gromacs_py/doc/notebook/00_basic_example.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# *Gromacs_py* basic example\n",
    "\n",
    "Here is an example of a short simulation of the SH3 domain of phospholipase Cγ1.\n",
    "Five successive steps are used:\n",
    "\n",
    "1. Topologie creation using ``GmxSys.prepare_top()``.\n",
    "2. Minimisation of the structure using ``GmxSys.em_2_steps()``.\n",
    "3. Solvation of the system using ``GmxSys.solvate_add_ions()``.\n",
    "4. Equilibration of the system using ``GmxSys.em_equi_three_step_iter_error()``.\n",
    "5. Production run using ``GmxSys.production()``.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Import"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Gromacs version is 2018.3\n",
      "FORCEFIELD_PATH = /home/murail/Documents/Code/gromacs_py/gromacs_py/gromacs/template\n"
     ]
    }
   ],
   "source": [
    "import sys\n",
    "import os\n",
    "import urllib.request  \n",
    "import pandas as pd\n",
    "import matplotlib\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import seaborn as sns\n",
    "\n",
    "# Gromacs_py import\n",
    "sys.path.insert(0, os.path.abspath('../../..'))\n",
    "import gromacs_py.gromacs.gmx5 as gmx"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Simulation setup"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Setup data location\n",
    "DATA_OUT = 'data_sim'\n",
    "PDB_ID = '1Y0M'\n",
    "\n",
    "# System Setup\n",
    "vsite='hydrogens'\n",
    "ion_C = 0.15\n",
    "sys_top_folder = os.path.join(DATA_OUT, 'sys_top')\n",
    "\n",
    "# Energy Minimisation\n",
    "em_folder = os.path.join(DATA_OUT, 'em')\n",
    "em_sys_folder = os.path.join(DATA_OUT, 'sys_em')\n",
    "em_step_number = 5000\n",
    "\n",
    "# Equillibration\n",
    "equi_folder = os.path.join(DATA_OUT, 'sys_equi')\n",
    "HA_time = 0.5\n",
    "CA_time = 1.0\n",
    "CA_LOW_time = 2.0\n",
    "\n",
    "dt_HA = 0.002\n",
    "dt = 0.005\n",
    "\n",
    "HA_step = 1000 * HA_time / dt_HA\n",
    "CA_step = 1000 * CA_time / dt\n",
    "CA_LOW_step = 1000 * CA_LOW_time / dt\n",
    "\n",
    "# Production\n",
    "prod_folder = os.path.join(DATA_OUT, 'sys_prod')\n",
    "prod_time = 10.0\n",
    "\n",
    "prod_step = 1000 * prod_time / dt"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Get PDB file from the ``rcsb.org`` website "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "os.makedirs(DATA_OUT, exist_ok = True)\n",
    "\n",
    "raw_pdb = urllib.request.urlretrieve('http://files.rcsb.org/download/{}.pdb'.format(PDB_ID),\n",
    "                           '{}/{}.pdb'.format(DATA_OUT, PDB_ID))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Define the simulation system"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "name         : 1Y0M\n",
      "coor_file    : data_sim/1Y0M.pdb\n",
      "nt           : 0\n",
      "ntmpi        : 0\n",
      "sys_history  : 0\n"
     ]
    }
   ],
   "source": [
    "md_sys = gmx.GmxSys(name=PDB_ID, coor_file=raw_pdb[0])\n",
    "md_sys.display()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 1. Create topology:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Succeed to read file ../1Y0M.pdb ,  648 atoms found\n",
      "Succeed to save file tmp_pdb2pqr.pdb\n",
      "pdb2pqr.py --ff CHARMM --ffout CHARMM --chain tmp_pdb2pqr.pdb 00_1Y0M.pqr\n",
      "Succeed to read file 00_1Y0M.pqr ,  996 atoms found\n",
      "Chain: A  Residue: 0 to 60\n",
      "Succeed to save file 01_1Y0M_good_his.pdb\n",
      "-Create topologie\n",
      "gmx pdb2gmx -f 01_1Y0M_good_his.pdb -o 1Y0M_pdb2gmx.pdb -p 1Y0M_pdb2gmx.top -i 1Y0M_posre.itp -water tip3p -ff charmm36-jul2017 -ignh -vsite hydrogens\n",
      "Molecule topologie present in 1Y0M_pdb2gmx.top , extract the topologie in a separate file: 1Y0M_pdb2gmx.itp\n",
      "Protein_chain_A\n",
      "-ITP file: 1Y0M_pdb2gmx.itp\n",
      "-molecules defined in the itp file:\n",
      "* Protein_chain_A\n",
      "Rewrite topologie: 1Y0M_pdb2gmx.top\n",
      "-Create pbc box\n",
      "gmx editconf -f data_sim/prot_top/1Y0M_pdb2gmx.pdb -o data_sim/prot_top/1Y0M_pdb2gmx_box.pdb -bt dodecahedron -d 1.0\n"
     ]
    }
   ],
   "source": [
    "md_sys.prepare_top(out_folder=os.path.join(DATA_OUT, 'prot_top'), vsite=vsite)\n",
    "md_sys.create_box(dist=1.0, box_type=\"dodecahedron\", check_file_out=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2. Energy minimisation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "-Create the tpr file  Init_em_1Y0M.tpr\n",
      "gmx grompp -f Init_em_1Y0M.mdp -c ../prot_top/1Y0M_pdb2gmx_box.pdb -r ../prot_top/1Y0M_pdb2gmx_box.pdb -p ../prot_top/1Y0M_pdb2gmx.top -po out_Init_em_1Y0M.mdp -o Init_em_1Y0M.tpr -maxwarn 1\n",
      "-Launch the simulation Init_em_1Y0M.tpr\n",
      "gmx mdrun -s Init_em_1Y0M.tpr -deffnm Init_em_1Y0M -nt 0 -ntmpi 0 -nsteps -2 -nocopyright\n",
      "-Create the tpr file  1Y0M.tpr\n",
      "gmx grompp -f 1Y0M.mdp -c Init_em_1Y0M.gro -r Init_em_1Y0M.gro -p ../prot_top/1Y0M_pdb2gmx.top -po out_1Y0M.mdp -o 1Y0M.tpr -maxwarn 1\n",
      "-Launch the simulation 1Y0M.tpr\n",
      "gmx mdrun -s 1Y0M.tpr -deffnm 1Y0M -nt 0 -ntmpi 0 -nsteps -2 -nocopyright\n"
     ]
    }
   ],
   "source": [
    "md_sys.em_2_steps(out_folder=em_folder,\n",
    "                  no_constr_nsteps=em_step_number,\n",
    "                  constr_nsteps=em_step_number,\n",
    "                  posres=\"\",\n",
    "                  create_box_flag=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Plot energy:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "-Extract energy\n",
      "gmx energy -f data_sim/em/Init_em_1Y0M.edr -o tmp.xvg\n",
      "-Extract energy\n",
      "gmx energy -f data_sim/em/1Y0M.edr -o tmp.xvg\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'energy (KJ/mol)')"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "ener_pd_1 = md_sys.sys_history[-1].get_ener(selection_list=['Potential'])\n",
    "ener_pd_2 = md_sys.get_ener(selection_list=['Potential'])\n",
    "\n",
    "ener_pd_1['label'] = 'no bond constr'\n",
    "ener_pd_2['label'] = 'bond constr'\n",
    "\n",
    "ener_pd = pd.concat([ener_pd_1, ener_pd_2])\n",
    "\n",
    "ener_pd.time = np.arange(len(ener_pd))\n",
    "\n",
    "#ax = ener_pd.plot(x='time')\n",
    "ax = sns.lineplot(x=\"time\", y=\"Potential\",\n",
    "             hue=\"label\",\n",
    "             data=ener_pd)\n",
    "ax.set_xlabel('step')\n",
    "ax.set_ylabel('energy (KJ/mol)')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 3. Solvation (water and $Na^{+} Cl^{-}$)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "-Create pbc box\n",
      "gmx editconf -f data_sim/em/1Y0M.gro -o data_sim/em/1Y0M_box.pdb -bt dodecahedron -d 1.1\n",
      "-Solvate the pbc box\n",
      "Copy topologie file and dependancies\n",
      "Copy topologie file and dependancies\n",
      "-Create the tpr file  genion_1Y0M_water_ion.tpr\n",
      "gmx grompp -f ../../../../gromacs/template/mini.mdp -c 1Y0M_water.pdb -r 1Y0M_water.pdb -p 1Y0M_water_ion.top -po out_mini.mdp -o genion_1Y0M_water_ion.tpr -maxwarn 1\n",
      "-Add ions to the system with an ionic concentration of 0.15 M , sytem charge = 0.0 water num= 11860\n",
      "Add ions : NA : 32   CL : 32\n",
      "gmx genion -s genion_1Y0M_water_ion.tpr -p 1Y0M_water_ion.top -o 1Y0M_water_ion.gro -np 32 -pname NA -nn 32 -nname CL\n",
      "name         : 1Y0M\n",
      "sim_name     : genion_1Y0M_water_ion\n",
      "coor_file    : data_sim/sys_top/1Y0M_water_ion.gro\n",
      "top_file     : data_sim/sys_top/1Y0M_water_ion.top\n",
      "tpr          : data_sim/sys_top/genion_1Y0M_water_ion.tpr\n",
      "mdp          : ../../gromacs/template/mini.mdp\n",
      "xtc          : data_sim/em/1Y0M.trr\n",
      "edr          : data_sim/em/1Y0M.edr\n",
      "log          : data_sim/em/1Y0M.log\n",
      "nt           : 0\n",
      "ntmpi        : 0\n",
      "sys_history  : 2\n"
     ]
    }
   ],
   "source": [
    "md_sys.solvate_add_ions(out_folder=sys_top_folder,\n",
    "                        ion_C=ion_C)\n",
    "md_sys.display()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 4. System minimisation and equilibration"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "-Create the tpr file  Init_em_1Y0M.tpr\n",
      "gmx grompp -f Init_em_1Y0M.mdp -c ../../sys_top/1Y0M_water_ion.gro -r ../../sys_top/1Y0M_water_ion.gro -p ../../sys_top/1Y0M_water_ion.top -po out_Init_em_1Y0M.mdp -o Init_em_1Y0M.tpr -maxwarn 1\n",
      "-Launch the simulation Init_em_1Y0M.tpr\n",
      "gmx mdrun -s Init_em_1Y0M.tpr -deffnm Init_em_1Y0M -nt 0 -ntmpi 0 -nsteps -2 -nocopyright\n",
      "-Create the tpr file  1Y0M.tpr\n",
      "gmx grompp -f 1Y0M.mdp -c Init_em_1Y0M.gro -r Init_em_1Y0M.gro -p ../../sys_top/1Y0M_water_ion.top -po out_1Y0M.mdp -o 1Y0M.tpr -maxwarn 1\n",
      "-Launch the simulation 1Y0M.tpr\n",
      "gmx mdrun -s 1Y0M.tpr -deffnm 1Y0M -nt 0 -ntmpi 0 -nsteps -2 -nocopyright\n",
      "-Convert trj/coor\n",
      "gmx trjconv -f data_sim/sys_equi/sys_em/1Y0M.gro -o data_sim/sys_equi/sys_em/1Y0M_compact.pdb -s data_sim/sys_equi/sys_em/1Y0M.tpr -ur compact -pbc mol\n",
      "-Create the tpr file  equi_HA_1Y0M.tpr\n",
      "gmx grompp -f equi_HA_1Y0M.mdp -c ../../sys_em/1Y0M_compact.pdb -r ../../sys_em/1Y0M_compact.pdb -p ../../../sys_top/1Y0M_water_ion.top -po out_equi_HA_1Y0M.mdp -o equi_HA_1Y0M.tpr -maxwarn 0\n",
      "-Launch the simulation equi_HA_1Y0M.tpr\n",
      "gmx mdrun -s equi_HA_1Y0M.tpr -deffnm equi_HA_1Y0M -nt 0 -ntmpi 0 -nsteps -2 -nocopyright\n",
      "-Create the tpr file  equi_CA_1Y0M.tpr\n",
      "gmx grompp -f equi_CA_1Y0M.mdp -c ../00_equi_HA/equi_HA_1Y0M.gro -r ../../sys_em/1Y0M_compact.pdb -p ../../../sys_top/1Y0M_water_ion.top -po out_equi_CA_1Y0M.mdp -o equi_CA_1Y0M.tpr -maxwarn 0\n",
      "-Launch the simulation equi_CA_1Y0M.tpr\n",
      "gmx mdrun -s equi_CA_1Y0M.tpr -deffnm equi_CA_1Y0M -nt 0 -ntmpi 0 -nsteps -2 -nocopyright\n",
      "-Create the tpr file  equi_CA_LOW_1Y0M.tpr\n",
      "gmx grompp -f equi_CA_LOW_1Y0M.mdp -c ../01_equi_CA/equi_CA_1Y0M.gro -r ../../sys_em/1Y0M_compact.pdb -p ../../../sys_top/1Y0M_water_ion.top -po out_equi_CA_LOW_1Y0M.mdp -o equi_CA_LOW_1Y0M.tpr -maxwarn 0\n",
      "-Launch the simulation equi_CA_LOW_1Y0M.tpr\n",
      "gmx mdrun -s equi_CA_LOW_1Y0M.tpr -deffnm equi_CA_LOW_1Y0M -nt 0 -ntmpi 0 -nsteps -2 -nocopyright\n"
     ]
    }
   ],
   "source": [
    "md_sys.em_equi_three_step_iter_error(out_folder=equi_folder,\n",
    "                                     no_constr_nsteps=em_step_number,\n",
    "                                     constr_nsteps=em_step_number,\n",
    "                                     nsteps_HA=HA_step,\n",
    "                                     nsteps_CA=CA_step,\n",
    "                                     nsteps_CA_LOW=CA_LOW_step,\n",
    "                                     dt=dt, dt_HA=dt_HA)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Display history and plot temperature"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "State -7:\n",
      "\n",
      "name         : 1Y0M\n",
      "coor_file    : data_sim/prot_top/1Y0M_pdb2gmx_box.pdb\n",
      "top_file     : data_sim/prot_top/1Y0M_pdb2gmx.top\n",
      "nt           : 0\n",
      "ntmpi        : 0\n",
      "sys_history  : 0\n",
      "\n",
      "State -6:\n",
      "\n",
      "name         : 1Y0M\n",
      "sim_name     : Init_em_1Y0M\n",
      "coor_file    : data_sim/em/Init_em_1Y0M.gro\n",
      "top_file     : data_sim/prot_top/1Y0M_pdb2gmx.top\n",
      "tpr          : data_sim/em/Init_em_1Y0M.tpr\n",
      "mdp          : data_sim/em/Init_em_1Y0M.mdp\n",
      "xtc          : data_sim/em/Init_em_1Y0M.trr\n",
      "edr          : data_sim/em/Init_em_1Y0M.edr\n",
      "log          : data_sim/em/Init_em_1Y0M.log\n",
      "nt           : 0\n",
      "ntmpi        : 0\n",
      "sys_history  : 0\n",
      "\n",
      "State -5:\n",
      "\n",
      "name         : 1Y0M\n",
      "sim_name     : genion_1Y0M_water_ion\n",
      "coor_file    : data_sim/sys_top/1Y0M_water_ion.gro\n",
      "top_file     : data_sim/sys_top/1Y0M_water_ion.top\n",
      "tpr          : data_sim/sys_top/genion_1Y0M_water_ion.tpr\n",
      "mdp          : ../../gromacs/template/mini.mdp\n",
      "xtc          : data_sim/em/1Y0M.trr\n",
      "edr          : data_sim/em/1Y0M.edr\n",
      "log          : data_sim/em/1Y0M.log\n",
      "nt           : 0\n",
      "ntmpi        : 0\n",
      "sys_history  : 0\n",
      "\n",
      "State -4:\n",
      "\n",
      "name         : 1Y0M\n",
      "sim_name     : Init_em_1Y0M\n",
      "coor_file    : data_sim/sys_equi/sys_em/Init_em_1Y0M.gro\n",
      "top_file     : data_sim/sys_top/1Y0M_water_ion.top\n",
      "tpr          : data_sim/sys_equi/sys_em/Init_em_1Y0M.tpr\n",
      "mdp          : data_sim/sys_equi/sys_em/Init_em_1Y0M.mdp\n",
      "xtc          : data_sim/sys_equi/sys_em/Init_em_1Y0M.trr\n",
      "edr          : data_sim/sys_equi/sys_em/Init_em_1Y0M.edr\n",
      "log          : data_sim/sys_equi/sys_em/Init_em_1Y0M.log\n",
      "nt           : 0\n",
      "ntmpi        : 0\n",
      "sys_history  : 0\n",
      "\n",
      "State -3:\n",
      "\n",
      "name         : 1Y0M\n",
      "sim_name     : 1Y0M\n",
      "coor_file    : data_sim/sys_equi/sys_em/1Y0M_compact.pdb\n",
      "top_file     : data_sim/sys_top/1Y0M_water_ion.top\n",
      "tpr          : data_sim/sys_equi/sys_em/1Y0M.tpr\n",
      "mdp          : data_sim/sys_equi/sys_em/1Y0M.mdp\n",
      "xtc          : data_sim/sys_equi/sys_em/1Y0M.trr\n",
      "edr          : data_sim/sys_equi/sys_em/1Y0M.edr\n",
      "log          : data_sim/sys_equi/sys_em/1Y0M.log\n",
      "nt           : 0\n",
      "ntmpi        : 0\n",
      "sys_history  : 0\n",
      "\n",
      "State -2:\n",
      "\n",
      "name         : 1Y0M\n",
      "sim_name     : equi_HA_1Y0M\n",
      "coor_file    : data_sim/sys_equi/sys_equi/00_equi_HA/equi_HA_1Y0M.gro\n",
      "top_file     : data_sim/sys_top/1Y0M_water_ion.top\n",
      "tpr          : data_sim/sys_equi/sys_equi/00_equi_HA/equi_HA_1Y0M.tpr\n",
      "mdp          : data_sim/sys_equi/sys_equi/00_equi_HA/equi_HA_1Y0M.mdp\n",
      "xtc          : data_sim/sys_equi/sys_equi/00_equi_HA/equi_HA_1Y0M.xtc\n",
      "edr          : data_sim/sys_equi/sys_equi/00_equi_HA/equi_HA_1Y0M.edr\n",
      "log          : data_sim/sys_equi/sys_equi/00_equi_HA/equi_HA_1Y0M.log\n",
      "nt           : 0\n",
      "ntmpi        : 0\n",
      "sys_history  : 0\n",
      "\n",
      "State -1:\n",
      "\n",
      "name         : 1Y0M\n",
      "sim_name     : equi_CA_1Y0M\n",
      "coor_file    : data_sim/sys_equi/sys_equi/01_equi_CA/equi_CA_1Y0M.gro\n",
      "top_file     : data_sim/sys_top/1Y0M_water_ion.top\n",
      "tpr          : data_sim/sys_equi/sys_equi/01_equi_CA/equi_CA_1Y0M.tpr\n",
      "mdp          : data_sim/sys_equi/sys_equi/01_equi_CA/equi_CA_1Y0M.mdp\n",
      "xtc          : data_sim/sys_equi/sys_equi/01_equi_CA/equi_CA_1Y0M.xtc\n",
      "edr          : data_sim/sys_equi/sys_equi/01_equi_CA/equi_CA_1Y0M.edr\n",
      "log          : data_sim/sys_equi/sys_equi/01_equi_CA/equi_CA_1Y0M.log\n",
      "nt           : 0\n",
      "ntmpi        : 0\n",
      "sys_history  : 0\n",
      "\n"
     ]
    }
   ],
   "source": [
    "md_sys.display_history()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "-Extract energy\n",
      "gmx energy -f data_sim/sys_equi/sys_equi/02_equi_CA_LOW/equi_CA_LOW_1Y0M.edr -o tmp.xvg\n",
      "-Extract energy\n",
      "gmx energy -f data_sim/sys_equi/sys_equi/02_equi_CA_LOW/equi_CA_LOW_1Y0M.edr -o tmp.xvg\n",
      "-Extract energy\n",
      "gmx energy -f data_sim/sys_prod/prod_1Y0M.edr -o tmp.xvg\n"
     ]
    }
   ],
   "source": [
    "ener_pd_1 = md_sys.sys_history[-2].get_ener(selection_list=['Volume'])\n",
    "ener_pd_2 = md_sys.sys_history[-1].get_ener(selection_list=['Volume'])\n",
    "ener_pd_3 = md_sys.get_ener(selection_list=['Volume'])\n",
    "\n",
    "ener_pd_1['label'] = 'HA_constr'\n",
    "ener_pd_2['label'] = 'CA_constr'\n",
    "ener_pd_2.time = ener_pd_2.time + ener_pd_1.time.max()\n",
    "ener_pd_3['label'] = 'CA_LOW_constr'\n",
    "ener_pd_3.time = ener_pd_3.time + ener_pd_2.time.max()\n",
    "\n",
    "ener_pd = pd.concat([ener_pd_1, ener_pd_2, ener_pd_3])\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'Volume ($Å^3$)')"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax = sns.lineplot(x=\"time\", y=\"Volume\",\n",
    "                  hue=\"label\",\n",
    "                  data=ener_pd)\n",
    "\n",
    "ax.set_xlabel('time')\n",
    "ax.set_ylabel('Volume ($Å^3$)')\n",
    "#ax.set_ylim(305, 322)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 5. Production"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "-Create the tpr file  prod_1Y0M.tpr\n",
      "gmx grompp -f prod_1Y0M.mdp -c ../sys_equi/sys_equi/02_equi_CA_LOW/equi_CA_LOW_1Y0M.gro -r ../sys_equi/sys_equi/02_equi_CA_LOW/equi_CA_LOW_1Y0M.gro -p ../sys_top/1Y0M_water_ion.top -po out_prod_1Y0M.mdp -o prod_1Y0M.tpr -maxwarn 0\n",
      "-Launch the simulation prod_1Y0M.tpr\n",
      "gmx mdrun -s prod_1Y0M.tpr -deffnm prod_1Y0M -nt 0 -ntmpi 0 -nsteps -2 -nocopyright\n"
     ]
    }
   ],
   "source": [
    "md_sys.production(out_folder=prod_folder,\n",
    "                  nsteps=prod_step,\n",
    "                  dt=dt)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "-Extract energy\n",
      "gmx energy -f data_sim/sys_prod/prod_1Y0M.edr -o tmp.xvg\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'Temperature (K)')"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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c8+fJBZVtrwj7m3/PZsQ1b7Tr3vbiZ49M41fPzcp6vVAvpmLUT6WKyC41yoULC9A5sLn+thLYIEK2DaJMPBbLJTq8MwPlyhrvfb2+4LLtjdR8YUb5RfAW6sWUMiSRUGFqszIZyxkI6MN3G6WUIGxik/JLUNYFKBcHi+1WgigGBREI2821c7vSYbjGXY7OporgpNozmOtbkrQkUkXfVwwCCeI7DseLqQQqJmslDFRMbgQEogAUEgdR9pTBgiq65hqExXBS7Xn0vW95h1P/+lk77iwc5eKyuL1ga3O96TiI0qmYimGMOhPlwtwEBKIAFCJB2B+02ElS35pkyuLadvWrPXDbIHKomIqYKMUO5rX1rQAsWNuQs1xHF5xyNZ5/V7G1uV5bLVQKCcKuq1x0/wGB2IZQCIFo78C68InpnPnIFzTFS69ueXXWau54c6HrnCGzSxDqMySL0cUW+ehTl2wCYFDPipzlOjpXy2WSbS/oqvddikA522W2qHEPvDZ7TcFbAhSDchm6AYEoAIWomNq7mH25wtw/ojPE8yuencVDH3/rOueSIDxtJpXnLIbgFfvss1fVAbDLgO45y3WUmwsIxNZFKbjvlkTKNQ5zIWWVK0WqjVA7JYjLn5lZ8JYAxaBcxm5AIApAISJsez+ofdvWGg7q+Pd2WTXQFWWkLrL3DW1Jqy+57+voJGnveiWlZG5NfYfa3h5RijVtzxvf5qxHphVU1p6XpUy1UT42iK7ugYmAQBSA4mwQ7Wtja+nLXak2PAt7SuHcivHmKHYwN1vqtHxtdHTBaa9U9trsNZxw/xRen7OmYx3YzlAqrvezpZvyltEN6Yyf0tggzP/l4uZaLnvbBwSiABRjg2hv0FipRcpsi6PLi8nzWGpa81SBYn6utv7w1kIu+uf0jPO2vSWfON9VEsS3G5sBWLy+qUPtb2/oiNdYSyLFZ9/mJww21DlZEi8mzY6DKI+FuUw0TPkD5YQQ/YAfAIOBVmAeMLOrtwPdmijEBpHrbRSy4VCpCUS2cZ4rkjrZTgkiW9cf/Ohb3/PNVkrlfG10nEC07/5y3fxp0fpGjvrTZP51wf78YJf+Xd2dDHRECr7qhTm8PqdwY69KIEqTrK+8IqnL3gYhhDhYCDEJeBf4MTASGA/cCswTQtwghMhtZdyGodK/QiI1c6mYCjF8lXo4ZDP0ub2YvCqmdtogiux8WoLI/V67yotJcxK3lccktWFz2G/OW9fFPfFHRxa1JRuKk9biSn600uZi6hoV09r6Vt5Svmu5EIhcEsQpwC+klEu9F4QQUeBE4BjghU7qW5dC5W4LSdaXiwhku9QZ23/m608uI7Xq4ldcoFxxfbcJRD4i1OE4iHbeXm6pn70o171HOqJiioSK03arRKE0bq6ZKqZ19W0ccPv7PHTmeI4ZvUOH28iFUx78lLX1bSy/4zhg2zBS3+hHHCyMllK+IKXc5olDNmOQyoEXYoNwvJF8qsu20DQn0gO71GtRtsU3l5urS4LYCkbq/F5MxdXrRXvdLjWtvFI/2yg3icaLjhDUQvN+2VDVvqWwQdhMgTpmZlnu2C9+lT07cqmwtr4NgD1vfIt/fLK0bL51LgLxnhCil/ekEOII4NXO69LWRTauRzXY5iIQz0xbyYhr3sgZ6JZt4tS1JJzjfONh0frGnGm8vVAlgGySSk4bRCflYjIMSUuiMBtEV8dBlAsXt62gI6+7WAlCnZOl2DPeViuqdbUmzTldFQ11uP5C0ZLQufWNr8tm7OX6Ko8BH1pGagCEEP8FPIKpXvpOINsipHrx5DJS//GdRQBsbIoD/uqWbB+7riWplMk9Ip6ZtpIbXp2Xs4wKdfFV23fnYvJIEGocRBEqpmIGc7OSoC8fAegoF9XeSVauNggbZaphKoqgL9nQyIhr3mDeajPeJBouUsWkEIhSqAJtqVG1i9mMTGV06ye9Lhf1ZtYnl1I+JISIYxKJo4BTgcuBw3OonrY5ZONiVU4il5dE3BJv61uTWctkmziqaJxvQKR0WZRvtHexD2kmF2S4VEzeNtrnxVSMib1Z2RQ+n5TSUS6qvQt8udogyqs3mSjmfb0930y3//qctYwe0qvdEkQsrJUkgttvw6BWm0BEtp4EYaNcxl7OryKlfAy4HfgKOAc48LtEHCC7W1uhNgibeNjqIr/vmm2hUolQvvFgSFmUEVBd7FVhQJ1L3kGYzOPF9D9//5xbX1/g07eCu0VT3CSklZFQ2cZBaGW2/aQNuz/5XKa7CsW8L3t+RS3bg9cGkY+423OyIhIqiTrGL5LaliCqYh0nEHUtCUZc8wbvLihsH5psj59IGZ2eJl9FLjfXmUKIr4CrgCqgJ/C2cv47gWyqlEIJhK1+2tJsLnx+3zXbAHbbCXL305AyI7AtF7Kpi3IRGVc5n8Y+W7qJf0xZlnG+mIWhyZIgelVGyjcOwpEgOtT8dodiOHl7IbYlh2jYvQjnsyvYHncVEa0kUcd+gXJpFVPHCcTXaxsB+McnhfHX2cbuT//+GXve+HaH+1MocinXTt1qvehCZLVBqKJmAV4SWxSDc8FtKJMg32KmG7KoBU+t2x09ncMGodxTjOGvGDdX24OpV2WEDY1tuevt4LxvP4EQHbq/s1BevclEMe/LZsDCFoHwShCtST2nXcIeq7FwqKT7fqiMka0CjmgdTzhhvxubEOUv739+5sq6DvelGOSyQfiHwX7HkN0GkR4oDVnsC6pk4Rici1IxFW5oM2RxfuYpw9+eoOewQbQ7m2seyUY3pDMxbG+vXt0irLH2hchabxfHQZQrylTDVJTElXQkCPNhoh4bxFcrt5BMGRy11yDf+20VaulsEJleTLYqpxQEyO5j4QSiPNiBXCqmD4UQlwghBnvOh4UQE4UQjwghzu38LnYusg0ue6BURUM0tvnr/GzPJcgjQRSQFynfcDAMiZSFG16zSRDZvJu81wpNuQz5JYiUD1fWIxYuwAZRcBey3N9eI3V5ShDljvZIEBFHgnAvRec+9iUXPTkj+/3W4IhFtJIs4CHHiyldlx2nVAoCVCyBKBcPulwqpuOAC4CXhRBDgM1AhfX3PvCAlDIzE9s2hmwShM2h9Osec9JTH/PnyQC89auJAGxSCEQuT6ds4yvp4ubzqJis64aEQmKKskkN2eIjoPS5mPzatwlvRQFG6o7HQbTvvrL1Yiqz/nhRlArUyE0g8t7vSBAh6ozsHoTFQh33bSUkEHa94Q6qmLY2cqmYWoB7gXuFEDFgANAqpdx6+2NuBWTLB2Qbn/tWRVlX34aUkoXrGl1lVJfNXMhmRHN5GuU1Utv9lQVxIaks6iKVCGS6ufpLGvmQb11w7zNhTexIftVARxfEdk9sR4Io7rbZq+r4auUWzj1wZPvazQN7ARZdHAmRjRsuxokikXIvmMVGUqdtELmN1B8u3MD3d+5HRR5XVXusqfPGjtkpjQRh1qsVqB/cptJ9SynjUspV3zXiALkkCPN8v6ooCd1wSQj2YPJzN/MPlMtvpPYrMn35Zv74zjdsaU44A6ZQLi2bWsnlWuvdD0K1WxShYiokhsNp31YNhEOkDJmTCHR1HESx95/0wFRu/k+mG3CpUIqI4VLgoDs/YPzv38043x4JwpaMi30y24spFs6uYlq0vpFzH/+Sa1+em7c+lQGz0VRgSphCYE+nQlVMpTS8dwRbP0SwzJAtWCupSBDgNlQ3tKXoVRlx3OCqe8TY2GhFUvtUl13FlNtI/dTnK3hl1hq2tCScgVvoYFXVV7pr4c9ug0h67BbPfbmSxeubuP74PXO2la9HLvdZxbho9yEb89jVcRBlsneMA/vbdbWR2s4b5EV7vOxs5qVYjjmZSquYsvEydkK/bzySvx/svqvMVFNbYRtbFQJ7wS/cBtHhJkuC7X7DoHyR1H27WwRCMVSvtbxv7EjLgT1jzjW/SdJRN9ctLUlngBUq7rpVTOnzuVVM7vw2V7841zfuwYu89hMfacYW+XOl9OiqOAhHgigzx1L7XZWbbcRGMaoYW4WbloyLays9jrSs7yMWMZe3YrYMVueAPedLoe6xmbTCbRDK2tCF6qaCCIQQYqgQ4jDrOCaEqOrcbm09ZLNB2IO9bzebQKQliLV1Jgdlq5h6VUbS9/l8y0LcXP2KJBXuyq4j11hR28kWKJfLtdYtQRTu8ppv/PrFV1RYkzdX3VszDmLpxiYnbbSt4y8TNbAD+5uWQifeGSimW/ZC7EgQRX7spBoHkaVhWxIsJNurPdzVd2x7JpbESG31V2uHkbor1U15CYQQ4jzgNeAf1qnhfIeyuWZNi219lD4WgahXEuvZ/vst1sDrWZEmEDa1V0Pqs42vXDEJkBajDSnTKqYcg1W9lM3N1W2DcCPhkSBs5HLh9a/JDbdHVVo14L3mxdaKg9jSnODwP37Mja/MN++jfYtWZ8O7qHZF+09/sSLr9WJsNvb4ssdzsfYe1dkh25yw6yxOgjD/b2lJOOOnFO/bCZQr1Egt/efv1kYhEsTlwAFAA4CUchGmR9N3Alk31rHO9+5mLv62jQFgfYN53JrQEQKqYmlTjm5Ivl7bwIXKXsyFRGv7LUY2t28GyVl15ZhI2dxZ/byIIHNS2oF/Qrjrqm2Kd8iYrBuZhMeRIHIYXrdGHMQrM1dz9mPTAJi2fLOr3TKjD867K8aBoJT417SVXPdy9ozCxSxkSQ+xK5ZLtqXraMhtpP5k8UZWbW5x1RkvQILwEoNNTWmmqJRG6nCB3lr5NhPbWmqnQghEm5TSeVtCiBDlm3G4IBiuhTSLBGGd72MZqdc3pA1zLZZ3Q3Ncp1sk5HLRM6R0ERP7nB/yRVKrBry0iqkwjjurBJFDaknoBmFNEAlprr7VNiY6pArKzCwrnBQLubizrREH8avnZjGnxko5HbIN5+3jagvFJ4s38sKMmozzKzY189E3G7LeZxP9rpIgWhK5F9qiVEwe1VK2e3O5iIc1QUgTrnHys0emcchdH1r3mufaipAgbGZGjXHq6DhcuK6BD63vaqu93pq31qWVyOiPT4JNdTxuLbVTIV5MU4UQVwEVlh3iMuD1zu1W5yKX+Cal5IT7pziTwbYvqFHTdoRlazJFZTTs8kzQDZkxkQpyc/W5nvBVMWV/LvVZsh3nIkqJlEE0rCFwq5U2Ncc7pAryxleENOEY63Ld2/H9IIq7PxJ2Z3HtrHX4Z4+YEsup+wx1nT/kro8AnG0nvbDfY1epHGJ59mwoTsVkETs9NzHWpUTz4UdThiQcEmiayPjOhvP9zINCdoS0y9oMVG1zevx39H0f8+dPnOOwJlhb38rFT33FxN2q+ed5++Xsj9p+qffAKASFSBBXAY3AQuAKzCjq6zqzU50Nlfp6F76vVm5h3uoGlm5sBtKTQk23YRunWxI63aIhwkoyL13KDKNYIW6ufhMkzWWlB0mugaE+VzKLkTmVwzBuE4iQJlxS0MbGeJ6FPOsl13OY7UsiFufnveaFeun0hz8vaKK7+1XcJLIliEKktVK268WmprjvopRWMXUNgcgXbFYMV2t/S5tjz8b4ZE+FYxDRNDRRmI0vH5w4CN1WMZnjv8IK6DQMyS3/WcDKTS0F1+mHkKY57rcrNzXn7Q+kpSh1H+6t5YKdk0BY6qRHpZR/lVL+WEp5snWct3tCiAohxDQhxGwhxHwhxM3W+aeFEN8IIeYJIR4VQkSs80IIca8QYokQYo4QYnxJntAH6sv1ejG9MnON63fUIRBpcdCOoE4TCEXF1E4Jwm8sp20Q0lmEcw16I4vUkC1QzleCCGlEwxq1ig62timRcyHP7+bqDsALhzTnneW2QaSvffrtJhatz+/PbqM5nmLe6gag8LiBqBKbAe23QXSUudvn1ve4862FGed1R8XUNTYI226UDcUw2jYTpechxjkJRFgjJETWMsUQeG8cxObmBJqAflUxdClZsLaBR6cu4xfPdGyng5Cm7DeSo5yfOsn2slPPdTbybRikAzvYi3iRiGPuPrc3MBY4RghxAPA0sDswBqjEzPcE8CNgV+vvIuCv7WizIBg5JIjNzW6PnbCmIYS/BNFqE4iQW4LwRlgXlGrDp4xLxVQAV5vNW0n3uLlmS6OcsK5FQppLglAjuf2Qb6gmPSp+6UJ+AAAgAElEQVSmSEiVIAqPgyhkTvzupbnc8Mo8LvvXV9zzrrkdbKEGM3tPgo5KEOp993+wmPlr6ouu4z2fjWVs9UehnPHb89cxZXHpkh9UhHNLEMW8r7ak183VPH/9cXu4ymVbCFO6JKwJx23Ub3y2j0CY/aptStC3Kko4ZBKgfAyaH5O0vLY5Y6dJTRPKfiOFSc+OBJHy1wp0JgqxQSwFPhFCvAo4MpGU8t5cN0nzjTVZPyPWn5RSTrLLCCGmAbYi9iTgn9Z9nwshegshdpBSri34aQqEOui8L7ox7l7cQ5ogomkOgehREXZsEC2JFN2iYY8Ekel3ne1bqsTJr4jqk617JlL+5/KPnk7pklhII5EystogUrqkZktalE4p7fsh3zx0q7hMG4Rf9sx89RYSuPbMtJVA+zaaTxup/dsvFI4O3JDc/c4i4imDvQb3ynmP9z34EXGboSg05cbPrWyo2WwauXD9K3N56vOVrnvzRQEX41nTZnHDqpvrsL6VnHnAcG5942unXPYdHyWRkOa4jfrZKopx9rKni/0dGlqT9LTsj+peLNmkUUNmZgQ49O6P2GVAd/dJqWxIlaN/ho8E4dqiuIy8mDYC7wLdgGrlLy+EECEhxCxgA/CulPIL5VoE+BnwlnVqCLBKub3GOldyGJ4FS0Wzl0AIczFrtLbKrO4ec7yYWhI6ldGQy3XNz0jd3khq1c017WWRS8Wk3utftypBeJuMWyqmSEg4i5wdqZqz3XxGapcXlUFYS6uYijF+FzMn1G05C92iM53+ozQShG0HKqQe1WsG/Hcxa6+RWg3yLBRPfW4SWlWtUcieJYXCXuxUN1dNiIxI46wShGE4RmrA4vK946UdEoTyjsOaICRMI7hdU7ZEidm+yZINTa7fqrq4kP6Yx+Z/lwRRLl5MUsob2lu5paIaK4TojZk2fLSU0nakfhCYLKW0Tfx+bz7jLQghLsJUQbHjjju2q1/qt/R+2CbP3g+aZvou2xJEv+5R1jiR1DpVHhuEqWJyEwjvwNUNSSJleIzUmf20A+WklAUtWtkkI/cCLV269ldmrube9xfz/q8PIaEbGZ4qVVFz34ZcAzLfUFVVaSndVjHlj6T2XssW9V4qeLn29jJp9qtKqwjz37PB4xrtp86xVUyF7NWhMjozV9ZxyG7+PF1tU5zWhM6wvt38+9UQd67le45CF+TGtqSjYlJTbdjMmIpczFVYkUT9mJhiuGy762oSQU0IEGZb9rNpAl6cUUOfqgiH7z4w3Zbn2VXC6uqTUiyX7U69lFYxFU6sS4VCIqnfFUK84/0rphEpZR3wEXCMVef/YUoh/6sUqwGGKb+HAm6LsVnX36WUE6SUE6qrCxJkMpBt8YR0BkcbNldjE45+VTGnjClBhF02CNNI7bFBeL7l9a/MZY8b38qbzVXVOdtrQk69ZRZvJa8XkyNBIPnf52extLaZhG6QSJnbPKoLZUXE3NLR3df8nFq2WBM7XXkhEoSfhNMe5JIfVOK+uTnBlMW1HY6DsPlNJ1q4gHq826/6GYTtb1qIBKHG7Sxc25C13IRb3+PgP3yYcb7S8lhaU5fe9S+vBFHggjxrVXrbTDUeQghT2lNpRE4jtapi8mFi1N/5+qYaqRevb3TGachyo7WrEkLw63/P5rzHp/vebyPbVgCFqov93FzbusCLqRAbxPXKcQXwE0wDdE4IIaqBpJSyTghRCRwJ3CmEuAA4GjjC4w31GvALIcSzwP5AfWfYH8DjIeB5014CYQd12QO5f4+oYqROZXgx6VJm1OEduM9MMzVpiTx+zS4VUwEGymyEz50LyVDcOc09gRMpg7aEQSJlUBkNuQZuRURD12XGgHVFhPp0KZs040xsRzVQuJG6GAJRqGE6EtJIGeZk/njRRj5etJErj9zNt30wVSNfr21g3I59stZpP679/bKtq4YhHRVJQ6t7zPi5lNrfNF+g3LRlm529DAop74c+3SK01uuuzK35JYjC6p6xYguaMImQPTakzbFjzjkjjzpNjYMAc8H0DiX11raUTrdo9uXO/tYzV9bxwz+ZG4N9b2gvpQ/mdVVb6Y52dtfnVVWr9xSiDXBpObrQi6kQFdMXnlMfCyE+LqDuHYAnLFdZDXheSvm6ECIFrAA+s3TDL0kpbwEmAccCS4AWoNO2M80WByGlzPiwmhBEFALQrypGUpfEUzotyUw3V92QGVuUZhsI+UTGlMKBOoMqV6BclufyejdFFH//sCZIYG4Sn9ANeoUiTrshK6pal9ITDS1RNSD5Mthm3qtIEEWk2sgXB5GNS8xlggiHBHhU9Is3NPq2D3Djq/N4fnoNn1x1WFa1jDdAK1u/koZBTAu5ytqwCcSSDY0M6d2NymhIycVk/p+1qo7qHjGG9K507qtrSfBff/vMVVd7JKFe3aKsqW9z7RteKBeeC8trm3n+y1WMGtSTejWNvZF2/zT/5yYQSd20Zdl8ii4zJQi1v6ZLevblzq/rdn9ShnSkQXUo5VRVZyEQpj3RajNrbzw2CFvF5JIgyoRACCF6Kj81YB/MxT8npJRzgHE+533btLyXLstXbyngF2U86vo3OXLPgRncVkgThEJpzsaOrN7cbCbzqoyGCHlUTN7Bke1jqsnx/EoklDiIQtxcDRch8DdopQzDZYOwOfnWpE4yZdon7HcQDWloQmAYMmuMBWTbA8Nf3WVGUisSRE4uyn0tH4FoLSDnjhdRn60uF1gqGb+e2Wk5chl+bblYlQD9kNIldhqvuO4lEGaA1gn3TeXXR+3GBQfvlJYgdMmqzS2c/MBUAGbfeBS9rJxhfvunt2ctsXmedS4JouME4qWvalhT38Z9p4/nV8/NdAWA2oQ8rAlHRZFtfNiSsOoNl2mzSv9uzZMmxK+dkGaapA1FxaruCKcSXi8RziZB6Aqzl9sGocw3R4IoTzfX+ZhzRQApYBlwYWd2qrOhfhd70sVTBm/MydRoaQIilkE1FtaoipmcXW2jGS9RFQ27JAxdygxDd7ZvGU8aTiSo32BxFhhDUTF11Eidki4vJluaaE3oVhxEyOGWomHN9AP3cGdert+vR972V25qYWNTGyndIKIJR0XlN9B3vnYSvz5qN3bq784qn0/F5HIOEOphdhHCby9kO4re75vYHlG51kLHiymPDUIl4l7iFwuHSKQMWpO6E5OSVNQuqn/9qi0t9OpmqkNUqbQqGqI5obfLoGkT2w0NaW1yKYzUdhzMPsP7mEFuDuOjSBAeiVxFzZYWhvbpRko3x7GjYpIygxFT+5PIY9j367tm2UR0QzoOJao02h4JQroIRK7+KMdGZp1lEShnYScp5Y5SymFSypFSysOBqZ3dsc5EtjxFXtgDxOZSIiHNEVNrLbfEymjI5XlhyMykZtkmTkIxGLuScxmSP727SMkJJBXf/BwEQnkWlUjpyuRIGobLnVOVIBKKmyuYBEKzJog7n5J7sqnPd8J9U0ikDCdIze7XxLs+5Cd//cz0PlG8mLwSW0o30A3JH976pmgVk4tLVO/NoWLK5dvv990KsW2kCURuN1fVFdlPxWQvSrY9QU33rRJL1U7QmjDPHzqqmtcvP9hqv4BOe9BmvUt1Yc1YgDN++9c1f029kybc8Q7CfPeqkdrOWONV2dqYvnwzB935IUs3NpE0JOE8Rmo/NU02+PVdE8KJ1HZ280Od60r9nuqzGalVW4lriHoGlrtu87hOyY/WWYkkvSiEQHhtEADTSt2RrYlc3LAKe/GwvZQiobQEYSfv6xYNubhQw0fUVQenehxPpg3GHy3awPLaZlbXtTJj5Rb+8v7i9D2KC18uRkgd5OsULxZ3qg0jbYMgPRnbkroZB2FFUgOOCK/aQMw+ZFcxzV1dz3PTV/HY1OXp9l0qJrP9bKk27D02hPBTMeVWE7Qk00RRdSFOpAymW6m8vSg2ANCeyJuaE5zxj8/52sdDyK4ykYdApIzsEoQQaTdne7FJG6kNV/l1ip3ADkA7/6CRjOxfhSayLybZXDHNeuygvOyOFLm8hgCW1TazoaGN4+6d4qQJl4qkENKEa6/1kHLeqVP5PmssQljblHAkUVuC2OwT7a/OlXwct987ClmSrkkgrMpcEkTmIm4jm4rJZU9U7vEyHn7SyRYl++vWyvieVcUkhBiAaWuoFEKMIf0MPTGD5rZZ5PJiAugRC9MYTzkDOexIEILKiPnK7Hzx3aIhF7fgNeiC+2OrqoG45VYKZmCSHZx0/+lu040ayZnTi8kqUxkJsa6+DSHMCWl4CGLYCveXqgSR0EmkdGJhjbhNIJRcN15Dswrv5PLm3/feq0ZSe+tqsd5lhc9OYcWomLwL7qkPfca0a49gQM8KT98K86KaW1NPYzzpEIjb3viab9Y38u6C9exUXcWPH/jUKeu4ueaJg0imVBVIptRpSxjN8RQnPTCVZbWm6kvXpYuzV5kBW4qy3VRtCdAPqr3Cduv01pMrX5huSFRnK69O/rC7P3I/r26YnltWMyFNUySItPouG4FotSSpRMpIS6LWPcffN4UbPHun52JqvPC7HNKE+f6kf5oTdd57CUQ2FZNqg8iZvsbHBrGlhBlmC0UuG8RxwHmY8QgPKucbgXYHz5UDVOrr5wLYszJCYzylSBBpFVPUSgltGykrI2HXYiRl5qKjci+blI9sRy574eU+pEwPiEJUTEP6VLKmrhXbFyRDgrBURy4bRFJ35WICy0ituW0gkN8G4X2nXi+qsOY2Lrqe3VoEKqMh32yzuaCqmPzmj99+BrnSVqif8YT7pwAweojps/GNlTiwf/cYy2tbHMM2pCUPu+6sW856JIiKiOb4ukuZ5t6bEylmK7EDSUO63oWqYrIjlCsUApFtLVHVkLaLs93fVifSOXv0bqZROH3s98jN8ZTL1hBW9nIw3VzNcuqua+pYsr9fPKWbEfmKkRrg0yXuvFNuFVNmf7KVtaEJe78JQ0lzkq5ITeCZqWLKZoMo0IvJR+ugpuDv8kA5KeVjUsqDgfOllAcrf8dKKf+9VXrXSchng7BzsIR8JAhbd95gSQJVsZBzzoZ3IVMXCPUj2yqdfFBtEIV4/QzuXUlLQk/f49kTOqJ4Z/jaICwiGAlbE0S61Wa5bBCQ+U5dyfp0I2eyvrQEkbkZfVFGah/4vblcUcmFZE3VjcycVhk2iCzVpDw2iJjiO2wY0rm/yaPP1pVr3WNhl6dRq4dA2JKiH1QJQpVI1Pfs2qLWqufgXfub/cih81ev2ExQUzzl8lbSFAJhqLYJzwZcNtIEwnDSxqsG7Vzj0O9b1rcmmVNTZ92bcdmRdHUj/a3U96FKCV5poCmRXcWUJoq+Rcy+K9fsqje7VExdTCBsSCmfF0IcLYT4XyHEtfbf1uhcZyFXNlcwE/JB2pvC3u9B1Z3bk6ubJxcTZBIItT11UCVShq8XjRoxCW6xtJBAOdUvHrxBcybnpQnhskE0tZncXTSsOc9ru7l6XQjzubl6F11VjeeNpM4mQVREQhmTNp8nijeC3QvfPTd0yf4j+7p2BXT66vOqvR5RfokMC7VBuLyYPFl2DZlejFo83GhKT9sghvXt5lIx2b7ydiS2bUPyg8oBq2NWlcTUhdVeBMcN6+36bSPbNpm2ZNIc101JQcuUINQ4CFWCUN+t/X3jKd2MgwhprqhrL1yeQD7v4GePfMGJ90/Nel0TZl8MxYtJ/WaqBFa4DSL9ngp2c7UepK4lQU9rbepyCcKGEOJB4GzMtBiVwJnALp3cr06FN3mdF3YmUK+Kyd5MBxQVkyebK/ipWNLHbcrki6d0XwKhEhHTkEdBXIfhEAi3nl2dZAk7UM4yAtvPZj+PmmrDfl41DsPv+bxd8i6Y3mR9aiR1hg3CWgRikVDxcRBFShBSmhN//5F9GTWoR0Z5m7Cpz+P1NlHtQzbs75AvDiLp4dpVdaNpg7CN1B4CoaiYBvaMUd+SZHltM7/411eOjauyABVTg7LAqX1pU4zXqp3EJpj2mM0Vd+AiEFZfmuIpdNUYLdwShP1us9kgbJ1/PGlkZHOFzO/rjt0hA3ZMi+HzDSGtYkoZhiJBKCqmuNuGoyK7F5PikehbwirnQ2y3NCfo3yOWcb0zUYgX00FSytOBTVbivv1Jp+jeJuHViXthu7JmGql9JIiIe0c5P6gfUw3mSurSV8WkEohYWHP5ThdipB7Qo8L3PNheRFa+G5nm1uyFRXVztSdghpHaa4PwDFbvO3W975RpJLffmZcLtSdWZUTLNH7n82LKQyC8MDOA4nKXtBEhRa/UJsDcctWGl2H1vhvITNaXjVNU7zNVTOmxIFUCkdDpa+2Nbt9nB9ZVd49R35rk2pfn8vqctUxevBFwq5iyLSYNBUgQfrseRsL+BEL9qTbZzZEgUhnGaF8VU1YjtaJissexx8VcRa60/t5yfgbjdC6mNGFQ35NbgnDfm02aVVVMORNvqh5YhulF1dCWon9VLON6Z6IQAmHLr21CiEHW7xGd1qOtAPVj2p4VKmyRWPW2ANMGYbu82uJ5t1imismLP727yNmq0Bvt60cgmj0EQh3AuQeV9K1T9yzukZCGwJQM7EXKIRAZRmpzEruT73ltLN5+uK+rBCOe0q04iNwShJ+KKZ8NIl8ktbefdtthz0ID8IfI33i6/mzQk67Nk7wihMrN2yg4DkK5z96L4xeH7WLdk35vzYrDxIG79ENX2uzfI0bKkM5in1YxpSUIv+brW5L8Qdm1TuWM03YMc2+Qv7y3mJ1+94bzHI560McGcVf4Ic4Mvetqs1IhEC5jtOYOlLOfUcuiYmpWVEwp29khS2Sz3R+/Yy9sRsGbyVhzbBDpeZLdSJ2bSVLLSeWZbXhT0use54AnPjPjSPr3iDp93hoohEBMstJ13w3MApYDL3RmpzobXhWTOtDDVv4hSA9YlaNWJYiQJogq57JhbX0b5z/xJZCpBvHzYnJLEOZCWVCqDelPIFzGUN3Mo2+7wNoDvsFDIDQMBqVqnHz42XI7+fXJu5Crg70t6d4PwluXLQVU+KiY8hKIfCqmjEls8ANtHvutfCTjG/44ZMWCNte6CISfBJGNQCTsyGel2amKp03ScH+XaFjjN0ePon/3KLoiQaQMMzr/7O8PZ8Lwvm4C0d3kKLc0m9+vtjnuSkGhZZEgVm5uobYpwdF7DXTat2F7QvWsiJDSDf703iJzDFpFsqmYDCk5LTyZWyOPudq0JYimeMpta/AEyuVTMTkSRNKw4nnc6cG9j5krPYy334aUGQkSQ0IogaK2DSJdj8tI7TO2VMy84YfsVF2FbiiEIccan1DaWVyznr+8boaejRnS27e9zkK+Pak14E0pZZ3luTQSGCOl3KaN1N7sourvikgIe832irzqxGtoTdItEkIIkVfFBOnFzbvbXF4JIqK59Ja5REv7mpfoePeENjd7N0Vnm3jYEkQsrBENadwVeYj/V3MOPWWDjwThr1JJ9z97HERr0pQg7Of2cv1pAqFlSHb5bBD5spbGU25pMalLTtamsveKx1xcq/thNrglCJ82M7zW7PpTbgni40UbOeMf6bhTNYAwodgghBAuFROY78kk3nbcSgqQDKww35e9Ve76+rZ0qvB18xjBWt/FxGY4BlpxIW4Vk3ncoyLsImJ2f/u01bCzWJ0ze6rbSG2qbG0vJntND1supPa99jdQP4XKvKUlCCMjmyu4dxzMcKzII0EYPhKE7Uxheo1ZRF95Tw1t2W0QXjVs724RKiMhpPTPq+YdferYOOaTU5lTcRGzbvwh+47o49teZyHfntQG8Bfld6uU0j8kdRuCK0dLym2giilePKPlYvjibw7HpEoQzdZuckBeFROkB32GiimPBFERNjnpolRMIcEB2gK600JPml1blxoSS8UEj05dxlIr+Eq1QcREkp+ETL///vp6lwRTSRvVC54AI3uQkJcI1re4E9sdtu5Rqh7+Pj0qwqxV9hsg3kjV5gUADEqtyfRiykMg8m0odPx9U7jgn+k8/indoLdoIqK3EhNZku81bXBck3t3i/gYqY0MycaWVNLpvs3fasSzeh3SKiawPWcy1RSm04BZpiWh8/Pw6xz/+j4MYAvXyb8zTKynOaGnOeGXL+a38lFfI7X9rmwDstqW/f16WBKE00fr+MTJx/F+7Lc+2VPVqOv0+W4RfxuEZrmQ2u/ITxD3t0Ho6Eamism9o6LhJli5JAjDHMNDwvUMFRud80JYfZTSUauq8/ebdY3Ocab6Mt0ZMzA1vbeEk4spa4/czM6OrAOgd7coPdZP44rQi4hEU7ZbS4pCVEzvCiFO6vSebEV4B5I6CGNWEBnAT/RJ8ObV9DBMb4ewR6S1Red8KiZIcwitCYM+NHCAZi6EEV8jdXoQRsNa0SqmISte4tnorcyruIA5FRc6EzepG/SkiYnL/wIp9wY1qg1iQPM3zvk+qVoXN3ak9hU7T78ZVn4OmHpYb49UA11IE7w0c7Xr+sTV/4DaRYzoFWZ1XboftY/+N+fM/RkTtdncuOxMdlr9qnPtrNDb/HLDDdCSnT/xkyD2FMvpRXoyfbBwg3OcNCS9hEkge6a3W3ejaYOzeIY1767HlgSREQVt1Z/SeTDyZ0Y1mepF9dONEGuRrfXO756J9Vxadzcsn+Kohbxqimgo5BCRxrYUF4TM7d3/O/QhZ4bf56rwc4Cl85cStixjqFzvuzjaVccimenGWx0CEXZxwm1JnTAq12zd88zpMP0xhK5IWi79uvm/Ka67Ym/cEkTaSG27EvekCZlsY/KDl5L4v77OXvD2/DCN1GqTbim30EjqlGFgSIMH237HlNgV7CFMfb+5w51tJHbf37cq6tr4KFfsj/28wpLaXW6u9auhaQO7UMM5obece3yZoVSCQfP+zpWRFxkx+49Zn6eUKIRA/AJzu9BWIcRmIcQWIcQ2LUUYUnKSNoVzQm9bRmrzvMDgTPk6h6x7FIBhxmpAsmeLufm7aW9IvzLb2ynsIwV4YXNNyXgL/4zewZOR24mSpKds4mBtjqtshpHaSO9olWugh1s20Ismhs26x3W+V5u5QKcMyfnhtxhX8ySniXddZRwVk6bTp3Wlc/7C1ddxbvxpp92+wuKa1s/n/a/XM+amd/hy2Wb2FQv53/DzLK84nWQ8zSnf6El/oGJ094b0jmWbl9J/vSm1HKSZeXt22PS5U/bi8H+Y0PY5fPwH37omL9roqFnSkEyKXcu/ozdnlE81bOC6Zz93CEN3mSYiUXWDiKb1zmQNaT7GRF268vQDHPWnyTz9xQqires4NjSNn6/7P6s3MFys46HIn/go9mtGzf+Tc8/E1vc4qPldeOpUK4gxU48di2j0sPKDb2pOUC1MAnNsyFRbVWA+f0U4BK1bINHEQGqRRqZtxv6elZEQ54cmUbUmnX9TJRBJj/1oV7FaqQOTEH3zBrz+K0Ipde+I9H222rDZo2JyAuXijaDrGe/2+ejvOfa1cUzc8DRRoSPi5thra20hQirD+0wlwLruVjHllLylZG8Ws4NcD8Dl4ZcAy4tJuFVMNvYZ3seVNsdbvypBeO1B9mfVZAr+tCc8chQ/CX3MTZF/ErO+oW+QZkstmmFer2xckfV5SolCCER/IAJ0x9wmtL/1f5uFLiV/iT7ITZEnXEbqY7VpXJp4lENWP4yGwTDD3PF0t2aTA4yENEJGK1eHn6E7LVza9jB88yaRZAP9qfdtqx/19KDF4aKOX3UXY7TlRITOAFHHQfX/4cnoHZwTeov3o7/mh9p0l/vceY0P8T4/5wfWoumMecOAt34Hq76E2sUw598c9eZEZldcRLhti6sPIxpNAqfrkkZpBtHtQg0a7skPMOqL69h/9nWu+8/V/+1w531sArFhPrO+Wcqt4UdoW/op/47dwuXhVwAY1LrEudfWh+8tlnCc9jkqazkqtsnckCbZBvem80+NEuaOe5GUuXgLDHpieoHRuBaaN7n6t2pzC2c9Oo1XZ7l3qK2yHPB209wSDED4nl25Yc0ljgTRSyEQA4Ty/po3kjIMdhJr2N34NosEYb67XUQNJ2kmkbvx1fn0aTQz2m4JDwDMxeFH2jSOCZnjqapxqVPP6KS1VXuqlb5aA1JKZFsjVaQX3WhIo7sVKLVZcb3dXVvlem8V0RDUmUQ+RpJuSfd4AIVAhAU3RJ5i3IdnOddsFdOgUBOjjUWO1BBP6XxPS/dZTyXNxd2CpisEIp5OPdLqIhCWrSEV55gt/6JSb4Tbh3JV8x8yVEy7a6sQynipTpjPd/3SM/hP9DpXPA2YI2u8WMRANpM03CqmfEkuT9CmEifGC/pEDtVmU0kbPfUt3DzzQI4wPstYsMdawYJOHV4CoRCUPbUVsPg9x+HDLnuiZuXv2rKMPpjvsTdN9KCFxV+8DUAsrLyUpg2E4+a3DCf815tSo5Ad5XQhxH9jpv2+TQgxFBgIzOj03nUSVJF7j9YZ9P7Lf1HNHUzQ0qqV0WIZ3WkGEWKXxmnAGUTCgtjCV7gk/B960sLxre/DM68yYNB4no2u48jEXajmpgliIS/EbuEtfV8u3ngle17zIgsq3uJrY0f20FYykM30T5l7UNwU+ScAD0fv4fvx7wGmO9tBrR/SUzRwoDaPT43R6b4veQ8+fxBWfAprZ7mer27MuayfOYk9rIVjePNcwCSM9oQ7Pfwh1aKeC5O/MdUdCFbIgfRe+wkAjbKSHiJzN7Fetipm/XwmJh9l3/D7nNn6vqv9EfGFwCAgbYS/IvwSe2nLmRYf5ZQbGdpEXcsOtNSucGV/3Nf6DrGkKcIPEZvoLixV1IJXzL9ffgX9dgbMLSxtREOas2D3Fdn3YgbYWVtLszS9gLrLRsBcyIegEKAl7yOGn8oHsd9ACk4Tb7rq0I20BPFe7CoAXm07CN2Q9GsyM/JuDlWzA3DcJz+mR3gprTLKl8Yo9kxZRE9Pspf+NZsig+iXXMcQuQFDjuCHH53EcbGN7IcdmuYAACAASURBVBp/0nmX3S0JorW5ES921DbSkyYqI32hfpVzvndiDSRaIJp+yzZT1Ju0moTWOqjs7Szolyy/gurIMq7nXFpkjD02DSSlpfdMEW1boDXt+RNKpseLbN7Eq9HrWSp34JHk7wDTthYJayaztPgdTtj4MHsJU60yMTmVSUYtGDpCGi7mxcbA5CoiDKafvpF+GrSseAQx+DKc7WokvBS7iS2yO3H9NE/GhOwUQpeSiWI2X1fszYsNB3NqaDLf1xYwOD4EgHvEPcxaNocLorP5Vg5mmNjItEr3ODAkkIqbu0VFKh2GKkaCF7gKnobzup3EW91PQcrhAOyvWW7GoSj9LTV2X9HIreHH+GFoBvu0/ZWjY4vAFgCbNzrM39YiEIVEUt8PHAb8zDrVAjzUmZ3qbBiKznhi6wdoiUbOC79lUnoLNpfHHifQM1nLqaHJHLH+cYTUrevpjOfRdV+xi7aGncUa+tBAlCR3hR/iusi/nLo0DAZanOnHxt4ADBJb6J3cyEbZk5TUqJVmIrjxqa8Ak3O2VR8jhGmocgyD0001GCLzE7aMOYv1sq/zu1fCFJ0NKekhWpzzPwx9xTmht/go9mv+E72eYWIDkVbTSKcSB4Bhq15FYKQliPUL6JncgB92TqT3gth31vWcqE1lT20FfWhkuFjvXBtsbTm+ec1S1/3dhMkd925ezsWh17gi9CIAcdLBYqyb6xzOXJkmELbjwHmhN/kkdqVv/0ik7Q1VVlvnbbyT0cLsx77WxF0r+0LtN+y/+nH/enBLEDZsFVV1sy1JSTB0ejd9S0hINtODjfSmIl4L816Ef/2USuLM7nM0ALfH/x8D25ZS1baOiNDZRdQAprrRliD2bHZn4Z+sjwFgvLaYqrCEujSBOHXtn+DPY6AtvajYBL9PMv09uHM4fPYAO6z/mOFiHdVtywDYVdRwT/Qhzl17M4OFkhCvdbPLJjR2bTpFW3jR6+ytLeXHoamOiqk1qVORamAv/RtT9w7sJNP93Kf5E7hrZy5v/ovLbmRjBGs4Xktvpzp+8X2M++fuTIqaTpXSsoH0EU3oTRupak7XnV3FJOn/r6MZqa1nftV+zDfMxXsnsZa+yrsZW/ceO2obOSw0m120NQxunu+q5bSHPqPuidPhtsGQaGFi/GP+EP6bYycCOLblVU5veBgjleKG8JMcGrIYOz3BKLHS6nsjozXzvf8y/DK36Wk1JM0bCVkEIlIuEgTwAynleCHETAAp5WYhRDTfTeWMcGvaU8FmyE8NfUwVcaZGvs+Byc+4NPwajaI7PQ7+NSx4hbsjf4O1IOcdBEA/kcnBvR/7LQC/TV7EaeHJrmt7iBV0t1Qec4yRAAwUW+idXM9Xxm48lDqBNbIfb8Wu4c/hB6irHMZPDtkP7X1z8dnJIhDOQN9ocR9rvnK1c3j8bp7svzPrZB+rvKB3aqNzbw9LZTHXGMEYbbkjufQULdwYfjLrOztw7vWcETqXPvbETTazQ9PXvmUPMT5ngphIPd0ZuuJl7lVGyykhU0Ih1otdlzzG3mIksr7St56KVD3XRJ4FYIPszXJtR/aTlr2mrR5a63hubj1PfraMByP38njqaGqi46hvTXJJ+FVXXRFSVNHKO7Gr4etMO0aV0cTrseu5JnkBB2rzmWeM4KbkWbwQu4UdmhY45QSCStqoIMEWejpeTD/S0gv298S33BP5KzvWme+90mgyuXMLm2UPNspeVMY3wQvnOecX9zmYwzc8QR9Zzynr73POPxm9gxf0iRwy7QHCQ8cj2J8LjX+zOjyIIYY5LhZW7cfEtrk8Hr2LubWToX4fCEVBTzAkbhGqmU/BgD1h5CGkDMnOYjX7TfMYO9++lhOB8VEzIV+97MaOIs0IDBZp6Uq0boHWNIMybn2aQPSe8nvn2IibTEk8ZXBB7S3s0ToDlh2bbrOiN2viFezf8DbEt3Ak79FXHJ3xja4Iv5xxDkwVTpgUFcn0O65++b84p3YBd/IorVS4VUwNayBsuveOEOuIbZjNRtmL2b2PpGF1C1tkd0aIdfRJhMiG4eveA44ETGP6TZF/0nuVqV7klYs5KbGIvcOZ8+OAtinwyuj0ylvRG9rq2MEy6/ajgSZZCQJODbnXEOpr0CypM5qotxJYFWIlaD8KqT1pxUNIACFEP/CR/7YhRFvSYvIQ3eRkqkUD3UScL6IHONeu7Xk7DBpDWyidp0esmOKu7MyXSIz+Ke/q+zinjtG+dI5nGTsBptrEliBWhoYTlxEGis30TKxnjezHTLkr6+nLm/p+RITOn/U7OWW4SVDWyT4W5225uxoGNKwGLeLqSktsAEvlYEJCsA5Tgpgld6avXgtr5xBaPYOeopmmysGckLiNlYZpSlpkDGGt7MsPQ18htSg1O57IJYkr+P2Oj/BVv+Od+i8KvU5v0UQ8YupfeybSHNY3hpl95ZnUYcRknBdit3Bb5B8Z7/708IcsHnIKnGtyVieEPoP6mnSBHpnbnS8zBnJS/PfUouh9/3M53Dmc/d85mR9Ev+XY0DSej/2ei4zn+SR2BdUe9dJAsZmdxRoGiDpY9BbZcEfkH3w/tIApxmimy915UT+YQa3pzZuQkr9EHmBmxcX0ogndgKrGb/lr1PEG53/CH7KjlmZCuhlN0JJeWDfLnmyUvQhJt2vt5u5p9VuVbnKI7+r7sEX24JfhVxiwYSp9v7qPC0KT2F1bxdsVP3LKn39KesEd0/KFaYPouxPvhyeaJyPd4O1r4cmT4b3/o9vmBdwWeYTKVpPAnK1f79zfEurFUFHLsuojmGqMdknWg6mlqc8eAOw+6TSoSbsNZ8ORiQ/4W+QeDmmcZBIHgG8msbpyN04MPQAXfsBXoe+xYzz9nk8OZd+08lntWD7S93aduyPyD6oTaVtTtNYk6v8VMqWh/hs+Nfv66I/gnj3g2TOoZgu/DptE7czE70jFTKZqhRzIKaEpHLjuKRqjAzgj8TseHHw7L+gTnfr7137Gr8Iv0IMWTgtN5pSQsi4seJW9ZZo4LBM5MhONPNj187fh59jVspk5alUbFlO41BiEwIBEJpNaahRCIB4AXgSqhRA3A1OAOzu1V52MCoVADDNWk+w1AgBdCibHJvLNgGN5KHUCy8M7gRDUVbo/8CZLFQTALkegn/hXfp68kj8mTwXgiNBM5/IcY2fqZBXjtCV8XzPF0qZoNetkHw7R5hDTm1kj+znlr0udx88S11Ata+FLc4Gdboyim4hzaeg1U+Jp3gh6AnazuKw+I+C0J3h7P1PtFNIE3xqDScgQ04w9qCAOfzuYvs8eR09aSIW7A1Ajq53/cy2pJjlgL2bucydvGvuzLrYT8/od4/RtR20ju4jVbOg7PuOd3pY6g4dSJ3Br6kxOSZheQ/tqizLKAawZeBgMGk1j39GMEqsQ9TWsl7155aDX4Gcml7hZ9HHK35w6i7X0o8myF9gw+uzEgORqHgvf5pw7J/ksQ3DvCwCwA5tN4gAu9ZSKQ+Jp769/64cAJuHrrqfF+UrZzFEhc5F7OPpHYsktdG+pcdWjqtEm62PoZjSb6hgLm+lBreyV0X44GoUf/p4mqhiaMNVd7xrjOSmR5sb16j35jbWoLY/u6pwP9Rjgrqx2EfTekbsrfsHjg66FE9MSCZ/ey4HvnexyrFiQHOwcTxr4c34ceYCP976bVbKagULhzKmjue9e6bo+uj3jOf6eOs71+xr5CEeHpnNZ070ApDA5c12LsVIOgH478044vfiu0wbyS8vhIaWZ3/zZ1KGskX25MnEJt6TO5pzk1RgirQA5NTSZ37ek35ONA7V5vBq9gUO/uBD+cQRs/hZECFZ+ysux/+OEkOkpt1gOdeJHVsoBdBNxNAxCMslUYwyzKvbj5uRZ/D55Bq/qP6DHlq/5Vfgl/hW9lSSKpDHxqow+LNd2hBEHZ5wHMs6rjIUKPVwJC98ATAIGuKTSzkIh6b7/CVyPmWpjM3CalPLZzu5YZyLanCYQPWkiVbUDx8Vv4/vx+zG0KB/udSt3pP7H8auuj5nGqpQwOXYXJ4uVcRWNZ/XDMtpaL/uwRA7hpNCn/E/4QwBkrAc1strxPlkj+zvlJRqfGnuho0GNKYm8pB/EMmMgV0WeY8i6D9Ic99gz4PTn4ZLPYK+Tqa8Y6vTndeMADovf4yz8AALJbqKGRMQkcKukuaispj9zLEnHGLxP2m9EQHOFORg39DDdVatEnKbYoIznXGgM447U/9BMJbPlzrTJSEYZG8nuppTQ3HsUu2uriDStZo3sj+y3MwzYgzv63MzpbVc75e3302i4kxAunnAj/9B/RMRIe/TMC+3JcjEYL3bVVjsSHJsWZ1wHWCEH8bY+gf/oB/CtNL/5IjnMVWbPNpP4v6vvwzixhN8uO5/jl9/hKjNGmDrkST1OY54caUkQaQLRILux0TOGZhi7Eg2F4MDLebDbz53ztbIXFRUV/DD+B2Ye9wbikKudoL5Vsd3SFXQfAGf/B3b8gXXjIug1jJRWwbQeR8KeJ8OubrXNzpbBebExhE2kmZ4NWjVbokMIh0POGLGhCUmrSiAsfHRAWlp8Tj/UdS0s3AqHa3qaKr6lPfd3vKlmanvx0sAr4JBr+Hv3S5yyzTGz/ZVyID+I389rTHRsGnV9TSni2dShLDEGuzy+AL4wducH2nx6CyXG5by34LdLIBRlqGVPqR8yEQPNdA8Gokqsx6IBJoPUljJopBuP6MexkvT4H6Mt53BNcRIZOsE53CRNzUMYA855na8qvw/A3D2u5HPDlMKo7OMrNV+VvJArEpfyWcjUTNTvfaETu7RcWu23ZnqnlRqFKrBCQBJIFHFP2aK27zgeTx3l/NZjvZgvR7CBPmbEo8cfOx6qAmBZP5Or7C/qGN/2EDftZnK7dqDcJjK5wg30ZonhXrC6xSJcmzqfa5Pns2DwT/jEGO26rhNic6gatiwHYIaxG0cl7mKVUc1uq19Ke6j0HmZKEZZ3iu1ZFxICicZqqh1bhI3h2gZSEVOC2IL5v0Hrw1xpEgiG7OMqX1+5Iycl7+DV76U3FWwN94Lz3uH5fZ7modQJznOmIVhvtZvobhKtZcbA9PP1MN9Ha5/dqRb19K6bz2rZjyorrmR25QEsVBZmW8JqNNwSxPKKvZhp7Oo6tzS8E5uFe/GtlT05WvvSMT7b+FfqcHQpWD/6Qp4dYho6f578X36ZvNwpM8PYzXXPLxr/RIuM8dvkRbxmfJ8+qVp6pdwSS0wkeUX/AX/Wfka9rCKM7lKjhTDYKNN9TB5yPacnrnM8vhaF023Wa73oHguzWA4lVb0n2p4nsFQOYZkxkFRUkWS79YORE+HHf02f6z3MTKliAKEwnPE8XDYNxp/tFFn50/f4YeIPGMq0Xk9fKiIhIiHBN4abQALE+5gJBTfL7s65KQ1pQtIoc+9IvDgyCq5axqdDznbtBzG130/gsN+xJJL+pi1h8z01WH5uvSvTjMfcgx5gzYnPcE3qIq5PnYeKhAwxx9jJUdOs6XcAHHEj9N2Jp+c28u2I/wbgfxMX882hfwPSLtn3pU7mNf373D/hHT7bxXR0ULfRXSfSz9okKzg0NDvdcPUox77xgj6RL4zdebziTABe73U667WBLB36Y36XvIAvjN1h1x9Cf/cYviv5X7yqH8irxkFsOv5xDonfQ+ygy5zry8qJQAghrgOeAQZjpvn+lxDid53dsc7E5l5j+H+pM53fqVh6sv7/9r48TI+izv/z7X6vuTKTmUzuO4FACLkI5OAMAcK1gK6ILgoqcgiIiBfILiseC654saKsux64Cl6LoqyCF6D+5BBXhLDchyYSIZA7mZn36Pr9UVXd1dXV/fb7zjsz72Tq8zzzzNtXdVXX8a3vTUAksqdHfGexRciIH8RibMU49Of5zlber04yj/Fz21gH9iCshG3Pu/gzm4xbK+vwwMJ/wk60Q8drWT4IKpTBDrShhAxeZJO46adcbDrDk1eGw85ng3pIG3wsCNj+clbqVEQQwoyL33qL8OHSeXAOOgNzJ3CCuHpuD1wH2MBmod9p9wndjtwkYOZKbB13IK4vvwn7lW4F04YSE2Xvncp1Or9TiKDTyhf8vV18IcyXd+ElNsG30OG27UEf7BaLwy6mcBCrLsFAph2Pe7ND792cmYbtTpgo/p83C0e7j+IUxfKsz2nHh8vvxIKBW/D0kg/hTz0nwYQBtx1FxSajje3FR8tvxXZ04LrS2biv4xTjc895U/G3Hf3+woaffsC/lkEFz7Ng11js3h8DyPkE4m/uVOwl/twOp8v32M+5DuC4+FDuKlxcujwcO8gVC2fXrOBc10wQaXGIehcAp92IZ+a8BRcVLwebuDASh+ol1oOWHA9j/3u2ADoqbRNxaP9NWDVwk3/utUpAFPoQEPJnPM6J7RT+NxU4IMcBWrvhuLlQ6Gvpb7pD6b/dxOeG9N/palU407YJKM7km7anvbAYeCOb6ItiSszF3ctvBo58HwDg6h9swImPH4d3Fd+DH3hHoCT6V2b0e5zNwWWld6OYHw/H4WNSDafyssvn5m5WwL1eWBey5otPcREWOEd6VvEa/DXL++QvLQfiHV1fwUCuGy+wKTireA3nIOYfHyrjpsoZvsXeqctm4r7rzkPb+MnASZ+CVxiPDVIq0AwEAjxB0KGMsX9kjF0N4DAA51R5pqlRYQwlZLDH4Tuwci4gEDyLVPj+B6aegwe9A/B/k88ALnsEn3AvBpAcg+k+bzEAYA8KuMdbCgD4VnkdLiteirZ8IDs1hdoAgG05IYbJT4RcLHegDbnyLm6FkW0DCmGORTq7qfGdduYn4XWljwNvvAWVAp94kkDcUeHiiAfya1CBi1sr65DNt2DRtE7cf9WxOHvlzFA+iNcXP4JTBz6OJybyxZRzWgRTVABpx753zgnYzHr8dwHCkQtAsTMQf73Eenwbf0lwSyxsRbJbEtqpy4ET/wWex0KcyydK/4Cft5yMHQ4/983yOizrvxn/y8I7NAB4OSvEhshgwaSOyCI5o7sFVxy/P4oVDx+e9O/4VWWpf+1PHve/2JkZj1t63ov7xp0KHc+yadg9UMZO1ha5toHNQQUuSsQX0oEWrguSBIIcFy/m+cK82+nyv4u8vqN1Jp5gs/jxqouBqYGTIYiAg8/kv9sni3DffBGefeX/4NM/4z4mf1x4Je7yDuMRibUxuL2SRyEjw9gTDuu/KdR/XksvtmA8isjithnX4JrSudhTCr5fn2KOvFHouR72eHsqlFHCfSNEIEwBE1/cxsWH/YLoqHkxsk4Q+marIiIDgPu9hT6B2ILOaCgMZPBTbyUYAr8ZdWMFiLVAlK/GF9ua5eW+yjr9sfCINw+z+2/FS7vKgCAq2wSHpYfaiAQOXH0pzitfiRMHrseJA2FxZQgrL8BrFz/p6w7R3wQ6CAB/RtgcNgPg+Zh7RwWkDfjmFt655Xyw0MosUip25Dm1H8h3A91zUHH5TtaUDU7i0tJluKp0Hu73FuK33sHYv/8WXF0+Dz/y1viiFIAH1jOh4vLF8C89gRJrJ2tFvrQL2P03bHXG4x/v2IBr7tjgB/cbKPOInyoH1JrL4I+VuSjBRd+Uw3j7XT7ZnmCzMLv/VmzKzvbvl+EOpnS2gCiIllnxGHaiHRvYXAxURLhnP6ZMtP5ychZ7F+ME+hIeYgf61+ROrdweiN5UAiE/yaqBL2BVf6Bc3SM5CFLDTRNeO/JjuDZ7Of6jcirg5lBy+Ld7hY3HNozDl8qn4T3Fi0P1eyi3EofOHo8Xrz8FE8cVIn3uEPmB7J6tTML15TeH6grwMBVlj+Hr49+Dn1fCivvn2FQed0f7LicMfBLfrHDzyB9NvwIA0Nc+S3wXR7wbeKxwCLbmpqCcafFDusjrPsFwHeDE64AL7g2/5O8+D5z6OWDmaj/hjVwg/+1X3ORV9p2rhLe/sPhebFz8HvSVeCBKef4VjMddlUOD8luCHf6DbcfiG5X1oSB2ZWTwh+O/hw+ULsBe8D6TorqftL1eiZLsKOG+w2FM3lK8Cv9cOhcBJykc+1oDApFxnQi3DwCXFt+Nj5XfihfFGLyzsjox1Ib0eo5Ec1XWAjU20o7cZGxbciHOL73PJxCTFO97JkxPt0HoINRQG54he53j4DdsKZ5kM/EkmxlbTwBwXQdb0YFfLvlshPMYCqQhEHsBPE5E/0lE/wHgMQDbiegzRPSZKs82JeRm4uVWvrP0SoE5GScQ/LPIfpQdqserNxGItxU/gI+XzsYetOC2yjrIAV5EwBqrcefV2E6XHTvfFydsaeMT6pkpf+df34l25Ms7gV0v49m+Nnzzgb/gG/f/GV/9LVeKDpQ8FLRBLsvrL1WwfSEXq2UqYWWenmdZhdTHFEX8/YxIwQiEQxLreE/pUlxRvAisa2boOz3s7R8shG7wHf7KJgQcBAU6nb+BL8Yzu1uxGxqBEP2yd9k78cvsMby+DvniFpdE9E/kcId3OABgi7BA+6lzNDoKQZ8YCYT4djv7S9w2XWAHOFdQyDq+H0RR2UNVGPmKxAe9A7EhG4jXuNKbv+uBcScB/7yd63QQLFBEhJ90nIlPzf8msq7jc5xyp98u6m0KFc8vtAEr3g44jh//R/UkPuiau5T4UuS/927vULyw6N3oK1bQknVDQSh3K2JSNxO0VXKtei6OreOX4HuVY3wC+TfWjYUDX8W328/xF3U5tjyPhaK5EoDfegfjlsp6vCx0NT4HESIQYX3hqQMfx5uLV+NObzUGkMNGNgmnVz6J68tvTgwFL8cxJ5ZBeY7CoagipkIui61HXINn2HQ8xjgXfF9lcVCgEDHpHITjh9owVKJ6vE9eFhHKyODF3rVcBznESOMo9z/iT+KBuBtHC+TC8mz3MTh8y3exuzWg2kRAZN0XHeqnIHWDaJQquttyuHfPMtyLZUiCysqqYqqFUzuRyzjYW6zgySmnA2eei9ceHQDAbap3sDZuO7/9z3iFBbtvlQ3Wk57IxaWvVMHu6Ufj8uLF+LuFZwNPBLbtcakQgEDcUyx7cIhAThCpMmnSbcU43O4dhcuJ/O+0oP/rqMDBndlgIZR4ifX4Ogh9V/ir9x2N+59/DT++4+FQhSUnKOP2A/x7eo7Jj5OwX/83UIaDF647Fc/fcC+WFoLhrxsmEAWhsHf2lTEQCgbC723JuiiLoHDfrazFKe5D8BgPWSI3BK+hEx/u/CR+dPiL+NkfnwMUy99SxQOIAt1RJshk6IHQzzKCQAgdhFjI18zrwa+f3oK/bA284uMgxRpqbKA9xYqfDc0lQkchi1d3F/069Zc8rqRWCJBKIFViKvNX62Hs5aIr9XIMwF5WwIAHSAmrHPtlEYbeJGL6l/LZeJLN9EW2XW0BUc86TshPbAObG2HZnsZseKgkhvuWOS+ICG35DLaL8PSuQiBUEZNKPPtQwJr+G/GqYqDCHBcErr9CWSEQMtz3IHI5yPYOpoya3lftBsbYV5L+hqOSjYb8uK90H4IjBj6HTTMCGTJRdKD6HIQ4louJujN+6MPrcMclh/vH+o5UhcrKqvoC9Zm2Qg7onBY6J3eu2LExZAUjFzKVQMgm+BxE0YPHCD/0jkCpJTCr5fcmcBCSQFQ8Xxwho4ymSVriOMH3HEAOZWR8c0KHyHcw3EEdfjv0xXpub7u/ePIKhzkI1yF/sXGIcM+40/H9ylH4ajmseC4hw5XpRPxbKWXqn4AQfLud/SXsQdjEFuCcYEWE2rjPW4LZ/bfiXm9JxPLJYwxY9hY80Htm6LyUfcvdqdw4yCxmMvufJPLyG5x/5FycvXImLjxqXqROOhziYaX1cNUyY5nrEDoVyyBOICpoyTnIKquvykGo80PGoeorVfB8a7CLlm2TJq8PC2V3f8nznw9lmlM5CKUv9qKAb1aOB8CzIKp11TkIE+TlpGB9kpg5BHzl3BX+/HQVi8bXlEjBLTk39A1ewoSQhGDP67+F71eOwvaMMGKhYGwypqVCrXGhl2UlJUBqJKpyEER0IoCPAZgl7icAjDEl2M8og+ygQsbFJjYR/eXgY1998kI880rYQ5FpHISEyo5OHFcIJcZRE7LrCImYQgQikHW2aeIWgOsgJFQCUfAJhOeb6jnEE53ISdhXqvjt1mlXnB4ECBbrUtnzU6yWKh7+/ku/CwXJi33eocjiKxdClwiXlC7DgnYPbciGktnryLqE7dKschK3w5eTSxULZhyC53bg/aWLYuvkeQwDZS/Eyck+lqlYHaJAmV72IPdSniILKGRdVFg43PcFpSsM7+P/9fDdsq/9PNKScIqdZrnCs8y1iXr4C5dD+MTrDo5tnwop1tCD1ckdsetQyDKoVGE8ZlImnGtd5SAyJg6iWMEX534eP/gjt7CTBOl33iLM7r819F5HWA3JbHYv7+xHxWOxG5Wvv/1QvO1rv0dL1vU3EQAiKUdN8MPkJyyosl9cIhwyqxu9HXls2tYHxyHsP7kDHfkMdikh+FuybuJ7ByYuxvtLF6G3kAX6B/zx7xCvh7oslD2GnJMk5A1DvrcpUo4KfAHAhQCmYV8J9y0jLYoFQk6W285fhYOnd0Y631MWD37MT+h5ILJKaF5TpjgJlYNQiQwR+bvJ9nywWEj4HAS4ZYZeXn+5oiSr59ekQlwlEGr7zl45E+84Yk5sXR2Ng8i4hL3FSiri4LdLO5Y7YSKum9k40O7rH9R3qsi5Dp5kM/HnU24D1nPP6YpBxOQ6TrxsXqBY8VAse6F+kNNNcoUOkZ8JTeJtxQ/idLrRP24RHMTeUrB4lJFBWdt3ye+uL9Kyr3XzZK434It11nUwtasF4wqZxDEVB4cI/SUPm3eEwzYMKARivCLXL5Y9RUkd9IPKQanjR4am7ytVUIGDivAqjoue2les+PNo0jiuV3h5Zz8Yi+e6V8/rARE3uFD7NuOYldQqKoIz8TyGzTv6jDt2yU3pG0CHgOUzRL0icQAAIABJREFUx+OP1xyPL569HKcczC0LW3LJBEISfl+nhEDnoouYTJvIX1xxVORcUKeweHWokUYHsQnAIyL96D4BSXzVnTcQViaF7kcgo+THHLqSWlU4J5nAFkK7IIWDoIDrCDiI4LkdisnkK4oDnJQVq2ITXleGVkFo+pQUqWr7PvG6g3Hf02b3fl4n/r9U8ZARIqY/bUxvXleuRHeGgbUOP7+zr4Te9sB23jT3fBPPKWuATB6PbNzup0tVrU1cJ2qNoqNU4YpldbGRYyLnOiiWPa6DyIUJxL3eUrR7GUB42hayDnb0sUhKVR2y7GI5PKl9DkJbUBwiPPA8j920dEYXzl45C6ccPKXqYmgCEfCHF7fh1H8LxxCTY96hsIhpb7EMxvgYzRhETLdlX4+jlHpsF0lz+ooVLde7eQHrK1X8fp/YwYnOKzsHQiImHfmMi0LGRWvODYkasxmnqoiJiQx2u/pLWH3dr3DglHGRe6SISRalG6NkXAcnHzzFTzFayCQTCJnwSx+HJJwWo2HIw+NszoSoX5SEfG+SyKyRSEMgPgjgx0R0LwA/pgFj7MbYJ5ockt3MZ8IchFyr9c5fMasbX/t/L+KgqXxwyf7NakRAPc4kRFkshHZBwTMhHYRBxKRyEKp3trRzHyh7/k5cPiU5iH5hAgtE5e1JC6pq5ucQJxDPbYlJz2mAydJLFZUAfLes+oaYJr0sRy6qZ9wUBHNznOA7ZlJwEH0lvpiF9BqyLPFqxgIZuQrV3DGX4eI2VfxgQhwHUdJ1EJkoAX9k43aeBnZcVAeSBibFLxAolTOaiGmn4AhasmERkwcHc/q/ibnt7VirjklBHAfKnh8CA4i3cOsrVfx+n6hwEHF+EBKFrCMIhMJ9O9VFTBWPc2Ey+9sTm6M5QsqxHET4WI6xfDaZMO32CURYHyj1QeFERsJUPPTe+PbIa02jgwBwLXiYjS6M8iiuEm8+dCbWHzTZHyxSjhrYZwtOQfTBKYun4NDZ6/xJKjkKffFTd8o68VCRVzgIdYCrYy7wCTDrIP6qSPnKFYbv/P4veGzTDhyzYGKoLdKGvr9Y8dNV6pMqaUGVu9aXdw6guy1Xk+zz5rcsx+TOQoQgZdxAlCIhLXXUd6qQ3/q7D2/EG26+P3RNtTYxOX7pkGKRsIgpKn7TLcIAhHI/ZFwH2/aWjH4gKvYWK3jh1T1RHYQkECVpxWQm4INB3D6lP0bEtEt+m6wTGd8MDhwnnMVN/R47+gJFrm7hls843By47Pn9ns+46GrN4tM/56Zdcv6Yml/IuhECkXGdRKIC8M2H61DEykqFTKuqfyt9nrhiTudi/C8k9gxEIxoAgV4wzEFIX6LgXJLRCBH5IrPhQBoCMZExdkj120YPOluz6GzN4vktPLeBLmKSi7LaBeoOTvalbuaqIlnEZLZcUomBzwkoxWxDB+5uPx3HvPFy4ItBwMFSxcOVtz8WKlsWG1ZSQ1zTCESCbFvWaeO2vThk5viILDsOXa1ZnLhoivF9EmGCGha16cgJ/c53H94UueYQhUyPTZyBCrnDMxESf3MA5hPXOGQcwra9eh7sKP66vQ9rb7gXR+4Xth6LiJgUAwOJ7120umr5SYj79v1CjEZEIU5JEo6s4xjHt5uwa9+miNp0EVNLzvXbqfb7duWZpJ1zIeuiLZ8Jba4yKZTUAB9PfaX4vW0cB6GPQ19ykDF/G4ndAyK/u0bwufFBeHGXv4O5WaUxCAjNcCCN1uuXRHTskNdkBCAXJbmD0zmIOAQipvjPl00QMakLmCqKUt/bbtztEy589Sx88Hfh+qkmeIGZK7+nJRfoWSQ7q68ZhWx1DmL73hKmdrXEhgbRoU6guA2R2jR1cpo+Xc6NX/T5ouX49U3PQQRl6pZqjCFkMRP33jSmvhI7lST3haxj0EGEDQx62nI4dPbgjAVjCUSxoohMgnZKhzfVw1qFKZilxHaFWOrckvot1X6fM6FNOU/+O3RM6SxgameLJmJyjAuqzr07DqG/mMBBVKKESz6nQvaXngtbxy5tfEkltUnEFHiSRznYOEgrt+FAmtl+PoBfENFuItpKRNuIaGvVp0YB5ARQ2W3ALOJQIdnBJAKRxEGogzwsYkrWQUg8oimJX9kZ7OoL2fCuRb6r7Hl+vfUJnrT4qgv91K4WZFMqSqux/kC47SECYdJBZOLLc0lxlHOoqpJ6V4wSUT4voRJOU7NNHF8SdmumkkXdiklT3qdZLKohroj+cqAsVjlIKW7NuGQcww7Fi6227S3530zXQYQJRJhDyrrBAqrivCPm4AcX8xhQXz5nBT5y2kGaiImiizpF9X+uQyFLMx1FxQ9CL8t0Xz6TLNrarY2vQAfBNxTq7t/XQfiWkuk4oqZxlAM3a80C6MQ+YuYqIcUWt9z/ZwBREVMcZNckEYFEJbXGJkuEldRhBZeKNk308fLOIB9CQVN0yt1hsewFbGwNOgg3RCAKiUQx7rm4yaSeV4s1+0EkczmBmWt6DsJ0n/w2DMKzVkZSNRETpe9CUUbj3qsQiELW9c0rpYhTDbUh2zJYxHIQirJ40bTAsmevwkGoY1ju9JNETBUvEMuVtAWsEEMgJrTnMaOb69bkt5dXT1w0Gctmcmu99nwGLZoVU5wITD/vOhQJBaJCipjkvPfNUrVySuUgGGaSiMm3YtI4UGm+zDQdhHqcpss551r9vkYgjSd1BcCZAD4kfk8BsDT5qdEBfdHxPR6rfBXP5yDiezNRSR3DQaiESU4E02RsL2gEYpfKQYQJi9wdlpWdi15k0o5bnczTuloSiaIKivkduke5UI2gxOlJAlPEgIOo5i+g7/CAYNIGBgr8eJwwATXpNdQ6pyEQUvQASA5CxIoqV5DPOD5hkMU2gkDE7UhVa6Lp41vxwnUno5B1fG6amzQHz8rfRMlyf8kpRDiIXLwRghTHRszLDZtkqafJOFHuQZbhamPUFb4gcSjHiZi0Y8lBZF1KlDLEcah+qI0QB+GFQqak4bw5oWkSDoKIvgBgLYC3ilN7Adw8lJUaLuhmjKk5iDQ6iIRr6m5KfZfptaYBo4szXlE5CE3R6YuYKp7iSU1425rZuGQtD9WQloOY2FFI7awVGr4xn9MJtd3MSUnE1dH1d9uBDkLfuenYbdjhyfrqBgp6oDwAePvhs3Hnu48I7bBVS6A4qGag+ayrWDGFnfaGRcRU8iLizazrKOJWB+MKWbxu2TT84OI1fvsdis4PdR7J8RdRUsfoIIBAfJimuXL8qfPrhetOxgkLJ4l6R3Uk1a2YzBunCAch+itXxQhij2YEERB+HmpDpZ3/9MPHcfSn7vWPZd+vnNMd0s+ocGrUfQ0GaWb7GsbYhQD6AYAxthVA1dlARAUieoiI/kREj4t81iCiOUT0IBE9Q0TfIeJ+90SUF8fPiuuz625VSsyf2IFzV8/yj+XAkrtRFkOlZd8kiZFkGScsnITJmg17rBWTYYaYCERbXhcxBRyEbkIqB2mpErCyDhE+ctpB+MD6AwCk5yDaC5nUHIS6w4l7Io57MisezXWUXRDSQdTFQcjyxMvFcShZj8DsnjYsmhZ43Odcx2gSq9ZLR4umpFaJlWzTkIuYDNZsvn+E2CV/9qylWDZzvP/9XQMH0dMeLAe+iEnjIOJETEDQt2nk7z4HoUUgkMem+jlONNqsiiAWUzIHMVAOOIgkmMyoeXlcDKeuK/cLh8igLfz/dy5cjXvef4yxfLfJrJhKRORATBki6kE6f4gBAMcyxpaAi6ROJKJVAD4J4LOMsf0AbANwnrj/PADbGGPzAXxW3DfkWD0vMD2UE7M6m8c7J5egOJXE4x9WzsRxC8N5fVWlsDrQHSLc/JbluOqkA5Rz0bLb8+FQzKrNuYzro+5aXIeH6JZzNuIAJCaomoxFQp1srUqOgDjISZFmgxMrYqqLgwg4Cd3+XIeMZGo0c43ZHZvEgrIPxrVkY3e/cYSjJeeKKKueL2KSkH2XJOdOiyQ/CH0hzbiBrF5/txqCRF/IpUc0oIqYdB2E2r5wXXQR06JpPIxMd1tUbCdFffo4VDnIiA6CqnAQ0sy1ih+EJOhVdVzCD8IX94rzJhGTjlQiJodiN6+NRmxLiUhuU28C8N8AegUX8FukWLwZx25xmBV/DMCxAL4vzt8C4Azx+3RxDHF9HaXZUgwSpomf1sw1iYMI7OmjslTVIifMQQAnLpqCC48OonSaBkxLNoMKY76ISEWfb7IL/3/WJZQqwcA0Vfumf1geikar1kkin4k6T6k4a8UMXLaO59gIK97M3zPOcsnsSR1ThrZYqzqIG85cgiuO3z/yTJKjnKqkBgKDgHAMoPA46WrNxrYxjjuTC2mpIgIHGkRMaRaLaoibQqUKi4xzLmIK+wRJ5PxdfrQslUOWAQ5LXjorJiAqYvrwyQfi9ovXYP7EDuiQ30knAmqf6DqIalaJsWau2mNnLOVZCJfPDKe01aH7QQTlBSKmajq1JKgheYYaSaTwIQBgjH0DwD8CuAF8x38mY+zbaQonIpeIHgHwCoCfA3gOwHbGmNTWbQIPAgjxf6N4ZxnADkBkixlCqBPfTTkx01gxySIYY3qI+tAiqxIZ03tNA8ZjDIzxcvTL/ZpPh+MQsg4PCaGKmHScsniKb02iQtcTxC3UuYyDT75hsS+LV8dv3OdUCUFVK6YYYqybJqt+EN1tWSNXJP1GzIpn/l9+q1Y/1HY8B9HZko20Ud4TRyAKinUZ10FEZfRpxXlJSBrLJofJQEkdrrf8prJdH1i/ABOEaKm3I4ij1apxEL4YLkQAw/XIaBxELuPELsLye0Y5iGDuRsxcq8xn3VHON0vVKnrcwkl48fpTjPNERVKoDclBxPkejSYrJr+qjLHHGWOfZ4x9jjG2IW3hjLEKY2wpgOnguawPNN2mv89wLagU0QVE9DARPbxlS3yQubQIDVxlkCVBLh5JClvy743qMkJew1Wsd0xVUcMT64vp/IntobIc4gsNT2wT/544mHaZJki7bLmohXUQQRnHHhCI2+I4CKN1imMmTq7STiDsSe06UXt1h4DfPPMqALMOIqKkNsRj8uXdYiHiBCL8HhlvK05hLgnEQKXCRUzZ6Eah2sKWBkk0RidAGTcQxUT7PTw3Llk7HytmcSe+cYpVnRTJybhT8rm4MR8qO8XqSMQ3AHrdff2hQ1WVzTpkm/X5nPb73335UX4YGyDKofoiJqE7YIzFtjWN0MRxhs+KKcm7p5eIosHtBRhjqdONMsa2i2B/qwB0EVFGcAnTAbwkbtsEYAaATUK81Qkg4pDHGPsygC8DwIoVKwb9lUIJe1IOCF9JncJSSbKVKsJB/cziJgnTYu6nixShBkoVhiPmT8CHTz4QB04Js+Vcgeeg7KlWTAmN06B/EznR23Iu9qjB2byw6a/qyCOLuPX8lVij6HxI+XzqhFHf2aEsPjxZUViWrE801yF/R9vTlsNL28PpVd+4Yga+/fuNAHQRk7m8FiVUSfCOsKK0syUbUcrms/z7VBMxFcs8sqwpedFQKqkBc9+qQfz0a2rdgCCKsGo00eLn0Ag2UTJJkPQ81xfBQL+Rrk15Q6gL1yfaUQ6i2oZIWh3p0XvTfn+HwjvZF1/jZquqabCsB2M80J5LfJxu2TWAXCYwWEjzyvZ8NjKuhwpJHIQLoB1AR8xfIoiol4i6xO8WAMeB5868B8AbxG3nArhD/P6ROIa4/is2DJqY0M4t5YCQ1UpSIn78jEW48Oi5OGr/XgOBiOEgDOWZBqnKQWSUxWrh1HHBYFQU7jyEtaqDSL/w6PfKNqv5nMPX+YtNPacvSHF6B/l5Tlg4CY99ZL1/3sS9mEwaF0zuwG8/tBaLpnVGJtwhswLRhSnUhmyfPFbzaejvlPXvbInqIPJVOQh+XRIIEweRpONKizTZAiWyrhNwUroOQvPy5vfz3635jP+dfSW1FzYJdZ3g20bMXN1o2UnIZ6LGEn7ZThAlVqLaQi9FQnpolbT1IQrWhKP2D3yI3RhCJYnkHZccjv8677DQJjXNO09YOAkPvbgVm3cMPZFIGoGbGWMfZYxda/pLUfYUAPcQ0aMAfg/g54yxOwF8CMAVRPQsuI5Bpi39CoAecf4KAFfW3aoaYEr5GegPzM/I00nWDD3teVx10oFwHYKuhYjjGkzjWB0vUzq5MlDaz7sKOx3r9CdFTJ4XmxkvCXGTS3fWk8iaREya+bBfNsV8B60fJJKC60kxlvy208e3hs5LTBsfZEZTy5sqvq3kPmSfyd2x6mhlsmK64Ki5ofdIDjKVkroU5jRcjcgPBklrY5wiGoj2lbymPiPr3JZz/W8pd+H3PrUldA/XDYQJq/6uWjiIOB2ES4TPnbUUHzxxQfRazAukA2OcX1Q1EJE/wz962kH+edmuQMTE/5cqPPfF1K4WHLlfb6qoAypet2waGAN+9MhLVe8dLFLpIOoBY+xRxtgyxthixtgixthHxfnnGWOHMcbmM8bOZIwNiPP94ni+uP78YN6fFiYldbU+ShPNVcX71y/AaUuC/A0Ut3M2KamVcz9771GY1tUSiJgc8sVckQBlyi4340gdRO0iJn3ASslRXOwhuesNKallW7QVTy1a/e0rC7UhaNIHyCJjxTLa4fSuQMGo9v27jpmHL5693I9AK7FqLpezr54b2EvoC05nSxaLpnXif//peP8en4OIU1Ir6UyLZS/kfBX4dgyeQtSipM7EiD4BsxhInmvNZXwjAl1MY/LAjo0mnJqDiNdBOA6hpz2Pdxw+J7gmFeUxIuE9RZkAKhoaIw1UMXIu4+Dvl08HEGwCdKV3uRJ2UlS/dZounz2hDd88byXOXTM7XQUHgaTqrBvytzcBwkrqdM/4IqaUXsUTOwq48c3LjNec0OCIjkj1XCHrwnECh52ME0y6aG6K4H9W5JH2EqyY4qBbocgyTMl0gBgltVy804qYYgj1hPaw6KBamaZjVfwQmqQia5ivpBbVXzZzPP7vo+tDynX5qWVbu0Q4DrX78j4HESNiEueLlUrEzJWUxW6wSBrT+iIbFn2arZhMIdrb8q6vj9DFNCphyRj0GOo9aSXKuYwTsWrzdRAUnQ/yXBzHL5XKkrj5O/6adBDSN8rBp96wGA9ctc5o5gpwfV04enFtHAQAHLHfhFgfm0YidvgIj+l9HuoErllJbRhA0xURRq0wDQ59x+YSBQothxTrjTgRE/kEIuItnAKyfGmVI7mQuFDYwWQPzvkiO03UplYjjYjJRCD0tuiLjN7SaqFCAjPX4FxrLqM59YXFLTJlp7p4BlZMMSImsRgNlD2UKl5oQVMtsgaLJB1EnEez6d2qJ7V+rjUX5MvWNw6qeWxcKBtJqNRsfUnIa9nu1PqaxElyasQRiHLMmE67HhDIXxNyGZ5MaHJnIXQHEPQr10FE687vGXyfNxJpEgbt0zDZt0uioSu7JC49dj4+dfdTRvHB3Zcf5duS1wrTgIwkMXHI10GEOYjwffKISOog4oP1JUFOLrkjlmVUCy1hMnPVN4hxCnrZFF3ENKHD4OldZULpO+hqxDFuQTVxO74fRGs8B1HIRBfMYtkLWTGVKh5ybnSRaMRiUYsOImRdF9FBSK4meo5zEGIjEcNBEJEfKj4SrE8JKJkGFx8zL9YkdUpnNDVrNRETwPtF/x7pdRDwFZPqO/TWyP7UnRTDMbFSvXLYMOYJhNqhcnGYM6ENN5y5BOsOmGh85pK183HJ2vnGa235TCRWUlqYxAEmAlFSYsfIiRynpAbgO8r5SUnqEDFJqxu5Q4+TrUsxgknEpE+YWF1MDAfR02YQMflKajN0IlMNcd/GlNBI9YPQ78nHcBA9bTls3tEfCmpXqjCNgwgToMEg0cw1ZqFOumYUMeUy/m+dk1VzPbiuuV/lPXF5rHWsP2hy9KQodG5ve+SSHrjSBBNHnJZAOw7hM2ctwY2/fCZMIFioaoEOwvNCZVsOookRt6N8wyHTh7km5sERCTymiJjUlIv6jk8W5Xn8mpoPopYIJnKBlVyVFDHFmW8GHIRaBodJxuwQv1dtpp+bWKunKaR2tQllunzb+avw59f2GO+X65te15A4TBR69P69uGTtPMwTi5L6rkIMByHrKxfUYtlDseKFMvX5Opsh9qSO83EBEjypVQKRCcRKUzoLeH7LHuibdNXpT/eY1t9VrKTjIEzYLPwCTBFQTd7cOkwEohY/iFMXT8Wpi6dqV3h7SLkPiIqYwjqIVK8cNox5AtFMMA1IfX5nXMLu/iCchq+Ai+EgGBgyroM9xYrvvFbLICz66TDD1klxOghjeAi/LqZLBGiepXFcgcn3Qv9mSVyKxOp5PVg9zxzFhWLqqpYj29jbkfcj4gLhhc+kg3BIydMhru8tlg06iGBRHSxq4SByBnGrhMmKac28Hrx+2TR0teZw45uW4X8e24z9JumOmqIejmrFFK5HEHG4/vgRLwqCbyQQVZTUgNnoIqUNSiyXGuEgfBGTF+rbZuYgGmBpbdEomJXUmohJ5SAcJ5aDCHbCXFZcKisiphoohJ4OUxKZuFgyJme2A8SiMc7gO2FKgxpnxWQyrQ0U2mJh11b2WndkuhWTqZy4SayeloRBfrfD5nTjiY+d6D8rxWUv7+z3+0h/V2NETPHX9HEQSuepEwiDo9zi6V34zFlL4QrT0nNWz458G7l4EiHWD6JWEZMJMnf3AZPDBKq7LeePEXUTtUAjZKruJI6DjUN6c1j+v1wJWzFVi8c2krAEoolgGmjR2PakOMpFRRZBWVLUw5BxZKgNfq0WEZPckb3jiDkAAtFSvCd1tOxrTz8It56/0hid0xTiIi4m1vyJpt1hcv1r1UGkiTwbR2DDOohwWOp8xkE+42JWD/fD6GrNoi3n4q/b+0P3qeU0xsy1MRyEzLFRVcmvHyu75zg/CLlA6kmGasEVx++P3199HHoUS7dff2AtfnnF0T7RV7m5m85ejkvWzsN4IbbU/TdMbYlD3Hw6ZsFErDtgIq4+eSEAVQcRFjGZLK6aBVbE1EQwx2LS7lE4CNdx/AU24gch/nssCNZXj4ippz2PF68/xT++8qQD0Nuew6mLp+CTdz0Zud/EQRSybigGkwnGQIXa8fyJHfjV+47GsZ++L7inmhVTjWusz3npJrlKs9IQkXUHTow4RAHAF968HPc//yqmdrWgtyOPvwrZedZgLNEYM9f4a7EOa4Z3p836tjcmMY+bQCAkBzEYEVPGdUJRZQFgpiDGUpejtq+nLYcPrD8AP/zjS9i2txTr15MGcd+kJefiK287VLlPEojwuKjVk3o40WT0amwjLseuCt3MNS4uFCkcRNZ1UPLqEzHp6GzJ4ooTFiRYMdVXdlp5r8lKRUVUd1BbPXzdjVZQtZSo/Nng9+q5Pbj29EX+Ofl8Z2vW99ae2FHwg66pSmr5TEM4CO0DvPe4/bF8ZheA6JhJp4NIrpNuSEAU/Ndzbutl60mGGgWTDiKIyMv/D8bpLLW1U6yIKfg9DClwaoIlEE0OR5tUrhN2lJOLvr5z//Qbl+CMpVNx8LROZF3Cxq19uO6nT4bKHAziBnKt4SFM8aF8C6IU1ZT3xjWp1gkXq19Qfsft7NV3qRE8+f/o/b0defx1GycQJj+IodBBvOe4/XzxYJKISf9uuZQipqldLfj91ccF5SD4DnGEb8VsHkDxeJFXutGQTVEdLX3HP1GXOKOLWsqvfl8gYgpZxTWxFZMlEMOIAyZ3+LF90sLRdj+uQyFPbvlbd5Sb19uOz71pGbKuEwkJ0ohNyvjWLGZ0t+D9J4QztlXL1xsHdZIECUKql1Vtz1lrbXxPau18XGiEatAJhYrejrwfJdbkST1U4b59vw2dQCSwcYGSuvo7ezvyOHx+2EqMB5bkD+tVmj+xAy9cdzKOGyIC8cKr3MJpmZKESLeoMhGItPxM2k2I5GTKFc9otcfr01wUwuoghhF3XX5Uzc/4nsyZIL+Ef43iOQgVWW1WN2IQZlwHv/ngsXjx1T244WdPh87Xg9Bi6HMVtZcz2Ajx8dZQyoSu4ftJehnHQUiYdBCNMHM1LV7yvTotTzIDzaUUMUnc8vbDUGEM77zlYfGcIjoz6ZuGcGF8dNMOAOFQ73poDlVJXWtN0o5T+a5iOewoF9JHNBmBsBxEk4M0DkIVO2Rc8hfTpIVZv9bIQRgXE6dWqAuEV0VspEIu5F0tPAxHh2ZKK9f5w2Z344GrqsefDCZuurhRVcvTzHBVyJSdQJjzaqgVUwJhUkOYA8kEotacDRmXW22pJqONJHy1YI3weZndE0Ty1Tk7VQdx/d8vxvKZXZgxPjm1qETabyLjM720oz/UL3LOtOczmNoVDRUykrAcRJOjUgmnN9UjPwYcRPwgjYv02gjoZSdxMklQF41qIqbffHAtbvjZU7hDiYd/0TFz0dmSwRsOmRG61ycgrVktgFr1eqhIo6ROes70SGsunC1Pwldsp35LPEzt6RWy+K0iN7dEUigKU8KgNJB3qzqI4d4k/+e5K7B7oGwk0tv28m8wSYm7dticbtx+8eGpy0/bnrm9gZl2eDzxb3vDmUtwwhCJ2eqF5SCaHEWRYlPacOsemIEOImn3Fx7BjWTn6w1wFi0n+K17oOqY0d2KVSI/gyQm+YyLtx0+x/D+9NyIel+So1xNHESCWEWVe4cIRAMphIkLkRzE1r1hApGog6gxqY8O1WdnuOXsrbkMJnbwzcG5q2eFrr28cwBAkMu9HqRtT2973s9dbfKkTspVPVKwHASAr7390GHL8SrxiyuOTiUvn9ndhtVze/D+9TxDlhqfR81WlyTaaUTimTjocfnrRciKyV/U49tUa2j2tA5zcvGPKKnrVCTGKWaBsNzbROAbY20WPecTCJ2DiPGOB9JbMcW9n4iQZNE1XLj29EW49vRFkfPzqphPJ6EWK6a5vW3406YdIb8aOafTRrMdTlgCAWDtAnPU1qExc1kTAAAR9ElEQVRE2h1LLuPgtgtW+cd61FOR+jdkR6+jXt+ENDCV3Z7PRFJwVoO6K/eqcBCh+6sQ2WrciI54JzjDu1OVJ95vIFCq3DuXUQik1MGkfkvS+4NSZJa1iTEEIufGm3o2RMQkLYeabJcMmMOEp0Ut32RubzsnEAYOwhukgcVQwBKIUQbdA1MuJkk7+bSJWOqBiUBsuHZ9zeWEJlmKBVK+t9qUYjWKmAK6oyUeqtOKiZI4iBgRUz25w+Mg2/OOw+fgmr/jIR/Gt3LleJKjnA5TsL5a66E7DTYTBlOnWp6c0c0V3yoxCMxfLYGwGCR087gg1Eb8MO0v15fAKA0aJmKqceVJu3iyGkVMTpyISf3uNXBkSXL31hgRUxoOKi3UYHl+nRzCJ163CMtmjA/d20grJv/90nLJIYWbqKmIIcWd7z5i0GXU8k2md/GMk1L3AQSbvooVMVkMFuquz1WsmJLMXPtj4uM0Ao0SFxitmBKKDhR7yeWmKUtFGk/qWjiIQEkdvRang0ijg0kLWZb+/rNXzorcWy3jGlCHDkL+V3QQzWTrv2ha56DLqKU500RK4s2KzlNyw5UmFDFZK6ZRBt0DM86TWkVfnSlQhxPq2hQEFYxvU9qFKgjFkVJJncJRrhamKUlcFNJBmDiI9K+JRS0RfNM5ytX2flIIZJJX+WhGLYRc5qzfo2zaJAfRjEpqSyBGGdSFNKSDSNj9xUXYbCaok+y0pdOwZHonzj8yXtHtcxApAyKkncKBmauugwh+17ID9hIIVEgHYVBSN2IhrSGsVVU/iPZ8Bl0t5jDv8Qi4BjlE9zH6UBOmdLZEzqkhOJoNVsQ0yqDbT7MUHMTCqeNw56Obh7pqg4Laru62HO64NFk27KQVMdVqxZRGB1HDNjrp/eqO3aykTv2a+PcjPYVI4iBch3DX5UdGQmpXQ2DmOnJ+EM0E0zeWjnJWB2ExaLiKfMNNiOaq4sKj5qG/5OHGXz4z5PWrF7U62KUN6eHL89PWw2chwudVsVItIgWPmXUAOsJK6tosr5JQi5I+SQcBANNThp5Qob41CCFSczH7FD571hJM6gjMamUWPGnh1EywBGKUQRcx+ZFdEya36xAOboAybihRq/LTrZmDSGnFFHNbvbteP2NeledzISU1RyPNQdN83iQOol6EmuDrI/YNDuKK4/eva9P1umXTQ8dnrpiO/Sa1h6LNNgssgRhl0JXUgQ4iedINpbNcI1CrZUva+2uRwQNKNFftfL3inrTcgNp/jeQgpMI/TVlDQSAkGNt3CIPEZev2w2Xr9ht0OUTUlMQBsErqUYdMhEDw39X8ERrlrzBUqHUBTu8oJ5Cy/IAziXeUqwVpORhzuPNGmLmK96f4AI1IUKRDvpchCC/ejB7DFmZYDqIJcOv5K7Grv5zq3kioDd8PYnRzEEPnKCd1ELWJmJKU1LWApdRBGMOd1/VG/f1I9X69Do2CGvxQfkOv+Yx1LGJgCUQTYM28CanvDYmYiFDIuthTrFRdwOrN9DZcqF1JzTmiagEP67Vi0lHv1/Pq4AbqeSa+rAa6ZdeBQOfPQnnSLUYHLIEYZdA5iO9cuAp3bfgb2vLJXek2vYipRg4iZXNqtWKKD9ZX3wLr1eHT0Mg1PVCSD76seuCLmFhQB0sgRg8sgRhlUOMAERHmT+zApcd2VH1uKOTLjUSt1Uu74B69/0S4DuGc1bNrqoe+htW7WNdj2p7kXFcrahWxNRyKyM4XMVn6MGpgCcQoQ71xbOrN9DZcqDfRULXN6OTOAp77l5NTlxcoVbWUo3XXL5mDWDazC3/8y/aYugwetXIjl6ydh/0nVd9wpEXID8IJ18mi+WEJxCiDn2Q9Gx+734ShVFJvuHb9oBezZjGBDGIHhetTLwNWTUn83QtXRzxoWQPNXGsVsX1g/QGDf6mpHszqIEYjLIEYZZALlxoJNA2G0sy1vYr+Iw3q5iBSxmJKi3zGwaVr5+Pkg6eEzg9WBxH3eNZ1oNP6tM51aTDCOuqQmCwu14ZF88ISiFEGyQk0EwfRCNRKIFTzyUaCiPz0rqb31Qop2ivU0F9pw3OkwVB4ZdcCU6iNZow5ZGGGJRCjDPVyEM1OIGoOIz3MStd6d/P/sHImtuwewLuOmZf6GS9Y1et6Z7isxomrBoOQH4SlD6MGza25tIhA7rRbm0jE1AjUugC3F/jeZsHkxilUk1AvgShkXXzoxAPQmku/F1t3AM+RvnxmV13vDKHGjHqNhmraSspvi9EBy0GMMjSjkroRqFXENK2rBd++YBUWTx+eIIRpq/fdC1fX3Dc61h04Cc984qSGWJ6NtB/EgsnjALyEKZ0tePylnSNTCYu6MWTbSiKaQUT3ENETRPQ4Eb1HnF9KRA8Q0SNE9DARHSbOExHdSETPEtGjRLR8qOo2muHWK2LaxzgIAFg1t6emnflgkHYHfticbhzcAKLVKLPkWoL1DQUuPGou/vtda7B6Xg+623IAMGx9ZjF4DGVPlQG8jzH2v0TUAeAPRPRzAP8K4FrG2E+J6GRxfAyAkwDsJ/5WAviS+G+hoF4RU7NzEI3KbT1UoOamr7E4Z/Vs3PX433D60mkj8n7HIRwyi0cqPf/IuWjPZ3DWoTNGpC4WtWPICARjbDOAzeL3LiJ6AsA0cK53nLitE8BL4vfpAL7BuA3cA0TURURTRDkWAsUyj3TWkq2t65rdk7qZEtmb0Cx+GrViZk8rfvuhY0e6GgB4OPFz18we6WpY1IBh4fWIaDaAZQAeBHA5gLuJ6AZwEdcacds0ABuVxzaJc5ZAKOgr8fzStXIQI2XmmBZNLgEbMRm+hcVIYsinJRG1A/hvAJczxnYCeBeA9zLGZgB4L4CvyFsNj0fMHYjoAqG7eHjLli1DVe2mxd4iJxC16iCaHZaDsLBoPgwpgSCiLDhx+BZj7HZx+lwA8vf3ABwmfm8CoAonpyMQP/lgjH2ZMbaCMbait7d3aCrexOgr8rwRg7WUaTbU60k9XLD0wWIsYiitmAicO3iCMfYZ5dJLAI4Wv48FIJO6/gjAOcKaaRWAHVb/EMWA0EHUKmJqdjS9CKzJ62dhMRQYSh3E4QDeCuAxInpEnPswgPMBfJ6IMgD6AVwgrv0EwMkAngWwF8Dbh7BuoxbvOmYeXt1dxFtWzRrpqjQUzc5BWAJhMRYxlFZMv0V8EMlDDPczAJcMVX32FXS15vDpNy4Z6Wo0HM2vgxjpGlhYDD+a3HbEYqyg2a2Yml0EZmExFGjyaWkxVmBFOBYWzQdLIMYYejvyI10FI5pdxGRhMRZhg6KMITz6kROa1qO62UNtWFiMRVgCMYYwrpAd6SpYWFiMIlgRk4WFhYWFEZZAWIwoulotV2Nh0aywIiaLEcVPLjsST7+8a6SrYWFhYYAlEBYjiqldLZja1TLS1bCwsDDAipgsLCwsLIywHISFRUp8/IxFOHja8OTAtrBoBlgCYWGREvtagEQLi2qwIiYLCwsLCyMsgbCwsLCwMMISCAsLCwsLIyyBsLCwsLAwwhIICwsLCwsjLIGwsLCwsDDCEggLCwsLCyMsgbCwsLCwMIIYYyNdh7pBRFsA/LnOxycAeLWB1RkNsG0eG7BtHhsYTJtnMcZ6q900qgnEYEBEDzPGVox0PYYTts1jA7bNYwPD0WYrYrKwsLCwMMISCAsLCwsLI8YygfjySFdgBGDbPDZg2zw2MORtHrM6CAsLCwuLZIxlDsLCwsLCIgFjkkAQ0YlE9BQRPUtEV450feoFEc0gonuI6AkiepyI3iPOdxPRz4noGfF/vDhPRHSjaPejRLRcKetccf8zRHTuSLUpLYjIJaI/EtGd4ngOET0o6v8dIsqJ83lx/Ky4Plsp4ypx/ikiWj8yLUkHIuoiou8T0ZOiv1fv6/1MRO8V43oDEd1GRIV9rZ+J6KtE9AoRbVDONaxfiegQInpMPHMjEVFNFWSMjak/AC6A5wDMBZAD8CcAC0e6XnW2ZQqA5eJ3B4CnASwE8K8ArhTnrwTwSfH7ZAA/BUAAVgF4UJzvBvC8+D9e/B4/0u2r0vYrANwK4E5x/F0AbxK/bwbwLvH7YgA3i99vAvAd8Xuh6Ps8gDliTLgj3a6E9t4C4J3idw5A177czwCmAXgBQIvSv2/b1/oZwFEAlgPYoJxrWL8CeAjAavHMTwGcVFP9RvoDjUCHrAZwt3J8FYCrRrpeDWrbHQCOB/AUgCni3BQAT4nf/w7gzcr9T4nrbwbw78r50H3N9gdgOoBfAjgWwJ1i8L8KIKP3MYC7AawWvzPiPtL7Xb2v2f4AjBOLJWnn99l+FgRio1j0MqKf1++L/QxgtkYgGtKv4tqTyvnQfWn+xqKISQ48iU3i3KiGYKmXAXgQwCTG2GYAEP8nitvi2j7avsnnAHwQgCeOewBsZ4yVxbFaf79t4voOcf9oavNcAFsAfE2I1f6TiNqwD/czY+yvAG4A8BcAm8H77Q/Yt/tZolH9Ok381s+nxlgkECYZ3Kg25SKidgD/DeByxtjOpFsN51jC+aYDEZ0K4BXG2B/U04ZbWZVro6bN4Dvi5QC+xBhbBmAPuOghDqO+zULufjq4WGgqgDYAJxlu3Zf6uRpqbeOg2z4WCcQmADOU4+kAXhqhugwaRJQFJw7fYozdLk6/TERTxPUpAF4R5+PaPpq+yeEATiOiFwF8G1zM9DkAXUSUEfeo9ffbJq53AtiK0dXmTQA2McYeFMffBycY+3I/HwfgBcbYFsZYCcDtANZg3+5niUb16ybxWz+fGmORQPwewH7CGiIHrtD60QjXqS4Ii4SvAHiCMfYZ5dKPAEhLhnPBdRPy/DnCGmIVgB2Chb0bwAlENF7s3E4Q55oOjLGrGGPTGWOzwfvuV4yxswHcA+AN4ja9zfJbvEHcz8T5NwnrlzkA9gNX6DUdGGN/A7CRiBaIU+sA/B/24X4GFy2tIqJWMc5lm/fZflbQkH4V13YR0SrxDc9RykqHkVbQjJBS6GRwi5/nAFw90vUZRDuOAGcZHwXwiPg7GVz2+ksAz4j/3eJ+AnCTaPdjAFYoZb0DwLPi7+0j3baU7T8GgRXTXPCJ/yyA7wHIi/MFcfysuD5Xef5q8S2eQo3WHSPQ1qUAHhZ9/UNwa5V9up8BXAvgSQAbAPwXuCXSPtXPAG4D17GUwHf85zWyXwGsEN/vOQBfgGboUO3PelJbWFhYWBgxFkVMFhYWFhYpYAmEhYWFhYURlkBYWFhYWBhhCYSFhYWFhRGWQFhYWFhYGGEJhMWYhoiSerFyPJWIvj9E7zqDiK6p47kcEf1acRCzsBgWWDNXizENEcPqTsbYomF41+8AnMYYe7WOZ/8ZwLOMsW81vmYWFmZYDsJirON6APOI6BEi+hQRzZax+YnobUT0QyL6MRG9QESXEtEVImDeA0TULe6bR0R3EdEfiOg3RHSA/hIi2h/AgCQORPR1IrpZ3P+0iDEFIjqIiB4S9XmUiPYTRfwQwNnD8UEsLCQsy2ox1nElgEWMsaWAz1GoWAQeJbcA7qX6IcbYMiL6LHjogs+B5wa+iDH2DBGtBPBF8BhRKg4H8L/audkAjgYwD8A9RDQfwEUAPs8Y+5YIBeOKezcAOHRwTbWwqA2WQFhYJOMextgu8Jg2OwD8WJx/DMBiEUl3DYDvKcm68oZypoCH7FbxXcaYB+AZInoewAEA7gdwNRFNB3A7Y+wZAGCMVYioSEQdoj4WFkMOK2KysEjGgPLbU4498A2WA56jYKnyd6ChnD5wLkSFrgBkjLFbAZwm7r+biFROJA+gv852WFjUDEsgLMY6doGna60LjOffeIGIzgT8vMFLDLc+AWC+du5MInKIaB54ELqniGgugOcZYzeCR+9cLMrtASBDX1tYDAssgbAY02CMvQbg/xHRBiL6VJ3FnA3gPCL6E4DHwRPd6Pg1gGVa0vinANwHniv4IsZYP4CzAGwgokfARU7fEPeuBfCTOutnYVEXrJmrhcUwgYg+D+DHjLFfENHXwc1rU/lcENHt4LmVnxrKOlpYqLAchIXF8OFfALTW+pCwZvqhJQ4Www3LQVhYWFhYGGE5CAsLCwsLIyyBsLCwsLAwwhIICwsLCwsjLIGwsLCwsDDCEggLCwsLCyMsgbCwsLCwMOL/A7X4TME08AZQAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "ener_temp = md_sys.get_ener(selection_list=['T-Protein', 'T-non-Protein'])\n",
    "\n",
    "ax = ener_temp.plot(x='time')\n",
    "ax.set_xlabel('time (ps)')\n",
    "ax.set_ylabel('Temperature (K)')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.8"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}