Lung Submodel - Troubleshooting Heatmap Anomalies.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "#%matplotlib\n",
    "%matplotlib inline\n",
    "import numpy\n",
    "import matplotlib.pyplot as plt\n",
    "import sys, os\n",
    "sys.path.append(os.path.abspath(os.path.join(os.getcwd(), os.pardir)))\n",
    "import math, gillespy2\n",
    "from gillespy2.solvers.cpp.ssa_c_solver import SSACSolver\n",
    "from gillespy2.solvers.numpy.basic_ode_solver import BasicODESolver\n",
    "from gillespy2.solvers.numpy.basic_ivp_solver import BasicIVPSolver\n",
    "from scipy import stats"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "class DayModel(gillespy2.Model):\n",
    "    def __init__(self, parameter_values=None, init_v=0, spore=1.61e9, macrophage=1e6):\n",
    "        # initialize\n",
    "        gillespy2.Model.__init__(self, name=\"Macrophage\")\n",
    "        \n",
    "        # species\n",
    "        #S_ = gillespy2.Species(name='S_', initial_value=3.256e6) # low = 4e3; mid = 2e4; high = 1e7\n",
    "        S_ = gillespy2.Species(name='S_', initial_value=spore) # low = 4e3; mid = 2e4; high = 1e7\n",
    "        \n",
    "        #A_ = gillespy2.Species(name='A_', initial_value=1e6) # A = Sa/(k2*S+MuA)\n",
    "        A_ = gillespy2.Species(name='A_', initial_value=macrophage) # A = Sa/(k2*S+MuA)\n",
    "        \n",
    "        H1 = gillespy2.Species(name='H1', initial_value=0)\n",
    "        H2 = gillespy2.Species(name='H2', initial_value=0)\n",
    "        H3 = gillespy2.Species(name='H3', initial_value=0)\n",
    "        H4 = gillespy2.Species(name='H4', initial_value=0)\n",
    "        H5 = gillespy2.Species(name='H5', initial_value=0)\n",
    "        H6 = gillespy2.Species(name='H6', initial_value=0)\n",
    "        \n",
    "        HLN1 = gillespy2.Species(name='HLN1', initial_value=0)\n",
    "        HLN2 = gillespy2.Species(name='HLN2', initial_value=0)\n",
    "        HLN3 = gillespy2.Species(name='HLN3', initial_value=0)\n",
    "        HLN4 = gillespy2.Species(name='HLN4', initial_value=0)\n",
    "        HLN5 = gillespy2.Species(name='HLN5', initial_value=0)\n",
    "        HLN6 = gillespy2.Species(name='HLN6', initial_value=0)\n",
    "        \n",
    "        self.add_species([S_,A_,H1,H2,H3,H4,H5,H6,HLN1,HLN2,HLN3,HLN4,HLN5,HLN6])\n",
    "        \n",
    "        # parameters        \n",
    "        # rate of phagocytosis\n",
    "        k2 = gillespy2.Parameter(name='k2', expression=1e-10)\n",
    "        \n",
    "        # migration to TMLN\n",
    "        k3 = gillespy2.Parameter(name='k3', expression=0.05)\n",
    "        \n",
    "        self.add_parameter([k2,k3])\n",
    "        \n",
    "        # reactions\n",
    "        R1 = gillespy2.Reaction(\n",
    "            name='R1',\n",
    "            reactants={S_:1, A_:1},\n",
    "            products={H1:1},\n",
    "            rate=k2\n",
    "        )\n",
    "        \n",
    "        R2 = gillespy2.Reaction(\n",
    "            name='R2',\n",
    "            reactants={S_:1, H1:1},\n",
    "            products={H2:1},\n",
    "            rate=k2\n",
    "        )\n",
    "        \n",
    "        R3 = gillespy2.Reaction(\n",
    "            name='R3',\n",
    "            reactants={S_:1, H2:1},\n",
    "            products={H3:1},\n",
    "            rate=k2\n",
    "        )\n",
    "        \n",
    "        R4 = gillespy2.Reaction(\n",
    "            name='R4',\n",
    "            reactants={S_:1, H3:1},\n",
    "            products={H4:1},\n",
    "            rate=k2\n",
    "        )\n",
    "        \n",
    "        R5 = gillespy2.Reaction(\n",
    "            name='R5',\n",
    "            reactants={S_:1, H4:1},\n",
    "            products={H5:1},\n",
    "            rate=k2\n",
    "        )\n",
    "        \n",
    "        R6 = gillespy2.Reaction(\n",
    "            name='R6',\n",
    "            reactants={S_:1, H5:1},\n",
    "            products={H6:1},\n",
    "            rate=k2\n",
    "        )\n",
    "        \n",
    "        # To the lung\n",
    "        R7 = gillespy2.Reaction(\n",
    "            name='R7',\n",
    "            reactants={H1:1},\n",
    "            products={HLN1:1},\n",
    "            rate=k3\n",
    "        )\n",
    "        \n",
    "        R8 = gillespy2.Reaction(\n",
    "            name='R8',\n",
    "            reactants={H2:1},\n",
    "            products={HLN2:1},\n",
    "            rate=k3\n",
    "        )\n",
    "        \n",
    "        R9 = gillespy2.Reaction(\n",
    "            name='R9',\n",
    "            reactants={H3:1},\n",
    "            products={HLN3:1},\n",
    "            rate=k3\n",
    "        )\n",
    "        \n",
    "        R10 = gillespy2.Reaction(\n",
    "            name='R10',\n",
    "            reactants={H4:1},\n",
    "            products={HLN4:1},\n",
    "            rate=k3\n",
    "        )\n",
    "        \n",
    "        R11 = gillespy2.Reaction(\n",
    "            name='R11',\n",
    "            reactants={H5:1},\n",
    "            products={HLN5:1},\n",
    "            rate=k3\n",
    "        )\n",
    "        \n",
    "        R12 = gillespy2.Reaction(\n",
    "            name='R12',\n",
    "            reactants={H6:1},\n",
    "            products={HLN6:1},\n",
    "            rate=k3\n",
    "        )\n",
    "                \n",
    "        self.add_reaction([R1,R2,R3,R4,R5,R6,R7,R8,R9,R10,R11,R12])\n",
    "        t = numpy.linspace(0,200,21)\n",
    "        self.timespan(t)\n",
    "        #print(t)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_mean(results):\n",
    "    num =  (\n",
    "        (1*results['HLN1'][-1]) +\n",
    "        (2*results['HLN2'][-1]) +\n",
    "        (3*results['HLN3'][-1]) +\n",
    "        (4*results['HLN4'][-1]) +\n",
    "        (5*results['HLN5'][-1]) +\n",
    "        (6*results['HLN6'][-1])\n",
    "    )\n",
    "\n",
    "    div = (\n",
    "        results['HLN1'][-1] +\n",
    "        results['HLN2'][-1] +\n",
    "        results['HLN3'][-1] +\n",
    "        results['HLN4'][-1] +\n",
    "        results['HLN5'][-1] +\n",
    "        results['HLN6'][-1]\n",
    "    )\n",
    "    \n",
    "    weighted_avg = num / div\n",
    "    return weighted_avg\n",
    "\n",
    "def get_std(results):\n",
    "    num =  (\n",
    "        (1*results['HLN1'][-1]) +\n",
    "        (2*results['HLN2'][-1]) +\n",
    "        (3*results['HLN3'][-1]) +\n",
    "        (4*results['HLN4'][-1]) +\n",
    "        (5*results['HLN5'][-1]) +\n",
    "        (6*results['HLN6'][-1])\n",
    "    )\n",
    "    \n",
    "    num_sq =  (\n",
    "        (1*results['HLN1'][-1]) +\n",
    "        (4*results['HLN2'][-1]) +\n",
    "        (9*results['HLN3'][-1]) +\n",
    "        (16*results['HLN4'][-1]) +\n",
    "        (25*results['HLN5'][-1]) +\n",
    "        (36*results['HLN6'][-1])\n",
    "    )\n",
    "\n",
    "    div = (\n",
    "        results['HLN1'][-1] +\n",
    "        results['HLN2'][-1] +\n",
    "        results['HLN3'][-1] +\n",
    "        results['HLN4'][-1] +\n",
    "        results['HLN5'][-1] +\n",
    "        results['HLN6'][-1]\n",
    "    )\n",
    "    \n",
    "    weighted_avg = num / div\n",
    "    var_x = (num_sq / div) - weighted_avg**2\n",
    "    return numpy.sqrt(var_x)\n",
    "\n",
    "def get_sem(results):\n",
    "    n = (\n",
    "        results['HLN1'][-1] +\n",
    "        results['HLN2'][-1] +\n",
    "        results['HLN3'][-1] +\n",
    "        results['HLN4'][-1] +\n",
    "        results['HLN5'][-1] +\n",
    "        results['HLN6'][-1]\n",
    "    )\n",
    "    return get_std(results)/numpy.sqrt(n)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Wall time: 137 ms\n",
      "Wall time: 0 ns\n",
      "5.891954818687327\n"
     ]
    },
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1296x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1296x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1296x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "################################ ODEINT METHOD ##############################\n",
    "\n",
    "# VALID (UPPER LEFT SPACE)\n",
    "# block at 5, 9\n",
    "model_valid_UL = DayModel(macrophage=4.28e8, spore=6.95e10)\n",
    "%time results_valid_UL = model_valid_UL.run(solver=BasicODESolver)\n",
    "%time mean_of_model_valid_UL = get_mean(results_valid_UL[0])\n",
    "#print(results_valid_UL[0])\n",
    "print(mean_of_model_valid_UL)\n",
    "\n",
    "res = results_valid_UL[0]\n",
    "\n",
    "data = [\n",
    "    res['HLN1'][-1],\n",
    "    res['HLN2'][-1],\n",
    "    res['HLN3'][-1],\n",
    "    res['HLN4'][-1],\n",
    "    res['HLN5'][-1],\n",
    "    res['HLN6'][-1]\n",
    "]\n",
    "x = [1,2,3,4,5,6]\n",
    "\n",
    "mean = get_mean(res)\n",
    "sd = get_std(res)\n",
    "sem = get_sem(res)\n",
    "\n",
    "plt.bar(x,data)\n",
    "plt.xlabel('HLN')\n",
    "plt.ylabel('Count')\n",
    "plt.show()\n",
    "\n",
    "### SPORES AVAILABLE ###\n",
    "\n",
    "fig = plt.figure(figsize=(18,10))\n",
    "fig.suptitle(\"Spores available\", fontsize=20)\n",
    "\n",
    "plt.plot(res['time'], res['S_'], 'g-', label='Spore')\n",
    "\n",
    "plt.xlabel(\"Time in Hours\", fontsize=12)\n",
    "plt.ylabel(\"Number of Cells\", fontsize=12)\n",
    "plt.legend(loc='best', fontsize=12)\n",
    "\n",
    "### HOSTS IN LUNG ###\n",
    "fig = plt.figure(figsize=(18,10))\n",
    "fig.suptitle(\"Anthrax-infected Cells in Lung\", fontsize=20)\n",
    "\n",
    "#plt.plot(results[0]['time'], results[0]['S_'], 'g-', label='Spore')\n",
    "plt.plot(res['time'], res['H1'], 'r-', label='H1')\n",
    "plt.plot(res['time'], res['H2'], 'g-', label='H2')\n",
    "plt.plot(res['time'], res['H3'], 'b-', label='H3')\n",
    "plt.plot(res['time'], res['H4'], 'k-', label='H4')\n",
    "plt.plot(res['time'], res['H5'], 'm-', label='H5')\n",
    "plt.plot(res['time'], res['H6'], 'y-', label='H6')\n",
    "\n",
    "plt.xlabel(\"Time in Hours\", fontsize=12)\n",
    "plt.ylabel(\"Number of Cells\", fontsize=12)\n",
    "plt.legend(loc='best', fontsize=12)\n",
    "\n",
    "### TMLN MIGRATION ###\n",
    "fig = plt.figure(figsize=(18,10))\n",
    "fig.suptitle(\"Migration to TMLN\", fontsize=20)\n",
    "\n",
    "#plt.plot(results[0]['time'], results[0]['S_'], 'b', label='Spores')\n",
    "plt.plot(res['time'], res['HLN1'], 'r-', label='HLN1')\n",
    "plt.plot(res['time'], res['HLN2'], 'g-', label='HLN2')\n",
    "plt.plot(res['time'], res['HLN3'], 'b-', label='HLN3')\n",
    "plt.plot(res['time'], res['HLN4'], 'k-', label='HLN4')\n",
    "plt.plot(res['time'], res['HLN5'], 'm-', label='HLN5')\n",
    "plt.plot(res['time'], res['HLN6'], 'y-', label='HLN6')\n",
    "\n",
    "plt.xlabel(\"Time in Hours\", fontsize=12)\n",
    "plt.ylabel(\"Number of Cells\", fontsize=12)\n",
    "plt.legend(loc='best', fontsize=12)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[ 6.95000000e+10  6.69782412e+10  6.69782412e+10  6.69782412e+10\n",
      "   6.69782412e+10  6.69782412e+10  6.69782412e+10  6.69782412e+10\n",
      "   6.69782412e+10  6.69782412e+10  6.69782412e+10  6.69782412e+10\n",
      "   6.69782412e+10  6.69782412e+10  6.69782412e+10  6.69782412e+10\n",
      "   6.69782412e+10  6.69782412e+10  6.69782412e+10  6.69782412e+10]\n",
      " [ 4.28000000e+08 -1.36639312e-09  1.27940627e-15 -3.77941674e-17\n",
      "  -6.07022248e-18  8.78598648e-19 -7.26975293e-20  1.69489299e-20\n",
      "  -1.90528563e-21  7.76920224e-22 -1.68657689e-22  5.66807110e-23\n",
      "  -4.68290564e-24  3.94096639e-24 -2.72189829e-25  1.88493946e-25\n",
      "   1.01960800e-26 -2.22664205e-27  6.16311368e-27 -1.74328181e-27]\n",
      " [ 0.00000000e+00 -1.28707724e-08 -1.84419080e-13  2.23992788e-14\n",
      "   1.02881683e-14 -3.73634379e-15  8.05021189e-16 -4.55617367e-16\n",
      "   1.31749318e-16 -1.30033828e-16  7.32050447e-17 -5.90299131e-17\n",
      "   1.29119537e-17 -2.55190994e-17  4.79950460e-18 -7.58944820e-18\n",
      "  -8.13232272e-19  5.62042446e-19 -3.72752833e-18  2.72225359e-18]\n",
      " [ 0.00000000e+00 -6.49136781e-08  1.02716294e-11 -3.22211486e-12\n",
      "  -2.50903806e-12  1.30039510e-12 -3.75094482e-13  2.64286295e-13\n",
      "  -9.27637528e-14  1.06807012e-13 -6.94190692e-14  6.28812166e-14\n",
      "  -1.54316932e-14  3.34188568e-14 -6.92579224e-15  1.17940531e-14\n",
      "   1.33516708e-15 -1.01130619e-15  7.14350840e-15 -5.56234075e-15]\n",
      " [ 0.00000000e+00 -2.18602446e-07 -3.64049271e-10  2.73636568e-10\n",
      "   3.44442924e-10 -2.46512764e-10  9.28444314e-11 -8.01371609e-11\n",
      "   3.37385223e-11 -4.49705072e-11  3.35480814e-11 -3.40073772e-11\n",
      "   9.33425627e-12 -2.21055233e-11  5.03868422e-12 -9.23026571e-12\n",
      "  -1.10266569e-12  9.14708506e-13 -6.87725879e-12  5.70622614e-12]\n",
      " [ 0.00000000e+00 -5.28222340e-07  9.55211266e-09 -1.66463466e-08\n",
      "  -3.32829148e-08  3.24893582e-08 -1.58205788e-08  1.66153239e-08\n",
      "  -8.34532776e-09  1.28290627e-08 -1.09509789e-08  1.23962718e-08\n",
      "  -3.79827062e-09  9.82441490e-09 -2.45988455e-09  4.84385826e-09\n",
      "   6.10042864e-10 -5.54010476e-10  4.43148577e-09 -3.91631043e-09]\n",
      " [ 0.00000000e+00 -8.80567791e-07 -1.99891270e-07  7.91823991e-07\n",
      "   2.49242812e-06 -3.29734532e-06  2.06487371e-06 -2.62874038e-06\n",
      "   1.57018351e-06 -2.77753583e-06  2.70757340e-06 -3.41774775e-06\n",
      "   1.16749490e-06 -3.29531862e-06  9.05515053e-07 -1.91565703e-06\n",
      "  -2.54133795e-07  2.52609763e-07 -2.14892259e-06  2.02203537e-06]\n",
      " [ 0.00000000e+00  2.61487910e+08  1.58600435e+08  9.61960263e+07\n",
      "   5.83458393e+07  3.53885404e+07  2.14642348e+07  1.30187165e+07\n",
      "   7.89625069e+06  4.78931814e+06  2.90486829e+06  1.76189168e+06\n",
      "   1.06864132e+06  6.48163727e+05  3.93131173e+05  2.38446110e+05\n",
      "   1.44624876e+05  8.77194216e+04  5.32045186e+04  3.22701718e+04]\n",
      " [ 0.00000000e+00  3.09335255e+06  3.09335255e+06  3.09335255e+06\n",
      "   3.09335255e+06  3.09335255e+06  3.09335255e+06  3.09335255e+06\n",
      "   3.09335255e+06  3.09335255e+06  3.09335255e+06  3.09335255e+06\n",
      "   3.09335255e+06  3.09335255e+06  3.09335255e+06  3.09335255e+06\n",
      "   3.09335255e+06  3.09335255e+06  3.09335255e+06  3.09335255e+06]\n",
      " [ 0.00000000e+00  3.08707662e+06  3.08707662e+06  3.08707662e+06\n",
      "   3.08707662e+06  3.08707662e+06  3.08707662e+06  3.08707662e+06\n",
      "   3.08707662e+06  3.08707662e+06  3.08707662e+06  3.08707662e+06\n",
      "   3.08707662e+06  3.08707662e+06  3.08707662e+06  3.08707662e+06\n",
      "   3.08707662e+06  3.08707662e+06  3.08707662e+06  3.08707662e+06]\n",
      " [ 0.00000000e+00  3.07863502e+06  3.07863502e+06  3.07863502e+06\n",
      "   3.07863502e+06  3.07863502e+06  3.07863502e+06  3.07863502e+06\n",
      "   3.07863502e+06  3.07863502e+06  3.07863502e+06  3.07863502e+06\n",
      "   3.07863502e+06  3.07863502e+06  3.07863502e+06  3.07863502e+06\n",
      "   3.07863502e+06  3.07863502e+06  3.07863502e+06  3.07863502e+06]\n",
      " [ 0.00000000e+00  3.06780801e+06  3.06780801e+06  3.06780801e+06\n",
      "   3.06780801e+06  3.06780801e+06  3.06780801e+06  3.06780801e+06\n",
      "   3.06780801e+06  3.06780801e+06  3.06780801e+06  3.06780801e+06\n",
      "   3.06780801e+06  3.06780801e+06  3.06780801e+06  3.06780801e+06\n",
      "   3.06780801e+06  3.06780801e+06  3.06780801e+06  3.06780801e+06]\n",
      " [ 0.00000000e+00  3.05464155e+06  3.05464155e+06  3.05464155e+06\n",
      "   3.05464155e+06  3.05464155e+06  3.05464155e+06  3.05464155e+06\n",
      "   3.05464155e+06  3.05464155e+06  3.05464155e+06  3.05464155e+06\n",
      "   3.05464155e+06  3.05464155e+06  3.05464155e+06  3.05464155e+06\n",
      "   3.05464155e+06  3.05464155e+06  3.05464155e+06  3.05464155e+06]\n",
      " [ 0.00000000e+00  1.51130576e+08  2.54018051e+08  3.16422460e+08\n",
      "   3.54272647e+08  3.77229946e+08  3.91154251e+08  3.99599770e+08\n",
      "   4.04722236e+08  4.07829168e+08  4.09713618e+08  4.10856595e+08\n",
      "   4.11549845e+08  4.11970323e+08  4.12225355e+08  4.12380040e+08\n",
      "   4.12473861e+08  4.12530767e+08  4.12565282e+08  4.12586216e+08]]\n",
      "Wall time: 407 ms\n",
      "Wall time: 0 ns\n",
      "3.50988044781236\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "ename": "ValueError",
     "evalue": "x and y must have same first dimension, but have shapes (20,) and (14,)",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mValueError\u001b[0m                                Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-5-3d0e5afec6a4>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[0;32m     34\u001b[0m \u001b[0mfig\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0msuptitle\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m\"Spores available\"\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mfontsize\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m20\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     35\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m---> 36\u001b[1;33m \u001b[0mplt\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mplot\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mres\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;34m'time'\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mres\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;34m'S_'\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;34m'g-'\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mlabel\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;34m'Spore'\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m     37\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     38\u001b[0m \u001b[0mplt\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mxlabel\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m\"Time in Hours\"\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mfontsize\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m12\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\Anaconda3\\lib\\site-packages\\matplotlib\\pyplot.py\u001b[0m in \u001b[0;36mplot\u001b[1;34m(scalex, scaley, data, *args, **kwargs)\u001b[0m\n\u001b[0;32m   2811\u001b[0m     return gca().plot(\n\u001b[0;32m   2812\u001b[0m         *args, scalex=scalex, scaley=scaley, **({\"data\": data} if data\n\u001b[1;32m-> 2813\u001b[1;33m         is not None else {}), **kwargs)\n\u001b[0m\u001b[0;32m   2814\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   2815\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\Anaconda3\\lib\\site-packages\\matplotlib\\__init__.py\u001b[0m in \u001b[0;36minner\u001b[1;34m(ax, data, *args, **kwargs)\u001b[0m\n\u001b[0;32m   1808\u001b[0m                         \u001b[1;34m\"the Matplotlib list!)\"\u001b[0m \u001b[1;33m%\u001b[0m \u001b[1;33m(\u001b[0m\u001b[0mlabel_namer\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mfunc\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m__name__\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1809\u001b[0m                         RuntimeWarning, stacklevel=2)\n\u001b[1;32m-> 1810\u001b[1;33m             \u001b[1;32mreturn\u001b[0m \u001b[0mfunc\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0max\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m*\u001b[0m\u001b[0margs\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   1811\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1812\u001b[0m         inner.__doc__ = _add_data_doc(inner.__doc__,\n",
      "\u001b[1;32m~\\Anaconda3\\lib\\site-packages\\matplotlib\\axes\\_axes.py\u001b[0m in \u001b[0;36mplot\u001b[1;34m(self, scalex, scaley, *args, **kwargs)\u001b[0m\n\u001b[0;32m   1609\u001b[0m         \u001b[0mkwargs\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mcbook\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mnormalize_kwargs\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mmlines\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mLine2D\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_alias_map\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1610\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 1611\u001b[1;33m         \u001b[1;32mfor\u001b[0m \u001b[0mline\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_get_lines\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m*\u001b[0m\u001b[0margs\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   1612\u001b[0m             \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0madd_line\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mline\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1613\u001b[0m             \u001b[0mlines\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mappend\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mline\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\Anaconda3\\lib\\site-packages\\matplotlib\\axes\\_base.py\u001b[0m in \u001b[0;36m_grab_next_args\u001b[1;34m(self, *args, **kwargs)\u001b[0m\n\u001b[0;32m    391\u001b[0m                 \u001b[0mthis\u001b[0m \u001b[1;33m+=\u001b[0m \u001b[0margs\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;36m0\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    392\u001b[0m                 \u001b[0margs\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0margs\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;36m1\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 393\u001b[1;33m             \u001b[1;32myield\u001b[0m \u001b[1;32mfrom\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_plot_args\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mthis\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mkwargs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    394\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    395\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\Anaconda3\\lib\\site-packages\\matplotlib\\axes\\_base.py\u001b[0m in \u001b[0;36m_plot_args\u001b[1;34m(self, tup, kwargs)\u001b[0m\n\u001b[0;32m    368\u001b[0m             \u001b[0mx\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0my\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mindex_of\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mtup\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;33m-\u001b[0m\u001b[1;36m1\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    369\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 370\u001b[1;33m         \u001b[0mx\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0my\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_xy_from_xy\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mx\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0my\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    371\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    372\u001b[0m         \u001b[1;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mcommand\u001b[0m \u001b[1;33m==\u001b[0m \u001b[1;34m'plot'\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\Anaconda3\\lib\\site-packages\\matplotlib\\axes\\_base.py\u001b[0m in \u001b[0;36m_xy_from_xy\u001b[1;34m(self, x, y)\u001b[0m\n\u001b[0;32m    229\u001b[0m         \u001b[1;32mif\u001b[0m \u001b[0mx\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mshape\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;36m0\u001b[0m\u001b[1;33m]\u001b[0m \u001b[1;33m!=\u001b[0m \u001b[0my\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mshape\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;36m0\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    230\u001b[0m             raise ValueError(\"x and y must have same first dimension, but \"\n\u001b[1;32m--> 231\u001b[1;33m                              \"have shapes {} and {}\".format(x.shape, y.shape))\n\u001b[0m\u001b[0;32m    232\u001b[0m         \u001b[1;32mif\u001b[0m \u001b[0mx\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mndim\u001b[0m \u001b[1;33m>\u001b[0m \u001b[1;36m2\u001b[0m \u001b[1;32mor\u001b[0m \u001b[0my\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mndim\u001b[0m \u001b[1;33m>\u001b[0m \u001b[1;36m2\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    233\u001b[0m             raise ValueError(\"x and y can be no greater than 2-D, but have \"\n",
      "\u001b[1;31mValueError\u001b[0m: x and y must have same first dimension, but have shapes (20,) and (14,)"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1296x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "################################# SOLVE_IVP METHOD #########################\n",
    "\n",
    "# VALID (UPPER LEFT SPACE)\n",
    "# block at 5, 9\n",
    "model_valid_UL = DayModel(macrophage=4.28e8, spore=6.95e10)\n",
    "%time results_valid_UL = model_valid_UL.run(solver=BasicIVPSolver)\n",
    "%time mean_of_model_valid_UL = get_mean(results_valid_UL[0])\n",
    "print(mean_of_model_valid_UL)\n",
    "\n",
    "res = results_valid_UL[0]\n",
    "\n",
    "data = [\n",
    "    res['HLN1'][-1],\n",
    "    res['HLN2'][-1],\n",
    "    res['HLN3'][-1],\n",
    "    res['HLN4'][-1],\n",
    "    res['HLN5'][-1],\n",
    "    res['HLN6'][-1]\n",
    "]\n",
    "x = [1,2,3,4,5,6]\n",
    "\n",
    "mean = get_mean(res)\n",
    "sd = get_std(res)\n",
    "sem = get_sem(res)\n",
    "\n",
    "plt.bar(x,data)\n",
    "plt.xlabel('HLN')\n",
    "plt.ylabel('Count')\n",
    "plt.show()\n",
    "\n",
    "### SPORES AVAILABLE ###\n",
    "\n",
    "fig = plt.figure(figsize=(18,10))\n",
    "fig.suptitle(\"Spores available\", fontsize=20)\n",
    "\n",
    "plt.plot(res['time'], res['S_'], 'g-', label='Spore')\n",
    "\n",
    "plt.xlabel(\"Time in Hours\", fontsize=12)\n",
    "plt.ylabel(\"Number of Cells\", fontsize=12)\n",
    "plt.legend(loc='best', fontsize=12)\n",
    "\n",
    "### HOSTS IN LUNG ###\n",
    "fig = plt.figure(figsize=(18,10))\n",
    "fig.suptitle(\"Anthrax-infected Cells in Lung\", fontsize=20)\n",
    "\n",
    "#plt.plot(results[0]['time'], results[0]['S_'], 'g-', label='Spore')\n",
    "plt.plot(res['time'], res['H1'], 'r-', label='H1')\n",
    "plt.plot(res['time'], res['H2'], 'g-', label='H2')\n",
    "plt.plot(res['time'], res['H3'], 'b-', label='H3')\n",
    "plt.plot(res['time'], res['H4'], 'k-', label='H4')\n",
    "plt.plot(res['time'], res['H5'], 'm-', label='H5')\n",
    "plt.plot(res['time'], res['H6'], 'y-', label='H6')\n",
    "\n",
    "plt.xlabel(\"Time in Hours\", fontsize=12)\n",
    "plt.ylabel(\"Number of Cells\", fontsize=12)\n",
    "plt.legend(loc='best', fontsize=12)\n",
    "\n",
    "### TMLN MIGRATION ###\n",
    "fig = plt.figure(figsize=(18,10))\n",
    "fig.suptitle(\"Migration to TMLN\", fontsize=20)\n",
    "\n",
    "#plt.plot(results[0]['time'], results[0]['S_'], 'b', label='Spores')\n",
    "plt.plot(res['time'], res['HLN1'], 'r-', label='HLN1')\n",
    "plt.plot(res['time'], res['HLN2'], 'g-', label='HLN2')\n",
    "plt.plot(res['time'], res['HLN3'], 'b-', label='HLN3')\n",
    "plt.plot(res['time'], res['HLN4'], 'k-', label='HLN4')\n",
    "plt.plot(res['time'], res['HLN5'], 'm-', label='HLN5')\n",
    "plt.plot(res['time'], res['HLN6'], 'y-', label='HLN6')\n",
    "\n",
    "plt.xlabel(\"Time in Hours\", fontsize=12)\n",
    "plt.ylabel(\"Number of Cells\", fontsize=12)\n",
    "plt.legend(loc='best', fontsize=12)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Wall time: 149 ms\n",
      "Wall time: 0 ns\n",
      "1.0943758845030915\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1296x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1296x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1296x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# VALID (LOWER RIGHT SPACE)\n",
    "# block at 10, 8\n",
    "model_valid_LR = DayModel(macrophage=1.83E11, spore=3.36E10)\n",
    "%time results_valid_LR = model_valid_LR.run(solver=BasicODESolver)\n",
    "%time mean_of_model_valid_LR = get_mean(results_valid_LR[0])\n",
    "print(mean_of_model_valid_LR)\n",
    "res = results_valid_LR[0]\n",
    "\n",
    "data = [\n",
    "    res['HLN1'][-1],\n",
    "    res['HLN2'][-1],\n",
    "    res['HLN3'][-1],\n",
    "    res['HLN4'][-1],\n",
    "    res['HLN5'][-1],\n",
    "    res['HLN6'][-1]\n",
    "]\n",
    "x = [1,2,3,4,5,6]\n",
    "\n",
    "mean = get_mean(res)\n",
    "sd = get_std(res)\n",
    "sem = get_sem(res)\n",
    "\n",
    "plt.bar(x,data)\n",
    "plt.xlabel('HLN')\n",
    "plt.ylabel('Count')\n",
    "plt.show()\n",
    "\n",
    "### SPORES AVAILABLE ###\n",
    "\n",
    "fig = plt.figure(figsize=(18,10))\n",
    "fig.suptitle(\"Spores available\", fontsize=20)\n",
    "\n",
    "plt.plot(res['time'], res['S_'], 'g-', label='Spore')\n",
    "\n",
    "plt.xlabel(\"Time in Hours\", fontsize=12)\n",
    "plt.ylabel(\"Number of Cells\", fontsize=12)\n",
    "plt.legend(loc='best', fontsize=12)\n",
    "\n",
    "### HOSTS IN LUNG ###\n",
    "fig = plt.figure(figsize=(18,10))\n",
    "fig.suptitle(\"Anthrax-infected Cells in Lung\", fontsize=20)\n",
    "\n",
    "#plt.plot(results[0]['time'], results[0]['S_'], 'g-', label='Spore')\n",
    "plt.plot(res['time'], res['H1'], 'r-', label='H1')\n",
    "plt.plot(res['time'], res['H2'], 'g-', label='H2')\n",
    "plt.plot(res['time'], res['H3'], 'b-', label='H3')\n",
    "plt.plot(res['time'], res['H4'], 'k-', label='H4')\n",
    "plt.plot(res['time'], res['H5'], 'm-', label='H5')\n",
    "plt.plot(res['time'], res['H6'], 'y-', label='H6')\n",
    "\n",
    "plt.xlabel(\"Time in Hours\", fontsize=12)\n",
    "plt.ylabel(\"Number of Cells\", fontsize=12)\n",
    "plt.legend(loc='best', fontsize=12)\n",
    "\n",
    "### TMLN MIGRATION ###\n",
    "fig = plt.figure(figsize=(18,10))\n",
    "fig.suptitle(\"Migration to TMLN\", fontsize=20)\n",
    "\n",
    "#plt.plot(results[0]['time'], results[0]['S_'], 'b', label='Spores')\n",
    "plt.plot(res['time'], res['HLN1'], 'r-', label='HLN1')\n",
    "plt.plot(res['time'], res['HLN2'], 'g-', label='HLN2')\n",
    "plt.plot(res['time'], res['HLN3'], 'b-', label='HLN3')\n",
    "plt.plot(res['time'], res['HLN4'], 'k-', label='HLN4')\n",
    "plt.plot(res['time'], res['HLN5'], 'm-', label='HLN5')\n",
    "plt.plot(res['time'], res['HLN6'], 'y-', label='HLN6')\n",
    "\n",
    "plt.xlabel(\"Time in Hours\", fontsize=12)\n",
    "plt.ylabel(\"Number of Cells\", fontsize=12)\n",
    "plt.legend(loc='best', fontsize=12)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Wall time: 84.8 ms\n",
      "Wall time: 0 ns\n",
      "4.405472394625981\n"
     ]
    },
    {
     "data": {
      "image/png": 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dMPAlqRMGvrqX5NARy69N8o+j9+9M8pZV9qkk716x/JYk72xerLQBBr50bH4GvCzJaUMXIk3KwJeOzSMsf7fpm4YuRJqUd9pKcOKKO5ABngh8fIL93gt8I8nftClLmi4DX4Kfjp68CSyP4bP8JSRjVdWDSa4F/hT4abvypOlwSEfamCuBS4GZei66+mTgSxtQVfcDN7Ic+tKWZuBLa/vLJAcOv1b5/N2As3W05fm0TEnqhD18SeqEgS9JnTDwJakTBr4kdcLAl6ROGPiS1AkDX5I68X9/vnPEypgw3QAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1296x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1296x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
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MBiDcHDnylrZsuVz//e8UHTjwe40Zc5M+/vFdmjDhp4qLy3Y6HgAAACIEcziEkCVLlmjixIm65ZZblJeX12n9Aw88oLPPPltTp051IB2AUHfo0H9UXHynqqr+KLc7RTk5SzV69LcUHZ3udDQAAABEoLAuHBYsWKBNmzYN6DGmTZumBx98sM/bz549W1FRx97WpqYmTZ8+vU/7ZmVlaf78+Vq2bJlWr17dbl1paal+/vOfa+PGjX3OAmDws9aqunq9iovvVHX13xQVla6xY3+gUaNuVFRUitPxAAAAEMHCunAIRWvXrtX555/f+rywsFArV67s8/6LFy/W+PHjtXnz5nbLFyxYoGXLliklhQ8QAHxFQ1XVn1RcfKcOH/6PYmKyNH78fRox4npFRSU5HQ8AAAAI78KhPyMPwkV6eroWLFigpUuXtlv+17/+Va+99poWLVrUuuyMM87Qj3/8Y82dOzfYMQE4xFqvDhxYq+LiO1VT87ZiY7M1YcLDysr6itzuOKfjAQAAAK3CunAIR83NzWpoaGh93vb0i6MWLlyocePGyVrbuuy9996T1+ttfT5ixAi9+OKLOuWUUwY2MICQ4PW2qKLityouXqG6uiLFxY1XXt4vlJl5lVyuGKfjAQAAAJ1QOATZrFmz2j1fsmRJu1MwJCk5OVmLFi3S4sWLW5cNHz6802tlZGQoPj5+YIICCAleb5P27fuVSkruUn39TiUkTFJBwdMaNuxzcrn4KxwAAAChy7T9Fj2UzJgxw27YsKHT8m3btqmgoMCBROGH9woIXx5Pg/bufUIlJT9UY2OJkpJOVU7O7crImC1juKIxAAAAnGOM2WitndHbdnw9BgAhxOOp1e7dP1dp6Y/U1LRXyckf18SJP1Na2oUyxjgdDwAAAOgzCgcACBF79vxCH354i5qbDyg19VwVFDyt1NRzKRoAAAAQligcAMBhXm+j3n//G9qz53GlpHxC48b9QCkpZzkdCwAAADghFA4A4KDGxt0qKrpchw+/ruzsWzV27PdljNvpWAAAAMAJo3AAAIccOvQvFRV9Vi0tRzRp0u80fPhnnY4EAAAABAxTnQNAkFlrVV7+qDZtOlcuV6KmT3+dsgEAAADjeKFlAAAgAElEQVSDDiMcACCIPJ4Gvf/+17V37y+UlnahCgqeVnT0UKdjAQAAAAFH4QAAQdLQUKaiost15Mibys5eorFjlzNfAwAAAAYtCgcACILq6n+qqOiz8nrrNHnyGg0bdpnTkQAAAIABxRwOAZSbm6tXXnml3bLCwkLNnDmz2/WStH79ehljdOONN7ZbPnPmTBUWFrZu43K5lJSU1Hp76qmnBuYHARAwvvkaHtbmzf+rqKgUTZ/+BmUDAAAAIgIjHEJEYmKiVq1apZtvvlm5ubldbjNy5EiVlZUFNxiA4+abr+EG7d37pNLTL1Z+/i8VHZ3qdCwAAAAgKBjhECJSU1M1b948LV++3OkoAAKgoaFUmzb9P+3d+6RycpZpypTfUzYAAAAgolA4hJAlS5ZozZo12rFjR5fr9+/fr8zMTI0dO1bf/va3VVtbG+SEAPqiuvof2rjxNNXV7dDkyc/7J4fkr1sAAABElrA+peL9Be+rZlPNgB4jaVqSJjw4oc/bz549W1FRx97WpqYmTZ8+vU/7ZmVlaf78+Vq2bJlWr17dbl1+fr42bdqk/Px8FRcX6+qrr9bChQv185//vM/ZAAws33wNP9XOnQsVH3+Spkx5XomJBU7HAgAAABzBV24BtnbtWlVXV7feHnnkkX7tv3jxYq1bt06bN29utzwrK0uTJk2Sy+XS2LFjdc899+jZZ58NZHQAJ8Djqdf27fO0c+e3lJ5+kU477Q3KBgAAAES0sB7h0J+RB+EiPT1dCxYs0NKlS3vczhgja22QUgHoSUNDibZsmaOamreUm7tcOTm3cwoFAAAAIl5YFw7hqLm5WQ0NDa3P255+cdTChQs1bty4doXC+vXrNW7cOI0ZM0ZlZWW65ZZbdOmllwYlM4DuHTz4d23d+jl5vU2aMuUFZWR8xulIAAAAQEjgK7ggmzVrluLj41tvd9xxR6dtkpOTtWjRIlVVVbUue+utt3TGGWcoMTFRZ555pqZMmaKf/OQnQUwOoC1rrUpLH9TmzZ9UdHSGTjvtTcoGAAAAoA0TqsPyZ8yYYTds2NBp+bZt21RQwHnRfcF7BQwMj6dOO3Zcr/37n1ZGxmzl5z+lqKhkp2MBAAAAQWGM2WitndHbdpxSAQD9UF+/S0VFl6mmZpNyc7+vnJzbmK8BAAAA6AKFAwD00cGDf1VR0edlbYtOPvlFpadf5HQkAAAAIGTxtRwA9MI3X8N92rz5U4qJydRpp/2XsgEAAADoBSMcAKAHvvkartP+/b9RRsblys9/UlFRQ5yOBQAAAIQ8CgcA6EZ9/UfasmWOamvf0dixK5SdfYuMMU7HAgAAAMIChQMAdKGq6i/auvVKSV6dfPIflZ5+gdORAAAAgLDCHA4A0Ia1ViUlP9I771yg2NiRmj79v5QNAAAAwHFghAMA+Hk8tdq+/SuqqPithg27Qnl5TygqKsnpWAAAAEBYonAAAEn19R/452so0rhxP9SYMTczXwMAAABwAjilIoByc3P1yiuvtFtWWFiomTNndrtektavXy9jjG688cZ2y2fOnKnCwsLW5xUVFZo7d65SU1M1dOhQffGLXwz8DwFEoKqqddq48XQ1NpZp6tQ/KTt7EWUDAAAAcIIoHEJEYmKiVq1apV27dnW7zWWXXaasrCwVFxdr//79+s53vhO8gMAgZK1VcfHdeuedCxUbO0annbZBaWmfcjoWAAAAMChwSkWISE1N1Zw5c7R8+XI9+eSTnda//PLLKi0t1fr16+V2uyVJp556arBjAoNGS0uNduy4RhUVz2r48CuVl7dSbnei07EAAACAQYMRDiFkyZIlWrNmjXbs2NFp3euvv668vDxdffXVSk9P1+mnn65//OMfDqQEwl9d3U699dbHVVHxnMaPv1cFBb+mbAAAAAACLKxHOLz//gLV1Gwa0GMkJU3ThAkP9nn72bNnKyrq2Nva1NSk6dOn92nfrKwszZ8/X8uWLdPq1avbrSsrK9PLL7+slStX6sknn9SaNWt06aWXaufOncrIyOhzPiDSVVb+Sdu2zZXk0tSp65SWdr7TkQAAAIBBiREOAbZ27VpVV1e33h555JF+7b948WKtW7dOmzdvbrc8Pj5eubm5uvbaaxUdHa0rr7xSY8aM0b/+9a9AxgcGLd98DT/Qu+9epLi4XP98DZQNAAAAwEAJ6xEO/Rl5EC7S09O1YMECLV26tN3yqVOn6sUXX3QoFRDeWlqOaPv2eTpw4DkNHz5XeXmPy+1OcDoWAAAAMKgxwiHImpub1dDQ0HpraWnptM3ChQv173//W9u2bWtdNmfOHB08eFBPPfWUPB6Pnn32WZWXl+uss84KZnwg7NTVva+33vq4Dhz4vcaPv18FBb+ibAAAAACCgMIhyGbNmqX4+PjW2x133NFpm+TkZC1atEhVVVWty9LS0vTCCy/o3nvvVUpKiu6++279/ve/Z/4GoAeVlS9p48bT1dy8X6ec8rLGjPm2jDFOxwIAAAAigrHWOp2hSzNmzLAbNmzotHzbtm0qKChwIFH44b1CpPLN13Cndu36rpKSTtWUKc8pLi7H6VgAAADAoGCM2WitndHbdmE9hwMAdKW09B7t2rVMmZlXaeLEx+R2xzsdCQAAAIg4FA4ABpXq6n/oww9v07Bhn1N+/ipOoQAAAAAcwhwOAAaNxsa92rr1SsXHn6S8vJWUDQAAAICDGOEAYFDwelu0bdsX1NJySFOnvqyoqCFORwIAAAAiWlgWDtZavrnsRahOBgoMlF27vqvq6vXKzy9UUtLJTscBAAAAIl7YnVLhdrvV3NzsdIyQV19fr+joaKdjAEFRWfmSSkpWaMSI65SVdbXTcQAAAAAoDAuH1NRU7du3T16v1+koIclaq7q6OpWXl2v48OFOxwEGXENDsbZt+5KSkqbppJN+4nQcAAAAAH5hd0pFRkaGysrKtGPHDqejhKzo6GhlZmYqOTnZ6SjAgPJ6G1VUdIWs9WjSpN9x+UsAAAAghIRd4eByuZSdne10DAAh4IMPvqMjR/6ryZPXKCHhJKfjAAAAAGgj7E6pAABJ2r9/tcrLH9Lo0d/WsGGXOR0HAAAAQAcUDgDCTl3dDu3YcZ2Sk8/UuHE/dDoOAAAAgC5QOAAIKx5PrbZsuVwuV5wmTVotl4ursQAAAAChKOzmcAAQuay1eu+9G1RXt1VTp/5ZcXGjnY4EAAAAoBuMcAAQNvbs+YX27VulnJxlSkv7lNNxAAAAAPSAwgFAWDhy5G29//7XNXToJ5Wbu9TpOAAAAAB6EbRTKowxuyQdkeSR1GKtnRGsYwMIb83N1SoqukLR0RkqKHhaxridjgQAAACgF8Gew+Fca+2BIB8TQBiz1mrHjmvU2FisadPWKyZmmNORAAAAAPQBk0YCCGllZQ/owIG1Gj/+PqWknOV0HAAAAAB9FMw5HKykl40xG40x1wfxuADC1KFD/9IHHyxSRsYcjR79bafjAAAAAOiHYI5wOMtau9sYM1zSX4wx2621r7bdwF9EXC9J2dnZQYwGINQ0NVWoqOjziovLVV7eEzLGOB0JAAAAQD8EbYSDtXa3/36/pOcl/U8X2zxmrZ1hrZ0xbBjnaQORylqPtm37opqbD2jy5GcVHZ3qdCQAAAAA/RSUwsEYk2iMGXL0saRPSdoSjGMDCD+7dn1fBw/+RRMmPKQhQ6Y5HQcAAADAcQjWKRWZkp73D4mOkvRra+2fg3RsAGGkquplFRd/T5mZX9aIEdc6HQcAAADAcQpK4WCt/VDSKcE4FoDw1dBQpm3bvqjExMmaOPER5m0AAAAAwlgwr1IBAN3yepu1devn5PU2aPLkZ+V2JzodCQAAAMAJCOZVKgCgWx9+uFiHD/9HkyY9o4SEPKfjAAAAADhBjHAA4LiKiudUVvaARo36uoYP/7zTcQAAAAAEAIUDAEfV1e3U9u3XaMiQ0zV+/L1OxwEAAAAQIBQOABzj8dSrqOizMsatyZN/J5cr1ulIAAAAAAKEORwAOGbnzm+qtnazTj75D4qLy3E6DgAAAIAAYoQDAEfs3fuU9uxZqezs25SefpHTcQAAAAAEGIUDgKCrqXlX7733NaWmnqPc3OVOxwEAAAAwACgcAARVS8thFRV9VlFRKSoo+I1cLs7sAgAAAAYj/qcPIGistdqx46uqr9+padP+ptjYLKcjAQAAABggFA4Agqa8/CFVVPxW48bdrdTUTzgdBwAAAMAA4pQKAEFx+PAb+uCDm5SefrHGjLnZ6TgAAAAABhiFA4AB19xcqaKiKxQTM1L5+U/JGP7qAQAAAAY7TqkAMKCs9Wrbti+pqWmfTj31X4qOTnM6EgAAAIAgoHAAMKBKSu5SVdWfNGHCw0pOnuF0HAAAAABBwrhmAAPm4MG/66OPlmn48C9o5MivOR0HAAAAQBBROAAYEI2Nu7V165VKSJioiRMfkzHG6UgAAAAAgohTKgAEnNfboq1bvyCPp0bTpv1NUVFJTkcCAAAAEGQUDgAC7qOPbtehQ68qP/+XSkyc7HQcAAAAAA7glAoAAXXgwAsqLf2hRoz4P2VlXeV0HAAAAAAOoXAAEDD19R9p+/arlZQ0XSed9KDTcQAAAAA4iMIBQEB4PA0qKrpC1lpNnvw7ud1xTkcCAAAA4CDmcAAQEB98sFA1NRs1ZcpaxcePczoOAAAAAIcxwgHACdu379favftnGjPmO8rIuNTpOAAAAABCAIUDgBNSW7tNO3Zcr5SUmRo7doXTcQAAAACECAoHAMetpaVGRUWXy+1O0KRJz8jlinY6EgAAAIAQwRwOAI6LtVbvvTdfdXXbdcopf1Fs7CinIwEAAAAIIRQOAI7Lnj2Paf/+p5Wb+z0NHXqe03EAAAAAhBhOqQDQb0eObNT7739TQ4d+Wjk5S5yOAwAAACAEUTgA6Jfm5oMqKrpCMTHDVVDwKxnDXyMAAAAAOuOUCgB9Zq3V9u3z1NhYqmnTXlVMTIbTkQAAAACEKAoHAH1WWnqvKitf0EknPaiUlDOcjgMAAAAghDEWGkCfVFe/qg8/vFUZGZdr1KhvOh0HAAAAQIijcADQq6amfdq69UrFx49Tfv4TMsY4HQkAAABAiOOUCgA9stajrVvnqqXloKZO/bOiopKdjgQAAAAgDFA4AOjRrl3LVV39N+XlPaGkpKlOxwEAAAAQJjilAkC3GhqKVVJylzIzv6QRI65xOg4AAACAMELhAKBbpaX3SpLGjv2Bw0kAAAAAhBsKBwBdamrapz17Vioz88uKixvjdBwAAAAAYYbCAUCXSksfkNfbpOzsxU5HAQAAABCGKBwAdNLcfFC7dz+iYcOuUELCRKfjAAAAAAhDFA4AOikvf1gezxHl5NzqdBQAAAAAYYrCAUA7LS01Kit7UGlpFykp6RSn4wAAAAAIUxQOANrZs+dxtbRUKidnidNRAAAAAIQxCgcArbzeRpWW3qvU1HOUknKG03EAAAAAhLEopwMACB179z6lpqbdys8vdDoKAAAAgDDHCAcAkiSvt0UlJT/UkCGna+jQ852OAwAAACDMUTgAkCRVVPxWDQ0fKjv7NhljnI4DAAAAIMxROACQtV4VF69QQsJkZWRc4nQcAAAAAIMAczgAUGXli6qrK1JBwa9kDD0kAAAAgBPHJwsgwllrVVy8QnFx4zRs2OedjgMAAABgkKBwACLcwYN/1ZEjbyo7e7FcLgY9AQAAAAgMCgcgwpWUrFBMzAhlZV3tdBQAAAAAgwiFAxDBDh36j6qr/64xY74jlyvW6TgAAAAABhEKByCClZSsUFRUukaMuN7pKAAAAAAGGQoHIELV1GxWZeUfNHr0txQVleR0HAAAAACDDIUDEKFKSu6W2z1Eo0Z93ekoAAAAAAYhCgcgAtXVva/9+3+rkSNvUHT0UKfjAAAAABiEKByACFRS8kO5XDEaM+bbTkcBAAAAMEhROAARpqGhVPv2rVJW1rWKicl0Og4AAACAQYrCAYgwpaX3SrLKzr7Z6SgAAAAABjEKByCCNDXt1549jysz8yrFxeU4HQcAAADAIEbhAESQsrIfy+ttUHb2LU5HAQAAADDIUTgAEaK5uVrl5Q9p2LDPKiEhz+k4AAAAAAY5CgcgQuze/Yg8nsPKzr7V6SgAAAAAIgCFAxABPJ46lZU9oLS0CzVkyKlOxwEAAAAQASgcgAiwZ8/jam4+oJycJU5HAQAAABAhglo4GGPcxpi3jTF/COZxgUjm9TappORHSkk5WykpZzkdBwAAAECECPYIh29J2hbkYwIRbd++X6qpqVw5Obc5HQUAAABABAla4WCMGS3pIkkrg3VMINJ5vS0qKblbSUmnaejQTzkdBwAAAEAEiQrisR6UtEjSkCAeE4hoFRXPqr5+pyZPXiNjjNNxAAAAAESQoIxwMMZcLGm/tXZjL9tdb4zZYIzZUFFREYxowKBlrVclJSuUkFCgjIzZTscBAAAAEGGCdUrFWZIuMcbskvSMpP81xvyq40bW2sestTOstTOGDRsWpGjA4FRZ+ZJqa99VdvatMoYL0gAAAAAIrqB8CrHW3mqtHW2tzZV0paS/WWuvCsaxgUhkrVVx8Q8UF5er4cOvdDoOAAAAgAjE157AIFRd/XcdOfKGxoxZLJcr2uk4AAAAACJQMCeNlCRZa9dLWh/s4wKRpLh4hWJispSVNc/pKAAAAAAiFCMcgEHm8OE3VF39V40efZPc7jin4wAAAACIUBQOwCBTXLxCUVFDNXLkfKejAAAAAIhgFA7AIFJT864qK1/Q6NHfUlRUktNxAAAAAEQwCgdgECkpuVtud5JGjfqG01EAAAAARDgKB2CQqKvbqf37n9HIkV9TdHSa03EAAAAARDgKB2CQKC29R8ZEa/TobzsdBQAAAAAoHIDBoLGxXHv3FmrEiK8oNnaE03EAAAAAgMIBGAxKS++VtV6NGbPI6SgAAAAAIKmPhYMx5lxjzFj/4xHGmKeMMU8YY7IGNh6A3jQ1VWj37seUmflFxcfnOh0HAAAAACT1fYTDI5I8/sf3SYqWZCU9NhChAPRdeflP5PXWKzv7FqejAAAAAECrqD5uN8paW2KMiZL0aUk5kpok7R6wZAB61dJySGVlP1VGxmVKTCxwOg4AAAAAtOpr4XDYGJMpaYqkrdbaGmNMjHwjHQA4pLz8Z/J4Dikn51anowAAAABAO30tHH4q6b+SYiQt8C87S9L2gQgFoHceT53Kyu5XWtoFGjLkNKfjAAAAAEA7fSocrLU/NMY8L8ljrf3Av7hc0nUDlgxAj/bs+YWamyuUnX2b01EAAAAAoJO+jnCQtfa9np4DCB6vt0mlpT9SSspMpab+P6fjAAAAAEAn3RYOxphS+a5E0SNrbXZAEwHo1b59T6uxsVQTJ3KhGAAAAAChqacRDlcFLQWAPrPWo5KSu5SUdKrS0j7tdBwAAAAA6FK3hYO19h/BDAKgbyoq1qi+/n1NmvQ7GWOcjgMAAAAAXerplIrv9eUFrLXLAhcHQE+stSouXqGEhHwNG3aZ03EAAAAAoFs9nVIxJmgpAPRJVdUfVVu7Wfn5hTLG5XQcAAAAAOhWT6dUXBPMIAB65hvd8APFxuZo+PC5TscBAAAAgB71+bKYxpgCSZ+VlGmt/boxJk9SrLX2nQFLB6DVoUOv6vDh/2jChIflckU7HQcAAAAAetSnMdnGmCskvSpplKQv+xcPkXT/AOUC0EFx8Q8UHZ2prCwGHwEAAAAIfX09Cfx7kj5prZ0vyeNftlnSKQOSCkA7hw//VwcP/kVjxiyU2x3vdBwAAAAA6FVfC4fh8hUMkmTb3NuuNwcQSCUldykqKlUjR37N6SgAAAAA0Cd9LRw2SvpSh2VXSnozsHEAdFRbW6QDB57XqFHfVFTUEKfjAAAAAECf9HXSyG9KetkYc62kRGPMOkkTJX1qwJIBkCSVlNwtlytRo0d/0+koAAAAANBnfSocrLXbjTH5ki6W9AdJpZL+YK2tGchwQKSrr/9Q+/b9RqNHL1B0dLrTcQAAAACgz3osHIwx8ZLGW2u3WGvrJP22zbopxpid1tqGgQ4JRKqSkntkjFtjxix0OgoAAAAA9EtvczgsknRtN+uukXRzYOMAOKqxcbf27n1SWVnXKDZ2pNNxAAAAAKBfeiscPi/p3m7W3S/pC4GNA+Co0tL7ZK1H2dmLnI4CAAAAAP3WW+Ewylpb3tUK//JRgY8EoLm5Urt3P6rMzC8oPn6c03EAAAAAoN96KxxqjTFjulphjMmWVBf4SADKyn4ir7dO2dm3Oh0FAAAAAI5Lb4XDHyWt6Gbd9yW9FNg4AFpaDqu8/CfKyJijxMRJTscBAAAAgOPS22Uxb5f0H2PMZknPSdojaYSkOZKSJZ05sPGAyLN796NqaalWdvZtTkcBAAAAgOPWY+Fgrd1rjJku6SZJF0hKl1Qp6UVJ91trDw58RCByeDz1Ki29X0OHfkrJyTOcjgMAAAAAx623EQ7ylwq3+28ABtDevU+ouXmfcnIY3QAAAAAgvPU2hwOAIPF6m1VSco+Sk89USsrZTscBAAAAgBPS6wgHAMGxf/+v1dhYookTfyZjjNNxAAAAAOCEMMIBCAHWelRcfJcSE09RWtqFTscBAAAAgBPWbeFgjHm9zePvBicOEJkqKp5Xff0O5eTcxugGAAAAAINCTyMcJhpj4vyPbwpGGCASWWtVUrJC8fETNWzY5U7HAQAAAICA6GkOh99Les8Ys0tSvDHm1a42stYyux1wAqqq/qyamreVl/eEjHE7HQcAAAAAAqLbwsFae40xZqakXEmnS/pFsEIBkaSkZIViY8coM/OLTkcBAAAAgIDp8SoV1trXJL1mjImx1j4VpExAxKiu/qcOHXpNJ530U7lcMU7HAQAAAICA6dNlMa21TxhjzpX0JUmjJJVL+pW19m8DGQ4Y7IqLf6Do6OEaMeJap6MAAAAAQED16bKYxpjrpP/P3n2HV1kfbBz/PplAwsxgD1HcG2rra124igupC+seVdS6wDprtXVXpYBYV7VqreBARakoKg7cxQECTnAQApwsAiEh6zzvHweRTQJJTsb3c125cvKcZ9xB/OPc/AZPAouAZ4GFwBNBEPy+HrNJzdqyZR9TVPQKPXpcRmJi63jHkSRJkqQ6VaMRDsAVwCFhGM746UAQBE8CE4AH6yOY1Nz98MOtJCa2p3v3C+IdRZIkSZLqXI1GOAAZwJy1jn0FdKrbOFLLsHz5F+TnP0uPHheRlNQu3nEkSZIkqc7VtHB4BxgZBEEbgCAI0oA7gPfqK5jUnP34420kJLSme/dL4h1FkiRJkupFTQuHYcCuQHEQBIuBJcBuwHn1FUxqrsrKvmfx4v/Qrdt5pKRkxjuOJEmSJNWLmu5SsRDYPwiCHkA3IDcMw5x6TSY1U/Pn/40gSKRnzxHxjiJJkiRJ9aami0YCsLJksGiQNlN5+UIWLnyYLl3OIDW1e7zjSJIkSVK9qemUCkl1ICfn74RhJb16XRHvKJIkSZJUrywcpAZSWVlIbu69ZGcPpXXrreMdR5IkSZLq1SYLhyAIEoIgGBgEQUpDBJKaq9zce6muLqFXr6vjHUWSJEmS6t0mC4cwDKPAxDAMKxogj9QshWHIokX/pkOHA0hP3znecSRJkiSp3tV0SsXbQRD8ql6TSM1YSckMysq+Ijv7pHhHkSRJkqQGUdNdKn4AJgdBMBGYD4Q/vRGG4Z/rI5jUnEQi4wiCJLKyjo13FEmSJElqEDUtHFoDz6983aOeskjNUhiGRCLj6djxUJKTM+IdR5IkSZIaRI0KhzAMz6zvIFJztXTp+5SX/8hWW90c7yiSJEmS1GBqOsKBIAh2AI4DOodh+IcgCLYDUsMwnFlv6aRmIBIZT0JCKzIzj453FEmSJElqMDVaNDIIguOBt4HuwGkrD7cFRtZTLqlZCMNqIpGn6NTpCJKS2sU7jiRJkiQ1mJruUvFX4JAwDIcB1SuPzQB2q5dUUjOxZMmbVFYupnNnd6eQJEmS1LLUtHDIJlYwwM87VISrvZa0HpHIeBIT29Kp0+HxjiJJkiRJDaqmhcPHwKlrHRsKfFS3caTmIxqtIC9vApmZx5CY2DrecSRJkiSpQdV00ciLgSlBEJwNpAVB8AqwLXBovSWTmrjCwilUVRWRnT003lEkSZIkqcHVdFvML4Mg2B44EpgEzAcmhWFYUp/hpKYsEhlPUlInOnY8ON5RJEmSJKnB1XhbzDAMS4MgeBf4DsitTdkQBEErYrtcpK585jNhGF5f27BSU1FdXUp+/vN07nwyCQkp8Y4jSZIkSQ2uptti9gqCYBrwPfBf4PsgCN4JgqB3DZ9TDgwMw3A3YHfgN0EQ/GpzAktNQUHBf4lGlzudQpIkSVKLVdNFIx8ltnBkhzAMs4GOwP9WHt+kMOanERHJK7/c4ULNViQyjpSUrnTosF+8o0iSJElSXNR0SkV/4NAwDCsBwjAsCYLgSqCgpg8KgiCRWGmxDXBPGIYf1jas1BRUVRVTUPAS3boNI/bXXpIkSZJanpqOcPgA2GutYwOA92v6oDAMq8Mw3B3oAewVBMHOa58TBMG5QRBMD4Jgel5eXk1vLTUq+fnPE4blTqeQJEmS1KJtcIRDEAR/Xe3HucBLQRD8l9gOFT2Bw4EnavvAMAyXBEHwJvAbYNZa7z0APAAwYMAAp1yoSYpExtOqVR/atftlvKNIkiRJUtxsbIRDz9W+WgHPElv8MXvl9+dWHt+kIAiygiDosPJ1a+Bg4MvNjy01ThUV+RQWvkp29lCCIIh3HEmSJEmKmw2OcAjD8Mw6fE5X4NGV6zgkAE+FYTipDu8vNQp5ec8A1WRnnxTvKJIkSZIUVzVdNJIgCNoQW/AxffXjYRi+t6lrwzCcCexR63RSExOJjKdNmx1IS9sl3lEkSZIkKa5qVDgEQXAaMBaoAMpWeysEetVDLqnJKZ0otdEAACAASURBVC9fQHHx2/Tpc4PTKSRJkiS1eDUd4fA34NgwDF+tzzBSUxaJPAWE7k4hSZIkSdR8W8wK4M16zCE1eZHIeNLT96RNm23jHUWSJEmS4q6mhcN1wMggCDLrM4zUVJWVzWXZso9cLFKSJEmSVqpp4fA1cDSwOAiC6pVf0SAIqusxm9RkRCJPApCdfUKck0iSJElS41DTNRz+DTwGPMmai0ZKAiKRcbRrtw+tWrmGqiRJkiRBzQuHDODPYRiG9RlGaopKSmaxfPks+vUbG+8okiRJktRo1HRKxb+AU+sziNRU5eU9CSSQlXVcvKNIkiRJUqNR0xEOewF/CILgWmDx6m+EYbhfnaeSmogwDFm8eBwdOx5ESkrneMeRJEmSpEajpoXDgyu/JK1m2bKPWbFiLr17XxPvKJIkSZLUqNSocAjD8NH6DiI1RZHIOIIgmczMIfGOIkmSJEmNSo0KhyAIztrQe2EYPlx3caSmIwyjRCJP0qnTIJKTO8Y7jiRJkiQ1KjWdUrH2gpFdgK2BdwELB7VIxcXvUFGxgOzsO+IdRZIkSZIanZpOqThw7WMrRz3sUOeJpCYiEhlPQkIbMjOPjncUSZIkSWp0arot5vo8ApxdRzmkJiUarSIv72kyMo4iMTEt3nEkSZIkqdGp6RoOaxcTbYBTgCV1nkhqApYseZ3Kynyys4fGO4okSZIkNUo1XcOhCgjXOrYA+H3dxpGahkhkPImJ7cnIGBTvKJIkSZLUKNW0cNhqrZ+Xh2GYX9dhpKagunoFeXnPkpX1WxISUuMdR5IkSZIapZouGvlDfQeRmorCwpeprl5KdvZJ8Y4iSZIkSY3WRguHIAjeYN2pFKsLwzA8qG4jSY1bJDKe5ORMOnQYGO8okiRJktRobWqEw+MbON4duJjY4pFSi1FVVUJBwQt06XIGCQk1nZEkSZIkSS3PRj8xhWH40Oo/B0GQAVxNbLHIJ4G/1l80qfEpKHiRaLTM6RSSJEmStAlrb3e5XkEQtAuC4EbgW6AzsGcYhueGYZhTr+mkRiYSGUdqag/at98n3lEkSZIkqVHbaOEQBEHrIAiuBuYBOwC/DsPw1DAM5zZIOqkRqawsorDwZbKyTiQIatTVSZIkSVKLtalJ6N8BicDfgOlA5yAIOq9+QhiGU+spm9So5Oc/SxhWkp09NN5RJEmSJKnR21ThsILYLhXnb+D9EOhbp4mkRioSGU/r1tvQtm3/eEeRJEmSpEZvU4tG9mmgHFKjVlGxmKKiqfTufQ1BEMQ7jiRJkiQ1ek5El2ogEnkaiDqdQpIkSZJqyMJBqoFIZDxpabuQlrZTvKNIkiRJUpNg4SBtwooVP7J06buObpAkSZKkWrBwkDYhEnkSwMJBkiRJkmrBwkHahEhkPG3b7kXr1m7IIkmSJEk1ZeEgbURp6deUlHzi6AZJkiRJqiULB2kjIpHxQEB29gnxjiJJkiRJTYqFg7QBYRgSiYyjffv9SE3tHu84kiRJktSkWDhIG7B8+UxKS7+kc+eT4h1FkiRJkpocCwdpA2LTKRLJzDw23lEkSZIkqcmxcJDWIzadYjydOh1CSkpmvONIkiRJUpNj4SCtx9KlH7JixfdkZzudQpIkSZI2h4WDtB6RyDiCIJXMzGPiHUWSJEmSmiQLB2ktYVhNXt5TZGQcQVJSu3jHkSRJkqQmycJBWsuSJW9RUbGI7Oyh8Y4iSZIkSU2WhYO0lkhkPImJ6WRkHBHvKJIkSZLUZFk4SKuJRivIy5tARsZgEhPbxDuOJEmSJDVZFg7SaoqKXqWqqtDpFJIkSZK0hSwcpNVEIuNJSupIp06HxjuKJEmSJDVpFg7SStXVpeTnP09W1rEkJKTEO44kSZIkNWkWDtJKBQUvUV1d4nQKSZIkSaoDFg7SSpHIeJKTO9OhwwHxjiJJkiRJTZ6FgwRUVS2loGAS2dknEASJ8Y4jSZIkSU2ehYME5OdPJAzLyc4+Kd5RJEmSJKlZsHCQgEhkHKmpvWnX7lfxjiJJkiRJzYKFg1q8iop8iopeJTv7RIIgiHccSZIkSWoWLBzU4uXnP0sYVjmdQpIkSZLqkIWDWrxIZBytW29Hevpu8Y4iSZIkSc2GhYNatPLyXJYseYvOnU9yOoUkSZIk1SELB7VokchTQEhW1onxjiJJkiRJzYqFg1q0SGQ86em7k5a2fbyjSJIkSVKzYuGgFqusbB7Lln3oYpGSJEmSVA8sHNRiRSJPApCd7XQKSZIkSaprFg5qsSKR8bRr93+0atU73lEkSZIkqdmxcFCLtHz5HJYvn0l29tB4R5EkSZKkZsnCQS1SJDIeSCAr6/h4R5EkSZKkZsnCQS1OGIZEIuPo0OFAUlO7xDuOJEmSJDVLFg5qcUpKPqGs7FunU0iSJElSPbJwUIsTiYwnCJLJyvptvKNIkiRJUrNl4aAWJQyjRCLj6dTpMJKTO8U7jiRJkiQ1WxYOalGKi9+jvDyH7OyT4h1FkiRJkpq1BikcgiDoGQTBG0EQfBEEwewgCC5piOdKa4tExpGQ0JqMjKPjHUWSJEmSmrWkBnpOFTAiDMNPgiBoC3wcBMGrYRjOaaDnS0SjVeTlPU1GxpEkJaXHO44kSZIkNWsNMsIhDMOFYRh+svL1MuALoHtDPFv6yZIlU6mszHM6hSRJkiQ1gAZfwyEIgj7AHsCHDf1stWyRyHgSE9vRqdOgeEeRJEmSpGavQQuHIAjSgQnApWEYLl3P++cGQTA9CILpeXl5DRlNzVw0Wk5e3rNkZg4hMbFVvONIkiRJUrPXYIVDEATJxMqG/4Rh+Oz6zgnD8IEwDAeEYTggKyuroaKpBSgsfJnq6mKys4fGO4okSZIktQgNtUtFADwEfBGG4ciGeKa0ukhkPElJGXTseFC8o0iSJElSi9BQIxz2AU4FBgZB8NnKr8Mb6Nlq4aqrl5Of/wLZ2ceTkJAc7ziSJEmS1CI0yLaYYRi+AwQN8Sxpbfn5LxKNljqdQpIkSZIaUIPvUiE1tEhkPCkp3Wjfft94R5EkSZKkFsPCQc1aZeUSCgsnk519IkHgX3dJkiRJaih+AlOzlp//HGFY4XQKSZIkSWpgFg5q1iKRcbRq1Ze2bX8R7yiSJEmS1KJYOKjZqqiIUFT0OtnZQ4ntzCpJkiRJaigWDmq28vKeAaJkZ58U7yiSJEmS1OJYOKjZikTG0abNTqSn7xzvKJIkSZLU4lg4qFlasWI+xcXvuFikJEmSJMWJhYOapUjkSQALB0mSJEmKEwsHNUuRyHjath1AmzbbxDuKJEmSJLVIFg5qdkpLv6Gk5GMXi5QkSZKkOLJwULMTiYwHICvrhDgnkSRJkqSWy8JBzUoYhkQi42jffl9ateoR7ziSJEmS1GJZOKhZWb78c0pLv3A6hSRJkiTFmYWDmpXYdIpEsrKOi3cUSZIkSWrRLBzUbMSmU4ynY8eDSUnJinccSZIkSWrRLBzUbCxb9hErVnxHdvbQeEeRJEmSpBbPwkHNRiQyniBIITPzmHhHkSRJkqQWz8JBzUIYVhOJPElGxuEkJ3eIdxxJkiRJavEsHNQsLFkyjYqKhU6nkCRJkqRGwsJBzUIkMo6EhDQyMo6MdxRJkiRJEhYOagai0Ury8p4hM/NoEhPT4h1HkiRJkoSFg5qBoqLXqKoqdDqFJEmSJDUiFg5q8iKRcSQldaBTp8PiHUWSJEmStJKFg5q06uoy8vOfJzPztyQkpMY7jiRJkiRpJQsHNWmFhS9RXb2M7OyT4h1FkiRJkrQaCwc1aZHIeJKTs+nQ4YB4R5EkSZIkrSYp3gGkzVVVtZSCgkl06XI2CQmN4K9yNApVVbGv6uqfX6/+c3X1uteF4frvVxfH6/MekiRJkrbcdttBUiP4PFMPmudvpeYrGoWPP4Z33iG/zbtEt1tB54nLoPDq9X/A39iH/7o+V5IkSZJqq6AAOnWKd4p6YeGgxm/RIpgyBV5+GV59FfLzAYjcAqmLod3V/4bEZEhMjDWDP33V5ufkZGjdevOurc25CQkQBOv+jus7VlfH6/MekiRJkrZMenq8E9QbCwc1PhUV8N57sYLhlVfgs89ixzt3hsMPh8MOo3L/PSj6dld6dL+UoOqO+OaVJEmSJK3DwkGNw7x5PxcMU6dCSUlsRMA++8Ctt8JvfgO77hobIQDk5T5IGFaR3dndKSRJkiSpMbJwUHwsXw5vvvlzyfDNN7HjW20Fp54Khx0GBx4I7dqt9/JIZBytW29LevoeDZdZkiRJklRjFg5qGGEIs2bFyoWXX4Zp02JTJ9q0gQMOgIsuio1i2GabTa4XUF6ey5Ilb9K793UEri0gSZIkSY2ShYPqT2EhvPbaz6MYcnNjx3feGS6+ODaK4de/hlatanXb3Nz7AOjc+ZS6TixJkiRJqiMWDqo71dXwv//9XDB89FFsG8uOHeGQQ2IFw6GHQo8eW/CIMhYs+AcZGUfRpk2/OgwvSZIkSapLFg7aMrm5P0+TePVVKCqKTYnYay+47rrYNIlf/CK2NWQdWLz431RVFdCz5/A6uZ8kSZIkqX5YOKh2ysvhnXd+HsXw+eex4127wjHHxEYxHHwwZGTU+aPDMEpOzt9JT+9P+/b71fn9JUmSJEl1x8JBGxeG8O23P49ieOMNKC2FlJTY+gt/+1usZNhll00u9rilCgsnU1r6JTvs8B8Xi5QkSZKkRs7CQetatixWLPw0imHevNjxbbaBs86KFQwHHADp6Q0aa/78kaSkdCcr6/gGfa4kSZIkqfYsHBQbxTBjxs8Fw7vvQmUlpKXBwIEwYkSsZNh667hFXLbsM5YsmUrfvreTkJActxwbUlFdQUlFyRpfyyuWr3NsRdUKQkIAwjDc6OswXPlzA73eVK768FMGSZIkqaUaedhI0lLS4h2jXlg4tHS33QajR8OiRbGfd9sNhg+PFQz77BObOtEI5OT8nYSENLp2/f0W3ac6Ws3yyuUbLQVKKkrWOGdjx366R2W0so5+0/ULCFZNI6nP1wErf97A63r53ZweI0mSpBbstoNvIw0LBzU3334L11wD++8fKx4OPTS2+GMjU16eSyQyjm7dhpGc3JHyqnJe/PpF8kvza1UKlFSUUFZVVuPnJgQJpKekr/GVlpxGVpsstuqw1XrfW/tYeko6aSk/H2+V1KrWZYAkSZIkNUUWDi3ZPfdAUhI88USjLBp+smDBPYRhFd27X8yEORO44rUrmFc0b41z2iS3WedDf9uUtnRN71rjMmDt8qBVUis/9EuSJEnSZrJwaKmWLYOHH4YTTmjUZUN19XJyc+8jKf0ABj11Nm//8DY7Ze3EpJMmsWfXPUlPSadNchsSExLjHVWSJEmStBoLh5bq0Udh6VK4+OJ4J9moL78fQ1VVIRdNe4PFVVnce8S9nLPnOSQl+FdXkiRJkhozP7W1RNEo3H03/PKXsNde8U6zXssrlnPne39jm7IbKakKOHzny7lm32tp36p9vKNJkiRJkmrAwqElmjIFvv46tnZDIxMNozw+83Guef0aeqUsYP+dIaPXKM7re0m8o0mSJEmSasHCoSUaPTq2bsOxx8Y7yRqm/TCN4VOGMz13OgO6DeDWXbJJCfPZqc8F8Y4mSZIkSaqlhHgHUAP76it4+WU4/3xISYl3GgDmFc3juKeOY79H9mPhsoU8dsxjvHbivYQrPqVHj0tISEiOd0RJkiRJUi05wqGlGTs2VjSce268k1C8opibp93M6A9Hk5SQxF8O+AuX/9/ltEluw5w5p5CYmE7XrufEO6YkSZIkaTNYOLQkxcXwyCMwdCh07hy3GFXRKh78+EH+/OafyS/N5/TdTufmgTfTvV13AFasyCEv70m6d/8DSUkuEilJkiRJTZGFQ0vyyCNQUhLXrTBf+fYVRkwZwey82ezXez9GHjqS/t36r3HOggVjCcMo3bs37i07ayIMIT8fcnJiX4WFsU1Cqqtj39f+akzHVz8Whhv/HTf1ZxCPa5uq5vp7SZIkaf1eeQXaN9N/Z7VwaCmqq2NbYe6zD/Tvv+nz69icvDlcPuVyJn87mb4d+zLhhAkM2X4IQRCscV5VVQkLF95PVtZvad16qwbPWRvV1bBo0c9lwoIFP79e/VhFRd09MwggIWHNr8TEdY/V5fGf3ttUrs19vz6vbaqa6+8lSZKkdSU045UVLRxaismTYe5cuOWWBn1sfmk+179xPfd/fD/pKencecid/GGvP5CalLre8xcteoSqqiX06DG8QXOurbwccnM3XiYsWhQrHVaXmgrdu0OPHrD33rHvP/3cowdkZq75wX59H/I39sHfD6KSJEmSmgoLh5ZizJjYJ98hQxrkceVV5dz90d3c9PZNlFSUMGzAMK7f/3qy0rI2eE0YVpOTM4p27X5F+/Z711u2kpJ1C4S1f87LW/e69HTo2TP2x3jIIT+XCKsXChkZlgKSJEmSBBYOLcOcOfDqq3DzzZBcv1tMhmHIc18+xxWvXsHcorkM2mYQdx56Jztm7bjJa/PzX2TFirn07XvrZj4bioo2XSYUF697bUbGz6XBL37x8+vVC4V27TYrliRJkiS1SBYOLcHdd8fG+tfzVpgf537M8CnDefuHt9kpaydePvllDtvmsBpfn5MzktTU3mRmbnwURkUFPP44fPPNumVCWdma5wYBdOkSKwy23RYOPHDdMqF7d2jdenN+Y0mSJEnShlg4NHdFRfDYY3DyybEFBOpB7rJcrnn9Gh6b8RgZbTK494h7OWfPc0hKqPlfr6VL/0dx8TS23nokCRu5Li8Pjj0Wpk2LDdbo1i1WHOy5Jxx99JrTG3r0iJUN9TyoQ5IkSZK0HhYOzd3DD0NpKVx0UZ3furSylDvfu5Pb372dqmgVl//f5Vy777W0b1X7PV1ycv5OYmI7unY9e4PnfP45HHUULF4MTzwBJ57YvFd0lSRJkqSmzMKhOauuhrFjYb/9YPfd6+y20TDKf2b+h6tfv5oFyxZw3I7HcfvBt9O3Y9/Nut+KFfOJRJ6iR49LSUpa/0IJEyfCKafE1lGYNg0GDNiS30CSJEmSVN8sHJqzSZPg++/hzjvr7Jbv/PgOl71yGdNzpzOg2wDGHTuOfXvvu0X3XLDgbgB69Fh3FEYYwm23wbXXxkqG55+PTaOQJEmSJDVuFg7N2ejR0KsXDB68xbeaVzSPK1+7kmfmPEP3tt157JjHOHnXk0kItmxOQ1XVMnJzHyAr6zhateq9xntlZXDOObHpE7/7Hfzzny7uKEmSJElNhYVDc/X55/DGG3D77ZC0+f+Zi1cUc/O0mxn94WiSEpL4ywF/YcTeI0hLSauTmIsWPUx1dTE9ew5f4/jChXDMMfDRR3DLLXDVVbEdJ1qSMAyprq6msrKSioqKGn2vq3PWPjcaja7KtPr3TR3bnGvq+lh9qM97S5IkqWWZOnUq7dvXfh28psDCobm6++7YcIBzztmsy6uiVfzzk3/y5zf+TF5pHqfvdjo3D7yZ7u2611nEMKwmJ2cU7drtQ7t2e606Pn16rGxYsiQ2haIOBmjETWlpKZ999hkff/wx06dP57vvvqvxh/2Kiop6z5ecnExKSsoa39d3LDExcdU1wcrmJ1itAdrYsZ9e//S1uffZkmP1oT7vLUmSpJYjoRmvhG/h0BwVFMDjj8dWWezUqdaXT5k7heGvDGd23mz27bUvkw+bTP9u/es8Zn7+86xY8T1bb33XqmNPPglnnAGdO8N778Guu9b5Y+tNWVkZM2bMYPr06asKhjlz5qwaHdC5c2e222472rdvv94P9Rv6Xptza3NNUlKSH5olSZIk1RsLh+booYdiCyDUcivML/K+YMSUEUz+djJ9O/ZlwgkTGLL9kHr7UDp//khatdqKzMzBRKNwww1w443w61/Ds89CVla9PLZOrFixgpkzZzJ9+vRVBcPs2bOprq4GICsriwEDBjBkyBD69+/PgAED6Natmx/wJUmSJLUYDVI4BEHwMHAkEAnDcOeGeGaLVVUV2wpz4EDYZZcaXZJfms8Nb97AfdPvIy0ljTsOuYOL9rqI1KTUeotZXPwBS5e+xzbbjKa0NJHTTouVDGefDf/4B6Sk1Nuja628vJyZM2euGrXw8ccfM2vWLKqqqgDIzMxkwIABHHXUUQwYMID+/fvTo0cPywVJkiRJLVpDjXB4BBgLPNZAz2u5Jk6E+fNjazjUwEOfPMSIKSMoqSjhvP7nccMBN5CVVv9DC3Jy/k5iYnsqK89kn31ia1yOGgUXXxzfxSHLy8uZNWvWGtMiZs2aRWVlJQAZGRn079+fK664YtXIhZ49e1ouSJIkSdJaGqRwCMPw7SAI+jTEs1q8MWOgTx848shNnvr54s85d9K57NtrX/5xxD/YMWvH+s8HlJV9T17eMyQkjOBXv2pLeTm89BIcdliDPH6ViooKZs2atcbIhZkzZ64qFzp27MiAAQMYMWLEqpELvXv3tlyQJEmSpBpwDYfm5LPP4O234c47YbVdBdYnDEMuefkSOrTqwLMnPkun1rVfXHJzLVhwN2EY8LvfXUS7dvDii7D99vX7zMrKSmbPnr3GyIWZM2eu2gmiQ4cO9O/fn+HDh68audCnTx/LBUmSJEnaTI2qcAiC4FzgXIBevXrFOU0TNGYMtGkTWwhhE57/8nne+P4Nxg4a26BlQ3n5Ur777kHefvsEtt++J089tVkbaWxUZWUlc+bMWWPkwowZMygvLwegffv29O/fn0suuWTVyIW+fftaLkiSJElSHWpUhUMYhg8ADwAMGDAgjHOcpiUvD554As46Czp02OipK6pWMGLKCHbK2onzBpzXQAGhuBjuuushBg5cBgxn8mRITt6ye1ZVVfHFF1+sMXJhxowZrFixAoB27dqx5557ctFFF60audC3b99mvdetJEmSJDUGjapw0BZ48EEoL4c//GGTp/79/b/z3ZLveO3U10hKaJi/At9+C8ccU8Wf/jSa0tL9uPHGAZt9ryVLlnDTTTfx3nvv8dlnn1FWVgZAeno6/fv354ILLlg1cmGbbbaxXFiPaGWU6uXVVJdUE13+8+vVv0eXR1e9DitDwjCEkFVfG/s5jNb83FU/R2tx7uo/r/astd+rqTCsZb9Zm9OtTiVJkrQROz2zE0ntmudH84baFnMccACQGQRBDnB9GIYPNcSzW4TKythekoccAjtufOHH3GW53DztZoZsP4SD+h7UIPGmToXjj4e9936OLl1+YOedR2/2vfLz8zn00EP5/PPP2XvvvRk2bNiqkQv9+vVrVuVCGIZEy37+0L9GQbDWsdqUB9XLqwkravcpOEgOIAACYlNPVr5e788JtTh3tZ9Xv67G1ybU4Nwa/5K1+iOp3RQcZ+tIkiSpBWqoXSpOaojntFjPPQcLFsB9923y1Kteu4rKaCV3HnpnAwSDe++Fiy6C7bYLueaau0hM3IaMjE3voLE+Cxcu5JBDDmHu3Lm88MILDBo0qI7T1p/q5dUUTimk5LOSdQuCDZUHpdFa/et4kByQmJ5IYloiiemJJKQlkJiWSErnlFXHEtNWHv/pvNWOr37NGsdaJ7i+hSRJkqRaa57jNlqa0aNh663h8MM3etoHOR/w75n/5upfX03fjn3rNVJlJVx6aWzgxZFHwv33v8/XX39Iv35jCYKN76CxPj/++CMHHXQQCxcu5KWXXuLAAw+sh9R1q2JxBfkv5lMwsYCi14qIrogC/Pyhfq0P9snZyescW6cgWKsoWP29hOTmM7pDkiRJUtNn4dDUTZ8O770Ho0bBRqYTRMMol7x8CV3Tu3L1r6+u10iFhbEpFFOnwhVXwC23wBdfjCQpqSNdupxR6/vNnTuXgQMHUlxczKuvvsree+9d96HrQBiGlH5ZSv7EfApeKGDpB0shhNReqXT9fVcyB2fSfr/2FgOSJEmSWgQLh6bu7rshPR3OOGOjpz0+83E+WvARjx7zKG1T29ZbnC++gKOOgvnz4dFH4bTToKxsHvn5z9Gr1xUkJqbV6n5z5szh4IMPpqKigqlTp7LnnnvWU/LNE1aHFL9fTMHEAvIn5lP2zcoFLPdMp88NfcgcnEnarmlOSZAkSZLU4lg4NGWLF8P48XDuudC+/QZPW1a+jKteu4q9uu/FKbueUm9xJk+GoUOhdWt48034aSBCTs4YgiCB7t03vYPG6j777DMOOeQQkpKSeOutt9hpp53qPvRmqC6tpujVothIhkkFVOZVEiQFdDiwAz0u6UHG0Rm06tkq3jElSZIkKa4sHJqy+++HiopNboV56zu3srBkIc+d+BwJQd0P5w9DGDkyNn1i111h4kTo1Sv2XmXlEhYteojs7KGkpnav8T0//PBDfvOb39C2bVtef/11+vXrV+e5a6MiUkHBiwXkv5BP0atFRMuiJLZLJOPwDDIGZ5AxKIOk9v7vJEmSJEk/8RNSU1VREdsCYtAg2G67DZ42t3Aud71/F6ftdhq/7PHLOo9RXg7DhsEjj8Cxx8amUaStNmti4cJ/Ul1dQo8el9X4nm+99RZHHnkknTt35vXXX6d37951nrsmSr+KrceQPzGfpe+vXI+hZypdz+5KxuAMOuzXgYQU12OQJEmSpPWxcGiqnnkGFi2Ciy/e6GmXv3o5yQnJ3HrQrXUeYfFi+O1vY2tWXn89/PnPa65bGY1WsmDBGDp0OIC2bWu29sIrr7zCkCFD6NOnD6+99hrdunWr89wbElaHLP1w6aqSoeyrlesx7J5O7z/3JnNwJum7p7segyRJkiTVgIVDUzVmDGy7LRx66AZPeW3eazz/5fPcMvAWurWt2w/uM2bA0UdDXh489VRsV4q15eVNoLx8Pv363VOje06cOJETTjiBHXfckSlTppCVlVWnmdenumyt9RgisfUY2u/fnu4Xdifz6Exa9XY9BkmSJEmqLQuHpujDD2Nfd9+9wa0wq6JVXPrypWzVYSsurR1KcwAAIABJREFU27vm0xlq4rnn4JRToGNHeOcdWN/GEWEYkpNzF61bb0tGxhGbvOe4ceM49dRTGTBgAJMnT6Zjx451mnl1FXkVFEyK7SpRNGXlegxtE+l0eCcyB2fSaVAnkjsk19vzJUmSJKklsHBoisaMgXbt4PTTN3jK/dPvZ3bebJ494VlaJdXNv9CHIdx8M1x3Hfzyl7HioWvX9Z9bXPwuy5ZNp1+/ewk2sVDlww8/zDnnnMO+++7LpEmTaNu27rftLP0mth5DwcQCit8rhiik9kily5ldyBycSYcDXI9BkiRJkuqShUNTk5sbm8Pwhz/ABj6YF5QWcN0b1zFwq4Ecs/0xdfLY0lI4++zYLpynnAIPPgitNtJj5OSMJCmpE126nLbR+44dO5aLLrqIQw89lOeee442bdrUSd4w+vN6DAUvFFD6RSkAabul0fvalesx7Ol6DJIkSZJUXywcmpr774fqarjwwg2ecsObN1BcXsyow0bVyQfqBQtg8GD45BO47bbY9pcbu21Z2Vzy85+nV69rSEzccIHwt7/9jSuvvJLBgwfz5JNPkpqaukU5q8uqKXq9iIKJBeS/mE/l4kpIhA77d6DbsG5kHJ1B6z6tt+gZkiRJkqSasXBoSsrL4b774IgjYJtt1nvKrMgs7p1+L+cPOJ9dOu+yxY/86CM45hhYtgwmToSjjtr0NTk5owiCJLp3X38pEoYhN9xwA3/9618ZOnQojz32GMnJm7dmQkV+BYX/LSR/Yj6FrxQSLY2SmJ5Ip0Er12M4vBPJHV2PQZIkSZIamoVDU/LUUxCJbHArzDAMueTlS2iX2o6/HPCXLX7cE0/AWWfF1mmYMgV23nnT11RWFrFw4cNkZ/+O1NR1F3gIw5A//vGP3HXXXZx11lk88MADJCYm1ipXtCJK7n255E3Io/id2HoMKd1S6HJaFzIGZ9DxwI4kpLoegyRJkiTFk4VDUxGGMHo07LADHHzwek+Z+NVEpn43lbsH3U1Gm4zNflQ0Cn/6E9x6K+y3H0yYAJmZNbt24cIHiEZL6dlz3Z0xotEoF154Iffddx8XXXQRo0aNImEDu2xsSHVpNbOPm03h5ELSdkmj9zW9yRicQdv+bV2PQZIkSZIaEQuHpuL99+Hjj+Hee9e7gMKKqhWMmDKCnbJ2YtiAYZv9mGXL4NRTY9MnzjkH7rkHUlJqdm00WkFOzhg6dDiI9PTd1nivqqqKs88+m8cee4wrr7ySW2+9tdYFQWVRJZ8f+TlLP1jKtg9sS7ffd6vV9ZIkSZKkhmPh0FSMGQPt28fagPUY9cEo5hXN49VTXyUpYfP+s37/PRx9NMyeHRtMcdFFG18ccm15eU9TUZHLdts9uMbxiooKTjnlFJ5++mluvPFGrr322lqXDeULy5l52ExKvyplxyd3JPu47FpdL0mSJElqWBYOTUFODjzzDFx6KaSlrfN27rJcbnr7JgZvN5iD+65/usWmTJsGv/0tVFbC5Mlw6KG1uz4MQ+bPH0mbNtvTqdNvVh1fsWIFxx9/PJMmTeKuu+5i+PDhtc5WNq+MGYfMoGJxBbv8dxc6Hdyp1veQJEmSJDUsV9ZrCu69N7aGwwa2wrz69aupjFZy56F3btbtH3oIDjoIOnWCDz+sfdkAUFz8NiUln9Cjx2UEQeyv1fLlyznqqKOYNGkS995772aVDSWfl/DpPp9StaSK3V/f3bJBkiRJkpoIC4fGrqwM7r8/Ntdhq63WefvDnA95bMZjXPary9im0/q3ytyQMIQrroit1XDggfDBB7DddpsXc/78kSQnZ9K5c2zKR3FxMYcddhhTp07l0UcfZdiw2q8rUfxeMZ/t9xkkwB5v70G7X7bbvHCSJEmSpAZn4dDYjR8PBQXr3QozGka55OVL6JLehWv3vbbWt779drjjDhg2DP77X+jYcfMilpZ+TUHBi3TrdgGJia0pLCzk4IMP5sMPP2T8+PGcdtpptb5nwcsFzDh4BslZyezx7h6k7bTuVBJJkiRJUuPlGg6NWRjGFovceWc44IB13v7PzP/w4YIPeWTwI7RNbVurWz/xBFx9NQwdGtuJopa7U64hJ2c0QZBM9+4XsHjxYg455BC+/vprnnvuOY488sha3y/yZIQvTv2CtJ3S2PXlXUnpXMNtMiRJkiRJjYaFQ2P2zjvw2WfwwAPrbBdRUlHCla9dyS+6/YJTd1v/zhUb8sYbcMYZsP/+8MgjW1Y2VFYWsmjRv+jc+RQikUoOPvhg5s+fz6RJkzj44NovYLng3gV8c+E3tP91e3Z5cReS2vtXVJIkSZKaIj/NNWajR8dWcjz55HXeunXarSwsWciEEyaQENS8MZg9G4YMgX794LnnIDV1yyLm5t5PNFpGEBzPfvvtR35+Pq+88gq//vWva3WfMAz54eYf+P6678k4MoMdn9qRxNaJWxZOkiRJkhQ3Fg6N1Y8/xhqBP/4R2rRZ4615RfO46/27OGXXU9i75941vmVuLgwaBK1bw0svbf6aDT+JRitYsOBuUlL24aCDzqGsrIypU6cyYMCAWt0njIbMHTGXnFE5dD6lM9s9vB0JyS4vIkmSJElNmYVDY/WPf8S+X3DBOm9dPuVyEhMSue2g22p8u2XL4IgjoLAQpk2D3r23PGIkMp6KioXccksplZWpvPnmm+yyyy61uke0KspX53zF4kcX0/2S7mwzchuChGDTF0qSJEmSGjULh8aotBQefDA296FXrzXeen3e6zz35XPcdOBNdG/XvUa3q6yE446Dzz+HSZNgjz22PGIYhnz99U38+GMCc+ak8fbbU9mulntqVpdVM2foHApeKKDPX/vQ+0+9CQLLBkmSJElqDiwcGqP//Cc2FGGtrTCrolVc+sql9OnQhxH/N6JGtwpDOO88mDIF/vlP+M1v6ibitGljiEa/4fXXM5k27R222mqrWl1fVVzF54M/p/jtYvqN7Uf3C2tWnkiSJEmSmgYLh8bmp60wd9sN9t13jbce+PgBZkVmMeGECbRKalWj2914I/zrX3DddXD22XUT8bXXXuOTT4az/faJ3Hjj+/TqVbuyoSJSwczfzGT558vZ4T870PmkznUTTJIkSZLUaLgyX2Pz5pswaxZccskaW2EWlhVy3RvXcWCfAxmy/ZAa3eqRR+D66+H00+Evf6mbeJMmTWLYsMPZa68offteRq9e29Tq+hU/rODTfT+l9MtSdp64s2WDJEmSJDVTFg6NzZgxkJkJJ520xuEb3ryBJSuWMOo3o2q0zsGUKfD738PBB8MDD6zRXWy2p59+miFDhnDOOR0IglS23faPtbp++RfL+fTXn1KxuIJdp+xKxuEZWx5KkiRJktQoWTg0Jt99By+8AOeeC61+njIxKzKLf/zvH5zX/zx27bzrJm8zY0Zskcgdd4QJEyAlZcujPfroowwdOpSBA/uz997L6NLlVFJSsmt8/dL/LeXTfT8lWhllj7f3oMOvO2x5KEmSJElSo2Xh0Jjcc09sKML55686FIYhl758KW1T2/LXA/+6yVvMnw+HHw7t2sF//xv7vqXuu+8+zjjjDAYOHMjYsYcShivo0eOyGl9f9HoRMwbOIKldEnu+uyfpu6ZveShJkiRJUqNm4dBYlJTEtpE47jjo0WPV4Re+eoHXv3udvxzwFzLbZG70FkuWwKBBsVtNnrzGbTbbyJEjOf/88znyyCOZOPEZIpEH6NRpEGlpO9bo+rxn85h5+Exa9WnFHu/sQeutW295KEmSJElSo2fh0Fg8/jgUF6+xFWZ5VTnDpwxnx6wdOX/A+Ru5GCoq4Le/ha+/hmefhV122bI4YRhy4403MmLECI4//nieffZZioufo7JyMT16DK/RPRY+tJDZx8+mbf+27P7W7qR2S92yUJIkSZKkJsNtMRuDn7bC7N8f9t571eFRH4xiXtE8ppwyheTE5I1efvbZ8MYb8NhjcNBBWxon5Oqrr+b222/n9NNP55///CeJiYnk5IwkLW0XOnbc9AN+vONH5l0xj46HdWTnCTuTmJa4ZaEkSZIkSU2KhUNj8Prr8MUX8Oijq7aTWLhsITdNu4mjtzuaQ7Y+ZKOX/+lPsQESN90Ep566ZVGi0SiXXHIJY8eO5fzzz2fs2LEkJCRQWPgay5d/znbb/Wuju2SEYci8q+cx//b5ZJ2YxQ6P7UBCigNpJEmSJKmlsXBoDEaPhuxsOPHEVYeumXoN5VXl3HXoXRu99IEH4JZb4Jxz4JprtixGdXU15557Lg8//DAjRozgjjvuWFUu5OTcRXJyZzp3PmmD14fVIV8P+5qF/1xIt2Hd6De2H0FiHezHKUmSJElqcvyn53j79tvYdhLDhkFqbI2DjxZ8xCOfPcJlv7qMbTpts8FLX3oJLrggtlDkvfeuGhyxWSorKznllFN4+OGHuf7669coG5Yvn01h4ct07/4HEhLWvw5DtDzK7BNns/CfC+l1bS/6/cOyQZIkSZJaMkc4xNs990BiYqxwAKJhlIsnX0zntM5cu9+1G7zs44/hhBNgt93gqacgaQv+S5aXl3PiiScyceJEbr/9dq644oo13s/JGUVCQiu6dRu23uurSqqYPWQ2Ra8VsfXIrel5Wc/NDyNJkiRJahYsHOJp2TJ4+OFYc9C1KwBPfP4EHy74kIePfph2qe3We9l338ERR0BmZmxwRHr65kcoLS1lyJAhTJkyhbFjx3LhhReu8X5FRYRFi/5Nly5nkJKy7raclQWVzDx8Jss+Xsb2j2xPl9O7bH4YSZIkSVKzYeEQT48+CkuXrtoKs6SihCtfu5IB3QZw+u6nr/eSwsLYFIqKitiuFF224PP9N998w2mnncZHH33Eww8/zJlnnrnOObm59xKG5fTocek675UvKGfGoTMom1vGzhN2JnPwuoWEJEmSJKllsnCIl2gU7r4b9toLfvlLAG575zZyl+XyzPHPkBCsu7zGihUweHBshMOrr8IOO2zeo6urqxkzZgzXXnstqampPPXUUxx77LHrOW8FCxbcQ6dOR5CWtv0a75V+XcqMQ2dQVVjFri/vSscDOm5eGEmSJElSs2ThEC9TpsDXX8N//gPAd0Xfced7d3LyLiezd8+91zk9GoXTT4d33oFx42C//TbvsV999RVnnXUW7733HkcddRT33Xcf3bp1W++5kch/qKzMo2fP4WscX/bpMmYeNhNC2P2N3Wnbv+3mhZEkSZIkNVvuUhEvY8bE5kMcdxwAl796OYkJidx28G3rPf3KK2OLQ/7tbzB0aO0fV11dzR133MHuu+/Ol19+yeOPP87EiRM3WDaEYcj8+SNJT9+dDh0OXHV8ydtL+OyAz0holcAe7+xh2SBJkiRJWi8Lh3j4+muYPBnOPx9SUpj63VSe/eJZrv711fRo12Od08eOhTvvhAsvhMsvr/3j5syZwz777MMVV1zBoEGDmD17NieffPKqbS/Xp6hoCqWlc+jRY/iq8/JfzGfmYTNJ7ZbKHu/uQZvt2tQ+jCRJkiSpRbBwiIe774bkZDjvPKqiVVz68qX0bt+bEXuPWOfU55+PrSk5eDCMHg0b6QjWUVVVxa233soee+zBt99+y/jx45kwYQJdarDS5Pz5I0lJ6Up29okALPr3ImYNmUXazmnsPm13WvVsVfMgkiRJkqQWxzUcGlpxMTzySGxeROfOPPi/e/k88jlPH/80rZNbr3HqBx/ASSfF1pV84glITKz5Y2bNmsWZZ57J9OnTOf744xk7dizZ2dk1urakZBZFRVPYaqtbSEhIIWd0Dt9e+i0dBnZg5+d3Jqmtf20kSZIkSRvnCIeG9sgjUFICl1xCYVkh171xHQf0OYBjd1hzl4hvv4WjjoLu3eHFF6FNDWcvVFZWcuONN7Lnnnvyww8/8PTTT/PUU0/VuGwAyMn5OwkJbeja9Vy+u/47vr30WzKHZLLLf3exbJAkSZIk1YifHhvST1th/t//Qf/+/GXyJRStKGLUYaPWWE8hLw8GDYIwjC31kJVVs9vPmDGDM888k08//ZShQ4dy9913k5mZWauI5eWLWLz4cbp2OZvvhxeQe08uXc7qwrb3b0tCkv2UJEmSJKlm/ATZkF56CebOhYsvZk7eHO753z2cu+e57NZlt1WnlJbC0UdDTk5sZEO/fpu+bUVFBTfccAMDBgwgNzeX5557jnHjxtW6bADIzf0HYVjJilFHkntPLj0v78l2/9zOskGSJEmSVCuOcGhIY8ZAt26EQ4Zw6ZNH0ja1LX898K+r3q6uhpNPhg8/hAkTYO+9N33LTz75hDPPPJOZM2dyyimnMHr0aDp16rRZ8aqry1iw4B8kf7M/hfe1oe9tfel1Za/NupckSZIkqWXzn60bypw58OqrcMEFvPjdy7w671Vu2P8GstJi8yXCEC67LLYrxahRMGTIxm9XXl7On/70J/baay/y8/N58cUX+fe//73ZZQNA7nePUFVVQOU9g9n2/m0tGyRJkiRJm80RDg1l7FhITaX87NMZ/tQBbJ+5PRf84oJVb//977HlHYYPj22DuTH/+9//OPPMM5k9ezZnnHEGI0eOpGPHjlsUb0VuGfOm/w2WbcsOfzqJzsd13qL7SZIkSZJaNkc4NIQlS+DRR+F3v2P03CeYWzSXUYeNIjkxGYCnn4YRI+C44+COOzZ8mxUrVnDVVVfxq1/9iuLiYl566SX+9a9/bXHZUDavjI8vuJewy/f03Gq4ZYMkSZIkaYs5wqEhPPQQlJay6PcnceObv+WobY/isG0OA+Cdd+DUU2GffeDf/4aEDVRA77//PmeddRZffvkl55xzDnfeeSft27ff4mglM0qYOWgmVVc+QTLd2GrgWVt8T0mSJEmSHOFQ36qrY9Mp9t2XayLjKK8q565D7wLgyy9jO1L06QMTJ0KrVuteXlZWxuWXX84+++xDaWkpr7zyCg8++OAWlQ3li8rJGZvDp/t+yvTdpxPt/Q3hbh/Ts+8lJCQkb/Z9JUmSJEn6iSMc6tukSfD99/zvr8P412dX8cf/+yP9MvqxeDEMGgTJyTB5MmRkrHvpu+++y1lnncXXX3/NsGHDuP3222nXrt1mxajIryB/Qj6RJyMseWsJRCFt5zT63NiH5Yc/REFJGl27/n4Lf1lJkiRJkmIsHOrbmDGEPXtwcflzZKdl86f9/sTy5XDkkRCJwFtvwVZbrXnJ8uXLufbaaxkzZgy9e/fm9ddfZ+DAgbV+dGVRJfnPxUqGoteLoBpab9ua3tf2JvvEbNJ2SqO8fCEffPAk3boNIzl5y9aCkCRJkiTpJxYO9enzz2HqVJ64+UQ+WPAkDx39EG0S23HMsfDJJ7FpFAMGrHnJW2+9xdlnn83cuXP5wx/+wK233kp6enqNH1m1tIr8F/LJezKPwlcKCStDWm3Vil5/7EXWiVmk75ZOEAQARKMV/Pjj7YRhFT16XFKXv7kkSZIkqYWzcKhPd99NSdtUrkh5i/6Z/Tl9tzO48AL473/h3ntjoxx+UlJSwlVXXcU999zD1ltvzZtvvsn+++9fo8dUL6+mYFIBkScjFLxUQFgektozle4Xdyf7xGzaDmhLEAREo1UsW/YRRUVvsGTJGxQXv0M0WkpW1gm0br11Pf0hSJIkSZJaIguH+lJQAI8/zu3n70Du8s946oRn+NvtCdx/P1x1FQwb9vOpU6dO5eyzz+aHH37g0ksv5aabbiItLW2jt68uq6ZwcmGsZJhUQLQ0SkrXFLqd143sE7Np96t2EEQpKZlBTs4bFBW9QXHx21RXLwOgTZud6Nr1bDp0OJBOnQbV55+EJEmSJKkFsnCoLw89xPepZdzRYQ6/2+l3fD9tH665Bn73O7j55tgpS5cu5YorruD++++nX79+TJs2jX322ef/27v3IL3q8oDj32c39xCyC1kQiAlUQOUyBRtDWgQTKhadDqAzYCgqoibQgY60BSnGSwZrxRuVotWqpKUjElCMpBVrUC4qFYyEDJDgJdwkJLILuZAAuWzy9I/3xL6E3WQXTt6z++73M7Oz5/z2vOc87z7zO+c9z/s75/S6yu2bt7NmUVFkuPkZtm3cxvCO4bzqnFfVigzH783zm5azbt21PLH8dtatu5Pu7rUAjB59OPvvfzZtbTNoa5vOiBH7NeK/IEmSJEkaoiw47And3fDlL3PJ2R20tj7HaSO+yLtnwvTpMG8etLTAokWLmDVrFitXruTiiy/m8ssvZ/To0S9Z1fat21n747V03dBF14Iutq3fxrD2YXS8q4OOmR2MnNrJ+g238eS621h2zx1s3doFwKhRhzBhwjtobz+JtrbpjBx5UIP/CZIkSZKkocyCw55w883c3vI7vtMBFxzwFWa/u4PDD4cFC2DTpvVccMHfc8011/C6172Ou+66i2nTpr3o5bktWXfHOjpv6KTru110P9NN696t7Hv6vrTPfIHtRy1h/YY7+fW629iyZDUAI0dOZJ99TilGMMxg9OiDK3jjkiRJkiTVWHDYA7qvvoqLTh3OgfnH3PyJ2YwZA7fcAj//+Q+YPXs2q1at4tJLL2Xu3LmMGjUKgNyerL9rPZ3zO+n6ThdbO7fSMraF9rO2Muodv6J78mLWPXsHnZsfh4dh+PD9aW+fUVdgOPQPT5+QJEmSJKlqFhzKtnQp33jup9w/ZhyT59/KM2tb+P731/Lxj/8t1157LUcccQQ33XQTU6dOJTNZf/d6um7oovPbnWx5cgtxwFr2+sAKxp54P5vG380zm1cAMGztPrS1zWDSpEtoa5vBmDGvt8AgSZIkSRqwLDiUbO2XPs+cNw+jfeGtrFwxno997L+YOfM8Ojs7mTNnDh/96EfZumwrD3/4YTpv7GTz2k6YspSRlzzEiCOWsGX4b9kAtLaOp22vEzlo4gW0t89g7NijiWip+u1JkiRJktQnDSs4RMQpwFVAK/CNzLyiUdtumKefZu7q+ay59+uw/FCmTXsPc+dex9FHHc33rvweEx6YwNKpP2PTuHvgT+6j9bMPwH6/AWBry1ja2k6grW0WbW0zGDfuWCJaK35DkiRJkiS9PA0pOETtzPnLwMnASmBxRCzMzOWN2H6jLP+3f+Tq5+bA0jbGjj2SzsVj+Y+T/5XDxm3i+Tuu5HfH3gdfXAEt22mJUYwbfzzt7e+lre0kxo2bQkvL8KrfgiRJkiRJpWjUCIepwIrMfAQgIuYDpwFNU3DILVt45/fXMHnJBs54w8844Y3TGHfUCnj9hWxp3Q45nL3HTqO94yza22ew997TaGkZWXXYkiRJkiTtEY0qOBwEPFE3vxI4rkHbbogv/fV7ufJd9zFm7qMwYitsa2XUpmPYt+Ni9p14MuPH/xmtrWOqDlOSJEmSpIZoVMGhp8cp5EsWipgNzAaYNGnSno6pVNtzIzFqCzxyJq+dfgYdh57EsGHjqg5LkiRJkqRKNKrgsBJ4dd38RGDVzgtl5teArwFMmTLlJQWJgezCr9/Mxg0vML5tr6pDkSRJkiSpco16zuJi4LCIOCQiRgAzgYUN2nZDtLa2WmyQJEmSJKnQkBEOmdkdERcCP6T2WMx5mbmsEduWJEmSJEmN16hLKsjMW4BbGrU9SZIkSZJUnUZdUiFJkiRJkoYQCw6SJEmSJKl0FhwkSZIkSVLpLDhIkiRJkqTSWXCQJEmSJEmls+AgSZIkSZJKZ8FBkiRJkiSVzoKDJEmSJEkqnQUHSZIkSZJUOgsOkiRJkiSpdBYcJEmSJElS6Sw4SJIkSZKk0llwkCRJkiRJpbPgIEmSJEmSSmfBQZIkSZIklc6CgyRJkiRJKp0FB0mSJEmSVDoLDpIkSZIkqXQWHCRJkiRJUuksOEiSJEmSpNJFZlYdQ48iogt4vOo4+mkC8HTVQegVM4/Nw1w2B/PYHMxjczCPzcE8Ngfz2BwGax4nZ2bH7hYasAWHwSgifpmZU6qOQ6+MeWwe5rI5mMfmYB6bg3lsDuaxOZjH5tDsefSSCkmSJEmSVDoLDpIkSZIkqXQWHMr1taoDUCnMY/Mwl83BPDYH89gczGNzMI/NwTw2h6bOo/dwkCRJkiRJpXOEgyRJkiRJKp0Fh5JExCkR8euIWBER/1B1POqbiHh1RNweEQ9FxLKI+FDRPjcinoyIpcXP26uOVbsWEY9FxANFvn5ZtO0TEbdGxG+L3+1Vx6neRcRr6/rc0oh4NiIusj8OfBExLyI6I+LBurYe+1/U/EtxvLw/It5QXeSq10sePxcRvypytSAi2or2gyPihbp++dXqItfOesllr/vSiLis6JO/joi/qCZq7ayXPN5Ql8PHImJp0W6fHKB2cb4xJI6TXlJRgohoBX4DnAysBBYDZ2Xm8koD025FxAHAAZm5JCLGAfcCpwNnAhsz8/OVBqg+i4jHgCmZ+XRd22eBNZl5RVEIbM/MS6uKUX1X7FefBI4DzsX+OKBFxInARuA/M/Oooq3H/lec5PwN8HZq+b0qM4+rKnb9v17y+FbgtszsjojPABR5PBj47x3LaWDpJZdz6WFfGhFHANcDU4EDgR8Bh2fmtoYGrZfoKY87/f0LwPrMvNw+OXDt4nzjfQyB46QjHMoxFViRmY9k5hZgPnBaxTGpDzJzdWYuKaY3AA8BB1UblUp0GnBtMX0ttZ27Boc/Bx7OzMerDkS7l5k/Adbs1Nxb/zuN2ofnzMy7gbbiw5gq1lMeM3NRZnYXs3cDExsemPqtlz7Zm9OA+Zm5OTMfBVZQ+2yriu0qjxER1L4gu76hQanfdnG+MSSOkxYcynEQ8ETd/Eo8aR10isrwscA9RdOFxTCmeQ7FHxQSWBQR90bE7KJt/8xcDbWdPbBfZdGpv2by4g9R9sfBp7f+5zFz8Ho/8IO6+UMi4r6IuDMiTqgqKPVLT/tS++TgdALwVGb+tq7NPjnA7XS+MSSOkxYcyhE9tHmtyiASEXsBNwEXZeazwFeA1wDHAKuBL1QYnvrm+Myeo5jzAAAFrklEQVR8A/A24IJiGKIGoYgYAZwKfLtosj82F4+Zg1BEzAG6geuKptXApMw8Fvg74FsRsXdV8alPetuX2icHp7N4cWHePjnA9XC+0euiPbQN2j5pwaEcK4FX181PBFZVFIv6KSKGU+v812XmdwEy86nM3JaZ24Gv49DCAS8zVxW/O4EF1HL21I4haMXvzuoiVD+8DViSmU+B/XEQ663/ecwcZCLiHOAvgbOzuPlXMfz+mWL6XuBh4PDqotTu7GJfap8cZCJiGPBO4IYdbfbJga2n8w2GyHHSgkM5FgOHRcQhxTdzM4GFFcekPiiuf7sGeCgzr6xrr79O6h3Agzu/VgNHRIwtbsJDRIwF3kotZwuBc4rFzgFuriZC9dOLvrWxPw5avfW/hcB7i7twT6N2w7PVVQSo3YuIU4BLgVMz8/m69o7i5q5ExB8BhwGPVBOl+mIX+9KFwMyIGBkRh1DL5S8aHZ/65S3ArzJz5Y4G++TA1dv5BkPkODms6gCaQXHn5guBHwKtwLzMXFZxWOqb44H3AA/seKwQ8BHgrIg4htrwpceA86oJT320P7Cgtj9nGPCtzPyfiFgM3BgRHwB+B5xRYYzqg4gYQ+2JP/V97rP2x4EtIq4HpgMTImIl8AngCnruf7dQu/P2CuB5ak8h0QDQSx4vA0YCtxb72Lsz83zgRODyiOgGtgHnZ2Zfb1KoPayXXE7vaV+amcsi4kZgObXLZi7wCRUDQ095zMxreOl9jsA+OZD1dr4xJI6TPhZTkiRJkiSVzksqJEmSJElS6Sw4SJIkSZKk0llwkCRJkiRJpbPgIEmSJEmSSmfBQZIkSZIklc6CgyRJTSwiPhIR32jAdiZFxMYdz4GXJEnysZiSJA1iEbGxbnYMsJnaM9gBzsvM6xofVf9ExHTgm5k5caf2O4r2PV4wkSRJ5RtWdQCSJOnly8y9dkxHxGPABzPzR9VFNPBFxLDM7K46DkmSmp2XVEiS1MQiYm5EfLOYPjgiMiLOjYgnImJtRJwfEW+MiPsjYl1EfGmn178/Ih4qlv1hREzuZTs71j2smL8jIj4ZEXdFxIaIWBQRE17he5kVESsiYk1ELIyIA3vadt32P1hMv6+I458jYg0wNyIOjYg7I2J9RDwdETe8ktgkSdJLWXCQJGnoOQ44DHgX8EVgDvAW4EjgzIh4M0BEnA58BHgn0AH8FLi+H9v5K+BcYD9gBHDxyw04Ik4CPg2cCRwAPA7M78cqjgMeKWL5FPBJYBHQDkwErn65sUmSpJ5ZcJAkaej5ZGZuysxFwHPA9ZnZmZlPUisqHFssdx7w6cx8qLgE4Z+AY3ob5dCDf8/M32TmC8CNwDG7WPbAYoTFH36AN9X9/WxgXmYuyczNwGXAn0bEwX2MZVVmXp2Z3UU8W4HJwIHF/+JnfVyPJEnqIwsOkiQNPU/VTb/Qw/yO+0JMBq6qKwCsAQI4qI/b+X3d9PN16+3Jqsxsq/8B6osAB1Ib1QBAZm4EnulHLE/sNP9hau/lFxGxLCLe38f1SJKkPvKmkZIkqTdPAJ8aIE+6WEWtAAJARIwF9gWepDZKA2pP6Xi2mH7VTq9/0WO5MvP3wKxiXW8CfhQRP8nMFeWHLknS0OQIB0mS1JuvApdFxJEAETE+Is6oKJZvAedGxDERMZLa5R33ZOZjmdlFrfDw7ohoLUYrvGZXK4uIMyJix2M411IrSGzbxUskSVI/WXCQJEk9yswFwGeA+RHxLPAg8LaKYvkx8DHgJmA1tYLCzLpFZgGXULvM4kjgf3ezyjcC90TERmAh8KHMfLTsuCVJGsoiM3e/lCRJkiRJUj84wkGSJEmSJJXOgoMkSZIkSSqdBQdJkiRJklQ6Cw6SJEmSJKl0FhwkSZIkSVLpLDhIkiRJkqTSWXCQJEmSJEmls+AgSZIkSZJKZ8FBkiRJkiSV7v8APeh6zwahWbwAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 1296x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# VALID (LOWER RIGHT SPACE)\n",
    "# block at 4, 5\n",
    "model_valid_45 = DayModel(macrophage=1.27e8, spore=3.79E9)\n",
    "%time results_valid_45 = model_valid_45.run(solver=BasicODESolver)\n",
    "%time mean_of_model_valid_45 = get_mean(results_valid_45[0])\n",
    "print(mean_of_model_valid_45)\n",
    "res = results_valid_45[0]\n",
    "\n",
    "data = [\n",
    "    res['HLN1'][-1],\n",
    "    res['HLN2'][-1],\n",
    "    res['HLN3'][-1],\n",
    "    res['HLN4'][-1],\n",
    "    res['HLN5'][-1],\n",
    "    res['HLN6'][-1]\n",
    "]\n",
    "x = [1,2,3,4,5,6]\n",
    "\n",
    "mean = get_mean(res)\n",
    "sd = get_std(res)\n",
    "sem = get_sem(res)\n",
    "\n",
    "plt.bar(x,data)\n",
    "plt.xlabel('HLN')\n",
    "plt.ylabel('Count')\n",
    "plt.show()\n",
    "\n",
    "### SPORES AVAILABLE ###\n",
    "\n",
    "fig = plt.figure(figsize=(18,10))\n",
    "fig.suptitle(\"Spores available\", fontsize=20)\n",
    "\n",
    "plt.plot(res['time'], res['S_'], 'g-', label='Spore')\n",
    "\n",
    "plt.xlabel(\"Time in Hours\", fontsize=12)\n",
    "plt.ylabel(\"Number of Cells\", fontsize=12)\n",
    "plt.legend(loc='best', fontsize=12)\n",
    "\n",
    "### HOSTS IN LUNG ###\n",
    "fig = plt.figure(figsize=(18,10))\n",
    "fig.suptitle(\"Anthrax-infected Cells in Lung\", fontsize=20)\n",
    "\n",
    "#plt.plot(results[0]['time'], results[0]['S_'], 'g-', label='Spore')\n",
    "plt.plot(res['time'], res['H1'], 'r-', label='H1')\n",
    "plt.plot(res['time'], res['H2'], 'g-', label='H2')\n",
    "plt.plot(res['time'], res['H3'], 'b-', label='H3')\n",
    "plt.plot(res['time'], res['H4'], 'k-', label='H4')\n",
    "plt.plot(res['time'], res['H5'], 'm-', label='H5')\n",
    "plt.plot(res['time'], res['H6'], 'y-', label='H6')\n",
    "\n",
    "plt.xlabel(\"Time in Hours\", fontsize=12)\n",
    "plt.ylabel(\"Number of Cells\", fontsize=12)\n",
    "plt.legend(loc='best', fontsize=12)\n",
    "\n",
    "### TMLN MIGRATION ###\n",
    "fig = plt.figure(figsize=(18,10))\n",
    "fig.suptitle(\"Migration to TMLN\", fontsize=20)\n",
    "\n",
    "#plt.plot(results[0]['time'], results[0]['S_'], 'b', label='Spores')\n",
    "plt.plot(res['time'], res['HLN1'], 'r-', label='HLN1')\n",
    "plt.plot(res['time'], res['HLN2'], 'g-', label='HLN2')\n",
    "plt.plot(res['time'], res['HLN3'], 'b-', label='HLN3')\n",
    "plt.plot(res['time'], res['HLN4'], 'k-', label='HLN4')\n",
    "plt.plot(res['time'], res['HLN5'], 'm-', label='HLN5')\n",
    "plt.plot(res['time'], res['HLN6'], 'y-', label='HLN6')\n",
    "\n",
    "plt.xlabel(\"Time in Hours\", fontsize=12)\n",
    "plt.ylabel(\"Number of Cells\", fontsize=12)\n",
    "plt.legend(loc='best', fontsize=12)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Wall time: 174 ms\n",
      "Wall time: 0 ns\n",
      "3.4735415841761603\n"
     ]
    },
    {
     "data": {
      "image/png": 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NnJzkBUmeDlwAbJ85IMmGGbPnAnt6zCNJWkBvZx9V1cEklwCfAdYA11fVfUmuBCarajvwliTnAgeB/cBFfeWRJC2st1IAqKrbgdtnLbt8xvRlwGV9ZpAkDc8rmiVJjaUgSWosBUlSYylIkhpLQZLUWAqSpMZSkCQ1loIkqbEUJEmNpSBJaiwFSVJjKUiSGktBktRYCpKkxlKQJDWWgiSpsRQkSY2lIElqei2FJJuTfDPJ3iSXzrH+mCS3dOt3JBnvM48kaX69lUKSNcAHgNcCvwS8PskvzRp2MfC9qnoh8D7gPX3lkSQtrM8thdOAvVX17ar6EXAzcN6sMecB27rp24CzkqTHTJKkeaSq+vng5Hxgc1W9qZt/A/DyqrpkxpivdWOmuvn/0Y357qzP2gJs6WZfBHyzl9BHZj3w3QVHrSyr7Tettt8Dq+83rbbfA0+93/T8qhpbaNDaHgPM9S/+2Q00zBiqaiuwdSlCLbUkk1U1MeocS2m1/abV9ntg9f2m1fZ7YOX+pj53H00Bm2bMbwQePNSYJGuBZwP7e8wkSZpHn6VwN3BykhckeTpwAbB91pjtwIXd9PnAndXX/ixJ0oJ6231UVQeTXAJ8BlgDXF9V9yW5Episqu3AdcCHk+xlsIVwQV95evSU3K21SKvtN6223wOr7zettt8DK/Q39XagWZK08nhFsySpsRQkSY2lcISSXJ9kX3etxYqXZFOSzyXZk+S+JG8ddabFSnJskq8kuaf7Te8adaalkGRNkn9I8olRZ1kKSe5P8tUku5NMjjrPYiU5IcltSb7R/f/0ilFnOhweUzhCSV4FHABuqKoXjzrPYiXZAGyoql1JngnsBP5VVX19xNGOWHd1/DOq6kCSdcCXgLdW1ZdHHG1RkrwdmACeVVXnjDrPYiW5H5iYfdHqSpVkG/DFqrq2O/Pyn1TVI6PONSy3FI5QVX2BVXRNRVU9VFW7uunvA3uAE0ebanFq4EA3u657reh/BSXZCJwNXDvqLHqyJM8CXsXgzEqq6kcrqRDAUtAcurvVngrsGG2Sxet2tewG9gF3VNVK/01XAX8K/GTUQZZQAf89yc7uljYr2S8A08B/63bxXZvkGaMOdTgsBf2MJMcDHwHeVlWPjTrPYlXVj6vqFAZX1J+WZMXu6ktyDrCvqnaOOssSO72qXsrgjspv7nbNrlRrgZcCH6yqU4H/CzzpsQFPZZaCmm6/+0eAG6vqo6POs5S6Tfi7gM0jjrIYpwPndvvgbwbOTPLXo420eFX1YPfnPuBjDO6wvFJNAVMztkhvY1ASK4alIKAdlL0O2FNV7x11nqWQZCzJCd30ccCrgW+MNtWRq6rLqmpjVY0zuPr/zqr6vRHHWpQkz+hObKDbzfIaYMWe0VdV/xt4IMmLukVnASvqZI0+75K6qiW5CTgDWJ9kCriiqq4bbapFOR14A/DVbh88wDur6vYRZlqsDcC27oFPTwNurapVcRrnKvJc4GPdY1TWAn9TVZ8ebaRF+0Pgxu7Mo28DbxxxnsPiKamSpMbdR5KkxlKQJDWWgiSpsRQkSY2lIElqLAVpCEkOzJq/KMnV3fSfJXnHHO+pJH8+Y/4dSf6s97DSIlgKUn8eB34zyfpRB5GGZSlI/TnI4Dm9fzTqINKwvKJZGs5xM670BngOsH2I930AuDfJf+onlrS0LAVpOD/s7rYKDI4pMHjQzbyq6rEkNwBvAX7YXzxpabj7SOrfVcDFwIq6r76OTpaC1LOq2g/cyqAYpKc0S0FaGv8hydQTrznW/zngWUh6yvMuqZKkxi0FSVJjKUiSGktBktRYCpKkxlKQJDWWgiSpsRQkSc3/B7hySe6+MhFBAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1296x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1296x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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9FBk7dizdu3enbHaTk5PDrl27ANi5cyc5OTmkpaXVbMGSJEmSJO2HWnmUI4TwVWB9FEWL99atnLY9RkuEEK4MISwKISz69NNPq63GumbYsGGkp6cXbzfeeOMefTIzMxk3bhybNm0q1Z6enk7Lli0BOPLII0lPT6+NkiVJkiRJqrJQHU9K7PNNQrgJ+BaQD6QBmcDfoyi6tESfp4Aboyh6OYTQBPgEOGhvj3IMHjw4WrRo0R7tK1asoHfv3tX8p2i4/LwkSZIkSdUthLA4iqLB++pXKyMmoij6aRRFh0ZRlA1cDDxfMpQoNBu4rHD/vwr71HxqIkmSJEmSElOry4WWFUL4ObAoiqLZwJ+B+0MI7wGbiAMMSZIkSZLUgNV6MBFF0VxgbuH+pBLtOcBFtV2PJEmSkhFF8bZr1+6toKD8/aLjgoL4mpKvFe1Xtq2mzxf9Ocs7rstbyb+jov3Ktu3PNdV5n4r293W+qvvVfY/y+lXUVpt9Knvdvs7V5Wsq40DH8x/I9aedBnfccWDvX5clOmJCkiSpMSgogPx8yMvbv9cDubaie+zty39Nnit5XFCQ9N9MwxBCzW0l71+0X9m2/bmmOu9T0f6+zld1vzLnq3KP8vpV1FabfSp73b7O1eVrKuNArj2Q67OzD+x96zqDCUmS1CBEUfyFe+dOyMmJX6u6vz/X5ebuOxg40N+y7Y+UFGjSBJo2Lf81NXX3lpJS8XFKCjRvXvG5vV1XE+eKthD2bz+J62o6OJCk+s5gQpIk1Zj8fPj88/K3bdtKH3/xxZ4BQVWDguoIAEKAtLT4y3jz5uXvp6dD27bxfrNmFX/531swUNnX/b0mpVamOJck6cAZTEiSJCD+zf7egoN9BQvlnd+5s/LvX/KLf0XBQOvWew8MKtqvSt8mTfxNtCRJtclgQpKkem77dtiwofRWFBpUJVzIza38e6anQ6tW0LLl7i0zEw45ZPdx2fMlt7LnMjLiQECSJDU+/hNAkqQ6ZOdO2Lhxz6Bhb9uOHXu/Z4sWewYBbdrAoYdWPUAoChFSU2vn85AkSQ2fwUQCsrOzmTJlCmeccUZx29SpU5kyZQrz588v9zzA3LlzOe2007jmmmu4/fbbi9uHDh3KFVdcwahRo5gzZw433XQTy5YtIy0tjfPOO4///d//pVWrVrX255MkxfLzYdOmqoUM27ZVfL82baBDh3jr3BkGDNh9XHJr3z5+5KFlyziUMESQJEl1mcFEPZORkcG0adO49tpryS5nzZgtW7Zw3XXXcfLJJ7Nz504uueQSrr32Wv70pz/VfrGS1IAUFMBnn1UtZNi8ueL7tWxZOkzo1av8kKFoa9cunthQkiSpoTGYqGfatGnDyJEjmTx5Mvfee+8e5y+55JLi/RYtWvDd736XG264oTZLlKR6J4pg/XpYuXLP7aOP4pBh48Y4nChP8+Zw0EG7Q4SuXfceMrRvH0+0KEmSJIOJemnixIn07NmTCRMm0KtXr732nTdvHn369KmlyiSp7tqypfzgYeVKWLUqnkCypI4doVs3OOqo0qFDeVuLFq7iIEmStL8aRTAx5h9jWPLJkhp9j4FZA7nl7Fsq3X/EiBE0KTH9eG5uLoMGDarUtVlZWVx11VVMmjSJ6dOnV9jvmWee4b777uOVV16pdF2SVF/t2BEHDOWFDitX7vlYRWZmHDz07AlnnRXvF23Z2fEEj5IkSap5jSKYqItmzZpV7uSXlTV+/Hh69OjB0qVLyz2/YMECLrnkEh555BF69ux5wPVKUtLy82H16opHPXzySen+zZvHAUO3bnD88aWDh27doG1bRzlIkiTVBY0imKjKSIb6on379owZM4brr79+j3Ovv/46559/Pvfccw9f/vKXE6hOkqouiuJwoaLgYfVq2LVrd//UVOjSJQ4Zhg3bHUIUbVlZkJKS2B9HkiRJldQogon6KC8vj5ycnOLjko99FBk7dizdu3cniqLitmXLlnH22Wdz6623ct5559VKrZJUWZs3732ehxL/2QPicKFbNzjppD1HPBx6qKtUSJIkNQQGE3XUsGHDSh1PnDix1KMfAJmZmYwbN47x48cXt/3hD3/g008/5fLLL+fyyy8HoGvXrixfvrzmi5akEtauhYUL4+2VV+D11+PlNktq02b3BJPnnrvnPA/p6YmULkmSpFoUSv62vb4ZPHhwtGjRoj3aV6xYQe/evROoqH7y85J0oLZuhcWL4wCiKIxYuzY+16QJDBwIxxwDRxxROnxo0ybZuiVJklRzQgiLoygavK9+jpiQJFVJXh4sW7Y7hHjlFVixIp4jAuDww+GUU+IJJ487Lg4l0tKSrVmSJEl1l8GEJKlCURTP/VAyhHjttd1zQXToEIcPX/96/HrssdC+faIlS5IkqZ4xmJAkFdu4EV59dXcIsXAhbNgQn0tLix/HuPrqOIQ4/vh4HgiX3JQkSdKBMJiQpEYqJweWLCk9L8R778XnQognpDzvvN0hRN++roIhSZKk6mcwIUmNQEEBvPNO6RBi6dJ4vgiAzp3jAOKKK+LXY46BzMxka5YkSVLjYDAhSQ3QJ5+UDiFefRW2bInPtWwZzwXx4x/HIcRxx8XBhCRJkpQEgwlJquc+/zxeqrPkvBCrV8fnUlOhf3/4xjd2P5LRq1fcLkmSJNUFBhOSVM+sWAHz5+8OIZYvjx/VAOjeHYYM2R1CHH00pKcnW68kSZK0NwYTklQPrFwJDz0Ef/0rLFsWt7VrFwcQF1ywe6nOgw5Ktk5JkiSpqlKSLqAxys7O5tlnny3VNnXqVIYOHVrheYC5c+cSQmD06NGl2ocOHcrUqVMB+Oc//0m/fv1o06YN7du3Z+TIkaxdu7Zm/iCSatS6dXDrrXDSSfFIiJ/9LJ6Q8tZb4d1342U8n3wSbrwRhg0zlJAkSVL9ZDBRz2RkZDBt2jRWrVpV7vmjjjqKp556is8++4yPPvqII444gquvvrp2i5S037ZsgalT4ayz4JBD4Ic/hC++gJtuikdNvPgifP/7cPjh8ZKekiRJUn3noxz1TJs2bRg5ciSTJ0/m3nvv3eN8p06dSh2npqby3nvv1VZ5kvZDTg7MmQMPPgiPPw47d0K3bjBhQjxpZd++SVcoSZIk1RyDiXpo4sSJ9OzZkwkTJtCrV689zn/44Yf079+frVu3kpqayt13351AlZL2Jj8fnn8+njNi5kzYuhU6dYLvfS8OI44/3hERkiRJahwaRTAxZgwsWVKz7zFwINxyS+X7jxgxgiZNdn/8ubm5DBo0qFLXZmVlcdVVVzFp0iSmT5++x/nDDjuMzz77jE2bNnH33Xdz5JFHVr4wSTUmimDBgjiMePhhWL8+njPiwgvjMOK006BJo/ivsiRJkrSb/wROyKxZszjjjDOKj6dOncqUKVMqff348ePp0aMHS5curbBPu3btuOyyyxgwYABr164tFYRIqj3LlsVhxIMPwqpV0Lw5nHdeHEYMGwZpaUlXKEmSJCWnUXxTrcpIhvqiffv2jBkzhuuvv36v/fLz81m/fj1bt26lXbt2tVSdpFWr4iDiwQfh3/+G1FQ44wyYPBlGjIhHSkiSJElqJMFEfZSXl0dOTk7xcXmjHcaOHUv37t2Joqi47e9//zt9+vThiCOOYOPGjYwdO5ajjz7aUEKqBevWwd/+Fo+OePnluO2kk+C22+Cii6Bjx2TrkyRJkuoilwuto4YNG0Z6enrxduONN+7RJzMzk3HjxrFp06bitrVr13L22WfTqlUr+vXrR0pKCjNnzqzFyqXGZetWuO++3ct7/uAHey7vOXq0oYQkSZJUkVDyt+31zeDBg6NFixbt0b5ixQp69+6dQEX1k5+XVDU5OfDEE/HIiJLLe37jGy7vKUmSJBUJISyOomjwvvr5KIckVUJ+Pvzzn3EY8fe/717e88or4ZJLXN5TkiRJ2l8GE5JUgaLlPR98EKZPd3lPSZIkqSb4T2pJKmPZst0raqxc6fKekiRJUk0ymJAk4uU9H3ooflSj5PKeN9wAI0e6vKckSZJUUwwmJDVamzfHQcRf/wovvRS3ubynJEmSVLsMJiQ1Ovn5cOedMGkSbNoE/frFy3tefDFkZyddnSRJktS4GExIalSefRbGjIHly+HLX4bf/hYGDUq6KkmSJKnxSkm6AEmqDe+9ByNGwJlnwo4dMGsWPPOMoYQkSZKUNIMJSQ3a1q0wfjz06QPPPQe/+Q28+SYMHw4hJF2dJEmSJIOJBGRnZ/Pss8+Waps6dSpDhw6t8DzA3LlzCSEwevToUu1Dhw5l6tSpe/T/9re/TQiB9957r/qKl+qJggK45x7o2TN+XOOb34R33olDiubNk65OkiRJUhGDiXomIyODadOmsWrVqr32mz9/Pu+//37tFCXVMS++CMcdB5dfDt27w8KFcUhx8MFJVyZJkiSpLIOJeqZNmzaMGjWKyZMnV9gnPz+fH/zgB9x22221WJmUvNWr4ZJLYOhQWLcOHnggDimOPTbpyiRJkiRVxGCiHpo4cSIzZszg7bffLvf8zTffzMknn0z//v1ruTIpGdu3w+TJ0KsXzJwZLwP61ltxSOE8EpIkSVLd1iiWCx0zZgxLliyp0fcYOHAgt9xyS6X7jxgxgiZNdn/8ubm5DKrk8gBZWVlcddVVTJo0ienTp5c6t3r1au68804WL15c6Vqk+iqK4OGH4dpr49ESX/taPJ9E165JVyZJkiSpshwxkZBZs2bx2WefFW933HFHla4fP348Tz31FEuXLi3VPmbMGCZNmkTr1q2rs1ypznntNTj5ZLj4YujQAebNg+nTDSUkSZKk+qZRjJioykiG+qJ9+/aMGTOG66+/vlT7c889x/z58xk3blxx24knnsgf//hHLrnkktouU6p269bBxInxZJYdOsDdd8O3vw2pqUlXJkmSJGl/NIpgoj7Ky8sjJyen+LjkYx9Fxo4dS/fu3YmiqLjtnXfeoaCgoPj44IMP5rHHHmPAgAE1W7BUw3Jz4f/+D37+c8jJgR//GK67DhwcJEmSJNVvPspRRw0bNoz09PTi7cYbb9yjT2ZmJuPGjWPTpk3FbR07diQrK6t4A+jQoQPp6em1VbpUraIIHnsM+vaN55I45RRYtgx+9ztDCUmSJKkhCCV/215jbxJCGjAPaE48SuORKIpuKNNnFPA7YG1h021RFE3Z230HDx4cLVq0aI/2FStW0Lt372qovHHw81Jd9eab8N//DU8/DUceCTffDGefnXRVkiRJkiojhLA4iqLB++pXW49y7AROj6Lo8xBCU2B+COHJKIoWlOk3PYqi79dSTZLqqE2b4uU/b78dWrWCP/4Rrr4amjZNujJJkiRJ1a1WgokoHpbxeeFh08Kt5odqSKpX8vPhrrvg+uvhs8/ge9+L55To0CHpyiRJkiTVlFqbYyKEkBpCWAKsB56JouiVcrpdGEJ4I4TwSAihS23VJil5zz0HRx8No0fDgAHw+utwxx2GEpIkSVJDV2vBRBRFu6IoGggcChwXQuhbpstjQHYURf2BZ4H7yrtPCOHKEMKiEMKiTz/9tGaLllTj3n8fRo6EM86AL76AGTPikKJ//6QrkyRJklQban1VjiiKPgPmAmeXad8YRdHOwsO7gWMquP6uKIoGR1E0+KCDDqrRWiXVnG3b4Kc/haOOgmeegV//Op7s8oILIISkq5MkSZJUW2olmAghHBRCaFO4nw6cAbxVps/BJQ7PB1bURm2SaldBAUydCj17wm9+AxdfDO+8E4cUaWlJVydJkiSpttXWqhwHA/eFEFKJw5CHoyh6PITwc2BRFEWzgR+GEM4H8oFNwKhaqk1SLXn5ZfjhD2HRIjj+eHj0UTjuuKSrkiRJkpSk2lqV4w3g6HLaJ5XY/ynw09qoR1LtWrMGJkyABx6AQw6B+++HSy6BlFp/mEySJElSXVNbIyYkNUI7dsDvfx8/srFrF1x3HYwfDy1bJl2ZJEmSpLrC31cmIDs7m2effbZU29SpUxk6dGiF5wHmzp1LCIHRo0eXah86dChTp04t7pOSkkLLli2Lt/vuK3eBE6nGRBH87W/QuzdMmgTDhsGKFfCLXxhKSJIkSSrNERP1TEZGBtOmTePaa68lOzu73D6HHHK3zM2IAAAgAElEQVQIa9asqd3CpEKvvw4/+hG88AIMGAD33QennJJ0VZIkqTxRFBW/lt3Knt/X6/5cU1P33Nt+Zfsldc3e2ut6W031SeL9qtq3pvu3a9eOPn36VOn+9YnBRD3Tpk0bRo4cyeTJk7n33nuTLkcqtn59/KjGlCnQvj3ceSdcfjmkpiZdmSQ1fAUFBeTn55e77dq1q8L2goICCgoKam2/qn137drFroL4NX9XPrsKdhEVRPFrFBUfFxQUUBAVEEW79wt2FRR/sS3qX3yuoICoICpuK9un6Lqi/bKvpfaL7hMV3pM9z5X6sh8VfuGmzJfuovYyX8aLv7iUOE9E8fVlz5c8V9wG5b6XpPqj95DevDn/zaTLqDEGE/XQxIkT6dmzJxMmTKBXr157nF+/fj2dOnWiRYsWjBgxgl/+8pdkZGQkUKkai6eegq99DbZvhzFj4sc32rRJuipJKl9+fj65ubns3LmT3NzcUvvlte3rfF5eXvGX/aL93Lxc8vLzdm95u19L9svfVUGYkF/4RTx/1+4v6PmlXwt2FbArf1fxl996KxRuKSX2K7tRwX4S5/bVb2+vtdFnf68vu7+v46r0Lec4hFCqPYRQeh8IlNOn5LUl75eyuy2UfLNSuyXeo8R+qfco8Z7l3adsW8laKnzfkn3KqX1/2kt32sc9ynyOe7v3Hp9LVeqoqLxQ/ueyR32Vub70hft/bTXY57338637HdFv/y6sJxpFMPHumHf5fMnnNfoeLQe25Ihbjqh0/xEjRtCkye6PPzc3l0GDBlXq2qysLK666iomTZrE9OnTS5078sgjWbJkCUceeSQffPABl112GWPHjuXOO++sdG1SVcycCV//OvTpAw8+CEcemXRFkuqiKIrYsWMH27dv54svvtjj9YsvvmDHjh17DQBycnLYsXMHOTtz2JETv+bk5LAzt/D8zhzycvPYuXMnebl5cTiQm0debh75uYVf+vPyiQpq4Et80YLoRV+wK7PtrW8ToNkBXJ8CKakppKSmkNokldTU1FL7RccpKSmkpqQSUkK8n5pKSkpK8bmUkLK7f2F7akpqcd+i9tTU1FLtTVKblLufmhIfF+83aUJKKHyfkLp7PyW13PaiLYQQvxKKj0vuF50rr19tnytqr+gVqNPnitpgz2CgvOOq9JWkIo0imKiLZs2axRlnnFF8PHXqVKZMmVLp68ePH0+PHj1YunRpqfasrCyysrIA6NatG7/97W8599xzDSZUI/7yFxg1Co49Fp580lESUn22a9euCkODvYUJWz/fypZtW/j8i8/Z9vk2vtheGDJs38GO7TvI2ZHDzh07yc3J3f/iAvG/WFKIA4Amha8lt7JtaUDLffdr0rQJqc1Sadq0KU2bNqVJsyY0a9Ys3po3K95Pa55G8+bNad6sOWlpaaQ1TyO9eTrpaek0a9qMpilNaZLSpHhLTUktdVzcHspv39s1+3NdSnB+c0lS/dEogomqjGSoL9q3b8+YMWO4/vrr99ovhFC/h3eqzrrrLrjqKjj1VJg929U2pNpWUFDA1q1b2bx5M5s2bSr1unnzZj7/PA4Ktn6+la3btsbBwRfb2P7Fdr7YXjo4yM3JJT83v+pFFP1Wv2mJreTxQXueS22eSrO0ZqSlp5GWnkaLjBa0aNGCjBYZtMhoUfxlv3mz5qQ1T6NFegvSmqXRLLUZzVOb0yy1WbzfpMR+Oe2V6dskpYm/tZUkqQ5oFMFEfZSXl0dOTk7xccnHPoqMHTuW7t27lwoe5s6dS/fu3enSpQtr1qxhwoQJDB8+vFZqVuPxv/8LP/4xnHtuvCxoenrSFUn1UxRFbN++vVSgUDJk2LRpE+s3rmf9hvVs2LiBTZs3sWXzFrZt3cb2bdv3/khCoOLAoBnQAmi957mmaU1JS0+jeXpz0lukk94inYwWGWS0zKBVRitatWxFZstMMjMyadm8JS2atiCjWUb82jR+La+t6LhJiv/0kCRJpfmvgzpq2LBhpY4nTpxY6tEPgMzMTMaNG8f48eOL21577TW++c1vsnnzZtq3b8+IESP49a9/XSs1q+GLIvjFL+CGG+Cii+JHOZo1S7oqKXk7d+7cI1goGS58uvFT1m1Yx4aNG9i4aSNbPtvC1s+28sXWL9iVv6viGwfiRxLSC7c04jAhKz5OSU8hIzODVm1a0bpNa9q3a0+H9h3o2L4jbVu1JaNZRoUBQXkhQnqTdEcQSJKkWhfq8zD/wYMHR4sWLdqjfcWKFfTu3TuBiuonPy9VRhTBuHHw+9/DZZfFy4KWM5BHqvcKCgr45JNPWLNmDatXr2bdunVs3ryZ9RvWs27DOj7d8CmbNsfhQ1G4sM/5E5qzO1hIp1TQENID6ZnptGodhwvt2rWjQ7sOdOzQkY7tOtK+RXvaprWlbXpb2qW3K95vm9aWls1aGiRIkqQ6K4SwOIqiwfvq59cKSftUUACjR8Of/hS//t//QYrzqqkeKigoYP369cWhw+rVq1n14SreXfkuqz5cxScffcKmdZso2FWw58VN2XP0wiFAj/g4rWUaLVu3pHWb1rRt25YOHTpwULuD6NS+Ex1adigOE8oGDJnNM52oUJIkNWoGE5L2Kj8fvvMduP9+GD8ebroJ/AWt6qIoivj0009ZvXp1cfCw6oNVvLvqXVZ9sIqPP/qYTes27fnoRCqQWbh1ALpDevt0Oh7ckUO7HEqXQ7rQqUMnOrbuWGq0Qrv0dsX7bdLakJqSWvt/aEmSpAbAYEJShXJz4ZJLYMYM+OUv4Wc/M5RQMqIoYuPGjaVCh5UfrCwe6fDx2o/ZuG4ju/LKhA4pxIFDa6AdkF06dOh+WHcO73I4h7U5jEMzD6VLZhc6Z3amZTOXmZEkSaotBhOSyrVjB1x4ITz5JNx8M4wZk3RFaqiiKGLz5s3Fj1asWbOGlR+s5J2V7/DBhx/w0dqP2PjJxj2Xs0wBWhGHDm2Aw+LQ4aCDD+LQQw+le9c4dOjatquhgyRJUh1mMCFpD9u2wXnnwbx5cPfdcMUVSVek+iyKIlavXs3y5cuLRzq8s/IdVn24io/WfMTGdRvJy8krfVFgd+iQCXTeHTp0PrQzPbr24PDDDB0kSZIaAoMJSaVs3gznnAOLFsEDD8A3vpF0RapPdu7cyfLly1m6dCkLFi3glcWv8M6b77Bj247dnYpCh6J5HY6GtHZpdDy4I50P7Uz3rt054rAj6NouDh2KNkMHSZKkhslgQlKx9evhK1+BFSvieSWGD0+6ItVl69evZ8mSJby+5HXmL5zP0qVLWbty7e4VLZoCHYGekNk1k15H9eLwbofTs2tPurbrSpfWXQwdJEmSZDAhKbZmDZxxBnz4ITz+OJx5ZtIVqa7Iz8/nnXfeKR4F8fKil3l7+dts3bh1d6dMoBOkDEnhsJ6HcfTAoxnSfwhHdz6aAZ0GcFDGQYnVL0mSpLrNYEIS//kPfPnLsHEjPPUUfOlLSVekpGzZsoWlS5eyZMkSXlj4Aq8teY0P3/1w98STKcSjIA6FjBMz6NW3FycccwInHHEC/Tv1p/dBvWmW2izJP4IkSZLqGYOJBGRnZzNlyhTOOOOM4rapU6cyZcoU5s+fX+55gLlz53LaaadxzTXXcPvttxe3Dx06lCuuuIJRo0YB8Omnn/KjH/2IJ554ghACw4YN44EHHqiVP5vqnxUr4pESOTnw/PMweHDSFak2FBQUsGrVKpYsWcLCxQt5adFLvPnvN9n48cbdnVoAWRAGBw45/BD69+/P0EFDOabLMQzoNICsllkE14+VJEnSATKYqGcyMjKYNm0a1157LdnZ2eX2ueCCCzj22GP54IMPaNGiBcuWLavdIlVvLFkSP7KRmgr/+hf07Zt0RaoJ27dvZ9myZcWjIBa9voj/vPUfcrfnxh0C0B7oBGkD0ji89+EcN+g4TjrqJAZmDaRPxz6kNUlL8o8gSZKkBsxgop5p06YNI0eOZPLkydx77717nH/66adZvXo1c+fOJTU1FYCjjz66tstUPbBgQbz6RqtW8NxzcMQRSVekAxVFER999BFLly7l1ddeZf7C+fz7jX+zfvV6ooIo7tQc6AT0gU6Hd6JPvz4MOWYIx3Y9lgFZA+iS2cVREJIkSapVBhP10MSJE+nZsycTJkygV69epc4tWLCAXr16cdlll/Hkk0/SvXt3fv/733PKKackVK3qon/+E847Dw4+GJ59Frp2TboiVVVubi4rVqxgyZIlvPjqiyx8bSHvvvku27ds392pDZAFzU5tRvfe3Rl89GCGDhjKwKyB9O3Yl4xmGYnVL0mSJBVpFMHEu++O4fPPl9Toe7RsOZAjjril0v1HjBhBkya7P/7c3FwGDRpUqWuzsrK46qqrmDRpEtOnTy91bs2aNTz99NNMmTKFe++9lxkzZjB8+HDee+89OnToUOn61HA98QRceCH06AHPPBOHE6r7oihiyZIlPDTjIR6Z9Qir3l5FQX7hspxNiCek7AHtu7Wnd9/eDBk8hON7HM+ArAFkt8kmJaQkWb4kSZJUoUYRTNRFs2bNKnfyy8oaP348PXr0YOnSpaXa09PTyc7O5vLLLwfg4osv5le/+hUvvvgiw4cPr57iVW898ghccgn06xevvmFWVbft3LmTuXPnMm36NObMmcOW9Vvi+SAOhSYnNaF7r+4cPfBohg4cyqBDB9G/U38ym2cmXbYkSZJUJY0imKjKSIb6on379owZM4brr7++VHv//v157LHHEqpKddl998F3vgMnnghz5kDr1klXpPJs2LCBxx5/jKnTp/Lyv14mb0ceNAV6QJezu3DR8Iu4+PiLGXTwIFJTUpMuV5IkSTpgjSKYqI/y8vLIyckpPi752EeRsWPH0r17d6IoKm4bOXIkP/nJT7jvvvu49NJLmTlzJmvXrmXIkCG1UrfqpjvugNGj42VBZ82CDKcWqFPeeecdHp7xMA888gBvL3k7nqiyFaT0TeGYU47hW8O/xch+Izms9WFJlypJkiRVO4OJOmrYsGGljidOnFjq0Q+AzMxMxo0bx/jx44vb2rVrx+zZs7nmmmsYPXo0Rx55JI8++qjzSzRiv/0tjB8P558P06dDmqs+Ji4/P5+XX36ZaQ9PY/bs2az/cH18IgtanN6C088+nVHnjOIrPb5Cq+atki1WkiRJqmGh5G/b65vBgwdHixYt2qN9xYoV9O7dO4GK6ic/r4YpiuCGG+AXv4CLL4Zp06Bp06Srary2bdvGP/7xD+6dfi9zn5nLjq07IAXoBlnHZDFy+Egu/dKlHN/5eB/RkCRJUoMQQlgcRdHgffVzxITUAEUR/PjHcPPNcPnlcOedkOp33Vq3evVqHpn5CPf/7X6WLlgar6KRDqFnoO+X+nLpiEu5aNBFdG/bPelSJUmSpMQYTEgNzK5dcPXVcPfd8MMfxuFEiitF1oooinj99df5y9/+wiMzH2H126vjE+2g+YnN+dKZX2LUeaM498hzaZPWJtliJUmSpDrCYEJqQPLyYNQo+OtfYeLE+DGOEJKuqmHbuXMnzz3/HPc8dA9PP/E02zZsi5f07ALth7fnvK+ex2VnXMaQLkNomuqzNJIkSVJZBhNSA7FzJ3z96/Doo3DTTTBhQtIVNVwbNmxg5qMzmfrwVBbOW0h+Tn68pOfhcMTwI/jGiG/wjRO+Qa/2vQgmQ5IkSdJeNdhgIooivxBUQn2e/FS7bd8OI0fC00/DrbfC97+fdEUNz9tvv80Df3uAh2Y8xLtL34UIaAVNBzRlyOlDGDViFCP6jqBDC1fAkSRJkqqiQQYTTZs2ZceOHbRo0SLpUuq8HTt20NSlGuq1LVvgq1+Fl16Ce+6Bb3876Yoahvz8fF588UXueege5jw+h41rNsYnsqD1V1pz1rCz+M6w73Bq9qk0b9I82WIlSZKkeqxBBhMdO3Zk7dq1dO7cmfT0dEdOlCOKInbs2MHatWvp1KlT0uVoP23cCGedBUuXwoMPwte+lnRF9du2bduY8+Qc/vzgn3nhuRfYuW0npALdoOs3u3LRiIv41pe+Rb+O/fzviiRJklRNGmQwkZmZCcBHH31EXl5ewtXUXU2bNqVTp07Fn5fql08+gTPPhHffhZkz41ETqrrVq1fz0IyHuP9v97N84fLiJT1Te6Uy+NTBjLpgFBcefSFZLbOSLlWSJElqkBpkMAFxOOEXbjVUH34IX/4yfPwxzJkT76tqnp/7PKPHjeatV9+KG9pDxtAMTj/rdK44/wrOPOJM0pumJ1ukJEmS1Ag02GBCaqjefRfOOCOeW+Lpp+Gkk5KuqH7557/+yTXjruGthW9BS+h0ficuvOBCvn3mtxl08CBSQkrSJUqSJEmNisGEVI8sWxY/vpGXB88/D4MGJV1R/TF33lyuvvbqOJDIgMO+fhh/nPhHhvcd7nwRkiRJUoL81aBUTyxeDKecAiHAvHmGEpU1d95ceh/fm9NOOY23lr/FYV87jJkvz2TVg6sY0W+EoYQkSZKUMIMJqR6YPx9OPx1atYIXXoCjjkq6orpv7ry5HHXCUcWBRNevdWXWy7NY9ZCBhCRJklSXGExIddyzz8ZLgmZlxaFEjx5JV1S3/euFfxUHEiuWreCwiw7j0QWPsvKhlQzv52MbkiRJUl1jMCHVYbNnw7nnxmHEvHnQpUvSFdVdRYHEqSefyop/r6DrRV159OVHWTV9Fef3Pd9AQpIkSaqjDCakOuqhh+CCC2DAAJg7Fzp1Srqiumne/HkcdWKZQGLBo6ycvpLz+xlISJIkSXWdwYRUB/35z3DJJTBkSPwoR7t2SVdU98x7cR59TurDKV86hRVvxIHE7FdmG0hIkiRJ9YzBhFTH3HYbXHEFfOUr8OSTkJmZdEV1S3EgMfQU3lz6JtkXZfPYgsdYOX0l5/U9z0BCkiRJqmeaJF2ApN1efRV+9CM4/3x4+GFo3jzpiuqOF156gat+chVvvvwmpEP2f2Vz2w23MazPMMMISZIkqR4zmJDqiLy8eKREVhZMm2YoUWTeS/O4+tqrefOl3YHE7Tfczjl9zjGQkCRJkhoAgwmpjvjDH+CNN2DmTGjdOulqkvfCyy9w1bVX8eaLpQOJYX2HJV2aJEmSpGrkHBNSHfDeezB5crwKx4gRSVeTrPkL5tN3aF9OPulk3nztTbpd2I05C+ew8m8rDSUkSZKkBsgRE1LCogiuvDJ+dOPWW5OuJjkvvvIiV/74yuIREt0u7MatN9zKuf3OTbo0SZIkSTXIYEJK2L33wj//CXfeCYccknQ1te/FV17kez/5HsvnL4c06HZBN2678TaG9XN0hCRJktQY1MqjHCGEtBDCwhDC0hDC8hDC5HL6NA8hTA8hvBdCeCWEkF0btUlJWrcOfvIT+NKX4okvG5MXF75I3y/1ZegJQ1m+aDndLujGE68+wX9m/MdQQpIkSWpEamuOiZ3A6VEUDQAGAmeHEE4o0+dyYHMURYcDNwP/U0u1SYn50Y/giy/grrsgpZHM+PLSwpfoe3Jfhh4fBxLdL+jOEwvjQOKcvuckXZ4kSZKkWlYrX4Wi2OeFh00Lt6hMt+HAfYX7jwBfDq4FqAZszhyYPh2uuw6OPDLpamrey6++TN+T+zLk+CEsfzUOJJ589Unen/E+5/QzkJAkSZIaq1r7HW0IITWEsARYDzwTRdErZbp0BlYDRFGUD2wB2tdWfVJt2rYNrr4a+vSB8eOTrqZmvfzqy/Q9pS8nHXcSyxfuHiHx/oz3Obvv2UmXJ0mSJClhtTb5ZRRFu4CBIYQ2wMwQQt8oipaV6FLe6IiyoyoIIVwJXAlw2GGH1UitUk277jpYswZefBGaNUu6mpqxYNECvvvj77Js3jJoDt1Hduf2ybdzdj/DCEmSJEm71fpT7VEUfQbMBcp+O1kDdAEIITQBWgObyrn+riiKBkdRNPiggw6q4Wql6rdgQbws6OjRcOKJSVdT/V5e9DL9Tu3HiceeyLJXltF9ZHf+segfvP/39w0lJEmSJO2htlblOKhwpAQhhHTgDOCtMt1mA5cV7v8X8HwURXuMmJDqs9xc+O53oXNn+PWvk66mei1YvIC+p/blpGNPYtmCZfQY2YN/vBoHEmf1PSvp8iRJkiTVUbX1KMfBwH0hhFTiMOThKIoeDyH8HFgURdFs4M/A/SGE94hHSlxcS7VJteZ3v4Nly2D2bGjVKulqqkcURXxrzLd44NYHoBn0GNmDO35+B1/p+5WkS5MkSZJUD4T6PChh8ODB0aJFi5IuQ6qUd96B/v3h/PPh4YeTrqZ6fPHFF5x0/km88fwbtD2+LQ/e/SBn9XN0hCRJkiQIISyOomjwvvrV2uSXUmNWUABXXgnp6fB//5d0NdXj3ZXvcsKZJ7Dp/U30v7Q/L/35JTKaZSRdliRJkqR6ptYnv5Qao3vugX/9C37/e8jKSrqaA/f484/TZ2AfNq3exKU3XcqSaUsMJSRJkiTtF4MJqYZ9/DH85Cdw6qnwne8kXc2B+/mtP+e8s84jPzWfP/7tj9w/4X5CKG+1X0mSJEnaNx/lkGrYD38IOTlw111Qn7+/FxQUMOK7I3jsnsdo3qM5T89+mpOPOjnpsiRJkiTVcwYTUg2aPRseeQR+9Ss44oikq9l/n235jGPPPpb3FrzHwacczKJZizikzSFJlyVJkiSpAfBRDqmGbN0K11wD/frBtdcmXc3+e+OtNzis72G898p7DP3eUFY9u8pQQpIkSVK1MZiQasjPfgYffQR33w1NmyZdzf756+N/ZdDgQWzbsI0f3vpDXvjTCzRr0izpsiRJkiQ1IAYTUg146SW44454fonjj0+6mv0z9tdj+ebwbxK1iJg2Zxp/HP3HpEuSJEmS1AA5x4RUzXbuhO9+F7p0gV/+Mulqqi4vL48zLz2Tfz38L1oe1ZIX5rzAwOyBSZclSZIkqYEymJCq2f/8D7z5JsyZAy1bJl1N1azbsI5jzjyGtUvW0n1YdxY9vIi2GW2TLkuSJElSA+ajHFI1WrEiXoHj4oth2LCkq6mal19/mW59u7H2jbWc+5Nzeffxdw0lJEmSJNU4gwmpmhQUwJVXQkYG3HJL0tVUzf976P8x5KQh7Ph8BzfcewOP/+5xUoL/eZAkSZJU83yUQ6omd98N8+fDPfdAp05JV1M5URRx+cTLufc399Ikqwl/n/V3zjvuvKTLkiRJktSIGExI1eCjj2DcODj9dBg1KulqKidnZw5DLhzCa3Neo+3Atix8YiGHH3x40mVJkiRJamQMJqRq8P3vQ24u3HknhJB0Nfu2au0qjj3zWDas2EC//+rHggcW0KJZi6TLkiRJktQI+RC5dIBmzoy3G2+Ew+vBgIOnX3qaXgN6seHdDXzzxm+y9OGlhhKSJEmSEmMwIR2ALVtg9GgYMADGjk26mn37zZTfcPZpZ5OXm8ctD93CX274C6E+DPGQJEmS1GD5KId0ACZMgHXrYPZsaNo06WoqFkUR//XD/+Lvt/+d5l2a8/Scpzm578lJlyVJkiRJBhPS/po/H/70J/jv/4bBg5OupmLbvtjGsV89lrfnvk3WCVksnrOYQ9odknRZkiRJkgT4KIe0X3buhO9+F7Kz4Re/SLqaiq34zwoO7X8ob899myGjhvDh/A8NJSRJkiTVKQYT0n749a/hrbfiERMZGUlXU75Hnn2EfoP6sXXNVkb/YTTz751P09Q6/LyJJEmSpEbJYEKqouXL4aab4JvfhLPOSrqa8k24ZQIXnXMRUUrE1NlTuW3sbUmXJEmSJEnlco4JqQoKCuDKKyEzE26+Oelq9rRr1y7OuvwsnrvvOTIOz2Dek/MYdPigpMuSJEmSpAoZTEhV8Kc/wUsvwX33wUEHJV1NaRs+28AxZx/Dh698SLfTu7H40cW0bdk26bIkSZIkaa98lEOqpDVr4uVBzzwTvvWtpKsp7dXlr9K1X1c+XPgh53z/HN575j1DCUmSJEn1gsGEVAlRBKNHQ35+PGoihKQr2u3Pj/6ZE044ge0btnP9ndfzxK1PkJLi/7QlSZIk1Q8+yiFVwowZMHs2/O530L170tXs9r1ffI+7Jt9Fk3ZNmDlzJucPOT/pkiRJkiSpSgwmpH3YvBl+8AMYNAjGjEm6mlhefh5DvzH0/2fvvsPjqO41jn/PqktWsaqrLFuuuABBmEAIvZoSSmihmJIQDNzQQyeEEGIwpoYeUUwxmA7G9N6JHXDBDbk3Fduyetly7h8jW8UqK3l31d7P88yzszNz5vzka3I9r86cww+v/EDSbkn88P4PjBg0orPLEhERERERaTcFEyJtuPZaKCqCd96B8C7wX8z6wvXsdcReFM4vZOyxY/nhlR+IjYrt7LJEREREREQ6RC+ii7Ti88/hiSfgiiucEROd7eO5H5M9IZvChYWcft3pLHxroUIJERERERHp1hRMiLSguhouvBCGDoW//72zq4Hpz03n8AMOx13mZvpz05n5r5mYrjQLp4iIiIiISAd0gYHpIl3TP/8Jy5fDBx9AbCcPSjj92tN56e6XiMqI4t3Z73Lwrw7u3IJEREREREQCRMGESDMWLoSpU+Gcc+DwwzuvjsrqSvY+aW8Wv7uYjF9lMPe9uQxKG9R5BYmIiIiIiASYXuUQacLrhT/9CZKSYPr0zqtj+brlDNxzIIvfXcyvT/81a79bq1BCRERERER6HAUTIk08/DB8/z3cdx+kpnZODa9/8Tpj9xzLtrxtTLljCt/O/JbIiMjOKUZERERERCSIFEyINLBuHdxwAxx5JPzhD51Tw82P3cxJR5yEr9bHk689ycPXP9w5hYiIiIiIiISA5pgQqWMtXHwx+Hzw6KPQGQtePPv+s9x+ye3EDozl8/c/J2d0TuiLEBERERERCSEFEyJ1Xn4ZZs925pXIygp9/+uL1nP+2ecT1ieMBV8vIHtQduiLEBERERERCTEFEyLA1q3wf/8HOTnwl7+EvsCOQHkAACAASURBVH9rLfv/fn88mz08NOshhRIiIiIiItJrKJgQAa65BrZsgQ8+gPBO+K/i/NvOZ80Xazj0/EO5+PcXh74AERERERGRTqLJL6XX+/RTePJJuPpq2H330Pf/9jdv8/QdT9N3dF/efezd0BcgIiIiIiLSiRRMSK9WVQUXXgjZ2fC3v4W+/61lWznltFMw4YaP3/iYiPCI0BchIiIiIiLSifQqh/Rq//gH5OXBRx9BTEzo+//tH35Lzfoabn/idvYctWfoCxAREREREelkGjEhvdb8+TBtGpx7Lhx6aOj7v/KBK1k8ezETT57IjX+8MfQFiIiIiIiIdAHGWtvZNXRYTk6OnTt3bmeXId2Q1wv77gtr1sDixZCSEtr+v1z4JQfscwBxaXEULC0gLiYutAWIiIiIiIgEmTFmnrU2p63r9CqH9EoPPgj//S/MnBn6UKKiuoKjTzoavDDn9TkKJUREREREpFdTMCG9zpo1cNNNMGkSnHZa6Ps/5IJDqMir4Iq7ruCAXx0Q+gJERERERES6EM0xIb2KtTBlirP/yCNgTGj7v33G7fww8wfGHDaGe665J7Sdi4iIiIiIdEEaMSG9yosvwrvvwn33QWZmaPv+aeVP3PJ/txCVHsWXL38Z2s5FRERERES6KAUT0mts2QKXXQYTJ8Kll4a2b7fXzSEnHYKtsLz05kukJIV4YgsREREREZEuSsGE9BpXXQXFxfDRRxAWFtq+J/1lEsXzi5l83WR+d9DvQtu5iIiIiIhIF6Y5JqRX+OgjeOYZ+OtfYcKE0Pb9yFuP8NGjH5E5MZOn7ngqtJ2LiIiIiIh0ccZa29k1dFhOTo6dO3duZ5chXVxlJYwf74ySWLAAoqND1/eKTSsYNWEUxmNYuWQlg/sNDl3nIiLSa1hrsdYLeLHWi7W+BvveFs75AB/OvwV9O76DbXCu+e/+nWt679bONb1XW+fqt4bf6/vZ+Vx7vwfyXvXfaXCMTjje+Hx9ja0dp9n9xs8Qze3XH2v+2ubb71xvR/tv/vvOzz5tfQ/EPdrbftfOtf5819K5QPfT3j5CdW1H6m7X3YN25+TkIxgz5tmg3T9YjDHzrLU5bV0Xklc5jDGDgRlAP5z/7/K4tfb+JtccBLwJrKo79Jq19rZQ1Cc929//DitXwqefhjaU8Fkfvz3lt3i3eHn6jacVSoiIBJi1Pqx14/O5sdaDte4Gm6fueONzbV9bf97/az3NPPx7cR6imwsGdj7ffIjg8/tcMP8x3HOYHZsxpo3vrnZc277vQINjdMLxxsfqa2ztOA2Obz/X+Fjz1zbfvnF/zd+/5Xs2f/+Wr237u9lpmbbmlm3b1Xu0t31b9bR1ruU2LfcV2H7a1/eu3ru9S+0Fb2m+9v2M/ouLC/Gw7xAL1RwTHuAqa+3/jDHxwDxjzIfW2sVNrvvSWntsiGqSXuDHH2H6dLjgAjjooND2fdpNp7Hp600c/+fjmXz85NB2LiISQM5v42vx+Wrw+aqbbP4ds9af62raESB4cH7XETrGRNRt4RgTgcu1fT8cCMOY+q3+u2unc8ZEtniu4XdwtXiu6fn2nXP6dvZN3bWuus/G3+sf0ts61/x3/841vXdb59oXJgTrIUFERAInJMGEtXYTsKluv8wYswQYCDQNJkQCxuOBP/0JUlNh2rTQ9j3z05m8cvcrpO2Wxqv/fjW0nYtIj2etxeerwest27F5PGV4veU7vvt8VS0+/HckSNh1BpcrBpcrCpcrusnmHAsP71v3sN9cAFD/vXEo0Pj6YF3rPNTrAVdERCQYQr4qhzEmC9gT+L6Z0/saY+YDG4GrrbU/h7A06WEeeQTmzYNZs6Bv39D1u2nbJiafPRlXhIsv3v6C8HAtfiMi4PPV1IUHDbfynY7Vfy9v5lj9OWfEgP+ahgHGNA4IwsOTWg0N2jrW9H5Nr3Me7vVgLyIiIjsL6ROTMaYP8CpwubW2tMnp/wFDrLXlxphJwBvAiGbucSFwIUBmZmaQK5buylp44AHYf3/4/e9D2a9l/zP2x73Bzb3P3MvoYaND17mIBJS1Fq+3DLd7a6NAoKWgoK2AwVq3X/0aE0FYWHzd1ofw8HjCwxOIihpIWFg84eH157ZfV3+s4bnYBqFAhEIBERER6bJCFkwYYyJwQonnrbWvNT3fMKiw1s4xxjxsjEm11m5uct3jwOPgrMoR5LKlm/riC8jLg1tugVD+W/zPd/+Zle+t5IDTDuDycy4PXcci0iZrLR5PCW53EW53EbW1hTv2ne9FuN2FDfaLsLa2zfsaE95sUBAZ2X+ngKFheNBSwOByRYXgT0NERESk6wjVqhwGyAWWWGvvaeGafkCBtdYaYybizKq0JRT1Sc+TmwsJCXDyyaHrc87cOTzxtydIzErk/affD13HIr2UEzRsw+0u3BEkNBc6NDzX0qgFlyuOyMh0IiLSiIwcSJ8+exARkUZERDoREcmNAoSmAYPLFaXRCCIiIiK7IFQjJn4DnA0sNMb8VHfsBiATwFr7KPB7YIoxxgNUAafb4C4yKz1USQm88gpMngyxsaHps7iimJNPPxnjM7z/5vtEh3JdUpEewlofHk9xgyCh9cDB7d7c4jwLYWHxdcFCGtHRmcTH71UXOqTtCBzq99MIC4sJ8U8rIiIiItuFalWOr2hjsVhr7b+Bf4eiHunZZs6EqipnidBQsNZy4HkHUr2impvuu4l9JuwTmo5Fugm3exvV1Suorl69I1ho/jWKzYC32XuEhSXuCBKio4cSHz9xxwiHpoFDREQqYWEKB0VERES6Cy0XID1Obi6MHw977RWa/q77z3UsfGUhexy5B/+47B+h6VSkC7HWR03NRqqrV1BVtYKqqpUN9lfg8WzdqU14eFJdiJBGTMxwEhL2bRAyNA0cUjXvgoiIiEgPpmBCepQFC2DuXLjvvtBMevnN0m+YdtU0YjJi+GzWZ8HvUKST+Hw1VFev3hE2VFWt2BE+VFevwuerbnB1GNHRQ4iJySY9/VSio7OJiRlGdPRQIiP71QUNEZ32s4iIiIhI16JgQnqU3FyIjISzzgp+X5W1lRx1ylHYSssb775BYkJi8DsVCaLtr1xUVa1sFDxUVa2gpmYdUD/tj8sVS0xMNrGxo0hOnkRMTPaOLSoqU8GDiIiIiPhNwYT0GDU18NxzcMIJkJIS/P4Ou+QwyhaVMeWWKRzxmyOC36HILrLWR23tpmZHPTT3ykVERDoxMdkkJR1QN+ph+8iHbCIjM7QShYiIiIgEhIIJ6THeeAO2bg3NpJd3zrqTb5/8luH7DuehWx8KfocifvL5ahu9ctEweKiuXtnMKxeZxMRkk5Z2SqNRD9HRwwgPj++0n0NEREREeg8FE9Jj5OZCZiYcdlhw+1mwdgE3XHwDkYmRfPXmV/qtsYScx1NGVdUvzYQPK+teufDtuLb+lYuRJCcf3WjUQ3T0EL1yISIiIiKdTsGE9Ahr1sBHH8Ett4DLFbx+ajw1HHzqwfi2+nh29rNkpGUErzMRnOVoq6ryKC39hpKSbykt/YaKikU0nO/BWdkim8TE/ZuMetArFyIiIiLS9SmYkB7hqaecz/POC24/J1x/Alu/38ppl57GqZNODW5n0it5vZWUlc2lpOQbSku/obT0W9zuzQCEhSWQkLAvaWknExc3nujoYcTEZOuVCxERERHp1hRMSLfn8znBxGGHwZAhwevnsfce473732PA+AE8f9/zwetIeg1rLTU16xqFEOXlP2GtB4CYmFGkpBxLQsJ+JCbuR2zsGIwJ4pAgERHpVqytGz23fRCdbXKswfEd1zc5tlObpm0b9kPj483tt+dav67vYB3NtmnhmmaPNdes6b2CeZ9dONfsz9zW/QLdT1t2oekut9+VsnflZ97FvsOTwokdEbtr/XdhCiak2/v4Y1i7Fu66K3h9rChcwSXnX0JYVBhfzv6SsLCw4HUmPZbPV0NZ2Y+Uln5b92rGN9TWbgScuSASEiYyePBfSUzcj4SEXxMREYLlZURkl1lrsV4LPrDeun0vWF87970W6/Njv2lffuw3e87nfGLr961t+Zj11T3UNtjf6R7NHfPnHm3dt2lt2x+wbRf/TpNjDb7v2KeZ62m7jYj0LinHpTD+rfGdXUbQKJiQbi83F5KTnWVCg8Hr83LgmQfi3eTlkecfYVjmsOB0JD1OTU1+oxCirGwe1tYAEB2dRVLSQSQk7Eti4n7ExU3A5dL/JEvPZ70WX42vfqv2YWvqj1m3xXps/afH4nP7Gh8L0jU7zrfzmgbzzXZvBnDhzEvjAuMy9cfq9o3LOddwf/v1zR3z6x5t3Ne4DIQ5n8bU3a9u6xbfodExaHAdNPpsdD0BatPkWIfa0Hi/0dxFzV3Tnmv9ub6jdbT0vWnbdrRreiyo92mtfVvnWrtdS30FuJ+27PIcWLvSvLPa0vGfOyK9Z09Yrn8FS7e2ZQu8/jpcdBFERQWnjzPvOJMNH23gyDOP5KI/XBScTqTb8/k8VFQsoLT027pXM76lunoVAMZEEh+fw8CBl9aNhtiXqKj+nVyx9CathgHV7Tze4JytsTtd19Zx6wn+r3tNuMFEmMafDfZdEa5mz7miXJg+Ta5p7l4N2rkiXM5Dc5jBhNU9SDez39q5RvvbH8Dbsx9m6h/e27u//eFfk+SKiEgnUjAh3drzz0NtLVxwQXDuP+ubWbx0x0skZyfzZu6bwelEuiW3ewulpd/tCCFKS3/A56sAIDKyPwkJ+zFw4KUkJOxHfPyeuFxBSs6kx7DW4qvy4S334i3zOp9+bp4yz07HfFWBDwN2PLxHGVzRLlxRdVvdvokyhCeFN3u8pesbHY9yOQ/9rYUJbQQFJszoIVtERKSb8SuYMMYcDKy21q4yxvQHpgJe4AZrbX4wCxRpibXOaxw5OTBhQuDvv6lkE2eddRbGZ/jkrU+ICtaQDOnyrPVRWblkRwhRUvINVVXL6s6G0afPHvTvf/6O1zKiojL1YNTDWZ/FW9GO8MDPoMHvd8ddENYnbKctMiOSsOwwwuLCcMX6EQS087hx6e+1iIiIBJ6/IyYeBo6s259e9+kBHgeOD3RRIv6YNw8WLIBHHgn8vX3WxwHnHYB7lZt//vuf7L7b7oHvRLosj6eU0tIfdswNUVr6HV5vCQDh4SkkJu5Hv36TSUzcj/j4HMLC4jq5YukI67W4t7pxb3Hj3tzy5tnWzGiEinZMKhAG4fHhO4UIUQOjCIvfOVxoc4sPwxXtUvglIiIiPYa/wcRAa+1aY0w4TkAxBKgFNgatMpE25OZCTAyccUbg733xvy8m7/U89jlmH2645IbAdyBdhrWWqqoVDUKIb6moWIjzq2tDXNw40tNP2zE3REzMCD0QdkHWZ/Fs8+wcLLQSOniKPS2OUHDFuohIjSAiNYLwpHAiUiNaDQuaCx62byZSrxaIiIiItMbfYKLUGJMBjAMWW2vLjTGRQM+eGlS6rMpKeOEF+P3vITExsPd+b/57PHbjY/QZ0IcPZ34Y2JtLl2Ctj23bPiU//xm2bn0Xt3szAGFhCSQk/Jq0tJNISNiXhIR9CA8P8F8waZO1Fm+pt9VRDDsFDlvcLa6MYCINEWkRO4KGPnv2cfZT6o812lIiCIvVksAiIiIioeJvMPEg8F8gEri87thvgKXBKEqkLa++CqWlgZ/0sriqmJP+cBJUwTsfvEN8fHxgO5BOVVm5jPz8GRQUPEtNzTrCwhJITf0diYn7k5CwH3FxYzBGD6SBZq3FXeSmem1162HDZjeeLc6oh5YmazThplGIEDc2zhnVkBLefMiQGkFYXJhGLIiIiIh0YX4FE9baO40xrwNea+2KusMbgD8GrTKRVuTmwvDhcMABgbuntZaDLzqYqsVVXPWPqzjg1wG8uXQat7uYwsIXKSiYQWnpd4CL5OQjGDbsLlJTf0dYWExnl9gjeEo8VK2qonpVtbOtdj6rVlVRvbq6+TkZXDQatRA7Mrb1kQypEYQlKGQQERER6Wn8Xi7UWru8te8ioZKXB59/DnfcAYF8PrnxuRuZ/9x8dvvtbky7cVrgbiwh5/N5KC5+n/z8Z9i8+U2srSUubhzDhk0jI+MPREUN6OwSux1vlXdH2NAwcNj+3VPsaXR9WJ8woodGE5MdQ9/D+hIzNIaoIVFEpkc2mrtBqzyIiIiISIvBhDFmHX4sXGatzQxoRSJtePJJcLlg8uTA3fPbvG+ZevlUovtG8/nrn+s3st1UefkC8vOfoaDgedzuAiIiUhkw4CL69ZtMnz576v+urfC5fdSsq6kPHVZVNxr9UJtf2+h6E2WIzoomZmgMCfskEJ0VTfRQZ4sZGkN4crj+vEVERETEL62NmDgrZFWI+MnjgaefhkmTYECAfuldXlPOUWcchS22zHp/FqkpqYG5sYREbW0hBQUvUFDwDOXlP2FMBCkpx9Cv37kkJx+NyxXZ2SV2CdZnqdlY02iUQ8MQomZ9TePJI8MgerATNCRPSt4ROGwPICL7RWq0g4iIiIgERIvBhLX281AWIuKP996DTZsCO+nl0dccTencUs694lyOO/y4wN1Ygsbnq2HLltk7VtWw1kOfPnsxfPgDpKefQWRk7wuXrLW4N7sbjXJoNPJhTTW2tvEguMgBkURnRZP420QndBhaP+ohalAUrnBXJ/00IiIiItKbtPYqx23+3MBae0vgyhFpXW4uZGTAMccE5n7T3pzGV49+xZDdh/Cfaf8JzE0lKKy1lJX9l/z8ZygsnInHU0xkZH8GDbqCfv0mExc3trNLDInaglrK5pZRubxyp0kmm04wGZ4STszQGPrs0YfUE1N3jHbYPt9DWLRWIBERERGRztfaqxyDQ1aFiB8KCmD2bLjiCoiI2PX7LdqwiOumXEd4VDhfzP6CsDA9pHVF1dXrKSh4joKCZ6isXIrLFU1q6glkZEymb9/DcLn8nsO32/FWeCmbV0bpD6WU/eB81qyp2XF++wST0cOiSTo0qX7UQ10AER7fc/9sRERERKTnaO1VjvNCWYhIW2bMcOaYOP/8Xb9XjaeGg886GN8mH0/OepLMQZrDtSvxeispKnqNgoIZFBd/BFgSEn7DyJGPk55+KuHhiZ1dYsD5PD4qf65sFEJULKrYMe9DdFY0CfskkPB/CcTvHU/c2DhNMCkiIiIiPYLfv04zxowBfg9kWGsvNcaMAqKstQuCVp1IHWud1zj22w9Gj971+53095PY/Nlmfnfu75h8SgCX95AOs9ZHScmX5Oc/Q1HRy3i95URHZzFkyM3063cOMTHZnV1iwFhrqV5T7QQQ3ztBRNm8MnxVTgoRnhxOwsQEUk9IJWGiE0REpmsSTxERERHpmfwKJowxpwAPA68CfwAuBeKBqcBhQatOpM4338CyZU44saue+OQJ5tw9h/QR6cx6bNau31B2SVXVCvLzZ1BQ8CzV1asIC+tDWtop9Os3mcTE32JM95+A0b3FTel/60dClP1QhrvIDTjLbsb/Kp7+F/Z3QoiJ8cRkx2gkhIiIiIj0Gv6OmLgNONxa+5Mx5rS6Y/OB3YNTlkhjubnQpw+ceuqu3WfllpVMOX8KLuvi07c+JTJSv4XuDB5PCYWFL1NQ8AwlJV8Bhr59DyUr6zbS0k4kLCyus0vsMG+Vl/KfyhuFEFV5Vc5JA7FjYkk5JoX4feJJmJhA3Lg4XJHdP3wREREREekof4OJdJwgAsA2+LTNXy4SOGVlMGsWnH66E050lNvr5sDzDsS7xsv0x6az2+jdAlektMlaL8XFH5Gf/wybN7+Oz1dNTMwohg69g4yMs4iO7n7z7VqvpXJZ5Y7XMUp/KKViQQXW4/xPY9SgKOInxtP/j/2JnxhP/F7xhCdoQkoRERERkYb8/RfyPOBsYEaDY6cDPwS8IpEmXnoJKirgggt27T7n3ncu699ez4EnHMiVF14ZmOKkTRUVi8nPf4aCgueord1IeHgS/fqdR79+k4mPn9itXlmoXl/daCRE2dwyvGVeAMISwojfO57B1wwmYR9nXoioAVGdXLGIiIiISNdnrG170IMxZjTwAbAK+DXwGTASOMJa+0swC2xNTk6OnTt3bmd1LyGy775QUgI//wwdfYZ9+YeXOfXQU0lMTGTDsg3ExXXfVwW6A7d7C4WFL5Kf/wxlZf8FwkhOPop+/SaTknIcYWHRnV1imzwlHsrmNl6qs3ZjLQAmwtBnjz7ET4zfMS9E7MhYjKv7hCwiIiIiIsFmjJlnrc1p6zq/RkxYa5fWhRPHArOBdcBsa235rpUp0rrFi+G77+DuuzseSmws3chZk8/CVBve+/Q9hRJB4vO52bp1Dvn5z7Bly2ysdRMXN4Hs7OlkZJxJZGRGZ5fYIl+tj/L5jeeFqFxaueN8zMgY+h7Sd0cQ0WePPriiNC+EiIiIiEggtBpMGGNigGxr7SJrbSUwq8G5ccaYPGttdbCLlN4rNxfCw+HsszvW3md9HHTRQdQureWGf93Ar3N+HdgCBWu9bNz4OKtX/w23u4iIiHQGDryUfv0m06dP150ft+LnCgpmFlD8UTHlP5Zja53RYxEZESRMTCDjrAxnXoiceCL6RnRytSIiIiIiPVdbIyb+CiQBVzRz7jxgG/CPQBclAlBbCzNmwPHHQ3p6x+5x6X8u5ZeXfmGPg/bg9mtvD2yBQlnZPJYvn0JZ2X9JSjqIQYOuIjn5SFyurvkgX7W6isIXCyl8oZCKhRXggsT9Ehl02aAdoyGiBkd1q3kvRERERES6u7aCidOAw1s4dw/wIQomJEjefhs2b+74pJcfLv6QR657hNi+sXz0ykd62Awgj6eEVatuYsOGh4mISGPMmOdJTz+jS/4Z1xbUUjirkMKZhZR+WwpAwr4JDH9gOGmnpBHVTxNUioiIiIh0praCiYHW2g3NnbDWbjDGDAxCTSKA8xrHwIFw5JEda3/O/50D2+C1D18jJSUlsMX1UtZaCgtnkpd3JW53IQMHXkJW1j+IiEjq7NIa8ZR4KHqtiMKZhRR/XAw+iBsfx9A7hpJ+ejoxQ2M6u0QREREREanTVjBRYYwZbK1d1/SEMSYTqGymjcguW78e3n8frr8ewsLa3/79he+T/0U++0zahyMP6WCyIY1UVCzll18uYdu2T4iPz2HChHeIj9+rs8vawVvlZcvsLRTOLGTLO1uwtZboYdFkXp9JxhkZxI3VpKciIiIiIl1RW8HEHOAOoLmpB/8BvBPwikSAZ54Bnw/OP79j7a++42rwwAO3PRDYwnohr7eSNWvuYN26u3C5Yhkx4mEGDLgQYzqQGAWYz+2j+KNiCl8oZPMbm/GWe4nsF8mAKQPIOMOZvLIrvl4iIiIiIiL12gombgK+NcbMB14DNgH9gROBBGC/4JYnvZHPB08+CQcfDMOGtb/90vylLJq9iKy9spi458TAF9iLbNnyDr/8cinV1avJyDib7Oxpnb7sp/VZSr4qoXBmIYUvF+LZ4iE8KZy009LI+EMGSQcmYcIURoiIiIiIdBetBhPW2nxjzK+Aq4CjgBRgC/A2cI+1tjj4JUpv8/nnsHIl3HZbx9pfdvdlUA7/uEHzsnZUdfVa8vIuZ/Pm14mNHcPuu39K374HdVo91lrKfyx3wogXC6lZX4MrxkXq71JJPyOd5COTcUW5Oq0+ERERERHpOGOt7ewaOiwnJ8fOnTu3s8uQADvrLJg9GzZtgph2zlFYXFVManYq8eHxFK8p1jD+dvL53Kxffx+rV98KWIYMuYXBg6/E5YrslHoql1dSOLOQgpkFVC2rwoQbko9KJv2MdFKOTyG8T1uDvkREREREpLMYY+ZZa3Pauk7/qpcuZds2ePVVZ26J9oYSANf95zp8m3xcdvdlCiXaadu2L1m+fAqVlT+TknIcw4c/QExMVsjrqF5fTeGLzvKe5f8rBwNJByYx+MrBpJ2cRkRKRMhrEhERERGR4FEwIV3KCy9AdTVccEH727q9bmY8OoOI+Aiuv+T6wBfXQ9XWFrFixTUUFDxDVFQm48a9SWrq8aGtYXMtRa84y3uWfFkCFuL3jif7nmzST00namBUSOsREREREZHQUTAhXUpuLuyxB/zqV+1ve/8791O9uJozLj2D6OjowBfXw1jrY9Om/7By5XV4vWVkZl7HkCE3ERYWmmU1PWUeNr+5mcKZhRR/UIz1WGLHxJL19yzST08ndkRsSOoQEREREZHO1WIwYYz5zlr767r9v1lr/x66sqQ3+ukn+N//4MEH29/WWsud0+/EhBum3zg98MX1MGVlP7J8+RTKyr4nMfFARo58mLi43YLer6/Gx5Z3t1A4s5Atb2/BV+UjKjOKQVcOIuMPGcRNiNMrOCIiIiIivUxrIyZGGmOirbXVOKtyKJiQoMrNhagoOPPM9rd968e32PzNZn5zzG/o369/4IvrITyeUlatuoUNGx4kIiKF0aNnkJFxVlDDAOu1FH9aTOHMQopeLcJb4iUiLYJ+5/cj44wMEvZNwLgURoiIiIiI9FatBRNvAsuNMauBGGPMF81dZK09IBiFSe9SXQ3PPw8nnQR9+7a//bV3XgseuP/W+wNfXA9graWoaBZ5eVdQW5vPgAF/ZujQO4iI6MAftp/9lX5X6izvOasQd4GbsPgwUk9KJeOMDJIOTcIVruU9RURERESklWDCWnueMWZ/IAvYG8gNVVHS+7z+OhQXd2zSy0UbF7FszjKy985mrz32Cnxx3Vxl5S/88sslFBd/SJ8+v2LcuDdISJgYlL7KF5Y7YcSLhVSvqsZEGVKOTSHjjAySJyUTFhMWlH5FRERERKT7anXyS2vtV8BXxphIa+0zIapJeqHcXBg6FA4+uP1t/zLtL1AO/7zxn4EvrBvzeqtYu3Yqa9dOxeWKZvjwBxk4cArGBDYcsNZS9GoRa25bQ8XCCgiD5MOTybo1i9QTUglP0By7IiIiIiLSMr+eGKy1TxpjDgbOW4Ia4gAAIABJREFUBgYCG4DnrLWfBLM46R1WrYKPP4bbbgNXO0f3F1UU8dmLn5GUmcSpx58anAK7oS1b3uOXXy6lunoF6el/IDv7bqKiAj/3RtlPZeRdlkfJFyXEjYtjxEMjSDsljci0yID3JSIiIiIiPZNfwYQx5o/AHcB/gO+BTOAFY8zN1tonglif9AJPPQXGwLnntr/tXx//KzbfcuW9V2o1B6C6ej0rVlxBUdErxMSMZPfdP6Jv30MD3k9tQS2rblrFptxNRKREMPLRkfT/Y39MmP5vICIiIiIi7WOstW1fZMxy4BRr7fwGxyYAr1prRwSxvlbl5OTYuXPndlb3EgBeL2Rlwbhx8O677Wtb7akmcUIibICSghKio6ODUmN34PN52LDhAVav/hvWehgy5CYGD74alysqsP3U+lj/wHrW3LYGX5WPgX8ZyJCbhxCRFBHQfkREREREpPszxsyz1ua0dZ2/L3+nAIubHFsGJLe3MJGGPvwQ1q+He+5pf9t73rqH2iW1nHPZOb06lCgp+Zrlyy+momIBycmTGDHiQWJihgW0D2stW97ewoqrVlCVV0XKsSlkT88mdmRsQPsREREREZHex983+r8C7jHGxAIYY+KAacA3/jQ2xgw2xnxqjFlijPnZGHNZM9cYY8wDxpg8Y8wCY8yv/P0hpPvKzYWUFDj++Pa1s9Zy9713Y8INd11/V3CK6+JqazezdOkf+fHH/fF4tjJ27GuMHz874KFE+aJyFhyxgEW/W4SJMEx4bwLj3x6vUEJERERERALC3xETFwEvAiXGmK04IyW+Ac7ws70HuMpa+z9jTDwwzxjzobW24SiMo4ERdds+wCN1n9JDFRXBm2/CJZdAVDvfOHj5vy9T/F0xBxx3ABkZGcEpsIuy1kd+/lOsWHEtXm8Jgwdfw5AhtxAe3ieg/dRurmX131az8dGNhCeGM/yB4Qy4aACuiHbOUCoiIiIiItIKf1fl2AQcaIwZBAwANlpr1/vbSV37TXX7ZcaYJTirezQMJn4HzLDOpBffGWOSjDH969pKD/Tcc+B2wwUXtL/tjXfdCB64/9b7A19YF1ZevoDly6dQWvoNiYn7M2LEI/TpMy6gffjcPjY+vJHVt67GU+Zh4MUDybo1i4gUzSMhIiIiIiKB5++ICQDqwgi/A4nmGGOygD1xVvdoaCCwrsH39XXHFEz0QNY6r3FMnOhMfNke89bOI++9PEbsM4I9JuwRnAK7GI+njNWrb2X9+vuJiOjLqFFP0a/f5ICvRLLlvS2suGIFlUsr6XtEX4bfM5y4sXEB7UNERERERKShdgUTu8oY0wd4FbjcWlva9HQzTXZaMsQYcyFwIUBmZmbAa5TQ+OEH+PlneOyx9re9/O7LoQL+ddO/Al9YF2OtpajoVfLyLqe2dgP9+1/IsGF3EBGREtB+KpdVkndlHlvnbCVmRAzj3h5HyjEpWoJVRGRXWQs+n7MMlc/XeOvosUC2216ftf7tt+fajrbz59rtq8o1/N7a8V05Fqh7hvIzWPdq7rs/+4G+zt82LV3TkWs74x6BON+Z996VfoPZflf77ixHHQUvvNDZVQRNyIIJY0wETijxvLX2tWYuWQ8MbvB9ELCx6UXW2seBx8FZLjQIpUoI5OZCbCycfnr72m0q28TXs74meUgyJx1zUnCK6yIqK/PIy/s/tm59j7i43Rk79hUSE38d0D7cxW7W3LaGDf/egCvWRfbd2Qz8v4G4IjWPhIgEgM8HtbXt2zwe5wHa4wn+fiDv11IoIC0zpn5zuXbeb+5Y063pfVo61p5rg9F++7GOfnbkPrvaZ0v3au67P/uBvs7fNi1d05FrO+MegTjfmffelX6D2b47/vKtvcPMu5k2gwljjAs4CPjKWlvbkU6M82vXXGCJtbalhSHfAi41xryIM+llieaX6JkqKuDFF+GUUyAhoX1tr370amyB5ZoHrumxv833eqtZt+4u1qy5A5crkuHD72PAgEtwuQKXI/o8PjY9sYlVN6/Cs9VD/z/1Z+g/hhKZHhmwPkQkRLxeqKpytsrK+q2mpuWH/9bO7crW9L5eb2j/LMLCIDzc2bbvN3estf2ICIiJaV/b7ZvL1Xjz51io220/tv1hv6WH//YEBR1tJyIiUqfNJx1rrc8Y86a1Nn4X+vkNcDaw0BjzU92xG4DMuj4eBeYAk4A8oBI4bxf6ky7s5ZehrKz9k15Wuit5+cmXiUqM4ooLrwhOcZ2spiaf+fMPo7LyZ9LSTmP48HuIihoQ0D6KPy4m7/I8KhZVkHRQEsPvG06f3QO7ooeI4AwVra5uHBa0tjUNFvzdamoCU68xzhJJkZFtb7GxkJTk37WRkf7fNyKi/oG/vaHC9gdeERER6Xb8/RXsF8aYX1trv+tIJ9bar6DZOSQaXmOBSzpyf+lecnNh5EjYf//2tZv6+lTcS91ccOUFRLV3fdFuoLa2gPnzD6a6eh3jx79DSsqkgN6/akUVK65eweY3NhOdFc3YV8aSelJqjx15ItIubjds21a/FRfXf5aVdTxU6IiYGOfBv+EWEwNxcZCWtvO55raYGIiO9j84iIys/y26iIiISIj5G0ysAd41xryJs3LGjrkdrLW3BKMw6ZmWLYOvvoKpU9v371+f9XH//fdjwg13XHtH8ArsJLW1hfz00yFUV69lwoR3SUo6IGD39pR6WPPPNay/bz0mwjD0jqEMumIQYdFhAetDpNNZ6wQITUOF5oKG5s5VVLTdx/aRAs1tffs2Hw74EyI03KKjnd/8i4iIiPQi/gYTMcAbdfuDglSL9AJPPun8Um7y5Pa1e/675yn9oZRDfncI6enpwSmuk9TWFtWFEquZMGFOwEIJ67XkP53PyhtX4i5w0+/cfgy9YyhR/XveaBPpIWpq2hcmND3W1kSDiYnO6wd9+zqfw4fX72//bLi//TM+3gkNwkO6kJWIiIhIr+HXv7KstZrvQXaZ2w3PPAPHHAP9+rWv7c3TbgYP3HvrvcEprpPU1hYxf/6hVFevZPz4d0hKOjAg99325TbyLsuj/MdyEvZLYPzb40nYu50zjYrsCq8XCgthw4b6bdMmJ0hoKWiorm79njExjcODjAwYPbrlQKHhfkKCk4qKiIiISJfj969/jDFjgN8DGdbaS40xo4Aoa+2CoFUnPcqcOVBQ0P5JL79e+TVrPljD6H1HM2HchOAU1wlqazczf/5hVFX9wvjxs+nb9+Bdvmf1mmpW/HUFRbOKiBoUxZgXxpB+errmkZDAqqhoHDg0t23atPOKDC7XzqHBwIGtj1ZouN8D55YRERERET+DCWPMKcDDwKvAH4BLgXhgKnBY0KqTHuXJJ52REpPaOafjVdOvggqYetPU4BTWCdzuLXWhxHLGjXubvn0P3aX7eco9rLtzHevuXgcGsm7NYvA1gwmL1W+IpR18Pigqqg8X1q9vPnQoKdm5bWKiEzIMHAhjxtTvN9zS0zV/goiIiIjsxN8RE7cBh1trfzLGnFZ3bD6we3DKkp5m0yZ45x24+ur2vaa9Ztsavn/le1KzUjn+6OODV2AIud1b65YEXcr48W+RnNzxbM/6LAXPF7DyupXUbqwl/Yx0ht05jOjB0QGsWHqEqir/Rjm43Y3bhYU5ieLAgTBqFBxySPOhQx8tOSsiIiIiHePvI2I6ThAB9Sty2Ab7Iq2aMcMZ1X3++e1rd/UjV0MhXPvQtT3idQS3u5j58w+nomIJ48e/SXLyER2+V8l3JeRdnkfZ92XE58Qz9uWxJO6XGMBqpVuwFjZvbnuUQ3Hxzm3j4+uDhYMOaj5wyMjQ3AwiIiIiElTG2razBWPMB8Bz1toZxpit1tpkY8xZwOnW2mODXmULcnJy7Ny5czure/GTtc78dBkZ8MUX/rcrrSkleUIyEQURbCvYRlQ3f7/c7d7G/PmHUVGxkHHj3iAl5egO3admQw0rr1tJwXMFRPaPZNi/hpFxdgbG1f2DG2mBzwdr18LChbBokbOtWeMEDhs3Qm1t4+tdLuc/uOaChoZbgiZEFREREZHgMcbMs9bmtHWdvyMm/gJ8YIy5AIgzxrwPjAQ6/ute6TW++gqWL4cbbmhfuzteuwPvci9/vOaPPSKUWLDgCCoqFjBu3OsdCiW8VV7W3b2OtVPXYr2WzBsyybw+k/A+WsKwRykqcoKH7SHE9s/y8vprMjMhOxv237/5wKFfPy1tKSIiIiLdhl8jJgCMMbHAscAQYB0w21pb3nqr4NKIie7h3HPhtdec19fj4vxr4/F56PubvlTOq6RgYwGpqalBrTGYPJ4S5s8/gvLyHxk79lVSU49rV3trLUWziljx1xXUrK0h9eRUsqdlEzM0JkgVS0hUVMDPP9eHD9sDiIKC+mtSUmD8eGcbN875HDtWIx1EREREpFsI9IgJrLWVxpivgVXAxs4OJaR7KC2Fl1+Gs87yP5QAePrrpyn/bzlHnHxENw8lSlmw4Ki6UOKVdocSZfPKyLs8j5KvSojbPY4xM8aQdGBSkKqVoHC74ZdfGocPCxfCqlXOe04AMTFO4DBpUuMQIiMDesDcKiIiIiIirfF3udBM4Hng10Ax0NcY8z1wprV2TRDrk27uxRehshIuuMD/NtZabr37VvDC9FumB622YPN4yliw4CjKyuay224vk5rq/6oiNfk1rLpxFflP5RORGsHIx0fS//z+mDA9pHZZ1jaeB2L759Kl9XNAhIXByJGQk+MMJdoeQgwbpmU0RURERKTX8nfExDPAPOAoa22FMaYP8I+64wcFqTbpAXJzneeuvff2v82nv3zKho83MHa/sYwbOy54xQWRE0ocTVnZf9ltt1mkpZ3gVztrLevvX8/qW1bjq/Yx+KrBDLlpCOGJmi+gS9m8ufl5IMrK6q8ZPNgJHo4+un4ExKhREK2lXEVEREREGvL3aWcv4AhrrRvAWltujLkW2BK0yqTbW7QIfvgB7r23faPRr77naqiAqTdPDV5xQeTxlLNw4SRKS79j7NiXSEs70a921mfJuyKPDQ9sIHlSMsPvG07siNggVyutqqxsPA/E9s/8/Ppr+vZ1QodzzqkfATFuHCRq6VYREREREX/4G0x8B0wEvm5wLAf4NuAVSY+RmwsREc78Ev7K25LHj6/9SPqwdI458pjgFRckXm8FCxceQ0nJt+y220zS0k72q531Wpb9aRn5T+Uz6IpBZE/PxmhugdDxeOrngWg4GeXKlfXzQERHO/NAHHVU/QiIceOgf3/NAyEiIiIisgtaDCaMMbc1+LoCmGOMeQdnRY7BwCTgheCWJ91VTQ08+yyccAK0Z+7Kqx65Corg+tuu73YP5k4ocSwlJV+x224vkJ5+il/tfLU+lpy1hKKXixhyyxCybs3qdj97t1NRAZ9+CnPmwDffwJIl9fNAuFwwYgTsuaczCmJ7CDFsmDNHhIiIiIiIBFRrIyYGN/n+Wt1nOlADvA7oZWlp1ltvwZYtcP75/rcpripm9ozZxPSNYcp5U4JXXBB4vZUsXHgc27Z9wZgxz5Gefpp/7aq8/Pz7n9k6ZyvDpg0j8+rMIFfaS1nrjIiYMwfefRc+/9xJz+LiYP/94Ygj6gOIMWM0D4SIiIiISAi1GExYa88LZSHSs+TmOnP/HX64/21ue+U2fL/4OP/a84mKigpecQFWH0p8zpgxz5KRcYZf7TxlHhYdv4htn29j5KMjGfDnAUGutJeprITPPnOCiDlznNcyAEaPhksucSal/O1voRv9XRMRERER6Yn8nurfGBMLDAf6NDxurf0m0EVJ97Z2LXzwAdx0k/8j32u9tTz+0OO4Il3cevWtQa0vkLzeKhYt+h3btn3K6NEzyMj4g1/t3FvdLDh6AWXzyhjz7BgyzswIcqW9RF5efRDx2WdQXQ0xMXDooXDVVU4YMXRoZ1cpIiIiIiIN+BVMGGPOAf4N1AJVDU5ZQGPPpZGnn3ZGzp/XjjE3T3zxBJVzK5l06iRS2zMpRSfyeqtZtOgEios/ZvTop+jXz79ZPmsLapl/xHwql1Yy9pWxpJ2QFuRKe7Dqaue1jO2vaPzyi3N85Ej4859h0iQ44AC9miEiIiIi0oUZu33G+dYuMiYfONta+2HwS/JfTk6OnTt3bmeXIQ34fJCd7WwffeRfG2st/Y/rT8E7BSxZsoTRo0cHt8gA8Hqr+fnnE9m69X1GjXqS/v3P9atd9bpq5h82n5r1NYx7YxzJhycHt9CeaNWq+iDik0+gqsoJHg4+2Akijj7a+QsoIiIiIiKdyhgzz1qb09Z1/r7KUQt8tksVSa/wySewejXccYf/bd5f9j4FnxYwYf8J3SKU8Plq+Pnnk9i69T1Gjcr1O5SozKtk/mHz8RR7mPD+BJL2TwpuoT1FTQ188UX9KxrLljnHs7Phj390goiDDnJe2RARERERkW7H32DiZuAeY8zfrbWbg1mQdG+5udC3L5x4ov9t/nrPX6ES7rzlzuAVFiA+Xw2LFp3M1q3vMnLkE/Tv79+yI+WLyllw+AJ8bh97fLIH8XvFB7nSbm7Nmvog4pNPnOU9o6KcAGLKFGdkxIgRnV2liIiIiIgEgL/BxHLgNuBiY8z2Ywaw1lo/pzeUnm7rVnj9dfjTn/x/pX9x4WIWvrGQftn9OPKwI4Nb4C5yRkr8nq1b32HkyMcYMOCPfrUrnVvKgiMX4IpysecXexK3W1yQK+2Gamvhq6/qX9FYvNg5npUFkyc7QcRBBznLe4qIiIiISI/ibzDxLDADeInGk1+K7PD8886o+wsu8L/NVY9cBUVw4z9vpEHo1eX4fLX8/POpbNkymxEjHmHAgAv9arfty20sPGYhESkR7P7x7sQM0+sGO6xb54QQ777rTEhSXg6Rkc5kldtf0Rg1Crrw3wsREREREdl1/k5+WQwkW38uDiFNftl1WAt77uksDzpvnn9tCisK6bdHP2K2xlC8qZjIyMjgFtlBPp+bxYtPZfPmNxgx4iEGDrzYr3Zb39/KohMXEZUZxe4f7U70oF6+MoTbDV9/Xf+KxqJFzvHMzPpJKw85BPr0af0+IiIiIiLSLQR68sungLNxRk2I7OR//4P58+Ghh/xvc+usW7F5lgtvuLCLhxKns3nzGwwf/qDfoUTRa0UsPn0xsbvFsvsHuxOZ3jV/vqDbsAHee88JIj76CEpLISICfvtbmDbNCSN2202jIkREREREejF/R0x8BUwEVgEFDc9Zaw8ITmlt04iJruPii+Gpp2DTJkjyY7GJKncVyb9JpnZ+LYUbC0lJSQl+ke3khBJnsHnzqwwffj+DBv3Fr3b5z+az9LylJOydwPg544noGxHkSrsQjwe+/bZ+roj5853jAwc6oyImTYJDD4V4Tf4pIiIiItLTBXrExBN1m8hOqqrghRfg5JP9CyUAHv70Yar/V83xpx/fRUMJD0uWnMnmza+SnX2v36HEhkc28MvFv5B0SBLj3hxHeB9//xPrxqx1lvN8+GF4/30oKXHe6dl/f5g61Qkjxo3TqAgREREREWmWX09N1tpngl2IdF+vvuo8i/o76aXP+ph631Twwl033xXc4jrA5/OwdOnZFBW9THb2dAYPvtyvdmunrWXlX1eScmwKu728G2HRPXzBGmth9mz417+cURKpqU46NWkSHHYYJCZ2doUiIiIiItIN+BVMGGPOb+mctfbJwJUj3VFuLgwbBgce6N/1by56k82fb2aPA/Zg1KhRwS2unZxQ4hwKC19k2LBpDB58ZZttrLWsvmU1a25fQ9ppaYx5dgyuCFcIqu0kHg/MmuUEEosWwZAh8O9/w/nnQ4xWHRERERERkfbxd5z52U2+9wOyga8BBRO92IoV8NlncPvt4PLzWfyGe2+Ayq43WsJaL0uXnkth4UyGDbuTzMyr/Whjybsijw33b6DfBf0Y9dgoTFgPfWWhuhqeftqZtHLlSmfSyhkz4PTTnQktRUREREREOsDfVzkObnqsbhTFmIBXJN3Kk086gcS55/p3/Y+bfmTp20sZMGIAhx16WFBraw8nlDiPwsLnGTr0X2Rm/rXtNl7Lsj8vIz83n0GXDyL7nmxMT5xHoawMHn0U7rkH8vNh4kRn/7jj/E+jREREREREWrArM/M9DWwGrglMKdLdeL3OL9CPOspZdMEfVz98NWyGm6fe3GUe4p1Q4gIKCp5l6NDbGTLkujbb+Gp9LDl7CUWzihhy8xCy/p7VZX6egCkqggcecF7T2LbNmTfi+efh4IM1kaWIiIiIiASMv3NMNP21aCxwFrAt4BVJt/H++7BxIzz4oH/XbyjdwKczPyUuOY7zz25x2pKQstbHsmV/oqDgGbKybmPIkBvbbOOt8vLzKT+z9Z2tDLtrGJnXZIag0hBatw6mT4fHH3eWXDnxRLj+eth7786uTEREREREeiB/R0x4ANvk2AbgT4EtR7qT3FxIS4Njj/Xv+lteugW7wjLl5ilERkYGtzg/OKHEheTnP0VW1q1kZd3cZhtPuYdFxy9i22fbGPHICAZe5OdQke5g2TK480547jlnxY0zz4Rrr4UxemNLRERERESCx99gYmiT7xXW2s2BLka6j8JCeOstuOwy8CdjKK8t57nHnyMsKozrL78++AW2wVofy5f/mfz8XIYMuYWsrL+12cZd7GbhpIWU/reU0TNG0++sfiGoNATmzXNW2HjtNYiKgj//Ga6+2lltQ0REREREJMj8nfxyTbALke7l2WedVSMvuMC/6x/4+AFqf6zlpDNPIjk5ObjFtcEJJaawadN/GDLkJrKybm2zTW1hLfOPmE/lkkrGvjyWtBPTgl9oMFkLn3/uBBIffACJic7rGpddBunpnV2diIiIiIj0Isbapm9oNDhpzKfs/ApHQ9Zae2jAq/JTTk6OnTt3bmd132tZC2PHQlISfPNN29d7fV5SJ6Wy7YNtLFu6jJEjRwa/yBZYa/nll0vYuPERMjOvZ+jQf7Y5aWX1+mrmHzafmrU1jHtjHMlHdG6wskt8Ppg92wkkvvvOCSGuvBIuusgJJ0RERERERALEGDPPWpvT1nVtjZh4roXjA4G/4EyCKb3Md9/BkiXwn//4d/3L819m25fbyDkopwuEEv/Hxo2PMHjwtX6FElUrqph/2HzcW91M+GACSfsnhajaAPN44KWXYOpUWLQIsrLgoYfgvPMgJqazqxMRERERkV6s1WDCWpvb8LsxJgW4HmfSy5eA24JXmnRVubkQFwennurf9TfddxNUwtSbpga3sFZYa8nLu4yNGx9i8OBrGDbsX22GEhWLK5h/2Hx8tT72+GQP4veKD1G1AVRdDU89BdOmwapVzlCXZ5+F006DiIjOrk5ERERERMTv5UITgGuAS4HZwK+stSuCWZh0TeXlzi/eTzsN4v14Tv927besmLOCQSMHccjBhwS/wGY4ocQVbNjwIIMGXcWwYXe2GUqUzStj/pHzcUW62PPzPYkbGxeiagOktBQefRTuvRfy82GffZz9444DV9PVf0VERERERDpPq8GEMSYGuBy4CvgM2N9a+3MI6pIuatYsJ5zwd9LLax+7FjbDLXfd0mYYEAzWWlasuIoNG+5n0KAryM6e1mYd277axsJjFhLeN5w9Pt6DmOxu9KpDURHcf7/zmsa2bXD44fDCC3DQQdAJf/4iIiIiIiJtaWvyy3wgDJgGNDvLpLX2k+CU1jZNfhl6v/kNbNnizDHR1nPu6m2rGbrXUPqU9GHLxi1E+rOuaAA5ocQ1rF8/nYEDL2P48HvbDCW2friVRb9bRFRmFLt/tDvRg6JDVO0uWrsW7r7bmfijuhpOPNFZZSOnzXlmREREREREgiJQk19W46zKMaWF8xYY1s7apJtassRZheOuu/z75ftNM2+ClXDp3y4NeSgBsHbtnXWhxKV+hRJFbxSx+LTFxI6JZfcPdicyPfQ1t9vSpXDnnfBc3Ty1Z50F114Lo0d3bl0iIiIiIiJ+amvyy6wQ1SHdwJNPQng4nHNO29eWVJfwUu5LhEWFcc1frgl+cU1UVa1g9epbSU09meHDH2gzlCh4voAlk5cQnxPPhHcnENG3i08MOXeus+Tn669DdDRMmQJXXw2ZmZ1dmYiIiIiISLv4NfmliNsNM2bAscdCRkbb10//cDqenzycevapJCcnB7/ABpxlQf+CyxXBiBH3txlKbHxsI8unLCfpoCTGvTmO8Pgu+p+FtfDZZ04g8eGHkJgIN9wAl10GaWmdXZ2IiIiIiEiHdNEnMOlqZs+GwkL/Jr10e93c/+D94IPbb7g9+MU1sWXL22zdOofs7LuJihrY6rVr717LymtWknxMMmNfHktYTFiIqmwHnw/eftsJJL7/3kmG7rwTLroIEhI6uzoREREREZFdomBC/JKbC/37w1FHtX3tC/97gdKvStnnkH0YMWJE8ItrwOutIi/vMmJjd2PgwL+0eJ21ltW3rmbNbWtIOy2NMc+OwRXRxZbR9HjgxRdh6lT4+WfIyoKHH4Zzz4WYbrRSiIiIiIiISCsUTEibNm6Ed9915lQMb+NvjLWWW+6/Bapg6s1TQ1NgA//P3n2HWVWdDRu/11R6h2HoVYyKFbEg9h6NvSvY0MREjV/UxDeamJjEWJJoYtSgrwpGjQaMFUV9bXNAATGKGqVXYQqdmYFhzsz+/jgTYOhtzply/67La89Ze+29n+OePcN5Zq1nzZv3e9asmcN++71HWtrm60REUcTMn8xkwZ8W0PHKjvQb3o+QXouW0ly9Gp58Eu67D+bMgX32SRS3vOCCbd8ASZIkSapj/JSjbXr77cRsgosu2nbfD+Z8wLyx8+i2ZzeOOvKomg9uA6WlM5g37x46dLiY1q2P3myfqCJi2vensejxRXS+sTN9/tiHkFaLkhITJ8J55yWW/zz0UHjwwURhj7RaNppDkiRJknYTExPaprw8aN0a9t57231/9ujPYDH88v5fbrPo5O4URREzZtzxqjlWAAAgAElEQVRAWloWvXvft9k+leWVfDPkGwr/UUj327vT49c9khrjVkURDB8ON9wAnTrB//0fHHPM9q3LKkmSJEl1mIkJbVMsBoMGbfuP9tOWTGPCPyfQvF1zLr3o0uQEV2XJkldYuvQNevf+I9nZnTbZX7Gmgv+c/x+WvLqEXvf0otuttWhZzdWr4brr4KmnEkU8/v53aNs21VFJkiRJUlIkZXx4COGJEEJhCOHLLew/OoSwIoTwWdV/v0hGXNq2oiKYOhWOOGLbfW9/9naYDTdcfwNZWVk1H1yViopSpk+/kaZN96Fz5x9tsj9eHOeL075gyWtL6Ptw39qVlJg1Cw4/PJGU+MUvEsufmJSQJEmS1IAka8TEU8BDwMit9MmLoui05ISj7TVuXGK7rcTEktIlvPjki2RkZ/CT639S84FtYN68uykrm8t3vvPBJgUvy5eX88WpX7By4kr2HLknHS/tmNTYtmrMGLj00sQ0jldfTdSSkCRJkqQGJikjJqIo+hBYmoxraffKy4PsbBgwYOv97ht7HxWfV3D+JefTunXr5AQHlJZOZ968e8nJuZRWrY6stm9t0Vo+P+ZzVn2yir3/uXftSUpUVsKddyYSEd26wSefmJSQJEmS1GDVplL/h4UQPg8hvBFC2I4yi0qGWAwGDkwkJ7akLF7GQw8/BBH86rZfJS22KIqYPv160tIa0avXfZvs+8+F/6F0ain9X+1P+7PaJy2urVq6NJGE+NWv4LLLYPx46N071VFJkiRJUsrUlsTEp0D3KIr2A/4CvLSljiGEa0IIn4QQPikqKkpagA1RSQl8+um2p3E8OfFJSsaVcPjxh9OnT5/kBAcsXvwSy5aNpWfPX5OdXX00RP6T+Sx/dzl9/tSHNie1SVpMW/Xvf8NBB8E778AjjyTqSjRpkuqoJEmSJCmlakViIoqilVEUFVd9PQbIDCG020Lf4VEUDYiiaED79rXkr+D11MSJEI9vPTERRRF3PXQXrIa7b787abFVVJQwY8aPadq0P506/bDavrL8MmbePJOWg1uSOyw3aTFt1ZNPJopcxuOJ+THf/75LgUqSJEkStSQxEULoGELiU1oIYSCJuJakNirl5SU+Ox9++Jb7jJ0xloVvLaTHXj0YPHhw0mKbO/d3lJXNo2/fv5KWVr2G64wbZ1BRUkG/x/oR0lL84b+sDK69Fq68MvE/cvJkOOSQ1MYkSZIkSbVIUlblCCE8BxwNtAshLAB+CWQCRFH0KHAu8IMQQhxYDVwYRVGUjNi0ZbEY9O8PrVptuc/P//ZzWAJ3/ulOQpJGAJSWTmP+/PvIybmMVq2qJ0MWv7KYoheK6PmbnjTpl+JpEvPmwbnnwqRJ8LOfwV13QUayFsKRJEmSpLohKZ+Soii6aBv7HyKxnKhqiXgcPvoIhgzZcp8vC7/k0xc/pUX7Flx84cVJiWt9wcvG9Op1b7V98ZVxpl03jab9m9L1lq5JiWeL3nkHLrwQ1q6FF1+Es85KbTySJEmSVEvViqkcqn2mTIHi4q3Xl/j5Mz+H2fDjG35MZmZmUuJavPhFli17i54979qk4OWs22axduFa+j3Wj7SsFH1rV1bC3XfDSSdBx46JpUBNSkiSJEnSFjmuXJsViyW2W0pM5Bfn89rI18holMGPf/jjpMSUKHh5E02b7kunTtdV27di3AoWPryQzjd2psUhLZISzyZWrIChQ+HllxOjJR57DJo1S00skiRJklRHmJjQZuXlQffu0HULMyJ+/8bvqZxSySVXXULr1q2TEtPcub+lrGw+3/nOs9UKXlaWVTJ12FSyu2XT8zc9kxLLJr74As4+G+bMgQcfhOuvd9UNSZIkSdoOJia0iShKjJg47rjN7y8tL2X4o8Mhgl/+9JdJiam0dCrz599PTs5QWrWqPoxj7t1zKf26lP5j+pPRLAXf0s8+C8OGQYsW8N57W5//IkmSJEmqxhoT2sSsWZCfv+XP149PeJzVH61m8ImD6d27d43Hs77gZRN6976n2r6Sr0qY97t5dLikA21PaVvjsVSzdi3ccANccgkcdBB8+qlJCUmSJEnaQY6Y0Ca2Vl+iMqrktw/9FlbDb3/+26TEU1Q0mmXL3qZPn7+QlZWzrj2qiJh69VTSW6TT5099khLLOgsXwnnnwfjxcNNNcM89kKQCoJIkSZJUn5iY0Cby8qB1a9hrr033vfrNqxS+U0jvfXpzRBJGB8TjxcyceRPNmu1Pp07fr7bv20e+ZeXHK9nz6T3Jap9V47Gs88EHcMEFiWVLnn8ezj8/edeWJEmSpHrGqRzaRCwGgwZB2ma+O27/2+2wBO687U5CEoo7zp37G8rKFtC371+rFbxcM38Ns2+bTeuTWpNzSc5WzrAbRRH84Q+J4hstW8LEiSYlJEmSJGkXmZhQNUVFMHXq5qdxTF44mS9f/pKWHVpywXkX1HgsJSVfs2DBH+jY8Qpatjx8XXsURUy/bjpRZcQej+yRlAQJq1YlkhA33wzf+x5MmrT5ISWSJEmSpB1iYkLVjBuX2G4uMXH7s7fDHPjJjT8hs4brKfy34GV6ejN69fp9tX1FLxSx5LUl9PxNTxr3bFyjcQDw9dcwcCC8+CLcey+MHp1YgUOSJEmStMusMaFq8vIgOxsGDKjePn/FfMb+fSyZjTK5/rrrazyOoqJ/snz5/9G371/Jyuqwrr18STnTr59O84Ob0+WGLjUeB6NGwRVXQOPG8PbbcOyxNX9NSZIkSWpAHDGhamKxxOCA7Ozq7Xe/cTfRlxGXDL2EVq1a1WgM8fgqZsy4iWbNDqBTp2ur7Zt580ziy+L0e6wfIb0Gp3DE43DLLYmVN/beO7EUqEkJSZIkSdrtTExonZKSxOfvjadxrCpbxRN/ewIq4Y5b76jxOObOvYu1axfSt+/DhJC+rn3pO0vJfyqfrrd2pdl+zWougIICOOEEuP9+uO66xCocXZIwOkOSJEmSGiCncmidiRMTAwU2TkyM/nw0ZRPKOPKkI+nVq1eNxlBS8h8WLPgTHTteRcuWh65rryitYNq102jctzHd7+hecwF89BGcey4sWwYjR8Jll9XctSRJkiRJjpjQerEYhACHH169feSokbAa7ri5ZkdLJApe/oj09Ob06nV3tX1z7pzDmllr6PdYP9IbpW/hDLt0cXjoITjqKGjUKJGgMCkhSZIkSTXOxITWycuD/v1hwxISURQxMW8iGY0zOPqoo2v0+oWFz7N8+Xv07PlbsrLar2tf9ekq5v9hPrnDcml1VA3UtygpSSQhrr8eTjoJPvkE9ttv919HkiRJkrQJExMCElM4Pvpo02kc3yz+hpKvS9j7kL3JyKi5mT/x+CpmzvwJzZodSKdO16xrryyvZOpVU8nqkEWve2tgGsmMGXDYYfDss3DXXfDyy9C69e6/jiRJkiRps6wxIQCmTIHi4k0TE8++/yysgHNOO6dGrz937q9Zu3Yh++zzYrWClwv+tIDiz4rZe/TeZLbK3L0XfeUVGDIE0tPhjTcSoyUkSZIkSUnliAkBifoSsGli4qUxLwFw8ZkX19i1S0q+YsGCB8jNvZoWLQ5Z1146o5Q5v5xDu7Pa0f7s9ls5ww6qqIDbb4czzoA+fWDyZJMSkiRJkpQijpgQkKgv0b07dO26vq28opyvJ3xN85zm9O7du0auu2HBy549767WPu2aaYSsQN+H+u6+Cy5eDBdfDG+/DVdfDX/5S6LYpSRJkiQpJUxMiChKjJg47rjq7bHZMSpmVnDYmYfV2LULC//B8uXvs8cej5KV1W5de/6T+Sx/bzl7PLoH2Z2yd8/FJk1KLAVaUACPPZZITEiSJEmSUsqpHGLWLMjP33Qax4gxI2AtXHrWpTVy3Xh8JTNn/oTmzQeQm7s+SVCWX8bMm2fScnBLcofl7vqFoiiRiDjiiMR6qOPGmZSQJEmSpFrCxIS2WF/inbffgQCnn3x6jVx3zpxfsXZtPn37Plyt4OWMG2dQUVJBv8f6EdLCrl1k9epEEuKaa+CYYxL1JA46aBcjlyRJkiTtLiYmRCyWWCFzr73Wty1fs5xvP/uWznt2plWrVrv9msXFX7JgwYPk5g6jRYuD17UvfmUxRS8U0eMXPWjSr8muXWTevES25Ykn4I474PXXoW3bXYxckiRJkrQ7WWNC5OXBoEGQtkGa6tXPXoVv4YTrT9jt10sUvPwhGRkt6dXrd+va4yvjTLtuGk37N6XrLV23cobtUFwMJ58MCxcmlgU9vWZGfUiSJEmSdo0jJhq4oiKYOnXTaRx/f/nvEMHQs4fu9msWFj7LihUf0qvX78nMXD+CYdZts1i7cC39Hu9HWtYufGtGUWL6xtSp8OKLJiUkSZIkqRZzxEQDN25cYrtxYuLjDz8mo3EGgw4ftFuvF4+vYObMm2nefCC5uVeta18xbgULH15Ilx93ocXAFrt2kT//GZ5/Hu6+G449dhcjliRJkiTVJBMTDVwsBtnZMGDA+rZZS2ex8j8r6X9wfzIzM3fr9ebMuZO1awvYZ59XCSExKqKyrJKpw6aS3T2bHnf12LULjBsHN98MZ5wBP/3prgcsSZIkSapRJiYauLw8GDgwkZz4r2c/fBaWwxmnnLFbr1VcPIUFC/5Cp07X0qLF+kzI3LvnUvp1Kf3H9Cej2S58S+bnw3nnQY8eMGJEYmlQSZIkSVKtZo2JBqykBD79dNNpHKNfGw3AZWdfttuutb7gZSt69vzt+hi+KmHe7+bR4ZIOtD1lF1bMiMfhwgth+XIYPRpattwNUUuSJEmSapojJhqwiRMTn+c3TExUVFbw1Udf0ax9M/r27bvbrlVQ8HdWrIjRr9/jZGa2ASCqiJh69VTSW6TT5099du0Ct90GH3wAI0fCvvvuhoglSZIkScngiIkGLBZLzHY4/PD1bRPmT6B8ZjkHH3kwYTdNhUgUvLyF5s0PoWPHK9a1f/vIt6z8eCV9HuhDVvusnb/Aiy/C/ffDD34Al+2+UR6SJEmSpJrniIkGLC8P+veHVq3Wt414fQSUwSVnXrLbrjN79i8pLy9k333HrCt4uWb+GmbfNpvWJ7Um55KcnT/51Klw+eWJQhl/+tPuCViSJEmSlDSOmGig4nH46KNN60uMfWssBDjr1LN2y3WKiz/n22//QqdOP6B58wOBqnoT100nqozY49E9dn5kRkkJnHNOonLnqFHVK3hKkiRJkuoER0w0UFOmQHFx9cRE8dpi5n06j9w9cmnTps0uXyOKIqZN+yGZmW3o2fM369qLXihiyWtL6P3H3jTu0XhnTw7DhsHXX8PYsdC16y7HK0mSJElKPkdMNFCxWGK7YWLi9SmvEy2IOPb4Y3fLNQoKnmblynH06nUPmZmtAShfUs7066fT/ODmdLmhy86f/KGH4Lnn4K674Pjjd0u8kiRJkqTkc8REAxWLQbdu1QcaPP3y0xDB5edcvsvnLy9fzsyZt9CixaF07Lj+fDNvnkl8WZx+b/cjpO/kFI7x4+H//T84/XT42c92OVZJkiRJUuo4YqIBiqJE4cvBg6u3j39/POmN0jly0JG7fI05c35Befli+vb967qCl0vfWUr+U/l0vbUrzfZrtnMnLiiA886D7t0TS4Om+S0sSZIkSXWZIyYaoFmzID+/+jSOb1d+y7KvlrHXQXuRlbULS3cCq1Z9xrff/rVawcuK0gqmXTuNxns0pvsd3XfuxPE4XHghLFsGY8ZUX05EkiRJklQnmZhogDZXX+KZD56BZXD6Kafv0rmjqJLp039IZmZbeva8a137nDvnsGbWGvZ/f3/SG6Xv3Ml//nN4/30YMQL222+X4pQkSZIk1Q4mJhqgWAxat4a99lrfNuq1UQAMPWfoLp07P38kK1eOp1+/J9cVvFz16Srm/2E+udfk0uqonRzl8K9/wb33wve/D0OG7FKMkiRJkqTawwn6DVBeHgwatL48Q2VUyZTxU2jSrgl79ttzp89bXr6MWbNupUWLw+nYMZE8qCyvZOpVU8nKyaLXPb127sTTpsHQoXDwwfDAAzsdnyRJkiSp9jEx0cAUFcHUqdWncfz7239TNr2Mg444iBB2cqUMYPbsOygvX1Kt4OWCPy2g+LNi+j7Ul8xWmTt+0pISOOccyMqCUaMgO3un45MkSZIk1T5O5Whgxo1LbDdMTDz5+pNQBhefcfFOn3fVqk9ZuPAROnf+Ic2b7w9A6YxS5vxyDu3Oakf7s9vv+EmjCK69Fr76Ct58M7G+qSRJkiSpXjEx0cDEYolBBwMGrG974603IMB5p5+3U+dcX/CyHT16/LqqLWLaNdMIWYG+D/XduWAffhieeQbuugtOPHHnziFJkiRJqtVMTDQwsRgMHLh+RsSa+BpmfzKbDn060LZt2506Z37+U6xc+TF77jmCzMxEccv8J/NZ/t5y9vjbHmR32onpFx9/DDfdBKedBv/zPzsVlyRJkiSp9rPGRANSUgKTJ1efxjH2q7FE8yOOPu7onTpneflSZs36KS1bHkFOzmUAlOWXMfPmmbQ8siW5V+fu+EkLC+Hcc6FrVxg5cn2VTkmSJElSveOIiQZk4kSIx6snJka8NAIiuPzsy3fqnImCl8uqCl4mCmfOuHEGFaUV9Bvej5C2g8U043G46CJYsgQ++iixrqkkSZIkqd4yMdGAxGIQAhx22Pq2vPfySMtO49gjj93h861aNbmq4OUNNGu2LwCLX1lM0QtF9PxNT5r0a7LjQd5xB7z7Ljz5JOy//44fL0mSJEmqUxwj34DEYrDPPusHIRSWFLL4i8X0PbAv2Tu4DGcUVTJt2g/JzOxAz56/AiC+Ms6066bRtH9Tut7SdccDfPll+P3v4Zpr4PLLd/x4SZIkSVKdY2KigYjHYfx4GDx4fdtzHz4HS+HUk07d4fPl5z/JqlUT6N37fjIyWgIw67ZZrF24ln6P9yMtawe/taZPhyFDEsuFPPjgDscjSZIkSaqbTEw0EFOmQHFx9foSL7z6AgBXnnvlDp2rvHwpM2f+lJYtB5OTcwkAK8atYOHDC+lyYxdaDGyxY8GVlsI550BGBowaBY0a7djxkiRJkqQ6yxoTDUQsltj+NzERRRH/Hv9vGrdtzN577b1D55o9++fE48vXFbysLKtk6rCpZHfPpsddPXYssCiC738fvvwS3nwTunffseMlSZIkSXVaUkZMhBCeCCEUhhC+3ML+EEL4cwhhRghhSgjhwGTE1ZDEYtCtW2IFToCvCr5i9dTVHHD4AetW09geK1d+wsKFf6NLlxto1qw/AHPvnkvp16Xs8egeZDTbwVzXo4/C00/Dr34FJ564Y8dKkiRJkuq8ZE3leAo4eSv7TwH6Vv13DfBIEmJqMKII8vKq15d44vUnYA1c8L0LduA8lUyffh1ZWTn06HEnACVflTDvd/PIuTSHtie33bHAJkyAG2+EU0+Fn/98x46VJEmSJNULSUlMRFH0IbB0K13OAEZGCR8DrUIIucmIrSGYNQvy86vXlxgzdgwEuPjMi7f7PIsW/S+rVk2qKnjZgqgiYurVU0lvkU7vP/besaCKiuDcc6Fz58SIiTTLnUiSJElSQ1Rbakx0BuZv8HpBVdui1IRTv2xcX2JtxVqmT5pOu17taNeu3Xado7x8CbNm/YyWLY+kQ4dEMuPbR75l5ccr2fPpPclqn7X9AVVUwMUXJ5IT48dDmzY78nYkSZIkSfVIbfkz9eaKHESb7RjCNSGET0IInxQVFdVwWPVDLAatWsFeeyVev/vNu1TOq+TIY47c7nPMmvU/xOMr1hW8XDN/DbNvm03rk1qTc0nOjgX0i1/AO+/Aww/DgZYTkSRJkqSGrLYkJhYAXTd43QVYuLmOURQNj6JoQBRFA9q3b5+U4Oq6WAwGDVo/W+LJfz0JlXD5uZdv1/HFxV+waNFjdOlyI82a7UMURUy/bjpRZcQej+6xQ8UzeeUV+N3v4Oqr4codW6ZUkiRJklT/1JbExCvAkKrVOQ4FVkRR5DSO3aCoCL75pnrhyw/e/YC0rDROPHr7VsFYtOh/CSGT7t0TBSqLXihiyWtL6PnbnjTu0Xj7g5kxA4YMgYMOgr/8ZUfehiRJkiSpnkpKjYkQwnPA0UC7EMIC4JdAJkAURY8CY4BTgRlAKXBFMuJqCMaNS2z/W19i2eplFEwpoM/+fcjOzt7m8ZWV5RQWPkvbtqeTmdmG8iXlTL9+Os0Pbk6X67tsfyClpXDOOZCeDqNGQaNGO/FuJEmSJEn1TVISE1EUXbSN/RHww2TE0tDEYpCdDQMGJF4/P+55WAKn/PCU7Tp+6dI3KS8vomPHoQDMvHkm8WVx+r3Tj5C+nVM4ogh+8AP44gsYMwZ69NiJdyJJkiRJqo9qy1QO1ZBYDA4+OJGcAHju5ecAuPKc7avvkJ8/gszM9rRpczJL31lK/lP5dL21K832bbb9QQwfDiNHwi9/CSefvKNvQZIkSZJUj5mYqMdKSmDy5Or1JSaPm0yj1o3Yr/9+2zy+vHwpS5a8Sk7OJURr0ph27TQa79GY7nd03/4gJk2CG26AU06BO+7YiXchSZIkSarPTEzUYxMnQjy+vr7E9MXTKfmmhH0P23e7VtIoLPwHUbSWnJwhzLlzDmtmraHf8H6kN0rfvgAWL07UlejUCf7+9/XLgkiSJEmSVCUpNSaUGrEYhACHHZZ4/cTrT8BqOO97523X8fn5I2natD9hXl/m/+ETcq/JpdVRrbbv4hUVcPHFUFiYqMDZps1OvgtJkiRJUn3mn7DrsVgM9tkHWrdOvH71zVcBuOzMy7Z5bGnpVFatmkDHjkNZNHwRISPQ87c9t//id94Jb78NDz2UWB5UkiRJkqTNMDFRT8XjMH78+voSFZUVfDPhG9r0bENOTs42j8/PHwGk067lhRQ8XUD7s9uT1S5r+y7+2mvwm9/AlVfC1Vfv/JuQJEmSJNV7JibqqSlToLh4fX2JD6d/SMXcCgYdPWibx0ZRBQUFT9OmzUmsfC2D+LI4ucNyt+/Cs2bBZZfBAQckRktIkiRJkrQVJibqqVgssf1vYuKJl56AShh69tBtHrts2XuUlS2gY8chLHpsEY16NaLV0dtRW2L16kSxyxBg9Gho3HgX3oEkSZIkqSEwMVFPxWLQrRt07Zp4/e477xIyA989/rvbPLagYCTp6S1psvwElr+/nNyrcwlp21jFI4rguuvg888TK3D03IF6FJIkSZKkBsvERD0URYnExH9HS6wqW8XCzxbSY78eNGrUaKvHxuOrKCoaTYcOF1DwxDJIh46Xd9z2RR97DJ56Cu64A049ddffhCRJkiSpQTAxUQ/NmgWLFq0vfDnq41GwGE468aRtHltUNJrKylI6tLuM/KfyaXtaW7Jzs7d+0CefwPXXw0knwS9+sRvegSRJkiSpoTAxUQ9tXF/imZeeAeCqc6/a5rEFBSNo3LgP5R/uQXlBOblXb6Po5ZIlcO65kJsLzzwD6em7ErokSZIkqYExMVEPxWLQqhXstVfi9aQPJ5HVMouD9j9oq8etWTOX5cvfJydnCPmP55PVOYs2J7fZ8gEVFXDJJYnhGaNGQdu2u/FdSJIkSZIaAhMT9VAsBoMGQVoazFs+j5Vfr6T/Yf0JYesFLPPznwagVeX5LH1zKblX5JKWsZVvkV//GsaOTSwLOmDA7nwLkiRJkqQGwsREPVNUBN98s76+xP++/r+wGs4+7eytHhdFEQUFI2nV6miWP50NEXS8aitFL8eMSSQmrrgCrr56N74DSZIkSVJDYmKinhk3LrH9b32Jl8a8BMAVZ1+x1eNWrvyI1aunk9NhCIueWETr41vTuEfjzXeePRsuvRT23x/++lfYxkgMSZIkSZK2xMREPROLQXZ2YmZFZVTJ1xO+plX3VuTmbr2IZX7+CNLSmpA+5RjK5pWRO2wL/VevhnPOSaxJOno0NN5C8kKSJEmSpO1gYqKeicXg4IMTyYkJsydQPrucQ486dKvHVFSsobDwedq3P5vCx4vJbJdJuzPabb7zj34E//43PP009OpVA+9AkiRJktSQmJioR0pLYfLk9dM4HnvxMaiEoWcP3epxS5a8QkXFCtpmX8ySl5eQMzSHtKzNfGs8/jg88QTcfjucdloNvANJkiRJUkNjYqIemTAB4vH1hS/feecdQkbgjBPP2Opx+fkjyM7uwurRexLFI3Kv3sw0jsmTE6MlTjwR7rxz9wcvSZIkSWqQTEzUI7FYog7lYYfB6vLVLPh0AV37d6XxVupAlJXls3TpWDp0uIT8xwtpeURLmu7ZtHqn5csTdSVycuCZZyA9vYbfiSRJkiSpoTAxUY/EYrDPPtC6Nbw08SWioojjTzx+q8cUFj4LVNB0wdmsnrZ680UvH3oI5s6F55+HdluoPSFJkiRJ0k4wMVFPxOMwfvz6+hJPv/Q0AMPOHbbV4/LzR9C8+UCWPd6c9JbptD+3ffUOq1fDn/8Mp54Kh269iKYkSZIkSTvKxEQ9MWUKFBevry/x0fsfkdkik4EHDtziMatWfUZJyRTat7iUolFF5FySQ3qTjaZpjBgBRUXw05/WYPSSJEmSpIbKxEQ9EYsltkccAYtWLmL5f5az96F7k5a25VtcUDCCEDKJ3jmayjWVmxa9rKiA+++HQw5Zn/GQJEmSJGk3MjFRT8Ri0K0bdO0KT775JJTCGadueTWOyspyCgqeoW3b0yl8dA3NDmpG8wOaV+/0r3/BzJlw662JqpqSJEmSJO1mJibqgShKJCb+W1/ixddfBODqc6/e4jFLl46lvLyIFqvOo2RKyaajJaII7rkH+vaFM7a+3KgkSZIkSTsrI9UBaNfNng2LFiVmW0RRxJcffUnLbi3p0rnLFo8pKBhBZmZ7SkfsQ1qTpeRcnFO9w/vvwyefwN/+5vKgkiRJkqQa44iJeiAvL7E94gj4dN6nlM0qY+DgLRe9LC9fyuLFr9C+9aIXveAAAB5bSURBVIUUPbOMDud3IKPFRjmqe++FDh1gyJAajFySJEmS1NCZmKgHYjFo1Qr22gsee/ExqIBLzrpki/0LC58nitaS+el3qSiuIHfYRtM4pkyBN9+EG2+ERo1qOHpJkiRJUkPmVI56IBaDQYMgLQ3eevstQkbgvFPO22L//PwRNG26D0v/2o4m36mgxWEtqne47z5o2hR+8IMajlySJEmS1NA5YqKOKyqCb75JTONYW7GWOZ/OodPenWjSpMlm+5eWTmXVqgm0ji5k1ceryB2WS9hwxY25c+G55+Caa6B16yS9C0mSJElSQ2Vioo4bNy6xHTwYXv3kVaKCiOOOP26L/fPzRwJpxEcfTcgK5Fy2UdHLBx5ILA160001F7QkSZIkSVVMTNRxsRhkZ8OAATDiXyMAuOrcqzbbN4oqKSh4mtatTmTx4xHtzmpHVrus9R2WLoXHHoOLL4auXZMRviRJkiSpgTMxUcfFYnDwwYnkxPj3x5PRPIMjBh6x2b7Ll79HWdl8Gs8+k/jSOLlXb1T08pFHoKQEbr45CZFLkiRJkmRiok4rLYXJkxP1JZaULGHJl0vYc+CepKVt/rbm548kPb0lJY/uR6OejWh97AY1JFavhgcfhFNPhf79k/QOJEmSJEkNnYmJOmzCBIjHE/Ulnhr7FJTA90753mb7xuPFFBWNpk2js1nx1hpyr8olpG1Q9HLEiEQlzVtvTU7wkiRJkiRhYqJOi8USdSoPOwz++eo/ARh23rDN9l28eDSVlSWkvXcypEHHKzqu31lRAfffDwMHwpFHJiN0SZIkSZIAyEh1ANp5sRjss09iVc/PP/qc5l2a06Nbj832zc8fQaNGvVn6p860/W4Lsjtlr9/5r3/BzJlwzz2JTIckSZIkSUniiIk6Kh6H8eMT9SW++vYr1sxYw0FHHLTZvmvWzGX58vdosfxcyvPLyR22QdHLKIJ774U+feDMM5MUvSRJkiRJCY6YqKO++AKKixOJib/9629QARefcfFm+xYU/B2AspFHkdUpizantFm/84MPYNIkePRRSE9PRuiSJEmSJK3jiIk6Ki8vsR08GN58601Ih4tOu2iTflEUkZ8/guaNBrPi+cZ0vKIjaRkb3PZ774UOHWDo0CRFLkmSJEnSeiYm6qhYDLp1g9zOcWZOmknuXrk0a9Zsk34rV37M6tXTyZpyOlRC7pUbTOOYMgXeeANuvBEaNUpi9JIkSZIkJZiYqIOiKJGYOOIIGPvZWCrzKzn62KM32zc/fwRpaY1Z9ccDaH18axr3arx+5333QdOm8IMfJCVuSZIkSZI2ZmKiDpo9GxYtSiQmnhz9JABXnXfVJv0qKtZQVPQ8Lcq/y9qpGeRevcFoiblz4bnn4JprEst6SJIkSZKUAiYm6qAN60vkvZdHRrMMjjnsmE36LVnyKvH4cqLXTySjbQbtzmy3fucDDySWBv3xj5MUtSRJkiRJmzIxUQfFYtCqFXTptZLCLwrpO6AvaWmb3sr8/BFkZXRmxcO96TikI2nZVX2WLoXHHoOLLkoUqpAkSZIkKUVMTNRBsRgMGgRPvzMCiuG0U07bpM/atQUsXfomTeafAWVp5A7bYBrHI49ASQnccksSo5YkSZIkaVMmJuqYoiL45ptEfYnnX30egGvPv3aTfgUFzwAVrP7bYFoMakHT7zRN7Fi9Gv78ZzjlFOjfP4mRS5IkSZK0KRMTdcy4cYnt4MHwWewzmnZqSu8evTfpl58/kiYcSNkHHasXvRw5EgoL4dZbkxSxJEmSJElbZmKijonFIDsbWnWdTsmMEg4cdOAmfYqLP6ek5HPSPzqV9BbpdDivQ2JHRQXcfz8cfDAcdVSSI5ckSZIkaVMZqQ5AOyYWS+QVnhzzN4jDBd+7YJM++fkjCCGT4gcGkntxDulN0xM7XnoJZsyAUaMSK3JIkiRJkpRijpioQ0pLYfLkRH2J1998HdJhyBlDqvWprCynoOAZmqw4jqiw+fqil1EE99wDffrAmWemIHpJkiRJkjZlYqIOmTgR4nE4fFAl0ydNp8OeHWjevHm1PsuWvUV5eSEV/zyeZgc0o/mBVfs/+AAmTYKbb4b09BREL0mSJEnSppKWmAghnBxCmBpCmBFC+Nlm9l8eQigKIXxW9d/VyYqtrsjLS8zAiLf8gIqFFRx5zJGb9MnPH0FGaMuaf+xbfYnQe++FDh1gyJBNjpEkSZIkKVWSUmMihJAO/BU4AVgATAohvBJF0X826vp8FEU/SkZMdVEsBvvsAy+8MxyAq869qtr+8vJlLF78Mo2/uYDKzGxyLs5J7JgyBd54A37zG2jcONlhS5IkSZK0RckaMTEQmBFF0awoitYC/wDOSNK164V4HMaPT9SX+ODdD0hvms4JR5xQrU9h4fNE0VrWPHIk7c9vT0bLqrzT/fdD06bwgx+kIHJJkiRJkrYsWYmJzsD8DV4vqGrb2DkhhCkhhFEhhK7JCa1u+OILKC6Ggw8pY9Hni+h9UG/SN6oVUVAwgqy1/aj8vDe5V1dN45g3D557DoYNgzZtUhC5JEmSJElblqzExObWpow2ev0q0COKon2Bd4ARmz1RCNeEED4JIXxSVFS0m8OsvfLyEtuC8BysglNOOqXa/tLSaaxc+THh/06myZ5NaTmoZWLHAw8kVuS46aYkRyxJkiRJ0rYlKzGxANhwBEQXYOGGHaIoWhJFUVnVy8eAgzZ3oiiKhkdRNCCKogHt27evkWBro1gMunWDseMT+Zrvn//9avvz80cCaZQ9Ppjcq3MJIcCyZTB8OFx0UeJgSZIkSZJqmWQlJiYBfUMIPUMIWcCFwCsbdgghbLCEBN8Dvk5SbLVeFCUSE0ccAZPzJtOkYxP27LPnBvsrKSh4muyCIwir2pEzpKro5cMPQ0kJ3HpriiKXJEmSJGnrkpKYiKIoDvwIGEsi4fBCFEVfhRB+HUL4XlW3G0IIX4UQPgduAC5PRmx1wezZsGgR7HVAEaumrWK/QftV2798+fuUlc2j/NljaHdmO7LaZ8Hq1fDnP8Mpp0D//imKXJIkSZKkrUvKcqEAURSNAcZs1PaLDb6+DbgtWfHUJbFYYjuneDjE4dzTzq22Pz9/JGmVzal88zByX6saeDJyJBQWOlpCkiRJklSrJS0xoZ2XlwetWsFHn/8D0uDKs65cty8eL6aoaBQZn59IWqeWtD6uNVRUJJYIPfhgOOqoFEYuSZIkSdLWmZioA2IxGDQo4q1PptK+X3tatWy1bt/ixS9SWVnC2ieOocdVHQlpAUa/BDNmwD//CWFzC6JIkiRJklQ7JKv4pXZSURF88w107vsfyheUc/jRh1fbn58/gozSbvCffeh4ecdEpcx77oHeveGss1IUtSRJkiRJ28fERC03fnxiO3fVcACuOOeKdfvWrJnH8uXvEY05gbantqNRl0bw4YcwaRLcfDOkp6ciZEmSJEmStpuJiVouLw+ys+HLaf8irUkapx192rp9BQV/ByIqRh9H7tVVRS/vvRfat4ehQ1MTsCRJkiRJO8DERC0Xi8GBB1Ww8PMF9DygJ+lVoyCiKEpM41hwEFmhO22+2wa++ALGjIEbboDGjVMcuSRJkiRJ22ZiohYrLYXJk6FN1/eIVkacdOJJ6/atXDmB1aunEX/uWDpe3pG0jDS47z5o2hSuuy6FUUuSJEmStP1MTNRiEydCPA7frnoKgGsvuHbdvoKCEYSKRvD+UeRelQvz5sFzz8GwYdCmTYoiliRJkiRpx5iYqMXy8hKrfc6a/SaNchqxb799AaisLKOw8B+EiUfS6tDONO7dGB54ILEix003pThqSZIkSZK2n4mJWiwWg37fKWHljCX0P6z/uvbFi18lHl9O5YvHkzssF5Ytg+HD4aKLoFu3FEYsSZIkSdKOMTFRS8XjiaVCm+W8BOVwzmnnrNtXUDCCtOIc0ucMpN2Z7eCRR6CkBG65JYURS5IkSZK040xM1FJffAHFxVBY8gykwbBzhgGwdm0BS5a8QeVrx5J7aWfSKYcHH4STT4Z9901x1JIkSZIk7ZiMVAegzYvFEttFCz6kTd82tGmVKGhZUPAsUAFvnkju67kwciQUFsKtt6YuWEmSJEmSdpIjJmqpvDzIyV1E+cISDjvysHXtBQUjSZv7HVp02pemezaC+++HAQPg6KNTF6wkSZIkSTvJxEQtFEWJERNN2z8PwJBzhgBQXDyF4uLPqHzpBHKvzoWXXoLp0xOjJUJIZciSJEmSJO0Up3LUQrNnw6JF0Kb5KNIap3HWsWcBkJ8/AioySJt4Ah2ebg/H3gO9e8PZZ6c4YkmSJEmSdo6JiVooUV8iYtnCSXTfvxuZmZlUVsYpyH8GPj6MnNP7kj55HEyalFiRIz091SFLkiRJkrRTnMpRC+XlQZOmXxEVr+X4E44HYNmytyiPF8AbJyamcdx7L7RvD0OHpjhaSZIkSZJ2nomJWmjD+hLfP//7QNU0jpKWNF1zHM2z5sCYMXDDDdC4cQojlSRJkiRp15iYqGWKiuCbb6B4zctkt8/moL0Porx8GYuLXoaxx9Lpim6EP/wBmjSB665LdbiSJEmSJO0SExO1zPjxAGtZvfgr9jp0LwCKil4goozw3il0OKocnn0Whg2DNm1SGqskSZIkSbvKxEQtE4tBesY4iFdy5qlnArDo26dgXg/aHzCIzCf/klhP9KabUhmmJEmSJEm7hYmJWiYvDxq3GgVpcO2511JaOp1VJR/DGyfS6cLmMHw4XHghdO+e6lAlSZIkSdplJiZqkdJSmDwZVq8dQ6verchpl0NBwUioTKPRrNNp+e+nobgYbrkl1aFKkiRJkrRbmJioRSZOhHh8KRUr5zBw8ECiqJJF80fAJwfR6cy9CH9+EE4+GfbbL9WhSpIkSZK0W5iYqEViMYB3ALjs7MtYvvwD1lbOh3dOpmPme1BYCLfemtIYJUmSJEnanUxM1CJ5eZDZ9CVCo8AFJ15A/sIRUNqEdm1OJ2v4PTBgABx9dKrDlCRJkiRpt8lIdQBKiMdh3LhKyuNv0XW/LqSlraWoYBS8dzSd+ubD89PhhRcghFSHKkmSJEnSbmNiopb44gsoKZkBLOHY40+jqOhFKtNKyPz8NFov/y306gVnn53qMCVJkiRJ2q2cylFLJOpLvA3Atedfy8I5T8LCXDp1+Q5h0gS4+WZIT09pjJIkSZIk7W4mJmqJvDxIy3yVzLaZHNCvCytXvw9vn0ju3L9B+/Zw+eWpDlGSJEmSpN3OxEQtEEXwYV4ZlRUf8p1DvkP+oqchRLRceiqN3v0HXH89NG6c6jAlSZIkSdrtrDFRC8yeDQX5k4DVfO/U01k4+0n4Yl+6rPwCmjSB665LdYiSJEmSJNUIR0zUAon6Em9BgMtPO5S1aTNIH38ybfPug2HDoG3bVIcoSZIkSVKNMDFRC8RiQHiDFr1asHbpq1CWRe7CzqQRh5tuSnV4kiRJkiTVGBMTtcA77xZB9CmHHHkgRYufh9gRdPr0IbjwQujePdXhSZIkSZJUY0xMpFhREcye+SFQyZVnfYfKzBU0/XwwTUqnwy23pDo8SZIkSZJqlImJFBs/HuAtyMygT5OZUNSOrnlT4KSTYL/9Uh2eJEmSJEk1ylU5UuzDDyuBsfQ7rD3FvEv44BzaL38Rbn0z1aFJkiRJklTjHDGRYq+/+RUwl6vO7grpcdp/2Ir0g/aFY45JdWiSJEmSJNU4R0ykUGkpTPv6AwAO7rEMpu5Bty/egud/DyGkODpJkiRJkmqeIyZSaOJEiKL/o89ejaHldLLfG0izXgHOPjvVoUmSJEmSlBQmJlLo3ffWAO8y7LxOUJ5Blzfy4eabIcOBLJIkSZKkhsFPwCn0z5ffJy1tJQcdFGDCQHKzvoHLL091WJIkSZIkJY2JiRSpqIBpX8UYNCCb9OYraD22HRk3nAyNG6c6NEmSJEmSksbERIpMmQKV8Xe59LsdYcUyuv97Nrz0RKrDkiRJkiQpqUxMpMhLr39L06YT6HtoOhmvDabllftA27apDkuSJEmSpKQyMZEi/xg9hvOPaUvIKqLjWxHhzZtSHZIkSZIkSUnnqhwpEEUw6z8f8d2TMmFON7r17wY9eqQ6LEmSJEmSks7ERArMmhXRpd2HtN1nIc3G9iLr5z9OdUiSJEmSJKWEiYkUGP73CVx1UgQVaXQr7Aj775/qkCRJkiRJSgkTEykw+qXXGXjiMqJP96L9/wxLdTiSJEmSJKWMiYkU6JPxMVkdl9FhYlfCscekOhxJkiRJklImaYmJEMLJIYSpIYQZIYSfbWZ/dgjh+ar9E0IIPZIVWzLN/3YN5x+7kKikCb1OvBhCSHVIkiRJkiSlTFISEyGEdOCvwCnAXsBFIYS9Nup2FbAsiqI+wJ+Ae5IRW7Ld/9Bz9DxqFqvG9afxFRemOhxJkiRJklIqWSMmBgIzoiiaFUXRWuAfwBkb9TkDGFH19SjguBDq33CCpjNeJjRZQ8f4IZCRkepwJEmSJElKqWQlJjoD8zd4vaCqbbN9oiiKAyuAtkmJLokOPWQq8YUdGHD7b1IdiiRJkiRJKZesxMTmRj5EO9GHEMI1IYRPQgifFBUV7ZbgkqW4aDFpGZVM/6A/aS2apzocSZIkSZJSLllzCRYAXTd43QVYuIU+C0IIGUBLYOnGJ4qiaDgwHGDAgAGbJC5qs2bt23Haj6cSX7Mm1aFIkiRJklQrJGvExCSgbwihZwghC7gQeGWjPq8AQ6u+Phd4N4qiOpV42F4ZjRqlOgRJkiRJkmqFpIyYiKIoHkL4ETAWSAeeiKLoqxDCr4FPoih6Bfhf4OkQwgwSIyVcskKSJEmSpHouactCRFE0BhizUdsvNvh6DXBesuKRJEmSJEmpl6ypHJIkSZIkSZswMSFJkiRJklLGxIQkSZIkSUoZExOSJEmSJCllTExIkiRJkqSUMTEhSZIkSZJSxsSEJEmSJElKGRMTkiRJkiQpZUxMSJIkSZKklDExIUmSJEmSUsbEhCRJkiRJShkTE5IkSZIkKWVMTEiSJEmSpJQxMSFJkiRJklLGxIQkSZIkSUoZExOSJEmSJCllTExIkiRJkqSUMTEhSZIkSZJSxsSEJEmSJElKGRMTkiRJkiQpZUIURamOYaeFEIqAuamOYye0AxanOgjtMu9j/eB9rB+8j/WD97H+8F7WD97H+sH7WD/U1fvYPYqi9tvqVKcTE3VVCOGTKIoGpDoO7RrvY/3gfawfvI/1g/ex/vBe1g/ex/rB+1g/1Pf76FQOSZIkSZKUMiYmJEmSJElSypiYSI3hqQ5Au4X3sX7wPtYP3sf6wftYf3gv6wfvY/3gfawf6vV9tMaEJEmSJElKGUdMSJIkSZKklDExkUQhhJNDCFNDCDNCCD9LdTzaPiGEriGE90IIX4cQvgoh3FjVfmcI4dsQwmdV/52a6li1bSGEOSGEL6ru2SdVbW1CCG+HEKZXbVunOk5tWQih3wbP3WchhJUhhB/7TNZ+IYQnQgiFIYQvN2jb7PMXEv5c9TtzSgjhwNRFrg1t4T7eF0L4pupe/SuE0KqqvUcIYfUGz+WjqYtcG9rCfdziz9EQwm1Vz+PUEMJJqYlaG9vCfXx+g3s4J4TwWVW7z2MttZXPGw3md6RTOZIkhJAOTANOABYAk4CLoij6T0oD0zaFEHKB3CiKPg0hNAcmA2cC5wPFURTdn9IAtUNCCHOAAVEULd6g7V5gaRRFv69KGraOouinqYpR26/qZ+u3wCHAFfhM1mohhCOBYmBkFEX7VLVt9vmr+kB0PXAqifv7YBRFh6Qqdq23hft4IvBuFEXxEMI9AFX3sQfw2n/7qfbYwn28k838HA0h7AU8BwwEOgHvAHtEUVSR1KC1ic3dx432/wFYEUXRr30ea6+tfN64nAbyO9IRE8kzEJgRRdGsKIrWAv8AzkhxTNoOURQtiqLo06qvVwFfA51TG5V2szOAEVVfjyDxi0B1w3HAzCiK5qY6EG1bFEUfAks3at7S83cGiX9oR1EUfQy0qvqHm1Jsc/cxiqK3oiiKV738GOiS9MC0Q7bwPG7JGcA/oigqi6JoNjCDxL9tlWJbu48hhEDiD2nPJTUo7bCtfN5oML8jTUwkT2dg/gavF+CH2zqnKtN8ADChqulHVcOnnnD4f50RAW+FECaHEK6pasuJomgRJH4xAB1SFp121IVU/weXz2Tds6Xnz9+bddeVwBsbvO4ZQvh3COGDEMLgVAWl7ba5n6M+j3XTYKAgiqLpG7T5PNZyG33eaDC/I01MJE/YTJvzaOqQEEIzYDTw4yiKVgKPAL2B/YFFwB9SGJ6236Aoig4ETgF+WDUEUnVQCCEL+B7wz6omn8n6xd+bdVAI4edAHHimqmkR0C2KogOA/wc8G0Jokar4tE1b+jnq81g3XUT15L3PYy23mc8bW+y6mbY6/UyamEieBUDXDV53ARamKBbtoBBCJokfEs9EUfQiQBRFBVEUVURRVAk8hkMa64QoihZWbQuBf5G4bwX/Hf5WtS1MXYTaAacAn0ZRVAA+k3XYlp4/f2/WMSGEocBpwCVRVRGzqqH/S6q+ngzMBPZIXZTamq38HPV5rGNCCBnA2cDz/23zeazdNvd5gwb0O9LERPJMAvqGEHpW/ZXvQuCVFMek7VA1P+9/ga+jKPrjBu0bzuM6C/hy42NVu4QQmlYVFCKE0BQ4kcR9ewUYWtVtKPByaiLUDqr2lyCfyTprS8/fK8CQqsrjh5Io3rYoFQFq20IIJwM/Bb4XRVHpBu3tq4rUEkLoBfQFZqUmSm3LVn6OvgJcGELIDiH0JHEfJyY7Pu2Q44Fvoiha8N8Gn8faa0ufN2hAvyMzUh1AQ1FVpfpHwFggHXgiiqL/397dhFhVxnEc//5QEiyoyN5MUqhWbmwhEklJtGkXgfYOaYpCizYVaESSmNWmwhYtetmYmhCCiygzsFeyoEVlQkhZptmblk2apPxbnDtxszs6o45nar4fuHDOnXOe53/ncs4wP57nPFtbLkuDczVwJ/Bp/3JLwBLg1iTTaIZN7QAWtlOehuBCYH1z72cssLqqXkvyEbAuyd3AN8DsFmvUICQZT7PKUfd194TX5MiWZA0wC5iQ5FvgYeAxel9/r9I8bXw7cIBm1RWNAAN8j4uBccAbnXvsB1W1CLgGeCTJYeAIsKiqBvvARQ2jAb7HWb3uo1W1Nck64HOaqTr3uCLHyNDre6yq5/n3M5jA63EkG+j/jVHzN9LlQiVJkiRJUmucyiFJkiRJklpjMCFJkiRJklpjMCFJkiRJklpjMCFJkiRJklpjMCFJkiRJklpjMCFJ0iiXZEmS505DP5cm6UsyZrj7kiRJ/x0uFypJ0v9ckr6u3fHAIZo17AEWVtVLp7+qoUkyC1hVVZOOen9z5/1hD1YkSdLwGNt2AZIkaXhV1Vn920l2APOralN7FY18ScZW1eG265AkaTRwKockSaNckqVJVnW2pySpJHOT7EyyL8miJNOTfJLklyTPHHX+vCTbOse+nmTyAP30tz22s785ybIk7yX5LcnGJBNO8rMsSLI9yd4kG5JM7NV3V//zO9t3dep4MsleYGmSy5O8leTXJD8leflkapMkSb0ZTEiSpF5mAFcANwNPAQ8C1wNTgTlJrgVIciOwBLgJOB94B1gzhH5uA+YCFwBnAPedaMFJrgNWAHOAi4GvgbVDaGIG8GWnluXAMmAjcC4wCVh5orVJkqSBGUxIkqRellXVH1W1EfgdWFNVP1TVLprw4crOcQuBFVW1rTP14VFg2kCjJnp4saq+qKqDwDpg2jGOndgZsfH3C5jZ9fPbgReq6uOqOgQsBq5KMmWQteyuqpVVdbhTz5/AZGBi53fx7iDbkSRJQ2AwIUmSevm+a/tgj/3+51ZMBp7uCgr2AgEuGWQ/e7q2D3S128vuqjqn+wV0hwUTaUZJAFBVfcDPQ6hl51H7D9B8lg+TbE0yb5DtSJKkIfDhl5Ik6WTsBJaPkJU9dtMEJQAkORM4D9hFM+oDmlVJ9ne2Lzrq/H8sVVZVe4AFnbZmApuSvF1V20996ZIkjV6OmJAkSSfjWWBxkqkASc5OMrulWlYDc5NMSzKOZlrJlqraUVU/0gQUdyQZ0xn9cNmxGksyO0n/8qT7aIKLI8c4RZIknQCDCUmSdMKqaj3wOLA2yX7gM+CGlmp5E3gIeAX4jiZ4uKXrkAXA/TTTO6YC7x+nyenAliR9wAbg3qr66lTXLUnSaJeqOv5RkiRJkiRJw8ARE5IkSZIkqTUGE5IkSZIkqTUGE5IkSZIkqTUGE5IkSZIkqTUGE5IkSZIkqTUGE5IkSZIkqTUGE5IkSZIkqTUGE5IkSZIkqTUGE5IkSZIkqTV/AV8AocHOKZ49AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 1296x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# ANOMALOUS block at 10, 12\n",
    "model_anom = DayModel(macrophage=1.83E+11, spore=6.16E+11)\n",
    "%time results_anom = model_anom.run(solver=BasicODESolver)\n",
    "%time mean_of_model_anom = get_mean(results_anom[0])\n",
    "print(mean_of_model_anom)\n",
    "res = results_anom[0]\n",
    "\n",
    "data = [\n",
    "    res['HLN1'][-1],\n",
    "    res['HLN2'][-1],\n",
    "    res['HLN3'][-1],\n",
    "    res['HLN4'][-1],\n",
    "    res['HLN5'][-1],\n",
    "    res['HLN6'][-1]\n",
    "]\n",
    "x = [1,2,3,4,5,6]\n",
    "\n",
    "mean = get_mean(res)\n",
    "sd = get_std(res)\n",
    "sem = get_sem(res)\n",
    "\n",
    "plt.bar(x,data)\n",
    "plt.xlabel('HLN')\n",
    "plt.ylabel('Count')\n",
    "plt.show()\n",
    "\n",
    "### SPORES AVAILABLE ###\n",
    "\n",
    "fig = plt.figure(figsize=(18,10))\n",
    "fig.suptitle(\"Spores available\", fontsize=20)\n",
    "\n",
    "plt.plot(res['time'], res['S_'], 'g-', label='Spore')\n",
    "\n",
    "plt.xlabel(\"Time in Hours\", fontsize=12)\n",
    "plt.ylabel(\"Number of Cells\", fontsize=12)\n",
    "plt.legend(loc='best', fontsize=12)\n",
    "\n",
    "### HOSTS IN LUNG ###\n",
    "fig = plt.figure(figsize=(18,10))\n",
    "fig.suptitle(\"Anthrax-infected Cells in Lung\", fontsize=20)\n",
    "\n",
    "#plt.plot(results[0]['time'], results[0]['S_'], 'g-', label='Spore')\n",
    "plt.plot(res['time'], res['H1'], 'r-', label='H1')\n",
    "plt.plot(res['time'], res['H2'], 'g-', label='H2')\n",
    "plt.plot(res['time'], res['H3'], 'b-', label='H3')\n",
    "plt.plot(res['time'], res['H4'], 'k-', label='H4')\n",
    "plt.plot(res['time'], res['H5'], 'm-', label='H5')\n",
    "plt.plot(res['time'], res['H6'], 'y-', label='H6')\n",
    "\n",
    "plt.xlabel(\"Time in Hours\", fontsize=12)\n",
    "plt.ylabel(\"Number of Cells\", fontsize=12)\n",
    "plt.legend(loc='best', fontsize=12)\n",
    "\n",
    "### TMLN MIGRATION ###\n",
    "fig = plt.figure(figsize=(18,10))\n",
    "fig.suptitle(\"Migration to TMLN\", fontsize=20)\n",
    "\n",
    "#plt.plot(results[0]['time'], results[0]['S_'], 'b', label='Spores')\n",
    "plt.plot(res['time'], res['HLN1'], 'r-', label='HLN1')\n",
    "plt.plot(res['time'], res['HLN2'], 'g-', label='HLN2')\n",
    "plt.plot(res['time'], res['HLN3'], 'b-', label='HLN3')\n",
    "plt.plot(res['time'], res['HLN4'], 'k-', label='HLN4')\n",
    "plt.plot(res['time'], res['HLN5'], 'm-', label='HLN5')\n",
    "plt.plot(res['time'], res['HLN6'], 'y-', label='HLN6')\n",
    "\n",
    "plt.xlabel(\"Time in Hours\", fontsize=12)\n",
    "plt.ylabel(\"Number of Cells\", fontsize=12)\n",
    "plt.legend(loc='best', fontsize=12)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Wall time: 183 ms\n",
      "Wall time: 0 ns\n",
      "5.998584536052348\n"
     ]
    },
    {
     "data": {
      "image/png": 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Yi760qhl8aXF/kmRm72OB338O8GodrXreLVOSGuERviQ1wuBLUiMMviQ1wuBLUiMMviQ1wuBLUiMMviQ14n8Buc4wVDpy1ZgAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1296x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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6sacsv5T0YUnfl9SpfPFwxaBN3irpfcpP7zhX0n2j7PJiSfeb2UFJd0n6a+fc1vHODQDAZGfOudG3AgAAAAAAmACMmAAAAAAAAN5QTAAAAAAAAG8oJgAAAAAAgDcUEwAAAAAAwBuKCQAAAAAA4A3FBAAAAAAA8IZiAgAAAPj/7dixAAAAAMAgf+th7CmMANiICQAAAGAjJgAAAIBNXfIu50/QqCMAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 1296x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1296x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# ANOMALOUS in UPPER LEFT\n",
    "# block at 9, 15\n",
    "model_anom2 = DayModel(macrophage=5.46e10, spore=5.46e12)\n",
    "%time results_anom2 = model_anom2.run(solver=BasicODESolver)\n",
    "%time mean_of_model_anom2 = get_mean(results_anom2[0])\n",
    "print(mean_of_model_anom2)\n",
    "res = results_anom2[0]\n",
    "\n",
    "data = [\n",
    "    res['HLN1'][-1],\n",
    "    res['HLN2'][-1],\n",
    "    res['HLN3'][-1],\n",
    "    res['HLN4'][-1],\n",
    "    res['HLN5'][-1],\n",
    "    res['HLN6'][-1]\n",
    "]\n",
    "x = [1,2,3,4,5,6]\n",
    "\n",
    "mean = get_mean(res)\n",
    "sd = get_std(res)\n",
    "sem = get_sem(res)\n",
    "\n",
    "plt.bar(x,data)\n",
    "plt.xlabel('HLN')\n",
    "plt.ylabel('Count')\n",
    "plt.show()\n",
    "\n",
    "### SPORES AVAILABLE ###\n",
    "\n",
    "fig = plt.figure(figsize=(18,10))\n",
    "fig.suptitle(\"Spores available\", fontsize=20)\n",
    "\n",
    "plt.plot(res['time'], res['S_'], 'g-', label='Spore')\n",
    "\n",
    "plt.xlabel(\"Time in Hours\", fontsize=12)\n",
    "plt.ylabel(\"Number of Cells\", fontsize=12)\n",
    "plt.legend(loc='best', fontsize=12)\n",
    "\n",
    "### HOSTS IN LUNG ###\n",
    "fig = plt.figure(figsize=(18,10))\n",
    "fig.suptitle(\"Anthrax-infected Cells in Lung\", fontsize=20)\n",
    "\n",
    "#plt.plot(results[0]['time'], results[0]['S_'], 'g-', label='Spore')\n",
    "plt.plot(res['time'], res['H1'], 'r-', label='H1')\n",
    "plt.plot(res['time'], res['H2'], 'g-', label='H2')\n",
    "plt.plot(res['time'], res['H3'], 'b-', label='H3')\n",
    "plt.plot(res['time'], res['H4'], 'k-', label='H4')\n",
    "plt.plot(res['time'], res['H5'], 'm-', label='H5')\n",
    "plt.plot(res['time'], res['H6'], 'y-', label='H6')\n",
    "\n",
    "plt.xlabel(\"Time in Hours\", fontsize=12)\n",
    "plt.ylabel(\"Number of Cells\", fontsize=12)\n",
    "plt.legend(loc='best', fontsize=12)\n",
    "\n",
    "### TMLN MIGRATION ###\n",
    "fig = plt.figure(figsize=(18,10))\n",
    "fig.suptitle(\"Migration to TMLN\", fontsize=20)\n",
    "\n",
    "#plt.plot(results[0]['time'], results[0]['S_'], 'b', label='Spores')\n",
    "plt.plot(res['time'], res['HLN1'], 'r-', label='HLN1')\n",
    "plt.plot(res['time'], res['HLN2'], 'g-', label='HLN2')\n",
    "plt.plot(res['time'], res['HLN3'], 'b-', label='HLN3')\n",
    "plt.plot(res['time'], res['HLN4'], 'k-', label='HLN4')\n",
    "plt.plot(res['time'], res['HLN5'], 'm-', label='HLN5')\n",
    "plt.plot(res['time'], res['HLN6'], 'y-', label='HLN6')\n",
    "\n",
    "plt.xlabel(\"Time in Hours\", fontsize=12)\n",
    "plt.ylabel(\"Number of Cells\", fontsize=12)\n",
    "plt.legend(loc='best', fontsize=12)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "ename": "NameError",
     "evalue": "name 'results_9_15' is not defined",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mNameError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-10-7d2931b19243>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[1;32m----> 1\u001b[1;33m \u001b[0mresults_9_15\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[1;31mNameError\u001b[0m: name 'results_9_15' is not defined"
     ]
    }
   ],
   "source": [
    "results_9_15"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "model_10_13 = DayModel(macrophage=1.83E+11, spore=1.27E+12)\n",
    "%time results_10_13 = model_10_13.run(solver=BasicODESolver)\n",
    "%time mean_of_model_10_13 = get_mean(results_10_13[0])\n",
    "mean_of_model_10_13"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "model_11_14 = DayModel(macrophage=6.16E+11, spore=2.64E+12)\n",
    "%time results_11_14 = model_11_14.run(solver=BasicODESolver)\n",
    "%time mean_of_model_11_14 = get_mean(results_11_14[0])\n",
    "mean_of_model_11_14"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "model_11_15 = DayModel(macrophage=6.16E+11, spore=5.46E+12)\n",
    "%time results_11_15 = model_11_15.run(solver=BasicODESolver)\n",
    "%time mean_of_model_11_15 = get_mean(results_11_15[0])\n",
    "mean_of_model_11_15"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "model_12_16 = DayModel(macrophage=2.07E+12, spore=1.13E+13)\n",
    "%time results_12_16 = model_12_16.run(solver=BasicODESolver)\n",
    "%time mean_of_model_12_16 = get_mean(results_12_16[0])\n",
    "mean_of_model_12_16"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "model_13_17 = DayModel(macrophage=6.95E+12, spore=2.34E+13)\n",
    "%time results_13_17 = model_13_17.run(solver=BasicODESolver)\n",
    "%time mean_of_model_13_17 = get_mean(results_13_17[0])\n",
    "mean_of_model_13_17"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "model_13_18 = DayModel(macrophage=6.95E+12, spore=4.83E+13)\n",
    "%time results_13_18 = model_13_18.run(solver=BasicODESolver)\n",
    "%time mean_of_model_13_18 = get_mean(results_13_18[0])\n",
    "mean_of_model_13_18"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "model_14_19 = DayModel(macrophage=2.34E+13, spore=1.00E+14)\n",
    "%time results_14_19 = model_14_19.run(solver=BasicODESolver)\n",
    "%time mean_of_model_14_19 = get_mean(results_14_19[0])\n",
    "mean_of_model_14_19"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# THIS IS ONE OF THE OUTLIERS\n",
    "model_15_15 = DayModel(macrophage=7.85E+13, spore=5.46E+12)\n",
    "%time results_15_15 = model_15_15.run(solver=BasicODESolver)\n",
    "%time mean_of_model_15_15 = get_mean(results_15_15[0])\n",
    "mean_of_model_15_15"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# THIS IS ONE OF THE OUTLIERS\n",
    "model_18_18 = DayModel(macrophage=2.48E+15, spore=4.83e13)\n",
    "%time results_18_18 = model_18_18.run(solver=BasicODESolver)\n",
    "%time mean_of_model_18_18 = get_mean(results_18_18[0])\n",
    "mean_of_model_18_18"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "res = results_10_12[0]\n",
    "data = [\n",
    "    res['HLN1'][-1],\n",
    "    res['HLN2'][-1],\n",
    "    res['HLN3'][-1],\n",
    "    res['HLN4'][-1],\n",
    "    res['HLN5'][-1],\n",
    "    res['HLN6'][-1]\n",
    "]\n",
    "x = [1,2,3,4,5,6]\n",
    "\n",
    "\n",
    "mean = get_mean(res)\n",
    "sd = get_std(res)\n",
    "sem = get_sem(res)\n",
    "\n",
    "plt.bar(x,data)\n",
    "plt.xlabel('HLN')\n",
    "plt.ylabel('Count')\n",
    "plt.show()\n",
    "\n",
    "# plt.hist(data3, bins=x,edgecolor=\"black\")\n",
    "# plt.xlabel('HLN')\n",
    "# plt.ylabel('Count')\n",
    "# plt.show()\n",
    "\n",
    "print(\"Mean: \\t{}\".format(mean))\n",
    "print(\"STD:  \\t{}\".format(sd))\n",
    "print(\"SEM:  \\t{}\".format(sem))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "ename": "NameError",
     "evalue": "name 'results_10_12' is not defined",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mNameError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-11-921033b5e6fa>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[0;32m      2\u001b[0m \u001b[0mfig\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0msuptitle\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m\"Spores available\"\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mfontsize\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m20\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      3\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 4\u001b[1;33m \u001b[0mplt\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mplot\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mresults_10_12\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;36m0\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;34m'time'\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mresults_10_12\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;36m0\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;34m'S_'\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;34m'g-'\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mlabel\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;34m'Spore'\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m      5\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      6\u001b[0m \u001b[0mplt\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mxlabel\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m\"Time in Hours\"\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mfontsize\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m12\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;31mNameError\u001b[0m: name 'results_10_12' is not defined"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 1296x720 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=(18,10))\n",
    "fig.suptitle(\"Spores available\", fontsize=20)\n",
    "\n",
    "plt.plot(results_10_12[0]['time'], results_10_12[0]['S_'], 'g-', label='Spore')\n",
    "\n",
    "plt.xlabel(\"Time in Hours\", fontsize=12)\n",
    "plt.ylabel(\"Number of Cells\", fontsize=12)\n",
    "plt.legend(loc='best', fontsize=12)\n",
    "# print(\"Initial spores: {}\".format(results['S_'][0]))\n",
    "# print(\"Spores remaining: {}\".format(results['S_'][-1]))\n",
    "# print(\"Spores at 5 hours: {}\".format(results['S_'][100]))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "ename": "NameError",
     "evalue": "name 'results_10_12' is not defined",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mNameError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-12-94879fcec0bc>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[1;32m----> 1\u001b[1;33m \u001b[0mres\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mresults_10_12\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;36m0\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m      2\u001b[0m \u001b[0mfig\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mplt\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mfigure\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mfigsize\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;36m18\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;36m10\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      3\u001b[0m \u001b[0mfig\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0msuptitle\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m\"Anthrax-infected Cells in Lung\"\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mfontsize\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m20\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      4\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      5\u001b[0m \u001b[1;31m#plt.plot(results[0]['time'], results[0]['S_'], 'g-', label='Spore')\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;31mNameError\u001b[0m: name 'results_10_12' is not defined"
     ]
    }
   ],
   "source": [
    "res = results_10_12[0]\n",
    "fig = plt.figure(figsize=(18,10))\n",
    "fig.suptitle(\"Anthrax-infected Cells in Lung\", fontsize=20)\n",
    "\n",
    "#plt.plot(results[0]['time'], results[0]['S_'], 'g-', label='Spore')\n",
    "plt.plot(res['time'], res['H1'], 'r-', label='H1')\n",
    "plt.plot(res['time'], res['H2'], 'g-', label='H2')\n",
    "plt.plot(res['time'], res['H3'], 'b-', label='H3')\n",
    "plt.plot(res['time'], res['H4'], 'k-', label='H4')\n",
    "plt.plot(res['time'], res['H5'], 'm-', label='H5')\n",
    "plt.plot(res['time'], res['H6'], 'y-', label='H6')\n",
    "\n",
    "plt.xlabel(\"Time in Hours\", fontsize=12)\n",
    "plt.ylabel(\"Number of Cells\", fontsize=12)\n",
    "plt.legend(loc='best', fontsize=12)\n",
    "\n",
    "print(\"Lung Hosts at end:\")\n",
    "print(\"H1: {}\".format(res['H1'][-1]))\n",
    "print(\"H2: {}\".format(res['H2'][-1]))\n",
    "print(\"H3: {}\".format(res['H3'][-1]))\n",
    "print(\"H4: {}\".format(res['H4'][-1]))\n",
    "print(\"H5: {}\".format(res['H5'][-1]))\n",
    "print(\"H6: {}\".format(res['H6'][-1]))\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "ename": "NameError",
     "evalue": "name 'results_10_12' is not defined",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mNameError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-13-c70dedea478c>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[0;32m      1\u001b[0m \u001b[0mfig\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mplt\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mfigure\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mfigsize\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;36m18\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;36m10\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      2\u001b[0m \u001b[0mfig\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0msuptitle\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m\"Migration to TMLN\"\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mfontsize\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m20\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 3\u001b[1;33m \u001b[0mres\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mresults_10_12\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;36m0\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m      4\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      5\u001b[0m \u001b[1;31m#plt.plot(results[0]['time'], results[0]['S_'], 'b', label='Spores')\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;31mNameError\u001b[0m: name 'results_10_12' is not defined"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 1296x720 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=(18,10))\n",
    "fig.suptitle(\"Migration to TMLN\", fontsize=20)\n",
    "res = results_10_12[0]\n",
    "\n",
    "#plt.plot(results[0]['time'], results[0]['S_'], 'b', label='Spores')\n",
    "plt.plot(res['time'], res['HLN1'], 'r-', label='HLN1')\n",
    "plt.plot(res['time'], res['HLN2'], 'g-', label='HLN2')\n",
    "plt.plot(res['time'], res['HLN3'], 'b-', label='HLN3')\n",
    "plt.plot(res['time'], res['HLN4'], 'k-', label='HLN4')\n",
    "plt.plot(res['time'], res['HLN5'], 'm-', label='HLN5')\n",
    "plt.plot(res['time'], res['HLN6'], 'y-', label='HLN6')\n",
    "\n",
    "plt.xlabel(\"Time in Hours\", fontsize=12)\n",
    "plt.ylabel(\"Number of Cells\", fontsize=12)\n",
    "plt.legend(loc='best', fontsize=12)\n",
    "\n",
    "print(\"k2 = {:.2e}, k3 = {:.2e}\".format(float(model_10_12.listOfParameters['k2'].expression), float(model_10_12.listOfParameters['k3'].expression)))\n",
    "\n",
    "print(\"Lung Hosts at end:\")\n",
    "print(\"H1: {}\".format(res['H1'][-1]))\n",
    "print(\"H2: {}\".format(res['H2'][-1]))\n",
    "print(\"H3: {}\".format(res['H3'][-1]))\n",
    "print(\"H4: {}\".format(res['H4'][-1]))\n",
    "print(\"H5: {}\".format(res['H5'][-1]))\n",
    "print(\"H6: {}\".format(res['H6'][-1]))\n",
    "\n",
    "print(\"Lymph Node Hosts at end:\")\n",
    "print(\"HLN1: {}\".format(res['HLN1'][-1]))\n",
    "print(\"HLN2: {}\".format(res['HLN2'][-1]))\n",
    "print(\"HLN3: {}\".format(res['HLN3'][-1]))\n",
    "print(\"HLN4: {}\".format(res['HLN4'][-1]))\n",
    "print(\"HLN5: {}\".format(res['HLN5'][-1]))\n",
    "print(\"HLN6: {}\".format(res['HLN6'][-1]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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