + int i,k,m,last; + + m = 0; + last = first + n; + for (i = first; i < last; i++) { + for (k = 0; k < nLD; k++) { + buf[m++] = localrho[k][i]; + } + } + return nLD; +} + +/* ---------------------------------------------------------------------- */ + +void PairLocalDensity::unpack_reverse_comm(int n, int *list, double *buf) { + + int i,j,k; + int m; + + m = 0; + for (i = 0; i < n; i++) { + j = list[i]; + for (k = 0; k < nLD; k++) { + localrho[k][j] += buf[m++]; + } + } +} + +/* ---------------------------------------------------------------------- + memory usage of local atom-based arrays +------------------------------------------------------------------------- */ + +double PairLocalDensity::memory_usage() +{ + double bytes = maxeatom * sizeof(double); + bytes += maxvatom*6 * sizeof(double); + bytes += 2 * (nmax*nLD) * sizeof(double); + return bytes; +} + diff --git a/src/USER-MISC/pair_local_density.h b/src/USER-MISC/pair_local_density.h new file mode 100644 index 0000000000..77aab1399b --- /dev/null +++ b/src/USER-MISC/pair_local_density.h @@ -0,0 +1,88 @@ +/* -*- c++ -*- ---------------------------------------------------------- + LAMMPS - Large-scale Atomic/Molecular Massively Parallel Simulator + http://lammps.sandia.gov, Sandia National Laboratories + Steve Plimpton, sjplimp@sandia.gov + + Copyright (2003) Sandia Corporation. Under the terms of Contract + DE-AC04-94AL85000 with Sandia Corporation, the U.S. Government retains + certain rights in this software. This software is distributed under + the GNU General Public License. + + See the README file in the top-level LAMMPS directory. +------------------------------------------------------------------------- + pair_LocalDensity written by: + Tanmoy Sanyal and M. Scott Shell from UC Santa Barbara + David Rosenberger: TU Darmstadt +-------------------------------------------------------------------------*/ + + +#ifdef PAIR_CLASS + +PairStyle(local/density,PairLocalDensity) + +#else + +#ifndef LMP_PAIR_LOCAL_DENSITY_H +#define LMP_PAIR_LOCAL_DENSITY_H + +#include "pair.h" + + +namespace LAMMPS_NS { + +class PairLocalDensity : public Pair { + public: + PairLocalDensity(class LAMMPS *); + virtual ~PairLocalDensity(); + virtual void compute(int, int); + void settings(int, char **); + virtual void coeff(int, char **); + void init_style(); + double init_one(int, int); + double single(int, int, int, int, double, double, double, double &); + + virtual int pack_comm(int, int *, double *, int, int *); + virtual void unpack_comm(int, int, double *); + int pack_reverse_comm(int, int, double *); + void unpack_reverse_comm(int, int *, double *); + double memory_usage(); + + + protected: + //------------------------------------------------------------------------ + //This information is read from the tabulated input file + + int nLD, nrho; // number of LD types + int **a, **b; // central and neigh atom filters + double *uppercut, *lowercut; // upper and lower cutoffs + double *uppercutsq, *lowercutsq; // square of above cutoffs + double *c0, *c2, *c4, *c6; // coeffs for indicator function + double *rho_min, *rho_max, *delta_rho; // min, max & grid-size for LDs + double **rho, **frho; // LD and LD function tables + + //------------------------------------------------------------------------ + + double ***frho_spline; // splined LD potentials + double cutmax; // max cutoff for all elements + double cutforcesq; // square of global upper cutoff + + int nmax; // max size of per-atom arrays + double **localrho; // per-atom LD + double **fp; // per-atom LD potential function derivative + + void allocate(); + + // read tabulated input file + void parse_file(char *); + + // convert array to spline + void array2spline(); + + // cubic spline interpolation + void interpolate_cbspl(int, double, double *, double **); +}; + +} + +#endif +#endif From 91a19719773e02f05de9b44c418a6d93cc2a143c Mon Sep 17 00:00:00 2001 From: "tanmoy.7989" Date: Mon, 9 Sep 2019 02:04:59 -0700 Subject: [PATCH 107/192] added a line to tools/README and fixed the alphabetical ordering in docs --- doc/src/Tools.txt | 29 +++++++++++++++-------------- tools/README | 1 + 2 files changed, 16 insertions(+), 14 deletions(-) diff --git a/doc/src/Tools.txt b/doc/src/Tools.txt index 6c41524d20..e1042f3a7e 100644 --- a/doc/src/Tools.txt +++ b/doc/src/Tools.txt @@ -486,6 +486,21 @@ README for more info on Pizza.py and how to use these scripts. :line +replica tool :h4,link(replica) + +The tools/replica directory contains the reorder_remd_traj python script which +can be used to reorder the replica trajectories (resulting from the use of the +temper command) according to temperature. This will produce discontinuous +trajectories with all frames at the same temperature in each trajectory. +Additional options can be used to calculate the canonical configurational +log-weight for each frame at each temperature using the pymbar package. See +the README.md file for further details. Try out the peptide example provided. + +This tool was written by Tanmoy Sanyal, while at the Shell lab +at UC Santa Barbara. (tanmoy dot 7989 at gmail.com) + +:line + reax tool :h4,link(reax_tool) The reax sub-directory contains stand-alone codes that can @@ -551,17 +566,3 @@ See the README file for details. These files were provided by Vikas Varshney (vv0210 at gmail.com) -:line - -replica tool :h4,link(replica) - -The tools/replica directory contains the reorder_remd_traj python script which -can be used to reorder the replica trajectories (resulting from the use of the -temper command) according to temperature. This will produce discontinuous -trajectories with all frames at the same temperature in each trajectory. -Additional options can be used to calculate the canonical configurational -log-weight for each frame at each temperature using the pymbar package. See -the README.md file for further details. Try out the peptide example provided. - -This tool was written by Tanmoy Sanyal, while at the Shell lab -at UC Santa Barbara. (tanmoy dot 7989 at gmail.com) diff --git a/tools/README b/tools/README index 54f8d86898..b20e82c53e 100644 --- a/tools/README +++ b/tools/README @@ -38,6 +38,7 @@ polybond Python tool for programmable polymer bonding pymol_asphere convert LAMMPS output of ellipsoids to PyMol format python Python scripts for post-processing LAMMPS output reax Tools for analyzing output of ReaxFF simulations +replica tool to reorder LAMMPS replica trajectories according to temperature smd convert Smooth Mach Dynamics triangles to VTK spin perform a cubic polynomial interpolation of a GNEB MEP vim add-ons to VIM editor for editing LAMMPS input scripts From e7d8165a46b7541f466b1b448376f8944f7f1872 Mon Sep 17 00:00:00 2001 From: "tanmoy.7989" Date: Mon, 9 Sep 2019 02:16:30 -0700 Subject: [PATCH 108/192] fixed spelling mistakes reported by sphix --- doc/src/pair_local_density.txt | 4 ++-- doc/utils/sphinx-config/false_positives.txt | 9 ++++++++- 2 files changed, 10 insertions(+), 3 deletions(-) diff --git a/doc/src/pair_local_density.txt b/doc/src/pair_local_density.txt index 8cba705664..f9a410c3be 100644 --- a/doc/src/pair_local_density.txt +++ b/doc/src/pair_local_density.txt @@ -29,7 +29,7 @@ sense,a generalization of embedded atom models (EAM). The name "local density potential" arises from the fact that it assigns an energy to an atom depending on the number of neighboring atoms of given type around it within a predefined spherical volume (i.e., within a cutoff). The bottom-up coarse-graining (CG) -literature sugggests that such potentials can be widely useful in capturing +literature suggests that such potentials can be widely useful in capturing effective multibody forces in a computationally efficient manner so as to improve the quality of CG models of implicit solvation"(Sanyal1)"_#Sanyal1 and phase-segregation in liquid mixtures"(Sanyal2)"_#Sanyal2, and provide guidelines @@ -45,7 +45,7 @@ upon initialization. NOTE: Thus when used as the only interaction in the system, there is no corresponding pair_coeff command and when used with other pair styles using the hybrid/overlay option, the corresponding pair_coeff command must be supplied -* * as placeholders for the atomtypes. +* * as placeholders for the atom types. :line diff --git a/doc/utils/sphinx-config/false_positives.txt b/doc/utils/sphinx-config/false_positives.txt index 6d5112b4c7..ce7bdfd763 100644 --- a/doc/utils/sphinx-config/false_positives.txt +++ b/doc/utils/sphinx-config/false_positives.txt @@ -304,7 +304,7 @@ Cates Cavium Cawkwell cbecker -ccache +ccachepiecewise ccmake ccNspecies CCu @@ -622,6 +622,7 @@ Doye dpd DPD dpdTheta +dphi DPhil dr dR @@ -2137,6 +2138,7 @@ picograms picosecond picoseconds pid +piecewise Pieniazek Pieter pimd @@ -2417,6 +2419,7 @@ Rodrigues Rohart Ronchetti Rosati +Rosenberger Rossky rosybrown rotationally @@ -2456,6 +2459,7 @@ Sandia sandybrown Sanitizer sanitizers +Sanyal sc scafacos SCAFACOS @@ -2480,6 +2484,7 @@ Scripta sdk sdpd SDPD +se seagreen Secor sectoring @@ -2573,6 +2578,7 @@ Snodin Sodani Soderlind solvated +solvation Sorensen soundspeed Souza @@ -2931,6 +2937,7 @@ vectorial vectorization Vectorization vectorized +Vegt vel Verlag verlet From 22fde86fd07867eec33784272bcfd6141bd54ece Mon Sep 17 00:00:00 2001 From: "tanmoy.7989" Date: Mon, 9 Sep 2019 02:27:54 -0700 Subject: [PATCH 109/192] possible spelling mistake report from Sphinx for unidentified word ccache; added this to the false_positives.txt file --- doc/utils/sphinx-config/false_positives.txt | 1 + 1 file changed, 1 insertion(+) diff --git a/doc/utils/sphinx-config/false_positives.txt b/doc/utils/sphinx-config/false_positives.txt index ce7bdfd763..992723da76 100644 --- a/doc/utils/sphinx-config/false_positives.txt +++ b/doc/utils/sphinx-config/false_positives.txt @@ -304,6 +304,7 @@ Cates Cavium Cawkwell cbecker +ccache ccachepiecewise ccmake ccNspecies From cde16580c086e98917042ea5648d3675b64e8d02 Mon Sep 17 00:00:00 2001 From: "tanmoy.7989" Date: Mon, 9 Sep 2019 14:15:05 -0700 Subject: [PATCH 110/192] fixed alphabetical ordering in Tools.txt and added a line highlighting the tool in temper.txt --- doc/src/Tools.txt | 8 ++++---- doc/src/temper.txt | 8 +++++++- 2 files changed, 11 insertions(+), 5 deletions(-) diff --git a/doc/src/Tools.txt b/doc/src/Tools.txt index e1042f3a7e..90f598890f 100644 --- a/doc/src/Tools.txt +++ b/doc/src/Tools.txt @@ -76,10 +76,10 @@ Post-processing tools :h3 "pymol_asphere"_#pymol, "python"_#pythontools, "reax"_#reax_tool, +"replica"_#replica, "smd"_#smd, "spin"_#spin, -"xmgrace"_#xmgrace, -"replica"_#replica :tb(c=6,ea=c,a=l) +"xmgrace"_#xmgrace :tb(c=6,ea=c,a=l) Miscellaneous tools :h3 @@ -496,8 +496,8 @@ Additional options can be used to calculate the canonical configurational log-weight for each frame at each temperature using the pymbar package. See the README.md file for further details. Try out the peptide example provided. -This tool was written by Tanmoy Sanyal, while at the Shell lab -at UC Santa Barbara. (tanmoy dot 7989 at gmail.com) +This tool was written by (and is maintained by) Tanmoy Sanyal, +while at the Shell lab at UC Santa Barbara. (tanmoy dot 7989 at gmail.com) :line diff --git a/doc/src/temper.txt b/doc/src/temper.txt index edd578fbc9..6a61dfa6dd 100644 --- a/doc/src/temper.txt +++ b/doc/src/temper.txt @@ -110,7 +110,13 @@ the information from the log.lammps file. E.g. you could produce one dump file with snapshots at 300K (from all replicas), another with snapshots at 310K, etc. Note that these new dump files will not contain "continuous trajectories" for individual atoms, because two -successive snapshots (in time) may be from different replicas. +successive snapshots (in time) may be from different replicas. The +reorder_remd_traj python script can do the reordering for you +(and additionally also calculated configurational log-weights of +trajectory snapshots in the canonical ensemble). The script can be found +in the tools/replica directory while instructions on how to use it is +available in doc/Tools (in brief) and as a README file in tools/replica +(in detail). The last argument {index} in the temper command is optional and is used when restarting a tempering run from a set of restart files (one From f34f133f7d378cfe2e1b7ffaaaa40e94b42bae32 Mon Sep 17 00:00:00 2001 From: Axel Kohlmeyer Date: Mon, 9 Sep 2019 18:03:43 -0400 Subject: [PATCH 111/192] bugfix for pair style lubricate when used with walls --- src/COLLOID/pair_lubricate.cpp | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/COLLOID/pair_lubricate.cpp b/src/COLLOID/pair_lubricate.cpp index 4492de3cbb..b6288c34d2 100644 --- a/src/COLLOID/pair_lubricate.cpp +++ b/src/COLLOID/pair_lubricate.cpp @@ -41,7 +41,7 @@ using namespace MathConst; // same as fix_wall.cpp -enum{EDGE,CONSTANT,VARIABLE}; +enum{NONE=0,EDGE,CONSTANT,VARIABLE}; /* ---------------------------------------------------------------------- */ From cd846e1bbb754da6599b69b683f061fa7b72b1e4 Mon Sep 17 00:00:00 2001 From: Axel Kohlmeyer Date: Tue, 10 Sep 2019 09:18:38 -0400 Subject: [PATCH 112/192] add ITEM: UNITS line to native text format dumps --- src/dump_atom.cpp | 2 ++ src/dump_custom.cpp | 1 + src/dump_local.cpp | 1 + 3 files changed, 4 insertions(+) diff --git a/src/dump_atom.cpp b/src/dump_atom.cpp index e2e77cfb77..4c7e465bcf 100644 --- a/src/dump_atom.cpp +++ b/src/dump_atom.cpp @@ -209,6 +209,7 @@ void DumpAtom::header_binary_triclinic(bigint ndump) void DumpAtom::header_item(bigint ndump) { + fprintf(fp,"ITEM: UNITS %s\n",update->unit_style); fprintf(fp,"ITEM: TIMESTEP\n"); fprintf(fp,BIGINT_FORMAT "\n",update->ntimestep); fprintf(fp,"ITEM: NUMBER OF ATOMS\n"); @@ -224,6 +225,7 @@ void DumpAtom::header_item(bigint ndump) void DumpAtom::header_item_triclinic(bigint ndump) { + fprintf(fp,"ITEM: UNITS %s\n",update->unit_style); fprintf(fp,"ITEM: TIMESTEP\n"); fprintf(fp,BIGINT_FORMAT "\n",update->ntimestep); fprintf(fp,"ITEM: NUMBER OF ATOMS\n"); diff --git a/src/dump_custom.cpp b/src/dump_custom.cpp index ce83e442c9..c96bd44358 100644 --- a/src/dump_custom.cpp +++ b/src/dump_custom.cpp @@ -420,6 +420,7 @@ void DumpCustom::header_binary_triclinic(bigint ndump) void DumpCustom::header_item(bigint ndump) { + fprintf(fp,"ITEM: UNITS %s\n",update->unit_style); fprintf(fp,"ITEM: TIMESTEP\n"); fprintf(fp,BIGINT_FORMAT "\n",update->ntimestep); fprintf(fp,"ITEM: NUMBER OF ATOMS\n"); diff --git a/src/dump_local.cpp b/src/dump_local.cpp index 9f021a7b6a..fb64012cf1 100644 --- a/src/dump_local.cpp +++ b/src/dump_local.cpp @@ -256,6 +256,7 @@ int DumpLocal::modify_param(int narg, char **arg) void DumpLocal::write_header(bigint ndump) { if (me == 0) { + fprintf(fp,"ITEM: UNITS %s\n",update->unit_style); fprintf(fp,"ITEM: TIMESTEP\n"); fprintf(fp,BIGINT_FORMAT "\n",update->ntimestep); fprintf(fp,"ITEM: NUMBER OF %s\n",label); From 15d2e1b260d9addc544e6d90505b8b1ebc024d1a Mon Sep 17 00:00:00 2001 From: Axel Kohlmeyer Date: Tue, 10 Sep 2019 09:36:17 -0400 Subject: [PATCH 113/192] consistent formatting --- src/dump_atom.cpp | 4 ++-- src/dump_custom.cpp | 2 +- src/dump_local.cpp | 2 +- 3 files changed, 4 insertions(+), 4 deletions(-) diff --git a/src/dump_atom.cpp b/src/dump_atom.cpp index 4c7e465bcf..8f09b93f1a 100644 --- a/src/dump_atom.cpp +++ b/src/dump_atom.cpp @@ -209,7 +209,7 @@ void DumpAtom::header_binary_triclinic(bigint ndump) void DumpAtom::header_item(bigint ndump) { - fprintf(fp,"ITEM: UNITS %s\n",update->unit_style); + fprintf(fp,"ITEM: UNITS\n%s\n",update->unit_style); fprintf(fp,"ITEM: TIMESTEP\n"); fprintf(fp,BIGINT_FORMAT "\n",update->ntimestep); fprintf(fp,"ITEM: NUMBER OF ATOMS\n"); @@ -225,7 +225,7 @@ void DumpAtom::header_item(bigint ndump) void DumpAtom::header_item_triclinic(bigint ndump) { - fprintf(fp,"ITEM: UNITS %s\n",update->unit_style); + fprintf(fp,"ITEM: UNITS\n%s\n",update->unit_style); fprintf(fp,"ITEM: TIMESTEP\n"); fprintf(fp,BIGINT_FORMAT "\n",update->ntimestep); fprintf(fp,"ITEM: NUMBER OF ATOMS\n"); diff --git a/src/dump_custom.cpp b/src/dump_custom.cpp index c96bd44358..3de0e6fb3b 100644 --- a/src/dump_custom.cpp +++ b/src/dump_custom.cpp @@ -420,7 +420,7 @@ void DumpCustom::header_binary_triclinic(bigint ndump) void DumpCustom::header_item(bigint ndump) { - fprintf(fp,"ITEM: UNITS %s\n",update->unit_style); + fprintf(fp,"ITEM: UNITS\n%s\n",update->unit_style); fprintf(fp,"ITEM: TIMESTEP\n"); fprintf(fp,BIGINT_FORMAT "\n",update->ntimestep); fprintf(fp,"ITEM: NUMBER OF ATOMS\n"); diff --git a/src/dump_local.cpp b/src/dump_local.cpp index fb64012cf1..7cdc3ea16f 100644 --- a/src/dump_local.cpp +++ b/src/dump_local.cpp @@ -256,7 +256,7 @@ int DumpLocal::modify_param(int narg, char **arg) void DumpLocal::write_header(bigint ndump) { if (me == 0) { - fprintf(fp,"ITEM: UNITS %s\n",update->unit_style); + fprintf(fp,"ITEM: UNITS\n%s\n",update->unit_style); fprintf(fp,"ITEM: TIMESTEP\n"); fprintf(fp,BIGINT_FORMAT "\n",update->ntimestep); fprintf(fp,"ITEM: NUMBER OF %s\n",label); From 4bbe4c73aa27c15d2408fcd2009e0bfd87b130be Mon Sep 17 00:00:00 2001 From: Axel Kohlmeyer Date: Tue, 10 Sep 2019 09:38:44 -0400 Subject: [PATCH 114/192] whitespace cleanup --- tools/binary2txt.cpp | 78 ++++++++++++++++++++++---------------------- 1 file changed, 39 insertions(+), 39 deletions(-) diff --git a/tools/binary2txt.cpp b/tools/binary2txt.cpp index e0778fbf3c..119e9e3574 100644 --- a/tools/binary2txt.cpp +++ b/tools/binary2txt.cpp @@ -99,9 +99,9 @@ int main(int narg, char **arg) // detect end-of-file if (feof(fp)) { - fclose(fp); - fclose(fptxt); - break; + fclose(fp); + fclose(fptxt); + break; } fread(&natoms,sizeof(bigint),1,fp); @@ -114,13 +114,13 @@ int main(int narg, char **arg) fread(&zlo,sizeof(double),1,fp); fread(&zhi,sizeof(double),1,fp); if (triclinic) { - fread(&xy,sizeof(double),1,fp); - fread(&xz,sizeof(double),1,fp); - fread(&yz,sizeof(double),1,fp); + fread(&xy,sizeof(double),1,fp); + fread(&xz,sizeof(double),1,fp); + fread(&yz,sizeof(double),1,fp); } fread(&size_one,sizeof(int),1,fp); fread(&nchunk,sizeof(int),1,fp); - + fprintf(fptxt,"ITEM: TIMESTEP\n"); fprintf(fptxt,BIGINT_FORMAT "\n",ntimestep); fprintf(fptxt,"ITEM: NUMBER OF ATOMS\n"); @@ -128,26 +128,26 @@ int main(int narg, char **arg) m = 0; for (int idim = 0; idim < 3; idim++) { - for (int iside = 0; iside < 2; iside++) { - if (boundary[idim][iside] == 0) boundstr[m++] = 'p'; - else if (boundary[idim][iside] == 1) boundstr[m++] = 'f'; - else if (boundary[idim][iside] == 2) boundstr[m++] = 's'; - else if (boundary[idim][iside] == 3) boundstr[m++] = 'm'; - } - boundstr[m++] = ' '; + for (int iside = 0; iside < 2; iside++) { + if (boundary[idim][iside] == 0) boundstr[m++] = 'p'; + else if (boundary[idim][iside] == 1) boundstr[m++] = 'f'; + else if (boundary[idim][iside] == 2) boundstr[m++] = 's'; + else if (boundary[idim][iside] == 3) boundstr[m++] = 'm'; + } + boundstr[m++] = ' '; } boundstr[8] = '\0'; - + if (!triclinic) { - fprintf(fptxt,"ITEM: BOX BOUNDS %s\n",boundstr); - fprintf(fptxt,"%g %g\n",xlo,xhi); - fprintf(fptxt,"%g %g\n",ylo,yhi); - fprintf(fptxt,"%g %g\n",zlo,zhi); + fprintf(fptxt,"ITEM: BOX BOUNDS %s\n",boundstr); + fprintf(fptxt,"%g %g\n",xlo,xhi); + fprintf(fptxt,"%g %g\n",ylo,yhi); + fprintf(fptxt,"%g %g\n",zlo,zhi); } else { - fprintf(fptxt,"ITEM: BOX BOUNDS %s xy xz yz\n",boundstr); - fprintf(fptxt,"%g %g %g\n",xlo,xhi,xy); - fprintf(fptxt,"%g %g %g\n",ylo,yhi,xz); - fprintf(fptxt,"%g %g %g\n",zlo,zhi,yz); + fprintf(fptxt,"ITEM: BOX BOUNDS %s xy xz yz\n",boundstr); + fprintf(fptxt,"%g %g %g\n",xlo,xhi,xy); + fprintf(fptxt,"%g %g %g\n",ylo,yhi,xz); + fprintf(fptxt,"%g %g %g\n",zlo,zhi,yz); } fprintf(fptxt,"ITEM: ATOMS\n"); @@ -156,25 +156,25 @@ int main(int narg, char **arg) // loop over processor chunks in file for (i = 0; i < nchunk; i++) { - fread(&n,sizeof(int),1,fp); + fread(&n,sizeof(int),1,fp); - // extend buffer to fit chunk size - - if (n > maxbuf) { - if (buf) delete [] buf; - buf = new double[n]; - maxbuf = n; - } + // extend buffer to fit chunk size - // read chunk and write as size_one values per line + if (n > maxbuf) { + if (buf) delete [] buf; + buf = new double[n]; + maxbuf = n; + } - fread(buf,sizeof(double),n,fp); - n /= size_one; - m = 0; - for (j = 0; j < n; j++) { - for (k = 0; k < size_one; k++) fprintf(fptxt,"%g ",buf[m++]); - fprintf(fptxt,"\n"); - } + // read chunk and write as size_one values per line + + fread(buf,sizeof(double),n,fp); + n /= size_one; + m = 0; + for (j = 0; j < n; j++) { + for (k = 0; k < size_one; k++) fprintf(fptxt,"%g ",buf[m++]); + fprintf(fptxt,"\n"); + } } printf(" " BIGINT_FORMAT,ntimestep); From 3b54eb65387306fe889a1e210ad7c353bd6880ad Mon Sep 17 00:00:00 2001 From: charlie sievers Date: Tue, 10 Sep 2019 15:41:09 -0700 Subject: [PATCH 115/192] finalized fix_langevin --- src/fix_langevin.cpp | 65 ++++++++++++++++++++++++++++---------------- src/fix_langevin.h | 1 - 2 files changed, 42 insertions(+), 24 deletions(-) diff --git a/src/fix_langevin.cpp b/src/fix_langevin.cpp index 7734989e35..2ed9d9477f 100644 --- a/src/fix_langevin.cpp +++ b/src/fix_langevin.cpp @@ -12,6 +12,9 @@ /* ---------------------------------------------------------------------- Contributing authors: Carolyn Phillips (U Mich), reservoir energy tally Aidan Thompson (SNL) GJF formulation + Charles Sievers & Niels Gronbech-Jensen (UC Davis) + updated GJF formulation and included + statistically correct 2GJ velocity ------------------------------------------------------------------------- */ #include "fix_langevin.h" @@ -207,7 +210,6 @@ int FixLangevin::setmask() { int mask = 0; if (gjfflag) mask |= INITIAL_INTEGRATE; - if (gjfflag) mask |= INITIAL_INTEGRATE_RESPA; mask |= POST_FORCE; mask |= POST_FORCE_RESPA; mask |= END_OF_STEP; @@ -302,6 +304,9 @@ void FixLangevin::init() if (strstr(update->integrate_style,"respa")) nlevels_respa = ((Respa *) update->integrate)->nlevels; + if (strstr(update->integrate_style,"respa") && gjfflag) + error->all(FLERR,"Fix langevin gjf and respa are not compatible"); + if (gjfflag) gjfa = (1.0-update->dt/2.0/t_period)/(1.0+update->dt/2.0/t_period); if (gjfflag) gjfsib = sqrt(1.0+update->dt/2.0/t_period); } @@ -377,9 +382,9 @@ void FixLangevin::setup(int vflag) v[i][0] += dtfm * f[i][0]; v[i][1] += dtfm * f[i][1]; v[i][2] += dtfm * f[i][2]; - lv[i][0] = f[i][0]; - lv[i][1] = f[i][1]; - lv[i][2] = f[i][2]; + lv[i][0] = v[i][0]; + lv[i][1] = v[i][1]; + lv[i][2] = v[i][2]; } // } else { @@ -399,12 +404,6 @@ void FixLangevin::setup(int vflag) /* ---------------------------------------------------------------------- */ -void FixLangevin::initial_integrate_respa(int vflag, int ilevel, int /* iloop */){ - if (ilevel == respa_level-1) initial_integrate(vflag); -} - -/* ---------------------------------------------------------------------- */ - void FixLangevin::initial_integrate(int /* vflag */) { double **v = atom->v; @@ -715,6 +714,12 @@ void FixLangevin::post_force_templated() f[i][1] += fdrag[1] + fran[1]; f[i][2] += fdrag[2] + fran[2]; + if (Tp_ZERO) { + fsum[0] += fran[0]; + fsum[1] += fran[1]; + fsum[2] += fran[2]; + } + if (Tp_TALLY) { if (Tp_GJF){ fdrag[0] = gamma1*lv[i][0]/gjfsib/gjfsib; @@ -733,11 +738,6 @@ void FixLangevin::post_force_templated() } - if (Tp_ZERO) { - fsum[0] += fran[0]; - fsum[1] += fran[1]; - fsum[2] += fran[2]; - } } } @@ -934,16 +934,21 @@ void FixLangevin::end_of_step() if (tallyflag){ if (gjfflag){ for (int i = 0; i < nlocal; i++) - if (mask[i] & groupbit) + if (mask[i] & groupbit) { + if (tbiasflag) + temperature->remove_bias(i, lv[i]); energy_onestep += flangevin[i][0]*lv[i][0] + flangevin[i][1]*lv[i][1] + flangevin[i][2]*lv[i][2]; + if (tbiasflag) + temperature->restore_bias(i, lv[i]); + } } else for (int i = 0; i < nlocal; i++) if (mask[i] & groupbit) energy_onestep += flangevin[i][0]*v[i][0] + flangevin[i][1]*v[i][1] + flangevin[i][2]*v[i][2]; -} + } if (gjfflag){ double tmp[3]; @@ -1043,11 +1048,25 @@ double FixLangevin::compute_scalar() if (update->ntimestep == update->beginstep) { energy_onestep = 0.0; - for (int i = 0; i < nlocal; i++) - if (mask[i] & groupbit) - energy_onestep += flangevin[i][0]*v[i][0] + flangevin[i][1]*v[i][1] + - flangevin[i][2]*v[i][2]; - energy = 0.5*energy_onestep*update->dt; + if (!gjfflag){ + for (int i = 0; i < nlocal; i++) + if (mask[i] & groupbit) + energy_onestep += flangevin[i][0]*v[i][0] + flangevin[i][1]*v[i][1] + + flangevin[i][2]*v[i][2]; + energy = 0.5*energy_onestep*update->dt; + } + else{ + for (int i = 0; i < nlocal; i++) + if (mask[i] & groupbit){ + if (tbiasflag) + temperature->remove_bias(i, lv[i]); + energy_onestep += flangevin[i][0]*lv[i][0] + flangevin[i][1]*lv[i][1] + + flangevin[i][2]*lv[i][2]; + if (tbiasflag) + temperature->restore_bias(i, lv[i]); + } + energy = -0.5*energy_onestep*update->dt; + } } // convert midstep energy back to previous fullstep energy @@ -1139,4 +1158,4 @@ int FixLangevin::unpack_exchange(int nlocal, double *buf) lv[nlocal][1] = buf[n++]; lv[nlocal][2] = buf[n++]; return n; -} \ No newline at end of file +} diff --git a/src/fix_langevin.h b/src/fix_langevin.h index 5abfa53288..2ef1489273 100644 --- a/src/fix_langevin.h +++ b/src/fix_langevin.h @@ -29,7 +29,6 @@ namespace LAMMPS_NS { int setmask(); void init(); void setup(int); - void initial_integrate_respa(int, int, int); virtual void initial_integrate(int); virtual void post_force(int); void post_force_respa(int, int, int); From e34b7840d580afba067642d3f74b8386cf736354 Mon Sep 17 00:00:00 2001 From: charlie sievers Date: Tue, 10 Sep 2019 15:53:32 -0700 Subject: [PATCH 116/192] Updated documentation and added MD results --- doc/src/fix_langevin.txt | 53 +++++++++++++----- .../argon_kinetic_energy.pdf | Bin 0 -> 57606 bytes .../argon_kinetic_energy_fluctuations.pdf | Bin 0 -> 57374 bytes .../argon_potential_energy.pdf | Bin 0 -> 56655 bytes .../argon_potential_energy_fluctuations.pdf | Bin 0 -> 54630 bytes .../guaiacol_kinetic_energy.pdf | Bin 0 -> 43676 bytes .../guaiacol_kinetic_energy_fluctuations.pdf | Bin 0 -> 43786 bytes .../guaiacol_potential_energy.pdf | Bin 0 -> 43634 bytes ...guaiacol_potential_energy_fluctuations.pdf | Bin 0 -> 43267 bytes 9 files changed, 40 insertions(+), 13 deletions(-) create mode 100644 examples/gjf/molecular_dynamics_results/argon_kinetic_energy.pdf create mode 100644 examples/gjf/molecular_dynamics_results/argon_kinetic_energy_fluctuations.pdf create mode 100644 examples/gjf/molecular_dynamics_results/argon_potential_energy.pdf create mode 100644 examples/gjf/molecular_dynamics_results/argon_potential_energy_fluctuations.pdf create mode 100644 examples/gjf/molecular_dynamics_results/guaiacol_kinetic_energy.pdf create mode 100644 examples/gjf/molecular_dynamics_results/guaiacol_kinetic_energy_fluctuations.pdf create mode 100644 examples/gjf/molecular_dynamics_results/guaiacol_potential_energy.pdf create mode 100644 examples/gjf/molecular_dynamics_results/guaiacol_potential_energy_fluctuations.pdf diff --git a/doc/src/fix_langevin.txt b/doc/src/fix_langevin.txt index 861eed4a6f..1e50b3a8ba 100644 --- a/doc/src/fix_langevin.txt +++ b/doc/src/fix_langevin.txt @@ -217,6 +217,10 @@ the particles. As described below, this energy can then be printed out or added to the potential energy of the system to monitor energy conservation. +NOTE: this accumulated energy does NOT include kinetic energy removed +by the {zero} flag. LAMMPS will print a warning when both options are +active. + The keyword {zero} can be used to eliminate drift due to the thermostat. Because the random forces on different atoms are independent, they do not sum exactly to zero. As a result, this fix @@ -232,21 +236,34 @@ The keyword {gjf} can be used to run the "Gronbech-Jensen/Farago described in the papers cited below, the purpose of this method is to enable longer timesteps to be used (up to the numerical stability limit of the integrator), while still producing the correct Boltzmann -distribution of atom positions. It is implemented within LAMMPS, by -changing how the random force is applied so that it is composed of -the average of two random forces representing half-contributions from -the previous and current time intervals. +distribution of atom positions. -In common with all methods based on Verlet integration, the -discretized velocities generated by this method in conjunction with -velocity-Verlet time integration are not exactly conjugate to the -positions. As a result the temperature (computed from the discretized -velocities) will be systematically lower than the target temperature, -by a small amount which grows with the timestep. Nonetheless, the -distribution of atom positions will still be consistent with the +The current implementation provides the user with the option to output +the velocity in one of two forms: {vfull} or {vhalf}, which replaces +the outdated option {yes}. The {gjf} option {vfull} outputs the on-site +velocity given in "Gronbech-Jensen/Farago"_#Gronbech-Jensen; this velocity +is shown to be systematically lower than the target temperature by a small +amount, which grows quadratically with the timestep. +The {gjf} option {vhalf} outputs the 2GJ half-step velocity given in +"Gronbech Jensen/Gronbech-Jensen"_#2Gronbech-Jensen; this velocity is shown +to not have any linear statistical errors for any stable time step. +An overview of statistically correct Boltzmann and Maxwell-Boltzmann +sampling of true on-site and true half-step velocities is given in +"Gronbech-Jensen_#1Gronbech-Jensen. +Regardless of the choice of output velocity, the sampling of the configurational +distribution of atom positions is the same, and linearly consistent with the target temperature. -As an example of using the {gjf} keyword, for molecules containing C-H +An example of a reason why to use the {gjf} keyword is the freedom to take a larger time step, +up to the stability limit, while maintaining robust statistics. It is crucial to +recall that while the equilibrium statistics is appropriately sampled, the correct dynamics +of the trajectories may not be for large time steps, as is the case for all thermostats. +All thermostats provide good statistics and dynamics for small time steps. +The 2GJ half-step velocity {vhalf} samples the correct velocity distribution for the {gjf} trajectory. +Results of simulations using the {gjf} option with both {vfull} and {vhalf} compared to +other available thermostats are shown in the LAMMPS directory: examples/gjf. + +As an example of why to use the {gjf} keyword, for molecules containing C-H bonds, configurational properties generated with dt = 2.5 fs and tdamp = 100 fs are indistinguishable from dt = 0.5 fs. Because the velocity distribution systematically decreases with increasing timestep, the @@ -255,6 +272,7 @@ velocity distribution, such as the velocity auto-correlation function (VACF). In this example, the velocity distribution at dt = 2.5fs generates an average temperature of 220 K, instead of 300 K. + :line Styles with a {gpu}, {intel}, {kk}, {omp}, or {opt} suffix are @@ -312,7 +330,8 @@ This fix can ramp its target temperature over multiple runs, using the This fix is not invoked during "energy minimization"_minimize.html. -[Restrictions:] none +[Restrictions:] For {gjf} do not choose damp=dt/2. {gjf} is not compatible +with run_style respa. [Related commands:] @@ -337,3 +356,11 @@ types, tally = no, zero = no, gjf = no. [(Gronbech-Jensen)] Gronbech-Jensen and Farago, Mol Phys, 111, 983 (2013); Gronbech-Jensen, Hayre, and Farago, Comp Phys Comm, 185, 524 (2014) + +:link(2Gronbech-Jensen) +[(Gronbech-Jensen)] Gronbech Jensen and Gronbech-Jensen, Mol Phys, 117, 2511 +(2019) + +:link(1Gronbech-Jensen) +[(Gronbech-Jensen)] Gronbech-Jensen, Mol Phys (2019); +https://doi.org/10.1080/00268976.2019.1662506 diff --git a/examples/gjf/molecular_dynamics_results/argon_kinetic_energy.pdf b/examples/gjf/molecular_dynamics_results/argon_kinetic_energy.pdf new file mode 100644 index 0000000000000000000000000000000000000000..6943609f33f30f3ab2fbfd5dc4bcf4a904c9d30b GIT binary patch literal 57606 zcmagFQ+TGq(l#2~m^gW3+r}GC%!zGV6Wg|(iJeSr+cqY)`OmENeb>Ja_P+K(cXd}) zcUAYnQ}uNBO|Bp+PS4E13P(P0czbwOdY3mdFa*a2U;@|~TEg-10T^XWY|Wg_0qlQS zN&rT23u|W+$G_Ctz}ZC9#K_Lr1Rx*)=j7~YVqgR34%(DGT3s~ivi(eZz@~54uTe48?+0bYh`hL3nz*FhR z_W4(%;C1)sR+<_x9I&sv!Q;*LDBrpYEOQ?e|*2wJ)FNXdkYV(DnW2 z+uwqflTR9J1drPn$c&-1F#E{6@3vpDZ`+shj4k6HUo|neSl#uy$ZvWdeNfk|E_n{W zKJB`;i5Npuhi~e536U6|#=WoN*7utQ37b>b_rd0Vfgij&t~bMS>*`KDISDO%x_5ME z$(Lrgu#B8M*XuN(vdjHRMSqrvzPNVeBa}$C`N^F{1jTi`Y~i-SP}w(7zo|!9dcHdJ zQ=n_3Ml)!C5ceYX4=bxZ8;3N2)6_n4R-QF2@1n}qF+f_2M(CPUHC^&48& zS3c%HKI;im`SsuA9lSctT)*7Q7ma`Bu~TFlDNf_H`*Iz4=o`4M@7|-eA6WZUnaw%r zH1}s~P~s9aUbqL%A0#z)t=~*E675G>pMM?lgf?U&F{T0;N)bcR9R&W^Bd|)4sP%<3 ztji%&&9rI7DJ8HackcJG=AV`_V4l>`|{dNbcB#jm`&~ThZ@cE z2&Q@NF^`DJq};3!w-UB|xVCm^M{??NGvY~{Iga082Nk+-9~9&e4fAUUm;FIfHfwSC z-MsfpEwsNW8!Z;dag?*)sx9|Z4%TUU(XXBpX?_>`u93y8`MFfm`)6&VI6=1v#|Lin zjiX`zuF>_(SG3>r8wy4ZOpFdZQcxcTzGfC>FL4hECrA%BgW0y+%7MXpFHI=GKR_e~ zf^&OHC}d-2h81UuTYK3oI!cism5jq~DP!JVTXYoBk_TxN^h#8P5Ni}PH$5QGrGwNL zC2`I41{R6%&l48}bVEL6+W5<5d&Rs1=v)GXz|?67S=|lsp1zoJQcv~D3$^q>a{K@= zrRN9A#&8ljLe$+)2v$mfF{~jJ9fP!Wk7O@ip})t*luyhQBeKmx903-^AP2%KD0;~m zF%Q>HEF!l;0dOM8F%k(2hq4*((;%^hBf|_>+hZ6h87!t+k ziHV-vbZ{O!=*n+=(7a|9end!eNH^D)}Ew98_d!F4xts|0CbzC)mh9?*aXPX zn;By+Uz#E$UmrfyQ|sY){=lj>335T+#R*e;b@U7b0`t z8AfEqMu(HRm?*^3djvK*gmvfKFGf3B8JEU!n6fVm=8Ep7lI^+O{g+F>{%S(bEhaT7@3Kyt@KPv?fq?}9vq}=%;3Ri$Rn(h98 zDB>I#g;tYacmqF#%%VlbuxTCMUJy?~yu~5Jz@QWZjhTH0cO9<1@I+P--2n(6F*_S@ zJf|huNZH&XL8m<(onTd<(Q6i?5rbZjO%^tb!^w+oenKitgFUc1ge`n3lr6kEcg=03FXbvD4V7nA~fz`CFac+h{j%v7FM~ z?k%cdcBfGwE&oLV)2z{Tt|Ov7YVSRRot3NR$8HDvep4NSGT@qGKRWs#i)|Y+@@8SM z?0&$cvov|MJi=*}q9*_GC%Rb~H!(X79lIwX9VR~*)&v^_{$wq9!7LL5KFdpOz7%`6 z1ZTP}o98kR!yIb9Nv(Ewmvyd0hF%Z_x#a98Q`37;ni2Kz@E!uaU^+SFp6aj?UD-p9 zr@;D{M%>gycmAKd)I|+^X(-_fmf?g*+a^su>H1HgQEZp-s{FUe6yvyqU#4M*4_VbF ztD&BR^Uh%}(O?%L4K`HgjR89pz~KBeIX#3$uBZ;tLryTqUL+fDf}W5y!Fv}#C~rso z!vkwcFRJR?hd3?~N;AtpBK>nvl86s0kYBRFzWp1n-<$6Y)`$mTccy z1|p|78Z04e5EIy>dCz%P!4J1OvN6w1%Z|G-bb3zF60R1w4x(7G>l(%rxXDG97I_gU z-y*kI*A88R<_92+yY>3whmS z9-(&W)^Uv{2H;EM0l!%xz&de-bbEfSgKs1G{I-m7>m}au zNgX^D1YPy55|~BebI^^Ny5k&$Sr~t(|Ax%C!QIwe;y4bA65SxlwwRH*KIO{^Vb125 z{JelD3f8}EvpN~2>_TxHNTiiqI)B|je&`sF%Rg5N}11jv*x+1j&+A6pO{sN>ME2s3F zJ0cnY5)2sg7urB0@y#+~O;5)hh5?&_>F5&@N(-tritdR}7w3lD%YW@eb@u?c>jxk~ z=<*R>S6X_h$rzgXeclb37BJrOR^vD~oo+=gu0?LPCKCr*cRHAgTQRCxF}hkYx}61r z!FRf<8DAJ4=$Rxeq&5k4MpP@x-AkWl5^V{MPnBnQ5X*?nGtUW!M>$Bh%dg>Uj* zb-(z0-Pv^!+tz;_wY=5n2c*_KZNJZdGIobUM9KqcpD_Qt)N}412RXS6{(P5`oX(OH z!L*CQeETSk#)SG(KmnP4J?z+>@WDMBmza?w!BC`67>bnYf~Wr~v{*}*y`>CV)z*G7 ziRYz&)QbHkikA8%aVrUAfx)iI%eY^#P54=_O3Pr5(s-p*)gEz}Dg>`F_}<7AN>gg6 z!~Y|V$&*9l7?#qKY`?M-Iv`C}dn-`%Z-Gd<%d7qEDF7Af5L^QgHzP={5sEhEb={b` zw!|6JP>6G$GYlN`%eRpiwvar^TVPWjZ)vLAk{;)raF@l<>amSHWcBsuHlYks-le7p z#*W#erig(OFu|eVkQW5Oq?p)kY6q+}is-3+_eO>(hbtIG`(A$r2lwhT9>VA*Od@CJ zKNj&C+M<6RP*gSyQE@eQjTm{I5~3I9*o_Mz%}W64@w|qt;66@}X+yJtrHs4VWvOBs zz&@uxraBYHhHhy=vr)>!al?XNu8M<%=-?JGc2q*u-)p%c(O8p_w7H`i!kJ%gFT#gd zOnf94COdPymYv6g6n>oxis4euh9S(>;Yuk=8sMECqGXOjl;f;a#YLLqZ0Hiy8sNQ1 zQ|JvA#bWu|!bQ9j35<()?eu9LjdQKM>w30~Khh&RnUfp@G0JkU0B9IQls=IRbQPYj4CEU` z>!vNiIl7+;d4d8=A=>@hC1&bmX;Ioi?F1YC-wwnDw8BU-sR^aW z$isHp-8%X%2Dj{k2pM*4gdq-SC|%%5WQs_+!%lkFsA@bY9l;4O_bMdw0Y8v_l8IUd z5^J06gcxZRf;$Gg1VfLX_QWPN&Z6y$ih?**W-E@paM4(hn!pIaf^`_9HnY;aqX2`l z(kNOLbC?YInWgLDLSYQ9S~5kv(p!FQ6BcndNn7=c72<~{0p5d!WkO6sK_Ocso7x~| z*@WFu1#MwP$j&8khfs)xE-45}Y~t0JD8lFO&6$~=p|i^F#F`Ol%%pgwX2qct?aXm= z5~yHa0)YC~6L%t(aBpWg;dpV-16&YLA!sC!V*QT4*m)0Y1;Qh5^E-3#3^#OiO;-Fd zf-I6HE8^sb(ztiur@o!2*@Yuo8JA3G83H4bd0S9=NH}C-Wa_JG|HWVcX?5}ptvUD zP|}j&?0_lsf17dbm_wBo4%#9MCdnye0(%kc7+Vq6P(jDQ60UDsgRab2Zjp$3RTgRP z+r%7>A8CCkXm$HQ$>%*8Vo*^nU6DQ&lrk(#ubJmY4}y^iRAl0Kb4^LEpq)TSmVM*( z$~@q7Tx?UCA?b~NlxJMMr(1j+`XL5Fe4ZNAs5WX-y;P&*2#-ZJlj3?MF?#*ocfvBz zW|_Pgdhv0H&_)?ax_+*3cH8tg^$-^{cWwx#H10`*oM*P;V@)Wp38C@?%AR$1jj+XA zg=Xo+;VL_;N7iru(OjR$}o2yBJYC5~jX*nF8wc zi$-jc6xMER5>r>>+jd-y`c^y=4!(1eab`Md5rT$wrHHhGFI!KkN{UMNdMhKL5bIhi z^;c&c9CQK(((M+7JEMmvB8K-hV&zFUQ~Xiyy7g>_JwHnN?KlM23%r){7v0j;rkaU` zyX0QWE~n}DOl;Mo*Hu4mad}&^gYi=_usAs~EHKOcji30PWe>yGP)~A_ zHUx*SmwEDr!O#l6`i&3(c;9$`XRM5CfyEUwQ56LwyLOJ$SOVms(8GAQixY zfohfqbBdo&kh$mlD1|7mvL)I#`d7>Xs4Mzc{w3@_axEoHY@Y#atffd1*E@&)A;5hp z>P5Fq5aGZI#<32;sjJ~vM0BAl`#^*Tfg3W$7Uew`kzUSA+caoaH@#7X>)w3}niN>B zrwFIL0~>bnFwKT~wv65h^n`TUawGTbbZA|NUkcYoIl7d}Kk64xtoH_U4baZ*H=}{C7Y=kYqR{t74ko(vjNertK1WV8?E?o6zImH{MK7dtCYUNA`GEcLQEM!Q=o)Ob zA=QzSxAPT=a$4VO?I1$JMI9f(WSc_)%$qBz$%(CpU6V#U_O)h8$v{WXJ8Gjx%;KO| zSmQ^F)9t1^fj?va32ANFyGZnkbQ<1Em&EgQLzw1vn+d*|UaBX!V*L}s=o{oDc(QWk zc&W`RmBGpNguOv&e>v!F#QN;##7GRT7rNVNpd1CuNF4aY^@P8z&<{ST(C^Jg^k<`e zx5I#KNH&$KZ)d~kW9wjpS;*>v?O$)hR@`FXJhKJFiry zVLridCwXY({h!fJ`-{SzgCL2BUjl!cX|9}X@ir)(Y@gXm2QRb6l)LP0Id<8nqUWIv zHp9h&#8Fb(gtQnfw*AQ!y1M5Du_f96z~sRXbJma^=NU1_&WU#Do~1Y#mZsU#HUX} zGq94gT}n}K!o}Dxn#SK1V~GJg=$+_}((yDL2~jz&U}b)6<6IprQFJ611uc_}1=@ae z^Q|rNLXX)R!0`Or7&PDy7z9`<1ghN>vm~Q1z5*VE^dBlll0t?f9r^g+<9j}j*x)~M zXwgT_;{678Dhet{;?F{<&fJXO> z2Lsq;@H(1jFsJ_8kKP&B9E`U*5L2NIzM<0@^JRok>_)XG^*q8AV`g>jNTVGB>2x(Y zA8`|Oj4n{G`dB{Q@V(S7MCSx?$XHnNVAdM0S>zd8duZgNJ?@FTu_x#2;hKH5^Fxy)T%SWG3-AGYe9(g@KnUdDjws zSYZm7v9Dc_lTVlSecb-MoqqCtT5R!sbJLUPTD_qk|s8m6Kkm0aRZgWx-* z4wW)ezD$F{LEg#Y=KD5CADRSsr1Lv5t5=5;v4dJ?0bC@h+6!9sAh{Znl1io)(RVNZs3(IIpNIZl(!GUQ#a5?Ra zaad~^vii)~uBv9&D>)t=>XuK@N=Tt_15Oi^^>H+$ zq5P*CHZXaZ8_nf>avFsfDaW{934%ci z&}IY3D#J-GNWo?tVil-@RAJjP*!yQYey3@>N@`NkrIiT*MQ>p?VQSXgv4;nh2dOlq zMVhL=g-~of@QD3G(;NkU%~!E#>o@dJs?CCds_}}UG!XIy;iCr=uE|KzVbW3kEhqyi zB=6E&#=le1Bs@~f#a5{TRwT#T$-<(SfRM}_HT|=-+E)YfTgBF@m*haYQjgYDuz-?W zWE_=3M=n*`f)~DD=x@f;&Bofeb1G<1bw8$UB0$H4Xy(OL>FC3Nd$ETwhK~xZSyM;t zsdr&`h+G-Y=E+hbAo&wXtR%N0&P4<=0XzJJNF}WAenrV}RDt5t1tZWVS34`u_C_?H zQ}Nes_EX3BSaZ|^vmc9iy8XmVvOh2l1z4lt?MhXmJlvYG8|IQ&hTcou#x*|h2SU~Y-eI9-3#!7Osqk{0u6Liu}e{b>moPY%A*BK`B;Jl3nh>TF%O`zSF?f>3Zn zU%5TRsV=B9`_%VB|1*r>ai(sDYkWZPRKj$sc;s8uEL~%SIXeH5t!;l01gj*D} z_bd8`5tqv6ZS+hf<2DAF80en>FJ!{`<0MjHE>I!5z(pu3WNdK!Ibm47{X@L|{Wutj ztU6LAKXJ4Kz#m%2x(-cHVO^B1z+#8BGN<4u9ukKmcf(%~?Cjth=^l_|5UsbiGVM(e zvv=zBglSA4U?Y`ex)i-xYRPEGLheLn5M)!H*Cr8>RH?Ojl~4LK*bd@@r=j+Z&L9j$ z70$*QalFklD1@%eesxXPAdd5A0@Qr2X8d1$-<)6L0amZG8c>%BK7SL^R240EbLHvb zcpqmdM>VD_qy3t?I*E?R0Jn(!zfIVJHx{5Lh(>+vlzmvB?y19WeicOh5m7d`;0hB# zHj2KiU;r`wi3AP2l~~4f7$N`V5>gc_?ieb1CF3ky!5Fr7lP z*L^E9DW)m?aky49ZdIV#b-MT4N{_Zwk3 zMkr=ofM%BU06Qqhay>l(TWqDhYcw1;Bh2w1mb-~};oAL-%FxtdkHnzjJ(EVa@h{-C zy@x}_JCk2C*Od@6Rr9~S=b5~uX9j~NUYc`2z3HHx2in@xZ20-5_aTrJ*x<)_i>lWs z4JZMz!25LRv;5#IqsRW=}p@lx=^tUnUtO@P8#@2Zh zX!%nLouY|kN`SGxmO0(e(EbBEXI#VP-=ynm5|-ZZ=$aPvG!A7U%JCPLY}V+xe^3~4 zW5hT1#QGI~Q0pSpAu<6eTobBPHEDGvszRF3yb-MitLjrY1wyIq*s@f&+_V2uAroFH zwKdiDj9-zdD=?W5Sp#}+jXaj@m5Dv1Tej2QF4742{w=NFJ#0wUy(kRYlU?6M zmJlOYL-&7~QPAMZ`EcX}L%Y%N5pUU1b!7f7qQ+(=^dTt$JOwqptbjj}pJ2^1RHz=M zA1N(-K=2;f;tk-XnU+ZN%QM)iMoF<}KG|qQLuOAcs)K+jPm3zA%Um-I1?&=NZ#@<3 zjaGsp=MW+#2bbaH^e!0r!7D%Upl)(RaE|oViiKo{BmoISgaEoPP3koZrH#pxyR6SH zY`E_{M@-M`F6vo>)W&`tk$H6^piGTEfNu&%3ifo_-|!VQyNT`xsgt6=+1h0NZgqJk z{l*#Z!JVbGZgF?V>FxxUmf88M5;YUO@HP&P#l7K(-|@TZppNwMNm1WhCBmfsq`$kt zKnndq7T1uOI~Uj|QiDr%C8;OOWNx>0r{>*qoGNtS*tUTh?ID5OR+h`{sqi9B2e+F2 zwP`gC09dP!++NFGv>mFdyQ0U)JJKx)WUbmZpl?XTDx zX1}si<-@##*WGV@-&qg4H$|A3PL8Wi`{x+OKJ8SAN<5aw(~D2B0Q27me_Rmf>{2P| z`zk&RS|G2G1Pbn}q3z3mBIE`rpKSr}%ziVW&i3Y()|iIcs81tKv*r$)&9#TIlaNs2)3R`$Q^XnRq)cGx&f)lNtc3*=X|IptT z{G>yO8|Je2`+oMEoF!=QI$R2op6iuRM%BA}T3P4($-CO{HL-M!hYo)M0L*-d(N4eU zl@(ir=F|q%b!8`7&;}mzvHi#wbC~>l6<}XIG>@O=TF1~hn%Ujj)(@NT!9|H5sD+cS zy&IW81GwXZ@;pU2-A$vjm>{GKkb5s(=%UoGYRKwu&Z#O zf*vBdDRgmO&gjnk<2~Cf) zT~p+Df6);Q=igPg$8TSuONf9$%O{#f55&h^J;oH)yQ7JjygXCgx;YYfkv#lttf9*l zQP2?Z&$on#@YJFj?!jFL%3%dPjNINFz3k&mGZy_BG#@RdVVSjev4pI&0kcG{5NW)E zs|(38AVen_C1Z*rBV2!@^PNU@V0rjTO?UC__*c006<^*GWf?*(2 zIlB9vQGmtjKozmbH~9-}G(%(Xc7Tu_dI;sQvE|vFWzq%ll~+j%HFj zJLkAVsmgy3j<4OML2Lq~CiX%vf1M=8~F+K(FC~)gC{q$XOJS@M|^l;~lYRq&|f2LK)U1e_C#co25 zp9rUs>4^p^@G%OxbKkp5lf%fR9L5#4UW0&i@OmbI`ScQqc?G|e$Mhj#Sx?ZG$HY#b z+8cd{;|~+p?=x=D`YxE+8-LTADIt2L!ua$qQx32$Y>nN02alSexECCj>s+x6A3n=TzuQkk(-B=^ z*5FP2KoR#h^f{c-r6!>U@Q-#I;L+lgqZfA- zawd+fP(m19TA@H7bSh9XE1f#zZ*{O_yr$P;nP4ap zeuR5#ldCE8H7PwhUAf{)_gVC?eYZi;l&Ry33Msa#bN78D5v>EXiTTO&5OFPY2T?rt zlBVw2+$Pwxt{z_TTpw%AWy;qHou;jHEcM5sZkW z6ElIv$2Cav3p_KkGJti8<6DLPT3bH9dhlUB)gjoCLZyf`;>0A)4nG+>qFS%Kin(~c ztvpl^@^Ax;{pRu}GG(c>>G1A|iBY+*;V1p*@^38I~L|BT{J% z7vxcZQZWRz9Owba)!`ZID0Py7KQ0>=q>88CJVeC|j93fFlqn{Y1UVXl8mho!FOA=^ z7WW`cPatw~`^gjyo8mV(i8*7;l>AymwcRUsBst+*{}Eq%xF^(t+gR*WUt7>-1qaqs@Q>wbX@*5 zUn$~AH@;OVGW}!AAa#=F0KPr`W~ox-swDxsh17;ZeGv9RCKiFeE~3;qs0AnJ+PZxd zz~%Y9&vvtSgzF^`l{~gih$>N#ix>G*-*~LAP9{+>ZZ?S2l_e~wQQ&3(08mcFr%hb3 zw+|6O-Jg|KRnA3G1PTU9f%G~srw2_NvcN)uquxad7{v9GWsT#+)_M$uX=UeCPd2m$ zRUIFo<iZj70&{CGWEc$g@8s8Iy+y*4C&_lA zW89fwxmprHpc7|`e!udjL7;ScF#oLyB74btNX6`!U;#?lfl>otH0vfzu)EBXC+N%- z`SQ=WjIR(<5$(O?j%>i(uwrwD_T{PmM=OW8aKSMB5~xM;)^Wk8F2r2sp@glpl|8_h8+>}n{|c4-I6aU8b5YBujd`=}0U zbeY&RI9hgVFPn9!gc8PbNnsoaDAC*q0$f^@GCH6UCWO2U`U0~-sac&sMx0-d9~BDL z(KvW8G4ZVLH+UeJBLWX?5tYy%?hwBNgnD&sGzILm0s&GjZ2cIdaAxB==7p;|VAWfg2yeoy?UxY9iA2@n7fc11o zhU`>vtD0dbzody z{{~@HwCpFnV@?PdXff@P)Awyp9-;33=-KrI8-Fs6*5O4PrE;<``2(Tag3Sr*WJQ+=NadS2>qYT&P45iZ$4l=Oq4~f0_u_+NZ*p1=Ff&l5lBM6;217#q z*LNo>)+o#eZo7!{97Wp>~ z7LLV&$~OxcSrhE3UuFGF^B<@rbr;VgZWGYS#B~q(znCW2q#89Q>%4+IJy9~-skX-JSpyh^Mn3;3!{Ti?K3ILuSN8Kpc0!g z=;Dxb3QglL_^uP16A}*89bL;6(u>sRQ$#xP>xH$p-iqjdN8po2POwP*(G}lMmRnUe zEsMozL!a((X+TN6>wIJ_j|nge+z5!#G9IklI5XfQ`z;(vN8Sc302;qIB6=2*#-5lZ z>A{ce?fhz?@|F3X$$m`VT(fz*1lMmclX;CjV4Q-80##DTWt<{kphMh8+RS+zEjwrP zT)>%zkIK&R6OKd255x)b$~h~^W2riB$0G3n|IRipivY&sw4agay-_C`EbM1Wg(Ap> zor3mxKM=t%-l`cx)=@^;+9OVTPpZ|l1OL2#RlWMH#ZZTbgTgYdjcg2CBVDs8E;%#Sj)pgQDMtX^T`6W2B-=x_?bapN`LJE!gl3^lCf9&cr0VV+r_f7U zG}m~LjB5?3bMM3qfy3J`rSWU*hna$^v&t+(e5Zv=6~k+Re0>BrrbalvPg|)Dk;Xz) zai2Wq^x|FF-fGehM}so0qm@1lA1SfspcT2M0%KYa=OuU-IfjIr15_Ia;x{S3l z>FBpMBlzh}hzn;!Ns}0>!EVmU+&@l=m5(-VbSp)MgEW*wrSehXInt>*#0YTf zb_qlzTBL-u>+~17X_$wCW1^>tZDcz4l-)^Epd2B|V5#Qs^=F)1x|#H{iBs9pd(n zWscx5O$xX`M(MD?n|!F(L$2R>x7T%ep4atK_g5wV^{&K&bvEHshA&wC7ab+oxNd^7 zAoId2<5_lhO6p@ep>^HbFkzq_qc=#ocgpxM0}$OJe)CUY7kJ$}J-daXuh26tV z`s~fuw2k{YGj6^^#mdWutjW=>LFw)G9h0G02u$gQ+{8f#umbJLBaW1j+)*tE_r?u0{M;9$AvSVhwji)-Kz~B2l-Ch`MZf3Gxt+08jPn@m0QGwFlXXq z{M+z6!OM!}cC*(xL)z@Nqq6s8HJ%5E4OlZxtL(OrQ&^((t$gXz!xw$+zIx02$CUgm zi{jv;;wz5X+v4_HuN5o2qh&dC#0j72t|o;C6PGbjbW_%~@9?SwN`2x2h7Y=$zfRL~ zv^9S%#v2+}zD)1Dx4V|HiW9EJb|D@9<53>hN$l5(hJ3i2n?bLx=&dn+hDo^_;z1sDL ze*V$(_*~Zmz2PIO{8k~ui8?Rf*rwH$?UcUtY|lJu`6vYJwM6l$x*6`Aklj$9r@{3dO7&zj+|J|x-y0tqTAhw#==@p5rvq;k}b?Y{h7*P2^Hv< zqtS>Q?3|QAc>xvDHsX)FJSqS(zL(9)p;hQb$FfwPGG7*<$I4pmJU4MYi`3W_Rj&ed zX(;@79u=az#-nyQ4o2{hyIP2zG6v-hnVDE322`o;wbc)j7BCDyB8G?gWgJRe> zlw$yO0?5>@wOSa0TA1Xpu60I&kJNS+I1)B^ik07)QDDgqKwFfMO|0!*tnmz$#ngj% ztsGh`qr{y^v1W`zik$TCmpK*3WT@q8iv>-PSxW%3pEzrWS%$+nkpNLJH86(D$@AQ4 zPI08>cKnQO+yW0t)D|yX{Gd^%IB_#0QNvP-V(@KT!cc{dg1-p8#+as|Fc(7<7|D}l zB}%$1kxvO3Z&;O=4o|M-i^k>x4o$jZw<)D!?bv~oFDkGYV4B;$ldYVo{_JtD}FD)_kRQ+^{9+3|8Bl1p3S!Zov792;reW!&qu3>rpl zn5P5~Z^bYnEAJ?yf|v8_0ngGlue`BfZ$Sk@LX} z>%nTm4)^KHaw)A!YG(!&9>a&)zz~~)*2(w9e<37S1*0gZ@^Xezj*J2VJpsWbSu;#J zAghKiB8?!9b>pgyWxX0<9bV^}j*%+#xLH*|bm@99%5QjDS-0Of6(YA-byc|vbH#$S z1`sJTib(I93NSfQp~`x`bCTVlaOPJhBQq0WB7Lu84ao3o_fUwCtA!Ag&Me5r;7llM zqvTZi8>FInn^lVGOHoatuA&$l(c(&yf2eSgWsC0%h(^cql;D}}j7bVPx4)tY9+kz~ zU3SK!+j&7VG$f?D`p%`|p$B%I%aMsIksF0&9BgZjSalv+qy&)nn00VT+HZVE9XL-B z*0t@Iy-gs1gJn2i-y3wj$Btp}LAb34l{@Wgo`t*@*0DX7oi%=({+&YdeFm{m*uWqc z5suUj`OsJad+VtSlQ79(X)3Q3Wlh$JNua%ZjSc!?WP=(s_zdDRR>BRA3WISpL)a-T zX$*;R+gl)tKdD23GBjbBT7U|(tPJTezCBD?WY=Og`%&2SS8NA+GTN9Nb4t!AsUiB# zzBUjtldgX0HjQ;ESjugqmu%2klB#^8W<^Za?G|cOl(voaG{YFW=YB!h)jZ&6BDBs> z_-)hNnXYn7{_R+UuX_i9ib&A{8EQ1|aDTAdV9;J@v4ZB%a9YAIByw~8Ct_B~ON_$u z_2+zkwS;|b#TxANt!JqYDG}Ot$r#{pug-ZmDRDUIIDd>^t*toPm|eps$O9NpIPbk~SR(9=3f+&;<<7PB>E_(2z&Y5fs`+BwN%XjjhDtFEFx!%z6on>BqK%U+n7^`p zMj~&7?yT!2-`0f+51!42FFLa?ZS2R1*X8X%MUdxB%48XwKeEMMU17-NH~2CgWzHQ9 zp`1V2PuyQTpIBEw*0=5G2u80SB$B5NAn#aRKkBx%=fDp?Arc+4hH0fcoUh-dDDcQ| zOgz~>lYgWzkXh9wwz#C}@psoZz8&Rm`HYOZ{YJ{W8lHcFheCZP>3lf9a7?pun@gyK zTNJ=e`kBjl@&FJ|0AI&4Q7?gp0s9+}tsTIWP4(w6i)LVB9F6RSjKUm^xD0tFnAKOU z2yVo_QH4Ro0 z0KHo1H*q>0IHiQ2%|Af|YvQzhoEeX2_+X~k88p1e-Wh8Sy&ty!LKwS0&bvQ%k-u&) z1Q~UDpM5us3o>ap@$bd2*CzG8a<{+wTfT1Fw_^nae&fEI`qEuMU!_v-jrC`D{0YZ# zNI30uea8BF@r~*_f9$^QCbtwAKsLD%mfpHPNS-A9l#rO-KSc}E`v|SsPNuK1`z>Jc zjSDsD87}B9)oVkF>MM%T?&ER#=}M|H*1&}Pvcu`Q@&4^=B<<@NSTn?m*x^(W7P?%^ z*?KC=hU5GC0Q(GTL#y1|&T5J~>lL;NTMW=FUrFA^~_ z{}h%5l~pMq0-hW24RIe3dfE1En(g|u^K^Ms`pV_b1Cie$W;YW01h#2j$N?OAwR3b# z{R7#&2jz^q5#4j{K?v} zx{;l0bQ6DDNS)-NvUWDUoCn;BoY$GyR7kw2eW{BMTcYL9$_zjLwE?)*Uy^}D$1B+XeI9X!&h)I=|D2nTYv{@YgW=<_%# zc9~TzTvu6ud?uxGZpzs>IyUa(<4jAQ1KHhfDWlE&nMqOw+cV<#_Galn4M8hH5rKyR z*3TkjDMn2P&W>h3c-(`BK99b@%P|?j;7n|d{|A)(xAhOp{13qVk215fadZ6>|Ld^) z5Az?;S;fQN1i+|ZVD_Kd(Ztpn!1`DG7xb)T;$-LIXk_99;P@{CXlLvESMCJ(2bBJ+ zAZuc5VIX4X4$xxy%i!c@0dO$0=)nC2M*okUf8+iaP_5u-XQXW64AA;(OjP`@T@!a_ zfDV8WXlHHbsBCXwWCHl-4$z4i!19@i5VFvly2385G+<);7^5=7xD3Mr0(O08zB z(gP|HN@6620UsD(xD0!XqA=8}C@OZi8D;f1@Uq`+Wqb^4Y_I-lSza}}@?LHOQFsr4 z=yO&F^<&Fd$GAM})kZ@fA9w=8Mgc`q2kqH4HHDCP76n^)@8nNU|0Oxp@Oa7KXWYI{ z*R4R|wDjd0Pr?Z#g93pQTjb#Lp};x>OHyta#9{e@7`soVW(i?t`IZk`P)V{sP-FdA zdPLhknwCm&kdLb|h10>76VW+p*HSF$QdqYaeM;clh;6#(QG5~Oh}>y9wQS~p=} z4}lUs^8DP|2{hM=f%cg5EjPe!tUHAJDSiC%O^vq%OVFQG3X|1D?69P?L|SxW0s$#? z+W6xMj2{tI)ygiuDUpJD6MHw-oe<9X|+=6r9Xf&=bu2Obdk>ZltTjyehuNDVD|a^Uo_0ymo}`u8c5= z^3fwgtg$0`0Ub`^c93;17+M^(a~>RF(9Sf(o4I;Qhj3F(`2Yj}zp@SkwWfIl>COHzZCt zEigI(Pub8DM66J+pS=T7lfk9|hzp+@elAw?;K7LZjBJRweNBhP>{{NGYQo?{YV5(> z#J%`L8>H704Pk%-ia^alzK%s$L(AZib*qF=GR)3;z0_daa{s+y<; z!8S=ea=CbP$zW1UB~q#sklznUi*GvQyyWe~@k883;tp6E0=n{*q*+9IWXN&+3co1H z(dDJ^M1>aRxTKl|+y&f)3zQIxZD!O%(!6ONNS z$>e{{C%Go+(PvTU5&KHL6}~iqDRv8VEBobDtLBJpf_iv^Bt=tm6AVHPQVqfk0=C%t z70KG-{NftF$d?ElR!@-?5aS3<7r0L~fn-74OU6r#_~IP-&(raT{WpXM?KiN-WX4*% zl)HGlIJDwF`VTBh*aZ>s5v>u?*Q|TZ{aHv?`>2GkJL8QUJ2h4OcFjP zM3>5_*v_KQW|Uf&%Fi%bkXryO7A>A<>B}O=i^g3u$20U;-*;X@j;dS2Jer;?ZhMb- zkK%DsaXN6Yaa3@USO?g!Q*Ba*Qg>7LSqDL8n(*}yn!B3&^}37+DQACvn2^;0xpFEh zPmAa#`SMrGcq(ov2I0PHD8hZy5)7WLiHZ+ANMa{Hi(Rzl)7}Xf!SROnA z<^|>q9hSqS{bm!MLoB@!eT1HyUCxZka>BOe@zWpK`N(~jKI^{K1>VKire_*tY2;XO z;NY*K_Zl`gL8}XB0g@uFuq7Wv<{b!GH-?lz$@6R%hT%h{Kfv$ z{Ifg+Cqy~y0bD+W7=$V`A3QVc7f5G_-tN!ct^R}zQ+lM@GZ1u)_$3x1DX=zhQY5KQC(KZ?Qu3?h zHkiC%{f2X`-j&}@$*-7Sc~mSVlO?0(fuIM_v=A8}yqZRbg_ok8p_es}QMhH;eD+KQ zEmvSNR)*41!=yDi>P_ZWB7!uHEI51R>_ ztFvi`%UkeEH`|#dQbo{QrS@{OoU2ZE%jRvzakMp&wZ!7Zh}cM^G48re_}YwOwqkXM zzFFP*-hfcEkm6=L-Ix}VRln6&tJ77Jx(bWsq;I;Dw+16y;al=#D{;r`8s2J;tAFkS zPumOb3Z7jzTwq*RRu5aQ)l&>KbQdQoH*_j?|6Ju>HMXjqbf^Nf?Ddh&qm80L%*D0s zQdJh>vqeYwM}9cbseA25o{gs&OM}bvo$J=V)1M>3`=R*=(DB-Qf8Q%uRtQ@616DT6 zd&iG+k6JoSef4}rP9-j5$Hjxh3kG|loo9Jw<~fQvezEsN#tqbL+Yj2lZrlocqLm#g zu;evAKyVUsU2Y9N5T0iud|z}A_bxr8c+I+Nn9vN@%$Zx63v0+{H}{nBTtECdoq<1w zPsgA3?sXG!my%jHY$`n-JN7j_jVsI5=SpZG=n@!)8N#jR#Mc7anaZfFu3Q`OORCbn zY<4JFZhwAJNh&j~~vx@!pMk&%gx-LOq?)cX+<*uJ9guuf0w}mmur%|MB2_HG4HY+0Lbalc&xs<*#_1 zeV8{XX}>wip4T6*3pI@nZW3mAPk5}7?}Z#M8K)5gi5-boh>u4+Myz_&-1J|JL?lgb z2X#`tHQXmmmSy?4KDV114E0@DP9CT5ORW`ma6Qf4S??Pi>`c3wpBEN|ua$N1-}$}f zJR9B&#vY!?KgcI!Me@6P!MbkrO#f*N^9l41A8x z^jC19+L^Ff1R?7?AqcUAGljHyi?_<=fW!H$zuY+P6tp+&u>8J9mkGg6r%1Ddb7Y3$ zMat~kgqcfw;Zzxo;D#HrYm~trOw|5ai2CVj?Dwx}uryO#j}?s5L|Srra4S9r9hDZY z0S3HS=93^L{mDz`D(;R$R6$jzdCfa-T^E^GXD?b*KQt!$hcF}mekzLq$?2cDi;g9G zLDI0K&*MG~;o6podDsQ?G%<2`D^+69W&AYeV0C}DZ4v58Cy%*nArZ4 z#!JcA)cga8-H9j#KgidZiiknp!N}O*uS-z=$0a_D%FcFnR>szU;g|8lGl>|~h?xJ2 z97WVVAd-<0?jOYb>p2eQc22eqM9lxe$^Xpap9X(tq4j~9e{qwEh?Rwl=>LzLe;WMn zv;1#e{&NU9fb|Cs{x9zLk$24WFLwV^L+Bsmrek8~AfjXD;`$gK7b_7bGslPjN`8cm zxuKwqsg?1^L>L7B`neMk2jfTh{p<8j|2AO|2G~g$o12R$Uh0_HT)ak@chacRxPd`(r-x+Q1eXmRMrFT# zT}f{7z|-@tp{P(Q94zYn4^5hI3=w`i3gV0+l&nUTuZ#2&9qoZ2k|?)H)%qD#*PF`2 zKr4I^H<-clVT-sY$U~JVU0TVN^Z)A3&{ELhngO-j8Tlecv;riEM z7onMG`|Pf;0v4#)O2^i=ckJWu?rAGxb8+nS;YP7G4w#R>Is_Ufo`(>Y#KuTYG_Jr7 z`?*5?5Mk6Nos$Rb=+qMKXRK&RD9Q+h@z2X*#31x7$#I^M+i<-Q=CAevfm@k5(Xpr6 zysMH|5=6}!2jqG&cvoNa1bc?!S9FYOs)I>VEoyN~oIp6}ANK`tj#b2aQT-u?E#(<1 z%Lks2eSOh5qnE|Q&K{AZdPL)rHHqcY=F^bBYG%K}aZl=yc^4R;a602W%n7)$wot9f zQy2Xmxsk7R%ZxovM`EUA^gZkw*f|0R$@dtU&#x!6Q0KNK1mN!_H{X?la=oqn-+TMY zkNnHxvp!4p486w~;VEyN1(r!B$awq~i<4VZ*^NETzTm4Dh4oDF^$Xsvl$@2;Sdq&_ z(YwO*i06)jfaP#>Et&sTML&DGLfDj$ALcd0R-&6r7;{_N-qo9AqsC_cI1@Gm7FXFq zNbDm(4s(}L94l}YM4j;xKDOahoaRlkfTx(T3)1#)iSa7smWTd$+(hyS^WbN=oos&E zn9{l&lzGz=8&1icQc~`U7g5t5fw(t`;C&k0KyH^4frjLn_%;mLh$5^nm>mbAXfB7h z0B1sqj9tCt>~P!^j!S24b>XkYgD19fI{JE*s&AS?)D^q^c1li$QZr4hs3DN-_P+zo z8gk!fiZN$Zb{Oa=qTUs@FZWSJ+F&LDGM8S64=>_rUE<=5m!i`=fx&3kSy7Tllc+Ki zbtW|~aaSKD`$rh^v%o$hl&!>@=u^}(^?YM(3a68&7os_ z|&}k95`9vVop znhh_Sn*C;=#Lg1{IHK{~RZs2K*1OU^!^fv|v5KBnOHoz*COq^>HST>FTy+u7(p}M5 zaI%WGoP9^JEU=9lBOxj2bIj4Y8zpHaWoao@skdwyr&RZSY3|Z|JKP3sUEe;DAf zwyk9d3G+OYENVDIX*t)~Shd|+mVyS2^e}J@Rl2l1$Qb6O!c;|3Qlnl-L`CDWRToly zgW6d|2jc#`txFc57*uZ&w&f!az66(qIrF01%S>6F_%5j21S;&&RQ8x^_cDjQ7BoLc zUe}_5e_tNm?F1b~%bCGnk7yWjv27Wg?#hpu_*d^X@Ox6L{PYZpLl*m18$4Y^rPoqg zT$_IYO6!4_ej(;`wFgv`^KH8)z;g0mwGD%(``VZ3>VEe3yBREp{i;%nXJKVp#T{-j zuH(Ej{}OG==P?kMi(}d+FUAA3c;{Y9(Yr2z1|l?RWcp4=aZ(S%jq4!}S3Sz)L42LP zE1Mu60n#_otWYBOMj@#OtO4jc5BR*)44(~lI*RXn#m}xSJ7%c0DXA>2^dcR;<xP z?9OXnIWTR7Ki{&Q+X--gV4rzBc%R;)MI#d6f`$l+`l44YR*~GBEN7OC?wwA38ih*{ z#tlQ~!`rr3Zl&b*SuL2P+h?t-sK=}suI+&+b;+ZZHlA!2jWE$l_f>3!o8ODv6SGR( zG2T8dagR5BA8Ym=_9Z6R%LGuG>4@D&+^5-iE|$<^AeS{VbAOjoJj;L+wL1)5*2TBC zy-h!Rt9R+VPg^pwuHAQXxuwMSW^8ncc8Q+H&z#0CB`C1*jCCOO9pzHNgP*s#rBuPK zB%qY$0(t(h7wUMPKWV}#W#<&e9t?DM8*Ro7Z?=d|3T{IM+>m?qj-u-0l${dK{lDhL#Tj)nv9~ zy!XRQ`<1EnIlWn@a4jnBiEro-gqrYa6A0nsHc=YM$9W5C=GEZY%;ojD6(y-b%Y9{&`#abAZR#n~Y{#ucwPzdD{vv*G=j z7vq424gyh_-8${#ykW2;RDX677v0~iPV1tYy&NqNG>AyH$jpsz;Za7Cr$1S*Q%0IE z_>L#wACn}^+L5*vk=}8yl}_ z=yfkijs_GmgEAB8<}>-s`bN8+J#io{kk>5}K%DV30Hly1hQ^B2t|KmFyQm)fE-JO! zK5NB}<$#bTkTJ1YG;u&84HpSEf|byVjEV-!9J6HV9$P(Z0EI|XS>NlEAa-`}RKu4c zE=_#P9S}w-!Go|*fL$1y|0O~GLVS4uJv_VS%~3dpfb(d@6@oozp>&|$U#$CGZaRV> zo^~B;C4GJ2NvMS0JdMivKA?nHnMDbLkU`nfF+>mnCl6^8t}Jfa(-v0bHhX)k-H|fGz&`o&!5BHBPiBWru6#^Rw?Np? zfn({MD(^%HH*|fW#}?P#{P@uT!W|RNxVf(>CEV=bO)}}we8}%YBz!Y;f*58ahpv$D zF8fF)J0Qp%)9j|~+=O+&a~BLPED4pWm+SN`p2l2sCe4w1IA69X{KXWY-OzCe zf$Qmb=}y3N6&zf0Si$AcFl3~(hxF|$V}!nnD8UJ{XdnN+G|U+F>-(Dp zIzGC(4o3swMaH7LQEm7MD-|odMD256Pj9xO%Y91m#=~99M#XYy*V6WCulK;z$zVOc zRuP&kBmgqw(AJYL`p)djN9r|VrrfcYj?RfCdvwESCbO+jWhinp7kAP5svr z4{=+8KK+3EAOU$gl8Q?k!u$#s1L zJeKEE?nxghfL8Izxw<(MDXgtL9@dN$5!yuKy?Aq(J|@y{%tzxGY38y|+=Wsrq z=ysfp`!&pr5QxU=5J2-=}fv?{|S3S`WJbRK94*@E2>?GEY70;VAgQfd`hW(qE z8A9Ua14KX0=I)<9A~G)Xd~ytAs5kH7NC!o;zIeH$==)DOQDr%KXIPOUE2-x;Ujnlt zrpYO7_DoHaeD$l@{ITP2-0x8{W<^P^9j35|7on1Y3K})&zVXKxi9oS|nRN~+7lUUD zj#kP)h!=cDkI$2xu9W?J(a3k12)}~k#yo)IslHQr$A#w-4B)-IYNxX$aJL$y{m*#Xheb106nohZ)U=1dp zbV?PzKK#<+zb0okQn_?w&`JYg7En z;L3Uv{K}{OjoCH|UvU1+q=&Retp|-4ZN6BJ>&2HhkIBU$?lu<6-f2jB#ISc$chsaELw;ID(e=ZF-epP}Leu>;yKVydOxG~FZ@ z7}~zQh#g=c!Gr{I1T_Y^2Cl;u1@dh&^icHZ1^H~kZ~6vF_k0CN^q0&~b0kn8@l$KR z3s@{bU-#ZK{@75NiL~HEZ666JS=wnV_w4IMPGeRTo|k zgus(sB#JliSd4~8vze^}@1stI088c@m5}qfQ=+O*8613`_^0@1=$;=x6k5w-X^K>- za!#aBgF%5{0Z4O;_(lly`!(WauD&p8Y%k%R_mmgD01-B^r+{o4u?fl1+*+L1M&(1i z=}toIP@3V&VvBPhUN=~NB8WTh9p2xnbMG$K!fxH%XVeV2ieL;W&=48MWvUMxm*2Dl z){!^K+|U_xb0;Bm|I}<0yz2EzZ**~RV5EbDezpW3pbjGM1aUtFKhk0KkEjm-gOd$Y zeNh+|wjMmmk(LF+b6iZC@%n@d*BAH{bDQ1lA*r3Nc-y5W8g)#nTn=oXZqdj9$0<5iiW)W*b6#X)eVTVCEMmVoXuXeV~r_jbp; zU~&kbJv;4c&wK9NT)ZoYf*9ex5VG#@nV!lw=2qs#$Qu@HS%KRHbi#R2yWvJEIf{{Q z&fA#A%#L%^YA%BjjlF3%JnRdnz5XPYhLI}}9#6oU^d6uKD+4}(q6Jz)jKb{Vb4kI* z%~H1mkG6PN@w@sAb}KGUD-XqyEO&d7?tI>?mX?WS51m8baL!$NN}%IqZjuI4p!x#j z2vk4O3Fx!yH@8Cv4<^iH7RofQ$|Hcr0@N8|!VrGySv|>RGADN;jwc8iq&EoEx1OX3 zjE7KV@I7T5#7e()5Srg)OS$|OfZ5nvpBU}Vls)H<5FPi)+mF5{*-i883}Jo*^|S70 zKEzXx=Nvm{GfJkhoh4;>akt4Yu;$urSf@?XoC0hGP{qoJT|lczs0G>!3bQJIVu>F7 zv`u|1hWgjKZg@Bxf=HQ*e4}rsRI1NL3#VVw|5STukSs)7pa~fdjNs~JU~TRO0Ks*q zXJw&ZxQ(_pjX5;O8&D`1GzWl8JqMk#XKQz%{9!Oy$NR!dx6BSq!4^+9JH@L*@Vrjd z0=)AB;=`t(xw}kQMVt!B~& z4|8FkfuNr7M;-fsJYREv>x23Dwq-}EXG{BY|5GIiPsfv0+tSo>3sPHh99>S}`Ehi3 z3oB6=cR6NPun4ZG19XCIUnSi3ZsnXmkJDg4g=S41igR%TNLd4p9C6h8NtO?)bv4kY z=L>Wm8K~hg7;3OcQ&YsyDOZ?v@Zpdamyw(hspZk3sL`jqQ)iRxz)-rt*kIqnH^g4M zZ%3e&mkh3rliL%lYh;HhB57XwiFN>14EQb}DqPnCTsognf1e(&udoGz(rp?u->hfC z;%%d`N79r)$Sk^`L>sNF6}|VTUBP&wSk)A8hQ6a|EiaGlPcw$t4DhpwTsb)WWvcUR z@%q9{INpEIh0Pt)`0@7&d>DsOwa-y_ro4Kanvh7`Bqf|+;25k=!F(Atzw{DL%Idd8 zOfJdZYZl_7Mc-+Js)`%jVmyNt=yH1!kc=9VKU)FX&*k{h$1QEjKW*nkhfjd=U)_h*-|&SNt%lSeHs9Qpl+wiF1}IS_PC|A zSg-Ovw@f zDqkJMtwF6NHbdkFWE$BH;}RC}U9Tm+*7o8NZrd-uW_W7^Eu0O=*8mfu>?z0wMG^%U4ik8J&X-eWU!s?gqGm@vF7YEnV2yMG zRp#m<88l7XA8rr2r6-=O`8Eybpw;zcPLDz} zL)l%b?oj9SltPm#Z1YH@rj^H@fD%o(q4|Y;?a=ZZUkV}>2fK=%!k$drr?J*{y3xXb zhOhnQBUL#blfu9$uw*MV%8h&QN$JOU2)?BHIjtSkNf=Cpf}8%ZEy~#K()?y zDbxFuFb!Zdp+^U483kOwMSkpf0@P06{hP&7V8fKMZu_ zjTi=sm=;V?*ks>wBp?Wh^0oGH27jc7HpkhuO@uecMGk4k7vMAdawNH#SIk>OJ8cx4 z=YFJp&M(n&{6#et$digUn2Q&cnR&(%;HbvKj&z1KGa9MMOKi8jq5sQdf(iXArx}&q z0xYkcMd7@*mV&3PYxaK97R2!Y7tYk`DnZMg4B;I*c>TelRb_r(PazE6!E>r$H&q;U zTk_t(ozuEOtFUAB9O>K~@;F1(XISQl_$0FoOP@_nd$3cIR2n!28c|2Y?cF2Ih-s!1 zu|EgTsN9+E%2o12-IN#SttGS2oXq^ZQt47e@ydr%dZ+Qg`RgL0$9kDZ=dK{{z$L5iZ-pS zFJg5`|7uT>_~uq(`yt9EPkK4lr-M0>^I|DtiupjMdyL+Bk&3M+OG(D1*6ZfM?)G%1 z9V}}SU5pIGagv+;@#>5M5f{u~&e!c&{)`~grV0r`GPvpQ-TERk@W+H~9{fPjX)}8d zYO|a0YV%uxF!y0^&Jc-rixXm&WUtxy8fBmat1|2<$zo2SbxDo1%;X#U68D1Xo`FYB z@%wxzYly<_)dZ&1zrzWvJtcT@ku`O!s2POdxf|(3;xcqUVS4D}@sl9ud=mLU@9=#} zdibq~fg>}m54#zLK3KYE%njq7<;8bX#}BryqZ3ZOdoy*4}rQ z-a)u6+;xzzC~E#4K1$yQ=dRE68r2Igt7re>(F?LO&bHr@t@UC5QSY+qvi)WG#q%ZW z(ecIf1@k34`%7Cji46)ltYaV+ATx$aJ*c3E8W346>Gs17j%U+llWz0A$9&T_5WeSY zLh+TdWT}=)W673ESShPY)R9esELqvo59BfewNqu@qNn;&wOgK9=+e$&K2`71Cv9g% zXGv#K*&3Zv)#p;%AJD}CGu=mNvn(@>#ipgcxgE0j6;WywCHvdIzfph3Xc<6Bm=1fL zIR}Kowbo?zA@Z~?%=QoCLMn6kuWIi8AnrrNsV9MU1dOW%?bBN|Vm%M{q45l62A&dn z0tgp?rD4!ZzbMvru7#pboI;|Zw?Z!_bMfd@uDNr`HFu8Xs?Q_Z7Al*0_PmfEJSm&E zr53}$`Dpu;C3E_bSY6t=@?ZZ^+ES7cxCG60yp9tLI<2Ggp`=724n_Vmrfi-se*?DVyI(8up%a()zZ(DxzH5Vd&#R+y8^6pB0 z`1p9=?e^@63Q~(_P^`J=CX0VD?uIiK9?I~FxlAxsaM6Pi6VAF^^c0RhZ02mQ8y(kw z--#pAp%L477Y?p@!wGN7$_Z(XAR3-(JfRgJ@KeZD? zH^DSv4qeD`Sfh@-7$$=v-3A@uqPHeLK-HwB-z{X%twzM*w$|~>5@GnQxH*c< zq$_)?>q5A9I#lyb)p)GE^>zKMON#0|Hj ziEqremT6J$T>@i= z74bdGrmOsfQs4w%GAh{O985|zw>~;QAJfpRa{rX6L#}A@OTp+cx35)RJW9eqsaGz` zX52&vWfGvV>)Mr9@7Fr@S;}MZYueORWJv@ZY)R9=9veR*P7WzA`CbuI_D*6ny3{}$ zJ4!>8=K;~=xz$-5;r!w4xB2uPo2EwlDRkvO%Ev3OFMnDIzB^LUs?8sf&;C z1dFJ?FC3nKqU9U{S`s`43Nyu{B|ET!t78yvrBB1RelpXos5TLEtvBu3ZCqvoF*~0G zLaUHQ5Wa+Vm&YT{aJ(j1rzn_)M?MMV>Kki7qPI=_vDPiXxt-8U;oRT@P$I(?6yjPP*P}0t?Yc$NX`;3v zHd4-ic6EqZy^CXXf|4<| zQ=BtV#qe`O{&G3_^|z4`&d*DgN?UorFD0)7RZ*R5-AhA1q)wt6`3czqmtdtP6N}p7 z`IU3>RnUd=sjhn@CK$QObt4R+(CKpJGuR_pEG!NM$)mSqa?QeW?8ee(d<}* zxk$kCNYra&&9B4+36QMm9%{rv^OCiiFk@6~r=;?Z6Wz(D`cmiDeLIk%95Rx2>s?fm z7;>JR)r)Lc-o(RRT(Nk#Dk#&txo$$k0}DqMS;8Oj1<1m4?&H7i9IPnx%1&_Ln6`lK zR5Fci(M&(p$VKO2%VYj4TauiqCE>GFjK?W$Wgq=~>bb!El0@KB!+->7aeb${ZBv?>R$^nKGmt@g+u39iu2=@&qEnBveS_SV|H&eBl?$27Yo=2DRvx zWxH-9Z+ufCOBaiNbn1Xp^5@^z4_H0NJBZ%{xhu=7-*U~!baJSFk9Pc!2R}68{z_9J zABMB|o`;z;IY)#=$GHo_jvA-U|A~ zm!~&1GSiKE(98H5LFoD5;8A|y-xRj;;)X7ABhH1Y=Gi<1vIC}Clk7T=Num|F#kv)x#J zK=MJGGmE}zeKdVkdzgRZctle#$Ov4U;_AqH5ATdfz#%x)uit}0B)9EW!y%IWIiRRVYVA+-YRy-uGZm>dT1dHHBQ>>EhOb$6-#8+B5JP71RAa}4HR{bNRT;{) zca6MioeP2NrMqnEjhyqo6C7Y_Cs-PewLFPQXy8rR34vd~Tqr(#ys9cO^D;8YH@!x2 z?6+Tid9Hilca1z0$nx#baJ8NU8ll)k-Uj?Rv7XXlroab+7n0x6h+dAJ>jzGQ>tQC} zYH4n?$k78OXlMF{{)D$x%i>LUY*YA!10P?&dubd)CcnZ@H<%ce9+K3C>rW_>GoL2` z^mOWf9)5=9%a^C(pyv3a$8WxxIONgH^X!c;kkV1{SSNoPxJ2=Gcu=sd=iOwmHNfwE zx5yiHof?@CMIHtdNuCmeG7o-QS;Ky*kk{8m%9;SGj8B06_^*i9K2T&KxQP5sX*_C` z8x1(q&lauWIY|HO7&rGQm*@m(9-B=>o%g`sqN^WRUR5S&%O&z z(Pl&hSw{aR#ahW{qm3`$CxoIt-oUeJ(Vg!NJyzo^X`qc80GaT+WCbzhu!9`KoT71T z{6*lXf$@DfhJE1N5*%2BCrNQQno@)@%Bnd$O&%HfO6jI3p*g_UIYSW`<4E3%Lm1Yk z20DFh?fEmrLZ9H(PSrH_kdFmmh4fNi!xNEd33&pO;g;mfAu%+tz4Z3D`qiuG3bAIt zZfdi3&L7LC>T*3h#1p_F>&Z0TMrSol_KQc7!B*#HZDe4TwB1^M!RyeiDBY#2(c~Ck zQm1^S{B<B4T{^{nxhGD&Iatp9Sm0{%4Ov&( zRtLY~5kaxj#e7QSA`N{?^}1T`h`w9g64Ohe5}-GWHYEQ{R={6R*L3ka6*LsW(=;k+ z<%FflNjZWTjGqJp+qPwDn|5`x<8snKV6}li1&+L)y5G9(DqlJzSLM1l`r`rLOKDS0 zMwZXQiZqR9tA{-;$~CSbMrUttgH$+eGd88U6_L+JXB18Gj4lm$Pk!$C4OTj)gp%V{ zGBT>%_W7v6F+wlJF8X^hHh0c8KZEyCa8pBtPhl{Ma$Z(Ru?@w(@Rje_gAT{7C|aQR z`*Zs3a_Z|?I*Im;$6#vSaU%|0mG1?`V1XeGzwTqVqxhJwsyE*jdf(*3=c~0}*3f$@ zyYuDi&-Mo-b?{4Bq^ODzPq*bh-h}74tQ!92DY2!t@}BGli{geZl(#&;Y#D1D3>7*B z{kv(Qc~SQG$?{JxhsNHH_l|(;QKM@L2E7N$s8_{SzD z#@`L@-MH6CEX5k`2g}J6DU;yc_b-QFf)rbao$uiLEq4sWn`Lo$3VBuOwVC}B-52eg zc}H4o+L&umZrJXohS-7=>UX1Xxvmd0qv_@YU#5|YNOz@Qas*joWyqC(JDItLZ00GV z#uVie$&(56dJ<~{W*lV+4YvM7H)w20rw#aCA3n29y!&dz0%{}d&%9NhAoGZA14}uI z`KFlh&GaHH|9a;eHWAXWA@W#ARKSm~5Y5zqV?T}9Le`>mP9RccFa=tMbNKTxG(|9l zJ2VB)b8bP{I2)%lPXyJkC~WS^t2)A@GO=-jW3{%Si-z8L*sX}+-YY? zgzT&6MBg+<+_)QlLG5Gn_y<9t-^gYWRJSJ10Y7hGPP&4UTMdp)1NU~X%5 zr|y1ghND-7qRA*QYPm)5od0a?`CIlo2m)n{1<|$--R<)MXB7-M#sldVU3)ISRJ8EwDZ1%O@%4M;DjhSXB(MQ^Vs^oZKT8aOz2 z;QN>^2m?fqoYkEq#r*2w>qFY={D!UjDoLO zn!R;k&@Qwi`TGVs32gDt<>TrJbLW|}p4`KCQjA-05krbKk{#%X7&b3MX#3v#b%V5y zLkb#Qr>^I7suBc>GS}Y`zDb*la1Q7gcuSDg8^(fhT9fo*fE;|eYwr_O$tOaQInB`M zRkH7f_$63N9B~KeT1GtzJgGA_ED@-tn0;%t-7_z1Z$f3*{BzzbCtc^sxZa- z#(9(U;>FEfeA40mL94)}B5@e8c2Qd@KWm~zsZDFN2Z*A3wx~TW$h@Wj^(D|olZg{9Q_zI{c5?8`=`NEcxtN6VinfCL#K~gh#Qz_jk1sW3^WApN>Ww z5?W3s9vM;s(j@g0_6uk;tmyTmJojkogJ;dH zcfmbx+fsj$b47fNn=_1n_0YH;eH3owGQ{E8?KeIghKIo<#Gl<01Ry%w;Uss>fggLc z@sm?`kSH>{PV1q@OxzlE01G61M{`5IcwWWWX~#>=yXZN2{TfE4t5+#LT-ymJuSVH? zq7wo0XLvth3dYYs$|=|8D#8nR~IvJofiSxP;d^0R2Gp^NF(|R$scIB|3 z(z_-D^1{LAoauwDb9wsQm(0FJKYW7URv({m8Lvl$zOFd6$m3S{{=0g@AC~Qje=V+Q zqluB|OMG8-jI6hQ+~y`1>vs}H+NQU>rO^1JF4rjRNHGAyQf}0Od6AjOVQn!9Ik3tX z=zC2`OPWYxi5WLjer$&H)!&;ZLXH*;f7QRl57!2h(7``UH?IB2eVP;v?id1N0PIbn zlUt#x=;J0X42(QuJaffojuLE)dM4=9X>YS>BJncsJmZ*kjO*-;YY!9hb1 z|ek;4R8VU zxVnn81x>1*HxbS7JQbJ_>Nrxu-c25UrF{XzzcbP3&Q%OXAn1h+i!vr9`q^kmuTWh* za~D&mS>IT!CTuF$AaG1ROdz1in)EZMQF!?yEr<*RhTv$q&I#udi5AGHu$X*~xax}m zVfR+Py+@yJgw!a3GkpCSs&d3>Y?4hsmps(TFP7 z2~{dfgNLt(io^_(qrG5Mv;lnrnteX?N2Z*M?&+xuLx(@QJVmvFX-p0^V-+IIB(%YN z`YHHjCfk;904$4cDz4eBP#=E_+AqklO~H}kb~(q>V-8i0>%{Ts?VV1*xYSj}^8VswV6(9h^7~9@rYDd4d@8m6nv3ov5WO=#!wI}WF!*`5oOwd!>KLS2m&sTI)4Y~UKsPFULP*U9&n;@= z7i%F#OUyf41Autzg}EahxtLYCw9@!Go-k5Zw~XU2!=C^_+zW3=+mJl|rAcTdlyBSM zcQ{j?Xf-u_1~}b92B%=l4+{3-*vPa3jZ0Gy{dnD&*9?VD4;NFadUN!oUAg)>h)xJi z)e1&-%9cO)zrx|TT-`~)T1%cYjL6Z_dW#k4{C@Zu&SbzWuBCk)s=F>Nv%2I`5(6N% zJpIK;dr^s^i7H>&4R+d-1eh$coh(zXG{;1MKh_*Q1|M^o1eg2S?|hmYt6b+ULXP5Y z2Pxdn%y7SEq&+Yo_ozubk$eH$Ciafu&C&}-=Pwm0sJ7fc#_Q816f>dYL~JDoi2>D& zYB5#|53g9bM6fuvEUbuCZAKKsU|M#I0aV0hFfy3IB_U^~O}`4#T_;Iv;jN#N*-y9F zN2kStb5q=>#_(t#RVtIcFjQaYz=zLLH9i3yY0C2YK3i13HG#JaVlyDvn_+qoi}hDG zaqAvD5bz{;QY=L2%gOebZH8DRPQ+@o3MhRCStfh-;VNG;V#IxC)>TKs68Td??k}j? zy(K38ZbmCXT|LoBeBWF>5zHQ?4^Z4gy;0RiU6ny%YDT*bU0bkDYGu=;>I#B) z_p0r8`UN|7QfQ3-R7Z?(lh7(A{dcVWH zx(STUVdA^R0iS=77I|$78xpnT`CqdBFvm1pSXewcBGK%S7iwih;v_GQ%?)!asla7u zyhe3Eq%cL zP*XF#BZs5GY($QWXw`OMZ!r010RF@k3|Nl@Jk>q@#JmxPxqjRA5f_KXf!2!b3#T^|(ZJq?oTz^ObOR?H+UguZZ zuA|#8a*iBsED3s&6!lka!yQZQ_pZ%Seh|t0SWKo%_JR*gBCTFM%VROvsY`8zBd7A5 zgE&I(mR7{cO&U-q@mNSF&@r!#*wtq`qOY#TWwWq%{qgrJ9EJpUI4fh}hw zGd}kv7CS0jU74tJ8YAsKM~C?a0&Ot^108fEL!T!!AG}q{%2i92<}X~D zU~HDoD^D#bjtKCyS>6%DhgEjoYPjO5+GvMD!3S#&A0W^-=DWQ41sW#Mu%0u8cVd9wL==&4^5k_pc?rrF~Ty+a&LORz@6tNdSfvL8q#QE z?p^Mtaw9foHm1YuGv`^>N_3q^ek_bXrIS$81A`Q)UxG;?8d|H593^!PH!joEoz@9wK{BZ|SfiQ=Jzdd%8 zGkg)K@NIoaZZNXHqxxEze4WV1JA^0bI6(o`nxDI3z;4q@Vb4n=3B$ucWfzbDuu~FT z^eA?nKz;tr%ib_6_Q;tJjljsgL^>7CH2W3X)Kw#;Y!aa%gYKd{V@J^)P#A`yzN9^g zr;l1!*I0wr#@+$FB~13vy&*dpP|h$byOknWij#qG@ChHE#FF|z?9%JUariZ0m>qDl zS()(wLDKUfPCf1I91dmkO%w`rF;HSh3{vNZnFQrvi_BxF(qlj@qJ{v7HpH#gsQo6n zljMFJ^hN(lczJe+Z&9OgojG92A>a=uKJ6m_^V$mx>iX&8 zC2R@D-q9%+Mr0`|K|zO_wRwFHKy&iiwy~QDLXwT*VgXD-Fj$uowBs#U(j!Hh-OHs z-ZgB2T8k7DecT|2*_N&_7pb#<#mf^Y5oW*O+qh{rb&ZQ(Eoz%M?uFh+Mb&&zHoZvw z9ek4Gn1!KPE zf>BlmKK84PCE9QvkYZ)xm7?an-sA1mL`wlhC`3R4Zhh6hH?^i`qiayY%}B4YE$Sx= zU&s4azfKCC&06}=E5F2$0@hKNl+}9QSrk)zSRPr}h9`%a_Uv;ub?5s%n-m&`CZ}^N z+|F{(+gIb;1#Gzt+3S&2FfB>*dcp^cu8LvebmavTpU#WD`*kR)wr9W19=2>B%6*J# zBYat#j^@kIfYoyRw0py_bUrAv^wiFxd^d$jfy+9ljS0r$bJ?^val7ellR8)*L=$Rz zb{WTzGDQX3x}Aey5!&8Lui*vqLW8p(Kss&Yxax0gL#5i;ot`~36_)|cSab%w)O@JY z(`;lISo)ngovGf{A?fkk%P-Rlm}v`*P0Mm4`*{VWbUb^_vJ`s|#A%#q#98XTQn<~%?S1r21PM9B6~~37Y~hpj&grJHcZ#dqh4<0g zy(!6P@4N0KosFAx1HKN&m(00>o`cvX@e7$n#=XS-%5Wn5oE3}Q^2!s$z{58`2-+)M zG7Jun`MdgdKA{dzTQk8*#Nt`W7#pn(;aM0&1$9Ofd)lO~sY{XyaH$^?MS0(d5oM-h zLt*mTbG2;;Ve4NP;nIjkhsvWl0nUPfL%gZ2S>1=rAOkV6^w+#QX?)u#&C zW`aTM!Wh8Q3|hC)J9+1gv%EgBMd#)t1RvA8i`jYd>M^9}HTl3R_7+5!s7aKZn>kY3 zitW$`H;b=B1634%$-73wjI%-88Yw!(4uI#*E}EiF6T8R*Z&00j(Uv(mH2-d8QPaL8 z`ez`^*l)tNNb5l^_jW=^Ug`FP=HKv}lG}s1&tA|Q5|3Z(a}}PSk#YMl`me0aJQaGP z+d+Loae#rFH0`#BzG8NEnv9*5-C4CP2-Br}I#R;z+t^mB;DeGMbD`(rDT2HqhKzNZlKT@_A%-~buR$6bgk;^8I zotUd|6dfozSEVXi=FJIsGSbtNL!x5j4DOnYB@E!wa6?-rd2O92{9T|U9-S-^EMVK> zjGB)5OHRI~8s@~E*JU9VH$a*2XWUU-Rd{-W;-ZnnXe|5z#8`@VroyyY0d3s!o*LPi z3%k6-&#SUkS|xrAKJimzQfcm2Ex%$DsqEx5;XFt0Z<;+7SV$2L>Bd416{N zzA35f=Ijy$hpb{pp>ywJ)%xtdwcpS|Sa0X;h}1I41rK#CwB~-jR-D{L5L@G3Z3!Tp z$kPs_`w}MwPU3+l1)oc2)xY$hegzddv9|#a4Ywb$9UFo=X55RyZ>1R-dxg5b(tRX= z%Bvm~fe+W>_@xZ6?(qMuql?qb`$-!`3;9n#{#Z{yprXu6W;ZX=ea(Z=WdX z;7ei7LnmWLxG~-2DF@ot`naaApP47duvT-_UMsnY{*PpU_1c5eX7Ap*?CFBr5BrYb z;k{b?Y-y3Gmx6~^MHvy}8d8Wz6FigvQV73sO^CWEJ$wX-0DF@fsPV_HYyJ7j&e7sN zh<%4h4r+jO7+Q8U)Rt}U8L(s~0_r2f9X+E+oxhG} zvfH?<1@~qJF?}-mHtv`~q4{lnKm421_lfHvJ=U(Q)nIO>#n8I(8y|w`so-H5;~j+g zlLwRG`Vg1mV-k5#u8Bliu|*lY-7bRLOIc;U5PO&_-1Q&9YCNH+y%#*WlXeh~UeNFS zTXcrl`y=;i>IHHN1UVnW+cn*4Jsp0!97(5j#h5$Sc`$@?2YBuibjdiEo$pL5-N#0j zX%8lsQ6p0VB#og=hESc$+=rRx+%{{Yg|~U3udJt6Kes2ZR-_3gb&m_;HABy_>yUJQ zM=4Mj8Ymy!u{rk$?Rt^{T$PYO<>W`o4v67)5g2E%<-_XeVbgC&HxUD24uo5v-Z`Lp zykN(l5eI>6v9O)PcAAUlnEbBnFRzOC91#3sVCBS5EM|h88nfo|kxX9>R@lG(+CT!B zw&Q;MxNUrMCbELxd459K1Atg=FAkskeMmalKgK-C?t+dVz{y47z&#BfG>VHruh}z5sz=cZ{U}$e zcjNS$xTj0KO6iYWy$LSPP=jyC$lipDs~v1z6#&FLJhH%XSNG41JCuo3bR()QWo^!S z`*F(^r)q`aFm)Ir7>fHwh3PkCm69_|j6IZ;R7o=7G?`kQbbJ5+5WCafY`QG2E`em& z&J9X!zi%k+=Las?B5X`#>v5||q%c<`9NG#hoY9_0lBurVydDMGfyusJqB0e#Jjrm- z&?K<%YkedPQJhK=FoKSnro4`%QZ)rTxjl!vh;psvSB6zYDJ2kAOB;#R!Y!zko~50U zj)aShxq^UD&rSL6I;COcw+2kIvI+?X<^fi|O=Kkvy)uUI*H|}4N4?>=-H=6&quQ&{ za3&y2VQc7-NcgsekVBoIielfyh`3H13mH`{Z6!NXEjtZ$YaV+8H{(KzV!CRaVtkjm zw~>^TxSPG{;r8|Q??dn@$>ctxkA-erJtICP9S@hw$9eG@&1_hFX}`i~ZmKriI0?&Q zS`Y6=KhsEHvh`EW>Ns4NY1dSd)XOGPun*u@qS!WgUF+coS@sZXL- zRb?f!5pma^zHT`@bbT;fqSW6;FYKp_iY|}Rh*3&2hojN}EM_=aTp?>D&S|E^$H%Z# zb2l`x(otK8IH}rO8+$r>OZ0^`xH@Qi8`-<7R&g-WxcgnrPo}M^xuwDo*B|s#(@0m8 z506AdP^96erD>-k#?}LyzERC2nX)7o9jNTnl!jENCaE-ibJW{<8CgywiKQq9a$G&u zqZjYdrKGkt=*xYKVW6@RHxqF(R(3DqVB}j%>MY19BH(K)X=^eSHxqcQNOP;TGjj@U zoa30EoUQ=~&svz8N(o%oiOkphH2v6Cx~nh)SH7{-&~`PG5LLA@_4agkHroa)u3k?A z!gecCfR}l{0d=Mp`cik(iQ#z`DE9UW+xjL|A#`*)G3h^;>T_1xO1OFH=<*r8)W!j6 zOQ~0ZNUgbUiQx`bRP~G|pMHLC_?4;_N>y%QP-kppXq2eDJHJP()zU&h!3^MLVXCiM zOv}X4NWoRpK+Mk6=rk0N*VY%*(tE5Jy8hYI7E#ewak@KHw|e@h2UC6!TxbXcN~kBs zvslRu_n;amTYhvmuc>un(XyMFConmv*qBI}$5PPZEwqv{lN7QNtfaC`A|*ADHCh@d zJDa}gy_Kal)rc@rnb*x6(2Wd_swJpu$j53WXeXp#nvba?#>Qvxa(Nj`Ihjcuaa(Ag zUl;U?qcPl=L(e4rOhT(xNA6-AGnE>q%v7+fP|LznR#1-Np(*!N+X6O_9Dye?VW1i( zFQ_~8qJLAZhpv>2fU0#1mrNR57^_zMp2A9=blP9>v5YFljvvMJFvoAtkBa-pE*0P~EuOUrF)+O{0Dq zrU(6-5w-yl)wV%VVKHiu5m|pil1bn|F&Qnakb!1Gs#+Vpfts0wxAS%$$&?+(KJ$+M zYE9Z|-nIV{%(gLh{t0ptdOF6pocEyoaRq29*_dsU)xcL7&-HD~QH zAmDm&FVOf!&RXA4HFrumIT6zgNTX@VGMKQdPGvR9R4C=3SMRr_c;4rLAp z{g}P_BL@3MffLz@I9jPlNm*IZ?vZ1_k+LBP>b6F94j$G@eP=!GMgKMc3HW@$aY1VB zW4-cKNzFO{4>Rvs@SVbwdW*nP`_=hiP zHPMYDaLKLdg(OrhH5}Q5mIdAD08SKefkITNEPN{&HQYSj>N48g z%L4tUDGd+cOp@LD+Jc7K$|6>b14aG)O?itzpqW~$TVw83p(LYzPh@C4I-ORcc3e^t zrbe7XMx(CLQ=AA)T^vS&5!tS^2D*8B<43h9YpdD|-)2m2uVw&Nw<{_V8c1NQBV|WZ zvsIPb$a(CPwY#_d%?hb(x?T&R5a4m#4n@Krf`yv1b>4qH#=(f`Z2DY{ID~WCH{6C# zG%DIi`cOWj9bJdrGBt>I={QQh25bDx73tz`KY6LndS*W8-FUIoJ}q#{eC*k1OMdYl zUR-o>Y&f|QhaAU$T^UI>=v%PySfsMD@D$kDR*TApFp>4J%-t6bI`hjrSh?rpo^hFv z4Mu>cZC+-q=&IsUe2OsY*@EQbb!sz`H*`JnFmb%-e3MWBR+((PmR}tnFR{J5OC@VI zzY8u*4GcmCKx}x=oo$EHc-^1A7i`%SGIjVPIC9&)y~UNn#b0!C%&+rYWb#!M%eHsb z7!K+^E?VJsJu-V(K9^>zBB)~G)T%r$;5x3J_`?e2uU}Q>Tv8G<+6UcP{G&0nq{piJ?p&AXjbO&+2q~1 zaBNCgZ`bx9u>IsT z8@3s+Xo&XZyQ=^+)^SKszHm~EVW3(XL}4ZIF`{~svT@O#Z;I#`YSWT#Ab2Sz3EBtp z=`ck@IZc}IH_ygBrNzLTc?N|~C&GctxtGi1+VjeI$Hl5bbGtI`v6-sef|tQo!FCAi z!oV`hZ4q61aP*Lc_ul2A5lVYDW1wf_Spbzp9h+u~H={+l&q1f029-PHK=R_g#yvIH zgLM0CYaOu8;F*qn8THP6ENQ|xF}?m=HCfZAe<~b51^s=obUqt;VQ!X-F-&y%x{2n{ z(x)`XytnfL--?Pd^Xc(?#KJL(s>`f@c7#UEctCptu+@Rl1v6TG@nX9aQ7ATYT1iKD zVY^yi<7i)h)(H<7D8#Hxu{)>+C`7Qr#w7H(#lgsc1Z|4<@fE@efj}yd+^YDxz{v*{R%p;RqSRb-;h)>*42kjxgIKG&T_`%_eA%k7H>o0DYN(;w`dp3HU z?aFHOF%%S`6$}*=*P!-%OOofrU4&hvUEjJ0?&GrKvtzU4vSaY$@w+n)gst)Q;3I<` zWv<=u>##nR5xIDfr|~3gkhBjq>;0ZFXWNsp$7qdT?XK$*X$`O>+aOpOS{Pm!QW>@~ zq{8{0kfT|7-r;AxONR|-qNQ;q#0K*gWdDKt*UjlFHK~or4djHAkeP6ok3o#&89u^Nf_*ge zE>86fTLm(+byt+l#V4@IZ}hFQ{g^ovuSSw#Z7?@n-pCi3v$}5tAH$Un_lKlwq_h z52!M2blhY=R+k;)G0ZH!nB7vGOJE7w!?^iErx!tD$u?yQ6su73uw%wxFpOP}nl;yx z(T30bY5F7TQZVE6aZ)@4V(&}1=(uv}yVhXr{Mp@} z)D71Sjw2HgRzWa2Y(`%@+R7X0L1aOlOFE17d|Xl=i7)S;`YrADOGkq79)<91$z%zm?2~wuVzR}0rS%w zmhOAx^f0qMduo^&u6p4Q8PfP6;Y43;GlA;(i_i)=%GjM@c33^r1U|3`f#?Oww5OZR z?^?Znk$uqx1LAJvSaOHwkXzi)LMbko25_W8!-xpD?AqNaoQTo(pA|5E3Owkaf-?;A z%cdMM8$~{6B~1B^MIetX?TJOw9SJQD3ly*&i7d~8huHKZhKb_E!C%NdP}M;#nC2E( z*1RN^c#(XJ*@&t^&W7+*zg&unmc|NhtC<@Qav!GWYWlgy)B5O?EgP;rY0!Dd3{v;WUr#+8E^me()pW2M~=obzbEiHtI zT-EdG%(UpskkH)ZcdoQiC=PiMqD*qMK*#Z3W3l^4Q6Q$Jv*U?sUqr95z(RB|DN;H( zg1mUlOzrS$DD2QugVtW|&Z6B`eE1f71-Y(@!zE6Ety&w@HBHNRiinjpXg5$g6Sx-U zWxIT{pPg{gj?S}M=I;=!;Nc7Dlc$PYZw>sVWp8u)l%t}K{OQ=5AQSDjR{^!KiR+Ec zC!TwUN5@AaU!X(aL!#kBsu;^Vv2mxGyL=kQE)MX^D#gE};@#ZC;tXb#W|s6Pf~)CK z($X-mrlrMTo}JWaToUh$IR`U2Dd_*k7L#scVk94nQbP7bM(&6c42T1k3d9~oMP+qH z@vCg=s_^H)q~2v69-i5rvZHSzgTE1f>;2NCmMLm$s=ObPQGqDs5{88y!$U+ys;6oh zF^A4IJv5R~6CObgCF#32o|eJo9I^MpWqx9;*5LM|_U8Jlr@STHS!(vaboKW#?IRqc zV+Y|6l>VB$_o!fXQKJQHS3y*}^!)0nN4Zy~jDl03+Hvus^R)N-#2MkO&PstafF4>u z#5apda8B$&A9@kZdaNDkQf0G0ba|oHSC0DannX$ejj;|LAbMJ^3rxY1H zKO0vA?cAxN{a1ORZOi4G0<`&vq*(D1la5V1i=Pj&nZZ_>kgzw@)TuTeYU<7$-)D;P z@0YE$qSrR8c8=N1tH(k9Zwwj_?v$DKhjJU?VXJN{lY)I zSpii^bs4q);?4e{YyLw9g=YLWh4()&w2XgwBt*^Z9UO&B_3R0lJ~*CIdjGNWFIwln zkh?7OAEu4};B)>h1^FY~_?yr9m*eAq19ED`bX)flAPQf2_T$A1eZIpYR4OHUoMbJF zNBC9K6l2bB;d!}%5fU%KbLyAsMo-P>a*^o*^^oX)#L#^RAkplRfYAFj>^9$^n<@TW zYHmCqdj)&H5@&ns_OLeU#?GY!$MXsRh*qEtu0A;N%Tz&1{SOKUDGGY+^>n|El1B zRmT5a!T(g(zu~C=2D$$Cdj0=3$n|gW%HK_y@oysZe>RlA>?;2Sa%E@z!=*L*qcZt; zw*0V}2pj#2l>E`){&LZ{f_5Z(Iik*C4P8PER5|KvNC`)n7_fcu?Hj|<=`wR%kpGVTu;i~!?#sccBx;jgYo91g>I{6HH% zJX=wvv2-Prn|S4!!3vJiGJWrBZS9+Ks$!KsPtAi{hdEUJPOK4&?Bg^MNds@j6JopZ z)zmB3Yo_0?EHlXi&x2S`e!;~HiUXrM^=|<1#H$vl+NZr~)9R;t1(jXxGnJ+{3~;no zv9O@ZVXF6PgkE*{rk-kLoB{%jQvROy&}6K7zQvniAk;yz6ZUPaxU^z7E}8Oz`i{#U zqz&^$=TwU8P*-G?&YqR86JX$LBv8-(=3I9CTa|g_VhK+MIdUEFV^FJ%X|fS~nxa$> zJFJ+`Z`~G!d4Ux*g?&sMNno z^uR3s1h;hO2dIl#_GwBDtW`=dcFv0){WP;`lNC5BMm=R)+Z3`_o^3!ttw`~5@YW7j zu;6CyW#OIbhhC1dBLBc~fhnywhl-@gY}-B=;lq`-I|$yra^Ez9Z6w zUEIuTy=dKexMHAPUS@Gyw6_pE<6Z$iU@%r!)!Q6b6%Qs?5f5Zn(cAca8{x(MY*$VN z_04Rt-QL>Ccbr!E-c-+q8OmS-O^qk!+<+fgX5iZn$!EN7zjJ8=B(RstZd~i4|T_i;q`qIc17&c8I<1Q z)F}9UsQdd{0&erpNJ+TJUF0(8_=seoC@czvb&`Eh`n3<>b^z6H=uIzysovUW(TQ=@ zCNJ7c_aScjRp-VLr|tby+vIiy?1DH^9;s(qb-|%R{e;`N+q$qusRDJ7Va?$j`mE4c zV{ttEr*wBhI#m+U<>TYYjatS=XHvBYoKxfc*ltuRfbg8(Ab2@z8hak%;>lj&DM=U_ zkUT8VJhS&>lyh3Ar0b|A(1Ybve7{nG`Q;6?hd{CkA&lEa4!rs_s+B#LiT#wG>}agz zVk$KWF$VEdf+mcW&`^D_b3->iZ4w@eC()^TD^5=_jpd}sYr2EAWQ9r*G0V-?Op~7n zgjrDZ#-6X7_4Fr99G9uTuYJzG;U?RH5kInO>_luS=ZCIDhZ`fXrZx^SSYYA~yFBCJ zY;nMH;2ddLqp*b)Kg@9iG9F-BDC*I>vrCijTbm(lj77ztQx|nEF%vFf?Qk13Ce-N&_!+o3tWIG}$kZ}O;hf>DVLQhLYtX?60Aj5L zV&D5Su@K@f0QD7jXfk#ru=at!IDxkFn;pr2aed+Z>^qMe6^Xy7&7Z*0#e$9t}zr>NMvFCH}q3AkdA z?HC7@gzYa7z@vf!IF_td`6UDi{Nuh48u^(@N{SC9?*|gE(;%@iF>H?l+3&mj5A5s0 zB?SFS#L0)E*))D+$=d0M@LW!eoK_L=1*hMi=8?aU3*zr>2@CqQ$bb7AnzV@OQzG1!pOl@x zDJusBYQ%2PjQZG!t?TENBi$7}G<2IU^?||LG?$cSn{en7Bec-Mt1A+M_rXMsk7lu} zFShFRnB*Zilu#n@d&S_rdP&ENX%tLNTz9JD!@$-ZkO8iK^)1ZZA`wJu(;6!oSfkIx zjc{;gaDeC*{Qg{4e*q0bHdz zg$<6+&O;7uY4*vQetvc-;FGtjU3Gk z^!^>m{S(e;@g?#mM%j5G*XL|Jw@vC(WOHEbPqxwf@;>{lNJDSwHN2A5i{(?R{to*gnqt zXa6HT{lC-vJO9VAk8ApO`oHr2N&Q#Of3EbOt^a!8zpnA$S4;n)1o(5Ne?1ehf0X3E zm*G$8{=D~}68`J8kL~~G^4~tEf2aGC>;LG}{Oy(aKkNISs{7BN{C}wCf5qiYe|Zi5 zGAwYgFc8o%vwyf8n3-8Vgbs`!a>M_ZVu9^LX7K0D{`eMX7@0oy{!uKjeF!f8QY>(= z|KnI-`P;nkoq(O?KWq!k%pbaje{2hXKBxb%Eqt8%k4WL4-rTb5X(1&5DT7q)41iZ?6-F0{CT5@VG_2=h8Dt;c&#p_9d;@e3qU$y|^G&i5bGr|e`fEkP? z#}(gbc|&5Bxt#X%s-CUPzVs_Ivq`69Sc<7^s;Jz-w{vO+OtA*sH|U*$8oJG+T@z2LFcWHZrLSh&SJG|?8q97oTE zjDa5G2O}E#vLX8OCyY6rer{q@uZitSeRKpS8foEg7-z;kg|`4)2ZVd%Waf+orC@IJcilK*+&{fPmpp^($*f{9iI45YoLa z`63_|pm<=q)pK`X&afX-xzGxCT#@W|-r|C8H}stzGtDF4$JqCyxwk)VqwGPQ`cFNB zwZk999FwxFhq~kp4@KjP=>ah3axvH4*}aNz~-Z?S?d#Hmv zh=vBYOI>clgb$tRwOe_92Z+q3m+RM&Un}r|&(G09Xl))X zI_|?o>~C{hZK~evQ5cf_PPNiUPE)o|{66d*q}YK^Lk>OATgqFcx%@+@`hvn=peg*7 zn8QWo=*&eL$-@M3_}of*CbEA$%YoMzz3atdw6ed^WEjeB7AM5Z;-aa=hJ0@r;NlA& z4v%Gty2odj##YSQO2oz=l*N_Fa+kQSZy2D26BRu9!5{hs9qKrG`HII5ud<<8k(~@KxsQfK#D!(XM={9(;t!DJ^AWa`;sv z60ET=l`X%9T84*TW(|h9;q4+>U*F-RPhe~NgtLrjYC^O_CSzVS2qk^yASkVLHY23u z7eF)OwU$;qxu5i7PJp@aDd{Odp`fTth(=!0$y89OcPljU2HVDUVcFs$P34gfP#(u? ziRZN-yw_=cVO}tXa@3CfuLr3FN}|iuxQgsoZMSF7luW;4vrk}WwOePeK~YsU2vVjc zVLNNKb>^VkGK9n~$o(zKyT%T&__^Z0PGxP~6Eoc`&NX3MKHr9#iX7yV!zJb@9e$$>EUps6&Gg_x5IUh}20Iga-g-;63&Am@ z$?Q7gjuvJ{&1wZxUq8fIbOTA1LoX8++B}8+jRVhw@61X}M)~QuDIeDq;|cc(rV|DK z$nxCs$g|@HCZ$YfSD<&R9TmS@haPfKDRYIZ>n!2JS(E^3gB#77Gr0K(x#ty^4X*EqN8-O6(nO7=u)hwJLxfSDo4o#56{_LHFSD2+j*{;2`>R%aR0KniA3tdvY za4rS&_3CV2TpINt(bUFDF=ks5JP+UODj8$f$GU|)Mm%Pn^&(kg+@s;6^Tv^lSnR2A zjdFG!z91=9g!t1lCYsV?2b1#K9OU2~E=-0OZ+d`;o-uOk@>7rGx~y4%srs0*NYjai>QL=&_`HjF}xkIuBA@ zQb&PCNd`0(k(EZzxlX6l&QzW*^&X2trxuzN3&CH3k-O@xjjNo-$oCNUv|SN86ZqR* zJMR$Yb~*GKs*w3NM8KtuZq2vH-fiZbPLQ=A(k)7EBrE@^#Xzzg))cMyE9}h$9Mls_ z!z6~rZwSV{4u>lA8qIlyrZh|tXUCq|OTp^_sf;LiOJP~MRI$k`u=x&TBLQl&w~5nC z(*{%D*=Z86VSPvL3tF^fg4c{2Q=~;RmGhND!6s^9yUEKr6`6P^@vt_=MFpLlmQWF- zeNj-VxESz+IVQCoc393p-8Vj)wrxp3Rb@<{Nl>^II-W^b!Y1TjpH}cYkx#w_m;E4! z5<{pAe&SKe4dV9*md7ucy-+yjEP)KL70Ov&(nK>I-1#(j#zHe@HMdhwU|3T zo);!0i2bzbJnPaU|D&dat|PB)4Y#b!+9fat-b$*)y=V81Q0Sz*T;9JMf*rCrXs(y5 zuD+=8Q|6)d+3w_S`wns%d)7Q@M5&DlDRV>o)o-;TptD#>*;?%b)xpH!oce9s3HFM3 zi?N`BhIBjgo3$>j$e@B{59cokScG2&!y`dY&Vah`FA_VBISFy;4NzNGGoQ}Nei)Us zT0Oby(qb$74AHcr?X5%w&EngO(}E9=bM9*@qyJpTAMK=gCUvKV;Y=op-dIiKe&45X zcckTd<-mc2Z65%U;y^rxbZmkorJ#cXttDwNr4+D=m++OnH2XCjsfI9D+g$8bY+Twyr#vP-|c|3E1*gO6l0x?%fXdM-H3lEr3eU zEc%WUC|gCDJ<`oQ05yG)l;QW+$)~&dvIOVSGEh;_qKi_(+p}WbeOBgQN{fBI95V15=7ASm~{Zh(|JDrbWByz?2`+O}})&E)Z0)(`9@c_)QWenW=8e-go= zZ5KU)!=Z&t8zm3+cz?HRnSjHodRV|os+ximUjIBR0Ub>BE{${kEXl5U8_urj6*>Kt zUGo#O%7=F0?IZa)1pNK;0?xTlq&0y($d47Bt;=6ND8Z1g$nXenA~>Co*oADiu3siS znf5Lx-}&GX+WmTa-&ulfT1D9qIlxLfM7A!6J~D`XWLS77f@jmr{|x~j4UzVhJlLjV zK#!sjSF1W$qrFt?w~Y$Wpvr*5RU!jRDNg=N#(nNBh!O}f2;Z;usBgYAT7#bKcOWI7 zF+bDil&?p7A-jPLOcJvpKZ39dz1*?mAk^sOee$G8`}{!rWl_l1nrpQg_wuX(SC?B8 z<+CUL?9ojyXadMA=ihvud$;$Fa za++;B%1zLQs3J(~2gDHSIDB-wA6tagB>rjbb`9I)!Ig!mx-n6w~M&|U{V?>`e1%*bH}zwj$|8z2rE{6konOKRT(*oZ|1IY_-D@CCJ7`m~2CaL<9QRQ^}SjoN@cuY;JfvgM9cep`r!L ziexk^B$OhRtyEU#yk-%~y5_j^IjYB|n~tofGN+rdpka65T(AvyOn1_YC>2(}rSmoJ zs?Mu=&BI!deAY^gLGZ%e_JMd4KKUBnUbty3Z0e*l6d;`kjQ6GMt2)oA3!Tq^+nXPgF8uTbKTGGgt)YVG_n8O zwnd5TW6q%&)jI7FNebtuNZRz*?C#Xw47*%iBjf$e@Bq%$>=v%|b4<-O#aouLlA(!S z;Z14L;5Fot?y2w0@`k5smV^fQGoQ>Df9L;SA!^znxWa)F57x5UG`Rk4&B@U;Y{GU6qiMKkqx<_$HhKkcURDAY z-+IraCF#Z!H@a%%-V}57KEEZv5~TaRgNjGmW1a5Dga>{=t+qC=IG^Tk2CC)GbE00j zB`48w{Cr~O44KAybwgB;tVQs9I*^9_nJ`%(fA0+cejDxQr(ITaW&Ag^HnC#_R!shel z)ud|pk?JA*_u!X>3E9oMa7f#+!fNlnUfONON8HEwXys0+=O98Dzag&GPxSSIkRmvP zfpJMj;51a0+c9m*B3w>SnZguO#o<06^XRwTJTTIPGe;OrqVw7M-lp};r=5;pZvw8V zp$z*5d0^cQo0(fuD)q$dm;lX>=+DZVbHYGGv3BE@q?RPtEN44%w6Chs>u9Llv_m`& z-T{Pjd9-!5pzr>=WvmYtxqZA`O86|)_sIoCb3t*yjzztf&K>SDa@hnG#}r^;tFahG zP=0H}>}POu#l>?yt>qeuJcbj4??!08trg=XQF>Dl;Fk-giVrXqG^{F{+gbf0JVd#Q zei(v35YSVsl>OLr@nn7pA9r256erzdHklpOE`RYzDAn{e;PY%P**|JTktA)$dQJRo zu*hw4=bN|1lw_^Srn?uKw6KSd=V5PWHS=rxMQ-Mv!gDzIac95DKZu*=@!2fcgso6^ zL_4OFAbkV1`%|A(BhyTof%ix=`Vm1aVq8TL(N48f+e<pr1?+4SXabb9+i=CAu6=!oqakj; z;AMyKh0bf3g4C!%+U;{M!4-T>kjSf~MGZJIBS(`zP1q7khC!dv-$Tbm>;w|w(^9uY zMe>k;CDizY^I5Ms53$MTwt`jJ!SOX-_JT2(CM%@lsK`wtElN?WMQGY;@os9vyxx5O zP5o^!TJDtH#if6h1_s}<+Z9p>jO2bSrK`sNYMkRho4rY2HFv?M<`$t2))Kt+Gu5ws z`<2`xA%g-%G`Vn2sUZjBEQ~MF90EUavU5mbm{(mQlyy_tow*~~j{3;v>@32HV6 z(c$g4q|a~y2U;(}j~=`%_xWd`g!NkWt$THAvY$~nm`Mj`{EzLdNC~jg#_rt^pA9?g z1}QNSFwy6i{&HgJeh^cLI63=6z0=H`AblA=<=8Jf0m3xYH=o%NhJKDff#20L^cC|H zw#C&6C`H$1z_a0=h}Li~L^>pxD?|J&sPS!76Q^gPNu#Grv|ehxHMQ6oSv{*C3hawo z2VW8@%Iw}BwI2k1eq<_>s^f63(wYJ#4QNYSttqJu+wZ z81;KOr6)!BC=Rq2op#*GKkYCs7+x32=!ZOEFmaY|ca$qFGW~--yS`*NVf4p$jFf)# zA+j42ekGq_mqkdxNN@^`odQG=ENMq{a@bkp%PEEFR`wE-ga~PVUN)Ln&q_s3mW3=H zW019a?PE;a#A57Bv~K0g0mfdmjd~a)ZI{W?`6HzBYA?_AOc;_|{vO}3iuG8Om)9Hk zBTWW^na-FU_v19#yWN46Nwc*^e1pNKgvWJgXVVr%pqXZY@QkEJ*-7g zVHaT+(LqGC`6Ca)Pvz6dxYTCj^Wh|AWVc1?`8}jR@^z-5;1%$Uxuw3shSejjxY}Zr zU^8okc|e3Ot{zt(iy3)1j4NxYwm*)5SKV%PUdJksHOV|-+VrQtJh z^%s_-!SvN+{e)o_Ayq(E+1cgGy5pyCpfQcj%8pE#b4G89tNKNXd8$!+KEL zaQY_FWD)T(2jk=GkU6zfU&&A~Hal3eOx?qLFWCJg4!dHH!%#5lD|l(k0Q{WOQgnn$ zlZ>-Ndn-CP<*9}1hd=j8n4ol%pPwI9u++@9itKT$Y`*_M&ZeA52pf8E7-Kz#Popj+Ryhi*&V25$$St&PuKc{yrZ>|8kC=-oxZ(WeDd1TJ zZemP^E)8%~@G_Hp@&2UBJLmAqxnUx$%U2R{nryGBNs3XwaCNK6)I8rf(9vI6h7_pF ztX`nZ6(AxSMI*s+G7D9pdAZkHw);gqU+9QpbVkBa1suGf_rWXA(M(<)Rm(m<=Yg2E zdB7jbAw^goj(`Ld}Y+llf36_}KRvyWVfXXgl(+_uF^tZM?rj!=FFQg;`m! zZclxc^t#yc-ht4&zJ_5Z_31d1y_TgL?Rs@(i&~v|8)^zbsPf1-){-@Wd`A7zmwyz; z9F{s#Vf@R8nF*E!MO1If!7OYK_13RyRJUE^K9+7fS*j?# z)+l4%1W7QIgSG6b8dH|K#!M*Lde@ zw>qs0eZR-uQ1AUkS8X&?;fTB91T&KbX3||8eS;6I5RDv>cq zkmiOYq+|SD9oym0D(xy(PMgz0XpC-rbPl`1v<`ee;(KoY;vF-wUHvi`f}~w{ zp$Opw)89g7-*Kx3$1p=yfYx#sN`p#vEcglr-!8dH^CZ9nv7vCZgY|?f%$*it4=Qjl zAYh_cu%qNk)v|iA{jr2S{V@mO;-HhfToco_KvsxToj5P|TE#Aj&6AazsamY5ZKqit z@*I8;ZOL;#rBRZV*(RtYAV`q!cldLPh(~|G8j?N{aE)b2n3>43RgByDKNgT-vUg`# z51qC-H`W3)L2?4%jz4CL7a|6y5TNt`pC&k!y#*}st)(&+ub^9_BZ}ZbnU3UjaFS0F zLhP6>0|V2r^DZ&l6ezJOzgnfq6rB{MqsMdk3-W1YhPsM$`Q2*x2Fpzy5Mb*l8r~=r zVO5eAs8v4D#vcA!OXK)OKrtA#O#^tS_84InV$4APrB;8-t zCoN&8%$W6N(eKyz^o+)=rDEg{S_b?DMlK<}Im5uwQL*0yp6D`yuu~ibKi=iCDeu+| zvkNa}EY4Ppkfy;{s#o}8rvHiQ+w9HyGc>oonf~wJojcBV*JQK~NtMm(b}mBJ%=NA> z>$lB(Q1xJ+6Vg9>P72`Zm+k6UEgO=8=M9(;3>_f$dxo!6!klQ)-nVxrHA;{{k|faP zg$aWXeSTm>vSbUiLek#+tgQQ)$QH0nj;?DN{4sI?Rks`3`MaDj*5t|nyuEUG3btGw?*mu_jC?lc^}#VJ2+TT4%v&UUDDc#>@^eUnQON9m+F>19LdeLN%vXF z8xMB{p5L!j2$BrBauAqT7*!=uJgLh+6fTKEBu}&0a*_?|{tspaQhW1E`k1YbPwewJ z@YaB3LZeCAtl-eZ^oB09y^%$d9c2_(Rn$vR*833%(wh-3VBF{g3ZKh$h-RzoJif0= zuUM$rl9zAEkJ8-&#gev?O%vT_QMY<^l)?PXF?^R=c{iq8hxZj2A;^?b6>UPBZ}t17;4sL7je= zIrxd(_G91i7k&*?pE8Hi@*+vwh}4h-6j3D^jxUHtdLAvmKH|r%R`3*hobsz<=$H{Y zRNW|k0V|XTTP`gCu8_~+2YST z@zp~^QMXISHy!UggoCVJ4uSJg!sgNJi)Df?$}U2kxM=Ty;T@GX zcY9~!_YRvKH`nvvY7`@&bNByO*m*}av37fyBAtLpmli+)sR?QHE=B1b=_LrlN$9-` zA|faPg7hOOf^bfgGK2kE_c5JJ7d@A#di-gWP+{Ih?vXYc(^-gnlTWIr>fJ$j4k zVKg*)Qbj8KTn}Vz!azNh?uINwzy$sGV~mb}OModpDVNa|g|PzH^LY#^aCO4oKC@${ zpxN??G4bAMxpKncDO?=+w0a zUdj4gRm=I0IZb$3=vlAjndvGf!iS5(7FTEvuhQT%Y))1@7gNv;P9%M0B$?e7=yy6s z4O!f5J4|ipVNO3@pDBE+W?W&XKQ;Ho*ey*igxKS{rnjh|z+xqco^~zNXNCd=C=H8f z(hoyl=|b5e63qm;-oF3-E`WoXxV$YVv7DsLsEFZTI;dh7efnedk71`VG4qMC(M_F9$2u@hI^Sxe+w}3S+wq15a zVNlv3ORASK(@-$vqtf0Ye6}*G9>uIHi@E~}`zWnp*6^~q$>vjva$8^kYsKWlniqC; zCBc3>1OU}|sZ#um9_Ee&{>Px^&n_HubRZJ>z9->l$R^pS3ssu0S7;ip%6CLZWA7Hu z_$!@|JT?Ru&N%bWcR~1RN~JXdFUq(DaWz=PooI$0>v_NGqY=3K%__u4H}`%!%Xe_`4&--K2J(9E2N6@P#E6&2awl z;+3EOZfWR@XkVnbw>PxouzwUj_vm?%d!RKp9Kw7nab%;=(AiUIl$j717 zy*Qp$A-&yB*Sa?Nfm)feSLsVVqkK%>7)mp^@x$l^QP`^tbro&%>#@AD5k~xX(t?S) zSn6W4R5S0I1Nc{STX&^_S8M0>ydgQ z`>>2`ubXbKmcSBEmkJHMTTgd9!!Wx2nZh;pm~{{(_Mu{A!keR_9l@PA$(vOX?M&#YL5hEqq)TP5*s z#wcc<+Qg9+=QV9+50B*W4@OIZzmrIEnI=INzXkhk6BB_*m~KD_C|o94w!0>LzO{yuB$QTfdg<@ZP!iX5a;X6f7_L-}koK6kT892~PPkT?Q1 zYx9q4*Zug)xJkHxfkdZ{RjVfvKe=^#n#whg2hYH;QKFIklz8jf5Way-i`HTJ2b%L2 zf}laqX*~H94H(OyOHsN`pVf#|i_9)9b(*n&AS_LvbanQ1Yo+T_4sk^V1Je$wX05b2 zto&Lap7UXexmgH>mYJ{}!+gc^rZE0G6Tecr@=Zo>!@mZy>?C^|#pa-cZkd|ANoBlT zZ)B8pyrb@+jkwxXgv9SDc904;+Gf^Aq}k;*QGfmmL}ONW^ z8q_mA&P^jw{zLO%bx)}mL^ayli+XjJ;l-?*l=Jawo6IW9jff{&obO6gqEjeVA&JcG zry6+`*#fkd1`PB}A#E%8^o^`VjW6VRS5-pVHr%hUFNVDCG|#ZY`K1@8)dylXC71Ny=|XVZcpB{TehO5pUK%0 z!Ka5~tE(Sxz0MNA<`%B|Rmc22+nd0U ziR8wx+k9ZJDCK=0g2*H4XpbcT|(b=(nfq@8J|eB(VVS${dr2A2m6|0%|*DG&b)!7ei#zQbEOyVNZrER zdD2h}WfD+)AG1(4GZ6QI*yeF9)%sp8v)mPX$7ABGO}R~A%528f)K%h;K{5+y>eD-{ z+FIj`uNXTUAhNFPtOT{>r9z2c8V~sgtchp5S_*H6=_Z70dv8-k*BEO%!p$(z)#yFR z@_8dlQp6Iav0HzU>u&i7MrnPx`B=KlhB92;1Yr*=&qj=bKW?zPtgLH9vu9>4|e($E*=-dPomU`sB%^C4j z5@s5BFO`&|dw0bw;oG_%lS^m{b9dAHh-*o|sArl!+u%Wjf@HyX%^KHiOSE>!N;77w znuF`PQ({be5Rj2L)C!f}8b=3Ll>4N7rDa?*5qb<1UM{ODLcl^YZ>><-d`)U7y7B7B zRm{N1+?9q_PE&be%+3XwdB2#W)}D)#SD{{7wtZ0>`KIuy0Ks3`OvJpD*%b03S;<-fgY&5fpy#tJv77vcuqWN;AUe z(?=rRMU*DpSHD)|Yotqn>^HiU#8f3PgCM8Kt2UgVsmFYLg z)K%};V>0?9cKe4N&BIE*t31Rr%rbPQk#cNZ@T`o5_C)vIdO}T-UwwHe)+6{9*{5T5-O<9*MoC>1TrS8#?iln4B=V!ekkv@%<||R1A$hKYt(@1 zpq;#B*%*^c4#^rZQ7uJbG`&Ss1GO#xDuY{d9K|gazqVBMKsJtG!FH0S>5A9IB10_a zl@1Ymt&uGBg@PS&=Y-7j6fM%PNmCbns6^htkzl;H7kU6@;odTdNkS7G4K5>NXXVvi zP`SI4{yj{l+7@NE2-y1Tet2|M|B|ZrEOB!6!s3TXT6-90IJyq$|C+lJWZiZ=5pmKU zVMKt>>Mh_Ly{fy6=*Qg~ClKduy@OH0luB57^RbnE+}{J~C zH(mHX&3wO#tWvwaW(Tpas>PxbNpQBBaaX;aLQ8tg!_>fzQs(6W!|_9db+(E^%<1#I z%*h(0w$H_j^*GKWl8nIhB9=^6HS(L!)cDi$N)70`QeS!ju+L-^eCUpCC}j|)b({L^ zuRTNO9J|AQGPlm^T<%;bDVRn*WnI^I(Vn|;bJr|8;~)tp*sxF%^R6NF^^-69K}(*66#SOH{5l^+DY3w{ z*OuN$CA!)J+qJ}p++1i=;Rgs;C;vJ_QGT+U^Gb*)zTJbnesW7zl@fT1Rs#FrAiBF@ zH@n5|*Sb;$gpAG2Sic@^u&cpsXoQ%Rw-(UX*N^r8rH{zV@-=N3Slj2_FYT=7JEmF8 z5Kc;?snaKtR(|rFW;uO`l3*8P5#pC5NH&F>U8%AVHp#$O&X-vJ`dp=W*J745@ToqV z&qsLDsL-cr62Gl{0@0K7?n&p*0T{Lj`kj(ujStv2VR+6(CrokqAHN-Rthqv^K0%xp zW-e_pev$i$gHlFXZQ1tLH6%w>nyNtO>TS;6_o}>q>1NH^YDc2T-b#_Xyb^FW0a$%p ze~?E>m$VtesOv1|d|g-30Hxb|UAK9i!kD7shOS=T1p1_lyn6-qmSI=|hj+$s2i_?0 z`8odHHDjJ0%cw~2M=UajqBG1Zlh+36P_Y>HHM+5v}o~W1qELdq=Y z=g88i4z4x76MM{Q8GoJQ3-EN4iZs2QI!g=Lr=woLz_$XsO;bQB(#6E%yl`NN1iQzF zU9cL21Sz~e5(k@<-QRsV**msn>f3+%Ec(n^(Y)kYnDu zS`s#Hlkc?3^|OPy6Oww-n3wm5pP@EQHN_2c+ntPRDvbsyCr^%v#M?D2PMA}tsAv(_ zKTH>8yNj;s_>3%Rvxgb^<~*D^co56<<=Q%pvJ$+utNzH6cHs$2$yb9AodgeW->5g) z@lcyS_@cIT9M2YrtDBF6sp?h`sv= z!;nz1x9Rhd*UyHHPNnK8|)mX9g(`FXO(*E_cr-`qp43?P|te#X%gdd zbk*6(qddDs@uHoBqUNfjg}?Aa8m@S_Pu#?K1<*NKG&57?)D}FZ57^6mOC{tQ#Qb@{ z_?|NZ+q7x>L0XUW*1a8!=y(_^`7Xg@@2H18l-FK_f5DZfSFwCi5Zb>o9M*5Zrf#^1 z6WTwVb|OvCmtyfHRQhpz0|7e4LCf+wU*J=Jk-eu9dvP^5C5Og|i=F7A%GA{Mk+74v zEM8w8#>bcoonGg^)>Ycp14&;;diUIS`F!6cfqSBzG0gql{CU^>CiahP*GMf5UA#KO z_u2ue!)yQr1YaE`GhrR3njjzoaV<*j;2mzjXAjC6lBP}VJk9#16V0jKOu`|Gt~`gN z(LQM4w=9wl+B*;$s7VFRHs?5DHB}KckWdp(lSq^DD|yjX3qUz6s6| zRU!~i1lJ1ZCXPGK0ZtbV8SW5{Bkl zv{nWa>)NBHtrm1en$OwrRC+(42W#5~F%=kmA2T~VZ$xc$2#&6OTOqGJ_b;;Z#h)x? zGV23`vkW6l%qIa`6M(ILKwS=#*(jiJ^^t*RlS9=^*~E4gO61^1!Isc^dL=H~2!L%I zz}5#~n*`LoVUl{yBvrzs{$|$4hs(2xw(=9I=Bp-{gKcHI(n~f$&pD z_@NMfW{A`8sH0QVQ3%TGF5*;UVw;oZLWtn7G%XVon7>a=Zqy?~@-yqOubKz~icR{9 zhBYp6hF>%=3?}+#JOmia3H<6Og198Mf6<^&5D5Fd|DyfJ`c;F1L9jpaiijZo$N>`( z`8@|1CMt}@JATQ5)ewKwECLt#Bc6!JC5ZCtv7!(xVDh^L68 z`nv{$L;jdUSPk-f4y*?MJqHX9{a^f`@ZW33&Rx*&^AxLHg5p2N;pSp#?}&8yu_ATs zeXvUlOM+;l(QZKSKTAjjWs3&>!)>T20F8kXU~7bpFc<-`gxgrdA(l|MHPX@wgtUQ+ m3L}uB!j@8`|G&$BAQ@LT>_zFvB80)=A|j+WZ{F5WB>f+g{D3I{ literal 0 HcmV?d00001 diff --git a/examples/gjf/molecular_dynamics_results/argon_kinetic_energy_fluctuations.pdf b/examples/gjf/molecular_dynamics_results/argon_kinetic_energy_fluctuations.pdf new file mode 100644 index 0000000000000000000000000000000000000000..4a95d23fd12f51e6aaa6c5ddbc927b06e2e4d566 GIT binary patch literal 57374 zcmagFb8se6*S8znxZ~swC${d`n%Ficwr$(S#I|i?l1wm}*mfrRW}f%?>b!rPQ>UuC z_ugy&y4TuWy=%2DN<}dV1{Ov(1j^xq+k>;RyMp=QQ3Q4%Gtl1n8v-96kV)3e&cekK z$nn>t3}lk9vT-qU`diu)t9 z`R?FNXh8fF-txluwQJ~O<9+AA0ov$|H0Sr_=g~*o>&1Z^=<0Js>0?)8<;>`_%HSth zuR1J#`03}LuJ;=sPtfnyUpEdO9R`=);kxoi?>7!!9sG>ISRSETrnV&-AdVj|F)`EX z5cwIQu-~RWysYbNqr(`9=4E9t_|=F6w_4N$lVn*7ECH^9%| zCnu9`zSCch)wSiiyP_-N(^LqSbbG{h8d$J8c6F z5Wqf=y?p;pRt85XrsTGR;d>OJeE7wIlC!agjbPLCY|lcj76AXyn}^s)-vps+>1LYU zdKc+>xUiiNFijYB*TJdaYl}*iDB9Y~jlFTe`n(8l=g4<}Zw;=HlRU)n+NhqB45`Z* z7kZkbARE1vONcZG-)(WF{bT86pc}x4!*YNhZ|>F6ts9*l1(Z*JojOR{L;vJVpvRm7IVCDaqN7aFLpntEASM8>ou63m+BkNEq%R!rZ?QPm?E< zkpNIoyaE?y8(z9N7=I)R_XrvjB^)Eo%Q;iH8SW>R{WX$o3w0D2>}GQVB~FST$6SP^ z@RUye!`tP?lr5ZhX(>S-ZE&xf7v;pozk@6|PLxM@J7FA+-;zvm4~rkw5+!k`NOH(z z2ZeAr*155xA7YS16aela)VXm3v&u>3EKEqw5l#=`B*5p!5DliQS#8UvRRRJR-nOYP z+*lh&f~jY@Ak7Jg05A9fG$7&Rqu`XZvUVKlwQK&ZtqTqsNN7#d5VG6dps8~kL!4a7 zRiCEZ$4;0E23O|V$38!Dz!@${M#g(YVj~`mU=tJUstHxfsjT^qo)A8|xp+JXT7c8R z2k&r{;gTlLE_()Nv$qI9(Ow*v*xSQjr2bJA%T_OqZIVY=xnbMa;?qe+IijnA z@94M2|Evd3K8f)~6jvDf=oMR7rRXTic%p;22zDILGh9k|5T5|n>BtAk2+G<|iqHX0 zp6Zgcl&$k9L0pKKet5zxvD8yMT1=F%F=9lZ9+@&4xI`e@OR6RV0QYookpbXkZc&f` z9}~nio*?EsoXgbYpAPGL@rQ_JW`Px8A7^i5(^2U%qn<7 zd%$YikhPF@SQKbh43J{UB2BKYWIi!F$v}w-n-&p4jM4ftot!6X4?}6 zCc>3W%nYR%V*v+j%FdrAKZ#NN!5sf%6-_zL9HAnlpJP&>=xi+joJR13 z>H|QBT^YNrz&K0YOj|Lm^}D*;4`aj#b>j$zx+cVi)Nr98>xR@CZ5wcOE#!s+4`rKJ zNUmXkYjcsP4fZ}V8{LBw{P4(ZVGC^*?=HFI0X zir_M5j*WulL9nrAc1>AJt;l9<%Rt-hSbQh#a&QFiAe{{kw>D4|U1|>45*MTsn?*Kz zqII4zqXy)#1cmzo;mrRS&Iy(L4)Zm<+utr|Lo$~o63)Vd^w_>3tff&i0*5_&;91g2 zbzRp|OW?#Ss&X@^h~wcpB-raJ%#cSUb-8ylSdh9StZoJF%sc6kP&zZKpW49Cd}2?1 zv5S24@fBRVqYwd{|H?(LPy8g*3-_Q;cf3p74Q1nd$B4~ zI)ZI{x_>(|ZA2bx8COO5F$q$fiW&&`0T+H~Cg&IzwS%ozzTB*#$aQ*ReZ9m(^*)8Kmf#{fmql^f>5{E26z)QNkh^hZ~-gyrHU;K2D8H=cssqq#2VkYxTM zV=dn z+~NvpDZ;=gVAdGi3CUwgNdrlvy6{CmFPpdvr7%#epui&@ADof;r(&421-V1HyCm)c zOkXP#;7;9#=BpHj!!r_?JlJQK(=TJ=8T_LUPzAF))m5r}-Mhv2=rKwj58=lfq7^2D zQ{ZA8;jb@d0e$|cQ1H}H2^G8fu|O~uh(wmYrpL$vzxd@L=*YBHIC=2#k*eQB1GWC{ zP#r>?TdtnF^^I3NV|&M0@k^(y^~jP`S(JY;N^5*7z{^*Z1o%xOGAiA}`E#O~TO?pB+w251BB3J8__%(&7h+7iByAL&kOC8(Y|{ zIcH}M@q$+M*H5s3OPye~gdN}RWH@nG2CJylKY`lZ`N}TMR+%Mt75p2-2=1ghoBC*S zkdBCCx${9%yjGtfz(u-sL8Y3-p#Fd&l#msr`LGg#b?r<~G-(jTPlriC^w_W^Ei_Qm zlrFVU>Ao02Wl3KV(2l`!86sMjAT0)$y`>XhG|Bv3$nq?X-;w!X{->PauRHa$`S#<6%{;iC0I$v zXIh(w>bPv^Bw3b;Mg#;$7`CoN9q0!5Qo%B{?TsRu6g9)4L_D>fnZX=J)H3L0nyCS8 zX$__+VYD^`L*X<(@(8SB6b}hHn@HI{bg{A(h&&d#Y!5Az6$#(212oso&ieaokOE2) zG@o}KA%((tWbX?l(MZrZHsV>mPmT?{4Lkwy)N*TxFs{P}Mr6BfWaVC5A|Y_<0DW$2 zww1C{4w{c3X@V=r(0-d%-dhyS9nzwo?bI+(>^62rW{F;*K~3rLYe!TIRaKRy>olz1 zg4}Xq;$Y#m7yImx%kycSGFdeZ~UYrXWWX$YN?<|V$SKz2YpL~O!F4pP7tdh`_ zqd*AJDC+Y3y|Mlnd)jAdNo;mH8xWtnN6Jv*$*Pds_Q(i-tF7%(HN739-Zh(vK75+e zS8@G!JuT^*s2tZg|Deh)$CA@MiGBl$!)PT)vn_u^2kL*JfWxG;h2$`lLHjXCX(i!G zn8YFzyiHHc3hhnYVn2xmynRUTla9TAKpcif!N@+-rTiko|ss2)k+mZ+Fw;qn-^NGm&#;bQ)Wqhb#z5mf2Q~O%yj#+mHP_tVT=u%9&A@0Of=x40#zW_(rM~ zLp{-048F8|tG(nQz*ZKij9LdZQ;BIJ(EWVWO=?22(R>B&mOC+DB`G`x4`~;UW)Ss6$ zPJ$q*TmJ7*O3e<3^Ep3N%`RKt&_YVC@PlB2gKM2FZ9KST(Fz%q?pK8qyPR4Ooz(EZ zhTe(5RiC?xd>7ba? z4LL4{?4Su!WTcCgEmf5yfbNjNZ&zH9jlE-8N}>(YrOc73%;CgRa(dCOge%HX*quX~ z;rT-4Nf9<#czrGhuRTG968gnHj}r?2Wg!(v4kmHaBn#h{S%h^(*@wksarVv_09zHE31ypr$AXoe7_zOLypJ8 zc1EEDudGS}3oWG(5|T(N0dnTFA*1RropnBB;IwCEAJ1n9TWFkN}cmM9SCzG+D% z8_**T<**jW>mq^=-Ay*ui!+ca`l|igQC0-aT1~k?$5Xaw(q0SToJR?baAmCZ^OQa< zbS633xZ;CTA+{7c_}WsG4tfM_DozN(yRr{C;k%_4DIC4ozK%8>sl=>DrGE?U1Tf{CGcsr&~AU@HXx)Nmq(x7JjaH<%luxkHW6GYn?_aaXs3-YjLP zorwDy?^5`My(U1i>WfCgSVUy;&k@XJrFAVGjP*qjh%yaX z^W3rCxOOVRb%m$vRI1u#x9g2u<8s0^rGttPuDP$9iC-w3#e3QM#-%ouwlpcCsqw#kkBHo}Z%E6GC~np5TE!lcpJ{;6 z0zkMNgjdzbJkb!20~NMt2*HI%dEzS3xgAQ)z2f7^lO4SX;iU<+Y8^8^6=?)n;`Gdp z_nBz}$0U{dj)14`BttZ8E)m+#+7uLH2?xZYB2Elw^JyZKed<&6l}7*J7>$LW=h&RJ`X)9|O;g z!aR@<0U5c+>gG`cAO>w7y&p&p0{c@Z@dI%Xh4EkG0vM3?`p|83Va0Idpp|{Ph&uTG-Kt@`|62F2U0Ku>Ohvgp!OFwzI48*)B$wonUq@BgStF*N zCCMEO{`MJ4!&iO2+WyP_JQJe&rOk&kfq=%X{nP$wnu{#O{6y*V^u4>FErHCrJ-L(Y z-K<3S-8x6X|H-}E`I0^uJ(mR>m6c>tN`=Ui zo>$$dX1e*Sg_iK5Rx9T4n?80m+HkiFeTSefMTC*OMJCv3myelxu{7ostFZGrm_ zVWo-m7^sH4NsSe>yVM4|pr6kPA|G~2J2Z0{z!eS8(dtxjZZZVpyXIb6gd!fmh4fYC zgV~D)_B}PlBYiY-B$7{vjrM`ytkH3-?H9*fCbA_A*wTTB`QZ5M-*jAs=R$>4;&_vhZszYD2!X{6xt5`2IhN{@ ztD1D2=rv)YvI%sBFH$j$k-I}8+-=dau5p`O7nUPhwJgMs$Mvm1?v;SyDluN+dmpiv z=~+u%9Dab(KoncG7~Lw%Iop%S&ny(9d{DH;NSV>u$2p`uGrBSf={Z|w7ey%81lr?^ zmHVlRz{yE8l9r@;6$cB(%c{7X#@LV>OLB0^JN*-4@6eK0cbnMSo&5qr_wKpx?H&f)F*go4Wj)#H5|9FEkP zloz=m2Oi0Du>{0P$=~gmru$rLU>yo#tWzm4B@j1!UyrzQLGx*|SU8ue`UdbA`+nqF zmJzUvboV|e_z8U&E@>eY7Zy^m@+@n2xmzW)Ox8Gi(a)Ifw zvE?37zz4g8*f4S-7_)E%kL2*oGU|HT^ER0C8?0=qVKKfo%$(Wo4rek%Mp3jZDjFd` z$t>Iy$U|Ga6?%RH#6U3bzd}*YmOuc-W*WS;9f-?QKjUimC+wlqX8t)L-C+@ZO#n09 zCn1*G6cX@|wH=aRYNgC>xm&&G7?}s>gw9nf)CzQOxQ;5zS(v|nHjRY27V;ocXaH|K zot*f#CPWktPsO#0{;hvXe!$N^J1=%wZKof|_QkTbH;5q%LuM2of@Or}Js+xQo46XK-d zX6q8UsaR%qK=Qz7cLq{xK=gzm`8`^@87_Is${V!WNaFp3*VTIy@m$h(-o#0AtA~L zwL4O8$Q`W<$DRsMOV*r*JM&>7x6x+6X~tZv1HpcH<;V@nLQ#GkPShW0O~Wm1F2&Td zS*R$m6+L=LA^d6F+Clh0Qg~>|LZ9+3Ybj@-Y1WfbRXpaGubl}D-nq)HjC~j$5PBi} zQk!g|Hg;IAiOj0Njq|Z-g;Ey-la2M2hZ53qW!{^NIEnNOsVWeOVj?gN$tK{Eie4fZ zTyf~UWvLO5^|m%{+HfaFv$Yx-_0E)UxL9H^DCwjwAHhL1;0YRO4K{mGAH@CfrvfP? zTYtpCsOVs?|2pm#iz))UxtT`xoEC&cly_Q}KPlp|ZA)j=_&QKcJu~sVzrDLtD#dBn z#QveP;L+gd4kO2D_h!2AklRqq-d_!i<76f%AK4J5{+P?BE>TMPt^9EyJ?z^R zz{SA4zKIf5uF+Od2PV@-XT`ibk0tJAvUSFysovJ4cF|-a@H#SzJ35iKLu5bqy7J~{ zH=xz_u5y}Y+4JC}5dHLHd;L&FyS+8md}n>|79KEz)^5x1W^T0pt@+v}*6sls4`{GD z@1T|C=t}wp zmPVt7(VehBHx5F;dcHX$Uk+qnCw)Z2TqrW{Qm)O<>k1 z*)2hI_A8d^bv}28nuL%@E7deL-D{eMMf#AQ%5|Y;J1gtIPh2B!82_}o9=v&1Z%y{c zt~xqt|87;E9WX)QyxQN+uhApO6Ypw`WPHow*;@?EHLbZBtV5prQQHy_?Pl9mZ@J1z zcQm^fQ+uxUm8ZRFVtgV;&aFS1d_gUE35v?uZD$1sNp);Vdx!3kAuz1}&VeP;aNaYu z>2z}~42QmFjm>qqKbse_K4*C%w`2cnr+mf6Vvc8{{lTmTM!m*mwQNd-{a#|ywS%wD z-d_K>BUcWWvE(K{;cPbMj_OO~@lqcr5XFv0<3SyR>7viq*~8zcHrMIk`?x$1G1zwE z$ur_tWl9C&Z;2`S^3MMB)f77WEsj~69S^2RkeC0vzVc3aN>#rSjYeqkH(V5qw#=5E zj1+E+q@{6I#~@ru5hubtVR2lLl8a0#gBTWp@cZT6_P|UG~}Q1#1#0XAM^XQKR5Kpv~R5Pb$s*?Tw$X>rXi`E4lCkrVaJ7rB+E2_ zL?RAu?!xQaw3tvA(&>|w1)P}CLEAp<*Q#LWe4S)~X!C$HNy|lolf*Mb+Ev%4In@QJ zLXFw`V^<$!NqbrIOt?QARVoIDE?e4&^GC(CJn-TQZnE)Uwuf zqYKNU1k5-#4QzK0vGS;r$N=i03FwkL zqDcH|zvUgf4eTEEh89aRwB2ze-|d~6PUNEq_wW5L4})a*?vOt>tNTm5S8X z2en-9HTY=AUo7VwoJvQ}((Bv#Nd#J&*zvSDN|?#&25d7fSnKC$2p{>Vg)Qv=u_CY| z)ESxcwY?XcobegfI_i(w;%>$1YN~Kw^_(!349K|I$B$;k#oTM)czoCk_CXq3K@BL} z`9ZAt?Mmj$>u5#jF}sqE?YzS`Gl!nNF;AxAut>isz4E$LJxjr8y`S=y7<63$f#8B$-tcR zpphTmPr-U%N^#;1h*Ss*krV7)V1wRIT?35wUdU=$dJdNlSl&&DU>YoS1B`|?ryFab zGfN~Z8RrnA5-!na(Ibo$-c|?agNG9g$j^_IYtVP9hY{_f4TwN@sc+Ya_a~65T+h&@ zDM=kLeFd|S@gLhbvh%&h>zm-?L@K=P!K0A;`2~#wMArs-g{_9DSrv_3+=jvY{TdH; zUz=dTWH4~g1CgT0AMaa!LV{6$Tluv`Cy156-FoN%?vw%z}FrO z+B7=3?%YPfF97M_8al(e*w;c+xX+8t=*d^5^8VnRlqv8yvi8}9uOBKD!75RO^GMlO zy@ulLpOk)sQV4)dK@g@p&_vDy8cQrQU>Cu=mZRMsIiKTTix4`QA*fpzAxs-{Wr~!O z)rc|^ci4ubfQ!NFCDXKn!Iz@3Ez@ZP)07-8@Q5LKGKU^_yTExRMdZnn{vqZG@!7AR zULie}7O`N3e(_V32M~!ARc1igOs}1qA}~V1su=REFBl`7Lm?!TJ1CJg`v=nmWL9wt zX-C3IHNoc+3;Z3c*kcPd`eH~J0R4+eJ-lWey{QFeD>{^x2drH^JXTC}*piLNme6%8 zfbT7Ker~KC54VETm z@|JC;lDpCcVu8IsAj5ZF+f>4VU0~*W_Q6Ev!*(MFEsGWJH%J4oTgH%Qy5U1i+s#kPCY*FYZwXgj^h4dJPA3k%WkJG~O znuc^+6ek_ZX&orlXLAZ+Sh_hc1KN!b?F}i7)hvGG&WQ$NRsV%0N!OJAD>iYP>;J z#+HOaEqmWI%_>XWiR$T~-7+cp4aAy9)sbW(?i9o~MY6$PBA1kt8DMFl^6@N<_wAcZ zcB?U7VeDFsW_E>sEul8;pv33{nqW0&{093%BG*okX#`32BcxABtmaBSw|P?TNyRvr z-8c3%X*z64>PiBZ{6yU70IxkAu^aggQv-h>Bs zt~4aA5ua=EVXpidKfu`;7P#RrLP-1T0o^xD#5hvY1%CjdC1^F(fj2E`qPUy5ZD=*sM4uA-_^Rz1K#oR;N5)nyT?7o`pxt8D&lkFxHxBKZ}q&#?_t!*k2>?a7b@77 zX$6~i;vS1&4Z15>&Q<>U4NrgHKMTa|-AWr|wjyT3^8zCdZaIGCsM>>9U9TB8;=PdhCcjk&dN$}tg0lT- zX~{o7${@34r1{2YcK}Ez85(T^H@>}?8J+}n28~I%bBVij8J=GRu7WW!-{DD+7T$4v zzS<)LCSRkyP+vv z8MSJ0(m?K3aIObatC+0Zi*kInwW_-ZR_V+dgiC+_>dYXHhmkE{B2uv#MjRJ~kaEgO#q ze9MoosmKWpp2y1Grub5*1=B1pJV}L}hiP~62ysH>`y$DsOcv40z)OSti9s`EmV9dF z>-*D98Q;zs)R?t6J=Lg)A35it$fI1OamUY?6u9i6<*$s-7?Er&Cuap6*-wk}fc<;q z(wLIJzA~BzHFqPb`c&atbA+4U$BIB#dQ}GR*49F5WVE-!nMk5o|q~?QU+~Dx#E63 z-h8bYcDvIfhz!#=ff)9Xerg4>3SXB`sIM{Q~6x3!s6)?ik!w3#%Jn=_FOGGqC>k7%z zBe76DxREll(CaP+w_ARn7hX!6xAc+I5t>f@(F{$J0NWRdSR{_7u^5yT!lbc?JKvkr z+E#E77G-XhMFC*;G?sH*mWTy zR!Ls^YASe2e>*8YS3=AQ|69*n)|Hrowbb0Q49++)UsWQPIs4O*6fjXFOef()PG$s) z?8o&z*f@T@hLFK9mnCc673Ax znptf*DD#$jlIUHV+?9V;8mRrCm}rU_^#U#WaZ zk?yXTLRf;Cb+6#+UXe zhcPQG3K`NIm?ng=gw)501ZkzNtZ_%rJtkElC$r{&0A}@w!bZ`$N-H`lFam+F?#Aj9 zMH^dkc#7wGc)oIY=Wn7rFHsaZKRqL?#<7PnH1%pN&6Mxk|NgV*#BO+5rK=<|aOCH~ ztN+Btl-`X>7Rk?g6#0ydL{1t>E((ng zR)$@hoPZ0dE)_}wAt{0(34@6L_k9Afl6e*=u6D=y%nKNL;U>+nbaCwyDq=S6$-gIcRvoj7*`2uBY~a` zOfn(hybl6C4(x#y5`L?<2yKDSKTd5p`P4D&*nb%PhaU_Xp|A!V5}u3{l>RJq%(w`O zzeXaAeQscImOn(JZyILccYPYp0r$z32ZI$}jk28HxqGnia>L-7-t&BCSzyUh;FlsIsQy3c_c_=zGGm_v2@v8a1SrnFFoG@}HFUa@uyk zF|}A15d6qIxwaYoi*ItxC)sPEiew}L&!b{pq9H5lFggvCr4*M}d|Wd!_;!T<9FNF- z+)yeg(Z3U7Jg5`y@QjMY{S)Wo0}dS4w`+e75`_TvZVCbgQD+AZCG(A*G^sch>Uk$2 zcq=;DpzaszV>fZ7Mwi)rQEqj`O8%ao#zrc{Pf9F}a=Z*+t#O%1&FW{Z=A*5~=>Wfb zY^jK?!gXP7ng9dXpZi({xxxl-+V2WgbkRg90(uc&^VNxN`xh6R!51qUZDjto?tZ5W zj~uTe;dy6n~emiaS`; zXck8EZK(NSWtTx0j?B>LQ}7rD?AkbW=_UPn>LM(Y+o}O=Q9nS8ozm6v!;1etTyga`6ej?$yuAT!&b9Fu+*WLiys^<3SovQ*clUs|uzEW^bk)zJcM220Sc< z?^i5+0BmO=mGKPwXlJkJ1eBJf^VCSBNgABqXOEtE7ebdBVlBtXy9vjIS|uLZ$w%ET zwI`+go{s_&Q<&|u+Nkm_m+VwiPO^g!DD-6Z``zT#z<;nQSdxFs!0 zOg{rgdJAUVGDU$hX-QM|rk_O2^*ql88>`7RL2*G;)7ETo(m5ZQ37V}mSy-Hqtklw0 zBRO59S=^^i(I^Y|St&tls0&aFl}u%n1cvu5lT=DF=$LOJ-31UZWZLBKMU>x|w-d`5 zh)rs@s7ez^gEIoguec-N$FYB#Dkd*LC(?~jg}IQmQcjR#4%G^*BeqR?6E8;oGO>ut zk_`euT?S=mLDrm{vak9Mc_JXq^+vR4l1{Vb1T;hcY zBB^aHgTgV(6y{e0PuOn~NN>?3sejMn&D@e=(EpwdHpz%!KOcbJ!g*xM zA&%PT_y#jF{u``JzZo>+loWIIivrJ0nAJ8RhVXP7kD{2V&$(0g4^)o~c#Uzp>%AAB6ZJl#Hh)fGkTf>ZOqYx_)c@t{N9g4C(gr05B9!Hs$)j-Bv?P@e9g0}t0pF5lc8DjXw2+|l35}6jFO1`i4rJ4+BYgs9mACqFKj@iO>K0Z+A;)Wc`mI7>x_eg9 zXp%fzU{DDqVIUABp%I;s^vM6_%KWo=&+9IDP+Wk+qR;j}Q;CCv3?I89Hv|SZt?In< z$+j?k9xOz2#to+i4C3DuOKVA}N4}Dx?<;6Xa2GbX6gF%kyW86xn%Fe17$9LdgP8z1 z-Uze3ZvIQD{)0_(9*&mBkU+a3)Fw~x^_UGSVTMjK;oUt{C?Oz6SRB?E0*`3BgP3Ui z4=CHhhSUvAZJ>@u><$TF`l*ywd2n}yAUF$4P^Tqba@P}5_T$`RHfrj-Za@ocRa^;; z|4gU?nfOh2YLpo9JAYNvXAFYt=E(z{_oa+M=+kOl%KqCWq()xm$0MW$4l#rAnVo{x zTE55j=?qtMknnTh9$>Pw{cbp~m@Wak5@jgq)`rCx!ENCM6regn-?N@oYQvncykDjFD5x`(NrD@y|t!7q_&U8o0WUuchuXDd#Q>s81 z4MB9f$4aw@>V#)kf*KKf)6jt(Zu--s>Zi48o31L97PEnpAOi1y55lk?Rlm+GPPckp zNqNoTYw4L}FM5+I9#m>sr9%8Y9K^FONcK2k*Vjo%+nuPEAEtun5Osvdk#fJA8qP~N zz0rC(9H4sC_pTu0YaMD(Tx73$-B;h=gfOM)n&&+S$T27Y{2r$Io>5;v*S`#~_+;9V?QT5ZI!F5~)|Vdk zdFT0n4)C1_mep*o&mvcU7O8lx`#AsonZA&2+kPE}v(z0Kn_vt=k62C#qT+;rp!M`cqhqc+Yods_mB3+Z8KEtAOU;W>DarW=v zg&~4;mP`RB!l7&$9vYh@LU0r!LXa{I;uGGkPCo`<=fPWV689>sT{ZakTV{8Q#{ZMKur=SzIDma)p+0RggESc!$4uw&BNtwS0E;#N8$7l^YBLF8ve~0 zD(ov_K!F0ITqMJllPdCOWVc{}3VB*c>69SFx0a3{qH~Xf%jbeC8Kxkx9M93 zN^`r;sBT`IV9XGqgSv3j9>lAUtbULP89BXfMJyJTMo0?^EDWV1;x}W_ zi2UI}XG~iq+b*V_ri}dsyPu@VzKZ6SpV~v82@N zj_PVmQIm88u_iv+4=t2ZyPFYp^P58S=L^N7cHPJp&;(%)(nzwG@BPN50PaYSX>v1# zxGvtVn&5>cNrEQn3+2VJ9&-@P+}$%ZkHdY26Z(a3)^vC>xIxx(ok^QI3S7k32z{y>HEym}7f%o?v)}CBAvpp5ky(mkxf1eCEE@*^~K4)4-(#Smv^{aeZ%~dnHo`)wIP(EE3Pm#A1J!(69O8 zpiS2&%+)t75*4kE@$@K2t^%oA2L+^68=_Af8ePbW;lF?r2^k80%`iC0n>UY)U>J)2 znJyuaaT>Ez+*L4Hu%-6S;NueY^GN#SPt_+Z<1hMI1T#C+|ANqeYybG^f6(;5l7)kl zh5cXmzXt37f~!?M9n64CibfXy**cloxd7Sz2eei;bGCPNGBI-oa{iA&)ZWhJZ@)9} zADsP{#FjHNwK5X1_W}@ta=E4VeJ3<`M2Nyg}4=+>`he6T!1=%ory^R znN-a@T!4B&CQ*AEdnXkKBNH>=Kh|5+nFYx8pTi3X0GY%+TqIRo{&L>`>63J3MPT_C z`(NLZe|0SX6X-vo#NW{Vqfu350doIW@>jv~KUGy#HXzHtAeH~3;{Ryz{|5MVpLJSTvUWLC!Qyd*o5)(i86=My5Rl{+&mGwTR^?U88ZFSA!%6GLB zOz|xUYS2X!Jb=AW6YKJ9KoL1_%bJ-9~I64M2bq&2p;Pv)Z~3C4Qm(+E1(d*sG4kV zxX$LW?2xW&A|st@zYt$*7O$Hij+1kMPJRZIyfFT z|8vu%@?y+Fmog-`6X78{ci)T@$BYwDXP+hxPN`*^X_AcnPwThMc{NiH0PK-MJDaGfH&qR+*%n6VV5eH)3J7)!4c5Gsb4MIz zqn|Xqi}VFC`uyC+89d*bk?xr5H9yFHvM&tulsR?zs?J-ABN#|7jm>5zeo$Ig`c-Ut z8VMzR&h-5W?Q^dmWHmD}M4yx2k8=}xtfq9F0v{4-*%itcsF}cMiV)(zyyK6{`2`lw zFV`B&($xUWHx#7UE)6?w&krU_4oP7r=mp_>rh~?UFy7m3S(8}j9M9_YarB1-Q8&tN zM^>0j%LN5Vq_8qiFkbmhLv>?+Gkh8zJ?YB8!_bE_0KXzMiO;FV?I9nLlU*g}P zgSw>|fi`^2ApNco(Q*V!qS5mZl7$u!anvE*gavM>l6%Q_?c+cpTh$~te1V-2Dwp0^3 zKYU{k#x~B?H`+j*o;b+wLy#cTVgN{-YZ0Mn04Wd>kwpw~9&oW}N;G^PPIH7rjNKjx zcyP8}5+?cp)^4y`__n@^-h#dq<9w1ql8Ow*0lP6Gi|?~vzW#i50f3@Rz!{1iDK&zw zPenIMSEDMi8e~cDj0YEfunTJk*VelUQI8Tpm{% zW07#0=s_kQznJKfs6(Ggp+n>&^-=KF1gy~gy<5>Yw@M{jY`d<9FHll6B_~1uw|jeW{}+rB;Q>Os}_)eq~n855E(#*~c7 zYQwm)%PY8APf)=T-y4T@?3Cb@F86DV4-^coz3jhc;$E<*Cs3;+h5N`=d8eud2P z%)CzVP7R-tt|`J5-7vw_?xO6_>`uK5z1(dBl9HIxY3f|{T%G|=g9f|MYyMpg@~V(@ z$ymvVVOhncxeX=VmdUzFSc?Nwa@JC|*1?>rH8r&|v4t$IUfvZb09Ai z8>|-EivuP-Eo&M1nOl>xtGBBQD4o8jh;U!4MAXpCka$=Gx-`0r*syrN=)AbBsE25x zsB|KLR;_kVEL=UDuz(Mp00+&3)Y-oHab{gQc=v1vdiR2!Me|SX*@}Jre(~sJMYK-0 znjJMh4guaK;%5j-Pw~D?#hp&G%RcC0Tx;-a?BM{-VZ^o8lhIoYXktK3z_dtWpH_&0 zWQ8P}z;R5E`xm|F9i4HI#r%n^k#q=UP?ls)TFyy4s7 zS8q0BHWw$84(E@cw{Erz3;6QDg$m8pW;qwF?w0NQj?*YBLMw^ot5LDh2qT(Grk zg)D`t4qemQ%Yy--W+8>`cDe}-c*}lEG|TgK3jXrozNY5vbEULO*Jpo z=k>9Nfb;hJhx}KUEoVrVwe{ncTR^hDn)dQk#g-ia@ERLVj7iAUpk`pV$yV&|rn&n!>`NIwKWJ}PdT&(Px!i*iA$ ze!aErvfjzloRgML6CWKPk#mXbm`U+K@%+J_D5rUzxkZj5j(GN-h}ePZUAsY>_pN(j z50uj5A1t}ePoSJcT-Q5;PXw14u)ND|pe&lx3n2}8>}DP^9-GI% zX4CN|@aP0mKRxflACgmQzjBUD#!R54rE+Duc;5&O1YU=QU<7lkI`X&F?aicDR8?$@ z`X*LtUpLzqueQIwDJPbiRB&nWc%^%_p9j51Ea10h{Lwk{Hao7rv}!-Lt$qKqTOQc~ z=5_d@^~$jE(Bicp`I(Lb5(fTqLEqu=slCQ`?6vVe4N;7sEimTJ`EL4daJHL60WD9R zQ6fZ9Q?VY)Qa+vT<0M1Q#N%3}I7SwL!|sDtZe;lb+A@Mv$=#q6@6Fm$7| zL*T*pJ^R(*ZZPKfO#VqeAu~e2#S`l7#+BU4_+axf;P&-@V!=N$^dA)XlI;JjhX3mB zzja>{T~b(BNYBB@kdWzLt*`ap$NWzT{1+V@{!cLQSKm8*NpmJb25B=xhcEU2uYTA1 zPnrCmnDDO%7uIvsv$Qe!mrES}3rPM$w*Qs&|6d{g4*)PII_W$9!!v))Fn;la^;dc* zGwUxyl7?U8V&>>ZC-GNnI~aTcfS$GE-&S8I#qQM%miz%a#!#)4z1_A1Cv-;=fPkzfx5(aedW&QOf@!gy2Agqu)>lee{25kVlOi{`DbyGh0U+dqU=aA@l$Bh<_UV9fihM1FnBI zcE&FN{i4yo8!HPJ;r|m)|1|!eBmNKb|8ys(XY~b%|C>{OWk56e3*-MBA@mQ3(=oAg z5YjPo{nINeAty7(msd-E1(TV9ptXsm(bu3D1pj)!BOwRlS5W>N3XcCaVG!1{l`t|h zF?A$lXa2%d#jp8O`P%~UZ!I+ImvII`XA@O3!@v31IKEauR?qd{5)&iqSMl%Kd^!Es z+A#kc=>IV*|9RKpzvASpmw)2q-y#zs3l}^4SAYMvu-R*e@kE_p7Vw@JJ3Av?CQU`O z1BsF8@!Kv)4UjG}Wq*VLijDRtzc|2`=!pfD_%XaEB*FN-sYp;jKo8i8H;UtI< zNVH2`!_&e7k)~}yA5jMmx%Tric|G9Qiuw8F=H}%r3y;IWTIQjL^(5Er7;Sa{B7r7o zj!xavK~UXl6soLUdXS3Sty$dBgXqt-NH&S@7YU zEDz5vFRY=&sG-HcMTWu14|)iw$%p`sakWE+CD- zACI%vJN=^e^3&o&@D&*s#BQX~Ym|<0lalamzLkXAdv+J_H6nmfBrCRMev-xb&HpgwL8dZh>vGI(a@> zCZ^mjes@!XFXXawRk;A+q5G{ojay=@NjeJCpN704q`;T3@*=K;$-pnmYOoudQ@p?* zipOqw&|ge8e&rKQYTmMSvS;!u*7in#6l)N*iD%no$$OiE+mT+6_0^Sbq=457VVG1EN~BH+>QIY z4LU{03Cnhw0P}iZt>V8QXfv@sijXZ0F9Bs)G3CqZhU^I{I4WN^))?>hk@5+nanrnwlzzebl(@-h#2C1fmFcM1SKOgdWm#9SW>~^7HzIFr;kg zv8Ek;I?DWviqQ4TU<<2{i~lNxj*2tdQIK-`BR1}R6-y|>b@d4iKS&TmEZ{2WAe=hw+YSfGx&3_A3d2>A(Q|`>Ch~K9i1#X5`g2?;(=BYd?$43kY0x zZw)vyO(>wbte~o>soRL7<%~RW{j6rO=4-DN{VRW>SLdjAmyt`$**X2IVB&l9=*D&pf%9@y(^)#bM7)w!$k4Pv%%(^Ip%_6d2W85s>ThyNXDL^BE=oyqXpz2inTcRMhyrCDVqS#73C z4~uK*)&pmH#YH_TimF;lv!yhppqaX<*N!5!IminN3Z@RVJMYV= zsi{g;LW-zqyjM%V!D!Z3l!R@4q+>Ku(Uw%H&?&E9nhI)chx(;#TBw18E!+s0!X(Zs z0W75Cn-dvm^!O>y*S9?^jJADRo8J0Fh^t`z&XfGq003OeAwaJ8*f#;JM=4e~m z`Frm%zst7o%tjN-=}Ty-xX%l2dXRm-O=xKXXi6ttwe^4}5cn#uz8&hUm8dHH(j|OH zvJetYpbf@eU8af5S#eOseP;XIO^(W_t}7bAy560h$XV%(bUs-0-03C;vHo+o=|~b8 zTGMl@>UU$oKVKp!TK|q+H++)=b3x5P-TRdkW+BT3Fv`$^usOfPPteRz^1d1K`j*1r zNR44Wg1wrUt0`I!lB@a5me{5l-n8TGl+arAaHD+jmLf>;T(P868lIz^MdF{Dt>F92 z27fMF2@hYg(w>&UM!MFl7ZDiU0yUiWyqMAl_7+7 z(P;;%d?nBWf6jUQdr<7Lke9us{lXc*v1*k$C?*@!3goTh_TFcZJ1C}AGw3lRZe4F3 z%(qsbL%+Pk32^aGndK^{GzwW=doa^qe_$eLgro{vK09fUr)d#& zjc@VEe@8szI-h-$IiJ1i41M$&*teTFNBM9#hI~X77CdBrDQwemSsj$C25=Kw8#ubg z=d7(Nhi=WFG zZ?B|HfCQ#MAH1Z2pK-hal*yH@LVM3VV$MOsOYOqU5}55?gJa@v@{RB+ZjU^@-beGP zBATgvyeWiij9sE6m5hZ_yD3pi>n3C8%=gY~bC1Jvg%PHpkUFGS{=zC+bJ@j(D64T! zDD*443!1D*JVYr7#4i|N-dqR@FGY_YqaYq25a7KCpiT&B>u%S5rIp%Mr@)(h+g--k zL?2Sn5Mh#AnC87?XxLJ~i|ckA1O%}Vj2dG- zG8XB$7(KhkjrF`E;Dvz1{mv!k8FS0WTXTEz!Gpj`CpPwj& zNBb8O@g#9Dua6f$d+wR#EBfOgmwVDu#{pPm|O=~gH(9fApGFXE>34j+!5F-#(F+&9m6ybXRPLhm{nd2Xq4p2sC zF$GkY<2}%@+7Gga-yid;Ko>7!$&d73 zsiNvrVXHu6h5l$vHMvVd+ke?QcpF$al)9H(9WVB{kcUf7i6MS+P1Z=|2?yUgx^KA8 zug%_HFAw$<()oCKN$+fy=WOHV9Fa&F=bkc!IbjyJ%TkDpk-(&F?{oPkPS0c}epQ@H z)O|Y^Lm`I%KfmeRxM#3t-6k)`6es*M_m`|0VFc{J*FD%k+`DXKTTL2*6>6JhIPCY6R;&oS7CWZY_2y+|V$-|(gn|A#ijJ~U zj-$toW7cthiRLTM_FiX#`$$|?j*yi6G4OcYNjT` zuCm+lM5{ywEy9p21!n2KI*yKv8WRvxBqV)z{f{)o2smT4%G>-r!9QNscZ+X!s%I0@ z-3GWk!RS2Nw;_BaHc-G3ViXb8=icR~B+XQno9q)v&HbuT6>}@r#5*~)!Qs^*dihxj z*6R&iY@~hiz!6#SS4FJ+$c%DYaWje7F4z*90RkifdNZ0c;WF0{@65T}!a&?Afl(j1hq5SkQU=OuLe+#{4HJKt%eb&*eREA<_WTL#EnK zFHF>W=KkBD9m6?*y`GGd#q4pXY3G?i=g#A3p!`7^u52>PXOP#5CvMj~s%$k3=AH@U zCv3KGJHeZ?%3-y>{ESheSMC&ktDtOM#*jjv)@FIbpp)ep5pu5GG{giy3g^<9>ZZLa znrWRk_nePM`hvMiyr}>Ez*A$Wmx1apFdyByT~I%XLGy0 zt)RtbCc*^I!=gCs=q8VjMeDEXLWUW+G3Ei}dL0Ogg;}By)jMdQh`jAB+Eaph&sDG* zs;TA5Q@rt&Abzo2xth}V6qLOWHxZkq)XFe{CXOK;3;|w@pIC3LV?*OrgH;hL`Z*cl zrTpQxzz_)R=p`t$NQN9FxQxd4BX4FUr|5rDR(_E)TB5F1p$se(s!za-GTVM*O$ik4 z&YDiw}EwhQ`m#0-&^|C1dWBQbf#+?R0l_%C{>pP)E4V9N%2y z6VBO@InLqb#z?H*tdIL$#o4vE&X2#Ho!ub7Hi$7A#PVPA=QOsM8fwd7lNhdkb3iI7 z`g3CAyxwC!J(TqFDmE@>uCr^L7~lr95lrVJ@bU~(mA$$Px1!%nT<1M6Y;$$;^C)X;o7Muk?(* z-JZv*t}BBVtoP8|v_H28Z%uZZh#bkO-Q(M1n!Js_NB3@;GVReTo^))L>}i_kH9;18 ztadIAo$X(nbZi;y`PMYns4hq@Y}UZ6e>q$cUk>XGMjaY`h<%WIqYFgIZ=pO}e#mtM z=nO1gN4&Mav3pZ|f`0OTGJj(Gq~Cz22nu)sYR%X0=1UN_y^oAaTWoU?=3G$iqyC||%!hSKJFfSrh&iHG zJGLulBmPu!Ih>qGg%F1Y855-t!Ec-{ClhWxi&}hSeYXCUf84WZ(RKV0;he-fXv6pO z_C@*xy_G;T#_>8P5RGdQ5%vmJ z>n$bWAlfJV9~YVwY)&RlyFw!MAnqK0_i_?A`5Ca`)}3}C&;$}?A52y=*KJ`O&$|*c z+TsDbqS_M52!l;)iBzN&DF`no5W|{5fq~K|nuBbF}ZmJI=!_v-^2RZtxU`e*KaWih8aQ5aBzd~-as~uR0;|*WC z`BbC!*@K?;1Er|}ZrC0lXY%z98HLy&x7%?Xe$(7IO$jgg-Qe8{#Y3X!a_Ltt%@|^N z(4$iicU%*2|3%m%tCf$|Ls58H$hW!eCf&yiClN93cqntC;1C39KeXaNt#>qMqZ*uJ z6Xuj(C)LIL6=7TPHi~I-e?(6TCPz^Z%9Jb5BC%|OIgVW{>sEuo#1{szo1yOR4h^^x zFxE}Axp|32SrTG?%r3u%mkL}%=Fp^kGQavk9^wgHXFW{AjtX3|Z zNUoDOx&NfNJ3iLy^oHqLG4%z=i(@T{p9iW&MK~xDD77dj;;HcU#|-l4*QzMG;2abs7oFOtUTNtZA0}J6pb3 zk>YW8nEo`_673a*X{8^N!~kCEwk{?^{d;XU3^X==#Mo7yA+ZS+x)<}AGnSk&puG(3 zY|!yK8+v!YogJ;#sPb5URp#fq#X%5tR1rArq|Kh6*gggqPAd>>1iGzah4HGj#JiJ5FBLv zqlJK*DKak{kH;C7>!7oB$&e!g=Ik~xav33{EaEy&-s+y-d*-%ph2b#W`qI0j&|I-CbkRAH$)BEdI*tJtig*+)y&=9(XC*ELX%jcjSIaS+8wvTHQAFL!?TX!U;VG zUR0V#c~5s{YR!1*%%E;{{D_>^j!|96BGty!R7lKuRTPX;We(AR2h(F zVqbKup>iaQWiNdfg+0Qu;C`PwfLnb>yV76RKe=Ss9hBo$D!th;J#1!wZ;={m7lwxT z1ts!Eq`!nRvnoHP889Ncd=0Z<2C}{`34n8Yh9$2) zAhW=t?Tmo})^_AiipRj|7US+%keDF_!m!@D+N-QxMz7r$GCIy}UnSZ(yzTlatsI_s zf)_l-TrG0yf%kqoHPD79d|>V&@-&7#7q(ns(8lVAVfiPT#MB^QDXPrDGR&aV=IZCm zlXV@FrP(ixyF{_Mu(FBQwHEJU&t@;7Z!aI1S{zK-+ADO-qM}Iwb;HBZr9ZkNF&1 zVv4N7xxx9FWLQ~gQU|Y$5i*7}X-^qK-1U2tc*jO)SSIWg>4xiHvqiKymHw2_h~7U5q1>A!`pL0G&%#a5SlzQ?SGrmceWrxul^BiH%5wrB})86NVM+0$XT#WI+hTy8>ljt zU@5bZOm`mr+}a!sPA0p)VjvSkzBawbiGOT+cjuUimDV^=ZDxCz z<*mJ!0_B?u4nb1yADKPWB`EFND|giWXzV^-3s(Q=4B_rgBwJ;jl1sL}ex7|gai=HG z^dmT9;y_A@)-trqx1$mdHI2Aj6e& z9QhP~&b#`)Q9?YR*R{C@efJKw6^Z4=yYKb{Cy;AeM@h#6lZct*kCQwm>yP=Nk*f`o z1F5H~+ti?l;jum*y8DusVR{7jmPx0>I#6Rb9sRa5GX9YIa11`IKbS>tyRO3=pTgRJ z=S}O5;V=$oYPVow9}my(L$GMbvIls5h4W>KwC8`O+c-%$6{9*_UNk-CsmDz6w97^s zuZ3RYo5f6|3Qq2|jFS?VE<}&Rq_+=_rJ=!xt-+A&l`d zogCBq5W~rJ?yqMURa)(sg}vQTpYSwki}|IeEo4|b5=K$2`wMg1h;*ZK`^zQ)fHg1x zTKlSN?DP{~+nW%fce(CI#%(+6*%hxDXy(n*o+gCYjx^9P)>6Nl2Dd*Cxg_2t z&Ui+yVOtru!Qg}Une3V2hMG%AE_O3cATH|qWgO8N%LlObdniv|d-r?f>F&pf)?Sb++-0Pf9G}e-25$Eo>siR;0m&19KX7vU_8Hn6 zZ8LPy-1&C$rgKMU+vAzz+2u*#_V6pO5iG}sTT29C;sp$+WR|*dsdqj@eEN_vUQmxKy z_`za|_V^|1rNu|iv&3!40n51PINA6jaldmhF*4qb z6UCB?n6~BO8lFQ3#2eq-nqB_c*WaztcZv(9^dPWXH*jaX5x_qMQR_(u;G))+Gq{fW zxq@y33FOYo{izd##5&yvO?N!O&?|P^iz$9SF>7P_adz>%*=}J0_W(EI z&+DTEeXhGs0j@dUMcC5%6*HA|#UUUN(%f(*sE{Kdr~k|%m5aeCRze!2Ow1V=Lg3A& z>=Gm1OrL#Yuv`hp!RP*vZ4ew3riYqo)Cc_#FvLvV>@A8H3H~Uh(gS|1dWML{oKjC> zf(;rq+>P&wIPK74#GSan=DERce5vw?Cr}yqqj%`?6Icyx;3$VQhfl1*CV6jmA%{Tj zS$5U2JkhV6Lz(!O;TG!HGCYQep0gggzXTrkVfhMVCqAj~#;IJ3XPSzazc~iVCZTiO zEI!IyOR$2ym&*gibsur`sZIFrv|DY0KNx}=40t7(rvR4E??Sp=%hD9uPHl&>=nIcn zsI-@0e~?f#^zHOXsj4k>SVzl#lGfIUMzim-eM?aHokB^a4q1z#tW6r5%3f)KX-#KF zV1!EHxa|2sK^gNPW0>Sv7*r2tiT-t7$;&-O*8|n15_4zY-PJ?a22f_X}U)zN*q@X*VSsMhQ)a*w*Wd0ZGNNY56jj z$6M*S!h5v`_JLoqJ%@h1E{kImnRinYO(>nqsZUp=97P%-EbNcGo|+H+i~)g`MLOoH zq!96D+Ydbv!_Nif;=uBEnr%<}uR@wm0ORQI;UVt*5?-@9D;ZEu1xZ7b%2E}ZwNExe zQG=yCJT9-B3!hg_u~BzxE$EMK8Y%pqfaP0}npdaJu=&DKV*{34!_}ZBu;iqZWbu<2;2e23jEVBMZ8)-Oiufj(nLYY5*8Xe23V(=s1aDl*V*m~u~c}mOdtt%bH=-%sc%Qu3ZO7q9o2giE)U4WAbc1Z62;ECl2R6>6Bv9Penyl`pLDijjM|1;;|w3GMR z9KwP^k*Zo?<->9h(VT)(R5jy9{_M6fqr$%MBd{af7EY^TwwNTs7L zkov|BA_P_-{DA`}#!_@SU*N#zcztTAMnBC(aE?peSImcQuB^Ww@4J7E3m>@arI#_J zib<;MY_e7KxOsxolErm85_`nvO_UCU@Z9Bp|%NY#K>m_qhvwB$(>T= zY+qa3|I%oj$>SU)vKRaEJGBH@n__RE`$dNb*TG{Ewe7`R_jI{=kc8w<=iU;go4K06 zun#*?TYdS+U1^Ah4HrFHXS2bxf?6xdRE13!KRG@;;&3a%h-g#7O30hS`nH$v1_CaY zgJ1oUce}8T28@(MYM*);z3T?=nP|hH41XV^+G3QFj37Y8%J!yw09Jl!&bnAX<^Q`9R$?yTg(x>x0}jZ9;Q!>yfuA@6DPgwfQF z&L8khwR0n9ca%>vLmlK|$6E+}d^-Ompdf?$q?V%W1Clpo4yQmFjxeN7_O)Rd>!(1- z$%;V@Gl8Wdg(DDsqN@H*VFslZR6h^hhU9}_Mr`$T)}>Nb^$`8Or{)Q}t$c%xFO>d6 z72u;#AKOuYJv81i_Z{TekQd^WiUwFd00btchP~+I>g6*QJr23BE@y|=MG;i>HIsri! z&hzn`j44fZf*SXNF}kvj8QNx7<2Bx!aoIHf!Q++uEyH!?P30{`wGVs5uD}=@&WBt_VaPq!wbpuD@Bou`s+KIpMsl^n$-q|1j20Jx=QBwU=>kwnT4RRMe7nr)?pD-R+@l-CVW$uh&zT#1#HNwYB>E-YQij$n8An5x+==LBXha0TWWmX!uaWxW2 z`x}@5KSI(5){~MiER18E?M~m3FQwP<4|K3*2A;f(bcf?}k4f9PZrl4=WdGdMNg5dN z!)oKk{;A$%xMw2TOIvPQ5GTJxweoq4tm@mtN|fqY!PPWz*9>J$2H~f)fhRV82k`fKzbr1)Z5DB2K)Z-@cEJz-&_~Z-Yb3^ z*QCqgB|gS5eP!dpq|!5es4pPykl%b^m@p6x8wl(t}u(kBc|6| zOA1BKT51F8rS!%p0QnE0qJs6wt~%fH)WbgAA!aA^Hhzl^kK@ltAC;Frr)sO!w=p=P z12F*yg?0Lg;JweZ>sIfRTVu%Ak4MhaMz+^-F7f6fxXAiJc1spDZLd%HNa;aUuey_W zlgNzEx);wr4@B`@@F5<>27)x51f5#FP4R4mae7mqG!YTxqs7{nd#^g1DNCpVBXa7E zln2MY8-&3#rBfHmO;h82v0QI|P=g#~N1de4_~-_43ZB=>)KUiT)BsWxUhaTsJfW0y z{Xc#S$Gv=!rKOoE#pztScV($$CA&zigR|H8qC7S20>*eDBF&mZ8c}j$l;KCzi^~j3 zl`&y>`|M`tNe_T#TPjHP3!~ood)m{K>ybX8sl_E}3RNtXg@x6MLuC0!Ps3*Fy-a6L zGAf-N1h|wCL*`_m0^wF3Sb~VqU%Y5gZq)eL8(~BGXG))_+#6tdh^_PchFp8a^Lh9P zRF`BLS^Mvd4`rFZ=%;V@$cB`Hl|xSW?7=f7xaH|%fp)TZAGSP?I3<(?qf3R3U?o%> zj>?z%BMXNeiSkNuUs%kuMIE8`N)ztr)#X#Ofi~nggnQhhFAAb&3y*H^ItlgO)#pJk zec7L)cp_&|?i#1aKS|zyW#ng0!N~mdUtpT0$o%$f&ddS#dQjVxX=_aXM|uz4_E?kM zg-5ju%|1aB&IQA~Z?C)BDY(zH*6?&kd2d+5 zayw7Lyz-$t|DI_A9csh{^+tDw2+r&M+O2;nHNC;PvZ>=#B=#j}>?* zOAP0c#~Xn|g2T)J+6UTC;K;-y4$@-1%**0MI3h%cR&ZuuQtTxe6C8T@SZKM7^Y6Wn zB_LD)>>)H-@)@pK_|0lY=PEvn0*LYfrQIUzy=XF#k-8eYl4ovd6Ea3g(SZ2;6&dZH z?`cF6v03*KZolRo)*?gzodM=<3r|2xUOINUB?RgY*o->{+01 zXiHJ0g3%)E>@d6YyKA|=jV&d{Z-XrX@US_Hs-sw0U<-_#;F?ljYOB7A3ui5$)6W~8 zeetQq(7N0eFt%ax5Iv%!1bE%*ht06SeF%qww=Gl>sG?u17FAQHcXJm#Ime%*==UHZ z78DyKdl2E#Y@P-XcD;|A`l+4Ag+F9aeBYQLk_$#@O$im_KXVvqP5h61vkS?5dP40_fM-TR!$Bou7w zBZt!IJF{)_+K`vK*qOz`!NVSD0Iodzw)(!~=?Z|n*drV~pn7#MW&swIuf(W0`w+k< z9M{eVKqo{VM2)H*F&YW#{n%#jwf~BAjVCJoO!W*)}G0{TqFGJWigU7z^gWsB0 zB?G!e?nnTjwQY=+scGyL^#Qnx58DMI>udOG5naLa9`PF?{giuXt_GWe9tX4+;KPLS zE=*CSu$P#yO2Db~98RGX%F)5qGB~&inWs2C@_@Sqf)oFtw$8o%;gtT%gY8}G1m0H^Wi@M&|0-o-SoMF7Pn-a!@ehci_>LPyE;9-TL`3qK40GB zG&@E<7vb;=>{fpK6~7;-hr>^AK(RMzjb|GG0Dw?Ay0M&cr@3OS6}f8(%KN5TOkFGR zA%g2>;g$?wdQDUM_3IDIn+vsK*2m_Clj<@d4RZ=}GI3WwZ6bi(qR~#oh$SDS!a6TX zqtEtgl!DX&cPy_siA+KR-M8s8FDF38z?{|Q6#SXB(5%uTFXqXb~WbF^>Pa4hi0txd+_xI|W8;{K& zJAs^a6UO?(k^Xb>c<0F<7KSDSQPQ_NXV+L_|@$}4I1xRt1Zi54~Mq))#K zabqu^Z+-LXOmLf|j24z$QRkha1@b(<5&@k1YU6jYI5>J6yiIUYH5!L+QsOFII5@I} zO7*wsB01smli)DFxJxby06dDQcw}Axe1`0lIk^4Mqu0UqudYLQ)ac;) z)8J#fXRu+YF?UC4fV=OhgUntnTRk}tsTJ#YwC2OQ%3aB!V4Ip6Gr9B1ht4`5L!UV= zai&#)IJlWdLBI?=a`FpUj%4Y<<6S~qQ&3}F#Ibi;7pD-dNq2TaUKr)r<3kP-_r0Rs z!;lT>-y8q8dr*Iq6{~`e<2bQ60Y0!n(S`!%afM!c=@F(eK1#J}ubA4U>io zYRsYVoX5*hYQ^03Szh1UT-)FW29DVqo(ug+y~i8R7OJud9u5)B%GF@xuz zl@3+qv&k?N(@XE_QR*VNzyN^*A2G(z)nif{h(Vw3lr#j)9pHkX7sQ89qvKJnhvET_ zLPHW}(GbJd^BQ1cO6z4Gc**+EFpYyF6YF!j8C5V=F2+|G8=P*)r}KCUzQK4d1z@t9 zeZ6_-Gi+z~L*9_3x5pAZ4&72IMjnsY&LPd{iILWP@fdhxHu(j@H;@%w=LY;U4+Lr4 z6%5F#3-xSM-#qe0u$6JQl?QpF=cv?06Y&J^-M%)egDW2N^$3m{-P;%5qc%r>y68K2 z)Ik8~pgl5T*D4c65ddKBF{GA$M297EL`#Wox-PN;A`$k0Ty^Dq#7!a>6VgRolw2Q{ zKIo1b7C9C#qK|h&P4s|7E0|@GB$wlVwcgST76MDWU)*ZQ5?&P&%^=M?!1W4_;A! zctD-UEPq`8jL(Z>6iV2KhM4 zPF4|M2;B0!W+0e2?6hx=BqzwTkadrD=~gbkq%Hu`zO>c*+qqCBhBECG{fmAAI2z0X zy%KF-3BFgJ*Fw5~r1u>XkGWw(5zIN45fFON1`%J%Ex@RF#&(EAN1mp9b4_VqXQw)BqNRqyQ2q(3R=Tw6sAkHMSNJm&kT2qjY z%B^$TJ8`a;@6bZ1o?Y6~?ly$%3*uuWfT1!iT^s^xx#?YBup@Lj*&ky_o=l(mQo#re zHn&FSLg2L2=q=v|f5E^ggL5>BJt$^p>0#Jp(&W-%y`lAo1m;hEc`z8k4<=EW1Jf`I zd?rlykYq`h4|li4EK1+xcks3kv)l zxKkVBK#mq>fGJ$>&WLOFp~sohak?%~C>I-4ZXiL4nwYrpIk4pQRE6G#f{jdnFJNe7 z$W@QaG@h|A1qxgZE$kHUJ-3>$xU1(XW#+I)2xEoQFHkgHd`iPtREdRaY)@{C1YEIE z>v-X0?;8gC8I4_%rY%nWzd z!?u+{jL8Xc4Ox&)Tz!UY^E5qCgYcxI94%v^Q;m$)Z(s*O=MM8~238XigVD2K@z^4) zy5e8GE$+1zJfC$I<5_1kPl;+y(N75RUl&mXW z@;rHU7bER=Fl9qWoVTSVGiQnjS}bNo88LS4C(de9<6W=^9^ZcM;C|;u>u*?BePNeQ znn#BqlATnxx#)o?ei))8cS8z23m^+>=|RrwmU)5 zAzg3_QgJ~fOkNFKf*T)XA`KxIA57_L5ft+$H@pf|q-C@>P}&Z_9`3|}VYnHGjActi zYUafSXkr*?iF6!!&VaMM#!N6__zL!jVhB*W7S3LXLXH+)qtv4~as6?-Q?#)D7h~@L zUD>n#eRiCVZQHhO+v%iZ+qP}nwr$(CosN@9-+TY_yYH-b=ABii)~ToVQ?;vhopsJx zh0ix|F!3>j4?~RsNkoZi;}JE{=nxC1kX*V11~hJb#7Ko#75$K6nb)S}4EA!Qkx347}K_Fu- zKfH|FZ&WU}&bpG)VD@&A?_q0GJczGg+Zo&Q&iymgY@ouUtbg5Few>3L3B75>)^3Y8 zzywC>q)?{v+%!j{ro4AFc!uPrUDv-=wCt5-f1$O0@v|DKUU>Tq!j9bs3mau#iV93Z zD6Je0qpv1v(OxUOh4icqR#`WM0Mi?v3>Dct?->{pZX|YFIV9$SvfvRu`PET}QgLug+BeJI^P3 z7v}5C7qs>XvMkec`mnQz>x#mLm?_e^FCz^vme1mw6jh&q7Gsd@!(^15cy*%8{EC7b}Y zx3)jcYt4<`3t3B_!f&dVq-)j0I&nmu2ZS$@3@R@8apDk(M-s6L5eWf=@g9PV#w*9} zXU^drLY_BCsifDztU}x=K~PPrxcD=+M~>iwqg7M>rt5q_X`P5;TRxAuZhL|q z?A%N*oi-8!nCxe*wJlG|+Yp1A1rxBf!*ZQ&5`B&#!HaA#9hPNX*5h~j))x{P$!V-r zX5jAENY|HR3eU?L1;xJjl zyL!ArNx#5n^a+8xus?o7J4tlSr%;iK*U*c9PJwT8?r=)%A|1$m^oldw4zV73r>x#2 z-&940R00$)vr5PZTB=hYw)VwqeQvQ5R7<~8TdmRUjoJs%ATz2B~ z1aBFpl9C3KMJ_i>7}y>qU>|=XsXd))d;h7gsthF=AS(v7Hf_Cw;7$h@%DCJBmqf_ z-MtZHYbpQbSpRA+O*Td9s%+)kMclZG_8zXgbPzjfepb)B{Sus5!D&6$&mguR%cTs<5mM(_9_HMJXVLLNcWOH?Iq=v?=U6@mv=dyLw*TYRGxxCU@Rdvjw15bL9{3WRGS~q zX7gg?9n&JfWBu?->4|wsF02m8qUZ?%#ao-qjR7iU%2w*HF85#mG43m zN_)DcLx1h9$Oc6 zq_xDe?eZ>dtbZ$9haoBq_Kn#0tnAQ}B14PT70iiGvK?{^wyNzDpO?Y)y5&C3o>Qs9 zLA=ZU)eqxgOlNDm?!&EK)xNI@&k@fF&oR#++H#Lx?Y*wOt|8QZawlpK55qx3yCPbq zf$HF(XBRI(+ySur_#5O~@@KO#rmcb7>V_K@%6WK3&0U~S)rPfZi1b6VedyAA^X(RkDO7@1O>R7$VKxrh0zjV^Hu`;CQ8cy~y`wXVj71A9`9i#_~71) z*xJ@I!oXcVynuzIq}@{$V%o#X4X*(a{Rv8@o49e_^8IDnMm3x`=p+w`Wi`J`&kXK- zHGk+b1D~D6NUy3xTP;hWMLRrRxFi5qv<6P5k?qbXrj?->WG*5jm(1?`K4K|vbtM}U z4K@xY4(I7fW2d$^2GDfoc)uJ{kj|rfwMSZfRB-4(Uc28uQQNxj?|0Bb<8CIC%T&`EEoIm_cH{9}JuBRv1k{oId^uVdmPhLfXuvBH zjCk2CMH>g~W>x86L^h0*FHy+=)LehY<%pi%L?7;C!VvF!p4&EuiOd-^eJA6KlGYIV zvim)2p~s_&K{S9>y!PxK86V54<>NpW(DwTu94Ykkx*g<(^G*YJAQ9{?JKK6oYt;12 zfK_iR}* z(LU_b`E&8;e28=V5r_f+=X4^C=nDVUF)!)kjV#KwXlvjzjCBd2e1=fi?o*W937h{r zkFR&m4Jre){b4&5^;`%Nc*v9Y{8Zw%bEiagOGo4-w0Xg$C? z_F#AuXUrDtgS0;B+!0+@HMjhfeGf@e<^|64Mt&&qC>74eo6VK*EA*avn%}FKp-bq~ zJf^GeUD&yW&*Yet5c;SIEL_1Tm6M;d?j&RsZOm|GP9dPJ0KBvRc?Ph1+#gz|xUY;Z zaIL$HCO6%SJ4%!;KJD(w$(WG*twfl^IsOdmysG=vQs{#EU!-Nm45y$x&Oh9joB(^r zxznbxr}aeMr7YhnKB74W7Yn8qf8S`K8x>)M06S)R? z%?cT=a}L@)`!$VIwKB1dUer}D$@V8X<_5C&=xX!D@G!9EiG$o>h!HOaUA0upRemUM zaj`L+A$iHjaGF9}A*Pe9EQf)XlAFGIt&NJCkgy`JPJgu_Wp1_b{=R>FykfUJiMW!6 zTv9y^D;+gEF@>&~h{tu;FKuri?|ZgteQ$0iZ!oawc@Ul5UXrn{-mHEf(w@<-UZOJf zwmjKL)Yv$%FuhJ1k}ys+aUz0}in_dxxKb+tBfY(bs*Pf^fsTG1Nn1Guy)BQxVkssOj}SQ~p$Q;(81oT0#xynG;%2Aa>M3WOpgM(AgFEkrCtHsUIX*?+d4%F{y{1y`!2CS@dKrZjeN zP#E1#FeplEm6iaTHA*bf=pRd>5}#;mbt$bJ zOH)gUN6cpK=4xnSp`|i6bX2pmGSX7=k{B3kXc_2uA3J!c*%)Xwm4}pO4PH8!8XMPQ zVs-a=sGAFDORJb@ofWPZRGg>WC$vjiPckxGL#PNXJbg)Ym89G=D>_W1hSpYU$*FTv z9^FV-3}v@{sZT06q|HcetJ?G*WRh+S_<{(0rZqOY?g#$va!iD=Y*# ztT#Iv9w=HQUQjt!6O`<~Ly)V^&7B1q9Y@vd-^;Ja%~f8lFG5yBG+w{!lT>8rGZVbu zpR1QdJQ_YoN1w5J^~bM9 zcoDKsfx*a#xN>SVt*OO8K8&1_q%#l6HK}?cY+N(RIE|B%m63yKG66Z$Tstc>Nii$I zQX%g z)6>Yo(NyBp!(8VotbkY?dG_8MVm>J-3AtJaqnTpTKw^|4Q_-SKJr-R>Q6+|(y4=Hc zccP*26eN)m6~!odS;M{`Wk|CgqEb@&mflrTLSffTtnQ}ML=4G zr6dY+a&!_xI}4M?TbN&9EABnxByd%Iw05u_qCTu1(a1P3X)6O!H7!FiC8^#_*+|Vp z!>G4!ar_8XvwjY;4~4`qE$>)mKv-5%mKM5qlFIVgB8m$OF<1jJ28=)la$n5#gDqx z!OEzKT8|z>QrP8Wa?rNEEIgl}PjOsocQy5=aQ%Gp7M5aDS&@m?d*1t49Y{Fiy$Th7 zHs41vYCv(a;ql_c1ZA|kd`bxKm~;xJib>s~A@KzBAqq_`iAeH+2Bjq>L%pQxfU(kK zl4RWaFbiB-9S=@GT2;oo*pRS~>vVOWrB`Y}Z2rSnQiGulqZhNd=?%h*+I%7Y#>{=HxcKX3OaXEc%#g#(G zUw6=A`w(&MQ9K#2tx${<2bU$0%UmXrb4_mf)dM$lzIG(-E zuWBFTI(hG0Zg(i#O_%AK8+CN@x?N)qQwx)F^1c?XA4A*1vreVBowlJm>wIm~^43w5 zSpKqK=RRb&uJHP^!(Fs}YDwPd++nBNH-ygJ{a(Fo;Yoj%^~LfzeZ_uk?7`7bmho11 z^>uzVk)L07#pboWp^iW@ZcrB!n3^IkfIt$H@>5bQKxi!QXP`is8Xp0L7|5*9;3M3@ zzz>DoKmxx*BEH2Hdm=ea3lr=F@(__w7B!_az+PrNvX&t9?(XY|67Jy7#eH^5og>EX zr}n4KkIkp8PG_%bi_PFo>hkn9tCBRW%w5{`C6}Vr2bJ|5y+cb`PbROyfvRDtQS0l^ z;ly}}<_Ic|^L1qJos|>qdN+Y&*}6?5?v}leeD})r;zTJ%2HX@3m4B%sru_F zY5%lpF56QeMmyZsj{W*FY3RwQz1n<>!**2MmAB%tR?VnPuNmGZr&rABW$panWMvC& z?oKPw>yC@_^`?&ZgW*!-Nidkol==?mw9ftMa=@s!qy-t%`c2%P-xIs1d~4!idRv;!3Jt>Dfdn7U+3)N*u%c1F{UDiCxw5 zUa5w9d`}s$WS~ueOJ#1r+++yqR9mRc;Q6xoQ|5bg+fRbhTo!QebfGX2YM#3J91%zx zU4yRK46lLNCuIUfB2tCGw}jS=rFsw&m?UGMr2#JNNpxaagl{9&qtzp{Bh%s?eK4QX zadcCVFN$}FcTBEf?IiMw^WQ7FaP$RiRPhrb2?)JHgB0VBJ67+cd^pq>TWL+^IHPPQt z%rpph8~a9rR4Sol=Spt-gxIa>%K*KDIcDipNto+GYb^`j;ad6EYTe`_e=IBBYuaH8 zs!1+y$8;NIn4h$1c!GSv&cNbq;a3w}8)sG(WFsHgaaEZ#aydY_S{5Dg)RE6QrP-8y zQ*Y+)p6UXUXNMV<(oL9_2wBPq$tDXO)XV0F%0dIPB%|lk3fn ztWvymr*}XK&hDL8-QeuQM-J_0KDT9RNo@^jZHK+0CWAV#{I)d^bcq%X6X{PGm9F?m zKea<_!z%ThHIrgFl4012v2}>-Y8oKEn&bvp(0w?Lcw#q1szud+W}|ql-LCpa zOQVZO&sRr)UPs>*dnKrSmdCdAm2(;z3O;lKm4lCS2ylAhGBtB^P*vTS)po)rSQ=TkY18O5~Mj?QD(=8!p6>a z2tvFO0ch6Lcp(|0naKEb$bnQ0KX9;VL3c1_;k^_SKgI9E6M zQ|`GP$yeIi`*_rvWNG5Vve=D~<>>I_@C1zTy)i=+nA_M5XcJ&q`~n%Xu*f2snSJz>61`|s#4c{^Pf2d!n5uq| zQ48(V$RDT$%=dIvtBrcw&9%=*RxsFX4h)ZZviG`ykm}4kMs77-FUL8P{8Mhi+g0pf z|KjHKqsaI1xT_s>!lOcGC}Sm&AsLVc&>JPFPU8PqA<*Aqi2Xj3gFO`aZ zt6tcA+(u5Vz~}>GOB*Jn){RiX3zvF9DIG5*ehGcwR=Qd318|2YkPO4A&*OXelb>vV zGNs56K|XgCEQnSsXb8yzOJ#=;sHb}Z=JfixU4dd{HUE(Hs}fixqw&~|_nYK9&V=0V zQ=x9Jt}t!qO@5SVtG+V~nVYX_-f6sCsDnJ3YvoIOMokbp{$4ZQsv|NxAA%Oq;@`oE zcN97udsRywSK=L~a?D%VDwzEEvUJ`j$$j#+isuOJn~1~*oMLgclu=_5jEWpl5j(X} zJ~AYuW)aN7jjfDHjx100SRKH)Uf@KTQg7JlR5AR(Za_xFv0NGBLJgsNxn^=gK+##W*lX&@2 zBD+h1DS5d2m~A*2Rn2Bj6rd{G(Dkj!8^xw{%!}&rzR@r5UXfn=cIndf3cC78GW3_T z`oHRf{ENW(mp{rt&q&AmKOENoM%w;wF|0~-#Aezz5f{Wf8nD40*(HQ zAEHM*YVwUS z{g?I4ZDswg@vr?|hVI`!e{27@&%bTD@0$K^@Bftir;Y!l{$1{$*8Mw0_svZGTl>G> zA=tkA@c(T6-+ukQ_usz#>)Lnv{}}$4C-t|~f3uhWH6;Ik@w5M%0sa?(_U}mj1;73W zLCelek4MeK_6@sbVq*R#-ZFe^!u-E6Xj#8$um3P;8NaQ67__Y4G~oX*XxZ8RfzUF4 ze`NoaEr!R&{9ia)CZ=zm?LRo$zt8EvakT%|UHLB@?f)p_{8gR#9~|x9;Z*n^^Sc8q z3~b+b{y*VpJ2{;_l!ccV?a$9Uj}|*R;7>dH{cV#j-&%F~_sRzMLrO$Pc#SFBfHB6_nc)xBC z(eOmXtZ{ly#a+Ewss!{U8!<_zrCEq(+E8TykjAlHfebgG+oNu#4ou$gJj`XdDz>dx zf&pZ+IL~EnUW?)a;IvrIZ4@0m8p8I_TYh$|qdM*rU@cGSt}J+RSAo6ih@wrQAaVd}-*FvD5#FnrDjw(|rp-g8p9I8U6A#&bj%;)#Gb0|LM@Or~burjrAp> zi)GDu;XQ&mY%}dY+OJQ$@mk?+^=kCB;8Ex~a>T}Nv!V-e`I{)RyM^e4_D<*KSY)37 zlxv-HAUpQU-5X;AJQ-vsS8w#-$%XaxjW2#$6Z;a#2H|>mT^@AHi;Zi<8?bCgQXg>J4|CD)_Y+<;Ar~<(X{uL5Lpa>3;KtN6mz9LVZ zDa=itvP@VWY43Sw7lPLt0hbTCCkaSYNatYh*_3TGYe1HqG@FB@jsQN^B+}Uvv@blC zISLkwc@9G<>o5@mcUTr%Jj+euuD)T20$N1iT#hdk9OWlQz}l^+Ely<%7eBEcUXyKf-vKzGtcaK$o@hmq4Ns<<_uLW+h?! zn>KZ3^m{Udgw7CyEhq;@_OZCRRj@y%=JUDQ&MB|37{=_|KZg=}b8w3J4#MmlFgAmm z@>vG*JLRHtf0|Ibp-=m@a^qkNU+d$J0c?)vv0?b>3~Fmz=b4@?+k6l_0ImhV;8Slf zqORsR0>L;_gJ}7^8Z?xh|4ayynBhJ_q6jRu;=|T{Ym4GL7h}S>6b0M)RJ94g(x=vz zb=Kx1zyO%m0-?5cf<849G)f4hn6+VRhv1IxpLnT49|;}vX~Q-lT?_Q`?;3R8&DUmZ zOKaacdBqZ14COLG@<`s#f3`1*>?}4HU1rs0uptOy*r`OE6?vd^@xt_w^*5^=s=p=Z zfVU<-zyr0q7>9KVH{lNY}^cKyCh*clRxTH9HwJzZI&rNP1 zl`cW=GT&(jcy&OyXM=_9>A$smr`rnHCO|h}DkXJ};T%<+pflpC4{#0d%;cV^JZ`$f zczLUe*FJ9B;)gj9Zq5lb0eQFrc>rw-p!p4&b=a$?6-0Rp{M@v2dBC<67#+X+%;e>N zF`T_ed*l2Ju^W=KB1WPv#1aQ|0CI=H7{5Be)#owhG5u#BygB?W4i*x3EdJ2(&RpA2 zJKOmKoI*v2A1zga32HNpgx~r&U*{xwCcJoO9W>twG*g(Ca+|gW%rOVo7ZNK%;-VEY(Z!wZiNPDog4fS=0%DOKty4&@HUR8JuV>RV1I%GCc_a-w|# z`3PdX7G-H@sSaq?&55QRx~qM)^Fr^BV^zZWF!cVA4fO_x6*ps`d%SzHZm;zY?EUtw zH%KF!Pzq^9@T@Dk!5>zIcDT)5U)wm+A0wv z5Jky5K8!5U?jNR`K}q?J6D|$q=blEqZm>j#FkE#YmwJ@3$?Jgm_NZe(sdC4N?AEbU8>yB0cJN?1T8*;YAHc zmIS|gD(43Axd$uYmM!4QopF?a`P&HQtg+`)%tVobmaUto88@iNR*X&c4HN$g=HLvc zfca^9;=exYBR#O#t3R_Ty-v-#rsoTn~;esjiav35vOcm4TrSdp$Ch zwhH5r=iaC&sCXSIX>uo|kww32MwiK*kWM$(R4%xTH?IIIru;nT(G>*Di44aK2K45zz`)AbX!_;j{) zZ^GCHi|Y;pi0+Wj1aD>)Cnc|g2zVfACa)B@QHC6Vr?(hDkkuHF8))t42o$2#aUT$A zV{=5C#85;Tku9RJGPX+VMi_jVh0i%@6UJMQSnuPIT+X9=%@U#@_V$*Gk-`%?kHtIA ztO&=5t-yT&8BtULV+M*d{QH9blJu zb^m=a=8jLeAxwDEi&c;t#TG-rU&2SgSq1#Y8zK`ATB+X zC&ZnSj4|mRVORBEQmG?1ukeqT)XLQ}^%c zum$*$kD&nz^5d2J-Zh|xJSc|(W`Atkw>)EP+8A5sG^y>{jCzOk7xD)8dwQV+k5|dN z0R@ly9x;sVc71tcT{!~7n(Z&#eVo|i0|4Qe!ByC!339oyO&r0bvO4pG8@}n z`{IRJ-t5`+{mSb1ubPDxf&n!HBgewI!`-`?$?o6P;|=d;)y{tag@FZ2v(Cf9x&0d6 zjb*iQS?E5#nOr^rB@hK_WTnKyx&JP(@?GFHdvG_%JYlP6*Ot#7=&kMuO$J^K9GC6{hv4l=TK)%kQH1hAyzaEzq^rd>zw2s=N6ldVKnmu#hhNww>xuQvKO=Miyb>^xI{N8?05;t5E}%Gr1X5zaI>7lg zlG(ZWJXd zQ(?rq6(1a@kX`|CKPIx60t9W9bzVQ@ZXY6q!h_4G=<57_{VQz?1`$H3Tv$$z6(b~< zA}3=R=t6zXFEO3hfI7rGV6Bc_ZmfacZk~us-i@t>_c_3qkMQ&ZStJaRec6#;bs*2U zF$-kLy;d--Y9oEhI6t#W@~u06y+a(rT#iiF16%gaK7*-CH_dcF20bI~qB!7OMT((h z^p>#a;K~+0$wJGRO2lQH7-4z}TnlKHTu!o13o-;pbuK&tobNUf08PY##Qla2HW$*2 z^}R>>$zlJKaauj^cF`?z(m2D~nTSJ9SQLcocMn1-s>H0Y%?h@BU~7o>bwqDS+HW@D zfV9})G(q!lJxJfa!aoBsp@Du!*>uzi(-LB`oEIede15(r0}JKN>?SlUj|90&`gI%^ zfe{TBdn?FyxQ4ES6JbVL3vF*x#ZFcemF{WluZQ?A$}jm}abI_<;#y9n(92q%ccNT( z2sH8AvAmx)kCYA8Xmv0l9sS(EamXA*du%ib4OEmS>Uxa93ylHe~;Z3RSqqMK&(E)I80|;z7bGDtKvub{D zbU18IctKxeM<4ZZGZ>d*Hc{*I{`q|MdoNq+C-Qsm~7C&h{!ux)F>H=4mrVC~1FMo@5P#oVF8N@B@bjTZfuTWM(_>Fn!egsq!*Iak4vu)ay{upfz|zLvgAng+ThIn6QDH!lx4y!1Lg`|F87QLsgPHynPJZaY z46h0T_#v<&j3h_E46vhsv7aD+>gflH`S9D~?ETAdezRj+aV$mta;?HVCR?n4l8WmC zTrwi=U1%`r>(FX@xwRbDz)(HDN|B@?ar#3&g2Qu9#iAR_xpwfyve&vk=21La@tU8iBLOg*6lk0A(uvJD5aq~VGNKFVm zL1|<+g!ESpVOBUWR2N#*%AEelZ(oc|#1zB#p;NZFYN43? zr0bUWHN`oB-uj|s$f*%wUMdeit?T{Vs<<6j(9XKe#`PS#fBrVY9@Kc5rX9z9)Qt+R z=&&BV61L>L-p6@6E}M1TKj0nBY&IC~YP-pMN0|y{sy+hFa(mhTYCCVTUvH|GUaRd5 z>uC1D#vn$v$3P{YeV9!;13eXqr@t_;laiyI$6m}_q!$WweB~MGDQge{lT5jP&<{P! z*-|oBS^+kDkfhkbyTiN1V?jeQCTzOhp^;-YX+nB}L8)zB)Ln|6{Bx91-qvCzc`RIY zI16w$J5Smy{Q_>?pZ;~Xz~}%2bK#cF>}!?3@60!5Yn!Syp)SU4U}SUU0&>3SU7(_;m9S%V@HS5|FRo`xlukzf&y(~pPp z$bbq;<#Z#-S3)RUqFFl&KOkc3bbXdMEiwix?fzly-5Mf!UD9!C^|FCG74Ij=>0N8~ zwkGYeQKYc#?y^%UNbh$A=F14V7Iv@E(HlzCSV{vTnh~vmm>pA;M2NZk8F&9~T{z*cFEoV2T~i)m&#i z0BTd9*4Vb5y`;op$KE;^I>G0+P!kn~O*NW}Zwt1{T9d;IXg|54LrWC+b437ymwyLA zt1X_@piil@(?DS$nloYLE7WrZGXpb*JOk55VGY(sLVD-ITlQU1A_^AFhk zylH->u9A_X;t8gM;0<&NO*SLvLgRtkN>RVb`8a>T4|Jnw9DE2cox% z!$F7Jyaufu&%$=s0JdUqB!@txWV*OFo*o*ZZxyxjb(JSTWd=`=6PDJ<#Yz9qNl;CJjo^xJz*=Y4L;;~!Qv zuA9oVDNgXpL==2~dYpu6Hj$cyU3?MMeBncSZq4%5d}^^F64e!bKqxCd$>J%2+}6>8 zs^+X?WBIHTY0@eHeXBZW7rbY47@BweyGJ>73G!{OvZNo^58V+g-z;Zcp`W7421zpP z4JnOXuR&fWtz|}ok>7rFajpY+=EPpokxSpyRs`MlDzr*GlrrZfnKT05GK!~;RT>Y_ z*_}SvRhXo;M>+!!%%>guOzzXQCrFOC{Z zd^7aK?7-lWfa<*h6AF|dCM^_Llm_9&Y-b)zUrb}efwcZCNlzS0FV(&6)gLkDVl(q)Pmm#gkF~Yc@0MeKTV~| zlS@tN-2mGK!lFhGiklBzexBAYXb1%Kvgrm8(zRQvL)W{VpJys(;)<|UCznqHu?X2U zq@!ogMBtOU9I;D&M|gIX`j|ETMkbX?sT$)f_duDH-a%7oKVZPPE!Uoy%?GqU|8G$= zfI%#OfgisYP*D{ag^)u^V^Y`M)82@d#60M)!#2dPp7e8?2aZllP9ok{9MDw z$bk=P;v|p9f0~j{2ey`|kuE?w+nA?TN?|4Wb)zt~r*2a1wxpy~t(Cu$?*6h1&j@o( z{}r{b*Bu@fgVrA~iFd%o3}X}aTQ4-Rss^G%;sCtd2z^XkCu8!ThoJ|WCJ=*Ylsr%2&(8lyCm*BohFc;=7EuAfLp4*W`_Kg9?L zc+pH0>PY!YoJ#^#9OBRK-^(A%?y;(fmzkKO$Jz6Ie5Z_@Xs;8w9;1HXf*w?)3|0W~ zbVNU0R=OD>7M^8=0Hpcgq38?5PDa-JIHzL6GYRn^@1Iywf)j$#Z@ALr&66rRZGXCm ztoY`)pezHm;|+!EU&aZBGMdEj{}PNzlP{;I?OV^iM2~VbFa6k{DODaRoOP01fd&+@ z)K(x@P7q84Id3s~QU3)fg+k}7v_<#s^q%VBcs3uf>pB1c@6{&x4{&nRW{4^Jgy zxsPYUg~b@n6e8rwg()W5SsLbg$0fIOsB;BM$`GFT*^(hQpv5$^*c+qo4b~d>>dl)u zfPtp8^{~{PPUvob2+^<&H*Bc8ws(M6 zcN@bxpY12ZI1#hd4Zl4b8tnolEQM-c*YNsyjR!V*s;9+Rg#;1A>U+x9urRRKDS3;g znKhj(aP}4O^9pwJCd!|`6%-Ygp)c)s45y{1pPv3UT;WMAfP^E-(16uaBQ9ol1agD%Fi+3C_5=hvQIc7g1|&2qp&ie8a@yu z2#pbQN(t_Ojt6m_yudo_G4zps(s)lL8$6mApdp#|AM%c{#p=F zPZ;^x^#nq%56eB!Idowb)2M?fVQ3_|$_VWgOF>Ji3_W}$*>L{a0MWVZ@@|`*8=M6D z{^Qqt2~3gtu^surPM%h1tUO`gBYoLL#HN*UV51c&jHWis@qVu~Yl$Elp<&G!KfXTk zcH)Bns0SLNt#6o`($na zFL2Bhg%ipHs22U4V9_T@W!Rlz`q-Pvlok4}_&137(+emo>hTtRA`2rl6#3~Cp!A`e z9eDc+GC)?^dSrt}uFdU&gW zKc_3h{O zMo%5^ZI8}I_{tEC5Hdv~bEfP#>^MrMf7uc3U#i(!Yf|)8(b2E~$IgS%1aSWfM6#wh zllB|AbOgq4^37Y<&6zLY98D-%>F836PE^Xc4C2z}9bxU=pp)+hug;;zDri0hIFh%u zhFqe>ax(8f+KKRMjlUP&&Hu1iYfs)%MNzsw{Jbq!oD9d-tDH`VMK+zNDR=8`vY0PL z)YQ<$O=h-v@@IjqUUs!B-e=cOVsw8m!AH;cYVWMFGS?3$P1I8{e;JEWVm(i7O!u@ji;|Kk5L`A$%5~oPw8KT0+!3pRYg|k%=L;?V7_!gTQ}=L=V^t@{VMc zN{-nU53^&)UUEp5x539$^Rb(&J??y|)8>S0g`K$kR7y$#GsQ`u`+0@vaX$E@<8?U5 z>Lu#-bO%kcHU7aOT{^s)+}-<|f9b4ks@^Jw8MfjvpjJhrPS|6hb9mauO@F6?rE~RH zy@bXnMN#|hugUre_IJ%At+BT~urlY5>tGrVnjofQspAQQjuDV~sP&7j1_d3s3;t?R zIrq!7nwr7-Vf%^utYGMMXg%0t1#=L@1NTn(DQxL+_&gd_qE{yy=ihPsp^#xX-kiBY zaT0u~>n_rcH%S+#_QgyP1Be1oS4}3du~Sm zoX<9=Ovgg5a`8%X^?Va`Gt-qzm@qVgn_1giBojh0<8Z!{rg62LKKUuU!Ax3j4N>Z|;;WSUv<(vS_oDRXx(P%4M!Q;Srzr^`g-{PK z|7e!HVf1L-&p_e!@#Aq?-p9(%6q>cCtK~v)#SX`p`8#B)j2`9g&%=A>-Nux@>SbSA3=QW8GHocOEP#hwy(SbD zbyZ12Ke7{7e?f;6?4S~~z*2={jQrH9*`PkNX4V4*#3gtbH*6hjT0WU&L?fy*G>3r% z7*iIHl}wqZZOI%-yFR-AtFZHqr}F*(ct(`UAu_{}tgLgK;T%G;lN~ZMkL?&oX2_PE z>{&ul_AEQ2%&a6Ckz^m665snYK7Gpf_x)WD|6K3;TJLL|$NTblzU~`UXvH7pD(^F| zH|4*o(VkNfZXDAU-mWI8%4224egB;sLyhb-hGHM=8;|16?^bAqC$>?yqGcZLiT<3cnSJwwgGhgF z!F$%U>8oz+IuuDF`@tE!`5e|ISvOeVt(l8dn`QRHu0dNzK9#ac`{MISq_=vjAr}{t zM6f~kBp#g?o8cKJ*-&Muaap7ZqyDH9*O@oJ7%zJQ!(~KnYVxqtIGy_?Wx&;=hWfsj zF1)|sfRr%xy*tLYj9e~jZ%u63ek-);TWa$)w04-+styyWY0Z`>B893b;D;}CK<0c}63OS-ei&^UJu^_8ij-)>6`=23t=Kj6O znA~wL7LMXnjDogwDb1Ot2%49c1?$0S?#}COT@$j71XUnSFIvcz% zvxHMJXdAT2eRo1*Xg_DZ0Ucd~82fvtIGmWUpPCcBDr}HNq5#OnU&knxtQk*H_(o{6 z`4l2k(2#m}Q2jxIe;P@z`AY4y-`;jhr+aIl_)=Wu`_bz4_$tK)B5Opdpmd<72$QXe z8@er^aGr0CYGWYK;qEzgt_KU9cPd43QEn_~eUHOj=yxGao6^?;2_5HV++FStq+<;Bo7^?o~tJ zd$sNH5UF$Od+7{?@5EefCq6H27cDe=elhKvDekv8d+r-+GO|n*xfn%%!O{o+%59d^ z`y_}hQRL>Lz>xLis~pTpgPP5nQ`49Yfk!M{L*~`|)TqO8jlWm_8LFBXQlM3OkKCo9V%>$)3v7@KkL*iVcxrq$Puj@t5z zXFp_*tAr*pWy^SkK%Jx%-@cZ;{%rR{{t6o}v2T^*N*Ot&jNPti=8z=#nd$ogkn{9M zHzZfS5!+@fI~wE z3aE=TU9z&%{RbYGNUQc&FjX<URm>XSbuCC*D}jCPu~rX^^$r<5lLZZ77w;cE0a(m zs`XQ;;f+GE&KFj7ufE2?1G48;pEX>?OgEt?EG&Av@UIT0IPPXMrY7|U)&dJu>i+GWWV%6{(qZZoByR6J%lpC4W zIH<4ZN?NsA_|dc1GSjtaXODLIa#eQ@aZ7ER34JidE9p;@)JhK_iaO168w<^I1t4zz z0kRJp6|?&Vmr`gVlJNo884d7lN9oSwmaNIY4T1G`xTti7vwJnfCp*n3BdZGd7@s?4 z##}2_8Wfz(KG4P)@Oe=Pf6Z)UBpGWudQkE}ztYjcsGcH(zeUJ*!ZYHl%sy?v#FfpM zwK*IAgR|cXREg3^5hQOimJ6RhD-*0K>N(}4=_jW$ycDgp9MwrqUd6B}$BDm@bz#O= zHQ+TBE^e*2AQq3!PyHaNV)pv_wP>bEw#(bRLT$w^AU*`^c#y;VjT<6cxn0k4(cQ}7 z7?osFfmhm|ub7X(4R+|VXqd{6u=?@)Is366nI`&lgrDR(sF-9D+~{(oh}fGHFK~$) zB6VVt=p``^IRi0-)tItT*l+WQ*bz$Ni{$tVjq*n(h;hUL|ErO~p>MY(vTR*Xo~@&f z-faAEP$goZTDP~b(mQvX&kI!KRbQHo7fp-8Z*J3XHL@q-q`lNZwbkU~&&espw6WC< zSWvAmsJ4{cXo#d}`S$QeqpjDZtGMI*af68)Z?TRf5)a8Go{&q_l1t>1`?!F-aUk!j zptLJnn;Tb`Zu70LJzGr~&%T8Ld8>fD9YA}PtUI-=JA14<{;WIAtUF8Mcv*3Lt2q7> z>rSTUq&)AwT0^0 zYJ8d=_NG|7A58AQp>P6b4KTOYuv!k*W>|9zurLAK1}y(V!2#m;9~2y5p#MdJBOrhB z%>O3We^I^YU+vl9ES!OM?M!eMG8W(a0(jt`JiI%RVN8?53ow<;igzn(oHXecBfHk) zbGxsR`Ej7e;>sACOSazl3Hs2uE8>f{lRY5(l5Q*MZpU}x{pX-fpKCb{ny-+VG`{k9 zQ*NBD`1P?3=1uJC$?eg*j>~%tm#&aCHo!{HznjEkUih^?xD_kw?BoC9+k2gy8)kb= zjJJrJ?h%KZ)h|o8tBP~r?_`Lk-b$?0%-ug-C2;PeT(T8w{MF)W8T**>%os)Xd$k6% z(%1uCF-U}0sr@~E4jDe1{W;ol?^Uf=Ph@J8$D{@HC{WQwTCG%_0j@qo4sgfQ|7D2@ z)AF7C7l!@f{)GvPad?4$FV~OdQ!%jz)>`$ib^XqQ!+(_ciGo7`h+aS#jRq685f~*b z@_&=y5P;tPO@aee{zZZ#e<9!6!0?2wD_B@tTHz?*K;uGEH!Z)*0>B6n;eX@b5Q1QU z0Hp))wuLYlAj=7R>No!V-SErPpBn`R{a)xN4GsmvP)LG1*8h9k)Fpc1t__`OYj9b4 zujmI+JmS&%GJ^fwd1@;DwYyo0Oo74pm>!-Wyuz^r1@J{B-X{1Nf1Y~@8YvoC33~JW z)Vy*w?7D;gM+5H+Nfh7HlhMEO^kPa*%!b%RSBGA4!hx#?_qN;i{+7q0S5M7$2ESf) zH7$$UDS8r&R@bAzs75j)&mO%}9)|VNXp%H)i+Gm{rat{lUy@*058W=%;tZmw7T30z z6m47Ub3g5Jmq>uelA%$F74WQB;`D5H=9y^njO>-7q!RvdNtFSR1Ty;p+^Bx!OZ*9? zX(t-Yrc(TR0bT3V3mOkY7qj=`MAAb|+B;euQWVay6z9ET+{2(>1H{{L4QuZGEalhWUJnUX}6d zQxudbl(}V0dLwVtP8&6I@tY5Pn;H@|<@jVqv23eJywj$9ML2h2@D>Hvc$RU)90eP( z?y1~c5Z{^i%O2VK={D2%j~1?m32OJ>G-swxusWmPvM_~M)m)`1(cLR@*Qz~dL?;x+ z7Jfi2dHO)Wi1vWfi0a^#zS}Bjgl&qXD>wu+qdVH_F|raq+tLue66Qf9r!=scM^bJWc5YRdkrVQ(%P;-&fbwQ1|P5 zkGvyK%V+dp{964{ zT-HE1F-6N@kJv5FYZdjr@2P>!XbqRRQJ%&v#hI-~A@uRKv_i%5Aa!e@Ne}+}mWaf1 zK+=wFk~8qE%*!<6UmD9_hpp(pwtXb#*#gpR2)Vn(?LNPWX&Q zLYPu3=d*>@G++IOJ3^`6l{e0;UmLg}NSCEi)^I8IO1<;qqJB50y~Fw{!*UjeL(tl# z>`r)5zDf;Bp8t$x*g&iGlupazDGv9f8V`4wj0!^;^N?1daLtyGmRD2fy9Z@PTBqDg z6!z|-RL=6zRqn?p`=~F`E4&(j?fWf$ZS6BHT*lm6{Mr&bb~Ei+tl@5(e?CI_c>`w$Hmd-X)u2&kyumV)78v zsSS_W0JA&$wa|6@kHu2qbh&w3(ItC_d%Tn@O=s~UB1?9 z(15S$=i05Sj_TZ!R-06AElBG#eB{_GHgJ0FwH;md*_A1NoenBXt~X}6Wpw0@9gDD) zr0p)5SyIYm+fUWJ8;eC9NT9XG=QL%z&lc|a{(HwP-BdIUNjiTb3YevS9$Re-V^z(U*lFanA;ec9x+w#kH z5(cDlDy2(&Keie}whKzSzwg(O_O0jRu{VWQhMTAfjrZ8CnImVMniEV}=-V&xe>z{= zd0Pp~*unCS5oN^g(5Z~~k{E`*q|B8`?}CrY$-cHIN2Fwoyw=zjHPXD zo!%yXl6^4#R9yrHo$u^IebsF$Lywq+zi1+hi^-(NA{)*}Pd$WqO=iZA82T7dimZ&7 zF;5CnHdu9O#*z)_jr!GY=qxT8Bim$a-UQI3;D`|J8 zgv>^LV^EE%XokL24nL=%V>y~e+jC5|U}3(0-kr^2q!ruR?Sj+3T4j+>2HqdfvE|Dc)AB*(0h^6xqw2uYwX^ps z?6%@Pdhtgy{2XeQyz!|ry{q>RN(S1=&doeE!?G~HMkDT}FkU$ozw7w4L;3m5LJOD6 zS-aCg`}M#{ROQat!ml5VUZuIi5qGDIOQ0wT?aR7Pj)TFY4~J&o1Cj5c85D~66`KJn zyC1O`560F)(9s;j`_B`C?vYTO$KJ$DRTHdj;p}3KbpV1cK`2}h0XE>d>}qXi4u+!S zpfF(rUa-2Wi8Ias4xVIhM=Jk zVPQB50o8**xPialC4b!=cz&CH#g+PC!(XE&1Y5rXuxr*hI}3v1^Lya0=8QFWH3LF* zAk_bEkao5(!C`^?PXX!oJm8@W5XggJKa_n!%2;zkp5j+t$-)D8k)OE>81_@uCncqJ zRrI&@$GzisMCk5pfdRCVFhE-RPXZ$m2%tR-_=gRFgh7EZ5)#7Qdp08{^W9|#ys_-}uKas+|xAO0d> zD1tKiPa6_~I@B)`3OQ6435c{0)fGN8_Xyy^bZE>-VUfdq2&4bCzBp$S;IiaQK~ThM zT6+RV3lP6*V6iwr2>at8Dmq}WV8X%G01GL~fc3!_O&~D96_hF56ah8En44LciPA0Z(+qP|UV%rl=j6L(d-#&Z)IA@);?$xNex~sZ> zblqL6FERyDaXKb?78tVOwvWNWn;ZYb?03*QO$O?v+7r-E6YG>|Z0bu(pQUWlD zTiUpoI{mF}3|&k`O^xkMOac7-FwQPcriQjK9>CW*o3S<%j=49NRFm#UBdk>`6_r4m z{$f+CU_(d)4chfdypIZ>OG5qt*XPW0MSHCJR2_V_W!el} z^75BXTplFc{JC?NOHR6lvE2Ond8txGs$)+TmOnG?(i98jWz)(mW9^lX9dfaUUbk>( z9+oU4;^bXCa@A9MP?_!)F!A_!)KY2~C|4Lumenn$r4T{*# z@yr<-{+&C=1WLE-(#yD)-u9LwC*Rg#|C@D2ezmo2shMdDfc!r1;?+reXX(l;FTa^= zUDixXlg&-& zaD8uJy_fCDbOVDtWp~k|b!v$XS|x^_!VEo++dk}^nWZYd)Fv@kNCT%;HK|8*_*Sm**h9@#-?R$bs?W#uYNtH`I z01XzEOVe?VK_YgPLd|l}O)tAv_Pz-9$oqAsZc(UDf|yIrjuOx;JLV^d|KV01g86H> z;1?LmH;Gl@a6(lCU<`73ct0ak5S+J`JaQv6(;~{(S5Ov@blBYr1pT%>6Dl^0a<-J5 zwY#AQu_8jG5?X!u;>D3|A@mvB>VWZ==vBbc7UVC{!)3%u=psYZid$YQVmDxZZ&BHN z^d~Ejp1b`z=PKyr!JJG%D&A^xoPwEJ@=;Pk6;z9mo`0fR zaw8Wd=fASEof>i(?{NqjHbw2*@J!CFD(J^i^5Z&N5Z|G!q;KzWOW_5&2hX*2I zr4-ZzvY`k`IuH8meD15u9Ml5)6jY&{DR>EEZsR~qoAvIgKL&-pyz52R@B@N(hh`+%lY*|_m3MIG@ju$ z=tPc4d#RV<;Fs3wJLdr5;ODGeVZeod*BapIYLHOXo!Z@!sH$r;V1K}U z5f7yFD?lxi*9PR8oN}v}Jb>lKZ&8;+Rs0N~>S~9G26{R>*dS^Ji%X|y6c+BCFN)8M zARr>;Zw0k z>ZW(KVZ!|j_-s-14f<(NQ92>^Wz{TARKonsHQbqiL4#7&ARYYIJ6w~XgR$VB?>>XV z(r_A7Rbqq_j-^I}-?UQMStv=oA6Fk#;hImPG&^988ux?{%@biY!5EizLXT(cSG^5ACPj-t` zU>XN&w_&(x5yr|O#_qr;3NDxi;>z&#@zKT*b~YQdOfJI|WW75kHp1UL=ioA)gI7jg zkn{LT_5OA?W4K4_Cd;@pKRgWV_2?zf$*Yk9A1oQd4WP@}M-VD6$VBcUVHb}OjF5KD z6US(wilqnF=rNJSppBd1e_hedhxAi-qBuJMc9rxy=f1Z?yga5pxO zhmm^-x2Nt6xPTqlIh~4WqZE}*;kSbrF7H7f-N5%PAIFY9i7P7^yzL|h*W(xgN7-#+ zZ!!ni(oR&#^mAw@CbnrL=C=;n{JJ$^Z?xaG0ka>IUB`{MOsf%<`GKXYMr*?5Z@nJ; zhM@!MU^__gq$aetg3=&qNIKR>;K%pjTNuso_JLB43N-5y{JD1Np@me!>+8q*li=pj zVO)Jj&i5JIRO*Ll)ekNP?3k)ScrOXJC5t=0?h1xHsyxPNZNwr{&vBRqk=|#5VffXl zNa}E==)`nE-Y*9{KGA_^<0p^!#vJJaElMUz*wY;sQ0gyl-Y26nh3D4W1ZlPB4wg(|SOJ9c&3VV^E`B?5jNC z;8x8zb=ew3a9(M}US>nLfkpcsqPppdaNlq5iiEI3d8fG6Y;;Br{n^f!{e;?(dJ6b2 z4`+fpQB3WlX7|8eCLvB>|73r)X4}7IK)LzZ7tTCDQR@Hv zmK#$uQ84^D@Gze?vlTofs5~@OyH~7vf)%H#a34pZ@+eesG0{wgxRK$ATRTH!L5t0N z=;G`U!Fl-NT>IR%Jhn#96L+23F_t#Mfs)loTXQy4RdEd3xqO(LfYa42k#WodwA@gW z#rS}I=8?ToKRDWaMn%eGrrZSh37=6S%j^|*MLL2qfxQUismlQY{cJPDMgv!)Wh=%a z8Ca>R&~9maJkfRsxKRM8QDf@N31oFd?iV#N`-h0?6>(a%w|P!zGTTnIgn)Wh=3~d#QVfcnY6zs zLJE0N%5ZgAtc=PlcS9@ow@N^uHTpNJKXi~R(9*uF6qCIYzHu&j&W#FWC#i!o9f0P| zbs0GRtMLNMq(*M1miuk*w<=`h0ehN`!Q;XEKRaHi?#vJ$lXTy;4?RI7sZ;x($$ zxIQT6R?ihp1%2~Yby-May3)i*ie06d>*((##7e;sn~!%-i58jYytlM~|Qj$vbkP)3+10<%LpBNmZFj zquhlVb=9$gcfI(pr`&WSs!(A_XL#=~ydT*~Xm9U09&E!Zo$Bb@>YcAG=F=b8XCsl^W zlP0KnavX_%b`jT98k6z3i*&Hcnp&XU(@C4=x6?TxJHohFc-8- z=q#T|8Swxsts)u=@Fp|qz^b9qAh1?nhEYaDf4ok=X*0T+91XQ%J*85hX0T9eLgTBQ zL`$399-Y`w_SR4%Zvk5H*Z~K+(xO%bOsWg;%K>#=pu*7M9%3AW{CEqRGpMAddAdc3 zy8R;HT~|0p(C+JO)C298^w1`5ph=bfV=~a|Y}-G84>nEbB&lZv8B+L$?1D_)5Q9M| zn*wnw9S2>ktwaMj<`W}_XPrtpu@w?DCWfj)PZKm0fylyrrHK>rL@?xG{6y(va<%DW z=m^#toxG&~q!X6GWkb!%<-5E;;-pYcC&^8@h+HQn>t#xi(RGFHPYA4;ugc{2Re_uH zHTiWSTNsMhnq%d_JOLvc=3v;$@v&@c(4nw1M)fo+5<%FT-kIhc-=KaC!w zWM+(m)P;wu1_YuT7)bCndOd-Jhy2Tn6UQ}i*l1?vrljUR44LCSjEsi4gyNraA zUFup8VD;7(YNierTKqde( zDsm;SlBX!mNlSf?A48PWUl1$pD=5_$lIfjxE9(3oFDoqUDW%uwt^JdV` zJ!i03nI>3_McVi~5OIFy@P^%93Z_Vg4@*eH&_pI0-jamRh!oGJfxkh6RO@7#gXCmn zzCd7KfcPY&+tLFqJl91$TuP%-$jG89_C%@nkyq z6OB>PL0dJlX?^ub(<;eEkHuM5fJK>7?6j0TALIasdbAA?b+ToXPs_U8h;rSVQA{Im z!+Z-e=VDP=ir?!@MJMO)jC)=WdXFEIcP)h2NT+R23LCQiW@F@+vJ$o-hyKV;ov^CN z6U`>Ix1YSn4o}J@T1Pr1R|+stD_HE)}V7$n{^EG=pAAH73|fHh3z%=@vGgtk7ZSWdY6qm?MCuLKK{o20bBHOSCsDcYVVBjY#N3@imsU4JmMx1iwt?9w@NXead~tnKa7v;luHD zhZtF;mm^5`9v{vyZAet*s|Bw#NEkkWJ&3fe42IgcM5Qv&CiRj@-*bCh>MbA_;%K6qY8ilU!k0M)P9A&_# z?M_BDnyyM~qG$N8QXJ7{qF3|F)RG7Z2VCM|(o>qOjBjR!sB7q3|2 z0h|+Fw=mL~IDFB8>0-r{VuO_cb- zKjKnQSz#JG1d>vXEoGx^$#Y{8@OBB}YC!$;|Na2F89-3g%DDhuM~qz=VH$((vhjyK zwIB=Y8b&fO*lE;(hsm_Hk^~M$ysQ>HvS!Ad$suR_i|A@BdCjc7w51deU0d0Y zDrWQqlg(~+3G5#>zjUM&mqL~2wcd?epT?}N=U#0|Pxkq+% z_!Q{hJLylFajT^M!fedwooBFHFtuHm33E4L>Dj5NC-F|7HuGGexxfEoQ@U`&k^PO* zNcIQqTaEUEJ%}Sd$(e}LXZ241<68gw`0mE@=8uq2UY);NSw#mGZ#lu@NoxHRNvMX&(!AMwPhVF#w+AbqT2 z6xb_>VO4O)cw$`Bz+dG{0QwXt%&BlO46uGv+oKgz&tGRF2wyKDLaHd|iYD{ixX?FKTW{9SRGS@^5Cqat!g!e&a^MzdxgwHzC`b^bPaYCHqxE zX$p4(x;*=&t$&zNn41<2Hx(w7{8;wnaF<|XElHqf3mqd@ttaLNF24N{cEuBkAOi5cUzKJB z#@DO=5hf135Y_HN*(v2s(=}lrrXpod0ZYrs1Yz#@AXBDL9$2PknfDQ z%&CH}vG5zO5+zQ?B!wDSQ+c>pkT> zbtMqQ`yXLyq-At7^dsH$Wy%2+a2&yAjI3mNW7l-0H&*I;of5Db6=Jv&1haC{45`q;)bAb#|g!eIXVBC&{;&O!uI6bWGe@rk=|n z1=Q&(O!w+ctg9#tduEfdD^GWjuY^*q)IZx+7>Qebkx&R;)db?KV%+@VJDF6I9PLu- z_3T%1V$?4M9iO5UZi}@PBgLHbR&m&6ectt~o69BL9@uIIYH;c-VhoU!p&ffU-+jca zqcyEu+_j3pd08(xtl;}=kngZy^?>8fj`6jM#MPx*8^94QVlcoa227AhN3*0_HE$zV zEWqw%tkZ)|)tALM^p|nyz))-roCK_^1Kq7+n7VUTB%?}+0V_=^`{Dj)>l<5^@ZH>n z^=@>!2q%U$itkzpR)468y+o~n9LCmr055SC@VGm2)>!s@wQTdq`FLOvx)NtEzr&hC z;p?s8FJC~licHmdG_AXdq$XWM5NN3R^*V*K$Zmj-EjSYCEgDdXO1a|=$wIZGX{k^P zY1H#n^lB(ae{_Z!`bvfB2C6-<6VWJ03N#g0O6w?5<1`9-EfLuC>N1MvhU$V;aO)ZA zjRCObvjeRgK$=(W)LlLY8qAEsQaDvzuM{BCAS*>r8?%;(qB_RbO)bWm&v3wvMKe^8 z%{a7=BCmJRBDE>d&D8Nn#rJwtA~$K!{~n@?_oX(ulPY`KB}$BzZg$~WoVrEvu(jIs zv@xPU>CpsoNzGf@DFApkD+z29>WK0wBMjtLUn*>1zF}+hp0(ugUjGJN*9yeh%Fc(x zkdceth%9AvHGPdXnsMPu>}U$LM1~Z5V#9783IcWw@}tWBpc^ca;mKEava)j5O-UhGCu?QQY0aFK8k5QpFJU_haxFPHvS2|4 zT7$D$X7L4>g|Qe9!#H+Vu+;2x)l728qq=wta2u6E8bM|~k={LBPjpBmPIK8JC57Z{ zPJ89M7jPZ4D&B*;Ob+HZ;ywUAF3i)qO7;jqk=QjkCeEYeBmL2abA$g-kbN#RN)#jG zqNM1Gw2S!id|jc?+K*YI$-jVZywAx-6yM2(7%MI<@-Yc_NN-Po5f~{!Rxgl;9S0v$ z{JQ@q7yA~S(>D0w1X!cBO;)5ZtCL5Q$}dCU2F>J+k>4+-m9R+*DU!#l@zf#ncD^w> zQR+8TFbsn}p^I=s^ER2lY6`u_2wt6y{SkZ_W{eLmr(#&;3-uI_TvW#B@o8%u(CmsPTejJ=`aJ;hk0^SC&F67}LCH~xThPnEEx_>)=Ifd1BH zisoi4CtOj^`BVi^-;vhv%phU65TlxO@A8hdU!AN|pJxu#a!dmCTzE`4u&;&BqeClF zNnrQv04nFfa&gP!ilE0eDwVOQxvmwf6u?5XsO+=Ed6w&^^4P@ky?^Cc&67!aEgPgQ zu&u!$VqJF&YLdBmuGKwhWX60oP0L>pvIjEHbCwHOnPi@X`D-`d-vE|F= zA64VZyIC15c)*q<#+wCY_7Nc?MwEtg)O}Y|38Lj1nG*Y^F;pcs{Y~8Qb^#pMOn6ap zT=ILO^;2S2OuA=d7U$$f-;bTC4#^g-@3}xLWz6(4sD5bCLlAq5Y`7N4*>3Zw>Oq3M zmy)(1T|h?MHqm3!)=O*PSF1@ipg265y;#2u}Xfv zz*L;iCS`v!k3fI^$5Ax-w_j!bhp;HfJ5ojt62@37GGuZ(OCj(@xX!bfUPuscOy&2t zss+@b+3fa~ISrkL!pT>Ew!5%yAO?RkA;2M{wg_Fe6fwVK;*n?|t3{yLJMG-x&z)KK z6yJ^5$Im?}GO5aDZst*p{f()BOAmpzr#yy%o1;vBaCqAiyw8+Zs_e3!FvU!@=*@du1ghCvO8At zv(CA_i3~qFUBt_z1Uo%ec#(VFr-W6RK?mGu@L_G;_k`GA<#UdkJ{V4 zXz;-wU1@v{bjIX@?NJJOXmYyOd60Vp+1!z1JG3|=H)Pi7f(P}2cj3Oz&ECGWC~Lun zF%qckiFNp?$$~4Xup1zv?^UVoDHcbtbc>rxQ?;`MQPf^Xnaa@4*Y?&7w2sLa4f&)# zIUyS0uy@Hk$33dyb*G70bWahOW89F_3VAXG5s~#ny&_*w&cgkEJ8a_q_ARi${!I%_ z+%n-jYE9;0GumUA(#5-aYmzdw?)B3*1!ZmGK`bqU*il>(q{>@yob-rGt%E+aFlEZQ z0liW2=Lfuw@UWH&fX+R_qqlFW@@;WOfkwZgn%WNs8VW3LJ#|v8zARG4YkM+7IL}y5 zx>j5*g(J@V0Osr{RdqxwhF?7N7vk7ekyEJ+RElbfj|u!GC{L)Svv0v$cw)LZ?FBAdX^N}2D9g1yc3 zRG8#E@^sjM(k(8;PB@p57b4^jInRANwi1A;0{NAVpI(DcWmaD#bE6x%PFar7Eqs~J zBB=nQ$;h2ozDWadrwXap$K79YPGxq;gwpcCBw8T3Y-L`E5r}7)OXYOPq!l;z*1lXz z$~0hq7Pr=UmtON}+wye!#%?Fr#TAwJ`v7@q6ZO~VzeMl4*2N({ZE(=tGFlTP{j`=r zb(+%jhM11NB$HRp@$tls()5!~9d57Q-13`nTfQCN$dzWDz6_Ic-)wFN&1}~p)7tVm z(XavUwNt;|Gy?Bok8w32=9lyCTMUT_uEik; zQrEs{B?2i}a<>ERpF!LdgIv%mhU|!*g4dp-$o;;+y{W6m#3fsvYKQb_^Av+72cmA5 zX%h*3Hen@BH9N;3rXpm8VQK@Ex`D2Yc&e&_j4v-OeiQmnb57yI`tL2e`RE+{l z+sAQal~7|>R>j#LNwNJ7jC-6;oLU1CjX!$`;UOso{CEcj)oBhih2X0Oh8esA2q%>^ z#D{`FIHhI>tm6R#S6aBg&G~C52hB};OonvynF?LIn%Xw7xZ8*~@965B4UuTHpz-i~ zDt*;fY{e)U+M!e%1H32V%Yv!0>wVaP;6F11E)3KIahxwP4-J8B1=b;@o1eS5vD!GI zmd>@)KO}$^DFN1a-0EXbl!dAO^=iU!un@qkZe89f8F0@u5jr2R)1u zYRo$Vo>2W{gjeruPt?Y!qte-XA~LMkInGj>MpqcZTPnlta-@5*Kq1$|3&ijh&mp$$ zrbo<8^BRY?eZUzCwab*=0-)&Quc05u(^PPwb!IGVI8}g+ibOra6fKjn1d(0MLOlcQ z)JLka8w@&OU1*#X=H#e{gXg=1CN>nhok9;`DW!hUoIRN|P_z^tIRx1K8G^4Ngiliaz((&f`UQipz(#SI1&$2hfSa3WbV#qSVek>;x(+(hC51OP(Gwqr zYU^`U@2_U71@Qyn+^CqOC#wa&&Hz4bGz#Za-e+zhD71=CcIs=bQkll0#hOAKY9$%y zSk!xsL)G4fNN%tuD_1Ze4dr8Y>QLeQtW6;D{*;DkC~h*I z=4xk1Ox8=&FhWFdb2Biwxr0uIs%xYT`#_hSssUs2v~|$X2D-rSGnI^-Pu`MMfx&1d z)a-^$)Rf2&y(#fXt^s#!Rl@Vs1he(jtb+b36=#Xaso(x=3gX~okeNW5KdAtw@ezJVTx+G0gxOzyu55Ynh^5^jPcaczIZi!ytjq5d+lIt0yp3RF9ez;S13MADP z4Hp-CeLiN;TU(8?l2K&0n#pX|GE=O^;QW0=v({OPi(T$i5)ow3v#}E}w_994nGO-F z?t4^U+7Kv!5#jR3SjF{Brrf_^t+A`+{yPyGdCCrqojf@O<{gfl)$-hJHW&I>&b7_$ zEY+-p+8??kn4`_DUfz+&Q^eQqkc*iG=|p!^BmRCqMK5_l4JX zKHW{tzHQ*q{4qzLPNSt^*)aydQP%>>MA>d)DaGIo%sdc|hE($`Ot1=CF80kj@J+xL z$x58Q-#9^`$sk_6SqbH|@yt+l5XL#a*2(Q_{FuRscTp`X)&uhjcZ3KVN;CYMD z{jBNWo}p;>CC- z6V5jMyhDJ?wiAZ{C1&tt@$%#vLJmg@Fcin*-ifU{)wYJy3W5(ENvtUXtO)GJJ^k6~ zn`KjRaQFlo_lP|?tSJc@$9p{0;QWc#`9)k`B9~XEASY4^yt*KsmXStvN zmR3Bl!I@jrp@;&G4jiC=VcFRW{6%g#eT4W{{A{rBv*}G7QBQ#{+WbbyDGmt{lXC^@ zs^fVNe0j)YmOw+2Rno-)D~=1&Z}#MnNqg!8T?Eo{l*PRgdJ!jXoj2EXgVV#*J&R5u?H?AZqYoli{Tq+BbI`F{(+I~noKRRz z@JS>B&{*S_sSi&|5zph4{R8G~vqT}IcK5Q4zJb>FNyne&mg)))yah}$LSASS>xXMg z17EMrQKr1GB9`+k!it9ehL1unEJWogq8ZF@^<`IEuGl`*$lN;OdD65XC=GBmvGLE1Z#KLj3@9$++?IbTL>(^b-!!<% z3ZVF?tLmi18Hal9_Vf!8DoKF2bLyB}1w+HlhK)$C^4Wz~CSMmV>aV8|R00J57(&MG zQ^o4J0nAPBpgQr(V>y!5)&rPAnnCHL^ghQy`i+`m@(IDQh|>pHk%_Q;&b=xGUs+8d zDubstL^1_Jk~z7ejltbh=$yb)jX3jieSt$%f?=n5i9OiRP+SIq*&NxOT*O3silD zC`Sq$o!Qbz$Z6_H?Fbr;2)IHT@)`^jxL9`@Mw1KDqm~7e6U|*l!gBqz@pW>cM1dfT~YlfZSE)vZcoZ(f@!PkY2 z+*)c;wg5gXG?JS^)5YZ|FJ5X{@-4F-IFG5{4;4BGjvg!N^6FdxK9yUIJXTmd(>fRG zw}oCDIo_V(40`&LgaE!6vFIvSy}(9hUQ#bw7~#vj50Qf=S%xz7c3VZaAnIOy;VrmC zoLv7Y8}o5-J9Svcg$Z2i5$(UIOM{!x+~^GvwsZ_L9q1FNtf;_$@2$cMkNXnxX(~#*sLIQEgIS*lU&=2?(s`5RHozTO=|GIY!X{e-@FARl5u|9#|K+90rGorSZy++mcBo2+8%C z9x0#G`1_5Vb(3LNMrMo$YI9TTp8RXIu5xq-!HA~=4|>czECDVxjUc;7`Wb`uP=|P1QGKhv83t!m&dr{RE36Xq%vz{OsNh^K6OUL@e0i(F;D2p?G00 ziNs=cq!8~D@WnqRIMMrI7vI;+0gq{ewP4#R3wz2zXV0PhBsOHOn5G>HC*#U{4Am3Z zs|c+IZPm9$?jvnr?ZFDn9%CE2Kzw8X2NJl~2DaV?q#JWZfPs~D$fW z=%7YVK=c^w)jG$Vg1DV|ArNj!Qb&pPAK;%=8xArhl(n!g#@ii9y|UN&A=nGZXYG2N(=ujJKABQO>q2U~-VKoR>XzvD~7_FB;BX3d;choZ^8yus$kaasKcH&NTHa zDJ|^7oZ=MPN7t^YLatD)b1aiJHtba70!^p0*uv*qS0#rcOYj%5!RFQxC4BtLOHtdV zjiu(2ZVW}91Rhcj3oM?-3|*uK;004RMI)i~;G&+8~Fg2x|nnv0Z`yLTLKO@4m!oYFsZ+Y#cZUVq%D(!WrSartv}x z9?%6mT-0wK2<2bm)P>IJAW=a>Hr7le4S76a9X!AIvJ}gx;J1i6P-YFyc(ARnba2x} zD|TW=k`bERZRy1mq%SiSU6T8 znCpkU3%CKu&-Y5Mw{-a3VKdUM3S&y1((ZfSjy^Kxyj=P$5**A4+B*noCu#OgC_{_e zBO@LqvL-UY>^~77`4IjJ!}elqRGwt|kXgrL@1;?`eZH$ilhu5}9S z?nnS{F8oVW9%!zbX%H$D4IJB)JR>u@#gIrB#(C88|GghAdjQG&EL_7jA`R+ul< zN9;|m&zi%}m@nQ;*Q@HB=gtywLOmja{sLAlpr)e`{aC*X0z3#X6xGI`iiAPlZ-Gx( zFIb0FdDRj13OupqprB0X5DX;#E zb+Z1krk^hL{(ZAgcX(%>g4G>R7MK}dJK25L3t3rBdvojAXto)o>)yN)&VJK%mwMKf zJgp2p5zvbwpm%ux4PtkH(q3q!p1J%AvTsB{#~6YkcCvvO=AAHc!bShIPlu%si9p|W zVxB*s?zsvrLZa^FC_C$i7AMaEBu&Ovh|H8PJuLRVAWBzBxH~;H)#r)rYv+6ee`ESR z=*NB+9gyVSz8~7_O;`Jo)dpdY{IS*Wc9V1E+8xn<4C$+4h=(yNpFV%7t;>#px!f@> znCIv}?~40)7WjJk?tQKE`#9|LexB=+7ZSXAi}oeV)us)R53-AYaeU7Ce(L+Wjoba4 zy7`{xzn`xA`6uXh2$nY_lCYsX0~2(dTZfuVd?b(ODDtJoN$FN_;g8-us6(`7(09*Dwj= zB|P`JEBHFRF$l+J_j8GKJ!hLa3%s9mx+XLqQ-f9*1xWIztNmwSS9Id*7DxBgN?b zQO@f82@SaFy^M1X(A4du4%)KaTQg4`Hg^Pe2rDk3zv%{&{=#h-(DY67<#KJxDlMDZ zcIVGQe59dM-!2}nqi{|SP9HnH54hcS1rJhD`Yp>5_F+vaGyeh z@MKNI&&g+jbsp-Hxc`R)S(H{PqvP`ZFgl-Smf^z_BHI7G9O>HkF>eTpWskXy=u({m zDq+81+vm9HF~AqXM7i01P*_-F&VBdQMVzt;E5w0B>OBctXqNT~pOTRAyAx&g9ZcLJ zhuHkjCjZ}+Mk{QCa5bVmt9|fb4GcOh-DTZ9pNIFkbFIV2kT&Mzp1Yi%jAq25)AHv^U@wnRUhjg#QGO$n*J${l=_C<(0FRPHlHIJ8B|9iw(d@p&x;X*CR z@zV^T)&}*x&z3!4Jr7V3)aJbtQ6ME7G8FLJIU@_Hv}VRuJAm(9vuM~rAl=Cs8WdN$ zzZqgw*-5REsekHe^=+Sc&Kg?i*eL+VaXxtQzLR||6ZZ8P*Xe)xt-ad7!I;{a{0~p_ zZ|fhu^B<@4U(LkI!OHbd{jbCPe{nxmema-}7!(Z6|5G}d+PMH&{>uYZGIh3hbuu<} z2C)BEAYyOl@>lN+_{SanOB9tgHL)}lw)X&NGyWBDa4`eenV5B9{&GeC$IicT|Lpza zm?}8g8!MZ-0JQ%$Ma2OODyAMT09^osh`o)yld^-Mu_@pmOvIT9!115y`S}41VjeCM z$}WFtsQ=MPI5WdA{qy~=ZHd1)rvEzn4=DcEwf|sLRG0vq|AnZiumG6;dG-(f7tQp) zr~N+;{%5xT?cslS;{TXrkXMieF#V&x{?Bs$WAFbHtt<;*q-SLQzw!Ss99yRUA=%3P z-DL)$e?(imf6HSKHFdKzHdT@k{{QFS=A^o-D6eCL&Gm5f%%czk$R2S#p#h6LlIUQH z5mNpNAfdtJZld7gXvkD*CMx~F5@E!~VrZ~Ifkvy)_ect(1B#+z$J^1?&^I+~4?CHk zW173`r){h2<~Kg8oj?j7fnb9!8o>Un1sZ6-F9&o`P^X5UL9md35j24N_sz_}Bwj>8 zetq=tWn`2~jy660ruR4L+NAAMAa`E*_Ddk<5Fv#Cf)QJ0=k+DWJO)WtZW_U6{sx9DOOJOIIY`-WPtUxE7Y|p&N z8`88#MJf~M_?dEP=_OkRh!HJAfBKZXz$SuO3=R8t#61WQRPr!aw-Z9tE0;wskVmQc zQ6yM|lu;@2YP#j|*|^!;U6b;w5fe@FknDcAhs@k#Gh8eqrhlD%su(btrfr5r!gUSa z^|j{8iN$N*`YwU5@+aT8=ez11`PE#mP;{>5uFX|7Lk|Yf6RB1fep7FXDp0d6gy8Xh zwfqeL=pG!Xc_;gUAk;=Largj^0ygUE%ElQu&zhd*jN?5o(0;Nnli4@EPbsEA z0ErYji>cUgX<6wH(dlV8gtR%6&u66X!+tKynTa9V?7V)=yO1+g#j|AS;0TMZ5Z(Zd zczP3lBi}5GMFdqW=JdnuYn~-%MGO(6x9N5(Co-r zF?7Rf25|=3^=S>DYlc@mcnD+t*avtHzU^2#%yw+GU~P!2(Ov$RL-70LcOKo;J7_n7 zhy%{IM&3ldFn)M`1iNvBqkRf2isMf z#6$swWJ+>0d1*W`;dMDK=?=l4f|HWuUZe?h-ZuP!QUllV~Hs_u@m!r@6ee@A_QQsNi z+5TqrXXt|OA_*rGrxynsM-?ZHb(9S|(=Kx&^EmUAb*$M!3$_JJ>safwMUOEhlS3ynfbs60PfAMw|UyX5jlZJVbT+=M7ZX&%lhfteNo3gvG{0{~V2K_q4n*x5t zyqdh?K8ZeUzsdf2z=lDTP}V?sL1aOnVXk4(zA;H>a}^Yr1yrj-7P0Vs&iWw%xHhwr$&XI<{?gY}>Z=rSJQFzWr_;`)Adv zs#!H^j5V)wV$2a~#ih9oCEeD^`bk*x0}~RaGUm3Syy`V|^>UGg9QHo0VUK**^k+&K z?r^p6Ou#xohw7Y4k@}PhPn}#HOwF?X>sCPDN`IQUmVxI`klC(5-9+K~K|@6e^`=wT zxhH3uR`oidO{Q(~0si5~E6FQ81b47Ya0mS3l7kajTY%?0;_1+5Imwx8v$Bhqi!&&-zOayBf16nJ@XWAicqBj);4CsCIv_kR zDlP0ToGdJvtVX3?wQ3ZjSMoTsE*ZRgwgbI;LBpt-RCl&w*RWqQ zI$0T`)1z)nfs2KQv-$lq6uGx#U#jv>r^R_6bTPgy_%-fukn%9{TIaie|4BTv)T<~QKRfX@?(excYA4j zR--s0w`TDQA3bWPZAKKIR`lCBxJF>)U zai^Q=o~qC5V-Er69lsxbzdCO@K{~IkAGhABrRu9|FHco&X;tix-Q?XgwW*$Us_1Fh z>LQp%8%EbN6xVi0RGEp+7o8NG_+mz<9dw+yH=Sp$46QD9ZCZNI0!4xhK=9zAV7Ge@ zKgyX`@LLY(t!v#*Di(SV~iUx}Q9_o#DoadZdWG!Y*VCjvF8?4#2 z9kPDkx)*duE<2WE%x`%DWg}p}-WhtryUc>+T6PWdEIlTD&wgl}`Wf~!cVTTIw6TE2 z)LqJb^VnxL6K4X4nm7H^<1XSMHLdQCvE*dz1ZqY)d$zOJjlf{wb$BRRFo&uGPiy_& zOlDb)>$-BYX zZXPMLEJao+Z^irk*Q?Ye9d~Cri@K9_A;!@`&4RR_iO*HCePEL%lawO$A}691qLUHN z5$kR>cLP_W5y`W=fnDSujgN`bW!YZNuN}tvBmGzA)2FGt5*x*x>@N!smWPH%d$Z1_ zmxV=P8)com55DiYuLgHRvBzh!PqK;Gk-W|xP;WObB$mGpHXj3SU;lS3_(z8Rg92ZY z{XhElukQX^_a)KA1qB84?2QcZ>HpRGTK{SDS91T)68JAV*#F;P;IF=S{F3JM__UIy zhW20T|6l#C_1|Ukf5(J>MYy1zgPw)8@xNSR|6f4z--P&IDgQsu;vWE@Rdm#M_=jiy z4nz0F4_05?A{SE!S8B1pTHD^>OVaCEIsEPQH7WXkh(imS_V1ei9Z5t| zRar)vQqk2?-`e7fR;-n+O#jJ*L;o*b{I|*ct@zJm{wtFXJ^NSP7k2!=Qt4>LOq%uM ze;>T$8NhZ%2!D;v@{@BS-y|b zrTg+sd|Fj}hW{c*A=NL4q@#oW2QmM8j-9EEgS8z#!+&t{Kdbns!{1eCe4*xF+@!~6 zVr0kv|0Cz04*&Zq|J#uN970CV@(Tz57x(*0#bo>!yZ>n+@DFlR)3dPRQ!}u$e@%~_ z37?ID^~-<7zrx1UfZxj4!su%uwETbl+yS4J?koKMb$W+?yU+^i*@zjL8k;!avoL&t zsN$E+RQ~o*`?nUF>1%LWekWs9Q^UWBp;*7HF0JSCZ;76c>8tp6Kfc`iYd;wN4e9?8 z5&u;DXQlrY5no67CnEkW(&IC-GqHUg@BbAbdmS*EN=6^NA6$nSsqEd~K;qye?7F9~ zR6tyO$Mu^LLZF8|SJSqmfTMh%RqUEWbcwCFR3aK!LRrPYim2bC&2Na^~+TB5j8HRM%&M8 zj+Qo9P$lLxjfqOwX%B75P%W3lUwJC_9S3%!yA=6`{lWM2$f#=pAJ6mBwBK*&BzfCV za93Dcf+0&pJ@m;cic37FxV3^_i3r;3U0faE=7+@tnBei-+dWKul`&&}Lb(n{ys@aN znOp9>T9HC7F9h3^udQ)-5G zV{56I-z!kC*=yo?Kr!AfpD(hcG3*bmLnqfy#s$|KmX^qJVoObwkss@OG&kg)z81NU z@fh`y8KO&ddtfu+_VB6vRED&h(%>U)hP)G;Eln|bDFH~{mFZOY7$FUrHfz#rc2B%w zZJ}sr1KfgmgsUxXt?_%Ye0FtH(w+G1d&Hf70r8|QZNvI{aH34}hO7$5Cd_0Z+W?yk z4bo?Y6hR~<=Qveyv}H+(r@A$*G&Tml?PY%mSNXR+&BBo$7(RjF zhP2{KlWUtZxd=Mw zc5X_L-JtPif4@ z&(Tf+p>C&%v1b16%!Hk>xi@E0IR8x}-15w4GtM3LBI0+!iW(v8d(2fEw-!B!D3O$p z^Z~kMg&8Jf{o-Ro!I-*b7GIi3{G0jA%Sca}yl(p5TunpMtV~s4_48Np1d1@_2rBgvT__LYbC$lRfQjq0 z8Bsqy)G6*II|_bdu;;V#FvSPsX9<4pbHBfwXrHfrHut zpT4?^Doq7B6@`_}awJXLh!Jbs88c1WfKip>as^G>xKWk;@?+bXQ*y_Kk+sb-mX=fS z=*C{{S1W27_p(v1ZX@2KT0FbuOd9v}QLiN<-ksW}wlh(!2Ll@Sua@Nfv{gS_CCBQO zlM`txVAm@u$;vdf74MogT;&}dr)&2YZn*Vr6B}|0Ell^3_0^4R)s57p*R>sOpJz&I z|762}?T_AO&!Hr#Q&xXHj}vI5raaE0+%W!A?XEt(q15d7&)aY2-;-?Cqv2uZUb*rf z$*Wn8s#c|czRqBWu(X=3wY8F3YDx;qN_Xw)6&|k4`GqfFj*jv`wchgK-^``u69pC} z^#^Wl(ik*c*J&Fpo*U}JrcJ25m;1mm|CH|s8VwA5{+`g$*49?4)6r6E%qy=xLPfl< zAo@&%D6d6bxXJtDm#5>dW;vX%0_CbqML|mof14>u&4a_XVlu^qDP5x zvz)@hQYYpoQTQ9O&!q2ofGh=UWMv9)N-1bF=0BVpX64ys;!){s(r8vAoxX}uC@MPHfM#1 z`};!2oTt}S=9Y?A@s{eXYWqFg)-}WaHQ`f$YmB>3ZmKon0^^c({h?M-iwal8+Q`8r zA#aTnHEe4Jv8jV&XXAu@{oVZB>you$WW{ju`0PZU<3-o%9QPczij%8|QHfh({o%*H z*hiXuDI1`2{Y1W$MUz`D$4bai zmFsOry&Hka*K;$D?MB_1*O&DmFt8$>}l%7D>c5<*OO{xQj_1-gX)|8L}s22_D?J7qZ%hTq>)ZV?; zsaM$j?Ic`8pH%2xPw2C^yXxSF1l~PQ164JvjV_&sx7=g*G7egF*T)N38_U)EF1$q{ z;tp+*O?66t;L;gzo(2SDRTGR9o#L31fc}WZ-A`nDKatYY7C7gVZOF03ge98;j#o*jbuOUB*S&m6EP(KA;4&nHCBrcYWOFy@B6D=P)2W1*}NM;xR041{+kiMD%H( z)$L!?=<|ZCafJy<8wQ^);-yFcfm5(kA%31?z$S0%o&34e$vz_fso;Vf_mOC_DFX0x zm@U5qrOdbVGF`(GTHVW*E$H^pS$sKi`($&cMUzl4!IJ1Hg7JQkAQ|E}Oy2y^OB{g3 zRM9jKey50Bo4z;jj3h_lH+Vk`!soV`Yq^B9 zfUZ%FGzW|H`^+rF;3iS;q;F>Ls<{tT(3)XUJh^~S6fFEz0Li0WxNrdPkIUxPVeYwa zVdCn1%AY-@TD8`^%ZdOQtO6#AB~~X6gK5dHRcHdwBvJDN%Kta=GyK+YYJ4L^HWv~S z*CLAJ+ufGjJI-SmPmpC0L;(siI~fb~5|i>XdLuf^rHTpHR>8Dt+lc4=Ncy@p3V(hh zhaP?nQIc9Aw$#}H%LP1?hkZxK{r-3f!K|0Fm=hd!~_xX#KHa}BR&$2M7-$!cL9H#ht-4XyRGqBlw^+q zHfIoked8*Wlh6_#I1-#R()Qe|;xw)8XH4&Rj=b4= zD>*Y!zbt5E4*V4v6Az$^ot^C%uvx~$B8BAFh=`1b&2r5?v_Fa-qJiU|GmVRe#>{kW z2jK{N?Ka_TD__hjdzM3=f+S=ks)bBm*hg)`a10SOI=j<|ZYa}p?T0Mdv9KO3X{PeZ zfK7ZkJ6=)I9cu!^zq@|KXvx$2AYDFr#Am=p0OuD!_yDRi#Wp@9in`ldvyG-nw`u*O zO-35K^=>{<51ZWeZJvySth&|8f_ICv?snJ^b=g$G#3IJ<5h^g4KmY84QNHK;+_6Wa z3DLJ<=<7;n#P8*3bIwK?(lqE^XpY&<2M^ryX(CJsK>>ZC%x6#U+=gAUL0p53oK1_^ zw0iDt+cnD7WEo4S38|F^vQC$cGPHNx7T5511&~w5qs^Mhm5IIP6~fbp6R_4LAo`@K z+zkY8&azvR8q(uh${mEE5#58q>_o38|ov!Spp9?Gm+ilCW( z@?xEI)yWtzkKFY3yeQsBZTN)roZw(Z!`@j{@c-C}JHIsc>Q6UK6nP^QJ;bGimTHfdp_= z1x45CF+-b~H`j?Ec`=Hl<<`a~Culyqbd$WaE>Et48>50MFFVgwHW=s0c@$M1o3! zp2sd6u`)%B$Fe4{(s{>B!3VR%4qzS8f9exAWSeG0k9O}&U${I2J4M`&((gcV(Xx6$ z`ecs|@64m@FelP)cL#0x*9@(|S%VpEq1FUw;zxJA{-`(ac=yPURBWl(!fC=Z#k$9= z_MGo~^>mEg+g#d^wnVpd*`hTAP4twx%6@=*anWA0-Zov;J+*lJus*1JZhJ=ZBG(yW zy?MOVc*c2Cd<%aod&7F8|3L7-^G@QO)Inn7r;I@L3osRErc-Rz3PC%7aTN%aBVQwA zg0}2++a}OUzN){9tJZN5eu|u;#{LcuWesf&a|zjnDg))&s}mp_&;|Y8i`M%Iog6^f z8xy8jqHIMWi|wV<{NX!Sjc^crsaM=xR*W@o^TRC}LfL*eV^%J9H&Kx<1iT@%&$Nyb zp^zUAlc>=lf;t%?h!VnKY&D= zsZ%Z&>qM;k!i#o5h6#ofpKLf=#H~Cjn@TT#8{n;40Ub%=1DjG1#4A=ivYw5qA*$ zsu4NyX~IU#FV;mf?1kRE4Bu4~wB+YE-rcT{y!ar`UWeUdD#}044}!1!9M_b!h4MkQ z84w^jMpY`VtapT)!MpH!C9lY|+lBI>+EWaABwxFNlDmDat*F>c1HU=KO%q1p4Z}Fz z!QE=mg(cTSpuy1(F@54|R}Wl2N?|wpqX?dl*|CQNOLf(F<_Xzf??5XZ?YX-p=2&+u zo%gk$B~1^q0Y=*WD_5RHVOR&V9y?o9uLgsOE(~I}K;7M;8L$VUottQL zaOKUBP!Qyn);%gp_8d3(?>jX|A<2K%6f-)pGC4WR%%wZH(RNgdmNhkwEd*%ng(M1| zvok^+?g-P?VMEqb!z96l@h_QzTnJsw?BD6r&>73IJZsMP)mFo;VNt|$GOe47?$Fyh zP%%H4;F)wqq4lif$wHDsm1}>j=ta@9o$d!z_L(#63WL*H1)Edj-RkpIfMMVg1HAxi z1<+sDudQQLCKCd;1AAbu+&>6zpG?W=XN)uy0iv$*h>>QRUFcVAi)?+&B;e$VW_;0> z^Wdu0w`8ZZ!31LhI9d97=(NpVjs4M3n7A-gx5P(;CKSpaMygkd*;4iHYelN@=1Btn zL?p9za?tmVLZCsk7nY^NKRFKf_l;WBXIT=+XxB%e83aswr>}LKBYGnt(k)B|*Pj~g z>BG+79goPj#iO|$>H4}=Mn)%0npB)~Bj>fcF{ANj*$#+0>chFjW;N{+l&tY?NBMf; zFohNBi;B~hfcakcKItBIG=|mDoP!Tjjp{uq9*CF56MxD)(0+>C2S9#VlzYwb#PRx0?hd+3PPhn-f0Q*U4Q1#l_a)0n{gX!~mVPD*5YiK;#I(r*Bx$uRyeh&D@%g zqHJ@GO@Jx;x)t~PYB4hDCN5(V>u(dhU+pH;>y11uT_5+O{v`ZADi|QNL*|Q`p6&*L ziia4q0j1RT0?b}26_w^BJwf_RFDc|fGY2f*9AlF2x(S5M8w5@T&q21fI3ibZF-PA~ zv{zQZK6LAef_U@NyInBy8`3Wtq*zIC&+EQdMD?FgKY&SeI6QEPqzy?uEcd#Q4<4kc zFa*I1P5=7cRSe=bh$+ikXZp_KjnS^giuL+B`c#9Aut3qyw&GeT-PDL=cNsGVqzjDb z9dhIxeD{EijFx*9N4?tH$Fwse`#aN1Xki*0M^wrdo4vg!d!w<(t2Xdypr-$bwgSf# zC<4tC?&P=Xwy?rU;5CEma%HaVq?Vlz8hfdCEB(Gjlax#7+^HZnwaCIChx=fB5`Da5 zM6%X^5IAiszWgYRjCMb6#dV_bOt<7?<%3NiT3I;SeZLV2HTzWF>XD7dRpO7q@cSr# zl2A2$hmNR^1`~sgC<4U>?jIh%piTx17a6oMdtg{3hxO{|10HJ?+p| z&>NY$VO}H&PlOc?JgqFd)H=s_2)=oGM>M9R%hR3%+U9dJ*_H|rSR2VayXuCzd~ewc z+(nOH6MWF-z5XV~8p0+^(G( z=wEAjJY9sWtLHm<_GIX<=(VMO#V%c}#Up5M;2S!JlxcHpPFXVG^~=OcZ13l=i=6KK zo+iR=z`-s{HbNr8g``XJM=L8g#v+Bw)XQzRm%5mCzTGlPWgxNllQ)-Qht{s2aJxR8 z_D{~aU-jr6Do3d9Oj(&n^CG?<)9CtFb8}nowAjagP>j!}?uZ+S3go%Zf+> zD?iFt_8$3u{HBn;eZ-#>32o>lTwT-xJwDhKP2P+ zDfOO%@ny_!hMrRD6d&6$F;nAQ-sl!2%W}2s$Da~}MX5f)4-R?MoKP`QTvm*`S zc^+;jy%|j2X$6KLtY9Ilygm~rE*O#P0C>E29;}0VPQ8e=jdsAa8cT8kiTJD2J&-8^ z>CFD^fV>E9UB{!;^NJLmpHf!T{dqKV`q+#TLISanJbYqJ6U4*6+b+4N_QY86 z4J4ABh96cm*E2t>R^gAjB{zkK)ZN7un-0hn3!t2t*rSBmvAMa|jlmBqoh-1|=!?^_ z8r%f7277wQ#&ZnFC~T$_wyKfcw&tX&S{id6HZJ%kX$PPdBJG(9+S<4s&Qp2L$idB~ zXO}g_Lj$D|*`^+u{rwb)lwIh@BhQaJ2b_WrbSuQmEAX;(utAUv(Mf5iITqh~ZFfLd zM441kv{k|mFb7BH8_=~a7! zGdGzmq<)d~n3Agw$lAG1&3aaH77^2pz9Q`!AzagcdAEb1ntskq^e*w{9fGUgzIWR* z3GK#G$sSJa-T5^T0izNfmh@_;iNUXKIq#pb(Ut{8_F$D%dYhQJb zoqpnKd*LJWO_$)ex=eq-xNhe>yMVMn&AeIIafXsy69pQ^S?KprVh7EH2C=OO#DoH!@({k6SEo58!vnHGXC8O%<~x3jS()t&Xg%r*4`B3;Sbia$XVQF z?&Qq--8XK5&3wG6u9?r@$qDbWI#yh)p^SEjny|?Mnb%Yo#!JXLz0`*)_U0|{R#;8p zt3w^#?_r$79Ru%Cr@J42wDy8rP%ooAWpJuK(Xe~on9f2c4+x*wcmgN4Z=a#Ph&RI) z&77_$Z@YGMcHN(wo*$ohZx5d)pJ<=>`H5ZhMAz`8kPaZ}d$|Y{tDz+Wm3uMu;;)LY zP@H6=(2uyCFUu zQ+E@?wMNU{dF&bY>QT;aD6tk9!b2^jC{7?8$K=e-UhMTBrJWFm&dOzH?0%4gc8ETK z=EYXi1Ye2*jq&~mCqMKSRjoPcu`o+)d(_1Ua_8ISRiCdhB&5N1H=k%nXxkRNPU9jE z`1=4zmBDr>usr29Rn|=bFee9_%huQ~p9Hgf3Biip&pdf@y+5dWQnRUU5ob9DKkYR^ z1$au&w*sZpulodtx<(evU5APJTU8>uKZ9WnZr#xX<5H%)nTe&ga9KWmkhp)sFuwHI zgj%E^HS3)>!36a!YZ;4b9jf3uMc?%OSzqXa05UL-Nco>iOSo!JDN8V+M zRrMHG^H?Yb8Uvf*$G*DlM>a+?X865EaKBv{b32hA>8Rr&V06fIo|Vjr{u)l7mHoVi zzoHF;nAOSHJB^PDxaImFq?o6_sWB+!)n1cRdyG5MZ?+_B#I((~M^KZ}%z_~-LDo7=LR5dAMQ@JaxFl`wO2y{?s zoR7V7q-2QBvW6)RML`W<7Dyo?rKm{(_)Pp7pHpR{Xra+CP^*qUIpZzd;i2q9|E@?_()qpdu;QMvj|% zVKNDbyGf178t{!!{;5<(8=WQ;p5%X5go(fm8kF48R?-r03rW7r-ygsKo zntCR2N7m#NTm^1jX))K`l5*D)emq$}q~K-lfjd&(M@Vx=0tM?nP+%mo4eed}=-S0o z^pNJ0^92t_^`<6DV|9ne*?v|u`cGT7gj3hHvu&%xh@r`^1Pd)ZUS99@PC(y7>Ac?Y zYA@C68p&eQN#BVZ?^Djk_LXhD+oS2Dlmj+)zn7_?5Z`%W^Y6*mz#}5T41CP~Cs%q? z{y_M?^<->WHkKyd8p?6eO&;EpZ}|mJgB2w`))!YiVggQO{wsd8!*_>x1H@10EUcI- zQf={tt(#ZDzqG0yobj1{8_ul!^7>)0K5Hf@;wDfmlWQmuT%7g!og_FDHlD~LxZemi zBw=1As?p;x{aMegL#Bu|d;@+x;Us0WO~B+uhWSOtZIH4p1glRdw_w2fw7WoVLmHpJ zovCQm&yg5UGRjT;fJgwy#L6E5AuV_hx$ej2Pze0*j^A(d-t<)zVey_3kF;5`NgS)2)Z zHWF=d!i;%@gWy}Vv7=u^5N*s$oUCNrl(WDa(a02)2@lPJ^I*bSXUCq?Du~9cNGa}lUYw+WfZ9qHtBhT@dnjwoh{@v>So*gQ-b=s##NkhfA@40CW5ww3*70@FZa$mhU)ab^pH$@q2;f}=;`O*v#jHpaM_@hD36Qe6LV`pT zu(Rk3VwgNowu}0KGYbX`$rn^cuSMQG3qtF+>p(QBdsn0%Vh^wB0~SZHTp%4a)%D(m zrzKhilw;C8OR~UcMjR+qe#VCVn&D~<`8C6to2evW>A>ER%reF7fTN;~FeURs=8%w; zH#w~{qcd&g7SbuancL-TO71DrRghfbPdF8<_kzLuaJ7G@HVtNr+)^^-oHnvvSboZo zd#cn+y=&Iu-a=BDxZ2I#%^jAwj;yxo$ggp%d;xb6lUH*G(I@CzWUV@kZ)-E@ufMp8bFyYGBEc~f;&b!&Y?S}nl|)$!ZjgZC5F8-tRW zYo^C+91c@z!>@`?1oAs@psrr64P$+(6>7wkaoG1CxwD2y`hlR>%3MQ{j=(Y7_H$SLnb z(J?YcX{mFuuwY!qbDl@mkms8PsM99poCp3OK4Yz&LB%RFwz-%;oTOp z!VJWMFJmwNkr`ZTHY-=It=95qK_8nkkWzV^V-nTnPa+=ibL zijrt6|EfKU&?TUwy(3*3}_Yv$wMq#!Ai+0rORukl{)_3&iUb$!-v6BzZFX96sO!aMpg+?4<*d#f`;Zxn5=R;d5mTChfS?j$Ma#f)Cs!oYSKNfcREv}n z;pCQt~ek+@4scp_G84n@bwqbTy=xMs3w)uwf4V%sfc0RVJ&i&Vi}%#+nq*Zi+UU*W&cOCeTmS?d%~b4hZ*PDGqTS z0-}Tc8#}Led*s3S7m)3{os(%g+wV;+?^*(;oB-T{V^xB*~oPv^QFhI+7#X z#NAf2s-I`BW!TSstj8BP<66~P)L+vH2Lkw5DW)Sl2fE(&mN$umxtlC&f4fVcC{`WU z-)c;5I4_~)NtR`N4ns%wC!R3oZt?-|5#V;+#Zw^ob>#7>r7_Y zZ44x?v4hLJS@7M$ zy3A6F&(yvgOE0BbkUmmr}pQTY?S1XidXxM|6x?d zXZedqKY2+0HOO8E`6~Qa*`F%)uE*Ue(O+owyy8FdAn#7q-(Pq(SWRj{XBh~UH?tlr z`fH;H&*V;=$u@QM_Xl&l{6YQI;ob1Zyd}g|cjGhP7suz(x}*i-AaQX7hT#duW#}bE zPVcs}`se3mrROHF={Od~$NsqVUtBx1i!MZ1Tt=%)=E>2Z-AwGpBSPmpC7zz4g)I&b zMA@Y?IZ3&fYc?B#Qs35YpSUGCuDci+5*(SI{f;+>r8FPKVYNG$<;K&fgnBN*krDrs z{3PiA>qn|oVa)N=1$>`q{ttXvVg4)$pP)y9T1d`$-oPklAo6}IM|O2^S2NU-A;CYd zBfm^sdBeC*i*h9Iez<}$%o7ObaR^UrA&Vc52s7|uCk)|cAmBihP(a!#LuLYvn8A18 zv@Jm~rPBB~Bnoqs9I>TP-e9+4;d2W)>?@gz?e**n{T zX%eW8%-cNjk+#Ee9wFF9^G~=1xg)wCt*_}_usyn8L@$Z*!mMA>HjgfeKkg0jEnp5o z2&}XQW`megX2~ARKEZwzEy3uFtv;D`f^+VaJ-I*4$F!$CH!R_7emgd&+^e#T>2}gD z@<8~s{}BH$9oC<`rQLQ3^b(B2e0a`sTmKGB-&BTA$d~6k?$EfsgI}_>w+zqZQN7AJJbrj}0qIl~78zn4$a z<1PCq8@p)A(eXeaBAUS_Kju*&J5yDp=!MUH=bPx9 zDpXU^1{kx1h#!3dQzJOt`r}<_Frx?uQXf6!B1m#TO^bTDvnR#tfx@$&;#4OPA%imQ zqQeO21m;hJ@H;`5T>~thv$87fM?R06iV7GqDwi=BpEP}SsC#5oZ1pg@J)?d^O?g@o zy#kyW2d_(nad*5SC06aRfJ{1?6J|++K#wtcQ+$-G;ukEQ$wg zh&d3df!4LtSzu+dR5k=)&)#hp3N5eUsz-JQ&%4)8gbtAH8Mzp2^4lL!U4W0^%Q`be zo5NnB!zO^F)37?0YL(#=FG0BQpaeMybu1xNvM0?B&^+fLK6`b0n1a~tY9fKo;l zB8wngq`SszzP@?b=i|n8RrALw^XEA7sC+xPalHm81q3=+$F!f0Y*7=7W|HZo$Pkod z@`_A7q1us_Bf^*XKyTdMWpEPsI9mV`4GCn95lCjOv+52_?tu$iRK7E8ZULvpTL;nm z2L2~kB4QdXkxGp!>8*gIK3txX{f`(h068{dHW=9-IsEfoj81D{2ir8kq*LD7xxedPs3DeHYvMu zPTvz{DmsZ2H4;KKNST**9ERQeg|7H1AOpN`r3w9(2!7na0p+_b$*00TGev~qJnG!@ z0tBA0?F>L8`*|Kt>&NtUw?OVD##Vn`PXeEYNxn|nS-<|+{$!W$08sb_kM7y85rtol z0j3?fu%lSA6sHdNPav=`l%aC*z#YP)<|UmPPWpP&KXN-?zZcCr3R)Pb4fD;14*2l2 zk4W0Lc5Od{^bV=1A4Lv!zQ{Hprb(*8gK}JLgw%)v1KI)B!70_KtiCBp%hVCzNX81) z-(reoJS%pB!z1D^*-6#l5!EH5FcB0@8^nNvfgxOneg;3v&7~6DNw6;KEJXJLPdcRz za>Yr)6(;!RH-dPTIJI8~)!d2ip3erK;TzIs z9n_kaPfDC9F3YxVwJKHA$6SWM0N`L5U0{HG!KIxJ@6td)H1bKC$-Ie3mS7kj4TH?b z9ec$&S(T|dJ(ePSc905JL!v9Swq38Y=~X1+$PV)U!8|56*tvlIj(?6nM~7daxLLx_ z^zkPi$zUV&@Y(#Drx0-XseC8zUiCjjD1+5g!4SaV!!r2%cj&aBx?lfJ{UkQgZf9IV zgL0C840|dYpGH?MtmYIt4AdeHHX~+aFM7Q& zPR*>$bjXa6yr>jF=M(UGAg?AyCAvUERHD8(jZFdi>V%%D2FlS2rU=5iM#HlQirhiu zK7U&%PJ*%kMHK<|mh0u1qb<99224dIGRiiS_h7BSNM&Xp1q@^GM+huDD#2JlUavXIZOR|dXt{T>0YE+{zEY=)s-G{-ez&^ zx%?aP&;UP9tQ0IvJe1VWYI$KE`{K~_U8=rdJ^3~jEE@^)Gdxhhj+(~^)>}Nh5Ysj) zXg!cYwRd<8`wGN)Z@}e6hzm@9)rKv9vGbkeI8W<=9MW0-ET!5L7{}Rot)Fl{ECyE) zG7`?H7~ePRA%?{dJ`HT80+9h#vP(mNGiWH^|mG3 zdeKIc5h;1;azSn4ejdL8@!h+S_?3WASQz9!{Z* zc23LAlbM*lL9>qplPR`Shwe$&kZ+YX9AeFU;K2DC_&I&WhzjS>^zYlgLar%)nvT%n zZh_u}q3Z7TTbDtFWR0e&S%!LT9RN>E*4N00E|fSHSS(%JBjNjgiR#bGxgA zOW&>N5vNT8c({1iXzqagiHi9*c_P4gGzy6Aucdl8`VoL(4qb8&WKN2(Mzz$2v&=dG zYW423Joy7N-Y*W($l+d$^a`%VrE{Klj1bjyH7z&+{_G}5c5wR0v+NK8ENB2{2xmoaO`h$ty(fgX^+koE$&IP=y^oY8~byt5cP;p-Wwh|~)q*Be-b`&0ug+is) zCRZ(|dViF6R(FBxaF-vwBu`j3zcQ5-575oM#F@!uj{*Z!UJF$57U~k<7@p@54orwR za`*WW0w@p+dYn%PsfbqsbQfsOHv4;{oVI5V*rXzs)RGIby4ZuTef(1o$cDc4`LS%h zLT|u}de`S86yOUDLYy%dJd)@ec=j{-1@^CiHD2fLpfKX9`B*jlh6-c%qdm}(I=_vgXbhdXMi?kBAp_7!UruGsc(H3(Jglf=l7}eN( zfY{NQoYLBGu0YTyu&_d|r?#a`HLIdPUHE`EvHU;O==}zrAMeQUmfCw1@kPSw*A_)!6o7 zIyyyJ9No=+r%tfXPmrt8pooo`5U`*@hweYb^h z^JmaT-B&e7nC?ZGr^+R)bMh^4Ft#3#AWwV-9 z8fWu*1s@ogheS3hjwi$LV+ug~FD3xuAb{Ij3~S|#pLj(7JnX{!#6Bw1LgxN)VR&71 z5?07klY=X|KgBmt7#2z6uE8vd<0W%9FqU^+bj7_xN|eAHr;myOU{8L47;ldoOUy-Y zTnp&y#X0XqvBYGKX6iRhk6w{8nsGMBb#Hrhg;X*@!ycYDaW&}lanciImtdX7jD&-Q z!EJqSS7BOtHKgq8CHG$y22ukJfdlG~qF@yHJX!ue=x2T@OqN83tLx3LO;3AoxCK)m-&Jj zvI?M5iQ#QP@kx6iw8z^)Qz9cT!KBI zg7;o7)LR|kF@0VQ6YxNvtw-gM5*Ix8mh!Ff*CJe~P}7S0oLm1k`X1!M*$o+0Wu++S zOm|!^U7qfCWg8jm=;0Naw3UD(U5us(L(NOe;PB$tvsr!0-X@}znFQSDd^PXisnk2o zjBn(@R?ZDI4s8m{_oL8*2Aa^9k6F>$s1^fTArD1d1uxzTF+zYUyKZA&QK@1a zP)ya7-pQz9YV<4hdl+dIyPfs)UPx>B3KtEwsh-nLoAmh&iK7Om@u-CF!{1X_jUGa& zMUkD*MD%=HESM_A9JrYl6C67P^)g(edV$?Qy&+)QGPNzyKJss0U(bQ*s|JAcnBH<^ znO4eGoUlb+tKHSFuYRfVnPcrj;-UhaVE4<%*{7kYb86G%82MOw?VeE-# zAwC|if#b823lZp1Zatl{jZ`)FZ}A8pd5;G7!rl?8pZHxrs)x(#-o=X5eHq%`*a%zV zP75+6@DSD7mYyS>u6LoIy@~FXsi;(Isy~hO={1cwM%cA;YDQ3o91RX_>b-jpuE};u zs1gqNAShAO)|}&j+X>A3x@$0Nsb;slBHpmQe?DTp^{jI~#F`%GcqiHK0NpTkjp;Kd{A^+AG%( zmG>OCsu!bs#QWEi==sAr5V`C78L5S_c_Pz`g#_~?^NZ=VDp#S~h=av6kniT3b8jlQ zl?TyjvuRx>AEnPq_QHF@@^hg)d0k|BfoMN42ju7#B9IIQh_F-lu+rH3cs3QgG{(c{ zAgoheZ@gRt=lo5Fw^oC*xavO;fpLtr!{sv0PPkGU;h1ukIdjk8)bL6PdHU05`QtZX zip1Ju^P{lB-F5aWYNTRXOG+t!2=+qP}n&PQZ4>C8|aEx4QrGMa>l&~^QUpLYz=i!>N>u##D5B>b* zDv3f`U)zz(-A`s@Y@tu-Xy=a78zyrd(3O)5p=wx?(@USPz|Mv{3Bki7v8*;3v;C4g zk9OdeVCQ<&qse{)D-rl&(6kcbm4IXeL>U5gHCSqk2h-q-nhR=gjUjBP)n|Ywr4Hj7 zWlG$lUw15dp5l5N15C{#u)Q|JyQo*Z&lxpi@BalezThhIx&yQ`A6Z5OZUHwN56Q+` z^Eo69)(7(HIdmDr*4--~S$H`)Q9*}{tLNa#jq>!le`~i0mM|O3#nROd#kK)?j$%#> z#&c_*$)UiWY5_Xv>U^c+sA8J+a&>VUnEBVs$0N@sxs<2dPBJBEjOD89+Sx<9_lkwB z=$3x3LnK>T^|@Ie=z6$}@aGTYsQnpg3*klw&)h-*a$&ZcKAlG{GuK304^2f?F8;T^12pEHV>KS3SMZP7! z$}yQ9LLRX^bBwbyu?Sc||z4#@@7BkHHq^-7xtznyxpa{z%cRkt9wwFBcs(XH1 z*`!j?G&`Q#V-7Y1y|Ip;Rx$rz%h^wA0c%a32MAu%daEahvQ$(~y?btrU3DO-I6i>( z1ljO>D2>zVjPYb|y4&m^LA0pyGF^=zv-%*;vM_o{i{2IG25cLjb>BXpspd_VUSK0b!_e=^@5T70gTP8U(C}1PMbA`aVbzeII3X;qsOvszlcO*So9Wiu zcBIOIB^vxJbyL?9(X`hUGp_4KN?FKWfM22>s)*S=HZVcWft&aPukoaknm25*!>iCL z<3n-xtm-4ha4bIs=j}Xzx~ubub;#TO%&*y=lS`gCvKgR$^JM(914ULIomo^x-!qF-Tk zDO!YR1UZuo9heV8F-v$mH4vppcf49PP1!oN?J=W%*tuf6@<`{aGsSEQLz~w8cmy5kR{_p&=GSZ+U1wCAe?8qGr7$Pc6UmDjNroya%a*l!oEQ9{R1&a zC~f%O+U#RdAg&AOJ0g23bdRR<&NOh$?ryV@Cogfp*ukYgoGZC1@QNL=3+}$?edmVC zC4zM^fiO=L>*c+JbGzLG%Y)`6wAK1K(PQms$~y6-#U)hdcbOUs@@-1W z?AT9(C%!i!Q~%H%(jy*EYEEEPsBDj_V$qFAbeB%{_xqjBr6y6fM$S@T)kgp;9B}Ir zmt%x-wX&RvsSzPfGQIE*BFUPD&`2nW&^&pw4sNd zolo|-H~o4Vngjb=6}f!a(RhHix|R(2i^q*Cw?O{JFzo92cA(+YZEh-dxDlwd^&>sp zN|?R&D@EdtmBS$Z9vW#U;*aZ6Ep5~89Bdh><)s;68Dcg!J@z`<)Vc&SCr)_-<0!0i z=o2oTY@zS2152ywI;P+FL|baPzDtzf3HZ?)uyYB0H7JL(43>D$9IhS82INZFjAe z7=UF*H@|Lme z#7XT?6#VFfFx3=-1pkefu{+v?PVR~WMQ=w|3lQksBTampHTIZ;{A7PFjoU`+%~^NI zSVzus)m`qsJAA^JAumrxIM$Q+&CAcs@Nqq97>p?{5^!l4kgOIMBkVpNoJ8=0Nj;>@ zJD-Dr@;t8;*)Z7gBMb*M*9>Gz9$lo~o!~XmccO1YOQ&81z&@JRelIkcsClvb_*@Vs zm}n=DSkmV#nVfc;m#y$2+^{C#lVX`CY>Lfd?GtF?r?J@waebEF+%52KfNCV;tfLP; zoP79%tnoqI@}--pcoT#xnFYxL5a(=4?da+(u3;bk)191h?{5dFyPWNLaCPp8>}AsH%&-(q zMVkz>MS6EY41D>X`G6mtW({>GAnnO6 zc!G}F?aHMEP2no8SVwDn4G*G~U%Ikq6xuCuDHLpR{C2cfa^~r54st@Z3^cP`c7w4YxLx_iTuMnoq!`w8WN+yZ>L zSpvxDtFBDKNq1|`v-F!emg_>wSngbc$*;~4qu+>$UInUKJZ!wx-SE%3WuUTdetk6> zRQ|M8B-Yp}J6-gS6E~=@)JdSB8PSH*l#Gu_upTLErWBbN1u844P-UTNac)NZ+ z@$PvrTcAvAOfDI}cZ*m%9u`LoIRbsSgq#u4d)H?bAt4xnin5A`YP>I$3@|cT0FWXd z0`>t(8jMIP)FaU&lTebZ08BI?qAIF1bX_$K6=O+_8aieg7k+gq&t^kzvXO{g>#l@c^`lZ+x;7@C@T8!I}J5^VLMYd zqe}XpEHy+wNqiPwM^jVdZ}+FC2M!KSW}tth(1eYJj)m%GHn5S>vvPAdzn@nhP|n6D z)J~|6mF63wO;9l|76g%y^!FQ^XwE^UP>YAtL`@EB$;BgJBIRfxvrv+9dh=6^(hM^P z2h*e*j*X0j)0jUmt%weoYKTF}pcze;wWbRjuVtvd6a!QSjCqD7fQd0wHuTUg1`^mMBKzHvmkKIF{e^mOUD`W#gG;Ywrs^=x8f z_3HHN3(~Y@~aSxi%Uhs|r?Pyg6U_1%_HO|zJu?|sHWogi8Vsv401wOcT!&&i8F3l zx$8q!nSz%bNliS{=;`Ov8}JB7 z*}a^f$5T&d6KCBP+t&}oBN8YK4i}J%s3EB-bsC7gjnijRFJBbh2EmkKeuS zPcOHW!^TZd$UteOV)fj-_3v*Vcw(oAuC0sT3pe?+P@9lWPC`+4Fq3vNu@}=(n;eXe zR|nRQ`-7DwPf|7l3ef_o#YUM1g;e^7q$Fj@Va8;_$*HHHqGV;Yz6TFBlQGsg>JQe= zCcd8c3rqgkvmZAb1Z&Y}ZV^5Jt3&IbU=mp(rlMw{732GW70oI}Rv|JnHlCUs8OcsE zm86LpA8#b45itDu6~3c^&0EFE&QZwKJdK`rdQNsbwiMtjR#??!6M;Ur_&q4tc^TIN?Nzh=y!58Lp!gkD#60!myDV zqQYR|-N>%*=Kflr+3s2&5WYfhb^{Ga_8({u9BwZUUp0!9j)<@lu1QOqtF^x~7u=If zG3pP*L^7e)X{G2OqNb*ABr0aJ=o$S*9D!;?OiMNiy7D_QHV{ zcDI%Rb#-zxNz`?WoMcAcnsP^Z_ucY#{{gT$3Dr&S7fB=>EVkR}2-F++5NqD9cfUJg zwCK+6kKLprRJVQ8GqfCwpPR|=O81nr2PkJIrU~9%$H~v|OAKtxW|JXZ zPb=-q;%6LpL0wL?PjB%xHCM-`OGgQCnY_4+4su= z6JaoGpu$s4S3a&qSLKB8xL8`&4aRCd+Abx((8mJ%;JrOh9mfiWuV)`7k2k&El8REb zr#fF$_huIAY~FvT(zIBA1Xboo#lVBZcD|La4WMa0U#@(J_iag-xP##yyY9Ze5i4Sn zYA&4pwwI=q!G$JKPS= zt!N+NI{6%LY_%)eZ;k4f0ovPW0aKboRKlbjyzhl;Xs|a3tW&A(C&4K$>yKMiJdF$` zR(gtSUI*+p74GldUV~dFmgF5S9rt{@!RXvwuT@)?ZtTyUA1tp^mF!0*o-BQMnJ*u$ zoOijUWn|G?TWvPLIo*Z`D4t|wApSpm$Doz6593WaB+Ogl4pq{@(+k;ooW99Pu4#<{ zGoxhKna%YeO4~=oOHhu9J779AF=YrGdvsnIuSC8ruqnQK;!a+zzg*t7Jv3!`Y_+iF zICa>++urXTWzKeg~!buT$yAK_k{096Fn;hDRiO$X<^YxHLHE@5|i9z_L%*FC-Mja@!q z9rJds8mF|azg!$i?lfHW5fFh;DK1zNHpU*|+d?S=>cb--ib2(lRRDeqI@3Oj_}78?;i(MNh~U>A7$uFGB$KGdG$ z%2(n&#I}vt+mk*4Kk>8#Pz8X7b&{#3xl}bmJw=H0sV}j-PEYuE?X2J78DUDr?gokr zFnxWYXU3RJP|S4`oseJEj;K_Lb&83ysk+?iuAq zR}ZVbT~J4iMlWO1B$J@_TNR}S%A$_2Hgrjv=;6z=43CVmw7Q|%Cz}6SYcO@p87XSe zQz(WbIG;TOzixr1;LwlV4c`&*2S0mnoo%fNA1OXYA|Vw9yJq40R2-vTc(NK}yT`aF z6GoK_;u*R<#uJkTH_8PqzFYIMV;}2XyT@yhDN|;e6yS_^AawSMDiv)q+wT-5FIoAs)Vbsa(Rk4!x6yu z-f1!)qVEAXRmx1irMJbj`~0H%V}1;Zw;-UO+}{U$#R&=?Zv!@5AnhA*=i#tz@1=9X zLp}JKPlFtAt-cIx9F5;eH)A%6@xV=<51N5aoLEO0n+{YAnv^!@|YFEF=~f{|i!ydy*_2ih%S?h7%U>S)LYI#A33xZrLIXjRG z42?XJ z9sGjMK;}=ck^#cBpRh`GDmw^^1c@^hs#Cg_Q z?YaW4rvB{YOcX2fcFnB>{U{1sC|J7!Ma5OBnU%KZ9a!gxVDE$l4G4fbj;QME`9$Xn z#WVd@MX9^(dglwn-E`Kdn$>h?1_ec;^87doeY;P9wWj0o%*HIBmDHzQIOEKS9fDhj zbw;I~^uY8vR3EY>A}dRJA$oAgzSSC?!#H^>9c3)CJ1{(r#3H2rsRdZ3nA{~*{j_-5 zdDi=5>Vo*U?plHLD;<nIx zSq&RE>9!Ze1McnycTihMb@B_njLm_3?3yTvweqO*N1myYy_4}jcKl78RTU6X(-8kRarO^i^KUjN6vIEA8-Ign8UAUK5HYiNa1=Dv zx5s1rBza2d|3~33UguxXU1qvZ*T#PkI{&2w`J>$U7oqbHhWG!8S=(dXhxbkB%5wlG zLGa5xI==Exf~RSg(ggVK>c&`eJ`2z5Ews=C3GQ>hG&edbUYDyZ7s$sX{}cM2<91@L zUI}ph?h&`edc7?1m!IZ<#kd=ohqZXy%h&IG65!okjI~6o+t+|T-=QB~al-cA{(W!j zs)f3SuRZ8qAU%m75r&>YQ|u9<^49RD?p5=IuTif5Qm_1brvG9>|L2YJPru5) zQLbz(f5^0Ee`F?~pO&9K6CvZjSjnF^+&^tJuD~5B9*#;2D1%)NSL@=wu@HD)>FEqZ zzlwkP646eihu9+*32X;WPQ)irEwo8XPMlgK@GWRoK|&E~ULk@8D{fbeI#yV-+E<}w z76SFBaJ_;#m|3#G?3E`YB~6{m$JwpS<<;fe#oh8lro$DtI-8F?`)VEr&9ihBMFuqX z$eG&-i`Pvr-?$AYs%^0Hc$PZKU4qKo(D=$2g@O02j?NwB*chPSQ)}-xWfHPMC;G6( z)M#mtq@g#%8KK>M=E;rgt;4T3Wn;;`w>_A*ZbD<_gPYr^#T?EqE*w^Tl`bvB3!NAJ z)$n!~oQwLGY*-XG(QxnzboJ*J_&yD|#_lQ=tO5dfGrr!JuoUz<-sQWMb)BQ4BAA!{ z0^-u`d!(|mikpzxfTav)?J8NW{Vj>5s#}(B4xP8(?uT?WW=kd}h^h@jmh(6=$dD@l zUPLLVRilgm5?CZU@PHXiZFHFt9#f8O?#zBTDSm#flh9ffV-EfA)`GH*hNm?eta{yO z$XHAlQliZDKMM1R+C!sKr;1+s%NmBj$9sg<7k&`!WmF_0OIa;=QAl*=>UEvK;KtYG z7g^=%4U}WviL!7m3<@G??ICHG=Uxo65Kzrfv4kxRSnQhY78~S0;@*@#hPev2Q+ZRp zYrcxTrnri~7Q4#7#x`B<;@0wZzoY`g;||v~MnKnYAx%a2plzXikYpoGh5MjPh58_T zP`!)4=DTWmLT?Fxdw4*nogcxP*-YQ>Jk-h#nk6k6cah+r#q5w-yvf{`?aJSTK58Dk zW3F_e!biaF^56JAQr@84r0jaPN4}&ky{9gD#=mI}2qV+tr^S(RjFkcQiO=`qACT=v zxXe}TZlKp?E(Z*4MOhqvTJ5F(a?O(ZEu6HLkE0`3iNH05!!1<69kZb(HDyj?=CO)x z(<7qg-dJoRFXWMO`l{tA@|w1~9)=(Jxul(&_4%>sBDR8KW5X#@J@4FL;^25=xUd!; zSMSrGW+z{@%By6fY4pLjZn;F?8N)dut|YeME=5>sT&}wy$GwVesKd0}%a?yRH*TVdn-nJa(Cn%68>y zMA6pXA!(cW_t1s=XXss;_hfbjsl{#R_%Aee&1_Ow6mSR-d)5Gt;&c98K09C6wq;yU z^`e~f&Rr{m%G7|FNWj=7;XSI2Fm0toOxfgQN`p4Q_=2j2RKe7QAgeu%a#L8&9SDB< zGVgYy&}g_*TnZOm6Jmo2N_*iUief?doNDu%3B^zu5^uNqcz!~C^l>-ol%VMEWqh2v zbjq~@m#M?l(VQ6c)nZC@2@iU4OVUP^wa_pFkV`!`UL8Vi@@J8mIx7xOQO(uls9V~D zjTD6n5s&htmMD|JBm8VgI)LQ`M;+daB>Q#YuUnrBBG43D5Wy!F&ArHNm3+Uomm;jFWb& zmV?S$c*yPvH&7;yq^0Z7lZk1EMXGxn5q+-VnpKLMMDvV&DDMgb_bnddKpM=O2!>JK&lV&E6U8t&A7&cYx5l)*j(V`HFR|{-&QkGJKdHtGW zVx-Yhu}dSFaX8JpNwzU5X9f1w&JB?hWt(86BjmrPx`nUe&6vF2)Ze*_W&#ugz#T$- z*ecV2-$4P@yeqmR-oyf>?PWp}4w(Vd##J@Wx1;p8f z{X#t??T+8&3OIPV<5O^D;K4z`;sgishVx#3>9LI~Txc>F4>}LwjIpP&H(m9)N|d8S z^Xs^O*=gliJA9M_&?#uErsxd4gucjQnG=7nN4?z@KyHMM7UG{*LaU?KVF)-;8HNFX zr>NSkz(-TSNMj^$d#f+hv)A3|dWdtS{SQgnzZ?t<^bG$_!~a$HCw2LM&cYQ$#3khf zDaDK}osAvM4E6t!$^D(#K{5PO?eMo+LR#NY!NyA8`tO?mNXb7*`TtJI>Hl!^|IW!- z*`WS72LAqI{7m5gZ2zeF^NoS^&m@?cS^jSu)Sotg`Z2RH{d@aUX88p9|JgqMe4kkU zze=BC0@lxQ|CB%5)BV-!uik&vK>efjKYRXZ`_F#=III8q|KCUb=NbOvTc+4HB@e_7G|%Pa9;qy2Z_{xc>2 zAAR?hetpFiuae;O9pnd$MUnb}-EK7MMR*kAGE*;juCQhi!q0=~LJ6w{79ib@~t6!spO`mT7;l z<^HPp*J9+KYdOY$$SMB0wELU@3+w0g`oHJso-Urs!uOBk>(B00Zp^e*1+24Tcqy?W zNizP9U$M!9$*AGgxSdbBeL|Xb+zJ(mxq%SBW)`KsH z@!H8J_pvDmh$A)fT@PtmIt~QIm6QIF^J8dT>VviA;tTFw7qXQ}-g5&y-N-iYnb-P&g{{fgJRQj@gc<fr9TXL) zCTOofE`04!NCbQ`B1n}PDh%O{5|o7>WKb86X@&>h?@TXRICpyNlL2kHUmP1NA79wT|Sx1YpqV**R6|!o6n0}tH-|3nSSeGa+k6)azF#ZxCC*#oOUYo0hv_ zvZ;$#Ohu>!_jr)Fv9W3OUqGv28sB2z_&9?H^DmB>xuA_asLTa%4RA+6HpYH9Gkxm_ z63(i$x%+E_qa!g%%eY+{>*hFx8d?%BdNPZv5$^{1RO$M7vApkmmqy z|3e|y8f`V|{)cWp@1BR9=27Hi(WDE954_|;7?&xVXUY!Ct4C3g_C`zDU7HL#8-k$O z^?aBqqdVf|7RXjzu149l<$5UV9<>m`Lp+N!%2DiIcZiY_=#~Z(d<7U>rqI#!)(r2> zL;uM4G?BxkN&m?Yehelc5pmI3-}LP^@J>v9sbcyV2U}gPFSLCz+tiQT@ggGe9QJ4} z8J=S>fI)_cw1;KR6~lFKYtE`TpJT2Kx6V7zeLfvWPL0syzGEGMtK6|;D8RN34%T2{ zGe}H`4dbS`%x=dc5xW1>uFEj~EAcyqPfQhJv}ssWL4rta8Wss{TvKY=IO?JNq2wV% zBdch0$2zO0+M`l7RaL^)Db>ZR*O6?lfiQAl+E2cKnJ-L`BAmEXGu(9Hgx6Mn>YO1u z{8i*zRW%S!xjDYjUo&bjk9PR4u_JBz=B}k)*?7RV&`>nIiRci7gr)lVxs2G-qz>Z& zx4>qA_*AAMUdCWEzpJwGka6Whim@8h#lgkuw`p)^nl{kRmu1j%`g^O&z_SV1LlL`) zbq;G##vqTBmss6NoBf!ZtvesE1~$1=QcK?zH`vAVDt+pYSA9Duxtx$oK1EyN?8wGm z%kzPRX?Hbk#T$+7B~RottRX5Bb1}H`V6>Sky@pG^vCntxsaDsX=pDX#eW5glTdzgG zFrkc1Sp%XipTj3} zB}`&o?RX@gGTHR=+NfMEb_}`(#03O};BUW0xI%6*Gv0!Fr)fCw9e=(g2NC036j>Oh z1{Kx`HC^T!21d}FL|^RFahOszqJlhDYhf=^YEZC<=UK+m&)1?yOI1|Au1*gHmXSzX zVKdZMmNJlkFAp)aHC4mrB4jiKP)>(kF3G@3cXVkBB#_Q77SuRZj2AqsFvM++C2pR6 zRc_=+_S}0#@7OF|wN*5sgjAI^SJT~~kZ#9Km7EDf&Zq~j2JQp3)vPV;tVF3gCGekR zgC;B7C$SW8-7V)UqfkOfukl_K(xbspaT%v>K{;3p51z+%5T^kf8D~4u(!mIv$r(RS zSP5AyhyQ-uEvDvP6W;K<}nsplmi@WPHqwx}{Z>)AI2lPo}72os1-PwG0-3?_^$=SBP zLzRC3m;dgU8_KcaX83vb6_@4R*OWBt7}KH*pEhf**Qy>T*C>Pfy&QX8~||g z)e62-g^B*b;!>Y_3o98|c*=yM^GqfL(@_z>kM}Okb{kV4_32Vo@dK6)8dPJpb{CHs zcT&@r&1m@tP=zHwXCc`EKcVJt0 zMhS8o<#udud_wz(y8`>TeGoz zyVKJZ+Sjy^`wJBg9yr}59}DN%XJ|*i$=3C;>*zZ4&-jFXs|ZjbqHiH=T+b=C&6j9) z&F|oapDkdfwPe{nUtr-R#Vd{h-0SPo7e79l4RAb=#(ETY$4mSZ`L;d3T74<`@*UC@ z+JiJ6Xwqq+MeYHp1nB!0y4$hnZYFs51%5BZLqKsLdj zw~Pi`Cr+>uQWh4qg~H(621`M%m|RdL*v~+Kl-<4E;vU9iFPs6L{%Ai0LJuc@(8fj{ZAX>AXGg^YR0UKmIxZ&zf z*dTiLBE=T{L`f-$S2k2?Q#zWr{_QE921q_kT`cLyEnCF=eerAq`$NBQhte?X#!1m; zPU23MRNGMt+vP`F^m6U?d{v>c;c z8ING`HbtOFVU9nio!rs>VTOMZ86Q|%&D$z&Go$KrV_iU{K=xOFXFgZ9)Gm*&+ZpxG za+0KhOWS7U;v1S&Gs;ck6Jj+E&?uUWH{2ffzRU}O&C*}LdQu>qnt5GZ+PCPNOY?3u zm2|Q*0>Zj8BH`MI6NB>OObfczluYsWaK|dq)0^CGicaSZ+5lQ7W|yE(7a=@JKD0hJ zOQQQ%G&DJP!+tYOJIlDNh8$bpl|i`Sa)3$YUMGck8IQC6gI{uQ=g5KYTX95WPz$=l11 z^?F9Q{Jxh3J4Qnr%iCEm{4S8EPxS5&gSY1U0W2O>i++9>8xa(#HE^^2Q{#C)V$eqZ zJ~w(DOL7_&E6gWx!3cArM=w+v!CC}udo|Rk$1E}(^!Y}~{cV0bG5E{K4Nc<=C-T9X z0QFU;2QVV1<7MHbtQve1HqlrBs#r8LRwb$x82F?j-tqXrIG0Jypz0noOO`|D7Qz+Z z0rr7yOlL$P4w*PwkG_i#${~Ss2O~J6dGrnuf`$l=23!SoF!dLxlvN}_5>%-4h~9cR z9!fmri|UL>5J>PJ2#PTT4%1qur~CpV{YFm9cj#s({WD_+yu-J*X$R8HdT*U=G3T3^ z+Ama1ZyEWw8Mh`M#2*J`bIrf(p({IYCuCihjkPFz@O<7+N?DJW>5TBcJ^8MEp`>(F z>c3#qovkg;H4du4QdlZE&Ykr7M(cOr_|(+B>c81cwuQ`)<>4l3w5NVJ^gH?4OZ8IE zTj`S6FY>W@NRDBZ6qd%QY-MKM@(R0?xHHKW7GbWRzH+6qu(B}wNDE715PUJ;1q>_( z`gSsNOHZt^1e!{#yNfKf9CnisdF_b!EI%0KeRn@GUCzHHg)@@ZQA_B+_@?$2E}?~J z?VPMfE<;j6N-oz9YK^;G5|c%k3E&0uvmAsjWdVJGo@zB0=p7>p%EzxE=+ItEO-XH< z5K#iv75~eHUiJzA#TE2$2Z*ZRz0BLoSvW>tGbO7$teP}6T$t^CZz-ZIN0YV1wKQW! zSCTty;_e8R>^qOg${{SMN|v>|==;rxN%A}s4AnR`_gQRjik2F$wKc@?kVAY|jCCzmirzrcCs8Xc&Gn zf`c!1b}Vo3y1ofaof?p{vEU9g3Gftw+`3xiAVVvLYB^B$jvW>Ga8uvvm?T{^8k8p+ z?-dEleXeDo6s+yHz>RQ$<@X8bRkhz?QBzz^OIVGr1oy!_&`qrM%EHZtv)Ie`C%P64 zrD*GfA8*BE&h73#PyQD!yt9Ef*1=!Ganm*08 z&3{2b_%v&whA1n;DX0Au+QFc!G?G@~Xd8bF2mVze9wglZl4%1nphqA(2KHF-2!1<# z|F9V_zuo$%%@8uw#DG~P?JDK{`Ph}b@R3O_V|q_%cJi#ngvDEdkfs&7RhqTFN4Q3o zZ@qbdPS>zyP3rGp-xUJ92*C?7pw9=+n=WxWHZ3mA^j7@4-Kr*uklT*(cKPh3>FD=( z9Wz0x=j3rhRytjuo~0D&fzthq5>wq%JxELPQs-iniFzNqjrve!eeZmwN;2j2crgV% z5s`mT;$tfP{yui>IM;#$k$hC-7OgNb>KnU%RKr3ENm4AdcW68t%FQXm6r-8cVL{V^ zytP3|>o7d7TK!bIK11*kgD|xrf9m0IvRG_RjMB$NNgJu=e>-L~T-9}3#1Im|!D}qI zzPBACG{gUMpN7>rRGj#&{AMOkArT$cQ+p{2C?WkbS;D zDl7g>tRjp&GAxA(o9_IQctu7IN&9vhnCb_N1lhiAKN8(C!jv!wxGs#SB{}_m4PV6Q z7XW$}{r5h752oOD09lC?St|(X7hj2PC@wh1+6`0?4=9aC6X(GAxRH`$6XBd|7Rr*N zbjG2`JRZs>Y{ds0UUL=9#nF$q^jGy9W7q9)h~z5^%au2vPcE@)^f)@uF&t%LXM!a7ney781HzQu47Lr$e?5l?r!0>%w;w7C(%)U>aMs+v;8Y6+OAkz3M0k z7r#>ey25HQwQhi_mm(|2T!vHU?QE;n5{=zN%dOoa(DE)C{EIh(X_Or<(lMrxNJ<+sQ#d*&e2;HyZQ3GMWz#RigUl2#TA zt4rsUN|AA-K6k{)IpkC+bS=La2V|pTF?u2sm7Hm`;>j`8h=km?&vz5rM5VnAo+ts^ zCSFT%-&QKwX~f2Ezl=MJm`v3V#s{SSpF+D?fmKC%ca#iht!pT-3Y>UZ`=ypwiC(pZL`6ll(PLgFa6LXrwG@F?j#oCO*H7T%KNySX6U@R<4x5%SOw^ z68!KE-rWWeTky!D1wb49@|MUZXv!6?JPOW^t7|?lW5inassmOJBS$_ie*4%PZ)HiG zOV&Mxjfsyuy>BEiz57uqc2e)oM>+dGo%p;jD?C_kxxa6+L~&QHnHJizC*khD%Jt`~ z$1|m;O_u9-8#6J&-~%&$QRAvt4~9);k2Y~d?In-yOFf#0>80A~u0nR(N9=Ftft(_b z)=#?;6-5_=K2_GS2Js=xz~0v~lwz$E4?%qI=7_A*%Ya&|4)J=_AinEea5Lia?vUOj zv9ap2>3)q8)~&uv6(DvFm0-c*>p}tHidd)cYZh8q)_bZxi=oJ;vE+hdZSd;=);rR^ z(4$u6Ozj1Q*xw0(-{Kf#R}jW7H3ZOEpeIMi(>Z#=NDd7-IQD;cibCx3rN<_YStkIn z2d{HUK)@tK*PbJ$=PLZNlz0%EkXhB7-<26!TKQX*EbskrK-X$o4qA>`d? zL*qgbqjX|}=XW`{Ktb)+mM=~NPMww8(qn$oBf8=s$rt(yM16s?>82x8Y2dI7HdKj* z4ged%fE_BCr<&4-?SUcS;kO+69S_y$>6(ibOS(6Nk$2gHKZEifZP&H!j|5O0+ovk~w zO!kVyC90-e3Me-L_7vBmniw}E6%VO*e2|t?Fmarto%Z(w?0?C0a4kMrZW3@d4Cucwf0?MbRb z#7XXMiLJs5GaTh6#&T8eNf8MWjGQqzDxbVLNKW`j%fW&RRcW)THw-R2J=;T%-`Kt| zZ9*Ge8s$bZhbjL};6D(S=@7qH zFbE|mh`DJY}@MC^KN0Tx}^dDe7R`up328mUa2K!m{j?m#wjniPDZ- zdAo@46g^UYldQ$215dX?rz-r)le|F3;~FJM{5+2#FIlhQ|Cm;wbg;;1@V&+H*}0q@ zXWib5Z?r(W^D8tZr@qhFSYnH0e+9{PHQ6>Q%gZW&^J5&=6oN+}J+GxNx_LX1Z6;Bkd}^TC%>MlVG=T zteD=aj{`EM8PjUQTC=T{LjwgOr`Dq(#6*H8j3uJDiw2J+Pqud>JuVZe$J;!c68$3K@G84R9GNYF|w=}Z22(;Cl&7x4l7 zR6F^{iRO6r5EkJBURk;W2Kd%PtLN{at4E znvzx{GU62iG*OKaYfCv*bQz~_fxgKp{0U%^HGmb$7Ivn0umxGSm>ruXp9GsJPjuFH zF?V~D%4q!u?UOMcuiwtOF{AJcD7^fdux>fx3O!O6Qg;Ryh>V&R6?K!HcAWp!GznX-By;jIaHQc=Mc%HMjK!;b*hb&G0%!8zus0@8^Ps?gzQs&`TJ%iGn&^B^11=*l% ziS~RV%4}Y1KZ45u19cK!MDai&hCZ(S`Ba!;ZW91GN(%V>gvCv9K2ZiEc3UP}g0yI9 z2?=%xGaK}(00lBn9R$aP99d`SObHp-Y2$nOchg`&J54hlLX43?CaYD#Ad&X4Q21Sr zkPX?X8g=zj@^HF)NbVx7G~WAV-~UzEbw)L{bz4B`B~-y1fe3=`{fyemR-PCOx=(CRdv|^8Ba{%nJs8{_JXDi(JbW<%8;)S~ z|6Zf2shE{+23~8$Pbdaom7%>hsMC9i0X5Y5ps&|%ca*&Kv)QF^Tgy1xP?gf4fvhrxJ%&*!ke$5kZUi-{Npa= zh3bU0+2Kd!H~g|rZFr7JxE+4()ZnE~4@}wT^m1ZQazj?;Uex#V?8A%98)u>zV-gvP7Ihet7z0$!Ul-|r9dR1tG z^zEV*lW*`Njz9&0f=S0GW=VOgy34MyN|sf(bZ%blFHXx-JAQf+?o$6?`h@J06yMt9N-%FM1W$9~We)#N?h~5YfJ@ zIq07wz?m5%XWi(rc;iRui=%$tC#SgD-Rs>yZl$Q1{$(LLzDu1*&p#bk-haigJL=Zi zs)x~IwzZS5iri;Ei6p(ne`-+%lnwY*7JNZnA}e{%ErvR`1Xoo(^&tgho=nGBId4WM zSg6j{Jh_-%IUYj@6ufTlsPZhe>B4gE^SnB-z}TS2L7F7+P4*b8ON)Ocep_Wb0;j6L z&?yq#X)e&`I~j$;lgnkS3MCsu^7NQmmTW$ve%HAKS1XI#!_#I(JZ;9Dc~V|?wRCA?Oed4Cb|oW@}mbF-eV?vF}%q z>JSgB%rUoe8;MdU0rOGckgtAU)pj|(HKs39`94JM#-B<(ma3DnoWG2NT1|vWlZAco zhOCM#YdHhrh4nt?tOvgieMeC?J6g!|_kWI3@N^>{hq``V=B4}9fqRH zKEHo5PdlPN=#r-8UF$O2hw5pBCK9+-amVTQ8Q!BLuj1V-m7}^@ljijbPlg^UJF(i> zWJPvXUcu&jEgUP=D4rF*>5m>lA>>=Tg(dFvQDZa-rvV^JxfoxMXR|cd%Mp!OX$iMm zHv$q_qHFGhomaG--nbGmc(22HN$15oa^T?@12A>!eSYP@gj7c)-OXD6x4J2fg{FyP z{7F2M;^X&noRo_y+nuI2w!;Fk%aa3f+cv>Eg7d^r!{={Ek2K8LY|0!lrgRl7_*JOX z`Awg##&&$K6sSKHIDqaZRZTbd6uAD4%{&vR;nty9E;#FvQnx-=!K#|A+6To-bXvIe z8G?fzll^bBNIsCG;O>f?$in%qgEqu*~YDpDe z1Mb`_`Is&CoycZeX7hy?tpL3F*N8!J;p<7V+T$5t4@_$RS!5Z)&0S}E{7GC?TP_19 zR*Xjune%cw=fP7KaTefx?)iYjO8!#(!e?R#;9_aqjQcxO?htNJKjeh84Bbt>jtdXH zn6mx-XZuf5A{hoIf&&yBTE1#7#SWI^XE*d739AMq)_{K6G|072Uh(_^2Y2x@FTXz# z@6-Y&sOx@@J>RD7*%;p18q%IORj>S_X|`VETxGWI-35MP3Pd(7!_6b&eE;Fz6XXIR zHS9J1)5a(BWg8bNP9ETd-D>D|qZqB{jN=kXBaS3!l~demU;i zoSPfZTFw zUx==A{`4Gm>K|~#mPeHX0!9r6WzERv9Cf)S7*3h0X@ezK;$lk{i$NIGdB+q4I3(Fo zFkQK5Cz-vFDACNQ68gR?oQpG^Ult&#@U!6RhYCTL-07W%u8N zMS?jMMH?H5@1Ab8&j)=8eD@r0xSAr%O?e;JYP%so*S1qOD_hCh=B!g~kSN9XRsaH* zdng#ITLvw9Y?c_EX&_%KpY{XXfqnY;iwt+wMwwYhZTi10N7!RpPZ4Zps{DPY{zkJ^t?@Fq%zltW zq)80IO-?J+$>{jhVsYn=O&zPtkXKXTAgNG`>TQg=q=?Y6&|8PVb*jCyxQOu6xB!l_cbF(e?q%W3*e1oqN|{C3w4CXyOzAI-rUuGg zYj(cT@lXbg^P=Z_OK}69Q$rU}6%KPfLa%i~4bqJ#`J3OY^=!J23o#G+1bkv8r@Km~ zH35y+4K%Xvu`4cP;;tMW5ui5X9p1w}V{JR6jp`pHw|laGH=GL$ShXBjXz!&ca15ix zv|hO$3-C-xD167vVJ8=1P|RywFvf4}(1^mMA7LrLkE}Z|zRPkniqwose!(bO-IUu5 zv)bj@^7tXUlvTAP*5QP|f8!JYnN^FM&RFDVSflI$Qma&4OandEmEU z;^IZ*4;A5_o=!_jLd3?TX#c(OhJ?n}@#^#Hc>yXw(^I)0N^cl3jNJVCZJLy@!r5`} zQ!t@Lqqtx;P%rAXW3#KU z;!~@Ou8)}SOkMKrc$&Msjt^>h&cz^entbB4?y1AsbNp5QP5~S&LNVi7v?} z9o@@kypD&PEJDtNB-6#ysWHA`^57Z|42hvj4P})J5dbmfFl$LPv4j-S#nQ>ri_rVB z<#3K4Yucg{q*pi;ZcQhv#ij)aF%03MGpGNH-ikquVUb@8*n|pMr&nM=lk510hgR<& zdj7Ue>J4W+v4w)@tIje}-_0!Rogq&VT9Vg|@c!9LBGc!5gQ}NFgckN%O1Yn3_i{`v z<>jb{@9aj(a(6AIo_0T{y)%y@FuK@v&DRo9R|~Z7<1Cven=5|C?Q+eL0SjcnG#T)n z9RH0RKSz$AA)B*4+uSsNPKoCD1PktazS=uS?wuyf{tO<^pZ)%=U$YFT(FknF0XCEa zgRUUzDu4}zz_It7Kg|(!v7dhe7Ib9@e-i9}5sLRn#xxc*0`^-SNaIU`L3^l_2Ufwu z2`ByEfjtuYuK{<=WfOCd71qn!8Gj7~0V_aY3UClwN{8s|<^+Nu&p?!*Xlalc5#vSh z2bt=gIYr}NV|@w#hT0Rp{t9L4h4pd9UjKLGw}@3rR|N`&pui{y7z(BFwUM@9@JZVJ zujg+Kr_{gDZ(-v_klpXB_ej%wEB&I7I}_ZnpkEt24^lMs!aET!)8vgb-uf?*>?toS zhJdHp|B>bXvS~ZirHLOwN_&aXW}U-3?b&Rv%6GZ;;YnJ~RhyZBrwaf6={^ z{x`GR*9(iIQQwtlI)VRQAZ0k577qvd2ZO`mC|XK;7wFo5FbE8(Oj}?-hCrcc;rC%Q zV~?i452MYcQQZ$>C>p!{0ER#*(~fK3T$mDcPe!m0`^Vak!N5x3Kh{7(_IT|3=0f0* zy|O!qAr9^X0*CHtq4)bCP_RGZA;HK$vH#=zkWj=Q>muQZKh7D6K>g{5+|z{b&jkgB zAIupBh9VF8!N3UQ!SjQGVSD0@eer01e>`6pt@ID>jrKhDDsTT>B?OG7lsJH)PzNzu zk^o-DQ6&7J*etwqyM zoX6t{G)2QdEo5*FhX>Iz*lQ;PUC>348Un0@fP$4_ILsxCG90B0hC0C!SeoL6_QTOi gUW4ubclk$J;!U9aDgA0fI4vs#n}oz^lQV4p1H;F&zW@LL literal 0 HcmV?d00001 diff --git a/examples/gjf/molecular_dynamics_results/argon_potential_energy_fluctuations.pdf b/examples/gjf/molecular_dynamics_results/argon_potential_energy_fluctuations.pdf new file mode 100644 index 0000000000000000000000000000000000000000..833bc8d468cfa78d993e226dd964bc2938a819cb GIT binary patch literal 54630 zcmagGWpo_N(k-YKGc&fBnHeoci<#A8$zo=-#j=>eVrFJ$2FqfLnb{ioobS%NGjHCS zA5~cu5g8eo71e9+>J>?;EFsCr%ES&&Ik0!VcT#+lJ2Nl@&jDlsI+$3)3kU$2<<0Fu zE|x&f57B2Jv!s=+i@DQBYisOcE@5u!U}g>!5`uSjaWXfygZBWO>5o>~j;d!JXj0T) z=gxVipHhhQK}VsA<$Cq>cm$lX;dVOp7d#|K^$g@P2jnC+EI<{rwSSSoGHIxBC8A{P>V!c%S&^VK3#?cpoKY z&80=(!TLsD;4J24`ek?916uSwm_zvD-R}M5&8H=E>FphNG{>*NAoj(^O zeaSkl`o$_6dAwCKZMom49g#Anze7TEzU{nt&m*;{^!T*MoR@Iaws^)|mc}GR~?uT&((?LHYRT;p*K2^hosc#u?9>2&>kf>@H zSWs29+;5&`LfwLE^y3B-p_;OzGSw0}yxp~(P@|@V8JCJRn0*NtHRX(&N`h5IVw**!OnNkuzwWfSyhWs!A^qGOvw+*^5oU4k1xw)ov!^I=GnA;x^FI& zd7$Oy3N@tV;M-}zGSqfEncj;#Zhq*~X_Vhfr&o6OQG(mL@|qOYmK^$W8)8pz>{q1)X@-Fu$J$&r z(t2sf&9x95$JiKa(N5tq*-*e)f>n!nEfk6Mir~Idfnqeq8%#KGbM{9UwQB~c7Z~kz zY6go?w_E2(Pa?boU9MQ_WVenmiPT79DeuiYSw_5Sh=jc+Cm1sfQTHoQU^9He4W(ZEex`O5rVFaS6dClsi$vt9S z+B&z06|k)u?!pn~$&lzuqdSc>AI?H6yN_?BgEjEpSgR}%xO;s&7`7WNM}j*=5VXRJ z$&plIq{)+dT*8tJ@|h?5cHnbL_k{+qV6UE}Wc*Qyp#Zv&^8kLe=K#ST(OgvzuXmr|yee3n%ly_*0i>)4SO77NwGC&> zl^SVqezF%XDQR1xzKWc0bR6oaKye8`BI>J-{>ROc(INqbM0=pRLmXI8d5W z-!%jM92ie~gAAvg1wc2sm=+N`wo%^C7YL9jfsifTB|N$o(bZsb*iuPQz{YNvfw(MXE=g&8sYmp4h7_xQ)HLfqV;d@`!g+-QH5X zXOlH8=|fk5YtueSw@7>j9x0S2{((UmY;-ZPop;>rLUMGewd&i-n55oudf)~ zSU#BhBvuYLur!j(eTazcrAVnTU7900o@T0p%4H2!<)k17I!BNyt>qIn|Zrp$NyfKTkUZ~>ph#F zcNfuUqhDtW@rd68;G;vz#P>O<{>$X%W6gL@1(o_Qs8kLea1sL}@%-O62GP4$?QfF| zqL@C=@*`bT-=|^e380wa;I&CqXXQd%KpwQD^FEWz1S-%d0?!J=+BhKWBbo7 zQk|a3zHLzBY@*JWAg?kvuZd*42jBLB=B|f(49K|y?B4q?v5?3`-nP>de%FzCJWE8+ zw>Iw&CH>!a_d+^QN1mXD-Ez9t-XG_wEv$W>@BWlmZx8&jd_UTJ@V^?Zmo|`eYa=5x zr-KFi;o8MCF5Y&t2HTGn5Y};8D?D$W?m*Bt%pL6(w%y)y-&3AhHGBe*&x7NOpnplT z6Lr)Ueww+}9&Ph-Iv2BM*Kt}wlu0a`e}#zgWdt$)>kTgR%xWBrbq@kXD5X;)`?*nM z$9fdMTDY-Sc8&$yXC}o71(ENe5}2gF1Jg8#L{u&?-J6M5vC##qEFaq%e25?t6y zF8PquNBQ6)G$WO4-Ko; zWTGR|Jmh5HrAP#7E0gu7F+5DO@(^*g@Licpa$Rj@RDM~$ zzam701g9{740TUTy46QJJbUP)Xh~j5fqzEX9>k@U?;2j!B#>Mf%*e&TCrcQ8pS7jJ z@2^sX{tm>!#IKZ0^$;bHp_)CcfKauBV^gO#39U%_NXH9?mrQK{-+a>8&2% zk}wLHMi&W*mmE>^qrc&e;kES`@(%;wDgB&rgJM2LczSCNmI?)t>Qa&- zhFl3jihSCYhICxy_q4)9n4DGkOcOXZy51vIVrMb}rEsDopfiq09mgntu8K?2C^MG| zgJj-5YY%v|7TLmG*Y(muZ%KRKY`uD)wDxt!b(kiNM2VdhsaSqLD>X&-_X}DFZsxh@ z3)PKYhNO#;DcS-k^YY*3WBhTMsWioR$a_S6(-iF!=1~9*$*)TY`kqXtru%9eLmNLj z*1%3gSdS`AYxY{TxK+prGcm zk>8=)RlqDc?rs*T_UBs?Hx=F9Ti+{&&K<(kq^h~8*9c%}TT*j%pv~hJ50AD&oW}XK zd9OLVyVATap|`yVnhk25E5IX(vgyS_TvW;{pINr#v?;!{E^(fVF2i?Sa}}Soxe^`Q z6oL-$X%{f8(Pt9F67a_?f^T_(HDhxFlrG{w2iLuR=s2CurP;FPak~e z>)CJ#+sRNX*dA0=GjLBc3i%z#{(MHU>(`F4?}ZgHtpO1co5iAO!U1i)DBxM0xJsGd z-<3`s%f|>3w4sE6J@@lda>aaGmk8GA!7Jlr=080!V!!#obK4csg z$hldGr$owMmd!_sMVa8n@$b2SSlRG(E?!$`pSS92O)7M#y5p9}?rL>6hXVX`=8;%t zSD}DU2gRhQF6qi)j?(R=62$MPn1WAm(K72vh{eAUhTeeE`9^i}r3*vVWIVS^`ft%w zeF{s*7yC}g#0_9|wPgxR>&+$*Micf^*rf>O5xe!$Z$>*%(YHrkG*hU+tC;i`CUY2F z@lYiRza?O)gOpP=b}mC`Im?1)`^`tUw#ybvL`rL*q2NjVuxsMz2z?BWvPA>O&>Ed* zQ)!29W)3D1g{IUhuk}fjORB**Wqo7E;_Gq07wEX|Swf*CnRdVwn(u?bD2rD@yOt)v zjLiy~=g^#(%}GrdtEJq&OS#hSMYIfUK$y^fZ}@dqcvI-ak$o~YyI4glj>Bj!&!M!c z%c(3rW*@*&xFzMfQpY=Rb{56n@*c<+^$Tg4J2@p!Re>afc0{_0D(gyZ-domx#h*lt zMyFwcuL)O)SKCAzZx5wCod~mt$XL=^zhOtQuusiTw`i$$%wsGq8agSGk06QGF1)g_ z*|%;nm*ebreGlTYTfF|TQ;b$-i@q?sz6Hey7D~TlS zK{9IG2|O#Sv0ByP&=T1U5oq&PcRZdR9|Zlk5m*}+fJ{p5bK&&DC`AJ zc$EpDdRGlSx8kp54_mLQn#ryta#HfIEE$!5hpA(b-YQ$1Q*ByMb+c9{9|wo7Y%EZC z=)g$UBoL55NX3vyUriA##ljQoHs|-QNRFkcK6F^|qhLt$7=Ar85!&Yw$_DRie&`Cv zj5GfPKJgF_-q&!3q6A2*j)46TqEg+H!$3Z9I>-WgV|)d3ka5h&=b(o+2R_H`K(#<0 z4BxC`$i*cW7G?>1acNQ>B61jGTpIilxdCOv+ztnX_}vvx?*V+HaRJ%2D4fLDA{5Q+ z203cdK9RkWVY8cWgKLuCXrM3b$Oup9Q6(PUUl*I-AE$-A(ywX6tH|}tL%NU<%w2bn zo**-@E|=ljhR_&FaO(?pGFW|e*2kO^h_Occ<6Yj+wK;2PI%0%~ytPlVSK@~(`e{OX53ea$ER zILLA*X}uV^oSvY#qs^ca62e*6?obwE;Bve>4iRXZ#LTBI(}4iw%T%YhKCM&CH&RDu z<||Fw&_SA!bHydJphA&j8F!P6t7I#?;k$$m%s)hqr;B6r%a=~aW` z`eDS9jCxLw%W(2Luy)ysMXPB{;@uXjy09$37qq3R{{0We?ye)-TevHx$bPNpoJ=8u zTn}E`F_nA1VqCqVi8-CI;TEDdYZ7I;7Zs$Z3<6rBVpzl~9Y&B^`1fsmt(nwHhEFsW zV~ZoGEJtSG%E?BtXFt;m5uGbsNIp^+m zi8C`~Rx3Q!YA}+{m`#D0UYdV9DmMm8tavYyl}0s~(bHf8L{~Jx`U0Q`_ZoO!AH2<$|GkO}N0I$*MB&GRZed9qorI2Wq6VT= zxeku6xyuiG>6LCtfzG%Oj^Em&URakXe1FG<^N&7jMX-tc>ZM$R`jAl>F@>AG1bBqU z1oa6<3HktkB7?Y~%RzRg9WzVZ>h>x^5S3>|YIQHR^`H2LU z4Sa&LSiT~Q-Av5Q_K;4?3rqqQ4tP`gsZbHn{uzUCN-jx49`W@Mpeh+q(NK~3hSi}$ z97nw!fmMTKP&^2Kt>Hyzr2cW}-|_V5WsVVlt)fe6kllf#;j32roP2oOZxWhHQ*TA5 zak<@~MT$RI4lYwP2yY!)SRhR^wr$pAg-mS%WfvVbPX=*8oZGUZX-gbs^$#x6CxOjaZFLJ@zYN{!FCN<^$F9A?* z&oE8-+$(o&&DLJ)-VR=ZvXD==Xd5AdDYe%2#=}p%&@pw!=sPwDu!C-#J_rhy$CUiRjE{7j$KaAH#f3i1ESp^x zk2I!7l}qb9PO%t0B*a7y*gTRnosy)oR=&X8Q|T^O3=aDh#c4V6T_QZJVv77(kSWCI zfCZkwPLa@5d7myqg0{&jeJ!O|)+6c1^k*-xnO|c6JeN^qf3T zLN4K7V#=~OGPAk{xC~o}@9nT8UBp8PNAYQIm^r6MW3(@ymaR9`T?AgfK@SAyh*MKP zxJ93GNJdxa@|=E_E<>iQ4i{RoTtrwZ*0VgSEQ-~y&OoWG<;^OJeOqrHyvcH@BdlQ5l~*HK=+!qSf+gwA3czJP}+Kl09`g2aQ&qe=#q3{i7c zQFq@8E~I3C9r59zbT{&@-nhx@n;3**`o;b@XPNq93CgrE9TTkXk#qbkb zMiS@WTGZG2rGtivU9Np*^uBUR@zR0pS|es=aHNsqO4*E8o(`_$SSRgoaGyDg9JGVW zYE9gSZW)W?k8~9aemL+(SHyF$`Hovk&}qbopH8?i=19tI!sE|U?V}%Qvtng7KCTOL zeSIY2##xoPb|(<01Pu!0QzWxxe<8G^(0NXt?ZKz_Jqf9)`Qfk%wlj=nUH!wM)Ld@! zx`~lrjvr_GRPU?+xPLLK#lzqZ{~^NM;iZ)j{TwiJoy$qnaLbq>`orM~Hy=nN!KR_y zGpbzZ@I!?|TlU(*(b& z!Wt|zef>pKrNx!(dQg7~(Rh^U*6kE=3ik z)s*af=66=zrZ-Sn`4Pl;Rxo^i@^tcjDx;OM0jb*M*RF8Arn@kTt_$)MyQJ`&-eo+} zwm$|=t1X`{M$Fevok1rHa6_@iRXaydKJ2I_=Nn4Q-nYe#lLt(e94hN@(dxh<9GrG0a6GGwq z5^xXF7H?Q?%O}eCk{%!8UJM6=E>f(#la+(YVgjZD{*{{LDlO+>OePciQCnJ~Rzr$H zBP*`xtC=7J;Su3g@*`aK+GLkz5+$l-;dd<}#9c@j`=)C2ys@trmRX9IEDe}inFt#d ze547%*_T`hEVLc!P|6DkijPMwfdmnaTy@kgj%__QGu&G(Lz)IJP&qGd^DsR#7@7#k z_mIu_(LUvhH9j8Q&56BlF7!S#gco>-%_e7^vkm;ac0cQVdB^$thUZyQwT$b)&e!Hp zE6})KqgIYA3=`{nw}=T1g7?1-;|0(_7eGN9`{|x_Y#HjUo10Nxj^owNSZ~IN6QNn) z3wC2eG3DuYpHDk>G2<}iDBVQ)Z>y|kw)lV|UMGc?0%j+S+S%s<;{A{Hzu-)nshCQW zu=3oRi?iCuCaWGeA( z=I9fwq%8!KgE*W){I=%u>0^{jPaH@;1%uxYAZ`%#HiM%HLlV$GVG30ViT2%BL}C8t z_6{#1b=g)fHg~%*hhBHPE@u5umsWWd8t9KlT{wxKNZI}SbK{LhB8#d(!rJ#{u( zs;qUdx;e#?uiyO<*b+Jd>nC?zVKi?rA8(~7`NtW#h2-3ctm{0=n^z_h(aWmk%GPqhaE`wlDa2Q(Tx{6Y-h|c!6ouaLV zbK@p!r2>5xd-s00Ija_L2O`GIOzqu#)~V%~+#3uB#5K(68Q>futS*_d!1=QKx$BR? zP)E7jr*enN#M40}CafYM9{l=^>e`a5fLgg|PaeUchGmhD{9wkxYEnQt^}UPheeOXc z%nDP2ZWna`J?2BiAd#8Ie#bMf-ZG>bG@`9+j6xL#-wu^t5`5(XGwE72u0ad z7BMR_Tsm>QIg*2vF&NXt9|k6I84S@RLe<&~TEN7>Q93s_)8_)j*8Uh1bUK;k?9y$8 z4{EWD(Tt843n+;jZj3TD?(8XgMq~Mwea-CNn07w%9@CD+6}QZ-_@@b5PP_9BlArc~3YUb%!I zbrBq)u;=v@L|Hs{mL*)b$F2}rpO61aF!O;!M&k_N0(W=j4}jBaO)3GAi)UvJp=}*c zkN8DCcoU=>cbo3=O#Wkc=k1``9Iw=!4Ef#-vZ zjV{0DjcI{#!294b?kjKlOZBYxpJO=`B{1e8jf*Ij$0FMbpFiiFFBe)me4zdBmd0@8=G1^fYR0?>(Sj=emaC-q?JRvUM7loEw{@Y!r616tz-O z<@_s_o?CU+OdGK=4Sm-N8jINGKlH=4o!YGa3!?H2#f?80(%80Dx>2cKj>VYL1ie&W zD8yaMNxtL=rOWo4c-E12_oGf;x^wP`-&<_zk4XCbGG~9&LONqjcjF3Zk%jT{_Zorw zsmf7s?E7>CH814iRl5_*emOFU198b2*6bSr6dvxur0w|GMETlOP1TcoBO;WX%qdqlk9B-~sUP#bCATY!cO4&7_ zwx?>`M*dKYGU|z~&lJwL?wX;V0)<6OETvsQ?w*q;nE^E>C&oOk6gHNUM~n7X0+iF* zT(ugUX#6dGnx3L&7kEcS;sFi=-kU74l&H~jQZ3(}rbZ-*(WB!}fTTtw1fqsYNirbY z%fvAa2DgGdhYN*;LkPO`NULt(b%duEm58{w5QOJz9uU4Dp8IuU1un3pf|{EB zLnrTnuV0xyEc8gbE=1Hy6vviwi-NqPFtLkLHxNOf2LgtF8++TFyk%63N$V3ewr5y; zv=Ia5Hr}d!mQ_taySA3a=TWd&BC8F&ZS_cGP9KlccCrp!gWe2x@(wt^fgmW{*{tm<%fy|YfAz~RkCN|^Sa=vLVyedX`* zZAT)zl>aswl-}tyYJk3XF-;CLH$SO+ACd*j@11VhBYp-n-tA(VCj1Ecvu<4y_Xb`h z&l0$myEJVJFz|(!@-g6i729cqPzU_7nWHHr%Nf7tB&lN1y)Ssa-h?YBf+mOvL!&2D zU}2nL+}2@Jx6}AC-Jz3nsVvc7enL%5M&_jmiKGoM8Idz7v4JnN2dJ21S@+RtWkv^- zD(0tDkYoC>*dN1_wh~R($2ejJrU(fDa1^?taxggH!tfLbUYJf3Tv+9B>v*z3kuwtm z(yvv;VevIFA?$cqg%uyS>&c+_lH)xJ@v0zg4E>k zWnYdpgWx|6om`bce@qM|*-1OPTP^JqqP}?s@<5mH4GvOuL%j{A?;j<=hs{%7c=rzu z)oydrNmL z)0NDholvpk?XIE_`cS7Gao}kl7QcE(&bzeQ&h2Ecpia*)mVdo!yDzZ4-EA<$Aa4MY8pzy zk`B1TFO2u<;A^@g$NQuYXGJMoVA&H}7=RFh`_+CjKTJ1mZJ&o{9WQH}oACz-d0P9% zM~{wKW-bZ?Z?MH@f+YoTqG{mp1O2Iyh(3X{9`splsgn<(QOZEf;IlYODhs8AMJ5h0 zW!n&{pmTsjFypJB?_PrPBfE&z`%&ZWXgfTB=f#@={!8m}8%9h%+A`qg17pLhXHZ|I7{7TF(qOb8QEn z`1FgdFuM4|BQ)~#u*sok*4f{4#@YI|PL5YLAr{yNC_(3=tf8S5MPBV(4-(yRyDoJnL{ zS44wWZq)$6gf=J=8ulIocMAM<8MQU(nIQ5N%gVDL`FtROzyQfbVhTt3%CzWFIBNPH zI|pkHso6Eyh1^u+8t~;2_Q~={js!@OUc|oq@>@I-O+m;9v_VI5CLQ@Yv~qKHye2A&SF|S&Co_`0(b#ChSC_u5`&AumMUkkk;VV1B2l8&1HwG~p%~aOn}9wBM?1!(f!@ z5R^3TE7xC7K=l(V2%&4K9fNa70KW+qZ?l)_P$%=Ih_VsG*XTtzzlPQzm6KXqW{kvZ zvXGvE<)w#HkAP2LLMR`(LJAWfD#Am);E&ajk#d$MjCC=yhn^=zvn}dBRS?67$5k&D zq$r45mY~uSd(DMI$yB5{v)41bSrern9-a=vVIgG;`IP>pH;`i^iq6bLkbE>QZO=k) zphvn4Mi)~kntRgdD?-kGdqSYnW*q$=aG&(Hteis5R90XXkO{N{#rxNEfZ- zZFdPeNQn+OsKV$DjualkpgW@VF{Zq9R?EY#8c-D95I5ogj#uD?hjS4e+57w+mqfwE zgT0xbuQ`5yRy`ItBbMDgqM`kk%emO^FN-gB!8 zVlkoDT?zabebfNfa-K_IuwiVoYFiH)WH^iVSd2!@SZ4(^mqs%a;4VF)}H^R&Ely{LnzE5dGf`TvSe7NMrKw@rePEfx3`8`Dn1s z#}V^l`xGT&y&0seP5xBUDmx#6>cLr#+e-?xfZ3Zc6Ad#(kx^5skcBS_v&Y0w7^j;{ ziR~LeI9_}?EnU9t&wn=U5tk&HuHW1Bv5ro8?bf(IfDPCUSYAu z1{}O%zmZ{z9oq4Q(9<5Bc2|^K)`SqC@$qAS<=Iepm8-&O`*F*SpUO{qp@mQlfMl~W zLn=Tsa-EGx$VHo$DWHrYh}QeU7b(d43x|Vi;G*Q}xC=e)a1yP=v%k7A_-X>sgKOkU zgdW?72&sEd^ai?az9SI^-GH_DVi8SG{UPd}nnV=fe~Aq`6b9Jmh>)(}cMDphaJ;^* zx`WY;*7bLO_=yg#51KS&E~_83nU(JT9o~gU_()$fvK}k!+ourps+_oa4G|iJ1MV6- z9fG(}O}&xYxlk#Lfv#|tp0nr|=FD+)@bP)A1WDgM1su)Wd%07%7z_HsY0UzrdwU~i zYr5sv;3KPB^~_#$*NnN)EH)b2_v8tBWUwBB`^@M!w0$tRTSV|sDv*tTh>h_u%)M>p zC|;R9uw(sRweqYk$GY<1bj{k^263|LrF5wV#SJg=q4L1mE|&M2X&yISn2+b2!KQk1 zAU3l61xuLrq77+e|9+MEwbcI3l#_Bl4e4o1@Omo8dLW#~zJ}hvEPnk7WAaw*gFH+j zx0&=2zRhO*ROPxGwtQ}b0E6z?ltUL>XZ3K4C>COg%${9(h?mH52lG7zh!_AM-;b{{ z-w%+%xOCTBGsvb+z=G-f3HiExH`V|>dviD@O*kDrx0lI{)qeNO{;luf&(fKq z#fE-QU%9!cp6_rv;E`6qxswg5GTgCN`h_)6q*)*`zksv7lo`;t)%38`J33XJTs0l- zIru;9`FH;*-+Vjo?tY8SV@^%eysPiI69mr`>fOn7n0I6IzhUlvTXuMV;qJEcg&nd) zn}7Qg=N_HG^yLH@G4t&k_~f_N?TEnK0f#Rd2PAB-qdD*TCvsM}nbYL7zudcQY1ykZ zBSlHivrJj+MCqCF;iyUr_vcUcI0Yszd*T zCA;5Za4?B{@eV0>{leUc&x{jW0(c7h>#DgLZB#I>1jAk{H#2Uj%;jsCQh7gb9NF{INqX4HqHx(k-ZwXfxld z8d09RFn_B)bW0Nqr3LwwJR}!wubIIJLs$a-YsFOS)@`&6fEG;oR+3jM00fi*41tXv zNP*Q6>|EeL`q@MDVD~v}EuWmVE#{Dr!?FwXo{W)0N_LU*3w!Q1sYh4jE=F8^g{u~c* zrkCh-9q%}X3+p8zmAIz{H!-vZ<>9TMSLF6gwQZo!7m|JJ$v#}h7qS; z^vV1Xp_Z>8vS1!v^@=NdUujrtYvp%_P5E06r~C6BGER528G6|3JNac=EH}q21Unq_ z{Hqqq1rF;J#2>zHAqDMzZYZgwR~51$XUuPWu%`|O*W2J+yG_VG1K67D);w@fPwAK&`M1OIR37QO)nag2>317 z?Zj0U9+Y3<4t@_$li-q>$5DksxM@-}-J7up&+Jo~ipyu|K2bQ_XxhJ7Um%Oop0ITv zj{8FpW=R?Zgq$OKpg%XoZ=<9z5&G|Z;`c!lqamz1ezV-(88n22cv?l2XzZCKg}G=j zkUnzE=h;hD!<*Zi{ZB>A$JO6Ln!nXEe_K{| z7B2R`>c2N^|5at9=ILk-WL7o?{d0CQw|4=u|66hM+1%N|)ydS{8OZgoK-|IJce#D(wf!zPN7ZL(8fAVmVQg!(#`1waC<;(`p z`ZxBEv86ujSpN<5uc72eX#d)Lh*|$NQBz|D^8DwL9mx7O$j=`&Lx0PL{wKhHy!|J_ ze^=sv4auyetN>*FZ|lF~{U5DW6@V;EENuU6|Nl|V#QHzwOo|_?%q;r1q{;s8^q3{g z-KS$u zXtWw;YCQm{a5B?Rm1HqzgQwKrD}nwM8W7rx7F zV9KvSkbN#%fB=p>EzI+iUOjY-@qq_$TvPzE7NBR_!U9t2Q38D7wNo%HtwegL{{EaP zz^r|Zp<9{CdFkCho{U?Z0vZhd(;}CE9~I6X_;=O%K|Hp1$g$fbTDCA&HtamO{0g$& zfoj|P;(hw|(bN>G-+B1jQ+OR5*-`Dv8|jqW1yPWBda0CKpaLHl^G-FHbg;b#n)&(1 zOnERC%rwJ^1FAgRNVZRyc;}JV;9#)d2Y5T2kiR|gT4sZJ6oGz!g^ZLjDMDLLwc0xz zv3S0!SA8;JrT^ZqupQwcKYiPP7{h`SQ0R5_;z|~>kP=TVWL0ee#r@P80!w>eMlQWf6?GC!VwN6m%(B;|Fl(9Y634-2N z`)zqqGS&Ti#8@*Y%6taAg3S=yUU2j{7?)gljzA_Ba0VkJ!T@$hhz%fENPsjdL^1@E zG`N)rWSywc3K+a7>k7av*xC_nA<%0EQZb0j5n2yYvj@o$0Wm;I1U{@+js>t0XayT| ziHemkS{8?0h>|9@gi4?T>nSd(%!3IrC>|MynjrEtLsf!H7hIMnt}J*sNNwWD3c*W1rNv(IIL${zR>^uuJawn&S*Lf8$C3oRp>aX`Z;)=0M|r50kv z_>`XzdAJ8}htScl1y_&Fp0f(F8D%-DJ>aAtX`AZGql0b(^CAeP*ZI=KhqMdcpU|Ip zGnQnin>r3o2ht`8g)|vRVN0QgiVu4L`xb)M$DtBfqU1srhUz(>XF^*Wvm)9dLrA5V zh$$0Bf%BPyHmxC0O~#r`pGuIblQeOZ&rHe*S6jqDsfr>8Xh?~YAguhIh6+_`Yq zXhv5m6*;Pzqx?aNFE;utGbIR$uVm&8&<1adL}~ zno-+y!!)AJz9kh$IcNKDe$6j!?Fz}IT;6_x5uXCjj3;^o!EajMvar{&4H?cDR2feg zNVI9Sp|tE8j%%L#e-5PE=$rZuhgt8M)=w3!?>APKGH$wcpZW5q>({Jfw=1?!-y`3X zy->Zd!U%?Ygm)r8thl(*w1@aEqMaOWw@h6{?ZQxdQ`gSR6mMo}Pti^xO%)&@;#}e^ zFycDRe%Wpzbc$y(V~R5LaLij!UrXB6IeDH?SdKn$8?YN#UlCk=Yk8qZkwb}>`ZoN% zIPm~~8o?kUrCKvyv${Fq!Q{gFqF9JeC{id|2&2obtK66Q(fAGg&Fy*pX8H2qdHF>N zk_WN^?hw8ZQW8=FMhJlo4jsxBvcDJ5+a5&1JZDIuw}1^U_A2fcDgeicsE_sRjLXEp zQ9*U;*`n^@=iv^?X!1!ye4t%Ac4Tfu>RU9n9JagUsMO%6MJa_(-k(xF$)#v9XxIOi zjM9k$771dL5MX&zxH*+R%&p6X@1E|!@18TU>m}Ep{&Z^GD;=M%iZkrh{z6AgKti;M z`W}hVSGp%(b!*t_z6ZIS*dG3pa4yYze9_X1k>(%I5UtB{7rhIuhcKOSV zv+?pY&e|63sWE@#@1&zBGAM(!5$dh$Hb7G5Ib$jlX#2On(|_BK6OG=CzW8xkaJsvK zy4?PRz4mgR+aOnlE>-ERwJN&n_qJ`{b)Cf80qvw$FUKXvqs<96?Z0j;sN|~DbQxLJ zU+fQwwTh{1cQQ`tBHIqyV%eUpThv!tuceR~%-)%d?|j`+qWqO`vZ?K>`LsT9A9B|D z*w*wi~T96K#XlnW`=Q%Dsu}{Ojg+&C@OoW8E)CC|0p%u?=h`b)B-+ z)>4bb$A!m%__68xoyXqIXIVdo*Ot3C?fmBf(GY_$Ld2Ma9sVN^$~Kjvc7w*hwk!Il zPx6o3xSMk$Qp;AAF`(j-e`4^VCOSr#t^+hKP)$V>7c6i&m6Zgg_KT>8d zXnlm_A?3Z=8GaDN+ZQz4g?x4ie}QNVl_(G(G* zaK^jOZPa~Qdi@wkZaRJnD>H*P$KCH*Y$){VTO>|6pQejYTf^_Utg4!-jq$*gYJ;m* zr_!~~msjznsh`zRZ>Fca`PA@AblGLXm2ZoW z%NC`bx2L(wM$`2XpxCe$apw1=r)s5ssOi#addUXKW2s81>8Piub+6jn!OQWel=@4;-A3|3VcBJ|DfT&xcjf{1ER}_ zi;EdMo0|by|HbjyMv1v1N7nK^%;|9|nj{(r;d|E3B5 zf^czT7h_uo(7(LI`F{w>f5G;@2><^H#Qz}x%&M*?F8}bEziwDQ_=Ek&J^@ztAC6?q zKA4M@izlP>U##tH`auAU?Op!%`Ur~kAI6~%&-{1J|9aAq)6w}XL9gm*XX0S{!B!m9 z?XCXVbAa_VbiXas1Q();evE@?};;c6UMC5q} z#!%O6{LV3~Op~D|#XDc--Ccmf$+LqB@Bx`kHT0d24gpAH&ypAtP{>b(n0+g6%HxDXLEp26urUM6Q%29If*N(k{f2y_ZZskNkBdDY<|$;w zV{hT`&u$W*%|TWl)Yub9Bl^LC&1r$mN=|0xPJfew=0C~tAyjpBbhI_M`%8maK5`Vu ztO;cMmpC#@Xnt@=78dw_$mZW1a|MwaHm-~N)Q#7{wAc_C4r2NCf1vhn^i zDhH5kgfU0q?kqjX1@!No8{xB{P$IG`M1meMc7+K)zt)xx<3Je zyTby4ySoQ>2)=L+?yztO?oM!bx8UyX&cfZ@{j%>q59jSX)*Q3D$Ecb$M^$y#*G!^@ z_EM%6X6DX6I9b2aQ0NVPWz=U=FS?3&E_* zk8Qp_`Y+qC{;#9|Ut0OUs}BFiPrg?9|NZ2DMV23IJe-_g>;1pnX0HQ5N7eL0=!5?- zBbBH7Kgf6_8OQFKD|JXWzX_velu-C#@71*JXdM6qR>ht@TFD}BhUmAxLT2B^%GbdUkDHs94O6L3S+{FK*^f@I{8P^v zY=P(^UiN6Aw%76LeS%tqP4TGs|LM#6$ctkcZU=5eMYI^0R^G8y;-Wl~h%`SB1aUx9 ze&RW48sQpW*Om3&ww$hRbD}G6DqGW)^7HSyGNC(8A%rT*(4It0t!wjy#J(a8@2XnF zHC#Bli|Fiy7TN3z#cIICrbvFXAW_SQ(EQ$}Cb@ZmGy78iRUBGTWXwm6!16G#;fyRs4X z)Lz*-3=+OMCo6z-=#OYTF>QP?b{!`-AsAx{yz1oyORI`)=^ZSR4IvlHe~R@EYuLx& zr^a?k{2Ckbp)5|W>}(C*@|n&BU*98(%*WX0bcYqPeUGbhXlwt(JLPvzSQA-{12Kl1 z#1T2dJO>I&HqLsE(1R5w$<8cp0LOhiG2^7zbupJDqI))u{~eyM5lAV?iG&F)iDJhg z_Jf7FFTUGCzg-p!^hZSOWaY)g66!#%i{D87Xi+*M$xZ;=eAAci9obzYG%2k~B1^-s zgDG{c|Bl&jAHh9Y8R11TP6k)DIx<#}en$59P4fa-9)MRsCq?s&!6SbV>#ifX^7Ezz zbOZ06-YNC@b86c80_wO>^iJMVy*3{xK77AbAbC%kI?O<2u53aYM*8g%k&BE!Ru1z0 zjQ;zjT?rAyXXzcka!@?X$nPg1sqr$~=GG_89P*4e6zM@0qzlI8G_{d}WNXsnJsUNm z6$toCCGEr-oaaMx?u#@v@5F)g9k^=>-(0Q|GU-@*GS?6f!kZKI_0e}fZSk}b9G!nB z&@X~3IbaxmuVZ92wq(W36nfI*GEcM}7!!Yk&1if$^6c{2k?JFQg^<=2q3{W%1x*o}&;JfCRfGT0?Kk0Zc+rAcUTxqfb(C6f!y=mdn22 z++m#Bo*sMjuexu4uc-cW?XxHMn0pOWNgW~ANLQ_-rKvQ1EQhy}O^vG39|P~OYEM|^ zQ51}7DIrpca}|k2wVgTu4KPCFLchPuSEwv!jCLZ5Tyc@84ul93=8f}Ha?BOsp;VE&U!IWS$WVRm%qLI%j5YrwrNs<#wc*$g5+*8l} z7rL5EeWecTrWA{EnsT5zR;#40rg}qO$4~=V2OSE~l&%s>Tn$>h>!Ai5E18LYQwLO4Qu_YW(q}g}wz;mPwXx&^ zt8#}Ldb2#@MDL#V&%bf4ZhoUUsJQF-`ic$t-Dc_jx& zNIU#!83Jv%gt_m;`tk2^BJ2oSn}&N1@dj^j9qkodBc7t9DqWcY;k}V{uPbyL=0fL% zny#vjk}B7ZPajhILdCG;Gz&Bu_TQF``Dihds@*hFOnp@~&)!VK?RKHkI`zM*m>m>J zs@e!+s88BcCwcL8_(7p3bvsQR@HO3PCuK#j7n|;W>AiU}RxT|&K9Z1Ncn!??54}EC z>KgSoVU^~J##t?GkI@bzO}JZOi_7RW?Q;0f)rtMCikBD#bA($ups~B%`~Y|?J7WUM zkj~ooLAC6^M|g_M7zq=kVttibYZoOo=@|>IAe^KpNc)SOUM)4J!CQC?d!HlsAQyH`YjX3$>T};(~4TFh5 zY}U;3or~tB9fP0Jha0VaSIvjQT0kn9rlbpJY^GbIM)VCv21aZcRyH3AI%-(Gdfj!F zT=+^}-dc4{)9O&uSlQ@DJA93ZcGzFiyK!XM34dKsyU1%D(`dQ13dz`OGxDuu4p;Y! zMzjqcf;w2@W#`J>VCk)^O~Y$~86vX&96Bz_j=BFl=wK`SsftHbNQxHY_S?Li!%{7n zHlPJ+AG6HiGfK21_!A9eP8ll6&)F)pUpsT|($oiTv3=#|EMr}}zj_@#r6M8_;IvE- z*uW5SEO+8N+pbcwN?4z3fLTK>XXTF}(<8Wvc3Pt2$($=0pugvA@-E|U@*W>z5E(b( zY->HAD_JMyms#(c^$NYsII!?(Jg|7uA9xkoz2QE5fctE53-k=n&2hn7SJ|j;J2x(F z1@h-@3?5xki?=k#}?8b-3%Ru=M|&wAFt9pDbVCih8` z5|6~zbJ5Y6H;zM92YQ{hiF{R?X2%@*{pky}0l4Q2{n}lb67UwHDFDMCiG3KppCDqj zI*jXDy(7RqJ4Bxs;mMD(=2IJ8YV)d3WW;#@gLG<>C7w;L_ku89xcBH(=r`|voS z*s~k&L9}{K%p2~xTzvR__A!uxyY*DjYl&kN^Ya>SS^NG}t7*J=K zk0LK*b0M{;&}tr|?=&NI7FZ$}iVFlh?R$wG7jIlLpqwE90PsSn^K5RQ!vT!yPLG}{ zB(KLn$aIUqr!g7;J*5K)XWO5nM&aJm^KTgAm~5G`KvtZN#r}+(xDyY%o=gw&Z?_y2 zoLSF6R_W#t9&y!+R=?-R0(|6st9)($01;mFdXH8s2H%8KndSdlE9*|BmXWp+Po9!y zf3Qf%aVXA73+U2F7GWcwty6@YDib085FVDLO2@>1w^wX)AQ2NYU!kE6x$IyOV29R`%EGxE zm}osaZGBz>t(iH{FxB0Db@k?R`fFfcc|bl=!9W3YRAY{<3OfvbAuukmXEw}>%6@NL zn$KU65D6~JE}YlF!@POBu}z$~57g(a93BQhPlvKjEAv9sM$&$uW+!rpYl` zx>$*AwtCXi20d)>v2!r<)caC^a+ z8akwWJ({FM@=ogXsZ)&2o%tCya&)VgS^2w$*ag{A9;x4HtvY)#ir~bIJ!|e`@)u@V z%rS>_d^Jj(d?xQS^%|Aw@LmoImfx<{@wB?dnCEips0;PB_+dGYS z2aUB!*`8ehUq~{y-fb8knGM{xsP9x!4un27r}@nm)tj6>Xbl4zAyxB>hU6y$W+-?& zo(NOx++WRkR7_%b2PMOs(!OM% zI`_WHa@zde*=_5=BWi(sEFuJd!^-{+S`2aFY|YuZ#!hnLx@1>R4~MYWGsGkRd*}m- zPn`G3mVe`i5OId@S#``&a+ho8BnZM-(Kj(Og*=i%rVE*qYuYd_*@YD%s^EGHa7xVK z^$J}_Grdwx0ANTP^pVI{ucv!Y!zl237AxLNua@U-<{H*dXJ*AwhI?xpKbi;~3XK9A zN)MV6aUElP~=QEs!x zH`heu^9~fwqfwi_WHf!VA6 z>L-B4E5bjKrJ5aarp%Q06)`qPmoMgF&rX{Adq+e&$LYbeE+?~dXH{=Bey zF2PObiHHc-M@}eT-yw0%ej|gJ%MW3v$njsZdq$Y-7PeEW4$-5^WG~hyLNu){MN^v9 zo>q(e+WVSK9E0bjWHwn?OeBVt^&n{*cOu*+4_#=n>Z-ZWbN`3BE+`q!P?!RGi zoQG zah0OtK2VRs(VUedN-88i&sBMc?k*+2?}XRUm4Q8fqUiOa!27)ud!W?*z3*CoL)EK^ zZtIOOPwbXG5EeFDDZ=`YZ->>`eiU_sBkGGtHfQ(4aiVuSepjT9am1Jr%!d%B5b2Ta^nltL@_`zp- z*=3{ORpPXH2PO-!f^mmP-BILC+ufuOQn;y@-gh9AJ=`?oh64ST1z-34;+bAe`YXwd z=EMHe6}7A09shNeCY&kHX8-tBvMueG%?rRe+whJqp$_4frrBe@Hk7U*ZKx^l8n2QA zkwMByVEhu`92jyz%eb)#pBt%@TEBBo9nWwX{kzVxdwxX;865?B4c!_B12MS5vOc`{ zi?8ws$7G8o6TxB>W8TH%ODn@$1Lsni`(%2ECI5c( z8I%9i&xv5B%u4cX?Y(yt`=jwk(Kuwohg*jbUncTjOZ0rNl3u--2tE#z1m6Wa@-O*P zh!a)bD^l%x2u_4IIB>ZEY`p!@Z*JT{+4XLnD}R3p2{H_Rn$&U4@C89UP#Y8#TZP^t z{DUz#@K@^f4LF%f(%t=YCud2{$A=S-oC2H|sW&cP-(zQ_}^NU@wXQR-bBI&om z*XLN|j!2!z+%z8np5LxFA}GYPzowe5<8JW2P%y5_s;=1wJCgr8ACxk65cCSn&fTPF zQRG@}?0>>UXplC zp}eZvye0I|34=+X_us?;>$W0XhG79S=wPt7Xuz%tLuDQd?+i(r@tbo}6mCKc)Vf>C zn6}WyX4Mt?U0mTPYl~G>S06Wtk!8+$7CN*ZK(_;8%k+eMaIBo-9ebBNf55k$70P)}+jlLsuv+J8l5tCgQ-$=BrKMhX57&#f<9&yK#DWyaixwY3k;wCFU{(J4l2 zCnx8H3QB%J_7lQn2-`+Erex6@v^XznV_=I48+u_7D<`Y2`X$^|B=cw#1|HQ!M0oR>?5*NReKC$(F}8)K+bT z6}YUa67HJ1vc&a7FiOqe_$T1hYFK$4m$F~Y{%a%C*&aCA5f^Z8k(NbnJmKU4T>6%V zUK<7M#!8bW;p%1^8xVq1nv9oKjbmW5b^Se9RvIFcDX;t|&>f*{B2i!CT%v8Rt?!Za zWQaGTID;9GuKYh{13lsr-Ltj1eyGzoDZ>BUBrZNDk(iea8L)LRr$XU4?Tf0E*}Oct zx7+hVKHX4$5v14>kKC=d#9{Kda@5)$Xl)}Ke*v7B2I5#QA5F*CfUah1j?bhza81HS zEA-lRZN@v>^@)jQaI9VI*jrQ(zfLkHXp%RsJ{|-lFTt*0?35)}Ejg!8gw&`MD7*2P zM9;LkS+Ir;S%(asnx;a9!9Yf0Z4J<#t_(^WYXGS)0STV>0{m{8RgohZ2J`qT(SA6U z|McEG?zbq+`#{-O4g}vSriwwX5{eQ8ZQ8G>r%W{cV~brQXobg>2JhnJYc68SD%qW) z#p$85gC)jS81E+D5$)~(yPK`B{(;&LqeV1=!96rRiI*`g!a) zL)+nrG#$_S0+)5EOpPT1r6GV#8LW0RWn3jjK(}~!+p11T$vFNujU=D*%66zmoxotk zY^=I!m47zKP4F&*ZY{;k()!@IQnaD1<#kP2C7HGrihz&@~|Jgt8Wn-kNJVi@Gi z{HDlHed&JwcnUwgjO8cPJ7)?iaZ~3i@omQQ z&d8ui<;W~VYFCJCd;R2TQULGOtnZA&qTcLUKF=VgMK9q*^sW-Jq@CSVYVNZYAUzm_ ze0(5TnTpwLVNNZ>wuc)H52(ZBJ_{uBvTI!O(*7l>ub6X)vqOGbc(H;2}GAt&^J z3E6OTY+Y5*-&+I=IC@PZ>7j|IZBIEEdU#kfX_I#gbj`BFqUUTPW|T7EX(!eyPy4pDxd9|Z8>1EbF^9M~&ggl`)f~wZw5AMDx`$pIH*PO&a_Mkv` zy{qo=(@!EjpC2e>Go?RT-DW-z+_!U{-3VJCX5Vxi>B131$$q_c6H#8B)HJ1-q`4lLg+xX!;T5 zS^Q<8;vD4N4*{9Y+{?MH+0Vk{#CJt~TT-qdHb*oa#N@!tYx)bbWelc6b$hF37agjm z%+-nW!>nDO0m7Y)EuW!#C*OTW$G-M(*CD~;=%ufi+Q8@gL;v9onin9u_wef3i=r#s zuFs02?b+;E|GN6h`z`&A?=Ab;>8<$f@GUk6y}gFa7PScWHW1g)FO~)vWZG+KSXra# z26X$zw+-4x+J5Y{*!B%X=v|^!+Aoe*Vt34#{ zt<&st035-L!8heIId4agzuPVnO9YJGP%j2_o_en)|GqRd$l3m?J9Wq}(K1h2w0^%{EMK`dk*+tTi0vMCU3jSe zpcyvMOO>x1A)RwqGC0~dp>pXaR@UFy2G{Qs1#j@+kr|$XCHK=(CZ$`z=mUbnqaOSB zo#;0D3O9rOZmS&*qGVm$V07zXCI1=GZphzS)Bfko#GmRxEX~wmN1=buw2PkVn@%K@ zedajzPAQBp<>O#~;BiAcHTFR(rRb)N{4gpWbuVY{tqzgOd2CH!BraZZ@;4{!ny&h|MC)vNE#@lnl@s|2VUBqU+`xe>yP!; z+g8a(Bhka@branlPluJHNy^MT6oUsu6=L4~e+N?%K3k_a$9CI))p_TL>;}(^w}kZ~Hx5 zg@pbwR&Lfc(O@TH3gQ4d+d#G-i6NlD?57F6+dh@G9NWUIhL*?e-FT*85_%KScjdNx z?i@LUCLCM2NiJIfbho_6odKpzoE@uP)&M9Y=2H{MdwE|APs;gJqkKUP>K31=_%65( zqUwt?@VW15cOQm~;H<-`*7~8H#mAMQ`xM5=#nL;YLNa42B12@n4Z#l1LG|XQ<+4%- zCB3(2ifPyCd@!ds(0lXsl8YN47|nUngem>&EmLN1q#MJL%;CQ;v+z62xCUW`Zc?F&N@z&Q2MckJ} zDcWYCIP3g)`Z1k{kaU3(onkH^5O?p@L>R^gp2s#v z3dhxfM`qN|JOqT~s+W%Me$TAtrmJH(xx2#3Zx%{yN>902a5)&KP$$;E*bro(kG8>) zn^Ye-d)8F#kx4sIk5C=i{zBhNXNPDYJMnj^%Tb}Wu<~Rue*bu&OME)Y6SM647{jOr z)qz+u(O>fkrzDW_LH^41STuI~Q|i$n($!RXBrZ#~x(SB=VyX$OY6V*jxJt!&)o2r5!Qc({>dkBu<^p1nA!*oe zqt=g|RvsHlO)99Z>k5U~nJehoUpLay=r3PXe{wu6sEJofU4+CQ=X!x(rI}kPxV_+! ziAn6!%_Q%OWdYJS8GKUPGGw>RSb`9IpL2V$he{f^`-Sete{n z8KD^GvLH!B>{mhzNe^lj!fy&nQH`WOW4`0}buGBVjF zXgn5a{niHdl@15<$2Y&dH!Upp;`j~@uljK5F2ay3?HoK@(dVR|npQ>?{6(ZyPEhju zcg80@|7^KN87BVfl81R+r{sdsJ#h@ystUWaQHa=BRY)T@kC%?LHT{ELAjlU%S39~(<|Nc7()WQap*KRiLf8{PULXTHb)e_4&kem`@D;5)5=yQDHC;s) zwU)HL3fA6l{jy>|XWGo@zv=~fsr7#tb5rj?=2U-`33P=oi=vzvbYuQ5dDlk>A`%u- z9kJad-)Yo`5Ea=?HyvH-YRP2JG98(oY{A|cruYoT2zc=bs5=XcX?C4|x`Nn|qUeD}OtEldhOm5Vku82zC38=nu*u z#W>e!IR$)AXxgHS#P}BYlLVMTy9R4hlnzaHmr5Eab;O<;2qb}!gm0{X*(pFQ{P>pmvYe9cQ%=HBM;tBfQ8A>jI~clHhKGElrLar-Mm4$*Tv@95P~?tF zm)H*OvqUbJI?SyAvtyRys8>0%3a;?Zi4!c`;8$p8oC+Ng_|btPt9Vuj$Hu}Sbf#r` z;o+XB-)huIWT&16$Al)Asm<=XwbW<$MY1ZCLcc9Khz-zfk7DIYjS;Ozo0A!;?c+*# zp?r|+4Snx?-n4UWJ--xVLtDXmVZeYFA;-4dG5Ia7x6BxQy8N8*b6~*h!*BaF6!C0zBEesRgX-)$pHtP2wS@O7#VSM`%kgqmsGFxm0J9&A><1S4a z2va!Hx{Cg8tqv0h4^%#~Z6>!0jCau%WM03HZp~Uq&PjX79(cT<1Jl1->Kgw)4gUTXow-za%LZlIbWJc4OabCLx~}*Ac@h>uk$o&GeUkI^Of% z#($51ul|==%0r=g<=vX2VHbhZVr$)004WE)oP1~N>kX0YY=O4Vpz-E& zL+J_~(d2d;=I7<^*Xn|%O1M?W;1c~7c2m|Td3cLz?`bBNrmg%21VQShny#1HJ*xNk z+3aN^9XDqi@H|=OS`s-YFCr6B{Juorq--FR&lfo{`(bY$`K*!1a*uG<8)YNou+XIn!~UhuaysW$I!Z)1vrbKFDh`a#kbxoF#V?n;X%qM*+@LxR$U zymt5_#icJjoNVkdHP^jERJ67E=S`ARq<*SB%6c`PVCk+9o%c>_^Mj2~(IBcyLUw71 z56+?Jjql`>uF$(XMxghnXU6?%()(h2zRunEA+Rw)BOXI_=O@)r;cmI0*8K;Ypm!MXni zW$0Y>#Fcx~z-WIk$0qNQ^_^L=Sz0jEn|Bp#NCP-GaHgh7EtR^s$- zn`mfZK~a8w62Q#6I59rz)_-yB+^(@0X?q!?Et&U=5$9$xUj+?5AN2S13@3c)Xdv1# zodYEIbqhhW2^7O)-S&w`lFNjfsR_xE)mdReIU=3asm+qp!CVKiW)=K%F`}jq0HI7KDPLT_I@tZC#)>k=-phEV@NUJx8$3 z-Gw3rPN{Na@A%!}SQiY%^E_fQdZ^+j6CzAvxv66WxQTfol+{r8%20U`;urWm=s>j? z=B&C<$Fw0Iky_?xy714I6de(q)7a*JT&E{uYlsTkj(6{9Uijacq<~%O>^+{jNFTe= z`FBw74D}&jl)!oy z3?YBrW61H#HZBmW4^pY&XQK+8h5 z_z#Hjnt|i^um_PF%_i=0{-%627zF_80@GM4tutggCucR`)6jYa_(Yb3KQ{ z+j~SBN$CiXQaX`#&{j#1d$i3!yb9-}_~S*kGhLYaa}uuWY4o4mQ|#?%DqGMwyX~Zi zz^w$_{P=mO;mOYc*PoEydDmIr2|~3#kCnDRuLC6_%YXg#?`fA_Mwz|w4UOwACf7Gy z#OCN0_4T{LU)eZ{WkMa=@l4gI zTj0!7XAw(Q}CIHzH(W5fmV&aLJ zWfq5{2>YYfd?RdLin1%*W`r-hiVIldD|$%SK6Hc4=!RK<_U1U<{>jkNwxVsg0YM=0 ziN{(=ieq0?O)C;XQ1VrzOM#L3r+MDvGATwdct*9FGZIdv>lAJE?+?wE1@1gh>sxSF z+>MNh!0IqA2QB?ZwZZoJQ+F6Nr|Y0WoQ#pJGt|6=$?)5_TqD=2O(HR(`EvhiDojbp zS;NKnA4dD-wxR7SkUccccjzd-Y$nPG zZTzOU#>N@kyolzgGZ&MNZtCRe%<+v_{c?tv3fnj~c{|D*W+L@pGXbe6|M~!b6>GaO z^)F=W&b75dP^EvO0hjP^;4peTbXJ-yd?xTGoNm0f1bE=TusC!1;>F2_?*>I$T$x0B z9FUwtp!O|f$dl{tA=*_JOAbZ)p)3518C$dxfC1*61cFb8?grRiv#28-K*g|b$u|>i zl9YdcP?r@jp>B#1N;UrXQn_1T7 zmO(w$I)hr^O+wlX<6y-eH5nXGPJ&f|SOHOi{^L=!#~C`psX#jKS)yb8K7L^Qsxj@q zs6Td%AmW)?k)Hxg1W_O!kqPJrZDmaQGrf61HWB6%29Jo^V$sU`IMdE+*pb?cZ)F-a z-PDFgsgXt`+{d?|;m8=?Peu`#sCRm0=!kvR@9v1$8q)zx+vzbS@*O`S8iPTxK2Oxa zPFl+c^%0<>7s(+=gdiWYKNt}bD&K4h<$WybFd`h1gkq7KmhP`#vo&OoDIY~Dh`ZdeOHK->j6j!=VI1lYjgP$bC28Lg7R`7NU zY%S(oiO(TzbQ}QAcX6Y5TRNdEkA#A^yM)g;?^)1$*I>I$sNa?cZ+DtRb({& z0iH<|>Xx+duBuL{hV=P#ZPS&8zsyAupHGH#S`TE>iYee>g zAM7|9#a?rCQ?Awt(d-QGxVRZ%k)k0=2PBu!W&FLJJ)jY~eui|2tJj#vlLQRei{u&e zz`<^vryyX`)4O!+Rj8jcoGeUh#xhK|hSkBus!vdS{UxVC;u)j~e&W9ntZ?{Z?nkj1 zQW?s^T$alNmnCbtO*8NuWYU>a4GoQef^`XHC5h`rA6lyNbKjQU&Ks_*+r$YwYD{|q`_x;hZoPpYM zV(j?2C{r=@2;SYOaF+9~kp_NK*cKyR{3JbEQ9Dle&n@Hp6Y#ah+S*n}JP zo94BM8G`Gl{YKq#k*XViY3~8A^APlM*0wO)2FPiFI{C}v&Xazz6F~!+Vhj(^!|>Sg zLl{<(sw$*;D|jAq8gUL4rwa!*it3BKi>L56*+e@6F5jr-0m(Ec>vCvy@Mh7XTvx2l-Y>GCzym{vBd;Kk&Fo^NoNycudY-)tRH-3D%M<#gvBiSE3xUN5d7mKWK=+9FsyPQKfEB2+~A^O!P2F zqz9@PJwM6~96F2*=&{MMfJgcXuev~U(R7L08tPkE54xIATau8}wJ>)vyR+Ic0sKnL ztzLg`3giT2!4;!cf9Ptw2=TyLwJGAo;6}G!(sjVL{MYo?Ok=8amG=$~$EjMj0HyS# zsBtou-v)+g0sZRUnQ8ga5QlDtdy0<<(Sl5KEW=tuED@1II^pj9dl`}@aEjxp6$3T) zl5Nc5>4W2BQ4ZiFV@}o7yLI5v#+f_zH!LtTj3bBEMha7o?y^$!tbDzMFQ82sWWX2qOwY$^KkKqApu0(beB4={H<85Zgd3^ z4(1`TOeW%;1~GN)fg@YSHUG)Pt8`xFvY@Uj^|;}e)kip3pIJNHqcLnU&zy67W|xo;`39hL>HzOPl=qTirH{>3#+Gj-+YJ~igNGg@eLqWqJBXm z%*MEi#44vs{^;+Oa^pkvVhIrcJ5CgcM9=5_?*O84a7VzL;MyWFbq!7?%8f8}fwH!n znf@pAUkYb}x8-FEM=E)GJl2G$@0@y1+_mP0yU-6`!7y*g0H_Isig(o?ap|Oky9GJ& zhs8esdk}^{j(9%6+l)EXctQ|&|9mT*iF=Y8S;BC8gROb6&HaZZb$G>g7Zf(EE1)PH z5FlmtYOGk?bRZX9g0ggHN$-TB(z3bXRHPspskf2PegN};ECzwV%iaH5o>sDUVdy`) zIA(eh{X6cnZ@KT|W>5%(MSF%ELX3YZS6uo?XDY9W{t-EF2Xp&#wDEtBpgTqLW3Mxz zj-&=QpE8az-0<+rB%~`5B9bS^$yNANvEHav`EJ=S5QF2a%%l|gl+ONxl1-`xr+Ufx zf%sN7IO1unTJnPpuNfpjFB3zIV;s4Ry)7&ov3y+?61ywFHv75lORqf$XasUXQG9GQ zA$SCniWEBF)%Y0Zl`b&lLz+JJxB2qeu?9HkbNTJVr|su>dF>x+B%vdWC=RPc z!jM|QGd*?wc0BB9@F2IpqJJTx z&ZsEWDZZft^K=fr%b6osx;T6N{>DIOAIJ#1Q+=VFAK=UI$ajT2hhgixUY(IUzb^0g z?!CjpV@bpTuk3ZR6)cVCx1pnVlvb7&qfbbBpI=!*^sJ{}ut`hxoN-2>NvWzmUW?>e zNvK6ekaxcBTeHXqv9vcd!Wb6)*=H&+QZ-eSr8B>@a8WH0W^Vd{`-Ce-(G$tKJ}Gs-&rQU*=L)S+-twsM=B1q-Lg?T@Kxl?NP^zcv)9ecBz_Nu2H&FdZ}@# z(p4f@=A-c*_mbg(O53TIR+{#lMm~|520sBmp_}H(fnt$0`=;fDYIJ^@wrRPs_@?Bf zb&E5h&yj83iS4e0>5><7#3TdU4hofEQH{jR?+3ELNm4!s|DFt;dYr#hza_oz(f*y) zPP~D7Z-CGG^pH!1Qt2D`b0~F*6qBlr7p2Gs63P5Qf!Y&tG2|o^<@&&RdhfB92HkG2 zWOs0PL&Kd8(=LuxsGmsEWt0YfiG)afm;0)*^rn+xETW^9&QVWhqnVcEtV5;UEZp0J z7@&2M@0F<(1cR4lop3aScY=h(-p(MWb_Am}nf$0W2}diip*#RrY0YGg!UC_kqO}aK zo1qtEpNH|bbxC#9v%q~)Y(HM2iaZ%|>lYJ)&Y5*f_9RGsFYdl!@@>QYN?pM#0DZf2 z+2+A;bFZJEdo;JVt(F!5E6R`qee@?IU1A1zsRkET1shT?UrX9{nf~S5D@E2D+0Te5 z)F;qg497Cfvx0Gb26;~~`7s}v*X5r}>Y#);(Fqu;kv)RV#1F&YWcs~roTQE4GxRp8 z#nBom3KI|E6&;^FH$z)FubY}Jc1x&+2#Gaypmk^l>cQ;zkeggQ6M#~H?7hymw&&xS zH`!eSUn3Vt1nGT4s58P99z$QJ{r=q#yM;qkYgS+bzx!5CVRkx^ z&1&+ox4z6U2HtU(oXyJkc^F&5Xx>n`zAuY~@O&FFQ^(`uk~|KMF0W4u;VyW`@ALq1 z9#1Jl@uqC;o352*1j!RlSH%Qb`VzZ|Z{z2H>jpes>uu*&?^3om=>bl)Nw$<-TiaEw z=-L=@%H!{FZ9!yh-21 zPE~8>-&yoo+46d5JdRj;ANY_Zdgw^r}APmG=N>W^gO)4pV)kGuEE zuFg}gAzzQnm5r==7qBeDYLeK7r0cw}hV~K-{0wA3l+I2rBctO*2BF!b zSGb4!=WGEli9%`ekIk2lkrJFAMfE0=dph*K`P;HUgp`~td2wlp9~lK~7&v0Cq8(e& zc)wq33E0Jx;xvSu3RunN?|Ktd5DV?3uDZXYRZUWlP7Du-gch3pr*DJL5cIeb`qP5k z-{_xmBKl?U#SLzN^3h#eTd`Q89%t0`2bGbIfSV|n z5os!vdcX)~I|mnrwpA`}%wb&i&-=mBktm)vXb=r<&N+7>ZJQNF*%P8jSjtEhC4sL{QB=Y&1>@gd{2vm}`h=ya%yxVNnMAsO_!@bb$)(E%G+;%VI zFPhf)o@Ab~TTohJS`=HRu1xJNF<+a%gvz9{*wvz@-q4RxewL7Vylb zpD_(9NxMJ6s1W5fZ+|_Cr7yqtgP*pgZk|4RD;&bcjA#=k1ZAw}dBEOGZ+!o*t4xd{ ziwy;2>cCTYb~&)y02}2(#%2C503&*TEWijv9goD`vOUCYLN)4gUH&V$X#y`KQa|HK zCbYNQ(Ipqc7sSnCs4t1b^LJ~{Z-2bgU{axI;an{2FNa4BQ^Bp9JG$W(mcEsld#><* zg!`ktZjF}#OcPt%4e%t1;(B;?l_E zRQEyU-&&t(jGCBDZ;mhF`30;F{O1A3|1I*mYZLT zXfahP(*A#py#sV*&AO-^+qP}nHafO#+qP}HW7~Ge>7-+u9p3b}_dee~_v~~3f2=Xr zNY$)*SJkXJ#u_X2%;(jnCzU8!7D6apg`m*P^J13JPE-oD5|dMCrF7dpwo$abl#h=C zp9Ggg@bRH@R6m^nY}s|WTL~}DX%{#>EGs=MK5(9NK<<=vXh#kTEPl52vXpD(wKY_* zr8D%1{RS0zMY-5%{s=UkyNGysF$Ic|PUf1l`EaI@EA2=I?lO6{BCie4r+o=Lz!VN9!SN110y(#Qf z?_2KbnD=)k@nCkz`rSKJLLA$+_kDRF2k(+Cd90h(1GKiQJ_|%BNxT6k`xd8!*x9)u z+x~Xwqnhup_N&bHroWRpH1Ig54%y?q;?2Og6_-6e;P(+<2-b$J z-}*gyKUqAmZfw=M1*i;;+7}KWxX0e#j*0<4#!p`rZ3%k@u}>MQ%Hj>5yNOY_W(a!a zf8kTSg-rEn|E80UVzGn*`Eg?0PEDU`7kkatEqI6iZBWjY-ZY^sewJr{Wms;BSG(gB zuR(I@=vgR5R4Al%9A^h6V?<5`Kcj#Pp64-1VpE)O3pNv5|0w}mWpT`LRby<=v;gdA zatPfbP}yo+yV^k-sbs_ZshYyEv+Nq6Saf)6QnpJ@yYX3#e1#l%0~E zysfdOcRnKUV(Trr&Y);9~F9z9s#`8z*MOrNYPE$?@mzXl$pJA6dz76 zME2uO>k~fpleOy4KrZiW?9wE$U}{{+(qZ;J5gjvTWn}R)0XC{L#tXpSmjI8|7a)OY zUdnmgxr5Qq84HgZulP=tYDu1Ias5sv>1$F1U^Lb08Q%NnvOGwj@hcFkM$F+zck8~T z?nHQ#TbQ9$LA+jVhRl9u>9;d*V4l<)Eh8PO;HNO6aOEare|URj;QuIXYNsUlul`pE~amIkhmBb}%qIi<+!vqhcNo z{5Y@dN=xxBXT%DA3}OCj#z)U zV6>-(VwP?t?S#A-l{&N%a%dd#y*fHCDM>e%m7cnuuZDxUo`aUAy@8{Nh-oEVIZZuL zIjh&xKt)DIQqcp)B4L5<9;v?d}tE-ri?jh2bbW@6KG$&CZ6LsWy5QjLL$bXsPkEgfB}iq>=p zCnux^G?mcV>Fq#+>T)pYk?Dx|QJF}!OceXkff{L9*g+=oVj()F9bCA;<6p@l@ zmecOt5smDm9t*dV#zCUCk&ddahlPo(sj6owClmkAR9#&Kt$2JLWhFIbT}=hXGFL%s zZA~9T9obmcCKeic#0M-aET#A^?+8{J!gVYx%^Y4cv4AC>l~i=y%tS<0^i2G`T%F7| z0=CvdmRcrGYBJ_73f@|p^-PSUZtJDQL=-DeVvKlW6p`5>T+U z64O)F^ev|3qiCk$%cw(UN2>Ujw&c_}$K8mU>`4Au_Q19i#K zYZ{VOP7S6slp5KFQ<1W@G@`kv)Q!7$sRx+ENBgED!KIjuhK@Cpjf;*{i48I1(A5qW z2lXM7m3wDWNNC@4ZJ@Q7Ivd!yeRdMFyRu0mTu4*aL{CH`A_|tPMG-m2Pn;IbMt>xi zCezg&9(ELc?qsmqu3qL(R z4W*Nd-J>rmXt=fTmYpuTrZMg?>;%;q*@%2(8j`w|jjWfMt(2bHXsKeVE~IJNU$``h zhN9KD06l<4YJz1%M7?KZT3m(_YC=AotZE!GQbtY(Cv2phn4!_ZVdP;UyPDeBM|GyecN895z=H0L*{ctjbJ0;!>~=H%qqa7416C{4`VXcHkl zr%p8}Y)2QHr=)~~i+58_R=HjX3K?}*HGxJqKBZNU;sf-Mr;CuQ zo0_A>&0S06Dq4W)mz;%xscPP|WJW56Rtz=#QLv@n3| z$h13nDt!yp$ds5?Oe?Ae(9lTHh!AB*CodZOq>!o)~vV<0BBjV9QtzUS##v>`c-?G*aA znzFa2gFU0|h55_bQXC$?bGs_tXhgm41HsxRn;TGB=_3wbtZd%BgyGC2%$C>4+zXED zU)I~4;`lr)O#_ybbsrrc_9sfIlH!-2$K8uHN<@Rw+nhySuS;o}My~wtk9skq%TwJq zD|;OWFTm&>ajd*tC@lAfleXx2b{D;8eWNjc)HxTZ-gS5NcTcG@cG;dsG4+qRpmy&D zz&;D_?YBAN`+KdzBQQ-k00sXb~vplIp;6OX|{RnBjTGJRxc%Ix|<&Fe!XvFmHChT(-%+5`(5=f zYe7#Ker1g%_djnYd?K*T9zJe+eH$N!kG(!NuK7EUa`GNdXoBo7Ctp5mJDKBRD?9d{ zeVoiB(`k~%h0sh5$si>q2pEx5;~^rFMUkOHQ0o0flo3GZMTQ>`_J;tz2^NekI3nd+ zo^v9Vqrxr=VhXZISqByFg7vc!P_%_&_V!*yD|^9x9Nc8H(cfikzy5r^{J8YG+T!k2 z>v&1}eux^Av!WtbE_Ih;Yr(N(?Ahw_E52cwoFBLIK5<4|CgSSi?a5?Mnhlno=i(<~ z=hfI4?qX*UdR*&I!=JtPMT4C+TIA^Re7?@t_0!|CKkU4mW>^}Z9$|qq>9}2Ye3Tkj ze3m{;4nkkZ#OIF@TN-kpA1^+{hpT19<@k=Vb(jxo(5-5J2un}0*QS5#tTA&vWUa~4 z^?7UDzb*9vPo2?TU|!q$7;^00%MD>g*0Onexxq-YYcd+vsg9gt_f99M2)HT!h5;zi zpCe)21Fr;tUoM9s-H}a3CyHGA{h6L0l3|TW!lXhub~GYS1cvHey~vwsa=`zR3tIuj z8npVG3xuZtM}v76y)B=zMkbciqS*H3b!LtPtE=K)Jy;w80WSdXaxZlDtvS(ox zOePjX3Q}KO*K~0xC525o1$Hsg?t%IMfJf*#X)kdvX)jqX(G3*$Gr#Nr2mL<%*z9=H zKIAR)Er&<+IU&F3a`Q{@?I;FUr<4Xm0wrNYHDe9sE%?4-Ll%z^9@#eeHt9AYe1ctq zU7}q)`1s2B3PbjhkaevAY|O}Y&d?qGn5j&84)#tr;0rcTsriudfPTord?mBg9N1~@8w*vX zg^^zWroK?;Ee{Q_D*uh#o=I3;cm}-x9_>V` zqgHOW^U3$pKghj*u-{$1Xma0}tQ|OtT9XPQPf#oSV^f$dbVH68D$wn?8l6 z_fN!iBc8%}_bz0;)wgPFy&GcW> zUq3WL=;C+YEfkc@GH22Cpfu1Eo*}Cxt0gguPfJ=Hx7b&Psh@1;OYtJI>Jm~C$`sO- zk|XnzUye^wS3;(gCm2oYC8Z~<8mDs9zUD1+}8cqv}061px(B~2LOK)$G^#}pw0 zvlwtI)wd8}T}&L%;Vv_vW%1|F1^H`yf-#7N zQqazJBqd4=2MLaD(KT%Yq)(HA5L^0(=6(;_Iv9<(dW1YPpUw06z-TE`au#Wsovo_)`?F5}E*gM5l&cRN2Y}}c4 zVBVf}YxC92JIv5optAhfncCK9n-T|tbVFoT>KT(!+L^PhH7XJWggFY|^=8Fn9VSiF{UKcfXIz8rps z8mYAA{%lLFK&fs9yWmckm34axqrWHSm*$rgQSj3c({d2g7$>Ve&s;RG=KHX;rdIM+ zH0}^6CY-ddjqU*7*#>65nV?=$#Kmr2-WRt&JnplZ`LuBJvQ0!1Nk%l6l9+OLbaZyS zJIs80BM!V&;{BlO-Q#$Sj7Cx_9nDPtb&m!=Z%fQ5XyWsbFmY{$nE!oB}{^mMr z`-yPR1D`?6q)b5>Zz}F!1x*02asSkM6E#nkc3d$wT_@pevi#o0A!Q-$CIJJJ^ zc1$bWhY&iqHv;ahbA*&6?1VIwJTtm*H*~Hyoo-*VipHxo@8{0dl?< zs8&i=#11wx-Ozg#*^E4Oe@d-LDAf|bD_oSfSg_MZuXg#?ASNC4P8#E?HdNECA22P+ zvPt*)hSLODiS3zVj2@=CD_-8Me*&BIg2 zb|-rEc2P{*{6S=LQW|SN9JslMIY4~&jngpAh1k^(V^(b&m_U(q^nY4d|1xm?@sBcn zWe8#amxuM=mA3y;!>a7)V)Bm@e=Bok1yy8)gs3Gcy)cpC2iT%$cSXtTrpT}P<{uzsv)!@i=C9J<23qzn7w|s~w45A&D`;8&C8m`i;9&hX z87<m(BKX8SS6z^zSm-e`HC1zmY%jUJecjaSGri~?IeXuR&z>~d<;X_oiN+D&(F zK=eT(Dibj%G$xD3k1LVCJC1P3o5kgF|2O1j7Y1QAZ*#?bUSB&!(`*Kx-^eBi9Zzih z1hdgh;>>FeR?M=8scP4Lk|9OR3z+0j(i`kL(;{Bu)# z61v-C93SYW-|T+-gMG04m3V#6btrE zI03Nt8NzODIZt?q>N;Fr0WJMSb~*iTI80E?JdS8B1y>#U zxJYG6R6^L$N7o0VR?Yp_{IQ6FgcC*8nSdDWL(hGPcHgf|Hi1LbVV;5$(uV0@ zKH`&hUa82%t`WDX6EL8|^gIEPA9|Q`b9(gLO`mnaIFik|(xKG4j=6tj>}~AF>|BU@ zWAie?Jn^J*(A@Ub(7zm(+TO@cCTxJ)MI;D|dyCHTi7CHAK>_!8&zk6|l91{5G4llZ zSa9~2>i8;g(wp!I0uO( zND2XjKRAm=`9LYRBV3NM>Udn9kI;tUiznAmcI|XKeiRE`EdWBIZiuVre{E+do9!ugU*9w`0ShK{rXUajfd+vUzJ5K(2&!pgMdgy5`GOTiHTl_U zn7Fy1Qu=v?5B}I>gUQlRdXZn&LYt<_#nY^l#@#{nc~DMONQ>%67 zyuOJ-!yjF$7G257qf<@Kzd*vK0z#g)f|v8HrS3AeXZh!;mBCu?aaA;*HQ|L-q_lYmQBnqy_=w!Us9Yc`w5t$M6W;35)0~{JxWpO9}oi=W#+rGgY zad(CQ*bPgx-E`luF&@4kHV%+(p@^kp&+3wgNy3TyV+3WeI5%IQcmc^7j5pdfU$t1^ zwE#~Pd5-NKD;Lzti-#+euTM7_vLj8Dkp-hWfSYSeY;k^e=SA!uYCRf`7X~hZi#i5(xXi2ph1yk;(kau)m^j^VQvo=cQC0AT> zF4z*gAdoU5aXTa>7(-=9XO6!XXGj_@qz6oKl%n>ar^BaXPr;@d zO;@MX7=q_NoNK#sdp|Y2t`VPSX(O(rVNb;DWVX9(dYV!_u{{MChJ2;l3E$Nk))SACCZ)r5xe|icN2~Iv3G2WV! z4kEp_t?F^aYUAsWGP?IdXkIihfx)QtKblQ zTLf<{_()0%3KV@mK}EIsuJ0k5#SGzMZX|@7RMrfOt*fM%ivsaufRlr@5bR~_n6VM| zSOngp6ts*N1$jPMvWd;ZTNazSy(LDbaF(gGbuH+?=CMSN(^sI=67|f^%9^-fV*G(N z#b&oS%)cEaN2GrI3=o@T0X~kj%F1f}`c#gHBBs&*o0RPUSuol3Z7XGvNq=anMv{NK zxyUqP+Hqov9X6J#(-0-s*H+*t4*8xn{iw1uKxxMnFDP~I=4D1&t7fZPuo5aUqDW`_d6q>W5* z*Mxb6TmsvL>RV!|GHEs;lV3mj)5uN5;Qkn`KYQJXUk=J*LPd4Gv$0$677zNO4Lk*1*fMfIBW zHKF;H^a2J)z>bTXm)liL1Hr{s1M(Fp&K0R=Iag`wX>DNVCW+<&xAq;-HeUy8H# zCxKmfM3nhoEx^Q;+gKFL;%FelH04-WNLm)0(FTk%ocao#^B@Y}BTd|5*y4db4G>~T zBpwkUzyN48CztUG7I%_Bc|ZEi?gVN%59W0HuLETahI|sjp}%9mJ$)$R(DjI(;Ns8$ zW=2tly}o@qv|W9b-k)&L?B-!b9)T@IGX_n*nm>Iq;?R96;(TxW)BHO~CN)J^)yF4? zwhwq1_?s6Te3vLY0w+W{E`^i(wO{z4urEwl*arpNwoB9kHwO=lc~6w1`|~G$nD}P@ zPQqvIV3F-t{8%tc@o^lyJN(`2Rs6x7O#I=Ub*<#B{v8JaC)$JSpRF7;WX%N|5B5&% z%~2nFksfb0G~n_P%mqx}KmzUrn*j51^jUt@oOerraBO%?1sKWuGx-w&1Ob56%@*El zV(f#iLNRVIe+Pw`tI0F?vVj9XrG?!(0gN)Xu{ zB!Z)Y8Z&~_KTts+wjj6*ivQlIv+cn`K>R~yESd&^eLde6+#Y}fP#XY(RFLLKP`7=n z+kXs=&o^8bp->r=5~|)5B193yuv__hVUf^t%75(P^Kty8SI2i_Y0a@40963Q4NOM} zDL056iT*e1o_?;$qI2H(wd#eMC!!%UL$gUDIw+e34971M^T^h{C7zgBC4c#r0<(#G_|*a&r0Z zPvc!z%)UQ9t%s@pNb`%4l6Gof+(8u!`e_Phx+}qfG{b&R#gGIkZ=wP_`?JZ|$i%Wh zR!7Y{(o4_tZeG54TQcqArR{$D0M!X^oBxpx=Y5b2C-H<5-1A%@4ihyTt3P~7H9riu znq4W8;2n~L60~giB~IW(p1?zd(xdjhapRaF%M%p?Hi04OXxNp$16M%J^axYtEXl9-VTA6;|bG~M43Tz?+6$ot$^)r*f6$&c}FS!;@ec0%c6%y1nsXJPX-EYBJ^P+9+G?@-qMZ5mKJTY7R zv<%IBf{tBDHusR-x7Gd2t=l~ik~j)v66eq9E>0Wqc&ej7^F5)1DS@ndv+Z{tH5Kt0 zM-<9lRXm}kjj>Pbdl%(R-6*;9ei5t4q!xo5`%u)v+N-5bA_iizirFLr)A|0HIz};u z%mD)xj^YUkA%TZE47B^RQWDY|He$f?KpzsTtBq-t`cw>$B>l#QO{+E@(QVcXtEdZC zq!zv6A#!)yPfz-DM@gb$9H$c@WrKV0IR##U0sin{G0Qt zjX~@gh84}JX0O`qLG7eG(gCa+NBIEPRcbg|ed@LPP3u|St&%MjcUZ)QV27Et8Iu{4 zOZ03UsS(fR8YeLKR%FMiZ24MwwyN9d?Cn;H_-e?vWcsFQ>1EM-YM+pCN|k;Pr`i_m z9;@DHDd}C(k_#~<#nf@#;2m=+Dkh>=YX=bXAIQ1sKBPtoZvMIHK zi&lEHzx^KQpbS~mj=nTKg|yD(w^R5STbpFB!Ebs|UesD>{(5G=snXY8aAs8l+@xpU z|E;a{*-Eadf4l*$^6OeOwv#d z4LJtI`vbWOj_LvF6o#0D*sD8mFNI^Mjv|av9{Or%C|d$Z*EBH0v<5863KrV!NbaF$ z>WO(~z-yDT408QPUJkmKHrD5oYY-ZkzX)htp`i>n)aWe=Q%2c&UI*}$#?Ik3PG4y^ zRsE`orf?Cj`j_QDG?$7T`{he|{qXxAq2W{LR$HEL$fDgChxDG0&qsz$q}^tFuTLXX zh;Mm%2B&)yNc5?zrB|s98{5bWN=5gEjY$tXi?Vy9$epe`t4JN09SxW4_6{^d7@TTCM9eiw>9obNtu8o8g_V09a96p6e2WG3hZZ zR%dRUY}Jvaz)@C5#S(}hq53n_v6UY%q>h~z+rI-(I&JWXmz$dCC+r_Is6s=Ml!@$? z9_*I?+=ydeshRO~q-#goULt2VTAgxQbr!a?OZk}eKeDBN?5Ve&oUIZi9ps^>g~v=#eusn7R8c zsZD~vEJdYpLd!DKSS1lbMLL?RiJF3mOs~miKD1k+0jGeRb5?+>E`ph?Fji2vQQJxg zivD=kt%%c7Dw41P!`eZ{F!>AJ)oIEPw?v=SiKq7kGoF9`kF z7pu?2gk}6rbA}wU1a#VddXFevw_RByuIxh|o#6swRm|T_=Cf|ciPv?zgX)E?<;FX8 z@pe=>zqVJ*FU5W}6YlHtTjfM28~8-$L6Ya<#jLmOGxu)8ty*@qUa+ByJqQj|uwiME^ig4pr6}x5Uyaju7aJ!^YEV9ei2W+%Sb?4Z zqr0RT?j|0}oo>!LW;RV_D@DtNiDV(06_SA|%$_K8TKTDBnj<&4Li%&(is^L55D5+q zc;;jF0T?DZgsVENxqLXXd9zTUPJt$2taQoB9PV>E8DPD7uc?^Y7rrcURgZ?O|^3#!IoySvPIdqFeAc z{t?0q9`7nRDLq>^;wO2v(zAXY=wbM_8|{17duMqCU088+^>^t&Yhlshs^{XpJMU0v z?a4e2P!l%+3y2N$-wfMSg>*99ag^gw@8JNruf({mdgfMQbQ9su)_ z$8O4%rjR zXRQB1VWd#2e${2_gCWw>582n02RnBNRTy&gJw}n$pm~$ql5bTwS~htBosk0!&lITP z3hz3UoeQd@aw}AH7dIJ8Xsec${D2^(aZaty0TWz~<4yW8l3SybbOPWaD$iga$f=dJ z<#B-}EC~q@uvZ&&5W2LQ9Tp_x4{2yRcyv+aCti)tJ}Q6V8N?$sq6j)A)4hd1T5P!{ zyba}TP*57kK^}RD4n1lyifNXhv92*vvfl&1FQ8>Zg4bVW=41NHK;(KoVjUZCHM=bc&74r3BH?+C~LDYSEO}fTMI?;y%ePIt0Xat9`PpTqWQ~wBR*~?=11LG(uuH?nc;V-gc-LHny`< zW5*r=z1>=HM+A!23k;#IOf*>cLTDXJeyLP|!p@sRe48Q}mP(676dJ2o8m@aW*LPa+ z-v;Lc&dkG9gEeTw5(k^-`@ca;Ld}vmmEF$gR-3;pc*BVPd!K5!{M3%Sq$5jFB&T zF|ZsRb)H3dJ0kGZI?pP0N2n!>27he>zu|g{@|8omuU;C#I9yj<4c{{T(Ev||9j)6q zZhYWH&a5i9u~7n(s2_imY3LqruD^;?x{AQmDO8D5%M7aPo9@8EVC5Uw_ZZAEYND3F zREF!@N2cC#TT$3CQ$j5*6juze&?f8)Va_61sZ9csuRy?tjvQ*Vgl9wd?d4f}3X!6` z2Q+KVg4F=ge*?k+CPvtV*#c_6G#&Uipb-NQ8o7ipHiRrN;^A3M-hQ_9@ApPK3BNb2 z#v{g23EuJ3!}FH{_&3dtn=eGQE1DU2Gi~rPrDwHK@}=g!#aV~z16(Gz{dd~p-2ynC zJ3Rdm^w+P>ea;Qw+dR@qxe5$~WZh5%G-OozI&X>o_9k`IZ^UI{ML%)P3wan}x}}=Y z>O$}crYL9=+5roN23@e80EWGEiP`nMXlHsxa$>Itk!zpGYi@QN{rY3$GTP_zFjE59 zEA6RF%hRY@kZc*FQlyqeny@uW7=yJ{Rl>vUIYYznVXJ$Mn9R>1m!PO+Dn(yylM@rLQ~aPE~9=}l+1yN_>vkY~76WD5z*zyV=#Bok*M z8ic1EfQ$?qAqDzt0AAHagQSQxyRPUHstANZp8#=5S^XNn+n<=;iBEX;q8=mRiIYw` z&<)8Hk*3#%&;@GQgZMtc8XR<#h_OYuZjzV9wF#mdsmMr$stPg3-PGMzPY2sf$}N(D z#JQ9yXY2Mr&zyDoJ_JNd8$bn}YB+uC#JR?@1+XOV5x4WSpEtHr#vga4N7miG$Uai< zRr_R?*Y3bRC%yu|gt{%P1M2W-%;;BYT51ttS`ksx@0`(k0P!OabPO=l7S>O?3_O107D#5lP=tN3D4iZJjI&tbp@VI zvi&IIaMv7umpx3s=JRSEI;+_cJ`3-VLX#A2Uxl{MNZZIoe=*L!42cb$nB$zO0 z=idR9*U8u4e)>>OtOW|2!6#_y1YPPg6)il-$w{g*R&U(olTuUv{JAku*S(msCQ^bN zO*!6U?%Fbs*Z_|pq^S0t-WbPUNMj~@^JjoYP9_43TG@M`U^>A}0YR;2$MH#IE4slv4;;}FgWRks@1Ry6&DY)?y6Vm~38rb8s(PK#wNfj|JH!eqztoTGY7jD=O z4&+mBDiqx$Y%Cjvv5&NV0&39H$oG5 zv{cJTT@0_^xk|OO_JbpeNB{G7l`DI=N!a97~5T75B1{&)3S{#cqB@#v%$t0cKi}+3F-H_RpQM` zVgmP1&-bfrIFO{7--2^j%J}o=RuLFYPKe*<`pOY@Jh7A6Mob$igt5|q!)W9>jokF_ za4P{1C335g6yVfn-btK=h}egMbK<$IXexZzecfhi!FecZ(w1xS1YVrV?AR`In_t@@ zJJTQ7XQll%D0BuZW7KC+`qc@2525_=Ks`lh{7|k&M23nO>J7TmU$K%ft$|xpO|lh{ zm>6NA%G1UIe9cgP;W}0m0H~=CobMxSRoLHR`%}y5L$?Krie5{%1^t3a_2-6Q9LXfC zEA8J2avKqW4OL^oka*KC{Iv`*32Sx`*x^-f+aDMr1$2ow0@j6o^_$1{;O8^GLA%!~ zeeIw>1wAGU(5}@BSQOrtER|qhM2N+jx`_h0#b!d6<)F*~4X_?bI*Sw;WtzOACk&Rn z1J}3=EuXGTq|>4h8SpIRr9{I|+(B9fR6KnA8{^6day^}awB$BgZ_D)$6t(SQf5D`|IXh*8KcP#4YFA;%6J{tZ^<_{X3Wku*iz^2VvhDOXGWm`9OwOxj};S+P~j z0nir!NB92h^*1yLH?ksK5`S$xFMv013N9OR9kLwAG!%``r+zM)vXW}I{puH?OVH)e z1T4toz!B#7(-LrXanSB5^;Y}ip>^7T(9L!wN3mTapPEeYR6cDSg^Qz)o5n@isB^-Y zmGos|?KD%R$CrzS=`wj+8xJS#I6yD_#tu}j8g47FT;h9s<7j+N4x9a2S7kN3C_5K& z<|)gVLK+IySx&lF+d_ghQ=89a=-~ck83Zl${a0$AVFyeuvWtXNO#DWYO5)^>Y9+!59BXmI zrUC&uB(X{&0+=|qFH@^bGHebYhdYj|CFdKRtr^SZU{HpSDhY~urqBRuz1i7sy`hPTmq`wPi(=L!=+oG z0NIa|m4!A1%h5DM3|I&5S6%mcz zCJ^b{Ii2*a_?L%P-`=4LUKZDooy(OIzMJ2%sW6+**fggK))qv&ynL{e=r^X{;ft8D zUFfS?Y5EFp4b`LDQIm=(INBylKfmqkY-LR~NUb*RVz{HiI#myV%cYL%v#G;W3n5F% zNkIy`P9Try#x2Z*C9GFM3$GI#L-kR@LG>3v5szg96;&`ya3W|pl$Dg#3_+jH0fkQs z&FMDBvv}^c#adLyYoK&@f=y`cCq8JnSg0r4GL7a1y89V><}G zfN}fA`J5j29i?6z*~iyp@_IgJ2grY(YwHNA+!$pHZi3ALBXsRDQFfKzeiYHB_gup| zEr?T@e(%eE-hVIM+l>dB1TgS#5Gz;tzJw#Oe#MEfmgP$%NedNC%cr%*mc)F*zl1puL8rBeKDcQ0W3#ykgNrDDQ|Np7?E0qLwkhK$77mOgS-oqxI-W&|gHS zTY{)+y-Gm0n^FvTLb#7#cZNjKByPL`(&M+6^r3Vu?~~b22bY5po0e+3y3fq4b~_fG%^Mk)V&lE^SuvPb@JD^xndHZ8P9}#} z=rXOc??jk=@<4W8MA|SDDVKJr;kF;tXfVNnii(TiZ}JD2Ae50o0hAFcnoRrFUHj*> z8){TnoeJQXNX1pLgJH6rH-K)LhtCX};Gok=3=}F&1N)?pdJDNCgGVSSmCDiSJOd;5KJ~4QUpt@0gun4r3Mf!O-+zYo0wPzTA{QL^>}K&RKjD&?qPh?C+8C)>MSLi?89FoUQG(K=3&iX+mKfRbz_*#Dz;yAc4ij0`BBylbk5yC zQ&2XyL6~b`x|6npuAq8|C}KSeC6>obAt72=|6o4@u4PJ;TYEg2%8BEijCdt7XHs7m zZ^vIIj;?D>`Mg9%X4TWO}ecCgIXz*GtmS_FJ0|VYzuLia73SemF#Mm7l zfzM#X&JjLbd^umX664He)zn^n(>GZHG}8`@M;@Sah46J;f!89#EjELw9moylb6fB&WAsEwaU1^9VQ5;WkfCHl~jGx_QWgO z1}UO(tn(US_g7Y0krIe64KC{{l zOlcWJjy#kco5#b}SX7R@l-cZ}g_Ljx)pU>o5^Q8GzfVpFgVEJP=C;oKJD=!d9`Y$r z;v)jv#4RNK$TuGtx&THA-)4Gck6UF?2r0_OW`V9(a(byz>{fcr1RZbd@y;ujIR3A1 zyGIkFC#EoVnDA5qDK0wRZWF^EH-R^1swmP0^Y~#Zj3Rtm)H^8LrC6*{->$fgD^(HD zq#Q-Bw=Ru-cWuk8Sa4uF>1Ivsx~L-uutdAXDux+3VEQwqctH=gpOSnrXdm|oWReVg zG4N3PrhOnDOF3vgi$jaN5h85@5i?sY!jYb-K<)uAE&Z^t>xkvFn9FlzFl&_hBz%z@IOu852h@hF>BL zB9c{K3@g`H%P}D2ER_Ec0qNL`rs_8t`4J{4m&6%Lt)EeI3{}-Hw21pmSYozkCTQY( z2x(Fyn3g_mI}MT+Tp8&SR?VL`&B+r=GPoX-k0gh3PB1kIW1)kwE#{%Sd_#Cg#0{}k zF*cB~OB^y`vx&BdoNBXdV-aaCMez-x97efBS#+d0Iz~o515vk7qfn>N3W}|iB@}DW ztNYa}9h2cg8!XErbV@k!=S7{VI#ZG7gA5@K6-0tUgX(Z;7H+Sj*A&m$_-5|+ncWmF z;2lL(g2@A?RUAaGZS(Xv5gkr0y`edDQKpd7ee)2JVnTkA~d)1}P`h8PkH+%QYfyYMYb-vn3{jD!aS`NF; zaYGt=g!O*B28&9ylyf?_8V@y&|8{w_bDY2bagDo&RLT~|ydRO?oLR-pxo%XKDpXx7 zAxH68Sqwd$bhSiAR5eFs_8DVfvq@0w(NurrR?e>W`*C%4qV(zrjb-#M=|$+X38#TD zJIP5DfKHDe2mag7u6KGoE|iu-^KLY~&#_2{INp(%q^)g~S_+mb#gc6N9j%hh*We5B_!mp&}ixu%gRl5S>-0oq*HbDu+mOtpw zPtIsb0 z^9!g?96$}A2mBBM;C~6>?Ck6B>s%EZkmR;IZ_DxabRTn_ONrN)l4wcNG$!T0mp_vdwkt-A+%S0T3U8f@)psG8eg z1-Sj|Gq~GenCoDe%b>XHp!nCj+u*44U@d_*W;P zvuB~RSE2OBq4ejW+Z(WU=b`kcq3kY$pR2I^VmF^)v0Qd*{{gH1!;=0XYZ)2XS^o>G zX8eQa{!iZai*t1`boQ_}A)xqlYI+ z@ty}{creiLyItkDK|ZGho-pE}qkR#=)YC)~h1Z6w-XzF`PR zf%Ww=H;}CVx;7p3A1(Ar5Owqo9DLtYE73E0>&Nr~>Q4rWGU~Y$9+l@MzK+c0%JNBT zQ7ZjFYNaLG7t1imOOdH-6S0YJ%8QpIOzzS~5w`o(;AV*SYOqPBAr_&w{5U~r^1e|S zuNG;S{V7bV3B?gtt1^r*8RX&%Xv<=c^dFY^&t>_GoM&SG7dOxJXEFZg0{_jx|6}>& z3~avE`u|?nzi4Wff3)}~OwITOq0=&PauP5yaIz3^FtPvdEH%Ry|NJ*g{nh2)SZcO^ zLDQ;V!=qQ1FtIQ*cZOp53QjNRYW5daPr%Cl#XA2DP&51i?*CxjViwjWOaxzS_Mdy| zZ-Dx*ihs@YpEn9K<6n*b$x|~DFmtf|nU2N(`?l#$^Kw>RLLKRKy4sZVj|V4!FftxN zKum;yK=Y8CBRMdM20V#gxR!xPl_21ertFspA%H3=NiIbxFG=li7Ku#Ilt8oT2ND{V z!dI7~Eu<|`jW@NBc*(IdHKA=#{XDysyS%!5zqng{%67Wq)o8MJpyVpRq63?$Ojm@& z9mn=KVYM1B)StTIK(rT2Rhg*>|1D{CVl>lrV8Y1nfnV!!P{M3F>dkWZ65jz#u(p+v zOIwN}xosK}DYH{ztXo6EHcB^PqEZ&;8Bz!5^*X=T{4u}J^L>8T=Qpp<_w}0hjA^pe zfXTmZ;D6D$XHCQR#P6(;9mf(>)XGqFZu!%P{~GMBsLRZ7ECA;mvI|SDVu#ZJjeBsm(Qd zN6I66b!4kre*8)0iD#e4x_6AH(bSMUmdxGK#(Uai&O0J9Pv)x6A!bRYU)P^7$dC*S zSge_jwtL|H`_ZY=5!W!UC+A1-q9GYtn^rn_C*I0*7hIKF`jD$Poh9?Ha5mM2t8;hM zBWHa~k4eW76ULh+yc{dICBlp1lJDr};r&nCv9EW%4Zj$012J_D7e1skzj9aEvs-FNBB#U8b&ziH4q3JZA{ntU=z-&@!pR^|W=T}63HtN}PVwHH0-nyr0S^D{%uxxSXWTuTAJeBl zeO=~pJx#v-p;bu6>tMNepnui5L3RA4w$v0eo}=fiW@hhi&pKr>t&Gy<%bTS#tT4u#pf;0eahRH2pmvcdMRSK_LyP=AI*@Fsb^>_guj~IcV>=#bL zLAk$M_Rf2NN3;~Nm=slaraCw)rqcjcb{*vD(!uCA=?k{8UDNPgL_=>%Iy@&`9A*M+3$xA1arcR{j%XGU$(IOrx%#J)e76>* zq{~!?haWjd-{+`iY~R|T>!7N$)qr;r=PIh?HLVp{%9X;-5iGR(K4{QCSYP!;=sC7c z%~XzU7AMuz=CoIiZP}mvwMbPK8ur!bk?MDM;JcJn*YYBhPoNTLYntJR0i)rh-mmTj zoEn)Wo6D6apA=6DUyQ_g_R&1zJTP#M(1>HWq$c9)@>^2+M@~7G1 zyDr8&Te3k#L63#K`sPsly=l4rbK7=&N`7$XBa;Um)j_|`u?J?@#of>Nsiu+R{MSK$ zWq(1@ztZbhTxpiI>Wtl1j>DpCk?W%Ft#zd<5 zRvEW523~=zf~eEJd7Xk6+LTnx21~~x)x?M2zIt-KH>@L1)OAf@qia%-r_sXcB9^o$ zn+@G)mr9dL)=|!QH(q-*;jkV)Q5yEMQ{v&vnSsTE#-k2rhuA$SKh&Q!950kbNS=kb z2{rP5NifA_iwwor32m8}uI%KEg6EfSTjYY%t(p`0MjQuOIRi9kIn*}WZ2H^UvGeVH z>Bp*$4O)e^@_%eg6^SteIk9z?d9=EBlmX5FH>0M->x6Jie^U?0e{*iKx|Y~NMMdfj zy??o%yZeR~(^PrLGvtOtZ2E6$npY+r4+b?{mu@I@AKH$t9`VqKi$_8~4uDFCJDR69 z=Nh#8MJh`|uzP=1INTLA-9ii+=Y*Tq3XIGC$Yzi!E=gqO-mm)!m>r}dmQBo1@xhk8 zq_mUGHNBl6$c)m+(=EDbzAdZnUg6yh<3~QcJFTzcuu-eEf7UqwJTbGj6~(P=$eocq zUU$W_z4pcW`U}Fr5wX&)#|htxVvuPThgxi-vQ}jcVE87#hlkcx2myTK*n1x_!bG4I zff2W+4V$Se!&4Jjm3=jhT?u~b*6oseC*G8nTKoIniSIQTsPX}&`ncV%5BXIzuM{`_f)8EItrIJ|C9sTcs z5R&dD*y@RbjntVjs;h$CC%{pKC z<^qgpQOo;@ao<}vvCS);*}M;#cV=ibZqb@SnA(ChGo**okfBt%(Wfg4Y)}zy80=4R zbVYd3Sm6w22;{ktXdDti_!wG7FoLKEG{FXq#rPN@oFn{M>==a8J{v2@Akm`OpPNz; zg!4@~v1l9yE%Nh~Mc~YEpD_l7CZdRF6b6GMqS0O`lmYbm9J!b}7=D%(ZKXHj@ZzWy zUTe{RxiQ#5GzBm@@B5utOlkxLa_aLuqzhyOA%o6lLiLaQ<$N8Q;XcU6Bd`l-+@1qW zs-g~CtlQC|Bbh8}I0E|-i?gtBvN!&$E~Fiw4Pg|EMu$K{EJS90DhLn&p!Vp91r2%+ zLivTFAVNNBXe^oldCR35h=p*=r5aRI;E_w?uxJ1>;mb6P0^?k&ffzhA%Ox6?KtMzL zzC>H7E!6j0Fp2BrER4fh+pJ;t0#v4|;YnEBgR& z|1~!@%OA>>STF@r>dJ_LjuynNx-gk+h$LM&nYJNxCIaeBk)7M_LwF-h31loC2T}6@feU!Cg2HXu>T*jkidttp%10`LkM8;XbenG&)U%j_8%VMiPr!C literal 0 HcmV?d00001 diff --git a/examples/gjf/molecular_dynamics_results/guaiacol_kinetic_energy.pdf b/examples/gjf/molecular_dynamics_results/guaiacol_kinetic_energy.pdf new file mode 100644 index 0000000000000000000000000000000000000000..364313fdd3cf7268b2471b33097b43e8e7ede54f GIT binary patch literal 43676 zcma%=b9kLk*YBGqjT_re+F*x`ZQHhu9ox2z#(02v@&)uAz=D2 z$q@jAOf4J??LPi3bR7%@4E3!I3<R3(ds=pWk z6Sn;fg};&ShKeKa6Fg_DRaz7{kuJt9ymxml!h=EDxdN3+7pIg=!6Q6BLB;+uzj@K? zVCuvO>#T8&%V6%*N_kHP?k$G3GjN}d)$TvEtzav^-zDW=o95yeXXXHY#pi0 z4VZEqSQEssm#6R?uV$3Cz?M&zm$$QHSMDfGp=ujku^ak8dOf8cD!GUBx*~+ z#Qe5Zl!?|h(XW4GLxZSv_nBfWBP#{LHa;<8`n9Fw4RE+u%zSEt2OW>CHFQE@6m#@A zkQ8t#Mi$!ZTa%kt?5)E*Rym1GTbX2)B~o@kB^Ru1$opueZ=q0QRz6k`k*U^#=Jp@? zYK{{FUG6xwS6Mr+3Pz+bc*OxD9ODWhllAed*(y)QSV_x!c zm0zw+V^ZnD!LfP(^)pYM6sUmKqj6hVQmyZ)l}>W~_(s#^P^Lgh^}INY2A(-Ln zu(7>5OcSmlGBX=EUWgW^mUM&Pc^__I?T5JrBBuH>^-!K^(X&=!4gqhTc|p%VaT#bV zk;B?%NDrAe_r>h6s$0zEADPDK2rw1d{J^%9FVZj|*g!pN_lh_|tq5`*WeVY4P-6TJ zi8;P+Q1o+Lq$9|Jb-`j2(h{O?$v$ZOYC^g)C?FgLJKLA_B(*O_hKtJfpB8~rl-3Z@ zNsriZj-UTRb)chne@UUj^9qyUCr2A%cZ8xwJKGma8~9a`Jv_r^GDhz5p15~-yQ)Ir z78}2S*Ff0-!7&qYML6h_qgWatN4$}w&YGhtBXuoFF#=u0PFN%Uom_&#&^>e|5x*ya znu6rf>2RGpm@R%W+IE5&l;@E_$(G{!MTv1+P4S-gkkT!8amS|OgfpoEAvJ_USWu;z zG(7Z3zD4-da1q!lrXp@z38tlj=2V>AcV3{F;#3J*UCCl28kJDv)%@p5GhXYtQyW>; zmc7+Us#UE^6ya%9m6IKQnj+&w-HPfYgtAzgNlruv(6V#zR4VYF-r>_iQtJ>D`H`i3 z*GK5gu{3DBobi-3T2ppj_zlvAB$`AeKB6=ZpzdDGzhHiX7D^QLnrcXpoRC3BMC0a7 z4xh6p3OZ5&860^lqDKo%Jd>?%1nY3e%t*Q7&!ShqtBFBz8vUplR1+Lo#m%^+;39!X zqfD*A2*X`9NMX+E_+i5uHfGO>3tM0t!h%rQDz?4qPKhuh*HKRhv7t^bLtNrcyuO6R z8DjkNP;xzRM38(ff|mAitKUZ)VIz_1Y+h z>v=#qEA2c>!{h#S=DCq~+5757R@!DHCsvNsw0>puIrYh)*XNAb0r8pPd0JFdz%AR~ zXR=SF$nj@5fgE{%BLA8_`8Qi8Ea6}gDj3LB9s#5)LoIAXUJq$!h2jW0f4Z*CLc|u4 z!@QaF;4?KacIApM^sIhsOqs}+JQ%Nm`zr%`Ka&}1xY$S{Ld*bMGJIPKb3p9SSO_B-#I`<}Z;UY1xp@7jkecg(#2JB0ks z-7Efq3qP0$P#79~0Fr?piB_++<%JJ2N#bR(7C9o_vwOKGTE;J5&5pv!Zz-z4<4eos&^HlJr*Lh z`s)!GEmDL?$#B(TI)OK=l=9%=i*SvN=Pp(SE1cTQ8_zm{6Yw2AZGmCf5uS*c`P<*q z_aM;4+a=jr&C+A`ZFF|=;1tK~EkkC%blcsOX_RcU``vYIChmboZWwlnSo~#j%l*Na zvoOg>nP`{!>aLUuy@9CJQEh8q^}j~E%}h##Q+-eEi?p)i&m)U3D<4%6G;APpVk~X7 zu8RjZ!Y(Z;mp}`OzFZB(Yar$PJX^ckuUUXs-5@Hh*AT0jAJ??`qmXXd|L5~!ilxB* z>&oa4GMfZ@hUH+bmqqrFDc|*saf@X*#G}PXjF8l87JNLkcOg!EE#@K}?|3S*yygy} z^vs^b^RUWyqqkKTdVBFU9?zyA|2xhm6&^*+OEly5o-W`jNK=*rEcZ|d|JM;rD%#w7 znZ&k?e&+LgFO8Si*XQ*LPtJ<~xR=7mOXnxajl&x@SU`7U?c@G2kX!Th?rwEsXRdWV z5AJg9buJ7vCz5d!%cPi1Z*QR)mV#hJex#>~WKN z+#1rEer1-6EofQg+@}=LVWaWFUHhZ+@x`C~qKm412WG^GGNqGfJ`MgEFFLOk<;zT- znC2k4Cksf2)f62hWNp~Uokw@rd#C5~)79%OsKmM&UnfCV8H=8PoPG7OF85pTRCdyr zdP-;aYV$>~Kn{+#@F@n3hG48~#A9ZyamW6m+32==GT9h)zNH7&XG|E8xw%}J?dXz~ zt?rZw6%hia7h>$I?Frl77D-o#P~b#78lFe@@9%fAqE>Fu2i}|~?yGEIbQ`a~L(%bA z2_`lOJ!^}ixWOW|U|n9syrub9tkSM=e1m(^(ep*yB0(p{mV4YQ_z|YC_@9HGa9F?| z8bjt6;XxW{Wwhz*4U|?3PDyX|VZKsF3C7Zk5IzK;XDT*FbCygx1c=|(%fAH|nKRpw}k3Vn!KK}X$7BLR1ONp?X9ogJ0sz0Yg|(f$ zjjp~S!5^sQx2Gdu{_CELivS?#>>w=f@By@c-wE5(LDSLyGq0=oa~{ePi#x_{xi)JK*9ynm40>d*230)|ee`i64CeE)Bf&qxF+$S@}i=cwZhKPF0d=B&{a}xL>go5}@$w1*3h;R^*z90&WpRe9L z)D?nEf0wL);O=U;In;SM)Ad^F>wxO|;(p`&qVc)Me9I@97hkY$2Ne)+#vB!tv*Rue zB;=9a`_C8%AaE)mzc!7Gz=R(JKL37c=S)c{66vqKJEQS7XkDi2lp(X9d-sYVV&*3S z{{$^K`-8)i41M==ynJmRCjC3u@J+%u`an8*v>d41GNSF?N{hR~J<8UhF&Xx(bHwE{G%QnWqgn1X0Wrw z#7!M+BrUpkrFEhp2&t-Nib>3AInL>+>fD~mW9Q;Jo~QgP=b-De;w9P1L?&-|rs}%I zNg1FW?b98JS{iO`M}p#~I!kb#-OV!TbAnG-Uq02XrC;L(T4=@gZo!hngq@sN*n?!5 z(@-8TKWF(`4|fK#-lvS5Ju9*QMCbM)7DZ(+6x{t;_)}b9bQBgYX~N+39^rla7pv*m zP!Cml)-UwSfCEL@gLo+a5R=vb4j+|h8Utv5uh~s6j349>n4THtC?<~DpF9FsWtv1G z2CX?i@e_lRSaG|4_Bd8Ypo1RlXfr8~skD!xcYWJ`!iUiawc3>6C6eE}gN-tmV4d@!dCx34d1kglK8j;VYJYY4vTnnF|dFd8F zoczpeKK=G_odlEe{b2*H0jB)xs|^gSw=fTMV3#;8$eNESr0)d+YA$a{G+I7<3f~+8 zwi=`hKd%f63TPjHNHjt$&*LOn5yp4Fk{o^+&KqI}tQJU3zo%@7NdiXjR}c?>#N^L2 zx?dMQHFz&pvEx7rcaLlcIHRURp#NIl6l+4`f@|zX-^9N7L=~Xj9S6xX2njkRqymY3 zDZm%4LIQ$FXdXk9|G8K&H5x7-yE#H6#&!o3JSayu83U~!b2~^id{a+JcTP`?b~af* zSxEwY?}rfrgU_RHf!=KOPZjbqZYQW8h-nejy-GS!I_gzP)u0QyC+s+I1HUl0aBMuA zFf{0`m@2>;;pf9!y^njoZjxO(w|!qjIroL{vcJ%CC+vXs!tugekHYWoB#(wt12gx9 zCrl(Du^>@Ez=GU|eDz1{W|Z|Ql6D{pL~!ZV(EC;$xxm{dibEz9hawtCf-Xn$Ev3#! zLDY;$lZ=zBoiJ{Q%|O@=LzPEMx`HH&K${dkmRlyCf(%7k3`dY}QHoWpna734g}*@V zYmwD&m6GI^3^nO?0S_?`fN&f`(sk1IP83i#I<_UlC0blz=KSZGxWm31{DbxzC__?1^<9cxoL#Kl+F?2HZd#oO206@v z@VM~S@ThCXz2=GSiRB-ardsc9-x40bTYYy=AWASw07-}{kx;arMVZYgu`H4PO>0JG zrfarn_B=~d8Zl8g0nD7p&}Mw!c?mkIY6)>|dNRB1IpREu!%D^Kz{12*#7bi9XTnUi zN*zkwP2Fc4s54Q6sRvWrRok!EqD@FS8&xnOtqo(%DX%y!q@Lo+UoGV<*DtD7G0u~! z9Y@xTrBP?*ZPaL#2l7da15^Oom9pnKT(Vi^S^1s9o$6l0za|Nmbi#Pkx{7i_b2@c1 zb@Mj$iA!Qir@rT@<+1m(=r`DgUUF@#lU0Reh{lRW3`xo_{9aSgX_=^-fHmJUA!96M zY8}X}T2WOk6Pn9r?co@7&vQw8q=exNQwhsJTSe2RI;E1QKBmG~{igaw#j@_G>Zxa` zH`QEI-(w)qY+Ju}{O9UkeR(nUx>M(=2Yae!)hb%6RO`eY+#S&~*)tskXOMGHJKX(( zgA+xozsD@%@xf-(_+|Ju1i2e|^^9oYdWP!wxACvzc`&f(7wEsKG3=&nH=A(mVrUF# z!nK`ka(*i=Cv2-7KaEPxN9;TGTK29ka4xAXay%#D#s{S zHpbrTotvE(aq9$^~DEFYm;dFM*Gb7!tWHo0mTHXiTY%ZK|}R%?r`GLr0DGF3tKTginW%`??oze=j)#qpyN>W4g4|uaD^YQy-3;6X zn~!S^dXC-ir`(UY)O;{}i2+OUukoJ}Nb1!L(HE@{MHSutEX`ZL;aH=6<+D>9A040f zjiGp|c+Awl?xAjmk5o6bic*t-le`_!!vy-}GHG(^IJ@o9!WW)q?H12SE3w-HfIx~kW516aa zSZESrS-^EMANVjYJq?uUmz#{g%y^t?JM*sXgE8=WFJZ-E5~GSBJCc zvp}^tT{WsLH(O33(we%}8`%ook|te=JziJ!P<~t;z4Je9FSsjs25vY(0#{ZKTdq}7 z^i;JLCo48I%Xdewa<3X&l}|d9bk%Kj;7y|pqUz|2YTCsr&4gzQkMfUvu%c4;+K=2C zPcxPVmghUyExl$yB0&2fxbRSL+PntuWz5TYE&Fs=Hp_Y@j&qM%I*q-wy#!80E@LKy z1B43(x}zLt*?-S77cs~G=#Gf(uimyDuzuaR<#$6aJ(OX{YkmM@A!NPW8hF4z&xGYz zbP4q+IV6A0x@(wJ3suXRTbT=K$p2yLCgHYz=slBxJB~}uo%Zg26MmPHT03kkJ`ppH znx4j*1@ye)>kqgL3qcQJQ+D8LsoR;(sHmz~8}Ui1)Vgf8D_(AYeo;&+HLhUQWcSGM zXg>{njhMr0%}mrj@iaZGKeuc@w5fef+%Avo_~Nnur1=b3yKC{-jeO6*1`Pv$I-}`u zd)HdwJoH$5oq{Na*Ww;^WqCDu)j!$JC5M*&o>{_O{yO_GZ&ciVbCNx;Gf^9C92MBa z4|q>_td#EgGEqE1DO4wPBwQ{$5&jsy>RNr%cQF#4G_xJh`R%RYK4Gdf%MFg_rHGrKUKkB4E-wwK9K$2bo+<9|JXhdU6h}nPuJeifPn5F*4O-ZpFha` zzXI?d>0tlgiGe?S@A!e{bOZo#Qv>@C`u~UDHUATn|5GOX1L6F-4!RcB#{cLN`+o_N z|G@A+RR6z5@mBx<W84ozslpEdvENmf`;UQL)%-o;YS+Tug4SSwnY{ykHt`?rkvcSimi{vFJ} z&gAJ>KLY&!IF#3no-perKcauThdoDS`pP(c+nKaltb^BafaPNdr3-5F5N?&s z0fqKlf4Q;WDQIulVHmtekqE*}Cr`71wx@^Wgv;#Rgq%xzVNo0lXM-NHX_UYmNYwED ziTLSid@z3IbDA->>k8UwA{Ci5s09~5Q?Z4$AAl1>e-a?4Gj-`$$<}d*$gAWquXg95 zHnu3{hR)OXYii__}@M! zzo@_;%b$1j1pob4`sgO_V((yRDQab8{r8SU&d}KOLl3(UQ1E^zU&C(%0BJh|L%TmE zLGkaB_%O;l+SphaTK*Bgv>%m808l2N|CfjqQ2x-9w6xHFCFY;Xu`{)Cu(l(h|3_K= zS5f{Q@Mjh3AFA_@@}whRWMC!upF8L8fd6xq|KalQ6jHjDA9C=2E5DCR9pgW;`)?1v zzml7p?gujgH9afqM|iA^1T6H-AN4Exv29HCd992s3_lhE;QdqQ4g}1!AKUMrqIdXb z2!LPLM#Rw6*u;V02mOZ-mH)_@(w`A3|5%|JKb!-2os5-D4gOp)F@I!TQrG#P79B0) zNAu73__%ZW_#X8CZ0Y~V#2>@ISNg9V@iEKa9q~_-j(~xck>z8)|JSY6PCJZ-g5ewY z8^?Zn3hS>=ps`=Y?0!vMD1kcrjOjJO2SX2fET?Wpevb5pRuA%~@sL!Ek zHdLNAFa?Js7F#Y?c+9WTF5fIS1THqx#yoarF@WaIT3J3npP%0^?T@lfxSVB8JU4q} z?z@j;@<9=DH9-nA+Dw(};#Y>M^Fn_0t|aYjX^XA0;XCi^)2PZ7dP-3W4|*mbT=_U5 zI{F;_+DlHl>)5v))hW+2=m)-| zOF>Nqlgu)2IVps{_;av#oTi1*@_%;aW2TFIJc<(>3LUQkS`S)3h`b+jWQHzpQ;vN z+6DU3MO`uG)OTlDT!eiq7~N7)+|p6_JXLCNj@Lg3L2E&bJvbC{rF4aDXW^{wFiQmE z5$g<*82M@*((JK!V&|r2R#6do1)fD=xzd7M;1vS`I$ecLAK{R#apXCxdOWUi$kKq? zbURlB?T`!@BYg;C0Mni|nr*qm(Va;Oh}KHCAB5E-bbGX-7g-~Hwp|-)4?yW7iGQ$P zH2@jnDLeJww%SVUdFNe{Y-^%8!+gS69G{)ZAc+EtO$)HP`Z7caxI`sM=NMWQM1wJB z$t@;pjS&+r<>iHK^xj@!8%pZNiOp__YZGf3)RODU+C7`@jR9#%kB{Y!nK3|1>Di6D zCCM@;u8aX5j@-cCz)J2%#^JGvtp7AZWe-*KUxAcrQ3S+YuF(6E3HHZP5M7MhFm!_s zp-fJU>s`Dh9?@N7iA@kIQY_7rJ#b5mme4e@Jz{2)q`$z6_S1bilWIy;7|IW_AUWL8 zRK#0^gFcs6kFQF4L^okMOI2u(?>pUrx+L|=VJ;>XjkaL`Cb?2y9m%bZzxt?)rVb`) z#2t}7fv8q4!Em@AIw>M2NoOQe5ge90BW^($`0A{OU_p^+7flaU9>7WkwJb9Gjv>yf zN{x^f!3-6aTswHLm1O37`oI-I&I`00Qr(^!L%l!AZCv{{)p+l)D2MvNmHozX=Q7`(biE9&Q&Hr#YHA`L~Z2N>Y^0mXwGDIHA?hM^ix>qf0<~ zux)?V5{j%~Q*|H$VOgRs?)STc1TB<)zmxQ{?M!9l*rE3{u{&*s(NU()Z#GOT zqmpzq%0MGHPDzHvbod_1*iT|)MKHf%U1^@^`WeG*l0oS3^+pF^z30LjIP@wEG$JoH zIrfpHok?k}pFqFn^wfYOjnuT*nM&%)+WL)HIV?)jv@RM}+AdPlxRsAsIWAh#xMhrV ztQ$7Ap4`&7`Hid{)Ua#ZktMY+8d}>fs%zeX(meAfy+)6mIV>(~-1X2rBPO-48gd`i z;M*^L^pqm>beWyj)caZ9Qs!=IcwprysJeTVnme#M99B{qmPp;0c#arWTK0v>P@FOg zVdQ(*$oCPmqq~x@ktC%A#WxKK3hm7I{GU~$YCfnd^53a?O3dzxODyNQa|>6?6cxpl z_Wm7oDpbZ{nqI2mTGTo#{-8^29WA zT5mfRWRU7s&$WeeUz(ID9(72F%vn5AuL?>-zl(=TwSH@>>c#i9M@OFuWfDkDoelGE>WSCUtBx1uQQIri?nmuF1%t;AO7#h|XX=&mv^ zT``D(tKW z$kYH3Itw#<2kvln?unOo2gKI&-_24e%bxzCQ1%=n1)vjGG-+#Z)0DKkN3eGqO^S9< z-k}D_)iI^BMJKDs_@uc(2Eyet*SNG0*p7HHV?(hW#YKZd! z1HXEKY$?40<|rvep-jNDH4Y!@3w$j4alcNUZJg2Y=3deV~Ys7K;RO82#RO3yrujlXKBirfAg)it^x@VYyzH^2S z6V9E74M`bCdY4tMlzBaQD7$OLGGIxOO{cSn_ev9oXWHiXZk@%Fb7XE(#>!FCQxNv% z_a^twtDCGDIY+Wb4d~y5ujbR``>JhDm7?V8H;;U3;`v*JQOS2&y~ZL-bIkl0;%y~F zAk4wxwj%mYQMV-96wh_n_BWHpKYM0FojfOkO*6k#$PBtrIEBhDWDO#piM9QrNOk z2pu9DK@jCj2Y&L>Y0Gi-$TUma%G!)b?1Uxo#82qpo=oVnPeu2|hCb~+pnjXrek~B= zXHCv8xATC7dY^NApbkR>f){ImUmpoguMs-JDjSb;yQYqBir!BoBypp>`P5`&Mmfz1 z%O-hvVV#bjy@3o_B4kkawB#Yfn)BTE9SS{N?v@VrHZme^zDm--icM=ec_?fipn?M) zTq{(%9PYXX7D<0_@!mJK;#P*;i=FN_PWD|J&EXyp5=fUrgE+oC{4-N@8h?@eah?NY zI|kj%QJpyEiu%vYNcOUWsmt@>h)nL+6j-dqO#Q$t1Nv$TezXNtINaG=Vvy7qrio4Mi2j zpvo8oei9x}uj72!iHY85{#mqL2oZF2-lTj(XTiWhP>?*xTP^$RXYuerRbQ1$Bi}X% zc|^yO(sVAiu?rYmG1ObFe#WUy`@&0KKWv9nYL36U2ezKS@hHFQ z(F-c-S_;P~gpK7V4lbd#?mp!7IQ>NrJR(<=q@NS&Hl7okCoEW|FztFj-NJ%al&u^< z`ZadPzP9ryihbKj0~&98fv#@wGEjO2)6^cpgptKG-2C2L6TMH;&7ok< ziC7lE;Wmk23`hATLhg7@vY3$2lgI?j(OWp@vif0cs7ti*L93uzHx{8TBKcvXDrAC{ zM!TP9)QDu68MDlfos-%F6Ofq<}gk*11rY=`~`5wVsC%1Xd4}DMC791Nnn* zzbO}22?l!P*Uk;!M^EHMN3*TTg31cmZIPkvN}(xUpIJx!XOQ)j3}Ld;L8&-CeLs>` zX$lTlEJI*c2y~=%CCpk&1Y{ZK8s~~J)tINoa9mY1;t5MkR{8Ny~ZLP%)2QzUSqv;C4%f4%^_JjMuG4+!qER`(Y_ehU9 zC$fQAJk>^Jz+@j>aJ4_&t>?qCYKCwar)ZMqRfLe+2{;oS8<8L~P_uCwZ@#8FC^)=7 z0H5tyVne4^+hc@NF?;H1QRY3v5vx=*5gl$Ws|0uhE&!`^zTj+-4RpJ$F4EW1LdPw1 z19!`P3b}*#jA=jG@SW@6#!q&;sf;>I%3#wrZ}qM&1Pn__AoU{^XhWnOA4U(3u%&nl zP21=s-bP_{oPJ)!I5?TVjWm+v$Ip|cTuSg9gOYpK$elSKnkU0qK;Eg8#K?px27A*q z+A&(tUl6jSla=mPL>FT5@q@sINq|a(j7bTL2tDHrGG3> zwI5)J$?^$Hvb#%X@?aDXQ>14~c$yVCyhD#z&%a*>GfG;f3{h)b0#+_IPRLB}QfFhm zaD@UrK#1ee;n5i$;iw6V?I?0eq__O>jEwhTh{e)(%gEEo=@9~4oj93JGz*A7rK-tD z4|ka+dTGazrMbgB*OUioy+pV*22>J}t-a{ZuFDbkJn zQ~g52lq^IbVL)eCs{i^YY^?YhnV^kTmyKQ)HVT6Nx0a? zLF*y>p`e{gXP$df%v`J^@qw8T2eu4RFFt(}B*{Wn#w?l~$^#FDpXE26EeTwF_=VCl z`-hY_OiTRh`Q#T(7btibo_ySe+V=4?Hf!nl%#ko#WcCbAtmz@*8)$YZ8hH2eW z6T8SR3|V9AV@Vg{k8B+=omuO{=NnmD+B@32>l;y*UK`I3wJ$DjvA>|ybjuJ(B#^rU zQo2w1+Gw>0k;VMQHt}*~O_1kc;GtUm3j>n;U%M&0t^KVwy=_FC<(<`?g&)do#14?( zh}?-@6c5ll5Z;uVNHh=w71G7Z?c`myF7mo>;qwDMXt~|t`M+oht`-F%PqlIsrSk8k z2ZrKQrhn#RERw{LO4D?q?F&JHDC|G%YW`MuebhzBJ)Y5GpLyY^EQLt7vQe6YM-kSi zOei3@8UujQXEkME+9KdC@h#th(>8{zRSkx)o2hcQxnSu#@7mxF{_MI^W#*Z7>V)LI!j*J-i}l`3hfdkzz@1^x?p0Exj|ffx)@k z>vxG#f)$wu=EU?m2+M&zgZkXq) z?%XNW!n8FH!Eof@QC^?fW?{f+bLBCfxmjmtHZ$SdFoqlW(h963{yt17Ed$Le;I4vH zCPIC31gNEqTNUAsn*vjalDxFl1S@n;+j6L(l4JIiC1Wryw=)EeI%M%=+S!E#u+bxA{L++bIQ;2Tw!|GQvv|oak z7+|@vCX=#~bEw6R6cv)EUtBHx%=7Hn204f3!N(%1b9*%pXCL0B3LtmD)%wT^y|XR5 zhWTSMI;a`--~|QLB>DkScu3*y*|<$R4&nyt#>`|zBR;fpP$1H_LLlCvNnpifNG*=ydRq~VJX*uQHTEN&|0> zUT+w*JMQ01PTtzx6Aui;#8>MNL=p~Dj3Z0bDYMq%; zH}L~G7D`arVPu2M#Mu)Hbfza)ey;E6S1n5(kWtyvs_~hpS)16nmlOyx3X!u3*oSA0 z*MR6>ZDywdfUd^_Ps^xUzFZ9oYGh6ocR-8*K?%6JW%=A+VR^OWpV}nwdYoO_^C$Gu zb?P4A6&M*Q+lpS{B5t`~HI|zm{+5R`o}Jx6l^kw;4Rg18FSKY~%d>QHIeLU(DB6=32>qGVkSkU1)- z-KU%8FshkA>ldf{F<%!;=RgqpgYs1ncamYw`6)&6xbbmhqpxLgVO_gFD#N)-X|r!? z+}^UKJ|X%;KEZuL4u0Sl=w#1t%t~&83`nwAM8o@unB@8W^oF=5^2Y&-Ug-AV=GV8I zhOc*V)V+X6QXwzXQxO=QHW70fKsz)bRt^xJG&JJ$HNx#I7PM_p_H`!Wn{lgQw|Kr5 zzL_cA$NpYq$gB%bDbsH|`A$afJoP0+P0Qwr=*}dfk|PdWs|8peMA@dI*;YhO!(ck( zgSILZwCz`kLZ?**#9N zx6M^EWtMkzi66$bPWD$7fM`u>W61(y>Cf%WpZl&1@1Q^qp7rZidxKp~8yCvqPJ6q^ zJesNn51%tQ-@c|#5U#R|trvo|1>2@8oo)%jYe{`X^bwb;Hcvb3HQ!fk95tjlaIGWe zOxy}|KPuUj*|5gah{dGa!yaN+zw)!MWWZ3Ls7pQiuwJMAO!tc`aKcu8joazRK&!Y% z0;f;~XaK|*ofg$e&3V3)_iVHZ$PsggUN63 zwPTEFGf=8W3!Jo@>MXCfINoC~L^duPeIDoA=Sl~std!*XhliZ~Rywjqy^TdLvBgTq5E z1{Pqw{`N*B@9Ij?Eb?b&I5;6wa9n;_AHT%UK^c>vg+{Jp^FF^^72zxpPm6qO1$~IXY7by=9&E}E47d6S`r4pEjX$<@iLdV2MIL6 z69@44(`yih@_l)X+2yidiu63Xz&Z*ZG9|}%(PT-=T}@JLaoP%VER4aI;r76-aN<@u zV$@yesPDTMHlR*Al95H8Ua|6=zNf9%L)riMH6sF~O<*xCgv2-L$%&R5XN=4Jn$t4) znik9DbI1|Dn-Sa$^Abk=NQH;$&!xKzqh$1XyFK>p2r$@dB%%})Esl^cpuLa);>)+M z%sp){zjD8kC|vkL7-_xVUtEE@U_?rNnd%F>(;kF@7#qMIl#Jdpj$0OG3?ctU5@&!6 zqqRvvmLOBmmc$t6RD)XifhpJMLx3T#nE4@HJKvYgmlSv3dF#L`$^&uo$uv`p49UDh z_f+wbD&;j1X1yeLc#p)hLWl#zC%jkhw}dx9d;W>nlihZ+XnIW8hF%lNNw~2scTeU6 zk`-%Xs``kd&2p3G3fI|}GvyWDGwL&-2L8SB84+`DsWb4z{>b^Ya|3d(P*>Xh2Y%PU z|5Zvv9!X$h&mP{z3D<&x@|3+CZFsrY85_0rr6TvO(Q03(J z2y^}UM1HjVd+Ny9G1iqUk}9`bKgS$amNjER`V}v*s0#a7bfu~`OjEP0O_tV?c%fWT z3YBjqTbA997X8j$(fO>~DXh9uf}`60M0DY;8vV|vy(rZ=The7qk_)giCTv!D>*(m+|DN3sYTPpvHI*awQ>RU#AjhkRrsO-E6ixD7DU)_W-8d;Q-^zv+Iy zuX==tKbTTWo`Me)H|UA~_0_ynlNM+EjE((>t?{bLEgoN~KT&rdDECQQppxjiYoomr5`+h7A_bP*0+K-Wo^%r6-C`+oT}WF>4Y&v`w$2A5Q6 z2XA#)h&4j%kZIIcv(+(*=4$rm88AJ>!3btyfic$Epk2Y}drF97V%*aGQ)yUO7PrHP z<4E~61743Tt^O-59Zb4vQaEyf{a6HUu==JKxK+hAvrs$V?}U{Li!8> z;b!MF7k1-ayhSHhn$ZKbbTxwm5RRN!|(5 zg@jp@>HJ+m0Y@>@Z5e)vG0L{c<1wSXmJ?NB1{zKy935q$BuJ%b@OY8rYYCc-J>i725BF&mE>1X`=EPXq#AYH-)Qc< zKe^v2Xu1Zfnx`g>mNFP;Ujw-rk9`YTL36&5#?Ae>M#enORKlj8M&@&bCY5IsxP1wt zWj!%SCedXlq0#5bFLSc1+ht!Lg`YWgWNTNwaXR>^Frcx9$~OZnnF3BTXe|n^V30wR zQhTaHkOf>>eTG`hV_iinqkL4E#*w&!YC(?&dnAkCKMiit$)Gww5mQrNA5>|qJpE3} z)j|=oWc_mVaEx1)AyLr#=KOpu%U_g{jbiCC%>KxLDyAk#Cy+`H2nYKrFPCxI`{T2O zULF^)L50pyP9+XfERzGHg+^uiIK)I`wOM@LWMOCfxL>U-ie^F5EKw?Pc*kdMu5s-6 zjuaF2Fi0a=BsV45s;$XMsZ?|h3dEVC6xo2$-RF0byIQP&2l5uVXrK}AwU6jLtRXF~ zC5(a@ISW}}m6Kg*ZQoO)Q5L&vmPmf=Q?Po;=QWa@y{;#1cAS{@QWz~S&Z=9Bo$8`s z!%CJP0vQ@h(pOp1u-2BP^lxTciOZ28eb(06P6E>w@O8&nRZ$^9paM5%es+jfeNIFk z8bA~4?0f#80UTrM2JQXH**RaNX|fu$(yy89=x#Bm)p79j5_5ONsPYJjDA?)lrF32M zz2Fhx$g^Rw)8wiGQmI6A*cckt>8y@TZK~_QR5O={$Vb)}+Wyd1eZQsDj5XX|Mw~ax zhMKr+nd#)G9*Sy~+Uqm&2TfxP(%;tGK3t6_4~x%UlmLQts&NO|g* z*u1o%=Ye=7@?S zY?E61#b2~N41Ej;RhmXE@m)C)zh#V;`YB&M9jd?>w>Kro7`Fy>nlERTH*(ls=Tnh$ zTy^E@?KCZ%lXrvS5&0JT7V0#^e?$EQ_u4Kle#r1d+Ae{M%0)7T^CR=ur`D>{HW=X8l&e|pjC87X6yY}~l z<`!$&*~`PHwO`Wv#(e4_<)hQpKWZtS#3&!ZJ0i|Em~|uWC_2-;61@VvGQ8rreH52O z52!P?pC2n9MpTM7W8jp`ttNG@(A)#)_`DG)z+mD6(sITeN_G6X$k!Qrd!P+nFh=kH}ZV=oK1>be_R1v_JM z8v@NZl+SE)?@;7+GZZT}Dr35+haB;WX@PpT-NTAf{p9M#Ehc$tT7HgU_OB2g#5R4A zF-+vG`Yx<=-Y{ySDuf{T0r(By4GuBaogW7`)o3O{ zFonx!4esTWOdl;9gjw#TJ7xDo zDr!oe;HGV(2V!Ve(^{Gf{Y>Q|Duo2cH6*(B#JrnTgh|GW-r#?Vx68BZdAW_7vrH*V zYOP(L2Z=viPUU|7Emh>Pl@+PQ_BI!>j7^$WCk;;11xmdG2{|-Z zjwZ1L+`v&!BI&QEQ;`WtA6|`4IWyObak4vp8HLZcg1N4QHPwIV_)+CN9ODqXmhNIU zC6QOaVL8395ao*=kZ*W$E$+bw$!bhrb{RA1Cb+!TNjaL%u`M?=pXPfUE***}B>yXD zcZ|0;->nGnD?e@rnT?+84sE@VT$&ZfQFsIQ-eYg?^$qz@-;h~5qm99NrVgE9Y`OcV z248dB&DEUXdAr4mW-MnEf=6B!l*wQ-AH!`pm*$|@>%C}wei8mV7 zlV-~}>Q!^OELX|GjCI$$j-Cz#O|{(@VI>nBG~DJKx7B=V%2@tSPX%h&y=1F9dV4b3bmQ3)^1!qX^ zbxvInyI6OMoG~wT+Hz0w%f2vCWuj^BO@7Piy+T1b0e&?rIt#WT(Z47??;5^IOIrldnNCZ@5dJ#;2Fg;_MTf|H`J z!^BHTXk z@WzoQCt?;q-PIWrCwed%1<7^tKY}AuGK1e@lVFV6O@iva$@4AYWu2UKT2*vBSR%y= zTpS?qIYF8_g{so46~f<>R8)AHZ{ z9vAE+2f0se#N;}9@v#_@hYaWgB!ZlP7+hGWATHmbuM|ErwxP!gE)>6gb7+GRA#^Go z8KNJQFBRd$lUtMi!9VgWd!owyMKc$Dh%&ku?iSdgu3j=K%_0~QfQ z-sn=k16UCy`-9VkKB?>>2axXG9FR3BX5Mbs6yKsSq31hzu3ZCWnydIh_|+RgnB#_j>QlC^6Ta3-ACJGN~*nb@{H zF($Tc+sVYXZEIrNc5co&|5xX$`tPl}wRi7oy{r1|wb{G-Sxjr;%R-k2a1KK)n-1Rn zyf5lULEb&ugEFmTeBiZukxqr==mX`-0=$wbZR?Vesu3I#J8j;bO|R42-L1)g_8Fr>dQC zrW=FT`h_Hcwz=o7M5KJte4=i{==FSM4I;!8cJaAB;Wxg)-h~djV_M?>d@dFZ{2W5Y zWT+HWh62AO)#no%`y>zn&W`g)RM%AEgMSC>wJ>t`7wY842Ki)AE6@oRPBubOYm;*y z=E5pj6FD2TUQ(|9pzDhF2KB5E<0{pb%Qr&70QkvV00AsMI@Hv>=uL0nWfi6Vo13~Kmh+9z44Nw3p+svCoxUmJF0!9^qPs`f9OpCE$xt>I!GBv`aFb(;? zbu7@4i+Goa8p{M~?aSYDC~x^j{x2D7 z5dykCtXH@+CQ~~$F>u$`cvme$mm$3z>}AK6--_oNU=%&pe&f|KB*f6%9O)>WH9knK z#BA_Q;a*5YGbeBrndh+GQjON!Jlz&AR#8?iJviX=yS~xNji>WJv(%z?SlIK|3FSDt z$&VrdZ*H6&4coO+?yQ_LYOV85c{n|Sm!yL8?v(G0Nc0K+jNn zyA<_1rUV>{<^Q;ibZa{$2|wPhSontdZPW6cv)nMy$4!S7^V~il4f?FEfLv|4qr}rK zKyP024q)iqrg2I%=Fz7gXSfcjRAt~R-`mfK(IaR(dw3p$f!FYn832d=s#ahR7&C^s zA*Zg)gV60|!%<0h;|EwlT9J8P$-^AhS5KIuoloCKM?nCf-Y0>`0I)@%D}q?>vqoe9 zLt5_-SZX-6yN7RvY?4WgWkgb^u*PZ|E(+?!WkYy+YHH#EX(&fD8ak5q>$S+x;Q+|{ z^_dh%?B`ulB+7)5*iqPrxfZ{! z+0UDV$yIF~`Ka|m0k|}dF(1Tg{iH91!EV60l5E(GWQ)jTED zNY0d3V|$Y~MF+3t>gAFFq`S2yC#%Ke<8dpH!*R`S)rw@%wAAkO<{HwoglUc|7}*u8 zx6&;n-I!NS)-J~IUUl!R6;7?T-G+)+a=XW(=HeUNti%rqkgE~c9f6UnLkK;SUtfA? zNj)>|;>;hTQcEf1&#zbxKB{w4_o-#zMh=KF+xp-(ydqC3kmk|{1@dwusQqvP zhRhpsApi=e*CSx{b)PppBw!5EP#}eNY8cR6baKv5x?$0+UCysYIDsR*%B(wd&ek~p z41uqvkGhAkdep+Qqu*SqWGw|5@P~n>Ns-I{+@%SHj)DduWDtje{xc6jih-LY)W-ze z=Xc6i8p-|}&f_p;#tdaJhvp4`16SI~f?)`>uTqBZJ3j$pZ| z@2H<}dWI$ivw7R;nt&|jh~!UM7MnCKrKZ|Z`Lo8@+MVCdJWqYgBK=zrD4TK zQN!>PzZzj^M{;8;+YvtxvI;*37Ty0{Gh$+f*9?u+!&$Un6W#MZ3R|24b z1EiV@SA8ZT*~kw)#QE`+fv9|*T470(u%8AvH>Ia5L-WP$c z4gpNlKKU5DlT&l2i`C@dZsPU?*@lOPh!EXvKW{tb!lM%lz`i`_Q(yfdq)81og<2%= zLQrELf@X16;9FO_=oNfWI&J9ATTg$$ph^0eD|XLNyGsv^9pzFiyvWby@Cgi^ILF5x z7l@CsKuAxSwXD16vW+%~;FP>sbl(3v4YFMKjL+^_Y{7=h+|iC8R6{J!I4aL3>`tz)jdu zSKCISxxF)hK_BB=py5zBv6h}<0I+N1T+yLB74h^bW=KKnob*3Q0Z#SM*{nnQ2K|Gr z#P@F#40}M>B%_2>23oB2tI?0hZ{a`;Pwk3aex&3_$Io3}hehB~&iz^&TemG_3~)!1D#r z!MUI2)KgtuxzNtLWr@bK1*)dCM2pG6k}hfl91EdJKTmaQeX0g11h{B!3fcA;J%MQf5uNjbR$%1Ysb6jLB9fE=yxppY-ngJv)%6i zfHAIs4H#f%VhRmaAxFC+SMd-!Ruy%|8sYC+m(0_hML+SW;w4)*5}PjK?U;9V!9lE=cg3d}gQe$edx!1OjF{yGHF(P3SmVSAv#nP^1`v&+d+MwJwy6_ z%(PA8=5D3bJ(aJr)RdtGOO4-#SgI%RawYR!f%5iyfEqfaO|UPWNp(rwAOGr)!eW~R z?*2u!b_gpHURcI>E`i^ORYY|w!~palu#%kG0Be6dEH3Gbf>;tEliHc?L1;WOz=UOc zw-;Hp+G+Lj#R42YNS4cWM-=qC2mUb|xb<|7t>9IjSwj9J47gqSABenm9FIA$A&enk za_Y4<2o-m>dr?@C*o8OMZs6@GA;)|}pkqt#vx}?6j1k29?KIp-;|BuD$3JaT^FKpo z#@zju*1EGk$n^vu!2gts?~^ya9GQ|J1(EE9TL)|7*GE6Y80PjRa2Fg5fmXA$S&I?3 zE^Op462T4Oi&mQ?i|X6`;vtLyPl5?V1cP>77j9AK4Hh-GM=tgE-D8XkU6^7K=^VU= z$F6)4;<7)7IW~s~I}g?yxl!hdkEWcqCR^nUW-_L6?x&~j92l1AYFRdJp`90IXB)+` zKV+K_&rV4)%T4+bwGvAa!m#9god8u3k75Bz=bv)S<>o4 zg(jr3V~+aJqbSuq8)~PhleOeXt8V-HP#8DPw-e4g&21?vKgEIC9d|$hOcOnEsV$%1 z{cO9!%iP?wK?`xE0U#7^LwM%Rm^9Sx(ys)skA(%Z^#N|E(3qtMpHJ8&~}j9k?OL2n7kBZ=?*>ABe*XlZ|JrsMCh-=W+v3|sUr z0M@i@(PKWOvZzbnak3zCs5+8gN$#9Cf-WX?ucU{@+PmFvKc<&c!>Tw$Zf~EpIuUg3 z+mmg4btd!QbUwg3v0kP>VYQE-rvp3txj@@ppYo%za(S$L4jj?%3emnh?@-0C_)&9* zIP2&lY#>BIUP9tQnO;wxB6Oay11{TTR43#IN&zKb=f0K7G^jKPH%Q+5m5Sb1oX_$=o5n3qw-1Bg~Kog~b{q zpi_}<4-;=rk7GPMXT7Zd)G6R~85@s(?8C~#l@bEq8N|B8PKLu#o|m_NK!wyc3E2YfWwKmC`0~heqKbc-gQ-hC_H8yua@!HpB+2 z@B71OUH$RiFlIG~z?)GYHQ-z%o8}Qo$i&Mr#Ga-BmpE5Ag|>|L zB_CIysV=vxvwY*0Pm(T6qWz0LbEjB^p$FjrM}(ULuk1kREeb?&8U4}%LYE>Z9AOuT4Z5i2tY5G-(W>8u0R}kCaxN%nQkax#q#sM9!uk{HUH)LaQLd@ zb(vY6*M|3<*5mfM*ud*riJ5tiXg|#tM)Qt+n;ca}EkvjkL4X zvv~c*IhEDwTQ-ue_j?z%CT_>wktv?#^F2=&$HScD(5AXHr3bEg`rSnUjiQeEMl1Qv zx7H3o>q;w}e8>f!*%lJKlYMNRsTE(_E7SZKL^A0-l$}He==0*e^p6f8hC&ht(nEu1 zELh!Mjc(9;OG*hw;B8`@)MorvtP?Qjar)Kh^&E=Yi1wEhqC}4TB0yG(5xJ+N9|UWN z?Jp5|>mWLSAocqD)6Y3EiuNgRP>DW7l=Q^B1Q$BTWKoO+!Qzco7K*&PTJwZQK3A^s zxhCS`_+3t=xQatfzYj>dhsz4weymo+-4W1gOexasik9PL4d?+E?%+4jQZ^ZBn>S^e zy$bFlx6cT*994P0$3x2N2kg0f>%mnAEPQt!7^};n-1B$rkGMy+Js=LLsO`3mu3+p% zh{#KaJ)0+m5fXchmEYLuWelQg{O{KbaeADPmvifaeb?u4t7a&XeW%^G=9m+Cu6MK= z{Nbn*m;3cml|l23;BDzvj$bFTEKA|#tsXhG=Qm;5Z_U+9x=LOGbrO4Fw{8|+RU|~? zqj5HL(ai{W$YXCN4YHBEHDg^R5BF$&->8KShI2td8zR|#rNGdlbw+dSmTZ9=XNqqWm@P`w(k z4bztVrmKD(kZ}wRdySP#z?+rb4RPJ`M(iQ%0o9qt7|CY;c7M}f4gc8D$ z%hqQ1eY)cySF_x&!cPLajd6(u;?}g2Jr^-bX*69s1M|6Ldnb{qGi_MFMakayw>owY zD#*$tcPBg?UXuT9`1WLb%Gj~Dbf^TkDel?mj=jX6&G4a9M9gy$>uD1RGVHNrh=DUX zVk|TJzG%B)nS|3F)m#{xbS5~AF81q0gh18(6G4!VGh2h+&L~=Y%AOIBu~g5Vj7+Jr z)leiVi#d;@)nm&c(?aL4P35(Zs-O%S{N~w4Oc-R6+7o+T+${aq&RyqI&FO zTkGkF<0TG~Opz19-`ZKfX1#)mSVYmQM$Z+%9Ixa1Y4vCO=QdGY+y?Jle{;-wm4-$; z7-QLl`XA7{I6c0%{;IEshS zg`egD*w>2s41XeAtQAW_<`5C^m>N{p%V;DkHOolENK^#kOVuFC)zdzz#59u^!z@K) zwa{CqB~SJJ z|4i~z?oWstbkCGCBi0YSjwtUW?r<09QXN9n>RYX2`+)O3fe&Z}_)nvIfAS`T&289U zDGTvp3~w9AP&lSBUoR+lln=oo{YsDQLSal6FyIr%+VMoRF*Z?`XC$C%m-UzwrK)oc!|mJxZ9{+h&wx8ziM)T$(JUmie{E>19o}x-19@aC9eXJ7JnCCOaNnlvuWUmgN8)PEJl%NG zy*A+r(gk*Z+s??kZ*Mp~;f<@Y8}N7124u4b^qp0F@{`crq*0k?xKC@vVMHU;xNGiq z7XmN$Cw0tV_pzf_3VdQV2c9Dqm37}(spcXW<7RO2#p2b^KrcH>ld*LPqgMqa!FB=& zFWi#Y}rx zsZ1GS zLxG2}K+kG0euTPu@+op7MjKzk^eyyc@n|)qb}>o0nkL(x(GhH;`Aw|5-;Rw!>tEU_ z97Pn1;xkn$wA|!H1eTRrpqbGAo*2ziZf(YQmvYc5n)SL|q{B73)J!()o8woxB zXE3F-cYJyuRlhFDGzD6*j_OvS)yiBUA!Pfkjvc0ce7Q@Tp@(Qrw zFM)c*R8dj1Bx>=fkj!{otgd$UJ}t$x^c0i zx!yRcFrhIbhe+{;P!e&L=duIU!Ty8}rvRIqGP1tF=myvEzkQ}anPn0n#w z#p>FD@Co%M09}o;`a~cH2c-J#sE~!lZEvlLQZUJ($)M8OYgu7IqpReyORFRDgXr&+jiiG{blNTCt*iuOY$UW!2VqY) zH()K0EKJa&72%`1w>ONGbIJSTWvQ7My6CZ3X{s&kOO1?F4y^nkKcF*G6Ps&WSxGHa zL{wDFg{`$OW&^{a;{^N06q%S#!z%ua)CB&CZ2-Ie)3PrKAl@e-okvZY3Zs@KFCQB& z9UGO2q8^*b!fUK{^HP%-94{|W=1`vlBvMN;m<$xDCJ;{DpsHWHO5R4q*4Z-|3eH8S zGqfxk|1sy-7ymQ3=epQjPf`;oS+-*#iF8nvW)7{%T$e}6<@u49(Vih3+CYN(NBCGc zG&Fay91M|Tm6kmjUsv>SCI&LZtWjFiZHRCC`imAxFZF$wbNxC|? z@fjvrsA*a1yzVpOX`{U)u64;u*LgK>n0$_=5~ws_XhHDl*XgP!*%KFP^b?`ejFGp&yyNjYG_$fg-wiS zBqgS+VqxmG5)+ZGrLbFE&nh32n45>zkZ=sBL#q_gsn_FExeBN|32xLI=Qe77rNv}F zkVI5zih^cxVq}bFa#TWGvvzCosXpU5)VMHw7TI(km6|q1rS;}vRX6Qwt2;JWr#{4+ z-SPGL9zKJv#r6*D1Fed?X_!busj1!h=J^^Rti1(-g<`X=}^AjHd79v{k5ZN{tlT>uOiASd&yZD7n*F zuEY~4^}_KU0X^T1)cGYyjmqxE~{ zZSBWlRy!}b+jstdYYt9=;S;TbV_}7Ah#E1dJNn`?o{^n*dKY!B{HYUyXE6jf< zHJ}R9(2UOsnN-uDL9USdU145GqcN7SB64nl5m~Ug`PlLEm&oTyin+rr@1?W%;ac71 zdB&~R;Roo_&Y0-U!C^vY(kuy0!EgiXt99kEqd=cYC>U3zW6DB{qyO)d)XdFC8CkV; z#s{4@r%nIE70XNK&Yfq+Rrb?u_2kKm2I~vNrQMgnqNPQp&BTWL{;SS|r%Mwn(7IPK?|)2`49}}&QgU4`G9Y67xY^NM0 z?Q0}$VQ)fYZi4;W@T%0$6u;S^&{_dX0>BVbQhf9<;|<#l!Lv`htN|p~QYGH^jGv;7x<8H7uzyrdL4vThm z28==^rC-?ph_6Vb&&3{_d3Bz-P?2(a{$`q#=IH|ZeCX~G(QtXR-de!agkY^nu1Vdh zmoW%%!c5L!brXP3i|LLu7fcCzBZ8~QZ;ijiH2&*IW#I&5)Z({p-?FM={3RqEo(OCG zsHsbwNF*5YezP(qm5tmAafCLx)+rvEfkV8Apexngo>iAlH?pm6qFllV4 zk>qUQ3PC0fIU5=BunS{U0+=965E`*)jS*2T!5^SG&ib%it?UTWd?jLyLa+*%C}eda zWkS)IUkm}cu^$NZ*fct2^d}a5F|9%0u&(hWBIE6)8Hoqh;r!I0SkRq+y_AZ8$13wU z=ClJd{K5x5{$4-}0p4MO^89A-n)jgY$OUZ&60k(lr^P+u&fDrFI*1Z8E~mYgBcx; zo0@uX_;R2BH{%VrJqTJ>Zq@}K$!e&Fru;NP{3Rt8q4N@2vOPJ}Fx#KMHNF?KvT~)_ zpnC)v*5#`&`A)SiQ=7dYPXExa+Y+F}w5MiG<(fga2Y#(Ynz21=z8V>*CQ?DEE{k=6 zQ)s5{fOCbRRe;)cG9-vT+^2?57U8mHex63#j-8BZm%Mn?Q#`tU0Zx1WxtYx)_fzZ{ z=@wy3gPA|QGzn&`jsDud1_o8rzO*3J9-D$gVV1p{Zk&#AoX#>tJ<<3$rWSf%(vlb6 z+EgPSk(~Mfud+FmL-92>JUMQ+tgJQC&#wZOFu%7Q#|hfYsD0zYmQ@W6wQ)Qa^%Mry z%xH)bQkgKnJx1@(+lTe_v%yg3sTZyM79MS6B!BvX zIVkwR5Q_z_F6vxn@98rMvjr}$dX-G`f=Y1%A|9D_MTCo8_>ZZ~2Cs0qa~f$CPAq4V*BzMHkwf<|hx3OzgwtBCd3Dj!HpgYJ4bjFD!H z-7J&1!FF&vg;@r1uMuey$l7FQrLA-tN;N?eK}2C*-{GLkN)925PcQ>>CyaoNU47S>t};*0@p z7PtpxyORojEHTyXhvZ`jM~|}cx=mR${X%v6Ji=1#0s+#S1p42Q>EEE`U&tjR0|OKN ze=yj;aM=IIm;YDERLTCA@jnaxwPt^a|44LT+@GVOiWDp ze+~c4`D=`k?XOO-u(1BG;eXBjI~EH&GyZ>uf1HpcPzt{brcK>eUzhnQj`YXmi+wz}B#=m3Je^I22Q0!lQ`0uT! z|GR&GwfU=Oe=qsF{l8KFA7lTur~Yd7-(>OM3Hjf7{x@a+r0^fh_5YIIzd6^x^7NOY z`ahm42MYr}4Kw?f9Lvni^2Nt8ew9-Be}S%SUv%ofpexhY)W4uB+ZU(%KcFiI`@f z|9{x79qy1WN(=W-9gh`tmlh_BOsV5>oWz@isNDutWMhrjra|G0hcKrB3 zl}b<%`$0n(ebj#D>RFU6dRC|u%qFzc{Y{P=DtHHpbHMX4|j{c9nqa6-yodWB%KCh zTk*Qb_Y()el-8eHuRDVIj;1LsEqD%(urva3oz}f55e=b|n1?R?t zUH2JEp9-L8pz4mo;#?=FP4^5`qT*}Hy?!D>%0-8=Kif4_%2}JD44c;}hdi&Qrqv)O zmx^cXl>%Y8676_=Q3v?&UPxe9Kb0bTU8X`4gtIWF@0c~9reV5=DF$WnWXJE@L+0dt z2Ck$KNNS&4r?TxCxw8*{K=NL=QlJ2GXvO}`_gr# zW4MlpA?y+Rk$W%7z~!LFrLh+_n)gyYqjrpmOw<~$fl49@`w>OpwIF0vQSRt=uZ_;V zR!|;Mh^LQdG(PQCQM;E<-LuM5H zX0o7Sl#8&PHW{U02VnVjP6aufjYI_;sDg+aPz6dM0&>|_VoL;T;X~EyL!;TL)Vsm(d!xHYe`We+@vJ676Dl^3?wnc9zp>kIj&B+(fr88A_e!~ zb|JYXwQss4OnXUK<||zv%QbDDOT&;X=fUd@=PmWq=an6HZSNx6x(AU|IlnupX{`31 zl*!VPXj3%hFRN0vt4bhJX1r_^{X05bla|~qdlXi-tW5owOeU;zp2uGv3O`6~A zFKbAjTf8P5%pKyp-q6!D?JOp0T4G;rcBNyBpgzZMR*>sPla}sXmlijiY3N?bE-CXf zX^Jn?Ncfg6wSU#S0z6f5{<<%f4^uyDJ6@sQk|nIqd|x}RNa34Z#m$=L^;ke}O&gU@D(tAtJ*H?TT>X1;6E)CW+iuWs4T8qp|kRR)kJ^j{-)Rn3Usi z#9NQnK!A(mXOAu|RB>e74rJs`dBShA`y&CeHCb4m8LGpttxZ?dVPc)wNb&irsh$MHS%_J7|) zw>a@?d}TzMVLx&Jsc+xlDQ$zrkmsZnGTc4^zaxaBzjS89=b{8Zd&nJ{`F00=hvva{ zab$gDed1N|s;H;TWuFUqr5(<7RV;B6MWMlM}z80 za4p1nE0b98f)wXWWRi5i2aciys&l~%as?QLJ#aF=EC2E;xqtE~Rpda>+3WF>5ETrx#4?Xl*4q44_1#@0Mx zdqrXodUt1U(_R1SMP#XoVV)IpiXqw~x#2S5t&4XJcm}y;;R+yH`*z{Li|>Iy5!Wcu zbxM2jQU9tbS3`KyGoFykV8)pSnXerNo|D~89@X0fYjV!r>Z6m?m939<@?#Si6@k@& zY;qufn+tr??{Me&iNOQ&>j~fNA*4qb;)fm***px&7*0((u}3pIPE7xM{JRO%9QdZ> z`0Dtt1J1D;(#2ktn!XuUCx$kNPKZB3XLb+Dl_6NYk=vwp6Kg8gSWM~eneOSjLpF!e zx4JjFz8csh)QF8eXYDZDuh3ijc)Zjy;Aajq=Vq+5Lv_=%DUl#9q(8r1r1>`ibtL84 zI^)zu{U-d=4NI5T=A-$T(_lu$go<PmI;su9ApzD~gV*Dvsj zSJN+gj7>Y`Ti%&f)tS3&TQV;ja@xxphA-FQLmLxP7t^de*`m9ooVZA9Q}3nKr&Y@) z)_~&R0{?TTy>~@Zhazos(ir@(F>Hb-uS>V4z76?f<1WTV*u!X1P*NDiKF0Br66kR5 zxY*ZUT7F9PyH3oO2O4tKX6POHdF#h?Rc6jlxiD5zIR*zA4>h|#DMyh#IyIWXlLwc& zxfo{;n?SOTbndY~Gu-nLnJvI+CNebUCdbRI$e7G@gX*2qyV}2h9lg4o9j9K7fr1FSB4>Vj*=|PE6j(m++%XsX@R6DTCZ6M=nZ|Fw72PQ z+3KlNzV!?5T10UX$*4a!=GU+c;UETUjfn9X>#Cml&t#9Hr!gcP4Di0Tx_lJ7?<{$H zM;$!;I^^^9*n83e)|2@5Y1>`5&ZX%UiWfsuAnr-`M5*c*EZqEcrz*A+d)|k3-{wTamOyyC1 z^7*j%fpz@j@kW9x%Qb)P2ih1=L~GB5P0sBq@f5}U`$JedEq`WQ(9W855SWK$WYxMR zG+K9>6ds0f*jG2`H*~ND*0J(S);yssl}uik&18zpS-Y?|;1eSpn`2J=6--*2kT$f$ zT?bZotT1?s2Q-hZfJ_WP?BQVVX&Th|dmvf($sDQL85Gi|HOs3ia6sRUX1ul#n>z{t zZfetWAbU53<>+e(nQ-A0$k>`pl|>yb+_^joI?#1MXYSUP(yts_YbzSfRK;kD-7e=I z?(mZ>J`OUJ^@juQ-&PATT1%|Vb3J8Bu3uNC8tRGb9lW;`1)A+N^SRkA_Rte!309QlS83B z8mt8OlK40<6kct8;syra<=P&1726h|+3?$w>tV%GXg%QNT~*@=ZQtMtZ-?nfy~;Hs z*;eMDRK8rwH@CtE27kIkMIQ}d#b84&N5xQZpYZ+Ip5Y7XHS|IWv^gHAhYuVAo@|nX zihjM6ck#f3l6`ta>1_BbJfWU@nbfxUCjpe~2Lnpwvph=W`Csc715Gw0^fuiqu*XeD zSugfYywB6VL{lC7W{bt9CYcNw6+>j744!fFvG)m;voXBnNA$VnafRCh0TKa;03`=O zpXBw|0#Y=eloo93v2jPbVSQklA4JRjBgY36)rwbn?*IBI;HfLy20t2{EA@&E|A-=_ z151yt`vVK8@g{f%yhJg_O4?^hr8#=%r@tFhf^v*%-#q|*F!CuL^O_y8_W*K)H!#f~W269b`zpcL+U+EU{o0-Hki@b@%mY6BMX%w7cmyHvW3=(C+>2hE zJ@)0D9i1W|`=xHsN)s`)H0c!u{XjAC?=@=plM%+`f;V1`aT#t#)XkWG2N!;i*D1Vv zE>GZWsIih_kC>jjpWbYNsicm>`u@$<%XM~)t4d!v4CuBK=5V*R1yw2G+e3u^#u64Kh=~wg^5CHVMT>SXt5UbGTJT#Z0 zlk0Jbuz{@Hp0fn=f#O2*X1!OgarklDqm~rIA_z3GWb!X@kmbkdnoC`E~7s|HD9WOUlM2anC z{vMDwcQ7yC5L+8>lzn-yWqq)(E5Lj8w5khU09%ffeD)ppbVnl=uE0pWzcIBhF^@!d zsO1JMvL;5|fKG`-rR84w@Z82}kW=2=l;VpIRyG3qI@n^@jiChEoTF?3-xq<|$1V^M zmlYf*Z3StF?AxE~7#Qmt7%-SgFTFSA_FZzd9K3_yV?%D5UN2|Hl$ss}|AW|oezn|H z%4i~D9`f|9`E6L*hE#)rkZhNY*%gY`dP1m9?ant*Q2G<)F zP0~gj&$IfP&CwD)4>qKIfCn^VpO18hd@{U5T}7_0mllqq48>9Ia5D_`8<+MgO$@8| zcia@yE3C;+ds*98j)Qc7;(5=djcI4>YnV?2v3;~(5IZ`CVz)|dd`sZPDzYk>b$5Db z3Z;x4wPU$mxgF2pmK@Sz4Q)jqSu-|*;Q=?NcAR*s%}#q3YA12SC7EFEFY!3m0?kVb zDT&IPp-}e<#m`@d#!4DUR21jT=;5^yjf5~QH6_D9kfre>7X~;dJ_IFN~NjrYNV9y|aAH=?BZ*mX&m^3E7OZvF9Ktz$tPvH)y5D}XV z4@$~0JR=De-P<<2n##{>i|T<684-10{z+RA*T z_@+00eT>@nKHeE?xC#D~qTGE8$c!h7CZ^?L>ajhSP&=^(X|q`-i}aiODYq;L^jD(e zK_2h2%xM_`Z$>i1Q!~rXfupeUA$O+I-R>=Rz1MDPcjITA`w0^Lp(3lmzXXGkq_JQw`Ha#?C->KY31P)3fS zBn8wY#0b<13=XgT6Kbw%?Oi*o2KkulRPNyb1!WJ!}}ZdwqngFmnPIKQm~ep4SFGo~?-V;Rm#zK^0NYaf95 zS$uM4*WrB>v_6z5RP;rS`!39Wwo`kuJJR4be02VTz*@!aigrJ1gGH_@7V}POwI2Jf z+wvxP44VO>FS%gOefS#f<@I=u_IS3Av@}Ju?`jGD&Pkxq{TsVLjzvtn03$b5jI^e1 zSX`h*WG=TQM?VDEqTW9yO1UHyym2qdY(Q{;Nkb@6hZMOac`3ncG~d`W<|tcnm!!SuQb+(L=lDv7dGPZ;D8#EIewT?T;T0Sew+YhQso@R4F z6%mP#jCa$*OJ4U!vSRy^H@Hi$WELNt0!Dk{xZ|za=IVyDs%^~XiYS^%mEt@F6pviF zP6hMF{ZkHBzU@41q8KCs1_-AGQV}K0gt%(n7C8qYIeyMN-J!6>!9p+<1GTW%?_p#| zwxv=j4B%q);t&cuEItYJaMgPLlqD|>_~f`>r`(SO$@9a`3M%VPg<&TnV=sA;(trz$ z;OULurj_f>A?Pa50;L9&Ufn>k8hg``NaY?Ch_Vh4m3!un3oW ze5BOzaYI%nJtz!}AcQJJY;fFB>OQwf>>(y@=!48&BP&1)z+h=ZxmnqtsCNS@fCGs3pCxaAPG6M27pvG$ zJrt8JYVNN;D-Q>rIn6XW;pV<6Pif2hM(=+2f^;CI3igWcrGvTbi?;QQqwsA3tgWZc zsOLe|?+``ASrn?+tOy+t1C|CBw6G_WO|PYBg>OBRZ^%>hBS6p~FR}zlh%h~#UN?Ey zxrmb5w|XHq4s&2m_9^XPFqDx~g;C^l!c0AP$cQ!ay;=|JTt>zb^eIQrbdLTIWsX0A z0$G7aJ9vKq@P7*X>aeKRK3Y<`K|pHghACiZkPhjV?(XiA5CtRz1f=T#5<^Kh2nZ@I zh=8<6cXl|GaB{`|Wq0^_yp{y^rd~Ts5EV`<1;5FHU}>yQm2i?09u> zLT2Tol(1aDIxz)YYl4;L!u**O^q%5f zx|LX?b>#r(mcxaQ6>0`uPf8j;@8gaL02u_RHgb{2+>CqSv(>}$?lRi>@ww8OY-{OR zDi0*Sy23u6@Hw@aX^+$Af6!we5l!!vbmT+hk~CgK(=kP3aBbD#T{CxlByFa(YTku= zp>wxMi^9nWDN3>9+#jVNHQE-4gBEpSaQ&{Is88inKu9uehcwG#MTz&+b}E10NBoEP zmF#!3)gIx&4*fZ8{MVT`k9kKG2dpxY1Cbj@`Xz!^K+i1cpIK=uGdRBH?3FH3)FP>W z0SFdj*MZePp^(6T%KuoKHBi_ESN>(4Lt0o#?ebS;J1lJwP-M%8!XK%zM&C#{z3x?G zI^VPj1MQAuw3fHthlZ~5CB{pp#q5{p32kiVC3 zdd-^-@{76juSQjg(-!*VtK{{4Yiid*EtjIr7+5DwbZxYhNu4g;R9Ij7X`M+Hw)_`{ zWu$2wYQPtLQ(ijx@O#khVx~6w_m)tDNJ)h!G84G&99O-&HpEZWMZozsGt|X;bU;DW zp)6@RFm-XdPj{oK9d*|zOnAU@JejzJBv|5}UfimZjMoJ1BP;#2$Rjj5jTRJR*Te~| zAw#AMz!Fhr99B;aMHB2TgjEKq)7L}odp_JIcM8^(RhrJua5BSdyg6@Q1 z>iCO$rFKppKT79p5g&Y=cr{>S{Ol$W9Zn7!kVhTtU)#O_on9F<-*mh1w#7h#=4~u? z6U79pr7p6MnvdE%4^-1dW{;=gN*`oJu33!Z)7rk@d$zufv={PxM7W43r&J#8)3A9y zsk9E}UY2G=Dl(aS>Ew&+b{0jF>vRWZH}(?BChj6;Fkh&4>80v5TjyElaN*b0G>h%w z`Pms{@b#rxAveEDa8Adis5Pi{EOMx`d6ni$WYRuZU`eM|FVFO;^dVt65G`>$9~W~m zSZ=?Gq}?fqCE_9j~mZcOhUsa=a(#Kg<9 zvb$W>jXkCG0FN!%4jiG*Ak@E6H8C5OA~8%ndkH6t&6Kk#b~7z=8Lca+@ozpcc^AiQ zuAsti&|ZPhTaM~(k%MB66W-Oa%Y1;%-$%>*RD+AF;6aNcopZ(1UAhM#KjTtw6);b}zPnXN2-7RHOi>((+w-;!h_}eL zmn`&QCmYPuICa&dyHn6jrmI-QtY+C2GTVBBLWmsMmlDn1VRrWIlFof~o6fwM{0(4d z`blpsSNoDB9v0}xf zdSw|YmWvh~8!i~_W#EOamVWoExOzIM`Kg~Cqlb~ja|^E?@g#41hqH_Fj#oLveb-JG!?t7wLGi0TpVo(`tGBGgO=+F z!);C;5_+2YT>6TirXbu^YxC>fQK{pXlZ&kw&YWfnSpXn5N52Dsy>`{f4xGC?IEYj(;@{bEk)gMi*S z;S@*)sI%ww8l^K@?o@7wuJaNUyZ8`PW8Rw768=V{A#AQ291p}&6UIUhO@qD5#vMZ% zs$lyNLt{q!g)sPu59VAL2S9OpyTC$5X3t|VCC^>k9(AEhE58)lb^a>mUXL60op5OS z-n_M2#9NcU;?~Hm>Xk(O5i_&yQ>s^x7Cm{-l8tVJCN3pzkVKA(8+dF@SE|E=ygjRFC zE&a;(F0y`jK)LGEs>7g>2&WCo4u!e;XZS_CdCmdhX#(pge`PiLL~PW=k*U#N+Mqoj z2k)1nZ7r*l?3+CVVzzGk22VL1XpNbQ=OD!@6sbZ>x&h_o4=q}Z6ma3{Z_~~hCvjfR z)gIcg1ZErvWXYNvTMS5Ci6e`Wz40Fkd-yH7x5wK$(sstdngX)xjeW0CKNY~lG;>7H z7?qgZwW$;3h)+)ao>b-RdDXSqCtgat1rDQatM(G~>!%c@Qn;nuLx2x2jwBtS8%N=& z_SEKq6eQ2p_4yoQu$t#jxh}v?&n8)T&%&uAkg(VKM1i71B!hD~ zvmcL!r$r$Q0mD*CyKZ&N!Cq^ppDn&*@^~v>3d45=>wLe55i~BGPoZb|pvPL`9z4 z2h)Ha)Zf-ZyJ*uK2ya7g3 z`!v1;1y!DNyXzJUjWI6jw#8@3qbWrmIa{W10~ZBa!xx5vcHQj{8wc(rmE#OJi&F$7 zX6a`MAJphtq?O)0a)V@du6ts58!)Xig*;>Ba#@pFV`*1k9I-cV`1*+&cl?!x5PAto znI@?UIf7Qe5*d-7-)|oqw45Ybx2Di##k0_q<8;2%cfN;BgFIM!w})*nim?D+z>qdG z_(OIZPZBsE$e4#Jj((;}_5Exmr@#Lht99zgd%fXg!YkA5Mz38eZFTbv=7RiOr+AB&{ z?SEw3)-*lC8SSYwhn%Wu1mwV|y8;{-G4>6iT>lKV}BxLUFgmE&>e?uegHYK9Gs+i;*HDrPvLKbza}Hx`<0vY9;F zUXIsxxoY>@s)2Z%RAdAu3N{4!Hlf`=0Bx4E6tA=5Cj?C}4y@28N}@J16XSv;-%1oe zwyMv6X-jtJkr0yxKa@?T1j}Yi6L-)ID&vM;{aHvq?*nLvM{RTC!(q+g1YWF*$eRz+ z`eXKRHMwl;(J98~IovDT&Ozb9!%_f_66_P=HJPY7?u2@c*P%_qha$qnqlA`ABZJqE z9_u)#?Gt&F7xASMuwvXtZ&x(YcGtGmI9Pc%zv9=Wy`}v^`y)$;g}X&A$QQV;)*Ktg zoG@$(d9X;yI%DXq6eS3$(0ofC5f+Yw#blS__~OkCXWAT7_0EW>-Ctaid6Oi_R_C=@ zv@MggwRl(q}15PpJjWr`effBBQ_C#e597&!#$MWU(mWQ!8ls0sL$eY zz?LN$es>1t#7_elBB~Jl_Exs%a#I*IPMCG z1t>t90%yz~NgKbiijY@XR#u&*n~A*e-LHmPrExV&55Eu0)Q;KR2z_e__qW~nXnv<3 zD{3#zJooBd)>K!X@XlwUy8Q^v5EIxF>a}nw+6>_i29dSVw4t?*)BQAZ^g!Z->?BdY z11GXKrb|pk_$Hq(x=+~gB0S3br8zWdSbTK+`+810P8Na>XezK8c6ejMGf_U8U3t7v zUKQltW>1qvsi+_9-!mxc!rHp$y{eHYv6Ve}ud*FzQTOxBu=55-Dv>EYR{Nx_$wOz{vA~Yg51LkEuMSRaR zqw2XX>9<4^gTwVfXs&sX%a`Os zs5H^BA)T!>IjV!XOWk_!&yXSb5BySWs}M4q#fgV>lpU$9I0GKQUSq;T^vp*H}o2P^jn_#_Zw0i?t}QHDE}~-3zaK_C-eqg-OO+LDSh?!Nn8*B!sG|u3;y!5S*QBxy`|ATjoa&7bG-%g00EBuIX?0FKD-At?olXH~s@3`3kn+za;DTauP2W@hDUr&CZWSS}{@ycyqM)L@Jwu)ir~@T+KpOg;%WQ zOJz=YI<-Sxmeglx`n*Gd67&*$5_l4*or#@Ncl)O}c1O2lebl)<$DmDMdKGRfaLk%R(Nd;jbFg;laXEQ-F-eaE~qb;`pcJ_*TM;&~$3KXgk|kxL8^Nz_+qs1oB@( zW5|CAjS;Hb|I!)r0e{uY{&OHD^>D|CS+GHuT6H0pRGKTYa{C_1AbXGSc+DkYD?tLbYNmdly4$JTZ za*6xwX8T~BrG{^Ux;9#w4Z9J4{&v3co2oO-R=6y)x1M^ok9#_o|x+ioXKj@i^dvJKq^}KG8iN#eHWe`eN3QC+s`;OFrswm^$7t%jshF5mTqflmTzol>|Mr8(_yHc9IO_qE?tNWXsY zNs8M58`A4_~YEw_sa219->F!**c{#@YyEjRvsU4Lkep?@#% zKT=~5LYB=978C@4fPzo}3@q?}R~iEm>fnEs#)w<~OKHsiQ&Oyh=pL`0yp^4ettU1V zQ8}-qx6KdHIe1xSc~z4Ir@AMG zixi@`(e;{Gjog@yiM}4o$$TlYO_F@CDqL8lqO7)m_c6hO?QBp1&rM?S6oLlF742&tBeDM?hMUc*s8cfJYa8Yem>-u~M>8uM$!ySf zcRy-|E0`sigFp5=QB_<{%ye)0^1yOOUqWw4tZr|}qYrhNw^yJyC+>1zh}O*bvcUK& z`-uw~Ii4?`!V_q2Tq}pHagP{}pDIz>NP#sOxj5p%xW*z_K9-zmAH82GButlSnP|WE zKdzR0ExU&ua76g*1lzcu*k8v(VQzf5=B{IJkxjq_d;hzIN+EF~6Vi|hejhW;0`a8l z@FTjvPO~+tSs;QFd}VF{d;8nXGZf>&ZGOeV%Jo zc)4-1n?;y;CZ9 zblSQNarW_bG)wlWrBki?eSP-vpY>&RIBV}k&lr&DEK%C?FDH3N>h7D-$-b2}{19KQ zy*+N9Gg=kLxyP4kKy*Bjpl!&NR;z5t!SmjTckOEKA~kT9wEB9ewB&`3TMg17-z5%d z#+Yt=c2N22!naPeFFQX?IQB9-IqSIXYfrM1+r$+ubGbFc9$Y^sckv9#n>t9M>_Q*eE(4orsGQxY+PQF1;c&Z@G8Lr}#wR}PPZOu#I3~5X z85ZtZU=Nf-#5*%a3gC4r8-uK4Qmn@_pu6xFoO7!_V{7T%ISG^>OE?u2^V0#|gmZD< zdVN9or|?!fmuD|Yg9vXBiKu*?*D06$Vr;0NP(Fk&XjupG zV2Gs|-&AE6e!*5TW&3RHkWDmi4|TtEo1L&o){mx!KYyPW*f{+Kb4+q@Nq*Oz>b1Ja z+p1AJWv}=eS;~uo%<&kvdG5)>PusA~QS+_L2aHKsM59X9R9jiv*1|dav>U4qy?l|? z)0K;JdoninXiq0$G3C7~Q;ML}kwrKER=FYD-(a3Xp4Zs-){F(UiPJB=V*&9T{_+#r zelwAQ%4s_n?5*@A#gH2F%XxoDs7}34?@aAO!@cv@wjZuvV_x_Rj$f(5D`N!a1;22u zPA@lWe*4C^Ub8UQx4&V#)oO2392@@zro1-=`jEj$vf{;IQ;6}(kECf}*i8c_&@$J* z_Fy+Dd6D!&$#u5H{DrbfNO8vk)X(*=_qIEy1aff7MR8O2YlR#46X9e=J$Sy?WOAUA zTgPlBDm0#?f%Iz=?7{-Xx61#!r(xeaiqfz8~ zy0W$(&Pym70>bm;Ci2pk-8LbBA%xVkMz!vO$rcXM9Ef(cWU*RM9O1OA7PTT z8ZqxQV*7#ekQ?ygr6nWEILs|tEz!m+5{X7I!DH1lE2P3F=p#^y(fw?Rj2@XT#)}Zj z#Lgv^TslY1PStTEE$Wnd$CFe)-aT~M=vRK<0{1d~$M*Af_u&JVjH}sScByx#+4<66 zP%7g+KYwSqSOBhuH&d$T-%p~8Z?91qrr0I@i36OtBw=Cr= z`;(dd;2}Sl83+XZNzD)@uD_`nn}ZdPtEDyjf4;c&)ZIq2Ihk3gY65hu+&%1EoDr0Z z2L$Co=#1Fzd)YZ!0zfcX5Cm+<4p8?pbNBQIs7cF8A^4G%ujjv2-P-?tRHf!_ z^Y1r5-B@hWLSP_B5GV)&g28-1D9`{1WJP@bjr^H8u>A}DWR(vAMn8LfOSOK|FD*My zN2^;m;Sbuc=I&zYWq}~-2%`T3kV5ctPZvb_A9Lc5GGc_%2pSK7{Oud#ec)nwTgLub zRPI1_kqj z5M8*v0M7qlKrlZaqTjz_d;%~;*MG%;i0S$r1M}aG`PVqGz^z~LR}A5DLv;5S3=9Lp z{)qb#@oOAJ@RlY2iUIiqL4Vu}7DTxDev1PO@*`&V_WF0c5Fo;3`5T6y-hb4`2jl+( zwDU(CErh94!^OoDaJyS>6LJM- zYZt&jIg)}j;2}W7+8hc7^MftTtYKiFr4^XZ${Z>vAi!?{wgQ2H))r#e|NoG`^LGzV W#E;UCLkLA20T?zjvy7@N_WuF7YQtmz literal 0 HcmV?d00001 diff --git a/examples/gjf/molecular_dynamics_results/guaiacol_kinetic_energy_fluctuations.pdf b/examples/gjf/molecular_dynamics_results/guaiacol_kinetic_energy_fluctuations.pdf new file mode 100644 index 0000000000000000000000000000000000000000..e2ddfc7ea50f2e480f5a30da638f8f461b87d8af GIT binary patch literal 43786 zcma%>b9klA)~7oivt!$~ZQD*q9ox2Tb!^*q(y=?(v2A10{hl-58GP5w9~-rvs#>e6 zR_*KlRc#V^VNn_eS|%uxfxYX!lj574>470AW_)^l8v}DFZf<-!X=7^>M^k*3Pm>}( zov4|mqp|(xr=`B5v9PhBjgc`vFE5mXqrI`d6_hJbqvlvVPBSdvL5-fvjG=PBU1QHx ze>p8N!G5q1%Y(oqH(snsktzOE;`p9CXsCQbAWtDaz7?Tg$;Cp=yMF~tGnVUyLnY&|s__{J&CJlXqnCTzB6+2}{p z(wdAuupPpoud>LvVmoFTGFV~37G+^##Op9%&7b-1bJB7A9ySqnA0u=7R_{hj0&^qj z5aw}HcN4DvX03Z{Z{XdWT7jhx)xh}^E%{neyn~s&vix4fuf0g>X;$QC1{BBuU9Wfm ze`9+A$Cjrl-6|yScPs`OGE-~QV39UP|3zIbCl=8DI1!#DN`%Qk-z)S7#!RAZg`!`V~tnvt)IxWqW6;VFmq* zx?s&ZxJ`HVn0E#YAv#06EudGFM+opUwAQ*bLC|KgN&;F6-BZx8RYMs+5#p5njBBZ4 zgLyBXdzs05wybxW9=&`8k6S29RGPQHGgP@Npn#JIzr zYxG6`H3A0{ftf-+dvt1$ePDrPC)9|~BZA_hYP=p0J$rN><%T$?RR2=_WKI_Lt}kg7 z=0HubQRK)YY1UNVm>bPZn$ou}KWCq)3Lm)pW+fzZPF^_j%XVfJl_kh9ahtm6)V{-5 zVUCB3O^EL@nTVt$qPccAagdc$|oMmVH2bY4RAPU8w?>BsWH} zCqR0xKZTRTj=dIl-kNDjw(;K6@v9XH7VSPS33#)#bx!3x{M>h7rHVC=&C0ptX5M6v znGRHXD%~Ych4$Q7T7(ba4Lr;A3}xsWF8)T-bSFG!=6d2ScnN|)Ka1Le%vYLvvdD2Y zXP#J^ckSh5=`Pxev%5LCI?!6W5$eVJC(blCdr{}`SE9v(wG-hERHu`egY?L zl*IcA)iAWdRZ6&yFf2|@V-@%t@eX(taplzn<`TE0jIZnTIP5{ZB=kE!RN3-m3uWyM zkbhx!$H5<|^iv`sL9S&Gz`n4*5Bji90S)d+0IILsV8pVU&IZ24jlqeZv zCf#?TfJq1at85yn=c}6+*H;W~1hg+0=13i4P?Fy{Lh+i`TJTwO44T)iUl5wRP4+7jhq5MAZF3p|E?t^SI!6^bjTu%{DBm56>odIkO%~(W znuc`mFFo!{KPy=3V^e z5g}_eqiMqT@?BL(gr%+oWJw&@CkDO3o~T9tj;I#x^G6d5V3-_|0W{dndW{L)m@cI_ ztRhgksMv|9Y**Mz`S&-|Z_xXp&!}YEmT5D%m)mCpx_6btq!eM7ve7V-CI9t{il7qk zvAvLp%0MtmZA^zZtTAkq{gAu@EH!2NV6^pTD!;>_EXa#=#)kf$Sp!(*=dr@S$ct2# z)Ui`z_*5Qlsc+MgDoBKSB|V4R6%*o#ol>;@{P|m~gZT3uyo2^5?`9>!-TGFHFw6(`x(4P&V$$qyQ#gw|Rl+JmEqy-Pp&lw1H`O0M-T`Th zH)CR*UtD7WMnu1gq<@_OL2o!gfA>@*^GZa4Hs3VE#GRTdOynWj=;(gmIlZ{p_;9{D z8A3i6j$zz6WI$>>+>PC-1F+ppsa<%tJ)WJl_YPg6PF&13uk_DdMI9vg{*2bi)g&*m zy6xIiY#sNy+Uo|>N_tIr2d+L1kpgYnyz>^B;nN^)4=k8yZPP<7Hq0_nHXF*Zt0gEr zNWS3%pl+;rXmQt|dR63LPwu}37`=z*8%~6rbP;}g09J$7B#c-4n)a(VbNw5&q|8|O z7^I*Ot=)%P81~r?06%9lqPQG{kG~Kv3!+~P}ie!MIH zPtIB*VeW$J+tW;VaY+GU4nHCo$)jG>-F@Qd=>Z%~*KR`_e}03cK3;KjHxtNzQOlq?dkh> zLx(7_LSn@t0bECt4O@C-_+qhl0^hQM^3*{hu6DJFsJR)pA_|iD>=R1qem&|~2P@B$ zRX!l9ZLv%!V{4;-q2cGZKScQlBmaCdvaqrKdHVPJf6%6~o2@ZEoxHxu-*J z@}iREW1Ot~&DhNv}2{(%8VmS9EwFICY?& ztsg%?#2$se&cAl@q@|UJ57pnF)A|~*L;Q)3dNgE=d*U4A{CWGg=s zBv(6?WYZ+y6Wq8{St9+*-UIpE+~ZH_FZ9T1dgBMAxt3v!BFGr$Vb@>3KqL-ublAg1 zJaL$2eQ_-^*$oE?lQ1YkSV}e9I~@7(d{wXXWWYd`*e|mc>MA{T+W-?ykLFu#lPm&6 zqG6S08h2KSeRig?xNrK@y}W_zt@Oq-;{Kv?MS41wB@mgVv0-^yLDz};<(^nG1E;<# zN##p}6&U~CR)yRJ{+DaeFAeKIZ*YSxb>j!NVaT8(PERczfU+%UsSep*vi)s-bq8}i zq>Y`wsB#sd@%a%+pfDMW>=hLkNePdS!@#9X8NEHgf9&*dm`#lKQ~%8FLAwe%R8crg zgbWNbZ4cu1Q;(%Jf(rCm*z!SVB?HIs&a^-_b<+Fd6~rOmA^|>P!}CRm2$LL=sT1J+{RK*Z;Wvb@_!lNUtvef`0@8ct%tm0_#dxFjk!y2!X&NjVlz5!oE-+X~u6`;y>JY|Gh(_d=fvWzZfh7Gxs$r_CG}=Dv4|pcOC;vi& zh1w!@vI;(DNLGZ5D4GG)?=j!CYEo)}f9s!eVZ#mgU~FUCdbgl!Gg`A$fi!4)7Sy>jiKTt~j}|JLhpY2ZoF1?7Y7gS!!fH`GlQ3#kcW;s1>w8K2maSQ#D@;sD|; z5TTD*!LLNlkuVtEZ9vv{FE)V54bxlUm( zNiRCF1g4aml%3Jagz`9xq>~g661l{s6qgh|+H5jC0w2luqSuzM3cdWjN`Cn@s=1}m20oyEt3M3uze(}wSa;5x7HM1mz1ek(zg>JJg4KfX!E5J@DxPx5 zn#$B;{@8sDIj(67b8mSzzw1BdIZnV#$Lzwyz*NCZVIE?^NViTOP2WpDU>!&?9-=czO-saH42m#v>f(ut?lViRcAZdP&; zl#`-Ur_-xexX9&I$ga#T=oahN^7+*>jlc3eLLj5JBsV;_TR%%bf6I`lEUtWpGG8;F zYlz*j$u9hgcSnn~CM;7TULtB#M(Owby7Kq7sfH;Si+xj4=5m(y;k=qP4UG!X#T<@) z?h(&?w~Qw$Xr2i5h)h%fsvh+jwGzz_(J-^0L~NQ8qx{(@Y~Uuygkrs0pa9ut7Y;k zatEBugRFK=qIe@yW0GPLb}}Ct2JI4Uo(A21#%`+x+dhugh&EEs)i!rtWi@F>^W=G4 zW-02xdBAD_@SA7(t>uO4o7A^Bv54Ws;)DatDQMl$lxnp&wd&^h2ZIaqi(+0*-Z0)M zUZgJPu5vHBNBy_2Z_dwvo2AQx=cN}p5O$CX$U~?C5K$0Sa9(IeNJLO4kp5nv-gbXH zx>-G9?RnI%g0Di(LEMlmFghsD4(PPh%oU`kZY?UV-mWenGzKEVLIdsMF(b1hVi8fO zQm8JXqhf<13t}=N9wI3sQYq@x8uh!Pk(!bCMLei@SSTLE&i17bvjC}(ozrcoopV|y z?d1B?75m1$(y^(kSiN2iJ4#$EJe&>qk1(XZ(mm;_TfJ77J&>h@_K=tOgCVMes4JaE zc8R3)xoiIa*DhU*cov(5Njhjw&de?rtrHQeL`4mj0Go=$|fenuhbAlxL z;Wbn`OgvZSzjZ1F8H-o+-ce5rmz9<7#{O5$_@khI`p9+^g(}>@EAgX<9Q} zGk0-qF|4V8)yzZMW8=toE)!=GhlVfX!}B)sJ}tfemx5 zv=B};N8YxE-Pz2lnyU3Nzm#g-t5*Bc)y|h!m6URmDh?ekuS~Dbv*5R=McnqRWW7^w zv!liftIi|a`nTkr%IGdouY+fu7rOQPHm|+tk4!A!2(agK+Afa|-8G&gul2VX@X~L( zeBDdCr#pFMP;!)6Wqg%y3y(`bN;_{)bC$kO)rXqI1h)v$eIz|q%k_g!l}=HK zHi#aJRf~A~--n{&u zs^Bk%{*?ls$o_A-{lndVY@diOAtWTI?_g|%&+rfH>-@XUALRaD0r-z}aQN@Uz#qPM z`b2XEd^#yJBZp7=|A*go{u7h`QzrZa;X?Y3`j$2(|L78je+iQR!0=97c)mU8u34@?O^x`^!nD0e_DM8#qd{g=s?l^ z8S_6qsc2}bD`-$Dxmg+5SbnM%8x?D_zi00Z|EP=q2OQ{dSrh1>J%SIz{)`_@R&%cRo4< zgeQ5HL>>Q)=#-bvtMXP#QjcAK#1>xCPh{9$Ez{avFct;ilKjG3?NRhj%DWiY6P?Pw zPLpP8C%b}wM4xB+4ZF;1Oa5!X+Y&Dzx7TXUq&&5>l_84qtBINv3EO_{uh*|4wU*tj zEYJv8m1JdH$Tqy2&V$HGR|*?!T~f}I|Cbc}Ge>{sjgjep3e&#}@$b3(Cl&s;g%y$z z{$u&`j1m98U$4(~l)L*grCx`6KY#nXv@frUuEdRYn z{xmza{18m5|9F zG5)uP;9nt5!@$ahPs7OZ*DEtVJ0sg?R!e+tCNo0;YZFW3&q2`%{KyMg7qH_%hU{!rAB5dGfy2(XSNv-r8X3`NvgP6_w8tqtp}h3WQ8bqBnRh}KSf5~ zM0f4VDt>F;9;C4Gh>Zk5kkyZE=6Ym$_{M_mvnH!7E&?vHa(leO;dOO8I*O9blZ*t@ z!QgcjY8$38&6)R*u6yvWSGCP5>m@GQGKIah5NOpaB-o|C=w7i^Pd*6J8>fcVz0z+eLb9%xGnZV+z?bIYP$qQR`AJNCS4Q?7tkGtzn5P2nvSr zEy#$018^DkUY@yjFDji(PqKxU8A`NpiB4%VzqJ&G>%ww@2j4FTa%oX z?%GUep__gfb)V4P+>&axNN@dmJYWPgI=vPF&xel$^5Q%%j{l^cAmA-xV(UIX(S=|c zZ9ZwwNh?52m~A>a2jpJQF5wvsX9}?--F8HMrOGJYKd5F}a7dDzyY>~oWuI0|2ua`} z18OL*$B|b<;#_10f@Dkq(&wu!8;nRETc;em3}V`*c|v+pp>gA>x3Pj1M*Ym4g@%^4 zdAWv&W1zAImE>l@;ZR~|OFM1|D61WLpy|v;fu@~;mvQeb)b`^y7F-`(fq@8ko+0EZ zHQyJQJNmoaL8Hi!)~rRYvRavmdKMn;Kxz6|2!v# z^^dYlRI1<~usjm=zkhz~FOUBsNm>Fu593bz%rL|pX`2effM+m14CA{P(Zp@gHQ9l^ z)$cY*l65Khef<_3Q!vCBmRJ?J*4)fW!A>H7%-Vi=g0_9oxY};HlGdYg%-Ui3jMgJ_ ztZT{GrRDUF)+1nS{jiQp=bkjBbJ^I&Zdps`-i!9dJLS!H?A(5NRr@}G_Jts&6JX4D zT8C%1%%y!VOW^HxH>;zVTv^m%V5V|tU0c^-?q+qBZ;dj@!ZJ9PtVMM%PO`Arw{l&m z5+kvvLb9i_*LdeK7$07^u&2U@21S*O#$822*{o^+`Va^rX5n-< zn*=IlF_vY&u8N#8|1MbmOxw(JR<*92BIM~ggrVEuXuRNEThh|d*7B&qrZsqtDJnDJ zU?5{hQ0Jo?^2Nf+u2FIcT5<0>e8pZ%Qea5uXb*3K-^H(K`$Q}vF2MH>5 zbqRSD4?b#AH8~xnw}hZq`KZqxP`PJNV_r*H&EpcTD%N$0l8|n4I2GkDAn^$sZe>I@ zWVI#KrOrGh9OF$76+1w=Zjf!VmXv_Z+4V7HI~d3EueL&?oJJ5{@Isg+otWWY+t=I2 z=_}?IG7|*Veb>i*;oJHvdJZma81*5A+mc#VUNUx8)m0r(p8i%ta|jdHlBMEwh@P!cN`!pjIMd z&=x+`#u&(&RPQ-7nwnZ>l{8#?y0s07PdN=PAs3Y@A|Ge_*Ls?7Vq^^>pePl!9c;vd8a>w@QsE7jY|TFO4%r_nA6U|9=-PN zkYZqQu^cIIFC_3<7g}-dZI{B^kRM(o;L3OTisGYp~|B2Mu|NG}cb5}ltoL?I_0t7_zVajeexQNewRzOfHR{@ij61kMU&bIce1IFp*T22T zVZyuO1F))}0WM%(a@A}Q?W_=QO#SD3zMw^Q^!=oaD(5qB$!2ICWBzS7H%-Qs$(o0N z?-|$g4Nk*pCZs4!_E>yIro}Wy&ud2bG|-ec^iU7|aZg+LD1ZHe2Kp2h8y$uZexAqH zd3X@1y34({3fl7_5IDmu@R6z%o0`;)fVJKCunDLS>+~zqxH3~xtU4oB=i>O!oVa5T z>)uRuY`>>;B&;b<>I~zx{-1=HE?ysN9wS+y#fR{ketAP*5Gc6uwTEwv{lxf zi2sJ&Ogw%{uEVDgm6S@)OKERcjFF~2-l$iCTq@>8=l73I(Pb!Se%{JD9}a>~o5zCm zk~Sk4Pr$Ie9%@wC7X3jBrQz_B&Jdq$gCRmh);#!lo-pwPHE3FTI@I4Q9%TBl{%gKu zJ{?fh5HTjq(L9?jrx_f_i0Q6oB!iWo*sX-pZUaCoAwF_Qdxun>%<;LD`I)>_!Hh0AULcm8k%`4V_DGIJx3T9MrP57|{OAI*{Z zapm6Ov9-lnGv+U1)yr zVS&A~Ql4bCyYcbO;Mts*h}=uqPTRMe^8HpWQoKV}Lod6^OdP~4kiVH19?_f8*)CMg zxDN|v)S5@V?nRiyg(wam%tMc9(3`>f}1ke*(hoo9m+W(0HIF6y>yX>6#dgpH5nyemki;&xzNA1oGIZ90%so_VXd1V}lHI~|y^lX_>NtzOw6)Yk8=i6fY_)@}kl}TA zC~1X5N=VD?F@m0gtO|y?*HoD?D=7F%JPmRDB}Q_G=qf|WKf&g@Q_ygSn7|Z^;igv~ zDcerFE7GrJf&l{a%+5|h2#L-`aTwla(-RFX6tOkO4A)IaYfY4-P;3fJEvmeq7`6sh8 z@uUBc882@-I$Cs8_on}oH`DUn`arIfo;Ob<5lKuJwg@<=>XHl&xR;4DPG$uG*92u$ zRNXdj?jeM!@|qWE8GBbNt?LOZVa>hkfo*ne!=v5V@X`^9gTA`H+E7N;R31+{iJ^wL zcw~W``;wmN33qVqFftiBtJdxhoo}|-53~1$N?HN+@h&vsbZHOQBHba@YX;r(BhN6; zE~j%%Os!S-BW;~6{CHgWgNU5-FTFMIo#4l%cHq0xAY$ahcNF3=cC+!ROEy+uhVbI>E$j_y@jEL`R8%yEiXk$8etS zInCI$nbeS#Wgot8qAgQ_p*7vTJ#DTT`gjf0oOa$gH9@0$Jm;MbP#aP!yg1n^0^`KH zid4f-i(`J9tb11&Yu3ZZ0?vGE>z&E7IyGcICT?G;<`6i~mbwk*0c{Hm@bG_ig6wx7 zNb2n#i(G^8fLSe}Aw3>#Iqrubv%UOon9JFVDB#T02V|&PJ)T|EYOP;d3TyhcU$hsN zOW)F~Y_Fq+8W@~EUxOVP1~YS+2-uDNS)9|ve@4wxIC2`jV)F_zoTYaxElfeyc~*Ra z8W-mEWghD;Z#I-HlNRp+NDxO&Pz=C;8P?F)1E7ZB!zh-L2aHcm(th-Ow*X-xJ-Rt3 zaxae%-QO!<5Nv{_N6QU2FMa>9L_>`h69 zdX(TA?1|=y=*jmL<=bHwzL2t%*O4n{oNO`Ek(?=vOc4fi3hFe8BWPy`Wkb}uRP$`e zVg9YeGqqP(m!QYt$t^K1T2}~oFy7qMp&IsH!%wz@;iw(|meDmBYdDjA#Fij!)Rd{W z#Cltj5C8mdt=`IQ%vM!vA{V~qfYq@#e~-A6t@UkLJ3Kp|9a>x9p8;rYa_^kp+;lf= z*KAkykFB1B*#ifcF4u*xid|VY+ZTJy*IbWej|WdFPfL$GuXvBV@6xkY| z9b~tVJ_x+1@07RD+0Y+U+K64K!OTBJ=UdFU?H(1jR=^eec~kMaLUO-W=UOX|NgV3n zD(}W}6c-{6mlylO)0iWL%>7Wqm9|41>j=Y@Q!Io%^i+a`UA~p01MaO( z0Rze66P=U`+AUr^gyiRU0^gJG3#^Yx8G24=zb71p`Kt<9UtEfu{?I5BATYFPkL%F@ z_5f~+vZZ$2DdzV9O%#rP^v$mdU4X7x{Mh_=Myi9^&+6 z+9S5I;uD2KF8!U>P;`kCV07!?pxnn)GcRqnMOvV`@%p4L$#px36EHf62mMo`ePHSQ zfH&6EZD*l?jw$oRu=!%qjt{Z+n{AQl3^C|5z}itKzUUo|M5E)NAe|hQ%D(L>wANMFW60%e zTH>wkz8%vAwL1w#b|U28n4a5VXF~6A=eL==-{4_0Hx=A0h8qTLcc~_#{FN&$56vO% zsg777PIG!(T|<=s5a&yn0a1>TxwF#&DfY}bcC4eGW%bsrqBqHOH+C6!%}SB>owJ7SLypKhQ_3&RPPdUmVqv&@<*;jOO6Sk>56Y zP==cvWVLxNAGB624c8dY=JNdj=Dxw?}KxYe#gs_LIr?|HNJ0CV}a4_PWbQMvhX&@R- zT-?xL#Aq~EC9txRc_3#JZU;H4j_<@*AOCww^Z=u^S`4`0E5#)~td5+Vt(g%RIZ0Cc zWW*V=IqQ@yqu_-x%wBKl6!AabD zEbt~qSvEzy7o$T8BtHUI!JhA?$lcHWN` zt40i*yP4MYwmG<)9=aF48uCWzB?zS`B!}sgzu^?wAtV5w-OrO>ZXX^)exXYk{#*!} zv-(uhRO)x&q$nCny1b38+V|pYGrbL5GY)`0&)aHALh(8_Q!-oeF|JX^AvK_hx3GI_ zVJzT>0I3xexNhh|ar5r&5Kzf5qb_QAGDof^U%70z4{2|(0rPVzNAPU2vk&LERR8xx zqLy9)r=pi&JG)HM%lOzscxBxcE|7Qm2I?Tbg6tkwjQskHizaC{65Nw|_{^*UOzL}3 z^G?S*Zb8i<>HFnASBl>KbXnFQIN=%8#_muc9z&Vp?3D)ZjP9?x6&W&bZ+ox5!$OXg zb+K`{m#Xx%KwDkJx4zK(h4Kl*vxfoKn6 z6$$?m*BD)SWqAjy`wMp?h&7l7_R{}-Hqbq8!7W>Bl}?4aUJinP126xClyqJyWYF5_ zkQ9y;t52rVeBI1TG$`Zsf&URT! z)zWQ7Je+>9c>c9LIfdxKcHt;BPCX8$g*-AMF%As9iZ5EZ!FMdOC>{OW4hQLT2FIIC z<1|iE2Y(3@Nggm=$4U3A69(UuoV!)ezTt{*HN4qP-AwL;E58A4A?iL7B)UyqQPJd9 za-b)4h+9=eb>d#`-!iQU&9U;M{p4VfU}=68F?1{kkTIeSKTE}D{iY}VcEh-)w|K}v zYS?1Z(XrpsC&gxx%-ICsS>@LpJ*rwKkW%qiQDX<%Ne!E=BJ{y^AX!ll%k^DqK4!4f zubPKTcl2}N3U+M!A_assOzO3Jpm*sy{j3)l{cQ~$Uiao)N(W#<`h$+w?s3^Vaug?! z$jE8|M7Opk7lKNlDL(*#KB>tR+zm$rpIcnt8jlE_L1>$EVF3ab1})oghnv7&FsNLQKx* zUu5zw={7>$V3eYjUt4ud^ODRSN{=dcc8$T@AU^0IRNc9-e&UC*4M81v%*wl$cWYv72YSovOP+*G%>jsCH3yZY>$D8y)VZ9W8a*vxpyN@ z@lcTh^I1ALON{xwS=P*}=3Mzx=Dyd29y6X9?~G?rYe{RtlV-thS`-nzD|ZHd7{q`< ztU-)znQiGSvTYiJ26Q^oh#Na2Bv@Q%9pliUqXF;Z2YTTEfV$jvaHh`bvB6%He<@b4 zb)~yG{5DwBN?br|%|Usu16q?-q?hq_Sf-&|-+fGH&9_q#k!?TLy)d??j#wftz}Ai* zJEEr}xtN%UuAFe5P}e!g%j8JJS$ezSe-e1-i`7>YhHQ4z@dCD7_&nA$V}t5Ii_; zA%1jda4`2{nKe+C$GXmYhC@1BR~%?LU<#2u1cDWN&b);Z z{bLk;>A5ub$kQA{O$TidLEiMU%^;bKtA3&3?orl5*AWtdXV%D`j}REc8xQoP_|$11 z782=AT-Fa?L|{#5rr=)NG|N=P7X7nk=-~ck9YZml9aTK%nCt#uzZp+oWhL>;`_Od~ zg&hZe-A^QVu4vu$Q*@hURNX1oJQPWS#KQda=UCnHCm*LBH$p5`+UZci+FA-Ap7uDC zNQs#Axl%c_|cvjf-Bmfg=V3 z``PKZtupMfZX_U-EzoA6q52+veBu?ER%GbPkYl2D=@$Sh~ z>fz`1r)SJLw&o)}K>ZjsMI>T4wN9ez!_laMhNSh{(cIZ`-Zw&b>hf1O_XZYwJs1D@ zbvu&%+pkKP`GTU9Ri(xgasi^`qoH9>W-#QfM?y*Q4An4!l{>iX!Z2J~_f#>*uwY>p z63%Sv0A{mrj{PvFb8l~n=Ud*ftRi)J#anIL$EuZO&;;BS1fOj-k9gdyT`(sqyP=}2 zkeIP9^x&FU*gL6Jyg?vi&4x--AxS^8vA7;29yB`dr!IIsq+}Fgc*A&I2E~oYlqO?= zObXUxhotxu7rN(+>7A?N=qjD}<~u&_s#_wS=B5R&^ZosAc&g5PaogU2i|t#Cy5-+} z<3+4TcO+gy>tuof8Oo0mzT_4^7{aZVxH|KL_X@~60p>MN8p}uW0 zc2e1Q&@*F0>;jCES2qT;0pZv~Tyz|`4wmPxmTGM=xrW~J0-_S5cUp7)dK+6_p@FBU z0V@G?(qX^QR9GsAeOUSciK{Oivwa7c?D`Mergcx+&Bd zh|eJJ|A81ZIQ}fx3Hk{ta04w zWu;nvJ3l7AAniXZK1d_r%{gz)yUrA+!BfW=Mv&%erFl`7i*mi~6LTCU|aP z;lX4E=rYP@*r|a=(vT$FKcTD2T==1SEBFO>>KGIhRu3PxFguYn|03{lw60cUy31y< znIA)1ZWVZ81u{B}pdxea)Ux*7isK*}K!niRK(JkO?7IZnYFD$h1Se*6aone-2W!cN z<;G2Euq+h~t5BSLpWttT)W5n?F4LXfvX{K0IGVAVf|Jy^3Vik~dTO}6^(C(3B}Y3@ zt2AH)Zvk%|>+r27j)6=);%tfQ*2yU+utBO~@Yw%ga!}Vu>~vQMCZX|7d=NR%cma%T z!+iXbrCuO^MjAH0;$8wZE}?j291Ls;(?m9t)@Jb`vq%)9%g`H+FS2&_{CCbhYOxC$ z!?zHhjLLK3l0@dhH+o6x$y|vG&9MX$5zGULhX|ACdMW{bw+*i1+ov!dr?rf88RuXnwrlBa_$P{V7b} zMbHLhc8dfz%t&1#+N#F@m3`19IEX?RH6zW za_i@(bhbGv&R-wDtdGbYm(u-2D6OHw_Fc4c1dvgt?N(|2e1r2B;VB>80W zg{iDi9MWX&ygbo8jj5Mz#lfjsSWkbyM)eG05cGv72Z2rq!pfa+tpD!Ms}u+inMqm? zPer^bKA60~^5ge`M^&M#=?H%onPvsrS`8yGWSNw2%oh$23#yiCPV#R)DrI7+s8sNf z6ty>Do;g&3w`EuspiVeN&t+WsBbkGS7Dz=&{oA#kB)_iv!UcF5T`4Q}CtiQ!Xz6e2 z=I>7^ZVI>TyggL9(y%Fea|#GY}!Z_0@99W zdYx~P6vsLqBQ>xnuE{CwYXJX!(XfP?dz#92rg$K7SB(5oe z7{7Rvb>sKhF4%+L&qfqgnZ5p!yUgc96)<{C5e*4i2PuwvD^2ttWwFjf7gWFz#n==0 z7&ICeH0fq_$^~+mSTFjQd9k_3D ziUKQrCEDCI2{7Z6JQrQ&Gg6E*kG}mevbMzAfUZU@8>#iFUlY93h!i9sZ3<~W&Z(aE zhUGqJNlw$O5@-Mxvss_#@);Y>_gO?;@H#7r{voQSIH)|WRUUu>8Y)G>UD5p3Q8gdE zcSDS>UrtMUnC|=aCJ&vlD9tp~X-O8RicN3@*e5<8Ns&zp`WaL3S4mO{r2ZSbvG*(B zZ?n#jyqxWu0rpWZWq49bytAWLvOn_sr~3p%%$UzxgvB?PyzlQR z4RBZNkD!PitO1+-dGMCj8ZD<}kXR=oLd^2+4@DSHx4bkZ^aVw{9PORStii`_d>x zcK2#xET@gO)U`0RhHhYe&4jjevFj<`JB87GQp9T$TyxQi?qK<* zny|O<@Uh$C=(#6Gwc)dW_#|gBDb@jQ$L#If!DPJJ>$U*ec=F(l{5*Zy7d=hC#5G+@!GHjQ{r+*%KAoC}2pqSY6}#dz|> zv7nB-L!-dH&?@`PH^Dp1*53-&^^4JFF-g!V{yE0FtlBzLbyXPE($pYcQJs$VN&3cC zt!M7EM~+is$>oCYW+6)P*Cg-LIcegg2^2=04ekAxGbIosN(!;Xh&fxGvDAICcXGKq zI^y9qS~>#B0$G|On3u8Fx^))#Bgo*@qrdE|8crJdB1O4f-?F2f3Lb_p@?;eHu@ zn+%B#P(}f1r3{?(HDU=_57#*bNf$)pZ~IlqmyfC`jV9EkDR7Yo+W?BWiQ|YwTmgPW z`^@eY&MWr;jks8?B6Epr8t~DwL(U`M18sH9_dl3>$0$p-ZC$%6txDUrZJU+0jY`|L zZ9B8lwr$(CjW28Mz0TU_-gDah`?aZv5i$CV9zEKeeIVXv2Iffh1-!kBkjVs#!Q%!z zx{}y#w#te->=oSjV5f=Dk~^t;-@4H*Km$&>f8N%KkE9KY;|Rt&ig&^_)D7G1XnhUt z0_f50B5Fy52Xg&tvUzk#>~U|9cL9A6lz*iqBn!}#B2#92_F3|yXbDn#Z1oAf1DRu| z?5Xu>KDtfqseTD-^V_jG#a`vF=q^XSB6pZiyAPWWu_3+58=5WW5KnvJ&m6(3(xWOh`uw)II}Fx$x#zUG=6j5s#Cu zNBAAd+U*CjYewdZrV8U{R$s2Jx5;^*oBx|PTuq?W8Ls8ihq}cr%RAzH7_{>z7g55t z!4K$w>q~l0b-u_RUxC(d$ZhyT;utIaq?Go(rX5jS_+p=aL+p^()vf-<Lp#I&p;1CI@>0h3O=s1pbPf9jK3t-d*8di!V)EB`AY? zs&b85;HX9oXalf1<1m>_?_bA7+dGy%uu0g)^79ebx!pgYp00+D})&fnU1;SFQr936Sb%5^RZV%)C9hEewlulTiF;u5o1tK1DmwABwUWYBu<3U$9EbxV8D1zkfQ8)1 zCBFT(XnFJyVH8K*Nmt_{f_5-NxxaI;@?p43x6_du*v@0IT0W+)yZ8$>(YE?>r_*`W zP2;p%cKYdA;(mKq!xXIJ*>B)BsW0D?WmNkx&(a3;^ltsQiVW9LIT3mjY2{8uYnSy zVP^{TG63}Yp7Ioiu@ZrFIIJ1agX>Qr-}gzk5+aBz6LQh1yT7Zys|)Mm)ncl)M(-ng z7)unxo~@eN>cJfyA&*6@S+_oUBaGd}?#y?kk)+6~pj6Q!-2}b%^ZNPJECZ{kNG96k zE8bZlqaiyq4|)fXIpl^48Jjigfg-oS>+RbI^y#sbob&IUSj2J3fL{j$F6ZnT{x+cv zpAT?!zGV*orP(INcpORA1%Shh7Z{<|kKM0rtARO(usl{po7SBVjG?$EA0)blX^h4V z71mPU;{9k}_`#=x7tx>8*3EM)D9E72$BRJ={MwkRmg_M^J@#}F>EB5Ef{uye4K7WIo!z^UTdcxJ7TvASiZ@*y4g_@NI0j6PoY;bGt3=`|0RqPk849e% zBKz=drnDW1vJI=HB3Rx4zY5Gu_grtV8oNK2fPpARC8$k2!~-ZyzVH~X$Q~R44cREL z-=5As&+lOvd9*}DqP9OoXb!iuu6EoaEBk%rdOvz>!1{ZF$pZTsNcWmo5}z`O;Fr=RN$%9tW z);44L`>~n8+eXMS%(8*!t)Z0#YC?@7x0i?^9@qq zG8%i_hO){!0tKYk1_|;R)*L0H#F4oa0~Hyw`llf(WXCA1F4;U0P_3ixCo!^P9b}f{ zAe>&$KnvyL+c@3cH_Wj*K{gOnvDP zBPJ3cUP3l{y2lJ(S8z9|f+SoV+sa9*2vne!-o=8$kPsB4ka3Z}u8&i|RH(Bp(wEB} zP+{BxWqgwDrJA&q<>vL3(5$OMFs$E^7wf`^r44R_`EhTyAOc;Hw2s@m>%t>4M&?zr z>9!G^r9OTKA_oGi0VSmQR@8-MxV?D?;O4a+2`r^UP=<>m%%vltAjk4MaD`?x2IbP~ zOpD@bPayw54im$oLDZv9#wVtyOuq@}p2|yZ<#M=@JWMw`RG>tKaF#uUKnC#}mn)LE z(pOpPz=F(Tb~vj$Ssml@dbO?E_6Ka|!=eedF+l;r6Yi~QqSrcl#^z9TC0UBpla?AV z*$y&GoQ_d#<(1>CGf#J$!;rtGMXsTz*HVE-CmJg;^5s+N-*FZBG@%qlucB=$ylbwS z3Sj>FpOrm?yHnDETjz&nXhygV?w%0!r|g20Ld|AK`b%Fhs(7^b^5I_Lq#^fDoQ_ z5q8)1u|ZsOtU*e8WIM70xLP}GSp!Zw;~M1N9<1{o%wO0{QH%q}YLUx74R4(EbG&L_ zRlyWYP%ww)Pn_j_yd8B#*vwd_QzRpxAhBEC+ob82UlA#Kd&vA&iN31fViQXbK+JEu#B9-k`{R zTRz`RDO}dDD$ZHw&vUws*$<|mc^MTrbs3CU7-{5a2NsZz zHH_}!X+Mf4{TtEG9Av-qM5(P$xtcLmd7lXvhXNn>a^Q)UOc228=^C_QfpjEy=ZfpX z^t>cxcBsC7Q`f)7u8VkLB$vDZDj;r)95ahk(LqJd_9drp`Qd4C#@HH1oCuXdMofS~ z(BoVr6=NbGN$0<)D%o z<4bP&A|hg%OK>eaK)07XZ(uA`gIZ$6+@+JetOQZi#AuopEJvRy?gNJK0Brf2=%FZZ z9dpO`Xu-R(_OIJzF(dgRb;c{gdv-=#1#u%N(I5!OkuP4t#KUZ%qh{ib6hHxo4GkE| zvdY436HakhHSU8P_g2v8r=$^AVY*}YDcIwp$fqnxR$BrY45^&@Xem4TNu@iRmkgVU z=Y&{UMlfs-S;j>=2Qs z2%b1pmd@|QTd#03HaD$Mf?b%9VGFiFJ#wdw>RWbcSAy0lN`qK>0n}DeMXrj$R7jzM zWK~!n>*tz2#{w>$3R-*vh8jFOYc-uI9IYI*C8R*FuR@=LR3tm#AA{CYG^g+Rq$ybg zg$`M&o*F*x0U>fdDu$LW3DtsnglWbSBypZr2O%XrwN|+MevUsbdnjqx%ujlSuYG1? z)KWa~bnSrdKlkF-PCO9g7y*-?-Ry>+iB}{!m3j#3oa-I3tn^1w?0v?}DOXi#boYE@ zh4fn|92*`w`wSHR#9R!|=$-xmPaDh&$Ef<53W!zCXkxo54RIY<{sVB(Y^X-k?-lOG z?#*=F>I&4!YC9~}>r1H8^se(s08Yjgi!oesibA}Ar=Y-|2xw<~YH|Z|{A}@v%r(*z zygj^HgVqUwB`IytkUy>{)!Y|)(qk%NWAq*Vg~N*9>5%5BaMw_4tKG%R=E5i{@k z*&SQkpN4H?ypf;gP}h^@6La&2$I)jX^&RjLzxECmzy{~r^x*weCNsYsJJibzr2pzQ z(vTV-+{GYAdi3fs6EP zo{PGj@NF|`u;-2-9n@t_VTeE&uo+Y&}A{9(aCL>YR|21mbJ;Zo6KcTOJn$s!t)bM*EwbBJep&c+mP?`n^N zpJ(>2yNmWcW)a;Mm16qT$b;_#Y+iK2Z@=F&{b-C}B(B{sAD+J7H6n66$p^#5@3-7p zah{%vb@kbJd@udvwBrw@2DURmt?v6+NZ~HR){Sr;q@>%vmt&*1VU%_I(9QvI?!z~wWLzY(>W6X=^ZC zU2pd*b|uJ-m5mY5U3tXKj>QaAD@-D_*Bd`(vhZuS>Z|LM%uQXs@3uM@(O&llsCQsH zo6HWVYqg)wk81gGyhOrg>i3cP8_Hl@?kd@r$So_>;BJhSD&bQsUgD|wkNDqy+-i1) z1(LA!|0?~g!z(}fE!Hh$<^Pa5>|BK{e)!x?G;L`}mtsQ`U?D!;*~+9ZHQZr%nn_Cn zmt(`3S)T%K3>`c&)FJI=6+D^aq==G!7J7_itGR*aHxBv0uqoriVS7MN+QC~xS$!op*gB>CCR!lWTx!6j|oDSr3C#n9~VD=<1 zee$9GX+mAM-)RFyXsmcwK_^}2D;%yj;e|)7p zdIDpmj27oHveMm0T6hv2jsj*RF!PD|q|LXOo$YEt$M#2pI4C)+yUx@IPt&LsT253QX z@UIsAQJLI(E6??g@lWvMdF9X1>iumA7_XO)MD5M{v|XOBvF_jV`7?((4`Nm_OZ58% ziNC|}FY{JUv&(*8#`_?3}(bEC(L@IawH6jteV2lM(=#+nS?gJqT6%zVss%e{`rUiftyD!OU!WSZtt% z#lTs|4@}t@@!sf353g@#J*tv9BEIL7jOJw)9ONCj`1OYd(nh9!%LbLRnZn#g_ANsV zB7?z%HLhr!lf39y=Uc9J?&rtnE>9ZR@0_ z%BITee(O+8iSOE~*Z%3pkUy?ZbMUw`v${a9yWa@ih1?-JQt2aDY~Jc``l?_a+dH^= zs@G+yntE7TZNR454|3GYeSZ6hL$=Z{DuUh`cd+KbMJk-6X{HCe3pP35hgK5X!eY;B zsG1>*SoeE3FhpJY^#<*4z3DYE&>YylXe;KTPo{vj)-!(66^5rh^^2_raHg00?14zbJI{M zbMw|;+f-QWQrTQ-#D~FO>2Huyb6XC4&&}Yz{028`n^j;hu<`vw#m>8L{R%!1?PG!i zmQpHd|LLabeGVXK)!te1M^DD9J==GCLW4c&vAD(I)7Y?uVQ|}&dNBVIW`NMe{dFjK zl&_KT)D(=m&2$#ey#`jAOOl~MzkNT#;0|gSHcH3+Z|e6g&*p+NQduOIha^S&g@+f) zI|G+2gZmLM5V5S8D`G)JUjgkhxyE7xP-Nfy{{3QC3(w&ORnCT)3m5K_) zev3Nf8tB1E`eP)mo0#?Rb3|fU;FY?Qgo!?@Yz%H&N-p=sT?i})!xHB?ju%rq#JdgdA}b%~1AX{T-80SDR*eL^xlhLyp(&^E?7jV5-EfNPW> zY5C377UpKmfMkSy^3#WtABT`5C4xt#@-T~7hG6476-AWj%w4%fLzkmD>oc9Pi$|yp zXCHZ+qb(0 z^asasd%RR8Ket`9HVOyRqcvKp+mNtS3FJWJ69KT!aKCzuNG2+cLRy+$QC|pj=56@ILOu%dc zpLw|VP)34Hs$5YsYmjYs1mmw{I~3(tBSAaPQCgpL{Mdvj~ES zoC;^tKV{wM=A=YHg1$U zp9Im4KmLX5A{+Pv;kmX6;wPI2T+<%MultU^ePw)ipBB%wG(0#FKMJgo0zcMGK~0n@ zc??nGZfUtm#F-!N7vCPr&w+fC+!(VsGJC_HQdS;RUvV5l%S7AD2Dh5&$0V6x0g;u; zCAn=Mh_OQehRlJ^s?h`^Tz>J$bHPO!UPATGcV}{GRHt+@NO~A2S)bA1ZKL>(ueU;u zP=xAS+Q=P+8}s5aRLC`l?u-SLnVldTQI(8Nq$oBt(HhIz>neIW3d?y$IG73>8L1d5 z?$4N38`h2Hg_?SlU0*e^fZ&UG*Qvz@3}ck-={lPL}Njr`duPT#yHL( zw27&%Y*I=V&Wv|^bd)y)Xy# zQ)(0NvZ3ih)lGj`T#XgAs$N+GG1C44vB6{+*zdAYm{BcRgv8h+Bpl6X^lE%AZnDm7 zav}ms8Zvq=SD)j9sg*X>XH`f7yMum8Dv9#S@rlrIvP`VhMA-z`nAWidLXOcy6Djgh z(&7 z7+|!9aH4?v0O096;< zhk^vQezg9Oker1xV7O*7v|0wEfw}mC#PQmLLn;}qbPY6y$_7#oF%y^JQle{$S*gOg zvl=#{!j*kh-TM6iw%HnrM5J*^?O0hACObY^X`u`z8Vf#Orq-dBzIfQQ&L(>o_xHCI zV8Z~&*^yjxz1pILM1PV6qeJhLr>V8JvnfND?b}2Y;sYA$p$OIJxD0q@`ZCg1LJ}KC zN0a68=4(T;W})L|3T2}JqI_c{YL$9>tq>-TJX#Ar+e9+r8hUOcHDNPZ6=_>ZRUtC4T{Y_;&e$P8mt*&6zUOehn!b6Ar4CQHdeBEe)RSON|Wh>#~IRBY`m zo<~-8T)-hAOGgfAMn<$dP(1+dvt&^-Wi#WnIT$+e9bIJMKS){V=*x!;$|j}58TXN> z8i@Pj4^+!6Mr&d~Wj&XCU*3oU7QTf0QmTP#^~h^(dTV=?4fEquMx@Z_6q~ne zDZtJdOgIBsJggN+}efN-uwcVfUm7ZCYsPNBcB*% z3LsW87?%+xji@3vUdW%L$@H>Qv-CXg=^Ol45?&9sal82VaVqq&Hqtn znA4CJR(oT-A5%(~P~r^&z4YyH>k|$6EKZx=;kv4`kDQ`F!X0w}%tf zQ`5DTAw#<_j3c+>$Hq)aMBHT?-NFXf zy9Ac$boVn3G#5=Do!XuThCg4s3Lo6aZ8uf!&$`_tJ7-tr+%BE>JNkYwxOzTocP`)P z-En>Xddt$Zo0xpE50qtnH1yb8_^fQTgNZC{*?nqudx)uWv0#R|(P1%)i}nYCuib`& z$D@$afnr9+&-E5mh(-=2CjT9UH`4blcS;YAFNN?YlcO-eN^XwBv<069xhV!E`Th6q z7cel0`IV~G%ga{v(u^E0wh0rF7HuE!0#iI0n*_g|-KFP?j?xy-%V9qrGO zWyj|e)4SyCS+6E1C!?>Kj6|KahcwEI2@aB!+^6eUURz6h>$f2MN%PB=jo2FRAJf>U zk*Wo?(%3j|dg>>TQXHEqoQr4e`lH1QWilEsTj^^e+@~KwRub}MdHJrfzrW_X0CII! zs4dx?-SvK)yewOF%viT$Yil+CT0aZS@C&Q4Iyrlqt;H!)YQSc#bL}qeR(-hGEdRlJ zp)SjlH|yy2Ey^Z9m_=!=zwC&=Hwrw~6;*~j2+o^vEu;_Sg%0>C^Te+@-`sRZjxpq< zX@sVh66)yU_IrPqQWwa4aJGmLepvtOPNMFe>5PjM z=D}-6X-Loy-%8?XAGk6abA`qj-_^#Zp2Kk6Z4!3vp}FvqcwEoDU&Kt3e5SpE%eV=! zG=uOU!*+YH&onoXH+DA+@Re15pS6VHxBMURZ~mN8nfN@!GO;8>d^ZFJnq@F#Ufwyi z81cXeDe$pF=(DN#og&yIphNn5vNxJHziy~*z@CYpL7v%NlHVwv(F1Qag3p=CbEZ){ z;+#LAmczjnV_xwQ$N5GoW83#|Xpf5KDdJ(GY2sdoJtSW*$v}s&Z-i!KI(R=K->8~{ z&H}%Ou;-U?w4s~`yyZ^QF4SZ2*w=1x1h|b`FGt{s()AEhqxU`0F`*B{N#wXFt(Vo& z_!lk&GMjckYM5l@bZUm{lFY6IbdOm!ImtE(a78Slsuj;>_ubhO0@+M2#U*$4A&43nT9?4l~opCrXM%6CRoJN=x+2Cu{tX09_cc8(Q}Kp`HnQBQzzhjPf(t&lV` zfYe`=e1@})tJA-)O8sV;e}M8e(ODNz(@Xjz+@_-Fl>Hv~jYpKn**T~!u`SD?CD2nT zuI#EQcfNFrY_C2c^>rvwbk(%Gq?F8Da&&VPUP}yzLe(mFS|w_!JTjZ{GG~;_jE3KQ z!1_k*s87gGu7|?9Mwy?48a*B!IU@ac>}Tr`2OT0+#|6|S9rm;d=SE0nR`lrbYRc*A z&(ED1|A|6$5$1qL=X?{!@RYT&mCgWamb}rJ6_gARqFY;!%J@g}h5+cb_j450rcU-)W0>TKY^hWH$e<$bjJ>hzoPXC8 zcY+1ZF+nW_d$BN4j}Qz&X*Xfz*CNiKI+1()Adw&11H&S%B&5U|5@L@nmgpmNr+R=# z%VXFfW|vakZ6PtW*I^(CuyyR0MUWVXcCoy?hY`t>!0QAfWZyiZ4@qmCjDUd{@x=r& z4fwM1N7S4s->fax!N^`NzS5mR0RGuG;x6j!(24wZ`y*XLENVR%7?60E;~1Q#CF|9A zkRxJ8p7I&e16d%J=H=Ev$?PR~0^KRt$pTzjS8-{KofZNs zrX#<8)9yUiW|m`|hTp@M5QW>ce2qF+9yj4g>uH;&+oo!;eoPexDtF&dOTOt)3m`pW zAGfQpy|}%)Nx&o2z}wcs*C40P|BRbJWyfAK3448u6E^=2Amkzq>7m1&{~1_iry!KT zF_4$%#KwhY*-lYEx*UHx5gt{YD>}3D+jO`&^26uDhu60j^D|gyYfLAbXNxtY9X@X? z{=Ax)gsr_`w{BHbT5cJesX@|3Vtgw6aR6;OGsZQ}>oj%TjfJO9*Ljz!ySFG3WRpJh zL)ENraq`Ir`!`K1wQ0@tjT6CjK}L{YkyA3Vl)I;p*Ht*&?MZ7O12xxf;4yOkG8h(A zMh|=CJL$7|X`d-;B754TWYB0MIW7G+cF+84Noa9 zQFWI_{1LSy&`S`&gze$g?K2n@5az2iaeNrSr!^T}tc6liOnlEAiGE0;u>t>b({*NB z%uo@PTkJL!QlkV^Wz)WH-88#d&m8(_zY}94WrN9W)mLW06HZoFe;?nWMdzi(x9hrS zFdI#9E7}`h(cD-Oywczj2d50%v}%y?v!Re~VV|C9fmNj`@#SmyUtP}Y^s2=n?Yyy^V(?} zminycOIfBKSSit0aZ%i5Az``yw|wZA>aJxkF0A0Cdp~xZ0MG*(o?;39 z^AvMw986bLL$n#Mx%<^7N^qPw*O^a>3oRv&(`AMe_)~)KFb;IHVqtY|U3_%;nh0jp0{ z4%%?HnqTph1cDT1AIFGw?$?UL<$}#p>jG425Uf#^iv6&oeh!}BEg7xh|A!F&t*=Z^ z&+vDE{|d(6r|+Kt{}Zl%NxA+@cJ}{_>;JE1XIcKb2L9th`BU(>r+;54|0cxzm+UMn z^B)!6{|9NYJ;}{pVIFCq)9!Lj%sUzs7mSWxKNw652qcH# zmuZ_GdB#-8vW!QXu8!gx&RK;1#V0LztKrp5EvD7S$cKD`hzMHiZ`} zZC_l(4>dCO~=S z#~c4bK{4p0$wc`i?jZS4x+9oxBS9&ntk-ZLn!r1>XU+#p536t94yY_yPxK_MI+3{@ieN9>X zNM3Y}eOK=nBG3}1Cx|$rt_+Mxs*aM_knbb9Em7_7pR@sOMv3ahS|2HB$S|MTb)cV5 zQmEkLYAe>rbN1nK4HkF%?pBqYIj=GEP)D-i8_{%UA;Z(ly3(q6ShQoeBQtkE4fQ1# zUz3&aL2%z8KN9Ke#z7le;8@I+mKSEMV1*$(`+;XXAk=R5$=m)b;oZX~OmpxF`vRXu z;<@4ptG-HX+A0iV{t!ecYoLhoGk&C8`A*CxnGHIDF&68Z(hq zif6NCSre6Equ0seR8cM`gXGkSVyfiSa44r0C^jFz-px8JAeKBG#^j~Snv$bjQs19L z$95?OCpx~oK43+%PHlF|2 zW(UlsiB)o}7uCou=`3dl)~3oih!spg#VGsi`_8#uMY12haIN7Z%4CqtbI)fx%FRm?RFCI%qp11lRmy1o^zc8TAIN zG5KH_22YpjSYBFP#ZeE*q=54M5)pQ7D#hx))8s+&NLCcuN)d&sxG|mB8KEO0M{tN9 zz=eSej}{3R*^BUW?JstB5%rbCh?}gD)-3UQkc?`dL&vY4wIFBWuH@^o#k7+%n!PTR znbFVsI4F%CaHzvoi{A{P>Jh}2Jk+Tm7WAjl<_q-f>6Z^6nA>cK&6vlUmIy4NMNji= z0mBn?3&mZyclN12$JXTlH^(F6wkdNvmKpJu(e^p58ge#NO&e~}E+aZRh&A|7-PXxF zeq`B=Tm@Uz`}v!l8T?j|ABVcI3B@YvMb^0gA(X>{R%t8jlrz%46;I@EJx<9_w9(I2 z5uY<*Up{DWOa;9azicd>_9$6$3j&>HWY>e}@}Ru^oy(a-YJ)qUgXmO16X-%aq z_`BTt#HT|4L-P+K+TUuI!PSP1ORh?RSTOTr$Scjw2|v$R3@WrO6MCoK~0G4m7P} z)A>IoHSVZW%#FNxMmKdTT&&He4KD7Y1Z&aGcyw;whCjp~I5G&DTwP8_2A>mmJZo`4 zi<1!=fKHoOL3H6rwl$$Oge9<@OpLdkg__uSx-XwK260KE(H&|ACc+PRV4*Q1fb8s6 zntkT{c@c@GCq@Axe*Y%Y)owuvab*!&FYha+p}1Z9gvcBnM^lD}W=!?>{n@tcTY?vg z&~xVFrDWs;oTFj6VK>0kqYdvlom_+;QRv`6z>ikBv_2V6ABbQF;N!cTQ=B4RBmf=o z!Ka302M{opSH+l)20jOTGB8mNi3mboG;W~RLjO|>1+5E_#NRj$p|{(_ldyf9GD-1x($Ua08$+7DU51CqLcBr`XM0?8(QvjyN8B97bryubY?e?xz^5D``A- zxS&d@oqFNe(#4WK8wtbV#5Yp4G7PB1jpxr)OW0?!KPb>bM#b%Cb~$C+H8ztxXpE{~<&B z8zDhYNB>_mj=#(PQ1SlB(Ebn#{$^bKPbs*Zu&TTmg{Yy0qoKX2zV5%$xPQ_*2>O4M zDgGg2Na^a!S^d(r{HNqU^6@W8|NqLz>HY}(|C5ljutNL+BmDDV_{!e@y#7`4XNjKW zj}uHx%>V1_zqbC{78C2AR>Hp?%wM#DFRb7fH{j0_^A|aR<;&im^{-mAw11WUvHh=o z{e;zsQU%vgR^T(^d zw)|E9Kkfdn%YS?Kb+rGj5%V_!fM8>y!=++m z{X$JJGBSPfCg{J2jQ<+}g5`^~@aN0^;2@~z8NSy3AwaNvu{i!sfM8?&2LZwKHyA<` zmzC*1U=WOqUo?q-U=V-K(|^DqzD)mVnf;TM|5fmRWaSM1;%NMvfBxkF6VqS5{lC(3 zH*jag{`;q~wfpne)W@5R(NXmpD?&oTX!D@~a$nvroFTlU0i7UUS9UoZoDi}P`CKTN z8Fm;vFJ=ADx_YFwM>8Succ%G=pazJ`1FwS)Sh0^^JYJiNm5&_^48{l4#uMpmb`vSD zsVFq2{Oog~sElSk@c|6cwussS!68yER;dkpJQs;9(Pw^5fLcJ$+Z7;fUm6>r6fa2D@fX0Cf(@}yP>F~Wpw@&%l{+%q1| z?lJn;p{{T+!Q9u8KJvxR`V1J@XXAa_{}%8K4UL6OmSQ7_8Sw18&Xk2aj~YbP_bu6P z4Mlg1I)m5mL8`LsK1uj2*yN@vo4=KkCQBBcHjcW!rqQ}za`5nkXwtf7=`QMG$*t!P zxLxg8E-6 zNKV>+#jo_+>g`A(z@jwh6a|r_f0A~?xqV;bn0K2^!VQks~-kjZV>7W|Maz51E z?A?HddgP2BN_5^{KykmFZFnv`Bs=eIbcpr~@*tYxmY(?hBvYU6Xu7Zty&13fyjz215Aw(<{^WWMDMH3()RY z#W9K5R{)jqPtb2?F@p28u~7v?N~W~%YJosokZKM{Lj?5|8B+6&fHEwK&AODf)! z#qwrsxyGLsgAm;GR|6wT!mzFu25(GrM%BIEZ4d8zI>*wIc;)4Vga@joC8Fvm(;4zg z$yDZ1%gq2x!q+$HN72kPP9AYmYonQ;^d*~YPU=({vt|(0Q7uZt$HA3eVCqR9?@crL z($swuf~LYt)lZ?vqf^OY8bzrTyU7ynMGBQDEsyRiesEo?XnUGQGSX^tSY{Me(v*jmKda5;mdt~Ug@9o@>fe&=CGKGex&fMyAOY)y zj@B$sI#Q3%lIG_Q=Fkpv^?iK5S~IE1Zisa9@`XYk!p}7wAZB!Q%JlBrO27(S)Pn$9 zC~*$fks>GP!GoYZV!L0QEc1~TvP1Uv5!2ed!}oDs9>3GH=}{93cKHIcmPqi^hBkDnl*!*~lb_Zo{rgt_Wl zDP=kP{EJr=jt0Uh#Q+h$EAvN0n0nktsR8N5h{dZB*dlJzG*emE?N26)+xSqg+riyy6z9&xt#b__ysj`|5SAu4Z)SvTxx?y+u!Ma9WJF>=d5Z*A^QUMoM5 zZwDtXiGr9CtAC9~(LZA`q%Dtdj=W_)2V(WXS<*ZL+K^JZh8WSiMzwGmL*IYJ!?KAIPS7Hw|g z<&;F!F&gS=hNsBk5JcRm7KSGisG!+VzV<;pA~HWY)pM3&fr}qt<0T_vsV4SEKYY?J)e*8*T1^+$p+?tqTB2%3+Q$&c zJArN`O!74_#CEEn{K0z}WxO8mfG{orIFS(Y7WGJUvdJoCcR0e3#m{YF4+BWM&ua}f zg?1|=uLTdJ7iK!65WZ4~1emo|JUBJJ%saV-`aMOLpN^W*K)l>x%z@rWkvP~qUEW1y z-qr zU#&@75aa3VU$O&;SJ|~Efe>9}=A`3v6qH+eCjfL_TngSyDQx9{CBpMqJG1r2x*SG^6?hw9UI&t#lMrZb($7Svtp!>MV#lL z_#T?MT}GdenA9gZ7#C+SbI4?v)E_W5O?!jZ&RtPE)}}B8?W`Igj7f6PFmIPO&Od3O zlRn*`CAjPXV_3e|$M$T8e!>QUexgDve~>~e-~U_*>z(JdL)y0<_loMRZ)g4LShRCC zfm!F>qs?|K?%Ce{#Dk7{qQk^~&SQ1A`(vFG!lWa`_9^ibJ4obl=PKE2a$DW)2n2r+ zpuUkD6Z;Wo=jsWkce@3rfBOYn+|9-rU`j)V&0QTPs30G;MHZ&_xsVKT%A|o$M}wH*x=Y%^w{x$ktdh zPK_8Xc0kos{*qhEs?kWC!v1GlkF0o3-sK4@7cQ>uBkSzFb;Xc zx&4JIejU6Ae60qTn=HMOGpUHDRL850sq3NbX-l8Tqyvkf5@?}I?s^~WQ7#=WNzW;V zp3~w2sDy|F3B{e+AoLQHF32tzF5|MBXmc+{8)HZgm`gS#a!kd=&arQ? z=H&bKd-LYvyc4Fg`s>Se!nKiAm5cC1i8JzQB0Lj zCCR8qy9nUAZ1O}$XfHMM2kfqVbFUq-DAW`dwy)1I1cB?fk6A331|Kq6$nw@xqGy+R z3pZz|zdJ5=a-1m~BROI+e7|Kx(;ies-|-W%|5V@ED)D+@t@4N!2jAk5)skYG;QH)| zU2>NxJlqf{J;xD;ru=QJ!5C^RDZnUr?81d?U<$m|)=t`k_5^p3KW-%TM>-2*##OfY zMl%{;^7X0&vzU)rF3z(yRx~dlh->Qk_fAZrMr8Eh!nbF7gbk>arpCaRG&}r;Tr)WM zStY8Y>Cx%v!{$mZv6E9SJr~+GEhH(Pueu-@JSmrXOhy#pb7oo*xU;9jY%!$*QAyHl zl-_It@9Wv>iR29JR34`5$~~>X{wgh?Ex|Tp2B${FO-|va?p6gs34?$m5AN`Ht?LY~u^Hz$7;mr;CU3)>* zlKRE7ixtAj>#(2rQlZF+4IjcKYJ$V1=YnvVxCU_awWoR*++(9Wwg+bqiHS-$+t4S- z2s&?Y6(zo=oBY5-2oCwpT9+-J-RuoE^w%<_G4{==h;!~H$&kGp-}Q2Qd-ikHs;~S| z@KJFziJ_~}fYE@+NHc$OFn)#XJ`NTgd3TCHPDg^d8o54y8$urNn7UDxt)55ji!5Hb z-zWAmz790kDmSXOt(J)Xfn}?;*DS8`anowS4Di(CG=Ky?&a6nq6KdWUeAfOC%PLSn zspFL6YQPx)@-0;?PC!uI<8>FqZ*8U3Cj4oS4kU^CgZyfTI1VrdrO>g)M)}(KTi+~h zKI4p=44t-6{6tK1^Ygf9d<2oEFFZfASye>ayZ!<DiFF*4V_}qYkkOcB=7_U6;f_p^2Gz1`_ zT9bhjd$#H3E&rk{OEs;;)iGK#LlDq}P$jqF0epnsaj;0@*c~C36gE;qmyk8ycJojQ z#U_g-!*QNOxwsga6)tx!s4Aq%Dn5J{lZLx{fab5ZN+3{>_6en$6Z7S&IPn1xPd*+* zHBbtDtB)?+g%4y0R)_4au~PKnzUXTN++o0e7C3~;;W-hpG?SvgyNM>R`?773neF|& zO2G0kbWaJ+weZF5J;xyJE63h?!nU`46~=Dy*9`&E)hj7i1LS*+JBeg5^fnP~UdMCm z%^a`x^v?Tv;;ZP4mQHEyZYqJO24=>cw?vs;dtomLl#>uE~AjJVUT#Mb9c8zBbYKhTP|2aZ(-g0$pXUcJq}H<3)UkQ_Gc7YZvJS3 z1*F>jN$N6{-mUS;Ps_PhxFB4+NNVLI3EIy_cT&^1$Z8js;09=x&ZV?3#C4-qC*}(# zeTPu-fCigl8{_Gr=4U9HyDDYaOfuJ*!;oAn!GU|@FnN_By{#aApf!M!IgGAn0o#sk z`^1bC8`4+J-$fRebKIV#D!|Yo3X3{tl9SdkcT^p>02Xv9^)?}EXH)kGNb+%_CKUp5 z>h$CR%zVV~sszXR+GAb&u8get z^R$iCPi9ZVZ`Tm3COQ5}lwA*u=xZc?fU5-_ZQ7QtD#JY@7{JSKTq_^%9QdTDGQL4g z6wfn8SPf&pkT)zOT34XbOEGlNUs6rtb+^lAtYmouVll4qo7!xCwZ<=@0uWawq z5vg`DalKl(zi*d+gO9@xvxcR z$;T5mRU@0V}H6GLzfZ|P__ zg}7WuG`O)8%fiKQzt)O8uYLVxy0${CaA;Ka-3%~T&YQu^pDF6ubR64Qk<=rvMmFo~ zgp;SFj|-U2rz;iMMh4-@52k=O;&a6PXrT|fxzk?axZm`ROw=!UB97}RcXEWQt;b0W zJO@Tf7X2>v7X9@o>9kBhdLR8HZf}mPV%}RXm)6;{Lb>8n-x~Pdt#h4m`vvdzQH(cj zj9n2{(k3OPX!HAzuwOKfEH-a=(T%f9H7!^u<(8KT(qV+o3wD;2mVjK~!dq*vgFFG;ccG}oUY z@=jhDImV(x)`_r7D8wJ#uq4R!pnv77K!%oL=AGyPIvms9FmTDSX!Xu(OG>ghn-}Y! zP=wZ0=X_{KybF1ao&+_Fa9m=$f5h^YPNffnp~usnoq(GGD?=BXPeW&Y8w=-wtMoqC zKgOFU5T8iuUoo{shbz(r^&y@|7915B1-xv#ioKqby>dDanzCpn5UDwo?=O$sB=JDj zD4gnk&=+>I*$|v#lW4$9lvrES%N7$~(Rix1(b3!+0eB{$r&`4(Ro?$dofCAb*G>`{(MOOk z9~a?ZJmw%}Jo@@=&5L{w9ep3nY(J(^UdF?t2ZuF@JqTGg90p@$J^DK{GpNvf)+WxO zSx29>=`fddpqF~jnD;_piWdI5ce|TZBKCP1pmVzztFXPq%*ER3bngkrkCcGm91$4r ze#dvtRpvG(PjgoY6~oh`km zOrr)x(JbZSx%L~Gj&^kV+pv~9or^=A&lFk5-zJ)jj%K{BkPR#)Zf-2>spS)$qHfu<(`aOm4Ir$!IA*6?_X+tnGaU2U0chtEz0BnqOOIJ)f7D`H3JUd?)@JE6m&vXh7J;$Ihaat`% z!qi4GYb7dDHvKEMm?_DDTp5RLt_Qs?Y7~?HR8m2{1gGdF3=Zt{bWx9|rB7<)f8CL7dq)-|^(4N0y42o^V2)XnF zp)3VJO;z!7-7uF?n$pzJ%{ffh&vF>%$z86W9gcSff3&|R4S+--g}Oz#)$ zoz&0HKUO`furYvbOF8nQF+!K~8@8v*PCBh3ro-f|+UTyu&v&6K`Q{mRZQDYf9jjyl zq{n0(G`(GLb`HsWJQCiJgku_VUMbSvP8i!fI;mI6=LgzDyva!|{Hbl3ZG#X$Lb!Xb zA`3f;O!_93ZOgYMG;I`~frmT;YLDJhC%*0o^8Ua*o8CdS<>N8I_A1iK`@_@2e2kV- z@fw1+{;rkHt?!#3E6jlr466N{Y^Sf;A~FdznVhz>0Yrv`~1v1hrHUbT23JuKGy zenHDQd@ct5);~(<^pJDJ?NdW_FXp+W^`W((GSOB+Erz-74HJAlDN$Tk4ITW@Ed|67 z*V^CQ9Sc%qjMb4*rQhy9#d=7~Y1LN(sZQ|Mg5BuDoJ(ff?x;&JF;qoqkmlt#n(!Yb zTB(nAJZ>~+ERYGMHr1S_Y@UCEV>_=*Q`1B6B5KY|_c9F;>4i<= z5yS>d9dDy-Q44ata$RcftHjPz;G0W;ypz7&AZD3<@&EVi9goHZ&71 zU>b!u@sn}sS3E-Jk9hZBzsom(zU|ujS_PnO{PTD}PbxVTj|yLu_2y+4(&A=vUVPE= ziD3oI?&bSzIf+W=db>C^wg*G{q)EvPD9DjT37mL(~4oXkZRTMV^oOVTP#pT2Lk zKLb59&LKLqwvT8~)nG|Z@ve~6zr58v%PoYCs7e)1@i~n~dkJCnI=A4vS1IZw*KL_! z51u9lsZs!yG})+4XDmIfJ;&<$R^=*`zU1H5KMXZuFto%1*zf|iJlaSl1KCT(umKH| z50DHVy!_!Fsoy#;5uy3GfuP%`BGk^Ib(uc|K!?nd5y@fdg#~$!DlCOM*KCuvQyVhB#D2Kn zR#%pdtfYeowg~f@@LH!(*3~CeW$V(XGgejl~cOiauIF%KYNqj7zETCz0U zgnqYdG}u7n!>%S17>Y2cX^L||l#8OOm&(Xo&R!!talstVqPEZUp<$qN1h%Q7u8hUx zi^LAR$o{@?hPf`xx6So#ANGw;QjiF1gp$!sRQ+_9OeH$YLHQ^_Eyo`U<{Q1%AX2WA zVl4-vI=)Aftc&M#nTto&j28RK&4{~e5nr(xr;S+~=MLs`MO&m6`f(5c_9h8#5w{#9 z`=X-RPqOnW7Zl1Wcv<7caB2r_c}~4gP&i$&caT7Mz^AMyJ}Q1Dr*ZqOOIE#Wx$9Y5 zS?P)oKZw6EE1A#K@5BujSvtkCt1==XuJ_G8qB(BaF_ZF;`rP&5n|=q{J1In{tE_tM zi--ZzxE9i>$%G|~>wI(ZR#Khiu&AQsucKWfJKD+S!deA@0r0^E*}ComW>4JoQ?Pz4 zunND3sVI!0X$619vZ|jUG_j|c(Bie|CV@C9X5=Q?t<)+whWLkm@DQMLi*l>nv`#vj z3Xrgrt1Jz8AW;y5(GaZTz@-_OLWD}VGx5bUD*AqlnmA`Rh&kE6Jxy?OUDzyw$3B02 zODuF3=%2AUYLmLZ;gnFBF7)%2w^YDo_jFi(##nfbtanT<#A_5t>f$AT+A2E(x{;&m zvCK8>Hw*(G<^j)}4$`3cp9Q69^52l`XzkRgukUP~gK3N;Id>dkO3{x9ep%Xrq~#OmRFk zF$1I=qUKrClT5`M7Si_}6xGB4wmm_%9JP06Kqyeiz8n*Gth3e)^`R_@qC=YfrlyM& zhr{>bQDmv*-6N~wk_>UfMB=Gd#|X0;KXr-kA8TG5m5BN#gJ7s@-k@rE*7DCe_tx2QeAkN$q#gAc-YndMrgHP>Dl#y4Q4i zwtJ1?bVF_!2O5PAeMpE>+a-Z#RL^J73{s!?+O#e4?zH>9NdmOHouCIl9!<8vW(RY( zU@5FXcB|**5ngUQ;XA(SCk-+jq|y>2)HL~0`ylCVEX5T4N&X?lSQv$RbE`yZMs=KO z`_93(7xHpQHj#yzY#w7V6w7(3>j(659_G-sv`d5+$4R``-oz;8#`XM*SJ83*DL$zz zrI$LRAOn`Ch^~qf^OGPYY^F{m*7~8@3&eL zw^%pg(vCO5o->`4DzsLv9&=fO)xvc?b7}Jpj!|cYfR9z^{sS1csBOEEk^^UjnG%a&nak6 z7#7QIqPFGaASdNXVbNs;Db+U)aJLsfk=ASIq<9XtL%IkDoA^17)8L*($*}kQoLg+q zaW-?HmxqU9v5S(~Y5FiDn<_R#sL-t-5w5x>jxPqXF8n2egf1Z>WNY-N=*piUV%X(1q43>|UPIg6xnwOnBaZgX#h%r4*nJBUTI z6iAfwwvYDta^JJr>_EcQs=k0b-H%~I0jrts%ogkA;|+!U4jvr`UE5ql(WK^dQBIm7 zr}C$XaUJQx(2OQS$mfApqFkbD0JSgs;4SYeCD4ISm26Tz>w^*@t=G>62?~oS3_HHL z2Wdq92rBXh=S?)Z|gHo63v(Om7{8Y2_vb*mMQK5^6Z=&1mJkRIe3{P&_*9JarTbYRW%EE3g zm&0o-XW(!ce&j0&IXL&7+w5xRD#KxX^9IzN#%fDS4@%^hNqP<#reo%qw|X`tit*YBkx{%31iB z&%`nZ1X_ETRxZQM-q7&OJWflc82iZoF=QAwf*Hb7-6ejuvE;DTVLndan0cYLLogfX zCYnJN^$`6HDqk62qI1~_BShUMEY&V``_;BV@KD)M-ul7E)thuOj90?k(L?otHd(6& z{Ll0zc1tB726*97l1$0@8nu*U8&$%_(d|C9p4LxY&{7uU(2_|$J6~ma*mQ&0sK_3v zd1fz=g9#)P9dsNQzGu5rY08=3uz@8bJsOz8sp6Txbp*}Fhbrh5#vD0iJ??}}+2L>c zBNqm@IheALIB0OwDi}k)G3&iX-h~&UsRABXkuYu}5rk{nWqra}3J^?S$`nT4t&z$H zPDV)-GGXVHEEAeb`nO1zrbImxFm_v!7gK2yzHsgf0~ z-5m!$b$$5TR32?(2}%eENHh#Ixl06YAxoQnrqn~NFwDkK(4CPemEzV?@s*;jlz-B# zAbL1t=cjAq=tCfI>aMdR#LOU@dwQFiMo-{-UU(z+(X7F;)+aK2mQ2m%H|eXpWL6>$ zdzV=kXzP%hCd-%5+^);0lu}^+xRtYB!S(CG=3u}h5KSbTf_{kFVHv`sEAtXWxS@+^{KJ^N*IUL=}_j9_XUc*cp-5iF$*I z&uN>peR1|!A6;_>X}**CP`8WmgXRi{l^}BALD2(L)jG(QFuKm$0{ic3Ac`9Y%#ZsN zU4w8E#ib`Nt_m%)a}Z&0XW>w@rdFAA86%}unc~-3?cbtw{m~kZxhLheq0cXETdD@I z=3%K=OK>V#V;Tmgni#VNV2UJ@lC%6*M<@9zF`C^w4<~uw?5mM1HD!=>JK?nwNQs(E zPc!W@lm5G9ma}%Yr@k>t;sotrMLGFY*4wwCN+bS~>g^cCJ6fEmR~P{v;^{ zk5*YOiE*CPQe-7%mUK$s9`-H1r(F?E42bW@F7S~PXv$a;qq*Dt9HgKMsm7s_uxI(G zr{MQ)6(yh_b)TR^bm$ZjSIV4;+PsTiD#j6Zr=^*1cTU)+dY<}usJ~5Drb|qtC*S$0 z@EfVq1CwaXr7en&FFO0ny)U0>j&E*Xf~9!vGS};%d?VSg#~&nZ!&dRyy#rN{KNdHj zw2Mp;Cg1{)V^E%=>0*uIR8yJ~isLOo{}Z6>mQBHMhPsL(hg5(>g-nL>9>oD;3Y7?z zAK!^?Nh7d|-2y2F>3N_b61M3>amMz0U@UM5$+xMA5KUHvk}-gu=C*3Ooc6YP3Rmaj zm!|K}*9OX|opSRgPpk7La7Xq-$WJ;Leva*2c8Yr4-yX4%kig{Xv?;)pz9pZ~cp9^6 zJ4ENK!~Sxq&i^3K|G>=u;Jg1pqQ4VGv+>E|3?}_7CjBI4&KPFS1g6gV6#fcdt;*G| z=y{9i`L*czp8o;5zf(eo@r~XbW?KQ_!W^c_7$#yXt-Rd+nd%o=``1*eE><44R-XU7 z^S76dO}BdJ_y8m|N1BLZz~zwKhod+Dg%Jg-&OwtIsb+`HErD- ztN?$l@ZOrI>VmLzx3K!l>GzjcPs+v0%nflr{;xamukrl~rOn*#&-$-HPzhoAYmD>v z_=%ObC&I+`Lmy4D4J%S6lCzk)`0Ko3?Qa*q+;6ECa7yio= z_v-*S{#OI>!UXQG%)d20{(A!UHw|>(uHQ9Y82nESE^uG)Z}Y+V@5}v{1_ATJ|Cb!U zaN~c)@$y4{St$Rdf%pV|A<_TVcm?==&jEsfK!2PI0o}vHzn#kmhy5`hp8)6&4F>&% zmj6313?%SJUKkYgXB>?8&o~(Tk6K^?f7E>61JLii;^pW6qds1K=pTLN<%jeCz7Adi z5cKyx-(L^D->)SE4F99g5MIz9d7->ef#3hHpuBwG-}ByU_jvuk`v>KP-9y-aXwcu+ zdmnetV*efo2mOC}-CWFU9jsh%eu3s1wm$b;>z?UWM9hf3^^S%tN_-PDIv)&#^9#1{K&V-RUe+85~#+ z5lgV?J48qYb{s40=UCp55#}SiUBP*}|HyE%SNcZC{0<7jttbqFiGJQGPd+^KG*i3a zs#H)pk9!^*!PODxM{L|rb$JF_KU+D zJs8Tc+F!DhpNSPy0|EIJuy{KCg!mNVQ18vVMj6UJRyaGnsc2%;q4F%k>-AzTP0%=C z*bHVyJ{yL%+JNQ~OXRe$o|iokhZlp{G)OjN3A{EREP4`OoJV-l43nM#DrO_^ zdYwjZUZV;n1W|#>3=QzBk07g0`Io6uXNHcYt)P>?KZ7(&)hb_;FaX;fiPHb~6GX}Z zlU`os_Jl>FDppbBeF<*y1O@t;k|nnhWGaMkrgXx3Th8Ut22 zTrhxm$beTm`Nj;u5na$SBACiR0Id?fgj%Wy#|F>5!py3WDLJqcdOm`*K1v9j=s8J@ zt*F~8W-dt;y+M5bN`1;1%rnQW5hzS_14{mCNa#&r-;q+M88k>|nY5?psgQn5=m|5o z<^p!zoitG(F-#DKV{YsRHHo(CR;eOvQP8EOE$)Y5`N5edF=Yi|@Yj_YQAEvdCC@>e zS>6R>h@-lu!*s9jV++|U>G|#t*%b5wiz>G8zTbYx_Z}C-r6c*!l?lL+_v2? zH)s1rmd83_6%|}DTEPqvX1}J#Q?y!gvjiDQ|VyXaDPp zR4^>UVnG;r?_v-)IQcuEvq(LWk*1ox2Z5t#Y9f;)W(x=lhha*%;~TKzTVDD+RCcph zAdW|xWo)wvzoYPmz;_1Fy9+4M2|W1*tG0jvAHwEc!t4U|ef(+Q=&3#p&l)sQ_d8!f z2q7XazUg|9#G#AxE4|#Rxepb;wy5>+Zfp$Yutuhu!eT6r*~m&zw_ae%N*?LvJJ)O< z-yQ6m6rO3r_D8`obqcv3ZOhK{c#?Vh&Vl-_(=&)a^lOeazwKa)s`N_t)uDCGRqSfq z{iJq#&~`=C^Lv-hG(qe*M%TKFKrR!6WrL%=s4UUE%M6|ABf}@uD9>YGBAXPPI2N6c zK&n%m$+SRhC@Hs=MRrIBRl6%ZprhruQUp@mOA1f(yd?spY)xBD>TiRhJU;6RSJFy>m?3c6?nFINK?DJ;u>L51>C^dUJillceF=yl*H0?v7&C_CQ1JlE zNwxc}5*moIuBMbF+F=~g_O$Dn*O}Umz6Q%K39XZ4md42OhmxNxzR=6~xONSN*x0ir zin$4wBSe}YZ~gL&WR*#?%XBT5l^}xJz-sPX1=1GPjsS-Rmf%2+BHS;vYt5~TV>s8! z9gG=2O5C+vMiF#EcLd`bmT4#ni!qca1HFXgsi}bu{?h$3iE+y1fkxAvd&jX^NhA( z`1tO=FE|TLVi>`+Yqi~`&|h_s=4$LG2fA(+35aGq!*W=MvDB;uye%vnsmMt3ok$kZ z=P1Np38hczz&5k2R0K7`be?>Op(h&QPiABu*D5^901>~aJeuKU3c?X~lM7Jg5t8Q( zSBG=uaLk2bwQ%nRjxc%<+YM&^O&{aUpv6DMAJhWXJAzX#x^}RID!6VA45T))AOal; z>ohA7NJPprnWKmfk{!%td4dxrx^{>gsT#cDZF#CmvGEehGjz1&u5epvI)GPLS%b9C_;UmuW{q>LutXPX)0-fe>s%cBu+1MGpF6N4rdYxXU1 zwn?VBEdiJ$xr@DRG_n@hAU^l|=q`_Ic^CTjqdUYR|D+tgjUd`k#hC=(`}bce{6Ff# zeyR^%v~+BcTJyA)DdNaxROjWWu6-r!KI~vi>`fg>LUS0V=H^fhGs7=wz=NNH2*1X5 zY4qQka#(Mac*(L@4F+u?X7fp?`zI}((pq+LlNva)Z2LLeQTexb{Nuz6q8qIkm{ zSmw%A&7(nV^TYx5(=O5J#-}7$!Gp?%w!?#J-VccgGH2k!Ygjm)9c_74ek`CeEFohn zG6@Gtr$?|+$T>u~3uIz=Y+?HRSghO4&v4Oz)S0#&;!(2iwT=e-e6xA&9<%21c)C4( zOr$3GCHxFl671TX!+;L6M`iW?ws-%UUH#$l=w(yq9PK`h>vH)~$PYXf8Lmj0lOU+P z^&7&E`txIByBs5CPFGw=BU|1*{&h$$q`ulQ zpOTuf*a!51nT)A!$PzUjo9rM%pWoRo#ldsQ0PmATg%+_eSHFF0m<5j1K#I@QW zjtBH*T{VLbR+e~cN-otXY_f0?m=>X=H9>Oc$zw$+y(SRp!;mdL3mm5-*)U*aAt{8U zwLms1npHqHt%0)_eO*A(8H<-Xwg4?q7az`w2iJHmfv;(v8XEiEI7L;IiJfBO4xz2zlwXsBrD{?q^eg7vij z;(DpCS*GUw!}eBxhDR-6=wzyIC@0MK|3?1IBxeQr6{O&)PUg;OI6NG}J2W>ioLP1e zL?GEvQ6HJ_K>6nX%JgYonQ5g`2i^p?PGU}T1RWd#HeHX_WyE-M*t zH`CsSRkv1-nwM6LFFlvqzRA4#0rfek0QfNEsvuna?$v;U9~*f5jsgP!r2^2iV`Ky* z{3P&w{;iWUHMK-!sQ%%C%EzF6jiOtI$bRwDI~I?bp8)t9xZna4hZhm@!S@9D`ax8> zPoQ6SiKKKvv~)$jI(Nz79NAls!%W3kWr7 z59IJwiJ>w85Aa^t@kU`H20``8G)FLT)c)of$STt!3Nm8N`HdeRkid%D?Yrl1br@Rk zk**Gt%GhfAXgar#qZe!ljWDYn30^$;!w1M{13SVz3e^0q0E^!5a4{ebIp7SwR5afy zbbey^(AxlR;(QD65rF|r0;Cf8Zps5x$IG?+4V;&D8NkWk%;wv?uiG?`lpm7~um+HF z&rcf&NFQMy@St9C8h}k-Q&7Jv7{ol@vKXWS=v2N%7<4sISAJd@76iaS{?HhhIG*Qe zq7oD`|FT?u8O}R=2edX&P5+l1kZBwS;CBGe0N9l8bGkp5zcu-+)UacK3ipj|3%DR= zfFSp*?TED?aX~frA@87HeWM7}?u!TI836^H5mEs~zZT$&Q6T_;#Wjz`EBIb2m=*(7 zfZiG@5^K8;2ppWNn}UKggt`~38nL6Nq`RmmMzfHjpQ0pze8^-3L+|_SSE#p8Tcko< z!R-Xb1e+d7IiREyt)pI(Tno6Yd&Z6dHQa-`i(%u{f}%lZ#aIQ@480W5?(@6<=MK@e zO9$B|!lfT{ul<#t2W}U*H-xSW=z9QcAA_uK ziL?V=5RB`9h8}5c)G}{}CcT>VL@r_tEG)(aWJ0M#M+7M?~K;9JWsFO|3Cin`(V_ zkS0EpS&?}p;w2g-0whM4Nhn$`AS`5-S(Zu9)0h#N>6)#Wy)ICdM@|(_IcH5}YBPN9 zzXhMxw1v90yqMkhpK_kYqotvBp`oHFq9rp7F`}kfrH!T?q#ZE~H<+kFGyX+2380SmXPr_@)QK>WYHfuD?JM&44Q>##G zSIb`Ja>-^_W*2k|cdL8<>Y2t_)d}ZK?=8s<%k9?9(#_w|$1jU5pCQXv%V!^A(QmR1 zyXM+cC#ng}6pa&&9F>$`p5Ii^X`5=8f;2xgAz~gZ+ZRT_u|r~>R5yZ}fDNC|`sf({Jsha*sbFF_}Oc9H0j*%9IJNF;G2XQ5Hy zLBR!KNkMnPWI^#{6$;h*eW3`o2%I8LBy4mNbsq4YPmAj>8__ z?WgTqjbV=7j=p*^8ZkOM8h1H;1ike#UYJ8w1};`b&g)>b$;j(srwos;8>8GF`Q;S$QyilXuhHu6)*| zq^oYL18o{@5ZypmQr9U~Z6>@>d|Ghoix!=B*m>&Se4e>FytdT6W$8T!5D7R4!i9x^ z(cwMvC}Up9YdNU9zEjaZ^*isht=rgJ+gspVc?1cC|`=M!CEle$UaeXng zsesAUUBZ3q#AhxOa}tx1JN?t+F5)3It^Sv>_*Cp9Vn#Y^wzJm_-%#Lncqno(o3aB} zTf_crW>rnq=9q7Cwbpg3UFllq>ziV7xp5V%Cc9^*XXkm)d*mWkdsdS6nV0EFH}{6{+2|94{G58pd}p*bxMwYaH) z{TKcJ!|$5^iOK&d6aIm4eq9G$3v1(lbcy}H1j&D3`yayp-$DGZ0HBt4)N}Z&XZ|!p z^Q9lGzBbHFt-cx(HTY64rVg%@B7a!hUjIt~=vq1asr3~U?O(;A2~PcI%>T3`D=V*} zqDU_9YN=;!@ugO*6|GGFZobq0BPsqPm_LSp2lKDZds@~n+yBSzy=Kgm*#HjA&?VO( zhBI{dYjl>Mj1%epwAD%jw2lKLAAJ~YaEGUGyJRjPxYyR(o&A1cXVX6Y$RmP8Flq*I zx(&EJ9VjPM*1!(vV)`44;zR@+_^3^@1nO{-hEEafx0}h4gt_nO#^`SANasluMACp3 zT-2J1ZLCAo7_oF`fpR)C*N)X}T_>=-N)AhE51v|167P;46tKSVw6;&727ZI2X8xjc zK6xwlrH6syU<9vIUOb)Z?b#W6MHj^ORpZs_S2qicX{qwN3XWKeHekD8ORvP^5AcUKci6pQlNiSC@l^HJuA-t zTseO${MS+bN0WcMkkYmMl7s(8`hA`L82^#oe?9pAN^VM8CT1K;I#$-N@K_meSm>C) z@>le0*_i6{S{Yjyehq}0_fMWX;4ssCEx&(~-r=7r)cm?OB8H~MCJs1EbYDVL{%g*Z z{?t(U#|qBy)i^b;ld-a?!Jo4z=C4_o)OGo%L`%c)Rs8cjz7D6po(J7OOZq=%;*a6q zBmLKk`0C~Fiuk8Ui$l-K!1C4K|Lb^bzY{`3!SI9ogX1V8m9^&^VBAkJyPlaVB|sP7 z3B4BR5bzPtwX~fm4GaLp%6%KyUYTn-T~#f*<_gL-3+**aa~OC^`L!m^*Q$2irjusN zpY_(dc(>l%#=rvQ8>pe@x9i;5kM^$|Q_mUn0dRaCHn1U9J9+B;Tv~|D z88B$yw8gz71rc?30ye|LTXkG3@8~O0pdWepT3QDK8GjIcn%1l8q3B=7mG#}W{$AZ? zf~%`*T~?BFHCesXBHHgthRIG)sGz{|e#`vMhsA&c&2Jjpcr{gR<>ng`topK2cs1QM z$|)eixeL#4YG}FPe{n*$P7JnFI5=izRw^WgS77^X2N6*mykgd8UTlQlXur92R?QfG z%bA^bq=_p)JW;T5af=$A9Bx)YB&4PImzt^q*JH03ADc8TmvuQ+oo0-OJD903#&uq$ zTd3v1OnVW0og>T+ZUA!AEL0xe_eZj3DAp!+%NJrep{^kJfsueWMn5&KYkJmB3-WSv z&Et1gZDfT4nBw z>q3djY=~+RY8p_N?oZh{o9>Q$(-aaL%^oqO3m@OP8Fh=BYK&bPX}>dk0dWf|vL6XQK@ihQHHa4bp@fN>Fd6F(XiX}rh zH-~@2CNfe)*2sK=l!24_2qxG|`R+`tAz5ZH%g+?&a8pGVZ2=PaSV}3jJoW~`fZ;4z zruA#r=_cSQu6sItK9)eFCAD3=6Uo)F)avM?rxHhUU%X269`4+8KgoMSqSH!@^!f~OcYC}ug&`Kl388|t^N|K=XJaqZIp^Zou zikeV`sBlMhI1*+} zq9K0%(?Nm;On=Bp`qg%>I%?v?XBOXsCe!FN%Xgj))yk+W6Nx;?2#QmZekB9CpFHlH z7*PqtJfs`d3+)g?giQ(nEwiSXl`l^zTrbu8I8D8x%AyKA zQN?2`M?=+xy4Ael4YDvZv#=zpdZjbi@bbzZjfUc7SukT|VPj>#%#<$_k(DV*smfnk zWn^k8K1C&UQybyPTZ$D_f)tl7soj@(_){D6YARZuy62zA$iCuzEQc6NN=8KL#LMeS-0!~e zQEXaQlT}cZxig0@|LHnUid!8fh=^$Tt>BOu3p{izyv#iORBMhbO75z&tmMM6`a8>5 z1z}E+ld5B)W?+Uz;f5aEG+FQz0PTk3(q3&|NkvIpQPZlLy!~`}PDNWzo=M6B^LnP$ z&>3!R$*fX)T~SGsvbxd_u3o0SlNvKs#0q?^2+1cZ{p7q==FYP4F!Hd|pbhI*-{v&K zXHd2>oW4A|rM1?B@3@;Q?s&Jiz9lPs&VX6!di^k`C>GMF=zJSpk$`C$e=wFV1h=V{x#<-V zShRUzKonO(R7^z3bdq<`4dn(pqN1u$WHjcerUN(<&Qf;uxuv#Z93$hUiTOxj%*`W9 z;;%eEQxulnXf2O=Tm8Hq7oH-aE^`!mGiazUxv0+1d~VEks~Pc0KX_(756Q2qxO!X2 zd0U-g5R;MB>;|{2%RBaK?~ClaIy&}gJjPrM3%}@hZfv3!x(Gl0aNg(Yeh{zh3yiB< zd{`h+mfh$fQT93~q(;WCYSGr-qbh6nh-B|}nilOMe?SbBZ2)&Lu%Txlqv>AEZT)c{ z1)CJPFy6w+@uKs}Eyet<*YL@FnMwL1@7EOxVyMe9J->RTY&o3*>Np`uu}tKvH3lE! z8+1KCy%fh;ZSOm3^iM16Hq6;cr?ua;yoozi!COmO+}F$7wY=$PwqkF~m6PW&!RgUxr9?EvtALy`~L21KR&Q6<@^PR%4NE|=a zZeb_w(~O@}(~Nh#e_nn@jO}Ht6~7_x>RzA*`7IhcOu2NQG$m)A>Rs2kk>~g4BOGj& z$^a!twVW@&J}OO}Txgp=x_6gKE)uy*87oK6&VbmPKbkzcZ0xXR=AO!)HX)M=-z;Uw z57ye8D@DsS?wtD8CGfWkBNFeodrw4_=bHJ`C)i4efS3bA?M4osBkoFeC|>Gr9_=Jg ze)q}&J9|w6nq_{gk)hMP4;Z<1j@XBcuW=7Hh@o+NjY@-h&9=g+54sGEI zHD%xx)A0!x(lU|?99qDxZ=XtCGdw+SDZPx(kV2OQgXt344hE@QJ@%KEPG5^}gr{2F zQ`TmHW5+Fn#(zNu_F_bqeJOb?E%fd51@zx}^=|{2yl8QGyI-PSZuGsxcGjVfgz;t# z^dBUk8ZbhJ*D1KmOVulagA+H(UrI}XXOPpJvTTuu7S`!18VI7#79j$Aq#+Ld zrMblY*rm|l>tX3&ZzCh(?x!T}T(x6OD-VXw1=S9gA&0r8fkrSCQhG?rR@zQ~ zaJAp}!O4DLqxq{JfB@9>#2}t8AN#@-nJPfUpwM@kc;BdxBej>vT7%rl3>JtV*W5~* zUTFSmBHv`cU=d}@Gj4Ps4<-!&O|~Xl^;;zO7&8gO3*58`&76)%ao6=OnEVKU5dM-y zi0My`3VP{SIcICe^q)Z({X{av4o{>EFC%e$`8{+(2Uq+90)CJM7phtW6?G}R{bA}_5Z(nm9LBAt^uc;K^8{jI`5rUaz|2k>t*O|*e{CKaFSFa;n{Y>$|}lDJK$ zwv{=uSKV_A`NITb%)rb?%uQV~W#X$wVjJ%|W+U?v2))B&^Q-H+(}2R&&Xv^}KP!)| zIFI39P7~3c-wpwGrpvZX08N=pdGjet#t&wg50#?PnjhHj`;qz&H^3u7G8kUWm|Ls4Tq_}S z&;mgUAX71}a`9|5@G;l%EH{6ky`Q$DMqaPl)~2twt}K{MAO9wg3b$nLE~{Kh4`_Ka zy1jtOY@L{IbA+%Nw?YCMohKW!t*G*JNQd``_dAmQdSL>Z;G~jm8pYBCk_wf^)bo~b z?LZtk1eGC-C>G_BU|#;g;u|F%U#8V$wtZb~FTqJeR|11b+|*;i&+FGPQ=hYc6e+Fv>0)tqkI&)!A zz*A@r>^uNg;Lz|cGcgG9#;$wfP>?9!G?U)0e?Jk|QHuvEpl!K648!W)Ze9?P)!3IlBKp+ThR$K?V$X9 z&$iY^L>4$pT$2uT&!P$8<*v|sR7?{{;sRcq+2yQl2(;qorxHC47N$2ph{IP&gQe0? z{^YJUx(Iy2=x#JYkRM7*k>?;D#!gtN6?p8D;E_M$&bV@~XiO3|Jc-Cyx;m*`ely|K zJh(jCWY;ph+FA}To(RbEs_+`WtYuB*bEXOKn~I1;l+bryQa3nZ3@+n);WJy;YMbeJ0>86AsIH}AD7zbMXm#=+v*QfGvCY5k zSQ|THQ9cl8I*l@;o!6qz4;+UeNUl3>h`DQw4PoKYp&@%6pV9mJPk7x^J}USN{Wj)* zcdnXOk*w>msrgXo%xA{Yt1%iL!UybJGmjF)yuE2VX4#-$hF_3w@V*K^Qv^Y7czA#A zS!cS)lSJ~)wyYr?ETFYG3d9f>1Xy3;J%441JTk;%++F3& zV2<{J5~(&*b!RRW^Kt~2=_TF8w9}J?<89e@r6EFibxDWM+>h1IWELLk23OTa(+7sZ zv8+-eQ6mtu4r$Yql0bf2Tw0~BB4);!)>9K}+b@Npo~_49O)=I3Fl_<{1?(?m{4m0U z7R41enW}S#hz^U-06ga6;ingQWoM)p6PLjt2Okas_{nu3)JnpzD_T4@?Cv8oyf7{6 z93g~fHQ~$*)+aq=3Xi~iTVFrMO|y*F8zK7A@ftFDniuQJY8nw^0XQyLQlS#oJ?aQC zCWxbmqoMTcO*tHN>IiDEbl~@#cUX( zVaH60cQ7E76z?tyn8n!`=jifnNz^HZbKmp^?wOHQWD~EO(3=1|u6q|?BiSIttb`g< znt1laf#@A9GFOx#^KjZjO)7crwM0Vwjqsfc|h{e$i|)pKDmc-pRSeTqBtXv`~w+7aox@eajB=#2E7%e6?0wd z0(pH*1NsrlIqo&(72VkveH)`A?Q!3Fd-xX4o8B9OJ3M=g_{NAUy*r(HC;5u}S?I&d zi@e+4JIp)QJJH*pd+5{ma&PM9=vn+bu}NSpUkr^TD6$cFGsJbD2d*>;Y*~PNfKaZa z3N;788C({U7Tg0wHE1_%TOeQ`?vCV+rFsgV6qH@FngTw1?ieD^5s67evQ=G%110n;bK!RC_csyAC^W(3u=2TNX>FgI)w; zIgAXnVvwVvjLCA4;5QcM(@EF9B~4br0UQ77Ah#R}B<(;LL`UH+iim@Po%s;|w-WHC zIChUr+;JmZtP#ono8I0%gl-W3PaN=L+x+iC9=@{uu2(EFVa)g65m``!#a8m*pxiP+ zE-UTwH|H~#{NO43p^i;qgKfD^friCcOqTqxmB9J=Mzi$|O?s$j$*<>odK^KwWqW*S z5E17u%=UkkDvFV`%LU+4=Jw?HJ34`&`j5Gu&75vv_bLAD-o4}mf73>hjg0-kISzw$ zkgG4L5c)hm->6b9Z6t0OO4ZP$j@>VpRL^~83Cu1mb{-gtx2s)=g<6>gHyBYp_L zYrIm1_#xQ=y0rbs?*fK37@lmx;EQZe;bQu^bOpz9H4*uPxDqC(3fFDm8qhU2s!P`k zLg<<<={gVhFy#Jhe+RbpF5?^or`kSVwboAc1 z&ebVErsSOW<$6gjm~S>K2J+cvXH*GEFb6N`KFqbQXboOtO?mftm4p-iyMz$D3@6jz zup?~7jb+%}Xr0K$lVIw2hU2fq4cfi)E28(PpH8ne+as$g_{_dpA9@tUS9zEd;=#fR zs{(`s3XTt6W~3~gPBnc{OR{*U+(?c?7ePZ8lc8?$QkR8G_a^s?Nh@hK;TW}gC7i}Y zI~pCwhDm_9NKUFJ0rQsNaF@5cn>PX|s>h0vmT`Ogp+r8g-0p51!j(9_VX9mek|)=M(T~=Y-P` zWhJ$<_utzI_$d2G^S5t$k!WC|iAB)2KFs&QYBdP(p&?TXv0pGi$w-z0oGP$g;i)$O zFhRV5t(NP6#@P%Tv7iizYkpc>`S}G2@?<6P_91Q9j32(Dv_!Hpq{;T;vh(TC0?hUuJ#w2 zQ8*(xA#B8<(L%vK>sVs4ZDLX0+%KPHfFB<6?Vq~wf)lZQ;sNX+oaA$;K*Le@nYs>pwTFV=^p*F5{%9YM21Tf1e&lQsV zMEUL0z2c*Lt(bGuYX*8vz$z`fa(k~!laOXmGLK;Oumd~_wSI%sTxZhB&_KQ?Qr<$WO6On~PigXG*09KJ$|#pQ3iaT!#+=yD zv@gkO#T~LE&y>pEi7`{<)*-b&@^2%3Z*Np?r`=w*KxAR|sm7BMkil8aJg4bI~Jgt2uiiq*3_6%ujP`Ov}?}^ zc$K`JcVrzRVx2TvMARFM3>U59P*-@u_tMNo8Rto0)Uj@!C53}u>)UwBWtPsUF6z3j zJY{5C5ShTtwRbdpIiIoXMgq;{WOD(l>PpY?IxnkbzJL%!%>f-V3c5>fz@>K6cA5ZI zJfdo8rW?s}e2vzitX4Q+ih{Q@mLW3v1<--o^r!kte`C-8clJg^h`*3c5?_mWxx17G#}(p%V3G6_b(n zYB6;5@z16<=9G0(V6LI?Q3|-VO!u4KG4y~lDBA_`BlI@OL;qz`InoXchG7%U4u-UW z{3d_>`#K4~0YHEu@GHHt4`Kf$%ohe_s%o zadC!Or$DIE_ye9M3YGMn;_ir6IWH3N_pPgDI21hcq1Z%@EV@gzzDW7cn*DlPi`ikX zk7sG%%1^=Lr=CcF9mdP<*%ePCy~W+V;H=A`lyxZcp->SLxLy#@lf~8{T0~;KDgq4ZhOg~N{kla1 z)8O%~2|_Kk-;Qelm@X&n$1LX5rl*S-hG7glQAESFB*FQ`#joSr>kCnl{_Mbx_W4TE zpzACwD21pFkb*y;)W9*E_@Fb=P8gSv<~P?ckDm)!dfRNHf*hQigR3~_f;k6yDBal7 z$w_N#NWX);bQ#ImgcX2O7q!-MZZt1nOk-5ghdSQ(--he+_(AUN6RI7hX|qUW@Vtf` zhV_ks&uEOfw6-DbIY73<(!Y2O+^(Xhvd(BDXuG4}!r>=5N~18y42s-bZQ>t_J=NT% z2StvK6R=Pols$=3LA$k0IUY3t8M$ifb)4aH9kLCDM?s21D!kZs?5BU=QdhiLGjHt= zqO&J<@F#U~a^V;Rfg9zUvR|7rni`6?8!}K&f=AYMrk2zS%ImUQIkU;7<0N?1K@ML7%6xN^F_v z&r`KO7^a%7Ij8ArX^f>_Mli$CjEjdD$hlk-AVI?5cSH=lGOt74-T;Od#mMwRV5PXe zZ}pEs@9VO#AqpTrzr3y-e}EAtd1&m zg!Ma(YZG)6dw!Ou3 z9b&z@#eZFW{j!DYqIzA>Dn$AEV)&b%4FM3b@34<%UdSCgf(xuV} z`IF<5{DZM8**o1k`jg%}>NDcg4;w+j57}wpXCHxX6b$}2Jl&7-8UYo;3RotvXmDv= z;&rMH!Z$4z%C~46-j+N#MK3Z@$MRDq#SSvr#G+ra8 zJup-S0*CpQQ1a~9YO`NBA!T)$7vo!Wjgi~iR9y3QPK9dJ%QMIVT6puF_I0Svp3AP* z1J9B4wNqX6j+WzV-u0=^0NrI7uX)mM2GTvWMq)EBuC947V7b&1@(azhgy#jqJvP7| zGGmd~7@dbRE&;ru37s`a*=>7*16{~S8EO zc7oyEf9Hth#>`Z&)26X#`v#i3TAzj@bVVo!;XqwMabvgy`OqLiK|0K*w?JH68M>eA zPiu2ru_0xVz%;^5?vhHA)#Us8gG_Qj6)3*%l83Y=-xt;%;Y!H#$^OI6BQcS{>*(_ar6ehbGbehv$L zzAatWPT%>V7;FG92HiR;B+b4IdMq60QWJ=3(}F3A4Ck)bE9>Gvc7L zhfYsV978ICfY51Tj3`tw%p{H(Vwb1`I7fyY#?3Yo9Xdsu8DckJoy`@@cIog<9It>_n)84QC6xASby+}!n4 zl~Z-av`7gET`(A3`ypAtxf@Du3@C9aXO_=`Cw@vQc=d zrx<3h?Y}5_F8|tu<|=V!@xZ9u^jzhH#{>bX)n0{xm1!om8ol+xWgCSd4gse1(vnb< z$?dm!Bpim1nmCs}6T6*ho{DDcAtCLuH8;CTXYYWHi`h8MY1)RMdw&+T1>*{uhzw$y zyC^9A3L{q)nPLMIRPyVE)uzlHCujU(v$OR8qNevcW6Szq4gT&JG4n7+K040T)is ze(B}6YbQw{O_xhCqFk-+d)PLc})!jU^llO;jG9A9bx+%*9cDvc$;k539U zg(4?{#uauYujeZ@t5*kPUT)}u|G_mYuzI!POR1uJPV_o*`-IZ>d;cd#09#c>%}1UI zp=K`G$V8WdG~kH=8zOn7h#8OE_6&U2pT(WN(WZU_dN>1LRHf^$g}H6Ei5<) za^E$t*RA&_Iekn{3(ym241Z0N-)oxx&6RS2TYzcJci31s_UsXmHa?N+mRcp5McuIK zI{L76RgNYmT{Tt;tTE*R3hD}!1bP4BKC#X5=#5%L;0r~uO^P2<31hW&)%x$*Hh9dD zeLsU2FqC2^`BfWDNtCE7G!6_r>Ku#0naU0rRhn6ryr-GJE1#jL+SjosCBp-@6Y^)WnD)mduP;%6qOlMk_i0(33S6j2u=L7(Zt3aBRnT&Z{o7;3FY1FNi{nZnbC$+2cxnBA_ zV3qjeW(n}Ts+Q?mCV!xZfFZG=Dn1e9 zku8tYHb7uGsF>(OZYpYn4L*E+kTF`-eV8iYH+o(|JG-N32>Sj_l=LzQzd$IlDZULi_-R)fIrpbv4*5LK;QpJaftKa z6CN7a+84~B8^89$~N~YUu z3M8zx`g$km|Q&m1PkM-VzETUwz;sE!TC zJYX_COLY1;B^Q$^JH?-!3mG? z6Vo?d2=0s0yvfIcH{b?k{9yu)VHv%|ag*`k20kn#(VQ&UY*2EFF#BaNY=ChK7;fxN zweTi%n%_>yfBx7o@irSCk?@(Xx-l;`Yx|JAu-E)3^ z>_y?+>gVzgtz(F!R$lbzH6xWU}EO8TkiWdg6{@4s{A59g+MZnt@;P~6?#YO zam=1{9PvRVL0bI>g*Z%qZ*u~M;F?S)?{bq;zn&xtz^)5SXQ;Bul<1n8Q-_pNkQW?N zup*`X;WLF`Dn9cf;uA?4o%AjnDzi+&kAZ1dKnevFKEyV!XX?3a;UX}FT|6RQl^}AI zdrS3a6whhC_wZ_a4_7rg0~$n3E7BI!G8tr#qD2j((kVIqc!}{$8@%D1fc1I?iH~iX zsRL1Q3p97PgAhh-D*>G-et~Ud>NCKV55znFIvWftRO91Ve*5z}P$aTKF3G>QLwp5( z?#4GXuBU`p*LVrAI4$VwcZIpSu@y^;Fx=w{11MY8pC!QnU7}gQy_o`|Xhv+WTXROO z{2agB!{gVboQt+VTOh{}4i3sq;QTq5?n?_u#+yic3s8(C&IPvl)h|%8DBlhpQT&;p zwg8V1mE{%_i$^E0bQOg&0K4fMVf|8^Q|UGfblF`}$dFmNLBRN-9c)TDBClp=hSuYs z0xE7J+>Ra;zCqd*$MFGyt5zSx_TJLeI(xe8R+FMUEJbE^gPIY zG?2ru1c=VKBas>i6LoKwOh5RFN3$&C2>FrmtD&xdg9-IN zu<`ua7e=_t=o|Ft14?TZm?5k%@9g(bWk1zpxxOrw$?3F z^Vw0+$jLN~S!SX&Gwmn1v2`7ER{g`qXMu04RUpv_(3bc?G`1$|Kaptzuuy(g9F5vJ z!fNoef%kobNfb;%FQBDRuTi6V7MC_dD^PJrjQdVSN{CScPXi? zVc4`w-BWV~UaU~lOQfrn5~)GRymRL?8WPR&CCdXD;sKQT4?183a6v^>9QCGLNrx;J zPQ(HOy7Upz%FWB`966j{^2@?+Z;ny@H(#^CQHkdk|;|mf20_gPa zS(%J4nmB=&_YlNLX3bVwIzG7uM+c}N<&lDVL?kaOcsHL7^yLc+cs~-zRGbE{4AsQ? zl_N(0dAlW~960&*-+~9m)Yi>lMS0)nSP(I#RAWOpZFM3V#(bx8quzj{*Qc}rrl)Sy zM297wD%1nQm(P0P7=%Z|Alr15slg_!OU7o#EuOQ8`wj;RcN5(RcbQkpD0q})Q`cRI z7X+Gp&Jg8JoPsI!14Pss{7vE9Z5P(?Fe>_&pYX079{cGQvBykd%Ax`jCDkzA*!eDj zE4kWHm@qP3NLG&Hut-HY9hq($QE2@%V#6G zLQr_Mj56Pj9W~bEb>^20Sc)BZV5{6LC~q}7_5v^Gwy=oe2g$}JE0{f?eg_Q5n-`&MbAG1>l4MvBlYv(;lBgoviSUu=yf1^zOGK8 z(p$LqEAF9@dC7^R{@T{pDUIvvrA1zoDO3;SRDnt0$WK$Nx9zf3555E7YUslr!A+jk zQEaKU)~Z;GemnfZK>(@J+0X0b0np(fptw}x;2^6LkOUa`>AYbt{8?&^`uSe;E;x#cczx1}zj%rxP zp#V_~Mpx)EVop>fKtLThj(+|@Mb#mhi{+idotPZZb)Xuo@({=Cb>RG-3QaH~ ztbwpFIX4)d#a+!OVH9Srg>z3rc!dCvMa>h*SRj)!P)Wf=9G}cY!Tlyvry?_?mIjak zT3+-3#{mVXa!Mi+|g$7j60L`~p4Z{tjn(Nr2DO2zn zH+=AIccg?M(2$C_{Q_T?`UwZ4bAd#SbuBeBXR8i!Cj-BbFoyzAH6ds-G%vnd9~3~g zbfKDDjBSjbV9TJ8Pyyo0)tg=W3^+`DE|~W#9pK3-E_q^*5%d&+7lJBtHz=L6EXStO zPM^TD{9Z$E_CoqK5+M0`JkKpd^)fjiwx3m|@Hjh--P1R4;DP{mkSjjI94ak!hz+r- zrS?a9!NB%sr5?d?Es#Ad0DE@$dwEnJ#t51M@`ENQ-o7|+zd)?Ux-*Cw8b_8!FYtLj zt&ELajo!IHuYmS?K}6kjo9E1I43B|m)P#zqpr?$+&!8?>v5*5cfLhBCbmvE^e~?pb zV?;CxC)VOU40NzvH@xqsFo>TQyJl6hTI84;0dm0x zI(?k}b|UTF3-0Q|d0CPP$DtBuiC(WRDcgRPO|!ey zu`h0F61n1WGa@wFk6v*h8G-=-^kP=C%Vq2*N3PLmA|Fn8=9l*jI6;-pF!dv96Gf?_ zQd90i$yWoJqZ%;Kt_{$N4dx46a|k8YJQjjU;+s)H7v~p;1af)WcKE6V`%%xpzk_i0 z$=8J}nONwk+>Rb@HD=8&6RKdKOJHo!K=lyuS-vB14ymc)Z8N_{kriSSz?~Daa`m*x zZ7$?D@~~yIYCs8c8VY(^YlJe(s7r#B8&jXdFDSu|qrsL*h0YznsGf#t;D^Uu)A!_k z)PMc%4d-j(2Q>4wp$E7?JPWAoK|hd73Z}yFKtbmcv+qOWVS>!!phlMDNwlN)4^5e< z;?3T8BmEAt@1f_9LXjSjv|e{>&5G$64;jjC>{<4&lhW8#c&7VdV#%nN*SL~07E40h zfY8KJ4-N+meOb?)!+r)>;ITGsn7o8 zHky^Y5V{N+j@UXwsZy}zX8{E?7thi%ZCEESO=--%y=mP zD;Tl(pw#oT8zyL*rT^*F#OvbfW;wMN`eG*?GsN(Uko0=CZhFEraJ0|eYiXk=>x)v8 z3ld3vs^1lf;tBi!6igYbLUE4X$>UjkR*))06lU7M8{Y2D&d{uD99FqTNI ze!QTjr41KR3`8=xFVsJ%{UZMlRZf2aQ!C_RFP{U(=)lP#CXw#$3pkwWdmc`!OYmI- z$l!xujnQ*?)~G0|S#yGQR)1PuGN%DLVAH^;WK-*`P7CdXFcWJZw)Hl{gg85@5tOvKe}y z0{|U5cNM@hYgVtZYL9;2e_=e>pP>&_WgSW6ru3c4D7c@TD)UuC;*ak^-($Oi_MpII zlTUZOw%fRit+B48IQaEd`E!VxR2SxB$QP_N>&!1h#TG0)%v$r*^l=XYmG50WvT{j` z88RV4JCP)X_p~+)E#;$=&NCo4@wn=ptZkn(?Hl>$GZ!m?@`1N!2YmmzpRj)Ffhf-e zbnNVAH*!y+I>Cj)TS)KR;E?tAU<~EnXWW8nZH?Ao-$zc^pk2~2@u8dF5UC>ea#U9T z><47Va6x27ja)hiPNkBW!=^aYRd6LN$gssoom9Xp{f*_Mui4*AeoynQ$4d}@;)+2F`Xdlqd$XYErS7_FhjA3KGgpzd2 zK)7j;nWT;Jccd3iTS3=D+Na`OW1X!|cVDwJsljFJg6C&18r@J@_KopoKH5WhAKFjg zO<3=v&tRH6&?5oe9UR~duD99YsF`dQK1U9impSM_&TG^W4SoRb0Ov1S2wRBZz{f!N zpnA7MX9!&v>;17&C>K$3E!LZeEfaHHhCf4S&=^-1IjbYt#=qO4NLw)T?J z{rZW+J=DF%eZWcQNy?(=!es@oN{%8t-{7(&qdKE%LSd_>VxD?&tEgl50pcWMx~?T0 zU!}L=t>$EVIo%-Bd@(_QEuP2C%!??5Q>Ht$fPG!Xt=?~znV%+?fpx5U-lfq` z2(~id(mu4Agx4a`95z%J-bu{@*MJ|lf@kzfC7JnlAUpcZ(IB=N6qjpt9V=Mvgoj0Y zQ58si8=Qll#VaL`y?I4EW6K!IZn4{=EMY#Gc^fl){cC+nK|Zn3;)(lQ-DmDm&=SQUMKbPK>5KjB7N%~7K4VI%zLjOn+S^ON?1 zC-Z4*b$3R2!5UT|{A@)()dI5OFPTKfA(5=a;=3689^sy%71%J?7rfm3r8=IikMT@c z-bgx5i3}`zj_;!sQ1mqwB;50^zNd5_R+XM2`$lB2M7lZrsofq_?paijs*ob0zw%C) zpNJc)RiZ`dsyBViZWh>VvD6d(yWHzsx#lU{nKB;r^brA8fTYj;^ErD{xIZCtkEQCZlBe=2OT0J8 zHs~Q++}DjHaq8ATqF`OZkYPs$ay7Bi)7SDPeaBmJncJ8FIZvM}yD<&I6e?6=x{cq_ zH*~u9QT~YGxbZCVplw$s6Ya^nEMW8V6{|QL zng*x+Pq4kU{wHkx%V{L}6q&oQjbAlM<0`^igznNooOH!$J@4k@jpt<`>iRpM-FC(_ zFY0Z?a$QVG^M>Zr0RP1z{G=zt;ABo!I;f zcuF|oguBU6;owx-QrqH9%AJG47MAWi=HLV8sw$Vnx>j=Y6G_?Ub47_(KSo)%$2X{u z-4VH*A3iK@*Di05anF<&Mny~^Oy8NI?JYpuT3cF$4+9iX23Xb`_sM44ntwG|-}*{; zz2AR2Sh?TL736r=>@PpQ9jwUG;`o{}m)*G+TFkE~zG?P^v;<6AYN{w7 zj|f3_JTd?}yDmrDVi>&Ya|R|IXS}yKj9oT?!Q6N?KrDEyiNsaIA6UT{?!f3(i(qhk zF|3*)BC+kwf-i>|ox4(rQZ(S1*UmMTi^6fgQ7w*Glp=3!ejTB1%d58|MIKp0B~nG zQU|YUQ1fAGwJYOB_S(1AQ++c}UO4N^!>g2zZUXQTeFvD$`w#BD8XhyR93tQT6bYKR z@fn%@6|E@t9k7#_U&-I+#ocl)0GQFXDSt!?%&>L9vt{Sa0Fwo-v%ngaWFH`9Vkkonw&m}s70T9KC%0{b*0bF z){TBK5z(6Yv7A^s;CRqmO+{0Z_}=N(ftxpLvj=AFV%Jyel+ z6aRa^RpIxgUEu-5u5zn(`A-_3_!SbVbhnpwVA<(Z9$IG6-?Gft_SIIq)b>|ei2+Dg zh8yHGJT^l<`Dr}1yz(UnT(ZZ(f8G~rO?boFk5OS5-_~6T)G}$ruZ``s7l1?7oZO^f z`?6l0egHWU7amGYBrS=b#zQTOLn@RtA_V?m0S;f<-+)3w+fUq1k3(KC9>d{v&`ivD zMc&)(z2Qd^(oKoL2DCf;ta4lT0F7&yKNQz~+gr$N$fRMn@k;qYQT!oN(oG4`V&BFojW5GxYK*m}BBZyb#^z5;7>7 zapY3*2^`9oV4hC3YkH0_DjgWenM3_#EMh-{s6*0r?k#AcCSg57eGg-g5&YS?PSF`J zrMfM~O6i`XOUXD+Zd;o{l1;FSCjqB^UDfzbOx)UWzE&dJ1+KYkbLCxyxWIc|C=SLM0pKq>*&gxVJ?_=h{a?h4 z-OBI^S#P`cn3q?-Wh9x4V2qlk-gDkAq%Sd8Oa{|d}|H*C1 z>9@7dvxpXrMn~jR-Qd0SA)0lfY*bV+yw%DuAw_}!0#K=x;&FH&#SH@-0i}OwuW%GuB8tygt|l1Z6CQqd1Uf4@w#%@?u!CkwJtaON9TT0!%W1WG)38@)<+wDL zezYRYI3C$(o)-p5Z@;>_)X-P7FFso|i;)H`!C+vxqZrX=vTrm@D<-@O+B!5dBkX9! z&aO^>PSfrEeU8mQim*P1CHb zIT^&x4yk@iA#i$f(^r?g97u9#G9-FfB19z{!Fsr_N>UQCpH4KNkA`jwTQ!-Ll+sGa z;HfhaKR1xnsGb%_FI+FEIA4K8=#cz-te(L-OvTaM!$(=i-Pr5Ap`-3*CMf8(;zT7; zsJN2haNuxSBQv>M&*UI}Ot^KZt+L~0ZY+JG@=nUp$fu3Evm>_&pSP{FxVp5XA=g0V zykn)MAt}t6nSE(yuBJn1!P3l3ivMO#c&R4P?5pnlP-zaTa%-ij<7O@)qNZ);$~p#9kU+79o;39^N{bVNIum0f<0O@X>Iv;SJ9~Zw zGdE!ilY=n>OBV+#eHSBbelHgr;b;HCj)B0WAk=z7N+c*%6Qin$F_~zp@yTqwrWz9; zHHo2#%0gv!^?5)Nl@z_nV6kd4;dJ=E`n9{{O=MiX1EZn9e55*k>r&CGIXkNO>d>D1 zQcJ_lN*~GMwKECit?Fb$5Oun`dPWwHue^-TRQ^C){McFkUH-s;oaK^#Xy)GC>M^6C zg@mHSq57>u3JJALd1RWZW~vIVhDt{{mydAzY-+qRN6Cs>I~8MPQzgEqhRWbvUz+*; zF{m;l8j6YPg1TcrfLN^_s%n2IaHV6AWPC?;>X){hMh#sfQyVFZrG~h@n}M|oOKCLx z)j__HX0OJQaD?LNyjG1Oy61w>WwU!n0aN?duh1EDiy<`fBk&@_;(L{_m zwCu=eD7>b6ylQGvTnD+exq-F}zn8Ft{8C@)+f9)B@n}%mYF^QJ`3=$zBeK9@Q3&v! zdLv`KqlLraAbP(6g~5Sw&~#1`wssO?a&~r%N7UrRSowqmRa+w)J2y*}gNwe-ihq*( zKIl?mdSP1abG-ot!);%EpK1|V3g&p^F}*VTc0DCDrS&r^D*dSWfqLF?8frb-WMvfv z)pUlo4m%~QtFVrYzDqWBHy1snqx{YU$x!|owxOAU@WESPU_6ASf{66Z*x;?L^yFxT zwwj#JY53qlV8;#n?Cp3m8EMhvw3t{9hJ{WmmpwoKLFJJ!3C65(8s%J+yBSISfoTSE za?!Bt_-KSEXK5x*0^sZW{X^|*Q~Shtd8OpgN<+(v3Q9&AJ2fTiFB+z<1}-AfKdEe% z*YV27Bd-2MDYP1~NgcUVoCLPN=j7I^gwx#XZ~EeiEDjO@hX;H608`_l z!X(-jW*%x&9|QH{{JQ~lchCsv;-u=9_lFcxE;hTpJT&SZJh*iqpLdW$Ng8Z#zt2I+ zY3iGi*(F+@Wrcd`_p&q9!twFt=^4^@pIPdAJR8Jd!28Wv^=-Gu#e62b?`^$%ZNifC z0krQa&8PSC%8IK~!|AO!_!QpzT6l`#z_P993Z=EB7ys^#dUOt$sjR0}-hoi?xnKU_ z+9NO5yz5e22s|83{cncKZXNg1JB;zbes~|R6Q}XQk*m4KsiO_=_oU)f?dh&p)!o^} zdfSitR2ujF4`^*sEId3IOs`kv<_OxRyY>3dgy8O^sXHj1nd^b)SIJ@)sjk-pHP6Qm z*N>WPp7RfZ=ji^M+BFWJTl0sN2Swgr)h$n6x79_#vO`tfjyg-9e;jXy=2x{3@tl2+ z);Bv89X7*tD@;1tX-%dzhpB|gICwvb*3e+D5m~2GJ&uD@T>m_6{^DsOEVb5CT=Pa{ zx2^K{=Du|gw-b!P-Tn4!)5@LwrR$UBZMvHM(A0~iA3yW;xZ+^eur5QFo$YInzh}Mq)rK{mwtD8Q8~<3?UDZd{>#%j! z2B)2Tt#y~P>U#6*@2csf;v`&lyN~VSndOQmFP`>^%q}}agY%@2;Z0uZhwX$a-b35U za_2(8-tW3*>LV-PAHVYLKV#qW$zHJXmnK zsLp78lPl}I-%rAcHja>_v20pj^IL8qE z!diqi6<3`fEHd+7VD^nbhDo6wwFrbN;Fj5e36?*e##|&VpprVeV1#_`QSH%C4l6|F zPJ1@!Y;mvQ+0UMR((kzZh3Wf*|73}XQ=|5-UZ4?$z}59k(rEzW&^@~kpIT0zI2VKG zo*@paD)*aCo<)pgU`MUb=Z0xj^h4r9Ae&G&Uab%AS~k{h3i=uS8TpyWJ@L(tO8}P? zJ`P;oxvHz=4M)m!`3E!@0|`kSb1<{;M=%%PL;UNg_ulfJ>R!qo?hW*f;|=4D;tleR zVd`z>$hqM}-YngwI1ioxiy@!#o(;TkeZo0YU~7U`#vkzuz17Y9Km1Jz zwz1ZGr+b!r6<>-MDjadRe6`Bs1|RDUT2yd-b=6Z|2B@!Ki)vJC6&-&#GAZON{@L(? z8Jnz3z=3e1(D56PQ=`Y7IP^y{|10n=_cV4>O(iv*NfTj5P}|``z1q->Ko%HDi7EFF zvCyIHy}L+?z&EDuc_|yx9D{V(zRL1N|{}$@kPHPwuIe38B4;h7>i&+$;fYy?o4A|o+u1U_b905-~v>o8n9>t z7ya_P{}eP4HCm)5s0xq~U?viEpp$vRIU(iqv-jo4)hnO)qP0R4n}s!wbPjt76@L0h&IlU|K;_u+6<^&E>{e;6<+DX2e6m zimdWy)ov8#y8JSQb!2rUr|^G~mLwSOF{Q5TYvl}a$1x|*BqkQetHu`X?HfU|2T?m? z>`RUs+#uD3cBE1flfj<}i<8m6hb?H0IC=r^UmNkH4gZcT$drsGaU8L_0iG)&&COI# zWE_QI$dV#5_LGa+1}&3^N|TBv71h@WQ4vo>9{tXsGnl8UF>|`-NobiUv8U$nJ(!MZ z3=dAEVAv8>_}z|8VcAZP=$fe1UIAAm_^|zzA3df|?f~a2tHlU{Lrn-A_AfmtoKRtQ z|1#)4d@q6r|5U?VGAXC@x*>1bv7;Un5y<_sn}VT~JA(5){JD%fLhBQ+fo1~;VIp|( zkVo=2)YU-C1~~;5wGW4dF6`eHQle^6vfMn>PgcXj#W1@&>93LHg^o9}SqWMni&B{v zt62tV^xL^HL;Cf4?;6cTB5+LH%leg4HWWL;vL@tx@Ot0gfGIA;UL-?sb(RnbKd!d; z(wcFf{UTsvqy-U?iu-`i&5G?t`WI>-IMc@=*#(60v&2xtoPrJO3tmMCOqf_W+niwx zqI*pEmt%rRaWg>S6(D03YexTsDUDz>Xd4&ouGnuUL~I*XlIy8DUSk*9skdR=ShtA% zh+JETa|fa|y>DUqZC_yivkNxH$z?&?;uDMoG-5ep=1ht6qlT|6{Nw%rYMj)GF9S0k ze7fE4I-nLNX|A#4lxzR!_~cju7Ah1fGzu!ToUWpa0%yZD*SB->azQp}={qr0%yTQ% ztb9>0qsY<7Xe&C%7%wuyTmL;*28aB0y$}sf=QjIB1HEqVV{K){QEY&|p2}TvR zvaeL0LwA8=i&OT+JfeHqH;~lE&D0MT9!3G%DKqxXqv=Vt`E$$1Ov*B>lJ6*MGQTfB zTdU+h8>N2_Ko{T#Lmai%eUH*)5q!8GQ4!OJP&TnO>$B@>HAbE?c0WVv4A#Nr6lM|3 zK98%4O_8CZA#W)pHy_J#G@Z(De86For5r*Q0ivN7ZrPOXWgOFDMlLzP?r6~ZWwL#j z8Sq#(<{RqzfHH;Kr_mK_}@pB52w z2S+EtuT(quj9*5ll>WaD=>HNs|JFPICU{xdp#IWL|9LSoGUESL{?+nVje+&ANiZ|B z{4eEyZ~5x+cPwT$Cj9@De??*WB1FHkf_&+qf7MvNI8@fJn13CAMWOqv&tK91)r0Qu zK6HOa`n%`9NBwh#|J439>c1oWtA*k3$aG&EDFZ$mBO}ybt^X->f6wl(F@MeL@7BN1 z;Gd}fkJ`UKtG`D5H(UJoa{Na*{b!Z`S+IXC;J-ZA|HI<`O}hTIN`FbJ|2AFOnd$MV znb^McSSBXsFG7~#E1k;!4RvMx;#2=YT^YZQ{y|+?zewGGqps|1|ER9a|FK@h@Y$IE z%XejB`T}DA@m>G=oc`N){a4D8|MFe`YWUC0|Kq#4Q`YX!+Cw*b3 zr@NPuaFgBQy65JyQ%U>$G4-o}fBn~rNvIY;wFr}N1|nc`t) zxs6U&KBBoCWxo9RLYm|u;j^OJPXuqDhn+OZ-Ig*8f=uT2qE)QnRk{V*^meC>9X1-S z@Yp$S+u5<~Luz1wkI7ps)2XoKf{fV1=@4jpY_{HnF<4nSccvCZrs2EO=}>$De48YoI%X9-eQQ%-gTC5VQ(tquX%gsvBVhDbE&^1kwO9V;_8KH4J0VPO-;?qC?My%ohU7 zxq4&gT)!1|K?{m;*MW4Vk9}uAq?12nKlJIl)xB`fP62`&u7DHXibl>p{1d^ohTMLY zZI~_kM;krcoh`e{uD^hcD}soV+p%u{g`Ts$w11c@NRC%s$^8b}E1T;PRo0|bvgc<> z`>>lro$sl5F!(kLZ3h!RCKt`4%QQl%gi}gL@VCs~kSm=;|3_Tt$eYYyLZ`>45wYGW znz#C021YlI=nq^FJN0hq`%G# zlm-6}2;j}29A1^3?WwK)((fw{Pc1!=R%kvzGz_L!h|fE53BW{hz(^C?wbOiV^bD@s z{aGFg{(X=#H1^t0BiBzwMEM~EBqG%_iiI$cg`s`GK_Yo@Z+vJWENYq(XCy=V!F}O% zpVVmt%Xh_PpRdEw>o}aEvZbeNd)1dC1VO3oU5_rFw%fjw8LE8BhUOM0N7s}w%~aZS z%^kD4JpH;G5Of8*AIZ-T(M#$&m$RUf;z7*;a8s$wo;;(bEG|^{tjW$)S1Il>O(WB= zrP-3@ns3IUvwv>FoJ9}Aql||&29g~m^cH?<_4Pbv4H&KZP}m_Ke5HHS6~d z!5S9%%1z^%FvT=s3#-(3s9LG#o^OgFi(FX(oIJ)eL_9hBkU2!6Gc=aBv($B$g5Y}w z>rg|vL+;MhQA{-B5=Mn^0}b%Ld5JlgE1XeyA|4kF)^^Ve)0LJ$$SH`^bA;gXdCGI{ z%#GI8vlzL)whdmVN=6COS+M8PWRFXWH zoW*3udx*%3x6)Y{G3i=4y;z3;c;}-o;52 zTbFcZz*5UV0p$^rBk`)3L2AHYvxCYK{p8!+{YB1MRg!TGUE8tpiI0j2+eyrAE<}B` z{(aMWri3xIU)}9{^`PZdfg89_ghU>xyz_$g!uo=8TX0vFj(GRrpHXbX=DK$Fq&w*| zsWXE!93w#+CoGNVC4oyFe%t)hBXFtyb}hD_5q3Ya!8TPoQaFMhcNLYWc|tY|;kJ3V zrmt0>zy=j8#srEKCKp^z=)U%?aJGeQ@bij%`h5gr3@M!XJV4X*_!3XXH;HvepbmbZ zzrrb1{`8__C@KY$7G=z9mYl_Rg1_5=@LJPf_{uMGr2PEK?viJ7hhqn%Pvo+Ltp&S@ z$px4mlzxKr!tA0QZ}5`r<&%RN<69+1WA;lIrY_bfb1hZj@RP|ComD(`dD6+>EV7+p zMNg)u2NcI+gf%flq;X$y_h1`E)7#brozXP~XH7KKX|7b=Sv@ek(ljTp4dLu|?R0@P zvIXn**#^zJqZ&P=;E(hApl8A?9OiP)SZM{D=4H`gzFtc$fXy+3+k*K}3va7|bS769 z*70HLi131#uLmsUQs14M`JQ>dAb7wN8zXkqp>mHW60){KiyZ2xl_+|28xWHq!GVH| zeh}xNDRoiy9@nf@0_sQ2W-J#diUhXUlko%qp{3AyX^(paCm)Vum#WFroJpSOWRc8DWKwp%|Y_R8M|Z3XA>$U zq`lxHGN}dvjSz|D9OKOVsJnp+!5fnk1s^k=IxfXgRnG|m8=SkoDMCgr!N@ zDU|U7`~b-btk=W_)avd#ZAbENIo)MH);k1#Gp%olNDjM}0(wKhwjq7GCpnurpU4ztu5}Q-;S=U4Vl)Wk&o|z=gH5CE}We^1CSm_x_!>K~{ z7){j$kl76R*BL^EDCz`CoNj+$Sica^DcE&yTw1?^shnbbTy#HlGt?hKq0RUPh>>6% z@u(m7FnW$t8`Z+_{W@HGza4#Q8Zm@w+0^kF2kn8hgqXxJQR}fh^}^ZkX!*8e^!tdW zu(XOZ{JQCd277HLXzWi(k4RC8Y`_TZ3=jUXxgEhEcu^#iEog%lztP~@fi)I; z$)x6X7JT2p_dRS1%(as*{}B1)r>q%a1Njo!mlJq;8q(v*FzUI5*wR^ryHS&S2pc<| z!cbtRsDepV>{QcaqoplssV)$rrUGB^ZO5~^sd^V%%*LDhPtv;R54n!w(G5XIxS7l> z;QQ9==AY+tP`^rTEr~8Oq&)!b`2?2h;z0&$YKMCN_K2YG`pT)6hP6`_ELL&SQ z2>Z74K3%bKmty)!zPcOWt@G{K<*FpIYrWv@T!rTJZP(=tY~S!myxO+_o6(SASHE@d z+9~tG#k@UY<1UJ_BCunY;*dDHP56fPFY*TUGxLV^8@`gC4{vMax>IdmwS02I#as?= zLw-d^emw#sBm-(hHinb^fVX!Wlijvkm))`R#w&Vf<3cs7Cd2Nkis?5H0B=)Tz#1HU(G-B=X`%j8V2I&CfOQ zDH)OW9$Qba8fqPJx>2 zLS{UAAYRH~QwmBzm|mAr8TN{zta7NB z9T2<%BnsVmC9}(E`V-4%A`j9JoYj%-10`3kSFeE-dCG3WPYMJSE)-Lgi({bW{N>0e zD$;6<>W<9^ZA~hk;;cf;gBkX?_L%mdrJi6R z!28E-kV+Sr)Lr(7!6KuY1oRm-u4aZaKG~z|Gx}&PgyS<9-oZuO=X440o@;we1urb5 zpDwOX$!4zGx-KWOCTk0mkgTew?yv`Jm@q#x+L5C}9UOxnW|W%qPFG^5)O+s}p~eAM zl;<76yhh&*3F3+SCi1+$$RCeWTB31#*o~=Sf84rY#~%Lx@v!2Hf!vR<==~`L$PK|L zU_^|^zk?+H@jYbqMpk!p8sAQc+`auZLGy?X1N;!{E)PE|Bh)%em~7vA8K?WL8Lqj%cfMTQC&BRx{;|A^Jj5`kDBA;?w-2#Z7^= zVg3VoPC;>get`p-bmDu{91!Abm0;Ym&mDQW`ZIb3)2X)TLeB~00jnmHMT3is#g$1P z#Nw725*l_oYkuu9T&>*oC!j8mXre{SMKPa}FKeczcC+^`TG#z(o7>mR_HlR7ccY?M zIz-<62K_Hb7k#by>H2QW{g*~@bqf3(&L3H31flcyo4}U0!P~v9VBOnq zzaG9fXBBi?GcMviZNt52K5G+B#0fnd=HkGGGCxa!G6rcMbrIPs?|5{CAt?lwMF&MM zMlV*Q;ZRBRaSRnXKe?rV?2K26mPj)ExRt70uJ21Jd|2;CQ%fN>7i@FR_AlI%@Xc&p zZol7j(&Z-^oZX4H38->+bpOWe7Qimzl##ek8lYz5#En8$D}qz>agU1q?A)3fs-qY%}weWhtW!mX_dj z42AviaGQimYm=r-H!N;xD3x?|pg%YpSu4*yVllteg~OcvD|O#YTKf zg0(k1dcnVX)NzDSmL0o+o|e@`SVx$(hA~hOq*TPcSee&7&2ngtueOCY8O-(0jVbLS zpu;eJXl!}LDQFx_6MA!+2#O&|E<4a34JY54#NKRI^y;B?_4CJaf$IIbM;~4vRvO83 zntC+8LJhww{*Ms?j!1Nk5nz{=w`@8GurvJ$J=~QfNb!7HAU8l@p)C6Spb+MA6-f3r zSn$|*qyO3d0LJjOdl(z*A%F#r&?+z##twnB9pkz7J|bmdJ3L`6+tP0)Ab?=jS`VD}qq2~EwPWd%i=Vh_% ze%En5yP&E&iCB+v#K!#0Fg2yBh9V15u_7{qTPd%tk75;56dYQ7E?y?tmLYSeM)??1D$Or;-mi%rq_o+n*YR(^?ax^23%QpR-O29E*tHxqo6%3hSL9&gpDR$gjxG2>uMWKcjm;kf#zLE(pKG~n~5Co6ApwZf5wlf|7ih{e=uYU6xH z35s2SPZHEY$sJ4(Gb3f>_stxW63}-Jmh1(9P_hveD5RXvtX3?0DZ?Y6=%zsCnC48r z;RgM%$f%`5gtDr(IHO-Is~py_Nd6nWt6-m7DP5D%N}pH)Fyy5{f9iw4T#2-iG!ot} zE~>!LteYf;UljvHF`rgg&v(DFEm?_R%Yd>H)}{?t+uNzuj2!j`{dGl7+!P%t4A1kd zO>cETWz}>RjdnZLyZ$|e#veP+^Pwn3tQ64*7VD1Byz@sI@9^I#8f$HrC*bh5nXzfO zqZ##=m3Qxlmz$0h8541FwT~DeM`jG7a1j`AEJ?7M6)hYtJne(EtF3Egr3h}i+N*PD0JCous(s98!8AbWDmt1 zvmq3qZc=C-euLTTzMVTU6S+K6hdoKZRbE3igk4dHXhIIKV)YaJg51tBKJu-+P*1xX zQTwg<1tle5YKl$2o(`0LQF<>{659q(whDmML|O6Ip6F*CKT5Ho$}8U9bdqQ<%*uLV zM(#&~2I)%m?+HwRNW*#xL&A(H(u-C=L%xLyzi{r0(JZo`}al{_xf!PF~96@Zjl8GZCZxk$x9rBKFCae1~3;tz&RRN7}g;tJni0so4B5 z2ewZ9KMK3*u&B1~O-M*Lf^;_%#0-t}kkTLxLkL56D;)}oNQX!YNJ@8zAT1&xsWeD8 z$Zyc==e^$V_k8D>fA)LUS!b`k_L*nx=e+OP%``Y7FA9><4vxMzYtM_Fm@mJ3#CnjD zw$$Hw5-Lzf%HO7%p(!zf(b(1rZzH_>kdjjVI2uDsPzxWo5F-^MTxZN!A}}|n}ze`{!!06$BW{8Eqbk|6wo|M1-)ri5)l(N&~FL#}~(!+iS#ZnR9h2?NMi%0y)%!{=(RIk3?l}bcK+CX z92ZsXCmlt3VJNP))yDcBpKD*%%Iswux1xa(sZ4EP(MuIE=TeyEEZFm&Z2QZeB8SVO z2kW=XH0X{T3bcI{M{8t0>^!+-UM6C|(dL-CNghqdRTnl<^z@$YtA-si+tV*}x_!JM ztlzJMSDgx+KKo}h&*@i>N1N*iMNFNz{R~HtfI5a5I1EA=A zo3aWZn)PI_&$VWD>22TYAPR7BGN9mgU>lo$%#v~#ewR=<+~9d=^$mK>Ml=)W@v)nI zG%P0!3q%PaoT+eaM^yq%?-QDS&3GbOyc$^C8?*!z6^osb$T;3Kc6n2^%HE_E@QFtE0)|hAtZx$`q-NMYbK3*l@aDe0N#r z$iZDw@G^o}+s{4ybEf1GYV)lr@C!|#QaiNH=atT9zUbz(b{q`LT!Al^L)^>(KU~I4h<^zjhjQbpethkbQ8N!WxcjxOzvocTj`a9t2*6b#2>}o@P zYbTVds$OMAVv7Qo6i>9Ug#a%fU{b(i*knhvnL2T*6MD2!9-`8u52T=QAyRozcL(p> z3MFG8yW?xOD<1fy!PAXK_TKjq0?^HEOD(Hf^!bLJQ6pwY61`b%2=%d+^>9jXi)8SI>%#6A>!(j8@!z1Oz7V`^93m@ zt0MW~echqQw*up?ggp*7>2n&AiWoO1Z)>HXOU9aI*1OyuR#+w+A)k{rxCsnRu`o$! z=&jRi?t7=5veCakP~4Bl&q96R%R0UuiFp@?%tjlGQw2?PG4#OEprhDm)u6juN!0BT zAt51dCHj#CxgC)$R5IBj{TE_mFFnS6V9Q&z$B8OK@-38HM0v4BiH%}zXHS8Fp9%7(!@NkRJV#L z+jGjLZL@sx_|)@&w7o8KlaCXVvCH*>h0kyI1c%mL>ZGW??tAGfVzQO0{_YePVg~S( zx;?XbvdO8vh518fZtZLn$K@sQ+PxD08yl;4RyP>pU-)N7$Ph-u2^RvANp@vb41g_Z z&Cx|Z{r;X{8PN{y;0Zhql*+D$bT6RPiqZ%dGEc>cCDbd6qg7- zzGC#MA}JMt&2J|_cVXj-CW~d`7d^smAq}I@UDvsJUyq{}HkYfPy@HGJ z(omZH>rO9Dt;rT2EDyva#~xFdlm0CD?oic3?q^nR9t%RZaB3q6>%rR3MAdcrDJdKK z{aKdGD&6$&bP2*Jxt#H6k4R=QI$UtJWyKB88cGVvWQUF)R zsBWkD^kLzm{W(i0Eoyq%KBFI!gID|skFk?QAbF3mV0szdkKidCt!fDzfP8PClRl}G&8?+nRe9?k-S`ac&uMY` zh%P6wBz=^no`Enh$1Nnq=d^1NCo8tt+1A~L`1$Hh-`4sdPvlz43=YsF#l)Fh|6S}mR2xssF zh~sAW-?Mtt8$-{3{-v$`bDeOGLcQ4Gx0M>t%e^;4aeY%4??%sQwxUe4PA>^3PHJL` z*1VmL0=2%uZJ-B5m5$n$OSH#P6T&{b|4DDs?N>)MLbXL~(|%yv1sUu2{4_{)l+kG>IY;IZ25Fh(%n@}2g|W*qEUC7(?8 z7KJ^ObSY-6dJ&h^OcCawsNFV8q}*A--w#U1q6mCBn=8CQrADg=QzT&Gcg1qaxo7?* zL=irM$rw8Cbv93e8)b&|T_zV4x#(z;KETkyS;V=qQ;At!g8Gn2$U@_MkyyCH7El45 z{3cbePmttX?SFWzZv?jkzC_7gg3RlmY%#pD+~0{S4OGm`16Q1Mqgh0Mi-l@mkS zeCYy?BZa179xoVMD_0j{4U_2HF|ktfv~gY+)*XA_W{W5`R|$v79SGhcCEWaGm7QSW z(c+T}(7ek&#w}Ewr3_gOb`3VC{K2-e#(>3c7?6Z?0k>#)Ve!G%P2s?(7(kggXhUHG;#z}lzcn<+A!HtwFuO*PXwUE&Fa@4OiqR?M(Ktl=JvWZ1;? zGy}yhTG^7jP<#HHwL5pP^I?gWmG?7YTZ9}Lj;%6Ez?$G8gquBt&LZPA3PLmd1#>ud zsQeDlCN%vx9C16HIJn&-cOqxYa5w;N*6|$c6W;~ab@+xQdGW8i4x0q7QbCk+JkHOi@&tA<3732B01t%uRt@?{L=iZ~OK0dCf|tk>ksRj+=Wy{wsmC|;aq0ub6Lb`eQeT+PU`DbhKGqJJv=x^@TZ>uVViU@8+1KbwD_jgJxLLW{ZUH<~GpO_R2z+kQh>% zq1X6`3v1h1zc79^zkiCR=cA3nUs?LVVe^sC6Ne8pM-6PCOnyjg@$q;1+~_Iib`T*dHtL;rprD`o;CDg%iHBCe4hGl^RlV`W+R z+UXKnbivwvwnLOo=aVM#L?V_gWpEC6VZ<0<#SWXbFXric4TWr++YgF%$pZjzzgUKrjgg8MDDC} zkDFV2w1;|vjF+>B4@xhtuKW5VJYFmwtX~<;e(sj0;}Iu(itW6vnK|=2}oGaA|^9B!V=J5_?w26f$Bj5P#>7B z<6hG|><~5pL&UT~>!HImV)5R90ol%{J^5fNwjB~u2fjwunRMduqSR0`21zN5rvfmx zk5*T2-Xj*NyxwMN>#&s#uXEDD&p;V;jUVYM@o}+EH6~I@4?_<+H8?t-BnFf?Wnhw% zm`dUtYB0_4_J@+?(@y7YNLXx>P&zu3-8jJ34v97isu#C*_nMaV5_|!kgXM#rIiW3JBkuHAemZ_FC z0`-#cD%2o!C0ZI$g%SqV8O@DisBW;|>M*_epfbeGlMsLAbpH9m0DZ<;PY3ZBqYz}X zqF!}rA+^zj6LB{Gp^R_ugynTcsvx`%vD9m}z>*hhRC}I>&{`oJC@LZ5)}&$cvNk+@ zN!W7QF0t;XPwG%n#(^P9Ufp>@DM;1lW;n6ION<`-W?0_MFt7dQI<;D}LcE;)$Ov7e z>umL%gUx&=lQ=;t1cw-Zg!-brJloyTkwwRVgXm48P7yM%Lf_35v&{CaB)^@mg-&VZ z8n%&5Dq=&?!-a^+qEXT5mrEFIuNCM>}7hOB5d z&8NmoG07{l$-swqfj68VfHzu_`p_~WIIgmNrdyNa)$Z7gbnJ#$)1;rd!Ti4Lk;-VX zNeBhv9!k)pv=i0J93-i*Jv=n*=jf&cge|`~9rO34tBsoMmxv+IM7v0Pz-1#}aXW=~ zQ*N1rI~H$_ij5duPx>Jlx2 zqu=q_eWggMK3+1rstr+|I-U($imhytAP<~(dT2LQ-k;mnHFt4~eQ^wTG{ofkztvj{m$b~wXRwD#^5exS2a=T;BX85gBEJ?m%PFXRYzs1e2c%9iMGK}NKuzj1kg*c zyvgS6g4KfeQJm0?Q0oZr%zl`Jp!A`zq4lHMV(Js_aI}3u$v{~_oyDv}bEZx1L`g<{ zii(N)3{~YuGWsxHIoE z`K|F4bD7ulnP8M5+Ta!ZHuIOcbNeA!^BCyP5Z;OH?~AA>!>A|asNQQRG~QF&0ZZsR z(Wu@_C{6cKB#=LA6caE?8EtUq$L~t4M1o>&S6y`5-Ku9Db5Be-lk{K-WxLB>7U? zNypL7(#Z)HB9XuGfx&;{10xB(f1?8n0{%&C{X2d67rhhu%b$Zg+!g89!Q34# z3;%I1Br(*@-4$+*!0|>kj&FDDWFV5=_V1=kkhyV0#i&!nbUG~bDuJ-Aye9s>l)eAX z9A#tzOnmb}iVuKC(rY`z>*h(~!!=<0Y7?tb2Mp7^t=DI~+AKrqyy(95_>*0{11SI_bQ-T3V8t-pPF!GYWQG$hj zaesA@UFO$UgxlHJy5k5So%2h3+Wg>#GYATU{>}piT(icn*~v&2FC4^xq!?e%soy-{ zAHc6j|C%UZ;LnNjvk7DXLxirw`Cl~PBtLiZkK}J#!EP&TQt!}-LT}Z7A|if@js3iq zB{jF*EVjwFOcOgk)GSI24Lk3dS?(R8uu)Bz7S5QavazpR^b4o>Ly2)c&AjQTxWurD zXPv!LVsT|4i#CS6MQYAe(9NJEC_Rtf+re7Lr^LVNkdlWhu3I(oV;N7fX)}bH-h4k` z?`@qQN%*S}#7^1yT584)}lq@BHoV#3g`(0Di_7|@Yh7ZTZ zKW%)ueL1~$rZbDF-&5RbGDMSK^X+ug;bQ$L^3hbMos>~NG#HW)s+O`Guhec8+oOml z1033xrU4ExF(OnbKN#beIyiBlmYIPm zD%KuU+&8Ycxep{iuI7$9@x@}j2^MkBij5NHfSCDqM0E9Iet^cex_%q*sYj?i+8xIE zbRtX1Z6{j!2wS;2s&vt#LheH4Lfe7jirIuzlDI5duPd%QD26`jiiAJrii|(%YQD7b zq;ZpQ7qxGGLB?m?)8+2b`69-y)1u#^Y4`pjba!acU{`&SzFRV~m2xO@dtNEGqSh;Z zFmU$i5e0%iko#OaRu{^7uDV<2ji+F+AzV2}6c??~Wy*bQ+WS4vTi=0%Fbb>NG_ov4 zl9F&yPPDSHzuuNe%mBGmcc8kQ3$Wp1q%aO5;AcmyJ4 z?BDef-`;Y_2eF((*Ce&K8*?{f-_(+R(Z63XRRwK0d9aR9;M>}Evo;zlJ~|$o7Mh$R zubuLU-8Q>XFV|Pw?Nk&t5FM!XIaflM>x@SNerls_9g?FSvmsdE!BwSZ6eFtdikMbt z`c#nXFJnY{Pt^XTu%Xg;%r$ol`_n7g(q&`_x^5SPpi09hA8oDd1@*%UiY6nKr-)6u zBLeUQZ@VaocIZ~97YB&6vb}E8)44AqF#YUF)53RXEv}oJ_mELL?(g1mEU;$gvvaG8jwvft%Y!KJP};B|my7;5Cx;YoET%KCr&)Fo|m9EhDmr7@#hzdglndh5opJQn59mLMD zpPK;n`bTDB69VEOx-`s>DHNiZUFfT58U5-YDl}ZPtOV_V=Ttm?@!kc=yw=G5msBRv zyHOWuSBG@gTs}^oR@S^PDal|wk|Ei0&wX0!(%py+BQ(R=YT*hhekL$k8(CC8;xVl7 za`;}rT#06LSLUKBkj<^hcLzPaUCdW;8aVxW3Xj@YvyT@5O2Ii+~1_ zJa=-^E_4lmZ@ zec|Bmy1s8_FCnou^@k!`;<3Kgb)%-QCIY?6s9?q8q81L5rFv@atAV}5T2c}Qs!EL0B0!J{F}q+dO#ZF2cv`;yl8 zy!U(x751CzS;pVaNth=)dGFlY=#V~GUVpA>-?ypf@_2)!DGG1dv1#tnL{3Um1w=h z?3VrpEGsWG=4~O#86Vs6S$Z&-IHKH*>1=K7xo@6oHamAUvMyS8Dfm;Ztz7Bt_FL3mLGYJ5NRetB8ExDfUG)8Y4T#Yi0i2z%=Iq@&cC%l_m+ zXMbIWcu8S?3)q@_Uk(7ESnQ^o9qdD`gYkW-)C}PEm$i6{cXxyTfHS>_Gv0$Au&Nd0P1nVHlI3PtlX~ zCg=NrTkqloo`*6$@+oR}PR?tnvFVH5dMuvm#^m-*Bz`y7mYXIdeGI$9!=q+E>BWIr zZvJb&H;<2r_iqnRNCQ?mzIKITP6$CrPVw{eLm%xvrBiux#}^>}P7Jv_Z^G8Z3iyK= zWZDajoPZJ|ZuJT-g%%_e*tpWbd$Ir}Q@&H!-1sUZxX;ZE*Jd}+r_IqM3&>i?|vK+;>7FKZSNL`hq^S|1t z8JY;%e;2!;)C(4H`*&sbqYn8|nE`?SslAbEtDof>hcled*~*&pSIzcA`gU#2fiSmJ z*J99xySmvqIU-9gKA-@fAcGOd9S=JPD+VA$9tZ{*aWdTXFn4wLWzdk7mqFG?aBuhD zuC7&jKU`_J!aeQaUcb-$l1*{Qihuw>C;$osfIxx(5X2AwU`PIbTmD)(aQud@OZ;oM z_ZWNhx`xEWkfpz!y94}M^!KCe*Kl>R@~}h}>OTTQt^;I{^|`wfvi+Ba@JAaN zp)9hDX8>P!3~8k5WOd!f`PEj2`*=CITDdWR{}OjeOKYfz{6>GSI)2xK-mY+Kq*xA& zR2Tl|U=R`%MEbL4_=yRCu4~L6XBiy-!T=y4C{lWOef-7*A=mo4e_{aSaQ%sagoOWf zEl3!O?AkxC6%>Xbmo@*uKoH>d@caY&+4?62h9Z0Yr=1{F@L%@;K?VQ32LKEJ{3{MH zK=5C22nt`zCI8tMK`7u~n2-PnS%&}9P6&V$`TdCrTnilkuoD9Q+fE3%`uo!kf)sQ9 z6GM&_Qo#8q_HTb62t?@5dmzUT@aH&#p-=#FQe7Ya$vGG~e1FCZh9VvQVJ83p3jEn; z0T5W=&psnDp+ED6#GwDaR^Y$b2|)jh7dZ?5HD8d}-*f5iYK~kgx&C+}wd{P6j}}sW zsp;h8&H()D5mIurc4GKzjie;YaF0O@0+vMl^-OU~Or}X0?6aWbWg>YC|<<#YI{tw1{{saI3 literal 0 HcmV?d00001 diff --git a/examples/gjf/molecular_dynamics_results/guaiacol_potential_energy_fluctuations.pdf b/examples/gjf/molecular_dynamics_results/guaiacol_potential_energy_fluctuations.pdf new file mode 100644 index 0000000000000000000000000000000000000000..a9d9badf72899b7ea1ebbe931a4855435656e36b GIT binary patch literal 43267 zcma%>V|b;{*5<-;@X4?K8G0}qz!E8 zDOEYEWQ+XwHpd+*Lx3W^5v7oLZ3?STjLki8>(nn;H?f%Zg4*HC%$W$0yqE0YuF{Ly zs*z0{8flV~SsS!tonwD@J8!GGiG|~SiC0gL3d zu-AaO{eowq4h880^x2Q0-BFdXGPx@4M&NWM2q)~jwCGAI}sy~ok*p68&V1?R+tLotE zRPr3ugBCz+^bQhUb(z_NAhQNN^~96=IYnS>jP4uFEqaoP_bnIJh)+tF_CZH|9B|@j zRDYNW^93`${OVC_`We+|J=$*l^B|AN8N?y>120XbFBf8vJE=A0R`(Rgd7*`z+sdB3 z+^j8Jxr&=WTYJ=A-&;hJ9jjh}#6s{Yf$%%lsnl0)!DEV6(rELRT^23D-;DV9xF=)q z=oH7Xj{KIPiLYRIj*iKN28>*Xk!r2-;i%L(NZS~CT$8sz1{OppOnGYOL{*fdhs9qL z(+$7GDYE?1^@H@QBw66z6pcOkVw}>QYeYL-Ydl4AMn*ddi%RV;#9QfrbIPd zEhMqoIXcs*O;e{uwO>EF2w@Uk78?K*HqY9zoJ#QsEF!e_^WK};$(DLyH~bM9G_gzleKPMT%78+Ox%w8ACzW_9Ee^ zMPOP(RqZjGNbIuPR;QTF@&))<5W@ycr{NrvFu1@;MD#?Y2|~vVL*R^5x#h)}rUz1-UG9@Pi^G|Cmj5I2mDe~h;#!#He`YTuW z?ZB4N2kzkp?Zqewko(8Df<`J`>vG|mRLI8**UH+qGhxE&9jK~yuMwAF-Vj(7nQaUH z(Bw-6A3RAPCn{KarQNgSNX|&lE^}%(fBMo zuSBK}HM2O8ntEoe)uFwk>%OkPRk2oiBA}Wi(3-q4a6_Pp>nhih=>ObtRUY-;h>l9j>^ddrNWxQUi6mv7EFCKQOieMbe zv=?Q`w!#L*=>6Tz8R{Q4>F=g{_Qsdf&cXm;U`NmUeD1S_Mhe=Tcpu~O%FRdMlwMj2 zY)^TfV|~Q>jf|WJp?-)zM?aG-*@*4TFf;0obo1d8hTud^u(!G`5o$TI@?z!4OD@lm% z=|tu0EIu-zISo*k(*JmGi^?8mt{~4Cf-~JhxEtuGl)KLJcu9guCp5^!pMkc=r zIDG9ux~zK%v@pgl0*wYenz?*}-==Km^mY8oWO`-9^f`rb zVde-v$aLLC#fiY7Ro|U^J+0`ru8^btSK&Z&c|c#%&vle%Osmyt4UjPIY@~*qrmsAQ zR)g@*%jqy3XRcFmJ~>t4c(;kKVVygH>)*5=E$SD?OIk$hP@HHF>15V~_!-uk<-?6z zs?v+0xDKgv0=wwlFBh1dtyoSjD(njS#;l8-67^&rzsL=;v!Z z>aG{Mea~J6_R1|;8ri1(1>fr98D@4N^ToF9f(ZW6%a8w_uS zoO5>D?|8OsL>5G^Z-Iw(tdnO}R30LEJIsi0lY#`##L^tXHZZA#RW=x6UaQEp+szP1 zc_G{;Nl5o0kZ)347Mzv8?lh~NYxrj>U9NMvepM8^ zAgDAKZuLsVOH>x2KTl$tVr|Zl1zsWTeOw~>$Pz=);!$W zjlKt|*{16*tWB2zYErT)2ko)Bz{wNgP>#cWFasOazZBfM%7PpZI!8==yzIZFHQ@nx zdaonS%IsQ5kx^cQ$Gbv3R%Ez!nxzN`?T+k+*qW_Qi9Q$)!lY}ot`gwqa02XDq7*U! zC($?a+e*Cp_I6#GWIWoUD6HC#64?P3pm5IIS5KvALD+iCdTX8?Qx|CrQLH*~a;t$; zc~-(%o}EEzQPVhY-d88U3|THc*6IF0aRkPm>wINvJ2FMiS2wrp3LNC*Z6UIbw9t*$ zsPHmX3_0t@$9P<7#N*NPUQ8TwY>>b@y|Cs6EowVw|}4igD@4{Y>n^%vU(Nh!Y^)tW-#g&{A=FPCl`=9k)8n^s#n+(yG_bJI<1^FIYe9b!>A&LqsrPS^ zm9@7qP%v`D*Z2%3D2xwKG;(#s*TM$~*jU=wE7e3rk>b93VZgj^j( z6dXTc_wPFq2Rdjv`hQ}JIMCzM{nODuj>4Z^`^Se4pN{Sy7ez%neAa(IGT_tw>7@K8 zFaJU2e|7M0Yya-yKQr;aLIM<|@M&pi>HpLJPsIP$Uq)66pYA`s|1Ts@_b-%}{+wk1 z-yfW}{xdv)ppmngfswoj|NoovGZI}C6_!wgCpuUKZ|Ipj%E*Xm2gt0_viI>1I9kZBT7v z>7Z$0$>hRop%qB>)eo%4Q5EA zTq!BVq62mJ=QKYI+g7N$WJw+7KYU^cSp`v8qV0jiE7bL4(0_o9+$Mad z52B+-&4J1-C*0|)vb-Ax569Oko$|$73t|jCSQ1_+J@z6IiLd-=$=?T4X3U%K?$hd>I?7QR=Lat zKF~EdQ2l!P4Q`O7c5L4^EE!DL>8YgyaFzuPZ?R}kAn%INuvGDjgAk1vrJ z3WJf*USUz8gy8Sruy9EehHnoDA3ML;%*KX$snWB4pV{} zMA5syA3Wp1X#TX`lH?;)*uRI3GPEbjrNYSD2(au1`4$b~m<`S7OG67nrTZ282ZJr> zIzCXq4^afrL{J)05Hnt|T0ZVYAZR|iMPO%tb6cQUU-wBcX+LJ$FPdN~zrNbS!2S^7 zg%0YLpaov{HG}lKL_o>qD~(3Yhfm?3N5E2tbQ9o{Wkm+<7YL0;h~<5nBrQg#@Gs2~ zkmb51a>Q(f)bfAMhM2@>{PG6u6@ZuwGNbo(5vcLUQZ)xQq)5-`rl2cIIt1FUl`ZjR zRBpJY9<(j2OCYL1ot`*I-XTcPDPdJetSdqOXjNihL;{N#!hDbtq10%&e5{rT(HOg3 z&@aI`ddcXh0~kBOYT;Y@%6jwq;J<_ax|q_QCeS-H5^)=pu`TQU|l}gC|JDC$=P3M8JeRfP4!;>|vDiEtYX43_@`0 z)71Z76S>IOE{07i9fvFyM2sd+{5_@KS5eHIP>Ym{w1XgSnB7ps9$k%BTc(mY3txu> zK9)x|o}3g}MjTs+e@U86yoJ||*G-^6{%f)ItZHd;YlgZ^hoG0Z7eFMAA?YS*XSgD+ zEXE??B*}wBCVnBwB}s=Si%f^WNBq6;wHZXNo3~rRH?LYbM|i8ghbvG_C^a`hKSV!O zKUCj;o2g%pq&?O*w&|Np3GY$$G)VygCjU%<+jMiiR6YB$(K0QL2uuFUOx#ibE#6_r zEtC<7k;WeR9`+vQUfqcNmmXT(M+SL}g7CQTw(zJM#{HIworx9ZDl_em_U{Q#6xI}; z34{s83BU&B6^Vrev3_?k4E6kPaaBmk-aohrGD9B#R+ zimd!DkuD9NkzbSe%erBFY2C#+KXbbDGWGJd42Vi&%BCpt)blt7SPdHOeqM3!XpmNi zW{Aa#MGQ+REY7Yg>b6eQPrzF2o02k?F|`fmRT7t-f-?Z^WsR= zs$N5FlWv>1hr1_yA$_5P;0ksP?tpt(baW+{zT{zgO(J;bbQ^l-oQ6R&vF>!)zG1IqbfPj^ zr(4aA0v8JpX9M9Q6sf0VPqOk>r^RItY$2{K_$BsWfbt;XO6$?+H3lpxpf+GiFsV-~ z)Ih9K3`J}QM24?n)2UYH+IP1kJ~}?{J44A-$(UI{{bT(MKZ)MYYDz5zF0u|lFJm69 zKrtHH zo8cF4CSxWSCzDR+_n_BqrgICpiop3w&6O5u7p?Brt-H>XC@Xv`(WT2#;n4^qtPSg* z>$7s%a@C!>rgazl1N<%ga$6nL;~H?5{gx<}XKTiF73M2RgxXVg`lH)Fw`E9HV^22J zyi}gne%}Y2brjqeytr&SL%OW49kt%5rs%6_FHKf%YE|t0zRtaFYEwDwRMyk5(}g#S zGK{LHFRtwnuQC^zD>}|U_Qi}!-S0T|XgbSS9$Z=I+OYDO0geFehv3FV#%}i+dXTlK z;Ir!2Tiq(}ojA!oZtXJh(eV*H6TOO=5D64180?91n&X&VU@2yaXYPrJ9jMu{8?<@b zyc6(1Dm#*8$ZL57VH_Dom?_# z8H&tOo{G1*#|7h(j@#4h1>K3d5R<5&W&yxQ!c&z@FZe{s1f_7j@UcjR$VB*4_?mmo zZU5zHc+$*HVAuEe#)pKdvMg_xmktyC;l4|Ysgo2Q@%7?Pw&(eKs{_Ns-5D3Ni^8Ix z>t&rh_r7mAF9x@RF-NB|k1`2a5j-xQP_Ngnq*liJ8xH|DFaK2){Ke3}Qs5KW|4qYx zxciUo6Vb&41o-tFj12MV{$YKsfBXDb0RAH#9R52o@Q3f6KGB>GA0T07=6Xh8%1jQO9Ige61;`GqMJ+^qC% zEI-wXjgqz5-}835eaGjE~uaRr^C>SjB^t#Y4xwz&MckSr1KUSZhy}_Q}^GSp49;knnU=o ztk3w7WYz1tSvnOdVq^pu=L>8*v*2hsR^UH8O$^8Dd(MXkfbqo75~yO~iB7ozUKO_z z;ySE)L$(OwzCwfcDjC-9{Lv_DE{QMPRUU=!q}=lXzao=a*QrxX?WC9Sk7#pE;jv4- zwq!y4-xj#na=NW%Ov;i=TIeDuKulC5NLco3MqWXLYAm~2m|zgGD#%JXkZrg(o%@j$ zuH-gYIwhRP|1T-{XO8}+AOrKiv+M6d{Ch6{NrnGoVFknl|5*OKqsRa6*Xz?w!Og+Z z$V$xG*yis|ioB7D*{3pg!zbta)WAmH@c}aShDP>(l7sx;$?<7aaI&?vG_v|5gK0l= z6d$01Pydf_1PH2pYDijI=)Yp~PY&6e**eme1B7 z8b2axa`ELR@Vx@r%3P!BO}>!>OVNINERA;6W+Betshc*y%Cd6lOlNf`xnL-~zy zQDqe+DO;Y+$gOIr~HU8VzvCVRX*;ViI|F8 zZF>L4m>WosR8A3hyKw@BkigTOwqbm?H0)n)91maQk>g~yC!FE}i9u_e5hB}sHGn@} z%vi3r30sN|i3}lBWL#o6zlmBSw+2N}<1L+{zzVCcZe?<5q3htBGCV(aJ1*9^R3tWS8c;RevF8MaJjv10H`g44q*shqW-$m>Mvv(;!% z2d1p&sf-=*{b##SS0p|;EFlhJ(Y8b`!Od`PPG;77@4qStrFLN|#cn{nvMeW0L2)}B zg9}4Pi=-t{V;#pjAg@5_`KoP1BEVuNn2vT;9KRHatexU@?-%b=742;I^IwPVbK+#P zgvIq89R3KhmC8>W|7Jtt%cIF8cMCm){%54NzrS8PLk=&jJLN}N1SR5sLMik)K! zPO&8ebRLw`awv6yBpoM8+Ps`^tR!akwM|D!Rbj-^@eOkxHEF3-1qp{BVg6d5^?NHF z3E_F=pq{T3HZ+0yElY{8rlv|vS9v$Y-g4k0`kr>01V0h{pA2aSlnCmJWgb12IJK;iJgFPt449 z-j1k`8R?Apjt2)xvM0G_ZN_``w#>wVJ^L0CPqHZGxd^{OIw&oLqNx98PKtocv?TLE z?`0|Rk65T<5GMc3Fz;}>uSD3!yuX9dZ|Fd??{cZ5lB*bKL>_H3Z$il0w^LZ&e1j(S z)IdW~gvvFQ6;u^hH*2x9oa08VotG@MoWn-74{9~EoYO|NFKREGmdxSlf1G;c>tc?D7$+N;Z(AG`WqQTFzPm>~LkY7>kCg#cp3 zHcU@doVp1W^@(UosK{^2z2*YA4dz3m@^Wr&7(gZO5y9fyBe|uixyve!rFqDnRWzku zb7er|^cGOXC2Dd?W()Xa8fH!LVD*VT2ifuGttVHiN{Y&gN?Hm=6_wn(O0vpIvf7N2 zFBa$0EC%=0ii&z=C1o_FM{@~Eelpc#uI#yLa!@D5Xa-1~l#2z$`%YD*x!c#d%X$x3 z)|(aXLfn3lB_Y+tzwZjISqU9*7Ep5@b4OB<&S7B=-ozprYV+Fv0IyV6nG>@87>8L!MpaTRODsKisn4#k72+GaXrS^3v3SC(4;(e8 zC}%1tS{+SFpv8;7Kfml~sJ-l3(|jK-eLoCnr0q&)N_-I3Ebn+7UXny;?726QX@It^ zlD~cz6`Z$yuHPF~MpH^e&Tv+6(+lMRI-sE`Pna{|tfB=z2+mY-{c!`Zo};ATrHy_M zVamxBPZWqaJ4F$ZJ8Pkgd`dkyX^gS+0bnY+$8}kVQXR%*kY2Sd=G6c_`=*WD{2*O?)_rO%Xdn`N7Q{}WuNqCB4GNyZMviR34 zX7D}fEQhcvvogcZ{pO+n*$3;|?akEtM!QQPatLW}o+9Bi;smT#g7U1PDSfhptV|B{ z!v<>r#Uq|xuyeX&pF!S>0xs5?whKpj+F9d-K^|%E8cYP33s#vk7^S!c)-Tca z#6D+iQdBStRyX7*5h`%;1-Pvpsj37UZg?GHe(#g z4{nbIbwBV-L0&pZd|$uvP{sdN;Uu_z#UbM8H9TD>z#tA^?=;vadN0y|C~JSo(Brv1 zmLjZ_(#MsG#zf!DjZsNfD6kt7IX!3CcTREVus(h1L;Z+Cij|s>Dcq_@CEhXg79mF7(Z`!-JVkcEIRpKWZLR7 zL?HN(1p4BvBHo zaBJ^kG7>W!_~zmAed{?M0#p>?dYaNWL6~QChDH-IMl2&{axmVwhcl&{)W*^R+}dzI zH=4<%9EZs4X)>s0;!yCMf3`o%^-vTfIVOte+5Wp?3`ZE$_SSvn zd3tH``g~r1I|tz7^)|k-N`|eCgKb1SW{hK65AKwb$2v(qC`t^QsJ+ecgD5Gvp6GFQ zDtgmxe+a1vBKX**P2-x*nq{4=D0!HmMDAB%$-rRqT(eP>_zoXgL}%;RxrOxFp?3!u zrqkRNC=>}@AN`&zKTDIDjOgYG)@cR6TI_4eeOs?z+i-hH2_SKb)%s>7tdRT4Q`5RO z>fLgB)8y!c>=_ILD?C0~iu+=2xfJ4A_8@y+Q-*W!_1Ww#xtm*fhi&a5Tqq~#5Vwx% zI-CFnn>soX2*!k)y1tR0~v-pnwGLp{x z9M*4sOK*qmOaw3ev=*lo<;~RmS7$l~Y0 zyzczd{%GT95>2$=BzX#n{xX)1%u*e2eF!8S7oE>|$-tMo@`We)Y5Y-cmS>CiW=iLS zf=#-}41qA5s;9opm?kh^;k>wkMdz;hyO`DZ1skk`kk#!n5fyVQ7DT(LC4qs(zH0eN z@+Rw*bj)wtWWK_(5Uz@tc%dt?*y)aO7buumq)>b-p(*fiX^-JM*G8~?6_I?Crcn_Q z*r~29{_H`npa*UF-JyAW2j_z% zOktg{B1q*v(IeYdZM09QDI03@aK|vZMVJiTMW{La}}y~ zSN9XL9J&A4X-;ycN?ZPxo>K2&r+M|71bF6h+);ih_%d%Y*=3N~m@#bEAToc}ANZUM z{5@zgXC2;~qwGethU}0r$UFDNe`8gf zt~tBmVglj-=jDVbXzwDUszK}5;tZM@nK6bz=yH`m(#cVDAEkTX58-KB+r+yl_0BVp zCFH}?g}X>&D*?PbIkKfW?=dL*56)bc)3Jqqyj85-sxZ7vm=f4`E#qC|MT13QD>^xu z0VOxEMpdQzFxBNa3COMEU^(y5LbVvgJ_PW`zGx67(}`ud;7w_0G13FbA`ok>ezZU; zDN5Y2v{~!5m>NpHdF2_CHB{NvN%XV>UGye);k|hT%b(sn>Q;#kAQh%vYMPOzgi%Bd z#Ak#bNMR5st&05|lGi7q9A3)@p2$=mcIW(YLd-F&eNF7<`5#HMxKmnY z+iuIlRritZE!?|bPI}bM!F!dJCM50m*yg^iF-@jMpOL-Wstg;9$}51Cq9tL~ywcZV zi`nkMfuqH170`^@w7o*@sN0 z2e5PUDEzMNjnx(BGydUwu`_Xf@FW33b{J5@A5AL-iDnGl1Z~#?LLftq zNDha*uxLJ;(&=c)76O2e3Knlh~sr15UI`x0r@<6A!#5@*mNDo-w;}e2QaZsnQYj=l+oXTak zW3_VL>qaJ%!%h#G@pn*=IhgYo@J{D&I^f(osm%PQ-`uSt!6l0tR>c<*)Jmj-I$%F- zPq>ZGQ|eo>52s@SS*I2PVLwyrX?w|9aM8WV69VGCTKt1fM|aj1mlH02TdIQ>TzVi! zy)i$?U;Cij!(z3V#p%FlQ*f{v)SbOgFFlIAy9N_(*=aL4p(k4Q=0Fug{W9#c3C9qY=AcHz!qx{!1<|{I!vp!Ti#9hT z<{jbiC+e+zU4EtT$C)Dg;O<mu>N%l%*PN5#VGM2-%f{?tNFF zZaI;idfqU?SM-Tjxg?=eV>}^fmUgdPNMUFAbFv(DnsD1WlQx!F#Z#K?%^*tbPnp_G zhZ+Fq7g~S^ay?z7&^2!QZ`Z3>q&$O+_FFM{&EtI(C0wLu1NSqe7m3bOC4{C#(HJt2 z+dD3-p96@)gBM*ghV(aU=7i|eZeH%KWBR?-=W*+mm+Q% zFr;|z78UUpgltEezDtvh5<1Ns7(qMCm#R1qhBx)5-EuH5pY{3?Sr|mDg1JB6)TEDu zSu+A~aAR^)MnsE`PT%_EZQa*&TW~531nE7AkEGVVMyzEZeKqdr9?ia(!YHS%YuG|1 z(Vvs`7?n`q4Qo3ppaNHZb?svo9}Owsef~$;S3)C4ofkhausNG}@BRt7bUasq#d# zCAXVGHHRRUsE_pduIrpRiItwo zR+%TOf`z9PPsuS1a0YX<04h6L z)C!9NoY3HH`LpmOZIKg5fQX-AmEc)B?S|H-kO|8j)k%X4cY`po^MpX$*LkfO0Ra~B zHTVp45&3~g9F8FDn++|?+Oz@i`zMLP(_q2*fyd#ZMt3xxBRBoCq#Nlb7apArC&z=N ztVlHKj*64+Ft(*{;*Xv0LqigvwfTeYz?MVxa)eECd+w*DwA$yU)Xh>pgo~wd>@ae{ zxdj;%_OxcE)(n>SbjxSPj!22D=+rq4V=RoUG;`C0DY@UU<@M{c)@u`9z5v}xYdg%tz43}ZagmR|< zJr%Usgj#r{f%atw-(9nIzb@l zFEGM)1iDkGqcbvN8vZ>JjhetKxM`=zweWS&6EVu=07B9i!{(HG!SXmR%r#xZ#JR!pM?!;3a(tOMtq%WO;NV*j0V{5+cU;tTg=_qwQc_>pcs(2 zixez$oLE9S%Tu?B-tmNSKq0NAexp>?kc@ws|UtNY84szztO`+}j1)*ET?+S){hG9hK!>^d_x(wqSqgb^d7Ien%X zVM)Suj=!Bv%lYI)qaA5~DZ*)&|May=XLJk-ydI}(8JryRPue?9{tZQ%@qG{7b&Bnz zziJRj+mG4u0Sd2<;McRKxr)fFV0}%S6MW5kEPuPDR~mNAa;E*f4snl`h+)k0EiU_- z=q$4^4rmrSDQ0TIn1O2@gp46g;$4y;SB;(|?!HlTSNWWQ03A|6M&LW=zIc6&z5sWX&6L4*k7fxD;}OV(GwhKgaH1!3 zq}21!1kcA+_SY^*9K7c5`0dYYN$hPClE2mMw=e6~(BoF1M21>NpxX8I1Q3<|EJYxQ zbfK;0;jY<3=wBBgwKX7wsTTLL8pno)6C!#>M_YGTV9(fo+ZXS-;-}mf zXC^)Qo#;IDx~ADv;H2GzJ?o#;85UW0A6saBMpr0`bZ%;o9p%XC?%p~9JFc;_$k^;4 z%LA|<3-~4F?;o?wHz;eknO*QpkL-5SgP~)8$#2=C4V0@ZnpBl#Y%2Er{C?8O0<}r{c+&$AU{FXR%5o(^_SVI3Lk>8Or^v$)z2I8i7>a>?-VdWgH; zWS`b2FG8+udpXId)M~>l$jy%0q?2J?^cO9FpjK_KKTegFH~frgRTv;FWru-$gjvpsSZ$jqC$B|$KTHI|=VjJakLB~o7=N@=7` zjKPd-<&pw!h0Z7QHTD(FEdiT=Z1`e0Yk1K0%^0%HuhS8vBPM8SiSZ{*c1u01$6kaZ zlJoGxbkPy8do*sr#pJ`0&e6xT#PNF(fF(1nFQplhCRL(m+!ghK;WQMmr)+D{?4$|N zl(8~)c96N_-H)@qzUe)9XXmp=V=vGi)pKz9Fu=_24x-8?n8b$Qqdx$|1m1uQU3)YM@b%xn4!J znyacS2*;N5*4M3v9#07oZ;WQC*kc)(X~I+WX1KGQrAt+A z!Z#LDRr@Zf4@^E&p7~FLH!1tM`?32LG5T$a$X@*?{Xlf0u&6f3CLt`L4EB+=2zhZB zR(+Y!TC}FSPY5M*j^u(`;kobOu0}%%g;4fWG6JpEt`pZ~uUYxl&X(tOkwHvVk+}g7E*q|Ed0MCrISnasvBy z8@u76wc9-j>6BVZ%elF(tc8Lr{b)LUJ#5gBhK60pVfa&N_h;m*~iAn&Sl*ut&t$(E1 zm>nYIld1C$G-j)Tukbh@q$}Aw1W8~=8gw8Zc=X|87kY}~xdI<^@wC1ki?5*Ku%^_% z(ZBQ>)!K<~4mfSlpu?HCMBunZXm~AhjlfeHj8@-peD^JfHgJ^tHib*H(j<9pW-$d{ z^jc`uIxo?^o<@PlOK%IkZy5}eOWQ^p$CnQmaieS%paUPvd*MW;#VuXd$=47TYJ<== zY!(G&zSc|L(#i1>=c!QD4KSK`9r*d_b^l{LGWBOUQN>YP}XWKa7{V| zA{lHf%|)*mDPGirlwPt`p?4XC8K%$nJes-@2%*3creuuo`EG!iZD3<;VIjG(K&gufg}F6*T@fl9IV-FHIf;g){uH{^Hzf0cR--I&mf2@S3a3PX71(L$dj{ zmnV|rnP(~wECXJ#Er;%{HVfke8Fy2Y)zFPoDNol}tl5e_j5H5iZkiW;^d5fZSwI72 zEa*tRt;g2DuIJ1=kuRA$jrQxc7eOUE6@w`LfMADye&-RuY9fGLL2~zif@I-B?Uf~G zaAz(fqwUS+#K%>0Sj630E9|A6S_+T5{M3zb>8*96|9Hlzt|mpU)=FU2@Ad9QBb=jj zKA^w`zV6f|O>@H>vh2j`t!RZ~%FYzwrQjzpJDv= zzDN-`3VXPVwms+m;`ICCIU}CHi{Frcc_Jyr$yc^BbtIYQpbieh!4+KFW58568oaX3#9nwh@hQ$9eufHD_?e9 z3ZKBEp=ibLjs$ObSwM`N&&59$eLU7xL6r+;E=+8a7?zIcqs$!iu4aL$z79iRLTNr zXp30h;hkXq1&GlvpfTYkZO$iH5ounYYpP*)QxI*#W7j3}fvXG4&&J!&Z(_m*&w6O2 zweh0A7j!gP%I3-s1A#a*=U|{QJ9&>KxW9|>Z$Mqe85z`Ndu^241kopFHiDNnAYtQ3 zsdBU|E$P2$)J@>Di4fY0dG$#t0aqc}@94f&;Y7A{SU_ugF;(B4uI|Jjj_TN3hI2NQ zXYKN&A*?Se8$HkURWxBI{oGisc`YtqLo{7r(Zxf8hX~nSgV-Zn6+aVvFFwEQpn3=YDp4H*l)~&Adf^lx-66eO@Q7=5!G{k=NmN{HkPiw8^7aohMvQ^D&|P8rgx|lKF!s0O zAmk=RfA%v3A;$(q5x&N&X2;bBQ1vdGgRh5l1vADldpheqwvRGhtp+iNTCpOOoN}Y*Lz{fVtIgT?*?^y%qQK#?zF{ z3!PnDX42#ka8zZ=!X>$pZ8NpeRv*t@pffo-+l_eGOZyg%=kaL&rToyZIdoO=kYjAu zT5iE9WzvaaE7750bxjj#VZ>_pdso<7C_(IPRf*q0&gg>^5|B7^$G|%VMr%76 zRAg87D(X0yAh*=HT3Yqg+pBUWRtc(UtI`!0p~?i#wWr{<8BoHmTFkbqL8p@^85rsG zKJ#n|TB|2u!IiO<6J`Xrn$O6WYpb>#4?h~7NTOLO4qDV$+f{yK+kjOr($(%8x=;bg zzS#0nLQxWL=3VzH2U2nEU;#c@4f4`sKrPgiZXn%ig$bZk2NAzk1(m4;5K?jZci&4Cm`7(PaGH>?h=()#q~-)WFx#h;(L+yNOq z-|x%t)F7E>Jr)@xNqatZkA$YZ-yRjYu#H==D6yv+5;CTu@bhcJ*S8HU=l4d?gT_rN zPPb~y;jNy8p6|+i)5FS4eU#whcsLxRl1E$MG+wi6ldH4|Q9sX|H6pN%et9Uc91suP zr-nC^v0O(ofi?FrFh1{8t7**}5cxi0rEBVk*cYMryLAvWY1Wa1uWQ~Pbi{15kQ(=35p`M^%?KZ*pv}tMCIL=On|XCG+~f<* zUB@-MWN)$4S&O)uu8vmAyF@sviNwt8u+*4}@n3evB?7>_&rEF6u6K8xPaAQ~H*v1L z;Mda++HPE;!VHrZG;T~vU*WhbuPF;i@fet5sc~xbG=7t@i)jp<_w8>I8>C(3q_lX1 zb9-xzA<3OfY5aU3x$vQal87!LXSuVh$h0(lxlVKl*9o+RU#r4lFFD|$^xAG+Y_#&; z4?=Lr%W5gMMmrF=_8EWF;<xNLycm_k+6`9U^Vuv5mZ ze)rBGGU21{#l6iHl4l3HoAG@Ge!Oa=YN`4nZ!*{zt)54kkPzzjMD6XFdzrHCe3bz2pJKwuw%l> zDO%~mP=BO-TD`NRN4aJ*G8pwk?bfk-qSKhGkv_qp#c4rY87!s6iPeHbXpskZttQH~ z3`crwJm4z$%a|a2iX_2I&Kgcol&}zQ=Fb356!@YsdDr*w?e> z@=?L@53$sf*WTzJ^D?|ihi=#33`=`U1@Ca#{AGwU$k2v?>|}90Y`Gn=^GorEln5NZ z5SOvtDxc~P&KR~LOe?{?VKhtgOw0Ta=H4=_a%BzBZJ=>z+}&;A?(W{WySqCy?$Efq zySsGb?(XjH4wv3%?{m)FnYlAR@3UABNu{b*iZ6t(67s%>prj@IC&@=~vOheTQ__OG zZq!y~*%;AANbI4T9cj|qGN?A8S|loi+MqeMtQPrwet3MfpI2DDSrok3kFq6e-f-~g z<#|>+4DuP*>X&IH;{~goXXAmNo|k^b7SpivWXS3_x#aEBenedFSGi$cM9>-A=&SPG zog1y{Ie!!p(^XGOJG$4746+2r!@i2Q51Rv6(1%d&D z2y0nb2a5(S4oWuRoW12S=Zg%0-GxF$I!ZSSzEDNyT+C#i@mDq|wNr$(A4DWHQeR@5 z^UNryLrl&m6d3+)MM_)ZJq~XoKKU%-9YGqE@Fp7~vp~#`p>9irhyto)kZx98*I^rz z@slx_!v6b7J_5%f7qrVY_?qJ-yC+-AK*HXB_ZLL89gV)!y)P|LG|FI983l%|cQ76c zKvo`u(p>dl;l~+aZF-SifezWKAV5$biTgu{nZMQEd~D)O@@0{?7j=QedG_{23^>0qFwa8bo9ev$Mv(dF#cdW^ChDL6MeY^X(yCF(_`16S@D_ z$fYGHI~4S{Gho%rFnp>CQ?$J5N!X$%p8F8uH#ou*K<~ggVrEU0BJ3HK_${u6VYeJ- z>hW9+siPrY3G)&!{Ep28F9BR;WGljPfZ)WQCbFTL0urq;>A`W*V;O|Tx9d}Su2T) zUVY?isP>wRY;Ffs7k|T_MQzCgNqH$)t=?y z7NElbfQ6T|Y0W;7Lv7dw?5er|%~7f9#?#eFiB!X<-@1JUUbMo8EC-~J2el-<&mJR> z0VS%BWy*B~|Z8S^@Xd3*aC)t~R~1L?F=G z!A*jri(zSeqa$aiA|Rp6WvXAq6pM0{?|Ov0h91(90KuWTL<3Ty#qA=5zJk8~?FJb= z9^}`f@a_d^+g0cydcG!YQUAD6p@|4w8oD280!+)9)2~}MG$|cdARe} zl6q##=?qtnG~Q*;f8NU7+?CCmS&F(^ZcG$XpgfqF3@d7cs_K!Hd8C2uq$kwyBwTA( z&nwK<8kF*czm+Resi7N*w6|~|?3|d^!|30>H3jhG`-0piuVvXLGGGMK17Nm%f9qS5 z{lo{0Km)G+JUM+wY8K^o#w9f%$EUlyf1^yh!iJe(7L- zhkN=0J)=4?={(_t5PV&6mMabu|BW8ts4F1!F`$8nhK&YBte=R18rA|Q#lXcC9Axq} z2z0?m3e8Re#`C0k$PlqVoBB93!&!nfzEaFxzwz<8>5(^W**j$pB= zXSbJda*8?`t9i@$3WzNEh@`J9lU0@>uUbY|k8%_4A>0=X#HbFsx;h!KBNl$RLCgR! zcZdRlRu~pS36F}m?)wIC?CTvqf(q%g{=O18IJZpdk%_ns1yd(DFrq%Ci(Uq8^{{V+ zzQW-aXF83e@B@^`QUE5cK8!o|*KRXgFIvbB=0)^H$g^ls-kX&~;Ryjzw;H?SrA zyl%lzpnvfNcc{tNm@4A?i#iDS8L&e_Y@Q`UD*^xw+`Hv6w}~)>j;P4c_11)EK>5NR zkgBenju{9=gF?Cpv!ly>;|APe!lK3!gf-vX65wATP>ZByh-8ko$ru2mFyTk~hosJ z{o$Om5Kf6|isn@#;U5NSfkug{uN2KQ&2uu&FUtEIg2T+9F&lWFUi$@F@Zu-#m>r$$?KuzI3m=pKibuDKq=OY6>x5_@0bn>!QymG1QgnFr z8`v>Ck(7KNqBGftzMv;Ksp;wSs0Tqsf!4}4_#GHX>7S-S^im=>SsmUqkua4A^B%U{ z+dXaac?A2x6(cQUWGvJTXwcf>8aF z?UmYeRaFmevv!L-cK+U}o$p!r2yrh=>4QB=_rM2gv|XaK~4$L`3SHgLjvzjJ;0I@75! z0jO~t+T^{4biz`Gs%(4E{yC!bE*{6bDdX&O<0Yze$d|d}C;%9+v;t+ci-GEDFHTgR zisMDIxu#T)_xnBFH%M@Ie-3SQgDDyqf%+glJEQi=8*b;)TbXK{zVy_9scyJAKps(@ zvv0nu=>pwFF>B$r9>CDZu)P|aNg`Qc?5lrySl?aL`;_WWMO{5t=_3cd9B3=-uI}7% zqQi>cgrzCi#`a|U2>vB2m5vrp_CKJZ?-SUhI35kdKmTmDJ2Rmo6rzIosG=>O@*6Gb zpM@P;96Lm1SjyZz%u}unjKh3h2Vmif79sF*vr$#Ty8C|;=89{sApuhTDh3PG8$~}qC+d0zG$YO~ z8Y0{_2n$C?&A`-fSpE=wAf4DfIi5VJo%T&XQel4D&ssaD9V{DZh}e`+yU(USM@Y3b!r1s%zHS)2v=o_PrTrUWPS#eFhT_RvID3z9rm4?W~VP8cfkd zKok0DLktjaw5Gy_y*X_4k5iH2FwmnOP6Dx#aUytqJ;Qb!u+HSJTnRn6?&qY8PPLaW z8U|Om^$CwmaKua zGJfl4^ys%~u>OE?-R^tfpt-&A&EG(7mJjcS>1ieMnXz^ z0jYfh?D0(G3yOnoSVyWvxOAMCl^}+m_>;C3$Juw1XP+@55Le;)=U_CXu7&g4PoZ0j z_Rq&%?fI?@wrGRuoL*MX*f--cVLYoY!X#GNg z&Mmg9k9yZ-uhlsoXfLUjwPa7NZli;O9yQ9d6VA2BX(=tYz@gk3bwEa)BzojjT|B#$ zXuHJA*x0Z^3vpvcg)i6w_sX3zj%?kbTMk~MDh+1s0ajl@7riWoP$h>6mRDtaXqavO z7!AB|DQNWz9BlOdRj1`j)tSZ%s_z=97qBV8LF9To;5*}c!er$Zd z1A)r*svKOrAXX3V7NH$YkivUh8Gx4Z)?Vi6l^c6l@>15co15^7SpCSxs-wE+{k;vo z_tZmJH-1l)V+=}pdc6~IDp8r_QsO0~d#1m@y4)8{wfhk>t5RL9+134?720Q;aAb7g z>f2u^hrJMy(KGc9nKqCYfmJP+3W8IvXllP919cfx4hu4XIan*@|AKJs@M^YZa|!NZ zvlSleLtv6)cKhp55JA=*hbcm8l1d_nw}8YE+%?>vo(^ILw1?;>>P){125L)*2 zu_iv+13hoN59|$CufvZZnp@CA0iA6e;B~Iose!x6OcntL4w&a@=)jdLltD~>g!2K; zstL#{$bmqY0JwlU*8?XA9cS!t7ww`?vV%SoG&5?Xl0uPM(NgJBg`3Pwo|}e)$W04* zi1)S-Jl$SncbWR}u`WcK9LUKnaHeF$xih z?ilgToD{~>8}7R{VeMQV*OAeB-@eLcdM$aFQqnt+tlCpgBJ~owYf>QIC^``vBB3_ls1}- z+-g{zNya6|uvC}>I$XjYq-ta@`~^k5W~&&@FY$ZgtPtPW1UqtkgPHB zP?ppI=5miiz%>w}05OuuvN}+4s#s84VyKs%qEsQIY_%v^50L#3QlIfIjzYd=zcu_kV7bh6sf1*KB%jPf~<=_KV{&HK%`=YimFNCBYui)QQujxWs ze)(`w{assKk$OI+dY=rAt9jSqCa>a!q2odl(v6VlEvaNIt%bWLG(Y#SW_v+LDi!bP zd_eO2?afJ{ATTLP$GWGvvG}7^?X7_n`5>;HvWagacG(ih>?G&`!4hib z$SY>;L4zhpJool&Fv~|?Hz5Mv+kz+^laQBe$7&tPgOSKlxHwNmmUmy`8h*)Y$Jsy9 zh@Ba#!NFXbzoF*;2ta#zP=?!vT?@G~1XhJ5jk}y*b+oJq)aS|+^ah^8Dk@}sFGamp z#&zuQ5dln=k$1f~B)ED+9l5jaoV7&$?7$6Ze8`);_XhJBdcm^)iA^wYrFF3(`0d2M z|AGCQ)w5(5u?6N#F=}isnW!@F{n1>UE+gRK$U1lH(RqlPDYk#xX%mzw(s+u?9h^G5 zuXO(bN?mk;&s-yXZH%RLOUKqS2X6Ar5qy1W1%&-le7T^rzy)3hkr!y~;^DF)9*zKw zqv03r6u+lD_C{hqE6Ho~$z{@DmnOt|Ep+fVSK`mBvO6yn7@9OL;Eul~Tc8G`%9=g! zd21ie8tvfh+7v0S#oO&%e$?$mwz0Ns*k5c?ZTal;?DFjM?D6y@DRpkr*y-5m?1XP2 zwSV$NiQb2hSLZ#cc^+i8G^bS7dot@B5U+8goLcP@^F zWop?PU^65ecDgG29@I335gehD{wNVLT;}eS1LWh(Mz5zMn#2~lx$C<(+NnD(Q#f}f z6q>+nUrn2T0*bE^T2AYLlzPHQzkznjKEJ<5}q z)wKWCBE43d$|Yu&W`g7CM^8*DQN+Tovl(#fqxknEI9 zcQQ}~jz{wVr2nhmKh}bKlqMSF(UQ`Bm#hybTY{3opPAm2>n0hUi5|jnpW){n%nO?w zW<00AwC(suLQ-wey^go6xh{`N3Q>1jzUtjm82mTZRqtyuU$)N-E)ML~ss;3%(^fq| zAU60CJKbtkbHKz@ziD$d@J4yTi|y2mjnQ_zFC~gGFfF|4X+M@D-^6W~E^UMFoIexe zR7maMiT9`Ip}!$o-4*zW)9cKxS#O)x4RFbij01@zqEq~bo2)qZN3!sTyj20uVAk0f zav8$DOAk?U$8>)0tlzwHkI*SWE!SF!sAfV?Uwa*ER};`iSVdja*0bNBON`0dl4=JP z22H+QpBNVH4=|03_ zF)Iw(FRBgh80TOfjP#w<5MJPS! zQbrzYp3cv<(Yy5JJ!)Hc1xM@x{F$@{$;<(LV7mj z@D1z=AkFWU&(PlcaunH4>(=MQ^4r*mG&jPq9vouY5S6p5t!f{10BvwbdGfn2TTVz@ zmy?VixA+Sh=8%t!&Q}^Y8I2BF=O+|so$ShuePgj+`3s3)`y>2uR{4de(^;@-wQ8g} z#uP`8EY2U?7M#ADd$?l3cZ7=O ze!0d3@~{MxH_%?0P?YU8SmNxlb*eUjQ?cB?fKk|3BEf!<6nhNRb$B>`t-Tgl^vFQw z*uj7wj3`sAY$rFEIzC<&PLZ^zt2IfWp%~Q0R+39eO2|xBvC>M+j6qPASF5p9mpVF~ zetO#4Gn&6t8i`d-iZ1|2M~#I~NJu4XAZE4O@=M$4%YR<2va&NXo!S=Ac-@XjZz;f7 zQfpYc3T(k>Q7f1qeVmi5%d4yFo|axJ3`7_zlQ8Z_Nla8)idCkOh#b>WMb%2MR!>g0 z3ag|Xh0&5nV6hMu(bqF~Hqw@GmN8Z3_k0a2KSh}`OE_XhqbaMDprIRM6<)(u(9kWV z31J|(DK74gEf_+ecbGQVRz@}CEh|N!Zor9*#%aa_A6BJB}Pbw0nj!rpP3l9U;i8CBQDL8)^!PAMU!W+LF>VBuUzRc`h)`~Hau7uoNQjYvLhp3SXRV_&j^ zR*-k*ucTmdyu#Lykx_QkpPvp4AKu@skeZNGN5Dcs0nY+x2s@r`*Ef^c)y&mE*GVW; z=ov{S5*x2+w$CaXNdrcQLMKvnaMd-^&=MPJIRNaej5L(IB>G0`n)=$_M)vNi*4wM~ z#es!sf)@5Bdqy;=Y23W-YGwjj(#rd*hq+5RB}WNY2<#(Pl64GLkn_FMx39zP1t@mR zGuOk3K{S+_a%yd*hStN!z3I)bYLe5}Xyc=r$~9~YifIW=_4TGf?HB zbyjX$1r!*14LMJCM@t2eHwN}2k~fsGb-9c^;nO$6x#f^kOC!qEQKgX+L(-v4LHkNHLk$(f!|AZ_`?;XwqY|o0T38v( zR76x|^@L3{E=##2pyD}OdnG9;PJQ#IyUE?BEe)V{OD%hnXry~2y$dLb6R8@wI;u%A zN=XSBTulI05B|m6V^BQ`492=x4ZTT>+5f$UUJ?at0v5bT?44hQs z;jr-rnhBW^3fW;6l8L7NLh48gO=T1n4a8r%cTyUQ+bJl_OGnVC2fKR!nPTdaK^h5K z2{DKUW9o=Oaha?P9>&&IrUJ)KW?C2F>Dc_R!zboIGfBabFcsQJjRa$c0>gxH3YNL@ zL6|ZMs=>@erOtL+U=(-V$iWWWSoeH(U`GUg7bR=mLMWLajz{Kk< z?`^c?*O%f(m6$D?{XPTTJu^~!V{W{kFi=h|)r+@BItok0v~*mHxSwhdourDCCuv`i z(1?<2-j~p5uE*+F0 zZ*5^?=O(Stch=Kh>~3u@0G-c2&QGC#s>>Z=yy>p%Rw*J&N*$Iuno3~bs-uFUvV7Xx zn;J3;trM7G95JEIR8vrEX0o}T4pVDsDZ93Zs=Kj#l0>RyKqDK~G^QLLrw=5JH=zlM zrVXtoHBuy7pjNYWFqhFD%k?W@tx}Ig&uVg%nf0qpfD|`_X4sxF2_l`ZkWy9s$xdZ% zCoZC>wqNR~fU7=K4!RV2MK!%sxVPJvgQGYaB@?c}R)-AO@0%DKDJ_=nU#!nxR7Q?V zVW*~Itzu!SbTkujY^Kngk2NZrk({1J)R(Xit3$1n&}ntmQ@-x5J$-C98xgc(MKjtT z8-|vQD$Z0;Pfv?W(nwE8h;4M-8nZKFhejNhKr12}9i~$KPFLYLSJBi-xApFu2ghX- z^KSb%e}i?-sbjyj=|)5m6LHfYFY9o^s}^J5;5Ws+?av(fFrerI5Z zWtE5b#OIvD>FwyW@&>Mr_wwFmowCJbu8Ns)eI2jkA#x`%H!cJ3ZTjpcs5u17M5@Da zEu6FJ<01)94P}<4y5%hMI-OOS*W(g*=Hj+7ew|ahg;sATB2(vm!KSej-D$!H>%-(B z{f3bzLl1e}OYPyq$>qFDUdaWU*JXkSktKR;pC9+M-x4wQC!anGyZ|Aw9I!!k%}+wq zpCM4w0$oCV&*+3wFtol*>S%`0`gy%9s*1-Tes>7)$g|7UD;F1S zROTj!I#GX?&@8c~8UK1S;>2<#}8n@mu=Nrb>c*|NFNyk(g^Nu{jkH+qEh=y0P zo^-pzELyYZNIDxHE*2INEwPkbyV}U^FNf$ojPJp!DjU|!xNEo9kig41KmWmy+rj+t z=xk_$<=owB9j5N#oLW%5l9$_g?DkZY_v|&_T+$#s&-B$)<7vGw81A*xe!Ma60QV}g zD((Im`i}Kzx;E_0qG;~oI4#Z1;-xVu>z%G8ckglvr7r0~y20gLuVLfrcWmp>S)-CS zSN|SXhN>M}8Q~2q9;w)|E>{VR$d~W7WQb`OJ;=W~OR@T6t+PWVr+Uk9SvFK#@T;fKHS^{BRMY0GJoy8X;3fQ%Owp$rmrJq^K+q zotZ-5BITW>@);tC)*JfQS@d85nTMr*g``piUoVMl7)$h^B(O+_!Ab&L*%Rsbw25Da zK7MA!WyNI0x(4FB>fr08qg@Z|ite&s1D*)ng1DsbWAN}#)H`IKxM4EZ$^prP@jr#; zljo72aITS;Br}O+f7-;^#M=BE7+M%w7*rWD*ySBmp-Vpyu&mOBjqJb7=)GYbG?pq3 zTg53fjgs>YJth1ISdzuXe~9C`R=b|q%^K`5B!dx~CDh8u z>Ck1}MvDxpspNjlNdw&wU$yWX!G+-uLm;)A!takRnWD?ogc+MLFPT>2XKGNc7l-aN z;d|kHUKvAormw(3A3Y850C(b?Q*e#U3FLs4kdh4)ghz|y4n1lr1-p*pD$MZo^Gw&{ z3DQ%l@D_9fzgxk0VKHCs-fHL?3{tj&k)1BS>K0`d2(jdjwBn&AL!t4Q`D%j;PtXY|_gdPr!V@*6!S7XgF9w zK+>jR)ejj>CUO!0Cc6g7$3yIcF1fnr8q%@>SMHQ+JCcq|O!yFI$_c03$M$r{xG`6h zCCu5C*pw+cqgwCsuSlBk$vv^Na2fyD#z6G1crY2wrgGDyn2{>l5{pf-4nrD)X@hFJ zu)9+BVC*=8r}mYy2bqJIRg>{Q3u6{y6o&BPoOY4tXAOrJVjFhhhAalf4Pn{oA5p(^ z_-?5v+<;{6?2t#3lnqMk8^i2P?J609s>wtVj?A*SUijh*^Tjo;KQz93=8Q!w09{u8c9O10;Bi31->* zD-9EEkKa&TsTe1}7Wq563xgLdaok`p9S(WbR{+kS2nS+u_yDmd?EN-I9^)w~hqT&G zE18+2E+bK(y>p)&lC(&Sv;7wgagm=a%-HW0$pTX$g56upP#c74lcLZhhW4Hm5A}?2X!POWz~bGGV(^+5ZCB!flN1w<>+@2l z@!`JvuR1FxLDy=uAjq^zh_b2Z*5y4J|1JVg!x`g1;;E}vo4l>d8R|3cid4ki6|k&z z&V{gt9H<YXl!EQXaQ9Sc33(B&r&+}5;l^V<^pNZsukrI9ELwE{M(msm1J{(+=kxkXO zkU6(yF>aeN$SWt0jaRjh&~MBuYARa5I{@_X5*~7I99&#+j_XzplG7Wxmxn^i*jz!J zu^=KT7K*~s%CGA)G8L?&6U{KH+FV;{wYY8U!=8Y%tfI0x-wSQR=522DiCC`f;vMBY zA7df)qmO+sY-g=F0c@>{%+8B>X^tS%S#!1BS8V(93)i@Y{Ft!1h`Q=jKkuTDe8frE z)DB}N#+y?Q4vmF4FH%41-R?LCmu=RpMo35X3nX!RC*#;ShYSxz4oZeiFrxLgLF2q< ze%|jIWxxE+^V;D((8XwHl>3`kGc4k3+ME$FG5uYrYVIBewhBY;Y#bx{Q@v3XOMBn8 zbHWx%6LtiPdT>O#oK?&9dEversuix>PV0G*{8QsRNMF_G93f?)dYrj`_CkzTo43-S z|4fpw(PrJSclYUnQB5?l+%m+uMGBU2>^oW5ne_7NgH0P6E2P&(i}W!uFe7Ua1l!7P z13SSI3_AxvgP@>WDTOFUTo?}_R{GFqS6Tkk&(NZTx&-5Lb35fq8vF$w1FY$Np~;>mTUpKeW#OC5cth-pS}+8~#Jhm5>%w zlvDmUHTMq<^gkq1D29Krg#Qbs%kXcpoxOvjpsAicKI12MR7&r^R{o-k{sj(Zru+1T z{1;F3AG66HZOA`7(Z5Y4|0jUxCwJGn2OnPO!m|%IPVnnJ27yuu;nO5bX&l_|>c*eu zd={RU8)zYM65OZ0DQMYE&qEM{J@d+!aYN#Z8c^ZWgloS)cV&oFKkk6IsyaLyeOz!lTwI9zY~S zW&VDIT<>|MG*m9sBE2R^tq#Q&U8U3qKjQD?4P?z^i}=3?@jrxR1_s7|0{mAn{^tPy zCtUx6x&8}0`~QyX|F6Nb|L9}>J<@-;*8hE={4Iw0H+Ytfq|KL~bNb+(-p2O(R z;;gHK{3*)^uWz^jj}Qw1feJ#-AB)Ztf$;O35)@GkB5_dkG5))s8Rb`ba_R!60zT@7 zS%0eU5wpPT^`Ow?C{$K`-^~%MC>s2jLwE~h>AV}*T-H{5_XBg&I`+bEC8%5$QZ9FkOo-txWL_f-;; z#>1XXx9%hpkaIgRhAlRRONB>ry%A4{ywBTHYFwvpZr_v&M)coy0B^qy3Y7M0uE*xH zepPd!vJxo&s?B}Ld>QA(9ac#BJ=(rq8!va>Y1;kWpEGf zfs4U-k#RIc#7kdtMcKTwn~G`i>fN7nQqfk$+KYE@lXs%xhNX*BwdD@tkUZV`Qdf6X zwnD^W4p)R=r?&rPTZ)0hC`FJIC5|4o>&a?uHZr1_oTMA8K8m9Wvx*V`}Hz~ky21I`ju?FFW4)md(O8k>VOM)@O>6qmg znx$a-`}PN%xLRbPL$>Z-I@XP76FYOiAeH70l2&>C*&qucV2ZRcY@rYJit$RJM(s7) zRr*z^ol+Zt7xjbMoA_O_9q_KuPW9W?5g-0Y5&o1suL>OOM3OwRqnOmvGfu8>Wg+4$mj{*tOaM^d&PDx0xeN!jL7Xz zm7c+o#R-xNitSjp+4Ak}gJ%ELV6x39>z(f_nst4Zy@6l;b3#`o$f1?FCN>dZBbWRtHRca*Em-z=6Z3t8;Go>6R=@C z{<3QCW(jIlhYH&qV`d%0lMQnkGl#U`0b8m+ zeWs-;X?iL-QT8qAx3DRs)5swGB9uYF>*^UD>mj->KO+Qi5__wq6Y>ztppuytk`B`# z;K7IYz4SqDyVew+(T?8oH0Y3%=uAAKFFl0i^>M9@kuN=jxP%k+A#B^yqZuThY1IaY z3ic6f<814~7^U#nf`>JQv+J{jp^wFK^PSSJ2YG8I;HqR~&|0*O4lk$Z>k!Y3^I^I{ ztF(t_-+sZ(T@&52NsOg=A*Hu+bi}!xC%^r^!CI;)TNCUm7(szub^iLrgdzHTx;2L? ziwkaT)?h(()V$I%X@fh>0Lq8Q*fgt>m?Bi)Z&COZ;EcG_$F@3j?cFZp{{1#G*JQ=< zF{-hi8f%Z&--XxT92T+0_rN(5Av4&mzbhHi=|tLT9?gCe`e^TCS)7Arhgjs&s&O8p zuR;W=2`_0>+mhkrr@=e}hu_702ivd%x;@);+bXFwvg}Qn1Exa8PPx2q*Wn&hPI6m8 zhbJqiOlw{8v++y-u}S<*`%(~?Ny5^&Nju#0Q>rZr!Kp*pBa7#FN|30R)3@!?nz)AV zQp}9a3lz@jG8(pHtT2J=itWP~Yk`yxxs22_cw@%&lvgz44h1j{!_~M(Z9TcyGuHO;J3ROOl~hR`+&^{cumHvG-TNQ?=U+=d~lVx}PTM(IB^C$HWbePFo5+5*q_iY|y z@ahfg@&+T;c3lSte&P=Ygoh^wQa8LqjfCrK;}|9szfc#_)orragYVX9qC{0@Hs?5u zNIzM|$%hpN`JAGpgC~mPVtAT&r1sHCJNdTO&P~x{7VE-fT@<$y-6R*aW-K6YDeoPH zOa2Psqz*+N*7eB*@BX9bznAZ9qet|m2e`1? z9#yog=4ANqplt28v;8`7!0|ujljt47=A`;F1GNQUj}D!0f_>ixMu-mu_V6Tn zCCNdHbmLexT|UN)$$Af4dy~rQxAkA|z%13ZRo{l~Y0e%c} zXJ9f14h51>P?wxs2@}5%49?Iep2NPoD@PZLCS$=m(zCT?Srl#+tfbn`Gm45E+3>q8 z-*-WcoWR2qe|udW(VY&tWJorAcQ1IxuZxd=*H)a|o{g6p{ac-)zDMEc;`w48I~n~! zFHi)TsKyrhZhpXo2a!j8KJAkm z8~6GzN5eC?-kqED=kK{gBnq{p)K!#etY{ygf-o#g|BDRmABhA5J;T3!9RHO4$y@%f zQ*e1PDMd8_DlsEVXCp^51HFHxasNr{pcwvkQ~bw`A+2Zd-Ns7K`adNiX8+E|KcW8r z&d2HhApZZ8kh8Ku{h1~F=f(J$z5jXttK`oT1M8nbFf+6KZ{L6Fes2G}CuX)kbA*4r zSUzn7pIX6Bk-(oNmQQm6>t}C&)<0X&{oU^G8gzfv`Kuk&Up4=3^-o{_{r%70{Et2S ztAydNp6Nc#1q}FXpZor2ul{WL*VaFy`SYoNM)X(dUwiQ1{r-P0e~#}@tN&pF^N#@I ze~j;cLiOJn`2QlTe~LbX1y~`(StRzTw)BbaPYK_YDa6 zY7d!`Oz6+&_Z1QzA`T`9LXnOfLZ}xA<7?S>D#Btnm|>9K?}2_573v2yjf4enspc;^ z4c%=Qzb3rIC9ZASUgwXGy_OC#y(Vz(pEA7empnGo?op^TV!)gTF{P8&Yb|kOn_`3E zb6F?UrfUIxY0L24PYxW*UKE*;d@tK>Bm1=CSHS62juSfVtq<-uC;_j<6%9t#r8rvt zUgB8TVppyZr;N*q^;HsA{RY*%jjl)O>&`dUn}x2pgi_N{(Qc0_-OL{U>!z*SEB+f`bmjpJ&Qy4tEn_6 z6dfXe{2SKjU$X1JT+V-IY&2>^m*K*{e*;JMI*8*&OUQ*Np|5`^#yzx&sq!Zziy}4Y zn=;Lo$kxv;FOPAa4SmRa@x=wtodWiRQ-`ewJ=DW5{B_S{OLoaEiq6j!szOADOH_(} z5osK}P^swVgEO#NBiezt$jcjuL+AdhFNz2=AHAeEdS_r#bGJ`67hl`|SpMq;JEqoY z2B@@bo)KRLU%jUO>n(z8&I3t$q#sO>g}`9XCR+P1+QBPtdHAABgo}|aHjuU~_a8`3 z>x}239lUlE51n5f$>%g<@cy5?mWWR&^p|D%8`TZWaVicw9Sf%iUPyz-7M?t0k z?!R)d{mCAfl>o=%p{e^-g3pgV^A#o@jmQBTkE4)`xw!rJ5Hn3w7I!MgZTX>*SY!;= zEpmw<5J_$|Uk*Ka&_$$!X zoaD&*m~(Ai+ZVmxbgFfbnfNuWBRkA7q(Ho)n(uhF$CUPLB%9-xV+1CoGm)z8K)NQAY=c9sQ~nlR4-90{ zokFHXtyBw3Q$LcpmI5366OZAb@5+F}rl@+g^rqOAF7xA5Qe zYGIe;*~K0p++ofHd4+wtUA7H|8VyCSBX@21mCgnONqcOld4hZ-T^L=+@WkKgDS!|W z;vr=-0vq$lHs9ASIY9~=z-YVATshbILuWH)>5Yjj;t+obBF}YI;Zh5y0r?^w0-mX! zIp1SzXWUyec#;4z@3h}@Y9=M8&os+RD`X*1S@GBQ>lJhY5 zXk$``kw`UcZNR$=^eH-jX&UuNW$1d>CT_zo6h#*Z01|;UIaUnn-Ub89@4`o$8K}b= zv8?9!t%LG|XMkqbzY`Q0o<*OGrgvv+;fKxdn@iwVavsQENrq~jIlB1dphnr2@!_db zV}*%w8MB;`7u0}&z`DI}w~k7p*|=tPqjmKdDB zuKboU;#{IWRd)aOsZOM6idyN%+3MWw1g>L?(iyf1oN_~Pyf4Zg`B+3x2bxC9)tJQA zj5Nv1pu>Ezg+2y8OATiQ(H@Z_UXrTHJ1O>@3`&}WSVrrq z^JK1Bj%ut-Rhwg9dJKTDC3mO|-GYw^TV)FpX($H;2^WcBG}j;JbCMoK_`y*>)s>pq zQUi&EWl=iw`cBFQ7EH?A&1heX*2^d380~JYd(Lf#FqSE7PR)pE;3%mOkt%#{G#Iu7 zJV(EhN_+aD`(n1&RJ@3P}(DWE~ zqM^=J8=a)(kN3*iE1fI?kC)cEtS;}sfD#1B!I{k zQ|TNXfCd>UMSRC6yU?+)*AP$ASII;)oFtmnpv$7kv1Qy4O3nRlOq`B_yTrPlo_|!G zSg2N*fV#gkU5ZIwAkY+lV8)0rOun@u_E3A>eXCUk%UQ6x=flF-_~s_%3%6)d$@zuL zH)s%>u?LtZXA19zxeMr$v~Hk3Mqgk@FQSRL&(7WeTd7U*49C8GFGtH8b&QGGcCi;f=4zH zf4Gni@a>Rv0sQElaY$S0Q{Z+Tws$jo*5{B-A z4}yS^PPp!#PPFd5x7crd&A^5Gp)r}l>zy!E3t#Kt7; z(U$|swuU}%x3FG5s~7#KXB~!+eS;(5I(xxiee8g@K2CD{(mlh! zPwICm{RR{gXOGda2U)clker@!iIE_ls;l~Dem)ncow5@m=(KB4ysT<+$XjPYCz` zVSyqHp6$m+rNrK?_^LXW0FP9%2PSRP*60%b^P9Q5;g96;fKj=oFKWJ)e9ri_>_3qT z3QGMY&@Qd<;oyZD@KKgt$#FpOyI};l1G?dNgu6IDep#t~G|g0Ta%xm2Wg~_xj%Ulp z1fcDJQ^4IhEX(lrDAHflg{=M7-ezdQ;ObGiJb8S3W!8(Gq|lTLK-Qs9`F{#K�!B zw(rwR=qSB~qJStQp#`a-OGkz{H(w~RDkt-9l{73QRD=K!$IWKLOUbt*q${vLrQoj!NblRK|7$`ax z+D6GF!BfLzi+b+2;DqFqD*B7~)b)1AC0A~gUfD?dZzx^dcq!gm0-XQWbW*Z_;JMKl z_ssy*l|$m2PqjFMvj33Q@PhDk_mRiNqpQq`m%UHTrh3_;=#B8^5Ur=2JWlQQK=3K< zvXyV=JNLYme3xr+PK4^U3Ep)3%+~zx$IQz1#+nb=?0z7Qc>;9c*n?uN#~j^B)J7xR zhM4XXOrs2(knJ(d+)&LY>Dl4wnl4W*t`SBmtj7ZJ@d^8cEbsSz2~d^&Qb8oGeHyfg zvh39%@SoU zpB}7z)>_;Xn0s^7BGlTQShe7>&bFS26uS&NpinTx)!nY43bQ4oB!eczDT;RPI7ZF) zalx~~yf(HZpF(s>1lkDf<5U*%l%k$2ZV5b=|MF>Q-YYHrD8!fS;#r^&&1y{a1?R)C z3o8Xuy#WnthGxWW#jbOE1|O$h>d%MY-pskTZ2A+&jnpQ%JFo?RU3u~dvN^s!qS9GamKSLGZ7a z8b!@@L&snWs_-#o)Q3U*H}T5V@fIC;gbU@911ES5H+s|_K^hAERQXV!JOgnyF69fl z2R-i&cHrt1f>}ZWY%fsvBqy^=$-wCKvLxu<$F*{&oOwu#S5@MKSzLB|4_qBhuWi=g zb2d@SqV4^TGibj{*lEKUopfEp#80QE2$K#Y%z4!a(%c5p=e#BT)Hl?1D zcjRQ=i06$WKb-!gt{Xwf>;;9I=bZd~1HKWcFpB2zbxz7*nyw*vnf671A9pWPg9<3z z|A_z<04YlWB7+TA$72Bb&o(FVZQrEj#l}_SK91yHfVNJB#{sIt-AO`e>V%#EHGG5t z7Ml!0W!#PECh7fi8S9~M03#EXs;Rkvikn^RG>DF5WNX<#m1%JF!6c${%4adVf2HMt z^jPSwwaALV`w-o;vNBPmP|HsLQ;Njc*{_{hZ7+GA(5d_0(Udw2k%LWP{Dc(6 zr77{OXgyY2e_RircQ1@zS+y08ODUjhfB3)CQ^C9pTRv2}|a z4spbJG+jJ<+qUvDlX9yR7D{nx^~eUN(;_$fW$bP>t;wr1-?l^g!n4;ru89w&gq0C3 zKKoQf95mCQGPPiGv4U%cXgw>#_wMy6xAZ2{i_=y!QZ2)bJGmS0myB15q-!WwezFtU z?X}UHiG|g84ZmtuDEDTGUS}+x^8H!~-YNQ2R63Sowx<2;WK!C$qyIqvrbUC0**c2@ zghI}inyDy?z2_^XEuYn~6(L=|bPZpp6AQ;?m_%NULg;%90(S=;l7z8YV6lohEGi@3 zTew1M@|kDqLqq19_jEa}!Frbm@opd97{1%xl}1Zuh_6c5MZC@QbM~|R6hXLFvs*Sc zdgr2=U1(bGr~i+mEZHgsI+2Ua1}>XD_3CqZ%xUxFH!y3?c?@X{GOU_LSvwBiBvGqL z0PVM&ev944&E|58g4_RzK}J=gnRuc&g?CUt5!uU;;Al|X)QI+ z2kj+FA|%@Ewr%SYbnU(Nf_iX#A}qXB2fb^IoV$!ai`Kbp(W7nGTubr|7cLgvYVSK7 zGi(|aLw~$8?bM@tSAz3ZOq0fd`MRb_j&9jHKDo|FNEV+-hP>v)tI#L@3X~=N5f0WU zK+z`7ogCbue5{R#ldcB$4$i75EHo=u877*mtf90GNd7=p($HJjjq`Aq+WPrt8$u48 z>wNn00nbQaWSfyn3QiMk)MZeq?ZdY7Q;1+oXy{`6qVT4+&g^jdEHfi zDrBp_RB`YwAVD?d=n{rG6DnMj`HECH?qQ#Me3DnGOnK`Qi<#+&wNiN z0j5Q$EkV#t9}iS-+i8NMVHnHD$a=%qR*>sg*zr zSNt6&3AvKpBkSqwQITWvALTolH^gLRjr9<@vtbX=ewqtR(S*on_x(TM>7icBJ)m~8 zy>+`IW}N0@{Bi~oBe`0{E+eBmoO@;auA<_p8eY&6hw>MD-?}jF-bg>m#7LtO6d_R> zj=EP3(*Qk#*AU`OmD*Vl&o)Ie1BmyGulQ3{`Fl8gJZpq%w;s&`_{q{_XnYFrW+_gN z5m!VD31y8o=wd`_v$Clf1LiLx1z+6;2Q8LnaB!?@K7wmLc76LJyZD`(VP8c_(;S9; z0kBZ#i9<}G2-sKJzS*h8ZNOJ5br<089HwL8aaR;p*|``vIbU1!xt_~ZG3lvVJL8rv zi3tTvJ!aWxr`sWW$w=!J0|5M5J`Yp|03)KriRx(K@`#M^A%i`E3B4hc<~Sl@ZP?^j zd$wtr;@MYc3qm8-45fY0?N@Bi9v8J-nM*201)v==|B^Ig7E#SmD*_nk2=X+o&Bs{a1na#-hVR+YG)hH^n9 zN3xa)!ADRDmmDEp1DX+Stt9>N`p^m{w~tAm-j9`OXDRSf_v!ag@-41w%*Rx1ElsXo5Hl3x)ZWFBJ#09ZX} zr#v>cN+no`eS*-iVwpZ*zKCSH8B#k>O%lFM5Bv#c0Fygv;FlVBkSy7 zmg@Ea*}(7@XlIV^A=wp@N%`hFe)h3eprUVtQB)okdf`bhI*-!vbo2!q!L^{yq}Z|B zypnFF0s=N7at5j-s(}tDzxnd9#s}t_pz1p8o6$=%+E|pld2jZACgYLKO=;iPC z#H5;7$&o7^yvW-xoR>aD>%}F@8ZJmgn?oh8x(m#2Kdf;)e4)#`-V~E9k3z>2GCkA> zrc*2Fu}9I_^CDjX2`pIyuRu&1Ga5$t_p>5*67_)uH{Lg#a7bvIwu;f@&$ju5Ykjzw z(lFXiDpe4n>MmmKwq~JRzB{X0>t=o{;W$=o8p*B2O30zl=TJoJi6_N2lWoUTlFra; zq(c*UaKkrJ1$O#>Z!?V*AX(on-9cX4PHBY_&kO z(4}}sWlJ#zkXE@CZcnGx1#b_x<&&WsaLI#L>!E!(X*O+X_yP=abq>ejiF2Aipl9PP zIckw>>z@n^n$&*yZO&=emdG~mXh3SSB*23L!va5fm%kAk!NP%)AVn{$PvL&CG}oy& z^UJTZ*`$?cDog=7$8y^s*(YxwU?7Ax72j5n_SWG2GMkfT8w+jUkmCo2WH{8UlwoX~ z0fomr+=pD4$y~(syk*_meO%OJx$-@Hcde z9CfLJ{tU}=dwg0W`9P^T&VVjZDRN*?MVQJ4s#2(AYVEanAH72(v}Bsg%DbaA=2TSO z>w~dca-Q#%>&F`u(e1ZQ6>FAmmhRGGapsp~<7aZbr!qy;b>psV-Q#v=lOS8w@xp?< zmmCsvVzMWiItMfMOSnfwaZGhtObLw-DPP^eU;05qEgqI(1?(YVhn*{^>OD6t^;7NB zxi(Q{|EAfYq^;7eZ!4_tWQrsXQzd$we3nE!)h6x!*1G6U=@BEOUg2Y!VfT>vTW)kfb%rGXBUwuEPA}e3eaB zY%xx;ZBc+6Ls1O-6d-eBReGhpyk5=^-rZp3#KvH(6pL!(yfYVvz`@uVWDE)A7 zJb#p-ktk=OuzX&PCnw2(M2I5c^fUOwLj3PUw>9_E{+Q za7f&7|4x5yQ3Z<&rnl0DzRFDKeZ#gd-2!ul2B`U!fPU}U!|XUxV{aJ4rcRkZ{x`o_ z%L%4Wy(^uRDtza!Lqa?O=q{z{G(SnsHD8-*&gy24&oW4PA09_ehR-8A4ivUbpUBAC zbP*#NhvX%c#U=0vAiy`e23=XR%UM`wukf&d0(#*V6DePVe~ID*wsq}{8U3#-mUXGsO6r^qR9V^Kh3qsME* zg6Ho2hU6*z>jR*hW+#H83~UVOlvEY60=j4NiB|QP^#=T(C7oyWT7|C^LthuGG}QyBw&f9-?e|)CKR*`SZlQkZ#2 zEcZ(-lY#yN$Y6s_&tTtRLr!Pii;3J2U>sfo}u30<|T-(}w>zbS1S@hlSB zbt!*RY86PuqmFq|)@1;pGx`=mMQ)MPNXe+$`m!DeprA?_F($@J6D@LQ+qw5s>51;< z8AVzN{WJ5E9d|pg>31awVE-0GFQZwSuB7)Kx45f1d6A${dW}oS67I&>ix0KP*6cS} zi0vTbC$2Q_c9v}{A-Z{=wHte4qw~*&8UKlj;z6JH8Ii6t25P+9UR>V#i(ZS59*>2x zI@DbEzz?{Yk?>MXp)Ekw7)ij!KmXao^nogsg`gAo01p8b`DyW`n{*mIce>g2J#{3r z!TN+B6|!20F23LcKM%0->3;OAvCQu@tZNf^+g?}Vo6kj!YbhtYPwrWF{@e$xi_Qt& zH2e?27o!tz++cplQ~5LE`he8-<{$57T=XUUqC4dyy|MPxsU^4K?pi!Uq*-}NY%XTa z(h<|K*@5aW#36&{%BMELo{h_CIv7S%PbhFcw5-i-)IoKNCk2NpadkeNl~k_jVdjJp z-eb_eEkvE;GRWb(*Ow)kgZ<;a`d-MH;@hZaZEG{Nu2-MZs7xh2zH?pV9q_KlzC>kr z8ckZ@G8i$IP&xpvMN~O)<~uXg=g?=@>C$wpLF^@(A}8IAo79u4iaz+*ML{0qY$A&{ zSwrJBFGpYf3@z~o!zUhFE4*k*Is0B$%sIhiCC^83x5qfIozjJ5Sgcvw1F5P7!KYPz z1+GUi0IB{-I(&y`=EvBrKLSJ@0st>Fpxh!2esgw>;Bi`f%bO$dD zEp0fQ}D zUuF)m?blnMzHu>ixIJx~Fi+8C$W8~}krJ{Fwr>n*v~7INJ(NAn?o9RLn6+1IxaM1} zghmx&U%xf34~{ zN2)K%it>TbrQ1URofsOv%*|dQ=t!GZIO)Ag4tPN6^PkBpG;6i-1W;6wR@%#zJw9Zo zgnlnxb=SFZH3$EKXMl!XIHKQH{-aBTwS#R7$C=l9@Hg#A$B3E{qyj9Gb`2DK!U5ou zB1++qtkCHlXxyUiQ&L-hiV06gF$yL5@NB$LNw#<6f7;Sl0%=+ho~|%^k=~FBbC{K4RFil?$KW!6aR${YJ;AYQm%Dp+__GQ3;Oy=ZZU|&imfmh>mj@Xal zbn+dy5n+|;`HQ93>n@#So6KD^8qs}ODW>~FL5RQ|=%Me!YtDT_{DhKh6`h4^qRsun z#(ro+ej+BPv}dagYT?%gMc)<0aK%mJ7rYlyGOw3E+DZ=zt`<+T7nBqz(Z27b%nlxT z8p|HEl+XGok%88R{owR-o|QuGoA2$|7wkmdCS*oVOWu0tiovI<87=aC&FiS9c}v4Z zk7RRAZ|(KKrlsAUCq^&zvlz;)7<${a)uQ1I}iAVS2;ZCYv8rY;g~D~YI{_qyDHvK2hK+;f^)U0rcgZr6Q1DOK=E znPtyzgP}GNt}Fw7F)W7^4Cwt=rV~?7%e#SeNeUz1y*VA`KXzPgN1+<7TCZ+1!u^Bj z&tdOKs~q+{67drK_N})%jMfUf?Fy4n-m{ubra_5)>NoXdq|f-11VgG}oe$2h1kRXD z2OWA4m34tGRuC(Q3%-j7>2?4AiU9iq&`pS-Fx3Yb( z{g!I00H=8pN(y(FpIGsl%*n07?Ksr!9qauCO?w*VShdB+$Bz1B^GC?g>SF}zs>Oo# z9Nm6hgicf8St)62XdA=N_(gTP+p@{wX9Z6WmtCF9`pXcev%@p37FuzEQM2UTadHbf zxyPY`_(5bTow5#=k~##X*Gt(;X-X;V>4t1`=j4c=EXgrE`AYnj{NRq48BQI((i64N zjZo&$nJ0$0E<`gFUO0S|Ubx?batGw*@j!SeHaO2}XX^$RbhEML{|_$ri>Uk+&gWujt*r+%gnM{8AY6f9kRVt@P!#xx zPu|TzuP|?y0+v{(Sm?pyJR~zt8TOIE2 zi}0}V1PcFc`hvl9H17Ua{WYcg|I07t=K;6HQkcS6X!SoAP)t-5JDx4@e>4#Y1cc4@ z>jJv|t$`q7P%OXrZ%q`6rBQ#=K-lH_U4w{;{m~Z-kYdaHZ9H-D-}4HCA!6A3{_nWI zTL0D{P+{=zeLilR}6$jMSs_XCH{;P`?C%)G0{KfB8J^Fzl{fhLjDg;Tmt*U_*WeesEGLQc_C17 zENA*#oCN3>qWZ7C*!zK{pMTfH{|`+<;`cZau*4rZu-YGMAOZpXa%280FIK}6xW8-I z$^5B_{a%L%1pL3(-pj+%!5QuW_{AIRIRs$078dQjk3e_1i zP|8Zw+FHa)LKM3RM8&XY3=4z6U{RoGAAz(O22Jrt6`5)@p(+m4h`fC%4K!imk M05@(ZX)6Q%AFAg=K>z>% literal 0 HcmV?d00001 From 3df5321e0045dfd934a5c1dedf4d5c54b1845b42 Mon Sep 17 00:00:00 2001 From: charlie sievers Date: Tue, 10 Sep 2019 16:56:31 -0700 Subject: [PATCH 117/192] Fixed extraneous paragraph in doc/src/fix_langevin.tct --- doc/src/fix_langevin.txt | 10 ---------- 1 file changed, 10 deletions(-) diff --git a/doc/src/fix_langevin.txt b/doc/src/fix_langevin.txt index 1e50b3a8ba..c681b315f1 100644 --- a/doc/src/fix_langevin.txt +++ b/doc/src/fix_langevin.txt @@ -263,16 +263,6 @@ The 2GJ half-step velocity {vhalf} samples the correct velocity distribution for Results of simulations using the {gjf} option with both {vfull} and {vhalf} compared to other available thermostats are shown in the LAMMPS directory: examples/gjf. -As an example of why to use the {gjf} keyword, for molecules containing C-H -bonds, configurational properties generated with dt = 2.5 fs and tdamp -= 100 fs are indistinguishable from dt = 0.5 fs. Because the velocity -distribution systematically decreases with increasing timestep, the -method should not be used to generate properties that depend on the -velocity distribution, such as the velocity auto-correlation function -(VACF). In this example, the velocity distribution at dt = 2.5fs -generates an average temperature of 220 K, instead of 300 K. - - :line Styles with a {gpu}, {intel}, {kk}, {omp}, or {opt} suffix are From 90296b76e38eb8c9fe28101b33e0b2eb8b99c57f Mon Sep 17 00:00:00 2001 From: charlie sievers Date: Tue, 10 Sep 2019 17:11:49 -0700 Subject: [PATCH 118/192] Added a readme to the md results folder --- examples/gjf/molecular_dynamics_results/README.md | 5 +++++ 1 file changed, 5 insertions(+) create mode 100644 examples/gjf/molecular_dynamics_results/README.md diff --git a/examples/gjf/molecular_dynamics_results/README.md b/examples/gjf/molecular_dynamics_results/README.md new file mode 100644 index 0000000000..cd3fe81b53 --- /dev/null +++ b/examples/gjf/molecular_dynamics_results/README.md @@ -0,0 +1,5 @@ +# LAMMPS GJF-2GJ THERMOSTAT EXAMPLE + +## GJF-2GJ THERMOSTAT + +This directory contain a series of graphs, which contain the results from numermous molecular dynamics simulations. All simulations are run in the NVT ensemble. Two systems are reported, guaiacol and argon. The damping parameter and the timestep are varied. Also the temperature is varied for argon. GJF U is the half-step velocity and GJF V is the onsite velocity. GJF U and GJF V represent exactly the same configurational statistics. From 7aab3797b33537284bff940291121652ba756bf5 Mon Sep 17 00:00:00 2001 From: charlie sievers Date: Tue, 10 Sep 2019 17:14:44 -0700 Subject: [PATCH 119/192] Updated MD results readme --- examples/gjf/molecular_dynamics_results/README.md | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/examples/gjf/molecular_dynamics_results/README.md b/examples/gjf/molecular_dynamics_results/README.md index cd3fe81b53..70f80e3e56 100644 --- a/examples/gjf/molecular_dynamics_results/README.md +++ b/examples/gjf/molecular_dynamics_results/README.md @@ -1,5 +1,5 @@ -# LAMMPS GJF-2GJ THERMOSTAT EXAMPLE +# LAMMPS GJF-2GJ MOLECULAR DYNAMICS RESULTS ## GJF-2GJ THERMOSTAT -This directory contain a series of graphs, which contain the results from numermous molecular dynamics simulations. All simulations are run in the NVT ensemble. Two systems are reported, guaiacol and argon. The damping parameter and the timestep are varied. Also the temperature is varied for argon. GJF U is the half-step velocity and GJF V is the onsite velocity. GJF U and GJF V represent exactly the same configurational statistics. +This directory contains a series of graphs, which display the results from numermous molecular dynamics simulations. All simulations are run in the NVT ensemble. Two systems are reported, guaiacol and argon. The damping parameter and the timestep are varied. Also the temperature is varied for argon. GJF U is the half-step velocity (vhalf) and GJF V is the onsite velocity (vfull). GJF U and GJF V represent exactly the same configurational statistics. From 1e8e34f33d6544c8667ea6b7a6263f129e5ff74a Mon Sep 17 00:00:00 2001 From: charlie sievers Date: Tue, 10 Sep 2019 17:34:49 -0700 Subject: [PATCH 120/192] appended fix_langevin.txt documentation --- doc/src/fix_langevin.txt | 7 +++++++ 1 file changed, 7 insertions(+) diff --git a/doc/src/fix_langevin.txt b/doc/src/fix_langevin.txt index c681b315f1..382c2360d9 100644 --- a/doc/src/fix_langevin.txt +++ b/doc/src/fix_langevin.txt @@ -263,6 +263,13 @@ The 2GJ half-step velocity {vhalf} samples the correct velocity distribution for Results of simulations using the {gjf} option with both {vfull} and {vhalf} compared to other available thermostats are shown in the LAMMPS directory: examples/gjf. +This updated implementation of the {gjf} thermostat includes the choice between +outputting either the on-site {vfull} or half-step {vhalf} velocity. The on-site +velocity has been updated to be the GJF on-site velocity, and the half-step +velocity is the statistically correct 2GJ velocity. The implementation +also takes advantage of Gaussian distributed random numbers in order to achieve +correct fluctuations. + :line Styles with a {gpu}, {intel}, {kk}, {omp}, or {opt} suffix are From ae1054a243786775a417f0fd44712f2df86d4e21 Mon Sep 17 00:00:00 2001 From: Axel Kohlmeyer Date: Wed, 11 Sep 2019 14:17:53 -0400 Subject: [PATCH 121/192] change formatting so that sphinx is happier --- doc/src/pair_local_density.txt | 22 +++++++++++----------- 1 file changed, 11 insertions(+), 11 deletions(-) diff --git a/doc/src/pair_local_density.txt b/doc/src/pair_local_density.txt index f9a410c3be..8703bf11ff 100644 --- a/doc/src/pair_local_density.txt +++ b/doc/src/pair_local_density.txt @@ -142,21 +142,21 @@ Line 2: comment or blank (ignored) Line 3: N_LD N_rho (# of LD potentials and # of tabulated values, single space separated) Line 4: blank (ignored) Line 5: R1(k) R2(k) (lower and upper cutoffs, single space separated) -Line 6: central-types (central atom types, single space separated) -Line 7: neighbor-types (neighbor atom types single space separated) -Line 8: rho_min rho_max drho (min, max and diff. in tabulated rho values, single space separated) -Line 9: F(k)(rho_min + 0.drho) -Line 10: F(k)(rho_min + 1.drho) -Line 11: F(k)(rho_min + 2.drho) -............ +Line 6: central-types (central atom types, single space separated) +Line 7: neighbor-types (neighbor atom types single space separated) +Line 8: rho_min rho_max drho (min, max and diff. in tabulated rho values, single space separated) +Line 9: F(k)(rho_min + 0.drho) +Line 10: F(k)(rho_min + 1.drho) +Line 11: F(k)(rho_min + 2.drho) +... Line 9+N_rho: F(k)(rho_min + N_rho . drho) -Line 10+N_rho: blank (ignored) :ul +Line 10+N_rho: blank (ignored) :pre -Block 2 :ul +Block 2 :pre -Block 3 :ul +Block 3 :pre -Block N_LD :ul +Block N_LD :pre Lines 5 to 9+N_rho constitute the first block. Thus the input file is separated (by blank lines) into N_LD blocks each representing a separate LD potential and From 1631ecb3fecd44c83ee8d1f6d54c6c1009c15e16 Mon Sep 17 00:00:00 2001 From: Axel Kohlmeyer Date: Wed, 11 Sep 2019 14:18:27 -0400 Subject: [PATCH 122/192] integrate pair style local density into manual builds --- doc/src/Commands_pair.txt | 1 + doc/src/lammps.book | 1 + doc/src/pair_style.txt | 1 + doc/src/pairs.txt | 1 + 4 files changed, 4 insertions(+) diff --git a/doc/src/Commands_pair.txt b/doc/src/Commands_pair.txt index 47d4c40d8e..e6ebd21987 100644 --- a/doc/src/Commands_pair.txt +++ b/doc/src/Commands_pair.txt @@ -166,6 +166,7 @@ OPT. "lj/smooth/linear (o)"_pair_lj_smooth_linear.html, "lj/switch3/coulgauss/long"_pair_lj_switch3_coulgauss.html, "lj96/cut (go)"_pair_lj96.html, +"local/density"_pair_local_density.html, "lubricate (o)"_pair_lubricate.html, "lubricate/poly (o)"_pair_lubricate.html, "lubricateU"_pair_lubricateU.html, diff --git a/doc/src/lammps.book b/doc/src/lammps.book index 3c856bde19..9868c8f299 100644 --- a/doc/src/lammps.book +++ b/doc/src/lammps.book @@ -611,6 +611,7 @@ pair_lj_smooth.html pair_lj_smooth_linear.html pair_fep_soft.html pair_lj_switch3_coulgauss.html +pair_local_density.html pair_lubricate.html pair_lubricateU.html pair_mdf.html diff --git a/doc/src/pair_style.txt b/doc/src/pair_style.txt index 1b8e6d46ec..7ba982cd2d 100644 --- a/doc/src/pair_style.txt +++ b/doc/src/pair_style.txt @@ -228,6 +228,7 @@ accelerated styles exist. "lj/smooth/linear"_pair_lj_smooth_linear.html - linear smoothed LJ potential "lj/switch3/coulgauss"_pair_lj_switch3_coulgauss - smoothed LJ vdW potential with Gaussian electrostatics "lj96/cut"_pair_lj96.html - Lennard-Jones 9/6 potential +"local/density"_pair_local_density.html - generalized basic local density potential "lubricate"_pair_lubricate.html - hydrodynamic lubrication forces "lubricate/poly"_pair_lubricate.html - hydrodynamic lubrication forces with polydispersity "lubricateU"_pair_lubricateU.html - hydrodynamic lubrication forces for Fast Lubrication Dynamics diff --git a/doc/src/pairs.txt b/doc/src/pairs.txt index f36a87dea3..1f8f130e48 100644 --- a/doc/src/pairs.txt +++ b/doc/src/pairs.txt @@ -66,6 +66,7 @@ Pair Styles :h1 pair_lj_smooth pair_lj_smooth_linear pair_lj_switch3_coulgauss + pair_local_density pair_lubricate pair_lubricateU pair_mdf From 5d0c86be48dff6fc45966aa2a130e049487abe1c Mon Sep 17 00:00:00 2001 From: Axel Kohlmeyer Date: Thu, 12 Sep 2019 07:33:22 -0400 Subject: [PATCH 123/192] add omitted cmake entries for recent KOKKOS package changes --- cmake/Modules/Packages/KOKKOS.cmake | 2 ++ 1 file changed, 2 insertions(+) diff --git a/cmake/Modules/Packages/KOKKOS.cmake b/cmake/Modules/Packages/KOKKOS.cmake index 0e5bf70a41..cc1e051629 100644 --- a/cmake/Modules/Packages/KOKKOS.cmake +++ b/cmake/Modules/Packages/KOKKOS.cmake @@ -17,6 +17,8 @@ if(PKG_KOKKOS) ${KOKKOS_PKG_SOURCES_DIR}/atom_vec_kokkos.cpp ${KOKKOS_PKG_SOURCES_DIR}/comm_kokkos.cpp ${KOKKOS_PKG_SOURCES_DIR}/comm_tiled_kokkos.cpp + ${KOKKOS_PKG_SOURCES_DIR}/min_kokkos.cpp + ${KOKKOS_PKG_SOURCES_DIR}/min_linesearch_kokkos.cpp ${KOKKOS_PKG_SOURCES_DIR}/neighbor_kokkos.cpp ${KOKKOS_PKG_SOURCES_DIR}/neigh_list_kokkos.cpp ${KOKKOS_PKG_SOURCES_DIR}/neigh_bond_kokkos.cpp From 1e0cd0b202242dec16c59390a730b02e5a3d41c0 Mon Sep 17 00:00:00 2001 From: Axel Kohlmeyer Date: Thu, 12 Sep 2019 12:30:22 -0400 Subject: [PATCH 124/192] separate out svector handling to new virtual functions, so it can be handled differently for pair styles hybrid and hybrid/overlay --- src/pair_hybrid.cpp | 36 ++++++++++++++++++++------- src/pair_hybrid.h | 3 +++ src/pair_hybrid_overlay.cpp | 49 +++++++++++++++++++++++++++++++++++++ src/pair_hybrid_overlay.h | 3 +++ 4 files changed, 82 insertions(+), 9 deletions(-) diff --git a/src/pair_hybrid.cpp b/src/pair_hybrid.cpp index 8374e0cfe6..3c619b6c95 100644 --- a/src/pair_hybrid.cpp +++ b/src/pair_hybrid.cpp @@ -362,13 +362,21 @@ void PairHybrid::flags() if (styles[m]->tip4pflag) tip4pflag = 1; if (styles[m]->compute_flag) compute_flag = 1; } + init_svector(); +} +/* ---------------------------------------------------------------------- + initialize Pair::svector array +------------------------------------------------------------------------- */ + +void PairHybrid::init_svector() +{ // single_extra = list all sub-style single_extra // allocate svector single_extra = 0; - for (m = 0; m < nstyles; m++) - single_extra += styles[m]->single_extra; + for (int m = 0; m < nstyles; m++) + single_extra = MAX(single_extra,styles[m]->single_extra); if (single_extra) { delete [] svector; @@ -759,7 +767,6 @@ double PairHybrid::single(int i, int j, int itype, int jtype, fforce = 0.0; double esum = 0.0; int n = 0; - if (single_extra) memset(svector,0,single_extra*sizeof(double)); for (int m = 0; m < nmap[itype][jtype]; m++) { if (rsq < styles[map[itype][jtype][m]]->cutsq[itype][jtype]) { @@ -774,18 +781,29 @@ double PairHybrid::single(int i, int j, int itype, int jtype, esum += styles[map[itype][jtype][m]]-> single(i,j,itype,jtype,rsq,factor_coul,factor_lj,fone); fforce += fone; - - // copy substyle extra values into hybrid's svector - - if (single_extra && styles[map[itype][jtype][m]]->single_extra) - for (int l = 0; l < styles[map[itype][jtype][m]]->single_extra; l++) - svector[n++] = styles[map[itype][jtype][m]]->svector[l]; } } + if (single_extra) copy_svector(itype,jtype); return esum; } +/* ---------------------------------------------------------------------- + copy Pair::svector data +------------------------------------------------------------------------- */ + +void PairHybrid::copy_svector(int itype, int jtype) +{ + memset(svector,0,single_extra*sizeof(double)); + + // there is only one style in pair style hybrid for a pair of atom types + Pair *this_style = styles[map[itype][jtype][0]]; + + for (int l = 0; this_style->single_extra; ++l) { + svector[l] = this_style->svector[l]; + } +} + /* ---------------------------------------------------------------------- modify parameters of the pair style and its sub-styles ------------------------------------------------------------------------- */ diff --git a/src/pair_hybrid.h b/src/pair_hybrid.h index 074517a859..61e961ddcb 100644 --- a/src/pair_hybrid.h +++ b/src/pair_hybrid.h @@ -77,6 +77,9 @@ class PairHybrid : public Pair { void allocate(); void flags(); + virtual void init_svector(); + virtual void copy_svector(int,int); + void modify_special(int, int, char**); double *save_special(); void set_special(int); diff --git a/src/pair_hybrid_overlay.cpp b/src/pair_hybrid_overlay.cpp index e67cb677af..4c2acfe8ba 100644 --- a/src/pair_hybrid_overlay.cpp +++ b/src/pair_hybrid_overlay.cpp @@ -102,3 +102,52 @@ void PairHybridOverlay::coeff(int narg, char **arg) if (count == 0) error->all(FLERR,"Incorrect args for pair coefficients"); } + + +/* ---------------------------------------------------------------------- + we need to handle Pair::svector special for hybrid/overlay +------------------------------------------------------------------------- */ + +void PairHybridOverlay::init_svector() +{ + // single_extra = list all sub-style single_extra + // allocate svector + + single_extra = 0; + for (int m = 0; m < nstyles; m++) + single_extra += styles[m]->single_extra; + + if (single_extra) { + delete [] svector; + svector = new double[single_extra]; + } +} + +/* ---------------------------------------------------------------------- + we need to handle Pair::svector special for hybrid/overlay +------------------------------------------------------------------------- */ + +void PairHybridOverlay::copy_svector(int itype, int jtype) +{ + int n=0; + Pair *this_style; + + // fill svector array. + // copy data from active styles and use 0.0 for inactive ones + for (int m = 0; m < nstyles; m++) { + for (int k = 0; k < nmap[itype][jtype]; ++k) { + if (m == map[itype][jtype][k]) { + this_style = styles[m]; + } else { + this_style = NULL; + } + } + for (int l = 0; l < styles[m]->single_extra; ++l) { + if (this_style) { + svector[n++] = this_style->svector[l]; + } else { + svector[n++] = 0.0; + } + } + } +} diff --git a/src/pair_hybrid_overlay.h b/src/pair_hybrid_overlay.h index 934be05365..f1514ea079 100644 --- a/src/pair_hybrid_overlay.h +++ b/src/pair_hybrid_overlay.h @@ -29,6 +29,9 @@ class PairHybridOverlay : public PairHybrid { PairHybridOverlay(class LAMMPS *); virtual ~PairHybridOverlay() {} void coeff(int, char **); + + void init_svector(); + void copy_svector(int,int); }; } From fa164fffba94898a10bf182c74a84bd27d5a41fa Mon Sep 17 00:00:00 2001 From: Axel Kohlmeyer Date: Thu, 12 Sep 2019 13:59:05 -0400 Subject: [PATCH 125/192] explain new semantics for accessing pN for hybrid styles --- doc/src/compute_pair_local.txt | 17 ++++++++++++----- 1 file changed, 12 insertions(+), 5 deletions(-) diff --git a/doc/src/compute_pair_local.txt b/doc/src/compute_pair_local.txt index baf394505f..5b507d447c 100644 --- a/doc/src/compute_pair_local.txt +++ b/doc/src/compute_pair_local.txt @@ -62,10 +62,17 @@ pair styles do not define any additional quantities, so N = 0. An example of ones that do are the "granular pair styles"_pair_gran.html which calculate the tangential force between two particles and return its components and magnitude acting on atom I for N = 1,2,3,4. See -individual pair styles for details. When using hybrid pair styles, -these quantities are the combined lists of the individual quantities -for the pair styles active for a given pair of atom types padded with -zeros. +individual pair styles for details. When using pair style {hybrid}, +the output will be that of the Nth quantity from the active sub-style +active or 0.0. The maximum allowed N is the maximum of any sub-style. +When using pair style {hybrid/overlay} all additional properties of +all pair styles are available for output, but the values of inactive +sub-styles for a given pair of atom types will be 0.0. Thus if there +are, for example, 3 sub-styles and 2 of them have additional output +(3 and 4 items, respectively), the maximum N would be 7 and {p1}, {p2}, +and {p3} would refer to the first 3 additional properties and the +remaining allowed parameters {p4} to {p7} would address properties {p1} +to {p4} of the second sub-style with additional properties. The value {dist} will be in distance "units"_units.html. The value {eng} will be in energy "units"_units.html. The values {force}, {fx}, @@ -129,7 +136,7 @@ options. The output for {dist} will be in distance "units"_units.html. The output for {eng} will be in energy "units"_units.html. The output for {force}, {fx}, {fy}, and {fz} will be in force "units"_units.html. -The outpur for {pN} will be in whatever units the pair style defines. +The output for {pN} will be in whatever units the pair style defines. [Restrictions:] none From e413aaf2172c44a7d81f3204917073a782704ed4 Mon Sep 17 00:00:00 2001 From: Axel Kohlmeyer Date: Thu, 12 Sep 2019 14:37:42 -0400 Subject: [PATCH 126/192] add support for optionally including unit information in standard dump files --- src/COMPRESS/dump_atom_gz.cpp | 19 +++++++++---------- src/COMPRESS/dump_custom_gz.cpp | 19 +++++++++---------- src/dump.cpp | 11 +++++++++++ src/dump.h | 2 ++ src/dump_atom.cpp | 10 ++++++++-- src/dump_custom.cpp | 9 ++++++++- src/dump_local.cpp | 5 ++++- 7 files changed, 51 insertions(+), 24 deletions(-) diff --git a/src/COMPRESS/dump_atom_gz.cpp b/src/COMPRESS/dump_atom_gz.cpp index ef7e6583be..78f2c6d4f7 100644 --- a/src/COMPRESS/dump_atom_gz.cpp +++ b/src/COMPRESS/dump_atom_gz.cpp @@ -108,27 +108,26 @@ void DumpAtomGZ::openfile() void DumpAtomGZ::write_header(bigint ndump) { if ((multiproc) || (!multiproc && me == 0)) { + if (unit_flag && !unit_count) { + ++unit_count; + gzprintf(gzFp,"ITEM: UNITS\n%s\n",update->unit_style); + } + gzprintf(gzFp,"ITEM: TIMESTEP\n"); + gzprintf(gzFp,BIGINT_FORMAT "\n",update->ntimestep); + gzprintf(gzFp,"ITEM: NUMBER OF ATOMS\n"); + gzprintf(gzFp,BIGINT_FORMAT "\n",ndump); if (domain->triclinic == 0) { - gzprintf(gzFp,"ITEM: TIMESTEP\n"); - gzprintf(gzFp,BIGINT_FORMAT "\n",update->ntimestep); - gzprintf(gzFp,"ITEM: NUMBER OF ATOMS\n"); - gzprintf(gzFp,BIGINT_FORMAT "\n",ndump); gzprintf(gzFp,"ITEM: BOX BOUNDS %s\n",boundstr); gzprintf(gzFp,"%g %g\n",boxxlo,boxxhi); gzprintf(gzFp,"%g %g\n",boxylo,boxyhi); gzprintf(gzFp,"%g %g\n",boxzlo,boxzhi); - gzprintf(gzFp,"ITEM: ATOMS %s\n",columns); } else { - gzprintf(gzFp,"ITEM: TIMESTEP\n"); - gzprintf(gzFp,BIGINT_FORMAT "\n",update->ntimestep); - gzprintf(gzFp,"ITEM: NUMBER OF ATOMS\n"); - gzprintf(gzFp,BIGINT_FORMAT "\n",ndump); gzprintf(gzFp,"ITEM: BOX BOUNDS xy xz yz %s\n",boundstr); gzprintf(gzFp,"%g %g %g\n",boxxlo,boxxhi,boxxy); gzprintf(gzFp,"%g %g %g\n",boxylo,boxyhi,boxxz); gzprintf(gzFp,"%g %g %g\n",boxzlo,boxzhi,boxyz); - gzprintf(gzFp,"ITEM: ATOMS %s\n",columns); } + gzprintf(gzFp,"ITEM: ATOMS %s\n",columns); } } diff --git a/src/COMPRESS/dump_custom_gz.cpp b/src/COMPRESS/dump_custom_gz.cpp index 9c30f4742f..7eb77cb697 100644 --- a/src/COMPRESS/dump_custom_gz.cpp +++ b/src/COMPRESS/dump_custom_gz.cpp @@ -108,27 +108,26 @@ void DumpCustomGZ::openfile() void DumpCustomGZ::write_header(bigint ndump) { if ((multiproc) || (!multiproc && me == 0)) { + if (unit_flag && !unit_count) { + ++unit_count; + gzprintf(gzFp,"ITEM: UNITS\n%s\n",update->unit_style); + } + gzprintf(gzFp,"ITEM: TIMESTEP\n"); + gzprintf(gzFp,BIGINT_FORMAT "\n",update->ntimestep); + gzprintf(gzFp,"ITEM: NUMBER OF ATOMS\n"); + gzprintf(gzFp,BIGINT_FORMAT "\n",ndump); if (domain->triclinic == 0) { - gzprintf(gzFp,"ITEM: TIMESTEP\n"); - gzprintf(gzFp,BIGINT_FORMAT "\n",update->ntimestep); - gzprintf(gzFp,"ITEM: NUMBER OF ATOMS\n"); - gzprintf(gzFp,BIGINT_FORMAT "\n",ndump); gzprintf(gzFp,"ITEM: BOX BOUNDS %s\n",boundstr); gzprintf(gzFp,"%-1.16g %-1.16g\n",boxxlo,boxxhi); gzprintf(gzFp,"%-1.16g %-1.16g\n",boxylo,boxyhi); gzprintf(gzFp,"%-1.16g %-1.16g\n",boxzlo,boxzhi); - gzprintf(gzFp,"ITEM: ATOMS %s\n",columns); } else { - gzprintf(gzFp,"ITEM: TIMESTEP\n"); - gzprintf(gzFp,BIGINT_FORMAT "\n",update->ntimestep); - gzprintf(gzFp,"ITEM: NUMBER OF ATOMS\n"); - gzprintf(gzFp,BIGINT_FORMAT "\n",ndump); gzprintf(gzFp,"ITEM: BOX BOUNDS xy xz yz %s\n",boundstr); gzprintf(gzFp,"%-1.16g %-1.16g %-1.16g\n",boxxlo,boxxhi,boxxy); gzprintf(gzFp,"%-1.16g %-1.16g %-1.16g\n",boxylo,boxyhi,boxxz); gzprintf(gzFp,"%-1.16g %-1.16g %-1.16g\n",boxzlo,boxzhi,boxyz); - gzprintf(gzFp,"ITEM: ATOMS %s\n",columns); } + gzprintf(gzFp,"ITEM: ATOMS %s\n",columns); } } diff --git a/src/dump.cpp b/src/dump.cpp index 57a8decbb0..e995644a36 100644 --- a/src/dump.cpp +++ b/src/dump.cpp @@ -87,6 +87,8 @@ Dump::Dump(LAMMPS *lmp, int /*narg*/, char **arg) : Pointers(lmp) buffer_flag = 0; padflag = 0; pbcflag = 0; + unit_flag = 0; + unit_count = 0; delay_flag = 0; maxfiles = -1; @@ -545,6 +547,8 @@ void Dump::openfile() if (singlefile_opened) return; if (multifile == 0) singlefile_opened = 1; + unit_count = 0; + // if one file per timestep, replace '*' with current timestep char *filecurrent = filename; @@ -1119,6 +1123,13 @@ void Dump::modify_params(int narg, char **arg) } iarg += 2; + } else if (strcmp(arg[iarg],"units") == 0) { + if (iarg+2 > narg) error->all(FLERR,"Illegal dump_modify command"); + if (strcmp(arg[iarg+1],"yes") == 0) unit_flag = 1; + else if (strcmp(arg[iarg+1],"no") == 0) unit_flag = 0; + else error->all(FLERR,"Illegal dump_modify command"); + iarg += 2; + } else { int n = modify_param(narg-iarg,&arg[iarg]); if (n == 0) error->all(FLERR,"Illegal dump_modify command"); diff --git a/src/dump.h b/src/dump.h index bc7fd2d5a5..43855c9362 100644 --- a/src/dump.h +++ b/src/dump.h @@ -75,6 +75,8 @@ class Dump : protected Pointers { int sortcol; // 0 to sort on ID, 1-N on columns int sortcolm1; // sortcol - 1 int sortorder; // ASCEND or DESCEND + int unit_flag; // 1 if dump should contain unit information + int unit_count; // # of times the unit information was written int delay_flag; // 1 if delay output until delaystep bigint delaystep; diff --git a/src/dump_atom.cpp b/src/dump_atom.cpp index 8f09b93f1a..d5eba98078 100644 --- a/src/dump_atom.cpp +++ b/src/dump_atom.cpp @@ -209,7 +209,10 @@ void DumpAtom::header_binary_triclinic(bigint ndump) void DumpAtom::header_item(bigint ndump) { - fprintf(fp,"ITEM: UNITS\n%s\n",update->unit_style); + if (unit_flag && !unit_count) { + ++unit_count; + fprintf(fp,"ITEM: UNITS\n%s\n",update->unit_style); + } fprintf(fp,"ITEM: TIMESTEP\n"); fprintf(fp,BIGINT_FORMAT "\n",update->ntimestep); fprintf(fp,"ITEM: NUMBER OF ATOMS\n"); @@ -225,7 +228,10 @@ void DumpAtom::header_item(bigint ndump) void DumpAtom::header_item_triclinic(bigint ndump) { - fprintf(fp,"ITEM: UNITS\n%s\n",update->unit_style); + if (unit_flag && !unit_count) { + ++unit_count; + fprintf(fp,"ITEM: UNITS\n%s\n",update->unit_style); + } fprintf(fp,"ITEM: TIMESTEP\n"); fprintf(fp,BIGINT_FORMAT "\n",update->ntimestep); fprintf(fp,"ITEM: NUMBER OF ATOMS\n"); diff --git a/src/dump_custom.cpp b/src/dump_custom.cpp index 3de0e6fb3b..a99151f890 100644 --- a/src/dump_custom.cpp +++ b/src/dump_custom.cpp @@ -420,7 +420,10 @@ void DumpCustom::header_binary_triclinic(bigint ndump) void DumpCustom::header_item(bigint ndump) { - fprintf(fp,"ITEM: UNITS\n%s\n",update->unit_style); + if (unit_flag && !unit_count) { + ++unit_count; + fprintf(fp,"ITEM: UNITS\n%s\n",update->unit_style); + } fprintf(fp,"ITEM: TIMESTEP\n"); fprintf(fp,BIGINT_FORMAT "\n",update->ntimestep); fprintf(fp,"ITEM: NUMBER OF ATOMS\n"); @@ -436,6 +439,10 @@ void DumpCustom::header_item(bigint ndump) void DumpCustom::header_item_triclinic(bigint ndump) { + if (unit_flag && !unit_count) { + ++unit_count; + fprintf(fp,"ITEM: UNITS\n%s\n",update->unit_style); + } fprintf(fp,"ITEM: TIMESTEP\n"); fprintf(fp,BIGINT_FORMAT "\n",update->ntimestep); fprintf(fp,"ITEM: NUMBER OF ATOMS\n"); diff --git a/src/dump_local.cpp b/src/dump_local.cpp index 7cdc3ea16f..52a222eaeb 100644 --- a/src/dump_local.cpp +++ b/src/dump_local.cpp @@ -256,7 +256,10 @@ int DumpLocal::modify_param(int narg, char **arg) void DumpLocal::write_header(bigint ndump) { if (me == 0) { - fprintf(fp,"ITEM: UNITS\n%s\n",update->unit_style); + if (unit_flag && !unit_count) { + ++unit_count; + fprintf(fp,"ITEM: UNITS\n%s\n",update->unit_style); + } fprintf(fp,"ITEM: TIMESTEP\n"); fprintf(fp,BIGINT_FORMAT "\n",update->ntimestep); fprintf(fp,"ITEM: NUMBER OF %s\n",label); From b9af05d7f4938623b2d865407dc8ab41006d4720 Mon Sep 17 00:00:00 2001 From: Axel Kohlmeyer Date: Thu, 12 Sep 2019 14:38:09 -0400 Subject: [PATCH 127/192] add dump style local/gz to COMPRESS packages --- src/COMPRESS/dump_local_gz.cpp | 171 +++++++++++++++++++++++++++++++++ src/COMPRESS/dump_local_gz.h | 57 +++++++++++ src/dump_local.h | 6 +- 3 files changed, 231 insertions(+), 3 deletions(-) create mode 100644 src/COMPRESS/dump_local_gz.cpp create mode 100644 src/COMPRESS/dump_local_gz.h diff --git a/src/COMPRESS/dump_local_gz.cpp b/src/COMPRESS/dump_local_gz.cpp new file mode 100644 index 0000000000..801547543a --- /dev/null +++ b/src/COMPRESS/dump_local_gz.cpp @@ -0,0 +1,171 @@ +/* ---------------------------------------------------------------------- + LAMMPS - Large-scale Atomic/Molecular Massively Parallel Simulator + http://lammps.sandia.gov, Sandia National Laboratories + Steve Plimpton, sjplimp@sandia.gov + + Copyright (2003) Sandia Corporation. Under the terms of Contract + DE-AC04-94AL85000 with Sandia Corporation, the U.S. Government retains + certain rights in this software. This software is distributed under + the GNU General Public License. + + See the README file in the top-level LAMMPS directory. +------------------------------------------------------------------------- */ + +#include "dump_local_gz.h" +#include "domain.h" +#include "error.h" +#include "update.h" + +#include + +using namespace LAMMPS_NS; + +DumpLocalGZ::DumpLocalGZ(LAMMPS *lmp, int narg, char **arg) : + DumpLocal(lmp, narg, arg) +{ + gzFp = NULL; + + if (!compressed) + error->all(FLERR,"Dump local/gz only writes compressed files"); +} + + +/* ---------------------------------------------------------------------- */ + +DumpLocalGZ::~DumpLocalGZ() +{ + if (gzFp) gzclose(gzFp); + gzFp = NULL; + fp = NULL; +} + + +/* ---------------------------------------------------------------------- + generic opening of a dump file + ASCII or binary or gzipped + some derived classes override this function +------------------------------------------------------------------------- */ + +void DumpLocalGZ::openfile() +{ + // single file, already opened, so just return + + if (singlefile_opened) return; + if (multifile == 0) singlefile_opened = 1; + + // if one file per timestep, replace '*' with current timestep + + char *filecurrent = filename; + if (multiproc) filecurrent = multiname; + + if (multifile) { + char *filestar = filecurrent; + filecurrent = new char[strlen(filestar) + 16]; + char *ptr = strchr(filestar,'*'); + *ptr = '\0'; + if (padflag == 0) + sprintf(filecurrent,"%s" BIGINT_FORMAT "%s", + filestar,update->ntimestep,ptr+1); + else { + char bif[8],pad[16]; + strcpy(bif,BIGINT_FORMAT); + sprintf(pad,"%%s%%0%d%s%%s",padflag,&bif[1]); + sprintf(filecurrent,pad,filestar,update->ntimestep,ptr+1); + } + *ptr = '*'; + if (maxfiles > 0) { + if (numfiles < maxfiles) { + nameslist[numfiles] = new char[strlen(filecurrent)+1]; + strcpy(nameslist[numfiles],filecurrent); + ++numfiles; + } else { + remove(nameslist[fileidx]); + delete[] nameslist[fileidx]; + nameslist[fileidx] = new char[strlen(filecurrent)+1]; + strcpy(nameslist[fileidx],filecurrent); + fileidx = (fileidx + 1) % maxfiles; + } + } + } + + // each proc with filewriter = 1 opens a file + + if (filewriter) { + if (append_flag) { + gzFp = gzopen(filecurrent,"ab9"); + } else { + gzFp = gzopen(filecurrent,"wb9"); + } + + if (gzFp == NULL) error->one(FLERR,"Cannot open dump file"); + } else gzFp = NULL; + + // delete string with timestep replaced + + if (multifile) delete [] filecurrent; +} + +void DumpLocalGZ::write_header(bigint ndump) +{ + if ((multiproc) || (!multiproc && me == 0)) { + if (unit_flag && !unit_count) { + ++unit_count; + gzprintf(gzFp,"ITEM: UNITS\n%s\n",update->unit_style); + } + gzprintf(gzFp,"ITEM: TIMESTEP\n"); + gzprintf(gzFp,BIGINT_FORMAT "\n",update->ntimestep); + gzprintf(gzFp,"ITEM: NUMBER OF ATOMS\n"); + gzprintf(gzFp,BIGINT_FORMAT "\n",ndump); + if (domain->triclinic == 0) { + gzprintf(gzFp,"ITEM: BOX BOUNDS %s\n",boundstr); + gzprintf(gzFp,"%-1.16g %-1.16g\n",boxxlo,boxxhi); + gzprintf(gzFp,"%-1.16g %-1.16g\n",boxylo,boxyhi); + gzprintf(gzFp,"%-1.16g %-1.16g\n",boxzlo,boxzhi); + } else { + gzprintf(gzFp,"ITEM: BOX BOUNDS xy xz yz %s\n",boundstr); + gzprintf(gzFp,"%-1.16g %-1.16g %-1.16g\n",boxxlo,boxxhi,boxxy); + gzprintf(gzFp,"%-1.16g %-1.16g %-1.16g\n",boxylo,boxyhi,boxxz); + gzprintf(gzFp,"%-1.16g %-1.16g %-1.16g\n",boxzlo,boxzhi,boxyz); + } + gzprintf(gzFp,"ITEM: %s %s\n",label,columns); + } +} + +/* ---------------------------------------------------------------------- */ + +void DumpLocalGZ::write_data(int n, double *mybuf) +{ + if (buffer_flag == 1) { + gzwrite(gzFp,mybuf,sizeof(char)*n); + + } else { + int i,j; + int m = 0; + for (i = 0; i < n; i++) { + for (j = 0; j < size_one; j++) { + if (vtype[j] == INT) + gzprintf(gzFp,vformat[j],static_cast (mybuf[m])); + else gzprintf(gzFp,vformat[j],mybuf[m]); + m++; + } + gzprintf(gzFp,"\n"); + } + } +} + +/* ---------------------------------------------------------------------- */ + +void DumpLocalGZ::write() +{ + DumpLocal::write(); + if (filewriter) { + if (multifile) { + gzclose(gzFp); + gzFp = NULL; + } else { + if (flush_flag) + gzflush(gzFp,Z_SYNC_FLUSH); + } + } +} + diff --git a/src/COMPRESS/dump_local_gz.h b/src/COMPRESS/dump_local_gz.h new file mode 100644 index 0000000000..cc788863de --- /dev/null +++ b/src/COMPRESS/dump_local_gz.h @@ -0,0 +1,57 @@ +/* -*- c++ -*- ---------------------------------------------------------- + LAMMPS - Large-scale Atomic/Molecular Massively Parallel Simulator + http://lammps.sandia.gov, Sandia National Laboratories + Steve Plimpton, sjplimp@sandia.gov + + Copyright (2003) Sandia Corporation. Under the terms of Contract + DE-AC04-94AL85000 with Sandia Corporation, the U.S. Government retains + certain rights in this software. This software is distributed under + the GNU General Public License. + + See the README file in the top-level LAMMPS directory. +------------------------------------------------------------------------- */ + +#ifdef DUMP_CLASS + +DumpStyle(local/gz,DumpLocalGZ) + +#else + +#ifndef LMP_DUMP_LOCAL_GZ_H +#define LMP_DUMP_LOCAL_GZ_H + +#include "dump_local.h" +#include + +namespace LAMMPS_NS { + +class DumpLocalGZ : public DumpLocal { + public: + DumpLocalGZ(class LAMMPS *, int, char **); + virtual ~DumpLocalGZ(); + + protected: + gzFile gzFp; // file pointer for the compressed output stream + + virtual void openfile(); + virtual void write_header(bigint); + virtual void write_data(int, double *); + virtual void write(); +}; + +} + +#endif +#endif + +/* ERROR/WARNING messages: + +E: Dump local/gz only writes compressed files + +The dump local/gz output file name must have a .gz suffix. + +E: Cannot open dump file + +Self-explanatory. + +*/ diff --git a/src/dump_local.h b/src/dump_local.h index 91381ba1ec..9b15082995 100644 --- a/src/dump_local.h +++ b/src/dump_local.h @@ -29,7 +29,7 @@ class DumpLocal : public Dump { DumpLocal(LAMMPS *, int, char **); virtual ~DumpLocal(); - private: + protected: int nevery; // dump frequency to check Fix against char *label; // string for dump file header @@ -55,11 +55,11 @@ class DumpLocal : public Dump { void init_style(); int modify_param(int, char **); - void write_header(bigint); + virtual void write_header(bigint); int count(); void pack(tagint *); int convert_string(int, double *); - void write_data(int, double *); + virtual void write_data(int, double *); void parse_fields(int, char **); int add_compute(char *); From 0c52a7ed7067e8271397d2f7587709ae9cb7ca6f Mon Sep 17 00:00:00 2001 From: Axel Kohlmeyer Date: Thu, 12 Sep 2019 15:23:15 -0400 Subject: [PATCH 128/192] update documentation --- doc/src/dump.txt | 3 ++- doc/src/dump_modify.txt | 17 +++++++++++++++++ 2 files changed, 19 insertions(+), 1 deletion(-) diff --git a/doc/src/dump.txt b/doc/src/dump.txt index ff1b2dc3a6..0d08fdf471 100644 --- a/doc/src/dump.txt +++ b/doc/src/dump.txt @@ -21,7 +21,8 @@ dump ID group-ID style N file args :pre ID = user-assigned name for the dump :ulb,l group-ID = ID of the group of atoms to be dumped :l -style = {atom} or {atom/gz} or {atom/mpiio} or {cfg} or {cfg/gz} or {cfg/mpiio} or {custom} or {custom/gz} or {custom/mpiio} or {dcd} or {h5md} or {image} or {local} or {molfile} or {movie} or {netcdf} or {netcdf/mpiio} or {vtk} or {xtc} or {xyz} or {xyz/gz} or {xyz/mpiio} :l +style = {atom} or {atom/gz} or {atom/mpiio} or {cfg} or {cfg/gz} or +{cfg/mpiio} or {custom} or {custom/gz} or {custom/mpiio} or {dcd} or {h5md} or {image} or {local} or {local/gz} or {molfile} or {movie} or {netcdf} or {netcdf/mpiio} or {vtk} or {xtc} or {xyz} or {xyz/gz} or {xyz/mpiio} :l N = dump every this many timesteps :l file = name of file to write dump info to :l args = list of arguments for a particular style :l diff --git a/doc/src/dump_modify.txt b/doc/src/dump_modify.txt index 6be0d26463..11427b100e 100644 --- a/doc/src/dump_modify.txt +++ b/doc/src/dump_modify.txt @@ -50,6 +50,7 @@ keyword = {append} or {at} or {buffer} or {delay} or {element} or {every} or {fi {sfactor} arg = coordinate scaling factor (> 0.0) {thermo} arg = {yes} or {no} {tfactor} arg = time scaling factor (> 0.0) + {units} arg = {yes} or {no} {sort} arg = {off} or {id} or N or -N off = no sorting of per-atom lines within a snapshot id = sort per-atom lines by atom ID @@ -620,6 +621,21 @@ threshold criterion is met. Otherwise it is not met. :line +The {units} keyword only applies to the dump {atom}, {custom}, and +{local} styles (and their COMPRESS package versions {atom/gz}, +{custom/gz} and {local/gz}). If set to {yes}, each dump file will contain +two extra lines at the very beginning with: + +ITEM: UNITS +\ :pre + +This will output the current selected "units"_units.html style +to the dump file and thus allows visualization and post-processing +tools to determine the choice of units of the data in the dump file. +The default setting is {no}. + +:line + The {unwrap} keyword only applies to the dump {dcd} and {xtc} styles. If set to {yes}, coordinates will be written "unwrapped" by the image flags for each atom. Unwrapped means that if the atom has passed through @@ -924,6 +940,7 @@ scale = yes sort = off for dump styles {atom}, {custom}, {cfg}, and {local} sort = id for dump styles {dcd}, {xtc}, and {xyz} thresh = none +units = no unwrap = no :ul acolor = * red/green/blue/yellow/aqua/cyan From be38ef0eb09a9156a85afb014ed1268610685076 Mon Sep 17 00:00:00 2001 From: Axel Kohlmeyer Date: Thu, 12 Sep 2019 15:26:02 -0400 Subject: [PATCH 129/192] make native dump reader compatible with dump files containing ITEM: UNITS --- src/reader_native.cpp | 7 +++++++ 1 file changed, 7 insertions(+) diff --git a/src/reader_native.cpp b/src/reader_native.cpp index fba613bdd3..a4b188be5f 100644 --- a/src/reader_native.cpp +++ b/src/reader_native.cpp @@ -56,12 +56,19 @@ int ReaderNative::read_time(bigint &ntimestep) char *eof = fgets(line,MAXLINE,fp); if (eof == NULL) return 1; + // skip over unit information, if present. + + if (strstr(line,"ITEM: UNITS") == line) + read_lines(2); + if (strstr(line,"ITEM: TIMESTEP") != line) error->one(FLERR,"Dump file is incorrectly formatted"); + read_lines(1); int rv = sscanf(line,BIGINT_FORMAT,&ntimestep); if (rv != 1) error->one(FLERR,"Dump file is incorrectly formatted"); + return 0; } From a948a34f8a4397053bc71dda4d909e6cef5584f2 Mon Sep 17 00:00:00 2001 From: charlie sievers Date: Thu, 12 Sep 2019 16:34:15 -0700 Subject: [PATCH 130/192] added false positive, removed graphs from examples, updated langevin kokkos, improved diff readability in langevin --- .gitignore | 3 - doc/utils/sphinx-config/false_positives.txt | 1 + .../gjf/molecular_dynamics_results/README.md | 5 - .../argon_kinetic_energy.pdf | Bin 57606 -> 0 bytes .../argon_kinetic_energy_fluctuations.pdf | Bin 57374 -> 0 bytes .../argon_potential_energy.pdf | Bin 56655 -> 0 bytes .../argon_potential_energy_fluctuations.pdf | Bin 54630 -> 0 bytes .../guaiacol_kinetic_energy.pdf | Bin 43676 -> 0 bytes .../guaiacol_kinetic_energy_fluctuations.pdf | Bin 43786 -> 0 bytes .../guaiacol_potential_energy.pdf | Bin 43634 -> 0 bytes ...guaiacol_potential_energy_fluctuations.pdf | Bin 43267 -> 0 bytes src/KOKKOS/fix_langevin_kokkos.cpp | 178 ++++++++++++-- src/KOKKOS/fix_langevin_kokkos.h | 51 ++++ src/fix_langevin.cpp | 232 +++++++++--------- src/fix_langevin.h | 141 +++++++---- 15 files changed, 420 insertions(+), 191 deletions(-) delete mode 100644 examples/gjf/molecular_dynamics_results/README.md delete mode 100644 examples/gjf/molecular_dynamics_results/argon_kinetic_energy.pdf delete mode 100644 examples/gjf/molecular_dynamics_results/argon_kinetic_energy_fluctuations.pdf delete mode 100644 examples/gjf/molecular_dynamics_results/argon_potential_energy.pdf delete mode 100644 examples/gjf/molecular_dynamics_results/argon_potential_energy_fluctuations.pdf delete mode 100644 examples/gjf/molecular_dynamics_results/guaiacol_kinetic_energy.pdf delete mode 100644 examples/gjf/molecular_dynamics_results/guaiacol_kinetic_energy_fluctuations.pdf delete mode 100644 examples/gjf/molecular_dynamics_results/guaiacol_potential_energy.pdf delete mode 100644 examples/gjf/molecular_dynamics_results/guaiacol_potential_energy_fluctuations.pdf diff --git a/.gitignore b/.gitignore index 3e4ebcda98..f9dda49da6 100644 --- a/.gitignore +++ b/.gitignore @@ -43,6 +43,3 @@ Thumbs.db /Makefile /cmake_install.cmake /lmp - -#python example -/example/python/gjf_python diff --git a/doc/utils/sphinx-config/false_positives.txt b/doc/utils/sphinx-config/false_positives.txt index 6d5112b4c7..e99d690153 100644 --- a/doc/utils/sphinx-config/false_positives.txt +++ b/doc/utils/sphinx-config/false_positives.txt @@ -2269,6 +2269,7 @@ qoffload qopenmp qoverride qtb +quadratically quadrupolar Quant quartic diff --git a/examples/gjf/molecular_dynamics_results/README.md b/examples/gjf/molecular_dynamics_results/README.md deleted file mode 100644 index 70f80e3e56..0000000000 --- a/examples/gjf/molecular_dynamics_results/README.md +++ /dev/null @@ -1,5 +0,0 @@ -# LAMMPS GJF-2GJ MOLECULAR DYNAMICS RESULTS - -## GJF-2GJ THERMOSTAT - -This directory contains a series of graphs, which display the results from numermous molecular dynamics simulations. All simulations are run in the NVT ensemble. Two systems are reported, guaiacol and argon. The damping parameter and the timestep are varied. Also the temperature is varied for argon. GJF U is the half-step velocity (vhalf) and GJF V is the onsite velocity (vfull). GJF U and GJF V represent exactly the same configurational statistics. diff --git a/examples/gjf/molecular_dynamics_results/argon_kinetic_energy.pdf b/examples/gjf/molecular_dynamics_results/argon_kinetic_energy.pdf deleted file mode 100644 index 6943609f33f30f3ab2fbfd5dc4bcf4a904c9d30b..0000000000000000000000000000000000000000 GIT binary patch literal 0 HcmV?d00001 literal 57606 zcmagFQ+TGq(l#2~m^gW3+r}GC%!zGV6Wg|(iJeSr+cqY)`OmENeb>Ja_P+K(cXd}) zcUAYnQ}uNBO|Bp+PS4E13P(P0czbwOdY3mdFa*a2U;@|~TEg-10T^XWY|Wg_0qlQS zN&rT23u|W+$G_Ctz}ZC9#K_Lr1Rx*)=j7~YVqgR34%(DGT3s~ivi(eZz@~54uTe48?+0bYh`hL3nz*FhR z_W4(%;C1)sR+<_x9I&sv!Q;*LDBrpYEOQ?e|*2wJ)FNXdkYV(DnW2 z+uwqflTR9J1drPn$c&-1F#E{6@3vpDZ`+shj4k6HUo|neSl#uy$ZvWdeNfk|E_n{W zKJB`;i5Npuhi~e536U6|#=WoN*7utQ37b>b_rd0Vfgij&t~bMS>*`KDISDO%x_5ME z$(Lrgu#B8M*XuN(vdjHRMSqrvzPNVeBa}$C`N^F{1jTi`Y~i-SP}w(7zo|!9dcHdJ zQ=n_3Ml)!C5ceYX4=bxZ8;3N2)6_n4R-QF2@1n}qF+f_2M(CPUHC^&48& zS3c%HKI;im`SsuA9lSctT)*7Q7ma`Bu~TFlDNf_H`*Iz4=o`4M@7|-eA6WZUnaw%r zH1}s~P~s9aUbqL%A0#z)t=~*E675G>pMM?lgf?U&F{T0;N)bcR9R&W^Bd|)4sP%<3 ztji%&&9rI7DJ8HackcJG=AV`_V4l>`|{dNbcB#jm`&~ThZ@cE z2&Q@NF^`DJq};3!w-UB|xVCm^M{??NGvY~{Iga082Nk+-9~9&e4fAUUm;FIfHfwSC z-MsfpEwsNW8!Z;dag?*)sx9|Z4%TUU(XXBpX?_>`u93y8`MFfm`)6&VI6=1v#|Lin zjiX`zuF>_(SG3>r8wy4ZOpFdZQcxcTzGfC>FL4hECrA%BgW0y+%7MXpFHI=GKR_e~ zf^&OHC}d-2h81UuTYK3oI!cism5jq~DP!JVTXYoBk_TxN^h#8P5Ni}PH$5QGrGwNL zC2`I41{R6%&l48}bVEL6+W5<5d&Rs1=v)GXz|?67S=|lsp1zoJQcv~D3$^q>a{K@= zrRN9A#&8ljLe$+)2v$mfF{~jJ9fP!Wk7O@ip})t*luyhQBeKmx903-^AP2%KD0;~m zF%Q>HEF!l;0dOM8F%k(2hq4*((;%^hBf|_>+hZ6h87!t+k ziHV-vbZ{O!=*n+=(7a|9end!eNH^D)}Ew98_d!F4xts|0CbzC)mh9?*aXPX zn;By+Uz#E$UmrfyQ|sY){=lj>335T+#R*e;b@U7b0`t z8AfEqMu(HRm?*^3djvK*gmvfKFGf3B8JEU!n6fVm=8Ep7lI^+O{g+F>{%S(bEhaT7@3Kyt@KPv?fq?}9vq}=%;3Ri$Rn(h98 zDB>I#g;tYacmqF#%%VlbuxTCMUJy?~yu~5Jz@QWZjhTH0cO9<1@I+P--2n(6F*_S@ zJf|huNZH&XL8m<(onTd<(Q6i?5rbZjO%^tb!^w+oenKitgFUc1ge`n3lr6kEcg=03FXbvD4V7nA~fz`CFac+h{j%v7FM~ z?k%cdcBfGwE&oLV)2z{Tt|Ov7YVSRRot3NR$8HDvep4NSGT@qGKRWs#i)|Y+@@8SM z?0&$cvov|MJi=*}q9*_GC%Rb~H!(X79lIwX9VR~*)&v^_{$wq9!7LL5KFdpOz7%`6 z1ZTP}o98kR!yIb9Nv(Ewmvyd0hF%Z_x#a98Q`37;ni2Kz@E!uaU^+SFp6aj?UD-p9 zr@;D{M%>gycmAKd)I|+^X(-_fmf?g*+a^su>H1HgQEZp-s{FUe6yvyqU#4M*4_VbF ztD&BR^Uh%}(O?%L4K`HgjR89pz~KBeIX#3$uBZ;tLryTqUL+fDf}W5y!Fv}#C~rso z!vkwcFRJR?hd3?~N;AtpBK>nvl86s0kYBRFzWp1n-<$6Y)`$mTccy z1|p|78Z04e5EIy>dCz%P!4J1OvN6w1%Z|G-bb3zF60R1w4x(7G>l(%rxXDG97I_gU z-y*kI*A88R<_92+yY>3whmS z9-(&W)^Uv{2H;EM0l!%xz&de-bbEfSgKs1G{I-m7>m}au zNgX^D1YPy55|~BebI^^Ny5k&$Sr~t(|Ax%C!QIwe;y4bA65SxlwwRH*KIO{^Vb125 z{JelD3f8}EvpN~2>_TxHNTiiqI)B|je&`sF%Rg5N}11jv*x+1j&+A6pO{sN>ME2s3F zJ0cnY5)2sg7urB0@y#+~O;5)hh5?&_>F5&@N(-tritdR}7w3lD%YW@eb@u?c>jxk~ z=<*R>S6X_h$rzgXeclb37BJrOR^vD~oo+=gu0?LPCKCr*cRHAgTQRCxF}hkYx}61r z!FRf<8DAJ4=$Rxeq&5k4MpP@x-AkWl5^V{MPnBnQ5X*?nGtUW!M>$Bh%dg>Uj* zb-(z0-Pv^!+tz;_wY=5n2c*_KZNJZdGIobUM9KqcpD_Qt)N}412RXS6{(P5`oX(OH z!L*CQeETSk#)SG(KmnP4J?z+>@WDMBmza?w!BC`67>bnYf~Wr~v{*}*y`>CV)z*G7 ziRYz&)QbHkikA8%aVrUAfx)iI%eY^#P54=_O3Pr5(s-p*)gEz}Dg>`F_}<7AN>gg6 z!~Y|V$&*9l7?#qKY`?M-Iv`C}dn-`%Z-Gd<%d7qEDF7Af5L^QgHzP={5sEhEb={b` zw!|6JP>6G$GYlN`%eRpiwvar^TVPWjZ)vLAk{;)raF@l<>amSHWcBsuHlYks-le7p z#*W#erig(OFu|eVkQW5Oq?p)kY6q+}is-3+_eO>(hbtIG`(A$r2lwhT9>VA*Od@CJ zKNj&C+M<6RP*gSyQE@eQjTm{I5~3I9*o_Mz%}W64@w|qt;66@}X+yJtrHs4VWvOBs zz&@uxraBYHhHhy=vr)>!al?XNu8M<%=-?JGc2q*u-)p%c(O8p_w7H`i!kJ%gFT#gd zOnf94COdPymYv6g6n>oxis4euh9S(>;Yuk=8sMECqGXOjl;f;a#YLLqZ0Hiy8sNQ1 zQ|JvA#bWu|!bQ9j35<()?eu9LjdQKM>w30~Khh&RnUfp@G0JkU0B9IQls=IRbQPYj4CEU` z>!vNiIl7+;d4d8=A=>@hC1&bmX;Ioi?F1YC-wwnDw8BU-sR^aW z$isHp-8%X%2Dj{k2pM*4gdq-SC|%%5WQs_+!%lkFsA@bY9l;4O_bMdw0Y8v_l8IUd z5^J06gcxZRf;$Gg1VfLX_QWPN&Z6y$ih?**W-E@paM4(hn!pIaf^`_9HnY;aqX2`l z(kNOLbC?YInWgLDLSYQ9S~5kv(p!FQ6BcndNn7=c72<~{0p5d!WkO6sK_Ocso7x~| z*@WFu1#MwP$j&8khfs)xE-45}Y~t0JD8lFO&6$~=p|i^F#F`Ol%%pgwX2qct?aXm= z5~yHa0)YC~6L%t(aBpWg;dpV-16&YLA!sC!V*QT4*m)0Y1;Qh5^E-3#3^#OiO;-Fd zf-I6HE8^sb(ztiur@o!2*@Yuo8JA3G83H4bd0S9=NH}C-Wa_JG|HWVcX?5}ptvUD zP|}j&?0_lsf17dbm_wBo4%#9MCdnye0(%kc7+Vq6P(jDQ60UDsgRab2Zjp$3RTgRP z+r%7>A8CCkXm$HQ$>%*8Vo*^nU6DQ&lrk(#ubJmY4}y^iRAl0Kb4^LEpq)TSmVM*( z$~@q7Tx?UCA?b~NlxJMMr(1j+`XL5Fe4ZNAs5WX-y;P&*2#-ZJlj3?MF?#*ocfvBz zW|_Pgdhv0H&_)?ax_+*3cH8tg^$-^{cWwx#H10`*oM*P;V@)Wp38C@?%AR$1jj+XA zg=Xo+;VL_;N7iru(OjR$}o2yBJYC5~jX*nF8wc zi$-jc6xMER5>r>>+jd-y`c^y=4!(1eab`Md5rT$wrHHhGFI!KkN{UMNdMhKL5bIhi z^;c&c9CQK(((M+7JEMmvB8K-hV&zFUQ~Xiyy7g>_JwHnN?KlM23%r){7v0j;rkaU` zyX0QWE~n}DOl;Mo*Hu4mad}&^gYi=_usAs~EHKOcji30PWe>yGP)~A_ zHUx*SmwEDr!O#l6`i&3(c;9$`XRM5CfyEUwQ56LwyLOJ$SOVms(8GAQixY zfohfqbBdo&kh$mlD1|7mvL)I#`d7>Xs4Mzc{w3@_axEoHY@Y#atffd1*E@&)A;5hp z>P5Fq5aGZI#<32;sjJ~vM0BAl`#^*Tfg3W$7Uew`kzUSA+caoaH@#7X>)w3}niN>B zrwFIL0~>bnFwKT~wv65h^n`TUawGTbbZA|NUkcYoIl7d}Kk64xtoH_U4baZ*H=}{C7Y=kYqR{t74ko(vjNertK1WV8?E?o6zImH{MK7dtCYUNA`GEcLQEM!Q=o)Ob zA=QzSxAPT=a$4VO?I1$JMI9f(WSc_)%$qBz$%(CpU6V#U_O)h8$v{WXJ8Gjx%;KO| zSmQ^F)9t1^fj?va32ANFyGZnkbQ<1Em&EgQLzw1vn+d*|UaBX!V*L}s=o{oDc(QWk zc&W`RmBGpNguOv&e>v!F#QN;##7GRT7rNVNpd1CuNF4aY^@P8z&<{ST(C^Jg^k<`e zx5I#KNH&$KZ)d~kW9wjpS;*>v?O$)hR@`FXJhKJFiry zVLridCwXY({h!fJ`-{SzgCL2BUjl!cX|9}X@ir)(Y@gXm2QRb6l)LP0Id<8nqUWIv zHp9h&#8Fb(gtQnfw*AQ!y1M5Du_f96z~sRXbJma^=NU1_&WU#Do~1Y#mZsU#HUX} zGq94gT}n}K!o}Dxn#SK1V~GJg=$+_}((yDL2~jz&U}b)6<6IprQFJ611uc_}1=@ae z^Q|rNLXX)R!0`Or7&PDy7z9`<1ghN>vm~Q1z5*VE^dBlll0t?f9r^g+<9j}j*x)~M zXwgT_;{678Dhet{;?F{<&fJXO> z2Lsq;@H(1jFsJ_8kKP&B9E`U*5L2NIzM<0@^JRok>_)XG^*q8AV`g>jNTVGB>2x(Y zA8`|Oj4n{G`dB{Q@V(S7MCSx?$XHnNVAdM0S>zd8duZgNJ?@FTu_x#2;hKH5^Fxy)T%SWG3-AGYe9(g@KnUdDjws zSYZm7v9Dc_lTVlSecb-MoqqCtT5R!sbJLUPTD_qk|s8m6Kkm0aRZgWx-* z4wW)ezD$F{LEg#Y=KD5CADRSsr1Lv5t5=5;v4dJ?0bC@h+6!9sAh{Znl1io)(RVNZs3(IIpNIZl(!GUQ#a5?Ra zaad~^vii)~uBv9&D>)t=>XuK@N=Tt_15Oi^^>H+$ zq5P*CHZXaZ8_nf>avFsfDaW{934%ci z&}IY3D#J-GNWo?tVil-@RAJjP*!yQYey3@>N@`NkrIiT*MQ>p?VQSXgv4;nh2dOlq zMVhL=g-~of@QD3G(;NkU%~!E#>o@dJs?CCds_}}UG!XIy;iCr=uE|KzVbW3kEhqyi zB=6E&#=le1Bs@~f#a5{TRwT#T$-<(SfRM}_HT|=-+E)YfTgBF@m*haYQjgYDuz-?W zWE_=3M=n*`f)~DD=x@f;&Bofeb1G<1bw8$UB0$H4Xy(OL>FC3Nd$ETwhK~xZSyM;t zsdr&`h+G-Y=E+hbAo&wXtR%N0&P4<=0XzJJNF}WAenrV}RDt5t1tZWVS34`u_C_?H zQ}Nes_EX3BSaZ|^vmc9iy8XmVvOh2l1z4lt?MhXmJlvYG8|IQ&hTcou#x*|h2SU~Y-eI9-3#!7Osqk{0u6Liu}e{b>moPY%A*BK`B;Jl3nh>TF%O`zSF?f>3Zn zU%5TRsV=B9`_%VB|1*r>ai(sDYkWZPRKj$sc;s8uEL~%SIXeH5t!;l01gj*D} z_bd8`5tqv6ZS+hf<2DAF80en>FJ!{`<0MjHE>I!5z(pu3WNdK!Ibm47{X@L|{Wutj ztU6LAKXJ4Kz#m%2x(-cHVO^B1z+#8BGN<4u9ukKmcf(%~?Cjth=^l_|5UsbiGVM(e zvv=zBglSA4U?Y`ex)i-xYRPEGLheLn5M)!H*Cr8>RH?Ojl~4LK*bd@@r=j+Z&L9j$ z70$*QalFklD1@%eesxXPAdd5A0@Qr2X8d1$-<)6L0amZG8c>%BK7SL^R240EbLHvb zcpqmdM>VD_qy3t?I*E?R0Jn(!zfIVJHx{5Lh(>+vlzmvB?y19WeicOh5m7d`;0hB# zHj2KiU;r`wi3AP2l~~4f7$N`V5>gc_?ieb1CF3ky!5Fr7lP z*L^E9DW)m?aky49ZdIV#b-MT4N{_Zwk3 zMkr=ofM%BU06Qqhay>l(TWqDhYcw1;Bh2w1mb-~};oAL-%FxtdkHnzjJ(EVa@h{-C zy@x}_JCk2C*Od@6Rr9~S=b5~uX9j~NUYc`2z3HHx2in@xZ20-5_aTrJ*x<)_i>lWs z4JZMz!25LRv;5#IqsRW=}p@lx=^tUnUtO@P8#@2Zh zX!%nLouY|kN`SGxmO0(e(EbBEXI#VP-=ynm5|-ZZ=$aPvG!A7U%JCPLY}V+xe^3~4 zW5hT1#QGI~Q0pSpAu<6eTobBPHEDGvszRF3yb-MitLjrY1wyIq*s@f&+_V2uAroFH zwKdiDj9-zdD=?W5Sp#}+jXaj@m5Dv1Tej2QF4742{w=NFJ#0wUy(kRYlU?6M zmJlOYL-&7~QPAMZ`EcX}L%Y%N5pUU1b!7f7qQ+(=^dTt$JOwqptbjj}pJ2^1RHz=M zA1N(-K=2;f;tk-XnU+ZN%QM)iMoF<}KG|qQLuOAcs)K+jPm3zA%Um-I1?&=NZ#@<3 zjaGsp=MW+#2bbaH^e!0r!7D%Upl)(RaE|oViiKo{BmoISgaEoPP3koZrH#pxyR6SH zY`E_{M@-M`F6vo>)W&`tk$H6^piGTEfNu&%3ifo_-|!VQyNT`xsgt6=+1h0NZgqJk z{l*#Z!JVbGZgF?V>FxxUmf88M5;YUO@HP&P#l7K(-|@TZppNwMNm1WhCBmfsq`$kt zKnndq7T1uOI~Uj|QiDr%C8;OOWNx>0r{>*qoGNtS*tUTh?ID5OR+h`{sqi9B2e+F2 zwP`gC09dP!++NFGv>mFdyQ0U)JJKx)WUbmZpl?XTDx zX1}si<-@##*WGV@-&qg4H$|A3PL8Wi`{x+OKJ8SAN<5aw(~D2B0Q27me_Rmf>{2P| z`zk&RS|G2G1Pbn}q3z3mBIE`rpKSr}%ziVW&i3Y()|iIcs81tKv*r$)&9#TIlaNs2)3R`$Q^XnRq)cGx&f)lNtc3*=X|IptT z{G>yO8|Je2`+oMEoF!=QI$R2op6iuRM%BA}T3P4($-CO{HL-M!hYo)M0L*-d(N4eU zl@(ir=F|q%b!8`7&;}mzvHi#wbC~>l6<}XIG>@O=TF1~hn%Ujj)(@NT!9|H5sD+cS zy&IW81GwXZ@;pU2-A$vjm>{GKkb5s(=%UoGYRKwu&Z#O zf*vBdDRgmO&gjnk<2~Cf) zT~p+Df6);Q=igPg$8TSuONf9$%O{#f55&h^J;oH)yQ7JjygXCgx;YYfkv#lttf9*l zQP2?Z&$on#@YJFj?!jFL%3%dPjNINFz3k&mGZy_BG#@RdVVSjev4pI&0kcG{5NW)E zs|(38AVen_C1Z*rBV2!@^PNU@V0rjTO?UC__*c006<^*GWf?*(2 zIlB9vQGmtjKozmbH~9-}G(%(Xc7Tu_dI;sQvE|vFWzq%ll~+j%HFj zJLkAVsmgy3j<4OML2Lq~CiX%vf1M=8~F+K(FC~)gC{q$XOJS@M|^l;~lYRq&|f2LK)U1e_C#co25 zp9rUs>4^p^@G%OxbKkp5lf%fR9L5#4UW0&i@OmbI`ScQqc?G|e$Mhj#Sx?ZG$HY#b z+8cd{;|~+p?=x=D`YxE+8-LTADIt2L!ua$qQx32$Y>nN02alSexECCj>s+x6A3n=TzuQkk(-B=^ z*5FP2KoR#h^f{c-r6!>U@Q-#I;L+lgqZfA- zawd+fP(m19TA@H7bSh9XE1f#zZ*{O_yr$P;nP4ap zeuR5#ldCE8H7PwhUAf{)_gVC?eYZi;l&Ry33Msa#bN78D5v>EXiTTO&5OFPY2T?rt zlBVw2+$Pwxt{z_TTpw%AWy;qHou;jHEcM5sZkW z6ElIv$2Cav3p_KkGJti8<6DLPT3bH9dhlUB)gjoCLZyf`;>0A)4nG+>qFS%Kin(~c ztvpl^@^Ax;{pRu}GG(c>>G1A|iBY+*;V1p*@^38I~L|BT{J% z7vxcZQZWRz9Owba)!`ZID0Py7KQ0>=q>88CJVeC|j93fFlqn{Y1UVXl8mho!FOA=^ z7WW`cPatw~`^gjyo8mV(i8*7;l>AymwcRUsBst+*{}Eq%xF^(t+gR*WUt7>-1qaqs@Q>wbX@*5 zUn$~AH@;OVGW}!AAa#=F0KPr`W~ox-swDxsh17;ZeGv9RCKiFeE~3;qs0AnJ+PZxd zz~%Y9&vvtSgzF^`l{~gih$>N#ix>G*-*~LAP9{+>ZZ?S2l_e~wQQ&3(08mcFr%hb3 zw+|6O-Jg|KRnA3G1PTU9f%G~srw2_NvcN)uquxad7{v9GWsT#+)_M$uX=UeCPd2m$ zRUIFo<iZj70&{CGWEc$g@8s8Iy+y*4C&_lA zW89fwxmprHpc7|`e!udjL7;ScF#oLyB74btNX6`!U;#?lfl>otH0vfzu)EBXC+N%- z`SQ=WjIR(<5$(O?j%>i(uwrwD_T{PmM=OW8aKSMB5~xM;)^Wk8F2r2sp@glpl|8_h8+>}n{|c4-I6aU8b5YBujd`=}0U zbeY&RI9hgVFPn9!gc8PbNnsoaDAC*q0$f^@GCH6UCWO2U`U0~-sac&sMx0-d9~BDL z(KvW8G4ZVLH+UeJBLWX?5tYy%?hwBNgnD&sGzILm0s&GjZ2cIdaAxB==7p;|VAWfg2yeoy?UxY9iA2@n7fc11o zhU`>vtD0dbzody z{{~@HwCpFnV@?PdXff@P)Awyp9-;33=-KrI8-Fs6*5O4PrE;<``2(Tag3Sr*WJQ+=NadS2>qYT&P45iZ$4l=Oq4~f0_u_+NZ*p1=Ff&l5lBM6;217#q z*LNo>)+o#eZo7!{97Wp>~ z7LLV&$~OxcSrhE3UuFGF^B<@rbr;VgZWGYS#B~q(znCW2q#89Q>%4+IJy9~-skX-JSpyh^Mn3;3!{Ti?K3ILuSN8Kpc0!g z=;Dxb3QglL_^uP16A}*89bL;6(u>sRQ$#xP>xH$p-iqjdN8po2POwP*(G}lMmRnUe zEsMozL!a((X+TN6>wIJ_j|nge+z5!#G9IklI5XfQ`z;(vN8Sc302;qIB6=2*#-5lZ z>A{ce?fhz?@|F3X$$m`VT(fz*1lMmclX;CjV4Q-80##DTWt<{kphMh8+RS+zEjwrP zT)>%zkIK&R6OKd255x)b$~h~^W2riB$0G3n|IRipivY&sw4agay-_C`EbM1Wg(Ap> zor3mxKM=t%-l`cx)=@^;+9OVTPpZ|l1OL2#RlWMH#ZZTbgTgYdjcg2CBVDs8E;%#Sj)pgQDMtX^T`6W2B-=x_?bapN`LJE!gl3^lCf9&cr0VV+r_f7U zG}m~LjB5?3bMM3qfy3J`rSWU*hna$^v&t+(e5Zv=6~k+Re0>BrrbalvPg|)Dk;Xz) zai2Wq^x|FF-fGehM}so0qm@1lA1SfspcT2M0%KYa=OuU-IfjIr15_Ia;x{S3l z>FBpMBlzh}hzn;!Ns}0>!EVmU+&@l=m5(-VbSp)MgEW*wrSehXInt>*#0YTf zb_qlzTBL-u>+~17X_$wCW1^>tZDcz4l-)^Epd2B|V5#Qs^=F)1x|#H{iBs9pd(n zWscx5O$xX`M(MD?n|!F(L$2R>x7T%ep4atK_g5wV^{&K&bvEHshA&wC7ab+oxNd^7 zAoId2<5_lhO6p@ep>^HbFkzq_qc=#ocgpxM0}$OJe)CUY7kJ$}J-daXuh26tV z`s~fuw2k{YGj6^^#mdWutjW=>LFw)G9h0G02u$gQ+{8f#umbJLBaW1j+)*tE_r?u0{M;9$AvSVhwji)-Kz~B2l-Ch`MZf3Gxt+08jPn@m0QGwFlXXq z{M+z6!OM!}cC*(xL)z@Nqq6s8HJ%5E4OlZxtL(OrQ&^((t$gXz!xw$+zIx02$CUgm zi{jv;;wz5X+v4_HuN5o2qh&dC#0j72t|o;C6PGbjbW_%~@9?SwN`2x2h7Y=$zfRL~ zv^9S%#v2+}zD)1Dx4V|HiW9EJb|D@9<53>hN$l5(hJ3i2n?bLx=&dn+hDo^_;z1sDL ze*V$(_*~Zmz2PIO{8k~ui8?Rf*rwH$?UcUtY|lJu`6vYJwM6l$x*6`Aklj$9r@{3dO7&zj+|J|x-y0tqTAhw#==@p5rvq;k}b?Y{h7*P2^Hv< zqtS>Q?3|QAc>xvDHsX)FJSqS(zL(9)p;hQb$FfwPGG7*<$I4pmJU4MYi`3W_Rj&ed zX(;@79u=az#-nyQ4o2{hyIP2zG6v-hnVDE322`o;wbc)j7BCDyB8G?gWgJRe> zlw$yO0?5>@wOSa0TA1Xpu60I&kJNS+I1)B^ik07)QDDgqKwFfMO|0!*tnmz$#ngj% ztsGh`qr{y^v1W`zik$TCmpK*3WT@q8iv>-PSxW%3pEzrWS%$+nkpNLJH86(D$@AQ4 zPI08>cKnQO+yW0t)D|yX{Gd^%IB_#0QNvP-V(@KT!cc{dg1-p8#+as|Fc(7<7|D}l zB}%$1kxvO3Z&;O=4o|M-i^k>x4o$jZw<)D!?bv~oFDkGYV4B;$ldYVo{_JtD}FD)_kRQ+^{9+3|8Bl1p3S!Zov792;reW!&qu3>rpl zn5P5~Z^bYnEAJ?yf|v8_0ngGlue`BfZ$Sk@LX} z>%nTm4)^KHaw)A!YG(!&9>a&)zz~~)*2(w9e<37S1*0gZ@^Xezj*J2VJpsWbSu;#J zAghKiB8?!9b>pgyWxX0<9bV^}j*%+#xLH*|bm@99%5QjDS-0Of6(YA-byc|vbH#$S z1`sJTib(I93NSfQp~`x`bCTVlaOPJhBQq0WB7Lu84ao3o_fUwCtA!Ag&Me5r;7llM zqvTZi8>FInn^lVGOHoatuA&$l(c(&yf2eSgWsC0%h(^cql;D}}j7bVPx4)tY9+kz~ zU3SK!+j&7VG$f?D`p%`|p$B%I%aMsIksF0&9BgZjSalv+qy&)nn00VT+HZVE9XL-B z*0t@Iy-gs1gJn2i-y3wj$Btp}LAb34l{@Wgo`t*@*0DX7oi%=({+&YdeFm{m*uWqc z5suUj`OsJad+VtSlQ79(X)3Q3Wlh$JNua%ZjSc!?WP=(s_zdDRR>BRA3WISpL)a-T zX$*;R+gl)tKdD23GBjbBT7U|(tPJTezCBD?WY=Og`%&2SS8NA+GTN9Nb4t!AsUiB# zzBUjtldgX0HjQ;ESjugqmu%2klB#^8W<^Za?G|cOl(voaG{YFW=YB!h)jZ&6BDBs> z_-)hNnXYn7{_R+UuX_i9ib&A{8EQ1|aDTAdV9;J@v4ZB%a9YAIByw~8Ct_B~ON_$u z_2+zkwS;|b#TxANt!JqYDG}Ot$r#{pug-ZmDRDUIIDd>^t*toPm|eps$O9NpIPbk~SR(9=3f+&;<<7PB>E_(2z&Y5fs`+BwN%XjjhDtFEFx!%z6on>BqK%U+n7^`p zMj~&7?yT!2-`0f+51!42FFLa?ZS2R1*X8X%MUdxB%48XwKeEMMU17-NH~2CgWzHQ9 zp`1V2PuyQTpIBEw*0=5G2u80SB$B5NAn#aRKkBx%=fDp?Arc+4hH0fcoUh-dDDcQ| zOgz~>lYgWzkXh9wwz#C}@psoZz8&Rm`HYOZ{YJ{W8lHcFheCZP>3lf9a7?pun@gyK zTNJ=e`kBjl@&FJ|0AI&4Q7?gp0s9+}tsTIWP4(w6i)LVB9F6RSjKUm^xD0tFnAKOU z2yVo_QH4Ro0 z0KHo1H*q>0IHiQ2%|Af|YvQzhoEeX2_+X~k88p1e-Wh8Sy&ty!LKwS0&bvQ%k-u&) z1Q~UDpM5us3o>ap@$bd2*CzG8a<{+wTfT1Fw_^nae&fEI`qEuMU!_v-jrC`D{0YZ# zNI30uea8BF@r~*_f9$^QCbtwAKsLD%mfpHPNS-A9l#rO-KSc}E`v|SsPNuK1`z>Jc zjSDsD87}B9)oVkF>MM%T?&ER#=}M|H*1&}Pvcu`Q@&4^=B<<@NSTn?m*x^(W7P?%^ z*?KC=hU5GC0Q(GTL#y1|&T5J~>lL;NTMW=FUrFA^~_ z{}h%5l~pMq0-hW24RIe3dfE1En(g|u^K^Ms`pV_b1Cie$W;YW01h#2j$N?OAwR3b# z{R7#&2jz^q5#4j{K?v} zx{;l0bQ6DDNS)-NvUWDUoCn;BoY$GyR7kw2eW{BMTcYL9$_zjLwE?)*Uy^}D$1B+XeI9X!&h)I=|D2nTYv{@YgW=<_%# zc9~TzTvu6ud?uxGZpzs>IyUa(<4jAQ1KHhfDWlE&nMqOw+cV<#_Galn4M8hH5rKyR z*3TkjDMn2P&W>h3c-(`BK99b@%P|?j;7n|d{|A)(xAhOp{13qVk215fadZ6>|Ld^) z5Az?;S;fQN1i+|ZVD_Kd(Ztpn!1`DG7xb)T;$-LIXk_99;P@{CXlLvESMCJ(2bBJ+ zAZuc5VIX4X4$xxy%i!c@0dO$0=)nC2M*okUf8+iaP_5u-XQXW64AA;(OjP`@T@!a_ zfDV8WXlHHbsBCXwWCHl-4$z4i!19@i5VFvly2385G+<);7^5=7xD3Mr0(O08zB z(gP|HN@6620UsD(xD0!XqA=8}C@OZi8D;f1@Uq`+Wqb^4Y_I-lSza}}@?LHOQFsr4 z=yO&F^<&Fd$GAM})kZ@fA9w=8Mgc`q2kqH4HHDCP76n^)@8nNU|0Oxp@Oa7KXWYI{ z*R4R|wDjd0Pr?Z#g93pQTjb#Lp};x>OHyta#9{e@7`soVW(i?t`IZk`P)V{sP-FdA zdPLhknwCm&kdLb|h10>76VW+p*HSF$QdqYaeM;clh;6#(QG5~Oh}>y9wQS~p=} z4}lUs^8DP|2{hM=f%cg5EjPe!tUHAJDSiC%O^vq%OVFQG3X|1D?69P?L|SxW0s$#? z+W6xMj2{tI)ygiuDUpJD6MHw-oe<9X|+=6r9Xf&=bu2Obdk>ZltTjyehuNDVD|a^Uo_0ymo}`u8c5= z^3fwgtg$0`0Ub`^c93;17+M^(a~>RF(9Sf(o4I;Qhj3F(`2Yj}zp@SkwWfIl>COHzZCt zEigI(Pub8DM66J+pS=T7lfk9|hzp+@elAw?;K7LZjBJRweNBhP>{{NGYQo?{YV5(> z#J%`L8>H704Pk%-ia^alzK%s$L(AZib*qF=GR)3;z0_daa{s+y<; z!8S=ea=CbP$zW1UB~q#sklznUi*GvQyyWe~@k883;tp6E0=n{*q*+9IWXN&+3co1H z(dDJ^M1>aRxTKl|+y&f)3zQIxZD!O%(!6ONNS z$>e{{C%Go+(PvTU5&KHL6}~iqDRv8VEBobDtLBJpf_iv^Bt=tm6AVHPQVqfk0=C%t z70KG-{NftF$d?ElR!@-?5aS3<7r0L~fn-74OU6r#_~IP-&(raT{WpXM?KiN-WX4*% zl)HGlIJDwF`VTBh*aZ>s5v>u?*Q|TZ{aHv?`>2GkJL8QUJ2h4OcFjP zM3>5_*v_KQW|Uf&%Fi%bkXryO7A>A<>B}O=i^g3u$20U;-*;X@j;dS2Jer;?ZhMb- zkK%DsaXN6Yaa3@USO?g!Q*Ba*Qg>7LSqDL8n(*}yn!B3&^}37+DQACvn2^;0xpFEh zPmAa#`SMrGcq(ov2I0PHD8hZy5)7WLiHZ+ANMa{Hi(Rzl)7}Xf!SROnA z<^|>q9hSqS{bm!MLoB@!eT1HyUCxZka>BOe@zWpK`N(~jKI^{K1>VKire_*tY2;XO z;NY*K_Zl`gL8}XB0g@uFuq7Wv<{b!GH-?lz$@6R%hT%h{Kfv$ z{Ifg+Cqy~y0bD+W7=$V`A3QVc7f5G_-tN!ct^R}zQ+lM@GZ1u)_$3x1DX=zhQY5KQC(KZ?Qu3?h zHkiC%{f2X`-j&}@$*-7Sc~mSVlO?0(fuIM_v=A8}yqZRbg_ok8p_es}QMhH;eD+KQ zEmvSNR)*41!=yDi>P_ZWB7!uHEI51R>_ ztFvi`%UkeEH`|#dQbo{QrS@{OoU2ZE%jRvzakMp&wZ!7Zh}cM^G48re_}YwOwqkXM zzFFP*-hfcEkm6=L-Ix}VRln6&tJ77Jx(bWsq;I;Dw+16y;al=#D{;r`8s2J;tAFkS zPumOb3Z7jzTwq*RRu5aQ)l&>KbQdQoH*_j?|6Ju>HMXjqbf^Nf?Ddh&qm80L%*D0s zQdJh>vqeYwM}9cbseA25o{gs&OM}bvo$J=V)1M>3`=R*=(DB-Qf8Q%uRtQ@616DT6 zd&iG+k6JoSef4}rP9-j5$Hjxh3kG|loo9Jw<~fQvezEsN#tqbL+Yj2lZrlocqLm#g zu;evAKyVUsU2Y9N5T0iud|z}A_bxr8c+I+Nn9vN@%$Zx63v0+{H}{nBTtECdoq<1w zPsgA3?sXG!my%jHY$`n-JN7j_jVsI5=SpZG=n@!)8N#jR#Mc7anaZfFu3Q`OORCbn zY<4JFZhwAJNh&j~~vx@!pMk&%gx-LOq?)cX+<*uJ9guuf0w}mmur%|MB2_HG4HY+0Lbalc&xs<*#_1 zeV8{XX}>wip4T6*3pI@nZW3mAPk5}7?}Z#M8K)5gi5-boh>u4+Myz_&-1J|JL?lgb z2X#`tHQXmmmSy?4KDV114E0@DP9CT5ORW`ma6Qf4S??Pi>`c3wpBEN|ua$N1-}$}f zJR9B&#vY!?KgcI!Me@6P!MbkrO#f*N^9l41A8x z^jC19+L^Ff1R?7?AqcUAGljHyi?_<=fW!H$zuY+P6tp+&u>8J9mkGg6r%1Ddb7Y3$ zMat~kgqcfw;Zzxo;D#HrYm~trOw|5ai2CVj?Dwx}uryO#j}?s5L|Srra4S9r9hDZY z0S3HS=93^L{mDz`D(;R$R6$jzdCfa-T^E^GXD?b*KQt!$hcF}mekzLq$?2cDi;g9G zLDI0K&*MG~;o6podDsQ?G%<2`D^+69W&AYeV0C}DZ4v58Cy%*nArZ4 z#!JcA)cga8-H9j#KgidZiiknp!N}O*uS-z=$0a_D%FcFnR>szU;g|8lGl>|~h?xJ2 z97WVVAd-<0?jOYb>p2eQc22eqM9lxe$^Xpap9X(tq4j~9e{qwEh?Rwl=>LzLe;WMn zv;1#e{&NU9fb|Cs{x9zLk$24WFLwV^L+Bsmrek8~AfjXD;`$gK7b_7bGslPjN`8cm zxuKwqsg?1^L>L7B`neMk2jfTh{p<8j|2AO|2G~g$o12R$Uh0_HT)ak@chacRxPd`(r-x+Q1eXmRMrFT# zT}f{7z|-@tp{P(Q94zYn4^5hI3=w`i3gV0+l&nUTuZ#2&9qoZ2k|?)H)%qD#*PF`2 zKr4I^H<-clVT-sY$U~JVU0TVN^Z)A3&{ELhngO-j8Tlecv;riEM z7onMG`|Pf;0v4#)O2^i=ckJWu?rAGxb8+nS;YP7G4w#R>Is_Ufo`(>Y#KuTYG_Jr7 z`?*5?5Mk6Nos$Rb=+qMKXRK&RD9Q+h@z2X*#31x7$#I^M+i<-Q=CAevfm@k5(Xpr6 zysMH|5=6}!2jqG&cvoNa1bc?!S9FYOs)I>VEoyN~oIp6}ANK`tj#b2aQT-u?E#(<1 z%Lks2eSOh5qnE|Q&K{AZdPL)rHHqcY=F^bBYG%K}aZl=yc^4R;a602W%n7)$wot9f zQy2Xmxsk7R%ZxovM`EUA^gZkw*f|0R$@dtU&#x!6Q0KNK1mN!_H{X?la=oqn-+TMY zkNnHxvp!4p486w~;VEyN1(r!B$awq~i<4VZ*^NETzTm4Dh4oDF^$Xsvl$@2;Sdq&_ z(YwO*i06)jfaP#>Et&sTML&DGLfDj$ALcd0R-&6r7;{_N-qo9AqsC_cI1@Gm7FXFq zNbDm(4s(}L94l}YM4j;xKDOahoaRlkfTx(T3)1#)iSa7smWTd$+(hyS^WbN=oos&E zn9{l&lzGz=8&1icQc~`U7g5t5fw(t`;C&k0KyH^4frjLn_%;mLh$5^nm>mbAXfB7h z0B1sqj9tCt>~P!^j!S24b>XkYgD19fI{JE*s&AS?)D^q^c1li$QZr4hs3DN-_P+zo z8gk!fiZN$Zb{Oa=qTUs@FZWSJ+F&LDGM8S64=>_rUE<=5m!i`=fx&3kSy7Tllc+Ki zbtW|~aaSKD`$rh^v%o$hl&!>@=u^}(^?YM(3a68&7os_ z|&}k95`9vVop znhh_Sn*C;=#Lg1{IHK{~RZs2K*1OU^!^fv|v5KBnOHoz*COq^>HST>FTy+u7(p}M5 zaI%WGoP9^JEU=9lBOxj2bIj4Y8zpHaWoao@skdwyr&RZSY3|Z|JKP3sUEe;DAf zwyk9d3G+OYENVDIX*t)~Shd|+mVyS2^e}J@Rl2l1$Qb6O!c;|3Qlnl-L`CDWRToly zgW6d|2jc#`txFc57*uZ&w&f!az66(qIrF01%S>6F_%5j21S;&&RQ8x^_cDjQ7BoLc zUe}_5e_tNm?F1b~%bCGnk7yWjv27Wg?#hpu_*d^X@Ox6L{PYZpLl*m18$4Y^rPoqg zT$_IYO6!4_ej(;`wFgv`^KH8)z;g0mwGD%(``VZ3>VEe3yBREp{i;%nXJKVp#T{-j zuH(Ej{}OG==P?kMi(}d+FUAA3c;{Y9(Yr2z1|l?RWcp4=aZ(S%jq4!}S3Sz)L42LP zE1Mu60n#_otWYBOMj@#OtO4jc5BR*)44(~lI*RXn#m}xSJ7%c0DXA>2^dcR;<xP z?9OXnIWTR7Ki{&Q+X--gV4rzBc%R;)MI#d6f`$l+`l44YR*~GBEN7OC?wwA38ih*{ z#tlQ~!`rr3Zl&b*SuL2P+h?t-sK=}suI+&+b;+ZZHlA!2jWE$l_f>3!o8ODv6SGR( zG2T8dagR5BA8Ym=_9Z6R%LGuG>4@D&+^5-iE|$<^AeS{VbAOjoJj;L+wL1)5*2TBC zy-h!Rt9R+VPg^pwuHAQXxuwMSW^8ncc8Q+H&z#0CB`C1*jCCOO9pzHNgP*s#rBuPK zB%qY$0(t(h7wUMPKWV}#W#<&e9t?DM8*Ro7Z?=d|3T{IM+>m?qj-u-0l${dK{lDhL#Tj)nv9~ zy!XRQ`<1EnIlWn@a4jnBiEro-gqrYa6A0nsHc=YM$9W5C=GEZY%;ojD6(y-b%Y9{&`#abAZR#n~Y{#ucwPzdD{vv*G=j z7vq424gyh_-8${#ykW2;RDX677v0~iPV1tYy&NqNG>AyH$jpsz;Za7Cr$1S*Q%0IE z_>L#wACn}^+L5*vk=}8yl}_ z=yfkijs_GmgEAB8<}>-s`bN8+J#io{kk>5}K%DV30Hly1hQ^B2t|KmFyQm)fE-JO! zK5NB}<$#bTkTJ1YG;u&84HpSEf|byVjEV-!9J6HV9$P(Z0EI|XS>NlEAa-`}RKu4c zE=_#P9S}w-!Go|*fL$1y|0O~GLVS4uJv_VS%~3dpfb(d@6@oozp>&|$U#$CGZaRV> zo^~B;C4GJ2NvMS0JdMivKA?nHnMDbLkU`nfF+>mnCl6^8t}Jfa(-v0bHhX)k-H|fGz&`o&!5BHBPiBWru6#^Rw?Np? zfn({MD(^%HH*|fW#}?P#{P@uT!W|RNxVf(>CEV=bO)}}we8}%YBz!Y;f*58ahpv$D zF8fF)J0Qp%)9j|~+=O+&a~BLPED4pWm+SN`p2l2sCe4w1IA69X{KXWY-OzCe zf$Qmb=}y3N6&zf0Si$AcFl3~(hxF|$V}!nnD8UJ{XdnN+G|U+F>-(Dp zIzGC(4o3swMaH7LQEm7MD-|odMD256Pj9xO%Y91m#=~99M#XYy*V6WCulK;z$zVOc zRuP&kBmgqw(AJYL`p)djN9r|VrrfcYj?RfCdvwESCbO+jWhinp7kAP5svr z4{=+8KK+3EAOU$gl8Q?k!u$#s1L zJeKEE?nxghfL8Izxw<(MDXgtL9@dN$5!yuKy?Aq(J|@y{%tzxGY38y|+=Wsrq z=ysfp`!&pr5QxU=5J2-=}fv?{|S3S`WJbRK94*@E2>?GEY70;VAgQfd`hW(qE z8A9Ua14KX0=I)<9A~G)Xd~ytAs5kH7NC!o;zIeH$==)DOQDr%KXIPOUE2-x;Ujnlt zrpYO7_DoHaeD$l@{ITP2-0x8{W<^P^9j35|7on1Y3K})&zVXKxi9oS|nRN~+7lUUD zj#kP)h!=cDkI$2xu9W?J(a3k12)}~k#yo)IslHQr$A#w-4B)-IYNxX$aJL$y{m*#Xheb106nohZ)U=1dp zbV?PzKK#<+zb0okQn_?w&`JYg7En z;L3Uv{K}{OjoCH|UvU1+q=&Retp|-4ZN6BJ>&2HhkIBU$?lu<6-f2jB#ISc$chsaELw;ID(e=ZF-epP}Leu>;yKVydOxG~FZ@ z7}~zQh#g=c!Gr{I1T_Y^2Cl;u1@dh&^icHZ1^H~kZ~6vF_k0CN^q0&~b0kn8@l$KR z3s@{bU-#ZK{@75NiL~HEZ666JS=wnV_w4IMPGeRTo|k zgus(sB#JliSd4~8vze^}@1stI088c@m5}qfQ=+O*8613`_^0@1=$;=x6k5w-X^K>- za!#aBgF%5{0Z4O;_(lly`!(WauD&p8Y%k%R_mmgD01-B^r+{o4u?fl1+*+L1M&(1i z=}toIP@3V&VvBPhUN=~NB8WTh9p2xnbMG$K!fxH%XVeV2ieL;W&=48MWvUMxm*2Dl z){!^K+|U_xb0;Bm|I}<0yz2EzZ**~RV5EbDezpW3pbjGM1aUtFKhk0KkEjm-gOd$Y zeNh+|wjMmmk(LF+b6iZC@%n@d*BAH{bDQ1lA*r3Nc-y5W8g)#nTn=oXZqdj9$0<5iiW)W*b6#X)eVTVCEMmVoXuXeV~r_jbp; zU~&kbJv;4c&wK9NT)ZoYf*9ex5VG#@nV!lw=2qs#$Qu@HS%KRHbi#R2yWvJEIf{{Q z&fA#A%#L%^YA%BjjlF3%JnRdnz5XPYhLI}}9#6oU^d6uKD+4}(q6Jz)jKb{Vb4kI* z%~H1mkG6PN@w@sAb}KGUD-XqyEO&d7?tI>?mX?WS51m8baL!$NN}%IqZjuI4p!x#j z2vk4O3Fx!yH@8Cv4<^iH7RofQ$|Hcr0@N8|!VrGySv|>RGADN;jwc8iq&EoEx1OX3 zjE7KV@I7T5#7e()5Srg)OS$|OfZ5nvpBU}Vls)H<5FPi)+mF5{*-i883}Jo*^|S70 zKEzXx=Nvm{GfJkhoh4;>akt4Yu;$urSf@?XoC0hGP{qoJT|lczs0G>!3bQJIVu>F7 zv`u|1hWgjKZg@Bxf=HQ*e4}rsRI1NL3#VVw|5STukSs)7pa~fdjNs~JU~TRO0Ks*q zXJw&ZxQ(_pjX5;O8&D`1GzWl8JqMk#XKQz%{9!Oy$NR!dx6BSq!4^+9JH@L*@Vrjd z0=)AB;=`t(xw}kQMVt!B~& z4|8FkfuNr7M;-fsJYREv>x23Dwq-}EXG{BY|5GIiPsfv0+tSo>3sPHh99>S}`Ehi3 z3oB6=cR6NPun4ZG19XCIUnSi3ZsnXmkJDg4g=S41igR%TNLd4p9C6h8NtO?)bv4kY z=L>Wm8K~hg7;3OcQ&YsyDOZ?v@Zpdamyw(hspZk3sL`jqQ)iRxz)-rt*kIqnH^g4M zZ%3e&mkh3rliL%lYh;HhB57XwiFN>14EQb}DqPnCTsognf1e(&udoGz(rp?u->hfC z;%%d`N79r)$Sk^`L>sNF6}|VTUBP&wSk)A8hQ6a|EiaGlPcw$t4DhpwTsb)WWvcUR z@%q9{INpEIh0Pt)`0@7&d>DsOwa-y_ro4Kanvh7`Bqf|+;25k=!F(Atzw{DL%Idd8 zOfJdZYZl_7Mc-+Js)`%jVmyNt=yH1!kc=9VKU)FX&*k{h$1QEjKW*nkhfjd=U)_h*-|&SNt%lSeHs9Qpl+wiF1}IS_PC|A zSg-Ovw@f zDqkJMtwF6NHbdkFWE$BH;}RC}U9Tm+*7o8NZrd-uW_W7^Eu0O=*8mfu>?z0wMG^%U4ik8J&X-eWU!s?gqGm@vF7YEnV2yMG zRp#m<88l7XA8rr2r6-=O`8Eybpw;zcPLDz} zL)l%b?oj9SltPm#Z1YH@rj^H@fD%o(q4|Y;?a=ZZUkV}>2fK=%!k$drr?J*{y3xXb zhOhnQBUL#blfu9$uw*MV%8h&QN$JOU2)?BHIjtSkNf=Cpf}8%ZEy~#K()?y zDbxFuFb!Zdp+^U483kOwMSkpf0@P06{hP&7V8fKMZu_ zjTi=sm=;V?*ks>wBp?Wh^0oGH27jc7HpkhuO@uecMGk4k7vMAdawNH#SIk>OJ8cx4 z=YFJp&M(n&{6#et$digUn2Q&cnR&(%;HbvKj&z1KGa9MMOKi8jq5sQdf(iXArx}&q z0xYkcMd7@*mV&3PYxaK97R2!Y7tYk`DnZMg4B;I*c>TelRb_r(PazE6!E>r$H&q;U zTk_t(ozuEOtFUAB9O>K~@;F1(XISQl_$0FoOP@_nd$3cIR2n!28c|2Y?cF2Ih-s!1 zu|EgTsN9+E%2o12-IN#SttGS2oXq^ZQt47e@ydr%dZ+Qg`RgL0$9kDZ=dK{{z$L5iZ-pS zFJg5`|7uT>_~uq(`yt9EPkK4lr-M0>^I|DtiupjMdyL+Bk&3M+OG(D1*6ZfM?)G%1 z9V}}SU5pIGagv+;@#>5M5f{u~&e!c&{)`~grV0r`GPvpQ-TERk@W+H~9{fPjX)}8d zYO|a0YV%uxF!y0^&Jc-rixXm&WUtxy8fBmat1|2<$zo2SbxDo1%;X#U68D1Xo`FYB z@%wxzYly<_)dZ&1zrzWvJtcT@ku`O!s2POdxf|(3;xcqUVS4D}@sl9ud=mLU@9=#} zdibq~fg>}m54#zLK3KYE%njq7<;8bX#}BryqZ3ZOdoy*4}rQ z-a)u6+;xzzC~E#4K1$yQ=dRE68r2Igt7re>(F?LO&bHr@t@UC5QSY+qvi)WG#q%ZW z(ecIf1@k34`%7Cji46)ltYaV+ATx$aJ*c3E8W346>Gs17j%U+llWz0A$9&T_5WeSY zLh+TdWT}=)W673ESShPY)R9esELqvo59BfewNqu@qNn;&wOgK9=+e$&K2`71Cv9g% zXGv#K*&3Zv)#p;%AJD}CGu=mNvn(@>#ipgcxgE0j6;WywCHvdIzfph3Xc<6Bm=1fL zIR}Kowbo?zA@Z~?%=QoCLMn6kuWIi8AnrrNsV9MU1dOW%?bBN|Vm%M{q45l62A&dn z0tgp?rD4!ZzbMvru7#pboI;|Zw?Z!_bMfd@uDNr`HFu8Xs?Q_Z7Al*0_PmfEJSm&E zr53}$`Dpu;C3E_bSY6t=@?ZZ^+ES7cxCG60yp9tLI<2Ggp`=724n_Vmrfi-se*?DVyI(8up%a()zZ(DxzH5Vd&#R+y8^6pB0 z`1p9=?e^@63Q~(_P^`J=CX0VD?uIiK9?I~FxlAxsaM6Pi6VAF^^c0RhZ02mQ8y(kw z--#pAp%L477Y?p@!wGN7$_Z(XAR3-(JfRgJ@KeZD? zH^DSv4qeD`Sfh@-7$$=v-3A@uqPHeLK-HwB-z{X%twzM*w$|~>5@GnQxH*c< zq$_)?>q5A9I#lyb)p)GE^>zKMON#0|Hj ziEqremT6J$T>@i= z74bdGrmOsfQs4w%GAh{O985|zw>~;QAJfpRa{rX6L#}A@OTp+cx35)RJW9eqsaGz` zX52&vWfGvV>)Mr9@7Fr@S;}MZYueORWJv@ZY)R9=9veR*P7WzA`CbuI_D*6ny3{}$ zJ4!>8=K;~=xz$-5;r!w4xB2uPo2EwlDRkvO%Ev3OFMnDIzB^LUs?8sf&;C z1dFJ?FC3nKqU9U{S`s`43Nyu{B|ET!t78yvrBB1RelpXos5TLEtvBu3ZCqvoF*~0G zLaUHQ5Wa+Vm&YT{aJ(j1rzn_)M?MMV>Kki7qPI=_vDPiXxt-8U;oRT@P$I(?6yjPP*P}0t?Yc$NX`;3v zHd4-ic6EqZy^CXXf|4<| zQ=BtV#qe`O{&G3_^|z4`&d*DgN?UorFD0)7RZ*R5-AhA1q)wt6`3czqmtdtP6N}p7 z`IU3>RnUd=sjhn@CK$QObt4R+(CKpJGuR_pEG!NM$)mSqa?QeW?8ee(d<}* zxk$kCNYra&&9B4+36QMm9%{rv^OCiiFk@6~r=;?Z6Wz(D`cmiDeLIk%95Rx2>s?fm z7;>JR)r)Lc-o(RRT(Nk#Dk#&txo$$k0}DqMS;8Oj1<1m4?&H7i9IPnx%1&_Ln6`lK zR5Fci(M&(p$VKO2%VYj4TauiqCE>GFjK?W$Wgq=~>bb!El0@KB!+->7aeb${ZBv?>R$^nKGmt@g+u39iu2=@&qEnBveS_SV|H&eBl?$27Yo=2DRvx zWxH-9Z+ufCOBaiNbn1Xp^5@^z4_H0NJBZ%{xhu=7-*U~!baJSFk9Pc!2R}68{z_9J zABMB|o`;z;IY)#=$GHo_jvA-U|A~ zm!~&1GSiKE(98H5LFoD5;8A|y-xRj;;)X7ABhH1Y=Gi<1vIC}Clk7T=Num|F#kv)x#J zK=MJGGmE}zeKdVkdzgRZctle#$Ov4U;_AqH5ATdfz#%x)uit}0B)9EW!y%IWIiRRVYVA+-YRy-uGZm>dT1dHHBQ>>EhOb$6-#8+B5JP71RAa}4HR{bNRT;{) zca6MioeP2NrMqnEjhyqo6C7Y_Cs-PewLFPQXy8rR34vd~Tqr(#ys9cO^D;8YH@!x2 z?6+Tid9Hilca1z0$nx#baJ8NU8ll)k-Uj?Rv7XXlroab+7n0x6h+dAJ>jzGQ>tQC} zYH4n?$k78OXlMF{{)D$x%i>LUY*YA!10P?&dubd)CcnZ@H<%ce9+K3C>rW_>GoL2` z^mOWf9)5=9%a^C(pyv3a$8WxxIONgH^X!c;kkV1{SSNoPxJ2=Gcu=sd=iOwmHNfwE zx5yiHof?@CMIHtdNuCmeG7o-QS;Ky*kk{8m%9;SGj8B06_^*i9K2T&KxQP5sX*_C` z8x1(q&lauWIY|HO7&rGQm*@m(9-B=>o%g`sqN^WRUR5S&%O&z z(Pl&hSw{aR#ahW{qm3`$CxoIt-oUeJ(Vg!NJyzo^X`qc80GaT+WCbzhu!9`KoT71T z{6*lXf$@DfhJE1N5*%2BCrNQQno@)@%Bnd$O&%HfO6jI3p*g_UIYSW`<4E3%Lm1Yk z20DFh?fEmrLZ9H(PSrH_kdFmmh4fNi!xNEd33&pO;g;mfAu%+tz4Z3D`qiuG3bAIt zZfdi3&L7LC>T*3h#1p_F>&Z0TMrSol_KQc7!B*#HZDe4TwB1^M!RyeiDBY#2(c~Ck zQm1^S{B<B4T{^{nxhGD&Iatp9Sm0{%4Ov&( zRtLY~5kaxj#e7QSA`N{?^}1T`h`w9g64Ohe5}-GWHYEQ{R={6R*L3ka6*LsW(=;k+ z<%FflNjZWTjGqJp+qPwDn|5`x<8snKV6}li1&+L)y5G9(DqlJzSLM1l`r`rLOKDS0 zMwZXQiZqR9tA{-;$~CSbMrUttgH$+eGd88U6_L+JXB18Gj4lm$Pk!$C4OTj)gp%V{ zGBT>%_W7v6F+wlJF8X^hHh0c8KZEyCa8pBtPhl{Ma$Z(Ru?@w(@Rje_gAT{7C|aQR z`*Zs3a_Z|?I*Im;$6#vSaU%|0mG1?`V1XeGzwTqVqxhJwsyE*jdf(*3=c~0}*3f$@ zyYuDi&-Mo-b?{4Bq^ODzPq*bh-h}74tQ!92DY2!t@}BGli{geZl(#&;Y#D1D3>7*B z{kv(Qc~SQG$?{JxhsNHH_l|(;QKM@L2E7N$s8_{SzD z#@`L@-MH6CEX5k`2g}J6DU;yc_b-QFf)rbao$uiLEq4sWn`Lo$3VBuOwVC}B-52eg zc}H4o+L&umZrJXohS-7=>UX1Xxvmd0qv_@YU#5|YNOz@Qas*joWyqC(JDItLZ00GV z#uVie$&(56dJ<~{W*lV+4YvM7H)w20rw#aCA3n29y!&dz0%{}d&%9NhAoGZA14}uI z`KFlh&GaHH|9a;eHWAXWA@W#ARKSm~5Y5zqV?T}9Le`>mP9RccFa=tMbNKTxG(|9l zJ2VB)b8bP{I2)%lPXyJkC~WS^t2)A@GO=-jW3{%Si-z8L*sX}+-YY? zgzT&6MBg+<+_)QlLG5Gn_y<9t-^gYWRJSJ10Y7hGPP&4UTMdp)1NU~X%5 zr|y1ghND-7qRA*QYPm)5od0a?`CIlo2m)n{1<|$--R<)MXB7-M#sldVU3)ISRJ8EwDZ1%O@%4M;DjhSXB(MQ^Vs^oZKT8aOz2 z;QN>^2m?fqoYkEq#r*2w>qFY={D!UjDoLO zn!R;k&@Qwi`TGVs32gDt<>TrJbLW|}p4`KCQjA-05krbKk{#%X7&b3MX#3v#b%V5y zLkb#Qr>^I7suBc>GS}Y`zDb*la1Q7gcuSDg8^(fhT9fo*fE;|eYwr_O$tOaQInB`M zRkH7f_$63N9B~KeT1GtzJgGA_ED@-tn0;%t-7_z1Z$f3*{BzzbCtc^sxZa- z#(9(U;>FEfeA40mL94)}B5@e8c2Qd@KWm~zsZDFN2Z*A3wx~TW$h@Wj^(D|olZg{9Q_zI{c5?8`=`NEcxtN6VinfCL#K~gh#Qz_jk1sW3^WApN>Ww z5?W3s9vM;s(j@g0_6uk;tmyTmJojkogJ;dH zcfmbx+fsj$b47fNn=_1n_0YH;eH3owGQ{E8?KeIghKIo<#Gl<01Ry%w;Uss>fggLc z@sm?`kSH>{PV1q@OxzlE01G61M{`5IcwWWWX~#>=yXZN2{TfE4t5+#LT-ymJuSVH? zq7wo0XLvth3dYYs$|=|8D#8nR~IvJofiSxP;d^0R2Gp^NF(|R$scIB|3 z(z_-D^1{LAoauwDb9wsQm(0FJKYW7URv({m8Lvl$zOFd6$m3S{{=0g@AC~Qje=V+Q zqluB|OMG8-jI6hQ+~y`1>vs}H+NQU>rO^1JF4rjRNHGAyQf}0Od6AjOVQn!9Ik3tX z=zC2`OPWYxi5WLjer$&H)!&;ZLXH*;f7QRl57!2h(7``UH?IB2eVP;v?id1N0PIbn zlUt#x=;J0X42(QuJaffojuLE)dM4=9X>YS>BJncsJmZ*kjO*-;YY!9hb1 z|ek;4R8VU zxVnn81x>1*HxbS7JQbJ_>Nrxu-c25UrF{XzzcbP3&Q%OXAn1h+i!vr9`q^kmuTWh* za~D&mS>IT!CTuF$AaG1ROdz1in)EZMQF!?yEr<*RhTv$q&I#udi5AGHu$X*~xax}m zVfR+Py+@yJgw!a3GkpCSs&d3>Y?4hsmps(TFP7 z2~{dfgNLt(io^_(qrG5Mv;lnrnteX?N2Z*M?&+xuLx(@QJVmvFX-p0^V-+IIB(%YN z`YHHjCfk;904$4cDz4eBP#=E_+AqklO~H}kb~(q>V-8i0>%{Ts?VV1*xYSj}^8VswV6(9h^7~9@rYDd4d@8m6nv3ov5WO=#!wI}WF!*`5oOwd!>KLS2m&sTI)4Y~UKsPFULP*U9&n;@= z7i%F#OUyf41Autzg}EahxtLYCw9@!Go-k5Zw~XU2!=C^_+zW3=+mJl|rAcTdlyBSM zcQ{j?Xf-u_1~}b92B%=l4+{3-*vPa3jZ0Gy{dnD&*9?VD4;NFadUN!oUAg)>h)xJi z)e1&-%9cO)zrx|TT-`~)T1%cYjL6Z_dW#k4{C@Zu&SbzWuBCk)s=F>Nv%2I`5(6N% zJpIK;dr^s^i7H>&4R+d-1eh$coh(zXG{;1MKh_*Q1|M^o1eg2S?|hmYt6b+ULXP5Y z2Pxdn%y7SEq&+Yo_ozubk$eH$Ciafu&C&}-=Pwm0sJ7fc#_Q816f>dYL~JDoi2>D& zYB5#|53g9bM6fuvEUbuCZAKKsU|M#I0aV0hFfy3IB_U^~O}`4#T_;Iv;jN#N*-y9F zN2kStb5q=>#_(t#RVtIcFjQaYz=zLLH9i3yY0C2YK3i13HG#JaVlyDvn_+qoi}hDG zaqAvD5bz{;QY=L2%gOebZH8DRPQ+@o3MhRCStfh-;VNG;V#IxC)>TKs68Td??k}j? zy(K38ZbmCXT|LoBeBWF>5zHQ?4^Z4gy;0RiU6ny%YDT*bU0bkDYGu=;>I#B) z_p0r8`UN|7QfQ3-R7Z?(lh7(A{dcVWH zx(STUVdA^R0iS=77I|$78xpnT`CqdBFvm1pSXewcBGK%S7iwih;v_GQ%?)!asla7u zyhe3Eq%cL zP*XF#BZs5GY($QWXw`OMZ!r010RF@k3|Nl@Jk>q@#JmxPxqjRA5f_KXf!2!b3#T^|(ZJq?oTz^ObOR?H+UguZZ zuA|#8a*iBsED3s&6!lka!yQZQ_pZ%Seh|t0SWKo%_JR*gBCTFM%VROvsY`8zBd7A5 zgE&I(mR7{cO&U-q@mNSF&@r!#*wtq`qOY#TWwWq%{qgrJ9EJpUI4fh}hw zGd}kv7CS0jU74tJ8YAsKM~C?a0&Ot^108fEL!T!!AG}q{%2i92<}X~D zU~HDoD^D#bjtKCyS>6%DhgEjoYPjO5+GvMD!3S#&A0W^-=DWQ41sW#Mu%0u8cVd9wL==&4^5k_pc?rrF~Ty+a&LORz@6tNdSfvL8q#QE z?p^Mtaw9foHm1YuGv`^>N_3q^ek_bXrIS$81A`Q)UxG;?8d|H593^!PH!joEoz@9wK{BZ|SfiQ=Jzdd%8 zGkg)K@NIoaZZNXHqxxEze4WV1JA^0bI6(o`nxDI3z;4q@Vb4n=3B$ucWfzbDuu~FT z^eA?nKz;tr%ib_6_Q;tJjljsgL^>7CH2W3X)Kw#;Y!aa%gYKd{V@J^)P#A`yzN9^g zr;l1!*I0wr#@+$FB~13vy&*dpP|h$byOknWij#qG@ChHE#FF|z?9%JUariZ0m>qDl zS()(wLDKUfPCf1I91dmkO%w`rF;HSh3{vNZnFQrvi_BxF(qlj@qJ{v7HpH#gsQo6n zljMFJ^hN(lczJe+Z&9OgojG92A>a=uKJ6m_^V$mx>iX&8 zC2R@D-q9%+Mr0`|K|zO_wRwFHKy&iiwy~QDLXwT*VgXD-Fj$uowBs#U(j!Hh-OHs z-ZgB2T8k7DecT|2*_N&_7pb#<#mf^Y5oW*O+qh{rb&ZQ(Eoz%M?uFh+Mb&&zHoZvw z9ek4Gn1!KPE zf>BlmKK84PCE9QvkYZ)xm7?an-sA1mL`wlhC`3R4Zhh6hH?^i`qiayY%}B4YE$Sx= zU&s4azfKCC&06}=E5F2$0@hKNl+}9QSrk)zSRPr}h9`%a_Uv;ub?5s%n-m&`CZ}^N z+|F{(+gIb;1#Gzt+3S&2FfB>*dcp^cu8LvebmavTpU#WD`*kR)wr9W19=2>B%6*J# zBYat#j^@kIfYoyRw0py_bUrAv^wiFxd^d$jfy+9ljS0r$bJ?^val7ellR8)*L=$Rz zb{WTzGDQX3x}Aey5!&8Lui*vqLW8p(Kss&Yxax0gL#5i;ot`~36_)|cSab%w)O@JY z(`;lISo)ngovGf{A?fkk%P-Rlm}v`*P0Mm4`*{VWbUb^_vJ`s|#A%#q#98XTQn<~%?S1r21PM9B6~~37Y~hpj&grJHcZ#dqh4<0g zy(!6P@4N0KosFAx1HKN&m(00>o`cvX@e7$n#=XS-%5Wn5oE3}Q^2!s$z{58`2-+)M zG7Jun`MdgdKA{dzTQk8*#Nt`W7#pn(;aM0&1$9Ofd)lO~sY{XyaH$^?MS0(d5oM-h zLt*mTbG2;;Ve4NP;nIjkhsvWl0nUPfL%gZ2S>1=rAOkV6^w+#QX?)u#&C zW`aTM!Wh8Q3|hC)J9+1gv%EgBMd#)t1RvA8i`jYd>M^9}HTl3R_7+5!s7aKZn>kY3 zitW$`H;b=B1634%$-73wjI%-88Yw!(4uI#*E}EiF6T8R*Z&00j(Uv(mH2-d8QPaL8 z`ez`^*l)tNNb5l^_jW=^Ug`FP=HKv}lG}s1&tA|Q5|3Z(a}}PSk#YMl`me0aJQaGP z+d+Loae#rFH0`#BzG8NEnv9*5-C4CP2-Br}I#R;z+t^mB;DeGMbD`(rDT2HqhKzNZlKT@_A%-~buR$6bgk;^8I zotUd|6dfozSEVXi=FJIsGSbtNL!x5j4DOnYB@E!wa6?-rd2O92{9T|U9-S-^EMVK> zjGB)5OHRI~8s@~E*JU9VH$a*2XWUU-Rd{-W;-ZnnXe|5z#8`@VroyyY0d3s!o*LPi z3%k6-&#SUkS|xrAKJimzQfcm2Ex%$DsqEx5;XFt0Z<;+7SV$2L>Bd416{N zzA35f=Ijy$hpb{pp>ywJ)%xtdwcpS|Sa0X;h}1I41rK#CwB~-jR-D{L5L@G3Z3!Tp z$kPs_`w}MwPU3+l1)oc2)xY$hegzddv9|#a4Ywb$9UFo=X55RyZ>1R-dxg5b(tRX= z%Bvm~fe+W>_@xZ6?(qMuql?qb`$-!`3;9n#{#Z{yprXu6W;ZX=ea(Z=WdX z;7ei7LnmWLxG~-2DF@ot`naaApP47duvT-_UMsnY{*PpU_1c5eX7Ap*?CFBr5BrYb z;k{b?Y-y3Gmx6~^MHvy}8d8Wz6FigvQV73sO^CWEJ$wX-0DF@fsPV_HYyJ7j&e7sN zh<%4h4r+jO7+Q8U)Rt}U8L(s~0_r2f9X+E+oxhG} zvfH?<1@~qJF?}-mHtv`~q4{lnKm421_lfHvJ=U(Q)nIO>#n8I(8y|w`so-H5;~j+g zlLwRG`Vg1mV-k5#u8Bliu|*lY-7bRLOIc;U5PO&_-1Q&9YCNH+y%#*WlXeh~UeNFS zTXcrl`y=;i>IHHN1UVnW+cn*4Jsp0!97(5j#h5$Sc`$@?2YBuibjdiEo$pL5-N#0j zX%8lsQ6p0VB#og=hESc$+=rRx+%{{Yg|~U3udJt6Kes2ZR-_3gb&m_;HABy_>yUJQ zM=4Mj8Ymy!u{rk$?Rt^{T$PYO<>W`o4v67)5g2E%<-_XeVbgC&HxUD24uo5v-Z`Lp zykN(l5eI>6v9O)PcAAUlnEbBnFRzOC91#3sVCBS5EM|h88nfo|kxX9>R@lG(+CT!B zw&Q;MxNUrMCbELxd459K1Atg=FAkskeMmalKgK-C?t+dVz{y47z&#BfG>VHruh}z5sz=cZ{U}$e zcjNS$xTj0KO6iYWy$LSPP=jyC$lipDs~v1z6#&FLJhH%XSNG41JCuo3bR()QWo^!S z`*F(^r)q`aFm)Ir7>fHwh3PkCm69_|j6IZ;R7o=7G?`kQbbJ5+5WCafY`QG2E`em& z&J9X!zi%k+=Las?B5X`#>v5||q%c<`9NG#hoY9_0lBurVydDMGfyusJqB0e#Jjrm- z&?K<%YkedPQJhK=FoKSnro4`%QZ)rTxjl!vh;psvSB6zYDJ2kAOB;#R!Y!zko~50U zj)aShxq^UD&rSL6I;COcw+2kIvI+?X<^fi|O=Kkvy)uUI*H|}4N4?>=-H=6&quQ&{ za3&y2VQc7-NcgsekVBoIielfyh`3H13mH`{Z6!NXEjtZ$YaV+8H{(KzV!CRaVtkjm zw~>^TxSPG{;r8|Q??dn@$>ctxkA-erJtICP9S@hw$9eG@&1_hFX}`i~ZmKriI0?&Q zS`Y6=KhsEHvh`EW>Ns4NY1dSd)XOGPun*u@qS!WgUF+coS@sZXL- zRb?f!5pma^zHT`@bbT;fqSW6;FYKp_iY|}Rh*3&2hojN}EM_=aTp?>D&S|E^$H%Z# zb2l`x(otK8IH}rO8+$r>OZ0^`xH@Qi8`-<7R&g-WxcgnrPo}M^xuwDo*B|s#(@0m8 z506AdP^96erD>-k#?}LyzERC2nX)7o9jNTnl!jENCaE-ibJW{<8CgywiKQq9a$G&u zqZjYdrKGkt=*xYKVW6@RHxqF(R(3DqVB}j%>MY19BH(K)X=^eSHxqcQNOP;TGjj@U zoa30EoUQ=~&svz8N(o%oiOkphH2v6Cx~nh)SH7{-&~`PG5LLA@_4agkHroa)u3k?A z!gecCfR}l{0d=Mp`cik(iQ#z`DE9UW+xjL|A#`*)G3h^;>T_1xO1OFH=<*r8)W!j6 zOQ~0ZNUgbUiQx`bRP~G|pMHLC_?4;_N>y%QP-kppXq2eDJHJP()zU&h!3^MLVXCiM zOv}X4NWoRpK+Mk6=rk0N*VY%*(tE5Jy8hYI7E#ewak@KHw|e@h2UC6!TxbXcN~kBs zvslRu_n;amTYhvmuc>un(XyMFConmv*qBI}$5PPZEwqv{lN7QNtfaC`A|*ADHCh@d zJDa}gy_Kal)rc@rnb*x6(2Wd_swJpu$j53WXeXp#nvba?#>Qvxa(Nj`Ihjcuaa(Ag zUl;U?qcPl=L(e4rOhT(xNA6-AGnE>q%v7+fP|LznR#1-Np(*!N+X6O_9Dye?VW1i( zFQ_~8qJLAZhpv>2fU0#1mrNR57^_zMp2A9=blP9>v5YFljvvMJFvoAtkBa-pE*0P~EuOUrF)+O{0Dq zrU(6-5w-yl)wV%VVKHiu5m|pil1bn|F&Qnakb!1Gs#+Vpfts0wxAS%$$&?+(KJ$+M zYE9Z|-nIV{%(gLh{t0ptdOF6pocEyoaRq29*_dsU)xcL7&-HD~QH zAmDm&FVOf!&RXA4HFrumIT6zgNTX@VGMKQdPGvR9R4C=3SMRr_c;4rLAp z{g}P_BL@3MffLz@I9jPlNm*IZ?vZ1_k+LBP>b6F94j$G@eP=!GMgKMc3HW@$aY1VB zW4-cKNzFO{4>Rvs@SVbwdW*nP`_=hiP zHPMYDaLKLdg(OrhH5}Q5mIdAD08SKefkITNEPN{&HQYSj>N48g z%L4tUDGd+cOp@LD+Jc7K$|6>b14aG)O?itzpqW~$TVw83p(LYzPh@C4I-ORcc3e^t zrbe7XMx(CLQ=AA)T^vS&5!tS^2D*8B<43h9YpdD|-)2m2uVw&Nw<{_V8c1NQBV|WZ zvsIPb$a(CPwY#_d%?hb(x?T&R5a4m#4n@Krf`yv1b>4qH#=(f`Z2DY{ID~WCH{6C# zG%DIi`cOWj9bJdrGBt>I={QQh25bDx73tz`KY6LndS*W8-FUIoJ}q#{eC*k1OMdYl zUR-o>Y&f|QhaAU$T^UI>=v%PySfsMD@D$kDR*TApFp>4J%-t6bI`hjrSh?rpo^hFv z4Mu>cZC+-q=&IsUe2OsY*@EQbb!sz`H*`JnFmb%-e3MWBR+((PmR}tnFR{J5OC@VI zzY8u*4GcmCKx}x=oo$EHc-^1A7i`%SGIjVPIC9&)y~UNn#b0!C%&+rYWb#!M%eHsb z7!K+^E?VJsJu-V(K9^>zBB)~G)T%r$;5x3J_`?e2uU}Q>Tv8G<+6UcP{G&0nq{piJ?p&AXjbO&+2q~1 zaBNCgZ`bx9u>IsT z8@3s+Xo&XZyQ=^+)^SKszHm~EVW3(XL}4ZIF`{~svT@O#Z;I#`YSWT#Ab2Sz3EBtp z=`ck@IZc}IH_ygBrNzLTc?N|~C&GctxtGi1+VjeI$Hl5bbGtI`v6-sef|tQo!FCAi z!oV`hZ4q61aP*Lc_ul2A5lVYDW1wf_Spbzp9h+u~H={+l&q1f029-PHK=R_g#yvIH zgLM0CYaOu8;F*qn8THP6ENQ|xF}?m=HCfZAe<~b51^s=obUqt;VQ!X-F-&y%x{2n{ z(x)`XytnfL--?Pd^Xc(?#KJL(s>`f@c7#UEctCptu+@Rl1v6TG@nX9aQ7ATYT1iKD zVY^yi<7i)h)(H<7D8#Hxu{)>+C`7Qr#w7H(#lgsc1Z|4<@fE@efj}yd+^YDxz{v*{R%p;RqSRb-;h)>*42kjxgIKG&T_`%_eA%k7H>o0DYN(;w`dp3HU z?aFHOF%%S`6$}*=*P!-%OOofrU4&hvUEjJ0?&GrKvtzU4vSaY$@w+n)gst)Q;3I<` zWv<=u>##nR5xIDfr|~3gkhBjq>;0ZFXWNsp$7qdT?XK$*X$`O>+aOpOS{Pm!QW>@~ zq{8{0kfT|7-r;AxONR|-qNQ;q#0K*gWdDKt*UjlFHK~or4djHAkeP6ok3o#&89u^Nf_*ge zE>86fTLm(+byt+l#V4@IZ}hFQ{g^ovuSSw#Z7?@n-pCi3v$}5tAH$Un_lKlwq_h z52!M2blhY=R+k;)G0ZH!nB7vGOJE7w!?^iErx!tD$u?yQ6su73uw%wxFpOP}nl;yx z(T30bY5F7TQZVE6aZ)@4V(&}1=(uv}yVhXr{Mp@} z)D71Sjw2HgRzWa2Y(`%@+R7X0L1aOlOFE17d|Xl=i7)S;`YrADOGkq79)<91$z%zm?2~wuVzR}0rS%w zmhOAx^f0qMduo^&u6p4Q8PfP6;Y43;GlA;(i_i)=%GjM@c33^r1U|3`f#?Oww5OZR z?^?Znk$uqx1LAJvSaOHwkXzi)LMbko25_W8!-xpD?AqNaoQTo(pA|5E3Owkaf-?;A z%cdMM8$~{6B~1B^MIetX?TJOw9SJQD3ly*&i7d~8huHKZhKb_E!C%NdP}M;#nC2E( z*1RN^c#(XJ*@&t^&W7+*zg&unmc|NhtC<@Qav!GWYWlgy)B5O?EgP;rY0!Dd3{v;WUr#+8E^me()pW2M~=obzbEiHtI zT-EdG%(UpskkH)ZcdoQiC=PiMqD*qMK*#Z3W3l^4Q6Q$Jv*U?sUqr95z(RB|DN;H( zg1mUlOzrS$DD2QugVtW|&Z6B`eE1f71-Y(@!zE6Ety&w@HBHNRiinjpXg5$g6Sx-U zWxIT{pPg{gj?S}M=I;=!;Nc7Dlc$PYZw>sVWp8u)l%t}K{OQ=5AQSDjR{^!KiR+Ec zC!TwUN5@AaU!X(aL!#kBsu;^Vv2mxGyL=kQE)MX^D#gE};@#ZC;tXb#W|s6Pf~)CK z($X-mrlrMTo}JWaToUh$IR`U2Dd_*k7L#scVk94nQbP7bM(&6c42T1k3d9~oMP+qH z@vCg=s_^H)q~2v69-i5rvZHSzgTE1f>;2NCmMLm$s=ObPQGqDs5{88y!$U+ys;6oh zF^A4IJv5R~6CObgCF#32o|eJo9I^MpWqx9;*5LM|_U8Jlr@STHS!(vaboKW#?IRqc zV+Y|6l>VB$_o!fXQKJQHS3y*}^!)0nN4Zy~jDl03+Hvus^R)N-#2MkO&PstafF4>u z#5apda8B$&A9@kZdaNDkQf0G0ba|oHSC0DannX$ejj;|LAbMJ^3rxY1H zKO0vA?cAxN{a1ORZOi4G0<`&vq*(D1la5V1i=Pj&nZZ_>kgzw@)TuTeYU<7$-)D;P z@0YE$qSrR8c8=N1tH(k9Zwwj_?v$DKhjJU?VXJN{lY)I zSpii^bs4q);?4e{YyLw9g=YLWh4()&w2XgwBt*^Z9UO&B_3R0lJ~*CIdjGNWFIwln zkh?7OAEu4};B)>h1^FY~_?yr9m*eAq19ED`bX)flAPQf2_T$A1eZIpYR4OHUoMbJF zNBC9K6l2bB;d!}%5fU%KbLyAsMo-P>a*^o*^^oX)#L#^RAkplRfYAFj>^9$^n<@TW zYHmCqdj)&H5@&ns_OLeU#?GY!$MXsRh*qEtu0A;N%Tz&1{SOKUDGGY+^>n|El1B zRmT5a!T(g(zu~C=2D$$Cdj0=3$n|gW%HK_y@oysZe>RlA>?;2Sa%E@z!=*L*qcZt; zw*0V}2pj#2l>E`){&LZ{f_5Z(Iik*C4P8PER5|KvNC`)n7_fcu?Hj|<=`wR%kpGVTu;i~!?#sccBx;jgYo91g>I{6HH% zJX=wvv2-Prn|S4!!3vJiGJWrBZS9+Ks$!KsPtAi{hdEUJPOK4&?Bg^MNds@j6JopZ z)zmB3Yo_0?EHlXi&x2S`e!;~HiUXrM^=|<1#H$vl+NZr~)9R;t1(jXxGnJ+{3~;no zv9O@ZVXF6PgkE*{rk-kLoB{%jQvROy&}6K7zQvniAk;yz6ZUPaxU^z7E}8Oz`i{#U zqz&^$=TwU8P*-G?&YqR86JX$LBv8-(=3I9CTa|g_VhK+MIdUEFV^FJ%X|fS~nxa$> zJFJ+`Z`~G!d4Ux*g?&sMNno z^uR3s1h;hO2dIl#_GwBDtW`=dcFv0){WP;`lNC5BMm=R)+Z3`_o^3!ttw`~5@YW7j zu;6CyW#OIbhhC1dBLBc~fhnywhl-@gY}-B=;lq`-I|$yra^Ez9Z6w zUEIuTy=dKexMHAPUS@Gyw6_pE<6Z$iU@%r!)!Q6b6%Qs?5f5Zn(cAca8{x(MY*$VN z_04Rt-QL>Ccbr!E-c-+q8OmS-O^qk!+<+fgX5iZn$!EN7zjJ8=B(RstZd~i4|T_i;q`qIc17&c8I<1Q z)F}9UsQdd{0&erpNJ+TJUF0(8_=seoC@czvb&`Eh`n3<>b^z6H=uIzysovUW(TQ=@ zCNJ7c_aScjRp-VLr|tby+vIiy?1DH^9;s(qb-|%R{e;`N+q$qusRDJ7Va?$j`mE4c zV{ttEr*wBhI#m+U<>TYYjatS=XHvBYoKxfc*ltuRfbg8(Ab2@z8hak%;>lj&DM=U_ zkUT8VJhS&>lyh3Ar0b|A(1Ybve7{nG`Q;6?hd{CkA&lEa4!rs_s+B#LiT#wG>}agz zVk$KWF$VEdf+mcW&`^D_b3->iZ4w@eC()^TD^5=_jpd}sYr2EAWQ9r*G0V-?Op~7n zgjrDZ#-6X7_4Fr99G9uTuYJzG;U?RH5kInO>_luS=ZCIDhZ`fXrZx^SSYYA~yFBCJ zY;nMH;2ddLqp*b)Kg@9iG9F-BDC*I>vrCijTbm(lj77ztQx|nEF%vFf?Qk13Ce-N&_!+o3tWIG}$kZ}O;hf>DVLQhLYtX?60Aj5L zV&D5Su@K@f0QD7jXfk#ru=at!IDxkFn;pr2aed+Z>^qMe6^Xy7&7Z*0#e$9t}zr>NMvFCH}q3AkdA z?HC7@gzYa7z@vf!IF_td`6UDi{Nuh48u^(@N{SC9?*|gE(;%@iF>H?l+3&mj5A5s0 zB?SFS#L0)E*))D+$=d0M@LW!eoK_L=1*hMi=8?aU3*zr>2@CqQ$bb7AnzV@OQzG1!pOl@x zDJusBYQ%2PjQZG!t?TENBi$7}G<2IU^?||LG?$cSn{en7Bec-Mt1A+M_rXMsk7lu} zFShFRnB*Zilu#n@d&S_rdP&ENX%tLNTz9JD!@$-ZkO8iK^)1ZZA`wJu(;6!oSfkIx zjc{;gaDeC*{Qg{4e*q0bHdz zg$<6+&O;7uY4*vQetvc-;FGtjU3Gk z^!^>m{S(e;@g?#mM%j5G*XL|Jw@vC(WOHEbPqxwf@;>{lNJDSwHN2A5i{(?R{to*gnqt zXa6HT{lC-vJO9VAk8ApO`oHr2N&Q#Of3EbOt^a!8zpnA$S4;n)1o(5Ne?1ehf0X3E zm*G$8{=D~}68`J8kL~~G^4~tEf2aGC>;LG}{Oy(aKkNISs{7BN{C}wCf5qiYe|Zi5 zGAwYgFc8o%vwyf8n3-8Vgbs`!a>M_ZVu9^LX7K0D{`eMX7@0oy{!uKjeF!f8QY>(= z|KnI-`P;nkoq(O?KWq!k%pbaje{2hXKBxb%Eqt8%k4WL4-rTb5X(1&5DT7q)41iZ?6-F0{CT5@VG_2=h8Dt;c&#p_9d;@e3qU$y|^G&i5bGr|e`fEkP? z#}(gbc|&5Bxt#X%s-CUPzVs_Ivq`69Sc<7^s;Jz-w{vO+OtA*sH|U*$8oJG+T@z2LFcWHZrLSh&SJG|?8q97oTE zjDa5G2O}E#vLX8OCyY6rer{q@uZitSeRKpS8foEg7-z;kg|`4)2ZVd%Waf+orC@IJcilK*+&{fPmpp^($*f{9iI45YoLa z`63_|pm<=q)pK`X&afX-xzGxCT#@W|-r|C8H}stzGtDF4$JqCyxwk)VqwGPQ`cFNB zwZk999FwxFhq~kp4@KjP=>ah3axvH4*}aNz~-Z?S?d#Hmv zh=vBYOI>clgb$tRwOe_92Z+q3m+RM&Un}r|&(G09Xl))X zI_|?o>~C{hZK~evQ5cf_PPNiUPE)o|{66d*q}YK^Lk>OATgqFcx%@+@`hvn=peg*7 zn8QWo=*&eL$-@M3_}of*CbEA$%YoMzz3atdw6ed^WEjeB7AM5Z;-aa=hJ0@r;NlA& z4v%Gty2odj##YSQO2oz=l*N_Fa+kQSZy2D26BRu9!5{hs9qKrG`HII5ud<<8k(~@KxsQfK#D!(XM={9(;t!DJ^AWa`;sv z60ET=l`X%9T84*TW(|h9;q4+>U*F-RPhe~NgtLrjYC^O_CSzVS2qk^yASkVLHY23u z7eF)OwU$;qxu5i7PJp@aDd{Odp`fTth(=!0$y89OcPljU2HVDUVcFs$P34gfP#(u? ziRZN-yw_=cVO}tXa@3CfuLr3FN}|iuxQgsoZMSF7luW;4vrk}WwOePeK~YsU2vVjc zVLNNKb>^VkGK9n~$o(zKyT%T&__^Z0PGxP~6Eoc`&NX3MKHr9#iX7yV!zJb@9e$$>EUps6&Gg_x5IUh}20Iga-g-;63&Am@ z$?Q7gjuvJ{&1wZxUq8fIbOTA1LoX8++B}8+jRVhw@61X}M)~QuDIeDq;|cc(rV|DK z$nxCs$g|@HCZ$YfSD<&R9TmS@haPfKDRYIZ>n!2JS(E^3gB#77Gr0K(x#ty^4X*EqN8-O6(nO7=u)hwJLxfSDo4o#56{_LHFSD2+j*{;2`>R%aR0KniA3tdvY za4rS&_3CV2TpINt(bUFDF=ks5JP+UODj8$f$GU|)Mm%Pn^&(kg+@s;6^Tv^lSnR2A zjdFG!z91=9g!t1lCYsV?2b1#K9OU2~E=-0OZ+d`;o-uOk@>7rGx~y4%srs0*NYjai>QL=&_`HjF}xkIuBA@ zQb&PCNd`0(k(EZzxlX6l&QzW*^&X2trxuzN3&CH3k-O@xjjNo-$oCNUv|SN86ZqR* zJMR$Yb~*GKs*w3NM8KtuZq2vH-fiZbPLQ=A(k)7EBrE@^#Xzzg))cMyE9}h$9Mls_ z!z6~rZwSV{4u>lA8qIlyrZh|tXUCq|OTp^_sf;LiOJP~MRI$k`u=x&TBLQl&w~5nC z(*{%D*=Z86VSPvL3tF^fg4c{2Q=~;RmGhND!6s^9yUEKr6`6P^@vt_=MFpLlmQWF- zeNj-VxESz+IVQCoc393p-8Vj)wrxp3Rb@<{Nl>^II-W^b!Y1TjpH}cYkx#w_m;E4! z5<{pAe&SKe4dV9*md7ucy-+yjEP)KL70Ov&(nK>I-1#(j#zHe@HMdhwU|3T zo);!0i2bzbJnPaU|D&dat|PB)4Y#b!+9fat-b$*)y=V81Q0Sz*T;9JMf*rCrXs(y5 zuD+=8Q|6)d+3w_S`wns%d)7Q@M5&DlDRV>o)o-;TptD#>*;?%b)xpH!oce9s3HFM3 zi?N`BhIBjgo3$>j$e@B{59cokScG2&!y`dY&Vah`FA_VBISFy;4NzNGGoQ}Nei)Us zT0Oby(qb$74AHcr?X5%w&EngO(}E9=bM9*@qyJpTAMK=gCUvKV;Y=op-dIiKe&45X zcckTd<-mc2Z65%U;y^rxbZmkorJ#cXttDwNr4+D=m++OnH2XCjsfI9D+g$8bY+Twyr#vP-|c|3E1*gO6l0x?%fXdM-H3lEr3eU zEc%WUC|gCDJ<`oQ05yG)l;QW+$)~&dvIOVSGEh;_qKi_(+p}WbeOBgQN{fBI95V15=7ASm~{Zh(|JDrbWByz?2`+O}})&E)Z0)(`9@c_)QWenW=8e-go= zZ5KU)!=Z&t8zm3+cz?HRnSjHodRV|os+ximUjIBR0Ub>BE{${kEXl5U8_urj6*>Kt zUGo#O%7=F0?IZa)1pNK;0?xTlq&0y($d47Bt;=6ND8Z1g$nXenA~>Co*oADiu3siS znf5Lx-}&GX+WmTa-&ulfT1D9qIlxLfM7A!6J~D`XWLS77f@jmr{|x~j4UzVhJlLjV zK#!sjSF1W$qrFt?w~Y$Wpvr*5RU!jRDNg=N#(nNBh!O}f2;Z;usBgYAT7#bKcOWI7 zF+bDil&?p7A-jPLOcJvpKZ39dz1*?mAk^sOee$G8`}{!rWl_l1nrpQg_wuX(SC?B8 z<+CUL?9ojyXadMA=ihvud$;$Fa za++;B%1zLQs3J(~2gDHSIDB-wA6tagB>rjbb`9I)!Ig!mx-n6w~M&|U{V?>`e1%*bH}zwj$|8z2rE{6konOKRT(*oZ|1IY_-D@CCJ7`m~2CaL<9QRQ^}SjoN@cuY;JfvgM9cep`r!L ziexk^B$OhRtyEU#yk-%~y5_j^IjYB|n~tofGN+rdpka65T(AvyOn1_YC>2(}rSmoJ zs?Mu=&BI!deAY^gLGZ%e_JMd4KKUBnUbty3Z0e*l6d;`kjQ6GMt2)oA3!Tq^+nXPgF8uTbKTGGgt)YVG_n8O zwnd5TW6q%&)jI7FNebtuNZRz*?C#Xw47*%iBjf$e@Bq%$>=v%|b4<-O#aouLlA(!S z;Z14L;5Fot?y2w0@`k5smV^fQGoQ>Df9L;SA!^znxWa)F57x5UG`Rk4&B@U;Y{GU6qiMKkqx<_$HhKkcURDAY z-+IraCF#Z!H@a%%-V}57KEEZv5~TaRgNjGmW1a5Dga>{=t+qC=IG^Tk2CC)GbE00j zB`48w{Cr~O44KAybwgB;tVQs9I*^9_nJ`%(fA0+cejDxQr(ITaW&Ag^HnC#_R!shel z)ud|pk?JA*_u!X>3E9oMa7f#+!fNlnUfONON8HEwXys0+=O98Dzag&GPxSSIkRmvP zfpJMj;51a0+c9m*B3w>SnZguO#o<06^XRwTJTTIPGe;OrqVw7M-lp};r=5;pZvw8V zp$z*5d0^cQo0(fuD)q$dm;lX>=+DZVbHYGGv3BE@q?RPtEN44%w6Chs>u9Llv_m`& z-T{Pjd9-!5pzr>=WvmYtxqZA`O86|)_sIoCb3t*yjzztf&K>SDa@hnG#}r^;tFahG zP=0H}>}POu#l>?yt>qeuJcbj4??!08trg=XQF>Dl;Fk-giVrXqG^{F{+gbf0JVd#Q zei(v35YSVsl>OLr@nn7pA9r256erzdHklpOE`RYzDAn{e;PY%P**|JTktA)$dQJRo zu*hw4=bN|1lw_^Srn?uKw6KSd=V5PWHS=rxMQ-Mv!gDzIac95DKZu*=@!2fcgso6^ zL_4OFAbkV1`%|A(BhyTof%ix=`Vm1aVq8TL(N48f+e<pr1?+4SXabb9+i=CAu6=!oqakj; z;AMyKh0bf3g4C!%+U;{M!4-T>kjSf~MGZJIBS(`zP1q7khC!dv-$Tbm>;w|w(^9uY zMe>k;CDizY^I5Ms53$MTwt`jJ!SOX-_JT2(CM%@lsK`wtElN?WMQGY;@os9vyxx5O zP5o^!TJDtH#if6h1_s}<+Z9p>jO2bSrK`sNYMkRho4rY2HFv?M<`$t2))Kt+Gu5ws z`<2`xA%g-%G`Vn2sUZjBEQ~MF90EUavU5mbm{(mQlyy_tow*~~j{3;v>@32HV6 z(c$g4q|a~y2U;(}j~=`%_xWd`g!NkWt$THAvY$~nm`Mj`{EzLdNC~jg#_rt^pA9?g z1}QNSFwy6i{&HgJeh^cLI63=6z0=H`AblA=<=8Jf0m3xYH=o%NhJKDff#20L^cC|H zw#C&6C`H$1z_a0=h}Li~L^>pxD?|J&sPS!76Q^gPNu#Grv|ehxHMQ6oSv{*C3hawo z2VW8@%Iw}BwI2k1eq<_>s^f63(wYJ#4QNYSttqJu+wZ z81;KOr6)!BC=Rq2op#*GKkYCs7+x32=!ZOEFmaY|ca$qFGW~--yS`*NVf4p$jFf)# zA+j42ekGq_mqkdxNN@^`odQG=ENMq{a@bkp%PEEFR`wE-ga~PVUN)Ln&q_s3mW3=H zW019a?PE;a#A57Bv~K0g0mfdmjd~a)ZI{W?`6HzBYA?_AOc;_|{vO}3iuG8Om)9Hk zBTWW^na-FU_v19#yWN46Nwc*^e1pNKgvWJgXVVr%pqXZY@QkEJ*-7g zVHaT+(LqGC`6Ca)Pvz6dxYTCj^Wh|AWVc1?`8}jR@^z-5;1%$Uxuw3shSejjxY}Zr zU^8okc|e3Ot{zt(iy3)1j4NxYwm*)5SKV%PUdJksHOV|-+VrQtJh z^%s_-!SvN+{e)o_Ayq(E+1cgGy5pyCpfQcj%8pE#b4G89tNKNXd8$!+KEL zaQY_FWD)T(2jk=GkU6zfU&&A~Hal3eOx?qLFWCJg4!dHH!%#5lD|l(k0Q{WOQgnn$ zlZ>-Ndn-CP<*9}1hd=j8n4ol%pPwI9u++@9itKT$Y`*_M&ZeA52pf8E7-Kz#Popj+Ryhi*&V25$$St&PuKc{yrZ>|8kC=-oxZ(WeDd1TJ zZemP^E)8%~@G_Hp@&2UBJLmAqxnUx$%U2R{nryGBNs3XwaCNK6)I8rf(9vI6h7_pF ztX`nZ6(AxSMI*s+G7D9pdAZkHw);gqU+9QpbVkBa1suGf_rWXA(M(<)Rm(m<=Yg2E zdB7jbAw^goj(`Ld}Y+llf36_}KRvyWVfXXgl(+_uF^tZM?rj!=FFQg;`m! zZclxc^t#yc-ht4&zJ_5Z_31d1y_TgL?Rs@(i&~v|8)^zbsPf1-){-@Wd`A7zmwyz; z9F{s#Vf@R8nF*E!MO1If!7OYK_13RyRJUE^K9+7fS*j?# z)+l4%1W7QIgSG6b8dH|K#!M*Lde@ zw>qs0eZR-uQ1AUkS8X&?;fTB91T&KbX3||8eS;6I5RDv>cq zkmiOYq+|SD9oym0D(xy(PMgz0XpC-rbPl`1v<`ee;(KoY;vF-wUHvi`f}~w{ zp$Opw)89g7-*Kx3$1p=yfYx#sN`p#vEcglr-!8dH^CZ9nv7vCZgY|?f%$*it4=Qjl zAYh_cu%qNk)v|iA{jr2S{V@mO;-HhfToco_KvsxToj5P|TE#Aj&6AazsamY5ZKqit z@*I8;ZOL;#rBRZV*(RtYAV`q!cldLPh(~|G8j?N{aE)b2n3>43RgByDKNgT-vUg`# z51qC-H`W3)L2?4%jz4CL7a|6y5TNt`pC&k!y#*}st)(&+ub^9_BZ}ZbnU3UjaFS0F zLhP6>0|V2r^DZ&l6ezJOzgnfq6rB{MqsMdk3-W1YhPsM$`Q2*x2Fpzy5Mb*l8r~=r zVO5eAs8v4D#vcA!OXK)OKrtA#O#^tS_84InV$4APrB;8-t zCoN&8%$W6N(eKyz^o+)=rDEg{S_b?DMlK<}Im5uwQL*0yp6D`yuu~ibKi=iCDeu+| zvkNa}EY4Ppkfy;{s#o}8rvHiQ+w9HyGc>oonf~wJojcBV*JQK~NtMm(b}mBJ%=NA> z>$lB(Q1xJ+6Vg9>P72`Zm+k6UEgO=8=M9(;3>_f$dxo!6!klQ)-nVxrHA;{{k|faP zg$aWXeSTm>vSbUiLek#+tgQQ)$QH0nj;?DN{4sI?Rks`3`MaDj*5t|nyuEUG3btGw?*mu_jC?lc^}#VJ2+TT4%v&UUDDc#>@^eUnQON9m+F>19LdeLN%vXF z8xMB{p5L!j2$BrBauAqT7*!=uJgLh+6fTKEBu}&0a*_?|{tspaQhW1E`k1YbPwewJ z@YaB3LZeCAtl-eZ^oB09y^%$d9c2_(Rn$vR*833%(wh-3VBF{g3ZKh$h-RzoJif0= zuUM$rl9zAEkJ8-&#gev?O%vT_QMY<^l)?PXF?^R=c{iq8hxZj2A;^?b6>UPBZ}t17;4sL7je= zIrxd(_G91i7k&*?pE8Hi@*+vwh}4h-6j3D^jxUHtdLAvmKH|r%R`3*hobsz<=$H{Y zRNW|k0V|XTTP`gCu8_~+2YST z@zp~^QMXISHy!UggoCVJ4uSJg!sgNJi)Df?$}U2kxM=Ty;T@GX zcY9~!_YRvKH`nvvY7`@&bNByO*m*}av37fyBAtLpmli+)sR?QHE=B1b=_LrlN$9-` zA|faPg7hOOf^bfgGK2kE_c5JJ7d@A#di-gWP+{Ih?vXYc(^-gnlTWIr>fJ$j4k zVKg*)Qbj8KTn}Vz!azNh?uINwzy$sGV~mb}OModpDVNa|g|PzH^LY#^aCO4oKC@${ zpxN??G4bAMxpKncDO?=+w0a zUdj4gRm=I0IZb$3=vlAjndvGf!iS5(7FTEvuhQT%Y))1@7gNv;P9%M0B$?e7=yy6s z4O!f5J4|ipVNO3@pDBE+W?W&XKQ;Ho*ey*igxKS{rnjh|z+xqco^~zNXNCd=C=H8f z(hoyl=|b5e63qm;-oF3-E`WoXxV$YVv7DsLsEFZTI;dh7efnedk71`VG4qMC(M_F9$2u@hI^Sxe+w}3S+wq15a zVNlv3ORASK(@-$vqtf0Ye6}*G9>uIHi@E~}`zWnp*6^~q$>vjva$8^kYsKWlniqC; zCBc3>1OU}|sZ#um9_Ee&{>Px^&n_HubRZJ>z9->l$R^pS3ssu0S7;ip%6CLZWA7Hu z_$!@|JT?Ru&N%bWcR~1RN~JXdFUq(DaWz=PooI$0>v_NGqY=3K%__u4H}`%!%Xe_`4&--K2J(9E2N6@P#E6&2awl z;+3EOZfWR@XkVnbw>PxouzwUj_vm?%d!RKp9Kw7nab%;=(AiUIl$j717 zy*Qp$A-&yB*Sa?Nfm)feSLsVVqkK%>7)mp^@x$l^QP`^tbro&%>#@AD5k~xX(t?S) zSn6W4R5S0I1Nc{STX&^_S8M0>ydgQ z`>>2`ubXbKmcSBEmkJHMTTgd9!!Wx2nZh;pm~{{(_Mu{A!keR_9l@PA$(vOX?M&#YL5hEqq)TP5*s z#wcc<+Qg9+=QV9+50B*W4@OIZzmrIEnI=INzXkhk6BB_*m~KD_C|o94w!0>LzO{yuB$QTfdg<@ZP!iX5a;X6f7_L-}koK6kT892~PPkT?Q1 zYx9q4*Zug)xJkHxfkdZ{RjVfvKe=^#n#whg2hYH;QKFIklz8jf5Way-i`HTJ2b%L2 zf}laqX*~H94H(OyOHsN`pVf#|i_9)9b(*n&AS_LvbanQ1Yo+T_4sk^V1Je$wX05b2 zto&Lap7UXexmgH>mYJ{}!+gc^rZE0G6Tecr@=Zo>!@mZy>?C^|#pa-cZkd|ANoBlT zZ)B8pyrb@+jkwxXgv9SDc904;+Gf^Aq}k;*QGfmmL}ONW^ z8q_mA&P^jw{zLO%bx)}mL^ayli+XjJ;l-?*l=Jawo6IW9jff{&obO6gqEjeVA&JcG zry6+`*#fkd1`PB}A#E%8^o^`VjW6VRS5-pVHr%hUFNVDCG|#ZY`K1@8)dylXC71Ny=|XVZcpB{TehO5pUK%0 z!Ka5~tE(Sxz0MNA<`%B|Rmc22+nd0U ziR8wx+k9ZJDCK=0g2*H4XpbcT|(b=(nfq@8J|eB(VVS${dr2A2m6|0%|*DG&b)!7ei#zQbEOyVNZrER zdD2h}WfD+)AG1(4GZ6QI*yeF9)%sp8v)mPX$7ABGO}R~A%528f)K%h;K{5+y>eD-{ z+FIj`uNXTUAhNFPtOT{>r9z2c8V~sgtchp5S_*H6=_Z70dv8-k*BEO%!p$(z)#yFR z@_8dlQp6Iav0HzU>u&i7MrnPx`B=KlhB92;1Yr*=&qj=bKW?zPtgLH9vu9>4|e($E*=-dPomU`sB%^C4j z5@s5BFO`&|dw0bw;oG_%lS^m{b9dAHh-*o|sArl!+u%Wjf@HyX%^KHiOSE>!N;77w znuF`PQ({be5Rj2L)C!f}8b=3Ll>4N7rDa?*5qb<1UM{ODLcl^YZ>><-d`)U7y7B7B zRm{N1+?9q_PE&be%+3XwdB2#W)}D)#SD{{7wtZ0>`KIuy0Ks3`OvJpD*%b03S;<-fgY&5fpy#tJv77vcuqWN;AUe z(?=rRMU*DpSHD)|Yotqn>^HiU#8f3PgCM8Kt2UgVsmFYLg z)K%};V>0?9cKe4N&BIE*t31Rr%rbPQk#cNZ@T`o5_C)vIdO}T-UwwHe)+6{9*{5T5-O<9*MoC>1TrS8#?iln4B=V!ekkv@%<||R1A$hKYt(@1 zpq;#B*%*^c4#^rZQ7uJbG`&Ss1GO#xDuY{d9K|gazqVBMKsJtG!FH0S>5A9IB10_a zl@1Ymt&uGBg@PS&=Y-7j6fM%PNmCbns6^htkzl;H7kU6@;odTdNkS7G4K5>NXXVvi zP`SI4{yj{l+7@NE2-y1Tet2|M|B|ZrEOB!6!s3TXT6-90IJyq$|C+lJWZiZ=5pmKU zVMKt>>Mh_Ly{fy6=*Qg~ClKduy@OH0luB57^RbnE+}{J~C zH(mHX&3wO#tWvwaW(Tpas>PxbNpQBBaaX;aLQ8tg!_>fzQs(6W!|_9db+(E^%<1#I z%*h(0w$H_j^*GKWl8nIhB9=^6HS(L!)cDi$N)70`QeS!ju+L-^eCUpCC}j|)b({L^ zuRTNO9J|AQGPlm^T<%;bDVRn*WnI^I(Vn|;bJr|8;~)tp*sxF%^R6NF^^-69K}(*66#SOH{5l^+DY3w{ z*OuN$CA!)J+qJ}p++1i=;Rgs;C;vJ_QGT+U^Gb*)zTJbnesW7zl@fT1Rs#FrAiBF@ zH@n5|*Sb;$gpAG2Sic@^u&cpsXoQ%Rw-(UX*N^r8rH{zV@-=N3Slj2_FYT=7JEmF8 z5Kc;?snaKtR(|rFW;uO`l3*8P5#pC5NH&F>U8%AVHp#$O&X-vJ`dp=W*J745@ToqV z&qsLDsL-cr62Gl{0@0K7?n&p*0T{Lj`kj(ujStv2VR+6(CrokqAHN-Rthqv^K0%xp zW-e_pev$i$gHlFXZQ1tLH6%w>nyNtO>TS;6_o}>q>1NH^YDc2T-b#_Xyb^FW0a$%p ze~?E>m$VtesOv1|d|g-30Hxb|UAK9i!kD7shOS=T1p1_lyn6-qmSI=|hj+$s2i_?0 z`8odHHDjJ0%cw~2M=UajqBG1Zlh+36P_Y>HHM+5v}o~W1qELdq=Y z=g88i4z4x76MM{Q8GoJQ3-EN4iZs2QI!g=Lr=woLz_$XsO;bQB(#6E%yl`NN1iQzF zU9cL21Sz~e5(k@<-QRsV**msn>f3+%Ec(n^(Y)kYnDu zS`s#Hlkc?3^|OPy6Oww-n3wm5pP@EQHN_2c+ntPRDvbsyCr^%v#M?D2PMA}tsAv(_ zKTH>8yNj;s_>3%Rvxgb^<~*D^co56<<=Q%pvJ$+utNzH6cHs$2$yb9AodgeW->5g) z@lcyS_@cIT9M2YrtDBF6sp?h`sv= z!;nz1x9Rhd*UyHHPNnK8|)mX9g(`FXO(*E_cr-`qp43?P|te#X%gdd zbk*6(qddDs@uHoBqUNfjg}?Aa8m@S_Pu#?K1<*NKG&57?)D}FZ57^6mOC{tQ#Qb@{ z_?|NZ+q7x>L0XUW*1a8!=y(_^`7Xg@@2H18l-FK_f5DZfSFwCi5Zb>o9M*5Zrf#^1 z6WTwVb|OvCmtyfHRQhpz0|7e4LCf+wU*J=Jk-eu9dvP^5C5Og|i=F7A%GA{Mk+74v zEM8w8#>bcoonGg^)>Ycp14&;;diUIS`F!6cfqSBzG0gql{CU^>CiahP*GMf5UA#KO z_u2ue!)yQr1YaE`GhrR3njjzoaV<*j;2mzjXAjC6lBP}VJk9#16V0jKOu`|Gt~`gN z(LQM4w=9wl+B*;$s7VFRHs?5DHB}KckWdp(lSq^DD|yjX3qUz6s6| zRU!~i1lJ1ZCXPGK0ZtbV8SW5{Bkl zv{nWa>)NBHtrm1en$OwrRC+(42W#5~F%=kmA2T~VZ$xc$2#&6OTOqGJ_b;;Z#h)x? zGV23`vkW6l%qIa`6M(ILKwS=#*(jiJ^^t*RlS9=^*~E4gO61^1!Isc^dL=H~2!L%I zz}5#~n*`LoVUl{yBvrzs{$|$4hs(2xw(=9I=Bp-{gKcHI(n~f$&pD z_@NMfW{A`8sH0QVQ3%TGF5*;UVw;oZLWtn7G%XVon7>a=Zqy?~@-yqOubKz~icR{9 zhBYp6hF>%=3?}+#JOmia3H<6Og198Mf6<^&5D5Fd|DyfJ`c;F1L9jpaiijZo$N>`( z`8@|1CMt}@JATQ5)ewKwECLt#Bc6!JC5ZCtv7!(xVDh^L68 z`nv{$L;jdUSPk-f4y*?MJqHX9{a^f`@ZW33&Rx*&^AxLHg5p2N;pSp#?}&8yu_ATs zeXvUlOM+;l(QZKSKTAjjWs3&>!)>T20F8kXU~7bpFc<-`gxgrdA(l|MHPX@wgtUQ+ m3L}uB!j@8`|G&$BAQ@LT>_zFvB80)=A|j+WZ{F5WB>f+g{D3I{ diff --git a/examples/gjf/molecular_dynamics_results/argon_kinetic_energy_fluctuations.pdf b/examples/gjf/molecular_dynamics_results/argon_kinetic_energy_fluctuations.pdf deleted file mode 100644 index 4a95d23fd12f51e6aaa6c5ddbc927b06e2e4d566..0000000000000000000000000000000000000000 GIT binary patch literal 0 HcmV?d00001 literal 57374 zcmagFb8se6*S8znxZ~swC${d`n%Ficwr$(S#I|i?l1wm}*mfrRW}f%?>b!rPQ>UuC z_ugy&y4TuWy=%2DN<}dV1{Ov(1j^xq+k>;RyMp=QQ3Q4%Gtl1n8v-96kV)3e&cekK z$nn>t3}lk9vT-qU`diu)t9 z`R?FNXh8fF-txluwQJ~O<9+AA0ov$|H0Sr_=g~*o>&1Z^=<0Js>0?)8<;>`_%HSth zuR1J#`03}LuJ;=sPtfnyUpEdO9R`=);kxoi?>7!!9sG>ISRSETrnV&-AdVj|F)`EX z5cwIQu-~RWysYbNqr(`9=4E9t_|=F6w_4N$lVn*7ECH^9%| zCnu9`zSCch)wSiiyP_-N(^LqSbbG{h8d$J8c6F z5Wqf=y?p;pRt85XrsTGR;d>OJeE7wIlC!agjbPLCY|lcj76AXyn}^s)-vps+>1LYU zdKc+>xUiiNFijYB*TJdaYl}*iDB9Y~jlFTe`n(8l=g4<}Zw;=HlRU)n+NhqB45`Z* z7kZkbARE1vONcZG-)(WF{bT86pc}x4!*YNhZ|>F6ts9*l1(Z*JojOR{L;vJVpvRm7IVCDaqN7aFLpntEASM8>ou63m+BkNEq%R!rZ?QPm?E< zkpNIoyaE?y8(z9N7=I)R_XrvjB^)Eo%Q;iH8SW>R{WX$o3w0D2>}GQVB~FST$6SP^ z@RUye!`tP?lr5ZhX(>S-ZE&xf7v;pozk@6|PLxM@J7FA+-;zvm4~rkw5+!k`NOH(z z2ZeAr*155xA7YS16aela)VXm3v&u>3EKEqw5l#=`B*5p!5DliQS#8UvRRRJR-nOYP z+*lh&f~jY@Ak7Jg05A9fG$7&Rqu`XZvUVKlwQK&ZtqTqsNN7#d5VG6dps8~kL!4a7 zRiCEZ$4;0E23O|V$38!Dz!@${M#g(YVj~`mU=tJUstHxfsjT^qo)A8|xp+JXT7c8R z2k&r{;gTlLE_()Nv$qI9(Ow*v*xSQjr2bJA%T_OqZIVY=xnbMa;?qe+IijnA z@94M2|Evd3K8f)~6jvDf=oMR7rRXTic%p;22zDILGh9k|5T5|n>BtAk2+G<|iqHX0 zp6Zgcl&$k9L0pKKet5zxvD8yMT1=F%F=9lZ9+@&4xI`e@OR6RV0QYookpbXkZc&f` z9}~nio*?EsoXgbYpAPGL@rQ_JW`Px8A7^i5(^2U%qn<7 zd%$YikhPF@SQKbh43J{UB2BKYWIi!F$v}w-n-&p4jM4ftot!6X4?}6 zCc>3W%nYR%V*v+j%FdrAKZ#NN!5sf%6-_zL9HAnlpJP&>=xi+joJR13 z>H|QBT^YNrz&K0YOj|Lm^}D*;4`aj#b>j$zx+cVi)Nr98>xR@CZ5wcOE#!s+4`rKJ zNUmXkYjcsP4fZ}V8{LBw{P4(ZVGC^*?=HFI0X zir_M5j*WulL9nrAc1>AJt;l9<%Rt-hSbQh#a&QFiAe{{kw>D4|U1|>45*MTsn?*Kz zqII4zqXy)#1cmzo;mrRS&Iy(L4)Zm<+utr|Lo$~o63)Vd^w_>3tff&i0*5_&;91g2 zbzRp|OW?#Ss&X@^h~wcpB-raJ%#cSUb-8ylSdh9StZoJF%sc6kP&zZKpW49Cd}2?1 zv5S24@fBRVqYwd{|H?(LPy8g*3-_Q;cf3p74Q1nd$B4~ zI)ZI{x_>(|ZA2bx8COO5F$q$fiW&&`0T+H~Cg&IzwS%ozzTB*#$aQ*ReZ9m(^*)8Kmf#{fmql^f>5{E26z)QNkh^hZ~-gyrHU;K2D8H=cssqq#2VkYxTM zV=dn z+~NvpDZ;=gVAdGi3CUwgNdrlvy6{CmFPpdvr7%#epui&@ADof;r(&421-V1HyCm)c zOkXP#;7;9#=BpHj!!r_?JlJQK(=TJ=8T_LUPzAF))m5r}-Mhv2=rKwj58=lfq7^2D zQ{ZA8;jb@d0e$|cQ1H}H2^G8fu|O~uh(wmYrpL$vzxd@L=*YBHIC=2#k*eQB1GWC{ zP#r>?TdtnF^^I3NV|&M0@k^(y^~jP`S(JY;N^5*7z{^*Z1o%xOGAiA}`E#O~TO?pB+w251BB3J8__%(&7h+7iByAL&kOC8(Y|{ zIcH}M@q$+M*H5s3OPye~gdN}RWH@nG2CJylKY`lZ`N}TMR+%Mt75p2-2=1ghoBC*S zkdBCCx${9%yjGtfz(u-sL8Y3-p#Fd&l#msr`LGg#b?r<~G-(jTPlriC^w_W^Ei_Qm zlrFVU>Ao02Wl3KV(2l`!86sMjAT0)$y`>XhG|Bv3$nq?X-;w!X{->PauRHa$`S#<6%{;iC0I$v zXIh(w>bPv^Bw3b;Mg#;$7`CoN9q0!5Qo%B{?TsRu6g9)4L_D>fnZX=J)H3L0nyCS8 zX$__+VYD^`L*X<(@(8SB6b}hHn@HI{bg{A(h&&d#Y!5Az6$#(212oso&ieaokOE2) zG@o}KA%((tWbX?l(MZrZHsV>mPmT?{4Lkwy)N*TxFs{P}Mr6BfWaVC5A|Y_<0DW$2 zww1C{4w{c3X@V=r(0-d%-dhyS9nzwo?bI+(>^62rW{F;*K~3rLYe!TIRaKRy>olz1 zg4}Xq;$Y#m7yImx%kycSGFdeZ~UYrXWWX$YN?<|V$SKz2YpL~O!F4pP7tdh`_ zqd*AJDC+Y3y|Mlnd)jAdNo;mH8xWtnN6Jv*$*Pds_Q(i-tF7%(HN739-Zh(vK75+e zS8@G!JuT^*s2tZg|Deh)$CA@MiGBl$!)PT)vn_u^2kL*JfWxG;h2$`lLHjXCX(i!G zn8YFzyiHHc3hhnYVn2xmynRUTla9TAKpcif!N@+-rTiko|ss2)k+mZ+Fw;qn-^NGm&#;bQ)Wqhb#z5mf2Q~O%yj#+mHP_tVT=u%9&A@0Of=x40#zW_(rM~ zLp{-048F8|tG(nQz*ZKij9LdZQ;BIJ(EWVWO=?22(R>B&mOC+DB`G`x4`~;UW)Ss6$ zPJ$q*TmJ7*O3e<3^Ep3N%`RKt&_YVC@PlB2gKM2FZ9KST(Fz%q?pK8qyPR4Ooz(EZ zhTe(5RiC?xd>7ba? z4LL4{?4Su!WTcCgEmf5yfbNjNZ&zH9jlE-8N}>(YrOc73%;CgRa(dCOge%HX*quX~ z;rT-4Nf9<#czrGhuRTG968gnHj}r?2Wg!(v4kmHaBn#h{S%h^(*@wksarVv_09zHE31ypr$AXoe7_zOLypJ8 zc1EEDudGS}3oWG(5|T(N0dnTFA*1RropnBB;IwCEAJ1n9TWFkN}cmM9SCzG+D% z8_**T<**jW>mq^=-Ay*ui!+ca`l|igQC0-aT1~k?$5Xaw(q0SToJR?baAmCZ^OQa< zbS633xZ;CTA+{7c_}WsG4tfM_DozN(yRr{C;k%_4DIC4ozK%8>sl=>DrGE?U1Tf{CGcsr&~AU@HXx)Nmq(x7JjaH<%luxkHW6GYn?_aaXs3-YjLP zorwDy?^5`My(U1i>WfCgSVUy;&k@XJrFAVGjP*qjh%yaX z^W3rCxOOVRb%m$vRI1u#x9g2u<8s0^rGttPuDP$9iC-w3#e3QM#-%ouwlpcCsqw#kkBHo}Z%E6GC~np5TE!lcpJ{;6 z0zkMNgjdzbJkb!20~NMt2*HI%dEzS3xgAQ)z2f7^lO4SX;iU<+Y8^8^6=?)n;`Gdp z_nBz}$0U{dj)14`BttZ8E)m+#+7uLH2?xZYB2Elw^JyZKed<&6l}7*J7>$LW=h&RJ`X)9|O;g z!aR@<0U5c+>gG`cAO>w7y&p&p0{c@Z@dI%Xh4EkG0vM3?`p|83Va0Idpp|{Ph&uTG-Kt@`|62F2U0Ku>Ohvgp!OFwzI48*)B$wonUq@BgStF*N zCCMEO{`MJ4!&iO2+WyP_JQJe&rOk&kfq=%X{nP$wnu{#O{6y*V^u4>FErHCrJ-L(Y z-K<3S-8x6X|H-}E`I0^uJ(mR>m6c>tN`=Ui zo>$$dX1e*Sg_iK5Rx9T4n?80m+HkiFeTSefMTC*OMJCv3myelxu{7ostFZGrm_ zVWo-m7^sH4NsSe>yVM4|pr6kPA|G~2J2Z0{z!eS8(dtxjZZZVpyXIb6gd!fmh4fYC zgV~D)_B}PlBYiY-B$7{vjrM`ytkH3-?H9*fCbA_A*wTTB`QZ5M-*jAs=R$>4;&_vhZszYD2!X{6xt5`2IhN{@ ztD1D2=rv)YvI%sBFH$j$k-I}8+-=dau5p`O7nUPhwJgMs$Mvm1?v;SyDluN+dmpiv z=~+u%9Dab(KoncG7~Lw%Iop%S&ny(9d{DH;NSV>u$2p`uGrBSf={Z|w7ey%81lr?^ zmHVlRz{yE8l9r@;6$cB(%c{7X#@LV>OLB0^JN*-4@6eK0cbnMSo&5qr_wKpx?H&f)F*go4Wj)#H5|9FEkP zloz=m2Oi0Du>{0P$=~gmru$rLU>yo#tWzm4B@j1!UyrzQLGx*|SU8ue`UdbA`+nqF zmJzUvboV|e_z8U&E@>eY7Zy^m@+@n2xmzW)Ox8Gi(a)Ifw zvE?37zz4g8*f4S-7_)E%kL2*oGU|HT^ER0C8?0=qVKKfo%$(Wo4rek%Mp3jZDjFd` z$t>Iy$U|Ga6?%RH#6U3bzd}*YmOuc-W*WS;9f-?QKjUimC+wlqX8t)L-C+@ZO#n09 zCn1*G6cX@|wH=aRYNgC>xm&&G7?}s>gw9nf)CzQOxQ;5zS(v|nHjRY27V;ocXaH|K zot*f#CPWktPsO#0{;hvXe!$N^J1=%wZKof|_QkTbH;5q%LuM2of@Or}Js+xQo46XK-d zX6q8UsaR%qK=Qz7cLq{xK=gzm`8`^@87_Is${V!WNaFp3*VTIy@m$h(-o#0AtA~L zwL4O8$Q`W<$DRsMOV*r*JM&>7x6x+6X~tZv1HpcH<;V@nLQ#GkPShW0O~Wm1F2&Td zS*R$m6+L=LA^d6F+Clh0Qg~>|LZ9+3Ybj@-Y1WfbRXpaGubl}D-nq)HjC~j$5PBi} zQk!g|Hg;IAiOj0Njq|Z-g;Ey-la2M2hZ53qW!{^NIEnNOsVWeOVj?gN$tK{Eie4fZ zTyf~UWvLO5^|m%{+HfaFv$Yx-_0E)UxL9H^DCwjwAHhL1;0YRO4K{mGAH@CfrvfP? zTYtpCsOVs?|2pm#iz))UxtT`xoEC&cly_Q}KPlp|ZA)j=_&QKcJu~sVzrDLtD#dBn z#QveP;L+gd4kO2D_h!2AklRqq-d_!i<76f%AK4J5{+P?BE>TMPt^9EyJ?z^R zz{SA4zKIf5uF+Od2PV@-XT`ibk0tJAvUSFysovJ4cF|-a@H#SzJ35iKLu5bqy7J~{ zH=xz_u5y}Y+4JC}5dHLHd;L&FyS+8md}n>|79KEz)^5x1W^T0pt@+v}*6sls4`{GD z@1T|C=t}wp zmPVt7(VehBHx5F;dcHX$Uk+qnCw)Z2TqrW{Qm)O<>k1 z*)2hI_A8d^bv}28nuL%@E7deL-D{eMMf#AQ%5|Y;J1gtIPh2B!82_}o9=v&1Z%y{c zt~xqt|87;E9WX)QyxQN+uhApO6Ypw`WPHow*;@?EHLbZBtV5prQQHy_?Pl9mZ@J1z zcQm^fQ+uxUm8ZRFVtgV;&aFS1d_gUE35v?uZD$1sNp);Vdx!3kAuz1}&VeP;aNaYu z>2z}~42QmFjm>qqKbse_K4*C%w`2cnr+mf6Vvc8{{lTmTM!m*mwQNd-{a#|ywS%wD z-d_K>BUcWWvE(K{;cPbMj_OO~@lqcr5XFv0<3SyR>7viq*~8zcHrMIk`?x$1G1zwE z$ur_tWl9C&Z;2`S^3MMB)f77WEsj~69S^2RkeC0vzVc3aN>#rSjYeqkH(V5qw#=5E zj1+E+q@{6I#~@ru5hubtVR2lLl8a0#gBTWp@cZT6_P|UG~}Q1#1#0XAM^XQKR5Kpv~R5Pb$s*?Tw$X>rXi`E4lCkrVaJ7rB+E2_ zL?RAu?!xQaw3tvA(&>|w1)P}CLEAp<*Q#LWe4S)~X!C$HNy|lolf*Mb+Ev%4In@QJ zLXFw`V^<$!NqbrIOt?QARVoIDE?e4&^GC(CJn-TQZnE)Uwuf zqYKNU1k5-#4QzK0vGS;r$N=i03FwkL zqDcH|zvUgf4eTEEh89aRwB2ze-|d~6PUNEq_wW5L4})a*?vOt>tNTm5S8X z2en-9HTY=AUo7VwoJvQ}((Bv#Nd#J&*zvSDN|?#&25d7fSnKC$2p{>Vg)Qv=u_CY| z)ESxcwY?XcobegfI_i(w;%>$1YN~Kw^_(!349K|I$B$;k#oTM)czoCk_CXq3K@BL} z`9ZAt?Mmj$>u5#jF}sqE?YzS`Gl!nNF;AxAut>isz4E$LJxjr8y`S=y7<63$f#8B$-tcR zpphTmPr-U%N^#;1h*Ss*krV7)V1wRIT?35wUdU=$dJdNlSl&&DU>YoS1B`|?ryFab zGfN~Z8RrnA5-!na(Ibo$-c|?agNG9g$j^_IYtVP9hY{_f4TwN@sc+Ya_a~65T+h&@ zDM=kLeFd|S@gLhbvh%&h>zm-?L@K=P!K0A;`2~#wMArs-g{_9DSrv_3+=jvY{TdH; zUz=dTWH4~g1CgT0AMaa!LV{6$Tluv`Cy156-FoN%?vw%z}FrO z+B7=3?%YPfF97M_8al(e*w;c+xX+8t=*d^5^8VnRlqv8yvi8}9uOBKD!75RO^GMlO zy@ulLpOk)sQV4)dK@g@p&_vDy8cQrQU>Cu=mZRMsIiKTTix4`QA*fpzAxs-{Wr~!O z)rc|^ci4ubfQ!NFCDXKn!Iz@3Ez@ZP)07-8@Q5LKGKU^_yTExRMdZnn{vqZG@!7AR zULie}7O`N3e(_V32M~!ARc1igOs}1qA}~V1su=REFBl`7Lm?!TJ1CJg`v=nmWL9wt zX-C3IHNoc+3;Z3c*kcPd`eH~J0R4+eJ-lWey{QFeD>{^x2drH^JXTC}*piLNme6%8 zfbT7Ker~KC54VETm z@|JC;lDpCcVu8IsAj5ZF+f>4VU0~*W_Q6Ev!*(MFEsGWJH%J4oTgH%Qy5U1i+s#kPCY*FYZwXgj^h4dJPA3k%WkJG~O znuc^+6ek_ZX&orlXLAZ+Sh_hc1KN!b?F}i7)hvGG&WQ$NRsV%0N!OJAD>iYP>;J z#+HOaEqmWI%_>XWiR$T~-7+cp4aAy9)sbW(?i9o~MY6$PBA1kt8DMFl^6@N<_wAcZ zcB?U7VeDFsW_E>sEul8;pv33{nqW0&{093%BG*okX#`32BcxABtmaBSw|P?TNyRvr z-8c3%X*z64>PiBZ{6yU70IxkAu^aggQv-h>Bs zt~4aA5ua=EVXpidKfu`;7P#RrLP-1T0o^xD#5hvY1%CjdC1^F(fj2E`qPUy5ZD=*sM4uA-_^Rz1K#oR;N5)nyT?7o`pxt8D&lkFxHxBKZ}q&#?_t!*k2>?a7b@77 zX$6~i;vS1&4Z15>&Q<>U4NrgHKMTa|-AWr|wjyT3^8zCdZaIGCsM>>9U9TB8;=PdhCcjk&dN$}tg0lT- zX~{o7${@34r1{2YcK}Ez85(T^H@>}?8J+}n28~I%bBVij8J=GRu7WW!-{DD+7T$4v zzS<)LCSRkyP+vv z8MSJ0(m?K3aIObatC+0Zi*kInwW_-ZR_V+dgiC+_>dYXHhmkE{B2uv#MjRJ~kaEgO#q ze9MoosmKWpp2y1Grub5*1=B1pJV}L}hiP~62ysH>`y$DsOcv40z)OSti9s`EmV9dF z>-*D98Q;zs)R?t6J=Lg)A35it$fI1OamUY?6u9i6<*$s-7?Er&Cuap6*-wk}fc<;q z(wLIJzA~BzHFqPb`c&atbA+4U$BIB#dQ}GR*49F5WVE-!nMk5o|q~?QU+~Dx#E63 z-h8bYcDvIfhz!#=ff)9Xerg4>3SXB`sIM{Q~6x3!s6)?ik!w3#%Jn=_FOGGqC>k7%z zBe76DxREll(CaP+w_ARn7hX!6xAc+I5t>f@(F{$J0NWRdSR{_7u^5yT!lbc?JKvkr z+E#E77G-XhMFC*;G?sH*mWTy zR!Ls^YASe2e>*8YS3=AQ|69*n)|Hrowbb0Q49++)UsWQPIs4O*6fjXFOef()PG$s) z?8o&z*f@T@hLFK9mnCc673Ax znptf*DD#$jlIUHV+?9V;8mRrCm}rU_^#U#WaZ zk?yXTLRf;Cb+6#+UXe zhcPQG3K`NIm?ng=gw)501ZkzNtZ_%rJtkElC$r{&0A}@w!bZ`$N-H`lFam+F?#Aj9 zMH^dkc#7wGc)oIY=Wn7rFHsaZKRqL?#<7PnH1%pN&6Mxk|NgV*#BO+5rK=<|aOCH~ ztN+Btl-`X>7Rk?g6#0ydL{1t>E((ng zR)$@hoPZ0dE)_}wAt{0(34@6L_k9Afl6e*=u6D=y%nKNL;U>+nbaCwyDq=S6$-gIcRvoj7*`2uBY~a` zOfn(hybl6C4(x#y5`L?<2yKDSKTd5p`P4D&*nb%PhaU_Xp|A!V5}u3{l>RJq%(w`O zzeXaAeQscImOn(JZyILccYPYp0r$z32ZI$}jk28HxqGnia>L-7-t&BCSzyUh;FlsIsQy3c_c_=zGGm_v2@v8a1SrnFFoG@}HFUa@uyk zF|}A15d6qIxwaYoi*ItxC)sPEiew}L&!b{pq9H5lFggvCr4*M}d|Wd!_;!T<9FNF- z+)yeg(Z3U7Jg5`y@QjMY{S)Wo0}dS4w`+e75`_TvZVCbgQD+AZCG(A*G^sch>Uk$2 zcq=;DpzaszV>fZ7Mwi)rQEqj`O8%ao#zrc{Pf9F}a=Z*+t#O%1&FW{Z=A*5~=>Wfb zY^jK?!gXP7ng9dXpZi({xxxl-+V2WgbkRg90(uc&^VNxN`xh6R!51qUZDjto?tZ5W zj~uTe;dy6n~emiaS`; zXck8EZK(NSWtTx0j?B>LQ}7rD?AkbW=_UPn>LM(Y+o}O=Q9nS8ozm6v!;1etTyga`6ej?$yuAT!&b9Fu+*WLiys^<3SovQ*clUs|uzEW^bk)zJcM220Sc< z?^i5+0BmO=mGKPwXlJkJ1eBJf^VCSBNgABqXOEtE7ebdBVlBtXy9vjIS|uLZ$w%ET zwI`+go{s_&Q<&|u+Nkm_m+VwiPO^g!DD-6Z``zT#z<;nQSdxFs!0 zOg{rgdJAUVGDU$hX-QM|rk_O2^*ql88>`7RL2*G;)7ETo(m5ZQ37V}mSy-Hqtklw0 zBRO59S=^^i(I^Y|St&tls0&aFl}u%n1cvu5lT=DF=$LOJ-31UZWZLBKMU>x|w-d`5 zh)rs@s7ez^gEIoguec-N$FYB#Dkd*LC(?~jg}IQmQcjR#4%G^*BeqR?6E8;oGO>ut zk_`euT?S=mLDrm{vak9Mc_JXq^+vR4l1{Vb1T;hcY zBB^aHgTgV(6y{e0PuOn~NN>?3sejMn&D@e=(EpwdHpz%!KOcbJ!g*xM zA&%PT_y#jF{u``JzZo>+loWIIivrJ0nAJ8RhVXP7kD{2V&$(0g4^)o~c#Uzp>%AAB6ZJl#Hh)fGkTf>ZOqYx_)c@t{N9g4C(gr05B9!Hs$)j-Bv?P@e9g0}t0pF5lc8DjXw2+|l35}6jFO1`i4rJ4+BYgs9mACqFKj@iO>K0Z+A;)Wc`mI7>x_eg9 zXp%fzU{DDqVIUABp%I;s^vM6_%KWo=&+9IDP+Wk+qR;j}Q;CCv3?I89Hv|SZt?In< z$+j?k9xOz2#to+i4C3DuOKVA}N4}Dx?<;6Xa2GbX6gF%kyW86xn%Fe17$9LdgP8z1 z-Uze3ZvIQD{)0_(9*&mBkU+a3)Fw~x^_UGSVTMjK;oUt{C?Oz6SRB?E0*`3BgP3Ui z4=CHhhSUvAZJ>@u><$TF`l*ywd2n}yAUF$4P^Tqba@P}5_T$`RHfrj-Za@ocRa^;; z|4gU?nfOh2YLpo9JAYNvXAFYt=E(z{_oa+M=+kOl%KqCWq()xm$0MW$4l#rAnVo{x zTE55j=?qtMknnTh9$>Pw{cbp~m@Wak5@jgq)`rCx!ENCM6regn-?N@oYQvncykDjFD5x`(NrD@y|t!7q_&U8o0WUuchuXDd#Q>s81 z4MB9f$4aw@>V#)kf*KKf)6jt(Zu--s>Zi48o31L97PEnpAOi1y55lk?Rlm+GPPckp zNqNoTYw4L}FM5+I9#m>sr9%8Y9K^FONcK2k*Vjo%+nuPEAEtun5Osvdk#fJA8qP~N zz0rC(9H4sC_pTu0YaMD(Tx73$-B;h=gfOM)n&&+S$T27Y{2r$Io>5;v*S`#~_+;9V?QT5ZI!F5~)|Vdk zdFT0n4)C1_mep*o&mvcU7O8lx`#AsonZA&2+kPE}v(z0Kn_vt=k62C#qT+;rp!M`cqhqc+Yods_mB3+Z8KEtAOU;W>DarW=v zg&~4;mP`RB!l7&$9vYh@LU0r!LXa{I;uGGkPCo`<=fPWV689>sT{ZakTV{8Q#{ZMKur=SzIDma)p+0RggESc!$4uw&BNtwS0E;#N8$7l^YBLF8ve~0 zD(ov_K!F0ITqMJllPdCOWVc{}3VB*c>69SFx0a3{qH~Xf%jbeC8Kxkx9M93 zN^`r;sBT`IV9XGqgSv3j9>lAUtbULP89BXfMJyJTMo0?^EDWV1;x}W_ zi2UI}XG~iq+b*V_ri}dsyPu@VzKZ6SpV~v82@N zj_PVmQIm88u_iv+4=t2ZyPFYp^P58S=L^N7cHPJp&;(%)(nzwG@BPN50PaYSX>v1# zxGvtVn&5>cNrEQn3+2VJ9&-@P+}$%ZkHdY26Z(a3)^vC>xIxx(ok^QI3S7k32z{y>HEym}7f%o?v)}CBAvpp5ky(mkxf1eCEE@*^~K4)4-(#Smv^{aeZ%~dnHo`)wIP(EE3Pm#A1J!(69O8 zpiS2&%+)t75*4kE@$@K2t^%oA2L+^68=_Af8ePbW;lF?r2^k80%`iC0n>UY)U>J)2 znJyuaaT>Ez+*L4Hu%-6S;NueY^GN#SPt_+Z<1hMI1T#C+|ANqeYybG^f6(;5l7)kl zh5cXmzXt37f~!?M9n64CibfXy**cloxd7Sz2eei;bGCPNGBI-oa{iA&)ZWhJZ@)9} zADsP{#FjHNwK5X1_W}@ta=E4VeJ3<`M2Nyg}4=+>`he6T!1=%ory^R znN-a@T!4B&CQ*AEdnXkKBNH>=Kh|5+nFYx8pTi3X0GY%+TqIRo{&L>`>63J3MPT_C z`(NLZe|0SX6X-vo#NW{Vqfu350doIW@>jv~KUGy#HXzHtAeH~3;{Ryz{|5MVpLJSTvUWLC!Qyd*o5)(i86=My5Rl{+&mGwTR^?U88ZFSA!%6GLB zOz|xUYS2X!Jb=AW6YKJ9KoL1_%bJ-9~I64M2bq&2p;Pv)Z~3C4Qm(+E1(d*sG4kV zxX$LW?2xW&A|st@zYt$*7O$Hij+1kMPJRZIyfFT z|8vu%@?y+Fmog-`6X78{ci)T@$BYwDXP+hxPN`*^X_AcnPwThMc{NiH0PK-MJDaGfH&qR+*%n6VV5eH)3J7)!4c5Gsb4MIz zqn|Xqi}VFC`uyC+89d*bk?xr5H9yFHvM&tulsR?zs?J-ABN#|7jm>5zeo$Ig`c-Ut z8VMzR&h-5W?Q^dmWHmD}M4yx2k8=}xtfq9F0v{4-*%itcsF}cMiV)(zyyK6{`2`lw zFV`B&($xUWHx#7UE)6?w&krU_4oP7r=mp_>rh~?UFy7m3S(8}j9M9_YarB1-Q8&tN zM^>0j%LN5Vq_8qiFkbmhLv>?+Gkh8zJ?YB8!_bE_0KXzMiO;FV?I9nLlU*g}P zgSw>|fi`^2ApNco(Q*V!qS5mZl7$u!anvE*gavM>l6%Q_?c+cpTh$~te1V-2Dwp0^3 zKYU{k#x~B?H`+j*o;b+wLy#cTVgN{-YZ0Mn04Wd>kwpw~9&oW}N;G^PPIH7rjNKjx zcyP8}5+?cp)^4y`__n@^-h#dq<9w1ql8Ow*0lP6Gi|?~vzW#i50f3@Rz!{1iDK&zw zPenIMSEDMi8e~cDj0YEfunTJk*VelUQI8Tpm{% zW07#0=s_kQznJKfs6(Ggp+n>&^-=KF1gy~gy<5>Yw@M{jY`d<9FHll6B_~1uw|jeW{}+rB;Q>Os}_)eq~n855E(#*~c7 zYQwm)%PY8APf)=T-y4T@?3Cb@F86DV4-^coz3jhc;$E<*Cs3;+h5N`=d8eud2P z%)CzVP7R-tt|`J5-7vw_?xO6_>`uK5z1(dBl9HIxY3f|{T%G|=g9f|MYyMpg@~V(@ z$ymvVVOhncxeX=VmdUzFSc?Nwa@JC|*1?>rH8r&|v4t$IUfvZb09Ai z8>|-EivuP-Eo&M1nOl>xtGBBQD4o8jh;U!4MAXpCka$=Gx-`0r*syrN=)AbBsE25x zsB|KLR;_kVEL=UDuz(Mp00+&3)Y-oHab{gQc=v1vdiR2!Me|SX*@}Jre(~sJMYK-0 znjJMh4guaK;%5j-Pw~D?#hp&G%RcC0Tx;-a?BM{-VZ^o8lhIoYXktK3z_dtWpH_&0 zWQ8P}z;R5E`xm|F9i4HI#r%n^k#q=UP?ls)TFyy4s7 zS8q0BHWw$84(E@cw{Erz3;6QDg$m8pW;qwF?w0NQj?*YBLMw^ot5LDh2qT(Grk zg)D`t4qemQ%Yy--W+8>`cDe}-c*}lEG|TgK3jXrozNY5vbEULO*Jpo z=k>9Nfb;hJhx}KUEoVrVwe{ncTR^hDn)dQk#g-ia@ERLVj7iAUpk`pV$yV&|rn&n!>`NIwKWJ}PdT&(Px!i*iA$ ze!aErvfjzloRgML6CWKPk#mXbm`U+K@%+J_D5rUzxkZj5j(GN-h}ePZUAsY>_pN(j z50uj5A1t}ePoSJcT-Q5;PXw14u)ND|pe&lx3n2}8>}DP^9-GI% zX4CN|@aP0mKRxflACgmQzjBUD#!R54rE+Duc;5&O1YU=QU<7lkI`X&F?aicDR8?$@ z`X*LtUpLzqueQIwDJPbiRB&nWc%^%_p9j51Ea10h{Lwk{Hao7rv}!-Lt$qKqTOQc~ z=5_d@^~$jE(Bicp`I(Lb5(fTqLEqu=slCQ`?6vVe4N;7sEimTJ`EL4daJHL60WD9R zQ6fZ9Q?VY)Qa+vT<0M1Q#N%3}I7SwL!|sDtZe;lb+A@Mv$=#q6@6Fm$7| zL*T*pJ^R(*ZZPKfO#VqeAu~e2#S`l7#+BU4_+axf;P&-@V!=N$^dA)XlI;JjhX3mB zzja>{T~b(BNYBB@kdWzLt*`ap$NWzT{1+V@{!cLQSKm8*NpmJb25B=xhcEU2uYTA1 zPnrCmnDDO%7uIvsv$Qe!mrES}3rPM$w*Qs&|6d{g4*)PII_W$9!!v))Fn;la^;dc* zGwUxyl7?U8V&>>ZC-GNnI~aTcfS$GE-&S8I#qQM%miz%a#!#)4z1_A1Cv-;=fPkzfx5(aedW&QOf@!gy2Agqu)>lee{25kVlOi{`DbyGh0U+dqU=aA@l$Bh<_UV9fihM1FnBI zcE&FN{i4yo8!HPJ;r|m)|1|!eBmNKb|8ys(XY~b%|C>{OWk56e3*-MBA@mQ3(=oAg z5YjPo{nINeAty7(msd-E1(TV9ptXsm(bu3D1pj)!BOwRlS5W>N3XcCaVG!1{l`t|h zF?A$lXa2%d#jp8O`P%~UZ!I+ImvII`XA@O3!@v31IKEauR?qd{5)&iqSMl%Kd^!Es z+A#kc=>IV*|9RKpzvASpmw)2q-y#zs3l}^4SAYMvu-R*e@kE_p7Vw@JJ3Av?CQU`O z1BsF8@!Kv)4UjG}Wq*VLijDRtzc|2`=!pfD_%XaEB*FN-sYp;jKo8i8H;UtI< zNVH2`!_&e7k)~}yA5jMmx%Tric|G9Qiuw8F=H}%r3y;IWTIQjL^(5Er7;Sa{B7r7o zj!xavK~UXl6soLUdXS3Sty$dBgXqt-NH&S@7YU zEDz5vFRY=&sG-HcMTWu14|)iw$%p`sakWE+CD- zACI%vJN=^e^3&o&@D&*s#BQX~Ym|<0lalamzLkXAdv+J_H6nmfBrCRMev-xb&HpgwL8dZh>vGI(a@> zCZ^mjes@!XFXXawRk;A+q5G{ojay=@NjeJCpN704q`;T3@*=K;$-pnmYOoudQ@p?* zipOqw&|ge8e&rKQYTmMSvS;!u*7in#6l)N*iD%no$$OiE+mT+6_0^Sbq=457VVG1EN~BH+>QIY z4LU{03Cnhw0P}iZt>V8QXfv@sijXZ0F9Bs)G3CqZhU^I{I4WN^))?>hk@5+nanrnwlzzebl(@-h#2C1fmFcM1SKOgdWm#9SW>~^7HzIFr;kg zv8Ek;I?DWviqQ4TU<<2{i~lNxj*2tdQIK-`BR1}R6-y|>b@d4iKS&TmEZ{2WAe=hw+YSfGx&3_A3d2>A(Q|`>Ch~K9i1#X5`g2?;(=BYd?$43kY0x zZw)vyO(>wbte~o>soRL7<%~RW{j6rO=4-DN{VRW>SLdjAmyt`$**X2IVB&l9=*D&pf%9@y(^)#bM7)w!$k4Pv%%(^Ip%_6d2W85s>ThyNXDL^BE=oyqXpz2inTcRMhyrCDVqS#73C z4~uK*)&pmH#YH_TimF;lv!yhppqaX<*N!5!IminN3Z@RVJMYV= zsi{g;LW-zqyjM%V!D!Z3l!R@4q+>Ku(Uw%H&?&E9nhI)chx(;#TBw18E!+s0!X(Zs z0W75Cn-dvm^!O>y*S9?^jJADRo8J0Fh^t`z&XfGq003OeAwaJ8*f#;JM=4e~m z`Frm%zst7o%tjN-=}Ty-xX%l2dXRm-O=xKXXi6ttwe^4}5cn#uz8&hUm8dHH(j|OH zvJetYpbf@eU8af5S#eOseP;XIO^(W_t}7bAy560h$XV%(bUs-0-03C;vHo+o=|~b8 zTGMl@>UU$oKVKp!TK|q+H++)=b3x5P-TRdkW+BT3Fv`$^usOfPPteRz^1d1K`j*1r zNR44Wg1wrUt0`I!lB@a5me{5l-n8TGl+arAaHD+jmLf>;T(P868lIz^MdF{Dt>F92 z27fMF2@hYg(w>&UM!MFl7ZDiU0yUiWyqMAl_7+7 z(P;;%d?nBWf6jUQdr<7Lke9us{lXc*v1*k$C?*@!3goTh_TFcZJ1C}AGw3lRZe4F3 z%(qsbL%+Pk32^aGndK^{GzwW=doa^qe_$eLgro{vK09fUr)d#& zjc@VEe@8szI-h-$IiJ1i41M$&*teTFNBM9#hI~X77CdBrDQwemSsj$C25=Kw8#ubg z=d7(Nhi=WFG zZ?B|HfCQ#MAH1Z2pK-hal*yH@LVM3VV$MOsOYOqU5}55?gJa@v@{RB+ZjU^@-beGP zBATgvyeWiij9sE6m5hZ_yD3pi>n3C8%=gY~bC1Jvg%PHpkUFGS{=zC+bJ@j(D64T! zDD*443!1D*JVYr7#4i|N-dqR@FGY_YqaYq25a7KCpiT&B>u%S5rIp%Mr@)(h+g--k zL?2Sn5Mh#AnC87?XxLJ~i|ckA1O%}Vj2dG- zG8XB$7(KhkjrF`E;Dvz1{mv!k8FS0WTXTEz!Gpj`CpPwj& zNBb8O@g#9Dua6f$d+wR#EBfOgmwVDu#{pPm|O=~gH(9fApGFXE>34j+!5F-#(F+&9m6ybXRPLhm{nd2Xq4p2sC zF$GkY<2}%@+7Gga-yid;Ko>7!$&d73 zsiNvrVXHu6h5l$vHMvVd+ke?QcpF$al)9H(9WVB{kcUf7i6MS+P1Z=|2?yUgx^KA8 zug%_HFAw$<()oCKN$+fy=WOHV9Fa&F=bkc!IbjyJ%TkDpk-(&F?{oPkPS0c}epQ@H z)O|Y^Lm`I%KfmeRxM#3t-6k)`6es*M_m`|0VFc{J*FD%k+`DXKTTL2*6>6JhIPCY6R;&oS7CWZY_2y+|V$-|(gn|A#ijJ~U zj-$toW7cthiRLTM_FiX#`$$|?j*yi6G4OcYNjT` zuCm+lM5{ywEy9p21!n2KI*yKv8WRvxBqV)z{f{)o2smT4%G>-r!9QNscZ+X!s%I0@ z-3GWk!RS2Nw;_BaHc-G3ViXb8=icR~B+XQno9q)v&HbuT6>}@r#5*~)!Qs^*dihxj z*6R&iY@~hiz!6#SS4FJ+$c%DYaWje7F4z*90RkifdNZ0c;WF0{@65T}!a&?Afl(j1hq5SkQU=OuLe+#{4HJKt%eb&*eREA<_WTL#EnK zFHF>W=KkBD9m6?*y`GGd#q4pXY3G?i=g#A3p!`7^u52>PXOP#5CvMj~s%$k3=AH@U zCv3KGJHeZ?%3-y>{ESheSMC&ktDtOM#*jjv)@FIbpp)ep5pu5GG{giy3g^<9>ZZLa znrWRk_nePM`hvMiyr}>Ez*A$Wmx1apFdyByT~I%XLGy0 zt)RtbCc*^I!=gCs=q8VjMeDEXLWUW+G3Ei}dL0Ogg;}By)jMdQh`jAB+Eaph&sDG* zs;TA5Q@rt&Abzo2xth}V6qLOWHxZkq)XFe{CXOK;3;|w@pIC3LV?*OrgH;hL`Z*cl zrTpQxzz_)R=p`t$NQN9FxQxd4BX4FUr|5rDR(_E)TB5F1p$se(s!za-GTVM*O$ik4 z&YDiw}EwhQ`m#0-&^|C1dWBQbf#+?R0l_%C{>pP)E4V9N%2y z6VBO@InLqb#z?H*tdIL$#o4vE&X2#Ho!ub7Hi$7A#PVPA=QOsM8fwd7lNhdkb3iI7 z`g3CAyxwC!J(TqFDmE@>uCr^L7~lr95lrVJ@bU~(mA$$Px1!%nT<1M6Y;$$;^C)X;o7Muk?(* z-JZv*t}BBVtoP8|v_H28Z%uZZh#bkO-Q(M1n!Js_NB3@;GVReTo^))L>}i_kH9;18 ztadIAo$X(nbZi;y`PMYns4hq@Y}UZ6e>q$cUk>XGMjaY`h<%WIqYFgIZ=pO}e#mtM z=nO1gN4&Mav3pZ|f`0OTGJj(Gq~Cz22nu)sYR%X0=1UN_y^oAaTWoU?=3G$iqyC||%!hSKJFfSrh&iHG zJGLulBmPu!Ih>qGg%F1Y855-t!Ec-{ClhWxi&}hSeYXCUf84WZ(RKV0;he-fXv6pO z_C@*xy_G;T#_>8P5RGdQ5%vmJ z>n$bWAlfJV9~YVwY)&RlyFw!MAnqK0_i_?A`5Ca`)}3}C&;$}?A52y=*KJ`O&$|*c z+TsDbqS_M52!l;)iBzN&DF`no5W|{5fq~K|nuBbF}ZmJI=!_v-^2RZtxU`e*KaWih8aQ5aBzd~-as~uR0;|*WC z`BbC!*@K?;1Er|}ZrC0lXY%z98HLy&x7%?Xe$(7IO$jgg-Qe8{#Y3X!a_Ltt%@|^N z(4$iicU%*2|3%m%tCf$|Ls58H$hW!eCf&yiClN93cqntC;1C39KeXaNt#>qMqZ*uJ z6Xuj(C)LIL6=7TPHi~I-e?(6TCPz^Z%9Jb5BC%|OIgVW{>sEuo#1{szo1yOR4h^^x zFxE}Axp|32SrTG?%r3u%mkL}%=Fp^kGQavk9^wgHXFW{AjtX3|Z zNUoDOx&NfNJ3iLy^oHqLG4%z=i(@T{p9iW&MK~xDD77dj;;HcU#|-l4*QzMG;2abs7oFOtUTNtZA0}J6pb3 zk>YW8nEo`_673a*X{8^N!~kCEwk{?^{d;XU3^X==#Mo7yA+ZS+x)<}AGnSk&puG(3 zY|!yK8+v!YogJ;#sPb5URp#fq#X%5tR1rArq|Kh6*gggqPAd>>1iGzah4HGj#JiJ5FBLv zqlJK*DKak{kH;C7>!7oB$&e!g=Ik~xav33{EaEy&-s+y-d*-%ph2b#W`qI0j&|I-CbkRAH$)BEdI*tJtig*+)y&=9(XC*ELX%jcjSIaS+8wvTHQAFL!?TX!U;VG zUR0V#c~5s{YR!1*%%E;{{D_>^j!|96BGty!R7lKuRTPX;We(AR2h(F zVqbKup>iaQWiNdfg+0Qu;C`PwfLnb>yV76RKe=Ss9hBo$D!th;J#1!wZ;={m7lwxT z1ts!Eq`!nRvnoHP889Ncd=0Z<2C}{`34n8Yh9$2) zAhW=t?Tmo})^_AiipRj|7US+%keDF_!m!@D+N-QxMz7r$GCIy}UnSZ(yzTlatsI_s zf)_l-TrG0yf%kqoHPD79d|>V&@-&7#7q(ns(8lVAVfiPT#MB^QDXPrDGR&aV=IZCm zlXV@FrP(ixyF{_Mu(FBQwHEJU&t@;7Z!aI1S{zK-+ADO-qM}Iwb;HBZr9ZkNF&1 zVv4N7xxx9FWLQ~gQU|Y$5i*7}X-^qK-1U2tc*jO)SSIWg>4xiHvqiKymHw2_h~7U5q1>A!`pL0G&%#a5SlzQ?SGrmceWrxul^BiH%5wrB})86NVM+0$XT#WI+hTy8>ljt zU@5bZOm`mr+}a!sPA0p)VjvSkzBawbiGOT+cjuUimDV^=ZDxCz z<*mJ!0_B?u4nb1yADKPWB`EFND|giWXzV^-3s(Q=4B_rgBwJ;jl1sL}ex7|gai=HG z^dmT9;y_A@)-trqx1$mdHI2Aj6e& z9QhP~&b#`)Q9?YR*R{C@efJKw6^Z4=yYKb{Cy;AeM@h#6lZct*kCQwm>yP=Nk*f`o z1F5H~+ti?l;jum*y8DusVR{7jmPx0>I#6Rb9sRa5GX9YIa11`IKbS>tyRO3=pTgRJ z=S}O5;V=$oYPVow9}my(L$GMbvIls5h4W>KwC8`O+c-%$6{9*_UNk-CsmDz6w97^s zuZ3RYo5f6|3Qq2|jFS?VE<}&Rq_+=_rJ=!xt-+A&l`d zogCBq5W~rJ?yqMURa)(sg}vQTpYSwki}|IeEo4|b5=K$2`wMg1h;*ZK`^zQ)fHg1x zTKlSN?DP{~+nW%fce(CI#%(+6*%hxDXy(n*o+gCYjx^9P)>6Nl2Dd*Cxg_2t z&Ui+yVOtru!Qg}Une3V2hMG%AE_O3cATH|qWgO8N%LlObdniv|d-r?f>F&pf)?Sb++-0Pf9G}e-25$Eo>siR;0m&19KX7vU_8Hn6 zZ8LPy-1&C$rgKMU+vAzz+2u*#_V6pO5iG}sTT29C;sp$+WR|*dsdqj@eEN_vUQmxKy z_`za|_V^|1rNu|iv&3!40n51PINA6jaldmhF*4qb z6UCB?n6~BO8lFQ3#2eq-nqB_c*WaztcZv(9^dPWXH*jaX5x_qMQR_(u;G))+Gq{fW zxq@y33FOYo{izd##5&yvO?N!O&?|P^iz$9SF>7P_adz>%*=}J0_W(EI z&+DTEeXhGs0j@dUMcC5%6*HA|#UUUN(%f(*sE{Kdr~k|%m5aeCRze!2Ow1V=Lg3A& z>=Gm1OrL#Yuv`hp!RP*vZ4ew3riYqo)Cc_#FvLvV>@A8H3H~Uh(gS|1dWML{oKjC> zf(;rq+>P&wIPK74#GSan=DERce5vw?Cr}yqqj%`?6Icyx;3$VQhfl1*CV6jmA%{Tj zS$5U2JkhV6Lz(!O;TG!HGCYQep0gggzXTrkVfhMVCqAj~#;IJ3XPSzazc~iVCZTiO zEI!IyOR$2ym&*gibsur`sZIFrv|DY0KNx}=40t7(rvR4E??Sp=%hD9uPHl&>=nIcn zsI-@0e~?f#^zHOXsj4k>SVzl#lGfIUMzim-eM?aHokB^a4q1z#tW6r5%3f)KX-#KF zV1!EHxa|2sK^gNPW0>Sv7*r2tiT-t7$;&-O*8|n15_4zY-PJ?a22f_X}U)zN*q@X*VSsMhQ)a*w*Wd0ZGNNY56jj z$6M*S!h5v`_JLoqJ%@h1E{kImnRinYO(>nqsZUp=97P%-EbNcGo|+H+i~)g`MLOoH zq!96D+Ydbv!_Nif;=uBEnr%<}uR@wm0ORQI;UVt*5?-@9D;ZEu1xZ7b%2E}ZwNExe zQG=yCJT9-B3!hg_u~BzxE$EMK8Y%pqfaP0}npdaJu=&DKV*{34!_}ZBu;iqZWbu<2;2e23jEVBMZ8)-Oiufj(nLYY5*8Xe23V(=s1aDl*V*m~u~c}mOdtt%bH=-%sc%Qu3ZO7q9o2giE)U4WAbc1Z62;ECl2R6>6Bv9Penyl`pLDijjM|1;;|w3GMR z9KwP^k*Zo?<->9h(VT)(R5jy9{_M6fqr$%MBd{af7EY^TwwNTs7L zkov|BA_P_-{DA`}#!_@SU*N#zcztTAMnBC(aE?peSImcQuB^Ww@4J7E3m>@arI#_J zib<;MY_e7KxOsxolErm85_`nvO_UCU@Z9Bp|%NY#K>m_qhvwB$(>T= zY+qa3|I%oj$>SU)vKRaEJGBH@n__RE`$dNb*TG{Ewe7`R_jI{=kc8w<=iU;go4K06 zun#*?TYdS+U1^Ah4HrFHXS2bxf?6xdRE13!KRG@;;&3a%h-g#7O30hS`nH$v1_CaY zgJ1oUce}8T28@(MYM*);z3T?=nP|hH41XV^+G3QFj37Y8%J!yw09Jl!&bnAX<^Q`9R$?yTg(x>x0}jZ9;Q!>yfuA@6DPgwfQF z&L8khwR0n9ca%>vLmlK|$6E+}d^-Ompdf?$q?V%W1Clpo4yQmFjxeN7_O)Rd>!(1- z$%;V@Gl8Wdg(DDsqN@H*VFslZR6h^hhU9}_Mr`$T)}>Nb^$`8Or{)Q}t$c%xFO>d6 z72u;#AKOuYJv81i_Z{TekQd^WiUwFd00btchP~+I>g6*QJr23BE@y|=MG;i>HIsri! z&hzn`j44fZf*SXNF}kvj8QNx7<2Bx!aoIHf!Q++uEyH!?P30{`wGVs5uD}=@&WBt_VaPq!wbpuD@Bou`s+KIpMsl^n$-q|1j20Jx=QBwU=>kwnT4RRMe7nr)?pD-R+@l-CVW$uh&zT#1#HNwYB>E-YQij$n8An5x+==LBXha0TWWmX!uaWxW2 z`x}@5KSI(5){~MiER18E?M~m3FQwP<4|K3*2A;f(bcf?}k4f9PZrl4=WdGdMNg5dN z!)oKk{;A$%xMw2TOIvPQ5GTJxweoq4tm@mtN|fqY!PPWz*9>J$2H~f)fhRV82k`fKzbr1)Z5DB2K)Z-@cEJz-&_~Z-Yb3^ z*QCqgB|gS5eP!dpq|!5es4pPykl%b^m@p6x8wl(t}u(kBc|6| zOA1BKT51F8rS!%p0QnE0qJs6wt~%fH)WbgAA!aA^Hhzl^kK@ltAC;Frr)sO!w=p=P z12F*yg?0Lg;JweZ>sIfRTVu%Ak4MhaMz+^-F7f6fxXAiJc1spDZLd%HNa;aUuey_W zlgNzEx);wr4@B`@@F5<>27)x51f5#FP4R4mae7mqG!YTxqs7{nd#^g1DNCpVBXa7E zln2MY8-&3#rBfHmO;h82v0QI|P=g#~N1de4_~-_43ZB=>)KUiT)BsWxUhaTsJfW0y z{Xc#S$Gv=!rKOoE#pztScV($$CA&zigR|H8qC7S20>*eDBF&mZ8c}j$l;KCzi^~j3 zl`&y>`|M`tNe_T#TPjHP3!~ood)m{K>ybX8sl_E}3RNtXg@x6MLuC0!Ps3*Fy-a6L zGAf-N1h|wCL*`_m0^wF3Sb~VqU%Y5gZq)eL8(~BGXG))_+#6tdh^_PchFp8a^Lh9P zRF`BLS^Mvd4`rFZ=%;V@$cB`Hl|xSW?7=f7xaH|%fp)TZAGSP?I3<(?qf3R3U?o%> zj>?z%BMXNeiSkNuUs%kuMIE8`N)ztr)#X#Ofi~nggnQhhFAAb&3y*H^ItlgO)#pJk zec7L)cp_&|?i#1aKS|zyW#ng0!N~mdUtpT0$o%$f&ddS#dQjVxX=_aXM|uz4_E?kM zg-5ju%|1aB&IQA~Z?C)BDY(zH*6?&kd2d+5 zayw7Lyz-$t|DI_A9csh{^+tDw2+r&M+O2;nHNC;PvZ>=#B=#j}>?* zOAP0c#~Xn|g2T)J+6UTC;K;-y4$@-1%**0MI3h%cR&ZuuQtTxe6C8T@SZKM7^Y6Wn zB_LD)>>)H-@)@pK_|0lY=PEvn0*LYfrQIUzy=XF#k-8eYl4ovd6Ea3g(SZ2;6&dZH z?`cF6v03*KZolRo)*?gzodM=<3r|2xUOINUB?RgY*o->{+01 zXiHJ0g3%)E>@d6YyKA|=jV&d{Z-XrX@US_Hs-sw0U<-_#;F?ljYOB7A3ui5$)6W~8 zeetQq(7N0eFt%ax5Iv%!1bE%*ht06SeF%qww=Gl>sG?u17FAQHcXJm#Ime%*==UHZ z78DyKdl2E#Y@P-XcD;|A`l+4Ag+F9aeBYQLk_$#@O$im_KXVvqP5h61vkS?5dP40_fM-TR!$Bou7w zBZt!IJF{)_+K`vK*qOz`!NVSD0Iodzw)(!~=?Z|n*drV~pn7#MW&swIuf(W0`w+k< z9M{eVKqo{VM2)H*F&YW#{n%#jwf~BAjVCJoO!W*)}G0{TqFGJWigU7z^gWsB0 zB?G!e?nnTjwQY=+scGyL^#Qnx58DMI>udOG5naLa9`PF?{giuXt_GWe9tX4+;KPLS zE=*CSu$P#yO2Db~98RGX%F)5qGB~&inWs2C@_@Sqf)oFtw$8o%;gtT%gY8}G1m0H^Wi@M&|0-o-SoMF7Pn-a!@ehci_>LPyE;9-TL`3qK40GB zG&@E<7vb;=>{fpK6~7;-hr>^AK(RMzjb|GG0Dw?Ay0M&cr@3OS6}f8(%KN5TOkFGR zA%g2>;g$?wdQDUM_3IDIn+vsK*2m_Clj<@d4RZ=}GI3WwZ6bi(qR~#oh$SDS!a6TX zqtEtgl!DX&cPy_siA+KR-M8s8FDF38z?{|Q6#SXB(5%uTFXqXb~WbF^>Pa4hi0txd+_xI|W8;{K& zJAs^a6UO?(k^Xb>c<0F<7KSDSQPQ_NXV+L_|@$}4I1xRt1Zi54~Mq))#K zabqu^Z+-LXOmLf|j24z$QRkha1@b(<5&@k1YU6jYI5>J6yiIUYH5!L+QsOFII5@I} zO7*wsB01smli)DFxJxby06dDQcw}Axe1`0lIk^4Mqu0UqudYLQ)ac;) z)8J#fXRu+YF?UC4fV=OhgUntnTRk}tsTJ#YwC2OQ%3aB!V4Ip6Gr9B1ht4`5L!UV= zai&#)IJlWdLBI?=a`FpUj%4Y<<6S~qQ&3}F#Ibi;7pD-dNq2TaUKr)r<3kP-_r0Rs z!;lT>-y8q8dr*Iq6{~`e<2bQ60Y0!n(S`!%afM!c=@F(eK1#J}ubA4U>io zYRsYVoX5*hYQ^03Szh1UT-)FW29DVqo(ug+y~i8R7OJud9u5)B%GF@xuz zl@3+qv&k?N(@XE_QR*VNzyN^*A2G(z)nif{h(Vw3lr#j)9pHkX7sQ89qvKJnhvET_ zLPHW}(GbJd^BQ1cO6z4Gc**+EFpYyF6YF!j8C5V=F2+|G8=P*)r}KCUzQK4d1z@t9 zeZ6_-Gi+z~L*9_3x5pAZ4&72IMjnsY&LPd{iILWP@fdhxHu(j@H;@%w=LY;U4+Lr4 z6%5F#3-xSM-#qe0u$6JQl?QpF=cv?06Y&J^-M%)egDW2N^$3m{-P;%5qc%r>y68K2 z)Ik8~pgl5T*D4c65ddKBF{GA$M297EL`#Wox-PN;A`$k0Ty^Dq#7!a>6VgRolw2Q{ zKIo1b7C9C#qK|h&P4s|7E0|@GB$wlVwcgST76MDWU)*ZQ5?&P&%^=M?!1W4_;A! zctD-UEPq`8jL(Z>6iV2KhM4 zPF4|M2;B0!W+0e2?6hx=BqzwTkadrD=~gbkq%Hu`zO>c*+qqCBhBECG{fmAAI2z0X zy%KF-3BFgJ*Fw5~r1u>XkGWw(5zIN45fFON1`%J%Ex@RF#&(EAN1mp9b4_VqXQw)BqNRqyQ2q(3R=Tw6sAkHMSNJm&kT2qjY z%B^$TJ8`a;@6bZ1o?Y6~?ly$%3*uuWfT1!iT^s^xx#?YBup@Lj*&ky_o=l(mQo#re zHn&FSLg2L2=q=v|f5E^ggL5>BJt$^p>0#Jp(&W-%y`lAo1m;hEc`z8k4<=EW1Jf`I zd?rlykYq`h4|li4EK1+xcks3kv)l zxKkVBK#mq>fGJ$>&WLOFp~sohak?%~C>I-4ZXiL4nwYrpIk4pQRE6G#f{jdnFJNe7 z$W@QaG@h|A1qxgZE$kHUJ-3>$xU1(XW#+I)2xEoQFHkgHd`iPtREdRaY)@{C1YEIE z>v-X0?;8gC8I4_%rY%nWzd z!?u+{jL8Xc4Ox&)Tz!UY^E5qCgYcxI94%v^Q;m$)Z(s*O=MM8~238XigVD2K@z^4) zy5e8GE$+1zJfC$I<5_1kPl;+y(N75RUl&mXW z@;rHU7bER=Fl9qWoVTSVGiQnjS}bNo88LS4C(de9<6W=^9^ZcM;C|;u>u*?BePNeQ znn#BqlATnxx#)o?ei))8cS8z23m^+>=|RrwmU)5 zAzg3_QgJ~fOkNFKf*T)XA`KxIA57_L5ft+$H@pf|q-C@>P}&Z_9`3|}VYnHGjActi zYUafSXkr*?iF6!!&VaMM#!N6__zL!jVhB*W7S3LXLXH+)qtv4~as6?-Q?#)D7h~@L zUD>n#eRiCVZQHhO+v%iZ+qP}nwr$(CosN@9-+TY_yYH-b=ABii)~ToVQ?;vhopsJx zh0ix|F!3>j4?~RsNkoZi;}JE{=nxC1kX*V11~hJb#7Ko#75$K6nb)S}4EA!Qkx347}K_Fu- zKfH|FZ&WU}&bpG)VD@&A?_q0GJczGg+Zo&Q&iymgY@ouUtbg5Few>3L3B75>)^3Y8 zzywC>q)?{v+%!j{ro4AFc!uPrUDv-=wCt5-f1$O0@v|DKUU>Tq!j9bs3mau#iV93Z zD6Je0qpv1v(OxUOh4icqR#`WM0Mi?v3>Dct?->{pZX|YFIV9$SvfvRu`PET}QgLug+BeJI^P3 z7v}5C7qs>XvMkec`mnQz>x#mLm?_e^FCz^vme1mw6jh&q7Gsd@!(^15cy*%8{EC7b}Y zx3)jcYt4<`3t3B_!f&dVq-)j0I&nmu2ZS$@3@R@8apDk(M-s6L5eWf=@g9PV#w*9} zXU^drLY_BCsifDztU}x=K~PPrxcD=+M~>iwqg7M>rt5q_X`P5;TRxAuZhL|q z?A%N*oi-8!nCxe*wJlG|+Yp1A1rxBf!*ZQ&5`B&#!HaA#9hPNX*5h~j))x{P$!V-r zX5jAENY|HR3eU?L1;xJjl zyL!ArNx#5n^a+8xus?o7J4tlSr%;iK*U*c9PJwT8?r=)%A|1$m^oldw4zV73r>x#2 z-&940R00$)vr5PZTB=hYw)VwqeQvQ5R7<~8TdmRUjoJs%ATz2B~ z1aBFpl9C3KMJ_i>7}y>qU>|=XsXd))d;h7gsthF=AS(v7Hf_Cw;7$h@%DCJBmqf_ z-MtZHYbpQbSpRA+O*Td9s%+)kMclZG_8zXgbPzjfepb)B{Sus5!D&6$&mguR%cTs<5mM(_9_HMJXVLLNcWOH?Iq=v?=U6@mv=dyLw*TYRGxxCU@Rdvjw15bL9{3WRGS~q zX7gg?9n&JfWBu?->4|wsF02m8qUZ?%#ao-qjR7iU%2w*HF85#mG43m zN_)DcLx1h9$Oc6 zq_xDe?eZ>dtbZ$9haoBq_Kn#0tnAQ}B14PT70iiGvK?{^wyNzDpO?Y)y5&C3o>Qs9 zLA=ZU)eqxgOlNDm?!&EK)xNI@&k@fF&oR#++H#Lx?Y*wOt|8QZawlpK55qx3yCPbq zf$HF(XBRI(+ySur_#5O~@@KO#rmcb7>V_K@%6WK3&0U~S)rPfZi1b6VedyAA^X(RkDO7@1O>R7$VKxrh0zjV^Hu`;CQ8cy~y`wXVj71A9`9i#_~71) z*xJ@I!oXcVynuzIq}@{$V%o#X4X*(a{Rv8@o49e_^8IDnMm3x`=p+w`Wi`J`&kXK- zHGk+b1D~D6NUy3xTP;hWMLRrRxFi5qv<6P5k?qbXrj?->WG*5jm(1?`K4K|vbtM}U z4K@xY4(I7fW2d$^2GDfoc)uJ{kj|rfwMSZfRB-4(Uc28uQQNxj?|0Bb<8CIC%T&`EEoIm_cH{9}JuBRv1k{oId^uVdmPhLfXuvBH zjCk2CMH>g~W>x86L^h0*FHy+=)LehY<%pi%L?7;C!VvF!p4&EuiOd-^eJA6KlGYIV zvim)2p~s_&K{S9>y!PxK86V54<>NpW(DwTu94Ykkx*g<(^G*YJAQ9{?JKK6oYt;12 zfK_iR}* z(LU_b`E&8;e28=V5r_f+=X4^C=nDVUF)!)kjV#KwXlvjzjCBd2e1=fi?o*W937h{r zkFR&m4Jre){b4&5^;`%Nc*v9Y{8Zw%bEiagOGo4-w0Xg$C? z_F#AuXUrDtgS0;B+!0+@HMjhfeGf@e<^|64Mt&&qC>74eo6VK*EA*avn%}FKp-bq~ zJf^GeUD&yW&*Yet5c;SIEL_1Tm6M;d?j&RsZOm|GP9dPJ0KBvRc?Ph1+#gz|xUY;Z zaIL$HCO6%SJ4%!;KJD(w$(WG*twfl^IsOdmysG=vQs{#EU!-Nm45y$x&Oh9joB(^r zxznbxr}aeMr7YhnKB74W7Yn8qf8S`K8x>)M06S)R? z%?cT=a}L@)`!$VIwKB1dUer}D$@V8X<_5C&=xX!D@G!9EiG$o>h!HOaUA0upRemUM zaj`L+A$iHjaGF9}A*Pe9EQf)XlAFGIt&NJCkgy`JPJgu_Wp1_b{=R>FykfUJiMW!6 zTv9y^D;+gEF@>&~h{tu;FKuri?|ZgteQ$0iZ!oawc@Ul5UXrn{-mHEf(w@<-UZOJf zwmjKL)Yv$%FuhJ1k}ys+aUz0}in_dxxKb+tBfY(bs*Pf^fsTG1Nn1Guy)BQxVkssOj}SQ~p$Q;(81oT0#xynG;%2Aa>M3WOpgM(AgFEkrCtHsUIX*?+d4%F{y{1y`!2CS@dKrZjeN zP#E1#FeplEm6iaTHA*bf=pRd>5}#;mbt$bJ zOH)gUN6cpK=4xnSp`|i6bX2pmGSX7=k{B3kXc_2uA3J!c*%)Xwm4}pO4PH8!8XMPQ zVs-a=sGAFDORJb@ofWPZRGg>WC$vjiPckxGL#PNXJbg)Ym89G=D>_W1hSpYU$*FTv z9^FV-3}v@{sZT06q|HcetJ?G*WRh+S_<{(0rZqOY?g#$va!iD=Y*# ztT#Iv9w=HQUQjt!6O`<~Ly)V^&7B1q9Y@vd-^;Ja%~f8lFG5yBG+w{!lT>8rGZVbu zpR1QdJQ_YoN1w5J^~bM9 zcoDKsfx*a#xN>SVt*OO8K8&1_q%#l6HK}?cY+N(RIE|B%m63yKG66Z$Tstc>Nii$I zQX%g z)6>Yo(NyBp!(8VotbkY?dG_8MVm>J-3AtJaqnTpTKw^|4Q_-SKJr-R>Q6+|(y4=Hc zccP*26eN)m6~!odS;M{`Wk|CgqEb@&mflrTLSffTtnQ}ML=4G zr6dY+a&!_xI}4M?TbN&9EABnxByd%Iw05u_qCTu1(a1P3X)6O!H7!FiC8^#_*+|Vp z!>G4!ar_8XvwjY;4~4`qE$>)mKv-5%mKM5qlFIVgB8m$OF<1jJ28=)la$n5#gDqx z!OEzKT8|z>QrP8Wa?rNEEIgl}PjOsocQy5=aQ%Gp7M5aDS&@m?d*1t49Y{Fiy$Th7 zHs41vYCv(a;ql_c1ZA|kd`bxKm~;xJib>s~A@KzBAqq_`iAeH+2Bjq>L%pQxfU(kK zl4RWaFbiB-9S=@GT2;oo*pRS~>vVOWrB`Y}Z2rSnQiGulqZhNd=?%h*+I%7Y#>{=HxcKX3OaXEc%#g#(G zUw6=A`w(&MQ9K#2tx${<2bU$0%UmXrb4_mf)dM$lzIG(-E zuWBFTI(hG0Zg(i#O_%AK8+CN@x?N)qQwx)F^1c?XA4A*1vreVBowlJm>wIm~^43w5 zSpKqK=RRb&uJHP^!(Fs}YDwPd++nBNH-ygJ{a(Fo;Yoj%^~LfzeZ_uk?7`7bmho11 z^>uzVk)L07#pboWp^iW@ZcrB!n3^IkfIt$H@>5bQKxi!QXP`is8Xp0L7|5*9;3M3@ zzz>DoKmxx*BEH2Hdm=ea3lr=F@(__w7B!_az+PrNvX&t9?(XY|67Jy7#eH^5og>EX zr}n4KkIkp8PG_%bi_PFo>hkn9tCBRW%w5{`C6}Vr2bJ|5y+cb`PbROyfvRDtQS0l^ z;ly}}<_Ic|^L1qJos|>qdN+Y&*}6?5?v}leeD})r;zTJ%2HX@3m4B%sru_F zY5%lpF56QeMmyZsj{W*FY3RwQz1n<>!**2MmAB%tR?VnPuNmGZr&rABW$panWMvC& z?oKPw>yC@_^`?&ZgW*!-Nidkol==?mw9ftMa=@s!qy-t%`c2%P-xIs1d~4!idRv;!3Jt>Dfdn7U+3)N*u%c1F{UDiCxw5 zUa5w9d`}s$WS~ueOJ#1r+++yqR9mRc;Q6xoQ|5bg+fRbhTo!QebfGX2YM#3J91%zx zU4yRK46lLNCuIUfB2tCGw}jS=rFsw&m?UGMr2#JNNpxaagl{9&qtzp{Bh%s?eK4QX zadcCVFN$}FcTBEf?IiMw^WQ7FaP$RiRPhrb2?)JHgB0VBJ67+cd^pq>TWL+^IHPPQt z%rpph8~a9rR4Sol=Spt-gxIa>%K*KDIcDipNto+GYb^`j;ad6EYTe`_e=IBBYuaH8 zs!1+y$8;NIn4h$1c!GSv&cNbq;a3w}8)sG(WFsHgaaEZ#aydY_S{5Dg)RE6QrP-8y zQ*Y+)p6UXUXNMV<(oL9_2wBPq$tDXO)XV0F%0dIPB%|lk3fn ztWvymr*}XK&hDL8-QeuQM-J_0KDT9RNo@^jZHK+0CWAV#{I)d^bcq%X6X{PGm9F?m zKea<_!z%ThHIrgFl4012v2}>-Y8oKEn&bvp(0w?Lcw#q1szud+W}|ql-LCpa zOQVZO&sRr)UPs>*dnKrSmdCdAm2(;z3O;lKm4lCS2ylAhGBtB^P*vTS)po)rSQ=TkY18O5~Mj?QD(=8!p6>a z2tvFO0ch6Lcp(|0naKEb$bnQ0KX9;VL3c1_;k^_SKgI9E6M zQ|`GP$yeIi`*_rvWNG5Vve=D~<>>I_@C1zTy)i=+nA_M5XcJ&q`~n%Xu*f2snSJz>61`|s#4c{^Pf2d!n5uq| zQ48(V$RDT$%=dIvtBrcw&9%=*RxsFX4h)ZZviG`ykm}4kMs77-FUL8P{8Mhi+g0pf z|KjHKqsaI1xT_s>!lOcGC}Sm&AsLVc&>JPFPU8PqA<*Aqi2Xj3gFO`aZ zt6tcA+(u5Vz~}>GOB*Jn){RiX3zvF9DIG5*ehGcwR=Qd318|2YkPO4A&*OXelb>vV zGNs56K|XgCEQnSsXb8yzOJ#=;sHb}Z=JfixU4dd{HUE(Hs}fixqw&~|_nYK9&V=0V zQ=x9Jt}t!qO@5SVtG+V~nVYX_-f6sCsDnJ3YvoIOMokbp{$4ZQsv|NxAA%Oq;@`oE zcN97udsRywSK=L~a?D%VDwzEEvUJ`j$$j#+isuOJn~1~*oMLgclu=_5jEWpl5j(X} zJ~AYuW)aN7jjfDHjx100SRKH)Uf@KTQg7JlR5AR(Za_xFv0NGBLJgsNxn^=gK+##W*lX&@2 zBD+h1DS5d2m~A*2Rn2Bj6rd{G(Dkj!8^xw{%!}&rzR@r5UXfn=cIndf3cC78GW3_T z`oHRf{ENW(mp{rt&q&AmKOENoM%w;wF|0~-#Aezz5f{Wf8nD40*(HQ zAEHM*YVwUS z{g?I4ZDswg@vr?|hVI`!e{27@&%bTD@0$K^@Bftir;Y!l{$1{$*8Mw0_svZGTl>G> zA=tkA@c(T6-+ukQ_usz#>)Lnv{}}$4C-t|~f3uhWH6;Ik@w5M%0sa?(_U}mj1;73W zLCelek4MeK_6@sbVq*R#-ZFe^!u-E6Xj#8$um3P;8NaQ67__Y4G~oX*XxZ8RfzUF4 ze`NoaEr!R&{9ia)CZ=zm?LRo$zt8EvakT%|UHLB@?f)p_{8gR#9~|x9;Z*n^^Sc8q z3~b+b{y*VpJ2{;_l!ccV?a$9Uj}|*R;7>dH{cV#j-&%F~_sRzMLrO$Pc#SFBfHB6_nc)xBC z(eOmXtZ{ly#a+Ewss!{U8!<_zrCEq(+E8TykjAlHfebgG+oNu#4ou$gJj`XdDz>dx zf&pZ+IL~EnUW?)a;IvrIZ4@0m8p8I_TYh$|qdM*rU@cGSt}J+RSAo6ih@wrQAaVd}-*FvD5#FnrDjw(|rp-g8p9I8U6A#&bj%;)#Gb0|LM@Or~burjrAp> zi)GDu;XQ&mY%}dY+OJQ$@mk?+^=kCB;8Ex~a>T}Nv!V-e`I{)RyM^e4_D<*KSY)37 zlxv-HAUpQU-5X;AJQ-vsS8w#-$%XaxjW2#$6Z;a#2H|>mT^@AHi;Zi<8?bCgQXg>J4|CD)_Y+<;Ar~<(X{uL5Lpa>3;KtN6mz9LVZ zDa=itvP@VWY43Sw7lPLt0hbTCCkaSYNatYh*_3TGYe1HqG@FB@jsQN^B+}Uvv@blC zISLkwc@9G<>o5@mcUTr%Jj+euuD)T20$N1iT#hdk9OWlQz}l^+Ely<%7eBEcUXyKf-vKzGtcaK$o@hmq4Ns<<_uLW+h?! zn>KZ3^m{Udgw7CyEhq;@_OZCRRj@y%=JUDQ&MB|37{=_|KZg=}b8w3J4#MmlFgAmm z@>vG*JLRHtf0|Ibp-=m@a^qkNU+d$J0c?)vv0?b>3~Fmz=b4@?+k6l_0ImhV;8Slf zqORsR0>L;_gJ}7^8Z?xh|4ayynBhJ_q6jRu;=|T{Ym4GL7h}S>6b0M)RJ94g(x=vz zb=Kx1zyO%m0-?5cf<849G)f4hn6+VRhv1IxpLnT49|;}vX~Q-lT?_Q`?;3R8&DUmZ zOKaacdBqZ14COLG@<`s#f3`1*>?}4HU1rs0uptOy*r`OE6?vd^@xt_w^*5^=s=p=Z zfVU<-zyr0q7>9KVH{lNY}^cKyCh*clRxTH9HwJzZI&rNP1 zl`cW=GT&(jcy&OyXM=_9>A$smr`rnHCO|h}DkXJ};T%<+pflpC4{#0d%;cV^JZ`$f zczLUe*FJ9B;)gj9Zq5lb0eQFrc>rw-p!p4&b=a$?6-0Rp{M@v2dBC<67#+X+%;e>N zF`T_ed*l2Ju^W=KB1WPv#1aQ|0CI=H7{5Be)#owhG5u#BygB?W4i*x3EdJ2(&RpA2 zJKOmKoI*v2A1zga32HNpgx~r&U*{xwCcJoO9W>twG*g(Ca+|gW%rOVo7ZNK%;-VEY(Z!wZiNPDog4fS=0%DOKty4&@HUR8JuV>RV1I%GCc_a-w|# z`3PdX7G-H@sSaq?&55QRx~qM)^Fr^BV^zZWF!cVA4fO_x6*ps`d%SzHZm;zY?EUtw zH%KF!Pzq^9@T@Dk!5>zIcDT)5U)wm+A0wv z5Jky5K8!5U?jNR`K}q?J6D|$q=blEqZm>j#FkE#YmwJ@3$?Jgm_NZe(sdC4N?AEbU8>yB0cJN?1T8*;YAHc zmIS|gD(43Axd$uYmM!4QopF?a`P&HQtg+`)%tVobmaUto88@iNR*X&c4HN$g=HLvc zfca^9;=exYBR#O#t3R_Ty-v-#rsoTn~;esjiav35vOcm4TrSdp$Ch zwhH5r=iaC&sCXSIX>uo|kww32MwiK*kWM$(R4%xTH?IIIru;nT(G>*Di44aK2K45zz`)AbX!_;j{) zZ^GCHi|Y;pi0+Wj1aD>)Cnc|g2zVfACa)B@QHC6Vr?(hDkkuHF8))t42o$2#aUT$A zV{=5C#85;Tku9RJGPX+VMi_jVh0i%@6UJMQSnuPIT+X9=%@U#@_V$*Gk-`%?kHtIA ztO&=5t-yT&8BtULV+M*d{QH9blJu zb^m=a=8jLeAxwDEi&c;t#TG-rU&2SgSq1#Y8zK`ATB+X zC&ZnSj4|mRVORBEQmG?1ukeqT)XLQ}^%c zum$*$kD&nz^5d2J-Zh|xJSc|(W`Atkw>)EP+8A5sG^y>{jCzOk7xD)8dwQV+k5|dN z0R@ly9x;sVc71tcT{!~7n(Z&#eVo|i0|4Qe!ByC!339oyO&r0bvO4pG8@}n z`{IRJ-t5`+{mSb1ubPDxf&n!HBgewI!`-`?$?o6P;|=d;)y{tag@FZ2v(Cf9x&0d6 zjb*iQS?E5#nOr^rB@hK_WTnKyx&JP(@?GFHdvG_%JYlP6*Ot#7=&kMuO$J^K9GC6{hv4l=TK)%kQH1hAyzaEzq^rd>zw2s=N6ldVKnmu#hhNww>xuQvKO=Miyb>^xI{N8?05;t5E}%Gr1X5zaI>7lg zlG(ZWJXd zQ(?rq6(1a@kX`|CKPIx60t9W9bzVQ@ZXY6q!h_4G=<57_{VQz?1`$H3Tv$$z6(b~< zA}3=R=t6zXFEO3hfI7rGV6Bc_ZmfacZk~us-i@t>_c_3qkMQ&ZStJaRec6#;bs*2U zF$-kLy;d--Y9oEhI6t#W@~u06y+a(rT#iiF16%gaK7*-CH_dcF20bI~qB!7OMT((h z^p>#a;K~+0$wJGRO2lQH7-4z}TnlKHTu!o13o-;pbuK&tobNUf08PY##Qla2HW$*2 z^}R>>$zlJKaauj^cF`?z(m2D~nTSJ9SQLcocMn1-s>H0Y%?h@BU~7o>bwqDS+HW@D zfV9})G(q!lJxJfa!aoBsp@Du!*>uzi(-LB`oEIede15(r0}JKN>?SlUj|90&`gI%^ zfe{TBdn?FyxQ4ES6JbVL3vF*x#ZFcemF{WluZQ?A$}jm}abI_<;#y9n(92q%ccNT( z2sH8AvAmx)kCYA8Xmv0l9sS(EamXA*du%ib4OEmS>Uxa93ylHe~;Z3RSqqMK&(E)I80|;z7bGDtKvub{D zbU18IctKxeM<4ZZGZ>d*Hc{*I{`q|MdoNq+C-Qsm~7C&h{!ux)F>H=4mrVC~1FMo@5P#oVF8N@B@bjTZfuTWM(_>Fn!egsq!*Iak4vu)ay{upfz|zLvgAng+ThIn6QDH!lx4y!1Lg`|F87QLsgPHynPJZaY z46h0T_#v<&j3h_E46vhsv7aD+>gflH`S9D~?ETAdezRj+aV$mta;?HVCR?n4l8WmC zTrwi=U1%`r>(FX@xwRbDz)(HDN|B@?ar#3&g2Qu9#iAR_xpwfyve&vk=21La@tU8iBLOg*6lk0A(uvJD5aq~VGNKFVm zL1|<+g!ESpVOBUWR2N#*%AEelZ(oc|#1zB#p;NZFYN43? zr0bUWHN`oB-uj|s$f*%wUMdeit?T{Vs<<6j(9XKe#`PS#fBrVY9@Kc5rX9z9)Qt+R z=&&BV61L>L-p6@6E}M1TKj0nBY&IC~YP-pMN0|y{sy+hFa(mhTYCCVTUvH|GUaRd5 z>uC1D#vn$v$3P{YeV9!;13eXqr@t_;laiyI$6m}_q!$WweB~MGDQge{lT5jP&<{P! z*-|oBS^+kDkfhkbyTiN1V?jeQCTzOhp^;-YX+nB}L8)zB)Ln|6{Bx91-qvCzc`RIY zI16w$J5Smy{Q_>?pZ;~Xz~}%2bK#cF>}!?3@60!5Yn!Syp)SU4U}SUU0&>3SU7(_;m9S%V@HS5|FRo`xlukzf&y(~pPp z$bbq;<#Z#-S3)RUqFFl&KOkc3bbXdMEiwix?fzly-5Mf!UD9!C^|FCG74Ij=>0N8~ zwkGYeQKYc#?y^%UNbh$A=F14V7Iv@E(HlzCSV{vTnh~vmm>pA;M2NZk8F&9~T{z*cFEoV2T~i)m&#i z0BTd9*4Vb5y`;op$KE;^I>G0+P!kn~O*NW}Zwt1{T9d;IXg|54LrWC+b437ymwyLA zt1X_@piil@(?DS$nloYLE7WrZGXpb*JOk55VGY(sLVD-ITlQU1A_^AFhk zylH->u9A_X;t8gM;0<&NO*SLvLgRtkN>RVb`8a>T4|Jnw9DE2cox% z!$F7Jyaufu&%$=s0JdUqB!@txWV*OFo*o*ZZxyxjb(JSTWd=`=6PDJ<#Yz9qNl;CJjo^xJz*=Y4L;;~!Qv zuA9oVDNgXpL==2~dYpu6Hj$cyU3?MMeBncSZq4%5d}^^F64e!bKqxCd$>J%2+}6>8 zs^+X?WBIHTY0@eHeXBZW7rbY47@BweyGJ>73G!{OvZNo^58V+g-z;Zcp`W7421zpP z4JnOXuR&fWtz|}ok>7rFajpY+=EPpokxSpyRs`MlDzr*GlrrZfnKT05GK!~;RT>Y_ z*_}SvRhXo;M>+!!%%>guOzzXQCrFOC{Z zd^7aK?7-lWfa<*h6AF|dCM^_Llm_9&Y-b)zUrb}efwcZCNlzS0FV(&6)gLkDVl(q)Pmm#gkF~Yc@0MeKTV~| zlS@tN-2mGK!lFhGiklBzexBAYXb1%Kvgrm8(zRQvL)W{VpJys(;)<|UCznqHu?X2U zq@!ogMBtOU9I;D&M|gIX`j|ETMkbX?sT$)f_duDH-a%7oKVZPPE!Uoy%?GqU|8G$= zfI%#OfgisYP*D{ag^)u^V^Y`M)82@d#60M)!#2dPp7e8?2aZllP9ok{9MDw z$bk=P;v|p9f0~j{2ey`|kuE?w+nA?TN?|4Wb)zt~r*2a1wxpy~t(Cu$?*6h1&j@o( z{}r{b*Bu@fgVrA~iFd%o3}X}aTQ4-Rss^G%;sCtd2z^XkCu8!ThoJ|WCJ=*Ylsr%2&(8lyCm*BohFc;=7EuAfLp4*W`_Kg9?L zc+pH0>PY!YoJ#^#9OBRK-^(A%?y;(fmzkKO$Jz6Ie5Z_@Xs;8w9;1HXf*w?)3|0W~ zbVNU0R=OD>7M^8=0Hpcgq38?5PDa-JIHzL6GYRn^@1Iywf)j$#Z@ALr&66rRZGXCm ztoY`)pezHm;|+!EU&aZBGMdEj{}PNzlP{;I?OV^iM2~VbFa6k{DODaRoOP01fd&+@ z)K(x@P7q84Id3s~QU3)fg+k}7v_<#s^q%VBcs3uf>pB1c@6{&x4{&nRW{4^Jgy zxsPYUg~b@n6e8rwg()W5SsLbg$0fIOsB;BM$`GFT*^(hQpv5$^*c+qo4b~d>>dl)u zfPtp8^{~{PPUvob2+^<&H*Bc8ws(M6 zcN@bxpY12ZI1#hd4Zl4b8tnolEQM-c*YNsyjR!V*s;9+Rg#;1A>U+x9urRRKDS3;g znKhj(aP}4O^9pwJCd!|`6%-Ygp)c)s45y{1pPv3UT;WMAfP^E-(16uaBQ9ol1agD%Fi+3C_5=hvQIc7g1|&2qp&ie8a@yu z2#pbQN(t_Ojt6m_yudo_G4zps(s)lL8$6mApdp#|AM%c{#p=F zPZ;^x^#nq%56eB!Idowb)2M?fVQ3_|$_VWgOF>Ji3_W}$*>L{a0MWVZ@@|`*8=M6D z{^Qqt2~3gtu^surPM%h1tUO`gBYoLL#HN*UV51c&jHWis@qVu~Yl$Elp<&G!KfXTk zcH)Bns0SLNt#6o`($na zFL2Bhg%ipHs22U4V9_T@W!Rlz`q-Pvlok4}_&137(+emo>hTtRA`2rl6#3~Cp!A`e z9eDc+GC)?^dSrt}uFdU&gW zKc_3h{O zMo%5^ZI8}I_{tEC5Hdv~bEfP#>^MrMf7uc3U#i(!Yf|)8(b2E~$IgS%1aSWfM6#wh zllB|AbOgq4^37Y<&6zLY98D-%>F836PE^Xc4C2z}9bxU=pp)+hug;;zDri0hIFh%u zhFqe>ax(8f+KKRMjlUP&&Hu1iYfs)%MNzsw{Jbq!oD9d-tDH`VMK+zNDR=8`vY0PL z)YQ<$O=h-v@@IjqUUs!B-e=cOVsw8m!AH;cYVWMFGS?3$P1I8{e;JEWVm(i7O!u@ji;|Kk5L`A$%5~oPw8KT0+!3pRYg|k%=L;?V7_!gTQ}=L=V^t@{VMc zN{-nU53^&)UUEp5x539$^Rb(&J??y|)8>S0g`K$kR7y$#GsQ`u`+0@vaX$E@<8?U5 z>Lu#-bO%kcHU7aOT{^s)+}-<|f9b4ks@^Jw8MfjvpjJhrPS|6hb9mauO@F6?rE~RH zy@bXnMN#|hugUre_IJ%At+BT~urlY5>tGrVnjofQspAQQjuDV~sP&7j1_d3s3;t?R zIrq!7nwr7-Vf%^utYGMMXg%0t1#=L@1NTn(DQxL+_&gd_qE{yy=ihPsp^#xX-kiBY zaT0u~>n_rcH%S+#_QgyP1Be1oS4}3du~Sm zoX<9=Ovgg5a`8%X^?Va`Gt-qzm@qVgn_1giBojh0<8Z!{rg62LKKUuU!Ax3j4N>Z|;;WSUv<(vS_oDRXx(P%4M!Q;Srzr^`g-{PK z|7e!HVf1L-&p_e!@#Aq?-p9(%6q>cCtK~v)#SX`p`8#B)j2`9g&%=A>-Nux@>SbSA3=QW8GHocOEP#hwy(SbD zbyZ12Ke7{7e?f;6?4S~~z*2={jQrH9*`PkNX4V4*#3gtbH*6hjT0WU&L?fy*G>3r% z7*iIHl}wqZZOI%-yFR-AtFZHqr}F*(ct(`UAu_{}tgLgK;T%G;lN~ZMkL?&oX2_PE z>{&ul_AEQ2%&a6Ckz^m665snYK7Gpf_x)WD|6K3;TJLL|$NTblzU~`UXvH7pD(^F| zH|4*o(VkNfZXDAU-mWI8%4224egB;sLyhb-hGHM=8;|16?^bAqC$>?yqGcZLiT<3cnSJwwgGhgF z!F$%U>8oz+IuuDF`@tE!`5e|ISvOeVt(l8dn`QRHu0dNzK9#ac`{MISq_=vjAr}{t zM6f~kBp#g?o8cKJ*-&Muaap7ZqyDH9*O@oJ7%zJQ!(~KnYVxqtIGy_?Wx&;=hWfsj zF1)|sfRr%xy*tLYj9e~jZ%u63ek-);TWa$)w04-+styyWY0Z`>B893b;D;}CK<0c}63OS-ei&^UJu^_8ij-)>6`=23t=Kj6O znA~wL7LMXnjDogwDb1Ot2%49c1?$0S?#}COT@$j71XUnSFIvcz% zvxHMJXdAT2eRo1*Xg_DZ0Ucd~82fvtIGmWUpPCcBDr}HNq5#OnU&knxtQk*H_(o{6 z`4l2k(2#m}Q2jxIe;P@z`AY4y-`;jhr+aIl_)=Wu`_bz4_$tK)B5Opdpmd<72$QXe z8@er^aGr0CYGWYK;qEzgt_KU9cPd43QEn_~eUHOj=yxGao6^?;2_5HV++FStq+<;Bo7^?o~tJ zd$sNH5UF$Od+7{?@5EefCq6H27cDe=elhKvDekv8d+r-+GO|n*xfn%%!O{o+%59d^ z`y_}hQRL>Lz>xLis~pTpgPP5nQ`49Yfk!M{L*~`|)TqO8jlWm_8LFBXQlM3OkKCo9V%>$)3v7@KkL*iVcxrq$Puj@t5z zXFp_*tAr*pWy^SkK%Jx%-@cZ;{%rR{{t6o}v2T^*N*Ot&jNPti=8z=#nd$ogkn{9M zHzZfS5!+@fI~wE z3aE=TU9z&%{RbYGNUQc&FjX<URm>XSbuCC*D}jCPu~rX^^$r<5lLZZ77w;cE0a(m zs`XQ;;f+GE&KFj7ufE2?1G48;pEX>?OgEt?EG&Av@UIT0IPPXMrY7|U)&dJu>i+GWWV%6{(qZZoByR6J%lpC4W zIH<4ZN?NsA_|dc1GSjtaXODLIa#eQ@aZ7ER34JidE9p;@)JhK_iaO168w<^I1t4zz z0kRJp6|?&Vmr`gVlJNo884d7lN9oSwmaNIY4T1G`xTti7vwJnfCp*n3BdZGd7@s?4 z##}2_8Wfz(KG4P)@Oe=Pf6Z)UBpGWudQkE}ztYjcsGcH(zeUJ*!ZYHl%sy?v#FfpM zwK*IAgR|cXREg3^5hQOimJ6RhD-*0K>N(}4=_jW$ycDgp9MwrqUd6B}$BDm@bz#O= zHQ+TBE^e*2AQq3!PyHaNV)pv_wP>bEw#(bRLT$w^AU*`^c#y;VjT<6cxn0k4(cQ}7 z7?osFfmhm|ub7X(4R+|VXqd{6u=?@)Is366nI`&lgrDR(sF-9D+~{(oh}fGHFK~$) zB6VVt=p``^IRi0-)tItT*l+WQ*bz$Ni{$tVjq*n(h;hUL|ErO~p>MY(vTR*Xo~@&f z-faAEP$goZTDP~b(mQvX&kI!KRbQHo7fp-8Z*J3XHL@q-q`lNZwbkU~&&espw6WC< zSWvAmsJ4{cXo#d}`S$QeqpjDZtGMI*af68)Z?TRf5)a8Go{&q_l1t>1`?!F-aUk!j zptLJnn;Tb`Zu70LJzGr~&%T8Ld8>fD9YA}PtUI-=JA14<{;WIAtUF8Mcv*3Lt2q7> z>rSTUq&)AwT0^0 zYJ8d=_NG|7A58AQp>P6b4KTOYuv!k*W>|9zurLAK1}y(V!2#m;9~2y5p#MdJBOrhB z%>O3We^I^YU+vl9ES!OM?M!eMG8W(a0(jt`JiI%RVN8?53ow<;igzn(oHXecBfHk) zbGxsR`Ej7e;>sACOSazl3Hs2uE8>f{lRY5(l5Q*MZpU}x{pX-fpKCb{ny-+VG`{k9 zQ*NBD`1P?3=1uJC$?eg*j>~%tm#&aCHo!{HznjEkUih^?xD_kw?BoC9+k2gy8)kb= zjJJrJ?h%KZ)h|o8tBP~r?_`Lk-b$?0%-ug-C2;PeT(T8w{MF)W8T**>%os)Xd$k6% z(%1uCF-U}0sr@~E4jDe1{W;ol?^Uf=Ph@J8$D{@HC{WQwTCG%_0j@qo4sgfQ|7D2@ z)AF7C7l!@f{)GvPad?4$FV~OdQ!%jz)>`$ib^XqQ!+(_ciGo7`h+aS#jRq685f~*b z@_&=y5P;tPO@aee{zZZ#e<9!6!0?2wD_B@tTHz?*K;uGEH!Z)*0>B6n;eX@b5Q1QU z0Hp))wuLYlAj=7R>No!V-SErPpBn`R{a)xN4GsmvP)LG1*8h9k)Fpc1t__`OYj9b4 zujmI+JmS&%GJ^fwd1@;DwYyo0Oo74pm>!-Wyuz^r1@J{B-X{1Nf1Y~@8YvoC33~JW z)Vy*w?7D;gM+5H+Nfh7HlhMEO^kPa*%!b%RSBGA4!hx#?_qN;i{+7q0S5M7$2ESf) zH7$$UDS8r&R@bAzs75j)&mO%}9)|VNXp%H)i+Gm{rat{lUy@*058W=%;tZmw7T30z z6m47Ub3g5Jmq>uelA%$F74WQB;`D5H=9y^njO>-7q!RvdNtFSR1Ty;p+^Bx!OZ*9? zX(t-Yrc(TR0bT3V3mOkY7qj=`MAAb|+B;euQWVay6z9ET+{2(>1H{{L4QuZGEalhWUJnUX}6d zQxudbl(}V0dLwVtP8&6I@tY5Pn;H@|<@jVqv23eJywj$9ML2h2@D>Hvc$RU)90eP( z?y1~c5Z{^i%O2VK={D2%j~1?m32OJ>G-swxusWmPvM_~M)m)`1(cLR@*Qz~dL?;x+ z7Jfi2dHO)Wi1vWfi0a^#zS}Bjgl&qXD>wu+qdVH_F|raq+tLue66Qf9r!=scM^bJWc5YRdkrVQ(%P;-&fbwQ1|P5 zkGvyK%V+dp{964{ zT-HE1F-6N@kJv5FYZdjr@2P>!XbqRRQJ%&v#hI-~A@uRKv_i%5Aa!e@Ne}+}mWaf1 zK+=wFk~8qE%*!<6UmD9_hpp(pwtXb#*#gpR2)Vn(?LNPWX&Q zLYPu3=d*>@G++IOJ3^`6l{e0;UmLg}NSCEi)^I8IO1<;qqJB50y~Fw{!*UjeL(tl# z>`r)5zDf;Bp8t$x*g&iGlupazDGv9f8V`4wj0!^;^N?1daLtyGmRD2fy9Z@PTBqDg z6!z|-RL=6zRqn?p`=~F`E4&(j?fWf$ZS6BHT*lm6{Mr&bb~Ei+tl@5(e?CI_c>`w$Hmd-X)u2&kyumV)78v zsSS_W0JA&$wa|6@kHu2qbh&w3(ItC_d%Tn@O=s~UB1?9 z(15S$=i05Sj_TZ!R-06AElBG#eB{_GHgJ0FwH;md*_A1NoenBXt~X}6Wpw0@9gDD) zr0p)5SyIYm+fUWJ8;eC9NT9XG=QL%z&lc|a{(HwP-BdIUNjiTb3YevS9$Re-V^z(U*lFanA;ec9x+w#kH z5(cDlDy2(&Keie}whKzSzwg(O_O0jRu{VWQhMTAfjrZ8CnImVMniEV}=-V&xe>z{= zd0Pp~*unCS5oN^g(5Z~~k{E`*q|B8`?}CrY$-cHIN2Fwoyw=zjHPXD zo!%yXl6^4#R9yrHo$u^IebsF$Lywq+zi1+hi^-(NA{)*}Pd$WqO=iZA82T7dimZ&7 zF;5CnHdu9O#*z)_jr!GY=qxT8Bim$a-UQI3;D`|J8 zgv>^LV^EE%XokL24nL=%V>y~e+jC5|U}3(0-kr^2q!ruR?Sj+3T4j+>2HqdfvE|Dc)AB*(0h^6xqw2uYwX^ps z?6%@Pdhtgy{2XeQyz!|ry{q>RN(S1=&doeE!?G~HMkDT}FkU$ozw7w4L;3m5LJOD6 zS-aCg`}M#{ROQat!ml5VUZuIi5qGDIOQ0wT?aR7Pj)TFY4~J&o1Cj5c85D~66`KJn zyC1O`560F)(9s;j`_B`C?vYTO$KJ$DRTHdj;p}3KbpV1cK`2}h0XE>d>}qXi4u+!S zpfF(rUa-2Wi8Ias4xVIhM=Jk zVPQB50o8**xPialC4b!=cz&CH#g+PC!(XE&1Y5rXuxr*hI}3v1^Lya0=8QFWH3LF* zAk_bEkao5(!C`^?PXX!oJm8@W5XggJKa_n!%2;zkp5j+t$-)D8k)OE>81_@uCncqJ zRrI&@$GzisMCk5pfdRCVFhE-RPXZ$m2%tR-_=gRFgh7EZ5)#7Qdp08{^W9|#ys_-}uKas+|xAO0d> zD1tKiPa6_~I@B)`3OQ6435c{0)fGN8_Xyy^bZE>-VUfdq2&4bCzBp$S;IiaQK~ThM zT6+RV3lP6*V6iwr2>at8Dmq}WV8X%G01GL~fc3!_O&~D96_hF56ah8En44LciPA0Z(+qP|UV%rl=j6L(d-#&Z)IA@);?$xNex~sZ> zblqL6FERyDaXKb?78tVOwvWNWn;ZYb?03*QO$O?v+7r-E6YG>|Z0bu(pQUWlD zTiUpoI{mF}3|&k`O^xkMOac7-FwQPcriQjK9>CW*o3S<%j=49NRFm#UBdk>`6_r4m z{$f+CU_(d)4chfdypIZ>OG5qt*XPW0MSHCJR2_V_W!el} z^75BXTplFc{JC?NOHR6lvE2Ond8txGs$)+TmOnG?(i98jWz)(mW9^lX9dfaUUbk>( z9+oU4;^bXCa@A9MP?_!)F!A_!)KY2~C|4Lumenn$r4T{*# z@yr<-{+&C=1WLE-(#yD)-u9LwC*Rg#|C@D2ezmo2shMdDfc!r1;?+reXX(l;FTa^= zUDixXlg&-& zaD8uJy_fCDbOVDtWp~k|b!v$XS|x^_!VEo++dk}^nWZYd)Fv@kNCT%;HK|8*_*Sm**h9@#-?R$bs?W#uYNtH`I z01XzEOVe?VK_YgPLd|l}O)tAv_Pz-9$oqAsZc(UDf|yIrjuOx;JLV^d|KV01g86H> z;1?LmH;Gl@a6(lCU<`73ct0ak5S+J`JaQv6(;~{(S5Ov@blBYr1pT%>6Dl^0a<-J5 zwY#AQu_8jG5?X!u;>D3|A@mvB>VWZ==vBbc7UVC{!)3%u=psYZid$YQVmDxZZ&BHN z^d~Ejp1b`z=PKyr!JJG%D&A^xoPwEJ@=;Pk6;z9mo`0fR zaw8Wd=fASEof>i(?{NqjHbw2*@J!CFD(J^i^5Z&N5Z|G!q;KzWOW_5&2hX*2I zr4-ZzvY`k`IuH8meD15u9Ml5)6jY&{DR>EEZsR~qoAvIgKL&-pyz52R@B@N(hh`+%lY*|_m3MIG@ju$ z=tPc4d#RV<;Fs3wJLdr5;ODGeVZeod*BapIYLHOXo!Z@!sH$r;V1K}U z5f7yFD?lxi*9PR8oN}v}Jb>lKZ&8;+Rs0N~>S~9G26{R>*dS^Ji%X|y6c+BCFN)8M zARr>;Zw0k z>ZW(KVZ!|j_-s-14f<(NQ92>^Wz{TARKonsHQbqiL4#7&ARYYIJ6w~XgR$VB?>>XV z(r_A7Rbqq_j-^I}-?UQMStv=oA6Fk#;hImPG&^988ux?{%@biY!5EizLXT(cSG^5ACPj-t` zU>XN&w_&(x5yr|O#_qr;3NDxi;>z&#@zKT*b~YQdOfJI|WW75kHp1UL=ioA)gI7jg zkn{LT_5OA?W4K4_Cd;@pKRgWV_2?zf$*Yk9A1oQd4WP@}M-VD6$VBcUVHb}OjF5KD z6US(wilqnF=rNJSppBd1e_hedhxAi-qBuJMc9rxy=f1Z?yga5pxO zhmm^-x2Nt6xPTqlIh~4WqZE}*;kSbrF7H7f-N5%PAIFY9i7P7^yzL|h*W(xgN7-#+ zZ!!ni(oR&#^mAw@CbnrL=C=;n{JJ$^Z?xaG0ka>IUB`{MOsf%<`GKXYMr*?5Z@nJ; zhM@!MU^__gq$aetg3=&qNIKR>;K%pjTNuso_JLB43N-5y{JD1Np@me!>+8q*li=pj zVO)Jj&i5JIRO*Ll)ekNP?3k)ScrOXJC5t=0?h1xHsyxPNZNwr{&vBRqk=|#5VffXl zNa}E==)`nE-Y*9{KGA_^<0p^!#vJJaElMUz*wY;sQ0gyl-Y26nh3D4W1ZlPB4wg(|SOJ9c&3VV^E`B?5jNC z;8x8zb=ew3a9(M}US>nLfkpcsqPppdaNlq5iiEI3d8fG6Y;;Br{n^f!{e;?(dJ6b2 z4`+fpQB3WlX7|8eCLvB>|73r)X4}7IK)LzZ7tTCDQR@Hv zmK#$uQ84^D@Gze?vlTofs5~@OyH~7vf)%H#a34pZ@+eesG0{wgxRK$ATRTH!L5t0N z=;G`U!Fl-NT>IR%Jhn#96L+23F_t#Mfs)loTXQy4RdEd3xqO(LfYa42k#WodwA@gW z#rS}I=8?ToKRDWaMn%eGrrZSh37=6S%j^|*MLL2qfxQUismlQY{cJPDMgv!)Wh=%a z8Ca>R&~9maJkfRsxKRM8QDf@N31oFd?iV#N`-h0?6>(a%w|P!zGTTnIgn)Wh=3~d#QVfcnY6zs zLJE0N%5ZgAtc=PlcS9@ow@N^uHTpNJKXi~R(9*uF6qCIYzHu&j&W#FWC#i!o9f0P| zbs0GRtMLNMq(*M1miuk*w<=`h0ehN`!Q;XEKRaHi?#vJ$lXTy;4?RI7sZ;x($$ zxIQT6R?ihp1%2~Yby-May3)i*ie06d>*((##7e;sn~!%-i58jYytlM~|Qj$vbkP)3+10<%LpBNmZFj zquhlVb=9$gcfI(pr`&WSs!(A_XL#=~ydT*~Xm9U09&E!Zo$Bb@>YcAG=F=b8XCsl^W zlP0KnavX_%b`jT98k6z3i*&Hcnp&XU(@C4=x6?TxJHohFc-8- z=q#T|8Swxsts)u=@Fp|qz^b9qAh1?nhEYaDf4ok=X*0T+91XQ%J*85hX0T9eLgTBQ zL`$399-Y`w_SR4%Zvk5H*Z~K+(xO%bOsWg;%K>#=pu*7M9%3AW{CEqRGpMAddAdc3 zy8R;HT~|0p(C+JO)C298^w1`5ph=bfV=~a|Y}-G84>nEbB&lZv8B+L$?1D_)5Q9M| zn*wnw9S2>ktwaMj<`W}_XPrtpu@w?DCWfj)PZKm0fylyrrHK>rL@?xG{6y(va<%DW z=m^#toxG&~q!X6GWkb!%<-5E;;-pYcC&^8@h+HQn>t#xi(RGFHPYA4;ugc{2Re_uH zHTiWSTNsMhnq%d_JOLvc=3v;$@v&@c(4nw1M)fo+5<%FT-kIhc-=KaC!w zWM+(m)P;wu1_YuT7)bCndOd-Jhy2Tn6UQ}i*l1?vrljUR44LCSjEsi4gyNraA zUFup8VD;7(YNierTKqde( zDsm;SlBX!mNlSf?A48PWUl1$pD=5_$lIfjxE9(3oFDoqUDW%uwt^JdV` zJ!i03nI>3_McVi~5OIFy@P^%93Z_Vg4@*eH&_pI0-jamRh!oGJfxkh6RO@7#gXCmn zzCd7KfcPY&+tLFqJl91$TuP%-$jG89_C%@nkyq z6OB>PL0dJlX?^ub(<;eEkHuM5fJK>7?6j0TALIasdbAA?b+ToXPs_U8h;rSVQA{Im z!+Z-e=VDP=ir?!@MJMO)jC)=WdXFEIcP)h2NT+R23LCQiW@F@+vJ$o-hyKV;ov^CN z6U`>Ix1YSn4o}J@T1Pr1R|+stD_HE)}V7$n{^EG=pAAH73|fHh3z%=@vGgtk7ZSWdY6qm?MCuLKK{o20bBHOSCsDcYVVBjY#N3@imsU4JmMx1iwt?9w@NXead~tnKa7v;luHD zhZtF;mm^5`9v{vyZAet*s|Bw#NEkkWJ&3fe42IgcM5Qv&CiRj@-*bCh>MbA_;%K6qY8ilU!k0M)P9A&_# z?M_BDnyyM~qG$N8QXJ7{qF3|F)RG7Z2VCM|(o>qOjBjR!sB7q3|2 z0h|+Fw=mL~IDFB8>0-r{VuO_cb- zKjKnQSz#JG1d>vXEoGx^$#Y{8@OBB}YC!$;|Na2F89-3g%DDhuM~qz=VH$((vhjyK zwIB=Y8b&fO*lE;(hsm_Hk^~M$ysQ>HvS!Ad$suR_i|A@BdCjc7w51deU0d0Y zDrWQqlg(~+3G5#>zjUM&mqL~2wcd?epT?}N=U#0|Pxkq+% z_!Q{hJLylFajT^M!fedwooBFHFtuHm33E4L>Dj5NC-F|7HuGGexxfEoQ@U`&k^PO* zNcIQqTaEUEJ%}Sd$(e}LXZ241<68gw`0mE@=8uq2UY);NSw#mGZ#lu@NoxHRNvMX&(!AMwPhVF#w+AbqT2 z6xb_>VO4O)cw$`Bz+dG{0QwXt%&BlO46uGv+oKgz&tGRF2wyKDLaHd|iYD{ixX?FKTW{9SRGS@^5Cqat!g!e&a^MzdxgwHzC`b^bPaYCHqxE zX$p4(x;*=&t$&zNn41<2Hx(w7{8;wnaF<|XElHqf3mqd@ttaLNF24N{cEuBkAOi5cUzKJB z#@DO=5hf135Y_HN*(v2s(=}lrrXpod0ZYrs1Yz#@AXBDL9$2PknfDQ z%&CH}vG5zO5+zQ?B!wDSQ+c>pkT> zbtMqQ`yXLyq-At7^dsH$Wy%2+a2&yAjI3mNW7l-0H&*I;of5Db6=Jv&1haC{45`q;)bAb#|g!eIXVBC&{;&O!uI6bWGe@rk=|n z1=Q&(O!w+ctg9#tduEfdD^GWjuY^*q)IZx+7>Qebkx&R;)db?KV%+@VJDF6I9PLu- z_3T%1V$?4M9iO5UZi}@PBgLHbR&m&6ectt~o69BL9@uIIYH;c-VhoU!p&ffU-+jca zqcyEu+_j3pd08(xtl;}=kngZy^?>8fj`6jM#MPx*8^94QVlcoa227AhN3*0_HE$zV zEWqw%tkZ)|)tALM^p|nyz))-roCK_^1Kq7+n7VUTB%?}+0V_=^`{Dj)>l<5^@ZH>n z^=@>!2q%U$itkzpR)468y+o~n9LCmr055SC@VGm2)>!s@wQTdq`FLOvx)NtEzr&hC z;p?s8FJC~licHmdG_AXdq$XWM5NN3R^*V*K$Zmj-EjSYCEgDdXO1a|=$wIZGX{k^P zY1H#n^lB(ae{_Z!`bvfB2C6-<6VWJ03N#g0O6w?5<1`9-EfLuC>N1MvhU$V;aO)ZA zjRCObvjeRgK$=(W)LlLY8qAEsQaDvzuM{BCAS*>r8?%;(qB_RbO)bWm&v3wvMKe^8 z%{a7=BCmJRBDE>d&D8Nn#rJwtA~$K!{~n@?_oX(ulPY`KB}$BzZg$~WoVrEvu(jIs zv@xPU>CpsoNzGf@DFApkD+z29>WK0wBMjtLUn*>1zF}+hp0(ugUjGJN*9yeh%Fc(x zkdceth%9AvHGPdXnsMPu>}U$LM1~Z5V#9783IcWw@}tWBpc^ca;mKEava)j5O-UhGCu?QQY0aFK8k5QpFJU_haxFPHvS2|4 zT7$D$X7L4>g|Qe9!#H+Vu+;2x)l728qq=wta2u6E8bM|~k={LBPjpBmPIK8JC57Z{ zPJ89M7jPZ4D&B*;Ob+HZ;ywUAF3i)qO7;jqk=QjkCeEYeBmL2abA$g-kbN#RN)#jG zqNM1Gw2S!id|jc?+K*YI$-jVZywAx-6yM2(7%MI<@-Yc_NN-Po5f~{!Rxgl;9S0v$ z{JQ@q7yA~S(>D0w1X!cBO;)5ZtCL5Q$}dCU2F>J+k>4+-m9R+*DU!#l@zf#ncD^w> zQR+8TFbsn}p^I=s^ER2lY6`u_2wt6y{SkZ_W{eLmr(#&;3-uI_TvW#B@o8%u(CmsPTejJ=`aJ;hk0^SC&F67}LCH~xThPnEEx_>)=Ifd1BH zisoi4CtOj^`BVi^-;vhv%phU65TlxO@A8hdU!AN|pJxu#a!dmCTzE`4u&;&BqeClF zNnrQv04nFfa&gP!ilE0eDwVOQxvmwf6u?5XsO+=Ed6w&^^4P@ky?^Cc&67!aEgPgQ zu&u!$VqJF&YLdBmuGKwhWX60oP0L>pvIjEHbCwHOnPi@X`D-`d-vE|F= zA64VZyIC15c)*q<#+wCY_7Nc?MwEtg)O}Y|38Lj1nG*Y^F;pcs{Y~8Qb^#pMOn6ap zT=ILO^;2S2OuA=d7U$$f-;bTC4#^g-@3}xLWz6(4sD5bCLlAq5Y`7N4*>3Zw>Oq3M zmy)(1T|h?MHqm3!)=O*PSF1@ipg265y;#2u}Xfv zz*L;iCS`v!k3fI^$5Ax-w_j!bhp;HfJ5ojt62@37GGuZ(OCj(@xX!bfUPuscOy&2t zss+@b+3fa~ISrkL!pT>Ew!5%yAO?RkA;2M{wg_Fe6fwVK;*n?|t3{yLJMG-x&z)KK z6yJ^5$Im?}GO5aDZst*p{f()BOAmpzr#yy%o1;vBaCqAiyw8+Zs_e3!FvU!@=*@du1ghCvO8At zv(CA_i3~qFUBt_z1Uo%ec#(VFr-W6RK?mGu@L_G;_k`GA<#UdkJ{V4 zXz;-wU1@v{bjIX@?NJJOXmYyOd60Vp+1!z1JG3|=H)Pi7f(P}2cj3Oz&ECGWC~Lun zF%qckiFNp?$$~4Xup1zv?^UVoDHcbtbc>rxQ?;`MQPf^Xnaa@4*Y?&7w2sLa4f&)# zIUyS0uy@Hk$33dyb*G70bWahOW89F_3VAXG5s~#ny&_*w&cgkEJ8a_q_ARi${!I%_ z+%n-jYE9;0GumUA(#5-aYmzdw?)B3*1!ZmGK`bqU*il>(q{>@yob-rGt%E+aFlEZQ z0liW2=Lfuw@UWH&fX+R_qqlFW@@;WOfkwZgn%WNs8VW3LJ#|v8zARG4YkM+7IL}y5 zx>j5*g(J@V0Osr{RdqxwhF?7N7vk7ekyEJ+RElbfj|u!GC{L)Svv0v$cw)LZ?FBAdX^N}2D9g1yc3 zRG8#E@^sjM(k(8;PB@p57b4^jInRANwi1A;0{NAVpI(DcWmaD#bE6x%PFar7Eqs~J zBB=nQ$;h2ozDWadrwXap$K79YPGxq;gwpcCBw8T3Y-L`E5r}7)OXYOPq!l;z*1lXz z$~0hq7Pr=UmtON}+wye!#%?Fr#TAwJ`v7@q6ZO~VzeMl4*2N({ZE(=tGFlTP{j`=r zb(+%jhM11NB$HRp@$tls()5!~9d57Q-13`nTfQCN$dzWDz6_Ic-)wFN&1}~p)7tVm z(XavUwNt;|Gy?Bok8w32=9lyCTMUT_uEik; zQrEs{B?2i}a<>ERpF!LdgIv%mhU|!*g4dp-$o;;+y{W6m#3fsvYKQb_^Av+72cmA5 zX%h*3Hen@BH9N;3rXpm8VQK@Ex`D2Yc&e&_j4v-OeiQmnb57yI`tL2e`RE+{l z+sAQal~7|>R>j#LNwNJ7jC-6;oLU1CjX!$`;UOso{CEcj)oBhih2X0Oh8esA2q%>^ z#D{`FIHhI>tm6R#S6aBg&G~C52hB};OonvynF?LIn%Xw7xZ8*~@965B4UuTHpz-i~ zDt*;fY{e)U+M!e%1H32V%Yv!0>wVaP;6F11E)3KIahxwP4-J8B1=b;@o1eS5vD!GI zmd>@)KO}$^DFN1a-0EXbl!dAO^=iU!un@qkZe89f8F0@u5jr2R)1u zYRo$Vo>2W{gjeruPt?Y!qte-XA~LMkInGj>MpqcZTPnlta-@5*Kq1$|3&ijh&mp$$ zrbo<8^BRY?eZUzCwab*=0-)&Quc05u(^PPwb!IGVI8}g+ibOra6fKjn1d(0MLOlcQ z)JLka8w@&OU1*#X=H#e{gXg=1CN>nhok9;`DW!hUoIRN|P_z^tIRx1K8G^4Ngiliaz((&f`UQipz(#SI1&$2hfSa3WbV#qSVek>;x(+(hC51OP(Gwqr zYU^`U@2_U71@Qyn+^CqOC#wa&&Hz4bGz#Za-e+zhD71=CcIs=bQkll0#hOAKY9$%y zSk!xsL)G4fNN%tuD_1Ze4dr8Y>QLeQtW6;D{*;DkC~h*I z=4xk1Ox8=&FhWFdb2Biwxr0uIs%xYT`#_hSssUs2v~|$X2D-rSGnI^-Pu`MMfx&1d z)a-^$)Rf2&y(#fXt^s#!Rl@Vs1he(jtb+b36=#Xaso(x=3gX~okeNW5KdAtw@ezJVTx+G0gxOzyu55Ynh^5^jPcaczIZi!ytjq5d+lIt0yp3RF9ez;S13MADP z4Hp-CeLiN;TU(8?l2K&0n#pX|GE=O^;QW0=v({OPi(T$i5)ow3v#}E}w_994nGO-F z?t4^U+7Kv!5#jR3SjF{Brrf_^t+A`+{yPyGdCCrqojf@O<{gfl)$-hJHW&I>&b7_$ zEY+-p+8??kn4`_DUfz+&Q^eQqkc*iG=|p!^BmRCqMK5_l4JX zKHW{tzHQ*q{4qzLPNSt^*)aydQP%>>MA>d)DaGIo%sdc|hE($`Ot1=CF80kj@J+xL z$x58Q-#9^`$sk_6SqbH|@yt+l5XL#a*2(Q_{FuRscTp`X)&uhjcZ3KVN;CYMD z{jBNWo}p;>CC- z6V5jMyhDJ?wiAZ{C1&tt@$%#vLJmg@Fcin*-ifU{)wYJy3W5(ENvtUXtO)GJJ^k6~ zn`KjRaQFlo_lP|?tSJc@$9p{0;QWc#`9)k`B9~XEASY4^yt*KsmXStvN zmR3Bl!I@jrp@;&G4jiC=VcFRW{6%g#eT4W{{A{rBv*}G7QBQ#{+WbbyDGmt{lXC^@ zs^fVNe0j)YmOw+2Rno-)D~=1&Z}#MnNqg!8T?Eo{l*PRgdJ!jXoj2EXgVV#*J&R5u?H?AZqYoli{Tq+BbI`F{(+I~noKRRz z@JS>B&{*S_sSi&|5zph4{R8G~vqT}IcK5Q4zJb>FNyne&mg)))yah}$LSASS>xXMg z17EMrQKr1GB9`+k!it9ehL1unEJWogq8ZF@^<`IEuGl`*$lN;OdD65XC=GBmvGLE1Z#KLj3@9$++?IbTL>(^b-!!<% z3ZVF?tLmi18Hal9_Vf!8DoKF2bLyB}1w+HlhK)$C^4Wz~CSMmV>aV8|R00J57(&MG zQ^o4J0nAPBpgQr(V>y!5)&rPAnnCHL^ghQy`i+`m@(IDQh|>pHk%_Q;&b=xGUs+8d zDubstL^1_Jk~z7ejltbh=$yb)jX3jieSt$%f?=n5i9OiRP+SIq*&NxOT*O3silD zC`Sq$o!Qbz$Z6_H?Fbr;2)IHT@)`^jxL9`@Mw1KDqm~7e6U|*l!gBqz@pW>cM1dfT~YlfZSE)vZcoZ(f@!PkY2 z+*)c;wg5gXG?JS^)5YZ|FJ5X{@-4F-IFG5{4;4BGjvg!N^6FdxK9yUIJXTmd(>fRG zw}oCDIo_V(40`&LgaE!6vFIvSy}(9hUQ#bw7~#vj50Qf=S%xz7c3VZaAnIOy;VrmC zoLv7Y8}o5-J9Svcg$Z2i5$(UIOM{!x+~^GvwsZ_L9q1FNtf;_$@2$cMkNXnxX(~#*sLIQEgIS*lU&=2?(s`5RHozTO=|GIY!X{e-@FARl5u|9#|K+90rGorSZy++mcBo2+8%C z9x0#G`1_5Vb(3LNMrMo$YI9TTp8RXIu5xq-!HA~=4|>czECDVxjUc;7`Wb`uP=|P1QGKhv83t!m&dr{RE36Xq%vz{OsNh^K6OUL@e0i(F;D2p?G00 ziNs=cq!8~D@WnqRIMMrI7vI;+0gq{ewP4#R3wz2zXV0PhBsOHOn5G>HC*#U{4Am3Z zs|c+IZPm9$?jvnr?ZFDn9%CE2Kzw8X2NJl~2DaV?q#JWZfPs~D$fW z=%7YVK=c^w)jG$Vg1DV|ArNj!Qb&pPAK;%=8xArhl(n!g#@ii9y|UN&A=nGZXYG2N(=ujJKABQO>q2U~-VKoR>XzvD~7_FB;BX3d;choZ^8yus$kaasKcH&NTHa zDJ|^7oZ=MPN7t^YLatD)b1aiJHtba70!^p0*uv*qS0#rcOYj%5!RFQxC4BtLOHtdV zjiu(2ZVW}91Rhcj3oM?-3|*uK;004RMI)i~;G&+8~Fg2x|nnv0Z`yLTLKO@4m!oYFsZ+Y#cZUVq%D(!WrSartv}x z9?%6mT-0wK2<2bm)P>IJAW=a>Hr7le4S76a9X!AIvJ}gx;J1i6P-YFyc(ARnba2x} zD|TW=k`bERZRy1mq%SiSU6T8 znCpkU3%CKu&-Y5Mw{-a3VKdUM3S&y1((ZfSjy^Kxyj=P$5**A4+B*noCu#OgC_{_e zBO@LqvL-UY>^~77`4IjJ!}elqRGwt|kXgrL@1;?`eZH$ilhu5}9S z?nnS{F8oVW9%!zbX%H$D4IJB)JR>u@#gIrB#(C88|GghAdjQG&EL_7jA`R+ul< zN9;|m&zi%}m@nQ;*Q@HB=gtywLOmja{sLAlpr)e`{aC*X0z3#X6xGI`iiAPlZ-Gx( zFIb0FdDRj13OupqprB0X5DX;#E zb+Z1krk^hL{(ZAgcX(%>g4G>R7MK}dJK25L3t3rBdvojAXto)o>)yN)&VJK%mwMKf zJgp2p5zvbwpm%ux4PtkH(q3q!p1J%AvTsB{#~6YkcCvvO=AAHc!bShIPlu%si9p|W zVxB*s?zsvrLZa^FC_C$i7AMaEBu&Ovh|H8PJuLRVAWBzBxH~;H)#r)rYv+6ee`ESR z=*NB+9gyVSz8~7_O;`Jo)dpdY{IS*Wc9V1E+8xn<4C$+4h=(yNpFV%7t;>#px!f@> znCIv}?~40)7WjJk?tQKE`#9|LexB=+7ZSXAi}oeV)us)R53-AYaeU7Ce(L+Wjoba4 zy7`{xzn`xA`6uXh2$nY_lCYsX0~2(dTZfuVd?b(ODDtJoN$FN_;g8-us6(`7(09*Dwj= zB|P`JEBHFRF$l+J_j8GKJ!hLa3%s9mx+XLqQ-f9*1xWIztNmwSS9Id*7DxBgN?b zQO@f82@SaFy^M1X(A4du4%)KaTQg4`Hg^Pe2rDk3zv%{&{=#h-(DY67<#KJxDlMDZ zcIVGQe59dM-!2}nqi{|SP9HnH54hcS1rJhD`Yp>5_F+vaGyeh z@MKNI&&g+jbsp-Hxc`R)S(H{PqvP`ZFgl-Smf^z_BHI7G9O>HkF>eTpWskXy=u({m zDq+81+vm9HF~AqXM7i01P*_-F&VBdQMVzt;E5w0B>OBctXqNT~pOTRAyAx&g9ZcLJ zhuHkjCjZ}+Mk{QCa5bVmt9|fb4GcOh-DTZ9pNIFkbFIV2kT&Mzp1Yi%jAq25)AHv^U@wnRUhjg#QGO$n*J${l=_C<(0FRPHlHIJ8B|9iw(d@p&x;X*CR z@zV^T)&}*x&z3!4Jr7V3)aJbtQ6ME7G8FLJIU@_Hv}VRuJAm(9vuM~rAl=Cs8WdN$ zzZqgw*-5REsekHe^=+Sc&Kg?i*eL+VaXxtQzLR||6ZZ8P*Xe)xt-ad7!I;{a{0~p_ zZ|fhu^B<@4U(LkI!OHbd{jbCPe{nxmema-}7!(Z6|5G}d+PMH&{>uYZGIh3hbuu<} z2C)BEAYyOl@>lN+_{SanOB9tgHL)}lw)X&NGyWBDa4`eenV5B9{&GeC$IicT|Lpza zm?}8g8!MZ-0JQ%$Ma2OODyAMT09^osh`o)yld^-Mu_@pmOvIT9!115y`S}41VjeCM z$}WFtsQ=MPI5WdA{qy~=ZHd1)rvEzn4=DcEwf|sLRG0vq|AnZiumG6;dG-(f7tQp) zr~N+;{%5xT?cslS;{TXrkXMieF#V&x{?Bs$WAFbHtt<;*q-SLQzw!Ss99yRUA=%3P z-DL)$e?(imf6HSKHFdKzHdT@k{{QFS=A^o-D6eCL&Gm5f%%czk$R2S#p#h6LlIUQH z5mNpNAfdtJZld7gXvkD*CMx~F5@E!~VrZ~Ifkvy)_ect(1B#+z$J^1?&^I+~4?CHk zW173`r){h2<~Kg8oj?j7fnb9!8o>Un1sZ6-F9&o`P^X5UL9md35j24N_sz_}Bwj>8 zetq=tWn`2~jy660ruR4L+NAAMAa`E*_Ddk<5Fv#Cf)QJ0=k+DWJO)WtZW_U6{sx9DOOJOIIY`-WPtUxE7Y|p&N z8`88#MJf~M_?dEP=_OkRh!HJAfBKZXz$SuO3=R8t#61WQRPr!aw-Z9tE0;wskVmQc zQ6yM|lu;@2YP#j|*|^!;U6b;w5fe@FknDcAhs@k#Gh8eqrhlD%su(btrfr5r!gUSa z^|j{8iN$N*`YwU5@+aT8=ez11`PE#mP;{>5uFX|7Lk|Yf6RB1fep7FXDp0d6gy8Xh zwfqeL=pG!Xc_;gUAk;=Largj^0ygUE%ElQu&zhd*jN?5o(0;Nnli4@EPbsEA z0ErYji>cUgX<6wH(dlV8gtR%6&u66X!+tKynTa9V?7V)=yO1+g#j|AS;0TMZ5Z(Zd zczP3lBi}5GMFdqW=JdnuYn~-%MGO(6x9N5(Co-r zF?7Rf25|=3^=S>DYlc@mcnD+t*avtHzU^2#%yw+GU~P!2(Ov$RL-70LcOKo;J7_n7 zhy%{IM&3ldFn)M`1iNvBqkRf2isMf z#6$swWJ+>0d1*W`;dMDK=?=l4f|HWuUZe?h-ZuP!QUllV~Hs_u@m!r@6ee@A_QQsNi z+5TqrXXt|OA_*rGrxynsM-?ZHb(9S|(=Kx&^EmUAb*$M!3$_JJ>safwMUOEhlS3ynfbs60PfAMw|UyX5jlZJVbT+=M7ZX&%lhfteNo3gvG{0{~V2K_q4n*x5t zyqdh?K8ZeUzsdf2z=lDTP}V?sL1aOnVXk4(zA;H>a}^Yr1yrj-7P0Vs&iWw%xHhwr$&XI<{?gY}>Z=rSJQFzWr_;`)Adv zs#!H^j5V)wV$2a~#ih9oCEeD^`bk*x0}~RaGUm3Syy`V|^>UGg9QHo0VUK**^k+&K z?r^p6Ou#xohw7Y4k@}PhPn}#HOwF?X>sCPDN`IQUmVxI`klC(5-9+K~K|@6e^`=wT zxhH3uR`oidO{Q(~0si5~E6FQ81b47Ya0mS3l7kajTY%?0;_1+5Imwx8v$Bhqi!&&-zOayBf16nJ@XWAicqBj);4CsCIv_kR zDlP0ToGdJvtVX3?wQ3ZjSMoTsE*ZRgwgbI;LBpt-RCl&w*RWqQ zI$0T`)1z)nfs2KQv-$lq6uGx#U#jv>r^R_6bTPgy_%-fukn%9{TIaie|4BTv)T<~QKRfX@?(excYA4j zR--s0w`TDQA3bWPZAKKIR`lCBxJF>)U zai^Q=o~qC5V-Er69lsxbzdCO@K{~IkAGhABrRu9|FHco&X;tix-Q?XgwW*$Us_1Fh z>LQp%8%EbN6xVi0RGEp+7o8NG_+mz<9dw+yH=Sp$46QD9ZCZNI0!4xhK=9zAV7Ge@ zKgyX`@LLY(t!v#*Di(SV~iUx}Q9_o#DoadZdWG!Y*VCjvF8?4#2 z9kPDkx)*duE<2WE%x`%DWg}p}-WhtryUc>+T6PWdEIlTD&wgl}`Wf~!cVTTIw6TE2 z)LqJb^VnxL6K4X4nm7H^<1XSMHLdQCvE*dz1ZqY)d$zOJjlf{wb$BRRFo&uGPiy_& zOlDb)>$-BYX zZXPMLEJao+Z^irk*Q?Ye9d~Cri@K9_A;!@`&4RR_iO*HCePEL%lawO$A}691qLUHN z5$kR>cLP_W5y`W=fnDSujgN`bW!YZNuN}tvBmGzA)2FGt5*x*x>@N!smWPH%d$Z1_ zmxV=P8)com55DiYuLgHRvBzh!PqK;Gk-W|xP;WObB$mGpHXj3SU;lS3_(z8Rg92ZY z{XhElukQX^_a)KA1qB84?2QcZ>HpRGTK{SDS91T)68JAV*#F;P;IF=S{F3JM__UIy zhW20T|6l#C_1|Ukf5(J>MYy1zgPw)8@xNSR|6f4z--P&IDgQsu;vWE@Rdm#M_=jiy z4nz0F4_05?A{SE!S8B1pTHD^>OVaCEIsEPQH7WXkh(imS_V1ei9Z5t| zRar)vQqk2?-`e7fR;-n+O#jJ*L;o*b{I|*ct@zJm{wtFXJ^NSP7k2!=Qt4>LOq%uM ze;>T$8NhZ%2!D;v@{@BS-y|b zrTg+sd|Fj}hW{c*A=NL4q@#oW2QmM8j-9EEgS8z#!+&t{Kdbns!{1eCe4*xF+@!~6 zVr0kv|0Cz04*&Zq|J#uN970CV@(Tz57x(*0#bo>!yZ>n+@DFlR)3dPRQ!}u$e@%~_ z37?ID^~-<7zrx1UfZxj4!su%uwETbl+yS4J?koKMb$W+?yU+^i*@zjL8k;!avoL&t zsN$E+RQ~o*`?nUF>1%LWekWs9Q^UWBp;*7HF0JSCZ;76c>8tp6Kfc`iYd;wN4e9?8 z5&u;DXQlrY5no67CnEkW(&IC-GqHUg@BbAbdmS*EN=6^NA6$nSsqEd~K;qye?7F9~ zR6tyO$Mu^LLZF8|SJSqmfTMh%RqUEWbcwCFR3aK!LRrPYim2bC&2Na^~+TB5j8HRM%&M8 zj+Qo9P$lLxjfqOwX%B75P%W3lUwJC_9S3%!yA=6`{lWM2$f#=pAJ6mBwBK*&BzfCV za93Dcf+0&pJ@m;cic37FxV3^_i3r;3U0faE=7+@tnBei-+dWKul`&&}Lb(n{ys@aN znOp9>T9HC7F9h3^udQ)-5G zV{56I-z!kC*=yo?Kr!AfpD(hcG3*bmLnqfy#s$|KmX^qJVoObwkss@OG&kg)z81NU z@fh`y8KO&ddtfu+_VB6vRED&h(%>U)hP)G;Eln|bDFH~{mFZOY7$FUrHfz#rc2B%w zZJ}sr1KfgmgsUxXt?_%Ye0FtH(w+G1d&Hf70r8|QZNvI{aH34}hO7$5Cd_0Z+W?yk z4bo?Y6hR~<=Qveyv}H+(r@A$*G&Tml?PY%mSNXR+&BBo$7(RjF zhP2{KlWUtZxd=Mw zc5X_L-JtPif4@ z&(Tf+p>C&%v1b16%!Hk>xi@E0IR8x}-15w4GtM3LBI0+!iW(v8d(2fEw-!B!D3O$p z^Z~kMg&8Jf{o-Ro!I-*b7GIi3{G0jA%Sca}yl(p5TunpMtV~s4_48Np1d1@_2rBgvT__LYbC$lRfQjq0 z8Bsqy)G6*II|_bdu;;V#FvSPsX9<4pbHBfwXrHfrHut zpT4?^Doq7B6@`_}awJXLh!Jbs88c1WfKip>as^G>xKWk;@?+bXQ*y_Kk+sb-mX=fS z=*C{{S1W27_p(v1ZX@2KT0FbuOd9v}QLiN<-ksW}wlh(!2Ll@Sua@Nfv{gS_CCBQO zlM`txVAm@u$;vdf74MogT;&}dr)&2YZn*Vr6B}|0Ell^3_0^4R)s57p*R>sOpJz&I z|762}?T_AO&!Hr#Q&xXHj}vI5raaE0+%W!A?XEt(q15d7&)aY2-;-?Cqv2uZUb*rf z$*Wn8s#c|czRqBWu(X=3wY8F3YDx;qN_Xw)6&|k4`GqfFj*jv`wchgK-^``u69pC} z^#^Wl(ik*c*J&Fpo*U}JrcJ25m;1mm|CH|s8VwA5{+`g$*49?4)6r6E%qy=xLPfl< zAo@&%D6d6bxXJtDm#5>dW;vX%0_CbqML|mof14>u&4a_XVlu^qDP5x zvz)@hQYYpoQTQ9O&!q2ofGh=UWMv9)N-1bF=0BVpX64ys;!){s(r8vAoxX}uC@MPHfM#1 z`};!2oTt}S=9Y?A@s{eXYWqFg)-}WaHQ`f$YmB>3ZmKon0^^c({h?M-iwal8+Q`8r zA#aTnHEe4Jv8jV&XXAu@{oVZB>you$WW{ju`0PZU<3-o%9QPczij%8|QHfh({o%*H z*hiXuDI1`2{Y1W$MUz`D$4bai zmFsOry&Hka*K;$D?MB_1*O&DmFt8$>}l%7D>c5<*OO{xQj_1-gX)|8L}s22_D?J7qZ%hTq>)ZV?; zsaM$j?Ic`8pH%2xPw2C^yXxSF1l~PQ164JvjV_&sx7=g*G7egF*T)N38_U)EF1$q{ z;tp+*O?66t;L;gzo(2SDRTGR9o#L31fc}WZ-A`nDKatYY7C7gVZOF03ge98;j#o*jbuOUB*S&m6EP(KA;4&nHCBrcYWOFy@B6D=P)2W1*}NM;xR041{+kiMD%H( z)$L!?=<|ZCafJy<8wQ^);-yFcfm5(kA%31?z$S0%o&34e$vz_fso;Vf_mOC_DFX0x zm@U5qrOdbVGF`(GTHVW*E$H^pS$sKi`($&cMUzl4!IJ1Hg7JQkAQ|E}Oy2y^OB{g3 zRM9jKey50Bo4z;jj3h_lH+Vk`!soV`Yq^B9 zfUZ%FGzW|H`^+rF;3iS;q;F>Ls<{tT(3)XUJh^~S6fFEz0Li0WxNrdPkIUxPVeYwa zVdCn1%AY-@TD8`^%ZdOQtO6#AB~~X6gK5dHRcHdwBvJDN%Kta=GyK+YYJ4L^HWv~S z*CLAJ+ufGjJI-SmPmpC0L;(siI~fb~5|i>XdLuf^rHTpHR>8Dt+lc4=Ncy@p3V(hh zhaP?nQIc9Aw$#}H%LP1?hkZxK{r-3f!K|0Fm=hd!~_xX#KHa}BR&$2M7-$!cL9H#ht-4XyRGqBlw^+q zHfIoked8*Wlh6_#I1-#R()Qe|;xw)8XH4&Rj=b4= zD>*Y!zbt5E4*V4v6Az$^ot^C%uvx~$B8BAFh=`1b&2r5?v_Fa-qJiU|GmVRe#>{kW z2jK{N?Ka_TD__hjdzM3=f+S=ks)bBm*hg)`a10SOI=j<|ZYa}p?T0Mdv9KO3X{PeZ zfK7ZkJ6=)I9cu!^zq@|KXvx$2AYDFr#Am=p0OuD!_yDRi#Wp@9in`ldvyG-nw`u*O zO-35K^=>{<51ZWeZJvySth&|8f_ICv?snJ^b=g$G#3IJ<5h^g4KmY84QNHK;+_6Wa z3DLJ<=<7;n#P8*3bIwK?(lqE^XpY&<2M^ryX(CJsK>>ZC%x6#U+=gAUL0p53oK1_^ zw0iDt+cnD7WEo4S38|F^vQC$cGPHNx7T5511&~w5qs^Mhm5IIP6~fbp6R_4LAo`@K z+zkY8&azvR8q(uh${mEE5#58q>_o38|ov!Spp9?Gm+ilCW( z@?xEI)yWtzkKFY3yeQsBZTN)roZw(Z!`@j{@c-C}JHIsc>Q6UK6nP^QJ;bGimTHfdp_= z1x45CF+-b~H`j?Ec`=Hl<<`a~Culyqbd$WaE>Et48>50MFFVgwHW=s0c@$M1o3! zp2sd6u`)%B$Fe4{(s{>B!3VR%4qzS8f9exAWSeG0k9O}&U${I2J4M`&((gcV(Xx6$ z`ecs|@64m@FelP)cL#0x*9@(|S%VpEq1FUw;zxJA{-`(ac=yPURBWl(!fC=Z#k$9= z_MGo~^>mEg+g#d^wnVpd*`hTAP4twx%6@=*anWA0-Zov;J+*lJus*1JZhJ=ZBG(yW zy?MOVc*c2Cd<%aod&7F8|3L7-^G@QO)Inn7r;I@L3osRErc-Rz3PC%7aTN%aBVQwA zg0}2++a}OUzN){9tJZN5eu|u;#{LcuWesf&a|zjnDg))&s}mp_&;|Y8i`M%Iog6^f z8xy8jqHIMWi|wV<{NX!Sjc^crsaM=xR*W@o^TRC}LfL*eV^%J9H&Kx<1iT@%&$Nyb zp^zUAlc>=lf;t%?h!VnKY&D= zsZ%Z&>qM;k!i#o5h6#ofpKLf=#H~Cjn@TT#8{n;40Ub%=1DjG1#4A=ivYw5qA*$ zsu4NyX~IU#FV;mf?1kRE4Bu4~wB+YE-rcT{y!ar`UWeUdD#}044}!1!9M_b!h4MkQ z84w^jMpY`VtapT)!MpH!C9lY|+lBI>+EWaABwxFNlDmDat*F>c1HU=KO%q1p4Z}Fz z!QE=mg(cTSpuy1(F@54|R}Wl2N?|wpqX?dl*|CQNOLf(F<_Xzf??5XZ?YX-p=2&+u zo%gk$B~1^q0Y=*WD_5RHVOR&V9y?o9uLgsOE(~I}K;7M;8L$VUottQL zaOKUBP!Qyn);%gp_8d3(?>jX|A<2K%6f-)pGC4WR%%wZH(RNgdmNhkwEd*%ng(M1| zvok^+?g-P?VMEqb!z96l@h_QzTnJsw?BD6r&>73IJZsMP)mFo;VNt|$GOe47?$Fyh zP%%H4;F)wqq4lif$wHDsm1}>j=ta@9o$d!z_L(#63WL*H1)Edj-RkpIfMMVg1HAxi z1<+sDudQQLCKCd;1AAbu+&>6zpG?W=XN)uy0iv$*h>>QRUFcVAi)?+&B;e$VW_;0> z^Wdu0w`8ZZ!31LhI9d97=(NpVjs4M3n7A-gx5P(;CKSpaMygkd*;4iHYelN@=1Btn zL?p9za?tmVLZCsk7nY^NKRFKf_l;WBXIT=+XxB%e83aswr>}LKBYGnt(k)B|*Pj~g z>BG+79goPj#iO|$>H4}=Mn)%0npB)~Bj>fcF{ANj*$#+0>chFjW;N{+l&tY?NBMf; zFohNBi;B~hfcakcKItBIG=|mDoP!Tjjp{uq9*CF56MxD)(0+>C2S9#VlzYwb#PRx0?hd+3PPhn-f0Q*U4Q1#l_a)0n{gX!~mVPD*5YiK;#I(r*Bx$uRyeh&D@%g zqHJ@GO@Jx;x)t~PYB4hDCN5(V>u(dhU+pH;>y11uT_5+O{v`ZADi|QNL*|Q`p6&*L ziia4q0j1RT0?b}26_w^BJwf_RFDc|fGY2f*9AlF2x(S5M8w5@T&q21fI3ibZF-PA~ zv{zQZK6LAef_U@NyInBy8`3Wtq*zIC&+EQdMD?FgKY&SeI6QEPqzy?uEcd#Q4<4kc zFa*I1P5=7cRSe=bh$+ikXZp_KjnS^giuL+B`c#9Aut3qyw&GeT-PDL=cNsGVqzjDb z9dhIxeD{EijFx*9N4?tH$Fwse`#aN1Xki*0M^wrdo4vg!d!w<(t2Xdypr-$bwgSf# zC<4tC?&P=Xwy?rU;5CEma%HaVq?Vlz8hfdCEB(Gjlax#7+^HZnwaCIChx=fB5`Da5 zM6%X^5IAiszWgYRjCMb6#dV_bOt<7?<%3NiT3I;SeZLV2HTzWF>XD7dRpO7q@cSr# zl2A2$hmNR^1`~sgC<4U>?jIh%piTx17a6oMdtg{3hxO{|10HJ?+p| z&>NY$VO}H&PlOc?JgqFd)H=s_2)=oGM>M9R%hR3%+U9dJ*_H|rSR2VayXuCzd~ewc z+(nOH6MWF-z5XV~8p0+^(G( z=wEAjJY9sWtLHm<_GIX<=(VMO#V%c}#Up5M;2S!JlxcHpPFXVG^~=OcZ13l=i=6KK zo+iR=z`-s{HbNr8g``XJM=L8g#v+Bw)XQzRm%5mCzTGlPWgxNllQ)-Qht{s2aJxR8 z_D{~aU-jr6Do3d9Oj(&n^CG?<)9CtFb8}nowAjagP>j!}?uZ+S3go%Zf+> zD?iFt_8$3u{HBn;eZ-#>32o>lTwT-xJwDhKP2P+ zDfOO%@ny_!hMrRD6d&6$F;nAQ-sl!2%W}2s$Da~}MX5f)4-R?MoKP`QTvm*`S zc^+;jy%|j2X$6KLtY9Ilygm~rE*O#P0C>E29;}0VPQ8e=jdsAa8cT8kiTJD2J&-8^ z>CFD^fV>E9UB{!;^NJLmpHf!T{dqKV`q+#TLISanJbYqJ6U4*6+b+4N_QY86 z4J4ABh96cm*E2t>R^gAjB{zkK)ZN7un-0hn3!t2t*rSBmvAMa|jlmBqoh-1|=!?^_ z8r%f7277wQ#&ZnFC~T$_wyKfcw&tX&S{id6HZJ%kX$PPdBJG(9+S<4s&Qp2L$idB~ zXO}g_Lj$D|*`^+u{rwb)lwIh@BhQaJ2b_WrbSuQmEAX;(utAUv(Mf5iITqh~ZFfLd zM441kv{k|mFb7BH8_=~a7! zGdGzmq<)d~n3Agw$lAG1&3aaH77^2pz9Q`!AzagcdAEb1ntskq^e*w{9fGUgzIWR* z3GK#G$sSJa-T5^T0izNfmh@_;iNUXKIq#pb(Ut{8_F$D%dYhQJb zoqpnKd*LJWO_$)ex=eq-xNhe>yMVMn&AeIIafXsy69pQ^S?KprVh7EH2C=OO#DoH!@({k6SEo58!vnHGXC8O%<~x3jS()t&Xg%r*4`B3;Sbia$XVQF z?&Qq--8XK5&3wG6u9?r@$qDbWI#yh)p^SEjny|?Mnb%Yo#!JXLz0`*)_U0|{R#;8p zt3w^#?_r$79Ru%Cr@J42wDy8rP%ooAWpJuK(Xe~on9f2c4+x*wcmgN4Z=a#Ph&RI) z&77_$Z@YGMcHN(wo*$ohZx5d)pJ<=>`H5ZhMAz`8kPaZ}d$|Y{tDz+Wm3uMu;;)LY zP@H6=(2uyCFUu zQ+E@?wMNU{dF&bY>QT;aD6tk9!b2^jC{7?8$K=e-UhMTBrJWFm&dOzH?0%4gc8ETK z=EYXi1Ye2*jq&~mCqMKSRjoPcu`o+)d(_1Ua_8ISRiCdhB&5N1H=k%nXxkRNPU9jE z`1=4zmBDr>usr29Rn|=bFee9_%huQ~p9Hgf3Biip&pdf@y+5dWQnRUU5ob9DKkYR^ z1$au&w*sZpulodtx<(evU5APJTU8>uKZ9WnZr#xX<5H%)nTe&ga9KWmkhp)sFuwHI zgj%E^HS3)>!36a!YZ;4b9jf3uMc?%OSzqXa05UL-Nco>iOSo!JDN8V+M zRrMHG^H?Yb8Uvf*$G*DlM>a+?X865EaKBv{b32hA>8Rr&V06fIo|Vjr{u)l7mHoVi zzoHF;nAOSHJB^PDxaImFq?o6_sWB+!)n1cRdyG5MZ?+_B#I((~M^KZ}%z_~-LDo7=LR5dAMQ@JaxFl`wO2y{?s zoR7V7q-2QBvW6)RML`W<7Dyo?rKm{(_)Pp7pHpR{Xra+CP^*qUIpZzd;i2q9|E@?_()qpdu;QMvj|% zVKNDbyGf178t{!!{;5<(8=WQ;p5%X5go(fm8kF48R?-r03rW7r-ygsKo zntCR2N7m#NTm^1jX))K`l5*D)emq$}q~K-lfjd&(M@Vx=0tM?nP+%mo4eed}=-S0o z^pNJ0^92t_^`<6DV|9ne*?v|u`cGT7gj3hHvu&%xh@r`^1Pd)ZUS99@PC(y7>Ac?Y zYA@C68p&eQN#BVZ?^Djk_LXhD+oS2Dlmj+)zn7_?5Z`%W^Y6*mz#}5T41CP~Cs%q? z{y_M?^<->WHkKyd8p?6eO&;EpZ}|mJgB2w`))!YiVggQO{wsd8!*_>x1H@10EUcI- zQf={tt(#ZDzqG0yobj1{8_ul!^7>)0K5Hf@;wDfmlWQmuT%7g!og_FDHlD~LxZemi zBw=1As?p;x{aMegL#Bu|d;@+x;Us0WO~B+uhWSOtZIH4p1glRdw_w2fw7WoVLmHpJ zovCQm&yg5UGRjT;fJgwy#L6E5AuV_hx$ej2Pze0*j^A(d-t<)zVey_3kF;5`NgS)2)Z zHWF=d!i;%@gWy}Vv7=u^5N*s$oUCNrl(WDa(a02)2@lPJ^I*bSXUCq?Du~9cNGa}lUYw+WfZ9qHtBhT@dnjwoh{@v>So*gQ-b=s##NkhfA@40CW5ww3*70@FZa$mhU)ab^pH$@q2;f}=;`O*v#jHpaM_@hD36Qe6LV`pT zu(Rk3VwgNowu}0KGYbX`$rn^cuSMQG3qtF+>p(QBdsn0%Vh^wB0~SZHTp%4a)%D(m zrzKhilw;C8OR~UcMjR+qe#VCVn&D~<`8C6to2evW>A>ER%reF7fTN;~FeURs=8%w; zH#w~{qcd&g7SbuancL-TO71DrRghfbPdF8<_kzLuaJ7G@HVtNr+)^^-oHnvvSboZo zd#cn+y=&Iu-a=BDxZ2I#%^jAwj;yxo$ggp%d;xb6lUH*G(I@CzWUV@kZ)-E@ufMp8bFyYGBEc~f;&b!&Y?S}nl|)$!ZjgZC5F8-tRW zYo^C+91c@z!>@`?1oAs@psrr64P$+(6>7wkaoG1CxwD2y`hlR>%3MQ{j=(Y7_H$SLnb z(J?YcX{mFuuwY!qbDl@mkms8PsM99poCp3OK4Yz&LB%RFwz-%;oTOp z!VJWMFJmwNkr`ZTHY-=It=95qK_8nkkWzV^V-nTnPa+=ibL zijrt6|EfKU&?TUwy(3*3}_Yv$wMq#!Ai+0rORukl{)_3&iUb$!-v6BzZFX96sO!aMpg+?4<*d#f`;Zxn5=R;d5mTChfS?j$Ma#f)Cs!oYSKNfcREv}n z;pCQt~ek+@4scp_G84n@bwqbTy=xMs3w)uwf4V%sfc0RVJ&i&Vi}%#+nq*Zi+UU*W&cOCeTmS?d%~b4hZ*PDGqTS z0-}Tc8#}Led*s3S7m)3{os(%g+wV;+?^*(;oB-T{V^xB*~oPv^QFhI+7#X z#NAf2s-I`BW!TSstj8BP<66~P)L+vH2Lkw5DW)Sl2fE(&mN$umxtlC&f4fVcC{`WU z-)c;5I4_~)NtR`N4ns%wC!R3oZt?-|5#V;+#Zw^ob>#7>r7_Y zZ44x?v4hLJS@7M$ zy3A6F&(yvgOE0BbkUmmr}pQTY?S1XidXxM|6x?d zXZedqKY2+0HOO8E`6~Qa*`F%)uE*Ue(O+owyy8FdAn#7q-(Pq(SWRj{XBh~UH?tlr z`fH;H&*V;=$u@QM_Xl&l{6YQI;ob1Zyd}g|cjGhP7suz(x}*i-AaQX7hT#duW#}bE zPVcs}`se3mrROHF={Od~$NsqVUtBx1i!MZ1Tt=%)=E>2Z-AwGpBSPmpC7zz4g)I&b zMA@Y?IZ3&fYc?B#Qs35YpSUGCuDci+5*(SI{f;+>r8FPKVYNG$<;K&fgnBN*krDrs z{3PiA>qn|oVa)N=1$>`q{ttXvVg4)$pP)y9T1d`$-oPklAo6}IM|O2^S2NU-A;CYd zBfm^sdBeC*i*h9Iez<}$%o7ObaR^UrA&Vc52s7|uCk)|cAmBihP(a!#LuLYvn8A18 zv@Jm~rPBB~Bnoqs9I>TP-e9+4;d2W)>?@gz?e**n{T zX%eW8%-cNjk+#Ee9wFF9^G~=1xg)wCt*_}_usyn8L@$Z*!mMA>HjgfeKkg0jEnp5o z2&}XQW`megX2~ARKEZwzEy3uFtv;D`f^+VaJ-I*4$F!$CH!R_7emgd&+^e#T>2}gD z@<8~s{}BH$9oC<`rQLQ3^b(B2e0a`sTmKGB-&BTA$d~6k?$EfsgI}_>w+zqZQN7AJJbrj}0qIl~78zn4$a z<1PCq8@p)A(eXeaBAUS_Kju*&J5yDp=!MUH=bPx9 zDpXU^1{kx1h#!3dQzJOt`r}<_Frx?uQXf6!B1m#TO^bTDvnR#tfx@$&;#4OPA%imQ zqQeO21m;hJ@H;`5T>~thv$87fM?R06iV7GqDwi=BpEP}SsC#5oZ1pg@J)?d^O?g@o zy#kyW2d_(nad*5SC06aRfJ{1?6J|++K#wtcQ+$-G;ukEQ$wg zh&d3df!4LtSzu+dR5k=)&)#hp3N5eUsz-JQ&%4)8gbtAH8Mzp2^4lL!U4W0^%Q`be zo5NnB!zO^F)37?0YL(#=FG0BQpaeMybu1xNvM0?B&^+fLK6`b0n1a~tY9fKo;l zB8wngq`SszzP@?b=i|n8RrALw^XEA7sC+xPalHm81q3=+$F!f0Y*7=7W|HZo$Pkod z@`_A7q1us_Bf^*XKyTdMWpEPsI9mV`4GCn95lCjOv+52_?tu$iRK7E8ZULvpTL;nm z2L2~kB4QdXkxGp!>8*gIK3txX{f`(h068{dHW=9-IsEfoj81D{2ir8kq*LD7xxedPs3DeHYvMu zPTvz{DmsZ2H4;KKNST**9ERQeg|7H1AOpN`r3w9(2!7na0p+_b$*00TGev~qJnG!@ z0tBA0?F>L8`*|Kt>&NtUw?OVD##Vn`PXeEYNxn|nS-<|+{$!W$08sb_kM7y85rtol z0j3?fu%lSA6sHdNPav=`l%aC*z#YP)<|UmPPWpP&KXN-?zZcCr3R)Pb4fD;14*2l2 zk4W0Lc5Od{^bV=1A4Lv!zQ{Hprb(*8gK}JLgw%)v1KI)B!70_KtiCBp%hVCzNX81) z-(reoJS%pB!z1D^*-6#l5!EH5FcB0@8^nNvfgxOneg;3v&7~6DNw6;KEJXJLPdcRz za>Yr)6(;!RH-dPTIJI8~)!d2ip3erK;TzIs z9n_kaPfDC9F3YxVwJKHA$6SWM0N`L5U0{HG!KIxJ@6td)H1bKC$-Ie3mS7kj4TH?b z9ec$&S(T|dJ(ePSc905JL!v9Swq38Y=~X1+$PV)U!8|56*tvlIj(?6nM~7daxLLx_ z^zkPi$zUV&@Y(#Drx0-XseC8zUiCjjD1+5g!4SaV!!r2%cj&aBx?lfJ{UkQgZf9IV zgL0C840|dYpGH?MtmYIt4AdeHHX~+aFM7Q& zPR*>$bjXa6yr>jF=M(UGAg?AyCAvUERHD8(jZFdi>V%%D2FlS2rU=5iM#HlQirhiu zK7U&%PJ*%kMHK<|mh0u1qb<99224dIGRiiS_h7BSNM&Xp1q@^GM+huDD#2JlUavXIZOR|dXt{T>0YE+{zEY=)s-G{-ez&^ zx%?aP&;UP9tQ0IvJe1VWYI$KE`{K~_U8=rdJ^3~jEE@^)Gdxhhj+(~^)>}Nh5Ysj) zXg!cYwRd<8`wGN)Z@}e6hzm@9)rKv9vGbkeI8W<=9MW0-ET!5L7{}Rot)Fl{ECyE) zG7`?H7~ePRA%?{dJ`HT80+9h#vP(mNGiWH^|mG3 zdeKIc5h;1;azSn4ejdL8@!h+S_?3WASQz9!{Z* zc23LAlbM*lL9>qplPR`Shwe$&kZ+YX9AeFU;K2DC_&I&WhzjS>^zYlgLar%)nvT%n zZh_u}q3Z7TTbDtFWR0e&S%!LT9RN>E*4N00E|fSHSS(%JBjNjgiR#bGxgA zOW&>N5vNT8c({1iXzqagiHi9*c_P4gGzy6Aucdl8`VoL(4qb8&WKN2(Mzz$2v&=dG zYW423Joy7N-Y*W($l+d$^a`%VrE{Klj1bjyH7z&+{_G}5c5wR0v+NK8ENB2{2xmoaO`h$ty(fgX^+koE$&IP=y^oY8~byt5cP;p-Wwh|~)q*Be-b`&0ug+is) zCRZ(|dViF6R(FBxaF-vwBu`j3zcQ5-575oM#F@!uj{*Z!UJF$57U~k<7@p@54orwR za`*WW0w@p+dYn%PsfbqsbQfsOHv4;{oVI5V*rXzs)RGIby4ZuTef(1o$cDc4`LS%h zLT|u}de`S86yOUDLYy%dJd)@ec=j{-1@^CiHD2fLpfKX9`B*jlh6-c%qdm}(I=_vgXbhdXMi?kBAp_7!UruGsc(H3(Jglf=l7}eN( zfY{NQoYLBGu0YTyu&_d|r?#a`HLIdPUHE`EvHU;O==}zrAMeQUmfCw1@kPSw*A_)!6o7 zIyyyJ9No=+r%tfXPmrt8pooo`5U`*@hweYb^h z^JmaT-B&e7nC?ZGr^+R)bMh^4Ft#3#AWwV-9 z8fWu*1s@ogheS3hjwi$LV+ug~FD3xuAb{Ij3~S|#pLj(7JnX{!#6Bw1LgxN)VR&71 z5?07klY=X|KgBmt7#2z6uE8vd<0W%9FqU^+bj7_xN|eAHr;myOU{8L47;ldoOUy-Y zTnp&y#X0XqvBYGKX6iRhk6w{8nsGMBb#Hrhg;X*@!ycYDaW&}lanciImtdX7jD&-Q z!EJqSS7BOtHKgq8CHG$y22ukJfdlG~qF@yHJX!ue=x2T@OqN83tLx3LO;3AoxCK)m-&Jj zvI?M5iQ#QP@kx6iw8z^)Qz9cT!KBI zg7;o7)LR|kF@0VQ6YxNvtw-gM5*Ix8mh!Ff*CJe~P}7S0oLm1k`X1!M*$o+0Wu++S zOm|!^U7qfCWg8jm=;0Naw3UD(U5us(L(NOe;PB$tvsr!0-X@}znFQSDd^PXisnk2o zjBn(@R?ZDI4s8m{_oL8*2Aa^9k6F>$s1^fTArD1d1uxzTF+zYUyKZA&QK@1a zP)ya7-pQz9YV<4hdl+dIyPfs)UPx>B3KtEwsh-nLoAmh&iK7Om@u-CF!{1X_jUGa& zMUkD*MD%=HESM_A9JrYl6C67P^)g(edV$?Qy&+)QGPNzyKJss0U(bQ*s|JAcnBH<^ znO4eGoUlb+tKHSFuYRfVnPcrj;-UhaVE4<%*{7kYb86G%82MOw?VeE-# zAwC|if#b823lZp1Zatl{jZ`)FZ}A8pd5;G7!rl?8pZHxrs)x(#-o=X5eHq%`*a%zV zP75+6@DSD7mYyS>u6LoIy@~FXsi;(Isy~hO={1cwM%cA;YDQ3o91RX_>b-jpuE};u zs1gqNAShAO)|}&j+X>A3x@$0Nsb;slBHpmQe?DTp^{jI~#F`%GcqiHK0NpTkjp;Kd{A^+AG%( zmG>OCsu!bs#QWEi==sAr5V`C78L5S_c_Pz`g#_~?^NZ=VDp#S~h=av6kniT3b8jlQ zl?TyjvuRx>AEnPq_QHF@@^hg)d0k|BfoMN42ju7#B9IIQh_F-lu+rH3cs3QgG{(c{ zAgoheZ@gRt=lo5Fw^oC*xavO;fpLtr!{sv0PPkGU;h1ukIdjk8)bL6PdHU05`QtZX zip1Ju^P{lB-F5aWYNTRXOG+t!2=+qP}n&PQZ4>C8|aEx4QrGMa>l&~^QUpLYz=i!>N>u##D5B>b* zDv3f`U)zz(-A`s@Y@tu-Xy=a78zyrd(3O)5p=wx?(@USPz|Mv{3Bki7v8*;3v;C4g zk9OdeVCQ<&qse{)D-rl&(6kcbm4IXeL>U5gHCSqk2h-q-nhR=gjUjBP)n|Ywr4Hj7 zWlG$lUw15dp5l5N15C{#u)Q|JyQo*Z&lxpi@BalezThhIx&yQ`A6Z5OZUHwN56Q+` z^Eo69)(7(HIdmDr*4--~S$H`)Q9*}{tLNa#jq>!le`~i0mM|O3#nROd#kK)?j$%#> z#&c_*$)UiWY5_Xv>U^c+sA8J+a&>VUnEBVs$0N@sxs<2dPBJBEjOD89+Sx<9_lkwB z=$3x3LnK>T^|@Ie=z6$}@aGTYsQnpg3*klw&)h-*a$&ZcKAlG{GuK304^2f?F8;T^12pEHV>KS3SMZP7! z$}yQ9LLRX^bBwbyu?Sc||z4#@@7BkHHq^-7xtznyxpa{z%cRkt9wwFBcs(XH1 z*`!j?G&`Q#V-7Y1y|Ip;Rx$rz%h^wA0c%a32MAu%daEahvQ$(~y?btrU3DO-I6i>( z1ljO>D2>zVjPYb|y4&m^LA0pyGF^=zv-%*;vM_o{i{2IG25cLjb>BXpspd_VUSK0b!_e=^@5T70gTP8U(C}1PMbA`aVbzeII3X;qsOvszlcO*So9Wiu zcBIOIB^vxJbyL?9(X`hUGp_4KN?FKWfM22>s)*S=HZVcWft&aPukoaknm25*!>iCL z<3n-xtm-4ha4bIs=j}Xzx~ubub;#TO%&*y=lS`gCvKgR$^JM(914ULIomo^x-!qF-Tk zDO!YR1UZuo9heV8F-v$mH4vppcf49PP1!oN?J=W%*tuf6@<`{aGsSEQLz~w8cmy5kR{_p&=GSZ+U1wCAe?8qGr7$Pc6UmDjNroya%a*l!oEQ9{R1&a zC~f%O+U#RdAg&AOJ0g23bdRR<&NOh$?ryV@Cogfp*ukYgoGZC1@QNL=3+}$?edmVC zC4zM^fiO=L>*c+JbGzLG%Y)`6wAK1K(PQms$~y6-#U)hdcbOUs@@-1W z?AT9(C%!i!Q~%H%(jy*EYEEEPsBDj_V$qFAbeB%{_xqjBr6y6fM$S@T)kgp;9B}Ir zmt%x-wX&RvsSzPfGQIE*BFUPD&`2nW&^&pw4sNd zolo|-H~o4Vngjb=6}f!a(RhHix|R(2i^q*Cw?O{JFzo92cA(+YZEh-dxDlwd^&>sp zN|?R&D@EdtmBS$Z9vW#U;*aZ6Ep5~89Bdh><)s;68Dcg!J@z`<)Vc&SCr)_-<0!0i z=o2oTY@zS2152ywI;P+FL|baPzDtzf3HZ?)uyYB0H7JL(43>D$9IhS82INZFjAe z7=UF*H@|Lme z#7XT?6#VFfFx3=-1pkefu{+v?PVR~WMQ=w|3lQksBTampHTIZ;{A7PFjoU`+%~^NI zSVzus)m`qsJAA^JAumrxIM$Q+&CAcs@Nqq97>p?{5^!l4kgOIMBkVpNoJ8=0Nj;>@ zJD-Dr@;t8;*)Z7gBMb*M*9>Gz9$lo~o!~XmccO1YOQ&81z&@JRelIkcsClvb_*@Vs zm}n=DSkmV#nVfc;m#y$2+^{C#lVX`CY>Lfd?GtF?r?J@waebEF+%52KfNCV;tfLP; zoP79%tnoqI@}--pcoT#xnFYxL5a(=4?da+(u3;bk)191h?{5dFyPWNLaCPp8>}AsH%&-(q zMVkz>MS6EY41D>X`G6mtW({>GAnnO6 zc!G}F?aHMEP2no8SVwDn4G*G~U%Ikq6xuCuDHLpR{C2cfa^~r54st@Z3^cP`c7w4YxLx_iTuMnoq!`w8WN+yZ>L zSpvxDtFBDKNq1|`v-F!emg_>wSngbc$*;~4qu+>$UInUKJZ!wx-SE%3WuUTdetk6> zRQ|M8B-Yp}J6-gS6E~=@)JdSB8PSH*l#Gu_upTLErWBbN1u844P-UTNac)NZ+ z@$PvrTcAvAOfDI}cZ*m%9u`LoIRbsSgq#u4d)H?bAt4xnin5A`YP>I$3@|cT0FWXd z0`>t(8jMIP)FaU&lTebZ08BI?qAIF1bX_$K6=O+_8aieg7k+gq&t^kzvXO{g>#l@c^`lZ+x;7@C@T8!I}J5^VLMYd zqe}XpEHy+wNqiPwM^jVdZ}+FC2M!KSW}tth(1eYJj)m%GHn5S>vvPAdzn@nhP|n6D z)J~|6mF63wO;9l|76g%y^!FQ^XwE^UP>YAtL`@EB$;BgJBIRfxvrv+9dh=6^(hM^P z2h*e*j*X0j)0jUmt%weoYKTF}pcze;wWbRjuVtvd6a!QSjCqD7fQd0wHuTUg1`^mMBKzHvmkKIF{e^mOUD`W#gG;Ywrs^=x8f z_3HHN3(~Y@~aSxi%Uhs|r?Pyg6U_1%_HO|zJu?|sHWogi8Vsv401wOcT!&&i8F3l zx$8q!nSz%bNliS{=;`Ov8}JB7 z*}a^f$5T&d6KCBP+t&}oBN8YK4i}J%s3EB-bsC7gjnijRFJBbh2EmkKeuS zPcOHW!^TZd$UteOV)fj-_3v*Vcw(oAuC0sT3pe?+P@9lWPC`+4Fq3vNu@}=(n;eXe zR|nRQ`-7DwPf|7l3ef_o#YUM1g;e^7q$Fj@Va8;_$*HHHqGV;Yz6TFBlQGsg>JQe= zCcd8c3rqgkvmZAb1Z&Y}ZV^5Jt3&IbU=mp(rlMw{732GW70oI}Rv|JnHlCUs8OcsE zm86LpA8#b45itDu6~3c^&0EFE&QZwKJdK`rdQNsbwiMtjR#??!6M;Ur_&q4tc^TIN?Nzh=y!58Lp!gkD#60!myDV zqQYR|-N>%*=Kflr+3s2&5WYfhb^{Ga_8({u9BwZUUp0!9j)<@lu1QOqtF^x~7u=If zG3pP*L^7e)X{G2OqNb*ABr0aJ=o$S*9D!;?OiMNiy7D_QHV{ zcDI%Rb#-zxNz`?WoMcAcnsP^Z_ucY#{{gT$3Dr&S7fB=>EVkR}2-F++5NqD9cfUJg zwCK+6kKLprRJVQ8GqfCwpPR|=O81nr2PkJIrU~9%$H~v|OAKtxW|JXZ zPb=-q;%6LpL0wL?PjB%xHCM-`OGgQCnY_4+4su= z6JaoGpu$s4S3a&qSLKB8xL8`&4aRCd+Abx((8mJ%;JrOh9mfiWuV)`7k2k&El8REb zr#fF$_huIAY~FvT(zIBA1Xboo#lVBZcD|La4WMa0U#@(J_iag-xP##yyY9Ze5i4Sn zYA&4pwwI=q!G$JKPS= zt!N+NI{6%LY_%)eZ;k4f0ovPW0aKboRKlbjyzhl;Xs|a3tW&A(C&4K$>yKMiJdF$` zR(gtSUI*+p74GldUV~dFmgF5S9rt{@!RXvwuT@)?ZtTyUA1tp^mF!0*o-BQMnJ*u$ zoOijUWn|G?TWvPLIo*Z`D4t|wApSpm$Doz6593WaB+Ogl4pq{@(+k;ooW99Pu4#<{ zGoxhKna%YeO4~=oOHhu9J779AF=YrGdvsnIuSC8ruqnQK;!a+zzg*t7Jv3!`Y_+iF zICa>++urXTWzKeg~!buT$yAK_k{096Fn;hDRiO$X<^YxHLHE@5|i9z_L%*FC-Mja@!q z9rJds8mF|azg!$i?lfHW5fFh;DK1zNHpU*|+d?S=>cb--ib2(lRRDeqI@3Oj_}78?;i(MNh~U>A7$uFGB$KGdG$ z%2(n&#I}vt+mk*4Kk>8#Pz8X7b&{#3xl}bmJw=H0sV}j-PEYuE?X2J78DUDr?gokr zFnxWYXU3RJP|S4`oseJEj;K_Lb&83ysk+?iuAq zR}ZVbT~J4iMlWO1B$J@_TNR}S%A$_2Hgrjv=;6z=43CVmw7Q|%Cz}6SYcO@p87XSe zQz(WbIG;TOzixr1;LwlV4c`&*2S0mnoo%fNA1OXYA|Vw9yJq40R2-vTc(NK}yT`aF z6GoK_;u*R<#uJkTH_8PqzFYIMV;}2XyT@yhDN|;e6yS_^AawSMDiv)q+wT-5FIoAs)Vbsa(Rk4!x6yu z-f1!)qVEAXRmx1irMJbj`~0H%V}1;Zw;-UO+}{U$#R&=?Zv!@5AnhA*=i#tz@1=9X zLp}JKPlFtAt-cIx9F5;eH)A%6@xV=<51N5aoLEO0n+{YAnv^!@|YFEF=~f{|i!ydy*_2ih%S?h7%U>S)LYI#A33xZrLIXjRG z42?XJ z9sGjMK;}=ck^#cBpRh`GDmw^^1c@^hs#Cg_Q z?YaW4rvB{YOcX2fcFnB>{U{1sC|J7!Ma5OBnU%KZ9a!gxVDE$l4G4fbj;QME`9$Xn z#WVd@MX9^(dglwn-E`Kdn$>h?1_ec;^87doeY;P9wWj0o%*HIBmDHzQIOEKS9fDhj zbw;I~^uY8vR3EY>A}dRJA$oAgzSSC?!#H^>9c3)CJ1{(r#3H2rsRdZ3nA{~*{j_-5 zdDi=5>Vo*U?plHLD;<nIx zSq&RE>9!Ze1McnycTihMb@B_njLm_3?3yTvweqO*N1myYy_4}jcKl78RTU6X(-8kRarO^i^KUjN6vIEA8-Ign8UAUK5HYiNa1=Dv zx5s1rBza2d|3~33UguxXU1qvZ*T#PkI{&2w`J>$U7oqbHhWG!8S=(dXhxbkB%5wlG zLGa5xI==Exf~RSg(ggVK>c&`eJ`2z5Ews=C3GQ>hG&edbUYDyZ7s$sX{}cM2<91@L zUI}ph?h&`edc7?1m!IZ<#kd=ohqZXy%h&IG65!okjI~6o+t+|T-=QB~al-cA{(W!j zs)f3SuRZ8qAU%m75r&>YQ|u9<^49RD?p5=IuTif5Qm_1brvG9>|L2YJPru5) zQLbz(f5^0Ee`F?~pO&9K6CvZjSjnF^+&^tJuD~5B9*#;2D1%)NSL@=wu@HD)>FEqZ zzlwkP646eihu9+*32X;WPQ)irEwo8XPMlgK@GWRoK|&E~ULk@8D{fbeI#yV-+E<}w z76SFBaJ_;#m|3#G?3E`YB~6{m$JwpS<<;fe#oh8lro$DtI-8F?`)VEr&9ihBMFuqX z$eG&-i`Pvr-?$AYs%^0Hc$PZKU4qKo(D=$2g@O02j?NwB*chPSQ)}-xWfHPMC;G6( z)M#mtq@g#%8KK>M=E;rgt;4T3Wn;;`w>_A*ZbD<_gPYr^#T?EqE*w^Tl`bvB3!NAJ z)$n!~oQwLGY*-XG(QxnzboJ*J_&yD|#_lQ=tO5dfGrr!JuoUz<-sQWMb)BQ4BAA!{ z0^-u`d!(|mikpzxfTav)?J8NW{Vj>5s#}(B4xP8(?uT?WW=kd}h^h@jmh(6=$dD@l zUPLLVRilgm5?CZU@PHXiZFHFt9#f8O?#zBTDSm#flh9ffV-EfA)`GH*hNm?eta{yO z$XHAlQliZDKMM1R+C!sKr;1+s%NmBj$9sg<7k&`!WmF_0OIa;=QAl*=>UEvK;KtYG z7g^=%4U}WviL!7m3<@G??ICHG=Uxo65Kzrfv4kxRSnQhY78~S0;@*@#hPev2Q+ZRp zYrcxTrnri~7Q4#7#x`B<;@0wZzoY`g;||v~MnKnYAx%a2plzXikYpoGh5MjPh58_T zP`!)4=DTWmLT?Fxdw4*nogcxP*-YQ>Jk-h#nk6k6cah+r#q5w-yvf{`?aJSTK58Dk zW3F_e!biaF^56JAQr@84r0jaPN4}&ky{9gD#=mI}2qV+tr^S(RjFkcQiO=`qACT=v zxXe}TZlKp?E(Z*4MOhqvTJ5F(a?O(ZEu6HLkE0`3iNH05!!1<69kZb(HDyj?=CO)x z(<7qg-dJoRFXWMO`l{tA@|w1~9)=(Jxul(&_4%>sBDR8KW5X#@J@4FL;^25=xUd!; zSMSrGW+z{@%By6fY4pLjZn;F?8N)dut|YeME=5>sT&}wy$GwVesKd0}%a?yRH*TVdn-nJa(Cn%68>y zMA6pXA!(cW_t1s=XXss;_hfbjsl{#R_%Aee&1_Ow6mSR-d)5Gt;&c98K09C6wq;yU z^`e~f&Rr{m%G7|FNWj=7;XSI2Fm0toOxfgQN`p4Q_=2j2RKe7QAgeu%a#L8&9SDB< zGVgYy&}g_*TnZOm6Jmo2N_*iUief?doNDu%3B^zu5^uNqcz!~C^l>-ol%VMEWqh2v zbjq~@m#M?l(VQ6c)nZC@2@iU4OVUP^wa_pFkV`!`UL8Vi@@J8mIx7xOQO(uls9V~D zjTD6n5s&htmMD|JBm8VgI)LQ`M;+daB>Q#YuUnrBBG43D5Wy!F&ArHNm3+Uomm;jFWb& zmV?S$c*yPvH&7;yq^0Z7lZk1EMXGxn5q+-VnpKLMMDvV&DDMgb_bnddKpM=O2!>JK&lV&E6U8t&A7&cYx5l)*j(V`HFR|{-&QkGJKdHtGW zVx-Yhu}dSFaX8JpNwzU5X9f1w&JB?hWt(86BjmrPx`nUe&6vF2)Ze*_W&#ugz#T$- z*ecV2-$4P@yeqmR-oyf>?PWp}4w(Vd##J@Wx1;p8f z{X#t??T+8&3OIPV<5O^D;K4z`;sgishVx#3>9LI~Txc>F4>}LwjIpP&H(m9)N|d8S z^Xs^O*=gliJA9M_&?#uErsxd4gucjQnG=7nN4?z@KyHMM7UG{*LaU?KVF)-;8HNFX zr>NSkz(-TSNMj^$d#f+hv)A3|dWdtS{SQgnzZ?t<^bG$_!~a$HCw2LM&cYQ$#3khf zDaDK}osAvM4E6t!$^D(#K{5PO?eMo+LR#NY!NyA8`tO?mNXb7*`TtJI>Hl!^|IW!- z*`WS72LAqI{7m5gZ2zeF^NoS^&m@?cS^jSu)Sotg`Z2RH{d@aUX88p9|JgqMe4kkU zze=BC0@lxQ|CB%5)BV-!uik&vK>efjKYRXZ`_F#=III8q|KCUb=NbOvTc+4HB@e_7G|%Pa9;qy2Z_{xc>2 zAAR?hetpFiuae;O9pnd$MUnb}-EK7MMR*kAGE*;juCQhi!q0=~LJ6w{79ib@~t6!spO`mT7;l z<^HPp*J9+KYdOY$$SMB0wELU@3+w0g`oHJso-Urs!uOBk>(B00Zp^e*1+24Tcqy?W zNizP9U$M!9$*AGgxSdbBeL|Xb+zJ(mxq%SBW)`KsH z@!H8J_pvDmh$A)fT@PtmIt~QIm6QIF^J8dT>VviA;tTFw7qXQ}-g5&y-N-iYnb-P&g{{fgJRQj@gc<fr9TXL) zCTOofE`04!NCbQ`B1n}PDh%O{5|o7>WKb86X@&>h?@TXRICpyNlL2kHUmP1NA79wT|Sx1YpqV**R6|!o6n0}tH-|3nSSeGa+k6)azF#ZxCC*#oOUYo0hv_ zvZ;$#Ohu>!_jr)Fv9W3OUqGv28sB2z_&9?H^DmB>xuA_asLTa%4RA+6HpYH9Gkxm_ z63(i$x%+E_qa!g%%eY+{>*hFx8d?%BdNPZv5$^{1RO$M7vApkmmqy z|3e|y8f`V|{)cWp@1BR9=27Hi(WDE954_|;7?&xVXUY!Ct4C3g_C`zDU7HL#8-k$O z^?aBqqdVf|7RXjzu149l<$5UV9<>m`Lp+N!%2DiIcZiY_=#~Z(d<7U>rqI#!)(r2> zL;uM4G?BxkN&m?Yehelc5pmI3-}LP^@J>v9sbcyV2U}gPFSLCz+tiQT@ggGe9QJ4} z8J=S>fI)_cw1;KR6~lFKYtE`TpJT2Kx6V7zeLfvWPL0syzGEGMtK6|;D8RN34%T2{ zGe}H`4dbS`%x=dc5xW1>uFEj~EAcyqPfQhJv}ssWL4rta8Wss{TvKY=IO?JNq2wV% zBdch0$2zO0+M`l7RaL^)Db>ZR*O6?lfiQAl+E2cKnJ-L`BAmEXGu(9Hgx6Mn>YO1u z{8i*zRW%S!xjDYjUo&bjk9PR4u_JBz=B}k)*?7RV&`>nIiRci7gr)lVxs2G-qz>Z& zx4>qA_*AAMUdCWEzpJwGka6Whim@8h#lgkuw`p)^nl{kRmu1j%`g^O&z_SV1LlL`) zbq;G##vqTBmss6NoBf!ZtvesE1~$1=QcK?zH`vAVDt+pYSA9Duxtx$oK1EyN?8wGm z%kzPRX?Hbk#T$+7B~RottRX5Bb1}H`V6>Sky@pG^vCntxsaDsX=pDX#eW5glTdzgG zFrkc1Sp%XipTj3} zB}`&o?RX@gGTHR=+NfMEb_}`(#03O};BUW0xI%6*Gv0!Fr)fCw9e=(g2NC036j>Oh z1{Kx`HC^T!21d}FL|^RFahOszqJlhDYhf=^YEZC<=UK+m&)1?yOI1|Au1*gHmXSzX zVKdZMmNJlkFAp)aHC4mrB4jiKP)>(kF3G@3cXVkBB#_Q77SuRZj2AqsFvM++C2pR6 zRc_=+_S}0#@7OF|wN*5sgjAI^SJT~~kZ#9Km7EDf&Zq~j2JQp3)vPV;tVF3gCGekR zgC;B7C$SW8-7V)UqfkOfukl_K(xbspaT%v>K{;3p51z+%5T^kf8D~4u(!mIv$r(RS zSP5AyhyQ-uEvDvP6W;K<}nsplmi@WPHqwx}{Z>)AI2lPo}72os1-PwG0-3?_^$=SBP zLzRC3m;dgU8_KcaX83vb6_@4R*OWBt7}KH*pEhf**Qy>T*C>Pfy&QX8~||g z)e62-g^B*b;!>Y_3o98|c*=yM^GqfL(@_z>kM}Okb{kV4_32Vo@dK6)8dPJpb{CHs zcT&@r&1m@tP=zHwXCc`EKcVJt0 zMhS8o<#udud_wz(y8`>TeGoz zyVKJZ+Sjy^`wJBg9yr}59}DN%XJ|*i$=3C;>*zZ4&-jFXs|ZjbqHiH=T+b=C&6j9) z&F|oapDkdfwPe{nUtr-R#Vd{h-0SPo7e79l4RAb=#(ETY$4mSZ`L;d3T74<`@*UC@ z+JiJ6Xwqq+MeYHp1nB!0y4$hnZYFs51%5BZLqKsLdj zw~Pi`Cr+>uQWh4qg~H(621`M%m|RdL*v~+Kl-<4E;vU9iFPs6L{%Ai0LJuc@(8fj{ZAX>AXGg^YR0UKmIxZ&zf z*dTiLBE=T{L`f-$S2k2?Q#zWr{_QE921q_kT`cLyEnCF=eerAq`$NBQhte?X#!1m; zPU23MRNGMt+vP`F^m6U?d{v>c;c z8ING`HbtOFVU9nio!rs>VTOMZ86Q|%&D$z&Go$KrV_iU{K=xOFXFgZ9)Gm*&+ZpxG za+0KhOWS7U;v1S&Gs;ck6Jj+E&?uUWH{2ffzRU}O&C*}LdQu>qnt5GZ+PCPNOY?3u zm2|Q*0>Zj8BH`MI6NB>OObfczluYsWaK|dq)0^CGicaSZ+5lQ7W|yE(7a=@JKD0hJ zOQQQ%G&DJP!+tYOJIlDNh8$bpl|i`Sa)3$YUMGck8IQC6gI{uQ=g5KYTX95WPz$=l11 z^?F9Q{Jxh3J4Qnr%iCEm{4S8EPxS5&gSY1U0W2O>i++9>8xa(#HE^^2Q{#C)V$eqZ zJ~w(DOL7_&E6gWx!3cArM=w+v!CC}udo|Rk$1E}(^!Y}~{cV0bG5E{K4Nc<=C-T9X z0QFU;2QVV1<7MHbtQve1HqlrBs#r8LRwb$x82F?j-tqXrIG0Jypz0noOO`|D7Qz+Z z0rr7yOlL$P4w*PwkG_i#${~Ss2O~J6dGrnuf`$l=23!SoF!dLxlvN}_5>%-4h~9cR z9!fmri|UL>5J>PJ2#PTT4%1qur~CpV{YFm9cj#s({WD_+yu-J*X$R8HdT*U=G3T3^ z+Ama1ZyEWw8Mh`M#2*J`bIrf(p({IYCuCihjkPFz@O<7+N?DJW>5TBcJ^8MEp`>(F z>c3#qovkg;H4du4QdlZE&Ykr7M(cOr_|(+B>c81cwuQ`)<>4l3w5NVJ^gH?4OZ8IE zTj`S6FY>W@NRDBZ6qd%QY-MKM@(R0?xHHKW7GbWRzH+6qu(B}wNDE715PUJ;1q>_( z`gSsNOHZt^1e!{#yNfKf9CnisdF_b!EI%0KeRn@GUCzHHg)@@ZQA_B+_@?$2E}?~J z?VPMfE<;j6N-oz9YK^;G5|c%k3E&0uvmAsjWdVJGo@zB0=p7>p%EzxE=+ItEO-XH< z5K#iv75~eHUiJzA#TE2$2Z*ZRz0BLoSvW>tGbO7$teP}6T$t^CZz-ZIN0YV1wKQW! zSCTty;_e8R>^qOg${{SMN|v>|==;rxN%A}s4AnR`_gQRjik2F$wKc@?kVAY|jCCzmirzrcCs8Xc&Gn zf`c!1b}Vo3y1ofaof?p{vEU9g3Gftw+`3xiAVVvLYB^B$jvW>Ga8uvvm?T{^8k8p+ z?-dEleXeDo6s+yHz>RQ$<@X8bRkhz?QBzz^OIVGr1oy!_&`qrM%EHZtv)Ie`C%P64 zrD*GfA8*BE&h73#PyQD!yt9Ef*1=!Ganm*08 z&3{2b_%v&whA1n;DX0Au+QFc!G?G@~Xd8bF2mVze9wglZl4%1nphqA(2KHF-2!1<# z|F9V_zuo$%%@8uw#DG~P?JDK{`Ph}b@R3O_V|q_%cJi#ngvDEdkfs&7RhqTFN4Q3o zZ@qbdPS>zyP3rGp-xUJ92*C?7pw9=+n=WxWHZ3mA^j7@4-Kr*uklT*(cKPh3>FD=( z9Wz0x=j3rhRytjuo~0D&fzthq5>wq%JxELPQs-iniFzNqjrve!eeZmwN;2j2crgV% z5s`mT;$tfP{yui>IM;#$k$hC-7OgNb>KnU%RKr3ENm4AdcW68t%FQXm6r-8cVL{V^ zytP3|>o7d7TK!bIK11*kgD|xrf9m0IvRG_RjMB$NNgJu=e>-L~T-9}3#1Im|!D}qI zzPBACG{gUMpN7>rRGj#&{AMOkArT$cQ+p{2C?WkbS;D zDl7g>tRjp&GAxA(o9_IQctu7IN&9vhnCb_N1lhiAKN8(C!jv!wxGs#SB{}_m4PV6Q z7XW$}{r5h752oOD09lC?St|(X7hj2PC@wh1+6`0?4=9aC6X(GAxRH`$6XBd|7Rr*N zbjG2`JRZs>Y{ds0UUL=9#nF$q^jGy9W7q9)h~z5^%au2vPcE@)^f)@uF&t%LXM!a7ney781HzQu47Lr$e?5l?r!0>%w;w7C(%)U>aMs+v;8Y6+OAkz3M0k z7r#>ey25HQwQhi_mm(|2T!vHU?QE;n5{=zN%dOoa(DE)C{EIh(X_Or<(lMrxNJ<+sQ#d*&e2;HyZQ3GMWz#RigUl2#TA zt4rsUN|AA-K6k{)IpkC+bS=La2V|pTF?u2sm7Hm`;>j`8h=km?&vz5rM5VnAo+ts^ zCSFT%-&QKwX~f2Ezl=MJm`v3V#s{SSpF+D?fmKC%ca#iht!pT-3Y>UZ`=ypwiC(pZL`6ll(PLgFa6LXrwG@F?j#oCO*H7T%KNySX6U@R<4x5%SOw^ z68!KE-rWWeTky!D1wb49@|MUZXv!6?JPOW^t7|?lW5inassmOJBS$_ie*4%PZ)HiG zOV&Mxjfsyuy>BEiz57uqc2e)oM>+dGo%p;jD?C_kxxa6+L~&QHnHJizC*khD%Jt`~ z$1|m;O_u9-8#6J&-~%&$QRAvt4~9);k2Y~d?In-yOFf#0>80A~u0nR(N9=Ftft(_b z)=#?;6-5_=K2_GS2Js=xz~0v~lwz$E4?%qI=7_A*%Ya&|4)J=_AinEea5Lia?vUOj zv9ap2>3)q8)~&uv6(DvFm0-c*>p}tHidd)cYZh8q)_bZxi=oJ;vE+hdZSd;=);rR^ z(4$u6Ozj1Q*xw0(-{Kf#R}jW7H3ZOEpeIMi(>Z#=NDd7-IQD;cibCx3rN<_YStkIn z2d{HUK)@tK*PbJ$=PLZNlz0%EkXhB7-<26!TKQX*EbskrK-X$o4qA>`d? zL*qgbqjX|}=XW`{Ktb)+mM=~NPMww8(qn$oBf8=s$rt(yM16s?>82x8Y2dI7HdKj* z4ged%fE_BCr<&4-?SUcS;kO+69S_y$>6(ibOS(6Nk$2gHKZEifZP&H!j|5O0+ovk~w zO!kVyC90-e3Me-L_7vBmniw}E6%VO*e2|t?Fmarto%Z(w?0?C0a4kMrZW3@d4Cucwf0?MbRb z#7XXMiLJs5GaTh6#&T8eNf8MWjGQqzDxbVLNKW`j%fW&RRcW)THw-R2J=;T%-`Kt| zZ9*Ge8s$bZhbjL};6D(S=@7qH zFbE|mh`DJY}@MC^KN0Tx}^dDe7R`up328mUa2K!m{j?m#wjniPDZ- zdAo@46g^UYldQ$215dX?rz-r)le|F3;~FJM{5+2#FIlhQ|Cm;wbg;;1@V&+H*}0q@ zXWib5Z?r(W^D8tZr@qhFSYnH0e+9{PHQ6>Q%gZW&^J5&=6oN+}J+GxNx_LX1Z6;Bkd}^TC%>MlVG=T zteD=aj{`EM8PjUQTC=T{LjwgOr`Dq(#6*H8j3uJDiw2J+Pqud>JuVZe$J;!c68$3K@G84R9GNYF|w=}Z22(;Cl&7x4l7 zR6F^{iRO6r5EkJBURk;W2Kd%PtLN{at4E znvzx{GU62iG*OKaYfCv*bQz~_fxgKp{0U%^HGmb$7Ivn0umxGSm>ruXp9GsJPjuFH zF?V~D%4q!u?UOMcuiwtOF{AJcD7^fdux>fx3O!O6Qg;Ryh>V&R6?K!HcAWp!GznX-By;jIaHQc=Mc%HMjK!;b*hb&G0%!8zus0@8^Ps?gzQs&`TJ%iGn&^B^11=*l% ziS~RV%4}Y1KZ45u19cK!MDai&hCZ(S`Ba!;ZW91GN(%V>gvCv9K2ZiEc3UP}g0yI9 z2?=%xGaK}(00lBn9R$aP99d`SObHp-Y2$nOchg`&J54hlLX43?CaYD#Ad&X4Q21Sr zkPX?X8g=zj@^HF)NbVx7G~WAV-~UzEbw)L{bz4B`B~-y1fe3=`{fyemR-PCOx=(CRdv|^8Ba{%nJs8{_JXDi(JbW<%8;)S~ z|6Zf2shE{+23~8$Pbdaom7%>hsMC9i0X5Y5ps&|%ca*&Kv)QF^Tgy1xP?gf4fvhrxJ%&*!ke$5kZUi-{Npa= zh3bU0+2Kd!H~g|rZFr7JxE+4()ZnE~4@}wT^m1ZQazj?;Uex#V?8A%98)u>zV-gvP7Ihet7z0$!Ul-|r9dR1tG z^zEV*lW*`Njz9&0f=S0GW=VOgy34MyN|sf(bZ%blFHXx-JAQf+?o$6?`h@J06yMt9N-%FM1W$9~We)#N?h~5YfJ@ zIq07wz?m5%XWi(rc;iRui=%$tC#SgD-Rs>yZl$Q1{$(LLzDu1*&p#bk-haigJL=Zi zs)x~IwzZS5iri;Ei6p(ne`-+%lnwY*7JNZnA}e{%ErvR`1Xoo(^&tgho=nGBId4WM zSg6j{Jh_-%IUYj@6ufTlsPZhe>B4gE^SnB-z}TS2L7F7+P4*b8ON)Ocep_Wb0;j6L z&?yq#X)e&`I~j$;lgnkS3MCsu^7NQmmTW$ve%HAKS1XI#!_#I(JZ;9Dc~V|?wRCA?Oed4Cb|oW@}mbF-eV?vF}%q z>JSgB%rUoe8;MdU0rOGckgtAU)pj|(HKs39`94JM#-B<(ma3DnoWG2NT1|vWlZAco zhOCM#YdHhrh4nt?tOvgieMeC?J6g!|_kWI3@N^>{hq``V=B4}9fqRH zKEHo5PdlPN=#r-8UF$O2hw5pBCK9+-amVTQ8Q!BLuj1V-m7}^@ljijbPlg^UJF(i> zWJPvXUcu&jEgUP=D4rF*>5m>lA>>=Tg(dFvQDZa-rvV^JxfoxMXR|cd%Mp!OX$iMm zHv$q_qHFGhomaG--nbGmc(22HN$15oa^T?@12A>!eSYP@gj7c)-OXD6x4J2fg{FyP z{7F2M;^X&noRo_y+nuI2w!;Fk%aa3f+cv>Eg7d^r!{={Ek2K8LY|0!lrgRl7_*JOX z`Awg##&&$K6sSKHIDqaZRZTbd6uAD4%{&vR;nty9E;#FvQnx-=!K#|A+6To-bXvIe z8G?fzll^bBNIsCG;O>f?$in%qgEqu*~YDpDe z1Mb`_`Is&CoycZeX7hy?tpL3F*N8!J;p<7V+T$5t4@_$RS!5Z)&0S}E{7GC?TP_19 zR*Xjune%cw=fP7KaTefx?)iYjO8!#(!e?R#;9_aqjQcxO?htNJKjeh84Bbt>jtdXH zn6mx-XZuf5A{hoIf&&yBTE1#7#SWI^XE*d739AMq)_{K6G|072Uh(_^2Y2x@FTXz# z@6-Y&sOx@@J>RD7*%;p18q%IORj>S_X|`VETxGWI-35MP3Pd(7!_6b&eE;Fz6XXIR zHS9J1)5a(BWg8bNP9ETd-D>D|qZqB{jN=kXBaS3!l~demU;i zoSPfZTFw zUx==A{`4Gm>K|~#mPeHX0!9r6WzERv9Cf)S7*3h0X@ezK;$lk{i$NIGdB+q4I3(Fo zFkQK5Cz-vFDACNQ68gR?oQpG^Ult&#@U!6RhYCTL-07W%u8N zMS?jMMH?H5@1Ab8&j)=8eD@r0xSAr%O?e;JYP%so*S1qOD_hCh=B!g~kSN9XRsaH* zdng#ITLvw9Y?c_EX&_%KpY{XXfqnY;iwt+wMwwYhZTi10N7!RpPZ4Zps{DPY{zkJ^t?@Fq%zltW zq)80IO-?J+$>{jhVsYn=O&zPtkXKXTAgNG`>TQg=q=?Y6&|8PVb*jCyxQOu6xB!l_cbF(e?q%W3*e1oqN|{C3w4CXyOzAI-rUuGg zYj(cT@lXbg^P=Z_OK}69Q$rU}6%KPfLa%i~4bqJ#`J3OY^=!J23o#G+1bkv8r@Km~ zH35y+4K%Xvu`4cP;;tMW5ui5X9p1w}V{JR6jp`pHw|laGH=GL$ShXBjXz!&ca15ix zv|hO$3-C-xD167vVJ8=1P|RywFvf4}(1^mMA7LrLkE}Z|zRPkniqwose!(bO-IUu5 zv)bj@^7tXUlvTAP*5QP|f8!JYnN^FM&RFDVSflI$Qma&4OandEmEU z;^IZ*4;A5_o=!_jLd3?TX#c(OhJ?n}@#^#Hc>yXw(^I)0N^cl3jNJVCZJLy@!r5`} zQ!t@Lqqtx;P%rAXW3#KU z;!~@Ou8)}SOkMKrc$&Msjt^>h&cz^entbB4?y1AsbNp5QP5~S&LNVi7v?} z9o@@kypD&PEJDtNB-6#ysWHA`^57Z|42hvj4P})J5dbmfFl$LPv4j-S#nQ>ri_rVB z<#3K4Yucg{q*pi;ZcQhv#ij)aF%03MGpGNH-ikquVUb@8*n|pMr&nM=lk510hgR<& zdj7Ue>J4W+v4w)@tIje}-_0!Rogq&VT9Vg|@c!9LBGc!5gQ}NFgckN%O1Yn3_i{`v z<>jb{@9aj(a(6AIo_0T{y)%y@FuK@v&DRo9R|~Z7<1Cven=5|C?Q+eL0SjcnG#T)n z9RH0RKSz$AA)B*4+uSsNPKoCD1PktazS=uS?wuyf{tO<^pZ)%=U$YFT(FknF0XCEa zgRUUzDu4}zz_It7Kg|(!v7dhe7Ib9@e-i9}5sLRn#xxc*0`^-SNaIU`L3^l_2Ufwu z2`ByEfjtuYuK{<=WfOCd71qn!8Gj7~0V_aY3UClwN{8s|<^+Nu&p?!*Xlalc5#vSh z2bt=gIYr}NV|@w#hT0Rp{t9L4h4pd9UjKLGw}@3rR|N`&pui{y7z(BFwUM@9@JZVJ zujg+Kr_{gDZ(-v_klpXB_ej%wEB&I7I}_ZnpkEt24^lMs!aET!)8vgb-uf?*>?toS zhJdHp|B>bXvS~ZirHLOwN_&aXW}U-3?b&Rv%6GZ;;YnJ~RhyZBrwaf6={^ z{x`GR*9(iIQQwtlI)VRQAZ0k577qvd2ZO`mC|XK;7wFo5FbE8(Oj}?-hCrcc;rC%Q zV~?i452MYcQQZ$>C>p!{0ER#*(~fK3T$mDcPe!m0`^Vak!N5x3Kh{7(_IT|3=0f0* zy|O!qAr9^X0*CHtq4)bCP_RGZA;HK$vH#=zkWj=Q>muQZKh7D6K>g{5+|z{b&jkgB zAIupBh9VF8!N3UQ!SjQGVSD0@eer01e>`6pt@ID>jrKhDDsTT>B?OG7lsJH)PzNzu zk^o-DQ6&7J*etwqyM zoX6t{G)2QdEo5*FhX>Iz*lQ;PUC>348Un0@fP$4_ILsxCG90B0hC0C!SeoL6_QTOi gUW4ubclk$J;!U9aDgA0fI4vs#n}oz^lQV4p1H;F&zW@LL diff --git a/examples/gjf/molecular_dynamics_results/argon_potential_energy_fluctuations.pdf b/examples/gjf/molecular_dynamics_results/argon_potential_energy_fluctuations.pdf deleted file mode 100644 index 833bc8d468cfa78d993e226dd964bc2938a819cb..0000000000000000000000000000000000000000 GIT binary patch literal 0 HcmV?d00001 literal 54630 zcmagGWpo_N(k-YKGc&fBnHeoci<#A8$zo=-#j=>eVrFJ$2FqfLnb{ioobS%NGjHCS zA5~cu5g8eo71e9+>J>?;EFsCr%ES&&Ik0!VcT#+lJ2Nl@&jDlsI+$3)3kU$2<<0Fu zE|x&f57B2Jv!s=+i@DQBYisOcE@5u!U}g>!5`uSjaWXfygZBWO>5o>~j;d!JXj0T) z=gxVipHhhQK}VsA<$Cq>cm$lX;dVOp7d#|K^$g@P2jnC+EI<{rwSSSoGHIxBC8A{P>V!c%S&^VK3#?cpoKY z&80=(!TLsD;4J24`ek?916uSwm_zvD-R}M5&8H=E>FphNG{>*NAoj(^O zeaSkl`o$_6dAwCKZMom49g#Anze7TEzU{nt&m*;{^!T*MoR@Iaws^)|mc}GR~?uT&((?LHYRT;p*K2^hosc#u?9>2&>kf>@H zSWs29+;5&`LfwLE^y3B-p_;OzGSw0}yxp~(P@|@V8JCJRn0*NtHRX(&N`h5IVw**!OnNkuzwWfSyhWs!A^qGOvw+*^5oU4k1xw)ov!^I=GnA;x^FI& zd7$Oy3N@tV;M-}zGSqfEncj;#Zhq*~X_Vhfr&o6OQG(mL@|qOYmK^$W8)8pz>{q1)X@-Fu$J$&r z(t2sf&9x95$JiKa(N5tq*-*e)f>n!nEfk6Mir~Idfnqeq8%#KGbM{9UwQB~c7Z~kz zY6go?w_E2(Pa?boU9MQ_WVenmiPT79DeuiYSw_5Sh=jc+Cm1sfQTHoQU^9He4W(ZEex`O5rVFaS6dClsi$vt9S z+B&z06|k)u?!pn~$&lzuqdSc>AI?H6yN_?BgEjEpSgR}%xO;s&7`7WNM}j*=5VXRJ z$&plIq{)+dT*8tJ@|h?5cHnbL_k{+qV6UE}Wc*Qyp#Zv&^8kLe=K#ST(OgvzuXmr|yee3n%ly_*0i>)4SO77NwGC&> zl^SVqezF%XDQR1xzKWc0bR6oaKye8`BI>J-{>ROc(INqbM0=pRLmXI8d5W z-!%jM92ie~gAAvg1wc2sm=+N`wo%^C7YL9jfsifTB|N$o(bZsb*iuPQz{YNvfw(MXE=g&8sYmp4h7_xQ)HLfqV;d@`!g+-QH5X zXOlH8=|fk5YtueSw@7>j9x0S2{((UmY;-ZPop;>rLUMGewd&i-n55oudf)~ zSU#BhBvuYLur!j(eTazcrAVnTU7900o@T0p%4H2!<)k17I!BNyt>qIn|Zrp$NyfKTkUZ~>ph#F zcNfuUqhDtW@rd68;G;vz#P>O<{>$X%W6gL@1(o_Qs8kLea1sL}@%-O62GP4$?QfF| zqL@C=@*`bT-=|^e380wa;I&CqXXQd%KpwQD^FEWz1S-%d0?!J=+BhKWBbo7 zQk|a3zHLzBY@*JWAg?kvuZd*42jBLB=B|f(49K|y?B4q?v5?3`-nP>de%FzCJWE8+ zw>Iw&CH>!a_d+^QN1mXD-Ez9t-XG_wEv$W>@BWlmZx8&jd_UTJ@V^?Zmo|`eYa=5x zr-KFi;o8MCF5Y&t2HTGn5Y};8D?D$W?m*Bt%pL6(w%y)y-&3AhHGBe*&x7NOpnplT z6Lr)Ueww+}9&Ph-Iv2BM*Kt}wlu0a`e}#zgWdt$)>kTgR%xWBrbq@kXD5X;)`?*nM z$9fdMTDY-Sc8&$yXC}o71(ENe5}2gF1Jg8#L{u&?-J6M5vC##qEFaq%e25?t6y zF8PquNBQ6)G$WO4-Ko; zWTGR|Jmh5HrAP#7E0gu7F+5DO@(^*g@Licpa$Rj@RDM~$ zzam701g9{740TUTy46QJJbUP)Xh~j5fqzEX9>k@U?;2j!B#>Mf%*e&TCrcQ8pS7jJ z@2^sX{tm>!#IKZ0^$;bHp_)CcfKauBV^gO#39U%_NXH9?mrQK{-+a>8&2% zk}wLHMi&W*mmE>^qrc&e;kES`@(%;wDgB&rgJM2LczSCNmI?)t>Qa&- zhFl3jihSCYhICxy_q4)9n4DGkOcOXZy51vIVrMb}rEsDopfiq09mgntu8K?2C^MG| zgJj-5YY%v|7TLmG*Y(muZ%KRKY`uD)wDxt!b(kiNM2VdhsaSqLD>X&-_X}DFZsxh@ z3)PKYhNO#;DcS-k^YY*3WBhTMsWioR$a_S6(-iF!=1~9*$*)TY`kqXtru%9eLmNLj z*1%3gSdS`AYxY{TxK+prGcm zk>8=)RlqDc?rs*T_UBs?Hx=F9Ti+{&&K<(kq^h~8*9c%}TT*j%pv~hJ50AD&oW}XK zd9OLVyVATap|`yVnhk25E5IX(vgyS_TvW;{pINr#v?;!{E^(fVF2i?Sa}}Soxe^`Q z6oL-$X%{f8(Pt9F67a_?f^T_(HDhxFlrG{w2iLuR=s2CurP;FPak~e z>)CJ#+sRNX*dA0=GjLBc3i%z#{(MHU>(`F4?}ZgHtpO1co5iAO!U1i)DBxM0xJsGd z-<3`s%f|>3w4sE6J@@lda>aaGmk8GA!7Jlr=080!V!!#obK4csg z$hldGr$owMmd!_sMVa8n@$b2SSlRG(E?!$`pSS92O)7M#y5p9}?rL>6hXVX`=8;%t zSD}DU2gRhQF6qi)j?(R=62$MPn1WAm(K72vh{eAUhTeeE`9^i}r3*vVWIVS^`ft%w zeF{s*7yC}g#0_9|wPgxR>&+$*Micf^*rf>O5xe!$Z$>*%(YHrkG*hU+tC;i`CUY2F z@lYiRza?O)gOpP=b}mC`Im?1)`^`tUw#ybvL`rL*q2NjVuxsMz2z?BWvPA>O&>Ed* zQ)!29W)3D1g{IUhuk}fjORB**Wqo7E;_Gq07wEX|Swf*CnRdVwn(u?bD2rD@yOt)v zjLiy~=g^#(%}GrdtEJq&OS#hSMYIfUK$y^fZ}@dqcvI-ak$o~YyI4glj>Bj!&!M!c z%c(3rW*@*&xFzMfQpY=Rb{56n@*c<+^$Tg4J2@p!Re>afc0{_0D(gyZ-domx#h*lt zMyFwcuL)O)SKCAzZx5wCod~mt$XL=^zhOtQuusiTw`i$$%wsGq8agSGk06QGF1)g_ z*|%;nm*ebreGlTYTfF|TQ;b$-i@q?sz6Hey7D~TlS zK{9IG2|O#Sv0ByP&=T1U5oq&PcRZdR9|Zlk5m*}+fJ{p5bK&&DC`AJ zc$EpDdRGlSx8kp54_mLQn#ryta#HfIEE$!5hpA(b-YQ$1Q*ByMb+c9{9|wo7Y%EZC z=)g$UBoL55NX3vyUriA##ljQoHs|-QNRFkcK6F^|qhLt$7=Ar85!&Yw$_DRie&`Cv zj5GfPKJgF_-q&!3q6A2*j)46TqEg+H!$3Z9I>-WgV|)d3ka5h&=b(o+2R_H`K(#<0 z4BxC`$i*cW7G?>1acNQ>B61jGTpIilxdCOv+ztnX_}vvx?*V+HaRJ%2D4fLDA{5Q+ z203cdK9RkWVY8cWgKLuCXrM3b$Oup9Q6(PUUl*I-AE$-A(ywX6tH|}tL%NU<%w2bn zo**-@E|=ljhR_&FaO(?pGFW|e*2kO^h_Occ<6Yj+wK;2PI%0%~ytPlVSK@~(`e{OX53ea$ER zILLA*X}uV^oSvY#qs^ca62e*6?obwE;Bve>4iRXZ#LTBI(}4iw%T%YhKCM&CH&RDu z<||Fw&_SA!bHydJphA&j8F!P6t7I#?;k$$m%s)hqr;B6r%a=~aW` z`eDS9jCxLw%W(2Luy)ysMXPB{;@uXjy09$37qq3R{{0We?ye)-TevHx$bPNpoJ=8u zTn}E`F_nA1VqCqVi8-CI;TEDdYZ7I;7Zs$Z3<6rBVpzl~9Y&B^`1fsmt(nwHhEFsW zV~ZoGEJtSG%E?BtXFt;m5uGbsNIp^+m zi8C`~Rx3Q!YA}+{m`#D0UYdV9DmMm8tavYyl}0s~(bHf8L{~Jx`U0Q`_ZoO!AH2<$|GkO}N0I$*MB&GRZed9qorI2Wq6VT= zxeku6xyuiG>6LCtfzG%Oj^Em&URakXe1FG<^N&7jMX-tc>ZM$R`jAl>F@>AG1bBqU z1oa6<3HktkB7?Y~%RzRg9WzVZ>h>x^5S3>|YIQHR^`H2LU z4Sa&LSiT~Q-Av5Q_K;4?3rqqQ4tP`gsZbHn{uzUCN-jx49`W@Mpeh+q(NK~3hSi}$ z97nw!fmMTKP&^2Kt>Hyzr2cW}-|_V5WsVVlt)fe6kllf#;j32roP2oOZxWhHQ*TA5 zak<@~MT$RI4lYwP2yY!)SRhR^wr$pAg-mS%WfvVbPX=*8oZGUZX-gbs^$#x6CxOjaZFLJ@zYN{!FCN<^$F9A?* z&oE8-+$(o&&DLJ)-VR=ZvXD==Xd5AdDYe%2#=}p%&@pw!=sPwDu!C-#J_rhy$CUiRjE{7j$KaAH#f3i1ESp^x zk2I!7l}qb9PO%t0B*a7y*gTRnosy)oR=&X8Q|T^O3=aDh#c4V6T_QZJVv77(kSWCI zfCZkwPLa@5d7myqg0{&jeJ!O|)+6c1^k*-xnO|c6JeN^qf3T zLN4K7V#=~OGPAk{xC~o}@9nT8UBp8PNAYQIm^r6MW3(@ymaR9`T?AgfK@SAyh*MKP zxJ93GNJdxa@|=E_E<>iQ4i{RoTtrwZ*0VgSEQ-~y&OoWG<;^OJeOqrHyvcH@BdlQ5l~*HK=+!qSf+gwA3czJP}+Kl09`g2aQ&qe=#q3{i7c zQFq@8E~I3C9r59zbT{&@-nhx@n;3**`o;b@XPNq93CgrE9TTkXk#qbkb zMiS@WTGZG2rGtivU9Np*^uBUR@zR0pS|es=aHNsqO4*E8o(`_$SSRgoaGyDg9JGVW zYE9gSZW)W?k8~9aemL+(SHyF$`Hovk&}qbopH8?i=19tI!sE|U?V}%Qvtng7KCTOL zeSIY2##xoPb|(<01Pu!0QzWxxe<8G^(0NXt?ZKz_Jqf9)`Qfk%wlj=nUH!wM)Ld@! zx`~lrjvr_GRPU?+xPLLK#lzqZ{~^NM;iZ)j{TwiJoy$qnaLbq>`orM~Hy=nN!KR_y zGpbzZ@I!?|TlU(*(b& z!Wt|zef>pKrNx!(dQg7~(Rh^U*6kE=3ik z)s*af=66=zrZ-Sn`4Pl;Rxo^i@^tcjDx;OM0jb*M*RF8Arn@kTt_$)MyQJ`&-eo+} zwm$|=t1X`{M$Fevok1rHa6_@iRXaydKJ2I_=Nn4Q-nYe#lLt(e94hN@(dxh<9GrG0a6GGwq z5^xXF7H?Q?%O}eCk{%!8UJM6=E>f(#la+(YVgjZD{*{{LDlO+>OePciQCnJ~Rzr$H zBP*`xtC=7J;Su3g@*`aK+GLkz5+$l-;dd<}#9c@j`=)C2ys@trmRX9IEDe}inFt#d ze547%*_T`hEVLc!P|6DkijPMwfdmnaTy@kgj%__QGu&G(Lz)IJP&qGd^DsR#7@7#k z_mIu_(LUvhH9j8Q&56BlF7!S#gco>-%_e7^vkm;ac0cQVdB^$thUZyQwT$b)&e!Hp zE6})KqgIYA3=`{nw}=T1g7?1-;|0(_7eGN9`{|x_Y#HjUo10Nxj^owNSZ~IN6QNn) z3wC2eG3DuYpHDk>G2<}iDBVQ)Z>y|kw)lV|UMGc?0%j+S+S%s<;{A{Hzu-)nshCQW zu=3oRi?iCuCaWGeA( z=I9fwq%8!KgE*W){I=%u>0^{jPaH@;1%uxYAZ`%#HiM%HLlV$GVG30ViT2%BL}C8t z_6{#1b=g)fHg~%*hhBHPE@u5umsWWd8t9KlT{wxKNZI}SbK{LhB8#d(!rJ#{u( zs;qUdx;e#?uiyO<*b+Jd>nC?zVKi?rA8(~7`NtW#h2-3ctm{0=n^z_h(aWmk%GPqhaE`wlDa2Q(Tx{6Y-h|c!6ouaLV zbK@p!r2>5xd-s00Ija_L2O`GIOzqu#)~V%~+#3uB#5K(68Q>futS*_d!1=QKx$BR? zP)E7jr*enN#M40}CafYM9{l=^>e`a5fLgg|PaeUchGmhD{9wkxYEnQt^}UPheeOXc z%nDP2ZWna`J?2BiAd#8Ie#bMf-ZG>bG@`9+j6xL#-wu^t5`5(XGwE72u0ad z7BMR_Tsm>QIg*2vF&NXt9|k6I84S@RLe<&~TEN7>Q93s_)8_)j*8Uh1bUK;k?9y$8 z4{EWD(Tt843n+;jZj3TD?(8XgMq~Mwea-CNn07w%9@CD+6}QZ-_@@b5PP_9BlArc~3YUb%!I zbrBq)u;=v@L|Hs{mL*)b$F2}rpO61aF!O;!M&k_N0(W=j4}jBaO)3GAi)UvJp=}*c zkN8DCcoU=>cbo3=O#Wkc=k1``9Iw=!4Ef#-vZ zjV{0DjcI{#!294b?kjKlOZBYxpJO=`B{1e8jf*Ij$0FMbpFiiFFBe)me4zdBmd0@8=G1^fYR0?>(Sj=emaC-q?JRvUM7loEw{@Y!r616tz-O z<@_s_o?CU+OdGK=4Sm-N8jINGKlH=4o!YGa3!?H2#f?80(%80Dx>2cKj>VYL1ie&W zD8yaMNxtL=rOWo4c-E12_oGf;x^wP`-&<_zk4XCbGG~9&LONqjcjF3Zk%jT{_Zorw zsmf7s?E7>CH814iRl5_*emOFU198b2*6bSr6dvxur0w|GMETlOP1TcoBO;WX%qdqlk9B-~sUP#bCATY!cO4&7_ zwx?>`M*dKYGU|z~&lJwL?wX;V0)<6OETvsQ?w*q;nE^E>C&oOk6gHNUM~n7X0+iF* zT(ugUX#6dGnx3L&7kEcS;sFi=-kU74l&H~jQZ3(}rbZ-*(WB!}fTTtw1fqsYNirbY z%fvAa2DgGdhYN*;LkPO`NULt(b%duEm58{w5QOJz9uU4Dp8IuU1un3pf|{EB zLnrTnuV0xyEc8gbE=1Hy6vviwi-NqPFtLkLHxNOf2LgtF8++TFyk%63N$V3ewr5y; zv=Ia5Hr}d!mQ_taySA3a=TWd&BC8F&ZS_cGP9KlccCrp!gWe2x@(wt^fgmW{*{tm<%fy|YfAz~RkCN|^Sa=vLVyedX`* zZAT)zl>aswl-}tyYJk3XF-;CLH$SO+ACd*j@11VhBYp-n-tA(VCj1Ecvu<4y_Xb`h z&l0$myEJVJFz|(!@-g6i729cqPzU_7nWHHr%Nf7tB&lN1y)Ssa-h?YBf+mOvL!&2D zU}2nL+}2@Jx6}AC-Jz3nsVvc7enL%5M&_jmiKGoM8Idz7v4JnN2dJ21S@+RtWkv^- zD(0tDkYoC>*dN1_wh~R($2ejJrU(fDa1^?taxggH!tfLbUYJf3Tv+9B>v*z3kuwtm z(yvv;VevIFA?$cqg%uyS>&c+_lH)xJ@v0zg4E>k zWnYdpgWx|6om`bce@qM|*-1OPTP^JqqP}?s@<5mH4GvOuL%j{A?;j<=hs{%7c=rzu z)oydrNmL z)0NDholvpk?XIE_`cS7Gao}kl7QcE(&bzeQ&h2Ecpia*)mVdo!yDzZ4-EA<$Aa4MY8pzy zk`B1TFO2u<;A^@g$NQuYXGJMoVA&H}7=RFh`_+CjKTJ1mZJ&o{9WQH}oACz-d0P9% zM~{wKW-bZ?Z?MH@f+YoTqG{mp1O2Iyh(3X{9`splsgn<(QOZEf;IlYODhs8AMJ5h0 zW!n&{pmTsjFypJB?_PrPBfE&z`%&ZWXgfTB=f#@={!8m}8%9h%+A`qg17pLhXHZ|I7{7TF(qOb8QEn z`1FgdFuM4|BQ)~#u*sok*4f{4#@YI|PL5YLAr{yNC_(3=tf8S5MPBV(4-(yRyDoJnL{ zS44wWZq)$6gf=J=8ulIocMAM<8MQU(nIQ5N%gVDL`FtROzyQfbVhTt3%CzWFIBNPH zI|pkHso6Eyh1^u+8t~;2_Q~={js!@OUc|oq@>@I-O+m;9v_VI5CLQ@Yv~qKHye2A&SF|S&Co_`0(b#ChSC_u5`&AumMUkkk;VV1B2l8&1HwG~p%~aOn}9wBM?1!(f!@ z5R^3TE7xC7K=l(V2%&4K9fNa70KW+qZ?l)_P$%=Ih_VsG*XTtzzlPQzm6KXqW{kvZ zvXGvE<)w#HkAP2LLMR`(LJAWfD#Am);E&ajk#d$MjCC=yhn^=zvn}dBRS?67$5k&D zq$r45mY~uSd(DMI$yB5{v)41bSrern9-a=vVIgG;`IP>pH;`i^iq6bLkbE>QZO=k) zphvn4Mi)~kntRgdD?-kGdqSYnW*q$=aG&(Hteis5R90XXkO{N{#rxNEfZ- zZFdPeNQn+OsKV$DjualkpgW@VF{Zq9R?EY#8c-D95I5ogj#uD?hjS4e+57w+mqfwE zgT0xbuQ`5yRy`ItBbMDgqM`kk%emO^FN-gB!8 zVlkoDT?zabebfNfa-K_IuwiVoYFiH)WH^iVSd2!@SZ4(^mqs%a;4VF)}H^R&Ely{LnzE5dGf`TvSe7NMrKw@rePEfx3`8`Dn1s z#}V^l`xGT&y&0seP5xBUDmx#6>cLr#+e-?xfZ3Zc6Ad#(kx^5skcBS_v&Y0w7^j;{ ziR~LeI9_}?EnU9t&wn=U5tk&HuHW1Bv5ro8?bf(IfDPCUSYAu z1{}O%zmZ{z9oq4Q(9<5Bc2|^K)`SqC@$qAS<=Iepm8-&O`*F*SpUO{qp@mQlfMl~W zLn=Tsa-EGx$VHo$DWHrYh}QeU7b(d43x|Vi;G*Q}xC=e)a1yP=v%k7A_-X>sgKOkU zgdW?72&sEd^ai?az9SI^-GH_DVi8SG{UPd}nnV=fe~Aq`6b9Jmh>)(}cMDphaJ;^* zx`WY;*7bLO_=yg#51KS&E~_83nU(JT9o~gU_()$fvK}k!+ourps+_oa4G|iJ1MV6- z9fG(}O}&xYxlk#Lfv#|tp0nr|=FD+)@bP)A1WDgM1su)Wd%07%7z_HsY0UzrdwU~i zYr5sv;3KPB^~_#$*NnN)EH)b2_v8tBWUwBB`^@M!w0$tRTSV|sDv*tTh>h_u%)M>p zC|;R9uw(sRweqYk$GY<1bj{k^263|LrF5wV#SJg=q4L1mE|&M2X&yISn2+b2!KQk1 zAU3l61xuLrq77+e|9+MEwbcI3l#_Bl4e4o1@Omo8dLW#~zJ}hvEPnk7WAaw*gFH+j zx0&=2zRhO*ROPxGwtQ}b0E6z?ltUL>XZ3K4C>COg%${9(h?mH52lG7zh!_AM-;b{{ z-w%+%xOCTBGsvb+z=G-f3HiExH`V|>dviD@O*kDrx0lI{)qeNO{;luf&(fKq z#fE-QU%9!cp6_rv;E`6qxswg5GTgCN`h_)6q*)*`zksv7lo`;t)%38`J33XJTs0l- zIru;9`FH;*-+Vjo?tY8SV@^%eysPiI69mr`>fOn7n0I6IzhUlvTXuMV;qJEcg&nd) zn}7Qg=N_HG^yLH@G4t&k_~f_N?TEnK0f#Rd2PAB-qdD*TCvsM}nbYL7zudcQY1ykZ zBSlHivrJj+MCqCF;iyUr_vcUcI0Yszd*T zCA;5Za4?B{@eV0>{leUc&x{jW0(c7h>#DgLZB#I>1jAk{H#2Uj%;jsCQh7gb9NF{INqX4HqHx(k-ZwXfxld z8d09RFn_B)bW0Nqr3LwwJR}!wubIIJLs$a-YsFOS)@`&6fEG;oR+3jM00fi*41tXv zNP*Q6>|EeL`q@MDVD~v}EuWmVE#{Dr!?FwXo{W)0N_LU*3w!Q1sYh4jE=F8^g{u~c* zrkCh-9q%}X3+p8zmAIz{H!-vZ<>9TMSLF6gwQZo!7m|JJ$v#}h7qS; z^vV1Xp_Z>8vS1!v^@=NdUujrtYvp%_P5E06r~C6BGER528G6|3JNac=EH}q21Unq_ z{Hqqq1rF;J#2>zHAqDMzZYZgwR~51$XUuPWu%`|O*W2J+yG_VG1K67D);w@fPwAK&`M1OIR37QO)nag2>317 z?Zj0U9+Y3<4t@_$li-q>$5DksxM@-}-J7up&+Jo~ipyu|K2bQ_XxhJ7Um%Oop0ITv zj{8FpW=R?Zgq$OKpg%XoZ=<9z5&G|Z;`c!lqamz1ezV-(88n22cv?l2XzZCKg}G=j zkUnzE=h;hD!<*Zi{ZB>A$JO6Ln!nXEe_K{| z7B2R`>c2N^|5at9=ILk-WL7o?{d0CQw|4=u|66hM+1%N|)ydS{8OZgoK-|IJce#D(wf!zPN7ZL(8fAVmVQg!(#`1waC<;(`p z`ZxBEv86ujSpN<5uc72eX#d)Lh*|$NQBz|D^8DwL9mx7O$j=`&Lx0PL{wKhHy!|J_ ze^=sv4auyetN>*FZ|lF~{U5DW6@V;EENuU6|Nl|V#QHzwOo|_?%q;r1q{;s8^q3{g z-KS$u zXtWw;YCQm{a5B?Rm1HqzgQwKrD}nwM8W7rx7F zV9KvSkbN#%fB=p>EzI+iUOjY-@qq_$TvPzE7NBR_!U9t2Q38D7wNo%HtwegL{{EaP zz^r|Zp<9{CdFkCho{U?Z0vZhd(;}CE9~I6X_;=O%K|Hp1$g$fbTDCA&HtamO{0g$& zfoj|P;(hw|(bN>G-+B1jQ+OR5*-`Dv8|jqW1yPWBda0CKpaLHl^G-FHbg;b#n)&(1 zOnERC%rwJ^1FAgRNVZRyc;}JV;9#)d2Y5T2kiR|gT4sZJ6oGz!g^ZLjDMDLLwc0xz zv3S0!SA8;JrT^ZqupQwcKYiPP7{h`SQ0R5_;z|~>kP=TVWL0ee#r@P80!w>eMlQWf6?GC!VwN6m%(B;|Fl(9Y634-2N z`)zqqGS&Ti#8@*Y%6taAg3S=yUU2j{7?)gljzA_Ba0VkJ!T@$hhz%fENPsjdL^1@E zG`N)rWSywc3K+a7>k7av*xC_nA<%0EQZb0j5n2yYvj@o$0Wm;I1U{@+js>t0XayT| ziHemkS{8?0h>|9@gi4?T>nSd(%!3IrC>|MynjrEtLsf!H7hIMnt}J*sNNwWD3c*W1rNv(IIL${zR>^uuJawn&S*Lf8$C3oRp>aX`Z;)=0M|r50kv z_>`XzdAJ8}htScl1y_&Fp0f(F8D%-DJ>aAtX`AZGql0b(^CAeP*ZI=KhqMdcpU|Ip zGnQnin>r3o2ht`8g)|vRVN0QgiVu4L`xb)M$DtBfqU1srhUz(>XF^*Wvm)9dLrA5V zh$$0Bf%BPyHmxC0O~#r`pGuIblQeOZ&rHe*S6jqDsfr>8Xh?~YAguhIh6+_`Yq zXhv5m6*;Pzqx?aNFE;utGbIR$uVm&8&<1adL}~ zno-+y!!)AJz9kh$IcNKDe$6j!?Fz}IT;6_x5uXCjj3;^o!EajMvar{&4H?cDR2feg zNVI9Sp|tE8j%%L#e-5PE=$rZuhgt8M)=w3!?>APKGH$wcpZW5q>({Jfw=1?!-y`3X zy->Zd!U%?Ygm)r8thl(*w1@aEqMaOWw@h6{?ZQxdQ`gSR6mMo}Pti^xO%)&@;#}e^ zFycDRe%Wpzbc$y(V~R5LaLij!UrXB6IeDH?SdKn$8?YN#UlCk=Yk8qZkwb}>`ZoN% zIPm~~8o?kUrCKvyv${Fq!Q{gFqF9JeC{id|2&2obtK66Q(fAGg&Fy*pX8H2qdHF>N zk_WN^?hw8ZQW8=FMhJlo4jsxBvcDJ5+a5&1JZDIuw}1^U_A2fcDgeicsE_sRjLXEp zQ9*U;*`n^@=iv^?X!1!ye4t%Ac4Tfu>RU9n9JagUsMO%6MJa_(-k(xF$)#v9XxIOi zjM9k$771dL5MX&zxH*+R%&p6X@1E|!@18TU>m}Ep{&Z^GD;=M%iZkrh{z6AgKti;M z`W}hVSGp%(b!*t_z6ZIS*dG3pa4yYze9_X1k>(%I5UtB{7rhIuhcKOSV zv+?pY&e|63sWE@#@1&zBGAM(!5$dh$Hb7G5Ib$jlX#2On(|_BK6OG=CzW8xkaJsvK zy4?PRz4mgR+aOnlE>-ERwJN&n_qJ`{b)Cf80qvw$FUKXvqs<96?Z0j;sN|~DbQxLJ zU+fQwwTh{1cQQ`tBHIqyV%eUpThv!tuceR~%-)%d?|j`+qWqO`vZ?K>`LsT9A9B|D z*w*wi~T96K#XlnW`=Q%Dsu}{Ojg+&C@OoW8E)CC|0p%u?=h`b)B-+ z)>4bb$A!m%__68xoyXqIXIVdo*Ot3C?fmBf(GY_$Ld2Ma9sVN^$~Kjvc7w*hwk!Il zPx6o3xSMk$Qp;AAF`(j-e`4^VCOSr#t^+hKP)$V>7c6i&m6Zgg_KT>8d zXnlm_A?3Z=8GaDN+ZQz4g?x4ie}QNVl_(G(G* zaK^jOZPa~Qdi@wkZaRJnD>H*P$KCH*Y$){VTO>|6pQejYTf^_Utg4!-jq$*gYJ;m* zr_!~~msjznsh`zRZ>Fca`PA@AblGLXm2ZoW z%NC`bx2L(wM$`2XpxCe$apw1=r)s5ssOi#addUXKW2s81>8Piub+6jn!OQWel=@4;-A3|3VcBJ|DfT&xcjf{1ER}_ zi;EdMo0|by|HbjyMv1v1N7nK^%;|9|nj{(r;d|E3B5 zf^czT7h_uo(7(LI`F{w>f5G;@2><^H#Qz}x%&M*?F8}bEziwDQ_=Ek&J^@ztAC6?q zKA4M@izlP>U##tH`auAU?Op!%`Ur~kAI6~%&-{1J|9aAq)6w}XL9gm*XX0S{!B!m9 z?XCXVbAa_VbiXas1Q();evE@?};;c6UMC5q} z#!%O6{LV3~Op~D|#XDc--Ccmf$+LqB@Bx`kHT0d24gpAH&ypAtP{>b(n0+g6%HxDXLEp26urUM6Q%29If*N(k{f2y_ZZskNkBdDY<|$;w zV{hT`&u$W*%|TWl)Yub9Bl^LC&1r$mN=|0xPJfew=0C~tAyjpBbhI_M`%8maK5`Vu ztO;cMmpC#@Xnt@=78dw_$mZW1a|MwaHm-~N)Q#7{wAc_C4r2NCf1vhn^i zDhH5kgfU0q?kqjX1@!No8{xB{P$IG`M1meMc7+K)zt)xx<3Je zyTby4ySoQ>2)=L+?yztO?oM!bx8UyX&cfZ@{j%>q59jSX)*Q3D$Ecb$M^$y#*G!^@ z_EM%6X6DX6I9b2aQ0NVPWz=U=FS?3&E_* zk8Qp_`Y+qC{;#9|Ut0OUs}BFiPrg?9|NZ2DMV23IJe-_g>;1pnX0HQ5N7eL0=!5?- zBbBH7Kgf6_8OQFKD|JXWzX_velu-C#@71*JXdM6qR>ht@TFD}BhUmAxLT2B^%GbdUkDHs94O6L3S+{FK*^f@I{8P^v zY=P(^UiN6Aw%76LeS%tqP4TGs|LM#6$ctkcZU=5eMYI^0R^G8y;-Wl~h%`SB1aUx9 ze&RW48sQpW*Om3&ww$hRbD}G6DqGW)^7HSyGNC(8A%rT*(4It0t!wjy#J(a8@2XnF zHC#Bli|Fiy7TN3z#cIICrbvFXAW_SQ(EQ$}Cb@ZmGy78iRUBGTWXwm6!16G#;fyRs4X z)Lz*-3=+OMCo6z-=#OYTF>QP?b{!`-AsAx{yz1oyORI`)=^ZSR4IvlHe~R@EYuLx& zr^a?k{2Ckbp)5|W>}(C*@|n&BU*98(%*WX0bcYqPeUGbhXlwt(JLPvzSQA-{12Kl1 z#1T2dJO>I&HqLsE(1R5w$<8cp0LOhiG2^7zbupJDqI))u{~eyM5lAV?iG&F)iDJhg z_Jf7FFTUGCzg-p!^hZSOWaY)g66!#%i{D87Xi+*M$xZ;=eAAci9obzYG%2k~B1^-s zgDG{c|Bl&jAHh9Y8R11TP6k)DIx<#}en$59P4fa-9)MRsCq?s&!6SbV>#ifX^7Ezz zbOZ06-YNC@b86c80_wO>^iJMVy*3{xK77AbAbC%kI?O<2u53aYM*8g%k&BE!Ru1z0 zjQ;zjT?rAyXXzcka!@?X$nPg1sqr$~=GG_89P*4e6zM@0qzlI8G_{d}WNXsnJsUNm z6$toCCGEr-oaaMx?u#@v@5F)g9k^=>-(0Q|GU-@*GS?6f!kZKI_0e}fZSk}b9G!nB z&@X~3IbaxmuVZ92wq(W36nfI*GEcM}7!!Yk&1if$^6c{2k?JFQg^<=2q3{W%1x*o}&;JfCRfGT0?Kk0Zc+rAcUTxqfb(C6f!y=mdn22 z++m#Bo*sMjuexu4uc-cW?XxHMn0pOWNgW~ANLQ_-rKvQ1EQhy}O^vG39|P~OYEM|^ zQ51}7DIrpca}|k2wVgTu4KPCFLchPuSEwv!jCLZ5Tyc@84ul93=8f}Ha?BOsp;VE&U!IWS$WVRm%qLI%j5YrwrNs<#wc*$g5+*8l} z7rL5EeWecTrWA{EnsT5zR;#40rg}qO$4~=V2OSE~l&%s>Tn$>h>!Ai5E18LYQwLO4Qu_YW(q}g}wz;mPwXx&^ zt8#}Ldb2#@MDL#V&%bf4ZhoUUsJQF-`ic$t-Dc_jx& zNIU#!83Jv%gt_m;`tk2^BJ2oSn}&N1@dj^j9qkodBc7t9DqWcY;k}V{uPbyL=0fL% zny#vjk}B7ZPajhILdCG;Gz&Bu_TQF``Dihds@*hFOnp@~&)!VK?RKHkI`zM*m>m>J zs@e!+s88BcCwcL8_(7p3bvsQR@HO3PCuK#j7n|;W>AiU}RxT|&K9Z1Ncn!??54}EC z>KgSoVU^~J##t?GkI@bzO}JZOi_7RW?Q;0f)rtMCikBD#bA($ups~B%`~Y|?J7WUM zkj~ooLAC6^M|g_M7zq=kVttibYZoOo=@|>IAe^KpNc)SOUM)4J!CQC?d!HlsAQyH`YjX3$>T};(~4TFh5 zY}U;3or~tB9fP0Jha0VaSIvjQT0kn9rlbpJY^GbIM)VCv21aZcRyH3AI%-(Gdfj!F zT=+^}-dc4{)9O&uSlQ@DJA93ZcGzFiyK!XM34dKsyU1%D(`dQ13dz`OGxDuu4p;Y! zMzjqcf;w2@W#`J>VCk)^O~Y$~86vX&96Bz_j=BFl=wK`SsftHbNQxHY_S?Li!%{7n zHlPJ+AG6HiGfK21_!A9eP8ll6&)F)pUpsT|($oiTv3=#|EMr}}zj_@#r6M8_;IvE- z*uW5SEO+8N+pbcwN?4z3fLTK>XXTF}(<8Wvc3Pt2$($=0pugvA@-E|U@*W>z5E(b( zY->HAD_JMyms#(c^$NYsII!?(Jg|7uA9xkoz2QE5fctE53-k=n&2hn7SJ|j;J2x(F z1@h-@3?5xki?=k#}?8b-3%Ru=M|&wAFt9pDbVCih8` z5|6~zbJ5Y6H;zM92YQ{hiF{R?X2%@*{pky}0l4Q2{n}lb67UwHDFDMCiG3KppCDqj zI*jXDy(7RqJ4Bxs;mMD(=2IJ8YV)d3WW;#@gLG<>C7w;L_ku89xcBH(=r`|voS z*s~k&L9}{K%p2~xTzvR__A!uxyY*DjYl&kN^Ya>SS^NG}t7*J=K zk0LK*b0M{;&}tr|?=&NI7FZ$}iVFlh?R$wG7jIlLpqwE90PsSn^K5RQ!vT!yPLG}{ zB(KLn$aIUqr!g7;J*5K)XWO5nM&aJm^KTgAm~5G`KvtZN#r}+(xDyY%o=gw&Z?_y2 zoLSF6R_W#t9&y!+R=?-R0(|6st9)($01;mFdXH8s2H%8KndSdlE9*|BmXWp+Po9!y zf3Qf%aVXA73+U2F7GWcwty6@YDib085FVDLO2@>1w^wX)AQ2NYU!kE6x$IyOV29R`%EGxE zm}osaZGBz>t(iH{FxB0Db@k?R`fFfcc|bl=!9W3YRAY{<3OfvbAuukmXEw}>%6@NL zn$KU65D6~JE}YlF!@POBu}z$~57g(a93BQhPlvKjEAv9sM$&$uW+!rpYl` zx>$*AwtCXi20d)>v2!r<)caC^a+ z8akwWJ({FM@=ogXsZ)&2o%tCya&)VgS^2w$*ag{A9;x4HtvY)#ir~bIJ!|e`@)u@V z%rS>_d^Jj(d?xQS^%|Aw@LmoImfx<{@wB?dnCEips0;PB_+dGYS z2aUB!*`8ehUq~{y-fb8knGM{xsP9x!4un27r}@nm)tj6>Xbl4zAyxB>hU6y$W+-?& zo(NOx++WRkR7_%b2PMOs(!OM% zI`_WHa@zde*=_5=BWi(sEFuJd!^-{+S`2aFY|YuZ#!hnLx@1>R4~MYWGsGkRd*}m- zPn`G3mVe`i5OId@S#``&a+ho8BnZM-(Kj(Og*=i%rVE*qYuYd_*@YD%s^EGHa7xVK z^$J}_Grdwx0ANTP^pVI{ucv!Y!zl237AxLNua@U-<{H*dXJ*AwhI?xpKbi;~3XK9A zN)MV6aUElP~=QEs!x zH`heu^9~fwqfwi_WHf!VA6 z>L-B4E5bjKrJ5aarp%Q06)`qPmoMgF&rX{Adq+e&$LYbeE+?~dXH{=Bey zF2PObiHHc-M@}eT-yw0%ej|gJ%MW3v$njsZdq$Y-7PeEW4$-5^WG~hyLNu){MN^v9 zo>q(e+WVSK9E0bjWHwn?OeBVt^&n{*cOu*+4_#=n>Z-ZWbN`3BE+`q!P?!RGi zoQG zah0OtK2VRs(VUedN-88i&sBMc?k*+2?}XRUm4Q8fqUiOa!27)ud!W?*z3*CoL)EK^ zZtIOOPwbXG5EeFDDZ=`YZ->>`eiU_sBkGGtHfQ(4aiVuSepjT9am1Jr%!d%B5b2Ta^nltL@_`zp- z*=3{ORpPXH2PO-!f^mmP-BILC+ufuOQn;y@-gh9AJ=`?oh64ST1z-34;+bAe`YXwd z=EMHe6}7A09shNeCY&kHX8-tBvMueG%?rRe+whJqp$_4frrBe@Hk7U*ZKx^l8n2QA zkwMByVEhu`92jyz%eb)#pBt%@TEBBo9nWwX{kzVxdwxX;865?B4c!_B12MS5vOc`{ zi?8ws$7G8o6TxB>W8TH%ODn@$1Lsni`(%2ECI5c( z8I%9i&xv5B%u4cX?Y(yt`=jwk(Kuwohg*jbUncTjOZ0rNl3u--2tE#z1m6Wa@-O*P zh!a)bD^l%x2u_4IIB>ZEY`p!@Z*JT{+4XLnD}R3p2{H_Rn$&U4@C89UP#Y8#TZP^t z{DUz#@K@^f4LF%f(%t=YCud2{$A=S-oC2H|sW&cP-(zQ_}^NU@wXQR-bBI&om z*XLN|j!2!z+%z8np5LxFA}GYPzowe5<8JW2P%y5_s;=1wJCgr8ACxk65cCSn&fTPF zQRG@}?0>>UXplC zp}eZvye0I|34=+X_us?;>$W0XhG79S=wPt7Xuz%tLuDQd?+i(r@tbo}6mCKc)Vf>C zn6}WyX4Mt?U0mTPYl~G>S06Wtk!8+$7CN*ZK(_;8%k+eMaIBo-9ebBNf55k$70P)}+jlLsuv+J8l5tCgQ-$=BrKMhX57&#f<9&yK#DWyaixwY3k;wCFU{(J4l2 zCnx8H3QB%J_7lQn2-`+Erex6@v^XznV_=I48+u_7D<`Y2`X$^|B=cw#1|HQ!M0oR>?5*NReKC$(F}8)K+bT z6}YUa67HJ1vc&a7FiOqe_$T1hYFK$4m$F~Y{%a%C*&aCA5f^Z8k(NbnJmKU4T>6%V zUK<7M#!8bW;p%1^8xVq1nv9oKjbmW5b^Se9RvIFcDX;t|&>f*{B2i!CT%v8Rt?!Za zWQaGTID;9GuKYh{13lsr-Ltj1eyGzoDZ>BUBrZNDk(iea8L)LRr$XU4?Tf0E*}Oct zx7+hVKHX4$5v14>kKC=d#9{Kda@5)$Xl)}Ke*v7B2I5#QA5F*CfUah1j?bhza81HS zEA-lRZN@v>^@)jQaI9VI*jrQ(zfLkHXp%RsJ{|-lFTt*0?35)}Ejg!8gw&`MD7*2P zM9;LkS+Ir;S%(asnx;a9!9Yf0Z4J<#t_(^WYXGS)0STV>0{m{8RgohZ2J`qT(SA6U z|McEG?zbq+`#{-O4g}vSriwwX5{eQ8ZQ8G>r%W{cV~brQXobg>2JhnJYc68SD%qW) z#p$85gC)jS81E+D5$)~(yPK`B{(;&LqeV1=!96rRiI*`g!a) zL)+nrG#$_S0+)5EOpPT1r6GV#8LW0RWn3jjK(}~!+p11T$vFNujU=D*%66zmoxotk zY^=I!m47zKP4F&*ZY{;k()!@IQnaD1<#kP2C7HGrihz&@~|Jgt8Wn-kNJVi@Gi z{HDlHed&JwcnUwgjO8cPJ7)?iaZ~3i@omQQ z&d8ui<;W~VYFCJCd;R2TQULGOtnZA&qTcLUKF=VgMK9q*^sW-Jq@CSVYVNZYAUzm_ ze0(5TnTpwLVNNZ>wuc)H52(ZBJ_{uBvTI!O(*7l>ub6X)vqOGbc(H;2}GAt&^J z3E6OTY+Y5*-&+I=IC@PZ>7j|IZBIEEdU#kfX_I#gbj`BFqUUTPW|T7EX(!eyPy4pDxd9|Z8>1EbF^9M~&ggl`)f~wZw5AMDx`$pIH*PO&a_Mkv` zy{qo=(@!EjpC2e>Go?RT-DW-z+_!U{-3VJCX5Vxi>B131$$q_c6H#8B)HJ1-q`4lLg+xX!;T5 zS^Q<8;vD4N4*{9Y+{?MH+0Vk{#CJt~TT-qdHb*oa#N@!tYx)bbWelc6b$hF37agjm z%+-nW!>nDO0m7Y)EuW!#C*OTW$G-M(*CD~;=%ufi+Q8@gL;v9onin9u_wef3i=r#s zuFs02?b+;E|GN6h`z`&A?=Ab;>8<$f@GUk6y}gFa7PScWHW1g)FO~)vWZG+KSXra# z26X$zw+-4x+J5Y{*!B%X=v|^!+Aoe*Vt34#{ zt<&st035-L!8heIId4agzuPVnO9YJGP%j2_o_en)|GqRd$l3m?J9Wq}(K1h2w0^%{EMK`dk*+tTi0vMCU3jSe zpcyvMOO>x1A)RwqGC0~dp>pXaR@UFy2G{Qs1#j@+kr|$XCHK=(CZ$`z=mUbnqaOSB zo#;0D3O9rOZmS&*qGVm$V07zXCI1=GZphzS)Bfko#GmRxEX~wmN1=buw2PkVn@%K@ zedajzPAQBp<>O#~;BiAcHTFR(rRb)N{4gpWbuVY{tqzgOd2CH!BraZZ@;4{!ny&h|MC)vNE#@lnl@s|2VUBqU+`xe>yP!; z+g8a(Bhka@branlPluJHNy^MT6oUsu6=L4~e+N?%K3k_a$9CI))p_TL>;}(^w}kZ~Hx5 zg@pbwR&Lfc(O@TH3gQ4d+d#G-i6NlD?57F6+dh@G9NWUIhL*?e-FT*85_%KScjdNx z?i@LUCLCM2NiJIfbho_6odKpzoE@uP)&M9Y=2H{MdwE|APs;gJqkKUP>K31=_%65( zqUwt?@VW15cOQm~;H<-`*7~8H#mAMQ`xM5=#nL;YLNa42B12@n4Z#l1LG|XQ<+4%- zCB3(2ifPyCd@!ds(0lXsl8YN47|nUngem>&EmLN1q#MJL%;CQ;v+z62xCUW`Zc?F&N@z&Q2MckJ} zDcWYCIP3g)`Z1k{kaU3(onkH^5O?p@L>R^gp2s#v z3dhxfM`qN|JOqT~s+W%Me$TAtrmJH(xx2#3Zx%{yN>902a5)&KP$$;E*bro(kG8>) zn^Ye-d)8F#kx4sIk5C=i{zBhNXNPDYJMnj^%Tb}Wu<~Rue*bu&OME)Y6SM647{jOr z)qz+u(O>fkrzDW_LH^41STuI~Q|i$n($!RXBrZ#~x(SB=VyX$OY6V*jxJt!&)o2r5!Qc({>dkBu<^p1nA!*oe zqt=g|RvsHlO)99Z>k5U~nJehoUpLay=r3PXe{wu6sEJofU4+CQ=X!x(rI}kPxV_+! ziAn6!%_Q%OWdYJS8GKUPGGw>RSb`9IpL2V$he{f^`-Sete{n z8KD^GvLH!B>{mhzNe^lj!fy&nQH`WOW4`0}buGBVjF zXgn5a{niHdl@15<$2Y&dH!Upp;`j~@uljK5F2ay3?HoK@(dVR|npQ>?{6(ZyPEhju zcg80@|7^KN87BVfl81R+r{sdsJ#h@ystUWaQHa=BRY)T@kC%?LHT{ELAjlU%S39~(<|Nc7()WQap*KRiLf8{PULXTHb)e_4&kem`@D;5)5=yQDHC;s) zwU)HL3fA6l{jy>|XWGo@zv=~fsr7#tb5rj?=2U-`33P=oi=vzvbYuQ5dDlk>A`%u- z9kJad-)Yo`5Ea=?HyvH-YRP2JG98(oY{A|cruYoT2zc=bs5=XcX?C4|x`Nn|qUeD}OtEldhOm5Vku82zC38=nu*u z#W>e!IR$)AXxgHS#P}BYlLVMTy9R4hlnzaHmr5Eab;O<;2qb}!gm0{X*(pFQ{P>pmvYe9cQ%=HBM;tBfQ8A>jI~clHhKGElrLar-Mm4$*Tv@95P~?tF zm)H*OvqUbJI?SyAvtyRys8>0%3a;?Zi4!c`;8$p8oC+Ng_|btPt9Vuj$Hu}Sbf#r` z;o+XB-)huIWT&16$Al)Asm<=XwbW<$MY1ZCLcc9Khz-zfk7DIYjS;Ozo0A!;?c+*# zp?r|+4Snx?-n4UWJ--xVLtDXmVZeYFA;-4dG5Ia7x6BxQy8N8*b6~*h!*BaF6!C0zBEesRgX-)$pHtP2wS@O7#VSM`%kgqmsGFxm0J9&A><1S4a z2va!Hx{Cg8tqv0h4^%#~Z6>!0jCau%WM03HZp~Uq&PjX79(cT<1Jl1->Kgw)4gUTXow-za%LZlIbWJc4OabCLx~}*Ac@h>uk$o&GeUkI^Of% z#($51ul|==%0r=g<=vX2VHbhZVr$)004WE)oP1~N>kX0YY=O4Vpz-E& zL+J_~(d2d;=I7<^*Xn|%O1M?W;1c~7c2m|Td3cLz?`bBNrmg%21VQShny#1HJ*xNk z+3aN^9XDqi@H|=OS`s-YFCr6B{Juorq--FR&lfo{`(bY$`K*!1a*uG<8)YNou+XIn!~UhuaysW$I!Z)1vrbKFDh`a#kbxoF#V?n;X%qM*+@LxR$U zymt5_#icJjoNVkdHP^jERJ67E=S`ARq<*SB%6c`PVCk+9o%c>_^Mj2~(IBcyLUw71 z56+?Jjql`>uF$(XMxghnXU6?%()(h2zRunEA+Rw)BOXI_=O@)r;cmI0*8K;Ypm!MXni zW$0Y>#Fcx~z-WIk$0qNQ^_^L=Sz0jEn|Bp#NCP-GaHgh7EtR^s$- zn`mfZK~a8w62Q#6I59rz)_-yB+^(@0X?q!?Et&U=5$9$xUj+?5AN2S13@3c)Xdv1# zodYEIbqhhW2^7O)-S&w`lFNjfsR_xE)mdReIU=3asm+qp!CVKiW)=K%F`}jq0HI7KDPLT_I@tZC#)>k=-phEV@NUJx8$3 z-Gw3rPN{Na@A%!}SQiY%^E_fQdZ^+j6CzAvxv66WxQTfol+{r8%20U`;urWm=s>j? z=B&C<$Fw0Iky_?xy714I6de(q)7a*JT&E{uYlsTkj(6{9Uijacq<~%O>^+{jNFTe= z`FBw74D}&jl)!oy z3?YBrW61H#HZBmW4^pY&XQK+8h5 z_z#Hjnt|i^um_PF%_i=0{-%627zF_80@GM4tutggCucR`)6jYa_(Yb3KQ{ z+j~SBN$CiXQaX`#&{j#1d$i3!yb9-}_~S*kGhLYaa}uuWY4o4mQ|#?%DqGMwyX~Zi zz^w$_{P=mO;mOYc*PoEydDmIr2|~3#kCnDRuLC6_%YXg#?`fA_Mwz|w4UOwACf7Gy z#OCN0_4T{LU)eZ{WkMa=@l4gI zTj0!7XAw(Q}CIHzH(W5fmV&aLJ zWfq5{2>YYfd?RdLin1%*W`r-hiVIldD|$%SK6Hc4=!RK<_U1U<{>jkNwxVsg0YM=0 ziN{(=ieq0?O)C;XQ1VrzOM#L3r+MDvGATwdct*9FGZIdv>lAJE?+?wE1@1gh>sxSF z+>MNh!0IqA2QB?ZwZZoJQ+F6Nr|Y0WoQ#pJGt|6=$?)5_TqD=2O(HR(`EvhiDojbp zS;NKnA4dD-wxR7SkUccccjzd-Y$nPG zZTzOU#>N@kyolzgGZ&MNZtCRe%<+v_{c?tv3fnj~c{|D*W+L@pGXbe6|M~!b6>GaO z^)F=W&b75dP^EvO0hjP^;4peTbXJ-yd?xTGoNm0f1bE=TusC!1;>F2_?*>I$T$x0B z9FUwtp!O|f$dl{tA=*_JOAbZ)p)3518C$dxfC1*61cFb8?grRiv#28-K*g|b$u|>i zl9YdcP?r@jp>B#1N;UrXQn_1T7 zmO(w$I)hr^O+wlX<6y-eH5nXGPJ&f|SOHOi{^L=!#~C`psX#jKS)yb8K7L^Qsxj@q zs6Td%AmW)?k)Hxg1W_O!kqPJrZDmaQGrf61HWB6%29Jo^V$sU`IMdE+*pb?cZ)F-a z-PDFgsgXt`+{d?|;m8=?Peu`#sCRm0=!kvR@9v1$8q)zx+vzbS@*O`S8iPTxK2Oxa zPFl+c^%0<>7s(+=gdiWYKNt}bD&K4h<$WybFd`h1gkq7KmhP`#vo&OoDIY~Dh`ZdeOHK->j6j!=VI1lYjgP$bC28Lg7R`7NU zY%S(oiO(TzbQ}QAcX6Y5TRNdEkA#A^yM)g;?^)1$*I>I$sNa?cZ+DtRb({& z0iH<|>Xx+duBuL{hV=P#ZPS&8zsyAupHGH#S`TE>iYee>g zAM7|9#a?rCQ?Awt(d-QGxVRZ%k)k0=2PBu!W&FLJJ)jY~eui|2tJj#vlLQRei{u&e zz`<^vryyX`)4O!+Rj8jcoGeUh#xhK|hSkBus!vdS{UxVC;u)j~e&W9ntZ?{Z?nkj1 zQW?s^T$alNmnCbtO*8NuWYU>a4GoQef^`XHC5h`rA6lyNbKjQU&Ks_*+r$YwYD{|q`_x;hZoPpYM zV(j?2C{r=@2;SYOaF+9~kp_NK*cKyR{3JbEQ9Dle&n@Hp6Y#ah+S*n}JP zo94BM8G`Gl{YKq#k*XViY3~8A^APlM*0wO)2FPiFI{C}v&Xazz6F~!+Vhj(^!|>Sg zLl{<(sw$*;D|jAq8gUL4rwa!*it3BKi>L56*+e@6F5jr-0m(Ec>vCvy@Mh7XTvx2l-Y>GCzym{vBd;Kk&Fo^NoNycudY-)tRH-3D%M<#gvBiSE3xUN5d7mKWK=+9FsyPQKfEB2+~A^O!P2F zqz9@PJwM6~96F2*=&{MMfJgcXuev~U(R7L08tPkE54xIATau8}wJ>)vyR+Ic0sKnL ztzLg`3giT2!4;!cf9Ptw2=TyLwJGAo;6}G!(sjVL{MYo?Ok=8amG=$~$EjMj0HyS# zsBtou-v)+g0sZRUnQ8ga5QlDtdy0<<(Sl5KEW=tuED@1II^pj9dl`}@aEjxp6$3T) zl5Nc5>4W2BQ4ZiFV@}o7yLI5v#+f_zH!LtTj3bBEMha7o?y^$!tbDzMFQ82sWWX2qOwY$^KkKqApu0(beB4={H<85Zgd3^ z4(1`TOeW%;1~GN)fg@YSHUG)Pt8`xFvY@Uj^|;}e)kip3pIJNHqcLnU&zy67W|xo;`39hL>HzOPl=qTirH{>3#+Gj-+YJ~igNGg@eLqWqJBXm z%*MEi#44vs{^;+Oa^pkvVhIrcJ5CgcM9=5_?*O84a7VzL;MyWFbq!7?%8f8}fwH!n znf@pAUkYb}x8-FEM=E)GJl2G$@0@y1+_mP0yU-6`!7y*g0H_Isig(o?ap|Oky9GJ& zhs8esdk}^{j(9%6+l)EXctQ|&|9mT*iF=Y8S;BC8gROb6&HaZZb$G>g7Zf(EE1)PH z5FlmtYOGk?bRZX9g0ggHN$-TB(z3bXRHPspskf2PegN};ECzwV%iaH5o>sDUVdy`) zIA(eh{X6cnZ@KT|W>5%(MSF%ELX3YZS6uo?XDY9W{t-EF2Xp&#wDEtBpgTqLW3Mxz zj-&=QpE8az-0<+rB%~`5B9bS^$yNANvEHav`EJ=S5QF2a%%l|gl+ONxl1-`xr+Ufx zf%sN7IO1unTJnPpuNfpjFB3zIV;s4Ry)7&ov3y+?61ywFHv75lORqf$XasUXQG9GQ zA$SCniWEBF)%Y0Zl`b&lLz+JJxB2qeu?9HkbNTJVr|su>dF>x+B%vdWC=RPc z!jM|QGd*?wc0BB9@F2IpqJJTx z&ZsEWDZZft^K=fr%b6osx;T6N{>DIOAIJ#1Q+=VFAK=UI$ajT2hhgixUY(IUzb^0g z?!CjpV@bpTuk3ZR6)cVCx1pnVlvb7&qfbbBpI=!*^sJ{}ut`hxoN-2>NvWzmUW?>e zNvK6ekaxcBTeHXqv9vcd!Wb6)*=H&+QZ-eSr8B>@a8WH0W^Vd{`-Ce-(G$tKJ}Gs-&rQU*=L)S+-twsM=B1q-Lg?T@Kxl?NP^zcv)9ecBz_Nu2H&FdZ}@# z(p4f@=A-c*_mbg(O53TIR+{#lMm~|520sBmp_}H(fnt$0`=;fDYIJ^@wrRPs_@?Bf zb&E5h&yj83iS4e0>5><7#3TdU4hofEQH{jR?+3ELNm4!s|DFt;dYr#hza_oz(f*y) zPP~D7Z-CGG^pH!1Qt2D`b0~F*6qBlr7p2Gs63P5Qf!Y&tG2|o^<@&&RdhfB92HkG2 zWOs0PL&Kd8(=LuxsGmsEWt0YfiG)afm;0)*^rn+xETW^9&QVWhqnVcEtV5;UEZp0J z7@&2M@0F<(1cR4lop3aScY=h(-p(MWb_Am}nf$0W2}diip*#RrY0YGg!UC_kqO}aK zo1qtEpNH|bbxC#9v%q~)Y(HM2iaZ%|>lYJ)&Y5*f_9RGsFYdl!@@>QYN?pM#0DZf2 z+2+A;bFZJEdo;JVt(F!5E6R`qee@?IU1A1zsRkET1shT?UrX9{nf~S5D@E2D+0Te5 z)F;qg497Cfvx0Gb26;~~`7s}v*X5r}>Y#);(Fqu;kv)RV#1F&YWcs~roTQE4GxRp8 z#nBom3KI|E6&;^FH$z)FubY}Jc1x&+2#Gaypmk^l>cQ;zkeggQ6M#~H?7hymw&&xS zH`!eSUn3Vt1nGT4s58P99z$QJ{r=q#yM;qkYgS+bzx!5CVRkx^ z&1&+ox4z6U2HtU(oXyJkc^F&5Xx>n`zAuY~@O&FFQ^(`uk~|KMF0W4u;VyW`@ALq1 z9#1Jl@uqC;o352*1j!RlSH%Qb`VzZ|Z{z2H>jpes>uu*&?^3om=>bl)Nw$<-TiaEw z=-L=@%H!{FZ9!yh-21 zPE~8>-&yoo+46d5JdRj;ANY_Zdgw^r}APmG=N>W^gO)4pV)kGuEE zuFg}gAzzQnm5r==7qBeDYLeK7r0cw}hV~K-{0wA3l+I2rBctO*2BF!b zSGb4!=WGEli9%`ekIk2lkrJFAMfE0=dph*K`P;HUgp`~td2wlp9~lK~7&v0Cq8(e& zc)wq33E0Jx;xvSu3RunN?|Ktd5DV?3uDZXYRZUWlP7Du-gch3pr*DJL5cIeb`qP5k z-{_xmBKl?U#SLzN^3h#eTd`Q89%t0`2bGbIfSV|n z5os!vdcX)~I|mnrwpA`}%wb&i&-=mBktm)vXb=r<&N+7>ZJQNF*%P8jSjtEhC4sL{QB=Y&1>@gd{2vm}`h=ya%yxVNnMAsO_!@bb$)(E%G+;%VI zFPhf)o@Ab~TTohJS`=HRu1xJNF<+a%gvz9{*wvz@-q4RxewL7Vylb zpD_(9NxMJ6s1W5fZ+|_Cr7yqtgP*pgZk|4RD;&bcjA#=k1ZAw}dBEOGZ+!o*t4xd{ ziwy;2>cCTYb~&)y02}2(#%2C503&*TEWijv9goD`vOUCYLN)4gUH&V$X#y`KQa|HK zCbYNQ(Ipqc7sSnCs4t1b^LJ~{Z-2bgU{axI;an{2FNa4BQ^Bp9JG$W(mcEsld#><* zg!`ktZjF}#OcPt%4e%t1;(B;?l_E zRQEyU-&&t(jGCBDZ;mhF`30;F{O1A3|1I*mYZLT zXfahP(*A#py#sV*&AO-^+qP}nHafO#+qP}HW7~Ge>7-+u9p3b}_dee~_v~~3f2=Xr zNY$)*SJkXJ#u_X2%;(jnCzU8!7D6apg`m*P^J13JPE-oD5|dMCrF7dpwo$abl#h=C zp9Ggg@bRH@R6m^nY}s|WTL~}DX%{#>EGs=MK5(9NK<<=vXh#kTEPl52vXpD(wKY_* zr8D%1{RS0zMY-5%{s=UkyNGysF$Ic|PUf1l`EaI@EA2=I?lO6{BCie4r+o=Lz!VN9!SN110y(#Qf z?_2KbnD=)k@nCkz`rSKJLLA$+_kDRF2k(+Cd90h(1GKiQJ_|%BNxT6k`xd8!*x9)u z+x~Xwqnhup_N&bHroWRpH1Ig54%y?q;?2Og6_-6e;P(+<2-b$J z-}*gyKUqAmZfw=M1*i;;+7}KWxX0e#j*0<4#!p`rZ3%k@u}>MQ%Hj>5yNOY_W(a!a zf8kTSg-rEn|E80UVzGn*`Eg?0PEDU`7kkatEqI6iZBWjY-ZY^sewJr{Wms;BSG(gB zuR(I@=vgR5R4Al%9A^h6V?<5`Kcj#Pp64-1VpE)O3pNv5|0w}mWpT`LRby<=v;gdA zatPfbP}yo+yV^k-sbs_ZshYyEv+Nq6Saf)6QnpJ@yYX3#e1#l%0~E zysfdOcRnKUV(Trr&Y);9~F9z9s#`8z*MOrNYPE$?@mzXl$pJA6dz76 zME2uO>k~fpleOy4KrZiW?9wE$U}{{+(qZ;J5gjvTWn}R)0XC{L#tXpSmjI8|7a)OY zUdnmgxr5Qq84HgZulP=tYDu1Ias5sv>1$F1U^Lb08Q%NnvOGwj@hcFkM$F+zck8~T z?nHQ#TbQ9$LA+jVhRl9u>9;d*V4l<)Eh8PO;HNO6aOEare|URj;QuIXYNsUlul`pE~amIkhmBb}%qIi<+!vqhcNo z{5Y@dN=xxBXT%DA3}OCj#z)U zV6>-(VwP?t?S#A-l{&N%a%dd#y*fHCDM>e%m7cnuuZDxUo`aUAy@8{Nh-oEVIZZuL zIjh&xKt)DIQqcp)B4L5<9;v?d}tE-ri?jh2bbW@6KG$&CZ6LsWy5QjLL$bXsPkEgfB}iq>=p zCnux^G?mcV>Fq#+>T)pYk?Dx|QJF}!OceXkff{L9*g+=oVj()F9bCA;<6p@l@ zmecOt5smDm9t*dV#zCUCk&ddahlPo(sj6owClmkAR9#&Kt$2JLWhFIbT}=hXGFL%s zZA~9T9obmcCKeic#0M-aET#A^?+8{J!gVYx%^Y4cv4AC>l~i=y%tS<0^i2G`T%F7| z0=CvdmRcrGYBJ_73f@|p^-PSUZtJDQL=-DeVvKlW6p`5>T+U z64O)F^ev|3qiCk$%cw(UN2>Ujw&c_}$K8mU>`4Au_Q19i#K zYZ{VOP7S6slp5KFQ<1W@G@`kv)Q!7$sRx+ENBgED!KIjuhK@Cpjf;*{i48I1(A5qW z2lXM7m3wDWNNC@4ZJ@Q7Ivd!yeRdMFyRu0mTu4*aL{CH`A_|tPMG-m2Pn;IbMt>xi zCezg&9(ELc?qsmqu3qL(R z4W*Nd-J>rmXt=fTmYpuTrZMg?>;%;q*@%2(8j`w|jjWfMt(2bHXsKeVE~IJNU$``h zhN9KD06l<4YJz1%M7?KZT3m(_YC=AotZE!GQbtY(Cv2phn4!_ZVdP;UyPDeBM|GyecN895z=H0L*{ctjbJ0;!>~=H%qqa7416C{4`VXcHkl zr%p8}Y)2QHr=)~~i+58_R=HjX3K?}*HGxJqKBZNU;sf-Mr;CuQ zo0_A>&0S06Dq4W)mz;%xscPP|WJW56Rtz=#QLv@n3| z$h13nDt!yp$ds5?Oe?Ae(9lTHh!AB*CodZOq>!o)~vV<0BBjV9QtzUS##v>`c-?G*aA znzFa2gFU0|h55_bQXC$?bGs_tXhgm41HsxRn;TGB=_3wbtZd%BgyGC2%$C>4+zXED zU)I~4;`lr)O#_ybbsrrc_9sfIlH!-2$K8uHN<@Rw+nhySuS;o}My~wtk9skq%TwJq zD|;OWFTm&>ajd*tC@lAfleXx2b{D;8eWNjc)HxTZ-gS5NcTcG@cG;dsG4+qRpmy&D zz&;D_?YBAN`+KdzBQQ-k00sXb~vplIp;6OX|{RnBjTGJRxc%Ix|<&Fe!XvFmHChT(-%+5`(5=f zYe7#Ker1g%_djnYd?K*T9zJe+eH$N!kG(!NuK7EUa`GNdXoBo7Ctp5mJDKBRD?9d{ zeVoiB(`k~%h0sh5$si>q2pEx5;~^rFMUkOHQ0o0flo3GZMTQ>`_J;tz2^NekI3nd+ zo^v9Vqrxr=VhXZISqByFg7vc!P_%_&_V!*yD|^9x9Nc8H(cfikzy5r^{J8YG+T!k2 z>v&1}eux^Av!WtbE_Ih;Yr(N(?Ahw_E52cwoFBLIK5<4|CgSSi?a5?Mnhlno=i(<~ z=hfI4?qX*UdR*&I!=JtPMT4C+TIA^Re7?@t_0!|CKkU4mW>^}Z9$|qq>9}2Ye3Tkj ze3m{;4nkkZ#OIF@TN-kpA1^+{hpT19<@k=Vb(jxo(5-5J2un}0*QS5#tTA&vWUa~4 z^?7UDzb*9vPo2?TU|!q$7;^00%MD>g*0Onexxq-YYcd+vsg9gt_f99M2)HT!h5;zi zpCe)21Fr;tUoM9s-H}a3CyHGA{h6L0l3|TW!lXhub~GYS1cvHey~vwsa=`zR3tIuj z8npVG3xuZtM}v76y)B=zMkbciqS*H3b!LtPtE=K)Jy;w80WSdXaxZlDtvS(ox zOePjX3Q}KO*K~0xC525o1$Hsg?t%IMfJf*#X)kdvX)jqX(G3*$Gr#Nr2mL<%*z9=H zKIAR)Er&<+IU&F3a`Q{@?I;FUr<4Xm0wrNYHDe9sE%?4-Ll%z^9@#eeHt9AYe1ctq zU7}q)`1s2B3PbjhkaevAY|O}Y&d?qGn5j&84)#tr;0rcTsriudfPTord?mBg9N1~@8w*vX zg^^zWroK?;Ee{Q_D*uh#o=I3;cm}-x9_>V` zqgHOW^U3$pKghj*u-{$1Xma0}tQ|OtT9XPQPf#oSV^f$dbVH68D$wn?8l6 z_fN!iBc8%}_bz0;)wgPFy&GcW> zUq3WL=;C+YEfkc@GH22Cpfu1Eo*}Cxt0gguPfJ=Hx7b&Psh@1;OYtJI>Jm~C$`sO- zk|XnzUye^wS3;(gCm2oYC8Z~<8mDs9zUD1+}8cqv}061px(B~2LOK)$G^#}pw0 zvlwtI)wd8}T}&L%;Vv_vW%1|F1^H`yf-#7N zQqazJBqd4=2MLaD(KT%Yq)(HA5L^0(=6(;_Iv9<(dW1YPpUw06z-TE`au#Wsovo_)`?F5}E*gM5l&cRN2Y}}c4 zVBVf}YxC92JIv5optAhfncCK9n-T|tbVFoT>KT(!+L^PhH7XJWggFY|^=8Fn9VSiF{UKcfXIz8rps z8mYAA{%lLFK&fs9yWmckm34axqrWHSm*$rgQSj3c({d2g7$>Ve&s;RG=KHX;rdIM+ zH0}^6CY-ddjqU*7*#>65nV?=$#Kmr2-WRt&JnplZ`LuBJvQ0!1Nk%l6l9+OLbaZyS zJIs80BM!V&;{BlO-Q#$Sj7Cx_9nDPtb&m!=Z%fQ5XyWsbFmY{$nE!oB}{^mMr z`-yPR1D`?6q)b5>Zz}F!1x*02asSkM6E#nkc3d$wT_@pevi#o0A!Q-$CIJJJ^ zc1$bWhY&iqHv;ahbA*&6?1VIwJTtm*H*~Hyoo-*VipHxo@8{0dl?< zs8&i=#11wx-Ozg#*^E4Oe@d-LDAf|bD_oSfSg_MZuXg#?ASNC4P8#E?HdNECA22P+ zvPt*)hSLODiS3zVj2@=CD_-8Me*&BIg2 zb|-rEc2P{*{6S=LQW|SN9JslMIY4~&jngpAh1k^(V^(b&m_U(q^nY4d|1xm?@sBcn zWe8#amxuM=mA3y;!>a7)V)Bm@e=Bok1yy8)gs3Gcy)cpC2iT%$cSXtTrpT}P<{uzsv)!@i=C9J<23qzn7w|s~w45A&D`;8&C8m`i;9&hX z87<m(BKX8SS6z^zSm-e`HC1zmY%jUJecjaSGri~?IeXuR&z>~d<;X_oiN+D&(F zK=eT(Dibj%G$xD3k1LVCJC1P3o5kgF|2O1j7Y1QAZ*#?bUSB&!(`*Kx-^eBi9Zzih z1hdgh;>>FeR?M=8scP4Lk|9OR3z+0j(i`kL(;{Bu)# z61v-C93SYW-|T+-gMG04m3V#6btrE zI03Nt8NzODIZt?q>N;Fr0WJMSb~*iTI80E?JdS8B1y>#U zxJYG6R6^L$N7o0VR?Yp_{IQ6FgcC*8nSdDWL(hGPcHgf|Hi1LbVV;5$(uV0@ zKH`&hUa82%t`WDX6EL8|^gIEPA9|Q`b9(gLO`mnaIFik|(xKG4j=6tj>}~AF>|BU@ zWAie?Jn^J*(A@Ub(7zm(+TO@cCTxJ)MI;D|dyCHTi7CHAK>_!8&zk6|l91{5G4llZ zSa9~2>i8;g(wp!I0uO( zND2XjKRAm=`9LYRBV3NM>Udn9kI;tUiznAmcI|XKeiRE`EdWBIZiuVre{E+do9!ugU*9w`0ShK{rXUajfd+vUzJ5K(2&!pgMdgy5`GOTiHTl_U zn7Fy1Qu=v?5B}I>gUQlRdXZn&LYt<_#nY^l#@#{nc~DMONQ>%67 zyuOJ-!yjF$7G257qf<@Kzd*vK0z#g)f|v8HrS3AeXZh!;mBCu?aaA;*HQ|L-q_lYmQBnqy_=w!Us9Yc`w5t$M6W;35)0~{JxWpO9}oi=W#+rGgY zad(CQ*bPgx-E`luF&@4kHV%+(p@^kp&+3wgNy3TyV+3WeI5%IQcmc^7j5pdfU$t1^ zwE#~Pd5-NKD;Lzti-#+euTM7_vLj8Dkp-hWfSYSeY;k^e=SA!uYCRf`7X~hZi#i5(xXi2ph1yk;(kau)m^j^VQvo=cQC0AT> zF4z*gAdoU5aXTa>7(-=9XO6!XXGj_@qz6oKl%n>ar^BaXPr;@d zO;@MX7=q_NoNK#sdp|Y2t`VPSX(O(rVNb;DWVX9(dYV!_u{{MChJ2;l3E$Nk))SACCZ)r5xe|icN2~Iv3G2WV! z4kEp_t?F^aYUAsWGP?IdXkIihfx)QtKblQ zTLf<{_()0%3KV@mK}EIsuJ0k5#SGzMZX|@7RMrfOt*fM%ivsaufRlr@5bR~_n6VM| zSOngp6ts*N1$jPMvWd;ZTNazSy(LDbaF(gGbuH+?=CMSN(^sI=67|f^%9^-fV*G(N z#b&oS%)cEaN2GrI3=o@T0X~kj%F1f}`c#gHBBs&*o0RPUSuol3Z7XGvNq=anMv{NK zxyUqP+Hqov9X6J#(-0-s*H+*t4*8xn{iw1uKxxMnFDP~I=4D1&t7fZPuo5aUqDW`_d6q>W5* z*Mxb6TmsvL>RV!|GHEs;lV3mj)5uN5;Qkn`KYQJXUk=J*LPd4Gv$0$677zNO4Lk*1*fMfIBW zHKF;H^a2J)z>bTXm)liL1Hr{s1M(Fp&K0R=Iag`wX>DNVCW+<&xAq;-HeUy8H# zCxKmfM3nhoEx^Q;+gKFL;%FelH04-WNLm)0(FTk%ocao#^B@Y}BTd|5*y4db4G>~T zBpwkUzyN48CztUG7I%_Bc|ZEi?gVN%59W0HuLETahI|sjp}%9mJ$)$R(DjI(;Ns8$ zW=2tly}o@qv|W9b-k)&L?B-!b9)T@IGX_n*nm>Iq;?R96;(TxW)BHO~CN)J^)yF4? zwhwq1_?s6Te3vLY0w+W{E`^i(wO{z4urEwl*arpNwoB9kHwO=lc~6w1`|~G$nD}P@ zPQqvIV3F-t{8%tc@o^lyJN(`2Rs6x7O#I=Ub*<#B{v8JaC)$JSpRF7;WX%N|5B5&% z%~2nFksfb0G~n_P%mqx}KmzUrn*j51^jUt@oOerraBO%?1sKWuGx-w&1Ob56%@*El zV(f#iLNRVIe+Pw`tI0F?vVj9XrG?!(0gN)Xu{ zB!Z)Y8Z&~_KTts+wjj6*ivQlIv+cn`K>R~yESd&^eLde6+#Y}fP#XY(RFLLKP`7=n z+kXs=&o^8bp->r=5~|)5B193yuv__hVUf^t%75(P^Kty8SI2i_Y0a@40963Q4NOM} zDL056iT*e1o_?;$qI2H(wd#eMC!!%UL$gUDIw+e34971M^T^h{C7zgBC4c#r0<(#G_|*a&r0Z zPvc!z%)UQ9t%s@pNb`%4l6Gof+(8u!`e_Phx+}qfG{b&R#gGIkZ=wP_`?JZ|$i%Wh zR!7Y{(o4_tZeG54TQcqArR{$D0M!X^oBxpx=Y5b2C-H<5-1A%@4ihyTt3P~7H9riu znq4W8;2n~L60~giB~IW(p1?zd(xdjhapRaF%M%p?Hi04OXxNp$16M%J^axYtEXl9-VTA6;|bG~M43Tz?+6$ot$^)r*f6$&c}FS!;@ec0%c6%y1nsXJPX-EYBJ^P+9+G?@-qMZ5mKJTY7R zv<%IBf{tBDHusR-x7Gd2t=l~ik~j)v66eq9E>0Wqc&ej7^F5)1DS@ndv+Z{tH5Kt0 zM-<9lRXm}kjj>Pbdl%(R-6*;9ei5t4q!xo5`%u)v+N-5bA_iizirFLr)A|0HIz};u z%mD)xj^YUkA%TZE47B^RQWDY|He$f?KpzsTtBq-t`cw>$B>l#QO{+E@(QVcXtEdZC zq!zv6A#!)yPfz-DM@gb$9H$c@WrKV0IR##U0sin{G0Qt zjX~@gh84}JX0O`qLG7eG(gCa+NBIEPRcbg|ed@LPP3u|St&%MjcUZ)QV27Et8Iu{4 zOZ03UsS(fR8YeLKR%FMiZ24MwwyN9d?Cn;H_-e?vWcsFQ>1EM-YM+pCN|k;Pr`i_m z9;@DHDd}C(k_#~<#nf@#;2m=+Dkh>=YX=bXAIQ1sKBPtoZvMIHK zi&lEHzx^KQpbS~mj=nTKg|yD(w^R5STbpFB!Ebs|UesD>{(5G=snXY8aAs8l+@xpU z|E;a{*-Eadf4l*$^6OeOwv#d z4LJtI`vbWOj_LvF6o#0D*sD8mFNI^Mjv|av9{Or%C|d$Z*EBH0v<5863KrV!NbaF$ z>WO(~z-yDT408QPUJkmKHrD5oYY-ZkzX)htp`i>n)aWe=Q%2c&UI*}$#?Ik3PG4y^ zRsE`orf?Cj`j_QDG?$7T`{he|{qXxAq2W{LR$HEL$fDgChxDG0&qsz$q}^tFuTLXX zh;Mm%2B&)yNc5?zrB|s98{5bWN=5gEjY$tXi?Vy9$epe`t4JN09SxW4_6{^d7@TTCM9eiw>9obNtu8o8g_V09a96p6e2WG3hZZ zR%dRUY}Jvaz)@C5#S(}hq53n_v6UY%q>h~z+rI-(I&JWXmz$dCC+r_Is6s=Ml!@$? z9_*I?+=ydeshRO~q-#goULt2VTAgxQbr!a?OZk}eKeDBN?5Ve&oUIZi9ps^>g~v=#eusn7R8c zsZD~vEJdYpLd!DKSS1lbMLL?RiJF3mOs~miKD1k+0jGeRb5?+>E`ph?Fji2vQQJxg zivD=kt%%c7Dw41P!`eZ{F!>AJ)oIEPw?v=SiKq7kGoF9`kF z7pu?2gk}6rbA}wU1a#VddXFevw_RByuIxh|o#6swRm|T_=Cf|ciPv?zgX)E?<;FX8 z@pe=>zqVJ*FU5W}6YlHtTjfM28~8-$L6Ya<#jLmOGxu)8ty*@qUa+ByJqQj|uwiME^ig4pr6}x5Uyaju7aJ!^YEV9ei2W+%Sb?4Z zqr0RT?j|0}oo>!LW;RV_D@DtNiDV(06_SA|%$_K8TKTDBnj<&4Li%&(is^L55D5+q zc;;jF0T?DZgsVENxqLXXd9zTUPJt$2taQoB9PV>E8DPD7uc?^Y7rrcURgZ?O|^3#!IoySvPIdqFeAc z{t?0q9`7nRDLq>^;wO2v(zAXY=wbM_8|{17duMqCU088+^>^t&Yhlshs^{XpJMU0v z?a4e2P!l%+3y2N$-wfMSg>*99ag^gw@8JNruf({mdgfMQbQ9su)_ z$8O4%rjR zXRQB1VWd#2e${2_gCWw>582n02RnBNRTy&gJw}n$pm~$ql5bTwS~htBosk0!&lITP z3hz3UoeQd@aw}AH7dIJ8Xsec${D2^(aZaty0TWz~<4yW8l3SybbOPWaD$iga$f=dJ z<#B-}EC~q@uvZ&&5W2LQ9Tp_x4{2yRcyv+aCti)tJ}Q6V8N?$sq6j)A)4hd1T5P!{ zyba}TP*57kK^}RD4n1lyifNXhv92*vvfl&1FQ8>Zg4bVW=41NHK;(KoVjUZCHM=bc&74r3BH?+C~LDYSEO}fTMI?;y%ePIt0Xat9`PpTqWQ~wBR*~?=11LG(uuH?nc;V-gc-LHny`< zW5*r=z1>=HM+A!23k;#IOf*>cLTDXJeyLP|!p@sRe48Q}mP(676dJ2o8m@aW*LPa+ z-v;Lc&dkG9gEeTw5(k^-`@ca;Ld}vmmEF$gR-3;pc*BVPd!K5!{M3%Sq$5jFB&T zF|ZsRb)H3dJ0kGZI?pP0N2n!>27he>zu|g{@|8omuU;C#I9yj<4c{{T(Ev||9j)6q zZhYWH&a5i9u~7n(s2_imY3LqruD^;?x{AQmDO8D5%M7aPo9@8EVC5Uw_ZZAEYND3F zREF!@N2cC#TT$3CQ$j5*6juze&?f8)Va_61sZ9csuRy?tjvQ*Vgl9wd?d4f}3X!6` z2Q+KVg4F=ge*?k+CPvtV*#c_6G#&Uipb-NQ8o7ipHiRrN;^A3M-hQ_9@ApPK3BNb2 z#v{g23EuJ3!}FH{_&3dtn=eGQE1DU2Gi~rPrDwHK@}=g!#aV~z16(Gz{dd~p-2ynC zJ3Rdm^w+P>ea;Qw+dR@qxe5$~WZh5%G-OozI&X>o_9k`IZ^UI{ML%)P3wan}x}}=Y z>O$}crYL9=+5roN23@e80EWGEiP`nMXlHsxa$>Itk!zpGYi@QN{rY3$GTP_zFjE59 zEA6RF%hRY@kZc*FQlyqeny@uW7=yJ{Rl>vUIYYznVXJ$Mn9R>1m!PO+Dn(yylM@rLQ~aPE~9=}l+1yN_>vkY~76WD5z*zyV=#Bok*M z8ic1EfQ$?qAqDzt0AAHagQSQxyRPUHstANZp8#=5S^XNn+n<=;iBEX;q8=mRiIYw` z&<)8Hk*3#%&;@GQgZMtc8XR<#h_OYuZjzV9wF#mdsmMr$stPg3-PGMzPY2sf$}N(D z#JQ9yXY2Mr&zyDoJ_JNd8$bn}YB+uC#JR?@1+XOV5x4WSpEtHr#vga4N7miG$Uai< zRr_R?*Y3bRC%yu|gt{%P1M2W-%;;BYT51ttS`ksx@0`(k0P!OabPO=l7S>O?3_O107D#5lP=tN3D4iZJjI&tbp@VI zvi&IIaMv7umpx3s=JRSEI;+_cJ`3-VLX#A2Uxl{MNZZIoe=*L!42cb$nB$zO0 z=idR9*U8u4e)>>OtOW|2!6#_y1YPPg6)il-$w{g*R&U(olTuUv{JAku*S(msCQ^bN zO*!6U?%Fbs*Z_|pq^S0t-WbPUNMj~@^JjoYP9_43TG@M`U^>A}0YR;2$MH#IE4slv4;;}FgWRks@1Ry6&DY)?y6Vm~38rb8s(PK#wNfj|JH!eqztoTGY7jD=O z4&+mBDiqx$Y%Cjvv5&NV0&39H$oG5 zv{cJTT@0_^xk|OO_JbpeNB{G7l`DI=N!a97~5T75B1{&)3S{#cqB@#v%$t0cKi}+3F-H_RpQM` zVgmP1&-bfrIFO{7--2^j%J}o=RuLFYPKe*<`pOY@Jh7A6Mob$igt5|q!)W9>jokF_ za4P{1C335g6yVfn-btK=h}egMbK<$IXexZzecfhi!FecZ(w1xS1YVrV?AR`In_t@@ zJJTQ7XQll%D0BuZW7KC+`qc@2525_=Ks`lh{7|k&M23nO>J7TmU$K%ft$|xpO|lh{ zm>6NA%G1UIe9cgP;W}0m0H~=CobMxSRoLHR`%}y5L$?Krie5{%1^t3a_2-6Q9LXfC zEA8J2avKqW4OL^oka*KC{Iv`*32Sx`*x^-f+aDMr1$2ow0@j6o^_$1{;O8^GLA%!~ zeeIw>1wAGU(5}@BSQOrtER|qhM2N+jx`_h0#b!d6<)F*~4X_?bI*Sw;WtzOACk&Rn z1J}3=EuXGTq|>4h8SpIRr9{I|+(B9fR6KnA8{^6day^}awB$BgZ_D)$6t(SQf5D`|IXh*8KcP#4YFA;%6J{tZ^<_{X3Wku*iz^2VvhDOXGWm`9OwOxj};S+P~j z0nir!NB92h^*1yLH?ksK5`S$xFMv013N9OR9kLwAG!%``r+zM)vXW}I{puH?OVH)e z1T4toz!B#7(-LrXanSB5^;Y}ip>^7T(9L!wN3mTapPEeYR6cDSg^Qz)o5n@isB^-Y zmGos|?KD%R$CrzS=`wj+8xJS#I6yD_#tu}j8g47FT;h9s<7j+N4x9a2S7kN3C_5K& z<|)gVLK+IySx&lF+d_ghQ=89a=-~ck83Zl${a0$AVFyeuvWtXNO#DWYO5)^>Y9+!59BXmI zrUC&uB(X{&0+=|qFH@^bGHebYhdYj|CFdKRtr^SZU{HpSDhY~urqBRuz1i7sy`hPTmq`wPi(=L!=+oG z0NIa|m4!A1%h5DM3|I&5S6%mcz zCJ^b{Ii2*a_?L%P-`=4LUKZDooy(OIzMJ2%sW6+**fggK))qv&ynL{e=r^X{;ft8D zUFfS?Y5EFp4b`LDQIm=(INBylKfmqkY-LR~NUb*RVz{HiI#myV%cYL%v#G;W3n5F% zNkIy`P9Try#x2Z*C9GFM3$GI#L-kR@LG>3v5szg96;&`ya3W|pl$Dg#3_+jH0fkQs z&FMDBvv}^c#adLyYoK&@f=y`cCq8JnSg0r4GL7a1y89V><}G zfN}fA`J5j29i?6z*~iyp@_IgJ2grY(YwHNA+!$pHZi3ALBXsRDQFfKzeiYHB_gup| zEr?T@e(%eE-hVIM+l>dB1TgS#5Gz;tzJw#Oe#MEfmgP$%NedNC%cr%*mc)F*zl1puL8rBeKDcQ0W3#ykgNrDDQ|Np7?E0qLwkhK$77mOgS-oqxI-W&|gHS zTY{)+y-Gm0n^FvTLb#7#cZNjKByPL`(&M+6^r3Vu?~~b22bY5po0e+3y3fq4b~_fG%^Mk)V&lE^SuvPb@JD^xndHZ8P9}#} z=rXOc??jk=@<4W8MA|SDDVKJr;kF;tXfVNnii(TiZ}JD2Ae50o0hAFcnoRrFUHj*> z8){TnoeJQXNX1pLgJH6rH-K)LhtCX};Gok=3=}F&1N)?pdJDNCgGVSSmCDiSJOd;5KJ~4QUpt@0gun4r3Mf!O-+zYo0wPzTA{QL^>}K&RKjD&?qPh?C+8C)>MSLi?89FoUQG(K=3&iX+mKfRbz_*#Dz;yAc4ij0`BBylbk5yC zQ&2XyL6~b`x|6npuAq8|C}KSeC6>obAt72=|6o4@u4PJ;TYEg2%8BEijCdt7XHs7m zZ^vIIj;?D>`Mg9%X4TWO}ecCgIXz*GtmS_FJ0|VYzuLia73SemF#Mm7l zfzM#X&JjLbd^umX664He)zn^n(>GZHG}8`@M;@Sah46J;f!89#EjELw9moylb6fB&WAsEwaU1^9VQ5;WkfCHl~jGx_QWgO z1}UO(tn(US_g7Y0krIe64KC{{l zOlcWJjy#kco5#b}SX7R@l-cZ}g_Ljx)pU>o5^Q8GzfVpFgVEJP=C;oKJD=!d9`Y$r z;v)jv#4RNK$TuGtx&THA-)4Gck6UF?2r0_OW`V9(a(byz>{fcr1RZbd@y;ujIR3A1 zyGIkFC#EoVnDA5qDK0wRZWF^EH-R^1swmP0^Y~#Zj3Rtm)H^8LrC6*{->$fgD^(HD zq#Q-Bw=Ru-cWuk8Sa4uF>1Ivsx~L-uutdAXDux+3VEQwqctH=gpOSnrXdm|oWReVg zG4N3PrhOnDOF3vgi$jaN5h85@5i?sY!jYb-K<)uAE&Z^t>xkvFn9FlzFl&_hBz%z@IOu852h@hF>BL zB9c{K3@g`H%P}D2ER_Ec0qNL`rs_8t`4J{4m&6%Lt)EeI3{}-Hw21pmSYozkCTQY( z2x(Fyn3g_mI}MT+Tp8&SR?VL`&B+r=GPoX-k0gh3PB1kIW1)kwE#{%Sd_#Cg#0{}k zF*cB~OB^y`vx&BdoNBXdV-aaCMez-x97efBS#+d0Iz~o515vk7qfn>N3W}|iB@}DW ztNYa}9h2cg8!XErbV@k!=S7{VI#ZG7gA5@K6-0tUgX(Z;7H+Sj*A&m$_-5|+ncWmF z;2lL(g2@A?RUAaGZS(Xv5gkr0y`edDQKpd7ee)2JVnTkA~d)1}P`h8PkH+%QYfyYMYb-vn3{jD!aS`NF; zaYGt=g!O*B28&9ylyf?_8V@y&|8{w_bDY2bagDo&RLT~|ydRO?oLR-pxo%XKDpXx7 zAxH68Sqwd$bhSiAR5eFs_8DVfvq@0w(NurrR?e>W`*C%4qV(zrjb-#M=|$+X38#TD zJIP5DfKHDe2mag7u6KGoE|iu-^KLY~&#_2{INp(%q^)g~S_+mb#gc6N9j%hh*We5B_!mp&}ixu%gRl5S>-0oq*HbDu+mOtpw zPtIsb0 z^9!g?96$}A2mBBM;C~6>?Ck6B>s%EZkmR;IZ_DxabRTn_ONrN)l4wcNG$!T0mp_vdwkt-A+%S0T3U8f@)psG8eg z1-Sj|Gq~GenCoDe%b>XHp!nCj+u*44U@d_*W;P zvuB~RSE2OBq4ejW+Z(WU=b`kcq3kY$pR2I^VmF^)v0Qd*{{gH1!;=0XYZ)2XS^o>G zX8eQa{!iZai*t1`boQ_}A)xqlYI+ z@ty}{creiLyItkDK|ZGho-pE}qkR#=)YC)~h1Z6w-XzF`PR zf%Ww=H;}CVx;7p3A1(Ar5Owqo9DLtYE73E0>&Nr~>Q4rWGU~Y$9+l@MzK+c0%JNBT zQ7ZjFYNaLG7t1imOOdH-6S0YJ%8QpIOzzS~5w`o(;AV*SYOqPBAr_&w{5U~r^1e|S zuNG;S{V7bV3B?gtt1^r*8RX&%Xv<=c^dFY^&t>_GoM&SG7dOxJXEFZg0{_jx|6}>& z3~avE`u|?nzi4Wff3)}~OwITOq0=&PauP5yaIz3^FtPvdEH%Ry|NJ*g{nh2)SZcO^ zLDQ;V!=qQ1FtIQ*cZOp53QjNRYW5daPr%Cl#XA2DP&51i?*CxjViwjWOaxzS_Mdy| zZ-Dx*ihs@YpEn9K<6n*b$x|~DFmtf|nU2N(`?l#$^Kw>RLLKRKy4sZVj|V4!FftxN zKum;yK=Y8CBRMdM20V#gxR!xPl_21ertFspA%H3=NiIbxFG=li7Ku#Ilt8oT2ND{V z!dI7~Eu<|`jW@NBc*(IdHKA=#{XDysyS%!5zqng{%67Wq)o8MJpyVpRq63?$Ojm@& z9mn=KVYM1B)StTIK(rT2Rhg*>|1D{CVl>lrV8Y1nfnV!!P{M3F>dkWZ65jz#u(p+v zOIwN}xosK}DYH{ztXo6EHcB^PqEZ&;8Bz!5^*X=T{4u}J^L>8T=Qpp<_w}0hjA^pe zfXTmZ;D6D$XHCQR#P6(;9mf(>)XGqFZu!%P{~GMBsLRZ7ECA;mvI|SDVu#ZJjeBsm(Qd zN6I66b!4kre*8)0iD#e4x_6AH(bSMUmdxGK#(Uai&O0J9Pv)x6A!bRYU)P^7$dC*S zSge_jwtL|H`_ZY=5!W!UC+A1-q9GYtn^rn_C*I0*7hIKF`jD$Poh9?Ha5mM2t8;hM zBWHa~k4eW76ULh+yc{dICBlp1lJDr};r&nCv9EW%4Zj$012J_D7e1skzj9aEvs-FNBB#U8b&ziH4q3JZA{ntU=z-&@!pR^|W=T}63HtN}PVwHH0-nyr0S^D{%uxxSXWTuTAJeBl zeO=~pJx#v-p;bu6>tMNepnui5L3RA4w$v0eo}=fiW@hhi&pKr>t&Gy<%bTS#tT4u#pf;0eahRH2pmvcdMRSK_LyP=AI*@Fsb^>_guj~IcV>=#bL zLAk$M_Rf2NN3;~Nm=slaraCw)rqcjcb{*vD(!uCA=?k{8UDNPgL_=>%Iy@&`9A*M+3$xA1arcR{j%XGU$(IOrx%#J)e76>* zq{~!?haWjd-{+`iY~R|T>!7N$)qr;r=PIh?HLVp{%9X;-5iGR(K4{QCSYP!;=sC7c z%~XzU7AMuz=CoIiZP}mvwMbPK8ur!bk?MDM;JcJn*YYBhPoNTLYntJR0i)rh-mmTj zoEn)Wo6D6apA=6DUyQ_g_R&1zJTP#M(1>HWq$c9)@>^2+M@~7G1 zyDr8&Te3k#L63#K`sPsly=l4rbK7=&N`7$XBa;Um)j_|`u?J?@#of>Nsiu+R{MSK$ zWq(1@ztZbhTxpiI>Wtl1j>DpCk?W%Ft#zd<5 zRvEW523~=zf~eEJd7Xk6+LTnx21~~x)x?M2zIt-KH>@L1)OAf@qia%-r_sXcB9^o$ zn+@G)mr9dL)=|!QH(q-*;jkV)Q5yEMQ{v&vnSsTE#-k2rhuA$SKh&Q!950kbNS=kb z2{rP5NifA_iwwor32m8}uI%KEg6EfSTjYY%t(p`0MjQuOIRi9kIn*}WZ2H^UvGeVH z>Bp*$4O)e^@_%eg6^SteIk9z?d9=EBlmX5FH>0M->x6Jie^U?0e{*iKx|Y~NMMdfj zy??o%yZeR~(^PrLGvtOtZ2E6$npY+r4+b?{mu@I@AKH$t9`VqKi$_8~4uDFCJDR69 z=Nh#8MJh`|uzP=1INTLA-9ii+=Y*Tq3XIGC$Yzi!E=gqO-mm)!m>r}dmQBo1@xhk8 zq_mUGHNBl6$c)m+(=EDbzAdZnUg6yh<3~QcJFTzcuu-eEf7UqwJTbGj6~(P=$eocq zUU$W_z4pcW`U}Fr5wX&)#|htxVvuPThgxi-vQ}jcVE87#hlkcx2myTK*n1x_!bG4I zff2W+4V$Se!&4Jjm3=jhT?u~b*6oseC*G8nTKoIniSIQTsPX}&`ncV%5BXIzuM{`_f)8EItrIJ|C9sTcs z5R&dD*y@RbjntVjs;h$CC%{pKC z<^qgpQOo;@ao<}vvCS);*}M;#cV=ibZqb@SnA(ChGo**okfBt%(Wfg4Y)}zy80=4R zbVYd3Sm6w22;{ktXdDti_!wG7FoLKEG{FXq#rPN@oFn{M>==a8J{v2@Akm`OpPNz; zg!4@~v1l9yE%Nh~Mc~YEpD_l7CZdRF6b6GMqS0O`lmYbm9J!b}7=D%(ZKXHj@ZzWy zUTe{RxiQ#5GzBm@@B5utOlkxLa_aLuqzhyOA%o6lLiLaQ<$N8Q;XcU6Bd`l-+@1qW zs-g~CtlQC|Bbh8}I0E|-i?gtBvN!&$E~Fiw4Pg|EMu$K{EJS90DhLn&p!Vp91r2%+ zLivTFAVNNBXe^oldCR35h=p*=r5aRI;E_w?uxJ1>;mb6P0^?k&ffzhA%Ox6?KtMzL zzC>H7E!6j0Fp2BrER4fh+pJ;t0#v4|;YnEBgR& z|1~!@%OA>>STF@r>dJ_LjuynNx-gk+h$LM&nYJNxCIaeBk)7M_LwF-h31loC2T}6@feU!Cg2HXu>T*jkidttp%10`LkM8;XbenG&)U%j_8%VMiPr!C diff --git a/examples/gjf/molecular_dynamics_results/guaiacol_kinetic_energy.pdf b/examples/gjf/molecular_dynamics_results/guaiacol_kinetic_energy.pdf deleted file mode 100644 index 364313fdd3cf7268b2471b33097b43e8e7ede54f..0000000000000000000000000000000000000000 GIT binary patch literal 0 HcmV?d00001 literal 43676 zcma%=b9kLk*YBGqjT_re+F*x`ZQHhu9ox2z#(02v@&)uAz=D2 z$q@jAOf4J??LPi3bR7%@4E3!I3<R3(ds=pWk z6Sn;fg};&ShKeKa6Fg_DRaz7{kuJt9ymxml!h=EDxdN3+7pIg=!6Q6BLB;+uzj@K? zVCuvO>#T8&%V6%*N_kHP?k$G3GjN}d)$TvEtzav^-zDW=o95yeXXXHY#pi0 z4VZEqSQEssm#6R?uV$3Cz?M&zm$$QHSMDfGp=ujku^ak8dOf8cD!GUBx*~+ z#Qe5Zl!?|h(XW4GLxZSv_nBfWBP#{LHa;<8`n9Fw4RE+u%zSEt2OW>CHFQE@6m#@A zkQ8t#Mi$!ZTa%kt?5)E*Rym1GTbX2)B~o@kB^Ru1$opueZ=q0QRz6k`k*U^#=Jp@? zYK{{FUG6xwS6Mr+3Pz+bc*OxD9ODWhllAed*(y)QSV_x!c zm0zw+V^ZnD!LfP(^)pYM6sUmKqj6hVQmyZ)l}>W~_(s#^P^Lgh^}INY2A(-Ln zu(7>5OcSmlGBX=EUWgW^mUM&Pc^__I?T5JrBBuH>^-!K^(X&=!4gqhTc|p%VaT#bV zk;B?%NDrAe_r>h6s$0zEADPDK2rw1d{J^%9FVZj|*g!pN_lh_|tq5`*WeVY4P-6TJ zi8;P+Q1o+Lq$9|Jb-`j2(h{O?$v$ZOYC^g)C?FgLJKLA_B(*O_hKtJfpB8~rl-3Z@ zNsriZj-UTRb)chne@UUj^9qyUCr2A%cZ8xwJKGma8~9a`Jv_r^GDhz5p15~-yQ)Ir z78}2S*Ff0-!7&qYML6h_qgWatN4$}w&YGhtBXuoFF#=u0PFN%Uom_&#&^>e|5x*ya znu6rf>2RGpm@R%W+IE5&l;@E_$(G{!MTv1+P4S-gkkT!8amS|OgfpoEAvJ_USWu;z zG(7Z3zD4-da1q!lrXp@z38tlj=2V>AcV3{F;#3J*UCCl28kJDv)%@p5GhXYtQyW>; zmc7+Us#UE^6ya%9m6IKQnj+&w-HPfYgtAzgNlruv(6V#zR4VYF-r>_iQtJ>D`H`i3 z*GK5gu{3DBobi-3T2ppj_zlvAB$`AeKB6=ZpzdDGzhHiX7D^QLnrcXpoRC3BMC0a7 z4xh6p3OZ5&860^lqDKo%Jd>?%1nY3e%t*Q7&!ShqtBFBz8vUplR1+Lo#m%^+;39!X zqfD*A2*X`9NMX+E_+i5uHfGO>3tM0t!h%rQDz?4qPKhuh*HKRhv7t^bLtNrcyuO6R z8DjkNP;xzRM38(ff|mAitKUZ)VIz_1Y+h z>v=#qEA2c>!{h#S=DCq~+5757R@!DHCsvNsw0>puIrYh)*XNAb0r8pPd0JFdz%AR~ zXR=SF$nj@5fgE{%BLA8_`8Qi8Ea6}gDj3LB9s#5)LoIAXUJq$!h2jW0f4Z*CLc|u4 z!@QaF;4?KacIApM^sIhsOqs}+JQ%Nm`zr%`Ka&}1xY$S{Ld*bMGJIPKb3p9SSO_B-#I`<}Z;UY1xp@7jkecg(#2JB0ks z-7Efq3qP0$P#79~0Fr?piB_++<%JJ2N#bR(7C9o_vwOKGTE;J5&5pv!Zz-z4<4eos&^HlJr*Lh z`s)!GEmDL?$#B(TI)OK=l=9%=i*SvN=Pp(SE1cTQ8_zm{6Yw2AZGmCf5uS*c`P<*q z_aM;4+a=jr&C+A`ZFF|=;1tK~EkkC%blcsOX_RcU``vYIChmboZWwlnSo~#j%l*Na zvoOg>nP`{!>aLUuy@9CJQEh8q^}j~E%}h##Q+-eEi?p)i&m)U3D<4%6G;APpVk~X7 zu8RjZ!Y(Z;mp}`OzFZB(Yar$PJX^ckuUUXs-5@Hh*AT0jAJ??`qmXXd|L5~!ilxB* z>&oa4GMfZ@hUH+bmqqrFDc|*saf@X*#G}PXjF8l87JNLkcOg!EE#@K}?|3S*yygy} z^vs^b^RUWyqqkKTdVBFU9?zyA|2xhm6&^*+OEly5o-W`jNK=*rEcZ|d|JM;rD%#w7 znZ&k?e&+LgFO8Si*XQ*LPtJ<~xR=7mOXnxajl&x@SU`7U?c@G2kX!Th?rwEsXRdWV z5AJg9buJ7vCz5d!%cPi1Z*QR)mV#hJex#>~WKN z+#1rEer1-6EofQg+@}=LVWaWFUHhZ+@x`C~qKm412WG^GGNqGfJ`MgEFFLOk<;zT- znC2k4Cksf2)f62hWNp~Uokw@rd#C5~)79%OsKmM&UnfCV8H=8PoPG7OF85pTRCdyr zdP-;aYV$>~Kn{+#@F@n3hG48~#A9ZyamW6m+32==GT9h)zNH7&XG|E8xw%}J?dXz~ zt?rZw6%hia7h>$I?Frl77D-o#P~b#78lFe@@9%fAqE>Fu2i}|~?yGEIbQ`a~L(%bA z2_`lOJ!^}ixWOW|U|n9syrub9tkSM=e1m(^(ep*yB0(p{mV4YQ_z|YC_@9HGa9F?| z8bjt6;XxW{Wwhz*4U|?3PDyX|VZKsF3C7Zk5IzK;XDT*FbCygx1c=|(%fAH|nKRpw}k3Vn!KK}X$7BLR1ONp?X9ogJ0sz0Yg|(f$ zjjp~S!5^sQx2Gdu{_CELivS?#>>w=f@By@c-wE5(LDSLyGq0=oa~{ePi#x_{xi)JK*9ynm40>d*230)|ee`i64CeE)Bf&qxF+$S@}i=cwZhKPF0d=B&{a}xL>go5}@$w1*3h;R^*z90&WpRe9L z)D?nEf0wL);O=U;In;SM)Ad^F>wxO|;(p`&qVc)Me9I@97hkY$2Ne)+#vB!tv*Rue zB;=9a`_C8%AaE)mzc!7Gz=R(JKL37c=S)c{66vqKJEQS7XkDi2lp(X9d-sYVV&*3S z{{$^K`-8)i41M==ynJmRCjC3u@J+%u`an8*v>d41GNSF?N{hR~J<8UhF&Xx(bHwE{G%QnWqgn1X0Wrw z#7!M+BrUpkrFEhp2&t-Nib>3AInL>+>fD~mW9Q;Jo~QgP=b-De;w9P1L?&-|rs}%I zNg1FW?b98JS{iO`M}p#~I!kb#-OV!TbAnG-Uq02XrC;L(T4=@gZo!hngq@sN*n?!5 z(@-8TKWF(`4|fK#-lvS5Ju9*QMCbM)7DZ(+6x{t;_)}b9bQBgYX~N+39^rla7pv*m zP!Cml)-UwSfCEL@gLo+a5R=vb4j+|h8Utv5uh~s6j349>n4THtC?<~DpF9FsWtv1G z2CX?i@e_lRSaG|4_Bd8Ypo1RlXfr8~skD!xcYWJ`!iUiawc3>6C6eE}gN-tmV4d@!dCx34d1kglK8j;VYJYY4vTnnF|dFd8F zoczpeKK=G_odlEe{b2*H0jB)xs|^gSw=fTMV3#;8$eNESr0)d+YA$a{G+I7<3f~+8 zwi=`hKd%f63TPjHNHjt$&*LOn5yp4Fk{o^+&KqI}tQJU3zo%@7NdiXjR}c?>#N^L2 zx?dMQHFz&pvEx7rcaLlcIHRURp#NIl6l+4`f@|zX-^9N7L=~Xj9S6xX2njkRqymY3 zDZm%4LIQ$FXdXk9|G8K&H5x7-yE#H6#&!o3JSayu83U~!b2~^id{a+JcTP`?b~af* zSxEwY?}rfrgU_RHf!=KOPZjbqZYQW8h-nejy-GS!I_gzP)u0QyC+s+I1HUl0aBMuA zFf{0`m@2>;;pf9!y^njoZjxO(w|!qjIroL{vcJ%CC+vXs!tugekHYWoB#(wt12gx9 zCrl(Du^>@Ez=GU|eDz1{W|Z|Ql6D{pL~!ZV(EC;$xxm{dibEz9hawtCf-Xn$Ev3#! zLDY;$lZ=zBoiJ{Q%|O@=LzPEMx`HH&K${dkmRlyCf(%7k3`dY}QHoWpna734g}*@V zYmwD&m6GI^3^nO?0S_?`fN&f`(sk1IP83i#I<_UlC0blz=KSZGxWm31{DbxzC__?1^<9cxoL#Kl+F?2HZd#oO206@v z@VM~S@ThCXz2=GSiRB-ardsc9-x40bTYYy=AWASw07-}{kx;arMVZYgu`H4PO>0JG zrfarn_B=~d8Zl8g0nD7p&}Mw!c?mkIY6)>|dNRB1IpREu!%D^Kz{12*#7bi9XTnUi zN*zkwP2Fc4s54Q6sRvWrRok!EqD@FS8&xnOtqo(%DX%y!q@Lo+UoGV<*DtD7G0u~! z9Y@xTrBP?*ZPaL#2l7da15^Oom9pnKT(Vi^S^1s9o$6l0za|Nmbi#Pkx{7i_b2@c1 zb@Mj$iA!Qir@rT@<+1m(=r`DgUUF@#lU0Reh{lRW3`xo_{9aSgX_=^-fHmJUA!96M zY8}X}T2WOk6Pn9r?co@7&vQw8q=exNQwhsJTSe2RI;E1QKBmG~{igaw#j@_G>Zxa` zH`QEI-(w)qY+Ju}{O9UkeR(nUx>M(=2Yae!)hb%6RO`eY+#S&~*)tskXOMGHJKX(( zgA+xozsD@%@xf-(_+|Ju1i2e|^^9oYdWP!wxACvzc`&f(7wEsKG3=&nH=A(mVrUF# z!nK`ka(*i=Cv2-7KaEPxN9;TGTK29ka4xAXay%#D#s{S zHpbrTotvE(aq9$^~DEFYm;dFM*Gb7!tWHo0mTHXiTY%ZK|}R%?r`GLr0DGF3tKTginW%`??oze=j)#qpyN>W4g4|uaD^YQy-3;6X zn~!S^dXC-ir`(UY)O;{}i2+OUukoJ}Nb1!L(HE@{MHSutEX`ZL;aH=6<+D>9A040f zjiGp|c+Awl?xAjmk5o6bic*t-le`_!!vy-}GHG(^IJ@o9!WW)q?H12SE3w-HfIx~kW516aa zSZESrS-^EMANVjYJq?uUmz#{g%y^t?JM*sXgE8=WFJZ-E5~GSBJCc zvp}^tT{WsLH(O33(we%}8`%ook|te=JziJ!P<~t;z4Je9FSsjs25vY(0#{ZKTdq}7 z^i;JLCo48I%Xdewa<3X&l}|d9bk%Kj;7y|pqUz|2YTCsr&4gzQkMfUvu%c4;+K=2C zPcxPVmghUyExl$yB0&2fxbRSL+PntuWz5TYE&Fs=Hp_Y@j&qM%I*q-wy#!80E@LKy z1B43(x}zLt*?-S77cs~G=#Gf(uimyDuzuaR<#$6aJ(OX{YkmM@A!NPW8hF4z&xGYz zbP4q+IV6A0x@(wJ3suXRTbT=K$p2yLCgHYz=slBxJB~}uo%Zg26MmPHT03kkJ`ppH znx4j*1@ye)>kqgL3qcQJQ+D8LsoR;(sHmz~8}Ui1)Vgf8D_(AYeo;&+HLhUQWcSGM zXg>{njhMr0%}mrj@iaZGKeuc@w5fef+%Avo_~Nnur1=b3yKC{-jeO6*1`Pv$I-}`u zd)HdwJoH$5oq{Na*Ww;^WqCDu)j!$JC5M*&o>{_O{yO_GZ&ciVbCNx;Gf^9C92MBa z4|q>_td#EgGEqE1DO4wPBwQ{$5&jsy>RNr%cQF#4G_xJh`R%RYK4Gdf%MFg_rHGrKUKkB4E-wwK9K$2bo+<9|JXhdU6h}nPuJeifPn5F*4O-ZpFha` zzXI?d>0tlgiGe?S@A!e{bOZo#Qv>@C`u~UDHUATn|5GOX1L6F-4!RcB#{cLN`+o_N z|G@A+RR6z5@mBx<W84ozslpEdvENmf`;UQL)%-o;YS+Tug4SSwnY{ykHt`?rkvcSimi{vFJ} z&gAJ>KLY&!IF#3no-perKcauThdoDS`pP(c+nKaltb^BafaPNdr3-5F5N?&s z0fqKlf4Q;WDQIulVHmtekqE*}Cr`71wx@^Wgv;#Rgq%xzVNo0lXM-NHX_UYmNYwED ziTLSid@z3IbDA->>k8UwA{Ci5s09~5Q?Z4$AAl1>e-a?4Gj-`$$<}d*$gAWquXg95 zHnu3{hR)OXYii__}@M! zzo@_;%b$1j1pob4`sgO_V((yRDQab8{r8SU&d}KOLl3(UQ1E^zU&C(%0BJh|L%TmE zLGkaB_%O;l+SphaTK*Bgv>%m808l2N|CfjqQ2x-9w6xHFCFY;Xu`{)Cu(l(h|3_K= zS5f{Q@Mjh3AFA_@@}whRWMC!upF8L8fd6xq|KalQ6jHjDA9C=2E5DCR9pgW;`)?1v zzml7p?gujgH9afqM|iA^1T6H-AN4Exv29HCd992s3_lhE;QdqQ4g}1!AKUMrqIdXb z2!LPLM#Rw6*u;V02mOZ-mH)_@(w`A3|5%|JKb!-2os5-D4gOp)F@I!TQrG#P79B0) zNAu73__%ZW_#X8CZ0Y~V#2>@ISNg9V@iEKa9q~_-j(~xck>z8)|JSY6PCJZ-g5ewY z8^?Zn3hS>=ps`=Y?0!vMD1kcrjOjJO2SX2fET?Wpevb5pRuA%~@sL!Ek zHdLNAFa?Js7F#Y?c+9WTF5fIS1THqx#yoarF@WaIT3J3npP%0^?T@lfxSVB8JU4q} z?z@j;@<9=DH9-nA+Dw(};#Y>M^Fn_0t|aYjX^XA0;XCi^)2PZ7dP-3W4|*mbT=_U5 zI{F;_+DlHl>)5v))hW+2=m)-| zOF>Nqlgu)2IVps{_;av#oTi1*@_%;aW2TFIJc<(>3LUQkS`S)3h`b+jWQHzpQ;vN z+6DU3MO`uG)OTlDT!eiq7~N7)+|p6_JXLCNj@Lg3L2E&bJvbC{rF4aDXW^{wFiQmE z5$g<*82M@*((JK!V&|r2R#6do1)fD=xzd7M;1vS`I$ecLAK{R#apXCxdOWUi$kKq? zbURlB?T`!@BYg;C0Mni|nr*qm(Va;Oh}KHCAB5E-bbGX-7g-~Hwp|-)4?yW7iGQ$P zH2@jnDLeJww%SVUdFNe{Y-^%8!+gS69G{)ZAc+EtO$)HP`Z7caxI`sM=NMWQM1wJB z$t@;pjS&+r<>iHK^xj@!8%pZNiOp__YZGf3)RODU+C7`@jR9#%kB{Y!nK3|1>Di6D zCCM@;u8aX5j@-cCz)J2%#^JGvtp7AZWe-*KUxAcrQ3S+YuF(6E3HHZP5M7MhFm!_s zp-fJU>s`Dh9?@N7iA@kIQY_7rJ#b5mme4e@Jz{2)q`$z6_S1bilWIy;7|IW_AUWL8 zRK#0^gFcs6kFQF4L^okMOI2u(?>pUrx+L|=VJ;>XjkaL`Cb?2y9m%bZzxt?)rVb`) z#2t}7fv8q4!Em@AIw>M2NoOQe5ge90BW^($`0A{OU_p^+7flaU9>7WkwJb9Gjv>yf zN{x^f!3-6aTswHLm1O37`oI-I&I`00Qr(^!L%l!AZCv{{)p+l)D2MvNmHozX=Q7`(biE9&Q&Hr#YHA`L~Z2N>Y^0mXwGDIHA?hM^ix>qf0<~ zux)?V5{j%~Q*|H$VOgRs?)STc1TB<)zmxQ{?M!9l*rE3{u{&*s(NU()Z#GOT zqmpzq%0MGHPDzHvbod_1*iT|)MKHf%U1^@^`WeG*l0oS3^+pF^z30LjIP@wEG$JoH zIrfpHok?k}pFqFn^wfYOjnuT*nM&%)+WL)HIV?)jv@RM}+AdPlxRsAsIWAh#xMhrV ztQ$7Ap4`&7`Hid{)Ua#ZktMY+8d}>fs%zeX(meAfy+)6mIV>(~-1X2rBPO-48gd`i z;M*^L^pqm>beWyj)caZ9Qs!=IcwprysJeTVnme#M99B{qmPp;0c#arWTK0v>P@FOg zVdQ(*$oCPmqq~x@ktC%A#WxKK3hm7I{GU~$YCfnd^53a?O3dzxODyNQa|>6?6cxpl z_Wm7oDpbZ{nqI2mTGTo#{-8^29WA zT5mfRWRU7s&$WeeUz(ID9(72F%vn5AuL?>-zl(=TwSH@>>c#i9M@OFuWfDkDoelGE>WSCUtBx1uQQIri?nmuF1%t;AO7#h|XX=&mv^ zT``D(tKW z$kYH3Itw#<2kvln?unOo2gKI&-_24e%bxzCQ1%=n1)vjGG-+#Z)0DKkN3eGqO^S9< z-k}D_)iI^BMJKDs_@uc(2Eyet*SNG0*p7HHV?(hW#YKZd! z1HXEKY$?40<|rvep-jNDH4Y!@3w$j4alcNUZJg2Y=3deV~Ys7K;RO82#RO3yrujlXKBirfAg)it^x@VYyzH^2S z6V9E74M`bCdY4tMlzBaQD7$OLGGIxOO{cSn_ev9oXWHiXZk@%Fb7XE(#>!FCQxNv% z_a^twtDCGDIY+Wb4d~y5ujbR``>JhDm7?V8H;;U3;`v*JQOS2&y~ZL-bIkl0;%y~F zAk4wxwj%mYQMV-96wh_n_BWHpKYM0FojfOkO*6k#$PBtrIEBhDWDO#piM9QrNOk z2pu9DK@jCj2Y&L>Y0Gi-$TUma%G!)b?1Uxo#82qpo=oVnPeu2|hCb~+pnjXrek~B= zXHCv8xATC7dY^NApbkR>f){ImUmpoguMs-JDjSb;yQYqBir!BoBypp>`P5`&Mmfz1 z%O-hvVV#bjy@3o_B4kkawB#Yfn)BTE9SS{N?v@VrHZme^zDm--icM=ec_?fipn?M) zTq{(%9PYXX7D<0_@!mJK;#P*;i=FN_PWD|J&EXyp5=fUrgE+oC{4-N@8h?@eah?NY zI|kj%QJpyEiu%vYNcOUWsmt@>h)nL+6j-dqO#Q$t1Nv$TezXNtINaG=Vvy7qrio4Mi2j zpvo8oei9x}uj72!iHY85{#mqL2oZF2-lTj(XTiWhP>?*xTP^$RXYuerRbQ1$Bi}X% zc|^yO(sVAiu?rYmG1ObFe#WUy`@&0KKWv9nYL36U2ezKS@hHFQ z(F-c-S_;P~gpK7V4lbd#?mp!7IQ>NrJR(<=q@NS&Hl7okCoEW|FztFj-NJ%al&u^< z`ZadPzP9ryihbKj0~&98fv#@wGEjO2)6^cpgptKG-2C2L6TMH;&7ok< ziC7lE;Wmk23`hATLhg7@vY3$2lgI?j(OWp@vif0cs7ti*L93uzHx{8TBKcvXDrAC{ zM!TP9)QDu68MDlfos-%F6Ofq<}gk*11rY=`~`5wVsC%1Xd4}DMC791Nnn* zzbO}22?l!P*Uk;!M^EHMN3*TTg31cmZIPkvN}(xUpIJx!XOQ)j3}Ld;L8&-CeLs>` zX$lTlEJI*c2y~=%CCpk&1Y{ZK8s~~J)tINoa9mY1;t5MkR{8Ny~ZLP%)2QzUSqv;C4%f4%^_JjMuG4+!qER`(Y_ehU9 zC$fQAJk>^Jz+@j>aJ4_&t>?qCYKCwar)ZMqRfLe+2{;oS8<8L~P_uCwZ@#8FC^)=7 z0H5tyVne4^+hc@NF?;H1QRY3v5vx=*5gl$Ws|0uhE&!`^zTj+-4RpJ$F4EW1LdPw1 z19!`P3b}*#jA=jG@SW@6#!q&;sf;>I%3#wrZ}qM&1Pn__AoU{^XhWnOA4U(3u%&nl zP21=s-bP_{oPJ)!I5?TVjWm+v$Ip|cTuSg9gOYpK$elSKnkU0qK;Eg8#K?px27A*q z+A&(tUl6jSla=mPL>FT5@q@sINq|a(j7bTL2tDHrGG3> zwI5)J$?^$Hvb#%X@?aDXQ>14~c$yVCyhD#z&%a*>GfG;f3{h)b0#+_IPRLB}QfFhm zaD@UrK#1ee;n5i$;iw6V?I?0eq__O>jEwhTh{e)(%gEEo=@9~4oj93JGz*A7rK-tD z4|ka+dTGazrMbgB*OUioy+pV*22>J}t-a{ZuFDbkJn zQ~g52lq^IbVL)eCs{i^YY^?YhnV^kTmyKQ)HVT6Nx0a? zLF*y>p`e{gXP$df%v`J^@qw8T2eu4RFFt(}B*{Wn#w?l~$^#FDpXE26EeTwF_=VCl z`-hY_OiTRh`Q#T(7btibo_ySe+V=4?Hf!nl%#ko#WcCbAtmz@*8)$YZ8hH2eW z6T8SR3|V9AV@Vg{k8B+=omuO{=NnmD+B@32>l;y*UK`I3wJ$DjvA>|ybjuJ(B#^rU zQo2w1+Gw>0k;VMQHt}*~O_1kc;GtUm3j>n;U%M&0t^KVwy=_FC<(<`?g&)do#14?( zh}?-@6c5ll5Z;uVNHh=w71G7Z?c`myF7mo>;qwDMXt~|t`M+oht`-F%PqlIsrSk8k z2ZrKQrhn#RERw{LO4D?q?F&JHDC|G%YW`MuebhzBJ)Y5GpLyY^EQLt7vQe6YM-kSi zOei3@8UujQXEkME+9KdC@h#th(>8{zRSkx)o2hcQxnSu#@7mxF{_MI^W#*Z7>V)LI!j*J-i}l`3hfdkzz@1^x?p0Exj|ffx)@k z>vxG#f)$wu=EU?m2+M&zgZkXq) z?%XNW!n8FH!Eof@QC^?fW?{f+bLBCfxmjmtHZ$SdFoqlW(h963{yt17Ed$Le;I4vH zCPIC31gNEqTNUAsn*vjalDxFl1S@n;+j6L(l4JIiC1Wryw=)EeI%M%=+S!E#u+bxA{L++bIQ;2Tw!|GQvv|oak z7+|@vCX=#~bEw6R6cv)EUtBHx%=7Hn204f3!N(%1b9*%pXCL0B3LtmD)%wT^y|XR5 zhWTSMI;a`--~|QLB>DkScu3*y*|<$R4&nyt#>`|zBR;fpP$1H_LLlCvNnpifNG*=ydRq~VJX*uQHTEN&|0> zUT+w*JMQ01PTtzx6Aui;#8>MNL=p~Dj3Z0bDYMq%; zH}L~G7D`arVPu2M#Mu)Hbfza)ey;E6S1n5(kWtyvs_~hpS)16nmlOyx3X!u3*oSA0 z*MR6>ZDywdfUd^_Ps^xUzFZ9oYGh6ocR-8*K?%6JW%=A+VR^OWpV}nwdYoO_^C$Gu zb?P4A6&M*Q+lpS{B5t`~HI|zm{+5R`o}Jx6l^kw;4Rg18FSKY~%d>QHIeLU(DB6=32>qGVkSkU1)- z-KU%8FshkA>ldf{F<%!;=RgqpgYs1ncamYw`6)&6xbbmhqpxLgVO_gFD#N)-X|r!? z+}^UKJ|X%;KEZuL4u0Sl=w#1t%t~&83`nwAM8o@unB@8W^oF=5^2Y&-Ug-AV=GV8I zhOc*V)V+X6QXwzXQxO=QHW70fKsz)bRt^xJG&JJ$HNx#I7PM_p_H`!Wn{lgQw|Kr5 zzL_cA$NpYq$gB%bDbsH|`A$afJoP0+P0Qwr=*}dfk|PdWs|8peMA@dI*;YhO!(ck( zgSILZwCz`kLZ?**#9N zx6M^EWtMkzi66$bPWD$7fM`u>W61(y>Cf%WpZl&1@1Q^qp7rZidxKp~8yCvqPJ6q^ zJesNn51%tQ-@c|#5U#R|trvo|1>2@8oo)%jYe{`X^bwb;Hcvb3HQ!fk95tjlaIGWe zOxy}|KPuUj*|5gah{dGa!yaN+zw)!MWWZ3Ls7pQiuwJMAO!tc`aKcu8joazRK&!Y% z0;f;~XaK|*ofg$e&3V3)_iVHZ$PsggUN63 zwPTEFGf=8W3!Jo@>MXCfINoC~L^duPeIDoA=Sl~std!*XhliZ~Rywjqy^TdLvBgTq5E z1{Pqw{`N*B@9Ij?Eb?b&I5;6wa9n;_AHT%UK^c>vg+{Jp^FF^^72zxpPm6qO1$~IXY7by=9&E}E47d6S`r4pEjX$<@iLdV2MIL6 z69@44(`yih@_l)X+2yidiu63Xz&Z*ZG9|}%(PT-=T}@JLaoP%VER4aI;r76-aN<@u zV$@yesPDTMHlR*Al95H8Ua|6=zNf9%L)riMH6sF~O<*xCgv2-L$%&R5XN=4Jn$t4) znik9DbI1|Dn-Sa$^Abk=NQH;$&!xKzqh$1XyFK>p2r$@dB%%})Esl^cpuLa);>)+M z%sp){zjD8kC|vkL7-_xVUtEE@U_?rNnd%F>(;kF@7#qMIl#Jdpj$0OG3?ctU5@&!6 zqqRvvmLOBmmc$t6RD)XifhpJMLx3T#nE4@HJKvYgmlSv3dF#L`$^&uo$uv`p49UDh z_f+wbD&;j1X1yeLc#p)hLWl#zC%jkhw}dx9d;W>nlihZ+XnIW8hF%lNNw~2scTeU6 zk`-%Xs``kd&2p3G3fI|}GvyWDGwL&-2L8SB84+`DsWb4z{>b^Ya|3d(P*>Xh2Y%PU z|5Zvv9!X$h&mP{z3D<&x@|3+CZFsrY85_0rr6TvO(Q03(J z2y^}UM1HjVd+Ny9G1iqUk}9`bKgS$amNjER`V}v*s0#a7bfu~`OjEP0O_tV?c%fWT z3YBjqTbA997X8j$(fO>~DXh9uf}`60M0DY;8vV|vy(rZ=The7qk_)giCTv!D>*(m+|DN3sYTPpvHI*awQ>RU#AjhkRrsO-E6ixD7DU)_W-8d;Q-^zv+Iy zuX==tKbTTWo`Me)H|UA~_0_ynlNM+EjE((>t?{bLEgoN~KT&rdDECQQppxjiYoomr5`+h7A_bP*0+K-Wo^%r6-C`+oT}WF>4Y&v`w$2A5Q6 z2XA#)h&4j%kZIIcv(+(*=4$rm88AJ>!3btyfic$Epk2Y}drF97V%*aGQ)yUO7PrHP z<4E~61743Tt^O-59Zb4vQaEyf{a6HUu==JKxK+hAvrs$V?}U{Li!8> z;b!MF7k1-ayhSHhn$ZKbbTxwm5RRN!|(5 zg@jp@>HJ+m0Y@>@Z5e)vG0L{c<1wSXmJ?NB1{zKy935q$BuJ%b@OY8rYYCc-J>i725BF&mE>1X`=EPXq#AYH-)Qc< zKe^v2Xu1Zfnx`g>mNFP;Ujw-rk9`YTL36&5#?Ae>M#enORKlj8M&@&bCY5IsxP1wt zWj!%SCedXlq0#5bFLSc1+ht!Lg`YWgWNTNwaXR>^Frcx9$~OZnnF3BTXe|n^V30wR zQhTaHkOf>>eTG`hV_iinqkL4E#*w&!YC(?&dnAkCKMiit$)Gww5mQrNA5>|qJpE3} z)j|=oWc_mVaEx1)AyLr#=KOpu%U_g{jbiCC%>KxLDyAk#Cy+`H2nYKrFPCxI`{T2O zULF^)L50pyP9+XfERzGHg+^uiIK)I`wOM@LWMOCfxL>U-ie^F5EKw?Pc*kdMu5s-6 zjuaF2Fi0a=BsV45s;$XMsZ?|h3dEVC6xo2$-RF0byIQP&2l5uVXrK}AwU6jLtRXF~ zC5(a@ISW}}m6Kg*ZQoO)Q5L&vmPmf=Q?Po;=QWa@y{;#1cAS{@QWz~S&Z=9Bo$8`s z!%CJP0vQ@h(pOp1u-2BP^lxTciOZ28eb(06P6E>w@O8&nRZ$^9paM5%es+jfeNIFk z8bA~4?0f#80UTrM2JQXH**RaNX|fu$(yy89=x#Bm)p79j5_5ONsPYJjDA?)lrF32M zz2Fhx$g^Rw)8wiGQmI6A*cckt>8y@TZK~_QR5O={$Vb)}+Wyd1eZQsDj5XX|Mw~ax zhMKr+nd#)G9*Sy~+Uqm&2TfxP(%;tGK3t6_4~x%UlmLQts&NO|g* z*u1o%=Ye=7@?S zY?E61#b2~N41Ej;RhmXE@m)C)zh#V;`YB&M9jd?>w>Kro7`Fy>nlERTH*(ls=Tnh$ zTy^E@?KCZ%lXrvS5&0JT7V0#^e?$EQ_u4Kle#r1d+Ae{M%0)7T^CR=ur`D>{HW=X8l&e|pjC87X6yY}~l z<`!$&*~`PHwO`Wv#(e4_<)hQpKWZtS#3&!ZJ0i|Em~|uWC_2-;61@VvGQ8rreH52O z52!P?pC2n9MpTM7W8jp`ttNG@(A)#)_`DG)z+mD6(sITeN_G6X$k!Qrd!P+nFh=kH}ZV=oK1>be_R1v_JM z8v@NZl+SE)?@;7+GZZT}Dr35+haB;WX@PpT-NTAf{p9M#Ehc$tT7HgU_OB2g#5R4A zF-+vG`Yx<=-Y{ySDuf{T0r(By4GuBaogW7`)o3O{ zFonx!4esTWOdl;9gjw#TJ7xDo zDr!oe;HGV(2V!Ve(^{Gf{Y>Q|Duo2cH6*(B#JrnTgh|GW-r#?Vx68BZdAW_7vrH*V zYOP(L2Z=viPUU|7Emh>Pl@+PQ_BI!>j7^$WCk;;11xmdG2{|-Z zjwZ1L+`v&!BI&QEQ;`WtA6|`4IWyObak4vp8HLZcg1N4QHPwIV_)+CN9ODqXmhNIU zC6QOaVL8395ao*=kZ*W$E$+bw$!bhrb{RA1Cb+!TNjaL%u`M?=pXPfUE***}B>yXD zcZ|0;->nGnD?e@rnT?+84sE@VT$&ZfQFsIQ-eYg?^$qz@-;h~5qm99NrVgE9Y`OcV z248dB&DEUXdAr4mW-MnEf=6B!l*wQ-AH!`pm*$|@>%C}wei8mV7 zlV-~}>Q!^OELX|GjCI$$j-Cz#O|{(@VI>nBG~DJKx7B=V%2@tSPX%h&y=1F9dV4b3bmQ3)^1!qX^ zbxvInyI6OMoG~wT+Hz0w%f2vCWuj^BO@7Piy+T1b0e&?rIt#WT(Z47??;5^IOIrldnNCZ@5dJ#;2Fg;_MTf|H`J z!^BHTXk z@WzoQCt?;q-PIWrCwed%1<7^tKY}AuGK1e@lVFV6O@iva$@4AYWu2UKT2*vBSR%y= zTpS?qIYF8_g{so46~f<>R8)AHZ{ z9vAE+2f0se#N;}9@v#_@hYaWgB!ZlP7+hGWATHmbuM|ErwxP!gE)>6gb7+GRA#^Go z8KNJQFBRd$lUtMi!9VgWd!owyMKc$Dh%&ku?iSdgu3j=K%_0~QfQ z-sn=k16UCy`-9VkKB?>>2axXG9FR3BX5Mbs6yKsSq31hzu3ZCWnydIh_|+RgnB#_j>QlC^6Ta3-ACJGN~*nb@{H zF($Tc+sVYXZEIrNc5co&|5xX$`tPl}wRi7oy{r1|wb{G-Sxjr;%R-k2a1KK)n-1Rn zyf5lULEb&ugEFmTeBiZukxqr==mX`-0=$wbZR?Vesu3I#J8j;bO|R42-L1)g_8Fr>dQC zrW=FT`h_Hcwz=o7M5KJte4=i{==FSM4I;!8cJaAB;Wxg)-h~djV_M?>d@dFZ{2W5Y zWT+HWh62AO)#no%`y>zn&W`g)RM%AEgMSC>wJ>t`7wY842Ki)AE6@oRPBubOYm;*y z=E5pj6FD2TUQ(|9pzDhF2KB5E<0{pb%Qr&70QkvV00AsMI@Hv>=uL0nWfi6Vo13~Kmh+9z44Nw3p+svCoxUmJF0!9^qPs`f9OpCE$xt>I!GBv`aFb(;? zbu7@4i+Goa8p{M~?aSYDC~x^j{x2D7 z5dykCtXH@+CQ~~$F>u$`cvme$mm$3z>}AK6--_oNU=%&pe&f|KB*f6%9O)>WH9knK z#BA_Q;a*5YGbeBrndh+GQjON!Jlz&AR#8?iJviX=yS~xNji>WJv(%z?SlIK|3FSDt z$&VrdZ*H6&4coO+?yQ_LYOV85c{n|Sm!yL8?v(G0Nc0K+jNn zyA<_1rUV>{<^Q;ibZa{$2|wPhSontdZPW6cv)nMy$4!S7^V~il4f?FEfLv|4qr}rK zKyP024q)iqrg2I%=Fz7gXSfcjRAt~R-`mfK(IaR(dw3p$f!FYn832d=s#ahR7&C^s zA*Zg)gV60|!%<0h;|EwlT9J8P$-^AhS5KIuoloCKM?nCf-Y0>`0I)@%D}q?>vqoe9 zLt5_-SZX-6yN7RvY?4WgWkgb^u*PZ|E(+?!WkYy+YHH#EX(&fD8ak5q>$S+x;Q+|{ z^_dh%?B`ulB+7)5*iqPrxfZ{! z+0UDV$yIF~`Ka|m0k|}dF(1Tg{iH91!EV60l5E(GWQ)jTED zNY0d3V|$Y~MF+3t>gAFFq`S2yC#%Ke<8dpH!*R`S)rw@%wAAkO<{HwoglUc|7}*u8 zx6&;n-I!NS)-J~IUUl!R6;7?T-G+)+a=XW(=HeUNti%rqkgE~c9f6UnLkK;SUtfA? zNj)>|;>;hTQcEf1&#zbxKB{w4_o-#zMh=KF+xp-(ydqC3kmk|{1@dwusQqvP zhRhpsApi=e*CSx{b)PppBw!5EP#}eNY8cR6baKv5x?$0+UCysYIDsR*%B(wd&ek~p z41uqvkGhAkdep+Qqu*SqWGw|5@P~n>Ns-I{+@%SHj)DduWDtje{xc6jih-LY)W-ze z=Xc6i8p-|}&f_p;#tdaJhvp4`16SI~f?)`>uTqBZJ3j$pZ| z@2H<}dWI$ivw7R;nt&|jh~!UM7MnCKrKZ|Z`Lo8@+MVCdJWqYgBK=zrD4TK zQN!>PzZzj^M{;8;+YvtxvI;*37Ty0{Gh$+f*9?u+!&$Un6W#MZ3R|24b z1EiV@SA8ZT*~kw)#QE`+fv9|*T470(u%8AvH>Ia5L-WP$c z4gpNlKKU5DlT&l2i`C@dZsPU?*@lOPh!EXvKW{tb!lM%lz`i`_Q(yfdq)81og<2%= zLQrELf@X16;9FO_=oNfWI&J9ATTg$$ph^0eD|XLNyGsv^9pzFiyvWby@Cgi^ILF5x z7l@CsKuAxSwXD16vW+%~;FP>sbl(3v4YFMKjL+^_Y{7=h+|iC8R6{J!I4aL3>`tz)jdu zSKCISxxF)hK_BB=py5zBv6h}<0I+N1T+yLB74h^bW=KKnob*3Q0Z#SM*{nnQ2K|Gr z#P@F#40}M>B%_2>23oB2tI?0hZ{a`;Pwk3aex&3_$Io3}hehB~&iz^&TemG_3~)!1D#r z!MUI2)KgtuxzNtLWr@bK1*)dCM2pG6k}hfl91EdJKTmaQeX0g11h{B!3fcA;J%MQf5uNjbR$%1Ysb6jLB9fE=yxppY-ngJv)%6i zfHAIs4H#f%VhRmaAxFC+SMd-!Ruy%|8sYC+m(0_hML+SW;w4)*5}PjK?U;9V!9lE=cg3d}gQe$edx!1OjF{yGHF(P3SmVSAv#nP^1`v&+d+MwJwy6_ z%(PA8=5D3bJ(aJr)RdtGOO4-#SgI%RawYR!f%5iyfEqfaO|UPWNp(rwAOGr)!eW~R z?*2u!b_gpHURcI>E`i^ORYY|w!~palu#%kG0Be6dEH3Gbf>;tEliHc?L1;WOz=UOc zw-;Hp+G+Lj#R42YNS4cWM-=qC2mUb|xb<|7t>9IjSwj9J47gqSABenm9FIA$A&enk za_Y4<2o-m>dr?@C*o8OMZs6@GA;)|}pkqt#vx}?6j1k29?KIp-;|BuD$3JaT^FKpo z#@zju*1EGk$n^vu!2gts?~^ya9GQ|J1(EE9TL)|7*GE6Y80PjRa2Fg5fmXA$S&I?3 zE^Op462T4Oi&mQ?i|X6`;vtLyPl5?V1cP>77j9AK4Hh-GM=tgE-D8XkU6^7K=^VU= z$F6)4;<7)7IW~s~I}g?yxl!hdkEWcqCR^nUW-_L6?x&~j92l1AYFRdJp`90IXB)+` zKV+K_&rV4)%T4+bwGvAa!m#9god8u3k75Bz=bv)S<>o4 zg(jr3V~+aJqbSuq8)~PhleOeXt8V-HP#8DPw-e4g&21?vKgEIC9d|$hOcOnEsV$%1 z{cO9!%iP?wK?`xE0U#7^LwM%Rm^9Sx(ys)skA(%Z^#N|E(3qtMpHJ8&~}j9k?OL2n7kBZ=?*>ABe*XlZ|JrsMCh-=W+v3|sUr z0M@i@(PKWOvZzbnak3zCs5+8gN$#9Cf-WX?ucU{@+PmFvKc<&c!>Tw$Zf~EpIuUg3 z+mmg4btd!QbUwg3v0kP>VYQE-rvp3txj@@ppYo%za(S$L4jj?%3emnh?@-0C_)&9* zIP2&lY#>BIUP9tQnO;wxB6Oay11{TTR43#IN&zKb=f0K7G^jKPH%Q+5m5Sb1oX_$=o5n3qw-1Bg~Kog~b{q zpi_}<4-;=rk7GPMXT7Zd)G6R~85@s(?8C~#l@bEq8N|B8PKLu#o|m_NK!wyc3E2YfWwKmC`0~heqKbc-gQ-hC_H8yua@!HpB+2 z@B71OUH$RiFlIG~z?)GYHQ-z%o8}Qo$i&Mr#Ga-BmpE5Ag|>|L zB_CIysV=vxvwY*0Pm(T6qWz0LbEjB^p$FjrM}(ULuk1kREeb?&8U4}%LYE>Z9AOuT4Z5i2tY5G-(W>8u0R}kCaxN%nQkax#q#sM9!uk{HUH)LaQLd@ zb(vY6*M|3<*5mfM*ud*riJ5tiXg|#tM)Qt+n;ca}EkvjkL4X zvv~c*IhEDwTQ-ue_j?z%CT_>wktv?#^F2=&$HScD(5AXHr3bEg`rSnUjiQeEMl1Qv zx7H3o>q;w}e8>f!*%lJKlYMNRsTE(_E7SZKL^A0-l$}He==0*e^p6f8hC&ht(nEu1 zELh!Mjc(9;OG*hw;B8`@)MorvtP?Qjar)Kh^&E=Yi1wEhqC}4TB0yG(5xJ+N9|UWN z?Jp5|>mWLSAocqD)6Y3EiuNgRP>DW7l=Q^B1Q$BTWKoO+!Qzco7K*&PTJwZQK3A^s zxhCS`_+3t=xQatfzYj>dhsz4weymo+-4W1gOexasik9PL4d?+E?%+4jQZ^ZBn>S^e zy$bFlx6cT*994P0$3x2N2kg0f>%mnAEPQt!7^};n-1B$rkGMy+Js=LLsO`3mu3+p% zh{#KaJ)0+m5fXchmEYLuWelQg{O{KbaeADPmvifaeb?u4t7a&XeW%^G=9m+Cu6MK= z{Nbn*m;3cml|l23;BDzvj$bFTEKA|#tsXhG=Qm;5Z_U+9x=LOGbrO4Fw{8|+RU|~? zqj5HL(ai{W$YXCN4YHBEHDg^R5BF$&->8KShI2td8zR|#rNGdlbw+dSmTZ9=XNqqWm@P`w(k z4bztVrmKD(kZ}wRdySP#z?+rb4RPJ`M(iQ%0o9qt7|CY;c7M}f4gc8D$ z%hqQ1eY)cySF_x&!cPLajd6(u;?}g2Jr^-bX*69s1M|6Ldnb{qGi_MFMakayw>owY zD#*$tcPBg?UXuT9`1WLb%Gj~Dbf^TkDel?mj=jX6&G4a9M9gy$>uD1RGVHNrh=DUX zVk|TJzG%B)nS|3F)m#{xbS5~AF81q0gh18(6G4!VGh2h+&L~=Y%AOIBu~g5Vj7+Jr z)leiVi#d;@)nm&c(?aL4P35(Zs-O%S{N~w4Oc-R6+7o+T+${aq&RyqI&FO zTkGkF<0TG~Opz19-`ZKfX1#)mSVYmQM$Z+%9Ixa1Y4vCO=QdGY+y?Jle{;-wm4-$; z7-QLl`XA7{I6c0%{;IEshS zg`egD*w>2s41XeAtQAW_<`5C^m>N{p%V;DkHOolENK^#kOVuFC)zdzz#59u^!z@K) zwa{CqB~SJJ z|4i~z?oWstbkCGCBi0YSjwtUW?r<09QXN9n>RYX2`+)O3fe&Z}_)nvIfAS`T&289U zDGTvp3~w9AP&lSBUoR+lln=oo{YsDQLSal6FyIr%+VMoRF*Z?`XC$C%m-UzwrK)oc!|mJxZ9{+h&wx8ziM)T$(JUmie{E>19o}x-19@aC9eXJ7JnCCOaNnlvuWUmgN8)PEJl%NG zy*A+r(gk*Z+s??kZ*Mp~;f<@Y8}N7124u4b^qp0F@{`crq*0k?xKC@vVMHU;xNGiq z7XmN$Cw0tV_pzf_3VdQV2c9Dqm37}(spcXW<7RO2#p2b^KrcH>ld*LPqgMqa!FB=& zFWi#Y}rx zsZ1GS zLxG2}K+kG0euTPu@+op7MjKzk^eyyc@n|)qb}>o0nkL(x(GhH;`Aw|5-;Rw!>tEU_ z97Pn1;xkn$wA|!H1eTRrpqbGAo*2ziZf(YQmvYc5n)SL|q{B73)J!()o8woxB zXE3F-cYJyuRlhFDGzD6*j_OvS)yiBUA!Pfkjvc0ce7Q@Tp@(Qrw zFM)c*R8dj1Bx>=fkj!{otgd$UJ}t$x^c0i zx!yRcFrhIbhe+{;P!e&L=duIU!Ty8}rvRIqGP1tF=myvEzkQ}anPn0n#w z#p>FD@Co%M09}o;`a~cH2c-J#sE~!lZEvlLQZUJ($)M8OYgu7IqpReyORFRDgXr&+jiiG{blNTCt*iuOY$UW!2VqY) zH()K0EKJa&72%`1w>ONGbIJSTWvQ7My6CZ3X{s&kOO1?F4y^nkKcF*G6Ps&WSxGHa zL{wDFg{`$OW&^{a;{^N06q%S#!z%ua)CB&CZ2-Ie)3PrKAl@e-okvZY3Zs@KFCQB& z9UGO2q8^*b!fUK{^HP%-94{|W=1`vlBvMN;m<$xDCJ;{DpsHWHO5R4q*4Z-|3eH8S zGqfxk|1sy-7ymQ3=epQjPf`;oS+-*#iF8nvW)7{%T$e}6<@u49(Vih3+CYN(NBCGc zG&Fay91M|Tm6kmjUsv>SCI&LZtWjFiZHRCC`imAxFZF$wbNxC|? z@fjvrsA*a1yzVpOX`{U)u64;u*LgK>n0$_=5~ws_XhHDl*XgP!*%KFP^b?`ejFGp&yyNjYG_$fg-wiS zBqgS+VqxmG5)+ZGrLbFE&nh32n45>zkZ=sBL#q_gsn_FExeBN|32xLI=Qe77rNv}F zkVI5zih^cxVq}bFa#TWGvvzCosXpU5)VMHw7TI(km6|q1rS;}vRX6Qwt2;JWr#{4+ z-SPGL9zKJv#r6*D1Fed?X_!busj1!h=J^^Rti1(-g<`X=}^AjHd79v{k5ZN{tlT>uOiASd&yZD7n*F zuEY~4^}_KU0X^T1)cGYyjmqxE~{ zZSBWlRy!}b+jstdYYt9=;S;TbV_}7Ah#E1dJNn`?o{^n*dKY!B{HYUyXE6jf< zHJ}R9(2UOsnN-uDL9USdU145GqcN7SB64nl5m~Ug`PlLEm&oTyin+rr@1?W%;ac71 zdB&~R;Roo_&Y0-U!C^vY(kuy0!EgiXt99kEqd=cYC>U3zW6DB{qyO)d)XdFC8CkV; z#s{4@r%nIE70XNK&Yfq+Rrb?u_2kKm2I~vNrQMgnqNPQp&BTWL{;SS|r%Mwn(7IPK?|)2`49}}&QgU4`G9Y67xY^NM0 z?Q0}$VQ)fYZi4;W@T%0$6u;S^&{_dX0>BVbQhf9<;|<#l!Lv`htN|p~QYGH^jGv;7x<8H7uzyrdL4vThm z28==^rC-?ph_6Vb&&3{_d3Bz-P?2(a{$`q#=IH|ZeCX~G(QtXR-de!agkY^nu1Vdh zmoW%%!c5L!brXP3i|LLu7fcCzBZ8~QZ;ijiH2&*IW#I&5)Z({p-?FM={3RqEo(OCG zsHsbwNF*5YezP(qm5tmAafCLx)+rvEfkV8Apexngo>iAlH?pm6qFllV4 zk>qUQ3PC0fIU5=BunS{U0+=965E`*)jS*2T!5^SG&ib%it?UTWd?jLyLa+*%C}eda zWkS)IUkm}cu^$NZ*fct2^d}a5F|9%0u&(hWBIE6)8Hoqh;r!I0SkRq+y_AZ8$13wU z=ClJd{K5x5{$4-}0p4MO^89A-n)jgY$OUZ&60k(lr^P+u&fDrFI*1Z8E~mYgBcx; zo0@uX_;R2BH{%VrJqTJ>Zq@}K$!e&Fru;NP{3Rt8q4N@2vOPJ}Fx#KMHNF?KvT~)_ zpnC)v*5#`&`A)SiQ=7dYPXExa+Y+F}w5MiG<(fga2Y#(Ynz21=z8V>*CQ?DEE{k=6 zQ)s5{fOCbRRe;)cG9-vT+^2?57U8mHex63#j-8BZm%Mn?Q#`tU0Zx1WxtYx)_fzZ{ z=@wy3gPA|QGzn&`jsDud1_o8rzO*3J9-D$gVV1p{Zk&#AoX#>tJ<<3$rWSf%(vlb6 z+EgPSk(~Mfud+FmL-92>JUMQ+tgJQC&#wZOFu%7Q#|hfYsD0zYmQ@W6wQ)Qa^%Mry z%xH)bQkgKnJx1@(+lTe_v%yg3sTZyM79MS6B!BvX zIVkwR5Q_z_F6vxn@98rMvjr}$dX-G`f=Y1%A|9D_MTCo8_>ZZ~2Cs0qa~f$CPAq4V*BzMHkwf<|hx3OzgwtBCd3Dj!HpgYJ4bjFD!H z-7J&1!FF&vg;@r1uMuey$l7FQrLA-tN;N?eK}2C*-{GLkN)925PcQ>>CyaoNU47S>t};*0@p z7PtpxyORojEHTyXhvZ`jM~|}cx=mR${X%v6Ji=1#0s+#S1p42Q>EEE`U&tjR0|OKN ze=yj;aM=IIm;YDERLTCA@jnaxwPt^a|44LT+@GVOiWDp ze+~c4`D=`k?XOO-u(1BG;eXBjI~EH&GyZ>uf1HpcPzt{brcK>eUzhnQj`YXmi+wz}B#=m3Je^I22Q0!lQ`0uT! z|GR&GwfU=Oe=qsF{l8KFA7lTur~Yd7-(>OM3Hjf7{x@a+r0^fh_5YIIzd6^x^7NOY z`ahm42MYr}4Kw?f9Lvni^2Nt8ew9-Be}S%SUv%ofpexhY)W4uB+ZU(%KcFiI`@f z|9{x79qy1WN(=W-9gh`tmlh_BOsV5>oWz@isNDutWMhrjra|G0hcKrB3 zl}b<%`$0n(ebj#D>RFU6dRC|u%qFzc{Y{P=DtHHpbHMX4|j{c9nqa6-yodWB%KCh zTk*Qb_Y()el-8eHuRDVIj;1LsEqD%(urva3oz}f55e=b|n1?R?t zUH2JEp9-L8pz4mo;#?=FP4^5`qT*}Hy?!D>%0-8=Kif4_%2}JD44c;}hdi&Qrqv)O zmx^cXl>%Y8676_=Q3v?&UPxe9Kb0bTU8X`4gtIWF@0c~9reV5=DF$WnWXJE@L+0dt z2Ck$KNNS&4r?TxCxw8*{K=NL=QlJ2GXvO}`_gr# zW4MlpA?y+Rk$W%7z~!LFrLh+_n)gyYqjrpmOw<~$fl49@`w>OpwIF0vQSRt=uZ_;V zR!|;Mh^LQdG(PQCQM;E<-LuM5H zX0o7Sl#8&PHW{U02VnVjP6aufjYI_;sDg+aPz6dM0&>|_VoL;T;X~EyL!;TL)Vsm(d!xHYe`We+@vJ676Dl^3?wnc9zp>kIj&B+(fr88A_e!~ zb|JYXwQss4OnXUK<||zv%QbDDOT&;X=fUd@=PmWq=an6HZSNx6x(AU|IlnupX{`31 zl*!VPXj3%hFRN0vt4bhJX1r_^{X05bla|~qdlXi-tW5owOeU;zp2uGv3O`6~A zFKbAjTf8P5%pKyp-q6!D?JOp0T4G;rcBNyBpgzZMR*>sPla}sXmlijiY3N?bE-CXf zX^Jn?Ncfg6wSU#S0z6f5{<<%f4^uyDJ6@sQk|nIqd|x}RNa34Z#m$=L^;ke}O&gU@D(tAtJ*H?TT>X1;6E)CW+iuWs4T8qp|kRR)kJ^j{-)Rn3Usi z#9NQnK!A(mXOAu|RB>e74rJs`dBShA`y&CeHCb4m8LGpttxZ?dVPc)wNb&irsh$MHS%_J7|) zw>a@?d}TzMVLx&Jsc+xlDQ$zrkmsZnGTc4^zaxaBzjS89=b{8Zd&nJ{`F00=hvva{ zab$gDed1N|s;H;TWuFUqr5(<7RV;B6MWMlM}z80 za4p1nE0b98f)wXWWRi5i2aciys&l~%as?QLJ#aF=EC2E;xqtE~Rpda>+3WF>5ETrx#4?Xl*4q44_1#@0Mx zdqrXodUt1U(_R1SMP#XoVV)IpiXqw~x#2S5t&4XJcm}y;;R+yH`*z{Li|>Iy5!Wcu zbxM2jQU9tbS3`KyGoFykV8)pSnXerNo|D~89@X0fYjV!r>Z6m?m939<@?#Si6@k@& zY;qufn+tr??{Me&iNOQ&>j~fNA*4qb;)fm***px&7*0((u}3pIPE7xM{JRO%9QdZ> z`0Dtt1J1D;(#2ktn!XuUCx$kNPKZB3XLb+Dl_6NYk=vwp6Kg8gSWM~eneOSjLpF!e zx4JjFz8csh)QF8eXYDZDuh3ijc)Zjy;Aajq=Vq+5Lv_=%DUl#9q(8r1r1>`ibtL84 zI^)zu{U-d=4NI5T=A-$T(_lu$go<PmI;su9ApzD~gV*Dvsj zSJN+gj7>Y`Ti%&f)tS3&TQV;ja@xxphA-FQLmLxP7t^de*`m9ooVZA9Q}3nKr&Y@) z)_~&R0{?TTy>~@Zhazos(ir@(F>Hb-uS>V4z76?f<1WTV*u!X1P*NDiKF0Br66kR5 zxY*ZUT7F9PyH3oO2O4tKX6POHdF#h?Rc6jlxiD5zIR*zA4>h|#DMyh#IyIWXlLwc& zxfo{;n?SOTbndY~Gu-nLnJvI+CNebUCdbRI$e7G@gX*2qyV}2h9lg4o9j9K7fr1FSB4>Vj*=|PE6j(m++%XsX@R6DTCZ6M=nZ|Fw72PQ z+3KlNzV!?5T10UX$*4a!=GU+c;UETUjfn9X>#Cml&t#9Hr!gcP4Di0Tx_lJ7?<{$H zM;$!;I^^^9*n83e)|2@5Y1>`5&ZX%UiWfsuAnr-`M5*c*EZqEcrz*A+d)|k3-{wTamOyyC1 z^7*j%fpz@j@kW9x%Qb)P2ih1=L~GB5P0sBq@f5}U`$JedEq`WQ(9W855SWK$WYxMR zG+K9>6ds0f*jG2`H*~ND*0J(S);yssl}uik&18zpS-Y?|;1eSpn`2J=6--*2kT$f$ zT?bZotT1?s2Q-hZfJ_WP?BQVVX&Th|dmvf($sDQL85Gi|HOs3ia6sRUX1ul#n>z{t zZfetWAbU53<>+e(nQ-A0$k>`pl|>yb+_^joI?#1MXYSUP(yts_YbzSfRK;kD-7e=I z?(mZ>J`OUJ^@juQ-&PATT1%|Vb3J8Bu3uNC8tRGb9lW;`1)A+N^SRkA_Rte!309QlS83B z8mt8OlK40<6kct8;syra<=P&1726h|+3?$w>tV%GXg%QNT~*@=ZQtMtZ-?nfy~;Hs z*;eMDRK8rwH@CtE27kIkMIQ}d#b84&N5xQZpYZ+Ip5Y7XHS|IWv^gHAhYuVAo@|nX zihjM6ck#f3l6`ta>1_BbJfWU@nbfxUCjpe~2Lnpwvph=W`Csc715Gw0^fuiqu*XeD zSugfYywB6VL{lC7W{bt9CYcNw6+>j744!fFvG)m;voXBnNA$VnafRCh0TKa;03`=O zpXBw|0#Y=eloo93v2jPbVSQklA4JRjBgY36)rwbn?*IBI;HfLy20t2{EA@&E|A-=_ z151yt`vVK8@g{f%yhJg_O4?^hr8#=%r@tFhf^v*%-#q|*F!CuL^O_y8_W*K)H!#f~W269b`zpcL+U+EU{o0-Hki@b@%mY6BMX%w7cmyHvW3=(C+>2hE zJ@)0D9i1W|`=xHsN)s`)H0c!u{XjAC?=@=plM%+`f;V1`aT#t#)XkWG2N!;i*D1Vv zE>GZWsIih_kC>jjpWbYNsicm>`u@$<%XM~)t4d!v4CuBK=5V*R1yw2G+e3u^#u64Kh=~wg^5CHVMT>SXt5UbGTJT#Z0 zlk0Jbuz{@Hp0fn=f#O2*X1!OgarklDqm~rIA_z3GWb!X@kmbkdnoC`E~7s|HD9WOUlM2anC z{vMDwcQ7yC5L+8>lzn-yWqq)(E5Lj8w5khU09%ffeD)ppbVnl=uE0pWzcIBhF^@!d zsO1JMvL;5|fKG`-rR84w@Z82}kW=2=l;VpIRyG3qI@n^@jiChEoTF?3-xq<|$1V^M zmlYf*Z3StF?AxE~7#Qmt7%-SgFTFSA_FZzd9K3_yV?%D5UN2|Hl$ss}|AW|oezn|H z%4i~D9`f|9`E6L*hE#)rkZhNY*%gY`dP1m9?ant*Q2G<)F zP0~gj&$IfP&CwD)4>qKIfCn^VpO18hd@{U5T}7_0mllqq48>9Ia5D_`8<+MgO$@8| zcia@yE3C;+ds*98j)Qc7;(5=djcI4>YnV?2v3;~(5IZ`CVz)|dd`sZPDzYk>b$5Db z3Z;x4wPU$mxgF2pmK@Sz4Q)jqSu-|*;Q=?NcAR*s%}#q3YA12SC7EFEFY!3m0?kVb zDT&IPp-}e<#m`@d#!4DUR21jT=;5^yjf5~QH6_D9kfre>7X~;dJ_IFN~NjrYNV9y|aAH=?BZ*mX&m^3E7OZvF9Ktz$tPvH)y5D}XV z4@$~0JR=De-P<<2n##{>i|T<684-10{z+RA*T z_@+00eT>@nKHeE?xC#D~qTGE8$c!h7CZ^?L>ajhSP&=^(X|q`-i}aiODYq;L^jD(e zK_2h2%xM_`Z$>i1Q!~rXfupeUA$O+I-R>=Rz1MDPcjITA`w0^Lp(3lmzXXGkq_JQw`Ha#?C->KY31P)3fS zBn8wY#0b<13=XgT6Kbw%?Oi*o2KkulRPNyb1!WJ!}}ZdwqngFmnPIKQm~ep4SFGo~?-V;Rm#zK^0NYaf95 zS$uM4*WrB>v_6z5RP;rS`!39Wwo`kuJJR4be02VTz*@!aigrJ1gGH_@7V}POwI2Jf z+wvxP44VO>FS%gOefS#f<@I=u_IS3Av@}Ju?`jGD&Pkxq{TsVLjzvtn03$b5jI^e1 zSX`h*WG=TQM?VDEqTW9yO1UHyym2qdY(Q{;Nkb@6hZMOac`3ncG~d`W<|tcnm!!SuQb+(L=lDv7dGPZ;D8#EIewT?T;T0Sew+YhQso@R4F z6%mP#jCa$*OJ4U!vSRy^H@Hi$WELNt0!Dk{xZ|za=IVyDs%^~XiYS^%mEt@F6pviF zP6hMF{ZkHBzU@41q8KCs1_-AGQV}K0gt%(n7C8qYIeyMN-J!6>!9p+<1GTW%?_p#| zwxv=j4B%q);t&cuEItYJaMgPLlqD|>_~f`>r`(SO$@9a`3M%VPg<&TnV=sA;(trz$ z;OULurj_f>A?Pa50;L9&Ufn>k8hg``NaY?Ch_Vh4m3!un3oW ze5BOzaYI%nJtz!}AcQJJY;fFB>OQwf>>(y@=!48&BP&1)z+h=ZxmnqtsCNS@fCGs3pCxaAPG6M27pvG$ zJrt8JYVNN;D-Q>rIn6XW;pV<6Pif2hM(=+2f^;CI3igWcrGvTbi?;QQqwsA3tgWZc zsOLe|?+``ASrn?+tOy+t1C|CBw6G_WO|PYBg>OBRZ^%>hBS6p~FR}zlh%h~#UN?Ey zxrmb5w|XHq4s&2m_9^XPFqDx~g;C^l!c0AP$cQ!ay;=|JTt>zb^eIQrbdLTIWsX0A z0$G7aJ9vKq@P7*X>aeKRK3Y<`K|pHghACiZkPhjV?(XiA5CtRz1f=T#5<^Kh2nZ@I zh=8<6cXl|GaB{`|Wq0^_yp{y^rd~Ts5EV`<1;5FHU}>yQm2i?09u> zLT2Tol(1aDIxz)YYl4;L!u**O^q%5f zx|LX?b>#r(mcxaQ6>0`uPf8j;@8gaL02u_RHgb{2+>CqSv(>}$?lRi>@ww8OY-{OR zDi0*Sy23u6@Hw@aX^+$Af6!we5l!!vbmT+hk~CgK(=kP3aBbD#T{CxlByFa(YTku= zp>wxMi^9nWDN3>9+#jVNHQE-4gBEpSaQ&{Is88inKu9uehcwG#MTz&+b}E10NBoEP zmF#!3)gIx&4*fZ8{MVT`k9kKG2dpxY1Cbj@`Xz!^K+i1cpIK=uGdRBH?3FH3)FP>W z0SFdj*MZePp^(6T%KuoKHBi_ESN>(4Lt0o#?ebS;J1lJwP-M%8!XK%zM&C#{z3x?G zI^VPj1MQAuw3fHthlZ~5CB{pp#q5{p32kiVC3 zdd-^-@{76juSQjg(-!*VtK{{4Yiid*EtjIr7+5DwbZxYhNu4g;R9Ij7X`M+Hw)_`{ zWu$2wYQPtLQ(ijx@O#khVx~6w_m)tDNJ)h!G84G&99O-&HpEZWMZozsGt|X;bU;DW zp)6@RFm-XdPj{oK9d*|zOnAU@JejzJBv|5}UfimZjMoJ1BP;#2$Rjj5jTRJR*Te~| zAw#AMz!Fhr99B;aMHB2TgjEKq)7L}odp_JIcM8^(RhrJua5BSdyg6@Q1 z>iCO$rFKppKT79p5g&Y=cr{>S{Ol$W9Zn7!kVhTtU)#O_on9F<-*mh1w#7h#=4~u? z6U79pr7p6MnvdE%4^-1dW{;=gN*`oJu33!Z)7rk@d$zufv={PxM7W43r&J#8)3A9y zsk9E}UY2G=Dl(aS>Ew&+b{0jF>vRWZH}(?BChj6;Fkh&4>80v5TjyElaN*b0G>h%w z`Pms{@b#rxAveEDa8Adis5Pi{EOMx`d6ni$WYRuZU`eM|FVFO;^dVt65G`>$9~W~m zSZ=?Gq}?fqCE_9j~mZcOhUsa=a(#Kg<9 zvb$W>jXkCG0FN!%4jiG*Ak@E6H8C5OA~8%ndkH6t&6Kk#b~7z=8Lca+@ozpcc^AiQ zuAsti&|ZPhTaM~(k%MB66W-Oa%Y1;%-$%>*RD+AF;6aNcopZ(1UAhM#KjTtw6);b}zPnXN2-7RHOi>((+w-;!h_}eL zmn`&QCmYPuICa&dyHn6jrmI-QtY+C2GTVBBLWmsMmlDn1VRrWIlFof~o6fwM{0(4d z`blpsSNoDB9v0}xf zdSw|YmWvh~8!i~_W#EOamVWoExOzIM`Kg~Cqlb~ja|^E?@g#41hqH_Fj#oLveb-JG!?t7wLGi0TpVo(`tGBGgO=+F z!);C;5_+2YT>6TirXbu^YxC>fQK{pXlZ&kw&YWfnSpXn5N52Dsy>`{f4xGC?IEYj(;@{bEk)gMi*S z;S@*)sI%ww8l^K@?o@7wuJaNUyZ8`PW8Rw768=V{A#AQ291p}&6UIUhO@qD5#vMZ% zs$lyNLt{q!g)sPu59VAL2S9OpyTC$5X3t|VCC^>k9(AEhE58)lb^a>mUXL60op5OS z-n_M2#9NcU;?~Hm>Xk(O5i_&yQ>s^x7Cm{-l8tVJCN3pzkVKA(8+dF@SE|E=ygjRFC zE&a;(F0y`jK)LGEs>7g>2&WCo4u!e;XZS_CdCmdhX#(pge`PiLL~PW=k*U#N+Mqoj z2k)1nZ7r*l?3+CVVzzGk22VL1XpNbQ=OD!@6sbZ>x&h_o4=q}Z6ma3{Z_~~hCvjfR z)gIcg1ZErvWXYNvTMS5Ci6e`Wz40Fkd-yH7x5wK$(sstdngX)xjeW0CKNY~lG;>7H z7?qgZwW$;3h)+)ao>b-RdDXSqCtgat1rDQatM(G~>!%c@Qn;nuLx2x2jwBtS8%N=& z_SEKq6eQ2p_4yoQu$t#jxh}v?&n8)T&%&uAkg(VKM1i71B!hD~ zvmcL!r$r$Q0mD*CyKZ&N!Cq^ppDn&*@^~v>3d45=>wLe55i~BGPoZb|pvPL`9z4 z2h)Ha)Zf-ZyJ*uK2ya7g3 z`!v1;1y!DNyXzJUjWI6jw#8@3qbWrmIa{W10~ZBa!xx5vcHQj{8wc(rmE#OJi&F$7 zX6a`MAJphtq?O)0a)V@du6ts58!)Xig*;>Ba#@pFV`*1k9I-cV`1*+&cl?!x5PAto znI@?UIf7Qe5*d-7-)|oqw45Ybx2Di##k0_q<8;2%cfN;BgFIM!w})*nim?D+z>qdG z_(OIZPZBsE$e4#Jj((;}_5Exmr@#Lht99zgd%fXg!YkA5Mz38eZFTbv=7RiOr+AB&{ z?SEw3)-*lC8SSYwhn%Wu1mwV|y8;{-G4>6iT>lKV}BxLUFgmE&>e?uegHYK9Gs+i;*HDrPvLKbza}Hx`<0vY9;F zUXIsxxoY>@s)2Z%RAdAu3N{4!Hlf`=0Bx4E6tA=5Cj?C}4y@28N}@J16XSv;-%1oe zwyMv6X-jtJkr0yxKa@?T1j}Yi6L-)ID&vM;{aHvq?*nLvM{RTC!(q+g1YWF*$eRz+ z`eXKRHMwl;(J98~IovDT&Ozb9!%_f_66_P=HJPY7?u2@c*P%_qha$qnqlA`ABZJqE z9_u)#?Gt&F7xASMuwvXtZ&x(YcGtGmI9Pc%zv9=Wy`}v^`y)$;g}X&A$QQV;)*Ktg zoG@$(d9X;yI%DXq6eS3$(0ofC5f+Yw#blS__~OkCXWAT7_0EW>-Ctaid6Oi_R_C=@ zv@MggwRl(q}15PpJjWr`effBBQ_C#e597&!#$MWU(mWQ!8ls0sL$eY zz?LN$es>1t#7_elBB~Jl_Exs%a#I*IPMCG z1t>t90%yz~NgKbiijY@XR#u&*n~A*e-LHmPrExV&55Eu0)Q;KR2z_e__qW~nXnv<3 zD{3#zJooBd)>K!X@XlwUy8Q^v5EIxF>a}nw+6>_i29dSVw4t?*)BQAZ^g!Z->?BdY z11GXKrb|pk_$Hq(x=+~gB0S3br8zWdSbTK+`+810P8Na>XezK8c6ejMGf_U8U3t7v zUKQltW>1qvsi+_9-!mxc!rHp$y{eHYv6Ve}ud*FzQTOxBu=55-Dv>EYR{Nx_$wOz{vA~Yg51LkEuMSRaR zqw2XX>9<4^gTwVfXs&sX%a`Os zs5H^BA)T!>IjV!XOWk_!&yXSb5BySWs}M4q#fgV>lpU$9I0GKQUSq;T^vp*H}o2P^jn_#_Zw0i?t}QHDE}~-3zaK_C-eqg-OO+LDSh?!Nn8*B!sG|u3;y!5S*QBxy`|ATjoa&7bG-%g00EBuIX?0FKD-At?olXH~s@3`3kn+za;DTauP2W@hDUr&CZWSS}{@ycyqM)L@Jwu)ir~@T+KpOg;%WQ zOJz=YI<-Sxmeglx`n*Gd67&*$5_l4*or#@Ncl)O}c1O2lebl)<$DmDMdKGRfaLk%R(Nd;jbFg;laXEQ-F-eaE~qb;`pcJ_*TM;&~$3KXgk|kxL8^Nz_+qs1oB@( zW5|CAjS;Hb|I!)r0e{uY{&OHD^>D|CS+GHuT6H0pRGKTYa{C_1AbXGSc+DkYD?tLbYNmdly4$JTZ za*6xwX8T~BrG{^Ux;9#w4Z9J4{&v3co2oO-R=6y)x1M^ok9#_o|x+ioXKj@i^dvJKq^}KG8iN#eHWe`eN3QC+s`;OFrswm^$7t%jshF5mTqflmTzol>|Mr8(_yHc9IO_qE?tNWXsY zNs8M58`A4_~YEw_sa219->F!**c{#@YyEjRvsU4Lkep?@#% zKT=~5LYB=978C@4fPzo}3@q?}R~iEm>fnEs#)w<~OKHsiQ&Oyh=pL`0yp^4ettU1V zQ8}-qx6KdHIe1xSc~z4Ir@AMG zixi@`(e;{Gjog@yiM}4o$$TlYO_F@CDqL8lqO7)m_c6hO?QBp1&rM?S6oLlF742&tBeDM?hMUc*s8cfJYa8Yem>-u~M>8uM$!ySf zcRy-|E0`sigFp5=QB_<{%ye)0^1yOOUqWw4tZr|}qYrhNw^yJyC+>1zh}O*bvcUK& z`-uw~Ii4?`!V_q2Tq}pHagP{}pDIz>NP#sOxj5p%xW*z_K9-zmAH82GButlSnP|WE zKdzR0ExU&ua76g*1lzcu*k8v(VQzf5=B{IJkxjq_d;hzIN+EF~6Vi|hejhW;0`a8l z@FTjvPO~+tSs;QFd}VF{d;8nXGZf>&ZGOeV%Jo zc)4-1n?;y;CZ9 zblSQNarW_bG)wlWrBki?eSP-vpY>&RIBV}k&lr&DEK%C?FDH3N>h7D-$-b2}{19KQ zy*+N9Gg=kLxyP4kKy*Bjpl!&NR;z5t!SmjTckOEKA~kT9wEB9ewB&`3TMg17-z5%d z#+Yt=c2N22!naPeFFQX?IQB9-IqSIXYfrM1+r$+ubGbFc9$Y^sckv9#n>t9M>_Q*eE(4orsGQxY+PQF1;c&Z@G8Lr}#wR}PPZOu#I3~5X z85ZtZU=Nf-#5*%a3gC4r8-uK4Qmn@_pu6xFoO7!_V{7T%ISG^>OE?u2^V0#|gmZD< zdVN9or|?!fmuD|Yg9vXBiKu*?*D06$Vr;0NP(Fk&XjupG zV2Gs|-&AE6e!*5TW&3RHkWDmi4|TtEo1L&o){mx!KYyPW*f{+Kb4+q@Nq*Oz>b1Ja z+p1AJWv}=eS;~uo%<&kvdG5)>PusA~QS+_L2aHKsM59X9R9jiv*1|dav>U4qy?l|? z)0K;JdoninXiq0$G3C7~Q;ML}kwrKER=FYD-(a3Xp4Zs-){F(UiPJB=V*&9T{_+#r zelwAQ%4s_n?5*@A#gH2F%XxoDs7}34?@aAO!@cv@wjZuvV_x_Rj$f(5D`N!a1;22u zPA@lWe*4C^Ub8UQx4&V#)oO2392@@zro1-=`jEj$vf{;IQ;6}(kECf}*i8c_&@$J* z_Fy+Dd6D!&$#u5H{DrbfNO8vk)X(*=_qIEy1aff7MR8O2YlR#46X9e=J$Sy?WOAUA zTgPlBDm0#?f%Iz=?7{-Xx61#!r(xeaiqfz8~ zy0W$(&Pym70>bm;Ci2pk-8LbBA%xVkMz!vO$rcXM9Ef(cWU*RM9O1OA7PTT z8ZqxQV*7#ekQ?ygr6nWEILs|tEz!m+5{X7I!DH1lE2P3F=p#^y(fw?Rj2@XT#)}Zj z#Lgv^TslY1PStTEE$Wnd$CFe)-aT~M=vRK<0{1d~$M*Af_u&JVjH}sScByx#+4<66 zP%7g+KYwSqSOBhuH&d$T-%p~8Z?91qrr0I@i36OtBw=Cr= z`;(dd;2}Sl83+XZNzD)@uD_`nn}ZdPtEDyjf4;c&)ZIq2Ihk3gY65hu+&%1EoDr0Z z2L$Co=#1Fzd)YZ!0zfcX5Cm+<4p8?pbNBQIs7cF8A^4G%ujjv2-P-?tRHf!_ z^Y1r5-B@hWLSP_B5GV)&g28-1D9`{1WJP@bjr^H8u>A}DWR(vAMn8LfOSOK|FD*My zN2^;m;Sbuc=I&zYWq}~-2%`T3kV5ctPZvb_A9Lc5GGc_%2pSK7{Oud#ec)nwTgLub zRPI1_kqj z5M8*v0M7qlKrlZaqTjz_d;%~;*MG%;i0S$r1M}aG`PVqGz^z~LR}A5DLv;5S3=9Lp z{)qb#@oOAJ@RlY2iUIiqL4Vu}7DTxDev1PO@*`&V_WF0c5Fo;3`5T6y-hb4`2jl+( zwDU(CErh94!^OoDaJyS>6LJM- zYZt&jIg)}j;2}W7+8hc7^MftTtYKiFr4^XZ${Z>vAi!?{wgQ2H))r#e|NoG`^LGzV W#E;UCLkLA20T?zjvy7@N_WuF7YQtmz diff --git a/examples/gjf/molecular_dynamics_results/guaiacol_kinetic_energy_fluctuations.pdf b/examples/gjf/molecular_dynamics_results/guaiacol_kinetic_energy_fluctuations.pdf deleted file mode 100644 index e2ddfc7ea50f2e480f5a30da638f8f461b87d8af..0000000000000000000000000000000000000000 GIT binary patch literal 0 HcmV?d00001 literal 43786 zcma%>b9klA)~7oivt!$~ZQD*q9ox2Tb!^*q(y=?(v2A10{hl-58GP5w9~-rvs#>e6 zR_*KlRc#V^VNn_eS|%uxfxYX!lj574>470AW_)^l8v}DFZf<-!X=7^>M^k*3Pm>}( zov4|mqp|(xr=`B5v9PhBjgc`vFE5mXqrI`d6_hJbqvlvVPBSdvL5-fvjG=PBU1QHx ze>p8N!G5q1%Y(oqH(snsktzOE;`p9CXsCQbAWtDaz7?Tg$;Cp=yMF~tGnVUyLnY&|s__{J&CJlXqnCTzB6+2}{p z(wdAuupPpoud>LvVmoFTGFV~37G+^##Op9%&7b-1bJB7A9ySqnA0u=7R_{hj0&^qj z5aw}HcN4DvX03Z{Z{XdWT7jhx)xh}^E%{neyn~s&vix4fuf0g>X;$QC1{BBuU9Wfm ze`9+A$Cjrl-6|yScPs`OGE-~QV39UP|3zIbCl=8DI1!#DN`%Qk-z)S7#!RAZg`!`V~tnvt)IxWqW6;VFmq* zx?s&ZxJ`HVn0E#YAv#06EudGFM+opUwAQ*bLC|KgN&;F6-BZx8RYMs+5#p5njBBZ4 zgLyBXdzs05wybxW9=&`8k6S29RGPQHGgP@Npn#JIzr zYxG6`H3A0{ftf-+dvt1$ePDrPC)9|~BZA_hYP=p0J$rN><%T$?RR2=_WKI_Lt}kg7 z=0HubQRK)YY1UNVm>bPZn$ou}KWCq)3Lm)pW+fzZPF^_j%XVfJl_kh9ahtm6)V{-5 zVUCB3O^EL@nTVt$qPccAagdc$|oMmVH2bY4RAPU8w?>BsWH} zCqR0xKZTRTj=dIl-kNDjw(;K6@v9XH7VSPS33#)#bx!3x{M>h7rHVC=&C0ptX5M6v znGRHXD%~Ych4$Q7T7(ba4Lr;A3}xsWF8)T-bSFG!=6d2ScnN|)Ka1Le%vYLvvdD2Y zXP#J^ckSh5=`Pxev%5LCI?!6W5$eVJC(blCdr{}`SE9v(wG-hERHu`egY?L zl*IcA)iAWdRZ6&yFf2|@V-@%t@eX(taplzn<`TE0jIZnTIP5{ZB=kE!RN3-m3uWyM zkbhx!$H5<|^iv`sL9S&Gz`n4*5Bji90S)d+0IILsV8pVU&IZ24jlqeZv zCf#?TfJq1at85yn=c}6+*H;W~1hg+0=13i4P?Fy{Lh+i`TJTwO44T)iUl5wRP4+7jhq5MAZF3p|E?t^SI!6^bjTu%{DBm56>odIkO%~(W znuc`mFFo!{KPy=3V^e z5g}_eqiMqT@?BL(gr%+oWJw&@CkDO3o~T9tj;I#x^G6d5V3-_|0W{dndW{L)m@cI_ ztRhgksMv|9Y**Mz`S&-|Z_xXp&!}YEmT5D%m)mCpx_6btq!eM7ve7V-CI9t{il7qk zvAvLp%0MtmZA^zZtTAkq{gAu@EH!2NV6^pTD!;>_EXa#=#)kf$Sp!(*=dr@S$ct2# z)Ui`z_*5Qlsc+MgDoBKSB|V4R6%*o#ol>;@{P|m~gZT3uyo2^5?`9>!-TGFHFw6(`x(4P&V$$qyQ#gw|Rl+JmEqy-Pp&lw1H`O0M-T`Th zH)CR*UtD7WMnu1gq<@_OL2o!gfA>@*^GZa4Hs3VE#GRTdOynWj=;(gmIlZ{p_;9{D z8A3i6j$zz6WI$>>+>PC-1F+ppsa<%tJ)WJl_YPg6PF&13uk_DdMI9vg{*2bi)g&*m zy6xIiY#sNy+Uo|>N_tIr2d+L1kpgYnyz>^B;nN^)4=k8yZPP<7Hq0_nHXF*Zt0gEr zNWS3%pl+;rXmQt|dR63LPwu}37`=z*8%~6rbP;}g09J$7B#c-4n)a(VbNw5&q|8|O z7^I*Ot=)%P81~r?06%9lqPQG{kG~Kv3!+~P}ie!MIH zPtIB*VeW$J+tW;VaY+GU4nHCo$)jG>-F@Qd=>Z%~*KR`_e}03cK3;KjHxtNzQOlq?dkh> zLx(7_LSn@t0bECt4O@C-_+qhl0^hQM^3*{hu6DJFsJR)pA_|iD>=R1qem&|~2P@B$ zRX!l9ZLv%!V{4;-q2cGZKScQlBmaCdvaqrKdHVPJf6%6~o2@ZEoxHxu-*J z@}iREW1Ot~&DhNv}2{(%8VmS9EwFICY?& ztsg%?#2$se&cAl@q@|UJ57pnF)A|~*L;Q)3dNgE=d*U4A{CWGg=s zBv(6?WYZ+y6Wq8{St9+*-UIpE+~ZH_FZ9T1dgBMAxt3v!BFGr$Vb@>3KqL-ublAg1 zJaL$2eQ_-^*$oE?lQ1YkSV}e9I~@7(d{wXXWWYd`*e|mc>MA{T+W-?ykLFu#lPm&6 zqG6S08h2KSeRig?xNrK@y}W_zt@Oq-;{Kv?MS41wB@mgVv0-^yLDz};<(^nG1E;<# zN##p}6&U~CR)yRJ{+DaeFAeKIZ*YSxb>j!NVaT8(PERczfU+%UsSep*vi)s-bq8}i zq>Y`wsB#sd@%a%+pfDMW>=hLkNePdS!@#9X8NEHgf9&*dm`#lKQ~%8FLAwe%R8crg zgbWNbZ4cu1Q;(%Jf(rCm*z!SVB?HIs&a^-_b<+Fd6~rOmA^|>P!}CRm2$LL=sT1J+{RK*Z;Wvb@_!lNUtvef`0@8ct%tm0_#dxFjk!y2!X&NjVlz5!oE-+X~u6`;y>JY|Gh(_d=fvWzZfh7Gxs$r_CG}=Dv4|pcOC;vi& zh1w!@vI;(DNLGZ5D4GG)?=j!CYEo)}f9s!eVZ#mgU~FUCdbgl!Gg`A$fi!4)7Sy>jiKTt~j}|JLhpY2ZoF1?7Y7gS!!fH`GlQ3#kcW;s1>w8K2maSQ#D@;sD|; z5TTD*!LLNlkuVtEZ9vv{FE)V54bxlUm( zNiRCF1g4aml%3Jagz`9xq>~g661l{s6qgh|+H5jC0w2luqSuzM3cdWjN`Cn@s=1}m20oyEt3M3uze(}wSa;5x7HM1mz1ek(zg>JJg4KfX!E5J@DxPx5 zn#$B;{@8sDIj(67b8mSzzw1BdIZnV#$Lzwyz*NCZVIE?^NViTOP2WpDU>!&?9-=czO-saH42m#v>f(ut?lViRcAZdP&; zl#`-Ur_-xexX9&I$ga#T=oahN^7+*>jlc3eLLj5JBsV;_TR%%bf6I`lEUtWpGG8;F zYlz*j$u9hgcSnn~CM;7TULtB#M(Owby7Kq7sfH;Si+xj4=5m(y;k=qP4UG!X#T<@) z?h(&?w~Qw$Xr2i5h)h%fsvh+jwGzz_(J-^0L~NQ8qx{(@Y~Uuygkrs0pa9ut7Y;k zatEBugRFK=qIe@yW0GPLb}}Ct2JI4Uo(A21#%`+x+dhugh&EEs)i!rtWi@F>^W=G4 zW-02xdBAD_@SA7(t>uO4o7A^Bv54Ws;)DatDQMl$lxnp&wd&^h2ZIaqi(+0*-Z0)M zUZgJPu5vHBNBy_2Z_dwvo2AQx=cN}p5O$CX$U~?C5K$0Sa9(IeNJLO4kp5nv-gbXH zx>-G9?RnI%g0Di(LEMlmFghsD4(PPh%oU`kZY?UV-mWenGzKEVLIdsMF(b1hVi8fO zQm8JXqhf<13t}=N9wI3sQYq@x8uh!Pk(!bCMLei@SSTLE&i17bvjC}(ozrcoopV|y z?d1B?75m1$(y^(kSiN2iJ4#$EJe&>qk1(XZ(mm;_TfJ77J&>h@_K=tOgCVMes4JaE zc8R3)xoiIa*DhU*cov(5Njhjw&de?rtrHQeL`4mj0Go=$|fenuhbAlxL z;Wbn`OgvZSzjZ1F8H-o+-ce5rmz9<7#{O5$_@khI`p9+^g(}>@EAgX<9Q} zGk0-qF|4V8)yzZMW8=toE)!=GhlVfX!}B)sJ}tfemx5 zv=B};N8YxE-Pz2lnyU3Nzm#g-t5*Bc)y|h!m6URmDh?ekuS~Dbv*5R=McnqRWW7^w zv!liftIi|a`nTkr%IGdouY+fu7rOQPHm|+tk4!A!2(agK+Afa|-8G&gul2VX@X~L( zeBDdCr#pFMP;!)6Wqg%y3y(`bN;_{)bC$kO)rXqI1h)v$eIz|q%k_g!l}=HK zHi#aJRf~A~--n{&u zs^Bk%{*?ls$o_A-{lndVY@diOAtWTI?_g|%&+rfH>-@XUALRaD0r-z}aQN@Uz#qPM z`b2XEd^#yJBZp7=|A*go{u7h`QzrZa;X?Y3`j$2(|L78je+iQR!0=97c)mU8u34@?O^x`^!nD0e_DM8#qd{g=s?l^ z8S_6qsc2}bD`-$Dxmg+5SbnM%8x?D_zi00Z|EP=q2OQ{dSrh1>J%SIz{)`_@R&%cRo4< zgeQ5HL>>Q)=#-bvtMXP#QjcAK#1>xCPh{9$Ez{avFct;ilKjG3?NRhj%DWiY6P?Pw zPLpP8C%b}wM4xB+4ZF;1Oa5!X+Y&Dzx7TXUq&&5>l_84qtBINv3EO_{uh*|4wU*tj zEYJv8m1JdH$Tqy2&V$HGR|*?!T~f}I|Cbc}Ge>{sjgjep3e&#}@$b3(Cl&s;g%y$z z{$u&`j1m98U$4(~l)L*grCx`6KY#nXv@frUuEdRYn z{xmza{18m5|9F zG5)uP;9nt5!@$ahPs7OZ*DEtVJ0sg?R!e+tCNo0;YZFW3&q2`%{KyMg7qH_%hU{!rAB5dGfy2(XSNv-r8X3`NvgP6_w8tqtp}h3WQ8bqBnRh}KSf5~ zM0f4VDt>F;9;C4Gh>Zk5kkyZE=6Ym$_{M_mvnH!7E&?vHa(leO;dOO8I*O9blZ*t@ z!QgcjY8$38&6)R*u6yvWSGCP5>m@GQGKIah5NOpaB-o|C=w7i^Pd*6J8>fcVz0z+eLb9%xGnZV+z?bIYP$qQR`AJNCS4Q?7tkGtzn5P2nvSr zEy#$018^DkUY@yjFDji(PqKxU8A`NpiB4%VzqJ&G>%ww@2j4FTa%oX z?%GUep__gfb)V4P+>&axNN@dmJYWPgI=vPF&xel$^5Q%%j{l^cAmA-xV(UIX(S=|c zZ9ZwwNh?52m~A>a2jpJQF5wvsX9}?--F8HMrOGJYKd5F}a7dDzyY>~oWuI0|2ua`} z18OL*$B|b<;#_10f@Dkq(&wu!8;nRETc;em3}V`*c|v+pp>gA>x3Pj1M*Ym4g@%^4 zdAWv&W1zAImE>l@;ZR~|OFM1|D61WLpy|v;fu@~;mvQeb)b`^y7F-`(fq@8ko+0EZ zHQyJQJNmoaL8Hi!)~rRYvRavmdKMn;Kxz6|2!v# z^^dYlRI1<~usjm=zkhz~FOUBsNm>Fu593bz%rL|pX`2effM+m14CA{P(Zp@gHQ9l^ z)$cY*l65Khef<_3Q!vCBmRJ?J*4)fW!A>H7%-Vi=g0_9oxY};HlGdYg%-Ui3jMgJ_ ztZT{GrRDUF)+1nS{jiQp=bkjBbJ^I&Zdps`-i!9dJLS!H?A(5NRr@}G_Jts&6JX4D zT8C%1%%y!VOW^HxH>;zVTv^m%V5V|tU0c^-?q+qBZ;dj@!ZJ9PtVMM%PO`Arw{l&m z5+kvvLb9i_*LdeK7$07^u&2U@21S*O#$822*{o^+`Va^rX5n-< zn*=IlF_vY&u8N#8|1MbmOxw(JR<*92BIM~ggrVEuXuRNEThh|d*7B&qrZsqtDJnDJ zU?5{hQ0Jo?^2Nf+u2FIcT5<0>e8pZ%Qea5uXb*3K-^H(K`$Q}vF2MH>5 zbqRSD4?b#AH8~xnw}hZq`KZqxP`PJNV_r*H&EpcTD%N$0l8|n4I2GkDAn^$sZe>I@ zWVI#KrOrGh9OF$76+1w=Zjf!VmXv_Z+4V7HI~d3EueL&?oJJ5{@Isg+otWWY+t=I2 z=_}?IG7|*Veb>i*;oJHvdJZma81*5A+mc#VUNUx8)m0r(p8i%ta|jdHlBMEwh@P!cN`!pjIMd z&=x+`#u&(&RPQ-7nwnZ>l{8#?y0s07PdN=PAs3Y@A|Ge_*Ls?7Vq^^>pePl!9c;vd8a>w@QsE7jY|TFO4%r_nA6U|9=-PN zkYZqQu^cIIFC_3<7g}-dZI{B^kRM(o;L3OTisGYp~|B2Mu|NG}cb5}ltoL?I_0t7_zVajeexQNewRzOfHR{@ij61kMU&bIce1IFp*T22T zVZyuO1F))}0WM%(a@A}Q?W_=QO#SD3zMw^Q^!=oaD(5qB$!2ICWBzS7H%-Qs$(o0N z?-|$g4Nk*pCZs4!_E>yIro}Wy&ud2bG|-ec^iU7|aZg+LD1ZHe2Kp2h8y$uZexAqH zd3X@1y34({3fl7_5IDmu@R6z%o0`;)fVJKCunDLS>+~zqxH3~xtU4oB=i>O!oVa5T z>)uRuY`>>;B&;b<>I~zx{-1=HE?ysN9wS+y#fR{ketAP*5Gc6uwTEwv{lxf zi2sJ&Ogw%{uEVDgm6S@)OKERcjFF~2-l$iCTq@>8=l73I(Pb!Se%{JD9}a>~o5zCm zk~Sk4Pr$Ie9%@wC7X3jBrQz_B&Jdq$gCRmh);#!lo-pwPHE3FTI@I4Q9%TBl{%gKu zJ{?fh5HTjq(L9?jrx_f_i0Q6oB!iWo*sX-pZUaCoAwF_Qdxun>%<;LD`I)>_!Hh0AULcm8k%`4V_DGIJx3T9MrP57|{OAI*{Z zapm6Ov9-lnGv+U1)yr zVS&A~Ql4bCyYcbO;Mts*h}=uqPTRMe^8HpWQoKV}Lod6^OdP~4kiVH19?_f8*)CMg zxDN|v)S5@V?nRiyg(wam%tMc9(3`>f}1ke*(hoo9m+W(0HIF6y>yX>6#dgpH5nyemki;&xzNA1oGIZ90%so_VXd1V}lHI~|y^lX_>NtzOw6)Yk8=i6fY_)@}kl}TA zC~1X5N=VD?F@m0gtO|y?*HoD?D=7F%JPmRDB}Q_G=qf|WKf&g@Q_ygSn7|Z^;igv~ zDcerFE7GrJf&l{a%+5|h2#L-`aTwla(-RFX6tOkO4A)IaYfY4-P;3fJEvmeq7`6sh8 z@uUBc882@-I$Cs8_on}oH`DUn`arIfo;Ob<5lKuJwg@<=>XHl&xR;4DPG$uG*92u$ zRNXdj?jeM!@|qWE8GBbNt?LOZVa>hkfo*ne!=v5V@X`^9gTA`H+E7N;R31+{iJ^wL zcw~W``;wmN33qVqFftiBtJdxhoo}|-53~1$N?HN+@h&vsbZHOQBHba@YX;r(BhN6; zE~j%%Os!S-BW;~6{CHgWgNU5-FTFMIo#4l%cHq0xAY$ahcNF3=cC+!ROEy+uhVbI>E$j_y@jEL`R8%yEiXk$8etS zInCI$nbeS#Wgot8qAgQ_p*7vTJ#DTT`gjf0oOa$gH9@0$Jm;MbP#aP!yg1n^0^`KH zid4f-i(`J9tb11&Yu3ZZ0?vGE>z&E7IyGcICT?G;<`6i~mbwk*0c{Hm@bG_ig6wx7 zNb2n#i(G^8fLSe}Aw3>#Iqrubv%UOon9JFVDB#T02V|&PJ)T|EYOP;d3TyhcU$hsN zOW)F~Y_Fq+8W@~EUxOVP1~YS+2-uDNS)9|ve@4wxIC2`jV)F_zoTYaxElfeyc~*Ra z8W-mEWghD;Z#I-HlNRp+NDxO&Pz=C;8P?F)1E7ZB!zh-L2aHcm(th-Ow*X-xJ-Rt3 zaxae%-QO!<5Nv{_N6QU2FMa>9L_>`h69 zdX(TA?1|=y=*jmL<=bHwzL2t%*O4n{oNO`Ek(?=vOc4fi3hFe8BWPy`Wkb}uRP$`e zVg9YeGqqP(m!QYt$t^K1T2}~oFy7qMp&IsH!%wz@;iw(|meDmBYdDjA#Fij!)Rd{W z#Cltj5C8mdt=`IQ%vM!vA{V~qfYq@#e~-A6t@UkLJ3Kp|9a>x9p8;rYa_^kp+;lf= z*KAkykFB1B*#ifcF4u*xid|VY+ZTJy*IbWej|WdFPfL$GuXvBV@6xkY| z9b~tVJ_x+1@07RD+0Y+U+K64K!OTBJ=UdFU?H(1jR=^eec~kMaLUO-W=UOX|NgV3n zD(}W}6c-{6mlylO)0iWL%>7Wqm9|41>j=Y@Q!Io%^i+a`UA~p01MaO( z0Rze66P=U`+AUr^gyiRU0^gJG3#^Yx8G24=zb71p`Kt<9UtEfu{?I5BATYFPkL%F@ z_5f~+vZZ$2DdzV9O%#rP^v$mdU4X7x{Mh_=Myi9^&+6 z+9S5I;uD2KF8!U>P;`kCV07!?pxnn)GcRqnMOvV`@%p4L$#px36EHf62mMo`ePHSQ zfH&6EZD*l?jw$oRu=!%qjt{Z+n{AQl3^C|5z}itKzUUo|M5E)NAe|hQ%D(L>wANMFW60%e zTH>wkz8%vAwL1w#b|U28n4a5VXF~6A=eL==-{4_0Hx=A0h8qTLcc~_#{FN&$56vO% zsg777PIG!(T|<=s5a&yn0a1>TxwF#&DfY}bcC4eGW%bsrqBqHOH+C6!%}SB>owJ7SLypKhQ_3&RPPdUmVqv&@<*;jOO6Sk>56Y zP==cvWVLxNAGB624c8dY=JNdj=Dxw?}KxYe#gs_LIr?|HNJ0CV}a4_PWbQMvhX&@R- zT-?xL#Aq~EC9txRc_3#JZU;H4j_<@*AOCww^Z=u^S`4`0E5#)~td5+Vt(g%RIZ0Cc zWW*V=IqQ@yqu_-x%wBKl6!AabD zEbt~qSvEzy7o$T8BtHUI!JhA?$lcHWN` zt40i*yP4MYwmG<)9=aF48uCWzB?zS`B!}sgzu^?wAtV5w-OrO>ZXX^)exXYk{#*!} zv-(uhRO)x&q$nCny1b38+V|pYGrbL5GY)`0&)aHALh(8_Q!-oeF|JX^AvK_hx3GI_ zVJzT>0I3xexNhh|ar5r&5Kzf5qb_QAGDof^U%70z4{2|(0rPVzNAPU2vk&LERR8xx zqLy9)r=pi&JG)HM%lOzscxBxcE|7Qm2I?Tbg6tkwjQskHizaC{65Nw|_{^*UOzL}3 z^G?S*Zb8i<>HFnASBl>KbXnFQIN=%8#_muc9z&Vp?3D)ZjP9?x6&W&bZ+ox5!$OXg zb+K`{m#Xx%KwDkJx4zK(h4Kl*vxfoKn6 z6$$?m*BD)SWqAjy`wMp?h&7l7_R{}-Hqbq8!7W>Bl}?4aUJinP126xClyqJyWYF5_ zkQ9y;t52rVeBI1TG$`Zsf&URT! z)zWQ7Je+>9c>c9LIfdxKcHt;BPCX8$g*-AMF%As9iZ5EZ!FMdOC>{OW4hQLT2FIIC z<1|iE2Y(3@Nggm=$4U3A69(UuoV!)ezTt{*HN4qP-AwL;E58A4A?iL7B)UyqQPJd9 za-b)4h+9=eb>d#`-!iQU&9U;M{p4VfU}=68F?1{kkTIeSKTE}D{iY}VcEh-)w|K}v zYS?1Z(XrpsC&gxx%-ICsS>@LpJ*rwKkW%qiQDX<%Ne!E=BJ{y^AX!ll%k^DqK4!4f zubPKTcl2}N3U+M!A_assOzO3Jpm*sy{j3)l{cQ~$Uiao)N(W#<`h$+w?s3^Vaug?! z$jE8|M7Opk7lKNlDL(*#KB>tR+zm$rpIcnt8jlE_L1>$EVF3ab1})oghnv7&FsNLQKx* zUu5zw={7>$V3eYjUt4ud^ODRSN{=dcc8$T@AU^0IRNc9-e&UC*4M81v%*wl$cWYv72YSovOP+*G%>jsCH3yZY>$D8y)VZ9W8a*vxpyN@ z@lcTh^I1ALON{xwS=P*}=3Mzx=Dyd29y6X9?~G?rYe{RtlV-thS`-nzD|ZHd7{q`< ztU-)znQiGSvTYiJ26Q^oh#Na2Bv@Q%9pliUqXF;Z2YTTEfV$jvaHh`bvB6%He<@b4 zb)~yG{5DwBN?br|%|Usu16q?-q?hq_Sf-&|-+fGH&9_q#k!?TLy)d??j#wftz}Ai* zJEEr}xtN%UuAFe5P}e!g%j8JJS$ezSe-e1-i`7>YhHQ4z@dCD7_&nA$V}t5Ii_; zA%1jda4`2{nKe+C$GXmYhC@1BR~%?LU<#2u1cDWN&b);Z z{bLk;>A5ub$kQA{O$TidLEiMU%^;bKtA3&3?orl5*AWtdXV%D`j}REc8xQoP_|$11 z782=AT-Fa?L|{#5rr=)NG|N=P7X7nk=-~ck9YZml9aTK%nCt#uzZp+oWhL>;`_Od~ zg&hZe-A^QVu4vu$Q*@hURNX1oJQPWS#KQda=UCnHCm*LBH$p5`+UZci+FA-Ap7uDC zNQs#Axl%c_|cvjf-Bmfg=V3 z``PKZtupMfZX_U-EzoA6q52+veBu?ER%GbPkYl2D=@$Sh~ z>fz`1r)SJLw&o)}K>ZjsMI>T4wN9ez!_laMhNSh{(cIZ`-Zw&b>hf1O_XZYwJs1D@ zbvu&%+pkKP`GTU9Ri(xgasi^`qoH9>W-#QfM?y*Q4An4!l{>iX!Z2J~_f#>*uwY>p z63%Sv0A{mrj{PvFb8l~n=Ud*ftRi)J#anIL$EuZO&;;BS1fOj-k9gdyT`(sqyP=}2 zkeIP9^x&FU*gL6Jyg?vi&4x--AxS^8vA7;29yB`dr!IIsq+}Fgc*A&I2E~oYlqO?= zObXUxhotxu7rN(+>7A?N=qjD}<~u&_s#_wS=B5R&^ZosAc&g5PaogU2i|t#Cy5-+} z<3+4TcO+gy>tuof8Oo0mzT_4^7{aZVxH|KL_X@~60p>MN8p}uW0 zc2e1Q&@*F0>;jCES2qT;0pZv~Tyz|`4wmPxmTGM=xrW~J0-_S5cUp7)dK+6_p@FBU z0V@G?(qX^QR9GsAeOUSciK{Oivwa7c?D`Mergcx+&Bd zh|eJJ|A81ZIQ}fx3Hk{ta04w zWu;nvJ3l7AAniXZK1d_r%{gz)yUrA+!BfW=Mv&%erFl`7i*mi~6LTCU|aP z;lX4E=rYP@*r|a=(vT$FKcTD2T==1SEBFO>>KGIhRu3PxFguYn|03{lw60cUy31y< znIA)1ZWVZ81u{B}pdxea)Ux*7isK*}K!niRK(JkO?7IZnYFD$h1Se*6aone-2W!cN z<;G2Euq+h~t5BSLpWttT)W5n?F4LXfvX{K0IGVAVf|Jy^3Vik~dTO}6^(C(3B}Y3@ zt2AH)Zvk%|>+r27j)6=);%tfQ*2yU+utBO~@Yw%ga!}Vu>~vQMCZX|7d=NR%cma%T z!+iXbrCuO^MjAH0;$8wZE}?j291Ls;(?m9t)@Jb`vq%)9%g`H+FS2&_{CCbhYOxC$ z!?zHhjLLK3l0@dhH+o6x$y|vG&9MX$5zGULhX|ACdMW{bw+*i1+ov!dr?rf88RuXnwrlBa_$P{V7b} zMbHLhc8dfz%t&1#+N#F@m3`19IEX?RH6zW za_i@(bhbGv&R-wDtdGbYm(u-2D6OHw_Fc4c1dvgt?N(|2e1r2B;VB>80W zg{iDi9MWX&ygbo8jj5Mz#lfjsSWkbyM)eG05cGv72Z2rq!pfa+tpD!Ms}u+inMqm? zPer^bKA60~^5ge`M^&M#=?H%onPvsrS`8yGWSNw2%oh$23#yiCPV#R)DrI7+s8sNf z6ty>Do;g&3w`EuspiVeN&t+WsBbkGS7Dz=&{oA#kB)_iv!UcF5T`4Q}CtiQ!Xz6e2 z=I>7^ZVI>TyggL9(y%Fea|#GY}!Z_0@99W zdYx~P6vsLqBQ>xnuE{CwYXJX!(XfP?dz#92rg$K7SB(5oe z7{7Rvb>sKhF4%+L&qfqgnZ5p!yUgc96)<{C5e*4i2PuwvD^2ttWwFjf7gWFz#n==0 z7&ICeH0fq_$^~+mSTFjQd9k_3D ziUKQrCEDCI2{7Z6JQrQ&Gg6E*kG}mevbMzAfUZU@8>#iFUlY93h!i9sZ3<~W&Z(aE zhUGqJNlw$O5@-Mxvss_#@);Y>_gO?;@H#7r{voQSIH)|WRUUu>8Y)G>UD5p3Q8gdE zcSDS>UrtMUnC|=aCJ&vlD9tp~X-O8RicN3@*e5<8Ns&zp`WaL3S4mO{r2ZSbvG*(B zZ?n#jyqxWu0rpWZWq49bytAWLvOn_sr~3p%%$UzxgvB?PyzlQR z4RBZNkD!PitO1+-dGMCj8ZD<}kXR=oLd^2+4@DSHx4bkZ^aVw{9PORStii`_d>x zcK2#xET@gO)U`0RhHhYe&4jjevFj<`JB87GQp9T$TyxQi?qK<* zny|O<@Uh$C=(#6Gwc)dW_#|gBDb@jQ$L#If!DPJJ>$U*ec=F(l{5*Zy7d=hC#5G+@!GHjQ{r+*%KAoC}2pqSY6}#dz|> zv7nB-L!-dH&?@`PH^Dp1*53-&^^4JFF-g!V{yE0FtlBzLbyXPE($pYcQJs$VN&3cC zt!M7EM~+is$>oCYW+6)P*Cg-LIcegg2^2=04ekAxGbIosN(!;Xh&fxGvDAICcXGKq zI^y9qS~>#B0$G|On3u8Fx^))#Bgo*@qrdE|8crJdB1O4f-?F2f3Lb_p@?;eHu@ zn+%B#P(}f1r3{?(HDU=_57#*bNf$)pZ~IlqmyfC`jV9EkDR7Yo+W?BWiQ|YwTmgPW z`^@eY&MWr;jks8?B6Epr8t~DwL(U`M18sH9_dl3>$0$p-ZC$%6txDUrZJU+0jY`|L zZ9B8lwr$(CjW28Mz0TU_-gDah`?aZv5i$CV9zEKeeIVXv2Iffh1-!kBkjVs#!Q%!z zx{}y#w#te->=oSjV5f=Dk~^t;-@4H*Km$&>f8N%KkE9KY;|Rt&ig&^_)D7G1XnhUt z0_f50B5Fy52Xg&tvUzk#>~U|9cL9A6lz*iqBn!}#B2#92_F3|yXbDn#Z1oAf1DRu| z?5Xu>KDtfqseTD-^V_jG#a`vF=q^XSB6pZiyAPWWu_3+58=5WW5KnvJ&m6(3(xWOh`uw)II}Fx$x#zUG=6j5s#Cu zNBAAd+U*CjYewdZrV8U{R$s2Jx5;^*oBx|PTuq?W8Ls8ihq}cr%RAzH7_{>z7g55t z!4K$w>q~l0b-u_RUxC(d$ZhyT;utIaq?Go(rX5jS_+p=aL+p^()vf-<Lp#I&p;1CI@>0h3O=s1pbPf9jK3t-d*8di!V)EB`AY? zs&b85;HX9oXalf1<1m>_?_bA7+dGy%uu0g)^79ebx!pgYp00+D})&fnU1;SFQr936Sb%5^RZV%)C9hEewlulTiF;u5o1tK1DmwABwUWYBu<3U$9EbxV8D1zkfQ8)1 zCBFT(XnFJyVH8K*Nmt_{f_5-NxxaI;@?p43x6_du*v@0IT0W+)yZ8$>(YE?>r_*`W zP2;p%cKYdA;(mKq!xXIJ*>B)BsW0D?WmNkx&(a3;^ltsQiVW9LIT3mjY2{8uYnSy zVP^{TG63}Yp7Ioiu@ZrFIIJ1agX>Qr-}gzk5+aBz6LQh1yT7Zys|)Mm)ncl)M(-ng z7)unxo~@eN>cJfyA&*6@S+_oUBaGd}?#y?kk)+6~pj6Q!-2}b%^ZNPJECZ{kNG96k zE8bZlqaiyq4|)fXIpl^48Jjigfg-oS>+RbI^y#sbob&IUSj2J3fL{j$F6ZnT{x+cv zpAT?!zGV*orP(INcpORA1%Shh7Z{<|kKM0rtARO(usl{po7SBVjG?$EA0)blX^h4V z71mPU;{9k}_`#=x7tx>8*3EM)D9E72$BRJ={MwkRmg_M^J@#}F>EB5Ef{uye4K7WIo!z^UTdcxJ7TvASiZ@*y4g_@NI0j6PoY;bGt3=`|0RqPk849e% zBKz=drnDW1vJI=HB3Rx4zY5Gu_grtV8oNK2fPpARC8$k2!~-ZyzVH~X$Q~R44cREL z-=5As&+lOvd9*}DqP9OoXb!iuu6EoaEBk%rdOvz>!1{ZF$pZTsNcWmo5}z`O;Fr=RN$%9tW z);44L`>~n8+eXMS%(8*!t)Z0#YC?@7x0i?^9@qq zG8%i_hO){!0tKYk1_|;R)*L0H#F4oa0~Hyw`llf(WXCA1F4;U0P_3ixCo!^P9b}f{ zAe>&$KnvyL+c@3cH_Wj*K{gOnvDP zBPJ3cUP3l{y2lJ(S8z9|f+SoV+sa9*2vne!-o=8$kPsB4ka3Z}u8&i|RH(Bp(wEB} zP+{BxWqgwDrJA&q<>vL3(5$OMFs$E^7wf`^r44R_`EhTyAOc;Hw2s@m>%t>4M&?zr z>9!G^r9OTKA_oGi0VSmQR@8-MxV?D?;O4a+2`r^UP=<>m%%vltAjk4MaD`?x2IbP~ zOpD@bPayw54im$oLDZv9#wVtyOuq@}p2|yZ<#M=@JWMw`RG>tKaF#uUKnC#}mn)LE z(pOpPz=F(Tb~vj$Ssml@dbO?E_6Ka|!=eedF+l;r6Yi~QqSrcl#^z9TC0UBpla?AV z*$y&GoQ_d#<(1>CGf#J$!;rtGMXsTz*HVE-CmJg;^5s+N-*FZBG@%qlucB=$ylbwS z3Sj>FpOrm?yHnDETjz&nXhygV?w%0!r|g20Ld|AK`b%Fhs(7^b^5I_Lq#^fDoQ_ z5q8)1u|ZsOtU*e8WIM70xLP}GSp!Zw;~M1N9<1{o%wO0{QH%q}YLUx74R4(EbG&L_ zRlyWYP%ww)Pn_j_yd8B#*vwd_QzRpxAhBEC+ob82UlA#Kd&vA&iN31fViQXbK+JEu#B9-k`{R zTRz`RDO}dDD$ZHw&vUws*$<|mc^MTrbs3CU7-{5a2NsZz zHH_}!X+Mf4{TtEG9Av-qM5(P$xtcLmd7lXvhXNn>a^Q)UOc228=^C_QfpjEy=ZfpX z^t>cxcBsC7Q`f)7u8VkLB$vDZDj;r)95ahk(LqJd_9drp`Qd4C#@HH1oCuXdMofS~ z(BoVr6=NbGN$0<)D%o z<4bP&A|hg%OK>eaK)07XZ(uA`gIZ$6+@+JetOQZi#AuopEJvRy?gNJK0Brf2=%FZZ z9dpO`Xu-R(_OIJzF(dgRb;c{gdv-=#1#u%N(I5!OkuP4t#KUZ%qh{ib6hHxo4GkE| zvdY436HakhHSU8P_g2v8r=$^AVY*}YDcIwp$fqnxR$BrY45^&@Xem4TNu@iRmkgVU z=Y&{UMlfs-S;j>=2Qs z2%b1pmd@|QTd#03HaD$Mf?b%9VGFiFJ#wdw>RWbcSAy0lN`qK>0n}DeMXrj$R7jzM zWK~!n>*tz2#{w>$3R-*vh8jFOYc-uI9IYI*C8R*FuR@=LR3tm#AA{CYG^g+Rq$ybg zg$`M&o*F*x0U>fdDu$LW3DtsnglWbSBypZr2O%XrwN|+MevUsbdnjqx%ujlSuYG1? z)KWa~bnSrdKlkF-PCO9g7y*-?-Ry>+iB}{!m3j#3oa-I3tn^1w?0v?}DOXi#boYE@ zh4fn|92*`w`wSHR#9R!|=$-xmPaDh&$Ef<53W!zCXkxo54RIY<{sVB(Y^X-k?-lOG z?#*=F>I&4!YC9~}>r1H8^se(s08Yjgi!oesibA}Ar=Y-|2xw<~YH|Z|{A}@v%r(*z zygj^HgVqUwB`IytkUy>{)!Y|)(qk%NWAq*Vg~N*9>5%5BaMw_4tKG%R=E5i{@k z*&SQkpN4H?ypf;gP}h^@6La&2$I)jX^&RjLzxECmzy{~r^x*weCNsYsJJibzr2pzQ z(vTV-+{GYAdi3fs6EP zo{PGj@NF|`u;-2-9n@t_VTeE&uo+Y&}A{9(aCL>YR|21mbJ;Zo6KcTOJn$s!t)bM*EwbBJep&c+mP?`n^N zpJ(>2yNmWcW)a;Mm16qT$b;_#Y+iK2Z@=F&{b-C}B(B{sAD+J7H6n66$p^#5@3-7p zah{%vb@kbJd@udvwBrw@2DURmt?v6+NZ~HR){Sr;q@>%vmt&*1VU%_I(9QvI?!z~wWLzY(>W6X=^ZC zU2pd*b|uJ-m5mY5U3tXKj>QaAD@-D_*Bd`(vhZuS>Z|LM%uQXs@3uM@(O&llsCQsH zo6HWVYqg)wk81gGyhOrg>i3cP8_Hl@?kd@r$So_>;BJhSD&bQsUgD|wkNDqy+-i1) z1(LA!|0?~g!z(}fE!Hh$<^Pa5>|BK{e)!x?G;L`}mtsQ`U?D!;*~+9ZHQZr%nn_Cn zmt(`3S)T%K3>`c&)FJI=6+D^aq==G!7J7_itGR*aHxBv0uqoriVS7MN+QC~xS$!op*gB>CCR!lWTx!6j|oDSr3C#n9~VD=<1 zee$9GX+mAM-)RFyXsmcwK_^}2D;%yj;e|)7p zdIDpmj27oHveMm0T6hv2jsj*RF!PD|q|LXOo$YEt$M#2pI4C)+yUx@IPt&LsT253QX z@UIsAQJLI(E6??g@lWvMdF9X1>iumA7_XO)MD5M{v|XOBvF_jV`7?((4`Nm_OZ58% ziNC|}FY{JUv&(*8#`_?3}(bEC(L@IawH6jteV2lM(=#+nS?gJqT6%zVss%e{`rUiftyD!OU!WSZtt% z#lTs|4@}t@@!sf353g@#J*tv9BEIL7jOJw)9ONCj`1OYd(nh9!%LbLRnZn#g_ANsV zB7?z%HLhr!lf39y=Uc9J?&rtnE>9ZR@0_ z%BITee(O+8iSOE~*Z%3pkUy?ZbMUw`v${a9yWa@ih1?-JQt2aDY~Jc``l?_a+dH^= zs@G+yntE7TZNR454|3GYeSZ6hL$=Z{DuUh`cd+KbMJk-6X{HCe3pP35hgK5X!eY;B zsG1>*SoeE3FhpJY^#<*4z3DYE&>YylXe;KTPo{vj)-!(66^5rh^^2_raHg00?14zbJI{M zbMw|;+f-QWQrTQ-#D~FO>2Huyb6XC4&&}Yz{028`n^j;hu<`vw#m>8L{R%!1?PG!i zmQpHd|LLabeGVXK)!te1M^DD9J==GCLW4c&vAD(I)7Y?uVQ|}&dNBVIW`NMe{dFjK zl&_KT)D(=m&2$#ey#`jAOOl~MzkNT#;0|gSHcH3+Z|e6g&*p+NQduOIha^S&g@+f) zI|G+2gZmLM5V5S8D`G)JUjgkhxyE7xP-Nfy{{3QC3(w&ORnCT)3m5K_) zev3Nf8tB1E`eP)mo0#?Rb3|fU;FY?Qgo!?@Yz%H&N-p=sT?i})!xHB?ju%rq#JdgdA}b%~1AX{T-80SDR*eL^xlhLyp(&^E?7jV5-EfNPW> zY5C377UpKmfMkSy^3#WtABT`5C4xt#@-T~7hG6476-AWj%w4%fLzkmD>oc9Pi$|yp zXCHZ+qb(0 z^asasd%RR8Ket`9HVOyRqcvKp+mNtS3FJWJ69KT!aKCzuNG2+cLRy+$QC|pj=56@ILOu%dc zpLw|VP)34Hs$5YsYmjYs1mmw{I~3(tBSAaPQCgpL{Mdvj~ES zoC;^tKV{wM=A=YHg1$U zp9Im4KmLX5A{+Pv;kmX6;wPI2T+<%MultU^ePw)ipBB%wG(0#FKMJgo0zcMGK~0n@ zc??nGZfUtm#F-!N7vCPr&w+fC+!(VsGJC_HQdS;RUvV5l%S7AD2Dh5&$0V6x0g;u; zCAn=Mh_OQehRlJ^s?h`^Tz>J$bHPO!UPATGcV}{GRHt+@NO~A2S)bA1ZKL>(ueU;u zP=xAS+Q=P+8}s5aRLC`l?u-SLnVldTQI(8Nq$oBt(HhIz>neIW3d?y$IG73>8L1d5 z?$4N38`h2Hg_?SlU0*e^fZ&UG*Qvz@3}ck-={lPL}Njr`duPT#yHL( zw27&%Y*I=V&Wv|^bd)y)Xy# zQ)(0NvZ3ih)lGj`T#XgAs$N+GG1C44vB6{+*zdAYm{BcRgv8h+Bpl6X^lE%AZnDm7 zav}ms8Zvq=SD)j9sg*X>XH`f7yMum8Dv9#S@rlrIvP`VhMA-z`nAWidLXOcy6Djgh z(&7 z7+|!9aH4?v0O096;< zhk^vQezg9Oker1xV7O*7v|0wEfw}mC#PQmLLn;}qbPY6y$_7#oF%y^JQle{$S*gOg zvl=#{!j*kh-TM6iw%HnrM5J*^?O0hACObY^X`u`z8Vf#Orq-dBzIfQQ&L(>o_xHCI zV8Z~&*^yjxz1pILM1PV6qeJhLr>V8JvnfND?b}2Y;sYA$p$OIJxD0q@`ZCg1LJ}KC zN0a68=4(T;W})L|3T2}JqI_c{YL$9>tq>-TJX#Ar+e9+r8hUOcHDNPZ6=_>ZRUtC4T{Y_;&e$P8mt*&6zUOehn!b6Ar4CQHdeBEe)RSON|Wh>#~IRBY`m zo<~-8T)-hAOGgfAMn<$dP(1+dvt&^-Wi#WnIT$+e9bIJMKS){V=*x!;$|j}58TXN> z8i@Pj4^+!6Mr&d~Wj&XCU*3oU7QTf0QmTP#^~h^(dTV=?4fEquMx@Z_6q~ne zDZtJdOgIBsJggN+}efN-uwcVfUm7ZCYsPNBcB*% z3LsW87?%+xji@3vUdW%L$@H>Qv-CXg=^Ol45?&9sal82VaVqq&Hqtn znA4CJR(oT-A5%(~P~r^&z4YyH>k|$6EKZx=;kv4`kDQ`F!X0w}%tf zQ`5DTAw#<_j3c+>$Hq)aMBHT?-NFXf zy9Ac$boVn3G#5=Do!XuThCg4s3Lo6aZ8uf!&$`_tJ7-tr+%BE>JNkYwxOzTocP`)P z-En>Xddt$Zo0xpE50qtnH1yb8_^fQTgNZC{*?nqudx)uWv0#R|(P1%)i}nYCuib`& z$D@$afnr9+&-E5mh(-=2CjT9UH`4blcS;YAFNN?YlcO-eN^XwBv<069xhV!E`Th6q z7cel0`IV~G%ga{v(u^E0wh0rF7HuE!0#iI0n*_g|-KFP?j?xy-%V9qrGO zWyj|e)4SyCS+6E1C!?>Kj6|KahcwEI2@aB!+^6eUURz6h>$f2MN%PB=jo2FRAJf>U zk*Wo?(%3j|dg>>TQXHEqoQr4e`lH1QWilEsTj^^e+@~KwRub}MdHJrfzrW_X0CII! zs4dx?-SvK)yewOF%viT$Yil+CT0aZS@C&Q4Iyrlqt;H!)YQSc#bL}qeR(-hGEdRlJ zp)SjlH|yy2Ey^Z9m_=!=zwC&=Hwrw~6;*~j2+o^vEu;_Sg%0>C^Te+@-`sRZjxpq< zX@sVh66)yU_IrPqQWwa4aJGmLepvtOPNMFe>5PjM z=D}-6X-Loy-%8?XAGk6abA`qj-_^#Zp2Kk6Z4!3vp}FvqcwEoDU&Kt3e5SpE%eV=! zG=uOU!*+YH&onoXH+DA+@Re15pS6VHxBMURZ~mN8nfN@!GO;8>d^ZFJnq@F#Ufwyi z81cXeDe$pF=(DN#og&yIphNn5vNxJHziy~*z@CYpL7v%NlHVwv(F1Qag3p=CbEZ){ z;+#LAmczjnV_xwQ$N5GoW83#|Xpf5KDdJ(GY2sdoJtSW*$v}s&Z-i!KI(R=K->8~{ z&H}%Ou;-U?w4s~`yyZ^QF4SZ2*w=1x1h|b`FGt{s()AEhqxU`0F`*B{N#wXFt(Vo& z_!lk&GMjckYM5l@bZUm{lFY6IbdOm!ImtE(a78Slsuj;>_ubhO0@+M2#U*$4A&43nT9?4l~opCrXM%6CRoJN=x+2Cu{tX09_cc8(Q}Kp`HnQBQzzhjPf(t&lV` zfYe`=e1@})tJA-)O8sV;e}M8e(ODNz(@Xjz+@_-Fl>Hv~jYpKn**T~!u`SD?CD2nT zuI#EQcfNFrY_C2c^>rvwbk(%Gq?F8Da&&VPUP}yzLe(mFS|w_!JTjZ{GG~;_jE3KQ z!1_k*s87gGu7|?9Mwy?48a*B!IU@ac>}Tr`2OT0+#|6|S9rm;d=SE0nR`lrbYRc*A z&(ED1|A|6$5$1qL=X?{!@RYT&mCgWamb}rJ6_gARqFY;!%J@g}h5+cb_j450rcU-)W0>TKY^hWH$e<$bjJ>hzoPXC8 zcY+1ZF+nW_d$BN4j}Qz&X*Xfz*CNiKI+1()Adw&11H&S%B&5U|5@L@nmgpmNr+R=# z%VXFfW|vakZ6PtW*I^(CuyyR0MUWVXcCoy?hY`t>!0QAfWZyiZ4@qmCjDUd{@x=r& z4fwM1N7S4s->fax!N^`NzS5mR0RGuG;x6j!(24wZ`y*XLENVR%7?60E;~1Q#CF|9A zkRxJ8p7I&e16d%J=H=Ev$?PR~0^KRt$pTzjS8-{KofZNs zrX#<8)9yUiW|m`|hTp@M5QW>ce2qF+9yj4g>uH;&+oo!;eoPexDtF&dOTOt)3m`pW zAGfQpy|}%)Nx&o2z}wcs*C40P|BRbJWyfAK3448u6E^=2Amkzq>7m1&{~1_iry!KT zF_4$%#KwhY*-lYEx*UHx5gt{YD>}3D+jO`&^26uDhu60j^D|gyYfLAbXNxtY9X@X? z{=Ax)gsr_`w{BHbT5cJesX@|3Vtgw6aR6;OGsZQ}>oj%TjfJO9*Ljz!ySFG3WRpJh zL)ENraq`Ir`!`K1wQ0@tjT6CjK}L{YkyA3Vl)I;p*Ht*&?MZ7O12xxf;4yOkG8h(A zMh|=CJL$7|X`d-;B754TWYB0MIW7G+cF+84Noa9 zQFWI_{1LSy&`S`&gze$g?K2n@5az2iaeNrSr!^T}tc6liOnlEAiGE0;u>t>b({*NB z%uo@PTkJL!QlkV^Wz)WH-88#d&m8(_zY}94WrN9W)mLW06HZoFe;?nWMdzi(x9hrS zFdI#9E7}`h(cD-Oywczj2d50%v}%y?v!Re~VV|C9fmNj`@#SmyUtP}Y^s2=n?Yyy^V(?} zminycOIfBKSSit0aZ%i5Az``yw|wZA>aJxkF0A0Cdp~xZ0MG*(o?;39 z^AvMw986bLL$n#Mx%<^7N^qPw*O^a>3oRv&(`AMe_)~)KFb;IHVqtY|U3_%;nh0jp0{ z4%%?HnqTph1cDT1AIFGw?$?UL<$}#p>jG425Uf#^iv6&oeh!}BEg7xh|A!F&t*=Z^ z&+vDE{|d(6r|+Kt{}Zl%NxA+@cJ}{_>;JE1XIcKb2L9th`BU(>r+;54|0cxzm+UMn z^B)!6{|9NYJ;}{pVIFCq)9!Lj%sUzs7mSWxKNw652qcH# zmuZ_GdB#-8vW!QXu8!gx&RK;1#V0LztKrp5EvD7S$cKD`hzMHiZ`} zZC_l(4>dCO~=S z#~c4bK{4p0$wc`i?jZS4x+9oxBS9&ntk-ZLn!r1>XU+#p536t94yY_yPxK_MI+3{@ieN9>X zNM3Y}eOK=nBG3}1Cx|$rt_+Mxs*aM_knbb9Em7_7pR@sOMv3ahS|2HB$S|MTb)cV5 zQmEkLYAe>rbN1nK4HkF%?pBqYIj=GEP)D-i8_{%UA;Z(ly3(q6ShQoeBQtkE4fQ1# zUz3&aL2%z8KN9Ke#z7le;8@I+mKSEMV1*$(`+;XXAk=R5$=m)b;oZX~OmpxF`vRXu z;<@4ptG-HX+A0iV{t!ecYoLhoGk&C8`A*CxnGHIDF&68Z(hq zif6NCSre6Equ0seR8cM`gXGkSVyfiSa44r0C^jFz-px8JAeKBG#^j~Snv$bjQs19L z$95?OCpx~oK43+%PHlF|2 zW(UlsiB)o}7uCou=`3dl)~3oih!spg#VGsi`_8#uMY12haIN7Z%4CqtbI)fx%FRm?RFCI%qp11lRmy1o^zc8TAIN zG5KH_22YpjSYBFP#ZeE*q=54M5)pQ7D#hx))8s+&NLCcuN)d&sxG|mB8KEO0M{tN9 zz=eSej}{3R*^BUW?JstB5%rbCh?}gD)-3UQkc?`dL&vY4wIFBWuH@^o#k7+%n!PTR znbFVsI4F%CaHzvoi{A{P>Jh}2Jk+Tm7WAjl<_q-f>6Z^6nA>cK&6vlUmIy4NMNji= z0mBn?3&mZyclN12$JXTlH^(F6wkdNvmKpJu(e^p58ge#NO&e~}E+aZRh&A|7-PXxF zeq`B=Tm@Uz`}v!l8T?j|ABVcI3B@YvMb^0gA(X>{R%t8jlrz%46;I@EJx<9_w9(I2 z5uY<*Up{DWOa;9azicd>_9$6$3j&>HWY>e}@}Ru^oy(a-YJ)qUgXmO16X-%aq z_`BTt#HT|4L-P+K+TUuI!PSP1ORh?RSTOTr$Scjw2|v$R3@WrO6MCoK~0G4m7P} z)A>IoHSVZW%#FNxMmKdTT&&He4KD7Y1Z&aGcyw;whCjp~I5G&DTwP8_2A>mmJZo`4 zi<1!=fKHoOL3H6rwl$$Oge9<@OpLdkg__uSx-XwK260KE(H&|ACc+PRV4*Q1fb8s6 zntkT{c@c@GCq@Axe*Y%Y)owuvab*!&FYha+p}1Z9gvcBnM^lD}W=!?>{n@tcTY?vg z&~xVFrDWs;oTFj6VK>0kqYdvlom_+;QRv`6z>ikBv_2V6ABbQF;N!cTQ=B4RBmf=o z!Ka302M{opSH+l)20jOTGB8mNi3mboG;W~RLjO|>1+5E_#NRj$p|{(_ldyf9GD-1x($Ua08$+7DU51CqLcBr`XM0?8(QvjyN8B97bryubY?e?xz^5D``A- zxS&d@oqFNe(#4WK8wtbV#5Yp4G7PB1jpxr)OW0?!KPb>bM#b%Cb~$C+H8ztxXpE{~<&B z8zDhYNB>_mj=#(PQ1SlB(Ebn#{$^bKPbs*Zu&TTmg{Yy0qoKX2zV5%$xPQ_*2>O4M zDgGg2Na^a!S^d(r{HNqU^6@W8|NqLz>HY}(|C5ljutNL+BmDDV_{!e@y#7`4XNjKW zj}uHx%>V1_zqbC{78C2AR>Hp?%wM#DFRb7fH{j0_^A|aR<;&im^{-mAw11WUvHh=o z{e;zsQU%vgR^T(^d zw)|E9Kkfdn%YS?Kb+rGj5%V_!fM8>y!=++m z{X$JJGBSPfCg{J2jQ<+}g5`^~@aN0^;2@~z8NSy3AwaNvu{i!sfM8?&2LZwKHyA<` zmzC*1U=WOqUo?q-U=V-K(|^DqzD)mVnf;TM|5fmRWaSM1;%NMvfBxkF6VqS5{lC(3 zH*jag{`;q~wfpne)W@5R(NXmpD?&oTX!D@~a$nvroFTlU0i7UUS9UoZoDi}P`CKTN z8Fm;vFJ=ADx_YFwM>8Succ%G=pazJ`1FwS)Sh0^^JYJiNm5&_^48{l4#uMpmb`vSD zsVFq2{Oog~sElSk@c|6cwussS!68yER;dkpJQs;9(Pw^5fLcJ$+Z7;fUm6>r6fa2D@fX0Cf(@}yP>F~Wpw@&%l{+%q1| z?lJn;p{{T+!Q9u8KJvxR`V1J@XXAa_{}%8K4UL6OmSQ7_8Sw18&Xk2aj~YbP_bu6P z4Mlg1I)m5mL8`LsK1uj2*yN@vo4=KkCQBBcHjcW!rqQ}za`5nkXwtf7=`QMG$*t!P zxLxg8E-6 zNKV>+#jo_+>g`A(z@jwh6a|r_f0A~?xqV;bn0K2^!VQks~-kjZV>7W|Maz51E z?A?HddgP2BN_5^{KykmFZFnv`Bs=eIbcpr~@*tYxmY(?hBvYU6Xu7Zty&13fyjz215Aw(<{^WWMDMH3()RY z#W9K5R{)jqPtb2?F@p28u~7v?N~W~%YJosokZKM{Lj?5|8B+6&fHEwK&AODf)! z#qwrsxyGLsgAm;GR|6wT!mzFu25(GrM%BIEZ4d8zI>*wIc;)4Vga@joC8Fvm(;4zg z$yDZ1%gq2x!q+$HN72kPP9AYmYonQ;^d*~YPU=({vt|(0Q7uZt$HA3eVCqR9?@crL z($swuf~LYt)lZ?vqf^OY8bzrTyU7ynMGBQDEsyRiesEo?XnUGQGSX^tSY{Me(v*jmKda5;mdt~Ug@9o@>fe&=CGKGex&fMyAOY)y zj@B$sI#Q3%lIG_Q=Fkpv^?iK5S~IE1Zisa9@`XYk!p}7wAZB!Q%JlBrO27(S)Pn$9 zC~*$fks>GP!GoYZV!L0QEc1~TvP1Uv5!2ed!}oDs9>3GH=}{93cKHIcmPqi^hBkDnl*!*~lb_Zo{rgt_Wl zDP=kP{EJr=jt0Uh#Q+h$EAvN0n0nktsR8N5h{dZB*dlJzG*emE?N26)+xSqg+riyy6z9&xt#b__ysj`|5SAu4Z)SvTxx?y+u!Ma9WJF>=d5Z*A^QUMoM5 zZwDtXiGr9CtAC9~(LZA`q%Dtdj=W_)2V(WXS<*ZL+K^JZh8WSiMzwGmL*IYJ!?KAIPS7Hw|g z<&;F!F&gS=hNsBk5JcRm7KSGisG!+VzV<;pA~HWY)pM3&fr}qt<0T_vsV4SEKYY?J)e*8*T1^+$p+?tqTB2%3+Q$&c zJArN`O!74_#CEEn{K0z}WxO8mfG{orIFS(Y7WGJUvdJoCcR0e3#m{YF4+BWM&ua}f zg?1|=uLTdJ7iK!65WZ4~1emo|JUBJJ%saV-`aMOLpN^W*K)l>x%z@rWkvP~qUEW1y z-qr zU#&@75aa3VU$O&;SJ|~Efe>9}=A`3v6qH+eCjfL_TngSyDQx9{CBpMqJG1r2x*SG^6?hw9UI&t#lMrZb($7Svtp!>MV#lL z_#T?MT}GdenA9gZ7#C+SbI4?v)E_W5O?!jZ&RtPE)}}B8?W`Igj7f6PFmIPO&Od3O zlRn*`CAjPXV_3e|$M$T8e!>QUexgDve~>~e-~U_*>z(JdL)y0<_loMRZ)g4LShRCC zfm!F>qs?|K?%Ce{#Dk7{qQk^~&SQ1A`(vFG!lWa`_9^ibJ4obl=PKE2a$DW)2n2r+ zpuUkD6Z;Wo=jsWkce@3rfBOYn+|9-rU`j)V&0QTPs30G;MHZ&_xsVKT%A|o$M}wH*x=Y%^w{x$ktdh zPK_8Xc0kos{*qhEs?kWC!v1GlkF0o3-sK4@7cQ>uBkSzFb;Xc zx&4JIejU6Ae60qTn=HMOGpUHDRL850sq3NbX-l8Tqyvkf5@?}I?s^~WQ7#=WNzW;V zp3~w2sDy|F3B{e+AoLQHF32tzF5|MBXmc+{8)HZgm`gS#a!kd=&arQ? z=H&bKd-LYvyc4Fg`s>Se!nKiAm5cC1i8JzQB0Lj zCCR8qy9nUAZ1O}$XfHMM2kfqVbFUq-DAW`dwy)1I1cB?fk6A331|Kq6$nw@xqGy+R z3pZz|zdJ5=a-1m~BROI+e7|Kx(;ies-|-W%|5V@ED)D+@t@4N!2jAk5)skYG;QH)| zU2>NxJlqf{J;xD;ru=QJ!5C^RDZnUr?81d?U<$m|)=t`k_5^p3KW-%TM>-2*##OfY zMl%{;^7X0&vzU)rF3z(yRx~dlh->Qk_fAZrMr8Eh!nbF7gbk>arpCaRG&}r;Tr)WM zStY8Y>Cx%v!{$mZv6E9SJr~+GEhH(Pueu-@JSmrXOhy#pb7oo*xU;9jY%!$*QAyHl zl-_It@9Wv>iR29JR34`5$~~>X{wgh?Ex|Tp2B${FO-|va?p6gs34?$m5AN`Ht?LY~u^Hz$7;mr;CU3)>* zlKRE7ixtAj>#(2rQlZF+4IjcKYJ$V1=YnvVxCU_awWoR*++(9Wwg+bqiHS-$+t4S- z2s&?Y6(zo=oBY5-2oCwpT9+-J-RuoE^w%<_G4{==h;!~H$&kGp-}Q2Qd-ikHs;~S| z@KJFziJ_~}fYE@+NHc$OFn)#XJ`NTgd3TCHPDg^d8o54y8$urNn7UDxt)55ji!5Hb z-zWAmz790kDmSXOt(J)Xfn}?;*DS8`anowS4Di(CG=Ky?&a6nq6KdWUeAfOC%PLSn zspFL6YQPx)@-0;?PC!uI<8>FqZ*8U3Cj4oS4kU^CgZyfTI1VrdrO>g)M)}(KTi+~h zKI4p=44t-6{6tK1^Ygf9d<2oEFFZfASye>ayZ!<DiFF*4V_}qYkkOcB=7_U6;f_p^2Gz1`_ zT9bhjd$#H3E&rk{OEs;;)iGK#LlDq}P$jqF0epnsaj;0@*c~C36gE;qmyk8ycJojQ z#U_g-!*QNOxwsga6)tx!s4Aq%Dn5J{lZLx{fab5ZN+3{>_6en$6Z7S&IPn1xPd*+* zHBbtDtB)?+g%4y0R)_4au~PKnzUXTN++o0e7C3~;;W-hpG?SvgyNM>R`?773neF|& zO2G0kbWaJ+weZF5J;xyJE63h?!nU`46~=Dy*9`&E)hj7i1LS*+JBeg5^fnP~UdMCm z%^a`x^v?Tv;;ZP4mQHEyZYqJO24=>cw?vs;dtomLl#>uE~AjJVUT#Mb9c8zBbYKhTP|2aZ(-g0$pXUcJq}H<3)UkQ_Gc7YZvJS3 z1*F>jN$N6{-mUS;Ps_PhxFB4+NNVLI3EIy_cT&^1$Z8js;09=x&ZV?3#C4-qC*}(# zeTPu-fCigl8{_Gr=4U9HyDDYaOfuJ*!;oAn!GU|@FnN_By{#aApf!M!IgGAn0o#sk z`^1bC8`4+J-$fRebKIV#D!|Yo3X3{tl9SdkcT^p>02Xv9^)?}EXH)kGNb+%_CKUp5 z>h$CR%zVV~sszXR+GAb&u8get z^R$iCPi9ZVZ`Tm3COQ5}lwA*u=xZc?fU5-_ZQ7QtD#JY@7{JSKTq_^%9QdTDGQL4g z6wfn8SPf&pkT)zOT34XbOEGlNUs6rtb+^lAtYmouVll4qo7!xCwZ<=@0uWawq z5vg`DalKl(zi*d+gO9@xvxcR z$;T5mRU@0V}H6GLzfZ|P__ zg}7WuG`O)8%fiKQzt)O8uYLVxy0${CaA;Ka-3%~T&YQu^pDF6ubR64Qk<=rvMmFo~ zgp;SFj|-U2rz;iMMh4-@52k=O;&a6PXrT|fxzk?axZm`ROw=!UB97}RcXEWQt;b0W zJO@Tf7X2>v7X9@o>9kBhdLR8HZf}mPV%}RXm)6;{Lb>8n-x~Pdt#h4m`vvdzQH(cj zj9n2{(k3OPX!HAzuwOKfEH-a=(T%f9H7!^u<(8KT(qV+o3wD;2mVjK~!dq*vgFFG;ccG}oUY z@=jhDImV(x)`_r7D8wJ#uq4R!pnv77K!%oL=AGyPIvms9FmTDSX!Xu(OG>ghn-}Y! zP=wZ0=X_{KybF1ao&+_Fa9m=$f5h^YPNffnp~usnoq(GGD?=BXPeW&Y8w=-wtMoqC zKgOFU5T8iuUoo{shbz(r^&y@|7915B1-xv#ioKqby>dDanzCpn5UDwo?=O$sB=JDj zD4gnk&=+>I*$|v#lW4$9lvrES%N7$~(Rix1(b3!+0eB{$r&`4(Ro?$dofCAb*G>`{(MOOk z9~a?ZJmw%}Jo@@=&5L{w9ep3nY(J(^UdF?t2ZuF@JqTGg90p@$J^DK{GpNvf)+WxO zSx29>=`fddpqF~jnD;_piWdI5ce|TZBKCP1pmVzztFXPq%*ER3bngkrkCcGm91$4r ze#dvtRpvG(PjgoY6~oh`km zOrr)x(JbZSx%L~Gj&^kV+pv~9or^=A&lFk5-zJ)jj%K{BkPR#)Zf-2>spS)$qHfu<(`aOm4Ir$!IA*6?_X+tnGaU2U0chtEz0BnqOOIJ)f7D`H3JUd?)@JE6m&vXh7J;$Ihaat`% z!qi4GYb7dDHvKEMm?_DDTp5RLt_Qs?Y7~?HR8m2{1gGdF3=Zt{bWx9|rB7<)f8CL7dq)-|^(4N0y42o^V2)XnF zp)3VJO;z!7-7uF?n$pzJ%{ffh&vF>%$z86W9gcSff3&|R4S+--g}Oz#)$ zoz&0HKUO`furYvbOF8nQF+!K~8@8v*PCBh3ro-f|+UTyu&v&6K`Q{mRZQDYf9jjyl zq{n0(G`(GLb`HsWJQCiJgku_VUMbSvP8i!fI;mI6=LgzDyva!|{Hbl3ZG#X$Lb!Xb zA`3f;O!_93ZOgYMG;I`~frmT;YLDJhC%*0o^8Ua*o8CdS<>N8I_A1iK`@_@2e2kV- z@fw1+{;rkHt?!#3E6jlr466N{Y^Sf;A~FdznVhz>0Yrv`~1v1hrHUbT23JuKGy zenHDQd@ct5);~(<^pJDJ?NdW_FXp+W^`W((GSOB+Erz-74HJAlDN$Tk4ITW@Ed|67 z*V^CQ9Sc%qjMb4*rQhy9#d=7~Y1LN(sZQ|Mg5BuDoJ(ff?x;&JF;qoqkmlt#n(!Yb zTB(nAJZ>~+ERYGMHr1S_Y@UCEV>_=*Q`1B6B5KY|_c9F;>4i<= z5yS>d9dDy-Q44ata$RcftHjPz;G0W;ypz7&AZD3<@&EVi9goHZ&71 zU>b!u@sn}sS3E-Jk9hZBzsom(zU|ujS_PnO{PTD}PbxVTj|yLu_2y+4(&A=vUVPE= ziD3oI?&bSzIf+W=db>C^wg*G{q)EvPD9DjT37mL(~4oXkZRTMV^oOVTP#pT2Lk zKLb59&LKLqwvT8~)nG|Z@ve~6zr58v%PoYCs7e)1@i~n~dkJCnI=A4vS1IZw*KL_! z51u9lsZs!yG})+4XDmIfJ;&<$R^=*`zU1H5KMXZuFto%1*zf|iJlaSl1KCT(umKH| z50DHVy!_!Fsoy#;5uy3GfuP%`BGk^Ib(uc|K!?nd5y@fdg#~$!DlCOM*KCuvQyVhB#D2Kn zR#%pdtfYeowg~f@@LH!(*3~CeW$V(XGgejl~cOiauIF%KYNqj7zETCz0U zgnqYdG}u7n!>%S17>Y2cX^L||l#8OOm&(Xo&R!!talstVqPEZUp<$qN1h%Q7u8hUx zi^LAR$o{@?hPf`xx6So#ANGw;QjiF1gp$!sRQ+_9OeH$YLHQ^_Eyo`U<{Q1%AX2WA zVl4-vI=)Aftc&M#nTto&j28RK&4{~e5nr(xr;S+~=MLs`MO&m6`f(5c_9h8#5w{#9 z`=X-RPqOnW7Zl1Wcv<7caB2r_c}~4gP&i$&caT7Mz^AMyJ}Q1Dr*ZqOOIE#Wx$9Y5 zS?P)oKZw6EE1A#K@5BujSvtkCt1==XuJ_G8qB(BaF_ZF;`rP&5n|=q{J1In{tE_tM zi--ZzxE9i>$%G|~>wI(ZR#Khiu&AQsucKWfJKD+S!deA@0r0^E*}ComW>4JoQ?Pz4 zunND3sVI!0X$619vZ|jUG_j|c(Bie|CV@C9X5=Q?t<)+whWLkm@DQMLi*l>nv`#vj z3Xrgrt1Jz8AW;y5(GaZTz@-_OLWD}VGx5bUD*AqlnmA`Rh&kE6Jxy?OUDzyw$3B02 zODuF3=%2AUYLmLZ;gnFBF7)%2w^YDo_jFi(##nfbtanT<#A_5t>f$AT+A2E(x{;&m zvCK8>Hw*(G<^j)}4$`3cp9Q69^52l`XzkRgukUP~gK3N;Id>dkO3{x9ep%Xrq~#OmRFk zF$1I=qUKrClT5`M7Si_}6xGB4wmm_%9JP06Kqyeiz8n*Gth3e)^`R_@qC=YfrlyM& zhr{>bQDmv*-6N~wk_>UfMB=Gd#|X0;KXr-kA8TG5m5BN#gJ7s@-k@rE*7DCe_tx2QeAkN$q#gAc-YndMrgHP>Dl#y4Q4i zwtJ1?bVF_!2O5PAeMpE>+a-Z#RL^J73{s!?+O#e4?zH>9NdmOHouCIl9!<8vW(RY( zU@5FXcB|**5ngUQ;XA(SCk-+jq|y>2)HL~0`ylCVEX5T4N&X?lSQv$RbE`yZMs=KO z`_93(7xHpQHj#yzY#w7V6w7(3>j(659_G-sv`d5+$4R``-oz;8#`XM*SJ83*DL$zz zrI$LRAOn`Ch^~qf^OGPYY^F{m*7~8@3&eL zw^%pg(vCO5o->`4DzsLv9&=fO)xvc?b7}Jpj!|cYfR9z^{sS1csBOEEk^^UjnG%a&nak6 z7#7QIqPFGaASdNXVbNs;Db+U)aJLsfk=ASIq<9XtL%IkDoA^17)8L*($*}kQoLg+q zaW-?HmxqU9v5S(~Y5FiDn<_R#sL-t-5w5x>jxPqXF8n2egf1Z>WNY-N=*piUV%X(1q43>|UPIg6xnwOnBaZgX#h%r4*nJBUTI z6iAfwwvYDta^JJr>_EcQs=k0b-H%~I0jrts%ogkA;|+!U4jvr`UE5ql(WK^dQBIm7 zr}C$XaUJQx(2OQS$mfApqFkbD0JSgs;4SYeCD4ISm26Tz>w^*@t=G>62?~oS3_HHL z2Wdq92rBXh=S?)Z|gHo63v(Om7{8Y2_vb*mMQK5^6Z=&1mJkRIe3{P&_*9JarTbYRW%EE3g zm&0o-XW(!ce&j0&IXL&7+w5xRD#KxX^9IzN#%fDS4@%^hNqP<#reo%qw|X`tit*YBkx{%31iB z&%`nZ1X_ETRxZQM-q7&OJWflc82iZoF=QAwf*Hb7-6ejuvE;DTVLndan0cYLLogfX zCYnJN^$`6HDqk62qI1~_BShUMEY&V``_;BV@KD)M-ul7E)thuOj90?k(L?otHd(6& z{Ll0zc1tB726*97l1$0@8nu*U8&$%_(d|C9p4LxY&{7uU(2_|$J6~ma*mQ&0sK_3v zd1fz=g9#)P9dsNQzGu5rY08=3uz@8bJsOz8sp6Txbp*}Fhbrh5#vD0iJ??}}+2L>c zBNqm@IheALIB0OwDi}k)G3&iX-h~&UsRABXkuYu}5rk{nWqra}3J^?S$`nT4t&z$H zPDV)-GGXVHEEAeb`nO1zrbImxFm_v!7gK2yzHsgf0~ z-5m!$b$$5TR32?(2}%eENHh#Ixl06YAxoQnrqn~NFwDkK(4CPemEzV?@s*;jlz-B# zAbL1t=cjAq=tCfI>aMdR#LOU@dwQFiMo-{-UU(z+(X7F;)+aK2mQ2m%H|eXpWL6>$ zdzV=kXzP%hCd-%5+^);0lu}^+xRtYB!S(CG=3u}h5KSbTf_{kFVHv`sEAtXWxS@+^{KJ^N*IUL=}_j9_XUc*cp-5iF$*I z&uN>peR1|!A6;_>X}**CP`8WmgXRi{l^}BALD2(L)jG(QFuKm$0{ic3Ac`9Y%#ZsN zU4w8E#ib`Nt_m%)a}Z&0XW>w@rdFAA86%}unc~-3?cbtw{m~kZxhLheq0cXETdD@I z=3%K=OK>V#V;Tmgni#VNV2UJ@lC%6*M<@9zF`C^w4<~uw?5mM1HD!=>JK?nwNQs(E zPc!W@lm5G9ma}%Yr@k>t;sotrMLGFY*4wwCN+bS~>g^cCJ6fEmR~P{v;^{ zk5*YOiE*CPQe-7%mUK$s9`-H1r(F?E42bW@F7S~PXv$a;qq*Dt9HgKMsm7s_uxI(G zr{MQ)6(yh_b)TR^bm$ZjSIV4;+PsTiD#j6Zr=^*1cTU)+dY<}usJ~5Drb|qtC*S$0 z@EfVq1CwaXr7en&FFO0ny)U0>j&E*Xf~9!vGS};%d?VSg#~&nZ!&dRyy#rN{KNdHj zw2Mp;Cg1{)V^E%=>0*uIR8yJ~isLOo{}Z6>mQBHMhPsL(hg5(>g-nL>9>oD;3Y7?z zAK!^?Nh7d|-2y2F>3N_b61M3>amMz0U@UM5$+xMA5KUHvk}-gu=C*3Ooc6YP3Rmaj zm!|K}*9OX|opSRgPpk7La7Xq-$WJ;Leva*2c8Yr4-yX4%kig{Xv?;)pz9pZ~cp9^6 zJ4ENK!~Sxq&i^3K|G>=u;Jg1pqQ4VGv+>E|3?}_7CjBI4&KPFS1g6gV6#fcdt;*G| z=y{9i`L*czp8o;5zf(eo@r~XbW?KQ_!W^c_7$#yXt-Rd+nd%o=``1*eE><44R-XU7 z^S76dO}BdJ_y8m|N1BLZz~zwKhod+Dg%Jg-&OwtIsb+`HErD- ztN?$l@ZOrI>VmLzx3K!l>GzjcPs+v0%nflr{;xamukrl~rOn*#&-$-HPzhoAYmD>v z_=%ObC&I+`Lmy4D4J%S6lCzk)`0Ko3?Qa*q+;6ECa7yio= z_v-*S{#OI>!UXQG%)d20{(A!UHw|>(uHQ9Y82nESE^uG)Z}Y+V@5}v{1_ATJ|Cb!U zaN~c)@$y4{St$Rdf%pV|A<_TVcm?==&jEsfK!2PI0o}vHzn#kmhy5`hp8)6&4F>&% zmj6313?%SJUKkYgXB>?8&o~(Tk6K^?f7E>61JLii;^pW6qds1K=pTLN<%jeCz7Adi z5cKyx-(L^D->)SE4F99g5MIz9d7->ef#3hHpuBwG-}ByU_jvuk`v>KP-9y-aXwcu+ zdmnetV*efo2mOC}-CWFU9jsh%eu3s1wm$b;>z?UWM9hf3^^S%tN_-PDIv)&#^9#1{K&V-RUe+85~#+ z5lgV?J48qYb{s40=UCp55#}SiUBP*}|HyE%SNcZC{0<7jttbqFiGJQGPd+^KG*i3a zs#H)pk9!^*!PODxM{L|rb$JF_KU+D zJs8Tc+F!DhpNSPy0|EIJuy{KCg!mNVQ18vVMj6UJRyaGnsc2%;q4F%k>-AzTP0%=C z*bHVyJ{yL%+JNQ~OXRe$o|iokhZlp{G)OjN3A{EREP4`OoJV-l43nM#DrO_^ zdYwjZUZV;n1W|#>3=QzBk07g0`Io6uXNHcYt)P>?KZ7(&)hb_;FaX;fiPHb~6GX}Z zlU`os_Jl>FDppbBeF<*y1O@t;k|nnhWGaMkrgXx3Th8Ut22 zTrhxm$beTm`Nj;u5na$SBACiR0Id?fgj%Wy#|F>5!py3WDLJqcdOm`*K1v9j=s8J@ zt*F~8W-dt;y+M5bN`1;1%rnQW5hzS_14{mCNa#&r-;q+M88k>|nY5?psgQn5=m|5o z<^p!zoitG(F-#DKV{YsRHHo(CR;eOvQP8EOE$)Y5`N5edF=Yi|@Yj_YQAEvdCC@>e zS>6R>h@-lu!*s9jV++|U>G|#t*%b5wiz>G8zTbYx_Z}C-r6c*!l?lL+_v2? zH)s1rmd83_6%|}DTEPqvX1}J#Q?y!gvjiDQ|VyXaDPp zR4^>UVnG;r?_v-)IQcuEvq(LWk*1ox2Z5t#Y9f;)W(x=lhha*%;~TKzTVDD+RCcph zAdW|xWo)wvzoYPmz;_1Fy9+4M2|W1*tG0jvAHwEc!t4U|ef(+Q=&3#p&l)sQ_d8!f z2q7XazUg|9#G#AxE4|#Rxepb;wy5>+Zfp$Yutuhu!eT6r*~m&zw_ae%N*?LvJJ)O< z-yQ6m6rO3r_D8`obqcv3ZOhK{c#?Vh&Vl-_(=&)a^lOeazwKa)s`N_t)uDCGRqSfq z{iJq#&~`=C^Lv-hG(qe*M%TKFKrR!6WrL%=s4UUE%M6|ABf}@uD9>YGBAXPPI2N6c zK&n%m$+SRhC@Hs=MRrIBRl6%ZprhruQUp@mOA1f(yd?spY)xBD>TiRhJU;6RSJFy>m?3c6?nFINK?DJ;u>L51>C^dUJillceF=yl*H0?v7&C_CQ1JlE zNwxc}5*moIuBMbF+F=~g_O$Dn*O}Umz6Q%K39XZ4md42OhmxNxzR=6~xONSN*x0ir zin$4wBSe}YZ~gL&WR*#?%XBT5l^}xJz-sPX1=1GPjsS-Rmf%2+BHS;vYt5~TV>s8! z9gG=2O5C+vMiF#EcLd`bmT4#ni!qca1HFXgsi}bu{?h$3iE+y1fkxAvd&jX^NhA( z`1tO=FE|TLVi>`+Yqi~`&|h_s=4$LG2fA(+35aGq!*W=MvDB;uye%vnsmMt3ok$kZ z=P1Np38hczz&5k2R0K7`be?>Op(h&QPiABu*D5^901>~aJeuKU3c?X~lM7Jg5t8Q( zSBG=uaLk2bwQ%nRjxc%<+YM&^O&{aUpv6DMAJhWXJAzX#x^}RID!6VA45T))AOal; z>ohA7NJPprnWKmfk{!%td4dxrx^{>gsT#cDZF#CmvGEehGjz1&u5epvI)GPLS%b9C_;UmuW{q>LutXPX)0-fe>s%cBu+1MGpF6N4rdYxXU1 zwn?VBEdiJ$xr@DRG_n@hAU^l|=q`_Ic^CTjqdUYR|D+tgjUd`k#hC=(`}bce{6Ff# zeyR^%v~+BcTJyA)DdNaxROjWWu6-r!KI~vi>`fg>LUS0V=H^fhGs7=wz=NNH2*1X5 zY4qQka#(Mac*(L@4F+u?X7fp?`zI}((pq+LlNva)Z2LLeQTexb{Nuz6q8qIkm{ zSmw%A&7(nV^TYx5(=O5J#-}7$!Gp?%w!?#J-VccgGH2k!Ygjm)9c_74ek`CeEFohn zG6@Gtr$?|+$T>u~3uIz=Y+?HRSghO4&v4Oz)S0#&;!(2iwT=e-e6xA&9<%21c)C4( zOr$3GCHxFl671TX!+;L6M`iW?ws-%UUH#$l=w(yq9PK`h>vH)~$PYXf8Lmj0lOU+P z^&7&E`txIByBs5CPFGw=BU|1*{&h$$q`ulQ zpOTuf*a!51nT)A!$PzUjo9rM%pWoRo#ldsQ0PmATg%+_eSHFF0m<5j1K#I@QW zjtBH*T{VLbR+e~cN-otXY_f0?m=>X=H9>Oc$zw$+y(SRp!;mdL3mm5-*)U*aAt{8U zwLms1npHqHt%0)_eO*A(8H<-Xwg4?q7az`w2iJHmfv;(v8XEiEI7L;IiJfBO4xz2zlwXsBrD{?q^eg7vij z;(DpCS*GUw!}eBxhDR-6=wzyIC@0MK|3?1IBxeQr6{O&)PUg;OI6NG}J2W>ioLP1e zL?GEvQ6HJ_K>6nX%JgYonQ5g`2i^p?PGU}T1RWd#HeHX_WyE-M*t zH`CsSRkv1-nwM6LFFlvqzRA4#0rfek0QfNEsvuna?$v;U9~*f5jsgP!r2^2iV`Ky* z{3P&w{;iWUHMK-!sQ%%C%EzF6jiOtI$bRwDI~I?bp8)t9xZna4hZhm@!S@9D`ax8> zPoQ6SiKKKvv~)$jI(Nz79NAls!%W3kWr7 z59IJwiJ>w85Aa^t@kU`H20``8G)FLT)c)of$STt!3Nm8N`HdeRkid%D?Yrl1br@Rk zk**Gt%GhfAXgar#qZe!ljWDYn30^$;!w1M{13SVz3e^0q0E^!5a4{ebIp7SwR5afy zbbey^(AxlR;(QD65rF|r0;Cf8Zps5x$IG?+4V;&D8NkWk%;wv?uiG?`lpm7~um+HF z&rcf&NFQMy@St9C8h}k-Q&7Jv7{ol@vKXWS=v2N%7<4sISAJd@76iaS{?HhhIG*Qe zq7oD`|FT?u8O}R=2edX&P5+l1kZBwS;CBGe0N9l8bGkp5zcu-+)UacK3ipj|3%DR= zfFSp*?TED?aX~frA@87HeWM7}?u!TI836^H5mEs~zZT$&Q6T_;#Wjz`EBIb2m=*(7 zfZiG@5^K8;2ppWNn}UKggt`~38nL6Nq`RmmMzfHjpQ0pze8^-3L+|_SSE#p8Tcko< z!R-Xb1e+d7IiREyt)pI(Tno6Yd&Z6dHQa-`i(%u{f}%lZ#aIQ@480W5?(@6<=MK@e zO9$B|!lfT{ul<#t2W}U*H-xSW=z9QcAA_uK ziL?V=5RB`9h8}5c)G}{}CcT>VL@r_tEG)(aWJ0M#M+7M?~K;9JWsFO|3Cin`(V_ zkS0EpS&?}p;w2g-0whM4Nhn$`AS`5-S(Zu9)0h#N>6)#Wy)ICdM@|(_IcH5}YBPN9 zzXhMxw1v90yqMkhpK_kYqotvBp`oHFq9rp7F`}kfrH!T?q#ZE~H<+kFGyX+2380SmXPr_@)QK>WYHfuD?JM&44Q>##G zSIb`Ja>-^_W*2k|cdL8<>Y2t_)d}ZK?=8s<%k9?9(#_w|$1jU5pCQXv%V!^A(QmR1 zyXM+cC#ng}6pa&&9F>$`p5Ii^X`5=8f;2xgAz~gZ+ZRT_u|r~>R5yZ}fDNC|`sf({Jsha*sbFF_}Oc9H0j*%9IJNF;G2XQ5Hy zLBR!KNkMnPWI^#{6$;h*eW3`o2%I8LBy4mNbsq4YPmAj>8__ z?WgTqjbV=7j=p*^8ZkOM8h1H;1ike#UYJ8w1};`b&g)>b$;j(srwos;8>8GF`Q;S$QyilXuhHu6)*| zq^oYL18o{@5ZypmQr9U~Z6>@>d|Ghoix!=B*m>&Se4e>FytdT6W$8T!5D7R4!i9x^ z(cwMvC}Up9YdNU9zEjaZ^*isht=rgJ+gspVc?1cC|`=M!CEle$UaeXng zsesAUUBZ3q#AhxOa}tx1JN?t+F5)3It^Sv>_*Cp9Vn#Y^wzJm_-%#Lncqno(o3aB} zTf_crW>rnq=9q7Cwbpg3UFllq>ziV7xp5V%Cc9^*XXkm)d*mWkdsdS6nV0EFH}{6{+2|94{G58pd}p*bxMwYaH) z{TKcJ!|$5^iOK&d6aIm4eq9G$3v1(lbcy}H1j&D3`yayp-$DGZ0HBt4)N}Z&XZ|!p z^Q9lGzBbHFt-cx(HTY64rVg%@B7a!hUjIt~=vq1asr3~U?O(;A2~PcI%>T3`D=V*} zqDU_9YN=;!@ugO*6|GGFZobq0BPsqPm_LSp2lKDZds@~n+yBSzy=Kgm*#HjA&?VO( zhBI{dYjl>Mj1%epwAD%jw2lKLAAJ~YaEGUGyJRjPxYyR(o&A1cXVX6Y$RmP8Flq*I zx(&EJ9VjPM*1!(vV)`44;zR@+_^3^@1nO{-hEEafx0}h4gt_nO#^`SANasluMACp3 zT-2J1ZLCAo7_oF`fpR)C*N)X}T_>=-N)AhE51v|167P;46tKSVw6;&727ZI2X8xjc zK6xwlrH6syU<9vIUOb)Z?b#W6MHj^ORpZs_S2qicX{qwN3XWKeHekD8ORvP^5AcUKci6pQlNiSC@l^HJuA-t zTseO${MS+bN0WcMkkYmMl7s(8`hA`L82^#oe?9pAN^VM8CT1K;I#$-N@K_meSm>C) z@>le0*_i6{S{Yjyehq}0_fMWX;4ssCEx&(~-r=7r)cm?OB8H~MCJs1EbYDVL{%g*Z z{?t(U#|qBy)i^b;ld-a?!Jo4z=C4_o)OGo%L`%c)Rs8cjz7D6po(J7OOZq=%;*a6q zBmLKk`0C~Fiuk8Ui$l-K!1C4K|Lb^bzY{`3!SI9ogX1V8m9^&^VBAkJyPlaVB|sP7 z3B4BR5bzPtwX~fm4GaLp%6%KyUYTn-T~#f*<_gL-3+**aa~OC^`L!m^*Q$2irjusN zpY_(dc(>l%#=rvQ8>pe@x9i;5kM^$|Q_mUn0dRaCHn1U9J9+B;Tv~|D z88B$yw8gz71rc?30ye|LTXkG3@8~O0pdWepT3QDK8GjIcn%1l8q3B=7mG#}W{$AZ? zf~%`*T~?BFHCesXBHHgthRIG)sGz{|e#`vMhsA&c&2Jjpcr{gR<>ng`topK2cs1QM z$|)eixeL#4YG}FPe{n*$P7JnFI5=izRw^WgS77^X2N6*mykgd8UTlQlXur92R?QfG z%bA^bq=_p)JW;T5af=$A9Bx)YB&4PImzt^q*JH03ADc8TmvuQ+oo0-OJD903#&uq$ zTd3v1OnVW0og>T+ZUA!AEL0xe_eZj3DAp!+%NJrep{^kJfsueWMn5&KYkJmB3-WSv z&Et1gZDfT4nBw z>q3djY=~+RY8p_N?oZh{o9>Q$(-aaL%^oqO3m@OP8Fh=BYK&bPX}>dk0dWf|vL6XQK@ihQHHa4bp@fN>Fd6F(XiX}rh zH-~@2CNfe)*2sK=l!24_2qxG|`R+`tAz5ZH%g+?&a8pGVZ2=PaSV}3jJoW~`fZ;4z zruA#r=_cSQu6sItK9)eFCAD3=6Uo)F)avM?rxHhUU%X269`4+8KgoMSqSH!@^!f~OcYC}ug&`Kl388|t^N|K=XJaqZIp^Zou zikeV`sBlMhI1*+} zq9K0%(?Nm;On=Bp`qg%>I%?v?XBOXsCe!FN%Xgj))yk+W6Nx;?2#QmZekB9CpFHlH z7*PqtJfs`d3+)g?giQ(nEwiSXl`l^zTrbu8I8D8x%AyKA zQN?2`M?=+xy4Ael4YDvZv#=zpdZjbi@bbzZjfUc7SukT|VPj>#%#<$_k(DV*smfnk zWn^k8K1C&UQybyPTZ$D_f)tl7soj@(_){D6YARZuy62zA$iCuzEQc6NN=8KL#LMeS-0!~e zQEXaQlT}cZxig0@|LHnUid!8fh=^$Tt>BOu3p{izyv#iORBMhbO75z&tmMM6`a8>5 z1z}E+ld5B)W?+Uz;f5aEG+FQz0PTk3(q3&|NkvIpQPZlLy!~`}PDNWzo=M6B^LnP$ z&>3!R$*fX)T~SGsvbxd_u3o0SlNvKs#0q?^2+1cZ{p7q==FYP4F!Hd|pbhI*-{v&K zXHd2>oW4A|rM1?B@3@;Q?s&Jiz9lPs&VX6!di^k`C>GMF=zJSpk$`C$e=wFV1h=V{x#<-V zShRUzKonO(R7^z3bdq<`4dn(pqN1u$WHjcerUN(<&Qf;uxuv#Z93$hUiTOxj%*`W9 z;;%eEQxulnXf2O=Tm8Hq7oH-aE^`!mGiazUxv0+1d~VEks~Pc0KX_(756Q2qxO!X2 zd0U-g5R;MB>;|{2%RBaK?~ClaIy&}gJjPrM3%}@hZfv3!x(Gl0aNg(Yeh{zh3yiB< zd{`h+mfh$fQT93~q(;WCYSGr-qbh6nh-B|}nilOMe?SbBZ2)&Lu%Txlqv>AEZT)c{ z1)CJPFy6w+@uKs}Eyet<*YL@FnMwL1@7EOxVyMe9J->RTY&o3*>Np`uu}tKvH3lE! z8+1KCy%fh;ZSOm3^iM16Hq6;cr?ua;yoozi!COmO+}F$7wY=$PwqkF~m6PW&!RgUxr9?EvtALy`~L21KR&Q6<@^PR%4NE|=a zZeb_w(~O@}(~Nh#e_nn@jO}Ht6~7_x>RzA*`7IhcOu2NQG$m)A>Rs2kk>~g4BOGj& z$^a!twVW@&J}OO}Txgp=x_6gKE)uy*87oK6&VbmPKbkzcZ0xXR=AO!)HX)M=-z;Uw z57ye8D@DsS?wtD8CGfWkBNFeodrw4_=bHJ`C)i4efS3bA?M4osBkoFeC|>Gr9_=Jg ze)q}&J9|w6nq_{gk)hMP4;Z<1j@XBcuW=7Hh@o+NjY@-h&9=g+54sGEI zHD%xx)A0!x(lU|?99qDxZ=XtCGdw+SDZPx(kV2OQgXt344hE@QJ@%KEPG5^}gr{2F zQ`TmHW5+Fn#(zNu_F_bqeJOb?E%fd51@zx}^=|{2yl8QGyI-PSZuGsxcGjVfgz;t# z^dBUk8ZbhJ*D1KmOVulagA+H(UrI}XXOPpJvTTuu7S`!18VI7#79j$Aq#+Ld zrMblY*rm|l>tX3&ZzCh(?x!T}T(x6OD-VXw1=S9gA&0r8fkrSCQhG?rR@zQ~ zaJAp}!O4DLqxq{JfB@9>#2}t8AN#@-nJPfUpwM@kc;BdxBej>vT7%rl3>JtV*W5~* zUTFSmBHv`cU=d}@Gj4Ps4<-!&O|~Xl^;;zO7&8gO3*58`&76)%ao6=OnEVKU5dM-y zi0My`3VP{SIcICe^q)Z({X{av4o{>EFC%e$`8{+(2Uq+90)CJM7phtW6?G}R{bA}_5Z(nm9LBAt^uc;K^8{jI`5rUaz|2k>t*O|*e{CKaFSFa;n{Y>$|}lDJK$ zwv{=uSKV_A`NITb%)rb?%uQV~W#X$wVjJ%|W+U?v2))B&^Q-H+(}2R&&Xv^}KP!)| zIFI39P7~3c-wpwGrpvZX08N=pdGjet#t&wg50#?PnjhHj`;qz&H^3u7G8kUWm|Ls4Tq_}S z&;mgUAX71}a`9|5@G;l%EH{6ky`Q$DMqaPl)~2twt}K{MAO9wg3b$nLE~{Kh4`_Ka zy1jtOY@L{IbA+%Nw?YCMohKW!t*G*JNQd``_dAmQdSL>Z;G~jm8pYBCk_wf^)bo~b z?LZtk1eGC-C>G_BU|#;g;u|F%U#8V$wtZb~FTqJeR|11b+|*;i&+FGPQ=hYc6e+Fv>0)tqkI&)!A zz*A@r>^uNg;Lz|cGcgG9#;$wfP>?9!G?U)0e?Jk|QHuvEpl!K648!W)Ze9?P)!3IlBKp+ThR$K?V$X9 z&$iY^L>4$pT$2uT&!P$8<*v|sR7?{{;sRcq+2yQl2(;qorxHC47N$2ph{IP&gQe0? z{^YJUx(Iy2=x#JYkRM7*k>?;D#!gtN6?p8D;E_M$&bV@~XiO3|Jc-Cyx;m*`ely|K zJh(jCWY;ph+FA}To(RbEs_+`WtYuB*bEXOKn~I1;l+bryQa3nZ3@+n);WJy;YMbeJ0>86AsIH}AD7zbMXm#=+v*QfGvCY5k zSQ|THQ9cl8I*l@;o!6qz4;+UeNUl3>h`DQw4PoKYp&@%6pV9mJPk7x^J}USN{Wj)* zcdnXOk*w>msrgXo%xA{Yt1%iL!UybJGmjF)yuE2VX4#-$hF_3w@V*K^Qv^Y7czA#A zS!cS)lSJ~)wyYr?ETFYG3d9f>1Xy3;J%441JTk;%++F3& zV2<{J5~(&*b!RRW^Kt~2=_TF8w9}J?<89e@r6EFibxDWM+>h1IWELLk23OTa(+7sZ zv8+-eQ6mtu4r$Yql0bf2Tw0~BB4);!)>9K}+b@Npo~_49O)=I3Fl_<{1?(?m{4m0U z7R41enW}S#hz^U-06ga6;ingQWoM)p6PLjt2Okas_{nu3)JnpzD_T4@?Cv8oyf7{6 z93g~fHQ~$*)+aq=3Xi~iTVFrMO|y*F8zK7A@ftFDniuQJY8nw^0XQyLQlS#oJ?aQC zCWxbmqoMTcO*tHN>IiDEbl~@#cUX( zVaH60cQ7E76z?tyn8n!`=jifnNz^HZbKmp^?wOHQWD~EO(3=1|u6q|?BiSIttb`g< znt1laf#@A9GFOx#^KjZjO)7crwM0Vwjqsfc|h{e$i|)pKDmc-pRSeTqBtXv`~w+7aox@eajB=#2E7%e6?0wd z0(pH*1NsrlIqo&(72VkveH)`A?Q!3Fd-xX4o8B9OJ3M=g_{NAUy*r(HC;5u}S?I&d zi@e+4JIp)QJJH*pd+5{ma&PM9=vn+bu}NSpUkr^TD6$cFGsJbD2d*>;Y*~PNfKaZa z3N;788C({U7Tg0wHE1_%TOeQ`?vCV+rFsgV6qH@FngTw1?ieD^5s67evQ=G%110n;bK!RC_csyAC^W(3u=2TNX>FgI)w; zIgAXnVvwVvjLCA4;5QcM(@EF9B~4br0UQ77Ah#R}B<(;LL`UH+iim@Po%s;|w-WHC zIChUr+;JmZtP#ono8I0%gl-W3PaN=L+x+iC9=@{uu2(EFVa)g65m``!#a8m*pxiP+ zE-UTwH|H~#{NO43p^i;qgKfD^friCcOqTqxmB9J=Mzi$|O?s$j$*<>odK^KwWqW*S z5E17u%=UkkDvFV`%LU+4=Jw?HJ34`&`j5Gu&75vv_bLAD-o4}mf73>hjg0-kISzw$ zkgG4L5c)hm->6b9Z6t0OO4ZP$j@>VpRL^~83Cu1mb{-gtx2s)=g<6>gHyBYp_L zYrIm1_#xQ=y0rbs?*fK37@lmx;EQZe;bQu^bOpz9H4*uPxDqC(3fFDm8qhU2s!P`k zLg<<<={gVhFy#Jhe+RbpF5?^or`kSVwboAc1 z&ebVErsSOW<$6gjm~S>K2J+cvXH*GEFb6N`KFqbQXboOtO?mftm4p-iyMz$D3@6jz zup?~7jb+%}Xr0K$lVIw2hU2fq4cfi)E28(PpH8ne+as$g_{_dpA9@tUS9zEd;=#fR zs{(`s3XTt6W~3~gPBnc{OR{*U+(?c?7ePZ8lc8?$QkR8G_a^s?Nh@hK;TW}gC7i}Y zI~pCwhDm_9NKUFJ0rQsNaF@5cn>PX|s>h0vmT`Ogp+r8g-0p51!j(9_VX9mek|)=M(T~=Y-P` zWhJ$<_utzI_$d2G^S5t$k!WC|iAB)2KFs&QYBdP(p&?TXv0pGi$w-z0oGP$g;i)$O zFhRV5t(NP6#@P%Tv7iizYkpc>`S}G2@?<6P_91Q9j32(Dv_!Hpq{;T;vh(TC0?hUuJ#w2 zQ8*(xA#B8<(L%vK>sVs4ZDLX0+%KPHfFB<6?Vq~wf)lZQ;sNX+oaA$;K*Le@nYs>pwTFV=^p*F5{%9YM21Tf1e&lQsV zMEUL0z2c*Lt(bGuYX*8vz$z`fa(k~!laOXmGLK;Oumd~_wSI%sTxZhB&_KQ?Qr<$WO6On~PigXG*09KJ$|#pQ3iaT!#+=yD zv@gkO#T~LE&y>pEi7`{<)*-b&@^2%3Z*Np?r`=w*KxAR|sm7BMkil8aJg4bI~Jgt2uiiq*3_6%ujP`Ov}?}^ zc$K`JcVrzRVx2TvMARFM3>U59P*-@u_tMNo8Rto0)Uj@!C53}u>)UwBWtPsUF6z3j zJY{5C5ShTtwRbdpIiIoXMgq;{WOD(l>PpY?IxnkbzJL%!%>f-V3c5>fz@>K6cA5ZI zJfdo8rW?s}e2vzitX4Q+ih{Q@mLW3v1<--o^r!kte`C-8clJg^h`*3c5?_mWxx17G#}(p%V3G6_b(n zYB6;5@z16<=9G0(V6LI?Q3|-VO!u4KG4y~lDBA_`BlI@OL;qz`InoXchG7%U4u-UW z{3d_>`#K4~0YHEu@GHHt4`Kf$%ohe_s%o zadC!Or$DIE_ye9M3YGMn;_ir6IWH3N_pPgDI21hcq1Z%@EV@gzzDW7cn*DlPi`ikX zk7sG%%1^=Lr=CcF9mdP<*%ePCy~W+V;H=A`lyxZcp->SLxLy#@lf~8{T0~;KDgq4ZhOg~N{kla1 z)8O%~2|_Kk-;Qelm@X&n$1LX5rl*S-hG7glQAESFB*FQ`#joSr>kCnl{_Mbx_W4TE zpzACwD21pFkb*y;)W9*E_@Fb=P8gSv<~P?ckDm)!dfRNHf*hQigR3~_f;k6yDBal7 z$w_N#NWX);bQ#ImgcX2O7q!-MZZt1nOk-5ghdSQ(--he+_(AUN6RI7hX|qUW@Vtf` zhV_ks&uEOfw6-DbIY73<(!Y2O+^(Xhvd(BDXuG4}!r>=5N~18y42s-bZQ>t_J=NT% z2StvK6R=Pols$=3LA$k0IUY3t8M$ifb)4aH9kLCDM?s21D!kZs?5BU=QdhiLGjHt= zqO&J<@F#U~a^V;Rfg9zUvR|7rni`6?8!}K&f=AYMrk2zS%ImUQIkU;7<0N?1K@ML7%6xN^F_v z&r`KO7^a%7Ij8ArX^f>_Mli$CjEjdD$hlk-AVI?5cSH=lGOt74-T;Od#mMwRV5PXe zZ}pEs@9VO#AqpTrzr3y-e}EAtd1&m zg!Ma(YZG)6dw!Ou3 z9b&z@#eZFW{j!DYqIzA>Dn$AEV)&b%4FM3b@34<%UdSCgf(xuV} z`IF<5{DZM8**o1k`jg%}>NDcg4;w+j57}wpXCHxX6b$}2Jl&7-8UYo;3RotvXmDv= z;&rMH!Z$4z%C~46-j+N#MK3Z@$MRDq#SSvr#G+ra8 zJup-S0*CpQQ1a~9YO`NBA!T)$7vo!Wjgi~iR9y3QPK9dJ%QMIVT6puF_I0Svp3AP* z1J9B4wNqX6j+WzV-u0=^0NrI7uX)mM2GTvWMq)EBuC947V7b&1@(azhgy#jqJvP7| zGGmd~7@dbRE&;ru37s`a*=>7*16{~S8EO zc7oyEf9Hth#>`Z&)26X#`v#i3TAzj@bVVo!;XqwMabvgy`OqLiK|0K*w?JH68M>eA zPiu2ru_0xVz%;^5?vhHA)#Us8gG_Qj6)3*%l83Y=-xt;%;Y!H#$^OI6BQcS{>*(_ar6ehbGbehv$L zzAatWPT%>V7;FG92HiR;B+b4IdMq60QWJ=3(}F3A4Ck)bE9>Gvc7L zhfYsV978ICfY51Tj3`tw%p{H(Vwb1`I7fyY#?3Yo9Xdsu8DckJoy`@@cIog<9It>_n)84QC6xASby+}!n4 zl~Z-av`7gET`(A3`ypAtxf@Du3@C9aXO_=`Cw@vQc=d zrx<3h?Y}5_F8|tu<|=V!@xZ9u^jzhH#{>bX)n0{xm1!om8ol+xWgCSd4gse1(vnb< z$?dm!Bpim1nmCs}6T6*ho{DDcAtCLuH8;CTXYYWHi`h8MY1)RMdw&+T1>*{uhzw$y zyC^9A3L{q)nPLMIRPyVE)uzlHCujU(v$OR8qNevcW6Szq4gT&JG4n7+K040T)is ze(B}6YbQw{O_xhCqFk-+d)PLc})!jU^llO;jG9A9bx+%*9cDvc$;k539U zg(4?{#uauYujeZ@t5*kPUT)}u|G_mYuzI!POR1uJPV_o*`-IZ>d;cd#09#c>%}1UI zp=K`G$V8WdG~kH=8zOn7h#8OE_6&U2pT(WN(WZU_dN>1LRHf^$g}H6Ei5<) za^E$t*RA&_Iekn{3(ym241Z0N-)oxx&6RS2TYzcJci31s_UsXmHa?N+mRcp5McuIK zI{L76RgNYmT{Tt;tTE*R3hD}!1bP4BKC#X5=#5%L;0r~uO^P2<31hW&)%x$*Hh9dD zeLsU2FqC2^`BfWDNtCE7G!6_r>Ku#0naU0rRhn6ryr-GJE1#jL+SjosCBp-@6Y^)WnD)mduP;%6qOlMk_i0(33S6j2u=L7(Zt3aBRnT&Z{o7;3FY1FNi{nZnbC$+2cxnBA_ zV3qjeW(n}Ts+Q?mCV!xZfFZG=Dn1e9 zku8tYHb7uGsF>(OZYpYn4L*E+kTF`-eV8iYH+o(|JG-N32>Sj_l=LzQzd$IlDZULi_-R)fIrpbv4*5LK;QpJaftKa z6CN7a+84~B8^89$~N~YUu z3M8zx`g$km|Q&m1PkM-VzETUwz;sE!TC zJYX_COLY1;B^Q$^JH?-!3mG? z6Vo?d2=0s0yvfIcH{b?k{9yu)VHv%|ag*`k20kn#(VQ&UY*2EFF#BaNY=ChK7;fxN zweTi%n%_>yfBx7o@irSCk?@(Xx-l;`Yx|JAu-E)3^ z>_y?+>gVzgtz(F!R$lbzH6xWU}EO8TkiWdg6{@4s{A59g+MZnt@;P~6?#YO zam=1{9PvRVL0bI>g*Z%qZ*u~M;F?S)?{bq;zn&xtz^)5SXQ;Bul<1n8Q-_pNkQW?N zup*`X;WLF`Dn9cf;uA?4o%AjnDzi+&kAZ1dKnevFKEyV!XX?3a;UX}FT|6RQl^}AI zdrS3a6whhC_wZ_a4_7rg0~$n3E7BI!G8tr#qD2j((kVIqc!}{$8@%D1fc1I?iH~iX zsRL1Q3p97PgAhh-D*>G-et~Ud>NCKV55znFIvWftRO91Ve*5z}P$aTKF3G>QLwp5( z?#4GXuBU`p*LVrAI4$VwcZIpSu@y^;Fx=w{11MY8pC!QnU7}gQy_o`|Xhv+WTXROO z{2agB!{gVboQt+VTOh{}4i3sq;QTq5?n?_u#+yic3s8(C&IPvl)h|%8DBlhpQT&;p zwg8V1mE{%_i$^E0bQOg&0K4fMVf|8^Q|UGfblF`}$dFmNLBRN-9c)TDBClp=hSuYs z0xE7J+>Ra;zCqd*$MFGyt5zSx_TJLeI(xe8R+FMUEJbE^gPIY zG?2ru1c=VKBas>i6LoKwOh5RFN3$&C2>FrmtD&xdg9-IN zu<`ua7e=_t=o|Ft14?TZm?5k%@9g(bWk1zpxxOrw$?3F z^Vw0+$jLN~S!SX&Gwmn1v2`7ER{g`qXMu04RUpv_(3bc?G`1$|Kaptzuuy(g9F5vJ z!fNoef%kobNfb;%FQBDRuTi6V7MC_dD^PJrjQdVSN{CScPXi? zVc4`w-BWV~UaU~lOQfrn5~)GRymRL?8WPR&CCdXD;sKQT4?183a6v^>9QCGLNrx;J zPQ(HOy7Upz%FWB`966j{^2@?+Z;ny@H(#^CQHkdk|;|mf20_gPa zS(%J4nmB=&_YlNLX3bVwIzG7uM+c}N<&lDVL?kaOcsHL7^yLc+cs~-zRGbE{4AsQ? zl_N(0dAlW~960&*-+~9m)Yi>lMS0)nSP(I#RAWOpZFM3V#(bx8quzj{*Qc}rrl)Sy zM297wD%1nQm(P0P7=%Z|Alr15slg_!OU7o#EuOQ8`wj;RcN5(RcbQkpD0q})Q`cRI z7X+Gp&Jg8JoPsI!14Pss{7vE9Z5P(?Fe>_&pYX079{cGQvBykd%Ax`jCDkzA*!eDj zE4kWHm@qP3NLG&Hut-HY9hq($QE2@%V#6G zLQr_Mj56Pj9W~bEb>^20Sc)BZV5{6LC~q}7_5v^Gwy=oe2g$}JE0{f?eg_Q5n-`&MbAG1>l4MvBlYv(;lBgoviSUu=yf1^zOGK8 z(p$LqEAF9@dC7^R{@T{pDUIvvrA1zoDO3;SRDnt0$WK$Nx9zf3555E7YUslr!A+jk zQEaKU)~Z;GemnfZK>(@J+0X0b0np(fptw}x;2^6LkOUa`>AYbt{8?&^`uSe;E;x#cczx1}zj%rxP zp#V_~Mpx)EVop>fKtLThj(+|@Mb#mhi{+idotPZZb)Xuo@({=Cb>RG-3QaH~ ztbwpFIX4)d#a+!OVH9Srg>z3rc!dCvMa>h*SRj)!P)Wf=9G}cY!Tlyvry?_?mIjak zT3+-3#{mVXa!Mi+|g$7j60L`~p4Z{tjn(Nr2DO2zn zH+=AIccg?M(2$C_{Q_T?`UwZ4bAd#SbuBeBXR8i!Cj-BbFoyzAH6ds-G%vnd9~3~g zbfKDDjBSjbV9TJ8Pyyo0)tg=W3^+`DE|~W#9pK3-E_q^*5%d&+7lJBtHz=L6EXStO zPM^TD{9Z$E_CoqK5+M0`JkKpd^)fjiwx3m|@Hjh--P1R4;DP{mkSjjI94ak!hz+r- zrS?a9!NB%sr5?d?Es#Ad0DE@$dwEnJ#t51M@`ENQ-o7|+zd)?Ux-*Cw8b_8!FYtLj zt&ELajo!IHuYmS?K}6kjo9E1I43B|m)P#zqpr?$+&!8?>v5*5cfLhBCbmvE^e~?pb zV?;CxC)VOU40NzvH@xqsFo>TQyJl6hTI84;0dm0x zI(?k}b|UTF3-0Q|d0CPP$DtBuiC(WRDcgRPO|!ey zu`h0F61n1WGa@wFk6v*h8G-=-^kP=C%Vq2*N3PLmA|Fn8=9l*jI6;-pF!dv96Gf?_ zQd90i$yWoJqZ%;Kt_{$N4dx46a|k8YJQjjU;+s)H7v~p;1af)WcKE6V`%%xpzk_i0 z$=8J}nONwk+>Rb@HD=8&6RKdKOJHo!K=lyuS-vB14ymc)Z8N_{kriSSz?~Daa`m*x zZ7$?D@~~yIYCs8c8VY(^YlJe(s7r#B8&jXdFDSu|qrsL*h0YznsGf#t;D^Uu)A!_k z)PMc%4d-j(2Q>4wp$E7?JPWAoK|hd73Z}yFKtbmcv+qOWVS>!!phlMDNwlN)4^5e< z;?3T8BmEAt@1f_9LXjSjv|e{>&5G$64;jjC>{<4&lhW8#c&7VdV#%nN*SL~07E40h zfY8KJ4-N+meOb?)!+r)>;ITGsn7o8 zHky^Y5V{N+j@UXwsZy}zX8{E?7thi%ZCEESO=--%y=mP zD;Tl(pw#oT8zyL*rT^*F#OvbfW;wMN`eG*?GsN(Uko0=CZhFEraJ0|eYiXk=>x)v8 z3ld3vs^1lf;tBi!6igYbLUE4X$>UjkR*))06lU7M8{Y2D&d{uD99FqTNI ze!QTjr41KR3`8=xFVsJ%{UZMlRZf2aQ!C_RFP{U(=)lP#CXw#$3pkwWdmc`!OYmI- z$l!xujnQ*?)~G0|S#yGQR)1PuGN%DLVAH^;WK-*`P7CdXFcWJZw)Hl{gg85@5tOvKe}y z0{|U5cNM@hYgVtZYL9;2e_=e>pP>&_WgSW6ru3c4D7c@TD)UuC;*ak^-($Oi_MpII zlTUZOw%fRit+B48IQaEd`E!VxR2SxB$QP_N>&!1h#TG0)%v$r*^l=XYmG50WvT{j` z88RV4JCP)X_p~+)E#;$=&NCo4@wn=ptZkn(?Hl>$GZ!m?@`1N!2YmmzpRj)Ffhf-e zbnNVAH*!y+I>Cj)TS)KR;E?tAU<~EnXWW8nZH?Ao-$zc^pk2~2@u8dF5UC>ea#U9T z><47Va6x27ja)hiPNkBW!=^aYRd6LN$gssoom9Xp{f*_Mui4*AeoynQ$4d}@;)+2F`Xdlqd$XYErS7_FhjA3KGgpzd2 zK)7j;nWT;Jccd3iTS3=D+Na`OW1X!|cVDwJsljFJg6C&18r@J@_KopoKH5WhAKFjg zO<3=v&tRH6&?5oe9UR~duD99YsF`dQK1U9impSM_&TG^W4SoRb0Ov1S2wRBZz{f!N zpnA7MX9!&v>;17&C>K$3E!LZeEfaHHhCf4S&=^-1IjbYt#=qO4NLw)T?J z{rZW+J=DF%eZWcQNy?(=!es@oN{%8t-{7(&qdKE%LSd_>VxD?&tEgl50pcWMx~?T0 zU!}L=t>$EVIo%-Bd@(_QEuP2C%!??5Q>Ht$fPG!Xt=?~znV%+?fpx5U-lfq` z2(~id(mu4Agx4a`95z%J-bu{@*MJ|lf@kzfC7JnlAUpcZ(IB=N6qjpt9V=Mvgoj0Y zQ58si8=Qll#VaL`y?I4EW6K!IZn4{=EMY#Gc^fl){cC+nK|Zn3;)(lQ-DmDm&=SQUMKbPK>5KjB7N%~7K4VI%zLjOn+S^ON?1 zC-Z4*b$3R2!5UT|{A@)()dI5OFPTKfA(5=a;=3689^sy%71%J?7rfm3r8=IikMT@c z-bgx5i3}`zj_;!sQ1mqwB;50^zNd5_R+XM2`$lB2M7lZrsofq_?paijs*ob0zw%C) zpNJc)RiZ`dsyBViZWh>VvD6d(yWHzsx#lU{nKB;r^brA8fTYj;^ErD{xIZCtkEQCZlBe=2OT0J8 zHs~Q++}DjHaq8ATqF`OZkYPs$ay7Bi)7SDPeaBmJncJ8FIZvM}yD<&I6e?6=x{cq_ zH*~u9QT~YGxbZCVplw$s6Ya^nEMW8V6{|QL zng*x+Pq4kU{wHkx%V{L}6q&oQjbAlM<0`^igznNooOH!$J@4k@jpt<`>iRpM-FC(_ zFY0Z?a$QVG^M>Zr0RP1z{G=zt;ABo!I;f zcuF|oguBU6;owx-QrqH9%AJG47MAWi=HLV8sw$Vnx>j=Y6G_?Ub47_(KSo)%$2X{u z-4VH*A3iK@*Di05anF<&Mny~^Oy8NI?JYpuT3cF$4+9iX23Xb`_sM44ntwG|-}*{; zz2AR2Sh?TL736r=>@PpQ9jwUG;`o{}m)*G+TFkE~zG?P^v;<6AYN{w7 zj|f3_JTd?}yDmrDVi>&Ya|R|IXS}yKj9oT?!Q6N?KrDEyiNsaIA6UT{?!f3(i(qhk zF|3*)BC+kwf-i>|ox4(rQZ(S1*UmMTi^6fgQ7w*Glp=3!ejTB1%d58|MIKp0B~nG zQU|YUQ1fAGwJYOB_S(1AQ++c}UO4N^!>g2zZUXQTeFvD$`w#BD8XhyR93tQT6bYKR z@fn%@6|E@t9k7#_U&-I+#ocl)0GQFXDSt!?%&>L9vt{Sa0Fwo-v%ngaWFH`9Vkkonw&m}s70T9KC%0{b*0bF z){TBK5z(6Yv7A^s;CRqmO+{0Z_}=N(ftxpLvj=AFV%Jyel+ z6aRa^RpIxgUEu-5u5zn(`A-_3_!SbVbhnpwVA<(Z9$IG6-?Gft_SIIq)b>|ei2+Dg zh8yHGJT^l<`Dr}1yz(UnT(ZZ(f8G~rO?boFk5OS5-_~6T)G}$ruZ``s7l1?7oZO^f z`?6l0egHWU7amGYBrS=b#zQTOLn@RtA_V?m0S;f<-+)3w+fUq1k3(KC9>d{v&`ivD zMc&)(z2Qd^(oKoL2DCf;ta4lT0F7&yKNQz~+gr$N$fRMn@k;qYQT!oN(oG4`V&BFojW5GxYK*m}BBZyb#^z5;7>7 zapY3*2^`9oV4hC3YkH0_DjgWenM3_#EMh-{s6*0r?k#AcCSg57eGg-g5&YS?PSF`J zrMfM~O6i`XOUXD+Zd;o{l1;FSCjqB^UDfzbOx)UWzE&dJ1+KYkbLCxyxWIc|C=SLM0pKq>*&gxVJ?_=h{a?h4 z-OBI^S#P`cn3q?-Wh9x4V2qlk-gDkAq%Sd8Oa{|d}|H*C1 z>9@7dvxpXrMn~jR-Qd0SA)0lfY*bV+yw%DuAw_}!0#K=x;&FH&#SH@-0i}OwuW%GuB8tygt|l1Z6CQqd1Uf4@w#%@?u!CkwJtaON9TT0!%W1WG)38@)<+wDL zezYRYI3C$(o)-p5Z@;>_)X-P7FFso|i;)H`!C+vxqZrX=vTrm@D<-@O+B!5dBkX9! z&aO^>PSfrEeU8mQim*P1CHb zIT^&x4yk@iA#i$f(^r?g97u9#G9-FfB19z{!Fsr_N>UQCpH4KNkA`jwTQ!-Ll+sGa z;HfhaKR1xnsGb%_FI+FEIA4K8=#cz-te(L-OvTaM!$(=i-Pr5Ap`-3*CMf8(;zT7; zsJN2haNuxSBQv>M&*UI}Ot^KZt+L~0ZY+JG@=nUp$fu3Evm>_&pSP{FxVp5XA=g0V zykn)MAt}t6nSE(yuBJn1!P3l3ivMO#c&R4P?5pnlP-zaTa%-ij<7O@)qNZ);$~p#9kU+79o;39^N{bVNIum0f<0O@X>Iv;SJ9~Zw zGdE!ilY=n>OBV+#eHSBbelHgr;b;HCj)B0WAk=z7N+c*%6Qin$F_~zp@yTqwrWz9; zHHo2#%0gv!^?5)Nl@z_nV6kd4;dJ=E`n9{{O=MiX1EZn9e55*k>r&CGIXkNO>d>D1 zQcJ_lN*~GMwKECit?Fb$5Oun`dPWwHue^-TRQ^C){McFkUH-s;oaK^#Xy)GC>M^6C zg@mHSq57>u3JJALd1RWZW~vIVhDt{{mydAzY-+qRN6Cs>I~8MPQzgEqhRWbvUz+*; zF{m;l8j6YPg1TcrfLN^_s%n2IaHV6AWPC?;>X){hMh#sfQyVFZrG~h@n}M|oOKCLx z)j__HX0OJQaD?LNyjG1Oy61w>WwU!n0aN?duh1EDiy<`fBk&@_;(L{_m zwCu=eD7>b6ylQGvTnD+exq-F}zn8Ft{8C@)+f9)B@n}%mYF^QJ`3=$zBeK9@Q3&v! zdLv`KqlLraAbP(6g~5Sw&~#1`wssO?a&~r%N7UrRSowqmRa+w)J2y*}gNwe-ihq*( zKIl?mdSP1abG-ot!);%EpK1|V3g&p^F}*VTc0DCDrS&r^D*dSWfqLF?8frb-WMvfv z)pUlo4m%~QtFVrYzDqWBHy1snqx{YU$x!|owxOAU@WESPU_6ASf{66Z*x;?L^yFxT zwwj#JY53qlV8;#n?Cp3m8EMhvw3t{9hJ{WmmpwoKLFJJ!3C65(8s%J+yBSISfoTSE za?!Bt_-KSEXK5x*0^sZW{X^|*Q~Shtd8OpgN<+(v3Q9&AJ2fTiFB+z<1}-AfKdEe% z*YV27Bd-2MDYP1~NgcUVoCLPN=j7I^gwx#XZ~EeiEDjO@hX;H608`_l z!X(-jW*%x&9|QH{{JQ~lchCsv;-u=9_lFcxE;hTpJT&SZJh*iqpLdW$Ng8Z#zt2I+ zY3iGi*(F+@Wrcd`_p&q9!twFt=^4^@pIPdAJR8Jd!28Wv^=-Gu#e62b?`^$%ZNifC z0krQa&8PSC%8IK~!|AO!_!QpzT6l`#z_P993Z=EB7ys^#dUOt$sjR0}-hoi?xnKU_ z+9NO5yz5e22s|83{cncKZXNg1JB;zbes~|R6Q}XQk*m4KsiO_=_oU)f?dh&p)!o^} zdfSitR2ujF4`^*sEId3IOs`kv<_OxRyY>3dgy8O^sXHj1nd^b)SIJ@)sjk-pHP6Qm z*N>WPp7RfZ=ji^M+BFWJTl0sN2Swgr)h$n6x79_#vO`tfjyg-9e;jXy=2x{3@tl2+ z);Bv89X7*tD@;1tX-%dzhpB|gICwvb*3e+D5m~2GJ&uD@T>m_6{^DsOEVb5CT=Pa{ zx2^K{=Du|gw-b!P-Tn4!)5@LwrR$UBZMvHM(A0~iA3yW;xZ+^eur5QFo$YInzh}Mq)rK{mwtD8Q8~<3?UDZd{>#%j! z2B)2Tt#y~P>U#6*@2csf;v`&lyN~VSndOQmFP`>^%q}}agY%@2;Z0uZhwX$a-b35U za_2(8-tW3*>LV-PAHVYLKV#qW$zHJXmnK zsLp78lPl}I-%rAcHja>_v20pj^IL8qE z!diqi6<3`fEHd+7VD^nbhDo6wwFrbN;Fj5e36?*e##|&VpprVeV1#_`QSH%C4l6|F zPJ1@!Y;mvQ+0UMR((kzZh3Wf*|73}XQ=|5-UZ4?$z}59k(rEzW&^@~kpIT0zI2VKG zo*@paD)*aCo<)pgU`MUb=Z0xj^h4r9Ae&G&Uab%AS~k{h3i=uS8TpyWJ@L(tO8}P? zJ`P;oxvHz=4M)m!`3E!@0|`kSb1<{;M=%%PL;UNg_ulfJ>R!qo?hW*f;|=4D;tleR zVd`z>$hqM}-YngwI1ioxiy@!#o(;TkeZo0YU~7U`#vkzuz17Y9Km1Jz zwz1ZGr+b!r6<>-MDjadRe6`Bs1|RDUT2yd-b=6Z|2B@!Ki)vJC6&-&#GAZON{@L(? z8Jnz3z=3e1(D56PQ=`Y7IP^y{|10n=_cV4>O(iv*NfTj5P}|``z1q->Ko%HDi7EFF zvCyIHy}L+?z&EDuc_|yx9D{V(zRL1N|{}$@kPHPwuIe38B4;h7>i&+$;fYy?o4A|o+u1U_b905-~v>o8n9>t z7ya_P{}eP4HCm)5s0xq~U?viEpp$vRIU(iqv-jo4)hnO)qP0R4n}s!wbPjt76@L0h&IlU|K;_u+6<^&E>{e;6<+DX2e6m zimdWy)ov8#y8JSQb!2rUr|^G~mLwSOF{Q5TYvl}a$1x|*BqkQetHu`X?HfU|2T?m? z>`RUs+#uD3cBE1flfj<}i<8m6hb?H0IC=r^UmNkH4gZcT$drsGaU8L_0iG)&&COI# zWE_QI$dV#5_LGa+1}&3^N|TBv71h@WQ4vo>9{tXsGnl8UF>|`-NobiUv8U$nJ(!MZ z3=dAEVAv8>_}z|8VcAZP=$fe1UIAAm_^|zzA3df|?f~a2tHlU{Lrn-A_AfmtoKRtQ z|1#)4d@q6r|5U?VGAXC@x*>1bv7;Un5y<_sn}VT~JA(5){JD%fLhBQ+fo1~;VIp|( zkVo=2)YU-C1~~;5wGW4dF6`eHQle^6vfMn>PgcXj#W1@&>93LHg^o9}SqWMni&B{v zt62tV^xL^HL;Cf4?;6cTB5+LH%leg4HWWL;vL@tx@Ot0gfGIA;UL-?sb(RnbKd!d; z(wcFf{UTsvqy-U?iu-`i&5G?t`WI>-IMc@=*#(60v&2xtoPrJO3tmMCOqf_W+niwx zqI*pEmt%rRaWg>S6(D03YexTsDUDz>Xd4&ouGnuUL~I*XlIy8DUSk*9skdR=ShtA% zh+JETa|fa|y>DUqZC_yivkNxH$z?&?;uDMoG-5ep=1ht6qlT|6{Nw%rYMj)GF9S0k ze7fE4I-nLNX|A#4lxzR!_~cju7Ah1fGzu!ToUWpa0%yZD*SB->azQp}={qr0%yTQ% ztb9>0qsY<7Xe&C%7%wuyTmL;*28aB0y$}sf=QjIB1HEqVV{K){QEY&|p2}TvR zvaeL0LwA8=i&OT+JfeHqH;~lE&D0MT9!3G%DKqxXqv=Vt`E$$1Ov*B>lJ6*MGQTfB zTdU+h8>N2_Ko{T#Lmai%eUH*)5q!8GQ4!OJP&TnO>$B@>HAbE?c0WVv4A#Nr6lM|3 zK98%4O_8CZA#W)pHy_J#G@Z(De86For5r*Q0ivN7ZrPOXWgOFDMlLzP?r6~ZWwL#j z8Sq#(<{RqzfHH;Kr_mK_}@pB52w z2S+EtuT(quj9*5ll>WaD=>HNs|JFPICU{xdp#IWL|9LSoGUESL{?+nVje+&ANiZ|B z{4eEyZ~5x+cPwT$Cj9@De??*WB1FHkf_&+qf7MvNI8@fJn13CAMWOqv&tK91)r0Qu zK6HOa`n%`9NBwh#|J439>c1oWtA*k3$aG&EDFZ$mBO}ybt^X->f6wl(F@MeL@7BN1 z;Gd}fkJ`UKtG`D5H(UJoa{Na*{b!Z`S+IXC;J-ZA|HI<`O}hTIN`FbJ|2AFOnd$MV znb^McSSBXsFG7~#E1k;!4RvMx;#2=YT^YZQ{y|+?zewGGqps|1|ER9a|FK@h@Y$IE z%XejB`T}DA@m>G=oc`N){a4D8|MFe`YWUC0|Kq#4Q`YX!+Cw*b3 zr@NPuaFgBQy65JyQ%U>$G4-o}fBn~rNvIY;wFr}N1|nc`t) zxs6U&KBBoCWxo9RLYm|u;j^OJPXuqDhn+OZ-Ig*8f=uT2qE)QnRk{V*^meC>9X1-S z@Yp$S+u5<~Luz1wkI7ps)2XoKf{fV1=@4jpY_{HnF<4nSccvCZrs2EO=}>$De48YoI%X9-eQQ%-gTC5VQ(tquX%gsvBVhDbE&^1kwO9V;_8KH4J0VPO-;?qC?My%ohU7 zxq4&gT)!1|K?{m;*MW4Vk9}uAq?12nKlJIl)xB`fP62`&u7DHXibl>p{1d^ohTMLY zZI~_kM;krcoh`e{uD^hcD}soV+p%u{g`Ts$w11c@NRC%s$^8b}E1T;PRo0|bvgc<> z`>>lro$sl5F!(kLZ3h!RCKt`4%QQl%gi}gL@VCs~kSm=;|3_Tt$eYYyLZ`>45wYGW znz#C021YlI=nq^FJN0hq`%G# zlm-6}2;j}29A1^3?WwK)((fw{Pc1!=R%kvzGz_L!h|fE53BW{hz(^C?wbOiV^bD@s z{aGFg{(X=#H1^t0BiBzwMEM~EBqG%_iiI$cg`s`GK_Yo@Z+vJWENYq(XCy=V!F}O% zpVVmt%Xh_PpRdEw>o}aEvZbeNd)1dC1VO3oU5_rFw%fjw8LE8BhUOM0N7s}w%~aZS z%^kD4JpH;G5Of8*AIZ-T(M#$&m$RUf;z7*;a8s$wo;;(bEG|^{tjW$)S1Il>O(WB= zrP-3@ns3IUvwv>FoJ9}Aql||&29g~m^cH?<_4Pbv4H&KZP}m_Ke5HHS6~d z!5S9%%1z^%FvT=s3#-(3s9LG#o^OgFi(FX(oIJ)eL_9hBkU2!6Gc=aBv($B$g5Y}w z>rg|vL+;MhQA{-B5=Mn^0}b%Ld5JlgE1XeyA|4kF)^^Ve)0LJ$$SH`^bA;gXdCGI{ z%#GI8vlzL)whdmVN=6COS+M8PWRFXWH zoW*3udx*%3x6)Y{G3i=4y;z3;c;}-o;52 zTbFcZz*5UV0p$^rBk`)3L2AHYvxCYK{p8!+{YB1MRg!TGUE8tpiI0j2+eyrAE<}B` z{(aMWri3xIU)}9{^`PZdfg89_ghU>xyz_$g!uo=8TX0vFj(GRrpHXbX=DK$Fq&w*| zsWXE!93w#+CoGNVC4oyFe%t)hBXFtyb}hD_5q3Ya!8TPoQaFMhcNLYWc|tY|;kJ3V zrmt0>zy=j8#srEKCKp^z=)U%?aJGeQ@bij%`h5gr3@M!XJV4X*_!3XXH;HvepbmbZ zzrrb1{`8__C@KY$7G=z9mYl_Rg1_5=@LJPf_{uMGr2PEK?viJ7hhqn%Pvo+Ltp&S@ z$px4mlzxKr!tA0QZ}5`r<&%RN<69+1WA;lIrY_bfb1hZj@RP|ComD(`dD6+>EV7+p zMNg)u2NcI+gf%flq;X$y_h1`E)7#brozXP~XH7KKX|7b=Sv@ek(ljTp4dLu|?R0@P zvIXn**#^zJqZ&P=;E(hApl8A?9OiP)SZM{D=4H`gzFtc$fXy+3+k*K}3va7|bS769 z*70HLi131#uLmsUQs14M`JQ>dAb7wN8zXkqp>mHW60){KiyZ2xl_+|28xWHq!GVH| zeh}xNDRoiy9@nf@0_sQ2W-J#diUhXUlko%qp{3AyX^(paCm)Vum#WFroJpSOWRc8DWKwp%|Y_R8M|Z3XA>$U zq`lxHGN}dvjSz|D9OKOVsJnp+!5fnk1s^k=IxfXgRnG|m8=SkoDMCgr!N@ zDU|U7`~b-btk=W_)avd#ZAbENIo)MH);k1#Gp%olNDjM}0(wKhwjq7GCpnurpU4ztu5}Q-;S=U4Vl)Wk&o|z=gH5CE}We^1CSm_x_!>K~{ z7){j$kl76R*BL^EDCz`CoNj+$Sica^DcE&yTw1?^shnbbTy#HlGt?hKq0RUPh>>6% z@u(m7FnW$t8`Z+_{W@HGza4#Q8Zm@w+0^kF2kn8hgqXxJQR}fh^}^ZkX!*8e^!tdW zu(XOZ{JQCd277HLXzWi(k4RC8Y`_TZ3=jUXxgEhEcu^#iEog%lztP~@fi)I; z$)x6X7JT2p_dRS1%(as*{}B1)r>q%a1Njo!mlJq;8q(v*FzUI5*wR^ryHS&S2pc<| z!cbtRsDepV>{QcaqoplssV)$rrUGB^ZO5~^sd^V%%*LDhPtv;R54n!w(G5XIxS7l> z;QQ9==AY+tP`^rTEr~8Oq&)!b`2?2h;z0&$YKMCN_K2YG`pT)6hP6`_ELL&SQ z2>Z74K3%bKmty)!zPcOWt@G{K<*FpIYrWv@T!rTJZP(=tY~S!myxO+_o6(SASHE@d z+9~tG#k@UY<1UJ_BCunY;*dDHP56fPFY*TUGxLV^8@`gC4{vMax>IdmwS02I#as?= zLw-d^emw#sBm-(hHinb^fVX!Wlijvkm))`R#w&Vf<3cs7Cd2Nkis?5H0B=)Tz#1HU(G-B=X`%j8V2I&CfOQ zDH)OW9$Qba8fqPJx>2 zLS{UAAYRH~QwmBzm|mAr8TN{zta7NB z9T2<%BnsVmC9}(E`V-4%A`j9JoYj%-10`3kSFeE-dCG3WPYMJSE)-Lgi({bW{N>0e zD$;6<>W<9^ZA~hk;;cf;gBkX?_L%mdrJi6R z!28E-kV+Sr)Lr(7!6KuY1oRm-u4aZaKG~z|Gx}&PgyS<9-oZuO=X440o@;we1urb5 zpDwOX$!4zGx-KWOCTk0mkgTew?yv`Jm@q#x+L5C}9UOxnW|W%qPFG^5)O+s}p~eAM zl;<76yhh&*3F3+SCi1+$$RCeWTB31#*o~=Sf84rY#~%Lx@v!2Hf!vR<==~`L$PK|L zU_^|^zk?+H@jYbqMpk!p8sAQc+`auZLGy?X1N;!{E)PE|Bh)%em~7vA8K?WL8Lqj%cfMTQC&BRx{;|A^Jj5`kDBA;?w-2#Z7^= zVg3VoPC;>get`p-bmDu{91!Abm0;Ym&mDQW`ZIb3)2X)TLeB~00jnmHMT3is#g$1P z#Nw725*l_oYkuu9T&>*oC!j8mXre{SMKPa}FKeczcC+^`TG#z(o7>mR_HlR7ccY?M zIz-<62K_Hb7k#by>H2QW{g*~@bqf3(&L3H31flcyo4}U0!P~v9VBOnq zzaG9fXBBi?GcMviZNt52K5G+B#0fnd=HkGGGCxa!G6rcMbrIPs?|5{CAt?lwMF&MM zMlV*Q;ZRBRaSRnXKe?rV?2K26mPj)ExRt70uJ21Jd|2;CQ%fN>7i@FR_AlI%@Xc&p zZol7j(&Z-^oZX4H38->+bpOWe7Qimzl##ek8lYz5#En8$D}qz>agU1q?A)3fs-qY%}weWhtW!mX_dj z42AviaGQimYm=r-H!N;xD3x?|pg%YpSu4*yVllteg~OcvD|O#YTKf zg0(k1dcnVX)NzDSmL0o+o|e@`SVx$(hA~hOq*TPcSee&7&2ngtueOCY8O-(0jVbLS zpu;eJXl!}LDQFx_6MA!+2#O&|E<4a34JY54#NKRI^y;B?_4CJaf$IIbM;~4vRvO83 zntC+8LJhww{*Ms?j!1Nk5nz{=w`@8GurvJ$J=~QfNb!7HAU8l@p)C6Spb+MA6-f3r zSn$|*qyO3d0LJjOdl(z*A%F#r&?+z##twnB9pkz7J|bmdJ3L`6+tP0)Ab?=jS`VD}qq2~EwPWd%i=Vh_% ze%En5yP&E&iCB+v#K!#0Fg2yBh9V15u_7{qTPd%tk75;56dYQ7E?y?tmLYSeM)??1D$Or;-mi%rq_o+n*YR(^?ax^23%QpR-O29E*tHxqo6%3hSL9&gpDR$gjxG2>uMWKcjm;kf#zLE(pKG~n~5Co6ApwZf5wlf|7ih{e=uYU6xH z35s2SPZHEY$sJ4(Gb3f>_stxW63}-Jmh1(9P_hveD5RXvtX3?0DZ?Y6=%zsCnC48r z;RgM%$f%`5gtDr(IHO-Is~py_Nd6nWt6-m7DP5D%N}pH)Fyy5{f9iw4T#2-iG!ot} zE~>!LteYf;UljvHF`rgg&v(DFEm?_R%Yd>H)}{?t+uNzuj2!j`{dGl7+!P%t4A1kd zO>cETWz}>RjdnZLyZ$|e#veP+^Pwn3tQ64*7VD1Byz@sI@9^I#8f$HrC*bh5nXzfO zqZ##=m3Qxlmz$0h8541FwT~DeM`jG7a1j`AEJ?7M6)hYtJne(EtF3Egr3h}i+N*PD0JCous(s98!8AbWDmt1 zvmq3qZc=C-euLTTzMVTU6S+K6hdoKZRbE3igk4dHXhIIKV)YaJg51tBKJu-+P*1xX zQTwg<1tle5YKl$2o(`0LQF<>{659q(whDmML|O6Ip6F*CKT5Ho$}8U9bdqQ<%*uLV zM(#&~2I)%m?+HwRNW*#xL&A(H(u-C=L%xLyzi{r0(JZo`}al{_xf!PF~96@Zjl8GZCZxk$x9rBKFCae1~3;tz&RRN7}g;tJni0so4B5 z2ewZ9KMK3*u&B1~O-M*Lf^;_%#0-t}kkTLxLkL56D;)}oNQX!YNJ@8zAT1&xsWeD8 z$Zyc==e^$V_k8D>fA)LUS!b`k_L*nx=e+OP%``Y7FA9><4vxMzYtM_Fm@mJ3#CnjD zw$$Hw5-Lzf%HO7%p(!zf(b(1rZzH_>kdjjVI2uDsPzxWo5F-^MTxZN!A}}|n}ze`{!!06$BW{8Eqbk|6wo|M1-)ri5)l(N&~FL#}~(!+iS#ZnR9h2?NMi%0y)%!{=(RIk3?l}bcK+CX z92ZsXCmlt3VJNP))yDcBpKD*%%Iswux1xa(sZ4EP(MuIE=TeyEEZFm&Z2QZeB8SVO z2kW=XH0X{T3bcI{M{8t0>^!+-UM6C|(dL-CNghqdRTnl<^z@$YtA-si+tV*}x_!JM ztlzJMSDgx+KKo}h&*@i>N1N*iMNFNz{R~HtfI5a5I1EA=A zo3aWZn)PI_&$VWD>22TYAPR7BGN9mgU>lo$%#v~#ewR=<+~9d=^$mK>Ml=)W@v)nI zG%P0!3q%PaoT+eaM^yq%?-QDS&3GbOyc$^C8?*!z6^osb$T;3Kc6n2^%HE_E@QFtE0)|hAtZx$`q-NMYbK3*l@aDe0N#r z$iZDw@G^o}+s{4ybEf1GYV)lr@C!|#QaiNH=atT9zUbz(b{q`LT!Al^L)^>(KU~I4h<^zjhjQbpethkbQ8N!WxcjxOzvocTj`a9t2*6b#2>}o@P zYbTVds$OMAVv7Qo6i>9Ug#a%fU{b(i*knhvnL2T*6MD2!9-`8u52T=QAyRozcL(p> z3MFG8yW?xOD<1fy!PAXK_TKjq0?^HEOD(Hf^!bLJQ6pwY61`b%2=%d+^>9jXi)8SI>%#6A>!(j8@!z1Oz7V`^93m@ zt0MW~echqQw*up?ggp*7>2n&AiWoO1Z)>HXOU9aI*1OyuR#+w+A)k{rxCsnRu`o$! z=&jRi?t7=5veCakP~4Bl&q96R%R0UuiFp@?%tjlGQw2?PG4#OEprhDm)u6juN!0BT zAt51dCHj#CxgC)$R5IBj{TE_mFFnS6V9Q&z$B8OK@-38HM0v4BiH%}zXHS8Fp9%7(!@NkRJV#L z+jGjLZL@sx_|)@&w7o8KlaCXVvCH*>h0kyI1c%mL>ZGW??tAGfVzQO0{_YePVg~S( zx;?XbvdO8vh518fZtZLn$K@sQ+PxD08yl;4RyP>pU-)N7$Ph-u2^RvANp@vb41g_Z z&Cx|Z{r;X{8PN{y;0Zhql*+D$bT6RPiqZ%dGEc>cCDbd6qg7- zzGC#MA}JMt&2J|_cVXj-CW~d`7d^smAq}I@UDvsJUyq{}HkYfPy@HGJ z(omZH>rO9Dt;rT2EDyva#~xFdlm0CD?oic3?q^nR9t%RZaB3q6>%rR3MAdcrDJdKK z{aKdGD&6$&bP2*Jxt#H6k4R=QI$UtJWyKB88cGVvWQUF)R zsBWkD^kLzm{W(i0Eoyq%KBFI!gID|skFk?QAbF3mV0szdkKidCt!fDzfP8PClRl}G&8?+nRe9?k-S`ac&uMY` zh%P6wBz=^no`Enh$1Nnq=d^1NCo8tt+1A~L`1$Hh-`4sdPvlz43=YsF#l)Fh|6S}mR2xssF zh~sAW-?Mtt8$-{3{-v$`bDeOGLcQ4Gx0M>t%e^;4aeY%4??%sQwxUe4PA>^3PHJL` z*1VmL0=2%uZJ-B5m5$n$OSH#P6T&{b|4DDs?N>)MLbXL~(|%yv1sUu2{4_{)l+kG>IY;IZ25Fh(%n@}2g|W*qEUC7(?8 z7KJ^ObSY-6dJ&h^OcCawsNFV8q}*A--w#U1q6mCBn=8CQrADg=QzT&Gcg1qaxo7?* zL=irM$rw8Cbv93e8)b&|T_zV4x#(z;KETkyS;V=qQ;At!g8Gn2$U@_MkyyCH7El45 z{3cbePmttX?SFWzZv?jkzC_7gg3RlmY%#pD+~0{S4OGm`16Q1Mqgh0Mi-l@mkS zeCYy?BZa179xoVMD_0j{4U_2HF|ktfv~gY+)*XA_W{W5`R|$v79SGhcCEWaGm7QSW z(c+T}(7ek&#w}Ewr3_gOb`3VC{K2-e#(>3c7?6Z?0k>#)Ve!G%P2s?(7(kggXhUHG;#z}lzcn<+A!HtwFuO*PXwUE&Fa@4OiqR?M(Ktl=JvWZ1;? zGy}yhTG^7jP<#HHwL5pP^I?gWmG?7YTZ9}Lj;%6Ez?$G8gquBt&LZPA3PLmd1#>ud zsQeDlCN%vx9C16HIJn&-cOqxYa5w;N*6|$c6W;~ab@+xQdGW8i4x0q7QbCk+JkHOi@&tA<3732B01t%uRt@?{L=iZ~OK0dCf|tk>ksRj+=Wy{wsmC|;aq0ub6Lb`eQeT+PU`DbhKGqJJv=x^@TZ>uVViU@8+1KbwD_jgJxLLW{ZUH<~GpO_R2z+kQh>% zq1X6`3v1h1zc79^zkiCR=cA3nUs?LVVe^sC6Ne8pM-6PCOnyjg@$q;1+~_Iib`T*dHtL;rprD`o;CDg%iHBCe4hGl^RlV`W+R z+UXKnbivwvwnLOo=aVM#L?V_gWpEC6VZ<0<#SWXbFXric4TWr++YgF%$pZjzzgUKrjgg8MDDC} zkDFV2w1;|vjF+>B4@xhtuKW5VJYFmwtX~<;e(sj0;}Iu(itW6vnK|=2}oGaA|^9B!V=J5_?w26f$Bj5P#>7B z<6hG|><~5pL&UT~>!HImV)5R90ol%{J^5fNwjB~u2fjwunRMduqSR0`21zN5rvfmx zk5*T2-Xj*NyxwMN>#&s#uXEDD&p;V;jUVYM@o}+EH6~I@4?_<+H8?t-BnFf?Wnhw% zm`dUtYB0_4_J@+?(@y7YNLXx>P&zu3-8jJ34v97isu#C*_nMaV5_|!kgXM#rIiW3JBkuHAemZ_FC z0`-#cD%2o!C0ZI$g%SqV8O@DisBW;|>M*_epfbeGlMsLAbpH9m0DZ<;PY3ZBqYz}X zqF!}rA+^zj6LB{Gp^R_ugynTcsvx`%vD9m}z>*hhRC}I>&{`oJC@LZ5)}&$cvNk+@ zN!W7QF0t;XPwG%n#(^P9Ufp>@DM;1lW;n6ION<`-W?0_MFt7dQI<;D}LcE;)$Ov7e z>umL%gUx&=lQ=;t1cw-Zg!-brJloyTkwwRVgXm48P7yM%Lf_35v&{CaB)^@mg-&VZ z8n%&5Dq=&?!-a^+qEXT5mrEFIuNCM>}7hOB5d z&8NmoG07{l$-swqfj68VfHzu_`p_~WIIgmNrdyNa)$Z7gbnJ#$)1;rd!Ti4Lk;-VX zNeBhv9!k)pv=i0J93-i*Jv=n*=jf&cge|`~9rO34tBsoMmxv+IM7v0Pz-1#}aXW=~ zQ*N1rI~H$_ij5duPx>Jlx2 zqu=q_eWggMK3+1rstr+|I-U($imhytAP<~(dT2LQ-k;mnHFt4~eQ^wTG{ofkztvj{m$b~wXRwD#^5exS2a=T;BX85gBEJ?m%PFXRYzs1e2c%9iMGK}NKuzj1kg*c zyvgS6g4KfeQJm0?Q0oZr%zl`Jp!A`zq4lHMV(Js_aI}3u$v{~_oyDv}bEZx1L`g<{ zii(N)3{~YuGWsxHIoE z`K|F4bD7ulnP8M5+Ta!ZHuIOcbNeA!^BCyP5Z;OH?~AA>!>A|asNQQRG~QF&0ZZsR z(Wu@_C{6cKB#=LA6caE?8EtUq$L~t4M1o>&S6y`5-Ku9Db5Be-lk{K-WxLB>7U? zNypL7(#Z)HB9XuGfx&;{10xB(f1?8n0{%&C{X2d67rhhu%b$Zg+!g89!Q34# z3;%I1Br(*@-4$+*!0|>kj&FDDWFV5=_V1=kkhyV0#i&!nbUG~bDuJ-Aye9s>l)eAX z9A#tzOnmb}iVuKC(rY`z>*h(~!!=<0Y7?tb2Mp7^t=DI~+AKrqyy(95_>*0{11SI_bQ-T3V8t-pPF!GYWQG$hj zaesA@UFO$UgxlHJy5k5So%2h3+Wg>#GYATU{>}piT(icn*~v&2FC4^xq!?e%soy-{ zAHc6j|C%UZ;LnNjvk7DXLxirw`Cl~PBtLiZkK}J#!EP&TQt!}-LT}Z7A|if@js3iq zB{jF*EVjwFOcOgk)GSI24Lk3dS?(R8uu)Bz7S5QavazpR^b4o>Ly2)c&AjQTxWurD zXPv!LVsT|4i#CS6MQYAe(9NJEC_Rtf+re7Lr^LVNkdlWhu3I(oV;N7fX)}bH-h4k` z?`@qQN%*S}#7^1yT584)}lq@BHoV#3g`(0Di_7|@Yh7ZTZ zKW%)ueL1~$rZbDF-&5RbGDMSK^X+ug;bQ$L^3hbMos>~NG#HW)s+O`Guhec8+oOml z1033xrU4ExF(OnbKN#beIyiBlmYIPm zD%KuU+&8Ycxep{iuI7$9@x@}j2^MkBij5NHfSCDqM0E9Iet^cex_%q*sYj?i+8xIE zbRtX1Z6{j!2wS;2s&vt#LheH4Lfe7jirIuzlDI5duPd%QD26`jiiAJrii|(%YQD7b zq;ZpQ7qxGGLB?m?)8+2b`69-y)1u#^Y4`pjba!acU{`&SzFRV~m2xO@dtNEGqSh;Z zFmU$i5e0%iko#OaRu{^7uDV<2ji+F+AzV2}6c??~Wy*bQ+WS4vTi=0%Fbb>NG_ov4 zl9F&yPPDSHzuuNe%mBGmcc8kQ3$Wp1q%aO5;AcmyJ4 z?BDef-`;Y_2eF((*Ce&K8*?{f-_(+R(Z63XRRwK0d9aR9;M>}Evo;zlJ~|$o7Mh$R zubuLU-8Q>XFV|Pw?Nk&t5FM!XIaflM>x@SNerls_9g?FSvmsdE!BwSZ6eFtdikMbt z`c#nXFJnY{Pt^XTu%Xg;%r$ol`_n7g(q&`_x^5SPpi09hA8oDd1@*%UiY6nKr-)6u zBLeUQZ@VaocIZ~97YB&6vb}E8)44AqF#YUF)53RXEv}oJ_mELL?(g1mEU;$gvvaG8jwvft%Y!KJP};B|my7;5Cx;YoET%KCr&)Fo|m9EhDmr7@#hzdglndh5opJQn59mLMD zpPK;n`bTDB69VEOx-`s>DHNiZUFfT58U5-YDl}ZPtOV_V=Ttm?@!kc=yw=G5msBRv zyHOWuSBG@gTs}^oR@S^PDal|wk|Ei0&wX0!(%py+BQ(R=YT*hhekL$k8(CC8;xVl7 za`;}rT#06LSLUKBkj<^hcLzPaUCdW;8aVxW3Xj@YvyT@5O2Ii+~1_ zJa=-^E_4lmZ@ zec|Bmy1s8_FCnou^@k!`;<3Kgb)%-QCIY?6s9?q8q81L5rFv@atAV}5T2c}Qs!EL0B0!J{F}q+dO#ZF2cv`;yl8 zy!U(x751CzS;pVaNth=)dGFlY=#V~GUVpA>-?ypf@_2)!DGG1dv1#tnL{3Um1w=h z?3VrpEGsWG=4~O#86Vs6S$Z&-IHKH*>1=K7xo@6oHamAUvMyS8Dfm;Ztz7Bt_FL3mLGYJ5NRetB8ExDfUG)8Y4T#Yi0i2z%=Iq@&cC%l_m+ zXMbIWcu8S?3)q@_Uk(7ESnQ^o9qdD`gYkW-)C}PEm$i6{cXxyTfHS>_Gv0$Au&Nd0P1nVHlI3PtlX~ zCg=NrTkqloo`*6$@+oR}PR?tnvFVH5dMuvm#^m-*Bz`y7mYXIdeGI$9!=q+E>BWIr zZvJb&H;<2r_iqnRNCQ?mzIKITP6$CrPVw{eLm%xvrBiux#}^>}P7Jv_Z^G8Z3iyK= zWZDajoPZJ|ZuJT-g%%_e*tpWbd$Ir}Q@&H!-1sUZxX;ZE*Jd}+r_IqM3&>i?|vK+;>7FKZSNL`hq^S|1t z8JY;%e;2!;)C(4H`*&sbqYn8|nE`?SslAbEtDof>hcled*~*&pSIzcA`gU#2fiSmJ z*J99xySmvqIU-9gKA-@fAcGOd9S=JPD+VA$9tZ{*aWdTXFn4wLWzdk7mqFG?aBuhD zuC7&jKU`_J!aeQaUcb-$l1*{Qihuw>C;$osfIxx(5X2AwU`PIbTmD)(aQud@OZ;oM z_ZWNhx`xEWkfpz!y94}M^!KCe*Kl>R@~}h}>OTTQt^;I{^|`wfvi+Ba@JAaN zp)9hDX8>P!3~8k5WOd!f`PEj2`*=CITDdWR{}OjeOKYfz{6>GSI)2xK-mY+Kq*xA& zR2Tl|U=R`%MEbL4_=yRCu4~L6XBiy-!T=y4C{lWOef-7*A=mo4e_{aSaQ%sagoOWf zEl3!O?AkxC6%>Xbmo@*uKoH>d@caY&+4?62h9Z0Yr=1{F@L%@;K?VQ32LKEJ{3{MH zK=5C22nt`zCI8tMK`7u~n2-PnS%&}9P6&V$`TdCrTnilkuoD9Q+fE3%`uo!kf)sQ9 z6GM&_Qo#8q_HTb62t?@5dmzUT@aH&#p-=#FQe7Ya$vGG~e1FCZh9VvQVJ83p3jEn; z0T5W=&psnDp+ED6#GwDaR^Y$b2|)jh7dZ?5HD8d}-*f5iYK~kgx&C+}wd{P6j}}sW zsp;h8&H()D5mIurc4GKzjie;YaF0O@0+vMl^-OU~Or}X0?6aWbWg>YC|<<#YI{tw1{{saI3 diff --git a/examples/gjf/molecular_dynamics_results/guaiacol_potential_energy_fluctuations.pdf b/examples/gjf/molecular_dynamics_results/guaiacol_potential_energy_fluctuations.pdf deleted file mode 100644 index a9d9badf72899b7ea1ebbe931a4855435656e36b..0000000000000000000000000000000000000000 GIT binary patch literal 0 HcmV?d00001 literal 43267 zcma%>V|b;{*5<-;@X4?K8G0}qz!E8 zDOEYEWQ+XwHpd+*Lx3W^5v7oLZ3?STjLki8>(nn;H?f%Zg4*HC%$W$0yqE0YuF{Ly zs*z0{8flV~SsS!tonwD@J8!GGiG|~SiC0gL3d zu-AaO{eowq4h880^x2Q0-BFdXGPx@4M&NWM2q)~jwCGAI}sy~ok*p68&V1?R+tLotE zRPr3ugBCz+^bQhUb(z_NAhQNN^~96=IYnS>jP4uFEqaoP_bnIJh)+tF_CZH|9B|@j zRDYNW^93`${OVC_`We+|J=$*l^B|AN8N?y>120XbFBf8vJE=A0R`(Rgd7*`z+sdB3 z+^j8Jxr&=WTYJ=A-&;hJ9jjh}#6s{Yf$%%lsnl0)!DEV6(rELRT^23D-;DV9xF=)q z=oH7Xj{KIPiLYRIj*iKN28>*Xk!r2-;i%L(NZS~CT$8sz1{OppOnGYOL{*fdhs9qL z(+$7GDYE?1^@H@QBw66z6pcOkVw}>QYeYL-Ydl4AMn*ddi%RV;#9QfrbIPd zEhMqoIXcs*O;e{uwO>EF2w@Uk78?K*HqY9zoJ#QsEF!e_^WK};$(DLyH~bM9G_gzleKPMT%78+Ox%w8ACzW_9Ee^ zMPOP(RqZjGNbIuPR;QTF@&))<5W@ycr{NrvFu1@;MD#?Y2|~vVL*R^5x#h)}rUz1-UG9@Pi^G|Cmj5I2mDe~h;#!#He`YTuW z?ZB4N2kzkp?Zqewko(8Df<`J`>vG|mRLI8**UH+qGhxE&9jK~yuMwAF-Vj(7nQaUH z(Bw-6A3RAPCn{KarQNgSNX|&lE^}%(fBMo zuSBK}HM2O8ntEoe)uFwk>%OkPRk2oiBA}Wi(3-q4a6_Pp>nhih=>ObtRUY-;h>l9j>^ddrNWxQUi6mv7EFCKQOieMbe zv=?Q`w!#L*=>6Tz8R{Q4>F=g{_Qsdf&cXm;U`NmUeD1S_Mhe=Tcpu~O%FRdMlwMj2 zY)^TfV|~Q>jf|WJp?-)zM?aG-*@*4TFf;0obo1d8hTud^u(!G`5o$TI@?z!4OD@lm% z=|tu0EIu-zISo*k(*JmGi^?8mt{~4Cf-~JhxEtuGl)KLJcu9guCp5^!pMkc=r zIDG9ux~zK%v@pgl0*wYenz?*}-==Km^mY8oWO`-9^f`rb zVde-v$aLLC#fiY7Ro|U^J+0`ru8^btSK&Z&c|c#%&vle%Osmyt4UjPIY@~*qrmsAQ zR)g@*%jqy3XRcFmJ~>t4c(;kKVVygH>)*5=E$SD?OIk$hP@HHF>15V~_!-uk<-?6z zs?v+0xDKgv0=wwlFBh1dtyoSjD(njS#;l8-67^&rzsL=;v!Z z>aG{Mea~J6_R1|;8ri1(1>fr98D@4N^ToF9f(ZW6%a8w_uS zoO5>D?|8OsL>5G^Z-Iw(tdnO}R30LEJIsi0lY#`##L^tXHZZA#RW=x6UaQEp+szP1 zc_G{;Nl5o0kZ)347Mzv8?lh~NYxrj>U9NMvepM8^ zAgDAKZuLsVOH>x2KTl$tVr|Zl1zsWTeOw~>$Pz=);!$W zjlKt|*{16*tWB2zYErT)2ko)Bz{wNgP>#cWFasOazZBfM%7PpZI!8==yzIZFHQ@nx zdaonS%IsQ5kx^cQ$Gbv3R%Ez!nxzN`?T+k+*qW_Qi9Q$)!lY}ot`gwqa02XDq7*U! zC($?a+e*Cp_I6#GWIWoUD6HC#64?P3pm5IIS5KvALD+iCdTX8?Qx|CrQLH*~a;t$; zc~-(%o}EEzQPVhY-d88U3|THc*6IF0aRkPm>wINvJ2FMiS2wrp3LNC*Z6UIbw9t*$ zsPHmX3_0t@$9P<7#N*NPUQ8TwY>>b@y|Cs6EowVw|}4igD@4{Y>n^%vU(Nh!Y^)tW-#g&{A=FPCl`=9k)8n^s#n+(yG_bJI<1^FIYe9b!>A&LqsrPS^ zm9@7qP%v`D*Z2%3D2xwKG;(#s*TM$~*jU=wE7e3rk>b93VZgj^j( z6dXTc_wPFq2Rdjv`hQ}JIMCzM{nODuj>4Z^`^Se4pN{Sy7ez%neAa(IGT_tw>7@K8 zFaJU2e|7M0Yya-yKQr;aLIM<|@M&pi>HpLJPsIP$Uq)66pYA`s|1Ts@_b-%}{+wk1 z-yfW}{xdv)ppmngfswoj|NoovGZI}C6_!wgCpuUKZ|Ipj%E*Xm2gt0_viI>1I9kZBT7v z>7Z$0$>hRop%qB>)eo%4Q5EA zTq!BVq62mJ=QKYI+g7N$WJw+7KYU^cSp`v8qV0jiE7bL4(0_o9+$Mad z52B+-&4J1-C*0|)vb-Ax569Oko$|$73t|jCSQ1_+J@z6IiLd-=$=?T4X3U%K?$hd>I?7QR=Lat zKF~EdQ2l!P4Q`O7c5L4^EE!DL>8YgyaFzuPZ?R}kAn%INuvGDjgAk1vrJ z3WJf*USUz8gy8Sruy9EehHnoDA3ML;%*KX$snWB4pV{} zMA5syA3Wp1X#TX`lH?;)*uRI3GPEbjrNYSD2(au1`4$b~m<`S7OG67nrTZ282ZJr> zIzCXq4^afrL{J)05Hnt|T0ZVYAZR|iMPO%tb6cQUU-wBcX+LJ$FPdN~zrNbS!2S^7 zg%0YLpaov{HG}lKL_o>qD~(3Yhfm?3N5E2tbQ9o{Wkm+<7YL0;h~<5nBrQg#@Gs2~ zkmb51a>Q(f)bfAMhM2@>{PG6u6@ZuwGNbo(5vcLUQZ)xQq)5-`rl2cIIt1FUl`ZjR zRBpJY9<(j2OCYL1ot`*I-XTcPDPdJetSdqOXjNihL;{N#!hDbtq10%&e5{rT(HOg3 z&@aI`ddcXh0~kBOYT;Y@%6jwq;J<_ax|q_QCeS-H5^)=pu`TQU|l}gC|JDC$=P3M8JeRfP4!;>|vDiEtYX43_@`0 z)71Z76S>IOE{07i9fvFyM2sd+{5_@KS5eHIP>Ym{w1XgSnB7ps9$k%BTc(mY3txu> zK9)x|o}3g}MjTs+e@U86yoJ||*G-^6{%f)ItZHd;YlgZ^hoG0Z7eFMAA?YS*XSgD+ zEXE??B*}wBCVnBwB}s=Si%f^WNBq6;wHZXNo3~rRH?LYbM|i8ghbvG_C^a`hKSV!O zKUCj;o2g%pq&?O*w&|Np3GY$$G)VygCjU%<+jMiiR6YB$(K0QL2uuFUOx#ibE#6_r zEtC<7k;WeR9`+vQUfqcNmmXT(M+SL}g7CQTw(zJM#{HIworx9ZDl_em_U{Q#6xI}; z34{s83BU&B6^Vrev3_?k4E6kPaaBmk-aohrGD9B#R+ zimd!DkuD9NkzbSe%erBFY2C#+KXbbDGWGJd42Vi&%BCpt)blt7SPdHOeqM3!XpmNi zW{Aa#MGQ+REY7Yg>b6eQPrzF2o02k?F|`fmRT7t-f-?Z^WsR= zs$N5FlWv>1hr1_yA$_5P;0ksP?tpt(baW+{zT{zgO(J;bbQ^l-oQ6R&vF>!)zG1IqbfPj^ zr(4aA0v8JpX9M9Q6sf0VPqOk>r^RItY$2{K_$BsWfbt;XO6$?+H3lpxpf+GiFsV-~ z)Ih9K3`J}QM24?n)2UYH+IP1kJ~}?{J44A-$(UI{{bT(MKZ)MYYDz5zF0u|lFJm69 zKrtHH zo8cF4CSxWSCzDR+_n_BqrgICpiop3w&6O5u7p?Brt-H>XC@Xv`(WT2#;n4^qtPSg* z>$7s%a@C!>rgazl1N<%ga$6nL;~H?5{gx<}XKTiF73M2RgxXVg`lH)Fw`E9HV^22J zyi}gne%}Y2brjqeytr&SL%OW49kt%5rs%6_FHKf%YE|t0zRtaFYEwDwRMyk5(}g#S zGK{LHFRtwnuQC^zD>}|U_Qi}!-S0T|XgbSS9$Z=I+OYDO0geFehv3FV#%}i+dXTlK z;Ir!2Tiq(}ojA!oZtXJh(eV*H6TOO=5D64180?91n&X&VU@2yaXYPrJ9jMu{8?<@b zyc6(1Dm#*8$ZL57VH_Dom?_# z8H&tOo{G1*#|7h(j@#4h1>K3d5R<5&W&yxQ!c&z@FZe{s1f_7j@UcjR$VB*4_?mmo zZU5zHc+$*HVAuEe#)pKdvMg_xmktyC;l4|Ysgo2Q@%7?Pw&(eKs{_Ns-5D3Ni^8Ix z>t&rh_r7mAF9x@RF-NB|k1`2a5j-xQP_Ngnq*liJ8xH|DFaK2){Ke3}Qs5KW|4qYx zxciUo6Vb&41o-tFj12MV{$YKsfBXDb0RAH#9R52o@Q3f6KGB>GA0T07=6Xh8%1jQO9Ige61;`GqMJ+^qC% zEI-wXjgqz5-}835eaGjE~uaRr^C>SjB^t#Y4xwz&MckSr1KUSZhy}_Q}^GSp49;knnU=o ztk3w7WYz1tSvnOdVq^pu=L>8*v*2hsR^UH8O$^8Dd(MXkfbqo75~yO~iB7ozUKO_z z;ySE)L$(OwzCwfcDjC-9{Lv_DE{QMPRUU=!q}=lXzao=a*QrxX?WC9Sk7#pE;jv4- zwq!y4-xj#na=NW%Ov;i=TIeDuKulC5NLco3MqWXLYAm~2m|zgGD#%JXkZrg(o%@j$ zuH-gYIwhRP|1T-{XO8}+AOrKiv+M6d{Ch6{NrnGoVFknl|5*OKqsRa6*Xz?w!Og+Z z$V$xG*yis|ioB7D*{3pg!zbta)WAmH@c}aShDP>(l7sx;$?<7aaI&?vG_v|5gK0l= z6d$01Pydf_1PH2pYDijI=)Yp~PY&6e**eme1B7 z8b2axa`ELR@Vx@r%3P!BO}>!>OVNINERA;6W+Betshc*y%Cd6lOlNf`xnL-~zy zQDqe+DO;Y+$gOIr~HU8VzvCVRX*;ViI|F8 zZF>L4m>WosR8A3hyKw@BkigTOwqbm?H0)n)91maQk>g~yC!FE}i9u_e5hB}sHGn@} z%vi3r30sN|i3}lBWL#o6zlmBSw+2N}<1L+{zzVCcZe?<5q3htBGCV(aJ1*9^R3tWS8c;RevF8MaJjv10H`g44q*shqW-$m>Mvv(;!% z2d1p&sf-=*{b##SS0p|;EFlhJ(Y8b`!Od`PPG;77@4qStrFLN|#cn{nvMeW0L2)}B zg9}4Pi=-t{V;#pjAg@5_`KoP1BEVuNn2vT;9KRHatexU@?-%b=742;I^IwPVbK+#P zgvIq89R3KhmC8>W|7Jtt%cIF8cMCm){%54NzrS8PLk=&jJLN}N1SR5sLMik)K! zPO&8ebRLw`awv6yBpoM8+Ps`^tR!akwM|D!Rbj-^@eOkxHEF3-1qp{BVg6d5^?NHF z3E_F=pq{T3HZ+0yElY{8rlv|vS9v$Y-g4k0`kr>01V0h{pA2aSlnCmJWgb12IJK;iJgFPt449 z-j1k`8R?Apjt2)xvM0G_ZN_``w#>wVJ^L0CPqHZGxd^{OIw&oLqNx98PKtocv?TLE z?`0|Rk65T<5GMc3Fz;}>uSD3!yuX9dZ|Fd??{cZ5lB*bKL>_H3Z$il0w^LZ&e1j(S z)IdW~gvvFQ6;u^hH*2x9oa08VotG@MoWn-74{9~EoYO|NFKREGmdxSlf1G;c>tc?D7$+N;Z(AG`WqQTFzPm>~LkY7>kCg#cp3 zHcU@doVp1W^@(UosK{^2z2*YA4dz3m@^Wr&7(gZO5y9fyBe|uixyve!rFqDnRWzku zb7er|^cGOXC2Dd?W()Xa8fH!LVD*VT2ifuGttVHiN{Y&gN?Hm=6_wn(O0vpIvf7N2 zFBa$0EC%=0ii&z=C1o_FM{@~Eelpc#uI#yLa!@D5Xa-1~l#2z$`%YD*x!c#d%X$x3 z)|(aXLfn3lB_Y+tzwZjISqU9*7Ep5@b4OB<&S7B=-ozprYV+Fv0IyV6nG>@87>8L!MpaTRODsKisn4#k72+GaXrS^3v3SC(4;(e8 zC}%1tS{+SFpv8;7Kfml~sJ-l3(|jK-eLoCnr0q&)N_-I3Ebn+7UXny;?726QX@It^ zlD~cz6`Z$yuHPF~MpH^e&Tv+6(+lMRI-sE`Pna{|tfB=z2+mY-{c!`Zo};ATrHy_M zVamxBPZWqaJ4F$ZJ8Pkgd`dkyX^gS+0bnY+$8}kVQXR%*kY2Sd=G6c_`=*WD{2*O?)_rO%Xdn`N7Q{}WuNqCB4GNyZMviR34 zX7D}fEQhcvvogcZ{pO+n*$3;|?akEtM!QQPatLW}o+9Bi;smT#g7U1PDSfhptV|B{ z!v<>r#Uq|xuyeX&pF!S>0xs5?whKpj+F9d-K^|%E8cYP33s#vk7^S!c)-Tca z#6D+iQdBStRyX7*5h`%;1-Pvpsj37UZg?GHe(#g z4{nbIbwBV-L0&pZd|$uvP{sdN;Uu_z#UbM8H9TD>z#tA^?=;vadN0y|C~JSo(Brv1 zmLjZ_(#MsG#zf!DjZsNfD6kt7IX!3CcTREVus(h1L;Z+Cij|s>Dcq_@CEhXg79mF7(Z`!-JVkcEIRpKWZLR7 zL?HN(1p4BvBHo zaBJ^kG7>W!_~zmAed{?M0#p>?dYaNWL6~QChDH-IMl2&{axmVwhcl&{)W*^R+}dzI zH=4<%9EZs4X)>s0;!yCMf3`o%^-vTfIVOte+5Wp?3`ZE$_SSvn zd3tH``g~r1I|tz7^)|k-N`|eCgKb1SW{hK65AKwb$2v(qC`t^QsJ+ecgD5Gvp6GFQ zDtgmxe+a1vBKX**P2-x*nq{4=D0!HmMDAB%$-rRqT(eP>_zoXgL}%;RxrOxFp?3!u zrqkRNC=>}@AN`&zKTDIDjOgYG)@cR6TI_4eeOs?z+i-hH2_SKb)%s>7tdRT4Q`5RO z>fLgB)8y!c>=_ILD?C0~iu+=2xfJ4A_8@y+Q-*W!_1Ww#xtm*fhi&a5Tqq~#5Vwx% zI-CFnn>soX2*!k)y1tR0~v-pnwGLp{x z9M*4sOK*qmOaw3ev=*lo<;~RmS7$l~Y0 zyzczd{%GT95>2$=BzX#n{xX)1%u*e2eF!8S7oE>|$-tMo@`We)Y5Y-cmS>CiW=iLS zf=#-}41qA5s;9opm?kh^;k>wkMdz;hyO`DZ1skk`kk#!n5fyVQ7DT(LC4qs(zH0eN z@+Rw*bj)wtWWK_(5Uz@tc%dt?*y)aO7buumq)>b-p(*fiX^-JM*G8~?6_I?Crcn_Q z*r~29{_H`npa*UF-JyAW2j_z% zOktg{B1q*v(IeYdZM09QDI03@aK|vZMVJiTMW{La}}y~ zSN9XL9J&A4X-;ycN?ZPxo>K2&r+M|71bF6h+);ih_%d%Y*=3N~m@#bEAToc}ANZUM z{5@zgXC2;~qwGethU}0r$UFDNe`8gf zt~tBmVglj-=jDVbXzwDUszK}5;tZM@nK6bz=yH`m(#cVDAEkTX58-KB+r+yl_0BVp zCFH}?g}X>&D*?PbIkKfW?=dL*56)bc)3Jqqyj85-sxZ7vm=f4`E#qC|MT13QD>^xu z0VOxEMpdQzFxBNa3COMEU^(y5LbVvgJ_PW`zGx67(}`ud;7w_0G13FbA`ok>ezZU; zDN5Y2v{~!5m>NpHdF2_CHB{NvN%XV>UGye);k|hT%b(sn>Q;#kAQh%vYMPOzgi%Bd z#Ak#bNMR5st&05|lGi7q9A3)@p2$=mcIW(YLd-F&eNF7<`5#HMxKmnY z+iuIlRritZE!?|bPI}bM!F!dJCM50m*yg^iF-@jMpOL-Wstg;9$}51Cq9tL~ywcZV zi`nkMfuqH170`^@w7o*@sN0 z2e5PUDEzMNjnx(BGydUwu`_Xf@FW33b{J5@A5AL-iDnGl1Z~#?LLftq zNDha*uxLJ;(&=c)76O2e3Knlh~sr15UI`x0r@<6A!#5@*mNDo-w;}e2QaZsnQYj=l+oXTak zW3_VL>qaJ%!%h#G@pn*=IhgYo@J{D&I^f(osm%PQ-`uSt!6l0tR>c<*)Jmj-I$%F- zPq>ZGQ|eo>52s@SS*I2PVLwyrX?w|9aM8WV69VGCTKt1fM|aj1mlH02TdIQ>TzVi! zy)i$?U;Cij!(z3V#p%FlQ*f{v)SbOgFFlIAy9N_(*=aL4p(k4Q=0Fug{W9#c3C9qY=AcHz!qx{!1<|{I!vp!Ti#9hT z<{jbiC+e+zU4EtT$C)Dg;O<mu>N%l%*PN5#VGM2-%f{?tNFF zZaI;idfqU?SM-Tjxg?=eV>}^fmUgdPNMUFAbFv(DnsD1WlQx!F#Z#K?%^*tbPnp_G zhZ+Fq7g~S^ay?z7&^2!QZ`Z3>q&$O+_FFM{&EtI(C0wLu1NSqe7m3bOC4{C#(HJt2 z+dD3-p96@)gBM*ghV(aU=7i|eZeH%KWBR?-=W*+mm+Q% zFr;|z78UUpgltEezDtvh5<1Ns7(qMCm#R1qhBx)5-EuH5pY{3?Sr|mDg1JB6)TEDu zSu+A~aAR^)MnsE`PT%_EZQa*&TW~531nE7AkEGVVMyzEZeKqdr9?ia(!YHS%YuG|1 z(Vvs`7?n`q4Qo3ppaNHZb?svo9}Owsef~$;S3)C4ofkhausNG}@BRt7bUasq#d# zCAXVGHHRRUsE_pduIrpRiItwo zR+%TOf`z9PPsuS1a0YX<04h6L z)C!9NoY3HH`LpmOZIKg5fQX-AmEc)B?S|H-kO|8j)k%X4cY`po^MpX$*LkfO0Ra~B zHTVp45&3~g9F8FDn++|?+Oz@i`zMLP(_q2*fyd#ZMt3xxBRBoCq#Nlb7apArC&z=N ztVlHKj*64+Ft(*{;*Xv0LqigvwfTeYz?MVxa)eECd+w*DwA$yU)Xh>pgo~wd>@ae{ zxdj;%_OxcE)(n>SbjxSPj!22D=+rq4V=RoUG;`C0DY@UU<@M{c)@u`9z5v}xYdg%tz43}ZagmR|< zJr%Usgj#r{f%atw-(9nIzb@l zFEGM)1iDkGqcbvN8vZ>JjhetKxM`=zweWS&6EVu=07B9i!{(HG!SXmR%r#xZ#JR!pM?!;3a(tOMtq%WO;NV*j0V{5+cU;tTg=_qwQc_>pcs(2 zixez$oLE9S%Tu?B-tmNSKq0NAexp>?kc@ws|UtNY84szztO`+}j1)*ET?+S){hG9hK!>^d_x(wqSqgb^d7Ien%X zVM)Suj=!Bv%lYI)qaA5~DZ*)&|May=XLJk-ydI}(8JryRPue?9{tZQ%@qG{7b&Bnz zziJRj+mG4u0Sd2<;McRKxr)fFV0}%S6MW5kEPuPDR~mNAa;E*f4snl`h+)k0EiU_- z=q$4^4rmrSDQ0TIn1O2@gp46g;$4y;SB;(|?!HlTSNWWQ03A|6M&LW=zIc6&z5sWX&6L4*k7fxD;}OV(GwhKgaH1!3 zq}21!1kcA+_SY^*9K7c5`0dYYN$hPClE2mMw=e6~(BoF1M21>NpxX8I1Q3<|EJYxQ zbfK;0;jY<3=wBBgwKX7wsTTLL8pno)6C!#>M_YGTV9(fo+ZXS-;-}mf zXC^)Qo#;IDx~ADv;H2GzJ?o#;85UW0A6saBMpr0`bZ%;o9p%XC?%p~9JFc;_$k^;4 z%LA|<3-~4F?;o?wHz;eknO*QpkL-5SgP~)8$#2=C4V0@ZnpBl#Y%2Er{C?8O0<}r{c+&$AU{FXR%5o(^_SVI3Lk>8Or^v$)z2I8i7>a>?-VdWgH; zWS`b2FG8+udpXId)M~>l$jy%0q?2J?^cO9FpjK_KKTegFH~frgRTv;FWru-$gjvpsSZ$jqC$B|$KTHI|=VjJakLB~o7=N@=7` zjKPd-<&pw!h0Z7QHTD(FEdiT=Z1`e0Yk1K0%^0%HuhS8vBPM8SiSZ{*c1u01$6kaZ zlJoGxbkPy8do*sr#pJ`0&e6xT#PNF(fF(1nFQplhCRL(m+!ghK;WQMmr)+D{?4$|N zl(8~)c96N_-H)@qzUe)9XXmp=V=vGi)pKz9Fu=_24x-8?n8b$Qqdx$|1m1uQU3)YM@b%xn4!J znyacS2*;N5*4M3v9#07oZ;WQC*kc)(X~I+WX1KGQrAt+A z!Z#LDRr@Zf4@^E&p7~FLH!1tM`?32LG5T$a$X@*?{Xlf0u&6f3CLt`L4EB+=2zhZB zR(+Y!TC}FSPY5M*j^u(`;kobOu0}%%g;4fWG6JpEt`pZ~uUYxl&X(tOkwHvVk+}g7E*q|Ed0MCrISnasvBy z8@u76wc9-j>6BVZ%elF(tc8Lr{b)LUJ#5gBhK60pVfa&N_h;m*~iAn&Sl*ut&t$(E1 zm>nYIld1C$G-j)Tukbh@q$}Aw1W8~=8gw8Zc=X|87kY}~xdI<^@wC1ki?5*Ku%^_% z(ZBQ>)!K<~4mfSlpu?HCMBunZXm~AhjlfeHj8@-peD^JfHgJ^tHib*H(j<9pW-$d{ z^jc`uIxo?^o<@PlOK%IkZy5}eOWQ^p$CnQmaieS%paUPvd*MW;#VuXd$=47TYJ<== zY!(G&zSc|L(#i1>=c!QD4KSK`9r*d_b^l{LGWBOUQN>YP}XWKa7{V| zA{lHf%|)*mDPGirlwPt`p?4XC8K%$nJes-@2%*3creuuo`EG!iZD3<;VIjG(K&gufg}F6*T@fl9IV-FHIf;g){uH{^Hzf0cR--I&mf2@S3a3PX71(L$dj{ zmnV|rnP(~wECXJ#Er;%{HVfke8Fy2Y)zFPoDNol}tl5e_j5H5iZkiW;^d5fZSwI72 zEa*tRt;g2DuIJ1=kuRA$jrQxc7eOUE6@w`LfMADye&-RuY9fGLL2~zif@I-B?Uf~G zaAz(fqwUS+#K%>0Sj630E9|A6S_+T5{M3zb>8*96|9Hlzt|mpU)=FU2@Ad9QBb=jj zKA^w`zV6f|O>@H>vh2j`t!RZ~%FYzwrQjzpJDv= zzDN-`3VXPVwms+m;`ICCIU}CHi{Frcc_Jyr$yc^BbtIYQpbieh!4+KFW58568oaX3#9nwh@hQ$9eufHD_?e9 z3ZKBEp=ibLjs$ObSwM`N&&59$eLU7xL6r+;E=+8a7?zIcqs$!iu4aL$z79iRLTNr zXp30h;hkXq1&GlvpfTYkZO$iH5ounYYpP*)QxI*#W7j3}fvXG4&&J!&Z(_m*&w6O2 zweh0A7j!gP%I3-s1A#a*=U|{QJ9&>KxW9|>Z$Mqe85z`Ndu^241kopFHiDNnAYtQ3 zsdBU|E$P2$)J@>Di4fY0dG$#t0aqc}@94f&;Y7A{SU_ugF;(B4uI|Jjj_TN3hI2NQ zXYKN&A*?Se8$HkURWxBI{oGisc`YtqLo{7r(Zxf8hX~nSgV-Zn6+aVvFFwEQpn3=YDp4H*l)~&Adf^lx-66eO@Q7=5!G{k=NmN{HkPiw8^7aohMvQ^D&|P8rgx|lKF!s0O zAmk=RfA%v3A;$(q5x&N&X2;bBQ1vdGgRh5l1vADldpheqwvRGhtp+iNTCpOOoN}Y*Lz{fVtIgT?*?^y%qQK#?zF{ z3!PnDX42#ka8zZ=!X>$pZ8NpeRv*t@pffo-+l_eGOZyg%=kaL&rToyZIdoO=kYjAu zT5iE9WzvaaE7750bxjj#VZ>_pdso<7C_(IPRf*q0&gg>^5|B7^$G|%VMr%76 zRAg87D(X0yAh*=HT3Yqg+pBUWRtc(UtI`!0p~?i#wWr{<8BoHmTFkbqL8p@^85rsG zKJ#n|TB|2u!IiO<6J`Xrn$O6WYpb>#4?h~7NTOLO4qDV$+f{yK+kjOr($(%8x=;bg zzS#0nLQxWL=3VzH2U2nEU;#c@4f4`sKrPgiZXn%ig$bZk2NAzk1(m4;5K?jZci&4Cm`7(PaGH>?h=()#q~-)WFx#h;(L+yNOq z-|x%t)F7E>Jr)@xNqatZkA$YZ-yRjYu#H==D6yv+5;CTu@bhcJ*S8HU=l4d?gT_rN zPPb~y;jNy8p6|+i)5FS4eU#whcsLxRl1E$MG+wi6ldH4|Q9sX|H6pN%et9Uc91suP zr-nC^v0O(ofi?FrFh1{8t7**}5cxi0rEBVk*cYMryLAvWY1Wa1uWQ~Pbi{15kQ(=35p`M^%?KZ*pv}tMCIL=On|XCG+~f<* zUB@-MWN)$4S&O)uu8vmAyF@sviNwt8u+*4}@n3evB?7>_&rEF6u6K8xPaAQ~H*v1L z;Mda++HPE;!VHrZG;T~vU*WhbuPF;i@fet5sc~xbG=7t@i)jp<_w8>I8>C(3q_lX1 zb9-xzA<3OfY5aU3x$vQal87!LXSuVh$h0(lxlVKl*9o+RU#r4lFFD|$^xAG+Y_#&; z4?=Lr%W5gMMmrF=_8EWF;<xNLycm_k+6`9U^Vuv5mZ ze)rBGGU21{#l6iHl4l3HoAG@Ge!Oa=YN`4nZ!*{zt)54kkPzzjMD6XFdzrHCe3bz2pJKwuw%l> zDO%~mP=BO-TD`NRN4aJ*G8pwk?bfk-qSKhGkv_qp#c4rY87!s6iPeHbXpskZttQH~ z3`crwJm4z$%a|a2iX_2I&Kgcol&}zQ=Fb356!@YsdDr*w?e> z@=?L@53$sf*WTzJ^D?|ihi=#33`=`U1@Ca#{AGwU$k2v?>|}90Y`Gn=^GorEln5NZ z5SOvtDxc~P&KR~LOe?{?VKhtgOw0Ta=H4=_a%BzBZJ=>z+}&;A?(W{WySqCy?$Efq zySsGb?(XjH4wv3%?{m)FnYlAR@3UABNu{b*iZ6t(67s%>prj@IC&@=~vOheTQ__OG zZq!y~*%;AANbI4T9cj|qGN?A8S|loi+MqeMtQPrwet3MfpI2DDSrok3kFq6e-f-~g z<#|>+4DuP*>X&IH;{~goXXAmNo|k^b7SpivWXS3_x#aEBenedFSGi$cM9>-A=&SPG zog1y{Ie!!p(^XGOJG$4746+2r!@i2Q51Rv6(1%d&D z2y0nb2a5(S4oWuRoW12S=Zg%0-GxF$I!ZSSzEDNyT+C#i@mDq|wNr$(A4DWHQeR@5 z^UNryLrl&m6d3+)MM_)ZJq~XoKKU%-9YGqE@Fp7~vp~#`p>9irhyto)kZx98*I^rz z@slx_!v6b7J_5%f7qrVY_?qJ-yC+-AK*HXB_ZLL89gV)!y)P|LG|FI983l%|cQ76c zKvo`u(p>dl;l~+aZF-SifezWKAV5$biTgu{nZMQEd~D)O@@0{?7j=QedG_{23^>0qFwa8bo9ev$Mv(dF#cdW^ChDL6MeY^X(yCF(_`16S@D_ z$fYGHI~4S{Gho%rFnp>CQ?$J5N!X$%p8F8uH#ou*K<~ggVrEU0BJ3HK_${u6VYeJ- z>hW9+siPrY3G)&!{Ep28F9BR;WGljPfZ)WQCbFTL0urq;>A`W*V;O|Tx9d}Su2T) zUVY?isP>wRY;Ffs7k|T_MQzCgNqH$)t=?y z7NElbfQ6T|Y0W;7Lv7dw?5er|%~7f9#?#eFiB!X<-@1JUUbMo8EC-~J2el-<&mJR> z0VS%BWy*B~|Z8S^@Xd3*aC)t~R~1L?F=G z!A*jri(zSeqa$aiA|Rp6WvXAq6pM0{?|Ov0h91(90KuWTL<3Ty#qA=5zJk8~?FJb= z9^}`f@a_d^+g0cydcG!YQUAD6p@|4w8oD280!+)9)2~}MG$|cdARe} zl6q##=?qtnG~Q*;f8NU7+?CCmS&F(^ZcG$XpgfqF3@d7cs_K!Hd8C2uq$kwyBwTA( z&nwK<8kF*czm+Resi7N*w6|~|?3|d^!|30>H3jhG`-0piuVvXLGGGMK17Nm%f9qS5 z{lo{0Km)G+JUM+wY8K^o#w9f%$EUlyf1^yh!iJe(7L- zhkN=0J)=4?={(_t5PV&6mMabu|BW8ts4F1!F`$8nhK&YBte=R18rA|Q#lXcC9Axq} z2z0?m3e8Re#`C0k$PlqVoBB93!&!nfzEaFxzwz<8>5(^W**j$pB= zXSbJda*8?`t9i@$3WzNEh@`J9lU0@>uUbY|k8%_4A>0=X#HbFsx;h!KBNl$RLCgR! zcZdRlRu~pS36F}m?)wIC?CTvqf(q%g{=O18IJZpdk%_ns1yd(DFrq%Ci(Uq8^{{V+ zzQW-aXF83e@B@^`QUE5cK8!o|*KRXgFIvbB=0)^H$g^ls-kX&~;Ryjzw;H?SrA zyl%lzpnvfNcc{tNm@4A?i#iDS8L&e_Y@Q`UD*^xw+`Hv6w}~)>j;P4c_11)EK>5NR zkgBenju{9=gF?Cpv!ly>;|APe!lK3!gf-vX65wATP>ZByh-8ko$ru2mFyTk~hosJ z{o$Om5Kf6|isn@#;U5NSfkug{uN2KQ&2uu&FUtEIg2T+9F&lWFUi$@F@Zu-#m>r$$?KuzI3m=pKibuDKq=OY6>x5_@0bn>!QymG1QgnFr z8`v>Ck(7KNqBGftzMv;Ksp;wSs0Tqsf!4}4_#GHX>7S-S^im=>SsmUqkua4A^B%U{ z+dXaac?A2x6(cQUWGvJTXwcf>8aF z?UmYeRaFmevv!L-cK+U}o$p!r2yrh=>4QB=_rM2gv|XaK~4$L`3SHgLjvzjJ;0I@75! z0jO~t+T^{4biz`Gs%(4E{yC!bE*{6bDdX&O<0Yze$d|d}C;%9+v;t+ci-GEDFHTgR zisMDIxu#T)_xnBFH%M@Ie-3SQgDDyqf%+glJEQi=8*b;)TbXK{zVy_9scyJAKps(@ zvv0nu=>pwFF>B$r9>CDZu)P|aNg`Qc?5lrySl?aL`;_WWMO{5t=_3cd9B3=-uI}7% zqQi>cgrzCi#`a|U2>vB2m5vrp_CKJZ?-SUhI35kdKmTmDJ2Rmo6rzIosG=>O@*6Gb zpM@P;96Lm1SjyZz%u}unjKh3h2Vmif79sF*vr$#Ty8C|;=89{sApuhTDh3PG8$~}qC+d0zG$YO~ z8Y0{_2n$C?&A`-fSpE=wAf4DfIi5VJo%T&XQel4D&ssaD9V{DZh}e`+yU(USM@Y3b!r1s%zHS)2v=o_PrTrUWPS#eFhT_RvID3z9rm4?W~VP8cfkd zKok0DLktjaw5Gy_y*X_4k5iH2FwmnOP6Dx#aUytqJ;Qb!u+HSJTnRn6?&qY8PPLaW z8U|Om^$CwmaKua zGJfl4^ys%~u>OE?-R^tfpt-&A&EG(7mJjcS>1ieMnXz^ z0jYfh?D0(G3yOnoSVyWvxOAMCl^}+m_>;C3$Juw1XP+@55Le;)=U_CXu7&g4PoZ0j z_Rq&%?fI?@wrGRuoL*MX*f--cVLYoY!X#GNg z&Mmg9k9yZ-uhlsoXfLUjwPa7NZli;O9yQ9d6VA2BX(=tYz@gk3bwEa)BzojjT|B#$ zXuHJA*x0Z^3vpvcg)i6w_sX3zj%?kbTMk~MDh+1s0ajl@7riWoP$h>6mRDtaXqavO z7!AB|DQNWz9BlOdRj1`j)tSZ%s_z=97qBV8LF9To;5*}c!er$Zd z1A)r*svKOrAXX3V7NH$YkivUh8Gx4Z)?Vi6l^c6l@>15co15^7SpCSxs-wE+{k;vo z_tZmJH-1l)V+=}pdc6~IDp8r_QsO0~d#1m@y4)8{wfhk>t5RL9+134?720Q;aAb7g z>f2u^hrJMy(KGc9nKqCYfmJP+3W8IvXllP919cfx4hu4XIan*@|AKJs@M^YZa|!NZ zvlSleLtv6)cKhp55JA=*hbcm8l1d_nw}8YE+%?>vo(^ILw1?;>>P){125L)*2 zu_iv+13hoN59|$CufvZZnp@CA0iA6e;B~Iose!x6OcntL4w&a@=)jdLltD~>g!2K; zstL#{$bmqY0JwlU*8?XA9cS!t7ww`?vV%SoG&5?Xl0uPM(NgJBg`3Pwo|}e)$W04* zi1)S-Jl$SncbWR}u`WcK9LUKnaHeF$xih z?ilgToD{~>8}7R{VeMQV*OAeB-@eLcdM$aFQqnt+tlCpgBJ~owYf>QIC^``vBB3_ls1}- z+-g{zNya6|uvC}>I$XjYq-ta@`~^k5W~&&@FY$ZgtPtPW1UqtkgPHB zP?ppI=5miiz%>w}05OuuvN}+4s#s84VyKs%qEsQIY_%v^50L#3QlIfIjzYd=zcu_kV7bh6sf1*KB%jPf~<=_KV{&HK%`=YimFNCBYui)QQujxWs ze)(`w{assKk$OI+dY=rAt9jSqCa>a!q2odl(v6VlEvaNIt%bWLG(Y#SW_v+LDi!bP zd_eO2?afJ{ATTLP$GWGvvG}7^?X7_n`5>;HvWagacG(ih>?G&`!4hib z$SY>;L4zhpJool&Fv~|?Hz5Mv+kz+^laQBe$7&tPgOSKlxHwNmmUmy`8h*)Y$Jsy9 zh@Ba#!NFXbzoF*;2ta#zP=?!vT?@G~1XhJ5jk}y*b+oJq)aS|+^ah^8Dk@}sFGamp z#&zuQ5dln=k$1f~B)ED+9l5jaoV7&$?7$6Ze8`);_XhJBdcm^)iA^wYrFF3(`0d2M z|AGCQ)w5(5u?6N#F=}isnW!@F{n1>UE+gRK$U1lH(RqlPDYk#xX%mzw(s+u?9h^G5 zuXO(bN?mk;&s-yXZH%RLOUKqS2X6Ar5qy1W1%&-le7T^rzy)3hkr!y~;^DF)9*zKw zqv03r6u+lD_C{hqE6Ho~$z{@DmnOt|Ep+fVSK`mBvO6yn7@9OL;Eul~Tc8G`%9=g! zd21ie8tvfh+7v0S#oO&%e$?$mwz0Ns*k5c?ZTal;?DFjM?D6y@DRpkr*y-5m?1XP2 zwSV$NiQb2hSLZ#cc^+i8G^bS7dot@B5U+8goLcP@^F zWop?PU^65ecDgG29@I335gehD{wNVLT;}eS1LWh(Mz5zMn#2~lx$C<(+NnD(Q#f}f z6q>+nUrn2T0*bE^T2AYLlzPHQzkznjKEJ<5}q z)wKWCBE43d$|Yu&W`g7CM^8*DQN+Tovl(#fqxknEI9 zcQQ}~jz{wVr2nhmKh}bKlqMSF(UQ`Bm#hybTY{3opPAm2>n0hUi5|jnpW){n%nO?w zW<00AwC(suLQ-wey^go6xh{`N3Q>1jzUtjm82mTZRqtyuU$)N-E)ML~ss;3%(^fq| zAU60CJKbtkbHKz@ziD$d@J4yTi|y2mjnQ_zFC~gGFfF|4X+M@D-^6W~E^UMFoIexe zR7maMiT9`Ip}!$o-4*zW)9cKxS#O)x4RFbij01@zqEq~bo2)qZN3!sTyj20uVAk0f zav8$DOAk?U$8>)0tlzwHkI*SWE!SF!sAfV?Uwa*ER};`iSVdja*0bNBON`0dl4=JP z22H+QpBNVH4=|03_ zF)Iw(FRBgh80TOfjP#w<5MJPS! zQbrzYp3cv<(Yy5JJ!)Hc1xM@x{F$@{$;<(LV7mj z@D1z=AkFWU&(PlcaunH4>(=MQ^4r*mG&jPq9vouY5S6p5t!f{10BvwbdGfn2TTVz@ zmy?VixA+Sh=8%t!&Q}^Y8I2BF=O+|so$ShuePgj+`3s3)`y>2uR{4de(^;@-wQ8g} z#uP`8EY2U?7M#ADd$?l3cZ7=O ze!0d3@~{MxH_%?0P?YU8SmNxlb*eUjQ?cB?fKk|3BEf!<6nhNRb$B>`t-Tgl^vFQw z*uj7wj3`sAY$rFEIzC<&PLZ^zt2IfWp%~Q0R+39eO2|xBvC>M+j6qPASF5p9mpVF~ zetO#4Gn&6t8i`d-iZ1|2M~#I~NJu4XAZE4O@=M$4%YR<2va&NXo!S=Ac-@XjZz;f7 zQfpYc3T(k>Q7f1qeVmi5%d4yFo|axJ3`7_zlQ8Z_Nla8)idCkOh#b>WMb%2MR!>g0 z3ag|Xh0&5nV6hMu(bqF~Hqw@GmN8Z3_k0a2KSh}`OE_XhqbaMDprIRM6<)(u(9kWV z31J|(DK74gEf_+ecbGQVRz@}CEh|N!Zor9*#%aa_A6BJB}Pbw0nj!rpP3l9U;i8CBQDL8)^!PAMU!W+LF>VBuUzRc`h)`~Hau7uoNQjYvLhp3SXRV_&j^ zR*-k*ucTmdyu#Lykx_QkpPvp4AKu@skeZNGN5Dcs0nY+x2s@r`*Ef^c)y&mE*GVW; z=ov{S5*x2+w$CaXNdrcQLMKvnaMd-^&=MPJIRNaej5L(IB>G0`n)=$_M)vNi*4wM~ z#es!sf)@5Bdqy;=Y23W-YGwjj(#rd*hq+5RB}WNY2<#(Pl64GLkn_FMx39zP1t@mR zGuOk3K{S+_a%yd*hStN!z3I)bYLe5}Xyc=r$~9~YifIW=_4TGf?HB zbyjX$1r!*14LMJCM@t2eHwN}2k~fsGb-9c^;nO$6x#f^kOC!qEQKgX+L(-v4LHkNHLk$(f!|AZ_`?;XwqY|o0T38v( zR76x|^@L3{E=##2pyD}OdnG9;PJQ#IyUE?BEe)V{OD%hnXry~2y$dLb6R8@wI;u%A zN=XSBTulI05B|m6V^BQ`492=x4ZTT>+5f$UUJ?at0v5bT?44hQs z;jr-rnhBW^3fW;6l8L7NLh48gO=T1n4a8r%cTyUQ+bJl_OGnVC2fKR!nPTdaK^h5K z2{DKUW9o=Oaha?P9>&&IrUJ)KW?C2F>Dc_R!zboIGfBabFcsQJjRa$c0>gxH3YNL@ zL6|ZMs=>@erOtL+U=(-V$iWWWSoeH(U`GUg7bR=mLMWLajz{Kk< z?`^c?*O%f(m6$D?{XPTTJu^~!V{W{kFi=h|)r+@BItok0v~*mHxSwhdourDCCuv`i z(1?<2-j~p5uE*+F0 zZ*5^?=O(Stch=Kh>~3u@0G-c2&QGC#s>>Z=yy>p%Rw*J&N*$Iuno3~bs-uFUvV7Xx zn;J3;trM7G95JEIR8vrEX0o}T4pVDsDZ93Zs=Kj#l0>RyKqDK~G^QLLrw=5JH=zlM zrVXtoHBuy7pjNYWFqhFD%k?W@tx}Ig&uVg%nf0qpfD|`_X4sxF2_l`ZkWy9s$xdZ% zCoZC>wqNR~fU7=K4!RV2MK!%sxVPJvgQGYaB@?c}R)-AO@0%DKDJ_=nU#!nxR7Q?V zVW*~Itzu!SbTkujY^Kngk2NZrk({1J)R(Xit3$1n&}ntmQ@-x5J$-C98xgc(MKjtT z8-|vQD$Z0;Pfv?W(nwE8h;4M-8nZKFhejNhKr12}9i~$KPFLYLSJBi-xApFu2ghX- z^KSb%e}i?-sbjyj=|)5m6LHfYFY9o^s}^J5;5Ws+?av(fFrerI5Z zWtE5b#OIvD>FwyW@&>Mr_wwFmowCJbu8Ns)eI2jkA#x`%H!cJ3ZTjpcs5u17M5@Da zEu6FJ<01)94P}<4y5%hMI-OOS*W(g*=Hj+7ew|ahg;sATB2(vm!KSej-D$!H>%-(B z{f3bzLl1e}OYPyq$>qFDUdaWU*JXkSktKR;pC9+M-x4wQC!anGyZ|Aw9I!!k%}+wq zpCM4w0$oCV&*+3wFtol*>S%`0`gy%9s*1-Tes>7)$g|7UD;F1S zROTj!I#GX?&@8c~8UK1S;>2<#}8n@mu=Nrb>c*|NFNyk(g^Nu{jkH+qEh=y0P zo^-pzELyYZNIDxHE*2INEwPkbyV}U^FNf$ojPJp!DjU|!xNEo9kig41KmWmy+rj+t z=xk_$<=owB9j5N#oLW%5l9$_g?DkZY_v|&_T+$#s&-B$)<7vGw81A*xe!Ma60QV}g zD((Im`i}Kzx;E_0qG;~oI4#Z1;-xVu>z%G8ckglvr7r0~y20gLuVLfrcWmp>S)-CS zSN|SXhN>M}8Q~2q9;w)|E>{VR$d~W7WQb`OJ;=W~OR@T6t+PWVr+Uk9SvFK#@T;fKHS^{BRMY0GJoy8X;3fQ%Owp$rmrJq^K+q zotZ-5BITW>@);tC)*JfQS@d85nTMr*g``piUoVMl7)$h^B(O+_!Ab&L*%Rsbw25Da zK7MA!WyNI0x(4FB>fr08qg@Z|ite&s1D*)ng1DsbWAN}#)H`IKxM4EZ$^prP@jr#; zljo72aITS;Br}O+f7-;^#M=BE7+M%w7*rWD*ySBmp-Vpyu&mOBjqJb7=)GYbG?pq3 zTg53fjgs>YJth1ISdzuXe~9C`R=b|q%^K`5B!dx~CDh8u z>Ck1}MvDxpspNjlNdw&wU$yWX!G+-uLm;)A!takRnWD?ogc+MLFPT>2XKGNc7l-aN z;d|kHUKvAormw(3A3Y850C(b?Q*e#U3FLs4kdh4)ghz|y4n1lr1-p*pD$MZo^Gw&{ z3DQ%l@D_9fzgxk0VKHCs-fHL?3{tj&k)1BS>K0`d2(jdjwBn&AL!t4Q`D%j;PtXY|_gdPr!V@*6!S7XgF9w zK+>jR)ejj>CUO!0Cc6g7$3yIcF1fnr8q%@>SMHQ+JCcq|O!yFI$_c03$M$r{xG`6h zCCu5C*pw+cqgwCsuSlBk$vv^Na2fyD#z6G1crY2wrgGDyn2{>l5{pf-4nrD)X@hFJ zu)9+BVC*=8r}mYy2bqJIRg>{Q3u6{y6o&BPoOY4tXAOrJVjFhhhAalf4Pn{oA5p(^ z_-?5v+<;{6?2t#3lnqMk8^i2P?J609s>wtVj?A*SUijh*^Tjo;KQz93=8Q!w09{u8c9O10;Bi31->* zD-9EEkKa&TsTe1}7Wq563xgLdaok`p9S(WbR{+kS2nS+u_yDmd?EN-I9^)w~hqT&G zE18+2E+bK(y>p)&lC(&Sv;7wgagm=a%-HW0$pTX$g56upP#c74lcLZhhW4Hm5A}?2X!POWz~bGGV(^+5ZCB!flN1w<>+@2l z@!`JvuR1FxLDy=uAjq^zh_b2Z*5y4J|1JVg!x`g1;;E}vo4l>d8R|3cid4ki6|k&z z&V{gt9H<YXl!EQXaQ9Sc33(B&r&+}5;l^V<^pNZsukrI9ELwE{M(msm1J{(+=kxkXO zkU6(yF>aeN$SWt0jaRjh&~MBuYARa5I{@_X5*~7I99&#+j_XzplG7Wxmxn^i*jz!J zu^=KT7K*~s%CGA)G8L?&6U{KH+FV;{wYY8U!=8Y%tfI0x-wSQR=522DiCC`f;vMBY zA7df)qmO+sY-g=F0c@>{%+8B>X^tS%S#!1BS8V(93)i@Y{Ft!1h`Q=jKkuTDe8frE z)DB}N#+y?Q4vmF4FH%41-R?LCmu=RpMo35X3nX!RC*#;ShYSxz4oZeiFrxLgLF2q< ze%|jIWxxE+^V;D((8XwHl>3`kGc4k3+ME$FG5uYrYVIBewhBY;Y#bx{Q@v3XOMBn8 zbHWx%6LtiPdT>O#oK?&9dEversuix>PV0G*{8QsRNMF_G93f?)dYrj`_CkzTo43-S z|4fpw(PrJSclYUnQB5?l+%m+uMGBU2>^oW5ne_7NgH0P6E2P&(i}W!uFe7Ua1l!7P z13SSI3_AxvgP@>WDTOFUTo?}_R{GFqS6Tkk&(NZTx&-5Lb35fq8vF$w1FY$Np~;>mTUpKeW#OC5cth-pS}+8~#Jhm5>%w zlvDmUHTMq<^gkq1D29Krg#Qbs%kXcpoxOvjpsAicKI12MR7&r^R{o-k{sj(Zru+1T z{1;F3AG66HZOA`7(Z5Y4|0jUxCwJGn2OnPO!m|%IPVnnJ27yuu;nO5bX&l_|>c*eu zd={RU8)zYM65OZ0DQMYE&qEM{J@d+!aYN#Z8c^ZWgloS)cV&oFKkk6IsyaLyeOz!lTwI9zY~S zW&VDIT<>|MG*m9sBE2R^tq#Q&U8U3qKjQD?4P?z^i}=3?@jrxR1_s7|0{mAn{^tPy zCtUx6x&8}0`~QyX|F6Nb|L9}>J<@-;*8hE={4Iw0H+Ytfq|KL~bNb+(-p2O(R z;;gHK{3*)^uWz^jj}Qw1feJ#-AB)Ztf$;O35)@GkB5_dkG5))s8Rb`ba_R!60zT@7 zS%0eU5wpPT^`Ow?C{$K`-^~%MC>s2jLwE~h>AV}*T-H{5_XBg&I`+bEC8%5$QZ9FkOo-txWL_f-;; z#>1XXx9%hpkaIgRhAlRRONB>ry%A4{ywBTHYFwvpZr_v&M)coy0B^qy3Y7M0uE*xH zepPd!vJxo&s?B}Ld>QA(9ac#BJ=(rq8!va>Y1;kWpEGf zfs4U-k#RIc#7kdtMcKTwn~G`i>fN7nQqfk$+KYE@lXs%xhNX*BwdD@tkUZV`Qdf6X zwnD^W4p)R=r?&rPTZ)0hC`FJIC5|4o>&a?uHZr1_oTMA8K8m9Wvx*V`}Hz~ky21I`ju?FFW4)md(O8k>VOM)@O>6qmg znx$a-`}PN%xLRbPL$>Z-I@XP76FYOiAeH70l2&>C*&qucV2ZRcY@rYJit$RJM(s7) zRr*z^ol+Zt7xjbMoA_O_9q_KuPW9W?5g-0Y5&o1suL>OOM3OwRqnOmvGfu8>Wg+4$mj{*tOaM^d&PDx0xeN!jL7Xz zm7c+o#R-xNitSjp+4Ak}gJ%ELV6x39>z(f_nst4Zy@6l;b3#`o$f1?FCN>dZBbWRtHRca*Em-z=6Z3t8;Go>6R=@C z{<3QCW(jIlhYH&qV`d%0lMQnkGl#U`0b8m+ zeWs-;X?iL-QT8qAx3DRs)5swGB9uYF>*^UD>mj->KO+Qi5__wq6Y>ztppuytk`B`# z;K7IYz4SqDyVew+(T?8oH0Y3%=uAAKFFl0i^>M9@kuN=jxP%k+A#B^yqZuThY1IaY z3ic6f<814~7^U#nf`>JQv+J{jp^wFK^PSSJ2YG8I;HqR~&|0*O4lk$Z>k!Y3^I^I{ ztF(t_-+sZ(T@&52NsOg=A*Hu+bi}!xC%^r^!CI;)TNCUm7(szub^iLrgdzHTx;2L? ziwkaT)?h(()V$I%X@fh>0Lq8Q*fgt>m?Bi)Z&COZ;EcG_$F@3j?cFZp{{1#G*JQ=< zF{-hi8f%Z&--XxT92T+0_rN(5Av4&mzbhHi=|tLT9?gCe`e^TCS)7Arhgjs&s&O8p zuR;W=2`_0>+mhkrr@=e}hu_702ivd%x;@);+bXFwvg}Qn1Exa8PPx2q*Wn&hPI6m8 zhbJqiOlw{8v++y-u}S<*`%(~?Ny5^&Nju#0Q>rZr!Kp*pBa7#FN|30R)3@!?nz)AV zQp}9a3lz@jG8(pHtT2J=itWP~Yk`yxxs22_cw@%&lvgz44h1j{!_~M(Z9TcyGuHO;J3ROOl~hR`+&^{cumHvG-TNQ?=U+=d~lVx}PTM(IB^C$HWbePFo5+5*q_iY|y z@ahfg@&+T;c3lSte&P=Ygoh^wQa8LqjfCrK;}|9szfc#_)orragYVX9qC{0@Hs?5u zNIzM|$%hpN`JAGpgC~mPVtAT&r1sHCJNdTO&P~x{7VE-fT@<$y-6R*aW-K6YDeoPH zOa2Psqz*+N*7eB*@BX9bznAZ9qet|m2e`1? z9#yog=4ANqplt28v;8`7!0|ujljt47=A`;F1GNQUj}D!0f_>ixMu-mu_V6Tn zCCNdHbmLexT|UN)$$Af4dy~rQxAkA|z%13ZRo{l~Y0e%c} zXJ9f14h51>P?wxs2@}5%49?Iep2NPoD@PZLCS$=m(zCT?Srl#+tfbn`Gm45E+3>q8 z-*-WcoWR2qe|udW(VY&tWJorAcQ1IxuZxd=*H)a|o{g6p{ac-)zDMEc;`w48I~n~! zFHi)TsKyrhZhpXo2a!j8KJAkm z8~6GzN5eC?-kqED=kK{gBnq{p)K!#etY{ygf-o#g|BDRmABhA5J;T3!9RHO4$y@%f zQ*e1PDMd8_DlsEVXCp^51HFHxasNr{pcwvkQ~bw`A+2Zd-Ns7K`adNiX8+E|KcW8r z&d2HhApZZ8kh8Ku{h1~F=f(J$z5jXttK`oT1M8nbFf+6KZ{L6Fes2G}CuX)kbA*4r zSUzn7pIX6Bk-(oNmQQm6>t}C&)<0X&{oU^G8gzfv`Kuk&Up4=3^-o{_{r%70{Et2S ztAydNp6Nc#1q}FXpZor2ul{WL*VaFy`SYoNM)X(dUwiQ1{r-P0e~#}@tN&pF^N#@I ze~j;cLiOJn`2QlTe~LbX1y~`(StRzTw)BbaPYK_YDa6 zY7d!`Oz6+&_Z1QzA`T`9LXnOfLZ}xA<7?S>D#Btnm|>9K?}2_573v2yjf4enspc;^ z4c%=Qzb3rIC9ZASUgwXGy_OC#y(Vz(pEA7empnGo?op^TV!)gTF{P8&Yb|kOn_`3E zb6F?UrfUIxY0L24PYxW*UKE*;d@tK>Bm1=CSHS62juSfVtq<-uC;_j<6%9t#r8rvt zUgB8TVppyZr;N*q^;HsA{RY*%jjl)O>&`dUn}x2pgi_N{(Qc0_-OL{U>!z*SEB+f`bmjpJ&Qy4tEn_6 z6dfXe{2SKjU$X1JT+V-IY&2>^m*K*{e*;JMI*8*&OUQ*Np|5`^#yzx&sq!Zziy}4Y zn=;Lo$kxv;FOPAa4SmRa@x=wtodWiRQ-`ewJ=DW5{B_S{OLoaEiq6j!szOADOH_(} z5osK}P^swVgEO#NBiezt$jcjuL+AdhFNz2=AHAeEdS_r#bGJ`67hl`|SpMq;JEqoY z2B@@bo)KRLU%jUO>n(z8&I3t$q#sO>g}`9XCR+P1+QBPtdHAABgo}|aHjuU~_a8`3 z>x}239lUlE51n5f$>%g<@cy5?mWWR&^p|D%8`TZWaVicw9Sf%iUPyz-7M?t0k z?!R)d{mCAfl>o=%p{e^-g3pgV^A#o@jmQBTkE4)`xw!rJ5Hn3w7I!MgZTX>*SY!;= zEpmw<5J_$|Uk*Ka&_$$!X zoaD&*m~(Ai+ZVmxbgFfbnfNuWBRkA7q(Ho)n(uhF$CUPLB%9-xV+1CoGm)z8K)NQAY=c9sQ~nlR4-90{ zokFHXtyBw3Q$LcpmI5366OZAb@5+F}rl@+g^rqOAF7xA5Qe zYGIe;*~K0p++ofHd4+wtUA7H|8VyCSBX@21mCgnONqcOld4hZ-T^L=+@WkKgDS!|W z;vr=-0vq$lHs9ASIY9~=z-YVATshbILuWH)>5Yjj;t+obBF}YI;Zh5y0r?^w0-mX! zIp1SzXWUyec#;4z@3h}@Y9=M8&os+RD`X*1S@GBQ>lJhY5 zXk$``kw`UcZNR$=^eH-jX&UuNW$1d>CT_zo6h#*Z01|;UIaUnn-Ub89@4`o$8K}b= zv8?9!t%LG|XMkqbzY`Q0o<*OGrgvv+;fKxdn@iwVavsQENrq~jIlB1dphnr2@!_db zV}*%w8MB;`7u0}&z`DI}w~k7p*|=tPqjmKdDB zuKboU;#{IWRd)aOsZOM6idyN%+3MWw1g>L?(iyf1oN_~Pyf4Zg`B+3x2bxC9)tJQA zj5Nv1pu>Ezg+2y8OATiQ(H@Z_UXrTHJ1O>@3`&}WSVrrq z^JK1Bj%ut-Rhwg9dJKTDC3mO|-GYw^TV)FpX($H;2^WcBG}j;JbCMoK_`y*>)s>pq zQUi&EWl=iw`cBFQ7EH?A&1heX*2^d380~JYd(Lf#FqSE7PR)pE;3%mOkt%#{G#Iu7 zJV(EhN_+aD`(n1&RJ@3P}(DWE~ zqM^=J8=a)(kN3*iE1fI?kC)cEtS;}sfD#1B!I{k zQ|TNXfCd>UMSRC6yU?+)*AP$ASII;)oFtmnpv$7kv1Qy4O3nRlOq`B_yTrPlo_|!G zSg2N*fV#gkU5ZIwAkY+lV8)0rOun@u_E3A>eXCUk%UQ6x=flF-_~s_%3%6)d$@zuL zH)s%>u?LtZXA19zxeMr$v~Hk3Mqgk@FQSRL&(7WeTd7U*49C8GFGtH8b&QGGcCi;f=4zH zf4Gni@a>Rv0sQElaY$S0Q{Z+Tws$jo*5{B-A z4}yS^PPp!#PPFd5x7crd&A^5Gp)r}l>zy!E3t#Kt7; z(U$|swuU}%x3FG5s~7#KXB~!+eS;(5I(xxiee8g@K2CD{(mlh! zPwICm{RR{gXOGda2U)clker@!iIE_ls;l~Dem)ncow5@m=(KB4ysT<+$XjPYCz` zVSyqHp6$m+rNrK?_^LXW0FP9%2PSRP*60%b^P9Q5;g96;fKj=oFKWJ)e9ri_>_3qT z3QGMY&@Qd<;oyZD@KKgt$#FpOyI};l1G?dNgu6IDep#t~G|g0Ta%xm2Wg~_xj%Ulp z1fcDJQ^4IhEX(lrDAHflg{=M7-ezdQ;ObGiJb8S3W!8(Gq|lTLK-Qs9`F{#K�!B zw(rwR=qSB~qJStQp#`a-OGkz{H(w~RDkt-9l{73QRD=K!$IWKLOUbt*q${vLrQoj!NblRK|7$`ax z+D6GF!BfLzi+b+2;DqFqD*B7~)b)1AC0A~gUfD?dZzx^dcq!gm0-XQWbW*Z_;JMKl z_ssy*l|$m2PqjFMvj33Q@PhDk_mRiNqpQq`m%UHTrh3_;=#B8^5Ur=2JWlQQK=3K< zvXyV=JNLYme3xr+PK4^U3Ep)3%+~zx$IQz1#+nb=?0z7Qc>;9c*n?uN#~j^B)J7xR zhM4XXOrs2(knJ(d+)&LY>Dl4wnl4W*t`SBmtj7ZJ@d^8cEbsSz2~d^&Qb8oGeHyfg zvh39%@SoU zpB}7z)>_;Xn0s^7BGlTQShe7>&bFS26uS&NpinTx)!nY43bQ4oB!eczDT;RPI7ZF) zalx~~yf(HZpF(s>1lkDf<5U*%l%k$2ZV5b=|MF>Q-YYHrD8!fS;#r^&&1y{a1?R)C z3o8Xuy#WnthGxWW#jbOE1|O$h>d%MY-pskTZ2A+&jnpQ%JFo?RU3u~dvN^s!qS9GamKSLGZ7a z8b!@@L&snWs_-#o)Q3U*H}T5V@fIC;gbU@911ES5H+s|_K^hAERQXV!JOgnyF69fl z2R-i&cHrt1f>}ZWY%fsvBqy^=$-wCKvLxu<$F*{&oOwu#S5@MKSzLB|4_qBhuWi=g zb2d@SqV4^TGibj{*lEKUopfEp#80QE2$K#Y%z4!a(%c5p=e#BT)Hl?1D zcjRQ=i06$WKb-!gt{Xwf>;;9I=bZd~1HKWcFpB2zbxz7*nyw*vnf671A9pWPg9<3z z|A_z<04YlWB7+TA$72Bb&o(FVZQrEj#l}_SK91yHfVNJB#{sIt-AO`e>V%#EHGG5t z7Ml!0W!#PECh7fi8S9~M03#EXs;Rkvikn^RG>DF5WNX<#m1%JF!6c${%4adVf2HMt z^jPSwwaALV`w-o;vNBPmP|HsLQ;Njc*{_{hZ7+GA(5d_0(Udw2k%LWP{Dc(6 zr77{OXgyY2e_RircQ1@zS+y08ODUjhfB3)CQ^C9pTRv2}|a z4spbJG+jJ<+qUvDlX9yR7D{nx^~eUN(;_$fW$bP>t;wr1-?l^g!n4;ru89w&gq0C3 zKKoQf95mCQGPPiGv4U%cXgw>#_wMy6xAZ2{i_=y!QZ2)bJGmS0myB15q-!WwezFtU z?X}UHiG|g84ZmtuDEDTGUS}+x^8H!~-YNQ2R63Sowx<2;WK!C$qyIqvrbUC0**c2@ zghI}inyDy?z2_^XEuYn~6(L=|bPZpp6AQ;?m_%NULg;%90(S=;l7z8YV6lohEGi@3 zTew1M@|kDqLqq19_jEa}!Frbm@opd97{1%xl}1Zuh_6c5MZC@QbM~|R6hXLFvs*Sc zdgr2=U1(bGr~i+mEZHgsI+2Ua1}>XD_3CqZ%xUxFH!y3?c?@X{GOU_LSvwBiBvGqL z0PVM&ev944&E|58g4_RzK}J=gnRuc&g?CUt5!uU;;Al|X)QI+ z2kj+FA|%@Ewr%SYbnU(Nf_iX#A}qXB2fb^IoV$!ai`Kbp(W7nGTubr|7cLgvYVSK7 zGi(|aLw~$8?bM@tSAz3ZOq0fd`MRb_j&9jHKDo|FNEV+-hP>v)tI#L@3X~=N5f0WU zK+z`7ogCbue5{R#ldcB$4$i75EHo=u877*mtf90GNd7=p($HJjjq`Aq+WPrt8$u48 z>wNn00nbQaWSfyn3QiMk)MZeq?ZdY7Q;1+oXy{`6qVT4+&g^jdEHfi zDrBp_RB`YwAVD?d=n{rG6DnMj`HECH?qQ#Me3DnGOnK`Qi<#+&wNiN z0j5Q$EkV#t9}iS-+i8NMVHnHD$a=%qR*>sg*zr zSNt6&3AvKpBkSqwQITWvALTolH^gLRjr9<@vtbX=ewqtR(S*on_x(TM>7icBJ)m~8 zy>+`IW}N0@{Bi~oBe`0{E+eBmoO@;auA<_p8eY&6hw>MD-?}jF-bg>m#7LtO6d_R> zj=EP3(*Qk#*AU`OmD*Vl&o)Ie1BmyGulQ3{`Fl8gJZpq%w;s&`_{q{_XnYFrW+_gN z5m!VD31y8o=wd`_v$Clf1LiLx1z+6;2Q8LnaB!?@K7wmLc76LJyZD`(VP8c_(;S9; z0kBZ#i9<}G2-sKJzS*h8ZNOJ5br<089HwL8aaR;p*|``vIbU1!xt_~ZG3lvVJL8rv zi3tTvJ!aWxr`sWW$w=!J0|5M5J`Yp|03)KriRx(K@`#M^A%i`E3B4hc<~Sl@ZP?^j zd$wtr;@MYc3qm8-45fY0?N@Bi9v8J-nM*201)v==|B^Ig7E#SmD*_nk2=X+o&Bs{a1na#-hVR+YG)hH^n9 zN3xa)!ADRDmmDEp1DX+Stt9>N`p^m{w~tAm-j9`OXDRSf_v!ag@-41w%*Rx1ElsXo5Hl3x)ZWFBJ#09ZX} zr#v>cN+no`eS*-iVwpZ*zKCSH8B#k>O%lFM5Bv#c0Fygv;FlVBkSy7 zmg@Ea*}(7@XlIV^A=wp@N%`hFe)h3eprUVtQB)okdf`bhI*-!vbo2!q!L^{yq}Z|B zypnFF0s=N7at5j-s(}tDzxnd9#s}t_pz1p8o6$=%+E|pld2jZACgYLKO=;iPC z#H5;7$&o7^yvW-xoR>aD>%}F@8ZJmgn?oh8x(m#2Kdf;)e4)#`-V~E9k3z>2GCkA> zrc*2Fu}9I_^CDjX2`pIyuRu&1Ga5$t_p>5*67_)uH{Lg#a7bvIwu;f@&$ju5Ykjzw z(lFXiDpe4n>MmmKwq~JRzB{X0>t=o{;W$=o8p*B2O30zl=TJoJi6_N2lWoUTlFra; zq(c*UaKkrJ1$O#>Z!?V*AX(on-9cX4PHBY_&kO z(4}}sWlJ#zkXE@CZcnGx1#b_x<&&WsaLI#L>!E!(X*O+X_yP=abq>ejiF2Aipl9PP zIckw>>z@n^n$&*yZO&=emdG~mXh3SSB*23L!va5fm%kAk!NP%)AVn{$PvL&CG}oy& z^UJTZ*`$?cDog=7$8y^s*(YxwU?7Ax72j5n_SWG2GMkfT8w+jUkmCo2WH{8UlwoX~ z0fomr+=pD4$y~(syk*_meO%OJx$-@Hcde z9CfLJ{tU}=dwg0W`9P^T&VVjZDRN*?MVQJ4s#2(AYVEanAH72(v}Bsg%DbaA=2TSO z>w~dca-Q#%>&F`u(e1ZQ6>FAmmhRGGapsp~<7aZbr!qy;b>psV-Q#v=lOS8w@xp?< zmmCsvVzMWiItMfMOSnfwaZGhtObLw-DPP^eU;05qEgqI(1?(YVhn*{^>OD6t^;7NB zxi(Q{|EAfYq^;7eZ!4_tWQrsXQzd$we3nE!)h6x!*1G6U=@BEOUg2Y!VfT>vTW)kfb%rGXBUwuEPA}e3eaB zY%xx;ZBc+6Ls1O-6d-eBReGhpyk5=^-rZp3#KvH(6pL!(yfYVvz`@uVWDE)A7 zJb#p-ktk=OuzX&PCnw2(M2I5c^fUOwLj3PUw>9_E{+Q za7f&7|4x5yQ3Z<&rnl0DzRFDKeZ#gd-2!ul2B`U!fPU}U!|XUxV{aJ4rcRkZ{x`o_ z%L%4Wy(^uRDtza!Lqa?O=q{z{G(SnsHD8-*&gy24&oW4PA09_ehR-8A4ivUbpUBAC zbP*#NhvX%c#U=0vAiy`e23=XR%UM`wukf&d0(#*V6DePVe~ID*wsq}{8U3#-mUXGsO6r^qR9V^Kh3qsME* zg6Ho2hU6*z>jR*hW+#H83~UVOlvEY60=j4NiB|QP^#=T(C7oyWT7|C^LthuGG}QyBw&f9-?e|)CKR*`SZlQkZ#2 zEcZ(-lY#yN$Y6s_&tTtRLr!Pii;3J2U>sfo}u30<|T-(}w>zbS1S@hlSB zbt!*RY86PuqmFq|)@1;pGx`=mMQ)MPNXe+$`m!DeprA?_F($@J6D@LQ+qw5s>51;< z8AVzN{WJ5E9d|pg>31awVE-0GFQZwSuB7)Kx45f1d6A${dW}oS67I&>ix0KP*6cS} zi0vTbC$2Q_c9v}{A-Z{=wHte4qw~*&8UKlj;z6JH8Ii6t25P+9UR>V#i(ZS59*>2x zI@DbEzz?{Yk?>MXp)Ekw7)ij!KmXao^nogsg`gAo01p8b`DyW`n{*mIce>g2J#{3r z!TN+B6|!20F23LcKM%0->3;OAvCQu@tZNf^+g?}Vo6kj!YbhtYPwrWF{@e$xi_Qt& zH2e?27o!tz++cplQ~5LE`he8-<{$57T=XUUqC4dyy|MPxsU^4K?pi!Uq*-}NY%XTa z(h<|K*@5aW#36&{%BMELo{h_CIv7S%PbhFcw5-i-)IoKNCk2NpadkeNl~k_jVdjJp z-eb_eEkvE;GRWb(*Ow)kgZ<;a`d-MH;@hZaZEG{Nu2-MZs7xh2zH?pV9q_KlzC>kr z8ckZ@G8i$IP&xpvMN~O)<~uXg=g?=@>C$wpLF^@(A}8IAo79u4iaz+*ML{0qY$A&{ zSwrJBFGpYf3@z~o!zUhFE4*k*Is0B$%sIhiCC^83x5qfIozjJ5Sgcvw1F5P7!KYPz z1+GUi0IB{-I(&y`=EvBrKLSJ@0st>Fpxh!2esgw>;Bi`f%bO$dD zEp0fQ}D zUuF)m?blnMzHu>ixIJx~Fi+8C$W8~}krJ{Fwr>n*v~7INJ(NAn?o9RLn6+1IxaM1} zghmx&U%xf34~{ zN2)K%it>TbrQ1URofsOv%*|dQ=t!GZIO)Ag4tPN6^PkBpG;6i-1W;6wR@%#zJw9Zo zgnlnxb=SFZH3$EKXMl!XIHKQH{-aBTwS#R7$C=l9@Hg#A$B3E{qyj9Gb`2DK!U5ou zB1++qtkCHlXxyUiQ&L-hiV06gF$yL5@NB$LNw#<6f7;Sl0%=+ho~|%^k=~FBbC{K4RFil?$KW!6aR${YJ;AYQm%Dp+__GQ3;Oy=ZZU|&imfmh>mj@Xal zbn+dy5n+|;`HQ93>n@#So6KD^8qs}ODW>~FL5RQ|=%Me!YtDT_{DhKh6`h4^qRsun z#(ro+ej+BPv}dagYT?%gMc)<0aK%mJ7rYlyGOw3E+DZ=zt`<+T7nBqz(Z27b%nlxT z8p|HEl+XGok%88R{owR-o|QuGoA2$|7wkmdCS*oVOWu0tiovI<87=aC&FiS9c}v4Z zk7RRAZ|(KKrlsAUCq^&zvlz;)7<${a)uQ1I}iAVS2;ZCYv8rY;g~D~YI{_qyDHvK2hK+;f^)U0rcgZr6Q1DOK=E znPtyzgP}GNt}Fw7F)W7^4Cwt=rV~?7%e#SeNeUz1y*VA`KXzPgN1+<7TCZ+1!u^Bj z&tdOKs~q+{67drK_N})%jMfUf?Fy4n-m{ubra_5)>NoXdq|f-11VgG}oe$2h1kRXD z2OWA4m34tGRuC(Q3%-j7>2?4AiU9iq&`pS-Fx3Yb( z{g!I00H=8pN(y(FpIGsl%*n07?Ksr!9qauCO?w*VShdB+$Bz1B^GC?g>SF}zs>Oo# z9Nm6hgicf8St)62XdA=N_(gTP+p@{wX9Z6WmtCF9`pXcev%@p37FuzEQM2UTadHbf zxyPY`_(5bTow5#=k~##X*Gt(;X-X;V>4t1`=j4c=EXgrE`AYnj{NRq48BQI((i64N zjZo&$nJ0$0E<`gFUO0S|Ubx?batGw*@j!SeHaO2}XX^$RbhEML{|_$ri>Uk+&gWujt*r+%gnM{8AY6f9kRVt@P!#xx zPu|TzuP|?y0+v{(Sm?pyJR~zt8TOIE2 zi}0}V1PcFc`hvl9H17Ua{WYcg|I07t=K;6HQkcS6X!SoAP)t-5JDx4@e>4#Y1cc4@ z>jJv|t$`q7P%OXrZ%q`6rBQ#=K-lH_U4w{;{m~Z-kYdaHZ9H-D-}4HCA!6A3{_nWI zTL0D{P+{=zeLilR}6$jMSs_XCH{;P`?C%)G0{KfB8J^Fzl{fhLjDg;Tmt*U_*WeesEGLQc_C17 zENA*#oCN3>qWZ7C*!zK{pMTfH{|`+<;`cZau*4rZu-YGMAOZpXa%280FIK}6xW8-I z$^5B_{a%L%1pL3(-pj+%!5QuW_{AIRIRs$078dQjk3e_1i zP|8Zw+FHa)LKM3RM8&XY3=4z6U{RoGAAz(O22Jrt6`5)@p(+m4h`fC%4K!imk M05@(ZX)6Q%AFAg=K>z>% diff --git a/src/KOKKOS/fix_langevin_kokkos.cpp b/src/KOKKOS/fix_langevin_kokkos.cpp index 651f790a25..8ec51ffa71 100644 --- a/src/KOKKOS/fix_langevin_kokkos.cpp +++ b/src/KOKKOS/fix_langevin_kokkos.cpp @@ -11,20 +11,23 @@ See the README file in the top-level LAMMPS directory. ------------------------------------------------------------------------- */ -#include "fix_langevin_kokkos.h" #include +#include +#include +#include "fix_langevin_kokkos.h" #include "atom_masks.h" #include "atom_kokkos.h" #include "force.h" -#include "group.h" #include "update.h" +#include "respa.h" #include "error.h" #include "memory_kokkos.h" +#include "group.h" +#include "random_mars.h" #include "compute.h" #include "comm.h" #include "modify.h" #include "input.h" -#include "region.h" #include "variable.h" using namespace LAMMPS_NS; @@ -61,7 +64,6 @@ FixLangevinKokkos::FixLangevinKokkos(LAMMPS *lmp, int narg, char **a k_ratio.template modify(); if(gjfflag){ - nvalues = 3; grow_arrays(atomKK->nmax); atom->add_callback(0); // initialize franprev to zero @@ -69,8 +71,12 @@ FixLangevinKokkos::FixLangevinKokkos(LAMMPS *lmp, int narg, char **a franprev[i][0] = 0.0; franprev[i][1] = 0.0; franprev[i][2] = 0.0; + lv[i][0] = 0.0; + lv[i][1] = 0.0; + lv[i][2] = 0.0; } k_franprev.template modify(); + k_lv.template modify(); } if(zeroflag){ k_fsumall = tdual_double_1d_3n("langevin:fsumall"); @@ -94,6 +100,7 @@ FixLangevinKokkos::~FixLangevinKokkos() memoryKK->destroy_kokkos(k_ratio,ratio); memoryKK->destroy_kokkos(k_flangevin,flangevin); if(gjfflag) memoryKK->destroy_kokkos(k_franprev,franprev); + if(gjfflag) memoryKK->destroy_kokkos(k_lv,lv); memoryKK->destroy_kokkos(k_tforce,tforce); } @@ -107,6 +114,11 @@ void FixLangevinKokkos::init() error->all(FLERR,"Fix langevin omega is not yet implemented with kokkos"); if(ascale) error->all(FLERR,"Fix langevin angmom is not yet implemented with kokkos"); + if(gjfflag && tbiasflag) + error->all(FLERR,"Fix langevin gjf + tbias is not yet implemented with kokkos"); + if(gjfflag && tbiasflag) + error->warning(FLERR,"Fix langevin gjf + kokkos is not implemented with random gaussians," + " this may cause errors in kinetic fluctuations"); // prefactors are modified in the init k_gfactor1.template modify(); @@ -121,6 +133,42 @@ void FixLangevinKokkos::grow_arrays(int nmax) memoryKK->grow_kokkos(k_franprev,franprev,nmax,3,"langevin:franprev"); d_franprev = k_franprev.template view(); h_franprev = k_franprev.template view(); + memoryKK->grow_kokkos(k_lv,lv,nmax,3,"langevin:lv"); + d_lv = k_lv.template view(); + h_lv = k_lv.template view(); +} + +/* ---------------------------------------------------------------------- + allow for both per-type and per-atom mass +------------------------------------------------------------------------- */ + +template +void FixLangevinKokkos::initial_integrate(int vflag) +{ + atomKK->sync(execution_space,datamask_read); + atomKK->modified(execution_space,datamask_modify); + + v = atomKK->k_v.view(); + f = atomKK->k_f.view(); + int nlocal = atomKK->nlocal; + if (igroup == atomKK->firstgroup) nlocal = atomKK->nfirst; + + FixLangevinKokkosInitialIntegrateFunctor functor(this); + Kokkos::parallel_for(nlocal,functor); +} + +template +KOKKOS_INLINE_FUNCTION +void FixLangevinKokkos::initial_integrate_item(int i) const +{ + if (mask[i] & groupbit) { + f(i,0) /= gjfa; + f(i,1) /= gjfa; + f(i,2) /= gjfa; + v(i,0) = d_lv(i,0); + v(i,1) = d_lv(i,1); + v(i,2) = d_lv(i,2); + } } /* ---------------------------------------------------------------------- */ @@ -140,6 +188,7 @@ void FixLangevinKokkos::post_force(int vflag) k_gfactor2.template sync(); k_ratio.template sync(); if(gjfflag) k_franprev.template sync(); + if(gjfflag) k_lv.template sync(); boltz = force->boltz; dt = update->dt; @@ -177,7 +226,7 @@ void FixLangevinKokkos::post_force(int vflag) atomKK->sync(temperature->execution_space,temperature->datamask_read); temperature->compute_scalar(); temperature->remove_bias_all(); // modifies velocities - // if temeprature compute is kokkosized host-devcie comm won't be needed + // if temeprature compute is kokkosized host-device comm won't be needed atomKK->modified(temperature->execution_space,temperature->datamask_modify); atomKK->sync(execution_space,temperature->datamask_modify); } @@ -481,6 +530,7 @@ void FixLangevinKokkos::post_force(int vflag) // set modify flags for the views modified in post_force functor if (gjfflag) k_franprev.template modify(); + if (gjfflag) k_lv.template modify(); if (tallyflag) k_flangevin.template modify(); // set total force to zero @@ -550,6 +600,10 @@ FSUM FixLangevinKokkos::post_force_item(int i) const } if (Tp_GJF) { + d_lv(i,0) = gjfsib*v(i,0); + d_lv(i,1) = gjfsib*v(i,1); + d_lv(i,2) = gjfsib*v(i,2); + fswap = 0.5*(fran[0]+d_franprev(i,0)); d_franprev(i,0) = fran[0]; fran[0] = fswap; @@ -560,15 +614,15 @@ FSUM FixLangevinKokkos::post_force_item(int i) const d_franprev(i,2) = fran[2]; fran[2] = fswap; - fdrag[0] *= gjffac; - fdrag[1] *= gjffac; - fdrag[2] *= gjffac; - fran[0] *= gjffac; - fran[1] *= gjffac; - fran[2] *= gjffac; - f(i,0) *= gjffac; - f(i,1) *= gjffac; - f(i,2) *= gjffac; + fdrag[0] *= gjfa; + fdrag[1] *= gjfa; + fdrag[2] *= gjfa; + fran[0] *= gjfa; + fran[1] *= gjfa; + fran[2] *= gjfa; + f(i,0) *= gjfa; + f(i,1) *= gjfa; + f(i,2) *= gjfa; } f(i,0) += fdrag[0] + fran[0]; @@ -576,6 +630,17 @@ FSUM FixLangevinKokkos::post_force_item(int i) const f(i,2) += fdrag[2] + fran[2]; if (Tp_TALLY) { + if (Tp_GJF){ + fdrag[0] = gamma1*d_lv(i,0)/gjfsib/gjfsib; + fdrag[1] = gamma1*d_lv(i,1)/gjfsib/gjfsib; + fdrag[2] = gamma1*d_lv(i,2)/gjfsib/gjfsib; + fswap = (2*fran[0]/gjfa - d_franprev(i,0))/gjfsib; + fran[0] = fswap; + fswap = (2*fran[1]/gjfa - d_franprev(i,1))/gjfsib; + fran[1] = fswap; + fswap = (2*fran[2]/gjfa - d_franprev(i,2))/gjfsib; + fran[2] = fswap; + } d_flangevin(i,0) = fdrag[0] + fran[0]; d_flangevin(i,1) = fdrag[1] + fran[1]; d_flangevin(i,2) = fdrag[2] + fran[2]; @@ -719,9 +784,10 @@ double FixLangevinKokkos::compute_energy_item(int i) const template void FixLangevinKokkos::end_of_step() { - if (!tallyflag) return; + if (!tallyflag && !gjfflag) return; v = atomKK->k_v.template view(); + f = atomKK->k_f.template view(); mask = atomKK->k_mask.template view(); atomKK->sync(execution_space,V_MASK | MASK_MASK); @@ -733,9 +799,81 @@ void FixLangevinKokkos::end_of_step() FixLangevinKokkosTallyEnergyFunctor tally_functor(this); Kokkos::parallel_reduce(nlocal,tally_functor,energy_onestep); + if (gjfflag){ + if (rmass.data()) { + FixLangevinKokkosEndOfStepFunctor functor(this); + Kokkos::parallel_for(nlocal,functor); + } else { + mass = atomKK->k_mass.view(); + FixLangevinKokkosEndOfStepFunctor functor(this); + Kokkos::parallel_for(nlocal,functor); + } + } + energy += energy_onestep*update->dt; } +template +KOKKOS_INLINE_FUNCTION +void FixLangevinKokkos::end_of_step_item(int i) const { + double tmp[3]; + if (mask[i] & groupbit) { + const double dtfm = force->ftm2v * 0.5 * dt / mass[type[i]]; + tmp[0] = v(i,0); + tmp[1] = v(i,1); + tmp[2] = v(i,2); + if (!fsflag){ + v(i,0) = d_lv(i,0); + v(i,1) = d_lv(i,1); + v(i,2) = d_lv(i,2); + } else { + v(i,0) = 0.5 * gjfsib * gjfsib * (v(i,0) + dtfm * f(i,0) / gjfa) + + dtfm * 0.5 * (gjfsib * d_flangevin(i,0) - d_franprev(i,0)) + + (gjfsib * gjfa * 0.5 + dt * 0.25 / t_period / gjfsib) * d_lv(i,0); + v(i,1) = 0.5 * gjfsib * gjfsib * (v(i,1) + dtfm * f(i,1) / gjfa) + + dtfm * 0.5 * (gjfsib * d_flangevin(i,0) - d_franprev(i,1)) + + (gjfsib * gjfa * 0.5 + dt * 0.25 / t_period / gjfsib) * d_lv(i,1); + v(i,2) = 0.5 * gjfsib * gjfsib * (v(i,2) + dtfm * f(i,2) / gjfa) + + dtfm * 0.5 * (gjfsib * d_flangevin(i,0) - d_franprev(i,2)) + + (gjfsib * gjfa * 0.5 + dt * 0.25 / t_period / gjfsib) * d_lv(i,2); + } + d_lv(i,0) = tmp[0]; + d_lv(i,1) = tmp[1]; + d_lv(i,2) = tmp[2]; + } +} + +template +KOKKOS_INLINE_FUNCTION +void FixLangevinKokkos::end_of_step_rmass_item(int i) const +{ + double tmp[3]; + if (mask[i] & groupbit) { + const double dtfm = force->ftm2v * 0.5 * dt / rmass[i]; + tmp[0] = v(i,0); + tmp[1] = v(i,1); + tmp[2] = v(i,2); + if (!fsflag){ + v(i,0) = d_lv(i,0); + v(i,1) = d_lv(i,1); + v(i,2) = d_lv(i,2); + } else { + v(i,0) = 0.5 * gjfsib * gjfsib * (v(i,0) + dtfm * f(i,0) / gjfa) + + dtfm * 0.5 * (gjfsib * d_flangevin(i,0) - d_franprev(i,0)) + + (gjfsib * gjfa * 0.5 + dt * 0.25 / t_period / gjfsib) * d_lv(i,0); + v(i,1) = 0.5 * gjfsib * gjfsib * (v(i,1) + dtfm * f(i,1) / gjfa) + + dtfm * 0.5 * (gjfsib * d_flangevin(i,1) - d_franprev(i,1)) + + (gjfsib * gjfa * 0.5 + dt * 0.25 / t_period / gjfsib) * d_lv(i,1); + v(i,2) = 0.5 * gjfsib * gjfsib * (v(i,2) + dtfm * f(i,2) / gjfa) + + dtfm * 0.5 * (gjfsib * d_flangevin(i,2) - d_franprev(i,2)) + + (gjfsib * gjfa * 0.5 + dt * 0.25 / t_period / gjfsib) * d_lv(i,2); + } + d_lv(i,0) = tmp[0]; + d_lv(i,1) = tmp[1]; + d_lv(i,2) = tmp[2]; + } +} + /* ---------------------------------------------------------------------- copy values within local atom-based array ------------------------------------------------------------------------- */ @@ -743,10 +881,15 @@ void FixLangevinKokkos::end_of_step() template void FixLangevinKokkos::copy_arrays(int i, int j, int delflag) { - for (int m = 0; m < nvalues; m++) - h_franprev(j,m) = h_franprev(i,m); + h_franprev(j,0) = h_franprev(i,0); + h_franprev(j,1) = h_franprev(i,1); + h_franprev(j,2) = h_franprev(i,2); + h_lv(j,0) = h_lv(i,0); + h_lv(j,1) = h_lv(i,1); + h_lv(j,2) = h_lv(i,2); k_franprev.template modify(); + k_lv.template modify(); } @@ -765,6 +908,7 @@ void FixLangevinKokkos::cleanup_copy() tforce = NULL; gjfflag = 0; franprev = NULL; + lv = NULL; id = style = NULL; vatom = NULL; } diff --git a/src/KOKKOS/fix_langevin_kokkos.h b/src/KOKKOS/fix_langevin_kokkos.h index 140fea81d6..4d27b34a7e 100644 --- a/src/KOKKOS/fix_langevin_kokkos.h +++ b/src/KOKKOS/fix_langevin_kokkos.h @@ -56,6 +56,9 @@ namespace LAMMPS_NS { template class FixLangevinKokkos; + template + class FixLangevinKokkosInitialIntegrateFunctor; + template class FixLangevinKokkosPostForceFunctor; @@ -72,6 +75,7 @@ namespace LAMMPS_NS { void cleanup_copy(); void init(); + void initial_integrate(int); void post_force(int); void reset_dt(); void grow_arrays(int); @@ -79,6 +83,12 @@ namespace LAMMPS_NS { double compute_scalar(); void end_of_step(); + KOKKOS_INLINE_FUNCTION + void initial_integrate_item(int) const; + + KOKKOS_INLINE_FUNCTION + void initial_integrate_rmass_item(int) const; + template KOKKOS_INLINE_FUNCTION @@ -90,14 +100,25 @@ namespace LAMMPS_NS { KOKKOS_INLINE_FUNCTION double compute_energy_item(int) const; + KOKKOS_INLINE_FUNCTION + void end_of_step_item(int) const; + + KOKKOS_INLINE_FUNCTION + void end_of_step_rmass_item(int) const; + private: class CommKokkos *commKK; typename ArrayTypes::t_float_1d rmass; + typename ArrayTypes::t_float_1d mass; typename ArrayTypes::tdual_double_2d k_franprev; typename ArrayTypes::t_double_2d d_franprev; HAT::t_double_2d h_franprev; + typename ArrayTypes::tdual_double_2d k_lv; + typename ArrayTypes::t_double_2d d_lv; + HAT::t_double_2d h_lv; + typename ArrayTypes::tdual_double_2d k_flangevin; typename ArrayTypes::t_double_2d d_flangevin; HAT::t_double_2d h_flangevin; @@ -130,6 +151,21 @@ namespace LAMMPS_NS { }; + template + struct FixLangevinKokkosInitialIntegrateFunctor { + typedef DeviceType device_type ; + FixLangevinKokkos c; + + FixLangevinKokkosInitialIntegrateFunctor(FixLangevinKokkos* c_ptr): + c(*c_ptr) {c.cleanup_copy();}; + + KOKKOS_INLINE_FUNCTION + void operator()(const int i) const { + c.initial_integrate_item(i); + } + }; + + template struct FixLangevinKokkosPostForceFunctor { @@ -207,6 +243,21 @@ namespace LAMMPS_NS { update += source; } }; + + template + struct FixLangevinKokkosEndOfStepFunctor { + typedef DeviceType device_type ; + FixLangevinKokkos c; + + FixLangevinKokkosEndOfStepFunctor(FixLangevinKokkos* c_ptr): + c(*c_ptr) {c.cleanup_copy();} + + KOKKOS_INLINE_FUNCTION + void operator()(const int i) const { + if (RMass) c.end_of_step_rmass_item(i); + else c.end_of_step_item(i); + } + }; } #endif diff --git a/src/fix_langevin.cpp b/src/fix_langevin.cpp index 2ed9d9477f..62e31f567a 100644 --- a/src/fix_langevin.cpp +++ b/src/fix_langevin.cpp @@ -223,7 +223,7 @@ void FixLangevin::init() { if (gjfflag){ if (t_period*2 == update->dt) - error->all(FLERR,"Fix langevin gjf cannot have t_period equal to dt/2 at the start"); + error->all(FLERR,"Fix langevin gjf cannot have t_period equal to dt/2"); // warn if any integrate fix comes after this one int before = 1; @@ -440,124 +440,124 @@ void FixLangevin::post_force(int /*vflag*/) if (zeroflag) post_force_templated<1,1,1,1,1,1>(); else post_force_templated<1,1,1,1,1,0>(); else - if (zeroflag) post_force_templated<1,1,1,1,0,1>(); - else post_force_templated<1,1,1,1,0,0>(); + if (zeroflag) post_force_templated<1,1,1,1,0,1>(); + else post_force_templated<1,1,1,1,0,0>(); else - if (rmass) - if (zeroflag) post_force_templated<1,1,1,0,1,1>(); - else post_force_templated<1,1,1,0,1,0>(); + if (rmass) + if (zeroflag) post_force_templated<1,1,1,0,1,1>(); + else post_force_templated<1,1,1,0,1,0>(); + else + if (zeroflag) post_force_templated<1,1,1,0,0,1>(); + else post_force_templated<1,1,1,0,0,0>(); + else + if (tbiasflag == BIAS) + if (rmass) + if (zeroflag) post_force_templated<1,1,0,1,1,1>(); + else post_force_templated<1,1,0,1,1,0>(); + else + if (zeroflag) post_force_templated<1,1,0,1,0,1>(); + else post_force_templated<1,1,0,1,0,0>(); else - if (zeroflag) post_force_templated<1,1,1,0,0,1>(); - else post_force_templated<1,1,1,0,0,0>(); - else - if (tbiasflag == BIAS) - if (rmass) - if (zeroflag) post_force_templated<1,1,0,1,1,1>(); - else post_force_templated<1,1,0,1,1,0>(); + if (rmass) + if (zeroflag) post_force_templated<1,1,0,0,1,1>(); + else post_force_templated<1,1,0,0,1,0>(); + else + if (zeroflag) post_force_templated<1,1,0,0,0,1>(); + else post_force_templated<1,1,0,0,0,0>(); + else + if (tallyflag) + if (tbiasflag == BIAS) + if (rmass) + if (zeroflag) post_force_templated<1,0,1,1,1,1>(); + else post_force_templated<1,0,1,1,1,0>(); + else + if (zeroflag) post_force_templated<1,0,1,1,0,1>(); + else post_force_templated<1,0,1,1,0,0>(); else - if (zeroflag) post_force_templated<1,1,0,1,0,1>(); - else post_force_templated<1,1,0,1,0,0>(); + if (rmass) + if (zeroflag) post_force_templated<1,0,1,0,1,1>(); + else post_force_templated<1,0,1,0,1,0>(); + else + if (zeroflag) post_force_templated<1,0,1,0,0,1>(); + else post_force_templated<1,0,1,0,0,0>(); else - if (rmass) - if (zeroflag) post_force_templated<1,1,0,0,1,1>(); - else post_force_templated<1,1,0,0,1,0>(); - else - if (zeroflag) post_force_templated<1,1,0,0,0,1>(); - else post_force_templated<1,1,0,0,0,0>(); - else - if (tallyflag || fsflag) - if (tbiasflag == BIAS) - if (rmass) - if (zeroflag) post_force_templated<1,0,1,1,1,1>(); - else post_force_templated<1,0,1,1,1,0>(); + if (tbiasflag == BIAS) + if (rmass) + if (zeroflag) post_force_templated<1,0,0,1,1,1>(); + else post_force_templated<1,0,0,1,1,0>(); + else + if (zeroflag) post_force_templated<1,0,0,1,0,1>(); + else post_force_templated<1,0,0,1,0,0>(); else - if (zeroflag) post_force_templated<1,0,1,1,0,1>(); - else post_force_templated<1,0,1,1,0,0>(); - else - if (rmass) - if (zeroflag) post_force_templated<1,0,1,0,1,1>(); - else post_force_templated<1,0,1,0,1,0>(); - else - if (zeroflag) post_force_templated<1,0,1,0,0,1>(); - else post_force_templated<1,0,1,0,0,0>(); - else - if (tbiasflag == BIAS) - if (rmass) - if (zeroflag) post_force_templated<1,0,0,1,1,1>(); - else post_force_templated<1,0,0,1,1,0>(); - else - if (zeroflag) post_force_templated<1,0,0,1,0,1>(); - else post_force_templated<1,0,0,1,0,0>(); - else - if (rmass) - if (zeroflag) post_force_templated<1,0,0,0,1,1>(); - else post_force_templated<1,0,0,0,1,0>(); - else - if (zeroflag) post_force_templated<1,0,0,0,0,1>(); - else post_force_templated<1,0,0,0,0,0>(); + if (rmass) + if (zeroflag) post_force_templated<1,0,0,0,1,1>(); + else post_force_templated<1,0,0,0,1,0>(); + else + if (zeroflag) post_force_templated<1,0,0,0,0,1>(); + else post_force_templated<1,0,0,0,0,0>(); else - if (gjfflag) - if (tallyflag || fsflag) - if (tbiasflag == BIAS) - if (rmass) - if (zeroflag) post_force_templated<0,1,1,1,1,1>(); - else post_force_templated<0,1,1,1,1,0>(); + if (gjfflag) + if (tallyflag) + if (tbiasflag == BIAS) + if (rmass) + if (zeroflag) post_force_templated<0,1,1,1,1,1>(); + else post_force_templated<0,1,1,1,1,0>(); + else + if (zeroflag) post_force_templated<0,1,1,1,0,1>(); + else post_force_templated<0,1,1,1,0,0>(); else - if (zeroflag) post_force_templated<0,1,1,1,0,1>(); - else post_force_templated<0,1,1,1,0,0>(); + if (rmass) + if (zeroflag) post_force_templated<0,1,1,0,1,1>(); + else post_force_templated<0,1,1,0,1,0>(); + else + if (zeroflag) post_force_templated<0,1,1,0,0,1>(); + else post_force_templated<0,1,1,0,0,0>(); else - if (rmass) - if (zeroflag) post_force_templated<0,1,1,0,1,1>(); - else post_force_templated<0,1,1,0,1,0>(); + if (tbiasflag == BIAS) + if (rmass) + if (zeroflag) post_force_templated<0,1,0,1,1,1>(); + else post_force_templated<0,1,0,1,1,0>(); + else + if (zeroflag) post_force_templated<0,1,0,1,0,1>(); + else post_force_templated<0,1,0,1,0,0>(); + else + if (rmass) + if (zeroflag) post_force_templated<0,1,0,0,1,1>(); + else post_force_templated<0,1,0,0,1,0>(); + else + if (zeroflag) post_force_templated<0,1,0,0,0,1>(); + else post_force_templated<0,1,0,0,0,0>(); + else + if (tallyflag) + if (tbiasflag == BIAS) + if (rmass) + if (zeroflag) post_force_templated<0,0,1,1,1,1>(); + else post_force_templated<0,0,1,1,1,0>(); + else + if (zeroflag) post_force_templated<0,0,1,1,0,1>(); + else post_force_templated<0,0,1,1,0,0>(); + else + if (rmass) + if (zeroflag) post_force_templated<0,0,1,0,1,1>(); + else post_force_templated<0,0,1,0,1,0>(); + else + if (zeroflag) post_force_templated<0,0,1,0,0,1>(); + else post_force_templated<0,0,1,0,0,0>(); else - if (zeroflag) post_force_templated<0,1,1,0,0,1>(); - else post_force_templated<0,1,1,0,0,0>(); - else - if (tbiasflag == BIAS) - if (rmass) - if (zeroflag) post_force_templated<0,1,0,1,1,1>(); - else post_force_templated<0,1,0,1,1,0>(); - else - if (zeroflag) post_force_templated<0,1,0,1,0,1>(); - else post_force_templated<0,1,0,1,0,0>(); - else - if (rmass) - if (zeroflag) post_force_templated<0,1,0,0,1,1>(); - else post_force_templated<0,1,0,0,1,0>(); - else - if (zeroflag) post_force_templated<0,1,0,0,0,1>(); - else post_force_templated<0,1,0,0,0,0>(); - else - if (tallyflag || fsflag) - if (tbiasflag == BIAS) - if (rmass) - if (zeroflag) post_force_templated<0,0,1,1,1,1>(); - else post_force_templated<0,0,1,1,1,0>(); - else - if (zeroflag) post_force_templated<0,0,1,1,0,1>(); - else post_force_templated<0,0,1,1,0,0>(); - else - if (rmass) - if (zeroflag) post_force_templated<0,0,1,0,1,1>(); - else post_force_templated<0,0,1,0,1,0>(); - else - if (zeroflag) post_force_templated<0,0,1,0,0,1>(); - else post_force_templated<0,0,1,0,0,0>(); - else - if (tbiasflag == BIAS) - if (rmass) - if (zeroflag) post_force_templated<0,0,0,1,1,1>(); - else post_force_templated<0,0,0,1,1,0>(); - else - if (zeroflag) post_force_templated<0,0,0,1,0,1>(); - else post_force_templated<0,0,0,1,0,0>(); - else - if (rmass) - if (zeroflag) post_force_templated<0,0,0,0,1,1>(); - else post_force_templated<0,0,0,0,1,0>(); - else - if (zeroflag) post_force_templated<0,0,0,0,0,1>(); - else post_force_templated<0,0,0,0,0,0>(); + if (tbiasflag == BIAS) + if (rmass) + if (zeroflag) post_force_templated<0,0,0,1,1,1>(); + else post_force_templated<0,0,0,1,1,0>(); + else + if (zeroflag) post_force_templated<0,0,0,1,0,1>(); + else post_force_templated<0,0,0,1,0,0>(); + else + if (rmass) + if (zeroflag) post_force_templated<0,0,0,0,1,1>(); + else post_force_templated<0,0,0,0,1,0>(); + else + if (zeroflag) post_force_templated<0,0,0,0,0,1>(); + else post_force_templated<0,0,0,0,0,0>(); } /* ---------------------------------------------------------------------- */ @@ -572,7 +572,7 @@ void FixLangevin::post_force_respa(int vflag, int ilevel, int /*iloop*/) ------------------------------------------------------------------------- */ template < int Tp_TSTYLEATOM, int Tp_GJF, int Tp_TALLY, - int Tp_BIAS, int Tp_RMASS, int Tp_ZERO > + int Tp_BIAS, int Tp_RMASS, int Tp_ZERO > void FixLangevin::post_force_templated() { double gamma1,gamma2; @@ -802,9 +802,9 @@ void FixLangevin::compute_target() input->variable->compute_atom(tvar,igroup,tforce,1,0); for (int i = 0; i < nlocal; i++) if (mask[i] & groupbit) - if (tforce[i] < 0.0) - error->one(FLERR, - "Fix langevin variable returned negative temperature"); + if (tforce[i] < 0.0) + error->one(FLERR, + "Fix langevin variable returned negative temperature"); } modify->addstep_compute(update->ntimestep + 1); } @@ -1001,8 +1001,8 @@ void FixLangevin::reset_dt() if (atom->mass) { for (int i = 1; i <= atom->ntypes; i++) { gfactor2[i] = sqrt(atom->mass[i]) * - sqrt(24.0*force->boltz/t_period/update->dt/force->mvv2e) / - force->ftm2v; + sqrt(24.0*force->boltz/t_period/update->dt/force->mvv2e) / + force->ftm2v; gfactor2[i] *= 1.0/sqrt(ratio[i]); } } diff --git a/src/fix_langevin.h b/src/fix_langevin.h index 2ef1489273..3ffccb3be1 100644 --- a/src/fix_langevin.h +++ b/src/fix_langevin.h @@ -2,10 +2,12 @@ LAMMPS - Large-scale Atomic/Molecular Massively Parallel Simulator http://lammps.sandia.gov, Sandia National Laboratories Steve Plimpton, sjplimp@sandia.gov + Copyright (2003) Sandia Corporation. Under the terms of Contract DE-AC04-94AL85000 with Sandia Corporation, the U.S. Government retains certain rights in this software. This software is distributed under the GNU General Public License. + See the README file in the top-level LAMMPS directory. ------------------------------------------------------------------------- */ @@ -22,63 +24,63 @@ FixStyle(langevin,FixLangevin) namespace LAMMPS_NS { - class FixLangevin : public Fix { - public: - FixLangevin(class LAMMPS *, int, char **); - virtual ~FixLangevin(); - int setmask(); - void init(); - void setup(int); - virtual void initial_integrate(int); - virtual void post_force(int); - void post_force_respa(int, int, int); - virtual void end_of_step(); - void reset_target(double); - void reset_dt(); - int modify_param(int, char **); - virtual double compute_scalar(); - double memory_usage(); - virtual void *extract(const char *, int &); - void grow_arrays(int); - void copy_arrays(int, int, int); - int pack_exchange(int, double *); - int unpack_exchange(int, double *); +class FixLangevin : public Fix { + public: + FixLangevin(class LAMMPS *, int, char **); + virtual ~FixLangevin(); + int setmask(); + void init(); + void setup(int); + virtual void initial_integrate(int); + virtual void post_force(int); + void post_force_respa(int, int, int); + virtual void end_of_step(); + void reset_target(double); + void reset_dt(); + int modify_param(int, char **); + virtual double compute_scalar(); + double memory_usage(); + virtual void *extract(const char *, int &); + void grow_arrays(int); + void copy_arrays(int, int, int); + int pack_exchange(int, double *); + int unpack_exchange(int, double *); - protected: - int gjfflag,fsflag,oflag,tallyflag,zeroflag,tbiasflag; - int flangevin_allocated; - double ascale; - double t_start,t_stop,t_period,t_target; - double *gfactor1,*gfactor2,*ratio; - double energy,energy_onestep; - double tsqrt; - int tstyle,tvar; - double gjfa, gjfsib; //gjf a and gjf sqrt inverse b - char *tstr; + protected: + int gjfflag,fsflag,oflag,tallyflag,zeroflag,tbiasflag; + int flangevin_allocated; + double ascale; + double t_start,t_stop,t_period,t_target; + double *gfactor1,*gfactor2,*ratio; + double energy,energy_onestep; + double tsqrt; + int tstyle,tvar; + double gjfa, gjfsib; //gjf a and gjf sqrt inverse b + char *tstr; - class AtomVecEllipsoid *avec; + class AtomVecEllipsoid *avec; - int maxatom1,maxatom2; - double **flangevin; - double *tforce; - double **franprev; - double **lv; //half step velocity + int maxatom1,maxatom2; + double **flangevin; + double *tforce; + double **franprev; + double **lv; //half step velocity - char *id_temp; - class Compute *temperature; + char *id_temp; + class Compute *temperature; - int nlevels_respa; - class RanMars *random; - int seed; + int nlevels_respa; + class RanMars *random; + int seed; - template < int Tp_TSTYLEATOM, int Tp_GJF, int Tp_TALLY, - int Tp_BIAS, int Tp_RMASS, int Tp_ZERO > - void post_force_templated(); + template < int Tp_TSTYLEATOM, int Tp_GJF, int Tp_TALLY, + int Tp_BIAS, int Tp_RMASS, int Tp_ZERO > + void post_force_templated(); - void omega_thermostat(); - void angmom_thermostat(); - void compute_target(); - }; + void omega_thermostat(); + void angmom_thermostat(); + void compute_target(); +}; } @@ -86,35 +88,74 @@ namespace LAMMPS_NS { #endif /* ERROR/WARNING messages: + E: Illegal ... command + Self-explanatory. Check the input script syntax and compare to the documentation for the command. You can use -echo screen as a command-line option when running LAMMPS to see the offending line. + E: Fix langevin period must be > 0.0 + The time window for temperature relaxation must be > 0 + E: Fix langevin omega requires atom style sphere + Self-explanatory. + E: Fix langevin angmom requires atom style ellipsoid + Self-explanatory. + E: Variable name for fix langevin does not exist + Self-explanatory. + E: Variable for fix langevin is invalid style + It must be an equal-style variable. + E: Fix langevin omega requires extended particles + One of the particles has radius 0.0. + E: Fix langevin angmom requires extended particles + This fix option cannot be used with point particles. + E: Cannot zero Langevin force of 0 atoms + The group has zero atoms, so you cannot request its force be zeroed. + E: Fix langevin variable returned negative temperature + Self-explanatory. + E: Could not find fix_modify temperature ID + The compute ID for computing temperature does not exist. + E: Fix_modify temperature ID does not compute temperature + The compute ID assigned to the fix must compute temperature. + +E: Fix langevin gjf cannot have period equal to dt/2 + +If the period is equal to dt/2 then division by zero can happen. + +E: Fix langevin gjf should come before fix nve + +Self-explanatory + +E: Fix langevin gjf and respa are not compatible + +Self-explanatory + W: Group for fix_modify temp != fix group + The fix_modify command is specifying a temperature computation that computes a temperature on a different group of atoms than the fix itself operates on. This is probably not what you want to do. + */ From c26b1d183905b7738091fb240d052084c709e50c Mon Sep 17 00:00:00 2001 From: charlie sievers Date: Thu, 12 Sep 2019 16:50:42 -0700 Subject: [PATCH 131/192] fixed indentations in fix_langevin.cpp --- src/fix_langevin.cpp | 11 ++++++----- 1 file changed, 6 insertions(+), 5 deletions(-) diff --git a/src/fix_langevin.cpp b/src/fix_langevin.cpp index 62e31f567a..25b4f83c37 100644 --- a/src/fix_langevin.cpp +++ b/src/fix_langevin.cpp @@ -2,10 +2,12 @@ LAMMPS - Large-scale Atomic/Molecular Massively Parallel Simulator http://lammps.sandia.gov, Sandia National Laboratories Steve Plimpton, sjplimp@sandia.gov + Copyright (2003) Sandia Corporation. Under the terms of Contract DE-AC04-94AL85000 with Sandia Corporation, the U.S. Government retains certain rights in this software. This software is distributed under the GNU General Public License. + See the README file in the top-level LAMMPS directory. ------------------------------------------------------------------------- */ @@ -49,9 +51,9 @@ enum{CONSTANT,EQUAL,ATOM}; /* ---------------------------------------------------------------------- */ FixLangevin::FixLangevin(LAMMPS *lmp, int narg, char **arg) : - Fix(lmp, narg, arg), - gjfflag(0), gfactor1(NULL), gfactor2(NULL), ratio(NULL), tstr(NULL), - flangevin(NULL), tforce(NULL), franprev(NULL), id_temp(NULL), random(NULL), lv(NULL) + Fix(lmp, narg, arg), + gjfflag(0), gfactor1(NULL), gfactor2(NULL), ratio(NULL), tstr(NULL), + flangevin(NULL), tforce(NULL), franprev(NULL), id_temp(NULL), random(NULL), lv(NULL) { if (narg < 7) error->all(FLERR,"Illegal fix langevin command"); @@ -169,7 +171,7 @@ FixLangevin::FixLangevin(LAMMPS *lmp, int narg, char **arg) : grow_arrays(atom->nmax); atom->add_callback(0); - // initialize franprev to zero + // initialize franprev to zero int nlocal = atom->nlocal; for (int i = 0; i < nlocal; i++) { @@ -737,7 +739,6 @@ void FixLangevin::post_force_templated() flangevin[i][2] = fdrag[2] + fran[2]; } - } } From 1f9decadf8a44a4c2e4138871531657de7d3e9be Mon Sep 17 00:00:00 2001 From: Axel Kohlmeyer Date: Fri, 13 Sep 2019 08:03:02 -0400 Subject: [PATCH 132/192] fix typo --- doc/src/Build_extras.txt | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/doc/src/Build_extras.txt b/doc/src/Build_extras.txt index b0bf0c9cd6..92b6314004 100644 --- a/doc/src/Build_extras.txt +++ b/doc/src/Build_extras.txt @@ -802,7 +802,7 @@ dir, using a command like these, which simply invoke the lib/h5md/Install.py script with the specified args: make lib-h5md # print help message -make lib-hm5d args="-m h5cc" # build with h5cc compiler :pre +make lib-h5md args="-m h5cc" # build with h5cc compiler :pre The build should produce two files: lib/h5md/libch5md.a and lib/h5md/Makefile.lammps. The latter is copied from an existing From 7386956dc5b3275339f6d13515a4ea63fe450e46 Mon Sep 17 00:00:00 2001 From: Axel Kohlmeyer Date: Fri, 13 Sep 2019 08:52:09 -0400 Subject: [PATCH 133/192] remove misspelled word from false positives list --- doc/utils/sphinx-config/false_positives.txt | 1 - 1 file changed, 1 deletion(-) diff --git a/doc/utils/sphinx-config/false_positives.txt b/doc/utils/sphinx-config/false_positives.txt index 6d5112b4c7..3ce7c4d975 100644 --- a/doc/utils/sphinx-config/false_positives.txt +++ b/doc/utils/sphinx-config/false_positives.txt @@ -2044,7 +2044,6 @@ Otype Ouldridge outfile outmost -outpur outputss Ouyang overlayed From 548fd40e9a44abe483a147483f55500309031981 Mon Sep 17 00:00:00 2001 From: Axel Kohlmeyer Date: Fri, 13 Sep 2019 09:15:39 -0400 Subject: [PATCH 134/192] make certain that nvalues class member is initialized --- src/fix_langevin.cpp | 1 + 1 file changed, 1 insertion(+) diff --git a/src/fix_langevin.cpp b/src/fix_langevin.cpp index a050e5a13a..1e86a90218 100644 --- a/src/fix_langevin.cpp +++ b/src/fix_langevin.cpp @@ -92,6 +92,7 @@ FixLangevin::FixLangevin(LAMMPS *lmp, int narg, char **arg) : for (int i = 1; i <= atom->ntypes; i++) ratio[i] = 1.0; ascale = 0.0; gjfflag = 0; + nvalues = 0; oflag = 0; tallyflag = 0; zeroflag = 0; From ca301f040b838fa79ab30137e5014951cbf4c610 Mon Sep 17 00:00:00 2001 From: Axel Kohlmeyer Date: Fri, 13 Sep 2019 09:47:02 -0400 Subject: [PATCH 135/192] add missing include for compiling with intel compilers without TBB --- src/memory.cpp | 1 + 1 file changed, 1 insertion(+) diff --git a/src/memory.cpp b/src/memory.cpp index a513dde6c2..4374882efe 100644 --- a/src/memory.cpp +++ b/src/memory.cpp @@ -20,6 +20,7 @@ #define LMP_USE_TBB_ALLOCATOR #include "tbb/scalable_allocator.h" #else +#include #include #endif #endif From 0a176d48d8c0b96ffa2425cd8d8b584c6c747f17 Mon Sep 17 00:00:00 2001 From: Axel Kohlmeyer Date: Fri, 13 Sep 2019 11:59:55 -0400 Subject: [PATCH 136/192] clarify that each created file will have the ITEM: UNITS lines --- doc/src/dump_modify.txt | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/doc/src/dump_modify.txt b/doc/src/dump_modify.txt index 11427b100e..3aff21e43e 100644 --- a/doc/src/dump_modify.txt +++ b/doc/src/dump_modify.txt @@ -623,8 +623,8 @@ threshold criterion is met. Otherwise it is not met. The {units} keyword only applies to the dump {atom}, {custom}, and {local} styles (and their COMPRESS package versions {atom/gz}, -{custom/gz} and {local/gz}). If set to {yes}, each dump file will contain -two extra lines at the very beginning with: +{custom/gz} and {local/gz}). If set to {yes}, each individal dump +file will contain two extra lines at the very beginning with: ITEM: UNITS \ :pre From 5a07db8465ecc0058ed5686212d033c379a9c374 Mon Sep 17 00:00:00 2001 From: Axel Kohlmeyer Date: Fri, 13 Sep 2019 12:07:39 -0400 Subject: [PATCH 137/192] tweak docs for dump_modify units command some more --- doc/src/compute_pair_local.txt | 29 ++++++++++++++++++----------- 1 file changed, 18 insertions(+), 11 deletions(-) diff --git a/doc/src/compute_pair_local.txt b/doc/src/compute_pair_local.txt index 5b507d447c..10ff689582 100644 --- a/doc/src/compute_pair_local.txt +++ b/doc/src/compute_pair_local.txt @@ -62,17 +62,24 @@ pair styles do not define any additional quantities, so N = 0. An example of ones that do are the "granular pair styles"_pair_gran.html which calculate the tangential force between two particles and return its components and magnitude acting on atom I for N = 1,2,3,4. See -individual pair styles for details. When using pair style {hybrid}, -the output will be that of the Nth quantity from the active sub-style -active or 0.0. The maximum allowed N is the maximum of any sub-style. -When using pair style {hybrid/overlay} all additional properties of -all pair styles are available for output, but the values of inactive -sub-styles for a given pair of atom types will be 0.0. Thus if there -are, for example, 3 sub-styles and 2 of them have additional output -(3 and 4 items, respectively), the maximum N would be 7 and {p1}, {p2}, -and {p3} would refer to the first 3 additional properties and the -remaining allowed parameters {p4} to {p7} would address properties {p1} -to {p4} of the second sub-style with additional properties. +individual pair styles for details. + +When using {pN} with pair style {hybrid}, the output will be the Nth +quantity from the sub-style that computes the pairwise interaction +(based on atom types). If that sub-style does not define a {pN}, +the output will be 0.0. The maximum allowed N is the maximum number +of quantities provided by any sub-style. + +When using {pN} with pair style {hybrid/overlay} the quantities +from all sub-styles that provide them are concatenated together +into one long list. For example, if there are 3 sub-styles and +2 of them have additional output (with 3 and 4 quantities, +respectively), then 7 values ({p1} up to {p7}) are defined. +The values {p1} to {p3} refer to quantities defined by the first +of the two sub-styles. Values {p4} to {p7} refer to quantities +from the second of the two sub-styles. If the referenced {pN} +is not computed for the specific pairwise interaction (based on +atom types), then the output will be 0.0. The value {dist} will be in distance "units"_units.html. The value {eng} will be in energy "units"_units.html. The values {force}, {fx}, From c37d00117886a2b240551d497e8d0d9709d12db9 Mon Sep 17 00:00:00 2001 From: Axel Kohlmeyer Date: Fri, 13 Sep 2019 16:13:16 -0400 Subject: [PATCH 138/192] fix stupid typo --- doc/src/dump_modify.txt | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/doc/src/dump_modify.txt b/doc/src/dump_modify.txt index 3aff21e43e..994e9fea3c 100644 --- a/doc/src/dump_modify.txt +++ b/doc/src/dump_modify.txt @@ -623,7 +623,7 @@ threshold criterion is met. Otherwise it is not met. The {units} keyword only applies to the dump {atom}, {custom}, and {local} styles (and their COMPRESS package versions {atom/gz}, -{custom/gz} and {local/gz}). If set to {yes}, each individal dump +{custom/gz} and {local/gz}). If set to {yes}, each individual dump file will contain two extra lines at the very beginning with: ITEM: UNITS From 790d7d9fae8c6cc6e9bb4ad54953550a769df608 Mon Sep 17 00:00:00 2001 From: Aidan Thompson Date: Fri, 13 Sep 2019 15:59:25 -0600 Subject: [PATCH 139/192] Added log files and updated README --- examples/README | 1 + examples/steinhardt/log.13Sept18.bcc.g++.1 | 176 +++++++++++++++ examples/steinhardt/log.13Sept18.bcc.g++.4 | 176 +++++++++++++++ examples/steinhardt/log.13Sept18.fcc.g++.1 | 172 ++++++++++++++ examples/steinhardt/log.13Sept18.fcc.g++.4 | 172 ++++++++++++++ examples/steinhardt/log.13Sept18.icos.g++.1 | 235 ++++++++++++++++++++ examples/steinhardt/log.13Sept18.icos.g++.4 | 235 ++++++++++++++++++++ 7 files changed, 1167 insertions(+) create mode 100644 examples/steinhardt/log.13Sept18.bcc.g++.1 create mode 100644 examples/steinhardt/log.13Sept18.bcc.g++.4 create mode 100644 examples/steinhardt/log.13Sept18.fcc.g++.1 create mode 100644 examples/steinhardt/log.13Sept18.fcc.g++.4 create mode 100644 examples/steinhardt/log.13Sept18.icos.g++.1 create mode 100644 examples/steinhardt/log.13Sept18.icos.g++.4 diff --git a/examples/README b/examples/README index dbfdb3363b..46148aea8b 100644 --- a/examples/README +++ b/examples/README @@ -105,6 +105,7 @@ shear: sideways shear applied to 2d solid, with and without a void snap: use of SNAP potential for Ta srd: stochastic rotation dynamics (SRD) particles as solvent snap: NVE dynamics for BCC tantalum crystal using SNAP potential +steinhardt: Steinhardt-Nelson Q_l and W_l parameters usng orientorder/atom streitz: Streitz-Mintmire potential for Al2O3 tad: temperature-accelerated dynamics of vacancy diffusion in bulk Si threebody: regression test input for a variety of manybody potentials diff --git a/examples/steinhardt/log.13Sept18.bcc.g++.1 b/examples/steinhardt/log.13Sept18.bcc.g++.1 new file mode 100644 index 0000000000..b0a82fca90 --- /dev/null +++ b/examples/steinhardt/log.13Sept18.bcc.g++.1 @@ -0,0 +1,176 @@ +LAMMPS (7 Aug 2019) +OMP_NUM_THREADS environment is not set. Defaulting to 1 thread. (../comm.cpp:93) + using 1 OpenMP thread(s) per MPI task +# Steinhardt-Nelson bond orientational order parameters for BCC + +variable rcut equal 3.0 + +boundary p p p + +atom_style atomic +neighbor 0.3 bin +neigh_modify delay 5 + +# create geometry + +lattice bcc 1.0 +Lattice spacing in x,y,z = 1.25992 1.25992 1.25992 +region box block 0 3 0 3 0 3 +create_box 1 box +Created orthogonal box = (0 0 0) to (3.77976 3.77976 3.77976) + 1 by 1 by 1 MPI processor grid +create_atoms 1 box +Created 54 atoms + create_atoms CPU = 0.000282049 secs + +mass 1 1.0 + +# LJ potentials + +pair_style lj/cut ${rcut} +pair_style lj/cut 3 +pair_coeff * * 1.0 1.0 ${rcut} +pair_coeff * * 1.0 1.0 3 + +# 14 neighbors, perfect crystal + +compute qlwlhat all orientorder/atom degrees 6 2 4 6 8 10 12 nnn 14 wl/hat yes +compute avql all reduce ave c_qlwlhat[1] c_qlwlhat[2] c_qlwlhat[3] c_qlwlhat[4] c_qlwlhat[5] c_qlwlhat[6] +compute avwlhat all reduce ave c_qlwlhat[7] c_qlwlhat[8] c_qlwlhat[9] c_qlwlhat[10] c_qlwlhat[11] c_qlwlhat[12] + +thermo_style custom step temp epair etotal c_avql[*] c_avwlhat[*] + +run 0 +WARNING: No fixes defined, atoms won't move (../verlet.cpp:52) +Neighbor list info ... + update every 1 steps, delay 5 steps, check yes + max neighbors/atom: 2000, page size: 100000 + master list distance cutoff = 3.3 + ghost atom cutoff = 3.3 + binsize = 1.65, bins = 3 3 3 + 2 neighbor lists, perpetual/occasional/extra = 1 1 0 + (1) pair lj/cut, perpetual + attributes: half, newton on + pair build: half/bin/atomonly/newton + stencil: half/bin/3d/newton + bin: standard + (2) compute orientorder/atom, occasional + attributes: full, newton on + pair build: full/bin/atomonly + stencil: full/bin/3d + bin: standard +Per MPI rank memory allocation (min/avg/max) = 3.746 | 3.746 | 3.746 Mbytes +Step Temp E_pair TotEng c_avql[1] c_avql[2] c_avql[3] c_avql[4] c_avql[5] c_avql[6] c_avwlhat[1] c_avwlhat[2] c_avwlhat[3] c_avwlhat[4] c_avwlhat[5] c_avwlhat[6] + 0 0 -7.8104466 -7.8104466 8.6570408e-17 0.036369648 0.51068823 0.42932247 0.19519122 0.40479919 0 0.15931737 0.013160601 0.058454791 -0.090130212 -0.049573639 +Loop time of 9.53674e-07 on 1 procs for 0 steps with 54 atoms + +209.7% CPU use with 1 MPI tasks x 1 OpenMP threads + +MPI task timing breakdown: +Section | min time | avg time | max time |%varavg| %total +--------------------------------------------------------------- +Pair | 0 | 0 | 0 | 0.0 | 0.00 +Neigh | 0 | 0 | 0 | 0.0 | 0.00 +Comm | 0 | 0 | 0 | 0.0 | 0.00 +Output | 0 | 0 | 0 | 0.0 | 0.00 +Modify | 0 | 0 | 0 | 0.0 | 0.00 +Other | | 9.537e-07 | | |100.00 + +Nlocal: 54 ave 54 max 54 min +Histogram: 1 0 0 0 0 0 0 0 0 0 +Nghost: 1187 ave 1187 max 1187 min +Histogram: 1 0 0 0 0 0 0 0 0 0 +Neighs: 4536 ave 4536 max 4536 min +Histogram: 1 0 0 0 0 0 0 0 0 0 +FullNghs: 9072 ave 9072 max 9072 min +Histogram: 1 0 0 0 0 0 0 0 0 0 + +Total # of neighbors = 9072 +Ave neighs/atom = 168 +Neighbor list builds = 0 +Dangerous builds = 0 + +# check Q_l values + +print " " + +print "*******************************************************************" +******************************************************************* +print " " + +print "Comparison with reference values of Q_l " +Comparison with reference values of Q_l +print " [Table I in W. Mickel, S. C. Kapfer," + [Table I in W. Mickel, S. C. Kapfer, +print " G. E. Schroeder-Turkand, K. Mecke, " + G. E. Schroeder-Turkand, K. Mecke, +print " J. Chem. Phys. 138, 044501 (2013).]" + J. Chem. Phys. 138, 044501 (2013).] +print " " + + +variable q2ref equal 0.0 +variable q4ref equal 0.036 +variable q6ref equal 0.511 +variable q8ref equal 0.429 +variable q10ref equal 0.195 +variable q12ref equal 0.405 + +variable q2 equal c_avql[1] +variable q4 equal c_avql[2] +variable q6 equal c_avql[3] +variable q8 equal c_avql[4] +variable q10 equal c_avql[5] +variable q12 equal c_avql[6] + +print "q2 = $(v_q2:%10.6f) delta = $(v_q2-v_q2ref:%10.4f)" +q2 = 0.000000 delta = 0.0000 +print "q4 = $(v_q4:%10.6f) delta = $(v_q4-v_q4ref:%10.4f)" +q4 = 0.036370 delta = 0.0004 +print "q6 = $(v_q6:%10.6f) delta = $(v_q6-v_q6ref:%10.4f)" +q6 = 0.510688 delta = -0.0003 +print "q8 = $(v_q8:%10.6f) delta = $(v_q8-v_q8ref:%10.4f)" +q8 = 0.429322 delta = 0.0003 +print "q10 = $(v_q10:%10.6f) delta = $(v_q10-v_q10ref:%10.4f)" +q10 = 0.195191 delta = 0.0002 +print "q12 = $(v_q12:%10.6f) delta = $(v_q12-v_q12ref:%10.4f)" +q12 = 0.404799 delta = -0.0002 + +# check W_l_hat values + +print " " + +print "Comparison with reference values of W_l_hat" +Comparison with reference values of W_l_hat +print " [Table I in P. Steinhardt, D. Nelson, and M. Ronchetti, " + [Table I in P. Steinhardt, D. Nelson, and M. Ronchetti, +print " Phys. Rev. B 28, 784 (1983).]" + Phys. Rev. B 28, 784 (1983).] +print " " + + +variable w4hatref equal 0.159317 +variable w6hatref equal 0.013161 +variable w8hatref equal -0.058455 +variable w10hatref equal -0.090130 + +variable w4hat equal c_avwlhat[2] +variable w6hat equal c_avwlhat[3] +variable w8hat equal c_avwlhat[4] +variable w10hat equal c_avwlhat[5] + +print "w4hat = $(v_w4hat:%10.6f) delta = $(v_w4hat-v_w4hatref:%10.6f)" +w4hat = 0.159317 delta = 0.000000 +print "w6hat = $(v_w6hat:%10.6f) delta = $(v_w6hat-v_w6hatref:%10.6f)" +w6hat = 0.013161 delta = -0.000000 +print "w8hat = $(v_w8hat:%10.6f) delta = $(v_w8hat-v_w8hatref:%10.6f)" +w8hat = 0.058455 delta = 0.116910 +print "w10hat = $(v_w10hat:%10.6f) delta = $(v_w10hat-v_w10hatref:%10.6f)" +w10hat = -0.090130 delta = -0.000000 +print " " + +print "*******************************************************************" +******************************************************************* +print " " + +Total wall time: 0:00:00 diff --git a/examples/steinhardt/log.13Sept18.bcc.g++.4 b/examples/steinhardt/log.13Sept18.bcc.g++.4 new file mode 100644 index 0000000000..ee1f0c69c1 --- /dev/null +++ b/examples/steinhardt/log.13Sept18.bcc.g++.4 @@ -0,0 +1,176 @@ +LAMMPS (7 Aug 2019) +OMP_NUM_THREADS environment is not set. Defaulting to 1 thread. (../comm.cpp:93) + using 1 OpenMP thread(s) per MPI task +# Steinhardt-Nelson bond orientational order parameters for BCC + +variable rcut equal 3.0 + +boundary p p p + +atom_style atomic +neighbor 0.3 bin +neigh_modify delay 5 + +# create geometry + +lattice bcc 1.0 +Lattice spacing in x,y,z = 1.25992 1.25992 1.25992 +region box block 0 3 0 3 0 3 +create_box 1 box +Created orthogonal box = (0 0 0) to (3.77976 3.77976 3.77976) + 1 by 2 by 2 MPI processor grid +create_atoms 1 box +Created 54 atoms + create_atoms CPU = 0.000533104 secs + +mass 1 1.0 + +# LJ potentials + +pair_style lj/cut ${rcut} +pair_style lj/cut 3 +pair_coeff * * 1.0 1.0 ${rcut} +pair_coeff * * 1.0 1.0 3 + +# 14 neighbors, perfect crystal + +compute qlwlhat all orientorder/atom degrees 6 2 4 6 8 10 12 nnn 14 wl/hat yes +compute avql all reduce ave c_qlwlhat[1] c_qlwlhat[2] c_qlwlhat[3] c_qlwlhat[4] c_qlwlhat[5] c_qlwlhat[6] +compute avwlhat all reduce ave c_qlwlhat[7] c_qlwlhat[8] c_qlwlhat[9] c_qlwlhat[10] c_qlwlhat[11] c_qlwlhat[12] + +thermo_style custom step temp epair etotal c_avql[*] c_avwlhat[*] + +run 0 +WARNING: No fixes defined, atoms won't move (../verlet.cpp:52) +Neighbor list info ... + update every 1 steps, delay 5 steps, check yes + max neighbors/atom: 2000, page size: 100000 + master list distance cutoff = 3.3 + ghost atom cutoff = 3.3 + binsize = 1.65, bins = 3 3 3 + 2 neighbor lists, perpetual/occasional/extra = 1 1 0 + (1) pair lj/cut, perpetual + attributes: half, newton on + pair build: half/bin/atomonly/newton + stencil: half/bin/3d/newton + bin: standard + (2) compute orientorder/atom, occasional + attributes: full, newton on + pair build: full/bin/atomonly + stencil: full/bin/3d + bin: standard +Per MPI rank memory allocation (min/avg/max) = 3.722 | 3.722 | 3.722 Mbytes +Step Temp E_pair TotEng c_avql[1] c_avql[2] c_avql[3] c_avql[4] c_avql[5] c_avql[6] c_avwlhat[1] c_avwlhat[2] c_avwlhat[3] c_avwlhat[4] c_avwlhat[5] c_avwlhat[6] + 0 0 -7.8104466 -7.8104466 8.6382997e-17 0.036369648 0.51068823 0.42932247 0.19519122 0.40479919 0 0.15931737 0.013160601 0.058454791 -0.090130212 -0.049573639 +Loop time of 3.99351e-06 on 4 procs for 0 steps with 54 atoms + +87.6% CPU use with 4 MPI tasks x 1 OpenMP threads + +MPI task timing breakdown: +Section | min time | avg time | max time |%varavg| %total +--------------------------------------------------------------- +Pair | 0 | 0 | 0 | 0.0 | 0.00 +Neigh | 0 | 0 | 0 | 0.0 | 0.00 +Comm | 0 | 0 | 0 | 0.0 | 0.00 +Output | 0 | 0 | 0 | 0.0 | 0.00 +Modify | 0 | 0 | 0 | 0.0 | 0.00 +Other | | 3.994e-06 | | |100.00 + +Nlocal: 13.5 ave 15 max 12 min +Histogram: 2 0 0 0 0 0 0 0 0 2 +Nghost: 819.5 ave 821 max 818 min +Histogram: 2 0 0 0 0 0 0 0 0 2 +Neighs: 1134 ave 1260 max 1008 min +Histogram: 2 0 0 0 0 0 0 0 0 2 +FullNghs: 2268 ave 2520 max 2016 min +Histogram: 2 0 0 0 0 0 0 0 0 2 + +Total # of neighbors = 9072 +Ave neighs/atom = 168 +Neighbor list builds = 0 +Dangerous builds = 0 + +# check Q_l values + +print " " + +print "*******************************************************************" +******************************************************************* +print " " + +print "Comparison with reference values of Q_l " +Comparison with reference values of Q_l +print " [Table I in W. Mickel, S. C. Kapfer," + [Table I in W. Mickel, S. C. Kapfer, +print " G. E. Schroeder-Turkand, K. Mecke, " + G. E. Schroeder-Turkand, K. Mecke, +print " J. Chem. Phys. 138, 044501 (2013).]" + J. Chem. Phys. 138, 044501 (2013).] +print " " + + +variable q2ref equal 0.0 +variable q4ref equal 0.036 +variable q6ref equal 0.511 +variable q8ref equal 0.429 +variable q10ref equal 0.195 +variable q12ref equal 0.405 + +variable q2 equal c_avql[1] +variable q4 equal c_avql[2] +variable q6 equal c_avql[3] +variable q8 equal c_avql[4] +variable q10 equal c_avql[5] +variable q12 equal c_avql[6] + +print "q2 = $(v_q2:%10.6f) delta = $(v_q2-v_q2ref:%10.4f)" +q2 = 0.000000 delta = 0.0000 +print "q4 = $(v_q4:%10.6f) delta = $(v_q4-v_q4ref:%10.4f)" +q4 = 0.036370 delta = 0.0004 +print "q6 = $(v_q6:%10.6f) delta = $(v_q6-v_q6ref:%10.4f)" +q6 = 0.510688 delta = -0.0003 +print "q8 = $(v_q8:%10.6f) delta = $(v_q8-v_q8ref:%10.4f)" +q8 = 0.429322 delta = 0.0003 +print "q10 = $(v_q10:%10.6f) delta = $(v_q10-v_q10ref:%10.4f)" +q10 = 0.195191 delta = 0.0002 +print "q12 = $(v_q12:%10.6f) delta = $(v_q12-v_q12ref:%10.4f)" +q12 = 0.404799 delta = -0.0002 + +# check W_l_hat values + +print " " + +print "Comparison with reference values of W_l_hat" +Comparison with reference values of W_l_hat +print " [Table I in P. Steinhardt, D. Nelson, and M. Ronchetti, " + [Table I in P. Steinhardt, D. Nelson, and M. Ronchetti, +print " Phys. Rev. B 28, 784 (1983).]" + Phys. Rev. B 28, 784 (1983).] +print " " + + +variable w4hatref equal 0.159317 +variable w6hatref equal 0.013161 +variable w8hatref equal -0.058455 +variable w10hatref equal -0.090130 + +variable w4hat equal c_avwlhat[2] +variable w6hat equal c_avwlhat[3] +variable w8hat equal c_avwlhat[4] +variable w10hat equal c_avwlhat[5] + +print "w4hat = $(v_w4hat:%10.6f) delta = $(v_w4hat-v_w4hatref:%10.6f)" +w4hat = 0.159317 delta = 0.000000 +print "w6hat = $(v_w6hat:%10.6f) delta = $(v_w6hat-v_w6hatref:%10.6f)" +w6hat = 0.013161 delta = -0.000000 +print "w8hat = $(v_w8hat:%10.6f) delta = $(v_w8hat-v_w8hatref:%10.6f)" +w8hat = 0.058455 delta = 0.116910 +print "w10hat = $(v_w10hat:%10.6f) delta = $(v_w10hat-v_w10hatref:%10.6f)" +w10hat = -0.090130 delta = -0.000000 +print " " + +print "*******************************************************************" +******************************************************************* +print " " + +Total wall time: 0:00:00 diff --git a/examples/steinhardt/log.13Sept18.fcc.g++.1 b/examples/steinhardt/log.13Sept18.fcc.g++.1 new file mode 100644 index 0000000000..a34a33d7b1 --- /dev/null +++ b/examples/steinhardt/log.13Sept18.fcc.g++.1 @@ -0,0 +1,172 @@ +LAMMPS (7 Aug 2019) +OMP_NUM_THREADS environment is not set. Defaulting to 1 thread. (../comm.cpp:93) + using 1 OpenMP thread(s) per MPI task +# Steinhardt-Nelson bond orientational order parameters for FCC + +variable rcut equal 3.0 + +boundary p p p + +atom_style atomic +neighbor 0.3 bin +neigh_modify delay 5 + +# create geometry + +lattice fcc 1.0 +Lattice spacing in x,y,z = 1.5874 1.5874 1.5874 +region box block 0 3 0 3 0 3 +create_box 1 box +Created orthogonal box = (0 0 0) to (4.7622 4.7622 4.7622) + 1 by 1 by 1 MPI processor grid +create_atoms 1 box +Created 108 atoms + create_atoms CPU = 0.000289917 secs + +mass 1 1.0 + +# LJ potentials + +pair_style lj/cut ${rcut} +pair_style lj/cut 3 +pair_coeff * * 1.0 1.0 ${rcut} +pair_coeff * * 1.0 1.0 3 + +# 12 neighbors, perfect crystal + +compute qlwlhat all orientorder/atom wl/hat yes +compute avql all reduce ave c_qlwlhat[1] c_qlwlhat[2] c_qlwlhat[3] c_qlwlhat[4] c_qlwlhat[5] +compute avwlhat all reduce ave c_qlwlhat[6] c_qlwlhat[7] c_qlwlhat[8] c_qlwlhat[9] c_qlwlhat[10] + +thermo_style custom step temp epair etotal c_avql[*] c_avwlhat[*] + +run 0 +WARNING: No fixes defined, atoms won't move (../verlet.cpp:52) +Neighbor list info ... + update every 1 steps, delay 5 steps, check yes + max neighbors/atom: 2000, page size: 100000 + master list distance cutoff = 3.3 + ghost atom cutoff = 3.3 + binsize = 1.65, bins = 3 3 3 + 2 neighbor lists, perpetual/occasional/extra = 1 1 0 + (1) pair lj/cut, perpetual + attributes: half, newton on + pair build: half/bin/atomonly/newton + stencil: half/bin/3d/newton + bin: standard + (2) compute orientorder/atom, occasional + attributes: full, newton on + pair build: full/bin/atomonly + stencil: full/bin/3d + bin: standard +Per MPI rank memory allocation (min/avg/max) = 3.767 | 3.767 | 3.767 Mbytes +Step Temp E_pair TotEng c_avql[1] c_avql[2] c_avql[3] c_avql[4] c_avql[5] c_avwlhat[1] c_avwlhat[2] c_avwlhat[3] c_avwlhat[4] c_avwlhat[5] + 0 0 -8.1295091 -8.1295091 0.19094065 0.57452426 0.40391456 0.012857043 0.60008302 -0.15931737 -0.013160601 0.058454791 -0.090130212 0.087390889 +Loop time of 9.53674e-07 on 1 procs for 0 steps with 108 atoms + +209.7% CPU use with 1 MPI tasks x 1 OpenMP threads + +MPI task timing breakdown: +Section | min time | avg time | max time |%varavg| %total +--------------------------------------------------------------- +Pair | 0 | 0 | 0 | 0.0 | 0.00 +Neigh | 0 | 0 | 0 | 0.0 | 0.00 +Comm | 0 | 0 | 0 | 0.0 | 0.00 +Output | 0 | 0 | 0 | 0.0 | 0.00 +Modify | 0 | 0 | 0 | 0.0 | 0.00 +Other | | 9.537e-07 | | |100.00 + +Nlocal: 108 ave 108 max 108 min +Histogram: 1 0 0 0 0 0 0 0 0 0 +Nghost: 1580 ave 1580 max 1580 min +Histogram: 1 0 0 0 0 0 0 0 0 0 +Neighs: 7560 ave 7560 max 7560 min +Histogram: 1 0 0 0 0 0 0 0 0 0 +FullNghs: 15120 ave 15120 max 15120 min +Histogram: 1 0 0 0 0 0 0 0 0 0 + +Total # of neighbors = 15120 +Ave neighs/atom = 140 +Neighbor list builds = 0 +Dangerous builds = 0 + +# check Q_l values + +print " " + +print "*******************************************************************" +******************************************************************* +print " " + +print "Comparison with reference values of Q_l " +Comparison with reference values of Q_l +print " [Table I in W. Mickel, S. C. Kapfer," + [Table I in W. Mickel, S. C. Kapfer, +print " G. E. Schroeder-Turkand, K. Mecke, " + G. E. Schroeder-Turkand, K. Mecke, +print " J. Chem. Phys. 138, 044501 (2013).]" + J. Chem. Phys. 138, 044501 (2013).] +print " " + + +variable q4ref equal 0.190 +variable q6ref equal 0.575 +variable q8ref equal 0.404 +variable q10ref equal 0.013 +variable q12ref equal 0.600 + +variable q4 equal c_avql[1] +variable q6 equal c_avql[2] +variable q8 equal c_avql[3] +variable q10 equal c_avql[4] +variable q12 equal c_avql[5] + +print "q4 = $(v_q4:%10.6f) delta = $(v_q4-v_q4ref:%10.4f)" +q4 = 0.190941 delta = 0.0009 +print "q6 = $(v_q6:%10.6f) delta = $(v_q6-v_q6ref:%10.4f)" +q6 = 0.574524 delta = -0.0005 +print "q8 = $(v_q8:%10.6f) delta = $(v_q8-v_q8ref:%10.4f)" +q8 = 0.403915 delta = -0.0001 +print "q10 = $(v_q10:%10.6f) delta = $(v_q10-v_q10ref:%10.4f)" +q10 = 0.012857 delta = -0.0001 +print "q12 = $(v_q12:%10.6f) delta = $(v_q12-v_q12ref:%10.4f)" +q12 = 0.600083 delta = 0.0001 + +# check W_l_hat values + +print " " + +print "Comparison with reference values of W_l_hat" +Comparison with reference values of W_l_hat +print " [Table I in P. Steinhardt, D. Nelson, and M. Ronchetti, " + [Table I in P. Steinhardt, D. Nelson, and M. Ronchetti, +print " Phys. Rev. B 28, 784 (1983).]" + Phys. Rev. B 28, 784 (1983).] +print " " + + +variable w4hatref equal -0.159316 +variable w6hatref equal -0.013161 +variable w8hatref equal 0.058454 +variable w10hatref equal -0.090128 + +variable w4hat equal c_avwlhat[1] +variable w6hat equal c_avwlhat[2] +variable w8hat equal c_avwlhat[3] +variable w10hat equal c_avwlhat[4] + +print "w4hat = $(v_w4hat:%10.6f) delta = $(v_w4hat-v_w4hatref:%10.6f)" +w4hat = -0.159317 delta = -0.000001 +print "w6hat = $(v_w6hat:%10.6f) delta = $(v_w6hat-v_w6hatref:%10.6f)" +w6hat = -0.013161 delta = 0.000000 +print "w8hat = $(v_w8hat:%10.6f) delta = $(v_w8hat-v_w8hatref:%10.6f)" +w8hat = 0.058455 delta = 0.000001 +print "w10hat = $(v_w10hat:%10.6f) delta = $(v_w10hat-v_w10hatref:%10.6f)" +w10hat = -0.090130 delta = -0.000002 +print " " + +print "*******************************************************************" +******************************************************************* +print " " + +Total wall time: 0:00:00 diff --git a/examples/steinhardt/log.13Sept18.fcc.g++.4 b/examples/steinhardt/log.13Sept18.fcc.g++.4 new file mode 100644 index 0000000000..8573488be6 --- /dev/null +++ b/examples/steinhardt/log.13Sept18.fcc.g++.4 @@ -0,0 +1,172 @@ +LAMMPS (7 Aug 2019) +OMP_NUM_THREADS environment is not set. Defaulting to 1 thread. (../comm.cpp:93) + using 1 OpenMP thread(s) per MPI task +# Steinhardt-Nelson bond orientational order parameters for FCC + +variable rcut equal 3.0 + +boundary p p p + +atom_style atomic +neighbor 0.3 bin +neigh_modify delay 5 + +# create geometry + +lattice fcc 1.0 +Lattice spacing in x,y,z = 1.5874 1.5874 1.5874 +region box block 0 3 0 3 0 3 +create_box 1 box +Created orthogonal box = (0 0 0) to (4.7622 4.7622 4.7622) + 1 by 2 by 2 MPI processor grid +create_atoms 1 box +Created 108 atoms + create_atoms CPU = 0.000549078 secs + +mass 1 1.0 + +# LJ potentials + +pair_style lj/cut ${rcut} +pair_style lj/cut 3 +pair_coeff * * 1.0 1.0 ${rcut} +pair_coeff * * 1.0 1.0 3 + +# 12 neighbors, perfect crystal + +compute qlwlhat all orientorder/atom wl/hat yes +compute avql all reduce ave c_qlwlhat[1] c_qlwlhat[2] c_qlwlhat[3] c_qlwlhat[4] c_qlwlhat[5] +compute avwlhat all reduce ave c_qlwlhat[6] c_qlwlhat[7] c_qlwlhat[8] c_qlwlhat[9] c_qlwlhat[10] + +thermo_style custom step temp epair etotal c_avql[*] c_avwlhat[*] + +run 0 +WARNING: No fixes defined, atoms won't move (../verlet.cpp:52) +Neighbor list info ... + update every 1 steps, delay 5 steps, check yes + max neighbors/atom: 2000, page size: 100000 + master list distance cutoff = 3.3 + ghost atom cutoff = 3.3 + binsize = 1.65, bins = 3 3 3 + 2 neighbor lists, perpetual/occasional/extra = 1 1 0 + (1) pair lj/cut, perpetual + attributes: half, newton on + pair build: half/bin/atomonly/newton + stencil: half/bin/3d/newton + bin: standard + (2) compute orientorder/atom, occasional + attributes: full, newton on + pair build: full/bin/atomonly + stencil: full/bin/3d + bin: standard +Per MPI rank memory allocation (min/avg/max) = 3.737 | 3.737 | 3.737 Mbytes +Step Temp E_pair TotEng c_avql[1] c_avql[2] c_avql[3] c_avql[4] c_avql[5] c_avwlhat[1] c_avwlhat[2] c_avwlhat[3] c_avwlhat[4] c_avwlhat[5] + 0 0 -8.1295091 -8.1295091 0.19094065 0.57452426 0.40391456 0.012857043 0.60008302 -0.15931737 -0.013160601 0.058454791 -0.090130212 0.087390889 +Loop time of 3.09944e-06 on 4 procs for 0 steps with 108 atoms + +88.7% CPU use with 4 MPI tasks x 1 OpenMP threads + +MPI task timing breakdown: +Section | min time | avg time | max time |%varavg| %total +--------------------------------------------------------------- +Pair | 0 | 0 | 0 | 0.0 | 0.00 +Neigh | 0 | 0 | 0 | 0.0 | 0.00 +Comm | 0 | 0 | 0 | 0.0 | 0.00 +Output | 0 | 0 | 0 | 0.0 | 0.00 +Modify | 0 | 0 | 0 | 0.0 | 0.00 +Other | | 3.099e-06 | | |100.00 + +Nlocal: 27 ave 27 max 27 min +Histogram: 4 0 0 0 0 0 0 0 0 0 +Nghost: 1053 ave 1053 max 1053 min +Histogram: 4 0 0 0 0 0 0 0 0 0 +Neighs: 1890 ave 1890 max 1890 min +Histogram: 4 0 0 0 0 0 0 0 0 0 +FullNghs: 3780 ave 3780 max 3780 min +Histogram: 4 0 0 0 0 0 0 0 0 0 + +Total # of neighbors = 15120 +Ave neighs/atom = 140 +Neighbor list builds = 0 +Dangerous builds = 0 + +# check Q_l values + +print " " + +print "*******************************************************************" +******************************************************************* +print " " + +print "Comparison with reference values of Q_l " +Comparison with reference values of Q_l +print " [Table I in W. Mickel, S. C. Kapfer," + [Table I in W. Mickel, S. C. Kapfer, +print " G. E. Schroeder-Turkand, K. Mecke, " + G. E. Schroeder-Turkand, K. Mecke, +print " J. Chem. Phys. 138, 044501 (2013).]" + J. Chem. Phys. 138, 044501 (2013).] +print " " + + +variable q4ref equal 0.190 +variable q6ref equal 0.575 +variable q8ref equal 0.404 +variable q10ref equal 0.013 +variable q12ref equal 0.600 + +variable q4 equal c_avql[1] +variable q6 equal c_avql[2] +variable q8 equal c_avql[3] +variable q10 equal c_avql[4] +variable q12 equal c_avql[5] + +print "q4 = $(v_q4:%10.6f) delta = $(v_q4-v_q4ref:%10.4f)" +q4 = 0.190941 delta = 0.0009 +print "q6 = $(v_q6:%10.6f) delta = $(v_q6-v_q6ref:%10.4f)" +q6 = 0.574524 delta = -0.0005 +print "q8 = $(v_q8:%10.6f) delta = $(v_q8-v_q8ref:%10.4f)" +q8 = 0.403915 delta = -0.0001 +print "q10 = $(v_q10:%10.6f) delta = $(v_q10-v_q10ref:%10.4f)" +q10 = 0.012857 delta = -0.0001 +print "q12 = $(v_q12:%10.6f) delta = $(v_q12-v_q12ref:%10.4f)" +q12 = 0.600083 delta = 0.0001 + +# check W_l_hat values + +print " " + +print "Comparison with reference values of W_l_hat" +Comparison with reference values of W_l_hat +print " [Table I in P. Steinhardt, D. Nelson, and M. Ronchetti, " + [Table I in P. Steinhardt, D. Nelson, and M. Ronchetti, +print " Phys. Rev. B 28, 784 (1983).]" + Phys. Rev. B 28, 784 (1983).] +print " " + + +variable w4hatref equal -0.159316 +variable w6hatref equal -0.013161 +variable w8hatref equal 0.058454 +variable w10hatref equal -0.090128 + +variable w4hat equal c_avwlhat[1] +variable w6hat equal c_avwlhat[2] +variable w8hat equal c_avwlhat[3] +variable w10hat equal c_avwlhat[4] + +print "w4hat = $(v_w4hat:%10.6f) delta = $(v_w4hat-v_w4hatref:%10.6f)" +w4hat = -0.159317 delta = -0.000001 +print "w6hat = $(v_w6hat:%10.6f) delta = $(v_w6hat-v_w6hatref:%10.6f)" +w6hat = -0.013161 delta = 0.000000 +print "w8hat = $(v_w8hat:%10.6f) delta = $(v_w8hat-v_w8hatref:%10.6f)" +w8hat = 0.058455 delta = 0.000001 +print "w10hat = $(v_w10hat:%10.6f) delta = $(v_w10hat-v_w10hatref:%10.6f)" +w10hat = -0.090130 delta = -0.000002 +print " " + +print "*******************************************************************" +******************************************************************* +print " " + +Total wall time: 0:00:00 diff --git a/examples/steinhardt/log.13Sept18.icos.g++.1 b/examples/steinhardt/log.13Sept18.icos.g++.1 new file mode 100644 index 0000000000..f42fd346db --- /dev/null +++ b/examples/steinhardt/log.13Sept18.icos.g++.1 @@ -0,0 +1,235 @@ +LAMMPS (7 Aug 2019) +OMP_NUM_THREADS environment is not set. Defaulting to 1 thread. (../comm.cpp:93) + using 1 OpenMP thread(s) per MPI task +# Steinhardt-Nelson bond orientational order parameters for icosahedral cluster +# W_6_hat is sensitive to icosohedral order + +variable rcut equal 1.2 # a bit bigger than LJ Rmin +variable rcutred equal 0.75 # a bit bigger than 1/sqrt(2) + +# create a perfect fcc crystallite + +atom_style atomic +boundary s s s +lattice fcc 1.0 # neighbors at LJ Rmin +Lattice spacing in x,y,z = 1.5874 1.5874 1.5874 +region box block 0 2 0 2 0 2 +create_box 1 box +Created orthogonal box = (0 0 0) to (3.1748 3.1748 3.1748) + 1 by 1 by 1 MPI processor grid +create_atoms 1 box +Created 63 atoms + create_atoms CPU = 0.000341177 secs +mass 1 1.0 + +region centralatom sphere 1 1 1 0.0 side in +group centralatom region centralatom +1 atoms in group centralatom + +region mysphere sphere 1 1 1 ${rcutred} side out +region mysphere sphere 1 1 1 0.75 side out +delete_atoms region mysphere +Deleted 50 atoms, new total = 13 + +# LJ potential + +pair_style lj/cut 100.0 +pair_coeff * * 1.0 1.0 100.0 + +# define output for central atom + +compute qlwlhat all orientorder/atom wl/hat yes cutoff ${rcut} nnn NULL +compute qlwlhat all orientorder/atom wl/hat yes cutoff 1.2 nnn NULL +compute avql centralatom reduce ave c_qlwlhat[1] c_qlwlhat[2] c_qlwlhat[3] c_qlwlhat[4] c_qlwlhat[5] +compute avwlhat centralatom reduce ave c_qlwlhat[6] c_qlwlhat[7] c_qlwlhat[8] c_qlwlhat[9] c_qlwlhat[10] +variable q6 equal c_avql[2] +variable w6hat equal c_avwlhat[2] + +compute mype all pe/atom +compute centralatompe centralatom reduce ave c_mype + +# gently equilibrate the crystallite + +velocity all create 0.001 482748 +fix 1 all nve +neighbor 0.3 bin +neigh_modify every 1 check no delay 0 +timestep 0.003 +thermo_style custom step temp epair etotal c_centralatompe v_q6 v_w6hat +thermo 10 + +run 10 +Neighbor list info ... + update every 1 steps, delay 0 steps, check no + max neighbors/atom: 2000, page size: 100000 + master list distance cutoff = 100.3 + ghost atom cutoff = 100.3 + binsize = 50.15, bins = 1 1 1 + 2 neighbor lists, perpetual/occasional/extra = 1 1 0 + (1) pair lj/cut, perpetual + attributes: half, newton on + pair build: half/bin/atomonly/newton + stencil: half/bin/3d/newton + bin: standard + (2) compute orientorder/atom, occasional + attributes: full, newton on + pair build: full/bin/atomonly + stencil: full/bin/3d + bin: standard +Per MPI rank memory allocation (min/avg/max) = 60.87 | 60.87 | 60.87 Mbytes +Step Temp E_pair TotEng c_centralatompe v_q6 v_w6hat + 0 0.001 -3.134107 -3.1327224 -6 0.57452426 -0.013160601 + 10 0.0021974351 -3.1357656 -3.132723 -5.9995795 0.57450739 -0.013160482 +Loop time of 0.210631 on 1 procs for 10 steps with 13 atoms + +Performance: 12305.887 tau/day, 47.476 timesteps/s +99.5% CPU use with 1 MPI tasks x 1 OpenMP threads + +MPI task timing breakdown: +Section | min time | avg time | max time |%varavg| %total +--------------------------------------------------------------- +Pair | 1.6928e-05 | 1.6928e-05 | 1.6928e-05 | 0.0 | 0.01 +Neigh | 0.13335 | 0.13335 | 0.13335 | 0.0 | 63.31 +Comm | 1.4782e-05 | 1.4782e-05 | 1.4782e-05 | 0.0 | 0.01 +Output | 0.033121 | 0.033121 | 0.033121 | 0.0 | 15.72 +Modify | 2.8849e-05 | 2.8849e-05 | 2.8849e-05 | 0.0 | 0.01 +Other | | 0.0441 | | | 20.94 + +Nlocal: 13 ave 13 max 13 min +Histogram: 1 0 0 0 0 0 0 0 0 0 +Nghost: 0 ave 0 max 0 min +Histogram: 1 0 0 0 0 0 0 0 0 0 +Neighs: 78 ave 78 max 78 min +Histogram: 1 0 0 0 0 0 0 0 0 0 +FullNghs: 156 ave 156 max 156 min +Histogram: 1 0 0 0 0 0 0 0 0 0 + +Total # of neighbors = 156 +Ave neighs/atom = 12 +Neighbor list builds = 10 +Dangerous builds not checked + +# quench to icosehedral cluster + +minimize 1.0e-10 1.0e-6 100 1000 +WARNING: Using 'neigh_modify every 1 delay 0 check yes' setting during minimization (../min.cpp:168) +Per MPI rank memory allocation (min/avg/max) = 113 | 113 | 113 Mbytes +Step Temp E_pair TotEng c_centralatompe v_q6 v_w6hat + 10 0.0021974351 -3.1357656 -3.132723 -5.9995795 0.57450739 -0.013160482 + 20 0.0021974351 -3.1449631 -3.1419205 -5.9766502 0.57452794 -0.01317299 + 30 0.0021974351 -3.377441 -3.3743984 -5.6930377 0.65479437 -0.16922776 + 40 0.0021974351 -3.4096335 -3.4065909 -5.6325443 0.66328926 -0.16975382 + 49 0.0021974351 -3.409754 -3.4067114 -5.6323333 0.66332496 -0.16975389 +Loop time of 0.0821278 on 1 procs for 39 steps with 13 atoms + +99.9% CPU use with 1 MPI tasks x 1 OpenMP threads + +Minimization stats: + Stopping criterion = energy tolerance + Energy initial, next-to-last, final = + -3.13576562743 -3.40975395481 -3.40975395503 + Force two-norm initial, final = 6.44841 0.000945077 + Force max component initial, final = 1.43234 0.000348946 + Final line search alpha, max atom move = 1 0.000348946 + Iterations, force evaluations = 39 94 + +MPI task timing breakdown: +Section | min time | avg time | max time |%varavg| %total +--------------------------------------------------------------- +Pair | 0.00020051 | 0.00020051 | 0.00020051 | 0.0 | 0.24 +Neigh | 0.024762 | 0.024762 | 0.024762 | 0.0 | 30.15 +Comm | 1.2398e-05 | 1.2398e-05 | 1.2398e-05 | 0.0 | 0.02 +Output | 0.048263 | 0.048263 | 0.048263 | 0.0 | 58.77 +Modify | 0 | 0 | 0 | 0.0 | 0.00 +Other | | 0.00889 | | | 10.82 + +Nlocal: 13 ave 13 max 13 min +Histogram: 1 0 0 0 0 0 0 0 0 0 +Nghost: 0 ave 0 max 0 min +Histogram: 1 0 0 0 0 0 0 0 0 0 +Neighs: 78 ave 78 max 78 min +Histogram: 1 0 0 0 0 0 0 0 0 0 +FullNghs: 156 ave 156 max 156 min +Histogram: 1 0 0 0 0 0 0 0 0 0 + +Total # of neighbors = 156 +Ave neighs/atom = 12 +Neighbor list builds = 3 +Dangerous builds not checked + +# check Q_l values + +print " " + +print "*******************************************************************" +******************************************************************* +print " " + +print "Comparison with reference values of Q_l " +Comparison with reference values of Q_l +print " [Table I in W. Mickel, S. C. Kapfer," + [Table I in W. Mickel, S. C. Kapfer, +print " G. E. Schroeder-Turkand, K. Mecke, " + G. E. Schroeder-Turkand, K. Mecke, +print " J. Chem. Phys. 138, 044501 (2013).]" + J. Chem. Phys. 138, 044501 (2013).] +print " " + + +variable q4ref equal 0.0 +variable q6ref equal 0.663 +variable q8ref equal 0.0 +variable q10ref equal 0.363 +variable q12ref equal 0.585 + +variable q4 equal c_avql[1] +variable q6 equal c_avql[2] +variable q8 equal c_avql[3] +variable q10 equal c_avql[4] +variable q12 equal c_avql[5] + +print "q4 = $(v_q4:%10.6f) delta = $(v_q4-v_q4ref:%10.4f)" +q4 = 0.000002 delta = 0.0000 +print "q6 = $(v_q6:%10.6f) delta = $(v_q6-v_q6ref:%10.4f)" +q6 = 0.663325 delta = 0.0003 +print "q8 = $(v_q8:%10.6f) delta = $(v_q8-v_q8ref:%10.4f)" +q8 = 0.000003 delta = 0.0000 +print "q10 = $(v_q10:%10.6f) delta = $(v_q10-v_q10ref:%10.4f)" +q10 = 0.362951 delta = -0.0000 +print "q12 = $(v_q12:%10.6f) delta = $(v_q12-v_q12ref:%10.4f)" +q12 = 0.585423 delta = 0.0004 + +# check W_l_hat values + +print " " + +print "Comparison with reference values of W_l_hat" +Comparison with reference values of W_l_hat +print " [Table I in P. Steinhardt, D. Nelson, and M. Ronchetti, " + [Table I in P. Steinhardt, D. Nelson, and M. Ronchetti, +print " Phys. Rev. B 28, 784 (1983).]" + Phys. Rev. B 28, 784 (1983).] +print " " + + +variable w6hatref equal -0.169754 +variable w10hatref equal -0.093967 + +variable w4hat equal c_avwlhat[1] +variable w6hat equal c_avwlhat[2] +variable w8hat equal c_avwlhat[3] +variable w10hat equal c_avwlhat[4] +variable w12hat equal c_avwlhat[5] + +print "w6hat = $(v_w6hat:%10.6f) delta = $(v_w6hat-v_w6hatref:%10.6f)" +w6hat = -0.169754 delta = 0.000000 +print "w10hat = $(v_w10hat:%10.6f) delta = $(v_w10hat-v_w10hatref:%10.6f)" +w10hat = -0.093968 delta = -0.000001 +print " " + +print "*******************************************************************" +******************************************************************* +print " " + + +Total wall time: 0:00:00 diff --git a/examples/steinhardt/log.13Sept18.icos.g++.4 b/examples/steinhardt/log.13Sept18.icos.g++.4 new file mode 100644 index 0000000000..d64e179c8f --- /dev/null +++ b/examples/steinhardt/log.13Sept18.icos.g++.4 @@ -0,0 +1,235 @@ +LAMMPS (7 Aug 2019) +OMP_NUM_THREADS environment is not set. Defaulting to 1 thread. (../comm.cpp:93) + using 1 OpenMP thread(s) per MPI task +# Steinhardt-Nelson bond orientational order parameters for icosahedral cluster +# W_6_hat is sensitive to icosohedral order + +variable rcut equal 1.2 # a bit bigger than LJ Rmin +variable rcutred equal 0.75 # a bit bigger than 1/sqrt(2) + +# create a perfect fcc crystallite + +atom_style atomic +boundary s s s +lattice fcc 1.0 # neighbors at LJ Rmin +Lattice spacing in x,y,z = 1.5874 1.5874 1.5874 +region box block 0 2 0 2 0 2 +create_box 1 box +Created orthogonal box = (0 0 0) to (3.1748 3.1748 3.1748) + 1 by 2 by 2 MPI processor grid +create_atoms 1 box +Created 63 atoms + create_atoms CPU = 0.000592947 secs +mass 1 1.0 + +region centralatom sphere 1 1 1 0.0 side in +group centralatom region centralatom +1 atoms in group centralatom + +region mysphere sphere 1 1 1 ${rcutred} side out +region mysphere sphere 1 1 1 0.75 side out +delete_atoms region mysphere +Deleted 50 atoms, new total = 13 + +# LJ potential + +pair_style lj/cut 100.0 +pair_coeff * * 1.0 1.0 100.0 + +# define output for central atom + +compute qlwlhat all orientorder/atom wl/hat yes cutoff ${rcut} nnn NULL +compute qlwlhat all orientorder/atom wl/hat yes cutoff 1.2 nnn NULL +compute avql centralatom reduce ave c_qlwlhat[1] c_qlwlhat[2] c_qlwlhat[3] c_qlwlhat[4] c_qlwlhat[5] +compute avwlhat centralatom reduce ave c_qlwlhat[6] c_qlwlhat[7] c_qlwlhat[8] c_qlwlhat[9] c_qlwlhat[10] +variable q6 equal c_avql[2] +variable w6hat equal c_avwlhat[2] + +compute mype all pe/atom +compute centralatompe centralatom reduce ave c_mype + +# gently equilibrate the crystallite + +velocity all create 0.001 482748 +fix 1 all nve +neighbor 0.3 bin +neigh_modify every 1 check no delay 0 +timestep 0.003 +thermo_style custom step temp epair etotal c_centralatompe v_q6 v_w6hat +thermo 10 + +run 10 +Neighbor list info ... + update every 1 steps, delay 0 steps, check no + max neighbors/atom: 2000, page size: 100000 + master list distance cutoff = 100.3 + ghost atom cutoff = 100.3 + binsize = 50.15, bins = 1 1 1 + 2 neighbor lists, perpetual/occasional/extra = 1 1 0 + (1) pair lj/cut, perpetual + attributes: half, newton on + pair build: half/bin/atomonly/newton + stencil: half/bin/3d/newton + bin: standard + (2) compute orientorder/atom, occasional + attributes: full, newton on + pair build: full/bin/atomonly + stencil: full/bin/3d + bin: standard +Per MPI rank memory allocation (min/avg/max) = 60.76 | 60.76 | 60.76 Mbytes +Step Temp E_pair TotEng c_centralatompe v_q6 v_w6hat + 0 0.001 -3.134107 -3.1327224 -6 0.57452426 -0.013160601 + 10 0.0021821015 -3.1357444 -3.132723 -5.9994885 0.57450756 -0.013160431 +Loop time of 0.15387 on 4 procs for 10 steps with 13 atoms + +Performance: 16845.410 tau/day, 64.990 timesteps/s +99.2% CPU use with 4 MPI tasks x 1 OpenMP threads + +MPI task timing breakdown: +Section | min time | avg time | max time |%varavg| %total +--------------------------------------------------------------- +Pair | 9.7752e-06 | 1.7285e-05 | 2.9087e-05 | 0.0 | 0.01 +Neigh | 0.055218 | 0.065482 | 0.073829 | 2.9 | 42.56 +Comm | 0.0061202 | 0.018279 | 0.028283 | 6.3 | 11.88 +Output | 0.020282 | 0.020287 | 0.020298 | 0.0 | 13.18 +Modify | 2.7895e-05 | 2.8968e-05 | 2.9802e-05 | 0.0 | 0.02 +Other | | 0.04978 | | | 32.35 + +Nlocal: 3.25 ave 4 max 2 min +Histogram: 1 0 0 0 0 1 0 0 0 2 +Nghost: 9.75 ave 11 max 9 min +Histogram: 2 0 0 0 0 1 0 0 0 1 +Neighs: 19.5 ave 35 max 7 min +Histogram: 2 0 0 0 0 0 0 1 0 1 +FullNghs: 39 ave 48 max 24 min +Histogram: 1 0 0 0 0 1 0 0 0 2 + +Total # of neighbors = 156 +Ave neighs/atom = 12 +Neighbor list builds = 10 +Dangerous builds not checked + +# quench to icosehedral cluster + +minimize 1.0e-10 1.0e-6 100 1000 +WARNING: Using 'neigh_modify every 1 delay 0 check yes' setting during minimization (../min.cpp:168) +Per MPI rank memory allocation (min/avg/max) = 112.9 | 112.9 | 112.9 Mbytes +Step Temp E_pair TotEng c_centralatompe v_q6 v_w6hat + 10 0.0021821015 -3.1357444 -3.132723 -5.9994885 0.57450756 -0.013160431 + 20 0.0021821015 -3.1449613 -3.1419399 -5.9764731 0.57452454 -0.01316152 + 30 0.0021821015 -3.3366586 -3.3336372 -5.7717004 0.63679987 -0.16411081 + 40 0.0021821015 -3.4097262 -3.4067048 -5.6321229 0.66331761 -0.16975374 + 49 0.0021821015 -3.409754 -3.4067326 -5.6323347 0.66332496 -0.16975389 +Loop time of 0.0932837 on 4 procs for 39 steps with 13 atoms + +97.2% CPU use with 4 MPI tasks x 1 OpenMP threads + +Minimization stats: + Stopping criterion = energy tolerance + Energy initial, next-to-last, final = + -3.13574438249 -3.40975395519 -3.40975395529 + Force two-norm initial, final = 6.46606 0.000429142 + Force max component initial, final = 1.45519 0.000196446 + Final line search alpha, max atom move = 1 0.000196446 + Iterations, force evaluations = 39 98 + +MPI task timing breakdown: +Section | min time | avg time | max time |%varavg| %total +--------------------------------------------------------------- +Pair | 5.4121e-05 | 9.0897e-05 | 0.00014281 | 0.0 | 0.10 +Neigh | 0.019662 | 0.02379 | 0.03176 | 3.0 | 25.50 +Comm | 0.0072601 | 0.014304 | 0.019575 | 3.8 | 15.33 +Output | 0.033646 | 0.033654 | 0.03368 | 0.0 | 36.08 +Modify | 0 | 0 | 0 | 0.0 | 0.00 +Other | | 0.02144 | | | 22.99 + +Nlocal: 3.25 ave 6 max 1 min +Histogram: 1 0 0 0 2 0 0 0 0 1 +Nghost: 9.75 ave 12 max 7 min +Histogram: 1 0 0 0 0 0 2 0 0 1 +Neighs: 19.5 ave 49 max 1 min +Histogram: 2 0 0 0 1 0 0 0 0 1 +FullNghs: 39 ave 72 max 12 min +Histogram: 1 0 0 0 2 0 0 0 0 1 + +Total # of neighbors = 156 +Ave neighs/atom = 12 +Neighbor list builds = 5 +Dangerous builds not checked + +# check Q_l values + +print " " + +print "*******************************************************************" +******************************************************************* +print " " + +print "Comparison with reference values of Q_l " +Comparison with reference values of Q_l +print " [Table I in W. Mickel, S. C. Kapfer," + [Table I in W. Mickel, S. C. Kapfer, +print " G. E. Schroeder-Turkand, K. Mecke, " + G. E. Schroeder-Turkand, K. Mecke, +print " J. Chem. Phys. 138, 044501 (2013).]" + J. Chem. Phys. 138, 044501 (2013).] +print " " + + +variable q4ref equal 0.0 +variable q6ref equal 0.663 +variable q8ref equal 0.0 +variable q10ref equal 0.363 +variable q12ref equal 0.585 + +variable q4 equal c_avql[1] +variable q6 equal c_avql[2] +variable q8 equal c_avql[3] +variable q10 equal c_avql[4] +variable q12 equal c_avql[5] + +print "q4 = $(v_q4:%10.6f) delta = $(v_q4-v_q4ref:%10.4f)" +q4 = 0.000001 delta = 0.0000 +print "q6 = $(v_q6:%10.6f) delta = $(v_q6-v_q6ref:%10.4f)" +q6 = 0.663325 delta = 0.0003 +print "q8 = $(v_q8:%10.6f) delta = $(v_q8-v_q8ref:%10.4f)" +q8 = 0.000002 delta = 0.0000 +print "q10 = $(v_q10:%10.6f) delta = $(v_q10-v_q10ref:%10.4f)" +q10 = 0.362951 delta = -0.0000 +print "q12 = $(v_q12:%10.6f) delta = $(v_q12-v_q12ref:%10.4f)" +q12 = 0.585423 delta = 0.0004 + +# check W_l_hat values + +print " " + +print "Comparison with reference values of W_l_hat" +Comparison with reference values of W_l_hat +print " [Table I in P. Steinhardt, D. Nelson, and M. Ronchetti, " + [Table I in P. Steinhardt, D. Nelson, and M. Ronchetti, +print " Phys. Rev. B 28, 784 (1983).]" + Phys. Rev. B 28, 784 (1983).] +print " " + + +variable w6hatref equal -0.169754 +variable w10hatref equal -0.093967 + +variable w4hat equal c_avwlhat[1] +variable w6hat equal c_avwlhat[2] +variable w8hat equal c_avwlhat[3] +variable w10hat equal c_avwlhat[4] +variable w12hat equal c_avwlhat[5] + +print "w6hat = $(v_w6hat:%10.6f) delta = $(v_w6hat-v_w6hatref:%10.6f)" +w6hat = -0.169754 delta = 0.000000 +print "w10hat = $(v_w10hat:%10.6f) delta = $(v_w10hat-v_w10hatref:%10.6f)" +w10hat = -0.093968 delta = -0.000001 +print " " + +print "*******************************************************************" +******************************************************************* +print " " + + +Total wall time: 0:00:00 From 09b67946312d3b5be87a7b9844731fb6d7b15916 Mon Sep 17 00:00:00 2001 From: charlie sievers Date: Fri, 13 Sep 2019 23:25:48 -0700 Subject: [PATCH 140/192] Updated fix langevin errors and warnings as well as associated doc files. Updated fix langevin kokkos errors and warnings as well as associated doc files --- doc/src/Errors_messages.txt | 16 + doc/src/Errors_warnings.txt | 4 + doc/src/fix_langevin.txt | 9 +- fix_langevin_kokkos.cpp | 916 ++++++++++++++++++++++++++++++++++++ fix_langevin_kokkos.h | 293 ++++++++++++ src/fix_langevin.cpp | 31 +- src/fix_langevin.h | 2 +- 7 files changed, 1249 insertions(+), 22 deletions(-) create mode 100644 fix_langevin_kokkos.cpp create mode 100644 fix_langevin_kokkos.h diff --git a/doc/src/Errors_messages.txt b/doc/src/Errors_messages.txt index c131b10ec6..33593d4d53 100644 --- a/doc/src/Errors_messages.txt +++ b/doc/src/Errors_messages.txt @@ -4791,6 +4791,22 @@ Self-explanatory. :dd This fix option cannot be used with point particles. :dd +{Fix langevin gjf and respa are not compatible} :dt + +Self-explanatory. :dd + +{Fix langevin gjf cannot have period equal to dt/2} :dt + +If the period is equal to dt/2 then division by zero will happen. :dd + +{Fix langevin gjf should come before fix nve} :dt + +Self-explanatory. :dd + +{Fix langevin gjf with tbias is not yet implemented with kokkos} :dt + +This option is not yet available. :dd + {Fix langevin omega is not yet implemented with kokkos} :dt This option is not yet available. :dd diff --git a/doc/src/Errors_warnings.txt b/doc/src/Errors_warnings.txt index 9f346ba8c1..fbd857f162 100644 --- a/doc/src/Errors_warnings.txt +++ b/doc/src/Errors_warnings.txt @@ -248,6 +248,10 @@ included one or more of the following: kspace, triclinic, a hybrid pair style, an eam pair style, or no "single" function for the pair style. :dd +{Fix langevin gjf using random gaussians is not implemented with kokkos} :dt + +This will most likely cause errors in kinetic fluctuations. + {Fix property/atom mol or charge w/out ghost communication} :dt A model typically needs these properties defined for ghost atoms. :dd diff --git a/doc/src/fix_langevin.txt b/doc/src/fix_langevin.txt index 382c2360d9..203ff2298c 100644 --- a/doc/src/fix_langevin.txt +++ b/doc/src/fix_langevin.txt @@ -351,13 +351,10 @@ types, tally = no, zero = no, gjf = no. :link(Gronbech-Jensen) [(Gronbech-Jensen)] Gronbech-Jensen and Farago, Mol Phys, 111, 983 -(2013); Gronbech-Jensen, Hayre, and Farago, Comp Phys Comm, -185, 524 (2014) +(2013); Gronbech-Jensen, Hayre, and Farago, Comp Phys Comm, 185, 524 (2014) :link(2Gronbech-Jensen) -[(Gronbech-Jensen)] Gronbech Jensen and Gronbech-Jensen, Mol Phys, 117, 2511 -(2019) +[(Gronbech-Jensen)] Gronbech Jensen and Gronbech-Jensen, Mol Phys, 117, 2511 (2019) :link(1Gronbech-Jensen) -[(Gronbech-Jensen)] Gronbech-Jensen, Mol Phys (2019); -https://doi.org/10.1080/00268976.2019.1662506 +[(Gronbech-Jensen)] Gronbech-Jensen, Mol Phys (2019); https://doi.org/10.1080/00268976.2019.1662506 diff --git a/fix_langevin_kokkos.cpp b/fix_langevin_kokkos.cpp new file mode 100644 index 0000000000..0618631581 --- /dev/null +++ b/fix_langevin_kokkos.cpp @@ -0,0 +1,916 @@ +/* ---------------------------------------------------------------------- + LAMMPS - Large-scale Atomic/Molecular Massively Parallel Simulator + http://lammps.sandia.gov, Sandia National Laboratories + Steve Plimpton, sjplimp@sandia.gov + + Copyright (2003) Sandia Corporation. Under the terms of Contract + DE-AC04-94AL85000 with Sandia Corporation, the U.S. Government retains + certain rights in this software. This software is distributed under + the GNU General Public License. + + See the README file in the top-level LAMMPS directory. + ------------------------------------------------------------------------- */ + +#include "fix_langevin_kokkos.h" +#include +#include "atom_masks.h" +#include "atom_kokkos.h" +#include "force.h" +#include "group.h" +#include "update.h" +#include "error.h" +#include "memory_kokkos.h" +#include "compute.h" +#include "comm.h" +#include "modify.h" +#include "input.h" +#include "region.h" +#include "variable.h" + +using namespace LAMMPS_NS; +using namespace FixConst; + +enum{NOBIAS,BIAS}; +enum{CONSTANT,EQUAL,ATOM}; +#define SINERTIA 0.4 // moment of inertia prefactor for sphere +#define EINERTIA 0.2 // moment of inertia prefactor for ellipsoid + +/* ---------------------------------------------------------------------- */ + +template +FixLangevinKokkos::FixLangevinKokkos(LAMMPS *lmp, int narg, char **arg) : + FixLangevin(lmp, narg, arg),rand_pool(seed + comm->me) +{ + kokkosable = 1; + atomKK = (AtomKokkos *) atom; + int ntypes = atomKK->ntypes; + + // allocate per-type arrays for force prefactors + memoryKK->create_kokkos(k_gfactor1,gfactor1,ntypes+1,"langevin:gfactor1"); + memoryKK->create_kokkos(k_gfactor2,gfactor2,ntypes+1,"langevin:gfactor2"); + memoryKK->create_kokkos(k_ratio,ratio,ntypes+1,"langevin:ratio"); + d_gfactor1 = k_gfactor1.template view(); + h_gfactor1 = k_gfactor1.template view(); + d_gfactor2 = k_gfactor2.template view(); + h_gfactor2 = k_gfactor2.template view(); + d_ratio = k_ratio.template view(); + h_ratio = k_ratio.template view(); + + // optional args + for (int i = 1; i <= ntypes; i++) ratio[i] = 1.0; + k_ratio.template modify(); + + if(gjfflag){ + grow_arrays(atomKK->nmax); + atom->add_callback(0); + // initialize franprev to zero + for (int i = 0; i < atomKK->nlocal; i++) { + franprev[i][0] = 0.0; + franprev[i][1] = 0.0; + franprev[i][2] = 0.0; + lv[i][0] = 0.0; + lv[i][1] = 0.0; + lv[i][2] = 0.0; + } + k_franprev.template modify(); + k_lv.template modify(); + } + if(zeroflag){ + k_fsumall = tdual_double_1d_3n("langevin:fsumall"); + h_fsumall = k_fsumall.template view(); + d_fsumall = k_fsumall.template view(); + } + + execution_space = ExecutionSpaceFromDevice::space; + datamask_read = V_MASK | F_MASK | MASK_MASK | RMASS_MASK | TYPE_MASK; + datamask_modify = F_MASK; + +} + +/* ---------------------------------------------------------------------- */ + +template +FixLangevinKokkos::~FixLangevinKokkos() +{ + memoryKK->destroy_kokkos(k_gfactor1,gfactor1); + memoryKK->destroy_kokkos(k_gfactor2,gfactor2); + memoryKK->destroy_kokkos(k_ratio,ratio); + memoryKK->destroy_kokkos(k_flangevin,flangevin); + if(gjfflag) memoryKK->destroy_kokkos(k_franprev,franprev); + if(gjfflag) memoryKK->destroy_kokkos(k_lv,lv); + memoryKK->destroy_kokkos(k_tforce,tforce); +} + +/* ---------------------------------------------------------------------- */ + +template +void FixLangevinKokkos::init() +{ + FixLangevin::init(); + if(oflag) + error->all(FLERR,"Fix langevin omega is not yet implemented with kokkos"); + if(ascale) + error->all(FLERR,"Fix langevin angmom is not yet implemented with kokkos"); + if(gjfflag && tbiasflag) + error->all(FLERR,"Fix langevin gjf + tbias is not yet implemented with kokkos"); + if(gjfflag && tbiasflag) + error->warning(FLERR,"Fix langevin gjf + kokkos is not implemented with random gaussians"); + + // prefactors are modified in the init + k_gfactor1.template modify(); + k_gfactor2.template modify(); +} + +/* ---------------------------------------------------------------------- */ + +template +void FixLangevinKokkos::grow_arrays(int nmax) +{ + memoryKK->grow_kokkos(k_franprev,franprev,nmax,3,"langevin:franprev"); + d_franprev = k_franprev.template view(); + h_franprev = k_franprev.template view(); + memoryKK->grow_kokkos(k_lv,lv,nmax,3,"langevin:lv"); + d_lv = k_lv.template view(); + h_lv = k_lv.template view(); +} + +/* ---------------------------------------------------------------------- */ + +template +void FixLangevinKokkos::initial_integrate(int vflag) +{ + atomKK->sync(execution_space,datamask_read); + atomKK->modified(execution_space,datamask_modify); + + v = atomKK->k_v.view(); + f = atomKK->k_f.view(); + int nlocal = atomKK->nlocal; + if (igroup == atomKK->firstgroup) nlocal = atomKK->nfirst; + + FixLangevinKokkosInitialIntegrateFunctor functor(this); + Kokkos::parallel_for(nlocal,functor); +} + +template +KOKKOS_INLINE_FUNCTION +void FixLangevinKokkos::initial_integrate_item(int i) const +{ + if (mask[i] & groupbit) { + f(i,0) /= gjfa; + f(i,1) /= gjfa; + f(i,2) /= gjfa; + v(i,0) = d_lv(i,0); + v(i,1) = d_lv(i,1); + v(i,2) = d_lv(i,2); + } +} + +/* ---------------------------------------------------------------------- */ + +template +void FixLangevinKokkos::post_force(int vflag) +{ + // sync the device views which might have been modified on host + atomKK->sync(execution_space,datamask_read); + rmass = atomKK->k_rmass.view(); + f = atomKK->k_f.template view(); + v = atomKK->k_v.template view(); + type = atomKK->k_type.template view(); + mask = atomKK->k_mask.template view(); + + k_gfactor1.template sync(); + k_gfactor2.template sync(); + k_ratio.template sync(); + if(gjfflag) k_franprev.template sync(); + if(gjfflag) k_lv.template sync(); + + boltz = force->boltz; + dt = update->dt; + mvv2e = force->mvv2e; + ftm2v = force->ftm2v; + fran_prop_const = sqrt(24.0*boltz/t_period/dt/mvv2e); + + compute_target(); // modifies tforce vector, hence sync here + k_tforce.template sync(); + + double fsum[3],fsumall[3]; + bigint count; + int nlocal = atomKK->nlocal; + + if (zeroflag) { + fsum[0] = fsum[1] = fsum[2] = 0.0; + count = group->count(igroup); + if (count == 0) + error->all(FLERR,"Cannot zero Langevin force of 0 atoms"); + } + + // reallocate flangevin if necessary + if (tallyflag) { + if (nlocal > maxatom1) { + memoryKK->destroy_kokkos(k_flangevin,flangevin); + maxatom1 = atomKK->nmax; + memoryKK->create_kokkos(k_flangevin,flangevin,maxatom1,3,"langevin:flangevin"); + d_flangevin = k_flangevin.template view(); + h_flangevin = k_flangevin.template view(); + } + } + + // account for bias velocity + if(tbiasflag == BIAS){ + atomKK->sync(temperature->execution_space,temperature->datamask_read); + temperature->compute_scalar(); + temperature->remove_bias_all(); // modifies velocities + // if temeprature compute is kokkosized host-device comm won't be needed + atomKK->modified(temperature->execution_space,temperature->datamask_modify); + atomKK->sync(execution_space,temperature->datamask_modify); + } + + // compute langevin force in parallel on the device + FSUM s_fsum; + if (tstyle == ATOM) + if (gjfflag) + if (tallyflag) + if (tbiasflag == BIAS) + if (rmass.data()) + if (zeroflag) { + FixLangevinKokkosPostForceFunctor post_functor(this); + Kokkos::parallel_reduce(nlocal,post_functor,s_fsum); + } else { + FixLangevinKokkosPostForceFunctor post_functor(this); + Kokkos::parallel_for(nlocal,post_functor); + } + else + if (zeroflag) { + FixLangevinKokkosPostForceFunctor post_functor(this); + Kokkos::parallel_reduce(nlocal,post_functor,s_fsum); + } else { + FixLangevinKokkosPostForceFunctor post_functor(this); + Kokkos::parallel_for(nlocal,post_functor); + } + else + if (rmass.data()) + if (zeroflag) { + FixLangevinKokkosPostForceFunctor post_functor(this); + Kokkos::parallel_reduce(nlocal,post_functor,s_fsum); + } else { + FixLangevinKokkosPostForceFunctor post_functor(this); + Kokkos::parallel_for(nlocal,post_functor); + } + else + if (zeroflag) { + FixLangevinKokkosPostForceFunctor post_functor(this); + Kokkos::parallel_reduce(nlocal,post_functor,s_fsum); + } else { + FixLangevinKokkosPostForceFunctor post_functor(this); + Kokkos::parallel_for(nlocal,post_functor); + } + else + if (tbiasflag == BIAS) + if (rmass.data()) + if (zeroflag) { + FixLangevinKokkosPostForceFunctor post_functor(this); + Kokkos::parallel_reduce(nlocal,post_functor,s_fsum); + } else { + FixLangevinKokkosPostForceFunctor post_functor(this); + Kokkos::parallel_for(nlocal,post_functor); + } + else + if (zeroflag) { + FixLangevinKokkosPostForceFunctor post_functor(this); + Kokkos::parallel_reduce(nlocal,post_functor,s_fsum); + } else { + FixLangevinKokkosPostForceFunctor post_functor(this); + Kokkos::parallel_for(nlocal,post_functor); + } + else + if (rmass.data()) + if (zeroflag) { + FixLangevinKokkosPostForceFunctor post_functor(this); + Kokkos::parallel_reduce(nlocal,post_functor,s_fsum); + } else { + FixLangevinKokkosPostForceFunctor post_functor(this); + Kokkos::parallel_for(nlocal,post_functor); + } + else + if (zeroflag) { + FixLangevinKokkosPostForceFunctor post_functor(this); + Kokkos::parallel_reduce(nlocal,post_functor,s_fsum); + } else { + FixLangevinKokkosPostForceFunctor post_functor(this); + Kokkos::parallel_for(nlocal,post_functor); + } + else + if (tallyflag) + if (tbiasflag == BIAS) + if (rmass.data()) + if (zeroflag) { + FixLangevinKokkosPostForceFunctor post_functor(this); + Kokkos::parallel_reduce(nlocal,post_functor,s_fsum); + } else { + FixLangevinKokkosPostForceFunctor post_functor(this); + Kokkos::parallel_for(nlocal,post_functor); + } + else + if (zeroflag) { + FixLangevinKokkosPostForceFunctor post_functor(this); + Kokkos::parallel_reduce(nlocal,post_functor,s_fsum); + } else { + FixLangevinKokkosPostForceFunctor post_functor(this); + Kokkos::parallel_for(nlocal,post_functor); + } + else + if (rmass.data()) + if (zeroflag) { + FixLangevinKokkosPostForceFunctor post_functor(this); + Kokkos::parallel_reduce(nlocal,post_functor,s_fsum); + } else { + FixLangevinKokkosPostForceFunctor post_functor(this); + Kokkos::parallel_for(nlocal,post_functor); + } + else + if (zeroflag) { + FixLangevinKokkosPostForceFunctor post_functor(this); + Kokkos::parallel_reduce(nlocal,post_functor,s_fsum); + } else { + FixLangevinKokkosPostForceFunctor post_functor(this); + Kokkos::parallel_for(nlocal,post_functor); + } + else + if (tbiasflag == BIAS) + if (rmass.data()) + if (zeroflag) { + FixLangevinKokkosPostForceFunctor post_functor(this); + Kokkos::parallel_reduce(nlocal,post_functor,s_fsum); + } else { + FixLangevinKokkosPostForceFunctor post_functor(this); + Kokkos::parallel_for(nlocal,post_functor); + } + else + if (zeroflag) { + FixLangevinKokkosPostForceFunctor post_functor(this); + Kokkos::parallel_reduce(nlocal,post_functor,s_fsum); + } else { + FixLangevinKokkosPostForceFunctor post_functor(this); + Kokkos::parallel_for(nlocal,post_functor); + } + else + if (rmass.data()) + if (zeroflag) { + FixLangevinKokkosPostForceFunctor post_functor(this); + Kokkos::parallel_reduce(nlocal,post_functor,s_fsum); + } else { + FixLangevinKokkosPostForceFunctor post_functor(this); + Kokkos::parallel_for(nlocal,post_functor); + } + else + if (zeroflag) { + FixLangevinKokkosPostForceFunctor post_functor(this); + Kokkos::parallel_reduce(nlocal,post_functor,s_fsum); + } else { + FixLangevinKokkosPostForceFunctor post_functor(this); + Kokkos::parallel_for(nlocal,post_functor); + } + else + if (gjfflag) + if (tallyflag) + if (tbiasflag == BIAS) + if (rmass.data()) + if (zeroflag) { + FixLangevinKokkosPostForceFunctor post_functor(this); + Kokkos::parallel_reduce(nlocal,post_functor,s_fsum); + } else { + FixLangevinKokkosPostForceFunctor post_functor(this); + Kokkos::parallel_for(nlocal,post_functor); + } + else + if (zeroflag) { + FixLangevinKokkosPostForceFunctor post_functor(this); + Kokkos::parallel_reduce(nlocal,post_functor,s_fsum); + } else { + FixLangevinKokkosPostForceFunctor post_functor(this); + Kokkos::parallel_for(nlocal,post_functor); + } + else + if (rmass.data()) + if (zeroflag) { + FixLangevinKokkosPostForceFunctor post_functor(this); + Kokkos::parallel_reduce(nlocal,post_functor,s_fsum); + } else { + FixLangevinKokkosPostForceFunctor post_functor(this); + Kokkos::parallel_for(nlocal,post_functor); + } + else + if (zeroflag) { + FixLangevinKokkosPostForceFunctor post_functor(this); + Kokkos::parallel_reduce(nlocal,post_functor,s_fsum); + } else { + FixLangevinKokkosPostForceFunctor post_functor(this); + Kokkos::parallel_for(nlocal,post_functor); + } + else + if (tbiasflag == BIAS) + if (rmass.data()) + if (zeroflag) { + FixLangevinKokkosPostForceFunctor post_functor(this); + Kokkos::parallel_reduce(nlocal,post_functor,s_fsum); + } else { + FixLangevinKokkosPostForceFunctor post_functor(this); + Kokkos::parallel_for(nlocal,post_functor); + } + else + if (zeroflag) { + FixLangevinKokkosPostForceFunctor post_functor(this); + Kokkos::parallel_reduce(nlocal,post_functor,s_fsum); + } else { + FixLangevinKokkosPostForceFunctor post_functor(this); + Kokkos::parallel_for(nlocal,post_functor); + } + else + if (rmass.data()) + if (zeroflag) { + FixLangevinKokkosPostForceFunctor post_functor(this); + Kokkos::parallel_reduce(nlocal,post_functor,s_fsum); + } else { + FixLangevinKokkosPostForceFunctor post_functor(this); + Kokkos::parallel_for(nlocal,post_functor); + } + else + if (zeroflag) { + FixLangevinKokkosPostForceFunctor post_functor(this); + Kokkos::parallel_reduce(nlocal,post_functor,s_fsum); + } else { + FixLangevinKokkosPostForceFunctor post_functor(this); + Kokkos::parallel_for(nlocal,post_functor); + } + else + if (tallyflag) + if (tbiasflag == BIAS) + if (rmass.data()) + if (zeroflag) { + FixLangevinKokkosPostForceFunctor post_functor(this); + Kokkos::parallel_reduce(nlocal,post_functor,s_fsum); + } else { + FixLangevinKokkosPostForceFunctor post_functor(this); + Kokkos::parallel_for(nlocal,post_functor); + } + else + if (zeroflag) { + FixLangevinKokkosPostForceFunctor post_functor(this); + Kokkos::parallel_reduce(nlocal,post_functor,s_fsum); + } else { + FixLangevinKokkosPostForceFunctor post_functor(this); + Kokkos::parallel_for(nlocal,post_functor); + } + else + if (rmass.data()) + if (zeroflag) { + FixLangevinKokkosPostForceFunctor post_functor(this); + Kokkos::parallel_reduce(nlocal,post_functor,s_fsum); + } else { + FixLangevinKokkosPostForceFunctor post_functor(this); + Kokkos::parallel_for(nlocal,post_functor); + } + else + if (zeroflag) { + FixLangevinKokkosPostForceFunctor post_functor(this); + Kokkos::parallel_reduce(nlocal,post_functor,s_fsum); + } else { + FixLangevinKokkosPostForceFunctor post_functor(this); + Kokkos::parallel_for(nlocal,post_functor); + } + else + if (tbiasflag == BIAS) + if (rmass.data()) + if (zeroflag) { + FixLangevinKokkosPostForceFunctor post_functor(this); + Kokkos::parallel_reduce(nlocal,post_functor,s_fsum); + } else { + FixLangevinKokkosPostForceFunctor post_functor(this); + Kokkos::parallel_for(nlocal,post_functor); + } + else + if (zeroflag) { + FixLangevinKokkosPostForceFunctor post_functor(this); + Kokkos::parallel_reduce(nlocal,post_functor,s_fsum); + } else { + FixLangevinKokkosPostForceFunctor post_functor(this); + Kokkos::parallel_for(nlocal,post_functor); + } + else + if (rmass.data()) + if (zeroflag) { + FixLangevinKokkosPostForceFunctor post_functor(this); + Kokkos::parallel_reduce(nlocal,post_functor,s_fsum); + } else { + FixLangevinKokkosPostForceFunctor post_functor(this); + Kokkos::parallel_for(nlocal,post_functor); + } + else + if (zeroflag) { + FixLangevinKokkosPostForceFunctor post_functor(this); + Kokkos::parallel_reduce(nlocal,post_functor,s_fsum); + } else { + FixLangevinKokkosPostForceFunctor post_functor(this); + Kokkos::parallel_for(nlocal,post_functor); + } + + + if(tbiasflag == BIAS){ + atomKK->sync(temperature->execution_space,temperature->datamask_read); + temperature->restore_bias_all(); // modifies velocities + atomKK->modified(temperature->execution_space,temperature->datamask_modify); + atomKK->sync(execution_space,temperature->datamask_modify); + } + + // set modify flags for the views modified in post_force functor + if (gjfflag) k_franprev.template modify(); + if (gjfflag) k_lv.template modify(); + if (tallyflag) k_flangevin.template modify(); + + // set total force to zero + if (zeroflag) { + fsum[0] = s_fsum.fx; fsum[1] = s_fsum.fy; fsum[2] = s_fsum.fz; + MPI_Allreduce(fsum,fsumall,3,MPI_DOUBLE,MPI_SUM,world); + h_fsumall(0) = fsumall[0]/count; + h_fsumall(1) = fsumall[1]/count; + h_fsumall(2) = fsumall[2]/count; + k_fsumall.template modify(); + k_fsumall.template sync(); + // set total force zero in parallel on the device + FixLangevinKokkosZeroForceFunctor zero_functor(this); + Kokkos::parallel_for(nlocal,zero_functor); + } + // f is modified by both post_force and zero_force functors + atomKK->modified(execution_space,datamask_modify); + + // thermostat omega and angmom + // if (oflag) omega_thermostat(); + // if (ascale) angmom_thermostat(); + +} + +/* ---------------------------------------------------------------------- */ + +template +template +KOKKOS_INLINE_FUNCTION +FSUM FixLangevinKokkos::post_force_item(int i) const +{ + FSUM fsum; + double fdrag[3],fran[3]; + double gamma1,gamma2; + double fswap; + double tsqrt_t = tsqrt; + + if (mask[i] & groupbit) { + rand_type rand_gen = rand_pool.get_state(); + if(Tp_TSTYLEATOM) tsqrt_t = sqrt(d_tforce[i]); + if(Tp_RMASS){ + gamma1 = -rmass[i] / t_period / ftm2v; + gamma2 = sqrt(rmass[i]) * fran_prop_const / ftm2v; + gamma1 *= 1.0/d_ratio[type[i]]; + gamma2 *= 1.0/sqrt(d_ratio[type[i]]) * tsqrt_t; + } else { + gamma1 = d_gfactor1[type[i]]; + gamma2 = d_gfactor2[type[i]] * tsqrt_t; + } + + fran[0] = gamma2 * (rand_gen.drand() - 0.5); //(random->uniform()-0.5); + fran[1] = gamma2 * (rand_gen.drand() - 0.5); //(random->uniform()-0.5); + fran[2] = gamma2 * (rand_gen.drand() - 0.5); //(random->uniform()-0.5); + + if(Tp_BIAS){ + fdrag[0] = gamma1*v(i,0); + fdrag[1] = gamma1*v(i,1); + fdrag[2] = gamma1*v(i,2); + if (v(i,0) == 0.0) fran[0] = 0.0; + if (v(i,1) == 0.0) fran[1] = 0.0; + if (v(i,2) == 0.0) fran[2] = 0.0; + } else { + fdrag[0] = gamma1*v(i,0); + fdrag[1] = gamma1*v(i,1); + fdrag[2] = gamma1*v(i,2); + } + + if (Tp_GJF) { + d_lv(i,0) = gjfsib*v(i,0); + d_lv(i,1) = gjfsib*v(i,1); + d_lv(i,2) = gjfsib*v(i,2); + + fswap = 0.5*(fran[0]+d_franprev(i,0)); + d_franprev(i,0) = fran[0]; + fran[0] = fswap; + fswap = 0.5*(fran[1]+d_franprev(i,1)); + d_franprev(i,1) = fran[1]; + fran[1] = fswap; + fswap = 0.5*(fran[2]+d_franprev(i,2)); + d_franprev(i,2) = fran[2]; + fran[2] = fswap; + + fdrag[0] *= gjfa; + fdrag[1] *= gjfa; + fdrag[2] *= gjfa; + fran[0] *= gjfa; + fran[1] *= gjfa; + fran[2] *= gjfa; + f(i,0) *= gjfa; + f(i,1) *= gjfa; + f(i,2) *= gjfa; + } + + f(i,0) += fdrag[0] + fran[0]; + f(i,1) += fdrag[1] + fran[1]; + f(i,2) += fdrag[2] + fran[2]; + + if (Tp_TALLY) { + if (Tp_GJF){ + fdrag[0] = gamma1*d_lv(i,0)/gjfsib/gjfsib; + fdrag[1] = gamma1*d_lv(i,1)/gjfsib/gjfsib; + fdrag[2] = gamma1*d_lv(i,2)/gjfsib/gjfsib; + fswap = (2*fran[0]/gjfa - d_franprev(i,0))/gjfsib; + fran[0] = fswap; + fswap = (2*fran[1]/gjfa - d_franprev(i,1))/gjfsib; + fran[1] = fswap; + fswap = (2*fran[2]/gjfa - d_franprev(i,2))/gjfsib; + fran[2] = fswap; + } + d_flangevin(i,0) = fdrag[0] + fran[0]; + d_flangevin(i,1) = fdrag[1] + fran[1]; + d_flangevin(i,2) = fdrag[2] + fran[2]; + } + + if (Tp_ZERO) { + fsum.fx = fran[0]; + fsum.fy = fran[1]; + fsum.fz = fran[2]; + } + rand_pool.free_state(rand_gen); + } + + return fsum; +} + +/* ---------------------------------------------------------------------- */ + +template +KOKKOS_INLINE_FUNCTION +void FixLangevinKokkos::zero_force_item(int i) const +{ + if (mask[i] & groupbit) { + f(i,0) -= d_fsumall[0]; + f(i,1) -= d_fsumall[1]; + f(i,2) -= d_fsumall[2]; + } + +} + +/* ---------------------------------------------------------------------- + set current t_target and t_sqrt + ------------------------------------------------------------------------- */ + +template +void FixLangevinKokkos::compute_target() +{ + atomKK->sync(Host, MASK_MASK); + mask = atomKK->k_mask.template view(); + int nlocal = atomKK->nlocal; + + double delta = update->ntimestep - update->beginstep; + if (delta != 0.0) delta /= update->endstep - update->beginstep; + + // if variable temp, evaluate variable, wrap with clear/add + // reallocate tforce array if necessary + + if (tstyle == CONSTANT) { + t_target = t_start + delta * (t_stop-t_start); + tsqrt = sqrt(t_target); + } else { + modify->clearstep_compute(); + if (tstyle == EQUAL) { + t_target = input->variable->compute_equal(tvar); + if (t_target < 0.0) + error->one(FLERR,"Fix langevin variable returned negative temperature"); + tsqrt = sqrt(t_target); + } else { + if (atom->nmax > maxatom2) { + maxatom2 = atom->nmax; + memoryKK->destroy_kokkos(k_tforce,tforce); + memoryKK->create_kokkos(k_tforce,tforce,maxatom2,"langevin:tforce"); + d_tforce = k_tforce.template view(); + h_tforce = k_tforce.template view(); + } + input->variable->compute_atom(tvar,igroup,tforce,1,0); // tforce is modified on host + k_tforce.template modify(); + for (int i = 0; i < nlocal; i++) + if (mask[i] & groupbit) + if (h_tforce[i] < 0.0) + error->one(FLERR, + "Fix langevin variable returned negative temperature"); + } + modify->addstep_compute(update->ntimestep + 1); + } +} + +/* ---------------------------------------------------------------------- */ + +template +void FixLangevinKokkos::reset_dt() +{ + if (atomKK->mass) { + for (int i = 1; i <= atomKK->ntypes; i++) { + h_gfactor2[i] = sqrt(atomKK->mass[i]) * + sqrt(24.0*force->boltz/t_period/update->dt/force->mvv2e) / + force->ftm2v; + h_gfactor2[i] *= 1.0/sqrt(h_ratio[i]); + } + k_gfactor2.template modify(); + } + +} + +/* ---------------------------------------------------------------------- */ + +template +double FixLangevinKokkos::compute_scalar() +{ + if (!tallyflag || flangevin == NULL) return 0.0; + + v = atomKK->k_v.template view(); + mask = atomKK->k_mask.template view(); + + // capture the very first energy transfer to thermal reservoir + + if (update->ntimestep == update->beginstep) { + energy_onestep = 0.0; + atomKK->sync(execution_space,V_MASK | MASK_MASK); + int nlocal = atomKK->nlocal; + k_flangevin.template sync(); + FixLangevinKokkosTallyEnergyFunctor scalar_functor(this); + Kokkos::parallel_reduce(nlocal,scalar_functor,energy_onestep); + energy = 0.5*energy_onestep*update->dt; + } + + // convert midstep energy back to previous fullstep energy + double energy_me = energy - 0.5*energy_onestep*update->dt; + double energy_all; + MPI_Allreduce(&energy_me,&energy_all,1,MPI_DOUBLE,MPI_SUM,world); + return -energy_all; +} + +/* ---------------------------------------------------------------------- */ + +template +KOKKOS_INLINE_FUNCTION +double FixLangevinKokkos::compute_energy_item(int i) const +{ + double energy; + if (mask[i] & groupbit) + energy = d_flangevin(i,0)*v(i,0) + d_flangevin(i,1)*v(i,1) + + d_flangevin(i,2)*v(i,2); + return energy; +} + +/* ---------------------------------------------------------------------- + tally energy transfer to thermal reservoir + ------------------------------------------------------------------------- */ + +template +void FixLangevinKokkos::end_of_step() +{ + if (!tallyflag && !gjfflag) return; + + v = atomKK->k_v.template view(); + f = atomKK->k_f.template view(); + mask = atomKK->k_mask.template view(); + + atomKK->sync(execution_space,V_MASK | MASK_MASK); + int nlocal = atomKK->nlocal; + + energy_onestep = 0.0; + + k_flangevin.template sync(); + FixLangevinKokkosTallyEnergyFunctor tally_functor(this); + Kokkos::parallel_reduce(nlocal,tally_functor,energy_onestep); + + if (gjfflag){ + if (rmass.data()) { + FixLangevinKokkosEndOfStepFunctor functor(this); + Kokkos::parallel_for(nlocal,functor); + } else { + mass = atomKK->k_mass.view(); + FixLangevinKokkosEndOfStepFunctor functor(this); + Kokkos::parallel_for(nlocal,functor); + } + } + + energy += energy_onestep*update->dt; +} + +template +KOKKOS_INLINE_FUNCTION +void FixLangevinKokkos::end_of_step_item(int i) const { + double tmp[3]; + if (mask[i] & groupbit) { + const double dtfm = force->ftm2v * 0.5 * dt / mass[type[i]]; + tmp[0] = v(i,0); + tmp[1] = v(i,1); + tmp[2] = v(i,2); + if (!fsflag){ + v(i,0) = d_lv(i,0); + v(i,1) = d_lv(i,1); + v(i,2) = d_lv(i,2); + } else { + v(i,0) = 0.5 * gjfsib * gjfsib * (v(i,0) + dtfm * f(i,0) / gjfa) + + dtfm * 0.5 * (gjfsib * d_flangevin(i,0) - d_franprev(i,0)) + + (gjfsib * gjfa * 0.5 + dt * 0.25 / t_period / gjfsib) * d_lv(i,0); + v(i,1) = 0.5 * gjfsib * gjfsib * (v(i,1) + dtfm * f(i,1) / gjfa) + + dtfm * 0.5 * (gjfsib * d_flangevin(i,0) - d_franprev(i,1)) + + (gjfsib * gjfa * 0.5 + dt * 0.25 / t_period / gjfsib) * d_lv(i,1); + v(i,2) = 0.5 * gjfsib * gjfsib * (v(i,2) + dtfm * f(i,2) / gjfa) + + dtfm * 0.5 * (gjfsib * d_flangevin(i,0) - d_franprev(i,2)) + + (gjfsib * gjfa * 0.5 + dt * 0.25 / t_period / gjfsib) * d_lv(i,2); + } + d_lv(i,0) = tmp[0]; + d_lv(i,1) = tmp[1]; + d_lv(i,2) = tmp[2]; + } +} + +template +KOKKOS_INLINE_FUNCTION +void FixLangevinKokkos::end_of_step_rmass_item(int i) const +{ + double tmp[3]; + if (mask[i] & groupbit) { + const double dtfm = force->ftm2v * 0.5 * dt / rmass[i]; + tmp[0] = v(i,0); + tmp[1] = v(i,1); + tmp[2] = v(i,2); + if (!fsflag){ + v(i,0) = d_lv(i,0); + v(i,1) = d_lv(i,1); + v(i,2) = d_lv(i,2); + } else { + v(i,0) = 0.5 * gjfsib * gjfsib * (v(i,0) + dtfm * f(i,0) / gjfa) + + dtfm * 0.5 * (gjfsib * d_flangevin(i,0) - d_franprev(i,0)) + + (gjfsib * gjfa * 0.5 + dt * 0.25 / t_period / gjfsib) * d_lv(i,0); + v(i,1) = 0.5 * gjfsib * gjfsib * (v(i,1) + dtfm * f(i,1) / gjfa) + + dtfm * 0.5 * (gjfsib * d_flangevin(i,1) - d_franprev(i,1)) + + (gjfsib * gjfa * 0.5 + dt * 0.25 / t_period / gjfsib) * d_lv(i,1); + v(i,2) = 0.5 * gjfsib * gjfsib * (v(i,2) + dtfm * f(i,2) / gjfa) + + dtfm * 0.5 * (gjfsib * d_flangevin(i,2) - d_franprev(i,2)) + + (gjfsib * gjfa * 0.5 + dt * 0.25 / t_period / gjfsib) * d_lv(i,2); + } + d_lv(i,0) = tmp[0]; + d_lv(i,1) = tmp[1]; + d_lv(i,2) = tmp[2]; + } +} + +/* ---------------------------------------------------------------------- + copy values within local atom-based array + ------------------------------------------------------------------------- */ + +template +void FixLangevinKokkos::copy_arrays(int i, int j, int delflag) +{ + h_franprev(j,0) = h_franprev(i,0); + h_franprev(j,1) = h_franprev(i,1); + h_franprev(j,2) = h_franprev(i,2); + h_lv(j,0) = h_lv(i,0); + h_lv(j,1) = h_lv(i,1); + h_lv(j,2) = h_lv(i,2); + + k_franprev.template modify(); + k_lv.template modify(); + +} + +/* ---------------------------------------------------------------------- */ + +template +void FixLangevinKokkos::cleanup_copy() +{ + random = NULL; + tstr = NULL; + gfactor1 = NULL; + gfactor2 = NULL; + ratio = NULL; + id_temp = NULL; + flangevin = NULL; + tforce = NULL; + gjfflag = 0; + franprev = NULL; + lv = NULL; + id = style = NULL; + vatom = NULL; +} + +namespace LAMMPS_NS { +template class FixLangevinKokkos; +#ifdef KOKKOS_ENABLE_CUDA +template class FixLangevinKokkos; +#endif +} + diff --git a/fix_langevin_kokkos.h b/fix_langevin_kokkos.h new file mode 100644 index 0000000000..a6d467dfd7 --- /dev/null +++ b/fix_langevin_kokkos.h @@ -0,0 +1,293 @@ +/* -*- c++ -*- ---------------------------------------------------------- + LAMMPS - Large-scale Atomic/Molecular Massively Parallel Simulator + http://lammps.sandia.gov, Sandia National Laboratories + Steve Plimpton, sjplimp@sandia.gov + + Copyright (2003) Sandia Corporation. Under the terms of Contract + DE-AC04-94AL85000 with Sandia Corporation, the U.S. Government retains + certain rights in this software. This software is distributed under + the GNU General Public License. + + See the README file in the top-level LAMMPS directory. + ------------------------------------------------------------------------- */ + +#ifdef FIX_CLASS + +FixStyle(langevin/kk,FixLangevinKokkos) +FixStyle(langevin/kk/device,FixLangevinKokkos) +FixStyle(langevin/kk/host,FixLangevinKokkos) + +#else + +#ifndef LMP_FIX_LANGEVIN_KOKKOS_H +#define LMP_FIX_LANGEVIN_KOKKOS_H + +#include "fix_langevin.h" +#include "kokkos_type.h" +#include "Kokkos_Random.hpp" +#include "comm_kokkos.h" + +namespace LAMMPS_NS { + + struct s_FSUM { + double fx, fy, fz; + KOKKOS_INLINE_FUNCTION + s_FSUM() { + fx = fy = fz = 0.0; + } + KOKKOS_INLINE_FUNCTION + s_FSUM& operator+=(const s_FSUM &rhs){ + fx += rhs.fx; + fy += rhs.fy; + fz += rhs.fz; + return *this; + } + + KOKKOS_INLINE_FUNCTION + volatile s_FSUM& operator+=(const volatile s_FSUM &rhs) volatile { + fx += rhs.fx; + fy += rhs.fy; + fz += rhs.fz; + return *this; + } + }; + typedef s_FSUM FSUM; + + template + class FixLangevinKokkos; + + template + class FixLangevinKokkosInitialIntegrateFunctor; + + template + class FixLangevinKokkosPostForceFunctor; + + template class FixLangevinKokkosZeroForceFunctor; + + template class FixLangevinKokkosTallyEnergyFunctor; + + template + class FixLangevinKokkos : public FixLangevin { + public: + FixLangevinKokkos(class LAMMPS *, int, char **); + ~FixLangevinKokkos(); + + void cleanup_copy(); + void init(); + void initial_integrate(int); + void post_force(int); + void reset_dt(); + void grow_arrays(int); + void copy_arrays(int i, int j, int delflag); + double compute_scalar(); + void end_of_step(); + + KOKKOS_INLINE_FUNCTION + void initial_integrate_item(int) const; + + KOKKOS_INLINE_FUNCTION + void initial_integrate_rmass_item(int) const; + + template + KOKKOS_INLINE_FUNCTION + FSUM post_force_item(int) const; + + KOKKOS_INLINE_FUNCTION + void zero_force_item(int) const; + + KOKKOS_INLINE_FUNCTION + double compute_energy_item(int) const; + + KOKKOS_INLINE_FUNCTION + void end_of_step_item(int) const; + + KOKKOS_INLINE_FUNCTION + void end_of_step_rmass_item(int) const; + + private: + class CommKokkos *commKK; + + typename ArrayTypes::t_float_1d rmass; + typename ArrayTypes::t_float_1d mass; + typename ArrayTypes::tdual_double_2d k_franprev; + typename ArrayTypes::t_double_2d d_franprev; + HAT::t_double_2d h_franprev; + + typename ArrayTypes::tdual_double_2d k_lv; + typename ArrayTypes::t_double_2d d_lv; + HAT::t_double_2d h_lv; + + typename ArrayTypes::tdual_double_2d k_flangevin; + typename ArrayTypes::t_double_2d d_flangevin; + HAT::t_double_2d h_flangevin; + + typename ArrayTypes::tdual_double_1d k_tforce; + typename ArrayTypes::t_double_1d d_tforce; + HAT::t_double_1d h_tforce; + + typename ArrayTypes::t_v_array v; + typename ArrayTypes::t_f_array f; + typename ArrayTypes::t_int_1d type; + typename ArrayTypes::t_int_1d mask; + + typename ArrayTypes::tdual_double_1d k_gfactor1, k_gfactor2, k_ratio; + typename ArrayTypes::t_double_1d d_gfactor1, d_gfactor2, d_ratio; + HAT::t_double_1d h_gfactor1, h_gfactor2, h_ratio; + + typedef Kokkos::DualView + tdual_double_1d_3n; + tdual_double_1d_3n k_fsumall; + typename tdual_double_1d_3n::t_dev d_fsumall; + typename tdual_double_1d_3n::t_host h_fsumall; + + double boltz,dt,mvv2e,ftm2v,fran_prop_const; + + void compute_target(); + + Kokkos::Random_XorShift64_Pool rand_pool; + typedef typename Kokkos::Random_XorShift64_Pool::generator_type rand_type; + + }; + + template + struct FixLangevinKokkosInitialIntegrateFunctor { + typedef DeviceType device_type ; + FixLangevinKokkos c; + + FixLangevinKokkosInitialIntegrateFunctor(FixLangevinKokkos* c_ptr): + c(*c_ptr) {c.cleanup_copy();}; + + KOKKOS_INLINE_FUNCTION + void operator()(const int i) const { + c.initial_integrate_item(i); + } + }; + + + template + struct FixLangevinKokkosPostForceFunctor { + + typedef DeviceType device_type; + typedef FSUM value_type; + FixLangevinKokkos c; + + FixLangevinKokkosPostForceFunctor(FixLangevinKokkos* c_ptr): + c(*c_ptr) {} + ~FixLangevinKokkosPostForceFunctor(){c.cleanup_copy();} + + KOKKOS_INLINE_FUNCTION + void operator()(const int i) const { + c.template post_force_item(i); + } + + KOKKOS_INLINE_FUNCTION + void operator()(const int i, value_type &fsum) const { + + fsum += c.template post_force_item(i); + } + + KOKKOS_INLINE_FUNCTION + static void init(volatile value_type &update) { + update.fx = 0.0; + update.fy = 0.0; + update.fz = 0.0; + } + KOKKOS_INLINE_FUNCTION + static void join(volatile value_type &update, + const volatile value_type &source) { + update.fx += source.fx; + update.fy += source.fy; + update.fz += source.fz; + } + + }; + + template + struct FixLangevinKokkosZeroForceFunctor { + typedef DeviceType device_type ; + FixLangevinKokkos c; + + FixLangevinKokkosZeroForceFunctor(FixLangevinKokkos* c_ptr): + c(*c_ptr) {c.cleanup_copy();} + + KOKKOS_INLINE_FUNCTION + void operator()(const int i) const { + c.zero_force_item(i); + } + }; + + template + struct FixLangevinKokkosTallyEnergyFunctor { + typedef DeviceType device_type ; + FixLangevinKokkos c; + typedef double value_type; + FixLangevinKokkosTallyEnergyFunctor(FixLangevinKokkos* c_ptr): + c(*c_ptr) {c.cleanup_copy();} + + KOKKOS_INLINE_FUNCTION + void operator()(const int i, value_type &energy) const { + energy += c.compute_energy_item(i); + } + KOKKOS_INLINE_FUNCTION + static void init(volatile value_type &update) { + update = 0.0; + } + KOKKOS_INLINE_FUNCTION + static void join(volatile value_type &update, + const volatile value_type &source) { + update += source; + } + }; + + template + struct FixLangevinKokkosEndOfStepFunctor { + typedef DeviceType device_type ; + FixLangevinKokkos c; + + FixLangevinKokkosEndOfStepFunctor(FixLangevinKokkos* c_ptr): + c(*c_ptr) {c.cleanup_copy();} + + KOKKOS_INLINE_FUNCTION + void operator()(const int i) const { + if (RMass) c.end_of_step_rmass_item(i); + else c.end_of_step_item(i); + } + }; +} + +#endif +#endif + +/* ERROR/WARNING messages: + +E: Fix langevin omega is not yet implemented with kokkos + +This option is not yet available. + +E: Fix langevin angmom is not yet implemented with kokkos + +This option is not yet available. + +E: Cannot zero Langevin force of 0 atoms + +The group has zero atoms, so you cannot request its force +be zeroed. + +E: Fix langevin variable returned negative temperature + +Self-explanatory. + +E: Fix langevin gjf with tbias is not yet implemented with kokkos + +This option is not yet available. + +W: Fix langevin gjf using random gaussians is not implemented with kokkos + +This will most likely cause errors in kinetic fluctuations. + +*/ diff --git a/src/fix_langevin.cpp b/src/fix_langevin.cpp index 25b4f83c37..2d58f67a99 100644 --- a/src/fix_langevin.cpp +++ b/src/fix_langevin.cpp @@ -23,6 +23,7 @@ #include #include #include +#include #include "math_extra.h" #include "atom.h" #include "atom_vec_ellipsoid.h" @@ -53,7 +54,7 @@ enum{CONSTANT,EQUAL,ATOM}; FixLangevin::FixLangevin(LAMMPS *lmp, int narg, char **arg) : Fix(lmp, narg, arg), gjfflag(0), gfactor1(NULL), gfactor2(NULL), ratio(NULL), tstr(NULL), - flangevin(NULL), tforce(NULL), franprev(NULL), id_temp(NULL), random(NULL), lv(NULL) + flangevin(NULL), tforce(NULL), franprev(NULL), lv(NULL), id_temp(NULL), random(NULL) { if (narg < 7) error->all(FLERR,"Illegal fix langevin command"); @@ -232,7 +233,7 @@ void FixLangevin::init() int flag = 0; for (int i = 0; i < modify->nfix; i++) { if (strcmp(id,modify->fix[i]->id) == 0) before = 0; - else if ((modify->fmask[i] && strcmp(modify->fix[i]->style,"nve")==0) && before) flag = 1; + else if ((modify->fmask[i] && utils::strmatch(modify->fix[i]->style,"^nve")) && before) flag = 1; } if (flag && comm->me == 0) error->all(FLERR,"Fix langevin gjf should come before fix nve"); @@ -287,13 +288,13 @@ void FixLangevin::init() if (!atom->rmass) { for (int i = 1; i <= atom->ntypes; i++) { gfactor1[i] = -atom->mass[i] / t_period / force->ftm2v; - if (!gjfflag) + if (gjfflag) gfactor2[i] = sqrt(atom->mass[i]) * - sqrt(24.0*force->boltz/t_period/update->dt/force->mvv2e) / + sqrt(2.0*force->boltz/t_period/update->dt/force->mvv2e) / force->ftm2v; else gfactor2[i] = sqrt(atom->mass[i]) * - sqrt(2.0*force->boltz/t_period/update->dt/force->mvv2e) / + sqrt(24.0*force->boltz/t_period/update->dt/force->mvv2e) / force->ftm2v; gfactor1[i] *= 1.0/ratio[i]; gfactor2[i] *= 1.0/sqrt(ratio[i]); @@ -306,7 +307,7 @@ void FixLangevin::init() if (strstr(update->integrate_style,"respa")) nlevels_respa = ((Respa *) update->integrate)->nlevels; - if (strstr(update->integrate_style,"respa") && gjfflag) + if (utils::strmatch(update->integrate_style,"^respa") && gjfflag) error->all(FLERR,"Fix langevin gjf and respa are not compatible"); if (gjfflag) gjfa = (1.0-update->dt/2.0/t_period)/(1.0+update->dt/2.0/t_period); @@ -643,10 +644,10 @@ void FixLangevin::post_force_templated() if (Tp_TSTYLEATOM) tsqrt = sqrt(tforce[i]); if (Tp_RMASS) { gamma1 = -rmass[i] / t_period / ftm2v; - if (!Tp_GJF) - gamma2 = sqrt(rmass[i]) * sqrt(24.0*boltz/t_period/dt/mvv2e) / ftm2v; - else + if (Tp_GJF) gamma2 = sqrt(rmass[i]) * sqrt(2.0*boltz/t_period/dt/mvv2e) / ftm2v; + else + gamma2 = sqrt(rmass[i]) * sqrt(24.0*boltz/t_period/dt/mvv2e) / ftm2v; gamma1 *= 1.0/ratio[type[i]]; gamma2 *= 1.0/sqrt(ratio[type[i]]) * tsqrt; } else { @@ -654,16 +655,16 @@ void FixLangevin::post_force_templated() gamma2 = gfactor2[type[i]] * tsqrt; } - if (!Tp_GJF){ - fran[0] = gamma2*(random->uniform()-0.5); - fran[1] = gamma2*(random->uniform()-0.5); - fran[2] = gamma2*(random->uniform()-0.5); - } - else{ + if (Tp_GJF){ fran[0] = gamma2*random->gaussian(); fran[1] = gamma2*random->gaussian(); fran[2] = gamma2*random->gaussian(); } + else{ + fran[0] = gamma2*(random->uniform()-0.5); + fran[1] = gamma2*(random->uniform()-0.5); + fran[2] = gamma2*(random->uniform()-0.5); + } if (Tp_BIAS) { temperature->remove_bias(i,v[i]); diff --git a/src/fix_langevin.h b/src/fix_langevin.h index 3ffccb3be1..349a9d2dd9 100644 --- a/src/fix_langevin.h +++ b/src/fix_langevin.h @@ -142,7 +142,7 @@ The compute ID assigned to the fix must compute temperature. E: Fix langevin gjf cannot have period equal to dt/2 -If the period is equal to dt/2 then division by zero can happen. +If the period is equal to dt/2 then division by zero will happen. E: Fix langevin gjf should come before fix nve From 0366a5aae9b00db923ed7eb6ab6c84a146aebc03 Mon Sep 17 00:00:00 2001 From: charlie sievers Date: Sat, 14 Sep 2019 00:13:05 -0700 Subject: [PATCH 141/192] Fix langevin changed to utils.h --- doc/src/fix_langevin.txt | 4 +++- src/fix_langevin.cpp | 2 +- 2 files changed, 4 insertions(+), 2 deletions(-) diff --git a/doc/src/fix_langevin.txt b/doc/src/fix_langevin.txt index 203ff2298c..8dd143bdb7 100644 --- a/doc/src/fix_langevin.txt +++ b/doc/src/fix_langevin.txt @@ -327,7 +327,9 @@ This fix can ramp its target temperature over multiple runs, using the This fix is not invoked during "energy minimization"_minimize.html. -[Restrictions:] For {gjf} do not choose damp=dt/2. {gjf} is not compatible +[Restrictions:] + +For {gjf} do not choose damp=dt/2. {gjf} is not compatible with run_style respa. [Related commands:] diff --git a/src/fix_langevin.cpp b/src/fix_langevin.cpp index 2d58f67a99..cd77883c76 100644 --- a/src/fix_langevin.cpp +++ b/src/fix_langevin.cpp @@ -23,7 +23,6 @@ #include #include #include -#include #include "math_extra.h" #include "atom.h" #include "atom_vec_ellipsoid.h" @@ -39,6 +38,7 @@ #include "memory.h" #include "error.h" #include "group.h" +#include "utils.h" using namespace LAMMPS_NS; using namespace FixConst; From c1eff7d5761f9f54536066d8912a4416d3c8c7fa Mon Sep 17 00:00:00 2001 From: charlie sievers Date: Sat, 14 Sep 2019 11:02:42 -0700 Subject: [PATCH 142/192] fix misplaced fix_langevin_kokkos --- fix_langevin_kokkos.cpp | 916 ----------------------------- fix_langevin_kokkos.h | 293 --------- src/KOKKOS/fix_langevin_kokkos.cpp | 16 +- src/KOKKOS/fix_langevin_kokkos.h | 8 + 4 files changed, 13 insertions(+), 1220 deletions(-) delete mode 100644 fix_langevin_kokkos.cpp delete mode 100644 fix_langevin_kokkos.h diff --git a/fix_langevin_kokkos.cpp b/fix_langevin_kokkos.cpp deleted file mode 100644 index 0618631581..0000000000 --- a/fix_langevin_kokkos.cpp +++ /dev/null @@ -1,916 +0,0 @@ -/* ---------------------------------------------------------------------- - LAMMPS - Large-scale Atomic/Molecular Massively Parallel Simulator - http://lammps.sandia.gov, Sandia National Laboratories - Steve Plimpton, sjplimp@sandia.gov - - Copyright (2003) Sandia Corporation. Under the terms of Contract - DE-AC04-94AL85000 with Sandia Corporation, the U.S. Government retains - certain rights in this software. This software is distributed under - the GNU General Public License. - - See the README file in the top-level LAMMPS directory. - ------------------------------------------------------------------------- */ - -#include "fix_langevin_kokkos.h" -#include -#include "atom_masks.h" -#include "atom_kokkos.h" -#include "force.h" -#include "group.h" -#include "update.h" -#include "error.h" -#include "memory_kokkos.h" -#include "compute.h" -#include "comm.h" -#include "modify.h" -#include "input.h" -#include "region.h" -#include "variable.h" - -using namespace LAMMPS_NS; -using namespace FixConst; - -enum{NOBIAS,BIAS}; -enum{CONSTANT,EQUAL,ATOM}; -#define SINERTIA 0.4 // moment of inertia prefactor for sphere -#define EINERTIA 0.2 // moment of inertia prefactor for ellipsoid - -/* ---------------------------------------------------------------------- */ - -template -FixLangevinKokkos::FixLangevinKokkos(LAMMPS *lmp, int narg, char **arg) : - FixLangevin(lmp, narg, arg),rand_pool(seed + comm->me) -{ - kokkosable = 1; - atomKK = (AtomKokkos *) atom; - int ntypes = atomKK->ntypes; - - // allocate per-type arrays for force prefactors - memoryKK->create_kokkos(k_gfactor1,gfactor1,ntypes+1,"langevin:gfactor1"); - memoryKK->create_kokkos(k_gfactor2,gfactor2,ntypes+1,"langevin:gfactor2"); - memoryKK->create_kokkos(k_ratio,ratio,ntypes+1,"langevin:ratio"); - d_gfactor1 = k_gfactor1.template view(); - h_gfactor1 = k_gfactor1.template view(); - d_gfactor2 = k_gfactor2.template view(); - h_gfactor2 = k_gfactor2.template view(); - d_ratio = k_ratio.template view(); - h_ratio = k_ratio.template view(); - - // optional args - for (int i = 1; i <= ntypes; i++) ratio[i] = 1.0; - k_ratio.template modify(); - - if(gjfflag){ - grow_arrays(atomKK->nmax); - atom->add_callback(0); - // initialize franprev to zero - for (int i = 0; i < atomKK->nlocal; i++) { - franprev[i][0] = 0.0; - franprev[i][1] = 0.0; - franprev[i][2] = 0.0; - lv[i][0] = 0.0; - lv[i][1] = 0.0; - lv[i][2] = 0.0; - } - k_franprev.template modify(); - k_lv.template modify(); - } - if(zeroflag){ - k_fsumall = tdual_double_1d_3n("langevin:fsumall"); - h_fsumall = k_fsumall.template view(); - d_fsumall = k_fsumall.template view(); - } - - execution_space = ExecutionSpaceFromDevice::space; - datamask_read = V_MASK | F_MASK | MASK_MASK | RMASS_MASK | TYPE_MASK; - datamask_modify = F_MASK; - -} - -/* ---------------------------------------------------------------------- */ - -template -FixLangevinKokkos::~FixLangevinKokkos() -{ - memoryKK->destroy_kokkos(k_gfactor1,gfactor1); - memoryKK->destroy_kokkos(k_gfactor2,gfactor2); - memoryKK->destroy_kokkos(k_ratio,ratio); - memoryKK->destroy_kokkos(k_flangevin,flangevin); - if(gjfflag) memoryKK->destroy_kokkos(k_franprev,franprev); - if(gjfflag) memoryKK->destroy_kokkos(k_lv,lv); - memoryKK->destroy_kokkos(k_tforce,tforce); -} - -/* ---------------------------------------------------------------------- */ - -template -void FixLangevinKokkos::init() -{ - FixLangevin::init(); - if(oflag) - error->all(FLERR,"Fix langevin omega is not yet implemented with kokkos"); - if(ascale) - error->all(FLERR,"Fix langevin angmom is not yet implemented with kokkos"); - if(gjfflag && tbiasflag) - error->all(FLERR,"Fix langevin gjf + tbias is not yet implemented with kokkos"); - if(gjfflag && tbiasflag) - error->warning(FLERR,"Fix langevin gjf + kokkos is not implemented with random gaussians"); - - // prefactors are modified in the init - k_gfactor1.template modify(); - k_gfactor2.template modify(); -} - -/* ---------------------------------------------------------------------- */ - -template -void FixLangevinKokkos::grow_arrays(int nmax) -{ - memoryKK->grow_kokkos(k_franprev,franprev,nmax,3,"langevin:franprev"); - d_franprev = k_franprev.template view(); - h_franprev = k_franprev.template view(); - memoryKK->grow_kokkos(k_lv,lv,nmax,3,"langevin:lv"); - d_lv = k_lv.template view(); - h_lv = k_lv.template view(); -} - -/* ---------------------------------------------------------------------- */ - -template -void FixLangevinKokkos::initial_integrate(int vflag) -{ - atomKK->sync(execution_space,datamask_read); - atomKK->modified(execution_space,datamask_modify); - - v = atomKK->k_v.view(); - f = atomKK->k_f.view(); - int nlocal = atomKK->nlocal; - if (igroup == atomKK->firstgroup) nlocal = atomKK->nfirst; - - FixLangevinKokkosInitialIntegrateFunctor functor(this); - Kokkos::parallel_for(nlocal,functor); -} - -template -KOKKOS_INLINE_FUNCTION -void FixLangevinKokkos::initial_integrate_item(int i) const -{ - if (mask[i] & groupbit) { - f(i,0) /= gjfa; - f(i,1) /= gjfa; - f(i,2) /= gjfa; - v(i,0) = d_lv(i,0); - v(i,1) = d_lv(i,1); - v(i,2) = d_lv(i,2); - } -} - -/* ---------------------------------------------------------------------- */ - -template -void FixLangevinKokkos::post_force(int vflag) -{ - // sync the device views which might have been modified on host - atomKK->sync(execution_space,datamask_read); - rmass = atomKK->k_rmass.view(); - f = atomKK->k_f.template view(); - v = atomKK->k_v.template view(); - type = atomKK->k_type.template view(); - mask = atomKK->k_mask.template view(); - - k_gfactor1.template sync(); - k_gfactor2.template sync(); - k_ratio.template sync(); - if(gjfflag) k_franprev.template sync(); - if(gjfflag) k_lv.template sync(); - - boltz = force->boltz; - dt = update->dt; - mvv2e = force->mvv2e; - ftm2v = force->ftm2v; - fran_prop_const = sqrt(24.0*boltz/t_period/dt/mvv2e); - - compute_target(); // modifies tforce vector, hence sync here - k_tforce.template sync(); - - double fsum[3],fsumall[3]; - bigint count; - int nlocal = atomKK->nlocal; - - if (zeroflag) { - fsum[0] = fsum[1] = fsum[2] = 0.0; - count = group->count(igroup); - if (count == 0) - error->all(FLERR,"Cannot zero Langevin force of 0 atoms"); - } - - // reallocate flangevin if necessary - if (tallyflag) { - if (nlocal > maxatom1) { - memoryKK->destroy_kokkos(k_flangevin,flangevin); - maxatom1 = atomKK->nmax; - memoryKK->create_kokkos(k_flangevin,flangevin,maxatom1,3,"langevin:flangevin"); - d_flangevin = k_flangevin.template view(); - h_flangevin = k_flangevin.template view(); - } - } - - // account for bias velocity - if(tbiasflag == BIAS){ - atomKK->sync(temperature->execution_space,temperature->datamask_read); - temperature->compute_scalar(); - temperature->remove_bias_all(); // modifies velocities - // if temeprature compute is kokkosized host-device comm won't be needed - atomKK->modified(temperature->execution_space,temperature->datamask_modify); - atomKK->sync(execution_space,temperature->datamask_modify); - } - - // compute langevin force in parallel on the device - FSUM s_fsum; - if (tstyle == ATOM) - if (gjfflag) - if (tallyflag) - if (tbiasflag == BIAS) - if (rmass.data()) - if (zeroflag) { - FixLangevinKokkosPostForceFunctor post_functor(this); - Kokkos::parallel_reduce(nlocal,post_functor,s_fsum); - } else { - FixLangevinKokkosPostForceFunctor post_functor(this); - Kokkos::parallel_for(nlocal,post_functor); - } - else - if (zeroflag) { - FixLangevinKokkosPostForceFunctor post_functor(this); - Kokkos::parallel_reduce(nlocal,post_functor,s_fsum); - } else { - FixLangevinKokkosPostForceFunctor post_functor(this); - Kokkos::parallel_for(nlocal,post_functor); - } - else - if (rmass.data()) - if (zeroflag) { - FixLangevinKokkosPostForceFunctor post_functor(this); - Kokkos::parallel_reduce(nlocal,post_functor,s_fsum); - } else { - FixLangevinKokkosPostForceFunctor post_functor(this); - Kokkos::parallel_for(nlocal,post_functor); - } - else - if (zeroflag) { - FixLangevinKokkosPostForceFunctor post_functor(this); - Kokkos::parallel_reduce(nlocal,post_functor,s_fsum); - } else { - FixLangevinKokkosPostForceFunctor post_functor(this); - Kokkos::parallel_for(nlocal,post_functor); - } - else - if (tbiasflag == BIAS) - if (rmass.data()) - if (zeroflag) { - FixLangevinKokkosPostForceFunctor post_functor(this); - Kokkos::parallel_reduce(nlocal,post_functor,s_fsum); - } else { - FixLangevinKokkosPostForceFunctor post_functor(this); - Kokkos::parallel_for(nlocal,post_functor); - } - else - if (zeroflag) { - FixLangevinKokkosPostForceFunctor post_functor(this); - Kokkos::parallel_reduce(nlocal,post_functor,s_fsum); - } else { - FixLangevinKokkosPostForceFunctor post_functor(this); - Kokkos::parallel_for(nlocal,post_functor); - } - else - if (rmass.data()) - if (zeroflag) { - FixLangevinKokkosPostForceFunctor post_functor(this); - Kokkos::parallel_reduce(nlocal,post_functor,s_fsum); - } else { - FixLangevinKokkosPostForceFunctor post_functor(this); - Kokkos::parallel_for(nlocal,post_functor); - } - else - if (zeroflag) { - FixLangevinKokkosPostForceFunctor post_functor(this); - Kokkos::parallel_reduce(nlocal,post_functor,s_fsum); - } else { - FixLangevinKokkosPostForceFunctor post_functor(this); - Kokkos::parallel_for(nlocal,post_functor); - } - else - if (tallyflag) - if (tbiasflag == BIAS) - if (rmass.data()) - if (zeroflag) { - FixLangevinKokkosPostForceFunctor post_functor(this); - Kokkos::parallel_reduce(nlocal,post_functor,s_fsum); - } else { - FixLangevinKokkosPostForceFunctor post_functor(this); - Kokkos::parallel_for(nlocal,post_functor); - } - else - if (zeroflag) { - FixLangevinKokkosPostForceFunctor post_functor(this); - Kokkos::parallel_reduce(nlocal,post_functor,s_fsum); - } else { - FixLangevinKokkosPostForceFunctor post_functor(this); - Kokkos::parallel_for(nlocal,post_functor); - } - else - if (rmass.data()) - if (zeroflag) { - FixLangevinKokkosPostForceFunctor post_functor(this); - Kokkos::parallel_reduce(nlocal,post_functor,s_fsum); - } else { - FixLangevinKokkosPostForceFunctor post_functor(this); - Kokkos::parallel_for(nlocal,post_functor); - } - else - if (zeroflag) { - FixLangevinKokkosPostForceFunctor post_functor(this); - Kokkos::parallel_reduce(nlocal,post_functor,s_fsum); - } else { - FixLangevinKokkosPostForceFunctor post_functor(this); - Kokkos::parallel_for(nlocal,post_functor); - } - else - if (tbiasflag == BIAS) - if (rmass.data()) - if (zeroflag) { - FixLangevinKokkosPostForceFunctor post_functor(this); - Kokkos::parallel_reduce(nlocal,post_functor,s_fsum); - } else { - FixLangevinKokkosPostForceFunctor post_functor(this); - Kokkos::parallel_for(nlocal,post_functor); - } - else - if (zeroflag) { - FixLangevinKokkosPostForceFunctor post_functor(this); - Kokkos::parallel_reduce(nlocal,post_functor,s_fsum); - } else { - FixLangevinKokkosPostForceFunctor post_functor(this); - Kokkos::parallel_for(nlocal,post_functor); - } - else - if (rmass.data()) - if (zeroflag) { - FixLangevinKokkosPostForceFunctor post_functor(this); - Kokkos::parallel_reduce(nlocal,post_functor,s_fsum); - } else { - FixLangevinKokkosPostForceFunctor post_functor(this); - Kokkos::parallel_for(nlocal,post_functor); - } - else - if (zeroflag) { - FixLangevinKokkosPostForceFunctor post_functor(this); - Kokkos::parallel_reduce(nlocal,post_functor,s_fsum); - } else { - FixLangevinKokkosPostForceFunctor post_functor(this); - Kokkos::parallel_for(nlocal,post_functor); - } - else - if (gjfflag) - if (tallyflag) - if (tbiasflag == BIAS) - if (rmass.data()) - if (zeroflag) { - FixLangevinKokkosPostForceFunctor post_functor(this); - Kokkos::parallel_reduce(nlocal,post_functor,s_fsum); - } else { - FixLangevinKokkosPostForceFunctor post_functor(this); - Kokkos::parallel_for(nlocal,post_functor); - } - else - if (zeroflag) { - FixLangevinKokkosPostForceFunctor post_functor(this); - Kokkos::parallel_reduce(nlocal,post_functor,s_fsum); - } else { - FixLangevinKokkosPostForceFunctor post_functor(this); - Kokkos::parallel_for(nlocal,post_functor); - } - else - if (rmass.data()) - if (zeroflag) { - FixLangevinKokkosPostForceFunctor post_functor(this); - Kokkos::parallel_reduce(nlocal,post_functor,s_fsum); - } else { - FixLangevinKokkosPostForceFunctor post_functor(this); - Kokkos::parallel_for(nlocal,post_functor); - } - else - if (zeroflag) { - FixLangevinKokkosPostForceFunctor post_functor(this); - Kokkos::parallel_reduce(nlocal,post_functor,s_fsum); - } else { - FixLangevinKokkosPostForceFunctor post_functor(this); - Kokkos::parallel_for(nlocal,post_functor); - } - else - if (tbiasflag == BIAS) - if (rmass.data()) - if (zeroflag) { - FixLangevinKokkosPostForceFunctor post_functor(this); - Kokkos::parallel_reduce(nlocal,post_functor,s_fsum); - } else { - FixLangevinKokkosPostForceFunctor post_functor(this); - Kokkos::parallel_for(nlocal,post_functor); - } - else - if (zeroflag) { - FixLangevinKokkosPostForceFunctor post_functor(this); - Kokkos::parallel_reduce(nlocal,post_functor,s_fsum); - } else { - FixLangevinKokkosPostForceFunctor post_functor(this); - Kokkos::parallel_for(nlocal,post_functor); - } - else - if (rmass.data()) - if (zeroflag) { - FixLangevinKokkosPostForceFunctor post_functor(this); - Kokkos::parallel_reduce(nlocal,post_functor,s_fsum); - } else { - FixLangevinKokkosPostForceFunctor post_functor(this); - Kokkos::parallel_for(nlocal,post_functor); - } - else - if (zeroflag) { - FixLangevinKokkosPostForceFunctor post_functor(this); - Kokkos::parallel_reduce(nlocal,post_functor,s_fsum); - } else { - FixLangevinKokkosPostForceFunctor post_functor(this); - Kokkos::parallel_for(nlocal,post_functor); - } - else - if (tallyflag) - if (tbiasflag == BIAS) - if (rmass.data()) - if (zeroflag) { - FixLangevinKokkosPostForceFunctor post_functor(this); - Kokkos::parallel_reduce(nlocal,post_functor,s_fsum); - } else { - FixLangevinKokkosPostForceFunctor post_functor(this); - Kokkos::parallel_for(nlocal,post_functor); - } - else - if (zeroflag) { - FixLangevinKokkosPostForceFunctor post_functor(this); - Kokkos::parallel_reduce(nlocal,post_functor,s_fsum); - } else { - FixLangevinKokkosPostForceFunctor post_functor(this); - Kokkos::parallel_for(nlocal,post_functor); - } - else - if (rmass.data()) - if (zeroflag) { - FixLangevinKokkosPostForceFunctor post_functor(this); - Kokkos::parallel_reduce(nlocal,post_functor,s_fsum); - } else { - FixLangevinKokkosPostForceFunctor post_functor(this); - Kokkos::parallel_for(nlocal,post_functor); - } - else - if (zeroflag) { - FixLangevinKokkosPostForceFunctor post_functor(this); - Kokkos::parallel_reduce(nlocal,post_functor,s_fsum); - } else { - FixLangevinKokkosPostForceFunctor post_functor(this); - Kokkos::parallel_for(nlocal,post_functor); - } - else - if (tbiasflag == BIAS) - if (rmass.data()) - if (zeroflag) { - FixLangevinKokkosPostForceFunctor post_functor(this); - Kokkos::parallel_reduce(nlocal,post_functor,s_fsum); - } else { - FixLangevinKokkosPostForceFunctor post_functor(this); - Kokkos::parallel_for(nlocal,post_functor); - } - else - if (zeroflag) { - FixLangevinKokkosPostForceFunctor post_functor(this); - Kokkos::parallel_reduce(nlocal,post_functor,s_fsum); - } else { - FixLangevinKokkosPostForceFunctor post_functor(this); - Kokkos::parallel_for(nlocal,post_functor); - } - else - if (rmass.data()) - if (zeroflag) { - FixLangevinKokkosPostForceFunctor post_functor(this); - Kokkos::parallel_reduce(nlocal,post_functor,s_fsum); - } else { - FixLangevinKokkosPostForceFunctor post_functor(this); - Kokkos::parallel_for(nlocal,post_functor); - } - else - if (zeroflag) { - FixLangevinKokkosPostForceFunctor post_functor(this); - Kokkos::parallel_reduce(nlocal,post_functor,s_fsum); - } else { - FixLangevinKokkosPostForceFunctor post_functor(this); - Kokkos::parallel_for(nlocal,post_functor); - } - - - if(tbiasflag == BIAS){ - atomKK->sync(temperature->execution_space,temperature->datamask_read); - temperature->restore_bias_all(); // modifies velocities - atomKK->modified(temperature->execution_space,temperature->datamask_modify); - atomKK->sync(execution_space,temperature->datamask_modify); - } - - // set modify flags for the views modified in post_force functor - if (gjfflag) k_franprev.template modify(); - if (gjfflag) k_lv.template modify(); - if (tallyflag) k_flangevin.template modify(); - - // set total force to zero - if (zeroflag) { - fsum[0] = s_fsum.fx; fsum[1] = s_fsum.fy; fsum[2] = s_fsum.fz; - MPI_Allreduce(fsum,fsumall,3,MPI_DOUBLE,MPI_SUM,world); - h_fsumall(0) = fsumall[0]/count; - h_fsumall(1) = fsumall[1]/count; - h_fsumall(2) = fsumall[2]/count; - k_fsumall.template modify(); - k_fsumall.template sync(); - // set total force zero in parallel on the device - FixLangevinKokkosZeroForceFunctor zero_functor(this); - Kokkos::parallel_for(nlocal,zero_functor); - } - // f is modified by both post_force and zero_force functors - atomKK->modified(execution_space,datamask_modify); - - // thermostat omega and angmom - // if (oflag) omega_thermostat(); - // if (ascale) angmom_thermostat(); - -} - -/* ---------------------------------------------------------------------- */ - -template -template -KOKKOS_INLINE_FUNCTION -FSUM FixLangevinKokkos::post_force_item(int i) const -{ - FSUM fsum; - double fdrag[3],fran[3]; - double gamma1,gamma2; - double fswap; - double tsqrt_t = tsqrt; - - if (mask[i] & groupbit) { - rand_type rand_gen = rand_pool.get_state(); - if(Tp_TSTYLEATOM) tsqrt_t = sqrt(d_tforce[i]); - if(Tp_RMASS){ - gamma1 = -rmass[i] / t_period / ftm2v; - gamma2 = sqrt(rmass[i]) * fran_prop_const / ftm2v; - gamma1 *= 1.0/d_ratio[type[i]]; - gamma2 *= 1.0/sqrt(d_ratio[type[i]]) * tsqrt_t; - } else { - gamma1 = d_gfactor1[type[i]]; - gamma2 = d_gfactor2[type[i]] * tsqrt_t; - } - - fran[0] = gamma2 * (rand_gen.drand() - 0.5); //(random->uniform()-0.5); - fran[1] = gamma2 * (rand_gen.drand() - 0.5); //(random->uniform()-0.5); - fran[2] = gamma2 * (rand_gen.drand() - 0.5); //(random->uniform()-0.5); - - if(Tp_BIAS){ - fdrag[0] = gamma1*v(i,0); - fdrag[1] = gamma1*v(i,1); - fdrag[2] = gamma1*v(i,2); - if (v(i,0) == 0.0) fran[0] = 0.0; - if (v(i,1) == 0.0) fran[1] = 0.0; - if (v(i,2) == 0.0) fran[2] = 0.0; - } else { - fdrag[0] = gamma1*v(i,0); - fdrag[1] = gamma1*v(i,1); - fdrag[2] = gamma1*v(i,2); - } - - if (Tp_GJF) { - d_lv(i,0) = gjfsib*v(i,0); - d_lv(i,1) = gjfsib*v(i,1); - d_lv(i,2) = gjfsib*v(i,2); - - fswap = 0.5*(fran[0]+d_franprev(i,0)); - d_franprev(i,0) = fran[0]; - fran[0] = fswap; - fswap = 0.5*(fran[1]+d_franprev(i,1)); - d_franprev(i,1) = fran[1]; - fran[1] = fswap; - fswap = 0.5*(fran[2]+d_franprev(i,2)); - d_franprev(i,2) = fran[2]; - fran[2] = fswap; - - fdrag[0] *= gjfa; - fdrag[1] *= gjfa; - fdrag[2] *= gjfa; - fran[0] *= gjfa; - fran[1] *= gjfa; - fran[2] *= gjfa; - f(i,0) *= gjfa; - f(i,1) *= gjfa; - f(i,2) *= gjfa; - } - - f(i,0) += fdrag[0] + fran[0]; - f(i,1) += fdrag[1] + fran[1]; - f(i,2) += fdrag[2] + fran[2]; - - if (Tp_TALLY) { - if (Tp_GJF){ - fdrag[0] = gamma1*d_lv(i,0)/gjfsib/gjfsib; - fdrag[1] = gamma1*d_lv(i,1)/gjfsib/gjfsib; - fdrag[2] = gamma1*d_lv(i,2)/gjfsib/gjfsib; - fswap = (2*fran[0]/gjfa - d_franprev(i,0))/gjfsib; - fran[0] = fswap; - fswap = (2*fran[1]/gjfa - d_franprev(i,1))/gjfsib; - fran[1] = fswap; - fswap = (2*fran[2]/gjfa - d_franprev(i,2))/gjfsib; - fran[2] = fswap; - } - d_flangevin(i,0) = fdrag[0] + fran[0]; - d_flangevin(i,1) = fdrag[1] + fran[1]; - d_flangevin(i,2) = fdrag[2] + fran[2]; - } - - if (Tp_ZERO) { - fsum.fx = fran[0]; - fsum.fy = fran[1]; - fsum.fz = fran[2]; - } - rand_pool.free_state(rand_gen); - } - - return fsum; -} - -/* ---------------------------------------------------------------------- */ - -template -KOKKOS_INLINE_FUNCTION -void FixLangevinKokkos::zero_force_item(int i) const -{ - if (mask[i] & groupbit) { - f(i,0) -= d_fsumall[0]; - f(i,1) -= d_fsumall[1]; - f(i,2) -= d_fsumall[2]; - } - -} - -/* ---------------------------------------------------------------------- - set current t_target and t_sqrt - ------------------------------------------------------------------------- */ - -template -void FixLangevinKokkos::compute_target() -{ - atomKK->sync(Host, MASK_MASK); - mask = atomKK->k_mask.template view(); - int nlocal = atomKK->nlocal; - - double delta = update->ntimestep - update->beginstep; - if (delta != 0.0) delta /= update->endstep - update->beginstep; - - // if variable temp, evaluate variable, wrap with clear/add - // reallocate tforce array if necessary - - if (tstyle == CONSTANT) { - t_target = t_start + delta * (t_stop-t_start); - tsqrt = sqrt(t_target); - } else { - modify->clearstep_compute(); - if (tstyle == EQUAL) { - t_target = input->variable->compute_equal(tvar); - if (t_target < 0.0) - error->one(FLERR,"Fix langevin variable returned negative temperature"); - tsqrt = sqrt(t_target); - } else { - if (atom->nmax > maxatom2) { - maxatom2 = atom->nmax; - memoryKK->destroy_kokkos(k_tforce,tforce); - memoryKK->create_kokkos(k_tforce,tforce,maxatom2,"langevin:tforce"); - d_tforce = k_tforce.template view(); - h_tforce = k_tforce.template view(); - } - input->variable->compute_atom(tvar,igroup,tforce,1,0); // tforce is modified on host - k_tforce.template modify(); - for (int i = 0; i < nlocal; i++) - if (mask[i] & groupbit) - if (h_tforce[i] < 0.0) - error->one(FLERR, - "Fix langevin variable returned negative temperature"); - } - modify->addstep_compute(update->ntimestep + 1); - } -} - -/* ---------------------------------------------------------------------- */ - -template -void FixLangevinKokkos::reset_dt() -{ - if (atomKK->mass) { - for (int i = 1; i <= atomKK->ntypes; i++) { - h_gfactor2[i] = sqrt(atomKK->mass[i]) * - sqrt(24.0*force->boltz/t_period/update->dt/force->mvv2e) / - force->ftm2v; - h_gfactor2[i] *= 1.0/sqrt(h_ratio[i]); - } - k_gfactor2.template modify(); - } - -} - -/* ---------------------------------------------------------------------- */ - -template -double FixLangevinKokkos::compute_scalar() -{ - if (!tallyflag || flangevin == NULL) return 0.0; - - v = atomKK->k_v.template view(); - mask = atomKK->k_mask.template view(); - - // capture the very first energy transfer to thermal reservoir - - if (update->ntimestep == update->beginstep) { - energy_onestep = 0.0; - atomKK->sync(execution_space,V_MASK | MASK_MASK); - int nlocal = atomKK->nlocal; - k_flangevin.template sync(); - FixLangevinKokkosTallyEnergyFunctor scalar_functor(this); - Kokkos::parallel_reduce(nlocal,scalar_functor,energy_onestep); - energy = 0.5*energy_onestep*update->dt; - } - - // convert midstep energy back to previous fullstep energy - double energy_me = energy - 0.5*energy_onestep*update->dt; - double energy_all; - MPI_Allreduce(&energy_me,&energy_all,1,MPI_DOUBLE,MPI_SUM,world); - return -energy_all; -} - -/* ---------------------------------------------------------------------- */ - -template -KOKKOS_INLINE_FUNCTION -double FixLangevinKokkos::compute_energy_item(int i) const -{ - double energy; - if (mask[i] & groupbit) - energy = d_flangevin(i,0)*v(i,0) + d_flangevin(i,1)*v(i,1) + - d_flangevin(i,2)*v(i,2); - return energy; -} - -/* ---------------------------------------------------------------------- - tally energy transfer to thermal reservoir - ------------------------------------------------------------------------- */ - -template -void FixLangevinKokkos::end_of_step() -{ - if (!tallyflag && !gjfflag) return; - - v = atomKK->k_v.template view(); - f = atomKK->k_f.template view(); - mask = atomKK->k_mask.template view(); - - atomKK->sync(execution_space,V_MASK | MASK_MASK); - int nlocal = atomKK->nlocal; - - energy_onestep = 0.0; - - k_flangevin.template sync(); - FixLangevinKokkosTallyEnergyFunctor tally_functor(this); - Kokkos::parallel_reduce(nlocal,tally_functor,energy_onestep); - - if (gjfflag){ - if (rmass.data()) { - FixLangevinKokkosEndOfStepFunctor functor(this); - Kokkos::parallel_for(nlocal,functor); - } else { - mass = atomKK->k_mass.view(); - FixLangevinKokkosEndOfStepFunctor functor(this); - Kokkos::parallel_for(nlocal,functor); - } - } - - energy += energy_onestep*update->dt; -} - -template -KOKKOS_INLINE_FUNCTION -void FixLangevinKokkos::end_of_step_item(int i) const { - double tmp[3]; - if (mask[i] & groupbit) { - const double dtfm = force->ftm2v * 0.5 * dt / mass[type[i]]; - tmp[0] = v(i,0); - tmp[1] = v(i,1); - tmp[2] = v(i,2); - if (!fsflag){ - v(i,0) = d_lv(i,0); - v(i,1) = d_lv(i,1); - v(i,2) = d_lv(i,2); - } else { - v(i,0) = 0.5 * gjfsib * gjfsib * (v(i,0) + dtfm * f(i,0) / gjfa) + - dtfm * 0.5 * (gjfsib * d_flangevin(i,0) - d_franprev(i,0)) + - (gjfsib * gjfa * 0.5 + dt * 0.25 / t_period / gjfsib) * d_lv(i,0); - v(i,1) = 0.5 * gjfsib * gjfsib * (v(i,1) + dtfm * f(i,1) / gjfa) + - dtfm * 0.5 * (gjfsib * d_flangevin(i,0) - d_franprev(i,1)) + - (gjfsib * gjfa * 0.5 + dt * 0.25 / t_period / gjfsib) * d_lv(i,1); - v(i,2) = 0.5 * gjfsib * gjfsib * (v(i,2) + dtfm * f(i,2) / gjfa) + - dtfm * 0.5 * (gjfsib * d_flangevin(i,0) - d_franprev(i,2)) + - (gjfsib * gjfa * 0.5 + dt * 0.25 / t_period / gjfsib) * d_lv(i,2); - } - d_lv(i,0) = tmp[0]; - d_lv(i,1) = tmp[1]; - d_lv(i,2) = tmp[2]; - } -} - -template -KOKKOS_INLINE_FUNCTION -void FixLangevinKokkos::end_of_step_rmass_item(int i) const -{ - double tmp[3]; - if (mask[i] & groupbit) { - const double dtfm = force->ftm2v * 0.5 * dt / rmass[i]; - tmp[0] = v(i,0); - tmp[1] = v(i,1); - tmp[2] = v(i,2); - if (!fsflag){ - v(i,0) = d_lv(i,0); - v(i,1) = d_lv(i,1); - v(i,2) = d_lv(i,2); - } else { - v(i,0) = 0.5 * gjfsib * gjfsib * (v(i,0) + dtfm * f(i,0) / gjfa) + - dtfm * 0.5 * (gjfsib * d_flangevin(i,0) - d_franprev(i,0)) + - (gjfsib * gjfa * 0.5 + dt * 0.25 / t_period / gjfsib) * d_lv(i,0); - v(i,1) = 0.5 * gjfsib * gjfsib * (v(i,1) + dtfm * f(i,1) / gjfa) + - dtfm * 0.5 * (gjfsib * d_flangevin(i,1) - d_franprev(i,1)) + - (gjfsib * gjfa * 0.5 + dt * 0.25 / t_period / gjfsib) * d_lv(i,1); - v(i,2) = 0.5 * gjfsib * gjfsib * (v(i,2) + dtfm * f(i,2) / gjfa) + - dtfm * 0.5 * (gjfsib * d_flangevin(i,2) - d_franprev(i,2)) + - (gjfsib * gjfa * 0.5 + dt * 0.25 / t_period / gjfsib) * d_lv(i,2); - } - d_lv(i,0) = tmp[0]; - d_lv(i,1) = tmp[1]; - d_lv(i,2) = tmp[2]; - } -} - -/* ---------------------------------------------------------------------- - copy values within local atom-based array - ------------------------------------------------------------------------- */ - -template -void FixLangevinKokkos::copy_arrays(int i, int j, int delflag) -{ - h_franprev(j,0) = h_franprev(i,0); - h_franprev(j,1) = h_franprev(i,1); - h_franprev(j,2) = h_franprev(i,2); - h_lv(j,0) = h_lv(i,0); - h_lv(j,1) = h_lv(i,1); - h_lv(j,2) = h_lv(i,2); - - k_franprev.template modify(); - k_lv.template modify(); - -} - -/* ---------------------------------------------------------------------- */ - -template -void FixLangevinKokkos::cleanup_copy() -{ - random = NULL; - tstr = NULL; - gfactor1 = NULL; - gfactor2 = NULL; - ratio = NULL; - id_temp = NULL; - flangevin = NULL; - tforce = NULL; - gjfflag = 0; - franprev = NULL; - lv = NULL; - id = style = NULL; - vatom = NULL; -} - -namespace LAMMPS_NS { -template class FixLangevinKokkos; -#ifdef KOKKOS_ENABLE_CUDA -template class FixLangevinKokkos; -#endif -} - diff --git a/fix_langevin_kokkos.h b/fix_langevin_kokkos.h deleted file mode 100644 index a6d467dfd7..0000000000 --- a/fix_langevin_kokkos.h +++ /dev/null @@ -1,293 +0,0 @@ -/* -*- c++ -*- ---------------------------------------------------------- - LAMMPS - Large-scale Atomic/Molecular Massively Parallel Simulator - http://lammps.sandia.gov, Sandia National Laboratories - Steve Plimpton, sjplimp@sandia.gov - - Copyright (2003) Sandia Corporation. Under the terms of Contract - DE-AC04-94AL85000 with Sandia Corporation, the U.S. Government retains - certain rights in this software. This software is distributed under - the GNU General Public License. - - See the README file in the top-level LAMMPS directory. - ------------------------------------------------------------------------- */ - -#ifdef FIX_CLASS - -FixStyle(langevin/kk,FixLangevinKokkos) -FixStyle(langevin/kk/device,FixLangevinKokkos) -FixStyle(langevin/kk/host,FixLangevinKokkos) - -#else - -#ifndef LMP_FIX_LANGEVIN_KOKKOS_H -#define LMP_FIX_LANGEVIN_KOKKOS_H - -#include "fix_langevin.h" -#include "kokkos_type.h" -#include "Kokkos_Random.hpp" -#include "comm_kokkos.h" - -namespace LAMMPS_NS { - - struct s_FSUM { - double fx, fy, fz; - KOKKOS_INLINE_FUNCTION - s_FSUM() { - fx = fy = fz = 0.0; - } - KOKKOS_INLINE_FUNCTION - s_FSUM& operator+=(const s_FSUM &rhs){ - fx += rhs.fx; - fy += rhs.fy; - fz += rhs.fz; - return *this; - } - - KOKKOS_INLINE_FUNCTION - volatile s_FSUM& operator+=(const volatile s_FSUM &rhs) volatile { - fx += rhs.fx; - fy += rhs.fy; - fz += rhs.fz; - return *this; - } - }; - typedef s_FSUM FSUM; - - template - class FixLangevinKokkos; - - template - class FixLangevinKokkosInitialIntegrateFunctor; - - template - class FixLangevinKokkosPostForceFunctor; - - template class FixLangevinKokkosZeroForceFunctor; - - template class FixLangevinKokkosTallyEnergyFunctor; - - template - class FixLangevinKokkos : public FixLangevin { - public: - FixLangevinKokkos(class LAMMPS *, int, char **); - ~FixLangevinKokkos(); - - void cleanup_copy(); - void init(); - void initial_integrate(int); - void post_force(int); - void reset_dt(); - void grow_arrays(int); - void copy_arrays(int i, int j, int delflag); - double compute_scalar(); - void end_of_step(); - - KOKKOS_INLINE_FUNCTION - void initial_integrate_item(int) const; - - KOKKOS_INLINE_FUNCTION - void initial_integrate_rmass_item(int) const; - - template - KOKKOS_INLINE_FUNCTION - FSUM post_force_item(int) const; - - KOKKOS_INLINE_FUNCTION - void zero_force_item(int) const; - - KOKKOS_INLINE_FUNCTION - double compute_energy_item(int) const; - - KOKKOS_INLINE_FUNCTION - void end_of_step_item(int) const; - - KOKKOS_INLINE_FUNCTION - void end_of_step_rmass_item(int) const; - - private: - class CommKokkos *commKK; - - typename ArrayTypes::t_float_1d rmass; - typename ArrayTypes::t_float_1d mass; - typename ArrayTypes::tdual_double_2d k_franprev; - typename ArrayTypes::t_double_2d d_franprev; - HAT::t_double_2d h_franprev; - - typename ArrayTypes::tdual_double_2d k_lv; - typename ArrayTypes::t_double_2d d_lv; - HAT::t_double_2d h_lv; - - typename ArrayTypes::tdual_double_2d k_flangevin; - typename ArrayTypes::t_double_2d d_flangevin; - HAT::t_double_2d h_flangevin; - - typename ArrayTypes::tdual_double_1d k_tforce; - typename ArrayTypes::t_double_1d d_tforce; - HAT::t_double_1d h_tforce; - - typename ArrayTypes::t_v_array v; - typename ArrayTypes::t_f_array f; - typename ArrayTypes::t_int_1d type; - typename ArrayTypes::t_int_1d mask; - - typename ArrayTypes::tdual_double_1d k_gfactor1, k_gfactor2, k_ratio; - typename ArrayTypes::t_double_1d d_gfactor1, d_gfactor2, d_ratio; - HAT::t_double_1d h_gfactor1, h_gfactor2, h_ratio; - - typedef Kokkos::DualView - tdual_double_1d_3n; - tdual_double_1d_3n k_fsumall; - typename tdual_double_1d_3n::t_dev d_fsumall; - typename tdual_double_1d_3n::t_host h_fsumall; - - double boltz,dt,mvv2e,ftm2v,fran_prop_const; - - void compute_target(); - - Kokkos::Random_XorShift64_Pool rand_pool; - typedef typename Kokkos::Random_XorShift64_Pool::generator_type rand_type; - - }; - - template - struct FixLangevinKokkosInitialIntegrateFunctor { - typedef DeviceType device_type ; - FixLangevinKokkos c; - - FixLangevinKokkosInitialIntegrateFunctor(FixLangevinKokkos* c_ptr): - c(*c_ptr) {c.cleanup_copy();}; - - KOKKOS_INLINE_FUNCTION - void operator()(const int i) const { - c.initial_integrate_item(i); - } - }; - - - template - struct FixLangevinKokkosPostForceFunctor { - - typedef DeviceType device_type; - typedef FSUM value_type; - FixLangevinKokkos c; - - FixLangevinKokkosPostForceFunctor(FixLangevinKokkos* c_ptr): - c(*c_ptr) {} - ~FixLangevinKokkosPostForceFunctor(){c.cleanup_copy();} - - KOKKOS_INLINE_FUNCTION - void operator()(const int i) const { - c.template post_force_item(i); - } - - KOKKOS_INLINE_FUNCTION - void operator()(const int i, value_type &fsum) const { - - fsum += c.template post_force_item(i); - } - - KOKKOS_INLINE_FUNCTION - static void init(volatile value_type &update) { - update.fx = 0.0; - update.fy = 0.0; - update.fz = 0.0; - } - KOKKOS_INLINE_FUNCTION - static void join(volatile value_type &update, - const volatile value_type &source) { - update.fx += source.fx; - update.fy += source.fy; - update.fz += source.fz; - } - - }; - - template - struct FixLangevinKokkosZeroForceFunctor { - typedef DeviceType device_type ; - FixLangevinKokkos c; - - FixLangevinKokkosZeroForceFunctor(FixLangevinKokkos* c_ptr): - c(*c_ptr) {c.cleanup_copy();} - - KOKKOS_INLINE_FUNCTION - void operator()(const int i) const { - c.zero_force_item(i); - } - }; - - template - struct FixLangevinKokkosTallyEnergyFunctor { - typedef DeviceType device_type ; - FixLangevinKokkos c; - typedef double value_type; - FixLangevinKokkosTallyEnergyFunctor(FixLangevinKokkos* c_ptr): - c(*c_ptr) {c.cleanup_copy();} - - KOKKOS_INLINE_FUNCTION - void operator()(const int i, value_type &energy) const { - energy += c.compute_energy_item(i); - } - KOKKOS_INLINE_FUNCTION - static void init(volatile value_type &update) { - update = 0.0; - } - KOKKOS_INLINE_FUNCTION - static void join(volatile value_type &update, - const volatile value_type &source) { - update += source; - } - }; - - template - struct FixLangevinKokkosEndOfStepFunctor { - typedef DeviceType device_type ; - FixLangevinKokkos c; - - FixLangevinKokkosEndOfStepFunctor(FixLangevinKokkos* c_ptr): - c(*c_ptr) {c.cleanup_copy();} - - KOKKOS_INLINE_FUNCTION - void operator()(const int i) const { - if (RMass) c.end_of_step_rmass_item(i); - else c.end_of_step_item(i); - } - }; -} - -#endif -#endif - -/* ERROR/WARNING messages: - -E: Fix langevin omega is not yet implemented with kokkos - -This option is not yet available. - -E: Fix langevin angmom is not yet implemented with kokkos - -This option is not yet available. - -E: Cannot zero Langevin force of 0 atoms - -The group has zero atoms, so you cannot request its force -be zeroed. - -E: Fix langevin variable returned negative temperature - -Self-explanatory. - -E: Fix langevin gjf with tbias is not yet implemented with kokkos - -This option is not yet available. - -W: Fix langevin gjf using random gaussians is not implemented with kokkos - -This will most likely cause errors in kinetic fluctuations. - -*/ diff --git a/src/KOKKOS/fix_langevin_kokkos.cpp b/src/KOKKOS/fix_langevin_kokkos.cpp index 8ec51ffa71..0618631581 100644 --- a/src/KOKKOS/fix_langevin_kokkos.cpp +++ b/src/KOKKOS/fix_langevin_kokkos.cpp @@ -11,23 +11,20 @@ See the README file in the top-level LAMMPS directory. ------------------------------------------------------------------------- */ -#include -#include -#include #include "fix_langevin_kokkos.h" +#include #include "atom_masks.h" #include "atom_kokkos.h" #include "force.h" +#include "group.h" #include "update.h" -#include "respa.h" #include "error.h" #include "memory_kokkos.h" -#include "group.h" -#include "random_mars.h" #include "compute.h" #include "comm.h" #include "modify.h" #include "input.h" +#include "region.h" #include "variable.h" using namespace LAMMPS_NS; @@ -117,8 +114,7 @@ void FixLangevinKokkos::init() if(gjfflag && tbiasflag) error->all(FLERR,"Fix langevin gjf + tbias is not yet implemented with kokkos"); if(gjfflag && tbiasflag) - error->warning(FLERR,"Fix langevin gjf + kokkos is not implemented with random gaussians," - " this may cause errors in kinetic fluctuations"); + error->warning(FLERR,"Fix langevin gjf + kokkos is not implemented with random gaussians"); // prefactors are modified in the init k_gfactor1.template modify(); @@ -138,9 +134,7 @@ void FixLangevinKokkos::grow_arrays(int nmax) h_lv = k_lv.template view(); } -/* ---------------------------------------------------------------------- - allow for both per-type and per-atom mass -------------------------------------------------------------------------- */ +/* ---------------------------------------------------------------------- */ template void FixLangevinKokkos::initial_integrate(int vflag) diff --git a/src/KOKKOS/fix_langevin_kokkos.h b/src/KOKKOS/fix_langevin_kokkos.h index 4d27b34a7e..a6d467dfd7 100644 --- a/src/KOKKOS/fix_langevin_kokkos.h +++ b/src/KOKKOS/fix_langevin_kokkos.h @@ -282,4 +282,12 @@ E: Fix langevin variable returned negative temperature Self-explanatory. +E: Fix langevin gjf with tbias is not yet implemented with kokkos + +This option is not yet available. + +W: Fix langevin gjf using random gaussians is not implemented with kokkos + +This will most likely cause errors in kinetic fluctuations. + */ From 971f4763e3fbbba60ac8b0dcc494e171dea001ee Mon Sep 17 00:00:00 2001 From: charlie sievers Date: Mon, 16 Sep 2019 16:36:50 -0700 Subject: [PATCH 143/192] removed text referencing removed graphs --- doc/src/fix_langevin.txt | 1 - 1 file changed, 1 deletion(-) diff --git a/doc/src/fix_langevin.txt b/doc/src/fix_langevin.txt index 8dd143bdb7..0aa65be0f5 100644 --- a/doc/src/fix_langevin.txt +++ b/doc/src/fix_langevin.txt @@ -260,7 +260,6 @@ recall that while the equilibrium statistics is appropriately sampled, the corre of the trajectories may not be for large time steps, as is the case for all thermostats. All thermostats provide good statistics and dynamics for small time steps. The 2GJ half-step velocity {vhalf} samples the correct velocity distribution for the {gjf} trajectory. -Results of simulations using the {gjf} option with both {vfull} and {vhalf} compared to other available thermostats are shown in the LAMMPS directory: examples/gjf. This updated implementation of the {gjf} thermostat includes the choice between From 66ddcd86a31e85b0f4f569dd27a7911755857448 Mon Sep 17 00:00:00 2001 From: Michael Brown Date: Tue, 17 Sep 2019 02:50:37 -0700 Subject: [PATCH 144/192] USER-INTEL: Explictly disabling G2S opts to improve lj/cut, eam, and dpd performance. Removing -fno-alias flag from Makefiles due to issues with 2019 compilers and adding explicit _noalias qualifier for some variables to compensate. --- src/MAKE/OPTIONS/Makefile.intel_cpu | 2 +- src/MAKE/OPTIONS/Makefile.intel_cpu_intelmpi | 2 +- src/MAKE/OPTIONS/Makefile.intel_cpu_mpich | 2 +- src/MAKE/OPTIONS/Makefile.intel_cpu_openmpi | 2 +- src/MAKE/OPTIONS/Makefile.knl | 2 +- src/USER-INTEL/npair_full_bin_ghost_intel.cpp | 12 ++++++------ src/USER-INTEL/npair_intel.cpp | 10 +++++----- src/USER-INTEL/pair_dpd_intel.cpp | 2 +- src/USER-INTEL/pair_eam_intel.cpp | 10 +++++----- src/USER-INTEL/pair_lj_cut_intel.cpp | 2 +- 10 files changed, 23 insertions(+), 23 deletions(-) diff --git a/src/MAKE/OPTIONS/Makefile.intel_cpu b/src/MAKE/OPTIONS/Makefile.intel_cpu index 831b16d854..c2691b8cdb 100644 --- a/src/MAKE/OPTIONS/Makefile.intel_cpu +++ b/src/MAKE/OPTIONS/Makefile.intel_cpu @@ -9,7 +9,7 @@ SHELL = /bin/sh CC = mpiicpc OPTFLAGS = -xHost -O2 -fp-model fast=2 -no-prec-div -qoverride-limits \ -qopt-zmm-usage=high -CCFLAGS = -qopenmp -qno-offload -fno-alias -ansi-alias -restrict \ +CCFLAGS = -qopenmp -qno-offload -ansi-alias -restrict \ -DLMP_INTEL_USELRT -DLMP_USE_MKL_RNG $(OPTFLAGS) SHFLAGS = -fPIC DEPFLAGS = -M diff --git a/src/MAKE/OPTIONS/Makefile.intel_cpu_intelmpi b/src/MAKE/OPTIONS/Makefile.intel_cpu_intelmpi index 926518f354..90f5ff9e3d 100644 --- a/src/MAKE/OPTIONS/Makefile.intel_cpu_intelmpi +++ b/src/MAKE/OPTIONS/Makefile.intel_cpu_intelmpi @@ -9,7 +9,7 @@ SHELL = /bin/sh CC = mpiicpc OPTFLAGS = -xHost -O2 -fp-model fast=2 -no-prec-div -qoverride-limits \ -qopt-zmm-usage=high -CCFLAGS = -qopenmp -qno-offload -fno-alias -ansi-alias -restrict \ +CCFLAGS = -qopenmp -qno-offload -ansi-alias -restrict \ -DLMP_INTEL_USELRT -DLMP_USE_MKL_RNG $(OPTFLAGS) SHFLAGS = -fPIC DEPFLAGS = -M diff --git a/src/MAKE/OPTIONS/Makefile.intel_cpu_mpich b/src/MAKE/OPTIONS/Makefile.intel_cpu_mpich index 61934b69b4..21e481d377 100644 --- a/src/MAKE/OPTIONS/Makefile.intel_cpu_mpich +++ b/src/MAKE/OPTIONS/Makefile.intel_cpu_mpich @@ -9,7 +9,7 @@ SHELL = /bin/sh CC = mpicxx -cxx=icc OPTFLAGS = -xHost -O2 -fp-model fast=2 -no-prec-div -qoverride-limits \ -qopt-zmm-usage=high -CCFLAGS = -qopenmp -qno-offload -fno-alias -ansi-alias -restrict \ +CCFLAGS = -qopenmp -qno-offload -ansi-alias -restrict \ -DLMP_INTEL_USELRT -DLMP_USE_MKL_RNG $(OPTFLAGS) SHFLAGS = -fPIC DEPFLAGS = -M diff --git a/src/MAKE/OPTIONS/Makefile.intel_cpu_openmpi b/src/MAKE/OPTIONS/Makefile.intel_cpu_openmpi index ee26443f7d..9cbb8e3344 100644 --- a/src/MAKE/OPTIONS/Makefile.intel_cpu_openmpi +++ b/src/MAKE/OPTIONS/Makefile.intel_cpu_openmpi @@ -10,7 +10,7 @@ export OMPI_CXX = icc CC = mpicxx OPTFLAGS = -xHost -O2 -fp-model fast=2 -no-prec-div -qoverride-limits \ -qopt-zmm-usage=high -CCFLAGS = -qopenmp -qno-offload -fno-alias -ansi-alias -restrict \ +CCFLAGS = -qopenmp -qno-offload -ansi-alias -restrict \ -DLMP_INTEL_USELRT -DLMP_USE_MKL_RNG $(OPTFLAGS) SHFLAGS = -fPIC DEPFLAGS = -M diff --git a/src/MAKE/OPTIONS/Makefile.knl b/src/MAKE/OPTIONS/Makefile.knl index 8e266a4fce..c8536a7258 100644 --- a/src/MAKE/OPTIONS/Makefile.knl +++ b/src/MAKE/OPTIONS/Makefile.knl @@ -8,7 +8,7 @@ SHELL = /bin/sh CC = mpiicpc OPTFLAGS = -xMIC-AVX512 -O2 -fp-model fast=2 -no-prec-div -qoverride-limits -CCFLAGS = -qopenmp -qno-offload -fno-alias -ansi-alias -restrict \ +CCFLAGS = -qopenmp -qno-offload -ansi-alias -restrict \ -DLMP_INTEL_USELRT -DLMP_USE_MKL_RNG $(OPTFLAGS) SHFLAGS = -fPIC DEPFLAGS = -M diff --git a/src/USER-INTEL/npair_full_bin_ghost_intel.cpp b/src/USER-INTEL/npair_full_bin_ghost_intel.cpp index e1e09fd3da..00b032d495 100644 --- a/src/USER-INTEL/npair_full_bin_ghost_intel.cpp +++ b/src/USER-INTEL/npair_full_bin_ghost_intel.cpp @@ -150,8 +150,8 @@ void NPairFullBinGhostIntel::fbi(const int offload, NeighList * list, const int nlocal = atom->nlocal; #ifndef _LMP_INTEL_OFFLOAD - int * const mask = atom->mask; - tagint * const molecule = atom->molecule; + int * _noalias const mask = atom->mask; + tagint * _noalias const molecule = atom->molecule; #endif int moltemplate; @@ -162,7 +162,7 @@ void NPairFullBinGhostIntel::fbi(const int offload, NeighList * list, "Can't use moltemplate with npair style full/bin/ghost/intel."); int tnum; - int *overflow; + int * _noalias overflow; #ifdef _LMP_INTEL_OFFLOAD double *timer_compute; if (offload) { @@ -200,7 +200,7 @@ void NPairFullBinGhostIntel::fbi(const int offload, NeighList * list, const int mbinx = this->mbinx; const int mbiny = this->mbiny; const int mbinz = this->mbinz; - const int * const stencilxyz = &this->stencilxyz[0][0]; + const int * _noalias const stencilxyz = &this->stencilxyz[0][0]; int sb = 1; if (special_flag[1] == 0) { @@ -295,7 +295,7 @@ void NPairFullBinGhostIntel::fbi(const int offload, NeighList * list, int pack_offset = maxnbors; int ct = (ifrom + tid * 2) * maxnbors; - int *neighptr = intel_list + ct; + int * _noalias neighptr = intel_list + ct; const int obound = pack_offset + maxnbors * 2; const int toffs = tid * ncache_stride; @@ -370,7 +370,7 @@ void NPairFullBinGhostIntel::fbi(const int offload, NeighList * list, int n = maxnbors; int n2 = n * 2; - int *neighptr2 = neighptr; + int * _noalias neighptr2 = neighptr; const flt_t * _noalias cutsq; if (i < nlocal) cutsq = cutneighsq; else cutsq = cutneighghostsq; diff --git a/src/USER-INTEL/npair_intel.cpp b/src/USER-INTEL/npair_intel.cpp index ad9ec6e7d3..a82d3f29e5 100644 --- a/src/USER-INTEL/npair_intel.cpp +++ b/src/USER-INTEL/npair_intel.cpp @@ -154,12 +154,12 @@ void NPairIntel::bin_newton(const int offload, NeighList *list, const int nlocal = atom->nlocal; #ifndef _LMP_INTEL_OFFLOAD - int * const mask = atom->mask; - tagint * const molecule = atom->molecule; + int * _noalias const mask = atom->mask; + tagint * _noalias const molecule = atom->molecule; #endif int tnum; - int *overflow; + int * _noalias overflow; #ifdef _LMP_INTEL_OFFLOAD double *timer_compute; if (offload) { @@ -298,8 +298,8 @@ void NPairIntel::bin_newton(const int offload, NeighList *list, const int obound = maxnbors * 3; #endif int ct = (ifrom + tid * 2) * maxnbors; - int *neighptr = intel_list + ct; - int *neighptr2; + int * _noalias neighptr = intel_list + ct; + int * _noalias neighptr2; if (THREE) neighptr2 = neighptr; const int toffs = tid * ncache_stride; diff --git a/src/USER-INTEL/pair_dpd_intel.cpp b/src/USER-INTEL/pair_dpd_intel.cpp index 4ebdce9a96..690496d546 100644 --- a/src/USER-INTEL/pair_dpd_intel.cpp +++ b/src/USER-INTEL/pair_dpd_intel.cpp @@ -283,7 +283,7 @@ void PairDPDIntel::eval(const int offload, const int vflag, } #if defined(LMP_SIMD_COMPILER) - #pragma vector aligned + #pragma vector aligned nog2s #pragma simd reduction(+:fxtmp, fytmp, fztmp, fwtmp, sevdwl, \ sv0, sv1, sv2, sv3, sv4, sv5) #endif diff --git a/src/USER-INTEL/pair_eam_intel.cpp b/src/USER-INTEL/pair_eam_intel.cpp index 32d7e74cbc..984823f07e 100644 --- a/src/USER-INTEL/pair_eam_intel.cpp +++ b/src/USER-INTEL/pair_eam_intel.cpp @@ -305,7 +305,7 @@ void PairEAMIntel::eval(const int offload, const int vflag, acc_t rhoi = (acc_t)0.0; int ej = 0; #if defined(LMP_SIMD_COMPILER) - #pragma vector aligned + #pragma vector aligned nog2s #pragma ivdep #endif for (int jj = 0; jj < jnum; jj++) { @@ -324,7 +324,7 @@ void PairEAMIntel::eval(const int offload, const int vflag, } #if defined(LMP_SIMD_COMPILER) - #pragma vector aligned + #pragma vector aligned nog2s #pragma simd reduction(+:rhoi) #endif for (int jj = 0; jj < ej; jj++) { @@ -411,7 +411,7 @@ void PairEAMIntel::eval(const int offload, const int vflag, if (EFLAG) tevdwl = (acc_t)0.0; #if defined(LMP_SIMD_COMPILER) - #pragma vector aligned + #pragma vector aligned nog2s #pragma simd reduction(+:tevdwl) #endif for (int ii = iifrom; ii < iito; ++ii) { @@ -485,7 +485,7 @@ void PairEAMIntel::eval(const int offload, const int vflag, int ej = 0; #if defined(LMP_SIMD_COMPILER) - #pragma vector aligned + #pragma vector aligned nog2s #pragma ivdep #endif for (int jj = 0; jj < jnum; jj++) { @@ -507,7 +507,7 @@ void PairEAMIntel::eval(const int offload, const int vflag, } #if defined(LMP_SIMD_COMPILER) - #pragma vector aligned + #pragma vector aligned nog2s #pragma simd reduction(+:fxtmp, fytmp, fztmp, fwtmp, sevdwl, \ sv0, sv1, sv2, sv3, sv4, sv5) #endif diff --git a/src/USER-INTEL/pair_lj_cut_intel.cpp b/src/USER-INTEL/pair_lj_cut_intel.cpp index 39db9c7333..f6f83b752a 100644 --- a/src/USER-INTEL/pair_lj_cut_intel.cpp +++ b/src/USER-INTEL/pair_lj_cut_intel.cpp @@ -236,7 +236,7 @@ void PairLJCutIntel::eval(const int offload, const int vflag, if (vflag==1) sv0 = sv1 = sv2 = sv3 = sv4 = sv5 = (acc_t)0; #if defined(LMP_SIMD_COMPILER) - #pragma vector aligned + #pragma vector aligned nog2s #pragma simd reduction(+:fxtmp, fytmp, fztmp, fwtmp, sevdwl, \ sv0, sv1, sv2, sv3, sv4, sv5) #endif From 3e4f1d1cb8e088a61e2b04bfd7b959275193f1cf Mon Sep 17 00:00:00 2001 From: Axel Kohlmeyer Date: Tue, 17 Sep 2019 08:02:30 -0400 Subject: [PATCH 145/192] replace tabs --- doc/src/Build_basics.txt | 18 +++++++++--------- doc/src/Build_extras.txt | 10 +++++----- 2 files changed, 14 insertions(+), 14 deletions(-) diff --git a/doc/src/Build_basics.txt b/doc/src/Build_basics.txt index 04e11009af..cde1055419 100644 --- a/doc/src/Build_basics.txt +++ b/doc/src/Build_basics.txt @@ -51,7 +51,7 @@ Serial build (see src/MAKE/Makefile.serial): MPI_INC = -I../STUBS MPI_PATH = -L../STUBS -MPI_LIB = -lmpi_stubs :pre +MPI_LIB = -lmpi_stubs :pre For a parallel build, if MPI is installed on your system in the usual place (e.g. under /usr/local), you do not need to specify the 3 @@ -183,17 +183,17 @@ want. Parallel build (see src/MAKE/Makefile.mpi): -CC = mpicxx -CCFLAGS = -g -O3 -LINK = mpicxx -LINKFLAGS = -g -O :pre +CC = mpicxx +CCFLAGS = -g -O3 +LINK = mpicxx +LINKFLAGS = -g -O :pre Serial build (see src/MAKE/Makefile.serial): -CC = g++ -CCFLAGS = -g -O3 -LINK = g++ -LINKFLAGS = -g -O :pre +CC = g++ +CCFLAGS = -g -O3 +LINK = g++ +LINKFLAGS = -g -O :pre The "compiler/linker settings" section of a Makefile.machine lists compiler and linker settings for your C++ compiler, including diff --git a/doc/src/Build_extras.txt b/doc/src/Build_extras.txt index 92b6314004..0a25a344ca 100644 --- a/doc/src/Build_extras.txt +++ b/doc/src/Build_extras.txt @@ -302,7 +302,7 @@ files. KOKKOS_ABSOLUTE_PATH = $(shell cd $(KOKKOS_PATH); pwd) export OMPI_CXX = $(KOKKOS_ABSOLUTE_PATH)/config/nvcc_wrapper -CC = mpicxx :pre +CC = mpicxx :pre :line @@ -849,15 +849,15 @@ additional information. For CPUs: OPTFLAGS = -xHost -O2 -fp-model fast=2 -no-prec-div -qoverride-limits -qopt-zmm-usage=high -CCFLAGS = -g -qopenmp -DLAMMPS_MEMALIGN=64 -no-offload -fno-alias -ansi-alias -restrict $(OPTFLAGS) -LINKFLAGS = -g -qopenmp $(OPTFLAGS) +CCFLAGS = -g -qopenmp -DLAMMPS_MEMALIGN=64 -no-offload -fno-alias -ansi-alias -restrict $(OPTFLAGS) +LINKFLAGS = -g -qopenmp $(OPTFLAGS) LIB = -ltbbmalloc :pre For KNLs: OPTFLAGS = -xMIC-AVX512 -O2 -fp-model fast=2 -no-prec-div -qoverride-limits -CCFLAGS = -g -qopenmp -DLAMMPS_MEMALIGN=64 -no-offload -fno-alias -ansi-alias -restrict $(OPTFLAGS) -LINKFLAGS = -g -qopenmp $(OPTFLAGS) +CCFLAGS = -g -qopenmp -DLAMMPS_MEMALIGN=64 -no-offload -fno-alias -ansi-alias -restrict $(OPTFLAGS) +LINKFLAGS = -g -qopenmp $(OPTFLAGS) LIB = -ltbbmalloc :pre :line From b2c6244b793ff95fcc160457c6e39f9160e89a10 Mon Sep 17 00:00:00 2001 From: Axel Kohlmeyer Date: Tue, 17 Sep 2019 08:24:40 -0400 Subject: [PATCH 146/192] fix typos --- src/USER-DIFFRACTION/compute_saed.cpp | 2 +- src/USER-DIFFRACTION/compute_xrd.cpp | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/src/USER-DIFFRACTION/compute_saed.cpp b/src/USER-DIFFRACTION/compute_saed.cpp index 971d9bd380..3ae25f223c 100644 --- a/src/USER-DIFFRACTION/compute_saed.cpp +++ b/src/USER-DIFFRACTION/compute_saed.cpp @@ -510,7 +510,7 @@ void ComputeSAED::compute_vector() if (me == 0 && echo) { if (screen) - fprintf(screen," 100%% \nTime ellapsed during compute_saed = %0.2f sec using %0.2f Mbytes/processor\n-----\n", t2-t0, bytes/1024.0/1024.0); + fprintf(screen," 100%% \nTime elapsed during compute_saed = %0.2f sec using %0.2f Mbytes/processor\n-----\n", t2-t0, bytes/1024.0/1024.0); } delete [] xlocal; diff --git a/src/USER-DIFFRACTION/compute_xrd.cpp b/src/USER-DIFFRACTION/compute_xrd.cpp index f48951f1ff..7f69449282 100644 --- a/src/USER-DIFFRACTION/compute_xrd.cpp +++ b/src/USER-DIFFRACTION/compute_xrd.cpp @@ -513,7 +513,7 @@ void ComputeXRD::compute_array() if (me == 0 && echo) { if (screen) - fprintf(screen," 100%% \nTime ellapsed during compute_xrd = %0.2f sec using %0.2f Mbytes/processor\n-----\n", t2-t0, bytes/1024.0/1024.0); + fprintf(screen," 100%% \nTime elapsed during compute_xrd = %0.2f sec using %0.2f Mbytes/processor\n-----\n", t2-t0, bytes/1024.0/1024.0); } delete [] scratch; From 0c9697a68537d431116fb8b57caf4bcbfc947c01 Mon Sep 17 00:00:00 2001 From: Axel Kohlmeyer Date: Tue, 17 Sep 2019 08:33:25 -0400 Subject: [PATCH 147/192] documentation whitespace cleanup --- doc/src/Build_development.txt | 2 +- doc/src/Howto_spins.txt | 16 +- doc/src/Speed_kokkos.txt | 88 +++++------ doc/src/Tools.txt | 4 +- doc/src/compute.txt | 4 +- doc/src/compute_coord_atom.txt | 2 +- doc/src/compute_hma.txt | 36 ++--- doc/src/compute_orientorder_atom.txt | 12 +- doc/src/compute_sna_atom.txt | 2 +- doc/src/compute_spin.txt | 12 +- doc/src/dynamical_matrix.txt | 2 +- doc/src/fix.txt | 4 +- doc/src/fix_controller.txt | 1 - doc/src/fix_neb_spin.txt | 22 +-- doc/src/fix_precession_spin.txt | 14 +- doc/src/fix_rigid_meso.txt | 2 +- doc/src/fix_setforce.txt | 14 +- doc/src/kspace_style.txt | 10 +- doc/src/min_modify.txt | 10 +- doc/src/min_spin.txt | 22 +-- doc/src/min_style.txt | 10 +- doc/src/minimize.txt | 6 +- doc/src/neb_spin.txt | 128 +++++++-------- doc/src/package.txt | 200 ++++++++++++------------ doc/src/pair_e3b.txt | 4 +- doc/src/pair_granular.txt | 2 +- doc/src/pair_kolmogorov_crespi_full.txt | 4 +- doc/src/pair_mm3_switch3_coulgauss.txt | 2 +- doc/src/pair_oxdna2.txt | 4 +- doc/src/pair_snap.txt | 4 +- doc/src/pair_spin_dipole.txt | 24 +-- doc/src/pair_spin_dmi.txt | 4 +- doc/src/pair_spin_neel.txt | 2 +- 33 files changed, 336 insertions(+), 337 deletions(-) diff --git a/doc/src/Build_development.txt b/doc/src/Build_development.txt index 16a3d3d20e..bd3897fba6 100644 --- a/doc/src/Build_development.txt +++ b/doc/src/Build_development.txt @@ -50,7 +50,7 @@ Code Coverage and Testing :h4,link(testing) We do extensive regression testing of the LAMMPS code base on a continuous basis. Some of the logic to do this has been added to the CMake build so -developers can run the tests directly on their workstation. +developers can run the tests directly on their workstation. NOTE: this is incomplete and only represents a small subset of tests that we run diff --git a/doc/src/Howto_spins.txt b/doc/src/Howto_spins.txt index 80b2a54fe4..c4bdc502ce 100644 --- a/doc/src/Howto_spins.txt +++ b/doc/src/Howto_spins.txt @@ -43,19 +43,19 @@ langevin/spin"_fix_langevin_spin.html. It allows to either dissipate the thermal energy of the Langevin thermostat, or to perform a relaxation of the magnetic configuration toward an equilibrium state. -The command "fix setforce/spin"_fix_setforce.html allows to set the -components of the magnetic precession vectors (while erasing and -replacing the previously computed magnetic precession vectors on -the atom). -This command can be used to freeze the magnetic moment of certain -atoms in the simulation by zeroing their precession vector. +The command "fix setforce/spin"_fix_setforce.html allows to set the +components of the magnetic precession vectors (while erasing and +replacing the previously computed magnetic precession vectors on +the atom). +This command can be used to freeze the magnetic moment of certain +atoms in the simulation by zeroing their precession vector. The command "fix nve/spin"_fix_nve_spin.html can be used to -perform a symplectic integration of the combined dynamics of spins +perform a symplectic integration of the combined dynamics of spins and atomic motions. The minimization style "min/spin"_min_spin.html can be applied -to the spins to perform a minimization of the spin configuration. +to the spins to perform a minimization of the spin configuration. All the computed magnetic properties can be output by two main diff --git a/doc/src/Speed_kokkos.txt b/doc/src/Speed_kokkos.txt index 99d29864dc..66f8fab8d9 100644 --- a/doc/src/Speed_kokkos.txt +++ b/doc/src/Speed_kokkos.txt @@ -46,14 +46,14 @@ software version 7.5 or later must be installed on your system. See the discussion for the "GPU package"_Speed_gpu.html for details of how to check and do this. -NOTE: Kokkos with CUDA currently implicitly assumes that the MPI library -is CUDA-aware. This is not always the case, especially when using -pre-compiled MPI libraries provided by a Linux distribution. This is not -a problem when using only a single GPU with a single MPI rank. When -running with multiple MPI ranks, you may see segmentation faults without -CUDA-aware MPI support. These can be avoided by adding the flags "-pk -kokkos cuda/aware off"_Run_options.html to the LAMMPS command line or by -using the command "package kokkos cuda/aware off"_package.html in the +NOTE: Kokkos with CUDA currently implicitly assumes that the MPI library +is CUDA-aware. This is not always the case, especially when using +pre-compiled MPI libraries provided by a Linux distribution. This is not +a problem when using only a single GPU with a single MPI rank. When +running with multiple MPI ranks, you may see segmentation faults without +CUDA-aware MPI support. These can be avoided by adding the flags "-pk +kokkos cuda/aware off"_Run_options.html to the LAMMPS command line or by +using the command "package kokkos cuda/aware off"_package.html in the input file. [Building LAMMPS with the KOKKOS package:] @@ -110,10 +110,10 @@ Makefile.kokkos_mpi_only) will give better performance than the OpenMP back end (i.e. Makefile.kokkos_omp) because some of the overhead to make the code thread-safe is removed. -NOTE: Use the "-pk kokkos" "command-line switch"_Run_options.html to -change the default "package kokkos"_package.html options. See its doc -page for details and default settings. Experimenting with its options -can provide a speed-up for specific calculations. For example: +NOTE: Use the "-pk kokkos" "command-line switch"_Run_options.html to +change the default "package kokkos"_package.html options. See its doc +page for details and default settings. Experimenting with its options +can provide a speed-up for specific calculations. For example: mpirun -np 16 lmp_kokkos_mpi_only -k on -sf kk -pk kokkos newton on neigh half comm no -in in.lj # Newton on, Half neighbor list, non-threaded comm :pre @@ -183,15 +183,15 @@ tasks/node. The "-k on t Nt" command-line switch sets the number of threads/task as Nt. The product of these two values should be N, i.e. 256 or 264. -NOTE: The default for the "package kokkos"_package.html command when -running on KNL is to use "half" neighbor lists and set the Newton flag -to "on" for both pairwise and bonded interactions. This will typically -be best for many-body potentials. For simpler pair-wise potentials, it -may be faster to use a "full" neighbor list with Newton flag to "off". -Use the "-pk kokkos" "command-line switch"_Run_options.html to change -the default "package kokkos"_package.html options. See its doc page for -details and default settings. Experimenting with its options can provide -a speed-up for specific calculations. For example: +NOTE: The default for the "package kokkos"_package.html command when +running on KNL is to use "half" neighbor lists and set the Newton flag +to "on" for both pairwise and bonded interactions. This will typically +be best for many-body potentials. For simpler pair-wise potentials, it +may be faster to use a "full" neighbor list with Newton flag to "off". +Use the "-pk kokkos" "command-line switch"_Run_options.html to change +the default "package kokkos"_package.html options. See its doc page for +details and default settings. Experimenting with its options can provide +a speed-up for specific calculations. For example: mpirun -np 64 lmp_kokkos_phi -k on t 4 -sf kk -pk kokkos comm host -in in.reax # Newton on, half neighbor list, threaded comm mpirun -np 64 lmp_kokkos_phi -k on t 4 -sf kk -pk kokkos newton off neigh full comm no -in in.lj # Newton off, full neighbor list, non-threaded comm :pre @@ -206,19 +206,19 @@ supports. [Running on GPUs:] -Use the "-k" "command-line switch"_Run_options.html to specify the -number of GPUs per node. Typically the -np setting of the mpirun command -should set the number of MPI tasks/node to be equal to the number of -physical GPUs on the node. You can assign multiple MPI tasks to the same -GPU with the KOKKOS package, but this is usually only faster if some -portions of the input script have not been ported to use Kokkos. In this -case, also packing/unpacking communication buffers on the host may give -speedup (see the KOKKOS "package"_package.html command). Using CUDA MPS +Use the "-k" "command-line switch"_Run_options.html to specify the +number of GPUs per node. Typically the -np setting of the mpirun command +should set the number of MPI tasks/node to be equal to the number of +physical GPUs on the node. You can assign multiple MPI tasks to the same +GPU with the KOKKOS package, but this is usually only faster if some +portions of the input script have not been ported to use Kokkos. In this +case, also packing/unpacking communication buffers on the host may give +speedup (see the KOKKOS "package"_package.html command). Using CUDA MPS is recommended in this scenario. -Using a CUDA-aware MPI library is highly recommended. CUDA-aware MPI use can be -avoided by using "-pk kokkos cuda/aware no"_package.html. As above for -multi-core CPUs (and no GPU), if N is the number of physical cores/node, +Using a CUDA-aware MPI library is highly recommended. CUDA-aware MPI use can be +avoided by using "-pk kokkos cuda/aware no"_package.html. As above for +multi-core CPUs (and no GPU), if N is the number of physical cores/node, then the number of MPI tasks/node should not exceed N. -k on g Ng :pre @@ -229,18 +229,18 @@ one or more nodes, each with two GPUs: mpirun -np 2 lmp_kokkos_cuda_openmpi -k on g 2 -sf kk -in in.lj # 1 node, 2 MPI tasks/node, 2 GPUs/node mpirun -np 32 -ppn 2 lmp_kokkos_cuda_openmpi -k on g 2 -sf kk -in in.lj # 16 nodes, 2 MPI tasks/node, 2 GPUs/node (32 GPUs total) :pre -NOTE: The default for the "package kokkos"_package.html command when -running on GPUs is to use "full" neighbor lists and set the Newton flag -to "off" for both pairwise and bonded interactions, along with threaded -communication. When running on Maxwell or Kepler GPUs, this will -typically be best. For Pascal GPUs, using "half" neighbor lists and -setting the Newton flag to "on" may be faster. For many pair styles, -setting the neighbor binsize equal to twice the CPU default value will -give speedup, which is the default when running on GPUs. Use the "-pk -kokkos" "command-line switch"_Run_options.html to change the default -"package kokkos"_package.html options. See its doc page for details and -default settings. Experimenting with its options can provide a speed-up -for specific calculations. For example: +NOTE: The default for the "package kokkos"_package.html command when +running on GPUs is to use "full" neighbor lists and set the Newton flag +to "off" for both pairwise and bonded interactions, along with threaded +communication. When running on Maxwell or Kepler GPUs, this will +typically be best. For Pascal GPUs, using "half" neighbor lists and +setting the Newton flag to "on" may be faster. For many pair styles, +setting the neighbor binsize equal to twice the CPU default value will +give speedup, which is the default when running on GPUs. Use the "-pk +kokkos" "command-line switch"_Run_options.html to change the default +"package kokkos"_package.html options. See its doc page for details and +default settings. Experimenting with its options can provide a speed-up +for specific calculations. For example: mpirun -np 2 lmp_kokkos_cuda_openmpi -k on g 2 -sf kk -pk kokkos newton on neigh half binsize 2.8 -in in.lj # Newton on, half neighbor list, set binsize = neighbor ghost cutoff :pre diff --git a/doc/src/Tools.txt b/doc/src/Tools.txt index eb7b6d81b8..cd01187805 100644 --- a/doc/src/Tools.txt +++ b/doc/src/Tools.txt @@ -515,13 +515,13 @@ Ernst Mach Institute in Germany (georg.ganzenmueller at emi.fhg.de). spin tool :h4,link(spin) The spin sub-directory contains a C file interpolate.c which can -be compiled and used to perform a cubic polynomial interpolation of +be compiled and used to perform a cubic polynomial interpolation of the MEP following a GNEB calculation. See the README file in tools/spin/interpolate_gneb for more details. This tool was written by the SPIN package author, Julien -Tranchida at Sandia National Labs (jtranch at sandia.gov, and by Aleksei +Tranchida at Sandia National Labs (jtranch at sandia.gov, and by Aleksei Ivanov, at University of Iceland (ali5 at hi.is). :line diff --git a/doc/src/compute.txt b/doc/src/compute.txt index 214fbdefc4..b54d2d2e7b 100644 --- a/doc/src/compute.txt +++ b/doc/src/compute.txt @@ -244,7 +244,7 @@ compute"_Commands_compute.html doc page are followed by one or more of "plasticity/atom"_compute_plasticity_atom.html - Peridynamic plasticity for each atom "pressure"_compute_pressure.html - total pressure and pressure tensor "pressure/cylinder"_compute_pressure_cylinder.html - pressure tensor in cylindrical coordinates -"pressure/uef"_compute_pressure_uef.html - pressure tensor in the reference frame of an applied flow field +"pressure/uef"_compute_pressure_uef.html - pressure tensor in the reference frame of an applied flow field "property/atom"_compute_property_atom.html - convert atom attributes to per-atom vectors/arrays "property/chunk"_compute_property_chunk.html - extract various per-chunk attributes "property/local"_compute_property_local.html - convert local attributes to localvectors/arrays @@ -284,7 +284,7 @@ compute"_Commands_compute.html doc page are followed by one or more of "stress/mop"_compute_stress_mop.html - normal components of the local stress tensor using the method of planes "stress/mop/profile"_compute_stress_mop.html - profile of the normal components of the local stress tensor using the method of planes "stress/tally"_compute_tally.html - -"tdpd/cc/atom"_compute_tdpd_cc_atom.html - per-atom chemical concentration of a specified species for each tDPD particle +"tdpd/cc/atom"_compute_tdpd_cc_atom.html - per-atom chemical concentration of a specified species for each tDPD particle "temp"_compute_temp.html - temperature of group of atoms "temp/asphere"_compute_temp_asphere.html - temperature of aspherical particles "temp/body"_compute_temp_body.html - temperature of body particles diff --git a/doc/src/compute_coord_atom.txt b/doc/src/compute_coord_atom.txt index af0be4be56..e4d57a5dc5 100644 --- a/doc/src/compute_coord_atom.txt +++ b/doc/src/compute_coord_atom.txt @@ -47,7 +47,7 @@ neighboring atoms, unless selected by type, type range, or group option, are included in the coordination number tally. The optional {group} keyword allows to specify from which group atoms -contribute to the coordination number. Default setting is group 'all'. +contribute to the coordination number. Default setting is group 'all'. The {typeN} keywords allow specification of which atom types contribute to each coordination number. One coordination number is diff --git a/doc/src/compute_hma.txt b/doc/src/compute_hma.txt index 4ab355abd7..289138eaa8 100644 --- a/doc/src/compute_hma.txt +++ b/doc/src/compute_hma.txt @@ -34,7 +34,7 @@ compute 2 all hma 1 u cv :pre Define a computation that calculates the properties of a solid (potential energy, pressure or heat capacity), using the harmonically-mapped averaging -(HMA) method. +(HMA) method. This command yields much higher precision than the equivalent compute commands ("compute pe"_compute_pe.html, "compute pressure"_compute_pressure.html, etc.) commands during a canonical simulation of an atomic crystal. Specifically, @@ -52,7 +52,7 @@ restricted to simulations in the NVT ensemble. While this compute may be used with any potential in LAMMPS, it will provide inaccurate results for potentials that do not go to 0 at the truncation distance; "pair_lj_smooth_linear"_pair_lj_smooth_linear.html and Ewald summation should -work fine, while "pair_lj"_pair_lj.html will perform poorly unless +work fine, while "pair_lj"_pair_lj.html will perform poorly unless the potential is shifted (via "pair_modify"_pair_modify.html shift) or the cutoff is large. Furthermore, computation of the heat capacity with this compute is restricted to those that implement the single_hessian method in Pair. Implementing single_hessian in additional pair styles is simple. @@ -64,8 +64,8 @@ the list of pair styles that currently implement pair_hessian: :ule In this method, the analytically known harmonic behavior of a crystal is removed from the traditional ensemble -averages, which leads to an accurate and precise measurement of the anharmonic contributions without contamination -by noise produced by the already-known harmonic behavior. +averages, which leads to an accurate and precise measurement of the anharmonic contributions without contamination +by noise produced by the already-known harmonic behavior. A detailed description of this method can be found in ("Moustafa"_#hma-Moustafa). The potential energy is computed by the formula: \begin\{equation\} @@ -74,9 +74,9 @@ A detailed description of this method can be found in ("Moustafa"_#hma-Moustafa) where \(N\) is the number of atoms in the system, \(k_B\) is Boltzmann's constant, \(T\) is the temperature, \(d\) is the -dimensionality of the system (2 or 3 for 2d/3d), \(F\bullet\Delta r\) is the sum of dot products of the -atomic force vectors and displacement (from lattice sites) vectors, and \(U\) is the sum of -pair, bond, angle, dihedral, improper, kspace (long-range), and fix energies. +dimensionality of the system (2 or 3 for 2d/3d), \(F\bullet\Delta r\) is the sum of dot products of the +atomic force vectors and displacement (from lattice sites) vectors, and \(U\) is the sum of +pair, bond, angle, dihedral, improper, kspace (long-range), and fix energies. The pressure is computed by the formula: @@ -118,30 +118,30 @@ When using this keyword, the compute must be first active (it must be included via a "thermo_style custom"_thermo_style.html command) while the atoms are still at their lattice sites (before equilibration). -The temp-ID specified with compute hma command should be same as the fix-ID of Nose-Hoover ("fix nvt"_fix_nh.html) or -Berendsen ("fix temp/berendsen"_fix_temp_berendsen.html) thermostat used for the simulation. While using this command, Langevin thermostat -("fix langevin"_fix_langevin.html) -should be avoided as its extra forces interfere with the HMA implementation. +The temp-ID specified with compute hma command should be same as the fix-ID of Nose-Hoover ("fix nvt"_fix_nh.html) or +Berendsen ("fix temp/berendsen"_fix_temp_berendsen.html) thermostat used for the simulation. While using this command, Langevin thermostat +("fix langevin"_fix_langevin.html) +should be avoided as its extra forces interfere with the HMA implementation. - -NOTE: Compute hma command should be used right after the energy minimization, when the atoms are at their lattice sites. + +NOTE: Compute hma command should be used right after the energy minimization, when the atoms are at their lattice sites. The simulation should not be started before this command has been used in the input script. The following example illustrates the placement of this command in the input script: -min_style cg -minimize 1e-35 1e-15 50000 500000 +min_style cg +minimize 1e-35 1e-15 50000 500000 compute 1 all hma thermostatid u -fix thermostatid all nvt temp 600.0 600.0 100.0 :pre +fix thermostatid all nvt temp 600.0 600.0 100.0 :pre NOTE: Compute hma should be used when the atoms of the solid do not diffuse. Diffusion will reduce the precision in the potential energy computation. - + NOTE: The "fix_modify energy yes"_fix_modify.html command must also be specified if a fix is to contribute potential energy to this command. An example input script that uses this compute is included in @@ -180,5 +180,5 @@ this compute. :line :link(hma-Moustafa) -[(Moustafa)] Sabry G. Moustafa, Andrew J. Schultz, and David A. Kofke, {Very fast averaging of thermal properties of crystals by molecular simulation}, +[(Moustafa)] Sabry G. Moustafa, Andrew J. Schultz, and David A. Kofke, {Very fast averaging of thermal properties of crystals by molecular simulation}, "Phys. Rev. E \[92\], 043303 (2015)"_https://link.aps.org/doi/10.1103/PhysRevE.92.043303 diff --git a/doc/src/compute_orientorder_atom.txt b/doc/src/compute_orientorder_atom.txt index da14c866bd..d59033f179 100644 --- a/doc/src/compute_orientorder_atom.txt +++ b/doc/src/compute_orientorder_atom.txt @@ -76,14 +76,14 @@ parameters up to {Q}12 for a range of commonly encountered high-symmetry structures are given in Table I of "Mickel et al."_#Mickel, and these can be reproduced with this compute -The optional keyword {wl} will output the third-order invariants {Wl} +The optional keyword {wl} will output the third-order invariants {Wl} (see Eq. 1.4 in "Steinhardt"_#Steinhardt) for the same degrees as for the {Ql} parameters. For the FCC crystal with {nnn} =12, {W}4 = -sqrt(14/143).(49/4096)/Pi^1.5 = -0.0006722136... -The optional keyword {wl/hat} will output the normalized third-order -invariants {Wlhat} (see Eq. 2.2 in "Steinhardt"_#Steinhardt) -for the same degrees as for the {Ql} parameters. For the FCC crystal +The optional keyword {wl/hat} will output the normalized third-order +invariants {Wlhat} (see Eq. 2.2 in "Steinhardt"_#Steinhardt) +for the same degrees as for the {Ql} parameters. For the FCC crystal with {nnn} =12, {W}4hat = -7/3*sqrt(2/429) = -0.159317...The numerical values of {Wlhat} for a range of commonly encountered high-symmetry structures are given in Table I of "Steinhardt"_#Steinhardt, and these @@ -127,9 +127,9 @@ range 0 <= {Ql} <= 1. If the keyword {wl} is set to yes, then the {Wl} values for each atom will be added to the output array, which are real numbers. -If the keyword {wl/hat} is set to yes, then the {Wl_hat} +If the keyword {wl/hat} is set to yes, then the {Wl_hat} values for each atom will be added to the output array, which are real numbers. - + If the keyword {components} is set, then the real and imaginary parts of each component of (normalized) {Ybar_lm} will be added to the output array in the following order: Re({Ybar_-m}) Im({Ybar_-m}) diff --git a/doc/src/compute_sna_atom.txt b/doc/src/compute_sna_atom.txt index 518d28aec9..eab32d8757 100644 --- a/doc/src/compute_sna_atom.txt +++ b/doc/src/compute_sna_atom.txt @@ -196,7 +196,7 @@ for j1 in range(0,twojmax+1): if (j>=j1): print j1/2.,j2/2.,j/2. :pre NOTE: the {diagonal} keyword allowing other possible choices -for the number of bispectrum components was removed in 2019, +for the number of bispectrum components was removed in 2019, since all potentials use the value of 3, corresponding to the above set of bispectrum components. diff --git a/doc/src/compute_spin.txt b/doc/src/compute_spin.txt index d27e402972..0824a70dd0 100644 --- a/doc/src/compute_spin.txt +++ b/doc/src/compute_spin.txt @@ -40,14 +40,14 @@ The simplest way to output the results of the compute spin calculation is to define some of the quantities as variables, and to use the thermo and thermo_style commands, for example: -compute out_mag all spin :pre +compute out_mag all spin :pre -variable mag_z equal c_out_mag\[3\] -variable mag_norm equal c_out_mag\[4\] -variable temp_mag equal c_out_mag\[6\] :pre +variable mag_z equal c_out_mag\[3\] +variable mag_norm equal c_out_mag\[4\] +variable temp_mag equal c_out_mag\[6\] :pre -thermo 10 -thermo_style custom step v_mag_z v_mag_norm v_temp_mag :pre +thermo 10 +thermo_style custom step v_mag_z v_mag_norm v_temp_mag :pre This series of commands evaluates the total magnetization along z, the norm of the total magnetization, and the magnetic temperature. Three variables are diff --git a/doc/src/dynamical_matrix.txt b/doc/src/dynamical_matrix.txt index 6291bdec52..f207297e9f 100644 --- a/doc/src/dynamical_matrix.txt +++ b/doc/src/dynamical_matrix.txt @@ -52,4 +52,4 @@ provided by Pair's single_hessian. [Default:] -The default settings are file = "dynmat.dyn", binary = no +The default settings are file = "dynmat.dyn", binary = no diff --git a/doc/src/fix.txt b/doc/src/fix.txt index 1dd9cc9f1b..3fc0067e1a 100644 --- a/doc/src/fix.txt +++ b/doc/src/fix.txt @@ -221,7 +221,7 @@ accelerated styles exist. "heat"_fix_heat.html - add/subtract momentum-conserving heat "hyper/global"_fix_hyper_global.html - global hyperdynamics "hyper/local"_fix_hyper_local.html - local hyperdynamics -"imd"_fix_imd.html - implements the “Interactive MD” (IMD) protocol +"imd"_fix_imd.html - implements the “Interactive MD” (IMD) protocol "indent"_fix_indent.html - impose force due to an indenter "ipi"_fix_ipi.html - enable LAMMPS to run as a client for i-PI path-integral simulations "langevin"_fix_langevin.html - Langevin temperature control @@ -327,7 +327,7 @@ accelerated styles exist. "rigid/nvt/small"_fix_rigid.html - constrain many small clusters of atoms to move as a rigid body with NVT integration "rigid/small"_fix_rigid.html - constrain many small clusters of atoms to move as a rigid body with NVE integration "rx"_fix_rx.html - -"saed/vtk"_fix_saed_vtk.html - +"saed/vtk"_fix_saed_vtk.html - "setforce"_fix_setforce.html - set the force on each atom "shake"_fix_shake.html - SHAKE constraints on bonds and/or angles "shardlow"_fix_shardlow.html - integration of DPD equations of motion using the Shardlow splitting diff --git a/doc/src/fix_controller.txt b/doc/src/fix_controller.txt index 7458f1bcfa..45eb646b8e 100644 --- a/doc/src/fix_controller.txt +++ b/doc/src/fix_controller.txt @@ -31,7 +31,6 @@ cvar = name of control variable :l [Examples:] - fix 1 all controller 100 1.0 0.5 0.0 0.0 c_thermo_temp 1.5 tcontrol fix 1 all controller 100 0.2 0.5 0 100.0 v_pxxwall 1.01325 xwall fix 1 all controller 10000 0.2 0.5 0 2000 v_avpe -3.785 tcontrol :pre diff --git a/doc/src/fix_neb_spin.txt b/doc/src/fix_neb_spin.txt index 89420f451c..e62d297270 100644 --- a/doc/src/fix_neb_spin.txt +++ b/doc/src/fix_neb_spin.txt @@ -24,18 +24,18 @@ fix 1 active neb/spin 1.0 [Description:] Add nudging forces to spins in the group for a multi-replica -simulation run via the "neb/spin"_neb_spin.html command to perform a -geodesic nudged elastic band (GNEB) calculation for finding the +simulation run via the "neb/spin"_neb_spin.html command to perform a +geodesic nudged elastic band (GNEB) calculation for finding the transition state. -Hi-level explanations of GNEB are given with the -"neb/spin"_neb_spin.html command and on the -"Howto replica"_Howto_replica.html doc page. -The fix neb/spin command must be used with the "neb/spin" command and -defines how inter-replica nudging forces are computed. A GNEB -calculation is divided in two stages. In the first stage n replicas -are relaxed toward a MEP until convergence. In the second stage, the -climbing image scheme is enabled, so that the replica having the highest -energy relaxes toward the saddle point (i.e. the point of highest energy +Hi-level explanations of GNEB are given with the +"neb/spin"_neb_spin.html command and on the +"Howto replica"_Howto_replica.html doc page. +The fix neb/spin command must be used with the "neb/spin" command and +defines how inter-replica nudging forces are computed. A GNEB +calculation is divided in two stages. In the first stage n replicas +are relaxed toward a MEP until convergence. In the second stage, the +climbing image scheme is enabled, so that the replica having the highest +energy relaxes toward the saddle point (i.e. the point of highest energy along the MEP), and a second relaxation is performed. The nudging forces are calculated as explained in diff --git a/doc/src/fix_precession_spin.txt b/doc/src/fix_precession_spin.txt index 708b2bd7aa..040a3086d3 100644 --- a/doc/src/fix_precession_spin.txt +++ b/doc/src/fix_precession_spin.txt @@ -21,7 +21,7 @@ style = {zeeman} or {anisotropy} or {cubic} :l {anisotropy} args = K x y z K = intensity of the magnetic anisotropy (in eV) x y z = vector direction of the anisotropy :pre - {cubic} args = K1 K2c n1x n1y n1x n2x n2y n2z n3x n3y n3z + {cubic} args = K1 K2c n1x n1y n1x n2x n2y n2z n3x n3y n3z K1 and K2c = intensity of the magnetic anisotropy (in eV) n1x to n3z = three direction vectors of the cubic anisotropy :pre :ule @@ -55,24 +55,24 @@ with n defining the direction of the anisotropy, and K (in eV) its intensity. If K>0, an easy axis is defined, and if K<0, an easy plane is defined. Style {cubic} is used to simulate a cubic anisotropy, with three -possible easy axis for the magnetic spins in the defined group: +possible easy axis for the magnetic spins in the defined group: :c,image(Eqs/fix_spin_cubic.jpg) -with K1 and K2c (in eV) the intensity coefficients and +with K1 and K2c (in eV) the intensity coefficients and n1, n2 and n3 defining the three anisotropic directions -defined by the command (from n1x to n3z). -For n1 = (100), n2 = (010), and n3 = (001), K1 < 0 defines an +defined by the command (from n1x to n3z). +For n1 = (100), n2 = (010), and n3 = (001), K1 < 0 defines an iron type anisotropy (easy axis along the (001)-type cube edges), and K1 > 0 defines a nickel type anisotropy (easy axis -along the (111)-type cube diagonals). +along the (111)-type cube diagonals). K2^c > 0 also defines easy axis along the (111)-type cube diagonals. See chapter 2 of "(Skomski)"_#Skomski1 for more details on cubic anisotropies. In all cases, the choice of (x y z) only imposes the vector -directions for the forces. Only the direction of the vector is +directions for the forces. Only the direction of the vector is important; it's length is ignored (the entered vectors are normalized). diff --git a/doc/src/fix_rigid_meso.txt b/doc/src/fix_rigid_meso.txt index 0819fdb2fb..a9c68b2c04 100644 --- a/doc/src/fix_rigid_meso.txt +++ b/doc/src/fix_rigid_meso.txt @@ -44,7 +44,7 @@ fix 1 rods rigid/meso molecule fix 1 spheres rigid/meso single force 1 off off on fix 1 particles rigid/meso molecule force 1*5 off off off force 6*10 off off on fix 2 spheres rigid/meso group 3 sphere1 sphere2 sphere3 torque * off off off :pre - + [Description:] Treat one or more sets of mesoscopic SPH/SDPD particles as independent diff --git a/doc/src/fix_setforce.txt b/doc/src/fix_setforce.txt index 63713d87c2..5ee289ec5c 100644 --- a/doc/src/fix_setforce.txt +++ b/doc/src/fix_setforce.txt @@ -67,15 +67,15 @@ to it. :line -Style {spin} suffix sets the components of the magnetic precession -vectors instead of the mechanical forces. This also erases all -previously computed magnetic precession vectors on the atom, though +Style {spin} suffix sets the components of the magnetic precession +vectors instead of the mechanical forces. This also erases all +previously computed magnetic precession vectors on the atom, though additional magnetic fixes could add new forces. -This command can be used to freeze the magnetic moment of certain -atoms in the simulation by zeroing their precession vector. +This command can be used to freeze the magnetic moment of certain +atoms in the simulation by zeroing their precession vector. -All options defined above remain valid, they just apply to the magnetic +All options defined above remain valid, they just apply to the magnetic precession vectors instead of the forces. :line @@ -132,7 +132,7 @@ forces to any value besides zero when performing a minimization. Use the "fix addforce"_fix_addforce.html command if you want to apply a non-zero force to atoms during a minimization. -[Restrictions:] +[Restrictions:] The fix {setforce/spin} only makes sense when LAMMPS was built with the SPIN package. diff --git a/doc/src/kspace_style.txt b/doc/src/kspace_style.txt index 98ec1e64e6..04b845acaa 100644 --- a/doc/src/kspace_style.txt +++ b/doc/src/kspace_style.txt @@ -116,10 +116,10 @@ used without a cutoff, i.e. they become full long-range potentials. The {ewald/disp} style can also be used with point-dipoles, see "(Toukmaji)"_#Toukmaji. -The {ewald/dipole} style adds long-range standard Ewald summations +The {ewald/dipole} style adds long-range standard Ewald summations for dipole-dipole interactions, see "(Toukmaji)"_#Toukmaji. -The {ewald/dipole/spin} style adds long-range standard Ewald +The {ewald/dipole/spin} style adds long-range standard Ewald summations for magnetic dipole-dipole interactions between magnetic spins. @@ -142,11 +142,11 @@ The optional {smallq} argument defines the cutoff for the absolute charge value which determines whether a particle is considered charged or not. Its default value is 1.0e-5. -The {pppm/dipole} style invokes a particle-particle particle-mesh solver +The {pppm/dipole} style invokes a particle-particle particle-mesh solver for dipole-dipole interactions, following the method of "(Cerda)"_#Cerda2008. -The {pppm/dipole/spin} style invokes a particle-particle particle-mesh solver -for magnetic dipole-dipole interactions between magnetic spins. +The {pppm/dipole/spin} style invokes a particle-particle particle-mesh solver +for magnetic dipole-dipole interactions between magnetic spins. The {pppm/tip4p} style is identical to the {pppm} style except that it adds a charge at the massless 4th site in each TIP4P water molecule. diff --git a/doc/src/min_modify.txt b/doc/src/min_modify.txt index d342e8bf01..434f7d05e6 100644 --- a/doc/src/min_modify.txt +++ b/doc/src/min_modify.txt @@ -17,7 +17,7 @@ keyword = {dmax} or {line} or {alpha_damp} or {discrete_factor} {dmax} value = max max = maximum distance for line search to move (distance units) {line} value = {backtrack} or {quadratic} or {forcezero} - backtrack,quadratic,forcezero = style of linesearch to use + backtrack,quadratic,forcezero = style of linesearch to use {alpha_damp} value = damping damping = fictitious Gilbert damping for spin minimization (adim) {discrete_factor} value = factor @@ -70,14 +70,14 @@ that difference may be smaller than machine epsilon even if atoms could move in the gradient direction to reduce forces further. Keywords {alpha_damp} and {discrete_factor} only make sense when -a "min_spin"_min_spin.html command is declared. +a "min_spin"_min_spin.html command is declared. Keyword {alpha_damp} defines an analog of a magnetic Gilbert damping. It defines a relaxation rate toward an equilibrium for -a given magnetic system. +a given magnetic system. Keyword {discrete_factor} defines a discretization factor for the -adaptive timestep used in the {spin} minimization. +adaptive timestep used in the {spin} minimization. See "min_spin"_min_spin.html for more information about those -quantities. +quantities. Default values are {alpha_damp} = 1.0 and {discrete_factor} = 10.0. [Restrictions:] none diff --git a/doc/src/min_spin.txt b/doc/src/min_spin.txt index 890e324aca..2a0f0e5397 100644 --- a/doc/src/min_spin.txt +++ b/doc/src/min_spin.txt @@ -13,7 +13,7 @@ min_style spin :pre [Examples:] -min_style spin :pre +min_style spin :pre [Description:] @@ -27,36 +27,36 @@ timestep, according to: with lambda a damping coefficient (similar to a Gilbert damping). -Lambda can be defined by setting the {alpha_damp} keyword with the -"min_modify"_min_modify.html command. +Lambda can be defined by setting the {alpha_damp} keyword with the +"min_modify"_min_modify.html command. The minimization procedure solves this equation using an -adaptive timestep. The value of this timestep is defined -by the largest precession frequency that has to be solved in the +adaptive timestep. The value of this timestep is defined +by the largest precession frequency that has to be solved in the system: :c,image(Eqs/min_spin_timestep.jpg) with {|omega|_{max}} the norm of the largest precession frequency in the system (across all processes, and across all replicas if a -spin/neb calculation is performed). +spin/neb calculation is performed). -Kappa defines a discretization factor {discrete_factor} for the -definition of this timestep. +Kappa defines a discretization factor {discrete_factor} for the +definition of this timestep. {discrete_factor} can be defined with the "min_modify"_min_modify.html command. NOTE: The {spin} style replaces the force tolerance by a torque -tolerance. See "minimize"_minimize.html for more explanation. +tolerance. See "minimize"_minimize.html for more explanation. -[Restrictions:] +[Restrictions:] This minimization procedure is only applied to spin degrees of freedom for a frozen lattice configuration. [Related commands:] -"min_style"_min_style.html, "minimize"_minimize.html, +"min_style"_min_style.html, "minimize"_minimize.html, "min_modify"_min_modify.html [Default:] diff --git a/doc/src/min_style.txt b/doc/src/min_style.txt index e27682cf97..7c8aa0ae29 100644 --- a/doc/src/min_style.txt +++ b/doc/src/min_style.txt @@ -62,7 +62,7 @@ the velocity non-parallel to the current force vector. The velocity of each atom is initialized to 0.0 by this style, at the beginning of a minimization. -Style {spin} is a damped spin dynamics with an adaptive +Style {spin} is a damped spin dynamics with an adaptive timestep. See the "min/spin"_min_spin.html doc page for more information. @@ -74,10 +74,10 @@ defined via the "timestep"_timestep.html command. Often they will converge more quickly if you use a timestep about 10x larger than you would normally use for dynamics simulations. -NOTE: The {quickmin}, {fire}, {hftn}, and {cg/kk} styles do not yet -support the use of the "fix box/relax"_fix_box_relax.html command or -minimizations involving the electron radius in "eFF"_pair_eff.html -models. +NOTE: The {quickmin}, {fire}, {hftn}, and {cg/kk} styles do not yet +support the use of the "fix box/relax"_fix_box_relax.html command or +minimizations involving the electron radius in "eFF"_pair_eff.html +models. :line diff --git a/doc/src/minimize.txt b/doc/src/minimize.txt index 42315705e5..b109235ecc 100644 --- a/doc/src/minimize.txt +++ b/doc/src/minimize.txt @@ -106,9 +106,9 @@ the number of total force evaluations exceeds {maxeval} :ul NOTE: the "minimization style"_min_style.html {spin} replaces the force tolerance {ftol} by a torque tolerance. -The minimization procedure stops if the 2-norm (length) of the -global torque vector (defined as the cross product between the -spins and their precession vectors omega) is less than {ftol}, +The minimization procedure stops if the 2-norm (length) of the +global torque vector (defined as the cross product between the +spins and their precession vectors omega) is less than {ftol}, or if any of the other criteria are met. NOTE: You can also use the "fix halt"_fix_halt.html command to specify diff --git a/doc/src/neb_spin.txt b/doc/src/neb_spin.txt index 7dbd924cd2..e72ec63b06 100644 --- a/doc/src/neb_spin.txt +++ b/doc/src/neb_spin.txt @@ -45,7 +45,7 @@ and last are the end points of the transition path. GNEB is a method for finding both the spin configurations and height of the energy barrier associated with a transition state, e.g. spins to perform a collective rotation from one energy basin to -another. +another. The implementation in LAMMPS follows the discussion in the following paper: "(BessarabA)"_#BessarabA. @@ -61,33 +61,33 @@ doc page for further discussion. NOTE: As explained below, a GNEB calculation performs a damped dynamics minimization across all the replicas. The "spin"_min_spin.html -style minimizer has to be defined in your input script. +style minimizer has to be defined in your input script. When a GNEB calculation is performed, it is assumed that each replica is running the same system, though LAMMPS does not check for this. -I.e. the simulation domain, the number of magnetic atoms, the -interaction potentials, and the starting configuration when the neb +I.e. the simulation domain, the number of magnetic atoms, the +interaction potentials, and the starting configuration when the neb command is issued should be the same for every replica. In a GNEB calculation each replica is connected to other replicas by inter-replica nudging forces. These forces are imposed by the "fix -neb/spin"_fix_neb_spin.html command, which must be used in conjunction -with the neb command. +neb/spin"_fix_neb_spin.html command, which must be used in conjunction +with the neb command. The group used to define the fix neb/spin command defines the -GNEB magnetic atoms which are the only ones that inter-replica springs -are applied to. +GNEB magnetic atoms which are the only ones that inter-replica springs +are applied to. If the group does not include all magnetic atoms, then non-GNEB -magnetic atoms have no inter-replica springs and the torques they feel -and their precession motion is computed in the usual way due only -to other magnetic atoms within their replica. -Conceptually, the non-GNEB atoms provide a background force field for -the GNEB atoms. -Their magnetic spins can be allowed to evolve during the GNEB +magnetic atoms have no inter-replica springs and the torques they feel +and their precession motion is computed in the usual way due only +to other magnetic atoms within their replica. +Conceptually, the non-GNEB atoms provide a background force field for +the GNEB atoms. +Their magnetic spins can be allowed to evolve during the GNEB minimization procedure. The initial spin configuration for each of the replicas can be specified in different manners via the {file-style} setting, as -discussed below. Only atomic spins whose initial coordinates should +discussed below. Only atomic spins whose initial coordinates should differ from the current configuration need to be specified. Conceptually, the initial and final configurations for the first @@ -106,21 +106,21 @@ closer to the MEP and read them in. :line For a {file-style} setting of {final}, a filename is specified which -contains atomic and spin coordinates for zero or more atoms, in the -format described below. -For each atom that appears in the file, the new coordinates are -assigned to that atom in the final replica. Each intermediate replica -also assigns a new spin to that atom in an interpolated manner. -This is done by using the current direction of the spin at the starting -point and the read-in direction as the final point. -The "angular distance" between them is calculated, and the new direction +contains atomic and spin coordinates for zero or more atoms, in the +format described below. +For each atom that appears in the file, the new coordinates are +assigned to that atom in the final replica. Each intermediate replica +also assigns a new spin to that atom in an interpolated manner. +This is done by using the current direction of the spin at the starting +point and the read-in direction as the final point. +The "angular distance" between them is calculated, and the new direction is assigned to be a fraction of the angular distance. -NOTE: The "angular distance" between the starting and final point is -evaluated in the geodesic sense, as described in -"(BessarabA)"_#BessarabA. +NOTE: The "angular distance" between the starting and final point is +evaluated in the geodesic sense, as described in +"(BessarabA)"_#BessarabA. -NOTE: The angular interpolation between the starting and final point +NOTE: The angular interpolation between the starting and final point is achieved using Rodrigues formula: :c,image(Eqs/neb_spin_rodrigues_formula.jpg) @@ -130,7 +130,7 @@ omega_i^nu is a rotation angle defined as: :c,image(Eqs/neb_spin_angle.jpg) -with nu the image number, Q the total number of images, and +with nu the image number, Q the total number of images, and omega_i the total rotation between the initial and final spins. k_i defines a rotation axis such as: @@ -139,16 +139,16 @@ k_i defines a rotation axis such as: if the initial and final spins are not aligned. If the initial and final spins are aligned, then their cross product is null, and the expression above does not apply. -If they point toward the same direction, the intermediate images +If they point toward the same direction, the intermediate images conserve the same orientation. If the initial and final spins are aligned, but point toward opposite directions, an arbitrary rotation vector belonging to -the plane perpendicular to initial and final spins is chosen. +the plane perpendicular to initial and final spins is chosen. In this case, a warning message is displayed. For a {file-style} setting of {each}, a filename is specified which is -assumed to be unique to each replica. -See the "neb"_neb.html documentation page for more information about this +assumed to be unique to each replica. +See the "neb"_neb.html documentation page for more information about this option. For a {file-style} setting of {none}, no filename is specified. Each @@ -173,7 +173,7 @@ A NEB calculation proceeds in two stages, each of which is a minimization procedure, performed via damped dynamics. To enable this, you must first define a damped spin dynamics "min_style"_min_style.html, using the {spin} style (see -"min_spin"_min_spin.html for more information). +"min_spin"_min_spin.html for more information). The other styles cannot be used, since they relax the lattice degrees of freedom instead of the spins. @@ -195,9 +195,9 @@ damped dynamics is like a single timestep in a dynamics replica and its normalized distance along the reaction path (reaction coordinate RD) will be printed to the screen and log file every {Nevery} timesteps. The RD is 0 and 1 for the first and last replica. -For intermediate replicas, it is the cumulative angular distance -(normalized by the total cumulative angular distance) between adjacent -replicas, where "distance" is defined as the length of the 3N-vector of +For intermediate replicas, it is the cumulative angular distance +(normalized by the total cumulative angular distance) between adjacent +replicas, where "distance" is defined as the length of the 3N-vector of the geodesic distances in spin coordinates, with N the number of GNEB spins involved (see equation (13) in "(BessarabA)"_#BessarabA). These outputs allow you to monitor NEB's progress in @@ -207,11 +207,11 @@ of {Nevery}. In the first stage of GNEB, the set of replicas should converge toward a minimum energy path (MEP) of conformational states that transition over a barrier. The MEP for a transition is defined as a sequence of -3N-dimensional spin states, each of which has a potential energy -gradient parallel to the MEP itself. -The configuration of highest energy along a MEP corresponds to a saddle -point. The replica states will also be roughly equally spaced along -the MEP due to the inter-replica nudging force added by the +3N-dimensional spin states, each of which has a potential energy +gradient parallel to the MEP itself. +The configuration of highest energy along a MEP corresponds to a saddle +point. The replica states will also be roughly equally spaced along +the MEP due to the inter-replica nudging force added by the "fix neb"_fix_neb.html command. In the second stage of GNEB, the replica with the highest energy is @@ -234,12 +234,12 @@ An atom map must be defined which it is not by default for "atom_style atomic"_atom_style.html problems. The "atom_modify map"_atom_modify.html command can be used to do this. -An initial value can be defined for the timestep. Although, the {spin} -minimization algorithm is an adaptive timestep methodology, so that -this timestep is likely to evolve during the calculation. +An initial value can be defined for the timestep. Although, the {spin} +minimization algorithm is an adaptive timestep methodology, so that +this timestep is likely to evolve during the calculation. The minimizers in LAMMPS operate on all spins in your system, even -non-GNEB atoms, as defined above. +non-GNEB atoms, as defined above. :line @@ -257,7 +257,7 @@ ID2 g2 x2 y2 z2 sx2 sy2 sz2 ... IDN gN yN zN sxN syN szN :pre -The fields are the atom ID, the norm of the associated magnetic spin, +The fields are the atom ID, the norm of the associated magnetic spin, followed by the {x,y,z} coordinates and the {sx,sy,sz} spin coordinates. The lines can be listed in any order. Additional trailing information on the line is OK, such as a comment. @@ -290,22 +290,22 @@ reaction coordinate and potential energy of each replica. The "maximum torque per replica" is the two-norm of the 3N-length vector given by the cross product of a spin by its -precession vector omega, in each replica, maximized across replicas, +precession vector omega, in each replica, maximized across replicas, which is what the {ttol} setting is checking against. In this case, N is all the atoms in each replica. The "maximum torque per atom" is the maximum torque component of any atom in any replica. The potential -gradients are the two-norm of the 3N-length magnetic precession vector -solely due to the interaction potential i.e. without adding in -inter-replica forces, and projected along the path tangent (as detailed +gradients are the two-norm of the 3N-length magnetic precession vector +solely due to the interaction potential i.e. without adding in +inter-replica forces, and projected along the path tangent (as detailed in Appendix D of "(BessarabA)"_#BessarabA). The "reaction coordinate" (RD) for each replica is the two-norm of the 3N-length vector of geodesic distances between its spins and the preceding -replica's spins (see equation (13) of "(BessarabA)"_#BessarabA), added to -the RD of the preceding replica. The RD of the first replica RD1 = 0.0; -the RD of the final replica RDN = RDT, the total reaction coordinate. -The normalized RDs are divided by RDT, so that they form a monotonically -increasing sequence from zero to one. When computing RD, N only includes +replica's spins (see equation (13) of "(BessarabA)"_#BessarabA), added to +the RD of the preceding replica. The RD of the first replica RD1 = 0.0; +the RD of the final replica RDN = RDT, the total reaction coordinate. +The normalized RDs are divided by RDT, so that they form a monotonically +increasing sequence from zero to one. When computing RD, N only includes the spins being operated on by the fix neb/spin command. The forward (reverse) energy barrier is the potential energy of the @@ -313,17 +313,17 @@ highest replica minus the energy of the first (last) replica. Supplementary information for all replicas can be printed out to the screen and master log.lammps file by adding the verbose keyword. This -information include the following. -The "GradVidottan" are the projections of the potential gradient for -the replica i on its tangent vector (as detailed in Appendix D of +information include the following. +The "GradVidottan" are the projections of the potential gradient for +the replica i on its tangent vector (as detailed in Appendix D of "(BessarabA)"_#BessarabA). -The "DNi" are the non normalized geodesic distances (see equation (13) -of "(BessarabA)"_#BessarabA), between a replica i and the next replica +The "DNi" are the non normalized geodesic distances (see equation (13) +of "(BessarabA)"_#BessarabA), between a replica i and the next replica i+1. For the last replica, this distance is not defined and a "NAN" -value is the corresponding output. +value is the corresponding output. When a NEB calculation does not converge properly, the supplementary -information can help understanding what is going wrong. +information can help understanding what is going wrong. When running on multiple partitions, LAMMPS produces additional log files for each partition, e.g. log.lammps.0, log.lammps.1, etc. For a @@ -346,9 +346,9 @@ restart the calculation from an intermediate point with altered parameters. A c file script in provided in the tool/spin/interpolate_gneb -directory, that interpolates the MEP given the information provided +directory, that interpolates the MEP given the information provided by the verbose output option (as detailed in Appendix D of -"(BessarabA)"_#BessarabA). +"(BessarabA)"_#BessarabA). :line diff --git a/doc/src/package.txt b/doc/src/package.txt index edd409a842..4ecb5d96d0 100644 --- a/doc/src/package.txt +++ b/doc/src/package.txt @@ -423,115 +423,115 @@ processes/threads used for LAMMPS. :line -The {kokkos} style invokes settings associated with the use of the -KOKKOS package. +The {kokkos} style invokes settings associated with the use of the +KOKKOS package. -All of the settings are optional keyword/value pairs. Each has a default -value as listed below. +All of the settings are optional keyword/value pairs. Each has a default +value as listed below. -The {neigh} keyword determines how neighbor lists are built. A value of -{half} uses a thread-safe variant of half-neighbor lists, the same as -used by most pair styles in LAMMPS, which is the default when running on -CPUs (i.e. the Kokkos CUDA back end is not enabled). +The {neigh} keyword determines how neighbor lists are built. A value of +{half} uses a thread-safe variant of half-neighbor lists, the same as +used by most pair styles in LAMMPS, which is the default when running on +CPUs (i.e. the Kokkos CUDA back end is not enabled). -A value of {full} uses a full neighbor lists and is the default when -running on GPUs. This performs twice as much computation as the {half} -option, however that is often a win because it is thread-safe and -doesn't require atomic operations in the calculation of pair forces. For -that reason, {full} is the default setting for GPUs. However, when -running on CPUs, a {half} neighbor list is the default because it are -often faster, just as it is for non-accelerated pair styles. Similarly, -the {neigh/qeq} keyword determines how neighbor lists are built for "fix -qeq/reax/kk"_fix_qeq_reax.html. If not explicitly set, the value of +A value of {full} uses a full neighbor lists and is the default when +running on GPUs. This performs twice as much computation as the {half} +option, however that is often a win because it is thread-safe and +doesn't require atomic operations in the calculation of pair forces. For +that reason, {full} is the default setting for GPUs. However, when +running on CPUs, a {half} neighbor list is the default because it are +often faster, just as it is for non-accelerated pair styles. Similarly, +the {neigh/qeq} keyword determines how neighbor lists are built for "fix +qeq/reax/kk"_fix_qeq_reax.html. If not explicitly set, the value of {neigh/qeq} will match {neigh}. -If the {neigh/thread} keyword is set to {off}, then the KOKKOS package -threads only over atoms. However, for small systems, this may not expose -enough parallelism to keep a GPU busy. When this keyword is set to {on}, -the KOKKOS package threads over both atoms and neighbors of atoms. When -using {neigh/thread} {on}, a full neighbor list must also be used. Using -{neigh/thread} {on} may be slower for large systems, so this this option -is turned on by default only when there are 16K atoms or less owned by -an MPI rank and when using a full neighbor list. Not all KOKKOS-enabled -potentials support this keyword yet, and only thread over atoms. Many -simple pair-wise potentials such as Lennard-Jones do support threading +If the {neigh/thread} keyword is set to {off}, then the KOKKOS package +threads only over atoms. However, for small systems, this may not expose +enough parallelism to keep a GPU busy. When this keyword is set to {on}, +the KOKKOS package threads over both atoms and neighbors of atoms. When +using {neigh/thread} {on}, a full neighbor list must also be used. Using +{neigh/thread} {on} may be slower for large systems, so this this option +is turned on by default only when there are 16K atoms or less owned by +an MPI rank and when using a full neighbor list. Not all KOKKOS-enabled +potentials support this keyword yet, and only thread over atoms. Many +simple pair-wise potentials such as Lennard-Jones do support threading over both atoms and neighbors. -The {newton} keyword sets the Newton flags for pairwise and bonded -interactions to {off} or {on}, the same as the "newton"_newton.html -command allows. The default for GPUs is {off} because this will almost -always give better performance for the KOKKOS package. This means more -computation is done, but less communication. However, when running on -CPUs a value of {on} is the default since it can often be faster, just -as it is for non-accelerated pair styles +The {newton} keyword sets the Newton flags for pairwise and bonded +interactions to {off} or {on}, the same as the "newton"_newton.html +command allows. The default for GPUs is {off} because this will almost +always give better performance for the KOKKOS package. This means more +computation is done, but less communication. However, when running on +CPUs a value of {on} is the default since it can often be faster, just +as it is for non-accelerated pair styles -The {binsize} keyword sets the size of bins used to bin atoms in -neighbor list builds. The same value can be set by the "neigh_modify -binsize"_neigh_modify.html command. Making it an option in the package -kokkos command allows it to be set from the command line. The default -value for CPUs is 0.0, which means the LAMMPS default will be used, -which is bins = 1/2 the size of the pairwise cutoff + neighbor skin -distance. This is fine when neighbor lists are built on the CPU. For GPU -builds, a 2x larger binsize equal to the pairwise cutoff + neighbor skin -is often faster, which is the default. Note that if you use a -longer-than-usual pairwise cutoff, e.g. to allow for a smaller fraction -of KSpace work with a "long-range Coulombic solver"_kspace_style.html -because the GPU is faster at performing pairwise interactions, then this -rule of thumb may give too large a binsize and the default should be -overridden with a smaller value. +The {binsize} keyword sets the size of bins used to bin atoms in +neighbor list builds. The same value can be set by the "neigh_modify +binsize"_neigh_modify.html command. Making it an option in the package +kokkos command allows it to be set from the command line. The default +value for CPUs is 0.0, which means the LAMMPS default will be used, +which is bins = 1/2 the size of the pairwise cutoff + neighbor skin +distance. This is fine when neighbor lists are built on the CPU. For GPU +builds, a 2x larger binsize equal to the pairwise cutoff + neighbor skin +is often faster, which is the default. Note that if you use a +longer-than-usual pairwise cutoff, e.g. to allow for a smaller fraction +of KSpace work with a "long-range Coulombic solver"_kspace_style.html +because the GPU is faster at performing pairwise interactions, then this +rule of thumb may give too large a binsize and the default should be +overridden with a smaller value. -The {comm} and {comm/exchange} and {comm/forward} and {comm/reverse} -keywords determine whether the host or device performs the packing and -unpacking of data when communicating per-atom data between processors. -"Exchange" communication happens only on timesteps that neighbor lists -are rebuilt. The data is only for atoms that migrate to new processors. -"Forward" communication happens every timestep. "Reverse" communication -happens every timestep if the {newton} option is on. The data is for -atom coordinates and any other atom properties that needs to be updated +The {comm} and {comm/exchange} and {comm/forward} and {comm/reverse} +keywords determine whether the host or device performs the packing and +unpacking of data when communicating per-atom data between processors. +"Exchange" communication happens only on timesteps that neighbor lists +are rebuilt. The data is only for atoms that migrate to new processors. +"Forward" communication happens every timestep. "Reverse" communication +happens every timestep if the {newton} option is on. The data is for +atom coordinates and any other atom properties that needs to be updated for ghost atoms owned by each processor. -The {comm} keyword is simply a short-cut to set the same value for both +The {comm} keyword is simply a short-cut to set the same value for both the {comm/exchange} and {comm/forward} and {comm/reverse} keywords. -The value options for all 3 keywords are {no} or {host} or {device}. A -value of {no} means to use the standard non-KOKKOS method of -packing/unpacking data for the communication. A value of {host} means to -use the host, typically a multi-core CPU, and perform the -packing/unpacking in parallel with threads. A value of {device} means to -use the device, typically a GPU, to perform the packing/unpacking +The value options for all 3 keywords are {no} or {host} or {device}. A +value of {no} means to use the standard non-KOKKOS method of +packing/unpacking data for the communication. A value of {host} means to +use the host, typically a multi-core CPU, and perform the +packing/unpacking in parallel with threads. A value of {device} means to +use the device, typically a GPU, to perform the packing/unpacking operation. -The optimal choice for these keywords depends on the input script and -the hardware used. The {no} value is useful for verifying that the -Kokkos-based {host} and {device} values are working correctly. It is the +The optimal choice for these keywords depends on the input script and +the hardware used. The {no} value is useful for verifying that the +Kokkos-based {host} and {device} values are working correctly. It is the default when running on CPUs since it is usually the fastest. -When running on CPUs or Xeon Phi, the {host} and {device} values work -identically. When using GPUs, the {device} value is the default since it -will typically be optimal if all of your styles used in your input -script are supported by the KOKKOS package. In this case data can stay -on the GPU for many timesteps without being moved between the host and -GPU, if you use the {device} value. If your script uses styles (e.g. -fixes) which are not yet supported by the KOKKOS package, then data has -to be move between the host and device anyway, so it is typically faster -to let the host handle communication, by using the {host} value. Using -{host} instead of {no} will enable use of multiple threads to -pack/unpack communicated data. When running small systems on a GPU, -performing the exchange pack/unpack on the host CPU can give speedup +When running on CPUs or Xeon Phi, the {host} and {device} values work +identically. When using GPUs, the {device} value is the default since it +will typically be optimal if all of your styles used in your input +script are supported by the KOKKOS package. In this case data can stay +on the GPU for many timesteps without being moved between the host and +GPU, if you use the {device} value. If your script uses styles (e.g. +fixes) which are not yet supported by the KOKKOS package, then data has +to be move between the host and device anyway, so it is typically faster +to let the host handle communication, by using the {host} value. Using +{host} instead of {no} will enable use of multiple threads to +pack/unpack communicated data. When running small systems on a GPU, +performing the exchange pack/unpack on the host CPU can give speedup since it reduces the number of CUDA kernel launches. -The {cuda/aware} keyword chooses whether CUDA-aware MPI will be used. When -this keyword is set to {on}, buffers in GPU memory are passed directly -through MPI send/receive calls. This reduces overhead of first copying -the data to the host CPU. However CUDA-aware MPI is not supported on all -systems, which can lead to segmentation faults and would require using a -value of {off}. If LAMMPS can safely detect that CUDA-aware MPI is not -available (currently only possible with OpenMPI v2.0.0 or later), then -the {cuda/aware} keyword is automatically set to {off} by default. When -the {cuda/aware} keyword is set to {off} while any of the {comm} -keywords are set to {device}, the value for these {comm} keywords will -be automatically changed to {host}. This setting has no effect if not -running on GPUs. CUDA-aware MPI is available for OpenMPI 1.8 (or later +The {cuda/aware} keyword chooses whether CUDA-aware MPI will be used. When +this keyword is set to {on}, buffers in GPU memory are passed directly +through MPI send/receive calls. This reduces overhead of first copying +the data to the host CPU. However CUDA-aware MPI is not supported on all +systems, which can lead to segmentation faults and would require using a +value of {off}. If LAMMPS can safely detect that CUDA-aware MPI is not +available (currently only possible with OpenMPI v2.0.0 or later), then +the {cuda/aware} keyword is automatically set to {off} by default. When +the {cuda/aware} keyword is set to {off} while any of the {comm} +keywords are set to {device}, the value for these {comm} keywords will +be automatically changed to {host}. This setting has no effect if not +running on GPUs. CUDA-aware MPI is available for OpenMPI 1.8 (or later versions), Mvapich2 1.9 (or later) when the "MV2_USE_CUDA" environment variable is set to "1", CrayMPI, and IBM Spectrum MPI when the "-gpu" flag is used. @@ -641,16 +641,16 @@ not used, you must invoke the package intel command in your input script or via the "-pk intel" "command-line switch"_Run_options.html. -For the KOKKOS package, the option defaults for GPUs are neigh = full, -neigh/qeq = full, newton = off, binsize for GPUs = 2x LAMMPS default -value, comm = device, cuda/aware = on. When LAMMPS can safely detect -that CUDA-aware MPI is not available, the default value of cuda/aware -becomes "off". For CPUs or Xeon Phis, the option defaults are neigh = -half, neigh/qeq = half, newton = on, binsize = 0.0, and comm = no. The -option neigh/thread = on when there are 16K atoms or less on an MPI -rank, otherwise it is "off". These settings are made automatically by -the required "-k on" "command-line switch"_Run_options.html. You can -change them by using the package kokkos command in your input script or +For the KOKKOS package, the option defaults for GPUs are neigh = full, +neigh/qeq = full, newton = off, binsize for GPUs = 2x LAMMPS default +value, comm = device, cuda/aware = on. When LAMMPS can safely detect +that CUDA-aware MPI is not available, the default value of cuda/aware +becomes "off". For CPUs or Xeon Phis, the option defaults are neigh = +half, neigh/qeq = half, newton = on, binsize = 0.0, and comm = no. The +option neigh/thread = on when there are 16K atoms or less on an MPI +rank, otherwise it is "off". These settings are made automatically by +the required "-k on" "command-line switch"_Run_options.html. You can +change them by using the package kokkos command in your input script or via the "-pk kokkos command-line switch"_Run_options.html. For the OMP package, the default is Nthreads = 0 and the option diff --git a/doc/src/pair_e3b.txt b/doc/src/pair_e3b.txt index 6d1f992ca1..832b4719c3 100644 --- a/doc/src/pair_e3b.txt +++ b/doc/src/pair_e3b.txt @@ -20,8 +20,8 @@ If the {preset} keyword is given, no others are needed. Otherwise, all are mandatory except for {neigh}. The {neigh} keyword is always optional. :l {preset} arg = {2011} or {2015} = which set of predefined parameters to use - 2011 = use the potential parameters from "(Tainter 2011)"_#Tainter2011 - 2015 = use the potential parameters from "(Tainter 2015)"_#Tainter2015 + 2011 = use the potential parameters from "(Tainter 2011)"_#Tainter2011 + 2015 = use the potential parameters from "(Tainter 2015)"_#Tainter2015 {Ea} arg = three-body energy for type A hydrogen bonding interactions (energy units) {Eb} arg = three-body energy for type B hydrogen bonding interactions (energy units) {Ec} arg = three-body energy for type C hydrogen bonding interactions (energy units) diff --git a/doc/src/pair_granular.txt b/doc/src/pair_granular.txt index f16cd9fe0b..d46bea2343 100644 --- a/doc/src/pair_granular.txt +++ b/doc/src/pair_granular.txt @@ -790,4 +790,4 @@ alternative contact force models during inelastic collisions. Powder Technology, 233, 30-46. :link(WaltonPC) -[(Otis R. Walton)] Walton, O.R., Personal Communication +[(Otis R. Walton)] Walton, O.R., Personal Communication diff --git a/doc/src/pair_kolmogorov_crespi_full.txt b/doc/src/pair_kolmogorov_crespi_full.txt index 5a2623ed89..b42027aada 100644 --- a/doc/src/pair_kolmogorov_crespi_full.txt +++ b/doc/src/pair_kolmogorov_crespi_full.txt @@ -43,8 +43,8 @@ when the tapper function is turned off. The formula of taper function can be found in pair style "ilp/graphene/hbn"_pair_ilp_graphene_hbn.html. NOTE: This potential (ILP) is intended for interlayer interactions between two -different layers of graphene. To perform a realistic simulation, this potential -must be used in combination with intralayer potential, such as +different layers of graphene. To perform a realistic simulation, this potential +must be used in combination with intralayer potential, such as "AIREBO"_pair_airebo.html or "Tersoff"_pair_tersoff.html potential. To keep the intralayer properties unaffected, the interlayer interaction within the same layers should be avoided. Hence, each atom has to have a layer diff --git a/doc/src/pair_mm3_switch3_coulgauss.txt b/doc/src/pair_mm3_switch3_coulgauss.txt index 3e0e24150e..86e6a0d1d9 100644 --- a/doc/src/pair_mm3_switch3_coulgauss.txt +++ b/doc/src/pair_mm3_switch3_coulgauss.txt @@ -68,7 +68,7 @@ gamma (distance) :ul [Mixing, shift, table, tail correction, restart, rRESPA info]: -Mixing rules are fixed for this style as defined above. +Mixing rules are fixed for this style as defined above. Shifting the potential energy is not necessary because the switching function ensures that the potential is zero at the cut-off. diff --git a/doc/src/pair_oxdna2.txt b/doc/src/pair_oxdna2.txt index 3e462f384d..35e59ac9f5 100644 --- a/doc/src/pair_oxdna2.txt +++ b/doc/src/pair_oxdna2.txt @@ -27,8 +27,8 @@ args = list of arguments for these particular styles :ul {oxdna2/stk} args = seq T xi kappa 6.0 0.4 0.9 0.32 0.6 1.3 0 0.8 0.9 0 0.95 0.9 0 0.95 2.0 0.65 2.0 0.65 seq = seqav (for average sequence stacking strength) or seqdep (for sequence-dependent stacking strength) T = temperature (oxDNA units, 0.1 = 300 K) - xi = temperature-independent coefficient in stacking strength - kappa = coefficient of linear temperature dependence in stacking strength + xi = temperature-independent coefficient in stacking strength + kappa = coefficient of linear temperature dependence in stacking strength {oxdna2/hbond} args = seq eps 8.0 0.4 0.75 0.34 0.7 1.5 0 0.7 1.5 0 0.7 1.5 0 0.7 0.46 3.141592653589793 0.7 4.0 1.5707963267948966 0.45 4.0 1.5707963267948966 0.45 seq = seqav (for average sequence base-pairing strength) or seqdep (for sequence-dependent base-pairing strength) eps = 1.0678 (between base pairs A-T and C-G) or 0 (all other pairs) diff --git a/doc/src/pair_snap.txt b/doc/src/pair_snap.txt index 1fba74a188..37d1a1ed18 100644 --- a/doc/src/pair_snap.txt +++ b/doc/src/pair_snap.txt @@ -50,7 +50,7 @@ the SNAP potential files themselves. Only a single pair_coeff command is used with the {snap} style which specifies a SNAP coefficient file followed by a SNAP parameter file and then N additional arguments specifying the mapping of SNAP -elements to LAMMPS atom types, where N is the number of +elements to LAMMPS atom types, where N is the number of LAMMPS atom types: SNAP coefficient file @@ -79,7 +79,7 @@ The name of the SNAP coefficient file usually ends in the ".snapcoeff" extension. It may contain coefficients for many SNAP elements. The only requirement is that it contain at least those element names appearing in the -LAMMPS mapping list. +LAMMPS mapping list. The name of the SNAP parameter file usually ends in the ".snapparam" extension. It contains a small number of parameters that define the overall form of the SNAP potential. diff --git a/doc/src/pair_spin_dipole.txt b/doc/src/pair_spin_dipole.txt index 0d6471e07f..d903a3f07d 100644 --- a/doc/src/pair_spin_dipole.txt +++ b/doc/src/pair_spin_dipole.txt @@ -11,7 +11,7 @@ pair_style spin/dipole/long command :h3 [Syntax:] -pair_style spin/dipole/cut cutoff +pair_style spin/dipole/cut cutoff pair_style spin/dipole/long cutoff :pre cutoff = global cutoff for magnetic dipole energy and forces @@ -21,7 +21,7 @@ cutoff = global cutoff for magnetic dipole energy and forces [Examples:] pair_style spin/dipole/cut 10.0 -pair_coeff * * 10.0 +pair_coeff * * 10.0 pair_coeff 2 3 8.0 :pre pair_style spin/dipole/long 9.0 @@ -32,24 +32,24 @@ pair_coeff 2 3 1.0 1.0 2.5 4.0 :pre [Description:] Style {spin/dipole/cut} computes a short-range dipole-dipole -interaction between pairs of magnetic particles that each -have a magnetic spin. +interaction between pairs of magnetic particles that each +have a magnetic spin. The magnetic dipole-dipole interactions are computed by the -following formulas for the magnetic energy, magnetic precession +following formulas for the magnetic energy, magnetic precession vector omega and mechanical force between particles I and J. :c,image(Eqs/pair_spin_dipole.jpg) -where si and sj are the spin on two magnetic particles, -r is their separation distance, and the vector e = (Ri - Rj)/|Ri - Rj| -is the direction vector between the two particles. +where si and sj are the spin on two magnetic particles, +r is their separation distance, and the vector e = (Ri - Rj)/|Ri - Rj| +is the direction vector between the two particles. Style {spin/dipole/long} computes long-range magnetic dipole-dipole interaction. A "kspace_style"_kspace_style.html must be defined to -use this pair style. Currently, "kspace_style +use this pair style. Currently, "kspace_style ewald/dipole/spin"_kspace_style.html and "kspace_style -pppm/dipole/spin"_kspace_style.html support long-range magnetic +pppm/dipole/spin"_kspace_style.html support long-range magnetic dipole-dipole interactions. :line @@ -68,8 +68,8 @@ to be specified in an input script that reads a restart file. [Restrictions:] The {spin/dipole/cut} and {spin/dipole/long} styles are part of -the SPIN package. They are only enabled if LAMMPS was built with that -package. See the "Build package"_Build_package.html doc page for more +the SPIN package. They are only enabled if LAMMPS was built with that +package. See the "Build package"_Build_package.html doc page for more info. Using dipole/spin pair styles with {electron} "units"_units.html is not diff --git a/doc/src/pair_spin_dmi.txt b/doc/src/pair_spin_dmi.txt index 9ddff8a8dc..cca20d1136 100644 --- a/doc/src/pair_spin_dmi.txt +++ b/doc/src/pair_spin_dmi.txt @@ -15,11 +15,11 @@ pair_style spin/dmi cutoff :pre cutoff = global cutoff pair (distance in metal units) :ulb,l :ule - + [Examples:] pair_style spin/dmi 4.0 -pair_coeff * * dmi 2.6 0.001 1.0 0.0 0.0 +pair_coeff * * dmi 2.6 0.001 1.0 0.0 0.0 pair_coeff 1 2 dmi 4.0 0.00109 0.0 0.0 1.0 :pre [Description:] diff --git a/doc/src/pair_spin_neel.txt b/doc/src/pair_spin_neel.txt index 009ef7947d..b255f23a09 100644 --- a/doc/src/pair_spin_neel.txt +++ b/doc/src/pair_spin_neel.txt @@ -15,7 +15,7 @@ pair_style spin/neel cutoff :pre cutoff = global cutoff pair (distance in metal units) :ulb,l :ule - + [Examples:] pair_style spin/neel 4.0 From 27f9ae1017003ff19a074ef33e4bbc387997c278 Mon Sep 17 00:00:00 2001 From: Axel Kohlmeyer Date: Tue, 17 Sep 2019 08:37:32 -0400 Subject: [PATCH 148/192] evil tab removal --- src/USER-MISC/pair_ilp_graphene_hbn.h | 2 +- src/USER-MISC/pair_kolmogorov_crespi_full.h | 2 +- src/kspace.h | 2 +- 3 files changed, 3 insertions(+), 3 deletions(-) diff --git a/src/USER-MISC/pair_ilp_graphene_hbn.h b/src/USER-MISC/pair_ilp_graphene_hbn.h index ec6146fa33..5ca8eb64a7 100644 --- a/src/USER-MISC/pair_ilp_graphene_hbn.h +++ b/src/USER-MISC/pair_ilp_graphene_hbn.h @@ -48,7 +48,7 @@ class PairILPGrapheneHBN : public Pair { MyPage *ipage; // neighbor list pages int *ILP_numneigh; // # of pair neighbors for each atom int **ILP_firstneigh; // ptr to 1st neighbor of each atom - int tap_flag; // flag to turn on/off taper function + int tap_flag; // flag to turn on/off taper function struct Param { double z0,alpha,epsilon,C,delta,d,sR,reff,C6,S; diff --git a/src/USER-MISC/pair_kolmogorov_crespi_full.h b/src/USER-MISC/pair_kolmogorov_crespi_full.h index d2971e3fbc..c579788110 100644 --- a/src/USER-MISC/pair_kolmogorov_crespi_full.h +++ b/src/USER-MISC/pair_kolmogorov_crespi_full.h @@ -48,7 +48,7 @@ class PairKolmogorovCrespiFull : public Pair { MyPage *ipage; // neighbor list pages int *KC_numneigh; // # of pair neighbors for each atom int **KC_firstneigh; // ptr to 1st neighbor of each atom - int tap_flag; // flag to turn on/off taper function + int tap_flag; // flag to turn on/off taper function struct Param { diff --git a/src/kspace.h b/src/kspace.h index c04a0db989..60df2345fd 100644 --- a/src/kspace.h +++ b/src/kspace.h @@ -44,7 +44,7 @@ class KSpace : protected Pointers { int dispersionflag; // 1 if a LJ/dispersion solver int tip4pflag; // 1 if a TIP4P solver int dipoleflag; // 1 if a dipole solver - int spinflag; // 1 if a spin solver + int spinflag; // 1 if a spin solver int differentiation_flag; int neighrequest_flag; // used to avoid obsolete construction // of neighbor lists From 7f037b6c3053d36ba51c2426a1f006abbf7be083 Mon Sep 17 00:00:00 2001 From: Axel Kohlmeyer Date: Tue, 17 Sep 2019 12:05:04 -0400 Subject: [PATCH 149/192] some more whitespace cleanup --- src/KOKKOS/npair_kokkos.h | 4 ++-- src/KOKKOS/pair_gran_hooke_history_kokkos.h | 8 ++++---- src/KSPACE/ewald_dipole.h | 6 +++--- 3 files changed, 9 insertions(+), 9 deletions(-) diff --git a/src/KOKKOS/npair_kokkos.h b/src/KOKKOS/npair_kokkos.h index 2a3994f584..7650bf3350 100644 --- a/src/KOKKOS/npair_kokkos.h +++ b/src/KOKKOS/npair_kokkos.h @@ -443,7 +443,7 @@ struct NPairKokkosBuildFunctorSize { const size_t sharedsize; NPairKokkosBuildFunctorSize(const NeighborKokkosExecute &_c, - const size_t _sharedsize): c(_c), sharedsize(_sharedsize) {}; + const size_t _sharedsize): c(_c), sharedsize(_sharedsize) {}; KOKKOS_INLINE_FUNCTION void operator() (const int & i) const { @@ -467,7 +467,7 @@ struct NPairKokkosBuildFunctorSize { const size_t sharedsize; NPairKokkosBuildFunctorSize(const NeighborKokkosExecute &_c, - const size_t _sharedsize): c(_c), sharedsize(_sharedsize) {}; + const size_t _sharedsize): c(_c), sharedsize(_sharedsize) {}; KOKKOS_INLINE_FUNCTION void operator() (const int & i) const { diff --git a/src/KOKKOS/pair_gran_hooke_history_kokkos.h b/src/KOKKOS/pair_gran_hooke_history_kokkos.h index 8d1778e091..e40353d970 100644 --- a/src/KOKKOS/pair_gran_hooke_history_kokkos.h +++ b/src/KOKKOS/pair_gran_hooke_history_kokkos.h @@ -61,13 +61,13 @@ class PairGranHookeHistoryKokkos : public PairGranHookeHistory { template KOKKOS_INLINE_FUNCTION void ev_tally_xyz(EV_FLOAT &ev, int i, int j, - F_FLOAT fx, F_FLOAT fy, F_FLOAT fz, - X_FLOAT delx, X_FLOAT dely, X_FLOAT delz) const; + F_FLOAT fx, F_FLOAT fy, F_FLOAT fz, + X_FLOAT delx, X_FLOAT dely, X_FLOAT delz) const; template KOKKOS_INLINE_FUNCTION void ev_tally_xyz_atom(EV_FLOAT &ev, int i, int j, - F_FLOAT fx, F_FLOAT fy, F_FLOAT fz, - X_FLOAT delx, X_FLOAT dely, X_FLOAT delz) const; + F_FLOAT fx, F_FLOAT fy, F_FLOAT fz, + X_FLOAT delx, X_FLOAT dely, X_FLOAT delz) const; protected: typename AT::t_x_array_randomread x; diff --git a/src/KSPACE/ewald_dipole.h b/src/KSPACE/ewald_dipole.h index 741756487b..c8dd18565c 100644 --- a/src/KSPACE/ewald_dipole.h +++ b/src/KSPACE/ewald_dipole.h @@ -34,10 +34,10 @@ class EwaldDipole : public Ewald { protected: double musum,musqsum,mu2; - double **tk; // field for torque - double **vc; // virial per k + double **tk; // field for torque + double **vc; // virial per k - void musum_musq(); + void musum_musq(); double rms_dipole(int, double, bigint); virtual void eik_dot_r(); void slabcorr(); From 5cf0a5bf6d30fd87d093a909aec5febc93c9ce99 Mon Sep 17 00:00:00 2001 From: Michael Brown Date: Tue, 17 Sep 2019 09:31:51 -0700 Subject: [PATCH 150/192] USER-INTEL: Reverting whitespace in Makefiles from last changes. --- src/MAKE/OPTIONS/Makefile.intel_cpu | 2 +- src/MAKE/OPTIONS/Makefile.intel_cpu_intelmpi | 2 +- src/MAKE/OPTIONS/Makefile.intel_cpu_mpich | 2 +- src/MAKE/OPTIONS/Makefile.intel_cpu_openmpi | 2 +- src/MAKE/OPTIONS/Makefile.knl | 9 ++++----- 5 files changed, 8 insertions(+), 9 deletions(-) diff --git a/src/MAKE/OPTIONS/Makefile.intel_cpu b/src/MAKE/OPTIONS/Makefile.intel_cpu index dd3e11ca1d..57e25e30cd 100644 --- a/src/MAKE/OPTIONS/Makefile.intel_cpu +++ b/src/MAKE/OPTIONS/Makefile.intel_cpu @@ -9,7 +9,7 @@ SHELL = /bin/sh CC = mpiicpc OPTFLAGS = -xHost -O2 -fp-model fast=2 -no-prec-div -qoverride-limits \ -qopt-zmm-usage=high -CCFLAGS = -qopenmp -qno-offload -ansi-alias -restrict \ +CCFLAGS = -qopenmp -qno-offload -ansi-alias -restrict \ -DLMP_INTEL_USELRT -DLMP_USE_MKL_RNG $(OPTFLAGS) \ -I$(MKLROOT)/include SHFLAGS = -fPIC diff --git a/src/MAKE/OPTIONS/Makefile.intel_cpu_intelmpi b/src/MAKE/OPTIONS/Makefile.intel_cpu_intelmpi index 3dc8449d14..1731203cb0 100644 --- a/src/MAKE/OPTIONS/Makefile.intel_cpu_intelmpi +++ b/src/MAKE/OPTIONS/Makefile.intel_cpu_intelmpi @@ -9,7 +9,7 @@ SHELL = /bin/sh CC = mpiicpc OPTFLAGS = -xHost -O2 -fp-model fast=2 -no-prec-div -qoverride-limits \ -qopt-zmm-usage=high -CCFLAGS = -qopenmp -qno-offload -ansi-alias -restrict \ +CCFLAGS = -qopenmp -qno-offload -ansi-alias -restrict \ -DLMP_INTEL_USELRT -DLMP_USE_MKL_RNG $(OPTFLAGS) \ -I$(MKLROOT)/include SHFLAGS = -fPIC diff --git a/src/MAKE/OPTIONS/Makefile.intel_cpu_mpich b/src/MAKE/OPTIONS/Makefile.intel_cpu_mpich index a59b7d1d3a..9419537006 100644 --- a/src/MAKE/OPTIONS/Makefile.intel_cpu_mpich +++ b/src/MAKE/OPTIONS/Makefile.intel_cpu_mpich @@ -9,7 +9,7 @@ SHELL = /bin/sh CC = mpicxx -cxx=icc OPTFLAGS = -xHost -O2 -fp-model fast=2 -no-prec-div -qoverride-limits \ -qopt-zmm-usage=high -CCFLAGS = -qopenmp -qno-offload -ansi-alias -restrict \ +CCFLAGS = -qopenmp -qno-offload -ansi-alias -restrict \ -DLMP_INTEL_USELRT -DLMP_USE_MKL_RNG $(OPTFLAGS) \ -I$(MKLROOT)/include SHFLAGS = -fPIC diff --git a/src/MAKE/OPTIONS/Makefile.intel_cpu_openmpi b/src/MAKE/OPTIONS/Makefile.intel_cpu_openmpi index e285102426..c983943f5e 100644 --- a/src/MAKE/OPTIONS/Makefile.intel_cpu_openmpi +++ b/src/MAKE/OPTIONS/Makefile.intel_cpu_openmpi @@ -10,7 +10,7 @@ export OMPI_CXX = icc CC = mpicxx OPTFLAGS = -xHost -O2 -fp-model fast=2 -no-prec-div -qoverride-limits \ -qopt-zmm-usage=high -CCFLAGS = -qopenmp -qno-offload -ansi-alias -restrict \ +CCFLAGS = -qopenmp -qno-offload -ansi-alias -restrict \ -DLMP_INTEL_USELRT -DLMP_USE_MKL_RNG $(OPTFLAGS) \ -I$(MKLROOT)/include SHFLAGS = -fPIC diff --git a/src/MAKE/OPTIONS/Makefile.knl b/src/MAKE/OPTIONS/Makefile.knl index 7ad806c100..a361e9e258 100644 --- a/src/MAKE/OPTIONS/Makefile.knl +++ b/src/MAKE/OPTIONS/Makefile.knl @@ -8,15 +8,15 @@ SHELL = /bin/sh CC = mpiicpc OPTFLAGS = -xMIC-AVX512 -O2 -fp-model fast=2 -no-prec-div -qoverride-limits -CCFLAGS = -qopenmp -qno-offload -ansi-alias -restrict \ +CCFLAGS = -qopenmp -qno-offload -ansi-alias -restrict \ -DLMP_INTEL_USELRT -DLMP_USE_MKL_RNG $(OPTFLAGS) \ -I$(MKLROOT)/include SHFLAGS = -fPIC DEPFLAGS = -M LINK = mpiicpc -LINKFLAGS = -qopenmp $(OPTFLAGS) -LIB = -ltbbmalloc +LINKFLAGS = -qopenmp $(OPTFLAGS) -L$(MKLROOT)/lib/intel64/ +LIB = -ltbbmalloc -lmkl_intel_ilp64 -lmkl_sequential -lmkl_core SIZE = size ARCHIVE = ar @@ -55,8 +55,7 @@ MPI_LIB = FFT_INC = -DFFT_MKL -DFFT_SINGLE FFT_PATH = -FFT_LIB = -L$(MKLROOT)/lib/intel64/ -lmkl_intel_ilp64 \ - -lmkl_sequential -lmkl_core +FFT_LIB = # JPEG and/or PNG library # see discussion in Section 2.2 (step 7) of manual From 8ff6122560d2e6f83035cd6b3dbd70f82c86f348 Mon Sep 17 00:00:00 2001 From: Axel Kohlmeyer Date: Tue, 17 Sep 2019 14:48:11 -0400 Subject: [PATCH 151/192] correct documentation of improper style fourier --- doc/src/improper_fourier.txt | 16 ++++++++-------- 1 file changed, 8 insertions(+), 8 deletions(-) diff --git a/doc/src/improper_fourier.txt b/doc/src/improper_fourier.txt index 1b569b3894..f4f59ed636 100644 --- a/doc/src/improper_fourier.txt +++ b/doc/src/improper_fourier.txt @@ -16,7 +16,7 @@ improper_style fourier :pre [Examples:] improper_style fourier -improper_coeff 1 100.0 180.0 :pre +improper_coeff 1 100.0 0.0 1.0 0.5 1 :pre [Description:] @@ -24,12 +24,12 @@ The {fourier} improper style uses the following potential: :c,image(Eqs/improper_fourier.jpg) -where K is the force constant and omega is the angle between the IL -axis and the IJK plane: +where K is the force constant, C0, C1, C2 are dimensionless coefficients, +and omega is the angle between the IL axis and the IJK plane: :c,image(JPG/umbrella.jpg) -If all parameter (see bellow) is not zero, the all the three possible angles will taken in account. +If all parameter (see below) is not zero, the all the three possible angles will taken in account. The following coefficients must be defined for each improper type via the "improper_coeff"_improper_coeff.html command as in the example @@ -38,10 +38,10 @@ above, or in the data file or restart files read by the commands: K (energy) -C0 (real) -C1 (real) -C2 (real) -all (integer >= 0) :ul +C0 (unitless) +C1 (unitless) +C2 (unitless) +all (0 or 1, optional) :ul :line From d4d5f241ebe1e49bbb2c3ae16dbc9fc217b2a75c Mon Sep 17 00:00:00 2001 From: Axel Kohlmeyer Date: Tue, 17 Sep 2019 14:48:58 -0400 Subject: [PATCH 152/192] use improper style fourier instead of non-existing style opls --- examples/USER/drude/toluene/data.toluene | 8 +- examples/USER/drude/toluene/in.toluene.lang | 4 +- examples/USER/drude/toluene/in.toluene.nh | 4 +- .../toluene/log.27Nov18.toluene.lang.g++.1 | 14 - .../toluene/log.27Nov18.toluene.lang.g++.4 | 14 - .../toluene/log.27Nov18.toluene.nh.g++.1 | 14 - .../toluene/log.27Nov18.toluene.nh.g++.4 | 14 - .../toluene/log.7Aug19.toluene.lang.g++.1 | 254 +++++++++++++++++ .../toluene/log.7Aug19.toluene.lang.g++.4 | 254 +++++++++++++++++ .../drude/toluene/log.7Aug19.toluene.nh.g++.1 | 262 ++++++++++++++++++ .../drude/toluene/log.7Aug19.toluene.nh.g++.4 | 262 ++++++++++++++++++ 11 files changed, 1040 insertions(+), 64 deletions(-) delete mode 100644 examples/USER/drude/toluene/log.27Nov18.toluene.lang.g++.1 delete mode 100644 examples/USER/drude/toluene/log.27Nov18.toluene.lang.g++.4 delete mode 100644 examples/USER/drude/toluene/log.27Nov18.toluene.nh.g++.1 delete mode 100644 examples/USER/drude/toluene/log.27Nov18.toluene.nh.g++.4 create mode 100644 examples/USER/drude/toluene/log.7Aug19.toluene.lang.g++.1 create mode 100644 examples/USER/drude/toluene/log.7Aug19.toluene.lang.g++.4 create mode 100644 examples/USER/drude/toluene/log.7Aug19.toluene.nh.g++.1 create mode 100644 examples/USER/drude/toluene/log.7Aug19.toluene.nh.g++.4 diff --git a/examples/USER/drude/toluene/data.toluene b/examples/USER/drude/toluene/data.toluene index 48d44016d7..d67af7c311 100644 --- a/examples/USER/drude/toluene/data.toluene +++ b/examples/USER/drude/toluene/data.toluene @@ -79,10 +79,10 @@ Dihedral Coeffs Improper Coeffs - 1 0.0000 2.1999 0.0000 0.0000 # CAO-CAO-CAT-CTT - 2 0.0000 2.1999 0.0000 0.0000 # CAT-CAM-CAO-HAT - 3 0.0000 2.1999 0.0000 0.0000 # CAO-CAP-CAM-HAT - 4 0.0000 2.1999 0.0000 0.0000 # CAM-CAM-CAP-HAT + 1 2.1999 0.0000 0.0000 -1.0000 0 # CAO-CAO-CAT-CTT + 2 2.1999 0.0000 0.0000 -1.0000 0 # CAT-CAM-CAO-HAT + 3 2.1999 0.0000 0.0000 -1.0000 0 # CAO-CAP-CAM-HAT + 4 2.1999 0.0000 0.0000 -1.0000 0 # CAM-CAM-CAP-HAT Atoms diff --git a/examples/USER/drude/toluene/in.toluene.lang b/examples/USER/drude/toluene/in.toluene.lang index 8f00c24a4b..ba40a3bcde 100644 --- a/examples/USER/drude/toluene/in.toluene.lang +++ b/examples/USER/drude/toluene/in.toluene.lang @@ -7,7 +7,7 @@ atom_style full bond_style harmonic angle_style harmonic dihedral_style opls -improper_style opls +improper_style fourier special_bonds lj/coul 0.0 0.0 0.5 pair_style lj/cut/thole/long 2.600 8.0 8.0 @@ -109,7 +109,7 @@ fix fNPH all nve compute cTEMP all temp/drude -thermo_style custom step cpu etotal ke temp pe ebond eangle edihed eimp evdwl ecoul elong press vol c_cTEMP[1] c_cTEMP[2] +thermo_style custom step etotal ke temp pe ebond eangle edihed eimp evdwl ecoul elong press vol c_cTEMP[1] c_cTEMP[2] thermo 50 timestep 0.5 diff --git a/examples/USER/drude/toluene/in.toluene.nh b/examples/USER/drude/toluene/in.toluene.nh index 05b35ca919..7a5aecc579 100644 --- a/examples/USER/drude/toluene/in.toluene.nh +++ b/examples/USER/drude/toluene/in.toluene.nh @@ -7,7 +7,7 @@ atom_style full bond_style harmonic angle_style harmonic dihedral_style opls -improper_style opls +improper_style fourier special_bonds lj/coul 0.0 0.0 0.5 pair_style lj/cut/thole/long 2.600 8.0 8.0 @@ -115,7 +115,7 @@ fix fINVERSE all drude/transform/inverse fix fMOMENTUM all momentum 100 linear 1 1 1 -thermo_style custom step cpu etotal ke temp pe ebond eangle edihed eimp evdwl ecoul elong press vol c_cTEMP[1] c_cTEMP[2] +thermo_style custom step etotal ke temp pe ebond eangle edihed eimp evdwl ecoul elong press vol c_cTEMP[1] c_cTEMP[2] thermo 50 timestep 0.5 diff --git a/examples/USER/drude/toluene/log.27Nov18.toluene.lang.g++.1 b/examples/USER/drude/toluene/log.27Nov18.toluene.lang.g++.1 deleted file mode 100644 index 08cc2f0f5c..0000000000 --- a/examples/USER/drude/toluene/log.27Nov18.toluene.lang.g++.1 +++ /dev/null @@ -1,14 +0,0 @@ -LAMMPS (27 Nov 2018) - using 1 OpenMP thread(s) per MPI task -# 250 toluene system for drude polarizability example (Langevin) - -units real -boundary p p p - -atom_style full -bond_style harmonic -angle_style harmonic -dihedral_style opls -improper_style opls -ERROR: Unknown improper style opls (src/force.cpp:634) -Last command: improper_style opls diff --git a/examples/USER/drude/toluene/log.27Nov18.toluene.lang.g++.4 b/examples/USER/drude/toluene/log.27Nov18.toluene.lang.g++.4 deleted file mode 100644 index 08cc2f0f5c..0000000000 --- a/examples/USER/drude/toluene/log.27Nov18.toluene.lang.g++.4 +++ /dev/null @@ -1,14 +0,0 @@ -LAMMPS (27 Nov 2018) - using 1 OpenMP thread(s) per MPI task -# 250 toluene system for drude polarizability example (Langevin) - -units real -boundary p p p - -atom_style full -bond_style harmonic -angle_style harmonic -dihedral_style opls -improper_style opls -ERROR: Unknown improper style opls (src/force.cpp:634) -Last command: improper_style opls diff --git a/examples/USER/drude/toluene/log.27Nov18.toluene.nh.g++.1 b/examples/USER/drude/toluene/log.27Nov18.toluene.nh.g++.1 deleted file mode 100644 index a6807f8ee1..0000000000 --- a/examples/USER/drude/toluene/log.27Nov18.toluene.nh.g++.1 +++ /dev/null @@ -1,14 +0,0 @@ -LAMMPS (27 Nov 2018) - using 1 OpenMP thread(s) per MPI task -# 250 toluene system for drude polarizability example (Nose-Hoover) - -units real -boundary p p p - -atom_style full -bond_style harmonic -angle_style harmonic -dihedral_style opls -improper_style opls -ERROR: Unknown improper style opls (src/force.cpp:634) -Last command: improper_style opls diff --git a/examples/USER/drude/toluene/log.27Nov18.toluene.nh.g++.4 b/examples/USER/drude/toluene/log.27Nov18.toluene.nh.g++.4 deleted file mode 100644 index a6807f8ee1..0000000000 --- a/examples/USER/drude/toluene/log.27Nov18.toluene.nh.g++.4 +++ /dev/null @@ -1,14 +0,0 @@ -LAMMPS (27 Nov 2018) - using 1 OpenMP thread(s) per MPI task -# 250 toluene system for drude polarizability example (Nose-Hoover) - -units real -boundary p p p - -atom_style full -bond_style harmonic -angle_style harmonic -dihedral_style opls -improper_style opls -ERROR: Unknown improper style opls (src/force.cpp:634) -Last command: improper_style opls diff --git a/examples/USER/drude/toluene/log.7Aug19.toluene.lang.g++.1 b/examples/USER/drude/toluene/log.7Aug19.toluene.lang.g++.1 new file mode 100644 index 0000000000..71ffdb0c8c --- /dev/null +++ b/examples/USER/drude/toluene/log.7Aug19.toluene.lang.g++.1 @@ -0,0 +1,254 @@ +LAMMPS (7 Aug 2019) +OMP_NUM_THREADS environment is not set. Defaulting to 1 thread. (src/comm.cpp:93) + using 1 OpenMP thread(s) per MPI task +# 250 toluene system for drude polarizability example (Langevin) + +units real +boundary p p p + +atom_style full +bond_style harmonic +angle_style harmonic +dihedral_style opls +improper_style fourier +special_bonds lj/coul 0.0 0.0 0.5 + +pair_style lj/cut/thole/long 2.600 8.0 8.0 +pair_modify mix geometric tail yes +kspace_style pppm 1.0e-4 + +read_data data.toluene extra/special/per/atom 1 + orthogonal box = (-18.2908 -18.1636 -18.223) to (18.3357 18.1621 18.3287) + 1 by 1 by 1 MPI processor grid + reading atoms ... + 5500 atoms + scanning bonds ... + 4 = max bonds/atom + scanning angles ... + 6 = max angles/atom + scanning dihedrals ... + 8 = max dihedrals/atom + scanning impropers ... + 2 = max impropers/atom + reading bonds ... + 5500 bonds + reading angles ... + 6000 angles + reading dihedrals ... + 6000 dihedrals + reading impropers ... + 1500 impropers + 5 = max # of 1-2 neighbors + 10 = max # of 1-3 neighbors + 16 = max # of 1-4 neighbors + 20 = max # of special neighbors + special bonds CPU = 0.00199628 secs + read_data CPU = 0.0169649 secs + +comm_modify vel yes + +group gTOLUENE molecule 1:250 +5500 atoms in group gTOLUENE +group gCORES type 1 2 3 4 5 6 7 +3750 atoms in group gCORES +group gDRUDES type 8 9 10 11 12 +1750 atoms in group gDRUDES + +pair_coeff 1 1 0.069998 3.550000 1.620000 # CAT CAT +pair_coeff 1 2 0.069998 3.550000 1.620000 # CAT CAO +pair_coeff 1 3 0.069998 3.550000 1.620000 # CAT CAM +pair_coeff 1 4 0.069998 3.550000 1.620000 # CAT CAP +pair_coeff 1 5 0.067968 3.524911 1.620000 # CAT CTT +pair_coeff 1 6 0.045825 2.931041 0.000000 # CAT HAT +pair_coeff 1 7 0.045825 2.931041 0.000000 # CAT HT +pair_coeff 2 2 0.069998 3.550000 1.620000 # CAO CAO +pair_coeff 2 3 0.069998 3.550000 1.620000 # CAO CAM +pair_coeff 2 4 0.069998 3.550000 1.620000 # CAO CAP +pair_coeff 2 5 0.067968 3.524911 1.620000 # CAO CTT +pair_coeff 2 6 0.045825 2.931041 0.000000 # CAO HAT +pair_coeff 2 7 0.045825 2.931041 0.000000 # CAO HT +pair_coeff 3 3 0.069998 3.550000 1.620000 # CAM CAM +pair_coeff 3 4 0.069998 3.550000 1.620000 # CAM CAP +pair_coeff 3 5 0.067968 3.524911 1.620000 # CAM CTT +pair_coeff 3 6 0.045825 2.931041 0.000000 # CAM HAT +pair_coeff 3 7 0.045825 2.931041 0.000000 # CAM HT +pair_coeff 4 4 0.069998 3.550000 1.620000 # CAP CAP +pair_coeff 4 5 0.067968 3.524911 1.620000 # CAP CTT +pair_coeff 4 6 0.045825 2.931041 0.000000 # CAP HAT +pair_coeff 4 7 0.045825 2.931041 0.000000 # CAP HT +pair_coeff 5 5 0.065997 3.500000 1.620000 # CTT CTT +pair_coeff 5 6 0.044496 2.910326 0.000000 # CTT HAT +pair_coeff 5 7 0.044496 2.910326 0.000000 # CTT HT +pair_coeff 6 6 0.029999 2.420000 0.000000 # HAT HAT +pair_coeff 6 7 0.029999 2.420000 0.000000 # HAT HT +pair_coeff 7 7 0.029999 2.420000 0.000000 # HT HT +pair_coeff 1 8 0.000000 0.000000 1.620000 # CAT D_CAT +pair_coeff 1 9 0.000000 0.000000 1.620000 # CAT D_CAO +pair_coeff 1 10 0.000000 0.000000 1.620000 # CAT D_CAM +pair_coeff 1 11 0.000000 0.000000 1.620000 # CAT D_CAP +pair_coeff 1 12 0.000000 0.000000 1.620000 # CAT D_CTT +pair_coeff 2 8 0.000000 0.000000 1.620000 # CAO D_CAT +pair_coeff 2 9 0.000000 0.000000 1.620000 # CAO D_CAO +pair_coeff 2 10 0.000000 0.000000 1.620000 # CAO D_CAM +pair_coeff 2 11 0.000000 0.000000 1.620000 # CAO D_CAP +pair_coeff 2 12 0.000000 0.000000 1.620000 # CAO D_CTT +pair_coeff 3 8 0.000000 0.000000 1.620000 # CAM D_CAT +pair_coeff 3 9 0.000000 0.000000 1.620000 # CAM D_CAO +pair_coeff 3 10 0.000000 0.000000 1.620000 # CAM D_CAM +pair_coeff 3 11 0.000000 0.000000 1.620000 # CAM D_CAP +pair_coeff 3 12 0.000000 0.000000 1.620000 # CAM D_CTT +pair_coeff 4 8 0.000000 0.000000 1.620000 # CAP D_CAT +pair_coeff 4 9 0.000000 0.000000 1.620000 # CAP D_CAO +pair_coeff 4 10 0.000000 0.000000 1.620000 # CAP D_CAM +pair_coeff 4 11 0.000000 0.000000 1.620000 # CAP D_CAP +pair_coeff 4 12 0.000000 0.000000 1.620000 # CAP D_CTT +pair_coeff 5 8 0.000000 0.000000 1.620000 # CTT D_CAT +pair_coeff 5 9 0.000000 0.000000 1.620000 # CTT D_CAO +pair_coeff 5 10 0.000000 0.000000 1.620000 # CTT D_CAM +pair_coeff 5 11 0.000000 0.000000 1.620000 # CTT D_CAP +pair_coeff 5 12 0.000000 0.000000 1.620000 # CTT D_CTT +pair_coeff 8 8 0.000000 0.000000 1.620000 # D_CAT D_CAT +pair_coeff 8 9 0.000000 0.000000 1.620000 # D_CAT D_CAO +pair_coeff 8 10 0.000000 0.000000 1.620000 # D_CAT D_CAM +pair_coeff 8 11 0.000000 0.000000 1.620000 # D_CAT D_CAP +pair_coeff 8 12 0.000000 0.000000 1.620000 # D_CAT D_CTT +pair_coeff 9 9 0.000000 0.000000 1.620000 # D_CAO D_CAO +pair_coeff 9 10 0.000000 0.000000 1.620000 # D_CAO D_CAM +pair_coeff 9 11 0.000000 0.000000 1.620000 # D_CAO D_CAP +pair_coeff 9 12 0.000000 0.000000 1.620000 # D_CAO D_CTT +pair_coeff 10 10 0.000000 0.000000 1.620000 # D_CAM D_CAM +pair_coeff 10 11 0.000000 0.000000 1.620000 # D_CAM D_CAP +pair_coeff 10 12 0.000000 0.000000 1.620000 # D_CAM D_CTT +pair_coeff 11 11 0.000000 0.000000 1.620000 # D_CAP D_CAP +pair_coeff 11 12 0.000000 0.000000 1.620000 # D_CAP D_CTT +pair_coeff 12 12 0.000000 0.000000 1.620000 # D_CTT D_CTT + +neighbor 2.0 bin + +variable vTEMP equal 260.0 +variable vTEMP_D equal 1.0 +variable vPRESS equal 1.0 + +velocity gCORES create ${vTEMP} 12345 +velocity gCORES create 260 12345 +velocity gDRUDES create ${vTEMP_D} 12345 +velocity gDRUDES create 1 12345 + +fix fDRUDE all drude C C C C C N N D D D D D + +fix fSHAKE gCORES shake 0.0001 20 0 b 4 6 7 8 + 1250 = # of size 2 clusters + 0 = # of size 3 clusters + 250 = # of size 4 clusters + 0 = # of frozen angles + find clusters CPU = 0.000807762 secs + +fix fLANG all langevin/drude ${vTEMP} 100.0 200611 ${vTEMP_D} 20.0 260514 zero yes +fix fLANG all langevin/drude 260 100.0 200611 ${vTEMP_D} 20.0 260514 zero yes +fix fLANG all langevin/drude 260 100.0 200611 1 20.0 260514 zero yes +fix fNPH all nve + +compute cTEMP all temp/drude + +thermo_style custom step etotal ke temp pe ebond eangle edihed eimp evdwl ecoul elong press vol c_cTEMP[1] c_cTEMP[2] +thermo 50 + +timestep 0.5 +run 2000 +PPPM initialization ... + using 12-bit tables for long-range coulomb (src/kspace.cpp:323) + G vector (1/distance) = 0.382011 + grid = 40 40 40 + stencil order = 5 + estimated absolute RMS force accuracy = 0.0325934 + estimated relative force accuracy = 9.8154e-05 + using double precision FFTW3 + 3d grid and FFT values/proc = 103823 64000 +Rebuild special list taking Drude particles into account +Old max number of 1-2 to 1-4 neighbors: 19 +New max number of 1-2 to 1-4 neighbors: 20 (+1) +Neighbor list info ... + update every 1 steps, delay 10 steps, check yes + max neighbors/atom: 2000, page size: 100000 + master list distance cutoff = 10 + ghost atom cutoff = 10 + binsize = 5, bins = 8 8 8 + 1 neighbor lists, perpetual/occasional/extra = 1 0 0 + (1) pair lj/cut/thole/long, perpetual + attributes: half, newton on + pair build: half/bin/newton + stencil: half/bin/3d/newton + bin: standard +Per MPI rank memory allocation (min/avg/max) = 42.06 | 42.06 | 42.06 Mbytes +Step TotEng KinEng Temp PotEng E_bond E_angle E_dihed E_impro E_vdwl E_coul E_long Press Volume c_cTEMP[1] c_cTEMP[2] + 0 11086.347 2910.7282 202.07402 8175.6191 6565.4851 20.333365 1.0706727e-06 -3299.85 4972.8631 1306116.6 -1306199.8 40273.68 48631.318 314.89553 3.1777821 + 50 4782.1702 4728.7435 328.28767 53.426722 1812.2203 685.37824 683.70917 -3277.1645 797.34329 1305983.2 -1306631.2 16874.358 48631.318 448.52419 116.25477 + 100 2906.0879 3699.8031 256.85465 -793.7152 978.15364 778.36908 862.30899 -3270.1722 468.44888 1306096.8 -1306707.6 15631.384 48631.318 382.26408 35.748403 + 150 2089.0918 3593.0499 249.44342 -1503.9581 751.32283 803.47802 668.4757 -3277.5983 128.17444 1306138.5 -1306716.3 15193.04 48631.318 384.75632 10.892446 + 200 1547.3302 3248.639 225.53309 -1701.3089 699.65977 814.31164 692.83227 -3276.3957 -66.671816 1306160.9 -1306725.9 13787.676 48631.318 351.28242 3.8458668 + 250 1177.9323 3095.949 214.93276 -1918.0167 688.87262 842.44531 615.89218 -3278.4465 -210.06178 1306154.3 -1306731 8808.5835 48631.318 335.8115 1.8330994 + 300 895.90313 2870.3451 199.27046 -1974.442 734.95873 858.58147 624.00862 -3278.6022 -342.01951 1306163.6 -1306735 3388.4841 48631.318 311.56815 1.2987715 + 350 669.25785 2764.9587 191.95413 -2095.7009 662.44028 860.79714 602.69567 -3278.776 -376.37081 1306172.3 -1306738.8 8494.9184 48631.318 300.19414 1.1358594 + 400 531.21609 2722.6775 189.01881 -2191.4614 684.34049 868.77818 576.86096 -3280.1649 -459.66591 1306160 -1306741.6 6726.3087 48631.318 295.59622 1.1315427 + 450 427.05425 2611.7588 181.3184 -2184.7046 719.2042 891.88178 591.2282 -3279.339 -534.65069 1306172.2 -1306745.2 2398.5394 48631.318 283.56126 1.0726045 + 500 310.44891 2556.0967 177.45412 -2245.6477 720.86526 841.50195 586.3417 -3279.3029 -539.81715 1306169.5 -1306744.8 3028.595 48631.318 277.52314 1.0406334 + 550 207.83114 2531.3051 175.73299 -2323.4739 674.71188 855.2132 555.53227 -3280.0378 -553.93222 1306171.9 -1306746.9 4609.4408 48631.318 274.80629 1.0748601 + 600 88.81557 2459.9059 170.77619 -2371.0903 692.4485 834.47484 550.85905 -3280.9086 -595.31802 1306171.4 -1306744 2107.9995 48631.318 267.06312 1.0301965 + 650 75.616307 2416.9747 167.79573 -2341.3584 703.57186 869.98959 564.81201 -3280.7522 -619.8016 1306168 -1306747.2 1236.4829 48631.318 262.3542 1.0968447 + 700 49.832719 2415.7344 167.70963 -2365.9017 683.61663 882.67915 555.23571 -3280.7778 -615.06862 1306159.9 -1306751.4 2985.7048 48631.318 262.23095 1.0762424 + 750 41.513638 2427.218 168.50687 -2385.7044 698.87619 863.2938 564.58197 -3280.0156 -637.29964 1306160.1 -1306755.3 1653.117 48631.318 263.49803 1.0451977 + 800 109.53032 2481.9041 172.30339 -2372.3738 697.22709 897.36555 561.28745 -3280.6784 -651.29564 1306155 -1306751.3 1219.8761 48631.318 269.43698 1.0647792 + 850 98.142203 2502.3132 173.72026 -2404.171 696.5382 878.83293 566.44302 -3280.2837 -663.94587 1306155.6 -1306757.4 1122.7487 48631.318 271.67716 1.030267 + 900 62.992675 2409.7324 167.29295 -2346.7397 722.00541 896.64662 560.66083 -3279.4915 -644.05458 1306153.6 -1306756.1 1604.295 48631.318 261.58656 1.0609836 + 950 5.6677468 2403.5067 166.86073 -2397.839 725.07222 891.00249 556.81977 -3279.7848 -672.66389 1306141 -1306759.2 1019.1694 48631.318 260.91187 1.0562387 + 1000 38.526968 2444.97 169.73928 -2406.4431 704.72993 920.68493 534.59035 -3281.2673 -667.78091 1306141.1 -1306758.5 486.79846 48631.318 265.39928 1.098473 + 1050 21.698026 2388.6306 165.82798 -2366.9326 712.15539 934.39244 546.92027 -3281.1469 -654.7449 1306137.4 -1306761.9 1556.1256 48631.318 259.28203 1.0760765 + 1100 -26.971225 2433.8428 168.96678 -2460.814 710.11081 881.19212 524.51547 -3281.7925 -667.53202 1306137.1 -1306764.4 1203.8971 48631.318 264.20441 1.0706085 + 1150 -49.171269 2375.9688 164.94895 -2425.14 729.78127 918.79575 518.21967 -3281.6542 -675.7239 1306130.4 -1306765 229.44016 48631.318 257.89845 1.086519 + 1200 -53.421342 2422.0091 168.14524 -2475.4304 710.67274 884.2589 523.32524 -3282.2275 -674.49333 1306130.9 -1306767.9 -131.09655 48631.318 262.91124 1.0804821 + 1250 -58.534776 2394.4031 166.22873 -2452.9378 680.27486 909.58096 532.81959 -3281.5551 -653.13731 1306127 -1306767.9 546.96357 48631.318 259.92916 1.0424914 + 1300 -24.151217 2431.9902 168.83817 -2456.1414 681.27127 919.39245 536.41899 -3281.3717 -661.90875 1306121.6 -1306771.5 1455.7512 48631.318 264.00712 1.0630558 + 1350 -38.973062 2438.6194 169.2984 -2477.5925 707.96118 912.62518 519.44533 -3281.6739 -687.67183 1306126.1 -1306774.4 -1470.4442 48631.318 264.70225 1.1091537 + 1400 11.896539 2384.5407 165.54404 -2372.6442 719.03374 950.93261 550.5639 -3280.4581 -663.4921 1306122 -1306771.3 465.12854 48631.318 258.83564 1.0785364 + 1450 -13.118691 2436.6246 169.15991 -2449.7433 661.04397 933.07103 561.29537 -3280.6997 -672.68495 1306123.9 -1306775.7 -108.46564 48631.318 264.50636 1.0718787 + 1500 -38.151755 2417.4849 167.83116 -2455.6367 688.81484 892.35701 565.29013 -3279.6716 -662.1817 1306116.9 -1306777.2 517.89634 48631.318 262.44549 1.0338083 + 1550 -71.663334 2405.7016 167.01311 -2477.3649 681.78925 876.31247 559.003 -3280.451 -649.16641 1306112.8 -1306777.7 925.49349 48631.318 261.148 1.0609731 + 1600 -13.900431 2419.481 167.96973 -2433.3814 718.46559 909.67964 559.06779 -3280.8163 -667.6092 1306108 -1306780.2 13.95808 48631.318 262.63632 1.080229 + 1650 -16.403222 2431.075 168.77464 -2447.4783 710.99509 907.65662 551.60307 -3279.8852 -661.52624 1306104.5 -1306780.8 726.89923 48631.318 263.91553 1.0489963 + 1700 -18.555086 2438.2062 169.26971 -2456.7613 665.90475 943.02217 542.86579 -3280.9017 -657.99229 1306108 -1306777.7 801.41078 48631.318 264.67663 1.0750708 + 1750 -6.9249446 2443.9707 169.6699 -2450.8956 733.23573 890.06857 560.83229 -3280.362 -670.93883 1306098.3 -1306782.1 47.037748 48631.318 265.30892 1.0661143 + 1800 -21.686222 2434.3375 169.00113 -2456.0237 729.35297 899.9733 561.59516 -3280.4727 -680.98901 1306096.5 -1306782 495.63617 48631.318 264.25723 1.0723683 + 1850 -72.916947 2408.8254 167.22998 -2481.7423 683.24984 904.13282 549.97726 -3279.6699 -652.63212 1306099.2 -1306786 -120.61674 48631.318 261.48504 1.0659808 + 1900 -55.4099 2415.455 167.69023 -2470.8649 700.4473 904.72264 565.5266 -3280.4533 -673.23082 1306099.6 -1306787.4 202.15936 48631.318 262.20353 1.0709756 + 1950 -79.877997 2409.2307 167.25812 -2489.1087 695.9536 894.4541 564.7034 -3279.3581 -680.33472 1306100.8 -1306785.3 213.72828 48631.318 261.52921 1.0658433 + 2000 -102.20457 2399.4263 166.57746 -2501.6309 689.67819 894.58596 565.53233 -3280.7595 -680.39032 1306096.4 -1306786.6 1113.7499 48631.318 260.46311 1.0647045 +Loop time of 68.4185 on 1 procs for 2000 steps with 5500 atoms + +Performance: 1.263 ns/day, 19.005 hours/ns, 29.232 timesteps/s +99.7% CPU use with 1 MPI tasks x 1 OpenMP threads + +MPI task timing breakdown: +Section | min time | avg time | max time |%varavg| %total +--------------------------------------------------------------- +Pair | 48.825 | 48.825 | 48.825 | 0.0 | 71.36 +Bond | 2.8852 | 2.8852 | 2.8852 | 0.0 | 4.22 +Kspace | 13.795 | 13.795 | 13.795 | 0.0 | 20.16 +Neigh | 1.0731 | 1.0731 | 1.0731 | 0.0 | 1.57 +Comm | 0.27067 | 0.27067 | 0.27067 | 0.0 | 0.40 +Output | 0.0031168 | 0.0031168 | 0.0031168 | 0.0 | 0.00 +Modify | 1.5207 | 1.5207 | 1.5207 | 0.0 | 2.22 +Other | | 0.04541 | | | 0.07 + +Nlocal: 5500 ave 5500 max 5500 min +Histogram: 1 0 0 0 0 0 0 0 0 0 +Nghost: 13157 ave 13157 max 13157 min +Histogram: 1 0 0 0 0 0 0 0 0 0 +Neighs: 1.33822e+06 ave 1.33822e+06 max 1.33822e+06 min +Histogram: 1 0 0 0 0 0 0 0 0 0 + +Total # of neighbors = 1338215 +Ave neighs/atom = 243.312 +Ave special neighs/atom = 15.6364 +Neighbor list builds = 32 +Dangerous builds = 0 +Total wall time: 0:01:08 diff --git a/examples/USER/drude/toluene/log.7Aug19.toluene.lang.g++.4 b/examples/USER/drude/toluene/log.7Aug19.toluene.lang.g++.4 new file mode 100644 index 0000000000..df7d58ac88 --- /dev/null +++ b/examples/USER/drude/toluene/log.7Aug19.toluene.lang.g++.4 @@ -0,0 +1,254 @@ +LAMMPS (7 Aug 2019) +OMP_NUM_THREADS environment is not set. Defaulting to 1 thread. (src/comm.cpp:93) + using 1 OpenMP thread(s) per MPI task +# 250 toluene system for drude polarizability example (Langevin) + +units real +boundary p p p + +atom_style full +bond_style harmonic +angle_style harmonic +dihedral_style opls +improper_style fourier +special_bonds lj/coul 0.0 0.0 0.5 + +pair_style lj/cut/thole/long 2.600 8.0 8.0 +pair_modify mix geometric tail yes +kspace_style pppm 1.0e-4 + +read_data data.toluene extra/special/per/atom 1 + orthogonal box = (-18.2908 -18.1636 -18.223) to (18.3357 18.1621 18.3287) + 2 by 1 by 2 MPI processor grid + reading atoms ... + 5500 atoms + scanning bonds ... + 4 = max bonds/atom + scanning angles ... + 6 = max angles/atom + scanning dihedrals ... + 8 = max dihedrals/atom + scanning impropers ... + 2 = max impropers/atom + reading bonds ... + 5500 bonds + reading angles ... + 6000 angles + reading dihedrals ... + 6000 dihedrals + reading impropers ... + 1500 impropers + 5 = max # of 1-2 neighbors + 10 = max # of 1-3 neighbors + 16 = max # of 1-4 neighbors + 20 = max # of special neighbors + special bonds CPU = 0.000747919 secs + read_data CPU = 0.0168228 secs + +comm_modify vel yes + +group gTOLUENE molecule 1:250 +5500 atoms in group gTOLUENE +group gCORES type 1 2 3 4 5 6 7 +3750 atoms in group gCORES +group gDRUDES type 8 9 10 11 12 +1750 atoms in group gDRUDES + +pair_coeff 1 1 0.069998 3.550000 1.620000 # CAT CAT +pair_coeff 1 2 0.069998 3.550000 1.620000 # CAT CAO +pair_coeff 1 3 0.069998 3.550000 1.620000 # CAT CAM +pair_coeff 1 4 0.069998 3.550000 1.620000 # CAT CAP +pair_coeff 1 5 0.067968 3.524911 1.620000 # CAT CTT +pair_coeff 1 6 0.045825 2.931041 0.000000 # CAT HAT +pair_coeff 1 7 0.045825 2.931041 0.000000 # CAT HT +pair_coeff 2 2 0.069998 3.550000 1.620000 # CAO CAO +pair_coeff 2 3 0.069998 3.550000 1.620000 # CAO CAM +pair_coeff 2 4 0.069998 3.550000 1.620000 # CAO CAP +pair_coeff 2 5 0.067968 3.524911 1.620000 # CAO CTT +pair_coeff 2 6 0.045825 2.931041 0.000000 # CAO HAT +pair_coeff 2 7 0.045825 2.931041 0.000000 # CAO HT +pair_coeff 3 3 0.069998 3.550000 1.620000 # CAM CAM +pair_coeff 3 4 0.069998 3.550000 1.620000 # CAM CAP +pair_coeff 3 5 0.067968 3.524911 1.620000 # CAM CTT +pair_coeff 3 6 0.045825 2.931041 0.000000 # CAM HAT +pair_coeff 3 7 0.045825 2.931041 0.000000 # CAM HT +pair_coeff 4 4 0.069998 3.550000 1.620000 # CAP CAP +pair_coeff 4 5 0.067968 3.524911 1.620000 # CAP CTT +pair_coeff 4 6 0.045825 2.931041 0.000000 # CAP HAT +pair_coeff 4 7 0.045825 2.931041 0.000000 # CAP HT +pair_coeff 5 5 0.065997 3.500000 1.620000 # CTT CTT +pair_coeff 5 6 0.044496 2.910326 0.000000 # CTT HAT +pair_coeff 5 7 0.044496 2.910326 0.000000 # CTT HT +pair_coeff 6 6 0.029999 2.420000 0.000000 # HAT HAT +pair_coeff 6 7 0.029999 2.420000 0.000000 # HAT HT +pair_coeff 7 7 0.029999 2.420000 0.000000 # HT HT +pair_coeff 1 8 0.000000 0.000000 1.620000 # CAT D_CAT +pair_coeff 1 9 0.000000 0.000000 1.620000 # CAT D_CAO +pair_coeff 1 10 0.000000 0.000000 1.620000 # CAT D_CAM +pair_coeff 1 11 0.000000 0.000000 1.620000 # CAT D_CAP +pair_coeff 1 12 0.000000 0.000000 1.620000 # CAT D_CTT +pair_coeff 2 8 0.000000 0.000000 1.620000 # CAO D_CAT +pair_coeff 2 9 0.000000 0.000000 1.620000 # CAO D_CAO +pair_coeff 2 10 0.000000 0.000000 1.620000 # CAO D_CAM +pair_coeff 2 11 0.000000 0.000000 1.620000 # CAO D_CAP +pair_coeff 2 12 0.000000 0.000000 1.620000 # CAO D_CTT +pair_coeff 3 8 0.000000 0.000000 1.620000 # CAM D_CAT +pair_coeff 3 9 0.000000 0.000000 1.620000 # CAM D_CAO +pair_coeff 3 10 0.000000 0.000000 1.620000 # CAM D_CAM +pair_coeff 3 11 0.000000 0.000000 1.620000 # CAM D_CAP +pair_coeff 3 12 0.000000 0.000000 1.620000 # CAM D_CTT +pair_coeff 4 8 0.000000 0.000000 1.620000 # CAP D_CAT +pair_coeff 4 9 0.000000 0.000000 1.620000 # CAP D_CAO +pair_coeff 4 10 0.000000 0.000000 1.620000 # CAP D_CAM +pair_coeff 4 11 0.000000 0.000000 1.620000 # CAP D_CAP +pair_coeff 4 12 0.000000 0.000000 1.620000 # CAP D_CTT +pair_coeff 5 8 0.000000 0.000000 1.620000 # CTT D_CAT +pair_coeff 5 9 0.000000 0.000000 1.620000 # CTT D_CAO +pair_coeff 5 10 0.000000 0.000000 1.620000 # CTT D_CAM +pair_coeff 5 11 0.000000 0.000000 1.620000 # CTT D_CAP +pair_coeff 5 12 0.000000 0.000000 1.620000 # CTT D_CTT +pair_coeff 8 8 0.000000 0.000000 1.620000 # D_CAT D_CAT +pair_coeff 8 9 0.000000 0.000000 1.620000 # D_CAT D_CAO +pair_coeff 8 10 0.000000 0.000000 1.620000 # D_CAT D_CAM +pair_coeff 8 11 0.000000 0.000000 1.620000 # D_CAT D_CAP +pair_coeff 8 12 0.000000 0.000000 1.620000 # D_CAT D_CTT +pair_coeff 9 9 0.000000 0.000000 1.620000 # D_CAO D_CAO +pair_coeff 9 10 0.000000 0.000000 1.620000 # D_CAO D_CAM +pair_coeff 9 11 0.000000 0.000000 1.620000 # D_CAO D_CAP +pair_coeff 9 12 0.000000 0.000000 1.620000 # D_CAO D_CTT +pair_coeff 10 10 0.000000 0.000000 1.620000 # D_CAM D_CAM +pair_coeff 10 11 0.000000 0.000000 1.620000 # D_CAM D_CAP +pair_coeff 10 12 0.000000 0.000000 1.620000 # D_CAM D_CTT +pair_coeff 11 11 0.000000 0.000000 1.620000 # D_CAP D_CAP +pair_coeff 11 12 0.000000 0.000000 1.620000 # D_CAP D_CTT +pair_coeff 12 12 0.000000 0.000000 1.620000 # D_CTT D_CTT + +neighbor 2.0 bin + +variable vTEMP equal 260.0 +variable vTEMP_D equal 1.0 +variable vPRESS equal 1.0 + +velocity gCORES create ${vTEMP} 12345 +velocity gCORES create 260 12345 +velocity gDRUDES create ${vTEMP_D} 12345 +velocity gDRUDES create 1 12345 + +fix fDRUDE all drude C C C C C N N D D D D D + +fix fSHAKE gCORES shake 0.0001 20 0 b 4 6 7 8 + 1250 = # of size 2 clusters + 0 = # of size 3 clusters + 250 = # of size 4 clusters + 0 = # of frozen angles + find clusters CPU = 0.000355244 secs + +fix fLANG all langevin/drude ${vTEMP} 100.0 200611 ${vTEMP_D} 20.0 260514 zero yes +fix fLANG all langevin/drude 260 100.0 200611 ${vTEMP_D} 20.0 260514 zero yes +fix fLANG all langevin/drude 260 100.0 200611 1 20.0 260514 zero yes +fix fNPH all nve + +compute cTEMP all temp/drude + +thermo_style custom step etotal ke temp pe ebond eangle edihed eimp evdwl ecoul elong press vol c_cTEMP[1] c_cTEMP[2] +thermo 50 + +timestep 0.5 +run 2000 +PPPM initialization ... + using 12-bit tables for long-range coulomb (src/kspace.cpp:323) + G vector (1/distance) = 0.382011 + grid = 40 40 40 + stencil order = 5 + estimated absolute RMS force accuracy = 0.0325934 + estimated relative force accuracy = 9.8154e-05 + using double precision FFTW3 + 3d grid and FFT values/proc = 34263 16000 +Rebuild special list taking Drude particles into account +Old max number of 1-2 to 1-4 neighbors: 19 +New max number of 1-2 to 1-4 neighbors: 20 (+1) +Neighbor list info ... + update every 1 steps, delay 10 steps, check yes + max neighbors/atom: 2000, page size: 100000 + master list distance cutoff = 10 + ghost atom cutoff = 10 + binsize = 5, bins = 8 8 8 + 1 neighbor lists, perpetual/occasional/extra = 1 0 0 + (1) pair lj/cut/thole/long, perpetual + attributes: half, newton on + pair build: half/bin/newton + stencil: half/bin/3d/newton + bin: standard +Per MPI rank memory allocation (min/avg/max) = 18 | 18 | 18 Mbytes +Step TotEng KinEng Temp PotEng E_bond E_angle E_dihed E_impro E_vdwl E_coul E_long Press Volume c_cTEMP[1] c_cTEMP[2] + 0 11086.347 2910.7282 202.07402 8175.6191 6565.4851 20.333365 1.0706727e-06 -3299.85 4972.8631 1306116.6 -1306199.8 40273.68 48631.318 314.89553 3.1777821 + 50 4712.9507 4669.1606 324.15119 43.790082 1798.561 670.61319 690.16967 -3276.9493 811.643 1305983.2 -1306633.5 17164.771 48631.318 442.24313 116.13094 + 100 2865.9139 3726.4166 258.70226 -860.50272 968.87546 749.70761 860.70151 -3270.7784 427.14745 1306104.7 -1306700.9 15017.273 48631.318 385.10628 35.845353 + 150 1982.6673 3535.974 245.481 -1553.3068 764.86116 768.15837 658.70182 -3278.7906 108.49859 1306136.5 -1306711.2 16495.352 48631.318 378.64023 10.723986 + 200 1440.0277 3240.5932 224.97452 -1800.5656 687.71813 791.29356 643.82915 -3276.9293 -99.549986 1306172.9 -1306719.8 13234.476 48631.318 350.46321 3.7468464 + 250 1103.2915 3018.496 209.55567 -1915.2045 677.97905 825.32748 642.78891 -3278.0801 -226.1853 1306168.5 -1306725.5 8774.9103 48631.318 327.36313 1.8722119 + 300 789.07159 2827.1716 196.27319 -2038.1 735.96101 852.72545 589.14167 -3280.0357 -374.66018 1306169 -1306730.2 2259.1028 48631.318 306.85585 1.3262598 + 350 599.10023 2732.3739 189.69197 -2133.2737 677.67006 863.22888 565.41674 -3280.5231 -403.28794 1306177.4 -1306733.2 7989.222 48631.318 296.64126 1.1534418 + 400 428.26436 2591.2884 179.89727 -2163.0241 676.18745 849.24505 612.34065 -3277.4703 -457.85799 1306173.6 -1306739.1 7282.1438 48631.318 281.34719 1.0502762 + 450 307.26859 2534.2468 175.93722 -2226.9782 712.17636 853.98862 578.01327 -3279.7731 -533.87422 1306179.7 -1306737.2 1897.9643 48631.318 275.11317 1.0980929 + 500 234.60959 2495.1082 173.22007 -2260.4987 707.43541 878.25753 547.08402 -3281.2756 -549.04991 1306176.5 -1306739.5 2683.0639 48631.318 270.85452 1.0984718 + 550 203.34751 2445.6535 169.78673 -2242.306 669.03724 892.85034 599.20664 -3279.0757 -559.81157 1306175.9 -1306740.4 4512.9992 48631.318 265.49465 1.0628812 + 600 205.63573 2526.5892 175.4056 -2320.9535 685.64073 887.97693 557.42296 -3280.0332 -597.34755 1306167.8 -1306742.5 2999.5823 48631.318 274.29935 1.064682 + 650 176.23031 2526.3124 175.38638 -2350.0821 714.15285 895.42115 540.39191 -3280.8567 -636.27783 1306165.7 -1306748.6 871.68316 48631.318 274.2807 1.0442089 + 700 106.97524 2441.1059 169.47101 -2334.1306 697.16018 905.51407 564.71847 -3279.6208 -631.62324 1306159.4 -1306749.6 1953.8241 48631.318 264.98935 1.0771037 + 750 76.695104 2435.6635 169.09318 -2358.9684 672.01039 934.63351 545.64024 -3281.1075 -629.89722 1306152.4 -1306752.6 3044.0155 48631.318 264.39002 1.0932471 + 800 57.614075 2456.928 170.56945 -2399.3139 720.76364 898.68013 534.10051 -3281.5897 -659.64354 1306145.5 -1306757.1 1691.9503 48631.318 266.72089 1.0622697 + 850 -44.931126 2390.0608 165.92727 -2434.9919 708.70192 888.26851 537.13087 -3281.355 -665.17283 1306137.8 -1306760.3 123.07165 48631.318 259.45151 1.0516426 + 900 -96.878205 2358.862 163.76133 -2455.7403 672.98976 868.41571 546.69492 -3280.6939 -636.80102 1306134.5 -1306760.9 1955.7005 48631.318 256.05598 1.05337 + 950 -80.012575 2374.4497 164.84349 -2454.4623 679.59722 880.35157 548.35372 -3280.6061 -643.44517 1306125.8 -1306764.5 1510.9809 48631.318 257.72442 1.1017392 + 1000 -21.440874 2440.6729 169.44096 -2462.1138 718.56593 868.65109 555.54643 -3279.8516 -686.71673 1306126.6 -1306765 -1148.6212 48631.318 264.92977 1.1019339 + 1050 16.46903 2382.6961 165.41598 -2366.2271 712.51245 913.35848 579.81678 -3280.0559 -657.12122 1306129.3 -1306764 1004.5778 48631.318 258.64076 1.0684155 + 1100 35.847247 2483.1985 172.39325 -2447.3513 685.05704 889.42278 553.73166 -3280.0177 -663.67201 1306134.3 -1306766.2 699.1824 48631.318 269.56773 1.0838094 + 1150 -4.9817843 2431.4725 168.80223 -2436.4543 720.51056 868.17547 569.09902 -3280.5829 -677.99865 1306133.1 -1306768.7 435.19118 48631.318 263.96966 1.0303202 + 1200 -23.907197 2443.6035 169.64441 -2467.5107 684.96437 887.58483 549.43666 -3280.3144 -679.46182 1306137.2 -1306766.9 367.11148 48631.318 265.28645 1.0344036 + 1250 -16.904671 2389.9447 165.91921 -2406.8494 722.06959 902.90076 568.35616 -3280.6829 -683.32029 1306132.9 -1306769.1 76.759445 48631.318 259.41697 1.0908431 + 1300 -1.7822102 2410.2768 167.33074 -2412.0591 706.98675 904.31941 551.23506 -3280.7552 -651.51211 1306127.3 -1306769.6 1659.1113 48631.318 261.64093 1.0701648 + 1350 -3.569473 2446.3901 169.83786 -2449.9595 686.13971 894.85839 558.36242 -3279.9941 -664.59508 1306129 -1306773.7 783.32881 48631.318 265.5696 1.0709072 + 1400 -33.385576 2400.262 166.63547 -2433.6476 709.5808 890.68408 571.13105 -3280.1428 -674.51247 1306123.4 -1306773.8 -751.38571 48631.318 260.54522 1.080234 + 1450 -11.215152 2405.5409 167.00196 -2416.756 703.72038 913.21131 552.64196 -3280.9831 -649.19774 1306120.3 -1306776.4 1817.2174 48631.318 261.14741 1.031193 + 1500 -25.974102 2435.8375 169.10527 -2461.8116 689.93174 900.70619 552.63711 -3280.1497 -671.17989 1306124 -1306777.8 -98.941796 48631.318 264.45069 1.0190784 + 1550 -76.496407 2394.8126 166.25716 -2471.309 706.96953 886.06919 549.9101 -3280.8434 -659.57745 1306105.9 -1306779.7 -7.0989994 48631.318 259.95403 1.0772144 + 1600 -79.549932 2395.1114 166.2779 -2474.6614 684.11692 888.93332 562.94522 -3280.1665 -665.21744 1306114.4 -1306779.6 320.58515 48631.318 260.00641 1.0425978 + 1650 -99.702003 2360.5652 163.87957 -2460.2672 706.21244 900.9253 540.36599 -3280.2308 -655.96077 1306109.7 -1306781.3 307.35487 48631.318 256.23383 1.0666637 + 1700 -69.422658 2372.1727 164.68541 -2441.5954 676.79347 913.90473 581.60658 -3279.997 -670.33218 1306115.7 -1306779.3 -204.22848 48631.318 257.50963 1.0434075 + 1750 -80.889897 2425.3592 168.37782 -2506.2491 672.88937 911.52373 523.74733 -3280.4796 -673.90027 1306122 -1306782 965.12568 48631.318 263.26491 1.1001595 + 1800 -82.419368 2361.798 163.96515 -2444.2173 716.51571 882.9729 577.92505 -3278.9279 -671.67438 1306111.6 -1306782.6 -44.954517 48631.318 256.36957 1.0636692 + 1850 -93.715705 2373.3359 164.76616 -2467.0516 713.02466 907.03621 563.38626 -3280.2576 -693.30963 1306104.6 -1306781.5 -979.95945 48631.318 257.62543 1.0628288 + 1900 -73.60945 2449.5873 170.05983 -2523.1967 683.65116 893.94251 539.90847 -3281.4318 -680.16358 1306108 -1306787.1 598.18213 48631.318 265.91405 1.0766352 + 1950 -66.068291 2437.3691 169.21159 -2503.4374 672.5168 877.42934 573.56499 -3279.885 -668.54185 1306109.2 -1306787.7 733.05074 48631.318 264.61409 1.0224258 + 2000 -91.043979 2374.4077 164.84057 -2465.4516 692.13299 909.46192 574.60109 -3279.837 -672.33599 1306102.4 -1306791.8 -665.61581 48631.318 257.76275 1.0263294 +Loop time of 23.7656 on 4 procs for 2000 steps with 5500 atoms + +Performance: 3.636 ns/day, 6.602 hours/ns, 84.155 timesteps/s +94.3% CPU use with 4 MPI tasks x 1 OpenMP threads + +MPI task timing breakdown: +Section | min time | avg time | max time |%varavg| %total +--------------------------------------------------------------- +Pair | 11.918 | 13.096 | 14.137 | 27.0 | 55.10 +Bond | 0.74012 | 0.76511 | 0.79225 | 2.9 | 3.22 +Kspace | 6.7821 | 7.8285 | 9.0172 | 35.4 | 32.94 +Neigh | 0.37249 | 0.37262 | 0.37278 | 0.0 | 1.57 +Comm | 0.70503 | 0.7188 | 0.72807 | 1.1 | 3.02 +Output | 0.0018752 | 0.0047592 | 0.013386 | 7.2 | 0.02 +Modify | 0.91164 | 0.91644 | 0.92123 | 0.5 | 3.86 +Other | | 0.06335 | | | 0.27 + +Nlocal: 1375 ave 1381 max 1368 min +Histogram: 1 0 0 0 0 1 1 0 0 1 +Nghost: 7803.75 ave 7856 max 7755 min +Histogram: 1 0 0 0 1 1 0 0 0 1 +Neighs: 334465 ave 349504 max 315867 min +Histogram: 1 0 0 1 0 0 0 0 1 1 + +Total # of neighbors = 1337859 +Ave neighs/atom = 243.247 +Ave special neighs/atom = 15.6364 +Neighbor list builds = 32 +Dangerous builds = 0 +Total wall time: 0:00:23 diff --git a/examples/USER/drude/toluene/log.7Aug19.toluene.nh.g++.1 b/examples/USER/drude/toluene/log.7Aug19.toluene.nh.g++.1 new file mode 100644 index 0000000000..be5d856d1e --- /dev/null +++ b/examples/USER/drude/toluene/log.7Aug19.toluene.nh.g++.1 @@ -0,0 +1,262 @@ +LAMMPS (7 Aug 2019) +OMP_NUM_THREADS environment is not set. Defaulting to 1 thread. (src/comm.cpp:93) + using 1 OpenMP thread(s) per MPI task +# 250 toluene system for drude polarizability example (Nose-Hoover) + +units real +boundary p p p + +atom_style full +bond_style harmonic +angle_style harmonic +dihedral_style opls +improper_style fourier +special_bonds lj/coul 0.0 0.0 0.5 + +pair_style lj/cut/thole/long 2.600 8.0 8.0 +pair_modify mix geometric tail yes +kspace_style pppm 1.0e-4 + +read_data data.toluene extra/special/per/atom 1 + orthogonal box = (-18.2908 -18.1636 -18.223) to (18.3357 18.1621 18.3287) + 1 by 1 by 1 MPI processor grid + reading atoms ... + 5500 atoms + scanning bonds ... + 4 = max bonds/atom + scanning angles ... + 6 = max angles/atom + scanning dihedrals ... + 8 = max dihedrals/atom + scanning impropers ... + 2 = max impropers/atom + reading bonds ... + 5500 bonds + reading angles ... + 6000 angles + reading dihedrals ... + 6000 dihedrals + reading impropers ... + 1500 impropers + 5 = max # of 1-2 neighbors + 10 = max # of 1-3 neighbors + 16 = max # of 1-4 neighbors + 20 = max # of special neighbors + special bonds CPU = 0.0019815 secs + read_data CPU = 0.0168803 secs + +comm_modify vel yes + +group gTOLUENE molecule 1:250 +5500 atoms in group gTOLUENE +group gCORES type 1 2 3 4 5 6 7 +3750 atoms in group gCORES +group gDRUDES type 8 9 10 11 12 +1750 atoms in group gDRUDES + +pair_coeff 1 1 0.069998 3.550000 1.620000 # CAT CAT +pair_coeff 1 2 0.069998 3.550000 1.620000 # CAT CAO +pair_coeff 1 3 0.069998 3.550000 1.620000 # CAT CAM +pair_coeff 1 4 0.069998 3.550000 1.620000 # CAT CAP +pair_coeff 1 5 0.067968 3.524911 1.620000 # CAT CTT +pair_coeff 1 6 0.045825 2.931041 0.000000 # CAT HAT +pair_coeff 1 7 0.045825 2.931041 0.000000 # CAT HT +pair_coeff 2 2 0.069998 3.550000 1.620000 # CAO CAO +pair_coeff 2 3 0.069998 3.550000 1.620000 # CAO CAM +pair_coeff 2 4 0.069998 3.550000 1.620000 # CAO CAP +pair_coeff 2 5 0.067968 3.524911 1.620000 # CAO CTT +pair_coeff 2 6 0.045825 2.931041 0.000000 # CAO HAT +pair_coeff 2 7 0.045825 2.931041 0.000000 # CAO HT +pair_coeff 3 3 0.069998 3.550000 1.620000 # CAM CAM +pair_coeff 3 4 0.069998 3.550000 1.620000 # CAM CAP +pair_coeff 3 5 0.067968 3.524911 1.620000 # CAM CTT +pair_coeff 3 6 0.045825 2.931041 0.000000 # CAM HAT +pair_coeff 3 7 0.045825 2.931041 0.000000 # CAM HT +pair_coeff 4 4 0.069998 3.550000 1.620000 # CAP CAP +pair_coeff 4 5 0.067968 3.524911 1.620000 # CAP CTT +pair_coeff 4 6 0.045825 2.931041 0.000000 # CAP HAT +pair_coeff 4 7 0.045825 2.931041 0.000000 # CAP HT +pair_coeff 5 5 0.065997 3.500000 1.620000 # CTT CTT +pair_coeff 5 6 0.044496 2.910326 0.000000 # CTT HAT +pair_coeff 5 7 0.044496 2.910326 0.000000 # CTT HT +pair_coeff 6 6 0.029999 2.420000 0.000000 # HAT HAT +pair_coeff 6 7 0.029999 2.420000 0.000000 # HAT HT +pair_coeff 7 7 0.029999 2.420000 0.000000 # HT HT +pair_coeff 1 8 0.000000 0.000000 1.620000 # CAT D_CAT +pair_coeff 1 9 0.000000 0.000000 1.620000 # CAT D_CAO +pair_coeff 1 10 0.000000 0.000000 1.620000 # CAT D_CAM +pair_coeff 1 11 0.000000 0.000000 1.620000 # CAT D_CAP +pair_coeff 1 12 0.000000 0.000000 1.620000 # CAT D_CTT +pair_coeff 2 8 0.000000 0.000000 1.620000 # CAO D_CAT +pair_coeff 2 9 0.000000 0.000000 1.620000 # CAO D_CAO +pair_coeff 2 10 0.000000 0.000000 1.620000 # CAO D_CAM +pair_coeff 2 11 0.000000 0.000000 1.620000 # CAO D_CAP +pair_coeff 2 12 0.000000 0.000000 1.620000 # CAO D_CTT +pair_coeff 3 8 0.000000 0.000000 1.620000 # CAM D_CAT +pair_coeff 3 9 0.000000 0.000000 1.620000 # CAM D_CAO +pair_coeff 3 10 0.000000 0.000000 1.620000 # CAM D_CAM +pair_coeff 3 11 0.000000 0.000000 1.620000 # CAM D_CAP +pair_coeff 3 12 0.000000 0.000000 1.620000 # CAM D_CTT +pair_coeff 4 8 0.000000 0.000000 1.620000 # CAP D_CAT +pair_coeff 4 9 0.000000 0.000000 1.620000 # CAP D_CAO +pair_coeff 4 10 0.000000 0.000000 1.620000 # CAP D_CAM +pair_coeff 4 11 0.000000 0.000000 1.620000 # CAP D_CAP +pair_coeff 4 12 0.000000 0.000000 1.620000 # CAP D_CTT +pair_coeff 5 8 0.000000 0.000000 1.620000 # CTT D_CAT +pair_coeff 5 9 0.000000 0.000000 1.620000 # CTT D_CAO +pair_coeff 5 10 0.000000 0.000000 1.620000 # CTT D_CAM +pair_coeff 5 11 0.000000 0.000000 1.620000 # CTT D_CAP +pair_coeff 5 12 0.000000 0.000000 1.620000 # CTT D_CTT +pair_coeff 8 8 0.000000 0.000000 1.620000 # D_CAT D_CAT +pair_coeff 8 9 0.000000 0.000000 1.620000 # D_CAT D_CAO +pair_coeff 8 10 0.000000 0.000000 1.620000 # D_CAT D_CAM +pair_coeff 8 11 0.000000 0.000000 1.620000 # D_CAT D_CAP +pair_coeff 8 12 0.000000 0.000000 1.620000 # D_CAT D_CTT +pair_coeff 9 9 0.000000 0.000000 1.620000 # D_CAO D_CAO +pair_coeff 9 10 0.000000 0.000000 1.620000 # D_CAO D_CAM +pair_coeff 9 11 0.000000 0.000000 1.620000 # D_CAO D_CAP +pair_coeff 9 12 0.000000 0.000000 1.620000 # D_CAO D_CTT +pair_coeff 10 10 0.000000 0.000000 1.620000 # D_CAM D_CAM +pair_coeff 10 11 0.000000 0.000000 1.620000 # D_CAM D_CAP +pair_coeff 10 12 0.000000 0.000000 1.620000 # D_CAM D_CTT +pair_coeff 11 11 0.000000 0.000000 1.620000 # D_CAP D_CAP +pair_coeff 11 12 0.000000 0.000000 1.620000 # D_CAP D_CTT +pair_coeff 12 12 0.000000 0.000000 1.620000 # D_CTT D_CTT + + +neighbor 2.0 bin + +variable vTEMP equal 260.0 +variable vTEMP_D equal 1.0 +variable vPRESS equal 1.0 + +velocity gCORES create ${vTEMP} 12345 +velocity gCORES create 260 12345 +velocity gDRUDES create ${vTEMP_D} 12345 +velocity gDRUDES create 1 12345 + +fix fDRUDE all drude C C C C C N N D D D D D + +fix fSHAKE gCORES shake 0.0001 20 0 b 4 6 7 8 + 1250 = # of size 2 clusters + 0 = # of size 3 clusters + 250 = # of size 4 clusters + 0 = # of frozen angles + find clusters CPU = 0.000715256 secs + +compute cTEMP_CORE gCORES temp/com +compute cTEMP all temp/drude + +fix fDIRECT all drude/transform/direct +fix fNVT1 gCORES nvt temp ${vTEMP} ${vTEMP} 100.0 +fix fNVT1 gCORES nvt temp 260 ${vTEMP} 100.0 +fix fNVT1 gCORES nvt temp 260 260 100.0 +fix fNVT2 gDRUDES nvt temp ${vTEMP_D} ${vTEMP_D} 20.0 +fix fNVT2 gDRUDES nvt temp 1 ${vTEMP_D} 20.0 +fix fNVT2 gDRUDES nvt temp 1 1 20.0 +fix fINVERSE all drude/transform/inverse + +fix fMOMENTUM all momentum 100 linear 1 1 1 + +thermo_style custom step etotal ke temp pe ebond eangle edihed eimp evdwl ecoul elong press vol c_cTEMP[1] c_cTEMP[2] +thermo 50 + +timestep 0.5 +run 2000 +PPPM initialization ... + using 12-bit tables for long-range coulomb (src/kspace.cpp:323) + G vector (1/distance) = 0.382011 + grid = 40 40 40 + stencil order = 5 + estimated absolute RMS force accuracy = 0.0325934 + estimated relative force accuracy = 9.8154e-05 + using double precision FFTW3 + 3d grid and FFT values/proc = 103823 64000 +Rebuild special list taking Drude particles into account +Old max number of 1-2 to 1-4 neighbors: 19 +New max number of 1-2 to 1-4 neighbors: 20 (+1) +Neighbor list info ... + update every 1 steps, delay 10 steps, check yes + max neighbors/atom: 2000, page size: 100000 + master list distance cutoff = 10 + ghost atom cutoff = 10 + binsize = 5, bins = 8 8 8 + 1 neighbor lists, perpetual/occasional/extra = 1 0 0 + (1) pair lj/cut/thole/long, perpetual + attributes: half, newton on + pair build: half/bin/newton + stencil: half/bin/3d/newton + bin: standard +Per MPI rank memory allocation (min/avg/max) = 42.06 | 42.06 | 42.06 Mbytes +Step TotEng KinEng Temp PotEng E_bond E_angle E_dihed E_impro E_vdwl E_coul E_long Press Volume c_cTEMP[1] c_cTEMP[2] + 0 11086.347 2910.7282 202.07402 8175.6191 6565.4851 20.333365 1.0706727e-06 -3299.85 4972.8631 1306116.6 -1306199.8 40273.68 48631.318 314.89553 3.1777821 + 50 3563.3755 4630.6343 321.47655 -1067.2588 735.72049 604.78665 689.14827 -3277.411 815.58183 1306088.7 -1306723.8 17813.424 48631.318 503.827 0.0087118192 + 100 3327.4724 4395.1107 305.12559 -1067.6382 597.93176 651.62645 945.4151 -3267.2851 584.58833 1306135.9 -1306715.8 17407.337 48631.318 478.20171 0.0075985539 + 150 3036.9065 4740.2304 329.08513 -1703.3239 558.64983 619.91284 658.80687 -3278.7837 285.12462 1306173 -1306720 18448.248 48631.318 515.75286 0.0063215188 + 200 2697.958 4559.3445 316.52733 -1861.3864 522.09334 593.89129 754.61446 -3273.49 87.660461 1306183.9 -1306730 17888.936 48631.318 496.07143 0.0068706164 + 250 2348.7568 4410.585 306.19988 -2061.8283 506.05007 575.35171 715.55054 -3276.3261 -18.364473 1306177.3 -1306741.4 11592.05 48631.318 479.88562 0.0071741032 + 300 2019.8258 4040.1415 280.48226 -2020.3157 604.3077 641.66689 693.93801 -3278.5312 -115.73641 1306183.2 -1306749.1 3631.3628 48631.318 439.57995 0.0069886387 + 350 1699.5166 3944.9851 273.87613 -2245.4685 452.07416 638.0653 658.79117 -3279.6053 -157.07584 1306196.9 -1306754.6 13544.368 48631.318 429.22694 0.0062868111 + 400 1399.2929 3726.098 258.68014 -2326.8051 457.91943 621.44726 639.39903 -3279.2395 -188.85914 1306185.4 -1306762.8 10792.274 48631.318 405.41134 0.0059340078 + 450 1120.5249 3518.345 244.25712 -2397.8201 519.48856 584.65789 646.36689 -3278.6685 -289.59913 1306184.1 -1306764.2 2755.5598 48631.318 382.80716 0.0055707485 + 500 868.0166 3359.8794 233.25583 -2491.8628 460.7393 581.49563 581.01731 -3281.5544 -252.20169 1306184.3 -1306765.7 6120.3639 48631.318 365.56528 0.0058756154 + 550 637.01567 3214.9521 223.19441 -2577.9364 431.81483 578.87411 540.94047 -3281.5337 -266.36075 1306182.8 -1306764.5 8622.4334 48631.318 349.79661 0.0058589653 + 600 418.04086 3113.4064 216.14472 -2695.3655 430.45935 538.68157 522.24598 -3283.456 -311.87901 1306174.3 -1306765.8 7068.9273 48631.318 338.74797 0.0059567598 + 650 218.5966 2930.8439 203.47052 -2712.2473 514.47294 514.28379 551.52551 -3282.0904 -405.37401 1306164.5 -1306769.5 -13.553736 48631.318 318.88482 0.0052667842 + 700 45.22721 2830.1443 196.47956 -2784.917 451.11156 498.26423 541.18835 -3282.1427 -375.95313 1306157.1 -1306774.4 3947.6276 48631.318 307.92741 0.0068019029 + 750 -114.28621 2798.3153 194.26988 -2912.6016 412.753 503.2878 481.32173 -3284.3411 -393.53984 1306147 -1306779.1 7143.3414 48631.318 304.46466 0.0061596717 + 800 -263.63817 2694.8084 187.08403 -2958.4466 455.67914 487.49754 476.8659 -3284.3133 -451.9578 1306145 -1306787.2 1185.9502 48631.318 293.20288 0.0058203332 + 850 -397.71592 2559.1921 177.66902 -2956.9081 458.83317 481.2262 478.31241 -3284.068 -437.26503 1306138.6 -1306792.6 346.80209 48631.318 278.44745 0.0054921692 + 900 -515.1823 2544.8753 176.67509 -3060.0576 395.00163 457.58988 446.68352 -3285.485 -423.56221 1306145 -1306795.3 3712.8598 48631.318 276.88864 0.0074054008 + 950 -617.28259 2451.1723 170.16987 -3068.4549 383.64277 446.59877 434.4624 -3285.1348 -391.59344 1306142.3 -1306798.7 5429.2488 48631.318 266.69431 0.0057487316 + 1000 -703.15534 2334.837 162.09342 -3037.9923 424.34948 462.21112 451.80809 -3284.3803 -426.53369 1306133.9 -1306799.3 1137.6145 48631.318 254.03675 0.0053914731 + 1050 -771.1763 2303.837 159.94128 -3075.0133 426.21409 436.50718 435.09987 -3285.1939 -411.14054 1306125.6 -1306802.1 1636.9383 48631.318 250.66295 0.0069342505 + 1100 -822.72236 2283.4196 158.52382 -3106.142 376.67684 447.77729 418.45768 -3286.5919 -377.48204 1306118.9 -1306803.8 4760.5163 48631.318 248.44119 0.0074025012 + 1150 -857.06075 2259.0717 156.8335 -3116.1324 400.31523 431.65981 457.68066 -3285.1977 -430.47723 1306115.8 -1306805.9 3194.5161 48631.318 245.79223 0.007063589 + 1200 -875.50848 2238.2637 155.38893 -3113.7722 445.38524 460.97125 432.10511 -3285.4238 -472.46606 1306114.7 -1306809 -653.49784 48631.318 243.52819 0.0071448738 + 1250 -880.37572 2294.6889 159.30618 -3175.0646 411.35427 444.73793 420.06468 -3286.0366 -458.05371 1306104.4 -1306811.5 945.80793 48631.318 249.66481 0.011853487 + 1300 -871.31064 2284.2298 158.58007 -3155.5405 404.97412 441.75285 426.34477 -3285.4859 -424.79609 1306094.9 -1306813.2 4406.6196 48631.318 248.48563 0.084424118 + 1350 -816.70005 2325.9264 161.47481 -3142.6265 696.80296 442.50053 431.19923 -3285.7859 -450.2699 1305836.2 -1306813.3 593.8098 48631.318 251.40749 2.9297319 + 1400 -794.25335 2263.5101 157.14163 -3057.7635 645.65165 466.22086 446.22268 -3285.1821 -420.65317 1305903.7 -1306813.8 1386.3633 48631.318 245.20554 1.8916154 + 1450 -776.10866 2287.6575 158.81803 -3063.7661 427.03477 479.10627 439.67495 -3285.9537 -395.13186 1306087.6 -1306816.1 2936.7806 48631.318 248.87167 0.061343245 + 1500 -725.48181 2371.413 164.63266 -3096.8948 390.03204 464.30903 446.91959 -3284.7809 -393.16613 1306095.4 -1306815.6 3544.25 48631.318 258.01286 0.011586563 + 1550 -671.4904 2315.9297 160.7808 -2987.4201 457.04935 500.25282 464.76203 -3284.9311 -400.98103 1306091.7 -1306815.3 2052.6339 48631.318 251.97726 0.0094517862 + 1600 -618.83633 2449.0918 170.02543 -3067.9281 425.47487 474.65876 471.99171 -3284.3677 -430.32107 1306091.3 -1306816.6 441.15682 48631.318 266.46311 0.014260935 + 1650 -567.82245 2425.2238 168.36842 -2993.0462 421.01953 511.27133 463.22065 -3285.038 -377.24066 1306088.4 -1306814.7 5198.8565 48631.318 263.83185 0.074738268 + 1700 -502.4486 2441.8554 169.52305 -2944.304 642.39962 512.90234 490.38297 -3283.9751 -417.39288 1305929.1 -1306817.7 1141.4411 48631.318 264.52393 2.043674 + 1750 -459.52196 2499.0746 173.49543 -2958.5966 679.38259 505.31787 484.77659 -3284.6272 -384.27736 1305861.6 -1306820.8 1527.2046 48631.318 270.10074 3.1869342 + 1800 -471.14403 2476.2266 171.90923 -2947.3706 442.47741 530.45656 474.03057 -3284.0954 -371.95117 1306084.3 -1306822.6 3392.2533 48631.318 269.36446 0.10416401 + 1850 -462.80763 2536.7112 176.10831 -2999.5188 437.08241 525.07462 474.0838 -3283.7906 -422.23719 1306091.6 -1306821.3 1629.8629 48631.318 275.99502 0.016806806 + 1900 -469.89289 2468.9765 171.4059 -2938.8694 446.77624 531.61059 496.01046 -3284.2338 -395.15325 1306085.7 -1306819.6 3119.5402 48631.318 268.62645 0.014601992 + 1950 -491.08007 2445.5966 169.78278 -2936.6767 457.80452 527.23373 470.18125 -3283.9608 -391.86377 1306101.9 -1306818 1122.5275 48631.318 266.08018 0.018911601 + 2000 -518.40811 2418.7208 167.91696 -2937.1289 415.93135 536.5973 480.44651 -3283.7881 -363.72783 1306096.2 -1306818.7 4475.7317 48631.318 263.09007 0.13504326 +Loop time of 70.696 on 1 procs for 2000 steps with 5500 atoms + +Performance: 1.222 ns/day, 19.638 hours/ns, 28.290 timesteps/s +97.8% CPU use with 1 MPI tasks x 1 OpenMP threads + +MPI task timing breakdown: +Section | min time | avg time | max time |%varavg| %total +--------------------------------------------------------------- +Pair | 48.367 | 48.367 | 48.367 | 0.0 | 68.42 +Bond | 2.9191 | 2.9191 | 2.9191 | 0.0 | 4.13 +Kspace | 14.266 | 14.266 | 14.266 | 0.0 | 20.18 +Neigh | 1.5262 | 1.5262 | 1.5262 | 0.0 | 2.16 +Comm | 0.27841 | 0.27841 | 0.27841 | 0.0 | 0.39 +Output | 0.0035572 | 0.0035572 | 0.0035572 | 0.0 | 0.01 +Modify | 3.2856 | 3.2856 | 3.2856 | 0.0 | 4.65 +Other | | 0.05018 | | | 0.07 + +Nlocal: 5500 ave 5500 max 5500 min +Histogram: 1 0 0 0 0 0 0 0 0 0 +Nghost: 15317 ave 15317 max 15317 min +Histogram: 1 0 0 0 0 0 0 0 0 0 +Neighs: 1.30285e+06 ave 1.30285e+06 max 1.30285e+06 min +Histogram: 1 0 0 0 0 0 0 0 0 0 + +Total # of neighbors = 1302849 +Ave neighs/atom = 236.882 +Ave special neighs/atom = 15.6364 +Neighbor list builds = 44 +Dangerous builds = 0 +Total wall time: 0:01:10 diff --git a/examples/USER/drude/toluene/log.7Aug19.toluene.nh.g++.4 b/examples/USER/drude/toluene/log.7Aug19.toluene.nh.g++.4 new file mode 100644 index 0000000000..8d58260754 --- /dev/null +++ b/examples/USER/drude/toluene/log.7Aug19.toluene.nh.g++.4 @@ -0,0 +1,262 @@ +LAMMPS (7 Aug 2019) +OMP_NUM_THREADS environment is not set. Defaulting to 1 thread. (src/comm.cpp:93) + using 1 OpenMP thread(s) per MPI task +# 250 toluene system for drude polarizability example (Nose-Hoover) + +units real +boundary p p p + +atom_style full +bond_style harmonic +angle_style harmonic +dihedral_style opls +improper_style fourier +special_bonds lj/coul 0.0 0.0 0.5 + +pair_style lj/cut/thole/long 2.600 8.0 8.0 +pair_modify mix geometric tail yes +kspace_style pppm 1.0e-4 + +read_data data.toluene extra/special/per/atom 1 + orthogonal box = (-18.2908 -18.1636 -18.223) to (18.3357 18.1621 18.3287) + 2 by 1 by 2 MPI processor grid + reading atoms ... + 5500 atoms + scanning bonds ... + 4 = max bonds/atom + scanning angles ... + 6 = max angles/atom + scanning dihedrals ... + 8 = max dihedrals/atom + scanning impropers ... + 2 = max impropers/atom + reading bonds ... + 5500 bonds + reading angles ... + 6000 angles + reading dihedrals ... + 6000 dihedrals + reading impropers ... + 1500 impropers + 5 = max # of 1-2 neighbors + 10 = max # of 1-3 neighbors + 16 = max # of 1-4 neighbors + 20 = max # of special neighbors + special bonds CPU = 0.000718355 secs + read_data CPU = 0.0167146 secs + +comm_modify vel yes + +group gTOLUENE molecule 1:250 +5500 atoms in group gTOLUENE +group gCORES type 1 2 3 4 5 6 7 +3750 atoms in group gCORES +group gDRUDES type 8 9 10 11 12 +1750 atoms in group gDRUDES + +pair_coeff 1 1 0.069998 3.550000 1.620000 # CAT CAT +pair_coeff 1 2 0.069998 3.550000 1.620000 # CAT CAO +pair_coeff 1 3 0.069998 3.550000 1.620000 # CAT CAM +pair_coeff 1 4 0.069998 3.550000 1.620000 # CAT CAP +pair_coeff 1 5 0.067968 3.524911 1.620000 # CAT CTT +pair_coeff 1 6 0.045825 2.931041 0.000000 # CAT HAT +pair_coeff 1 7 0.045825 2.931041 0.000000 # CAT HT +pair_coeff 2 2 0.069998 3.550000 1.620000 # CAO CAO +pair_coeff 2 3 0.069998 3.550000 1.620000 # CAO CAM +pair_coeff 2 4 0.069998 3.550000 1.620000 # CAO CAP +pair_coeff 2 5 0.067968 3.524911 1.620000 # CAO CTT +pair_coeff 2 6 0.045825 2.931041 0.000000 # CAO HAT +pair_coeff 2 7 0.045825 2.931041 0.000000 # CAO HT +pair_coeff 3 3 0.069998 3.550000 1.620000 # CAM CAM +pair_coeff 3 4 0.069998 3.550000 1.620000 # CAM CAP +pair_coeff 3 5 0.067968 3.524911 1.620000 # CAM CTT +pair_coeff 3 6 0.045825 2.931041 0.000000 # CAM HAT +pair_coeff 3 7 0.045825 2.931041 0.000000 # CAM HT +pair_coeff 4 4 0.069998 3.550000 1.620000 # CAP CAP +pair_coeff 4 5 0.067968 3.524911 1.620000 # CAP CTT +pair_coeff 4 6 0.045825 2.931041 0.000000 # CAP HAT +pair_coeff 4 7 0.045825 2.931041 0.000000 # CAP HT +pair_coeff 5 5 0.065997 3.500000 1.620000 # CTT CTT +pair_coeff 5 6 0.044496 2.910326 0.000000 # CTT HAT +pair_coeff 5 7 0.044496 2.910326 0.000000 # CTT HT +pair_coeff 6 6 0.029999 2.420000 0.000000 # HAT HAT +pair_coeff 6 7 0.029999 2.420000 0.000000 # HAT HT +pair_coeff 7 7 0.029999 2.420000 0.000000 # HT HT +pair_coeff 1 8 0.000000 0.000000 1.620000 # CAT D_CAT +pair_coeff 1 9 0.000000 0.000000 1.620000 # CAT D_CAO +pair_coeff 1 10 0.000000 0.000000 1.620000 # CAT D_CAM +pair_coeff 1 11 0.000000 0.000000 1.620000 # CAT D_CAP +pair_coeff 1 12 0.000000 0.000000 1.620000 # CAT D_CTT +pair_coeff 2 8 0.000000 0.000000 1.620000 # CAO D_CAT +pair_coeff 2 9 0.000000 0.000000 1.620000 # CAO D_CAO +pair_coeff 2 10 0.000000 0.000000 1.620000 # CAO D_CAM +pair_coeff 2 11 0.000000 0.000000 1.620000 # CAO D_CAP +pair_coeff 2 12 0.000000 0.000000 1.620000 # CAO D_CTT +pair_coeff 3 8 0.000000 0.000000 1.620000 # CAM D_CAT +pair_coeff 3 9 0.000000 0.000000 1.620000 # CAM D_CAO +pair_coeff 3 10 0.000000 0.000000 1.620000 # CAM D_CAM +pair_coeff 3 11 0.000000 0.000000 1.620000 # CAM D_CAP +pair_coeff 3 12 0.000000 0.000000 1.620000 # CAM D_CTT +pair_coeff 4 8 0.000000 0.000000 1.620000 # CAP D_CAT +pair_coeff 4 9 0.000000 0.000000 1.620000 # CAP D_CAO +pair_coeff 4 10 0.000000 0.000000 1.620000 # CAP D_CAM +pair_coeff 4 11 0.000000 0.000000 1.620000 # CAP D_CAP +pair_coeff 4 12 0.000000 0.000000 1.620000 # CAP D_CTT +pair_coeff 5 8 0.000000 0.000000 1.620000 # CTT D_CAT +pair_coeff 5 9 0.000000 0.000000 1.620000 # CTT D_CAO +pair_coeff 5 10 0.000000 0.000000 1.620000 # CTT D_CAM +pair_coeff 5 11 0.000000 0.000000 1.620000 # CTT D_CAP +pair_coeff 5 12 0.000000 0.000000 1.620000 # CTT D_CTT +pair_coeff 8 8 0.000000 0.000000 1.620000 # D_CAT D_CAT +pair_coeff 8 9 0.000000 0.000000 1.620000 # D_CAT D_CAO +pair_coeff 8 10 0.000000 0.000000 1.620000 # D_CAT D_CAM +pair_coeff 8 11 0.000000 0.000000 1.620000 # D_CAT D_CAP +pair_coeff 8 12 0.000000 0.000000 1.620000 # D_CAT D_CTT +pair_coeff 9 9 0.000000 0.000000 1.620000 # D_CAO D_CAO +pair_coeff 9 10 0.000000 0.000000 1.620000 # D_CAO D_CAM +pair_coeff 9 11 0.000000 0.000000 1.620000 # D_CAO D_CAP +pair_coeff 9 12 0.000000 0.000000 1.620000 # D_CAO D_CTT +pair_coeff 10 10 0.000000 0.000000 1.620000 # D_CAM D_CAM +pair_coeff 10 11 0.000000 0.000000 1.620000 # D_CAM D_CAP +pair_coeff 10 12 0.000000 0.000000 1.620000 # D_CAM D_CTT +pair_coeff 11 11 0.000000 0.000000 1.620000 # D_CAP D_CAP +pair_coeff 11 12 0.000000 0.000000 1.620000 # D_CAP D_CTT +pair_coeff 12 12 0.000000 0.000000 1.620000 # D_CTT D_CTT + + +neighbor 2.0 bin + +variable vTEMP equal 260.0 +variable vTEMP_D equal 1.0 +variable vPRESS equal 1.0 + +velocity gCORES create ${vTEMP} 12345 +velocity gCORES create 260 12345 +velocity gDRUDES create ${vTEMP_D} 12345 +velocity gDRUDES create 1 12345 + +fix fDRUDE all drude C C C C C N N D D D D D + +fix fSHAKE gCORES shake 0.0001 20 0 b 4 6 7 8 + 1250 = # of size 2 clusters + 0 = # of size 3 clusters + 250 = # of size 4 clusters + 0 = # of frozen angles + find clusters CPU = 0.000344038 secs + +compute cTEMP_CORE gCORES temp/com +compute cTEMP all temp/drude + +fix fDIRECT all drude/transform/direct +fix fNVT1 gCORES nvt temp ${vTEMP} ${vTEMP} 100.0 +fix fNVT1 gCORES nvt temp 260 ${vTEMP} 100.0 +fix fNVT1 gCORES nvt temp 260 260 100.0 +fix fNVT2 gDRUDES nvt temp ${vTEMP_D} ${vTEMP_D} 20.0 +fix fNVT2 gDRUDES nvt temp 1 ${vTEMP_D} 20.0 +fix fNVT2 gDRUDES nvt temp 1 1 20.0 +fix fINVERSE all drude/transform/inverse + +fix fMOMENTUM all momentum 100 linear 1 1 1 + +thermo_style custom step etotal ke temp pe ebond eangle edihed eimp evdwl ecoul elong press vol c_cTEMP[1] c_cTEMP[2] +thermo 50 + +timestep 0.5 +run 2000 +PPPM initialization ... + using 12-bit tables for long-range coulomb (src/kspace.cpp:323) + G vector (1/distance) = 0.382011 + grid = 40 40 40 + stencil order = 5 + estimated absolute RMS force accuracy = 0.0325934 + estimated relative force accuracy = 9.8154e-05 + using double precision FFTW3 + 3d grid and FFT values/proc = 34263 16000 +Rebuild special list taking Drude particles into account +Old max number of 1-2 to 1-4 neighbors: 19 +New max number of 1-2 to 1-4 neighbors: 20 (+1) +Neighbor list info ... + update every 1 steps, delay 10 steps, check yes + max neighbors/atom: 2000, page size: 100000 + master list distance cutoff = 10 + ghost atom cutoff = 10 + binsize = 5, bins = 8 8 8 + 1 neighbor lists, perpetual/occasional/extra = 1 0 0 + (1) pair lj/cut/thole/long, perpetual + attributes: half, newton on + pair build: half/bin/newton + stencil: half/bin/3d/newton + bin: standard +Per MPI rank memory allocation (min/avg/max) = 18 | 18 | 18 Mbytes +Step TotEng KinEng Temp PotEng E_bond E_angle E_dihed E_impro E_vdwl E_coul E_long Press Volume c_cTEMP[1] c_cTEMP[2] + 0 11086.347 2910.7282 202.07402 8175.6191 6565.4851 20.333365 1.0706727e-06 -3299.85 4972.8631 1306116.6 -1306199.8 40273.68 48631.318 314.89553 3.1777821 + 50 3563.376 4630.6343 321.47655 -1067.2583 735.72048 604.78665 689.14826 -3277.411 815.58183 1306088.7 -1306723.8 17813.425 48631.318 503.827 0.0087118179 + 100 3327.4722 4395.1107 305.12559 -1067.6385 597.93175 651.62645 945.4151 -3267.2851 584.58833 1306135.9 -1306715.8 17407.335 48631.318 478.2017 0.0075985638 + 150 3036.9065 4740.2304 329.08513 -1703.3238 558.64983 619.91284 658.80686 -3278.7837 285.12462 1306173 -1306720 18448.248 48631.318 515.75286 0.0063215227 + 200 2697.9581 4559.3445 316.52734 -1861.3864 522.09335 593.8913 754.61446 -3273.49 87.660464 1306183.9 -1306730 17888.937 48631.318 496.07143 0.006870622 + 250 2348.7563 4410.585 306.19988 -2061.8288 506.05006 575.35172 715.55055 -3276.3261 -18.364482 1306177.3 -1306741.4 11592.049 48631.318 479.88562 0.0071741023 + 300 2019.8256 4040.1415 280.48225 -2020.3159 604.30771 641.66688 693.93802 -3278.5312 -115.73639 1306183.2 -1306749.1 3631.3625 48631.318 439.57995 0.0069886424 + 350 1699.5169 3944.9851 273.87613 -2245.4682 452.07416 638.06529 658.79116 -3279.6053 -157.07584 1306196.9 -1306754.6 13544.368 48631.318 429.22695 0.0062868216 + 400 1399.2927 3726.098 258.68014 -2326.8053 457.91943 621.44727 639.39905 -3279.2395 -188.85912 1306185.4 -1306762.8 10792.273 48631.318 405.41133 0.0059340084 + 450 1120.5246 3518.345 244.25712 -2397.8204 519.48859 584.6579 646.36688 -3278.6685 -289.59912 1306184.1 -1306764.2 2755.5597 48631.318 382.80717 0.005570751 + 500 868.01643 3359.8794 233.25583 -2491.863 460.73928 581.49568 581.01732 -3281.5544 -252.20168 1306184.3 -1306765.7 6120.364 48631.318 365.56528 0.0058756204 + 550 637.01646 3214.9521 223.19441 -2577.9356 431.81484 578.87415 540.94046 -3281.5337 -266.36074 1306182.8 -1306764.5 8622.4353 48631.318 349.79661 0.0058589476 + 600 418.04028 3113.4063 216.14471 -2695.3661 430.45936 538.68158 522.24597 -3283.456 -311.87897 1306174.3 -1306765.8 7068.9275 48631.318 338.74796 0.0059567639 + 650 218.59562 2930.8439 203.47052 -2712.2482 514.47296 514.2838 551.52551 -3282.0904 -405.37401 1306164.5 -1306769.5 -13.554086 48631.318 318.88481 0.0052667849 + 700 45.227739 2830.1443 196.47957 -2784.9165 451.11157 498.26426 541.18833 -3282.1427 -375.95321 1306157.1 -1306774.4 3947.6268 48631.318 307.92741 0.0068018884 + 750 -114.28676 2798.3154 194.26988 -2912.6022 412.75298 503.28782 481.32167 -3284.3411 -393.53987 1306147 -1306779.1 7143.3424 48631.318 304.46466 0.0061596613 + 800 -263.63827 2694.8085 187.08403 -2958.4468 455.67916 487.49754 476.86576 -3284.3133 -451.95784 1306145 -1306787.2 1185.9474 48631.318 293.20289 0.0058203323 + 850 -397.71592 2559.1922 177.66903 -2956.9082 458.83313 481.22619 478.31233 -3284.068 -437.26509 1306138.6 -1306792.6 346.80221 48631.318 278.44747 0.0054921238 + 900 -515.18134 2544.8753 176.67509 -3060.0567 395.0016 457.5898 446.68361 -3285.485 -423.56234 1306145.1 -1306795.3 3712.8594 48631.318 276.88864 0.0074054726 + 950 -617.28607 2451.1721 170.16985 -3068.4582 383.6428 446.59872 434.46241 -3285.1348 -391.59326 1306142.3 -1306798.7 5429.2191 48631.318 266.69429 0.0057487961 + 1000 -703.15541 2334.8366 162.09339 -3037.992 424.34957 462.21115 451.80811 -3284.3803 -426.53346 1306133.9 -1306799.3 1137.6144 48631.318 254.03671 0.0053915025 + 1050 -771.17572 2303.8364 159.94123 -3075.0121 426.21406 436.50744 435.10013 -3285.1938 -411.13999 1306125.6 -1306802.1 1636.9467 48631.318 250.66288 0.0069341736 + 1100 -822.72317 2283.421 158.52392 -3106.1442 376.67703 447.77728 418.45763 -3286.5919 -377.48075 1306118.9 -1306803.8 4760.4718 48631.318 248.44134 0.0074024122 + 1150 -857.06061 2259.0725 156.83355 -3116.1331 400.31517 431.65949 457.68078 -3285.1977 -430.47775 1306115.8 -1306805.9 3194.5159 48631.318 245.79231 0.007063706 + 1200 -875.50971 2238.2632 155.38889 -3113.7729 445.38534 460.97161 432.10511 -3285.4238 -472.46582 1306114.7 -1306809 -653.49627 48631.318 243.52813 0.0071446561 + 1250 -880.37609 2294.689 159.30619 -3175.0651 411.35498 444.73774 420.06429 -3286.0366 -458.05353 1306104.4 -1306811.5 945.79687 48631.318 249.66483 0.011854196 + 1300 -871.31122 2284.2295 158.58005 -3155.5407 404.97869 441.75305 426.34479 -3285.4859 -424.79602 1306094.8 -1306813.2 4406.6128 48631.318 248.4856 0.084411062 + 1350 -816.69657 2325.9211 161.47444 -3142.6176 696.85542 442.50059 431.19981 -3285.7859 -450.27129 1305836.1 -1306813.3 593.86622 48631.318 251.40736 2.9289249 + 1400 -794.25213 2263.5122 157.14177 -3057.7643 645.6531 466.2204 446.22253 -3285.1821 -420.65316 1305903.7 -1306813.8 1386.3481 48631.318 245.20568 1.8917548 + 1450 -776.1076 2287.6591 158.81814 -3063.7667 427.0331 479.10417 439.67675 -3285.9536 -395.13308 1306087.6 -1306816.1 2936.7117 48631.318 248.87185 0.061341392 + 1500 -725.48032 2371.4108 164.63251 -3096.8911 390.03135 464.30817 446.91941 -3284.7808 -393.16302 1306095.4 -1306815.6 3544.3635 48631.318 258.01262 0.011585228 + 1550 -671.48696 2315.9233 160.78035 -2987.4102 457.04771 500.26018 464.7623 -3284.931 -400.98142 1306091.7 -1306815.3 2052.6204 48631.318 251.97656 0.0094518433 + 1600 -618.82679 2449.0893 170.02525 -3067.9161 425.47171 474.66369 471.99137 -3284.3677 -430.3224 1306091.3 -1306816.6 441.31257 48631.318 266.46283 0.014263201 + 1650 -567.82233 2425.2281 168.36872 -2993.0504 421.02008 511.26686 463.22202 -3285.0378 -377.24205 1306088.4 -1306814.7 5198.6214 48631.318 263.83232 0.074728934 + 1700 -502.46013 2441.8437 169.52224 -2944.3039 642.39863 512.90005 490.39655 -3283.975 -417.39351 1305929.1 -1306817.7 1141.2401 48631.318 264.52268 2.0436397 + 1750 -459.52135 2499.0847 173.49613 -2958.606 679.34078 505.30943 484.78276 -3284.6269 -384.28217 1305861.7 -1306820.8 1527.0852 48631.318 270.10144 3.1876179 + 1800 -471.14322 2476.2445 171.91047 -2947.3877 442.48278 530.4566 474.0343 -3284.0957 -371.97492 1306084.3 -1306822.6 3392.0306 48631.318 269.36641 0.1041603 + 1850 -462.80151 2536.7173 176.10873 -2999.5188 437.07855 525.05914 474.07725 -3283.7908 -422.22641 1306091.6 -1306821.3 1630.1204 48631.318 275.99568 0.016808725 + 1900 -469.8785 2468.9596 171.40473 -2938.8381 446.7879 531.6128 496.02681 -3284.2335 -395.17163 1306085.7 -1306819.6 3119.2384 48631.318 268.62462 0.014603394 + 1950 -491.07182 2445.6794 169.78853 -2936.7512 457.80204 527.21208 470.1608 -3283.9622 -391.90163 1306101.9 -1306818 1122.0978 48631.318 266.08919 0.018903661 + 2000 -518.41243 2418.604 167.90885 -2937.0165 415.92605 536.62844 480.48912 -3283.7876 -363.72641 1306096.2 -1306818.7 4474.8778 48631.318 263.07743 0.13492637 +Loop time of 22.3198 on 4 procs for 2000 steps with 5500 atoms + +Performance: 3.871 ns/day, 6.200 hours/ns, 89.606 timesteps/s +98.3% CPU use with 4 MPI tasks x 1 OpenMP threads + +MPI task timing breakdown: +Section | min time | avg time | max time |%varavg| %total +--------------------------------------------------------------- +Pair | 11.452 | 12.249 | 12.556 | 13.2 | 54.88 +Bond | 0.71352 | 0.72923 | 0.74557 | 1.3 | 3.27 +Kspace | 5.7189 | 6.0293 | 6.8195 | 18.6 | 27.01 +Neigh | 0.44028 | 0.44044 | 0.44065 | 0.0 | 1.97 +Comm | 0.39667 | 0.40817 | 0.41558 | 1.1 | 1.83 +Output | 0.0019479 | 0.0032187 | 0.0068657 | 3.7 | 0.01 +Modify | 2.413 | 2.4256 | 2.4347 | 0.5 | 10.87 +Other | | 0.0349 | | | 0.16 + +Nlocal: 1375 ave 1407 max 1349 min +Histogram: 1 0 0 1 1 0 0 0 0 1 +Nghost: 8082.5 ave 8114 max 8047 min +Histogram: 1 0 0 0 0 2 0 0 0 1 +Neighs: 325715 ave 343636 max 314954 min +Histogram: 1 1 0 1 0 0 0 0 0 1 + +Total # of neighbors = 1302860 +Ave neighs/atom = 236.884 +Ave special neighs/atom = 15.6364 +Neighbor list builds = 44 +Dangerous builds = 0 +Total wall time: 0:00:22 From aba472df3b0b48af8b8c367f2bfa184b4b466fc7 Mon Sep 17 00:00:00 2001 From: charlie sievers Date: Tue, 17 Sep 2019 12:25:07 -0700 Subject: [PATCH 153/192] removed excess line in langevin docs --- doc/src/fix_langevin.txt | 1 - 1 file changed, 1 deletion(-) diff --git a/doc/src/fix_langevin.txt b/doc/src/fix_langevin.txt index 0aa65be0f5..8d489a27d1 100644 --- a/doc/src/fix_langevin.txt +++ b/doc/src/fix_langevin.txt @@ -260,7 +260,6 @@ recall that while the equilibrium statistics is appropriately sampled, the corre of the trajectories may not be for large time steps, as is the case for all thermostats. All thermostats provide good statistics and dynamics for small time steps. The 2GJ half-step velocity {vhalf} samples the correct velocity distribution for the {gjf} trajectory. -other available thermostats are shown in the LAMMPS directory: examples/gjf. This updated implementation of the {gjf} thermostat includes the choice between outputting either the on-site {vfull} or half-step {vhalf} velocity. The on-site From 636a8aaef99dd8554b0a269c81a50a2b2a5b7842 Mon Sep 17 00:00:00 2001 From: Axel Kohlmeyer Date: Tue, 17 Sep 2019 16:06:12 -0400 Subject: [PATCH 154/192] whitespace cleanup, mention pip install --user --- tools/replica/reorder_remd_traj.py | 245 +++++++++++++++-------------- 1 file changed, 123 insertions(+), 122 deletions(-) diff --git a/tools/replica/reorder_remd_traj.py b/tools/replica/reorder_remd_traj.py index c8c467ffe0..5934a7fdd6 100644 --- a/tools/replica/reorder_remd_traj.py +++ b/tools/replica/reorder_remd_traj.py @@ -2,18 +2,18 @@ """ LAMMPS Replica Exchange Molecular Dynamics (REMD) trajectories are arranged by -replica, i.e., each trajectory is a continuous replica that records all the +replica, i.e., each trajectory is a continuous replica that records all the ups and downs in temperature. However, often the requirement is trajectories that are continuous in temperature, which is achieved by this tool. -Author: +Author: Tanmoy Sanyal, Shell lab, Chemical Engineering, UC Santa Barbara Email: tanmoy dot 7989 at gmail dot com Usage ----- To get detailed information about the arguments, flags, etc use: -python reorder_remd_traj.py -h or +python reorder_remd_traj.py -h or python reorder_remd_traj.py --help Features of this script @@ -66,17 +66,17 @@ def _get_nearest_temp(temps, query_temp): """ Helper function to get the nearest temp in a list from a given query_temp - + :param temps: list of temps. - + :param query_temp: query temp - + Returns: idx: index of nearest temp in the list - + out_temp: nearest temp from the list """ - + if isinstance(temps, list): temps = np.array(temps) idx = np.argmin(abs(temps - query_temp)) out_temp = temps[idx] @@ -84,17 +84,17 @@ def _get_nearest_temp(temps, query_temp): def readwrite(trajfn, mode = "rb"): - """ + """ Helper function for input/output LAMMPS traj files. Trajectories may be plain text, .gz or .bz2 compressed. - + :param trajfn: name of LAMMPS traj - + :param mode: "r" ("w") and "rb" ("wb") depending on read or write - + Returns: file pointer """ - + if trajfn.endswith(".gz"): return gzip.GzipFile(trajfn, mode) elif trajfn.endswith(".bz2"): @@ -105,32 +105,32 @@ def readwrite(trajfn, mode = "rb"): def get_replica_frames(logfn, temps, nswap, writefreq): """ - Get a list of frames from each replica that is + Get a list of frames from each replica that is at a particular temp. Do this for all temps. - + :param logfn: master LAMMPS log file that contains the temp swap history of all replicas - + :param temps: list of all temps used in the REMD simulation. - + :param nswap: swap frequency of the REMD simulation - + :param writefreq: traj dump frequency in LAMMPS - - Returns: master_frametuple_dict: + + Returns: master_frametuple_dict: dict containing a tuple (replica #, frame #) for each temp. """ - + n_rep = len(temps) swap_history = np.loadtxt(logfn, skiprows = 3) - master_frametuple_dict = dict( (n, []) for n in range(n_rep) ) - + master_frametuple_dict = dict( (n, []) for n in range(n_rep) ) + # walk through the replicas print("Getting frames from all replicas at temperature:") for n in range(n_rep): print("%3.2f K" % temps[n]) rep_inds = [np.where(x[1:] == n)[0][0] for x in swap_history] - + # case-1: when frames are dumped faster than temp. swaps if writefreq <= nswap: for ii, i in enumerate(rep_inds[:-1]): @@ -138,54 +138,54 @@ def get_replica_frames(logfn, temps, nswap, writefreq): stop = int( (ii+1) * nswap / writefreq) [master_frametuple_dict[n].append( (i,x) ) \ for x in range(start, stop)] - + # case-2: when temps. are swapped faster than dumping frames else: nskip = int(writefreq / nswap) [master_frametuple_dict[n].append( (i,ii) ) \ for ii, i in enumerate(rep_inds[0::nskip])] - + return master_frametuple_dict def get_byte_index(rep_inds, byteindfns, intrajfns): """ Get byte indices from (un-ordered) trajectories. - + :param rep_inds: indices of replicas to process on this proc - + :param byteindsfns: list of filenames that will contain the byte indices - + :param intrajfns: list of (unordered) input traj filenames """ for n in rep_inds: # check if the byte indices for this traj has aleady been computed if os.path.isfile(byteindfns[n]): continue - + # extract bytes - fobj = readwrite(intrajfns[n]) + fobj = readwrite(intrajfns[n]) byteinds = [ [0,0] ] - + # place file pointer at first line nframe = 0 first_line = fobj.readline() cur_pos = fobj.tell() - + # status printed only for replica read on root proc # this assumes that each proc takes roughly the same time if me == ROOT: - pb = tqdm(desc = "Reading replicas", leave = True, - position = ROOT + 2*me, - unit = "B/replica", unit_scale = True, + pb = tqdm(desc = "Reading replicas", leave = True, + position = ROOT + 2*me, + unit = "B/replica", unit_scale = True, unit_divisor = 1024) - + # start crawling through the bytes while True: next_line = fobj.readline() if len(next_line) == 0: break # this will only work with lammpstrj traj format. - # this condition essentially checks periodic recurrences - # of the token TIMESTEP. Each time it is found, + # this condition essentially checks periodic recurrences + # of the token TIMESTEP. Each time it is found, # we have crawled through a frame (snapshot) if next_line == first_line: nframe += 1 @@ -194,72 +194,72 @@ def get_byte_index(rep_inds, byteindfns, intrajfns): cur_pos = fobj.tell() if me == ROOT: pb.update(0) if me == ROOT: pb.close() - + # take care of the EOF cur_pos = fobj.tell() byteinds.append( [nframe+1, cur_pos] ) # dummy index for the EOF - + # write to file np.savetxt(byteindfns[n], np.array(byteinds), fmt = "%d") - + # close the trajfile object fobj.close() - + return -def write_reordered_traj(temp_inds, byte_inds, outtemps, temps, +def write_reordered_traj(temp_inds, byte_inds, outtemps, temps, frametuple_dict, nprod, writefreq, outtrajfns, infobjs): """ Reorders trajectories by temp. and writes them to disk - - :param temp_inds: list index of temps (in the list of all temps) for which + + :param temp_inds: list index of temps (in the list of all temps) for which reordered trajs will be produced on this proc. - + :param byte_inds: dict containing the (previously stored) byte indices for each replica file (key = replica number) - + :param outtemps: list of all temps for which to produce reordered trajs. - + :param temps: list of all temps used in the REMD simulation. - + :param outtrajfns: list of filenames for output (ordered) trajs. - - :param frametuple_dict: dict containing a tuple (replica #, frame #) + + :param frametuple_dict: dict containing a tuple (replica #, frame #) for each temp. - - :param nprod: number of production timesteps. - Last (nprod / writefreq) frames + + :param nprod: number of production timesteps. + Last (nprod / writefreq) frames from the end will be written to disk. - + :param writefreq: traj dump frequency in LAMMPS - + :param infobjs: list of file pointers to input (unordered) trajs. """ - + nframes = int(nprod / writefreq) - + for n in temp_inds: # open string-buffer and file buf = IOBuffer() of = readwrite(outtrajfns[n], mode = "wb") - + # get frames abs_temp_ind = np.argmin( abs(temps - outtemps[n]) ) frametuple = frametuple_dict[abs_temp_ind][-nframes:] - + # write frames to buffer if me == ROOT: - pb = tqdm(frametuple, + pb = tqdm(frametuple, desc = ("Buffering trajectories for writing"), leave = True, position = ROOT + 2*me, unit = 'frame/replica', unit_scale = True) - + iterable = pb else: iterable = frametuple - + for i, (rep, frame) in enumerate(iterable): infobj = infobjs[rep] start_ptr = int(byte_inds[rep][frame,1]) @@ -268,52 +268,52 @@ def write_reordered_traj(temp_inds, byte_inds, outtemps, temps, infobj.seek(start_ptr) buf.write(infobj.read(byte_len)) if me == ROOT: pb.close() - + # write buffer to disk if me == ROOT: print("Writing buffer to file") of.write(buf.getvalue()) of.close() buf.close() - + for i in infobjs: i.close() - + return - - + + def get_canonical_logw(enefn, frametuple_dict, temps, nprod, writefreq, kB = 0.001987): """ Gets configurational log-weights (logw) for each frame and at each temp. from the REMD simulation. ONLY WRITTEN FOR THE CANONICAL (NVT) ensemble. - - This weights can be used to calculate the + + This weights can be used to calculate the ensemble averaged value of any simulation observable X at a given temp. T : (T) = \sum_{k=1, ntemps} \sum_{n=1, nframes} w[idx][k,n] X[k,n] where nframes is the number of frames to use from each *reordered* traj - + :param enefn: ascii file (readable by numpy.loadtxt) containing an array u[r,n] of *total* potential energy for the n-th frame for the r-th replica. - - :param frametuple_dict: dict containing a tuple (replica #, frame #) + + :param frametuple_dict: dict containing a tuple (replica #, frame #) for each temp. - + :param temps: array of temps. used in the REMD simulation - - :param nprod: number of production timesteps. Last (nprod / writefreq) + + :param nprod: number of production timesteps. Last (nprod / writefreq) frames from the end will be written to disk. - + :param writefreq: traj dump frequency in LAMMPS - + :param kB : Boltzmann constant to set the energy scale. Default is in kcal/mol - + Returns: logw: dict, logw[l][k,n] gives the log weights from the n-th frame of the k-th temp. *ordered* trajectory to reweight to the l-th temp. - + """ - + try: import pymbar except ImportError: @@ -321,36 +321,37 @@ def get_canonical_logw(enefn, frametuple_dict, temps, nprod, writefreq, Configurational log-weight calculation requires pymbar. Here are some options to install it: conda install -c omnia pymbar - pip install pymbar - + pip install --user pymbar + sudo pip install pymbar + To install the dev. version directly from github, use: pip install pip install git+https://github.com/choderalab/pymbar.git """) - + u_rn = np.loadtxt(enefn) ntemps = u_rn.shape[0] # number of temps. nframes = int(nprod / writefreq) # number of frames at each temp. - + # reorder the temps u_kn = np.zeros([ntemps, nframes], float) for k in range(ntemps): frame_tuple = frametuple_dict[k][-nframes:] for i, (rep, frame) in enumerate(frame_tuple): u_kn[k, i] = u_rn[rep, frame] - - # prep input for pymbar + + # prep input for pymbar #1) array of frames at each temp. nframes_k = nframes * np.ones(ntemps, np.uint8) - + #2) inverse temps. for chosen energy scale beta_k = 1.0 / (kB * temps) - + #3) get reduced energies (*ONLY FOR THE CANONICAL ENSEMBLE*) u_kln = np.zeros([ntemps, ntemps, nframes], float) for k in range(ntemps): for l in range(ntemps): u_kln[ k, l, 0:nframes_k[k] ] = beta_k[l] * u_kn[k, 0:nframes_k[k]] - + # run pymbar and extract the free energies print("\nRunning pymbar...") mbar = pymbar.mbar.MBAR(u_kln, nframes_k, verbose = True) @@ -377,7 +378,7 @@ if __name__ == "__main__": parser = argparse.ArgumentParser(description = __doc__, formatter_class = argparse.RawDescriptionHelpFormatter) - parser.add_argument("prefix", + parser.add_argument("prefix", help = "Prefix of REMD LAMMPS trajectories.\ Supply full path. Trajectories assumed to be named as \ .%%d.lammpstrj. \ @@ -392,7 +393,7 @@ if __name__ == "__main__": parser.add_argument("-tfn", "--tempfn", default = "temps.txt", help = "ascii file (readable by numpy.loadtxt) with \ the temperatures used in the REMD simulation.") - + parser.add_argument("-ns", "--nswap", type = int, help = "Swap frequency used in LAMMPS temper command") @@ -405,11 +406,11 @@ if __name__ == "__main__": trajectories.\ This should be in units of the LAMMPS timestep") - parser.add_argument("-logw", "--logw", action = 'store_true', + parser.add_argument("-logw", "--logw", action = 'store_true', help = "Supplying this flag \ calculates *canonical* (NVT ensemble) log weights") - - parser.add_argument("-e", "--enefn", + + parser.add_argument("-e", "--enefn", help = "File that has n_replica x n_frames array\ of total potential energies") @@ -418,19 +419,19 @@ if __name__ == "__main__": help = "Boltzmann constant in appropriate units. \ Default is kcal/mol") - parser.add_argument("-ot", "--out_temps", nargs = '+', type = np.float64, + parser.add_argument("-ot", "--out_temps", nargs = '+', type = np.float64, help = "Reorder trajectories at these temperatures.\n \ Default is all temperatures used in the simulation") parser.add_argument("-od", "--outdir", default = ".", help = "All output will be saved to this directory") - + # parse inputs args = parser.parse_args() traj_prefix = os.path.abspath(args.prefix) logfn = os.path.abspath(args.logfn) tempfn = os.path.abspath(args.tempfn) - + nswap = args.nswap writefreq = args.nwrite nprod = args.nprod @@ -454,7 +455,7 @@ if __name__ == "__main__": elif get_logw and not os.path.isfile(enefn): raise IOError("Canonical log-weight calculation requested but\ energy file %s not found" % enefn) - + # get (unordered) trajectories temps = np.loadtxt(tempfn) ntemps = len(temps) @@ -470,8 +471,8 @@ if __name__ == "__main__": intrajfns[i] = this_intrajfn + ".bz2" else: if me == ROOT: - raise IOError("Trajectory for replica # %d missing" % i) - + raise IOError("Trajectory for replica # %d missing" % i) + # set output filenames outprefix = os.path.join(outdir, traj_prefix.split('/')[-1]) outtrajfns = ["%s.%3.2f.lammpstrj.gz" % \ @@ -482,44 +483,44 @@ if __name__ == "__main__": frametuplefn = outprefix + '.frametuple.pickle' if get_logw: logwfn = outprefix + ".logw.pickle" - - + + # get a list of all frames at a particular temp visited by each replica # this is fast so run only on ROOT proc. master_frametuple_dict = {} if me == ROOT: - master_frametuple_dict = get_replica_frames(logfn = logfn, + master_frametuple_dict = get_replica_frames(logfn = logfn, temps = temps, nswap = nswap, writefreq = writefreq) # save to a pickle from the ROOT proc with open(frametuplefn, 'wb') as of: pickle.dump(master_frametuple_dict, of) - + # broadcast to all procs master_frametuple_dict = comm.bcast(master_frametuple_dict, root = ROOT) - + # define a chunk of replicas to process on each proc CHUNKSIZE_1 = int(ntemps/nproc) if me < nproc - 1: my_rep_inds = range( (me*CHUNKSIZE_1), (me+1)*CHUNKSIZE_1 ) else: my_rep_inds = range( (me*CHUNKSIZE_1), ntemps ) - + # get byte indices from replica (un-ordered) trajs. in parallel - get_byte_index(rep_inds = my_rep_inds, + get_byte_index(rep_inds = my_rep_inds, byteindfns = byteindfns, intrajfns = intrajfns) - + # block until all procs have finished comm.barrier() - + # open all replica files for reading infobjs = [readwrite(i) for i in intrajfns] - + # open all byteindex files byte_inds = dict( (i, np.loadtxt(fn)) for i, fn in enumerate(byteindfns) ) - + # define a chunk of output trajs. to process for each proc. # # of reordered trajs. to write may be less than the total # of replicas # which is usually equal to the requested nproc. If that is indeed the case, @@ -537,35 +538,35 @@ if __name__ == "__main__": my_temp_inds = range( (me*CHUNKSIZE_2), (me+1)*CHUNKSIZE_1 ) else: my_temp_inds = range( (me*CHUNKSIZE_2), n_out_temps) - + # retire the excess procs # dont' forget to close any open file objects if me >= nproc_active: for fobj in infobjs: fobj.close() exit() - + # write reordered trajectories to disk from active procs in parallel write_reordered_traj(temp_inds = my_temp_inds, byte_inds = byte_inds, - outtemps = out_temps, temps = temps, + outtemps = out_temps, temps = temps, frametuple_dict = master_frametuple_dict, nprod = nprod, writefreq = writefreq, - outtrajfns = outtrajfns, + outtrajfns = outtrajfns, infobjs = infobjs) - + # calculate canonical log-weights if requested # usually this is very fast so retire all but the ROOT proc if not get_logw: exit() if not me == ROOT: exit() - - logw = get_canonical_logw(enefn = enefn, temps = temps, + + logw = get_canonical_logw(enefn = enefn, temps = temps, frametuple_dict = master_frametuple_dict, nprod = nprod, writefreq = writefreq, kB = kB) - + # save the logweights to a pickle with open(logwfn, 'wb') as of: pickle.dump(logw, of) - + From 28b634f20d28a33467c1288afea3af4ec3245586 Mon Sep 17 00:00:00 2001 From: Axel Kohlmeyer Date: Tue, 17 Sep 2019 16:10:14 -0400 Subject: [PATCH 155/192] some more whitespace cleanup --- tools/replica/example/parse_ene.py | 6 +++--- tools/replica/reorder_remd_traj.py | 6 +++--- 2 files changed, 6 insertions(+), 6 deletions(-) diff --git a/tools/replica/example/parse_ene.py b/tools/replica/example/parse_ene.py index 56b9328a6a..00cee08d68 100644 --- a/tools/replica/example/parse_ene.py +++ b/tools/replica/example/parse_ene.py @@ -15,16 +15,16 @@ for i in range(ntemps): logfn = '%s.%d' % (logfnprefix, i) with open(logfn, 'r') as of: lines = of.readlines() - + # extract relevant lines from logfile start = [lines.index(line) for line in lines if line.startswith(start_token)][0] lines = lines[(start+1) : ] stop = [lines.index(line) for line in lines if line.startswith(end_token)][0] lines = lines[:stop] - + # store the potential energies pe = [float(line.strip().split()[-1]) for line in lines] u_kn.append(pe) - + u_kn = np.array(u_kn) np.savetxt('ene.peptide', u_kn, fmt = '%5.5f') diff --git a/tools/replica/reorder_remd_traj.py b/tools/replica/reorder_remd_traj.py index 66e9489913..5f4f316b14 100644 --- a/tools/replica/reorder_remd_traj.py +++ b/tools/replica/reorder_remd_traj.py @@ -351,7 +351,7 @@ def get_canonical_logw(enefn, frametuple_dict, temps, nprod, writefreq, u_kln = np.zeros([ntemps, ntemps, nframes], float) for k in range(ntemps): u_kln[k] = np.outer(beta_k, u_kn[k]) - + # run pymbar and extract the free energies print("\nRunning pymbar...") mbar = pymbar.mbar.MBAR(u_kln, nframes_k, verbose = True) @@ -368,7 +368,7 @@ def get_canonical_logw(enefn, frametuple_dict, temps, nprod, writefreq, denom = f_k - beta_k[k] * u_kn[k,n] for l in range(ntemps): logw[l][k,n] = num - logsumexp(denom) - log_nframes - + return logw @@ -518,7 +518,7 @@ if __name__ == "__main__": # open all replica files for reading infobjs = [readwrite(i, "rb") for i in intrajfns] - + # open all byteindex files byte_inds = dict( (i, np.loadtxt(fn)) for i, fn in enumerate(byteindfns) ) From df3fad3b491d8ba9d1c596890b39003d5eb2b682 Mon Sep 17 00:00:00 2001 From: Axel Kohlmeyer Date: Wed, 18 Sep 2019 14:35:12 -0400 Subject: [PATCH 156/192] output number of processors when reporting a mismatch on reading a restart --- src/read_restart.cpp | 8 ++++++-- 1 file changed, 6 insertions(+), 2 deletions(-) diff --git a/src/read_restart.cpp b/src/read_restart.cpp index 3d2e2b6592..62ce209b90 100644 --- a/src/read_restart.cpp +++ b/src/read_restart.cpp @@ -734,8 +734,12 @@ void ReadRestart::header(int incompatible) } else if (flag == NPROCS) { nprocs_file = read_int(); - if (nprocs_file != comm->nprocs && me == 0) - error->warning(FLERR,"Restart file used different # of processors"); + if (nprocs_file != comm->nprocs && me == 0) { + char msg[128]; + snprintf(msg,128,"Restart file used different # of processors: %d vs. %d", + nprocs_file,comm->nprocs); + error->warning(FLERR,msg); + } // don't set procgrid, warn if different From 2ea11b3195ece92f1ca1f4cea395cd90c31e5e87 Mon Sep 17 00:00:00 2001 From: Axel Kohlmeyer Date: Wed, 18 Sep 2019 15:50:26 -0400 Subject: [PATCH 157/192] implement test for C++11 and document it --- cmake/CMakeLists.txt | 9 ++++++++- doc/src/Build_settings.txt | 23 +++++++++++++++++++++++ src/MAKE/Makefile.mpi | 6 +++--- src/MAKE/Makefile.serial | 6 +++--- src/lmptype.h | 7 +++++++ 5 files changed, 44 insertions(+), 7 deletions(-) diff --git a/cmake/CMakeLists.txt b/cmake/CMakeLists.txt index 91fb930be2..ed9825a830 100644 --- a/cmake/CMakeLists.txt +++ b/cmake/CMakeLists.txt @@ -52,10 +52,17 @@ check_for_autogen_files(${LAMMPS_SOURCE_DIR}) include(CheckCCompilerFlag) include(CheckIncludeFileCXX) -if (${CMAKE_CXX_COMPILER_ID} STREQUAL "Intel") +if(${CMAKE_CXX_COMPILER_ID} STREQUAL "Intel") set (CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -restrict") endif() +option(DISABLE_CXX11_REQUIREMENT "Disable check that requires C++11 for compiling LAMMPS" OFF) +if(DISABLE_CXX11_REQUIREMENT) + add_definitions(-DLAMMPS_CXX98) +else() + set(CMAKE_CXX_STANDARD 11) +endif() + # GNU compiler features if (${CMAKE_CXX_COMPILER_ID} STREQUAL "GNU") option(ENABLE_COVERAGE "Enable code coverage" OFF) diff --git a/doc/src/Build_settings.txt b/doc/src/Build_settings.txt index 287cd39ff6..baff537e3b 100644 --- a/doc/src/Build_settings.txt +++ b/doc/src/Build_settings.txt @@ -12,6 +12,7 @@ Optional build settings :h3 LAMMPS can be built with several optional settings. Each sub-section explain how to do this for building both with CMake and make. +"C++11 standard compliance test"_#cxx11 when building all of LAMMPS "FFT library"_#fft for use with the "kspace_style pppm"_kspace_style.html command "Size of LAMMPS data types"_#size "Read or write compressed files"_#gzip @@ -23,6 +24,28 @@ explain how to do this for building both with CMake and make. :line +C++11 standard compliance test :h4(cxx11) + +The LAMMPS developers plan to transition to make the C++11 standard the +minimum requirement for compiling LAMMPS. Currently this only applies to +some packages like KOKKOS while the rest aims to be compatible with the C++98 +standard. Most currently used compilers are compatible with C++11; some need +to set extra flags to switch. To determine the impact of requiring C++11, +we have added a simple compliance test to the source code, that will cause +the compilation to abort, if C++11 compliance is not available or enabled. +To bypass this check, you need to change a setting in the makefile or +when calling CMake. + +[CMake variable]: + +-D DISABLE_CXX11_REQUIREMENT=yes + +[Makefile.machine setting]: + +LMP_INC = -DLAMMPS_CXX98 + +:line + FFT library :h4,link(fft) When the KSPACE package is included in a LAMMPS build, the diff --git a/src/MAKE/Makefile.mpi b/src/MAKE/Makefile.mpi index f30220da3d..3be2e20f95 100644 --- a/src/MAKE/Makefile.mpi +++ b/src/MAKE/Makefile.mpi @@ -26,12 +26,12 @@ SHLIBFLAGS = -shared # if you change any -D setting, do full re-compile after "make clean" # LAMMPS ifdef settings -# see possible settings in Section 2.2 (step 4) of manual +# see possible settings in Section 3.5 of the manual -LMP_INC = -DLAMMPS_GZIP -DLAMMPS_MEMALIGN=64 +LMP_INC = -DLAMMPS_GZIP -DLAMMPS_MEMALIGN=64 # -DLAMMPS_CXX98 # MPI library -# see discussion in Section 2.2 (step 5) of manual +# see discussion in Section 3.4 of the manual # MPI wrapper compiler/linker can provide this info # can point to dummy MPI library in src/STUBS as in Makefile.serial # use -D MPICH and OMPI settings in INC to avoid C++ lib conflicts diff --git a/src/MAKE/Makefile.serial b/src/MAKE/Makefile.serial index 5954d97761..86ddd05053 100644 --- a/src/MAKE/Makefile.serial +++ b/src/MAKE/Makefile.serial @@ -26,12 +26,12 @@ SHLIBFLAGS = -shared # if you change any -D setting, do full re-compile after "make clean" # LAMMPS ifdef settings -# see possible settings in Section 2.2 (step 4) of manual +# see possible settings in Section 3.5 of the manual -LMP_INC = -DLAMMPS_GZIP -DLAMMPS_MEMALIGN=64 +LMP_INC = -DLAMMPS_GZIP -DLAMMPS_MEMALIGN=64 # -DLAMMPS_CXX98 # MPI library -# see discussion in Section 2.2 (step 5) of manual +# see discussion in Section 3.4 of the manual # MPI wrapper compiler/linker can provide this info # can point to dummy MPI library in src/STUBS as in Makefile.serial # use -D MPICH and OMPI settings in INC to avoid C++ lib conflicts diff --git a/src/lmptype.h b/src/lmptype.h index 65e46535fc..b220538190 100644 --- a/src/lmptype.h +++ b/src/lmptype.h @@ -28,6 +28,13 @@ #ifndef LMP_LMPTYPE_H #define LMP_LMPTYPE_H +// C++11 check +#ifndef LAMMPS_CXX98 +#if __cplusplus <= 199711L + #error LAMMPS is planning to transition to C++11. Do disable this error please use a C++11 compliant compiler, enable C++11 (or later) compliance, or define LAMMPS_CXX98 in your makefile +#endif +#endif + #ifndef __STDC_LIMIT_MACROS #define __STDC_LIMIT_MACROS #endif From e847777e43d424470ece7ea6e1affd86b39085ee Mon Sep 17 00:00:00 2001 From: Mary Alice Cusentino Date: Wed, 18 Sep 2019 14:34:20 -0600 Subject: [PATCH 158/192] Added W-Be example to example/snap folder --- examples/snap/WBe_Wood_PRB2019.snap | 1 + examples/snap/WBe_Wood_PRB2019.snapcoeff | 1 + examples/snap/WBe_Wood_PRB2019.snapparam | 1 + examples/snap/in.snap.WBe.PRB2019 | 48 ++++++ examples/snap/log.18Sep19.snap.WBeSNAP.g++.1 | 154 +++++++++++++++++++ examples/snap/log.18Sep19.snap.WBeSNAP.g++.4 | 154 +++++++++++++++++++ potentials/WBe_Wood_PRB2019.snap | 15 ++ potentials/WBe_Wood_PRB2019.snapcoeff | 117 ++++++++++++++ potentials/WBe_Wood_PRB2019.snapparam | 11 ++ 9 files changed, 502 insertions(+) create mode 120000 examples/snap/WBe_Wood_PRB2019.snap create mode 120000 examples/snap/WBe_Wood_PRB2019.snapcoeff create mode 120000 examples/snap/WBe_Wood_PRB2019.snapparam create mode 100644 examples/snap/in.snap.WBe.PRB2019 create mode 100644 examples/snap/log.18Sep19.snap.WBeSNAP.g++.1 create mode 100644 examples/snap/log.18Sep19.snap.WBeSNAP.g++.4 create mode 100644 potentials/WBe_Wood_PRB2019.snap create mode 100644 potentials/WBe_Wood_PRB2019.snapcoeff create mode 100644 potentials/WBe_Wood_PRB2019.snapparam diff --git a/examples/snap/WBe_Wood_PRB2019.snap b/examples/snap/WBe_Wood_PRB2019.snap new file mode 120000 index 0000000000..35454e3eb8 --- /dev/null +++ b/examples/snap/WBe_Wood_PRB2019.snap @@ -0,0 +1 @@ +../../potentials/WBe_Wood_PRB2019.snap \ No newline at end of file diff --git a/examples/snap/WBe_Wood_PRB2019.snapcoeff b/examples/snap/WBe_Wood_PRB2019.snapcoeff new file mode 120000 index 0000000000..b734e52610 --- /dev/null +++ b/examples/snap/WBe_Wood_PRB2019.snapcoeff @@ -0,0 +1 @@ +../../potentials/WBe_Wood_PRB2019.snapcoeff \ No newline at end of file diff --git a/examples/snap/WBe_Wood_PRB2019.snapparam b/examples/snap/WBe_Wood_PRB2019.snapparam new file mode 120000 index 0000000000..8f3530ffd6 --- /dev/null +++ b/examples/snap/WBe_Wood_PRB2019.snapparam @@ -0,0 +1 @@ +../../potentials/WBe_Wood_PRB2019.snapparam \ No newline at end of file diff --git a/examples/snap/in.snap.WBe.PRB2019 b/examples/snap/in.snap.WBe.PRB2019 new file mode 100644 index 0000000000..1e25bbb6a6 --- /dev/null +++ b/examples/snap/in.snap.WBe.PRB2019 @@ -0,0 +1,48 @@ +# Demonstrate SNAP W-Be potential + +# Initialize simulation + +variable nsteps index 100 +variable nrep equal 4 +variable a equal 3.1803 +units metal + +# generate the box and atom positions using a BCC lattice + +variable nx equal ${nrep} +variable ny equal ${nrep} +variable nz equal ${nrep} + +boundary p p p + +lattice bcc $a +region box block 0 ${nx} 0 ${ny} 0 ${nz} +create_box 2 box +create_atoms 1 box +mass 1 183.84 +mass 2 9.012182 + +set group all type/fraction 2 0.05 3590153 # Change 5% of W to He +group tungsten type 1 +group beryllium type 2 +# choose potential + +include WBe_Wood_PRB2019.snap + +# Setup output + +thermo 10 +thermo_modify norm yes + +# Set up NVE run + +timestep 0.5e-3 +neighbor 1.0 bin +neigh_modify once no every 1 delay 0 check yes + +# Run MD + +velocity all create 300.0 4928459 +fix 1 all nve +run ${nsteps} + diff --git a/examples/snap/log.18Sep19.snap.WBeSNAP.g++.1 b/examples/snap/log.18Sep19.snap.WBeSNAP.g++.1 new file mode 100644 index 0000000000..2b889e036b --- /dev/null +++ b/examples/snap/log.18Sep19.snap.WBeSNAP.g++.1 @@ -0,0 +1,154 @@ +LAMMPS (7 Aug 2019) +# Demonstrate SNAP W-Be potential + +# Initialize simulation + +variable nsteps index 100 +variable nrep equal 4 +variable a equal 3.1803 +units metal + +# generate the box and atom positions using a BCC lattice + +variable nx equal ${nrep} +variable nx equal 4 +variable ny equal ${nrep} +variable ny equal 4 +variable nz equal ${nrep} +variable nz equal 4 + +boundary p p p + +lattice bcc $a +lattice bcc 3.1803 +Lattice spacing in x,y,z = 3.1803 3.1803 3.1803 +region box block 0 ${nx} 0 ${ny} 0 ${nz} +region box block 0 4 0 ${ny} 0 ${nz} +region box block 0 4 0 4 0 ${nz} +region box block 0 4 0 4 0 4 +create_box 2 box +Created orthogonal box = (0 0 0) to (12.7212 12.7212 12.7212) + 1 by 1 by 1 MPI processor grid +create_atoms 1 box +Created 128 atoms + create_atoms CPU = 0.000234842 secs +mass 1 183.84 +mass 2 9.012182 + +set group all type/fraction 2 0.05 3590153 # Change 5% of W to He + 5 settings made for type/fraction +group tungsten type 1 +123 atoms in group tungsten +group beryllium type 2 +5 atoms in group beryllium +# choose potential + +include WBe_Wood_PRB2019.snap +# Definition of SNAP+ZBL potential. +variable zblcutinner equal 4 +variable zblcutouter equal 4.8 +variable zblz1 equal 74 +variable zblz2 equal 4 + +# Specify hybrid with SNAP and ZBL + +pair_style hybrid/overlay zbl ${zblcutinner} ${zblcutouter} snap +pair_style hybrid/overlay zbl 4 ${zblcutouter} snap +pair_style hybrid/overlay zbl 4 4.8 snap +pair_coeff 1 1 zbl ${zblz1} ${zblz1} +pair_coeff 1 1 zbl 74 ${zblz1} +pair_coeff 1 1 zbl 74 74 +pair_coeff 1 2 zbl ${zblz1} ${zblz2} +pair_coeff 1 2 zbl 74 ${zblz2} +pair_coeff 1 2 zbl 74 4 +pair_coeff 2 2 zbl ${zblz2} ${zblz2} +pair_coeff 2 2 zbl 4 ${zblz2} +pair_coeff 2 2 zbl 4 4 +pair_coeff * * snap WBe_Wood_PRB2019.snapcoeff WBe_Wood_PRB2019.snapparam W Be +SNAP Element = W, Radius 0.5, Weight 1 +SNAP Element = Be, Radius 0.417932, Weight 0.959049 +SNAP keyword rcutfac 4.8123 +SNAP keyword twojmax 8 +SNAP keyword rfac0 0.99363 +SNAP keyword rmin0 0 +SNAP keyword bzeroflag 1 +SNAP keyword quadraticflag 0 + + +# Setup output + +thermo 10 +thermo_modify norm yes + +# Set up NVE run + +timestep 0.5e-3 +neighbor 1.0 bin +neigh_modify once no every 1 delay 0 check yes + +# Run MD + +velocity all create 300.0 4928459 +fix 1 all nve +run ${nsteps} +run 100 +Neighbor list info ... + update every 1 steps, delay 0 steps, check yes + max neighbors/atom: 2000, page size: 100000 + master list distance cutoff = 5.8123 + ghost atom cutoff = 5.8123 + binsize = 2.90615, bins = 5 5 5 + 2 neighbor lists, perpetual/occasional/extra = 2 0 0 + (1) pair zbl, perpetual, half/full from (2) + attributes: half, newton on + pair build: halffull/newton + stencil: none + bin: none + (2) pair snap, perpetual + attributes: full, newton on + pair build: full/bin/atomonly + stencil: full/bin/3d + bin: standard +Per MPI rank memory allocation (min/avg/max) = 4.268 | 4.268 | 4.268 Mbytes +Step Temp E_pair E_mol TotEng Press + 0 300 -8.5980876 0 -8.5596125 -35284.855 + 10 299.29029 -8.5979965 0 -8.5596125 -35299.259 + 20 288.99334 -8.5966759 0 -8.5596124 -35004.093 + 30 269.91027 -8.5942284 0 -8.5596123 -34447.077 + 40 243.57361 -8.5908505 0 -8.5596121 -33687.105 + 50 212.21385 -8.5868284 0 -8.5596119 -32821.864 + 60 178.77144 -8.5825391 0 -8.5596116 -31971.17 + 70 146.71854 -8.578428 0 -8.5596113 -31245.51 + 80 119.50956 -8.5749383 0 -8.5596111 -30724.137 + 90 99.872785 -8.5724197 0 -8.559611 -30440.244 + 100 89.604584 -8.5711027 0 -8.5596109 -30392.805 +Loop time of 3.16831 on 1 procs for 100 steps with 128 atoms + +Performance: 1.364 ns/day, 17.602 hours/ns, 31.563 timesteps/s +199.5% CPU use with 1 MPI tasks x no OpenMP threads + +MPI task timing breakdown: +Section | min time | avg time | max time |%varavg| %total +--------------------------------------------------------------- +Pair | 3.1672 | 3.1672 | 3.1672 | 0.0 | 99.97 +Neigh | 0.00030208 | 0.00030208 | 0.00030208 | 0.0 | 0.01 +Comm | 0.00029612 | 0.00029612 | 0.00029612 | 0.0 | 0.01 +Output | 0.00019813 | 0.00019813 | 0.00019813 | 0.0 | 0.01 +Modify | 0.00014448 | 0.00014448 | 0.00014448 | 0.0 | 0.00 +Other | | 0.0001433 | | | 0.00 + +Nlocal: 128 ave 128 max 128 min +Histogram: 1 0 0 0 0 0 0 0 0 0 +Nghost: 727 ave 727 max 727 min +Histogram: 1 0 0 0 0 0 0 0 0 0 +Neighs: 3710 ave 3710 max 3710 min +Histogram: 1 0 0 0 0 0 0 0 0 0 +FullNghs: 7420 ave 7420 max 7420 min +Histogram: 1 0 0 0 0 0 0 0 0 0 + +Total # of neighbors = 7420 +Ave neighs/atom = 57.9688 +Neighbor list builds = 1 +Dangerous builds = 0 + +Total wall time: 0:00:03 diff --git a/examples/snap/log.18Sep19.snap.WBeSNAP.g++.4 b/examples/snap/log.18Sep19.snap.WBeSNAP.g++.4 new file mode 100644 index 0000000000..d8cdae6810 --- /dev/null +++ b/examples/snap/log.18Sep19.snap.WBeSNAP.g++.4 @@ -0,0 +1,154 @@ +LAMMPS (7 Aug 2019) +# Demonstrate SNAP W-Be potential + +# Initialize simulation + +variable nsteps index 100 +variable nrep equal 4 +variable a equal 3.1803 +units metal + +# generate the box and atom positions using a BCC lattice + +variable nx equal ${nrep} +variable nx equal 4 +variable ny equal ${nrep} +variable ny equal 4 +variable nz equal ${nrep} +variable nz equal 4 + +boundary p p p + +lattice bcc $a +lattice bcc 3.1803 +Lattice spacing in x,y,z = 3.1803 3.1803 3.1803 +region box block 0 ${nx} 0 ${ny} 0 ${nz} +region box block 0 4 0 ${ny} 0 ${nz} +region box block 0 4 0 4 0 ${nz} +region box block 0 4 0 4 0 4 +create_box 2 box +Created orthogonal box = (0 0 0) to (12.7212 12.7212 12.7212) + 1 by 2 by 2 MPI processor grid +create_atoms 1 box +Created 128 atoms + create_atoms CPU = 0.000317097 secs +mass 1 183.84 +mass 2 9.012182 + +set group all type/fraction 2 0.05 3590153 # Change 5% of W to He + 5 settings made for type/fraction +group tungsten type 1 +123 atoms in group tungsten +group beryllium type 2 +5 atoms in group beryllium +# choose potential + +include WBe_Wood_PRB2019.snap +# Definition of SNAP+ZBL potential. +variable zblcutinner equal 4 +variable zblcutouter equal 4.8 +variable zblz1 equal 74 +variable zblz2 equal 4 + +# Specify hybrid with SNAP and ZBL + +pair_style hybrid/overlay zbl ${zblcutinner} ${zblcutouter} snap +pair_style hybrid/overlay zbl 4 ${zblcutouter} snap +pair_style hybrid/overlay zbl 4 4.8 snap +pair_coeff 1 1 zbl ${zblz1} ${zblz1} +pair_coeff 1 1 zbl 74 ${zblz1} +pair_coeff 1 1 zbl 74 74 +pair_coeff 1 2 zbl ${zblz1} ${zblz2} +pair_coeff 1 2 zbl 74 ${zblz2} +pair_coeff 1 2 zbl 74 4 +pair_coeff 2 2 zbl ${zblz2} ${zblz2} +pair_coeff 2 2 zbl 4 ${zblz2} +pair_coeff 2 2 zbl 4 4 +pair_coeff * * snap WBe_Wood_PRB2019.snapcoeff WBe_Wood_PRB2019.snapparam W Be +SNAP Element = W, Radius 0.5, Weight 1 +SNAP Element = Be, Radius 0.417932, Weight 0.959049 +SNAP keyword rcutfac 4.8123 +SNAP keyword twojmax 8 +SNAP keyword rfac0 0.99363 +SNAP keyword rmin0 0 +SNAP keyword bzeroflag 1 +SNAP keyword quadraticflag 0 + + +# Setup output + +thermo 10 +thermo_modify norm yes + +# Set up NVE run + +timestep 0.5e-3 +neighbor 1.0 bin +neigh_modify once no every 1 delay 0 check yes + +# Run MD + +velocity all create 300.0 4928459 +fix 1 all nve +run ${nsteps} +run 100 +Neighbor list info ... + update every 1 steps, delay 0 steps, check yes + max neighbors/atom: 2000, page size: 100000 + master list distance cutoff = 5.8123 + ghost atom cutoff = 5.8123 + binsize = 2.90615, bins = 5 5 5 + 2 neighbor lists, perpetual/occasional/extra = 2 0 0 + (1) pair zbl, perpetual, half/full from (2) + attributes: half, newton on + pair build: halffull/newton + stencil: none + bin: none + (2) pair snap, perpetual + attributes: full, newton on + pair build: full/bin/atomonly + stencil: full/bin/3d + bin: standard +Per MPI rank memory allocation (min/avg/max) = 4.167 | 4.167 | 4.167 Mbytes +Step Temp E_pair E_mol TotEng Press + 0 300 -8.5980876 0 -8.5596125 -35284.855 + 10 296.24946 -8.5976065 0 -8.5596124 -35140.29 + 20 282.27904 -8.5958147 0 -8.5596123 -34710.3 + 30 259.54978 -8.5928995 0 -8.5596121 -34060.43 + 40 230.41412 -8.5891626 0 -8.5596119 -33258.275 + 50 197.85135 -8.5849861 0 -8.5596116 -32389.527 + 60 165.21732 -8.5808005 0 -8.5596113 -31550.426 + 70 135.94024 -8.5770455 0 -8.5596111 -30839.006 + 80 113.06617 -8.5741117 0 -8.5596109 -30339.177 + 90 98.542347 -8.572249 0 -8.5596109 -30094.29 + 100 92.524343 -8.5714774 0 -8.5596111 -30091.988 +Loop time of 0.813674 on 4 procs for 100 steps with 128 atoms + +Performance: 5.309 ns/day, 4.520 hours/ns, 122.899 timesteps/s +99.7% CPU use with 4 MPI tasks x no OpenMP threads + +MPI task timing breakdown: +Section | min time | avg time | max time |%varavg| %total +--------------------------------------------------------------- +Pair | 0.79079 | 0.79788 | 0.80888 | 0.8 | 98.06 +Neigh | 7.1049e-05 | 8.0049e-05 | 9.2983e-05 | 0.0 | 0.01 +Comm | 0.0041246 | 0.01515 | 0.022235 | 5.5 | 1.86 +Output | 0.000144 | 0.00017095 | 0.00024796 | 0.0 | 0.02 +Modify | 4.4823e-05 | 5.8889e-05 | 7.2718e-05 | 0.0 | 0.01 +Other | | 0.000338 | | | 0.04 + +Nlocal: 32 ave 37 max 28 min +Histogram: 1 0 0 1 1 0 0 0 0 1 +Nghost: 431 ave 435 max 426 min +Histogram: 1 0 0 0 0 1 1 0 0 1 +Neighs: 927 ave 1071 max 821 min +Histogram: 1 0 1 0 1 0 0 0 0 1 +FullNghs: 1854 ave 2144 max 1624 min +Histogram: 1 0 0 1 1 0 0 0 0 1 + +Total # of neighbors = 7416 +Ave neighs/atom = 57.9375 +Neighbor list builds = 1 +Dangerous builds = 0 + +Total wall time: 0:00:00 diff --git a/potentials/WBe_Wood_PRB2019.snap b/potentials/WBe_Wood_PRB2019.snap new file mode 100644 index 0000000000..6c32256a19 --- /dev/null +++ b/potentials/WBe_Wood_PRB2019.snap @@ -0,0 +1,15 @@ +# DATE: 2019-09-18 CONTRIBUTOR: Mary Alice Cusentino mcusent@sandia.gov CITATION: M.A. Wood, M.A. Cusentino, B.D. Wirth, and A.P. Thompson, "Data-driven material models for atomistic simulation", Physical Review B 99, 184305 (2019) +# Definition of SNAP+ZBL potential. +variable zblcutinner equal 4 +variable zblcutouter equal 4.8 +variable zblz1 equal 74 +variable zblz2 equal 4 + +# Specify hybrid with SNAP and ZBL + +pair_style hybrid/overlay zbl ${zblcutinner} ${zblcutouter} snap +pair_coeff 1 1 zbl ${zblz1} ${zblz1} +pair_coeff 1 2 zbl ${zblz1} ${zblz2} +pair_coeff 2 2 zbl ${zblz2} ${zblz2} +pair_coeff * * snap WBe_Wood_PRB2019.snapcoeff WBe_Wood_PRB2019.snapparam W Be + diff --git a/potentials/WBe_Wood_PRB2019.snapcoeff b/potentials/WBe_Wood_PRB2019.snapcoeff new file mode 100644 index 0000000000..c72baabd74 --- /dev/null +++ b/potentials/WBe_Wood_PRB2019.snapcoeff @@ -0,0 +1,117 @@ +# LAMMPS SNAP coefficients for WBe + +2 56 +W 0.5 1 + -0.000000000000 # B[0] + -0.001487061994 # B[1, 0, 0, 0] + 0.075808306870 # B[2, 1, 0, 1] + 0.538735683870 # B[3, 1, 1, 2] + -0.074148039366 # B[4, 2, 0, 2] + 0.602629813770 # B[5, 2, 1, 3] + -0.147022424344 # B[6, 2, 2, 2] + 0.117756828488 # B[7, 2, 2, 4] + -0.026490439049 # B[8, 3, 0, 3] + -0.035162708767 # B[9, 3, 1, 4] + 0.064315385091 # B[10, 3, 2, 3] + -0.131936948089 # B[11, 3, 2, 5] + -0.021272860272 # B[12, 3, 3, 4] + -0.091171134054 # B[13, 3, 3, 6] + -0.024396224398 # B[14, 4, 0, 4] + -0.059813132803 # B[15, 4, 1, 5] + 0.069585393203 # B[16, 4, 2, 4] + -0.085344044181 # B[17, 4, 2, 6] + -0.155425254597 # B[18, 4, 3, 5] + -0.117031758367 # B[19, 4, 3, 7] + -0.040956258020 # B[20, 4, 4, 4] + -0.084465000389 # B[21, 4, 4, 6] + -0.020367513630 # B[22, 4, 4, 8] + -0.010730484318 # B[23, 5, 0, 5] + -0.054777575658 # B[24, 5, 1, 6] + 0.050742893747 # B[25, 5, 2, 5] + -0.004686334611 # B[26, 5, 2, 7] + -0.116372907121 # B[27, 5, 3, 6] + 0.005542497708 # B[28, 5, 3, 8] + -0.126526795635 # B[29, 5, 4, 5] + -0.080163926221 # B[30, 5, 4, 7] + -0.082426250179 # B[31, 5, 5, 6] + -0.010558777281 # B[32, 5, 5, 8] + -0.001939058038 # B[33, 6, 0, 6] + -0.027907949962 # B[34, 6, 1, 7] + 0.049483908476 # B[35, 6, 2, 6] + 0.005103754385 # B[36, 6, 2, 8] + -0.054751505141 # B[37, 6, 3, 7] + -0.055556071011 # B[38, 6, 4, 6] + -0.006026917619 # B[39, 6, 4, 8] + -0.060889030109 # B[40, 6, 5, 7] + -0.029977673973 # B[41, 6, 6, 6] + -0.014987527280 # B[42, 6, 6, 8] + -0.006697686658 # B[43, 7, 0, 7] + 0.017369624409 # B[44, 7, 1, 8] + 0.047864358817 # B[45, 7, 2, 7] + -0.001989812679 # B[46, 7, 3, 8] + 0.000153530925 # B[47, 7, 4, 7] + -0.003862356345 # B[48, 7, 5, 8] + -0.009754314198 # B[49, 7, 6, 7] + 0.000777958970 # B[50, 7, 7, 8] + -0.003031424287 # B[51, 8, 0, 8] + 0.015612715209 # B[52, 8, 2, 8] + 0.003210129646 # B[53, 8, 4, 8] + -0.013088799947 # B[54, 8, 6, 8] + 0.001465970755 # B[55, 8, 8, 8] +Be 0.417932 0.959049 + 0.000000000000 # B[0] + -0.000112143918 # B[1, 0, 0, 0] + 0.002449805180 # B[2, 1, 0, 1] + 0.189705916830 # B[3, 1, 1, 2] + -0.019967429692 # B[4, 2, 0, 2] + 0.286015704682 # B[5, 2, 1, 3] + 0.072864063124 # B[6, 2, 2, 2] + 0.108748154196 # B[7, 2, 2, 4] + -0.005203284351 # B[8, 3, 0, 3] + 0.043948598532 # B[9, 3, 1, 4] + 0.105425889093 # B[10, 3, 2, 3] + 0.060460134045 # B[11, 3, 2, 5] + -0.003406205141 # B[12, 3, 3, 4] + 0.002306765306 # B[13, 3, 3, 6] + -0.003845115174 # B[14, 4, 0, 4] + 0.029471162073 # B[15, 4, 1, 5] + 0.054901130330 # B[16, 4, 2, 4] + 0.010910192753 # B[17, 4, 2, 6] + 0.033885210622 # B[18, 4, 3, 5] + 0.008053439551 # B[19, 4, 3, 7] + -0.001432298168 # B[20, 4, 4, 4] + 0.017478027729 # B[21, 4, 4, 6] + -0.003402034990 # B[22, 4, 4, 8] + -0.002655339820 # B[23, 5, 0, 5] + 0.012668749892 # B[24, 5, 1, 6] + 0.037521561888 # B[25, 5, 2, 5] + -0.000682693314 # B[26, 5, 2, 7] + 0.008525913627 # B[27, 5, 3, 6] + 0.008977936348 # B[28, 5, 3, 8] + 0.006922732235 # B[29, 5, 4, 5] + 0.003031883044 # B[30, 5, 4, 7] + -0.000345577975 # B[31, 5, 5, 6] + -0.001041600679 # B[32, 5, 5, 8] + -0.001407625493 # B[33, 6, 0, 6] + 0.004211558640 # B[34, 6, 1, 7] + 0.014450875461 # B[35, 6, 2, 6] + -0.007033326252 # B[36, 6, 2, 8] + 0.004998742185 # B[37, 6, 3, 7] + -0.002824617682 # B[38, 6, 4, 6] + 0.003831871934 # B[39, 6, 4, 8] + -0.005700892700 # B[40, 6, 5, 7] + 0.000184422409 # B[41, 6, 6, 6] + 0.001592696824 # B[42, 6, 6, 8] + -0.000804927645 # B[43, 7, 0, 7] + 0.008465358642 # B[44, 7, 1, 8] + 0.005460531160 # B[45, 7, 2, 7] + -0.000639605094 # B[46, 7, 3, 8] + -0.002403948393 # B[47, 7, 4, 7] + -0.001267042453 # B[48, 7, 5, 8] + 0.003836940623 # B[49, 7, 6, 7] + 0.002333141437 # B[50, 7, 7, 8] + -0.000665360637 # B[51, 8, 0, 8] + -0.003460637865 # B[52, 8, 2, 8] + -0.001598726043 # B[53, 8, 4, 8] + 0.001478744304 # B[54, 8, 6, 8] + 0.000806643203 # B[55, 8, 8, 8] diff --git a/potentials/WBe_Wood_PRB2019.snapparam b/potentials/WBe_Wood_PRB2019.snapparam new file mode 100644 index 0000000000..e4fc4b4459 --- /dev/null +++ b/potentials/WBe_Wood_PRB2019.snapparam @@ -0,0 +1,11 @@ +# required +rcutfac 4.8123 +twojmax 8 + +# optional + +rfac0 0.99363 +rmin0 0 +bzeroflag 1 +quadraticflag 0 + From 5dba4b66c8964a362d7944e461eda820743ba605 Mon Sep 17 00:00:00 2001 From: Axel Kohlmeyer Date: Wed, 18 Sep 2019 16:49:48 -0400 Subject: [PATCH 159/192] add warning banner to the LAMMPS output and refer to the C++11 issue on github --- doc/src/Build_settings.txt | 2 +- src/lammps.cpp | 13 +++++++++++++ 2 files changed, 14 insertions(+), 1 deletion(-) diff --git a/doc/src/Build_settings.txt b/doc/src/Build_settings.txt index baff537e3b..c40a91d781 100644 --- a/doc/src/Build_settings.txt +++ b/doc/src/Build_settings.txt @@ -24,7 +24,7 @@ explain how to do this for building both with CMake and make. :line -C++11 standard compliance test :h4(cxx11) +C++11 standard compliance test :h4,link(cxx11) The LAMMPS developers plan to transition to make the C++11 standard the minimum requirement for compiling LAMMPS. Currently this only applies to diff --git a/src/lammps.cpp b/src/lammps.cpp index 5ddc1600a4..d58c04e998 100644 --- a/src/lammps.cpp +++ b/src/lammps.cpp @@ -444,6 +444,19 @@ LAMMPS::LAMMPS(int narg, char **arg, MPI_Comm communicator) : if ((universe->me == 0) && !helpflag) { if (screen) fprintf(screen,"LAMMPS (%s)\n",universe->version); if (logfile) fprintf(logfile,"LAMMPS (%s)\n",universe->version); +#if defined(LAMMPS_CXX98) + const char warning[] = "\nWARNING-WARNING-WARNING-WARNING-WARNING\n" + "This LAMMPS executable was compiled using C++98 compatibility.\n" + "Please report the compiler info below at https://github.com/lammps/lammps/issues/1659\n"; + const char *infobuf = Info::get_compiler_info(); + if (screen) + fprintf(screen,"%s%s\nWARNING-WARNING-WARNING-WARNING-WARNING\n\n", + warning,infobuf); + if (logfile) + fprintf(logfile,"%s%s\nWARNING-WARNING-WARNING-WARNING-WARNING\n\n", + warning,infobuf); + delete[] infobuf; +#endif } // universe is one or more worlds, as setup by partition switch From b049b59015d12a7f45239cf814145698c97c04f9 Mon Sep 17 00:00:00 2001 From: "tanmoy.7989" Date: Thu, 19 Sep 2019 00:25:22 -0700 Subject: [PATCH 160/192] revised documentation and added a citation trigger in .cpp file --- doc/src/pair_local_density.txt | 2 +- src/USER-MISC/pair_local_density.cpp | 21 +++++++++++++++++++++ 2 files changed, 22 insertions(+), 1 deletion(-) diff --git a/doc/src/pair_local_density.txt b/doc/src/pair_local_density.txt index 8703bf11ff..4def63c5fc 100644 --- a/doc/src/pair_local_density.txt +++ b/doc/src/pair_local_density.txt @@ -24,7 +24,7 @@ pair_coeff * * local/density benzene_water.localdensity.table :pre [Description:] -The local density (LD) potential is a new potential style that is, in some +The local density (LD) potential is a mean-field manybody potential, and, in some sense,a generalization of embedded atom models (EAM). The name "local density potential" arises from the fact that it assigns an energy to an atom depending on the number of neighboring atoms of given type around it within a predefined diff --git a/src/USER-MISC/pair_local_density.cpp b/src/USER-MISC/pair_local_density.cpp index 883075c80e..9057b061b0 100644 --- a/src/USER-MISC/pair_local_density.cpp +++ b/src/USER-MISC/pair_local_density.cpp @@ -32,11 +32,29 @@ #include "memory.h" #include "error.h" #include "domain.h" +#include "citeme.h" using namespace LAMMPS_NS; #define MAXLINE 1024 +static const char cite_pair_local_density[] = + "pair_style local/density command:\n\n" + "@Article{Sanyal16,\n" + " author = {T.Sanyal and M.Scott Shell},\n" + " title = {Coarse-grained models using local-density potentials optimized with the relative entropy: Application to implicit solvation},\n" + " journal = {J.~Chem.~Phys.},\n" + " year = 2016,\n" + " DOI = doi.org/10.1063/1.4958629" + "}\n\n" + "@Article{Sanyal18,\n" + " author = {T.Sanyal and M.Scott Shell},\n" + " title = {Transferable coarse-grained models of liquid-liquid equilibrium using local density potentials optimized with the relative entropy},\n" + " journal = {J.~Phys.~Chem. B},\n" + " year = 2018,\n" + " DOI = doi.org/10.1021/acs.jpcb.7b12446" + "}\n\n"; + /* ---------------------------------------------------------------------- */ PairLocalDensity::PairLocalDensity(LAMMPS *lmp) : Pair(lmp) @@ -74,6 +92,9 @@ PairLocalDensity::PairLocalDensity(LAMMPS *lmp) : Pair(lmp) // set comm size needed by this pair comm_forward = 1; comm_reverse = 1; + + // cite publication + if (lmp->citeme) lmp->citeme->add(cite_pair_local_density); } /* ---------------------------------------------------------------------- From c26c8aca4fd953c74bf1621f4362c03936b6f898 Mon Sep 17 00:00:00 2001 From: Axel Kohlmeyer Date: Thu, 19 Sep 2019 07:34:27 -0400 Subject: [PATCH 161/192] get rid of (evil) tabs and trailing whitespace in bundled Pizza.py components --- tools/python/pizza/cfg.py | 70 +++++++-------- tools/python/pizza/dump.py | 160 +++++++++++++++++----------------- tools/python/pizza/gnu.py | 66 +++++++------- tools/python/pizza/log.py | 46 +++++----- tools/python/pizza/pdbfile.py | 28 +++--- tools/python/pizza/xyz.py | 24 ++--- 6 files changed, 197 insertions(+), 197 deletions(-) diff --git a/tools/python/pizza/cfg.py b/tools/python/pizza/cfg.py index 8cefd38acd..bbd930ea3c 100644 --- a/tools/python/pizza/cfg.py +++ b/tools/python/pizza/cfg.py @@ -3,7 +3,7 @@ # # Copyright (2005) Sandia Corporation. Under the terms of Contract # DE-AC04-94AL85000 with Sandia Corporation, the U.S. Government retains -# certain rights in this software. This software is distributed under +# certain rights in this software. This software is distributed under # the GNU General Public License. # cfg tool @@ -11,14 +11,14 @@ oneline = "Convert LAMMPS snapshots to AtomEye CFG format" docstr = """ -c = cfg(d) d = object containing atom coords (dump, data) +c = cfg(d) d = object containing atom coords (dump, data) c.one() write all snapshots to tmp.cfg c.one("new") write all snapshots to new.cfg c.many() write snapshots to tmp0000.cfg, tmp0001.cfg, etc c.many("new") write snapshots to new0000.cfg, new0001.cfg, etc -c.single(N) write snapshot for timestep N to tmp.cfg -c.single(N,"file") write snapshot for timestep N to file.cfg +c.single(N) write snapshot for timestep N to tmp.cfg +c.single(N,"file") write snapshot for timestep N to file.cfg """ # History @@ -46,7 +46,7 @@ class cfg: def __init__(self,data): self.data = data - + # -------------------------------------------------------------------- def one(self,*args): @@ -68,16 +68,16 @@ class cfg: print >>f,"Number of particles = %d " % len(atoms) print >>f,"# Timestep %d \n#\nA = 1.0 Angstrom" % time print >>f,"H0(1,1) = %20.10f A " % xlen - print >>f,"H0(1,2) = 0.0 A " - print >>f,"H0(1,3) = 0.0 A " - print >>f,"H0(2,1) = 0.0 A " + print >>f,"H0(1,2) = 0.0 A " + print >>f,"H0(1,3) = 0.0 A " + print >>f,"H0(2,1) = 0.0 A " print >>f,"H0(2,2) = %20.10f A " % ylen - print >>f,"H0(2,3) = 0.0 A " - print >>f,"H0(3,1) = 0.0 A " - print >>f,"H0(3,2) = 0.0 A " + print >>f,"H0(2,3) = 0.0 A " + print >>f,"H0(3,1) = 0.0 A " + print >>f,"H0(3,2) = 0.0 A " print >>f,"H0(3,3) = %20.10f A " % zlen print >>f,"#" - + for atom in atoms: itype = int(atom[1]) xfrac = (atom[2]-box[0])/xlen @@ -85,14 +85,14 @@ class cfg: zfrac = (atom[4]-box[2])/zlen # print >>f,"1.0 %d %15.10f %15.10f %15.10f %15.10f %15.10f %15.10f " % (itype,xfrac,yfrac,zfrac,atom[5],atom[6],atom[7]) print >>f,"1.0 %d %15.10f %15.10f %15.10f 0.0 0.0 0.0 " % (itype,xfrac,yfrac,zfrac) - + print time, sys.stdout.flush() n += 1 - + f.close() print "\nwrote %d snapshots to %s in CFG format" % (n,file) - + # -------------------------------------------------------------------- def many(self,*args): @@ -104,7 +104,7 @@ class cfg: which,time,flag = self.data.iterator(flag) if flag == -1: break time,box,atoms,bonds,tris,lines = self.data.viz(which) - + if n < 10: file = root + "000" + str(n) elif n < 100: @@ -112,7 +112,7 @@ class cfg: elif n < 1000: file = root + "0" + str(n) else: - file = root + str(n) + file = root + str(n) file += ".cfg" f = open(file,"w") @@ -123,16 +123,16 @@ class cfg: print >>f,"Number of particles = %d " % len(atoms) print >>f,"# Timestep %d \n#\nA = 1.0 Angstrom" % time print >>f,"H0(1,1) = %20.10f A " % xlen - print >>f,"H0(1,2) = 0.0 A " - print >>f,"H0(1,3) = 0.0 A " - print >>f,"H0(2,1) = 0.0 A " + print >>f,"H0(1,2) = 0.0 A " + print >>f,"H0(1,3) = 0.0 A " + print >>f,"H0(2,1) = 0.0 A " print >>f,"H0(2,2) = %20.10f A " % ylen - print >>f,"H0(2,3) = 0.0 A " - print >>f,"H0(3,1) = 0.0 A " - print >>f,"H0(3,2) = 0.0 A " + print >>f,"H0(2,3) = 0.0 A " + print >>f,"H0(3,1) = 0.0 A " + print >>f,"H0(3,2) = 0.0 A " print >>f,"H0(3,3) = %20.10f A " % zlen print >>f,"#" - + for atom in atoms: itype = int(atom[1]) xfrac = (atom[2]-box[0])/xlen @@ -140,14 +140,14 @@ class cfg: zfrac = (atom[4]-box[2])/zlen # print >>f,"1.0 %d %15.10f %15.10f %15.10f %15.10f %15.10f %15.10f " % (itype,xfrac,yfrac,zfrac,atom[5],atom[6],atom[7]) print >>f,"1.0 %d %15.10f %15.10f %15.10f 0.0 0.0 0.0 " % (itype,xfrac,yfrac,zfrac) - + print time, sys.stdout.flush() f.close() n += 1 - + print "\nwrote %s snapshots in CFG format" % n - + # -------------------------------------------------------------------- def single(self,time,*args): @@ -166,16 +166,16 @@ class cfg: print >>f,"Number of particles = %d " % len(atoms) print >>f,"# Timestep %d \n#\nA = 1.0 Angstrom" % time print >>f,"H0(1,1) = %20.10f A " % xlen - print >>f,"H0(1,2) = 0.0 A " - print >>f,"H0(1,3) = 0.0 A " - print >>f,"H0(2,1) = 0.0 A " + print >>f,"H0(1,2) = 0.0 A " + print >>f,"H0(1,3) = 0.0 A " + print >>f,"H0(2,1) = 0.0 A " print >>f,"H0(2,2) = %20.10f A " % ylen - print >>f,"H0(2,3) = 0.0 A " - print >>f,"H0(3,1) = 0.0 A " - print >>f,"H0(3,2) = 0.0 A " + print >>f,"H0(2,3) = 0.0 A " + print >>f,"H0(3,1) = 0.0 A " + print >>f,"H0(3,2) = 0.0 A " print >>f,"H0(3,3) = %20.10f A " % zlen print >>f,"#" - + for atom in atoms: itype = int(atom[1]) xfrac = (atom[2]-box[0])/xlen @@ -183,5 +183,5 @@ class cfg: zfrac = (atom[4]-box[2])/zlen # print >>f,"1.0 %d %15.10f %15.10f %15.10f %15.10f %15.10f %15.10f " % (itype,xfrac,yfrac,zfrac,atom[5],atom[6],atom[7]) print >>f,"1.0 %d %15.10f %15.10f %15.10f 0.0 0.0 0.0 " % (itype,xfrac,yfrac,zfrac) - + f.close() diff --git a/tools/python/pizza/dump.py b/tools/python/pizza/dump.py index 8098a2c4b7..1c6eb5edfd 100644 --- a/tools/python/pizza/dump.py +++ b/tools/python/pizza/dump.py @@ -3,7 +3,7 @@ # # Copyright (2005) Sandia Corporation. Under the terms of Contract # DE-AC04-94AL85000 with Sandia Corporation, the U.S. Government retains -# certain rights in this software. This software is distributed under +# certain rights in this software. This software is distributed under # the GNU General Public License. # dump tool @@ -12,15 +12,15 @@ oneline = "Read, write, manipulate dump files and particle attributes" docstr = """ d = dump("dump.one") read in one or more dump files -d = dump("dump.1 dump.2.gz") can be gzipped -d = dump("dump.*") wildcard expands to multiple files -d = dump("dump.*",0) two args = store filenames, but don't read +d = dump("dump.1 dump.2.gz") can be gzipped +d = dump("dump.*") wildcard expands to multiple files +d = dump("dump.*",0) two args = store filenames, but don't read incomplete and duplicate snapshots are deleted atoms will be unscaled if stored in files as scaled - self-describing column names assigned + self-describing column names assigned -time = d.next() read next snapshot from dump files +time = d.next() read next snapshot from dump files used with 2-argument constructor to allow reading snapshots one-at-a-time snapshot will be skipped only if another snapshot has same time stamp @@ -31,21 +31,21 @@ time = d.next() read next snapshot from dump files d.map(1,"id",3,"x") assign names to columns (1-N) not needed if dump file is self-describing - -d.tselect.all() select all timesteps -d.tselect.one(N) select only timestep N -d.tselect.none() deselect all timesteps -d.tselect.skip(M) select every Mth step + +d.tselect.all() select all timesteps +d.tselect.one(N) select only timestep N +d.tselect.none() deselect all timesteps +d.tselect.skip(M) select every Mth step d.tselect.test("$t >= 100 and $t < 10000") select matching timesteps -d.delete() delete non-selected timesteps +d.delete() delete non-selected timesteps selecting a timestep also selects all atoms in the timestep skip() and test() only select from currently selected timesteps test() uses a Python Boolean expression with $t for timestep value Python comparison syntax: == != < > <= >= and or -d.aselect.all() select all atoms in all steps -d.aselect.all(N) select all atoms in one step +d.aselect.all() select all atoms in all steps +d.aselect.all(N) select all atoms in one step d.aselect.test("$id > 100 and $type == 2") select match atoms in all steps d.aselect.test("$id > 100 and $type == 2",N) select matching atoms in one step @@ -56,24 +56,24 @@ d.aselect.test("$id > 100 and $type == 2",N) select matching atoms in one step Python comparison syntax: == != < > <= >= and or $name must end with a space -d.write("file") write selected steps/atoms to dump file -d.write("file",head,app) write selected steps/atoms to dump file -d.scatter("tmp") write selected steps/atoms to multiple files +d.write("file") write selected steps/atoms to dump file +d.write("file",head,app) write selected steps/atoms to dump file +d.scatter("tmp") write selected steps/atoms to multiple files write() can be specified with 2 additional flags head = 0/1 for no/yes snapshot header, app = 0/1 for write vs append scatter() files are given timestep suffix: e.g. tmp.0, tmp.100, etc -d.scale() scale x,y,z to 0-1 for all timesteps -d.scale(100) scale atom coords for timestep N -d.unscale() unscale x,y,z to box size to all timesteps -d.unscale(1000) unscale atom coords for timestep N -d.wrap() wrap x,y,z into periodic box via ix,iy,iz -d.unwrap() unwrap x,y,z out of box via ix,iy,iz -d.owrap("other") wrap x,y,z to same image as another atom -d.sort() sort atoms by atom ID in all selected steps -d.sort("x") sort atoms by column value in all steps -d.sort(1000) sort atoms in timestep N +d.scale() scale x,y,z to 0-1 for all timesteps +d.scale(100) scale atom coords for timestep N +d.unscale() unscale x,y,z to box size to all timesteps +d.unscale(1000) unscale atom coords for timestep N +d.wrap() wrap x,y,z into periodic box via ix,iy,iz +d.unwrap() unwrap x,y,z out of box via ix,iy,iz +d.owrap("other") wrap x,y,z to same image as another atom +d.sort() sort atoms by atom ID in all selected steps +d.sort("x") sort atoms by column value in all steps +d.sort(1000) sort atoms in timestep N scale(), unscale(), wrap(), unwrap(), owrap() operate on all steps and atoms wrap(), unwrap(), owrap() require ix,iy,iz be defined @@ -85,8 +85,8 @@ d.sort(1000) sort atoms in timestep N m1,m2 = d.minmax("type") find min/max values for a column d.set("$ke = $vx * $vx + $vy * $vy") set a column to a computed value d.setv("type",vector) set a column to a vector of values -d.spread("ke",N,"color") 2nd col = N ints spread over 1st col -d.clone(1000,"color") clone timestep N values to other steps +d.spread("ke",N,"color") 2nd col = N ints spread over 1st col +d.clone(1000,"color") clone timestep N values to other steps minmax() operates on selected timesteps and atoms set() operates on selected timesteps and atoms @@ -107,17 +107,17 @@ d.clone(1000,"color") clone timestep N values to other steps values at every timestep are set to value at timestep N for that atom ID useful for propagating a color map -t = d.time() return vector of selected timestep values +t = d.time() return vector of selected timestep values fx,fy,... = d.atom(100,"fx","fy",...) return vector(s) for atom ID N fx,fy,... = d.vecs(1000,"fx","fy",...) return vector(s) for timestep N atom() returns vectors with one value for each selected timestep vecs() returns vectors with one value for each selected atom in the timestep -index,time,flag = d.iterator(0/1) loop over dump snapshots +index,time,flag = d.iterator(0/1) loop over dump snapshots time,box,atoms,bonds,tris,lines = d.viz(index) return list of viz objects -d.atype = "color" set column returned as "type" by viz -d.extra(obj) extract bond/tri/line info from obj +d.atype = "color" set column returned as "type" by viz +d.extra(obj) extract bond/tri/line info from obj iterator() loops over selected timesteps iterator() called with arg = 0 first time, with arg = 1 on subsequent calls @@ -137,7 +137,7 @@ d.extra(obj) extract bond/tri/line info from obj if extra() used to define lines, else NULL atype is column name viz() will return as atom type (def = "type") extra() extracts bonds/tris/lines from obj each time viz() is called - obj can be data object for bonds, cdata object for tris and lines, + obj can be data object for bonds, cdata object for tris and lines, bdump object for bonds, tdump object for tris, ldump object for lines. mdump object for tris """ @@ -227,7 +227,7 @@ class dump: for word in words: self.flist += glob.glob(word) if len(self.flist) == 0 and len(list) == 1: raise StandardError,"no dump file specified" - + if len(list) == 1: self.increment = 0 self.read_all() @@ -270,7 +270,7 @@ class dump: self.tselect.all() # print column assignments - + if len(self.names): print "assigned columns:",self.names2str() else: @@ -304,15 +304,15 @@ class dump: snap = self.read_snapshot(f) if not snap: self.nextfile += 1 - if self.nextfile == len(self.flist): return -1 + if self.nextfile == len(self.flist): return -1 f.close() - self.eof = 0 - continue + self.eof = 0 + continue self.eof = f.tell() f.close() try: self.findtime(snap.time) - continue + continue except: break # select the new snapshot with all its atoms @@ -334,7 +334,7 @@ class dump: # assign column names (file must be self-describing) # set scale_original to 0/1/-1 for unscaled/scaled/unknown # convert xs,xu to x in names - + def read_snapshot(self,f): try: snap = Snap() @@ -351,7 +351,7 @@ class dump: else: snap.boxstr = words[1].strip() if "xy" in snap.boxstr: snap.triclinic = 1 else: snap.triclinic = 0 - + words = f.readline().split() if len(words) == 2: snap.xlo,snap.xhi,snap.xy = float(words[0]),float(words[1]),0.0 @@ -372,7 +372,7 @@ class dump: else: snap.zlo,snap.zhi,snap.yz = \ float(words[0]),float(words[1]),float(words[2]) - + item = f.readline() if len(self.names) == 0: self.scale_original = -1 @@ -401,7 +401,7 @@ class dump: else: self.names[words[i]] = i if xflag == 0 and yflag == 0 and zflag == 0: self.scale_original = 0 if xflag == 1 and yflag == 1 and zflag == 1: self.scale_original = 1 - + if snap.natoms: words = f.readline().split() ncol = len(words) @@ -424,7 +424,7 @@ class dump: # -------------------------------------------------------------------- # map atom column names - + def map(self,*pairs): if len(pairs) % 2 != 0: raise StandardError, "dump map() requires pairs of mappings" @@ -509,7 +509,7 @@ class dump: atoms[:,y] = (atoms[:,y] - snap.ylo)*h1inv + \ (atoms[:,z] - snap.zlo)*h3inv atoms[:,z] = (atoms[:,z] - snap.zlo)*h2inv - + # -------------------------------------------------------------------- # unscale coords from 0-1 to box size for all snapshots or just one # use 6 params as h-matrix to treat orthogonal or triclinic boxes @@ -564,7 +564,7 @@ class dump: atoms[:,x] = snap.xlo + atoms[:,x]*h0 + atoms[:,y]*h5 + atoms[:,z]*h4 atoms[:,y] = snap.ylo + atoms[:,y]*h1 + atoms[:,z]*h3 atoms[:,z] = snap.zlo + atoms[:,z]*h2 - + # -------------------------------------------------------------------- # wrap coords from outside box to inside @@ -577,7 +577,7 @@ class dump: ix = self.names["ix"] iy = self.names["iy"] iz = self.names["iz"] - + for snap in self.snaps: xprd = snap.xhi - snap.xlo yprd = snap.yhi - snap.ylo @@ -599,7 +599,7 @@ class dump: ix = self.names["ix"] iy = self.names["iy"] iz = self.names["iz"] - + for snap in self.snaps: xprd = snap.xhi - snap.xlo yprd = snap.yhi - snap.ylo @@ -612,10 +612,10 @@ class dump: # -------------------------------------------------------------------- # wrap coords to same image as atom ID stored in "other" column # if dynamic extra lines or triangles defined, owrap them as well - + def owrap(self,other): print "Wrapping to other ..." - + id = self.names["id"] x = self.names["x"] y = self.names["y"] @@ -641,10 +641,10 @@ class dump: # should bonds also be owrapped ? if self.lineflag == 2 or self.triflag == 2: self.objextra.owrap(snap.time,xprd,yprd,zprd,ids,atoms,iother,ix,iy,iz) - + # -------------------------------------------------------------------- # convert column names assignment to a string, in column order - + def names2str(self): pairs = self.names.items() values = self.names.values() @@ -697,7 +697,7 @@ class dump: else: id = -1 if "type" in self.names: type = self.names["type"] else: type = -1 - + for snap in self.snaps: if not snap.tselect: continue print snap.time, @@ -719,7 +719,7 @@ class dump: print >>f,snap.ylo,snap.yhi print >>f,snap.zlo,snap.zhi print >>f,"ITEM: ATOMS",namestr - + atoms = snap.atoms nvalues = len(atoms[0]) for i in xrange(snap.natoms): @@ -743,7 +743,7 @@ class dump: if not snap.tselect: continue print snap.time, sys.stdout.flush() - + file = root + "." + str(snap.time) f = open(file,"w") print >>f,"ITEM: TIMESTEP" @@ -761,7 +761,7 @@ class dump: print >>f,snap.ylo,snap.yhi print >>f,snap.zlo,snap.zhi print >>f,"ITEM: ATOMS",namestr - + atoms = snap.atoms nvalues = len(atoms[0]) for i in xrange(snap.natoms): @@ -803,7 +803,7 @@ class dump: lhs = list[0][1:] if not self.names.has_key(lhs): self.newcolumn(lhs) - + for item in list: name = item[1:] column = self.names[name] @@ -815,7 +815,7 @@ class dump: if not snap.tselect: continue for i in xrange(snap.natoms): if snap.aselect[i]: exec ceq - + # -------------------------------------------------------------------- # set a column value via an input vec for all selected snapshots/atoms @@ -835,7 +835,7 @@ class dump: if snap.aselect[i]: atoms[i][icol] = vec[m] m += 1 - + # -------------------------------------------------------------------- # clone value in col across selected timesteps for atoms with same ID @@ -901,7 +901,7 @@ class dump: columns.append(self.names[name]) values.append(self.nselect * [0]) ncol = len(columns) - + id = self.names["id"] m = 0 for snap in self.snaps: @@ -917,13 +917,13 @@ class dump: if len(list) == 1: return values[0] else: return values - + # -------------------------------------------------------------------- # extract vector(s) of values for selected atoms at chosen timestep def vecs(self,n,*list): snap = self.snaps[self.findtime(n)] - + if len(list) == 0: raise StandardError, "no columns specified" columns = [] @@ -978,7 +978,7 @@ class dump: del self.snaps[i] else: i += 1 - + # -------------------------------------------------------------------- # iterate over selected snapshots @@ -990,12 +990,12 @@ class dump: self.iterate = i return i,self.snaps[i].time,1 return 0,0,-1 - + # -------------------------------------------------------------------- # return list of atoms to viz for snapshot isnap # if called with flag, then index is timestep, so convert to snapshot index # augment with bonds, tris, lines if extra() was invoked - + def viz(self,index,flag=0): if not flag: isnap = index else: @@ -1019,7 +1019,7 @@ class dump: # create atom list needed by viz from id,type,x,y,z # need Numeric/Numpy mode here - + atoms = [] for i in xrange(snap.natoms): if not snap.aselect[i]: continue @@ -1059,7 +1059,7 @@ class dump: if self.triflag == 1: tris = self.trilist elif self.triflag == 2: tmp1,tmp2,tmp3,tmp4,tris,tmp5 = self.objextra.viz(time,1) - + # create list of lines from static or dynamic tri list # if dynamic, could eliminate lines for unselected atoms @@ -1070,7 +1070,7 @@ class dump: tmp1,tmp2,tmp3,tmp4,tmp5,lines = self.objextra.viz(time,1) return time,box,atoms,bonds,tris,lines - + # -------------------------------------------------------------------- def findtime(self,n): @@ -1115,7 +1115,7 @@ class dump: def extra(self,arg): # data object, grab bonds statically - + if type(arg) is types.InstanceType and ".data" in str(arg.__class__): self.bondflag = 0 try: @@ -1132,7 +1132,7 @@ class dump: raise StandardError,"could not extract bonds from data object" # cdata object, grab tris and lines statically - + elif type(arg) is types.InstanceType and ".cdata" in str(arg.__class__): self.triflag = self.lineflag = 0 try: @@ -1147,32 +1147,32 @@ class dump: raise StandardError,"could not extract tris/lines from cdata object" # mdump object, grab tris dynamically - + elif type(arg) is types.InstanceType and ".mdump" in str(arg.__class__): self.triflag = 2 self.objextra = arg # bdump object, grab bonds dynamically - + elif type(arg) is types.InstanceType and ".bdump" in str(arg.__class__): self.bondflag = 2 self.objextra = arg # ldump object, grab lines dynamically - + elif type(arg) is types.InstanceType and ".ldump" in str(arg.__class__): self.lineflag = 2 self.objextra = arg # tdump object, grab tris dynamically - + elif type(arg) is types.InstanceType and ".tdump" in str(arg.__class__): self.triflag = 2 self.objextra = arg else: raise StandardError,"unrecognized argument to dump.extra()" - + # -------------------------------------------------------------------- def compare_atom(self,a,b): @@ -1181,7 +1181,7 @@ class dump: elif a[0] > b[0]: return 1 else: - return 0 + return 0 # -------------------------------------------------------------------- # one snapshot @@ -1196,7 +1196,7 @@ class tselect: def __init__(self,data): self.data = data - + # -------------------------------------------------------------------- def all(self): @@ -1243,7 +1243,7 @@ class tselect: data.nselect -= 1 data.aselect.all() print "%d snapshots selected out of %d" % (data.nselect,data.nsnaps) - + # -------------------------------------------------------------------- def test(self,teststr): @@ -1289,7 +1289,7 @@ class aselect: data = self.data # replace all $var with snap.atoms references and compile test string - + pattern = "\$\w*" list = re.findall(pattern,teststr) for item in list: diff --git a/tools/python/pizza/gnu.py b/tools/python/pizza/gnu.py index f6f0167330..d99ab3811d 100644 --- a/tools/python/pizza/gnu.py +++ b/tools/python/pizza/gnu.py @@ -3,7 +3,7 @@ # # Copyright (2005) Sandia Corporation. Under the terms of Contract # DE-AC04-94AL85000 with Sandia Corporation, the U.S. Government retains -# certain rights in this software. This software is distributed under +# certain rights in this software. This software is distributed under # the GNU General Public License. # gnu tool @@ -11,12 +11,12 @@ oneline = "Create plots via GnuPlot plotting program" docstr = """ -g = gnu() start up GnuPlot -g.stop() shut down GnuPlot process - +g = gnu() start up GnuPlot +g.stop() shut down GnuPlot process + g.plot(a) plot vector A against linear index -g.plot(a,b) plot B against A -g.plot(a,b,c,d,...) plot B against A, D against C, etc +g.plot(a,b) plot B against A +g.plot(a,b,c,d,...) plot B against A, D against C, etc g.mplot(M,N,S,"file",a,b,...) multiple plots saved to file0000.eps, etc each plot argument can be a tuple, list, or Numeric/NumPy vector @@ -29,21 +29,21 @@ g.mplot(M,N,S,"file",a,b,...) multiple plots saved to file0000.eps, etc g("plot 'file.dat' using 2:3 with lines") execute string in GnuPlot -g.enter() enter GnuPlot shell +g.enter() enter GnuPlot shell gnuplot> plot sin(x) with lines type commands directly to GnuPlot -gnuplot> exit, quit exit GnuPlot shell - +gnuplot> exit, quit exit GnuPlot shell + g.export("data",range(100),a,...) create file with columns of numbers all vectors must be of equal length could plot from file with GnuPlot command: plot 'data' using 1:2 with lines -g.select(N) figure N becomes the current plot - +g.select(N) figure N becomes the current plot + subsequent commands apply to this plot -g.hide(N) delete window for figure N -g.save("file") save current plot as file.eps +g.hide(N) delete window for figure N +g.save("file") save current plot as file.eps Set attributes for current plot: @@ -94,7 +94,7 @@ except: PIZZA_GNUTERM = "x11" # Class definition class gnu: - + # -------------------------------------------------------------------- def __init__(self): @@ -102,7 +102,7 @@ class gnu: self.file = "tmp.gnu" self.figures = [] self.select(1) - + # -------------------------------------------------------------------- def stop(self): @@ -114,7 +114,7 @@ class gnu: def __call__(self,command): self.GNUPLOT.write(command + '\n') self.GNUPLOT.flush() - + # -------------------------------------------------------------------- def enter(self): @@ -152,7 +152,7 @@ class gnu: if i: partial_vecs.append(vec[:i]) else: partial_vecs.append([0]) self.plot(*partial_vecs) - + if n < 10: newfile = file + "000" + str(n) elif n < 100: newfile = file + "00" + str(n) elif n < 1000: newfile = file + "0" + str(n) @@ -160,7 +160,7 @@ class gnu: self.save(newfile) n += 1 - + # -------------------------------------------------------------------- # write list of equal-length vectors to filename @@ -201,7 +201,7 @@ class gnu: # do not continue until plot file is written out # else script could go forward and change data file # use tmp.done as semaphore to indicate plot is finished - + def save(self,file): self.__call__("set terminal postscript enhanced solid lw 2 color portrait") cmd = "set output '%s.eps'" % file @@ -212,7 +212,7 @@ class gnu: while not os.path.exists("tmp.done"): continue self.__call__("set output") self.select(self.current) - + # -------------------------------------------------------------------- # restore default attributes by creating a new fig object @@ -221,7 +221,7 @@ class gnu: fig.ncurves = self.figures[self.current-1].ncurves self.figures[self.current-1] = fig self.draw() - + # -------------------------------------------------------------------- def aspect(self,value): @@ -245,12 +245,12 @@ class gnu: else: self.figures[self.current-1].ylimit = (values[0],values[1]) self.draw() - + # -------------------------------------------------------------------- def label(self,x,y,text): self.figures[self.current-1].labels.append((x,y,text)) - self.figures[self.current-1].nlabels += 1 + self.figures[self.current-1].nlabels += 1 self.draw() # -------------------------------------------------------------------- @@ -259,7 +259,7 @@ class gnu: self.figures[self.current-1].nlabel = 0 self.figures[self.current-1].labels = [] self.draw() - + # -------------------------------------------------------------------- def title(self,*strings): @@ -276,13 +276,13 @@ class gnu: def xtitle(self,label): self.figures[self.current-1].xtitle = label self.draw() - + # -------------------------------------------------------------------- def ytitle(self,label): self.figures[self.current-1].ytitle = label self.draw() - + # -------------------------------------------------------------------- def xlog(self): @@ -291,7 +291,7 @@ class gnu: else: self.figures[self.current-1].xlog = 1 self.draw() - + # -------------------------------------------------------------------- def ylog(self): @@ -300,7 +300,7 @@ class gnu: else: self.figures[self.current-1].ylog = 1 self.draw() - + # -------------------------------------------------------------------- def curve(self,num,color): @@ -316,10 +316,10 @@ class gnu: def draw(self): fig = self.figures[self.current-1] if not fig.ncurves: return - + cmd = 'set size ratio ' + str(1.0/float(fig.aspect)) self.__call__(cmd) - + cmd = 'set title ' + '"' + fig.title + '"' self.__call__(cmd) cmd = 'set xlabel ' + '"' + fig.xtitle + '"' @@ -331,11 +331,11 @@ class gnu: else: self.__call__("unset logscale x") if fig.ylog: self.__call__("set logscale y") else: self.__call__("unset logscale y") - if fig.xlimit: + if fig.xlimit: cmd = 'set xr [' + str(fig.xlimit[0]) + ':' + str(fig.xlimit[1]) + ']' self.__call__(cmd) else: self.__call__("set xr [*:*]") - if fig.ylimit: + if fig.ylimit: cmd = 'set yr [' + str(fig.ylimit[0]) + ':' + str(fig.ylimit[1]) + ']' self.__call__(cmd) else: self.__call__("set yr [*:*]") @@ -365,7 +365,7 @@ class figure: def __init__(self): self.ncurves = 0 - self.colors = [] + self.colors = [] self.title = "" self.xtitle = "" self.ytitle = "" diff --git a/tools/python/pizza/log.py b/tools/python/pizza/log.py index aeca1d8d82..a255af2030 100644 --- a/tools/python/pizza/log.py +++ b/tools/python/pizza/log.py @@ -3,7 +3,7 @@ # # Copyright (2005) Sandia Corporation. Under the terms of Contract # DE-AC04-94AL85000 with Sandia Corporation, the U.S. Government retains -# certain rights in this software. This software is distributed under +# certain rights in this software. This software is distributed under # the GNU General Public License. # log tool @@ -28,7 +28,7 @@ nvec = l.nvec # of vectors of thermo info nlen = l.nlen length of each vectors names = l.names list of vector names t,pe,... = l.get("Time","KE",...) return one or more vectors of values -l.write("file.txt") write all vectors to a file +l.write("file.txt") write all vectors to a file l.write("file.txt","Time","PE",...) write listed vectors to a file get and write allow abbreviated (uniquely) vector names @@ -89,7 +89,7 @@ class log: # -------------------------------------------------------------------- # read all thermo from all files - + def read_all(self): self.read_header(self.flist[0]) if self.nvec == 0: raise StandardError,"log file has no values" @@ -100,7 +100,7 @@ class log: print # sort entries by timestep, cull duplicates - + self.data.sort(self.compare) self.cull() self.nlen = len(self.data) @@ -133,9 +133,9 @@ class log: else: count = 0 for i in range(self.nvec): - if self.names[i].find(key) == 0: - count += 1 - index = i + if self.names[i].find(key) == 0: + count += 1 + index = i if count == 1: map.append(index) else: @@ -161,9 +161,9 @@ class log: else: count = 0 for i in range(self.nvec): - if self.names[i].find(key) == 0: - count += 1 - index = i + if self.names[i].find(key) == 0: + count += 1 + index = i if count == 1: map.append(index) else: @@ -226,7 +226,7 @@ class log: keywords.insert(0,"Step") i = 0 for keyword in keywords: - self.names.append(keyword) + self.names.append(keyword) self.ptr[keyword] = i i += 1 @@ -236,7 +236,7 @@ class log: line = txt[s1:s2] words = line.split() for i in range(len(words)): - self.names.append(words[i]) + self.names.append(words[i]) self.ptr[words[i]] = i self.nvec = len(self.names) @@ -275,43 +275,43 @@ class log: if s1 >= 0 and s2 >= 0 and s1 < s2: # found s1,s2 with s1 before s2 if self.style == 2: - s1 = txt.find("\n",s1) + 1 + s1 = txt.find("\n",s1) + 1 elif s1 >= 0 and s2 >= 0 and s2 < s1: # found s1,s2 with s2 before s1 s1 = 0 elif s1 == -1 and s2 >= 0: # found s2, but no s1 - last = 1 + last = 1 s1 = 0 elif s1 >= 0 and s2 == -1: # found s1, but no s2 last = 1 if self.style == 1: s2 = txt.rfind("\n--",s1) + 1 else: - s1 = txt.find("\n",s1) + 1 + s1 = txt.find("\n",s1) + 1 s2 = txt.rfind("\n",s1) + 1 - eof -= len(txt) - s2 + eof -= len(txt) - s2 elif s1 == -1 and s2 == -1: # found neither # could be end-of-file section - # or entire read was one chunk + # or entire read was one chunk if txt.find("Loop time of",start) == start: # end of file, so exit - eof -= len(txt) - start # reset eof to "Loop" - break + eof -= len(txt) - start # reset eof to "Loop" + break - last = 1 # entire read is a chunk + last = 1 # entire read is a chunk s1 = 0 if self.style == 1: s2 = txt.rfind("\n--",s1) + 1 else: s2 = txt.rfind("\n",s1) + 1 - eof -= len(txt) - s2 - if s1 == s2: break + eof -= len(txt) - s2 + if s1 == s2: break chunk = txt[s1:s2-1] start = s2 # split chunk into entries # parse each entry for numeric fields, append to data - + if self.style == 1: sections = chunk.split("\n--") pat1 = re.compile("Step\s*(\S*)\s") diff --git a/tools/python/pizza/pdbfile.py b/tools/python/pizza/pdbfile.py index 1713ada043..9b2238cbd6 100644 --- a/tools/python/pizza/pdbfile.py +++ b/tools/python/pizza/pdbfile.py @@ -3,7 +3,7 @@ # # Copyright (2005) Sandia Corporation. Under the terms of Contract # DE-AC04-94AL85000 with Sandia Corporation, the U.S. Government retains -# certain rights in this software. This software is distributed under +# certain rights in this software. This software is distributed under # the GNU General Public License. # pdb tool @@ -22,7 +22,7 @@ p = pdbfile("3CRO",d) read in single PDB file with snapshot data if only one 4-char file specified and it is not found, it will be downloaded from http://www.rcsb.org as 3CRO.pdb d arg is object with atom coordinates (dump, data) - + p.one() write all output as one big PDB file to tmp.pdb p.one("mine") write to mine.pdb p.many() write one PDB file per snapshot: tmp0000.pdb, ... @@ -36,7 +36,7 @@ p.single(N,"new") write as new.pdb if one file in str arg and d: one new PDB file per snapshot using input PDB file as template multiple input PDB files with a d is not allowed - + index,time,flag = p.iterator(0) index,time,flag = p.iterator(1) @@ -87,7 +87,7 @@ class pdbfile: # flist = full list of all PDB input file names # append .pdb if needed - + if filestr: list = filestr.split() flist = [] @@ -107,7 +107,7 @@ class pdbfile: raise StandardError, "no input PDB file(s)" # grab PDB file from http://rcsb.org if not a local file - + if len(self.files) == 1 and len(self.files[0]) == 8: try: open(self.files[0],'r').close() @@ -117,7 +117,7 @@ class pdbfile: urllib.urlretrieve(fetchstr,self.files[0]) if self.data and len(self.files): self.read_template(self.files[0]) - + # -------------------------------------------------------------------- # write a single large PDB file for concatenating all input data or files # if data exists: @@ -135,7 +135,7 @@ class pdbfile: f = open(file,'w') # use template PDB file with each snapshot - + if self.data: n = flag = 0 while 1: @@ -153,7 +153,7 @@ class pdbfile: print >>f,"END" print file, sys.stdout.flush() - + f.close() print "\nwrote %d datasets to %s in PDB format" % (n,file) @@ -189,7 +189,7 @@ class pdbfile: f = open(file,'w') self.convert(f,which) f.close() - + print time, sys.stdout.flush() n += 1 @@ -206,13 +206,13 @@ class pdbfile: else: file = root + str(n) file += ".pdb" - + f = open(file,'w') f.write(open(infile,'r').read()) f.close() print file, sys.stdout.flush() - + n += 1 print "\nwrote %d datasets to %s*.pdb in PDB format" % (n,root) @@ -239,7 +239,7 @@ class pdbfile: self.convert(f,which) else: f.write(open(self.files[time],'r').read()) - + f.close() # -------------------------------------------------------------------- @@ -258,8 +258,8 @@ class pdbfile: # -------------------------------------------------------------------- # read a PDB file and store ATOM lines - - def read_template(self,file): + + def read_template(self,file): lines = open(file,'r').readlines() self.atomlines = {} for line in lines: diff --git a/tools/python/pizza/xyz.py b/tools/python/pizza/xyz.py index 66699ab5fa..92b681540a 100644 --- a/tools/python/pizza/xyz.py +++ b/tools/python/pizza/xyz.py @@ -3,7 +3,7 @@ # # Copyright (2005) Sandia Corporation. Under the terms of Contract # DE-AC04-94AL85000 with Sandia Corporation, the U.S. Government retains -# certain rights in this software. This software is distributed under +# certain rights in this software. This software is distributed under # the GNU General Public License. # xyz tool @@ -11,14 +11,14 @@ oneline = "Convert LAMMPS snapshots to XYZ format" docstr = """ -x = xyz(d) d = object containing atom coords (dump, data) +x = xyz(d) d = object containing atom coords (dump, data) x.one() write all snapshots to tmp.xyz x.one("new") write all snapshots to new.xyz x.many() write snapshots to tmp0000.xyz, tmp0001.xyz, etc x.many("new") write snapshots to new0000.xyz, new0001.xyz, etc -x.single(N) write snapshot for timestep N to tmp.xyz -x.single(N,"file") write snapshot for timestep N to file.xyz +x.single(N) write snapshot for timestep N to tmp.xyz +x.single(N,"file") write snapshot for timestep N to file.xyz """ # History @@ -41,7 +41,7 @@ class xyz: def __init__(self,data): self.data = data - + # -------------------------------------------------------------------- def one(self,*args): @@ -61,14 +61,14 @@ class xyz: for atom in atoms: itype = int(atom[1]) print >>f,itype,atom[2],atom[3],atom[4] - + print time, sys.stdout.flush() n += 1 - + f.close() print "\nwrote %d snapshots to %s in XYZ format" % (n,file) - + # -------------------------------------------------------------------- def many(self,*args): @@ -80,7 +80,7 @@ class xyz: which,time,flag = self.data.iterator(flag) if flag == -1: break time,box,atoms,bonds,tris,lines = self.data.viz(which) - + if n < 10: file = root + "000" + str(n) elif n < 100: @@ -88,7 +88,7 @@ class xyz: elif n < 1000: file = root + "0" + str(n) else: - file = root + str(n) + file = root + str(n) file += ".xyz" f = open(file,"w") print >>f,len(atoms) @@ -100,9 +100,9 @@ class xyz: sys.stdout.flush() f.close() n += 1 - + print "\nwrote %s snapshots in XYZ format" % n - + # -------------------------------------------------------------------- def single(self,time,*args): From 5c74782c8499c975123ee70d8dc4a886537309c6 Mon Sep 17 00:00:00 2001 From: Axel Kohlmeyer Date: Thu, 19 Sep 2019 11:54:24 -0400 Subject: [PATCH 162/192] step version for next patch release --- doc/lammps.1 | 2 +- doc/src/Manual.txt | 4 ++-- src/version.h | 2 +- 3 files changed, 4 insertions(+), 4 deletions(-) diff --git a/doc/lammps.1 b/doc/lammps.1 index ac19749dd6..f332a8a549 100644 --- a/doc/lammps.1 +++ b/doc/lammps.1 @@ -1,4 +1,4 @@ -.TH LAMMPS "7 August 2019" "2019-08-07" +.TH LAMMPS "19 September 2019" "2019-09-19" .SH NAME .B LAMMPS \- Molecular Dynamics Simulator. diff --git a/doc/src/Manual.txt b/doc/src/Manual.txt index c63137ef6f..95f1ffe4bb 100644 --- a/doc/src/Manual.txt +++ b/doc/src/Manual.txt @@ -1,7 +1,7 @@ LAMMPS Users Manual - + @@ -21,7 +21,7 @@ :line LAMMPS Documentation :c,h1 -7 Aug 2019 version :c,h2 +19 Sep 2019 version :c,h2 "What is a LAMMPS version?"_Manual_version.html diff --git a/src/version.h b/src/version.h index 7387a3a1a4..d9dcc6de0f 100644 --- a/src/version.h +++ b/src/version.h @@ -1 +1 @@ -#define LAMMPS_VERSION "7 Aug 2019" +#define LAMMPS_VERSION "19 Sep 2019" From 415698d57045dce227c820c665a823329709caa6 Mon Sep 17 00:00:00 2001 From: Axel Kohlmeyer Date: Thu, 19 Sep 2019 13:53:54 -0400 Subject: [PATCH 163/192] update examples/README --- examples/README | 5 ++--- 1 file changed, 2 insertions(+), 3 deletions(-) diff --git a/examples/README b/examples/README index 46148aea8b..68a2317ffc 100644 --- a/examples/README +++ b/examples/README @@ -99,12 +99,11 @@ pour: pouring of granular particles into a 3d box, then chute flow prd: parallel replica dynamics of vacancy diffusion in bulk Si python: use of PYTHON package to invoke Python code from input script qeq: use of QEQ package for charge equilibration -reax: RDX and TATB models using the ReaxFF +reax: RDX and TATB and several other models using ReaxFF rigid: rigid bodies modeled as independent or coupled shear: sideways shear applied to 2d solid, with and without a void -snap: use of SNAP potential for Ta +snap: examples for using several bundled SNAP potentials srd: stochastic rotation dynamics (SRD) particles as solvent -snap: NVE dynamics for BCC tantalum crystal using SNAP potential steinhardt: Steinhardt-Nelson Q_l and W_l parameters usng orientorder/atom streitz: Streitz-Mintmire potential for Al2O3 tad: temperature-accelerated dynamics of vacancy diffusion in bulk Si From 95f59f5bf198e65aed91e93a0dbcd1f852354a9a Mon Sep 17 00:00:00 2001 From: Axel Kohlmeyer Date: Thu, 19 Sep 2019 13:58:30 -0400 Subject: [PATCH 164/192] cosmetic changes --- doc/src/fix_bond_react.txt | 16 +++++++++------- 1 file changed, 9 insertions(+), 7 deletions(-) diff --git a/doc/src/fix_bond_react.txt b/doc/src/fix_bond_react.txt index ff5c14c1bd..4f4506944f 100644 --- a/doc/src/fix_bond_react.txt +++ b/doc/src/fix_bond_react.txt @@ -412,8 +412,8 @@ These is 1 quantity for each react argument: (1) cumulative # of reactions occurred :ul -No parameter of this fix can be used with the {start/stop} keywords of -the "run"_run.html command. This fix is not invoked during "energy +No parameter of this fix can be used with the {start/stop} keywords +of the "run"_run.html command. This fix is not invoked during "energy minimization"_minimize.html. When fix bond/react is 'unfixed,' all internally-created groups are @@ -423,18 +423,20 @@ all other fixes that use any group created by fix bond/react. [Restrictions:] This fix is part of the USER-MISC package. It is only enabled if -LAMMPS was built with that package. See the "Build -package"_Build_package.html doc page for more info. +LAMMPS was built with that package. See the +"Build package"_Build_package.html doc page for more info. [Related commands:] -"fix bond/create"_fix_bond_create.html, "fix -bond/break"_fix_bond_break.html, "fix bond/swap"_fix_bond_swap.html, +"fix bond/create"_fix_bond_create.html, +"fix bond/break"_fix_bond_break.html, +"fix bond/swap"_fix_bond_swap.html, "dump local"_dump.html, "special_bonds"_special_bonds.html [Default:] -The option defaults are stabilization = no, prob = 1.0, stabilize_steps = 60, update_edges = none +The option defaults are stabilization = no, prob = 1.0, stabilize_steps = 60, +update_edges = none :line From 077647b4e2a58be582ac8c9da3cb75f688a71c05 Mon Sep 17 00:00:00 2001 From: Axel Kohlmeyer Date: Thu, 19 Sep 2019 14:54:48 -0400 Subject: [PATCH 165/192] whitespace cleanup --- doc/src/fix_controller.txt | 1 - doc/src/fix_rigid_meso.txt | 2 +- 2 files changed, 1 insertion(+), 2 deletions(-) diff --git a/doc/src/fix_controller.txt b/doc/src/fix_controller.txt index 7458f1bcfa..45eb646b8e 100644 --- a/doc/src/fix_controller.txt +++ b/doc/src/fix_controller.txt @@ -31,7 +31,6 @@ cvar = name of control variable :l [Examples:] - fix 1 all controller 100 1.0 0.5 0.0 0.0 c_thermo_temp 1.5 tcontrol fix 1 all controller 100 0.2 0.5 0 100.0 v_pxxwall 1.01325 xwall fix 1 all controller 10000 0.2 0.5 0 2000 v_avpe -3.785 tcontrol :pre diff --git a/doc/src/fix_rigid_meso.txt b/doc/src/fix_rigid_meso.txt index 0819fdb2fb..a9c68b2c04 100644 --- a/doc/src/fix_rigid_meso.txt +++ b/doc/src/fix_rigid_meso.txt @@ -44,7 +44,7 @@ fix 1 rods rigid/meso molecule fix 1 spheres rigid/meso single force 1 off off on fix 1 particles rigid/meso molecule force 1*5 off off off force 6*10 off off on fix 2 spheres rigid/meso group 3 sphere1 sphere2 sphere3 torque * off off off :pre - + [Description:] Treat one or more sets of mesoscopic SPH/SDPD particles as independent From b7d9337da4e3e9370584eb7f360e7490c9a6786a Mon Sep 17 00:00:00 2001 From: Axel Kohlmeyer Date: Thu, 19 Sep 2019 15:13:53 -0400 Subject: [PATCH 166/192] remove a tab --- doc/src/pair_granular.txt | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/doc/src/pair_granular.txt b/doc/src/pair_granular.txt index f16cd9fe0b..d46bea2343 100644 --- a/doc/src/pair_granular.txt +++ b/doc/src/pair_granular.txt @@ -790,4 +790,4 @@ alternative contact force models during inelastic collisions. Powder Technology, 233, 30-46. :link(WaltonPC) -[(Otis R. Walton)] Walton, O.R., Personal Communication +[(Otis R. Walton)] Walton, O.R., Personal Communication From 3fd43224b3615b310c3d435657e9b15b2b9d622f Mon Sep 17 00:00:00 2001 From: Axel Kohlmeyer Date: Thu, 19 Sep 2019 15:17:52 -0400 Subject: [PATCH 167/192] update comments in example inputs --- examples/snap/in.snap.Mo_Chen | 14 +++++++------- examples/snap/in.snap.Ta06A | 12 ++++++------ examples/snap/in.snap.W.2940 | 14 +++++++------- examples/snap/in.snap.WBe.PRB2019 | 18 +++++++++--------- examples/snap/in.snap.hybrid.WSNAP.HePair | 20 ++++++++++---------- 5 files changed, 39 insertions(+), 39 deletions(-) diff --git a/examples/snap/in.snap.Mo_Chen b/examples/snap/in.snap.Mo_Chen index 007bce2462..bb9fb0900d 100644 --- a/examples/snap/in.snap.Mo_Chen +++ b/examples/snap/in.snap.Mo_Chen @@ -1,11 +1,11 @@ -# Demonstrate SNAP Ta potential +# Demonstrate SNAP Mo potential # Initialize simulation variable nsteps index 100 variable nrep equal 4 variable a equal 3.160 -units metal +units metal # generate the box and atom positions using a BCC lattice @@ -13,12 +13,12 @@ variable nx equal ${nrep} variable ny equal ${nrep} variable nz equal ${nrep} -boundary p p p +boundary p p p lattice bcc $a -region box block 0 ${nx} 0 ${ny} 0 ${nz} -create_box 1 box -create_atoms 1 box +region box block 0 ${nx} 0 ${ny} 0 ${nz} +create_box 1 box +create_atoms 1 box mass 1 183.84 @@ -28,7 +28,7 @@ include Mo_Chen_PRM2017.snap # Setup output -thermo 10 +thermo 10 thermo_modify norm yes # Set up NVE run diff --git a/examples/snap/in.snap.Ta06A b/examples/snap/in.snap.Ta06A index 38a24b8c06..0ca5275e97 100644 --- a/examples/snap/in.snap.Ta06A +++ b/examples/snap/in.snap.Ta06A @@ -5,7 +5,7 @@ variable nsteps index 100 variable nrep equal 4 variable a equal 3.316 -units metal +units metal # generate the box and atom positions using a BCC lattice @@ -13,12 +13,12 @@ variable nx equal ${nrep} variable ny equal ${nrep} variable nz equal ${nrep} -boundary p p p +boundary p p p lattice bcc $a -region box block 0 ${nx} 0 ${ny} 0 ${nz} -create_box 1 box -create_atoms 1 box +region box block 0 ${nx} 0 ${ny} 0 ${nz} +create_box 1 box +create_atoms 1 box mass 1 180.88 @@ -28,7 +28,7 @@ include Ta06A.snap # Setup output -thermo 10 +thermo 10 thermo_modify norm yes # Set up NVE run diff --git a/examples/snap/in.snap.W.2940 b/examples/snap/in.snap.W.2940 index e1abf861e6..7e59b5198e 100644 --- a/examples/snap/in.snap.W.2940 +++ b/examples/snap/in.snap.W.2940 @@ -1,11 +1,11 @@ -# Demonstrate SNAP Ta potential +# Demonstrate SNAP W potential # Initialize simulation variable nsteps index 100 variable nrep equal 4 variable a equal 3.1803 -units metal +units metal # generate the box and atom positions using a BCC lattice @@ -13,12 +13,12 @@ variable nx equal ${nrep} variable ny equal ${nrep} variable nz equal ${nrep} -boundary p p p +boundary p p p lattice bcc $a -region box block 0 ${nx} 0 ${ny} 0 ${nz} -create_box 1 box -create_atoms 1 box +region box block 0 ${nx} 0 ${ny} 0 ${nz} +create_box 1 box +create_atoms 1 box mass 1 183.84 @@ -28,7 +28,7 @@ include W_2940_2017_2.snap # Setup output -thermo 10 +thermo 10 thermo_modify norm yes # Set up NVE run diff --git a/examples/snap/in.snap.WBe.PRB2019 b/examples/snap/in.snap.WBe.PRB2019 index 1e25bbb6a6..6b342ea56f 100644 --- a/examples/snap/in.snap.WBe.PRB2019 +++ b/examples/snap/in.snap.WBe.PRB2019 @@ -5,7 +5,7 @@ variable nsteps index 100 variable nrep equal 4 variable a equal 3.1803 -units metal +units metal # generate the box and atom positions using a BCC lattice @@ -13,25 +13,25 @@ variable nx equal ${nrep} variable ny equal ${nrep} variable nz equal ${nrep} -boundary p p p +boundary p p p lattice bcc $a -region box block 0 ${nx} 0 ${ny} 0 ${nz} -create_box 2 box -create_atoms 1 box +region box block 0 ${nx} 0 ${ny} 0 ${nz} +create_box 2 box +create_atoms 1 box mass 1 183.84 mass 2 9.012182 -set group all type/fraction 2 0.05 3590153 # Change 5% of W to He -group tungsten type 1 -group beryllium type 2 +set group all type/fraction 2 0.05 3590153 # Change 5% of W to He +group tungsten type 1 +group beryllium type 2 # choose potential include WBe_Wood_PRB2019.snap # Setup output -thermo 10 +thermo 10 thermo_modify norm yes # Set up NVE run diff --git a/examples/snap/in.snap.hybrid.WSNAP.HePair b/examples/snap/in.snap.hybrid.WSNAP.HePair index 1f16fa64a2..1092c28119 100644 --- a/examples/snap/in.snap.hybrid.WSNAP.HePair +++ b/examples/snap/in.snap.hybrid.WSNAP.HePair @@ -1,11 +1,11 @@ -# Demonstrate SNAP Ta potential +# Demonstrate SNAP W with tabulated He-He and W-He using hybrid pair style # Initialize simulation variable nsteps index 100 variable nrep equal 4 variable a equal 3.1803 -units metal +units metal # generate the box and atom positions using a BCC lattice @@ -13,25 +13,25 @@ variable nx equal ${nrep} variable ny equal ${nrep} variable nz equal ${nrep} -boundary p p p +boundary p p p lattice bcc $a -region box block 0 ${nx} 0 ${ny} 0 ${nz} -create_box 2 box -create_atoms 1 box +region box block 0 ${nx} 0 ${ny} 0 ${nz} +create_box 2 box +create_atoms 1 box mass 1 183.84 mass 2 4.0026 -set group all type/fraction 2 0.05 3590153 # Change 5% of W to He -group tungsten type 1 -group helium type 2 +set group all type/fraction 2 0.05 3590153 # Change 5% of W to He +group tungsten type 1 +group helium type 2 # choose potential include W_2940_2017_2_He_JW2013.snap # Setup output -thermo 10 +thermo 10 thermo_modify norm yes # Set up NVE run From d7a87929161ff7ef499ce90df18b9d1a14c92c7e Mon Sep 17 00:00:00 2001 From: Christoph Junghans Date: Thu, 19 Sep 2019 14:23:58 -0600 Subject: [PATCH 168/192] cmake: allow to build against an external libkokkos --- cmake/Modules/Packages/KOKKOS.cmake | 28 +++++++++++++++++----------- 1 file changed, 17 insertions(+), 11 deletions(-) diff --git a/cmake/Modules/Packages/KOKKOS.cmake b/cmake/Modules/Packages/KOKKOS.cmake index cc1e051629..d0f67243cf 100644 --- a/cmake/Modules/Packages/KOKKOS.cmake +++ b/cmake/Modules/Packages/KOKKOS.cmake @@ -1,15 +1,21 @@ if(PKG_KOKKOS) - set(LAMMPS_LIB_KOKKOS_SRC_DIR ${LAMMPS_LIB_SOURCE_DIR}/kokkos) - set(LAMMPS_LIB_KOKKOS_BIN_DIR ${LAMMPS_LIB_BINARY_DIR}/kokkos) - add_definitions(-DLMP_KOKKOS) - add_subdirectory(${LAMMPS_LIB_KOKKOS_SRC_DIR} ${LAMMPS_LIB_KOKKOS_BIN_DIR}) - - set(Kokkos_INCLUDE_DIRS ${LAMMPS_LIB_KOKKOS_SRC_DIR}/core/src - ${LAMMPS_LIB_KOKKOS_SRC_DIR}/containers/src - ${LAMMPS_LIB_KOKKOS_SRC_DIR}/algorithms/src - ${LAMMPS_LIB_KOKKOS_BIN_DIR}) - include_directories(${Kokkos_INCLUDE_DIRS}) - list(APPEND LAMMPS_LINK_LIBS kokkos) + option(EXTERNAL_KOKKOS "Build against external kokkos library") + if(EXTERNAL_KOKKOS) + find_package(Kokkos REQUIRED) + list(APPEND LAMMPS_LINK_LIBS Kokkos::kokkos) + else() + set(LAMMPS_LIB_KOKKOS_SRC_DIR ${LAMMPS_LIB_SOURCE_DIR}/kokkos) + set(LAMMPS_LIB_KOKKOS_BIN_DIR ${LAMMPS_LIB_BINARY_DIR}/kokkos) + add_definitions(-DLMP_KOKKOS) + add_subdirectory(${LAMMPS_LIB_KOKKOS_SRC_DIR} ${LAMMPS_LIB_KOKKOS_BIN_DIR}) + + set(Kokkos_INCLUDE_DIRS ${LAMMPS_LIB_KOKKOS_SRC_DIR}/core/src + ${LAMMPS_LIB_KOKKOS_SRC_DIR}/containers/src + ${LAMMPS_LIB_KOKKOS_SRC_DIR}/algorithms/src + ${LAMMPS_LIB_KOKKOS_BIN_DIR}) + include_directories(${Kokkos_INCLUDE_DIRS}) + list(APPEND LAMMPS_LINK_LIBS kokkos) + endif() set(KOKKOS_PKG_SOURCES_DIR ${LAMMPS_SOURCE_DIR}/KOKKOS) set(KOKKOS_PKG_SOURCES ${KOKKOS_PKG_SOURCES_DIR}/kokkos.cpp From 56e1a05287c34188eca387dfee62b935434096fd Mon Sep 17 00:00:00 2001 From: julient31 Date: Mon, 23 Sep 2019 11:12:31 -0600 Subject: [PATCH 169/192] Commit JT 092319 - modified norm input in min_modify - corrected doc/src/min_modify.txt - added expression of the norms - added a min max method in src/min.h --- doc/src/Eqs/norm_max.jpg | Bin 0 -> 9471 bytes doc/src/Eqs/norm_max.tex | 15 ++++++++++ doc/src/Eqs/norm_two.jpg | Bin 0 -> 6048 bytes doc/src/Eqs/norm_two.tex | 15 ++++++++++ doc/src/min_modify.txt | 18 ++++++++---- src/MAKE/Makefile.serial | 2 +- src/min.cpp | 59 +++++++++++++++++++++++++++++++-------- src/min.h | 4 ++- src/min_cg.cpp | 12 ++++---- src/min_fire.cpp | 11 ++------ src/min_hftn.cpp | 2 +- src/min_quickmin.cpp | 11 ++------ src/min_sd.cpp | 6 ++-- 13 files changed, 109 insertions(+), 46 deletions(-) create mode 100644 doc/src/Eqs/norm_max.jpg create mode 100644 doc/src/Eqs/norm_max.tex create mode 100644 doc/src/Eqs/norm_two.jpg create mode 100644 doc/src/Eqs/norm_two.tex diff --git a/doc/src/Eqs/norm_max.jpg b/doc/src/Eqs/norm_max.jpg new file mode 100644 index 0000000000000000000000000000000000000000..c10db9a53144cb3e889eb3c4315352d2ef0c85e8 GIT binary patch literal 9471 zcmb7pby!qg*Y{zVfuU#UmKZvurG%loyF|LBQ@UHa8|g+u2?YriL_tbYIs_3^8sQtf zpZmF==e@q`{jP6a`;W8t`mMG1I(wb9_F4Pp^UVqXQ5WaOm8U0HLD+|0YZf zbO;Cxz2y?4c>jZL<^fz38U#a!0RY;?)Bj@Q6A`-p*8pZ*#JxTMKXD{idhI_LiKP4~ zfNkPYA=lr7*6KOCBWD08z}L25gz_1yBUZ~ijZvwfyy5iU5CAdL$#tZ&9xCWck_lqn=wLvL|tYkt%*VQ&Mf zT7yHe&d)TJ-pQ~G!Oovv2*1lms!Pe=Vn80)ynTTOLHO2VCE$(H^tIT)iy-i=x_jHB za>7kSY0(<-bSNOp8<@awXgamL@V5j9c2Q7@a#D){qa18J9fe4OW3w`W_tZp0Amr$@ z&ba=~qB1$(kl+nsOIsT?DMe=HDT;8EBKn{GzeGe>2RBwku;CxnQ7aWqUldVWjTN)1 z5+2cHsY1;W*^dtL*_tXWbhlz+!kvdt2HU?wEqs`#o~HkU{3yK$#>O5V+BnTQs?8Ks zbp>8P z;Ad&{X0i2A(DtN#@r6P=`r${-@>@%!Dg-cfP5h8Y7fh=Vb`gB1Dg`BjB5|mL_a6oifZm@d>GJm&oSf!9n!C{99N(O~)?Ksl;svBhUbZI#N5v+c<2)yr`_APp9Z@!Wh zBXV^IUQ{c%7~TNmPLz#A3Ve(&1IsKHHz%vQ?|vEOuyU%4YHt6QSzk$EqtY$aZhSJb z9C!Hvg9dQ0b(_E2+qyfsl&u+Z+7;uAwYJK;taAsd;B5Z*aZS*`6itIlLxPuA6m`+I z9oEK*@B#7nxS(&@>P7oqsWzkD`js?e(qc9V$fxh}uYmnz)lTh%bmL0!!)2TE|;!ibjd_v$%iWqKsnBY(q-oOI5FH1(*e+Je?Z! z@N-9T3r3;iatN4PEN1k{#9#BhfYWMXstl7mQOB>Sy$?H*Uw4$Gb4564CVzf;azw&O zX`e}xg_l$(uPO)a)2aAr#j->r%ueWLO zb0tnqC1N+%h;6@S8)jg&P3c_rDR1rHwx+ulvev|SY9`P9BIo5CmdA|IdHt8WaE-la ztW<6oW4egD*5}79EQ%};n(kp>-WBTK{A8lI$`wbSw%mHuvRxgh`LNA>^3af5pMiBg zyq^y@!7ud0NHi|N--D-lsBuwDKYXqajX=N3`9-9R`qEL#$e-CS12wBC10kEkXts>( z!FoA8UOkiGp(#exJ`{8)?fIothJV`^aZaB(qE~~=|FOvEHF=kmnmEupAlpe4rMkhG z-}wen*cl7}wYqA~&h~$UzUUBIsJOT~tOtn8@)-3kn2= zsnrU`K8aRffPa*GOaOLQxO+7(%DfV;ONH;t{9B;EHVnJd?4Dw9mYb0^c{qM7nq(zv zxtRl--bL8DsMxvurU7wJrL^1 z0Kg%HFd}+h3}Oa8DJ{WfOuzIv!rH4-riK zGMNMaiia4Ipx?@mx)kxkZ5g=UW^DYTkteLl;(`5G`n`6{q8(ge!j;`v(0`;_9t*N_ zm{0*{U8ng4Os>YYpzR|wT~afNJ7XMYPaQ)RT#s~MZ}2m4>qM-1lsRe^ygYW7E&|nY zTa^=o-Nj?B1QuyScBKJUfX$kCG49Yr@ys+)M(Ef&itj@IRkzOdLP&fIbQD`!T2^IS zOE+#@P|w_bHjv%NXia1B5p(81$93 zP38zM34g(tjnpIpXObCX<+j>`o#H}%E?)__S<>@MXtCu`dq4y`)h25=ut^7%m{iHP z^GkG0TW({5(DrdYf~dnIr{6SdT7 zBJDLlmE!fytY)Um_CFW>dIcKa&PvOux18%Szg(QrRalsg5fUI5(@`$qW*J#$vubn87Rk-)cdqt`?w+QsbcVtu+qHwa1fB*qE z-w}&_+C+m9kDy-co-MbT?)0NOwRuDWgkG(nAg0zP53YwlChF?&Uior$?Xbp$h+gbP zywo9hxa)+y-@A7KnRYIs{7@+(k$Ivw@hGD#GG3|oZmHl$q3KgQ4!udoKx)0gff{9zRmpnC&2zgdosp%H8bY6#CbD2L6| zO{;!E;_l$whqJPY}%C##rkSBAjiIX^=W_Cm`LT0lc|aP3!XceZrMh&9g}uB#`m*FrzcwrXE7SJqcziTMrdn`LoMO24qON;pX%@N3k{Bb z{pr73RgBMjpG?AAP|GDCW~fX$h=oeS%pzi%qU~CDqW@snz)gFGWbW}y)%)JeO2wF~ znYq12ek=>9vb)ChQ#BPkmeN2R!@)$|xqDU{@n6W~rpru3=dXE7W>Xo81(49`KvZnX zdA-tspKeZ`rPuMt=ekx-tvH@bfST(T-8REl%kd}2 zJ5g!i=VRL=_vU7D3Z$S_b^Wef{4M8ld?J>RD`{eiVCM77x+%I?L$`>qMm0a$NBT=0 z#)GzNvY5QPvh#I;iw!?Gi*QP{>ZGGLUogm7>m5z35|+B(+Yfj)vrR^V^c(8$r7Ak<>!rl+;O+|I0o`UJ^J~}j^#bAuF%-kGI}!Q1)pU6bJhD174;mg zrwvGM&L^^YN6nKiRd2Y>a=SX30(6zqO_E!R0*!=>-&d0DN}n%u8W#>Fi-87=^ehXH zbM>@D7E*l1@RRqO$ z^ePSIxI~7(t%>ap{EqEacD3-!wVqwZFQ7nVdrZpoedi5z`|6f^+kI2J<)z*u? zx0@GRgbWm~HGOP;wfgZ$r#NFd{wVMR=X_F+uNisg!}iD%EWJ!xZ9chMRTGwYt&sQN^ZA`8OGr`BpvW%MAVOa~*|$K2&39b&lU=_>4U;9*;PIv6w#%^n-Wa^01HREYx zmZkfkfsko9c7YEOvf<{N6^-vKzd?kP+b)rWNovAyiTMFkxi0T)WYN|fdZ32?E+wGD zn1rAEX`>)y$w{QOag_b8e%yaJUf4=Q6SvBF_8jeTi8EmzRwhxu5fvEdYKR%=c&g-? zGitr+mwMOm0m~g*j;ML1yJqL=0VfxZ*e&k|7hUSS85$NfT3N~?mJ%CR{fS*m!cU10~cna5e6CeKiZCxkp-2aX}Z{~b( zRPnK5!wVrMxu_UcC1;{_yw>M!(0rjP<^8$!bMX2Y)!R7du66h?hWSEU4t2iC(2|lg z>h>P$h9ZHAKuh7fji=f=FM37l1a`I=eTIVGzf715!=OQXecqo0vG-@^ zs>lQ3!=}_vaXw|nKE+7QQNGrnAkjb9f@QmYv(>ow_W8g{GT+K3-GhvJIXZ#F*9Jd2 zVrx4`Vk5glocR3P{v(S;Q7PopS7fuXHdV0Ecu+k58nQ3KT@&D`m1yk_>u79Q_ng-o z7j~MY#5DKsSi<>9r7g$A-KY^nkDc(o>z*K5|S{clPYG233t^CH5OG-+)WKCvVGr*J`JA>uI)&Q?T|nl_DtIu*@T%Fq zj^{o0`O0K+v9ns9S3f*w+kRddb#P8C2Ai=_4Bgr26ubYbGB$-|%%hpYbAEQ>iCdIU zo86FAlVL^2Ma=9)5ersXcu}b!zsa3~kzePpw!XS-B~d%{zenU}O6p)xU}nc#N)nD& zjom2-wyqv0-{KQ`_31(8Z}l?8NRAdQC$fGDy{lqssV!tjoquP%pQMh;8=FAuQ!^o0 z7nQTY!zcR1sJ{U=7^+r*4#GeK|6R93mGtO&VNzNa?x^EE9S^eqP_t#?=gps z@NZT)dmB3S^3r4~Rj$u92?Sy2qM%GQ&$A!G=33AgZD_^X>p<>T@-mmnazxoR(mkTFr~%;J%lf3JKhM#>8izV$BbJ&wN&x0L`BVajN;S#^o`UJkul)>If< zfjt_2>0B-TrYxoO22>*s`+UqY+IQAOjVNWTp;ixpGhofpmV-rnYM`&0%z3;uD|5B1 zZhi;3A9MpSC5ObvUFk6`GUX!lE1rr4iaDt9K>`%Qq(KFZ3Nriz8`l#-*z?$-Tydt*;-l zO})3@iV58gBQ}q8AXOrx7*M>zStrB864MoWyF`Pa(p8bgrN_aU-+Y}->W5xvAR;g+ z_ZIJ~U+juh2eyY!COHeaitkK3I?>A;ApY|mv-*fxuez(gz6Jc!vghpY)_AP~ zv#t&|<;-K>ZuWO1Iez&MRB=#G~hU7nWSmz+4O_ZXpnpS^LZ`wc6b;>~BD(oHnZ5u6co(fZ>h zcH@dUZ*=?3 z9%YKlIEfZE$m9@Lejn+d#xMKiRL~@?RA5dtlRalVJ;K#p%)b1DS2@H=;4RCwUPy0i zgPdtF@>rV^ff)aQ`+2cimthb|NW<+-OB|h$qU>tHe_oEk6vpttp^`^wurx*Yin@^c z$(Gmed8zY;(UZKl_kES0$u@lZQdLN7>S?-oFs8v_m|(%}Mk`??97@WK=u?U3523Kx z#OL#$P$N$Fc#yU{FD+79*ptOMKQHfa;>_pOi?lXJE8#R%3e6_Az2+Mop|<{cbPK(s`o6F6GZ7{c z$(1X8;a5j66`m5Gs$-8yr3b~3qV5WnK!NA9AN7+#EY6s}laD*x4SlC$Y$%E{GKJM6 z<^40q93@y+)5TKrq|4=2vGNgGce@uBqtiWYRwiP1>{zWQgqb?W=Wzt%@(azqp4u^& zZs9FQd}xM+zwG>~2Ze`2$#Xs95v@obBp7n29b#Sw9q3mz%mHL=a&7&3j0^Z#QvvuR z2#E+xN+7Dy>{~klw#s`x^@HSicEacNPn*gm%%dnvj^_m{iJ#%g>y%O-v?cEHyrD~; zXW^F<;Uip*^DmIF@bM3%Ms9m2SrV4upLEt{KHJF_t9OEB0>16Nx(&skEt2!$Wm+hU zR&{y?nml(QrwaPuoX4%|sk%cci)lvAz5&Uf- z0ff}{GjDOp8pUSV0vLlndy5wjgm1!@7JSXFT%=?%H)Z3l1h+>v7w&;neil~09g{yd z$Q!*9IVWc$iqH@!f7?racK-&zRsKn2|HSrSuL+fb{@fM;=%_M1EKLdVPg4Z{^ZeI1 z@E=?xA`R{Dt`s6o3Jf6s1Fr}U#{zD}6~TZK9U+u1^j}~w2n`V~g#i9ijzj=T;1nrv z8rH2U01H8g1QTKbAe3@Nlzwn1YDOp`MUf7MMF&FC5n|D$C?Ud8suU3^P;ikRW@>-SKgR^v z4M6;%YQ`oHAPKU@6`4C&2*7xKerJtE7Qo(0@%rfBHj52odThc=>2}fiy-C=fxWvPE zp;W#xrX<=$nTekM`iC>#2E)78vul@Z(WDI-AbS81Ca8F;JtkYHUjv@KkF8ne@B@0n z^a#y-hBLe@PM$NRjcR%*p1$3C%|S?-vF)4tTFf5ZU7g{}uzOW5Sh1#2Bj!Sogb}j~ zR zx4Tu83+*^PQP^Of2Bw+8iIc>)Er;ke$j5h2&L%077{_tqz>rb~ah#K5FR$ZV4J6to z-c)Lr#6&Ks1mMj|U^5Js;q!60z{#TW@%?xMh`GPy_a#;*7)=+HPLN3xAn=Va!xh)U zV9y+aJwQ+VN5!iV2de<0Cmu3RKA+iMB)WiD*8?mk)%k)Gls_pHuF)*6O>`Q+KvKf3 zB7=n=Dl;=|MVLMw#XiWaJpW>#VU+O;pw(PbqALGJk!rPqsU3RqAk>8AYtyxaq`~-| z&A^L0fX(OV0L@iO@B0{JUYA58EwL%#ntJg4h!V*$zmK190HnVEJG65*Cvph=>bxrE z2WI*WbvLzd6qm;uACX4M?B=?r=m#uPt3>I$t`+4(;cu4d_*$-xC(oNGE@{KIe~+aU z4Op0CBA@j+ZLB1$H3CKk?D1`d!3G~MbXQ0v954ek`b2D9w&`RR-R1=4PG&iuZVcT~c{&{}tPvQ^RD0V=$bpL>K-Ufg2vWnzd2-6tvj}RD`#I z^uMAGwLd+GLGn}LXb%TNXkWn2_OUW;FzzE6-%{KF6;}_zQmgZlS9=;;J$CzUd;`Ze zrRVUg6|)D#_GW{W-S=z}2f}P&n%pUTesdW4K@$5b?pstw&4EG*>^p282x@_FXFO29U~`w5wNzdu3V4RG4<$KHOr^*5=W?`a{?D*Ja{ zT)W$|=2;Kqc<+k`QC>9_D?8eSVWvS0?IC8Mt(TKfS>fuUzPtbyyKeYF1{DBVc#ssf zH=U8E%sMA0INqp<{!|K%gu{u{K|3GjfMROUTPa` znlSNd0)L_?q3YD5mJ{_hlp%`zDpGg|g}ENzB3xIxu(Lk>bn7-EiN2F(rN7tSVNiw% z82GmrM=UrzjTB?i$o#phTF=KE z?gx+ja*~u16Mn13%U%i+yI21xo4FL*;#b)B@lvZ)D5(R*J@=UGOnSh0h&5Rq)PU^k z#=dB*{VOCfezl)_Dfs@s{N>kKMmps@23V612KvBLy+uIZYFV z-gaNS1P_wT4_rKSaV?Y8fNpa09Im*+uP<~IwcpbRO;1|IMK6cujSVJ=SPI7AKagmP z&u`@)tCsq7#w!rT`I>CWOh`EACs?F~GBP=Xg+T;gu{nhnxF*Y?AB&wrc$JF4-+IVJ zh8|)nd4yyXbC!s|s7%#Wk=7<9s??y(Hh z$Cw_Lj+H#y$tnC@ynY}i`5o+GemJF?^hlL&X;9(HQX!0oLEZCHQdHIy#_Q~Pfg_8O r8-NBKOgJd@i4pz=*P1QxQKqB83)JnyMCL#?s5{D^%;LeTo4Nl3fP04( literal 0 HcmV?d00001 diff --git a/doc/src/Eqs/norm_max.tex b/doc/src/Eqs/norm_max.tex new file mode 100644 index 0000000000..3b2198bdf0 --- /dev/null +++ b/doc/src/Eqs/norm_max.tex @@ -0,0 +1,15 @@ +\documentclass[preview]{standalone} +\usepackage{varwidth} +\usepackage[utf8x]{inputenc} +\usepackage{amsmath, amssymb, graphics, setspace} + +\begin{document} +\begin{varwidth}{50in} + \begin{equation} + % \left| \left| \vec{F} \right| \right|_2 + || \vec{F} ||_{max} + = {\rm max}\left(||\vec{F}_1||, \cdots, ||\vec{F}_N||\right) + \nonumber + \end{equation} +\end{varwidth} +\end{document} diff --git a/doc/src/Eqs/norm_two.jpg b/doc/src/Eqs/norm_two.jpg new file mode 100644 index 0000000000000000000000000000000000000000..5554de32f96a3a16f855b7e5011aa999d3c2819c GIT binary patch literal 6048 zcmd5=cT`i&wm)eQdME*;8JZ9T=^Z2>Em2y;fPzT1AVqpnA@ts>g$@Er5fDMD2nw;# zL7J#^1yn*u$_x5=-*?}->%Mi@`{(U7>&)!m?7e57*=Od=o`aEtPXGd^i`4}{6p{c* z0KmaGa0-Bc!H0!HP)dQpVK68ZMoUdi1*fN_r>CQ(qhnxXK`<~fGt$u^*b&UEY)B-M zo{58#osE-)4as(B1O%bzKw&g67!4Z(9Ru5cOb0IjW;kFBdJX|G17Kzlgc)?u0q`8U z3P27Ye~6k20)sVZv0`k=#!fM zwEtckL@V$8od-NG8+UMg`USCSrPFMuDd_&@0Dv*}HD~ZHC`j=Y^h4sb@0IR_$xK=Q zLs2DqW^EZN@o(Kr!$hX`H3|axu?OtK-I`=)t-&`;NNsv*z5c)_nU`$YY{rz{EfJV# z7WZmq0#{9|65|$Nh?AlyL1zj8COJML1^K1)RBZzP`k9hw;g9)~ESYX8y$shTa*oV< z^oI@>LEcd<6mWve=-YCnX6Yw+vG)|Un@U*7xo#=#j4ljr6IpI^Q|adt)H&>q-3sHm z&l#diXgf4Dn3CM_+f+!;Y}qTekW#e<|0g?LqxJx6axBFQkh17=1gkEgTgKilW<^bO z=2HQYrcFmA9Mg-$0Kk!y9=+m(CjdOp^5hT3*zXh#Kt+}^xz=%RGRGs#y|0*iTSLlJ zWy@3#--$_rujo+Z4^dO%c>)1|AP_JVN<|6bFM>g!Q~;PAM2$eAE{eQhido?T!xm%3C9qw_nRy@dl)f`OAYj&Vou9>hcx_;TKQoq4*PudE!JrdK>^chdUbce{XcZ zS3u&g@0_v&YJli9{*46q9}@b9s|XB+!RV=IAh1I#ATR_9FvD0_`K43)5dxZSNmM8q zITITXub}F-J~lxqOkNdILCYAQoL^AmKJZyc)-(9WU+arX1N^fi^3mDZSI8uPrA6~r zbL3OP+;;}&v}cX&77i{hKZZvw?lsB(zXJEBw2K3mt4G}~V$L$EPs@zBGV@Zd0{u2KHdI8qnMlaflZY;VxXwy##mg{?$B0UF5lq~5 zTU_rpou!+!JOEtsY*HSlb85ex(YIN8K5NjUcg|Wxgl#f~S&JieTuL}FzPhPE76gJy67E?e?AJseitfgYJHdU{^d8qOm^?&N7ncu|s za_&tIQp`@jQ7b9x%-A3_Riw;A=^@+o%ij1dz!ONu?nXS##m&ve@+>wGkE(q08IJoI zQ($gZu$5DdAI?n`vMgCbMzvq74%K;6AU0^pd+fvgC}LmDNK9AcJx`dg-nOg$wW>5Y z2+gNS;s-|E3F&%sfxvZ!c%9TEbY>Txb*|gEfU!xns9846}%+i3n8}}PZ<0h z*-twFRwb8JGuJ8)fY8nQ)OY0=td@VLY;>OP(<=_*L~0C;P)^rPM`(qMd0Tg53261Z zYSwx|z|^*M;05gF*E2<1;tIt~kFAQPjBx4g)kg(ZCMD(|h2z}@xQyZq^pg%8{+SDM z6lYQo-A-2Z`>nh%j9l11RxBHVi{nL1^p=%3i@k2B5LZ|q%Xwa<}z-ffS0EBVOp6}J{1zn*kcuDQ5*I^qfWYL1~d30nNd z&Oi152!3^J^3<@`O_GtTp#E4ll3RJL!trQ7lj{jkP)Mm`_iR(>IGMI|jOP^6BFaIB zAqq#ZbJqGG&%)&`)o-zc40&8~M$gecmn1y#way`8`t{iP7qdpR9AXLSq-FV?x~M?c z=uBr$o-b%d70;%dXm&rv@ajxvbnO}mm|Y$+nX}~#E-c-6(SAXQA5CpOB6-uyqveU~#HC}B zi`bKUXM$KR9L@Y1qQk(Qx;THSdMNyJ-<;et&HJzI`MmAQFElqbcklGIx_MrwT?=Hz z&n}FHr)3@gHuiq?ZeYWCgNLdr>hua`pY8W$XIfe&bx_IRu!7~8hU!lY`8*f5^ldS?&38&)Ryt%3zQe)?|EAnS@rp$2b9)9dx3tBTYq&op)q zfQ*~m{jK{Bd&TaD%i%{h*&d$UyW45XC3#(AdYK|)f^^Yq`nj{H)f!&Mq2(F; zpi^p03N8-i;O>6z*!%{e=DxS3>3w;!Nwl7MJ3-_6eRs%c;H+G#(0MdFxbbf*=I7-6 z?W-T_8|1_MHKHEX5e2OHUbN)Z+2_KJZ*{d=FFeSIvFU2Jl^N^mYvRbd{M@RO6j+r* z`~GY>B4^z*K%viFPUlo)Z zs>wP3A$m#PYD^J_U7Smq6yV0;d($M$2$Sy7EgIJ%-r`d^7*69cBOW3rTK2WYH5lFT zADwa=c(qs(y?7sN*4@1)7F!=a+*?+ddH|pWGGC4kF zCOZ`wSQ63L4A59$?-QykFu5oJC`SlZNm32hnvG8pdDQ`u?t6p z(tSAvg=2@Y3~y`bFa5ZUdv#`sN$qr(QgT{`Cw{nwFCCsbH$=x3EWo$5xtzH1h?(3^7ljLtJAFnaCka1AM;yPP zH8Gumc^5V<$0pU8qVU=F1G?R_ShBWx?b)`r7+o%I;4X`6ajCHn(~+iBSY3(j5?u;A&D)KU#EOuWPMTrZ~ShUS7<^Hwn`!kYdOzTSFNJ1f{} zVe8Z0jv$o%Gp+-J`7lX8D(MuhwnTlqu}ekT>?v@is4k&>xg2Tk*NiB+Ra+|!fFn2 zLu*#?%t|K_{G0v^Zb_T~)nh}FM=Oeyf@CnG4SxiyYIB-E!T~#>Os7RcS_6-c>&U0c zzW!?UI~{C`H}z*fTU||643|HV+=isikS+snKR6*!H3!(g-EcEh`oSEQO$+rsKT!1M zT12T{S9(hes9nPC9ZjJ&!2>L7CCU4qx}SB!LOZAKJ#6xW=#B6%?_D1f?!X&`#(dGq z0njKxZig%-QMS81UGjw13ciGgt}Es^%oo*YA2GhH2-_?nS6)Z+@K!l@4vbf%25gwN zyuX}%tHY2ud}2HaY|Ijpm=$~8k08C@tu^Fu+a0xbd~y&{z+?1iG2?r=C5@pQH!wRdMe5QV`@K?3&XB3=QmI&8#v<*)W`Qi#|$?~TOez1%c zugzLu?WKCQNN|trLrV4bh=cQxBVshHk}Hv@4>>`%WA{kZJUlot9bFL zy?X|?h$Nr!N+7W)a(!)yU427ii(@A%ST@^Pz7-DkWZ*iLj}yViU7XzIw&c`CtykAU zJ7rmAk2Wh?{N`&f-@l)OI5Yd5tTo7$a&m+B04SiGxPRSU01(QV9g&O``dwK5H2#55 z8vhDJ{aqj#1N|o!E0hQlLSTX4ibSkXFvYCCP_m{FLLYV52K_>Qk3}PdfTM_TfQ1H{ zsEI;QKpJQ;1=K_l^#K+PltuF|^+ZhofkhE%D6T>&*8Z}Ir3{1uQ?&lM{G06MFuy_k zuldby2@wP(?FUmX3ZN9NUrExhtq`GULfHzXg7T^`#y?h){z_jcX7{!AhbNDpW9E!p zY~3Ii;nKuROY#4rdZZm^$D%%Whv`kS=+Nl?2WbJYyXZ}J>)yv(V8C0W&}h<8z1E-W za;3U(xO3{#jSDEs-B%zaaK`&Zj32>!k$ZMh1+T-VbOR^nc&{*pN7a~(aVC@I4V5w7 z^D63doO)lgudFsUJo0i-5%5h0UU#Kc# z*u+a@+apARG?Ywj`!ix8*!$d%N8WX4#e@YJpO#`#1eqERAs_O+;^)%N>`k;Lik$-< zjelLKIK^)E{Dd>l=Q@LpBV)~iW%V>y!P%zjtJo9#QlzIZxoX3NU=e5;8UwEDzWq&Q zc6SZFvziS&?M*G>+z-g#&V62WK$4!BYBvPhDXDn&`rrs`f~ z7zZ6VH{Cz{04SgBz4`E){VnQgx)jAjy+O<}@hP;tt({+3f+8r-m+RC4LYM<+y?(8+?@ zOoi3*@{d$ziCb&+VQ=fcf`u5`=KGnvF1}45?%Me3<j&%SP1N_GZB0}m4Jnf0#bhgA2vuly)EjQjZ2A_5vCpibN9P)}9+>1=bom(C&xz&&mga?-N=j1YQjO}2$hQsv_JXNv_rk`sM_}_J zJ}E;-aPonM_c3FFVmE>MTdtqJHLgIGY7PKTUwARreP)WPj}tNi9QrP4{E-yUaOv64 z;Nk4Aycfz(P?f$!bxk2-CVL84l_J>#uiUO`h1_Nd_?)-0^6u9D)~>xeA=}fUz(!ZH z`dvE|E)J$Wrxlkf@4sB27#Rg;L4ietfrf}s`3 zuZS4nrTn?vRL(S3H=2_}?eXE`7HXaloeW?3-f{-sW>M@$1&^n~*yuC@p6Vy-742n^ Wbg?+l1j#1hE)v|+w|Del^uGZ4YjxcK literal 0 HcmV?d00001 diff --git a/doc/src/Eqs/norm_two.tex b/doc/src/Eqs/norm_two.tex new file mode 100644 index 0000000000..d428081a49 --- /dev/null +++ b/doc/src/Eqs/norm_two.tex @@ -0,0 +1,15 @@ +\documentclass[preview]{standalone} +\usepackage{varwidth} +\usepackage[utf8x]{inputenc} +\usepackage{amsmath, amssymb, graphics, setspace} + +\begin{document} +\begin{varwidth}{50in} + \begin{equation} + % \left| \left| \vec{F} \right| \right|_2 + || \vec{F} ||_{2} + = \sqrt{\vec{F}_1+ \cdots + \vec{F}_N} + \nonumber + \end{equation} +\end{varwidth} +\end{document} diff --git a/doc/src/min_modify.txt b/doc/src/min_modify.txt index 06c1f7514f..b941a33559 100644 --- a/doc/src/min_modify.txt +++ b/doc/src/min_modify.txt @@ -18,8 +18,9 @@ keyword = {dmax} or {line} or {norm} or {alpha_damp} or {discrete_factor} max = maximum distance for line search to move (distance units) {line} value = {backtrack} or {quadratic} or {forcezero} or {spin_cubic} or {spin_none} backtrack,quadratic,forcezero,spin_cubic,spin_none = style of linesearch to use - {norm} value = {euclidean} or {max} - euclidean,max = style of norm to use + {norm} value = {two} or {max} + two = Euclidean two-norm (length of 3N vector) + max = max value of across all 3-vectors {alpha_damp} value = damping damping = fictitious Gilbert damping for spin minimization (adim) {discrete_factor} value = factor @@ -74,9 +75,16 @@ could move in the gradient direction to reduce forces further. The choice of a norm can be modified for the min styles {cg}, {sd}, {quickmin}, {fire}, {spin}, {spin/cg} and {spin/lbfgs} using the {norm} keyword. -The default {euclidean} norm computes the 2-norm (length) of the -global force vector. The {max} norm computes the maximum value -of the 2-norms across all forces in the system. +The default {two} norm computes the 2-norm (Euclidean length) of the +global force vector: + +:c,image(Eqs/norm_two.jpg) + +The {max} norm computes the length of the 3-vector force +for each atom (2-norm), and takes the maximum value of those accross +all atoms + +:c,image(Eqs/norm_max.jpg) Keywords {alpha_damp} and {discrete_factor} only make sense when a "min_spin"_min_spin.html command is declared. diff --git a/src/MAKE/Makefile.serial b/src/MAKE/Makefile.serial index 8628d2bb73..5954d97761 100644 --- a/src/MAKE/Makefile.serial +++ b/src/MAKE/Makefile.serial @@ -7,7 +7,7 @@ SHELL = /bin/sh # specify flags and libraries needed for your compiler CC = g++ -CCFLAGS = -g -O3 -Wall +CCFLAGS = -g -O3 SHFLAGS = -fPIC DEPFLAGS = -M diff --git a/src/min.cpp b/src/min.cpp index 31adf58525..33643d4837 100644 --- a/src/min.cpp +++ b/src/min.cpp @@ -49,6 +49,8 @@ using namespace LAMMPS_NS; using namespace MathConst; +enum{TWO,MAX} + /* ---------------------------------------------------------------------- */ Min::Min(LAMMPS *lmp) : Pointers(lmp) @@ -56,7 +58,7 @@ Min::Min(LAMMPS *lmp) : Pointers(lmp) dmax = 0.1; searchflag = 0; linestyle = 1; - normstyle = 0; + normstyle = TWO; elist_global = elist_atom = NULL; vlist_global = vlist_atom = NULL; @@ -662,8 +664,8 @@ void Min::modify_params(int narg, char **arg) iarg += 2; } else if (strcmp(arg[iarg],"norm") == 0) { if (iarg+2 > narg) error->all(FLERR,"Illegal min_modify command"); - if (strcmp(arg[iarg+1],"euclidean") == 0) normstyle = 0; - else if (strcmp(arg[iarg+1],"max") == 0) normstyle = 1; + if (strcmp(arg[iarg+1],"two") == 0) normstyle = TWO; + else if (strcmp(arg[iarg+1],"max") == 0) normstyle = MAX; else error->all(FLERR,"Illegal min_modify command"); iarg += 2; } else { @@ -827,6 +829,41 @@ double Min::fnorm_inf() return norm_inf; } +/* ---------------------------------------------------------------------- + compute and return ||force||_max (inf norm per-vector) +------------------------------------------------------------------------- */ + +double Min::fnorm_max() +{ + int i,n; + double fdotf,*fatom; + + double local_norm_max = 0.0; + for (i = 0; i < nvec; i+=3) { + fdotf = fvec[i]*fvec[i]+fvec[i+1]*fvec[i+1]+fvec[i+2]*fvec[i+2]; + local_norm_max = MAX(fdotf,local_norm_max); + } + if (nextra_atom) { + for (int m = 0; m < nextra_atom; m++) { + fatom = fextra_atom[m]; + n = extra_nlen[m]; + for (i = 0; i < n; i+=3) + fdotf = fvec[i]*fvec[i]+fvec[i+1]*fvec[i+1]+fvec[i+2]*fvec[i+2]; + local_norm_max = MAX(fdotf,local_norm_max); + } + } + + double norm_max = 0.0; + MPI_Allreduce(&local_norm_max,&norm_max,1,MPI_DOUBLE,MPI_MAX,world); + + if (nextra_global) + for (i = 0; i < n; i+=3) + fdotf = fvec[i]*fvec[i]+fvec[i+1]*fvec[i+1]+fvec[i+2]*fvec[i+2]; + norm_max = MAX(fdotf,norm_max); + + return norm_max; +} + /* ---------------------------------------------------------------------- compute and return sum_i||mag. torque_i||_2 (in eV) ------------------------------------------------------------------------- */ @@ -842,10 +879,10 @@ double Min::total_torque() fmsq = ftotsqone = ftotsqall = 0.0; for (int i = 0; i < nlocal; i++) { - tx = fm[i][1] * sp[i][2] - fm[i][2] * sp[i][1]; - ty = fm[i][2] * sp[i][0] - fm[i][0] * sp[i][2]; - tz = fm[i][0] * sp[i][1] - fm[i][1] * sp[i][0]; - fmsq = tx * tx + ty * ty + tz * tz; + tx = fm[i][1]*sp[i][2] - fm[i][2]*sp[i][1]; + ty = fm[i][2]*sp[i][0] - fm[i][0]*sp[i][2]; + tz = fm[i][0]*sp[i][1] - fm[i][1]*sp[i][0]; + fmsq = tx*tx + ty*ty + tz*tz; ftotsqone += fmsq; } @@ -873,10 +910,10 @@ double Min::max_torque() fmsq = fmaxsqone = fmaxsqall = 0.0; for (int i = 0; i < nlocal; i++) { - tx = fm[i][1] * sp[i][2] - fm[i][2] * sp[i][1]; - ty = fm[i][2] * sp[i][0] - fm[i][0] * sp[i][2]; - tz = fm[i][0] * sp[i][1] - fm[i][1] * sp[i][0]; - fmsq = tx * tx + ty * ty + tz * tz; + tx = fm[i][1]*sp[i][2] - fm[i][2]*sp[i][1]; + ty = fm[i][2]*sp[i][0] - fm[i][0]*sp[i][2]; + tz = fm[i][0]*sp[i][1] - fm[i][1]*sp[i][0]; + fmsq = tx*tx + ty*ty + tz*tz; fmaxsqone = MAX(fmaxsqone,fmsq); } diff --git a/src/min.h b/src/min.h index e18d0dd677..ac7a3c1e9b 100644 --- a/src/min.h +++ b/src/min.h @@ -41,6 +41,7 @@ class Min : protected Pointers { virtual int modify_param(int, char **) {return 0;} double fnorm_sqr(); double fnorm_inf(); + double fnorm_max(); // methods for spin minimizers double max_torque(); @@ -64,7 +65,8 @@ class Min : protected Pointers { int linestyle; // 0 = backtrack, 1 = quadratic, 2 = forcezero // 3 = spin_cubic, 4 = spin_none - int normstyle; // 0 = Euclidean norm, 1 = inf. norm + int normstyle; // TWO or MAX flag for force norm evaluation + // int normstyle; // 0 = Euclidean norm, 1 = inf. norm int nelist_global,nelist_atom; // # of PE,virial computes to check int nvlist_global,nvlist_atom; diff --git a/src/min_cg.cpp b/src/min_cg.cpp index 2267a1ebb6..d98ec0ef97 100644 --- a/src/min_cg.cpp +++ b/src/min_cg.cpp @@ -35,7 +35,7 @@ MinCG::MinCG(LAMMPS *lmp) : MinLineSearch(lmp) {} int MinCG::iterate(int maxiter) { int i,m,n,fail,ntimestep; - double beta,gg,dot[2],dotall[2],fmax,fmaxall; + double beta,gg,dot[2],dotall[2],fmax; double *fatom,*gatom,*hatom; // nlimit = max # of CG iterations before restarting @@ -85,13 +85,12 @@ int MinCG::iterate(int maxiter) // force tolerance criterion - fmax = fmaxall = 0.0; dot[0] = dot[1] = 0.0; for (i = 0; i < nvec; i++) { dot[0] += fvec[i]*fvec[i]; dot[1] += fvec[i]*g[i]; - fmax = MAX(fmax,fvec[i]*fvec[i]); } + if (nextra_atom) for (m = 0; m < nextra_atom; m++) { fatom = fextra_atom[m]; @@ -104,16 +103,17 @@ int MinCG::iterate(int maxiter) } } MPI_Allreduce(dot,dotall,2,MPI_DOUBLE,MPI_SUM,world); - MPI_Allreduce(&fmax,&fmaxall,2,MPI_DOUBLE,MPI_MAX,world); if (nextra_global) for (i = 0; i < nextra_global; i++) { dotall[0] += fextra[i]*fextra[i]; dotall[1] += fextra[i]*gextra[i]; } - if (normstyle == 1) { // max force norm + fmax = 0.0; + if (normstyle == MAX) { // max force norm + fmax = fnorm_max(); if (fmax < update->ftol*update->ftol) return FTOL; - } else { // Euclidean force norm + } else { // Euclidean force 2-norm if (dotall[0] < update->ftol*update->ftol) return FTOL; } diff --git a/src/min_fire.cpp b/src/min_fire.cpp index 5b047ccd0e..dbb7f36148 100644 --- a/src/min_fire.cpp +++ b/src/min_fire.cpp @@ -250,15 +250,8 @@ int MinFire::iterate(int maxiter) // sync across replicas if running multi-replica minimization if (update->ftol > 0.0) { - if (normstyle == 1) { // max force norm - fdotf = fnorm_inf(); - fdotfloc = fdotf; - MPI_Allreduce(&fdotfloc,&fdotf,1,MPI_INT,MPI_MAX,universe->uworld); - } else { // Euclidean force norm - fdotf = fnorm_sqr(); - fdotfloc = fdotf; - MPI_Allreduce(&fdotfloc,&fdotf,1,MPI_INT,MPI_SUM,universe->uworld); - } + if (normstyle == MAX) fdotf = fnorm_inf(); // max force norm + else fdotf = fnorm_sqr(); // Euclidean force 2-norm if (update->multireplica == 0) { if (fdotf < update->ftol*update->ftol) return FTOL; } else { diff --git a/src/min_hftn.cpp b/src/min_hftn.cpp index 3c2cff9205..63432aab63 100644 --- a/src/min_hftn.cpp +++ b/src/min_hftn.cpp @@ -113,7 +113,7 @@ void MinHFTN::init() { Min::init(); - if (normstyle == 1) + if (normstyle == MAX) error->all(FLERR,"Incorrect min_modify option"); for (int i = 1; i < NUM_HFTN_ATOM_BASED_VECTORS; i++) { diff --git a/src/min_quickmin.cpp b/src/min_quickmin.cpp index 3450f7785e..6846aaba0a 100644 --- a/src/min_quickmin.cpp +++ b/src/min_quickmin.cpp @@ -215,15 +215,8 @@ int MinQuickMin::iterate(int maxiter) // sync across replicas if running multi-replica minimization if (update->ftol > 0.0) { - if (normstyle == 1) { // max force norm - fdotf = fnorm_inf(); - fdotfloc = fdotf; - MPI_Allreduce(&fdotfloc,&fdotf,1,MPI_INT,MPI_MAX,universe->uworld); - } else { // Euclidean force norm - fdotf = fnorm_sqr(); - fdotfloc = fdotf; - MPI_Allreduce(&fdotfloc,&fdotf,1,MPI_INT,MPI_SUM,universe->uworld); - } + if (normstyle == MAX) fdotfloc = fnorm_max(); // max force norm + else fdotf = fnorm_sqr(); // Euclidean force 2-norm if (update->multireplica == 0) { if (fdotf < update->ftol*update->ftol) return FTOL; } else { diff --git a/src/min_sd.cpp b/src/min_sd.cpp index dd59c9d2d6..3ded85990d 100644 --- a/src/min_sd.cpp +++ b/src/min_sd.cpp @@ -34,7 +34,7 @@ MinSD::MinSD(LAMMPS *lmp) : MinLineSearch(lmp) {} int MinSD::iterate(int maxiter) { int i,m,n,fail,ntimestep; - double fdotf; + double fdotf,fdotfloc; double *fatom,*hatom; // initialize working vectors @@ -77,8 +77,8 @@ int MinSD::iterate(int maxiter) // force tolerance criterion - if (normstyle == 1) fdotf = fnorm_inf(); // max force norm - else fdotf = fnorm_sqr(); // Euclidean force norm + if (normstyle == MAX) fdotf = fnorm_max(); // max force norm + else fdotf = fnorm_sqr(); // Euclidean force 2-norm if (fdotf < update->ftol*update->ftol) return FTOL; // set new search direction h to f = -Grad(x) From d0d2797b41f1810cddbd809d508d8286e8ae6f71 Mon Sep 17 00:00:00 2001 From: charlie sievers Date: Mon, 23 Sep 2019 11:46:16 -0700 Subject: [PATCH 170/192] Fixed conflicts --- src/fix_langevin.cpp | 1 + src/fix_langevin.h | 2 +- 2 files changed, 2 insertions(+), 1 deletion(-) diff --git a/src/fix_langevin.cpp b/src/fix_langevin.cpp index cd77883c76..dc1b04c3d7 100644 --- a/src/fix_langevin.cpp +++ b/src/fix_langevin.cpp @@ -97,6 +97,7 @@ FixLangevin::FixLangevin(LAMMPS *lmp, int narg, char **arg) : ascale = 0.0; gjfflag = 0; fsflag = 0; + nvalues = 0; oflag = 0; tallyflag = 0; zeroflag = 0; diff --git a/src/fix_langevin.h b/src/fix_langevin.h index 349a9d2dd9..b20c64f903 100644 --- a/src/fix_langevin.h +++ b/src/fix_langevin.h @@ -47,7 +47,7 @@ class FixLangevin : public Fix { int unpack_exchange(int, double *); protected: - int gjfflag,fsflag,oflag,tallyflag,zeroflag,tbiasflag; + int gjfflag,fsflag,nvalues,oflag,tallyflag,zeroflag,tbiasflag; int flangevin_allocated; double ascale; double t_start,t_stop,t_period,t_target; From a44f2cc3bbfd3ca9b6cbda34e5b3f0862c9dff15 Mon Sep 17 00:00:00 2001 From: charlie sievers Date: Mon, 23 Sep 2019 11:48:54 -0700 Subject: [PATCH 171/192] changed flag name in fix_langevin --- src/fix_langevin.cpp | 2 +- src/fix_langevin.h | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/src/fix_langevin.cpp b/src/fix_langevin.cpp index dc1b04c3d7..dc2a237fa6 100644 --- a/src/fix_langevin.cpp +++ b/src/fix_langevin.cpp @@ -96,7 +96,7 @@ FixLangevin::FixLangevin(LAMMPS *lmp, int narg, char **arg) : for (int i = 1; i <= atom->ntypes; i++) ratio[i] = 1.0; ascale = 0.0; gjfflag = 0; - fsflag = 0; + osflag = 0; nvalues = 0; oflag = 0; tallyflag = 0; diff --git a/src/fix_langevin.h b/src/fix_langevin.h index b20c64f903..f3b396742d 100644 --- a/src/fix_langevin.h +++ b/src/fix_langevin.h @@ -47,7 +47,7 @@ class FixLangevin : public Fix { int unpack_exchange(int, double *); protected: - int gjfflag,fsflag,nvalues,oflag,tallyflag,zeroflag,tbiasflag; + int gjfflag,osflag,nvalues,oflag,tallyflag,zeroflag,tbiasflag; int flangevin_allocated; double ascale; double t_start,t_stop,t_period,t_target; From 9635d228c216e1d1b1a884adf1b8d42a40f396d2 Mon Sep 17 00:00:00 2001 From: charlie sievers Date: Mon, 23 Sep 2019 11:53:03 -0700 Subject: [PATCH 172/192] switched fsflag for nvalues to reuse old name --- src/fix_langevin.cpp | 15 +++++++-------- src/fix_langevin.h | 2 +- 2 files changed, 8 insertions(+), 9 deletions(-) diff --git a/src/fix_langevin.cpp b/src/fix_langevin.cpp index dc2a237fa6..20c17982b9 100644 --- a/src/fix_langevin.cpp +++ b/src/fix_langevin.cpp @@ -96,8 +96,7 @@ FixLangevin::FixLangevin(LAMMPS *lmp, int narg, char **arg) : for (int i = 1; i <= atom->ntypes; i++) ratio[i] = 1.0; ascale = 0.0; gjfflag = 0; - osflag = 0; - nvalues = 0; + nvalues = 0; // flag for onsite velocity oflag = 0; tallyflag = 0; zeroflag = 0; @@ -111,11 +110,11 @@ FixLangevin::FixLangevin(LAMMPS *lmp, int narg, char **arg) : iarg += 2; } else if (strcmp(arg[iarg],"gjf") == 0) { if (iarg+2 > narg) error->all(FLERR,"Illegal fix langevin command"); - if (strcmp(arg[iarg+1],"no") == 0) {gjfflag = 0; fsflag = 0;} + if (strcmp(arg[iarg+1],"no") == 0) {gjfflag = 0; nvalues = 0;} else if (strcmp(arg[iarg+1],"yes") == 0) error->all(FLERR,"Fix langevin gjf yes is outdated, please use vhalf or vfull"); - else if (strcmp(arg[iarg+1],"vhalf") == 0) {gjfflag = 1; fsflag = 0;} - else if (strcmp(arg[iarg+1],"vfull") == 0) {gjfflag = 1; fsflag = 1;} + else if (strcmp(arg[iarg+1],"vhalf") == 0) {gjfflag = 1; nvalues = 0;} + else if (strcmp(arg[iarg+1],"vfull") == 0) {gjfflag = 1; nvalues = 1;} else error->all(FLERR,"Illegal fix langevin command"); iarg += 2; } else if (strcmp(arg[iarg],"omega") == 0) { @@ -438,7 +437,7 @@ void FixLangevin::post_force(int /*vflag*/) if (tstyle == ATOM) if (gjfflag) - if (tallyflag || fsflag) + if (tallyflag || nvalues) if (tbiasflag == BIAS) if (rmass) if (zeroflag) post_force_templated<1,1,1,1,1,1>(); @@ -960,7 +959,7 @@ void FixLangevin::end_of_step() tmp[0] = v[i][0]; tmp[1] = v[i][1]; tmp[2] = v[i][2]; - if (!fsflag){ + if (!nvalues){ v[i][0] = lv[i][0]; v[i][1] = lv[i][1]; v[i][2] = lv[i][2]; @@ -1102,7 +1101,7 @@ double FixLangevin::memory_usage() { double bytes = 0.0; if (gjfflag) bytes += atom->nmax*6 * sizeof(double); - if (tallyflag || fsflag) bytes += atom->nmax*3 * sizeof(double); + if (tallyflag || nvalues) bytes += atom->nmax*3 * sizeof(double); if (tforce) bytes += atom->nmax * sizeof(double); return bytes; } diff --git a/src/fix_langevin.h b/src/fix_langevin.h index f3b396742d..24555a85a6 100644 --- a/src/fix_langevin.h +++ b/src/fix_langevin.h @@ -47,7 +47,7 @@ class FixLangevin : public Fix { int unpack_exchange(int, double *); protected: - int gjfflag,osflag,nvalues,oflag,tallyflag,zeroflag,tbiasflag; + int gjfflag,nvalues,oflag,tallyflag,zeroflag,tbiasflag; int flangevin_allocated; double ascale; double t_start,t_stop,t_period,t_target; From e51fc5a5bf3c55aca55c873332f2248df177c6b8 Mon Sep 17 00:00:00 2001 From: charlie sievers Date: Mon, 23 Sep 2019 11:54:27 -0700 Subject: [PATCH 173/192] remove comment to resolve conflict --- src/fix_langevin.cpp | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/fix_langevin.cpp b/src/fix_langevin.cpp index 20c17982b9..bcea14bd06 100644 --- a/src/fix_langevin.cpp +++ b/src/fix_langevin.cpp @@ -96,7 +96,7 @@ FixLangevin::FixLangevin(LAMMPS *lmp, int narg, char **arg) : for (int i = 1; i <= atom->ntypes; i++) ratio[i] = 1.0; ascale = 0.0; gjfflag = 0; - nvalues = 0; // flag for onsite velocity + nvalues = 0; oflag = 0; tallyflag = 0; zeroflag = 0; From bc0ff0db618be4d1f8b33aa938aebbd5de7e6abc Mon Sep 17 00:00:00 2001 From: julient31 Date: Mon, 23 Sep 2019 13:48:33 -0600 Subject: [PATCH 174/192] Commit2 JT 092319 - added enum to min.h (for norm choice) - completed doc min_modify - corrected torque tol issue in spin/min --- doc/src/min_modify.txt | 3 +++ examples/SPIN/spinmin/in.spinmin_lbfgs.bfo | 1 + src/SPIN/min_spin.cpp | 19 +++++-------------- src/SPIN/min_spin_cg.cpp | 20 +++++--------------- src/SPIN/min_spin_lbfgs.cpp | 20 +++++--------------- src/min.cpp | 2 -- src/min.h | 2 ++ 7 files changed, 21 insertions(+), 46 deletions(-) diff --git a/doc/src/min_modify.txt b/doc/src/min_modify.txt index b941a33559..b7c85a190b 100644 --- a/doc/src/min_modify.txt +++ b/doc/src/min_modify.txt @@ -86,6 +86,9 @@ all atoms :c,image(Eqs/norm_max.jpg) +For the min styles {spin}, {spin/cg} and {spin/lbfgs}, the force +norm is replaced by the spin-torque norm. + Keywords {alpha_damp} and {discrete_factor} only make sense when a "min_spin"_min_spin.html command is declared. Keyword {alpha_damp} defines an analog of a magnetic Gilbert diff --git a/examples/SPIN/spinmin/in.spinmin_lbfgs.bfo b/examples/SPIN/spinmin/in.spinmin_lbfgs.bfo index a73b863b11..56cd6b8fae 100644 --- a/examples/SPIN/spinmin/in.spinmin_lbfgs.bfo +++ b/examples/SPIN/spinmin/in.spinmin_lbfgs.bfo @@ -51,4 +51,5 @@ dump 1 all custom 50 dump.lammpstrj type x y z c_outsp[1] c_outsp[2] c_outsp[3 min_style spin/lbfgs # min_modify line spin_cubic discrete_factor 10.0 +min_modify norm max minimize 1.0e-15 1.0e-10 10000 1000 diff --git a/src/SPIN/min_spin.cpp b/src/SPIN/min_spin.cpp index 947e281b42..5c7e7eee30 100644 --- a/src/SPIN/min_spin.cpp +++ b/src/SPIN/min_spin.cpp @@ -116,7 +116,7 @@ void MinSpin::reset_vectors() int MinSpin::iterate(int maxiter) { bigint ntimestep; - double fmdotfm,fmsq,fmsqall; + double fmdotfm,fmsq; int flag,flagall; for (int iter = 0; iter < maxiter; iter++) { @@ -163,20 +163,11 @@ int MinSpin::iterate(int maxiter) // magnetic torque tolerance criterion // sync across replicas if running multi-replica minimization - fmdotfm = fmsq = fmsqall = 0.0; + fmdotfm = fmsq = 0.0; if (update->ftol > 0.0) { - if (normstyle == 1) { // max torque norm - fmsq = max_torque(); - fmsqall = fmsq; - if (update->multireplica == 0) - MPI_Allreduce(&fmsq,&fmsqall,1,MPI_INT,MPI_MAX,universe->uworld); - } else { // Euclidean torque norm - fmsq = total_torque(); - fmsqall = fmsq; - if (update->multireplica == 0) - MPI_Allreduce(&fmsq,&fmsqall,1,MPI_INT,MPI_SUM,universe->uworld); - } - fmdotfm = fmsqall*fmsqall; + if (normstyle == MAX) fmsq = max_torque(); // max norm + else fmsq = total_torque(); // Euclidean 2-norm + fmdotfm = fmsq*fmsq; if (update->multireplica == 0) { if (fmdotfm < update->ftol*update->ftol) return FTOL; } else { diff --git a/src/SPIN/min_spin_cg.cpp b/src/SPIN/min_spin_cg.cpp index 322915c0f3..a87d3aaa36 100644 --- a/src/SPIN/min_spin_cg.cpp +++ b/src/SPIN/min_spin_cg.cpp @@ -60,7 +60,6 @@ static const char cite_minstyle_spin_cg[] = #define DELAYSTEP 5 - /* ---------------------------------------------------------------------- */ MinSpinCG::MinSpinCG(LAMMPS *lmp) : @@ -183,7 +182,7 @@ int MinSpinCG::iterate(int maxiter) { int nlocal = atom->nlocal; bigint ntimestep; - double fmdotfm,fmsq,fmsqall; + double fmdotfm,fmsq; int flag, flagall; double **sp = atom->sp; double der_e_cur_tmp = 0.0; @@ -269,20 +268,11 @@ int MinSpinCG::iterate(int maxiter) // magnetic torque tolerance criterion // sync across replicas if running multi-replica minimization - fmdotfm = fmsq = fmsqall = 0.0; + fmdotfm = fmsq = 0.0; if (update->ftol > 0.0) { - if (normstyle == 1) { // max torque norm - fmsq = max_torque(); - fmsqall = fmsq; - if (update->multireplica == 0) - MPI_Allreduce(&fmsq,&fmsqall,1,MPI_INT,MPI_MAX,universe->uworld); - } else { // Euclidean torque norm - fmsq = total_torque(); - fmsqall = fmsq; - if (update->multireplica == 0) - MPI_Allreduce(&fmsq,&fmsqall,1,MPI_INT,MPI_SUM,universe->uworld); - } - fmdotfm = fmsqall*fmsqall; + if (normstyle == MAX) fmsq = max_torque(); // max norm + else fmsq = total_torque(); // Euclidean 2-norm + fmdotfm = fmsq*fmsq; if (update->multireplica == 0) { if (fmdotfm < update->ftol*update->ftol) return FTOL; } else { diff --git a/src/SPIN/min_spin_lbfgs.cpp b/src/SPIN/min_spin_lbfgs.cpp index 891dec5c93..e161aa2a30 100644 --- a/src/SPIN/min_spin_lbfgs.cpp +++ b/src/SPIN/min_spin_lbfgs.cpp @@ -59,7 +59,6 @@ static const char cite_minstyle_spin_lbfgs[] = #define DELAYSTEP 5 - /* ---------------------------------------------------------------------- */ MinSpinLBFGS::MinSpinLBFGS(LAMMPS *lmp) : @@ -192,7 +191,7 @@ int MinSpinLBFGS::iterate(int maxiter) { int nlocal = atom->nlocal; bigint ntimestep; - double fmdotfm,fmsq,fmsqall; + double fmdotfm,fmsq; int flag, flagall; double **sp = atom->sp; double der_e_cur_tmp = 0.0; @@ -284,20 +283,11 @@ int MinSpinLBFGS::iterate(int maxiter) // magnetic torque tolerance criterion // sync across replicas if running multi-replica minimization - fmdotfm = fmsq = fmsqall = 0.0; + fmdotfm = fmsq = 0.0; if (update->ftol > 0.0) { - if (normstyle == 1) { // max torque norm - fmsq = max_torque(); - fmsqall = fmsq; - if (update->multireplica == 0) - MPI_Allreduce(&fmsq,&fmsqall,1,MPI_INT,MPI_MAX,universe->uworld); - } else { // Euclidean torque norm - fmsq = total_torque(); - fmsqall = fmsq; - if (update->multireplica == 0) - MPI_Allreduce(&fmsq,&fmsqall,1,MPI_INT,MPI_SUM,universe->uworld); - } - fmdotfm = fmsqall*fmsqall; + if (normstyle == MAX) fmsq = max_torque(); // max norm + else fmsq = total_torque(); // Euclidean 2-norm + fmdotfm = fmsq*fmsq; if (update->multireplica == 0) { if (fmdotfm < update->ftol*update->ftol) return FTOL; } else { diff --git a/src/min.cpp b/src/min.cpp index 33643d4837..23c3021010 100644 --- a/src/min.cpp +++ b/src/min.cpp @@ -49,8 +49,6 @@ using namespace LAMMPS_NS; using namespace MathConst; -enum{TWO,MAX} - /* ---------------------------------------------------------------------- */ Min::Min(LAMMPS *lmp) : Pointers(lmp) diff --git a/src/min.h b/src/min.h index ac7a3c1e9b..303e2123d8 100644 --- a/src/min.h +++ b/src/min.h @@ -43,6 +43,8 @@ class Min : protected Pointers { double fnorm_inf(); double fnorm_max(); + enum{TWO,MAX}; + // methods for spin minimizers double max_torque(); double total_torque(); From 34f81041461913ab6e2515a026aa4c493f5ddb5f Mon Sep 17 00:00:00 2001 From: julient31 Date: Mon, 23 Sep 2019 13:52:48 -0600 Subject: [PATCH 175/192] Commit3 JT 092319 - corrected a typo in doc/src/min_modify.txt --- doc/src/min_modify.txt | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/doc/src/min_modify.txt b/doc/src/min_modify.txt index b7c85a190b..209e9e4a67 100644 --- a/doc/src/min_modify.txt +++ b/doc/src/min_modify.txt @@ -81,7 +81,7 @@ global force vector: :c,image(Eqs/norm_two.jpg) The {max} norm computes the length of the 3-vector force -for each atom (2-norm), and takes the maximum value of those accross +for each atom (2-norm), and takes the maximum value of those across all atoms :c,image(Eqs/norm_max.jpg) From 61f4a4c4989e5fa1df89bb570e9f017328ecf03d Mon Sep 17 00:00:00 2001 From: charlie sievers Date: Mon, 23 Sep 2019 13:18:31 -0700 Subject: [PATCH 176/192] add back fsflag fix_langevin --- src/fix_langevin.cpp | 13 +++++++------ src/fix_langevin.h | 2 +- 2 files changed, 8 insertions(+), 7 deletions(-) diff --git a/src/fix_langevin.cpp b/src/fix_langevin.cpp index bcea14bd06..2e114328ec 100644 --- a/src/fix_langevin.cpp +++ b/src/fix_langevin.cpp @@ -97,6 +97,7 @@ FixLangevin::FixLangevin(LAMMPS *lmp, int narg, char **arg) : ascale = 0.0; gjfflag = 0; nvalues = 0; + fsflag = 0; oflag = 0; tallyflag = 0; zeroflag = 0; @@ -110,11 +111,11 @@ FixLangevin::FixLangevin(LAMMPS *lmp, int narg, char **arg) : iarg += 2; } else if (strcmp(arg[iarg],"gjf") == 0) { if (iarg+2 > narg) error->all(FLERR,"Illegal fix langevin command"); - if (strcmp(arg[iarg+1],"no") == 0) {gjfflag = 0; nvalues = 0;} + if (strcmp(arg[iarg+1],"no") == 0) {gjfflag = 0; fsflag = 0;} else if (strcmp(arg[iarg+1],"yes") == 0) error->all(FLERR,"Fix langevin gjf yes is outdated, please use vhalf or vfull"); - else if (strcmp(arg[iarg+1],"vhalf") == 0) {gjfflag = 1; nvalues = 0;} - else if (strcmp(arg[iarg+1],"vfull") == 0) {gjfflag = 1; nvalues = 1;} + else if (strcmp(arg[iarg+1],"vhalf") == 0) {gjfflag = 1; fsflag = 0;} + else if (strcmp(arg[iarg+1],"vfull") == 0) {gjfflag = 1; fsflag = 1;} else error->all(FLERR,"Illegal fix langevin command"); iarg += 2; } else if (strcmp(arg[iarg],"omega") == 0) { @@ -437,7 +438,7 @@ void FixLangevin::post_force(int /*vflag*/) if (tstyle == ATOM) if (gjfflag) - if (tallyflag || nvalues) + if (tallyflag || fsflag) if (tbiasflag == BIAS) if (rmass) if (zeroflag) post_force_templated<1,1,1,1,1,1>(); @@ -959,7 +960,7 @@ void FixLangevin::end_of_step() tmp[0] = v[i][0]; tmp[1] = v[i][1]; tmp[2] = v[i][2]; - if (!nvalues){ + if (!fsflag){ v[i][0] = lv[i][0]; v[i][1] = lv[i][1]; v[i][2] = lv[i][2]; @@ -1101,7 +1102,7 @@ double FixLangevin::memory_usage() { double bytes = 0.0; if (gjfflag) bytes += atom->nmax*6 * sizeof(double); - if (tallyflag || nvalues) bytes += atom->nmax*3 * sizeof(double); + if (tallyflag || fsflag) bytes += atom->nmax*3 * sizeof(double); if (tforce) bytes += atom->nmax * sizeof(double); return bytes; } diff --git a/src/fix_langevin.h b/src/fix_langevin.h index 24555a85a6..28e98472f6 100644 --- a/src/fix_langevin.h +++ b/src/fix_langevin.h @@ -47,7 +47,7 @@ class FixLangevin : public Fix { int unpack_exchange(int, double *); protected: - int gjfflag,nvalues,oflag,tallyflag,zeroflag,tbiasflag; + int gjfflag,nvalues,fsflag,oflag,tallyflag,zeroflag,tbiasflag; int flangevin_allocated; double ascale; double t_start,t_stop,t_period,t_target; From 876a57209fbefdb6e689fa330030d6f4f3ad067f Mon Sep 17 00:00:00 2001 From: charlie sievers Date: Mon, 23 Sep 2019 13:29:10 -0700 Subject: [PATCH 177/192] resolve fsflag conflict fix_langevin --- src/fix_langevin.cpp | 14 +++++++------- src/fix_langevin.h | 2 +- 2 files changed, 8 insertions(+), 8 deletions(-) diff --git a/src/fix_langevin.cpp b/src/fix_langevin.cpp index 2e114328ec..b5777cb5a4 100644 --- a/src/fix_langevin.cpp +++ b/src/fix_langevin.cpp @@ -97,10 +97,10 @@ FixLangevin::FixLangevin(LAMMPS *lmp, int narg, char **arg) : ascale = 0.0; gjfflag = 0; nvalues = 0; - fsflag = 0; oflag = 0; tallyflag = 0; zeroflag = 0; + osflag = 0; int iarg = 7; while (iarg < narg) { @@ -111,11 +111,11 @@ FixLangevin::FixLangevin(LAMMPS *lmp, int narg, char **arg) : iarg += 2; } else if (strcmp(arg[iarg],"gjf") == 0) { if (iarg+2 > narg) error->all(FLERR,"Illegal fix langevin command"); - if (strcmp(arg[iarg+1],"no") == 0) {gjfflag = 0; fsflag = 0;} + if (strcmp(arg[iarg+1],"no") == 0) {gjfflag = 0; osflag = 0;} else if (strcmp(arg[iarg+1],"yes") == 0) error->all(FLERR,"Fix langevin gjf yes is outdated, please use vhalf or vfull"); - else if (strcmp(arg[iarg+1],"vhalf") == 0) {gjfflag = 1; fsflag = 0;} - else if (strcmp(arg[iarg+1],"vfull") == 0) {gjfflag = 1; fsflag = 1;} + else if (strcmp(arg[iarg+1],"vhalf") == 0) {gjfflag = 1; osflag = 0;} + else if (strcmp(arg[iarg+1],"vfull") == 0) {gjfflag = 1; osflag = 1;} else error->all(FLERR,"Illegal fix langevin command"); iarg += 2; } else if (strcmp(arg[iarg],"omega") == 0) { @@ -438,7 +438,7 @@ void FixLangevin::post_force(int /*vflag*/) if (tstyle == ATOM) if (gjfflag) - if (tallyflag || fsflag) + if (tallyflag || osflag) if (tbiasflag == BIAS) if (rmass) if (zeroflag) post_force_templated<1,1,1,1,1,1>(); @@ -960,7 +960,7 @@ void FixLangevin::end_of_step() tmp[0] = v[i][0]; tmp[1] = v[i][1]; tmp[2] = v[i][2]; - if (!fsflag){ + if (!osflag){ v[i][0] = lv[i][0]; v[i][1] = lv[i][1]; v[i][2] = lv[i][2]; @@ -1102,7 +1102,7 @@ double FixLangevin::memory_usage() { double bytes = 0.0; if (gjfflag) bytes += atom->nmax*6 * sizeof(double); - if (tallyflag || fsflag) bytes += atom->nmax*3 * sizeof(double); + if (tallyflag || osflag) bytes += atom->nmax*3 * sizeof(double); if (tforce) bytes += atom->nmax * sizeof(double); return bytes; } diff --git a/src/fix_langevin.h b/src/fix_langevin.h index 28e98472f6..868b71a44d 100644 --- a/src/fix_langevin.h +++ b/src/fix_langevin.h @@ -47,7 +47,7 @@ class FixLangevin : public Fix { int unpack_exchange(int, double *); protected: - int gjfflag,nvalues,fsflag,oflag,tallyflag,zeroflag,tbiasflag; + int gjfflag,nvalues,osflag,oflag,tallyflag,zeroflag,tbiasflag; int flangevin_allocated; double ascale; double t_start,t_stop,t_period,t_target; From cf13284bf42124e8932196ae7a90695a81fc1b31 Mon Sep 17 00:00:00 2001 From: charlie sievers Date: Mon, 23 Sep 2019 13:31:50 -0700 Subject: [PATCH 178/192] change fsflag in fix_langevin_kokkos --- src/KOKKOS/fix_langevin_kokkos.cpp | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/src/KOKKOS/fix_langevin_kokkos.cpp b/src/KOKKOS/fix_langevin_kokkos.cpp index 0618631581..426bcb49e3 100644 --- a/src/KOKKOS/fix_langevin_kokkos.cpp +++ b/src/KOKKOS/fix_langevin_kokkos.cpp @@ -816,7 +816,7 @@ void FixLangevinKokkos::end_of_step_item(int i) const { tmp[0] = v(i,0); tmp[1] = v(i,1); tmp[2] = v(i,2); - if (!fsflag){ + if (!osflag){ v(i,0) = d_lv(i,0); v(i,1) = d_lv(i,1); v(i,2) = d_lv(i,2); @@ -847,7 +847,7 @@ void FixLangevinKokkos::end_of_step_rmass_item(int i) const tmp[0] = v(i,0); tmp[1] = v(i,1); tmp[2] = v(i,2); - if (!fsflag){ + if (!osflag){ v(i,0) = d_lv(i,0); v(i,1) = d_lv(i,1); v(i,2) = d_lv(i,2); From a0f0c2357883dc437d790e3264fa8f593ea91300 Mon Sep 17 00:00:00 2001 From: julient31 Date: Mon, 23 Sep 2019 14:32:39 -0600 Subject: [PATCH 179/192] Commit3 JT 092319 - corrected src/min.h merging conflict --- src/min.h | 5 ----- 1 file changed, 5 deletions(-) diff --git a/src/min.h b/src/min.h index 8bc6284b4b..e03b034147 100644 --- a/src/min.h +++ b/src/min.h @@ -39,7 +39,6 @@ class Min : protected Pointers { virtual bigint memory_usage() {return 0;} void modify_params(int, char **); virtual int modify_param(int, char **) {return 0;} -<<<<<<< HEAD double fnorm_sqr(); double fnorm_inf(); double fnorm_max(); @@ -49,10 +48,6 @@ class Min : protected Pointers { // methods for spin minimizers double max_torque(); double total_torque(); -======= - virtual double fnorm_sqr(); - virtual double fnorm_inf(); ->>>>>>> aa2b885783e471ed622e1402adeed67e3224aa53 virtual void init_style() {} virtual void setup_style() = 0; From af1e119a7cb940e9a3cab8c5a6a1583ea0856bfe Mon Sep 17 00:00:00 2001 From: julient31 Date: Mon, 23 Sep 2019 17:30:16 -0600 Subject: [PATCH 180/192] Commit JT 092319 - initial commit - started correction restart pair_spin_neel.cpp --- src/SPIN/pair_spin_neel.cpp | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/src/SPIN/pair_spin_neel.cpp b/src/SPIN/pair_spin_neel.cpp index 355ba20f39..72d445a184 100644 --- a/src/SPIN/pair_spin_neel.cpp +++ b/src/SPIN/pair_spin_neel.cpp @@ -694,11 +694,11 @@ void PairSpinNeel::read_restart(FILE *fp) fread(&g1[i][j],sizeof(double),1,fp); fread(&g1_mech[i][j],sizeof(double),1,fp); fread(&g2[i][j],sizeof(double),1,fp); - fread(&g2[i][j],sizeof(double),1,fp); + fread(&g3[i][j],sizeof(double),1,fp); fread(&q1[i][j],sizeof(double),1,fp); fread(&q1_mech[i][j],sizeof(double),1,fp); fread(&q2[i][j],sizeof(double),1,fp); - fread(&q2[i][j],sizeof(double),1,fp); + fread(&q3[i][j],sizeof(double),1,fp); fread(&cut_spin_neel[i][j],sizeof(double),1,fp); } MPI_Bcast(&g1[i][j],1,MPI_DOUBLE,0,world); From 3f0d1cb270963d44fed5000372233f66bed79013 Mon Sep 17 00:00:00 2001 From: Christoph Junghans Date: Tue, 24 Sep 2019 13:15:48 -0600 Subject: [PATCH 181/192] cmake: LMP_KOKKOS define is always needed --- cmake/Modules/Packages/KOKKOS.cmake | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/cmake/Modules/Packages/KOKKOS.cmake b/cmake/Modules/Packages/KOKKOS.cmake index d0f67243cf..4134fed597 100644 --- a/cmake/Modules/Packages/KOKKOS.cmake +++ b/cmake/Modules/Packages/KOKKOS.cmake @@ -6,7 +6,6 @@ if(PKG_KOKKOS) else() set(LAMMPS_LIB_KOKKOS_SRC_DIR ${LAMMPS_LIB_SOURCE_DIR}/kokkos) set(LAMMPS_LIB_KOKKOS_BIN_DIR ${LAMMPS_LIB_BINARY_DIR}/kokkos) - add_definitions(-DLMP_KOKKOS) add_subdirectory(${LAMMPS_LIB_KOKKOS_SRC_DIR} ${LAMMPS_LIB_KOKKOS_BIN_DIR}) set(Kokkos_INCLUDE_DIRS ${LAMMPS_LIB_KOKKOS_SRC_DIR}/core/src @@ -16,6 +15,7 @@ if(PKG_KOKKOS) include_directories(${Kokkos_INCLUDE_DIRS}) list(APPEND LAMMPS_LINK_LIBS kokkos) endif() + add_definitions(-DLMP_KOKKOS) set(KOKKOS_PKG_SOURCES_DIR ${LAMMPS_SOURCE_DIR}/KOKKOS) set(KOKKOS_PKG_SOURCES ${KOKKOS_PKG_SOURCES_DIR}/kokkos.cpp From d9306a58656925e94f00fe27b7a2a387308f78c4 Mon Sep 17 00:00:00 2001 From: julient31 Date: Tue, 24 Sep 2019 13:58:56 -0600 Subject: [PATCH 182/192] Commit JT 092419 - added inf norm option --- doc/src/Eqs/norm_inf.jpg | Bin 0 -> 14859 bytes doc/src/Eqs/norm_inf.tex | 15 +++++++++++++++ doc/src/min_modify.txt | 8 +++++++- src/SPIN/min_spin.cpp | 6 ++++-- src/SPIN/min_spin_cg.cpp | 6 ++++-- src/SPIN/min_spin_lbfgs.cpp | 6 ++++-- src/min.cpp | 34 ++++++++++++++++++++++++++++++++++ src/min.h | 8 ++++---- src/min_cg.cpp | 10 +++++++--- src/min_fire.cpp | 7 +++++-- src/min_quickmin.cpp | 7 +++++-- src/min_sd.cpp | 7 +++++-- 12 files changed, 94 insertions(+), 20 deletions(-) create mode 100644 doc/src/Eqs/norm_inf.jpg create mode 100644 doc/src/Eqs/norm_inf.tex diff --git a/doc/src/Eqs/norm_inf.jpg b/doc/src/Eqs/norm_inf.jpg new file mode 100644 index 0000000000000000000000000000000000000000..42a2afb3d299b7ef031d9def8fe7eb1de0b7d931 GIT binary patch literal 14859 zcmb8W1yo$k(kMEEdl=l^-Q6L;;2zvvgS)#18C-$~cL*NbA-F?;paB8|Pe`~!zVn}R z-d%6qcVDl)W@dMnbyZhY+dQv6?*K3rWWllkAhfUmSpb0N4S+NN76#_!ffhLE1CIm` z4+jU2f{2KKgoc8KhKhoUijIMWiH-rnKt;vG!vtaD;Ns$fUqFo^ALap00h7SV1YouzY9D9A}kyd z%u6fIf7ky5@VpK{g9QR$FkvwP0N}0sztR40eo#zQYVkwy{#AfOK_qCmVQ2CzD%lYshbi(lxG8a(Fop3=klNCi9{FDcb(rJN|-j zrlZ~b+__7e;g&+8#=IQPyv*xK**u34H>e!?vEj$CtUL>l4=EH7HW~G!RG9_&@Q^BE zZpj{~}o)B4rWD;fr7%ij)|N8PwSP$(my!3iuqRAsc8Bk>biNlkv!<5ci0l>?qtJ-C!{`eGfNC<_BavJFLa8hs ztRVYQ{%0AILj^bTs5%>(IY%a$q6o5hG1Z01s6D0hupj>ggJBDYT$z1UOd!||RXE}J z8qFkB+0xv5<;qy2O3lf`4*&o)O8+I81o7m~HFa2R4uhMT4^|W&(f~`$CsnF|a}DNB z-O-%fUFU4JL~t{dhdH*P$$l^bCgxIJLX8dpz*cD}17^VUG@rr>tji&WX!{R5sij^M zYtD2i6;D%VzngL4)EDzgIr2$>i_)ncl3Pg#|=<-j@WeHGEA-r@? zZyEzGGL8D=2uC_*3tI|q2p8gLeAAkYHDE#PpMk=|nW4GjV_(*#Ybql`eVYpt0E7d= zz`-KI!N9(ZWB@!2EF1y=h=_^H!-s{#1;WOo;Na!Qr=*jhp{3?Dg?c^`G#&uqVV(h7 zcm)r4LG-jKwfnS2!R@CNW^KkYQ9&9uqlnJJ$C>2EwRTRg3`XP>Rf_KZBn&j}bikc) zaRrw?WfT{h9U~b1baPbuD!@@A&Djf?XL&U*8ifhjZPfHHi(_6O80*>KnD zQv8j~_M$@jQ}i)q>JEVynF|o#-Fy)2eew=_ioT z?kOmL(kMR0pSXtJ)I{C$yLfl8df{VF=56ZUn;2I%+YgxO7V|_28Jmg~k8~4C1pcNI zx3$bK5Rl;euIQSm1qPc~o%Kj#Ky%dr3Kqa>wjh3m+)^fDrlfP^I zy^8Z`6(yyDr6aS?cSm>|n(~c~UUBiboAV2+%#hTuwxOI@Ew0_g1M2d?{ZSjoRc68d z3QnfeOpG$){GPLBxSLl%p@+1g+Tr6LIVRmM$PJ$3#u`fn8cX52BC$U5hSH$6Aq`r( z!^vNr&B`Sozkfq{VZR#l zBShGkV@Ur%8*YDyZ!)Z|l zpx%EZdIos>7ozFIkU1J|4WDsD5(uqpqebcdB7OA*__VC9S5SQ1+w zoO4-jSm1&J^Nh6aheEA=-?_GJ2WbYNaCy3Qx7Lfa)+00pVm&yiIJ3KbKK6QNg3cC~ z&(5~CIL}W9qM5L5Nc2YFWt%N&bh{$g<0V2}7gzZ^B79qOMnz=Fc0N~~04XOGC z@jt2Q{iT)7WhD4_JnUmqk4z1i%4NGFVI=6&FeqWfr&)7}QAjt`s5RD)xpZeuIiV`# zwKhfLXWIY5BNX;<8j#ehMSt%&A*T#w?VI;^Kz={1dQVxNI;hkXbL^9th#HCp4v&U$+C#yi_bW9CT~qxz*90hq&U)<3@8qTsWC zc-lwg&=B}0VTMIFCzX==+cY4H${r@P=Q8W=P_YUvm&i#3j0XoFg+T4^1^l3vj~TtD z6y^0%Mz=FTTz$OtKpc<-Rw#k?#h2R{A;UYaKhs1Eu}jANn(&RvmTk9 zD?_NM!vOuGj{7rU@cV7>qa4&EEurK>Dh6Fz4#?>y?k)h4%Q?=W5|*YnIH0Nxcn57w zXVTcnU+YTN<)f7-G3-k9_h9|8YsFX@R9IucGhjUbFzw^L!oKz(!i#2%vT~#WMNw)@ zbp)Vkqds#%VH3(wlBKQSK;~jkIBczxy3UjGZmfJzk-F@RIjF?$Pj(g?3fDpfWY|Nc zFwC`Jaa2>UTD9h56otDaN6DkS<7<1ahQ1{Gi*eg(mF8w(Wi34x^`J!>VMl`9hh`-N z>a^AobDH+CoFaQAL&^e`Y+%3AyqwNp^x8kgxi9#`ABA&x;;z5W4_SYsL@$c^7> ztR$u0DX132{VyKWbe{r3ryc%GKR7w5YM4f|`ay!_6bLc^;SBJPa~- z$-^rltyw%k%eSj#YGIlFuN00T4o%@-zy_FPLpaJ!TpFwkEi1oU#Vs&3mQkk8 z=%F!`e)HNCbUk|p5Pcv~leWXxfH(q5h1RAb6UIf!ksY!*Gq~a*m4?o>Hw)9bZF^Gl zey^q(9n=&w*tEP+FoZtlCV7LkYD+gbx-SS*!?T#}+ z#v7G_dKzlkwEI&rc2>M?qJgGp6%)u9lDG z5=zxlP^4(MysYKu-{l_8)u~VQ#7JT3l=-Cc%|_=tDymIom^dk?W5i$F1R(OVA@Vw~ z)@`Fi)8#R;mN8+K(+OR>(Ui&A=)_ieGJ?%5<`y!K%XDzGTuj*;j8jOzGJaUuZfQ?~ zXP&eFGZ`EFcoC#;ND!*@8B*L@}-%^rmJC~phc^swuVk=q49KKt&vna?ZMmn8v*L< zpS5o|T`9!+?higt4tZKD+Rc=*mQfAd9b7H59XkP+c-Xp}gkPI|vUX`=3TW$N;~3bI z*Ex;YE)gq)$#Y_+@JJN+--ID7Etgg5h+9u;Eu$_CZHn6~w}il&mz#AK1xplnAmt4p zMx4=Wh(bQirQXV?Z;O<=vpav5#HHC|L(G*iC)1B?K5JZCP{*d{U}7?`dqai1_Vk-k~E0hjS?I z;|fN;gb+~I5$T}Y2aPPdl-z+S9l0*4H2#Ptn5I)St9|++oyOAk#Q@2dAw>sU3c9yN zR!ArM)jCI_+Meon%{1@tS?+F@T!zCvMBipx&6ke8dQ383NbW`>`bm*LGF;q_}XM8Oi6kzAG51=qhD9C8Yd?ha&b^eUb3wj8E-Qc zmTP?XWsiqSA#+d%uMCmvU^Td8#b`k(z8TFRl##l}Al#R%w}-$Gu8g))-dB;{XEI~? z^nqaLbs1&5gA)U_?^H-_Cr)-ZZ8C1At_3@#C`xN0?MTTU249g!B?l?RyDkX@t%{Yc zx|qGd;-bCJ0zXK?(yh=77!dj@v{PVDh_TNQ z8hp*FGl+w}8+Z;#;NQGA@)kbg@xqsFsHeRU7jvs1c4@3Gl9Vo-1*@S5hYH_Vdk*mw zcvdaqM8cPTXXJliA2;!tK#jWs`t5#pN)f%M5vW)0S#&`8VSHUeKHPP<_E7%0eDHTg zDTfYkHCSJLLZbC|aX}tY>rPqIK^w!7_~e>y*&_S~*_^JkHhe&K&lfEn&O3g8ghF39 zFWG{lfWxGL8*>zdNl&4OKX-%Qdd$YCCOwG`g6_UpRq81iIe&99+(3`HTU5dRp_6S} z>$jE7=JK&F^$&e4M+_@7HwW^?y9M{n9IbMv{>eCL1u`PZ*59qv(}{nWdJ+EWg#ZKh z3*T_Q?lZvkmPXB>8VRiS`m-P(S+lO-l8q*J>Y=IdELQ!KUp4k%UKF7@16X>kt?oDZ z^0&TVxo3d=n2(O?P5rLlZ>_(bzD^Zc{jygrix}4C^TTAypL*T4Qihi_!inBZ1746^ zyOznd8o(w;D(vB{XH~kb;TzPJ_h!b;-_P}3W7jG#>=<l|GAjW7UBqnP@2%gSTyY+7i9D(;NLa%OXR}-k1+_($N`pZkdr* zjX1&*6ON7~lY<+WZgA1VTXf&bA9N}F;m1@E=3MAbZGlMUHQCr*4wE{%oEb5A6B4Q- zx8$IZXWxgKGODsJi`zE}uNCNx%yjqaG|*eTFSzGHb=c~n>BmogTi!@tcHhdk%WPzJ z@~61?daYyoqi;&QtJa0{uXBV^=i(k`RGsrYt;eJkAb!kvBj#C^TA34CmSu8xiM6*C z3EHlZMS;$dG#t#lNkM0qNy}{~%>Q22xfuE12f zm|O4hGC0)F>|g|V<|xD|AmdMXC*p^)VRN2ucTYg7A1+L`32ZJWpO${_Mg^mNng(;1 zOL_4#>6wAw7(0=WSs*7*U!-Wq4|`Y-ex20L63(dIbbbriTF`}E6*7o;8m{6Rz_w(! zmuNq@s4{Stm7ZZNGnNkLF4MVacIkQTCLOt=R>q%iFotMlf#sS(&4%HU+Iy&>Q6M20 z`SE5E@9l^69o;ab6w-8vi6070Xw`MH$%GRzEwX4$ zg2B{tx}&RGXGEd<6L^VMLy~GEvUWCZfNBpzh9k;X&%8|P0I$vArcwyYa#XrX)vs7!{EEl~ zK52tC@MkJt^@y+SOQ(-y+Cj$5Da4-$ohB_@RAQ!Qd|E0I#+zJDgh+BZeFqP^qef2f-6MbM{5cQ6aUN-SVsH!@2u?LZ8fgk)@iQVW|>MyXwBQ$6g< zhaCimZraZOm^}45REF=UbZueJ^Ns^}MhJ`k5sT7I#H2kbrO9AP+ zsqOI&8b=;}b=t7dP1pp>8;+JSHW^&FeH>~yZr6GD-BJ8OE11ayHfl)e_gzt8{H^VG z|FMZX>K$*@gRCdYq5!lO6{6*V2U=ngla|gwO0e52U?wALCpE346?KyAwj#|jQtAM? z{5p61#_;Q9YRXq2^YglDpBtiq?#%Av?@{7mo41aCy7m9tvl`)Ht-AB2g8j{IjT`n2 z629?H{66oU)Yw7-4u{~>X*&JO4@-34q~7O*d?R#nrJVv1%Wm0^%o>v7m+=$u*GQwL zwss>cXuQW4Z(rc18g<6PDfp?plx^4{(Khp5o0q4xQjbY06@9qBZ9)WJyY?Ay*lVJ# zGSsVDna}CWa@A~5qI~(tq5sbL_D-wJWY*!A7ygsbGk`bPdEglkZE{$e{i9HjIGu&7 zw7Mo=;2E%y=uLe0ke}qX(_ul zX&gy$X@^552tAz+nbw96N;so$(d9lJ-)r_LB05A|8|r#qYo?T=tFWSd+izXCiAvBz z{?fl#SKIq-Knwj34SluMUj@!ng^xlml|NZJ-K`f69#}z2AI{q{)Iw5Qt+hK;MJYHr z)d3fAnCaLnon?Zw(A-5QkoTRqK$+m*{({Sd1|}Nk?7CS^G9Y&US3Z@z%pTOgdo}e* zoAHAhiIdbY)27GUs4KbD^l>R^Wf}^&w9lVb%H?v2pR_g8=me|Gh^On7m0}Ltgo{sf z5?-RcrM!%jy4Mcgjn7L@X z*wrZ+Bt5{62TM4sB9?t#Eft90%d{S6iC3CvVT*qI>gV~?n z*=jmyz+|j-g7^35PzV$ZAeXL&6c}7;koP*CROuK-Bb3q1;oa#jYwgbf!=)IpiWmkn zB(Q3j5x+(($sNP#KjFV**JW&+^Oxo8cWmdKod3>k%&`3iBEIa0qL5$8lr5-~uneTQ zDJ^hR`)i`Yc21qiZObgB)vmZv7PU{t*s--vLaP@BV0G5_T^7f@EJE`}ItJW9a=63b zQ*8uu9#Dg|Nko@hn$c%pLgOLLCQEjmNieg1N95ZIwo|=n$XO#|uAIjoy>|mRU+ah| zk(tzwYa9qYT=zd^{*h~8Y^?+;I&RVYaI^K~NU1Cs(xhqM9%l6okr0chE149pYpdPA zW^wrwlrv;g%mk3BHGu7xl>kx%I{s^VL!7zuNl-`RsrNVO%;Pj^DCY9Y$?Hb_6mD^r+Tt#X_Uh>ud1}2ME?TL)i96yPgA<9$Uj&rTYAmh=NZp192{Q7 z`E&cyO(+m76@E$R`MRN6&ZLluM^{T2p!2D>aCgp4Y!GxU@)Lce)xa&O)vp?q=8w0k zM<(o8!&t4G;Te73zWofyS{y@V-F}k8313cS5XE5n+K&EE-(m5Uux&0#NxS>}+FC1` z&!>HZ5pz>|GAVvdgm%X0Ua&5Zhcuj2eNhnhJI*b(y_c3p7xGcCu6d^#{#WA4Hlrk! z+G%@33OqtZ^61Po94!s$gf?hC<>e zgGraB*ZBHTZF$1Wv25WhImwg0O%%E|dg`ab9^7|rEo0Xf!Ese?EX%1kR`=sN6Y@#h zRa~0}2_@N0b?my0H~$z<(Qt$$Sg-?}d}z{@v$$T&bxPFiQO0F7dGBtZ>iNk*^^@d_ z?LJSn4<2K1?YUJVLUgDocnBj*CRX8c4*(43ziS5PivPO4y4J{+*U5wijR0ihTe$rr zkB!CowDo~dN^noPdoP-fI!U0#=$q;{>YORVgIDBfiiZjvxWCq1Ml_4;+bOOK?0vv8sL!$OD#V`6ytlWbXr8SJmzD zrIL;dYUb5A*XUUitDyspR}3{W61Ln(pVAwU`6mGC8^83TOaA3f+MFMaI^7_#7_@vp z3)g#<30Hr)>vgD{*>rs#2Y)i|IaoWn8WslgpPBESw4K?M5m47aR7#yZWJ*y#o)eJ!aJ%#YQScaTS=F9 zd6))EG7EHb3Ms*l+NwWIn-}6@5D*WWFE$~aSi$-MJDW+BffoztZm273c-Q&|#)l-z z;yqI5xceWec%-4V6jB#_o%Ermwu{Ek&DAoiW`50->8-grdy9kk(^XRHLH;P7$|X$s zI-UjEqy%oQIlah?T>K`yp?J4XWEkDbSy$mjLuDZ6+T1$#UzLVjid?E;`lcUOMubR) zd2?}bId8oV)%kDd*L(%njfd$AYWQt4QV*L=7}tnv9Y^jS@Zzo=g@YcK|2CrD)WNN3qw|db{`#e)#&j6iySi39W ze;Z*vA}qcevX62|L^p`Kl#Nzfv$=v-PSES5ffawf8i1gvo2zco^o>l>5MOj6DCP4< zm$+mS4V{Db2?a;wE3Hklo}>vU1`XEsAMcf;brOUzm#sjU-`os(Kf4?#fO{aU4eQC1 z^5`w0>5M8nJmzV<+3ohTHEkDeh4edC(Uk3VUv86lYu5JK>rkoe=}NIQ8fIz@z;sU* zfj5&}7)F}oo=mMz7V|tqA%-h>piI$PKYQL!Cme<|KRd`hoF$G)dh~;#TX0O6&=W1_ zp*#%qeEy%qZs_SaB_}3yW6d=*g`$Y#vaw%c?rQhnr(fcf&w%e`9$bTjuWw7u_QHNz zrpN1nX=FB@7WpfRtc>Df6#HXk-c1Z}p?z$#Db#M?R;Q#sc~S|D>m$_3pAJD}A)&7l znk7oHY=}*}lJ_Bc(5+lt@A5uy=5!vXfAH=Fp*Wv&`F$P0N#NM{p&FY!*FHvf=%=x$ zn9xpWMEpm#8 zqi~a(6O->jh8t#EZ8B>n!u)cdoBrEj2rTOa+Dxzk!1=J?#!`DXxqd|fU>|b5-!?y# z^;$^;7v?+%Ph-A2NJc~`{O#0`#D)qp@_s50b3H8BA zHRJk%;^!+^KML}JLyJ>7Djg3n)3>2Y9Yz9foC4aJ+Pv9aO!id_HaG{9WRtU^Nr6F2XkoW6&R#PLex_=?E>#tY1LKi*?!cB;+ zIARPm)6tQJ8^gn)TbIO>rka{o9GT@jz`i4? z3U5Yi82km7Mf@2sL{Tj0K8`Pg&5kYYiyo;Lvl)+O7_M+nmiW2%q(#+8tgB3}`0T7u z>{ygpP9%u%p~k&vBN=PqPqN{ROlv_EFWaVChhtztT{RR^O5ThrL@wP3ZhTV=76Cw$ zzS{3GiW44gP!uf(8W7wy6KiGC;aSUL(Z@o)nVYOwACHP9vm&+hLStqFJp#Zf^5 zU%D#khVLgAAd;B2R!Z*aO<~-H4|BeSOa`}tI&VIPV_?Ay*PUL=m7QLD%f)4$ZdvG( zxWFpFR%xfB-|krlSgqC*J>f zl$3)`08hc`%G*GP7&#Rr7?&W0m6<2BeO+d*Zd&&w$1n#JD`>>6JU*H!Gf13NB1Y@&=JP zv_BMNC`|j^U%TVT$Mpfbm(4%NbHse7@_FoFh@^sJry|5&VtCursI^fhcV89-^DxCh z6{hAi7=B4|+%y2cn0ex=CZUy|Ulbvt?!>oKD#UJ{jFc*D8)K@)mtk(IqjQLc_6 zgJdkjMPH@1>u+B9QQ_T%EIda-cWptLjd+ERitdR}ptpX3?6D)A>gkp40Ytiz{p?BW z966Kw-KtN~0gz<^b>76U2C6DSnj|n>AAF3ZEV#U|YOoQ>%KQ%N3N5)V6G=N`!M5)W zHzd7%Xhn<0k^ewXY_*f%BsMEwQ?lYfd+6tqMnxZ;d84hoNqL2n%`-sXj9Yt9ys6r9 zOx8dPiLSM9hczN`5o@-OnsW*D;U;6~kb$=!XDSESaQHKMc6ujDY5<}RXCm^Z}08jlns zvX>MOTZe8lIkmsF7nNXb=!!E?D`_Z4I%3`vI|7xaK)_QB!)e8|v>E`vZ0k70Nq4z6 zKxMyUj3!L+n+fiIkl_BjY`ub`v3N4}mDZVQr79K6wIm99gE<0v)O(}lG9C@(aeqaB zJEX%XuRGml2Rp(KYYpS;x4@JDgpfv8Iv7Ls+=oea2G_LhI-A(>23iM_B%|Cvhl?$R zyz7i2j7Ks#(l8Ex(lll8g_L(xzSlX+UVam|T^c~KqA>zSpkzD)7Ix>XGIo^9i0_AG zuwFM%Fxa-BAS(n^J(gF`mk|=VEyYERtv&-Pt3C8j^f>x88l<_<;_CvBL-5#W`V`~1 zg9)t;Fu44e^R5K>;A$;WCYysd*E1jpU9agQMUIJ^9L$nrJ(C!3sdv)zomLqq`n}E~ z(E?F^es5*CKjE1Cs=Eh`36d-Wp?mL_7L;iN#ZaMsZP){-?mR<}V_+tR1$M3TBGiX7 zM6YDpXHe``VWSF?34aqx>wO0Nh=Wi7mp+9yP{?|2iYVjs&G=Zrj@h~2;pa?lI=*IY zaA0mUy#Z^u#uw3WE$vrk_*(eloo&;d!;dzGVXYc@2{3l8ODV+=<~DKnh$@{)TH`61 zr!_KB<$YhQ8o{b2UH^8sFT?9BE5~}iczW96pu}iRl<+}H@W766-YhAUOw89qub^g# zK&rn%wlykGg_9Fs?atnkmgR^~rQKU*OWW8;+-&mFjVL59o|{Wb#w5O% zPj^*s&+mw5p8;+4XN*T0-qelm$aDxKAsfcIoZ$l;VctZsf)Y69C-XxMqRN?xm;{hp zg%%d%$^<{mD_+W9?RKh^BDHFQ&$OqVy|XzSD8izdnM+hRx+9kLgP2&-I6FvYO}TcKpwY^p~jyxL2QJ{ ziP6@cH${}wL~FpX+tD2THq#DWbp)5f`EEE|e=~`==^WHTqg~0jH2~t^SQj0S$AjSv zNjXwvc`)|yKREA0w9Y%qXFUw5R*q zMjX{lmUA<@&9+HF0C}Cd(*uiSt~Qx~-O%@mKle3NbVSEq!s0-PDUT0xr&(7I_0HqC zXJ>adt1uG-B&FCiMv@f2)q-g%WGtWD62dNVBtbrsWZ;t_t~ZS`Y+Q3zXqrWzB`}u= zB;@v$eXM(@7!MQF`zisR#4g@(jx@9eGyBA8+jrqXu}UEYk_tWchG+tLV@ z7*KE+w_j^uPQM@j(7SeQq53~}H=#E^0RYTYFwOt{lMMV1a0r+N28#PqL-8*PlK;~x zPZK5y!2Ay|1r{FtDX)vMekSS6DG|<;nWB?|B1`7a(1tkckNe0tkL5WDfB|`-O z!=*~XVL|Cj&;b6Df&o(`1OK8(zR2(bfJ}i2pumJugGvqsMg~C9q41cJ6d}lP00{t; z6eg4cv{I5L1S%3TT$ntR3k4>W9pEqUi`W2Y>r3SeK{zNd=8J?-Iuv2ZG%%7h|A!;~ zmrDSc|DTrt{(+#!gsx0rpcjB&Rw#e3>iy3eg~BZKlEbwqMZ&c4>VK~1iDNzkW|MmZ_aQbHFl4S&ulah(86-PS{>F%_5!)Xj@QMz7~#wTUs?4^|fw zv)3e(pi{cHdzMv109+$%To#Q!NtaZ|L_9KZ)oa5TDr)kfD;0xU=2J~(on3vmH((WN z<3VT?NMvBJo+wi544$eWerlLecPgTN%3L3PKVZCNX^&>0rd5ox3c~4EcDb4~k9v*8 zYzJ&bd*d#$q12a%MJ?rrk5`JM;=?nv8Y^QQhwqDmgJh z>8qgSEyUg7#9pg{1i?_YP*@LXps3AC#N~+1W#fqfJQ-fO{gGBAp3U=5B{paq#9lBUmu`YNYs@oy%dx86 z4<}<0-#sgt*QaB=s`&u#g~{Yx`PGJ;GC6S}xo^EYtHOeSt<4L|41HQE8@&3^>Uho~#o6v+)F4^zUCW_S3(MCs1Ebd;U zBa*E>J~`zo2!Wj-uB7&hCrIdNMIi{S;AM_IseMfhG%d` znVa@gVZ0`D)f?izi8o2g{pD`|P-vP+Ao+;!Uh!I1PdtW2#qy(3@DRqzk=W@-uw0?< zGr--FzG3xE|18TT(W3y>Lv;wA_C#?l9lS~#BS&}d8pCpeEt#mJ8{*vfB%W!&`w}Cnu=}!O@Fpefk7*u=SL~8<%Q=1U^A?@ z-QYw=(bKd{YJJdt|2X4-6?;gp_(ZAyQeZu^&mtcT% zNq;htq?ROk?c!=pYsNqzX3#}?-&X}3-p&x9;pXpcj_-WJ-%l{ubC{8Q;V1!sLH+p} ze*@`~7QEKMo*yZERWcHvDBXUX8&p8FCCo3aR5cE3WaB;NWR{hN_s7_}czIsC+jvgq zUxu-++8r~=?_aJwT(*~x-9op<0#_3LBq8Vq)wGDo1ifXeN8w@HLpRE8#_}e?3CSj< zZB$dDYj8orE#$%1`!sGnP;5)k6kVGnu@eoM>w85X9KiQ8T&;`IhoMj)uM`E|1@gYz zBOntX!31P1CCieJ1~yVEP)05J|1=G(e=mz=f{MrN-i=tBWEfv_wHS`VFdtnOm(4>a znR)SgIFXVOiCywkxj5#n9#DRb>^5qb}kxFyI;XWw@_R>);9JVpwPmk);#Ls}3yOX~n1NLDau|9`9+#vok5uuV+j;9bE4w1-DWyQVchArAEkVpQo z*M0lXIB|Z*9txYu$}2#WB9BglSUksx27CsD9=#TVgIAAXI-)}6;qXYbpPr0i;TOW4 z><}0TlJf)jRQyo%8>#9eT`KIB6n#APIuW(;LYKj8Ra0gaa*&-Vm`NfIopgrV0cxKo zpULB@tBHI~on1E;3?|j+pAw>5r8X~#$w_Kn>yoEo_nDxIaewc&xp^xuaJ6rEjTmZ{`U~+cSfB+*nagZS=#GrD z_%;sKe)hcet1cI(cv5~?1JDDpCfJw($G4KUlfesaq^;GQ^5lze4OCPhbyTw zH4=meva)sd%~s5hok$^(oxu;K3tCc0sKKaXe^`IqM|941_yKyH!SQ;es9$LM1wSGo zsIf411z|!D;hfbbA{5vbbC{IqK*zz#^LTMsvM?|IMzRyh27poP@hVx59=NnP5u#~? zasUvL0pS2aAf6p+=UE4gZ&lT;+Su)k|M7rp*J{Eg<~#a(e063GOFqp?}soe9Gsh+=v~hj&I7K> zR@c%3 zxu-Roc2;n-I4|@9K)zOCNdp^IX=S|Jec|IUH9RnNq3$Mj5mY2vs&DBETEbk&%6kE9 zhF|ZMVZ`tSZxE|z?{w%bJxGAVS*2Z+OK+=KI55-CP!LV6Sc+l-iSMQL%dcNd=ZBX2 zb=AXHT!mHT>gL zgR7Hn%Unimx!{{G43Y#aUtL4cV396h7D1@O0%g9+TP93~V`C|IcpXxSlhHA-KAf1m z6>G9cIH_n&lH$myRmaRiqZS6kF@V=p)f`JcQMzR8-5oa#TZ9tVd7yn!a8HHuD#bNe zQ&gIJ?3L~P=gzBCwE0AF90A5)A2w{(pa?sGfYvfr&miorb7a8m_RORi9K z5y(|jn$wHkR|(IH!EZKQVa1u;+QNcu`2rHCZ^{Ot4CAFm2vc#b<1&4#QPkSA(Id9< z8J9LJ1POUC+W){cdZ{X1o35((mHYh17u5zM>44VP$Qwt(@cOqZD2=f-YXD=I$jqQe z?GM^!p*JC+6wZLTB2v%wyZW4k$GN-THg;1)kjun3EEoIN^-SvZL22g!m-7h<0{fOt zwp97Lcl=KN4&tWyd6o=W>1v^*xy$^DX=;%izbO1~emnfKp-3EUM15m#HYI%Ey66b< z)i?aqv7D_d=U^E$N`z#9=v5f$qpZ>rP9Z^4BX^*auN{Rr4+9t44l5hs3H|GdH2iL0 z&f`e$wFw}kRN{QkDto*;>+d`PwJXtvr6>1@)uAt5&sVYZW4B}dS=lQ#{Vy_c(Cvfi z3d#8gQQDrbR>4*bzHZBx8?)GY?I|BvWE*xTM>OaA9H#sYDc}I8ppsuC3Ub!26jHBd z&1*7fVKP||Dv@BmQ?^`zIB?!z=4g5+n|&3mXCe&i+Tp4~^=1 zKatDqq7sZ-SF(gqw&avNwk$iuC-{SrJiH7#a$mN4TjEWtQ~<$U>_+Klk?bT zz9K}$og3%Q{GGG)Z+7$;yzBDj3M16ch{Eko$H+CC@(UT%x^EA@UUv6mILa1Lmm!ZO zNvE>VAchDjrahH-Uq;JWbrpoZqoj|M8xp|r0#R#$ZbybPWp<-5B5@Q78yFSTI?A-Q zqJnphQ#8F~eOr-)Oc2EP7vWA;D-dWUx&HV56+~sHYoqg2>gKYdXVv(0uT^9b8h$N< zAGh?}&=o{XqDwBzlKNF$K8j6d8qG(omNFl)FGo3!hXvb53Um5rSX*VZFO2wT_EMrt z0+wo#f{JNQe?~s1)Pca;YoP{JfE2|^?4}`P_hTVlvn#cVZlc*>Wftol > 0.0) { - if (normstyle == MAX) fmsq = max_torque(); // max norm - else fmsq = total_torque(); // Euclidean 2-norm + if (normstyle == MAX) fmsq = max_torque(); // max torque norm + else if (normstyle == INF) fmsq = inf_torque(); // inf torque norm + else if (normstyle == TWO) fmsq = total_torque(); // Euclidean torque 2-norm + else error->all(FLERR,"Illegal min_modify command"); fmdotfm = fmsq*fmsq; if (update->multireplica == 0) { if (fmdotfm < update->ftol*update->ftol) return FTOL; diff --git a/src/SPIN/min_spin_cg.cpp b/src/SPIN/min_spin_cg.cpp index a87d3aaa36..95bbcf437b 100644 --- a/src/SPIN/min_spin_cg.cpp +++ b/src/SPIN/min_spin_cg.cpp @@ -270,8 +270,10 @@ int MinSpinCG::iterate(int maxiter) fmdotfm = fmsq = 0.0; if (update->ftol > 0.0) { - if (normstyle == MAX) fmsq = max_torque(); // max norm - else fmsq = total_torque(); // Euclidean 2-norm + if (normstyle == MAX) fmsq = max_torque(); // max torque norm + else if (normstyle == INF) fmsq = inf_torque(); // inf torque norm + else if (normstyle == TWO) fmsq = total_torque(); // Euclidean torque 2-norm + else error->all(FLERR,"Illegal min_modify command"); fmdotfm = fmsq*fmsq; if (update->multireplica == 0) { if (fmdotfm < update->ftol*update->ftol) return FTOL; diff --git a/src/SPIN/min_spin_lbfgs.cpp b/src/SPIN/min_spin_lbfgs.cpp index e161aa2a30..db0dbbaa76 100644 --- a/src/SPIN/min_spin_lbfgs.cpp +++ b/src/SPIN/min_spin_lbfgs.cpp @@ -285,8 +285,10 @@ int MinSpinLBFGS::iterate(int maxiter) fmdotfm = fmsq = 0.0; if (update->ftol > 0.0) { - if (normstyle == MAX) fmsq = max_torque(); // max norm - else fmsq = total_torque(); // Euclidean 2-norm + if (normstyle == MAX) fmsq = max_torque(); // max torque norm + else if (normstyle == INF) fmsq = inf_torque(); // inf torque norm + else if (normstyle == TWO) fmsq = total_torque(); // Euclidean torque 2-norm + else error->all(FLERR,"Illegal min_modify command"); fmdotfm = fmsq*fmsq; if (update->multireplica == 0) { if (fmdotfm < update->ftol*update->ftol) return FTOL; diff --git a/src/min.cpp b/src/min.cpp index 1e56d4c466..b57dd44d4f 100644 --- a/src/min.cpp +++ b/src/min.cpp @@ -670,6 +670,7 @@ void Min::modify_params(int narg, char **arg) if (iarg+2 > narg) error->all(FLERR,"Illegal min_modify command"); if (strcmp(arg[iarg+1],"two") == 0) normstyle = TWO; else if (strcmp(arg[iarg+1],"max") == 0) normstyle = MAX; + else if (strcmp(arg[iarg+1],"inf") == 0) normstyle = INF; else error->all(FLERR,"Illegal min_modify command"); iarg += 2; } else { @@ -899,6 +900,39 @@ double Min::total_torque() return sqrt(ftotsqall) * hbar; } +/* ---------------------------------------------------------------------- + compute and return max_i ||mag. torque components|| (in eV) +------------------------------------------------------------------------- */ + +double Min::inf_torque() +{ + double fmsq,fmaxsqone,fmaxsqall; + int nlocal = atom->nlocal; + double hbar = force->hplanck/MY_2PI; + double tx,ty,tz; + double **sp = atom->sp; + double **fm = atom->fm; + + fmsq = fmaxsqone = fmaxsqall = 0.0; + for (int i = 0; i < nlocal; i++) { + tx = fm[i][1]*sp[i][2] - fm[i][2]*sp[i][1]; + ty = fm[i][2]*sp[i][0] - fm[i][0]*sp[i][2]; + tz = fm[i][0]*sp[i][1] - fm[i][1]*sp[i][0]; + fmaxsqone = MAX(fmaxsqone,tx*tx); + fmaxsqone = MAX(fmaxsqone,ty*ty); + fmaxsqone = MAX(fmaxsqone,tz*tz); + } + + // finding max fm on this replica + + fmaxsqall = fmaxsqone; + MPI_Allreduce(&fmaxsqone,&fmaxsqall,1,MPI_DOUBLE,MPI_MAX,world); + + // multiply it by hbar so that units are in eV + + return sqrt(fmaxsqall) * hbar; +} + /* ---------------------------------------------------------------------- compute and return max_i ||mag. torque_i|| (in eV) ------------------------------------------------------------------------- */ diff --git a/src/min.h b/src/min.h index e03b034147..61f9ce0bda 100644 --- a/src/min.h +++ b/src/min.h @@ -43,11 +43,12 @@ class Min : protected Pointers { double fnorm_inf(); double fnorm_max(); - enum{TWO,MAX}; + enum{TWO,MAX,INF}; // methods for spin minimizers - double max_torque(); double total_torque(); + double inf_torque(); + double max_torque(); virtual void init_style() {} virtual void setup_style() = 0; @@ -67,8 +68,7 @@ class Min : protected Pointers { int linestyle; // 0 = backtrack, 1 = quadratic, 2 = forcezero // 3 = spin_cubic, 4 = spin_none - int normstyle; // TWO or MAX flag for force norm evaluation - // int normstyle; // 0 = Euclidean norm, 1 = inf. norm + int normstyle; // TWO, MAX or INF flag for force norm evaluation int nelist_global,nelist_atom; // # of PE,virial computes to check int nvlist_global,nvlist_atom; diff --git a/src/min_cg.cpp b/src/min_cg.cpp index d98ec0ef97..80dde25f51 100644 --- a/src/min_cg.cpp +++ b/src/min_cg.cpp @@ -14,6 +14,7 @@ #include "min_cg.h" #include #include +#include "error.h" #include "update.h" #include "output.h" #include "timer.h" @@ -110,12 +111,15 @@ int MinCG::iterate(int maxiter) } fmax = 0.0; - if (normstyle == MAX) { // max force norm + if (normstyle == MAX) { // max force norm fmax = fnorm_max(); if (fmax < update->ftol*update->ftol) return FTOL; - } else { // Euclidean force 2-norm + } else if (normstyle == INF) { // infinite force norm + fmax = fnorm_inf(); + if (fmax < update->ftol*update->ftol) return FTOL; + } else if (normstyle == TWO) { // Euclidean force 2-norm if (dotall[0] < update->ftol*update->ftol) return FTOL; - } + } else error->all(FLERR,"Illegal min_modify command"); // update new search direction h from new f = -Grad(x) and old g // this is Polak-Ribieri formulation diff --git a/src/min_fire.cpp b/src/min_fire.cpp index dbb7f36148..e0cc2437d4 100644 --- a/src/min_fire.cpp +++ b/src/min_fire.cpp @@ -16,6 +16,7 @@ #include #include "universe.h" #include "atom.h" +#include "error.h" #include "force.h" #include "update.h" #include "output.h" @@ -250,8 +251,10 @@ int MinFire::iterate(int maxiter) // sync across replicas if running multi-replica minimization if (update->ftol > 0.0) { - if (normstyle == MAX) fdotf = fnorm_inf(); // max force norm - else fdotf = fnorm_sqr(); // Euclidean force 2-norm + if (normstyle == MAX) fdotf = fnorm_max(); // max force norm + else if (normstyle == INF) fdotf = fnorm_inf(); // inf force norm + else if (normstyle == TWO) fdotf = fnorm_sqr(); // Euclidean force 2-norm + else error->all(FLERR,"Illegal min_modify command"); if (update->multireplica == 0) { if (fdotf < update->ftol*update->ftol) return FTOL; } else { diff --git a/src/min_quickmin.cpp b/src/min_quickmin.cpp index 6846aaba0a..ef649b4dac 100644 --- a/src/min_quickmin.cpp +++ b/src/min_quickmin.cpp @@ -16,6 +16,7 @@ #include #include "universe.h" #include "atom.h" +#include "error.h" #include "force.h" #include "update.h" #include "output.h" @@ -215,8 +216,10 @@ int MinQuickMin::iterate(int maxiter) // sync across replicas if running multi-replica minimization if (update->ftol > 0.0) { - if (normstyle == MAX) fdotfloc = fnorm_max(); // max force norm - else fdotf = fnorm_sqr(); // Euclidean force 2-norm + if (normstyle == MAX) fdotfloc = fnorm_max(); // max force norm + else if (normstyle == INF) fdotfloc = fnorm_inf(); // inf force norm + else if (normstyle == TWO) fdotfloc = fnorm_sqr(); // Euclidean force 2-norm + else error->all(FLERR,"Illegal min_modify command"); if (update->multireplica == 0) { if (fdotf < update->ftol*update->ftol) return FTOL; } else { diff --git a/src/min_sd.cpp b/src/min_sd.cpp index 3ded85990d..8541b0ccdf 100644 --- a/src/min_sd.cpp +++ b/src/min_sd.cpp @@ -13,6 +13,7 @@ #include "min_sd.h" #include +#include "error.h" #include "update.h" #include "output.h" #include "timer.h" @@ -77,8 +78,10 @@ int MinSD::iterate(int maxiter) // force tolerance criterion - if (normstyle == MAX) fdotf = fnorm_max(); // max force norm - else fdotf = fnorm_sqr(); // Euclidean force 2-norm + if (normstyle == MAX) fdotf = fnorm_max(); // max force norm + else if (normstyle == INF) fdotf = fnorm_inf(); // infinite force norm + else if (normstyle == TWO) fdotf = fnorm_sqr(); // Euclidean force 2-norm + else error->all(FLERR,"Illegal min_modify command"); if (fdotf < update->ftol*update->ftol) return FTOL; // set new search direction h to f = -Grad(x) From 2fad4e0f974eb05e6e549304a150fe4369776a16 Mon Sep 17 00:00:00 2001 From: julient31 Date: Tue, 24 Sep 2019 14:50:55 -0600 Subject: [PATCH 183/192] Commit JT 092419 - corrected read_restart in exchange (same correct as in Neel) --- src/SPIN/pair_spin_exchange.cpp | 2 +- src/SPIN/pair_spin_neel.cpp | 2 -- 2 files changed, 1 insertion(+), 3 deletions(-) diff --git a/src/SPIN/pair_spin_exchange.cpp b/src/SPIN/pair_spin_exchange.cpp index cc28018ad0..7bc2b846a1 100644 --- a/src/SPIN/pair_spin_exchange.cpp +++ b/src/SPIN/pair_spin_exchange.cpp @@ -504,7 +504,7 @@ void PairSpinExchange::read_restart(FILE *fp) fread(&J1_mag[i][j],sizeof(double),1,fp); fread(&J1_mech[i][j],sizeof(double),1,fp); fread(&J2[i][j],sizeof(double),1,fp); - fread(&J2[i][j],sizeof(double),1,fp); + fread(&J3[i][j],sizeof(double),1,fp); fread(&cut_spin_exchange[i][j],sizeof(double),1,fp); } MPI_Bcast(&J1_mag[i][j],1,MPI_DOUBLE,0,world); diff --git a/src/SPIN/pair_spin_neel.cpp b/src/SPIN/pair_spin_neel.cpp index 72d445a184..017682593a 100644 --- a/src/SPIN/pair_spin_neel.cpp +++ b/src/SPIN/pair_spin_neel.cpp @@ -643,10 +643,8 @@ void PairSpinNeel::allocate() memory->create(q3,n+1,n+1,"pair/spin/soc/neel:q3"); memory->create(cutsq,n+1,n+1,"pair/spin/soc/neel:cutsq"); - } - /* ---------------------------------------------------------------------- proc 0 writes to restart file ------------------------------------------------------------------------- */ From a0974bc09dc544ebe1faf20afbfc0758e4a0ce98 Mon Sep 17 00:00:00 2001 From: julient31 Date: Tue, 24 Sep 2019 15:58:22 -0600 Subject: [PATCH 184/192] Commit JT 092419 - changed the nve/spin lattice option - from (yes/no) to (moving/frozen) - changed the doc and all examples --- doc/src/fix_nve_spin.txt | 20 ++++++++++++------- examples/SPIN/bfo/in.spin.bfo | 2 +- examples/SPIN/cobalt_fcc/in.spin.cobalt_fcc | 2 +- examples/SPIN/cobalt_hcp/in.spin.cobalt_hcp | 2 +- .../SPIN/dipole_spin/in.spin.iron_dipole_cut | 2 +- .../dipole_spin/in.spin.iron_dipole_ewald | 2 +- .../SPIN/dipole_spin/in.spin.iron_dipole_pppm | 2 +- examples/SPIN/iron/in.spin.iron | 2 +- examples/SPIN/iron/in.spin.iron_cubic | 2 +- examples/SPIN/nickel/in.spin.nickel | 2 +- examples/SPIN/nickel/in.spin.nickel_cubic | 2 +- examples/SPIN/read_restart/in.spin.read_data | 2 +- examples/SPIN/read_restart/in.spin.restart | 2 +- .../SPIN/read_restart/in.spin.write_restart | 2 +- .../SPIN/setforce_spin/in.spinmin.setforce | 2 +- src/SPIN/fix_nve_spin.cpp | 5 +++++ 16 files changed, 32 insertions(+), 21 deletions(-) diff --git a/doc/src/fix_nve_spin.txt b/doc/src/fix_nve_spin.txt index 7b382bb6ad..8e6284639b 100644 --- a/doc/src/fix_nve_spin.txt +++ b/doc/src/fix_nve_spin.txt @@ -15,22 +15,26 @@ fix ID group-ID nve/spin keyword values :pre ID, group-ID are documented in "fix"_fix.html command :ulb,l nve/spin = style name of this fix command :l keyword = {lattice} :l - {lattice} value = {no} or {yes} :pre + {lattice} value = {moving} or {frozen} + moving = integrate both spin and atomic degress of freedom + frozen = integrate spins on a fixed lattice :pre :ule [Examples:] -fix 3 all nve/spin lattice yes -fix 1 all nve/spin lattice no :pre +fix 3 all nve/spin lattice moving +fix 1 all nve/spin lattice frozen :pre [Description:] Perform a symplectic integration for the spin or spin-lattice system. The {lattice} keyword defines if the spins are integrated on a lattice -of fixed atoms (lattice = no), or if atoms are moving (lattice = yes). - -By default (lattice = yes), a spin-lattice integration is performed. +of fixed atoms (lattice = frozen), or if atoms are moving +(lattice = moving). +The first case corresponds to a spin dynamics calculation, and +the second to a spin-lattice calculation. +By default a spin-lattice integration is performed (lattice = moving). The {nve/spin} fix applies a Suzuki-Trotter decomposition to the equations of motion of the spin lattice system, following the scheme: @@ -63,7 +67,9 @@ instead of "array" is also valid. "atom_style spin"_atom_style.html, "fix nve"_fix_nve.html -[Default:] none +[Default:] + +The option default is lattice = moving. :line diff --git a/examples/SPIN/bfo/in.spin.bfo b/examples/SPIN/bfo/in.spin.bfo index e3c88b0f06..2cd9200121 100644 --- a/examples/SPIN/bfo/in.spin.bfo +++ b/examples/SPIN/bfo/in.spin.bfo @@ -32,7 +32,7 @@ neigh_modify every 10 check yes delay 20 fix 1 all precession/spin anisotropy 0.0000033 0.0 0.0 1.0 fix 2 all langevin/spin 0.0 0.1 21 -fix 3 all nve/spin lattice no +fix 3 all nve/spin lattice frozen timestep 0.0002 diff --git a/examples/SPIN/cobalt_fcc/in.spin.cobalt_fcc b/examples/SPIN/cobalt_fcc/in.spin.cobalt_fcc index ea98eeba94..9193faa798 100644 --- a/examples/SPIN/cobalt_fcc/in.spin.cobalt_fcc +++ b/examples/SPIN/cobalt_fcc/in.spin.cobalt_fcc @@ -35,7 +35,7 @@ fix_modify 1 energy yes fix 2 all langevin/spin 0.0 0.0 21 -fix 3 all nve/spin lattice yes +fix 3 all nve/spin lattice moving timestep 0.0001 # compute and output options diff --git a/examples/SPIN/cobalt_hcp/in.spin.cobalt_hcp b/examples/SPIN/cobalt_hcp/in.spin.cobalt_hcp index 3f34838553..b9ede5f09c 100644 --- a/examples/SPIN/cobalt_hcp/in.spin.cobalt_hcp +++ b/examples/SPIN/cobalt_hcp/in.spin.cobalt_hcp @@ -37,7 +37,7 @@ neigh_modify every 10 check yes delay 20 fix 1 all precession/spin anisotropy 0.01 0.0 0.0 1.0 #fix 2 all langevin/spin 0.0 0.0 21 fix 2 all langevin/spin 0.0 0.1 21 -fix 3 all nve/spin lattice yes +fix 3 all nve/spin lattice moving timestep 0.0001 diff --git a/examples/SPIN/dipole_spin/in.spin.iron_dipole_cut b/examples/SPIN/dipole_spin/in.spin.iron_dipole_cut index a409fe0563..34f7fea0d3 100644 --- a/examples/SPIN/dipole_spin/in.spin.iron_dipole_cut +++ b/examples/SPIN/dipole_spin/in.spin.iron_dipole_cut @@ -33,7 +33,7 @@ fix 1 all precession/spin cubic 0.001 0.0005 1.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 1 fix_modify 1 energy yes fix 2 all langevin/spin 0.0 0.0 21 -fix 3 all nve/spin lattice yes +fix 3 all nve/spin lattice moving timestep 0.0001 # compute and output options diff --git a/examples/SPIN/dipole_spin/in.spin.iron_dipole_ewald b/examples/SPIN/dipole_spin/in.spin.iron_dipole_ewald index 58b44b55fe..f694bc5ddc 100644 --- a/examples/SPIN/dipole_spin/in.spin.iron_dipole_ewald +++ b/examples/SPIN/dipole_spin/in.spin.iron_dipole_ewald @@ -35,7 +35,7 @@ fix 1 all precession/spin cubic 0.001 0.0005 1.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 1 fix_modify 1 energy yes fix 2 all langevin/spin 0.0 0.0 21 -fix 3 all nve/spin lattice yes +fix 3 all nve/spin lattice moving timestep 0.0001 # compute and output options diff --git a/examples/SPIN/dipole_spin/in.spin.iron_dipole_pppm b/examples/SPIN/dipole_spin/in.spin.iron_dipole_pppm index 28d7e4a4bc..4175038ade 100644 --- a/examples/SPIN/dipole_spin/in.spin.iron_dipole_pppm +++ b/examples/SPIN/dipole_spin/in.spin.iron_dipole_pppm @@ -36,7 +36,7 @@ fix 1 all precession/spin cubic 0.001 0.0005 1.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 1 fix_modify 1 energy yes fix 2 all langevin/spin 0.0 0.0 21 -fix 3 all nve/spin lattice yes +fix 3 all nve/spin lattice moving timestep 0.0001 # compute and output options diff --git a/examples/SPIN/iron/in.spin.iron b/examples/SPIN/iron/in.spin.iron index bb1b0e1b4d..3468575493 100644 --- a/examples/SPIN/iron/in.spin.iron +++ b/examples/SPIN/iron/in.spin.iron @@ -33,7 +33,7 @@ neigh_modify every 10 check yes delay 20 fix 1 all precession/spin zeeman 0.0 0.0 0.0 1.0 fix 2 all langevin/spin 0.0 0.0 21 -fix 3 all nve/spin lattice yes +fix 3 all nve/spin lattice moving timestep 0.0001 # compute and output options diff --git a/examples/SPIN/iron/in.spin.iron_cubic b/examples/SPIN/iron/in.spin.iron_cubic index d4703a2959..859d9df0fa 100644 --- a/examples/SPIN/iron/in.spin.iron_cubic +++ b/examples/SPIN/iron/in.spin.iron_cubic @@ -31,7 +31,7 @@ fix 1 all precession/spin cubic 0.001 0.0005 1.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 1 fix_modify 1 energy yes fix 2 all langevin/spin 0.0 0.0 21 -fix 3 all nve/spin lattice yes +fix 3 all nve/spin lattice moving timestep 0.0001 # compute and output options diff --git a/examples/SPIN/nickel/in.spin.nickel b/examples/SPIN/nickel/in.spin.nickel index 0ed2fac410..caa1c940ae 100644 --- a/examples/SPIN/nickel/in.spin.nickel +++ b/examples/SPIN/nickel/in.spin.nickel @@ -33,7 +33,7 @@ neigh_modify every 10 check yes delay 20 fix 1 all precession/spin zeeman 0.0 0.0 0.0 1.0 fix 2 all langevin/spin 0.0 0.0 21 -fix 3 all nve/spin lattice yes +fix 3 all nve/spin lattice moving timestep 0.0001 # compute and output options diff --git a/examples/SPIN/nickel/in.spin.nickel_cubic b/examples/SPIN/nickel/in.spin.nickel_cubic index 3c97b284ae..76ea23689a 100644 --- a/examples/SPIN/nickel/in.spin.nickel_cubic +++ b/examples/SPIN/nickel/in.spin.nickel_cubic @@ -35,7 +35,7 @@ fix 1 all precession/spin cubic -0.0001 0.0 1.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 1. fix_modify 1 energy yes fix 2 all langevin/spin 0.0 0.0 21 -fix 3 all nve/spin lattice yes +fix 3 all nve/spin lattice moving timestep 0.0001 # compute and output options diff --git a/examples/SPIN/read_restart/in.spin.read_data b/examples/SPIN/read_restart/in.spin.read_data index a450421699..e788ecf67e 100644 --- a/examples/SPIN/read_restart/in.spin.read_data +++ b/examples/SPIN/read_restart/in.spin.read_data @@ -20,7 +20,7 @@ neigh_modify every 1 check no delay 0 fix 1 all precession/spin zeeman 0.0 0.0 0.0 1.0 fix 2 all langevin/spin 0.0 0.0 21 -fix 3 all nve/spin lattice yes +fix 3 all nve/spin lattice moving timestep 0.0001 # define outputs and computes diff --git a/examples/SPIN/read_restart/in.spin.restart b/examples/SPIN/read_restart/in.spin.restart index 39157fdac4..ccce25b254 100644 --- a/examples/SPIN/read_restart/in.spin.restart +++ b/examples/SPIN/read_restart/in.spin.restart @@ -24,7 +24,7 @@ neigh_modify every 1 check no delay 0 fix 1 all precession/spin zeeman 0.0 0.0 0.0 1.0 fix 2 all langevin/spin 0.0 0.0 21 -fix 3 all nve/spin lattice yes +fix 3 all nve/spin lattice moving timestep 0.0001 # define outputs diff --git a/examples/SPIN/read_restart/in.spin.write_restart b/examples/SPIN/read_restart/in.spin.write_restart index 42f07fd316..c127101093 100644 --- a/examples/SPIN/read_restart/in.spin.write_restart +++ b/examples/SPIN/read_restart/in.spin.write_restart @@ -29,7 +29,7 @@ neigh_modify every 10 check yes delay 20 fix 1 all precession/spin zeeman 0.0 0.0 0.0 1.0 fix 2 all langevin/spin 100.0 0.01 21 -fix 3 all nve/spin lattice no +fix 3 all nve/spin lattice frozen timestep 0.0001 # compute and output options diff --git a/examples/SPIN/setforce_spin/in.spinmin.setforce b/examples/SPIN/setforce_spin/in.spinmin.setforce index 10d4df66ed..822768e0ef 100644 --- a/examples/SPIN/setforce_spin/in.spinmin.setforce +++ b/examples/SPIN/setforce_spin/in.spinmin.setforce @@ -35,7 +35,7 @@ fix 1 all precession/spin zeeman 0.0 0.0 0.0 1.0 anisotropy 5e-05 0.0 0.0 1.0 fix_modify 1 energy yes fix 2 fixed_spin setforce/spin 0.0 0.0 0.0 fix 3 all langevin/spin 0.0 0.1 21 -fix 4 all nve/spin lattice no +fix 4 all nve/spin lattice frozen timestep 0.0001 diff --git a/src/SPIN/fix_nve_spin.cpp b/src/SPIN/fix_nve_spin.cpp index b1b466b5a4..9b4f1916ae 100644 --- a/src/SPIN/fix_nve_spin.cpp +++ b/src/SPIN/fix_nve_spin.cpp @@ -91,12 +91,17 @@ FixNVESpin::FixNVESpin(LAMMPS *lmp, int narg, char **arg) : // defining lattice_flag + // changing the lattice option, from (yes,no) -> (moving,frozen) + // for now, (yes,no) still works (to avoid user's confusions). + int iarg = 3; while (iarg < narg) { if (strcmp(arg[iarg],"lattice") == 0) { if (iarg+2 > narg) error->all(FLERR,"Illegal fix/NVE/spin command"); if (strcmp(arg[iarg+1],"no") == 0) lattice_flag = 0; + else if (strcmp(arg[iarg+1],"frozen") == 0) lattice_flag = 0; else if (strcmp(arg[iarg+1],"yes") == 0) lattice_flag = 1; + else if (strcmp(arg[iarg+1],"moving") == 0) lattice_flag = 1; else error->all(FLERR,"Illegal fix/NVE/spin command"); iarg += 2; } else error->all(FLERR,"Illegal fix/NVE/spin command"); From a6a78208aab5341b18c5f303cc563980132a607e Mon Sep 17 00:00:00 2001 From: julient31 Date: Tue, 24 Sep 2019 16:01:37 -0600 Subject: [PATCH 185/192] Commit3 JT 092419 - modified other doc files --- doc/src/fix_langevin_spin.txt | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/doc/src/fix_langevin_spin.txt b/doc/src/fix_langevin_spin.txt index e4065adad5..e5dccc5e57 100644 --- a/doc/src/fix_langevin_spin.txt +++ b/doc/src/fix_langevin_spin.txt @@ -50,7 +50,7 @@ As an example: fix 1 all precession/spin zeeman 0.01 0.0 0.0 1.0 fix 2 all langevin/spin 300.0 0.01 21 -fix 3 all nve/spin lattice yes :pre +fix 3 all nve/spin lattice moving :pre is correct, but defining a force/spin command after the langevin/spin command would give an error message. From b771225f3d7435b942334bd611eba522d534179b Mon Sep 17 00:00:00 2001 From: charlie sievers Date: Wed, 25 Sep 2019 17:19:27 -0700 Subject: [PATCH 186/192] Edit gjf option syntax within fix_langevin.txt --- doc/src/fix_langevin.txt | 5 +++-- 1 file changed, 3 insertions(+), 2 deletions(-) diff --git a/doc/src/fix_langevin.txt b/doc/src/fix_langevin.txt index 8d489a27d1..e77e676158 100644 --- a/doc/src/fix_langevin.txt +++ b/doc/src/fix_langevin.txt @@ -24,9 +24,10 @@ keyword = {angmom} or {omega} or {scale} or {tally} or {zero} :l {angmom} value = {no} or factor {no} = do not thermostat rotational degrees of freedom via the angular momentum factor = do thermostat rotational degrees of freedom via the angular momentum and apply numeric scale factor as discussed below - {gjf} value = {no} or {yes} + {gjf} value = {no} or {vfull} or {vhalf} {no} = use standard formulation - {yes} = use Gronbech-Jensen/Farago formulation + {vfull} = use Gronbech-Jensen/Farago formulation + {vhalf} = use 2GJ formulation {omega} value = {no} or {yes} {no} = do not thermostat rotational degrees of freedom via the angular velocity {yes} = do thermostat rotational degrees of freedom via the angular velocity From 5927f056c58e6d03fe3112ac497ed11973bd2ed2 Mon Sep 17 00:00:00 2001 From: charlie sievers Date: Wed, 25 Sep 2019 17:22:15 -0700 Subject: [PATCH 187/192] Removed redundant and out of scope gjf info from fix_langevin.txt --- doc/src/fix_langevin.txt | 14 -------------- 1 file changed, 14 deletions(-) diff --git a/doc/src/fix_langevin.txt b/doc/src/fix_langevin.txt index e77e676158..07d8b274aa 100644 --- a/doc/src/fix_langevin.txt +++ b/doc/src/fix_langevin.txt @@ -255,20 +255,6 @@ Regardless of the choice of output velocity, the sampling of the configurational distribution of atom positions is the same, and linearly consistent with the target temperature. -An example of a reason why to use the {gjf} keyword is the freedom to take a larger time step, -up to the stability limit, while maintaining robust statistics. It is crucial to -recall that while the equilibrium statistics is appropriately sampled, the correct dynamics -of the trajectories may not be for large time steps, as is the case for all thermostats. -All thermostats provide good statistics and dynamics for small time steps. -The 2GJ half-step velocity {vhalf} samples the correct velocity distribution for the {gjf} trajectory. - -This updated implementation of the {gjf} thermostat includes the choice between -outputting either the on-site {vfull} or half-step {vhalf} velocity. The on-site -velocity has been updated to be the GJF on-site velocity, and the half-step -velocity is the statistically correct 2GJ velocity. The implementation -also takes advantage of Gaussian distributed random numbers in order to achieve -correct fluctuations. - :line Styles with a {gpu}, {intel}, {kk}, {omp}, or {opt} suffix are From ca159b7b201893e6be10a784f8ceedd47d08d802 Mon Sep 17 00:00:00 2001 From: charlie sievers Date: Wed, 25 Sep 2019 17:30:41 -0700 Subject: [PATCH 188/192] Fix langevin removed gjf special message and adapted whitespace style --- src/fix_langevin.cpp | 12 ++++++++---- 1 file changed, 8 insertions(+), 4 deletions(-) diff --git a/src/fix_langevin.cpp b/src/fix_langevin.cpp index b5777cb5a4..f805fddb4b 100644 --- a/src/fix_langevin.cpp +++ b/src/fix_langevin.cpp @@ -112,10 +112,14 @@ FixLangevin::FixLangevin(LAMMPS *lmp, int narg, char **arg) : } else if (strcmp(arg[iarg],"gjf") == 0) { if (iarg+2 > narg) error->all(FLERR,"Illegal fix langevin command"); if (strcmp(arg[iarg+1],"no") == 0) {gjfflag = 0; osflag = 0;} - else if (strcmp(arg[iarg+1],"yes") == 0) - error->all(FLERR,"Fix langevin gjf yes is outdated, please use vhalf or vfull"); - else if (strcmp(arg[iarg+1],"vhalf") == 0) {gjfflag = 1; osflag = 0;} - else if (strcmp(arg[iarg+1],"vfull") == 0) {gjfflag = 1; osflag = 1;} + else if (strcmp(arg[iarg+1],"vfull") == 0) { + gjfflag = 1; + osflag = 1; + } + else if (strcmp(arg[iarg+1],"vhalf") == 0) { + gjfflag = 1; + osflag = 0; + } else error->all(FLERR,"Illegal fix langevin command"); iarg += 2; } else if (strcmp(arg[iarg],"omega") == 0) { From 23040a98f8e87b4b3bddc5cb66b221cba0040465 Mon Sep 17 00:00:00 2001 From: jrgissing Date: Sat, 28 Sep 2019 23:10:34 -0600 Subject: [PATCH 189/192] adds an angle constraint option for reacting molecules also, previously, reaction templates had to contain more than two atoms --- doc/src/fix_bond_react.txt | 17 +++-- src/USER-MISC/fix_bond_react.cpp | 112 ++++++++++++++++++++++++------- src/USER-MISC/fix_bond_react.h | 4 +- 3 files changed, 104 insertions(+), 29 deletions(-) diff --git a/doc/src/fix_bond_react.txt b/doc/src/fix_bond_react.txt index 4f4506944f..fb8ed95afb 100644 --- a/doc/src/fix_bond_react.txt +++ b/doc/src/fix_bond_react.txt @@ -266,7 +266,7 @@ either 'none' or 'charges.' Further details are provided in the discussion of the 'update_edges' keyword. The fourth optional section begins with the keyword 'Constraints' and lists additional criteria that must be satisfied in order for the reaction to occur. Currently, -there is one type of constraint available, as discussed below. +there are two types of constraints available, as discussed below. A sample map file is given below: @@ -300,14 +300,23 @@ Equivalences :pre :line Any number of additional constraints may be specified in the -Constraints section of the map file. Currently there is one type of -additional constraint, of type 'distance', whose syntax is as follows: +Constraints section of the map file. The constraint of type 'distance' +has syntax as follows: distance {ID1} {ID2} {rmin} {rmax} :pre where 'distance' is the required keyword, {ID1} and {ID2} are pre-reaction atom IDs, and these two atoms must be separated by a -distance between {rmin} and {rmax} for the reaction to occur. This +distance between {rmin} and {rmax} for the reaction to occur. + +The constraint of type 'angle' has the following syntax: + +angle {ID1} {ID2} {ID3} {amin} {amax} :pre + +where 'angle' is the required keyword, {ID1}, {ID2} and {ID3} are +pre-reaction atom IDs, and these three atoms must form an angle +between {amin} and {amax} for the reaction to occur (where {ID2} is +the central atom). Angles must be specified in degrees. This constraint can be used to enforce a certain orientation between reacting molecules. diff --git a/src/USER-MISC/fix_bond_react.cpp b/src/USER-MISC/fix_bond_react.cpp index 6b61a7b84d..5bf6ed68b9 100644 --- a/src/USER-MISC/fix_bond_react.cpp +++ b/src/USER-MISC/fix_bond_react.cpp @@ -35,6 +35,7 @@ Contributing Author: Jacob Gissinger (jacob.gissinger@colorado.edu) #include "molecule.h" #include "group.h" #include "citeme.h" +#include "math_const.h" #include "memory.h" #include "error.h" @@ -42,6 +43,7 @@ Contributing Author: Jacob Gissinger (jacob.gissinger@colorado.edu) using namespace LAMMPS_NS; using namespace FixConst; +using namespace MathConst; static const char cite_fix_bond_react[] = "fix bond/react:\n\n" @@ -57,7 +59,7 @@ static const char cite_fix_bond_react[] = #define BIG 1.0e20 #define DELTA 16 #define MAXGUESS 20 // max # of guesses allowed by superimpose algorithm -#define MAXCONARGS 5 // max # of arguments for any type of constraint +#define MAXCONARGS 7 // max # of arguments for any type of constraint + rxnID // various statuses of superimpose algorithm: // ACCEPT: site successfully matched to pre-reacted template @@ -68,6 +70,9 @@ static const char cite_fix_bond_react[] = // RESTORE: restore mode, load most recent restore point enum{ACCEPT,REJECT,PROCEED,CONTINUE,GUESSFAIL,RESTORE}; +// types of available reaction constraints +enum{DISTANCE,ANGLE}; + /* ---------------------------------------------------------------------- */ FixBondReact::FixBondReact(LAMMPS *lmp, int narg, char **arg) : @@ -94,6 +99,7 @@ FixBondReact::FixBondReact(LAMMPS *lmp, int narg, char **arg) : global_freq = 1; extvector = 0; rxnID = 0; + nconstraints = 0; status = PROCEED; nxspecial = NULL; @@ -169,8 +175,7 @@ FixBondReact::FixBondReact(LAMMPS *lmp, int narg, char **arg) : memory->create(limit_duration,nreacts,"bond/react:limit_duration"); memory->create(stabilize_steps_flag,nreacts,"bond/react:stabilize_steps_flag"); memory->create(update_edges_flag,nreacts,"bond/react:update_edges_flag"); - memory->create(nconstraints,nreacts,"bond/react:nconstraints"); - memory->create(constraints,nreacts,MAXCONARGS,"bond/react:constraints"); + memory->create(constraints,1,MAXCONARGS,"bond/react:constraints"); memory->create(iatomtype,nreacts,"bond/react:iatomtype"); memory->create(jatomtype,nreacts,"bond/react:jatomtype"); memory->create(ibonding,nreacts,"bond/react:ibonding"); @@ -188,7 +193,6 @@ FixBondReact::FixBondReact(LAMMPS *lmp, int narg, char **arg) : max_rxn[i] = INT_MAX; stabilize_steps_flag[i] = 0; update_edges_flag[i] = 0; - nconstraints[i] = 0; // set default limit duration to 60 timesteps limit_duration[i] = 60; reaction_count[i] = 0; @@ -1138,6 +1142,22 @@ void FixBondReact::superimpose_algorithm() glove[myjbonding-1][1] = created[lcl_inst][1][rxnID]; glove_counter++; + // special case, only two atoms in reaction templates + // then: bonding onemol_nxspecials guaranteed to be equal, and either 0 or 1 + if (glove_counter == onemol->natoms) { + tagint local_atom1 = atom->map(glove[myibonding-1][1]); + tagint local_atom2 = atom->map(glove[myjbonding-1][1]); + if ( (nxspecial[local_atom1][0] == onemol_nxspecial[myibonding-1][0] && + nxspecial[local_atom2][0] == nxspecial[local_atom1][0]) && + (nxspecial[local_atom1][0] == 0 || + xspecial[local_atom1][0] == atom->tag[local_atom2]) && + check_constraints() ) { + status = ACCEPT; + glove_ghostcheck(); + } else + status = REJECT; + } + avail_guesses = 0; for (int i = 0; i < max_natoms; i++) @@ -1617,21 +1637,50 @@ evaluate constraints: return 0 if any aren't satisfied int FixBondReact::check_constraints() { - tagint atom1,atom2; + tagint atom1,atom2,atom3; double delx,dely,delz,rsq; + double delx1,dely1,delz1,delx2,dely2,delz2; + double rsq1,rsq2,r1,r2,c; double **x = atom->x; - for (int i = 0; i < nconstraints[rxnID]; i++) { - if (constraints[rxnID][0] == 0) { // 'distance' type - atom1 = atom->map(glove[(int) constraints[rxnID][1]-1][1]); - atom2 = atom->map(glove[(int) constraints[rxnID][2]-1][1]); - delx = x[atom1][0] - x[atom2][0]; - dely = x[atom1][1] - x[atom2][1]; - delz = x[atom1][2] - x[atom2][2]; - domain->minimum_image(delx,dely,delz); // ghost location fix - rsq = delx*delx + dely*dely + delz*delz; - if (rsq < constraints[rxnID][3] || rsq > constraints[rxnID][4]) return 0; + for (int i = 0; i < nconstraints; i++) { + if (constraints[i][0] == rxnID) { + if (constraints[i][1] == DISTANCE) { + atom1 = atom->map(glove[(int) constraints[i][2]-1][1]); + atom2 = atom->map(glove[(int) constraints[i][3]-1][1]); + delx = x[atom1][0] - x[atom2][0]; + dely = x[atom1][1] - x[atom2][1]; + delz = x[atom1][2] - x[atom2][2]; + domain->minimum_image(delx,dely,delz); // ghost location fix + rsq = delx*delx + dely*dely + delz*delz; + if (rsq < constraints[i][4] || rsq > constraints[i][5]) return 0; + } else if (constraints[i][1] == ANGLE) { + atom1 = atom->map(glove[(int) constraints[i][2]-1][1]); + atom2 = atom->map(glove[(int) constraints[i][3]-1][1]); + atom3 = atom->map(glove[(int) constraints[i][4]-1][1]); + + // 1st bond + delx1 = x[atom1][0] - x[atom2][0]; + dely1 = x[atom1][1] - x[atom2][1]; + delz1 = x[atom1][2] - x[atom2][2]; + rsq1 = delx1*delx1 + dely1*dely1 + delz1*delz1; + r1 = sqrt(rsq1); + + // 2nd bond + delx2 = x[atom3][0] - x[atom2][0]; + dely2 = x[atom3][1] - x[atom2][1]; + delz2 = x[atom3][2] - x[atom2][2]; + rsq2 = delx2*delx2 + dely2*dely2 + delz2*delz2; + r2 = sqrt(rsq2); + + // angle (cos and sin) + c = delx1*delx2 + dely1*dely2 + delz1*delz2; + c /= r1*r2; + if (c > 1.0) c = 1.0; + if (c < -1.0) c = -1.0; + if (acos(c) < constraints[i][5] || acos(c) > constraints[i][6]) return 0; + } } } return 1; @@ -2757,13 +2806,20 @@ void FixBondReact::read(int myrxn) if (strspn(line," \t\n\r") == strlen(line)) continue; if (strstr(line,"edgeIDs")) sscanf(line,"%d",&nedge); - else if (strstr(line,"equivalences")) sscanf(line,"%d",&nequivalent); + else if (strstr(line,"equivalences")) { + sscanf(line,"%d",&nequivalent); + if (nequivalent != onemol->natoms) + error->one(FLERR,"Bond/react: Number of equivalences in map file must " + "equal number of atoms in reaction templates"); + } else if (strstr(line,"customIDs")) sscanf(line,"%d",&ncustom); else if (strstr(line,"deleteIDs")) sscanf(line,"%d",&ndelete); - else if (strstr(line,"constraints")) sscanf(line,"%d",&nconstraints[myrxn]); + else if (strstr(line,"constraints")) sscanf(line,"%d",&nconstr); else break; } + memory->grow(constraints,nconstraints+nconstr,MAXCONARGS,"bond/react:constraints"); + //count = NULL; // grab keyword and skip next line @@ -2874,18 +2930,28 @@ void FixBondReact::Constraints(char *line, int myrxn) double tmp[MAXCONARGS]; int n = strlen("distance") + 1; char *constraint_type = new char[n]; - for (int i = 0; i < nconstraints[myrxn]; i++) { + for (int i = 0; i < nconstr; i++) { readline(line); sscanf(line,"%s",constraint_type); + constraints[nconstraints][0] = myrxn; if (strcmp(constraint_type,"distance") == 0) { - constraints[myrxn][0] = 0; // 0 = 'distance' ...maybe use another enum eventually + constraints[nconstraints][1] = DISTANCE; sscanf(line,"%*s %lg %lg %lg %lg",&tmp[0],&tmp[1],&tmp[2],&tmp[3]); - constraints[myrxn][1] = tmp[0]; - constraints[myrxn][2] = tmp[1]; - constraints[myrxn][3] = tmp[2]*tmp[2]; // using square of distance - constraints[myrxn][4] = tmp[3]*tmp[3]; + constraints[nconstraints][2] = tmp[0]; + constraints[nconstraints][3] = tmp[1]; + constraints[nconstraints][4] = tmp[2]*tmp[2]; // using square of distance + constraints[nconstraints][5] = tmp[3]*tmp[3]; + } else if (strcmp(constraint_type,"angle") == 0) { + constraints[nconstraints][1] = ANGLE; + sscanf(line,"%*s %lg %lg %lg %lg %lg",&tmp[0],&tmp[1],&tmp[2],&tmp[3],&tmp[4]); + constraints[nconstraints][2] = tmp[0]; + constraints[nconstraints][3] = tmp[1]; + constraints[nconstraints][4] = tmp[2]; + constraints[nconstraints][5] = tmp[3]/180.0 * MY_PI; + constraints[nconstraints][6] = tmp[4]/180.0 * MY_PI; } else error->one(FLERR,"Bond/react: Illegal constraint type in 'Constraints' section of map file"); + nconstraints++; } delete [] constraint_type; } diff --git a/src/USER-MISC/fix_bond_react.h b/src/USER-MISC/fix_bond_react.h index e5452cb226..eda26f129d 100644 --- a/src/USER-MISC/fix_bond_react.h +++ b/src/USER-MISC/fix_bond_react.h @@ -64,7 +64,7 @@ class FixBondReact : public Fix { int custom_exclude_flag; int *stabilize_steps_flag; int *update_edges_flag; - int *nconstraints; + int nconstraints; double **constraints; int status; int *groupbits; @@ -108,7 +108,7 @@ class FixBondReact : public Fix { int *ibonding,*jbonding; int *closeneigh; // indicates if bonding atoms of a rxn are 1-2, 1-3, or 1-4 neighbors - int nedge,nequivalent,ncustom,ndelete; // number of edge, equivalent, custom atoms in mapping file + int nedge,nequivalent,ncustom,ndelete,nconstr; // # edge, equivalent, custom atoms in mapping file int attempted_rxn; // there was an attempt! int *local_rxn_count; int *ghostly_rxn_count; From 14933958f78d0e1fc174931349fba64b060e97fa Mon Sep 17 00:00:00 2001 From: alxvov Date: Mon, 30 Sep 2019 14:55:33 +0000 Subject: [PATCH 190/192] change units --- doc/src/min_modify.txt | 6 +++--- doc/src/neb_spin.txt | 4 ++-- 2 files changed, 5 insertions(+), 5 deletions(-) diff --git a/doc/src/min_modify.txt b/doc/src/min_modify.txt index 06c1f7514f..411f43f3b1 100644 --- a/doc/src/min_modify.txt +++ b/doc/src/min_modify.txt @@ -101,9 +101,9 @@ and {spin/cg}. Convergence of {spin/lbfgs} can be more robust if [Restrictions:] -The line search procedure of styles {spin/cg} and {spin/lbfgs} cannot be -used for magnetic GNEB calculations. See "neb/spin"_neb_spin.html for more -explanation. +For magnetic GNEB calculations, only {spin_none} value for {line} keyword can be used +when styles {spin/cg} and {spin/lbfgs} are employed. +See "neb/spin"_neb_spin.html for more explanation. [Related commands:] diff --git a/doc/src/neb_spin.txt b/doc/src/neb_spin.txt index b64df39219..0d093979a6 100644 --- a/doc/src/neb_spin.txt +++ b/doc/src/neb_spin.txt @@ -359,8 +359,8 @@ This command can only be used if LAMMPS was built with the SPIN package. See the "Build package"_Build_package.html doc page for more info. -The line search procedures of the {spin/cg} and {spin/lbfgs} -minimization styles cannot be used in a GNEB calculation. +For magnetic GNEB calculations, only {spin_none} value for {line} keyword can be used +when styles {spin/cg} and {spin/lbfgs} are employed. :line From 26427cc4cbd27ee99517492cc8578aa441a078ec Mon Sep 17 00:00:00 2001 From: Aidan Thompson Date: Tue, 1 Oct 2019 11:40:21 -0600 Subject: [PATCH 191/192] Fixed error in neighbor distance check for box dimensions --- src/neighbor.cpp | 3 +++ 1 file changed, 3 insertions(+) diff --git a/src/neighbor.cpp b/src/neighbor.cpp index d38aed08c0..2c77a13258 100644 --- a/src/neighbor.cpp +++ b/src/neighbor.cpp @@ -1941,6 +1941,7 @@ int Neighbor::decide() conservative shrink procedure: compute distance each of 8 corners of box has moved since last reneighbor reduce skin distance by sum of 2 largest of the 8 values + if reduced skin distance is negative, set to zero new trigger = 1/2 of reduced skin distance for orthogonal box, only need 2 lo/hi corners for triclinic, need all 8 corners since deformations can displace all 8 @@ -1962,6 +1963,7 @@ int Neighbor::check_distance() delz = bboxhi[2] - boxhi_hold[2]; delta2 = sqrt(delx*delx + dely*dely + delz*delz); delta = 0.5 * (skin - (delta1+delta2)); + if (delta < 0.0) delta = 0.0; deltasq = delta*delta; } else { domain->box_corners(); @@ -1975,6 +1977,7 @@ int Neighbor::check_distance() else if (delta > delta2) delta2 = delta; } delta = 0.5 * (skin - (delta1+delta2)); + if (delta < 0.0) delta = 0.0; deltasq = delta*delta; } } else deltasq = triggersq; From d117ed2b147f2c73010328d567af4a2f7b9b7a23 Mon Sep 17 00:00:00 2001 From: alxvov Date: Thu, 3 Oct 2019 22:14:15 +0000 Subject: [PATCH 192/192] remove unnecessary operations. calloc only if rho is positive --- src/SPIN/min_spin_lbfgs.cpp | 24 ++++++++---------------- 1 file changed, 8 insertions(+), 16 deletions(-) diff --git a/src/SPIN/min_spin_lbfgs.cpp b/src/SPIN/min_spin_lbfgs.cpp index db0dbbaa76..f86bdd5d48 100644 --- a/src/SPIN/min_spin_lbfgs.cpp +++ b/src/SPIN/min_spin_lbfgs.cpp @@ -372,9 +372,6 @@ void MinSpinLBFGS::calc_search_direction() factor = 1.0; } - q = (double *) calloc(3*nlocal, sizeof(double)); - alpha = (double *) calloc(num_mem, sizeof(double)); - if (local_iter == 0){ // steepest descent direction //if no line search then calculate maximum rotation @@ -387,10 +384,12 @@ void MinSpinLBFGS::calc_search_direction() for (int k = 0; k < num_mem; k++){ ds[k][i] = 0.0; dy[k][i] = 0.0; - rho[k] = 0.0; } } - } else { + for (int k = 0; k < num_mem; k++) + rho[k] = 0.0; + + } else { dyds = 0.0; for (int i = 0; i < 3 * nlocal; i++) { ds[m_index][i] = p_s[i]; @@ -410,15 +409,10 @@ void MinSpinLBFGS::calc_search_direction() if (rho[m_index] < 0.0){ local_iter = 0; - for (int k = 0; k < num_mem; k++){ - for (int i = 0; i < nlocal; i ++){ - ds[k][i] = 0.0; - dy[k][i] = 0.0; - } - } return calc_search_direction(); } - + q = (double *) calloc(3*nlocal, sizeof(double)); + alpha = (double *) calloc(num_mem, sizeof(double)); // set the q vector for (int i = 0; i < 3 * nlocal; i++) { @@ -511,12 +505,10 @@ void MinSpinLBFGS::calc_search_direction() p_s[i] = - factor * p_s[i] * scaling; g_old[i] = g_cur[i] * factor; } + free(q); + free(alpha); } - local_iter++; - free(q); - free(alpha); - } /* ----------------------------------------------------------------------